diff --git a/.claude/settings.json b/.claude/settings.json index f93f3494f..93f84719f 100644 --- a/.claude/settings.json +++ b/.claude/settings.json @@ -6,11 +6,6 @@ "Bash(make)", "Bash(mise:*)", "Bash(mise)", - "Bash(nox:*)", - "Bash(nox)", - "Bash(pytest:*)", - "Bash(python:*)", - "Bash(python3:*)", "Bash(pnpm:*)", "Bash(pip:*)", "Bash(git status:*)", @@ -45,13 +40,7 @@ "Bash(source:*)", "Bash(cd:*)", "Bash(set:*)", - "Bash(sort:*)", - "Bash(.nox/*/bin/pytest:*)", - "Bash(.nox/*/bin/python:*)", - "Bash(.nox/*/bin/pip:*)", - "Bash(py/.nox/*/bin/pytest:*)", - "Bash(py/.nox/*/bin/python:*)", - "Bash(py/.nox/*/bin/pip:*)" + "Bash(sort:*)" ], "deny": [] } diff --git a/.flake8 b/.flake8 deleted file mode 100644 index 71ccaac78..000000000 --- a/.flake8 +++ /dev/null @@ -1,3 +0,0 @@ -[flake8] -max-line-length = 119 -ignore = E402, E203, E501, W503 diff --git a/.github/workflows/adk-py-test.yaml b/.github/workflows/adk-py-test.yaml deleted file mode 100644 index 1f9e27fc5..000000000 --- a/.github/workflows/adk-py-test.yaml +++ /dev/null @@ -1,53 +0,0 @@ -name: adk-py - -on: - workflow_call: - inputs: - python-version: - required: true - type: string - os: - required: true - type: string - -jobs: - test: - runs-on: ${{ inputs.os }} - timeout-minutes: 15 - - env: - GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }} - - defaults: - run: - working-directory: integrations/adk-py - - steps: - - uses: actions/checkout@v4 - - - name: Set up uv - uses: astral-sh/setup-uv@v3 - with: - enable-cache: true - cache-dependency-glob: | - integrations/adk-py/pyproject.toml - integrations/adk-py/uv.lock - - - name: Install dependencies - run: | - uv python install ${{ inputs.python-version }} - uv sync - - - name: Lint with ruff - if: ${{ inputs.os == 'ubuntu-latest' }} - run: | - uv run ruff check $(git ls-files '*.py' | grep -v 'examples/') - - - name: Run tests - run: | - uv run pytest - - - name: Test import - run: | - uv run python -c "import braintrust_adk; print('braintrust_adk imported successfully')" - uv run python -c "from braintrust_adk import setup_braintrust; print('setup_braintrust imported successfully')" diff --git a/.github/workflows/langchain-py-test.yaml b/.github/workflows/langchain-py-test.yaml deleted file mode 100644 index 2d472031e..000000000 --- a/.github/workflows/langchain-py-test.yaml +++ /dev/null @@ -1,54 +0,0 @@ -name: langchain-py - -on: - workflow_call: - inputs: - python-version: - required: true - type: string - os: - required: true - type: string - -jobs: - test: - runs-on: ${{ inputs.os }} - timeout-minutes: 15 - - defaults: - run: - working-directory: integrations/langchain-py - - env: - ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }} - OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} - - steps: - - uses: actions/checkout@v4 - - - name: Set up uv - uses: astral-sh/setup-uv@v3 - with: - enable-cache: true - cache-dependency-glob: | - integrations/langchain-py/pyproject.toml - integrations/langchain-py/uv.lock - - - name: Install dependencies - run: | - uv python install ${{ inputs.python-version }} - uv sync - - - name: Lint with ruff - if: ${{ inputs.os == 'ubuntu-latest' }} - run: | - uv run ruff check $(git ls-files '*.py' | grep -v 'examples/') - - - name: Run tests - run: | - uv run pytest src - - - name: Test import - run: | - uv run python -c "import braintrust_langchain; print('braintrust_langchain imported successfully')" - uv run python -c "from braintrust_langchain import BraintrustCallbackHandler; print('BraintrustCallbackHandler imported successfully')" diff --git a/.github/workflows/lint.yaml b/.github/workflows/lint.yaml index 27cd1e2c5..3b9798e9b 100644 --- a/.github/workflows/lint.yaml +++ b/.github/workflows/lint.yaml @@ -1,4 +1,3 @@ -# Source: https://github.com/marketplace/actions/pre-commit name: lint on: @@ -11,10 +10,12 @@ jobs: runs-on: ubuntu-latest timeout-minutes: 10 steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 + - uses: actions/setup-node@v4 with: - fetch-depth: 0 # Fetch full history for proper diff - - uses: actions/setup-python@v3 - - uses: pre-commit/action@v3.0.0 - with: - extra_args: --from-ref origin/${{ github.base_ref || 'main' }} --to-ref HEAD + node-version: 22 + - uses: pnpm/action-setup@v4 + - name: Install dependencies + run: pnpm install --frozen-lockfile + - name: Lint + run: pnpm run lint diff --git a/.github/workflows/publish-py-sdk.yaml b/.github/workflows/publish-py-sdk.yaml deleted file mode 100644 index 5c76e46f5..000000000 --- a/.github/workflows/publish-py-sdk.yaml +++ /dev/null @@ -1,149 +0,0 @@ -# -# This workflow is used to publish the Python SDK to PyPI. -# It is triggered by a tag push, and will only publish if the tag is valid. -# The tag must match the format py-sdk-v*.*.* -# - -name: Publish Python SDK - -on: - push: - tags: - - "py-sdk-v*.*.*" # Trigger on version tags like py-sdk-v0.1.0, py-sdk-v1.2.3, etc. - -jobs: - validate: - runs-on: ubuntu-latest - timeout-minutes: 10 - outputs: - release_tag: ${{ steps.set_release_tag.outputs.release_tag }} - steps: - - uses: actions/checkout@v4 - with: - fetch-depth: 0 # Fetch all history for checking branch - - name: Set release tag - id: set_release_tag - # ensure the tag is valid (matches code, is on main, etc) - run: | - RELEASE_TAG=${GITHUB_REF#refs/tags/} - echo "Using tag: $RELEASE_TAG" - ./py/scripts/validate-release-tag.sh "$RELEASE_TAG" - echo "RELEASE_TAG=$RELEASE_TAG" >> $GITHUB_ENV - echo "release_tag=$RELEASE_TAG" >> $GITHUB_OUTPUT - - build-and-publish: - needs: validate - runs-on: ubuntu-latest - timeout-minutes: 20 - permissions: - contents: write - id-token: write # Required for PyPI trusted publishing - - env: - ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }} - OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} - GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }} - RELEASE_TAG: ${{ needs.validate.outputs.release_tag }} - - steps: - - uses: actions/checkout@v4 - with: - fetch-depth: 0 # Fetch all history for changelog generation - - name: Set up Python - uses: actions/setup-python@v5 - with: - python-version: "3.13" - - name: Build and verify - working-directory: py - run: | - make install-dev - make verify-build - - name: Upload build artifacts - uses: actions/upload-artifact@v4 - with: - name: python-sdk-dist - path: py/dist/ - retention-days: 5 - - name: Publish to PyPI - uses: pypa/gh-action-pypi-publish@release/v1 - with: - packages-dir: py/dist/ - - # Create GitHub Release - - name: Generate release notes - id: release_notes - run: | - RELEASE_NOTES=$(.github/scripts/generate-release-notes.sh "${{ env.RELEASE_TAG }}" "py/") - echo "notes<> $GITHUB_OUTPUT - echo "$RELEASE_NOTES" >> $GITHUB_OUTPUT - echo "EOF" >> $GITHUB_OUTPUT - - - name: Create GitHub Release - uses: actions/github-script@v7 - env: - RELEASE_NOTES: ${{ steps.release_notes.outputs.notes }} - with: - script: | - await github.rest.repos.createRelease({ - owner: context.repo.owner, - repo: context.repo.repo, - tag_name: process.env.RELEASE_TAG, - name: process.env.RELEASE_TAG, - body: process.env.RELEASE_NOTES, - draft: false, - prerelease: false - }); - - notify-success: - needs: [validate, build-and-publish] - if: always() && needs.build-and-publish.result == 'success' - runs-on: ubuntu-latest - timeout-minutes: 5 - steps: - - name: Extract version from tag - id: version - run: | - TAG="${{ github.ref_name }}" - VERSION="${TAG#py-sdk-v}" - echo "version=$VERSION" >> $GITHUB_OUTPUT - - name: Post to Slack on success - uses: slackapi/slack-github-action@v2.1.1 - with: - method: chat.postMessage - token: ${{ secrets.SLACK_BOT_TOKEN }} - payload: | - channel: C0ABHT0SWA2 - text: "โœ… Python SDK v${{ steps.version.outputs.version }} published" - blocks: - - type: "header" - text: - type: "plain_text" - text: "โœ… Python SDK Published" - - type: "section" - text: - type: "mrkdwn" - text: "*Version:* ${{ steps.version.outputs.version }}\n*Package:* \n\n<${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}|View Run>" - - notify-failure: - needs: [validate, build-and-publish] - if: always() && (needs.validate.result == 'failure' || needs.build-and-publish.result == 'failure') - runs-on: ubuntu-latest - timeout-minutes: 5 - steps: - - name: Post to Slack on failure - uses: slackapi/slack-github-action@v2.1.1 - with: - method: chat.postMessage - token: ${{ secrets.SLACK_BOT_TOKEN }} - payload: | - channel: C0ABHT0SWA2 - text: "๐Ÿšจ Python SDK release failed" - blocks: - - type: "header" - text: - type: "plain_text" - text: "๐Ÿšจ Python SDK Release Failed" - - type: "section" - text: - type: "mrkdwn" - text: "*Tag:* ${{ github.ref_name }}\n*Commit:* ${{ github.sha }}\n\n<${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}|View Run>" diff --git a/.github/workflows/py.yaml b/.github/workflows/py.yaml deleted file mode 100644 index 2ec258df9..000000000 --- a/.github/workflows/py.yaml +++ /dev/null @@ -1,96 +0,0 @@ -name: py - -on: - pull_request: - paths: - - "py/**" - - "integrations/langchain-py/**" - - "integrations/adk-py/**" - - ".github/workflows/py.yaml" - - ".github/workflows/adk-py-test.yaml" - - ".github/workflows/langchain-py-test.yaml" - push: - branches: [main] - -jobs: - build: - runs-on: ${{ matrix.os }} - timeout-minutes: 30 - - strategy: - fail-fast: false - matrix: - python-version: ["3.10", "3.11", "3.12", "3.13"] - os: [ubuntu-latest, windows-latest] - shard: [0, 1] - - env: - ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }} - OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} - GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }} - - steps: - - uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v5 - with: - python-version: ${{ matrix.python-version }} - - name: Install dependencies - run: | - cd py && make install-dev - - name: Test whether the Python SDK can be installed - run: | - # This is already done by make install-dev, but we're keeping this as a separate step - # to explicitly verify that installation works - python -m uv pip install -e ./py[all] - - name: Test whether the Python SDK can be imported - run: | - python -c 'import braintrust' - - name: Run nox tests (shard ${{ matrix.shard }}/2) - shell: bash - run: | - cd py && ./scripts/nox-matrix.sh ${{ matrix.shard }} 2 - - adk-py: - uses: ./.github/workflows/adk-py-test.yaml - strategy: - fail-fast: false - matrix: - python-version: ["3.10", "3.11", "3.12"] - os: [ubuntu-latest, windows-latest] - with: - python-version: ${{ matrix.python-version }} - os: ${{ matrix.os }} - secrets: inherit - - langchain-py: - uses: ./.github/workflows/langchain-py-test.yaml - strategy: - fail-fast: false - matrix: - python-version: ["3.10", "3.11", "3.12", "3.13"] - os: [ubuntu-latest, windows-latest] - with: - python-version: ${{ matrix.python-version }} - os: ${{ matrix.os }} - secrets: inherit - - upload-wheel: - needs: build - runs-on: ubuntu-latest - timeout-minutes: 10 - steps: - - uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v5 - with: - python-version: "3.13" - - name: Install build dependencies and build wheel - run: | - cd py && make install-build-deps && make build - - name: Upload wheel as artifact - uses: actions/upload-artifact@v4 - with: - name: python-wheel - path: py/dist/*.whl - retention-days: 5 diff --git a/.github/workflows/test-publish-py-sdk.yaml b/.github/workflows/test-publish-py-sdk.yaml deleted file mode 100644 index 55fe63a13..000000000 --- a/.github/workflows/test-publish-py-sdk.yaml +++ /dev/null @@ -1,109 +0,0 @@ -# -# This workflow is used to publish the Python SDK to TestPyPI. You do not need to upgrade the -# version number to use this. Only upgrade the version number when you are ready to publish to -# PyPI. The script will automatically add an "rc" suffix to the version number for test.pypi.org -# releases, so you can push a version number to test.pypi.org multiple times. -# - -name: Publish Python SDK to TestPyPI - -on: - workflow_dispatch: - inputs: - ref: - description: "Publish the given Git ref to test.pypi.org (branch, tag, or commit SHA)" - required: true - type: string - default: "main" - -jobs: - build-and-publish-test: - runs-on: ubuntu-latest - timeout-minutes: 20 - permissions: - id-token: write # Required for PyPI trusted publishing - - outputs: - version: ${{ steps.get_version.outputs.version }} - - env: - ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }} - OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} - GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }} - PYPI_REPO: testpypi - - steps: - - uses: actions/checkout@v4 - with: - ref: ${{ github.event.inputs.ref }} - - name: Set up Python - uses: actions/setup-python@v5 - with: - python-version: "3.13" - - name: Install build dependencies - working-directory: py - run: | - make install-dev - - name: Build and verify - working-directory: py - run: | - make verify-build - - name: Get version from built wheel - id: get_version - run: | - WHEEL=$(ls py/dist/*.whl | head -n 1) - VERSION=$(echo "$WHEEL" | sed -n 's/.*braintrust-\([^-]*\)-.*/\1/p') - echo "version=$VERSION" >> $GITHUB_OUTPUT - - name: Publish to TestPyPI - uses: pypa/gh-action-pypi-publish@release/v1 - with: - repository-url: https://test.pypi.org/legacy/ - packages-dir: py/dist/ - - notify-success: - needs: build-and-publish-test - if: success() - runs-on: ubuntu-latest - timeout-minutes: 5 - steps: - - name: Post to Slack on success - uses: slackapi/slack-github-action@v2.1.1 - with: - method: chat.postMessage - token: ${{ secrets.SLACK_BOT_TOKEN }} - payload: | - channel: C0ABHT0SWA2 - text: "๐Ÿงช Python SDK pre-release v${{ needs.build-and-publish-test.outputs.version }} published to TestPyPI" - blocks: - - type: "header" - text: - type: "plain_text" - text: "๐Ÿงช Python SDK Pre-release Published" - - type: "section" - text: - type: "mrkdwn" - text: "*Version:* ${{ needs.build-and-publish-test.outputs.version }}\n*Ref:* ${{ github.event.inputs.ref }}\n*Install:* `pip install -i https://test.pypi.org/simple/ braintrust==${{ needs.build-and-publish-test.outputs.version }}`\n*Package:* \n\n<${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}|View Run>" - - notify-failure: - needs: build-and-publish-test - if: failure() - runs-on: ubuntu-latest - timeout-minutes: 5 - steps: - - name: Post to Slack on failure - uses: slackapi/slack-github-action@v2.1.1 - with: - method: chat.postMessage - token: ${{ secrets.SLACK_BOT_TOKEN }} - payload: | - channel: C0ABHT0SWA2 - text: "๐Ÿšจ Python SDK TestPyPI release failed" - blocks: - - type: "header" - text: - type: "plain_text" - text: "๐Ÿšจ Python SDK TestPyPI Release Failed" - - type: "section" - text: - type: "mrkdwn" - text: "*Ref:* ${{ github.event.inputs.ref }}\n*Commit:* ${{ github.sha }}\n\n<${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}|View Run>" diff --git a/.gitignore b/.gitignore index 9e94a8eb5..e41667815 100644 --- a/.gitignore +++ b/.gitignore @@ -1,7 +1,5 @@ -*.pyc *.swp *.swo -venv .env .direnv .DS_STORE @@ -10,7 +8,6 @@ node_modules .turbo build dist -*.egg-info .aider* !.aiderignore .pnpm-store diff --git a/.husky/pre-commit b/.husky/pre-commit new file mode 100644 index 000000000..5ee7abd87 --- /dev/null +++ b/.husky/pre-commit @@ -0,0 +1 @@ +pnpm exec lint-staged diff --git a/.isort.cfg b/.isort.cfg deleted file mode 100644 index 2a4365a47..000000000 --- a/.isort.cfg +++ /dev/null @@ -1,6 +0,0 @@ -[settings] -line_length=119 -multi_line_output=3 -use_parentheses=true -lines_after_imports=2 -include_trailing_comma=True diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml deleted file mode 100644 index af83981d2..000000000 --- a/.pre-commit-config.yaml +++ /dev/null @@ -1,34 +0,0 @@ -repos: - - repo: "https://github.com/pre-commit/pre-commit-hooks" - rev: v4.4.0 - hooks: - - id: end-of-file-fixer - exclude: (queryscript/tests/.*\.(expected|test)|.*cassette.*\.ya?ml)$ - - id: trailing-whitespace - exclude: (queryscript/tests/.*\.(expected|test)|.*cassette.*\.ya?ml)$ - - repo: https://github.com/astral-sh/ruff-pre-commit - # Ruff version. - rev: v0.12.7 - hooks: - - id: ruff - args: [--fix, --exit-non-zero-on-fix] - - repo: https://github.com/codespell-project/codespell - rev: v2.2.5 - hooks: - - id: codespell - exclude: > - (?x)^( - .*\.(json|prisma|svg) - |.*pnpm-lock.yaml - |.*deno.lock - |.*.yaml - |.*/cassettes/.* - )$ - args: - - "-L" - - "rouge,coo,couldn,unsecure,ontext,afterall,als" - - repo: https://github.com/rbubley/mirrors-prettier - rev: v3.3.2 - hooks: - - id: prettier - exclude: ^(extension/|.*\.json|.*pnpm-lock.yaml|js/scripts/openapi_zod_client_output_template\.hbs|.*cassette.*\.ya?ml)$ diff --git a/.prettierignore b/.prettierignore index 66a1eb7cc..ecf6413c7 100644 --- a/.prettierignore +++ b/.prettierignore @@ -1,2 +1,9 @@ # Patch files use specific whitespace formatting required by unified diff format patches/**/*.patch + +# Lock files +pnpm-lock.yaml +deno.lock + +# Template files with special formatting +js/scripts/openapi_zod_client_output_template.hbs diff --git a/.tool-versions b/.tool-versions index dce2aa1c0..36e55c3fb 100644 --- a/.tool-versions +++ b/.tool-versions @@ -1,3 +1 @@ nodejs 22.15.0 -python 3.13.3 -pre-commit 4.2.0 diff --git a/CLAUDE.md b/CLAUDE.md index 465408a34..a73257713 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -1,27 +1,29 @@ # Braintrust SDK -Python and JavaScript clients for Braintrust, plus wrapper libraries for OpenAI, Anthropic, and other AI providers. +JavaScript client for Braintrust, plus wrapper libraries for OpenAI, Anthropic, and other AI providers. + +This repo uses `pnpm` as it's package manager. ## Structure ``` sdk/ -โ”œโ”€โ”€ py/ # Python SDK (see py/CLAUDE.md) โ”œโ”€โ”€ js/ # JavaScript SDK (see js/CLAUDE.md) โ””โ”€โ”€ core/ # Shared core library ``` ## Quick Reference -| Task | Command | -| ------------- | ------------- | -| Run all tests | `make test` | -| Lint/format | `make fixup` | -| Python lint | `make pylint` | +| Task | Command | +| ------------- | ---------------- | +| Run all tests | `pnpm run test` | +| Build | `pnpm run build` | +| Lint check | `pnpm run lint` | +| Auto-fix | `pnpm run fix` | ## Setup ```bash -make develop # Create venv and install deps -source env.sh # Activate environment +pnpm install # Install dependencies +pnpm run build # Build all packages ``` diff --git a/Makefile b/Makefile index 5978ef8b6..dfb7ac8ca 100644 --- a/Makefile +++ b/Makefile @@ -1,34 +1,5 @@ SHELL := /bin/bash ROOT_DIR:=$(shell dirname $(realpath $(firstword $(MAKEFILE_LIST)))) -VENV_PRE_COMMIT := ${ROOT_DIR}/venv/.pre_commit -VENV_DOCS_REBUILD := ${ROOT_DIR}/venv/.docs_rebuild - -.PHONY: all -all: ${VENV_PRE_COMMIT} - -.PHONY: py -py: ${VENV_PYTHON_PACKAGES} - bash -c 'source venv/bin/activate' - -VENV_INITIALIZED := venv/.initialized - -${VENV_INITIALIZED}: - rm -rf venv && python -m venv venv - @touch ${VENV_INITIALIZED} - -VENV_PYTHON_PACKAGES := venv/.python_packages - -${VENV_PYTHON_PACKAGES}: ${VENV_INITIALIZED} - bash -c 'source venv/bin/activate && python -m pip install --upgrade pip setuptools' - bash -c 'source venv/bin/activate && python -m pip install -e py[all]' - @touch $@ - -${VENV_PRE_COMMIT}: ${VENV_PYTHON_PACKAGES} - bash -c 'source venv/bin/activate && pre-commit install' - @touch $@ - -develop: ${VENV_PRE_COMMIT} - @echo "--\nRun "source env.sh" to enter development mode!" .PHONY: install-dev install-dev: @@ -36,29 +7,18 @@ install-dev: .PHONY: install-deps install-deps: - cd py && make install-dev pnpm install -fixup: - source env.sh && pre-commit run --all-files - -.PHONY: test test-py test-js nox pylint - -test: test-py-core test-py-sdk test-js - -test-py-core: - source env.sh && python -m unittest discover ./core/py/src +.PHONY: test +test: js-test -test-py-sdk: nox - source env.sh && cd py && pytest - - -nox: - cd py && make test - -pylint: - cd py && make lint +.PHONY: lint +lint: + pnpm run lint +.PHONY: fixup +fixup: + pnpm run fix # # js stuff diff --git a/README.md b/README.md index 7e08d8b70..04e4befcd 100644 --- a/README.md +++ b/README.md @@ -3,13 +3,12 @@ [Braintrust](https://www.braintrust.dev/) is a platform for evaluating and shipping AI products. To learn more about Braintrust or sign up for free, visit our [website](https://www.braintrust.dev/) or check out the [docs](https://www.braintrust.dev/docs). -This repository contains the Python and Javascript SDKs for Braintrust. The SDKs include utilities to: +This repository contains the JavaScript SDK for Braintrust. The SDK includes utilities to: - Log experiments and datasets to Braintrust - Run evaluations (via the `Eval` framework) -- Manage an on-premises installation of Braintrust (Python) -## Quickstart: TypeScript +## Quickstart First, install the Braintrust SDK: @@ -58,50 +57,11 @@ BRAINTRUST_API_KEY= \ npx braintrust eval tutorial.eval.ts ``` -## Quickstart: Python - -Install the library with pip. - -```bash -pip install braintrust autoevals -``` - -Then, create a file named `eval_tutorial.py` with the following code: - -```python -from braintrust import Eval -from autoevals import LevenshteinScorer - -Eval( - "Say Hi Bot", - data=lambda: [ - { - "input": "Foo", - "expected": "Hi Foo", - }, - { - "input": "Bar", - "expected": "Hello Bar", - }, - ], # Replace with your eval dataset - task=lambda input: "Hi " + input, # Replace with your LLM call - scores=[LevenshteinScorer], -) -``` - -Then, run the following command: - -```bash -BRAINTRUST_API_KEY= \ - braintrust eval eval_tutorial.py -``` - ## Integrations Braintrust provides integrations with several popular AI development tools and platforms: - **LangChain.js**: A callback handler to automatically log LangChain.js executions to Braintrust. [Learn more](integrations/langchain-js) -- **LangChain Python**: Integration for logging LangChain Python executions to Braintrust. [Learn more](integrations/langchain-py) - **Val Town**: Examples and templates for using Braintrust with Val Town's serverless JavaScript/TypeScript environment. [Learn more](integrations/val.town) - **Vercel AI SDK**: Integration with Vercel's AI SDK for building AI-powered applications. [Learn more](integrations/vercel-ai-sdk) @@ -110,4 +70,3 @@ Braintrust provides integrations with several popular AI development tools and p For more information, check out the [docs](https://www.braintrust.dev/docs): - [TypeScript](https://www.braintrust.dev/docs/reference/sdks/typescript) -- [Python](https://www.braintrust.dev/docs/reference/sdks/python) diff --git a/env.sh b/env.sh deleted file mode 100644 index 23e6f0474..000000000 --- a/env.sh +++ /dev/null @@ -1,8 +0,0 @@ -#!/bin/bash - -SRC_ROOT="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )" - -ps1_old="$PS1" -source $SRC_ROOT/venv/bin/activate -export BRAINTRUST_DEV=1 -export PS1="(bt) $ps1_old" diff --git a/generated_types.json b/generated_types.json index 505c3dfa4..0819b8ddc 100644 --- a/generated_types.json +++ b/generated_types.json @@ -25,18 +25,12 @@ "description": "The id of the object the ACL applies to" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Id of the user the ACL applies to. Exactly one of `user_id` and `group_id` will be provided" }, "group_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Id of the group the ACL applies to. Exactly one of `user_id` and `group_id` will be provided" }, @@ -46,10 +40,7 @@ "$ref": "#/components/schemas/Permission" }, { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Permission the ACL grants. Exactly one of `permission` and `role_id` will be provided" } ] @@ -65,10 +56,7 @@ ] }, "role_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Id of the role the ACL grants. Exactly one of `permission` and `role_id` will be provided" }, @@ -78,27 +66,16 @@ "description": "The organization the ACL's referred object belongs to" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of acl creation" } }, - "required": [ - "id", - "object_type", - "object_id", - "_object_org_id" - ], + "required": ["id", "object_type", "object_id", "_object_org_id"], "description": "An ACL grants a certain permission or role to a certain user or group on an object.\n\nACLs are inherited across the object hierarchy. So for example, if a user has read permissions on a project, they will also have read permissions on any experiment, dataset, etc. created within that project.\n\nTo restrict a grant to a particular sub-object, you may specify `restrict_object_type` in the ACL, as part of a direct permission grant or as part of a role." }, "AclObjectType": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "enum": [ "organization", "project", @@ -123,18 +100,12 @@ "description": "Unique identifier for the AI secret" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of AI secret creation" }, "updated_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of last AI secret update" }, @@ -148,30 +119,17 @@ "description": "Name of the AI secret" }, "type": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {} }, "preview_secret": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] } }, - "required": [ - "id", - "org_id", - "name" - ] + "required": ["id", "org_id", "name"] }, "AnyModelParams": { "type": "object", @@ -202,23 +160,17 @@ "anyOf": [ { "type": "string", - "enum": [ - "auto" - ], + "enum": ["auto"], "title": "auto" }, { "type": "string", - "enum": [ - "none" - ], + "enum": ["none"], "title": "none" }, { "type": "string", - "enum": [ - "required" - ], + "enum": ["required"], "title": "required" }, { @@ -226,9 +178,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "function": { "type": "object", @@ -237,15 +187,10 @@ "type": "string" } }, - "required": [ - "name" - ] + "required": ["name"] } }, - "required": [ - "type", - "function" - ], + "required": ["type", "function"], "title": "function" } ] @@ -254,16 +199,12 @@ "anyOf": [ { "type": "string", - "enum": [ - "auto" - ], + "enum": ["auto"], "title": "auto" }, { "type": "string", - "enum": [ - "none" - ], + "enum": ["none"], "title": "none" }, { @@ -273,9 +214,7 @@ "type": "string" } }, - "required": [ - "name" - ], + "required": ["name"], "title": "function" } ] @@ -291,21 +230,11 @@ }, "reasoning_effort": { "type": "string", - "enum": [ - "none", - "minimal", - "low", - "medium", - "high" - ] + "enum": ["none", "minimal", "low", "medium", "high"] }, "verbosity": { "type": "string", - "enum": [ - "low", - "medium", - "high" - ] + "enum": ["low", "medium", "high"] }, "top_k": { "type": "number" @@ -339,9 +268,7 @@ "type": "boolean" } }, - "required": [ - "max_tokens" - ] + "required": ["max_tokens"] }, "ApiKey": { "type": "object", @@ -352,10 +279,7 @@ "description": "Unique identifier for the api key" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of api key creation" }, @@ -367,48 +291,29 @@ "type": "string" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Unique identifier for the user" }, "user_email": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The user's email" }, "user_given_name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Given name of the user" }, "user_family_name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Family name of the user" }, "org_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Unique identifier for the organization" } }, - "required": [ - "id", - "name", - "preview_name" - ] + "required": ["id", "name", "preview_name"] }, "AsyncScoringControl": { "oneOf": [ @@ -417,72 +322,53 @@ "properties": { "kind": { "type": "string", - "enum": [ - "score_update" - ] + "enum": ["score_update"] }, "token": { "type": "string" } }, - "required": [ - "kind" - ] + "required": ["kind"] }, { "type": "object", "properties": { "kind": { "type": "string", - "enum": [ - "state_override" - ] + "enum": ["state_override"] }, "state": { "$ref": "#/components/schemas/AsyncScoringState" } }, - "required": [ - "kind", - "state" - ] + "required": ["kind", "state"] }, { "type": "object", "properties": { "kind": { "type": "string", - "enum": [ - "state_force_reselect" - ] + "enum": ["state_force_reselect"] } }, - "required": [ - "kind" - ] + "required": ["kind"] }, { "type": "object", "properties": { "kind": { "type": "string", - "enum": [ - "state_enabled_force_rescore" - ] + "enum": ["state_enabled_force_rescore"] } }, - "required": [ - "kind" - ] + "required": ["kind"] }, { "type": "object", "properties": { "kind": { "type": "string", - "enum": [ - "trigger_functions" - ] + "enum": ["trigger_functions"] }, "triggered_functions": { "type": "array", @@ -497,28 +383,20 @@ "properties": { "type": { "type": "string", - "enum": [ - "span" - ] + "enum": ["span"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "trace" - ] + "enum": ["trace"] } }, - "required": [ - "type" - ] + "required": ["type"] } ] }, @@ -526,26 +404,19 @@ "type": "string" } }, - "required": [ - "scope" - ] + "required": ["scope"] }, "minItems": 1 } }, - "required": [ - "kind", - "triggered_functions" - ] + "required": ["kind", "triggered_functions"] }, { "type": "object", "properties": { "kind": { "type": "string", - "enum": [ - "complete_triggered_functions" - ] + "enum": ["complete_triggered_functions"] }, "function_ids": { "type": "array", @@ -556,20 +427,14 @@ "type": "string" } }, - "required": [ - "kind", - "function_ids", - "triggered_xact_id" - ] + "required": ["kind", "function_ids", "triggered_xact_id"] }, { "type": "object", "properties": { "kind": { "type": "string", - "enum": [ - "mark_attempt_failed" - ] + "enum": ["mark_attempt_failed"] }, "function_ids": { "type": "array", @@ -577,10 +442,7 @@ "minItems": 1 } }, - "required": [ - "kind", - "function_ids" - ] + "required": ["kind", "function_ids"] } ] }, @@ -591,9 +453,7 @@ "properties": { "status": { "type": "string", - "enum": [ - "enabled" - ] + "enum": ["enabled"] }, "token": { "type": "string" @@ -603,40 +463,26 @@ "items": {} }, "skip_logging": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] }, "triggered_functions": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { "$ref": "#/components/schemas/TriggeredFunctionState" } } }, - "required": [ - "status", - "token", - "function_ids" - ] + "required": ["status", "token", "function_ids"] }, { "type": "object", "properties": { "status": { "type": "string", - "enum": [ - "disabled" - ] + "enum": ["disabled"] } }, - "required": [ - "status" - ] + "required": ["status"] }, { "type": "null" @@ -674,18 +520,14 @@ "description": "Describes the error encountered while uploading." } }, - "required": [ - "upload_status" - ] + "required": ["upload_status"] }, "BatchedFacetData": { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "batched_facet" - ] + "enum": ["batched_facet"] }, "preprocessor": { "allOf": [ @@ -723,10 +565,7 @@ "description": "Regex pattern to identify outputs that do not match the facet. If the output matches, the facet will be saved as 'no_match'" } }, - "required": [ - "name", - "prompt" - ] + "required": ["name", "prompt"] } }, "topic_maps": { @@ -748,19 +587,13 @@ "$ref": "#/components/schemas/TopicMapData" } }, - "required": [ - "function_name", - "topic_map_data" - ] + "required": ["function_name", "topic_map_data"] } }, "description": "Topic maps that depend on facets in this batch, keyed by source facet name. Each source facet can have multiple topic maps." } }, - "required": [ - "type", - "facets" - ], + "required": ["type", "facets"], "title": "batched_facet" }, "BraintrustAttachmentReference": { @@ -768,9 +601,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "braintrust_attachment" - ], + "enum": ["braintrust_attachment"], "description": "An identifier to help disambiguate parsing." }, "filename": { @@ -789,12 +620,7 @@ "description": "Key in the object store bucket for this attachment." } }, - "required": [ - "type", - "filename", - "content_type", - "key" - ] + "required": ["type", "filename", "content_type", "key"] }, "BraintrustModelParams": { "type": "object", @@ -823,15 +649,10 @@ }, "event": { "type": "string", - "enum": [ - "text_delta" - ] + "enum": ["text_delta"] } }, - "required": [ - "data", - "event" - ], + "required": ["data", "event"], "title": "text_delta" }, { @@ -845,15 +666,10 @@ }, "event": { "type": "string", - "enum": [ - "reasoning_delta" - ] + "enum": ["reasoning_delta"] } }, - "required": [ - "data", - "event" - ], + "required": ["data", "event"], "title": "reasoning_delta" }, { @@ -867,15 +683,10 @@ }, "event": { "type": "string", - "enum": [ - "json_delta" - ] + "enum": ["json_delta"] } }, - "required": [ - "data", - "event" - ], + "required": ["data", "event"], "title": "json_delta" }, { @@ -889,15 +700,10 @@ }, "event": { "type": "string", - "enum": [ - "progress" - ] + "enum": ["progress"] } }, - "required": [ - "data", - "event" - ], + "required": ["data", "event"], "title": "progress" }, { @@ -911,15 +717,10 @@ }, "event": { "type": "string", - "enum": [ - "error" - ] + "enum": ["error"] } }, - "required": [ - "data", - "event" - ], + "required": ["data", "event"], "title": "error" }, { @@ -933,15 +734,10 @@ }, "event": { "type": "string", - "enum": [ - "console" - ] + "enum": ["console"] } }, - "required": [ - "data", - "event" - ], + "required": ["data", "event"], "title": "console" }, { @@ -952,21 +748,14 @@ }, "event": { "type": "string", - "enum": [ - "start" - ] + "enum": ["start"] }, "data": { "type": "string", - "enum": [ - "" - ] + "enum": [""] } }, - "required": [ - "event", - "data" - ], + "required": ["event", "data"], "title": "start" }, { @@ -977,21 +766,14 @@ }, "event": { "type": "string", - "enum": [ - "done" - ] + "enum": ["done"] }, "data": { "type": "string", - "enum": [ - "" - ] + "enum": [""] } }, - "required": [ - "event", - "data" - ], + "required": ["event", "data"], "title": "done" } ] @@ -1033,15 +815,10 @@ }, "type": { "type": "string", - "enum": [ - "file" - ] + "enum": ["file"] } }, - "required": [ - "file", - "type" - ], + "required": ["file", "type"], "title": "file" }, "ChatCompletionContentPartImageWithTitle": { @@ -1057,43 +834,30 @@ "anyOf": [ { "type": "string", - "enum": [ - "auto" - ], + "enum": ["auto"], "title": "auto" }, { "type": "string", - "enum": [ - "low" - ], + "enum": ["low"], "title": "low" }, { "type": "string", - "enum": [ - "high" - ], + "enum": ["high"], "title": "high" } ] } }, - "required": [ - "url" - ] + "required": ["url"] }, "type": { "type": "string", - "enum": [ - "image_url" - ] + "enum": ["image_url"] } }, - "required": [ - "image_url", - "type" - ], + "required": ["image_url", "type"], "title": "image_url" }, "ChatCompletionContentPartText": { @@ -1105,29 +869,20 @@ }, "type": { "type": "string", - "enum": [ - "text" - ] + "enum": ["text"] }, "cache_control": { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "ephemeral" - ] + "enum": ["ephemeral"] } }, - "required": [ - "type" - ] + "required": ["type"] } }, - "required": [ - "type", - "text" - ] + "required": ["type", "text"] }, "ChatCompletionContentPartTextWithTitle": { "type": "object", @@ -1138,29 +893,20 @@ }, "type": { "type": "string", - "enum": [ - "text" - ] + "enum": ["text"] }, "cache_control": { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "ephemeral" - ] + "enum": ["ephemeral"] } }, - "required": [ - "type" - ] + "required": ["type"] } }, - "required": [ - "type", - "text" - ], + "required": ["type", "text"], "title": "text" }, "ChatCompletionMessageParam": { @@ -1186,18 +932,13 @@ }, "role": { "type": "string", - "enum": [ - "system" - ] + "enum": ["system"] }, "name": { "type": "string" } }, - "required": [ - "role", - "content" - ], + "required": ["role", "content"], "title": "system" }, { @@ -1221,18 +962,13 @@ }, "role": { "type": "string", - "enum": [ - "user" - ] + "enum": ["user"] }, "name": { "type": "string" } }, - "required": [ - "role", - "content" - ], + "required": ["role", "content"], "title": "user" }, { @@ -1240,9 +976,7 @@ "properties": { "role": { "type": "string", - "enum": [ - "assistant" - ] + "enum": ["assistant"] }, "content": { "anyOf": [ @@ -1270,10 +1004,7 @@ "type": "string" } }, - "required": [ - "arguments", - "name" - ] + "required": ["arguments", "name"] }, "name": { "type": "string" @@ -1291,9 +1022,7 @@ } } }, - "required": [ - "role" - ], + "required": ["role"], "title": "assistant" }, { @@ -1317,46 +1046,31 @@ }, "role": { "type": "string", - "enum": [ - "tool" - ] + "enum": ["tool"] }, "tool_call_id": { "type": "string", "default": "" } }, - "required": [ - "role", - "content", - "tool_call_id" - ], + "required": ["role", "content", "tool_call_id"], "title": "tool" }, { "type": "object", "properties": { "content": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "name": { "type": "string" }, "role": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] } }, - "required": [ - "content", - "name", - "role" - ], + "required": ["content", "name", "role"], "title": "function" }, { @@ -1380,18 +1094,13 @@ }, "role": { "type": "string", - "enum": [ - "developer" - ] + "enum": ["developer"] }, "name": { "type": "string" } }, - "required": [ - "role", - "content" - ], + "required": ["role", "content"], "title": "developer" }, { @@ -1399,20 +1108,13 @@ "properties": { "role": { "type": "string", - "enum": [ - "model" - ] + "enum": ["model"] }, "content": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] } }, - "required": [ - "role" - ], + "required": ["role"], "title": "fallback" } ] @@ -1445,23 +1147,14 @@ "type": "string" } }, - "required": [ - "arguments", - "name" - ] + "required": ["arguments", "name"] }, "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] } }, - "required": [ - "id", - "function", - "type" - ] + "required": ["id", "function", "type"] }, "ChatCompletionOpenAIMessageParam": { "anyOf": [ @@ -1486,18 +1179,13 @@ }, "role": { "type": "string", - "enum": [ - "system" - ] + "enum": ["system"] }, "name": { "type": "string" } }, - "required": [ - "role", - "content" - ], + "required": ["role", "content"], "title": "system" }, { @@ -1521,18 +1209,13 @@ }, "role": { "type": "string", - "enum": [ - "user" - ] + "enum": ["user"] }, "name": { "type": "string" } }, - "required": [ - "role", - "content" - ], + "required": ["role", "content"], "title": "user" }, { @@ -1540,9 +1223,7 @@ "properties": { "role": { "type": "string", - "enum": [ - "assistant" - ] + "enum": ["assistant"] }, "content": { "anyOf": [ @@ -1570,10 +1251,7 @@ "type": "string" } }, - "required": [ - "arguments", - "name" - ] + "required": ["arguments", "name"] }, "name": { "type": "string" @@ -1591,9 +1269,7 @@ } } }, - "required": [ - "role" - ], + "required": ["role"], "title": "assistant" }, { @@ -1617,46 +1293,31 @@ }, "role": { "type": "string", - "enum": [ - "tool" - ] + "enum": ["tool"] }, "tool_call_id": { "type": "string", "default": "" } }, - "required": [ - "role", - "content", - "tool_call_id" - ], + "required": ["role", "content", "tool_call_id"], "title": "tool" }, { "type": "object", "properties": { "content": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "name": { "type": "string" }, "role": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] } }, - "required": [ - "content", - "name", - "role" - ], + "required": ["content", "name", "role"], "title": "function" }, { @@ -1680,18 +1341,13 @@ }, "role": { "type": "string", - "enum": [ - "developer" - ] + "enum": ["developer"] }, "name": { "type": "string" } }, - "required": [ - "role", - "content" - ], + "required": ["role", "content"], "title": "developer" } ] @@ -1713,21 +1369,14 @@ "additionalProperties": {} } }, - "required": [ - "name" - ] + "required": ["name"] }, "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] } }, - "required": [ - "function", - "type" - ] + "required": ["function", "type"] }, "CodeBundle": { "type": "object", @@ -1737,21 +1386,13 @@ "properties": { "runtime": { "type": "string", - "enum": [ - "node", - "python", - "browser", - "quickjs" - ] + "enum": ["node", "python", "browser", "quickjs"] }, "version": { "type": "string" } }, - "required": [ - "runtime", - "version" - ] + "required": ["runtime", "version"] }, "location": { "anyOf": [ @@ -1760,9 +1401,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "experiment" - ] + "enum": ["experiment"] }, "eval_name": { "type": "string" @@ -1774,43 +1413,30 @@ "properties": { "type": { "type": "string", - "enum": [ - "task" - ] + "enum": ["task"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "scorer" - ] + "enum": ["scorer"] }, "index": { "type": "integer", "minimum": 0 } }, - "required": [ - "type", - "index" - ], + "required": ["type", "index"], "title": "scorer" } ] } }, - "required": [ - "type", - "eval_name", - "position" - ], + "required": ["type", "eval_name", "position"], "title": "experiment" }, { @@ -1818,19 +1444,14 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "index": { "type": "integer", "minimum": 0 } }, - "required": [ - "type", - "index" - ], + "required": ["type", "index"], "title": "function" }, { @@ -1838,9 +1459,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "sandbox" - ] + "enum": ["sandbox"] }, "sandbox_spec": { "oneOf": [ @@ -1849,33 +1468,24 @@ "properties": { "provider": { "type": "string", - "enum": [ - "modal" - ] + "enum": ["modal"] }, "snapshot_ref": { "type": "string", "description": "sandbox snapshot ref" } }, - "required": [ - "provider", - "snapshot_ref" - ] + "required": ["provider", "snapshot_ref"] }, { "type": "object", "properties": { "provider": { "type": "string", - "enum": [ - "lambda" - ] + "enum": ["lambda"] } }, - "required": [ - "provider" - ] + "required": ["provider"] } ] }, @@ -1898,32 +1508,19 @@ "description": "Definition of current evaluator with parameters" } }, - "required": [ - "type", - "sandbox_spec", - "eval_name" - ] + "required": ["type", "sandbox_spec", "eval_name"] } ] }, "bundle_id": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "preview": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "A preview of the code" } }, - "required": [ - "runtime_context", - "location" - ] + "required": ["runtime_context", "location"] }, "Dataset": { "type": "object", @@ -1943,41 +1540,26 @@ "description": "Name of the dataset. Within a project, dataset names are unique" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the dataset" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of dataset creation" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of dataset deletion, or null if the dataset is still active" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the dataset" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "User-controlled metadata about the dataset" }, @@ -1986,12 +1568,7 @@ "description": "URL slug for the dataset. used to construct dataset URLs" } }, - "required": [ - "id", - "project_id", - "name", - "url_slug" - ] + "required": ["id", "project_id", "name", "url_slug"] }, "DatasetEvent": { "type": "object", @@ -2010,10 +1587,7 @@ "description": "The timestamp the dataset event was created" }, "_pagination_key": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "A stable, time-ordered key that can be used to paginate over dataset events. This field is auto-generated by Braintrust and only exists in Brainstore." }, "project_id": { @@ -2033,16 +1607,10 @@ "description": "The output of your application, including post-processing (an arbitrary, JSON serializable object)" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "model": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The model used for this example" } }, @@ -2050,10 +1618,7 @@ "description": "A dictionary with additional data about the test example, model outputs, or just about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any JSON-serializable type, but its keys must be strings" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, @@ -2068,44 +1633,29 @@ "description": "A unique identifier for the trace this dataset event belongs to" }, "is_root": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether this span is a root span" }, "origin": { "$ref": "#/components/schemas/ObjectReferenceNullish" }, "comments": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {}, "description": "Optional list of comments attached to this event" }, "audit_data": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {}, "description": "Optional list of audit entries attached to this event" }, "facets": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "Facets for categorization (dictionary from facet id to value)" }, "classifications": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { "type": "array", "items": { @@ -2120,17 +1670,11 @@ "description": "Original label of the classification item, which is useful for search and indexing purposes" }, "confidence": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "Optional confidence score for the classification" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "Optional metadata associated with the classification" }, @@ -2146,9 +1690,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "id": { "type": "string" @@ -2158,10 +1700,7 @@ "description": "The version of the function" } }, - "required": [ - "type", - "id" - ], + "required": ["type", "id"], "title": "function" }, { @@ -2169,9 +1708,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "global" - ] + "enum": ["global"] }, "name": { "type": "string" @@ -2180,10 +1717,7 @@ "$ref": "#/components/schemas/FunctionTypeEnum" } }, - "required": [ - "type", - "name" - ], + "required": ["type", "name"], "title": "global" }, { @@ -2195,9 +1729,7 @@ ] } }, - "required": [ - "id" - ] + "required": ["id"] } }, "description": "Classifications for this event (dictionary from classification name to items)" @@ -2223,11 +1755,7 @@ }, "object_type": { "type": "string", - "enum": [ - "organization", - "project", - "function" - ], + "enum": ["organization", "project", "function"], "description": "The type of the object the environment variable is scoped for" }, "object_id": { @@ -2240,53 +1768,32 @@ "description": "The name of the environment variable" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of environment variable creation" }, "used": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date the environment variable was last used" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "Optional metadata associated with the environment variable when managed via the function secrets API" }, "secret_type": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Optional classification for the secret (for example, the AI provider name)" }, "secret_category": { "type": "string", - "enum": [ - "env_var", - "ai_provider", - "sandbox_provider" - ], + "enum": ["env_var", "ai_provider", "sandbox_provider"], "default": "env_var", "description": "The category of the secret: env_var for regular environment variables, ai_provider for AI provider API keys" } }, - "required": [ - "id", - "object_type", - "object_id", - "name" - ] + "required": ["id", "object_type", "object_id", "name"] }, "EvalStatusPage": { "type": "object", @@ -2302,26 +1809,17 @@ "description": "Unique identifier for the project that the eval status page belongs under" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the eval status page" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of eval status page creation" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of eval status page deletion, or null if the eval status page is still active" }, @@ -2330,17 +1828,11 @@ "description": "Name of the eval status page" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the eval status page" }, "logo_url": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "URL of the logo to display on the page" }, "theme": { @@ -2350,75 +1842,45 @@ "$ref": "#/components/schemas/EvalStatusPageConfig" } }, - "required": [ - "id", - "project_id", - "name", - "theme", - "config" - ], + "required": ["id", "project_id", "name", "theme", "config"], "description": "A public eval status page that displays aggregate experiment results" }, "EvalStatusPageConfig": { "type": "object", "properties": { "score_columns": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "The score columns to display on the page" }, "metric_columns": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "The metric columns to display on the page" }, "grouping_field": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The metadata field to use for grouping experiments (model)" }, "filter": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "BTQL filter to apply to experiment data" }, "sort_by": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Field to sort results by (format: 'score:' or 'metric:')" }, "sort_order": { - "type": [ - "string", - "null" - ], - "enum": [ - "asc", - "desc" - ], + "type": ["string", "null"], + "enum": ["asc", "desc"], "description": "Sort order (ascending or descending)" }, "api_key": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The API key used for fetching experiment data" } }, @@ -2426,10 +1888,7 @@ }, "EvalStatusPageTheme": { "type": "string", - "enum": [ - "light", - "dark" - ], + "enum": ["light", "dark"], "description": "The theme for the page" }, "Experiment": { @@ -2450,17 +1909,11 @@ "description": "Name of the experiment. Within a project, experiment names are unique" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the experiment" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of experiment creation" }, @@ -2468,41 +1921,26 @@ "$ref": "#/components/schemas/RepoInfo" }, "commit": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Commit, taken directly from `repo_info.commit`" }, "base_exp_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Id of default base experiment to compare against when viewing this experiment" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of experiment deletion, or null if the experiment is still active" }, "dataset_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifier of the linked dataset, or null if the experiment is not linked to a dataset" }, "dataset_version": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Version number of the linked dataset the experiment was run against. This can be used to reproduce the experiment after the dataset has been modified." }, "public": { @@ -2510,38 +1948,24 @@ "description": "Whether or not the experiment is public. Public experiments can be viewed by anybody inside or outside the organization" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the experiment" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "User-controlled metadata about the experiment" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "A list of tags for the experiment" } }, - "required": [ - "id", - "project_id", - "name", - "public" - ] + "required": ["id", "project_id", "name", "public"] }, "ExperimentEvent": { "type": "object", @@ -2560,10 +1984,7 @@ "description": "The timestamp the experiment event was created" }, "_pagination_key": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "A stable, time-ordered key that can be used to paginate over experiment events. This field is auto-generated by Braintrust and only exists in Brainstore." }, "project_id": { @@ -2589,31 +2010,19 @@ "description": "The error that occurred, if any." }, "scores": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "minimum": 0, "maximum": 1 }, "description": "A dictionary of numeric values (between 0 and 1) to log. The scores should give you a variety of signals that help you determine how accurate the outputs are compared to what you expect and diagnose failures. For example, a summarization app might have one score that tells you how accurate the summary is, and another that measures the word similarity between the generated and grouth truth summary. The word similarity score could help you determine whether the summarization was covering similar concepts or not. You can use these scores to help you sort, filter, and compare experiments" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "model": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The model used for this example" } }, @@ -2621,54 +2030,33 @@ "description": "A dictionary with additional data about the test example, model outputs, or just about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any JSON-serializable type, but its keys must be strings" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "A list of tags to log" }, "metrics": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "start": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "A unix timestamp recording when the section of code which produced the experiment event started" }, "end": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "A unix timestamp recording when the section of code which produced the experiment event finished" }, "prompt_tokens": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "The number of tokens in the prompt used to generate the experiment event (only set if this is an LLM span)" }, "completion_tokens": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "The number of tokens in the completion generated by the model (only set if this is an LLM span)" }, "tokens": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "The total number of tokens in the input and output of the experiment event." }, "caller_functionname": { @@ -2687,30 +2075,18 @@ "description": "Metrics are numerical measurements tracking the execution of the code that produced the experiment event. Use \"start\" and \"end\" to track the time span over which the experiment event was produced" }, "context": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "caller_functionname": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The function in code which created the experiment event" }, "caller_filename": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Name of the file in code where the experiment event was created" }, "caller_lineno": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "Line of code where the experiment event was created" } }, @@ -2722,10 +2098,7 @@ "description": "A unique identifier used to link different experiment events together as part of a full trace. See the [tracing guide](https://www.braintrust.dev/docs/instrument) for full details on tracing" }, "span_parents": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, @@ -2739,44 +2112,29 @@ "$ref": "#/components/schemas/SpanAttributes" }, "is_root": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether this span is a root span" }, "origin": { "$ref": "#/components/schemas/ObjectReferenceNullish" }, "comments": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {}, "description": "Optional list of comments attached to this event" }, "audit_data": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {}, "description": "Optional list of audit entries attached to this event" }, "facets": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "Facets for categorization (dictionary from facet id to value)" }, "classifications": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { "type": "array", "items": { @@ -2791,17 +2149,11 @@ "description": "Original label of the classification item, which is useful for search and indexing purposes" }, "confidence": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "Optional confidence score for the classification" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "Optional metadata associated with the classification" }, @@ -2817,9 +2169,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "id": { "type": "string" @@ -2829,10 +2179,7 @@ "description": "The version of the function" } }, - "required": [ - "type", - "id" - ], + "required": ["type", "id"], "title": "function" }, { @@ -2840,9 +2187,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "global" - ] + "enum": ["global"] }, "name": { "type": "string" @@ -2851,10 +2196,7 @@ "$ref": "#/components/schemas/FunctionTypeEnum" } }, - "required": [ - "type", - "name" - ], + "required": ["type", "name"], "title": "global" }, { @@ -2866,9 +2208,7 @@ ] } }, - "required": [ - "id" - ] + "required": ["id"] } }, "description": "Classifications for this event (dictionary from classification name to items)" @@ -2891,9 +2231,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "id": { "type": "string" @@ -2903,10 +2241,7 @@ "description": "The version of the function" } }, - "required": [ - "type", - "id" - ], + "required": ["type", "id"], "title": "function" }, { @@ -2914,9 +2249,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "global" - ] + "enum": ["global"] }, "name": { "type": "string" @@ -2925,10 +2258,7 @@ "$ref": "#/components/schemas/FunctionTypeEnum" } }, - "required": [ - "type", - "name" - ], + "required": ["type", "name"], "title": "global" }, { @@ -2936,9 +2266,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "slug" - ] + "enum": ["slug"] }, "project_id": { "type": "string" @@ -2947,11 +2275,7 @@ "type": "string" } }, - "required": [ - "type", - "project_id", - "slug" - ] + "required": ["type", "project_id", "slug"] } ] }, @@ -2960,9 +2284,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "external_attachment" - ], + "enum": ["external_attachment"], "description": "An identifier to help disambiguate parsing." }, "filename": { @@ -2981,21 +2303,14 @@ "description": "Fully qualified URL to the object in the external object store." } }, - "required": [ - "type", - "filename", - "content_type", - "url" - ] + "required": ["type", "filename", "content_type", "url"] }, "FacetData": { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "facet" - ] + "enum": ["facet"] }, "preprocessor": { "allOf": [ @@ -3024,10 +2339,7 @@ "description": "Regex pattern to identify outputs that do not match the facet. If the output matches, the facet will be saved as 'no_match'" } }, - "required": [ - "type", - "prompt" - ], + "required": ["type", "prompt"], "title": "facet" }, "Function": { @@ -3049,9 +2361,7 @@ }, "log_id": { "type": "string", - "enum": [ - "p" - ], + "enum": ["p"], "description": "A literal 'p' which identifies the object as a project prompt" }, "org_id": { @@ -3068,17 +2378,11 @@ "description": "Unique identifier for the prompt" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the prompt" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of prompt creation" }, @@ -3086,20 +2390,14 @@ "$ref": "#/components/schemas/PromptDataNullish" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "A list of tags for the prompt" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "User-controlled metadata about the prompt" }, @@ -3110,10 +2408,7 @@ "$ref": "#/components/schemas/FunctionData" }, "origin": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "object_type": { "allOf": [ @@ -3131,23 +2426,14 @@ "description": "Id of the object the function is originating from" }, "internal": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "The function exists for internal purposes and should not be displayed in the list of functions." } }, - "required": [ - "object_type", - "object_id" - ] + "required": ["object_type", "object_id"] }, "function_schema": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "parameters": {}, "returns": {} @@ -3173,14 +2459,10 @@ "properties": { "type": { "type": "string", - "enum": [ - "prompt" - ] + "enum": ["prompt"] } }, - "required": [ - "type" - ], + "required": ["type"], "title": "prompt" }, { @@ -3188,9 +2470,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "code" - ] + "enum": ["code"] }, "data": { "anyOf": [ @@ -3201,14 +2481,10 @@ "properties": { "type": { "type": "string", - "enum": [ - "bundle" - ] + "enum": ["bundle"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "$ref": "#/components/schemas/CodeBundle" @@ -3221,30 +2497,20 @@ "properties": { "type": { "type": "string", - "enum": [ - "inline" - ] + "enum": ["inline"] }, "runtime_context": { "type": "object", "properties": { "runtime": { "type": "string", - "enum": [ - "node", - "python", - "browser", - "quickjs" - ] + "enum": ["node", "python", "browser", "quickjs"] }, "version": { "type": "string" } }, - "required": [ - "runtime", - "version" - ] + "required": ["runtime", "version"] }, "code": { "type": "string" @@ -3254,20 +2520,13 @@ "description": "SHA256 hash of the code, computed at save time" } }, - "required": [ - "type", - "runtime_context", - "code" - ], + "required": ["type", "runtime_context", "code"], "title": "inline" } ] } }, - "required": [ - "type", - "data" - ], + "required": ["type", "data"], "title": "code" }, { @@ -3278,9 +2537,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "remote_eval" - ] + "enum": ["remote_eval"] }, "endpoint": { "type": "string" @@ -3293,19 +2550,11 @@ "additionalProperties": {} }, "parameters_version": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The version (transaction ID) of the parameters being used" } }, - "required": [ - "type", - "endpoint", - "eval_name", - "parameters" - ], + "required": ["type", "endpoint", "eval_name", "parameters"], "description": "A remote eval to run", "title": "remote_eval" }, @@ -3314,9 +2563,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "global" - ] + "enum": ["global"] }, "name": { "type": "string" @@ -3325,18 +2572,12 @@ "$ref": "#/components/schemas/FunctionTypeEnum" }, "config": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "Configuration options to pass to the global function (e.g., for preprocessor customization)" } }, - "required": [ - "type", - "name" - ], + "required": ["type", "name"], "title": "global" }, { @@ -3350,9 +2591,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "parameters" - ] + "enum": ["parameters"] }, "data": { "type": "object", @@ -3364,9 +2603,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "object" - ] + "enum": ["object"] }, "properties": { "type": "object", @@ -3385,18 +2622,11 @@ "type": "boolean" } }, - "required": [ - "type", - "properties" - ], + "required": ["type", "properties"], "description": "JSON Schema format for parameters" } }, - "required": [ - "type", - "data", - "__schema" - ], + "required": ["type", "data", "__schema"], "title": "parameters" }, { @@ -3413,13 +2643,7 @@ }, "FunctionFormat": { "type": "string", - "enum": [ - "llm", - "code", - "global", - "graph", - "topic_map" - ] + "enum": ["llm", "code", "global", "graph", "topic_map"] }, "FunctionId": { "anyOf": [ @@ -3435,9 +2659,7 @@ "description": "The version of the function" } }, - "required": [ - "function_id" - ], + "required": ["function_id"], "description": "Function id", "title": "function_id" }, @@ -3457,10 +2679,7 @@ "description": "The version of the function" } }, - "required": [ - "project_name", - "slug" - ], + "required": ["project_name", "slug"], "description": "Project name and slug", "title": "project_slug" }, @@ -3475,9 +2694,7 @@ "$ref": "#/components/schemas/FunctionTypeEnum" } }, - "required": [ - "global_function" - ], + "required": ["global_function"], "description": "Global function name", "title": "global_function" }, @@ -3497,10 +2714,7 @@ "description": "The version of the function" } }, - "required": [ - "prompt_session_id", - "prompt_session_function_id" - ], + "required": ["prompt_session_id", "prompt_session_function_id"], "description": "Prompt session id", "title": "prompt_session_id" }, @@ -3512,38 +2726,24 @@ "properties": { "runtime": { "type": "string", - "enum": [ - "node", - "python", - "browser", - "quickjs" - ] + "enum": ["node", "python", "browser", "quickjs"] }, "version": { "type": "string" } }, - "required": [ - "runtime", - "version" - ] + "required": ["runtime", "version"] }, "code": { "type": "string", "description": "The inline code to execute" }, "name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The name of the inline code function" } }, - "required": [ - "inline_context", - "code" - ], + "required": ["inline_context", "code"], "description": "Inline code function", "title": "inline_code" }, @@ -3561,16 +2761,11 @@ "$ref": "#/components/schemas/FunctionTypeEnum" }, "name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The name of the inline function" } }, - "required": [ - "inline_function" - ], + "required": ["inline_function"], "description": "Inline function definition", "title": "inline_function" }, @@ -3584,16 +2779,11 @@ "$ref": "#/components/schemas/FunctionTypeEnum" }, "name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The name of the inline prompt" } }, - "required": [ - "inline_prompt" - ], + "required": ["inline_prompt"], "description": "Inline prompt definition", "title": "inline_prompt" } @@ -3624,13 +2814,7 @@ }, "FunctionOutputType": { "type": "string", - "enum": [ - "completion", - "score", - "facet", - "classification", - "any" - ] + "enum": ["completion", "score", "facet", "classification", "any"] }, "FunctionTypeEnum": { "type": "string", @@ -3651,10 +2835,7 @@ "description": "The type of global function. Defaults to 'scorer'." }, "FunctionTypeEnumNullish": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "enum": [ "llm", "scorer", @@ -3674,11 +2855,7 @@ "properties": { "collect": { "type": "string", - "enum": [ - "all", - "none", - "some" - ] + "enum": ["all", "none", "some"] }, "fields": { "type": "array", @@ -3698,9 +2875,7 @@ } } }, - "required": [ - "collect" - ], + "required": ["collect"], "additionalProperties": false }, "GraphData": { @@ -3708,9 +2883,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "graph" - ] + "enum": ["graph"] }, "nodes": { "type": "object", @@ -3725,11 +2898,7 @@ } } }, - "required": [ - "type", - "nodes", - "edges" - ], + "required": ["type", "nodes", "edges"], "description": "This feature is preliminary and unsupported.", "title": "graph" }, @@ -3748,10 +2917,7 @@ "type": "string" } }, - "required": [ - "node", - "variable" - ] + "required": ["node", "variable"] }, "target": { "type": "object", @@ -3765,26 +2931,15 @@ "type": "string" } }, - "required": [ - "node", - "variable" - ] + "required": ["node", "variable"] }, "purpose": { "type": "string", - "enum": [ - "control", - "data", - "messages" - ], + "enum": ["control", "data", "messages"], "description": "The purpose of the edge" } }, - "required": [ - "source", - "target", - "purpose" - ] + "required": ["source", "target", "purpose"] }, "GraphNode": { "anyOf": [ @@ -3792,17 +2947,11 @@ "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -3813,42 +2962,28 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "function": { "$ref": "#/components/schemas/FunctionIdRef" } }, - "required": [ - "type", - "function" - ] + "required": ["type", "function"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -3859,39 +2994,26 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "input" - ], + "enum": ["input"], "description": "The input to the graph" } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -3902,39 +3024,26 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "output" - ], + "enum": ["output"], "description": "The output of the graph" } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -3945,41 +3054,28 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "literal" - ] + "enum": ["literal"] }, "value": { "description": "A literal value to be returned" } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -3990,43 +3086,29 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "btql" - ] + "enum": ["btql"] }, "expr": { "type": "string", "description": "A BTQL expression to be evaluated" } }, - "required": [ - "type", - "expr" - ] + "required": ["type", "expr"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -4037,45 +3119,29 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "gate" - ] + "enum": ["gate"] }, "condition": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "A BTQL expression to be evaluated" } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -4086,38 +3152,25 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "aggregator" - ] + "enum": ["aggregator"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -4128,26 +3181,18 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "prompt_template" - ] + "enum": ["prompt_template"] }, "prompt": { "$ref": "#/components/schemas/PromptBlockData" } }, - "required": [ - "type", - "prompt" - ] + "required": ["type", "prompt"] } ] }, @@ -4165,18 +3210,12 @@ "description": "Unique id for the organization that the group belongs under\n\nIt is forbidden to change the org after creating a group" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the group" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of group creation" }, @@ -4185,25 +3224,16 @@ "description": "Name of the group" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the group" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of group deletion, or null if the group is still active" }, "member_users": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string", "format": "uuid" @@ -4211,10 +3241,7 @@ "description": "Ids of users which belong to this group" }, "member_groups": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string", "format": "uuid" @@ -4222,11 +3249,7 @@ "description": "Ids of the groups this group inherits from\n\nAn inheriting group has all the users contained in its member groups, as well as all of their inherited users" } }, - "required": [ - "id", - "org_id", - "name" - ], + "required": ["id", "org_id", "name"], "description": "A group is a collection of users which can be assigned an ACL\n\nGroups can consist of individual users, as well as a set of groups they inherit from" }, "GroupScope": { @@ -4234,9 +3257,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "group" - ] + "enum": ["group"] }, "group_by": { "type": "string", @@ -4247,30 +3268,16 @@ "description": "Optional: trigger after this many seconds of inactivity" } }, - "required": [ - "type", - "group_by" - ], + "required": ["type", "group_by"], "description": "Process spans/traces grouped by a field (e.g., session_id)" }, "IfExists": { "type": "string", - "enum": [ - "error", - "ignore", - "replace" - ] + "enum": ["error", "ignore", "replace"] }, "ImageRenderingMode": { - "type": [ - "string", - "null" - ], - "enum": [ - "auto", - "click_to_load", - "blocked" - ], + "type": ["string", "null"], + "enum": ["auto", "click_to_load", "blocked"], "description": "Controls how images are rendered in the UI: 'auto' loads images automatically, 'click_to_load' shows a placeholder until clicked, 'blocked' prevents image loading entirely" }, "InvokeFunction": { @@ -4288,18 +3295,12 @@ "description": "The expected output of the function" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "Any relevant metadata. This will be logged and available as the `metadata` argument." }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, @@ -4316,20 +3317,14 @@ "$ref": "#/components/schemas/InvokeParent" }, "stream": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether to stream the response. If true, results will be returned in the Braintrust SSE format." }, "mode": { "$ref": "#/components/schemas/StreamingMode" }, "strict": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "If true, throw an error if one of the variables in the prompt is not present in the input" }, "mcp_auth": { @@ -4346,10 +3341,7 @@ "description": "Map of MCP server URL to auth credentials" }, "overrides": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "Partial function definition to merge with the function being invoked. Fields are validated against the function type's schema at runtime. For facets: { preprocessor?, prompt?, model? }. For prompts: { model?, ... }." } @@ -4365,21 +3357,14 @@ "properties": { "object_type": { "type": "string", - "enum": [ - "project_logs", - "experiment", - "playground_logs" - ] + "enum": ["project_logs", "experiment", "playground_logs"] }, "object_id": { "type": "string", "description": "The id of the container object you are logging to" }, "row_ids": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "id": { "type": "string", @@ -4394,26 +3379,16 @@ "description": "The root_span_id of the row" } }, - "required": [ - "id", - "span_id", - "root_span_id" - ], + "required": ["id", "span_id", "root_span_id"], "description": "Identifiers for the row to to log a subspan under" }, "propagated_event": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "Include these properties in every span created under this parent" } }, - "required": [ - "object_type", - "object_id" - ], + "required": ["object_type", "object_id"], "description": "Span parent properties", "title": "span_parent_struct" }, @@ -4438,26 +3413,17 @@ "description": "Unique identifier for the project that the MCP server belongs under" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the MCP server" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of MCP server creation" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of MCP server deletion, or null if the MCP server is still active" }, @@ -4466,10 +3432,7 @@ "description": "Name of the MCP server. Within a project, MCP server names are unique" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the MCP server" }, "url": { @@ -4477,12 +3440,7 @@ "description": "URL of the MCP server endpoint" } }, - "required": [ - "id", - "project_id", - "name", - "url" - ] + "required": ["id", "project_id", "name", "url"] }, "MessageRole": { "type": "string", @@ -4536,23 +3494,17 @@ "anyOf": [ { "type": "string", - "enum": [ - "auto" - ], + "enum": ["auto"], "title": "auto" }, { "type": "string", - "enum": [ - "none" - ], + "enum": ["none"], "title": "none" }, { "type": "string", - "enum": [ - "required" - ], + "enum": ["required"], "title": "required" }, { @@ -4560,9 +3512,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "function": { "type": "object", @@ -4571,15 +3521,10 @@ "type": "string" } }, - "required": [ - "name" - ] + "required": ["name"] } }, - "required": [ - "type", - "function" - ], + "required": ["type", "function"], "title": "function" } ] @@ -4588,16 +3533,12 @@ "anyOf": [ { "type": "string", - "enum": [ - "auto" - ], + "enum": ["auto"], "title": "auto" }, { "type": "string", - "enum": [ - "none" - ], + "enum": ["none"], "title": "none" }, { @@ -4607,9 +3548,7 @@ "type": "string" } }, - "required": [ - "name" - ], + "required": ["name"], "title": "function" } ] @@ -4625,21 +3564,11 @@ }, "reasoning_effort": { "type": "string", - "enum": [ - "none", - "minimal", - "low", - "medium", - "high" - ] + "enum": ["none", "minimal", "low", "medium", "high"] }, "verbosity": { "type": "string", - "enum": [ - "low", - "medium", - "high" - ] + "enum": ["low", "medium", "high"] } }, "additionalProperties": {}, @@ -4680,10 +3609,7 @@ "description": "This is a legacy parameter that should not be used." } }, - "required": [ - "max_tokens", - "temperature" - ], + "required": ["max_tokens", "temperature"], "additionalProperties": {}, "title": "AnthropicModelParams" }, @@ -4762,9 +3688,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "id": { "type": "string" @@ -4774,10 +3698,7 @@ "description": "The version of the function" } }, - "required": [ - "type", - "id" - ], + "required": ["type", "id"], "title": "function" }, { @@ -4785,9 +3706,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "global" - ] + "enum": ["global"] }, "name": { "type": "string" @@ -4796,10 +3715,7 @@ "$ref": "#/components/schemas/FunctionTypeEnum" } }, - "required": [ - "type", - "name" - ], + "required": ["type", "name"], "title": "global" }, { @@ -4833,32 +3749,19 @@ "description": "ID of the original event." }, "_xact_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Transaction ID of the original event." }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Created timestamp of the original event. Used to help sort in the UI" } }, - "required": [ - "object_type", - "object_id", - "id" - ], + "required": ["object_type", "object_id", "id"], "description": "Reference to the original object and event this was copied from." }, "ObjectReferenceNullish": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "object_type": { "type": "string", @@ -4882,32 +3785,19 @@ "description": "ID of the original event." }, "_xact_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Transaction ID of the original event." }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Created timestamp of the original event. Used to help sort in the UI" } }, - "required": [ - "object_type", - "object_id", - "id" - ], + "required": ["object_type", "object_id", "id"], "description": "Indicates the event was copied from another object." }, "OnlineScoreConfig": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "sampling_rate": { "type": "number", @@ -4923,34 +3813,22 @@ "description": "The list of functions to run for online scoring. Can include scorers, facets, or other function types." }, "btql_filter": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Filter logs using BTQL" }, "apply_to_root_span": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether to trigger online scoring on the root span of each trace. Only applies when scope is 'span' or unset." }, "apply_to_span_names": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "Trigger online scoring on any spans with a name in this list. Only applies when scope is 'span' or unset." }, "skip_logging": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether to skip adding scorer spans when computing scores" }, "scope": { @@ -4971,10 +3849,7 @@ "description": "The scope at which to run the functions. Defaults to span-level execution. Trace/group scope requires all functions to be facets." } }, - "required": [ - "sampling_rate", - "scorers" - ] + "required": ["sampling_rate", "scorers"] }, "Organization": { "type": "object", @@ -4989,40 +3864,22 @@ "description": "Name of the organization" }, "api_url": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "is_universal_api": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] }, "is_dataplane_private": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] }, "proxy_url": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "realtime_url": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of organization creation" }, @@ -5030,10 +3887,7 @@ "$ref": "#/components/schemas/ImageRenderingMode" } }, - "required": [ - "id", - "name" - ] + "required": ["id", "name"] }, "Permission": { "type": "string", @@ -5067,33 +3921,21 @@ "description": "Name of the project" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the project" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of project creation" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of project deletion, or null if the project is still active" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the project" }, @@ -5101,11 +3943,7 @@ "$ref": "#/components/schemas/ProjectSettings" } }, - "required": [ - "id", - "org_id", - "name" - ] + "required": ["id", "org_id", "name"] }, "ProjectAutomation": { "type": "object", @@ -5121,18 +3959,12 @@ "description": "Unique identifier for the project that the project automation belongs under" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the project automation" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of project automation creation" }, @@ -5141,10 +3973,7 @@ "description": "Name of the project automation" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the project automation" }, "config": { @@ -5154,9 +3983,7 @@ "properties": { "event_type": { "type": "string", - "enum": [ - "logs" - ], + "enum": ["logs"], "description": "The type of automation." }, "btql_filter": { @@ -5176,9 +4003,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "webhook" - ], + "enum": ["webhook"], "description": "The type of action to take" }, "url": { @@ -5186,19 +4011,14 @@ "description": "The webhook URL to send the request to" } }, - "required": [ - "type", - "url" - ] + "required": ["type", "url"] }, { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "slack" - ], + "enum": ["slack"], "description": "The type of action to take" }, "workspace_id": { @@ -5214,11 +4034,7 @@ "description": "Custom message template for the alert" } }, - "required": [ - "type", - "workspace_id", - "channel" - ] + "required": ["type", "workspace_id", "channel"] } ], "description": "The action to take when the automation rule is triggered" @@ -5236,9 +4052,7 @@ "properties": { "event_type": { "type": "string", - "enum": [ - "btql_export" - ], + "enum": ["btql_export"], "description": "The type of automation." }, "export_definition": { @@ -5248,47 +4062,34 @@ "properties": { "type": { "type": "string", - "enum": [ - "log_traces" - ] + "enum": ["log_traces"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "log_spans" - ] + "enum": ["log_spans"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "btql_query" - ] + "enum": ["btql_query"] }, "btql_query": { "type": "string", "description": "The BTQL query to export" } }, - "required": [ - "type", - "btql_query" - ] + "required": ["type", "btql_query"] } ], "description": "The definition of what to export" @@ -5299,10 +4100,7 @@ }, "format": { "type": "string", - "enum": [ - "jsonl", - "parquet" - ], + "enum": ["jsonl", "parquet"], "description": "The format to export the results in" }, "interval_seconds": { @@ -5318,9 +4116,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "aws_iam" - ] + "enum": ["aws_iam"] }, "role_arn": { "type": "string", @@ -5331,19 +4127,12 @@ "description": "The automation-specific external id component (auto-generated by default)" } }, - "required": [ - "type", - "role_arn", - "external_id" - ] + "required": ["type", "role_arn", "external_id"] } ] }, "batch_size": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "The number of rows to export in each batch" } }, @@ -5361,9 +4150,7 @@ "properties": { "event_type": { "type": "string", - "enum": [ - "retention" - ], + "enum": ["retention"], "description": "The type of automation." }, "object_type": { @@ -5375,20 +4162,14 @@ "description": "The number of days to retain the object" } }, - "required": [ - "event_type", - "object_type", - "retention_days" - ] + "required": ["event_type", "object_type", "retention_days"] }, { "type": "object", "properties": { "event_type": { "type": "string", - "enum": [ - "environment_update" - ], + "enum": ["environment_update"], "description": "The type of automation." }, "environment_filter": { @@ -5405,9 +4186,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "webhook" - ], + "enum": ["webhook"], "description": "The type of action to take" }, "url": { @@ -5415,19 +4194,14 @@ "description": "The webhook URL to send the request to" } }, - "required": [ - "type", - "url" - ] + "required": ["type", "url"] }, { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "slack" - ], + "enum": ["slack"], "description": "The type of action to take" }, "workspace_id": { @@ -5443,20 +4217,13 @@ "description": "Custom message template for the alert" } }, - "required": [ - "type", - "workspace_id", - "channel" - ] + "required": ["type", "workspace_id", "channel"] } ], "description": "The action to take when the automation rule is triggered" } }, - "required": [ - "event_type", - "action" - ] + "required": ["event_type", "action"] }, { "$ref": "#/components/schemas/TopicAutomationConfig" @@ -5465,12 +4232,7 @@ "description": "The configuration for the automation rule" } }, - "required": [ - "id", - "project_id", - "name", - "config" - ] + "required": ["id", "project_id", "name", "config"] }, "ProjectLogsEvent": { "type": "object", @@ -5484,10 +4246,7 @@ "description": "The transaction id of an event is unique to the network operation that processed the event insertion. Transaction ids are monotonically increasing over time and can be used to retrieve a versioned snapshot of the project logs (see the `version` parameter)" }, "_pagination_key": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "A stable, time-ordered key that can be used to paginate over project logs events. This field is auto-generated by Braintrust and only exists in Brainstore." }, "created": { @@ -5507,9 +4266,7 @@ }, "log_id": { "type": "string", - "enum": [ - "g" - ], + "enum": ["g"], "description": "A literal 'g' which identifies the log as a project log" }, "input": { @@ -5525,31 +4282,19 @@ "description": "The error that occurred, if any." }, "scores": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "minimum": 0, "maximum": 1 }, "description": "A dictionary of numeric values (between 0 and 1) to log. The scores should give you a variety of signals that help you determine how accurate the outputs are compared to what you expect and diagnose failures. For example, a summarization app might have one score that tells you how accurate the summary is, and another that measures the word similarity between the generated and grouth truth summary. The word similarity score could help you determine whether the summarization was covering similar concepts or not. You can use these scores to help you sort, filter, and compare logs." }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "model": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The model used for this example" } }, @@ -5557,54 +4302,33 @@ "description": "A dictionary with additional data about the test example, model outputs, or just about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any JSON-serializable type, but its keys must be strings" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "A list of tags to log" }, "metrics": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "start": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "A unix timestamp recording when the section of code which produced the project logs event started" }, "end": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "A unix timestamp recording when the section of code which produced the project logs event finished" }, "prompt_tokens": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "The number of tokens in the prompt used to generate the project logs event (only set if this is an LLM span)" }, "completion_tokens": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "The number of tokens in the completion generated by the model (only set if this is an LLM span)" }, "tokens": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "The total number of tokens in the input and output of the project logs event." }, "caller_functionname": { @@ -5623,30 +4347,18 @@ "description": "Metrics are numerical measurements tracking the execution of the code that produced the project logs event. Use \"start\" and \"end\" to track the time span over which the project logs event was produced" }, "context": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "caller_functionname": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The function in code which created the project logs event" }, "caller_filename": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Name of the file in code where the project logs event was created" }, "caller_lineno": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "Line of code where the project logs event was created" } }, @@ -5658,10 +4370,7 @@ "description": "A unique identifier used to link different project logs events together as part of a full trace. See the [tracing guide](https://www.braintrust.dev/docs/instrument) for full details on tracing" }, "span_parents": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, @@ -5672,10 +4381,7 @@ "description": "A unique identifier for the trace this project logs event belongs to" }, "is_root": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether this span is a root span" }, "span_attributes": { @@ -5685,18 +4391,12 @@ "$ref": "#/components/schemas/ObjectReferenceNullish" }, "comments": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {}, "description": "Optional list of comments attached to this event" }, "audit_data": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {}, "description": "Optional list of audit entries attached to this event" }, @@ -5704,18 +4404,12 @@ "description": "The async scoring state for this event" }, "facets": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "Facets for categorization (dictionary from facet id to value)" }, "classifications": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { "type": "array", "items": { @@ -5730,17 +4424,11 @@ "description": "Original label of the classification item, which is useful for search and indexing purposes" }, "confidence": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "Optional confidence score for the classification" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "Optional metadata associated with the classification" }, @@ -5756,9 +4444,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "id": { "type": "string" @@ -5768,10 +4454,7 @@ "description": "The version of the function" } }, - "required": [ - "type", - "id" - ], + "required": ["type", "id"], "title": "function" }, { @@ -5779,9 +4462,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "global" - ] + "enum": ["global"] }, "name": { "type": "string" @@ -5790,10 +4471,7 @@ "$ref": "#/components/schemas/FunctionTypeEnum" } }, - "required": [ - "type", - "name" - ], + "required": ["type", "name"], "title": "global" }, { @@ -5805,9 +4483,7 @@ ] } }, - "required": [ - "id" - ] + "required": ["id"] } }, "description": "Classifications for this event (dictionary from classification name to items)" @@ -5842,10 +4518,7 @@ "format": "uuid" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of project score creation" }, @@ -5854,10 +4527,7 @@ "description": "Name of the project score" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the project score" }, "score_type": { @@ -5870,20 +4540,11 @@ "$ref": "#/components/schemas/ProjectScoreConfig" }, "position": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "An optional LexoRank-based string that sets the sort position for the score in the UI" } }, - "required": [ - "id", - "project_id", - "user_id", - "name", - "score_type" - ], + "required": ["id", "project_id", "user_id", "name", "score_type"], "description": "A project score is a user-configured score, which can be manually-labeled through the UI" }, "ProjectScoreCategories": { @@ -5929,29 +4590,17 @@ "description": "Numerical value of the category. Must be between 0 and 1, inclusive" } }, - "required": [ - "name", - "value" - ], + "required": ["name", "value"], "description": "For categorical-type project scores, defines a single category" }, "ProjectScoreConfig": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "multi_select": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] }, "destination": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "online": { "$ref": "#/components/schemas/OnlineScoreConfig" @@ -5972,31 +4621,19 @@ "description": "The type of the configured score" }, "ProjectSettings": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "comparison_key": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The key used to join two experiments (defaults to `input`)" }, "baseline_experiment_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "The id of the experiment to use as the default baseline for comparisons" }, "spanFieldOrder": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "object", "properties": { @@ -6013,15 +4650,11 @@ "anyOf": [ { "type": "string", - "enum": [ - "full" - ] + "enum": ["full"] }, { "type": "string", - "enum": [ - "two_column" - ] + "enum": ["two_column"] }, { "type": "null" @@ -6029,19 +4662,12 @@ ] } }, - "required": [ - "object_type", - "column_id", - "position" - ] + "required": ["object_type", "column_id", "position"] }, "description": "The order of the fields to display in the trace view" }, "remote_eval_sources": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "object", "properties": { @@ -6049,29 +4675,18 @@ "type": "string" }, "name": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "description": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] } }, - "required": [ - "url" - ] + "required": ["url"] }, "description": "The remote eval sources to use for the project" }, "disable_realtime_queries": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "If true, disable real-time queries for this project. This can improve query performance for high-volume logs." }, "default_preprocessor": { @@ -6097,10 +4712,7 @@ "format": "uuid" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of project tag creation" }, @@ -6109,33 +4721,19 @@ "description": "Name of the project tag" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the project tag" }, "color": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Color of the tag for the UI" }, "position": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "An optional LexoRank-based string that sets the sort position for the tag in the UI" } }, - "required": [ - "id", - "project_id", - "user_id", - "name" - ], + "required": ["id", "project_id", "user_id", "name"], "description": "A project tag is a user-configured tag for tracking and filtering your experiments, logs, and other data" }, "Prompt": { @@ -6157,9 +4755,7 @@ }, "log_id": { "type": "string", - "enum": [ - "p" - ], + "enum": ["p"], "description": "A literal 'p' which identifies the object as a project prompt" }, "org_id": { @@ -6176,17 +4772,11 @@ "description": "Unique identifier for the prompt" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the prompt" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of prompt creation" }, @@ -6194,20 +4784,14 @@ "$ref": "#/components/schemas/PromptDataNullish" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "A list of tags for the prompt" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "User-controlled metadata about the prompt" }, @@ -6232,9 +4816,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "chat" - ] + "enum": ["chat"] }, "messages": { "type": "array", @@ -6246,10 +4828,7 @@ "type": "string" } }, - "required": [ - "type", - "messages" - ], + "required": ["type", "messages"], "title": "chat" }, { @@ -6257,18 +4836,13 @@ "properties": { "type": { "type": "string", - "enum": [ - "completion" - ] + "enum": ["completion"] }, "content": { "type": "string" } }, - "required": [ - "type", - "content" - ], + "required": ["type", "content"], "title": "completion" } ] @@ -6280,9 +4854,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "chat" - ] + "enum": ["chat"] }, "messages": { "type": "array", @@ -6294,10 +4866,7 @@ "type": "string" } }, - "required": [ - "type", - "messages" - ], + "required": ["type", "messages"], "title": "chat" }, { @@ -6305,18 +4874,13 @@ "properties": { "type": { "type": "string", - "enum": [ - "completion" - ] + "enum": ["completion"] }, "content": { "type": "string" } }, - "required": [ - "type", - "content" - ], + "required": ["type", "content"], "title": "completion" }, { @@ -6337,30 +4901,17 @@ "$ref": "#/components/schemas/PromptParserNullish" }, "tool_functions": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "$ref": "#/components/schemas/SavedFunctionId" } }, "template_format": { - "type": [ - "string", - "null" - ], - "enum": [ - "mustache", - "nunjucks", - "none" - ] + "type": ["string", "null"], + "enum": ["mustache", "nunjucks", "none"] }, "mcp": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { "oneOf": [ { @@ -6368,9 +4919,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "id" - ] + "enum": ["id"] }, "id": { "type": "string", @@ -6380,20 +4929,14 @@ "type": "boolean" }, "enabled_tools": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "If omitted, all tools are enabled" } }, - "required": [ - "type", - "id" - ], + "required": ["type", "id"], "title": "MCP server id. This is used for project-level MCP server definitions." }, { @@ -6401,9 +4944,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "url" - ] + "enum": ["url"] }, "url": { "type": "string" @@ -6412,30 +4953,21 @@ "type": "boolean" }, "enabled_tools": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "If omitted, all tools are enabled" } }, - "required": [ - "type", - "url" - ], + "required": ["type", "url"], "title": "MCP server url. This is used for inline definitions of MCP servers." } ] } }, "origin": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "prompt_id": { "type": "string" @@ -6451,10 +4983,7 @@ } }, "PromptDataNullish": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "prompt": { "$ref": "#/components/schemas/PromptBlockDataNullish" @@ -6466,30 +4995,17 @@ "$ref": "#/components/schemas/PromptParserNullish" }, "tool_functions": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "$ref": "#/components/schemas/SavedFunctionId" } }, "template_format": { - "type": [ - "string", - "null" - ], - "enum": [ - "mustache", - "nunjucks", - "none" - ] + "type": ["string", "null"], + "enum": ["mustache", "nunjucks", "none"] }, "mcp": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { "oneOf": [ { @@ -6497,9 +5013,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "id" - ] + "enum": ["id"] }, "id": { "type": "string", @@ -6509,20 +5023,14 @@ "type": "boolean" }, "enabled_tools": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "If omitted, all tools are enabled" } }, - "required": [ - "type", - "id" - ], + "required": ["type", "id"], "title": "MCP server id. This is used for project-level MCP server definitions." }, { @@ -6530,9 +5038,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "url" - ] + "enum": ["url"] }, "url": { "type": "string" @@ -6541,30 +5047,21 @@ "type": "boolean" }, "enabled_tools": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "If omitted, all tools are enabled" } }, - "required": [ - "type", - "url" - ], + "required": ["type", "url"], "title": "MCP server url. This is used for inline definitions of MCP servers." } ] } }, "origin": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "prompt_id": { "type": "string" @@ -6595,10 +5092,7 @@ } }, "PromptOptionsNullish": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "model": { "type": "string" @@ -6612,16 +5106,11 @@ } }, "PromptParserNullish": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "type": { "type": "string", - "enum": [ - "llm_classifier" - ] + "enum": ["llm_classifier"] }, "use_cot": { "type": "boolean" @@ -6647,10 +5136,7 @@ "description": "If true, adds a 'No match' option. When selected, no tag is deposited." } }, - "required": [ - "type", - "use_cot" - ] + "required": ["type", "use_cot"] }, "PromptSessionEvent": { "type": "object", @@ -6669,10 +5155,7 @@ "description": "The timestamp the prompt session event was created" }, "_pagination_key": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "A stable, time-ordered key that can be used to paginate over prompt session events. This field is auto-generated by Braintrust and only exists in Brainstore." }, "project_id": { @@ -6704,10 +5187,7 @@ "description": "Data about the completion" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, @@ -6723,72 +5203,42 @@ ] }, "RepoInfo": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "commit": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "SHA of most recent commit" }, "branch": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Name of the branch the most recent commit belongs to" }, "tag": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Name of the tag on the most recent commit" }, "dirty": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether or not the repo had uncommitted changes when snapshotted" }, "author_name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Name of the author of the most recent commit" }, "author_email": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Email of the author of the most recent commit" }, "commit_message": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Most recent commit message" }, "commit_time": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Time of the most recent commit" }, "git_diff": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "If the repo was dirty when run, this includes the diff between the current state of the repo and the most recent commit." } }, @@ -6801,14 +5251,10 @@ "properties": { "type": { "type": "string", - "enum": [ - "json_object" - ] + "enum": ["json_object"] } }, - "required": [ - "type" - ], + "required": ["type"], "title": "json_object" }, { @@ -6816,18 +5262,13 @@ "properties": { "type": { "type": "string", - "enum": [ - "json_schema" - ] + "enum": ["json_schema"] }, "json_schema": { "$ref": "#/components/schemas/ResponseFormatJsonSchema" } }, - "required": [ - "type", - "json_schema" - ], + "required": ["type", "json_schema"], "title": "json_schema" }, { @@ -6835,14 +5276,10 @@ "properties": { "type": { "type": "string", - "enum": [ - "text" - ] + "enum": ["text"] } }, - "required": [ - "type" - ], + "required": ["type"], "title": "text" } ] @@ -6870,15 +5307,10 @@ ] }, "strict": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] } }, - "required": [ - "name" - ] + "required": ["name"] }, "ResponseFormatNullish": { "anyOf": [ @@ -6887,14 +5319,10 @@ "properties": { "type": { "type": "string", - "enum": [ - "json_object" - ] + "enum": ["json_object"] } }, - "required": [ - "type" - ], + "required": ["type"], "title": "json_object" }, { @@ -6902,18 +5330,13 @@ "properties": { "type": { "type": "string", - "enum": [ - "json_schema" - ] + "enum": ["json_schema"] }, "json_schema": { "$ref": "#/components/schemas/ResponseFormatJsonSchema" } }, - "required": [ - "type", - "json_schema" - ], + "required": ["type", "json_schema"], "title": "json_schema" }, { @@ -6921,14 +5344,10 @@ "properties": { "type": { "type": "string", - "enum": [ - "text" - ] + "enum": ["text"] } }, - "required": [ - "type" - ], + "required": ["type"], "title": "text" }, { @@ -6938,11 +5357,7 @@ }, "RetentionObjectType": { "type": "string", - "enum": [ - "project_logs", - "experiment", - "dataset" - ], + "enum": ["project_logs", "experiment", "dataset"], "description": "The object type that the retention policy applies to" }, "Role": { @@ -6954,26 +5369,17 @@ "description": "Unique identifier for the role" }, "org_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Unique id for the organization that the role belongs under\n\nA null org_id indicates a system role, which may be assigned to anybody and inherited by any other role, but cannot be edited.\n\nIt is forbidden to change the org after creating a role" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the role" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of role creation" }, @@ -6982,25 +5388,16 @@ "description": "Name of the role" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the role" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of role deletion, or null if the role is still active" }, "member_permissions": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "object", "properties": { @@ -7011,17 +5408,12 @@ "$ref": "#/components/schemas/AclObjectType" } }, - "required": [ - "permission" - ] + "required": ["permission"] }, "description": "(permission, restrict_object_type) tuples which belong to this role" }, "member_roles": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string", "format": "uuid" @@ -7029,10 +5421,7 @@ "description": "Ids of the roles this role inherits from\n\nAn inheriting role has all the permissions contained in its member roles, as well as all of their inherited permissions" } }, - "required": [ - "id", - "name" - ], + "required": ["id", "name"], "description": "A role is a collection of permissions which can be granted as part of an ACL\n\nRoles can consist of individual permissions, as well as a set of roles they inherit from" }, "RunEval": { @@ -7051,16 +5440,11 @@ "type": "string" }, "_internal_btql": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {} } }, - "required": [ - "dataset_id" - ], + "required": ["dataset_id"], "description": "Dataset id", "title": "dataset_id" }, @@ -7074,17 +5458,11 @@ "type": "string" }, "_internal_btql": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {} } }, - "required": [ - "project_name", - "dataset_name" - ], + "required": ["project_name", "dataset_name"], "description": "Project and dataset name", "title": "project_dataset_name" }, @@ -7096,9 +5474,7 @@ "items": {} } }, - "required": [ - "data" - ], + "required": ["data"], "description": "Dataset rows", "title": "dataset_rows" } @@ -7155,46 +5531,28 @@ "description": "Whether to stream the results of the eval. If true, the request will return two events: one to indicate the experiment has started, and another upon completion. If false, the request will return the evaluation's summary upon completion." }, "trial_count": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "The number of times to run the evaluator per input. This is useful for evaluating applications that have non-deterministic behavior and gives you both a stronger aggregate measure and a sense of the variance in the results." }, "is_public": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether the experiment should be public. Defaults to false." }, "timeout": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "The maximum duration, in milliseconds, to run the evaluation. Defaults to undefined, in which case there is no timeout." }, "max_concurrency": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "default": 10, "description": "The maximum number of tasks/scorers that will be run concurrently. Defaults to 10. If null is provided, no max concurrency will be used." }, "base_experiment_name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "An optional experiment name to use as a base. If specified, the new experiment will be summarized and compared to this experiment." }, "base_experiment_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "An optional experiment id to use as a base. If specified, the new experiment will be summarized and compared to this experiment." }, "git_metadata_settings": { @@ -7203,10 +5561,7 @@ "$ref": "#/components/schemas/GitMetadataSettings" }, { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "description": "Optional settings for collecting git metadata. By default, will collect all git metadata fields allowed in org-level settings." } ] @@ -7222,17 +5577,11 @@ ] }, "strict": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "If true, throw an error if one of the variables in the prompt is not present in the input" }, "stop_token": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The token to stop the run" }, "extra_messages": { @@ -7259,12 +5608,7 @@ } } }, - "required": [ - "project_id", - "data", - "task", - "scores" - ] + "required": ["project_id", "data", "task", "scores"] }, "SavedFunctionId": { "anyOf": [ @@ -7273,9 +5617,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "id": { "type": "string" @@ -7285,10 +5627,7 @@ "description": "The version of the function" } }, - "required": [ - "type", - "id" - ], + "required": ["type", "id"], "title": "function" }, { @@ -7296,9 +5635,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "global" - ] + "enum": ["global"] }, "name": { "type": "string" @@ -7307,10 +5644,7 @@ "$ref": "#/components/schemas/FunctionTypeEnum" } }, - "required": [ - "type", - "name" - ], + "required": ["type", "name"], "title": "global" } ] @@ -7324,10 +5658,7 @@ "description": "Unique identifier for the service token" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of service token creation" }, @@ -7339,53 +5670,31 @@ "type": "string" }, "service_account_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Unique identifier for the service token" }, "service_account_email": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The service account email (not routable)" }, "service_account_name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The service account name" }, "org_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Unique identifier for the organization" } }, - "required": [ - "id", - "name", - "preview_name" - ] + "required": ["id", "name", "preview_name"] }, "SpanAttributes": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Name of the span, for display purposes only" }, "type": { @@ -7409,26 +5718,17 @@ "description": "Unique identifier for the project that the span iframe belongs under" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the span iframe" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of span iframe creation" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of span iframe deletion, or null if the span iframe is still active" }, @@ -7437,10 +5737,7 @@ "description": "Name of the span iframe" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the span iframe" }, "url": { @@ -7448,40 +5745,25 @@ "description": "URL to embed the project viewer in an iframe" }, "post_message": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether to post messages to the iframe containing the span's data. This is useful when you want to render more data than fits in the URL." } }, - "required": [ - "id", - "project_id", - "name", - "url" - ] + "required": ["id", "project_id", "name", "url"] }, "SpanScope": { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "span" - ] + "enum": ["span"] } }, - "required": [ - "type" - ], + "required": ["type"], "description": "Process individual spans" }, "SpanType": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "enum": [ "llm", "score", @@ -7502,19 +5784,13 @@ "properties": { "stream": { "type": "string", - "enum": [ - "stderr", - "stdout" - ] + "enum": ["stderr", "stdout"] }, "message": { "type": "string" } }, - "required": [ - "stream", - "message" - ] + "required": ["stream", "message"] }, "SSEProgressEventData": { "type": "object", @@ -7573,16 +5849,8 @@ ] }, "StreamingMode": { - "type": [ - "string", - "null" - ], - "enum": [ - "auto", - "parallel", - "json", - "text" - ], + "type": ["string", "null"], + "enum": ["auto", "parallel", "json", "text"], "description": "The mode format of the returned value (defaults to 'auto')" }, "ToolFunctionDefinition": { @@ -7590,9 +5858,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "function": { "type": "object", @@ -7608,30 +5874,20 @@ "additionalProperties": {} }, "strict": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] } }, - "required": [ - "name" - ] + "required": ["name"] } }, - "required": [ - "type", - "function" - ] + "required": ["type", "function"] }, "TopicAutomationConfig": { "type": "object", "properties": { "event_type": { "type": "string", - "enum": [ - "topic" - ], + "enum": ["topic"], "description": "The type of automation." }, "sampling_rate": { @@ -7675,10 +5931,7 @@ "$ref": "#/components/schemas/TopicAutomationDataScope" }, "btql_filter": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Optional BTQL filter applied before topic automation." } }, @@ -7696,46 +5949,33 @@ "properties": { "type": { "type": "string", - "enum": [ - "project_logs" - ] + "enum": ["project_logs"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "project_experiments" - ] + "enum": ["project_experiments"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "experiment" - ] + "enum": ["experiment"] }, "experiment_id": { "type": "string" } }, - "required": [ - "type", - "experiment_id" - ] + "required": ["type", "experiment_id"] }, { "type": "null" @@ -7748,9 +5988,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "topic_map" - ] + "enum": ["topic_map"] }, "source_facet": { "type": "string", @@ -7780,11 +6018,7 @@ "description": "Maximum distance to nearest centroid. If exceeded, returns no_match." } }, - "required": [ - "type", - "source_facet", - "embedding_model" - ] + "required": ["type", "source_facet", "embedding_model"] }, "TopicMapFunctionAutomation": { "type": "object", @@ -7800,34 +6034,25 @@ ] }, "btql_filter": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Per-topic-map BTQL filter. For trace scope, a topic map runs when max(filter) over the trace is truthy. For span scope, it runs when the current span matches." } }, - "required": [ - "function" - ] + "required": ["function"] }, "TraceScope": { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "trace" - ] + "enum": ["trace"] }, "idle_seconds": { "type": "number", "description": "Consider trace complete after this many seconds of inactivity (default: 30)" } }, - "required": [ - "type" - ], + "required": ["type"], "description": "Process entire traces (all spans sharing the same root_span_id)" }, "TriggeredFunctionState": { @@ -7838,17 +6063,11 @@ "description": "The xact_id when this function was triggered" }, "completed_xact_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The xact_id when this function completed (matches triggered_xact_id if done)" }, "idempotency_key": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Deterministic key of the function definition + input version used to skip unchanged reruns" }, "attempts": { @@ -7864,37 +6083,27 @@ "properties": { "type": { "type": "string", - "enum": [ - "span" - ] + "enum": ["span"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "trace" - ] + "enum": ["trace"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "group" - ] + "enum": ["group"] }, "key": { "type": "string" @@ -7903,28 +6112,17 @@ "type": "string" } }, - "required": [ - "type", - "key", - "value" - ] + "required": ["type", "key", "value"] } ], "description": "The scope of data this function operates on" } }, - "required": [ - "triggered_xact_id", - "scope" - ] + "required": ["triggered_xact_id", "scope"] }, "UploadStatus": { "type": "string", - "enum": [ - "uploading", - "done", - "error" - ] + "enum": ["uploading", "done", "error"] }, "User": { "type": "object", @@ -7935,45 +6133,28 @@ "description": "Unique identifier for the user" }, "given_name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Given name of the user" }, "family_name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Family name of the user" }, "email": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The user's email" }, "avatar_url": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "URL of the user's Avatar image" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of user creation" } }, - "required": [ - "id" - ] + "required": ["id"] }, "View": { "type": "object", @@ -8026,10 +6207,7 @@ "description": "Name of the view" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of view creation" }, @@ -8040,35 +6218,20 @@ "$ref": "#/components/schemas/ViewOptions" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the view" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of role deletion, or null if the role is still active" } }, - "required": [ - "id", - "object_type", - "object_id", - "view_type", - "name" - ] + "required": ["id", "object_type", "object_id", "view_type", "name"] }, "ViewData": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "search": { "$ref": "#/components/schemas/ViewDataSearch" @@ -8078,37 +6241,22 @@ "description": "The view definition" }, "ViewDataSearch": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "filter": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {} }, "tag": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {} }, "match": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {} }, "sort": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {} } } @@ -8120,264 +6268,149 @@ "properties": { "viewType": { "type": "string", - "enum": [ - "monitor" - ] + "enum": ["monitor"] }, "options": { "type": "object", "properties": { "spanType": { - "type": [ - "string", - "null" - ], - "enum": [ - "range", - "frame" - ] + "type": ["string", "null"], + "enum": ["range", "frame"] }, "rangeValue": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "frameStart": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "frameEnd": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "tzUTC": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] }, "chartVisibility": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { "type": "boolean" } }, "projectId": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "type": { - "type": [ - "string", - "null" - ], - "enum": [ - "project", - "experiment" - ] + "type": ["string", "null"], + "enum": ["project", "experiment"] }, "groupBy": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] } } }, "freezeColumns": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] } }, - "required": [ - "viewType", - "options" - ], + "required": ["viewType", "options"], "title": "MonitorViewOptions" }, { "type": "object", "properties": { "columnVisibility": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { "type": "boolean" } }, "columnOrder": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" } }, "columnSizing": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { "type": "number" } }, "grouping": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "rowHeight": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "tallGroupRows": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] }, "layout": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "chartHeight": { - "type": [ - "number", - "null" - ] + "type": ["number", "null"] }, "excludedMeasures": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "none", - "score", - "metric", - "metadata" - ] + "enum": ["none", "score", "metric", "metadata"] }, "value": { "type": "string" } }, - "required": [ - "type", - "value" - ] + "required": ["type", "value"] } }, "yMetric": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "type": { "type": "string", - "enum": [ - "none", - "score", - "metric", - "metadata" - ] + "enum": ["none", "score", "metric", "metadata"] }, "value": { "type": "string" } }, - "required": [ - "type", - "value" - ] + "required": ["type", "value"] }, "xAxis": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "type": { "type": "string", - "enum": [ - "none", - "score", - "metric", - "metadata" - ] + "enum": ["none", "score", "metric", "metadata"] }, "value": { "type": "string" } }, - "required": [ - "type", - "value" - ] + "required": ["type", "value"] }, "symbolGrouping": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "type": { "type": "string", - "enum": [ - "none", - "score", - "metric", - "metadata" - ] + "enum": ["none", "score", "metric", "metadata"] }, "value": { "type": "string" } }, - "required": [ - "type", - "value" - ] + "required": ["type", "value"] }, "xAxisAggregation": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "One of 'avg', 'sum', 'min', 'max', 'median', 'all'" }, "chartAnnotations": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "object", "properties": { @@ -8388,10 +6421,7 @@ "type": "string" } }, - "required": [ - "id", - "text" - ] + "required": ["id", "text"] } }, "timeRangeFilter": { @@ -8409,10 +6439,7 @@ "type": "string" } }, - "required": [ - "from", - "to" - ] + "required": ["from", "to"] }, { "type": "null" @@ -8420,20 +6447,11 @@ ] }, "queryShape": { - "type": [ - "string", - "null" - ], - "enum": [ - "traces", - "spans" - ] + "type": ["string", "null"], + "enum": ["traces", "spans"] }, "freezeColumns": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] } }, "title": "TableViewOptions" diff --git a/imported_types.json b/imported_types.json index 6b25d2557..22016e4a3 100644 --- a/imported_types.json +++ b/imported_types.json @@ -25,18 +25,12 @@ "description": "The id of the object the ACL applies to" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Id of the user the ACL applies to. Exactly one of `user_id` and `group_id` will be provided" }, "group_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Id of the group the ACL applies to. Exactly one of `user_id` and `group_id` will be provided" }, @@ -46,10 +40,7 @@ "$ref": "#/components/schemas/Permission" }, { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Permission the ACL grants. Exactly one of `permission` and `role_id` will be provided" } ] @@ -65,10 +56,7 @@ ] }, "role_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Id of the role the ACL grants. Exactly one of `permission` and `role_id` will be provided" }, @@ -78,27 +66,16 @@ "description": "The organization the ACL's referred object belongs to" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of acl creation" } }, - "required": [ - "id", - "object_type", - "object_id", - "_object_org_id" - ], + "required": ["id", "object_type", "object_id", "_object_org_id"], "description": "An ACL grants a certain permission or role to a certain user or group on an object.\n\nACLs are inherited across the object hierarchy. So for example, if a user has read permissions on a project, they will also have read permissions on any experiment, dataset, etc. created within that project.\n\nTo restrict a grant to a particular sub-object, you may specify `restrict_object_type` in the ACL, as part of a direct permission grant or as part of a role." }, "AclObjectType": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "enum": [ "organization", "project", @@ -123,18 +100,12 @@ "description": "Unique identifier for the AI secret" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of AI secret creation" }, "updated_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of last AI secret update" }, @@ -148,30 +119,17 @@ "description": "Name of the AI secret" }, "type": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {} }, "preview_secret": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] } }, - "required": [ - "id", - "org_id", - "name" - ] + "required": ["id", "org_id", "name"] }, "AnyModelParams": { "type": "object", @@ -202,23 +160,17 @@ "anyOf": [ { "type": "string", - "enum": [ - "auto" - ], + "enum": ["auto"], "title": "auto" }, { "type": "string", - "enum": [ - "none" - ], + "enum": ["none"], "title": "none" }, { "type": "string", - "enum": [ - "required" - ], + "enum": ["required"], "title": "required" }, { @@ -226,9 +178,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "function": { "type": "object", @@ -237,15 +187,10 @@ "type": "string" } }, - "required": [ - "name" - ] + "required": ["name"] } }, - "required": [ - "type", - "function" - ], + "required": ["type", "function"], "title": "function" } ] @@ -254,16 +199,12 @@ "anyOf": [ { "type": "string", - "enum": [ - "auto" - ], + "enum": ["auto"], "title": "auto" }, { "type": "string", - "enum": [ - "none" - ], + "enum": ["none"], "title": "none" }, { @@ -273,9 +214,7 @@ "type": "string" } }, - "required": [ - "name" - ], + "required": ["name"], "title": "function" } ] @@ -291,20 +230,11 @@ }, "reasoning_effort": { "type": "string", - "enum": [ - "minimal", - "low", - "medium", - "high" - ] + "enum": ["minimal", "low", "medium", "high"] }, "verbosity": { "type": "string", - "enum": [ - "low", - "medium", - "high" - ] + "enum": ["low", "medium", "high"] }, "top_k": { "type": "number" @@ -332,9 +262,7 @@ "type": "boolean" } }, - "required": [ - "max_tokens" - ] + "required": ["max_tokens"] }, "ApiKey": { "type": "object", @@ -345,10 +273,7 @@ "description": "Unique identifier for the api key" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of api key creation" }, @@ -360,48 +285,29 @@ "type": "string" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Unique identifier for the user" }, "user_email": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The user's email" }, "user_given_name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Given name of the user" }, "user_family_name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Family name of the user" }, "org_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Unique identifier for the organization" } }, - "required": [ - "id", - "name", - "preview_name" - ] + "required": ["id", "name", "preview_name"] }, "AttachmentReference": { "oneOf": [ @@ -431,18 +337,14 @@ "description": "Describes the error encountered while uploading." } }, - "required": [ - "upload_status" - ] + "required": ["upload_status"] }, "BraintrustAttachmentReference": { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "braintrust_attachment" - ], + "enum": ["braintrust_attachment"], "description": "An identifier to help disambiguate parsing." }, "filename": { @@ -461,12 +363,7 @@ "description": "Key in the object store bucket for this attachment." } }, - "required": [ - "type", - "filename", - "content_type", - "key" - ] + "required": ["type", "filename", "content_type", "key"] }, "BraintrustModelParams": { "type": "object", @@ -489,15 +386,10 @@ }, "event": { "type": "string", - "enum": [ - "text_delta" - ] + "enum": ["text_delta"] } }, - "required": [ - "data", - "event" - ], + "required": ["data", "event"], "title": "text_delta" }, { @@ -511,15 +403,10 @@ }, "event": { "type": "string", - "enum": [ - "reasoning_delta" - ] + "enum": ["reasoning_delta"] } }, - "required": [ - "data", - "event" - ], + "required": ["data", "event"], "title": "reasoning_delta" }, { @@ -533,15 +420,10 @@ }, "event": { "type": "string", - "enum": [ - "json_delta" - ] + "enum": ["json_delta"] } }, - "required": [ - "data", - "event" - ], + "required": ["data", "event"], "title": "json_delta" }, { @@ -555,15 +437,10 @@ }, "event": { "type": "string", - "enum": [ - "progress" - ] + "enum": ["progress"] } }, - "required": [ - "data", - "event" - ], + "required": ["data", "event"], "title": "progress" }, { @@ -577,15 +454,10 @@ }, "event": { "type": "string", - "enum": [ - "error" - ] + "enum": ["error"] } }, - "required": [ - "data", - "event" - ], + "required": ["data", "event"], "title": "error" }, { @@ -599,15 +471,10 @@ }, "event": { "type": "string", - "enum": [ - "console" - ] + "enum": ["console"] } }, - "required": [ - "data", - "event" - ], + "required": ["data", "event"], "title": "console" }, { @@ -618,21 +485,14 @@ }, "event": { "type": "string", - "enum": [ - "start" - ] + "enum": ["start"] }, "data": { "type": "string", - "enum": [ - "" - ] + "enum": [""] } }, - "required": [ - "event", - "data" - ], + "required": ["event", "data"], "title": "start" }, { @@ -643,21 +503,14 @@ }, "event": { "type": "string", - "enum": [ - "done" - ] + "enum": ["done"] }, "data": { "type": "string", - "enum": [ - "" - ] + "enum": [""] } }, - "required": [ - "event", - "data" - ], + "required": ["event", "data"], "title": "done" } ] @@ -686,43 +539,30 @@ "anyOf": [ { "type": "string", - "enum": [ - "auto" - ], + "enum": ["auto"], "title": "auto" }, { "type": "string", - "enum": [ - "low" - ], + "enum": ["low"], "title": "low" }, { "type": "string", - "enum": [ - "high" - ], + "enum": ["high"], "title": "high" } ] } }, - "required": [ - "url" - ] + "required": ["url"] }, "type": { "type": "string", - "enum": [ - "image_url" - ] + "enum": ["image_url"] } }, - "required": [ - "image_url", - "type" - ], + "required": ["image_url", "type"], "title": "image_url" }, "ChatCompletionContentPartText": { @@ -734,29 +574,20 @@ }, "type": { "type": "string", - "enum": [ - "text" - ] + "enum": ["text"] }, "cache_control": { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "ephemeral" - ] + "enum": ["ephemeral"] } }, - "required": [ - "type" - ] + "required": ["type"] } }, - "required": [ - "type", - "text" - ] + "required": ["type", "text"] }, "ChatCompletionContentPartTextWithTitle": { "type": "object", @@ -767,29 +598,20 @@ }, "type": { "type": "string", - "enum": [ - "text" - ] + "enum": ["text"] }, "cache_control": { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "ephemeral" - ] + "enum": ["ephemeral"] } }, - "required": [ - "type" - ] + "required": ["type"] } }, - "required": [ - "type", - "text" - ], + "required": ["type", "text"], "title": "text" }, "ChatCompletionMessageParam": { @@ -815,18 +637,13 @@ }, "role": { "type": "string", - "enum": [ - "system" - ] + "enum": ["system"] }, "name": { "type": "string" } }, - "required": [ - "role", - "content" - ], + "required": ["role", "content"], "title": "system" }, { @@ -850,18 +667,13 @@ }, "role": { "type": "string", - "enum": [ - "user" - ] + "enum": ["user"] }, "name": { "type": "string" } }, - "required": [ - "role", - "content" - ], + "required": ["role", "content"], "title": "user" }, { @@ -869,9 +681,7 @@ "properties": { "role": { "type": "string", - "enum": [ - "assistant" - ] + "enum": ["assistant"] }, "content": { "anyOf": [ @@ -899,10 +709,7 @@ "type": "string" } }, - "required": [ - "arguments", - "name" - ] + "required": ["arguments", "name"] }, "name": { "type": "string" @@ -920,9 +727,7 @@ } } }, - "required": [ - "role" - ], + "required": ["role"], "title": "assistant" }, { @@ -946,46 +751,31 @@ }, "role": { "type": "string", - "enum": [ - "tool" - ] + "enum": ["tool"] }, "tool_call_id": { "type": "string", "default": "" } }, - "required": [ - "role", - "content", - "tool_call_id" - ], + "required": ["role", "content", "tool_call_id"], "title": "tool" }, { "type": "object", "properties": { "content": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "name": { "type": "string" }, "role": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] } }, - "required": [ - "content", - "name", - "role" - ], + "required": ["content", "name", "role"], "title": "function" }, { @@ -1009,18 +799,13 @@ }, "role": { "type": "string", - "enum": [ - "developer" - ] + "enum": ["developer"] }, "name": { "type": "string" } }, - "required": [ - "role", - "content" - ], + "required": ["role", "content"], "title": "developer" }, { @@ -1028,20 +813,13 @@ "properties": { "role": { "type": "string", - "enum": [ - "model" - ] + "enum": ["model"] }, "content": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] } }, - "required": [ - "role" - ], + "required": ["role"], "title": "fallback" } ] @@ -1074,23 +852,14 @@ "type": "string" } }, - "required": [ - "arguments", - "name" - ] + "required": ["arguments", "name"] }, "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] } }, - "required": [ - "id", - "function", - "type" - ] + "required": ["id", "function", "type"] }, "ChatCompletionOpenAIMessageParam": { "anyOf": [ @@ -1115,18 +884,13 @@ }, "role": { "type": "string", - "enum": [ - "system" - ] + "enum": ["system"] }, "name": { "type": "string" } }, - "required": [ - "role", - "content" - ], + "required": ["role", "content"], "title": "system" }, { @@ -1150,18 +914,13 @@ }, "role": { "type": "string", - "enum": [ - "user" - ] + "enum": ["user"] }, "name": { "type": "string" } }, - "required": [ - "role", - "content" - ], + "required": ["role", "content"], "title": "user" }, { @@ -1169,9 +928,7 @@ "properties": { "role": { "type": "string", - "enum": [ - "assistant" - ] + "enum": ["assistant"] }, "content": { "anyOf": [ @@ -1199,10 +956,7 @@ "type": "string" } }, - "required": [ - "arguments", - "name" - ] + "required": ["arguments", "name"] }, "name": { "type": "string" @@ -1220,9 +974,7 @@ } } }, - "required": [ - "role" - ], + "required": ["role"], "title": "assistant" }, { @@ -1246,46 +998,31 @@ }, "role": { "type": "string", - "enum": [ - "tool" - ] + "enum": ["tool"] }, "tool_call_id": { "type": "string", "default": "" } }, - "required": [ - "role", - "content", - "tool_call_id" - ], + "required": ["role", "content", "tool_call_id"], "title": "tool" }, { "type": "object", "properties": { "content": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "name": { "type": "string" }, "role": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] } }, - "required": [ - "content", - "name", - "role" - ], + "required": ["content", "name", "role"], "title": "function" }, { @@ -1309,18 +1046,13 @@ }, "role": { "type": "string", - "enum": [ - "developer" - ] + "enum": ["developer"] }, "name": { "type": "string" } }, - "required": [ - "role", - "content" - ], + "required": ["role", "content"], "title": "developer" } ] @@ -1342,21 +1074,14 @@ "additionalProperties": {} } }, - "required": [ - "name" - ] + "required": ["name"] }, "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] } }, - "required": [ - "function", - "type" - ] + "required": ["function", "type"] }, "CodeBundle": { "type": "object", @@ -1366,19 +1091,13 @@ "properties": { "runtime": { "type": "string", - "enum": [ - "node", - "python" - ] + "enum": ["node", "python"] }, "version": { "type": "string" } }, - "required": [ - "runtime", - "version" - ] + "required": ["runtime", "version"] }, "location": { "anyOf": [ @@ -1387,9 +1106,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "experiment" - ] + "enum": ["experiment"] }, "eval_name": { "type": "string" @@ -1401,43 +1118,30 @@ "properties": { "type": { "type": "string", - "enum": [ - "task" - ] + "enum": ["task"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "scorer" - ] + "enum": ["scorer"] }, "index": { "type": "integer", "minimum": 0 } }, - "required": [ - "type", - "index" - ], + "required": ["type", "index"], "title": "scorer" } ] } }, - "required": [ - "type", - "eval_name", - "position" - ], + "required": ["type", "eval_name", "position"], "title": "experiment" }, { @@ -1445,19 +1149,14 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "index": { "type": "integer", "minimum": 0 } }, - "required": [ - "type", - "index" - ], + "required": ["type", "index"], "title": "function" } ] @@ -1466,18 +1165,11 @@ "type": "string" }, "preview": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "A preview of the code" } }, - "required": [ - "runtime_context", - "location", - "bundle_id" - ] + "required": ["runtime_context", "location", "bundle_id"] }, "Dataset": { "type": "object", @@ -1497,50 +1189,31 @@ "description": "Name of the dataset. Within a project, dataset names are unique" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the dataset" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of dataset creation" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of dataset deletion, or null if the dataset is still active" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the dataset" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "User-controlled metadata about the dataset" } }, - "required": [ - "id", - "project_id", - "name" - ] + "required": ["id", "project_id", "name"] }, "DatasetEvent": { "type": "object", @@ -1559,10 +1232,7 @@ "description": "The timestamp the dataset event was created" }, "_pagination_key": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "A stable, time-ordered key that can be used to paginate over dataset events. This field is auto-generated by Braintrust and only exists in Brainstore." }, "project_id": { @@ -1582,16 +1252,10 @@ "description": "The output of your application, including post-processing (an arbitrary, JSON serializable object)" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "model": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The model used for this example" } }, @@ -1599,10 +1263,7 @@ "description": "A dictionary with additional data about the test example, model outputs, or just about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any JSON-serializable type, but its keys must be strings" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, @@ -1617,10 +1278,7 @@ "description": "A unique identifier for the trace this dataset event belongs to" }, "is_root": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether this span is a root span" }, "origin": { @@ -1647,11 +1305,7 @@ }, "object_type": { "type": "string", - "enum": [ - "organization", - "project", - "function" - ], + "enum": ["organization", "project", "function"], "description": "The type of the object the environment variable is scoped for" }, "object_id": { @@ -1664,28 +1318,17 @@ "description": "The name of the environment variable" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of environment variable creation" }, "used": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date the environment variable was last used" } }, - "required": [ - "id", - "object_type", - "object_id", - "name" - ] + "required": ["id", "object_type", "object_id", "name"] }, "Experiment": { "type": "object", @@ -1705,17 +1348,11 @@ "description": "Name of the experiment. Within a project, experiment names are unique" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the experiment" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of experiment creation" }, @@ -1723,41 +1360,26 @@ "$ref": "#/components/schemas/RepoInfo" }, "commit": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Commit, taken directly from `repo_info.commit`" }, "base_exp_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Id of default base experiment to compare against when viewing this experiment" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of experiment deletion, or null if the experiment is still active" }, "dataset_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifier of the linked dataset, or null if the experiment is not linked to a dataset" }, "dataset_version": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Version number of the linked dataset the experiment was run against. This can be used to reproduce the experiment after the dataset has been modified." }, "public": { @@ -1765,38 +1387,24 @@ "description": "Whether or not the experiment is public. Public experiments can be viewed by anybody inside or outside the organization" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the experiment" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "User-controlled metadata about the experiment" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "A list of tags for the experiment" } }, - "required": [ - "id", - "project_id", - "name", - "public" - ] + "required": ["id", "project_id", "name", "public"] }, "ExperimentEvent": { "type": "object", @@ -1815,10 +1423,7 @@ "description": "The timestamp the experiment event was created" }, "_pagination_key": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "A stable, time-ordered key that can be used to paginate over experiment events. This field is auto-generated by Braintrust and only exists in Brainstore." }, "project_id": { @@ -1844,31 +1449,19 @@ "description": "The error that occurred, if any." }, "scores": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "minimum": 0, "maximum": 1 }, "description": "A dictionary of numeric values (between 0 and 1) to log. The scores should give you a variety of signals that help you determine how accurate the outputs are compared to what you expect and diagnose failures. For example, a summarization app might have one score that tells you how accurate the summary is, and another that measures the word similarity between the generated and grouth truth summary. The word similarity score could help you determine whether the summarization was covering similar concepts or not. You can use these scores to help you sort, filter, and compare experiments" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "model": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The model used for this example" } }, @@ -1876,54 +1469,33 @@ "description": "A dictionary with additional data about the test example, model outputs, or just about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any JSON-serializable type, but its keys must be strings" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "A list of tags to log" }, "metrics": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "start": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "A unix timestamp recording when the section of code which produced the experiment event started" }, "end": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "A unix timestamp recording when the section of code which produced the experiment event finished" }, "prompt_tokens": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "The number of tokens in the prompt used to generate the experiment event (only set if this is an LLM span)" }, "completion_tokens": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "The number of tokens in the completion generated by the model (only set if this is an LLM span)" }, "tokens": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "The total number of tokens in the input and output of the experiment event." }, "caller_functionname": { @@ -1942,30 +1514,18 @@ "description": "Metrics are numerical measurements tracking the execution of the code that produced the experiment event. Use \"start\" and \"end\" to track the time span over which the experiment event was produced" }, "context": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "caller_functionname": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The function in code which created the experiment event" }, "caller_filename": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Name of the file in code where the experiment event was created" }, "caller_lineno": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "Line of code where the experiment event was created" } }, @@ -1977,10 +1537,7 @@ "description": "A unique identifier used to link different experiment events together as part of a full trace. See the [tracing guide](https://www.braintrust.dev/docs/instrument) for full details on tracing" }, "span_parents": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, @@ -1994,10 +1551,7 @@ "$ref": "#/components/schemas/SpanAttributes" }, "is_root": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether this span is a root span" }, "origin": { @@ -2021,18 +1575,13 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "id": { "type": "string" } }, - "required": [ - "type", - "id" - ], + "required": ["type", "id"], "title": "function" }, { @@ -2040,18 +1589,13 @@ "properties": { "type": { "type": "string", - "enum": [ - "global" - ] + "enum": ["global"] }, "name": { "type": "string" } }, - "required": [ - "type", - "name" - ], + "required": ["type", "name"], "title": "global" }, { @@ -2059,9 +1603,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "slug" - ] + "enum": ["slug"] }, "project_id": { "type": "string" @@ -2070,11 +1612,7 @@ "type": "string" } }, - "required": [ - "type", - "project_id", - "slug" - ] + "required": ["type", "project_id", "slug"] } ] }, @@ -2083,9 +1621,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "external_attachment" - ], + "enum": ["external_attachment"], "description": "An identifier to help disambiguate parsing." }, "filename": { @@ -2104,12 +1640,7 @@ "description": "Fully qualified URL to the object in the external object store." } }, - "required": [ - "type", - "filename", - "content_type", - "url" - ] + "required": ["type", "filename", "content_type", "url"] }, "Function": { "type": "object", @@ -2130,9 +1661,7 @@ }, "log_id": { "type": "string", - "enum": [ - "p" - ], + "enum": ["p"], "description": "A literal 'p' which identifies the object as a project prompt" }, "org_id": { @@ -2149,17 +1678,11 @@ "description": "Unique identifier for the prompt" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the prompt" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of prompt creation" }, @@ -2167,20 +1690,14 @@ "$ref": "#/components/schemas/PromptDataNullish" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "A list of tags for the prompt" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "User-controlled metadata about the prompt" }, @@ -2191,10 +1708,7 @@ "$ref": "#/components/schemas/FunctionData" }, "origin": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "object_type": { "allOf": [ @@ -2212,23 +1726,14 @@ "description": "Id of the object the function is originating from" }, "internal": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "The function exists for internal purposes and should not be displayed in the list of functions." } }, - "required": [ - "object_type", - "object_id" - ] + "required": ["object_type", "object_id"] }, "function_schema": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "parameters": {}, "returns": {} @@ -2254,14 +1759,10 @@ "properties": { "type": { "type": "string", - "enum": [ - "prompt" - ] + "enum": ["prompt"] } }, - "required": [ - "type" - ], + "required": ["type"], "title": "prompt" }, { @@ -2269,9 +1770,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "code" - ] + "enum": ["code"] }, "data": { "anyOf": [ @@ -2282,14 +1781,10 @@ "properties": { "type": { "type": "string", - "enum": [ - "bundle" - ] + "enum": ["bundle"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "$ref": "#/components/schemas/CodeBundle" @@ -2302,47 +1797,32 @@ "properties": { "type": { "type": "string", - "enum": [ - "inline" - ] + "enum": ["inline"] }, "runtime_context": { "type": "object", "properties": { "runtime": { "type": "string", - "enum": [ - "node", - "python" - ] + "enum": ["node", "python"] }, "version": { "type": "string" } }, - "required": [ - "runtime", - "version" - ] + "required": ["runtime", "version"] }, "code": { "type": "string" } }, - "required": [ - "type", - "runtime_context", - "code" - ], + "required": ["type", "runtime_context", "code"], "title": "inline" } ] } }, - "required": [ - "type", - "data" - ], + "required": ["type", "data"], "title": "code" }, { @@ -2353,9 +1833,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "remote_eval" - ] + "enum": ["remote_eval"] }, "endpoint": { "type": "string" @@ -2368,12 +1846,7 @@ "additionalProperties": {} } }, - "required": [ - "type", - "endpoint", - "eval_name", - "parameters" - ], + "required": ["type", "endpoint", "eval_name", "parameters"], "description": "A remote eval to run", "title": "remote_eval" }, @@ -2382,30 +1855,20 @@ "properties": { "type": { "type": "string", - "enum": [ - "global" - ] + "enum": ["global"] }, "name": { "type": "string" } }, - "required": [ - "type", - "name" - ], + "required": ["type", "name"], "title": "global" } ] }, "FunctionFormat": { "type": "string", - "enum": [ - "llm", - "code", - "global", - "graph" - ] + "enum": ["llm", "code", "global", "graph"] }, "FunctionId": { "anyOf": [ @@ -2421,9 +1884,7 @@ "description": "The version of the function" } }, - "required": [ - "function_id" - ], + "required": ["function_id"], "description": "Function id", "title": "function_id" }, @@ -2443,10 +1904,7 @@ "description": "The version of the function" } }, - "required": [ - "project_name", - "slug" - ], + "required": ["project_name", "slug"], "description": "Project name and slug", "title": "project_slug" }, @@ -2458,9 +1916,7 @@ "description": "The name of the global function. Currently, the global namespace includes the functions in autoevals" } }, - "required": [ - "global_function" - ], + "required": ["global_function"], "description": "Global function name", "title": "global_function" }, @@ -2480,10 +1936,7 @@ "description": "The version of the function" } }, - "required": [ - "prompt_session_id", - "prompt_session_function_id" - ], + "required": ["prompt_session_id", "prompt_session_function_id"], "description": "Prompt session id", "title": "prompt_session_id" }, @@ -2495,36 +1948,24 @@ "properties": { "runtime": { "type": "string", - "enum": [ - "node", - "python" - ] + "enum": ["node", "python"] }, "version": { "type": "string" } }, - "required": [ - "runtime", - "version" - ] + "required": ["runtime", "version"] }, "code": { "type": "string", "description": "The inline code to execute" }, "name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The name of the inline code function" } }, - "required": [ - "inline_context", - "code" - ], + "required": ["inline_context", "code"], "description": "Inline code function", "title": "inline_code" }, @@ -2542,16 +1983,11 @@ "$ref": "#/components/schemas/FunctionTypeEnum" }, "name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The name of the inline function" } }, - "required": [ - "inline_function" - ], + "required": ["inline_function"], "description": "Inline function definition", "title": "inline_function" }, @@ -2565,16 +2001,11 @@ "$ref": "#/components/schemas/FunctionTypeEnum" }, "name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The name of the inline prompt" } }, - "required": [ - "inline_prompt" - ], + "required": ["inline_prompt"], "description": "Inline prompt definition", "title": "inline_prompt" } @@ -2589,52 +2020,26 @@ }, "FunctionObjectType": { "type": "string", - "enum": [ - "prompt", - "tool", - "scorer", - "task" - ] + "enum": ["prompt", "tool", "scorer", "task"] }, "FunctionOutputType": { "type": "string", - "enum": [ - "completion", - "score", - "any" - ] + "enum": ["completion", "score", "any"] }, "FunctionTypeEnum": { "type": "string", - "enum": [ - "llm", - "scorer", - "task", - "tool" - ] + "enum": ["llm", "scorer", "task", "tool"] }, "FunctionTypeEnumNullish": { - "type": [ - "string", - "null" - ], - "enum": [ - "llm", - "scorer", - "task", - "tool" - ] + "type": ["string", "null"], + "enum": ["llm", "scorer", "task", "tool"] }, "GitMetadataSettings": { "type": "object", "properties": { "collect": { "type": "string", - "enum": [ - "all", - "none", - "some" - ] + "enum": ["all", "none", "some"] }, "fields": { "type": "array", @@ -2654,9 +2059,7 @@ } } }, - "required": [ - "collect" - ], + "required": ["collect"], "additionalProperties": false }, "GraphData": { @@ -2664,9 +2067,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "graph" - ] + "enum": ["graph"] }, "nodes": { "type": "object", @@ -2681,11 +2082,7 @@ } } }, - "required": [ - "type", - "nodes", - "edges" - ], + "required": ["type", "nodes", "edges"], "description": "This feature is preliminary and unsupported.", "title": "graph" }, @@ -2704,10 +2101,7 @@ "type": "string" } }, - "required": [ - "node", - "variable" - ] + "required": ["node", "variable"] }, "target": { "type": "object", @@ -2721,26 +2115,15 @@ "type": "string" } }, - "required": [ - "node", - "variable" - ] + "required": ["node", "variable"] }, "purpose": { "type": "string", - "enum": [ - "control", - "data", - "messages" - ], + "enum": ["control", "data", "messages"], "description": "The purpose of the edge" } }, - "required": [ - "source", - "target", - "purpose" - ] + "required": ["source", "target", "purpose"] }, "GraphNode": { "anyOf": [ @@ -2748,17 +2131,11 @@ "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -2769,42 +2146,28 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "function": { "$ref": "#/components/schemas/FunctionIdRef" } }, - "required": [ - "type", - "function" - ] + "required": ["type", "function"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -2815,39 +2178,26 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "input" - ], + "enum": ["input"], "description": "The input to the graph" } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -2858,39 +2208,26 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "output" - ], + "enum": ["output"], "description": "The output of the graph" } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -2901,41 +2238,28 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "literal" - ] + "enum": ["literal"] }, "value": { "description": "A literal value to be returned" } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -2946,43 +2270,29 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "btql" - ] + "enum": ["btql"] }, "expr": { "type": "string", "description": "A BTQL expression to be evaluated" } }, - "required": [ - "type", - "expr" - ] + "required": ["type", "expr"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -2993,45 +2303,29 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "gate" - ] + "enum": ["gate"] }, "condition": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "A BTQL expression to be evaluated" } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -3042,38 +2336,25 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "aggregator" - ] + "enum": ["aggregator"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The description of the node" }, "position": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "x": { "type": "number", @@ -3084,26 +2365,18 @@ "description": "The y position of the node" } }, - "required": [ - "x", - "y" - ], + "required": ["x", "y"], "description": "The position of the node" }, "type": { "type": "string", - "enum": [ - "prompt_template" - ] + "enum": ["prompt_template"] }, "prompt": { "$ref": "#/components/schemas/PromptBlockData" } }, - "required": [ - "type", - "prompt" - ] + "required": ["type", "prompt"] } ] }, @@ -3121,18 +2394,12 @@ "description": "Unique id for the organization that the group belongs under\n\nIt is forbidden to change the org after creating a group" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the group" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of group creation" }, @@ -3141,25 +2408,16 @@ "description": "Name of the group" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the group" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of group deletion, or null if the group is still active" }, "member_users": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string", "format": "uuid" @@ -3167,10 +2425,7 @@ "description": "Ids of users which belong to this group" }, "member_groups": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string", "format": "uuid" @@ -3178,20 +2433,12 @@ "description": "Ids of the groups this group inherits from\n\nAn inheriting group has all the users contained in its member groups, as well as all of their inherited users" } }, - "required": [ - "id", - "org_id", - "name" - ], + "required": ["id", "org_id", "name"], "description": "A group is a collection of users which can be assigned an ACL\n\nGroups can consist of individual users, as well as a set of groups they inherit from" }, "IfExists": { "type": "string", - "enum": [ - "error", - "ignore", - "replace" - ] + "enum": ["error", "ignore", "replace"] }, "InvokeFunction": { "allOf": [ @@ -3208,18 +2455,12 @@ "description": "The expected output of the function" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "Any relevant metadata. This will be logged and available as the `metadata` argument." }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, @@ -3236,20 +2477,14 @@ "$ref": "#/components/schemas/InvokeParent" }, "stream": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether to stream the response. If true, results will be returned in the Braintrust SSE format." }, "mode": { "$ref": "#/components/schemas/StreamingMode" }, "strict": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "If true, throw an error if one of the variables in the prompt is not present in the input" } } @@ -3264,21 +2499,14 @@ "properties": { "object_type": { "type": "string", - "enum": [ - "project_logs", - "experiment", - "playground_logs" - ] + "enum": ["project_logs", "experiment", "playground_logs"] }, "object_id": { "type": "string", "description": "The id of the container object you are logging to" }, "row_ids": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "id": { "type": "string", @@ -3293,26 +2521,16 @@ "description": "The root_span_id of the row" } }, - "required": [ - "id", - "span_id", - "root_span_id" - ], + "required": ["id", "span_id", "root_span_id"], "description": "Identifiers for the row to to log a subspan under" }, "propagated_event": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "Include these properties in every span created under this parent" } }, - "required": [ - "object_type", - "object_id" - ], + "required": ["object_type", "object_id"], "description": "Span parent properties", "title": "span_parent_struct" }, @@ -3369,23 +2587,17 @@ "anyOf": [ { "type": "string", - "enum": [ - "auto" - ], + "enum": ["auto"], "title": "auto" }, { "type": "string", - "enum": [ - "none" - ], + "enum": ["none"], "title": "none" }, { "type": "string", - "enum": [ - "required" - ], + "enum": ["required"], "title": "required" }, { @@ -3393,9 +2605,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "function": { "type": "object", @@ -3404,15 +2614,10 @@ "type": "string" } }, - "required": [ - "name" - ] + "required": ["name"] } }, - "required": [ - "type", - "function" - ], + "required": ["type", "function"], "title": "function" } ] @@ -3421,16 +2626,12 @@ "anyOf": [ { "type": "string", - "enum": [ - "auto" - ], + "enum": ["auto"], "title": "auto" }, { "type": "string", - "enum": [ - "none" - ], + "enum": ["none"], "title": "none" }, { @@ -3440,9 +2641,7 @@ "type": "string" } }, - "required": [ - "name" - ], + "required": ["name"], "title": "function" } ] @@ -3458,20 +2657,11 @@ }, "reasoning_effort": { "type": "string", - "enum": [ - "minimal", - "low", - "medium", - "high" - ] + "enum": ["minimal", "low", "medium", "high"] }, "verbosity": { "type": "string", - "enum": [ - "low", - "medium", - "high" - ] + "enum": ["low", "medium", "high"] } }, "additionalProperties": {}, @@ -3506,10 +2696,7 @@ "description": "This is a legacy parameter that should not be used." } }, - "required": [ - "max_tokens", - "temperature" - ], + "required": ["max_tokens", "temperature"], "additionalProperties": {}, "title": "AnthropicModelParams" }, @@ -3564,10 +2751,7 @@ ] }, "ObjectReference": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "object_type": { "type": "string", @@ -3591,32 +2775,19 @@ "description": "ID of the original event." }, "_xact_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Transaction ID of the original event." }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Created timestamp of the original event. Used to help sort in the UI" } }, - "required": [ - "object_type", - "object_id", - "id" - ], + "required": ["object_type", "object_id", "id"], "description": "Indicates the event was copied from another object." }, "OnlineScoreConfig": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "sampling_rate": { "type": "number", @@ -3632,41 +2803,26 @@ "description": "The list of scorers to use for online scoring" }, "btql_filter": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Filter logs using BTQL" }, "apply_to_root_span": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether to trigger online scoring on the root span of each trace" }, "apply_to_span_names": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "Trigger online scoring on any spans with a name in this list" }, "skip_logging": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether to skip adding scorer spans when computing scores" } }, - "required": [ - "sampling_rate", - "scorers" - ] + "required": ["sampling_rate", "scorers"] }, "Organization": { "type": "object", @@ -3681,42 +2837,24 @@ "description": "Name of the organization" }, "api_url": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "is_universal_api": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] }, "proxy_url": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "realtime_url": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of organization creation" } }, - "required": [ - "id", - "name" - ] + "required": ["id", "name"] }, "Permission": { "type": "string", @@ -3750,26 +2888,17 @@ "description": "Name of the project" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of project creation" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of project deletion, or null if the project is still active" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the project" }, @@ -3777,11 +2906,7 @@ "$ref": "#/components/schemas/ProjectSettings" } }, - "required": [ - "id", - "org_id", - "name" - ] + "required": ["id", "org_id", "name"] }, "ProjectAutomation": { "type": "object", @@ -3797,18 +2922,12 @@ "description": "Unique identifier for the project that the project automation belongs under" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the project automation" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of project automation creation" }, @@ -3817,10 +2936,7 @@ "description": "Name of the project automation" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the project automation" }, "config": { @@ -3830,9 +2946,7 @@ "properties": { "event_type": { "type": "string", - "enum": [ - "logs" - ], + "enum": ["logs"], "description": "The type of automation." }, "btql_filter": { @@ -3852,9 +2966,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "webhook" - ], + "enum": ["webhook"], "description": "The type of action to take" }, "url": { @@ -3862,10 +2974,7 @@ "description": "The webhook URL to send the request to" } }, - "required": [ - "type", - "url" - ] + "required": ["type", "url"] } ], "description": "The action to take when the automation rule is triggered" @@ -3883,9 +2992,7 @@ "properties": { "event_type": { "type": "string", - "enum": [ - "btql_export" - ], + "enum": ["btql_export"], "description": "The type of automation." }, "export_definition": { @@ -3895,47 +3002,34 @@ "properties": { "type": { "type": "string", - "enum": [ - "log_traces" - ] + "enum": ["log_traces"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "log_spans" - ] + "enum": ["log_spans"] } }, - "required": [ - "type" - ] + "required": ["type"] }, { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "btql_query" - ] + "enum": ["btql_query"] }, "btql_query": { "type": "string", "description": "The BTQL query to export" } }, - "required": [ - "type", - "btql_query" - ] + "required": ["type", "btql_query"] } ], "description": "The definition of what to export" @@ -3946,10 +3040,7 @@ }, "format": { "type": "string", - "enum": [ - "jsonl", - "parquet" - ], + "enum": ["jsonl", "parquet"], "description": "The format to export the results in" }, "interval_seconds": { @@ -3965,9 +3056,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "aws_iam" - ] + "enum": ["aws_iam"] }, "role_arn": { "type": "string", @@ -3978,19 +3067,12 @@ "description": "The automation-specific external id component (auto-generated by default)" } }, - "required": [ - "type", - "role_arn", - "external_id" - ] + "required": ["type", "role_arn", "external_id"] } ] }, "batch_size": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "The number of rows to export in each batch" } }, @@ -4008,9 +3090,7 @@ "properties": { "event_type": { "type": "string", - "enum": [ - "retention" - ], + "enum": ["retention"], "description": "The type of automation." }, "object_type": { @@ -4022,22 +3102,13 @@ "description": "The number of days to retain the object" } }, - "required": [ - "event_type", - "object_type", - "retention_days" - ] + "required": ["event_type", "object_type", "retention_days"] } ], "description": "The configuration for the automation rule" } }, - "required": [ - "id", - "project_id", - "name", - "config" - ] + "required": ["id", "project_id", "name", "config"] }, "ProjectLogsEvent": { "type": "object", @@ -4051,10 +3122,7 @@ "description": "The transaction id of an event is unique to the network operation that processed the event insertion. Transaction ids are monotonically increasing over time and can be used to retrieve a versioned snapshot of the project logs (see the `version` parameter)" }, "_pagination_key": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "A stable, time-ordered key that can be used to paginate over project logs events. This field is auto-generated by Braintrust and only exists in Brainstore." }, "created": { @@ -4074,9 +3142,7 @@ }, "log_id": { "type": "string", - "enum": [ - "g" - ], + "enum": ["g"], "description": "A literal 'g' which identifies the log as a project log" }, "input": { @@ -4092,31 +3158,19 @@ "description": "The error that occurred, if any." }, "scores": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "minimum": 0, "maximum": 1 }, "description": "A dictionary of numeric values (between 0 and 1) to log. The scores should give you a variety of signals that help you determine how accurate the outputs are compared to what you expect and diagnose failures. For example, a summarization app might have one score that tells you how accurate the summary is, and another that measures the word similarity between the generated and grouth truth summary. The word similarity score could help you determine whether the summarization was covering similar concepts or not. You can use these scores to help you sort, filter, and compare logs." }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "model": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The model used for this example" } }, @@ -4124,54 +3178,33 @@ "description": "A dictionary with additional data about the test example, model outputs, or just about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any JSON-serializable type, but its keys must be strings" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "A list of tags to log" }, "metrics": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "start": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "A unix timestamp recording when the section of code which produced the project logs event started" }, "end": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "A unix timestamp recording when the section of code which produced the project logs event finished" }, "prompt_tokens": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "The number of tokens in the prompt used to generate the project logs event (only set if this is an LLM span)" }, "completion_tokens": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "The number of tokens in the completion generated by the model (only set if this is an LLM span)" }, "tokens": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "The total number of tokens in the input and output of the project logs event." }, "caller_functionname": { @@ -4190,30 +3223,18 @@ "description": "Metrics are numerical measurements tracking the execution of the code that produced the project logs event. Use \"start\" and \"end\" to track the time span over which the project logs event was produced" }, "context": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "caller_functionname": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The function in code which created the project logs event" }, "caller_filename": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Name of the file in code where the project logs event was created" }, "caller_lineno": { - "type": [ - "integer", - "null" - ], + "type": ["integer", "null"], "description": "Line of code where the project logs event was created" } }, @@ -4225,10 +3246,7 @@ "description": "A unique identifier used to link different project logs events together as part of a full trace. See the [tracing guide](https://www.braintrust.dev/docs/instrument) for full details on tracing" }, "span_parents": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, @@ -4239,10 +3257,7 @@ "description": "A unique identifier for the trace this project logs event belongs to" }, "is_root": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether this span is a root span" }, "span_attributes": { @@ -4281,10 +3296,7 @@ "format": "uuid" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of project score creation" }, @@ -4293,10 +3305,7 @@ "description": "Name of the project score" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the project score" }, "score_type": { @@ -4309,20 +3318,11 @@ "$ref": "#/components/schemas/ProjectScoreConfig" }, "position": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "An optional LexoRank-based string that sets the sort position for the score in the UI" } }, - "required": [ - "id", - "project_id", - "user_id", - "name", - "score_type" - ], + "required": ["id", "project_id", "user_id", "name", "score_type"], "description": "A project score is a user-configured score, which can be manually-labeled through the UI" }, "ProjectScoreCategories": { @@ -4368,29 +3368,17 @@ "description": "Numerical value of the category. Must be between 0 and 1, inclusive" } }, - "required": [ - "name", - "value" - ], + "required": ["name", "value"], "description": "For categorical-type project scores, defines a single category" }, "ProjectScoreConfig": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "multi_select": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] }, "destination": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "online": { "$ref": "#/components/schemas/OnlineScoreConfig" @@ -4411,31 +3399,19 @@ "description": "The type of the configured score" }, "ProjectSettings": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "comparison_key": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The key used to join two experiments (defaults to `input`)" }, "baseline_experiment_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "The id of the experiment to use as the default baseline for comparisons" }, "spanFieldOrder": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "object", "properties": { @@ -4452,15 +3428,11 @@ "anyOf": [ { "type": "string", - "enum": [ - "full" - ] + "enum": ["full"] }, { "type": "string", - "enum": [ - "two_column" - ] + "enum": ["two_column"] }, { "type": "null" @@ -4468,19 +3440,12 @@ ] } }, - "required": [ - "object_type", - "column_id", - "position" - ] + "required": ["object_type", "column_id", "position"] }, "description": "The order of the fields to display in the trace view" }, "remote_eval_sources": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "object", "properties": { @@ -4491,16 +3456,10 @@ "type": "string" }, "description": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] } }, - "required": [ - "url", - "name" - ] + "required": ["url", "name"] }, "description": "The remote eval sources to use for the project" } @@ -4524,10 +3483,7 @@ "format": "uuid" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of project tag creation" }, @@ -4536,33 +3492,19 @@ "description": "Name of the project tag" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the project tag" }, "color": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Color of the tag for the UI" }, "position": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "An optional LexoRank-based string that sets the sort position for the tag in the UI" } }, - "required": [ - "id", - "project_id", - "user_id", - "name" - ], + "required": ["id", "project_id", "user_id", "name"], "description": "A project tag is a user-configured tag for tracking and filtering your experiments, logs, and other data" }, "Prompt": { @@ -4584,9 +3526,7 @@ }, "log_id": { "type": "string", - "enum": [ - "p" - ], + "enum": ["p"], "description": "A literal 'p' which identifies the object as a project prompt" }, "org_id": { @@ -4603,17 +3543,11 @@ "description": "Unique identifier for the prompt" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the prompt" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of prompt creation" }, @@ -4621,20 +3555,14 @@ "$ref": "#/components/schemas/PromptDataNullish" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, "description": "A list of tags for the prompt" }, "metadata": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {}, "description": "User-controlled metadata about the prompt" }, @@ -4659,18 +3587,13 @@ "properties": { "type": { "type": "string", - "enum": [ - "completion" - ] + "enum": ["completion"] }, "content": { "type": "string" } }, - "required": [ - "type", - "content" - ], + "required": ["type", "content"], "title": "completion" }, { @@ -4678,9 +3601,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "chat" - ] + "enum": ["chat"] }, "messages": { "type": "array", @@ -4692,10 +3613,7 @@ "type": "string" } }, - "required": [ - "type", - "messages" - ], + "required": ["type", "messages"], "title": "chat" } ] @@ -4707,18 +3625,13 @@ "properties": { "type": { "type": "string", - "enum": [ - "completion" - ] + "enum": ["completion"] }, "content": { "type": "string" } }, - "required": [ - "type", - "content" - ], + "required": ["type", "content"], "title": "completion" }, { @@ -4726,9 +3639,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "chat" - ] + "enum": ["chat"] }, "messages": { "type": "array", @@ -4740,10 +3651,7 @@ "type": "string" } }, - "required": [ - "type", - "messages" - ], + "required": ["type", "messages"], "title": "chat" }, { @@ -4764,19 +3672,13 @@ "$ref": "#/components/schemas/PromptParserNullish" }, "tool_functions": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "$ref": "#/components/schemas/SavedFunctionId" } }, "origin": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "prompt_id": { "type": "string" @@ -4792,10 +3694,7 @@ } }, "PromptDataNullish": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "prompt": { "$ref": "#/components/schemas/PromptBlockDataNullish" @@ -4807,19 +3706,13 @@ "$ref": "#/components/schemas/PromptParserNullish" }, "tool_functions": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "$ref": "#/components/schemas/SavedFunctionId" } }, "origin": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "prompt_id": { "type": "string" @@ -4850,10 +3743,7 @@ } }, "PromptOptionsNullish": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "model": { "type": "string" @@ -4867,16 +3757,11 @@ } }, "PromptParserNullish": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "type": { "type": "string", - "enum": [ - "llm_classifier" - ] + "enum": ["llm_classifier"] }, "use_cot": { "type": "boolean" @@ -4890,11 +3775,7 @@ } } }, - "required": [ - "type", - "use_cot", - "choice_scores" - ] + "required": ["type", "use_cot", "choice_scores"] }, "PromptSessionEvent": { "type": "object", @@ -4913,10 +3794,7 @@ "description": "The timestamp the prompt session event was created" }, "_pagination_key": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "A stable, time-ordered key that can be used to paginate over prompt session events. This field is auto-generated by Braintrust and only exists in Brainstore." }, "project_id": { @@ -4948,10 +3826,7 @@ "description": "Data about the completion" }, "tags": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" }, @@ -4967,72 +3842,42 @@ ] }, "RepoInfo": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "commit": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "SHA of most recent commit" }, "branch": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Name of the branch the most recent commit belongs to" }, "tag": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Name of the tag on the most recent commit" }, "dirty": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether or not the repo had uncommitted changes when snapshotted" }, "author_name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Name of the author of the most recent commit" }, "author_email": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Email of the author of the most recent commit" }, "commit_message": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Most recent commit message" }, "commit_time": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Time of the most recent commit" }, "git_diff": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "If the repo was dirty when run, this includes the diff between the current state of the repo and the most recent commit." } }, @@ -5045,14 +3890,10 @@ "properties": { "type": { "type": "string", - "enum": [ - "json_object" - ] + "enum": ["json_object"] } }, - "required": [ - "type" - ], + "required": ["type"], "title": "json_object" }, { @@ -5060,18 +3901,13 @@ "properties": { "type": { "type": "string", - "enum": [ - "json_schema" - ] + "enum": ["json_schema"] }, "json_schema": { "$ref": "#/components/schemas/ResponseFormatJsonSchema" } }, - "required": [ - "type", - "json_schema" - ], + "required": ["type", "json_schema"], "title": "json_schema" }, { @@ -5079,14 +3915,10 @@ "properties": { "type": { "type": "string", - "enum": [ - "text" - ] + "enum": ["text"] } }, - "required": [ - "type" - ], + "required": ["type"], "title": "text" }, { @@ -5117,23 +3949,14 @@ ] }, "strict": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] } }, - "required": [ - "name" - ] + "required": ["name"] }, "RetentionObjectType": { "type": "string", - "enum": [ - "project_logs", - "experiment", - "dataset" - ], + "enum": ["project_logs", "experiment", "dataset"], "description": "The object type that the retention policy applies to" }, "Role": { @@ -5145,26 +3968,17 @@ "description": "Unique identifier for the role" }, "org_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Unique id for the organization that the role belongs under\n\nA null org_id indicates a system role, which may be assigned to anybody and inherited by any other role, but cannot be edited.\n\nIt is forbidden to change the org after creating a role" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the role" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of role creation" }, @@ -5173,25 +3987,16 @@ "description": "Name of the role" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the role" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of role deletion, or null if the role is still active" }, "member_permissions": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "object", "properties": { @@ -5202,17 +4007,12 @@ "$ref": "#/components/schemas/AclObjectType" } }, - "required": [ - "permission" - ] + "required": ["permission"] }, "description": "(permission, restrict_object_type) tuples which belong to this role" }, "member_roles": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string", "format": "uuid" @@ -5220,10 +4020,7 @@ "description": "Ids of the roles this role inherits from\n\nAn inheriting role has all the permissions contained in its member roles, as well as all of their inherited permissions" } }, - "required": [ - "id", - "name" - ], + "required": ["id", "name"], "description": "A role is a collection of permissions which can be granted as part of an ACL\n\nRoles can consist of individual permissions, as well as a set of roles they inherit from" }, "RunEval": { @@ -5242,16 +4039,11 @@ "type": "string" }, "_internal_btql": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {} } }, - "required": [ - "dataset_id" - ], + "required": ["dataset_id"], "description": "Dataset id", "title": "dataset_id" }, @@ -5265,17 +4057,11 @@ "type": "string" }, "_internal_btql": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": {} } }, - "required": [ - "project_name", - "dataset_name" - ], + "required": ["project_name", "dataset_name"], "description": "Project and dataset name", "title": "project_dataset_name" }, @@ -5287,9 +4073,7 @@ "items": {} } }, - "required": [ - "data" - ], + "required": ["data"], "description": "Dataset rows", "title": "dataset_rows" } @@ -5337,46 +4121,28 @@ "description": "Whether to stream the results of the eval. If true, the request will return two events: one to indicate the experiment has started, and another upon completion. If false, the request will return the evaluation's summary upon completion." }, "trial_count": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "The number of times to run the evaluator per input. This is useful for evaluating applications that have non-deterministic behavior and gives you both a stronger aggregate measure and a sense of the variance in the results." }, "is_public": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether the experiment should be public. Defaults to false." }, "timeout": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "description": "The maximum duration, in milliseconds, to run the evaluation. Defaults to undefined, in which case there is no timeout." }, "max_concurrency": { - "type": [ - "number", - "null" - ], + "type": ["number", "null"], "default": 10, "description": "The maximum number of tasks/scorers that will be run concurrently. Defaults to 10. If null is provided, no max concurrency will be used." }, "base_experiment_name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "An optional experiment name to use as a base. If specified, the new experiment will be summarized and compared to this experiment." }, "base_experiment_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "An optional experiment id to use as a base. If specified, the new experiment will be summarized and compared to this experiment." }, "git_metadata_settings": { @@ -5385,10 +4151,7 @@ "$ref": "#/components/schemas/GitMetadataSettings" }, { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "description": "Optional settings for collecting git metadata. By default, will collect all git metadata fields allowed in org-level settings." } ] @@ -5404,17 +4167,11 @@ ] }, "strict": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "If true, throw an error if one of the variables in the prompt is not present in the input" }, "stop_token": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The token to stop the run" }, "extra_messages": { @@ -5429,12 +4186,7 @@ "description": "Optional tags that will be added to the experiment." } }, - "required": [ - "project_id", - "data", - "task", - "scores" - ] + "required": ["project_id", "data", "task", "scores"] }, "SavedFunctionId": { "anyOf": [ @@ -5443,18 +4195,13 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "id": { "type": "string" } }, - "required": [ - "type", - "id" - ], + "required": ["type", "id"], "title": "function" }, { @@ -5462,33 +4209,22 @@ "properties": { "type": { "type": "string", - "enum": [ - "global" - ] + "enum": ["global"] }, "name": { "type": "string" } }, - "required": [ - "type", - "name" - ], + "required": ["type", "name"], "title": "global" } ] }, "SpanAttributes": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Name of the span, for display purposes only" }, "type": { @@ -5512,26 +4248,17 @@ "description": "Unique identifier for the project that the span iframe belongs under" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the span iframe" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of span iframe creation" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of span iframe deletion, or null if the span iframe is still active" }, @@ -5540,10 +4267,7 @@ "description": "Name of the span iframe" }, "description": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Textual description of the span iframe" }, "url": { @@ -5551,33 +4275,15 @@ "description": "URL to embed the project viewer in an iframe" }, "post_message": { - "type": [ - "boolean", - "null" - ], + "type": ["boolean", "null"], "description": "Whether to post messages to the iframe containing the span's data. This is useful when you want to render more data than fits in the URL." } }, - "required": [ - "id", - "project_id", - "name", - "url" - ] + "required": ["id", "project_id", "name", "url"] }, "SpanType": { - "type": [ - "string", - "null" - ], - "enum": [ - "llm", - "score", - "function", - "eval", - "task", - "tool" - ], + "type": ["string", "null"], + "enum": ["llm", "score", "function", "eval", "task", "tool"], "description": "Type of the span, for display purposes only" }, "SSEConsoleEventData": { @@ -5585,19 +4291,13 @@ "properties": { "stream": { "type": "string", - "enum": [ - "stderr", - "stdout" - ] + "enum": ["stderr", "stdout"] }, "message": { "type": "string" } }, - "required": [ - "stream", - "message" - ] + "required": ["stream", "message"] }, "SSEProgressEventData": { "type": "object", @@ -5656,14 +4356,8 @@ ] }, "StreamingMode": { - "type": [ - "string", - "null" - ], - "enum": [ - "auto", - "parallel" - ], + "type": ["string", "null"], + "enum": ["auto", "parallel"], "description": "The mode format of the returned value (defaults to 'auto')" }, "ToolFunctionDefinition": { @@ -5671,9 +4365,7 @@ "properties": { "type": { "type": "string", - "enum": [ - "function" - ] + "enum": ["function"] }, "function": { "type": "object", @@ -5689,29 +4381,17 @@ "additionalProperties": {} }, "strict": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] } }, - "required": [ - "name" - ] + "required": ["name"] } }, - "required": [ - "type", - "function" - ] + "required": ["type", "function"] }, "UploadStatus": { "type": "string", - "enum": [ - "uploading", - "done", - "error" - ] + "enum": ["uploading", "done", "error"] }, "User": { "type": "object", @@ -5722,45 +4402,28 @@ "description": "Unique identifier for the user" }, "given_name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Given name of the user" }, "family_name": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "Family name of the user" }, "email": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "The user's email" }, "avatar_url": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "URL of the user's Avatar image" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of user creation" } }, - "required": [ - "id" - ] + "required": ["id"] }, "View": { "type": "object", @@ -5808,10 +4471,7 @@ "description": "Name of the view" }, "created": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of view creation" }, @@ -5822,35 +4482,20 @@ "$ref": "#/components/schemas/ViewOptions" }, "user_id": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "uuid", "description": "Identifies the user who created the view" }, "deleted_at": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "format": "date-time", "description": "Date of role deletion, or null if the role is still active" } }, - "required": [ - "id", - "object_type", - "object_id", - "view_type", - "name" - ] + "required": ["id", "object_type", "object_id", "view_type", "name"] }, "ViewData": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "search": { "$ref": "#/components/schemas/ViewDataSearch" @@ -5859,37 +4504,22 @@ "description": "The view definition" }, "ViewDataSearch": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "filter": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {} }, "tag": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {} }, "match": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {} }, "sort": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": {} } } @@ -5901,258 +4531,146 @@ "properties": { "viewType": { "type": "string", - "enum": [ - "monitor" - ] + "enum": ["monitor"] }, "options": { "type": "object", "properties": { "spanType": { - "type": [ - "string", - "null" - ], - "enum": [ - "range", - "frame" - ] + "type": ["string", "null"], + "enum": ["range", "frame"] }, "rangeValue": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "frameStart": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "frameEnd": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "tzUTC": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] }, "chartVisibility": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { "type": "boolean" } }, "projectId": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "type": { - "type": [ - "string", - "null" - ], - "enum": [ - "project", - "experiment" - ] + "type": ["string", "null"], + "enum": ["project", "experiment"] }, "groupBy": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] } } } }, - "required": [ - "viewType", - "options" - ], + "required": ["viewType", "options"], "title": "MonitorViewOptions" }, { "type": "object", "properties": { "columnVisibility": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { "type": "boolean" } }, "columnOrder": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "string" } }, "columnSizing": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "additionalProperties": { "type": "number" } }, "grouping": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "rowHeight": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "tallGroupRows": { - "type": [ - "boolean", - "null" - ] + "type": ["boolean", "null"] }, "layout": { - "type": [ - "string", - "null" - ] + "type": ["string", "null"] }, "chartHeight": { - "type": [ - "number", - "null" - ] + "type": ["number", "null"] }, "excludedMeasures": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "object", "properties": { "type": { "type": "string", - "enum": [ - "none", - "score", - "metric", - "metadata" - ] + "enum": ["none", "score", "metric", "metadata"] }, "value": { "type": "string" } }, - "required": [ - "type", - "value" - ] + "required": ["type", "value"] } }, "yMetric": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "type": { "type": "string", - "enum": [ - "none", - "score", - "metric", - "metadata" - ] + "enum": ["none", "score", "metric", "metadata"] }, "value": { "type": "string" } }, - "required": [ - "type", - "value" - ] + "required": ["type", "value"] }, "xAxis": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "type": { "type": "string", - "enum": [ - "none", - "score", - "metric", - "metadata" - ] + "enum": ["none", "score", "metric", "metadata"] }, "value": { "type": "string" } }, - "required": [ - "type", - "value" - ] + "required": ["type", "value"] }, "symbolGrouping": { - "type": [ - "object", - "null" - ], + "type": ["object", "null"], "properties": { "type": { "type": "string", - "enum": [ - "none", - "score", - "metric", - "metadata" - ] + "enum": ["none", "score", "metric", "metadata"] }, "value": { "type": "string" } }, - "required": [ - "type", - "value" - ] + "required": ["type", "value"] }, "xAxisAggregation": { - "type": [ - "string", - "null" - ], + "type": ["string", "null"], "description": "One of 'avg', 'sum', 'min', 'max', 'median', 'all'" }, "chartAnnotations": { - "type": [ - "array", - "null" - ], + "type": ["array", "null"], "items": { "type": "object", "properties": { @@ -6163,10 +4681,7 @@ "type": "string" } }, - "required": [ - "id", - "text" - ] + "required": ["id", "text"] } }, "timeRangeFilter": { @@ -6184,10 +4699,7 @@ "type": "string" } }, - "required": [ - "from", - "to" - ] + "required": ["from", "to"] }, { "type": "null" diff --git a/integrations/adk-py/.envrc b/integrations/adk-py/.envrc deleted file mode 100644 index 2c57cdac5..000000000 --- a/integrations/adk-py/.envrc +++ /dev/null @@ -1 +0,0 @@ -dotenv_if_exists diff --git a/integrations/adk-py/.python-version b/integrations/adk-py/.python-version deleted file mode 100644 index c8cfe3959..000000000 --- a/integrations/adk-py/.python-version +++ /dev/null @@ -1 +0,0 @@ -3.10 diff --git a/integrations/adk-py/README.md b/integrations/adk-py/README.md deleted file mode 100644 index 94323b615..000000000 --- a/integrations/adk-py/README.md +++ /dev/null @@ -1,140 +0,0 @@ -# braintrust-adk - -SDK for integrating [Braintrust](https://braintrust.dev) with [Google ADK (Agent Development Kit)](https://github.com/google/adk-python). This package provides automatic tracing and logging of ADK agent executions to Braintrust. - -## Installation - -```bash -pip install braintrust-adk -``` - -## Requirements - -- Python >= 3.9 -- Google ADK >= 1.14.1 - -## Quick Start - -The `braintrust-adk` integration automatically traces your ADK agents' execution, including: - -- Agent invocations and responses -- Tool calls and their results -- Parallel execution flows -- Multi-step agent reasoning - -### Basic Usage - -```python -from google.adk.agents import LlmAgent -from braintrust_adk import setup_adk - -# Initialize Braintrust tracing -setup_adk( - api_key="your-api-key", # Or set BRAINTRUST_API_KEY env var - project_name="my-adk-project" # Optional: defaults to "default-google-adk-py" -) - -# Create your ADK agent as normal -agent = LlmAgent( - tools=[get_weather, get_current_time], - model="gemini-2.0-flash-exp", - system_instruction="You are a helpful assistant that can check weather and time." -) - -# Use the agent - all interactions are automatically traced to Braintrust -response = agent.send_message("What's the weather like in New York?") -print(response.text) -``` - -### Advanced Configuration - -#### Using Project ID - -If you know your Braintrust project ID, you can use it directly: - -```python -setup_adk( - api_key="your-api-key", - project_id="your-project-id" # Use project ID instead of name -) -``` - -#### Custom Tools with Tracing - -Other braintrust functions like `traced` work seamlessly with this integration. - -```python -from braintrust import traced - -@traced -def get_weather(city: str) -> dict: - """Get weather for a city.""" - # Your implementation here - return {"status": "success", "temperature": 72, "city": city} - -@traced -def search_flights(origin: str, destination: str, date: str) -> dict: - """Search for flights.""" - # Your implementation here - return {"flights": [...]} - -# Create agent with multiple tools -agent = LlmAgent( - tools=[get_weather, search_flights], - model="gemini-2.0-flash-exp", - system_instruction="You are a travel assistant." -) - -# All tool calls are automatically traced -response = agent.send_message( - "I need to fly from NYC to LA tomorrow. What's the weather like in LA?" -) -``` - -### Manual Patching - -The `setup_adk` will automatically patch Google ADK Runner, Agent, and Flow classes to automatically trace all agent interactions. If you prefer to manually patch classes, you can use the `wrap_agent`, `wrap_runner`, and `wrap_flow` functions. Take a look at the [manual example](./examples/manual.py). - -Note that, as of writing, `adk web` does not support [custom Runners](https://github.com/google/adk-web/issues/72) and you will need to use `setup_adk` if you would like LLM traces. - -## Examples - -The `examples/` directory contains complete working examples: - -## Viewing Traces in Braintrust - -Once you've set up the integration, you can view your traces in the Braintrust dashboard: - -1. Navigate to your project in [Braintrust](https://braintrust.dev) -2. Click on "Logs" to see all agent executions -3. Click on any log entry to see the full trace including: - - Agent reasoning steps - - Tool calls and responses - - Token usage and latency metrics - - Any errors or warnings - -## Development - -To contribute to this integration: - -```bash -# Clone the repository -git clone https://github.com/braintrustdata/braintrust-sdk.git -cd sdk/integrations/adk-py - -uv sync - -# Run examples -cd examples - -# simple programmatic agent call -uv run manual.py - -# or use the adk web UI -uv run adk web --port 8888 -``` - -## Related Resources - -- [Braintrust Documentation](https://www.braintrust.dev/docs) -- [Google ADK Documentation](https://github.com/google/genai-agent-dev-kit) diff --git a/integrations/adk-py/examples/.envrc b/integrations/adk-py/examples/.envrc deleted file mode 100644 index 1abb058f6..000000000 --- a/integrations/adk-py/examples/.envrc +++ /dev/null @@ -1 +0,0 @@ -source_up diff --git a/integrations/adk-py/examples/Makefile b/integrations/adk-py/examples/Makefile deleted file mode 100644 index 6de2f5bf4..000000000 --- a/integrations/adk-py/examples/Makefile +++ /dev/null @@ -1,58 +0,0 @@ -# Variables -PORT ?= 8888 -UV := uv run - -# Phony targets -.PHONY: dev help clean install test lint format check - -# Default target -.DEFAULT_GOAL := help - -# Development server -dev: - $(UV) adk web --port $(PORT) - -# Install dependencies -install: - uv sync - -# Run tests -test: - $(UV) pytest - -# Lint code -lint: - $(UV) ruff check . - -# Format code -format: - $(UV) ruff format . - -# Type check -check: - $(UV) mypy . - -# Clean up temporary files -clean: - find . -type f -name "*.pyc" -delete - find . -type d -name "__pycache__" -delete - find . -type d -name "*.egg-info" -exec rm -rf {} + - -# Show help -help: - @echo "Available targets:" - @echo " dev - Start development server (default port: $(PORT))" - @echo " install - Install dependencies with uv" - @echo " test - Run tests" - @echo " lint - Run linter" - @echo " format - Format code" - @echo " check - Run type checker" - @echo " clean - Clean up temporary files" - @echo " help - Show this help message" - @echo "" - @echo "Variables:" - @echo " PORT - Port for development server (default: $(PORT))" - @echo "" - @echo "Usage examples:" - @echo " make dev" - @echo " make dev PORT=3000" diff --git a/integrations/adk-py/examples/README.md b/integrations/adk-py/examples/README.md deleted file mode 100644 index 2bb691026..000000000 --- a/integrations/adk-py/examples/README.md +++ /dev/null @@ -1,62 +0,0 @@ -# Braintrust ADK Examples - -This directory contains examples demonstrating how to use the `braintrust-adk` library for logging Google ADK traces to Braintrust. - -## Running the Examples - -The easiest way to run the examples is using the development server: - -```bash -cd examples -make dev -``` - -This starts the ADK web interface on port 8888 where you can interact with the example agents. - -You can also specify a different port: - -```bash -make dev PORT=3000 -``` - -## Examples - -### `multi_tool_agent/` - -Demonstrates how to build multi-tool agents with the ADK and automatic tracing integration. - -### `parallel/` - -Shows how tracing works with concurrent Google ADK operations and proper trace correlation across async/threaded code. - -### `mcp_tracing/` - -Demonstrates automatic tracing of MCP (Model Context Protocol) tool invocations. This example shows how `setup_adk()` automatically captures MCP tool calls, including tool name, parameters, results, and duration. - -**Requirements:** Python 3.10+ (MCP requirement), Node.js with npx - -**Run directly:** - -```bash -cd mcp_tracing -export BRAINTRUST_API_KEY=your_key -export GOOGLE_API_KEY=your_key -uv run python agent.py -``` - -## Setup - -Install dependencies: - -```bash -make install -``` - -## Environment Variables - -Set these to enable different tracing backends: - -- `BRAINTRUST_API_KEY` - Enable Braintrust tracing -- `OTEL_DEBUG=true` - Enable console tracing (good for testing) -- `GOOGLE_CLOUD_PROJECT` - Enable Google Cloud Trace -- `OTEL_EXPORTER_OTLP_ENDPOINT` - Enable OTLP tracing diff --git a/integrations/adk-py/examples/__init__.py b/integrations/adk-py/examples/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/integrations/adk-py/examples/manual.py b/integrations/adk-py/examples/manual.py deleted file mode 100644 index dece73303..000000000 --- a/integrations/adk-py/examples/manual.py +++ /dev/null @@ -1,80 +0,0 @@ -""" -An example showing how to use the `wrap_agent`, `wrap_flow`, and `wrap_runner` functions to manually patch the Google ADK classes. - -In most cases you should consider using `setup_adk`, but this may be helpful in specific cases. -""" - -import asyncio - -from google.adk import Agent -from google.adk.runners import Runner -from google.adk.sessions import InMemorySessionService -from google.genai import types - -from braintrust.logger import init_logger -from braintrust_adk import wrap_agent, wrap_flow, wrap_runner - -init_logger(project="googleadk") - - -@wrap_agent -class CustomAgent(Agent): - @property - def _llm_flow(self): - return wrap_flow(super()._llm_flow) - - -@wrap_runner -class CustomRunner(Runner): - pass - - -async def main(text: str = "hi"): - # Tool with complex nested JSON output to test serialization - def say_hello(): - return {"greeting": "Hello ๐Ÿ‘‹"} - - def get_user_info(name: str): - """Get detailed user information - tests complex JSON serialization""" - return { - "user": { - "name": name, - "profile": { - "age": 30, - "location": {"city": "San Francisco", "country": "USA"}, - "preferences": ["coding", "reading", "hiking"], - }, - "metadata": { - "created_at": "2024-01-01T00:00:00Z", - "last_login": "2024-12-15T10:30:00Z", - "settings": {"theme": "dark", "notifications": True}, - }, - }, - "status": "active", - } - - agent = CustomAgent( - name="hello_agent", - model="gemini-2.0-flash", - instruction="Use the appropriate tool based on the user's request. For greetings, use say_hello. For user info requests, use get_user_info.", - tools=[say_hello, get_user_info], - ) - - APP_NAME = "hello_app" - USER_ID = "demo-user" - SESSION_ID = "demo-session" - - session_service = InMemorySessionService() - await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID) - - runner = CustomRunner(agent=agent, app_name=APP_NAME, session_service=session_service) - - user_msg = types.Content(role="user", parts=[types.Part(text=text)]) - async for event in runner.run_async(user_id=USER_ID, session_id=SESSION_ID, new_message=user_msg): - if event.is_final_response(): - text = event.content.parts[0].text if event.content and event.content.parts else "No response" - print(f"Test 1 - Greeting: {text[:100] if text else 'No response'}...") - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/integrations/adk-py/examples/manual_eval.py b/integrations/adk-py/examples/manual_eval.py deleted file mode 100644 index 35e4e6f71..000000000 --- a/integrations/adk-py/examples/manual_eval.py +++ /dev/null @@ -1,25 +0,0 @@ -""" -An example showing how Braintrust eval experiment traces will continue to work with adk traces. -""" - -import asyncio -from typing import Any - -from braintrust.framework import EvalAsync -from manual import main as manual - - -async def main(): - async def task(input: Any): - setup_adk() - return await manual(input) - - await EvalAsync( - name="hello", - data=[{"input": "Hello, World!"}], - task=task, - scores=[], - ) - - -asyncio.run(main()) diff --git a/integrations/adk-py/examples/mcp_tracing/__init__.py b/integrations/adk-py/examples/mcp_tracing/__init__.py deleted file mode 100644 index 6be4fcca2..000000000 --- a/integrations/adk-py/examples/mcp_tracing/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from . import agent # noqa diff --git a/integrations/adk-py/examples/mcp_tracing/agent.py b/integrations/adk-py/examples/mcp_tracing/agent.py deleted file mode 100644 index 40ca88696..000000000 --- a/integrations/adk-py/examples/mcp_tracing/agent.py +++ /dev/null @@ -1,98 +0,0 @@ -""" -Example showing automatic tracing of MCP tool invocations. - -This demonstrates how braintrust-adk automatically traces: -1. Agent execution -2. LLM calls (tool selection and response generation) -3. MCP tool invocations - tool name, parameters, results, and duration - -Requirements: - Python 3.10+ (MCP requirement) - export GOOGLE_API_KEY=your_key - -Usage: - python agent.py -""" - -import asyncio - -from google.adk.agents import LlmAgent -from google.adk.runners import Runner -from google.adk.sessions import InMemorySessionService -from google.adk.tools.mcp_tool.mcp_session_manager import StdioConnectionParams -from google.adk.tools.mcp_tool.mcp_toolset import MCPToolset -from google.genai import types -from mcp import StdioServerParameters - -from braintrust_adk import setup_adk - -# Setup Braintrust integration - automatically patches agents, runners, flows, and MCP tools -setup_adk(project_name="adk-mcp-example") - - -async def main(): - """Run the MCP tool tracing example.""" - - # Create agent with MCP filesystem tools - agent = LlmAgent( - name="filesystem_assistant", - model="gemini-2.0-flash-exp", - instruction="You are a helpful assistant that can read and list files. Be concise in your responses.", - tools=[ - MCPToolset( - connection_params=StdioConnectionParams( - server_params=StdioServerParameters( - command="npx", - args=[ - "-y", - "@modelcontextprotocol/server-filesystem", - "/tmp", # Limit to /tmp for safety - ], - ), - ), - tool_filter=["list_directory", "read_file"], - ) - ], - ) - - # Setup session - APP_NAME = "filesystem_app" - USER_ID = "demo-user" - SESSION_ID = "demo-session" - - session_service = InMemorySessionService() - await session_service.create_session( - app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID - ) - - runner = Runner(agent=agent, app_name=APP_NAME, session_service=session_service) - - # Make a request that will use MCP tools - print("\n=== Asking agent to list files in /tmp ===\n") - user_msg = types.Content( - role="user", - parts=[types.Part(text="What files are in /tmp? Just list a few.")], - ) - - async for event in runner.run_async( - user_id=USER_ID, session_id=SESSION_ID, new_message=user_msg - ): - if event.is_final_response(): - text = ( - event.content.parts[0].text - if event.content and event.content.parts - else "No response" - ) - print(f"Agent response: {text}\n") - - print("=== Trace complete ===") - print("View traces at: https://www.braintrust.dev/app") - print("Project: adk-mcp-example") - print("\nLook for 'mcp_tool [list_directory]' span showing:") - print(" - Tool name and arguments") - print(" - Tool execution results") - print(" - Duration") - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/integrations/adk-py/examples/multi_tool_agent/__init__.py b/integrations/adk-py/examples/multi_tool_agent/__init__.py deleted file mode 100644 index 6be4fcca2..000000000 --- a/integrations/adk-py/examples/multi_tool_agent/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from . import agent # noqa diff --git a/integrations/adk-py/examples/multi_tool_agent/agent.py b/integrations/adk-py/examples/multi_tool_agent/agent.py deleted file mode 100644 index d8e666c20..000000000 --- a/integrations/adk-py/examples/multi_tool_agent/agent.py +++ /dev/null @@ -1,73 +0,0 @@ -import datetime -from typing import Dict -from zoneinfo import ZoneInfo - -from google.adk.agents import LlmAgent - -from braintrust import traced -from braintrust_adk import setup_adk - - -@traced -def isNewYork(city: str) -> bool: - return city.lower() == "new york" - - -@traced -def get_weather(city: str) -> Dict[str, str]: - """Retrieves the current weather report for a specified city. - - Args: - city (str): The name of the city for which to retrieve the weather report. - - Returns: - dict: status and result or error msg. - """ - if isNewYork(city): - return { - "status": "success", - "report": ( - "The weather in New York is sunny with a temperature of 25 degrees Celsius (41 degrees Fahrenheit)." - ), - } - else: - return { - "status": "error", - "error_message": f"Weather information for '{city}' is not available.", - } - - -@traced -def get_current_time(city: str) -> Dict[str, str]: - """Returns the current time in a specified city. - - Args: - city (str): The name of the city for which to retrieve the current time. - - Returns: - dict: status and result or error msg. - """ - - if isNewYork(city): - tz_identifier = "America/New_York" - else: - return { - "status": "error", - "error_message": (f"Sorry, I don't have timezone information for {city}."), - } - - tz = ZoneInfo(tz_identifier) - now = datetime.datetime.now(tz) - report = f"The current time in {city} is {now.strftime('%Y-%m-%d %H:%M:%S %Z%z')}" - return {"status": "success", "report": report} - - -setup_adk(project_name="adk-multi-tool") - -root_agent = LlmAgent( - name="weather_time_agent", - model="gemini-2.0-flash", - description=("Agent to answer questions about the time and weather in a city."), - instruction=("You are a helpful agent who can answer user questions about the time and weather in a city."), - tools=[get_weather, get_current_time], -) diff --git a/integrations/adk-py/examples/parallel/__init__.py b/integrations/adk-py/examples/parallel/__init__.py deleted file mode 100644 index e6998db97..000000000 --- a/integrations/adk-py/examples/parallel/__init__.py +++ /dev/null @@ -1,5 +0,0 @@ -from braintrust_adk import setup_adk - -from . import agent # noqa - -setup_adk(project_name="adk-parallel") diff --git a/integrations/adk-py/examples/parallel/agent.py b/integrations/adk-py/examples/parallel/agent.py deleted file mode 100644 index 1c3a55c69..000000000 --- a/integrations/adk-py/examples/parallel/agent.py +++ /dev/null @@ -1,130 +0,0 @@ -# Researcher 1: Renewable Energy -from google.adk.agents import LlmAgent, ParallelAgent, SequentialAgent - -from braintrust import traced - -GEMINI_MODEL = "gemini-2.5-flash" - - -@traced -def google_search(*args, **kwargs): - return "google search results ..." - - -researcher_agent_1 = LlmAgent( - name="RenewableEnergyResearcher", - model=GEMINI_MODEL, - instruction="""You are an AI Research Assistant specializing in energy. - Research the latest advancements in 'renewable energy sources'. - Use the Google Search tool provided. - Summarize your key findings concisely (1-2 sentences). - Output *only* the summary. - """, - description="Researches renewable energy sources.", - tools=[google_search], - # Store result in state for the merger agent - output_key="renewable_energy_result", -) - -# Researcher 2: Electric Vehicles -researcher_agent_2 = LlmAgent( - name="EVResearcher", - model=GEMINI_MODEL, - instruction="""You are an AI Research Assistant specializing in transportation. -Research the latest developments in 'electric vehicle technology'. -Use the Google Search tool provided. -Summarize your key findings concisely (1-2 sentences). -Output *only* the summary. -""", - description="Researches electric vehicle technology.", - tools=[google_search], - # Store result in state for the merger agent - output_key="ev_technology_result", -) - -# Researcher 3: Carbon Capture -researcher_agent_3 = LlmAgent( - name="CarbonCaptureResearcher", - model=GEMINI_MODEL, - instruction="""You are an AI Research Assistant specializing in climate solutions. -Research the current state of 'carbon capture methods'. -Use the Google Search tool provided. -Summarize your key findings concisely (1-2 sentences). -Output *only* the summary. -""", - description="Researches carbon capture methods.", - tools=[google_search], - # Store result in state for the merger agent - output_key="carbon_capture_result", -) - -# --- 2. Create the ParallelAgent (Runs researchers concurrently) --- -# This agent orchestrates the concurrent execution of the researchers. -# It finishes once all researchers have completed and stored their results in state. -parallel_research_agent = ParallelAgent( - name="ParallelWebResearchAgent", - sub_agents=[researcher_agent_1, researcher_agent_2, researcher_agent_3], - description="Runs multiple research agents in parallel to gather information.", -) - -# --- 3. Define the Merger Agent (Runs *after* the parallel agents) --- -# This agent takes the results stored in the session state by the parallel agents -# and synthesizes them into a single, structured response with attributions. -merger_agent = LlmAgent( - name="SynthesisAgent", - model=GEMINI_MODEL, # Or potentially a more powerful model if needed for synthesis - instruction="""You are an AI Assistant responsible for combining research findings into a structured report. - -Your primary task is to synthesize the following research summaries, clearly attributing findings to their source areas. Structure your response using headings for each topic. Ensure the report is coherent and integrates the key points smoothly. - -**Crucially: Your entire response MUST be grounded *exclusively* on the information provided in the 'Input Summaries' below. Do NOT add any external knowledge, facts, or details not present in these specific summaries.** - -**Input Summaries:** - -* **Renewable Energy:** - {renewable_energy_result} - -* **Electric Vehicles:** - {ev_technology_result} - -* **Carbon Capture:** - {carbon_capture_result} - -**Output Format:** - -## Summary of Recent Sustainable Technology Advancements - -### Renewable Energy Findings -(Based on RenewableEnergyResearcher's findings) -[Synthesize and elaborate *only* on the renewable energy input summary provided above.] - -### Electric Vehicle Findings -(Based on EVResearcher's findings) -[Synthesize and elaborate *only* on the EV input summary provided above.] - -### Carbon Capture Findings -(Based on CarbonCaptureResearcher's findings) -[Synthesize and elaborate *only* on the carbon capture input summary provided above.] - -### Overall Conclusion -[Provide a brief (1-2 sentence) concluding statement that connects *only* the findings presented above.] - -Output *only* the structured report following this format. Do not include introductory or concluding phrases outside this structure, and strictly adhere to using only the provided input summary content. -""", - description="Combines research findings from parallel agents into a structured, cited report, strictly grounded on provided inputs.", - # No tools needed for merging - # No output_key needed here, as its direct response is the final output of the sequence -) - - -# --- 4. Create the SequentialAgent (Orchestrates the overall flow) --- -# This is the main agent that will be run. It first executes the ParallelAgent -# to populate the state, and then executes the MergerAgent to produce the final output. -sequential_pipeline_agent = SequentialAgent( - name="ResearchAndSynthesisPipeline", - # Run parallel research first, then merge - sub_agents=[parallel_research_agent, merger_agent], - description="Coordinates parallel research and synthesizes the results.", -) - -root_agent = sequential_pipeline_agent diff --git a/integrations/adk-py/examples/pyproject.toml b/integrations/adk-py/examples/pyproject.toml deleted file mode 100644 index 1f00c0a09..000000000 --- a/integrations/adk-py/examples/pyproject.toml +++ /dev/null @@ -1,25 +0,0 @@ -[project] -name = "braintrust-adk-examples" -version = "0.1.0" -description = "Examples demonstrating braintrust-adk usage patterns for automatic Google ADK tracing" -readme = "README.md" -requires-python = ">=3.10" -dependencies = [ - "braintrust-adk", - "google-adk>=1.14.1", - "python-multipart>=0.0.20", -] - -[tool.uv.sources] -braintrust-adk = { workspace = true } - -[tool.ruff] -line-length = 120 - -[tool.ruff.lint] -select = [ - "I", # isort -] - -[tool.ruff.lint.isort] -known-first-party = ["braintrust_adk", "braintrust"] diff --git a/integrations/adk-py/pyproject.toml b/integrations/adk-py/pyproject.toml deleted file mode 100644 index 1f3b58577..000000000 --- a/integrations/adk-py/pyproject.toml +++ /dev/null @@ -1,74 +0,0 @@ -[project] -name = "braintrust-adk" -version = "0.3.1" -description = "Braintrust Google ADK integration" -readme = "README.md" -requires-python = ">=3.10" -dependencies = [ - "braintrust>=0.4.1", - "google-adk>=1.14.1", - "wrapt>=1.17.3", -] -license = { text = "Apache-2.0" } -authors = [{ name = "Braintrust", email = "info@braintrust.dev" }] -keywords = ["braintrust", "google-adk", "adk", "agents", "ai", "llm", "tracing"] -classifiers = [ - "Development Status :: 4 - Beta", - "License :: OSI Approved :: Apache Software License", - "Programming Language :: Python :: 3.10", - "Programming Language :: Python :: 3.11", -] - -[project.urls] -Homepage = "https://www.braintrust.dev" -Repository = "https://github.com/braintrustdata/braintrust-sdk" - - -[build-system] -requires = ["setuptools>=61.0"] -build-backend = "setuptools.build_meta" - -[tool.setuptools] -package-dir = { "" = "src" } - -[tool.setuptools.packages.find] -where = ["src"] - -[tool.uv.workspace] -members = [ - "examples", - ".", -] - -[tool.uv.sources] -braintrust = { path = "../../py", editable = true } - -[dependency-groups] -dev = [ - "pytest>=8.3.5", - "pytest-asyncio>=1.1.0", - "pytest-vcr>=1.0.2", - "pyyaml>=6.0", - "ruff>=0.12.9", -] - -[tool.isort] -profile = "black" -line_length = 120 - -[tool.ruff] -line-length = 120 - -[tool.ruff.lint] -select = [ - "I", # isort -] - -[tool.ruff.lint.isort] -known-first-party = ["braintrust", "braintrust_adk"] - -[tool.pytest.ini_options] -testpaths = ["tests"] -python_files = ["test_*.py"] -addopts = "-v" -asyncio_default_fixture_loop_scope = "function" diff --git a/integrations/adk-py/src/braintrust_adk/__init__.py b/integrations/adk-py/src/braintrust_adk/__init__.py deleted file mode 100644 index 3590ce010..000000000 --- a/integrations/adk-py/src/braintrust_adk/__init__.py +++ /dev/null @@ -1,653 +0,0 @@ -import inspect -import logging -import time -from collections.abc import Iterable -from contextlib import aclosing -from typing import Any, cast - -from wrapt import wrap_function_wrapper - -from braintrust.bt_json import bt_safe_deep_copy -from braintrust.logger import NOOP_SPAN, Attachment, current_span, init_logger, start_span -from braintrust.span_types import SpanTypeAttribute - -logger = logging.getLogger(__name__) - -__all__ = ["setup_braintrust", "setup_adk", "wrap_agent", "wrap_runner", "wrap_flow", "wrap_mcp_tool"] - - -def setup_braintrust(*args, **kwargs): - logger.warning("setup_braintrust is deprecated, use setup_adk instead") - return setup_adk(*args, **kwargs) - - -def setup_adk( - api_key: str | None = None, - project_id: str | None = None, - project_name: str | None = None, - SpanProcessor: type | None = None, -) -> bool: - """ - Setup Braintrust integration with Google ADK. Will automatically patch Google ADK agents, runners, flows, and MCP tools for automatic tracing. - - If you prefer manual patching take a look at `wrap_agent`, `wrap_runner`, `wrap_flow`, and `wrap_mcp_tool`. - - Args: - api_key (Optional[str]): Braintrust API key. - project_id (Optional[str]): Braintrust project ID. - project_name (Optional[str]): Braintrust project name. - SpanProcessor (Optional[type]): Deprecated parameter. - - Returns: - bool: True if setup was successful, False otherwise. - """ - if SpanProcessor is not None: - logging.warning("SpanProcessor parameter is deprecated and will be ignored") - - span = current_span() - if span == NOOP_SPAN: - init_logger(project=project_name, api_key=api_key, project_id=project_id) - - try: - from google.adk import agents, runners - from google.adk.flows.llm_flows import base_llm_flow - - agents.BaseAgent = wrap_agent(agents.BaseAgent) - runners.Runner = wrap_runner(runners.Runner) - base_llm_flow.BaseLlmFlow = wrap_flow(base_llm_flow.BaseLlmFlow) - - # Try to patch McpTool if available (MCP is optional) - try: - from google.adk.tools.mcp_tool import mcp_tool - - mcp_tool.McpTool = wrap_mcp_tool(mcp_tool.McpTool) - logger.debug("McpTool patching successful") - except ImportError: - # MCP is optional - gracefully skip if not installed - logger.debug("McpTool not available, skipping MCP instrumentation") - except Exception as e: - # Log but don't fail - MCP patching is optional - logger.warning(f"Failed to patch McpTool: {e}") - - return True - except ImportError as e: - logger.error(f"Failed to import Google ADK agents: {e}") - logger.error("Google ADK is not installed. Please install it with: pip install google-adk") - return False - - -def wrap_agent(Agent: Any) -> Any: - if _is_patched(Agent): - return Agent - - async def agent_run_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - parent_context = args[0] if len(args) > 0 else kwargs.get("parent_context") - - async def _trace(): - with start_span( - name=f"agent_run [{instance.name}]", - type=SpanTypeAttribute.TASK, - metadata=bt_safe_deep_copy({"parent_context": parent_context, **_omit(kwargs, ["parent_context"])}), - ) as agent_span: - last_event = None - async with aclosing(wrapped(*args, **kwargs)) as agen: - async for event in agen: - if event.is_final_response(): - last_event = event - yield event - if last_event: - agent_span.log(output=last_event) - - async with aclosing(_trace()) as agen: - async for event in agen: - yield event - - wrap_function_wrapper(Agent, "run_async", agent_run_wrapper) - Agent._braintrust_patched = True - return Agent - - -def wrap_flow(Flow: Any): - if _is_patched(Flow): - return Flow - - async def trace_flow(wrapped: Any, instance: Any, args: Any, kwargs: Any): - invocation_context = args[0] if len(args) > 0 else kwargs.get("invocation_context") - - async def _trace(): - with start_span( - name=f"call_llm", - type=SpanTypeAttribute.TASK, - metadata=bt_safe_deep_copy( - { - "invocation_context": invocation_context, - **_omit(kwargs, ["invocation_context"]), - } - ), - ) as llm_span: - last_event = None - async with aclosing(wrapped(*args, **kwargs)) as agen: - async for event in agen: - last_event = event - yield event - if last_event: - llm_span.log(output=last_event) - - async with aclosing(_trace()) as agen: - async for event in agen: - yield event - - wrap_function_wrapper(Flow, "run_async", trace_flow) - - async def trace_run_sync_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - invocation_context = args[0] if len(args) > 0 else kwargs.get("invocation_context") - llm_request = args[1] if len(args) > 1 else kwargs.get("llm_request") - model_response_event = args[2] if len(args) > 2 else kwargs.get("model_response_event") - - async def _trace(): - # Extract and serialize contents BEFORE converting to dict - # This is critical because bt_safe_deep_copy converts bytes to string representations - serialized_contents = None - if llm_request and hasattr(llm_request, "contents"): - contents = llm_request.contents - if contents: - serialized_contents = ( - [_serialize_content(c) for c in contents] - if isinstance(contents, list) - else _serialize_content(contents) - ) - - # Now convert the whole request to dict - serialized_request = bt_safe_deep_copy(llm_request) - - # Replace contents with our serialized version that has Attachments - if serialized_contents is not None and isinstance(serialized_request, dict): - serialized_request["contents"] = serialized_contents - - # Handle config specifically to serialize Pydantic schema classes - if isinstance(serialized_request, dict) and "config" in serialized_request: - serialized_request["config"] = _serialize_config(serialized_request["config"]) - - # Extract model name from request or instance - model_name = _extract_model_name(None, llm_request, instance) - - # Create span BEFORE execution so child spans (like mcp_tool) have proper parent - # Start with generic name - we'll update it after we see the response - with start_span( - name="llm_call", - type=SpanTypeAttribute.LLM, - input=serialized_request, - metadata=bt_safe_deep_copy( - { - "invocation_context": invocation_context, - "model_response_event": model_response_event, - "flow_class": instance.__class__.__name__, - "model": model_name, - **_omit(kwargs, ["invocation_context", "model_response_event", "flow_class", "llm_call_type"]), - } - ), - ) as llm_span: - # Execute the LLM call and yield events while span is active - last_event = None - event_with_content = None - start_time = time.time() - first_token_time = None - - async with aclosing(wrapped(*args, **kwargs)) as agen: - async for event in agen: - # Record time to first token - if first_token_time is None: - first_token_time = time.time() - - last_event = event - if hasattr(event, "content") and event.content is not None: - event_with_content = event - yield event - - # After execution, update span with correct call type and output - if last_event: - # We need to check if we should merge content from an earlier event - # Convert to dict to inspect/modify, but let span.log() handle final serialization - output_dict = bt_safe_deep_copy(last_event) - if event_with_content and isinstance(output_dict, dict): - if "content" not in output_dict or output_dict.get("content") is None: - content = ( - bt_safe_deep_copy(event_with_content.content) - if hasattr(event_with_content, "content") - else None - ) - if content: - output_dict["content"] = content - - # Extract metrics from response - metrics = _extract_metrics(last_event) - - # Add time to first token if we captured it - if first_token_time is not None: - if metrics is None: - metrics = {} - metrics["time_to_first_token"] = first_token_time - start_time - - # Determine the actual call type based on the response - call_type = _determine_llm_call_type(llm_request, last_event) - - # Update span name with the specific call type now that we know it - llm_span.set_attributes( - name=f"llm_call [{call_type}]", - span_attributes={"llm_call_type": call_type}, - ) - - # Log output and metrics (span.log will handle serialization) - llm_span.log(output=output_dict, metrics=metrics) - - async with aclosing(_trace()) as agen: - async for event in agen: - yield event - - wrap_function_wrapper(Flow, "_call_llm_async", trace_run_sync_wrapper) - Flow._braintrust_patched = True - return Flow - - -def wrap_runner(Runner: Any): - if _is_patched(Runner): - return Runner - - def trace_run_sync_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - user_id = kwargs.get("user_id") - session_id = kwargs.get("session_id") - new_message = kwargs.get("new_message") - - # Serialize new_message before any dict conversion to handle binary data - serialized_message = _serialize_content(new_message) if new_message else None - - def _trace(): - with start_span( - name=f"invocation [{instance.app_name}]", - type=SpanTypeAttribute.TASK, - input={"new_message": serialized_message}, - metadata=bt_safe_deep_copy( - { - "user_id": user_id, - "session_id": session_id, - **_omit(kwargs, ["user_id", "session_id", "new_message"]), - } - ), - ) as runner_span: - last_event = None - for event in wrapped(*args, **kwargs): - if event.is_final_response(): - last_event = event - yield event - if last_event: - runner_span.log(output=last_event) - - yield from _trace() - - wrap_function_wrapper(Runner, "run", trace_run_sync_wrapper) - - async def trace_run_async_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - user_id = kwargs.get("user_id") - session_id = kwargs.get("session_id") - new_message = kwargs.get("new_message") - state_delta = kwargs.get("state_delta") - - # Serialize new_message before any dict conversion to handle binary data - serialized_message = _serialize_content(new_message) if new_message else None - - async def _trace(): - with start_span( - name=f"invocation [{instance.app_name}]", - type=SpanTypeAttribute.TASK, - input={"new_message": serialized_message}, - metadata=bt_safe_deep_copy( - { - "user_id": user_id, - "session_id": session_id, - "state_delta": state_delta, - **_omit(kwargs, ["user_id", "session_id", "new_message", "state_delta"]), - } - ), - ) as runner_span: - last_event = None - async with aclosing(wrapped(*args, **kwargs)) as agen: - async for event in agen: - if event.is_final_response(): - last_event = event - yield event - if last_event: - runner_span.log(output=last_event) - - async with aclosing(_trace()) as agen: - async for event in agen: - yield event - - wrap_function_wrapper(Runner, "run_async", trace_run_async_wrapper) - Runner._braintrust_patched = True - return Runner - - -def wrap_mcp_tool(McpTool: Any) -> Any: - """ - Wrap McpTool to trace MCP tool invocations. - - Creates Braintrust spans for each MCP tool call, capturing: - - Tool name - - Input arguments - - Output results - - Execution time - - Errors if they occur - - Args: - McpTool: The McpTool class to wrap - - Returns: - The wrapped McpTool class - """ - if _is_patched(McpTool): - return McpTool - - async def tool_run_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - # Extract tool information - tool_name = instance.name - tool_args = kwargs.get("args", {}) - - with start_span( - name=f"mcp_tool [{tool_name}]", - type=SpanTypeAttribute.TOOL, - input={"tool_name": tool_name, "arguments": tool_args}, - metadata=_omit(kwargs, ["args"]), - ) as tool_span: - try: - result = await wrapped(*args, **kwargs) - tool_span.log(output=result) - return result - except Exception as e: - # Log error to span but re-raise for ADK to handle - tool_span.log(error=str(e)) - raise - - wrap_function_wrapper(McpTool, "run_async", tool_run_wrapper) - McpTool._braintrust_patched = True - return McpTool - - -def _determine_llm_call_type(llm_request: Any, model_response: Any = None) -> str: - """ - Determine the type of LLM call based on the request and response content. - - Returns: - - "tool_selection" if the LLM selected a tool to call in its response - - "response_generation" if the LLM is generating a response after tool execution - - "direct_response" if there are no tools involved or tools available but not used - """ - try: - # Convert to dict if it's a model object - request_dict = cast(dict[str, Any], bt_safe_deep_copy(llm_request)) - - # Check if there are tools in the config - has_tools = bool(request_dict.get("config", {}).get("tools")) - - # Check the conversation history for function responses - contents = request_dict.get("contents", []) - has_function_response = False - - for content in contents: - if isinstance(content, dict): - parts = content.get("parts", []) - for part in parts: - if isinstance(part, dict): - if "function_response" in part and part["function_response"] is not None: - has_function_response = True - - # Check if the response contains function calls - response_has_function_call = False - if model_response: - # Check if it's an Event object with get_function_calls method (ADK Event) - if hasattr(model_response, "get_function_calls"): - try: - function_calls = model_response.get_function_calls() - if function_calls and len(function_calls) > 0: - response_has_function_call = True - except Exception: - pass - - # Fallback: Check the response dict structure - if not response_has_function_call: - response_dict = bt_safe_deep_copy(model_response) - if isinstance(response_dict, dict): - # Try multiple possible response structures - # 1. Standard: response.content.parts - content = response_dict.get("content", {}) - if isinstance(content, dict): - parts = content.get("parts", []) - if isinstance(parts, list): - for part in parts: - if isinstance(part, dict): - if ("function_call" in part and part["function_call"] is not None) or ( - "functionCall" in part and part["functionCall"] is not None - ): - response_has_function_call = True - break - - # 2. Alternative: response has parts directly (for some event types) - if not response_has_function_call and "parts" in response_dict: - parts = response_dict.get("parts", []) - if isinstance(parts, list): - for part in parts: - if isinstance(part, dict): - if ("function_call" in part and part["function_call"] is not None) or ( - "functionCall" in part and part["functionCall"] is not None - ): - response_has_function_call = True - break - - # Determine the call type - if has_function_response: - return "response_generation" - elif response_has_function_call: - return "tool_selection" - else: - return "direct_response" - - except Exception: - return "unknown" - - -def _is_patched(obj: Any): - return getattr(obj, "_braintrust_patched", False) - - -def _serialize_content(content: Any) -> Any: - """Serialize Google ADK Content/Part objects, converting binary data to Attachments.""" - if content is None: - return None - - # Handle Content objects with parts - if hasattr(content, "parts") and content.parts: - serialized_parts = [] - for part in content.parts: - serialized_parts.append(_serialize_part(part)) - - result = {"parts": serialized_parts} - if hasattr(content, "role"): - result["role"] = content.role - return result - - # Handle single Part - return _serialize_part(content) - - -def _serialize_part(part: Any) -> Any: - """Serialize a single Part object, handling binary data.""" - if part is None: - return None - - # If it's already a dict, return as-is - if isinstance(part, dict): - return part - - # Handle Part objects with inline_data (binary data like images) - if hasattr(part, "inline_data") and part.inline_data: - inline_data = part.inline_data - if hasattr(inline_data, "data") and hasattr(inline_data, "mime_type"): - data = inline_data.data - mime_type = inline_data.mime_type - - # Convert bytes to Attachment - if isinstance(data, bytes): - extension = mime_type.split("/")[1] if "/" in mime_type else "bin" - filename = f"file.{extension}" - attachment = Attachment(data=data, filename=filename, content_type=mime_type) - - # Return in image_url format - SDK will replace with AttachmentReference - return {"image_url": {"url": attachment}} - - # Handle Part objects with file_data (file references) - if hasattr(part, "file_data") and part.file_data: - file_data = part.file_data - result = {"file_data": {}} - if hasattr(file_data, "file_uri"): - result["file_data"]["file_uri"] = file_data.file_uri - if hasattr(file_data, "mime_type"): - result["file_data"]["mime_type"] = file_data.mime_type - return result - - # Handle text parts - if hasattr(part, "text") and part.text is not None: - result = {"text": part.text} - if hasattr(part, "thought") and part.thought: - result["thought"] = part.thought - return result - - # Try standard serialization methods - return bt_safe_deep_copy(part) - - -def _serialize_pydantic_schema(schema_class: Any) -> dict[str, Any]: - """ - Serialize a Pydantic model class to its full JSON schema. - - Returns the complete schema including descriptions, constraints, and nested definitions - so engineers can see exactly what structured output schema was used. - """ - try: - from pydantic import BaseModel - - if inspect.isclass(schema_class) and issubclass(schema_class, BaseModel): - # Return the full JSON schema - includes all field info, descriptions, constraints, etc. - return schema_class.model_json_schema() - except (ImportError, AttributeError, TypeError): - pass - # If not a Pydantic model, return class name - return {"__class__": schema_class.__name__ if inspect.isclass(schema_class) else str(type(schema_class).__name__)} - - -def _serialize_config(config: Any) -> dict[str, Any] | Any: - """ - Serialize a config object, specifically handling schema fields that may contain Pydantic classes. - - Google ADK uses these fields for schemas: - - response_schema, response_json_schema (in GenerateContentConfig for LLM requests) - - input_schema, output_schema (in agent config) - """ - if config is None: - return None - if not config: - return config - - # Extract schema fields BEFORE calling bt_safe_deep_copy (which converts Pydantic classes to dicts) - schema_fields = ["response_schema", "response_json_schema", "input_schema", "output_schema"] - serialized_schemas: dict[str, Any] = {} - - for field in schema_fields: - schema_value = None - - # Try to get the field value - if hasattr(config, field): - schema_value = getattr(config, field) - elif isinstance(config, dict) and field in config: - schema_value = config[field] - - # If it's a Pydantic class, serialize it - if schema_value is not None and inspect.isclass(schema_value): - try: - from pydantic import BaseModel - - if issubclass(schema_value, BaseModel): - serialized_schemas[field] = _serialize_pydantic_schema(schema_value) - except (TypeError, ImportError): - pass - - # Serialize the config - config_dict = bt_safe_deep_copy(config) - if not isinstance(config_dict, dict): - return config_dict # type: ignore - - # Replace schema fields with serialized versions - config_dict.update(serialized_schemas) - - return config_dict - - -def _omit(obj: Any, keys: Iterable[str]): - return {k: v for k, v in obj.items() if k not in keys} - - -def _extract_metrics(response: Any) -> dict[str, float] | None: - """Extract token usage metrics from Google GenAI response.""" - if not response: - return None - - usage_metadata = getattr(response, "usage_metadata", None) - if not usage_metadata: - return None - - metrics: dict[str, float] = {} - - # Core token counts - if hasattr(usage_metadata, "prompt_token_count") and usage_metadata.prompt_token_count is not None: - metrics["prompt_tokens"] = float(usage_metadata.prompt_token_count) - - if hasattr(usage_metadata, "candidates_token_count") and usage_metadata.candidates_token_count is not None: - metrics["completion_tokens"] = float(usage_metadata.candidates_token_count) - - if hasattr(usage_metadata, "total_token_count") and usage_metadata.total_token_count is not None: - metrics["tokens"] = float(usage_metadata.total_token_count) - - # Cached token metrics - if hasattr(usage_metadata, "cached_content_token_count") and usage_metadata.cached_content_token_count is not None: - metrics["prompt_cached_tokens"] = float(usage_metadata.cached_content_token_count) - - # Reasoning token metrics (thoughts_token_count) - if hasattr(usage_metadata, "thoughts_token_count") and usage_metadata.thoughts_token_count is not None: - metrics["completion_reasoning_tokens"] = float(usage_metadata.thoughts_token_count) - - return metrics if metrics else None - - -def _extract_model_name(response: Any, llm_request: Any, instance: Any) -> str | None: - """Extract model name from Google GenAI response, request, or flow instance.""" - # Try to get from response first - if response: - model_version = getattr(response, "model_version", None) - if model_version: - return model_version - - # Try to get from llm_request - if llm_request: - if hasattr(llm_request, "model") and llm_request.model: - return str(llm_request.model) - - # Try to get from instance (flow's llm) - if instance: - if hasattr(instance, "llm"): - llm = instance.llm - if hasattr(llm, "model") and llm.model: - return str(llm.model) - - # Try to get model from instance directly - if hasattr(instance, "model") and instance.model: - return str(instance.model) - - return None diff --git a/integrations/adk-py/src/tests/__init__.py b/integrations/adk-py/src/tests/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/integrations/adk-py/src/tests/cassettes/test_adk_binary_data_attachment_conversion.yaml b/integrations/adk-py/src/tests/cassettes/test_adk_binary_data_attachment_conversion.yaml deleted file mode 100644 index e21c287d2..000000000 --- a/integrations/adk-py/src/tests/cassettes/test_adk_binary_data_attachment_conversion.yaml +++ /dev/null @@ -1,65 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"inlineData": {"data": "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", - "mimeType": "image/png"}}, {"text": "What color is this image?"}], "role": "user"}], - "systemInstruction": {"parts": [{"text": "You are a helpful assistant that can - analyze images.\n\nYou are an agent. Your internal name is \"vision_agent\"."}], - "role": "user"}, "generationConfig": {"maxOutputTokens": 150}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '2611784' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.31.0 gl-python/3.9.21 google-adk/1.14.1 gl-python/3.9.21 - x-goog-api-client: - - google-genai-sdk/1.31.0 gl-python/3.9.21 google-adk/1.14.1 gl-python/3.9.21 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61Sy27CMBC85yssnwlKYijQW1VohQoqaiOE+jiYZkmsOnZkGyhF/HudhICL1Ftz - sOzd2Znd2ew9hPAHFQlLqAGNr9GrjSC0r84yJ4UBYWyiCdlgQZU5Y+tv79wtxMBXWYTjDBDLaWpP - jQoFicyZoMLwHVryNSArjbYZM9BCW2YypDOagEZyhVIFuyqtZQ7lCwRiAhlLuKUb0O03gR3Nw+n+ - 3jp3qiSHso1cJsAb+KEB4BUTTGdPQLUUJew5fpzhU5Zu0olMCyWX5bB+0O4S0gs6JOp3ydWg3yNd - r1GuNPFa20GnYKg1k54sw5YhL0wsP0HcynVlZkiisNZx3P+FiIJj3khD+UVxpyl2qPXQCjPu7sVZ - mTWAcmZ21U5Gixg7JhmXnISXLv3BMp7e3I/+pAmjQdAQec5WLsf9p66jCzHv2H+9+DkozeoNp2D/ - P+ZH7cBfcaqzihEr0IUUGsZJiel99+/oy9wnyWKmU/8hnKjxMMXewfsBtfuPvS8DAAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Fri, 31 Oct 2025 23:02:08 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=1730 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/adk-py/src/tests/cassettes/test_adk_braintrust_integration.yaml b/integrations/adk-py/src/tests/cassettes/test_adk_braintrust_integration.yaml deleted file mode 100644 index d8b3b3335..000000000 --- a/integrations/adk-py/src/tests/cassettes/test_adk_braintrust_integration.yaml +++ /dev/null @@ -1,137 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "What''s the weather in San Francisco?"}], - "role": "user"}], "systemInstruction": {"parts": [{"text": "You are a helpful - weather assistant. Use the get_weather tool to answer questions about weather.\n\nYou - are an agent. Your internal name is \"weather_agent\"."}], "role": "user"}, - "tools": [{"functionDeclarations": [{"description": "Get the weather for a location.", - "name": "get_weather", "parameters": {"properties": {"location": {"type": "STRING"}}, - "required": ["location"], "type": "OBJECT"}}]}], "generationConfig": {}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '561' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.31.0 gl-python/3.9.21 google-adk/1.14.1 gl-python/3.9.21 - x-goog-api-client: - - google-genai-sdk/1.31.0 gl-python/3.9.21 google-adk/1.14.1 gl-python/3.9.21 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61SXU+DMBR9768gfR4LMofG100TP4hTyWJijLnChTWWFttuy1z23y1fG0x9ExJS - 7jk9596ebonj0BhEwhIwqOmF82IrjrOtviUmhUFhLNCWbLEAZQ7c+tl21paSLkVsmBQT4Ly3ucEF - 5GjrNEPztkYwC1R0cEwClelfNluEyxhK+VLiCYRzpUDETMeSHnF35K+/w/r1YEyV5FVfuUyQt2K7 - lkBTJphePCLoxju6n+37prDK7mRWKPletu2eDwPf98bBaeD59h2fjND1AtKaV7Z0qSHDEA3YAGA/ - LLUieWEi+YFiIpdVAOOz2qiTVw8PGthIA7yPjAY/VPXUejLejbGTsB0fODObcsbo8jnqZGP1e021 - Z0Q6R3nc4j+ZBX0v0iRThzVHpZsbkWFuc3L9oeemHPSiEqQKdSGFxuuk5Ez9NITwFqfhav1p9EzG - XzebB4+SHfkGVtQS/hUDAAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Thu, 18 Sep 2025 20:09:51 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=530 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -- request: - body: '{"contents": [{"parts": [{"text": "What''s the weather in San Francisco?"}], - "role": "user"}, {"parts": [{"functionCall": {"args": {"location": "San Francisco"}, - "name": "get_weather"}}], "role": "model"}, {"parts": [{"functionResponse": - {"name": "get_weather", "response": {"location": "San Francisco", "temperature": - "72\u00b0F", "condition": "sunny", "humidity": "45%", "wind": "5 mph NW"}}}], - "role": "user"}], "systemInstruction": {"parts": [{"text": "You are a helpful - weather assistant. Use the get_weather tool to answer questions about weather.\n\nYou - are an agent. Your internal name is \"weather_agent\"."}], "role": "user"}, - "tools": [{"functionDeclarations": [{"description": "Get the weather for a location.", - "name": "get_weather", "parameters": {"properties": {"location": {"type": "STRING"}}, - "required": ["location"], "type": "OBJECT"}}]}], "generationConfig": {}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '881' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.31.0 gl-python/3.9.21 google-adk/1.14.1 gl-python/3.9.21 - x-goog-api-client: - - google-genai-sdk/1.31.0 gl-python/3.9.21 google-adk/1.14.1 gl-python/3.9.21 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61R0U7bQBB891esTuobiS5OHELfqqaRUIEisACprdA2Xsen2nfmbl2IovwT38CX - cefUwaGv9YO12pnbGc1sIgCxRJ2pDJmc+Ajf/QZg0/4DZjSTZg90K7+s0fIbd/dterOnMD2FRyIt - CB4JuSALSsM1alhY1EvllgaUA9dovYZHxQUgMFU1WeTGEpgcjuOX58UQwomiqVSmeB2eTJIP4B0D - h9PKD36XQFUXcHE7/KFFz8h2P/88erNvTUnBW2UyKjv6tiOIXGnliitCZ3SgXaffLsUexT+rM7Oq - rfkVEhjIoZQymU1HUo6n8iSeTpKTWRx14q2saByu6JwYfci4j1L4I1XNqflN+rNp2pBnk51Qr5MD - fNzhbBjLA2g0mh39c9fNvaoq+2X1evQBYOlTbYv6cpeKXkh8aKtLKeqF+d7kfxIbvxOL/paz6+uG - rFO7YlZU+aoG8VAO8hJd0V4UllxttKPTLHDmcX6Op+nXi3v19MDu8j6npPkkRbSNXgFas32N/AIA - AA== - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Thu, 18 Sep 2025 20:09:52 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=612 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/adk-py/src/tests/cassettes/test_adk_captures_metrics.yaml b/integrations/adk-py/src/tests/cassettes/test_adk_captures_metrics.yaml deleted file mode 100644 index b12cc877b..000000000 --- a/integrations/adk-py/src/tests/cassettes/test_adk_captures_metrics.yaml +++ /dev/null @@ -1,63 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "Say hello in 3 words"}], "role": "user"}], - "systemInstruction": {"parts": [{"text": "You are a helpful assistant.\n\nYou - are an agent. Your internal name is \"metrics_agent\"."}], "role": "user"}, - "generationConfig": {}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '255' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.31.0 gl-python/3.9.21 google-adk/1.14.1 gl-python/3.9.21 - x-goog-api-client: - - google-genai-sdk/1.31.0 gl-python/3.9.21 google-adk/1.14.1 gl-python/3.9.21 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61Ry07DMBC85yssn9sqD2gDF1TxrFRERQNCAg6GbB7C9UaxC4Uq/147aVIHrvhg - WTvjmd3ZrUMIfWcizmOmQNJT8qwrhGzr22AoFAilgbakiwUr1YHbnK311hQFG/OJ3gDnOCAZfhFt - Q2YkA16cvQhq0avu/To4mJTIwSisMAbe0quWQJNc5DK7ByZRGNoyulvQDmWf6RzTosQ30+fQHXmT - MPC88Yk7DkMvCPwjp3WuPelashRuQTGdA+umpVphVagIP0Cc47rOwZ80LlZsPTzcwwoV4z0kOB78 - UZUX2jPndppW0Hp2xnP1bQaMLp8iauWj+k21ATlWjr9b/CezsO/l7NfSbOoRSpk3K0lhpZc09Efu - MOFMZrUgLUEWKCTMYsPZuA9XLIZsmiyzn8lsgfPrwJ+61KmcHftOmoycAgAA - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Fri, 31 Oct 2025 23:27:03 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=491 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/adk-py/src/tests/cassettes/test_adk_complex_nested_schema.yaml b/integrations/adk-py/src/tests/cassettes/test_adk_complex_nested_schema.yaml deleted file mode 100644 index 009f6096a..000000000 --- a/integrations/adk-py/src/tests/cassettes/test_adk_complex_nested_schema.yaml +++ /dev/null @@ -1,74 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "Give me info about Alice who lives in - Paris, France."}], "role": "user"}], "systemInstruction": {"parts": [{"text": - "Return a person with their address.\n\nYou are an agent. Your internal name - is \"nested_agent\"."}], "role": "user"}, "generationConfig": {"responseMimeType": - "application/json", "responseSchema": {"properties": {"name": {"description": - "Person''s name", "title": "Name", "type": "STRING"}, "age": {"description": - "Person''s age", "maximum": 150.0, "minimum": 0.0, "title": "Age", "type": "INTEGER"}, - "address": {"properties": {"street": {"description": "Street address", "title": - "Street", "type": "STRING"}, "city": {"description": "City name", "title": "City", - "type": "STRING"}, "country": {"description": "Country name", "title": "Country", - "type": "STRING"}}, "property_ordering": ["street", "city", "country"], "required": - ["street", "city", "country"], "title": "Address", "type": "OBJECT"}}, "property_ordering": - ["name", "age", "address"], "required": ["name", "age", "address"], "title": - "Person", "type": "OBJECT"}}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '1078' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.56.0 gl-python/3.13.3 google-adk/1.21.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.56.0 gl-python/3.13.3 google-adk/1.21.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61SXU/CMBR9369o+gxkDDbUNxSIRokEF2PiDCnsMqpbu7Sd0ZD9d9t9QKev7qFp - z7m9p/ecHR2E8I6wmMZEgcRX6FUjCB2r1XCcKWBKEy2kwZwIda6tv6O11yUKvswlfIwYQhFmJINI - nyM8TelOb3s1TpIKHrntOY4FSGmw6qbBpBIAqr69LgDFgNb0k6e06WJqdlR91xUrIqi0GV4wJRpy - IQgz6oYsI1Zi69Hlaf/WO48qeApmjozHkLblZVuA95RReVgDkZyZsqfwcYVPLPlMHniSC741bvXd - getOJp7rB4HnDYOxf+m0wpUkLqT2YwmK6DDIyXKsG2S5CvkHsBszjWYuhrWIlV2H94OGV1yRtEMN - R5Pen75yplVpaodq5a2HJ6l22EwYzl9CbBmkus9qHXIsI38/8p/E/KAr5jTB1Fk9g5C0DiWBTMfU - 9wZuf58Seag6Yv2f5ZxJuIur4OaLGdm+q+vxLWyK5cq93xRyOsZO6fwAprqOZyQDAAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Wed, 17 Dec 2025 23:48:24 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=740 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/adk-py/src/tests/cassettes/test_adk_input_schema_serialization.yaml b/integrations/adk-py/src/tests/cassettes/test_adk_input_schema_serialization.yaml deleted file mode 100644 index 70e114205..000000000 --- a/integrations/adk-py/src/tests/cassettes/test_adk_input_schema_serialization.yaml +++ /dev/null @@ -1,63 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "Hello"}], "role": "user"}], "systemInstruction": - {"parts": [{"text": "You are a test agent with input schema.\n\nYou are an agent. - Your internal name is \"input_schema_agent\"."}], "role": "user"}, "generationConfig": - {}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '256' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.56.0 gl-python/3.13.3 google-adk/1.21.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.56.0 gl-python/3.13.3 google-adk/1.21.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61RTU/DMAy991eEnNmUfdAyLggxYJWYmEaFEB+aAvW6allcNelgmvbfl7TrlnIm - h8jye/azn7ceIfSbyziNuQZFr8i7yRCyLX+LodQgtQHqlElmPNcnbvW2TmwoGn5tER2BEHhGRvhD - jAwJyQJERjZYEI0x31x/SOoU7o7x5/lJLkcBttcKYxA1fVcT6DyVqVpMgSuUlvYcPU3oEeXr5BGT - LMcvO3GLtRnzBz7rdAdBL7i86DPW73m1dqlKC8UTGIPmxhN+3JyaHqtMR7gEeYtF6Uk3qHQcCxt4 - hx1wjZqLBtSrS522amhEU+Fa67hu1uci1Ru7Y3T3GlHHIt2cqvbIc6z8O+M/iXVYU8w7nKa61gvk - Kq3OksDKHKrVbbPWXHC1KDvSHFSGUkEYW86U3Q/520MYxv5sVownawXL4gapt/P2SVZ1D6oCAAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Wed, 17 Dec 2025 23:48:23 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=497 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/adk-py/src/tests/cassettes/test_adk_max_tokens_captures_content.yaml b/integrations/adk-py/src/tests/cassettes/test_adk_max_tokens_captures_content.yaml deleted file mode 100644 index 7f05caa2f..000000000 --- a/integrations/adk-py/src/tests/cassettes/test_adk_max_tokens_captures_content.yaml +++ /dev/null @@ -1,66 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "Tell me a long story about a lighthouse."}], - "role": "user"}], "systemInstruction": {"parts": [{"text": "You are a creative - storyteller.\n\nYou are an agent. Your internal name is \"creative_agent\"."}], - "role": "user"}, "generationConfig": {"temperature": 0.7, "maxOutputTokens": - 50}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '320' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.31.0 gl-python/3.9.21 google-adk/1.14.1 gl-python/3.9.21 - x-goog-api-client: - - google-genai-sdk/1.31.0 gl-python/3.9.21 google-adk/1.14.1 gl-python/3.9.21 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61STU/bQBC9+1eM9sIliUJCPuiN8qGiQkHgtkgFoUl2bC9sdt3dSVMT5b93bePg - 5FzLsnZmnufNvLfrCEDM0UglkcmLT/ArZADW1besWcNkOBSaVEjm6PgDWz/r1jlAmP6WP4mbVyw6 - 4IlZEyjTgRnNcekJOFMewssZgWfrCrBJFfxU0q4OPFypNOMOhNlAcYjxHcYZluGMyMAqNMnJkQRr - 6k6ouYCVMtJDYh2kZMghK2t879E8mnifAFbozQHDy9Jz4CpAl9nMhhF7cEtunpEUrdU22/NT50MQ - ZzWV2y6sJN3ANw1AJMoon90RemtK2PXJw3N88/X8273YYvBPemXT3NlZqWy33xtOR4PR8eRoMBmO - p4fjo6ihr4jF0mNK18QYjMOtPSI0WOQc21cyp3ZZGTfs1yQtn3fqo6bOllHvlKZNqdXWnwVSpdv+ - t65GUAC14qJcMz5/iEVLJd6dqpEpaqm5P+N/IhvtkUXv7tSG/SDnVe1MSovgVXfQ63cTjT6rOgpH - Pg83iC5liXk5m15gMj78Ip+/v00ub9mefv590hfRJvoHTxCJAU8DAAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Fri, 31 Oct 2025 23:00:29 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=868 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/adk-py/src/tests/cassettes/test_adk_response_json_schema_dict.yaml b/integrations/adk-py/src/tests/cassettes/test_adk_response_json_schema_dict.yaml deleted file mode 100644 index 1f41b3a9c..000000000 --- a/integrations/adk-py/src/tests/cassettes/test_adk_response_json_schema_dict.yaml +++ /dev/null @@ -1,68 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "Tell me about Tokyo"}], "role": "user"}], - "systemInstruction": {"parts": [{"text": "You are a City Information Agent. - Provide city information.\n\nYou are an agent. Your internal name is \"city_agent\"."}], - "role": "user"}, "generationConfig": {"responseMimeType": "application/json", - "responseJsonSchema": {"type": "object", "properties": {"city": {"type": "string", - "description": "Name of the city"}, "population": {"type": "integer", "description": - "Population of the city", "minimum": 0}, "country": {"type": "string", "description": - "Country where the city is located"}}, "required": ["city", "country"]}}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '647' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.56.0 gl-python/3.13.3 google-adk/1.21.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.56.0 gl-python/3.13.3 google-adk/1.21.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61Ry07DMBC85ysin5sqbegj3BDl0NKKAhFCIhyWxE2jprYVu0CJ8u+s86rDGR8i - Z2e8sztTWLZNImBxGoOiklzbb1ix7aL6aowzRZlCoC1hUUCuLtz6FMYdKYp+60ekCJlthyRK1TnE - /5AE/HDmIRk0dX5iKm+gFQhgHSS4OGWgUs40OvL8qYsnZCUxlMru/j64zJfzjGrxI49p1tLLlkB2 - KUvl/omC5EzTnoOHLelQ+EzWPBE5/9ArOu4QVa/86WQ2d72J740n/nw2slrxSpacJCR0QxWgi9B5 - RbDJUSjcmLJbvSginlsLGab3ca/BFVeQ9aBpCxlt5QJF08wMw8gJ94cMnddLBnevATE8Uv2pWpMs - w8u/M/6XmNcXs5ps6rheaC7TOpeEHjEpZzx0nV0Gcl91JDmVgjNJl7HmrA5iAdEiWorxvSNvtl/r - n5H7uCFWaf0CGhSW3NwCAAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Thu, 18 Dec 2025 00:26:15 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=598 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/adk-py/src/tests/cassettes/test_adk_structured_output_pydantic.yaml b/integrations/adk-py/src/tests/cassettes/test_adk_structured_output_pydantic.yaml deleted file mode 100644 index 41a158500..000000000 --- a/integrations/adk-py/src/tests/cassettes/test_adk_structured_output_pydantic.yaml +++ /dev/null @@ -1,67 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "What is the capital of France?"}], "role": - "user"}], "systemInstruction": {"parts": [{"text": "You are a Capital Information - Agent. Given a country, respond ONLY with a JSON object containing the capital. - Format: {\"capital\": \"capital_name\"}\n\nYou are an agent. Your internal name - is \"capital_agent\"."}], "role": "user"}, "generationConfig": {"responseMimeType": - "application/json", "responseSchema": {"properties": {"capital": {"description": - "The capital of the country.", "title": "Capital", "type": "STRING"}}, "required": - ["capital"], "title": "CapitalOutput", "type": "OBJECT"}}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '626' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.56.0 gl-python/3.13.3 google-adk/1.21.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.56.0 gl-python/3.13.3 google-adk/1.21.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61RTU/DMAy991dEOW9Tu4l+cGUckChso5qQVg5mzbqMLilJhoCq/52kXbsUruQQ - WX7PfvZz5SCEt8AymoEiEl+jjc4gVDW/wThThCkNdCmdLEGoC7d9lRVriiKfpghXKUMo1RIlVVCk - OpXiBQgqU5yyGltFdR+/jC5SghfE9DnyjBQdve4IeEcZlfsVAcmZoT0ljwvco/CR3/O8FPzVTDt2 - J24YeX7kX0WzKAi9MJxNnU66EcUnCTmJiQJtB/RLY93iWKqEvxF2w0+NHb7fyljuDXDPO+OK68UH - UBCM/rSVcy1KC9tVy3C9PRRUfZkVk9vnBFsOqeFUnUWO5eTvGf9JzPOGYs75Mu2x1kRI2l4lJ0d9 - p/F04o53Bch90xELIkvOJLnLDGf9/TAH8N/j+LA6xNuFKwLmL5fYqZ0f+Qzu4aUCAAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Wed, 17 Dec 2025 22:48:56 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=713 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/adk-py/src/tests/conftest.py b/integrations/adk-py/src/tests/conftest.py deleted file mode 100644 index f9ea7606b..000000000 --- a/integrations/adk-py/src/tests/conftest.py +++ /dev/null @@ -1,13 +0,0 @@ -import os - -import pytest - - -@pytest.fixture(autouse=True) -def setup_braintrust(): - os.environ["BRAINTRUST_SYNC_FLUSH"] = "1" - os.environ.setdefault("BRAINTRUST_API_URL", "http://localhost:8000") - os.environ.setdefault("BRAINTRUST_APP_URL", "http://localhost:3000") - os.environ.setdefault("BRAINTRUST_API_KEY", "your_api_key_here") - os.environ.setdefault("GOOGLE_API_KEY", os.environ.get("GEMINI_API_KEY", "your_google_api_key_here")) - os.environ.setdefault("GOOGLE_GENAI_USE_VERTEXAI", "FALSE") diff --git a/integrations/adk-py/src/tests/test_adk.py b/integrations/adk-py/src/tests/test_adk.py deleted file mode 100644 index e67d53204..000000000 --- a/integrations/adk-py/src/tests/test_adk.py +++ /dev/null @@ -1,1418 +0,0 @@ -import json -from pathlib import Path - -import pytest -from google.adk import Agent -from google.adk.agents import LlmAgent -from google.adk.runners import Runner -from google.adk.sessions import InMemorySessionService -from google.genai import types -from pydantic import BaseModel, Field - -from braintrust import logger -from braintrust.bt_json import bt_safe_deep_copy -from braintrust.logger import Attachment -from braintrust.test_helpers import init_test_logger -from braintrust_adk import setup_adk - -PROJECT_NAME = "test_adk" - -setup_adk(project_name=PROJECT_NAME) - - -@pytest.fixture(scope="module") -def vcr_config(): - return { - "record_mode": "once", - "filter_headers": [ - "authorization", - "x-goog-api-key", - ], - } - - -@pytest.fixture -def memory_logger(): - init_test_logger(PROJECT_NAME) - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_adk_braintrust_integration(memory_logger): - assert not memory_logger.pop() - - def get_weather(location: str): - """Get the weather for a location.""" - return { - "location": location, - "temperature": "72ยฐF", - "condition": "sunny", - "humidity": "45%", - "wind": "5 mph NW", - } - - agent = Agent( - name="weather_agent", - model="gemini-2.0-flash", - instruction="You are a helpful weather assistant. Use the get_weather tool to answer questions about weather.", - tools=[get_weather], - ) - - # Set up session - APP_NAME = "weather_app" - USER_ID = "test-user" - SESSION_ID = "test-session" - - session_service = InMemorySessionService() - await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID) - - runner = Runner(agent=agent, app_name=APP_NAME, session_service=session_service) - - user_msg = types.Content(role="user", parts=[types.Part(text="What's the weather in San Francisco?")]) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id=SESSION_ID, new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - assert len(responses) > 0 - assert responses[0].content - assert responses[0].content.parts - - response_text = responses[0].content.parts[0].text - assert any(word in response_text.lower() for word in ["weather", "san francisco", "72", "sunny"]), ( - f"Response doesn't mention weather: {response_text}" - ) - - spans = memory_logger.pop() - - # Check that we have the expected span types - span_types = {row["span_attributes"]["type"] for row in spans} - assert "task" in span_types, "Missing 'task' spans" - assert "llm" in span_types, "Missing 'llm' spans" - - # Verify the invocation span - invocation_spans = [row for row in spans if row["span_attributes"]["name"] == "invocation [weather_app]"] - assert len(invocation_spans) > 0, "Missing invocation span" - invocation_span = invocation_spans[0] - - # Check invocation input - assert "input" in invocation_span, "Missing input in invocation span" - assert "new_message" in invocation_span["input"], "Missing new_message in input" - assert invocation_span["input"]["new_message"]["parts"][0]["text"] == "What's the weather in San Francisco?" - - # Check metadata - assert "metadata" in invocation_span, "Missing metadata in invocation span" - assert invocation_span["metadata"]["user_id"] == "test-user" - assert invocation_span["metadata"]["session_id"] == "test-session" - - # Verify LLM call spans - llm_spans = [row for row in spans if row["span_attributes"]["type"] == "llm"] - assert len(llm_spans) >= 2, "Should have at least 2 LLM calls (tool selection and response generation)" - - # Check tool selection LLM call - tool_selection_spans = [span for span in llm_spans if "tool_selection" in span["span_attributes"]["name"]] - assert len(tool_selection_spans) > 0, "Missing tool selection LLM call" - - tool_selection_span = tool_selection_spans[0] - assert "output" in tool_selection_span, "Missing output in tool selection span" - assert "content" in tool_selection_span["output"], "Missing content in tool selection output" - # Verify it called the get_weather function - function_call = tool_selection_span["output"]["content"]["parts"][0]["function_call"] - assert function_call["name"] == "get_weather" - assert function_call["args"]["location"] == "San Francisco" - - # Check response generation LLM call - response_gen_spans = [span for span in llm_spans if "response_generation" in span["span_attributes"]["name"]] - assert len(response_gen_spans) > 0, "Missing response generation LLM call" - - response_span = response_gen_spans[0] - assert "output" in response_span, "Missing output in response generation span" - response_output = response_span["output"]["content"]["parts"][0]["text"] - assert "san francisco" in response_output.lower(), "Response doesn't mention San Francisco" - assert "72" in response_output, "Response doesn't mention temperature" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_adk_max_tokens_captures_content(memory_logger): - """Test that content is captured even when MAX_TOKENS finish reason occurs.""" - assert not memory_logger.pop() - - agent = Agent( - name="creative_agent", - model="gemini-2.0-flash", - instruction="You are a creative storyteller.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=50, # Set low to trigger MAX_TOKENS - temperature=0.7, - ), - ) - - APP_NAME = "creative_app" - USER_ID = "test-user" - SESSION_ID = "test-session-max-tokens" - - session_service = InMemorySessionService() - await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID) - - runner = Runner(agent=agent, app_name=APP_NAME, session_service=session_service) - - user_msg = types.Content(role="user", parts=[types.Part(text="Tell me a long story about a lighthouse.")]) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id=SESSION_ID, new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - assert len(responses) > 0 - spans = memory_logger.pop() - - # Find the LLM call span - llm_spans = [row for row in spans if row["span_attributes"]["type"] == "llm"] - assert len(llm_spans) > 0, "Missing LLM call span" - - llm_span = llm_spans[0] - assert "output" in llm_span, "Missing output in LLM span" - - output = llm_span["output"] - - # When MAX_TOKENS is hit, we should still have content captured - # The integration should merge content from earlier events if the final event lacks it - if "finish_reason" in output and output["finish_reason"] == "MAX_TOKENS": - # This is the MAX_TOKENS case - verify we still captured content - assert "content" in output, "Content should be captured even with MAX_TOKENS" - assert output["content"] is not None, "Content should not be None" - assert "parts" in output["content"], "Content should have parts" - assert len(output["content"]["parts"]) > 0, "Content parts should not be empty" - - # Verify the text was actually captured - text_content = output["content"]["parts"][0].get("text", "") - assert len(text_content) > 0, "Should have captured some text content before MAX_TOKENS" - - # Verify usage metadata is present - assert "usage_metadata" in output, "Should have usage metadata" - - -def test_serialize_content_with_binary_data(): - """Test that _serialize_content converts binary data to Attachment references.""" - from braintrust.logger import Attachment - from braintrust_adk import _serialize_content, _serialize_part - - # Create a minimal PNG image (1x1 red pixel) - minimal_png = ( - b"\x89PNG\r\n\x1a\n" # PNG signature - b"\x00\x00\x00\rIHDR\x00\x00\x00\x01\x00\x00\x00\x01" - b"\x08\x02\x00\x00\x00\x90wS\xde" # IHDR - b"\x00\x00\x00\x0cIDATx\x9cc\xf8\xcf\xc0\x00\x00\x00\x03\x00\x01\x00\x18\xdd\x8d\xb4" # IDAT - b"\x00\x00\x00\x00IEND\xaeB`\x82" # IEND - ) - - # Create a mock Part with inline_data - class MockBlob: - def __init__(self, data, mime_type): - self.data = data - self.mime_type = mime_type - - class MockPart: - def __init__(self, inline_data=None, text=None): - self.inline_data = inline_data - self.text = text - - # Test serializing a Part with binary data - part_with_image = MockPart(inline_data=MockBlob(minimal_png, "image/png")) - serialized_part = _serialize_part(part_with_image) - - # Verify structure - assert "image_url" in serialized_part, "Should have image_url field" - assert "url" in serialized_part["image_url"], "Should have url field" - - attachment = serialized_part["image_url"]["url"] - # The Attachment object should be in the serialized output - assert isinstance(attachment, Attachment), "Should be an Attachment object" - assert attachment.reference["type"] == "braintrust_attachment" - assert attachment.reference["content_type"] == "image/png" - assert attachment.reference["filename"] == "file.png" - assert "key" in attachment.reference - - # Test serializing a Part with text - part_with_text = MockPart(text="Hello, world!") - serialized_text_part = _serialize_part(part_with_text) - assert serialized_text_part == {"text": "Hello, world!"}, "Text part should serialize correctly" - - # Test serializing Content with multiple parts - class MockContent: - def __init__(self, parts, role): - self.parts = parts - self.role = role - - content = MockContent( - parts=[ - MockPart(inline_data=MockBlob(minimal_png, "image/png")), - MockPart(text="What's in this image?"), - ], - role="user", - ) - - serialized_content = _serialize_content(content) - assert "parts" in serialized_content - assert "role" in serialized_content - assert serialized_content["role"] == "user" - assert len(serialized_content["parts"]) == 2 - - # First part should be the image as Attachment - assert "image_url" in serialized_content["parts"][0] - assert isinstance(serialized_content["parts"][0]["image_url"]["url"], Attachment) - - # Second part should be text - assert serialized_content["parts"][1] == {"text": "What's in this image?"} - - -def test_serialize_part_with_file_data(): - """Test that _serialize_part handles file_data (file references) correctly.""" - from braintrust_adk import _serialize_part - - class MockFileData: - def __init__(self, file_uri, mime_type): - self.file_uri = file_uri - self.mime_type = mime_type - - class MockPart: - def __init__(self, file_data=None, text=None): - self.file_data = file_data - self.text = text - - # Test serializing a Part with file_data - part_with_file = MockPart(file_data=MockFileData("gs://bucket/file.pdf", "application/pdf")) - serialized_part = _serialize_part(part_with_file) - - assert "file_data" in serialized_part - assert serialized_part["file_data"]["file_uri"] == "gs://bucket/file.pdf" - assert serialized_part["file_data"]["mime_type"] == "application/pdf" - - -def test_serialize_part_with_dict(): - """Test that _serialize_part handles dict input correctly.""" - from braintrust_adk import _serialize_part - - # Test that dicts pass through unchanged - dict_part = {"text": "Hello", "custom": "field"} - serialized = _serialize_part(dict_part) - assert serialized == dict_part, "Dict should pass through unchanged" - - -def test_serialize_content_with_none(): - """Test that _serialize_content handles None correctly.""" - from braintrust_adk import _serialize_content - - result = _serialize_content(None) - assert result is None, "None should serialize to None" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_adk_binary_data_attachment_conversion(memory_logger): - """Test that binary data in messages is converted to Attachment references.""" - assert not memory_logger.pop() - - agent = Agent( - name="vision_agent", - model="gemini-2.0-flash", - instruction="You are a helpful assistant that can analyze images.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=150, - ), - ) - - APP_NAME = "vision_app" - USER_ID = "test-user" - SESSION_ID = "test-session-image" - - session_service = InMemorySessionService() - await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID) - - runner = Runner(agent=agent, app_name=APP_NAME, session_service=session_service) - - # Load test image from fixtures - fixtures_dir = Path(__file__).parent.parent.parent.parent.parent / "internal" / "golden" / "fixtures" - image_path = fixtures_dir / "test-image.png" - with open(image_path, "rb") as f: - image_data = f.read() - - # Create message with inline binary data - user_msg = types.Content( - role="user", - parts=[ - types.Part(inline_data=types.Blob(mime_type="image/png", data=image_data)), - types.Part(text="What color is this image?"), - ], - ) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id=SESSION_ID, new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - assert len(responses) > 0 - - spans = memory_logger.pop() - - # Find the invocation span - invocation_spans = [row for row in spans if row["span_attributes"]["name"] == "invocation [vision_app]"] - assert len(invocation_spans) > 0, "Missing invocation span" - invocation_span = invocation_spans[0] - - # Verify the input contains properly serialized content - assert "input" in invocation_span, "Missing input in invocation span" - assert "new_message" in invocation_span["input"], "Missing new_message in input" - - new_message = invocation_span["input"]["new_message"] - assert "parts" in new_message, "Missing parts in new_message" - assert len(new_message["parts"]) == 2, "Should have 2 parts (image and text)" - - # First part should be the image as an Attachment reference - image_part = new_message["parts"][0] - assert "image_url" in image_part, "Image part should have image_url field" - assert "url" in image_part["image_url"], "image_url should have url field" - - attachment_ref = image_part["image_url"]["url"] - # Verify it's an Attachment object, not raw binary data - assert isinstance(attachment_ref, Attachment), "Attachment should be an Attachment object" - ref = attachment_ref.reference - assert "key" in ref, "Attachment reference should have a key" - assert "filename" in ref, "Attachment reference should have a filename" - assert "content_type" in ref, "Attachment reference should have a content_type" - assert ref["content_type"] == "image/png", "Content type should be image/png" - assert ref["filename"] == "file.png", "Filename should be file.png" - - # Second part should be the text - text_part = new_message["parts"][1] - assert "text" in text_part, "Second part should have text" - assert text_part["text"] == "What color is this image?", "Text content should match" - - # Verify no raw binary data is present in the logged span - span_str = str(invocation_span) - # Check that the binary PNG signature is NOT in the logged data - assert b"\x89PNG".hex() not in span_str, "Raw binary data should not be in logged span" - assert "89504e47" not in span_str.lower(), "Raw binary data (hex) should not be in logged span" - - # Find LLM spans and verify they also don't contain raw binary - llm_spans = [row for row in spans if row["span_attributes"]["type"] == "llm"] - assert len(llm_spans) > 0, "Should have LLM spans" - - for llm_span in llm_spans: - if "input" in llm_span and "contents" in llm_span["input"]: - llm_str = str(llm_span["input"]) - assert b"\x89PNG".hex() not in llm_str, "Raw binary data should not be in LLM span input" - assert "89504e47" not in llm_str.lower(), "Raw binary data (hex) should not be in LLM span input" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_adk_captures_metrics(memory_logger): - """Test that token usage metrics are captured from LLM responses.""" - assert not memory_logger.pop() - - agent = Agent( - name="metrics_agent", - model="gemini-2.0-flash", - instruction="You are a helpful assistant.", - ) - - APP_NAME = "metrics_app" - USER_ID = "test-user" - SESSION_ID = "test-session-metrics" - - session_service = InMemorySessionService() - await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID) - - runner = Runner(agent=agent, app_name=APP_NAME, session_service=session_service) - - user_msg = types.Content(role="user", parts=[types.Part(text="Say hello in 3 words")]) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id=SESSION_ID, new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - assert len(responses) > 0 - - spans = memory_logger.pop() - - # Find LLM spans - llm_spans = [row for row in spans if row["span_attributes"].get("type") == "llm"] - assert len(llm_spans) > 0, "Should have LLM spans" - - # Verify metrics are present in at least one LLM span - llm_span_with_metrics = None - for llm_span in llm_spans: - if "metrics" in llm_span and llm_span["metrics"]: - llm_span_with_metrics = llm_span - break - - assert llm_span_with_metrics is not None, "At least one LLM span should have metrics" - - metrics = llm_span_with_metrics["metrics"] - - # Verify core token metrics are present - assert "prompt_tokens" in metrics, "Metrics should include prompt_tokens" - assert "completion_tokens" in metrics, "Metrics should include completion_tokens" - assert "tokens" in metrics, "Metrics should include total tokens" - - # Verify token counts are reasonable - assert metrics["prompt_tokens"] > 0, "prompt_tokens should be greater than 0" - assert metrics["completion_tokens"] > 0, "completion_tokens should be greater than 0" - assert metrics["tokens"] > 0, "total tokens should be greater than 0" - assert metrics["tokens"] == metrics["prompt_tokens"] + metrics["completion_tokens"], ( - "total tokens should equal prompt + completion tokens" - ) - - # Verify time to first token is captured for streaming responses - assert "time_to_first_token" in metrics, "Metrics should include time_to_first_token" - assert metrics["time_to_first_token"] > 0, "time_to_first_token should be greater than 0" - assert metrics["time_to_first_token"] < 10, "time_to_first_token should be reasonable (< 10 seconds)" - - # Verify model name is captured in metadata - metadata = llm_span_with_metrics.get("metadata", {}) - assert "model" in metadata, "Metadata should include model name" - assert metadata["model"] == "gemini-2.0-flash", "Model name should match the agent's model" - - -def test_determine_llm_call_type_direct_response(): - """Test that _determine_llm_call_type returns 'direct_response' when tools are available but not used.""" - from braintrust_adk import _determine_llm_call_type - - # Request with tools available - llm_request = { - "config": { - "tools": [ - { - "function_declarations": [ - {"name": "read_file", "description": "Read a file"}, - {"name": "list_directory", "description": "List directory"}, - ] - } - ] - }, - "contents": [{"parts": [{"text": "What is 2+2?"}], "role": "user"}], - } - - # Response without function calls - model_response = { - "content": {"parts": [{"text": "4\n"}], "role": "model"}, - "finish_reason": "STOP", - } - - call_type = _determine_llm_call_type(llm_request, model_response) - assert call_type == "direct_response", "Should be direct_response when tools available but not used" - - -def test_determine_llm_call_type_tool_selection(): - """Test that _determine_llm_call_type returns 'tool_selection' when LLM calls a tool.""" - from braintrust_adk import _determine_llm_call_type - - # Request with tools available - llm_request = { - "config": { - "tools": [ - { - "function_declarations": [ - {"name": "get_weather", "description": "Get weather"}, - ] - } - ] - }, - "contents": [{"parts": [{"text": "What's the weather?"}], "role": "user"}], - } - - # Response with function call (camelCase) - model_response = { - "content": { - "parts": [{"functionCall": {"name": "get_weather", "args": {"location": "SF"}}}], - "role": "model", - }, - } - - call_type = _determine_llm_call_type(llm_request, model_response) - assert call_type == "tool_selection", "Should be tool_selection when LLM calls a tool" - - -def test_determine_llm_call_type_tool_selection_snake_case(): - """Test that _determine_llm_call_type handles snake_case function_call.""" - from braintrust_adk import _determine_llm_call_type - - llm_request = { - "config": {"tools": [{"function_declarations": [{"name": "search"}]}]}, - "contents": [{"parts": [{"text": "Search for pizza"}], "role": "user"}], - } - - # Response with function call (snake_case) - model_response = { - "content": { - "parts": [{"function_call": {"name": "search", "args": {"query": "pizza"}}}], - "role": "model", - }, - } - - call_type = _determine_llm_call_type(llm_request, model_response) - assert call_type == "tool_selection", "Should be tool_selection for snake_case function_call" - - -def test_determine_llm_call_type_response_generation(): - """Test that _determine_llm_call_type returns 'response_generation' after tool execution.""" - from braintrust_adk import _determine_llm_call_type - - # Request with function_response in history - llm_request = { - "config": {"tools": [{"function_declarations": [{"name": "get_weather"}]}]}, - "contents": [ - {"parts": [{"text": "What's the weather?"}], "role": "user"}, - {"parts": [{"functionCall": {"name": "get_weather", "args": {}}}], "role": "model"}, - { - "parts": [{"function_response": {"name": "get_weather", "response": {"temp": "72F"}}}], - "role": "user", - }, - ], - } - - # Response after tool execution - model_response = { - "content": {"parts": [{"text": "It's 72 degrees"}], "role": "model"}, - } - - call_type = _determine_llm_call_type(llm_request, model_response) - assert call_type == "response_generation", "Should be response_generation after tool execution" - - -def test_determine_llm_call_type_no_tools(): - """Test that _determine_llm_call_type returns 'direct_response' when no tools configured.""" - from braintrust_adk import _determine_llm_call_type - - llm_request = { - "config": {}, - "contents": [{"parts": [{"text": "Hello"}], "role": "user"}], - } - - model_response = { - "content": {"parts": [{"text": "Hi there"}], "role": "model"}, - } - - call_type = _determine_llm_call_type(llm_request, model_response) - assert call_type == "direct_response", "Should be direct_response when no tools configured" - - -def test_determine_llm_call_type_no_response(): - """Test that _determine_llm_call_type handles missing model_response gracefully.""" - from braintrust_adk import _determine_llm_call_type - - llm_request = { - "config": {"tools": [{"function_declarations": [{"name": "tool1"}]}]}, - "contents": [{"parts": [{"text": "Test"}], "role": "user"}], - } - - # No model_response provided - call_type = _determine_llm_call_type(llm_request, None) - assert call_type == "direct_response", "Should default to direct_response when no response available" - - -@pytest.mark.asyncio -async def test_llm_call_span_wraps_child_spans(memory_logger): - """Test that llm_call span is created BEFORE yielding events, so child spans have proper parent. - - This test validates the fix for the issue where mcp_tool and other child spans - were losing their parent context because the llm_call span was created AFTER - all events were yielded. - - The fix ensures: - 1. llm_call span is created BEFORE wrapped() is called - 2. Child spans (like mcp_tool) created during execution have proper parent - 3. Span is updated with correct call_type after response is received - """ - from unittest.mock import ANY, MagicMock - - from braintrust import current_span, start_span - from braintrust_adk import wrap_flow - - # Clear any existing logs - memory_logger.pop() - - # Mock Flow class - class MockFlow: - def __init__(self): - self.llm = MagicMock() - self.llm.model = "test-model" - - async def run_async(self, invocation_context, llm_request=None, model_response_event=None): - """Method that wrap_flow will wrap.""" - async for event in self._call_llm_async(invocation_context, llm_request, model_response_event): - yield event - - async def _call_llm_async(self, invocation_context, llm_request, model_response_event): - """Simulates the flow making LLM calls and potentially calling tools.""" - # Simulate an event stream - yield {"type": "start"} - - # During execution, child spans might be created (like mcp_tool calls) - # This simulates an MCP tool being called during LLM execution - with start_span(name="mcp_tool [test_tool]", type="tool") as tool_span: - tool_span.log(output={"result": "success"}) - - yield {"type": "complete", "content": {"parts": [{"text": "Done"}], "role": "model"}} - - # Wrap the flow - wrap_flow(MockFlow) - - # Create flow instance - flow = MockFlow() - - # Track parent span during execution - parent_spans_during_execution = [] - - async def wrapped_execution(): - """Wrapper that tracks parent span during execution.""" - async for event in flow.run_async( - invocation_context={"test": "context"}, - llm_request={"contents": [{"parts": [{"text": "test"}], "role": "user"}]}, - model_response_event=None, - ): - # Check what the current parent span is during execution - parent = current_span() - if parent and hasattr(parent, "id"): - parent_spans_during_execution.append(parent.id) - - # Execute - await wrapped_execution() - - # Give background logger time to flush - memory_logger.flush() - - # Get all logged spans - logs = memory_logger.pop() - - # Find the spans by name - llm_call_spans = [log for log in logs if "llm_call" in log.get("span_attributes", {}).get("name", "")] - mcp_tool_spans = [log for log in logs if "mcp_tool" in log.get("span_attributes", {}).get("name", "")] - - # Verify llm_call span exists - assert len(llm_call_spans) > 0, "Should have created llm_call span" - - # Verify mcp_tool span exists - assert len(mcp_tool_spans) > 0, "Should have created mcp_tool span" - - # Verify mcp_tool span has the llm_call span as parent - llm_call_span_id = llm_call_spans[0]["span_id"] - mcp_tool_span = mcp_tool_spans[0] - - # The mcp_tool span should have the llm_call span in its parent chain - assert "span_parents" in mcp_tool_span, "mcp_tool span should have span_parents" - assert llm_call_span_id in mcp_tool_span["span_parents"], ( - f"mcp_tool span should have llm_call span as parent. " - f"Expected {llm_call_span_id} in {mcp_tool_span['span_parents']}" - ) - - # Verify llm_call span name was updated with call_type - llm_call_name = llm_call_spans[0]["span_attributes"]["name"] - assert "[" in llm_call_name, f"llm_call span name should include call_type in brackets: {llm_call_name}" - - -@pytest.mark.asyncio -async def test_async_context_preservation_across_yields(): - """Test that async context is preserved across generator yields. - - This validates that the aclosing wrapper properly handles ContextVar errors - that occur when async generators yield control and resume in different contexts. - """ - import asyncio - - from braintrust import start_span - from braintrust_adk import aclosing - - # Initialize logger - init_test_logger("test-context") - - async def context_switching_generator(): - """Generator that creates spans and yields, potentially switching contexts.""" - with start_span(name="outer_span", type="task") as outer: - yield {"event": 1} - await asyncio.sleep(0.001) # Force context switch - - with start_span(name="inner_span", type="task") as inner: - inner.log(output={"data": "test"}) - yield {"event": 2} - await asyncio.sleep(0.001) # Another context switch - - yield {"event": 3} - - # Collect events using aclosing - events = [] - async with aclosing(context_switching_generator()) as gen: - async for event in gen: - events.append(event) - await asyncio.sleep(0.001) # Force context switches during iteration - - # Verify all events were collected successfully - assert len(events) == 3 - assert events[0]["event"] == 1 - assert events[1]["event"] == 2 - assert events[2]["event"] == 3 - - # If we get here, the context error suppression in aclosing.__aexit__ worked correctly - - -class CapitalOutput(BaseModel): - capital: str = Field(description="The capital of the country.") - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_adk_structured_output_pydantic(memory_logger): - """Test that structured output with Pydantic models is properly captured.""" - from unittest.mock import ANY - - assert not memory_logger.pop() - - structured_capital_agent = LlmAgent( - name="capital_agent", - model="gemini-2.0-flash", - instruction="""You are a Capital Information Agent. Given a country, respond ONLY with a JSON object containing the capital. Format: {"capital": "capital_name"}""", - output_schema=CapitalOutput, - output_key="found_capital", - ) - - APP_NAME = "capital_app" - USER_ID = "test-user" - SESSION_ID = "test-session-structured" - - session_service = InMemorySessionService() - await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID) - - runner = Runner(agent=structured_capital_agent, app_name=APP_NAME, session_service=session_service) - - user_msg = types.Content(role="user", parts=[types.Part(text="What is the capital of France?")]) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id=SESSION_ID, new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - assert len(responses) > 0 - - spans = memory_logger.pop() - - # Find the LLM span that has response_schema in the config - llm_spans_with_schema = [ - span - for span in spans - if span["span_attributes"]["type"] == "llm" - and "input" in span - and "config" in span["input"] - and span["input"]["config"].get("response_schema") is not None - ] - - assert len(llm_spans_with_schema) > 0, "Should have at least one LLM call with response_schema" - - llm_span = llm_spans_with_schema[0] - - # Assert the complete input structure - use ANY for values we don't care about - assert llm_span["input"] == { - "model": ANY, - "contents": ANY, - "config": { - "system_instruction": ANY, - "response_mime_type": ANY, - "response_schema": { - "properties": { - "capital": {"description": "The capital of the country.", "title": "Capital", "type": "string"} - }, - "required": ["capital"], - "title": "CapitalOutput", - "type": "object", - }, - }, - "live_connect_config": ANY, - } - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_adk_input_schema_serialization(memory_logger): - """Test that input_schema with Pydantic models is properly serialized.""" - from unittest.mock import ANY - - class UserInput(BaseModel): - name: str = Field(description="User's name") - age: int = Field(description="User's age", ge=0) - - assert not memory_logger.pop() - - agent = LlmAgent( - name="input_schema_agent", - model="gemini-2.0-flash", - instruction="You are a test agent with input schema.", - input_schema=UserInput, - ) - - APP_NAME = "input_schema_app" - USER_ID = "test-user" - SESSION_ID = "test-session-input-schema" - - session_service = InMemorySessionService() - await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID) - - runner = Runner(agent=agent, app_name=APP_NAME, session_service=session_service) - - user_msg = types.Content(role="user", parts=[types.Part(text="Hello")]) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id=SESSION_ID, new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - assert len(responses) > 0 - - spans = memory_logger.pop() - - # Find LLM span - input_schema is on the agent, but we verify serialization doesn't break - llm_spans = [span for span in spans if span["span_attributes"]["type"] == "llm"] - - assert len(llm_spans) > 0, "Should have at least one LLM call" - - llm_span = llm_spans[0] - - # Assert complete input structure - assert llm_span["input"] == { - "model": "gemini-2.0-flash", - "contents": [ - { - "role": "user", - "parts": [{"text": "Hello"}], - } - ], - "config": { - "system_instruction": ANY, # Contains agent name - }, - "live_connect_config": { - "input_audio_transcription": {}, - "output_audio_transcription": {}, - }, - } - - # Assert complete output structure - assert llm_span["output"] == { - "content": { - "role": "model", - "parts": ANY, # Response text varies - }, - "finish_reason": ANY, - "usage_metadata": ANY, # Token counts vary - "avg_logprobs": ANY, - } - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_adk_complex_nested_schema(memory_logger): - """Test that complex nested Pydantic schemas are properly serialized.""" - from unittest.mock import ANY - - class Address(BaseModel): - street: str = Field(description="Street address") - city: str = Field(description="City name") - country: str = Field(description="Country name") - - class Person(BaseModel): - name: str = Field(description="Person's name") - age: int = Field(description="Person's age", ge=0, le=150) - address: Address = Field(description="Person's address") - - assert not memory_logger.pop() - - nested_agent = LlmAgent( - name="nested_agent", - model="gemini-2.0-flash", - instruction="Return a person with their address.", - output_schema=Person, - output_key="person_data", - ) - - APP_NAME = "nested_app" - USER_ID = "test-user" - SESSION_ID = "test-session-nested" - - session_service = InMemorySessionService() - await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID) - - runner = Runner(agent=nested_agent, app_name=APP_NAME, session_service=session_service) - - user_msg = types.Content( - role="user", parts=[types.Part(text="Give me info about Alice who lives in Paris, France.")] - ) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id=SESSION_ID, new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - assert len(responses) > 0 - - spans = memory_logger.pop() - - # Find LLM span with response_schema - llm_spans_with_schema = [ - span - for span in spans - if span["span_attributes"]["type"] == "llm" - and "input" in span - and "config" in span["input"] - and span["input"]["config"].get("response_schema") is not None - ] - - assert len(llm_spans_with_schema) > 0, "Should have at least one LLM call with response_schema" - - llm_span = llm_spans_with_schema[0] - - # Assert complete input structure with nested schema - assert llm_span["input"] == { - "model": "gemini-2.0-flash", - "contents": [ - { - "role": "user", - "parts": [{"text": "Give me info about Alice who lives in Paris, France."}], - } - ], - "config": { - "system_instruction": ANY, # Contains agent name - "response_mime_type": "application/json", - "response_schema": { - "properties": { - "name": { - "description": "Person's name", - "title": "Name", - "type": "string", - }, - "age": { - "description": "Person's age", - "maximum": 150, - "minimum": 0, - "title": "Age", - "type": "integer", - }, - "address": { - "$ref": "#/$defs/Address", - "description": "Person's address", - }, - }, - "$defs": { - "Address": { - "properties": { - "street": { - "description": "Street address", - "title": "Street", - "type": "string", - }, - "city": { - "description": "City name", - "title": "City", - "type": "string", - }, - "country": { - "description": "Country name", - "title": "Country", - "type": "string", - }, - }, - "required": ["street", "city", "country"], - "title": "Address", - "type": "object", - }, - }, - "required": ["name", "age", "address"], - "title": "Person", - "type": "object", - }, - }, - "live_connect_config": { - "input_audio_transcription": {}, - "output_audio_transcription": {}, - }, - } - - # Assert complete output structure - assert llm_span["output"] == { - "content": { - "role": "model", - "parts": ANY, # Response text varies - }, - "finish_reason": ANY, - "usage_metadata": ANY, # Token counts vary - "avg_logprobs": ANY, - } - - -@pytest.mark.asyncio -async def test_serialize_config_handles_all_schema_fields(): - """Test that _serialize_config handles all 4 schema fields.""" - from braintrust_adk import _serialize_config - - class TestSchema(BaseModel): - value: str = Field(description="Test value") - - # Test with a dict config that has all schema fields - config = { - "response_schema": TestSchema, - "response_json_schema": TestSchema, - "input_schema": TestSchema, - "output_schema": TestSchema, - "other_field": "keep me", - } - - serialized = _serialize_config(config) - - assert isinstance(serialized, dict) - - # All schema fields should be serialized to JSON Schema format - for field in ["response_schema", "response_json_schema", "input_schema", "output_schema"]: - assert field in serialized, f"Missing {field}" - schema = serialized[field] - assert isinstance(schema, dict) - assert "properties" in schema - assert "value" in schema["properties"] - assert schema["properties"]["value"]["description"] == "Test value" - - # Other fields should be preserved - assert "other_field" in serialized - - -@pytest.mark.asyncio -async def test_serialize_config_handles_non_pydantic(): - """Test that _serialize_config handles non-Pydantic values gracefully.""" - from braintrust_adk import _serialize_config - - # Test with non-Pydantic values - config = {"response_schema": "not a pydantic model", "other_field": {"key": "value"}} - - serialized = _serialize_config(config) - - assert isinstance(serialized, dict) - # Non-Pydantic schema should remain as-is - assert "response_schema" in serialized - assert serialized["response_schema"] == "not a pydantic model" - - -@pytest.mark.asyncio -async def test_serialize_pydantic_schema_direct(): - """Test _serialize_pydantic_schema directly with various inputs.""" - from braintrust_adk import _serialize_pydantic_schema - - class SimpleSchema(BaseModel): - name: str = Field(description="A name") - count: int = Field(description="A count", ge=0) - - # Test with Pydantic class - result = _serialize_pydantic_schema(SimpleSchema) - assert isinstance(result, dict) - assert result["type"] == "object" - assert "properties" in result - assert "name" in result["properties"] - assert result["properties"]["name"]["description"] == "A name" - assert "count" in result["properties"] - - # Test with non-Pydantic class - class NotPydantic: - pass - - result = _serialize_pydantic_schema(NotPydantic) - assert isinstance(result, dict) - assert "__class__" in result - assert result["__class__"] == "NotPydantic" - - # Test with non-class object - result = _serialize_pydantic_schema("not a class") - assert isinstance(result, dict) - assert "__class__" in result - - -@pytest.mark.asyncio -async def test_bt_safe_deep_copy_never_raises(): - """Test that bt_safe_deep_copy never raises exceptions.""" - from braintrust_adk import bt_safe_deep_copy - - class BrokenModel: - def model_dump(self): - raise ValueError("I'm broken!") - - # Should not raise - result = bt_safe_deep_copy(BrokenModel()) - assert result is not None - - # Test with various types - assert bt_safe_deep_copy({"key": "value"}) == {"key": "value"} - assert bt_safe_deep_copy([1, 2, 3]) == [1, 2, 3] - assert bt_safe_deep_copy("string") == "string" - assert bt_safe_deep_copy(123) == 123 - assert bt_safe_deep_copy(None) is None - - # Test with Pydantic model instance - class WorkingModel(BaseModel): - value: str = "test" - - instance = WorkingModel() - result = bt_safe_deep_copy(instance) - assert isinstance(result, dict) - assert result["value"] == "test" - - # Test with Pydantic model class (not instance) - # bt_safe_deep_copy now returns the JSON schema for Pydantic model classes - result = bt_safe_deep_copy(WorkingModel) - assert isinstance(result, dict) - assert "properties" in result - assert "value" in result["properties"] - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_adk_response_json_schema_dict(memory_logger): - """Test that Google ADK with response_json_schema (plain dict) is properly captured.""" - from unittest.mock import ANY - - # Use a plain JSON schema dict (not Pydantic) - json_schema_dict = { - "type": "object", - "properties": { - "city": { - "type": "string", - "description": "Name of the city", - }, - "population": { - "type": "integer", - "description": "Population of the city", - "minimum": 0, - }, - "country": { - "type": "string", - "description": "Country where the city is located", - }, - }, - "required": ["city", "country"], - } - - assert not memory_logger.pop() - - # Pass JSON schema via generate_content_config - config = types.GenerateContentConfig( - response_mime_type="application/json", - response_json_schema=json_schema_dict, - ) - - json_schema_agent = LlmAgent( - name="city_agent", - model="gemini-2.0-flash", - instruction="You are a City Information Agent. Provide city information.", - generate_content_config=config, - ) - - APP_NAME = "city_app" - USER_ID = "test-user" - SESSION_ID = "test-session-json-dict" - - session_service = InMemorySessionService() - await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID) - - runner = Runner(agent=json_schema_agent, app_name=APP_NAME, session_service=session_service) - - user_msg = types.Content(role="user", parts=[types.Part(text="Tell me about Tokyo")]) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id=SESSION_ID, new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - assert len(responses) > 0 - - spans = memory_logger.pop() - - # Find LLM span with response_json_schema - llm_spans_with_schema = [ - span - for span in spans - if span["span_attributes"]["type"] == "llm" - and "input" in span - and "config" in span["input"] - and span["input"]["config"].get("response_json_schema") is not None - ] - - assert len(llm_spans_with_schema) > 0, "Should have at least one LLM call with response_json_schema" - - llm_span = llm_spans_with_schema[0] - - # Assert complete input structure - plain JSON schema dict should be preserved - assert llm_span["input"] == { - "model": "gemini-2.0-flash", - "contents": [ - { - "role": "user", - "parts": [{"text": "Tell me about Tokyo"}], - } - ], - "config": { - "system_instruction": ANY, # Contains agent name - "response_mime_type": "application/json", - "response_json_schema": { - "type": "object", - "properties": { - "city": { - "type": "string", - "description": "Name of the city", - }, - "population": { - "type": "integer", - "description": "Population of the city", - "minimum": 0, - }, - "country": { - "type": "string", - "description": "Country where the city is located", - }, - }, - "required": ["city", "country"], - }, - }, - "live_connect_config": { - "input_audio_transcription": {}, - "output_audio_transcription": {}, - }, - } - - # Assert complete output structure - assert llm_span["output"] == { - "content": { - "role": "model", - "parts": ANY, # Response contains Tokyo info in JSON - }, - "finish_reason": ANY, - "usage_metadata": ANY, - "avg_logprobs": ANY, - } - - -@pytest.mark.asyncio -async def test_serialize_config_preserves_none(): - """Test that _serialize_config returns None when config is None (not empty dict).""" - from braintrust_adk import _serialize_config - - # None should be preserved as None, not converted to {} - result = _serialize_config(None) - assert result is None, f"Expected None, got {result}" - - # Empty dict should remain empty dict - result = _serialize_config({}) - assert result == {} - - # False should be preserved as False - result = _serialize_config(False) - assert result is False - - # 0 should be preserved as 0 - result = _serialize_config(0) - assert result == 0 - - # Empty string should be preserved - result = _serialize_config("") - assert result == "" - - -@pytest.mark.asyncio -async def test_bt_safe_deep_copy_with_attachments(memory_logger): - """Test that bt_safe_deep_copy preserves Attachment objects in ADK context.""" - from braintrust.bt_json import bt_safe_deep_copy - - attachment = Attachment(data=b"test data", filename="test.txt", content_type="text/plain") - - # Test preserving attachment in nested structure (simulating ADK metadata) - metadata = {"file": attachment, "nested": {"also_file": attachment}} - - result = bt_safe_deep_copy(metadata) - - # Attachment identity should be preserved - assert result["file"] is attachment - assert result["nested"]["also_file"] is attachment - - -@pytest.mark.asyncio -async def test_adk_agent_metadata_with_attachment(memory_logger): - """Test that attachments in ADK agent metadata are preserved and uploaded.""" - from unittest.mock import patch - - assert not memory_logger.pop() - - attachment = Attachment(data=b"context data", filename="context.txt", content_type="text/plain") - - def simple_tool(query: str): - """A simple tool.""" - return {"result": f"Processed: {query}"} - - agent = Agent( - name="tool_agent", - model="gemini-2.0-flash", - instruction="You are a helpful assistant with tools.", - tools=[simple_tool], - ) - - APP_NAME = "attachment_app" - USER_ID = "test-user" - SESSION_ID = "test-session-attachment" - - session_service = InMemorySessionService() - await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID) - - runner = Runner(agent=agent, app_name=APP_NAME, session_service=session_service) - - # Create message with attachment in metadata context - user_msg = types.Content(role="user", parts=[types.Part(text="Use the tool with query: test")]) - - with patch.object(Attachment, "upload", return_value={"upload_status": "done"}) as mock_upload: - responses = [] - # We can't directly inject attachment into ADK's internal flow, - # but we can test that if an attachment appears in logged metadata, - # bt_safe_deep_copy preserves it - async for event in runner.run_async(user_id=USER_ID, session_id=SESSION_ID, new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - memory_logger.flush() - - spans = memory_logger.pop() - assert len(spans) > 0, "Should have logged spans" - - # Verify bt_safe_deep_copy behavior with attachment - test_data = {"metadata": {"context_file": attachment}} - copied = bt_safe_deep_copy(test_data) - assert copied["metadata"]["context_file"] is attachment - - -@pytest.mark.asyncio -async def test_adk_bytes_and_attachment_in_structure(): - """Test that dataclass/dict with both bytes and attachment fields are handled correctly.""" - from braintrust.bt_json import bt_safe_deep_copy - - attachment = Attachment(data=b"attachment data", filename="file.txt", content_type="text/plain") - - # Simulate ADK structure with both bytes and attachments - structure = { - "binary_data": b"some bytes", - "attachment": attachment, - "nested": {"more_bytes": bytearray(b"more data"), "another_attachment": attachment}, - } - - result = bt_safe_deep_copy(structure) - - # Attachment should be preserved - assert result["attachment"] is attachment - assert result["nested"]["another_attachment"] is attachment - - # Bytes should be handled (converted via bt_dumps/bt_loads) - assert "binary_data" in result - assert "nested" in result - assert "more_bytes" in result["nested"] diff --git a/integrations/adk-py/src/tests/test_mcp_tool.py b/integrations/adk-py/src/tests/test_mcp_tool.py deleted file mode 100644 index 17c4c4b2c..000000000 --- a/integrations/adk-py/src/tests/test_mcp_tool.py +++ /dev/null @@ -1,389 +0,0 @@ -"""Tests for MCP tool tracing integration.""" - -from unittest.mock import AsyncMock, MagicMock, patch - -import pytest - -from braintrust_adk import setup_adk, wrap_mcp_tool - - -@pytest.mark.asyncio -async def test_wrap_mcp_tool_marks_as_patched(): - """Test that wrap_mcp_tool marks the class as patched.""" - - # Create a real class to wrap - class MockMcpTool: - async def run_async(self, *, args, tool_context): - return {"result": "success"} - - # Wrap the class - wrapped_class = wrap_mcp_tool(MockMcpTool) - - # Verify it's marked as patched - assert hasattr(wrapped_class, "_braintrust_patched") - assert wrapped_class._braintrust_patched is True - - -@pytest.mark.asyncio -async def test_mcp_tool_execution_creates_span(): - """Test that MCP tool execution creates proper trace spans.""" - - with patch("braintrust_adk.start_span") as mock_start_span: - # Setup mock span - mock_span = MagicMock() - mock_span.__enter__ = MagicMock(return_value=mock_span) - mock_span.__exit__ = MagicMock(return_value=False) - mock_start_span.return_value = mock_span - - # Mock McpTool class and instance - MockMcpTool = MagicMock() - mock_instance = MagicMock() - mock_instance.name = "read_file" - mock_instance.run_async = AsyncMock(return_value={"content": [{"type": "text", "text": "file contents"}]}) - - # Wrap the class - wrapped_class = wrap_mcp_tool(MockMcpTool) - - # Simulate tool execution - tool_args = {"path": "/tmp/test.txt"} - tool_context = None - - # Call the wrapped method directly on the mock instance - # We need to manually trigger the wrapper - - # Get the original method - original_run_async = mock_instance.run_async - - # Create wrapped version by calling wrap_mcp_tool's wrapper - # This simulates what wrapt does - async def call_wrapped(): - return await original_run_async(args=tool_args, tool_context=tool_context) - - result = await call_wrapped() - - # For now, just verify the mock was called - mock_instance.run_async.assert_called_once_with(args=tool_args, tool_context=tool_context) - - -@pytest.mark.asyncio -async def test_mcp_tool_span_captures_tool_info(): - """Test that MCP tool spans capture tool name, args, and results.""" - from braintrust.span_types import SpanTypeAttribute - - with patch("braintrust_adk.start_span") as mock_start_span: - mock_span = MagicMock() - mock_span.__enter__ = MagicMock(return_value=mock_span) - mock_span.__exit__ = MagicMock(return_value=False) - mock_start_span.return_value = mock_span - - # Create a real-ish McpTool mock - class MockMcpTool: - def __init__(self): - self.name = "list_directory" - self._original_run_async = AsyncMock( - return_value={"content": [{"type": "text", "text": "file1.txt\nfile2.txt"}]} - ) - - async def run_async(self, *, args, tool_context): - return await self._original_run_async(args=args, tool_context=tool_context) - - # Wrap the class - wrap_mcp_tool(MockMcpTool) - - # Create instance and call - tool = MockMcpTool() - tool_args = {"path": "/tmp"} - tool_context = None - - result = await tool.run_async(args=tool_args, tool_context=tool_context) - - # Verify span was created - assert mock_start_span.called - call_kwargs = mock_start_span.call_args[1] - - # Check span name includes tool name - assert "list_directory" in call_kwargs["name"] - - # Check span type is TOOL - assert call_kwargs["type"] == SpanTypeAttribute.TOOL - - # Check input contains tool name and arguments - assert "tool_name" in call_kwargs["input"] - assert call_kwargs["input"]["tool_name"] == "list_directory" - assert call_kwargs["input"]["arguments"] == tool_args - - # Verify output was logged - mock_span.log.assert_called_once() - log_call = mock_span.log.call_args[1] - assert "output" in log_call - - -@pytest.mark.asyncio -async def test_mcp_tool_error_handling(): - """Test that MCP tool errors are captured in spans.""" - with patch("braintrust_adk.start_span") as mock_start_span: - mock_span = MagicMock() - mock_span.__enter__ = MagicMock(return_value=mock_span) - mock_span.__exit__ = MagicMock(return_value=False) - mock_start_span.return_value = mock_span - - # Create mock tool that raises error - class MockMcpTool: - def __init__(self): - self.name = "failing_tool" - - async def run_async(self, *, args, tool_context): - raise ValueError("Tool execution failed") - - # Wrap the class - wrap_mcp_tool(MockMcpTool) - - # Create instance and call (should raise) - tool = MockMcpTool() - - with pytest.raises(ValueError, match="Tool execution failed"): - await tool.run_async(args={}, tool_context=None) - - # Verify error was logged to span - assert mock_span.log.called - # Check if error was logged - log_calls = [call for call in mock_span.log.call_args_list] - # Should have logged the error - - -@pytest.mark.asyncio -async def test_setup_adk_patches_mcp_tool(): - """Test that setup_adk automatically patches McpTool.""" - import importlib - import sys - - # Mock google-adk imports - mock_mcp_tool_module = MagicMock() - MockMcpTool = MagicMock() - mock_mcp_tool_module.McpTool = MockMcpTool - - # Mock google.adk modules hierarchy - mock_google = MagicMock() - mock_google_adk = MagicMock() - mock_google_adk_tools = MagicMock() - mock_google_adk_tools_mcp_tool = MagicMock() - mock_google_adk_tools_mcp_tool.mcp_tool = mock_mcp_tool_module - - # Clear all google.adk modules from cache - modules_to_remove = [ - key - for key in list(sys.modules.keys()) - if key.startswith("google.adk.tools.mcp_tool") - ] - for module in modules_to_remove: - del sys.modules[module] - - # Critical: Also clear the mcp_tool submodule to force re-import with mock - sys.modules.pop("google.adk.tools.mcp_tool.mcp_tool", None) - - with patch.dict( - "sys.modules", - { - "google.adk.tools.mcp_tool": mock_google_adk_tools_mcp_tool, - "google.adk.tools.mcp_tool.mcp_tool": mock_mcp_tool_module, - }, - clear=False, - ): - with patch("braintrust_adk.init_logger"): - with patch("braintrust_adk.wrap_mcp_tool") as mock_wrap: - result = setup_adk(project_name="test") - - # Verify wrap_mcp_tool was called - assert result is True - mock_wrap.assert_called_once_with(MockMcpTool) - - -@pytest.mark.asyncio -async def test_setup_adk_graceful_fallback_when_mcp_unavailable(): - """Test that setup_adk gracefully handles MCP not being installed.""" - with patch("braintrust_adk.init_logger"): - # This test is tricky - we need MCP import to fail but not break other imports - # The actual behavior is tested in integration: when MCP is not available, - # it gets ImportError from the google.adk.tools.mcp_tool module itself - # For this test, we just verify setup_adk succeeds even when MCP module raises ImportError - - result = setup_adk(project_name="test") - - # Should succeed - MCP is optional - assert result is True - - # When MCP is not available, MCP import fails but setup_adk continues - # This is the actual graceful fallback in action - - -@pytest.mark.asyncio -async def test_mcp_tool_async_context_preservation(): - """Test that MCP tool spans handle async context switching correctly. - - This test reproduces the "was created in a different Context" error that occurs - when async generators yield control and resume in a different async context. - This is the issue we're seeing in the trace screenshot where mcp_tool spans - lose their parent context. - """ - import contextvars - - from braintrust_adk import wrap_mcp_tool - - # Track context switches - context_var = contextvars.ContextVar("test_context", default=None) - - class MockMcpTool: - def __init__(self): - self.name = "test_tool" - - async def run_async(self, *, args, tool_context): - # Simulate async work that might switch contexts - import asyncio - - await asyncio.sleep(0.001) - return {"result": "success"} - - # Wrap the tool - wrap_mcp_tool(MockMcpTool) - - # Create tool instance - tool = MockMcpTool() - - # Set initial context - context_var.set("initial") - - # Create an async generator that yields and switches contexts - async def context_switching_generator(): - # Call the tool (creates span) - context_var.set("during_call") - result = await tool.run_async(args={"test": "value"}, tool_context=None) - yield result - - # Switch context after yield - context_var.set("after_yield") - - # Execute the generator - this should trigger the context switch issue - results = [] - async for result in context_switching_generator(): - results.append(result) - - # Verify the tool executed successfully despite context switches - assert len(results) == 1 - assert results[0]["result"] == "success" - - # The test passes if no ValueError about "different Context" is raised - # The aclosing wrapper in __init__.py should suppress this error - - -@pytest.mark.asyncio -async def test_mcp_tool_nested_async_generators(): - """Test MCP tool execution within nested async generators. - - This simulates the real-world scenario where: - 1. Runner.run_async creates an async generator with a span - 2. Agent.run_async creates another async generator with a span - 3. MCP tool execution happens deep in the stack - 4. All generators yield and resume, potentially in different contexts - """ - from braintrust_adk import wrap_mcp_tool - - class MockMcpTool: - def __init__(self): - self.name = "nested_tool" - - async def run_async(self, *, args, tool_context): - import asyncio - - await asyncio.sleep(0.001) - return {"nested": "result"} - - wrap_mcp_tool(MockMcpTool) - tool = MockMcpTool() - - # Simulate nested async generators like Runner -> Agent -> Tool - async def outer_generator(): - """Simulates Runner.run_async""" - async for event in middle_generator(): - yield event - - async def middle_generator(): - """Simulates Agent.run_async""" - # Execute tool in the middle of generator execution - result = await tool.run_async(args={"nested": "test"}, tool_context=None) - yield {"type": "tool_result", "data": result} - - # Yield more events after tool execution - yield {"type": "final", "done": True} - - # Collect all events - events = [] - async for event in outer_generator(): - events.append(event) - - # Verify execution completed successfully - assert len(events) == 2 - assert events[0]["type"] == "tool_result" - assert events[0]["data"]["nested"] == "result" - assert events[1]["type"] == "final" - - # If we get here without ValueError, the context handling is working - - -@pytest.mark.asyncio -async def test_real_context_loss_with_braintrust_spans(): - """Test that demonstrates the actual context loss issue with real Braintrust spans. - - This test creates a scenario that matches the real-world issue: - 1. Create a span in an async generator - 2. Yield from that generator - 3. Try to clean up the span after context has switched - - This should trigger the "was created in a different Context" error that we're - suppressing in the aclosing.__aexit__ method. - """ - import asyncio - - from braintrust import init_logger - from braintrust_adk import aclosing - - # Initialize a test logger - logger = init_logger(project="test-context-loss") - - # Track if we hit the context error - context_error_occurred = False - - async def problematic_generator(): - """Generator that creates a span and yields, simulating the Flow behavior.""" - from braintrust import start_span - - with start_span(name="test_span", type="task") as span: - # Yield some events - yield {"event": 1} - await asyncio.sleep(0.001) - yield {"event": 2} - # Span cleanup happens in __exit__, which may be in different context - - # Create a new async context and run the generator - async def outer_context(): - """Simulates the outer runner context.""" - events = [] - - # Use aclosing which has the error suppression - async with aclosing(problematic_generator()) as gen: - async for event in gen: - events.append(event) - # Force context switch - await asyncio.sleep(0.001) - - return events - - # Run in a fresh event loop context - events = await outer_context() - - # Verify we got the events - assert len(events) == 2 - assert events[0]["event"] == 1 - assert events[1]["event"] == 2 - - # If we get here without an unhandled ValueError, the suppression is working - # The aclosing.__aexit__ should have caught and suppressed any context errors diff --git a/integrations/adk-py/uv.lock b/integrations/adk-py/uv.lock deleted file mode 100644 index 1f848f1d9..000000000 --- a/integrations/adk-py/uv.lock +++ /dev/null @@ -1,3277 +0,0 @@ -version = 1 -revision = 2 -requires-python = ">=3.10" -resolution-markers = [ - "python_full_version >= '3.14' and platform_python_implementation == 'PyPy'", - "python_full_version >= '3.14' and platform_python_implementation != 'PyPy'", - "python_full_version == '3.13.*' and platform_python_implementation == 'PyPy'", - "python_full_version == '3.13.*' and platform_python_implementation != 'PyPy'", - "python_full_version >= '3.11' and python_full_version < '3.13' and platform_python_implementation == 'PyPy'", - "python_full_version >= '3.11' and python_full_version < '3.13' and platform_python_implementation != 'PyPy'", - "python_full_version < '3.11' and platform_python_implementation != 'PyPy'", - "python_full_version < '3.11' and platform_python_implementation == 'PyPy'", -] - -[manifest] -members = [ - "braintrust-adk", - "braintrust-adk-examples", -] - -[[package]] -name = "absolufy-imports" -version = "0.3.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/74/0f/9da9dc9a12ebf4622ec96d9338d221e0172699e7574929f65ec8fdb30f9c/absolufy_imports-0.3.1.tar.gz", hash = "sha256:c90638a6c0b66826d1fb4880ddc20ef7701af34192c94faf40b95d32b59f9793", size = 4724, upload-time = "2022-01-20T14:48:53.434Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a3/a4/b65c9fbc2c0c09c0ea3008f62d2010fd261e62a4881502f03a6301079182/absolufy_imports-0.3.1-py2.py3-none-any.whl", hash = "sha256:49bf7c753a9282006d553ba99217f48f947e3eef09e18a700f8a82f75dc7fc5c", size = 5937, upload-time = "2022-01-20T14:48:51.718Z" }, -] - -[[package]] -name = "alembic" -version = "1.17.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "mako" }, - { name = "sqlalchemy" }, - { name = "tomli", marker = "python_full_version < '3.11'" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/6e/b6/2a81d7724c0c124edc5ec7a167e85858b6fd31b9611c6fb8ecf617b7e2d3/alembic-1.17.1.tar.gz", hash = "sha256:8a289f6778262df31571d29cca4c7fbacd2f0f582ea0816f4c399b6da7528486", size = 1981285, upload-time = "2025-10-29T00:23:16.667Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a5/32/7df1d81ec2e50fb661944a35183d87e62d3f6c6d9f8aff64a4f245226d55/alembic-1.17.1-py3-none-any.whl", hash = "sha256:cbc2386e60f89608bb63f30d2d6cc66c7aaed1fe105bd862828600e5ad167023", size = 247848, upload-time = "2025-10-29T00:23:18.79Z" }, -] - -[[package]] -name = "annotated-doc" -version = "0.0.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/d7/a6/dc46877b911e40c00d395771ea710d5e77b6de7bacd5fdcd78d70cc5a48f/annotated_doc-0.0.3.tar.gz", hash = "sha256:e18370014c70187422c33e945053ff4c286f453a984eba84d0dbfa0c935adeda", size = 5535, upload-time = "2025-10-24T14:57:10.718Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/02/b7/cf592cb5de5cb3bade3357f8d2cf42bf103bbe39f459824b4939fd212911/annotated_doc-0.0.3-py3-none-any.whl", hash = "sha256:348ec6664a76f1fd3be81f43dffbee4c7e8ce931ba71ec67cc7f4ade7fbbb580", size = 5488, upload-time = "2025-10-24T14:57:09.462Z" }, -] - -[[package]] -name = "annotated-types" -version = "0.7.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" }, -] - -[[package]] -name = "anyio" -version = "4.11.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "exceptiongroup", marker = "python_full_version < '3.11'" }, - { name = "idna" }, - { name = "sniffio" }, - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/c6/78/7d432127c41b50bccba979505f272c16cbcadcc33645d5fa3a738110ae75/anyio-4.11.0.tar.gz", hash = "sha256:82a8d0b81e318cc5ce71a5f1f8b5c4e63619620b63141ef8c995fa0db95a57c4", size = 219094, upload-time = "2025-09-23T09:19:12.58Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/15/b3/9b1a8074496371342ec1e796a96f99c82c945a339cd81a8e73de28b4cf9e/anyio-4.11.0-py3-none-any.whl", hash = "sha256:0287e96f4d26d4149305414d4e3bc32f0dcd0862365a4bddea19d7a1ec38c4fc", size = 109097, upload-time = "2025-09-23T09:19:10.601Z" }, -] - -[[package]] -name = "attrs" -version = "25.4.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/6b/5c/685e6633917e101e5dcb62b9dd76946cbb57c26e133bae9e0cd36033c0a9/attrs-25.4.0.tar.gz", hash = "sha256:16d5969b87f0859ef33a48b35d55ac1be6e42ae49d5e853b597db70c35c57e11", size = 934251, upload-time = "2025-10-06T13:54:44.725Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl", hash = "sha256:adcf7e2a1fb3b36ac48d97835bb6d8ade15b8dcce26aba8bf1d14847b57a3373", size = 67615, upload-time = "2025-10-06T13:54:43.17Z" }, -] - -[[package]] -name = "authlib" -version = "1.6.5" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "cryptography" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/cd/3f/1d3bbd0bf23bdd99276d4def22f29c27a914067b4cf66f753ff9b8bbd0f3/authlib-1.6.5.tar.gz", hash = "sha256:6aaf9c79b7cc96c900f0b284061691c5d4e61221640a948fe690b556a6d6d10b", size = 164553, upload-time = "2025-10-02T13:36:09.489Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/f8/aa/5082412d1ee302e9e7d80b6949bc4d2a8fa1149aaab610c5fc24709605d6/authlib-1.6.5-py2.py3-none-any.whl", hash = "sha256:3e0e0507807f842b02175507bdee8957a1d5707fd4afb17c32fb43fee90b6e3a", size = 243608, upload-time = "2025-10-02T13:36:07.637Z" }, -] - -[[package]] -name = "backports-asyncio-runner" -version = "1.2.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/8e/ff/70dca7d7cb1cbc0edb2c6cc0c38b65cba36cccc491eca64cabd5fe7f8670/backports_asyncio_runner-1.2.0.tar.gz", hash = "sha256:a5aa7b2b7d8f8bfcaa2b57313f70792df84e32a2a746f585213373f900b42162", size = 69893, upload-time = "2025-07-02T02:27:15.685Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a0/59/76ab57e3fe74484f48a53f8e337171b4a2349e506eabe136d7e01d059086/backports_asyncio_runner-1.2.0-py3-none-any.whl", hash = "sha256:0da0a936a8aeb554eccb426dc55af3ba63bcdc69fa1a600b5bb305413a4477b5", size = 12313, upload-time = "2025-07-02T02:27:14.263Z" }, -] - -[[package]] -name = "braintrust" -version = "0.4.0" -source = { editable = "../../py" } -dependencies = [ - { name = "chevron" }, - { name = "exceptiongroup" }, - { name = "gitpython" }, - { name = "python-dotenv" }, - { name = "python-slugify" }, - { name = "requests" }, - { name = "sseclient-py" }, - { name = "tqdm" }, - { name = "typing-extensions" }, - { name = "wrapt" }, -] - -[package.metadata] -requires-dist = [ - { name = "boto3", marker = "extra == 'all'" }, - { name = "boto3", marker = "extra == 'cli'" }, - { name = "chevron" }, - { name = "exceptiongroup", specifier = ">=1.2.0" }, - { name = "gitpython" }, - { name = "openai-agents", marker = "extra == 'all'" }, - { name = "openai-agents", marker = "extra == 'openai-agents'" }, - { name = "opentelemetry-api", marker = "extra == 'all'" }, - { name = "opentelemetry-api", marker = "extra == 'otel'" }, - { name = "opentelemetry-exporter-otlp-proto-http", marker = "extra == 'all'" }, - { name = "opentelemetry-exporter-otlp-proto-http", marker = "extra == 'otel'" }, - { name = "opentelemetry-sdk", marker = "extra == 'all'" }, - { name = "opentelemetry-sdk", marker = "extra == 'otel'" }, - { name = "psycopg2-binary", marker = "extra == 'all'" }, - { name = "psycopg2-binary", marker = "extra == 'cli'" }, - { name = "pydoc-markdown", marker = "extra == 'all'" }, - { name = "pydoc-markdown", marker = "extra == 'doc'" }, - { name = "python-dotenv" }, - { name = "python-slugify" }, - { name = "requests" }, - { name = "sseclient-py" }, - { name = "starlette", marker = "extra == 'all'" }, - { name = "starlette", marker = "extra == 'cli'" }, - { name = "temporalio", marker = "python_full_version >= '3.10' and extra == 'all'", specifier = ">=1.19.0" }, - { name = "temporalio", marker = "python_full_version >= '3.10' and extra == 'temporal'", specifier = ">=1.19.0" }, - { name = "tqdm" }, - { name = "typing-extensions", specifier = ">=4.1.0" }, - { name = "uv", marker = "extra == 'all'" }, - { name = "uv", marker = "extra == 'cli'" }, - { name = "uvicorn", marker = "extra == 'all'" }, - { name = "uvicorn", marker = "extra == 'cli'" }, - { name = "wrapt" }, -] -provides-extras = ["cli", "doc", "openai-agents", "otel", "temporal", "all"] - -[[package]] -name = "braintrust-adk" -version = "0.3.1" -source = { editable = "." } -dependencies = [ - { name = "braintrust" }, - { name = "google-adk" }, - { name = "wrapt" }, -] - -[package.dev-dependencies] -dev = [ - { name = "pytest" }, - { name = "pytest-asyncio" }, - { name = "pytest-vcr" }, - { name = "pyyaml" }, - { name = "ruff" }, -] - -[package.metadata] -requires-dist = [ - { name = "braintrust", editable = "../../py" }, - { name = "google-adk", specifier = ">=1.14.1" }, - { name = "wrapt", specifier = ">=1.17.3" }, -] - -[package.metadata.requires-dev] -dev = [ - { name = "pytest", specifier = ">=8.3.5" }, - { name = "pytest-asyncio", specifier = ">=1.1.0" }, - { name = "pytest-vcr", specifier = ">=1.0.2" }, - { name = "pyyaml", specifier = ">=6.0" }, - { name = "ruff", specifier = ">=0.12.9" }, -] - -[[package]] -name = "braintrust-adk-examples" -version = "0.1.0" -source = { virtual = "examples" } -dependencies = [ - { name = "braintrust-adk" }, - { name = "google-adk" }, - { name = "python-multipart" }, -] - -[package.metadata] -requires-dist = [ - { name = "braintrust-adk", editable = "." }, - { name = "google-adk", specifier = ">=1.14.1" }, - { name = "python-multipart", specifier = ">=0.0.20" }, -] - -[[package]] -name = "cachetools" -version = "6.2.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/cc/7e/b975b5814bd36faf009faebe22c1072a1fa1168db34d285ef0ba071ad78c/cachetools-6.2.1.tar.gz", hash = "sha256:3f391e4bd8f8bf0931169baf7456cc822705f4e2a31f840d218f445b9a854201", size = 31325, upload-time = "2025-10-12T14:55:30.139Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/96/c5/1e741d26306c42e2bf6ab740b2202872727e0f606033c9dd713f8b93f5a8/cachetools-6.2.1-py3-none-any.whl", hash = "sha256:09868944b6dde876dfd44e1d47e18484541eaf12f26f29b7af91b26cc892d701", size = 11280, upload-time = "2025-10-12T14:55:28.382Z" }, -] - -[[package]] -name = "certifi" -version = "2025.10.5" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/4c/5b/b6ce21586237c77ce67d01dc5507039d444b630dd76611bbca2d8e5dcd91/certifi-2025.10.5.tar.gz", hash = "sha256:47c09d31ccf2acf0be3f701ea53595ee7e0b8fa08801c6624be771df09ae7b43", size = 164519, upload-time = "2025-10-05T04:12:15.808Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e4/37/af0d2ef3967ac0d6113837b44a4f0bfe1328c2b9763bd5b1744520e5cfed/certifi-2025.10.5-py3-none-any.whl", hash = "sha256:0f212c2744a9bb6de0c56639a6f68afe01ecd92d91f14ae897c4fe7bbeeef0de", size = 163286, upload-time = "2025-10-05T04:12:14.03Z" }, -] - -[[package]] -name = "cffi" -version = "2.0.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "pycparser", marker = "implementation_name != 'PyPy' and platform_python_implementation != 'PyPy'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/eb/56/b1ba7935a17738ae8453301356628e8147c79dbb825bcbc73dc7401f9846/cffi-2.0.0.tar.gz", hash = "sha256:44d1b5909021139fe36001ae048dbdde8214afa20200eda0f64c068cac5d5529", size = 523588, upload-time = "2025-09-08T23:24:04.541Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/93/d7/516d984057745a6cd96575eea814fe1edd6646ee6efd552fb7b0921dec83/cffi-2.0.0-cp310-cp310-macosx_10_13_x86_64.whl", hash = "sha256:0cf2d91ecc3fcc0625c2c530fe004f82c110405f101548512cce44322fa8ac44", size = 184283, upload-time = "2025-09-08T23:22:08.01Z" }, - { url = "https://files.pythonhosted.org/packages/9e/84/ad6a0b408daa859246f57c03efd28e5dd1b33c21737c2db84cae8c237aa5/cffi-2.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f73b96c41e3b2adedc34a7356e64c8eb96e03a3782b535e043a986276ce12a49", size = 180504, upload-time = "2025-09-08T23:22:10.637Z" }, - { url = "https://files.pythonhosted.org/packages/50/bd/b1a6362b80628111e6653c961f987faa55262b4002fcec42308cad1db680/cffi-2.0.0-cp310-cp310-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:53f77cbe57044e88bbd5ed26ac1d0514d2acf0591dd6bb02a3ae37f76811b80c", size = 208811, upload-time = "2025-09-08T23:22:12.267Z" }, - { url = "https://files.pythonhosted.org/packages/4f/27/6933a8b2562d7bd1fb595074cf99cc81fc3789f6a6c05cdabb46284a3188/cffi-2.0.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:3e837e369566884707ddaf85fc1744b47575005c0a229de3327f8f9a20f4efeb", size = 216402, upload-time = "2025-09-08T23:22:13.455Z" }, - { url = "https://files.pythonhosted.org/packages/05/eb/b86f2a2645b62adcfff53b0dd97e8dfafb5c8aa864bd0d9a2c2049a0d551/cffi-2.0.0-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:5eda85d6d1879e692d546a078b44251cdd08dd1cfb98dfb77b670c97cee49ea0", size = 203217, upload-time = "2025-09-08T23:22:14.596Z" }, - { url = "https://files.pythonhosted.org/packages/9f/e0/6cbe77a53acf5acc7c08cc186c9928864bd7c005f9efd0d126884858a5fe/cffi-2.0.0-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:9332088d75dc3241c702d852d4671613136d90fa6881da7d770a483fd05248b4", size = 203079, upload-time = "2025-09-08T23:22:15.769Z" }, - { url = "https://files.pythonhosted.org/packages/98/29/9b366e70e243eb3d14a5cb488dfd3a0b6b2f1fb001a203f653b93ccfac88/cffi-2.0.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:fc7de24befaeae77ba923797c7c87834c73648a05a4bde34b3b7e5588973a453", size = 216475, upload-time = "2025-09-08T23:22:17.427Z" }, - { url = "https://files.pythonhosted.org/packages/21/7a/13b24e70d2f90a322f2900c5d8e1f14fa7e2a6b3332b7309ba7b2ba51a5a/cffi-2.0.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:cf364028c016c03078a23b503f02058f1814320a56ad535686f90565636a9495", size = 218829, upload-time = "2025-09-08T23:22:19.069Z" }, - { url = "https://files.pythonhosted.org/packages/60/99/c9dc110974c59cc981b1f5b66e1d8af8af764e00f0293266824d9c4254bc/cffi-2.0.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:e11e82b744887154b182fd3e7e8512418446501191994dbf9c9fc1f32cc8efd5", size = 211211, upload-time = "2025-09-08T23:22:20.588Z" }, - { url = "https://files.pythonhosted.org/packages/49/72/ff2d12dbf21aca1b32a40ed792ee6b40f6dc3a9cf1644bd7ef6e95e0ac5e/cffi-2.0.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:8ea985900c5c95ce9db1745f7933eeef5d314f0565b27625d9a10ec9881e1bfb", size = 218036, upload-time = "2025-09-08T23:22:22.143Z" }, - { url = "https://files.pythonhosted.org/packages/e2/cc/027d7fb82e58c48ea717149b03bcadcbdc293553edb283af792bd4bcbb3f/cffi-2.0.0-cp310-cp310-win32.whl", hash = "sha256:1f72fb8906754ac8a2cc3f9f5aaa298070652a0ffae577e0ea9bd480dc3c931a", size = 172184, upload-time = "2025-09-08T23:22:23.328Z" }, - { url = "https://files.pythonhosted.org/packages/33/fa/072dd15ae27fbb4e06b437eb6e944e75b068deb09e2a2826039e49ee2045/cffi-2.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:b18a3ed7d5b3bd8d9ef7a8cb226502c6bf8308df1525e1cc676c3680e7176739", size = 182790, upload-time = "2025-09-08T23:22:24.752Z" }, - { url = "https://files.pythonhosted.org/packages/12/4a/3dfd5f7850cbf0d06dc84ba9aa00db766b52ca38d8b86e3a38314d52498c/cffi-2.0.0-cp311-cp311-macosx_10_13_x86_64.whl", hash = "sha256:b4c854ef3adc177950a8dfc81a86f5115d2abd545751a304c5bcf2c2c7283cfe", size = 184344, upload-time = "2025-09-08T23:22:26.456Z" }, - { url = "https://files.pythonhosted.org/packages/4f/8b/f0e4c441227ba756aafbe78f117485b25bb26b1c059d01f137fa6d14896b/cffi-2.0.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2de9a304e27f7596cd03d16f1b7c72219bd944e99cc52b84d0145aefb07cbd3c", size = 180560, upload-time = "2025-09-08T23:22:28.197Z" }, - { url = "https://files.pythonhosted.org/packages/b1/b7/1200d354378ef52ec227395d95c2576330fd22a869f7a70e88e1447eb234/cffi-2.0.0-cp311-cp311-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:baf5215e0ab74c16e2dd324e8ec067ef59e41125d3eade2b863d294fd5035c92", size = 209613, upload-time = "2025-09-08T23:22:29.475Z" }, - { url = "https://files.pythonhosted.org/packages/b8/56/6033f5e86e8cc9bb629f0077ba71679508bdf54a9a5e112a3c0b91870332/cffi-2.0.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:730cacb21e1bdff3ce90babf007d0a0917cc3e6492f336c2f0134101e0944f93", size = 216476, upload-time = "2025-09-08T23:22:31.063Z" }, - { url = "https://files.pythonhosted.org/packages/dc/7f/55fecd70f7ece178db2f26128ec41430d8720f2d12ca97bf8f0a628207d5/cffi-2.0.0-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:6824f87845e3396029f3820c206e459ccc91760e8fa24422f8b0c3d1731cbec5", size = 203374, upload-time = "2025-09-08T23:22:32.507Z" }, - { url = "https://files.pythonhosted.org/packages/84/ef/a7b77c8bdc0f77adc3b46888f1ad54be8f3b7821697a7b89126e829e676a/cffi-2.0.0-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:9de40a7b0323d889cf8d23d1ef214f565ab154443c42737dfe52ff82cf857664", size = 202597, upload-time = "2025-09-08T23:22:34.132Z" }, - { url = "https://files.pythonhosted.org/packages/d7/91/500d892b2bf36529a75b77958edfcd5ad8e2ce4064ce2ecfeab2125d72d1/cffi-2.0.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:8941aaadaf67246224cee8c3803777eed332a19d909b47e29c9842ef1e79ac26", size = 215574, upload-time = "2025-09-08T23:22:35.443Z" }, - { url = "https://files.pythonhosted.org/packages/44/64/58f6255b62b101093d5df22dcb752596066c7e89dd725e0afaed242a61be/cffi-2.0.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:a05d0c237b3349096d3981b727493e22147f934b20f6f125a3eba8f994bec4a9", size = 218971, upload-time = "2025-09-08T23:22:36.805Z" }, - { url = "https://files.pythonhosted.org/packages/ab/49/fa72cebe2fd8a55fbe14956f9970fe8eb1ac59e5df042f603ef7c8ba0adc/cffi-2.0.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:94698a9c5f91f9d138526b48fe26a199609544591f859c870d477351dc7b2414", size = 211972, upload-time = "2025-09-08T23:22:38.436Z" }, - { url = "https://files.pythonhosted.org/packages/0b/28/dd0967a76aab36731b6ebfe64dec4e981aff7e0608f60c2d46b46982607d/cffi-2.0.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:5fed36fccc0612a53f1d4d9a816b50a36702c28a2aa880cb8a122b3466638743", size = 217078, upload-time = "2025-09-08T23:22:39.776Z" }, - { url = "https://files.pythonhosted.org/packages/2b/c0/015b25184413d7ab0a410775fdb4a50fca20f5589b5dab1dbbfa3baad8ce/cffi-2.0.0-cp311-cp311-win32.whl", hash = "sha256:c649e3a33450ec82378822b3dad03cc228b8f5963c0c12fc3b1e0ab940f768a5", size = 172076, upload-time = "2025-09-08T23:22:40.95Z" }, - { url = "https://files.pythonhosted.org/packages/ae/8f/dc5531155e7070361eb1b7e4c1a9d896d0cb21c49f807a6c03fd63fc877e/cffi-2.0.0-cp311-cp311-win_amd64.whl", hash = "sha256:66f011380d0e49ed280c789fbd08ff0d40968ee7b665575489afa95c98196ab5", size = 182820, upload-time = "2025-09-08T23:22:42.463Z" }, - { url = "https://files.pythonhosted.org/packages/95/5c/1b493356429f9aecfd56bc171285a4c4ac8697f76e9bbbbb105e537853a1/cffi-2.0.0-cp311-cp311-win_arm64.whl", hash = "sha256:c6638687455baf640e37344fe26d37c404db8b80d037c3d29f58fe8d1c3b194d", size = 177635, upload-time = "2025-09-08T23:22:43.623Z" }, - { url = "https://files.pythonhosted.org/packages/ea/47/4f61023ea636104d4f16ab488e268b93008c3d0bb76893b1b31db1f96802/cffi-2.0.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:6d02d6655b0e54f54c4ef0b94eb6be0607b70853c45ce98bd278dc7de718be5d", size = 185271, upload-time = "2025-09-08T23:22:44.795Z" }, - { url = "https://files.pythonhosted.org/packages/df/a2/781b623f57358e360d62cdd7a8c681f074a71d445418a776eef0aadb4ab4/cffi-2.0.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8eca2a813c1cb7ad4fb74d368c2ffbbb4789d377ee5bb8df98373c2cc0dee76c", size = 181048, upload-time = "2025-09-08T23:22:45.938Z" }, - { url = "https://files.pythonhosted.org/packages/ff/df/a4f0fbd47331ceeba3d37c2e51e9dfc9722498becbeec2bd8bc856c9538a/cffi-2.0.0-cp312-cp312-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:21d1152871b019407d8ac3985f6775c079416c282e431a4da6afe7aefd2bccbe", size = 212529, upload-time = "2025-09-08T23:22:47.349Z" }, - { url = "https://files.pythonhosted.org/packages/d5/72/12b5f8d3865bf0f87cf1404d8c374e7487dcf097a1c91c436e72e6badd83/cffi-2.0.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:b21e08af67b8a103c71a250401c78d5e0893beff75e28c53c98f4de42f774062", size = 220097, upload-time = "2025-09-08T23:22:48.677Z" }, - { url = "https://files.pythonhosted.org/packages/c2/95/7a135d52a50dfa7c882ab0ac17e8dc11cec9d55d2c18dda414c051c5e69e/cffi-2.0.0-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:1e3a615586f05fc4065a8b22b8152f0c1b00cdbc60596d187c2a74f9e3036e4e", size = 207983, upload-time = "2025-09-08T23:22:50.06Z" }, - { url = "https://files.pythonhosted.org/packages/3a/c8/15cb9ada8895957ea171c62dc78ff3e99159ee7adb13c0123c001a2546c1/cffi-2.0.0-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:81afed14892743bbe14dacb9e36d9e0e504cd204e0b165062c488942b9718037", size = 206519, upload-time = "2025-09-08T23:22:51.364Z" }, - { url = "https://files.pythonhosted.org/packages/78/2d/7fa73dfa841b5ac06c7b8855cfc18622132e365f5b81d02230333ff26e9e/cffi-2.0.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:3e17ed538242334bf70832644a32a7aae3d83b57567f9fd60a26257e992b79ba", size = 219572, upload-time = "2025-09-08T23:22:52.902Z" }, - { url = "https://files.pythonhosted.org/packages/07/e0/267e57e387b4ca276b90f0434ff88b2c2241ad72b16d31836adddfd6031b/cffi-2.0.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:3925dd22fa2b7699ed2617149842d2e6adde22b262fcbfada50e3d195e4b3a94", size = 222963, upload-time = "2025-09-08T23:22:54.518Z" }, - { url = "https://files.pythonhosted.org/packages/b6/75/1f2747525e06f53efbd878f4d03bac5b859cbc11c633d0fb81432d98a795/cffi-2.0.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:2c8f814d84194c9ea681642fd164267891702542f028a15fc97d4674b6206187", size = 221361, upload-time = "2025-09-08T23:22:55.867Z" }, - { url = "https://files.pythonhosted.org/packages/7b/2b/2b6435f76bfeb6bbf055596976da087377ede68df465419d192acf00c437/cffi-2.0.0-cp312-cp312-win32.whl", hash = "sha256:da902562c3e9c550df360bfa53c035b2f241fed6d9aef119048073680ace4a18", size = 172932, upload-time = "2025-09-08T23:22:57.188Z" }, - { url = "https://files.pythonhosted.org/packages/f8/ed/13bd4418627013bec4ed6e54283b1959cf6db888048c7cf4b4c3b5b36002/cffi-2.0.0-cp312-cp312-win_amd64.whl", hash = "sha256:da68248800ad6320861f129cd9c1bf96ca849a2771a59e0344e88681905916f5", size = 183557, upload-time = "2025-09-08T23:22:58.351Z" }, - { url = "https://files.pythonhosted.org/packages/95/31/9f7f93ad2f8eff1dbc1c3656d7ca5bfd8fb52c9d786b4dcf19b2d02217fa/cffi-2.0.0-cp312-cp312-win_arm64.whl", hash = "sha256:4671d9dd5ec934cb9a73e7ee9676f9362aba54f7f34910956b84d727b0d73fb6", size = 177762, upload-time = "2025-09-08T23:22:59.668Z" }, - { url = "https://files.pythonhosted.org/packages/4b/8d/a0a47a0c9e413a658623d014e91e74a50cdd2c423f7ccfd44086ef767f90/cffi-2.0.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:00bdf7acc5f795150faa6957054fbbca2439db2f775ce831222b66f192f03beb", size = 185230, upload-time = "2025-09-08T23:23:00.879Z" }, - { url = "https://files.pythonhosted.org/packages/4a/d2/a6c0296814556c68ee32009d9c2ad4f85f2707cdecfd7727951ec228005d/cffi-2.0.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:45d5e886156860dc35862657e1494b9bae8dfa63bf56796f2fb56e1679fc0bca", size = 181043, upload-time = "2025-09-08T23:23:02.231Z" }, - { url = "https://files.pythonhosted.org/packages/b0/1e/d22cc63332bd59b06481ceaac49d6c507598642e2230f201649058a7e704/cffi-2.0.0-cp313-cp313-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:07b271772c100085dd28b74fa0cd81c8fb1a3ba18b21e03d7c27f3436a10606b", size = 212446, upload-time = "2025-09-08T23:23:03.472Z" }, - { url = "https://files.pythonhosted.org/packages/a9/f5/a2c23eb03b61a0b8747f211eb716446c826ad66818ddc7810cc2cc19b3f2/cffi-2.0.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d48a880098c96020b02d5a1f7d9251308510ce8858940e6fa99ece33f610838b", size = 220101, upload-time = "2025-09-08T23:23:04.792Z" }, - { url = "https://files.pythonhosted.org/packages/f2/7f/e6647792fc5850d634695bc0e6ab4111ae88e89981d35ac269956605feba/cffi-2.0.0-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:f93fd8e5c8c0a4aa1f424d6173f14a892044054871c771f8566e4008eaa359d2", size = 207948, upload-time = "2025-09-08T23:23:06.127Z" }, - { url = "https://files.pythonhosted.org/packages/cb/1e/a5a1bd6f1fb30f22573f76533de12a00bf274abcdc55c8edab639078abb6/cffi-2.0.0-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:dd4f05f54a52fb558f1ba9f528228066954fee3ebe629fc1660d874d040ae5a3", size = 206422, upload-time = "2025-09-08T23:23:07.753Z" }, - { url = "https://files.pythonhosted.org/packages/98/df/0a1755e750013a2081e863e7cd37e0cdd02664372c754e5560099eb7aa44/cffi-2.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:c8d3b5532fc71b7a77c09192b4a5a200ea992702734a2e9279a37f2478236f26", size = 219499, upload-time = "2025-09-08T23:23:09.648Z" }, - { url = "https://files.pythonhosted.org/packages/50/e1/a969e687fcf9ea58e6e2a928ad5e2dd88cc12f6f0ab477e9971f2309b57c/cffi-2.0.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:d9b29c1f0ae438d5ee9acb31cadee00a58c46cc9c0b2f9038c6b0b3470877a8c", size = 222928, upload-time = "2025-09-08T23:23:10.928Z" }, - { url = "https://files.pythonhosted.org/packages/36/54/0362578dd2c9e557a28ac77698ed67323ed5b9775ca9d3fe73fe191bb5d8/cffi-2.0.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:6d50360be4546678fc1b79ffe7a66265e28667840010348dd69a314145807a1b", size = 221302, upload-time = "2025-09-08T23:23:12.42Z" }, - { url = "https://files.pythonhosted.org/packages/eb/6d/bf9bda840d5f1dfdbf0feca87fbdb64a918a69bca42cfa0ba7b137c48cb8/cffi-2.0.0-cp313-cp313-win32.whl", hash = "sha256:74a03b9698e198d47562765773b4a8309919089150a0bb17d829ad7b44b60d27", size = 172909, upload-time = "2025-09-08T23:23:14.32Z" }, - { url = "https://files.pythonhosted.org/packages/37/18/6519e1ee6f5a1e579e04b9ddb6f1676c17368a7aba48299c3759bbc3c8b3/cffi-2.0.0-cp313-cp313-win_amd64.whl", hash = "sha256:19f705ada2530c1167abacb171925dd886168931e0a7b78f5bffcae5c6b5be75", size = 183402, upload-time = "2025-09-08T23:23:15.535Z" }, - { url = "https://files.pythonhosted.org/packages/cb/0e/02ceeec9a7d6ee63bb596121c2c8e9b3a9e150936f4fbef6ca1943e6137c/cffi-2.0.0-cp313-cp313-win_arm64.whl", hash = "sha256:256f80b80ca3853f90c21b23ee78cd008713787b1b1e93eae9f3d6a7134abd91", size = 177780, upload-time = "2025-09-08T23:23:16.761Z" }, - { url = "https://files.pythonhosted.org/packages/92/c4/3ce07396253a83250ee98564f8d7e9789fab8e58858f35d07a9a2c78de9f/cffi-2.0.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:fc33c5141b55ed366cfaad382df24fe7dcbc686de5be719b207bb248e3053dc5", size = 185320, upload-time = "2025-09-08T23:23:18.087Z" }, - { url = "https://files.pythonhosted.org/packages/59/dd/27e9fa567a23931c838c6b02d0764611c62290062a6d4e8ff7863daf9730/cffi-2.0.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:c654de545946e0db659b3400168c9ad31b5d29593291482c43e3564effbcee13", size = 181487, upload-time = "2025-09-08T23:23:19.622Z" }, - { url = "https://files.pythonhosted.org/packages/d6/43/0e822876f87ea8a4ef95442c3d766a06a51fc5298823f884ef87aaad168c/cffi-2.0.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:24b6f81f1983e6df8db3adc38562c83f7d4a0c36162885ec7f7b77c7dcbec97b", size = 220049, upload-time = "2025-09-08T23:23:20.853Z" }, - { url = "https://files.pythonhosted.org/packages/b4/89/76799151d9c2d2d1ead63c2429da9ea9d7aac304603de0c6e8764e6e8e70/cffi-2.0.0-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:12873ca6cb9b0f0d3a0da705d6086fe911591737a59f28b7936bdfed27c0d47c", size = 207793, upload-time = "2025-09-08T23:23:22.08Z" }, - { url = "https://files.pythonhosted.org/packages/bb/dd/3465b14bb9e24ee24cb88c9e3730f6de63111fffe513492bf8c808a3547e/cffi-2.0.0-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:d9b97165e8aed9272a6bb17c01e3cc5871a594a446ebedc996e2397a1c1ea8ef", size = 206300, upload-time = "2025-09-08T23:23:23.314Z" }, - { url = "https://files.pythonhosted.org/packages/47/d9/d83e293854571c877a92da46fdec39158f8d7e68da75bf73581225d28e90/cffi-2.0.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:afb8db5439b81cf9c9d0c80404b60c3cc9c3add93e114dcae767f1477cb53775", size = 219244, upload-time = "2025-09-08T23:23:24.541Z" }, - { url = "https://files.pythonhosted.org/packages/2b/0f/1f177e3683aead2bb00f7679a16451d302c436b5cbf2505f0ea8146ef59e/cffi-2.0.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:737fe7d37e1a1bffe70bd5754ea763a62a066dc5913ca57e957824b72a85e205", size = 222828, upload-time = "2025-09-08T23:23:26.143Z" }, - { url = "https://files.pythonhosted.org/packages/c6/0f/cafacebd4b040e3119dcb32fed8bdef8dfe94da653155f9d0b9dc660166e/cffi-2.0.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:38100abb9d1b1435bc4cc340bb4489635dc2f0da7456590877030c9b3d40b0c1", size = 220926, upload-time = "2025-09-08T23:23:27.873Z" }, - { url = "https://files.pythonhosted.org/packages/3e/aa/df335faa45b395396fcbc03de2dfcab242cd61a9900e914fe682a59170b1/cffi-2.0.0-cp314-cp314-win32.whl", hash = "sha256:087067fa8953339c723661eda6b54bc98c5625757ea62e95eb4898ad5e776e9f", size = 175328, upload-time = "2025-09-08T23:23:44.61Z" }, - { url = "https://files.pythonhosted.org/packages/bb/92/882c2d30831744296ce713f0feb4c1cd30f346ef747b530b5318715cc367/cffi-2.0.0-cp314-cp314-win_amd64.whl", hash = "sha256:203a48d1fb583fc7d78a4c6655692963b860a417c0528492a6bc21f1aaefab25", size = 185650, upload-time = "2025-09-08T23:23:45.848Z" }, - { url = "https://files.pythonhosted.org/packages/9f/2c/98ece204b9d35a7366b5b2c6539c350313ca13932143e79dc133ba757104/cffi-2.0.0-cp314-cp314-win_arm64.whl", hash = "sha256:dbd5c7a25a7cb98f5ca55d258b103a2054f859a46ae11aaf23134f9cc0d356ad", size = 180687, upload-time = "2025-09-08T23:23:47.105Z" }, - { url = "https://files.pythonhosted.org/packages/3e/61/c768e4d548bfa607abcda77423448df8c471f25dbe64fb2ef6d555eae006/cffi-2.0.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:9a67fc9e8eb39039280526379fb3a70023d77caec1852002b4da7e8b270c4dd9", size = 188773, upload-time = "2025-09-08T23:23:29.347Z" }, - { url = "https://files.pythonhosted.org/packages/2c/ea/5f76bce7cf6fcd0ab1a1058b5af899bfbef198bea4d5686da88471ea0336/cffi-2.0.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:7a66c7204d8869299919db4d5069a82f1561581af12b11b3c9f48c584eb8743d", size = 185013, upload-time = "2025-09-08T23:23:30.63Z" }, - { url = "https://files.pythonhosted.org/packages/be/b4/c56878d0d1755cf9caa54ba71e5d049479c52f9e4afc230f06822162ab2f/cffi-2.0.0-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:7cc09976e8b56f8cebd752f7113ad07752461f48a58cbba644139015ac24954c", size = 221593, upload-time = "2025-09-08T23:23:31.91Z" }, - { url = "https://files.pythonhosted.org/packages/e0/0d/eb704606dfe8033e7128df5e90fee946bbcb64a04fcdaa97321309004000/cffi-2.0.0-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:92b68146a71df78564e4ef48af17551a5ddd142e5190cdf2c5624d0c3ff5b2e8", size = 209354, upload-time = "2025-09-08T23:23:33.214Z" }, - { url = "https://files.pythonhosted.org/packages/d8/19/3c435d727b368ca475fb8742ab97c9cb13a0de600ce86f62eab7fa3eea60/cffi-2.0.0-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:b1e74d11748e7e98e2f426ab176d4ed720a64412b6a15054378afdb71e0f37dc", size = 208480, upload-time = "2025-09-08T23:23:34.495Z" }, - { url = "https://files.pythonhosted.org/packages/d0/44/681604464ed9541673e486521497406fadcc15b5217c3e326b061696899a/cffi-2.0.0-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:28a3a209b96630bca57cce802da70c266eb08c6e97e5afd61a75611ee6c64592", size = 221584, upload-time = "2025-09-08T23:23:36.096Z" }, - { url = "https://files.pythonhosted.org/packages/25/8e/342a504ff018a2825d395d44d63a767dd8ebc927ebda557fecdaca3ac33a/cffi-2.0.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:7553fb2090d71822f02c629afe6042c299edf91ba1bf94951165613553984512", size = 224443, upload-time = "2025-09-08T23:23:37.328Z" }, - { url = "https://files.pythonhosted.org/packages/e1/5e/b666bacbbc60fbf415ba9988324a132c9a7a0448a9a8f125074671c0f2c3/cffi-2.0.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:6c6c373cfc5c83a975506110d17457138c8c63016b563cc9ed6e056a82f13ce4", size = 223437, upload-time = "2025-09-08T23:23:38.945Z" }, - { url = "https://files.pythonhosted.org/packages/a0/1d/ec1a60bd1a10daa292d3cd6bb0b359a81607154fb8165f3ec95fe003b85c/cffi-2.0.0-cp314-cp314t-win32.whl", hash = "sha256:1fc9ea04857caf665289b7a75923f2c6ed559b8298a1b8c49e59f7dd95c8481e", size = 180487, upload-time = "2025-09-08T23:23:40.423Z" }, - { url = "https://files.pythonhosted.org/packages/bf/41/4c1168c74fac325c0c8156f04b6749c8b6a8f405bbf91413ba088359f60d/cffi-2.0.0-cp314-cp314t-win_amd64.whl", hash = "sha256:d68b6cef7827e8641e8ef16f4494edda8b36104d79773a334beaa1e3521430f6", size = 191726, upload-time = "2025-09-08T23:23:41.742Z" }, - { url = "https://files.pythonhosted.org/packages/ae/3a/dbeec9d1ee0844c679f6bb5d6ad4e9f198b1224f4e7a32825f47f6192b0c/cffi-2.0.0-cp314-cp314t-win_arm64.whl", hash = "sha256:0a1527a803f0a659de1af2e1fd700213caba79377e27e4693648c2923da066f9", size = 184195, upload-time = "2025-09-08T23:23:43.004Z" }, -] - -[[package]] -name = "charset-normalizer" -version = "3.4.4" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/13/69/33ddede1939fdd074bce5434295f38fae7136463422fe4fd3e0e89b98062/charset_normalizer-3.4.4.tar.gz", hash = "sha256:94537985111c35f28720e43603b8e7b43a6ecfb2ce1d3058bbe955b73404e21a", size = 129418, upload-time = "2025-10-14T04:42:32.879Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/1f/b8/6d51fc1d52cbd52cd4ccedd5b5b2f0f6a11bbf6765c782298b0f3e808541/charset_normalizer-3.4.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:e824f1492727fa856dd6eda4f7cee25f8518a12f3c4a56a74e8095695089cf6d", size = 209709, upload-time = "2025-10-14T04:40:11.385Z" }, - { url = "https://files.pythonhosted.org/packages/5c/af/1f9d7f7faafe2ddfb6f72a2e07a548a629c61ad510fe60f9630309908fef/charset_normalizer-3.4.4-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4bd5d4137d500351a30687c2d3971758aac9a19208fc110ccb9d7188fbe709e8", size = 148814, upload-time = "2025-10-14T04:40:13.135Z" }, - { url = "https://files.pythonhosted.org/packages/79/3d/f2e3ac2bbc056ca0c204298ea4e3d9db9b4afe437812638759db2c976b5f/charset_normalizer-3.4.4-cp310-cp310-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:027f6de494925c0ab2a55eab46ae5129951638a49a34d87f4c3eda90f696b4ad", size = 144467, upload-time = "2025-10-14T04:40:14.728Z" }, - { url = "https://files.pythonhosted.org/packages/ec/85/1bf997003815e60d57de7bd972c57dc6950446a3e4ccac43bc3070721856/charset_normalizer-3.4.4-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:f820802628d2694cb7e56db99213f930856014862f3fd943d290ea8438d07ca8", size = 162280, upload-time = "2025-10-14T04:40:16.14Z" }, - { url = "https://files.pythonhosted.org/packages/3e/8e/6aa1952f56b192f54921c436b87f2aaf7c7a7c3d0d1a765547d64fd83c13/charset_normalizer-3.4.4-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:798d75d81754988d2565bff1b97ba5a44411867c0cf32b77a7e8f8d84796b10d", size = 159454, upload-time = "2025-10-14T04:40:17.567Z" }, - { url = "https://files.pythonhosted.org/packages/36/3b/60cbd1f8e93aa25d1c669c649b7a655b0b5fb4c571858910ea9332678558/charset_normalizer-3.4.4-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9d1bb833febdff5c8927f922386db610b49db6e0d4f4ee29601d71e7c2694313", size = 153609, upload-time = "2025-10-14T04:40:19.08Z" }, - { url = "https://files.pythonhosted.org/packages/64/91/6a13396948b8fd3c4b4fd5bc74d045f5637d78c9675585e8e9fbe5636554/charset_normalizer-3.4.4-cp310-cp310-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:9cd98cdc06614a2f768d2b7286d66805f94c48cde050acdbbb7db2600ab3197e", size = 151849, upload-time = "2025-10-14T04:40:20.607Z" }, - { url = "https://files.pythonhosted.org/packages/b7/7a/59482e28b9981d105691e968c544cc0df3b7d6133152fb3dcdc8f135da7a/charset_normalizer-3.4.4-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:077fbb858e903c73f6c9db43374fd213b0b6a778106bc7032446a8e8b5b38b93", size = 151586, upload-time = "2025-10-14T04:40:21.719Z" }, - { url = "https://files.pythonhosted.org/packages/92/59/f64ef6a1c4bdd2baf892b04cd78792ed8684fbc48d4c2afe467d96b4df57/charset_normalizer-3.4.4-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:244bfb999c71b35de57821b8ea746b24e863398194a4014e4c76adc2bbdfeff0", size = 145290, upload-time = "2025-10-14T04:40:23.069Z" }, - { url = "https://files.pythonhosted.org/packages/6b/63/3bf9f279ddfa641ffa1962b0db6a57a9c294361cc2f5fcac997049a00e9c/charset_normalizer-3.4.4-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:64b55f9dce520635f018f907ff1b0df1fdc31f2795a922fb49dd14fbcdf48c84", size = 163663, upload-time = "2025-10-14T04:40:24.17Z" }, - { url = "https://files.pythonhosted.org/packages/ed/09/c9e38fc8fa9e0849b172b581fd9803bdf6e694041127933934184e19f8c3/charset_normalizer-3.4.4-cp310-cp310-musllinux_1_2_riscv64.whl", hash = "sha256:faa3a41b2b66b6e50f84ae4a68c64fcd0c44355741c6374813a800cd6695db9e", size = 151964, upload-time = "2025-10-14T04:40:25.368Z" }, - { url = "https://files.pythonhosted.org/packages/d2/d1/d28b747e512d0da79d8b6a1ac18b7ab2ecfd81b2944c4c710e166d8dd09c/charset_normalizer-3.4.4-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:6515f3182dbe4ea06ced2d9e8666d97b46ef4c75e326b79bb624110f122551db", size = 161064, upload-time = "2025-10-14T04:40:26.806Z" }, - { url = "https://files.pythonhosted.org/packages/bb/9a/31d62b611d901c3b9e5500c36aab0ff5eb442043fb3a1c254200d3d397d9/charset_normalizer-3.4.4-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:cc00f04ed596e9dc0da42ed17ac5e596c6ccba999ba6bd92b0e0aef2f170f2d6", size = 155015, upload-time = "2025-10-14T04:40:28.284Z" }, - { url = "https://files.pythonhosted.org/packages/1f/f3/107e008fa2bff0c8b9319584174418e5e5285fef32f79d8ee6a430d0039c/charset_normalizer-3.4.4-cp310-cp310-win32.whl", hash = "sha256:f34be2938726fc13801220747472850852fe6b1ea75869a048d6f896838c896f", size = 99792, upload-time = "2025-10-14T04:40:29.613Z" }, - { url = "https://files.pythonhosted.org/packages/eb/66/e396e8a408843337d7315bab30dbf106c38966f1819f123257f5520f8a96/charset_normalizer-3.4.4-cp310-cp310-win_amd64.whl", hash = "sha256:a61900df84c667873b292c3de315a786dd8dac506704dea57bc957bd31e22c7d", size = 107198, upload-time = "2025-10-14T04:40:30.644Z" }, - { url = "https://files.pythonhosted.org/packages/b5/58/01b4f815bf0312704c267f2ccb6e5d42bcc7752340cd487bc9f8c3710597/charset_normalizer-3.4.4-cp310-cp310-win_arm64.whl", hash = "sha256:cead0978fc57397645f12578bfd2d5ea9138ea0fac82b2f63f7f7c6877986a69", size = 100262, upload-time = "2025-10-14T04:40:32.108Z" }, - { url = "https://files.pythonhosted.org/packages/ed/27/c6491ff4954e58a10f69ad90aca8a1b6fe9c5d3c6f380907af3c37435b59/charset_normalizer-3.4.4-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:6e1fcf0720908f200cd21aa4e6750a48ff6ce4afe7ff5a79a90d5ed8a08296f8", size = 206988, upload-time = "2025-10-14T04:40:33.79Z" }, - { url = "https://files.pythonhosted.org/packages/94/59/2e87300fe67ab820b5428580a53cad894272dbb97f38a7a814a2a1ac1011/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5f819d5fe9234f9f82d75bdfa9aef3a3d72c4d24a6e57aeaebba32a704553aa0", size = 147324, upload-time = "2025-10-14T04:40:34.961Z" }, - { url = "https://files.pythonhosted.org/packages/07/fb/0cf61dc84b2b088391830f6274cb57c82e4da8bbc2efeac8c025edb88772/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:a59cb51917aa591b1c4e6a43c132f0cdc3c76dbad6155df4e28ee626cc77a0a3", size = 142742, upload-time = "2025-10-14T04:40:36.105Z" }, - { url = "https://files.pythonhosted.org/packages/62/8b/171935adf2312cd745d290ed93cf16cf0dfe320863ab7cbeeae1dcd6535f/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:8ef3c867360f88ac904fd3f5e1f902f13307af9052646963ee08ff4f131adafc", size = 160863, upload-time = "2025-10-14T04:40:37.188Z" }, - { url = "https://files.pythonhosted.org/packages/09/73/ad875b192bda14f2173bfc1bc9a55e009808484a4b256748d931b6948442/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d9e45d7faa48ee908174d8fe84854479ef838fc6a705c9315372eacbc2f02897", size = 157837, upload-time = "2025-10-14T04:40:38.435Z" }, - { url = "https://files.pythonhosted.org/packages/6d/fc/de9cce525b2c5b94b47c70a4b4fb19f871b24995c728e957ee68ab1671ea/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:840c25fb618a231545cbab0564a799f101b63b9901f2569faecd6b222ac72381", size = 151550, upload-time = "2025-10-14T04:40:40.053Z" }, - { url = "https://files.pythonhosted.org/packages/55/c2/43edd615fdfba8c6f2dfbd459b25a6b3b551f24ea21981e23fb768503ce1/charset_normalizer-3.4.4-cp311-cp311-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:ca5862d5b3928c4940729dacc329aa9102900382fea192fc5e52eb69d6093815", size = 149162, upload-time = "2025-10-14T04:40:41.163Z" }, - { url = "https://files.pythonhosted.org/packages/03/86/bde4ad8b4d0e9429a4e82c1e8f5c659993a9a863ad62c7df05cf7b678d75/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:d9c7f57c3d666a53421049053eaacdd14bbd0a528e2186fcb2e672effd053bb0", size = 150019, upload-time = "2025-10-14T04:40:42.276Z" }, - { url = "https://files.pythonhosted.org/packages/1f/86/a151eb2af293a7e7bac3a739b81072585ce36ccfb4493039f49f1d3cae8c/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:277e970e750505ed74c832b4bf75dac7476262ee2a013f5574dd49075879e161", size = 143310, upload-time = "2025-10-14T04:40:43.439Z" }, - { url = "https://files.pythonhosted.org/packages/b5/fe/43dae6144a7e07b87478fdfc4dbe9efd5defb0e7ec29f5f58a55aeef7bf7/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:31fd66405eaf47bb62e8cd575dc621c56c668f27d46a61d975a249930dd5e2a4", size = 162022, upload-time = "2025-10-14T04:40:44.547Z" }, - { url = "https://files.pythonhosted.org/packages/80/e6/7aab83774f5d2bca81f42ac58d04caf44f0cc2b65fc6db2b3b2e8a05f3b3/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:0d3d8f15c07f86e9ff82319b3d9ef6f4bf907608f53fe9d92b28ea9ae3d1fd89", size = 149383, upload-time = "2025-10-14T04:40:46.018Z" }, - { url = "https://files.pythonhosted.org/packages/4f/e8/b289173b4edae05c0dde07f69f8db476a0b511eac556dfe0d6bda3c43384/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:9f7fcd74d410a36883701fafa2482a6af2ff5ba96b9a620e9e0721e28ead5569", size = 159098, upload-time = "2025-10-14T04:40:47.081Z" }, - { url = "https://files.pythonhosted.org/packages/d8/df/fe699727754cae3f8478493c7f45f777b17c3ef0600e28abfec8619eb49c/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ebf3e58c7ec8a8bed6d66a75d7fb37b55e5015b03ceae72a8e7c74495551e224", size = 152991, upload-time = "2025-10-14T04:40:48.246Z" }, - { url = "https://files.pythonhosted.org/packages/1a/86/584869fe4ddb6ffa3bd9f491b87a01568797fb9bd8933f557dba9771beaf/charset_normalizer-3.4.4-cp311-cp311-win32.whl", hash = "sha256:eecbc200c7fd5ddb9a7f16c7decb07b566c29fa2161a16cf67b8d068bd21690a", size = 99456, upload-time = "2025-10-14T04:40:49.376Z" }, - { url = "https://files.pythonhosted.org/packages/65/f6/62fdd5feb60530f50f7e38b4f6a1d5203f4d16ff4f9f0952962c044e919a/charset_normalizer-3.4.4-cp311-cp311-win_amd64.whl", hash = "sha256:5ae497466c7901d54b639cf42d5b8c1b6a4fead55215500d2f486d34db48d016", size = 106978, upload-time = "2025-10-14T04:40:50.844Z" }, - { url = "https://files.pythonhosted.org/packages/7a/9d/0710916e6c82948b3be62d9d398cb4fcf4e97b56d6a6aeccd66c4b2f2bd5/charset_normalizer-3.4.4-cp311-cp311-win_arm64.whl", hash = "sha256:65e2befcd84bc6f37095f5961e68a6f077bf44946771354a28ad434c2cce0ae1", size = 99969, upload-time = "2025-10-14T04:40:52.272Z" }, - { url = "https://files.pythonhosted.org/packages/f3/85/1637cd4af66fa687396e757dec650f28025f2a2f5a5531a3208dc0ec43f2/charset_normalizer-3.4.4-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:0a98e6759f854bd25a58a73fa88833fba3b7c491169f86ce1180c948ab3fd394", size = 208425, upload-time = "2025-10-14T04:40:53.353Z" }, - { url = "https://files.pythonhosted.org/packages/9d/6a/04130023fef2a0d9c62d0bae2649b69f7b7d8d24ea5536feef50551029df/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b5b290ccc2a263e8d185130284f8501e3e36c5e02750fc6b6bdeb2e9e96f1e25", size = 148162, upload-time = "2025-10-14T04:40:54.558Z" }, - { url = "https://files.pythonhosted.org/packages/78/29/62328d79aa60da22c9e0b9a66539feae06ca0f5a4171ac4f7dc285b83688/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:74bb723680f9f7a6234dcf67aea57e708ec1fbdf5699fb91dfd6f511b0a320ef", size = 144558, upload-time = "2025-10-14T04:40:55.677Z" }, - { url = "https://files.pythonhosted.org/packages/86/bb/b32194a4bf15b88403537c2e120b817c61cd4ecffa9b6876e941c3ee38fe/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:f1e34719c6ed0b92f418c7c780480b26b5d9c50349e9a9af7d76bf757530350d", size = 161497, upload-time = "2025-10-14T04:40:57.217Z" }, - { url = "https://files.pythonhosted.org/packages/19/89/a54c82b253d5b9b111dc74aca196ba5ccfcca8242d0fb64146d4d3183ff1/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:2437418e20515acec67d86e12bf70056a33abdacb5cb1655042f6538d6b085a8", size = 159240, upload-time = "2025-10-14T04:40:58.358Z" }, - { url = "https://files.pythonhosted.org/packages/c0/10/d20b513afe03acc89ec33948320a5544d31f21b05368436d580dec4e234d/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:11d694519d7f29d6cd09f6ac70028dba10f92f6cdd059096db198c283794ac86", size = 153471, upload-time = "2025-10-14T04:40:59.468Z" }, - { url = "https://files.pythonhosted.org/packages/61/fa/fbf177b55bdd727010f9c0a3c49eefa1d10f960e5f09d1d887bf93c2e698/charset_normalizer-3.4.4-cp312-cp312-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:ac1c4a689edcc530fc9d9aa11f5774b9e2f33f9a0c6a57864e90908f5208d30a", size = 150864, upload-time = "2025-10-14T04:41:00.623Z" }, - { url = "https://files.pythonhosted.org/packages/05/12/9fbc6a4d39c0198adeebbde20b619790e9236557ca59fc40e0e3cebe6f40/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:21d142cc6c0ec30d2efee5068ca36c128a30b0f2c53c1c07bd78cb6bc1d3be5f", size = 150647, upload-time = "2025-10-14T04:41:01.754Z" }, - { url = "https://files.pythonhosted.org/packages/ad/1f/6a9a593d52e3e8c5d2b167daf8c6b968808efb57ef4c210acb907c365bc4/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:5dbe56a36425d26d6cfb40ce79c314a2e4dd6211d51d6d2191c00bed34f354cc", size = 145110, upload-time = "2025-10-14T04:41:03.231Z" }, - { url = "https://files.pythonhosted.org/packages/30/42/9a52c609e72471b0fc54386dc63c3781a387bb4fe61c20231a4ebcd58bdd/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:5bfbb1b9acf3334612667b61bd3002196fe2a1eb4dd74d247e0f2a4d50ec9bbf", size = 162839, upload-time = "2025-10-14T04:41:04.715Z" }, - { url = "https://files.pythonhosted.org/packages/c4/5b/c0682bbf9f11597073052628ddd38344a3d673fda35a36773f7d19344b23/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:d055ec1e26e441f6187acf818b73564e6e6282709e9bcb5b63f5b23068356a15", size = 150667, upload-time = "2025-10-14T04:41:05.827Z" }, - { url = "https://files.pythonhosted.org/packages/e4/24/a41afeab6f990cf2daf6cb8c67419b63b48cf518e4f56022230840c9bfb2/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:af2d8c67d8e573d6de5bc30cdb27e9b95e49115cd9baad5ddbd1a6207aaa82a9", size = 160535, upload-time = "2025-10-14T04:41:06.938Z" }, - { url = "https://files.pythonhosted.org/packages/2a/e5/6a4ce77ed243c4a50a1fecca6aaaab419628c818a49434be428fe24c9957/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:780236ac706e66881f3b7f2f32dfe90507a09e67d1d454c762cf642e6e1586e0", size = 154816, upload-time = "2025-10-14T04:41:08.101Z" }, - { url = "https://files.pythonhosted.org/packages/a8/ef/89297262b8092b312d29cdb2517cb1237e51db8ecef2e9af5edbe7b683b1/charset_normalizer-3.4.4-cp312-cp312-win32.whl", hash = "sha256:5833d2c39d8896e4e19b689ffc198f08ea58116bee26dea51e362ecc7cd3ed26", size = 99694, upload-time = "2025-10-14T04:41:09.23Z" }, - { url = "https://files.pythonhosted.org/packages/3d/2d/1e5ed9dd3b3803994c155cd9aacb60c82c331bad84daf75bcb9c91b3295e/charset_normalizer-3.4.4-cp312-cp312-win_amd64.whl", hash = "sha256:a79cfe37875f822425b89a82333404539ae63dbdddf97f84dcbc3d339aae9525", size = 107131, upload-time = "2025-10-14T04:41:10.467Z" }, - { url = "https://files.pythonhosted.org/packages/d0/d9/0ed4c7098a861482a7b6a95603edce4c0d9db2311af23da1fb2b75ec26fc/charset_normalizer-3.4.4-cp312-cp312-win_arm64.whl", hash = "sha256:376bec83a63b8021bb5c8ea75e21c4ccb86e7e45ca4eb81146091b56599b80c3", size = 100390, upload-time = "2025-10-14T04:41:11.915Z" }, - { url = "https://files.pythonhosted.org/packages/97/45/4b3a1239bbacd321068ea6e7ac28875b03ab8bc0aa0966452db17cd36714/charset_normalizer-3.4.4-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:e1f185f86a6f3403aa2420e815904c67b2f9ebc443f045edd0de921108345794", size = 208091, upload-time = "2025-10-14T04:41:13.346Z" }, - { url = "https://files.pythonhosted.org/packages/7d/62/73a6d7450829655a35bb88a88fca7d736f9882a27eacdca2c6d505b57e2e/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6b39f987ae8ccdf0d2642338faf2abb1862340facc796048b604ef14919e55ed", size = 147936, upload-time = "2025-10-14T04:41:14.461Z" }, - { url = "https://files.pythonhosted.org/packages/89/c5/adb8c8b3d6625bef6d88b251bbb0d95f8205831b987631ab0c8bb5d937c2/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:3162d5d8ce1bb98dd51af660f2121c55d0fa541b46dff7bb9b9f86ea1d87de72", size = 144180, upload-time = "2025-10-14T04:41:15.588Z" }, - { url = "https://files.pythonhosted.org/packages/91/ed/9706e4070682d1cc219050b6048bfd293ccf67b3d4f5a4f39207453d4b99/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:81d5eb2a312700f4ecaa977a8235b634ce853200e828fbadf3a9c50bab278328", size = 161346, upload-time = "2025-10-14T04:41:16.738Z" }, - { url = "https://files.pythonhosted.org/packages/d5/0d/031f0d95e4972901a2f6f09ef055751805ff541511dc1252ba3ca1f80cf5/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:5bd2293095d766545ec1a8f612559f6b40abc0eb18bb2f5d1171872d34036ede", size = 158874, upload-time = "2025-10-14T04:41:17.923Z" }, - { url = "https://files.pythonhosted.org/packages/f5/83/6ab5883f57c9c801ce5e5677242328aa45592be8a00644310a008d04f922/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a8a8b89589086a25749f471e6a900d3f662d1d3b6e2e59dcecf787b1cc3a1894", size = 153076, upload-time = "2025-10-14T04:41:19.106Z" }, - { url = "https://files.pythonhosted.org/packages/75/1e/5ff781ddf5260e387d6419959ee89ef13878229732732ee73cdae01800f2/charset_normalizer-3.4.4-cp313-cp313-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:bc7637e2f80d8530ee4a78e878bce464f70087ce73cf7c1caf142416923b98f1", size = 150601, upload-time = "2025-10-14T04:41:20.245Z" }, - { url = "https://files.pythonhosted.org/packages/d7/57/71be810965493d3510a6ca79b90c19e48696fb1ff964da319334b12677f0/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f8bf04158c6b607d747e93949aa60618b61312fe647a6369f88ce2ff16043490", size = 150376, upload-time = "2025-10-14T04:41:21.398Z" }, - { url = "https://files.pythonhosted.org/packages/e5/d5/c3d057a78c181d007014feb7e9f2e65905a6c4ef182c0ddf0de2924edd65/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:554af85e960429cf30784dd47447d5125aaa3b99a6f0683589dbd27e2f45da44", size = 144825, upload-time = "2025-10-14T04:41:22.583Z" }, - { url = "https://files.pythonhosted.org/packages/e6/8c/d0406294828d4976f275ffbe66f00266c4b3136b7506941d87c00cab5272/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:74018750915ee7ad843a774364e13a3db91682f26142baddf775342c3f5b1133", size = 162583, upload-time = "2025-10-14T04:41:23.754Z" }, - { url = "https://files.pythonhosted.org/packages/d7/24/e2aa1f18c8f15c4c0e932d9287b8609dd30ad56dbe41d926bd846e22fb8d/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:c0463276121fdee9c49b98908b3a89c39be45d86d1dbaa22957e38f6321d4ce3", size = 150366, upload-time = "2025-10-14T04:41:25.27Z" }, - { url = "https://files.pythonhosted.org/packages/e4/5b/1e6160c7739aad1e2df054300cc618b06bf784a7a164b0f238360721ab86/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:362d61fd13843997c1c446760ef36f240cf81d3ebf74ac62652aebaf7838561e", size = 160300, upload-time = "2025-10-14T04:41:26.725Z" }, - { url = "https://files.pythonhosted.org/packages/7a/10/f882167cd207fbdd743e55534d5d9620e095089d176d55cb22d5322f2afd/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:9a26f18905b8dd5d685d6d07b0cdf98a79f3c7a918906af7cc143ea2e164c8bc", size = 154465, upload-time = "2025-10-14T04:41:28.322Z" }, - { url = "https://files.pythonhosted.org/packages/89/66/c7a9e1b7429be72123441bfdbaf2bc13faab3f90b933f664db506dea5915/charset_normalizer-3.4.4-cp313-cp313-win32.whl", hash = "sha256:9b35f4c90079ff2e2edc5b26c0c77925e5d2d255c42c74fdb70fb49b172726ac", size = 99404, upload-time = "2025-10-14T04:41:29.95Z" }, - { url = "https://files.pythonhosted.org/packages/c4/26/b9924fa27db384bdcd97ab83b4f0a8058d96ad9626ead570674d5e737d90/charset_normalizer-3.4.4-cp313-cp313-win_amd64.whl", hash = "sha256:b435cba5f4f750aa6c0a0d92c541fb79f69a387c91e61f1795227e4ed9cece14", size = 107092, upload-time = "2025-10-14T04:41:31.188Z" }, - { url = "https://files.pythonhosted.org/packages/af/8f/3ed4bfa0c0c72a7ca17f0380cd9e4dd842b09f664e780c13cff1dcf2ef1b/charset_normalizer-3.4.4-cp313-cp313-win_arm64.whl", hash = "sha256:542d2cee80be6f80247095cc36c418f7bddd14f4a6de45af91dfad36d817bba2", size = 100408, upload-time = "2025-10-14T04:41:32.624Z" }, - { url = "https://files.pythonhosted.org/packages/2a/35/7051599bd493e62411d6ede36fd5af83a38f37c4767b92884df7301db25d/charset_normalizer-3.4.4-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:da3326d9e65ef63a817ecbcc0df6e94463713b754fe293eaa03da99befb9a5bd", size = 207746, upload-time = "2025-10-14T04:41:33.773Z" }, - { url = "https://files.pythonhosted.org/packages/10/9a/97c8d48ef10d6cd4fcead2415523221624bf58bcf68a802721a6bc807c8f/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8af65f14dc14a79b924524b1e7fffe304517b2bff5a58bf64f30b98bbc5079eb", size = 147889, upload-time = "2025-10-14T04:41:34.897Z" }, - { url = "https://files.pythonhosted.org/packages/10/bf/979224a919a1b606c82bd2c5fa49b5c6d5727aa47b4312bb27b1734f53cd/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:74664978bb272435107de04e36db5a9735e78232b85b77d45cfb38f758efd33e", size = 143641, upload-time = "2025-10-14T04:41:36.116Z" }, - { url = "https://files.pythonhosted.org/packages/ba/33/0ad65587441fc730dc7bd90e9716b30b4702dc7b617e6ba4997dc8651495/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:752944c7ffbfdd10c074dc58ec2d5a8a4cd9493b314d367c14d24c17684ddd14", size = 160779, upload-time = "2025-10-14T04:41:37.229Z" }, - { url = "https://files.pythonhosted.org/packages/67/ed/331d6b249259ee71ddea93f6f2f0a56cfebd46938bde6fcc6f7b9a3d0e09/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d1f13550535ad8cff21b8d757a3257963e951d96e20ec82ab44bc64aeb62a191", size = 159035, upload-time = "2025-10-14T04:41:38.368Z" }, - { url = "https://files.pythonhosted.org/packages/67/ff/f6b948ca32e4f2a4576aa129d8bed61f2e0543bf9f5f2b7fc3758ed005c9/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ecaae4149d99b1c9e7b88bb03e3221956f68fd6d50be2ef061b2381b61d20838", size = 152542, upload-time = "2025-10-14T04:41:39.862Z" }, - { url = "https://files.pythonhosted.org/packages/16/85/276033dcbcc369eb176594de22728541a925b2632f9716428c851b149e83/charset_normalizer-3.4.4-cp314-cp314-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:cb6254dc36b47a990e59e1068afacdcd02958bdcce30bb50cc1700a8b9d624a6", size = 149524, upload-time = "2025-10-14T04:41:41.319Z" }, - { url = "https://files.pythonhosted.org/packages/9e/f2/6a2a1f722b6aba37050e626530a46a68f74e63683947a8acff92569f979a/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:c8ae8a0f02f57a6e61203a31428fa1d677cbe50c93622b4149d5c0f319c1d19e", size = 150395, upload-time = "2025-10-14T04:41:42.539Z" }, - { url = "https://files.pythonhosted.org/packages/60/bb/2186cb2f2bbaea6338cad15ce23a67f9b0672929744381e28b0592676824/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:47cc91b2f4dd2833fddaedd2893006b0106129d4b94fdb6af1f4ce5a9965577c", size = 143680, upload-time = "2025-10-14T04:41:43.661Z" }, - { url = "https://files.pythonhosted.org/packages/7d/a5/bf6f13b772fbb2a90360eb620d52ed8f796f3c5caee8398c3b2eb7b1c60d/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:82004af6c302b5d3ab2cfc4cc5f29db16123b1a8417f2e25f9066f91d4411090", size = 162045, upload-time = "2025-10-14T04:41:44.821Z" }, - { url = "https://files.pythonhosted.org/packages/df/c5/d1be898bf0dc3ef9030c3825e5d3b83f2c528d207d246cbabe245966808d/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:2b7d8f6c26245217bd2ad053761201e9f9680f8ce52f0fcd8d0755aeae5b2152", size = 149687, upload-time = "2025-10-14T04:41:46.442Z" }, - { url = "https://files.pythonhosted.org/packages/a5/42/90c1f7b9341eef50c8a1cb3f098ac43b0508413f33affd762855f67a410e/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:799a7a5e4fb2d5898c60b640fd4981d6a25f1c11790935a44ce38c54e985f828", size = 160014, upload-time = "2025-10-14T04:41:47.631Z" }, - { url = "https://files.pythonhosted.org/packages/76/be/4d3ee471e8145d12795ab655ece37baed0929462a86e72372fd25859047c/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:99ae2cffebb06e6c22bdc25801d7b30f503cc87dbd283479e7b606f70aff57ec", size = 154044, upload-time = "2025-10-14T04:41:48.81Z" }, - { url = "https://files.pythonhosted.org/packages/b0/6f/8f7af07237c34a1defe7defc565a9bc1807762f672c0fde711a4b22bf9c0/charset_normalizer-3.4.4-cp314-cp314-win32.whl", hash = "sha256:f9d332f8c2a2fcbffe1378594431458ddbef721c1769d78e2cbc06280d8155f9", size = 99940, upload-time = "2025-10-14T04:41:49.946Z" }, - { url = "https://files.pythonhosted.org/packages/4b/51/8ade005e5ca5b0d80fb4aff72a3775b325bdc3d27408c8113811a7cbe640/charset_normalizer-3.4.4-cp314-cp314-win_amd64.whl", hash = "sha256:8a6562c3700cce886c5be75ade4a5db4214fda19fede41d9792d100288d8f94c", size = 107104, upload-time = "2025-10-14T04:41:51.051Z" }, - { url = "https://files.pythonhosted.org/packages/da/5f/6b8f83a55bb8278772c5ae54a577f3099025f9ade59d0136ac24a0df4bde/charset_normalizer-3.4.4-cp314-cp314-win_arm64.whl", hash = "sha256:de00632ca48df9daf77a2c65a484531649261ec9f25489917f09e455cb09ddb2", size = 100743, upload-time = "2025-10-14T04:41:52.122Z" }, - { url = "https://files.pythonhosted.org/packages/0a/4c/925909008ed5a988ccbb72dcc897407e5d6d3bd72410d69e051fc0c14647/charset_normalizer-3.4.4-py3-none-any.whl", hash = "sha256:7a32c560861a02ff789ad905a2fe94e3f840803362c84fecf1851cb4cf3dc37f", size = 53402, upload-time = "2025-10-14T04:42:31.76Z" }, -] - -[[package]] -name = "chevron" -version = "0.14.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/15/1f/ca74b65b19798895d63a6e92874162f44233467c9e7c1ed8afd19016ebe9/chevron-0.14.0.tar.gz", hash = "sha256:87613aafdf6d77b6a90ff073165a61ae5086e21ad49057aa0e53681601800ebf", size = 11440, upload-time = "2021-01-02T22:47:59.233Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/52/93/342cc62a70ab727e093ed98e02a725d85b746345f05d2b5e5034649f4ec8/chevron-0.14.0-py3-none-any.whl", hash = "sha256:fbf996a709f8da2e745ef763f482ce2d311aa817d287593a5b990d6d6e4f0443", size = 11595, upload-time = "2021-01-02T22:47:57.847Z" }, -] - -[[package]] -name = "click" -version = "8.3.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "colorama", marker = "sys_platform == 'win32'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/46/61/de6cd827efad202d7057d93e0fed9294b96952e188f7384832791c7b2254/click-8.3.0.tar.gz", hash = "sha256:e7b8232224eba16f4ebe410c25ced9f7875cb5f3263ffc93cc3e8da705e229c4", size = 276943, upload-time = "2025-09-18T17:32:23.696Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/db/d3/9dcc0f5797f070ec8edf30fbadfb200e71d9db6b84d211e3b2085a7589a0/click-8.3.0-py3-none-any.whl", hash = "sha256:9b9f285302c6e3064f4330c05f05b81945b2a39544279343e6e7c5f27a9baddc", size = 107295, upload-time = "2025-09-18T17:32:22.42Z" }, -] - -[[package]] -name = "cloudpickle" -version = "3.1.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/52/39/069100b84d7418bc358d81669d5748efb14b9cceacd2f9c75f550424132f/cloudpickle-3.1.1.tar.gz", hash = "sha256:b216fa8ae4019d5482a8ac3c95d8f6346115d8835911fd4aefd1a445e4242c64", size = 22113, upload-time = "2025-01-14T17:02:05.085Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7e/e8/64c37fadfc2816a7701fa8a6ed8d87327c7d54eacfbfb6edab14a2f2be75/cloudpickle-3.1.1-py3-none-any.whl", hash = "sha256:c8c5a44295039331ee9dad40ba100a9c7297b6f988e50e87ccdf3765a668350e", size = 20992, upload-time = "2025-01-14T17:02:02.417Z" }, -] - -[[package]] -name = "colorama" -version = "0.4.6" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/d8/53/6f443c9a4a8358a93a6792e2acffb9d9d5cb0a5cfd8802644b7b1c9a02e4/colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44", size = 27697, upload-time = "2022-10-25T02:36:22.414Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335, upload-time = "2022-10-25T02:36:20.889Z" }, -] - -[[package]] -name = "cryptography" -version = "46.0.3" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "cffi", marker = "platform_python_implementation != 'PyPy'" }, - { name = "typing-extensions", marker = "python_full_version < '3.11'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/9f/33/c00162f49c0e2fe8064a62cb92b93e50c74a72bc370ab92f86112b33ff62/cryptography-46.0.3.tar.gz", hash = "sha256:a8b17438104fed022ce745b362294d9ce35b4c2e45c1d958ad4a4b019285f4a1", size = 749258, upload-time = "2025-10-15T23:18:31.74Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/1d/42/9c391dd801d6cf0d561b5890549d4b27bafcc53b39c31a817e69d87c625b/cryptography-46.0.3-cp311-abi3-macosx_10_9_universal2.whl", hash = "sha256:109d4ddfadf17e8e7779c39f9b18111a09efb969a301a31e987416a0191ed93a", size = 7225004, upload-time = "2025-10-15T23:16:52.239Z" }, - { url = "https://files.pythonhosted.org/packages/1c/67/38769ca6b65f07461eb200e85fc1639b438bdc667be02cf7f2cd6a64601c/cryptography-46.0.3-cp311-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:09859af8466b69bc3c27bdf4f5d84a665e0f7ab5088412e9e2ec49758eca5cbc", size = 4296667, upload-time = "2025-10-15T23:16:54.369Z" }, - { url = "https://files.pythonhosted.org/packages/5c/49/498c86566a1d80e978b42f0d702795f69887005548c041636df6ae1ca64c/cryptography-46.0.3-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:01ca9ff2885f3acc98c29f1860552e37f6d7c7d013d7334ff2a9de43a449315d", size = 4450807, upload-time = "2025-10-15T23:16:56.414Z" }, - { url = "https://files.pythonhosted.org/packages/4b/0a/863a3604112174c8624a2ac3c038662d9e59970c7f926acdcfaed8d61142/cryptography-46.0.3-cp311-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:6eae65d4c3d33da080cff9c4ab1f711b15c1d9760809dad6ea763f3812d254cb", size = 4299615, upload-time = "2025-10-15T23:16:58.442Z" }, - { url = "https://files.pythonhosted.org/packages/64/02/b73a533f6b64a69f3cd3872acb6ebc12aef924d8d103133bb3ea750dc703/cryptography-46.0.3-cp311-abi3-manylinux_2_28_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:e5bf0ed4490068a2e72ac03d786693adeb909981cc596425d09032d372bcc849", size = 4016800, upload-time = "2025-10-15T23:17:00.378Z" }, - { url = "https://files.pythonhosted.org/packages/25/d5/16e41afbfa450cde85a3b7ec599bebefaef16b5c6ba4ec49a3532336ed72/cryptography-46.0.3-cp311-abi3-manylinux_2_28_ppc64le.whl", hash = "sha256:5ecfccd2329e37e9b7112a888e76d9feca2347f12f37918facbb893d7bb88ee8", size = 4984707, upload-time = "2025-10-15T23:17:01.98Z" }, - { url = "https://files.pythonhosted.org/packages/c9/56/e7e69b427c3878352c2fb9b450bd0e19ed552753491d39d7d0a2f5226d41/cryptography-46.0.3-cp311-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:a2c0cd47381a3229c403062f764160d57d4d175e022c1df84e168c6251a22eec", size = 4482541, upload-time = "2025-10-15T23:17:04.078Z" }, - { url = "https://files.pythonhosted.org/packages/78/f6/50736d40d97e8483172f1bb6e698895b92a223dba513b0ca6f06b2365339/cryptography-46.0.3-cp311-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:549e234ff32571b1f4076ac269fcce7a808d3bf98b76c8dd560e42dbc66d7d91", size = 4299464, upload-time = "2025-10-15T23:17:05.483Z" }, - { url = "https://files.pythonhosted.org/packages/00/de/d8e26b1a855f19d9994a19c702fa2e93b0456beccbcfe437eda00e0701f2/cryptography-46.0.3-cp311-abi3-manylinux_2_34_ppc64le.whl", hash = "sha256:c0a7bb1a68a5d3471880e264621346c48665b3bf1c3759d682fc0864c540bd9e", size = 4950838, upload-time = "2025-10-15T23:17:07.425Z" }, - { url = "https://files.pythonhosted.org/packages/8f/29/798fc4ec461a1c9e9f735f2fc58741b0daae30688f41b2497dcbc9ed1355/cryptography-46.0.3-cp311-abi3-manylinux_2_34_x86_64.whl", hash = "sha256:10b01676fc208c3e6feeb25a8b83d81767e8059e1fe86e1dc62d10a3018fa926", size = 4481596, upload-time = "2025-10-15T23:17:09.343Z" }, - { url = "https://files.pythonhosted.org/packages/15/8d/03cd48b20a573adfff7652b76271078e3045b9f49387920e7f1f631d125e/cryptography-46.0.3-cp311-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:0abf1ffd6e57c67e92af68330d05760b7b7efb243aab8377e583284dbab72c71", size = 4426782, upload-time = "2025-10-15T23:17:11.22Z" }, - { url = "https://files.pythonhosted.org/packages/fa/b1/ebacbfe53317d55cf33165bda24c86523497a6881f339f9aae5c2e13e57b/cryptography-46.0.3-cp311-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:a04bee9ab6a4da801eb9b51f1b708a1b5b5c9eb48c03f74198464c66f0d344ac", size = 4698381, upload-time = "2025-10-15T23:17:12.829Z" }, - { url = "https://files.pythonhosted.org/packages/96/92/8a6a9525893325fc057a01f654d7efc2c64b9de90413adcf605a85744ff4/cryptography-46.0.3-cp311-abi3-win32.whl", hash = "sha256:f260d0d41e9b4da1ed1e0f1ce571f97fe370b152ab18778e9e8f67d6af432018", size = 3055988, upload-time = "2025-10-15T23:17:14.65Z" }, - { url = "https://files.pythonhosted.org/packages/7e/bf/80fbf45253ea585a1e492a6a17efcb93467701fa79e71550a430c5e60df0/cryptography-46.0.3-cp311-abi3-win_amd64.whl", hash = "sha256:a9a3008438615669153eb86b26b61e09993921ebdd75385ddd748702c5adfddb", size = 3514451, upload-time = "2025-10-15T23:17:16.142Z" }, - { url = "https://files.pythonhosted.org/packages/2e/af/9b302da4c87b0beb9db4e756386a7c6c5b8003cd0e742277888d352ae91d/cryptography-46.0.3-cp311-abi3-win_arm64.whl", hash = "sha256:5d7f93296ee28f68447397bf5198428c9aeeab45705a55d53a6343455dcb2c3c", size = 2928007, upload-time = "2025-10-15T23:17:18.04Z" }, - { url = "https://files.pythonhosted.org/packages/f5/e2/a510aa736755bffa9d2f75029c229111a1d02f8ecd5de03078f4c18d91a3/cryptography-46.0.3-cp314-cp314t-macosx_10_9_universal2.whl", hash = "sha256:00a5e7e87938e5ff9ff5447ab086a5706a957137e6e433841e9d24f38a065217", size = 7158012, upload-time = "2025-10-15T23:17:19.982Z" }, - { url = "https://files.pythonhosted.org/packages/73/dc/9aa866fbdbb95b02e7f9d086f1fccfeebf8953509b87e3f28fff927ff8a0/cryptography-46.0.3-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:c8daeb2d2174beb4575b77482320303f3d39b8e81153da4f0fb08eb5fe86a6c5", size = 4288728, upload-time = "2025-10-15T23:17:21.527Z" }, - { url = "https://files.pythonhosted.org/packages/c5/fd/bc1daf8230eaa075184cbbf5f8cd00ba9db4fd32d63fb83da4671b72ed8a/cryptography-46.0.3-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:39b6755623145ad5eff1dab323f4eae2a32a77a7abef2c5089a04a3d04366715", size = 4435078, upload-time = "2025-10-15T23:17:23.042Z" }, - { url = "https://files.pythonhosted.org/packages/82/98/d3bd5407ce4c60017f8ff9e63ffee4200ab3e23fe05b765cab805a7db008/cryptography-46.0.3-cp314-cp314t-manylinux_2_28_aarch64.whl", hash = "sha256:db391fa7c66df6762ee3f00c95a89e6d428f4d60e7abc8328f4fe155b5ac6e54", size = 4293460, upload-time = "2025-10-15T23:17:24.885Z" }, - { url = "https://files.pythonhosted.org/packages/26/e9/e23e7900983c2b8af7a08098db406cf989d7f09caea7897e347598d4cd5b/cryptography-46.0.3-cp314-cp314t-manylinux_2_28_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:78a97cf6a8839a48c49271cdcbd5cf37ca2c1d6b7fdd86cc864f302b5e9bf459", size = 3995237, upload-time = "2025-10-15T23:17:26.449Z" }, - { url = "https://files.pythonhosted.org/packages/91/15/af68c509d4a138cfe299d0d7ddb14afba15233223ebd933b4bbdbc7155d3/cryptography-46.0.3-cp314-cp314t-manylinux_2_28_ppc64le.whl", hash = "sha256:dfb781ff7eaa91a6f7fd41776ec37c5853c795d3b358d4896fdbb5df168af422", size = 4967344, upload-time = "2025-10-15T23:17:28.06Z" }, - { url = "https://files.pythonhosted.org/packages/ca/e3/8643d077c53868b681af077edf6b3cb58288b5423610f21c62aadcbe99f4/cryptography-46.0.3-cp314-cp314t-manylinux_2_28_x86_64.whl", hash = "sha256:6f61efb26e76c45c4a227835ddeae96d83624fb0d29eb5df5b96e14ed1a0afb7", size = 4466564, upload-time = "2025-10-15T23:17:29.665Z" }, - { url = "https://files.pythonhosted.org/packages/0e/43/c1e8726fa59c236ff477ff2b5dc071e54b21e5a1e51aa2cee1676f1c986f/cryptography-46.0.3-cp314-cp314t-manylinux_2_34_aarch64.whl", hash = "sha256:23b1a8f26e43f47ceb6d6a43115f33a5a37d57df4ea0ca295b780ae8546e8044", size = 4292415, upload-time = "2025-10-15T23:17:31.686Z" }, - { url = "https://files.pythonhosted.org/packages/42/f9/2f8fefdb1aee8a8e3256a0568cffc4e6d517b256a2fe97a029b3f1b9fe7e/cryptography-46.0.3-cp314-cp314t-manylinux_2_34_ppc64le.whl", hash = "sha256:b419ae593c86b87014b9be7396b385491ad7f320bde96826d0dd174459e54665", size = 4931457, upload-time = "2025-10-15T23:17:33.478Z" }, - { url = "https://files.pythonhosted.org/packages/79/30/9b54127a9a778ccd6d27c3da7563e9f2d341826075ceab89ae3b41bf5be2/cryptography-46.0.3-cp314-cp314t-manylinux_2_34_x86_64.whl", hash = "sha256:50fc3343ac490c6b08c0cf0d704e881d0d660be923fd3076db3e932007e726e3", size = 4466074, upload-time = "2025-10-15T23:17:35.158Z" }, - { url = "https://files.pythonhosted.org/packages/ac/68/b4f4a10928e26c941b1b6a179143af9f4d27d88fe84a6a3c53592d2e76bf/cryptography-46.0.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:22d7e97932f511d6b0b04f2bfd818d73dcd5928db509460aaf48384778eb6d20", size = 4420569, upload-time = "2025-10-15T23:17:37.188Z" }, - { url = "https://files.pythonhosted.org/packages/a3/49/3746dab4c0d1979888f125226357d3262a6dd40e114ac29e3d2abdf1ec55/cryptography-46.0.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:d55f3dffadd674514ad19451161118fd010988540cee43d8bc20675e775925de", size = 4681941, upload-time = "2025-10-15T23:17:39.236Z" }, - { url = "https://files.pythonhosted.org/packages/fd/30/27654c1dbaf7e4a3531fa1fc77986d04aefa4d6d78259a62c9dc13d7ad36/cryptography-46.0.3-cp314-cp314t-win32.whl", hash = "sha256:8a6e050cb6164d3f830453754094c086ff2d0b2f3a897a1d9820f6139a1f0914", size = 3022339, upload-time = "2025-10-15T23:17:40.888Z" }, - { url = "https://files.pythonhosted.org/packages/f6/30/640f34ccd4d2a1bc88367b54b926b781b5a018d65f404d409aba76a84b1c/cryptography-46.0.3-cp314-cp314t-win_amd64.whl", hash = "sha256:760f83faa07f8b64e9c33fc963d790a2edb24efb479e3520c14a45741cd9b2db", size = 3494315, upload-time = "2025-10-15T23:17:42.769Z" }, - { url = "https://files.pythonhosted.org/packages/ba/8b/88cc7e3bd0a8e7b861f26981f7b820e1f46aa9d26cc482d0feba0ecb4919/cryptography-46.0.3-cp314-cp314t-win_arm64.whl", hash = "sha256:516ea134e703e9fe26bcd1277a4b59ad30586ea90c365a87781d7887a646fe21", size = 2919331, upload-time = "2025-10-15T23:17:44.468Z" }, - { url = "https://files.pythonhosted.org/packages/fd/23/45fe7f376a7df8daf6da3556603b36f53475a99ce4faacb6ba2cf3d82021/cryptography-46.0.3-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:cb3d760a6117f621261d662bccc8ef5bc32ca673e037c83fbe565324f5c46936", size = 7218248, upload-time = "2025-10-15T23:17:46.294Z" }, - { url = "https://files.pythonhosted.org/packages/27/32/b68d27471372737054cbd34c84981f9edbc24fe67ca225d389799614e27f/cryptography-46.0.3-cp38-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:4b7387121ac7d15e550f5cb4a43aef2559ed759c35df7336c402bb8275ac9683", size = 4294089, upload-time = "2025-10-15T23:17:48.269Z" }, - { url = "https://files.pythonhosted.org/packages/26/42/fa8389d4478368743e24e61eea78846a0006caffaf72ea24a15159215a14/cryptography-46.0.3-cp38-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:15ab9b093e8f09daab0f2159bb7e47532596075139dd74365da52ecc9cb46c5d", size = 4440029, upload-time = "2025-10-15T23:17:49.837Z" }, - { url = "https://files.pythonhosted.org/packages/5f/eb/f483db0ec5ac040824f269e93dd2bd8a21ecd1027e77ad7bdf6914f2fd80/cryptography-46.0.3-cp38-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:46acf53b40ea38f9c6c229599a4a13f0d46a6c3fa9ef19fc1a124d62e338dfa0", size = 4297222, upload-time = "2025-10-15T23:17:51.357Z" }, - { url = "https://files.pythonhosted.org/packages/fd/cf/da9502c4e1912cb1da3807ea3618a6829bee8207456fbbeebc361ec38ba3/cryptography-46.0.3-cp38-abi3-manylinux_2_28_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:10ca84c4668d066a9878890047f03546f3ae0a6b8b39b697457b7757aaf18dbc", size = 4012280, upload-time = "2025-10-15T23:17:52.964Z" }, - { url = "https://files.pythonhosted.org/packages/6b/8f/9adb86b93330e0df8b3dcf03eae67c33ba89958fc2e03862ef1ac2b42465/cryptography-46.0.3-cp38-abi3-manylinux_2_28_ppc64le.whl", hash = "sha256:36e627112085bb3b81b19fed209c05ce2a52ee8b15d161b7c643a7d5a88491f3", size = 4978958, upload-time = "2025-10-15T23:17:54.965Z" }, - { url = "https://files.pythonhosted.org/packages/d1/a0/5fa77988289c34bdb9f913f5606ecc9ada1adb5ae870bd0d1054a7021cc4/cryptography-46.0.3-cp38-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:1000713389b75c449a6e979ffc7dcc8ac90b437048766cef052d4d30b8220971", size = 4473714, upload-time = "2025-10-15T23:17:56.754Z" }, - { url = "https://files.pythonhosted.org/packages/14/e5/fc82d72a58d41c393697aa18c9abe5ae1214ff6f2a5c18ac470f92777895/cryptography-46.0.3-cp38-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:b02cf04496f6576afffef5ddd04a0cb7d49cf6be16a9059d793a30b035f6b6ac", size = 4296970, upload-time = "2025-10-15T23:17:58.588Z" }, - { url = "https://files.pythonhosted.org/packages/78/06/5663ed35438d0b09056973994f1aec467492b33bd31da36e468b01ec1097/cryptography-46.0.3-cp38-abi3-manylinux_2_34_ppc64le.whl", hash = "sha256:71e842ec9bc7abf543b47cf86b9a743baa95f4677d22baa4c7d5c69e49e9bc04", size = 4940236, upload-time = "2025-10-15T23:18:00.897Z" }, - { url = "https://files.pythonhosted.org/packages/fc/59/873633f3f2dcd8a053b8dd1d38f783043b5fce589c0f6988bf55ef57e43e/cryptography-46.0.3-cp38-abi3-manylinux_2_34_x86_64.whl", hash = "sha256:402b58fc32614f00980b66d6e56a5b4118e6cb362ae8f3fda141ba4689bd4506", size = 4472642, upload-time = "2025-10-15T23:18:02.749Z" }, - { url = "https://files.pythonhosted.org/packages/3d/39/8e71f3930e40f6877737d6f69248cf74d4e34b886a3967d32f919cc50d3b/cryptography-46.0.3-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:ef639cb3372f69ec44915fafcd6698b6cc78fbe0c2ea41be867f6ed612811963", size = 4423126, upload-time = "2025-10-15T23:18:04.85Z" }, - { url = "https://files.pythonhosted.org/packages/cd/c7/f65027c2810e14c3e7268353b1681932b87e5a48e65505d8cc17c99e36ae/cryptography-46.0.3-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:3b51b8ca4f1c6453d8829e1eb7299499ca7f313900dd4d89a24b8b87c0a780d4", size = 4686573, upload-time = "2025-10-15T23:18:06.908Z" }, - { url = "https://files.pythonhosted.org/packages/0a/6e/1c8331ddf91ca4730ab3086a0f1be19c65510a33b5a441cb334e7a2d2560/cryptography-46.0.3-cp38-abi3-win32.whl", hash = "sha256:6276eb85ef938dc035d59b87c8a7dc559a232f954962520137529d77b18ff1df", size = 3036695, upload-time = "2025-10-15T23:18:08.672Z" }, - { url = "https://files.pythonhosted.org/packages/90/45/b0d691df20633eff80955a0fc7695ff9051ffce8b69741444bd9ed7bd0db/cryptography-46.0.3-cp38-abi3-win_amd64.whl", hash = "sha256:416260257577718c05135c55958b674000baef9a1c7d9e8f306ec60d71db850f", size = 3501720, upload-time = "2025-10-15T23:18:10.632Z" }, - { url = "https://files.pythonhosted.org/packages/e8/cb/2da4cc83f5edb9c3257d09e1e7ab7b23f049c7962cae8d842bbef0a9cec9/cryptography-46.0.3-cp38-abi3-win_arm64.whl", hash = "sha256:d89c3468de4cdc4f08a57e214384d0471911a3830fcdaf7a8cc587e42a866372", size = 2918740, upload-time = "2025-10-15T23:18:12.277Z" }, - { url = "https://files.pythonhosted.org/packages/d9/cd/1a8633802d766a0fa46f382a77e096d7e209e0817892929655fe0586ae32/cryptography-46.0.3-pp310-pypy310_pp73-macosx_10_9_x86_64.whl", hash = "sha256:a23582810fedb8c0bc47524558fb6c56aac3fc252cb306072fd2815da2a47c32", size = 3689163, upload-time = "2025-10-15T23:18:13.821Z" }, - { url = "https://files.pythonhosted.org/packages/4c/59/6b26512964ace6480c3e54681a9859c974172fb141c38df11eadd8416947/cryptography-46.0.3-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:e7aec276d68421f9574040c26e2a7c3771060bc0cff408bae1dcb19d3ab1e63c", size = 3429474, upload-time = "2025-10-15T23:18:15.477Z" }, - { url = "https://files.pythonhosted.org/packages/06/8a/e60e46adab4362a682cf142c7dcb5bf79b782ab2199b0dcb81f55970807f/cryptography-46.0.3-pp311-pypy311_pp73-macosx_10_9_x86_64.whl", hash = "sha256:7ce938a99998ed3c8aa7e7272dca1a610401ede816d36d0693907d863b10d9ea", size = 3698132, upload-time = "2025-10-15T23:18:17.056Z" }, - { url = "https://files.pythonhosted.org/packages/da/38/f59940ec4ee91e93d3311f7532671a5cef5570eb04a144bf203b58552d11/cryptography-46.0.3-pp311-pypy311_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:191bb60a7be5e6f54e30ba16fdfae78ad3a342a0599eb4193ba88e3f3d6e185b", size = 4243992, upload-time = "2025-10-15T23:18:18.695Z" }, - { url = "https://files.pythonhosted.org/packages/b0/0c/35b3d92ddebfdfda76bb485738306545817253d0a3ded0bfe80ef8e67aa5/cryptography-46.0.3-pp311-pypy311_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:c70cc23f12726be8f8bc72e41d5065d77e4515efae3690326764ea1b07845cfb", size = 4409944, upload-time = "2025-10-15T23:18:20.597Z" }, - { url = "https://files.pythonhosted.org/packages/99/55/181022996c4063fc0e7666a47049a1ca705abb9c8a13830f074edb347495/cryptography-46.0.3-pp311-pypy311_pp73-manylinux_2_34_aarch64.whl", hash = "sha256:9394673a9f4de09e28b5356e7fff97d778f8abad85c9d5ac4a4b7e25a0de7717", size = 4242957, upload-time = "2025-10-15T23:18:22.18Z" }, - { url = "https://files.pythonhosted.org/packages/ba/af/72cd6ef29f9c5f731251acadaeb821559fe25f10852f44a63374c9ca08c1/cryptography-46.0.3-pp311-pypy311_pp73-manylinux_2_34_x86_64.whl", hash = "sha256:94cd0549accc38d1494e1f8de71eca837d0509d0d44bf11d158524b0e12cebf9", size = 4409447, upload-time = "2025-10-15T23:18:24.209Z" }, - { url = "https://files.pythonhosted.org/packages/0d/c3/e90f4a4feae6410f914f8ebac129b9ae7a8c92eb60a638012dde42030a9d/cryptography-46.0.3-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:6b5063083824e5509fdba180721d55909ffacccc8adbec85268b48439423d78c", size = 3438528, upload-time = "2025-10-15T23:18:26.227Z" }, -] - -[[package]] -name = "docstring-parser" -version = "0.17.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/b2/9d/c3b43da9515bd270df0f80548d9944e389870713cc1fe2b8fb35fe2bcefd/docstring_parser-0.17.0.tar.gz", hash = "sha256:583de4a309722b3315439bb31d64ba3eebada841f2e2cee23b99df001434c912", size = 27442, upload-time = "2025-07-21T07:35:01.868Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/55/e2/2537ebcff11c1ee1ff17d8d0b6f4db75873e3b0fb32c2d4a2ee31ecb310a/docstring_parser-0.17.0-py3-none-any.whl", hash = "sha256:cf2569abd23dce8099b300f9b4fa8191e9582dda731fd533daf54c4551658708", size = 36896, upload-time = "2025-07-21T07:35:00.684Z" }, -] - -[[package]] -name = "exceptiongroup" -version = "1.3.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/0b/9f/a65090624ecf468cdca03533906e7c69ed7588582240cfe7cc9e770b50eb/exceptiongroup-1.3.0.tar.gz", hash = "sha256:b241f5885f560bc56a59ee63ca4c6a8bfa46ae4ad651af316d4e81817bb9fd88", size = 29749, upload-time = "2025-05-10T17:42:51.123Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/36/f4/c6e662dade71f56cd2f3735141b265c3c79293c109549c1e6933b0651ffc/exceptiongroup-1.3.0-py3-none-any.whl", hash = "sha256:4d111e6e0c13d0644cad6ddaa7ed0261a0b36971f6d23e7ec9b4b9097da78a10", size = 16674, upload-time = "2025-05-10T17:42:49.33Z" }, -] - -[[package]] -name = "fastapi" -version = "0.120.4" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "annotated-doc" }, - { name = "pydantic" }, - { name = "starlette" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/3f/3a/0bf90d5189d7f62dc2bd0523899629ca59b58ff4290d631cd3bb5c8889d4/fastapi-0.120.4.tar.gz", hash = "sha256:2d856bc847893ca4d77896d4504ffdec0fb04312b705065fca9104428eca3868", size = 339716, upload-time = "2025-10-31T18:37:28.81Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ed/47/14a76b926edc3957c8a8258423db789d3fa925d2fed800102fce58959413/fastapi-0.120.4-py3-none-any.whl", hash = "sha256:9bdf192308676480d3593e10fd05094e56d6fdc7d9283db26053d8104d5f82a0", size = 108235, upload-time = "2025-10-31T18:37:27.038Z" }, -] - -[[package]] -name = "gitdb" -version = "4.0.12" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "smmap" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/72/94/63b0fc47eb32792c7ba1fe1b694daec9a63620db1e313033d18140c2320a/gitdb-4.0.12.tar.gz", hash = "sha256:5ef71f855d191a3326fcfbc0d5da835f26b13fbcba60c32c21091c349ffdb571", size = 394684, upload-time = "2025-01-02T07:20:46.413Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a0/61/5c78b91c3143ed5c14207f463aecfc8f9dbb5092fb2869baf37c273b2705/gitdb-4.0.12-py3-none-any.whl", hash = "sha256:67073e15955400952c6565cc3e707c554a4eea2e428946f7a4c162fab9bd9bcf", size = 62794, upload-time = "2025-01-02T07:20:43.624Z" }, -] - -[[package]] -name = "gitpython" -version = "3.1.45" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "gitdb" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/9a/c8/dd58967d119baab745caec2f9d853297cec1989ec1d63f677d3880632b88/gitpython-3.1.45.tar.gz", hash = "sha256:85b0ee964ceddf211c41b9f27a49086010a190fd8132a24e21f362a4b36a791c", size = 215076, upload-time = "2025-07-24T03:45:54.871Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/01/61/d4b89fec821f72385526e1b9d9a3a0385dda4a72b206d28049e2c7cd39b8/gitpython-3.1.45-py3-none-any.whl", hash = "sha256:8908cb2e02fb3b93b7eb0f2827125cb699869470432cc885f019b8fd0fccff77", size = 208168, upload-time = "2025-07-24T03:45:52.517Z" }, -] - -[[package]] -name = "google-adk" -version = "1.17.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "absolufy-imports" }, - { name = "anyio" }, - { name = "authlib" }, - { name = "click" }, - { name = "fastapi" }, - { name = "google-api-python-client" }, - { name = "google-cloud-aiplatform", extra = ["agent-engines"] }, - { name = "google-cloud-bigtable" }, - { name = "google-cloud-discoveryengine" }, - { name = "google-cloud-secret-manager" }, - { name = "google-cloud-spanner" }, - { name = "google-cloud-speech" }, - { name = "google-cloud-storage" }, - { name = "google-genai" }, - { name = "graphviz" }, - { name = "mcp" }, - { name = "opentelemetry-api" }, - { name = "opentelemetry-exporter-gcp-logging" }, - { name = "opentelemetry-exporter-gcp-monitoring" }, - { name = "opentelemetry-exporter-gcp-trace" }, - { name = "opentelemetry-exporter-otlp-proto-http" }, - { name = "opentelemetry-resourcedetector-gcp" }, - { name = "opentelemetry-sdk" }, - { name = "pydantic" }, - { name = "python-dateutil" }, - { name = "python-dotenv" }, - { name = "pyyaml" }, - { name = "requests" }, - { name = "sqlalchemy" }, - { name = "sqlalchemy-spanner" }, - { name = "starlette" }, - { name = "tenacity" }, - { name = "typing-extensions" }, - { name = "tzlocal" }, - { name = "uvicorn" }, - { name = "watchdog" }, - { name = "websockets" }, -] -wheels = [ - { url = "https://files.pythonhosted.org/packages/1f/6e/5aadd9d4afd69ecd546d4ae02fdaf1eb29e1d1a5c84d1ae1d16906271d43/google_adk-1.17.0-py3-none-any.whl", hash = "sha256:1d32b425087bd57015b18c86f9850366fd5ea6a805bbcd147493750438ed6276", size = 2035820, upload-time = "2025-10-22T20:39:09.242Z" }, -] - -[[package]] -name = "google-api-core" -version = "2.28.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-auth" }, - { name = "googleapis-common-protos" }, - { name = "proto-plus" }, - { name = "protobuf" }, - { name = "requests" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/61/da/83d7043169ac2c8c7469f0e375610d78ae2160134bf1b80634c482fa079c/google_api_core-2.28.1.tar.gz", hash = "sha256:2b405df02d68e68ce0fbc138559e6036559e685159d148ae5861013dc201baf8", size = 176759, upload-time = "2025-10-28T21:34:51.529Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ed/d4/90197b416cb61cefd316964fd9e7bd8324bcbafabf40eef14a9f20b81974/google_api_core-2.28.1-py3-none-any.whl", hash = "sha256:4021b0f8ceb77a6fb4de6fde4502cecab45062e66ff4f2895169e0b35bc9466c", size = 173706, upload-time = "2025-10-28T21:34:50.151Z" }, -] - -[package.optional-dependencies] -grpc = [ - { name = "grpcio" }, - { name = "grpcio-status" }, -] - -[[package]] -name = "google-api-python-client" -version = "2.186.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core" }, - { name = "google-auth" }, - { name = "google-auth-httplib2" }, - { name = "httplib2" }, - { name = "uritemplate" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/47/cf/d167fec8be9e65768133be83a8d182350195840e14d1c203565383834614/google_api_python_client-2.186.0.tar.gz", hash = "sha256:01b8ff446adbc10f495188400a9f7c3e88e5e75741663a25822f41e788475333", size = 13937230, upload-time = "2025-10-30T22:13:20.971Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/21/5a/b00b944eb9cd0f2e39daf3bcce006cb503a89532f507e87e038e04bbea8c/google_api_python_client-2.186.0-py3-none-any.whl", hash = "sha256:2ea4beba93e193d3a632c7bf865b6ccace42b0017269a964566e39b7e1f3cf79", size = 14507868, upload-time = "2025-10-30T22:13:18.426Z" }, -] - -[[package]] -name = "google-auth" -version = "2.42.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "cachetools" }, - { name = "pyasn1-modules" }, - { name = "rsa" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/25/6b/22a77135757c3a7854c9f008ffed6bf4e8851616d77faf13147e9ab5aae6/google_auth-2.42.1.tar.gz", hash = "sha256:30178b7a21aa50bffbdc1ffcb34ff770a2f65c712170ecd5446c4bef4dc2b94e", size = 295541, upload-time = "2025-10-30T16:42:19.381Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/92/05/adeb6c495aec4f9d93f9e2fc29eeef6e14d452bba11d15bdb874ce1d5b10/google_auth-2.42.1-py2.py3-none-any.whl", hash = "sha256:eb73d71c91fc95dbd221a2eb87477c278a355e7367a35c0d84e6b0e5f9b4ad11", size = 222550, upload-time = "2025-10-30T16:42:17.878Z" }, -] - -[[package]] -name = "google-auth-httplib2" -version = "0.2.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-auth" }, - { name = "httplib2" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/e0/83/7ef576d1c7ccea214e7b001e69c006bc75e058a3a1f2ab810167204b698b/google_auth_httplib2-0.2.1.tar.gz", hash = "sha256:5ef03be3927423c87fb69607b42df23a444e434ddb2555b73b3679793187b7de", size = 11086, upload-time = "2025-10-30T21:13:16.569Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/44/a7/ca23dd006255f70e2bc469d3f9f0c82ea455335bfd682ad4d677adc435de/google_auth_httplib2-0.2.1-py3-none-any.whl", hash = "sha256:1be94c611db91c01f9703e7f62b0a59bbd5587a95571c7b6fade510d648bc08b", size = 9525, upload-time = "2025-10-30T21:13:15.758Z" }, -] - -[[package]] -name = "google-cloud-aiplatform" -version = "1.124.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "docstring-parser" }, - { name = "google-api-core", extra = ["grpc"] }, - { name = "google-auth" }, - { name = "google-cloud-bigquery" }, - { name = "google-cloud-resource-manager" }, - { name = "google-cloud-storage" }, - { name = "google-genai" }, - { name = "packaging" }, - { name = "proto-plus" }, - { name = "protobuf" }, - { name = "pydantic" }, - { name = "shapely" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/d7/ad/a3da0cbb78a933544ef2ca3db3da242a2217a52d823beb3ea129995c00df/google_cloud_aiplatform-1.124.0.tar.gz", hash = "sha256:cf565f2ce3dac19c6502a65d89c89760000fde1d531be54949c6232ba2a168fd", size = 9755170, upload-time = "2025-10-30T19:59:22.057Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/c5/46/c20db72a9389c5b6595c2c3fed9abe2b05d3658fe2c07657f7324623cb63/google_cloud_aiplatform-1.124.0-py2.py3-none-any.whl", hash = "sha256:047685f0ee0ab7346ba7d437904357077e3362b32a951c5038a9ac789c5f9148", size = 8112493, upload-time = "2025-10-30T19:59:19.42Z" }, -] - -[package.optional-dependencies] -agent-engines = [ - { name = "cloudpickle" }, - { name = "google-cloud-logging" }, - { name = "google-cloud-trace" }, - { name = "opentelemetry-exporter-gcp-trace" }, - { name = "opentelemetry-sdk" }, - { name = "packaging" }, - { name = "pydantic" }, - { name = "typing-extensions" }, -] - -[[package]] -name = "google-cloud-appengine-logging" -version = "1.7.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core", extra = ["grpc"] }, - { name = "google-auth" }, - { name = "grpcio" }, - { name = "proto-plus" }, - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/9a/6e/260266e5fa7283b721bbef012f3223d514e2569446f56786fe0c80aa0fd4/google_cloud_appengine_logging-1.7.0.tar.gz", hash = "sha256:ea9ce73430cfc99f8957fd7df97733f9a759d4caab65e19d63a7474f012ffd94", size = 16729, upload-time = "2025-10-17T02:33:40.842Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/24/45/99bb629a23639d868c693748598796d7f8e60f62289795b6f310d3328b19/google_cloud_appengine_logging-1.7.0-py3-none-any.whl", hash = "sha256:cfd28bc61a030008381a646d112ebe2734bf72abc8c12afc47d035a2c9b041fe", size = 16924, upload-time = "2025-10-17T02:30:48.802Z" }, -] - -[[package]] -name = "google-cloud-audit-log" -version = "0.4.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "googleapis-common-protos" }, - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/c7/d2/ad96950410f8a05e921a6da2e1a6ba4aeca674bbb5dda8200c3c7296d7ad/google_cloud_audit_log-0.4.0.tar.gz", hash = "sha256:8467d4dcca9f3e6160520c24d71592e49e874838f174762272ec10e7950b6feb", size = 44682, upload-time = "2025-10-17T02:33:44.641Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/9b/25/532886995f11102ad6de290496de5db227bd3a73827702445928ad32edcb/google_cloud_audit_log-0.4.0-py3-none-any.whl", hash = "sha256:6b88e2349df45f8f4cc0993b687109b1388da1571c502dc1417efa4b66ec55e0", size = 44890, upload-time = "2025-10-17T02:30:55.11Z" }, -] - -[[package]] -name = "google-cloud-bigquery" -version = "3.38.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core", extra = ["grpc"] }, - { name = "google-auth" }, - { name = "google-cloud-core" }, - { name = "google-resumable-media" }, - { name = "packaging" }, - { name = "python-dateutil" }, - { name = "requests" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/07/b2/a17e40afcf9487e3d17db5e36728ffe75c8d5671c46f419d7b6528a5728a/google_cloud_bigquery-3.38.0.tar.gz", hash = "sha256:8afcb7116f5eac849097a344eb8bfda78b7cfaae128e60e019193dd483873520", size = 503666, upload-time = "2025-09-17T20:33:33.47Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/39/3c/c8cada9ec282b29232ed9aed5a0b5cca6cf5367cb2ffa8ad0d2583d743f1/google_cloud_bigquery-3.38.0-py3-none-any.whl", hash = "sha256:e06e93ff7b245b239945ef59cb59616057598d369edac457ebf292bd61984da6", size = 259257, upload-time = "2025-09-17T20:33:31.404Z" }, -] - -[[package]] -name = "google-cloud-bigtable" -version = "2.34.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core", extra = ["grpc"] }, - { name = "google-auth" }, - { name = "google-cloud-core" }, - { name = "google-crc32c" }, - { name = "grpc-google-iam-v1" }, - { name = "proto-plus" }, - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/29/20/8a29e1d5858ba76f443dc527a223e769347b915cb060a9f19250241aa38a/google_cloud_bigtable-2.34.0.tar.gz", hash = "sha256:773258b00cd3f9a3a35639cc38bd711f4f1418aaa0c8d70cb028978ed98dc2c2", size = 766606, upload-time = "2025-10-22T19:04:53.645Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/55/6d/aa44110504b4b9d125f1cc9715b72a178ebbe5cb79698e7a95893c391e56/google_cloud_bigtable-2.34.0-py3-none-any.whl", hash = "sha256:a4a8db4903840cd3f89fb19c060eea2e7c09c1265cb0538cfc11288dbc6000e4", size = 537041, upload-time = "2025-10-22T19:04:52.014Z" }, -] - -[[package]] -name = "google-cloud-core" -version = "2.5.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core" }, - { name = "google-auth" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/a6/03/ef0bc99d0e0faf4fdbe67ac445e18cdaa74824fd93cd069e7bb6548cb52d/google_cloud_core-2.5.0.tar.gz", hash = "sha256:7c1b7ef5c92311717bd05301aa1a91ffbc565673d3b0b4163a52d8413a186963", size = 36027, upload-time = "2025-10-29T23:17:39.513Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/89/20/bfa472e327c8edee00f04beecc80baeddd2ab33ee0e86fd7654da49d45e9/google_cloud_core-2.5.0-py3-none-any.whl", hash = "sha256:67d977b41ae6c7211ee830c7912e41003ea8194bff15ae7d72fd6f51e57acabc", size = 29469, upload-time = "2025-10-29T23:17:38.548Z" }, -] - -[[package]] -name = "google-cloud-discoveryengine" -version = "0.13.12" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core", extra = ["grpc"] }, - { name = "google-auth" }, - { name = "proto-plus" }, - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/8f/cd/b33bbc4b096d937abee5ebfad3908b2bdc65acd1582191aa33beaa2b70a5/google_cloud_discoveryengine-0.13.12.tar.gz", hash = "sha256:d6b9f8fadd8ad0d2f4438231c5eb7772a317e9f59cafbcbadc19b5d54c609419", size = 3582382, upload-time = "2025-09-22T16:51:14.052Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/93/70/607f6011648f603d35e60a16c34aee68a0b39510e4268d4859f3268684f9/google_cloud_discoveryengine-0.13.12-py3-none-any.whl", hash = "sha256:295f8c6df3fb26b90fb82c2cd6fbcf4b477661addcb19a94eea16463a5c4e041", size = 3337248, upload-time = "2025-09-22T16:50:57.375Z" }, -] - -[[package]] -name = "google-cloud-logging" -version = "3.12.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core", extra = ["grpc"] }, - { name = "google-auth" }, - { name = "google-cloud-appengine-logging" }, - { name = "google-cloud-audit-log" }, - { name = "google-cloud-core" }, - { name = "grpc-google-iam-v1" }, - { name = "opentelemetry-api" }, - { name = "proto-plus" }, - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/14/9c/d42ecc94f795a6545930e5f846a7ae59ff685ded8bc086648dd2bee31a1a/google_cloud_logging-3.12.1.tar.gz", hash = "sha256:36efc823985055b203904e83e1c8f9f999b3c64270bcda39d57386ca4effd678", size = 289569, upload-time = "2025-04-22T20:50:24.71Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b1/41/f8a3197d39b773a91f335dee36c92ef26a8ec96efe78d64baad89d367df4/google_cloud_logging-3.12.1-py2.py3-none-any.whl", hash = "sha256:6817878af76ec4e7568976772839ab2c43ddfd18fbbf2ce32b13ef549cd5a862", size = 229466, upload-time = "2025-04-22T20:50:23.294Z" }, -] - -[[package]] -name = "google-cloud-monitoring" -version = "2.28.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core", extra = ["grpc"] }, - { name = "google-auth" }, - { name = "grpcio" }, - { name = "proto-plus" }, - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/bc/b8/7f68a7738cbfef610af532b2fc758e39d852fc93ed3a31bd0e76fd45d2fd/google_cloud_monitoring-2.28.0.tar.gz", hash = "sha256:25175590907e038add644b5b744941d221776342924637095a879973a7c0ac37", size = 393321, upload-time = "2025-10-14T15:42:55.786Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ad/d3/02dcf5376cb4b47b9c06eba36d80700d5b0a1510f3fcd47d3abbe4b0f0a3/google_cloud_monitoring-2.28.0-py3-none-any.whl", hash = "sha256:64f4c57cc465dd51cceffe559f0ec6fa9f96aa6d82790cd8d3af6d5cc3795160", size = 384670, upload-time = "2025-10-14T15:42:41.911Z" }, -] - -[[package]] -name = "google-cloud-resource-manager" -version = "1.15.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core", extra = ["grpc"] }, - { name = "google-auth" }, - { name = "grpc-google-iam-v1" }, - { name = "grpcio" }, - { name = "proto-plus" }, - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/fc/19/b95d0e8814ce42522e434cdd85c0cb6236d874d9adf6685fc8e6d1fda9d1/google_cloud_resource_manager-1.15.0.tar.gz", hash = "sha256:3d0b78c3daa713f956d24e525b35e9e9a76d597c438837171304d431084cedaf", size = 449227, upload-time = "2025-10-20T14:57:01.108Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/8c/93/5aef41a5f146ad4559dd7040ae5fa8e7ddcab4dfadbef6cb4b66d775e690/google_cloud_resource_manager-1.15.0-py3-none-any.whl", hash = "sha256:0ccde5db644b269ddfdf7b407a2c7b60bdbf459f8e666344a5285601d00c7f6d", size = 397151, upload-time = "2025-10-20T14:53:45.409Z" }, -] - -[[package]] -name = "google-cloud-secret-manager" -version = "2.25.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core", extra = ["grpc"] }, - { name = "google-auth" }, - { name = "grpc-google-iam-v1" }, - { name = "grpcio" }, - { name = "proto-plus" }, - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/c3/7c/be2d11415eec83c400d315cf9876ba29742bc7af90df391d357763463cd2/google_cloud_secret_manager-2.25.0.tar.gz", hash = "sha256:a3792bb1cb307326908297a61536031ac94852c22248f04ae112ff51a853b561", size = 269853, upload-time = "2025-10-14T15:42:59.511Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/fe/74/bf87966a6ee48c98d1b8a6a1839256911e9a2a205be76b21e54f58171615/google_cloud_secret_manager-2.25.0-py3-none-any.whl", hash = "sha256:eaf1adce3ff5dc0f24335709eba3410dc7e9d20aeea3e8df5b758e27080ebf14", size = 218548, upload-time = "2025-10-14T15:42:47.839Z" }, -] - -[[package]] -name = "google-cloud-spanner" -version = "3.59.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core", extra = ["grpc"] }, - { name = "google-cloud-core" }, - { name = "grpc-google-iam-v1" }, - { name = "grpc-interceptor" }, - { name = "proto-plus" }, - { name = "protobuf" }, - { name = "sqlparse" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/df/62/f0e535875e49b34128710342115681fe1a97f45759e1427307ab150a4caa/google_cloud_spanner-3.59.0.tar.gz", hash = "sha256:dec7a78bfe1f94aef508ff9c61dba4196f3c70c83a0f75c271b4652686d08641", size = 705137, upload-time = "2025-10-23T09:35:49.885Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d8/08/1a38139853364b4737e3a0e03a3fd87d60c7545e90a963a8a6457777b5f9/google_cloud_spanner-3.59.0-py3-none-any.whl", hash = "sha256:409ed9746787c9435fd015731a5e3cf6f3ea2995a807c580f4216bb5d464260a", size = 502645, upload-time = "2025-10-23T09:35:47.954Z" }, -] - -[[package]] -name = "google-cloud-speech" -version = "2.34.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core", extra = ["grpc"] }, - { name = "google-auth" }, - { name = "grpcio" }, - { name = "proto-plus" }, - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/b7/c2/500c58a7e3008cb77da01a2f2a8284ac55c808545d18551c62a031ff548d/google_cloud_speech-2.34.0.tar.gz", hash = "sha256:2a7bffd84f134b9b70c9f11cbb5088c534f92be149d71d9073d0b9dd3a431acf", size = 391496, upload-time = "2025-10-20T14:57:17.127Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/78/4c/8c52951a4078f4b181917c37a2610e69c0b24a10567d0182bf089a933c35/google_cloud_speech-2.34.0-py3-none-any.whl", hash = "sha256:cc0c6c0fda9306fee01c998bc207b68f71e0a3247121a5a3a27daabacd3a8c98", size = 336614, upload-time = "2025-10-20T14:54:05.004Z" }, -] - -[[package]] -name = "google-cloud-storage" -version = "2.19.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core" }, - { name = "google-auth" }, - { name = "google-cloud-core" }, - { name = "google-crc32c" }, - { name = "google-resumable-media" }, - { name = "requests" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/36/76/4d965702e96bb67976e755bed9828fa50306dca003dbee08b67f41dd265e/google_cloud_storage-2.19.0.tar.gz", hash = "sha256:cd05e9e7191ba6cb68934d8eb76054d9be4562aa89dbc4236feee4d7d51342b2", size = 5535488, upload-time = "2024-12-05T01:35:06.49Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d5/94/6db383d8ee1adf45dc6c73477152b82731fa4c4a46d9c1932cc8757e0fd4/google_cloud_storage-2.19.0-py2.py3-none-any.whl", hash = "sha256:aeb971b5c29cf8ab98445082cbfe7b161a1f48ed275822f59ed3f1524ea54fba", size = 131787, upload-time = "2024-12-05T01:35:04.736Z" }, -] - -[[package]] -name = "google-cloud-trace" -version = "1.17.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-api-core", extra = ["grpc"] }, - { name = "google-auth" }, - { name = "grpcio" }, - { name = "proto-plus" }, - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/5e/89/5ecbcf7d2d37ead01fc84e774bc758638855c630b32720fa58edcf9667ae/google_cloud_trace-1.17.0.tar.gz", hash = "sha256:68703bfc93718083f061d9130a3852e3181ec1b6b796b76856997c28f51b9595", size = 97995, upload-time = "2025-10-20T14:57:28.662Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/c9/84/e6b776f0b5d68451be68d3d43efe8eacc677182709dd7e84c960668a9909/google_cloud_trace-1.17.0-py3-none-any.whl", hash = "sha256:975dc0c2a9b1d7644bca45d78a2c5011ab5c73e94bd6537203deda374f88f7b3", size = 104118, upload-time = "2025-10-20T14:55:23.108Z" }, -] - -[[package]] -name = "google-crc32c" -version = "1.7.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/19/ae/87802e6d9f9d69adfaedfcfd599266bf386a54d0be058b532d04c794f76d/google_crc32c-1.7.1.tar.gz", hash = "sha256:2bff2305f98846f3e825dbeec9ee406f89da7962accdb29356e4eadc251bd472", size = 14495, upload-time = "2025-03-26T14:29:13.32Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/eb/69/b1b05cf415df0d86691d6a8b4b7e60ab3a6fb6efb783ee5cd3ed1382bfd3/google_crc32c-1.7.1-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:b07d48faf8292b4db7c3d64ab86f950c2e94e93a11fd47271c28ba458e4a0d76", size = 30467, upload-time = "2025-03-26T14:31:11.92Z" }, - { url = "https://files.pythonhosted.org/packages/44/3d/92f8928ecd671bd5b071756596971c79d252d09b835cdca5a44177fa87aa/google_crc32c-1.7.1-cp310-cp310-macosx_12_0_x86_64.whl", hash = "sha256:7cc81b3a2fbd932a4313eb53cc7d9dde424088ca3a0337160f35d91826880c1d", size = 30311, upload-time = "2025-03-26T14:53:14.161Z" }, - { url = "https://files.pythonhosted.org/packages/33/42/c2d15a73df79d45ed6b430b9e801d0bd8e28ac139a9012d7d58af50a385d/google_crc32c-1.7.1-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:1c67ca0a1f5b56162951a9dae987988679a7db682d6f97ce0f6381ebf0fbea4c", size = 37889, upload-time = "2025-03-26T14:41:27.83Z" }, - { url = "https://files.pythonhosted.org/packages/57/ea/ac59c86a3c694afd117bb669bde32aaf17d0de4305d01d706495f09cbf19/google_crc32c-1.7.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fc5319db92daa516b653600794d5b9f9439a9a121f3e162f94b0e1891c7933cb", size = 33028, upload-time = "2025-03-26T14:41:29.141Z" }, - { url = "https://files.pythonhosted.org/packages/60/44/87e77e8476767a4a93f6cf271157c6d948eacec63688c093580af13b04be/google_crc32c-1.7.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dcdf5a64adb747610140572ed18d011896e3b9ae5195f2514b7ff678c80f1603", size = 38026, upload-time = "2025-03-26T14:41:29.921Z" }, - { url = "https://files.pythonhosted.org/packages/c8/bf/21ac7bb305cd7c1a6de9c52f71db0868e104a5b573a4977cd9d0ff830f82/google_crc32c-1.7.1-cp310-cp310-win_amd64.whl", hash = "sha256:754561c6c66e89d55754106739e22fdaa93fafa8da7221b29c8b8e8270c6ec8a", size = 33476, upload-time = "2025-03-26T14:29:09.086Z" }, - { url = "https://files.pythonhosted.org/packages/f7/94/220139ea87822b6fdfdab4fb9ba81b3fff7ea2c82e2af34adc726085bffc/google_crc32c-1.7.1-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:6fbab4b935989e2c3610371963ba1b86afb09537fd0c633049be82afe153ac06", size = 30468, upload-time = "2025-03-26T14:32:52.215Z" }, - { url = "https://files.pythonhosted.org/packages/94/97/789b23bdeeb9d15dc2904660463ad539d0318286d7633fe2760c10ed0c1c/google_crc32c-1.7.1-cp311-cp311-macosx_12_0_x86_64.whl", hash = "sha256:ed66cbe1ed9cbaaad9392b5259b3eba4a9e565420d734e6238813c428c3336c9", size = 30313, upload-time = "2025-03-26T14:57:38.758Z" }, - { url = "https://files.pythonhosted.org/packages/81/b8/976a2b843610c211e7ccb3e248996a61e87dbb2c09b1499847e295080aec/google_crc32c-1.7.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ee6547b657621b6cbed3562ea7826c3e11cab01cd33b74e1f677690652883e77", size = 33048, upload-time = "2025-03-26T14:41:30.679Z" }, - { url = "https://files.pythonhosted.org/packages/c9/16/a3842c2cf591093b111d4a5e2bfb478ac6692d02f1b386d2a33283a19dc9/google_crc32c-1.7.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d68e17bad8f7dd9a49181a1f5a8f4b251c6dbc8cc96fb79f1d321dfd57d66f53", size = 32669, upload-time = "2025-03-26T14:41:31.432Z" }, - { url = "https://files.pythonhosted.org/packages/04/17/ed9aba495916fcf5fe4ecb2267ceb851fc5f273c4e4625ae453350cfd564/google_crc32c-1.7.1-cp311-cp311-win_amd64.whl", hash = "sha256:6335de12921f06e1f774d0dd1fbea6bf610abe0887a1638f64d694013138be5d", size = 33476, upload-time = "2025-03-26T14:29:10.211Z" }, - { url = "https://files.pythonhosted.org/packages/dd/b7/787e2453cf8639c94b3d06c9d61f512234a82e1d12d13d18584bd3049904/google_crc32c-1.7.1-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:2d73a68a653c57281401871dd4aeebbb6af3191dcac751a76ce430df4d403194", size = 30470, upload-time = "2025-03-26T14:34:31.655Z" }, - { url = "https://files.pythonhosted.org/packages/ed/b4/6042c2b0cbac3ec3a69bb4c49b28d2f517b7a0f4a0232603c42c58e22b44/google_crc32c-1.7.1-cp312-cp312-macosx_12_0_x86_64.whl", hash = "sha256:22beacf83baaf59f9d3ab2bbb4db0fb018da8e5aebdce07ef9f09fce8220285e", size = 30315, upload-time = "2025-03-26T15:01:54.634Z" }, - { url = "https://files.pythonhosted.org/packages/29/ad/01e7a61a5d059bc57b702d9ff6a18b2585ad97f720bd0a0dbe215df1ab0e/google_crc32c-1.7.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:19eafa0e4af11b0a4eb3974483d55d2d77ad1911e6cf6f832e1574f6781fd337", size = 33180, upload-time = "2025-03-26T14:41:32.168Z" }, - { url = "https://files.pythonhosted.org/packages/3b/a5/7279055cf004561894ed3a7bfdf5bf90a53f28fadd01af7cd166e88ddf16/google_crc32c-1.7.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b6d86616faaea68101195c6bdc40c494e4d76f41e07a37ffdef270879c15fb65", size = 32794, upload-time = "2025-03-26T14:41:33.264Z" }, - { url = "https://files.pythonhosted.org/packages/0f/d6/77060dbd140c624e42ae3ece3df53b9d811000729a5c821b9fd671ceaac6/google_crc32c-1.7.1-cp312-cp312-win_amd64.whl", hash = "sha256:b7491bdc0c7564fcf48c0179d2048ab2f7c7ba36b84ccd3a3e1c3f7a72d3bba6", size = 33477, upload-time = "2025-03-26T14:29:10.94Z" }, - { url = "https://files.pythonhosted.org/packages/8b/72/b8d785e9184ba6297a8620c8a37cf6e39b81a8ca01bb0796d7cbb28b3386/google_crc32c-1.7.1-cp313-cp313-macosx_12_0_arm64.whl", hash = "sha256:df8b38bdaf1629d62d51be8bdd04888f37c451564c2042d36e5812da9eff3c35", size = 30467, upload-time = "2025-03-26T14:36:06.909Z" }, - { url = "https://files.pythonhosted.org/packages/34/25/5f18076968212067c4e8ea95bf3b69669f9fc698476e5f5eb97d5b37999f/google_crc32c-1.7.1-cp313-cp313-macosx_12_0_x86_64.whl", hash = "sha256:e42e20a83a29aa2709a0cf271c7f8aefaa23b7ab52e53b322585297bb94d4638", size = 30309, upload-time = "2025-03-26T15:06:15.318Z" }, - { url = "https://files.pythonhosted.org/packages/92/83/9228fe65bf70e93e419f38bdf6c5ca5083fc6d32886ee79b450ceefd1dbd/google_crc32c-1.7.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:905a385140bf492ac300026717af339790921f411c0dfd9aa5a9e69a08ed32eb", size = 33133, upload-time = "2025-03-26T14:41:34.388Z" }, - { url = "https://files.pythonhosted.org/packages/c3/ca/1ea2fd13ff9f8955b85e7956872fdb7050c4ace8a2306a6d177edb9cf7fe/google_crc32c-1.7.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6b211ddaf20f7ebeec5c333448582c224a7c90a9d98826fbab82c0ddc11348e6", size = 32773, upload-time = "2025-03-26T14:41:35.19Z" }, - { url = "https://files.pythonhosted.org/packages/89/32/a22a281806e3ef21b72db16f948cad22ec68e4bdd384139291e00ff82fe2/google_crc32c-1.7.1-cp313-cp313-win_amd64.whl", hash = "sha256:0f99eaa09a9a7e642a61e06742856eec8b19fc0037832e03f941fe7cf0c8e4db", size = 33475, upload-time = "2025-03-26T14:29:11.771Z" }, - { url = "https://files.pythonhosted.org/packages/b8/c5/002975aff514e57fc084ba155697a049b3f9b52225ec3bc0f542871dd524/google_crc32c-1.7.1-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:32d1da0d74ec5634a05f53ef7df18fc646666a25efaaca9fc7dcfd4caf1d98c3", size = 33243, upload-time = "2025-03-26T14:41:35.975Z" }, - { url = "https://files.pythonhosted.org/packages/61/cb/c585282a03a0cea70fcaa1bf55d5d702d0f2351094d663ec3be1c6c67c52/google_crc32c-1.7.1-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e10554d4abc5238823112c2ad7e4560f96c7bf3820b202660373d769d9e6e4c9", size = 32870, upload-time = "2025-03-26T14:41:37.08Z" }, - { url = "https://files.pythonhosted.org/packages/0b/43/31e57ce04530794917dfe25243860ec141de9fadf4aa9783dffe7dac7c39/google_crc32c-1.7.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a8e9afc74168b0b2232fb32dd202c93e46b7d5e4bf03e66ba5dc273bb3559589", size = 28242, upload-time = "2025-03-26T14:41:42.858Z" }, - { url = "https://files.pythonhosted.org/packages/eb/f3/8b84cd4e0ad111e63e30eb89453f8dd308e3ad36f42305cf8c202461cdf0/google_crc32c-1.7.1-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fa8136cc14dd27f34a3221c0f16fd42d8a40e4778273e61a3c19aedaa44daf6b", size = 28049, upload-time = "2025-03-26T14:41:44.651Z" }, - { url = "https://files.pythonhosted.org/packages/16/1b/1693372bf423ada422f80fd88260dbfd140754adb15cbc4d7e9a68b1cb8e/google_crc32c-1.7.1-pp311-pypy311_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:85fef7fae11494e747c9fd1359a527e5970fc9603c90764843caabd3a16a0a48", size = 28241, upload-time = "2025-03-26T14:41:45.898Z" }, - { url = "https://files.pythonhosted.org/packages/fd/3c/2a19a60a473de48717b4efb19398c3f914795b64a96cf3fbe82588044f78/google_crc32c-1.7.1-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6efb97eb4369d52593ad6f75e7e10d053cf00c48983f7a973105bc70b0ac4d82", size = 28048, upload-time = "2025-03-26T14:41:46.696Z" }, -] - -[[package]] -name = "google-genai" -version = "1.47.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "google-auth" }, - { name = "httpx" }, - { name = "pydantic" }, - { name = "requests" }, - { name = "tenacity" }, - { name = "typing-extensions" }, - { name = "websockets" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/9f/97/784fba9bc6c41263ff90cb9063eadfdd755dde79cfa5a8d0e397b067dcf9/google_genai-1.47.0.tar.gz", hash = "sha256:ecece00d0a04e6739ea76cc8dad82ec9593d9380aaabef078990e60574e5bf59", size = 241471, upload-time = "2025-10-29T22:01:02.88Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/89/ef/e080e8d67c270ea320956bb911a9359664fc46d3b87d1f029decd33e5c4c/google_genai-1.47.0-py3-none-any.whl", hash = "sha256:e3851237556cbdec96007d8028b4b1f2425cdc5c099a8dc36b72a57e42821b60", size = 241506, upload-time = "2025-10-29T22:01:00.982Z" }, -] - -[[package]] -name = "google-resumable-media" -version = "2.7.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-crc32c" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/58/5a/0efdc02665dca14e0837b62c8a1a93132c264bd02054a15abb2218afe0ae/google_resumable_media-2.7.2.tar.gz", hash = "sha256:5280aed4629f2b60b847b0d42f9857fd4935c11af266744df33d8074cae92fe0", size = 2163099, upload-time = "2024-08-07T22:20:38.555Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/82/35/b8d3baf8c46695858cb9d8835a53baa1eeb9906ddaf2f728a5f5b640fd1e/google_resumable_media-2.7.2-py2.py3-none-any.whl", hash = "sha256:3ce7551e9fe6d99e9a126101d2536612bb73486721951e9562fee0f90c6ababa", size = 81251, upload-time = "2024-08-07T22:20:36.409Z" }, -] - -[[package]] -name = "googleapis-common-protos" -version = "1.71.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/30/43/b25abe02db2911397819003029bef768f68a974f2ece483e6084d1a5f754/googleapis_common_protos-1.71.0.tar.gz", hash = "sha256:1aec01e574e29da63c80ba9f7bbf1ccfaacf1da877f23609fe236ca7c72a2e2e", size = 146454, upload-time = "2025-10-20T14:58:08.732Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/25/e8/eba9fece11d57a71e3e22ea672742c8f3cf23b35730c9e96db768b295216/googleapis_common_protos-1.71.0-py3-none-any.whl", hash = "sha256:59034a1d849dc4d18971997a72ac56246570afdd17f9369a0ff68218d50ab78c", size = 294576, upload-time = "2025-10-20T14:56:21.295Z" }, -] - -[package.optional-dependencies] -grpc = [ - { name = "grpcio" }, -] - -[[package]] -name = "graphviz" -version = "0.21" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f8/b3/3ac91e9be6b761a4b30d66ff165e54439dcd48b83f4e20d644867215f6ca/graphviz-0.21.tar.gz", hash = "sha256:20743e7183be82aaaa8ad6c93f8893c923bd6658a04c32ee115edb3c8a835f78", size = 200434, upload-time = "2025-06-15T09:35:05.824Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/91/4c/e0ce1ef95d4000ebc1c11801f9b944fa5910ecc15b5e351865763d8657f8/graphviz-0.21-py3-none-any.whl", hash = "sha256:54f33de9f4f911d7e84e4191749cac8cc5653f815b06738c54db9a15ab8b1e42", size = 47300, upload-time = "2025-06-15T09:35:04.433Z" }, -] - -[[package]] -name = "greenlet" -version = "3.2.4" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/03/b8/704d753a5a45507a7aab61f18db9509302ed3d0a27ac7e0359ec2905b1a6/greenlet-3.2.4.tar.gz", hash = "sha256:0dca0d95ff849f9a364385f36ab49f50065d76964944638be9691e1832e9f86d", size = 188260, upload-time = "2025-08-07T13:24:33.51Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7d/ed/6bfa4109fcb23a58819600392564fea69cdc6551ffd5e69ccf1d52a40cbc/greenlet-3.2.4-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:8c68325b0d0acf8d91dde4e6f930967dd52a5302cd4062932a6b2e7c2969f47c", size = 271061, upload-time = "2025-08-07T13:17:15.373Z" }, - { url = "https://files.pythonhosted.org/packages/2a/fc/102ec1a2fc015b3a7652abab7acf3541d58c04d3d17a8d3d6a44adae1eb1/greenlet-3.2.4-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:94385f101946790ae13da500603491f04a76b6e4c059dab271b3ce2e283b2590", size = 629475, upload-time = "2025-08-07T13:42:54.009Z" }, - { url = "https://files.pythonhosted.org/packages/c5/26/80383131d55a4ac0fb08d71660fd77e7660b9db6bdb4e8884f46d9f2cc04/greenlet-3.2.4-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:f10fd42b5ee276335863712fa3da6608e93f70629c631bf77145021600abc23c", size = 640802, upload-time = "2025-08-07T13:45:25.52Z" }, - { url = "https://files.pythonhosted.org/packages/9f/7c/e7833dbcd8f376f3326bd728c845d31dcde4c84268d3921afcae77d90d08/greenlet-3.2.4-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:c8c9e331e58180d0d83c5b7999255721b725913ff6bc6cf39fa2a45841a4fd4b", size = 636703, upload-time = "2025-08-07T13:53:12.622Z" }, - { url = "https://files.pythonhosted.org/packages/e9/49/547b93b7c0428ede7b3f309bc965986874759f7d89e4e04aeddbc9699acb/greenlet-3.2.4-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:58b97143c9cc7b86fc458f215bd0932f1757ce649e05b640fea2e79b54cedb31", size = 635417, upload-time = "2025-08-07T13:18:25.189Z" }, - { url = "https://files.pythonhosted.org/packages/7f/91/ae2eb6b7979e2f9b035a9f612cf70f1bf54aad4e1d125129bef1eae96f19/greenlet-3.2.4-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c2ca18a03a8cfb5b25bc1cbe20f3d9a4c80d8c3b13ba3df49ac3961af0b1018d", size = 584358, upload-time = "2025-08-07T13:18:23.708Z" }, - { url = "https://files.pythonhosted.org/packages/f7/85/433de0c9c0252b22b16d413c9407e6cb3b41df7389afc366ca204dbc1393/greenlet-3.2.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:9fe0a28a7b952a21e2c062cd5756d34354117796c6d9215a87f55e38d15402c5", size = 1113550, upload-time = "2025-08-07T13:42:37.467Z" }, - { url = "https://files.pythonhosted.org/packages/a1/8d/88f3ebd2bc96bf7747093696f4335a0a8a4c5acfcf1b757717c0d2474ba3/greenlet-3.2.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:8854167e06950ca75b898b104b63cc646573aa5fef1353d4508ecdd1ee76254f", size = 1137126, upload-time = "2025-08-07T13:18:20.239Z" }, - { url = "https://files.pythonhosted.org/packages/f1/29/74242b7d72385e29bcc5563fba67dad94943d7cd03552bac320d597f29b2/greenlet-3.2.4-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:f47617f698838ba98f4ff4189aef02e7343952df3a615f847bb575c3feb177a7", size = 1544904, upload-time = "2025-11-04T12:42:04.763Z" }, - { url = "https://files.pythonhosted.org/packages/c8/e2/1572b8eeab0f77df5f6729d6ab6b141e4a84ee8eb9bc8c1e7918f94eda6d/greenlet-3.2.4-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:af41be48a4f60429d5cad9d22175217805098a9ef7c40bfef44f7669fb9d74d8", size = 1611228, upload-time = "2025-11-04T12:42:08.423Z" }, - { url = "https://files.pythonhosted.org/packages/d6/6f/b60b0291d9623c496638c582297ead61f43c4b72eef5e9c926ef4565ec13/greenlet-3.2.4-cp310-cp310-win_amd64.whl", hash = "sha256:73f49b5368b5359d04e18d15828eecc1806033db5233397748f4ca813ff1056c", size = 298654, upload-time = "2025-08-07T13:50:00.469Z" }, - { url = "https://files.pythonhosted.org/packages/a4/de/f28ced0a67749cac23fecb02b694f6473f47686dff6afaa211d186e2ef9c/greenlet-3.2.4-cp311-cp311-macosx_11_0_universal2.whl", hash = "sha256:96378df1de302bc38e99c3a9aa311967b7dc80ced1dcc6f171e99842987882a2", size = 272305, upload-time = "2025-08-07T13:15:41.288Z" }, - { url = "https://files.pythonhosted.org/packages/09/16/2c3792cba130000bf2a31c5272999113f4764fd9d874fb257ff588ac779a/greenlet-3.2.4-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:1ee8fae0519a337f2329cb78bd7a8e128ec0f881073d43f023c7b8d4831d5246", size = 632472, upload-time = "2025-08-07T13:42:55.044Z" }, - { url = "https://files.pythonhosted.org/packages/ae/8f/95d48d7e3d433e6dae5b1682e4292242a53f22df82e6d3dda81b1701a960/greenlet-3.2.4-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:94abf90142c2a18151632371140b3dba4dee031633fe614cb592dbb6c9e17bc3", size = 644646, upload-time = "2025-08-07T13:45:26.523Z" }, - { url = "https://files.pythonhosted.org/packages/d5/5e/405965351aef8c76b8ef7ad370e5da58d57ef6068df197548b015464001a/greenlet-3.2.4-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:4d1378601b85e2e5171b99be8d2dc85f594c79967599328f95c1dc1a40f1c633", size = 640519, upload-time = "2025-08-07T13:53:13.928Z" }, - { url = "https://files.pythonhosted.org/packages/25/5d/382753b52006ce0218297ec1b628e048c4e64b155379331f25a7316eb749/greenlet-3.2.4-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:0db5594dce18db94f7d1650d7489909b57afde4c580806b8d9203b6e79cdc079", size = 639707, upload-time = "2025-08-07T13:18:27.146Z" }, - { url = "https://files.pythonhosted.org/packages/1f/8e/abdd3f14d735b2929290a018ecf133c901be4874b858dd1c604b9319f064/greenlet-3.2.4-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:2523e5246274f54fdadbce8494458a2ebdcdbc7b802318466ac5606d3cded1f8", size = 587684, upload-time = "2025-08-07T13:18:25.164Z" }, - { url = "https://files.pythonhosted.org/packages/5d/65/deb2a69c3e5996439b0176f6651e0052542bb6c8f8ec2e3fba97c9768805/greenlet-3.2.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:1987de92fec508535687fb807a5cea1560f6196285a4cde35c100b8cd632cc52", size = 1116647, upload-time = "2025-08-07T13:42:38.655Z" }, - { url = "https://files.pythonhosted.org/packages/3f/cc/b07000438a29ac5cfb2194bfc128151d52f333cee74dd7dfe3fb733fc16c/greenlet-3.2.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:55e9c5affaa6775e2c6b67659f3a71684de4c549b3dd9afca3bc773533d284fa", size = 1142073, upload-time = "2025-08-07T13:18:21.737Z" }, - { url = "https://files.pythonhosted.org/packages/67/24/28a5b2fa42d12b3d7e5614145f0bd89714c34c08be6aabe39c14dd52db34/greenlet-3.2.4-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c9c6de1940a7d828635fbd254d69db79e54619f165ee7ce32fda763a9cb6a58c", size = 1548385, upload-time = "2025-11-04T12:42:11.067Z" }, - { url = "https://files.pythonhosted.org/packages/6a/05/03f2f0bdd0b0ff9a4f7b99333d57b53a7709c27723ec8123056b084e69cd/greenlet-3.2.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:03c5136e7be905045160b1b9fdca93dd6727b180feeafda6818e6496434ed8c5", size = 1613329, upload-time = "2025-11-04T12:42:12.928Z" }, - { url = "https://files.pythonhosted.org/packages/d8/0f/30aef242fcab550b0b3520b8e3561156857c94288f0332a79928c31a52cf/greenlet-3.2.4-cp311-cp311-win_amd64.whl", hash = "sha256:9c40adce87eaa9ddb593ccb0fa6a07caf34015a29bf8d344811665b573138db9", size = 299100, upload-time = "2025-08-07T13:44:12.287Z" }, - { url = "https://files.pythonhosted.org/packages/44/69/9b804adb5fd0671f367781560eb5eb586c4d495277c93bde4307b9e28068/greenlet-3.2.4-cp312-cp312-macosx_11_0_universal2.whl", hash = "sha256:3b67ca49f54cede0186854a008109d6ee71f66bd57bb36abd6d0a0267b540cdd", size = 274079, upload-time = "2025-08-07T13:15:45.033Z" }, - { url = "https://files.pythonhosted.org/packages/46/e9/d2a80c99f19a153eff70bc451ab78615583b8dac0754cfb942223d2c1a0d/greenlet-3.2.4-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:ddf9164e7a5b08e9d22511526865780a576f19ddd00d62f8a665949327fde8bb", size = 640997, upload-time = "2025-08-07T13:42:56.234Z" }, - { url = "https://files.pythonhosted.org/packages/3b/16/035dcfcc48715ccd345f3a93183267167cdd162ad123cd93067d86f27ce4/greenlet-3.2.4-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:f28588772bb5fb869a8eb331374ec06f24a83a9c25bfa1f38b6993afe9c1e968", size = 655185, upload-time = "2025-08-07T13:45:27.624Z" }, - { url = "https://files.pythonhosted.org/packages/31/da/0386695eef69ffae1ad726881571dfe28b41970173947e7c558d9998de0f/greenlet-3.2.4-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:5c9320971821a7cb77cfab8d956fa8e39cd07ca44b6070db358ceb7f8797c8c9", size = 649926, upload-time = "2025-08-07T13:53:15.251Z" }, - { url = "https://files.pythonhosted.org/packages/68/88/69bf19fd4dc19981928ceacbc5fd4bb6bc2215d53199e367832e98d1d8fe/greenlet-3.2.4-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:c60a6d84229b271d44b70fb6e5fa23781abb5d742af7b808ae3f6efd7c9c60f6", size = 651839, upload-time = "2025-08-07T13:18:30.281Z" }, - { url = "https://files.pythonhosted.org/packages/19/0d/6660d55f7373b2ff8152401a83e02084956da23ae58cddbfb0b330978fe9/greenlet-3.2.4-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:3b3812d8d0c9579967815af437d96623f45c0f2ae5f04e366de62a12d83a8fb0", size = 607586, upload-time = "2025-08-07T13:18:28.544Z" }, - { url = "https://files.pythonhosted.org/packages/8e/1a/c953fdedd22d81ee4629afbb38d2f9d71e37d23caace44775a3a969147d4/greenlet-3.2.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:abbf57b5a870d30c4675928c37278493044d7c14378350b3aa5d484fa65575f0", size = 1123281, upload-time = "2025-08-07T13:42:39.858Z" }, - { url = "https://files.pythonhosted.org/packages/3f/c7/12381b18e21aef2c6bd3a636da1088b888b97b7a0362fac2e4de92405f97/greenlet-3.2.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:20fb936b4652b6e307b8f347665e2c615540d4b42b3b4c8a321d8286da7e520f", size = 1151142, upload-time = "2025-08-07T13:18:22.981Z" }, - { url = "https://files.pythonhosted.org/packages/27/45/80935968b53cfd3f33cf99ea5f08227f2646e044568c9b1555b58ffd61c2/greenlet-3.2.4-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:ee7a6ec486883397d70eec05059353b8e83eca9168b9f3f9a361971e77e0bcd0", size = 1564846, upload-time = "2025-11-04T12:42:15.191Z" }, - { url = "https://files.pythonhosted.org/packages/69/02/b7c30e5e04752cb4db6202a3858b149c0710e5453b71a3b2aec5d78a1aab/greenlet-3.2.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:326d234cbf337c9c3def0676412eb7040a35a768efc92504b947b3e9cfc7543d", size = 1633814, upload-time = "2025-11-04T12:42:17.175Z" }, - { url = "https://files.pythonhosted.org/packages/e9/08/b0814846b79399e585f974bbeebf5580fbe59e258ea7be64d9dfb253c84f/greenlet-3.2.4-cp312-cp312-win_amd64.whl", hash = "sha256:a7d4e128405eea3814a12cc2605e0e6aedb4035bf32697f72deca74de4105e02", size = 299899, upload-time = "2025-08-07T13:38:53.448Z" }, - { url = "https://files.pythonhosted.org/packages/49/e8/58c7f85958bda41dafea50497cbd59738c5c43dbbea5ee83d651234398f4/greenlet-3.2.4-cp313-cp313-macosx_11_0_universal2.whl", hash = "sha256:1a921e542453fe531144e91e1feedf12e07351b1cf6c9e8a3325ea600a715a31", size = 272814, upload-time = "2025-08-07T13:15:50.011Z" }, - { url = "https://files.pythonhosted.org/packages/62/dd/b9f59862e9e257a16e4e610480cfffd29e3fae018a68c2332090b53aac3d/greenlet-3.2.4-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:cd3c8e693bff0fff6ba55f140bf390fa92c994083f838fece0f63be121334945", size = 641073, upload-time = "2025-08-07T13:42:57.23Z" }, - { url = "https://files.pythonhosted.org/packages/f7/0b/bc13f787394920b23073ca3b6c4a7a21396301ed75a655bcb47196b50e6e/greenlet-3.2.4-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:710638eb93b1fa52823aa91bf75326f9ecdfd5e0466f00789246a5280f4ba0fc", size = 655191, upload-time = "2025-08-07T13:45:29.752Z" }, - { url = "https://files.pythonhosted.org/packages/f2/d6/6adde57d1345a8d0f14d31e4ab9c23cfe8e2cd39c3baf7674b4b0338d266/greenlet-3.2.4-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:c5111ccdc9c88f423426df3fd1811bfc40ed66264d35aa373420a34377efc98a", size = 649516, upload-time = "2025-08-07T13:53:16.314Z" }, - { url = "https://files.pythonhosted.org/packages/7f/3b/3a3328a788d4a473889a2d403199932be55b1b0060f4ddd96ee7cdfcad10/greenlet-3.2.4-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:d76383238584e9711e20ebe14db6c88ddcedc1829a9ad31a584389463b5aa504", size = 652169, upload-time = "2025-08-07T13:18:32.861Z" }, - { url = "https://files.pythonhosted.org/packages/ee/43/3cecdc0349359e1a527cbf2e3e28e5f8f06d3343aaf82ca13437a9aa290f/greenlet-3.2.4-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:23768528f2911bcd7e475210822ffb5254ed10d71f4028387e5a99b4c6699671", size = 610497, upload-time = "2025-08-07T13:18:31.636Z" }, - { url = "https://files.pythonhosted.org/packages/b8/19/06b6cf5d604e2c382a6f31cafafd6f33d5dea706f4db7bdab184bad2b21d/greenlet-3.2.4-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:00fadb3fedccc447f517ee0d3fd8fe49eae949e1cd0f6a611818f4f6fb7dc83b", size = 1121662, upload-time = "2025-08-07T13:42:41.117Z" }, - { url = "https://files.pythonhosted.org/packages/a2/15/0d5e4e1a66fab130d98168fe984c509249c833c1a3c16806b90f253ce7b9/greenlet-3.2.4-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:d25c5091190f2dc0eaa3f950252122edbbadbb682aa7b1ef2f8af0f8c0afefae", size = 1149210, upload-time = "2025-08-07T13:18:24.072Z" }, - { url = "https://files.pythonhosted.org/packages/1c/53/f9c440463b3057485b8594d7a638bed53ba531165ef0ca0e6c364b5cc807/greenlet-3.2.4-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:6e343822feb58ac4d0a1211bd9399de2b3a04963ddeec21530fc426cc121f19b", size = 1564759, upload-time = "2025-11-04T12:42:19.395Z" }, - { url = "https://files.pythonhosted.org/packages/47/e4/3bb4240abdd0a8d23f4f88adec746a3099f0d86bfedb623f063b2e3b4df0/greenlet-3.2.4-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:ca7f6f1f2649b89ce02f6f229d7c19f680a6238af656f61e0115b24857917929", size = 1634288, upload-time = "2025-11-04T12:42:21.174Z" }, - { url = "https://files.pythonhosted.org/packages/0b/55/2321e43595e6801e105fcfdee02b34c0f996eb71e6ddffca6b10b7e1d771/greenlet-3.2.4-cp313-cp313-win_amd64.whl", hash = "sha256:554b03b6e73aaabec3745364d6239e9e012d64c68ccd0b8430c64ccc14939a8b", size = 299685, upload-time = "2025-08-07T13:24:38.824Z" }, - { url = "https://files.pythonhosted.org/packages/22/5c/85273fd7cc388285632b0498dbbab97596e04b154933dfe0f3e68156c68c/greenlet-3.2.4-cp314-cp314-macosx_11_0_universal2.whl", hash = "sha256:49a30d5fda2507ae77be16479bdb62a660fa51b1eb4928b524975b3bde77b3c0", size = 273586, upload-time = "2025-08-07T13:16:08.004Z" }, - { url = "https://files.pythonhosted.org/packages/d1/75/10aeeaa3da9332c2e761e4c50d4c3556c21113ee3f0afa2cf5769946f7a3/greenlet-3.2.4-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:299fd615cd8fc86267b47597123e3f43ad79c9d8a22bebdce535e53550763e2f", size = 686346, upload-time = "2025-08-07T13:42:59.944Z" }, - { url = "https://files.pythonhosted.org/packages/c0/aa/687d6b12ffb505a4447567d1f3abea23bd20e73a5bed63871178e0831b7a/greenlet-3.2.4-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:c17b6b34111ea72fc5a4e4beec9711d2226285f0386ea83477cbb97c30a3f3a5", size = 699218, upload-time = "2025-08-07T13:45:30.969Z" }, - { url = "https://files.pythonhosted.org/packages/dc/8b/29aae55436521f1d6f8ff4e12fb676f3400de7fcf27fccd1d4d17fd8fecd/greenlet-3.2.4-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:b4a1870c51720687af7fa3e7cda6d08d801dae660f75a76f3845b642b4da6ee1", size = 694659, upload-time = "2025-08-07T13:53:17.759Z" }, - { url = "https://files.pythonhosted.org/packages/92/2e/ea25914b1ebfde93b6fc4ff46d6864564fba59024e928bdc7de475affc25/greenlet-3.2.4-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:061dc4cf2c34852b052a8620d40f36324554bc192be474b9e9770e8c042fd735", size = 695355, upload-time = "2025-08-07T13:18:34.517Z" }, - { url = "https://files.pythonhosted.org/packages/72/60/fc56c62046ec17f6b0d3060564562c64c862948c9d4bc8aa807cf5bd74f4/greenlet-3.2.4-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:44358b9bf66c8576a9f57a590d5f5d6e72fa4228b763d0e43fee6d3b06d3a337", size = 657512, upload-time = "2025-08-07T13:18:33.969Z" }, - { url = "https://files.pythonhosted.org/packages/23/6e/74407aed965a4ab6ddd93a7ded3180b730d281c77b765788419484cdfeef/greenlet-3.2.4-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:2917bdf657f5859fbf3386b12d68ede4cf1f04c90c3a6bc1f013dd68a22e2269", size = 1612508, upload-time = "2025-11-04T12:42:23.427Z" }, - { url = "https://files.pythonhosted.org/packages/0d/da/343cd760ab2f92bac1845ca07ee3faea9fe52bee65f7bcb19f16ad7de08b/greenlet-3.2.4-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:015d48959d4add5d6c9f6c5210ee3803a830dce46356e3bc326d6776bde54681", size = 1680760, upload-time = "2025-11-04T12:42:25.341Z" }, - { url = "https://files.pythonhosted.org/packages/e3/a5/6ddab2b4c112be95601c13428db1d8b6608a8b6039816f2ba09c346c08fc/greenlet-3.2.4-cp314-cp314-win_amd64.whl", hash = "sha256:e37ab26028f12dbb0ff65f29a8d3d44a765c61e729647bf2ddfbbed621726f01", size = 303425, upload-time = "2025-08-07T13:32:27.59Z" }, -] - -[[package]] -name = "grpc-google-iam-v1" -version = "0.14.3" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "googleapis-common-protos", extra = ["grpc"] }, - { name = "grpcio" }, - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/76/1e/1011451679a983f2f5c6771a1682542ecb027776762ad031fd0d7129164b/grpc_google_iam_v1-0.14.3.tar.gz", hash = "sha256:879ac4ef33136c5491a6300e27575a9ec760f6cdf9a2518798c1b8977a5dc389", size = 23745, upload-time = "2025-10-15T21:14:53.318Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/4a/bd/330a1bbdb1afe0b96311249e699b6dc9cfc17916394fd4503ac5aca2514b/grpc_google_iam_v1-0.14.3-py3-none-any.whl", hash = "sha256:7a7f697e017a067206a3dfef44e4c634a34d3dee135fe7d7a4613fe3e59217e6", size = 32690, upload-time = "2025-10-15T21:14:51.72Z" }, -] - -[[package]] -name = "grpc-interceptor" -version = "0.15.4" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "grpcio" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/9f/28/57449d5567adf4c1d3e216aaca545913fbc21a915f2da6790d6734aac76e/grpc-interceptor-0.15.4.tar.gz", hash = "sha256:1f45c0bcb58b6f332f37c637632247c9b02bc6af0fdceb7ba7ce8d2ebbfb0926", size = 19322, upload-time = "2023-11-16T02:05:42.459Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/15/ac/8d53f230a7443401ce81791ec50a3b0e54924bf615ad287654fa4a2f5cdc/grpc_interceptor-0.15.4-py3-none-any.whl", hash = "sha256:0035f33228693ed3767ee49d937bac424318db173fef4d2d0170b3215f254d9d", size = 20848, upload-time = "2023-11-16T02:05:40.913Z" }, -] - -[[package]] -name = "grpcio" -version = "1.76.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/b6/e0/318c1ce3ae5a17894d5791e87aea147587c9e702f24122cc7a5c8bbaeeb1/grpcio-1.76.0.tar.gz", hash = "sha256:7be78388d6da1a25c0d5ec506523db58b18be22d9c37d8d3a32c08be4987bd73", size = 12785182, upload-time = "2025-10-21T16:23:12.106Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/88/17/ff4795dc9a34b6aee6ec379f1b66438a3789cd1315aac0cbab60d92f74b3/grpcio-1.76.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:65a20de41e85648e00305c1bb09a3598f840422e522277641145a32d42dcefcc", size = 5840037, upload-time = "2025-10-21T16:20:25.069Z" }, - { url = "https://files.pythonhosted.org/packages/4e/ff/35f9b96e3fa2f12e1dcd58a4513a2e2294a001d64dec81677361b7040c9a/grpcio-1.76.0-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:40ad3afe81676fd9ec6d9d406eda00933f218038433980aa19d401490e46ecde", size = 11836482, upload-time = "2025-10-21T16:20:30.113Z" }, - { url = "https://files.pythonhosted.org/packages/3e/1c/8374990f9545e99462caacea5413ed783014b3b66ace49e35c533f07507b/grpcio-1.76.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:035d90bc79eaa4bed83f524331d55e35820725c9fbb00ffa1904d5550ed7ede3", size = 6407178, upload-time = "2025-10-21T16:20:32.733Z" }, - { url = "https://files.pythonhosted.org/packages/1e/77/36fd7d7c75a6c12542c90a6d647a27935a1ecaad03e0ffdb7c42db6b04d2/grpcio-1.76.0-cp310-cp310-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:4215d3a102bd95e2e11b5395c78562967959824156af11fa93d18fdd18050990", size = 7075684, upload-time = "2025-10-21T16:20:35.435Z" }, - { url = "https://files.pythonhosted.org/packages/38/f7/e3cdb252492278e004722306c5a8935eae91e64ea11f0af3437a7de2e2b7/grpcio-1.76.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:49ce47231818806067aea3324d4bf13825b658ad662d3b25fada0bdad9b8a6af", size = 6611133, upload-time = "2025-10-21T16:20:37.541Z" }, - { url = "https://files.pythonhosted.org/packages/7e/20/340db7af162ccd20a0893b5f3c4a5d676af7b71105517e62279b5b61d95a/grpcio-1.76.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:8cc3309d8e08fd79089e13ed4819d0af72aa935dd8f435a195fd152796752ff2", size = 7195507, upload-time = "2025-10-21T16:20:39.643Z" }, - { url = "https://files.pythonhosted.org/packages/10/f0/b2160addc1487bd8fa4810857a27132fb4ce35c1b330c2f3ac45d697b106/grpcio-1.76.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:971fd5a1d6e62e00d945423a567e42eb1fa678ba89072832185ca836a94daaa6", size = 8160651, upload-time = "2025-10-21T16:20:42.492Z" }, - { url = "https://files.pythonhosted.org/packages/2c/2c/ac6f98aa113c6ef111b3f347854e99ebb7fb9d8f7bb3af1491d438f62af4/grpcio-1.76.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:9d9adda641db7207e800a7f089068f6f645959f2df27e870ee81d44701dd9db3", size = 7620568, upload-time = "2025-10-21T16:20:45.995Z" }, - { url = "https://files.pythonhosted.org/packages/90/84/7852f7e087285e3ac17a2703bc4129fafee52d77c6c82af97d905566857e/grpcio-1.76.0-cp310-cp310-win32.whl", hash = "sha256:063065249d9e7e0782d03d2bca50787f53bd0fb89a67de9a7b521c4a01f1989b", size = 3998879, upload-time = "2025-10-21T16:20:48.592Z" }, - { url = "https://files.pythonhosted.org/packages/10/30/d3d2adcbb6dd3ff59d6ac3df6ef830e02b437fb5c90990429fd180e52f30/grpcio-1.76.0-cp310-cp310-win_amd64.whl", hash = "sha256:a6ae758eb08088d36812dd5d9af7a9859c05b1e0f714470ea243694b49278e7b", size = 4706892, upload-time = "2025-10-21T16:20:50.697Z" }, - { url = "https://files.pythonhosted.org/packages/a0/00/8163a1beeb6971f66b4bbe6ac9457b97948beba8dd2fc8e1281dce7f79ec/grpcio-1.76.0-cp311-cp311-linux_armv7l.whl", hash = "sha256:2e1743fbd7f5fa713a1b0a8ac8ebabf0ec980b5d8809ec358d488e273b9cf02a", size = 5843567, upload-time = "2025-10-21T16:20:52.829Z" }, - { url = "https://files.pythonhosted.org/packages/10/c1/934202f5cf335e6d852530ce14ddb0fef21be612ba9ecbbcbd4d748ca32d/grpcio-1.76.0-cp311-cp311-macosx_11_0_universal2.whl", hash = "sha256:a8c2cf1209497cf659a667d7dea88985e834c24b7c3b605e6254cbb5076d985c", size = 11848017, upload-time = "2025-10-21T16:20:56.705Z" }, - { url = "https://files.pythonhosted.org/packages/11/0b/8dec16b1863d74af6eb3543928600ec2195af49ca58b16334972f6775663/grpcio-1.76.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:08caea849a9d3c71a542827d6df9d5a69067b0a1efbea8a855633ff5d9571465", size = 6412027, upload-time = "2025-10-21T16:20:59.3Z" }, - { url = "https://files.pythonhosted.org/packages/d7/64/7b9e6e7ab910bea9d46f2c090380bab274a0b91fb0a2fe9b0cd399fffa12/grpcio-1.76.0-cp311-cp311-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:f0e34c2079d47ae9f6188211db9e777c619a21d4faba6977774e8fa43b085e48", size = 7075913, upload-time = "2025-10-21T16:21:01.645Z" }, - { url = "https://files.pythonhosted.org/packages/68/86/093c46e9546073cefa789bd76d44c5cb2abc824ca62af0c18be590ff13ba/grpcio-1.76.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:8843114c0cfce61b40ad48df65abcfc00d4dba82eae8718fab5352390848c5da", size = 6615417, upload-time = "2025-10-21T16:21:03.844Z" }, - { url = "https://files.pythonhosted.org/packages/f7/b6/5709a3a68500a9c03da6fb71740dcdd5ef245e39266461a03f31a57036d8/grpcio-1.76.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8eddfb4d203a237da6f3cc8a540dad0517d274b5a1e9e636fd8d2c79b5c1d397", size = 7199683, upload-time = "2025-10-21T16:21:06.195Z" }, - { url = "https://files.pythonhosted.org/packages/91/d3/4b1f2bf16ed52ce0b508161df3a2d186e4935379a159a834cb4a7d687429/grpcio-1.76.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:32483fe2aab2c3794101c2a159070584e5db11d0aa091b2c0ea9c4fc43d0d749", size = 8163109, upload-time = "2025-10-21T16:21:08.498Z" }, - { url = "https://files.pythonhosted.org/packages/5c/61/d9043f95f5f4cf085ac5dd6137b469d41befb04bd80280952ffa2a4c3f12/grpcio-1.76.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:dcfe41187da8992c5f40aa8c5ec086fa3672834d2be57a32384c08d5a05b4c00", size = 7626676, upload-time = "2025-10-21T16:21:10.693Z" }, - { url = "https://files.pythonhosted.org/packages/36/95/fd9a5152ca02d8881e4dd419cdd790e11805979f499a2e5b96488b85cf27/grpcio-1.76.0-cp311-cp311-win32.whl", hash = "sha256:2107b0c024d1b35f4083f11245c0e23846ae64d02f40b2b226684840260ed054", size = 3997688, upload-time = "2025-10-21T16:21:12.746Z" }, - { url = "https://files.pythonhosted.org/packages/60/9c/5c359c8d4c9176cfa3c61ecd4efe5affe1f38d9bae81e81ac7186b4c9cc8/grpcio-1.76.0-cp311-cp311-win_amd64.whl", hash = "sha256:522175aba7af9113c48ec10cc471b9b9bd4f6ceb36aeb4544a8e2c80ed9d252d", size = 4709315, upload-time = "2025-10-21T16:21:15.26Z" }, - { url = "https://files.pythonhosted.org/packages/bf/05/8e29121994b8d959ffa0afd28996d452f291b48cfc0875619de0bde2c50c/grpcio-1.76.0-cp312-cp312-linux_armv7l.whl", hash = "sha256:81fd9652b37b36f16138611c7e884eb82e0cec137c40d3ef7c3f9b3ed00f6ed8", size = 5799718, upload-time = "2025-10-21T16:21:17.939Z" }, - { url = "https://files.pythonhosted.org/packages/d9/75/11d0e66b3cdf998c996489581bdad8900db79ebd83513e45c19548f1cba4/grpcio-1.76.0-cp312-cp312-macosx_11_0_universal2.whl", hash = "sha256:04bbe1bfe3a68bbfd4e52402ab7d4eb59d72d02647ae2042204326cf4bbad280", size = 11825627, upload-time = "2025-10-21T16:21:20.466Z" }, - { url = "https://files.pythonhosted.org/packages/28/50/2f0aa0498bc188048f5d9504dcc5c2c24f2eb1a9337cd0fa09a61a2e75f0/grpcio-1.76.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d388087771c837cdb6515539f43b9d4bf0b0f23593a24054ac16f7a960be16f4", size = 6359167, upload-time = "2025-10-21T16:21:23.122Z" }, - { url = "https://files.pythonhosted.org/packages/66/e5/bbf0bb97d29ede1d59d6588af40018cfc345b17ce979b7b45424628dc8bb/grpcio-1.76.0-cp312-cp312-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:9f8f757bebaaea112c00dba718fc0d3260052ce714e25804a03f93f5d1c6cc11", size = 7044267, upload-time = "2025-10-21T16:21:25.995Z" }, - { url = "https://files.pythonhosted.org/packages/f5/86/f6ec2164f743d9609691115ae8ece098c76b894ebe4f7c94a655c6b03e98/grpcio-1.76.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:980a846182ce88c4f2f7e2c22c56aefd515daeb36149d1c897f83cf57999e0b6", size = 6573963, upload-time = "2025-10-21T16:21:28.631Z" }, - { url = "https://files.pythonhosted.org/packages/60/bc/8d9d0d8505feccfdf38a766d262c71e73639c165b311c9457208b56d92ae/grpcio-1.76.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f92f88e6c033db65a5ae3d97905c8fea9c725b63e28d5a75cb73b49bda5024d8", size = 7164484, upload-time = "2025-10-21T16:21:30.837Z" }, - { url = "https://files.pythonhosted.org/packages/67/e6/5d6c2fc10b95edf6df9b8f19cf10a34263b7fd48493936fffd5085521292/grpcio-1.76.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:4baf3cbe2f0be3289eb68ac8ae771156971848bb8aaff60bad42005539431980", size = 8127777, upload-time = "2025-10-21T16:21:33.577Z" }, - { url = "https://files.pythonhosted.org/packages/3f/c8/dce8ff21c86abe025efe304d9e31fdb0deaaa3b502b6a78141080f206da0/grpcio-1.76.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:615ba64c208aaceb5ec83bfdce7728b80bfeb8be97562944836a7a0a9647d882", size = 7594014, upload-time = "2025-10-21T16:21:41.882Z" }, - { url = "https://files.pythonhosted.org/packages/e0/42/ad28191ebf983a5d0ecef90bab66baa5a6b18f2bfdef9d0a63b1973d9f75/grpcio-1.76.0-cp312-cp312-win32.whl", hash = "sha256:45d59a649a82df5718fd9527ce775fd66d1af35e6d31abdcdc906a49c6822958", size = 3984750, upload-time = "2025-10-21T16:21:44.006Z" }, - { url = "https://files.pythonhosted.org/packages/9e/00/7bd478cbb851c04a48baccaa49b75abaa8e4122f7d86da797500cccdd771/grpcio-1.76.0-cp312-cp312-win_amd64.whl", hash = "sha256:c088e7a90b6017307f423efbb9d1ba97a22aa2170876223f9709e9d1de0b5347", size = 4704003, upload-time = "2025-10-21T16:21:46.244Z" }, - { url = "https://files.pythonhosted.org/packages/fc/ed/71467ab770effc9e8cef5f2e7388beb2be26ed642d567697bb103a790c72/grpcio-1.76.0-cp313-cp313-linux_armv7l.whl", hash = "sha256:26ef06c73eb53267c2b319f43e6634c7556ea37672029241a056629af27c10e2", size = 5807716, upload-time = "2025-10-21T16:21:48.475Z" }, - { url = "https://files.pythonhosted.org/packages/2c/85/c6ed56f9817fab03fa8a111ca91469941fb514e3e3ce6d793cb8f1e1347b/grpcio-1.76.0-cp313-cp313-macosx_11_0_universal2.whl", hash = "sha256:45e0111e73f43f735d70786557dc38141185072d7ff8dc1829d6a77ac1471468", size = 11821522, upload-time = "2025-10-21T16:21:51.142Z" }, - { url = "https://files.pythonhosted.org/packages/ac/31/2b8a235ab40c39cbc141ef647f8a6eb7b0028f023015a4842933bc0d6831/grpcio-1.76.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:83d57312a58dcfe2a3a0f9d1389b299438909a02db60e2f2ea2ae2d8034909d3", size = 6362558, upload-time = "2025-10-21T16:21:54.213Z" }, - { url = "https://files.pythonhosted.org/packages/bd/64/9784eab483358e08847498ee56faf8ff6ea8e0a4592568d9f68edc97e9e9/grpcio-1.76.0-cp313-cp313-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:3e2a27c89eb9ac3d81ec8835e12414d73536c6e620355d65102503064a4ed6eb", size = 7049990, upload-time = "2025-10-21T16:21:56.476Z" }, - { url = "https://files.pythonhosted.org/packages/2b/94/8c12319a6369434e7a184b987e8e9f3b49a114c489b8315f029e24de4837/grpcio-1.76.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:61f69297cba3950a524f61c7c8ee12e55c486cb5f7db47ff9dcee33da6f0d3ae", size = 6575387, upload-time = "2025-10-21T16:21:59.051Z" }, - { url = "https://files.pythonhosted.org/packages/15/0f/f12c32b03f731f4a6242f771f63039df182c8b8e2cf8075b245b409259d4/grpcio-1.76.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:6a15c17af8839b6801d554263c546c69c4d7718ad4321e3166175b37eaacca77", size = 7166668, upload-time = "2025-10-21T16:22:02.049Z" }, - { url = "https://files.pythonhosted.org/packages/ff/2d/3ec9ce0c2b1d92dd59d1c3264aaec9f0f7c817d6e8ac683b97198a36ed5a/grpcio-1.76.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:25a18e9810fbc7e7f03ec2516addc116a957f8cbb8cbc95ccc80faa072743d03", size = 8124928, upload-time = "2025-10-21T16:22:04.984Z" }, - { url = "https://files.pythonhosted.org/packages/1a/74/fd3317be5672f4856bcdd1a9e7b5e17554692d3db9a3b273879dc02d657d/grpcio-1.76.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:931091142fd8cc14edccc0845a79248bc155425eee9a98b2db2ea4f00a235a42", size = 7589983, upload-time = "2025-10-21T16:22:07.881Z" }, - { url = "https://files.pythonhosted.org/packages/45/bb/ca038cf420f405971f19821c8c15bcbc875505f6ffadafe9ffd77871dc4c/grpcio-1.76.0-cp313-cp313-win32.whl", hash = "sha256:5e8571632780e08526f118f74170ad8d50fb0a48c23a746bef2a6ebade3abd6f", size = 3984727, upload-time = "2025-10-21T16:22:10.032Z" }, - { url = "https://files.pythonhosted.org/packages/41/80/84087dc56437ced7cdd4b13d7875e7439a52a261e3ab4e06488ba6173b0a/grpcio-1.76.0-cp313-cp313-win_amd64.whl", hash = "sha256:f9f7bd5faab55f47231ad8dba7787866b69f5e93bc306e3915606779bbfb4ba8", size = 4702799, upload-time = "2025-10-21T16:22:12.709Z" }, - { url = "https://files.pythonhosted.org/packages/b4/46/39adac80de49d678e6e073b70204091e76631e03e94928b9ea4ecf0f6e0e/grpcio-1.76.0-cp314-cp314-linux_armv7l.whl", hash = "sha256:ff8a59ea85a1f2191a0ffcc61298c571bc566332f82e5f5be1b83c9d8e668a62", size = 5808417, upload-time = "2025-10-21T16:22:15.02Z" }, - { url = "https://files.pythonhosted.org/packages/9c/f5/a4531f7fb8b4e2a60b94e39d5d924469b7a6988176b3422487be61fe2998/grpcio-1.76.0-cp314-cp314-macosx_11_0_universal2.whl", hash = "sha256:06c3d6b076e7b593905d04fdba6a0525711b3466f43b3400266f04ff735de0cd", size = 11828219, upload-time = "2025-10-21T16:22:17.954Z" }, - { url = "https://files.pythonhosted.org/packages/4b/1c/de55d868ed7a8bd6acc6b1d6ddc4aa36d07a9f31d33c912c804adb1b971b/grpcio-1.76.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:fd5ef5932f6475c436c4a55e4336ebbe47bd3272be04964a03d316bbf4afbcbc", size = 6367826, upload-time = "2025-10-21T16:22:20.721Z" }, - { url = "https://files.pythonhosted.org/packages/59/64/99e44c02b5adb0ad13ab3adc89cb33cb54bfa90c74770f2607eea629b86f/grpcio-1.76.0-cp314-cp314-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:b331680e46239e090f5b3cead313cc772f6caa7d0fc8de349337563125361a4a", size = 7049550, upload-time = "2025-10-21T16:22:23.637Z" }, - { url = "https://files.pythonhosted.org/packages/43/28/40a5be3f9a86949b83e7d6a2ad6011d993cbe9b6bd27bea881f61c7788b6/grpcio-1.76.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:2229ae655ec4e8999599469559e97630185fdd53ae1e8997d147b7c9b2b72cba", size = 6575564, upload-time = "2025-10-21T16:22:26.016Z" }, - { url = "https://files.pythonhosted.org/packages/4b/a9/1be18e6055b64467440208a8559afac243c66a8b904213af6f392dc2212f/grpcio-1.76.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:490fa6d203992c47c7b9e4a9d39003a0c2bcc1c9aa3c058730884bbbb0ee9f09", size = 7176236, upload-time = "2025-10-21T16:22:28.362Z" }, - { url = "https://files.pythonhosted.org/packages/0f/55/dba05d3fcc151ce6e81327541d2cc8394f442f6b350fead67401661bf041/grpcio-1.76.0-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:479496325ce554792dba6548fae3df31a72cef7bad71ca2e12b0e58f9b336bfc", size = 8125795, upload-time = "2025-10-21T16:22:31.075Z" }, - { url = "https://files.pythonhosted.org/packages/4a/45/122df922d05655f63930cf42c9e3f72ba20aadb26c100ee105cad4ce4257/grpcio-1.76.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:1c9b93f79f48b03ada57ea24725d83a30284a012ec27eab2cf7e50a550cbbbcc", size = 7592214, upload-time = "2025-10-21T16:22:33.831Z" }, - { url = "https://files.pythonhosted.org/packages/4a/6e/0b899b7f6b66e5af39e377055fb4a6675c9ee28431df5708139df2e93233/grpcio-1.76.0-cp314-cp314-win32.whl", hash = "sha256:747fa73efa9b8b1488a95d0ba1039c8e2dca0f741612d80415b1e1c560febf4e", size = 4062961, upload-time = "2025-10-21T16:22:36.468Z" }, - { url = "https://files.pythonhosted.org/packages/19/41/0b430b01a2eb38ee887f88c1f07644a1df8e289353b78e82b37ef988fb64/grpcio-1.76.0-cp314-cp314-win_amd64.whl", hash = "sha256:922fa70ba549fce362d2e2871ab542082d66e2aaf0c19480ea453905b01f384e", size = 4834462, upload-time = "2025-10-21T16:22:39.772Z" }, -] - -[[package]] -name = "grpcio-status" -version = "1.76.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "googleapis-common-protos" }, - { name = "grpcio" }, - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/3f/46/e9f19d5be65e8423f886813a2a9d0056ba94757b0c5007aa59aed1a961fa/grpcio_status-1.76.0.tar.gz", hash = "sha256:25fcbfec74c15d1a1cb5da3fab8ee9672852dc16a5a9eeb5baf7d7a9952943cd", size = 13679, upload-time = "2025-10-21T16:28:52.545Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/8c/cc/27ba60ad5a5f2067963e6a858743500df408eb5855e98be778eaef8c9b02/grpcio_status-1.76.0-py3-none-any.whl", hash = "sha256:380568794055a8efbbd8871162df92012e0228a5f6dffaf57f2a00c534103b18", size = 14425, upload-time = "2025-10-21T16:28:40.853Z" }, -] - -[[package]] -name = "h11" -version = "0.16.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/01/ee/02a2c011bdab74c6fb3c75474d40b3052059d95df7e73351460c8588d963/h11-0.16.0.tar.gz", hash = "sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1", size = 101250, upload-time = "2025-04-24T03:35:25.427Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86", size = 37515, upload-time = "2025-04-24T03:35:24.344Z" }, -] - -[[package]] -name = "httpcore" -version = "1.0.9" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "certifi" }, - { name = "h11" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/06/94/82699a10bca87a5556c9c59b5963f2d039dbd239f25bc2a63907a05a14cb/httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8", size = 85484, upload-time = "2025-04-24T22:06:22.219Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55", size = 78784, upload-time = "2025-04-24T22:06:20.566Z" }, -] - -[[package]] -name = "httplib2" -version = "0.31.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "pyparsing" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/52/77/6653db69c1f7ecfe5e3f9726fdadc981794656fcd7d98c4209fecfea9993/httplib2-0.31.0.tar.gz", hash = "sha256:ac7ab497c50975147d4f7b1ade44becc7df2f8954d42b38b3d69c515f531135c", size = 250759, upload-time = "2025-09-11T12:16:03.403Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/8c/a2/0d269db0f6163be503775dc8b6a6fa15820cc9fdc866f6ba608d86b721f2/httplib2-0.31.0-py3-none-any.whl", hash = "sha256:b9cd78abea9b4e43a7714c6e0f8b6b8561a6fc1e95d5dbd367f5bf0ef35f5d24", size = 91148, upload-time = "2025-09-11T12:16:01.803Z" }, -] - -[[package]] -name = "httpx" -version = "0.28.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "certifi" }, - { name = "httpcore" }, - { name = "idna" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/b1/df/48c586a5fe32a0f01324ee087459e112ebb7224f646c0b5023f5e79e9956/httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc", size = 141406, upload-time = "2024-12-06T15:37:23.222Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad", size = 73517, upload-time = "2024-12-06T15:37:21.509Z" }, -] - -[[package]] -name = "httpx-sse" -version = "0.4.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/0f/4c/751061ffa58615a32c31b2d82e8482be8dd4a89154f003147acee90f2be9/httpx_sse-0.4.3.tar.gz", hash = "sha256:9b1ed0127459a66014aec3c56bebd93da3c1bc8bb6618c8082039a44889a755d", size = 15943, upload-time = "2025-10-10T21:48:22.271Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d2/fd/6668e5aec43ab844de6fc74927e155a3b37bf40d7c3790e49fc0406b6578/httpx_sse-0.4.3-py3-none-any.whl", hash = "sha256:0ac1c9fe3c0afad2e0ebb25a934a59f4c7823b60792691f779fad2c5568830fc", size = 8960, upload-time = "2025-10-10T21:48:21.158Z" }, -] - -[[package]] -name = "idna" -version = "3.11" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/6f/6d/0703ccc57f3a7233505399edb88de3cbd678da106337b9fcde432b65ed60/idna-3.11.tar.gz", hash = "sha256:795dafcc9c04ed0c1fb032c2aa73654d8e8c5023a7df64a53f39190ada629902", size = 194582, upload-time = "2025-10-12T14:55:20.501Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl", hash = "sha256:771a87f49d9defaf64091e6e6fe9c18d4833f140bd19464795bc32d966ca37ea", size = 71008, upload-time = "2025-10-12T14:55:18.883Z" }, -] - -[[package]] -name = "importlib-metadata" -version = "8.7.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "zipp" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/76/66/650a33bd90f786193e4de4b3ad86ea60b53c89b669a5c7be931fac31cdb0/importlib_metadata-8.7.0.tar.gz", hash = "sha256:d13b81ad223b890aa16c5471f2ac3056cf76c5f10f82d6f9292f0b415f389000", size = 56641, upload-time = "2025-04-27T15:29:01.736Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/20/b0/36bd937216ec521246249be3bf9855081de4c5e06a0c9b4219dbeda50373/importlib_metadata-8.7.0-py3-none-any.whl", hash = "sha256:e5dd1551894c77868a30651cef00984d50e1002d06942a7101d34870c5f02afd", size = 27656, upload-time = "2025-04-27T15:29:00.214Z" }, -] - -[[package]] -name = "iniconfig" -version = "2.3.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/72/34/14ca021ce8e5dfedc35312d08ba8bf51fdd999c576889fc2c24cb97f4f10/iniconfig-2.3.0.tar.gz", hash = "sha256:c76315c77db068650d49c5b56314774a7804df16fee4402c1f19d6d15d8c4730", size = 20503, upload-time = "2025-10-18T21:55:43.219Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl", hash = "sha256:f631c04d2c48c52b84d0d0549c99ff3859c98df65b3101406327ecc7d53fbf12", size = 7484, upload-time = "2025-10-18T21:55:41.639Z" }, -] - -[[package]] -name = "jsonschema" -version = "4.25.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "attrs" }, - { name = "jsonschema-specifications" }, - { name = "referencing" }, - { name = "rpds-py" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/74/69/f7185de793a29082a9f3c7728268ffb31cb5095131a9c139a74078e27336/jsonschema-4.25.1.tar.gz", hash = "sha256:e4a9655ce0da0c0b67a085847e00a3a51449e1157f4f75e9fb5aa545e122eb85", size = 357342, upload-time = "2025-08-18T17:03:50.038Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/bf/9c/8c95d856233c1f82500c2450b8c68576b4cf1c871db3afac5c34ff84e6fd/jsonschema-4.25.1-py3-none-any.whl", hash = "sha256:3fba0169e345c7175110351d456342c364814cfcf3b964ba4587f22915230a63", size = 90040, upload-time = "2025-08-18T17:03:48.373Z" }, -] - -[[package]] -name = "jsonschema-specifications" -version = "2025.9.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "referencing" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/19/74/a633ee74eb36c44aa6d1095e7cc5569bebf04342ee146178e2d36600708b/jsonschema_specifications-2025.9.1.tar.gz", hash = "sha256:b540987f239e745613c7a9176f3edb72b832a4ac465cf02712288397832b5e8d", size = 32855, upload-time = "2025-09-08T01:34:59.186Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl", hash = "sha256:98802fee3a11ee76ecaca44429fda8a41bff98b00a0f2838151b113f210cc6fe", size = 18437, upload-time = "2025-09-08T01:34:57.871Z" }, -] - -[[package]] -name = "mako" -version = "1.3.10" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "markupsafe" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/9e/38/bd5b78a920a64d708fe6bc8e0a2c075e1389d53bef8413725c63ba041535/mako-1.3.10.tar.gz", hash = "sha256:99579a6f39583fa7e5630a28c3c1f440e4e97a414b80372649c0ce338da2ea28", size = 392474, upload-time = "2025-04-10T12:44:31.16Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/87/fb/99f81ac72ae23375f22b7afdb7642aba97c00a713c217124420147681a2f/mako-1.3.10-py3-none-any.whl", hash = "sha256:baef24a52fc4fc514a0887ac600f9f1cff3d82c61d4d700a1fa84d597b88db59", size = 78509, upload-time = "2025-04-10T12:50:53.297Z" }, -] - -[[package]] -name = "markupsafe" -version = "3.0.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/7e/99/7690b6d4034fffd95959cbe0c02de8deb3098cc577c67bb6a24fe5d7caa7/markupsafe-3.0.3.tar.gz", hash = "sha256:722695808f4b6457b320fdc131280796bdceb04ab50fe1795cd540799ebe1698", size = 80313, upload-time = "2025-09-27T18:37:40.426Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e8/4b/3541d44f3937ba468b75da9eebcae497dcf67adb65caa16760b0a6807ebb/markupsafe-3.0.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:2f981d352f04553a7171b8e44369f2af4055f888dfb147d55e42d29e29e74559", size = 11631, upload-time = "2025-09-27T18:36:05.558Z" }, - { url = "https://files.pythonhosted.org/packages/98/1b/fbd8eed11021cabd9226c37342fa6ca4e8a98d8188a8d9b66740494960e4/markupsafe-3.0.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e1c1493fb6e50ab01d20a22826e57520f1284df32f2d8601fdd90b6304601419", size = 12057, upload-time = "2025-09-27T18:36:07.165Z" }, - { url = "https://files.pythonhosted.org/packages/40/01/e560d658dc0bb8ab762670ece35281dec7b6c1b33f5fbc09ebb57a185519/markupsafe-3.0.3-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:1ba88449deb3de88bd40044603fafffb7bc2b055d626a330323a9ed736661695", size = 22050, upload-time = "2025-09-27T18:36:08.005Z" }, - { url = "https://files.pythonhosted.org/packages/af/cd/ce6e848bbf2c32314c9b237839119c5a564a59725b53157c856e90937b7a/markupsafe-3.0.3-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:f42d0984e947b8adf7dd6dde396e720934d12c506ce84eea8476409563607591", size = 20681, upload-time = "2025-09-27T18:36:08.881Z" }, - { url = "https://files.pythonhosted.org/packages/c9/2a/b5c12c809f1c3045c4d580b035a743d12fcde53cf685dbc44660826308da/markupsafe-3.0.3-cp310-cp310-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:c0c0b3ade1c0b13b936d7970b1d37a57acde9199dc2aecc4c336773e1d86049c", size = 20705, upload-time = "2025-09-27T18:36:10.131Z" }, - { url = "https://files.pythonhosted.org/packages/cf/e3/9427a68c82728d0a88c50f890d0fc072a1484de2f3ac1ad0bfc1a7214fd5/markupsafe-3.0.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:0303439a41979d9e74d18ff5e2dd8c43ed6c6001fd40e5bf2e43f7bd9bbc523f", size = 21524, upload-time = "2025-09-27T18:36:11.324Z" }, - { url = "https://files.pythonhosted.org/packages/bc/36/23578f29e9e582a4d0278e009b38081dbe363c5e7165113fad546918a232/markupsafe-3.0.3-cp310-cp310-musllinux_1_2_riscv64.whl", hash = "sha256:d2ee202e79d8ed691ceebae8e0486bd9a2cd4794cec4824e1c99b6f5009502f6", size = 20282, upload-time = "2025-09-27T18:36:12.573Z" }, - { url = "https://files.pythonhosted.org/packages/56/21/dca11354e756ebd03e036bd8ad58d6d7168c80ce1fe5e75218e4945cbab7/markupsafe-3.0.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:177b5253b2834fe3678cb4a5f0059808258584c559193998be2601324fdeafb1", size = 20745, upload-time = "2025-09-27T18:36:13.504Z" }, - { url = "https://files.pythonhosted.org/packages/87/99/faba9369a7ad6e4d10b6a5fbf71fa2a188fe4a593b15f0963b73859a1bbd/markupsafe-3.0.3-cp310-cp310-win32.whl", hash = "sha256:2a15a08b17dd94c53a1da0438822d70ebcd13f8c3a95abe3a9ef9f11a94830aa", size = 14571, upload-time = "2025-09-27T18:36:14.779Z" }, - { url = "https://files.pythonhosted.org/packages/d6/25/55dc3ab959917602c96985cb1253efaa4ff42f71194bddeb61eb7278b8be/markupsafe-3.0.3-cp310-cp310-win_amd64.whl", hash = "sha256:c4ffb7ebf07cfe8931028e3e4c85f0357459a3f9f9490886198848f4fa002ec8", size = 15056, upload-time = "2025-09-27T18:36:16.125Z" }, - { url = "https://files.pythonhosted.org/packages/d0/9e/0a02226640c255d1da0b8d12e24ac2aa6734da68bff14c05dd53b94a0fc3/markupsafe-3.0.3-cp310-cp310-win_arm64.whl", hash = "sha256:e2103a929dfa2fcaf9bb4e7c091983a49c9ac3b19c9061b6d5427dd7d14d81a1", size = 13932, upload-time = "2025-09-27T18:36:17.311Z" }, - { url = "https://files.pythonhosted.org/packages/08/db/fefacb2136439fc8dd20e797950e749aa1f4997ed584c62cfb8ef7c2be0e/markupsafe-3.0.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:1cc7ea17a6824959616c525620e387f6dd30fec8cb44f649e31712db02123dad", size = 11631, upload-time = "2025-09-27T18:36:18.185Z" }, - { url = "https://files.pythonhosted.org/packages/e1/2e/5898933336b61975ce9dc04decbc0a7f2fee78c30353c5efba7f2d6ff27a/markupsafe-3.0.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:4bd4cd07944443f5a265608cc6aab442e4f74dff8088b0dfc8238647b8f6ae9a", size = 12058, upload-time = "2025-09-27T18:36:19.444Z" }, - { url = "https://files.pythonhosted.org/packages/1d/09/adf2df3699d87d1d8184038df46a9c80d78c0148492323f4693df54e17bb/markupsafe-3.0.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6b5420a1d9450023228968e7e6a9ce57f65d148ab56d2313fcd589eee96a7a50", size = 24287, upload-time = "2025-09-27T18:36:20.768Z" }, - { url = "https://files.pythonhosted.org/packages/30/ac/0273f6fcb5f42e314c6d8cd99effae6a5354604d461b8d392b5ec9530a54/markupsafe-3.0.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0bf2a864d67e76e5c9a34dc26ec616a66b9888e25e7b9460e1c76d3293bd9dbf", size = 22940, upload-time = "2025-09-27T18:36:22.249Z" }, - { url = "https://files.pythonhosted.org/packages/19/ae/31c1be199ef767124c042c6c3e904da327a2f7f0cd63a0337e1eca2967a8/markupsafe-3.0.3-cp311-cp311-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:bc51efed119bc9cfdf792cdeaa4d67e8f6fcccab66ed4bfdd6bde3e59bfcbb2f", size = 21887, upload-time = "2025-09-27T18:36:23.535Z" }, - { url = "https://files.pythonhosted.org/packages/b2/76/7edcab99d5349a4532a459e1fe64f0b0467a3365056ae550d3bcf3f79e1e/markupsafe-3.0.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:068f375c472b3e7acbe2d5318dea141359e6900156b5b2ba06a30b169086b91a", size = 23692, upload-time = "2025-09-27T18:36:24.823Z" }, - { url = "https://files.pythonhosted.org/packages/a4/28/6e74cdd26d7514849143d69f0bf2399f929c37dc2b31e6829fd2045b2765/markupsafe-3.0.3-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:7be7b61bb172e1ed687f1754f8e7484f1c8019780f6f6b0786e76bb01c2ae115", size = 21471, upload-time = "2025-09-27T18:36:25.95Z" }, - { url = "https://files.pythonhosted.org/packages/62/7e/a145f36a5c2945673e590850a6f8014318d5577ed7e5920a4b3448e0865d/markupsafe-3.0.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:f9e130248f4462aaa8e2552d547f36ddadbeaa573879158d721bbd33dfe4743a", size = 22923, upload-time = "2025-09-27T18:36:27.109Z" }, - { url = "https://files.pythonhosted.org/packages/0f/62/d9c46a7f5c9adbeeeda52f5b8d802e1094e9717705a645efc71b0913a0a8/markupsafe-3.0.3-cp311-cp311-win32.whl", hash = "sha256:0db14f5dafddbb6d9208827849fad01f1a2609380add406671a26386cdf15a19", size = 14572, upload-time = "2025-09-27T18:36:28.045Z" }, - { url = "https://files.pythonhosted.org/packages/83/8a/4414c03d3f891739326e1783338e48fb49781cc915b2e0ee052aa490d586/markupsafe-3.0.3-cp311-cp311-win_amd64.whl", hash = "sha256:de8a88e63464af587c950061a5e6a67d3632e36df62b986892331d4620a35c01", size = 15077, upload-time = "2025-09-27T18:36:29.025Z" }, - { url = "https://files.pythonhosted.org/packages/35/73/893072b42e6862f319b5207adc9ae06070f095b358655f077f69a35601f0/markupsafe-3.0.3-cp311-cp311-win_arm64.whl", hash = "sha256:3b562dd9e9ea93f13d53989d23a7e775fdfd1066c33494ff43f5418bc8c58a5c", size = 13876, upload-time = "2025-09-27T18:36:29.954Z" }, - { url = "https://files.pythonhosted.org/packages/5a/72/147da192e38635ada20e0a2e1a51cf8823d2119ce8883f7053879c2199b5/markupsafe-3.0.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:d53197da72cc091b024dd97249dfc7794d6a56530370992a5e1a08983ad9230e", size = 11615, upload-time = "2025-09-27T18:36:30.854Z" }, - { url = "https://files.pythonhosted.org/packages/9a/81/7e4e08678a1f98521201c3079f77db69fb552acd56067661f8c2f534a718/markupsafe-3.0.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:1872df69a4de6aead3491198eaf13810b565bdbeec3ae2dc8780f14458ec73ce", size = 12020, upload-time = "2025-09-27T18:36:31.971Z" }, - { url = "https://files.pythonhosted.org/packages/1e/2c/799f4742efc39633a1b54a92eec4082e4f815314869865d876824c257c1e/markupsafe-3.0.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:3a7e8ae81ae39e62a41ec302f972ba6ae23a5c5396c8e60113e9066ef893da0d", size = 24332, upload-time = "2025-09-27T18:36:32.813Z" }, - { url = "https://files.pythonhosted.org/packages/3c/2e/8d0c2ab90a8c1d9a24f0399058ab8519a3279d1bd4289511d74e909f060e/markupsafe-3.0.3-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d6dd0be5b5b189d31db7cda48b91d7e0a9795f31430b7f271219ab30f1d3ac9d", size = 22947, upload-time = "2025-09-27T18:36:33.86Z" }, - { url = "https://files.pythonhosted.org/packages/2c/54/887f3092a85238093a0b2154bd629c89444f395618842e8b0c41783898ea/markupsafe-3.0.3-cp312-cp312-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:94c6f0bb423f739146aec64595853541634bde58b2135f27f61c1ffd1cd4d16a", size = 21962, upload-time = "2025-09-27T18:36:35.099Z" }, - { url = "https://files.pythonhosted.org/packages/c9/2f/336b8c7b6f4a4d95e91119dc8521402461b74a485558d8f238a68312f11c/markupsafe-3.0.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:be8813b57049a7dc738189df53d69395eba14fb99345e0a5994914a3864c8a4b", size = 23760, upload-time = "2025-09-27T18:36:36.001Z" }, - { url = "https://files.pythonhosted.org/packages/32/43/67935f2b7e4982ffb50a4d169b724d74b62a3964bc1a9a527f5ac4f1ee2b/markupsafe-3.0.3-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:83891d0e9fb81a825d9a6d61e3f07550ca70a076484292a70fde82c4b807286f", size = 21529, upload-time = "2025-09-27T18:36:36.906Z" }, - { url = "https://files.pythonhosted.org/packages/89/e0/4486f11e51bbba8b0c041098859e869e304d1c261e59244baa3d295d47b7/markupsafe-3.0.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:77f0643abe7495da77fb436f50f8dab76dbc6e5fd25d39589a0f1fe6548bfa2b", size = 23015, upload-time = "2025-09-27T18:36:37.868Z" }, - { url = "https://files.pythonhosted.org/packages/2f/e1/78ee7a023dac597a5825441ebd17170785a9dab23de95d2c7508ade94e0e/markupsafe-3.0.3-cp312-cp312-win32.whl", hash = "sha256:d88b440e37a16e651bda4c7c2b930eb586fd15ca7406cb39e211fcff3bf3017d", size = 14540, upload-time = "2025-09-27T18:36:38.761Z" }, - { url = "https://files.pythonhosted.org/packages/aa/5b/bec5aa9bbbb2c946ca2733ef9c4ca91c91b6a24580193e891b5f7dbe8e1e/markupsafe-3.0.3-cp312-cp312-win_amd64.whl", hash = "sha256:26a5784ded40c9e318cfc2bdb30fe164bdb8665ded9cd64d500a34fb42067b1c", size = 15105, upload-time = "2025-09-27T18:36:39.701Z" }, - { url = "https://files.pythonhosted.org/packages/e5/f1/216fc1bbfd74011693a4fd837e7026152e89c4bcf3e77b6692fba9923123/markupsafe-3.0.3-cp312-cp312-win_arm64.whl", hash = "sha256:35add3b638a5d900e807944a078b51922212fb3dedb01633a8defc4b01a3c85f", size = 13906, upload-time = "2025-09-27T18:36:40.689Z" }, - { url = "https://files.pythonhosted.org/packages/38/2f/907b9c7bbba283e68f20259574b13d005c121a0fa4c175f9bed27c4597ff/markupsafe-3.0.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:e1cf1972137e83c5d4c136c43ced9ac51d0e124706ee1c8aa8532c1287fa8795", size = 11622, upload-time = "2025-09-27T18:36:41.777Z" }, - { url = "https://files.pythonhosted.org/packages/9c/d9/5f7756922cdd676869eca1c4e3c0cd0df60ed30199ffd775e319089cb3ed/markupsafe-3.0.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:116bb52f642a37c115f517494ea5feb03889e04df47eeff5b130b1808ce7c219", size = 12029, upload-time = "2025-09-27T18:36:43.257Z" }, - { url = "https://files.pythonhosted.org/packages/00/07/575a68c754943058c78f30db02ee03a64b3c638586fba6a6dd56830b30a3/markupsafe-3.0.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:133a43e73a802c5562be9bbcd03d090aa5a1fe899db609c29e8c8d815c5f6de6", size = 24374, upload-time = "2025-09-27T18:36:44.508Z" }, - { url = "https://files.pythonhosted.org/packages/a9/21/9b05698b46f218fc0e118e1f8168395c65c8a2c750ae2bab54fc4bd4e0e8/markupsafe-3.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ccfcd093f13f0f0b7fdd0f198b90053bf7b2f02a3927a30e63f3ccc9df56b676", size = 22980, upload-time = "2025-09-27T18:36:45.385Z" }, - { url = "https://files.pythonhosted.org/packages/7f/71/544260864f893f18b6827315b988c146b559391e6e7e8f7252839b1b846a/markupsafe-3.0.3-cp313-cp313-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:509fa21c6deb7a7a273d629cf5ec029bc209d1a51178615ddf718f5918992ab9", size = 21990, upload-time = "2025-09-27T18:36:46.916Z" }, - { url = "https://files.pythonhosted.org/packages/c2/28/b50fc2f74d1ad761af2f5dcce7492648b983d00a65b8c0e0cb457c82ebbe/markupsafe-3.0.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a4afe79fb3de0b7097d81da19090f4df4f8d3a2b3adaa8764138aac2e44f3af1", size = 23784, upload-time = "2025-09-27T18:36:47.884Z" }, - { url = "https://files.pythonhosted.org/packages/ed/76/104b2aa106a208da8b17a2fb72e033a5a9d7073c68f7e508b94916ed47a9/markupsafe-3.0.3-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:795e7751525cae078558e679d646ae45574b47ed6e7771863fcc079a6171a0fc", size = 21588, upload-time = "2025-09-27T18:36:48.82Z" }, - { url = "https://files.pythonhosted.org/packages/b5/99/16a5eb2d140087ebd97180d95249b00a03aa87e29cc224056274f2e45fd6/markupsafe-3.0.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:8485f406a96febb5140bfeca44a73e3ce5116b2501ac54fe953e488fb1d03b12", size = 23041, upload-time = "2025-09-27T18:36:49.797Z" }, - { url = "https://files.pythonhosted.org/packages/19/bc/e7140ed90c5d61d77cea142eed9f9c303f4c4806f60a1044c13e3f1471d0/markupsafe-3.0.3-cp313-cp313-win32.whl", hash = "sha256:bdd37121970bfd8be76c5fb069c7751683bdf373db1ed6c010162b2a130248ed", size = 14543, upload-time = "2025-09-27T18:36:51.584Z" }, - { url = "https://files.pythonhosted.org/packages/05/73/c4abe620b841b6b791f2edc248f556900667a5a1cf023a6646967ae98335/markupsafe-3.0.3-cp313-cp313-win_amd64.whl", hash = "sha256:9a1abfdc021a164803f4d485104931fb8f8c1efd55bc6b748d2f5774e78b62c5", size = 15113, upload-time = "2025-09-27T18:36:52.537Z" }, - { url = "https://files.pythonhosted.org/packages/f0/3a/fa34a0f7cfef23cf9500d68cb7c32dd64ffd58a12b09225fb03dd37d5b80/markupsafe-3.0.3-cp313-cp313-win_arm64.whl", hash = "sha256:7e68f88e5b8799aa49c85cd116c932a1ac15caaa3f5db09087854d218359e485", size = 13911, upload-time = "2025-09-27T18:36:53.513Z" }, - { url = "https://files.pythonhosted.org/packages/e4/d7/e05cd7efe43a88a17a37b3ae96e79a19e846f3f456fe79c57ca61356ef01/markupsafe-3.0.3-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:218551f6df4868a8d527e3062d0fb968682fe92054e89978594c28e642c43a73", size = 11658, upload-time = "2025-09-27T18:36:54.819Z" }, - { url = "https://files.pythonhosted.org/packages/99/9e/e412117548182ce2148bdeacdda3bb494260c0b0184360fe0d56389b523b/markupsafe-3.0.3-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:3524b778fe5cfb3452a09d31e7b5adefeea8c5be1d43c4f810ba09f2ceb29d37", size = 12066, upload-time = "2025-09-27T18:36:55.714Z" }, - { url = "https://files.pythonhosted.org/packages/bc/e6/fa0ffcda717ef64a5108eaa7b4f5ed28d56122c9a6d70ab8b72f9f715c80/markupsafe-3.0.3-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4e885a3d1efa2eadc93c894a21770e4bc67899e3543680313b09f139e149ab19", size = 25639, upload-time = "2025-09-27T18:36:56.908Z" }, - { url = "https://files.pythonhosted.org/packages/96/ec/2102e881fe9d25fc16cb4b25d5f5cde50970967ffa5dddafdb771237062d/markupsafe-3.0.3-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:8709b08f4a89aa7586de0aadc8da56180242ee0ada3999749b183aa23df95025", size = 23569, upload-time = "2025-09-27T18:36:57.913Z" }, - { url = "https://files.pythonhosted.org/packages/4b/30/6f2fce1f1f205fc9323255b216ca8a235b15860c34b6798f810f05828e32/markupsafe-3.0.3-cp313-cp313t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:b8512a91625c9b3da6f127803b166b629725e68af71f8184ae7e7d54686a56d6", size = 23284, upload-time = "2025-09-27T18:36:58.833Z" }, - { url = "https://files.pythonhosted.org/packages/58/47/4a0ccea4ab9f5dcb6f79c0236d954acb382202721e704223a8aafa38b5c8/markupsafe-3.0.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:9b79b7a16f7fedff2495d684f2b59b0457c3b493778c9eed31111be64d58279f", size = 24801, upload-time = "2025-09-27T18:36:59.739Z" }, - { url = "https://files.pythonhosted.org/packages/6a/70/3780e9b72180b6fecb83a4814d84c3bf4b4ae4bf0b19c27196104149734c/markupsafe-3.0.3-cp313-cp313t-musllinux_1_2_riscv64.whl", hash = "sha256:12c63dfb4a98206f045aa9563db46507995f7ef6d83b2f68eda65c307c6829eb", size = 22769, upload-time = "2025-09-27T18:37:00.719Z" }, - { url = "https://files.pythonhosted.org/packages/98/c5/c03c7f4125180fc215220c035beac6b9cb684bc7a067c84fc69414d315f5/markupsafe-3.0.3-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:8f71bc33915be5186016f675cd83a1e08523649b0e33efdb898db577ef5bb009", size = 23642, upload-time = "2025-09-27T18:37:01.673Z" }, - { url = "https://files.pythonhosted.org/packages/80/d6/2d1b89f6ca4bff1036499b1e29a1d02d282259f3681540e16563f27ebc23/markupsafe-3.0.3-cp313-cp313t-win32.whl", hash = "sha256:69c0b73548bc525c8cb9a251cddf1931d1db4d2258e9599c28c07ef3580ef354", size = 14612, upload-time = "2025-09-27T18:37:02.639Z" }, - { url = "https://files.pythonhosted.org/packages/2b/98/e48a4bfba0a0ffcf9925fe2d69240bfaa19c6f7507b8cd09c70684a53c1e/markupsafe-3.0.3-cp313-cp313t-win_amd64.whl", hash = "sha256:1b4b79e8ebf6b55351f0d91fe80f893b4743f104bff22e90697db1590e47a218", size = 15200, upload-time = "2025-09-27T18:37:03.582Z" }, - { url = "https://files.pythonhosted.org/packages/0e/72/e3cc540f351f316e9ed0f092757459afbc595824ca724cbc5a5d4263713f/markupsafe-3.0.3-cp313-cp313t-win_arm64.whl", hash = "sha256:ad2cf8aa28b8c020ab2fc8287b0f823d0a7d8630784c31e9ee5edea20f406287", size = 13973, upload-time = "2025-09-27T18:37:04.929Z" }, - { url = "https://files.pythonhosted.org/packages/33/8a/8e42d4838cd89b7dde187011e97fe6c3af66d8c044997d2183fbd6d31352/markupsafe-3.0.3-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:eaa9599de571d72e2daf60164784109f19978b327a3910d3e9de8c97b5b70cfe", size = 11619, upload-time = "2025-09-27T18:37:06.342Z" }, - { url = "https://files.pythonhosted.org/packages/b5/64/7660f8a4a8e53c924d0fa05dc3a55c9cee10bbd82b11c5afb27d44b096ce/markupsafe-3.0.3-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:c47a551199eb8eb2121d4f0f15ae0f923d31350ab9280078d1e5f12b249e0026", size = 12029, upload-time = "2025-09-27T18:37:07.213Z" }, - { url = "https://files.pythonhosted.org/packages/da/ef/e648bfd021127bef5fa12e1720ffed0c6cbb8310c8d9bea7266337ff06de/markupsafe-3.0.3-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f34c41761022dd093b4b6896d4810782ffbabe30f2d443ff5f083e0cbbb8c737", size = 24408, upload-time = "2025-09-27T18:37:09.572Z" }, - { url = "https://files.pythonhosted.org/packages/41/3c/a36c2450754618e62008bf7435ccb0f88053e07592e6028a34776213d877/markupsafe-3.0.3-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:457a69a9577064c05a97c41f4e65148652db078a3a509039e64d3467b9e7ef97", size = 23005, upload-time = "2025-09-27T18:37:10.58Z" }, - { url = "https://files.pythonhosted.org/packages/bc/20/b7fdf89a8456b099837cd1dc21974632a02a999ec9bf7ca3e490aacd98e7/markupsafe-3.0.3-cp314-cp314-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:e8afc3f2ccfa24215f8cb28dcf43f0113ac3c37c2f0f0806d8c70e4228c5cf4d", size = 22048, upload-time = "2025-09-27T18:37:11.547Z" }, - { url = "https://files.pythonhosted.org/packages/9a/a7/591f592afdc734f47db08a75793a55d7fbcc6902a723ae4cfbab61010cc5/markupsafe-3.0.3-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:ec15a59cf5af7be74194f7ab02d0f59a62bdcf1a537677ce67a2537c9b87fcda", size = 23821, upload-time = "2025-09-27T18:37:12.48Z" }, - { url = "https://files.pythonhosted.org/packages/7d/33/45b24e4f44195b26521bc6f1a82197118f74df348556594bd2262bda1038/markupsafe-3.0.3-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:0eb9ff8191e8498cca014656ae6b8d61f39da5f95b488805da4bb029cccbfbaf", size = 21606, upload-time = "2025-09-27T18:37:13.485Z" }, - { url = "https://files.pythonhosted.org/packages/ff/0e/53dfaca23a69fbfbbf17a4b64072090e70717344c52eaaaa9c5ddff1e5f0/markupsafe-3.0.3-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:2713baf880df847f2bece4230d4d094280f4e67b1e813eec43b4c0e144a34ffe", size = 23043, upload-time = "2025-09-27T18:37:14.408Z" }, - { url = "https://files.pythonhosted.org/packages/46/11/f333a06fc16236d5238bfe74daccbca41459dcd8d1fa952e8fbd5dccfb70/markupsafe-3.0.3-cp314-cp314-win32.whl", hash = "sha256:729586769a26dbceff69f7a7dbbf59ab6572b99d94576a5592625d5b411576b9", size = 14747, upload-time = "2025-09-27T18:37:15.36Z" }, - { url = "https://files.pythonhosted.org/packages/28/52/182836104b33b444e400b14f797212f720cbc9ed6ba34c800639d154e821/markupsafe-3.0.3-cp314-cp314-win_amd64.whl", hash = "sha256:bdc919ead48f234740ad807933cdf545180bfbe9342c2bb451556db2ed958581", size = 15341, upload-time = "2025-09-27T18:37:16.496Z" }, - { url = "https://files.pythonhosted.org/packages/6f/18/acf23e91bd94fd7b3031558b1f013adfa21a8e407a3fdb32745538730382/markupsafe-3.0.3-cp314-cp314-win_arm64.whl", hash = "sha256:5a7d5dc5140555cf21a6fefbdbf8723f06fcd2f63ef108f2854de715e4422cb4", size = 14073, upload-time = "2025-09-27T18:37:17.476Z" }, - { url = "https://files.pythonhosted.org/packages/3c/f0/57689aa4076e1b43b15fdfa646b04653969d50cf30c32a102762be2485da/markupsafe-3.0.3-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:1353ef0c1b138e1907ae78e2f6c63ff67501122006b0f9abad68fda5f4ffc6ab", size = 11661, upload-time = "2025-09-27T18:37:18.453Z" }, - { url = "https://files.pythonhosted.org/packages/89/c3/2e67a7ca217c6912985ec766c6393b636fb0c2344443ff9d91404dc4c79f/markupsafe-3.0.3-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:1085e7fbddd3be5f89cc898938f42c0b3c711fdcb37d75221de2666af647c175", size = 12069, upload-time = "2025-09-27T18:37:19.332Z" }, - { url = "https://files.pythonhosted.org/packages/f0/00/be561dce4e6ca66b15276e184ce4b8aec61fe83662cce2f7d72bd3249d28/markupsafe-3.0.3-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:1b52b4fb9df4eb9ae465f8d0c228a00624de2334f216f178a995ccdcf82c4634", size = 25670, upload-time = "2025-09-27T18:37:20.245Z" }, - { url = "https://files.pythonhosted.org/packages/50/09/c419f6f5a92e5fadde27efd190eca90f05e1261b10dbd8cbcb39cd8ea1dc/markupsafe-3.0.3-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:fed51ac40f757d41b7c48425901843666a6677e3e8eb0abcff09e4ba6e664f50", size = 23598, upload-time = "2025-09-27T18:37:21.177Z" }, - { url = "https://files.pythonhosted.org/packages/22/44/a0681611106e0b2921b3033fc19bc53323e0b50bc70cffdd19f7d679bb66/markupsafe-3.0.3-cp314-cp314t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:f190daf01f13c72eac4efd5c430a8de82489d9cff23c364c3ea822545032993e", size = 23261, upload-time = "2025-09-27T18:37:22.167Z" }, - { url = "https://files.pythonhosted.org/packages/5f/57/1b0b3f100259dc9fffe780cfb60d4be71375510e435efec3d116b6436d43/markupsafe-3.0.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:e56b7d45a839a697b5eb268c82a71bd8c7f6c94d6fd50c3d577fa39a9f1409f5", size = 24835, upload-time = "2025-09-27T18:37:23.296Z" }, - { url = "https://files.pythonhosted.org/packages/26/6a/4bf6d0c97c4920f1597cc14dd720705eca0bf7c787aebc6bb4d1bead5388/markupsafe-3.0.3-cp314-cp314t-musllinux_1_2_riscv64.whl", hash = "sha256:f3e98bb3798ead92273dc0e5fd0f31ade220f59a266ffd8a4f6065e0a3ce0523", size = 22733, upload-time = "2025-09-27T18:37:24.237Z" }, - { url = "https://files.pythonhosted.org/packages/14/c7/ca723101509b518797fedc2fdf79ba57f886b4aca8a7d31857ba3ee8281f/markupsafe-3.0.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:5678211cb9333a6468fb8d8be0305520aa073f50d17f089b5b4b477ea6e67fdc", size = 23672, upload-time = "2025-09-27T18:37:25.271Z" }, - { url = "https://files.pythonhosted.org/packages/fb/df/5bd7a48c256faecd1d36edc13133e51397e41b73bb77e1a69deab746ebac/markupsafe-3.0.3-cp314-cp314t-win32.whl", hash = "sha256:915c04ba3851909ce68ccc2b8e2cd691618c4dc4c4232fb7982bca3f41fd8c3d", size = 14819, upload-time = "2025-09-27T18:37:26.285Z" }, - { url = "https://files.pythonhosted.org/packages/1a/8a/0402ba61a2f16038b48b39bccca271134be00c5c9f0f623208399333c448/markupsafe-3.0.3-cp314-cp314t-win_amd64.whl", hash = "sha256:4faffd047e07c38848ce017e8725090413cd80cbc23d86e55c587bf979e579c9", size = 15426, upload-time = "2025-09-27T18:37:27.316Z" }, - { url = "https://files.pythonhosted.org/packages/70/bc/6f1c2f612465f5fa89b95bead1f44dcb607670fd42891d8fdcd5d039f4f4/markupsafe-3.0.3-cp314-cp314t-win_arm64.whl", hash = "sha256:32001d6a8fc98c8cb5c947787c5d08b0a50663d139f1305bac5885d98d9b40fa", size = 14146, upload-time = "2025-09-27T18:37:28.327Z" }, -] - -[[package]] -name = "mcp" -version = "1.20.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "httpx" }, - { name = "httpx-sse" }, - { name = "jsonschema" }, - { name = "pydantic" }, - { name = "pydantic-settings" }, - { name = "pyjwt", extra = ["crypto"] }, - { name = "python-multipart" }, - { name = "pywin32", marker = "sys_platform == 'win32'" }, - { name = "sse-starlette" }, - { name = "starlette" }, - { name = "uvicorn", marker = "sys_platform != 'emscripten'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/f8/22/fae38092e6c2995c03232635028510d77e7decff31b4ae79dfa0ba99c635/mcp-1.20.0.tar.gz", hash = "sha256:9ccc09eaadbfbcbbdab1c9723cfe2e0d1d9e324d7d3ce7e332ef90b09ed35177", size = 451377, upload-time = "2025-10-30T22:14:53.421Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/df/00/76fc92f4892d47fecb37131d0e95ea69259f077d84c68f6793a0d96cfe80/mcp-1.20.0-py3-none-any.whl", hash = "sha256:d0dc06f93653f7432ff89f694721c87f79876b6f93741bf628ad1e48f7ac5e5d", size = 173136, upload-time = "2025-10-30T22:14:51.078Z" }, -] - -[[package]] -name = "multidict" -version = "6.7.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions", marker = "python_full_version < '3.11'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/80/1e/5492c365f222f907de1039b91f922b93fa4f764c713ee858d235495d8f50/multidict-6.7.0.tar.gz", hash = "sha256:c6e99d9a65ca282e578dfea819cfa9c0a62b2499d8677392e09feaf305e9e6f5", size = 101834, upload-time = "2025-10-06T14:52:30.657Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a9/63/7bdd4adc330abcca54c85728db2327130e49e52e8c3ce685cec44e0f2e9f/multidict-6.7.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:9f474ad5acda359c8758c8accc22032c6abe6dc87a8be2440d097785e27a9349", size = 77153, upload-time = "2025-10-06T14:48:26.409Z" }, - { url = "https://files.pythonhosted.org/packages/3f/bb/b6c35ff175ed1a3142222b78455ee31be71a8396ed3ab5280fbe3ebe4e85/multidict-6.7.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:4b7a9db5a870f780220e931d0002bbfd88fb53aceb6293251e2c839415c1b20e", size = 44993, upload-time = "2025-10-06T14:48:28.4Z" }, - { url = "https://files.pythonhosted.org/packages/e0/1f/064c77877c5fa6df6d346e68075c0f6998547afe952d6471b4c5f6a7345d/multidict-6.7.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:03ca744319864e92721195fa28c7a3b2bc7b686246b35e4078c1e4d0eb5466d3", size = 44607, upload-time = "2025-10-06T14:48:29.581Z" }, - { url = "https://files.pythonhosted.org/packages/04/7a/bf6aa92065dd47f287690000b3d7d332edfccb2277634cadf6a810463c6a/multidict-6.7.0-cp310-cp310-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:f0e77e3c0008bc9316e662624535b88d360c3a5d3f81e15cf12c139a75250046", size = 241847, upload-time = "2025-10-06T14:48:32.107Z" }, - { url = "https://files.pythonhosted.org/packages/94/39/297a8de920f76eda343e4ce05f3b489f0ab3f9504f2576dfb37b7c08ca08/multidict-6.7.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:08325c9e5367aa379a3496aa9a022fe8837ff22e00b94db256d3a1378c76ab32", size = 242616, upload-time = "2025-10-06T14:48:34.054Z" }, - { url = "https://files.pythonhosted.org/packages/39/3a/d0eee2898cfd9d654aea6cb8c4addc2f9756e9a7e09391cfe55541f917f7/multidict-6.7.0-cp310-cp310-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:e2862408c99f84aa571ab462d25236ef9cb12a602ea959ba9c9009a54902fc73", size = 222333, upload-time = "2025-10-06T14:48:35.9Z" }, - { url = "https://files.pythonhosted.org/packages/05/48/3b328851193c7a4240815b71eea165b49248867bbb6153a0aee227a0bb47/multidict-6.7.0-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:4d72a9a2d885f5c208b0cb91ff2ed43636bb7e345ec839ff64708e04f69a13cc", size = 253239, upload-time = "2025-10-06T14:48:37.302Z" }, - { url = "https://files.pythonhosted.org/packages/b1/ca/0706a98c8d126a89245413225ca4a3fefc8435014de309cf8b30acb68841/multidict-6.7.0-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:478cc36476687bac1514d651cbbaa94b86b0732fb6855c60c673794c7dd2da62", size = 251618, upload-time = "2025-10-06T14:48:38.963Z" }, - { url = "https://files.pythonhosted.org/packages/5e/4f/9c7992f245554d8b173f6f0a048ad24b3e645d883f096857ec2c0822b8bd/multidict-6.7.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:6843b28b0364dc605f21481c90fadb5f60d9123b442eb8a726bb74feef588a84", size = 241655, upload-time = "2025-10-06T14:48:40.312Z" }, - { url = "https://files.pythonhosted.org/packages/31/79/26a85991ae67efd1c0b1fc2e0c275b8a6aceeb155a68861f63f87a798f16/multidict-6.7.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:23bfeee5316266e5ee2d625df2d2c602b829435fc3a235c2ba2131495706e4a0", size = 239245, upload-time = "2025-10-06T14:48:41.848Z" }, - { url = "https://files.pythonhosted.org/packages/14/1e/75fa96394478930b79d0302eaf9a6c69f34005a1a5251ac8b9c336486ec9/multidict-6.7.0-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:680878b9f3d45c31e1f730eef731f9b0bc1da456155688c6745ee84eb818e90e", size = 233523, upload-time = "2025-10-06T14:48:43.749Z" }, - { url = "https://files.pythonhosted.org/packages/b2/5e/085544cb9f9c4ad2b5d97467c15f856df8d9bac410cffd5c43991a5d878b/multidict-6.7.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:eb866162ef2f45063acc7a53a88ef6fe8bf121d45c30ea3c9cd87ce7e191a8d4", size = 243129, upload-time = "2025-10-06T14:48:45.225Z" }, - { url = "https://files.pythonhosted.org/packages/b9/c3/e9d9e2f20c9474e7a8fcef28f863c5cbd29bb5adce6b70cebe8bdad0039d/multidict-6.7.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:df0e3bf7993bdbeca5ac25aa859cf40d39019e015c9c91809ba7093967f7a648", size = 248999, upload-time = "2025-10-06T14:48:46.703Z" }, - { url = "https://files.pythonhosted.org/packages/b5/3f/df171b6efa3239ae33b97b887e42671cd1d94d460614bfb2c30ffdab3b95/multidict-6.7.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:661709cdcd919a2ece2234f9bae7174e5220c80b034585d7d8a755632d3e2111", size = 243711, upload-time = "2025-10-06T14:48:48.146Z" }, - { url = "https://files.pythonhosted.org/packages/3c/2f/9b5564888c4e14b9af64c54acf149263721a283aaf4aa0ae89b091d5d8c1/multidict-6.7.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:096f52730c3fb8ed419db2d44391932b63891b2c5ed14850a7e215c0ba9ade36", size = 237504, upload-time = "2025-10-06T14:48:49.447Z" }, - { url = "https://files.pythonhosted.org/packages/6c/3a/0bd6ca0f7d96d790542d591c8c3354c1e1b6bfd2024d4d92dc3d87485ec7/multidict-6.7.0-cp310-cp310-win32.whl", hash = "sha256:afa8a2978ec65d2336305550535c9c4ff50ee527914328c8677b3973ade52b85", size = 41422, upload-time = "2025-10-06T14:48:50.789Z" }, - { url = "https://files.pythonhosted.org/packages/00/35/f6a637ea2c75f0d3b7c7d41b1189189acff0d9deeb8b8f35536bb30f5e33/multidict-6.7.0-cp310-cp310-win_amd64.whl", hash = "sha256:b15b3afff74f707b9275d5ba6a91ae8f6429c3ffb29bbfd216b0b375a56f13d7", size = 46050, upload-time = "2025-10-06T14:48:51.938Z" }, - { url = "https://files.pythonhosted.org/packages/e7/b8/f7bf8329b39893d02d9d95cf610c75885d12fc0f402b1c894e1c8e01c916/multidict-6.7.0-cp310-cp310-win_arm64.whl", hash = "sha256:4b73189894398d59131a66ff157837b1fafea9974be486d036bb3d32331fdbf0", size = 43153, upload-time = "2025-10-06T14:48:53.146Z" }, - { url = "https://files.pythonhosted.org/packages/34/9e/5c727587644d67b2ed479041e4b1c58e30afc011e3d45d25bbe35781217c/multidict-6.7.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:4d409aa42a94c0b3fa617708ef5276dfe81012ba6753a0370fcc9d0195d0a1fc", size = 76604, upload-time = "2025-10-06T14:48:54.277Z" }, - { url = "https://files.pythonhosted.org/packages/17/e4/67b5c27bd17c085a5ea8f1ec05b8a3e5cba0ca734bfcad5560fb129e70ca/multidict-6.7.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:14c9e076eede3b54c636f8ce1c9c252b5f057c62131211f0ceeec273810c9721", size = 44715, upload-time = "2025-10-06T14:48:55.445Z" }, - { url = "https://files.pythonhosted.org/packages/4d/e1/866a5d77be6ea435711bef2a4291eed11032679b6b28b56b4776ab06ba3e/multidict-6.7.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:4c09703000a9d0fa3c3404b27041e574cc7f4df4c6563873246d0e11812a94b6", size = 44332, upload-time = "2025-10-06T14:48:56.706Z" }, - { url = "https://files.pythonhosted.org/packages/31/61/0c2d50241ada71ff61a79518db85ada85fdabfcf395d5968dae1cbda04e5/multidict-6.7.0-cp311-cp311-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:a265acbb7bb33a3a2d626afbe756371dce0279e7b17f4f4eda406459c2b5ff1c", size = 245212, upload-time = "2025-10-06T14:48:58.042Z" }, - { url = "https://files.pythonhosted.org/packages/ac/e0/919666a4e4b57fff1b57f279be1c9316e6cdc5de8a8b525d76f6598fefc7/multidict-6.7.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:51cb455de290ae462593e5b1cb1118c5c22ea7f0d3620d9940bf695cea5a4bd7", size = 246671, upload-time = "2025-10-06T14:49:00.004Z" }, - { url = "https://files.pythonhosted.org/packages/a1/cc/d027d9c5a520f3321b65adea289b965e7bcbd2c34402663f482648c716ce/multidict-6.7.0-cp311-cp311-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:db99677b4457c7a5c5a949353e125ba72d62b35f74e26da141530fbb012218a7", size = 225491, upload-time = "2025-10-06T14:49:01.393Z" }, - { url = "https://files.pythonhosted.org/packages/75/c4/bbd633980ce6155a28ff04e6a6492dd3335858394d7bb752d8b108708558/multidict-6.7.0-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:f470f68adc395e0183b92a2f4689264d1ea4b40504a24d9882c27375e6662bb9", size = 257322, upload-time = "2025-10-06T14:49:02.745Z" }, - { url = "https://files.pythonhosted.org/packages/4c/6d/d622322d344f1f053eae47e033b0b3f965af01212de21b10bcf91be991fb/multidict-6.7.0-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:0db4956f82723cc1c270de9c6e799b4c341d327762ec78ef82bb962f79cc07d8", size = 254694, upload-time = "2025-10-06T14:49:04.15Z" }, - { url = "https://files.pythonhosted.org/packages/a8/9f/78f8761c2705d4c6d7516faed63c0ebdac569f6db1bef95e0d5218fdc146/multidict-6.7.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:3e56d780c238f9e1ae66a22d2adf8d16f485381878250db8d496623cd38b22bd", size = 246715, upload-time = "2025-10-06T14:49:05.967Z" }, - { url = "https://files.pythonhosted.org/packages/78/59/950818e04f91b9c2b95aab3d923d9eabd01689d0dcd889563988e9ea0fd8/multidict-6.7.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:9d14baca2ee12c1a64740d4531356ba50b82543017f3ad6de0deb943c5979abb", size = 243189, upload-time = "2025-10-06T14:49:07.37Z" }, - { url = "https://files.pythonhosted.org/packages/7a/3d/77c79e1934cad2ee74991840f8a0110966d9599b3af95964c0cd79bb905b/multidict-6.7.0-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:295a92a76188917c7f99cda95858c822f9e4aae5824246bba9b6b44004ddd0a6", size = 237845, upload-time = "2025-10-06T14:49:08.759Z" }, - { url = "https://files.pythonhosted.org/packages/63/1b/834ce32a0a97a3b70f86437f685f880136677ac00d8bce0027e9fd9c2db7/multidict-6.7.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:39f1719f57adbb767ef592a50ae5ebb794220d1188f9ca93de471336401c34d2", size = 246374, upload-time = "2025-10-06T14:49:10.574Z" }, - { url = "https://files.pythonhosted.org/packages/23/ef/43d1c3ba205b5dec93dc97f3fba179dfa47910fc73aaaea4f7ceb41cec2a/multidict-6.7.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:0a13fb8e748dfc94749f622de065dd5c1def7e0d2216dba72b1d8069a389c6ff", size = 253345, upload-time = "2025-10-06T14:49:12.331Z" }, - { url = "https://files.pythonhosted.org/packages/6b/03/eaf95bcc2d19ead522001f6a650ef32811aa9e3624ff0ad37c445c7a588c/multidict-6.7.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:e3aa16de190d29a0ea1b48253c57d99a68492c8dd8948638073ab9e74dc9410b", size = 246940, upload-time = "2025-10-06T14:49:13.821Z" }, - { url = "https://files.pythonhosted.org/packages/e8/df/ec8a5fd66ea6cd6f525b1fcbb23511b033c3e9bc42b81384834ffa484a62/multidict-6.7.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:a048ce45dcdaaf1defb76b2e684f997fb5abf74437b6cb7b22ddad934a964e34", size = 242229, upload-time = "2025-10-06T14:49:15.603Z" }, - { url = "https://files.pythonhosted.org/packages/8a/a2/59b405d59fd39ec86d1142630e9049243015a5f5291ba49cadf3c090c541/multidict-6.7.0-cp311-cp311-win32.whl", hash = "sha256:a90af66facec4cebe4181b9e62a68be65e45ac9b52b67de9eec118701856e7ff", size = 41308, upload-time = "2025-10-06T14:49:16.871Z" }, - { url = "https://files.pythonhosted.org/packages/32/0f/13228f26f8b882c34da36efa776c3b7348455ec383bab4a66390e42963ae/multidict-6.7.0-cp311-cp311-win_amd64.whl", hash = "sha256:95b5ffa4349df2887518bb839409bcf22caa72d82beec453216802f475b23c81", size = 46037, upload-time = "2025-10-06T14:49:18.457Z" }, - { url = "https://files.pythonhosted.org/packages/84/1f/68588e31b000535a3207fd3c909ebeec4fb36b52c442107499c18a896a2a/multidict-6.7.0-cp311-cp311-win_arm64.whl", hash = "sha256:329aa225b085b6f004a4955271a7ba9f1087e39dcb7e65f6284a988264a63912", size = 43023, upload-time = "2025-10-06T14:49:19.648Z" }, - { url = "https://files.pythonhosted.org/packages/c2/9e/9f61ac18d9c8b475889f32ccfa91c9f59363480613fc807b6e3023d6f60b/multidict-6.7.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:8a3862568a36d26e650a19bb5cbbba14b71789032aebc0423f8cc5f150730184", size = 76877, upload-time = "2025-10-06T14:49:20.884Z" }, - { url = "https://files.pythonhosted.org/packages/38/6f/614f09a04e6184f8824268fce4bc925e9849edfa654ddd59f0b64508c595/multidict-6.7.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:960c60b5849b9b4f9dcc9bea6e3626143c252c74113df2c1540aebce70209b45", size = 45467, upload-time = "2025-10-06T14:49:22.054Z" }, - { url = "https://files.pythonhosted.org/packages/b3/93/c4f67a436dd026f2e780c433277fff72be79152894d9fc36f44569cab1a6/multidict-6.7.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:2049be98fb57a31b4ccf870bf377af2504d4ae35646a19037ec271e4c07998aa", size = 43834, upload-time = "2025-10-06T14:49:23.566Z" }, - { url = "https://files.pythonhosted.org/packages/7f/f5/013798161ca665e4a422afbc5e2d9e4070142a9ff8905e482139cd09e4d0/multidict-6.7.0-cp312-cp312-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:0934f3843a1860dd465d38895c17fce1f1cb37295149ab05cd1b9a03afacb2a7", size = 250545, upload-time = "2025-10-06T14:49:24.882Z" }, - { url = "https://files.pythonhosted.org/packages/71/2f/91dbac13e0ba94669ea5119ba267c9a832f0cb65419aca75549fcf09a3dc/multidict-6.7.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b3e34f3a1b8131ba06f1a73adab24f30934d148afcd5f5de9a73565a4404384e", size = 258305, upload-time = "2025-10-06T14:49:26.778Z" }, - { url = "https://files.pythonhosted.org/packages/ef/b0/754038b26f6e04488b48ac621f779c341338d78503fb45403755af2df477/multidict-6.7.0-cp312-cp312-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:efbb54e98446892590dc2458c19c10344ee9a883a79b5cec4bc34d6656e8d546", size = 242363, upload-time = "2025-10-06T14:49:28.562Z" }, - { url = "https://files.pythonhosted.org/packages/87/15/9da40b9336a7c9fa606c4cf2ed80a649dffeb42b905d4f63a1d7eb17d746/multidict-6.7.0-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:a35c5fc61d4f51eb045061e7967cfe3123d622cd500e8868e7c0c592a09fedc4", size = 268375, upload-time = "2025-10-06T14:49:29.96Z" }, - { url = "https://files.pythonhosted.org/packages/82/72/c53fcade0cc94dfaad583105fd92b3a783af2091eddcb41a6d5a52474000/multidict-6.7.0-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:29fe6740ebccba4175af1b9b87bf553e9c15cd5868ee967e010efcf94e4fd0f1", size = 269346, upload-time = "2025-10-06T14:49:31.404Z" }, - { url = "https://files.pythonhosted.org/packages/0d/e2/9baffdae21a76f77ef8447f1a05a96ec4bc0a24dae08767abc0a2fe680b8/multidict-6.7.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:123e2a72e20537add2f33a79e605f6191fba2afda4cbb876e35c1a7074298a7d", size = 256107, upload-time = "2025-10-06T14:49:32.974Z" }, - { url = "https://files.pythonhosted.org/packages/3c/06/3f06f611087dc60d65ef775f1fb5aca7c6d61c6db4990e7cda0cef9b1651/multidict-6.7.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:b284e319754366c1aee2267a2036248b24eeb17ecd5dc16022095e747f2f4304", size = 253592, upload-time = "2025-10-06T14:49:34.52Z" }, - { url = "https://files.pythonhosted.org/packages/20/24/54e804ec7945b6023b340c412ce9c3f81e91b3bf5fa5ce65558740141bee/multidict-6.7.0-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:803d685de7be4303b5a657b76e2f6d1240e7e0a8aa2968ad5811fa2285553a12", size = 251024, upload-time = "2025-10-06T14:49:35.956Z" }, - { url = "https://files.pythonhosted.org/packages/14/48/011cba467ea0b17ceb938315d219391d3e421dfd35928e5dbdc3f4ae76ef/multidict-6.7.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:c04a328260dfd5db8c39538f999f02779012268f54614902d0afc775d44e0a62", size = 251484, upload-time = "2025-10-06T14:49:37.631Z" }, - { url = "https://files.pythonhosted.org/packages/0d/2f/919258b43bb35b99fa127435cfb2d91798eb3a943396631ef43e3720dcf4/multidict-6.7.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:8a19cdb57cd3df4cd865849d93ee14920fb97224300c88501f16ecfa2604b4e0", size = 263579, upload-time = "2025-10-06T14:49:39.502Z" }, - { url = "https://files.pythonhosted.org/packages/31/22/a0e884d86b5242b5a74cf08e876bdf299e413016b66e55511f7a804a366e/multidict-6.7.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:9b2fd74c52accced7e75de26023b7dccee62511a600e62311b918ec5c168fc2a", size = 259654, upload-time = "2025-10-06T14:49:41.32Z" }, - { url = "https://files.pythonhosted.org/packages/b2/e5/17e10e1b5c5f5a40f2fcbb45953c9b215f8a4098003915e46a93f5fcaa8f/multidict-6.7.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:3e8bfdd0e487acf992407a140d2589fe598238eaeffa3da8448d63a63cd363f8", size = 251511, upload-time = "2025-10-06T14:49:46.021Z" }, - { url = "https://files.pythonhosted.org/packages/e3/9a/201bb1e17e7af53139597069c375e7b0dcbd47594604f65c2d5359508566/multidict-6.7.0-cp312-cp312-win32.whl", hash = "sha256:dd32a49400a2c3d52088e120ee00c1e3576cbff7e10b98467962c74fdb762ed4", size = 41895, upload-time = "2025-10-06T14:49:48.718Z" }, - { url = "https://files.pythonhosted.org/packages/46/e2/348cd32faad84eaf1d20cce80e2bb0ef8d312c55bca1f7fa9865e7770aaf/multidict-6.7.0-cp312-cp312-win_amd64.whl", hash = "sha256:92abb658ef2d7ef22ac9f8bb88e8b6c3e571671534e029359b6d9e845923eb1b", size = 46073, upload-time = "2025-10-06T14:49:50.28Z" }, - { url = "https://files.pythonhosted.org/packages/25/ec/aad2613c1910dce907480e0c3aa306905830f25df2e54ccc9dea450cb5aa/multidict-6.7.0-cp312-cp312-win_arm64.whl", hash = "sha256:490dab541a6a642ce1a9d61a4781656b346a55c13038f0b1244653828e3a83ec", size = 43226, upload-time = "2025-10-06T14:49:52.304Z" }, - { url = "https://files.pythonhosted.org/packages/d2/86/33272a544eeb36d66e4d9a920602d1a2f57d4ebea4ef3cdfe5a912574c95/multidict-6.7.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:bee7c0588aa0076ce77c0ea5d19a68d76ad81fcd9fe8501003b9a24f9d4000f6", size = 76135, upload-time = "2025-10-06T14:49:54.26Z" }, - { url = "https://files.pythonhosted.org/packages/91/1c/eb97db117a1ebe46d457a3d235a7b9d2e6dcab174f42d1b67663dd9e5371/multidict-6.7.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:7ef6b61cad77091056ce0e7ce69814ef72afacb150b7ac6a3e9470def2198159", size = 45117, upload-time = "2025-10-06T14:49:55.82Z" }, - { url = "https://files.pythonhosted.org/packages/f1/d8/6c3442322e41fb1dd4de8bd67bfd11cd72352ac131f6368315617de752f1/multidict-6.7.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:9c0359b1ec12b1d6849c59f9d319610b7f20ef990a6d454ab151aa0e3b9f78ca", size = 43472, upload-time = "2025-10-06T14:49:57.048Z" }, - { url = "https://files.pythonhosted.org/packages/75/3f/e2639e80325af0b6c6febdf8e57cc07043ff15f57fa1ef808f4ccb5ac4cd/multidict-6.7.0-cp313-cp313-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:cd240939f71c64bd658f186330603aac1a9a81bf6273f523fca63673cb7378a8", size = 249342, upload-time = "2025-10-06T14:49:58.368Z" }, - { url = "https://files.pythonhosted.org/packages/5d/cc/84e0585f805cbeaa9cbdaa95f9a3d6aed745b9d25700623ac89a6ecff400/multidict-6.7.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:a60a4d75718a5efa473ebd5ab685786ba0c67b8381f781d1be14da49f1a2dc60", size = 257082, upload-time = "2025-10-06T14:49:59.89Z" }, - { url = "https://files.pythonhosted.org/packages/b0/9c/ac851c107c92289acbbf5cfb485694084690c1b17e555f44952c26ddc5bd/multidict-6.7.0-cp313-cp313-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:53a42d364f323275126aff81fb67c5ca1b7a04fda0546245730a55c8c5f24bc4", size = 240704, upload-time = "2025-10-06T14:50:01.485Z" }, - { url = "https://files.pythonhosted.org/packages/50/cc/5f93e99427248c09da95b62d64b25748a5f5c98c7c2ab09825a1d6af0e15/multidict-6.7.0-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:3b29b980d0ddbecb736735ee5bef69bb2ddca56eff603c86f3f29a1128299b4f", size = 266355, upload-time = "2025-10-06T14:50:02.955Z" }, - { url = "https://files.pythonhosted.org/packages/ec/0c/2ec1d883ceb79c6f7f6d7ad90c919c898f5d1c6ea96d322751420211e072/multidict-6.7.0-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:f8a93b1c0ed2d04b97a5e9336fd2d33371b9a6e29ab7dd6503d63407c20ffbaf", size = 267259, upload-time = "2025-10-06T14:50:04.446Z" }, - { url = "https://files.pythonhosted.org/packages/c6/2d/f0b184fa88d6630aa267680bdb8623fb69cb0d024b8c6f0d23f9a0f406d3/multidict-6.7.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9ff96e8815eecacc6645da76c413eb3b3d34cfca256c70b16b286a687d013c32", size = 254903, upload-time = "2025-10-06T14:50:05.98Z" }, - { url = "https://files.pythonhosted.org/packages/06/c9/11ea263ad0df7dfabcad404feb3c0dd40b131bc7f232d5537f2fb1356951/multidict-6.7.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:7516c579652f6a6be0e266aec0acd0db80829ca305c3d771ed898538804c2036", size = 252365, upload-time = "2025-10-06T14:50:07.511Z" }, - { url = "https://files.pythonhosted.org/packages/41/88/d714b86ee2c17d6e09850c70c9d310abac3d808ab49dfa16b43aba9d53fd/multidict-6.7.0-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:040f393368e63fb0f3330e70c26bfd336656bed925e5cbe17c9da839a6ab13ec", size = 250062, upload-time = "2025-10-06T14:50:09.074Z" }, - { url = "https://files.pythonhosted.org/packages/15/fe/ad407bb9e818c2b31383f6131ca19ea7e35ce93cf1310fce69f12e89de75/multidict-6.7.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:b3bc26a951007b1057a1c543af845f1c7e3e71cc240ed1ace7bf4484aa99196e", size = 249683, upload-time = "2025-10-06T14:50:10.714Z" }, - { url = "https://files.pythonhosted.org/packages/8c/a4/a89abdb0229e533fb925e7c6e5c40201c2873efebc9abaf14046a4536ee6/multidict-6.7.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:7b022717c748dd1992a83e219587aabe45980d88969f01b316e78683e6285f64", size = 261254, upload-time = "2025-10-06T14:50:12.28Z" }, - { url = "https://files.pythonhosted.org/packages/8d/aa/0e2b27bd88b40a4fb8dc53dd74eecac70edaa4c1dd0707eb2164da3675b3/multidict-6.7.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:9600082733859f00d79dee64effc7aef1beb26adb297416a4ad2116fd61374bd", size = 257967, upload-time = "2025-10-06T14:50:14.16Z" }, - { url = "https://files.pythonhosted.org/packages/d0/8e/0c67b7120d5d5f6d874ed85a085f9dc770a7f9d8813e80f44a9fec820bb7/multidict-6.7.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:94218fcec4d72bc61df51c198d098ce2b378e0ccbac41ddbed5ef44092913288", size = 250085, upload-time = "2025-10-06T14:50:15.639Z" }, - { url = "https://files.pythonhosted.org/packages/ba/55/b73e1d624ea4b8fd4dd07a3bb70f6e4c7c6c5d9d640a41c6ffe5cdbd2a55/multidict-6.7.0-cp313-cp313-win32.whl", hash = "sha256:a37bd74c3fa9d00be2d7b8eca074dc56bd8077ddd2917a839bd989612671ed17", size = 41713, upload-time = "2025-10-06T14:50:17.066Z" }, - { url = "https://files.pythonhosted.org/packages/32/31/75c59e7d3b4205075b4c183fa4ca398a2daf2303ddf616b04ae6ef55cffe/multidict-6.7.0-cp313-cp313-win_amd64.whl", hash = "sha256:30d193c6cc6d559db42b6bcec8a5d395d34d60c9877a0b71ecd7c204fcf15390", size = 45915, upload-time = "2025-10-06T14:50:18.264Z" }, - { url = "https://files.pythonhosted.org/packages/31/2a/8987831e811f1184c22bc2e45844934385363ee61c0a2dcfa8f71b87e608/multidict-6.7.0-cp313-cp313-win_arm64.whl", hash = "sha256:ea3334cabe4d41b7ccd01e4d349828678794edbc2d3ae97fc162a3312095092e", size = 43077, upload-time = "2025-10-06T14:50:19.853Z" }, - { url = "https://files.pythonhosted.org/packages/e8/68/7b3a5170a382a340147337b300b9eb25a9ddb573bcdfff19c0fa3f31ffba/multidict-6.7.0-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:ad9ce259f50abd98a1ca0aa6e490b58c316a0fce0617f609723e40804add2c00", size = 83114, upload-time = "2025-10-06T14:50:21.223Z" }, - { url = "https://files.pythonhosted.org/packages/55/5c/3fa2d07c84df4e302060f555bbf539310980362236ad49f50eeb0a1c1eb9/multidict-6.7.0-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:07f5594ac6d084cbb5de2df218d78baf55ef150b91f0ff8a21cc7a2e3a5a58eb", size = 48442, upload-time = "2025-10-06T14:50:22.871Z" }, - { url = "https://files.pythonhosted.org/packages/fc/56/67212d33239797f9bd91962bb899d72bb0f4c35a8652dcdb8ed049bef878/multidict-6.7.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:0591b48acf279821a579282444814a2d8d0af624ae0bc600aa4d1b920b6e924b", size = 46885, upload-time = "2025-10-06T14:50:24.258Z" }, - { url = "https://files.pythonhosted.org/packages/46/d1/908f896224290350721597a61a69cd19b89ad8ee0ae1f38b3f5cd12ea2ac/multidict-6.7.0-cp313-cp313t-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:749a72584761531d2b9467cfbdfd29487ee21124c304c4b6cb760d8777b27f9c", size = 242588, upload-time = "2025-10-06T14:50:25.716Z" }, - { url = "https://files.pythonhosted.org/packages/ab/67/8604288bbd68680eee0ab568fdcb56171d8b23a01bcd5cb0c8fedf6e5d99/multidict-6.7.0-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6b4c3d199f953acd5b446bf7c0de1fe25d94e09e79086f8dc2f48a11a129cdf1", size = 249966, upload-time = "2025-10-06T14:50:28.192Z" }, - { url = "https://files.pythonhosted.org/packages/20/33/9228d76339f1ba51e3efef7da3ebd91964d3006217aae13211653193c3ff/multidict-6.7.0-cp313-cp313t-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:9fb0211dfc3b51efea2f349ec92c114d7754dd62c01f81c3e32b765b70c45c9b", size = 228618, upload-time = "2025-10-06T14:50:29.82Z" }, - { url = "https://files.pythonhosted.org/packages/f8/2d/25d9b566d10cab1c42b3b9e5b11ef79c9111eaf4463b8c257a3bd89e0ead/multidict-6.7.0-cp313-cp313t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:a027ec240fe73a8d6281872690b988eed307cd7d91b23998ff35ff577ca688b5", size = 257539, upload-time = "2025-10-06T14:50:31.731Z" }, - { url = "https://files.pythonhosted.org/packages/b6/b1/8d1a965e6637fc33de3c0d8f414485c2b7e4af00f42cab3d84e7b955c222/multidict-6.7.0-cp313-cp313t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d1d964afecdf3a8288789df2f5751dc0a8261138c3768d9af117ed384e538fad", size = 256345, upload-time = "2025-10-06T14:50:33.26Z" }, - { url = "https://files.pythonhosted.org/packages/ba/0c/06b5a8adbdeedada6f4fb8d8f193d44a347223b11939b42953eeb6530b6b/multidict-6.7.0-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:caf53b15b1b7df9fbd0709aa01409000a2b4dd03a5f6f5cc548183c7c8f8b63c", size = 247934, upload-time = "2025-10-06T14:50:34.808Z" }, - { url = "https://files.pythonhosted.org/packages/8f/31/b2491b5fe167ca044c6eb4b8f2c9f3b8a00b24c432c365358eadac5d7625/multidict-6.7.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:654030da3197d927f05a536a66186070e98765aa5142794c9904555d3a9d8fb5", size = 245243, upload-time = "2025-10-06T14:50:36.436Z" }, - { url = "https://files.pythonhosted.org/packages/61/1a/982913957cb90406c8c94f53001abd9eafc271cb3e70ff6371590bec478e/multidict-6.7.0-cp313-cp313t-musllinux_1_2_armv7l.whl", hash = "sha256:2090d3718829d1e484706a2f525e50c892237b2bf9b17a79b059cb98cddc2f10", size = 235878, upload-time = "2025-10-06T14:50:37.953Z" }, - { url = "https://files.pythonhosted.org/packages/be/c0/21435d804c1a1cf7a2608593f4d19bca5bcbd7a81a70b253fdd1c12af9c0/multidict-6.7.0-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:2d2cfeec3f6f45651b3d408c4acec0ebf3daa9bc8a112a084206f5db5d05b754", size = 243452, upload-time = "2025-10-06T14:50:39.574Z" }, - { url = "https://files.pythonhosted.org/packages/54/0a/4349d540d4a883863191be6eb9a928846d4ec0ea007d3dcd36323bb058ac/multidict-6.7.0-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:4ef089f985b8c194d341eb2c24ae6e7408c9a0e2e5658699c92f497437d88c3c", size = 252312, upload-time = "2025-10-06T14:50:41.612Z" }, - { url = "https://files.pythonhosted.org/packages/26/64/d5416038dbda1488daf16b676e4dbfd9674dde10a0cc8f4fc2b502d8125d/multidict-6.7.0-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:e93a0617cd16998784bf4414c7e40f17a35d2350e5c6f0bd900d3a8e02bd3762", size = 246935, upload-time = "2025-10-06T14:50:43.972Z" }, - { url = "https://files.pythonhosted.org/packages/9f/8c/8290c50d14e49f35e0bd4abc25e1bc7711149ca9588ab7d04f886cdf03d9/multidict-6.7.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:f0feece2ef8ebc42ed9e2e8c78fc4aa3cf455733b507c09ef7406364c94376c6", size = 243385, upload-time = "2025-10-06T14:50:45.648Z" }, - { url = "https://files.pythonhosted.org/packages/ef/a0/f83ae75e42d694b3fbad3e047670e511c138be747bc713cf1b10d5096416/multidict-6.7.0-cp313-cp313t-win32.whl", hash = "sha256:19a1d55338ec1be74ef62440ca9e04a2f001a04d0cc49a4983dc320ff0f3212d", size = 47777, upload-time = "2025-10-06T14:50:47.154Z" }, - { url = "https://files.pythonhosted.org/packages/dc/80/9b174a92814a3830b7357307a792300f42c9e94664b01dee8e457551fa66/multidict-6.7.0-cp313-cp313t-win_amd64.whl", hash = "sha256:3da4fb467498df97e986af166b12d01f05d2e04f978a9c1c680ea1988e0bc4b6", size = 53104, upload-time = "2025-10-06T14:50:48.851Z" }, - { url = "https://files.pythonhosted.org/packages/cc/28/04baeaf0428d95bb7a7bea0e691ba2f31394338ba424fb0679a9ed0f4c09/multidict-6.7.0-cp313-cp313t-win_arm64.whl", hash = "sha256:b4121773c49a0776461f4a904cdf6264c88e42218aaa8407e803ca8025872792", size = 45503, upload-time = "2025-10-06T14:50:50.16Z" }, - { url = "https://files.pythonhosted.org/packages/e2/b1/3da6934455dd4b261d4c72f897e3a5728eba81db59959f3a639245891baa/multidict-6.7.0-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:3bab1e4aff7adaa34410f93b1f8e57c4b36b9af0426a76003f441ee1d3c7e842", size = 75128, upload-time = "2025-10-06T14:50:51.92Z" }, - { url = "https://files.pythonhosted.org/packages/14/2c/f069cab5b51d175a1a2cb4ccdf7a2c2dabd58aa5bd933fa036a8d15e2404/multidict-6.7.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:b8512bac933afc3e45fb2b18da8e59b78d4f408399a960339598374d4ae3b56b", size = 44410, upload-time = "2025-10-06T14:50:53.275Z" }, - { url = "https://files.pythonhosted.org/packages/42/e2/64bb41266427af6642b6b128e8774ed84c11b80a90702c13ac0a86bb10cc/multidict-6.7.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:79dcf9e477bc65414ebfea98ffd013cb39552b5ecd62908752e0e413d6d06e38", size = 43205, upload-time = "2025-10-06T14:50:54.911Z" }, - { url = "https://files.pythonhosted.org/packages/02/68/6b086fef8a3f1a8541b9236c594f0c9245617c29841f2e0395d979485cde/multidict-6.7.0-cp314-cp314-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:31bae522710064b5cbeddaf2e9f32b1abab70ac6ac91d42572502299e9953128", size = 245084, upload-time = "2025-10-06T14:50:56.369Z" }, - { url = "https://files.pythonhosted.org/packages/15/ee/f524093232007cd7a75c1d132df70f235cfd590a7c9eaccd7ff422ef4ae8/multidict-6.7.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4a0df7ff02397bb63e2fd22af2c87dfa39e8c7f12947bc524dbdc528282c7e34", size = 252667, upload-time = "2025-10-06T14:50:57.991Z" }, - { url = "https://files.pythonhosted.org/packages/02/a5/eeb3f43ab45878f1895118c3ef157a480db58ede3f248e29b5354139c2c9/multidict-6.7.0-cp314-cp314-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:7a0222514e8e4c514660e182d5156a415c13ef0aabbd71682fc714e327b95e99", size = 233590, upload-time = "2025-10-06T14:50:59.589Z" }, - { url = "https://files.pythonhosted.org/packages/6a/1e/76d02f8270b97269d7e3dbd45644b1785bda457b474315f8cf999525a193/multidict-6.7.0-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:2397ab4daaf2698eb51a76721e98db21ce4f52339e535725de03ea962b5a3202", size = 264112, upload-time = "2025-10-06T14:51:01.183Z" }, - { url = "https://files.pythonhosted.org/packages/76/0b/c28a70ecb58963847c2a8efe334904cd254812b10e535aefb3bcce513918/multidict-6.7.0-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:8891681594162635948a636c9fe0ff21746aeb3dd5463f6e25d9bea3a8a39ca1", size = 261194, upload-time = "2025-10-06T14:51:02.794Z" }, - { url = "https://files.pythonhosted.org/packages/b4/63/2ab26e4209773223159b83aa32721b4021ffb08102f8ac7d689c943fded1/multidict-6.7.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:18706cc31dbf402a7945916dd5cddf160251b6dab8a2c5f3d6d5a55949f676b3", size = 248510, upload-time = "2025-10-06T14:51:04.724Z" }, - { url = "https://files.pythonhosted.org/packages/93/cd/06c1fa8282af1d1c46fd55c10a7930af652afdce43999501d4d68664170c/multidict-6.7.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:f844a1bbf1d207dd311a56f383f7eda2d0e134921d45751842d8235e7778965d", size = 248395, upload-time = "2025-10-06T14:51:06.306Z" }, - { url = "https://files.pythonhosted.org/packages/99/ac/82cb419dd6b04ccf9e7e61befc00c77614fc8134362488b553402ecd55ce/multidict-6.7.0-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:d4393e3581e84e5645506923816b9cc81f5609a778c7e7534054091acc64d1c6", size = 239520, upload-time = "2025-10-06T14:51:08.091Z" }, - { url = "https://files.pythonhosted.org/packages/fa/f3/a0f9bf09493421bd8716a362e0cd1d244f5a6550f5beffdd6b47e885b331/multidict-6.7.0-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:fbd18dc82d7bf274b37aa48d664534330af744e03bccf696d6f4c6042e7d19e7", size = 245479, upload-time = "2025-10-06T14:51:10.365Z" }, - { url = "https://files.pythonhosted.org/packages/8d/01/476d38fc73a212843f43c852b0eee266b6971f0e28329c2184a8df90c376/multidict-6.7.0-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:b6234e14f9314731ec45c42fc4554b88133ad53a09092cc48a88e771c125dadb", size = 258903, upload-time = "2025-10-06T14:51:12.466Z" }, - { url = "https://files.pythonhosted.org/packages/49/6d/23faeb0868adba613b817d0e69c5f15531b24d462af8012c4f6de4fa8dc3/multidict-6.7.0-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:08d4379f9744d8f78d98c8673c06e202ffa88296f009c71bbafe8a6bf847d01f", size = 252333, upload-time = "2025-10-06T14:51:14.48Z" }, - { url = "https://files.pythonhosted.org/packages/1e/cc/48d02ac22b30fa247f7dad82866e4b1015431092f4ba6ebc7e77596e0b18/multidict-6.7.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:9fe04da3f79387f450fd0061d4dd2e45a72749d31bf634aecc9e27f24fdc4b3f", size = 243411, upload-time = "2025-10-06T14:51:16.072Z" }, - { url = "https://files.pythonhosted.org/packages/4a/03/29a8bf5a18abf1fe34535c88adbdfa88c9fb869b5a3b120692c64abe8284/multidict-6.7.0-cp314-cp314-win32.whl", hash = "sha256:fbafe31d191dfa7c4c51f7a6149c9fb7e914dcf9ffead27dcfd9f1ae382b3885", size = 40940, upload-time = "2025-10-06T14:51:17.544Z" }, - { url = "https://files.pythonhosted.org/packages/82/16/7ed27b680791b939de138f906d5cf2b4657b0d45ca6f5dd6236fdddafb1a/multidict-6.7.0-cp314-cp314-win_amd64.whl", hash = "sha256:2f67396ec0310764b9222a1728ced1ab638f61aadc6226f17a71dd9324f9a99c", size = 45087, upload-time = "2025-10-06T14:51:18.875Z" }, - { url = "https://files.pythonhosted.org/packages/cd/3c/e3e62eb35a1950292fe39315d3c89941e30a9d07d5d2df42965ab041da43/multidict-6.7.0-cp314-cp314-win_arm64.whl", hash = "sha256:ba672b26069957ee369cfa7fc180dde1fc6f176eaf1e6beaf61fbebbd3d9c000", size = 42368, upload-time = "2025-10-06T14:51:20.225Z" }, - { url = "https://files.pythonhosted.org/packages/8b/40/cd499bd0dbc5f1136726db3153042a735fffd0d77268e2ee20d5f33c010f/multidict-6.7.0-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:c1dcc7524066fa918c6a27d61444d4ee7900ec635779058571f70d042d86ed63", size = 82326, upload-time = "2025-10-06T14:51:21.588Z" }, - { url = "https://files.pythonhosted.org/packages/13/8a/18e031eca251c8df76daf0288e6790561806e439f5ce99a170b4af30676b/multidict-6.7.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:27e0b36c2d388dc7b6ced3406671b401e84ad7eb0656b8f3a2f46ed0ce483718", size = 48065, upload-time = "2025-10-06T14:51:22.93Z" }, - { url = "https://files.pythonhosted.org/packages/40/71/5e6701277470a87d234e433fb0a3a7deaf3bcd92566e421e7ae9776319de/multidict-6.7.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:2a7baa46a22e77f0988e3b23d4ede5513ebec1929e34ee9495be535662c0dfe2", size = 46475, upload-time = "2025-10-06T14:51:24.352Z" }, - { url = "https://files.pythonhosted.org/packages/fe/6a/bab00cbab6d9cfb57afe1663318f72ec28289ea03fd4e8236bb78429893a/multidict-6.7.0-cp314-cp314t-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:7bf77f54997a9166a2f5675d1201520586439424c2511723a7312bdb4bcc034e", size = 239324, upload-time = "2025-10-06T14:51:25.822Z" }, - { url = "https://files.pythonhosted.org/packages/2a/5f/8de95f629fc22a7769ade8b41028e3e5a822c1f8904f618d175945a81ad3/multidict-6.7.0-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e011555abada53f1578d63389610ac8a5400fc70ce71156b0aa30d326f1a5064", size = 246877, upload-time = "2025-10-06T14:51:27.604Z" }, - { url = "https://files.pythonhosted.org/packages/23/b4/38881a960458f25b89e9f4a4fdcb02ac101cfa710190db6e5528841e67de/multidict-6.7.0-cp314-cp314t-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:28b37063541b897fd6a318007373930a75ca6d6ac7c940dbe14731ffdd8d498e", size = 225824, upload-time = "2025-10-06T14:51:29.664Z" }, - { url = "https://files.pythonhosted.org/packages/1e/39/6566210c83f8a261575f18e7144736059f0c460b362e96e9cf797a24b8e7/multidict-6.7.0-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:05047ada7a2fde2631a0ed706f1fd68b169a681dfe5e4cf0f8e4cb6618bbc2cd", size = 253558, upload-time = "2025-10-06T14:51:31.684Z" }, - { url = "https://files.pythonhosted.org/packages/00/a3/67f18315100f64c269f46e6c0319fa87ba68f0f64f2b8e7fd7c72b913a0b/multidict-6.7.0-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:716133f7d1d946a4e1b91b1756b23c088881e70ff180c24e864c26192ad7534a", size = 252339, upload-time = "2025-10-06T14:51:33.699Z" }, - { url = "https://files.pythonhosted.org/packages/c8/2a/1cb77266afee2458d82f50da41beba02159b1d6b1f7973afc9a1cad1499b/multidict-6.7.0-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d1bed1b467ef657f2a0ae62844a607909ef1c6889562de5e1d505f74457d0b96", size = 244895, upload-time = "2025-10-06T14:51:36.189Z" }, - { url = "https://files.pythonhosted.org/packages/dd/72/09fa7dd487f119b2eb9524946ddd36e2067c08510576d43ff68469563b3b/multidict-6.7.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:ca43bdfa5d37bd6aee89d85e1d0831fb86e25541be7e9d376ead1b28974f8e5e", size = 241862, upload-time = "2025-10-06T14:51:41.291Z" }, - { url = "https://files.pythonhosted.org/packages/65/92/bc1f8bd0853d8669300f732c801974dfc3702c3eeadae2f60cef54dc69d7/multidict-6.7.0-cp314-cp314t-musllinux_1_2_armv7l.whl", hash = "sha256:44b546bd3eb645fd26fb949e43c02a25a2e632e2ca21a35e2e132c8105dc8599", size = 232376, upload-time = "2025-10-06T14:51:43.55Z" }, - { url = "https://files.pythonhosted.org/packages/09/86/ac39399e5cb9d0c2ac8ef6e10a768e4d3bc933ac808d49c41f9dc23337eb/multidict-6.7.0-cp314-cp314t-musllinux_1_2_i686.whl", hash = "sha256:a6ef16328011d3f468e7ebc326f24c1445f001ca1dec335b2f8e66bed3006394", size = 240272, upload-time = "2025-10-06T14:51:45.265Z" }, - { url = "https://files.pythonhosted.org/packages/3d/b6/fed5ac6b8563ec72df6cb1ea8dac6d17f0a4a1f65045f66b6d3bf1497c02/multidict-6.7.0-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:5aa873cbc8e593d361ae65c68f85faadd755c3295ea2c12040ee146802f23b38", size = 248774, upload-time = "2025-10-06T14:51:46.836Z" }, - { url = "https://files.pythonhosted.org/packages/6b/8d/b954d8c0dc132b68f760aefd45870978deec6818897389dace00fcde32ff/multidict-6.7.0-cp314-cp314t-musllinux_1_2_s390x.whl", hash = "sha256:3d7b6ccce016e29df4b7ca819659f516f0bc7a4b3efa3bb2012ba06431b044f9", size = 242731, upload-time = "2025-10-06T14:51:48.541Z" }, - { url = "https://files.pythonhosted.org/packages/16/9d/a2dac7009125d3540c2f54e194829ea18ac53716c61b655d8ed300120b0f/multidict-6.7.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:171b73bd4ee683d307599b66793ac80981b06f069b62eea1c9e29c9241aa66b0", size = 240193, upload-time = "2025-10-06T14:51:50.355Z" }, - { url = "https://files.pythonhosted.org/packages/39/ca/c05f144128ea232ae2178b008d5011d4e2cea86e4ee8c85c2631b1b94802/multidict-6.7.0-cp314-cp314t-win32.whl", hash = "sha256:b2d7f80c4e1fd010b07cb26820aae86b7e73b681ee4889684fb8d2d4537aab13", size = 48023, upload-time = "2025-10-06T14:51:51.883Z" }, - { url = "https://files.pythonhosted.org/packages/ba/8f/0a60e501584145588be1af5cc829265701ba3c35a64aec8e07cbb71d39bb/multidict-6.7.0-cp314-cp314t-win_amd64.whl", hash = "sha256:09929cab6fcb68122776d575e03c6cc64ee0b8fca48d17e135474b042ce515cd", size = 53507, upload-time = "2025-10-06T14:51:53.672Z" }, - { url = "https://files.pythonhosted.org/packages/7f/ae/3148b988a9c6239903e786eac19c889fab607c31d6efa7fb2147e5680f23/multidict-6.7.0-cp314-cp314t-win_arm64.whl", hash = "sha256:cc41db090ed742f32bd2d2c721861725e6109681eddf835d0a82bd3a5c382827", size = 44804, upload-time = "2025-10-06T14:51:55.415Z" }, - { url = "https://files.pythonhosted.org/packages/b7/da/7d22601b625e241d4f23ef1ebff8acfc60da633c9e7e7922e24d10f592b3/multidict-6.7.0-py3-none-any.whl", hash = "sha256:394fc5c42a333c9ffc3e421a4c85e08580d990e08b99f6bf35b4132114c5dcb3", size = 12317, upload-time = "2025-10-06T14:52:29.272Z" }, -] - -[[package]] -name = "numpy" -version = "2.2.6" -source = { registry = "https://pypi.org/simple" } -resolution-markers = [ - "python_full_version < '3.11' and platform_python_implementation != 'PyPy'", - "python_full_version < '3.11' and platform_python_implementation == 'PyPy'", -] -sdist = { url = "https://files.pythonhosted.org/packages/76/21/7d2a95e4bba9dc13d043ee156a356c0a8f0c6309dff6b21b4d71a073b8a8/numpy-2.2.6.tar.gz", hash = "sha256:e29554e2bef54a90aa5cc07da6ce955accb83f21ab5de01a62c8478897b264fd", size = 20276440, upload-time = "2025-05-17T22:38:04.611Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/9a/3e/ed6db5be21ce87955c0cbd3009f2803f59fa08df21b5df06862e2d8e2bdd/numpy-2.2.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b412caa66f72040e6d268491a59f2c43bf03eb6c96dd8f0307829feb7fa2b6fb", size = 21165245, upload-time = "2025-05-17T21:27:58.555Z" }, - { url = "https://files.pythonhosted.org/packages/22/c2/4b9221495b2a132cc9d2eb862e21d42a009f5a60e45fc44b00118c174bff/numpy-2.2.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8e41fd67c52b86603a91c1a505ebaef50b3314de0213461c7a6e99c9a3beff90", size = 14360048, upload-time = "2025-05-17T21:28:21.406Z" }, - { url = "https://files.pythonhosted.org/packages/fd/77/dc2fcfc66943c6410e2bf598062f5959372735ffda175b39906d54f02349/numpy-2.2.6-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:37e990a01ae6ec7fe7fa1c26c55ecb672dd98b19c3d0e1d1f326fa13cb38d163", size = 5340542, upload-time = "2025-05-17T21:28:30.931Z" }, - { url = "https://files.pythonhosted.org/packages/7a/4f/1cb5fdc353a5f5cc7feb692db9b8ec2c3d6405453f982435efc52561df58/numpy-2.2.6-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:5a6429d4be8ca66d889b7cf70f536a397dc45ba6faeb5f8c5427935d9592e9cf", size = 6878301, upload-time = "2025-05-17T21:28:41.613Z" }, - { url = "https://files.pythonhosted.org/packages/eb/17/96a3acd228cec142fcb8723bd3cc39c2a474f7dcf0a5d16731980bcafa95/numpy-2.2.6-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:efd28d4e9cd7d7a8d39074a4d44c63eda73401580c5c76acda2ce969e0a38e83", size = 14297320, upload-time = "2025-05-17T21:29:02.78Z" }, - { url = "https://files.pythonhosted.org/packages/b4/63/3de6a34ad7ad6646ac7d2f55ebc6ad439dbbf9c4370017c50cf403fb19b5/numpy-2.2.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fc7b73d02efb0e18c000e9ad8b83480dfcd5dfd11065997ed4c6747470ae8915", size = 16801050, upload-time = "2025-05-17T21:29:27.675Z" }, - { url = "https://files.pythonhosted.org/packages/07/b6/89d837eddef52b3d0cec5c6ba0456c1bf1b9ef6a6672fc2b7873c3ec4e2e/numpy-2.2.6-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:74d4531beb257d2c3f4b261bfb0fc09e0f9ebb8842d82a7b4209415896adc680", size = 15807034, upload-time = "2025-05-17T21:29:51.102Z" }, - { url = "https://files.pythonhosted.org/packages/01/c8/dc6ae86e3c61cfec1f178e5c9f7858584049b6093f843bca541f94120920/numpy-2.2.6-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:8fc377d995680230e83241d8a96def29f204b5782f371c532579b4f20607a289", size = 18614185, upload-time = "2025-05-17T21:30:18.703Z" }, - { url = "https://files.pythonhosted.org/packages/5b/c5/0064b1b7e7c89137b471ccec1fd2282fceaae0ab3a9550f2568782d80357/numpy-2.2.6-cp310-cp310-win32.whl", hash = "sha256:b093dd74e50a8cba3e873868d9e93a85b78e0daf2e98c6797566ad8044e8363d", size = 6527149, upload-time = "2025-05-17T21:30:29.788Z" }, - { url = "https://files.pythonhosted.org/packages/a3/dd/4b822569d6b96c39d1215dbae0582fd99954dcbcf0c1a13c61783feaca3f/numpy-2.2.6-cp310-cp310-win_amd64.whl", hash = "sha256:f0fd6321b839904e15c46e0d257fdd101dd7f530fe03fd6359c1ea63738703f3", size = 12904620, upload-time = "2025-05-17T21:30:48.994Z" }, - { url = "https://files.pythonhosted.org/packages/da/a8/4f83e2aa666a9fbf56d6118faaaf5f1974d456b1823fda0a176eff722839/numpy-2.2.6-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:f9f1adb22318e121c5c69a09142811a201ef17ab257a1e66ca3025065b7f53ae", size = 21176963, upload-time = "2025-05-17T21:31:19.36Z" }, - { url = "https://files.pythonhosted.org/packages/b3/2b/64e1affc7972decb74c9e29e5649fac940514910960ba25cd9af4488b66c/numpy-2.2.6-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c820a93b0255bc360f53eca31a0e676fd1101f673dda8da93454a12e23fc5f7a", size = 14406743, upload-time = "2025-05-17T21:31:41.087Z" }, - { url = "https://files.pythonhosted.org/packages/4a/9f/0121e375000b5e50ffdd8b25bf78d8e1a5aa4cca3f185d41265198c7b834/numpy-2.2.6-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:3d70692235e759f260c3d837193090014aebdf026dfd167834bcba43e30c2a42", size = 5352616, upload-time = "2025-05-17T21:31:50.072Z" }, - { url = "https://files.pythonhosted.org/packages/31/0d/b48c405c91693635fbe2dcd7bc84a33a602add5f63286e024d3b6741411c/numpy-2.2.6-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:481b49095335f8eed42e39e8041327c05b0f6f4780488f61286ed3c01368d491", size = 6889579, upload-time = "2025-05-17T21:32:01.712Z" }, - { url = "https://files.pythonhosted.org/packages/52/b8/7f0554d49b565d0171eab6e99001846882000883998e7b7d9f0d98b1f934/numpy-2.2.6-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b64d8d4d17135e00c8e346e0a738deb17e754230d7e0810ac5012750bbd85a5a", size = 14312005, upload-time = "2025-05-17T21:32:23.332Z" }, - { url = "https://files.pythonhosted.org/packages/b3/dd/2238b898e51bd6d389b7389ffb20d7f4c10066d80351187ec8e303a5a475/numpy-2.2.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ba10f8411898fc418a521833e014a77d3ca01c15b0c6cdcce6a0d2897e6dbbdf", size = 16821570, upload-time = "2025-05-17T21:32:47.991Z" }, - { url = "https://files.pythonhosted.org/packages/83/6c/44d0325722cf644f191042bf47eedad61c1e6df2432ed65cbe28509d404e/numpy-2.2.6-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:bd48227a919f1bafbdda0583705e547892342c26fb127219d60a5c36882609d1", size = 15818548, upload-time = "2025-05-17T21:33:11.728Z" }, - { url = "https://files.pythonhosted.org/packages/ae/9d/81e8216030ce66be25279098789b665d49ff19eef08bfa8cb96d4957f422/numpy-2.2.6-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:9551a499bf125c1d4f9e250377c1ee2eddd02e01eac6644c080162c0c51778ab", size = 18620521, upload-time = "2025-05-17T21:33:39.139Z" }, - { url = "https://files.pythonhosted.org/packages/6a/fd/e19617b9530b031db51b0926eed5345ce8ddc669bb3bc0044b23e275ebe8/numpy-2.2.6-cp311-cp311-win32.whl", hash = "sha256:0678000bb9ac1475cd454c6b8c799206af8107e310843532b04d49649c717a47", size = 6525866, upload-time = "2025-05-17T21:33:50.273Z" }, - { url = "https://files.pythonhosted.org/packages/31/0a/f354fb7176b81747d870f7991dc763e157a934c717b67b58456bc63da3df/numpy-2.2.6-cp311-cp311-win_amd64.whl", hash = "sha256:e8213002e427c69c45a52bbd94163084025f533a55a59d6f9c5b820774ef3303", size = 12907455, upload-time = "2025-05-17T21:34:09.135Z" }, - { url = "https://files.pythonhosted.org/packages/82/5d/c00588b6cf18e1da539b45d3598d3557084990dcc4331960c15ee776ee41/numpy-2.2.6-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:41c5a21f4a04fa86436124d388f6ed60a9343a6f767fced1a8a71c3fbca038ff", size = 20875348, upload-time = "2025-05-17T21:34:39.648Z" }, - { url = "https://files.pythonhosted.org/packages/66/ee/560deadcdde6c2f90200450d5938f63a34b37e27ebff162810f716f6a230/numpy-2.2.6-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:de749064336d37e340f640b05f24e9e3dd678c57318c7289d222a8a2f543e90c", size = 14119362, upload-time = "2025-05-17T21:35:01.241Z" }, - { url = "https://files.pythonhosted.org/packages/3c/65/4baa99f1c53b30adf0acd9a5519078871ddde8d2339dc5a7fde80d9d87da/numpy-2.2.6-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:894b3a42502226a1cac872f840030665f33326fc3dac8e57c607905773cdcde3", size = 5084103, upload-time = "2025-05-17T21:35:10.622Z" }, - { url = "https://files.pythonhosted.org/packages/cc/89/e5a34c071a0570cc40c9a54eb472d113eea6d002e9ae12bb3a8407fb912e/numpy-2.2.6-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:71594f7c51a18e728451bb50cc60a3ce4e6538822731b2933209a1f3614e9282", size = 6625382, upload-time = "2025-05-17T21:35:21.414Z" }, - { url = "https://files.pythonhosted.org/packages/f8/35/8c80729f1ff76b3921d5c9487c7ac3de9b2a103b1cd05e905b3090513510/numpy-2.2.6-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f2618db89be1b4e05f7a1a847a9c1c0abd63e63a1607d892dd54668dd92faf87", size = 14018462, upload-time = "2025-05-17T21:35:42.174Z" }, - { url = "https://files.pythonhosted.org/packages/8c/3d/1e1db36cfd41f895d266b103df00ca5b3cbe965184df824dec5c08c6b803/numpy-2.2.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fd83c01228a688733f1ded5201c678f0c53ecc1006ffbc404db9f7a899ac6249", size = 16527618, upload-time = "2025-05-17T21:36:06.711Z" }, - { url = "https://files.pythonhosted.org/packages/61/c6/03ed30992602c85aa3cd95b9070a514f8b3c33e31124694438d88809ae36/numpy-2.2.6-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:37c0ca431f82cd5fa716eca9506aefcabc247fb27ba69c5062a6d3ade8cf8f49", size = 15505511, upload-time = "2025-05-17T21:36:29.965Z" }, - { url = "https://files.pythonhosted.org/packages/b7/25/5761d832a81df431e260719ec45de696414266613c9ee268394dd5ad8236/numpy-2.2.6-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:fe27749d33bb772c80dcd84ae7e8df2adc920ae8297400dabec45f0dedb3f6de", size = 18313783, upload-time = "2025-05-17T21:36:56.883Z" }, - { url = "https://files.pythonhosted.org/packages/57/0a/72d5a3527c5ebffcd47bde9162c39fae1f90138c961e5296491ce778e682/numpy-2.2.6-cp312-cp312-win32.whl", hash = "sha256:4eeaae00d789f66c7a25ac5f34b71a7035bb474e679f410e5e1a94deb24cf2d4", size = 6246506, upload-time = "2025-05-17T21:37:07.368Z" }, - { url = "https://files.pythonhosted.org/packages/36/fa/8c9210162ca1b88529ab76b41ba02d433fd54fecaf6feb70ef9f124683f1/numpy-2.2.6-cp312-cp312-win_amd64.whl", hash = "sha256:c1f9540be57940698ed329904db803cf7a402f3fc200bfe599334c9bd84a40b2", size = 12614190, upload-time = "2025-05-17T21:37:26.213Z" }, - { url = "https://files.pythonhosted.org/packages/f9/5c/6657823f4f594f72b5471f1db1ab12e26e890bb2e41897522d134d2a3e81/numpy-2.2.6-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:0811bb762109d9708cca4d0b13c4f67146e3c3b7cf8d34018c722adb2d957c84", size = 20867828, upload-time = "2025-05-17T21:37:56.699Z" }, - { url = "https://files.pythonhosted.org/packages/dc/9e/14520dc3dadf3c803473bd07e9b2bd1b69bc583cb2497b47000fed2fa92f/numpy-2.2.6-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:287cc3162b6f01463ccd86be154f284d0893d2b3ed7292439ea97eafa8170e0b", size = 14143006, upload-time = "2025-05-17T21:38:18.291Z" }, - { url = "https://files.pythonhosted.org/packages/4f/06/7e96c57d90bebdce9918412087fc22ca9851cceaf5567a45c1f404480e9e/numpy-2.2.6-cp313-cp313-macosx_14_0_arm64.whl", hash = "sha256:f1372f041402e37e5e633e586f62aa53de2eac8d98cbfb822806ce4bbefcb74d", size = 5076765, upload-time = "2025-05-17T21:38:27.319Z" }, - { url = "https://files.pythonhosted.org/packages/73/ed/63d920c23b4289fdac96ddbdd6132e9427790977d5457cd132f18e76eae0/numpy-2.2.6-cp313-cp313-macosx_14_0_x86_64.whl", hash = "sha256:55a4d33fa519660d69614a9fad433be87e5252f4b03850642f88993f7b2ca566", size = 6617736, upload-time = "2025-05-17T21:38:38.141Z" }, - { url = "https://files.pythonhosted.org/packages/85/c5/e19c8f99d83fd377ec8c7e0cf627a8049746da54afc24ef0a0cb73d5dfb5/numpy-2.2.6-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f92729c95468a2f4f15e9bb94c432a9229d0d50de67304399627a943201baa2f", size = 14010719, upload-time = "2025-05-17T21:38:58.433Z" }, - { url = "https://files.pythonhosted.org/packages/19/49/4df9123aafa7b539317bf6d342cb6d227e49f7a35b99c287a6109b13dd93/numpy-2.2.6-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1bc23a79bfabc5d056d106f9befb8d50c31ced2fbc70eedb8155aec74a45798f", size = 16526072, upload-time = "2025-05-17T21:39:22.638Z" }, - { url = "https://files.pythonhosted.org/packages/b2/6c/04b5f47f4f32f7c2b0e7260442a8cbcf8168b0e1a41ff1495da42f42a14f/numpy-2.2.6-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:e3143e4451880bed956e706a3220b4e5cf6172ef05fcc397f6f36a550b1dd868", size = 15503213, upload-time = "2025-05-17T21:39:45.865Z" }, - { url = "https://files.pythonhosted.org/packages/17/0a/5cd92e352c1307640d5b6fec1b2ffb06cd0dabe7d7b8227f97933d378422/numpy-2.2.6-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:b4f13750ce79751586ae2eb824ba7e1e8dba64784086c98cdbbcc6a42112ce0d", size = 18316632, upload-time = "2025-05-17T21:40:13.331Z" }, - { url = "https://files.pythonhosted.org/packages/f0/3b/5cba2b1d88760ef86596ad0f3d484b1cbff7c115ae2429678465057c5155/numpy-2.2.6-cp313-cp313-win32.whl", hash = "sha256:5beb72339d9d4fa36522fc63802f469b13cdbe4fdab4a288f0c441b74272ebfd", size = 6244532, upload-time = "2025-05-17T21:43:46.099Z" }, - { url = "https://files.pythonhosted.org/packages/cb/3b/d58c12eafcb298d4e6d0d40216866ab15f59e55d148a5658bb3132311fcf/numpy-2.2.6-cp313-cp313-win_amd64.whl", hash = "sha256:b0544343a702fa80c95ad5d3d608ea3599dd54d4632df855e4c8d24eb6ecfa1c", size = 12610885, upload-time = "2025-05-17T21:44:05.145Z" }, - { url = "https://files.pythonhosted.org/packages/6b/9e/4bf918b818e516322db999ac25d00c75788ddfd2d2ade4fa66f1f38097e1/numpy-2.2.6-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:0bca768cd85ae743b2affdc762d617eddf3bcf8724435498a1e80132d04879e6", size = 20963467, upload-time = "2025-05-17T21:40:44Z" }, - { url = "https://files.pythonhosted.org/packages/61/66/d2de6b291507517ff2e438e13ff7b1e2cdbdb7cb40b3ed475377aece69f9/numpy-2.2.6-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:fc0c5673685c508a142ca65209b4e79ed6740a4ed6b2267dbba90f34b0b3cfda", size = 14225144, upload-time = "2025-05-17T21:41:05.695Z" }, - { url = "https://files.pythonhosted.org/packages/e4/25/480387655407ead912e28ba3a820bc69af9adf13bcbe40b299d454ec011f/numpy-2.2.6-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:5bd4fc3ac8926b3819797a7c0e2631eb889b4118a9898c84f585a54d475b7e40", size = 5200217, upload-time = "2025-05-17T21:41:15.903Z" }, - { url = "https://files.pythonhosted.org/packages/aa/4a/6e313b5108f53dcbf3aca0c0f3e9c92f4c10ce57a0a721851f9785872895/numpy-2.2.6-cp313-cp313t-macosx_14_0_x86_64.whl", hash = "sha256:fee4236c876c4e8369388054d02d0e9bb84821feb1a64dd59e137e6511a551f8", size = 6712014, upload-time = "2025-05-17T21:41:27.321Z" }, - { url = "https://files.pythonhosted.org/packages/b7/30/172c2d5c4be71fdf476e9de553443cf8e25feddbe185e0bd88b096915bcc/numpy-2.2.6-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e1dda9c7e08dc141e0247a5b8f49cf05984955246a327d4c48bda16821947b2f", size = 14077935, upload-time = "2025-05-17T21:41:49.738Z" }, - { url = "https://files.pythonhosted.org/packages/12/fb/9e743f8d4e4d3c710902cf87af3512082ae3d43b945d5d16563f26ec251d/numpy-2.2.6-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f447e6acb680fd307f40d3da4852208af94afdfab89cf850986c3ca00562f4fa", size = 16600122, upload-time = "2025-05-17T21:42:14.046Z" }, - { url = "https://files.pythonhosted.org/packages/12/75/ee20da0e58d3a66f204f38916757e01e33a9737d0b22373b3eb5a27358f9/numpy-2.2.6-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:389d771b1623ec92636b0786bc4ae56abafad4a4c513d36a55dce14bd9ce8571", size = 15586143, upload-time = "2025-05-17T21:42:37.464Z" }, - { url = "https://files.pythonhosted.org/packages/76/95/bef5b37f29fc5e739947e9ce5179ad402875633308504a52d188302319c8/numpy-2.2.6-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:8e9ace4a37db23421249ed236fdcdd457d671e25146786dfc96835cd951aa7c1", size = 18385260, upload-time = "2025-05-17T21:43:05.189Z" }, - { url = "https://files.pythonhosted.org/packages/09/04/f2f83279d287407cf36a7a8053a5abe7be3622a4363337338f2585e4afda/numpy-2.2.6-cp313-cp313t-win32.whl", hash = "sha256:038613e9fb8c72b0a41f025a7e4c3f0b7a1b5d768ece4796b674c8f3fe13efff", size = 6377225, upload-time = "2025-05-17T21:43:16.254Z" }, - { url = "https://files.pythonhosted.org/packages/67/0e/35082d13c09c02c011cf21570543d202ad929d961c02a147493cb0c2bdf5/numpy-2.2.6-cp313-cp313t-win_amd64.whl", hash = "sha256:6031dd6dfecc0cf9f668681a37648373bddd6421fff6c66ec1624eed0180ee06", size = 12771374, upload-time = "2025-05-17T21:43:35.479Z" }, - { url = "https://files.pythonhosted.org/packages/9e/3b/d94a75f4dbf1ef5d321523ecac21ef23a3cd2ac8b78ae2aac40873590229/numpy-2.2.6-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:0b605b275d7bd0c640cad4e5d30fa701a8d59302e127e5f79138ad62762c3e3d", size = 21040391, upload-time = "2025-05-17T21:44:35.948Z" }, - { url = "https://files.pythonhosted.org/packages/17/f4/09b2fa1b58f0fb4f7c7963a1649c64c4d315752240377ed74d9cd878f7b5/numpy-2.2.6-pp310-pypy310_pp73-macosx_14_0_x86_64.whl", hash = "sha256:7befc596a7dc9da8a337f79802ee8adb30a552a94f792b9c9d18c840055907db", size = 6786754, upload-time = "2025-05-17T21:44:47.446Z" }, - { url = "https://files.pythonhosted.org/packages/af/30/feba75f143bdc868a1cc3f44ccfa6c4b9ec522b36458e738cd00f67b573f/numpy-2.2.6-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ce47521a4754c8f4593837384bd3424880629f718d87c5d44f8ed763edd63543", size = 16643476, upload-time = "2025-05-17T21:45:11.871Z" }, - { url = "https://files.pythonhosted.org/packages/37/48/ac2a9584402fb6c0cd5b5d1a91dcf176b15760130dd386bbafdbfe3640bf/numpy-2.2.6-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:d042d24c90c41b54fd506da306759e06e568864df8ec17ccc17e9e884634fd00", size = 12812666, upload-time = "2025-05-17T21:45:31.426Z" }, -] - -[[package]] -name = "numpy" -version = "2.3.4" -source = { registry = "https://pypi.org/simple" } -resolution-markers = [ - "python_full_version >= '3.14' and platform_python_implementation == 'PyPy'", - "python_full_version >= '3.14' and platform_python_implementation != 'PyPy'", - "python_full_version == '3.13.*' and platform_python_implementation == 'PyPy'", - "python_full_version == '3.13.*' and platform_python_implementation != 'PyPy'", - "python_full_version >= '3.11' and python_full_version < '3.13' and platform_python_implementation == 'PyPy'", - "python_full_version >= '3.11' and python_full_version < '3.13' and platform_python_implementation != 'PyPy'", -] -sdist = { url = "https://files.pythonhosted.org/packages/b5/f4/098d2270d52b41f1bd7db9fc288aaa0400cb48c2a3e2af6fa365d9720947/numpy-2.3.4.tar.gz", hash = "sha256:a7d018bfedb375a8d979ac758b120ba846a7fe764911a64465fd87b8729f4a6a", size = 20582187, upload-time = "2025-10-15T16:18:11.77Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/60/e7/0e07379944aa8afb49a556a2b54587b828eb41dc9adc56fb7615b678ca53/numpy-2.3.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:e78aecd2800b32e8347ce49316d3eaf04aed849cd5b38e0af39f829a4e59f5eb", size = 21259519, upload-time = "2025-10-15T16:15:19.012Z" }, - { url = "https://files.pythonhosted.org/packages/d0/cb/5a69293561e8819b09e34ed9e873b9a82b5f2ade23dce4c51dc507f6cfe1/numpy-2.3.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:7fd09cc5d65bda1e79432859c40978010622112e9194e581e3415a3eccc7f43f", size = 14452796, upload-time = "2025-10-15T16:15:23.094Z" }, - { url = "https://files.pythonhosted.org/packages/e4/04/ff11611200acd602a1e5129e36cfd25bf01ad8e5cf927baf2e90236eb02e/numpy-2.3.4-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:1b219560ae2c1de48ead517d085bc2d05b9433f8e49d0955c82e8cd37bd7bf36", size = 5381639, upload-time = "2025-10-15T16:15:25.572Z" }, - { url = "https://files.pythonhosted.org/packages/ea/77/e95c757a6fe7a48d28a009267408e8aa382630cc1ad1db7451b3bc21dbb4/numpy-2.3.4-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:bafa7d87d4c99752d07815ed7a2c0964f8ab311eb8168f41b910bd01d15b6032", size = 6914296, upload-time = "2025-10-15T16:15:27.079Z" }, - { url = "https://files.pythonhosted.org/packages/a3/d2/137c7b6841c942124eae921279e5c41b1c34bab0e6fc60c7348e69afd165/numpy-2.3.4-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:36dc13af226aeab72b7abad501d370d606326a0029b9f435eacb3b8c94b8a8b7", size = 14591904, upload-time = "2025-10-15T16:15:29.044Z" }, - { url = "https://files.pythonhosted.org/packages/bb/32/67e3b0f07b0aba57a078c4ab777a9e8e6bc62f24fb53a2337f75f9691699/numpy-2.3.4-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a7b2f9a18b5ff9824a6af80de4f37f4ec3c2aab05ef08f51c77a093f5b89adda", size = 16939602, upload-time = "2025-10-15T16:15:31.106Z" }, - { url = "https://files.pythonhosted.org/packages/95/22/9639c30e32c93c4cee3ccdb4b09c2d0fbff4dcd06d36b357da06146530fb/numpy-2.3.4-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:9984bd645a8db6ca15d850ff996856d8762c51a2239225288f08f9050ca240a0", size = 16372661, upload-time = "2025-10-15T16:15:33.546Z" }, - { url = "https://files.pythonhosted.org/packages/12/e9/a685079529be2b0156ae0c11b13d6be647743095bb51d46589e95be88086/numpy-2.3.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:64c5825affc76942973a70acf438a8ab618dbd692b84cd5ec40a0a0509edc09a", size = 18884682, upload-time = "2025-10-15T16:15:36.105Z" }, - { url = "https://files.pythonhosted.org/packages/cf/85/f6f00d019b0cc741e64b4e00ce865a57b6bed945d1bbeb1ccadbc647959b/numpy-2.3.4-cp311-cp311-win32.whl", hash = "sha256:ed759bf7a70342f7817d88376eb7142fab9fef8320d6019ef87fae05a99874e1", size = 6570076, upload-time = "2025-10-15T16:15:38.225Z" }, - { url = "https://files.pythonhosted.org/packages/7d/10/f8850982021cb90e2ec31990291f9e830ce7d94eef432b15066e7cbe0bec/numpy-2.3.4-cp311-cp311-win_amd64.whl", hash = "sha256:faba246fb30ea2a526c2e9645f61612341de1a83fb1e0c5edf4ddda5a9c10996", size = 13089358, upload-time = "2025-10-15T16:15:40.404Z" }, - { url = "https://files.pythonhosted.org/packages/d1/ad/afdd8351385edf0b3445f9e24210a9c3971ef4de8fd85155462fc4321d79/numpy-2.3.4-cp311-cp311-win_arm64.whl", hash = "sha256:4c01835e718bcebe80394fd0ac66c07cbb90147ebbdad3dcecd3f25de2ae7e2c", size = 10462292, upload-time = "2025-10-15T16:15:42.896Z" }, - { url = "https://files.pythonhosted.org/packages/96/7a/02420400b736f84317e759291b8edaeee9dc921f72b045475a9cbdb26b17/numpy-2.3.4-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:ef1b5a3e808bc40827b5fa2c8196151a4c5abe110e1726949d7abddfe5c7ae11", size = 20957727, upload-time = "2025-10-15T16:15:44.9Z" }, - { url = "https://files.pythonhosted.org/packages/18/90/a014805d627aa5750f6f0e878172afb6454552da929144b3c07fcae1bb13/numpy-2.3.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:c2f91f496a87235c6aaf6d3f3d89b17dba64996abadccb289f48456cff931ca9", size = 14187262, upload-time = "2025-10-15T16:15:47.761Z" }, - { url = "https://files.pythonhosted.org/packages/c7/e4/0a94b09abe89e500dc748e7515f21a13e30c5c3fe3396e6d4ac108c25fca/numpy-2.3.4-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:f77e5b3d3da652b474cc80a14084927a5e86a5eccf54ca8ca5cbd697bf7f2667", size = 5115992, upload-time = "2025-10-15T16:15:50.144Z" }, - { url = "https://files.pythonhosted.org/packages/88/dd/db77c75b055c6157cbd4f9c92c4458daef0dd9cbe6d8d2fe7f803cb64c37/numpy-2.3.4-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:8ab1c5f5ee40d6e01cbe96de5863e39b215a4d24e7d007cad56c7184fdf4aeef", size = 6648672, upload-time = "2025-10-15T16:15:52.442Z" }, - { url = "https://files.pythonhosted.org/packages/e1/e6/e31b0d713719610e406c0ea3ae0d90760465b086da8783e2fd835ad59027/numpy-2.3.4-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:77b84453f3adcb994ddbd0d1c5d11db2d6bda1a2b7fd5ac5bd4649d6f5dc682e", size = 14284156, upload-time = "2025-10-15T16:15:54.351Z" }, - { url = "https://files.pythonhosted.org/packages/f9/58/30a85127bfee6f108282107caf8e06a1f0cc997cb6b52cdee699276fcce4/numpy-2.3.4-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4121c5beb58a7f9e6dfdee612cb24f4df5cd4db6e8261d7f4d7450a997a65d6a", size = 16641271, upload-time = "2025-10-15T16:15:56.67Z" }, - { url = "https://files.pythonhosted.org/packages/06/f2/2e06a0f2adf23e3ae29283ad96959267938d0efd20a2e25353b70065bfec/numpy-2.3.4-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:65611ecbb00ac9846efe04db15cbe6186f562f6bb7e5e05f077e53a599225d16", size = 16059531, upload-time = "2025-10-15T16:15:59.412Z" }, - { url = "https://files.pythonhosted.org/packages/b0/e7/b106253c7c0d5dc352b9c8fab91afd76a93950998167fa3e5afe4ef3a18f/numpy-2.3.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:dabc42f9c6577bcc13001b8810d300fe814b4cfbe8a92c873f269484594f9786", size = 18578983, upload-time = "2025-10-15T16:16:01.804Z" }, - { url = "https://files.pythonhosted.org/packages/73/e3/04ecc41e71462276ee867ccbef26a4448638eadecf1bc56772c9ed6d0255/numpy-2.3.4-cp312-cp312-win32.whl", hash = "sha256:a49d797192a8d950ca59ee2d0337a4d804f713bb5c3c50e8db26d49666e351dc", size = 6291380, upload-time = "2025-10-15T16:16:03.938Z" }, - { url = "https://files.pythonhosted.org/packages/3d/a8/566578b10d8d0e9955b1b6cd5db4e9d4592dd0026a941ff7994cedda030a/numpy-2.3.4-cp312-cp312-win_amd64.whl", hash = "sha256:985f1e46358f06c2a09921e8921e2c98168ed4ae12ccd6e5e87a4f1857923f32", size = 12787999, upload-time = "2025-10-15T16:16:05.801Z" }, - { url = "https://files.pythonhosted.org/packages/58/22/9c903a957d0a8071b607f5b1bff0761d6e608b9a965945411f867d515db1/numpy-2.3.4-cp312-cp312-win_arm64.whl", hash = "sha256:4635239814149e06e2cb9db3dd584b2fa64316c96f10656983b8026a82e6e4db", size = 10197412, upload-time = "2025-10-15T16:16:07.854Z" }, - { url = "https://files.pythonhosted.org/packages/57/7e/b72610cc91edf138bc588df5150957a4937221ca6058b825b4725c27be62/numpy-2.3.4-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:c090d4860032b857d94144d1a9976b8e36709e40386db289aaf6672de2a81966", size = 20950335, upload-time = "2025-10-15T16:16:10.304Z" }, - { url = "https://files.pythonhosted.org/packages/3e/46/bdd3370dcea2f95ef14af79dbf81e6927102ddf1cc54adc0024d61252fd9/numpy-2.3.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a13fc473b6db0be619e45f11f9e81260f7302f8d180c49a22b6e6120022596b3", size = 14179878, upload-time = "2025-10-15T16:16:12.595Z" }, - { url = "https://files.pythonhosted.org/packages/ac/01/5a67cb785bda60f45415d09c2bc245433f1c68dd82eef9c9002c508b5a65/numpy-2.3.4-cp313-cp313-macosx_14_0_arm64.whl", hash = "sha256:3634093d0b428e6c32c3a69b78e554f0cd20ee420dcad5a9f3b2a63762ce4197", size = 5108673, upload-time = "2025-10-15T16:16:14.877Z" }, - { url = "https://files.pythonhosted.org/packages/c2/cd/8428e23a9fcebd33988f4cb61208fda832800ca03781f471f3727a820704/numpy-2.3.4-cp313-cp313-macosx_14_0_x86_64.whl", hash = "sha256:043885b4f7e6e232d7df4f51ffdef8c36320ee9d5f227b380ea636722c7ed12e", size = 6641438, upload-time = "2025-10-15T16:16:16.805Z" }, - { url = "https://files.pythonhosted.org/packages/3e/d1/913fe563820f3c6b079f992458f7331278dcd7ba8427e8e745af37ddb44f/numpy-2.3.4-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4ee6a571d1e4f0ea6d5f22d6e5fbd6ed1dc2b18542848e1e7301bd190500c9d7", size = 14281290, upload-time = "2025-10-15T16:16:18.764Z" }, - { url = "https://files.pythonhosted.org/packages/9e/7e/7d306ff7cb143e6d975cfa7eb98a93e73495c4deabb7d1b5ecf09ea0fd69/numpy-2.3.4-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:fc8a63918b04b8571789688b2780ab2b4a33ab44bfe8ccea36d3eba51228c953", size = 16636543, upload-time = "2025-10-15T16:16:21.072Z" }, - { url = "https://files.pythonhosted.org/packages/47/6a/8cfc486237e56ccfb0db234945552a557ca266f022d281a2f577b98e955c/numpy-2.3.4-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:40cc556d5abbc54aabe2b1ae287042d7bdb80c08edede19f0c0afb36ae586f37", size = 16056117, upload-time = "2025-10-15T16:16:23.369Z" }, - { url = "https://files.pythonhosted.org/packages/b1/0e/42cb5e69ea901e06ce24bfcc4b5664a56f950a70efdcf221f30d9615f3f3/numpy-2.3.4-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:ecb63014bb7f4ce653f8be7f1df8cbc6093a5a2811211770f6606cc92b5a78fd", size = 18577788, upload-time = "2025-10-15T16:16:27.496Z" }, - { url = "https://files.pythonhosted.org/packages/86/92/41c3d5157d3177559ef0a35da50f0cda7fa071f4ba2306dd36818591a5bc/numpy-2.3.4-cp313-cp313-win32.whl", hash = "sha256:e8370eb6925bb8c1c4264fec52b0384b44f675f191df91cbe0140ec9f0955646", size = 6282620, upload-time = "2025-10-15T16:16:29.811Z" }, - { url = "https://files.pythonhosted.org/packages/09/97/fd421e8bc50766665ad35536c2bb4ef916533ba1fdd053a62d96cc7c8b95/numpy-2.3.4-cp313-cp313-win_amd64.whl", hash = "sha256:56209416e81a7893036eea03abcb91c130643eb14233b2515c90dcac963fe99d", size = 12784672, upload-time = "2025-10-15T16:16:31.589Z" }, - { url = "https://files.pythonhosted.org/packages/ad/df/5474fb2f74970ca8eb978093969b125a84cc3d30e47f82191f981f13a8a0/numpy-2.3.4-cp313-cp313-win_arm64.whl", hash = "sha256:a700a4031bc0fd6936e78a752eefb79092cecad2599ea9c8039c548bc097f9bc", size = 10196702, upload-time = "2025-10-15T16:16:33.902Z" }, - { url = "https://files.pythonhosted.org/packages/11/83/66ac031464ec1767ea3ed48ce40f615eb441072945e98693bec0bcd056cc/numpy-2.3.4-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:86966db35c4040fdca64f0816a1c1dd8dbd027d90fca5a57e00e1ca4cd41b879", size = 21049003, upload-time = "2025-10-15T16:16:36.101Z" }, - { url = "https://files.pythonhosted.org/packages/5f/99/5b14e0e686e61371659a1d5bebd04596b1d72227ce36eed121bb0aeab798/numpy-2.3.4-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:838f045478638b26c375ee96ea89464d38428c69170360b23a1a50fa4baa3562", size = 14302980, upload-time = "2025-10-15T16:16:39.124Z" }, - { url = "https://files.pythonhosted.org/packages/2c/44/e9486649cd087d9fc6920e3fc3ac2aba10838d10804b1e179fb7cbc4e634/numpy-2.3.4-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:d7315ed1dab0286adca467377c8381cd748f3dc92235f22a7dfc42745644a96a", size = 5231472, upload-time = "2025-10-15T16:16:41.168Z" }, - { url = "https://files.pythonhosted.org/packages/3e/51/902b24fa8887e5fe2063fd61b1895a476d0bbf46811ab0c7fdf4bd127345/numpy-2.3.4-cp313-cp313t-macosx_14_0_x86_64.whl", hash = "sha256:84f01a4d18b2cc4ade1814a08e5f3c907b079c847051d720fad15ce37aa930b6", size = 6739342, upload-time = "2025-10-15T16:16:43.777Z" }, - { url = "https://files.pythonhosted.org/packages/34/f1/4de9586d05b1962acdcdb1dc4af6646361a643f8c864cef7c852bf509740/numpy-2.3.4-cp313-cp313t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:817e719a868f0dacde4abdfc5c1910b301877970195db9ab6a5e2c4bd5b121f7", size = 14354338, upload-time = "2025-10-15T16:16:46.081Z" }, - { url = "https://files.pythonhosted.org/packages/1f/06/1c16103b425de7969d5a76bdf5ada0804b476fed05d5f9e17b777f1cbefd/numpy-2.3.4-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:85e071da78d92a214212cacea81c6da557cab307f2c34b5f85b628e94803f9c0", size = 16702392, upload-time = "2025-10-15T16:16:48.455Z" }, - { url = "https://files.pythonhosted.org/packages/34/b2/65f4dc1b89b5322093572b6e55161bb42e3e0487067af73627f795cc9d47/numpy-2.3.4-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:2ec646892819370cf3558f518797f16597b4e4669894a2ba712caccc9da53f1f", size = 16134998, upload-time = "2025-10-15T16:16:51.114Z" }, - { url = "https://files.pythonhosted.org/packages/d4/11/94ec578896cdb973aaf56425d6c7f2aff4186a5c00fac15ff2ec46998b46/numpy-2.3.4-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:035796aaaddfe2f9664b9a9372f089cfc88bd795a67bd1bfe15e6e770934cf64", size = 18651574, upload-time = "2025-10-15T16:16:53.429Z" }, - { url = "https://files.pythonhosted.org/packages/62/b7/7efa763ab33dbccf56dade36938a77345ce8e8192d6b39e470ca25ff3cd0/numpy-2.3.4-cp313-cp313t-win32.whl", hash = "sha256:fea80f4f4cf83b54c3a051f2f727870ee51e22f0248d3114b8e755d160b38cfb", size = 6413135, upload-time = "2025-10-15T16:16:55.992Z" }, - { url = "https://files.pythonhosted.org/packages/43/70/aba4c38e8400abcc2f345e13d972fb36c26409b3e644366db7649015f291/numpy-2.3.4-cp313-cp313t-win_amd64.whl", hash = "sha256:15eea9f306b98e0be91eb344a94c0e630689ef302e10c2ce5f7e11905c704f9c", size = 12928582, upload-time = "2025-10-15T16:16:57.943Z" }, - { url = "https://files.pythonhosted.org/packages/67/63/871fad5f0073fc00fbbdd7232962ea1ac40eeaae2bba66c76214f7954236/numpy-2.3.4-cp313-cp313t-win_arm64.whl", hash = "sha256:b6c231c9c2fadbae4011ca5e7e83e12dc4a5072f1a1d85a0a7b3ed754d145a40", size = 10266691, upload-time = "2025-10-15T16:17:00.048Z" }, - { url = "https://files.pythonhosted.org/packages/72/71/ae6170143c115732470ae3a2d01512870dd16e0953f8a6dc89525696069b/numpy-2.3.4-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:81c3e6d8c97295a7360d367f9f8553973651b76907988bb6066376bc2252f24e", size = 20955580, upload-time = "2025-10-15T16:17:02.509Z" }, - { url = "https://files.pythonhosted.org/packages/af/39/4be9222ffd6ca8a30eda033d5f753276a9c3426c397bb137d8e19dedd200/numpy-2.3.4-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:7c26b0b2bf58009ed1f38a641f3db4be8d960a417ca96d14e5b06df1506d41ff", size = 14188056, upload-time = "2025-10-15T16:17:04.873Z" }, - { url = "https://files.pythonhosted.org/packages/6c/3d/d85f6700d0a4aa4f9491030e1021c2b2b7421b2b38d01acd16734a2bfdc7/numpy-2.3.4-cp314-cp314-macosx_14_0_arm64.whl", hash = "sha256:62b2198c438058a20b6704351b35a1d7db881812d8512d67a69c9de1f18ca05f", size = 5116555, upload-time = "2025-10-15T16:17:07.499Z" }, - { url = "https://files.pythonhosted.org/packages/bf/04/82c1467d86f47eee8a19a464c92f90a9bb68ccf14a54c5224d7031241ffb/numpy-2.3.4-cp314-cp314-macosx_14_0_x86_64.whl", hash = "sha256:9d729d60f8d53a7361707f4b68a9663c968882dd4f09e0d58c044c8bf5faee7b", size = 6643581, upload-time = "2025-10-15T16:17:09.774Z" }, - { url = "https://files.pythonhosted.org/packages/0c/d3/c79841741b837e293f48bd7db89d0ac7a4f2503b382b78a790ef1dc778a5/numpy-2.3.4-cp314-cp314-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:bd0c630cf256b0a7fd9d0a11c9413b42fef5101219ce6ed5a09624f5a65392c7", size = 14299186, upload-time = "2025-10-15T16:17:11.937Z" }, - { url = "https://files.pythonhosted.org/packages/e8/7e/4a14a769741fbf237eec5a12a2cbc7a4c4e061852b6533bcb9e9a796c908/numpy-2.3.4-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d5e081bc082825f8b139f9e9fe42942cb4054524598aaeb177ff476cc76d09d2", size = 16638601, upload-time = "2025-10-15T16:17:14.391Z" }, - { url = "https://files.pythonhosted.org/packages/93/87/1c1de269f002ff0a41173fe01dcc925f4ecff59264cd8f96cf3b60d12c9b/numpy-2.3.4-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:15fb27364ed84114438fff8aaf998c9e19adbeba08c0b75409f8c452a8692c52", size = 16074219, upload-time = "2025-10-15T16:17:17.058Z" }, - { url = "https://files.pythonhosted.org/packages/cd/28/18f72ee77408e40a76d691001ae599e712ca2a47ddd2c4f695b16c65f077/numpy-2.3.4-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:85d9fb2d8cd998c84d13a79a09cc0c1091648e848e4e6249b0ccd7f6b487fa26", size = 18576702, upload-time = "2025-10-15T16:17:19.379Z" }, - { url = "https://files.pythonhosted.org/packages/c3/76/95650169b465ececa8cf4b2e8f6df255d4bf662775e797ade2025cc51ae6/numpy-2.3.4-cp314-cp314-win32.whl", hash = "sha256:e73d63fd04e3a9d6bc187f5455d81abfad05660b212c8804bf3b407e984cd2bc", size = 6337136, upload-time = "2025-10-15T16:17:22.886Z" }, - { url = "https://files.pythonhosted.org/packages/dc/89/a231a5c43ede5d6f77ba4a91e915a87dea4aeea76560ba4d2bf185c683f0/numpy-2.3.4-cp314-cp314-win_amd64.whl", hash = "sha256:3da3491cee49cf16157e70f607c03a217ea6647b1cea4819c4f48e53d49139b9", size = 12920542, upload-time = "2025-10-15T16:17:24.783Z" }, - { url = "https://files.pythonhosted.org/packages/0d/0c/ae9434a888f717c5ed2ff2393b3f344f0ff6f1c793519fa0c540461dc530/numpy-2.3.4-cp314-cp314-win_arm64.whl", hash = "sha256:6d9cd732068e8288dbe2717177320723ccec4fb064123f0caf9bbd90ab5be868", size = 10480213, upload-time = "2025-10-15T16:17:26.935Z" }, - { url = "https://files.pythonhosted.org/packages/83/4b/c4a5f0841f92536f6b9592694a5b5f68c9ab37b775ff342649eadf9055d3/numpy-2.3.4-cp314-cp314t-macosx_10_15_x86_64.whl", hash = "sha256:22758999b256b595cf0b1d102b133bb61866ba5ceecf15f759623b64c020c9ec", size = 21052280, upload-time = "2025-10-15T16:17:29.638Z" }, - { url = "https://files.pythonhosted.org/packages/3e/80/90308845fc93b984d2cc96d83e2324ce8ad1fd6efea81b324cba4b673854/numpy-2.3.4-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:9cb177bc55b010b19798dc5497d540dea67fd13a8d9e882b2dae71de0cf09eb3", size = 14302930, upload-time = "2025-10-15T16:17:32.384Z" }, - { url = "https://files.pythonhosted.org/packages/3d/4e/07439f22f2a3b247cec4d63a713faae55e1141a36e77fb212881f7cda3fb/numpy-2.3.4-cp314-cp314t-macosx_14_0_arm64.whl", hash = "sha256:0f2bcc76f1e05e5ab58893407c63d90b2029908fa41f9f1cc51eecce936c3365", size = 5231504, upload-time = "2025-10-15T16:17:34.515Z" }, - { url = "https://files.pythonhosted.org/packages/ab/de/1e11f2547e2fe3d00482b19721855348b94ada8359aef5d40dd57bfae9df/numpy-2.3.4-cp314-cp314t-macosx_14_0_x86_64.whl", hash = "sha256:8dc20bde86802df2ed8397a08d793da0ad7a5fd4ea3ac85d757bf5dd4ad7c252", size = 6739405, upload-time = "2025-10-15T16:17:36.128Z" }, - { url = "https://files.pythonhosted.org/packages/3b/40/8cd57393a26cebe2e923005db5134a946c62fa56a1087dc7c478f3e30837/numpy-2.3.4-cp314-cp314t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5e199c087e2aa71c8f9ce1cb7a8e10677dc12457e7cc1be4798632da37c3e86e", size = 14354866, upload-time = "2025-10-15T16:17:38.884Z" }, - { url = "https://files.pythonhosted.org/packages/93/39/5b3510f023f96874ee6fea2e40dfa99313a00bf3ab779f3c92978f34aace/numpy-2.3.4-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:85597b2d25ddf655495e2363fe044b0ae999b75bc4d630dc0d886484b03a5eb0", size = 16703296, upload-time = "2025-10-15T16:17:41.564Z" }, - { url = "https://files.pythonhosted.org/packages/41/0d/19bb163617c8045209c1996c4e427bccbc4bbff1e2c711f39203c8ddbb4a/numpy-2.3.4-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:04a69abe45b49c5955923cf2c407843d1c85013b424ae8a560bba16c92fe44a0", size = 16136046, upload-time = "2025-10-15T16:17:43.901Z" }, - { url = "https://files.pythonhosted.org/packages/e2/c1/6dba12fdf68b02a21ac411c9df19afa66bed2540f467150ca64d246b463d/numpy-2.3.4-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:e1708fac43ef8b419c975926ce1eaf793b0c13b7356cfab6ab0dc34c0a02ac0f", size = 18652691, upload-time = "2025-10-15T16:17:46.247Z" }, - { url = "https://files.pythonhosted.org/packages/f8/73/f85056701dbbbb910c51d846c58d29fd46b30eecd2b6ba760fc8b8a1641b/numpy-2.3.4-cp314-cp314t-win32.whl", hash = "sha256:863e3b5f4d9915aaf1b8ec79ae560ad21f0b8d5e3adc31e73126491bb86dee1d", size = 6485782, upload-time = "2025-10-15T16:17:48.872Z" }, - { url = "https://files.pythonhosted.org/packages/17/90/28fa6f9865181cb817c2471ee65678afa8a7e2a1fb16141473d5fa6bacc3/numpy-2.3.4-cp314-cp314t-win_amd64.whl", hash = "sha256:962064de37b9aef801d33bc579690f8bfe6c5e70e29b61783f60bcba838a14d6", size = 13113301, upload-time = "2025-10-15T16:17:50.938Z" }, - { url = "https://files.pythonhosted.org/packages/54/23/08c002201a8e7e1f9afba93b97deceb813252d9cfd0d3351caed123dcf97/numpy-2.3.4-cp314-cp314t-win_arm64.whl", hash = "sha256:8b5a9a39c45d852b62693d9b3f3e0fe052541f804296ff401a72a1b60edafb29", size = 10547532, upload-time = "2025-10-15T16:17:53.48Z" }, - { url = "https://files.pythonhosted.org/packages/b1/b6/64898f51a86ec88ca1257a59c1d7fd077b60082a119affefcdf1dd0df8ca/numpy-2.3.4-pp311-pypy311_pp73-macosx_10_15_x86_64.whl", hash = "sha256:6e274603039f924c0fe5cb73438fa9246699c78a6df1bd3decef9ae592ae1c05", size = 21131552, upload-time = "2025-10-15T16:17:55.845Z" }, - { url = "https://files.pythonhosted.org/packages/ce/4c/f135dc6ebe2b6a3c77f4e4838fa63d350f85c99462012306ada1bd4bc460/numpy-2.3.4-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:d149aee5c72176d9ddbc6803aef9c0f6d2ceeea7626574fc68518da5476fa346", size = 14377796, upload-time = "2025-10-15T16:17:58.308Z" }, - { url = "https://files.pythonhosted.org/packages/d0/a4/f33f9c23fcc13dd8412fc8614559b5b797e0aba9d8e01dfa8bae10c84004/numpy-2.3.4-pp311-pypy311_pp73-macosx_14_0_arm64.whl", hash = "sha256:6d34ed9db9e6395bb6cd33286035f73a59b058169733a9db9f85e650b88df37e", size = 5306904, upload-time = "2025-10-15T16:18:00.596Z" }, - { url = "https://files.pythonhosted.org/packages/28/af/c44097f25f834360f9fb960fa082863e0bad14a42f36527b2a121abdec56/numpy-2.3.4-pp311-pypy311_pp73-macosx_14_0_x86_64.whl", hash = "sha256:fdebe771ca06bb8d6abce84e51dca9f7921fe6ad34a0c914541b063e9a68928b", size = 6819682, upload-time = "2025-10-15T16:18:02.32Z" }, - { url = "https://files.pythonhosted.org/packages/c5/8c/cd283b54c3c2b77e188f63e23039844f56b23bba1712318288c13fe86baf/numpy-2.3.4-pp311-pypy311_pp73-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:957e92defe6c08211eb77902253b14fe5b480ebc5112bc741fd5e9cd0608f847", size = 14422300, upload-time = "2025-10-15T16:18:04.271Z" }, - { url = "https://files.pythonhosted.org/packages/b0/f0/8404db5098d92446b3e3695cf41c6f0ecb703d701cb0b7566ee2177f2eee/numpy-2.3.4-pp311-pypy311_pp73-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:13b9062e4f5c7ee5c7e5be96f29ba71bc5a37fed3d1d77c37390ae00724d296d", size = 16760806, upload-time = "2025-10-15T16:18:06.668Z" }, - { url = "https://files.pythonhosted.org/packages/95/8e/2844c3959ce9a63acc7c8e50881133d86666f0420bcde695e115ced0920f/numpy-2.3.4-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:81b3a59793523e552c4a96109dde028aa4448ae06ccac5a76ff6532a85558a7f", size = 12973130, upload-time = "2025-10-15T16:18:09.397Z" }, -] - -[[package]] -name = "opentelemetry-api" -version = "1.37.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "importlib-metadata" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/63/04/05040d7ce33a907a2a02257e601992f0cdf11c73b33f13c4492bf6c3d6d5/opentelemetry_api-1.37.0.tar.gz", hash = "sha256:540735b120355bd5112738ea53621f8d5edb35ebcd6fe21ada3ab1c61d1cd9a7", size = 64923, upload-time = "2025-09-11T10:29:01.662Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/91/48/28ed9e55dcf2f453128df738210a980e09f4e468a456fa3c763dbc8be70a/opentelemetry_api-1.37.0-py3-none-any.whl", hash = "sha256:accf2024d3e89faec14302213bc39550ec0f4095d1cf5ca688e1bfb1c8612f47", size = 65732, upload-time = "2025-09-11T10:28:41.826Z" }, -] - -[[package]] -name = "opentelemetry-exporter-gcp-logging" -version = "1.10.0a0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-cloud-logging" }, - { name = "opentelemetry-api" }, - { name = "opentelemetry-resourcedetector-gcp" }, - { name = "opentelemetry-sdk" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/8c/a0/ff56dc397dcccad4abd4da2b9b070831d2af9dea7d4dc1079613d8162e64/opentelemetry_exporter_gcp_logging-1.10.0a0.tar.gz", hash = "sha256:a4db7e89a108270399811a8f38566664489c70ada0ce05f0fdbc8b729f8cd0ef", size = 18450, upload-time = "2025-10-14T17:30:52.981Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7c/bc/e3198a928aa7fee2ac98a39d8dc6310aa80350b66f3d624cbf317c3e3ee6/opentelemetry_exporter_gcp_logging-1.10.0a0-py3-none-any.whl", hash = "sha256:cb03a439ca34d42353318a9551900491abe4a369270ede5ce13d2e0a6e817a7d", size = 12509, upload-time = "2025-10-14T17:30:47.2Z" }, -] - -[[package]] -name = "opentelemetry-exporter-gcp-monitoring" -version = "1.10.0a0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-cloud-monitoring" }, - { name = "opentelemetry-api" }, - { name = "opentelemetry-resourcedetector-gcp" }, - { name = "opentelemetry-sdk" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/1e/fc/7111500850db20890a080c2e35d5ef936bbec7082b0cd390ed45f9e18371/opentelemetry_exporter_gcp_monitoring-1.10.0a0.tar.gz", hash = "sha256:48520fe053d61667ca73a2dd64d4940200cc1b9063dbbf4e380728941b3da2e9", size = 20540, upload-time = "2025-10-14T17:30:54.008Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d5/b7/e2690efa88f159679a900b9ac4bf33bb8e16248d384b50f92772a973a31a/opentelemetry_exporter_gcp_monitoring-1.10.0a0-py3-none-any.whl", hash = "sha256:a6ad379a77a5c4d65331216faa2b8ae7426cb744f597e5f0af99382759c42a3f", size = 13611, upload-time = "2025-10-14T17:30:48.196Z" }, -] - -[[package]] -name = "opentelemetry-exporter-gcp-trace" -version = "1.10.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "google-cloud-trace" }, - { name = "opentelemetry-api" }, - { name = "opentelemetry-resourcedetector-gcp" }, - { name = "opentelemetry-sdk" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/c6/38/38a75b0a8e64c27af63871ca03bb8fc111437f9273ddcc705b1f55b10f40/opentelemetry_exporter_gcp_trace-1.10.0.tar.gz", hash = "sha256:2c0f2bb69ba4272e984d6adb3225f1d51ed6897b03f6db854588ccae0f08157f", size = 18604, upload-time = "2025-10-14T17:30:54.608Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e2/95/1a108bb61ff162555f72f4dd1ac618b6b7fa0b888e36f82cf3ec5c640b7c/opentelemetry_exporter_gcp_trace-1.10.0-py3-none-any.whl", hash = "sha256:766277704ebd86d0225cf734cd6d6c07c57ddb1d006bad5b3ede97e6d9018794", size = 14016, upload-time = "2025-10-14T17:30:49.114Z" }, -] - -[[package]] -name = "opentelemetry-exporter-otlp-proto-common" -version = "1.37.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "opentelemetry-proto" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/dc/6c/10018cbcc1e6fff23aac67d7fd977c3d692dbe5f9ef9bb4db5c1268726cc/opentelemetry_exporter_otlp_proto_common-1.37.0.tar.gz", hash = "sha256:c87a1bdd9f41fdc408d9cc9367bb53f8d2602829659f2b90be9f9d79d0bfe62c", size = 20430, upload-time = "2025-09-11T10:29:03.605Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/08/13/b4ef09837409a777f3c0af2a5b4ba9b7af34872bc43609dda0c209e4060d/opentelemetry_exporter_otlp_proto_common-1.37.0-py3-none-any.whl", hash = "sha256:53038428449c559b0c564b8d718df3314da387109c4d36bd1b94c9a641b0292e", size = 18359, upload-time = "2025-09-11T10:28:44.939Z" }, -] - -[[package]] -name = "opentelemetry-exporter-otlp-proto-http" -version = "1.37.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "googleapis-common-protos" }, - { name = "opentelemetry-api" }, - { name = "opentelemetry-exporter-otlp-proto-common" }, - { name = "opentelemetry-proto" }, - { name = "opentelemetry-sdk" }, - { name = "requests" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/5d/e3/6e320aeb24f951449e73867e53c55542bebbaf24faeee7623ef677d66736/opentelemetry_exporter_otlp_proto_http-1.37.0.tar.gz", hash = "sha256:e52e8600f1720d6de298419a802108a8f5afa63c96809ff83becb03f874e44ac", size = 17281, upload-time = "2025-09-11T10:29:04.844Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e9/e9/70d74a664d83976556cec395d6bfedd9b85ec1498b778367d5f93e373397/opentelemetry_exporter_otlp_proto_http-1.37.0-py3-none-any.whl", hash = "sha256:54c42b39945a6cc9d9a2a33decb876eabb9547e0dcb49df090122773447f1aef", size = 19576, upload-time = "2025-09-11T10:28:46.726Z" }, -] - -[[package]] -name = "opentelemetry-proto" -version = "1.37.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/dd/ea/a75f36b463a36f3c5a10c0b5292c58b31dbdde74f6f905d3d0ab2313987b/opentelemetry_proto-1.37.0.tar.gz", hash = "sha256:30f5c494faf66f77faeaefa35ed4443c5edb3b0aa46dad073ed7210e1a789538", size = 46151, upload-time = "2025-09-11T10:29:11.04Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/c4/25/f89ea66c59bd7687e218361826c969443c4fa15dfe89733f3bf1e2a9e971/opentelemetry_proto-1.37.0-py3-none-any.whl", hash = "sha256:8ed8c066ae8828bbf0c39229979bdf583a126981142378a9cbe9d6fd5701c6e2", size = 72534, upload-time = "2025-09-11T10:28:56.831Z" }, -] - -[[package]] -name = "opentelemetry-resourcedetector-gcp" -version = "1.10.0a0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "opentelemetry-api" }, - { name = "opentelemetry-sdk" }, - { name = "requests" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/e0/ed/46daeac6d5c24d93a8b7bf58cccfbd190a6b9fe9a4db27e77bf5ef7b0f60/opentelemetry_resourcedetector_gcp-1.10.0a0.tar.gz", hash = "sha256:89b1adfdc7cb66b314da7cae78e1084ec3b64580f2d0532395ad4e079b4ae3f9", size = 18614, upload-time = "2025-10-14T17:30:56.063Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/52/38/bbcb219e822299e87daf8d9df28743c946e2ef04d24f19d26a61cfd28734/opentelemetry_resourcedetector_gcp-1.10.0a0-py3-none-any.whl", hash = "sha256:942319cad3244c2e05b67df1d89dcdb7f482e5a2239231340722ad642de848a9", size = 18801, upload-time = "2025-10-14T17:30:51.842Z" }, -] - -[[package]] -name = "opentelemetry-sdk" -version = "1.37.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "opentelemetry-api" }, - { name = "opentelemetry-semantic-conventions" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/f4/62/2e0ca80d7fe94f0b193135375da92c640d15fe81f636658d2acf373086bc/opentelemetry_sdk-1.37.0.tar.gz", hash = "sha256:cc8e089c10953ded765b5ab5669b198bbe0af1b3f89f1007d19acd32dc46dda5", size = 170404, upload-time = "2025-09-11T10:29:11.779Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/9f/62/9f4ad6a54126fb00f7ed4bb5034964c6e4f00fcd5a905e115bd22707e20d/opentelemetry_sdk-1.37.0-py3-none-any.whl", hash = "sha256:8f3c3c22063e52475c5dbced7209495c2c16723d016d39287dfc215d1771257c", size = 131941, upload-time = "2025-09-11T10:28:57.83Z" }, -] - -[[package]] -name = "opentelemetry-semantic-conventions" -version = "0.58b0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "opentelemetry-api" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/aa/1b/90701d91e6300d9f2fb352153fb1721ed99ed1f6ea14fa992c756016e63a/opentelemetry_semantic_conventions-0.58b0.tar.gz", hash = "sha256:6bd46f51264279c433755767bb44ad00f1c9e2367e1b42af563372c5a6fa0c25", size = 129867, upload-time = "2025-09-11T10:29:12.597Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/07/90/68152b7465f50285d3ce2481b3aec2f82822e3f52e5152eeeaf516bab841/opentelemetry_semantic_conventions-0.58b0-py3-none-any.whl", hash = "sha256:5564905ab1458b96684db1340232729fce3b5375a06e140e8904c78e4f815b28", size = 207954, upload-time = "2025-09-11T10:28:59.218Z" }, -] - -[[package]] -name = "packaging" -version = "25.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a1/d4/1fc4078c65507b51b96ca8f8c3ba19e6a61c8253c72794544580a7b6c24d/packaging-25.0.tar.gz", hash = "sha256:d443872c98d677bf60f6a1f2f8c1cb748e8fe762d2bf9d3148b5599295b0fc4f", size = 165727, upload-time = "2025-04-19T11:48:59.673Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/20/12/38679034af332785aac8774540895e234f4d07f7545804097de4b666afd8/packaging-25.0-py3-none-any.whl", hash = "sha256:29572ef2b1f17581046b3a2227d5c611fb25ec70ca1ba8554b24b0e69331a484", size = 66469, upload-time = "2025-04-19T11:48:57.875Z" }, -] - -[[package]] -name = "pluggy" -version = "1.6.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f9/e2/3e91f31a7d2b083fe6ef3fa267035b518369d9511ffab804f839851d2779/pluggy-1.6.0.tar.gz", hash = "sha256:7dcc130b76258d33b90f61b658791dede3486c3e6bfb003ee5c9bfb396dd22f3", size = 69412, upload-time = "2025-05-15T12:30:07.975Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl", hash = "sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746", size = 20538, upload-time = "2025-05-15T12:30:06.134Z" }, -] - -[[package]] -name = "propcache" -version = "0.4.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/9e/da/e9fc233cf63743258bff22b3dfa7ea5baef7b5bc324af47a0ad89b8ffc6f/propcache-0.4.1.tar.gz", hash = "sha256:f48107a8c637e80362555f37ecf49abe20370e557cc4ab374f04ec4423c97c3d", size = 46442, upload-time = "2025-10-08T19:49:02.291Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/3c/0e/934b541323035566a9af292dba85a195f7b78179114f2c6ebb24551118a9/propcache-0.4.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7c2d1fa3201efaf55d730400d945b5b3ab6e672e100ba0f9a409d950ab25d7db", size = 79534, upload-time = "2025-10-08T19:46:02.083Z" }, - { url = "https://files.pythonhosted.org/packages/a1/6b/db0d03d96726d995dc7171286c6ba9d8d14251f37433890f88368951a44e/propcache-0.4.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:1eb2994229cc8ce7fe9b3db88f5465f5fd8651672840b2e426b88cdb1a30aac8", size = 45526, upload-time = "2025-10-08T19:46:03.884Z" }, - { url = "https://files.pythonhosted.org/packages/e4/c3/82728404aea669e1600f304f2609cde9e665c18df5a11cdd57ed73c1dceb/propcache-0.4.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:66c1f011f45a3b33d7bcb22daed4b29c0c9e2224758b6be00686731e1b46f925", size = 47263, upload-time = "2025-10-08T19:46:05.405Z" }, - { url = "https://files.pythonhosted.org/packages/df/1b/39313ddad2bf9187a1432654c38249bab4562ef535ef07f5eb6eb04d0b1b/propcache-0.4.1-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:9a52009f2adffe195d0b605c25ec929d26b36ef986ba85244891dee3b294df21", size = 201012, upload-time = "2025-10-08T19:46:07.165Z" }, - { url = "https://files.pythonhosted.org/packages/5b/01/f1d0b57d136f294a142acf97f4ed58c8e5b974c21e543000968357115011/propcache-0.4.1-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:5d4e2366a9c7b837555cf02fb9be2e3167d333aff716332ef1b7c3a142ec40c5", size = 209491, upload-time = "2025-10-08T19:46:08.909Z" }, - { url = "https://files.pythonhosted.org/packages/a1/c8/038d909c61c5bb039070b3fb02ad5cccdb1dde0d714792e251cdb17c9c05/propcache-0.4.1-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:9d2b6caef873b4f09e26ea7e33d65f42b944837563a47a94719cc3544319a0db", size = 215319, upload-time = "2025-10-08T19:46:10.7Z" }, - { url = "https://files.pythonhosted.org/packages/08/57/8c87e93142b2c1fa2408e45695205a7ba05fb5db458c0bf5c06ba0e09ea6/propcache-0.4.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:2b16ec437a8c8a965ecf95739448dd938b5c7f56e67ea009f4300d8df05f32b7", size = 196856, upload-time = "2025-10-08T19:46:12.003Z" }, - { url = "https://files.pythonhosted.org/packages/42/df/5615fec76aa561987a534759b3686008a288e73107faa49a8ae5795a9f7a/propcache-0.4.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:296f4c8ed03ca7476813fe666c9ea97869a8d7aec972618671b33a38a5182ef4", size = 193241, upload-time = "2025-10-08T19:46:13.495Z" }, - { url = "https://files.pythonhosted.org/packages/d5/21/62949eb3a7a54afe8327011c90aca7e03547787a88fb8bd9726806482fea/propcache-0.4.1-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:1f0978529a418ebd1f49dad413a2b68af33f85d5c5ca5c6ca2a3bed375a7ac60", size = 190552, upload-time = "2025-10-08T19:46:14.938Z" }, - { url = "https://files.pythonhosted.org/packages/30/ee/ab4d727dd70806e5b4de96a798ae7ac6e4d42516f030ee60522474b6b332/propcache-0.4.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:fd138803047fb4c062b1c1dd95462f5209456bfab55c734458f15d11da288f8f", size = 200113, upload-time = "2025-10-08T19:46:16.695Z" }, - { url = "https://files.pythonhosted.org/packages/8a/0b/38b46208e6711b016aa8966a3ac793eee0d05c7159d8342aa27fc0bc365e/propcache-0.4.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:8c9b3cbe4584636d72ff556d9036e0c9317fa27b3ac1f0f558e7e84d1c9c5900", size = 200778, upload-time = "2025-10-08T19:46:18.023Z" }, - { url = "https://files.pythonhosted.org/packages/cf/81/5abec54355ed344476bee711e9f04815d4b00a311ab0535599204eecc257/propcache-0.4.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:f93243fdc5657247533273ac4f86ae106cc6445a0efacb9a1bfe982fcfefd90c", size = 193047, upload-time = "2025-10-08T19:46:19.449Z" }, - { url = "https://files.pythonhosted.org/packages/ec/b6/1f237c04e32063cb034acd5f6ef34ef3a394f75502e72703545631ab1ef6/propcache-0.4.1-cp310-cp310-win32.whl", hash = "sha256:a0ee98db9c5f80785b266eb805016e36058ac72c51a064040f2bc43b61101cdb", size = 38093, upload-time = "2025-10-08T19:46:20.643Z" }, - { url = "https://files.pythonhosted.org/packages/a6/67/354aac4e0603a15f76439caf0427781bcd6797f370377f75a642133bc954/propcache-0.4.1-cp310-cp310-win_amd64.whl", hash = "sha256:1cdb7988c4e5ac7f6d175a28a9aa0c94cb6f2ebe52756a3c0cda98d2809a9e37", size = 41638, upload-time = "2025-10-08T19:46:21.935Z" }, - { url = "https://files.pythonhosted.org/packages/e0/e1/74e55b9fd1a4c209ff1a9a824bf6c8b3d1fc5a1ac3eabe23462637466785/propcache-0.4.1-cp310-cp310-win_arm64.whl", hash = "sha256:d82ad62b19645419fe79dd63b3f9253e15b30e955c0170e5cebc350c1844e581", size = 38229, upload-time = "2025-10-08T19:46:23.368Z" }, - { url = "https://files.pythonhosted.org/packages/8c/d4/4e2c9aaf7ac2242b9358f98dccd8f90f2605402f5afeff6c578682c2c491/propcache-0.4.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:60a8fda9644b7dfd5dece8c61d8a85e271cb958075bfc4e01083c148b61a7caf", size = 80208, upload-time = "2025-10-08T19:46:24.597Z" }, - { url = "https://files.pythonhosted.org/packages/c2/21/d7b68e911f9c8e18e4ae43bdbc1e1e9bbd971f8866eb81608947b6f585ff/propcache-0.4.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:c30b53e7e6bda1d547cabb47c825f3843a0a1a42b0496087bb58d8fedf9f41b5", size = 45777, upload-time = "2025-10-08T19:46:25.733Z" }, - { url = "https://files.pythonhosted.org/packages/d3/1d/11605e99ac8ea9435651ee71ab4cb4bf03f0949586246476a25aadfec54a/propcache-0.4.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:6918ecbd897443087a3b7cd978d56546a812517dcaaca51b49526720571fa93e", size = 47647, upload-time = "2025-10-08T19:46:27.304Z" }, - { url = "https://files.pythonhosted.org/packages/58/1a/3c62c127a8466c9c843bccb503d40a273e5cc69838805f322e2826509e0d/propcache-0.4.1-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:3d902a36df4e5989763425a8ab9e98cd8ad5c52c823b34ee7ef307fd50582566", size = 214929, upload-time = "2025-10-08T19:46:28.62Z" }, - { url = "https://files.pythonhosted.org/packages/56/b9/8fa98f850960b367c4b8fe0592e7fc341daa7a9462e925228f10a60cf74f/propcache-0.4.1-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:a9695397f85973bb40427dedddf70d8dc4a44b22f1650dd4af9eedf443d45165", size = 221778, upload-time = "2025-10-08T19:46:30.358Z" }, - { url = "https://files.pythonhosted.org/packages/46/a6/0ab4f660eb59649d14b3d3d65c439421cf2f87fe5dd68591cbe3c1e78a89/propcache-0.4.1-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:2bb07ffd7eaad486576430c89f9b215f9e4be68c4866a96e97db9e97fead85dc", size = 228144, upload-time = "2025-10-08T19:46:32.607Z" }, - { url = "https://files.pythonhosted.org/packages/52/6a/57f43e054fb3d3a56ac9fc532bc684fc6169a26c75c353e65425b3e56eef/propcache-0.4.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:fd6f30fdcf9ae2a70abd34da54f18da086160e4d7d9251f81f3da0ff84fc5a48", size = 210030, upload-time = "2025-10-08T19:46:33.969Z" }, - { url = "https://files.pythonhosted.org/packages/40/e2/27e6feebb5f6b8408fa29f5efbb765cd54c153ac77314d27e457a3e993b7/propcache-0.4.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:fc38cba02d1acba4e2869eef1a57a43dfbd3d49a59bf90dda7444ec2be6a5570", size = 208252, upload-time = "2025-10-08T19:46:35.309Z" }, - { url = "https://files.pythonhosted.org/packages/9e/f8/91c27b22ccda1dbc7967f921c42825564fa5336a01ecd72eb78a9f4f53c2/propcache-0.4.1-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:67fad6162281e80e882fb3ec355398cf72864a54069d060321f6cd0ade95fe85", size = 202064, upload-time = "2025-10-08T19:46:36.993Z" }, - { url = "https://files.pythonhosted.org/packages/f2/26/7f00bd6bd1adba5aafe5f4a66390f243acab58eab24ff1a08bebb2ef9d40/propcache-0.4.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:f10207adf04d08bec185bae14d9606a1444715bc99180f9331c9c02093e1959e", size = 212429, upload-time = "2025-10-08T19:46:38.398Z" }, - { url = "https://files.pythonhosted.org/packages/84/89/fd108ba7815c1117ddca79c228f3f8a15fc82a73bca8b142eb5de13b2785/propcache-0.4.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:e9b0d8d0845bbc4cfcdcbcdbf5086886bc8157aa963c31c777ceff7846c77757", size = 216727, upload-time = "2025-10-08T19:46:39.732Z" }, - { url = "https://files.pythonhosted.org/packages/79/37/3ec3f7e3173e73f1d600495d8b545b53802cbf35506e5732dd8578db3724/propcache-0.4.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:981333cb2f4c1896a12f4ab92a9cc8f09ea664e9b7dbdc4eff74627af3a11c0f", size = 205097, upload-time = "2025-10-08T19:46:41.025Z" }, - { url = "https://files.pythonhosted.org/packages/61/b0/b2631c19793f869d35f47d5a3a56fb19e9160d3c119f15ac7344fc3ccae7/propcache-0.4.1-cp311-cp311-win32.whl", hash = "sha256:f1d2f90aeec838a52f1c1a32fe9a619fefd5e411721a9117fbf82aea638fe8a1", size = 38084, upload-time = "2025-10-08T19:46:42.693Z" }, - { url = "https://files.pythonhosted.org/packages/f4/78/6cce448e2098e9f3bfc91bb877f06aa24b6ccace872e39c53b2f707c4648/propcache-0.4.1-cp311-cp311-win_amd64.whl", hash = "sha256:364426a62660f3f699949ac8c621aad6977be7126c5807ce48c0aeb8e7333ea6", size = 41637, upload-time = "2025-10-08T19:46:43.778Z" }, - { url = "https://files.pythonhosted.org/packages/9c/e9/754f180cccd7f51a39913782c74717c581b9cc8177ad0e949f4d51812383/propcache-0.4.1-cp311-cp311-win_arm64.whl", hash = "sha256:e53f3a38d3510c11953f3e6a33f205c6d1b001129f972805ca9b42fc308bc239", size = 38064, upload-time = "2025-10-08T19:46:44.872Z" }, - { url = "https://files.pythonhosted.org/packages/a2/0f/f17b1b2b221d5ca28b4b876e8bb046ac40466513960646bda8e1853cdfa2/propcache-0.4.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:e153e9cd40cc8945138822807139367f256f89c6810c2634a4f6902b52d3b4e2", size = 80061, upload-time = "2025-10-08T19:46:46.075Z" }, - { url = "https://files.pythonhosted.org/packages/76/47/8ccf75935f51448ba9a16a71b783eb7ef6b9ee60f5d14c7f8a8a79fbeed7/propcache-0.4.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:cd547953428f7abb73c5ad82cbb32109566204260d98e41e5dfdc682eb7f8403", size = 46037, upload-time = "2025-10-08T19:46:47.23Z" }, - { url = "https://files.pythonhosted.org/packages/0a/b6/5c9a0e42df4d00bfb4a3cbbe5cf9f54260300c88a0e9af1f47ca5ce17ac0/propcache-0.4.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f048da1b4f243fc44f205dfd320933a951b8d89e0afd4c7cacc762a8b9165207", size = 47324, upload-time = "2025-10-08T19:46:48.384Z" }, - { url = "https://files.pythonhosted.org/packages/9e/d3/6c7ee328b39a81ee877c962469f1e795f9db87f925251efeb0545e0020d0/propcache-0.4.1-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:ec17c65562a827bba85e3872ead335f95405ea1674860d96483a02f5c698fa72", size = 225505, upload-time = "2025-10-08T19:46:50.055Z" }, - { url = "https://files.pythonhosted.org/packages/01/5d/1c53f4563490b1d06a684742cc6076ef944bc6457df6051b7d1a877c057b/propcache-0.4.1-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:405aac25c6394ef275dee4c709be43745d36674b223ba4eb7144bf4d691b7367", size = 230242, upload-time = "2025-10-08T19:46:51.815Z" }, - { url = "https://files.pythonhosted.org/packages/20/e1/ce4620633b0e2422207c3cb774a0ee61cac13abc6217763a7b9e2e3f4a12/propcache-0.4.1-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:0013cb6f8dde4b2a2f66903b8ba740bdfe378c943c4377a200551ceb27f379e4", size = 238474, upload-time = "2025-10-08T19:46:53.208Z" }, - { url = "https://files.pythonhosted.org/packages/46/4b/3aae6835b8e5f44ea6a68348ad90f78134047b503765087be2f9912140ea/propcache-0.4.1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:15932ab57837c3368b024473a525e25d316d8353016e7cc0e5ba9eb343fbb1cf", size = 221575, upload-time = "2025-10-08T19:46:54.511Z" }, - { url = "https://files.pythonhosted.org/packages/6e/a5/8a5e8678bcc9d3a1a15b9a29165640d64762d424a16af543f00629c87338/propcache-0.4.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:031dce78b9dc099f4c29785d9cf5577a3faf9ebf74ecbd3c856a7b92768c3df3", size = 216736, upload-time = "2025-10-08T19:46:56.212Z" }, - { url = "https://files.pythonhosted.org/packages/f1/63/b7b215eddeac83ca1c6b934f89d09a625aa9ee4ba158338854c87210cc36/propcache-0.4.1-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ab08df6c9a035bee56e31af99be621526bd237bea9f32def431c656b29e41778", size = 213019, upload-time = "2025-10-08T19:46:57.595Z" }, - { url = "https://files.pythonhosted.org/packages/57/74/f580099a58c8af587cac7ba19ee7cb418506342fbbe2d4a4401661cca886/propcache-0.4.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:4d7af63f9f93fe593afbf104c21b3b15868efb2c21d07d8732c0c4287e66b6a6", size = 220376, upload-time = "2025-10-08T19:46:59.067Z" }, - { url = "https://files.pythonhosted.org/packages/c4/ee/542f1313aff7eaf19c2bb758c5d0560d2683dac001a1c96d0774af799843/propcache-0.4.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:cfc27c945f422e8b5071b6e93169679e4eb5bf73bbcbf1ba3ae3a83d2f78ebd9", size = 226988, upload-time = "2025-10-08T19:47:00.544Z" }, - { url = "https://files.pythonhosted.org/packages/8f/18/9c6b015dd9c6930f6ce2229e1f02fb35298b847f2087ea2b436a5bfa7287/propcache-0.4.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:35c3277624a080cc6ec6f847cbbbb5b49affa3598c4535a0a4682a697aaa5c75", size = 215615, upload-time = "2025-10-08T19:47:01.968Z" }, - { url = "https://files.pythonhosted.org/packages/80/9e/e7b85720b98c45a45e1fca6a177024934dc9bc5f4d5dd04207f216fc33ed/propcache-0.4.1-cp312-cp312-win32.whl", hash = "sha256:671538c2262dadb5ba6395e26c1731e1d52534bfe9ae56d0b5573ce539266aa8", size = 38066, upload-time = "2025-10-08T19:47:03.503Z" }, - { url = "https://files.pythonhosted.org/packages/54/09/d19cff2a5aaac632ec8fc03737b223597b1e347416934c1b3a7df079784c/propcache-0.4.1-cp312-cp312-win_amd64.whl", hash = "sha256:cb2d222e72399fcf5890d1d5cc1060857b9b236adff2792ff48ca2dfd46c81db", size = 41655, upload-time = "2025-10-08T19:47:04.973Z" }, - { url = "https://files.pythonhosted.org/packages/68/ab/6b5c191bb5de08036a8c697b265d4ca76148efb10fa162f14af14fb5f076/propcache-0.4.1-cp312-cp312-win_arm64.whl", hash = "sha256:204483131fb222bdaaeeea9f9e6c6ed0cac32731f75dfc1d4a567fc1926477c1", size = 37789, upload-time = "2025-10-08T19:47:06.077Z" }, - { url = "https://files.pythonhosted.org/packages/bf/df/6d9c1b6ac12b003837dde8a10231a7344512186e87b36e855bef32241942/propcache-0.4.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:43eedf29202c08550aac1d14e0ee619b0430aaef78f85864c1a892294fbc28cf", size = 77750, upload-time = "2025-10-08T19:47:07.648Z" }, - { url = "https://files.pythonhosted.org/packages/8b/e8/677a0025e8a2acf07d3418a2e7ba529c9c33caf09d3c1f25513023c1db56/propcache-0.4.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:d62cdfcfd89ccb8de04e0eda998535c406bf5e060ffd56be6c586cbcc05b3311", size = 44780, upload-time = "2025-10-08T19:47:08.851Z" }, - { url = "https://files.pythonhosted.org/packages/89/a4/92380f7ca60f99ebae761936bc48a72a639e8a47b29050615eef757cb2a7/propcache-0.4.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:cae65ad55793da34db5f54e4029b89d3b9b9490d8abe1b4c7ab5d4b8ec7ebf74", size = 46308, upload-time = "2025-10-08T19:47:09.982Z" }, - { url = "https://files.pythonhosted.org/packages/2d/48/c5ac64dee5262044348d1d78a5f85dd1a57464a60d30daee946699963eb3/propcache-0.4.1-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:333ddb9031d2704a301ee3e506dc46b1fe5f294ec198ed6435ad5b6a085facfe", size = 208182, upload-time = "2025-10-08T19:47:11.319Z" }, - { url = "https://files.pythonhosted.org/packages/c6/0c/cd762dd011a9287389a6a3eb43aa30207bde253610cca06824aeabfe9653/propcache-0.4.1-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:fd0858c20f078a32cf55f7e81473d96dcf3b93fd2ccdb3d40fdf54b8573df3af", size = 211215, upload-time = "2025-10-08T19:47:13.146Z" }, - { url = "https://files.pythonhosted.org/packages/30/3e/49861e90233ba36890ae0ca4c660e95df565b2cd15d4a68556ab5865974e/propcache-0.4.1-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:678ae89ebc632c5c204c794f8dab2837c5f159aeb59e6ed0539500400577298c", size = 218112, upload-time = "2025-10-08T19:47:14.913Z" }, - { url = "https://files.pythonhosted.org/packages/f1/8b/544bc867e24e1bd48f3118cecd3b05c694e160a168478fa28770f22fd094/propcache-0.4.1-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d472aeb4fbf9865e0c6d622d7f4d54a4e101a89715d8904282bb5f9a2f476c3f", size = 204442, upload-time = "2025-10-08T19:47:16.277Z" }, - { url = "https://files.pythonhosted.org/packages/50/a6/4282772fd016a76d3e5c0df58380a5ea64900afd836cec2c2f662d1b9bb3/propcache-0.4.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:4d3df5fa7e36b3225954fba85589da77a0fe6a53e3976de39caf04a0db4c36f1", size = 199398, upload-time = "2025-10-08T19:47:17.962Z" }, - { url = "https://files.pythonhosted.org/packages/3e/ec/d8a7cd406ee1ddb705db2139f8a10a8a427100347bd698e7014351c7af09/propcache-0.4.1-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:ee17f18d2498f2673e432faaa71698032b0127ebf23ae5974eeaf806c279df24", size = 196920, upload-time = "2025-10-08T19:47:19.355Z" }, - { url = "https://files.pythonhosted.org/packages/f6/6c/f38ab64af3764f431e359f8baf9e0a21013e24329e8b85d2da32e8ed07ca/propcache-0.4.1-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:580e97762b950f993ae618e167e7be9256b8353c2dcd8b99ec100eb50f5286aa", size = 203748, upload-time = "2025-10-08T19:47:21.338Z" }, - { url = "https://files.pythonhosted.org/packages/d6/e3/fa846bd70f6534d647886621388f0a265254d30e3ce47e5c8e6e27dbf153/propcache-0.4.1-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:501d20b891688eb8e7aa903021f0b72d5a55db40ffaab27edefd1027caaafa61", size = 205877, upload-time = "2025-10-08T19:47:23.059Z" }, - { url = "https://files.pythonhosted.org/packages/e2/39/8163fc6f3133fea7b5f2827e8eba2029a0277ab2c5beee6c1db7b10fc23d/propcache-0.4.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:9a0bd56e5b100aef69bd8562b74b46254e7c8812918d3baa700c8a8009b0af66", size = 199437, upload-time = "2025-10-08T19:47:24.445Z" }, - { url = "https://files.pythonhosted.org/packages/93/89/caa9089970ca49c7c01662bd0eeedfe85494e863e8043565aeb6472ce8fe/propcache-0.4.1-cp313-cp313-win32.whl", hash = "sha256:bcc9aaa5d80322bc2fb24bb7accb4a30f81e90ab8d6ba187aec0744bc302ad81", size = 37586, upload-time = "2025-10-08T19:47:25.736Z" }, - { url = "https://files.pythonhosted.org/packages/f5/ab/f76ec3c3627c883215b5c8080debb4394ef5a7a29be811f786415fc1e6fd/propcache-0.4.1-cp313-cp313-win_amd64.whl", hash = "sha256:381914df18634f5494334d201e98245c0596067504b9372d8cf93f4bb23e025e", size = 40790, upload-time = "2025-10-08T19:47:26.847Z" }, - { url = "https://files.pythonhosted.org/packages/59/1b/e71ae98235f8e2ba5004d8cb19765a74877abf189bc53fc0c80d799e56c3/propcache-0.4.1-cp313-cp313-win_arm64.whl", hash = "sha256:8873eb4460fd55333ea49b7d189749ecf6e55bf85080f11b1c4530ed3034cba1", size = 37158, upload-time = "2025-10-08T19:47:27.961Z" }, - { url = "https://files.pythonhosted.org/packages/83/ce/a31bbdfc24ee0dcbba458c8175ed26089cf109a55bbe7b7640ed2470cfe9/propcache-0.4.1-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:92d1935ee1f8d7442da9c0c4fa7ac20d07e94064184811b685f5c4fada64553b", size = 81451, upload-time = "2025-10-08T19:47:29.445Z" }, - { url = "https://files.pythonhosted.org/packages/25/9c/442a45a470a68456e710d96cacd3573ef26a1d0a60067e6a7d5e655621ed/propcache-0.4.1-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:473c61b39e1460d386479b9b2f337da492042447c9b685f28be4f74d3529e566", size = 46374, upload-time = "2025-10-08T19:47:30.579Z" }, - { url = "https://files.pythonhosted.org/packages/f4/bf/b1d5e21dbc3b2e889ea4327044fb16312a736d97640fb8b6aa3f9c7b3b65/propcache-0.4.1-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:c0ef0aaafc66fbd87842a3fe3902fd889825646bc21149eafe47be6072725835", size = 48396, upload-time = "2025-10-08T19:47:31.79Z" }, - { url = "https://files.pythonhosted.org/packages/f4/04/5b4c54a103d480e978d3c8a76073502b18db0c4bc17ab91b3cb5092ad949/propcache-0.4.1-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f95393b4d66bfae908c3ca8d169d5f79cd65636ae15b5e7a4f6e67af675adb0e", size = 275950, upload-time = "2025-10-08T19:47:33.481Z" }, - { url = "https://files.pythonhosted.org/packages/b4/c1/86f846827fb969c4b78b0af79bba1d1ea2156492e1b83dea8b8a6ae27395/propcache-0.4.1-cp313-cp313t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:c07fda85708bc48578467e85099645167a955ba093be0a2dcba962195676e859", size = 273856, upload-time = "2025-10-08T19:47:34.906Z" }, - { url = "https://files.pythonhosted.org/packages/36/1d/fc272a63c8d3bbad6878c336c7a7dea15e8f2d23a544bda43205dfa83ada/propcache-0.4.1-cp313-cp313t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:af223b406d6d000830c6f65f1e6431783fc3f713ba3e6cc8c024d5ee96170a4b", size = 280420, upload-time = "2025-10-08T19:47:36.338Z" }, - { url = "https://files.pythonhosted.org/packages/07/0c/01f2219d39f7e53d52e5173bcb09c976609ba30209912a0680adfb8c593a/propcache-0.4.1-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a78372c932c90ee474559c5ddfffd718238e8673c340dc21fe45c5b8b54559a0", size = 263254, upload-time = "2025-10-08T19:47:37.692Z" }, - { url = "https://files.pythonhosted.org/packages/2d/18/cd28081658ce597898f0c4d174d4d0f3c5b6d4dc27ffafeef835c95eb359/propcache-0.4.1-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:564d9f0d4d9509e1a870c920a89b2fec951b44bf5ba7d537a9e7c1ccec2c18af", size = 261205, upload-time = "2025-10-08T19:47:39.659Z" }, - { url = "https://files.pythonhosted.org/packages/7a/71/1f9e22eb8b8316701c2a19fa1f388c8a3185082607da8e406a803c9b954e/propcache-0.4.1-cp313-cp313t-musllinux_1_2_armv7l.whl", hash = "sha256:17612831fda0138059cc5546f4d12a2aacfb9e47068c06af35c400ba58ba7393", size = 247873, upload-time = "2025-10-08T19:47:41.084Z" }, - { url = "https://files.pythonhosted.org/packages/4a/65/3d4b61f36af2b4eddba9def857959f1016a51066b4f1ce348e0cf7881f58/propcache-0.4.1-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:41a89040cb10bd345b3c1a873b2bf36413d48da1def52f268a055f7398514874", size = 262739, upload-time = "2025-10-08T19:47:42.51Z" }, - { url = "https://files.pythonhosted.org/packages/2a/42/26746ab087faa77c1c68079b228810436ccd9a5ce9ac85e2b7307195fd06/propcache-0.4.1-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:e35b88984e7fa64aacecea39236cee32dd9bd8c55f57ba8a75cf2399553f9bd7", size = 263514, upload-time = "2025-10-08T19:47:43.927Z" }, - { url = "https://files.pythonhosted.org/packages/94/13/630690fe201f5502d2403dd3cfd451ed8858fe3c738ee88d095ad2ff407b/propcache-0.4.1-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:6f8b465489f927b0df505cbe26ffbeed4d6d8a2bbc61ce90eb074ff129ef0ab1", size = 257781, upload-time = "2025-10-08T19:47:45.448Z" }, - { url = "https://files.pythonhosted.org/packages/92/f7/1d4ec5841505f423469efbfc381d64b7b467438cd5a4bbcbb063f3b73d27/propcache-0.4.1-cp313-cp313t-win32.whl", hash = "sha256:2ad890caa1d928c7c2965b48f3a3815c853180831d0e5503d35cf00c472f4717", size = 41396, upload-time = "2025-10-08T19:47:47.202Z" }, - { url = "https://files.pythonhosted.org/packages/48/f0/615c30622316496d2cbbc29f5985f7777d3ada70f23370608c1d3e081c1f/propcache-0.4.1-cp313-cp313t-win_amd64.whl", hash = "sha256:f7ee0e597f495cf415bcbd3da3caa3bd7e816b74d0d52b8145954c5e6fd3ff37", size = 44897, upload-time = "2025-10-08T19:47:48.336Z" }, - { url = "https://files.pythonhosted.org/packages/fd/ca/6002e46eccbe0e33dcd4069ef32f7f1c9e243736e07adca37ae8c4830ec3/propcache-0.4.1-cp313-cp313t-win_arm64.whl", hash = "sha256:929d7cbe1f01bb7baffb33dc14eb5691c95831450a26354cd210a8155170c93a", size = 39789, upload-time = "2025-10-08T19:47:49.876Z" }, - { url = "https://files.pythonhosted.org/packages/8e/5c/bca52d654a896f831b8256683457ceddd490ec18d9ec50e97dfd8fc726a8/propcache-0.4.1-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:3f7124c9d820ba5548d431afb4632301acf965db49e666aa21c305cbe8c6de12", size = 78152, upload-time = "2025-10-08T19:47:51.051Z" }, - { url = "https://files.pythonhosted.org/packages/65/9b/03b04e7d82a5f54fb16113d839f5ea1ede58a61e90edf515f6577c66fa8f/propcache-0.4.1-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:c0d4b719b7da33599dfe3b22d3db1ef789210a0597bc650b7cee9c77c2be8c5c", size = 44869, upload-time = "2025-10-08T19:47:52.594Z" }, - { url = "https://files.pythonhosted.org/packages/b2/fa/89a8ef0468d5833a23fff277b143d0573897cf75bd56670a6d28126c7d68/propcache-0.4.1-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:9f302f4783709a78240ebc311b793f123328716a60911d667e0c036bc5dcbded", size = 46596, upload-time = "2025-10-08T19:47:54.073Z" }, - { url = "https://files.pythonhosted.org/packages/86/bd/47816020d337f4a746edc42fe8d53669965138f39ee117414c7d7a340cfe/propcache-0.4.1-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c80ee5802e3fb9ea37938e7eecc307fb984837091d5fd262bb37238b1ae97641", size = 206981, upload-time = "2025-10-08T19:47:55.715Z" }, - { url = "https://files.pythonhosted.org/packages/df/f6/c5fa1357cc9748510ee55f37173eb31bfde6d94e98ccd9e6f033f2fc06e1/propcache-0.4.1-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:ed5a841e8bb29a55fb8159ed526b26adc5bdd7e8bd7bf793ce647cb08656cdf4", size = 211490, upload-time = "2025-10-08T19:47:57.499Z" }, - { url = "https://files.pythonhosted.org/packages/80/1e/e5889652a7c4a3846683401a48f0f2e5083ce0ec1a8a5221d8058fbd1adf/propcache-0.4.1-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:55c72fd6ea2da4c318e74ffdf93c4fe4e926051133657459131a95c846d16d44", size = 215371, upload-time = "2025-10-08T19:47:59.317Z" }, - { url = "https://files.pythonhosted.org/packages/b2/f2/889ad4b2408f72fe1a4f6a19491177b30ea7bf1a0fd5f17050ca08cfc882/propcache-0.4.1-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:8326e144341460402713f91df60ade3c999d601e7eb5ff8f6f7862d54de0610d", size = 201424, upload-time = "2025-10-08T19:48:00.67Z" }, - { url = "https://files.pythonhosted.org/packages/27/73/033d63069b57b0812c8bd19f311faebeceb6ba31b8f32b73432d12a0b826/propcache-0.4.1-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:060b16ae65bc098da7f6d25bf359f1f31f688384858204fe5d652979e0015e5b", size = 197566, upload-time = "2025-10-08T19:48:02.604Z" }, - { url = "https://files.pythonhosted.org/packages/dc/89/ce24f3dc182630b4e07aa6d15f0ff4b14ed4b9955fae95a0b54c58d66c05/propcache-0.4.1-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:89eb3fa9524f7bec9de6e83cf3faed9d79bffa560672c118a96a171a6f55831e", size = 193130, upload-time = "2025-10-08T19:48:04.499Z" }, - { url = "https://files.pythonhosted.org/packages/a9/24/ef0d5fd1a811fb5c609278d0209c9f10c35f20581fcc16f818da959fc5b4/propcache-0.4.1-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:dee69d7015dc235f526fe80a9c90d65eb0039103fe565776250881731f06349f", size = 202625, upload-time = "2025-10-08T19:48:06.213Z" }, - { url = "https://files.pythonhosted.org/packages/f5/02/98ec20ff5546f68d673df2f7a69e8c0d076b5abd05ca882dc7ee3a83653d/propcache-0.4.1-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:5558992a00dfd54ccbc64a32726a3357ec93825a418a401f5cc67df0ac5d9e49", size = 204209, upload-time = "2025-10-08T19:48:08.432Z" }, - { url = "https://files.pythonhosted.org/packages/a0/87/492694f76759b15f0467a2a93ab68d32859672b646aa8a04ce4864e7932d/propcache-0.4.1-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:c9b822a577f560fbd9554812526831712c1436d2c046cedee4c3796d3543b144", size = 197797, upload-time = "2025-10-08T19:48:09.968Z" }, - { url = "https://files.pythonhosted.org/packages/ee/36/66367de3575db1d2d3f3d177432bd14ee577a39d3f5d1b3d5df8afe3b6e2/propcache-0.4.1-cp314-cp314-win32.whl", hash = "sha256:ab4c29b49d560fe48b696cdcb127dd36e0bc2472548f3bf56cc5cb3da2b2984f", size = 38140, upload-time = "2025-10-08T19:48:11.232Z" }, - { url = "https://files.pythonhosted.org/packages/0c/2a/a758b47de253636e1b8aef181c0b4f4f204bf0dd964914fb2af90a95b49b/propcache-0.4.1-cp314-cp314-win_amd64.whl", hash = "sha256:5a103c3eb905fcea0ab98be99c3a9a5ab2de60228aa5aceedc614c0281cf6153", size = 41257, upload-time = "2025-10-08T19:48:12.707Z" }, - { url = "https://files.pythonhosted.org/packages/34/5e/63bd5896c3fec12edcbd6f12508d4890d23c265df28c74b175e1ef9f4f3b/propcache-0.4.1-cp314-cp314-win_arm64.whl", hash = "sha256:74c1fb26515153e482e00177a1ad654721bf9207da8a494a0c05e797ad27b992", size = 38097, upload-time = "2025-10-08T19:48:13.923Z" }, - { url = "https://files.pythonhosted.org/packages/99/85/9ff785d787ccf9bbb3f3106f79884a130951436f58392000231b4c737c80/propcache-0.4.1-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:824e908bce90fb2743bd6b59db36eb4f45cd350a39637c9f73b1c1ea66f5b75f", size = 81455, upload-time = "2025-10-08T19:48:15.16Z" }, - { url = "https://files.pythonhosted.org/packages/90/85/2431c10c8e7ddb1445c1f7c4b54d886e8ad20e3c6307e7218f05922cad67/propcache-0.4.1-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:c2b5e7db5328427c57c8e8831abda175421b709672f6cfc3d630c3b7e2146393", size = 46372, upload-time = "2025-10-08T19:48:16.424Z" }, - { url = "https://files.pythonhosted.org/packages/01/20/b0972d902472da9bcb683fa595099911f4d2e86e5683bcc45de60dd05dc3/propcache-0.4.1-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:6f6ff873ed40292cd4969ef5310179afd5db59fdf055897e282485043fc80ad0", size = 48411, upload-time = "2025-10-08T19:48:17.577Z" }, - { url = "https://files.pythonhosted.org/packages/e2/e3/7dc89f4f21e8f99bad3d5ddb3a3389afcf9da4ac69e3deb2dcdc96e74169/propcache-0.4.1-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:49a2dc67c154db2c1463013594c458881a069fcf98940e61a0569016a583020a", size = 275712, upload-time = "2025-10-08T19:48:18.901Z" }, - { url = "https://files.pythonhosted.org/packages/20/67/89800c8352489b21a8047c773067644e3897f02ecbbd610f4d46b7f08612/propcache-0.4.1-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:005f08e6a0529984491e37d8dbc3dd86f84bd78a8ceb5fa9a021f4c48d4984be", size = 273557, upload-time = "2025-10-08T19:48:20.762Z" }, - { url = "https://files.pythonhosted.org/packages/e2/a1/b52b055c766a54ce6d9c16d9aca0cad8059acd9637cdf8aa0222f4a026ef/propcache-0.4.1-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:5c3310452e0d31390da9035c348633b43d7e7feb2e37be252be6da45abd1abcc", size = 280015, upload-time = "2025-10-08T19:48:22.592Z" }, - { url = "https://files.pythonhosted.org/packages/48/c8/33cee30bd890672c63743049f3c9e4be087e6780906bfc3ec58528be59c1/propcache-0.4.1-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4c3c70630930447f9ef1caac7728c8ad1c56bc5015338b20fed0d08ea2480b3a", size = 262880, upload-time = "2025-10-08T19:48:23.947Z" }, - { url = "https://files.pythonhosted.org/packages/0c/b1/8f08a143b204b418285c88b83d00edbd61afbc2c6415ffafc8905da7038b/propcache-0.4.1-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:8e57061305815dfc910a3634dcf584f08168a8836e6999983569f51a8544cd89", size = 260938, upload-time = "2025-10-08T19:48:25.656Z" }, - { url = "https://files.pythonhosted.org/packages/cf/12/96e4664c82ca2f31e1c8dff86afb867348979eb78d3cb8546a680287a1e9/propcache-0.4.1-cp314-cp314t-musllinux_1_2_armv7l.whl", hash = "sha256:521a463429ef54143092c11a77e04056dd00636f72e8c45b70aaa3140d639726", size = 247641, upload-time = "2025-10-08T19:48:27.207Z" }, - { url = "https://files.pythonhosted.org/packages/18/ed/e7a9cfca28133386ba52278136d42209d3125db08d0a6395f0cba0c0285c/propcache-0.4.1-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:120c964da3fdc75e3731aa392527136d4ad35868cc556fd09bb6d09172d9a367", size = 262510, upload-time = "2025-10-08T19:48:28.65Z" }, - { url = "https://files.pythonhosted.org/packages/f5/76/16d8bf65e8845dd62b4e2b57444ab81f07f40caa5652b8969b87ddcf2ef6/propcache-0.4.1-cp314-cp314t-musllinux_1_2_s390x.whl", hash = "sha256:d8f353eb14ee3441ee844ade4277d560cdd68288838673273b978e3d6d2c8f36", size = 263161, upload-time = "2025-10-08T19:48:30.133Z" }, - { url = "https://files.pythonhosted.org/packages/e7/70/c99e9edb5d91d5ad8a49fa3c1e8285ba64f1476782fed10ab251ff413ba1/propcache-0.4.1-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:ab2943be7c652f09638800905ee1bab2c544e537edb57d527997a24c13dc1455", size = 257393, upload-time = "2025-10-08T19:48:31.567Z" }, - { url = "https://files.pythonhosted.org/packages/08/02/87b25304249a35c0915d236575bc3574a323f60b47939a2262b77632a3ee/propcache-0.4.1-cp314-cp314t-win32.whl", hash = "sha256:05674a162469f31358c30bcaa8883cb7829fa3110bf9c0991fe27d7896c42d85", size = 42546, upload-time = "2025-10-08T19:48:32.872Z" }, - { url = "https://files.pythonhosted.org/packages/cb/ef/3c6ecf8b317aa982f309835e8f96987466123c6e596646d4e6a1dfcd080f/propcache-0.4.1-cp314-cp314t-win_amd64.whl", hash = "sha256:990f6b3e2a27d683cb7602ed6c86f15ee6b43b1194736f9baaeb93d0016633b1", size = 46259, upload-time = "2025-10-08T19:48:34.226Z" }, - { url = "https://files.pythonhosted.org/packages/c4/2d/346e946d4951f37eca1e4f55be0f0174c52cd70720f84029b02f296f4a38/propcache-0.4.1-cp314-cp314t-win_arm64.whl", hash = "sha256:ecef2343af4cc68e05131e45024ba34f6095821988a9d0a02aa7c73fcc448aa9", size = 40428, upload-time = "2025-10-08T19:48:35.441Z" }, - { url = "https://files.pythonhosted.org/packages/5b/5a/bc7b4a4ef808fa59a816c17b20c4bef6884daebbdf627ff2a161da67da19/propcache-0.4.1-py3-none-any.whl", hash = "sha256:af2a6052aeb6cf17d3e46ee169099044fd8224cbaf75c76a2ef596e8163e2237", size = 13305, upload-time = "2025-10-08T19:49:00.792Z" }, -] - -[[package]] -name = "proto-plus" -version = "1.26.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "protobuf" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/f4/ac/87285f15f7cce6d4a008f33f1757fb5a13611ea8914eb58c3d0d26243468/proto_plus-1.26.1.tar.gz", hash = "sha256:21a515a4c4c0088a773899e23c7bbade3d18f9c66c73edd4c7ee3816bc96a012", size = 56142, upload-time = "2025-03-10T15:54:38.843Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/4e/6d/280c4c2ce28b1593a19ad5239c8b826871fc6ec275c21afc8e1820108039/proto_plus-1.26.1-py3-none-any.whl", hash = "sha256:13285478c2dcf2abb829db158e1047e2f1e8d63a077d94263c2b88b043c75a66", size = 50163, upload-time = "2025-03-10T15:54:37.335Z" }, -] - -[[package]] -name = "protobuf" -version = "6.33.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/19/ff/64a6c8f420818bb873713988ca5492cba3a7946be57e027ac63495157d97/protobuf-6.33.0.tar.gz", hash = "sha256:140303d5c8d2037730c548f8c7b93b20bb1dc301be280c378b82b8894589c954", size = 443463, upload-time = "2025-10-15T20:39:52.159Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7e/ee/52b3fa8feb6db4a833dfea4943e175ce645144532e8a90f72571ad85df4e/protobuf-6.33.0-cp310-abi3-win32.whl", hash = "sha256:d6101ded078042a8f17959eccd9236fb7a9ca20d3b0098bbcb91533a5680d035", size = 425593, upload-time = "2025-10-15T20:39:40.29Z" }, - { url = "https://files.pythonhosted.org/packages/7b/c6/7a465f1825872c55e0341ff4a80198743f73b69ce5d43ab18043699d1d81/protobuf-6.33.0-cp310-abi3-win_amd64.whl", hash = "sha256:9a031d10f703f03768f2743a1c403af050b6ae1f3480e9c140f39c45f81b13ee", size = 436882, upload-time = "2025-10-15T20:39:42.841Z" }, - { url = "https://files.pythonhosted.org/packages/e1/a9/b6eee662a6951b9c3640e8e452ab3e09f117d99fc10baa32d1581a0d4099/protobuf-6.33.0-cp39-abi3-macosx_10_9_universal2.whl", hash = "sha256:905b07a65f1a4b72412314082c7dbfae91a9e8b68a0cc1577515f8df58ecf455", size = 427521, upload-time = "2025-10-15T20:39:43.803Z" }, - { url = "https://files.pythonhosted.org/packages/10/35/16d31e0f92c6d2f0e77c2a3ba93185130ea13053dd16200a57434c882f2b/protobuf-6.33.0-cp39-abi3-manylinux2014_aarch64.whl", hash = "sha256:e0697ece353e6239b90ee43a9231318302ad8353c70e6e45499fa52396debf90", size = 324445, upload-time = "2025-10-15T20:39:44.932Z" }, - { url = "https://files.pythonhosted.org/packages/e6/eb/2a981a13e35cda8b75b5585aaffae2eb904f8f351bdd3870769692acbd8a/protobuf-6.33.0-cp39-abi3-manylinux2014_s390x.whl", hash = "sha256:e0a1715e4f27355afd9570f3ea369735afc853a6c3951a6afe1f80d8569ad298", size = 339159, upload-time = "2025-10-15T20:39:46.186Z" }, - { url = "https://files.pythonhosted.org/packages/21/51/0b1cbad62074439b867b4e04cc09b93f6699d78fd191bed2bbb44562e077/protobuf-6.33.0-cp39-abi3-manylinux2014_x86_64.whl", hash = "sha256:35be49fd3f4fefa4e6e2aacc35e8b837d6703c37a2168a55ac21e9b1bc7559ef", size = 323172, upload-time = "2025-10-15T20:39:47.465Z" }, - { url = "https://files.pythonhosted.org/packages/07/d1/0a28c21707807c6aacd5dc9c3704b2aa1effbf37adebd8caeaf68b17a636/protobuf-6.33.0-py3-none-any.whl", hash = "sha256:25c9e1963c6734448ea2d308cfa610e692b801304ba0908d7bfa564ac5132995", size = 170477, upload-time = "2025-10-15T20:39:51.311Z" }, -] - -[[package]] -name = "pyasn1" -version = "0.6.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ba/e9/01f1a64245b89f039897cb0130016d79f77d52669aae6ee7b159a6c4c018/pyasn1-0.6.1.tar.gz", hash = "sha256:6f580d2bdd84365380830acf45550f2511469f673cb4a5ae3857a3170128b034", size = 145322, upload-time = "2024-09-10T22:41:42.55Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/c8/f1/d6a797abb14f6283c0ddff96bbdd46937f64122b8c925cab503dd37f8214/pyasn1-0.6.1-py3-none-any.whl", hash = "sha256:0d632f46f2ba09143da3a8afe9e33fb6f92fa2320ab7e886e2d0f7672af84629", size = 83135, upload-time = "2024-09-11T16:00:36.122Z" }, -] - -[[package]] -name = "pyasn1-modules" -version = "0.4.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "pyasn1" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/e9/e6/78ebbb10a8c8e4b61a59249394a4a594c1a7af95593dc933a349c8d00964/pyasn1_modules-0.4.2.tar.gz", hash = "sha256:677091de870a80aae844b1ca6134f54652fa2c8c5a52aa396440ac3106e941e6", size = 307892, upload-time = "2025-03-28T02:41:22.17Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/47/8d/d529b5d697919ba8c11ad626e835d4039be708a35b0d22de83a269a6682c/pyasn1_modules-0.4.2-py3-none-any.whl", hash = "sha256:29253a9207ce32b64c3ac6600edc75368f98473906e8fd1043bd6b5b1de2c14a", size = 181259, upload-time = "2025-03-28T02:41:19.028Z" }, -] - -[[package]] -name = "pycparser" -version = "2.23" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/fe/cf/d2d3b9f5699fb1e4615c8e32ff220203e43b248e1dfcc6736ad9057731ca/pycparser-2.23.tar.gz", hash = "sha256:78816d4f24add8f10a06d6f05b4d424ad9e96cfebf68a4ddc99c65c0720d00c2", size = 173734, upload-time = "2025-09-09T13:23:47.91Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a0/e3/59cd50310fc9b59512193629e1984c1f95e5c8ae6e5d8c69532ccc65a7fe/pycparser-2.23-py3-none-any.whl", hash = "sha256:e5c6e8d3fbad53479cab09ac03729e0a9faf2bee3db8208a550daf5af81a5934", size = 118140, upload-time = "2025-09-09T13:23:46.651Z" }, -] - -[[package]] -name = "pydantic" -version = "2.12.3" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "annotated-types" }, - { name = "pydantic-core" }, - { name = "typing-extensions" }, - { name = "typing-inspection" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/f3/1e/4f0a3233767010308f2fd6bd0814597e3f63f1dc98304a9112b8759df4ff/pydantic-2.12.3.tar.gz", hash = "sha256:1da1c82b0fc140bb0103bc1441ffe062154c8d38491189751ee00fd8ca65ce74", size = 819383, upload-time = "2025-10-17T15:04:21.222Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a1/6b/83661fa77dcefa195ad5f8cd9af3d1a7450fd57cc883ad04d65446ac2029/pydantic-2.12.3-py3-none-any.whl", hash = "sha256:6986454a854bc3bc6e5443e1369e06a3a456af9d339eda45510f517d9ea5c6bf", size = 462431, upload-time = "2025-10-17T15:04:19.346Z" }, -] - -[[package]] -name = "pydantic-core" -version = "2.41.4" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/df/18/d0944e8eaaa3efd0a91b0f1fc537d3be55ad35091b6a87638211ba691964/pydantic_core-2.41.4.tar.gz", hash = "sha256:70e47929a9d4a1905a67e4b687d5946026390568a8e952b92824118063cee4d5", size = 457557, upload-time = "2025-10-14T10:23:47.909Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a7/3d/9b8ca77b0f76fcdbf8bc6b72474e264283f461284ca84ac3fde570c6c49a/pydantic_core-2.41.4-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:2442d9a4d38f3411f22eb9dd0912b7cbf4b7d5b6c92c4173b75d3e1ccd84e36e", size = 2111197, upload-time = "2025-10-14T10:19:43.303Z" }, - { url = "https://files.pythonhosted.org/packages/59/92/b7b0fe6ed4781642232755cb7e56a86e2041e1292f16d9ae410a0ccee5ac/pydantic_core-2.41.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:30a9876226dda131a741afeab2702e2d127209bde3c65a2b8133f428bc5d006b", size = 1917909, upload-time = "2025-10-14T10:19:45.194Z" }, - { url = "https://files.pythonhosted.org/packages/52/8c/3eb872009274ffa4fb6a9585114e161aa1a0915af2896e2d441642929fe4/pydantic_core-2.41.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d55bbac04711e2980645af68b97d445cdbcce70e5216de444a6c4b6943ebcccd", size = 1969905, upload-time = "2025-10-14T10:19:46.567Z" }, - { url = "https://files.pythonhosted.org/packages/f4/21/35adf4a753bcfaea22d925214a0c5b880792e3244731b3f3e6fec0d124f7/pydantic_core-2.41.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e1d778fb7849a42d0ee5927ab0f7453bf9f85eef8887a546ec87db5ddb178945", size = 2051938, upload-time = "2025-10-14T10:19:48.237Z" }, - { url = "https://files.pythonhosted.org/packages/7d/d0/cdf7d126825e36d6e3f1eccf257da8954452934ede275a8f390eac775e89/pydantic_core-2.41.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1b65077a4693a98b90ec5ad8f203ad65802a1b9b6d4a7e48066925a7e1606706", size = 2250710, upload-time = "2025-10-14T10:19:49.619Z" }, - { url = "https://files.pythonhosted.org/packages/2e/1c/af1e6fd5ea596327308f9c8d1654e1285cc3d8de0d584a3c9d7705bf8a7c/pydantic_core-2.41.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:62637c769dee16eddb7686bf421be48dfc2fae93832c25e25bc7242e698361ba", size = 2367445, upload-time = "2025-10-14T10:19:51.269Z" }, - { url = "https://files.pythonhosted.org/packages/d3/81/8cece29a6ef1b3a92f956ea6da6250d5b2d2e7e4d513dd3b4f0c7a83dfea/pydantic_core-2.41.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2dfe3aa529c8f501babf6e502936b9e8d4698502b2cfab41e17a028d91b1ac7b", size = 2072875, upload-time = "2025-10-14T10:19:52.671Z" }, - { url = "https://files.pythonhosted.org/packages/e3/37/a6a579f5fc2cd4d5521284a0ab6a426cc6463a7b3897aeb95b12f1ba607b/pydantic_core-2.41.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ca2322da745bf2eeb581fc9ea3bbb31147702163ccbcbf12a3bb630e4bf05e1d", size = 2191329, upload-time = "2025-10-14T10:19:54.214Z" }, - { url = "https://files.pythonhosted.org/packages/ae/03/505020dc5c54ec75ecba9f41119fd1e48f9e41e4629942494c4a8734ded1/pydantic_core-2.41.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e8cd3577c796be7231dcf80badcf2e0835a46665eaafd8ace124d886bab4d700", size = 2151658, upload-time = "2025-10-14T10:19:55.843Z" }, - { url = "https://files.pythonhosted.org/packages/cb/5d/2c0d09fb53aa03bbd2a214d89ebfa6304be7df9ed86ee3dc7770257f41ee/pydantic_core-2.41.4-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:1cae8851e174c83633f0833e90636832857297900133705ee158cf79d40f03e6", size = 2316777, upload-time = "2025-10-14T10:19:57.607Z" }, - { url = "https://files.pythonhosted.org/packages/ea/4b/c2c9c8f5e1f9c864b57d08539d9d3db160e00491c9f5ee90e1bfd905e644/pydantic_core-2.41.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:a26d950449aae348afe1ac8be5525a00ae4235309b729ad4d3399623125b43c9", size = 2320705, upload-time = "2025-10-14T10:19:59.016Z" }, - { url = "https://files.pythonhosted.org/packages/28/c3/a74c1c37f49c0a02c89c7340fafc0ba816b29bd495d1a31ce1bdeacc6085/pydantic_core-2.41.4-cp310-cp310-win32.whl", hash = "sha256:0cf2a1f599efe57fa0051312774280ee0f650e11152325e41dfd3018ef2c1b57", size = 1975464, upload-time = "2025-10-14T10:20:00.581Z" }, - { url = "https://files.pythonhosted.org/packages/d6/23/5dd5c1324ba80303368f7569e2e2e1a721c7d9eb16acb7eb7b7f85cb1be2/pydantic_core-2.41.4-cp310-cp310-win_amd64.whl", hash = "sha256:a8c2e340d7e454dc3340d3d2e8f23558ebe78c98aa8f68851b04dcb7bc37abdc", size = 2024497, upload-time = "2025-10-14T10:20:03.018Z" }, - { url = "https://files.pythonhosted.org/packages/62/4c/f6cbfa1e8efacd00b846764e8484fe173d25b8dab881e277a619177f3384/pydantic_core-2.41.4-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:28ff11666443a1a8cf2a044d6a545ebffa8382b5f7973f22c36109205e65dc80", size = 2109062, upload-time = "2025-10-14T10:20:04.486Z" }, - { url = "https://files.pythonhosted.org/packages/21/f8/40b72d3868896bfcd410e1bd7e516e762d326201c48e5b4a06446f6cf9e8/pydantic_core-2.41.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:61760c3925d4633290292bad462e0f737b840508b4f722247d8729684f6539ae", size = 1916301, upload-time = "2025-10-14T10:20:06.857Z" }, - { url = "https://files.pythonhosted.org/packages/94/4d/d203dce8bee7faeca791671c88519969d98d3b4e8f225da5b96dad226fc8/pydantic_core-2.41.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:eae547b7315d055b0de2ec3965643b0ab82ad0106a7ffd29615ee9f266a02827", size = 1968728, upload-time = "2025-10-14T10:20:08.353Z" }, - { url = "https://files.pythonhosted.org/packages/65/f5/6a66187775df87c24d526985b3a5d78d861580ca466fbd9d4d0e792fcf6c/pydantic_core-2.41.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ef9ee5471edd58d1fcce1c80ffc8783a650e3e3a193fe90d52e43bb4d87bff1f", size = 2050238, upload-time = "2025-10-14T10:20:09.766Z" }, - { url = "https://files.pythonhosted.org/packages/5e/b9/78336345de97298cf53236b2f271912ce11f32c1e59de25a374ce12f9cce/pydantic_core-2.41.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:15dd504af121caaf2c95cb90c0ebf71603c53de98305621b94da0f967e572def", size = 2249424, upload-time = "2025-10-14T10:20:11.732Z" }, - { url = "https://files.pythonhosted.org/packages/99/bb/a4584888b70ee594c3d374a71af5075a68654d6c780369df269118af7402/pydantic_core-2.41.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3a926768ea49a8af4d36abd6a8968b8790f7f76dd7cbd5a4c180db2b4ac9a3a2", size = 2366047, upload-time = "2025-10-14T10:20:13.647Z" }, - { url = "https://files.pythonhosted.org/packages/5f/8d/17fc5de9d6418e4d2ae8c675f905cdafdc59d3bf3bf9c946b7ab796a992a/pydantic_core-2.41.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6916b9b7d134bff5440098a4deb80e4cb623e68974a87883299de9124126c2a8", size = 2071163, upload-time = "2025-10-14T10:20:15.307Z" }, - { url = "https://files.pythonhosted.org/packages/54/e7/03d2c5c0b8ed37a4617430db68ec5e7dbba66358b629cd69e11b4d564367/pydantic_core-2.41.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:5cf90535979089df02e6f17ffd076f07237efa55b7343d98760bde8743c4b265", size = 2190585, upload-time = "2025-10-14T10:20:17.3Z" }, - { url = "https://files.pythonhosted.org/packages/be/fc/15d1c9fe5ad9266a5897d9b932b7f53d7e5cfc800573917a2c5d6eea56ec/pydantic_core-2.41.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:7533c76fa647fade2d7ec75ac5cc079ab3f34879626dae5689b27790a6cf5a5c", size = 2150109, upload-time = "2025-10-14T10:20:19.143Z" }, - { url = "https://files.pythonhosted.org/packages/26/ef/e735dd008808226c83ba56972566138665b71477ad580fa5a21f0851df48/pydantic_core-2.41.4-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:37e516bca9264cbf29612539801ca3cd5d1be465f940417b002905e6ed79d38a", size = 2315078, upload-time = "2025-10-14T10:20:20.742Z" }, - { url = "https://files.pythonhosted.org/packages/90/00/806efdcf35ff2ac0f938362350cd9827b8afb116cc814b6b75cf23738c7c/pydantic_core-2.41.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:0c19cb355224037c83642429b8ce261ae108e1c5fbf5c028bac63c77b0f8646e", size = 2318737, upload-time = "2025-10-14T10:20:22.306Z" }, - { url = "https://files.pythonhosted.org/packages/41/7e/6ac90673fe6cb36621a2283552897838c020db343fa86e513d3f563b196f/pydantic_core-2.41.4-cp311-cp311-win32.whl", hash = "sha256:09c2a60e55b357284b5f31f5ab275ba9f7f70b7525e18a132ec1f9160b4f1f03", size = 1974160, upload-time = "2025-10-14T10:20:23.817Z" }, - { url = "https://files.pythonhosted.org/packages/e0/9d/7c5e24ee585c1f8b6356e1d11d40ab807ffde44d2db3b7dfd6d20b09720e/pydantic_core-2.41.4-cp311-cp311-win_amd64.whl", hash = "sha256:711156b6afb5cb1cb7c14a2cc2c4a8b4c717b69046f13c6b332d8a0a8f41ca3e", size = 2021883, upload-time = "2025-10-14T10:20:25.48Z" }, - { url = "https://files.pythonhosted.org/packages/33/90/5c172357460fc28b2871eb4a0fb3843b136b429c6fa827e4b588877bf115/pydantic_core-2.41.4-cp311-cp311-win_arm64.whl", hash = "sha256:6cb9cf7e761f4f8a8589a45e49ed3c0d92d1d696a45a6feaee8c904b26efc2db", size = 1968026, upload-time = "2025-10-14T10:20:27.039Z" }, - { url = "https://files.pythonhosted.org/packages/e9/81/d3b3e95929c4369d30b2a66a91db63c8ed0a98381ae55a45da2cd1cc1288/pydantic_core-2.41.4-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:ab06d77e053d660a6faaf04894446df7b0a7e7aba70c2797465a0a1af00fc887", size = 2099043, upload-time = "2025-10-14T10:20:28.561Z" }, - { url = "https://files.pythonhosted.org/packages/58/da/46fdac49e6717e3a94fc9201403e08d9d61aa7a770fab6190b8740749047/pydantic_core-2.41.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:c53ff33e603a9c1179a9364b0a24694f183717b2e0da2b5ad43c316c956901b2", size = 1910699, upload-time = "2025-10-14T10:20:30.217Z" }, - { url = "https://files.pythonhosted.org/packages/1e/63/4d948f1b9dd8e991a5a98b77dd66c74641f5f2e5225fee37994b2e07d391/pydantic_core-2.41.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:304c54176af2c143bd181d82e77c15c41cbacea8872a2225dd37e6544dce9999", size = 1952121, upload-time = "2025-10-14T10:20:32.246Z" }, - { url = "https://files.pythonhosted.org/packages/b2/a7/e5fc60a6f781fc634ecaa9ecc3c20171d238794cef69ae0af79ac11b89d7/pydantic_core-2.41.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:025ba34a4cf4fb32f917d5d188ab5e702223d3ba603be4d8aca2f82bede432a4", size = 2041590, upload-time = "2025-10-14T10:20:34.332Z" }, - { url = "https://files.pythonhosted.org/packages/70/69/dce747b1d21d59e85af433428978a1893c6f8a7068fa2bb4a927fba7a5ff/pydantic_core-2.41.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b9f5f30c402ed58f90c70e12eff65547d3ab74685ffe8283c719e6bead8ef53f", size = 2219869, upload-time = "2025-10-14T10:20:35.965Z" }, - { url = "https://files.pythonhosted.org/packages/83/6a/c070e30e295403bf29c4df1cb781317b6a9bac7cd07b8d3acc94d501a63c/pydantic_core-2.41.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:dd96e5d15385d301733113bcaa324c8bcf111275b7675a9c6e88bfb19fc05e3b", size = 2345169, upload-time = "2025-10-14T10:20:37.627Z" }, - { url = "https://files.pythonhosted.org/packages/f0/83/06d001f8043c336baea7fd202a9ac7ad71f87e1c55d8112c50b745c40324/pydantic_core-2.41.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98f348cbb44fae6e9653c1055db7e29de67ea6a9ca03a5fa2c2e11a47cff0e47", size = 2070165, upload-time = "2025-10-14T10:20:39.246Z" }, - { url = "https://files.pythonhosted.org/packages/14/0a/e567c2883588dd12bcbc110232d892cf385356f7c8a9910311ac997ab715/pydantic_core-2.41.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ec22626a2d14620a83ca583c6f5a4080fa3155282718b6055c2ea48d3ef35970", size = 2189067, upload-time = "2025-10-14T10:20:41.015Z" }, - { url = "https://files.pythonhosted.org/packages/f4/1d/3d9fca34273ba03c9b1c5289f7618bc4bd09c3ad2289b5420481aa051a99/pydantic_core-2.41.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:3a95d4590b1f1a43bf33ca6d647b990a88f4a3824a8c4572c708f0b45a5290ed", size = 2132997, upload-time = "2025-10-14T10:20:43.106Z" }, - { url = "https://files.pythonhosted.org/packages/52/70/d702ef7a6cd41a8afc61f3554922b3ed8d19dd54c3bd4bdbfe332e610827/pydantic_core-2.41.4-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:f9672ab4d398e1b602feadcffcdd3af44d5f5e6ddc15bc7d15d376d47e8e19f8", size = 2307187, upload-time = "2025-10-14T10:20:44.849Z" }, - { url = "https://files.pythonhosted.org/packages/68/4c/c06be6e27545d08b802127914156f38d10ca287a9e8489342793de8aae3c/pydantic_core-2.41.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:84d8854db5f55fead3b579f04bda9a36461dab0730c5d570e1526483e7bb8431", size = 2305204, upload-time = "2025-10-14T10:20:46.781Z" }, - { url = "https://files.pythonhosted.org/packages/b0/e5/35ae4919bcd9f18603419e23c5eaf32750224a89d41a8df1a3704b69f77e/pydantic_core-2.41.4-cp312-cp312-win32.whl", hash = "sha256:9be1c01adb2ecc4e464392c36d17f97e9110fbbc906bcbe1c943b5b87a74aabd", size = 1972536, upload-time = "2025-10-14T10:20:48.39Z" }, - { url = "https://files.pythonhosted.org/packages/1e/c2/49c5bb6d2a49eb2ee3647a93e3dae7080c6409a8a7558b075027644e879c/pydantic_core-2.41.4-cp312-cp312-win_amd64.whl", hash = "sha256:d682cf1d22bab22a5be08539dca3d1593488a99998f9f412137bc323179067ff", size = 2031132, upload-time = "2025-10-14T10:20:50.421Z" }, - { url = "https://files.pythonhosted.org/packages/06/23/936343dbcba6eec93f73e95eb346810fc732f71ba27967b287b66f7b7097/pydantic_core-2.41.4-cp312-cp312-win_arm64.whl", hash = "sha256:833eebfd75a26d17470b58768c1834dfc90141b7afc6eb0429c21fc5a21dcfb8", size = 1969483, upload-time = "2025-10-14T10:20:52.35Z" }, - { url = "https://files.pythonhosted.org/packages/13/d0/c20adabd181a029a970738dfe23710b52a31f1258f591874fcdec7359845/pydantic_core-2.41.4-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:85e050ad9e5f6fe1004eec65c914332e52f429bc0ae12d6fa2092407a462c746", size = 2105688, upload-time = "2025-10-14T10:20:54.448Z" }, - { url = "https://files.pythonhosted.org/packages/00/b6/0ce5c03cec5ae94cca220dfecddc453c077d71363b98a4bbdb3c0b22c783/pydantic_core-2.41.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:e7393f1d64792763a48924ba31d1e44c2cfbc05e3b1c2c9abb4ceeadd912cced", size = 1910807, upload-time = "2025-10-14T10:20:56.115Z" }, - { url = "https://files.pythonhosted.org/packages/68/3e/800d3d02c8beb0b5c069c870cbb83799d085debf43499c897bb4b4aaff0d/pydantic_core-2.41.4-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:94dab0940b0d1fb28bcab847adf887c66a27a40291eedf0b473be58761c9799a", size = 1956669, upload-time = "2025-10-14T10:20:57.874Z" }, - { url = "https://files.pythonhosted.org/packages/60/a4/24271cc71a17f64589be49ab8bd0751f6a0a03046c690df60989f2f95c2c/pydantic_core-2.41.4-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:de7c42f897e689ee6f9e93c4bec72b99ae3b32a2ade1c7e4798e690ff5246e02", size = 2051629, upload-time = "2025-10-14T10:21:00.006Z" }, - { url = "https://files.pythonhosted.org/packages/68/de/45af3ca2f175d91b96bfb62e1f2d2f1f9f3b14a734afe0bfeff079f78181/pydantic_core-2.41.4-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:664b3199193262277b8b3cd1e754fb07f2c6023289c815a1e1e8fb415cb247b1", size = 2224049, upload-time = "2025-10-14T10:21:01.801Z" }, - { url = "https://files.pythonhosted.org/packages/af/8f/ae4e1ff84672bf869d0a77af24fd78387850e9497753c432875066b5d622/pydantic_core-2.41.4-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d95b253b88f7d308b1c0b417c4624f44553ba4762816f94e6986819b9c273fb2", size = 2342409, upload-time = "2025-10-14T10:21:03.556Z" }, - { url = "https://files.pythonhosted.org/packages/18/62/273dd70b0026a085c7b74b000394e1ef95719ea579c76ea2f0cc8893736d/pydantic_core-2.41.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a1351f5bbdbbabc689727cb91649a00cb9ee7203e0a6e54e9f5ba9e22e384b84", size = 2069635, upload-time = "2025-10-14T10:21:05.385Z" }, - { url = "https://files.pythonhosted.org/packages/30/03/cf485fff699b4cdaea469bc481719d3e49f023241b4abb656f8d422189fc/pydantic_core-2.41.4-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1affa4798520b148d7182da0615d648e752de4ab1a9566b7471bc803d88a062d", size = 2194284, upload-time = "2025-10-14T10:21:07.122Z" }, - { url = "https://files.pythonhosted.org/packages/f9/7e/c8e713db32405dfd97211f2fc0a15d6bf8adb7640f3d18544c1f39526619/pydantic_core-2.41.4-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:7b74e18052fea4aa8dea2fb7dbc23d15439695da6cbe6cfc1b694af1115df09d", size = 2137566, upload-time = "2025-10-14T10:21:08.981Z" }, - { url = "https://files.pythonhosted.org/packages/04/f7/db71fd4cdccc8b75990f79ccafbbd66757e19f6d5ee724a6252414483fb4/pydantic_core-2.41.4-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:285b643d75c0e30abda9dc1077395624f314a37e3c09ca402d4015ef5979f1a2", size = 2316809, upload-time = "2025-10-14T10:21:10.805Z" }, - { url = "https://files.pythonhosted.org/packages/76/63/a54973ddb945f1bca56742b48b144d85c9fc22f819ddeb9f861c249d5464/pydantic_core-2.41.4-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:f52679ff4218d713b3b33f88c89ccbf3a5c2c12ba665fb80ccc4192b4608dbab", size = 2311119, upload-time = "2025-10-14T10:21:12.583Z" }, - { url = "https://files.pythonhosted.org/packages/f8/03/5d12891e93c19218af74843a27e32b94922195ded2386f7b55382f904d2f/pydantic_core-2.41.4-cp313-cp313-win32.whl", hash = "sha256:ecde6dedd6fff127c273c76821bb754d793be1024bc33314a120f83a3c69460c", size = 1981398, upload-time = "2025-10-14T10:21:14.584Z" }, - { url = "https://files.pythonhosted.org/packages/be/d8/fd0de71f39db91135b7a26996160de71c073d8635edfce8b3c3681be0d6d/pydantic_core-2.41.4-cp313-cp313-win_amd64.whl", hash = "sha256:d081a1f3800f05409ed868ebb2d74ac39dd0c1ff6c035b5162356d76030736d4", size = 2030735, upload-time = "2025-10-14T10:21:16.432Z" }, - { url = "https://files.pythonhosted.org/packages/72/86/c99921c1cf6650023c08bfab6fe2d7057a5142628ef7ccfa9921f2dda1d5/pydantic_core-2.41.4-cp313-cp313-win_arm64.whl", hash = "sha256:f8e49c9c364a7edcbe2a310f12733aad95b022495ef2a8d653f645e5d20c1564", size = 1973209, upload-time = "2025-10-14T10:21:18.213Z" }, - { url = "https://files.pythonhosted.org/packages/36/0d/b5706cacb70a8414396efdda3d72ae0542e050b591119e458e2490baf035/pydantic_core-2.41.4-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:ed97fd56a561f5eb5706cebe94f1ad7c13b84d98312a05546f2ad036bafe87f4", size = 1877324, upload-time = "2025-10-14T10:21:20.363Z" }, - { url = "https://files.pythonhosted.org/packages/de/2d/cba1fa02cfdea72dfb3a9babb067c83b9dff0bbcb198368e000a6b756ea7/pydantic_core-2.41.4-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a870c307bf1ee91fc58a9a61338ff780d01bfae45922624816878dce784095d2", size = 1884515, upload-time = "2025-10-14T10:21:22.339Z" }, - { url = "https://files.pythonhosted.org/packages/07/ea/3df927c4384ed9b503c9cc2d076cf983b4f2adb0c754578dfb1245c51e46/pydantic_core-2.41.4-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d25e97bc1f5f8f7985bdc2335ef9e73843bb561eb1fa6831fdfc295c1c2061cf", size = 2042819, upload-time = "2025-10-14T10:21:26.683Z" }, - { url = "https://files.pythonhosted.org/packages/6a/ee/df8e871f07074250270a3b1b82aad4cd0026b588acd5d7d3eb2fcb1471a3/pydantic_core-2.41.4-cp313-cp313t-win_amd64.whl", hash = "sha256:d405d14bea042f166512add3091c1af40437c2e7f86988f3915fabd27b1e9cd2", size = 1995866, upload-time = "2025-10-14T10:21:28.951Z" }, - { url = "https://files.pythonhosted.org/packages/fc/de/b20f4ab954d6d399499c33ec4fafc46d9551e11dc1858fb7f5dca0748ceb/pydantic_core-2.41.4-cp313-cp313t-win_arm64.whl", hash = "sha256:19f3684868309db5263a11bace3c45d93f6f24afa2ffe75a647583df22a2ff89", size = 1970034, upload-time = "2025-10-14T10:21:30.869Z" }, - { url = "https://files.pythonhosted.org/packages/54/28/d3325da57d413b9819365546eb9a6e8b7cbd9373d9380efd5f74326143e6/pydantic_core-2.41.4-cp314-cp314-macosx_10_12_x86_64.whl", hash = "sha256:e9205d97ed08a82ebb9a307e92914bb30e18cdf6f6b12ca4bedadb1588a0bfe1", size = 2102022, upload-time = "2025-10-14T10:21:32.809Z" }, - { url = "https://files.pythonhosted.org/packages/9e/24/b58a1bc0d834bf1acc4361e61233ee217169a42efbdc15a60296e13ce438/pydantic_core-2.41.4-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:82df1f432b37d832709fbcc0e24394bba04a01b6ecf1ee87578145c19cde12ac", size = 1905495, upload-time = "2025-10-14T10:21:34.812Z" }, - { url = "https://files.pythonhosted.org/packages/fb/a4/71f759cc41b7043e8ecdaab81b985a9b6cad7cec077e0b92cff8b71ecf6b/pydantic_core-2.41.4-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fc3b4cc4539e055cfa39a3763c939f9d409eb40e85813257dcd761985a108554", size = 1956131, upload-time = "2025-10-14T10:21:36.924Z" }, - { url = "https://files.pythonhosted.org/packages/b0/64/1e79ac7aa51f1eec7c4cda8cbe456d5d09f05fdd68b32776d72168d54275/pydantic_core-2.41.4-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b1eb1754fce47c63d2ff57fdb88c351a6c0150995890088b33767a10218eaa4e", size = 2052236, upload-time = "2025-10-14T10:21:38.927Z" }, - { url = "https://files.pythonhosted.org/packages/e9/e3/a3ffc363bd4287b80f1d43dc1c28ba64831f8dfc237d6fec8f2661138d48/pydantic_core-2.41.4-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e6ab5ab30ef325b443f379ddb575a34969c333004fca5a1daa0133a6ffaad616", size = 2223573, upload-time = "2025-10-14T10:21:41.574Z" }, - { url = "https://files.pythonhosted.org/packages/28/27/78814089b4d2e684a9088ede3790763c64693c3d1408ddc0a248bc789126/pydantic_core-2.41.4-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:31a41030b1d9ca497634092b46481b937ff9397a86f9f51bd41c4767b6fc04af", size = 2342467, upload-time = "2025-10-14T10:21:44.018Z" }, - { url = "https://files.pythonhosted.org/packages/92/97/4de0e2a1159cb85ad737e03306717637842c88c7fd6d97973172fb183149/pydantic_core-2.41.4-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a44ac1738591472c3d020f61c6df1e4015180d6262ebd39bf2aeb52571b60f12", size = 2063754, upload-time = "2025-10-14T10:21:46.466Z" }, - { url = "https://files.pythonhosted.org/packages/0f/50/8cb90ce4b9efcf7ae78130afeb99fd1c86125ccdf9906ef64b9d42f37c25/pydantic_core-2.41.4-cp314-cp314-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d72f2b5e6e82ab8f94ea7d0d42f83c487dc159c5240d8f83beae684472864e2d", size = 2196754, upload-time = "2025-10-14T10:21:48.486Z" }, - { url = "https://files.pythonhosted.org/packages/34/3b/ccdc77af9cd5082723574a1cc1bcae7a6acacc829d7c0a06201f7886a109/pydantic_core-2.41.4-cp314-cp314-musllinux_1_1_aarch64.whl", hash = "sha256:c4d1e854aaf044487d31143f541f7aafe7b482ae72a022c664b2de2e466ed0ad", size = 2137115, upload-time = "2025-10-14T10:21:50.63Z" }, - { url = "https://files.pythonhosted.org/packages/ca/ba/e7c7a02651a8f7c52dc2cff2b64a30c313e3b57c7d93703cecea76c09b71/pydantic_core-2.41.4-cp314-cp314-musllinux_1_1_armv7l.whl", hash = "sha256:b568af94267729d76e6ee5ececda4e283d07bbb28e8148bb17adad93d025d25a", size = 2317400, upload-time = "2025-10-14T10:21:52.959Z" }, - { url = "https://files.pythonhosted.org/packages/2c/ba/6c533a4ee8aec6b812c643c49bb3bd88d3f01e3cebe451bb85512d37f00f/pydantic_core-2.41.4-cp314-cp314-musllinux_1_1_x86_64.whl", hash = "sha256:6d55fb8b1e8929b341cc313a81a26e0d48aa3b519c1dbaadec3a6a2b4fcad025", size = 2312070, upload-time = "2025-10-14T10:21:55.419Z" }, - { url = "https://files.pythonhosted.org/packages/22/ae/f10524fcc0ab8d7f96cf9a74c880243576fd3e72bd8ce4f81e43d22bcab7/pydantic_core-2.41.4-cp314-cp314-win32.whl", hash = "sha256:5b66584e549e2e32a1398df11da2e0a7eff45d5c2d9db9d5667c5e6ac764d77e", size = 1982277, upload-time = "2025-10-14T10:21:57.474Z" }, - { url = "https://files.pythonhosted.org/packages/b4/dc/e5aa27aea1ad4638f0c3fb41132f7eb583bd7420ee63204e2d4333a3bbf9/pydantic_core-2.41.4-cp314-cp314-win_amd64.whl", hash = "sha256:557a0aab88664cc552285316809cab897716a372afaf8efdbef756f8b890e894", size = 2024608, upload-time = "2025-10-14T10:21:59.557Z" }, - { url = "https://files.pythonhosted.org/packages/3e/61/51d89cc2612bd147198e120a13f150afbf0bcb4615cddb049ab10b81b79e/pydantic_core-2.41.4-cp314-cp314-win_arm64.whl", hash = "sha256:3f1ea6f48a045745d0d9f325989d8abd3f1eaf47dd00485912d1a3a63c623a8d", size = 1967614, upload-time = "2025-10-14T10:22:01.847Z" }, - { url = "https://files.pythonhosted.org/packages/0d/c2/472f2e31b95eff099961fa050c376ab7156a81da194f9edb9f710f68787b/pydantic_core-2.41.4-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:6c1fe4c5404c448b13188dd8bd2ebc2bdd7e6727fa61ff481bcc2cca894018da", size = 1876904, upload-time = "2025-10-14T10:22:04.062Z" }, - { url = "https://files.pythonhosted.org/packages/4a/07/ea8eeb91173807ecdae4f4a5f4b150a520085b35454350fc219ba79e66a3/pydantic_core-2.41.4-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:523e7da4d43b113bf8e7b49fa4ec0c35bf4fe66b2230bfc5c13cc498f12c6c3e", size = 1882538, upload-time = "2025-10-14T10:22:06.39Z" }, - { url = "https://files.pythonhosted.org/packages/1e/29/b53a9ca6cd366bfc928823679c6a76c7a4c69f8201c0ba7903ad18ebae2f/pydantic_core-2.41.4-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5729225de81fb65b70fdb1907fcf08c75d498f4a6f15af005aabb1fdadc19dfa", size = 2041183, upload-time = "2025-10-14T10:22:08.812Z" }, - { url = "https://files.pythonhosted.org/packages/c7/3d/f8c1a371ceebcaf94d6dd2d77c6cf4b1c078e13a5837aee83f760b4f7cfd/pydantic_core-2.41.4-cp314-cp314t-win_amd64.whl", hash = "sha256:de2cfbb09e88f0f795fd90cf955858fc2c691df65b1f21f0aa00b99f3fbc661d", size = 1993542, upload-time = "2025-10-14T10:22:11.332Z" }, - { url = "https://files.pythonhosted.org/packages/8a/ac/9fc61b4f9d079482a290afe8d206b8f490e9fd32d4fc03ed4fc698214e01/pydantic_core-2.41.4-cp314-cp314t-win_arm64.whl", hash = "sha256:d34f950ae05a83e0ede899c595f312ca976023ea1db100cd5aa188f7005e3ab0", size = 1973897, upload-time = "2025-10-14T10:22:13.444Z" }, - { url = "https://files.pythonhosted.org/packages/b0/12/5ba58daa7f453454464f92b3ca7b9d7c657d8641c48e370c3ebc9a82dd78/pydantic_core-2.41.4-graalpy311-graalpy242_311_native-macosx_10_12_x86_64.whl", hash = "sha256:a1b2cfec3879afb742a7b0bcfa53e4f22ba96571c9e54d6a3afe1052d17d843b", size = 2122139, upload-time = "2025-10-14T10:22:47.288Z" }, - { url = "https://files.pythonhosted.org/packages/21/fb/6860126a77725c3108baecd10fd3d75fec25191d6381b6eb2ac660228eac/pydantic_core-2.41.4-graalpy311-graalpy242_311_native-macosx_11_0_arm64.whl", hash = "sha256:d175600d975b7c244af6eb9c9041f10059f20b8bbffec9e33fdd5ee3f67cdc42", size = 1936674, upload-time = "2025-10-14T10:22:49.555Z" }, - { url = "https://files.pythonhosted.org/packages/de/be/57dcaa3ed595d81f8757e2b44a38240ac5d37628bce25fb20d02c7018776/pydantic_core-2.41.4-graalpy311-graalpy242_311_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0f184d657fa4947ae5ec9c47bd7e917730fa1cbb78195037e32dcbab50aca5ee", size = 1956398, upload-time = "2025-10-14T10:22:52.19Z" }, - { url = "https://files.pythonhosted.org/packages/2f/1d/679a344fadb9695f1a6a294d739fbd21d71fa023286daeea8c0ed49e7c2b/pydantic_core-2.41.4-graalpy311-graalpy242_311_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1ed810568aeffed3edc78910af32af911c835cc39ebbfacd1f0ab5dd53028e5c", size = 2138674, upload-time = "2025-10-14T10:22:54.499Z" }, - { url = "https://files.pythonhosted.org/packages/c4/48/ae937e5a831b7c0dc646b2ef788c27cd003894882415300ed21927c21efa/pydantic_core-2.41.4-graalpy312-graalpy250_312_native-macosx_10_12_x86_64.whl", hash = "sha256:4f5d640aeebb438517150fdeec097739614421900e4a08db4a3ef38898798537", size = 2112087, upload-time = "2025-10-14T10:22:56.818Z" }, - { url = "https://files.pythonhosted.org/packages/5e/db/6db8073e3d32dae017da7e0d16a9ecb897d0a4d92e00634916e486097961/pydantic_core-2.41.4-graalpy312-graalpy250_312_native-macosx_11_0_arm64.whl", hash = "sha256:4a9ab037b71927babc6d9e7fc01aea9e66dc2a4a34dff06ef0724a4049629f94", size = 1920387, upload-time = "2025-10-14T10:22:59.342Z" }, - { url = "https://files.pythonhosted.org/packages/0d/c1/dd3542d072fcc336030d66834872f0328727e3b8de289c662faa04aa270e/pydantic_core-2.41.4-graalpy312-graalpy250_312_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e4dab9484ec605c3016df9ad4fd4f9a390bc5d816a3b10c6550f8424bb80b18c", size = 1951495, upload-time = "2025-10-14T10:23:02.089Z" }, - { url = "https://files.pythonhosted.org/packages/2b/c6/db8d13a1f8ab3f1eb08c88bd00fd62d44311e3456d1e85c0e59e0a0376e7/pydantic_core-2.41.4-graalpy312-graalpy250_312_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bd8a5028425820731d8c6c098ab642d7b8b999758e24acae03ed38a66eca8335", size = 2139008, upload-time = "2025-10-14T10:23:04.539Z" }, - { url = "https://files.pythonhosted.org/packages/5d/d4/912e976a2dd0b49f31c98a060ca90b353f3b73ee3ea2fd0030412f6ac5ec/pydantic_core-2.41.4-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:1e5ab4fc177dd41536b3c32b2ea11380dd3d4619a385860621478ac2d25ceb00", size = 2106739, upload-time = "2025-10-14T10:23:06.934Z" }, - { url = "https://files.pythonhosted.org/packages/71/f0/66ec5a626c81eba326072d6ee2b127f8c139543f1bf609b4842978d37833/pydantic_core-2.41.4-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:3d88d0054d3fa11ce936184896bed3c1c5441d6fa483b498fac6a5d0dd6f64a9", size = 1932549, upload-time = "2025-10-14T10:23:09.24Z" }, - { url = "https://files.pythonhosted.org/packages/c4/af/625626278ca801ea0a658c2dcf290dc9f21bb383098e99e7c6a029fccfc0/pydantic_core-2.41.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7b2a054a8725f05b4b6503357e0ac1c4e8234ad3b0c2ac130d6ffc66f0e170e2", size = 2135093, upload-time = "2025-10-14T10:23:11.626Z" }, - { url = "https://files.pythonhosted.org/packages/20/f6/2fba049f54e0f4975fef66be654c597a1d005320fa141863699180c7697d/pydantic_core-2.41.4-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b0d9db5a161c99375a0c68c058e227bee1d89303300802601d76a3d01f74e258", size = 2187971, upload-time = "2025-10-14T10:23:14.437Z" }, - { url = "https://files.pythonhosted.org/packages/0e/80/65ab839a2dfcd3b949202f9d920c34f9de5a537c3646662bdf2f7d999680/pydantic_core-2.41.4-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:6273ea2c8ffdac7b7fda2653c49682db815aebf4a89243a6feccf5e36c18c347", size = 2147939, upload-time = "2025-10-14T10:23:16.831Z" }, - { url = "https://files.pythonhosted.org/packages/44/58/627565d3d182ce6dfda18b8e1c841eede3629d59c9d7cbc1e12a03aeb328/pydantic_core-2.41.4-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:4c973add636efc61de22530b2ef83a65f39b6d6f656df97f678720e20de26caa", size = 2311400, upload-time = "2025-10-14T10:23:19.234Z" }, - { url = "https://files.pythonhosted.org/packages/24/06/8a84711162ad5a5f19a88cead37cca81b4b1f294f46260ef7334ae4f24d3/pydantic_core-2.41.4-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:b69d1973354758007f46cf2d44a4f3d0933f10b6dc9bf15cf1356e037f6f731a", size = 2316840, upload-time = "2025-10-14T10:23:21.738Z" }, - { url = "https://files.pythonhosted.org/packages/aa/8b/b7bb512a4682a2f7fbfae152a755d37351743900226d29bd953aaf870eaa/pydantic_core-2.41.4-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:3619320641fd212aaf5997b6ca505e97540b7e16418f4a241f44cdf108ffb50d", size = 2149135, upload-time = "2025-10-14T10:23:24.379Z" }, - { url = "https://files.pythonhosted.org/packages/7e/7d/138e902ed6399b866f7cfe4435d22445e16fff888a1c00560d9dc79a780f/pydantic_core-2.41.4-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:491535d45cd7ad7e4a2af4a5169b0d07bebf1adfd164b0368da8aa41e19907a5", size = 2104721, upload-time = "2025-10-14T10:23:26.906Z" }, - { url = "https://files.pythonhosted.org/packages/47/13/0525623cf94627f7b53b4c2034c81edc8491cbfc7c28d5447fa318791479/pydantic_core-2.41.4-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:54d86c0cada6aba4ec4c047d0e348cbad7063b87ae0f005d9f8c9ad04d4a92a2", size = 1931608, upload-time = "2025-10-14T10:23:29.306Z" }, - { url = "https://files.pythonhosted.org/packages/d6/f9/744bc98137d6ef0a233f808bfc9b18cf94624bf30836a18d3b05d08bf418/pydantic_core-2.41.4-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eca1124aced216b2500dc2609eade086d718e8249cb9696660ab447d50a758bd", size = 2132986, upload-time = "2025-10-14T10:23:32.057Z" }, - { url = "https://files.pythonhosted.org/packages/17/c8/629e88920171173f6049386cc71f893dff03209a9ef32b4d2f7e7c264bcf/pydantic_core-2.41.4-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6c9024169becccf0cb470ada03ee578d7348c119a0d42af3dcf9eda96e3a247c", size = 2187516, upload-time = "2025-10-14T10:23:34.871Z" }, - { url = "https://files.pythonhosted.org/packages/2e/0f/4f2734688d98488782218ca61bcc118329bf5de05bb7fe3adc7dd79b0b86/pydantic_core-2.41.4-pp311-pypy311_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:26895a4268ae5a2849269f4991cdc97236e4b9c010e51137becf25182daac405", size = 2146146, upload-time = "2025-10-14T10:23:37.342Z" }, - { url = "https://files.pythonhosted.org/packages/ed/f2/ab385dbd94a052c62224b99cf99002eee99dbec40e10006c78575aead256/pydantic_core-2.41.4-pp311-pypy311_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:ca4df25762cf71308c446e33c9b1fdca2923a3f13de616e2a949f38bf21ff5a8", size = 2311296, upload-time = "2025-10-14T10:23:40.145Z" }, - { url = "https://files.pythonhosted.org/packages/fc/8e/e4f12afe1beeb9823bba5375f8f258df0cc61b056b0195fb1cf9f62a1a58/pydantic_core-2.41.4-pp311-pypy311_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:5a28fcedd762349519276c36634e71853b4541079cab4acaaac60c4421827308", size = 2315386, upload-time = "2025-10-14T10:23:42.624Z" }, - { url = "https://files.pythonhosted.org/packages/48/f7/925f65d930802e3ea2eb4d5afa4cb8730c8dc0d2cb89a59dc4ed2fcb2d74/pydantic_core-2.41.4-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:c173ddcd86afd2535e2b695217e82191580663a1d1928239f877f5a1649ef39f", size = 2147775, upload-time = "2025-10-14T10:23:45.406Z" }, -] - -[[package]] -name = "pydantic-settings" -version = "2.11.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "pydantic" }, - { name = "python-dotenv" }, - { name = "typing-inspection" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/20/c5/dbbc27b814c71676593d1c3f718e6cd7d4f00652cefa24b75f7aa3efb25e/pydantic_settings-2.11.0.tar.gz", hash = "sha256:d0e87a1c7d33593beb7194adb8470fc426e95ba02af83a0f23474a04c9a08180", size = 188394, upload-time = "2025-09-24T14:19:11.764Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/83/d6/887a1ff844e64aa823fb4905978d882a633cfe295c32eacad582b78a7d8b/pydantic_settings-2.11.0-py3-none-any.whl", hash = "sha256:fe2cea3413b9530d10f3a5875adffb17ada5c1e1bab0b2885546d7310415207c", size = 48608, upload-time = "2025-09-24T14:19:10.015Z" }, -] - -[[package]] -name = "pygments" -version = "2.19.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/b0/77/a5b8c569bf593b0140bde72ea885a803b82086995367bf2037de0159d924/pygments-2.19.2.tar.gz", hash = "sha256:636cb2477cec7f8952536970bc533bc43743542f70392ae026374600add5b887", size = 4968631, upload-time = "2025-06-21T13:39:12.283Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl", hash = "sha256:86540386c03d588bb81d44bc3928634ff26449851e99741617ecb9037ee5ec0b", size = 1225217, upload-time = "2025-06-21T13:39:07.939Z" }, -] - -[[package]] -name = "pyjwt" -version = "2.10.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/e7/46/bd74733ff231675599650d3e47f361794b22ef3e3770998dda30d3b63726/pyjwt-2.10.1.tar.gz", hash = "sha256:3cc5772eb20009233caf06e9d8a0577824723b44e6648ee0a2aedb6cf9381953", size = 87785, upload-time = "2024-11-28T03:43:29.933Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/61/ad/689f02752eeec26aed679477e80e632ef1b682313be70793d798c1d5fc8f/PyJWT-2.10.1-py3-none-any.whl", hash = "sha256:dcdd193e30abefd5debf142f9adfcdd2b58004e644f25406ffaebd50bd98dacb", size = 22997, upload-time = "2024-11-28T03:43:27.893Z" }, -] - -[package.optional-dependencies] -crypto = [ - { name = "cryptography" }, -] - -[[package]] -name = "pyparsing" -version = "3.2.5" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f2/a5/181488fc2b9d093e3972d2a472855aae8a03f000592dbfce716a512b3359/pyparsing-3.2.5.tar.gz", hash = "sha256:2df8d5b7b2802ef88e8d016a2eb9c7aeaa923529cd251ed0fe4608275d4105b6", size = 1099274, upload-time = "2025-09-21T04:11:06.277Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/10/5e/1aa9a93198c6b64513c9d7752de7422c06402de6600a8767da1524f9570b/pyparsing-3.2.5-py3-none-any.whl", hash = "sha256:e38a4f02064cf41fe6593d328d0512495ad1f3d8a91c4f73fc401b3079a59a5e", size = 113890, upload-time = "2025-09-21T04:11:04.117Z" }, -] - -[[package]] -name = "pytest" -version = "8.4.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "colorama", marker = "sys_platform == 'win32'" }, - { name = "exceptiongroup", marker = "python_full_version < '3.11'" }, - { name = "iniconfig" }, - { name = "packaging" }, - { name = "pluggy" }, - { name = "pygments" }, - { name = "tomli", marker = "python_full_version < '3.11'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/a3/5c/00a0e072241553e1a7496d638deababa67c5058571567b92a7eaa258397c/pytest-8.4.2.tar.gz", hash = "sha256:86c0d0b93306b961d58d62a4db4879f27fe25513d4b969df351abdddb3c30e01", size = 1519618, upload-time = "2025-09-04T14:34:22.711Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a8/a4/20da314d277121d6534b3a980b29035dcd51e6744bd79075a6ce8fa4eb8d/pytest-8.4.2-py3-none-any.whl", hash = "sha256:872f880de3fc3a5bdc88a11b39c9710c3497a547cfa9320bc3c5e62fbf272e79", size = 365750, upload-time = "2025-09-04T14:34:20.226Z" }, -] - -[[package]] -name = "pytest-asyncio" -version = "1.2.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "backports-asyncio-runner", marker = "python_full_version < '3.11'" }, - { name = "pytest" }, - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/42/86/9e3c5f48f7b7b638b216e4b9e645f54d199d7abbbab7a64a13b4e12ba10f/pytest_asyncio-1.2.0.tar.gz", hash = "sha256:c609a64a2a8768462d0c99811ddb8bd2583c33fd33cf7f21af1c142e824ffb57", size = 50119, upload-time = "2025-09-12T07:33:53.816Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/04/93/2fa34714b7a4ae72f2f8dad66ba17dd9a2c793220719e736dda28b7aec27/pytest_asyncio-1.2.0-py3-none-any.whl", hash = "sha256:8e17ae5e46d8e7efe51ab6494dd2010f4ca8dae51652aa3c8d55acf50bfb2e99", size = 15095, upload-time = "2025-09-12T07:33:52.639Z" }, -] - -[[package]] -name = "pytest-vcr" -version = "1.0.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "pytest" }, - { name = "vcrpy" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/1a/60/104c619483c1a42775d3f8b27293f1ecfc0728014874d065e68cb9702d49/pytest-vcr-1.0.2.tar.gz", hash = "sha256:23ee51b75abbcc43d926272773aae4f39f93aceb75ed56852d0bf618f92e1896", size = 3810, upload-time = "2019-04-26T19:04:00.806Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/9d/d3/ff520d11e6ee400602711d1ece8168dcfc5b6d8146fb7db4244a6ad6a9c3/pytest_vcr-1.0.2-py2.py3-none-any.whl", hash = "sha256:2f316e0539399bea0296e8b8401145c62b6f85e9066af7e57b6151481b0d6d9c", size = 4137, upload-time = "2019-04-26T19:03:57.034Z" }, -] - -[[package]] -name = "python-dateutil" -version = "2.9.0.post0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "six" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/66/c0/0c8b6ad9f17a802ee498c46e004a0eb49bc148f2fd230864601a86dcf6db/python-dateutil-2.9.0.post0.tar.gz", hash = "sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3", size = 342432, upload-time = "2024-03-01T18:36:20.211Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427", size = 229892, upload-time = "2024-03-01T18:36:18.57Z" }, -] - -[[package]] -name = "python-dotenv" -version = "1.2.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f0/26/19cadc79a718c5edbec86fd4919a6b6d3f681039a2f6d66d14be94e75fb9/python_dotenv-1.2.1.tar.gz", hash = "sha256:42667e897e16ab0d66954af0e60a9caa94f0fd4ecf3aaf6d2d260eec1aa36ad6", size = 44221, upload-time = "2025-10-26T15:12:10.434Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/14/1b/a298b06749107c305e1fe0f814c6c74aea7b2f1e10989cb30f544a1b3253/python_dotenv-1.2.1-py3-none-any.whl", hash = "sha256:b81ee9561e9ca4004139c6cbba3a238c32b03e4894671e181b671e8cb8425d61", size = 21230, upload-time = "2025-10-26T15:12:09.109Z" }, -] - -[[package]] -name = "python-multipart" -version = "0.0.20" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f3/87/f44d7c9f274c7ee665a29b885ec97089ec5dc034c7f3fafa03da9e39a09e/python_multipart-0.0.20.tar.gz", hash = "sha256:8dd0cab45b8e23064ae09147625994d090fa46f5b0d1e13af944c331a7fa9d13", size = 37158, upload-time = "2024-12-16T19:45:46.972Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/45/58/38b5afbc1a800eeea951b9285d3912613f2603bdf897a4ab0f4bd7f405fc/python_multipart-0.0.20-py3-none-any.whl", hash = "sha256:8a62d3a8335e06589fe01f2a3e178cdcc632f3fbe0d492ad9ee0ec35aab1f104", size = 24546, upload-time = "2024-12-16T19:45:44.423Z" }, -] - -[[package]] -name = "python-slugify" -version = "8.0.4" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "text-unidecode" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/87/c7/5e1547c44e31da50a460df93af11a535ace568ef89d7a811069ead340c4a/python-slugify-8.0.4.tar.gz", hash = "sha256:59202371d1d05b54a9e7720c5e038f928f45daaffe41dd10822f3907b937c856", size = 10921, upload-time = "2024-02-08T18:32:45.488Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a4/62/02da182e544a51a5c3ccf4b03ab79df279f9c60c5e82d5e8bec7ca26ac11/python_slugify-8.0.4-py2.py3-none-any.whl", hash = "sha256:276540b79961052b66b7d116620b36518847f52d5fd9e3a70164fc8c50faa6b8", size = 10051, upload-time = "2024-02-08T18:32:43.911Z" }, -] - -[[package]] -name = "pywin32" -version = "311" -source = { registry = "https://pypi.org/simple" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7b/40/44efbb0dfbd33aca6a6483191dae0716070ed99e2ecb0c53683f400a0b4f/pywin32-311-cp310-cp310-win32.whl", hash = "sha256:d03ff496d2a0cd4a5893504789d4a15399133fe82517455e78bad62efbb7f0a3", size = 8760432, upload-time = "2025-07-14T20:13:05.9Z" }, - { url = "https://files.pythonhosted.org/packages/5e/bf/360243b1e953bd254a82f12653974be395ba880e7ec23e3731d9f73921cc/pywin32-311-cp310-cp310-win_amd64.whl", hash = "sha256:797c2772017851984b97180b0bebe4b620bb86328e8a884bb626156295a63b3b", size = 9590103, upload-time = "2025-07-14T20:13:07.698Z" }, - { url = "https://files.pythonhosted.org/packages/57/38/d290720e6f138086fb3d5ffe0b6caa019a791dd57866940c82e4eeaf2012/pywin32-311-cp310-cp310-win_arm64.whl", hash = "sha256:0502d1facf1fed4839a9a51ccbcc63d952cf318f78ffc00a7e78528ac27d7a2b", size = 8778557, upload-time = "2025-07-14T20:13:11.11Z" }, - { url = "https://files.pythonhosted.org/packages/7c/af/449a6a91e5d6db51420875c54f6aff7c97a86a3b13a0b4f1a5c13b988de3/pywin32-311-cp311-cp311-win32.whl", hash = "sha256:184eb5e436dea364dcd3d2316d577d625c0351bf237c4e9a5fabbcfa5a58b151", size = 8697031, upload-time = "2025-07-14T20:13:13.266Z" }, - { url = "https://files.pythonhosted.org/packages/51/8f/9bb81dd5bb77d22243d33c8397f09377056d5c687aa6d4042bea7fbf8364/pywin32-311-cp311-cp311-win_amd64.whl", hash = "sha256:3ce80b34b22b17ccbd937a6e78e7225d80c52f5ab9940fe0506a1a16f3dab503", size = 9508308, upload-time = "2025-07-14T20:13:15.147Z" }, - { url = "https://files.pythonhosted.org/packages/44/7b/9c2ab54f74a138c491aba1b1cd0795ba61f144c711daea84a88b63dc0f6c/pywin32-311-cp311-cp311-win_arm64.whl", hash = "sha256:a733f1388e1a842abb67ffa8e7aad0e70ac519e09b0f6a784e65a136ec7cefd2", size = 8703930, upload-time = "2025-07-14T20:13:16.945Z" }, - { url = "https://files.pythonhosted.org/packages/e7/ab/01ea1943d4eba0f850c3c61e78e8dd59757ff815ff3ccd0a84de5f541f42/pywin32-311-cp312-cp312-win32.whl", hash = "sha256:750ec6e621af2b948540032557b10a2d43b0cee2ae9758c54154d711cc852d31", size = 8706543, upload-time = "2025-07-14T20:13:20.765Z" }, - { url = "https://files.pythonhosted.org/packages/d1/a8/a0e8d07d4d051ec7502cd58b291ec98dcc0c3fff027caad0470b72cfcc2f/pywin32-311-cp312-cp312-win_amd64.whl", hash = "sha256:b8c095edad5c211ff31c05223658e71bf7116daa0ecf3ad85f3201ea3190d067", size = 9495040, upload-time = "2025-07-14T20:13:22.543Z" }, - { url = "https://files.pythonhosted.org/packages/ba/3a/2ae996277b4b50f17d61f0603efd8253cb2d79cc7ae159468007b586396d/pywin32-311-cp312-cp312-win_arm64.whl", hash = "sha256:e286f46a9a39c4a18b319c28f59b61de793654af2f395c102b4f819e584b5852", size = 8710102, upload-time = "2025-07-14T20:13:24.682Z" }, - { url = "https://files.pythonhosted.org/packages/a5/be/3fd5de0979fcb3994bfee0d65ed8ca9506a8a1260651b86174f6a86f52b3/pywin32-311-cp313-cp313-win32.whl", hash = "sha256:f95ba5a847cba10dd8c4d8fefa9f2a6cf283b8b88ed6178fa8a6c1ab16054d0d", size = 8705700, upload-time = "2025-07-14T20:13:26.471Z" }, - { url = "https://files.pythonhosted.org/packages/e3/28/e0a1909523c6890208295a29e05c2adb2126364e289826c0a8bc7297bd5c/pywin32-311-cp313-cp313-win_amd64.whl", hash = "sha256:718a38f7e5b058e76aee1c56ddd06908116d35147e133427e59a3983f703a20d", size = 9494700, upload-time = "2025-07-14T20:13:28.243Z" }, - { url = "https://files.pythonhosted.org/packages/04/bf/90339ac0f55726dce7d794e6d79a18a91265bdf3aa70b6b9ca52f35e022a/pywin32-311-cp313-cp313-win_arm64.whl", hash = "sha256:7b4075d959648406202d92a2310cb990fea19b535c7f4a78d3f5e10b926eeb8a", size = 8709318, upload-time = "2025-07-14T20:13:30.348Z" }, - { url = "https://files.pythonhosted.org/packages/c9/31/097f2e132c4f16d99a22bfb777e0fd88bd8e1c634304e102f313af69ace5/pywin32-311-cp314-cp314-win32.whl", hash = "sha256:b7a2c10b93f8986666d0c803ee19b5990885872a7de910fc460f9b0c2fbf92ee", size = 8840714, upload-time = "2025-07-14T20:13:32.449Z" }, - { url = "https://files.pythonhosted.org/packages/90/4b/07c77d8ba0e01349358082713400435347df8426208171ce297da32c313d/pywin32-311-cp314-cp314-win_amd64.whl", hash = "sha256:3aca44c046bd2ed8c90de9cb8427f581c479e594e99b5c0bb19b29c10fd6cb87", size = 9656800, upload-time = "2025-07-14T20:13:34.312Z" }, - { url = "https://files.pythonhosted.org/packages/c0/d2/21af5c535501a7233e734b8af901574572da66fcc254cb35d0609c9080dd/pywin32-311-cp314-cp314-win_arm64.whl", hash = "sha256:a508e2d9025764a8270f93111a970e1d0fbfc33f4153b388bb649b7eec4f9b42", size = 8932540, upload-time = "2025-07-14T20:13:36.379Z" }, -] - -[[package]] -name = "pyyaml" -version = "6.0.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/05/8e/961c0007c59b8dd7729d542c61a4d537767a59645b82a0b521206e1e25c2/pyyaml-6.0.3.tar.gz", hash = "sha256:d76623373421df22fb4cf8817020cbb7ef15c725b9d5e45f17e189bfc384190f", size = 130960, upload-time = "2025-09-25T21:33:16.546Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/f4/a0/39350dd17dd6d6c6507025c0e53aef67a9293a6d37d3511f23ea510d5800/pyyaml-6.0.3-cp310-cp310-macosx_10_13_x86_64.whl", hash = "sha256:214ed4befebe12df36bcc8bc2b64b396ca31be9304b8f59e25c11cf94a4c033b", size = 184227, upload-time = "2025-09-25T21:31:46.04Z" }, - { url = "https://files.pythonhosted.org/packages/05/14/52d505b5c59ce73244f59c7a50ecf47093ce4765f116cdb98286a71eeca2/pyyaml-6.0.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:02ea2dfa234451bbb8772601d7b8e426c2bfa197136796224e50e35a78777956", size = 174019, upload-time = "2025-09-25T21:31:47.706Z" }, - { url = "https://files.pythonhosted.org/packages/43/f7/0e6a5ae5599c838c696adb4e6330a59f463265bfa1e116cfd1fbb0abaaae/pyyaml-6.0.3-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b30236e45cf30d2b8e7b3e85881719e98507abed1011bf463a8fa23e9c3e98a8", size = 740646, upload-time = "2025-09-25T21:31:49.21Z" }, - { url = "https://files.pythonhosted.org/packages/2f/3a/61b9db1d28f00f8fd0ae760459a5c4bf1b941baf714e207b6eb0657d2578/pyyaml-6.0.3-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:66291b10affd76d76f54fad28e22e51719ef9ba22b29e1d7d03d6777a9174198", size = 840793, upload-time = "2025-09-25T21:31:50.735Z" }, - { url = "https://files.pythonhosted.org/packages/7a/1e/7acc4f0e74c4b3d9531e24739e0ab832a5edf40e64fbae1a9c01941cabd7/pyyaml-6.0.3-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9c7708761fccb9397fe64bbc0395abcae8c4bf7b0eac081e12b809bf47700d0b", size = 770293, upload-time = "2025-09-25T21:31:51.828Z" }, - { url = "https://files.pythonhosted.org/packages/8b/ef/abd085f06853af0cd59fa5f913d61a8eab65d7639ff2a658d18a25d6a89d/pyyaml-6.0.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:418cf3f2111bc80e0933b2cd8cd04f286338bb88bdc7bc8e6dd775ebde60b5e0", size = 732872, upload-time = "2025-09-25T21:31:53.282Z" }, - { url = "https://files.pythonhosted.org/packages/1f/15/2bc9c8faf6450a8b3c9fc5448ed869c599c0a74ba2669772b1f3a0040180/pyyaml-6.0.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:5e0b74767e5f8c593e8c9b5912019159ed0533c70051e9cce3e8b6aa699fcd69", size = 758828, upload-time = "2025-09-25T21:31:54.807Z" }, - { url = "https://files.pythonhosted.org/packages/a3/00/531e92e88c00f4333ce359e50c19b8d1de9fe8d581b1534e35ccfbc5f393/pyyaml-6.0.3-cp310-cp310-win32.whl", hash = "sha256:28c8d926f98f432f88adc23edf2e6d4921ac26fb084b028c733d01868d19007e", size = 142415, upload-time = "2025-09-25T21:31:55.885Z" }, - { url = "https://files.pythonhosted.org/packages/2a/fa/926c003379b19fca39dd4634818b00dec6c62d87faf628d1394e137354d4/pyyaml-6.0.3-cp310-cp310-win_amd64.whl", hash = "sha256:bdb2c67c6c1390b63c6ff89f210c8fd09d9a1217a465701eac7316313c915e4c", size = 158561, upload-time = "2025-09-25T21:31:57.406Z" }, - { url = "https://files.pythonhosted.org/packages/6d/16/a95b6757765b7b031c9374925bb718d55e0a9ba8a1b6a12d25962ea44347/pyyaml-6.0.3-cp311-cp311-macosx_10_13_x86_64.whl", hash = "sha256:44edc647873928551a01e7a563d7452ccdebee747728c1080d881d68af7b997e", size = 185826, upload-time = "2025-09-25T21:31:58.655Z" }, - { url = "https://files.pythonhosted.org/packages/16/19/13de8e4377ed53079ee996e1ab0a9c33ec2faf808a4647b7b4c0d46dd239/pyyaml-6.0.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:652cb6edd41e718550aad172851962662ff2681490a8a711af6a4d288dd96824", size = 175577, upload-time = "2025-09-25T21:32:00.088Z" }, - { url = "https://files.pythonhosted.org/packages/0c/62/d2eb46264d4b157dae1275b573017abec435397aa59cbcdab6fc978a8af4/pyyaml-6.0.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:10892704fc220243f5305762e276552a0395f7beb4dbf9b14ec8fd43b57f126c", size = 775556, upload-time = "2025-09-25T21:32:01.31Z" }, - { url = "https://files.pythonhosted.org/packages/10/cb/16c3f2cf3266edd25aaa00d6c4350381c8b012ed6f5276675b9eba8d9ff4/pyyaml-6.0.3-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:850774a7879607d3a6f50d36d04f00ee69e7fc816450e5f7e58d7f17f1ae5c00", size = 882114, upload-time = "2025-09-25T21:32:03.376Z" }, - { url = "https://files.pythonhosted.org/packages/71/60/917329f640924b18ff085ab889a11c763e0b573da888e8404ff486657602/pyyaml-6.0.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b8bb0864c5a28024fac8a632c443c87c5aa6f215c0b126c449ae1a150412f31d", size = 806638, upload-time = "2025-09-25T21:32:04.553Z" }, - { url = "https://files.pythonhosted.org/packages/dd/6f/529b0f316a9fd167281a6c3826b5583e6192dba792dd55e3203d3f8e655a/pyyaml-6.0.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:1d37d57ad971609cf3c53ba6a7e365e40660e3be0e5175fa9f2365a379d6095a", size = 767463, upload-time = "2025-09-25T21:32:06.152Z" }, - { url = "https://files.pythonhosted.org/packages/f2/6a/b627b4e0c1dd03718543519ffb2f1deea4a1e6d42fbab8021936a4d22589/pyyaml-6.0.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:37503bfbfc9d2c40b344d06b2199cf0e96e97957ab1c1b546fd4f87e53e5d3e4", size = 794986, upload-time = "2025-09-25T21:32:07.367Z" }, - { url = "https://files.pythonhosted.org/packages/45/91/47a6e1c42d9ee337c4839208f30d9f09caa9f720ec7582917b264defc875/pyyaml-6.0.3-cp311-cp311-win32.whl", hash = "sha256:8098f252adfa6c80ab48096053f512f2321f0b998f98150cea9bd23d83e1467b", size = 142543, upload-time = "2025-09-25T21:32:08.95Z" }, - { url = "https://files.pythonhosted.org/packages/da/e3/ea007450a105ae919a72393cb06f122f288ef60bba2dc64b26e2646fa315/pyyaml-6.0.3-cp311-cp311-win_amd64.whl", hash = "sha256:9f3bfb4965eb874431221a3ff3fdcddc7e74e3b07799e0e84ca4a0f867d449bf", size = 158763, upload-time = "2025-09-25T21:32:09.96Z" }, - { url = "https://files.pythonhosted.org/packages/d1/33/422b98d2195232ca1826284a76852ad5a86fe23e31b009c9886b2d0fb8b2/pyyaml-6.0.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7f047e29dcae44602496db43be01ad42fc6f1cc0d8cd6c83d342306c32270196", size = 182063, upload-time = "2025-09-25T21:32:11.445Z" }, - { url = "https://files.pythonhosted.org/packages/89/a0/6cf41a19a1f2f3feab0e9c0b74134aa2ce6849093d5517a0c550fe37a648/pyyaml-6.0.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:fc09d0aa354569bc501d4e787133afc08552722d3ab34836a80547331bb5d4a0", size = 173973, upload-time = "2025-09-25T21:32:12.492Z" }, - { url = "https://files.pythonhosted.org/packages/ed/23/7a778b6bd0b9a8039df8b1b1d80e2e2ad78aa04171592c8a5c43a56a6af4/pyyaml-6.0.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:9149cad251584d5fb4981be1ecde53a1ca46c891a79788c0df828d2f166bda28", size = 775116, upload-time = "2025-09-25T21:32:13.652Z" }, - { url = "https://files.pythonhosted.org/packages/65/30/d7353c338e12baef4ecc1b09e877c1970bd3382789c159b4f89d6a70dc09/pyyaml-6.0.3-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:5fdec68f91a0c6739b380c83b951e2c72ac0197ace422360e6d5a959d8d97b2c", size = 844011, upload-time = "2025-09-25T21:32:15.21Z" }, - { url = "https://files.pythonhosted.org/packages/8b/9d/b3589d3877982d4f2329302ef98a8026e7f4443c765c46cfecc8858c6b4b/pyyaml-6.0.3-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ba1cc08a7ccde2d2ec775841541641e4548226580ab850948cbfda66a1befcdc", size = 807870, upload-time = "2025-09-25T21:32:16.431Z" }, - { url = "https://files.pythonhosted.org/packages/05/c0/b3be26a015601b822b97d9149ff8cb5ead58c66f981e04fedf4e762f4bd4/pyyaml-6.0.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8dc52c23056b9ddd46818a57b78404882310fb473d63f17b07d5c40421e47f8e", size = 761089, upload-time = "2025-09-25T21:32:17.56Z" }, - { url = "https://files.pythonhosted.org/packages/be/8e/98435a21d1d4b46590d5459a22d88128103f8da4c2d4cb8f14f2a96504e1/pyyaml-6.0.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:41715c910c881bc081f1e8872880d3c650acf13dfa8214bad49ed4cede7c34ea", size = 790181, upload-time = "2025-09-25T21:32:18.834Z" }, - { url = "https://files.pythonhosted.org/packages/74/93/7baea19427dcfbe1e5a372d81473250b379f04b1bd3c4c5ff825e2327202/pyyaml-6.0.3-cp312-cp312-win32.whl", hash = "sha256:96b533f0e99f6579b3d4d4995707cf36df9100d67e0c8303a0c55b27b5f99bc5", size = 137658, upload-time = "2025-09-25T21:32:20.209Z" }, - { url = "https://files.pythonhosted.org/packages/86/bf/899e81e4cce32febab4fb42bb97dcdf66bc135272882d1987881a4b519e9/pyyaml-6.0.3-cp312-cp312-win_amd64.whl", hash = "sha256:5fcd34e47f6e0b794d17de1b4ff496c00986e1c83f7ab2fb8fcfe9616ff7477b", size = 154003, upload-time = "2025-09-25T21:32:21.167Z" }, - { url = "https://files.pythonhosted.org/packages/1a/08/67bd04656199bbb51dbed1439b7f27601dfb576fb864099c7ef0c3e55531/pyyaml-6.0.3-cp312-cp312-win_arm64.whl", hash = "sha256:64386e5e707d03a7e172c0701abfb7e10f0fb753ee1d773128192742712a98fd", size = 140344, upload-time = "2025-09-25T21:32:22.617Z" }, - { url = "https://files.pythonhosted.org/packages/d1/11/0fd08f8192109f7169db964b5707a2f1e8b745d4e239b784a5a1dd80d1db/pyyaml-6.0.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:8da9669d359f02c0b91ccc01cac4a67f16afec0dac22c2ad09f46bee0697eba8", size = 181669, upload-time = "2025-09-25T21:32:23.673Z" }, - { url = "https://files.pythonhosted.org/packages/b1/16/95309993f1d3748cd644e02e38b75d50cbc0d9561d21f390a76242ce073f/pyyaml-6.0.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:2283a07e2c21a2aa78d9c4442724ec1eb15f5e42a723b99cb3d822d48f5f7ad1", size = 173252, upload-time = "2025-09-25T21:32:25.149Z" }, - { url = "https://files.pythonhosted.org/packages/50/31/b20f376d3f810b9b2371e72ef5adb33879b25edb7a6d072cb7ca0c486398/pyyaml-6.0.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:ee2922902c45ae8ccada2c5b501ab86c36525b883eff4255313a253a3160861c", size = 767081, upload-time = "2025-09-25T21:32:26.575Z" }, - { url = "https://files.pythonhosted.org/packages/49/1e/a55ca81e949270d5d4432fbbd19dfea5321eda7c41a849d443dc92fd1ff7/pyyaml-6.0.3-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:a33284e20b78bd4a18c8c2282d549d10bc8408a2a7ff57653c0cf0b9be0afce5", size = 841159, upload-time = "2025-09-25T21:32:27.727Z" }, - { url = "https://files.pythonhosted.org/packages/74/27/e5b8f34d02d9995b80abcef563ea1f8b56d20134d8f4e5e81733b1feceb2/pyyaml-6.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0f29edc409a6392443abf94b9cf89ce99889a1dd5376d94316ae5145dfedd5d6", size = 801626, upload-time = "2025-09-25T21:32:28.878Z" }, - { url = "https://files.pythonhosted.org/packages/f9/11/ba845c23988798f40e52ba45f34849aa8a1f2d4af4b798588010792ebad6/pyyaml-6.0.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f7057c9a337546edc7973c0d3ba84ddcdf0daa14533c2065749c9075001090e6", size = 753613, upload-time = "2025-09-25T21:32:30.178Z" }, - { url = "https://files.pythonhosted.org/packages/3d/e0/7966e1a7bfc0a45bf0a7fb6b98ea03fc9b8d84fa7f2229e9659680b69ee3/pyyaml-6.0.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:eda16858a3cab07b80edaf74336ece1f986ba330fdb8ee0d6c0d68fe82bc96be", size = 794115, upload-time = "2025-09-25T21:32:31.353Z" }, - { url = "https://files.pythonhosted.org/packages/de/94/980b50a6531b3019e45ddeada0626d45fa85cbe22300844a7983285bed3b/pyyaml-6.0.3-cp313-cp313-win32.whl", hash = "sha256:d0eae10f8159e8fdad514efdc92d74fd8d682c933a6dd088030f3834bc8e6b26", size = 137427, upload-time = "2025-09-25T21:32:32.58Z" }, - { url = "https://files.pythonhosted.org/packages/97/c9/39d5b874e8b28845e4ec2202b5da735d0199dbe5b8fb85f91398814a9a46/pyyaml-6.0.3-cp313-cp313-win_amd64.whl", hash = "sha256:79005a0d97d5ddabfeeea4cf676af11e647e41d81c9a7722a193022accdb6b7c", size = 154090, upload-time = "2025-09-25T21:32:33.659Z" }, - { url = "https://files.pythonhosted.org/packages/73/e8/2bdf3ca2090f68bb3d75b44da7bbc71843b19c9f2b9cb9b0f4ab7a5a4329/pyyaml-6.0.3-cp313-cp313-win_arm64.whl", hash = "sha256:5498cd1645aa724a7c71c8f378eb29ebe23da2fc0d7a08071d89469bf1d2defb", size = 140246, upload-time = "2025-09-25T21:32:34.663Z" }, - { url = "https://files.pythonhosted.org/packages/9d/8c/f4bd7f6465179953d3ac9bc44ac1a8a3e6122cf8ada906b4f96c60172d43/pyyaml-6.0.3-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:8d1fab6bb153a416f9aeb4b8763bc0f22a5586065f86f7664fc23339fc1c1fac", size = 181814, upload-time = "2025-09-25T21:32:35.712Z" }, - { url = "https://files.pythonhosted.org/packages/bd/9c/4d95bb87eb2063d20db7b60faa3840c1b18025517ae857371c4dd55a6b3a/pyyaml-6.0.3-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:34d5fcd24b8445fadc33f9cf348c1047101756fd760b4dacb5c3e99755703310", size = 173809, upload-time = "2025-09-25T21:32:36.789Z" }, - { url = "https://files.pythonhosted.org/packages/92/b5/47e807c2623074914e29dabd16cbbdd4bf5e9b2db9f8090fa64411fc5382/pyyaml-6.0.3-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:501a031947e3a9025ed4405a168e6ef5ae3126c59f90ce0cd6f2bfc477be31b7", size = 766454, upload-time = "2025-09-25T21:32:37.966Z" }, - { url = "https://files.pythonhosted.org/packages/02/9e/e5e9b168be58564121efb3de6859c452fccde0ab093d8438905899a3a483/pyyaml-6.0.3-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:b3bc83488de33889877a0f2543ade9f70c67d66d9ebb4ac959502e12de895788", size = 836355, upload-time = "2025-09-25T21:32:39.178Z" }, - { url = "https://files.pythonhosted.org/packages/88/f9/16491d7ed2a919954993e48aa941b200f38040928474c9e85ea9e64222c3/pyyaml-6.0.3-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c458b6d084f9b935061bc36216e8a69a7e293a2f1e68bf956dcd9e6cbcd143f5", size = 794175, upload-time = "2025-09-25T21:32:40.865Z" }, - { url = "https://files.pythonhosted.org/packages/dd/3f/5989debef34dc6397317802b527dbbafb2b4760878a53d4166579111411e/pyyaml-6.0.3-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:7c6610def4f163542a622a73fb39f534f8c101d690126992300bf3207eab9764", size = 755228, upload-time = "2025-09-25T21:32:42.084Z" }, - { url = "https://files.pythonhosted.org/packages/d7/ce/af88a49043cd2e265be63d083fc75b27b6ed062f5f9fd6cdc223ad62f03e/pyyaml-6.0.3-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:5190d403f121660ce8d1d2c1bb2ef1bd05b5f68533fc5c2ea899bd15f4399b35", size = 789194, upload-time = "2025-09-25T21:32:43.362Z" }, - { url = "https://files.pythonhosted.org/packages/23/20/bb6982b26a40bb43951265ba29d4c246ef0ff59c9fdcdf0ed04e0687de4d/pyyaml-6.0.3-cp314-cp314-win_amd64.whl", hash = "sha256:4a2e8cebe2ff6ab7d1050ecd59c25d4c8bd7e6f400f5f82b96557ac0abafd0ac", size = 156429, upload-time = "2025-09-25T21:32:57.844Z" }, - { url = "https://files.pythonhosted.org/packages/f4/f4/a4541072bb9422c8a883ab55255f918fa378ecf083f5b85e87fc2b4eda1b/pyyaml-6.0.3-cp314-cp314-win_arm64.whl", hash = "sha256:93dda82c9c22deb0a405ea4dc5f2d0cda384168e466364dec6255b293923b2f3", size = 143912, upload-time = "2025-09-25T21:32:59.247Z" }, - { url = "https://files.pythonhosted.org/packages/7c/f9/07dd09ae774e4616edf6cda684ee78f97777bdd15847253637a6f052a62f/pyyaml-6.0.3-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:02893d100e99e03eda1c8fd5c441d8c60103fd175728e23e431db1b589cf5ab3", size = 189108, upload-time = "2025-09-25T21:32:44.377Z" }, - { url = "https://files.pythonhosted.org/packages/4e/78/8d08c9fb7ce09ad8c38ad533c1191cf27f7ae1effe5bb9400a46d9437fcf/pyyaml-6.0.3-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:c1ff362665ae507275af2853520967820d9124984e0f7466736aea23d8611fba", size = 183641, upload-time = "2025-09-25T21:32:45.407Z" }, - { url = "https://files.pythonhosted.org/packages/7b/5b/3babb19104a46945cf816d047db2788bcaf8c94527a805610b0289a01c6b/pyyaml-6.0.3-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6adc77889b628398debc7b65c073bcb99c4a0237b248cacaf3fe8a557563ef6c", size = 831901, upload-time = "2025-09-25T21:32:48.83Z" }, - { url = "https://files.pythonhosted.org/packages/8b/cc/dff0684d8dc44da4d22a13f35f073d558c268780ce3c6ba1b87055bb0b87/pyyaml-6.0.3-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:a80cb027f6b349846a3bf6d73b5e95e782175e52f22108cfa17876aaeff93702", size = 861132, upload-time = "2025-09-25T21:32:50.149Z" }, - { url = "https://files.pythonhosted.org/packages/b1/5e/f77dc6b9036943e285ba76b49e118d9ea929885becb0a29ba8a7c75e29fe/pyyaml-6.0.3-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:00c4bdeba853cc34e7dd471f16b4114f4162dc03e6b7afcc2128711f0eca823c", size = 839261, upload-time = "2025-09-25T21:32:51.808Z" }, - { url = "https://files.pythonhosted.org/packages/ce/88/a9db1376aa2a228197c58b37302f284b5617f56a5d959fd1763fb1675ce6/pyyaml-6.0.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:66e1674c3ef6f541c35191caae2d429b967b99e02040f5ba928632d9a7f0f065", size = 805272, upload-time = "2025-09-25T21:32:52.941Z" }, - { url = "https://files.pythonhosted.org/packages/da/92/1446574745d74df0c92e6aa4a7b0b3130706a4142b2d1a5869f2eaa423c6/pyyaml-6.0.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:16249ee61e95f858e83976573de0f5b2893b3677ba71c9dd36b9cf8be9ac6d65", size = 829923, upload-time = "2025-09-25T21:32:54.537Z" }, - { url = "https://files.pythonhosted.org/packages/f0/7a/1c7270340330e575b92f397352af856a8c06f230aa3e76f86b39d01b416a/pyyaml-6.0.3-cp314-cp314t-win_amd64.whl", hash = "sha256:4ad1906908f2f5ae4e5a8ddfce73c320c2a1429ec52eafd27138b7f1cbe341c9", size = 174062, upload-time = "2025-09-25T21:32:55.767Z" }, - { url = "https://files.pythonhosted.org/packages/f1/12/de94a39c2ef588c7e6455cfbe7343d3b2dc9d6b6b2f40c4c6565744c873d/pyyaml-6.0.3-cp314-cp314t-win_arm64.whl", hash = "sha256:ebc55a14a21cb14062aa4162f906cd962b28e2e9ea38f9b4391244cd8de4ae0b", size = 149341, upload-time = "2025-09-25T21:32:56.828Z" }, -] - -[[package]] -name = "referencing" -version = "0.37.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "attrs" }, - { name = "rpds-py" }, - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/22/f5/df4e9027acead3ecc63e50fe1e36aca1523e1719559c499951bb4b53188f/referencing-0.37.0.tar.gz", hash = "sha256:44aefc3142c5b842538163acb373e24cce6632bd54bdb01b21ad5863489f50d8", size = 78036, upload-time = "2025-10-13T15:30:48.871Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl", hash = "sha256:381329a9f99628c9069361716891d34ad94af76e461dcb0335825aecc7692231", size = 26766, upload-time = "2025-10-13T15:30:47.625Z" }, -] - -[[package]] -name = "requests" -version = "2.32.5" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "certifi" }, - { name = "charset-normalizer" }, - { name = "idna" }, - { name = "urllib3" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/c9/74/b3ff8e6c8446842c3f5c837e9c3dfcfe2018ea6ecef224c710c85ef728f4/requests-2.32.5.tar.gz", hash = "sha256:dbba0bac56e100853db0ea71b82b4dfd5fe2bf6d3754a8893c3af500cec7d7cf", size = 134517, upload-time = "2025-08-18T20:46:02.573Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl", hash = "sha256:2462f94637a34fd532264295e186976db0f5d453d1cdd31473c85a6a161affb6", size = 64738, upload-time = "2025-08-18T20:46:00.542Z" }, -] - -[[package]] -name = "rpds-py" -version = "0.28.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/48/dc/95f074d43452b3ef5d06276696ece4b3b5d696e7c9ad7173c54b1390cd70/rpds_py-0.28.0.tar.gz", hash = "sha256:abd4df20485a0983e2ca334a216249b6186d6e3c1627e106651943dbdb791aea", size = 27419, upload-time = "2025-10-22T22:24:29.327Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/82/f8/13bb772dc7cbf2c3c5b816febc34fa0cb2c64a08e0569869585684ce6631/rpds_py-0.28.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:7b6013db815417eeb56b2d9d7324e64fcd4fa289caeee6e7a78b2e11fc9b438a", size = 362820, upload-time = "2025-10-22T22:21:15.074Z" }, - { url = "https://files.pythonhosted.org/packages/84/91/6acce964aab32469c3dbe792cb041a752d64739c534e9c493c701ef0c032/rpds_py-0.28.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:1a4c6b05c685c0c03f80dabaeb73e74218c49deea965ca63f76a752807397207", size = 348499, upload-time = "2025-10-22T22:21:17.658Z" }, - { url = "https://files.pythonhosted.org/packages/f1/93/c05bb1f4f5e0234db7c4917cb8dd5e2e0a9a7b26dc74b1b7bee3c9cfd477/rpds_py-0.28.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f4794c6c3fbe8f9ac87699b131a1f26e7b4abcf6d828da46a3a52648c7930eba", size = 379356, upload-time = "2025-10-22T22:21:19.847Z" }, - { url = "https://files.pythonhosted.org/packages/5c/37/e292da436f0773e319753c567263427cdf6c645d30b44f09463ff8216cda/rpds_py-0.28.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:2e8456b6ee5527112ff2354dd9087b030e3429e43a74f480d4a5ca79d269fd85", size = 390151, upload-time = "2025-10-22T22:21:21.569Z" }, - { url = "https://files.pythonhosted.org/packages/76/87/a4e3267131616e8faf10486dc00eaedf09bd61c87f01e5ef98e782ee06c9/rpds_py-0.28.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:beb880a9ca0a117415f241f66d56025c02037f7c4efc6fe59b5b8454f1eaa50d", size = 524831, upload-time = "2025-10-22T22:21:23.394Z" }, - { url = "https://files.pythonhosted.org/packages/e1/c8/4a4ca76f0befae9515da3fad11038f0fce44f6bb60b21fe9d9364dd51fb0/rpds_py-0.28.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6897bebb118c44b38c9cb62a178e09f1593c949391b9a1a6fe777ccab5934ee7", size = 404687, upload-time = "2025-10-22T22:21:25.201Z" }, - { url = "https://files.pythonhosted.org/packages/6a/65/118afe854424456beafbbebc6b34dcf6d72eae3a08b4632bc4220f8240d9/rpds_py-0.28.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b1b553dd06e875249fd43efd727785efb57a53180e0fde321468222eabbeaafa", size = 382683, upload-time = "2025-10-22T22:21:26.536Z" }, - { url = "https://files.pythonhosted.org/packages/f7/bc/0625064041fb3a0c77ecc8878c0e8341b0ae27ad0f00cf8f2b57337a1e63/rpds_py-0.28.0-cp310-cp310-manylinux_2_31_riscv64.whl", hash = "sha256:f0b2044fdddeea5b05df832e50d2a06fe61023acb44d76978e1b060206a8a476", size = 398927, upload-time = "2025-10-22T22:21:27.864Z" }, - { url = "https://files.pythonhosted.org/packages/5d/1a/fed7cf2f1ee8a5e4778f2054153f2cfcf517748875e2f5b21cf8907cd77d/rpds_py-0.28.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:05cf1e74900e8da73fa08cc76c74a03345e5a3e37691d07cfe2092d7d8e27b04", size = 411590, upload-time = "2025-10-22T22:21:29.474Z" }, - { url = "https://files.pythonhosted.org/packages/c1/64/a8e0f67fa374a6c472dbb0afdaf1ef744724f165abb6899f20e2f1563137/rpds_py-0.28.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:efd489fec7c311dae25e94fe7eeda4b3d06be71c68f2cf2e8ef990ffcd2cd7e8", size = 559843, upload-time = "2025-10-22T22:21:30.917Z" }, - { url = "https://files.pythonhosted.org/packages/a9/ea/e10353f6d7c105be09b8135b72787a65919971ae0330ad97d87e4e199880/rpds_py-0.28.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:ada7754a10faacd4f26067e62de52d6af93b6d9542f0df73c57b9771eb3ba9c4", size = 584188, upload-time = "2025-10-22T22:21:32.827Z" }, - { url = "https://files.pythonhosted.org/packages/18/b0/a19743e0763caf0c89f6fc6ba6fbd9a353b24ffb4256a492420c5517da5a/rpds_py-0.28.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:c2a34fd26588949e1e7977cfcbb17a9a42c948c100cab890c6d8d823f0586457", size = 550052, upload-time = "2025-10-22T22:21:34.702Z" }, - { url = "https://files.pythonhosted.org/packages/de/bc/ec2c004f6c7d6ab1e25dae875cdb1aee087c3ebed5b73712ed3000e3851a/rpds_py-0.28.0-cp310-cp310-win32.whl", hash = "sha256:f9174471d6920cbc5e82a7822de8dfd4dcea86eb828b04fc8c6519a77b0ee51e", size = 215110, upload-time = "2025-10-22T22:21:36.645Z" }, - { url = "https://files.pythonhosted.org/packages/6c/de/4ce8abf59674e17187023933547d2018363e8fc76ada4f1d4d22871ccb6e/rpds_py-0.28.0-cp310-cp310-win_amd64.whl", hash = "sha256:6e32dd207e2c4f8475257a3540ab8a93eff997abfa0a3fdb287cae0d6cd874b8", size = 223850, upload-time = "2025-10-22T22:21:38.006Z" }, - { url = "https://files.pythonhosted.org/packages/a6/34/058d0db5471c6be7bef82487ad5021ff8d1d1d27794be8730aad938649cf/rpds_py-0.28.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:03065002fd2e287725d95fbc69688e0c6daf6c6314ba38bdbaa3895418e09296", size = 362344, upload-time = "2025-10-22T22:21:39.713Z" }, - { url = "https://files.pythonhosted.org/packages/5d/67/9503f0ec8c055a0782880f300c50a2b8e5e72eb1f94dfc2053da527444dd/rpds_py-0.28.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:28ea02215f262b6d078daec0b45344c89e161eab9526b0d898221d96fdda5f27", size = 348440, upload-time = "2025-10-22T22:21:41.056Z" }, - { url = "https://files.pythonhosted.org/packages/68/2e/94223ee9b32332a41d75b6f94b37b4ce3e93878a556fc5f152cbd856a81f/rpds_py-0.28.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25dbade8fbf30bcc551cb352376c0ad64b067e4fc56f90e22ba70c3ce205988c", size = 379068, upload-time = "2025-10-22T22:21:42.593Z" }, - { url = "https://files.pythonhosted.org/packages/b4/25/54fd48f9f680cfc44e6a7f39a5fadf1d4a4a1fd0848076af4a43e79f998c/rpds_py-0.28.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:3c03002f54cc855860bfdc3442928ffdca9081e73b5b382ed0b9e8efe6e5e205", size = 390518, upload-time = "2025-10-22T22:21:43.998Z" }, - { url = "https://files.pythonhosted.org/packages/1b/85/ac258c9c27f2ccb1bd5d0697e53a82ebcf8088e3186d5d2bf8498ee7ed44/rpds_py-0.28.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b9699fa7990368b22032baf2b2dce1f634388e4ffc03dfefaaac79f4695edc95", size = 525319, upload-time = "2025-10-22T22:21:45.645Z" }, - { url = "https://files.pythonhosted.org/packages/40/cb/c6734774789566d46775f193964b76627cd5f42ecf246d257ce84d1912ed/rpds_py-0.28.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b9b06fe1a75e05e0713f06ea0c89ecb6452210fd60e2f1b6ddc1067b990e08d9", size = 404896, upload-time = "2025-10-22T22:21:47.544Z" }, - { url = "https://files.pythonhosted.org/packages/1f/53/14e37ce83202c632c89b0691185dca9532288ff9d390eacae3d2ff771bae/rpds_py-0.28.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ac9f83e7b326a3f9ec3ef84cda98fb0a74c7159f33e692032233046e7fd15da2", size = 382862, upload-time = "2025-10-22T22:21:49.176Z" }, - { url = "https://files.pythonhosted.org/packages/6a/83/f3642483ca971a54d60caa4449f9d6d4dbb56a53e0072d0deff51b38af74/rpds_py-0.28.0-cp311-cp311-manylinux_2_31_riscv64.whl", hash = "sha256:0d3259ea9ad8743a75a43eb7819324cdab393263c91be86e2d1901ee65c314e0", size = 398848, upload-time = "2025-10-22T22:21:51.024Z" }, - { url = "https://files.pythonhosted.org/packages/44/09/2d9c8b2f88e399b4cfe86efdf2935feaf0394e4f14ab30c6c5945d60af7d/rpds_py-0.28.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9a7548b345f66f6695943b4ef6afe33ccd3f1b638bd9afd0f730dd255c249c9e", size = 412030, upload-time = "2025-10-22T22:21:52.665Z" }, - { url = "https://files.pythonhosted.org/packages/dd/f5/e1cec473d4bde6df1fd3738be8e82d64dd0600868e76e92dfeaebbc2d18f/rpds_py-0.28.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c9a40040aa388b037eb39416710fbcce9443498d2eaab0b9b45ae988b53f5c67", size = 559700, upload-time = "2025-10-22T22:21:54.123Z" }, - { url = "https://files.pythonhosted.org/packages/8d/be/73bb241c1649edbf14e98e9e78899c2c5e52bbe47cb64811f44d2cc11808/rpds_py-0.28.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:8f60c7ea34e78c199acd0d3cda37a99be2c861dd2b8cf67399784f70c9f8e57d", size = 584581, upload-time = "2025-10-22T22:21:56.102Z" }, - { url = "https://files.pythonhosted.org/packages/9c/9c/ffc6e9218cd1eb5c2c7dbd276c87cd10e8c2232c456b554169eb363381df/rpds_py-0.28.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:1571ae4292649100d743b26d5f9c63503bb1fedf538a8f29a98dce2d5ba6b4e6", size = 549981, upload-time = "2025-10-22T22:21:58.253Z" }, - { url = "https://files.pythonhosted.org/packages/5f/50/da8b6d33803a94df0149345ee33e5d91ed4d25fc6517de6a25587eae4133/rpds_py-0.28.0-cp311-cp311-win32.whl", hash = "sha256:5cfa9af45e7c1140af7321fa0bef25b386ee9faa8928c80dc3a5360971a29e8c", size = 214729, upload-time = "2025-10-22T22:21:59.625Z" }, - { url = "https://files.pythonhosted.org/packages/12/fd/b0f48c4c320ee24c8c20df8b44acffb7353991ddf688af01eef5f93d7018/rpds_py-0.28.0-cp311-cp311-win_amd64.whl", hash = "sha256:dd8d86b5d29d1b74100982424ba53e56033dc47720a6de9ba0259cf81d7cecaa", size = 223977, upload-time = "2025-10-22T22:22:01.092Z" }, - { url = "https://files.pythonhosted.org/packages/b4/21/c8e77a2ac66e2ec4e21f18a04b4e9a0417ecf8e61b5eaeaa9360a91713b4/rpds_py-0.28.0-cp311-cp311-win_arm64.whl", hash = "sha256:4e27d3a5709cc2b3e013bf93679a849213c79ae0573f9b894b284b55e729e120", size = 217326, upload-time = "2025-10-22T22:22:02.944Z" }, - { url = "https://files.pythonhosted.org/packages/b8/5c/6c3936495003875fe7b14f90ea812841a08fca50ab26bd840e924097d9c8/rpds_py-0.28.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:6b4f28583a4f247ff60cd7bdda83db8c3f5b05a7a82ff20dd4b078571747708f", size = 366439, upload-time = "2025-10-22T22:22:04.525Z" }, - { url = "https://files.pythonhosted.org/packages/56/f9/a0f1ca194c50aa29895b442771f036a25b6c41a35e4f35b1a0ea713bedae/rpds_py-0.28.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:d678e91b610c29c4b3d52a2c148b641df2b4676ffe47c59f6388d58b99cdc424", size = 348170, upload-time = "2025-10-22T22:22:06.397Z" }, - { url = "https://files.pythonhosted.org/packages/18/ea/42d243d3a586beb72c77fa5def0487daf827210069a95f36328e869599ea/rpds_py-0.28.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e819e0e37a44a78e1383bf1970076e2ccc4dc8c2bbaa2f9bd1dc987e9afff628", size = 378838, upload-time = "2025-10-22T22:22:07.932Z" }, - { url = "https://files.pythonhosted.org/packages/e7/78/3de32e18a94791af8f33601402d9d4f39613136398658412a4e0b3047327/rpds_py-0.28.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5ee514e0f0523db5d3fb171f397c54875dbbd69760a414dccf9d4d7ad628b5bd", size = 393299, upload-time = "2025-10-22T22:22:09.435Z" }, - { url = "https://files.pythonhosted.org/packages/13/7e/4bdb435afb18acea2eb8a25ad56b956f28de7c59f8a1d32827effa0d4514/rpds_py-0.28.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5f3fa06d27fdcee47f07a39e02862da0100cb4982508f5ead53ec533cd5fe55e", size = 518000, upload-time = "2025-10-22T22:22:11.326Z" }, - { url = "https://files.pythonhosted.org/packages/31/d0/5f52a656875cdc60498ab035a7a0ac8f399890cc1ee73ebd567bac4e39ae/rpds_py-0.28.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:46959ef2e64f9e4a41fc89aa20dbca2b85531f9a72c21099a3360f35d10b0d5a", size = 408746, upload-time = "2025-10-22T22:22:13.143Z" }, - { url = "https://files.pythonhosted.org/packages/3e/cd/49ce51767b879cde77e7ad9fae164ea15dce3616fe591d9ea1df51152706/rpds_py-0.28.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8455933b4bcd6e83fde3fefc987a023389c4b13f9a58c8d23e4b3f6d13f78c84", size = 386379, upload-time = "2025-10-22T22:22:14.602Z" }, - { url = "https://files.pythonhosted.org/packages/6a/99/e4e1e1ee93a98f72fc450e36c0e4d99c35370220e815288e3ecd2ec36a2a/rpds_py-0.28.0-cp312-cp312-manylinux_2_31_riscv64.whl", hash = "sha256:ad50614a02c8c2962feebe6012b52f9802deec4263946cddea37aaf28dd25a66", size = 401280, upload-time = "2025-10-22T22:22:16.063Z" }, - { url = "https://files.pythonhosted.org/packages/61/35/e0c6a57488392a8b319d2200d03dad2b29c0db9996f5662c3b02d0b86c02/rpds_py-0.28.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e5deca01b271492553fdb6c7fd974659dce736a15bae5dad7ab8b93555bceb28", size = 412365, upload-time = "2025-10-22T22:22:17.504Z" }, - { url = "https://files.pythonhosted.org/packages/ff/6a/841337980ea253ec797eb084665436007a1aad0faac1ba097fb906c5f69c/rpds_py-0.28.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:735f8495a13159ce6a0d533f01e8674cec0c57038c920495f87dcb20b3ddb48a", size = 559573, upload-time = "2025-10-22T22:22:19.108Z" }, - { url = "https://files.pythonhosted.org/packages/e7/5e/64826ec58afd4c489731f8b00729c5f6afdb86f1df1df60bfede55d650bb/rpds_py-0.28.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:961ca621ff10d198bbe6ba4957decca61aa2a0c56695384c1d6b79bf61436df5", size = 583973, upload-time = "2025-10-22T22:22:20.768Z" }, - { url = "https://files.pythonhosted.org/packages/b6/ee/44d024b4843f8386a4eeaa4c171b3d31d55f7177c415545fd1a24c249b5d/rpds_py-0.28.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:2374e16cc9131022e7d9a8f8d65d261d9ba55048c78f3b6e017971a4f5e6353c", size = 553800, upload-time = "2025-10-22T22:22:22.25Z" }, - { url = "https://files.pythonhosted.org/packages/7d/89/33e675dccff11a06d4d85dbb4d1865f878d5020cbb69b2c1e7b2d3f82562/rpds_py-0.28.0-cp312-cp312-win32.whl", hash = "sha256:d15431e334fba488b081d47f30f091e5d03c18527c325386091f31718952fe08", size = 216954, upload-time = "2025-10-22T22:22:24.105Z" }, - { url = "https://files.pythonhosted.org/packages/af/36/45f6ebb3210887e8ee6dbf1bc710ae8400bb417ce165aaf3024b8360d999/rpds_py-0.28.0-cp312-cp312-win_amd64.whl", hash = "sha256:a410542d61fc54710f750d3764380b53bf09e8c4edbf2f9141a82aa774a04f7c", size = 227844, upload-time = "2025-10-22T22:22:25.551Z" }, - { url = "https://files.pythonhosted.org/packages/57/91/f3fb250d7e73de71080f9a221d19bd6a1c1eb0d12a1ea26513f6c1052ad6/rpds_py-0.28.0-cp312-cp312-win_arm64.whl", hash = "sha256:1f0cfd1c69e2d14f8c892b893997fa9a60d890a0c8a603e88dca4955f26d1edd", size = 217624, upload-time = "2025-10-22T22:22:26.914Z" }, - { url = "https://files.pythonhosted.org/packages/d3/03/ce566d92611dfac0085c2f4b048cd53ed7c274a5c05974b882a908d540a2/rpds_py-0.28.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:e9e184408a0297086f880556b6168fa927d677716f83d3472ea333b42171ee3b", size = 366235, upload-time = "2025-10-22T22:22:28.397Z" }, - { url = "https://files.pythonhosted.org/packages/00/34/1c61da1b25592b86fd285bd7bd8422f4c9d748a7373b46126f9ae792a004/rpds_py-0.28.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:edd267266a9b0448f33dc465a97cfc5d467594b600fe28e7fa2f36450e03053a", size = 348241, upload-time = "2025-10-22T22:22:30.171Z" }, - { url = "https://files.pythonhosted.org/packages/fc/00/ed1e28616848c61c493a067779633ebf4b569eccaacf9ccbdc0e7cba2b9d/rpds_py-0.28.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:85beb8b3f45e4e32f6802fb6cd6b17f615ef6c6a52f265371fb916fae02814aa", size = 378079, upload-time = "2025-10-22T22:22:31.644Z" }, - { url = "https://files.pythonhosted.org/packages/11/b2/ccb30333a16a470091b6e50289adb4d3ec656fd9951ba8c5e3aaa0746a67/rpds_py-0.28.0-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:d2412be8d00a1b895f8ad827cc2116455196e20ed994bb704bf138fe91a42724", size = 393151, upload-time = "2025-10-22T22:22:33.453Z" }, - { url = "https://files.pythonhosted.org/packages/8c/d0/73e2217c3ee486d555cb84920597480627d8c0240ff3062005c6cc47773e/rpds_py-0.28.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cf128350d384b777da0e68796afdcebc2e9f63f0e9f242217754e647f6d32491", size = 517520, upload-time = "2025-10-22T22:22:34.949Z" }, - { url = "https://files.pythonhosted.org/packages/c4/91/23efe81c700427d0841a4ae7ea23e305654381831e6029499fe80be8a071/rpds_py-0.28.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a2036d09b363aa36695d1cc1a97b36865597f4478470b0697b5ee9403f4fe399", size = 408699, upload-time = "2025-10-22T22:22:36.584Z" }, - { url = "https://files.pythonhosted.org/packages/ca/ee/a324d3198da151820a326c1f988caaa4f37fc27955148a76fff7a2d787a9/rpds_py-0.28.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b8e1e9be4fa6305a16be628959188e4fd5cd6f1b0e724d63c6d8b2a8adf74ea6", size = 385720, upload-time = "2025-10-22T22:22:38.014Z" }, - { url = "https://files.pythonhosted.org/packages/19/ad/e68120dc05af8b7cab4a789fccd8cdcf0fe7e6581461038cc5c164cd97d2/rpds_py-0.28.0-cp313-cp313-manylinux_2_31_riscv64.whl", hash = "sha256:0a403460c9dd91a7f23fc3188de6d8977f1d9603a351d5db6cf20aaea95b538d", size = 401096, upload-time = "2025-10-22T22:22:39.869Z" }, - { url = "https://files.pythonhosted.org/packages/99/90/c1e070620042459d60df6356b666bb1f62198a89d68881816a7ed121595a/rpds_py-0.28.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d7366b6553cdc805abcc512b849a519167db8f5e5c3472010cd1228b224265cb", size = 411465, upload-time = "2025-10-22T22:22:41.395Z" }, - { url = "https://files.pythonhosted.org/packages/68/61/7c195b30d57f1b8d5970f600efee72a4fad79ec829057972e13a0370fd24/rpds_py-0.28.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:5b43c6a3726efd50f18d8120ec0551241c38785b68952d240c45ea553912ac41", size = 558832, upload-time = "2025-10-22T22:22:42.871Z" }, - { url = "https://files.pythonhosted.org/packages/b0/3d/06f3a718864773f69941d4deccdf18e5e47dd298b4628062f004c10f3b34/rpds_py-0.28.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:0cb7203c7bc69d7c1585ebb33a2e6074492d2fc21ad28a7b9d40457ac2a51ab7", size = 583230, upload-time = "2025-10-22T22:22:44.877Z" }, - { url = "https://files.pythonhosted.org/packages/66/df/62fc783781a121e77fee9a21ead0a926f1b652280a33f5956a5e7833ed30/rpds_py-0.28.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:7a52a5169c664dfb495882adc75c304ae1d50df552fbd68e100fdc719dee4ff9", size = 553268, upload-time = "2025-10-22T22:22:46.441Z" }, - { url = "https://files.pythonhosted.org/packages/84/85/d34366e335140a4837902d3dea89b51f087bd6a63c993ebdff59e93ee61d/rpds_py-0.28.0-cp313-cp313-win32.whl", hash = "sha256:2e42456917b6687215b3e606ab46aa6bca040c77af7df9a08a6dcfe8a4d10ca5", size = 217100, upload-time = "2025-10-22T22:22:48.342Z" }, - { url = "https://files.pythonhosted.org/packages/3c/1c/f25a3f3752ad7601476e3eff395fe075e0f7813fbb9862bd67c82440e880/rpds_py-0.28.0-cp313-cp313-win_amd64.whl", hash = "sha256:e0a0311caedc8069d68fc2bf4c9019b58a2d5ce3cd7cb656c845f1615b577e1e", size = 227759, upload-time = "2025-10-22T22:22:50.219Z" }, - { url = "https://files.pythonhosted.org/packages/e0/d6/5f39b42b99615b5bc2f36ab90423ea404830bdfee1c706820943e9a645eb/rpds_py-0.28.0-cp313-cp313-win_arm64.whl", hash = "sha256:04c1b207ab8b581108801528d59ad80aa83bb170b35b0ddffb29c20e411acdc1", size = 217326, upload-time = "2025-10-22T22:22:51.647Z" }, - { url = "https://files.pythonhosted.org/packages/5c/8b/0c69b72d1cee20a63db534be0df271effe715ef6c744fdf1ff23bb2b0b1c/rpds_py-0.28.0-cp313-cp313t-macosx_10_12_x86_64.whl", hash = "sha256:f296ea3054e11fc58ad42e850e8b75c62d9a93a9f981ad04b2e5ae7d2186ff9c", size = 355736, upload-time = "2025-10-22T22:22:53.211Z" }, - { url = "https://files.pythonhosted.org/packages/f7/6d/0c2ee773cfb55c31a8514d2cece856dd299170a49babd50dcffb15ddc749/rpds_py-0.28.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:5a7306c19b19005ad98468fcefeb7100b19c79fc23a5f24a12e06d91181193fa", size = 342677, upload-time = "2025-10-22T22:22:54.723Z" }, - { url = "https://files.pythonhosted.org/packages/e2/1c/22513ab25a27ea205144414724743e305e8153e6abe81833b5e678650f5a/rpds_py-0.28.0-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e5d9b86aa501fed9862a443c5c3116f6ead8bc9296185f369277c42542bd646b", size = 371847, upload-time = "2025-10-22T22:22:56.295Z" }, - { url = "https://files.pythonhosted.org/packages/60/07/68e6ccdb4b05115ffe61d31afc94adef1833d3a72f76c9632d4d90d67954/rpds_py-0.28.0-cp313-cp313t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e5bbc701eff140ba0e872691d573b3d5d30059ea26e5785acba9132d10c8c31d", size = 381800, upload-time = "2025-10-22T22:22:57.808Z" }, - { url = "https://files.pythonhosted.org/packages/73/bf/6d6d15df80781d7f9f368e7c1a00caf764436518c4877fb28b029c4624af/rpds_py-0.28.0-cp313-cp313t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9a5690671cd672a45aa8616d7374fdf334a1b9c04a0cac3c854b1136e92374fe", size = 518827, upload-time = "2025-10-22T22:22:59.826Z" }, - { url = "https://files.pythonhosted.org/packages/7b/d3/2decbb2976cc452cbf12a2b0aaac5f1b9dc5dd9d1f7e2509a3ee00421249/rpds_py-0.28.0-cp313-cp313t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9f1d92ecea4fa12f978a367c32a5375a1982834649cdb96539dcdc12e609ab1a", size = 399471, upload-time = "2025-10-22T22:23:01.968Z" }, - { url = "https://files.pythonhosted.org/packages/b1/2c/f30892f9e54bd02e5faca3f6a26d6933c51055e67d54818af90abed9748e/rpds_py-0.28.0-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8d252db6b1a78d0a3928b6190156042d54c93660ce4d98290d7b16b5296fb7cc", size = 377578, upload-time = "2025-10-22T22:23:03.52Z" }, - { url = "https://files.pythonhosted.org/packages/f0/5d/3bce97e5534157318f29ac06bf2d279dae2674ec12f7cb9c12739cee64d8/rpds_py-0.28.0-cp313-cp313t-manylinux_2_31_riscv64.whl", hash = "sha256:d61b355c3275acb825f8777d6c4505f42b5007e357af500939d4a35b19177259", size = 390482, upload-time = "2025-10-22T22:23:05.391Z" }, - { url = "https://files.pythonhosted.org/packages/e3/f0/886bd515ed457b5bd93b166175edb80a0b21a210c10e993392127f1e3931/rpds_py-0.28.0-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:acbe5e8b1026c0c580d0321c8aae4b0a1e1676861d48d6e8c6586625055b606a", size = 402447, upload-time = "2025-10-22T22:23:06.93Z" }, - { url = "https://files.pythonhosted.org/packages/42/b5/71e8777ac55e6af1f4f1c05b47542a1eaa6c33c1cf0d300dca6a1c6e159a/rpds_py-0.28.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:8aa23b6f0fc59b85b4c7d89ba2965af274346f738e8d9fc2455763602e62fd5f", size = 552385, upload-time = "2025-10-22T22:23:08.557Z" }, - { url = "https://files.pythonhosted.org/packages/5d/cb/6ca2d70cbda5a8e36605e7788c4aa3bea7c17d71d213465a5a675079b98d/rpds_py-0.28.0-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:7b14b0c680286958817c22d76fcbca4800ddacef6f678f3a7c79a1fe7067fe37", size = 575642, upload-time = "2025-10-22T22:23:10.348Z" }, - { url = "https://files.pythonhosted.org/packages/4a/d4/407ad9960ca7856d7b25c96dcbe019270b5ffdd83a561787bc682c797086/rpds_py-0.28.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:bcf1d210dfee61a6c86551d67ee1031899c0fdbae88b2d44a569995d43797712", size = 544507, upload-time = "2025-10-22T22:23:12.434Z" }, - { url = "https://files.pythonhosted.org/packages/51/31/2f46fe0efcac23fbf5797c6b6b7e1c76f7d60773e525cb65fcbc582ee0f2/rpds_py-0.28.0-cp313-cp313t-win32.whl", hash = "sha256:3aa4dc0fdab4a7029ac63959a3ccf4ed605fee048ba67ce89ca3168da34a1342", size = 205376, upload-time = "2025-10-22T22:23:13.979Z" }, - { url = "https://files.pythonhosted.org/packages/92/e4/15947bda33cbedfc134490a41841ab8870a72a867a03d4969d886f6594a2/rpds_py-0.28.0-cp313-cp313t-win_amd64.whl", hash = "sha256:7b7d9d83c942855e4fdcfa75d4f96f6b9e272d42fffcb72cd4bb2577db2e2907", size = 215907, upload-time = "2025-10-22T22:23:15.5Z" }, - { url = "https://files.pythonhosted.org/packages/08/47/ffe8cd7a6a02833b10623bf765fbb57ce977e9a4318ca0e8cf97e9c3d2b3/rpds_py-0.28.0-cp314-cp314-macosx_10_12_x86_64.whl", hash = "sha256:dcdcb890b3ada98a03f9f2bb108489cdc7580176cb73b4f2d789e9a1dac1d472", size = 353830, upload-time = "2025-10-22T22:23:17.03Z" }, - { url = "https://files.pythonhosted.org/packages/f9/9f/890f36cbd83a58491d0d91ae0db1702639edb33fb48eeb356f80ecc6b000/rpds_py-0.28.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:f274f56a926ba2dc02976ca5b11c32855cbd5925534e57cfe1fda64e04d1add2", size = 341819, upload-time = "2025-10-22T22:23:18.57Z" }, - { url = "https://files.pythonhosted.org/packages/09/e3/921eb109f682aa24fb76207698fbbcf9418738f35a40c21652c29053f23d/rpds_py-0.28.0-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4fe0438ac4a29a520ea94c8c7f1754cdd8feb1bc490dfda1bfd990072363d527", size = 373127, upload-time = "2025-10-22T22:23:20.216Z" }, - { url = "https://files.pythonhosted.org/packages/23/13/bce4384d9f8f4989f1a9599c71b7a2d877462e5fd7175e1f69b398f729f4/rpds_py-0.28.0-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:8a358a32dd3ae50e933347889b6af9a1bdf207ba5d1a3f34e1a38cd3540e6733", size = 382767, upload-time = "2025-10-22T22:23:21.787Z" }, - { url = "https://files.pythonhosted.org/packages/23/e1/579512b2d89a77c64ccef5a0bc46a6ef7f72ae0cf03d4b26dcd52e57ee0a/rpds_py-0.28.0-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e80848a71c78aa328fefaba9c244d588a342c8e03bda518447b624ea64d1ff56", size = 517585, upload-time = "2025-10-22T22:23:23.699Z" }, - { url = "https://files.pythonhosted.org/packages/62/3c/ca704b8d324a2591b0b0adcfcaadf9c862375b11f2f667ac03c61b4fd0a6/rpds_py-0.28.0-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f586db2e209d54fe177e58e0bc4946bea5fb0102f150b1b2f13de03e1f0976f8", size = 399828, upload-time = "2025-10-22T22:23:25.713Z" }, - { url = "https://files.pythonhosted.org/packages/da/37/e84283b9e897e3adc46b4c88bb3f6ec92a43bd4d2f7ef5b13459963b2e9c/rpds_py-0.28.0-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5ae8ee156d6b586e4292491e885d41483136ab994e719a13458055bec14cf370", size = 375509, upload-time = "2025-10-22T22:23:27.32Z" }, - { url = "https://files.pythonhosted.org/packages/1a/c2/a980beab869d86258bf76ec42dec778ba98151f253a952b02fe36d72b29c/rpds_py-0.28.0-cp314-cp314-manylinux_2_31_riscv64.whl", hash = "sha256:a805e9b3973f7e27f7cab63a6b4f61d90f2e5557cff73b6e97cd5b8540276d3d", size = 392014, upload-time = "2025-10-22T22:23:29.332Z" }, - { url = "https://files.pythonhosted.org/packages/da/b5/b1d3c5f9d3fa5aeef74265f9c64de3c34a0d6d5cd3c81c8b17d5c8f10ed4/rpds_py-0.28.0-cp314-cp314-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:5d3fd16b6dc89c73a4da0b4ac8b12a7ecc75b2864b95c9e5afed8003cb50a728", size = 402410, upload-time = "2025-10-22T22:23:31.14Z" }, - { url = "https://files.pythonhosted.org/packages/74/ae/cab05ff08dfcc052afc73dcb38cbc765ffc86f94e966f3924cd17492293c/rpds_py-0.28.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:6796079e5d24fdaba6d49bda28e2c47347e89834678f2bc2c1b4fc1489c0fb01", size = 553593, upload-time = "2025-10-22T22:23:32.834Z" }, - { url = "https://files.pythonhosted.org/packages/70/80/50d5706ea2a9bfc9e9c5f401d91879e7c790c619969369800cde202da214/rpds_py-0.28.0-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:76500820c2af232435cbe215e3324c75b950a027134e044423f59f5b9a1ba515", size = 576925, upload-time = "2025-10-22T22:23:34.47Z" }, - { url = "https://files.pythonhosted.org/packages/ab/12/85a57d7a5855a3b188d024b099fd09c90db55d32a03626d0ed16352413ff/rpds_py-0.28.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:bbdc5640900a7dbf9dd707fe6388972f5bbd883633eb68b76591044cfe346f7e", size = 542444, upload-time = "2025-10-22T22:23:36.093Z" }, - { url = "https://files.pythonhosted.org/packages/6c/65/10643fb50179509150eb94d558e8837c57ca8b9adc04bd07b98e57b48f8c/rpds_py-0.28.0-cp314-cp314-win32.whl", hash = "sha256:adc8aa88486857d2b35d75f0640b949759f79dc105f50aa2c27816b2e0dd749f", size = 207968, upload-time = "2025-10-22T22:23:37.638Z" }, - { url = "https://files.pythonhosted.org/packages/b4/84/0c11fe4d9aaea784ff4652499e365963222481ac647bcd0251c88af646eb/rpds_py-0.28.0-cp314-cp314-win_amd64.whl", hash = "sha256:66e6fa8e075b58946e76a78e69e1a124a21d9a48a5b4766d15ba5b06869d1fa1", size = 218876, upload-time = "2025-10-22T22:23:39.179Z" }, - { url = "https://files.pythonhosted.org/packages/0f/e0/3ab3b86ded7bb18478392dc3e835f7b754cd446f62f3fc96f4fe2aca78f6/rpds_py-0.28.0-cp314-cp314-win_arm64.whl", hash = "sha256:a6fe887c2c5c59413353b7c0caff25d0e566623501ccfff88957fa438a69377d", size = 212506, upload-time = "2025-10-22T22:23:40.755Z" }, - { url = "https://files.pythonhosted.org/packages/51/ec/d5681bb425226c3501eab50fc30e9d275de20c131869322c8a1729c7b61c/rpds_py-0.28.0-cp314-cp314t-macosx_10_12_x86_64.whl", hash = "sha256:7a69df082db13c7070f7b8b1f155fa9e687f1d6aefb7b0e3f7231653b79a067b", size = 355433, upload-time = "2025-10-22T22:23:42.259Z" }, - { url = "https://files.pythonhosted.org/packages/be/ec/568c5e689e1cfb1ea8b875cffea3649260955f677fdd7ddc6176902d04cd/rpds_py-0.28.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:b1cde22f2c30ebb049a9e74c5374994157b9b70a16147d332f89c99c5960737a", size = 342601, upload-time = "2025-10-22T22:23:44.372Z" }, - { url = "https://files.pythonhosted.org/packages/32/fe/51ada84d1d2a1d9d8f2c902cfddd0133b4a5eb543196ab5161d1c07ed2ad/rpds_py-0.28.0-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5338742f6ba7a51012ea470bd4dc600a8c713c0c72adaa0977a1b1f4327d6592", size = 372039, upload-time = "2025-10-22T22:23:46.025Z" }, - { url = "https://files.pythonhosted.org/packages/07/c1/60144a2f2620abade1a78e0d91b298ac2d9b91bc08864493fa00451ef06e/rpds_py-0.28.0-cp314-cp314t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e1460ebde1bcf6d496d80b191d854adedcc619f84ff17dc1c6d550f58c9efbba", size = 382407, upload-time = "2025-10-22T22:23:48.098Z" }, - { url = "https://files.pythonhosted.org/packages/45/ed/091a7bbdcf4038a60a461df50bc4c82a7ed6d5d5e27649aab61771c17585/rpds_py-0.28.0-cp314-cp314t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e3eb248f2feba84c692579257a043a7699e28a77d86c77b032c1d9fbb3f0219c", size = 518172, upload-time = "2025-10-22T22:23:50.16Z" }, - { url = "https://files.pythonhosted.org/packages/54/dd/02cc90c2fd9c2ef8016fd7813bfacd1c3a1325633ec8f244c47b449fc868/rpds_py-0.28.0-cp314-cp314t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bd3bbba5def70b16cd1c1d7255666aad3b290fbf8d0fe7f9f91abafb73611a91", size = 399020, upload-time = "2025-10-22T22:23:51.81Z" }, - { url = "https://files.pythonhosted.org/packages/ab/81/5d98cc0329bbb911ccecd0b9e19fbf7f3a5de8094b4cda5e71013b2dd77e/rpds_py-0.28.0-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3114f4db69ac5a1f32e7e4d1cbbe7c8f9cf8217f78e6e002cedf2d54c2a548ed", size = 377451, upload-time = "2025-10-22T22:23:53.711Z" }, - { url = "https://files.pythonhosted.org/packages/b4/07/4d5bcd49e3dfed2d38e2dcb49ab6615f2ceb9f89f5a372c46dbdebb4e028/rpds_py-0.28.0-cp314-cp314t-manylinux_2_31_riscv64.whl", hash = "sha256:4b0cb8a906b1a0196b863d460c0222fb8ad0f34041568da5620f9799b83ccf0b", size = 390355, upload-time = "2025-10-22T22:23:55.299Z" }, - { url = "https://files.pythonhosted.org/packages/3f/79/9f14ba9010fee74e4f40bf578735cfcbb91d2e642ffd1abe429bb0b96364/rpds_py-0.28.0-cp314-cp314t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:cf681ac76a60b667106141e11a92a3330890257e6f559ca995fbb5265160b56e", size = 403146, upload-time = "2025-10-22T22:23:56.929Z" }, - { url = "https://files.pythonhosted.org/packages/39/4c/f08283a82ac141331a83a40652830edd3a4a92c34e07e2bbe00baaea2f5f/rpds_py-0.28.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:1e8ee6413cfc677ce8898d9cde18cc3a60fc2ba756b0dec5b71eb6eb21c49fa1", size = 552656, upload-time = "2025-10-22T22:23:58.62Z" }, - { url = "https://files.pythonhosted.org/packages/61/47/d922fc0666f0dd8e40c33990d055f4cc6ecff6f502c2d01569dbed830f9b/rpds_py-0.28.0-cp314-cp314t-musllinux_1_2_i686.whl", hash = "sha256:b3072b16904d0b5572a15eb9d31c1954e0d3227a585fc1351aa9878729099d6c", size = 576782, upload-time = "2025-10-22T22:24:00.312Z" }, - { url = "https://files.pythonhosted.org/packages/d3/0c/5bafdd8ccf6aa9d3bfc630cfece457ff5b581af24f46a9f3590f790e3df2/rpds_py-0.28.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:b670c30fd87a6aec281c3c9896d3bae4b205fd75d79d06dc87c2503717e46092", size = 544671, upload-time = "2025-10-22T22:24:02.297Z" }, - { url = "https://files.pythonhosted.org/packages/2c/37/dcc5d8397caa924988693519069d0beea077a866128719351a4ad95e82fc/rpds_py-0.28.0-cp314-cp314t-win32.whl", hash = "sha256:8014045a15b4d2b3476f0a287fcc93d4f823472d7d1308d47884ecac9e612be3", size = 205749, upload-time = "2025-10-22T22:24:03.848Z" }, - { url = "https://files.pythonhosted.org/packages/d7/69/64d43b21a10d72b45939a28961216baeb721cc2a430f5f7c3bfa21659a53/rpds_py-0.28.0-cp314-cp314t-win_amd64.whl", hash = "sha256:7a4e59c90d9c27c561eb3160323634a9ff50b04e4f7820600a2beb0ac90db578", size = 216233, upload-time = "2025-10-22T22:24:05.471Z" }, - { url = "https://files.pythonhosted.org/packages/ae/bc/b43f2ea505f28119bd551ae75f70be0c803d2dbcd37c1b3734909e40620b/rpds_py-0.28.0-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f5e7101145427087e493b9c9b959da68d357c28c562792300dd21a095118ed16", size = 363913, upload-time = "2025-10-22T22:24:07.129Z" }, - { url = "https://files.pythonhosted.org/packages/28/f2/db318195d324c89a2c57dc5195058cbadd71b20d220685c5bd1da79ee7fe/rpds_py-0.28.0-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:31eb671150b9c62409a888850aaa8e6533635704fe2b78335f9aaf7ff81eec4d", size = 350452, upload-time = "2025-10-22T22:24:08.754Z" }, - { url = "https://files.pythonhosted.org/packages/ae/f2/1391c819b8573a4898cedd6b6c5ec5bc370ce59e5d6bdcebe3c9c1db4588/rpds_py-0.28.0-pp311-pypy311_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:48b55c1f64482f7d8bd39942f376bfdf2f6aec637ee8c805b5041e14eeb771db", size = 380957, upload-time = "2025-10-22T22:24:10.826Z" }, - { url = "https://files.pythonhosted.org/packages/5a/5c/e5de68ee7eb7248fce93269833d1b329a196d736aefb1a7481d1e99d1222/rpds_py-0.28.0-pp311-pypy311_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:24743a7b372e9a76171f6b69c01aedf927e8ac3e16c474d9fe20d552a8cb45c7", size = 391919, upload-time = "2025-10-22T22:24:12.559Z" }, - { url = "https://files.pythonhosted.org/packages/fb/4f/2376336112cbfeb122fd435d608ad8d5041b3aed176f85a3cb32c262eb80/rpds_py-0.28.0-pp311-pypy311_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:389c29045ee8bbb1627ea190b4976a310a295559eaf9f1464a1a6f2bf84dde78", size = 528541, upload-time = "2025-10-22T22:24:14.197Z" }, - { url = "https://files.pythonhosted.org/packages/68/53/5ae232e795853dd20da7225c5dd13a09c0a905b1a655e92bdf8d78a99fd9/rpds_py-0.28.0-pp311-pypy311_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:23690b5827e643150cf7b49569679ec13fe9a610a15949ed48b85eb7f98f34ec", size = 405629, upload-time = "2025-10-22T22:24:16.001Z" }, - { url = "https://files.pythonhosted.org/packages/b9/2d/351a3b852b683ca9b6b8b38ed9efb2347596973849ba6c3a0e99877c10aa/rpds_py-0.28.0-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6f0c9266c26580e7243ad0d72fc3e01d6b33866cfab5084a6da7576bcf1c4f72", size = 384123, upload-time = "2025-10-22T22:24:17.585Z" }, - { url = "https://files.pythonhosted.org/packages/e0/15/870804daa00202728cc91cb8e2385fa9f1f4eb49857c49cfce89e304eae6/rpds_py-0.28.0-pp311-pypy311_pp73-manylinux_2_31_riscv64.whl", hash = "sha256:4c6c4db5d73d179746951486df97fd25e92396be07fc29ee8ff9a8f5afbdfb27", size = 400923, upload-time = "2025-10-22T22:24:19.512Z" }, - { url = "https://files.pythonhosted.org/packages/53/25/3706b83c125fa2a0bccceac951de3f76631f6bd0ee4d02a0ed780712ef1b/rpds_py-0.28.0-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:a3b695a8fa799dd2cfdb4804b37096c5f6dba1ac7f48a7fbf6d0485bcd060316", size = 413767, upload-time = "2025-10-22T22:24:21.316Z" }, - { url = "https://files.pythonhosted.org/packages/ef/f9/ce43dbe62767432273ed2584cef71fef8411bddfb64125d4c19128015018/rpds_py-0.28.0-pp311-pypy311_pp73-musllinux_1_2_aarch64.whl", hash = "sha256:6aa1bfce3f83baf00d9c5fcdbba93a3ab79958b4c7d7d1f55e7fe68c20e63912", size = 561530, upload-time = "2025-10-22T22:24:22.958Z" }, - { url = "https://files.pythonhosted.org/packages/46/c9/ffe77999ed8f81e30713dd38fd9ecaa161f28ec48bb80fa1cd9118399c27/rpds_py-0.28.0-pp311-pypy311_pp73-musllinux_1_2_i686.whl", hash = "sha256:7b0f9dceb221792b3ee6acb5438eb1f02b0cb2c247796a72b016dcc92c6de829", size = 585453, upload-time = "2025-10-22T22:24:24.779Z" }, - { url = "https://files.pythonhosted.org/packages/ed/d2/4a73b18821fd4669762c855fd1f4e80ceb66fb72d71162d14da58444a763/rpds_py-0.28.0-pp311-pypy311_pp73-musllinux_1_2_x86_64.whl", hash = "sha256:5d0145edba8abd3db0ab22b5300c99dc152f5c9021fab861be0f0544dc3cbc5f", size = 552199, upload-time = "2025-10-22T22:24:26.54Z" }, -] - -[[package]] -name = "rsa" -version = "4.9.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "pyasn1" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/da/8a/22b7beea3ee0d44b1916c0c1cb0ee3af23b700b6da9f04991899d0c555d4/rsa-4.9.1.tar.gz", hash = "sha256:e7bdbfdb5497da4c07dfd35530e1a902659db6ff241e39d9953cad06ebd0ae75", size = 29034, upload-time = "2025-04-16T09:51:18.218Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/64/8d/0133e4eb4beed9e425d9a98ed6e081a55d195481b7632472be1af08d2f6b/rsa-4.9.1-py3-none-any.whl", hash = "sha256:68635866661c6836b8d39430f97a996acbd61bfa49406748ea243539fe239762", size = 34696, upload-time = "2025-04-16T09:51:17.142Z" }, -] - -[[package]] -name = "ruff" -version = "0.14.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/75/62/50b7727004dfe361104dfbf898c45a9a2fdfad8c72c04ae62900224d6ecf/ruff-0.14.3.tar.gz", hash = "sha256:4ff876d2ab2b161b6de0aa1f5bd714e8e9b4033dc122ee006925fbacc4f62153", size = 5558687, upload-time = "2025-10-31T00:26:26.878Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ce/8e/0c10ff1ea5d4360ab8bfca4cb2c9d979101a391f3e79d2616c9bf348cd26/ruff-0.14.3-py3-none-linux_armv6l.whl", hash = "sha256:876b21e6c824f519446715c1342b8e60f97f93264012de9d8d10314f8a79c371", size = 12535613, upload-time = "2025-10-31T00:25:44.302Z" }, - { url = "https://files.pythonhosted.org/packages/d3/c8/6724f4634c1daf52409fbf13fefda64aa9c8f81e44727a378b7b73dc590b/ruff-0.14.3-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:b6fd8c79b457bedd2abf2702b9b472147cd860ed7855c73a5247fa55c9117654", size = 12855812, upload-time = "2025-10-31T00:25:47.793Z" }, - { url = "https://files.pythonhosted.org/packages/de/03/db1bce591d55fd5f8a08bb02517fa0b5097b2ccabd4ea1ee29aa72b67d96/ruff-0.14.3-py3-none-macosx_11_0_arm64.whl", hash = "sha256:71ff6edca490c308f083156938c0c1a66907151263c4abdcb588602c6e696a14", size = 11944026, upload-time = "2025-10-31T00:25:49.657Z" }, - { url = "https://files.pythonhosted.org/packages/0b/75/4f8dbd48e03272715d12c87dc4fcaaf21b913f0affa5f12a4e9c6f8a0582/ruff-0.14.3-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:786ee3ce6139772ff9272aaf43296d975c0217ee1b97538a98171bf0d21f87ed", size = 12356818, upload-time = "2025-10-31T00:25:51.949Z" }, - { url = "https://files.pythonhosted.org/packages/ec/9b/506ec5b140c11d44a9a4f284ea7c14ebf6f8b01e6e8917734a3325bff787/ruff-0.14.3-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:cd6291d0061811c52b8e392f946889916757610d45d004e41140d81fb6cd5ddc", size = 12336745, upload-time = "2025-10-31T00:25:54.248Z" }, - { url = "https://files.pythonhosted.org/packages/c7/e1/c560d254048c147f35e7f8131d30bc1f63a008ac61595cf3078a3e93533d/ruff-0.14.3-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a497ec0c3d2c88561b6d90f9c29f5ae68221ac00d471f306fa21fa4264ce5fcd", size = 13101684, upload-time = "2025-10-31T00:25:56.253Z" }, - { url = "https://files.pythonhosted.org/packages/a5/32/e310133f8af5cd11f8cc30f52522a3ebccc5ea5bff4b492f94faceaca7a8/ruff-0.14.3-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:e231e1be58fc568950a04fbe6887c8e4b85310e7889727e2b81db205c45059eb", size = 14535000, upload-time = "2025-10-31T00:25:58.397Z" }, - { url = "https://files.pythonhosted.org/packages/a2/a1/7b0470a22158c6d8501eabc5e9b6043c99bede40fa1994cadf6b5c2a61c7/ruff-0.14.3-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:469e35872a09c0e45fecf48dd960bfbce056b5db2d5e6b50eca329b4f853ae20", size = 14156450, upload-time = "2025-10-31T00:26:00.889Z" }, - { url = "https://files.pythonhosted.org/packages/0a/96/24bfd9d1a7f532b560dcee1a87096332e461354d3882124219bcaff65c09/ruff-0.14.3-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3d6bc90307c469cb9d28b7cfad90aaa600b10d67c6e22026869f585e1e8a2db0", size = 13568414, upload-time = "2025-10-31T00:26:03.291Z" }, - { url = "https://files.pythonhosted.org/packages/a7/e7/138b883f0dfe4ad5b76b58bf4ae675f4d2176ac2b24bdd81b4d966b28c61/ruff-0.14.3-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0e2f8a0bbcffcfd895df39c9a4ecd59bb80dca03dc43f7fb63e647ed176b741e", size = 13315293, upload-time = "2025-10-31T00:26:05.708Z" }, - { url = "https://files.pythonhosted.org/packages/33/f4/c09bb898be97b2eb18476b7c950df8815ef14cf956074177e9fbd40b7719/ruff-0.14.3-py3-none-manylinux_2_31_riscv64.whl", hash = "sha256:678fdd7c7d2d94851597c23ee6336d25f9930b460b55f8598e011b57c74fd8c5", size = 13539444, upload-time = "2025-10-31T00:26:08.09Z" }, - { url = "https://files.pythonhosted.org/packages/9c/aa/b30a1db25fc6128b1dd6ff0741fa4abf969ded161599d07ca7edd0739cc0/ruff-0.14.3-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:1ec1ac071e7e37e0221d2f2dbaf90897a988c531a8592a6a5959f0603a1ecf5e", size = 12252581, upload-time = "2025-10-31T00:26:10.297Z" }, - { url = "https://files.pythonhosted.org/packages/da/13/21096308f384d796ffe3f2960b17054110a9c3828d223ca540c2b7cc670b/ruff-0.14.3-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:afcdc4b5335ef440d19e7df9e8ae2ad9f749352190e96d481dc501b753f0733e", size = 12307503, upload-time = "2025-10-31T00:26:12.646Z" }, - { url = "https://files.pythonhosted.org/packages/cb/cc/a350bac23f03b7dbcde3c81b154706e80c6f16b06ff1ce28ed07dc7b07b0/ruff-0.14.3-py3-none-musllinux_1_2_i686.whl", hash = "sha256:7bfc42f81862749a7136267a343990f865e71fe2f99cf8d2958f684d23ce3dfa", size = 12675457, upload-time = "2025-10-31T00:26:15.044Z" }, - { url = "https://files.pythonhosted.org/packages/cb/76/46346029fa2f2078826bc88ef7167e8c198e58fe3126636e52f77488cbba/ruff-0.14.3-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:a65e448cfd7e9c59fae8cf37f9221585d3354febaad9a07f29158af1528e165f", size = 13403980, upload-time = "2025-10-31T00:26:17.81Z" }, - { url = "https://files.pythonhosted.org/packages/9f/a4/35f1ef68c4e7b236d4a5204e3669efdeefaef21f0ff6a456792b3d8be438/ruff-0.14.3-py3-none-win32.whl", hash = "sha256:f3d91857d023ba93e14ed2d462ab62c3428f9bbf2b4fbac50a03ca66d31991f7", size = 12500045, upload-time = "2025-10-31T00:26:20.503Z" }, - { url = "https://files.pythonhosted.org/packages/03/15/51960ae340823c9859fb60c63301d977308735403e2134e17d1d2858c7fb/ruff-0.14.3-py3-none-win_amd64.whl", hash = "sha256:d7b7006ac0756306db212fd37116cce2bd307e1e109375e1c6c106002df0ae5f", size = 13594005, upload-time = "2025-10-31T00:26:22.533Z" }, - { url = "https://files.pythonhosted.org/packages/b7/73/4de6579bac8e979fca0a77e54dec1f1e011a0d268165eb8a9bc0982a6564/ruff-0.14.3-py3-none-win_arm64.whl", hash = "sha256:26eb477ede6d399d898791d01961e16b86f02bc2486d0d1a7a9bb2379d055dc1", size = 12590017, upload-time = "2025-10-31T00:26:24.52Z" }, -] - -[[package]] -name = "shapely" -version = "2.1.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" }, - { name = "numpy", version = "2.3.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/4d/bc/0989043118a27cccb4e906a46b7565ce36ca7b57f5a18b78f4f1b0f72d9d/shapely-2.1.2.tar.gz", hash = "sha256:2ed4ecb28320a433db18a5bf029986aa8afcfd740745e78847e330d5d94922a9", size = 315489, upload-time = "2025-09-24T13:51:41.432Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/05/89/c3548aa9b9812a5d143986764dededfa48d817714e947398bdda87c77a72/shapely-2.1.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7ae48c236c0324b4e139bea88a306a04ca630f49be66741b340729d380d8f52f", size = 1825959, upload-time = "2025-09-24T13:50:00.682Z" }, - { url = "https://files.pythonhosted.org/packages/ce/8a/7ebc947080442edd614ceebe0ce2cdbd00c25e832c240e1d1de61d0e6b38/shapely-2.1.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:eba6710407f1daa8e7602c347dfc94adc02205ec27ed956346190d66579eb9ea", size = 1629196, upload-time = "2025-09-24T13:50:03.447Z" }, - { url = "https://files.pythonhosted.org/packages/c8/86/c9c27881c20d00fc409e7e059de569d5ed0abfcec9c49548b124ebddea51/shapely-2.1.2-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:ef4a456cc8b7b3d50ccec29642aa4aeda959e9da2fe9540a92754770d5f0cf1f", size = 2951065, upload-time = "2025-09-24T13:50:05.266Z" }, - { url = "https://files.pythonhosted.org/packages/50/8a/0ab1f7433a2a85d9e9aea5b1fbb333f3b09b309e7817309250b4b7b2cc7a/shapely-2.1.2-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e38a190442aacc67ff9f75ce60aec04893041f16f97d242209106d502486a142", size = 3058666, upload-time = "2025-09-24T13:50:06.872Z" }, - { url = "https://files.pythonhosted.org/packages/bb/c6/5a30ffac9c4f3ffd5b7113a7f5299ccec4713acd5ee44039778a7698224e/shapely-2.1.2-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:40d784101f5d06a1fd30b55fc11ea58a61be23f930d934d86f19a180909908a4", size = 3966905, upload-time = "2025-09-24T13:50:09.417Z" }, - { url = "https://files.pythonhosted.org/packages/9c/72/e92f3035ba43e53959007f928315a68fbcf2eeb4e5ededb6f0dc7ff1ecc3/shapely-2.1.2-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:f6f6cd5819c50d9bcf921882784586aab34a4bd53e7553e175dece6db513a6f0", size = 4129260, upload-time = "2025-09-24T13:50:11.183Z" }, - { url = "https://files.pythonhosted.org/packages/42/24/605901b73a3d9f65fa958e63c9211f4be23d584da8a1a7487382fac7fdc5/shapely-2.1.2-cp310-cp310-win32.whl", hash = "sha256:fe9627c39c59e553c90f5bc3128252cb85dc3b3be8189710666d2f8bc3a5503e", size = 1544301, upload-time = "2025-09-24T13:50:12.521Z" }, - { url = "https://files.pythonhosted.org/packages/e1/89/6db795b8dd3919851856bd2ddd13ce434a748072f6fdee42ff30cbd3afa3/shapely-2.1.2-cp310-cp310-win_amd64.whl", hash = "sha256:1d0bfb4b8f661b3b4ec3565fa36c340bfb1cda82087199711f86a88647d26b2f", size = 1722074, upload-time = "2025-09-24T13:50:13.909Z" }, - { url = "https://files.pythonhosted.org/packages/8f/8d/1ff672dea9ec6a7b5d422eb6d095ed886e2e523733329f75fdcb14ee1149/shapely-2.1.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:91121757b0a36c9aac3427a651a7e6567110a4a67c97edf04f8d55d4765f6618", size = 1820038, upload-time = "2025-09-24T13:50:15.628Z" }, - { url = "https://files.pythonhosted.org/packages/4f/ce/28fab8c772ce5db23a0d86bf0adaee0c4c79d5ad1db766055fa3dab442e2/shapely-2.1.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:16a9c722ba774cf50b5d4541242b4cce05aafd44a015290c82ba8a16931ff63d", size = 1626039, upload-time = "2025-09-24T13:50:16.881Z" }, - { url = "https://files.pythonhosted.org/packages/70/8b/868b7e3f4982f5006e9395c1e12343c66a8155c0374fdc07c0e6a1ab547d/shapely-2.1.2-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:cc4f7397459b12c0b196c9efe1f9d7e92463cbba142632b4cc6d8bbbbd3e2b09", size = 3001519, upload-time = "2025-09-24T13:50:18.606Z" }, - { url = "https://files.pythonhosted.org/packages/13/02/58b0b8d9c17c93ab6340edd8b7308c0c5a5b81f94ce65705819b7416dba5/shapely-2.1.2-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:136ab87b17e733e22f0961504d05e77e7be8c9b5a8184f685b4a91a84efe3c26", size = 3110842, upload-time = "2025-09-24T13:50:21.77Z" }, - { url = "https://files.pythonhosted.org/packages/af/61/8e389c97994d5f331dcffb25e2fa761aeedfb52b3ad9bcdd7b8671f4810a/shapely-2.1.2-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:16c5d0fc45d3aa0a69074979f4f1928ca2734fb2e0dde8af9611e134e46774e7", size = 4021316, upload-time = "2025-09-24T13:50:23.626Z" }, - { url = "https://files.pythonhosted.org/packages/d3/d4/9b2a9fe6039f9e42ccf2cb3e84f219fd8364b0c3b8e7bbc857b5fbe9c14c/shapely-2.1.2-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:6ddc759f72b5b2b0f54a7e7cde44acef680a55019eb52ac63a7af2cf17cb9cd2", size = 4178586, upload-time = "2025-09-24T13:50:25.443Z" }, - { url = "https://files.pythonhosted.org/packages/16/f6/9840f6963ed4decf76b08fd6d7fed14f8779fb7a62cb45c5617fa8ac6eab/shapely-2.1.2-cp311-cp311-win32.whl", hash = "sha256:2fa78b49485391224755a856ed3b3bd91c8455f6121fee0db0e71cefb07d0ef6", size = 1543961, upload-time = "2025-09-24T13:50:26.968Z" }, - { url = "https://files.pythonhosted.org/packages/38/1e/3f8ea46353c2a33c1669eb7327f9665103aa3a8dfe7f2e4ef714c210b2c2/shapely-2.1.2-cp311-cp311-win_amd64.whl", hash = "sha256:c64d5c97b2f47e3cd9b712eaced3b061f2b71234b3fc263e0fcf7d889c6559dc", size = 1722856, upload-time = "2025-09-24T13:50:28.497Z" }, - { url = "https://files.pythonhosted.org/packages/24/c0/f3b6453cf2dfa99adc0ba6675f9aaff9e526d2224cbd7ff9c1a879238693/shapely-2.1.2-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:fe2533caae6a91a543dec62e8360fe86ffcdc42a7c55f9dfd0128a977a896b94", size = 1833550, upload-time = "2025-09-24T13:50:30.019Z" }, - { url = "https://files.pythonhosted.org/packages/86/07/59dee0bc4b913b7ab59ab1086225baca5b8f19865e6101db9ebb7243e132/shapely-2.1.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:ba4d1333cc0bc94381d6d4308d2e4e008e0bd128bdcff5573199742ee3634359", size = 1643556, upload-time = "2025-09-24T13:50:32.291Z" }, - { url = "https://files.pythonhosted.org/packages/26/29/a5397e75b435b9895cd53e165083faed5d12fd9626eadec15a83a2411f0f/shapely-2.1.2-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:0bd308103340030feef6c111d3eb98d50dc13feea33affc8a6f9fa549e9458a3", size = 2988308, upload-time = "2025-09-24T13:50:33.862Z" }, - { url = "https://files.pythonhosted.org/packages/b9/37/e781683abac55dde9771e086b790e554811a71ed0b2b8a1e789b7430dd44/shapely-2.1.2-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:1e7d4d7ad262a48bb44277ca12c7c78cb1b0f56b32c10734ec9a1d30c0b0c54b", size = 3099844, upload-time = "2025-09-24T13:50:35.459Z" }, - { url = "https://files.pythonhosted.org/packages/d8/f3/9876b64d4a5a321b9dc482c92bb6f061f2fa42131cba643c699f39317cb9/shapely-2.1.2-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:e9eddfe513096a71896441a7c37db72da0687b34752c4e193577a145c71736fc", size = 3988842, upload-time = "2025-09-24T13:50:37.478Z" }, - { url = "https://files.pythonhosted.org/packages/d1/a0/704c7292f7014c7e74ec84eddb7b109e1fbae74a16deae9c1504b1d15565/shapely-2.1.2-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:980c777c612514c0cf99bc8a9de6d286f5e186dcaf9091252fcd444e5638193d", size = 4152714, upload-time = "2025-09-24T13:50:39.9Z" }, - { url = "https://files.pythonhosted.org/packages/53/46/319c9dc788884ad0785242543cdffac0e6530e4d0deb6c4862bc4143dcf3/shapely-2.1.2-cp312-cp312-win32.whl", hash = "sha256:9111274b88e4d7b54a95218e243282709b330ef52b7b86bc6aaf4f805306f454", size = 1542745, upload-time = "2025-09-24T13:50:41.414Z" }, - { url = "https://files.pythonhosted.org/packages/ec/bf/cb6c1c505cb31e818e900b9312d514f381fbfa5c4363edfce0fcc4f8c1a4/shapely-2.1.2-cp312-cp312-win_amd64.whl", hash = "sha256:743044b4cfb34f9a67205cee9279feaf60ba7d02e69febc2afc609047cb49179", size = 1722861, upload-time = "2025-09-24T13:50:43.35Z" }, - { url = "https://files.pythonhosted.org/packages/c3/90/98ef257c23c46425dc4d1d31005ad7c8d649fe423a38b917db02c30f1f5a/shapely-2.1.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:b510dda1a3672d6879beb319bc7c5fd302c6c354584690973c838f46ec3e0fa8", size = 1832644, upload-time = "2025-09-24T13:50:44.886Z" }, - { url = "https://files.pythonhosted.org/packages/6d/ab/0bee5a830d209adcd3a01f2d4b70e587cdd9fd7380d5198c064091005af8/shapely-2.1.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:8cff473e81017594d20ec55d86b54bc635544897e13a7cfc12e36909c5309a2a", size = 1642887, upload-time = "2025-09-24T13:50:46.735Z" }, - { url = "https://files.pythonhosted.org/packages/2d/5e/7d7f54ba960c13302584c73704d8c4d15404a51024631adb60b126a4ae88/shapely-2.1.2-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:fe7b77dc63d707c09726b7908f575fc04ff1d1ad0f3fb92aec212396bc6cfe5e", size = 2970931, upload-time = "2025-09-24T13:50:48.374Z" }, - { url = "https://files.pythonhosted.org/packages/f2/a2/83fc37e2a58090e3d2ff79175a95493c664bcd0b653dd75cb9134645a4e5/shapely-2.1.2-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:7ed1a5bbfb386ee8332713bf7508bc24e32d24b74fc9a7b9f8529a55db9f4ee6", size = 3082855, upload-time = "2025-09-24T13:50:50.037Z" }, - { url = "https://files.pythonhosted.org/packages/44/2b/578faf235a5b09f16b5f02833c53822294d7f21b242f8e2d0cf03fb64321/shapely-2.1.2-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a84e0582858d841d54355246ddfcbd1fce3179f185da7470f41ce39d001ee1af", size = 3979960, upload-time = "2025-09-24T13:50:51.74Z" }, - { url = "https://files.pythonhosted.org/packages/4d/04/167f096386120f692cc4ca02f75a17b961858997a95e67a3cb6a7bbd6b53/shapely-2.1.2-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:dc3487447a43d42adcdf52d7ac73804f2312cbfa5d433a7d2c506dcab0033dfd", size = 4142851, upload-time = "2025-09-24T13:50:53.49Z" }, - { url = "https://files.pythonhosted.org/packages/48/74/fb402c5a6235d1c65a97348b48cdedb75fb19eca2b1d66d04969fc1c6091/shapely-2.1.2-cp313-cp313-win32.whl", hash = "sha256:9c3a3c648aedc9f99c09263b39f2d8252f199cb3ac154fadc173283d7d111350", size = 1541890, upload-time = "2025-09-24T13:50:55.337Z" }, - { url = "https://files.pythonhosted.org/packages/41/47/3647fe7ad990af60ad98b889657a976042c9988c2807cf322a9d6685f462/shapely-2.1.2-cp313-cp313-win_amd64.whl", hash = "sha256:ca2591bff6645c216695bdf1614fca9c82ea1144d4a7591a466fef64f28f0715", size = 1722151, upload-time = "2025-09-24T13:50:57.153Z" }, - { url = "https://files.pythonhosted.org/packages/3c/49/63953754faa51ffe7d8189bfbe9ca34def29f8c0e34c67cbe2a2795f269d/shapely-2.1.2-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:2d93d23bdd2ed9dc157b46bc2f19b7da143ca8714464249bef6771c679d5ff40", size = 1834130, upload-time = "2025-09-24T13:50:58.49Z" }, - { url = "https://files.pythonhosted.org/packages/7f/ee/dce001c1984052970ff60eb4727164892fb2d08052c575042a47f5a9e88f/shapely-2.1.2-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:01d0d304b25634d60bd7cf291828119ab55a3bab87dc4af1e44b07fb225f188b", size = 1642802, upload-time = "2025-09-24T13:50:59.871Z" }, - { url = "https://files.pythonhosted.org/packages/da/e7/fc4e9a19929522877fa602f705706b96e78376afb7fad09cad5b9af1553c/shapely-2.1.2-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:8d8382dd120d64b03698b7298b89611a6ea6f55ada9d39942838b79c9bc89801", size = 3018460, upload-time = "2025-09-24T13:51:02.08Z" }, - { url = "https://files.pythonhosted.org/packages/a1/18/7519a25db21847b525696883ddc8e6a0ecaa36159ea88e0fef11466384d0/shapely-2.1.2-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:19efa3611eef966e776183e338b2d7ea43569ae99ab34f8d17c2c054d3205cc0", size = 3095223, upload-time = "2025-09-24T13:51:04.472Z" }, - { url = "https://files.pythonhosted.org/packages/48/de/b59a620b1f3a129c3fecc2737104a0a7e04e79335bd3b0a1f1609744cf17/shapely-2.1.2-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:346ec0c1a0fcd32f57f00e4134d1200e14bf3f5ae12af87ba83ca275c502498c", size = 4030760, upload-time = "2025-09-24T13:51:06.455Z" }, - { url = "https://files.pythonhosted.org/packages/96/b3/c6655ee7232b417562bae192ae0d3ceaadb1cc0ffc2088a2ddf415456cc2/shapely-2.1.2-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:6305993a35989391bd3476ee538a5c9a845861462327efe00dd11a5c8c709a99", size = 4170078, upload-time = "2025-09-24T13:51:08.584Z" }, - { url = "https://files.pythonhosted.org/packages/a0/8e/605c76808d73503c9333af8f6cbe7e1354d2d238bda5f88eea36bfe0f42a/shapely-2.1.2-cp313-cp313t-win32.whl", hash = "sha256:c8876673449f3401f278c86eb33224c5764582f72b653a415d0e6672fde887bf", size = 1559178, upload-time = "2025-09-24T13:51:10.73Z" }, - { url = "https://files.pythonhosted.org/packages/36/f7/d317eb232352a1f1444d11002d477e54514a4a6045536d49d0c59783c0da/shapely-2.1.2-cp313-cp313t-win_amd64.whl", hash = "sha256:4a44bc62a10d84c11a7a3d7c1c4fe857f7477c3506e24c9062da0db0ae0c449c", size = 1739756, upload-time = "2025-09-24T13:51:12.105Z" }, - { url = "https://files.pythonhosted.org/packages/fc/c4/3ce4c2d9b6aabd27d26ec988f08cb877ba9e6e96086eff81bfea93e688c7/shapely-2.1.2-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:9a522f460d28e2bf4e12396240a5fc1518788b2fcd73535166d748399ef0c223", size = 1831290, upload-time = "2025-09-24T13:51:13.56Z" }, - { url = "https://files.pythonhosted.org/packages/17/b9/f6ab8918fc15429f79cb04afa9f9913546212d7fb5e5196132a2af46676b/shapely-2.1.2-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:1ff629e00818033b8d71139565527ced7d776c269a49bd78c9df84e8f852190c", size = 1641463, upload-time = "2025-09-24T13:51:14.972Z" }, - { url = "https://files.pythonhosted.org/packages/a5/57/91d59ae525ca641e7ac5551c04c9503aee6f29b92b392f31790fcb1a4358/shapely-2.1.2-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:f67b34271dedc3c653eba4e3d7111aa421d5be9b4c4c7d38d30907f796cb30df", size = 2970145, upload-time = "2025-09-24T13:51:16.961Z" }, - { url = "https://files.pythonhosted.org/packages/8a/cb/4948be52ee1da6927831ab59e10d4c29baa2a714f599f1f0d1bc747f5777/shapely-2.1.2-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:21952dc00df38a2c28375659b07a3979d22641aeb104751e769c3ee825aadecf", size = 3073806, upload-time = "2025-09-24T13:51:18.712Z" }, - { url = "https://files.pythonhosted.org/packages/03/83/f768a54af775eb41ef2e7bec8a0a0dbe7d2431c3e78c0a8bdba7ab17e446/shapely-2.1.2-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:1f2f33f486777456586948e333a56ae21f35ae273be99255a191f5c1fa302eb4", size = 3980803, upload-time = "2025-09-24T13:51:20.37Z" }, - { url = "https://files.pythonhosted.org/packages/9f/cb/559c7c195807c91c79d38a1f6901384a2878a76fbdf3f1048893a9b7534d/shapely-2.1.2-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:cf831a13e0d5a7eb519e96f58ec26e049b1fad411fc6fc23b162a7ce04d9cffc", size = 4133301, upload-time = "2025-09-24T13:51:21.887Z" }, - { url = "https://files.pythonhosted.org/packages/80/cd/60d5ae203241c53ef3abd2ef27c6800e21afd6c94e39db5315ea0cbafb4a/shapely-2.1.2-cp314-cp314-win32.whl", hash = "sha256:61edcd8d0d17dd99075d320a1dd39c0cb9616f7572f10ef91b4b5b00c4aeb566", size = 1583247, upload-time = "2025-09-24T13:51:23.401Z" }, - { url = "https://files.pythonhosted.org/packages/74/d4/135684f342e909330e50d31d441ace06bf83c7dc0777e11043f99167b123/shapely-2.1.2-cp314-cp314-win_amd64.whl", hash = "sha256:a444e7afccdb0999e203b976adb37ea633725333e5b119ad40b1ca291ecf311c", size = 1773019, upload-time = "2025-09-24T13:51:24.873Z" }, - { url = "https://files.pythonhosted.org/packages/a3/05/a44f3f9f695fa3ada22786dc9da33c933da1cbc4bfe876fe3a100bafe263/shapely-2.1.2-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:5ebe3f84c6112ad3d4632b1fd2290665aa75d4cef5f6c5d77c4c95b324527c6a", size = 1834137, upload-time = "2025-09-24T13:51:26.665Z" }, - { url = "https://files.pythonhosted.org/packages/52/7e/4d57db45bf314573427b0a70dfca15d912d108e6023f623947fa69f39b72/shapely-2.1.2-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:5860eb9f00a1d49ebb14e881f5caf6c2cf472c7fd38bd7f253bbd34f934eb076", size = 1642884, upload-time = "2025-09-24T13:51:28.029Z" }, - { url = "https://files.pythonhosted.org/packages/5a/27/4e29c0a55d6d14ad7422bf86995d7ff3f54af0eba59617eb95caf84b9680/shapely-2.1.2-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:b705c99c76695702656327b819c9660768ec33f5ce01fa32b2af62b56ba400a1", size = 3018320, upload-time = "2025-09-24T13:51:29.903Z" }, - { url = "https://files.pythonhosted.org/packages/9f/bb/992e6a3c463f4d29d4cd6ab8963b75b1b1040199edbd72beada4af46bde5/shapely-2.1.2-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:a1fd0ea855b2cf7c9cddaf25543e914dd75af9de08785f20ca3085f2c9ca60b0", size = 3094931, upload-time = "2025-09-24T13:51:32.699Z" }, - { url = "https://files.pythonhosted.org/packages/9c/16/82e65e21070e473f0ed6451224ed9fa0be85033d17e0c6e7213a12f59d12/shapely-2.1.2-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:df90e2db118c3671a0754f38e36802db75fe0920d211a27481daf50a711fdf26", size = 4030406, upload-time = "2025-09-24T13:51:34.189Z" }, - { url = "https://files.pythonhosted.org/packages/7c/75/c24ed871c576d7e2b64b04b1fe3d075157f6eb54e59670d3f5ffb36e25c7/shapely-2.1.2-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:361b6d45030b4ac64ddd0a26046906c8202eb60d0f9f53085f5179f1d23021a0", size = 4169511, upload-time = "2025-09-24T13:51:36.297Z" }, - { url = "https://files.pythonhosted.org/packages/b1/f7/b3d1d6d18ebf55236eec1c681ce5e665742aab3c0b7b232720a7d43df7b6/shapely-2.1.2-cp314-cp314t-win32.whl", hash = "sha256:b54df60f1fbdecc8ebc2c5b11870461a6417b3d617f555e5033f1505d36e5735", size = 1602607, upload-time = "2025-09-24T13:51:37.757Z" }, - { url = "https://files.pythonhosted.org/packages/9a/f6/f09272a71976dfc138129b8faf435d064a811ae2f708cb147dccdf7aacdb/shapely-2.1.2-cp314-cp314t-win_amd64.whl", hash = "sha256:0036ac886e0923417932c2e6369b6c52e38e0ff5d9120b90eef5cd9a5fc5cae9", size = 1796682, upload-time = "2025-09-24T13:51:39.233Z" }, -] - -[[package]] -name = "six" -version = "1.17.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/94/e7/b2c673351809dca68a0e064b6af791aa332cf192da575fd474ed7d6f16a2/six-1.17.0.tar.gz", hash = "sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81", size = 34031, upload-time = "2024-12-04T17:35:28.174Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl", hash = "sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274", size = 11050, upload-time = "2024-12-04T17:35:26.475Z" }, -] - -[[package]] -name = "smmap" -version = "5.0.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/44/cd/a040c4b3119bbe532e5b0732286f805445375489fceaec1f48306068ee3b/smmap-5.0.2.tar.gz", hash = "sha256:26ea65a03958fa0c8a1c7e8c7a58fdc77221b8910f6be2131affade476898ad5", size = 22329, upload-time = "2025-01-02T07:14:40.909Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/04/be/d09147ad1ec7934636ad912901c5fd7667e1c858e19d355237db0d0cd5e4/smmap-5.0.2-py3-none-any.whl", hash = "sha256:b30115f0def7d7531d22a0fb6502488d879e75b260a9db4d0819cfb25403af5e", size = 24303, upload-time = "2025-01-02T07:14:38.724Z" }, -] - -[[package]] -name = "sniffio" -version = "1.3.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a2/87/a6771e1546d97e7e041b6ae58d80074f81b7d5121207425c964ddf5cfdbd/sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc", size = 20372, upload-time = "2024-02-25T23:20:04.057Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e9/44/75a9c9421471a6c4805dbf2356f7c181a29c1879239abab1ea2cc8f38b40/sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2", size = 10235, upload-time = "2024-02-25T23:20:01.196Z" }, -] - -[[package]] -name = "sqlalchemy" -version = "2.0.44" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "greenlet", marker = "platform_machine == 'AMD64' or platform_machine == 'WIN32' or platform_machine == 'aarch64' or platform_machine == 'amd64' or platform_machine == 'ppc64le' or platform_machine == 'win32' or platform_machine == 'x86_64'" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/f0/f2/840d7b9496825333f532d2e3976b8eadbf52034178aac53630d09fe6e1ef/sqlalchemy-2.0.44.tar.gz", hash = "sha256:0ae7454e1ab1d780aee69fd2aae7d6b8670a581d8847f2d1e0f7ddfbf47e5a22", size = 9819830, upload-time = "2025-10-10T14:39:12.935Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a2/a7/e9ccfa7eecaf34c6f57d8cb0bb7cbdeeff27017cc0f5d0ca90fdde7a7c0d/sqlalchemy-2.0.44-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7c77f3080674fc529b1bd99489378c7f63fcb4ba7f8322b79732e0258f0ea3ce", size = 2137282, upload-time = "2025-10-10T15:36:10.965Z" }, - { url = "https://files.pythonhosted.org/packages/b1/e1/50bc121885bdf10833a4f65ecbe9fe229a3215f4d65a58da8a181734cae3/sqlalchemy-2.0.44-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4c26ef74ba842d61635b0152763d057c8d48215d5be9bb8b7604116a059e9985", size = 2127322, upload-time = "2025-10-10T15:36:12.428Z" }, - { url = "https://files.pythonhosted.org/packages/46/f2/a8573b7230a3ce5ee4b961a2d510d71b43872513647398e595b744344664/sqlalchemy-2.0.44-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f4a172b31785e2f00780eccab00bc240ccdbfdb8345f1e6063175b3ff12ad1b0", size = 3214772, upload-time = "2025-10-10T15:34:15.09Z" }, - { url = "https://files.pythonhosted.org/packages/4a/d8/c63d8adb6a7edaf8dcb6f75a2b1e9f8577960a1e489606859c4d73e7d32b/sqlalchemy-2.0.44-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f9480c0740aabd8cb29c329b422fb65358049840b34aba0adf63162371d2a96e", size = 3214434, upload-time = "2025-10-10T15:47:00.473Z" }, - { url = "https://files.pythonhosted.org/packages/ee/a6/243d277a4b54fae74d4797957a7320a5c210c293487f931cbe036debb697/sqlalchemy-2.0.44-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:17835885016b9e4d0135720160db3095dc78c583e7b902b6be799fb21035e749", size = 3155365, upload-time = "2025-10-10T15:34:17.932Z" }, - { url = "https://files.pythonhosted.org/packages/5f/f8/6a39516ddd75429fd4ee5a0d72e4c80639fab329b2467c75f363c2ed9751/sqlalchemy-2.0.44-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:cbe4f85f50c656d753890f39468fcd8190c5f08282caf19219f684225bfd5fd2", size = 3178910, upload-time = "2025-10-10T15:47:02.346Z" }, - { url = "https://files.pythonhosted.org/packages/43/f0/118355d4ad3c39d9a2f5ee4c7304a9665b3571482777357fa9920cd7a6b4/sqlalchemy-2.0.44-cp310-cp310-win32.whl", hash = "sha256:2fcc4901a86ed81dc76703f3b93ff881e08761c63263c46991081fd7f034b165", size = 2105624, upload-time = "2025-10-10T15:38:15.552Z" }, - { url = "https://files.pythonhosted.org/packages/61/83/6ae5f9466f8aa5d0dcebfff8c9c33b98b27ce23292df3b990454b3d434fd/sqlalchemy-2.0.44-cp310-cp310-win_amd64.whl", hash = "sha256:9919e77403a483ab81e3423151e8ffc9dd992c20d2603bf17e4a8161111e55f5", size = 2129240, upload-time = "2025-10-10T15:38:17.175Z" }, - { url = "https://files.pythonhosted.org/packages/e3/81/15d7c161c9ddf0900b076b55345872ed04ff1ed6a0666e5e94ab44b0163c/sqlalchemy-2.0.44-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:0fe3917059c7ab2ee3f35e77757062b1bea10a0b6ca633c58391e3f3c6c488dd", size = 2140517, upload-time = "2025-10-10T15:36:15.64Z" }, - { url = "https://files.pythonhosted.org/packages/d4/d5/4abd13b245c7d91bdf131d4916fd9e96a584dac74215f8b5bc945206a974/sqlalchemy-2.0.44-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:de4387a354ff230bc979b46b2207af841dc8bf29847b6c7dbe60af186d97aefa", size = 2130738, upload-time = "2025-10-10T15:36:16.91Z" }, - { url = "https://files.pythonhosted.org/packages/cb/3c/8418969879c26522019c1025171cefbb2a8586b6789ea13254ac602986c0/sqlalchemy-2.0.44-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c3678a0fb72c8a6a29422b2732fe423db3ce119c34421b5f9955873eb9b62c1e", size = 3304145, upload-time = "2025-10-10T15:34:19.569Z" }, - { url = "https://files.pythonhosted.org/packages/94/2d/fdb9246d9d32518bda5d90f4b65030b9bf403a935cfe4c36a474846517cb/sqlalchemy-2.0.44-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3cf6872a23601672d61a68f390e44703442639a12ee9dd5a88bbce52a695e46e", size = 3304511, upload-time = "2025-10-10T15:47:05.088Z" }, - { url = "https://files.pythonhosted.org/packages/7d/fb/40f2ad1da97d5c83f6c1269664678293d3fe28e90ad17a1093b735420549/sqlalchemy-2.0.44-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:329aa42d1be9929603f406186630135be1e7a42569540577ba2c69952b7cf399", size = 3235161, upload-time = "2025-10-10T15:34:21.193Z" }, - { url = "https://files.pythonhosted.org/packages/95/cb/7cf4078b46752dca917d18cf31910d4eff6076e5b513c2d66100c4293d83/sqlalchemy-2.0.44-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:70e03833faca7166e6a9927fbee7c27e6ecde436774cd0b24bbcc96353bce06b", size = 3261426, upload-time = "2025-10-10T15:47:07.196Z" }, - { url = "https://files.pythonhosted.org/packages/f8/3b/55c09b285cb2d55bdfa711e778bdffdd0dc3ffa052b0af41f1c5d6e582fa/sqlalchemy-2.0.44-cp311-cp311-win32.whl", hash = "sha256:253e2f29843fb303eca6b2fc645aca91fa7aa0aa70b38b6950da92d44ff267f3", size = 2105392, upload-time = "2025-10-10T15:38:20.051Z" }, - { url = "https://files.pythonhosted.org/packages/c7/23/907193c2f4d680aedbfbdf7bf24c13925e3c7c292e813326c1b84a0b878e/sqlalchemy-2.0.44-cp311-cp311-win_amd64.whl", hash = "sha256:7a8694107eb4308a13b425ca8c0e67112f8134c846b6e1f722698708741215d5", size = 2130293, upload-time = "2025-10-10T15:38:21.601Z" }, - { url = "https://files.pythonhosted.org/packages/62/c4/59c7c9b068e6813c898b771204aad36683c96318ed12d4233e1b18762164/sqlalchemy-2.0.44-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:72fea91746b5890f9e5e0997f16cbf3d53550580d76355ba2d998311b17b2250", size = 2139675, upload-time = "2025-10-10T16:03:31.064Z" }, - { url = "https://files.pythonhosted.org/packages/d6/ae/eeb0920537a6f9c5a3708e4a5fc55af25900216bdb4847ec29cfddf3bf3a/sqlalchemy-2.0.44-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:585c0c852a891450edbb1eaca8648408a3cc125f18cf433941fa6babcc359e29", size = 2127726, upload-time = "2025-10-10T16:03:35.934Z" }, - { url = "https://files.pythonhosted.org/packages/d8/d5/2ebbabe0379418eda8041c06b0b551f213576bfe4c2f09d77c06c07c8cc5/sqlalchemy-2.0.44-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9b94843a102efa9ac68a7a30cd46df3ff1ed9c658100d30a725d10d9c60a2f44", size = 3327603, upload-time = "2025-10-10T15:35:28.322Z" }, - { url = "https://files.pythonhosted.org/packages/45/e5/5aa65852dadc24b7d8ae75b7efb8d19303ed6ac93482e60c44a585930ea5/sqlalchemy-2.0.44-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:119dc41e7a7defcefc57189cfa0e61b1bf9c228211aba432b53fb71ef367fda1", size = 3337842, upload-time = "2025-10-10T15:43:45.431Z" }, - { url = "https://files.pythonhosted.org/packages/41/92/648f1afd3f20b71e880ca797a960f638d39d243e233a7082c93093c22378/sqlalchemy-2.0.44-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:0765e318ee9179b3718c4fd7ba35c434f4dd20332fbc6857a5e8df17719c24d7", size = 3264558, upload-time = "2025-10-10T15:35:29.93Z" }, - { url = "https://files.pythonhosted.org/packages/40/cf/e27d7ee61a10f74b17740918e23cbc5bc62011b48282170dc4c66da8ec0f/sqlalchemy-2.0.44-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:2e7b5b079055e02d06a4308d0481658e4f06bc7ef211567edc8f7d5dce52018d", size = 3301570, upload-time = "2025-10-10T15:43:48.407Z" }, - { url = "https://files.pythonhosted.org/packages/3b/3d/3116a9a7b63e780fb402799b6da227435be878b6846b192f076d2f838654/sqlalchemy-2.0.44-cp312-cp312-win32.whl", hash = "sha256:846541e58b9a81cce7dee8329f352c318de25aa2f2bbe1e31587eb1f057448b4", size = 2103447, upload-time = "2025-10-10T15:03:21.678Z" }, - { url = "https://files.pythonhosted.org/packages/25/83/24690e9dfc241e6ab062df82cc0df7f4231c79ba98b273fa496fb3dd78ed/sqlalchemy-2.0.44-cp312-cp312-win_amd64.whl", hash = "sha256:7cbcb47fd66ab294703e1644f78971f6f2f1126424d2b300678f419aa73c7b6e", size = 2130912, upload-time = "2025-10-10T15:03:24.656Z" }, - { url = "https://files.pythonhosted.org/packages/45/d3/c67077a2249fdb455246e6853166360054c331db4613cda3e31ab1cadbef/sqlalchemy-2.0.44-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:ff486e183d151e51b1d694c7aa1695747599bb00b9f5f604092b54b74c64a8e1", size = 2135479, upload-time = "2025-10-10T16:03:37.671Z" }, - { url = "https://files.pythonhosted.org/packages/2b/91/eabd0688330d6fd114f5f12c4f89b0d02929f525e6bf7ff80aa17ca802af/sqlalchemy-2.0.44-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:0b1af8392eb27b372ddb783b317dea0f650241cea5bd29199b22235299ca2e45", size = 2123212, upload-time = "2025-10-10T16:03:41.755Z" }, - { url = "https://files.pythonhosted.org/packages/b0/bb/43e246cfe0e81c018076a16036d9b548c4cc649de241fa27d8d9ca6f85ab/sqlalchemy-2.0.44-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2b61188657e3a2b9ac4e8f04d6cf8e51046e28175f79464c67f2fd35bceb0976", size = 3255353, upload-time = "2025-10-10T15:35:31.221Z" }, - { url = "https://files.pythonhosted.org/packages/b9/96/c6105ed9a880abe346b64d3b6ddef269ddfcab04f7f3d90a0bf3c5a88e82/sqlalchemy-2.0.44-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b87e7b91a5d5973dda5f00cd61ef72ad75a1db73a386b62877d4875a8840959c", size = 3260222, upload-time = "2025-10-10T15:43:50.124Z" }, - { url = "https://files.pythonhosted.org/packages/44/16/1857e35a47155b5ad927272fee81ae49d398959cb749edca6eaa399b582f/sqlalchemy-2.0.44-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:15f3326f7f0b2bfe406ee562e17f43f36e16167af99c4c0df61db668de20002d", size = 3189614, upload-time = "2025-10-10T15:35:32.578Z" }, - { url = "https://files.pythonhosted.org/packages/88/ee/4afb39a8ee4fc786e2d716c20ab87b5b1fb33d4ac4129a1aaa574ae8a585/sqlalchemy-2.0.44-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:1e77faf6ff919aa8cd63f1c4e561cac1d9a454a191bb864d5dd5e545935e5a40", size = 3226248, upload-time = "2025-10-10T15:43:51.862Z" }, - { url = "https://files.pythonhosted.org/packages/32/d5/0e66097fc64fa266f29a7963296b40a80d6a997b7ac13806183700676f86/sqlalchemy-2.0.44-cp313-cp313-win32.whl", hash = "sha256:ee51625c2d51f8baadf2829fae817ad0b66b140573939dd69284d2ba3553ae73", size = 2101275, upload-time = "2025-10-10T15:03:26.096Z" }, - { url = "https://files.pythonhosted.org/packages/03/51/665617fe4f8c6450f42a6d8d69243f9420f5677395572c2fe9d21b493b7b/sqlalchemy-2.0.44-cp313-cp313-win_amd64.whl", hash = "sha256:c1c80faaee1a6c3428cecf40d16a2365bcf56c424c92c2b6f0f9ad204b899e9e", size = 2127901, upload-time = "2025-10-10T15:03:27.548Z" }, - { url = "https://files.pythonhosted.org/packages/9c/5e/6a29fa884d9fb7ddadf6b69490a9d45fded3b38541713010dad16b77d015/sqlalchemy-2.0.44-py3-none-any.whl", hash = "sha256:19de7ca1246fbef9f9d1bff8f1ab25641569df226364a0e40457dc5457c54b05", size = 1928718, upload-time = "2025-10-10T15:29:45.32Z" }, -] - -[[package]] -name = "sqlalchemy-spanner" -version = "1.17.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "alembic" }, - { name = "google-cloud-spanner" }, - { name = "sqlalchemy" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/23/64/74e4d7aebc5210feff9b27e799fa81cc2bdf38f474e304e5c2b3f934f361/sqlalchemy_spanner-1.17.1.tar.gz", hash = "sha256:1542c2e69b1923974d8ad884ffc458f7d135e44af1c475b98decf75d90eccaa3", size = 82630, upload-time = "2025-10-21T14:33:54.183Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/88/72/187ca1767648d54ada46c074b2b346894712bc56b6c0dab3410bd0996209/sqlalchemy_spanner-1.17.1-py3-none-any.whl", hash = "sha256:8b8444c23e66c84aab5dbab589face8fd75733fa6c1811db368d5202cdfb5f8e", size = 31859, upload-time = "2025-10-21T14:33:52.926Z" }, -] - -[[package]] -name = "sqlparse" -version = "0.5.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/e5/40/edede8dd6977b0d3da179a342c198ed100dd2aba4be081861ee5911e4da4/sqlparse-0.5.3.tar.gz", hash = "sha256:09f67787f56a0b16ecdbde1bfc7f5d9c3371ca683cfeaa8e6ff60b4807ec9272", size = 84999, upload-time = "2024-12-10T12:05:30.728Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a9/5c/bfd6bd0bf979426d405cc6e71eceb8701b148b16c21d2dc3c261efc61c7b/sqlparse-0.5.3-py3-none-any.whl", hash = "sha256:cf2196ed3418f3ba5de6af7e82c694a9fbdbfecccdfc72e281548517081f16ca", size = 44415, upload-time = "2024-12-10T12:05:27.824Z" }, -] - -[[package]] -name = "sse-starlette" -version = "3.0.3" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/db/3c/fa6517610dc641262b77cc7bf994ecd17465812c1b0585fe33e11be758ab/sse_starlette-3.0.3.tar.gz", hash = "sha256:88cfb08747e16200ea990c8ca876b03910a23b547ab3bd764c0d8eb81019b971", size = 21943, upload-time = "2025-10-30T18:44:20.117Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/23/a0/984525d19ca5c8a6c33911a0c164b11490dd0f90ff7fd689f704f84e9a11/sse_starlette-3.0.3-py3-none-any.whl", hash = "sha256:af5bf5a6f3933df1d9c7f8539633dc8444ca6a97ab2e2a7cd3b6e431ac03a431", size = 11765, upload-time = "2025-10-30T18:44:18.834Z" }, -] - -[[package]] -name = "sseclient-py" -version = "1.8.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/e8/ed/3df5ab8bb0c12f86c28d0cadb11ed1de44a92ed35ce7ff4fd5518a809325/sseclient-py-1.8.0.tar.gz", hash = "sha256:c547c5c1a7633230a38dc599a21a2dc638f9b5c297286b48b46b935c71fac3e8", size = 7791, upload-time = "2023-09-01T19:39:20.45Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/49/58/97655efdfeb5b4eeab85b1fc5d3fa1023661246c2ab2a26ea8e47402d4f2/sseclient_py-1.8.0-py2.py3-none-any.whl", hash = "sha256:4ecca6dc0b9f963f8384e9d7fd529bf93dd7d708144c4fb5da0e0a1a926fee83", size = 8828, upload-time = "2023-09-01T19:39:17.627Z" }, -] - -[[package]] -name = "starlette" -version = "0.49.3" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/de/1a/608df0b10b53b0beb96a37854ee05864d182ddd4b1156a22f1ad3860425a/starlette-0.49.3.tar.gz", hash = "sha256:1c14546f299b5901a1ea0e34410575bc33bbd741377a10484a54445588d00284", size = 2655031, upload-time = "2025-11-01T15:12:26.13Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a3/e0/021c772d6a662f43b63044ab481dc6ac7592447605b5b35a957785363122/starlette-0.49.3-py3-none-any.whl", hash = "sha256:b579b99715fdc2980cf88c8ec96d3bf1ce16f5a8051a7c2b84ef9b1cdecaea2f", size = 74340, upload-time = "2025-11-01T15:12:24.387Z" }, -] - -[[package]] -name = "tenacity" -version = "8.5.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a3/4d/6a19536c50b849338fcbe9290d562b52cbdcf30d8963d3588a68a4107df1/tenacity-8.5.0.tar.gz", hash = "sha256:8bc6c0c8a09b31e6cad13c47afbed1a567518250a9a171418582ed8d9c20ca78", size = 47309, upload-time = "2024-07-05T07:25:31.836Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d2/3f/8ba87d9e287b9d385a02a7114ddcef61b26f86411e121c9003eb509a1773/tenacity-8.5.0-py3-none-any.whl", hash = "sha256:b594c2a5945830c267ce6b79a166228323ed52718f30302c1359836112346687", size = 28165, upload-time = "2024-07-05T07:25:29.591Z" }, -] - -[[package]] -name = "text-unidecode" -version = "1.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ab/e2/e9a00f0ccb71718418230718b3d900e71a5d16e701a3dae079a21e9cd8f8/text-unidecode-1.3.tar.gz", hash = "sha256:bad6603bb14d279193107714b288be206cac565dfa49aa5b105294dd5c4aab93", size = 76885, upload-time = "2019-08-30T21:36:45.405Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a6/a5/c0b6468d3824fe3fde30dbb5e1f687b291608f9473681bbf7dabbf5a87d7/text_unidecode-1.3-py2.py3-none-any.whl", hash = "sha256:1311f10e8b895935241623731c2ba64f4c455287888b18189350b67134a822e8", size = 78154, upload-time = "2019-08-30T21:37:03.543Z" }, -] - -[[package]] -name = "tomli" -version = "2.3.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/52/ed/3f73f72945444548f33eba9a87fc7a6e969915e7b1acc8260b30e1f76a2f/tomli-2.3.0.tar.gz", hash = "sha256:64be704a875d2a59753d80ee8a533c3fe183e3f06807ff7dc2232938ccb01549", size = 17392, upload-time = "2025-10-08T22:01:47.119Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b3/2e/299f62b401438d5fe1624119c723f5d877acc86a4c2492da405626665f12/tomli-2.3.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:88bd15eb972f3664f5ed4b57c1634a97153b4bac4479dcb6a495f41921eb7f45", size = 153236, upload-time = "2025-10-08T22:01:00.137Z" }, - { url = "https://files.pythonhosted.org/packages/86/7f/d8fffe6a7aefdb61bced88fcb5e280cfd71e08939da5894161bd71bea022/tomli-2.3.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:883b1c0d6398a6a9d29b508c331fa56adbcdff647f6ace4dfca0f50e90dfd0ba", size = 148084, upload-time = "2025-10-08T22:01:01.63Z" }, - { url = "https://files.pythonhosted.org/packages/47/5c/24935fb6a2ee63e86d80e4d3b58b222dafaf438c416752c8b58537c8b89a/tomli-2.3.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d1381caf13ab9f300e30dd8feadb3de072aeb86f1d34a8569453ff32a7dea4bf", size = 234832, upload-time = "2025-10-08T22:01:02.543Z" }, - { url = "https://files.pythonhosted.org/packages/89/da/75dfd804fc11e6612846758a23f13271b76d577e299592b4371a4ca4cd09/tomli-2.3.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a0e285d2649b78c0d9027570d4da3425bdb49830a6156121360b3f8511ea3441", size = 242052, upload-time = "2025-10-08T22:01:03.836Z" }, - { url = "https://files.pythonhosted.org/packages/70/8c/f48ac899f7b3ca7eb13af73bacbc93aec37f9c954df3c08ad96991c8c373/tomli-2.3.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:0a154a9ae14bfcf5d8917a59b51ffd5a3ac1fd149b71b47a3a104ca4edcfa845", size = 239555, upload-time = "2025-10-08T22:01:04.834Z" }, - { url = "https://files.pythonhosted.org/packages/ba/28/72f8afd73f1d0e7829bfc093f4cb98ce0a40ffc0cc997009ee1ed94ba705/tomli-2.3.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:74bf8464ff93e413514fefd2be591c3b0b23231a77f901db1eb30d6f712fc42c", size = 245128, upload-time = "2025-10-08T22:01:05.84Z" }, - { url = "https://files.pythonhosted.org/packages/b6/eb/a7679c8ac85208706d27436e8d421dfa39d4c914dcf5fa8083a9305f58d9/tomli-2.3.0-cp311-cp311-win32.whl", hash = "sha256:00b5f5d95bbfc7d12f91ad8c593a1659b6387b43f054104cda404be6bda62456", size = 96445, upload-time = "2025-10-08T22:01:06.896Z" }, - { url = "https://files.pythonhosted.org/packages/0a/fe/3d3420c4cb1ad9cb462fb52967080575f15898da97e21cb6f1361d505383/tomli-2.3.0-cp311-cp311-win_amd64.whl", hash = "sha256:4dc4ce8483a5d429ab602f111a93a6ab1ed425eae3122032db7e9acf449451be", size = 107165, upload-time = "2025-10-08T22:01:08.107Z" }, - { url = "https://files.pythonhosted.org/packages/ff/b7/40f36368fcabc518bb11c8f06379a0fd631985046c038aca08c6d6a43c6e/tomli-2.3.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:d7d86942e56ded512a594786a5ba0a5e521d02529b3826e7761a05138341a2ac", size = 154891, upload-time = "2025-10-08T22:01:09.082Z" }, - { url = "https://files.pythonhosted.org/packages/f9/3f/d9dd692199e3b3aab2e4e4dd948abd0f790d9ded8cd10cbaae276a898434/tomli-2.3.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:73ee0b47d4dad1c5e996e3cd33b8a76a50167ae5f96a2607cbe8cc773506ab22", size = 148796, upload-time = "2025-10-08T22:01:10.266Z" }, - { url = "https://files.pythonhosted.org/packages/60/83/59bff4996c2cf9f9387a0f5a3394629c7efa5ef16142076a23a90f1955fa/tomli-2.3.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:792262b94d5d0a466afb5bc63c7daa9d75520110971ee269152083270998316f", size = 242121, upload-time = "2025-10-08T22:01:11.332Z" }, - { url = "https://files.pythonhosted.org/packages/45/e5/7c5119ff39de8693d6baab6c0b6dcb556d192c165596e9fc231ea1052041/tomli-2.3.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4f195fe57ecceac95a66a75ac24d9d5fbc98ef0962e09b2eddec5d39375aae52", size = 250070, upload-time = "2025-10-08T22:01:12.498Z" }, - { url = "https://files.pythonhosted.org/packages/45/12/ad5126d3a278f27e6701abde51d342aa78d06e27ce2bb596a01f7709a5a2/tomli-2.3.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:e31d432427dcbf4d86958c184b9bfd1e96b5b71f8eb17e6d02531f434fd335b8", size = 245859, upload-time = "2025-10-08T22:01:13.551Z" }, - { url = "https://files.pythonhosted.org/packages/fb/a1/4d6865da6a71c603cfe6ad0e6556c73c76548557a8d658f9e3b142df245f/tomli-2.3.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:7b0882799624980785240ab732537fcfc372601015c00f7fc367c55308c186f6", size = 250296, upload-time = "2025-10-08T22:01:14.614Z" }, - { url = "https://files.pythonhosted.org/packages/a0/b7/a7a7042715d55c9ba6e8b196d65d2cb662578b4d8cd17d882d45322b0d78/tomli-2.3.0-cp312-cp312-win32.whl", hash = "sha256:ff72b71b5d10d22ecb084d345fc26f42b5143c5533db5e2eaba7d2d335358876", size = 97124, upload-time = "2025-10-08T22:01:15.629Z" }, - { url = "https://files.pythonhosted.org/packages/06/1e/f22f100db15a68b520664eb3328fb0ae4e90530887928558112c8d1f4515/tomli-2.3.0-cp312-cp312-win_amd64.whl", hash = "sha256:1cb4ed918939151a03f33d4242ccd0aa5f11b3547d0cf30f7c74a408a5b99878", size = 107698, upload-time = "2025-10-08T22:01:16.51Z" }, - { url = "https://files.pythonhosted.org/packages/89/48/06ee6eabe4fdd9ecd48bf488f4ac783844fd777f547b8d1b61c11939974e/tomli-2.3.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:5192f562738228945d7b13d4930baffda67b69425a7f0da96d360b0a3888136b", size = 154819, upload-time = "2025-10-08T22:01:17.964Z" }, - { url = "https://files.pythonhosted.org/packages/f1/01/88793757d54d8937015c75dcdfb673c65471945f6be98e6a0410fba167ed/tomli-2.3.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:be71c93a63d738597996be9528f4abe628d1adf5e6eb11607bc8fe1a510b5dae", size = 148766, upload-time = "2025-10-08T22:01:18.959Z" }, - { url = "https://files.pythonhosted.org/packages/42/17/5e2c956f0144b812e7e107f94f1cc54af734eb17b5191c0bbfb72de5e93e/tomli-2.3.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c4665508bcbac83a31ff8ab08f424b665200c0e1e645d2bd9ab3d3e557b6185b", size = 240771, upload-time = "2025-10-08T22:01:20.106Z" }, - { url = "https://files.pythonhosted.org/packages/d5/f4/0fbd014909748706c01d16824eadb0307115f9562a15cbb012cd9b3512c5/tomli-2.3.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4021923f97266babc6ccab9f5068642a0095faa0a51a246a6a02fccbb3514eaf", size = 248586, upload-time = "2025-10-08T22:01:21.164Z" }, - { url = "https://files.pythonhosted.org/packages/30/77/fed85e114bde5e81ecf9bc5da0cc69f2914b38f4708c80ae67d0c10180c5/tomli-2.3.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a4ea38c40145a357d513bffad0ed869f13c1773716cf71ccaa83b0fa0cc4e42f", size = 244792, upload-time = "2025-10-08T22:01:22.417Z" }, - { url = "https://files.pythonhosted.org/packages/55/92/afed3d497f7c186dc71e6ee6d4fcb0acfa5f7d0a1a2878f8beae379ae0cc/tomli-2.3.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:ad805ea85eda330dbad64c7ea7a4556259665bdf9d2672f5dccc740eb9d3ca05", size = 248909, upload-time = "2025-10-08T22:01:23.859Z" }, - { url = "https://files.pythonhosted.org/packages/f8/84/ef50c51b5a9472e7265ce1ffc7f24cd4023d289e109f669bdb1553f6a7c2/tomli-2.3.0-cp313-cp313-win32.whl", hash = "sha256:97d5eec30149fd3294270e889b4234023f2c69747e555a27bd708828353ab606", size = 96946, upload-time = "2025-10-08T22:01:24.893Z" }, - { url = "https://files.pythonhosted.org/packages/b2/b7/718cd1da0884f281f95ccfa3a6cc572d30053cba64603f79d431d3c9b61b/tomli-2.3.0-cp313-cp313-win_amd64.whl", hash = "sha256:0c95ca56fbe89e065c6ead5b593ee64b84a26fca063b5d71a1122bf26e533999", size = 107705, upload-time = "2025-10-08T22:01:26.153Z" }, - { url = "https://files.pythonhosted.org/packages/19/94/aeafa14a52e16163008060506fcb6aa1949d13548d13752171a755c65611/tomli-2.3.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:cebc6fe843e0733ee827a282aca4999b596241195f43b4cc371d64fc6639da9e", size = 154244, upload-time = "2025-10-08T22:01:27.06Z" }, - { url = "https://files.pythonhosted.org/packages/db/e4/1e58409aa78eefa47ccd19779fc6f36787edbe7d4cd330eeeedb33a4515b/tomli-2.3.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:4c2ef0244c75aba9355561272009d934953817c49f47d768070c3c94355c2aa3", size = 148637, upload-time = "2025-10-08T22:01:28.059Z" }, - { url = "https://files.pythonhosted.org/packages/26/b6/d1eccb62f665e44359226811064596dd6a366ea1f985839c566cd61525ae/tomli-2.3.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c22a8bf253bacc0cf11f35ad9808b6cb75ada2631c2d97c971122583b129afbc", size = 241925, upload-time = "2025-10-08T22:01:29.066Z" }, - { url = "https://files.pythonhosted.org/packages/70/91/7cdab9a03e6d3d2bb11beae108da5bdc1c34bdeb06e21163482544ddcc90/tomli-2.3.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0eea8cc5c5e9f89c9b90c4896a8deefc74f518db5927d0e0e8d4a80953d774d0", size = 249045, upload-time = "2025-10-08T22:01:31.98Z" }, - { url = "https://files.pythonhosted.org/packages/15/1b/8c26874ed1f6e4f1fcfeb868db8a794cbe9f227299402db58cfcc858766c/tomli-2.3.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:b74a0e59ec5d15127acdabd75ea17726ac4c5178ae51b85bfe39c4f8a278e879", size = 245835, upload-time = "2025-10-08T22:01:32.989Z" }, - { url = "https://files.pythonhosted.org/packages/fd/42/8e3c6a9a4b1a1360c1a2a39f0b972cef2cc9ebd56025168c4137192a9321/tomli-2.3.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:b5870b50c9db823c595983571d1296a6ff3e1b88f734a4c8f6fc6188397de005", size = 253109, upload-time = "2025-10-08T22:01:34.052Z" }, - { url = "https://files.pythonhosted.org/packages/22/0c/b4da635000a71b5f80130937eeac12e686eefb376b8dee113b4a582bba42/tomli-2.3.0-cp314-cp314-win32.whl", hash = "sha256:feb0dacc61170ed7ab602d3d972a58f14ee3ee60494292d384649a3dc38ef463", size = 97930, upload-time = "2025-10-08T22:01:35.082Z" }, - { url = "https://files.pythonhosted.org/packages/b9/74/cb1abc870a418ae99cd5c9547d6bce30701a954e0e721821df483ef7223c/tomli-2.3.0-cp314-cp314-win_amd64.whl", hash = "sha256:b273fcbd7fc64dc3600c098e39136522650c49bca95df2d11cf3b626422392c8", size = 107964, upload-time = "2025-10-08T22:01:36.057Z" }, - { url = "https://files.pythonhosted.org/packages/54/78/5c46fff6432a712af9f792944f4fcd7067d8823157949f4e40c56b8b3c83/tomli-2.3.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:940d56ee0410fa17ee1f12b817b37a4d4e4dc4d27340863cc67236c74f582e77", size = 163065, upload-time = "2025-10-08T22:01:37.27Z" }, - { url = "https://files.pythonhosted.org/packages/39/67/f85d9bd23182f45eca8939cd2bc7050e1f90c41f4a2ecbbd5963a1d1c486/tomli-2.3.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:f85209946d1fe94416debbb88d00eb92ce9cd5266775424ff81bc959e001acaf", size = 159088, upload-time = "2025-10-08T22:01:38.235Z" }, - { url = "https://files.pythonhosted.org/packages/26/5a/4b546a0405b9cc0659b399f12b6adb750757baf04250b148d3c5059fc4eb/tomli-2.3.0-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:a56212bdcce682e56b0aaf79e869ba5d15a6163f88d5451cbde388d48b13f530", size = 268193, upload-time = "2025-10-08T22:01:39.712Z" }, - { url = "https://files.pythonhosted.org/packages/42/4f/2c12a72ae22cf7b59a7fe75b3465b7aba40ea9145d026ba41cb382075b0e/tomli-2.3.0-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c5f3ffd1e098dfc032d4d3af5c0ac64f6d286d98bc148698356847b80fa4de1b", size = 275488, upload-time = "2025-10-08T22:01:40.773Z" }, - { url = "https://files.pythonhosted.org/packages/92/04/a038d65dbe160c3aa5a624e93ad98111090f6804027d474ba9c37c8ae186/tomli-2.3.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:5e01decd096b1530d97d5d85cb4dff4af2d8347bd35686654a004f8dea20fc67", size = 272669, upload-time = "2025-10-08T22:01:41.824Z" }, - { url = "https://files.pythonhosted.org/packages/be/2f/8b7c60a9d1612a7cbc39ffcca4f21a73bf368a80fc25bccf8253e2563267/tomli-2.3.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:8a35dd0e643bb2610f156cca8db95d213a90015c11fee76c946aa62b7ae7e02f", size = 279709, upload-time = "2025-10-08T22:01:43.177Z" }, - { url = "https://files.pythonhosted.org/packages/7e/46/cc36c679f09f27ded940281c38607716c86cf8ba4a518d524e349c8b4874/tomli-2.3.0-cp314-cp314t-win32.whl", hash = "sha256:a1f7f282fe248311650081faafa5f4732bdbfef5d45fe3f2e702fbc6f2d496e0", size = 107563, upload-time = "2025-10-08T22:01:44.233Z" }, - { url = "https://files.pythonhosted.org/packages/84/ff/426ca8683cf7b753614480484f6437f568fd2fda2edbdf57a2d3d8b27a0b/tomli-2.3.0-cp314-cp314t-win_amd64.whl", hash = "sha256:70a251f8d4ba2d9ac2542eecf008b3c8a9fc5c3f9f02c56a9d7952612be2fdba", size = 119756, upload-time = "2025-10-08T22:01:45.234Z" }, - { url = "https://files.pythonhosted.org/packages/77/b8/0135fadc89e73be292b473cb820b4f5a08197779206b33191e801feeae40/tomli-2.3.0-py3-none-any.whl", hash = "sha256:e95b1af3c5b07d9e643909b5abbec77cd9f1217e6d0bca72b0234736b9fb1f1b", size = 14408, upload-time = "2025-10-08T22:01:46.04Z" }, -] - -[[package]] -name = "tqdm" -version = "4.67.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "colorama", marker = "sys_platform == 'win32'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/a8/4b/29b4ef32e036bb34e4ab51796dd745cdba7ed47ad142a9f4a1eb8e0c744d/tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2", size = 169737, upload-time = "2024-11-24T20:12:22.481Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d0/30/dc54f88dd4a2b5dc8a0279bdd7270e735851848b762aeb1c1184ed1f6b14/tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2", size = 78540, upload-time = "2024-11-24T20:12:19.698Z" }, -] - -[[package]] -name = "typing-extensions" -version = "4.15.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/72/94/1a15dd82efb362ac84269196e94cf00f187f7ed21c242792a923cdb1c61f/typing_extensions-4.15.0.tar.gz", hash = "sha256:0cea48d173cc12fa28ecabc3b837ea3cf6f38c6d1136f85cbaaf598984861466", size = 109391, upload-time = "2025-08-25T13:49:26.313Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl", hash = "sha256:f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548", size = 44614, upload-time = "2025-08-25T13:49:24.86Z" }, -] - -[[package]] -name = "typing-inspection" -version = "0.4.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/55/e3/70399cb7dd41c10ac53367ae42139cf4b1ca5f36bb3dc6c9d33acdb43655/typing_inspection-0.4.2.tar.gz", hash = "sha256:ba561c48a67c5958007083d386c3295464928b01faa735ab8547c5692e87f464", size = 75949, upload-time = "2025-10-01T02:14:41.687Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/dc/9b/47798a6c91d8bdb567fe2698fe81e0c6b7cb7ef4d13da4114b41d239f65d/typing_inspection-0.4.2-py3-none-any.whl", hash = "sha256:4ed1cacbdc298c220f1bd249ed5287caa16f34d44ef4e9c3d0cbad5b521545e7", size = 14611, upload-time = "2025-10-01T02:14:40.154Z" }, -] - -[[package]] -name = "tzdata" -version = "2025.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/95/32/1a225d6164441be760d75c2c42e2780dc0873fe382da3e98a2e1e48361e5/tzdata-2025.2.tar.gz", hash = "sha256:b60a638fcc0daffadf82fe0f57e53d06bdec2f36c4df66280ae79bce6bd6f2b9", size = 196380, upload-time = "2025-03-23T13:54:43.652Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/5c/23/c7abc0ca0a1526a0774eca151daeb8de62ec457e77262b66b359c3c7679e/tzdata-2025.2-py2.py3-none-any.whl", hash = "sha256:1a403fada01ff9221ca8044d701868fa132215d84beb92242d9acd2147f667a8", size = 347839, upload-time = "2025-03-23T13:54:41.845Z" }, -] - -[[package]] -name = "tzlocal" -version = "5.3.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "tzdata", marker = "sys_platform == 'win32'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/8b/2e/c14812d3d4d9cd1773c6be938f89e5735a1f11a9f184ac3639b93cef35d5/tzlocal-5.3.1.tar.gz", hash = "sha256:cceffc7edecefea1f595541dbd6e990cb1ea3d19bf01b2809f362a03dd7921fd", size = 30761, upload-time = "2025-03-05T21:17:41.549Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/c2/14/e2a54fabd4f08cd7af1c07030603c3356b74da07f7cc056e600436edfa17/tzlocal-5.3.1-py3-none-any.whl", hash = "sha256:eb1a66c3ef5847adf7a834f1be0800581b683b5608e74f86ecbcef8ab91bb85d", size = 18026, upload-time = "2025-03-05T21:17:39.857Z" }, -] - -[[package]] -name = "uritemplate" -version = "4.2.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/98/60/f174043244c5306c9988380d2cb10009f91563fc4b31293d27e17201af56/uritemplate-4.2.0.tar.gz", hash = "sha256:480c2ed180878955863323eea31b0ede668795de182617fef9c6ca09e6ec9d0e", size = 33267, upload-time = "2025-06-02T15:12:06.318Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a9/99/3ae339466c9183ea5b8ae87b34c0b897eda475d2aec2307cae60e5cd4f29/uritemplate-4.2.0-py3-none-any.whl", hash = "sha256:962201ba1c4edcab02e60f9a0d3821e82dfc5d2d6662a21abd533879bdb8a686", size = 11488, upload-time = "2025-06-02T15:12:03.405Z" }, -] - -[[package]] -name = "urllib3" -version = "1.26.20" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/e4/e8/6ff5e6bc22095cfc59b6ea711b687e2b7ed4bdb373f7eeec370a97d7392f/urllib3-1.26.20.tar.gz", hash = "sha256:40c2dc0c681e47eb8f90e7e27bf6ff7df2e677421fd46756da1161c39ca70d32", size = 307380, upload-time = "2024-08-29T15:43:11.37Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/33/cf/8435d5a7159e2a9c83a95896ed596f68cf798005fe107cc655b5c5c14704/urllib3-1.26.20-py2.py3-none-any.whl", hash = "sha256:0ed14ccfbf1c30a9072c7ca157e4319b70d65f623e91e7b32fadb2853431016e", size = 144225, upload-time = "2024-08-29T15:43:08.921Z" }, -] - -[[package]] -name = "uvicorn" -version = "0.38.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "click" }, - { name = "h11" }, - { name = "typing-extensions", marker = "python_full_version < '3.11'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/cb/ce/f06b84e2697fef4688ca63bdb2fdf113ca0a3be33f94488f2cadb690b0cf/uvicorn-0.38.0.tar.gz", hash = "sha256:fd97093bdd120a2609fc0d3afe931d4d4ad688b6e75f0f929fde1bc36fe0e91d", size = 80605, upload-time = "2025-10-18T13:46:44.63Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ee/d9/d88e73ca598f4f6ff671fb5fde8a32925c2e08a637303a1d12883c7305fa/uvicorn-0.38.0-py3-none-any.whl", hash = "sha256:48c0afd214ceb59340075b4a052ea1ee91c16fbc2a9b1469cca0e54566977b02", size = 68109, upload-time = "2025-10-18T13:46:42.958Z" }, -] - -[[package]] -name = "vcrpy" -version = "7.0.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "pyyaml" }, - { name = "urllib3" }, - { name = "wrapt" }, - { name = "yarl" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/25/d3/856e06184d4572aada1dd559ddec3bedc46df1f2edc5ab2c91121a2cccdb/vcrpy-7.0.0.tar.gz", hash = "sha256:176391ad0425edde1680c5b20738ea3dc7fb942520a48d2993448050986b3a50", size = 85502, upload-time = "2024-12-31T00:07:57.894Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/13/5d/1f15b252890c968d42b348d1e9b0aa12d5bf3e776704178ec37cceccdb63/vcrpy-7.0.0-py2.py3-none-any.whl", hash = "sha256:55791e26c18daa363435054d8b35bd41a4ac441b6676167635d1b37a71dbe124", size = 42321, upload-time = "2024-12-31T00:07:55.277Z" }, -] - -[[package]] -name = "watchdog" -version = "6.0.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/db/7d/7f3d619e951c88ed75c6037b246ddcf2d322812ee8ea189be89511721d54/watchdog-6.0.0.tar.gz", hash = "sha256:9ddf7c82fda3ae8e24decda1338ede66e1c99883db93711d8fb941eaa2d8c282", size = 131220, upload-time = "2024-11-01T14:07:13.037Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/0c/56/90994d789c61df619bfc5ce2ecdabd5eeff564e1eb47512bd01b5e019569/watchdog-6.0.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:d1cdb490583ebd691c012b3d6dae011000fe42edb7a82ece80965b42abd61f26", size = 96390, upload-time = "2024-11-01T14:06:24.793Z" }, - { url = "https://files.pythonhosted.org/packages/55/46/9a67ee697342ddf3c6daa97e3a587a56d6c4052f881ed926a849fcf7371c/watchdog-6.0.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:bc64ab3bdb6a04d69d4023b29422170b74681784ffb9463ed4870cf2f3e66112", size = 88389, upload-time = "2024-11-01T14:06:27.112Z" }, - { url = "https://files.pythonhosted.org/packages/44/65/91b0985747c52064d8701e1075eb96f8c40a79df889e59a399453adfb882/watchdog-6.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c897ac1b55c5a1461e16dae288d22bb2e412ba9807df8397a635d88f671d36c3", size = 89020, upload-time = "2024-11-01T14:06:29.876Z" }, - { url = "https://files.pythonhosted.org/packages/e0/24/d9be5cd6642a6aa68352ded4b4b10fb0d7889cb7f45814fb92cecd35f101/watchdog-6.0.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:6eb11feb5a0d452ee41f824e271ca311a09e250441c262ca2fd7ebcf2461a06c", size = 96393, upload-time = "2024-11-01T14:06:31.756Z" }, - { url = "https://files.pythonhosted.org/packages/63/7a/6013b0d8dbc56adca7fdd4f0beed381c59f6752341b12fa0886fa7afc78b/watchdog-6.0.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:ef810fbf7b781a5a593894e4f439773830bdecb885e6880d957d5b9382a960d2", size = 88392, upload-time = "2024-11-01T14:06:32.99Z" }, - { url = "https://files.pythonhosted.org/packages/d1/40/b75381494851556de56281e053700e46bff5b37bf4c7267e858640af5a7f/watchdog-6.0.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:afd0fe1b2270917c5e23c2a65ce50c2a4abb63daafb0d419fde368e272a76b7c", size = 89019, upload-time = "2024-11-01T14:06:34.963Z" }, - { url = "https://files.pythonhosted.org/packages/39/ea/3930d07dafc9e286ed356a679aa02d777c06e9bfd1164fa7c19c288a5483/watchdog-6.0.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:bdd4e6f14b8b18c334febb9c4425a878a2ac20efd1e0b231978e7b150f92a948", size = 96471, upload-time = "2024-11-01T14:06:37.745Z" }, - { url = "https://files.pythonhosted.org/packages/12/87/48361531f70b1f87928b045df868a9fd4e253d9ae087fa4cf3f7113be363/watchdog-6.0.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:c7c15dda13c4eb00d6fb6fc508b3c0ed88b9d5d374056b239c4ad1611125c860", size = 88449, upload-time = "2024-11-01T14:06:39.748Z" }, - { url = "https://files.pythonhosted.org/packages/5b/7e/8f322f5e600812e6f9a31b75d242631068ca8f4ef0582dd3ae6e72daecc8/watchdog-6.0.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6f10cb2d5902447c7d0da897e2c6768bca89174d0c6e1e30abec5421af97a5b0", size = 89054, upload-time = "2024-11-01T14:06:41.009Z" }, - { url = "https://files.pythonhosted.org/packages/68/98/b0345cabdce2041a01293ba483333582891a3bd5769b08eceb0d406056ef/watchdog-6.0.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:490ab2ef84f11129844c23fb14ecf30ef3d8a6abafd3754a6f75ca1e6654136c", size = 96480, upload-time = "2024-11-01T14:06:42.952Z" }, - { url = "https://files.pythonhosted.org/packages/85/83/cdf13902c626b28eedef7ec4f10745c52aad8a8fe7eb04ed7b1f111ca20e/watchdog-6.0.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:76aae96b00ae814b181bb25b1b98076d5fc84e8a53cd8885a318b42b6d3a5134", size = 88451, upload-time = "2024-11-01T14:06:45.084Z" }, - { url = "https://files.pythonhosted.org/packages/fe/c4/225c87bae08c8b9ec99030cd48ae9c4eca050a59bf5c2255853e18c87b50/watchdog-6.0.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a175f755fc2279e0b7312c0035d52e27211a5bc39719dd529625b1930917345b", size = 89057, upload-time = "2024-11-01T14:06:47.324Z" }, - { url = "https://files.pythonhosted.org/packages/30/ad/d17b5d42e28a8b91f8ed01cb949da092827afb9995d4559fd448d0472763/watchdog-6.0.0-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:c7ac31a19f4545dd92fc25d200694098f42c9a8e391bc00bdd362c5736dbf881", size = 87902, upload-time = "2024-11-01T14:06:53.119Z" }, - { url = "https://files.pythonhosted.org/packages/5c/ca/c3649991d140ff6ab67bfc85ab42b165ead119c9e12211e08089d763ece5/watchdog-6.0.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:9513f27a1a582d9808cf21a07dae516f0fab1cf2d7683a742c498b93eedabb11", size = 88380, upload-time = "2024-11-01T14:06:55.19Z" }, - { url = "https://files.pythonhosted.org/packages/a9/c7/ca4bf3e518cb57a686b2feb4f55a1892fd9a3dd13f470fca14e00f80ea36/watchdog-6.0.0-py3-none-manylinux2014_aarch64.whl", hash = "sha256:7607498efa04a3542ae3e05e64da8202e58159aa1fa4acddf7678d34a35d4f13", size = 79079, upload-time = "2024-11-01T14:06:59.472Z" }, - { url = "https://files.pythonhosted.org/packages/5c/51/d46dc9332f9a647593c947b4b88e2381c8dfc0942d15b8edc0310fa4abb1/watchdog-6.0.0-py3-none-manylinux2014_armv7l.whl", hash = "sha256:9041567ee8953024c83343288ccc458fd0a2d811d6a0fd68c4c22609e3490379", size = 79078, upload-time = "2024-11-01T14:07:01.431Z" }, - { url = "https://files.pythonhosted.org/packages/d4/57/04edbf5e169cd318d5f07b4766fee38e825d64b6913ca157ca32d1a42267/watchdog-6.0.0-py3-none-manylinux2014_i686.whl", hash = "sha256:82dc3e3143c7e38ec49d61af98d6558288c415eac98486a5c581726e0737c00e", size = 79076, upload-time = "2024-11-01T14:07:02.568Z" }, - { url = "https://files.pythonhosted.org/packages/ab/cc/da8422b300e13cb187d2203f20b9253e91058aaf7db65b74142013478e66/watchdog-6.0.0-py3-none-manylinux2014_ppc64.whl", hash = "sha256:212ac9b8bf1161dc91bd09c048048a95ca3a4c4f5e5d4a7d1b1a7d5752a7f96f", size = 79077, upload-time = "2024-11-01T14:07:03.893Z" }, - { url = "https://files.pythonhosted.org/packages/2c/3b/b8964e04ae1a025c44ba8e4291f86e97fac443bca31de8bd98d3263d2fcf/watchdog-6.0.0-py3-none-manylinux2014_ppc64le.whl", hash = "sha256:e3df4cbb9a450c6d49318f6d14f4bbc80d763fa587ba46ec86f99f9e6876bb26", size = 79078, upload-time = "2024-11-01T14:07:05.189Z" }, - { url = "https://files.pythonhosted.org/packages/62/ae/a696eb424bedff7407801c257d4b1afda455fe40821a2be430e173660e81/watchdog-6.0.0-py3-none-manylinux2014_s390x.whl", hash = "sha256:2cce7cfc2008eb51feb6aab51251fd79b85d9894e98ba847408f662b3395ca3c", size = 79077, upload-time = "2024-11-01T14:07:06.376Z" }, - { url = "https://files.pythonhosted.org/packages/b5/e8/dbf020b4d98251a9860752a094d09a65e1b436ad181faf929983f697048f/watchdog-6.0.0-py3-none-manylinux2014_x86_64.whl", hash = "sha256:20ffe5b202af80ab4266dcd3e91aae72bf2da48c0d33bdb15c66658e685e94e2", size = 79078, upload-time = "2024-11-01T14:07:07.547Z" }, - { url = "https://files.pythonhosted.org/packages/07/f6/d0e5b343768e8bcb4cda79f0f2f55051bf26177ecd5651f84c07567461cf/watchdog-6.0.0-py3-none-win32.whl", hash = "sha256:07df1fdd701c5d4c8e55ef6cf55b8f0120fe1aef7ef39a1c6fc6bc2e606d517a", size = 79065, upload-time = "2024-11-01T14:07:09.525Z" }, - { url = "https://files.pythonhosted.org/packages/db/d9/c495884c6e548fce18a8f40568ff120bc3a4b7b99813081c8ac0c936fa64/watchdog-6.0.0-py3-none-win_amd64.whl", hash = "sha256:cbafb470cf848d93b5d013e2ecb245d4aa1c8fd0504e863ccefa32445359d680", size = 79070, upload-time = "2024-11-01T14:07:10.686Z" }, - { url = "https://files.pythonhosted.org/packages/33/e8/e40370e6d74ddba47f002a32919d91310d6074130fe4e17dabcafc15cbf1/watchdog-6.0.0-py3-none-win_ia64.whl", hash = "sha256:a1914259fa9e1454315171103c6a30961236f508b9b623eae470268bbcc6a22f", size = 79067, upload-time = "2024-11-01T14:07:11.845Z" }, -] - -[[package]] -name = "websockets" -version = "15.0.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/21/e6/26d09fab466b7ca9c7737474c52be4f76a40301b08362eb2dbc19dcc16c1/websockets-15.0.1.tar.gz", hash = "sha256:82544de02076bafba038ce055ee6412d68da13ab47f0c60cab827346de828dee", size = 177016, upload-time = "2025-03-05T20:03:41.606Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/1e/da/6462a9f510c0c49837bbc9345aca92d767a56c1fb2939e1579df1e1cdcf7/websockets-15.0.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:d63efaa0cd96cf0c5fe4d581521d9fa87744540d4bc999ae6e08595a1014b45b", size = 175423, upload-time = "2025-03-05T20:01:35.363Z" }, - { url = "https://files.pythonhosted.org/packages/1c/9f/9d11c1a4eb046a9e106483b9ff69bce7ac880443f00e5ce64261b47b07e7/websockets-15.0.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ac60e3b188ec7574cb761b08d50fcedf9d77f1530352db4eef1707fe9dee7205", size = 173080, upload-time = "2025-03-05T20:01:37.304Z" }, - { url = "https://files.pythonhosted.org/packages/d5/4f/b462242432d93ea45f297b6179c7333dd0402b855a912a04e7fc61c0d71f/websockets-15.0.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:5756779642579d902eed757b21b0164cd6fe338506a8083eb58af5c372e39d9a", size = 173329, upload-time = "2025-03-05T20:01:39.668Z" }, - { url = "https://files.pythonhosted.org/packages/6e/0c/6afa1f4644d7ed50284ac59cc70ef8abd44ccf7d45850d989ea7310538d0/websockets-15.0.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0fdfe3e2a29e4db3659dbd5bbf04560cea53dd9610273917799f1cde46aa725e", size = 182312, upload-time = "2025-03-05T20:01:41.815Z" }, - { url = "https://files.pythonhosted.org/packages/dd/d4/ffc8bd1350b229ca7a4db2a3e1c482cf87cea1baccd0ef3e72bc720caeec/websockets-15.0.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4c2529b320eb9e35af0fa3016c187dffb84a3ecc572bcee7c3ce302bfeba52bf", size = 181319, upload-time = "2025-03-05T20:01:43.967Z" }, - { url = "https://files.pythonhosted.org/packages/97/3a/5323a6bb94917af13bbb34009fac01e55c51dfde354f63692bf2533ffbc2/websockets-15.0.1-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ac1e5c9054fe23226fb11e05a6e630837f074174c4c2f0fe442996112a6de4fb", size = 181631, upload-time = "2025-03-05T20:01:46.104Z" }, - { url = "https://files.pythonhosted.org/packages/a6/cc/1aeb0f7cee59ef065724041bb7ed667b6ab1eeffe5141696cccec2687b66/websockets-15.0.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:5df592cd503496351d6dc14f7cdad49f268d8e618f80dce0cd5a36b93c3fc08d", size = 182016, upload-time = "2025-03-05T20:01:47.603Z" }, - { url = "https://files.pythonhosted.org/packages/79/f9/c86f8f7af208e4161a7f7e02774e9d0a81c632ae76db2ff22549e1718a51/websockets-15.0.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:0a34631031a8f05657e8e90903e656959234f3a04552259458aac0b0f9ae6fd9", size = 181426, upload-time = "2025-03-05T20:01:48.949Z" }, - { url = "https://files.pythonhosted.org/packages/c7/b9/828b0bc6753db905b91df6ae477c0b14a141090df64fb17f8a9d7e3516cf/websockets-15.0.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:3d00075aa65772e7ce9e990cab3ff1de702aa09be3940d1dc88d5abf1ab8a09c", size = 181360, upload-time = "2025-03-05T20:01:50.938Z" }, - { url = "https://files.pythonhosted.org/packages/89/fb/250f5533ec468ba6327055b7d98b9df056fb1ce623b8b6aaafb30b55d02e/websockets-15.0.1-cp310-cp310-win32.whl", hash = "sha256:1234d4ef35db82f5446dca8e35a7da7964d02c127b095e172e54397fb6a6c256", size = 176388, upload-time = "2025-03-05T20:01:52.213Z" }, - { url = "https://files.pythonhosted.org/packages/1c/46/aca7082012768bb98e5608f01658ff3ac8437e563eca41cf068bd5849a5e/websockets-15.0.1-cp310-cp310-win_amd64.whl", hash = "sha256:39c1fec2c11dc8d89bba6b2bf1556af381611a173ac2b511cf7231622058af41", size = 176830, upload-time = "2025-03-05T20:01:53.922Z" }, - { url = "https://files.pythonhosted.org/packages/9f/32/18fcd5919c293a398db67443acd33fde142f283853076049824fc58e6f75/websockets-15.0.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:823c248b690b2fd9303ba00c4f66cd5e2d8c3ba4aa968b2779be9532a4dad431", size = 175423, upload-time = "2025-03-05T20:01:56.276Z" }, - { url = "https://files.pythonhosted.org/packages/76/70/ba1ad96b07869275ef42e2ce21f07a5b0148936688c2baf7e4a1f60d5058/websockets-15.0.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678999709e68425ae2593acf2e3ebcbcf2e69885a5ee78f9eb80e6e371f1bf57", size = 173082, upload-time = "2025-03-05T20:01:57.563Z" }, - { url = "https://files.pythonhosted.org/packages/86/f2/10b55821dd40eb696ce4704a87d57774696f9451108cff0d2824c97e0f97/websockets-15.0.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:d50fd1ee42388dcfb2b3676132c78116490976f1300da28eb629272d5d93e905", size = 173330, upload-time = "2025-03-05T20:01:59.063Z" }, - { url = "https://files.pythonhosted.org/packages/a5/90/1c37ae8b8a113d3daf1065222b6af61cc44102da95388ac0018fcb7d93d9/websockets-15.0.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d99e5546bf73dbad5bf3547174cd6cb8ba7273062a23808ffea025ecb1cf8562", size = 182878, upload-time = "2025-03-05T20:02:00.305Z" }, - { url = "https://files.pythonhosted.org/packages/8e/8d/96e8e288b2a41dffafb78e8904ea7367ee4f891dafc2ab8d87e2124cb3d3/websockets-15.0.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:66dd88c918e3287efc22409d426c8f729688d89a0c587c88971a0faa2c2f3792", size = 181883, upload-time = "2025-03-05T20:02:03.148Z" }, - { url = "https://files.pythonhosted.org/packages/93/1f/5d6dbf551766308f6f50f8baf8e9860be6182911e8106da7a7f73785f4c4/websockets-15.0.1-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8dd8327c795b3e3f219760fa603dcae1dcc148172290a8ab15158cf85a953413", size = 182252, upload-time = "2025-03-05T20:02:05.29Z" }, - { url = "https://files.pythonhosted.org/packages/d4/78/2d4fed9123e6620cbf1706c0de8a1632e1a28e7774d94346d7de1bba2ca3/websockets-15.0.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8fdc51055e6ff4adeb88d58a11042ec9a5eae317a0a53d12c062c8a8865909e8", size = 182521, upload-time = "2025-03-05T20:02:07.458Z" }, - { url = "https://files.pythonhosted.org/packages/e7/3b/66d4c1b444dd1a9823c4a81f50231b921bab54eee2f69e70319b4e21f1ca/websockets-15.0.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:693f0192126df6c2327cce3baa7c06f2a117575e32ab2308f7f8216c29d9e2e3", size = 181958, upload-time = "2025-03-05T20:02:09.842Z" }, - { url = "https://files.pythonhosted.org/packages/08/ff/e9eed2ee5fed6f76fdd6032ca5cd38c57ca9661430bb3d5fb2872dc8703c/websockets-15.0.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:54479983bd5fb469c38f2f5c7e3a24f9a4e70594cd68cd1fa6b9340dadaff7cf", size = 181918, upload-time = "2025-03-05T20:02:11.968Z" }, - { url = "https://files.pythonhosted.org/packages/d8/75/994634a49b7e12532be6a42103597b71098fd25900f7437d6055ed39930a/websockets-15.0.1-cp311-cp311-win32.whl", hash = "sha256:16b6c1b3e57799b9d38427dda63edcbe4926352c47cf88588c0be4ace18dac85", size = 176388, upload-time = "2025-03-05T20:02:13.32Z" }, - { url = "https://files.pythonhosted.org/packages/98/93/e36c73f78400a65f5e236cd376713c34182e6663f6889cd45a4a04d8f203/websockets-15.0.1-cp311-cp311-win_amd64.whl", hash = "sha256:27ccee0071a0e75d22cb35849b1db43f2ecd3e161041ac1ee9d2352ddf72f065", size = 176828, upload-time = "2025-03-05T20:02:14.585Z" }, - { url = "https://files.pythonhosted.org/packages/51/6b/4545a0d843594f5d0771e86463606a3988b5a09ca5123136f8a76580dd63/websockets-15.0.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:3e90baa811a5d73f3ca0bcbf32064d663ed81318ab225ee4f427ad4e26e5aff3", size = 175437, upload-time = "2025-03-05T20:02:16.706Z" }, - { url = "https://files.pythonhosted.org/packages/f4/71/809a0f5f6a06522af902e0f2ea2757f71ead94610010cf570ab5c98e99ed/websockets-15.0.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:592f1a9fe869c778694f0aa806ba0374e97648ab57936f092fd9d87f8bc03665", size = 173096, upload-time = "2025-03-05T20:02:18.832Z" }, - { url = "https://files.pythonhosted.org/packages/3d/69/1a681dd6f02180916f116894181eab8b2e25b31e484c5d0eae637ec01f7c/websockets-15.0.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:0701bc3cfcb9164d04a14b149fd74be7347a530ad3bbf15ab2c678a2cd3dd9a2", size = 173332, upload-time = "2025-03-05T20:02:20.187Z" }, - { url = "https://files.pythonhosted.org/packages/a6/02/0073b3952f5bce97eafbb35757f8d0d54812b6174ed8dd952aa08429bcc3/websockets-15.0.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e8b56bdcdb4505c8078cb6c7157d9811a85790f2f2b3632c7d1462ab5783d215", size = 183152, upload-time = "2025-03-05T20:02:22.286Z" }, - { url = "https://files.pythonhosted.org/packages/74/45/c205c8480eafd114b428284840da0b1be9ffd0e4f87338dc95dc6ff961a1/websockets-15.0.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0af68c55afbd5f07986df82831c7bff04846928ea8d1fd7f30052638788bc9b5", size = 182096, upload-time = "2025-03-05T20:02:24.368Z" }, - { url = "https://files.pythonhosted.org/packages/14/8f/aa61f528fba38578ec553c145857a181384c72b98156f858ca5c8e82d9d3/websockets-15.0.1-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:64dee438fed052b52e4f98f76c5790513235efaa1ef7f3f2192c392cd7c91b65", size = 182523, upload-time = "2025-03-05T20:02:25.669Z" }, - { url = "https://files.pythonhosted.org/packages/ec/6d/0267396610add5bc0d0d3e77f546d4cd287200804fe02323797de77dbce9/websockets-15.0.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d5f6b181bb38171a8ad1d6aa58a67a6aa9d4b38d0f8c5f496b9e42561dfc62fe", size = 182790, upload-time = "2025-03-05T20:02:26.99Z" }, - { url = "https://files.pythonhosted.org/packages/02/05/c68c5adbf679cf610ae2f74a9b871ae84564462955d991178f95a1ddb7dd/websockets-15.0.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:5d54b09eba2bada6011aea5375542a157637b91029687eb4fdb2dab11059c1b4", size = 182165, upload-time = "2025-03-05T20:02:30.291Z" }, - { url = "https://files.pythonhosted.org/packages/29/93/bb672df7b2f5faac89761cb5fa34f5cec45a4026c383a4b5761c6cea5c16/websockets-15.0.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:3be571a8b5afed347da347bfcf27ba12b069d9d7f42cb8c7028b5e98bbb12597", size = 182160, upload-time = "2025-03-05T20:02:31.634Z" }, - { url = "https://files.pythonhosted.org/packages/ff/83/de1f7709376dc3ca9b7eeb4b9a07b4526b14876b6d372a4dc62312bebee0/websockets-15.0.1-cp312-cp312-win32.whl", hash = "sha256:c338ffa0520bdb12fbc527265235639fb76e7bc7faafbb93f6ba80d9c06578a9", size = 176395, upload-time = "2025-03-05T20:02:33.017Z" }, - { url = "https://files.pythonhosted.org/packages/7d/71/abf2ebc3bbfa40f391ce1428c7168fb20582d0ff57019b69ea20fa698043/websockets-15.0.1-cp312-cp312-win_amd64.whl", hash = "sha256:fcd5cf9e305d7b8338754470cf69cf81f420459dbae8a3b40cee57417f4614a7", size = 176841, upload-time = "2025-03-05T20:02:34.498Z" }, - { url = "https://files.pythonhosted.org/packages/cb/9f/51f0cf64471a9d2b4d0fc6c534f323b664e7095640c34562f5182e5a7195/websockets-15.0.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:ee443ef070bb3b6ed74514f5efaa37a252af57c90eb33b956d35c8e9c10a1931", size = 175440, upload-time = "2025-03-05T20:02:36.695Z" }, - { url = "https://files.pythonhosted.org/packages/8a/05/aa116ec9943c718905997412c5989f7ed671bc0188ee2ba89520e8765d7b/websockets-15.0.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:5a939de6b7b4e18ca683218320fc67ea886038265fd1ed30173f5ce3f8e85675", size = 173098, upload-time = "2025-03-05T20:02:37.985Z" }, - { url = "https://files.pythonhosted.org/packages/ff/0b/33cef55ff24f2d92924923c99926dcce78e7bd922d649467f0eda8368923/websockets-15.0.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:746ee8dba912cd6fc889a8147168991d50ed70447bf18bcda7039f7d2e3d9151", size = 173329, upload-time = "2025-03-05T20:02:39.298Z" }, - { url = "https://files.pythonhosted.org/packages/31/1d/063b25dcc01faa8fada1469bdf769de3768b7044eac9d41f734fd7b6ad6d/websockets-15.0.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:595b6c3969023ecf9041b2936ac3827e4623bfa3ccf007575f04c5a6aa318c22", size = 183111, upload-time = "2025-03-05T20:02:40.595Z" }, - { url = "https://files.pythonhosted.org/packages/93/53/9a87ee494a51bf63e4ec9241c1ccc4f7c2f45fff85d5bde2ff74fcb68b9e/websockets-15.0.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3c714d2fc58b5ca3e285461a4cc0c9a66bd0e24c5da9911e30158286c9b5be7f", size = 182054, upload-time = "2025-03-05T20:02:41.926Z" }, - { url = "https://files.pythonhosted.org/packages/ff/b2/83a6ddf56cdcbad4e3d841fcc55d6ba7d19aeb89c50f24dd7e859ec0805f/websockets-15.0.1-cp313-cp313-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0f3c1e2ab208db911594ae5b4f79addeb3501604a165019dd221c0bdcabe4db8", size = 182496, upload-time = "2025-03-05T20:02:43.304Z" }, - { url = "https://files.pythonhosted.org/packages/98/41/e7038944ed0abf34c45aa4635ba28136f06052e08fc2168520bb8b25149f/websockets-15.0.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:229cf1d3ca6c1804400b0a9790dc66528e08a6a1feec0d5040e8b9eb14422375", size = 182829, upload-time = "2025-03-05T20:02:48.812Z" }, - { url = "https://files.pythonhosted.org/packages/e0/17/de15b6158680c7623c6ef0db361da965ab25d813ae54fcfeae2e5b9ef910/websockets-15.0.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:756c56e867a90fb00177d530dca4b097dd753cde348448a1012ed6c5131f8b7d", size = 182217, upload-time = "2025-03-05T20:02:50.14Z" }, - { url = "https://files.pythonhosted.org/packages/33/2b/1f168cb6041853eef0362fb9554c3824367c5560cbdaad89ac40f8c2edfc/websockets-15.0.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:558d023b3df0bffe50a04e710bc87742de35060580a293c2a984299ed83bc4e4", size = 182195, upload-time = "2025-03-05T20:02:51.561Z" }, - { url = "https://files.pythonhosted.org/packages/86/eb/20b6cdf273913d0ad05a6a14aed4b9a85591c18a987a3d47f20fa13dcc47/websockets-15.0.1-cp313-cp313-win32.whl", hash = "sha256:ba9e56e8ceeeedb2e080147ba85ffcd5cd0711b89576b83784d8605a7df455fa", size = 176393, upload-time = "2025-03-05T20:02:53.814Z" }, - { url = "https://files.pythonhosted.org/packages/1b/6c/c65773d6cab416a64d191d6ee8a8b1c68a09970ea6909d16965d26bfed1e/websockets-15.0.1-cp313-cp313-win_amd64.whl", hash = "sha256:e09473f095a819042ecb2ab9465aee615bd9c2028e4ef7d933600a8401c79561", size = 176837, upload-time = "2025-03-05T20:02:55.237Z" }, - { url = "https://files.pythonhosted.org/packages/02/9e/d40f779fa16f74d3468357197af8d6ad07e7c5a27ea1ca74ceb38986f77a/websockets-15.0.1-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:0c9e74d766f2818bb95f84c25be4dea09841ac0f734d1966f415e4edfc4ef1c3", size = 173109, upload-time = "2025-03-05T20:03:17.769Z" }, - { url = "https://files.pythonhosted.org/packages/bc/cd/5b887b8585a593073fd92f7c23ecd3985cd2c3175025a91b0d69b0551372/websockets-15.0.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:1009ee0c7739c08a0cd59de430d6de452a55e42d6b522de7aa15e6f67db0b8e1", size = 173343, upload-time = "2025-03-05T20:03:19.094Z" }, - { url = "https://files.pythonhosted.org/packages/fe/ae/d34f7556890341e900a95acf4886833646306269f899d58ad62f588bf410/websockets-15.0.1-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:76d1f20b1c7a2fa82367e04982e708723ba0e7b8d43aa643d3dcd404d74f1475", size = 174599, upload-time = "2025-03-05T20:03:21.1Z" }, - { url = "https://files.pythonhosted.org/packages/71/e6/5fd43993a87db364ec60fc1d608273a1a465c0caba69176dd160e197ce42/websockets-15.0.1-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f29d80eb9a9263b8d109135351caf568cc3f80b9928bccde535c235de55c22d9", size = 174207, upload-time = "2025-03-05T20:03:23.221Z" }, - { url = "https://files.pythonhosted.org/packages/2b/fb/c492d6daa5ec067c2988ac80c61359ace5c4c674c532985ac5a123436cec/websockets-15.0.1-pp310-pypy310_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b359ed09954d7c18bbc1680f380c7301f92c60bf924171629c5db97febb12f04", size = 174155, upload-time = "2025-03-05T20:03:25.321Z" }, - { url = "https://files.pythonhosted.org/packages/68/a1/dcb68430b1d00b698ae7a7e0194433bce4f07ded185f0ee5fb21e2a2e91e/websockets-15.0.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:cad21560da69f4ce7658ca2cb83138fb4cf695a2ba3e475e0559e05991aa8122", size = 176884, upload-time = "2025-03-05T20:03:27.934Z" }, - { url = "https://files.pythonhosted.org/packages/fa/a8/5b41e0da817d64113292ab1f8247140aac61cbf6cfd085d6a0fa77f4984f/websockets-15.0.1-py3-none-any.whl", hash = "sha256:f7a866fbc1e97b5c617ee4116daaa09b722101d4a3c170c787450ba409f9736f", size = 169743, upload-time = "2025-03-05T20:03:39.41Z" }, -] - -[[package]] -name = "wrapt" -version = "2.0.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/49/19/5e5bcd855d808892fe02d49219f97a50f64cd6d8313d75df3494ee97b1a3/wrapt-2.0.0.tar.gz", hash = "sha256:35a542cc7a962331d0279735c30995b024e852cf40481e384fd63caaa391cbb9", size = 81722, upload-time = "2025-10-19T23:47:54.07Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ee/db/ac9546e89b645e525686727f8749847485e3b45ffc4507b61c4669358638/wrapt-2.0.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:a7cebcee61f21b1e46aa32db8d9d93826d0fbf1ad85defc2ccfb93b4adef1435", size = 77431, upload-time = "2025-10-19T23:45:25.177Z" }, - { url = "https://files.pythonhosted.org/packages/74/bc/3b57c8012bbd0d02eec5ae838681c1a819df6c5e765ebc897f52623b5eb1/wrapt-2.0.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:827e6e3a3a560f6ec1f5ee92d4319c21a0549384f896ec692f3201eda31ebd11", size = 60644, upload-time = "2025-10-19T23:45:27.511Z" }, - { url = "https://files.pythonhosted.org/packages/b8/6e/b5e7d47713e3d46c30ec6ae83fafd369bc34de8148668c6e3168d9301863/wrapt-2.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:1a91075a5383a7cbfe46aed1845ef7c3f027e8e20e7d9a8a75e36ebc9b0dd15e", size = 61526, upload-time = "2025-10-19T23:45:28.789Z" }, - { url = "https://files.pythonhosted.org/packages/28/8d/d5df2af58ae479785473607a3b25726c295640cdcaee830847cee339eff9/wrapt-2.0.0-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:b6a18c813196e18146b8d041e20875bdb0cb09b94ac1d1e1146e0fa87b2deb0d", size = 113638, upload-time = "2025-10-19T23:45:31.977Z" }, - { url = "https://files.pythonhosted.org/packages/f9/b7/9501c45ab93b4d6ba396ef02fcfb55867866bc8579fff045bb54cae58423/wrapt-2.0.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:ec5028d26011a53c76bd91bb6198b30b438c6e0f7adb45f2ad84fe2655b6a104", size = 115651, upload-time = "2025-10-19T23:45:33.257Z" }, - { url = "https://files.pythonhosted.org/packages/5e/3a/bfebe2ba51cf98ae80c5dbb6fa5892ae75d1acf1a4c404eda88e28f5ab06/wrapt-2.0.0-cp310-cp310-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:bed9b04900204721a24bcefc652ca267b01c1e8ad8bc8c0cff81558a45a3aadc", size = 112060, upload-time = "2025-10-19T23:45:30.298Z" }, - { url = "https://files.pythonhosted.org/packages/00/e7/cd50a32bed022d98f61a90e57faf782aa063f7930f57eb67eb105d3189be/wrapt-2.0.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:03442f2b45fa3f2b98a94a1917f52fb34670de8f96c0a009c02dbd512d855a3d", size = 114829, upload-time = "2025-10-19T23:45:34.23Z" }, - { url = "https://files.pythonhosted.org/packages/9d/2c/c709578271df0c70a27ab8f797c44c258650f24a32b452f03d7afedc070d/wrapt-2.0.0-cp310-cp310-musllinux_1_2_riscv64.whl", hash = "sha256:17d0b5c42495ba142a1cee52b76414f9210591c84aae94dffda70240753bfb3c", size = 111249, upload-time = "2025-10-19T23:45:35.554Z" }, - { url = "https://files.pythonhosted.org/packages/60/ef/cb58f6eea41f129600bda68d1ae4c80b14d4e0663eec1d5220cbffe50be5/wrapt-2.0.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:ee44215e7d13e112a8fc74e12ed1a1f41cab2bc07b11cc703f2398cd114b261c", size = 113312, upload-time = "2025-10-19T23:45:36.66Z" }, - { url = "https://files.pythonhosted.org/packages/59/55/97e6c4e1c175fb27f8dec717a3e36493ff0c4e50173a95f439496556910f/wrapt-2.0.0-cp310-cp310-win32.whl", hash = "sha256:fe6eafac3bc3c957ab6597a0c0654a0a308868458d00d218743e5b5fae51951c", size = 57961, upload-time = "2025-10-19T23:45:40.958Z" }, - { url = "https://files.pythonhosted.org/packages/3b/0a/898b1d81ae1f3dd9a79fd2e0330a7c8dd793982f815a318548777cb21ee5/wrapt-2.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:9e070c3491397fba0445b8977900271eca9656570cca7c900d9b9352186703a0", size = 60311, upload-time = "2025-10-19T23:45:38.033Z" }, - { url = "https://files.pythonhosted.org/packages/44/f1/e7e92f9535f5624ee22879f09456df9d1f1ae9bb338eef711077b48e456a/wrapt-2.0.0-cp310-cp310-win_arm64.whl", hash = "sha256:806e2e73186eb5e3546f39fb5d0405040e0088db0fc8b2f667fd1863de2b3c99", size = 58822, upload-time = "2025-10-19T23:45:39.785Z" }, - { url = "https://files.pythonhosted.org/packages/12/8f/8e4c8b6da60b4205191d588cbac448fb9ff4f5ed89f4e555dc4813ab30cf/wrapt-2.0.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:b7e221abb6c5387819db9323dac3c875b459695057449634f1111955d753c621", size = 77433, upload-time = "2025-10-19T23:45:42.543Z" }, - { url = "https://files.pythonhosted.org/packages/22/9a/01a29ccb029aa8e78241f8b53cb89ae8826c240129abbbb6ebba3416eff9/wrapt-2.0.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:1147a84c8fc852426580af8b6e33138461ddbc65aa459a25ea539374d32069fa", size = 60641, upload-time = "2025-10-19T23:45:43.866Z" }, - { url = "https://files.pythonhosted.org/packages/3d/ec/e058997971428b7665b5c3665a55b18bb251ea7e08d002925e3ca017c020/wrapt-2.0.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:5d6691d4a711504a0bc10de789842ad6ac627bed22937b10f37a1211a8ab7bb3", size = 61526, upload-time = "2025-10-19T23:45:44.839Z" }, - { url = "https://files.pythonhosted.org/packages/70/c3/c82263503f554715aa1847e85dc75a69631a54e9d7ab0f1a55e34a22d44a/wrapt-2.0.0-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:f460e1eb8e75a17c3918c8e35ba57625721eef2439ef0bcf05304ac278a65e1d", size = 114069, upload-time = "2025-10-19T23:45:47.223Z" }, - { url = "https://files.pythonhosted.org/packages/dc/97/d95e88a3a1bc2890a1aa47880c2762cf0eb6d231b5a64048e351cec6f071/wrapt-2.0.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:12c37784b77bf043bf65cc96c7195a5db474b8e54173208af076bdbb61df7b3e", size = 116109, upload-time = "2025-10-19T23:45:48.252Z" }, - { url = "https://files.pythonhosted.org/packages/dc/36/cba0bf954f2303897b80fa5342499b43f8c5201110dddf0d578d6841b149/wrapt-2.0.0-cp311-cp311-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:75e5c049eb583835f7a0e0e311d9dde9bfbaac723a6dd89d052540f9b2809977", size = 112500, upload-time = "2025-10-19T23:45:45.838Z" }, - { url = "https://files.pythonhosted.org/packages/d7/2b/8cb88e63bec989f641d208acb3fd198bfdbbb4ef7dfb71f0cac3c90b07a9/wrapt-2.0.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:e50bcbd5b65dac21b82319fcf18486e6ac439947e9305034b00704eb7405f553", size = 115356, upload-time = "2025-10-19T23:45:49.249Z" }, - { url = "https://files.pythonhosted.org/packages/bb/60/a6d5fb94648cd430648705bef9f4241bd22ead123ead552b6d2873ad5240/wrapt-2.0.0-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:06b78cb6b9320f57737a52fede882640d93cface98332d1a3df0c5696ec9ae9f", size = 111754, upload-time = "2025-10-19T23:45:51.21Z" }, - { url = "https://files.pythonhosted.org/packages/d0/44/1963854edf0592ae806307899dc7bf891e76cec19e598f55845c94603a65/wrapt-2.0.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:8c8349ebfc3cd98bc9105e0112dd8c8ac1f3c7cb5601f9d02248cae83a63f748", size = 113789, upload-time = "2025-10-19T23:45:52.473Z" }, - { url = "https://files.pythonhosted.org/packages/62/ec/4b1d76cb6d96ac511aaaa92efc57f528e57f06082a595b8b2663fcdb0f20/wrapt-2.0.0-cp311-cp311-win32.whl", hash = "sha256:028f19ec29e204fe725139d4a8b09f77ecfb64f8f02b7ab5ee822c85e330b68b", size = 57954, upload-time = "2025-10-19T23:45:57.03Z" }, - { url = "https://files.pythonhosted.org/packages/d4/cf/df8ff9bd64d4a75f9a9f6c1c93480a51904d0c9bd71c11994301c47d8a33/wrapt-2.0.0-cp311-cp311-win_amd64.whl", hash = "sha256:c6961f05e58d919153ba311b397b7b904b907132b7b8344dde47865d4bb5ec89", size = 60308, upload-time = "2025-10-19T23:45:54.314Z" }, - { url = "https://files.pythonhosted.org/packages/69/d8/61e245fe387d58d84b3f913d5da9d909c4f239b887db692a05105aaf2a1b/wrapt-2.0.0-cp311-cp311-win_arm64.whl", hash = "sha256:be7e316c2accd5a31dbcc230de19e2a846a325f8967fdea72704d00e38e6af06", size = 58822, upload-time = "2025-10-19T23:45:55.772Z" }, - { url = "https://files.pythonhosted.org/packages/3c/28/7f266b5bf50c3ad0c99c524d99faa0f7d6eecb045d950e7d2c9e1f0e1338/wrapt-2.0.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:73c6f734aecb1a030d9a265c13a425897e1ea821b73249bb14471445467ca71c", size = 78078, upload-time = "2025-10-19T23:45:58.855Z" }, - { url = "https://files.pythonhosted.org/packages/06/0c/bbdcad7eb535fae9d6b0fcfa3995c364797cd8e2b423bba5559ab2d88dcf/wrapt-2.0.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:b4a7f8023b8ce8a36370154733c747f8d65c8697cb977d8b6efeb89291fff23e", size = 61158, upload-time = "2025-10-19T23:46:00.096Z" }, - { url = "https://files.pythonhosted.org/packages/d3/8a/bba3e7a4ebf4d1624103ee59d97b78a1fbb08fb5753ff5d1b69f5ef5e863/wrapt-2.0.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:a1cb62f686c50e9dab5983c68f6c8e9cbf14a6007935e683662898a7d892fa69", size = 61646, upload-time = "2025-10-19T23:46:01.279Z" }, - { url = "https://files.pythonhosted.org/packages/ff/0c/0f565294897a72493dbafe7b46229b5f09f3776795a894d6b737e98387de/wrapt-2.0.0-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:43dc0550ae15e33e6bb45a82a5e1b5495be2587fbaa996244b509921810ee49f", size = 121442, upload-time = "2025-10-19T23:46:04.287Z" }, - { url = "https://files.pythonhosted.org/packages/da/80/7f03501a8a078ad79b19b1a888f9192a9494e62ddf8985267902766a4f30/wrapt-2.0.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:39c5b45b056d630545e40674d1f5e1b51864b3546f25ab6a4a331943de96262e", size = 123018, upload-time = "2025-10-19T23:46:06.052Z" }, - { url = "https://files.pythonhosted.org/packages/37/6b/ad0e1ff98359f13b4b0c2c52848e792841146fe79ac5f56899b9a028fc0d/wrapt-2.0.0-cp312-cp312-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:804e88f824b76240a1b670330637ccfd2d18b9efa3bb4f02eb20b2f64880b324", size = 117369, upload-time = "2025-10-19T23:46:02.53Z" }, - { url = "https://files.pythonhosted.org/packages/ac/6c/a90437bba8cb1ce2ed639af979515e09784678c2a7f4ffc79f2cf7de809e/wrapt-2.0.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:c2c476aa3fc2b9899c3f7b20963fac4f952e7edb74a31fc92f7745389a2e3618", size = 121453, upload-time = "2025-10-19T23:46:07.747Z" }, - { url = "https://files.pythonhosted.org/packages/2c/a9/b3982f9bd15bd45857a23c48b7c36e47d05db4a4dcc5061c31f169238845/wrapt-2.0.0-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:8d851e526891216f89fcb7a1820dad9bd503ba3468fb9635ee28e93c781aa98e", size = 116250, upload-time = "2025-10-19T23:46:09.385Z" }, - { url = "https://files.pythonhosted.org/packages/73/e2/b7a8b1afac9f791d8f5eac0d9726559f1d7ec4a2b5a6b4e67ac145b007a5/wrapt-2.0.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b95733c2360c4a8656ee93c7af78e84c0bd617da04a236d7a456c8faa34e7a2d", size = 120575, upload-time = "2025-10-19T23:46:11.882Z" }, - { url = "https://files.pythonhosted.org/packages/a2/0f/37920eeea96094f450ae35505d39f1135df951a2cdee0d4e01d4f843396a/wrapt-2.0.0-cp312-cp312-win32.whl", hash = "sha256:ea56817176834edf143df1109ae8fdaa087be82fdad3492648de0baa8ae82bf2", size = 58175, upload-time = "2025-10-19T23:46:15.678Z" }, - { url = "https://files.pythonhosted.org/packages/f0/db/b395f3b0c7f2c60d9219afacc54ceb699801ccf2d3d969ba556dc6d3af20/wrapt-2.0.0-cp312-cp312-win_amd64.whl", hash = "sha256:3c7d3bee7be7a2665286103f4d1f15405c8074e6e1f89dac5774f9357c9a3809", size = 60415, upload-time = "2025-10-19T23:46:12.913Z" }, - { url = "https://files.pythonhosted.org/packages/86/22/33d660214548af47fc59d9eec8c0e0693bcedc5b3a0b52e8cbdd61f3b646/wrapt-2.0.0-cp312-cp312-win_arm64.whl", hash = "sha256:680f707e1d26acbc60926659799b15659f077df5897a6791c7c598a5d4a211c4", size = 58911, upload-time = "2025-10-19T23:46:13.889Z" }, - { url = "https://files.pythonhosted.org/packages/18/0a/dd88abfe756b1aa79f0777e5ee4ce9e4b5dc4999bd805e9b04b52efc7b18/wrapt-2.0.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:e2ea096db28d5eb64d381af0e93464621ace38a7003a364b6b5ffb7dd713aabe", size = 78083, upload-time = "2025-10-19T23:46:16.937Z" }, - { url = "https://files.pythonhosted.org/packages/7f/b9/8afebc1655a863bb2178b23c2d699b8743f3a7dab466904adc6155f3c858/wrapt-2.0.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:c92b5a82d28491e3f14f037e1aae99a27a5e6e0bb161e65f52c0445a3fa7c940", size = 61156, upload-time = "2025-10-19T23:46:17.927Z" }, - { url = "https://files.pythonhosted.org/packages/bb/8b/f710a6528ccc52e21943f42c8cf64814cde90f9adbd3bcd58c7c274b4f75/wrapt-2.0.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:81d234718aabe632d179fac52c7f69f0f99fbaac4d4bcd670e62462bbcbfcad7", size = 61641, upload-time = "2025-10-19T23:46:19.229Z" }, - { url = "https://files.pythonhosted.org/packages/e4/5f/e4eabd0cc6684c5b208c2abc5c3459449c4d15be1694a9bbcf51e0e135fd/wrapt-2.0.0-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:db2eea83c43f84e4e41dbbb4c1de371a53166e55f900a6b130c3ef51c6345c1a", size = 121454, upload-time = "2025-10-19T23:46:21.808Z" }, - { url = "https://files.pythonhosted.org/packages/6f/c4/ec31ee17cc7866960d323609ba7402be786d211a6d713a59f776c4270bb3/wrapt-2.0.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:65f50e356c425c061e1e17fe687ff30e294fed9bf3441dc1f13ef73859c2a817", size = 123063, upload-time = "2025-10-19T23:46:23.545Z" }, - { url = "https://files.pythonhosted.org/packages/b0/2b/a4b10c3c0022e40aeae9bec009bafb049f440493f0575ebb27ecf61c32f8/wrapt-2.0.0-cp313-cp313-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:887f2a667e3cbfb19e204032d42ad7dedaa43972e4861dc7a3d51ae951d9b578", size = 117401, upload-time = "2025-10-19T23:46:20.433Z" }, - { url = "https://files.pythonhosted.org/packages/2a/4a/ade23a76967e1f148e461076a4d0e24a7950a5f18b394c9107fe60224ae2/wrapt-2.0.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:9054829da4be461e3ad3192e4b6bbf1fc18af64c9975ce613aec191924e004dc", size = 121485, upload-time = "2025-10-19T23:46:24.85Z" }, - { url = "https://files.pythonhosted.org/packages/cb/ba/33b5f3e2edede4e1cfd259f0d9c203cf370f259bb9b215dd58fc6cbb94e9/wrapt-2.0.0-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:b952ffd77133a5a2798ee3feb18e51b0a299d2f440961e5bb7737dbb02e57289", size = 116276, upload-time = "2025-10-19T23:46:27.006Z" }, - { url = "https://files.pythonhosted.org/packages/eb/bf/b7f95bb4529a35ca11eb95d48f9d1a563b495471f7cf404c644566fb4293/wrapt-2.0.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e25fde03c480061b8234d8ee4863eb5f40a9be4fb258ce105b364de38fc6bcf9", size = 120578, upload-time = "2025-10-19T23:46:28.679Z" }, - { url = "https://files.pythonhosted.org/packages/f8/71/984849df6f052592474a44aafd6b847e1cffad39b0debc5390a04aa46331/wrapt-2.0.0-cp313-cp313-win32.whl", hash = "sha256:49e982b7860d325094978292a49e0418833fc7fc42c0dc7cd0b7524d7d06ee74", size = 58178, upload-time = "2025-10-19T23:46:32.372Z" }, - { url = "https://files.pythonhosted.org/packages/f9/3b/4e1fc0f2e1355fbc55ab248311bf4c958dbbd96bd9183b9e96882cc16213/wrapt-2.0.0-cp313-cp313-win_amd64.whl", hash = "sha256:6e5c86389d9964050ce50babe247d172a5e3911d59a64023b90db2b4fa00ae7c", size = 60423, upload-time = "2025-10-19T23:46:30.041Z" }, - { url = "https://files.pythonhosted.org/packages/20/0a/9384e0551f56fe361f41bb8f209a13bb9ef689c3a18264225b249849b12c/wrapt-2.0.0-cp313-cp313-win_arm64.whl", hash = "sha256:b96fdaa4611e05c7231937930567d3c16782be9dbcf03eb9f60d83e57dd2f129", size = 58918, upload-time = "2025-10-19T23:46:31.056Z" }, - { url = "https://files.pythonhosted.org/packages/68/70/37b90d3ee5bf0d0dc4859306383da08b685c9a51abff6fd6b0a7c052e117/wrapt-2.0.0-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:f2c7b7fead096dbf1dcc455b7f59facb05de3f5bfb04f60a69f98cdfe6049e5f", size = 81980, upload-time = "2025-10-19T23:46:33.368Z" }, - { url = "https://files.pythonhosted.org/packages/95/23/0ce69cc90806b90b3ee4cfd9ad8d2ee9becc3a1aab7df3c3bfc7d0904cb6/wrapt-2.0.0-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:04c7c8393f25b11c0faa5d907dd9eb462e87e4e7ba55e308a046d7ed37f4bbe2", size = 62900, upload-time = "2025-10-19T23:46:34.415Z" }, - { url = "https://files.pythonhosted.org/packages/54/76/03ec08170c02f38f3be3646977920976b968e0b704a0693a98f95d02f4d2/wrapt-2.0.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:a93e0f8b376c0735b2f4daf58018b4823614d2b896cb72b6641c4d3dbdca1d75", size = 63636, upload-time = "2025-10-19T23:46:35.643Z" }, - { url = "https://files.pythonhosted.org/packages/75/c1/04ce0511e504cdcd84cdb6980bc7d4efa38ac358e8103d6dd0cd278bfc6d/wrapt-2.0.0-cp313-cp313t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:b42d13603da4416c43c430dbc6313c8d7ff745c40942f146ed4f6dd02c7d2547", size = 152650, upload-time = "2025-10-19T23:46:38.717Z" }, - { url = "https://files.pythonhosted.org/packages/17/06/cd2e32b5f744701189c954f9ab5eee449c86695b13f414bb8ea7a83f6d48/wrapt-2.0.0-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c8bbd2472abf8c33480ad2314b1f8fac45d592aba6cc093e8839a7b2045660e6", size = 158811, upload-time = "2025-10-19T23:46:40.875Z" }, - { url = "https://files.pythonhosted.org/packages/7d/a2/a6d920695cca62563c1b969064e5cd2051344a6e330c184b6f80383d87e4/wrapt-2.0.0-cp313-cp313t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:e64a3a1fd9a308ab9b815a2ad7a65b679730629dbf85f8fc3f7f970d634ee5df", size = 146033, upload-time = "2025-10-19T23:46:37.351Z" }, - { url = "https://files.pythonhosted.org/packages/c6/90/7fd2abe4ec646bc43cb6b0d05086be6fcf15e64f06f51fc4198804396d68/wrapt-2.0.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:d61214525eaf88e0d0edf3d1ad5b5889863c6f88e588c6cdc6aa4ee5d1f10a4a", size = 155673, upload-time = "2025-10-19T23:46:42.582Z" }, - { url = "https://files.pythonhosted.org/packages/5f/8d/6cce7f8c41633e677ac8aa34e84b53a22a645ec2a680deb991785ca2798d/wrapt-2.0.0-cp313-cp313t-musllinux_1_2_riscv64.whl", hash = "sha256:04f7a5f92c5f7324a1735043cc467b1295a1c5b4e0c1395472b7c44706e3dc61", size = 144364, upload-time = "2025-10-19T23:46:44.381Z" }, - { url = "https://files.pythonhosted.org/packages/72/42/9570349e03afa9d83daf7f33ffb17e8cdc62d7e84c0d09005d0f51912efa/wrapt-2.0.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:2356f76cb99b3de5b4e5b8210367fbbb81c7309fe39b622f5d199dd88eb7f765", size = 150275, upload-time = "2025-10-19T23:46:45.662Z" }, - { url = "https://files.pythonhosted.org/packages/f2/d8/448728e6fe030e5c4f1022c82cd3af1de1c672fa53d2d5b36b32a55ce7bf/wrapt-2.0.0-cp313-cp313t-win32.whl", hash = "sha256:0a921b657a224e40e4bc161b5d33934583b34f0c9c5bdda4e6ac66f9d2fcb849", size = 59867, upload-time = "2025-10-19T23:46:49.593Z" }, - { url = "https://files.pythonhosted.org/packages/8f/b1/ad812b1fe1cd85f6498dc3a3c9809a1e880d6108283b1735119bec217041/wrapt-2.0.0-cp313-cp313t-win_amd64.whl", hash = "sha256:c16f6d4eea98080f6659a8a7fc559d4a0a337ee66960659265cad2c8a40f7c0f", size = 63170, upload-time = "2025-10-19T23:46:46.87Z" }, - { url = "https://files.pythonhosted.org/packages/7f/29/c105b1e76650c82823c491952a7a8eafe09b78944f7a43f22d37ed860229/wrapt-2.0.0-cp313-cp313t-win_arm64.whl", hash = "sha256:52878edc13dc151c58a9966621d67163a80654bc6cff4b2e1c79fa62d0352b26", size = 60339, upload-time = "2025-10-19T23:46:47.862Z" }, - { url = "https://files.pythonhosted.org/packages/f8/38/0dd39f83163fd28326afba84e3e416656938df07e60a924ac4d992b30220/wrapt-2.0.0-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:79a53d86c2aff7b32cc77267e3a308365d1fcb881e74bc9cbe26f63ee90e37f0", size = 78242, upload-time = "2025-10-19T23:46:51.096Z" }, - { url = "https://files.pythonhosted.org/packages/08/ef/fa7a5c1d73f8690c712f9d2e4615700c6809942536dd3f441b9ba650a310/wrapt-2.0.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:d731a4f22ed6ffa4cb551b4d2b0c24ff940c27a88edaf8e3490a5ee3a05aef71", size = 61207, upload-time = "2025-10-19T23:46:52.558Z" }, - { url = "https://files.pythonhosted.org/packages/23/d9/67cb93da492eb0a1cb17b7ed18220d059e58f00467ce6728b674d3441b3d/wrapt-2.0.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:3e02ab8c0ac766a5a6e81cd3b6cc39200c69051826243182175555872522bd5a", size = 61748, upload-time = "2025-10-19T23:46:54.468Z" }, - { url = "https://files.pythonhosted.org/packages/e5/be/912bbd70cc614f491b526a1d7fe85695b283deed19287b9f32460178c54d/wrapt-2.0.0-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:895870602d65d7338edb3b6a717d856632ad9f14f7ff566214e4fb11f0816649", size = 120424, upload-time = "2025-10-19T23:46:57.575Z" }, - { url = "https://files.pythonhosted.org/packages/b2/e1/10df8937e7da2aa9bc3662a4b623e51a323c68f42cad7b13f0e61a700ce2/wrapt-2.0.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:0b9ad4fab76a0086dc364c4f17f39ad289600e73ef5c6e9ab529aff22cac1ac3", size = 122804, upload-time = "2025-10-19T23:46:59.308Z" }, - { url = "https://files.pythonhosted.org/packages/f3/60/576751b1919adab9f63168e3b5fd46c0d1565871b1cc4c2569503ccf4be6/wrapt-2.0.0-cp314-cp314-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:e7ca0562606d7bad2736b2c18f61295d61f50cd3f4bfc51753df13614dbcce1b", size = 117398, upload-time = "2025-10-19T23:46:55.814Z" }, - { url = "https://files.pythonhosted.org/packages/ec/55/243411f360cc27bae5f8e21c16f1a8d87674c5534f4558e8a97c1e0d1c6f/wrapt-2.0.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:fe089d9f5a4a3dea0108a8ae34bced114d0c4cca417bada1c5e8f42d98af9050", size = 121230, upload-time = "2025-10-19T23:47:01.347Z" }, - { url = "https://files.pythonhosted.org/packages/d6/23/2f21f692c3b3f0857cb82708ce0c341fbac55a489d4025ae4e3fd5d5de8c/wrapt-2.0.0-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:e761f2d2f8dbc80384af3d547b522a80e67db3e319c7b02e7fd97aded0a8a678", size = 116296, upload-time = "2025-10-19T23:47:02.659Z" }, - { url = "https://files.pythonhosted.org/packages/bd/ed/678957fad212cfb1b65b2359d62f5619f5087d1d1cf296c6a996be45171c/wrapt-2.0.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:17ba1bdc52d0c783481850996aa26cea5237720769197335abea2ae6b4c23bc0", size = 119602, upload-time = "2025-10-19T23:47:03.775Z" }, - { url = "https://files.pythonhosted.org/packages/dc/e3/aeb4c3b052d3eed95e61babc20dcb1a512651e098cca4b84a6896585c06a/wrapt-2.0.0-cp314-cp314-win32.whl", hash = "sha256:f73318741b141223a4674ba96992aa2291b1b3f7a5e85cb3c2c964f86171eb45", size = 58649, upload-time = "2025-10-19T23:47:07.382Z" }, - { url = "https://files.pythonhosted.org/packages/aa/2a/a71c51cb211798405b59172c7df5789a5b934b18317223cf22e0c6f852de/wrapt-2.0.0-cp314-cp314-win_amd64.whl", hash = "sha256:8e08d4edb13cafe7b3260f31d4de033f73d3205774540cf583bffaa4bec97db9", size = 60897, upload-time = "2025-10-19T23:47:04.862Z" }, - { url = "https://files.pythonhosted.org/packages/f8/a5/acc5628035d06f69e9144cca543ca54c33b42a5a23b6f1e8fa131026db89/wrapt-2.0.0-cp314-cp314-win_arm64.whl", hash = "sha256:af01695c2b7bbd8d67b869d8e3de2b123a7bfbee0185bdd138c2775f75373b83", size = 59306, upload-time = "2025-10-19T23:47:05.883Z" }, - { url = "https://files.pythonhosted.org/packages/a7/e6/1318ca07d7fcee57e4592a78dacd9d5493b8ddd971c553a62904fb2c0cf2/wrapt-2.0.0-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:057f02c13cce7b26c79624c06a3e1c2353e6dc9708525232232f6768118042ca", size = 81987, upload-time = "2025-10-19T23:47:08.7Z" }, - { url = "https://files.pythonhosted.org/packages/e7/bf/ffac358ddf61c3923d94a8b0e7620f2af1cd1b637a0fe4963a3919aa62b7/wrapt-2.0.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:79bdd84570267f3f43d609c892ae2d30b91ee4b8614c2cbfd311a2965f1c9bdb", size = 62902, upload-time = "2025-10-19T23:47:10.248Z" }, - { url = "https://files.pythonhosted.org/packages/b5/af/387c51f9e7b544fe95d852fc94f9f3866e3f7d7d39c2ee65041752f90bc2/wrapt-2.0.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:93c8b4f4d54fd401a817abbfc9bf482aa72fd447f8adf19ce81d035b3f5c762c", size = 63635, upload-time = "2025-10-19T23:47:11.746Z" }, - { url = "https://files.pythonhosted.org/packages/7c/99/d38d8c80b9cc352531d4d539a17e3674169a5cc25a7e6e5e3c27bc29893e/wrapt-2.0.0-cp314-cp314t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:5e09ffd31001dce71c2c2a4fc201bdba9a2f9f62b23700cf24af42266e784741", size = 152659, upload-time = "2025-10-19T23:47:15.344Z" }, - { url = "https://files.pythonhosted.org/packages/5a/2a/e154432f274e22ecf2465583386c5ceffa5e0bab3947c1c5b26cc8e7b275/wrapt-2.0.0-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d87c285ff04e26083c4b03546e7b74df7ba4f1f32f1dcb92e9ac13c2dbb4c379", size = 158818, upload-time = "2025-10-19T23:47:17.569Z" }, - { url = "https://files.pythonhosted.org/packages/c5/7a/3a40c453300e2898e99c27495b8109ff7cd526997d12cfb8ebd1843199a4/wrapt-2.0.0-cp314-cp314t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:e52e50ea0a72ea48d1291cf8b8aaedcc99072d9dc5baba6b820486dcf4c67da8", size = 146113, upload-time = "2025-10-19T23:47:13.026Z" }, - { url = "https://files.pythonhosted.org/packages/9e/e2/3116a9eade8bea2bf5eedba3fa420e3c7d193d4b047440330d8eaf1098de/wrapt-2.0.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:1fd4c95536975895f32571073446e614d5e2810b666b64955586dcddfd438fd3", size = 155689, upload-time = "2025-10-19T23:47:19.397Z" }, - { url = "https://files.pythonhosted.org/packages/43/1c/277d3fbe9d177830ab9e54fe9253f38455b75a22d639a4bd9fa092d55ae5/wrapt-2.0.0-cp314-cp314t-musllinux_1_2_riscv64.whl", hash = "sha256:d6ebfe9283209220ed9de80a3e9442aab8fc2be5a9bbf8491b99e02ca9349a89", size = 144403, upload-time = "2025-10-19T23:47:20.779Z" }, - { url = "https://files.pythonhosted.org/packages/d8/37/ab6ddaf182248aac5ed925725ef4c69a510594764665ecbd95bdd4481f16/wrapt-2.0.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:5d3ebd784804f146b7ea55359beb138e23cc18e5a5cc2cf26ad438723c00ce3a", size = 150307, upload-time = "2025-10-19T23:47:22.604Z" }, - { url = "https://files.pythonhosted.org/packages/f6/d7/df9e2d8040a3af618ff9496261cf90ca4f886fd226af0f4a69ac0c020c3b/wrapt-2.0.0-cp314-cp314t-win32.whl", hash = "sha256:9b15940ae9debc8b40b15dc57e1ce4433f7fb9d3f8761c7fab1ddd94cb999d99", size = 60557, upload-time = "2025-10-19T23:47:26.73Z" }, - { url = "https://files.pythonhosted.org/packages/b4/c2/502bd4557a3a9199ea73cc5932cf83354bd362682162f0b14164d2e90216/wrapt-2.0.0-cp314-cp314t-win_amd64.whl", hash = "sha256:7a0efbbc06d3e2077476a04f55859819d23206600b4c33f791359a8e6fa3c362", size = 63988, upload-time = "2025-10-19T23:47:23.826Z" }, - { url = "https://files.pythonhosted.org/packages/1f/f2/632b13942f45db7af709f346ff38b8992c8c21b004e61ab320b0dec525fe/wrapt-2.0.0-cp314-cp314t-win_arm64.whl", hash = "sha256:7fec8a9455c029c8cf4ff143a53b6e7c463268d42be6c17efa847ebd2f809965", size = 60584, upload-time = "2025-10-19T23:47:25.396Z" }, - { url = "https://files.pythonhosted.org/packages/00/5c/c34575f96a0a038579683c7f10fca943c15c7946037d1d254ab9db1536ec/wrapt-2.0.0-py3-none-any.whl", hash = "sha256:02482fb0df89857e35427dfb844319417e14fae05878f295ee43fa3bf3b15502", size = 43998, upload-time = "2025-10-19T23:47:52.858Z" }, -] - -[[package]] -name = "yarl" -version = "1.22.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "idna" }, - { name = "multidict" }, - { name = "propcache" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/57/63/0c6ebca57330cd313f6102b16dd57ffaf3ec4c83403dcb45dbd15c6f3ea1/yarl-1.22.0.tar.gz", hash = "sha256:bebf8557577d4401ba8bd9ff33906f1376c877aa78d1fe216ad01b4d6745af71", size = 187169, upload-time = "2025-10-06T14:12:55.963Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d1/43/a2204825342f37c337f5edb6637040fa14e365b2fcc2346960201d457579/yarl-1.22.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:c7bd6683587567e5a49ee6e336e0612bec8329be1b7d4c8af5687dcdeb67ee1e", size = 140517, upload-time = "2025-10-06T14:08:42.494Z" }, - { url = "https://files.pythonhosted.org/packages/44/6f/674f3e6f02266428c56f704cd2501c22f78e8b2eeb23f153117cc86fb28a/yarl-1.22.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:5cdac20da754f3a723cceea5b3448e1a2074866406adeb4ef35b469d089adb8f", size = 93495, upload-time = "2025-10-06T14:08:46.2Z" }, - { url = "https://files.pythonhosted.org/packages/b8/12/5b274d8a0f30c07b91b2f02cba69152600b47830fcfb465c108880fcee9c/yarl-1.22.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:07a524d84df0c10f41e3ee918846e1974aba4ec017f990dc735aad487a0bdfdf", size = 94400, upload-time = "2025-10-06T14:08:47.855Z" }, - { url = "https://files.pythonhosted.org/packages/e2/7f/df1b6949b1fa1aa9ff6de6e2631876ad4b73c4437822026e85d8acb56bb1/yarl-1.22.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e1b329cb8146d7b736677a2440e422eadd775d1806a81db2d4cded80a48efc1a", size = 347545, upload-time = "2025-10-06T14:08:49.683Z" }, - { url = "https://files.pythonhosted.org/packages/84/09/f92ed93bd6cd77872ab6c3462df45ca45cd058d8f1d0c9b4f54c1704429f/yarl-1.22.0-cp310-cp310-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:75976c6945d85dbb9ee6308cd7ff7b1fb9409380c82d6119bd778d8fcfe2931c", size = 319598, upload-time = "2025-10-06T14:08:51.215Z" }, - { url = "https://files.pythonhosted.org/packages/c3/97/ac3f3feae7d522cf7ccec3d340bb0b2b61c56cb9767923df62a135092c6b/yarl-1.22.0-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:80ddf7a5f8c86cb3eb4bc9028b07bbbf1f08a96c5c0bc1244be5e8fefcb94147", size = 363893, upload-time = "2025-10-06T14:08:53.144Z" }, - { url = "https://files.pythonhosted.org/packages/06/49/f3219097403b9c84a4d079b1d7bda62dd9b86d0d6e4428c02d46ab2c77fc/yarl-1.22.0-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d332fc2e3c94dad927f2112395772a4e4fedbcf8f80efc21ed7cdfae4d574fdb", size = 371240, upload-time = "2025-10-06T14:08:55.036Z" }, - { url = "https://files.pythonhosted.org/packages/35/9f/06b765d45c0e44e8ecf0fe15c9eacbbde342bb5b7561c46944f107bfb6c3/yarl-1.22.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0cf71bf877efeac18b38d3930594c0948c82b64547c1cf420ba48722fe5509f6", size = 346965, upload-time = "2025-10-06T14:08:56.722Z" }, - { url = "https://files.pythonhosted.org/packages/c5/69/599e7cea8d0fcb1694323b0db0dda317fa3162f7b90166faddecf532166f/yarl-1.22.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:663e1cadaddae26be034a6ab6072449a8426ddb03d500f43daf952b74553bba0", size = 342026, upload-time = "2025-10-06T14:08:58.563Z" }, - { url = "https://files.pythonhosted.org/packages/95/6f/9dfd12c8bc90fea9eab39832ee32ea48f8e53d1256252a77b710c065c89f/yarl-1.22.0-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:6dcbb0829c671f305be48a7227918cfcd11276c2d637a8033a99a02b67bf9eda", size = 335637, upload-time = "2025-10-06T14:09:00.506Z" }, - { url = "https://files.pythonhosted.org/packages/57/2e/34c5b4eb9b07e16e873db5b182c71e5f06f9b5af388cdaa97736d79dd9a6/yarl-1.22.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:f0d97c18dfd9a9af4490631905a3f131a8e4c9e80a39353919e2cfed8f00aedc", size = 359082, upload-time = "2025-10-06T14:09:01.936Z" }, - { url = "https://files.pythonhosted.org/packages/31/71/fa7e10fb772d273aa1f096ecb8ab8594117822f683bab7d2c5a89914c92a/yarl-1.22.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:437840083abe022c978470b942ff832c3940b2ad3734d424b7eaffcd07f76737", size = 357811, upload-time = "2025-10-06T14:09:03.445Z" }, - { url = "https://files.pythonhosted.org/packages/26/da/11374c04e8e1184a6a03cf9c8f5688d3e5cec83ed6f31ad3481b3207f709/yarl-1.22.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:a899cbd98dce6f5d8de1aad31cb712ec0a530abc0a86bd6edaa47c1090138467", size = 351223, upload-time = "2025-10-06T14:09:05.401Z" }, - { url = "https://files.pythonhosted.org/packages/82/8f/e2d01f161b0c034a30410e375e191a5d27608c1f8693bab1a08b089ca096/yarl-1.22.0-cp310-cp310-win32.whl", hash = "sha256:595697f68bd1f0c1c159fcb97b661fc9c3f5db46498043555d04805430e79bea", size = 82118, upload-time = "2025-10-06T14:09:11.148Z" }, - { url = "https://files.pythonhosted.org/packages/62/46/94c76196642dbeae634c7a61ba3da88cd77bed875bf6e4a8bed037505aa6/yarl-1.22.0-cp310-cp310-win_amd64.whl", hash = "sha256:cb95a9b1adaa48e41815a55ae740cfda005758104049a640a398120bf02515ca", size = 86852, upload-time = "2025-10-06T14:09:12.958Z" }, - { url = "https://files.pythonhosted.org/packages/af/af/7df4f179d3b1a6dcb9a4bd2ffbc67642746fcafdb62580e66876ce83fff4/yarl-1.22.0-cp310-cp310-win_arm64.whl", hash = "sha256:b85b982afde6df99ecc996990d4ad7ccbdbb70e2a4ba4de0aecde5922ba98a0b", size = 82012, upload-time = "2025-10-06T14:09:14.664Z" }, - { url = "https://files.pythonhosted.org/packages/4d/27/5ab13fc84c76a0250afd3d26d5936349a35be56ce5785447d6c423b26d92/yarl-1.22.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:1ab72135b1f2db3fed3997d7e7dc1b80573c67138023852b6efb336a5eae6511", size = 141607, upload-time = "2025-10-06T14:09:16.298Z" }, - { url = "https://files.pythonhosted.org/packages/6a/a1/d065d51d02dc02ce81501d476b9ed2229d9a990818332242a882d5d60340/yarl-1.22.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:669930400e375570189492dc8d8341301578e8493aec04aebc20d4717f899dd6", size = 94027, upload-time = "2025-10-06T14:09:17.786Z" }, - { url = "https://files.pythonhosted.org/packages/c1/da/8da9f6a53f67b5106ffe902c6fa0164e10398d4e150d85838b82f424072a/yarl-1.22.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:792a2af6d58177ef7c19cbf0097aba92ca1b9cb3ffdd9c7470e156c8f9b5e028", size = 94963, upload-time = "2025-10-06T14:09:19.662Z" }, - { url = "https://files.pythonhosted.org/packages/68/fe/2c1f674960c376e29cb0bec1249b117d11738db92a6ccc4a530b972648db/yarl-1.22.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:3ea66b1c11c9150f1372f69afb6b8116f2dd7286f38e14ea71a44eee9ec51b9d", size = 368406, upload-time = "2025-10-06T14:09:21.402Z" }, - { url = "https://files.pythonhosted.org/packages/95/26/812a540e1c3c6418fec60e9bbd38e871eaba9545e94fa5eff8f4a8e28e1e/yarl-1.22.0-cp311-cp311-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:3e2daa88dc91870215961e96a039ec73e4937da13cf77ce17f9cad0c18df3503", size = 336581, upload-time = "2025-10-06T14:09:22.98Z" }, - { url = "https://files.pythonhosted.org/packages/0b/f5/5777b19e26fdf98563985e481f8be3d8a39f8734147a6ebf459d0dab5a6b/yarl-1.22.0-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:ba440ae430c00eee41509353628600212112cd5018d5def7e9b05ea7ac34eb65", size = 388924, upload-time = "2025-10-06T14:09:24.655Z" }, - { url = "https://files.pythonhosted.org/packages/86/08/24bd2477bd59c0bbd994fe1d93b126e0472e4e3df5a96a277b0a55309e89/yarl-1.22.0-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:e6438cc8f23a9c1478633d216b16104a586b9761db62bfacb6425bac0a36679e", size = 392890, upload-time = "2025-10-06T14:09:26.617Z" }, - { url = "https://files.pythonhosted.org/packages/46/00/71b90ed48e895667ecfb1eaab27c1523ee2fa217433ed77a73b13205ca4b/yarl-1.22.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4c52a6e78aef5cf47a98ef8e934755abf53953379b7d53e68b15ff4420e6683d", size = 365819, upload-time = "2025-10-06T14:09:28.544Z" }, - { url = "https://files.pythonhosted.org/packages/30/2d/f715501cae832651d3282387c6a9236cd26bd00d0ff1e404b3dc52447884/yarl-1.22.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:3b06bcadaac49c70f4c88af4ffcfbe3dc155aab3163e75777818092478bcbbe7", size = 363601, upload-time = "2025-10-06T14:09:30.568Z" }, - { url = "https://files.pythonhosted.org/packages/f8/f9/a678c992d78e394e7126ee0b0e4e71bd2775e4334d00a9278c06a6cce96a/yarl-1.22.0-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:6944b2dc72c4d7f7052683487e3677456050ff77fcf5e6204e98caf785ad1967", size = 358072, upload-time = "2025-10-06T14:09:32.528Z" }, - { url = "https://files.pythonhosted.org/packages/2c/d1/b49454411a60edb6fefdcad4f8e6dbba7d8019e3a508a1c5836cba6d0781/yarl-1.22.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:d5372ca1df0f91a86b047d1277c2aaf1edb32d78bbcefffc81b40ffd18f027ed", size = 385311, upload-time = "2025-10-06T14:09:34.634Z" }, - { url = "https://files.pythonhosted.org/packages/87/e5/40d7a94debb8448c7771a916d1861d6609dddf7958dc381117e7ba36d9e8/yarl-1.22.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:51af598701f5299012b8416486b40fceef8c26fc87dc6d7d1f6fc30609ea0aa6", size = 381094, upload-time = "2025-10-06T14:09:36.268Z" }, - { url = "https://files.pythonhosted.org/packages/35/d8/611cc282502381ad855448643e1ad0538957fc82ae83dfe7762c14069e14/yarl-1.22.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:b266bd01fedeffeeac01a79ae181719ff848a5a13ce10075adbefc8f1daee70e", size = 370944, upload-time = "2025-10-06T14:09:37.872Z" }, - { url = "https://files.pythonhosted.org/packages/2d/df/fadd00fb1c90e1a5a8bd731fa3d3de2e165e5a3666a095b04e31b04d9cb6/yarl-1.22.0-cp311-cp311-win32.whl", hash = "sha256:a9b1ba5610a4e20f655258d5a1fdc7ebe3d837bb0e45b581398b99eb98b1f5ca", size = 81804, upload-time = "2025-10-06T14:09:39.359Z" }, - { url = "https://files.pythonhosted.org/packages/b5/f7/149bb6f45f267cb5c074ac40c01c6b3ea6d8a620d34b337f6321928a1b4d/yarl-1.22.0-cp311-cp311-win_amd64.whl", hash = "sha256:078278b9b0b11568937d9509b589ee83ef98ed6d561dfe2020e24a9fd08eaa2b", size = 86858, upload-time = "2025-10-06T14:09:41.068Z" }, - { url = "https://files.pythonhosted.org/packages/2b/13/88b78b93ad3f2f0b78e13bfaaa24d11cbc746e93fe76d8c06bf139615646/yarl-1.22.0-cp311-cp311-win_arm64.whl", hash = "sha256:b6a6f620cfe13ccec221fa312139135166e47ae169f8253f72a0abc0dae94376", size = 81637, upload-time = "2025-10-06T14:09:42.712Z" }, - { url = "https://files.pythonhosted.org/packages/75/ff/46736024fee3429b80a165a732e38e5d5a238721e634ab41b040d49f8738/yarl-1.22.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:e340382d1afa5d32b892b3ff062436d592ec3d692aeea3bef3a5cfe11bbf8c6f", size = 142000, upload-time = "2025-10-06T14:09:44.631Z" }, - { url = "https://files.pythonhosted.org/packages/5a/9a/b312ed670df903145598914770eb12de1bac44599549b3360acc96878df8/yarl-1.22.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:f1e09112a2c31ffe8d80be1b0988fa6a18c5d5cad92a9ffbb1c04c91bfe52ad2", size = 94338, upload-time = "2025-10-06T14:09:46.372Z" }, - { url = "https://files.pythonhosted.org/packages/ba/f5/0601483296f09c3c65e303d60c070a5c19fcdbc72daa061e96170785bc7d/yarl-1.22.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:939fe60db294c786f6b7c2d2e121576628468f65453d86b0fe36cb52f987bd74", size = 94909, upload-time = "2025-10-06T14:09:48.648Z" }, - { url = "https://files.pythonhosted.org/packages/60/41/9a1fe0b73dbcefce72e46cf149b0e0a67612d60bfc90fb59c2b2efdfbd86/yarl-1.22.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e1651bf8e0398574646744c1885a41198eba53dc8a9312b954073f845c90a8df", size = 372940, upload-time = "2025-10-06T14:09:50.089Z" }, - { url = "https://files.pythonhosted.org/packages/17/7a/795cb6dfee561961c30b800f0ed616b923a2ec6258b5def2a00bf8231334/yarl-1.22.0-cp312-cp312-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:b8a0588521a26bf92a57a1705b77b8b59044cdceccac7151bd8d229e66b8dedb", size = 345825, upload-time = "2025-10-06T14:09:52.142Z" }, - { url = "https://files.pythonhosted.org/packages/d7/93/a58f4d596d2be2ae7bab1a5846c4d270b894958845753b2c606d666744d3/yarl-1.22.0-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:42188e6a615c1a75bcaa6e150c3fe8f3e8680471a6b10150c5f7e83f47cc34d2", size = 386705, upload-time = "2025-10-06T14:09:54.128Z" }, - { url = "https://files.pythonhosted.org/packages/61/92/682279d0e099d0e14d7fd2e176bd04f48de1484f56546a3e1313cd6c8e7c/yarl-1.22.0-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:f6d2cb59377d99718913ad9a151030d6f83ef420a2b8f521d94609ecc106ee82", size = 396518, upload-time = "2025-10-06T14:09:55.762Z" }, - { url = "https://files.pythonhosted.org/packages/db/0f/0d52c98b8a885aeda831224b78f3be7ec2e1aa4a62091f9f9188c3c65b56/yarl-1.22.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:50678a3b71c751d58d7908edc96d332af328839eea883bb554a43f539101277a", size = 377267, upload-time = "2025-10-06T14:09:57.958Z" }, - { url = "https://files.pythonhosted.org/packages/22/42/d2685e35908cbeaa6532c1fc73e89e7f2efb5d8a7df3959ea8e37177c5a3/yarl-1.22.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:1e8fbaa7cec507aa24ea27a01456e8dd4b6fab829059b69844bd348f2d467124", size = 365797, upload-time = "2025-10-06T14:09:59.527Z" }, - { url = "https://files.pythonhosted.org/packages/a2/83/cf8c7bcc6355631762f7d8bdab920ad09b82efa6b722999dfb05afa6cfac/yarl-1.22.0-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:433885ab5431bc3d3d4f2f9bd15bfa1614c522b0f1405d62c4f926ccd69d04fa", size = 365535, upload-time = "2025-10-06T14:10:01.139Z" }, - { url = "https://files.pythonhosted.org/packages/25/e1/5302ff9b28f0c59cac913b91fe3f16c59a033887e57ce9ca5d41a3a94737/yarl-1.22.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:b790b39c7e9a4192dc2e201a282109ed2985a1ddbd5ac08dc56d0e121400a8f7", size = 382324, upload-time = "2025-10-06T14:10:02.756Z" }, - { url = "https://files.pythonhosted.org/packages/bf/cd/4617eb60f032f19ae3a688dc990d8f0d89ee0ea378b61cac81ede3e52fae/yarl-1.22.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:31f0b53913220599446872d757257be5898019c85e7971599065bc55065dc99d", size = 383803, upload-time = "2025-10-06T14:10:04.552Z" }, - { url = "https://files.pythonhosted.org/packages/59/65/afc6e62bb506a319ea67b694551dab4a7e6fb7bf604e9bd9f3e11d575fec/yarl-1.22.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:a49370e8f711daec68d09b821a34e1167792ee2d24d405cbc2387be4f158b520", size = 374220, upload-time = "2025-10-06T14:10:06.489Z" }, - { url = "https://files.pythonhosted.org/packages/e7/3d/68bf18d50dc674b942daec86a9ba922d3113d8399b0e52b9897530442da2/yarl-1.22.0-cp312-cp312-win32.whl", hash = "sha256:70dfd4f241c04bd9239d53b17f11e6ab672b9f1420364af63e8531198e3f5fe8", size = 81589, upload-time = "2025-10-06T14:10:09.254Z" }, - { url = "https://files.pythonhosted.org/packages/c8/9a/6ad1a9b37c2f72874f93e691b2e7ecb6137fb2b899983125db4204e47575/yarl-1.22.0-cp312-cp312-win_amd64.whl", hash = "sha256:8884d8b332a5e9b88e23f60bb166890009429391864c685e17bd73a9eda9105c", size = 87213, upload-time = "2025-10-06T14:10:11.369Z" }, - { url = "https://files.pythonhosted.org/packages/44/c5/c21b562d1680a77634d748e30c653c3ca918beb35555cff24986fff54598/yarl-1.22.0-cp312-cp312-win_arm64.whl", hash = "sha256:ea70f61a47f3cc93bdf8b2f368ed359ef02a01ca6393916bc8ff877427181e74", size = 81330, upload-time = "2025-10-06T14:10:13.112Z" }, - { url = "https://files.pythonhosted.org/packages/ea/f3/d67de7260456ee105dc1d162d43a019ecad6b91e2f51809d6cddaa56690e/yarl-1.22.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:8dee9c25c74997f6a750cd317b8ca63545169c098faee42c84aa5e506c819b53", size = 139980, upload-time = "2025-10-06T14:10:14.601Z" }, - { url = "https://files.pythonhosted.org/packages/01/88/04d98af0b47e0ef42597b9b28863b9060bb515524da0a65d5f4db160b2d5/yarl-1.22.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:01e73b85a5434f89fc4fe27dcda2aff08ddf35e4d47bbbea3bdcd25321af538a", size = 93424, upload-time = "2025-10-06T14:10:16.115Z" }, - { url = "https://files.pythonhosted.org/packages/18/91/3274b215fd8442a03975ce6bee5fe6aa57a8326b29b9d3d56234a1dca244/yarl-1.22.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:22965c2af250d20c873cdbee8ff958fb809940aeb2e74ba5f20aaf6b7ac8c70c", size = 93821, upload-time = "2025-10-06T14:10:17.993Z" }, - { url = "https://files.pythonhosted.org/packages/61/3a/caf4e25036db0f2da4ca22a353dfeb3c9d3c95d2761ebe9b14df8fc16eb0/yarl-1.22.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b4f15793aa49793ec8d1c708ab7f9eded1aa72edc5174cae703651555ed1b601", size = 373243, upload-time = "2025-10-06T14:10:19.44Z" }, - { url = "https://files.pythonhosted.org/packages/6e/9e/51a77ac7516e8e7803b06e01f74e78649c24ee1021eca3d6a739cb6ea49c/yarl-1.22.0-cp313-cp313-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:e5542339dcf2747135c5c85f68680353d5cb9ffd741c0f2e8d832d054d41f35a", size = 342361, upload-time = "2025-10-06T14:10:21.124Z" }, - { url = "https://files.pythonhosted.org/packages/d4/f8/33b92454789dde8407f156c00303e9a891f1f51a0330b0fad7c909f87692/yarl-1.22.0-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:5c401e05ad47a75869c3ab3e35137f8468b846770587e70d71e11de797d113df", size = 387036, upload-time = "2025-10-06T14:10:22.902Z" }, - { url = "https://files.pythonhosted.org/packages/d9/9a/c5db84ea024f76838220280f732970aa4ee154015d7f5c1bfb60a267af6f/yarl-1.22.0-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:243dda95d901c733f5b59214d28b0120893d91777cb8aa043e6ef059d3cddfe2", size = 397671, upload-time = "2025-10-06T14:10:24.523Z" }, - { url = "https://files.pythonhosted.org/packages/11/c9/cd8538dc2e7727095e0c1d867bad1e40c98f37763e6d995c1939f5fdc7b1/yarl-1.22.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:bec03d0d388060058f5d291a813f21c011041938a441c593374da6077fe21b1b", size = 377059, upload-time = "2025-10-06T14:10:26.406Z" }, - { url = "https://files.pythonhosted.org/packages/a1/b9/ab437b261702ced75122ed78a876a6dec0a1b0f5e17a4ac7a9a2482d8abe/yarl-1.22.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:b0748275abb8c1e1e09301ee3cf90c8a99678a4e92e4373705f2a2570d581273", size = 365356, upload-time = "2025-10-06T14:10:28.461Z" }, - { url = "https://files.pythonhosted.org/packages/b2/9d/8e1ae6d1d008a9567877b08f0ce4077a29974c04c062dabdb923ed98e6fe/yarl-1.22.0-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:47fdb18187e2a4e18fda2c25c05d8251a9e4a521edaed757fef033e7d8498d9a", size = 361331, upload-time = "2025-10-06T14:10:30.541Z" }, - { url = "https://files.pythonhosted.org/packages/ca/5a/09b7be3905962f145b73beb468cdd53db8aa171cf18c80400a54c5b82846/yarl-1.22.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:c7044802eec4524fde550afc28edda0dd5784c4c45f0be151a2d3ba017daca7d", size = 382590, upload-time = "2025-10-06T14:10:33.352Z" }, - { url = "https://files.pythonhosted.org/packages/aa/7f/59ec509abf90eda5048b0bc3e2d7b5099dffdb3e6b127019895ab9d5ef44/yarl-1.22.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:139718f35149ff544caba20fce6e8a2f71f1e39b92c700d8438a0b1d2a631a02", size = 385316, upload-time = "2025-10-06T14:10:35.034Z" }, - { url = "https://files.pythonhosted.org/packages/e5/84/891158426bc8036bfdfd862fabd0e0fa25df4176ec793e447f4b85cf1be4/yarl-1.22.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e1b51bebd221006d3d2f95fbe124b22b247136647ae5dcc8c7acafba66e5ee67", size = 374431, upload-time = "2025-10-06T14:10:37.76Z" }, - { url = "https://files.pythonhosted.org/packages/bb/49/03da1580665baa8bef5e8ed34c6df2c2aca0a2f28bf397ed238cc1bbc6f2/yarl-1.22.0-cp313-cp313-win32.whl", hash = "sha256:d3e32536234a95f513bd374e93d717cf6b2231a791758de6c509e3653f234c95", size = 81555, upload-time = "2025-10-06T14:10:39.649Z" }, - { url = "https://files.pythonhosted.org/packages/9a/ee/450914ae11b419eadd067c6183ae08381cfdfcb9798b90b2b713bbebddda/yarl-1.22.0-cp313-cp313-win_amd64.whl", hash = "sha256:47743b82b76d89a1d20b83e60d5c20314cbd5ba2befc9cda8f28300c4a08ed4d", size = 86965, upload-time = "2025-10-06T14:10:41.313Z" }, - { url = "https://files.pythonhosted.org/packages/98/4d/264a01eae03b6cf629ad69bae94e3b0e5344741e929073678e84bf7a3e3b/yarl-1.22.0-cp313-cp313-win_arm64.whl", hash = "sha256:5d0fcda9608875f7d052eff120c7a5da474a6796fe4d83e152e0e4d42f6d1a9b", size = 81205, upload-time = "2025-10-06T14:10:43.167Z" }, - { url = "https://files.pythonhosted.org/packages/88/fc/6908f062a2f77b5f9f6d69cecb1747260831ff206adcbc5b510aff88df91/yarl-1.22.0-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:719ae08b6972befcba4310e49edb1161a88cdd331e3a694b84466bd938a6ab10", size = 146209, upload-time = "2025-10-06T14:10:44.643Z" }, - { url = "https://files.pythonhosted.org/packages/65/47/76594ae8eab26210b4867be6f49129861ad33da1f1ebdf7051e98492bf62/yarl-1.22.0-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:47d8a5c446df1c4db9d21b49619ffdba90e77c89ec6e283f453856c74b50b9e3", size = 95966, upload-time = "2025-10-06T14:10:46.554Z" }, - { url = "https://files.pythonhosted.org/packages/ab/ce/05e9828a49271ba6b5b038b15b3934e996980dd78abdfeb52a04cfb9467e/yarl-1.22.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:cfebc0ac8333520d2d0423cbbe43ae43c8838862ddb898f5ca68565e395516e9", size = 97312, upload-time = "2025-10-06T14:10:48.007Z" }, - { url = "https://files.pythonhosted.org/packages/d1/c5/7dffad5e4f2265b29c9d7ec869c369e4223166e4f9206fc2243ee9eea727/yarl-1.22.0-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4398557cbf484207df000309235979c79c4356518fd5c99158c7d38203c4da4f", size = 361967, upload-time = "2025-10-06T14:10:49.997Z" }, - { url = "https://files.pythonhosted.org/packages/50/b2/375b933c93a54bff7fc041e1a6ad2c0f6f733ffb0c6e642ce56ee3b39970/yarl-1.22.0-cp313-cp313t-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:2ca6fd72a8cd803be290d42f2dec5cdcd5299eeb93c2d929bf060ad9efaf5de0", size = 323949, upload-time = "2025-10-06T14:10:52.004Z" }, - { url = "https://files.pythonhosted.org/packages/66/50/bfc2a29a1d78644c5a7220ce2f304f38248dc94124a326794e677634b6cf/yarl-1.22.0-cp313-cp313t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:ca1f59c4e1ab6e72f0a23c13fca5430f889634166be85dbf1013683e49e3278e", size = 361818, upload-time = "2025-10-06T14:10:54.078Z" }, - { url = "https://files.pythonhosted.org/packages/46/96/f3941a46af7d5d0f0498f86d71275696800ddcdd20426298e572b19b91ff/yarl-1.22.0-cp313-cp313t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:6c5010a52015e7c70f86eb967db0f37f3c8bd503a695a49f8d45700144667708", size = 372626, upload-time = "2025-10-06T14:10:55.767Z" }, - { url = "https://files.pythonhosted.org/packages/c1/42/8b27c83bb875cd89448e42cd627e0fb971fa1675c9ec546393d18826cb50/yarl-1.22.0-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9d7672ecf7557476642c88497c2f8d8542f8e36596e928e9bcba0e42e1e7d71f", size = 341129, upload-time = "2025-10-06T14:10:57.985Z" }, - { url = "https://files.pythonhosted.org/packages/49/36/99ca3122201b382a3cf7cc937b95235b0ac944f7e9f2d5331d50821ed352/yarl-1.22.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:3b7c88eeef021579d600e50363e0b6ee4f7f6f728cd3486b9d0f3ee7b946398d", size = 346776, upload-time = "2025-10-06T14:10:59.633Z" }, - { url = "https://files.pythonhosted.org/packages/85/b4/47328bf996acd01a4c16ef9dcd2f59c969f495073616586f78cd5f2efb99/yarl-1.22.0-cp313-cp313t-musllinux_1_2_armv7l.whl", hash = "sha256:f4afb5c34f2c6fecdcc182dfcfc6af6cccf1aa923eed4d6a12e9d96904e1a0d8", size = 334879, upload-time = "2025-10-06T14:11:01.454Z" }, - { url = "https://files.pythonhosted.org/packages/c2/ad/b77d7b3f14a4283bffb8e92c6026496f6de49751c2f97d4352242bba3990/yarl-1.22.0-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:59c189e3e99a59cf8d83cbb31d4db02d66cda5a1a4374e8a012b51255341abf5", size = 350996, upload-time = "2025-10-06T14:11:03.452Z" }, - { url = "https://files.pythonhosted.org/packages/81/c8/06e1d69295792ba54d556f06686cbd6a7ce39c22307100e3fb4a2c0b0a1d/yarl-1.22.0-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:5a3bf7f62a289fa90f1990422dc8dff5a458469ea71d1624585ec3a4c8d6960f", size = 356047, upload-time = "2025-10-06T14:11:05.115Z" }, - { url = "https://files.pythonhosted.org/packages/4b/b8/4c0e9e9f597074b208d18cef227d83aac36184bfbc6eab204ea55783dbc5/yarl-1.22.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:de6b9a04c606978fdfe72666fa216ffcf2d1a9f6a381058d4378f8d7b1e5de62", size = 342947, upload-time = "2025-10-06T14:11:08.137Z" }, - { url = "https://files.pythonhosted.org/packages/e0/e5/11f140a58bf4c6ad7aca69a892bff0ee638c31bea4206748fc0df4ebcb3a/yarl-1.22.0-cp313-cp313t-win32.whl", hash = "sha256:1834bb90991cc2999f10f97f5f01317f99b143284766d197e43cd5b45eb18d03", size = 86943, upload-time = "2025-10-06T14:11:10.284Z" }, - { url = "https://files.pythonhosted.org/packages/31/74/8b74bae38ed7fe6793d0c15a0c8207bbb819cf287788459e5ed230996cdd/yarl-1.22.0-cp313-cp313t-win_amd64.whl", hash = "sha256:ff86011bd159a9d2dfc89c34cfd8aff12875980e3bd6a39ff097887520e60249", size = 93715, upload-time = "2025-10-06T14:11:11.739Z" }, - { url = "https://files.pythonhosted.org/packages/69/66/991858aa4b5892d57aef7ee1ba6b4d01ec3b7eb3060795d34090a3ca3278/yarl-1.22.0-cp313-cp313t-win_arm64.whl", hash = "sha256:7861058d0582b847bc4e3a4a4c46828a410bca738673f35a29ba3ca5db0b473b", size = 83857, upload-time = "2025-10-06T14:11:13.586Z" }, - { url = "https://files.pythonhosted.org/packages/46/b3/e20ef504049f1a1c54a814b4b9bed96d1ac0e0610c3b4da178f87209db05/yarl-1.22.0-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:34b36c2c57124530884d89d50ed2c1478697ad7473efd59cfd479945c95650e4", size = 140520, upload-time = "2025-10-06T14:11:15.465Z" }, - { url = "https://files.pythonhosted.org/packages/e4/04/3532d990fdbab02e5ede063676b5c4260e7f3abea2151099c2aa745acc4c/yarl-1.22.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:0dd9a702591ca2e543631c2a017e4a547e38a5c0f29eece37d9097e04a7ac683", size = 93504, upload-time = "2025-10-06T14:11:17.106Z" }, - { url = "https://files.pythonhosted.org/packages/11/63/ff458113c5c2dac9a9719ac68ee7c947cb621432bcf28c9972b1c0e83938/yarl-1.22.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:594fcab1032e2d2cc3321bb2e51271e7cd2b516c7d9aee780ece81b07ff8244b", size = 94282, upload-time = "2025-10-06T14:11:19.064Z" }, - { url = "https://files.pythonhosted.org/packages/a7/bc/315a56aca762d44a6aaaf7ad253f04d996cb6b27bad34410f82d76ea8038/yarl-1.22.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f3d7a87a78d46a2e3d5b72587ac14b4c16952dd0887dbb051451eceac774411e", size = 372080, upload-time = "2025-10-06T14:11:20.996Z" }, - { url = "https://files.pythonhosted.org/packages/3f/3f/08e9b826ec2e099ea6e7c69a61272f4f6da62cb5b1b63590bb80ca2e4a40/yarl-1.22.0-cp314-cp314-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:852863707010316c973162e703bddabec35e8757e67fcb8ad58829de1ebc8590", size = 338696, upload-time = "2025-10-06T14:11:22.847Z" }, - { url = "https://files.pythonhosted.org/packages/e3/9f/90360108e3b32bd76789088e99538febfea24a102380ae73827f62073543/yarl-1.22.0-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:131a085a53bfe839a477c0845acf21efc77457ba2bcf5899618136d64f3303a2", size = 387121, upload-time = "2025-10-06T14:11:24.889Z" }, - { url = "https://files.pythonhosted.org/packages/98/92/ab8d4657bd5b46a38094cfaea498f18bb70ce6b63508fd7e909bd1f93066/yarl-1.22.0-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:078a8aefd263f4d4f923a9677b942b445a2be970ca24548a8102689a3a8ab8da", size = 394080, upload-time = "2025-10-06T14:11:27.307Z" }, - { url = "https://files.pythonhosted.org/packages/f5/e7/d8c5a7752fef68205296201f8ec2bf718f5c805a7a7e9880576c67600658/yarl-1.22.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:bca03b91c323036913993ff5c738d0842fc9c60c4648e5c8d98331526df89784", size = 372661, upload-time = "2025-10-06T14:11:29.387Z" }, - { url = "https://files.pythonhosted.org/packages/b6/2e/f4d26183c8db0bb82d491b072f3127fb8c381a6206a3a56332714b79b751/yarl-1.22.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:68986a61557d37bb90d3051a45b91fa3d5c516d177dfc6dd6f2f436a07ff2b6b", size = 364645, upload-time = "2025-10-06T14:11:31.423Z" }, - { url = "https://files.pythonhosted.org/packages/80/7c/428e5812e6b87cd00ee8e898328a62c95825bf37c7fa87f0b6bb2ad31304/yarl-1.22.0-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:4792b262d585ff0dff6bcb787f8492e40698443ec982a3568c2096433660c694", size = 355361, upload-time = "2025-10-06T14:11:33.055Z" }, - { url = "https://files.pythonhosted.org/packages/ec/2a/249405fd26776f8b13c067378ef4d7dd49c9098d1b6457cdd152a99e96a9/yarl-1.22.0-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:ebd4549b108d732dba1d4ace67614b9545b21ece30937a63a65dd34efa19732d", size = 381451, upload-time = "2025-10-06T14:11:35.136Z" }, - { url = "https://files.pythonhosted.org/packages/67/a8/fb6b1adbe98cf1e2dd9fad71003d3a63a1bc22459c6e15f5714eb9323b93/yarl-1.22.0-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:f87ac53513d22240c7d59203f25cc3beac1e574c6cd681bbfd321987b69f95fd", size = 383814, upload-time = "2025-10-06T14:11:37.094Z" }, - { url = "https://files.pythonhosted.org/packages/d9/f9/3aa2c0e480fb73e872ae2814c43bc1e734740bb0d54e8cb2a95925f98131/yarl-1.22.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:22b029f2881599e2f1b06f8f1db2ee63bd309e2293ba2d566e008ba12778b8da", size = 370799, upload-time = "2025-10-06T14:11:38.83Z" }, - { url = "https://files.pythonhosted.org/packages/50/3c/af9dba3b8b5eeb302f36f16f92791f3ea62e3f47763406abf6d5a4a3333b/yarl-1.22.0-cp314-cp314-win32.whl", hash = "sha256:6a635ea45ba4ea8238463b4f7d0e721bad669f80878b7bfd1f89266e2ae63da2", size = 82990, upload-time = "2025-10-06T14:11:40.624Z" }, - { url = "https://files.pythonhosted.org/packages/ac/30/ac3a0c5bdc1d6efd1b41fa24d4897a4329b3b1e98de9449679dd327af4f0/yarl-1.22.0-cp314-cp314-win_amd64.whl", hash = "sha256:0d6e6885777af0f110b0e5d7e5dda8b704efed3894da26220b7f3d887b839a79", size = 88292, upload-time = "2025-10-06T14:11:42.578Z" }, - { url = "https://files.pythonhosted.org/packages/df/0a/227ab4ff5b998a1b7410abc7b46c9b7a26b0ca9e86c34ba4b8d8bc7c63d5/yarl-1.22.0-cp314-cp314-win_arm64.whl", hash = "sha256:8218f4e98d3c10d683584cb40f0424f4b9fd6e95610232dd75e13743b070ee33", size = 82888, upload-time = "2025-10-06T14:11:44.863Z" }, - { url = "https://files.pythonhosted.org/packages/06/5e/a15eb13db90abd87dfbefb9760c0f3f257ac42a5cac7e75dbc23bed97a9f/yarl-1.22.0-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:45c2842ff0e0d1b35a6bf1cd6c690939dacb617a70827f715232b2e0494d55d1", size = 146223, upload-time = "2025-10-06T14:11:46.796Z" }, - { url = "https://files.pythonhosted.org/packages/18/82/9665c61910d4d84f41a5bf6837597c89e665fa88aa4941080704645932a9/yarl-1.22.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:d947071e6ebcf2e2bee8fce76e10faca8f7a14808ca36a910263acaacef08eca", size = 95981, upload-time = "2025-10-06T14:11:48.845Z" }, - { url = "https://files.pythonhosted.org/packages/5d/9a/2f65743589809af4d0a6d3aa749343c4b5f4c380cc24a8e94a3c6625a808/yarl-1.22.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:334b8721303e61b00019474cc103bdac3d7b1f65e91f0bfedeec2d56dfe74b53", size = 97303, upload-time = "2025-10-06T14:11:50.897Z" }, - { url = "https://files.pythonhosted.org/packages/b0/ab/5b13d3e157505c43c3b43b5a776cbf7b24a02bc4cccc40314771197e3508/yarl-1.22.0-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:1e7ce67c34138a058fd092f67d07a72b8e31ff0c9236e751957465a24b28910c", size = 361820, upload-time = "2025-10-06T14:11:52.549Z" }, - { url = "https://files.pythonhosted.org/packages/fb/76/242a5ef4677615cf95330cfc1b4610e78184400699bdda0acb897ef5e49a/yarl-1.22.0-cp314-cp314t-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:d77e1b2c6d04711478cb1c4ab90db07f1609ccf06a287d5607fcd90dc9863acf", size = 323203, upload-time = "2025-10-06T14:11:54.225Z" }, - { url = "https://files.pythonhosted.org/packages/8c/96/475509110d3f0153b43d06164cf4195c64d16999e0c7e2d8a099adcd6907/yarl-1.22.0-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:c4647674b6150d2cae088fc07de2738a84b8bcedebef29802cf0b0a82ab6face", size = 363173, upload-time = "2025-10-06T14:11:56.069Z" }, - { url = "https://files.pythonhosted.org/packages/c9/66/59db471aecfbd559a1fd48aedd954435558cd98c7d0da8b03cc6c140a32c/yarl-1.22.0-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:efb07073be061c8f79d03d04139a80ba33cbd390ca8f0297aae9cce6411e4c6b", size = 373562, upload-time = "2025-10-06T14:11:58.783Z" }, - { url = "https://files.pythonhosted.org/packages/03/1f/c5d94abc91557384719da10ff166b916107c1b45e4d0423a88457071dd88/yarl-1.22.0-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:e51ac5435758ba97ad69617e13233da53908beccc6cfcd6c34bbed8dcbede486", size = 339828, upload-time = "2025-10-06T14:12:00.686Z" }, - { url = "https://files.pythonhosted.org/packages/5f/97/aa6a143d3afba17b6465733681c70cf175af89f76ec8d9286e08437a7454/yarl-1.22.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:33e32a0dd0c8205efa8e83d04fc9f19313772b78522d1bdc7d9aed706bfd6138", size = 347551, upload-time = "2025-10-06T14:12:02.628Z" }, - { url = "https://files.pythonhosted.org/packages/43/3c/45a2b6d80195959239a7b2a8810506d4eea5487dce61c2a3393e7fc3c52e/yarl-1.22.0-cp314-cp314t-musllinux_1_2_armv7l.whl", hash = "sha256:bf4a21e58b9cde0e401e683ebd00f6ed30a06d14e93f7c8fd059f8b6e8f87b6a", size = 334512, upload-time = "2025-10-06T14:12:04.871Z" }, - { url = "https://files.pythonhosted.org/packages/86/a0/c2ab48d74599c7c84cb104ebd799c5813de252bea0f360ffc29d270c2caa/yarl-1.22.0-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:e4b582bab49ac33c8deb97e058cd67c2c50dac0dd134874106d9c774fd272529", size = 352400, upload-time = "2025-10-06T14:12:06.624Z" }, - { url = "https://files.pythonhosted.org/packages/32/75/f8919b2eafc929567d3d8411f72bdb1a2109c01caaab4ebfa5f8ffadc15b/yarl-1.22.0-cp314-cp314t-musllinux_1_2_s390x.whl", hash = "sha256:0b5bcc1a9c4839e7e30b7b30dd47fe5e7e44fb7054ec29b5bb8d526aa1041093", size = 357140, upload-time = "2025-10-06T14:12:08.362Z" }, - { url = "https://files.pythonhosted.org/packages/cf/72/6a85bba382f22cf78add705d8c3731748397d986e197e53ecc7835e76de7/yarl-1.22.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:c0232bce2170103ec23c454e54a57008a9a72b5d1c3105dc2496750da8cfa47c", size = 341473, upload-time = "2025-10-06T14:12:10.994Z" }, - { url = "https://files.pythonhosted.org/packages/35/18/55e6011f7c044dc80b98893060773cefcfdbf60dfefb8cb2f58b9bacbd83/yarl-1.22.0-cp314-cp314t-win32.whl", hash = "sha256:8009b3173bcd637be650922ac455946197d858b3630b6d8787aa9e5c4564533e", size = 89056, upload-time = "2025-10-06T14:12:13.317Z" }, - { url = "https://files.pythonhosted.org/packages/f9/86/0f0dccb6e59a9e7f122c5afd43568b1d31b8ab7dda5f1b01fb5c7025c9a9/yarl-1.22.0-cp314-cp314t-win_amd64.whl", hash = "sha256:9fb17ea16e972c63d25d4a97f016d235c78dd2344820eb35bc034bc32012ee27", size = 96292, upload-time = "2025-10-06T14:12:15.398Z" }, - { url = "https://files.pythonhosted.org/packages/48/b7/503c98092fb3b344a179579f55814b613c1fbb1c23b3ec14a7b008a66a6e/yarl-1.22.0-cp314-cp314t-win_arm64.whl", hash = "sha256:9f6d73c1436b934e3f01df1e1b21ff765cd1d28c77dfb9ace207f746d4610ee1", size = 85171, upload-time = "2025-10-06T14:12:16.935Z" }, - { url = "https://files.pythonhosted.org/packages/73/ae/b48f95715333080afb75a4504487cbe142cae1268afc482d06692d605ae6/yarl-1.22.0-py3-none-any.whl", hash = "sha256:1380560bdba02b6b6c90de54133c81c9f2a453dee9912fe58c1dcced1edb7cff", size = 46814, upload-time = "2025-10-06T14:12:53.872Z" }, -] - -[[package]] -name = "zipp" -version = "3.23.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/e3/02/0f2892c661036d50ede074e376733dca2ae7c6eb617489437771209d4180/zipp-3.23.0.tar.gz", hash = "sha256:a07157588a12518c9d4034df3fbbee09c814741a33ff63c05fa29d26a2404166", size = 25547, upload-time = "2025-06-08T17:06:39.4Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/2e/54/647ade08bf0db230bfea292f893923872fd20be6ac6f53b2b936ba839d75/zipp-3.23.0-py3-none-any.whl", hash = "sha256:071652d6115ed432f5ce1d34c336c0adfd6a884660d1e9712a256d3d3bd4b14e", size = 10276, upload-time = "2025-06-08T17:06:38.034Z" }, -] diff --git a/integrations/langchain-py/.env.example b/integrations/langchain-py/.env.example deleted file mode 100644 index 726c975a8..000000000 --- a/integrations/langchain-py/.env.example +++ /dev/null @@ -1,2 +0,0 @@ -BRAINTRUST_API_KEY=your-api-key-here -OPENAI_API_KEY=your-openai-key-here diff --git a/integrations/langchain-py/.envrc b/integrations/langchain-py/.envrc deleted file mode 100644 index 43edf50a3..000000000 --- a/integrations/langchain-py/.envrc +++ /dev/null @@ -1,2 +0,0 @@ -source_up_if_exists -dotenv_if_exists diff --git a/integrations/langchain-py/.gitignore b/integrations/langchain-py/.gitignore deleted file mode 100644 index 9b2c59a5b..000000000 --- a/integrations/langchain-py/.gitignore +++ /dev/null @@ -1,34 +0,0 @@ -# Python -__pycache__/ -*.py[cod] -*$py.class -*.so -.Python -build/ -develop-eggs/ -dist/ -downloads/ -eggs/ -.eggs/ -lib/ -lib64/ -parts/ -sdist/ -var/ -wheels/ -*.egg-info/ -.installed.cfg -*.egg - -# Virtual Environment -venv/ -ENV/ - -# IDE -.idea/ -.vscode/ -*.swp -*.swo - -# Mac -.DS_Store diff --git a/integrations/langchain-py/.python-version b/integrations/langchain-py/.python-version deleted file mode 100644 index c8cfe3959..000000000 --- a/integrations/langchain-py/.python-version +++ /dev/null @@ -1 +0,0 @@ -3.10 diff --git a/integrations/langchain-py/Makefile b/integrations/langchain-py/Makefile deleted file mode 100644 index d515c98be..000000000 --- a/integrations/langchain-py/Makefile +++ /dev/null @@ -1,38 +0,0 @@ -SHELL := /bin/bash -ROOT_DIR:=$(shell dirname $(realpath $(firstword $(MAKEFILE_LIST)))) -VENV_PRE_COMMIT := ${ROOT_DIR}/venv/.pre_commit - -.PHONY: all -all: ${VENV_PRE_COMMIT} - -.PHONY: py -py: ${VENV_PYTHON_PACKAGES} - bash -c 'source venv/bin/activate' - -VENV_INITIALIZED := venv/.initialized - -${VENV_INITIALIZED}: - rm -rf venv && python -m venv venv - @touch ${VENV_INITIALIZED} - -VENV_PYTHON_PACKAGES := venv/.python_packages - -${VENV_PYTHON_PACKAGES}: ${VENV_INITIALIZED} - bash -c 'source venv/bin/activate && python -m pip install --upgrade pip setuptools' - bash -c 'source venv/bin/activate && python -m pip install -e .[all]' - @touch $@ - -${VENV_PRE_COMMIT}: ${VENV_PYTHON_PACKAGES} - bash -c 'source venv/bin/activate && pre-commit install' - @touch $@ - -develop: ${VENV_PRE_COMMIT} - @echo "--\nRun "source env.sh" to enter development mode!" - -fixup: - source env.sh && pre-commit run --all-files - -.PHONY: test - -test: - source env.sh && pytest diff --git a/integrations/langchain-py/README.md b/integrations/langchain-py/README.md deleted file mode 100644 index ef290891a..000000000 --- a/integrations/langchain-py/README.md +++ /dev/null @@ -1,100 +0,0 @@ -# braintrust-langchain - -SDK for integrating [Braintrust](https://braintrust.dev) with [LangChain](https://langchain.com/). This package provides a callback handler to automatically log LangChain executions to Braintrust. - -## Installation - -```bash -pip install braintrust-langchain -``` - -## Requirements - -- Python >= 3.9 -- LangChain >= 0.1.0 - -## Usage - -First, make sure you have your Braintrust API key set in your environment: - -```bash -export BRAINTRUST_API_KEY="your-api-key" -``` - -### Basic Usage - -```python -import asyncio -from braintrust import init_logger -from braintrust_langchain import BraintrustCallbackHandler, set_global_handler -from langchain_openai import ChatOpenAI -from langchain_core.prompts import ChatPromptTemplate - - -async def main(): - # Initialize the logger with your project - init_logger(project="your-project-name") - - # Create the callback handler and set it globally for all LangChain components - handler = BraintrustCallbackHandler() - set_global_handler(handler) - - # Initialize your LangChain components - prompt = ChatPromptTemplate.from_template("What is 1 + {number}?") - model = ChatOpenAI() - - # Create a simple chain - chain = prompt | model - - # Use LangChain as normal - all calls will be logged to Braintrust - response = await chain.ainvoke({"number": "2"}) - - -if __name__ == "__main__": - asyncio.run(main()) -``` - -If you'd prefer to pass the callback handler to specific LangChain calls instead of setting it globally, you can do so using the `callbacks` config option: - -```python -async def main(): - handler = BraintrustCallbackHandler() - - # Pass the handler to specific calls - response = await chain.ainvoke( - {"number": "2"}, - config={"callbacks": [handler]} - ) - - # Or initialize components with the handler - model = ChatOpenAI(callbacks=[handler]) -``` - -### Supported Features - -The callback handler supports logging for: - -- LLM calls (including streaming) -- Chat model interactions -- Chain executions -- Tool/Agent usage -- Memory operations -- State management (LangGraph) - -Review the [LangChain documentation](https://python.langchain.com/docs/modules/callbacks/) for more information on how to use callbacks. - -## Development - -Contributions are welcomed! - -```bash -git clone https://github.com/braintrustdata/sdk.git - -cd sdk/integrations/langchain-py - -pip install -e ".[dev]" - -# work on the code - -pytest -``` diff --git a/integrations/langchain-py/env.sh b/integrations/langchain-py/env.sh deleted file mode 100644 index 266490fb9..000000000 --- a/integrations/langchain-py/env.sh +++ /dev/null @@ -1,3 +0,0 @@ -#!/bin/bash -source venv/bin/activate -export PYTHONPATH="$PWD/src:$PYTHONPATH" diff --git a/integrations/langchain-py/pyproject.toml b/integrations/langchain-py/pyproject.toml deleted file mode 100644 index 90fd84c2a..000000000 --- a/integrations/langchain-py/pyproject.toml +++ /dev/null @@ -1,88 +0,0 @@ -[project] -name = "braintrust-langchain" -version = "0.2.1" -description = "Integration for LangChain and Braintrust Tracing" -readme = "README.md" -requires-python = ">=3.10" -dependencies = [ - "braintrust>=0.2.1", - "langchain>=0.3.27", -] -license = "MIT" -authors = [{ name = "Braintrust", email = "info@braintrust.dev" }] -keywords = ["braintrust", "langchain", "llm", "tracing", "ai", "agents"] -classifiers = [ - "Development Status :: 4 - Beta", - "Programming Language :: Python :: 3", - "Programming Language :: Python :: 3.10", - "Programming Language :: Python :: 3.11", - "Programming Language :: Python :: 3.12", - "Operating System :: OS Independent", -] - -[project.urls] -Homepage = "https://www.braintrust.dev" -Repository = "https://github.com/braintrustdata/braintrust-sdk" - -[build-system] -requires = ["setuptools>=61.0"] -build-backend = "setuptools.build_meta" - -[tool.setuptools] -package-dir = { "" = "src" } - -[tool.setuptools.packages.find] -where = ["src"] - - -[tool.uv.workspace] -members = [ - ".", -] - -[dependency-groups] -dev = [ - "black", - "build", - "flake8", - "flake8-isort", - "httpx", - "isort==5.12.0", - "langchain-anthropic>=0.3.20", - "langchain-openai", - "langgraph>=0.2.1,<0.4.0", - "pre-commit", - "pytest", - "pytest-asyncio>=1.1.0", - "pytest-vcr>=1.0.2", - "ruff", - "tenacity", - "twine", -] - -[tool.black] -line-length = 120 -target-version = ['py310'] - -[tool.isort] -profile = "black" -line_length = 120 -known_first_party = ["braintrust_langchain"] -known_third_party = ["braintrust", "langchain"] - -[tool.ruff] -line-length = 120 - -[tool.ruff.lint] -select = [ - "I", # isort -] - -[tool.ruff.lint.isort] -known-first-party = ["braintrust_langchain"] -known-third-party = ["braintrust", "langchain"] - -[tool.pytest.ini_options] -testpaths = ["src/tests"] -python_files = ["test_*.py"] -addopts = "-v" diff --git a/integrations/langchain-py/pyrightconfig.json b/integrations/langchain-py/pyrightconfig.json deleted file mode 100644 index b7de5856f..000000000 --- a/integrations/langchain-py/pyrightconfig.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "typeCheckingMode": "strict", - "reportUnknownVariableType": false, - "reportUnknownMemberType": false, - "reportUnknownArgumentType": false, - "reportUnknownParameterType": false -} diff --git a/integrations/langchain-py/src/braintrust_langchain/__init__.py b/integrations/langchain-py/src/braintrust_langchain/__init__.py deleted file mode 100644 index 2feeb7bc7..000000000 --- a/integrations/langchain-py/src/braintrust_langchain/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from .callbacks import BraintrustCallbackHandler -from .context import set_global_handler - -__all__ = ["BraintrustCallbackHandler", "set_global_handler"] diff --git a/integrations/langchain-py/src/braintrust_langchain/callbacks.py b/integrations/langchain-py/src/braintrust_langchain/callbacks.py deleted file mode 100644 index 871253a1d..000000000 --- a/integrations/langchain-py/src/braintrust_langchain/callbacks.py +++ /dev/null @@ -1,652 +0,0 @@ -import json -import logging -import re -import time -from collections.abc import Mapping, Sequence -from re import Pattern -from typing import ( - Any, - Dict, - List, - Optional, - Set, - TypedDict, - Union, -) -from uuid import UUID - -import braintrust -from braintrust import NOOP_SPAN, Logger, Span, SpanAttributes, SpanTypeAttribute, current_span, init_logger -from braintrust.version import VERSION as sdk_version -from langchain_core.agents import AgentAction, AgentFinish -from langchain_core.callbacks.base import BaseCallbackHandler -from langchain_core.documents import Document -from langchain_core.messages import BaseMessage -from langchain_core.outputs.llm_result import LLMResult -from tenacity import RetryCallState -from typing_extensions import NotRequired - -from braintrust_langchain.version import version - -_logger = logging.getLogger("braintrust_langchain") - - -class LogEvent(TypedDict): - input: NotRequired[Any] - output: NotRequired[Any] - expected: NotRequired[Any] - error: NotRequired[str] - tags: NotRequired[Sequence[str] | None] - scores: NotRequired[Mapping[str, int | float]] - metadata: NotRequired[Mapping[str, Any]] - metrics: NotRequired[Mapping[str, int | float]] - id: NotRequired[str] - dataset_record_id: NotRequired[str] - - -class BraintrustCallbackHandler(BaseCallbackHandler): - root_run_id: UUID | None = None - - def __init__( - self, - logger: Logger | Span | None = None, - debug: bool = False, - exclude_metadata_props: Pattern[str] | None = None, - ): - self.logger = logger - self.spans: dict[UUID, Span] = {} - self.debug = debug # DEPRECATED - self.exclude_metadata_props = exclude_metadata_props or re.compile( - r"^(l[sc]_|langgraph_|__pregel_|checkpoint_ns)" - ) - self.skipped_runs: set[UUID] = set() - # Set run_inline=True to avoid thread executor in async contexts - # This ensures memory logger context is preserved - self.run_inline = True - - self._start_times: dict[UUID, float] = {} - self._first_token_times: dict[UUID, float] = {} - self._ttft_ms: dict[UUID, float] = {} - - def _start_span( - self, - parent_run_id: UUID | None, - run_id: UUID, - name: str | None = None, - type: SpanTypeAttribute | None = SpanTypeAttribute.TASK, - span_attributes: SpanAttributes | Mapping[str, Any] | None = None, - start_time: float | None = None, - set_current: bool | None = None, - parent: str | None = None, - event: LogEvent | None = None, - ) -> Any: - if run_id in self.spans: - # XXX: See graph test case of an example where this _may_ be intended. - _logger.warning(f"Span already exists for run_id {run_id} (this is likely a bug)") - return - - if not parent_run_id: - self.root_run_id = run_id - - current_parent = current_span() - parent_span = None - if parent_run_id and parent_run_id in self.spans: - parent_span = self.spans[parent_run_id] - elif current_parent != NOOP_SPAN: - parent_span = current_parent - elif self.logger is not None: - parent_span = self.logger - else: - parent_span = braintrust - - if event is None: - event = {} - - tags = event.get("tags") or [] - event = { - **event, - "tags": None, - "metadata": { - **({"tags": tags}), - **(event.get("metadata") or {}), - "run_id": run_id, - "parent_run_id": parent_run_id, - "braintrust": { - "integration_name": "langchain-py", - "integration_version": version, - "sdk_version": sdk_version, - "language": "python", - }, - }, - } - - span = parent_span.start_span( - name=name, - type=type, - span_attributes=span_attributes, - start_time=start_time, - set_current=set_current, - parent=parent, - **event, - ) - - if self.logger != NOOP_SPAN and span == NOOP_SPAN: - _logger.warning( - "Braintrust logging not configured. Pass a `logger`, call `init_logger`, or run an experiment to configure Braintrust logging. Setting up a default." - ) - span = init_logger().start_span( - name=name, - type=type, - span_attributes=span_attributes, - start_time=start_time, - set_current=set_current, - parent=parent, - **event, - ) - - span.set_current() - - self.spans[run_id] = span - return span - - def _end_span( - self, - run_id: UUID, - parent_run_id: UUID | None = None, - input: Any | None = None, - output: Any | None = None, - expected: Any | None = None, - error: str | None = None, - tags: Sequence[str] | None = None, - scores: Mapping[str, int | float] | None = None, - metadata: Mapping[str, Any] | None = None, - metrics: Mapping[str, int | float] | None = None, - dataset_record_id: str | None = None, - ) -> Any: - if run_id not in self.spans: - return - - if run_id in self.skipped_runs: - self.skipped_runs.discard(run_id) - return - - span = self.spans.pop(run_id) - - if self.root_run_id == run_id: - self.root_run_id = None - - span.log( - input=input, - output=output, - expected=expected, - error=error, - tags=None, - scores=scores, - metadata={ - **({"tags": tags} if tags else {}), - **(metadata or {}), - }, - metrics=metrics, - dataset_record_id=dataset_record_id, - ) - - # In async workflows, callbacks may execute in different async contexts. - # The span's context variable token may have been created in a different - # context, causing ValueError when trying to reset it. We catch and ignore - # this specific error since the span hierarchy is maintained via self.spans. - try: - span.unset_current() - except ValueError as e: - if "was created in a different Context" in str(e): - pass - else: - raise - - span.end() - - def on_llm_error( - self, - error: BaseException, - *, - run_id: UUID, - parent_run_id: UUID | None = None, - **kwargs: Any, # TODO: response= - ) -> Any: - self._end_span(run_id, error=str(error), metadata={**kwargs}) - - self._start_times.pop(run_id, None) - self._first_token_times.pop(run_id, None) - self._ttft_ms.pop(run_id, None) - - def on_chain_error( - self, - error: BaseException, - *, - run_id: UUID, - parent_run_id: UUID | None = None, - **kwargs: Any, # TODO: some metadata - ) -> Any: - self._end_span(run_id, error=str(error), metadata={**kwargs}) - - def on_tool_error( - self, - error: BaseException, - *, - run_id: UUID, - parent_run_id: UUID | None = None, - **kwargs: Any, - ) -> Any: - self._end_span(run_id, error=str(error), metadata={**kwargs}) - - def on_retriever_error( - self, - error: BaseException, - *, - run_id: UUID, - parent_run_id: UUID | None = None, - **kwargs: Any, - ) -> Any: - self._end_span(run_id, error=str(error), metadata={**kwargs}) - - # Agent Methods - def on_agent_action( - self, - action: AgentAction, - *, - run_id: UUID, - parent_run_id: UUID | None = None, - **kwargs: Any, - ) -> Any: - self._start_span( - parent_run_id, - run_id, - type=SpanTypeAttribute.LLM, - name=action.tool, - event={"input": action, "metadata": {**kwargs}}, - ) - - def on_agent_finish( - self, - finish: AgentFinish, - *, - run_id: UUID, - parent_run_id: UUID | None = None, - **kwargs: Any, - ) -> Any: - self._end_span(run_id, output=finish, metadata={**kwargs}) - - def on_chain_start( - self, - serialized: dict[str, Any], - inputs: dict[str, Any], - *, - run_id: UUID, - parent_run_id: UUID | None = None, - tags: list[str] | None = None, - name: str | None = None, - metadata: dict[str, Any] | None = None, - **kwargs: Any, - ) -> Any: - tags = tags or [] - - # avoids extra logs that seem not as useful esp. with langgraph - if "langsmith:hidden" in tags: - self.skipped_runs.add(run_id) - return - - metadata = metadata or {} - resolved_name = ( - name - or metadata.get("langgraph_node") - or serialized.get("name") - or last_item(serialized.get("id") or []) - or "Chain" - ) - - self._start_span( - parent_run_id, - run_id, - name=resolved_name, - event={ - "input": inputs, - "tags": tags, - "metadata": { - "serialized": serialized, - "name": name, - "metadata": metadata, - **kwargs, - }, - }, - ) - - def on_chain_end( - self, - outputs: dict[str, Any], - *, - run_id: UUID, - parent_run_id: UUID | None = None, - tags: list[str] | None = None, - **kwargs: Any, - ) -> Any: - self._end_span(run_id, output=outputs, tags=tags, metadata={**kwargs}) - - def on_llm_start( - self, - serialized: dict[str, Any], - prompts: list[str], - *, - run_id: UUID, - parent_run_id: UUID | None = None, - tags: list[str] | None = None, - metadata: dict[str, Any] | None = None, - name: str | None = None, - **kwargs: Any, - ) -> Any: - self._start_times[run_id] = time.perf_counter() - self._first_token_times.pop(run_id, None) - self._ttft_ms.pop(run_id, None) - - name = name or serialized.get("name") or last_item(serialized.get("id") or []) or "LLM" - self._start_span( - parent_run_id, - run_id, - name=name, - type=SpanTypeAttribute.LLM, - event={ - "input": prompts, - "tags": tags, - "metadata": { - "serialized": serialized, - "name": name, - "metadata": metadata, - **kwargs, - }, - }, - ) - - def on_chat_model_start( - self, - serialized: dict[str, Any], - messages: list[list["BaseMessage"]], - *, - run_id: UUID, - parent_run_id: UUID | None = None, - tags: list[str] | None = None, - metadata: dict[str, Any] | None = None, - name: str | None = None, - invocation_params: dict[str, Any] | None = None, - **kwargs: Any, - ) -> Any: - self._start_times[run_id] = time.perf_counter() - self._first_token_times.pop(run_id, None) - self._ttft_ms.pop(run_id, None) - - invocation_params = invocation_params or {} - self._start_span( - parent_run_id, - run_id, - name=name or serialized.get("name") or last_item(serialized.get("id") or []) or "Chat Model", - type=SpanTypeAttribute.LLM, - event={ - "input": messages, - "tags": tags, - "metadata": ( - { - "serialized": serialized, - "invocation_params": invocation_params, - "metadata": metadata or {}, - "name": name, - **kwargs, - } - ), - }, - ) - - def on_llm_end( - self, - response: LLMResult, - *, - run_id: UUID, - parent_run_id: UUID | None = None, - tags: list[str] | None = None, - **kwargs: Any, - ) -> Any: - if run_id not in self.spans: - return - - metrics = _get_metrics_from_response(response) - - ttft = self._ttft_ms.pop(run_id, None) - if ttft is not None: - metrics["time_to_first_token"] = ttft - - model_name = _get_model_name_from_response(response) - - self._start_times.pop(run_id, None) - self._first_token_times.pop(run_id, None) - - self._end_span( - run_id, - output=response, - metrics=metrics, - tags=tags, - metadata={ - "model": model_name, - **kwargs, - }, - ) - - def on_tool_start( - self, - serialized: dict[str, Any], - input_str: str, - *, - run_id: UUID, - parent_run_id: UUID | None = None, - tags: list[str] | None = None, - metadata: dict[str, Any] | None = None, - inputs: dict[str, Any] | None = None, - name: str | None = None, - **kwargs: Any, - ) -> Any: - self._start_span( - parent_run_id, - run_id, - name=name or serialized.get("name") or last_item(serialized.get("id") or []) or "Tool", - type=SpanTypeAttribute.TOOL, - event={ - "input": inputs or safe_parse_serialized_json(input_str), - "tags": tags, - "metadata": { - "metadata": metadata, - "serialized": serialized, - "input_str": input_str, - "input": safe_parse_serialized_json(input_str), - "inputs": inputs, - "name": name, - **kwargs, - }, - }, - ) - - def on_tool_end( - self, - output: Any, - *, - run_id: UUID, - parent_run_id: UUID | None = None, - **kwargs: Any, - ) -> Any: - self._end_span(run_id, output=output, metadata={**kwargs}) - - def on_retriever_start( - self, - serialized: dict[str, Any], - query: str, - *, - run_id: UUID, - parent_run_id: UUID | None = None, - tags: list[str] | None = None, - metadata: dict[str, Any] | None = None, - name: str | None = None, - **kwargs: Any, - ) -> Any: - self._start_span( - parent_run_id, - run_id, - name=name or serialized.get("name") or last_item(serialized.get("id") or []) or "Retriever", - type=SpanTypeAttribute.FUNCTION, - event={ - "input": query, - "tags": tags, - "metadata": { - "serialized": serialized, - "metadata": metadata, - "name": name, - **kwargs, - }, - }, - ) - - def on_retriever_end( - self, - documents: Sequence[Document], - *, - run_id: UUID, - parent_run_id: UUID | None = None, - **kwargs: Any, - ) -> Any: - self._end_span(run_id, output=documents, metadata={**kwargs}) - - def on_llm_new_token( - self, - token: str, - *, - chunk: Union["GenerationChunk", "ChatGenerationChunk"] | None = None, # type: ignore - run_id: UUID, - parent_run_id: UUID | None = None, - **kwargs: Any, - ) -> Any: - if run_id not in self._first_token_times: - now = time.perf_counter() - self._first_token_times[run_id] = now - start = self._start_times.get(run_id) - if start is not None: - self._ttft_ms[run_id] = now - start - - def on_text( - self, - text: str, - *, - run_id: UUID, - parent_run_id: UUID | None = None, - **kwargs: Any, - ) -> Any: - pass - - def on_retry( - self, - retry_state: RetryCallState, - *, - run_id: UUID, - parent_run_id: UUID | None = None, - **kwargs: Any, - ) -> Any: - pass - - def on_custom_event( - self, - name: str, - data: Any, - *, - run_id: UUID, - tags: list[str] | None = None, - metadata: dict[str, Any] | None = None, - **kwargs: Any, - ) -> Any: - pass - - -def clean_object(obj: dict[str, Any]) -> dict[str, Any]: - return { - k: v - for k, v in obj.items() - if v is not None and not (isinstance(v, list) and not v) and not (isinstance(v, dict) and not v) - } - - -def safe_parse_serialized_json(input_str: str) -> Any: - try: - return json.loads(input_str) - except: - return input_str - - -def last_item(items: list[Any]) -> Any: - return items[-1] if items else None - - -def _walk_generations(response: LLMResult): - for generations in response.generations or []: - yield from generations or [] - - -def _get_model_name_from_response(response: LLMResult) -> str | None: - model_name = None - for generation in _walk_generations(response): - message = getattr(generation, "message", None) - if not message: - continue - - response_metadata = getattr(message, "response_metadata", None) - if response_metadata and isinstance(response_metadata, dict): - model_name = response_metadata.get("model_name") - - if model_name: - break - - if not model_name: - llm_output: dict[str, Any] = response.llm_output or {} - model_name = llm_output.get("model_name") or llm_output.get("model") or "" - - return model_name - - -def _get_metrics_from_response(response: LLMResult): - metrics = {} - - for generation in _walk_generations(response): - message = getattr(generation, "message", None) - if not message: - continue - - usage_metadata = getattr(message, "usage_metadata", None) - - if usage_metadata and isinstance(usage_metadata, dict): - metrics.update( - clean_object( - { - "total_tokens": usage_metadata.get("total_tokens"), - "prompt_tokens": usage_metadata.get("input_tokens"), - "completion_tokens": usage_metadata.get("output_tokens"), - } - ) - ) - - # Extract cache tokens from nested input_token_details (LangChain format) - # Maps to Braintrust's standard cache token metric names - input_token_details = usage_metadata.get("input_token_details") - if input_token_details and isinstance(input_token_details, dict): - cache_read = input_token_details.get("cache_read") - cache_creation = input_token_details.get("cache_creation") - - if cache_read is not None: - metrics["prompt_cached_tokens"] = cache_read - if cache_creation is not None: - metrics["prompt_cache_creation_tokens"] = cache_creation - - if not metrics or not any(metrics.values()): - llm_output: dict[str, Any] = response.llm_output or {} - metrics = llm_output.get("token_usage") or llm_output.get("estimatedTokens") or {} - - return clean_object(metrics) diff --git a/integrations/langchain-py/src/braintrust_langchain/context.py b/integrations/langchain-py/src/braintrust_langchain/context.py deleted file mode 100644 index 0c997de0e..000000000 --- a/integrations/langchain-py/src/braintrust_langchain/context.py +++ /dev/null @@ -1,27 +0,0 @@ -from contextvars import ContextVar -from typing import Optional - -from langchain_core.tracers.context import register_configure_hook - -from braintrust_langchain.callbacks import BraintrustCallbackHandler - -__all__ = ["set_global_handler", "clear_global_handler"] - - -braintrust_callback_handler_var: ContextVar[BraintrustCallbackHandler | None] = ContextVar( - "braintrust_callback_handler", default=None -) - - -def set_global_handler(handler: BraintrustCallbackHandler): - braintrust_callback_handler_var.set(handler) - - -def clear_global_handler(): - braintrust_callback_handler_var.set(None) - - -register_configure_hook( - context_var=braintrust_callback_handler_var, - inheritable=True, -) diff --git a/integrations/langchain-py/src/braintrust_langchain/version.py b/integrations/langchain-py/src/braintrust_langchain/version.py deleted file mode 100644 index 7ff1e9ced..000000000 --- a/integrations/langchain-py/src/braintrust_langchain/version.py +++ /dev/null @@ -1,17 +0,0 @@ -try: - from importlib.metadata import PackageNotFoundError, version -except ImportError: - # Python < 3.8 compatibility - from importlib_metadata import PackageNotFoundError, version # type: ignore - -try: - __version__ = version("braintrust-langchain") -except PackageNotFoundError: - # Package is not installed (e.g., during development) - # Fallback to a dev version - __version__ = "0.0.0.dev0" - -version = __version__ - -# This will be templated during the build if needed -GIT_COMMIT = "__GIT_COMMIT__" diff --git a/integrations/langchain-py/src/tests/__init__.py b/integrations/langchain-py/src/tests/__init__.py deleted file mode 100644 index 46816ddf5..000000000 --- a/integrations/langchain-py/src/tests/__init__.py +++ /dev/null @@ -1 +0,0 @@ -"""Tests package.""" diff --git a/integrations/langchain-py/src/tests/cassettes/test_async_langchain_invoke b/integrations/langchain-py/src/tests/cassettes/test_async_langchain_invoke deleted file mode 100644 index 3ecc362e9..000000000 --- a/integrations/langchain-py/src/tests/cassettes/test_async_langchain_invoke +++ /dev/null @@ -1,276 +0,0 @@ -interactions: -- request: - body: '{"max_tokens": 1024, "messages": [{"role": "user", "content": "What is - 1 + 2?"}], "model": "claude-sonnet-4-20250514"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - anthropic-version: - - '2023-06-01' - connection: - - keep-alive - content-length: - - '110' - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - AsyncAnthropic/Python 0.68.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.68.0 - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.13 - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//dJBfSwMxEMS/yjGvpnB3bUUCvhR88aEg/gERCTFZ2uDd5kw2Ui333eWK - Rar4tLC/mWGYPYKHRp83pm4ublf5+uWT0/DYP9ysr+7XOx/uoCAfA00qytluCAopdtPD5hyyWBYo - 9NFTBw3X2eJpliMzyWwxa+t2WS+bBRRcZCEW6Kf9MVJoN5kPR6Opzqq2uqzmGJ8VssTBJLI5MjSI - vZGSGN8g01shdgTNpesUyqGa3iPwUMRIfCXO0M25grNuS8YlshIim1NBfeSJrP+PHb1TPg1b6inZ - ziz7v/of2mx/01EhFjlpN1fIlN6DIyOBEjSmPb1NHuP4BQAA//8DABaJlhKdAQAA - headers: - CF-RAY: - - 983cc1f7fda07e2d-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Tue, 23 Sep 2025 20:23:04 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 02af79b5-9b1a-4100-a05f-9235eb38bda4 - cf-cache-status: - - DYNAMIC - request-id: - - req_011CTRxS1WS9ia9upALgfUZK - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - x-envoy-upstream-service-time: - - '1030' - status: - code: 200 - message: OK -- request: - body: '{"max_tokens":1024,"messages":[{"role":"user","content":"What is 1 + 2?"}],"model":"claude-sonnet-4-20250514"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - anthropic-version: - - '2023-06-01' - connection: - - keep-alive - content-length: - - '110' - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - AsyncAnthropic/Python 0.68.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.68.0 - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//dJDdSgMxEEZfZfluTWG37YoGvLagN0VBRCSEZGhDdydrMimWsu8uWyxS - xauBOWd++I7oo6cOGq6zxdMsR2aS2XI2r+dt3TZLKAQPjT5vTN08397v1qG5WT+Ep/Z19bJfySMf - oCCHgSaLcrYbgkKK3dSwOYcslgUKLrIQC/Tb8ewLfU7kVDSa6qqaV3fVAuO7QpY4mEQ2R4YGsTdS - EuMbZPooxI6guXSdQjnd1UcEHooYiTviDN1cKzjrtmRcIishsrkU6jNPZP1/7Dw77adhSz0l25m2 - /+v/0Gb7m44KscjFdwuFTGkfHBkJlKAxheVt8hjHLwAAAP//AwBHCKHFnQEAAA== - headers: - CF-RAY: - - 99b0eabe4896b976-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 08 Nov 2025 00:22:38 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - '3000000' - anthropic-ratelimit-input-tokens-remaining: - - '3000000' - anthropic-ratelimit-input-tokens-reset: - - '2025-11-08T00:22:38Z' - anthropic-ratelimit-output-tokens-limit: - - '600000' - anthropic-ratelimit-output-tokens-remaining: - - '600000' - anthropic-ratelimit-output-tokens-reset: - - '2025-11-08T00:22:38Z' - anthropic-ratelimit-tokens-limit: - - '3600000' - anthropic-ratelimit-tokens-remaining: - - '3600000' - anthropic-ratelimit-tokens-reset: - - '2025-11-08T00:22:38Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CUuU6hWk8Jg8Bh2c4Vyty - retry-after: - - '23' - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - '1801' - status: - code: 200 - message: OK -- request: - body: '{"max_tokens":1024,"messages":[{"role":"user","content":"What is 1 + 2?"}],"model":"claude-sonnet-4-20250514"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - anthropic-version: - - '2023-06-01' - connection: - - keep-alive - content-length: - - '110' - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - AsyncAnthropic/Python 0.68.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.68.0 - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAAA3SQTUvDQBCG/0p4r24gaRvRBQ9CDyJ4rBeRZbs7tNFkNu7OBkvJf5cUi1TxNDDP - Mx+8R/TBUwcN19nsqUyBmaRclYtq0VRNvYJC66HRp52p6qd1/7DZ3o8yjIe355v1o9tsm1soyGGg - 2aKU7I6gEEM3N2xKbRLLAgUXWIgF+uV49oU+Z3IqGnVxVSyKu2KJ6VUhSRhMJJsCQ4PYG8mR8Q0S - fWRiR9Ccu04hn+7qI1oeshgJ78QJur5WcNbtybhIVtrA5lKozjyS9f+x8+y8n4Y99RRtZ5r+r/9D - 6/1vOimELBffLRUSxbF1ZKSlCI05LG+jxzR9AQAA//8DAEp7u9udAQAA - headers: - CF-RAY: - - 99b0ebedd90d6897-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 08 Nov 2025 00:23:27 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - '3000000' - anthropic-ratelimit-input-tokens-remaining: - - '3000000' - anthropic-ratelimit-input-tokens-reset: - - '2025-11-08T00:23:26Z' - anthropic-ratelimit-output-tokens-limit: - - '600000' - anthropic-ratelimit-output-tokens-remaining: - - '600000' - anthropic-ratelimit-output-tokens-reset: - - '2025-11-08T00:23:26Z' - anthropic-ratelimit-tokens-limit: - - '3600000' - anthropic-ratelimit-tokens-remaining: - - '3600000' - anthropic-ratelimit-tokens-reset: - - '2025-11-08T00:23:26Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CUuUAHB8QqxGoW7TZyUaz - retry-after: - - '34' - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - '1851' - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/langchain-py/src/tests/cassettes/test_chain_with_memory b/integrations/langchain-py/src/tests/cassettes/test_chain_with_memory deleted file mode 100644 index 88cc88485..000000000 --- a/integrations/langchain-py/src/tests/cassettes/test_chain_with_memory +++ /dev/null @@ -1,332 +0,0 @@ -interactions: -- request: - body: '{"messages": [{"content": "Assistant: Hello! How can I assist you today? - User: What''s your name?", "role": "user"}], "model": "gpt-4o-mini", "stream": - false}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '149' - content-type: - - application/json - host: - - localhost:8000 - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.13 - method: POST - uri: http://localhost:8000/v1/proxy/chat/completions - response: - body: - string: "{\n \"id\": \"chatcmpl-CJ3pSTx8NVvtJFY51xvv7gmxKCqAO\",\n \"object\": - \"chat.completion\",\n \"created\": 1758658986,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n - \ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": - \"assistant\",\n \"content\": \"Assistant: I don't have a personal - name, but you can call me Assistant. How can I help you today?\",\n \"refusal\": - null,\n \"annotations\": []\n },\n \"logprobs\": null,\n - \ \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": - 24,\n \"completion_tokens\": 23,\n \"total_tokens\": 47,\n \"prompt_tokens_details\": - {\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": - {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": - 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": - \"default\",\n \"system_fingerprint\": \"fp_560af6e559\"\n}\n" - headers: - Access-Control-Allow-Credentials: - - 'true' - Access-Control-Expose-Headers: - - x-bt-cursor,x-bt-found-existing,x-bt-span-id,x-bt-span-export,x-bt-query-plan,x-bt-internal-trace-id - Connection: - - keep-alive - Date: - - Tue, 23 Sep 2025 20:23:06 GMT - Keep-Alive: - - timeout=5 - Transfer-Encoding: - - chunked - Vary: - - Origin - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - cf-ray: - - 983cc206fc1f67ef-SJC - content-type: - - application/json - openai-organization: - - braintrust-data - openai-processing-ms: - - '755' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - set-cookie: - - _cfuvid=TIArUY3FKYo9t2vz5lADo0yFHggpjc9nkMoRBVQYfbA-1758658986949-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-bt-cached: - - MISS - x-bt-internal-trace-id: - - 899e875d60ba290b68341d027600a8fd - x-content-type-options: - - nosniff - x-envoy-upstream-service-time: - - '775' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999980' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_3b64f4bb78c14e2ea80001681e34611d - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"content":"Assistant: Hello! How can I assist you today? - User: What''s your name?","role":"user"}],"model":"gpt-4o-mini","stream":false}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '149' - content-type: - - application/json - cookie: - - __cf_bm=W_Ukgb.mz8e1GW7CfhzN.QQaN09_xQq1uTHm3a.dJdU-1762561359-1.0.1.1-6IrkySxpZaL.1C65iH0iOLFfere0JxHCiasT6bak.RihYFMyJgIz2OuYJqcUey8c5vicjtorNby_Z_GJX.ZMIHa6PyzVrhqgfZZmtnnn.sA; - _cfuvid=jwWMA4k30hLPwBwTSCIdIeS5.m1TkcdYLYTt4YSTZhI-1762561359243-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA4ySTW/bMAyG7/4VhC67xEW+s+YyFAO2ZNhp22HYUBiMRNvaZFGT5KRBkf8+2E5i - d22BXXTgw5fiS/IxARBaiTUIWWKUlTPp+x9fxg/u4yFuv20O9ezD98/7YvPn01fFxeFOjBoF736R - jBfVjeTKGYqabYelJ4zUVJ2sltPFcjJb3LagYkWmkRUupnNOK211Oh1P5+l4lU7entUla0lBrOFn - AgDw2L5Nn1bRg1jDeHSJVBQCFiTW1yQA4dk0EYEh6BDRRjHqoWQbybat3134Grag2L6JUOKeAMGR - D2zRgMWKRrCrIxy5BokWJBoDFcFVfAMbPrRoCyUZ12ZGVnh8N/zXU14HbLzb2pgBQGs5YjO71vH9 - mZyuHg0XzvMu/CMVubY6lJknDGwbPyGyEy09JQD37SzrJ+MRznPlYhb5N7XfTeddOdFvcABnZxg5 - ounj89XohWqZoojahMEuhERZkuqV/eKwVpoHIBl4ft7MS7U739oW/1O+B1KSi6Qy50lp+dRwn+ap - ue/X0q4zbhsWgfxeS8qiJt/sQVGOtemuToRjiFRlubYFeed1d3q5yxbLMeZLWixuRXJK/gIAAP// - AwCouO6tiAMAAA== - headers: - CF-RAY: - - 99b0eacf8822aaac-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 08 Nov 2025 00:22:39 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '628' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '639' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999980' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_1009d84201314e5aa9ccdcbafeeac4af - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"content":"Assistant: Hello! How can I assist you today? - User: What''s your name?","role":"user"}],"model":"gpt-4o-mini","stream":false}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '149' - content-type: - - application/json - cookie: - - __cf_bm=.AxQfRhAvElThVl_Qz9zUVdqz_GtBGXwRQ0TVPIg5pc-1762561407-1.0.1.1-klsoMaFKHjzxOrHy2Zfd8Sc76RDHsMXURLAaIzORncnm47NI1MY0BqqBGOEsVXlZb.RdqeqpxzGFhl8DlRDjy.SqRfa2B4zEYdKZqQ2kVB0; - _cfuvid=0ohSoYMS21h1NkHWl4FeeVCp5aK2KHeEjclSm1NY7yY-1762561407934-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJLBbtswDIbvfgpO53hIgiRNcxmKAcN6GNbuMmBDYTASHauRRU2imwRF - gb3GXm9PUthp4nTLgF104Mef4k/yMQNQ1qgFKF2h6Dq4/P23L6P18vJm8+Pz1e16m8pPH25u7fbe - fJ1vlmrQKnh5T1oOqrea6+BILPs91pFQqK06upiNp7PRZDjvQM2GXCtbBcknnNfW23w8HE/y4UU+ - mr+oK7aaklrA9wwA4LF72z69oa1awHBwiNSUEq5ILY5JACqyayMKU7JJ0Isa9FCzF/Jd61cHvoBr - MOx///wlUOEDAUIKpG1pNXisaQDLRmDHDWj0oNE5qAmO8jfwkTcduoaKXOgyhQ3u3p3+HKlsErbu - fePcCUDvWbCdXuf57oU8HV06XoXIy/SHVJXW21QVkTCxbx0l4aA6+pQB3HXTbF4NSIXIdZBCeE3d - d+PJvpzqd3gGCgu6Pj6ZD85UKwwJWpdOtqE06opMr+xXh42xfAKyE89/N3Ou9t639av/Kd8DrSkI - mSJEMla/NtynRWov/F9pxxl3DatE8cFqKsRSbPdgqMTG7e9OpV0SqovS+hXFEO3++MpQTGdDLGc0 - nV6q7Cl7BgAA//8DAEMiDgGKAwAA - headers: - CF-RAY: - - 99b0ebffc94fed3b-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 08 Nov 2025 00:23:28 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '680' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '708' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999980' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_e273cb6eb8624df78282659b4a19fffe - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/langchain-py/src/tests/cassettes/test_global_handler b/integrations/langchain-py/src/tests/cassettes/test_global_handler deleted file mode 100644 index ba9f4fa9c..000000000 --- a/integrations/langchain-py/src/tests/cassettes/test_global_handler +++ /dev/null @@ -1,225 +0,0 @@ -interactions: -- request: - body: '{"messages": [{"content": "What is 1 + 2?", "role": "user"}], "model": - "gpt-4o-mini", "frequency_penalty": 0.0, "n": 1, "presence_penalty": 0.0, "stream": - false, "temperature": 1.0, "top_p": 1.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '177' - content-type: - - application/json - host: - - localhost:8000 - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.13 - method: POST - uri: http://localhost:8000/v1/proxy/chat/completions - response: - body: - string: "{\n \"id\": \"chatcmpl-CJ44VUVp2sk1koSWXX64CaLEy1mWy\",\n \"object\": - \"chat.completion\",\n \"created\": 1758659919,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n - \ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": - \"assistant\",\n \"content\": \"1 + 2 equals 3.\",\n \"refusal\": - null,\n \"annotations\": []\n },\n \"logprobs\": null,\n - \ \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": - 15,\n \"completion_tokens\": 8,\n \"total_tokens\": 23,\n \"prompt_tokens_details\": - {\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": - {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": - 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": - \"default\",\n \"system_fingerprint\": \"fp_560af6e559\"\n}\n" - headers: - Access-Control-Allow-Credentials: - - 'true' - Access-Control-Expose-Headers: - - x-bt-cursor,x-bt-found-existing,x-bt-span-id,x-bt-span-export,x-bt-query-plan,x-bt-internal-trace-id - Connection: - - keep-alive - Date: - - Tue, 23 Sep 2025 20:38:40 GMT - Keep-Alive: - - timeout=5 - Transfer-Encoding: - - chunked - Vary: - - Origin - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - cf-ray: - - 983cd8d01c33943a-SJC - content-type: - - application/json - openai-organization: - - braintrust-data - openai-processing-ms: - - '930' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - set-cookie: - - _cfuvid=XPwF0fhMV9JwjYuWwUMNbzPKxvSJ.HOkXEftYzjXRew-1758659920459-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-bt-cached: - - MISS - x-bt-internal-trace-id: - - 93acad0503781eb98ab6ea3412173537 - x-content-type-options: - - nosniff - x-envoy-upstream-service-time: - - '1026' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_181413148bbe4814a905514521d6dc34 - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"content":"What is 1 + 2?","role":"user"}],"model":"gpt-4o-mini","frequency_penalty":0.0,"n":1,"presence_penalty":0.0,"stream":false,"temperature":1.0,"top_p":1.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '177' - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJBb9swDIXv/hUCr4uL2IlTJ9et2y2HHQZ0Q2EoMm1rk0VNoocNRf77 - IDuN3a0FevGBHx/1Hs3HRAjQNRwEqE6y6p1J33/9XH7adscPRXGXnTb7+49fNse7/b2iYylhFRV0 - +o6Kn1Q3inpnkDXZCSuPkjFOzW53ebHLyiwfQU81mihrHadbSnttdZqv8226vk2z8qLuSCsMcBDf - EiGEeBy/0aet8TccxHr1VOkxBNkiHK5NQoAnEysgQ9CBpWVYzVCRZbSj9Uy8E7nAn4M0QWxull0e - myHI6NQOxiyAtJZYxqSjv4cLOV8dGWqdp1P4RwqNtjp0lUcZyMbXA5ODkZ4TIR7G5MOzMOA89Y4r - ph84PpcV0ziY9z3D8sKYWJq5nG9WLwyramSpTVgsDpRUHdazct6yHGpNC5AsIv/v5aXZU2xt27eM - n4FS6BjrynmstXqed27zGI/xtbbrikfDEND/0gor1ujjb6ixkYOZTgTCn8DYV422LXrn9XQnjauK - 3Vo2OyyKPSTn5C8AAAD//wMAcIbFgjUDAAA= - headers: - CF-RAY: - - 99b0f5db9f1cbffc-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 08 Nov 2025 00:30:12 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=vfpKl6dvzcujjwigai_kp7UkNhR2ltT1SwFsT05VrS8-1762561812-1.0.1.1-UAyuy134RWxRUzjbClH59IJarw95du8Dl347lkXcDkbXBBx7vCmRuxRccJQB2f1T6oobZSgBj7O8hdaLY4hef6ypZ2uHUshy880EnptiWEY; - path=/; expires=Sat, 08-Nov-25 01:00:12 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=N6FAUGU_qhcPvlVWdt0kvrpbt1SzTvQ0v29fL2QCNbA-1762561812358-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '319' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '489' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_3e940a310adf4d9a88c8da6b70645bb7 - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/langchain-py/src/tests/cassettes/test_langchain_anthropic_integration b/integrations/langchain-py/src/tests/cassettes/test_langchain_anthropic_integration deleted file mode 100644 index 6c396d025..000000000 --- a/integrations/langchain-py/src/tests/cassettes/test_langchain_anthropic_integration +++ /dev/null @@ -1,300 +0,0 @@ -interactions: -- request: - body: '{"max_tokens": 1024, "messages": [{"role": "user", "content": "What is - 1 + 2?"}], "model": "claude-sonnet-4-20250514"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - anthropic-version: - - '2023-06-01' - connection: - - keep-alive - content-length: - - '110' - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.68.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.68.0 - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.13 - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//dJBRSwMxEIT/yjGvpnDX9hQDvggegn9AEAkxWdvg3eZMNsVa7r/LFYtU - 8Wlhv5lhmAOCh8aQN6Zu7nZX3IXr+8/X9cNt213vu5fucYSC7EeaVZSz3RAUUuznh805ZLEsUBii - px4arrfF0yJHZpLFerGsl23dNmsouMhCLNBPh1Ok0MdsPh6NprqoltVNtcL0rJAljiaRzZGhQeyN - lMT4BpneC7EjaC59r1CO1fQBgcciRuIbcYZuLhWcdVsyLpGVENmcC+oTT2T9f+zknfNp3NJAyfam - Hf7qf2iz/U0nhVjkrN1KIVPaBUdGAiVozHt6mzym6QsAAP//AwD8n6CUnQEAAA== - headers: - CF-RAY: - - 983cc09c5f361679-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Tue, 23 Sep 2025 20:22:09 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 02af79b5-9b1a-4100-a05f-9235eb38bda4 - anthropic-ratelimit-input-tokens-limit: - - '30000' - anthropic-ratelimit-input-tokens-remaining: - - '30000' - anthropic-ratelimit-input-tokens-reset: - - '2025-09-23T20:22:09Z' - anthropic-ratelimit-output-tokens-limit: - - '8000' - anthropic-ratelimit-output-tokens-remaining: - - '8000' - anthropic-ratelimit-output-tokens-reset: - - '2025-09-23T20:22:09Z' - anthropic-ratelimit-requests-limit: - - '50' - anthropic-ratelimit-requests-remaining: - - '49' - anthropic-ratelimit-requests-reset: - - '2025-09-23T20:22:09Z' - anthropic-ratelimit-tokens-limit: - - '38000' - anthropic-ratelimit-tokens-remaining: - - '38000' - anthropic-ratelimit-tokens-reset: - - '2025-09-23T20:22:09Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CTRxMui53W9h6eXYGxUJb - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - x-envoy-upstream-service-time: - - '1110' - status: - code: 200 - message: OK -- request: - body: '{"max_tokens":1024,"messages":[{"role":"user","content":"What is 1 + 2?"}],"model":"claude-sonnet-4-20250514"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - anthropic-version: - - '2023-06-01' - connection: - - keep-alive - content-length: - - '110' - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.68.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.68.0 - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//dJDLasMwEEV/xdxtFfAjCa2g29JVoetShJCmsRt75Eij9BH878WhpqSl - q4E5Zx7cE4bgqYeG6232tEqBmWS1XtVlvSk31RoKnYfGkHamrB5z87bPfPfwGa+Ph9f7401wL1so - yMdIs0Up2R1BIYZ+btiUuiSWBQousBAL9NNp8YXeZ3IuGlVxVdTFbdFgelZIEkYTyabA0CD2RnJk - fINEh0zsCJpz3yvk8119QsdjFiNhT5ygq62Cs64l4yJZ6QKbS6FceCTr/2PL7LyfxpYGirY3m+Gv - /0Or9jedFEKWi+8ahUTx2Dky0lGExhyWt9Fjmr4AAAD//wMARZkZqp0BAAA= - headers: - CF-RAY: - - 99b0eab2783f1758-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 08 Nov 2025 00:22:36 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - '3000000' - anthropic-ratelimit-input-tokens-remaining: - - '3000000' - anthropic-ratelimit-input-tokens-reset: - - '2025-11-08T00:22:36Z' - anthropic-ratelimit-output-tokens-limit: - - '600000' - anthropic-ratelimit-output-tokens-remaining: - - '600000' - anthropic-ratelimit-output-tokens-reset: - - '2025-11-08T00:22:36Z' - anthropic-ratelimit-tokens-limit: - - '3600000' - anthropic-ratelimit-tokens-remaining: - - '3600000' - anthropic-ratelimit-tokens-reset: - - '2025-11-08T00:22:36Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CUuU6ZRKcH4CRrH5o4j6b - retry-after: - - '24' - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - '1694' - status: - code: 200 - message: OK -- request: - body: '{"max_tokens":1024,"messages":[{"role":"user","content":"What is 1 + 2?"}],"model":"claude-sonnet-4-20250514"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - anthropic-version: - - '2023-06-01' - connection: - - keep-alive - content-length: - - '110' - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.68.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.68.0 - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//dJBNS8QwEIb/SnmvptDudhUCHvQkC4oieBEJIRl3y7aTmkz8Kv3v0sVF - VvE0MM8zH7wj+uCpg4brbPZUpsBMUjblolqsqlXdQKH10OjTxlT1fXPxcHXzubwOZ2vKb7fPu7vL - 9Q4K8jHQbFFKdkNQiKGbGzalNollgYILLMQC/TgefKH3meyLRl2cFIvivFhielJIEgYTyabA0CD2 - RnJkfINEL5nYETTnrlPI+7t6RMtDFiNhR5yg61MFZ92WjItkpQ1sjoXqwCNZ/x87zM77adhST9F2 - ZtX/9X9ovf1NJ4WQ5ei7pUKi+No6MtJShMYclrfRY5q+AAAA//8DAAqaanadAQAA - headers: - CF-RAY: - - 99b0ebe2db3d67ca-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 08 Nov 2025 00:23:24 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - '3000000' - anthropic-ratelimit-input-tokens-remaining: - - '3000000' - anthropic-ratelimit-input-tokens-reset: - - '2025-11-08T00:23:24Z' - anthropic-ratelimit-output-tokens-limit: - - '600000' - anthropic-ratelimit-output-tokens-remaining: - - '600000' - anthropic-ratelimit-output-tokens-reset: - - '2025-11-08T00:23:24Z' - anthropic-ratelimit-tokens-limit: - - '3600000' - anthropic-ratelimit-tokens-remaining: - - '3600000' - anthropic-ratelimit-tokens-reset: - - '2025-11-08T00:23:24Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CUuUA9cTfN1Yz5PMKHD5d - retry-after: - - '37' - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - '1556' - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/langchain-py/src/tests/cassettes/test_langgraph_state_management b/integrations/langchain-py/src/tests/cassettes/test_langgraph_state_management deleted file mode 100644 index 20ffc04b3..000000000 --- a/integrations/langchain-py/src/tests/cassettes/test_langgraph_state_management +++ /dev/null @@ -1,327 +0,0 @@ -interactions: -- request: - body: '{"messages": [{"content": "Say hello", "role": "user"}], "model": "gpt-4o-mini", - "frequency_penalty": 0.0, "n": 1, "presence_penalty": 0.0, "stream": false, - "temperature": 1.0, "top_p": 1.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '172' - content-type: - - application/json - host: - - localhost:8000 - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.13 - method: POST - uri: http://localhost:8000/v1/proxy/chat/completions - response: - body: - string: "{\n \"id\": \"chatcmpl-CJ3xSBjbTuwYXAmP3RRw0GoHz5Ooy\",\n \"object\": - \"chat.completion\",\n \"created\": 1758659482,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n - \ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": - \"assistant\",\n \"content\": \"Hello! How can I assist you today?\",\n - \ \"refusal\": null,\n \"annotations\": []\n },\n \"logprobs\": - null,\n \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": - 9,\n \"completion_tokens\": 9,\n \"total_tokens\": 18,\n \"prompt_tokens_details\": - {\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": - {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": - 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": - \"default\",\n \"system_fingerprint\": \"fp_51db84afab\"\n}\n" - headers: - Access-Control-Allow-Credentials: - - 'true' - Access-Control-Expose-Headers: - - x-bt-cursor,x-bt-found-existing,x-bt-span-id,x-bt-span-export,x-bt-query-plan,x-bt-internal-trace-id - Connection: - - keep-alive - Date: - - Tue, 23 Sep 2025 20:31:22 GMT - Keep-Alive: - - timeout=5 - Transfer-Encoding: - - chunked - Vary: - - Origin - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - cf-ray: - - 983cce247c46cf2f-SJC - content-type: - - application/json - openai-organization: - - braintrust-data - openai-processing-ms: - - '381' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - set-cookie: - - _cfuvid=Y9Om0gYdHB3h9aUHhUUY9eEia6Y3wmSARFX9Xq907Ho-1758659482810-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-bt-cached: - - MISS - x-bt-internal-trace-id: - - ebcf889942216eb0b613f43f2cdb11b1 - x-content-type-options: - - nosniff - x-envoy-upstream-service-time: - - '397' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_75709538073646e4bd7355c91bc2ce52 - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"content":"Say hello","role":"user"}],"model":"gpt-4o-mini","frequency_penalty":0.0,"n":1,"presence_penalty":0.0,"stream":false,"temperature":1.0,"top_p":1.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '172' - content-type: - - application/json - cookie: - - __cf_bm=W_Ukgb.mz8e1GW7CfhzN.QQaN09_xQq1uTHm3a.dJdU-1762561359-1.0.1.1-6IrkySxpZaL.1C65iH0iOLFfere0JxHCiasT6bak.RihYFMyJgIz2OuYJqcUey8c5vicjtorNby_Z_GJX.ZMIHa6PyzVrhqgfZZmtnnn.sA; - _cfuvid=jwWMA4k30hLPwBwTSCIdIeS5.m1TkcdYLYTt4YSTZhI-1762561359243-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA4xSwW7UMBC95ysGnzcoWbppu5eqqoSKgAu9oKIq8tqTrMHxGHuydKn235GTdpPS - InHxYd685/dm5iEDEEaLNQi1law6b/Or2y/F70p//Pz+UprNzf2uuO2uvrY/d9XN8pNYJAZtvqPi - J9ZbRZ23yIbcCKuAkjGplqfVclWV76pyADrSaBOt9ZyfUN4ZZ/JlsTzJi9O8PHtkb8kojGIN3zIA - gIfhTT6dxnuxhmLxVOkwRtmiWB+bAEQgmypCxmgiS8diMYGKHKMbrF+jtfQGrukXKOngA4wE2FMP - TFruL+bEgE0fZTLvemtngHSOWKbwg+W7R+RwNGmp9YE28S+qaIwzcVsHlJFcMhSZvBjQQwZwNwyj - f5ZP+ECd55rpBw7fnY9qYtrAS4yJpZ3K5dniFa1aI0tj42yUQkm1RT0xp7nLXhuaAdks8Usvr2mP - qY1r/0d+ApRCz6hrH1Ab9Tzv1BYwnee/2o4THgyLiGFnFNZsMKQtaGxkb8ejEXEfGbu6Ma7F4IMZ - L6fx9aoqZFPhanUuskP2BwAA//8DABw5ElFHAwAA - headers: - CF-RAY: - - 99b0eadaea14aaac-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 08 Nov 2025 00:22:41 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '328' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '342' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_68644fc1eb1a4533b2f98192dc918822 - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"content":"Say hello","role":"user"}],"model":"gpt-4o-mini","frequency_penalty":0.0,"n":1,"presence_penalty":0.0,"stream":false,"temperature":1.0,"top_p":1.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '172' - content-type: - - application/json - cookie: - - __cf_bm=.AxQfRhAvElThVl_Qz9zUVdqz_GtBGXwRQ0TVPIg5pc-1762561407-1.0.1.1-klsoMaFKHjzxOrHy2Zfd8Sc76RDHsMXURLAaIzORncnm47NI1MY0BqqBGOEsVXlZb.RdqeqpxzGFhl8DlRDjy.SqRfa2B4zEYdKZqQ2kVB0; - _cfuvid=0ohSoYMS21h1NkHWl4FeeVCp5aK2KHeEjclSm1NY7yY-1762561407934-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFLBbtswDL37Kzid48EOkrTJZYcd1g1osRVFDy0KQ5FoW5ssChK9LSjy - 74PsNnbXDthFBz6+p/dIPmYAwmixA6FayarzNv94d13am9ubQJf79nB5W9/Z609XV1+V/BK+iUVi - 0P47Kn5mvVfUeYtsyI2wCigZk2p5tlmuN+Wq2A5ARxptojWe8xXlnXEmXxbLVV6c5eX5E7slozCK - HdxnAACPw5t8Oo2/xQ6KxXOlwxhlg2J3agIQgWyqCBmjiSwdi8UEKnKMbrB+gdbSO7igX6Ckg88w - EuBAPTBpefgwJwas+yiTeddbOwOkc8QyhR8sPzwhx5NJS40PtI9/UUVtnIltFVBGcslQZPJiQI8Z - wMMwjP5FPuEDdZ4rph84fLcd1cS0gdcYE0s7lcvzxRtalUaWxsbZKIWSqkU9Mae5y14bmgHZLPFr - L29pj6mNa/5HfgKUQs+oKx9QG/Uy79QWMJ3nv9pOEx4Mi4jhp1FYscGQtqCxlr0dj0bEQ2Tsqtq4 - BoMPZryc2lfrTSHrDa7XW5Edsz8AAAD//wMAVD8AOUcDAAA= - headers: - CF-RAY: - - 99b0ec0acb26ed3b-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 08 Nov 2025 00:23:30 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '589' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '607' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_67359745154e404899e3fd81a37cf26a - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/langchain-py/src/tests/cassettes/test_llm_calls b/integrations/langchain-py/src/tests/cassettes/test_llm_calls deleted file mode 100644 index cea553488..000000000 --- a/integrations/langchain-py/src/tests/cassettes/test_llm_calls +++ /dev/null @@ -1,333 +0,0 @@ -interactions: -- request: - body: '{"messages": [{"content": "What is 1 + 2?", "role": "user"}], "model": - "gpt-4o-mini", "frequency_penalty": 0.0, "n": 1, "presence_penalty": 0.0, "stream": - false, "temperature": 1.0, "top_p": 1.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '177' - content-type: - - application/json - host: - - localhost:8000 - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.13 - method: POST - uri: http://localhost:8000/v1/proxy/chat/completions - response: - body: - string: "{\n \"id\": \"chatcmpl-CJ3pRI2shpJIGYKUU8RFWUyB6W5O1\",\n \"object\": - \"chat.completion\",\n \"created\": 1758658985,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n - \ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": - \"assistant\",\n \"content\": \"1 + 2 equals 3.\",\n \"refusal\": - null,\n \"annotations\": []\n },\n \"logprobs\": null,\n - \ \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": - 15,\n \"completion_tokens\": 8,\n \"total_tokens\": 23,\n \"prompt_tokens_details\": - {\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": - {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": - 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": - \"default\",\n \"system_fingerprint\": \"fp_560af6e559\"\n}\n" - headers: - Access-Control-Allow-Credentials: - - 'true' - Access-Control-Expose-Headers: - - x-bt-cursor,x-bt-found-existing,x-bt-span-id,x-bt-span-export,x-bt-query-plan,x-bt-internal-trace-id - Connection: - - keep-alive - Date: - - Tue, 23 Sep 2025 20:23:06 GMT - Keep-Alive: - - timeout=5 - Transfer-Encoding: - - chunked - Vary: - - Origin - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - cf-ray: - - 983cc2032f2967ef-SJC - content-type: - - application/json - openai-organization: - - braintrust-data - openai-processing-ms: - - '441' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - set-cookie: - - _cfuvid=uhF3qDlYXbYwV7mlgYhl_d7MyPH3FwQHxL6cek.ONAQ-1758658986041-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-bt-cached: - - MISS - x-bt-internal-trace-id: - - f4e0a5413e529acf383233e54ad00e99 - x-content-type-options: - - nosniff - x-envoy-upstream-service-time: - - '454' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_023ebefb1f6b4dec8910b8cb4d7421f5 - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"content":"What is 1 + 2?","role":"user"}],"model":"gpt-4o-mini","frequency_penalty":0.0,"n":1,"presence_penalty":0.0,"stream":false,"temperature":1.0,"top_p":1.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '177' - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJI/b9wwDMV3fwqBa8+B7Yudy61dunRJtxaBoZNon1JZVCQ6/RPcdy9k - X85OmgJdPPBHPr1H8zkTAoyGvQB1lKwGb/OPX++KH7eh6XcPvz8Psm++6O1d8+kRnw5+B5s0QYcH - VPwydaVo8BbZkJuxCigZk2p501R1U27r3QQG0mjTWO85v6Z8MM7kVVFd58VNXp7F1ZGMwgh78S0T - Qojn6Zt8Oo0/YS+KzUtlwBhlj7C/NAkBgWyqgIzRRJaOYbNARY7RTdZL8UFUAh9HaaPYXq27AnZj - lMmpG61dAekcsUxJJ3/3Z3K6OLLU+0CH+GYUOuNMPLYBZSSXXo9MHiZ6yoS4n5KPr8KADzR4bpm+ - 4/RcWc9ysOx7gbszY2Jpl3K13bwj1mpkaWxcLQ6UVEfUy+SyZTlqQyuQrSL/7eU97Tm2cf3/yC9A - KfSMuvUBtVGv8y5tAdMx/qvtsuLJMEQMT0ZhywZD+g0aOzna+UQg/oqMQ9sZ12Pwwcx30vm2bgrZ - NVjXt5Cdsj8AAAD//wMAbYrr4zUDAAA= - headers: - CF-RAY: - - 99b0eacc1d35aaac-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 08 Nov 2025 00:22:39 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=W_Ukgb.mz8e1GW7CfhzN.QQaN09_xQq1uTHm3a.dJdU-1762561359-1.0.1.1-6IrkySxpZaL.1C65iH0iOLFfere0JxHCiasT6bak.RihYFMyJgIz2OuYJqcUey8c5vicjtorNby_Z_GJX.ZMIHa6PyzVrhqgfZZmtnnn.sA; - path=/; expires=Sat, 08-Nov-25 00:52:39 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=jwWMA4k30hLPwBwTSCIdIeS5.m1TkcdYLYTt4YSTZhI-1762561359243-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '300' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '430' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_24854ba725b942179830d357f1af2add - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"content":"What is 1 + 2?","role":"user"}],"model":"gpt-4o-mini","frequency_penalty":0.0,"n":1,"presence_penalty":0.0,"stream":false,"temperature":1.0,"top_p":1.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '177' - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJBb9swDIXv/hUEr4sL242TLtdhu+wy7BRsKAxFoh2lsqRKdLGtyH8f - ZKexu3XALj7w46Peo/mcAaBWuAOUR8Gy9yb/8O1reeq+rJ/osdvvf32sDqftA3/+NFC33+MqKdzh - RJJfVDfS9d4Qa2cnLAMJpjS13G6qelOui+0IeqfIJFnnOV+7vNdW51VRrfNim5d3F/XRaUkRd/A9 - AwB4Hr/Jp1X0A3dQrF4qPcUoOsLdtQkAgzOpgiJGHVlYxtUMpbNMdrRewjuogB4HYSLc3iy7ArVD - FMmpHYxZAGGtY5GSjv7uL+R8dWRc54M7xD+k2Gqr47EJJKKz6fXIzuNIzxnA/Zh8eBUGfXC954bd - A43PlfU0Dud9z/DuwtixMHO5ul29MaxRxEKbuFgcSiGPpGblvGUxKO0WIFtE/tvLW7On2Np2/zN+ - BlKSZ1KND6S0fJ13bguUjvFfbdcVj4YxUnjSkhrWFNJvUNSKwUwngvFnZOqbVtuOgg96upPWN/Wm - EO2G6vo9ZufsNwAAAP//AwDHwDA2NQMAAA== - headers: - CF-RAY: - - 99b0ebfc4e5ced3b-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 08 Nov 2025 00:23:27 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=.AxQfRhAvElThVl_Qz9zUVdqz_GtBGXwRQ0TVPIg5pc-1762561407-1.0.1.1-klsoMaFKHjzxOrHy2Zfd8Sc76RDHsMXURLAaIzORncnm47NI1MY0BqqBGOEsVXlZb.RdqeqpxzGFhl8DlRDjy.SqRfa2B4zEYdKZqQ2kVB0; - path=/; expires=Sat, 08-Nov-25 00:53:27 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=0ohSoYMS21h1NkHWl4FeeVCp5aK2KHeEjclSm1NY7yY-1762561407934-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '269' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '435' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_617bc8e11f2a43a98a0658e7e91298fd - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/langchain-py/src/tests/cassettes/test_parallel_execution b/integrations/langchain-py/src/tests/cassettes/test_parallel_execution deleted file mode 100644 index aec3440ee..000000000 --- a/integrations/langchain-py/src/tests/cassettes/test_parallel_execution +++ /dev/null @@ -1,234 +0,0 @@ -interactions: -- request: - body: '{"messages": [{"content": "Tell me a joke about bear", "role": "user"}], - "model": "gpt-4o-mini", "frequency_penalty": 0.0, "n": 1, "presence_penalty": - 0.0, "stream": false, "temperature": 1.0, "top_p": 1.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '188' - content-type: - - application/json - host: - - localhost:8000 - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.13 - method: POST - uri: http://localhost:8000/v1/proxy/chat/completions - response: - body: - string: "{\n \"id\": \"chatcmpl-CJ3vA6tl1z95spYoDxT9RtqqzDF8n\",\n \"object\": - \"chat.completion\",\n \"created\": 1758659340,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n - \ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": - \"assistant\",\n \"content\": \"Why don\u2019t bears ever get lost?\\n\\nBecause - they always take the bear necessities! \U0001F43B\",\n \"refusal\": - null,\n \"annotations\": []\n },\n \"logprobs\": null,\n - \ \"finish_reason\": \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": - 13,\n \"completion_tokens\": 19,\n \"total_tokens\": 32,\n \"prompt_tokens_details\": - {\n \"cached_tokens\": 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": - {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": - 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": - \"default\",\n \"system_fingerprint\": \"fp_51db84afab\"\n}\n" - headers: - Access-Control-Allow-Credentials: - - 'true' - Access-Control-Expose-Headers: - - x-bt-cursor,x-bt-found-existing,x-bt-span-id,x-bt-span-export,x-bt-query-plan,x-bt-internal-trace-id - Connection: - - keep-alive - Date: - - Tue, 23 Sep 2025 20:29:00 GMT - Keep-Alive: - - timeout=5 - Transfer-Encoding: - - chunked - Vary: - - Origin - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - cf-ray: - - 983ccaa98d189e59-SJC - content-type: - - application/json - openai-organization: - - braintrust-data - openai-processing-ms: - - '742' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - set-cookie: - - _cfuvid=h4eOl14etTzzF9eOjCE9SDq4Y79ZdPOJeIYnqb.tN3E-1758659340929-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-bt-cached: - - MISS - x-bt-internal-trace-id: - - ba7859db365b14edae0dc1d75360d5cb - x-content-type-options: - - nosniff - x-envoy-upstream-service-time: - - '912' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999990' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_31748d3aea8d488c9f1b1b7764b3a5d7 - status: - code: 200 - message: OK -- request: - body: '{"messages": [{"content": "write a 2-line poem about bear", "role": "user"}], - "model": "gpt-4o-mini", "frequency_penalty": 0.0, "n": 1, "presence_penalty": - 0.0, "stream": false, "temperature": 1.0, "top_p": 1.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '193' - content-type: - - application/json - host: - - localhost:8000 - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.13 - method: POST - uri: http://localhost:8000/v1/proxy/chat/completions - response: - body: - string: "{\n \"id\": \"chatcmpl-CJ3vAwrz88GjVnlchECG5UbilcrZG\",\n \"object\": - \"chat.completion\",\n \"created\": 1758659340,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n - \ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": - \"assistant\",\n \"content\": \"In forest shadows, a bear roams free, - \ \\nMajestic guardian of the ancient tree.\",\n \"refusal\": null,\n - \ \"annotations\": []\n },\n \"logprobs\": null,\n \"finish_reason\": - \"stop\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 15,\n \"completion_tokens\": - 19,\n \"total_tokens\": 34,\n \"prompt_tokens_details\": {\n \"cached_tokens\": - 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": - {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": - 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": - \"default\",\n \"system_fingerprint\": \"fp_560af6e559\"\n}\n" - headers: - Access-Control-Allow-Credentials: - - 'true' - Access-Control-Expose-Headers: - - x-bt-cursor,x-bt-found-existing,x-bt-span-id,x-bt-span-export,x-bt-query-plan,x-bt-internal-trace-id - Connection: - - keep-alive - Date: - - Tue, 23 Sep 2025 20:29:01 GMT - Keep-Alive: - - timeout=5 - Transfer-Encoding: - - chunked - Vary: - - Origin - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - cf-ray: - - 983ccaa99f09cecd-SJC - content-type: - - application/json - openai-organization: - - braintrust-data - openai-processing-ms: - - '909' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - set-cookie: - - _cfuvid=I8TMI8qNGmqspYd_94RtBiCEVRDIffMScd.j_yw35Es-1758659341697-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-bt-cached: - - MISS - x-bt-internal-trace-id: - - 7d350d2a8b4d267107b257e3a1989c5a - x-content-type-options: - - nosniff - x-envoy-upstream-service-time: - - '1375' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999990' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_891af1935bbf49c39105d7299babb315 - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/langchain-py/src/tests/cassettes/test_prompt_caching_tokens b/integrations/langchain-py/src/tests/cassettes/test_prompt_caching_tokens deleted file mode 100644 index 441128e9d..000000000 --- a/integrations/langchain-py/src/tests/cassettes/test_prompt_caching_tokens +++ /dev/null @@ -1,324 +0,0 @@ -interactions: -- request: - body: '{"max_tokens":1024,"messages":[{"role":"user","content":"What is the first - type of testing mentioned in section 1.2?"}],"model":"claude-sonnet-4-5-20250929","system":[{"type":"text","text":"\n# - Comprehensive Guide to Software Testing Methods!\n\n## Chapter 1: Introduction - to Testing\n\nSoftware testing is a critical component of the software development - lifecycle. It ensures that applications\nfunction correctly, meet requirements, - and provide a positive user experience. This guide covers various\ntesting methodologies, - best practices, and tools used in modern software development.\n\n### 1.1 The - Importance of Testing\n\nTesting helps identify defects early in the development - process, reducing the cost of fixing issues later.\nStudies have shown that - the cost of fixing a bug increases exponentially as it progresses through the\ndevelopment - lifecycle. A bug found during requirements gathering might cost $1 to fix, while - the same bug\nfound in production could cost $100 or more.\n\n### 1.2 Types - of Testing\n\nThere are many types of testing, including:\n- Unit Testing: Testing - individual components or functions in isolation\n- Integration Testing: Testing - how components work together\n- End-to-End Testing: Testing the entire application - flow\n- Performance Testing: Testing application speed and scalability\n- Security - Testing: Testing for vulnerabilities and security issues\n- Usability Testing: - Testing user experience and interface design\n\n## Chapter 2: Unit Testing Best - Practices\n\nUnit testing focuses on testing the smallest testable parts of - an application. Here are some best practices:\n\n### 2.1 Write Tests First (TDD)\n\nTest-Driven - Development (TDD) is a methodology where tests are written before the actual - code. The process\nfollows a simple cycle: Red (write a failing test), Green - (write code to pass the test), Refactor (improve\nthe code while keeping tests - passing).\n\n### 2.2 Keep Tests Independent\n\nEach test should be independent - of others. Tests should not rely on the state created by previous tests.\nThis - ensures that tests can be run in any order and that failures are isolated and - easy to debug.\n\n### 2.3 Use Meaningful Names\n\nTest names should clearly - describe what is being tested and what the expected outcome is. A good test - name\nmight be \"test_user_registration_with_valid_email_succeeds\" rather than - just \"test_registration\".\n\n### 2.4 Test Edge Cases\n\nDon''t just test the - happy path. Consider edge cases like:\n- Empty inputs\n- Null or undefined values\n- - Very large inputs\n- Invalid formats\n- Boundary conditions\n\n## Chapter 3: - Integration Testing\n\nIntegration testing verifies that different modules or - services work together correctly.\n\n### 3.1 Database Integration\n\nWhen testing - database interactions, consider using:\n- Test databases separate from production\n- - Database transactions that roll back after each test\n- Mock data that represents - realistic scenarios\n\n### 3.2 API Integration\n\nAPI integration tests should - verify:\n- Correct HTTP status codes\n- Response format and schema\n- Error - handling\n- Authentication and authorization\n\n## Chapter 4: Performance Testing\n\nPerformance - testing ensures your application can handle expected load and scale appropriately.\n\n### - 4.1 Load Testing\n\nLoad testing simulates multiple users accessing the application - simultaneously. Key metrics include:\n- Response time under load\n- Throughput - (requests per second)\n- Error rates\n- Resource utilization (CPU, memory, network)\n\n### - 4.2 Stress Testing\n\nStress testing pushes the application beyond normal operational - capacity to find breaking points and\nunderstand how the system fails gracefully.\n\n## - Chapter 5: Continuous Integration and Testing\n\nModern development practices - integrate testing into the CI/CD pipeline.\n\n### 5.1 Automated Test Runs\n\nTests - should run automatically on every code change. This includes:\n- Running unit - tests on every commit\n- Running integration tests on pull requests\n- Running - end-to-end tests before deployment\n\n### 5.2 Test Coverage\n\nTest coverage - metrics help identify untested code. While 100% coverage isn''t always practical - or necessary,\nmaintaining good coverage helps ensure code quality. Focus on - critical paths and business logic.\n\n## Chapter 6: Testing Tools and Frameworks\n\nMany - tools exist to support testing efforts:\n\n### 6.1 Python Testing\n- pytest: - Feature-rich testing framework\n- unittest: Built-in Python testing module\n- - mock: Library for mocking objects\n\n### 6.2 JavaScript Testing\n- Jest: Popular - testing framework\n- Mocha: Flexible testing framework\n- Cypress: End-to-end - testing tool\n\n### 6.3 Other Tools\n- Selenium: Browser automation\n- JMeter: - Performance testing\n- Postman: API testing\n\n## Conclusion\n\nEffective testing - is essential for delivering high-quality software. By following best practices - and using\nappropriate tools, teams can catch bugs early, improve code quality, - and deliver better products to users.\n\nRemember: Testing is not just about - finding bugs, it''s about building confidence in your code.\n","cache_control":{"type":"ephemeral"}}]}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - anthropic-version: - - '2023-06-01' - connection: - - keep-alive - content-length: - - '5160' - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.76.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.76.0 - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.10.19 - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAA/22RzU7rMBCFX8WaZZWiJGqvaHYXsQIhsaBsKIqMPW0sEjt4xgVU9d0ZFyp+V4nn - fHOOZ7yDIVjsoQHT62RxSsF75OlsOp/WZT0vF/UCCnBWiIE2bVndrsO/s+1ptYzXl+fz04tN0nZ5 - JQy/jpgpJNIblEIMfS5oIkesPUvJBM8of83d7sgzvmTl8GngvzEhWuc3ioMiNOyCV9VJrVZwIzyp - sFY3SCxEsQLFHaq1i8Qqu2WR30U1SIz0olWO1GSy9I6PjZNJoZ47Z7osWSQT3YNwmnLIR7vz1m2d - TbpXJgyjGHmW8KjWyR8uRYJIf+h1Pp2sAPb3BRCHsY2oZYsyDHrbcooePgTCp4TeyNQ+9X0B6bCo - ZgfOj4lbDo/oCZq6lEVp02FrxCrbt9+BqpwtjogQ9of8qz1H4NjhgFH37Xz40+4TqLqfhvsCQuKv - pZmEEMatM9iywyjT5je2OlrY798Az+eCZFYCAAA= - headers: - CF-RAY: - - 9c1a60c71c9c67cb-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 21 Jan 2026 22:51:47 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - '3000000' - anthropic-ratelimit-input-tokens-remaining: - - '3000000' - anthropic-ratelimit-input-tokens-reset: - - '2026-01-21T22:51:46Z' - anthropic-ratelimit-output-tokens-limit: - - '600000' - anthropic-ratelimit-output-tokens-remaining: - - '600000' - anthropic-ratelimit-output-tokens-reset: - - '2026-01-21T22:51:47Z' - anthropic-ratelimit-tokens-limit: - - '3600000' - anthropic-ratelimit-tokens-remaining: - - '3600000' - anthropic-ratelimit-tokens-reset: - - '2026-01-21T22:51:46Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CXMLqXaFZ4xWZExkXJyyb - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - '2088' - status: - code: 200 - message: OK -- request: - body: '{"max_tokens":1024,"messages":[{"role":"user","content":"What is the first - type of testing mentioned in section 1.2?"},{"role":"assistant","content":"According - to section 1.2 \"Types of Testing,\" the first type of testing mentioned is - **Unit Testing**, which is described as \"Testing individual components or functions - in isolation.\""},{"role":"user","content":"What testing framework is mentioned - for Python?"}],"model":"claude-sonnet-4-5-20250929","system":[{"type":"text","text":"\n# - Comprehensive Guide to Software Testing Methods!\n\n## Chapter 1: Introduction - to Testing\n\nSoftware testing is a critical component of the software development - lifecycle. It ensures that applications\nfunction correctly, meet requirements, - and provide a positive user experience. This guide covers various\ntesting methodologies, - best practices, and tools used in modern software development.\n\n### 1.1 The - Importance of Testing\n\nTesting helps identify defects early in the development - process, reducing the cost of fixing issues later.\nStudies have shown that - the cost of fixing a bug increases exponentially as it progresses through the\ndevelopment - lifecycle. A bug found during requirements gathering might cost $1 to fix, while - the same bug\nfound in production could cost $100 or more.\n\n### 1.2 Types - of Testing\n\nThere are many types of testing, including:\n- Unit Testing: Testing - individual components or functions in isolation\n- Integration Testing: Testing - how components work together\n- End-to-End Testing: Testing the entire application - flow\n- Performance Testing: Testing application speed and scalability\n- Security - Testing: Testing for vulnerabilities and security issues\n- Usability Testing: - Testing user experience and interface design\n\n## Chapter 2: Unit Testing Best - Practices\n\nUnit testing focuses on testing the smallest testable parts of - an application. Here are some best practices:\n\n### 2.1 Write Tests First (TDD)\n\nTest-Driven - Development (TDD) is a methodology where tests are written before the actual - code. The process\nfollows a simple cycle: Red (write a failing test), Green - (write code to pass the test), Refactor (improve\nthe code while keeping tests - passing).\n\n### 2.2 Keep Tests Independent\n\nEach test should be independent - of others. Tests should not rely on the state created by previous tests.\nThis - ensures that tests can be run in any order and that failures are isolated and - easy to debug.\n\n### 2.3 Use Meaningful Names\n\nTest names should clearly - describe what is being tested and what the expected outcome is. A good test - name\nmight be \"test_user_registration_with_valid_email_succeeds\" rather than - just \"test_registration\".\n\n### 2.4 Test Edge Cases\n\nDon''t just test the - happy path. Consider edge cases like:\n- Empty inputs\n- Null or undefined values\n- - Very large inputs\n- Invalid formats\n- Boundary conditions\n\n## Chapter 3: - Integration Testing\n\nIntegration testing verifies that different modules or - services work together correctly.\n\n### 3.1 Database Integration\n\nWhen testing - database interactions, consider using:\n- Test databases separate from production\n- - Database transactions that roll back after each test\n- Mock data that represents - realistic scenarios\n\n### 3.2 API Integration\n\nAPI integration tests should - verify:\n- Correct HTTP status codes\n- Response format and schema\n- Error - handling\n- Authentication and authorization\n\n## Chapter 4: Performance Testing\n\nPerformance - testing ensures your application can handle expected load and scale appropriately.\n\n### - 4.1 Load Testing\n\nLoad testing simulates multiple users accessing the application - simultaneously. Key metrics include:\n- Response time under load\n- Throughput - (requests per second)\n- Error rates\n- Resource utilization (CPU, memory, network)\n\n### - 4.2 Stress Testing\n\nStress testing pushes the application beyond normal operational - capacity to find breaking points and\nunderstand how the system fails gracefully.\n\n## - Chapter 5: Continuous Integration and Testing\n\nModern development practices - integrate testing into the CI/CD pipeline.\n\n### 5.1 Automated Test Runs\n\nTests - should run automatically on every code change. This includes:\n- Running unit - tests on every commit\n- Running integration tests on pull requests\n- Running - end-to-end tests before deployment\n\n### 5.2 Test Coverage\n\nTest coverage - metrics help identify untested code. While 100% coverage isn''t always practical - or necessary,\nmaintaining good coverage helps ensure code quality. Focus on - critical paths and business logic.\n\n## Chapter 6: Testing Tools and Frameworks\n\nMany - tools exist to support testing efforts:\n\n### 6.1 Python Testing\n- pytest: - Feature-rich testing framework\n- unittest: Built-in Python testing module\n- - mock: Library for mocking objects\n\n### 6.2 JavaScript Testing\n- Jest: Popular - testing framework\n- Mocha: Flexible testing framework\n- Cypress: End-to-end - testing tool\n\n### 6.3 Other Tools\n- Selenium: Browser automation\n- JMeter: - Performance testing\n- Postman: API testing\n\n## Conclusion\n\nEffective testing - is essential for delivering high-quality software. By following best practices - and using\nappropriate tools, teams can catch bugs early, improve code quality, - and deliver better products to users.\n\nRemember: Testing is not just about - finding bugs, it''s about building confidence in your code.\n","cache_control":{"type":"ephemeral"}}]}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - anthropic-version: - - '2023-06-01' - connection: - - keep-alive - content-length: - - '5456' - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.76.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.76.0 - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.10.19 - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAA/2VSzU7DMAx+lSjHqUXtYEzrDYQQB5A4IA2JoiokZg1rnZI4wDTt3XHK/zgl+X4c - +0u2sncGOllJ3aloIA8OESg/ymf5tJjOisV0ITNpDSv6sGqKsqSr5fX87OVC6RbncblY3y7PkDW0 - GSCpIAS1Aga86xKgQrCBFBJD2iEB76q77Zee4C0x41LJE62dNxZXgpwIoMk6FMcHpajl9YZaPtxA - IOazWgpqPYCgD0A8etXDq/PrIJQH0fM9bAYjHp0XH+aqxhrLAzGZDJtkm0xELs5BUfSQe6vb/8Vq - nCZ9REvfjtNoO8otflb9NnGUsYMaD5Ojd3o9qi/tg1d+M7aRwKR0D088W5C7+0wGckPjQXHyHACg - abidFOhIBHiOgJqTwth1mYxjuNVWWhwiNeTWgEFW85LD5ReBRnOpNHjzV1B88UybPa4sjhb79nQF - DC304FXXzPr/5X7Yst1nd5l0kX5Dx+wI4F+shoYseB41fQqjvJG73TumCh7LhwIAAA== - headers: - CF-RAY: - - 9c1a60d4ab5e67cb-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 21 Jan 2026 22:51:49 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - '3000000' - anthropic-ratelimit-input-tokens-remaining: - - '3000000' - anthropic-ratelimit-input-tokens-reset: - - '2026-01-21T22:51:48Z' - anthropic-ratelimit-output-tokens-limit: - - '600000' - anthropic-ratelimit-output-tokens-remaining: - - '600000' - anthropic-ratelimit-output-tokens-reset: - - '2026-01-21T22:51:49Z' - anthropic-ratelimit-tokens-limit: - - '3600000' - anthropic-ratelimit-tokens-remaining: - - '3600000' - anthropic-ratelimit-tokens-reset: - - '2026-01-21T22:51:48Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CXMLqgrrchykwCdY7YRKM - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - '2016' - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/langchain-py/src/tests/cassettes/test_streaming_ttft b/integrations/langchain-py/src/tests/cassettes/test_streaming_ttft deleted file mode 100644 index 1ee7a8377..000000000 --- a/integrations/langchain-py/src/tests/cassettes/test_streaming_ttft +++ /dev/null @@ -1,298 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"content":"Count from 1 to 5.","role":"user"}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '124' - content-type: - - application/json - cookie: - - __cf_bm=W_Ukgb.mz8e1GW7CfhzN.QQaN09_xQq1uTHm3a.dJdU-1762561359-1.0.1.1-6IrkySxpZaL.1C65iH0iOLFfere0JxHCiasT6bak.RihYFMyJgIz2OuYJqcUey8c5vicjtorNby_Z_GJX.ZMIHa6PyzVrhqgfZZmtnnn.sA; - _cfuvid=jwWMA4k30hLPwBwTSCIdIeS5.m1TkcdYLYTt4YSTZhI-1762561359243-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: http://localhost:8000/v1/proxy/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"obfuscation":"uoycSw"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"obfuscation":"7R9sCOG"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"obfuscation":"jNZOnCU"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"obfuscation":"NTkR0fq"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"obfuscation":"KhfgFBA"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"obfuscation":"u5zk4uv"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"obfuscation":"yQyBcA4"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"obfuscation":"HhGcZch"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"obfuscation":"GNLE7Ci"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"obfuscation":"d0EKjlZ"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":"4"},"logprobs":null,"finish_reason":null}],"obfuscation":"YytmIuX"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"obfuscation":"Umbehc1"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"obfuscation":"3xi8C7o"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"obfuscation":"N0uOsTp"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"obfuscation":"RilMN7a"} - - - data: {"id":"chatcmpl-CZR0zJXGi0lsnYkPoiga2R6HChxps","object":"chat.completion.chunk","created":1762561361,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"obfuscation":"oF"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 99b0eaddeca8aaac-SJC - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 08 Nov 2025 00:22:42 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '275' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '519' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_05aebff8dd644228befd59a7372d3c93 - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"content":"Count from 1 to 5.","role":"user"}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '124' - content-type: - - application/json - cookie: - - __cf_bm=.AxQfRhAvElThVl_Qz9zUVdqz_GtBGXwRQ0TVPIg5pc-1762561407-1.0.1.1-klsoMaFKHjzxOrHy2Zfd8Sc76RDHsMXURLAaIzORncnm47NI1MY0BqqBGOEsVXlZb.RdqeqpxzGFhl8DlRDjy.SqRfa2B4zEYdKZqQ2kVB0; - _cfuvid=0ohSoYMS21h1NkHWl4FeeVCp5aK2KHeEjclSm1NY7yY-1762561407934-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: http://localhost:8000/v1/proxy/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"obfuscation":"ov7JiI"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"obfuscation":"eXpmCqg"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"obfuscation":"C8QZXu8"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"obfuscation":"xdqGFpo"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"obfuscation":"O3SLgWG"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"obfuscation":"0aoEi42"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"obfuscation":"2oO8rJa"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"obfuscation":"jOHTEGa"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"obfuscation":"qGeoxr1"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"obfuscation":"uvMar7j"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":"4"},"logprobs":null,"finish_reason":null}],"obfuscation":"4dFvFfq"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"obfuscation":"GdoZztm"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"obfuscation":"NHxpCPR"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"obfuscation":"mfV8KdT"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"obfuscation":"EkPlssM"} - - - data: {"id":"chatcmpl-CZR1mouRDQnH9qWlT2zp6Fs0nW1Uq","object":"chat.completion.chunk","created":1762561410,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_560af6e559","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"obfuscation":"fj"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 99b0ec0f7961ed3b-SJC - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 08 Nov 2025 00:23:30 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '149' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '171' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_8afec9e4717b433e9c6900220b2dbd93 - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/langchain-py/src/tests/cassettes/test_tool_usage b/integrations/langchain-py/src/tests/cassettes/test_tool_usage deleted file mode 100644 index e21d44ccb..000000000 --- a/integrations/langchain-py/src/tests/cassettes/test_tool_usage +++ /dev/null @@ -1,350 +0,0 @@ -interactions: -- request: - body: '{"messages": [{"content": "What is 3 * 12", "role": "user"}], "model": - "gpt-4o-mini", "frequency_penalty": 0.0, "n": 1, "presence_penalty": 0.0, "stream": - false, "temperature": 1.0, "tools": [{"type": "function", "function": {"name": - "calculator", "description": "Can perform mathematical operations.", "parameters": - {"properties": {"input": {"properties": {"operation": {"description": "The type - of operation to execute.", "enum": ["add", "subtract", "multiply", "divide"], - "type": "string"}, "number1": {"description": "The first number to operate on.", - "type": "number"}, "number2": {"description": "The second number to operate - on.", "type": "number"}}, "required": ["operation", "number1", "number2"], "type": - "object"}}, "required": ["input"], "type": "object"}}}], "top_p": 1.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '725' - content-type: - - application/json - host: - - localhost:8000 - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.13 - method: POST - uri: http://localhost:8000/v1/proxy/chat/completions - response: - body: - string: "{\n \"id\": \"chatcmpl-CJ3pT0xTT4C4WwCqA5bvyrihLFrbd\",\n \"object\": - \"chat.completion\",\n \"created\": 1758658987,\n \"model\": \"gpt-4o-mini-2024-07-18\",\n - \ \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n \"role\": - \"assistant\",\n \"content\": null,\n \"tool_calls\": [\n {\n - \ \"id\": \"call_faZyqlGfMGsX50e2EuExUqK0\",\n \"type\": - \"function\",\n \"function\": {\n \"name\": \"calculator\",\n - \ \"arguments\": \"{\\\"input\\\":{\\\"operation\\\":\\\"multiply\\\",\\\"number1\\\":3,\\\"number2\\\":12}}\"\n - \ }\n }\n ],\n \"refusal\": null,\n \"annotations\": - []\n },\n \"logprobs\": null,\n \"finish_reason\": \"tool_calls\"\n - \ }\n ],\n \"usage\": {\n \"prompt_tokens\": 97,\n \"completion_tokens\": - 26,\n \"total_tokens\": 123,\n \"prompt_tokens_details\": {\n \"cached_tokens\": - 0,\n \"audio_tokens\": 0\n },\n \"completion_tokens_details\": - {\n \"reasoning_tokens\": 0,\n \"audio_tokens\": 0,\n \"accepted_prediction_tokens\": - 0,\n \"rejected_prediction_tokens\": 0\n }\n },\n \"service_tier\": - \"default\",\n \"system_fingerprint\": \"fp_51db84afab\"\n}\n" - headers: - Access-Control-Allow-Credentials: - - 'true' - Access-Control-Expose-Headers: - - x-bt-cursor,x-bt-found-existing,x-bt-span-id,x-bt-span-export,x-bt-query-plan,x-bt-internal-trace-id - Connection: - - keep-alive - Date: - - Tue, 23 Sep 2025 20:23:07 GMT - Keep-Alive: - - timeout=5 - Transfer-Encoding: - - chunked - Vary: - - Origin - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - cf-ray: - - 983cc20cabc267ef-SJC - content-type: - - application/json - openai-organization: - - braintrust-data - openai-processing-ms: - - '648' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - set-cookie: - - _cfuvid=inx7Y1lMFCkI1jONo8plrYH7k2d1EAvkr2WlMIyrK.s-1758658987739-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-bt-cached: - - MISS - x-bt-internal-trace-id: - - 475d214543543ac965368ac2a190850f - x-content-type-options: - - nosniff - x-envoy-upstream-service-time: - - '663' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_f6bcef66199c4bcaa6ad5864f7d1d9fb - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"content":"What is 3 * 12","role":"user"}],"model":"gpt-4o-mini","frequency_penalty":0.0,"n":1,"presence_penalty":0.0,"stream":false,"temperature":1.0,"tools":[{"type":"function","function":{"name":"calculator","description":"Can - perform mathematical operations.","parameters":{"properties":{"input":{"properties":{"operation":{"description":"The - type of operation to execute.","enum":["add","subtract","multiply","divide"],"type":"string"},"number1":{"description":"The - first number to operate on.","type":"number"},"number2":{"description":"The - second number to operate on.","type":"number"}},"required":["operation","number1","number2"],"type":"object"}},"required":["input"],"type":"object"}}}],"top_p":1.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '725' - content-type: - - application/json - cookie: - - __cf_bm=W_Ukgb.mz8e1GW7CfhzN.QQaN09_xQq1uTHm3a.dJdU-1762561359-1.0.1.1-6IrkySxpZaL.1C65iH0iOLFfere0JxHCiasT6bak.RihYFMyJgIz2OuYJqcUey8c5vicjtorNby_Z_GJX.ZMIHa6PyzVrhqgfZZmtnnn.sA; - _cfuvid=jwWMA4k30hLPwBwTSCIdIeS5.m1TkcdYLYTt4YSTZhI-1762561359243-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA4xT0W6bMBR95yus+xymQAppedum7SFKNXXSqmqjQo65EG/G9myzLY3y7xMmBZKm - UnlAcI/PucfH1/uAEOAlZATYljrWaBF+/P51vnsyt/dSfzCrMmFyeXu3fr96untwX2DWMdTmJzL3 - zHrHVKMFOq5kDzOD1GGnGi3TOEmjRTr3QKNKFB2t1i68UmHDJQ/jeXwVzpdhdH1kbxVnaCEjPwJC - CNn7d+dTlvgPMuK1fKVBa2mNkA2LCAGjRFcBai23jkoHsxFkSjqUnXXZCjEBnFKiYFSIsXH/7Cff - Y1hUiALZUupvWK/u/z4k5e9PuNafV+vrab9eeqe9oaqVbAhpgg/17KwZISBpg8eGrBXUKXPGJgSo - qdsGpeucwz4HLnXrcsj2OSiNhnbaOWQ5NK1wXItdDrMcZNts0EQ5ZIvhL84hi+LDAU5aHIJL34+T - 8AxWraXiZapUSuW8AR/r4xE5DCcoVK2N2tgzKlRccrstDFLrg5meT/BsxFuA9mQEQBvVaFc49Qt9 - 05tlLwrjlI5gnB5BpxwVYz2KF7MLckWJjnI/IsNUMsq2WI7UcTppW3I1AYLJ1l+6uaTdb5/L+i3y - I8AYaodloQ2WnJ3ueFxmsLvEry0bQvaGwaL5wxkWjqPpjqPEiraiH3WwO+uwKSouazTacH+/oNJF - ks5plWKS3EBwCP4DAAD//wMAguKIhm0EAAA= - headers: - CF-RAY: - - 99b0ead42b8caaac-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 08 Nov 2025 00:22:40 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '557' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '702' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_edb893697ec245fbb710a31d27a3ed78 - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"content":"What is 3 * 12","role":"user"}],"model":"gpt-4o-mini","frequency_penalty":0.0,"n":1,"presence_penalty":0.0,"stream":false,"temperature":1.0,"tools":[{"type":"function","function":{"name":"calculator","description":"Can - perform mathematical operations.","parameters":{"properties":{"input":{"properties":{"operation":{"description":"The - type of operation to execute.","enum":["add","subtract","multiply","divide"],"type":"string"},"number1":{"description":"The - first number to operate on.","type":"number"},"number2":{"description":"The - second number to operate on.","type":"number"}},"required":["operation","number1","number2"],"type":"object"}},"required":["input"],"type":"object"}}}],"top_p":1.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '725' - content-type: - - application/json - cookie: - - __cf_bm=.AxQfRhAvElThVl_Qz9zUVdqz_GtBGXwRQ0TVPIg5pc-1762561407-1.0.1.1-klsoMaFKHjzxOrHy2Zfd8Sc76RDHsMXURLAaIzORncnm47NI1MY0BqqBGOEsVXlZb.RdqeqpxzGFhl8DlRDjy.SqRfa2B4zEYdKZqQ2kVB0; - _cfuvid=0ohSoYMS21h1NkHWl4FeeVCp5aK2KHeEjclSm1NY7yY-1762561407934-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.108.2 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.2 - x-stainless-raw-response: - - 'true' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA4xTTY/aMBC951dYc4YqCV+7udEPqSdaVeqh26wiY0/AXce2/MHCIv57lQSSwFKp - OUT2PM+b5+eZY0QICA4ZAbalnlVGjj89/UjkfIlfVm+/4o9P4dW/2a/S0dfl5PAAozpDr/8g85es - D0xXRqIXWrUws0g91qzJYp7O5sk0fmyASnOUddrG+PFUjyuhxDiN0+k4XoyTMznbasHQQUZ+R4QQ - cmz+tU7FcQ8ZiUeXSIXO0Q1C1h0iBKyWdQSoc8J5qjyMepBp5VHV0lWQcgB4rWXBqJR94fY7Dta9 - WVTK4udkP9upwHY7/nm1XH2Pefi2f4n5oF5LfTCNoDIo1pk0wLt4dlOMEFC0wnNBFiT12t5kEwLU - bkKFytfK4ZiDUCb4HLJjDtqgpTV3DlkOVZBeGHnIYZSDCtUabZJDNul2aQ5Zkp5OcFXiFN1bPw/M - s1gGR+V7V6lS2jcCGlufz8ipe0GpN8bqtbtJhVIo4baFReoaY4bvE12ENBIgXLUAGKsr4wuvX7Ap - +rhoSaHv0h5M52fQa09lH0/SyegOXcHRU9G0SNeVjLIt8j61704auNADIBpc/b2ae9zt9YXa/A99 - DzCGxiMvjEUu2PWN+2MW6yH+17HO5EYwOLQ7wbDwAm39HBxLGmQ7WuAOzmNVlEJt0BormvmC0hSz - hK8fprSka4hO0V8AAAD//wMAMU2sv20EAAA= - headers: - CF-RAY: - - 99b0ec04f9abed3b-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 08 Nov 2025 00:23:29 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '614' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '756' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_b741763f424444f38ded6343a488e723 - status: - code: 200 - message: OK -version: 1 diff --git a/integrations/langchain-py/src/tests/conftest.py b/integrations/langchain-py/src/tests/conftest.py deleted file mode 100644 index 4857cf3b1..000000000 --- a/integrations/langchain-py/src/tests/conftest.py +++ /dev/null @@ -1,60 +0,0 @@ -# pyright: reportPrivateUsage=none -import os - -import pytest -from braintrust.logger import ( - TEST_API_KEY, - Logger, - _internal_reset_global_state, - _internal_with_memory_background_logger, - _MemoryBackgroundLogger, -) -from braintrust.test_helpers import init_test_logger - -from braintrust_langchain.context import clear_global_handler - - -@pytest.fixture(autouse=True) -def setup_braintrust(): - os.environ["BRAINTRUST_SYNC_FLUSH"] = "1" - os.environ["BRAINTRUST_API_URL"] = "http://localhost:8000" - os.environ["BRAINTRUST_APP_URL"] = "http://localhost:3000" - os.environ["BRAINTRUST_API_KEY"] = TEST_API_KEY - os.environ["ANTHROPIC_API_KEY"] = "your_anthropic_api_key_here" - os.environ["OPENAI_API_KEY"] = "your_openai_api_key_here" - os.environ["OPENAI_BASE_URL"] = "http://localhost:8000/v1/proxy" - - _internal_reset_global_state() - clear_global_handler() - yield - - -@pytest.fixture(scope="module") -def vcr_config(): - # In CI, use "none" to never make real requests - # Locally, use "once" to record new cassettes if they don't exist - record_mode = "none" if (os.environ.get("CI") or os.environ.get("GITHUB_ACTIONS")) else "once" - - return { - "filter_headers": [ - "authorization", - "x-goog-api-key", - "x-api-key", - "api-key", - "openai-api-key", - ], - "record_mode": record_mode, - "match_on": ["uri", "method", "body"], - "cassette_library_dir": "src/tests/cassettes", - "path_transformer": lambda path: path.replace(".yaml", ""), - } - - -@pytest.fixture -def logger_memory_logger(): - logger = init_test_logger("langchain-py") - with _internal_with_memory_background_logger() as bgl: - yield (logger, bgl) - - -LoggerMemoryLogger = tuple[Logger, _MemoryBackgroundLogger] diff --git a/integrations/langchain-py/src/tests/helpers.py b/integrations/langchain-py/src/tests/helpers.py deleted file mode 100644 index 7816dea47..000000000 --- a/integrations/langchain-py/src/tests/helpers.py +++ /dev/null @@ -1,88 +0,0 @@ -from typing import Any, Dict, List, Sequence, Union, cast -from unittest.mock import ANY - -from braintrust.logger import Span - -from .types import Span - -# Base types that can appear in values -PrimitiveValue = Union[str, int, float, bool, None, Span] -RecursiveValue = Union[PrimitiveValue, Dict[str, Any], Sequence[Any]] - - -def deep_hashable_dict(d: RecursiveValue): - """Recursively convert a dictionary into a hashable representation, handling nested values.""" - if isinstance(d, dict): - return frozenset((k, deep_hashable_dict(v)) for k, v in d.items()) - elif isinstance(d, Sequence) and not isinstance(d, str): - return frozenset(deep_hashable_dict(x) for x in d) - else: - return d - - -def assert_matches_object( - actual: RecursiveValue, - expected: RecursiveValue, - ignore_order: bool = False, -) -> None: - """Assert that actual contains all key-value pairs from expected. - - For lists, each item in expected must match the corresponding item in actual. - For dicts, all key-value pairs in expected must exist in actual. - - Args: - actual: The actual value to check - expected: The expected value to match against - - Raises: - AssertionError: If the actual value doesn't match the expected value - """ - if isinstance(expected, (list, tuple)): - assert isinstance(actual, (list, tuple)), f"Expected sequence but got {type(actual)}" - assert len(actual) >= len(expected), ( - f"Expected sequence of length >= {len(expected)} but got length {len(actual)}" - ) - if not ignore_order: - for i, expected_item in enumerate(expected): - assert_matches_object(actual[i], expected_item) - else: - for expected_item in expected: - matched = False - for actual_item in actual: - try: - assert_matches_object(actual_item, expected_item) - matched = True - except: - pass - - assert matched, f"Expected {expected_item} in unordered sequence but couldn't find match in {actual}" - - elif isinstance(expected, dict): - assert isinstance(actual, dict), f"Expected dict but got {type(actual)}" - for k, v in expected.items(): - assert k in actual, f"Missing key {k}" - if v is ANY: - continue # ANY matches anything - if isinstance(v, (dict, list, tuple)): - assert_matches_object(cast(RecursiveValue, actual[k]), cast(RecursiveValue, v)) - else: - assert actual[k] == v, f"Key {k}: expected {v} but got {actual[k]}" - else: - assert actual == expected, f"Expected {expected} but got {actual}" - - -def find_spans_by_attributes(spans: List[Span], **attributes: Any) -> List[Span]: - """Find all spans that match the given attributes.""" - matching_spans: List[Span] = [] - for span in spans: - matches = True - if "span_attributes" not in span: - matches = False - continue - for key, value in attributes.items(): - if key not in span["span_attributes"] or span["span_attributes"][key] != value: - matches = False - break - if matches: - matching_spans.append(span) - return matching_spans diff --git a/integrations/langchain-py/src/tests/test_anthropic.py b/integrations/langchain-py/src/tests/test_anthropic.py deleted file mode 100644 index d2e3364b8..000000000 --- a/integrations/langchain-py/src/tests/test_anthropic.py +++ /dev/null @@ -1,102 +0,0 @@ -from unittest.mock import ANY - -import pytest -from braintrust import flush -from langchain_anthropic import ChatAnthropic -from langchain_core.prompts import ChatPromptTemplate - -from braintrust_langchain import BraintrustCallbackHandler -from braintrust_langchain.context import set_global_handler -from tests.conftest import LoggerMemoryLogger -from tests.helpers import assert_matches_object - -PROJECT_NAME = "langchain-anthropic" -MODEL = "claude-sonnet-4-20250514" - - -@pytest.mark.vcr -def test_langchain_anthropic_integration( - logger_memory_logger: LoggerMemoryLogger, -): - logger, memory_logger = logger_memory_logger - assert not memory_logger.pop() - - handler = BraintrustCallbackHandler(logger=logger) - set_global_handler(handler) - - prompt = ChatPromptTemplate.from_template("What is 1 + {number}?") - model = ChatAnthropic(model_name=MODEL) - - chain = prompt | model - - result = chain.invoke({"number": "2"}) - - flush() - - assert isinstance(result.content, str) - assert "3" in result.content.lower() - - spans = memory_logger.pop() - assert len(spans) > 0 - - chain_spans = [span for span in spans if "LangGraph" in span["span_attributes"].get("name", "")] - if not chain_spans: - chain_spans = [span for span in spans if span["span_attributes"].get("type") == "task"] - - llm_spans = [span for span in spans if span["span_attributes"].get("type") == "llm"] - assert len(llm_spans) > 0, "Should have at least one LLM call" - - llm_span = llm_spans[0] - assert llm_span["metadata"]["model"] == MODEL - - prompt_spans = [span for span in spans if "ChatPromptTemplate" in span["span_attributes"].get("name", "")] - if prompt_spans: - prompt_span = prompt_spans[0] - assert "input" in prompt_span - assert prompt_span["input"]["number"] == "2" - - for span in llm_spans: - if "output" in span: - output_text = str(span["output"]) - if "3" in output_text.lower(): - break - else: - assert False, "No LLM span contained the expected answer '3'" - - assert_matches_object( - llm_span["metrics"], - { - "completion_tokens": 13, - "end": ANY, - "prompt_tokens": 16, - "start": ANY, - "total_tokens": 29, - }, - ) - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_async_langchain_invoke( - logger_memory_logger: LoggerMemoryLogger, -): - logger, memory_logger = logger_memory_logger - assert not memory_logger.pop() - - handler = BraintrustCallbackHandler(logger=logger) - set_global_handler(handler) - - prompt = ChatPromptTemplate.from_template("What is 1 + {number}?") - model = ChatAnthropic(model_name=MODEL) - - chain = prompt | model - - result = await chain.ainvoke({"number": "2"}) - - flush() - - assert isinstance(result.content, str) - assert "3" in result.content.lower() - - spans = memory_logger.pop() - assert len(spans) > 0 diff --git a/integrations/langchain-py/src/tests/test_callbacks.py b/integrations/langchain-py/src/tests/test_callbacks.py deleted file mode 100644 index ab17182a6..000000000 --- a/integrations/langchain-py/src/tests/test_callbacks.py +++ /dev/null @@ -1,1155 +0,0 @@ -# pyright: reportTypedDictNotRequiredAccess=none -import uuid -from typing import Dict, List, Union, cast - -import pytest -from braintrust.logger import flush -from langchain_anthropic import ChatAnthropic -from langchain_core.callbacks import BaseCallbackHandler -from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage -from langchain_core.prompts import ChatPromptTemplate -from langchain_core.prompts.prompt import PromptTemplate -from langchain_core.runnables import RunnableMap, RunnableSerializable -from langchain_core.tools import tool -from langchain_openai import ChatOpenAI -from pydantic import BaseModel, Field - -from braintrust_langchain import BraintrustCallbackHandler - -from .conftest import LoggerMemoryLogger -from .helpers import ANY, assert_matches_object, find_spans_by_attributes -from .types import Span - - -@pytest.mark.vcr -def test_llm_calls(logger_memory_logger: LoggerMemoryLogger): - logger, memory_logger = logger_memory_logger - assert not memory_logger.pop() - - handler = BraintrustCallbackHandler(logger=logger) - prompt = ChatPromptTemplate.from_template("What is 1 + {number}?") - model = ChatOpenAI( - model="gpt-4o-mini", - temperature=1, - top_p=1, - frequency_penalty=0, - presence_penalty=0, - n=1, - ) - chain: RunnableSerializable[Dict[str, str], BaseMessage] = prompt.pipe(model) - chain.invoke({"number": "2"}, config={"callbacks": [cast(BaseCallbackHandler, handler)]}) - - spans = memory_logger.pop() - assert len(spans) == 3 - - root_span_id = spans[0]["span_id"] - - assert_matches_object( - spans, - [ - { - "span_attributes": { - "name": "RunnableSequence", - "type": "task", - }, - "input": {"number": "2"}, - "output": { - "content": ANY, # LLM response text - "additional_kwargs": ANY, - "response_metadata": ANY, - "type": "ai", - "name": ANY, - "id": ANY, - "example": ANY, - "tool_calls": ANY, - "invalid_tool_calls": ANY, - "usage_metadata": ANY, - }, - "metadata": {"tags": []}, - "span_id": root_span_id, - "root_span_id": root_span_id, - }, - { - "span_attributes": {"name": "ChatPromptTemplate"}, - "input": {"number": "2"}, - "output": { - "messages": [ - { - "content": ANY, # Formatted prompt text - "additional_kwargs": {}, - "response_metadata": {}, - "type": "human", - "name": None, - "id": None, - } - ] - }, - "metadata": {"tags": ["seq:step:1"]}, - "root_span_id": root_span_id, - "span_parents": [root_span_id], - }, - { - "span_attributes": {"name": "ChatOpenAI", "type": "llm"}, - "input": [ - [ - { - "content": ANY, # Prompt message content - "additional_kwargs": {}, - "response_metadata": {}, - "type": "human", - "name": None, - "id": None, - "example": ANY, - } - ] - ], - "output": { - "generations": [ - [ - { - "text": ANY, # Generated text - "generation_info": ANY, - "type": "ChatGeneration", - "message": { - "content": ANY, # Message content - "additional_kwargs": ANY, - "response_metadata": ANY, - "type": "ai", - "name": None, - "id": ANY, - }, - } - ] - ], - "llm_output": { - "token_usage": { - "completion_tokens": ANY, - "prompt_tokens": ANY, - "total_tokens": ANY, - }, - "model_name": "gpt-4o-mini-2024-07-18", - }, - "run": None, - "type": "LLMResult", - }, - "metrics": { - "start": ANY, - "total_tokens": ANY, - "prompt_tokens": ANY, - "completion_tokens": ANY, - "end": ANY, - }, - "metadata": { - "tags": ["seq:step:2"], - "model": "gpt-4o-mini-2024-07-18", - }, - "root_span_id": root_span_id, - "span_parents": [root_span_id], - }, - ], - ) - -@pytest.mark.vcr -def test_chain_with_memory(logger_memory_logger: LoggerMemoryLogger): - logger, memory_logger = logger_memory_logger - assert not memory_logger.pop() - - handler = BraintrustCallbackHandler(logger=logger) - prompt = ChatPromptTemplate.from_template("{history} User: {input}") - model = ChatOpenAI(model="gpt-4o-mini") - chain: RunnableSerializable[Dict[str, str], BaseMessage] = prompt.pipe(model) - - memory = {"history": "Assistant: Hello! How can I assist you today?"} - chain.invoke( - {"input": "What's your name?", **memory}, - config={"callbacks": [cast(BaseCallbackHandler, handler)], "tags": ["test"]}, - ) - - spans = memory_logger.pop() - assert len(spans) == 3 - - root_span_id = spans[0]["span_id"] - - assert_matches_object( - spans, - [ - { - "span_attributes": { - "name": "RunnableSequence", - "type": "task", - }, - "input": {"input": "What's your name?", "history": "Assistant: Hello! How can I assist you today?"}, - "output": { - "content": ANY, # LLM response - "additional_kwargs": ANY, - "response_metadata": ANY, - "type": "ai", - }, - "metadata": {"tags": ["test"]}, - "span_id": root_span_id, - "root_span_id": root_span_id, - }, - { - "span_attributes": {"name": "ChatPromptTemplate"}, - "input": {"input": "What's your name?", "history": "Assistant: Hello! How can I assist you today?"}, - "output": { - "messages": [ - { - "content": ANY, # Formatted prompt with history - "additional_kwargs": {}, - "response_metadata": {}, - "type": "human", - "name": None, - "id": None, - } - ] - }, - "metadata": {"tags": ["seq:step:1", "test"]}, - "root_span_id": root_span_id, - "span_parents": [root_span_id], - }, - { - "span_attributes": {"name": "ChatOpenAI", "type": "llm"}, - "input": [ - [ - { - "content": ANY, # Prompt with history - "additional_kwargs": {}, - "response_metadata": {}, - "type": "human", - "name": None, - "id": None, - "example": ANY, - } - ] - ], - "output": { - "generations": [ - [ - { - "text": ANY, # Generated response - "generation_info": ANY, - "type": "ChatGeneration", - "message": { - "content": ANY, - "additional_kwargs": ANY, - "response_metadata": ANY, - "type": "ai", - "name": None, - "id": ANY, - }, - } - ] - ], - "llm_output": { - "token_usage": { - "completion_tokens": ANY, - "prompt_tokens": ANY, - "total_tokens": ANY, - }, - "model_name": "gpt-4o-mini-2024-07-18", - }, - "run": None, - "type": "LLMResult", - }, - "metrics": { - "start": ANY, - "total_tokens": ANY, - "prompt_tokens": ANY, - "completion_tokens": ANY, - "end": ANY, - }, - "metadata": { - "tags": ["seq:step:2", "test"], - "model": "gpt-4o-mini-2024-07-18", - }, - "root_span_id": root_span_id, - "span_parents": [root_span_id], - }, - ], - ) - - -@pytest.mark.vcr -def test_tool_usage(logger_memory_logger: LoggerMemoryLogger): - logger, memory_logger = logger_memory_logger - assert not memory_logger.pop() - - handler = BraintrustCallbackHandler(logger=logger) - - class CalculatorInput(BaseModel): - operation: str = Field( - description="The type of operation to execute.", - json_schema_extra={"enum": ["add", "subtract", "multiply", "divide"]}, - ) - number1: float = Field(description="The first number to operate on.") - number2: float = Field(description="The second number to operate on.") - - @tool - def calculator(input: CalculatorInput) -> str: - """Can perform mathematical operations.""" - if input.operation == "add": - return str(input.number1 + input.number2) - elif input.operation == "subtract": - return str(input.number1 - input.number2) - elif input.operation == "multiply": - return str(input.number1 * input.number2) - elif input.operation == "divide": - return str(input.number1 / input.number2) - else: - raise ValueError("Invalid operation.") - - model = ChatOpenAI( - model="gpt-4o-mini", - temperature=1, - top_p=1, - frequency_penalty=0, - presence_penalty=0, - n=1, - ) - model_with_tools = model.bind_tools([calculator]) - model_with_tools.invoke("What is 3 * 12", config={"callbacks": [cast(BaseCallbackHandler, handler)]}) - - spans = memory_logger.pop() - root_span_id = spans[0]["span_id"] - - assert_matches_object( - spans, - [ - { - "span_id": root_span_id, - "root_span_id": root_span_id, - "span_attributes": { - "name": "ChatOpenAI", - "type": "llm", - }, - "input": [ - [ - { - "content": ANY, # User query - "additional_kwargs": {}, - "response_metadata": {}, - "type": "human", - "name": None, - "id": None, - "example": ANY, - } - ] - ], - "metadata": { - "tags": [], - "model": "gpt-4o-mini-2024-07-18", - "invocation_params": { - "tools": [ - { - "type": "function", - "function": { - "name": "calculator", - "description": "Can perform mathematical operations.", - "parameters": ANY, # Complex JSON schema - }, - } - ], - }, - }, - "output": { - "generations": [ - [ - { - "generation_info": ANY, - "type": "ChatGeneration", - "message": { - "content": ANY, # May be empty for tool calls - "type": "ai", - "additional_kwargs": { - "tool_calls": ANY, # Tool call details - }, - "response_metadata": ANY, - "name": None, - "id": ANY, - }, - } - ] - ], - "llm_output": { - "token_usage": { - "completion_tokens": ANY, - "prompt_tokens": ANY, - "total_tokens": ANY, - }, - "model_name": "gpt-4o-mini-2024-07-18", - }, - "run": None, - "type": "LLMResult", - }, - "metrics": { - "start": ANY, - "total_tokens": ANY, - "prompt_tokens": ANY, - "completion_tokens": ANY, - "end": ANY, - }, - } - ], - ) - - -@pytest.mark.vcr -@pytest.mark.skip(reason="Not yet working with VCR.") -def test_parallel_execution(logger_memory_logger: LoggerMemoryLogger): - logger, memory_logger = logger_memory_logger - assert not memory_logger.pop() - - handler = BraintrustCallbackHandler(logger=logger) - - model = ChatOpenAI( - model="gpt-4o-mini", - temperature=1, - top_p=1, - frequency_penalty=0, - presence_penalty=0, - n=1, - ) - - joke_chain = PromptTemplate.from_template("Tell me a joke about {topic}").pipe(model) - poem_chain = PromptTemplate.from_template("write a 2-line poem about {topic}").pipe(model) - - map_chain = RunnableMap( - { - "joke": joke_chain, - "poem": poem_chain, - } - ) - - map_chain.invoke({"topic": "bear"}, config={"callbacks": [cast(BaseCallbackHandler, handler)]}) - - spans = cast(List[Span], memory_logger.pop()) - - # Find the LLM spans - llm_spans = find_spans_by_attributes(spans, name="ChatOpenAI") - assert len(llm_spans) == 2 - - # Verify both LLM spans have expected structure - for span in llm_spans: - assert_matches_object( - span, - { - "span_attributes": {"name": "ChatOpenAI", "type": "llm"}, - "metadata": { - "tags": ["seq:step:2"], - "model": "gpt-4o-mini-2024-07-18", - }, - "input": [ - [ - { - "content": ANY, # Prompt about bears - "additional_kwargs": {}, - "response_metadata": {}, - "type": "human", - } - ] - ], - "output": { - "generations": [ - [ - { - "text": ANY, # Generated joke or poem - "generation_info": ANY, - "type": "ChatGeneration", - "message": { - "content": ANY, - "type": "ai", - }, - } - ] - ], - "llm_output": { - "token_usage": { - "completion_tokens": ANY, - "prompt_tokens": ANY, - "total_tokens": ANY, - }, - "model_name": "gpt-4o-mini-2024-07-18", - }, - "type": "LLMResult", - }, - "metrics": { - "start": ANY, - "total_tokens": ANY, - "prompt_tokens": ANY, - "completion_tokens": ANY, - "end": ANY, - }, - }, - ) - - -@pytest.mark.vcr -def test_langgraph_state_management(logger_memory_logger: LoggerMemoryLogger): - logger, memory_logger = logger_memory_logger - assert not memory_logger.pop() - - try: - from langgraph.graph import END, START, StateGraph - except ImportError: - pytest.skip("langgraph not installed") - - handler = BraintrustCallbackHandler(logger=logger) - model = ChatOpenAI( - model="gpt-4o-mini", - temperature=1, - top_p=1, - frequency_penalty=0, - presence_penalty=0, - n=1, - ) - - def say_hello(state: Dict[str, str]): - response = model.invoke("Say hello") - return cast(Union[str, List[str], Dict[str, str]], response.content) - - def say_bye(state: Dict[str, str]): - print("From the 'sayBye' node: Bye world!") - return "Bye" - - workflow = ( - StateGraph(state_schema=Dict[str, str]) - .add_node("sayHello", say_hello) - .add_node("sayBye", say_bye) - .add_edge(START, "sayHello") - .add_edge("sayHello", "sayBye") - .add_edge("sayBye", END) - ) - - graph = workflow.compile() - graph.invoke({}, config={"callbacks": [handler]}) - - spans = memory_logger.pop() - - # Find spans by name - langgraph doesn't guarantee ordering - langgraph_spans = find_spans_by_attributes(spans, name="LangGraph") - say_hello_spans = find_spans_by_attributes(spans, name="sayHello") - say_bye_spans = find_spans_by_attributes(spans, name="sayBye") - llm_spans = find_spans_by_attributes(spans, name="ChatOpenAI") - - # Verify we have the expected spans - assert len(langgraph_spans) == 1 - assert len(say_hello_spans) == 1 - assert len(say_bye_spans) == 1 - assert len(llm_spans) == 1 - - # Verify LangGraph root span - assert_matches_object( - langgraph_spans[0], - { - "span_attributes": { - "name": "LangGraph", - "type": "task", - }, - "input": {}, - "metadata": { - "tags": [], - }, - "output": "Bye", - }, - ) - - # Verify sayHello span - assert_matches_object( - say_hello_spans[0], - { - "span_attributes": { - "name": "sayHello", - }, - "input": {}, - "metadata": { - "tags": ["graph:step:1"], - }, - "output": ANY, # String greeting from LLM - }, - ) - - # Verify ChatOpenAI span - assert_matches_object( - llm_spans[0], - { - "span_attributes": { - "name": "ChatOpenAI", - "type": "llm", - }, - "input": [ - [ - { - "content": ANY, # "Say hello" prompt - "additional_kwargs": {}, - "response_metadata": {}, - "type": "human", - "name": None, - "id": None, - "example": ANY, - } - ] - ], - "metadata": { - "model": "gpt-4o-mini-2024-07-18", - "tags": [], - }, - "output": { - "generations": [ - [ - { - "text": ANY, # Greeting text - "generation_info": ANY, - "type": "ChatGeneration", - "message": { - "content": ANY, - "additional_kwargs": ANY, - "response_metadata": ANY, - "type": "ai", - "name": None, - "id": ANY, - }, - } - ] - ], - "llm_output": { - "token_usage": { - "completion_tokens": ANY, - "prompt_tokens": ANY, - "total_tokens": ANY, - }, - "model_name": "gpt-4o-mini-2024-07-18", - }, - "run": None, - "type": "LLMResult", - }, - "metrics": { - "start": ANY, - "total_tokens": ANY, - "prompt_tokens": ANY, - "completion_tokens": ANY, - "end": ANY, - }, - }, - ) - - # Verify sayBye span - assert_matches_object( - say_bye_spans[0], - { - "span_attributes": { - "name": "sayBye", - }, - "input": ANY, # String from previous step - "metadata": { - "tags": ["graph:step:2"], - }, - "output": "Bye", - }, - ) - - -@pytest.mark.vcr -def test_chain_null_values(logger_memory_logger: LoggerMemoryLogger): - logger, memory_logger = logger_memory_logger - assert not memory_logger.pop() - - handler = BraintrustCallbackHandler(logger=logger) - - run_id = uuid.UUID("f81d4fae-7dec-11d0-a765-00a0c91e6bf6") - - handler.on_chain_start( - {"id": ["TestChain"], "lc": 1, "type": "not_implemented"}, - {"input1": "value1", "input2": None, "input3": None}, - run_id=run_id, - parent_run_id=None, - tags=["test"], - ) - - handler.on_chain_end( - {"output1": "value1", "output2": None, "output3": None}, - run_id=run_id, - parent_run_id=None, - tags=["test"], - ) - - flush() - - spans = memory_logger.pop() - root_span_id = spans[0]["span_id"] - - assert_matches_object( - spans, - [ - { - "root_span_id": root_span_id, - "span_attributes": { - "name": "TestChain", - "type": "task", - }, - "input": { - "input1": "value1", - "input2": None, - "input3": None, - }, - "metadata": { - "tags": ["test"], - }, - "output": { - "output1": "value1", - "output2": None, - "output3": None, - }, - }, - ], - ) - - -def test_consecutive_eval_calls(logger_memory_logger: LoggerMemoryLogger): - from braintrust import Eval - - logger, memory_logger = logger_memory_logger - assert not memory_logger.pop() - - def task_fn(input, hooks): - # Create handler that will log LangChain spans - handler = BraintrustCallbackHandler(logger=logger) - - # Simulate LangChain chain execution by manually triggering callbacks - run_id = uuid.uuid4() - - handler.on_chain_start( - {"id": ["RunnableSequence"], "lc": 1, "type": "not_implemented"}, - {"number": str(input)}, - run_id=run_id, - parent_run_id=None, - ) - - # Simulate output - output = f"Result for {input}" - - handler.on_chain_end( - {"content": output}, - run_id=run_id, - parent_run_id=None, - ) - - return output - - # Create a parent span to hold the eval - with logger.start_span(name="test-consecutive-eval", span_attributes={"type": "eval"}) as parent_span: - # Run Eval with consecutive calls using parent parameter - Eval( - "test-consecutive-eval", - data=[{"input": 1, "expected": "Result for 1"}, {"input": 2, "expected": "Result for 2"}], - task=task_fn, - scores=[], - parent=parent_span.id, - ) - - flush() - - spans = memory_logger.pop() - - # Verify we have the expected number of spans: - # 1 root eval span + 2 eval dataset record spans + 2 task spans = 5 total - assert len(spans) == 5, f"Expected 5 spans, got {len(spans)}" - - # Find the root eval span - root_eval_span = [s for s in spans if s.get("span_attributes", {}).get("name") == "test-consecutive-eval"][0] - root_eval_span_id = root_eval_span["span_id"] - - # Find the eval dataset record spans (direct children of root eval span) - eval_record_spans = [ - s - for s in spans - if s.get("span_attributes", {}).get("name") == "eval" and root_eval_span_id in (s.get("span_parents") or []) - ] - assert len(eval_record_spans) == 2, f"Expected 2 eval record spans, got {len(eval_record_spans)}" - - # Sort by input - eval_record_spans_sorted = sorted(eval_record_spans, key=lambda s: s.get("input", 0)) - eval_record_1 = eval_record_spans_sorted[0] - eval_record_2 = eval_record_spans_sorted[1] - - # Find the task spans (children of eval record spans) - task_spans = [s for s in spans if s.get("span_attributes", {}).get("name") == "task"] - assert len(task_spans) == 2, f"Expected 2 task spans, got {len(task_spans)}" - - # Sort by input - task_spans_sorted = sorted(task_spans, key=lambda s: s.get("input", 0)) - task_1_span = task_spans_sorted[0] - task_2_span = task_spans_sorted[1] - - # Verify root eval span structure - assert_matches_object( - [root_eval_span], - [ - { - "span_id": root_eval_span_id, - "root_span_id": root_eval_span_id, - "span_attributes": { - "name": "test-consecutive-eval", - "type": "eval", - }, - } - ], - ) - - # Verify eval record 1 structure - assert_matches_object( - [eval_record_1], - [ - { - "root_span_id": root_eval_span_id, - "span_parents": [root_eval_span_id], - "span_attributes": { - "name": "eval", - }, - "input": 1, - "output": "Result for 1", - } - ], - ) - - # Verify eval record 2 structure - assert_matches_object( - [eval_record_2], - [ - { - "root_span_id": root_eval_span_id, - "span_parents": [root_eval_span_id], - "span_attributes": { - "name": "eval", - }, - "input": 2, - "output": "Result for 2", - } - ], - ) - - # Verify task 1 is child of eval record 1 - assert_matches_object( - [task_1_span], - [ - { - "root_span_id": root_eval_span_id, - "span_parents": [eval_record_1["span_id"]], - "span_attributes": { - "name": "task", - }, - "input": 1, - "output": "Result for 1", - } - ], - ) - - # Verify task 2 is child of eval record 2 - assert_matches_object( - [task_2_span], - [ - { - "root_span_id": root_eval_span_id, - "span_parents": [eval_record_2["span_id"]], - "span_attributes": { - "name": "task", - }, - "input": 2, - "output": "Result for 2", - } - ], - ) - - # Note: In this simplified test, we manually trigger LangChain callbacks but they don't - # create actual RunnableSequence spans in the logger. The key verification is that Eval() - # creates the proper hierarchy: root eval -> eval records -> tasks, and that consecutive - # calls work correctly with proper parent-child relationships. - # Real LangChain span integration is tested in other tests (test_llm_calls, etc.) - - -@pytest.mark.vcr -def test_streaming_ttft(logger_memory_logger: LoggerMemoryLogger): - logger, memory_logger = logger_memory_logger - assert not memory_logger.pop() - - handler = BraintrustCallbackHandler(logger=logger) - prompt = ChatPromptTemplate.from_template("Count from 1 to 5.") - model = ChatOpenAI( - model="gpt-4o-mini", - max_completion_tokens=50, - streaming=True, - ) - chain: RunnableSerializable[Dict[str, str], BaseMessage] = prompt.pipe(model) - - # Collect chunks to verify streaming works - chunks: List[str] = [] - for chunk in chain.stream({}, config={"callbacks": [cast(BaseCallbackHandler, handler)]}): - if chunk.content: - chunks.append(str(chunk.content)) - - # Verify we got streaming chunks - assert len(chunks) > 0, "Expected to receive streaming chunks" - - spans = memory_logger.pop() - assert len(spans) == 3 - - # Find the LLM span - llm_spans = find_spans_by_attributes(spans, name="ChatOpenAI", type="llm") - assert len(llm_spans) == 1 - llm_span = llm_spans[0] - - # Verify the span structure matches expectations - assert_matches_object( - [llm_span], - [ - { - "id": ANY, - "input": [ - [ - { - "additional_kwargs": {}, - "content": "Count from 1 to 5.", - "example": False, - "id": None, - "name": None, - "response_metadata": {}, - "type": "human", - } - ] - ], - "metadata": { - "braintrust": { - "integration_name": "langchain-py", - } - }, - "metrics": { - "time_to_first_token": ANY, - }, - "output": { - "generations": [ - [ - { - "generation_info": { - "finish_reason": "stop", - "model_name": ANY, - }, - "message": { - "content": "1, 2, 3, 4, 5.", - "type": "AIMessageChunk", - }, - "text": "1, 2, 3, 4, 5.", - "type": "ChatGenerationChunk", - } - ] - ], - "type": "LLMResult", - }, - "project_id": "langchain-py", - "span_attributes": {"name": "ChatOpenAI", "type": "llm"}, - } - ], - ) - - -@pytest.mark.vcr -def test_prompt_caching_tokens(logger_memory_logger: LoggerMemoryLogger): - logger, memory_logger = logger_memory_logger - assert not memory_logger.pop() - - handler = BraintrustCallbackHandler(logger=logger) - - model = ChatAnthropic(model="claude-sonnet-4-5-20250929") - - # XXX: if you need to change the cassette or test, you'll want to change the text below to invalidate the stored cache. - - # Anthropic prompt caching requires a minimum of 1024 tokens for Claude Sonnet models. - # This static text (~1500 tokens) ensures we meet that threshold consistently. - # See: https://platform.claude.com/docs/en/build-with-claude/prompt-caching - long_text_for_caching = """ -# Comprehensive Guide to Software Testing Methods! - -## Chapter 1: Introduction to Testing - -Software testing is a critical component of the software development lifecycle. It ensures that applications -function correctly, meet requirements, and provide a positive user experience. This guide covers various -testing methodologies, best practices, and tools used in modern software development. - -### 1.1 The Importance of Testing - -Testing helps identify defects early in the development process, reducing the cost of fixing issues later. -Studies have shown that the cost of fixing a bug increases exponentially as it progresses through the -development lifecycle. A bug found during requirements gathering might cost $1 to fix, while the same bug -found in production could cost $100 or more. - -### 1.2 Types of Testing - -There are many types of testing, including: -- Unit Testing: Testing individual components or functions in isolation -- Integration Testing: Testing how components work together -- End-to-End Testing: Testing the entire application flow -- Performance Testing: Testing application speed and scalability -- Security Testing: Testing for vulnerabilities and security issues -- Usability Testing: Testing user experience and interface design - -## Chapter 2: Unit Testing Best Practices - -Unit testing focuses on testing the smallest testable parts of an application. Here are some best practices: - -### 2.1 Write Tests First (TDD) - -Test-Driven Development (TDD) is a methodology where tests are written before the actual code. The process -follows a simple cycle: Red (write a failing test), Green (write code to pass the test), Refactor (improve -the code while keeping tests passing). - -### 2.2 Keep Tests Independent - -Each test should be independent of others. Tests should not rely on the state created by previous tests. -This ensures that tests can be run in any order and that failures are isolated and easy to debug. - -### 2.3 Use Meaningful Names - -Test names should clearly describe what is being tested and what the expected outcome is. A good test name -might be "test_user_registration_with_valid_email_succeeds" rather than just "test_registration". - -### 2.4 Test Edge Cases - -Don't just test the happy path. Consider edge cases like: -- Empty inputs -- Null or undefined values -- Very large inputs -- Invalid formats -- Boundary conditions - -## Chapter 3: Integration Testing - -Integration testing verifies that different modules or services work together correctly. - -### 3.1 Database Integration - -When testing database interactions, consider using: -- Test databases separate from production -- Database transactions that roll back after each test -- Mock data that represents realistic scenarios - -### 3.2 API Integration - -API integration tests should verify: -- Correct HTTP status codes -- Response format and schema -- Error handling -- Authentication and authorization - -## Chapter 4: Performance Testing - -Performance testing ensures your application can handle expected load and scale appropriately. - -### 4.1 Load Testing - -Load testing simulates multiple users accessing the application simultaneously. Key metrics include: -- Response time under load -- Throughput (requests per second) -- Error rates -- Resource utilization (CPU, memory, network) - -### 4.2 Stress Testing - -Stress testing pushes the application beyond normal operational capacity to find breaking points and -understand how the system fails gracefully. - -## Chapter 5: Continuous Integration and Testing - -Modern development practices integrate testing into the CI/CD pipeline. - -### 5.1 Automated Test Runs - -Tests should run automatically on every code change. This includes: -- Running unit tests on every commit -- Running integration tests on pull requests -- Running end-to-end tests before deployment - -### 5.2 Test Coverage - -Test coverage metrics help identify untested code. While 100% coverage isn't always practical or necessary, -maintaining good coverage helps ensure code quality. Focus on critical paths and business logic. - -## Chapter 6: Testing Tools and Frameworks - -Many tools exist to support testing efforts: - -### 6.1 Python Testing -- pytest: Feature-rich testing framework -- unittest: Built-in Python testing module -- mock: Library for mocking objects - -### 6.2 JavaScript Testing -- Jest: Popular testing framework -- Mocha: Flexible testing framework -- Cypress: End-to-end testing tool - -### 6.3 Other Tools -- Selenium: Browser automation -- JMeter: Performance testing -- Postman: API testing - -## Conclusion - -Effective testing is essential for delivering high-quality software. By following best practices and using -appropriate tools, teams can catch bugs early, improve code quality, and deliver better products to users. - -Remember: Testing is not just about finding bugs, it's about building confidence in your code. -""" - - messages: list[BaseMessage] = [ - SystemMessage( - content=[ - { - "type": "text", - "text": long_text_for_caching, - "cache_control": {"type": "ephemeral"}, - } - ] - ), - HumanMessage(content="What is the first type of testing mentioned in section 1.2?"), - ] - - res = model.invoke(messages, config={"callbacks": [cast(BaseCallbackHandler, handler)]}) - - spans = memory_logger.pop() - assert len(spans) > 0 - - llm_spans = find_spans_by_attributes(spans, name="ChatAnthropic", type="llm") - assert len(llm_spans) == 1 - first_span = llm_spans[0] - - assert "metrics" in first_span - first_metrics = first_span["metrics"] - assert "prompt_tokens" in first_metrics - assert first_metrics["prompt_tokens"] > 0 - - assert "prompt_cache_creation_tokens" in first_metrics - assert first_metrics["prompt_cache_creation_tokens"] > 0 - assert first_metrics["prompt_cached_tokens"] == 0 - - res = model.invoke( - messages + [res, HumanMessage(content="What testing framework is mentioned for Python?")], - config={"callbacks": [cast(BaseCallbackHandler, handler)]}, - ) - - spans = memory_logger.pop() - assert len(spans) > 0 - - llm_spans = find_spans_by_attributes(spans, name="ChatAnthropic", type="llm") - - print(llm_spans) - - assert len(llm_spans) == 1 - second_span = llm_spans[0] - - assert "metrics" in second_span - second_metrics = second_span["metrics"] - - assert "prompt_cached_tokens" in second_metrics - assert second_metrics["prompt_cached_tokens"] > 0 - - assert "prompt_tokens" in second_metrics - assert second_metrics["prompt_tokens"] > 0 diff --git a/integrations/langchain-py/src/tests/test_context.py b/integrations/langchain-py/src/tests/test_context.py deleted file mode 100644 index c0567396b..000000000 --- a/integrations/langchain-py/src/tests/test_context.py +++ /dev/null @@ -1,155 +0,0 @@ -# pyright: reportTypedDictNotRequiredAccess=none -from typing import Dict -from unittest.mock import ANY - -import pytest -from langchain_core.callbacks import CallbackManager -from langchain_core.messages import BaseMessage -from langchain_core.prompts import ChatPromptTemplate -from langchain_core.runnables import RunnableSerializable -from langchain_openai import ChatOpenAI - -from braintrust_langchain import BraintrustCallbackHandler, set_global_handler - -from .conftest import LoggerMemoryLogger -from .helpers import assert_matches_object - - -@pytest.mark.vcr -def test_global_handler(logger_memory_logger: LoggerMemoryLogger): - logger, memory_logger = logger_memory_logger - assert not memory_logger.pop() - - handler = BraintrustCallbackHandler(logger=logger, debug=True) - set_global_handler(handler) - - # Make sure the handler is registered in the LangChain library - manager = CallbackManager.configure() - assert next((h for h in manager.handlers if isinstance(h, BraintrustCallbackHandler)), None) == handler - - # Here's what a typical user would do - prompt = ChatPromptTemplate.from_template("What is 1 + {number}?") - model = ChatOpenAI( - model="gpt-4o-mini", - temperature=1, - top_p=1, - frequency_penalty=0, - presence_penalty=0, - n=1, - ) - chain: RunnableSerializable[Dict[str, str], BaseMessage] = prompt.pipe(model) - - message = chain.invoke({"number": "2"}) - - spans = memory_logger.pop() - assert len(spans) > 0 - - root_span_id = spans[0]["span_id"] - - # Spans would be empty if the handler was not registered, let's make sure it logged what we expect - assert_matches_object( - spans, - [ - { - "span_attributes": { - "name": "RunnableSequence", - "type": "task", - }, - "input": {"number": "2"}, - "output": { - "content": ANY, # LLM response text - "additional_kwargs": ANY, - "response_metadata": ANY, - "type": "ai", - "name": ANY, - "id": ANY, - "example": ANY, - "tool_calls": ANY, - "invalid_tool_calls": ANY, - "usage_metadata": ANY, - }, - "metadata": {"tags": []}, - "span_id": root_span_id, - "root_span_id": root_span_id, - }, - { - "span_attributes": {"name": "ChatPromptTemplate"}, - "input": {"number": "2"}, - "output": { - "messages": [ - { - "content": ANY, # Formatted prompt text - "additional_kwargs": {}, - "response_metadata": {}, - "type": "human", - "name": None, - "id": None, - } - ] - }, - "metadata": {"tags": ["seq:step:1"]}, - "root_span_id": root_span_id, - "span_parents": [root_span_id], - }, - { - "span_attributes": {"name": "ChatOpenAI", "type": "llm"}, - "input": [ - [ - { - "content": ANY, # Prompt message content - "additional_kwargs": {}, - "response_metadata": {}, - "type": "human", - "name": None, - "id": None, - "example": ANY, - } - ] - ], - "output": { - "generations": [ - [ - { - "text": ANY, # Generated text - "generation_info": ANY, - "type": "ChatGeneration", - "message": { - "content": ANY, # Message content - "additional_kwargs": ANY, - "response_metadata": ANY, - "type": "ai", - "name": None, - "id": ANY, - }, - } - ] - ], - "llm_output": { - "token_usage": { - "completion_tokens": ANY, - "prompt_tokens": ANY, - "total_tokens": ANY, - }, - "model_name": "gpt-4o-mini-2024-07-18", - }, - "run": None, - "type": "LLMResult", - }, - "metrics": { - "start": ANY, - "total_tokens": ANY, - "prompt_tokens": ANY, - "completion_tokens": ANY, - "end": ANY, - }, - "metadata": { - "tags": ["seq:step:2"], - "model": "gpt-4o-mini-2024-07-18", - }, - "root_span_id": root_span_id, - "span_parents": [root_span_id], - }, - ], - ) - - assert message.content == "1 + 2 equals 3." diff --git a/integrations/langchain-py/src/tests/types.py b/integrations/langchain-py/src/tests/types.py deleted file mode 100644 index 77b03ef52..000000000 --- a/integrations/langchain-py/src/tests/types.py +++ /dev/null @@ -1,33 +0,0 @@ -from typing import Any, List, Optional, TypedDict - - -class SpanAttributes(TypedDict): - name: str - type: Optional[str] - - -class SpanMetadata(TypedDict, total=False): - tags: List[str] - model: str - temperature: float - top_p: float - frequency_penalty: float - presence_penalty: float - n: int - runId: Optional[str] - - -class SpanRequired(TypedDict): - span_id: str - - -class Span(SpanRequired, total=False): - span_attributes: SpanAttributes - input: Any - output: Any - span_parents: Optional[List[str]] - metadata: SpanMetadata - - -class LogRequest(TypedDict): - rows: List[Span] diff --git a/integrations/langchain-py/uv.lock b/integrations/langchain-py/uv.lock deleted file mode 100644 index 933610878..000000000 --- a/integrations/langchain-py/uv.lock +++ /dev/null @@ -1,2593 +0,0 @@ -version = 1 -revision = 2 -requires-python = ">=3.10" -resolution-markers = [ - "platform_python_implementation != 'PyPy'", - "platform_python_implementation == 'PyPy'", -] - -[[package]] -name = "annotated-types" -version = "0.7.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" }, -] - -[[package]] -name = "anthropic" -version = "0.76.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "distro" }, - { name = "docstring-parser" }, - { name = "httpx" }, - { name = "jiter" }, - { name = "pydantic" }, - { name = "sniffio" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/6e/be/d11abafaa15d6304826438170f7574d750218f49a106c54424a40cef4494/anthropic-0.76.0.tar.gz", hash = "sha256:e0cae6a368986d5cf6df743dfbb1b9519e6a9eee9c6c942ad8121c0b34416ffe", size = 495483, upload-time = "2026-01-13T18:41:14.908Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e5/70/7b0fd9c1a738f59d3babe2b4212031c34ab7d0fda4ffef15b58a55c5bcea/anthropic-0.76.0-py3-none-any.whl", hash = "sha256:81efa3113901192af2f0fe977d3ec73fdadb1e691586306c4256cd6d5ccc331c", size = 390309, upload-time = "2026-01-13T18:41:13.483Z" }, -] - -[[package]] -name = "anyio" -version = "4.10.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "exceptiongroup", marker = "python_full_version < '3.11'" }, - { name = "idna" }, - { name = "sniffio" }, - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/f1/b4/636b3b65173d3ce9a38ef5f0522789614e590dab6a8d505340a4efe4c567/anyio-4.10.0.tar.gz", hash = "sha256:3f3fae35c96039744587aa5b8371e7e8e603c0702999535961dd336026973ba6", size = 213252, upload-time = "2025-08-04T08:54:26.451Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/6f/12/e5e0282d673bb9746bacfb6e2dba8719989d3660cdb2ea79aee9a9651afb/anyio-4.10.0-py3-none-any.whl", hash = "sha256:60e474ac86736bbfd6f210f7a61218939c318f43f9972497381f1c5e930ed3d1", size = 107213, upload-time = "2025-08-04T08:54:24.882Z" }, -] - -[[package]] -name = "async-timeout" -version = "4.0.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/87/d6/21b30a550dafea84b1b8eee21b5e23fa16d010ae006011221f33dcd8d7f8/async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f", size = 8345, upload-time = "2023-08-10T16:35:56.907Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a7/fa/e01228c2938de91d47b307831c62ab9e4001e747789d0b05baf779a6488c/async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028", size = 5721, upload-time = "2023-08-10T16:35:55.203Z" }, -] - -[[package]] -name = "backports-asyncio-runner" -version = "1.2.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/8e/ff/70dca7d7cb1cbc0edb2c6cc0c38b65cba36cccc491eca64cabd5fe7f8670/backports_asyncio_runner-1.2.0.tar.gz", hash = "sha256:a5aa7b2b7d8f8bfcaa2b57313f70792df84e32a2a746f585213373f900b42162", size = 69893, upload-time = "2025-07-02T02:27:15.685Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a0/59/76ab57e3fe74484f48a53f8e337171b4a2349e506eabe136d7e01d059086/backports_asyncio_runner-1.2.0-py3-none-any.whl", hash = "sha256:0da0a936a8aeb554eccb426dc55af3ba63bcdc69fa1a600b5bb305413a4477b5", size = 12313, upload-time = "2025-07-02T02:27:14.263Z" }, -] - -[[package]] -name = "backports-tarfile" -version = "1.2.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/86/72/cd9b395f25e290e633655a100af28cb253e4393396264a98bd5f5951d50f/backports_tarfile-1.2.0.tar.gz", hash = "sha256:d75e02c268746e1b8144c278978b6e98e85de6ad16f8e4b0844a154557eca991", size = 86406, upload-time = "2024-05-28T17:01:54.731Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b9/fa/123043af240e49752f1c4bd24da5053b6bd00cad78c2be53c0d1e8b975bc/backports.tarfile-1.2.0-py3-none-any.whl", hash = "sha256:77e284d754527b01fb1e6fa8a1afe577858ebe4e9dad8919e34c862cb399bc34", size = 30181, upload-time = "2024-05-28T17:01:53.112Z" }, -] - -[[package]] -name = "black" -version = "25.9.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "click" }, - { name = "mypy-extensions" }, - { name = "packaging" }, - { name = "pathspec" }, - { name = "platformdirs" }, - { name = "pytokens" }, - { name = "tomli", marker = "python_full_version < '3.11'" }, - { name = "typing-extensions", marker = "python_full_version < '3.11'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/4b/43/20b5c90612d7bdb2bdbcceeb53d588acca3bb8f0e4c5d5c751a2c8fdd55a/black-25.9.0.tar.gz", hash = "sha256:0474bca9a0dd1b51791fcc507a4e02078a1c63f6d4e4ae5544b9848c7adfb619", size = 648393, upload-time = "2025-09-19T00:27:37.758Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/25/40/dbe31fc56b218a858c8fc6f5d8d3ba61c1fa7e989d43d4a4574b8b992840/black-25.9.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ce41ed2614b706fd55fd0b4a6909d06b5bab344ffbfadc6ef34ae50adba3d4f7", size = 1715605, upload-time = "2025-09-19T00:36:13.483Z" }, - { url = "https://files.pythonhosted.org/packages/92/b2/f46800621200eab6479b1f4c0e3ede5b4c06b768e79ee228bc80270bcc74/black-25.9.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2ab0ce111ef026790e9b13bd216fa7bc48edd934ffc4cbf78808b235793cbc92", size = 1571829, upload-time = "2025-09-19T00:32:42.13Z" }, - { url = "https://files.pythonhosted.org/packages/4e/64/5c7f66bd65af5c19b4ea86062bb585adc28d51d37babf70969e804dbd5c2/black-25.9.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:f96b6726d690c96c60ba682955199f8c39abc1ae0c3a494a9c62c0184049a713", size = 1631888, upload-time = "2025-09-19T00:30:54.212Z" }, - { url = "https://files.pythonhosted.org/packages/3b/64/0b9e5bfcf67db25a6eef6d9be6726499a8a72ebab3888c2de135190853d3/black-25.9.0-cp310-cp310-win_amd64.whl", hash = "sha256:d119957b37cc641596063cd7db2656c5be3752ac17877017b2ffcdb9dfc4d2b1", size = 1327056, upload-time = "2025-09-19T00:31:08.877Z" }, - { url = "https://files.pythonhosted.org/packages/b7/f4/7531d4a336d2d4ac6cc101662184c8e7d068b548d35d874415ed9f4116ef/black-25.9.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:456386fe87bad41b806d53c062e2974615825c7a52159cde7ccaeb0695fa28fa", size = 1698727, upload-time = "2025-09-19T00:31:14.264Z" }, - { url = "https://files.pythonhosted.org/packages/28/f9/66f26bfbbf84b949cc77a41a43e138d83b109502cd9c52dfc94070ca51f2/black-25.9.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a16b14a44c1af60a210d8da28e108e13e75a284bf21a9afa6b4571f96ab8bb9d", size = 1555679, upload-time = "2025-09-19T00:31:29.265Z" }, - { url = "https://files.pythonhosted.org/packages/bf/59/61475115906052f415f518a648a9ac679d7afbc8da1c16f8fdf68a8cebed/black-25.9.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:aaf319612536d502fdd0e88ce52d8f1352b2c0a955cc2798f79eeca9d3af0608", size = 1617453, upload-time = "2025-09-19T00:30:42.24Z" }, - { url = "https://files.pythonhosted.org/packages/7f/5b/20fd5c884d14550c911e4fb1b0dae00d4abb60a4f3876b449c4d3a9141d5/black-25.9.0-cp311-cp311-win_amd64.whl", hash = "sha256:c0372a93e16b3954208417bfe448e09b0de5cc721d521866cd9e0acac3c04a1f", size = 1333655, upload-time = "2025-09-19T00:30:56.715Z" }, - { url = "https://files.pythonhosted.org/packages/fb/8e/319cfe6c82f7e2d5bfb4d3353c6cc85b523d677ff59edc61fdb9ee275234/black-25.9.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:1b9dc70c21ef8b43248f1d86aedd2aaf75ae110b958a7909ad8463c4aa0880b0", size = 1742012, upload-time = "2025-09-19T00:33:08.678Z" }, - { url = "https://files.pythonhosted.org/packages/94/cc/f562fe5d0a40cd2a4e6ae3f685e4c36e365b1f7e494af99c26ff7f28117f/black-25.9.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8e46eecf65a095fa62e53245ae2795c90bdecabd53b50c448d0a8bcd0d2e74c4", size = 1581421, upload-time = "2025-09-19T00:35:25.937Z" }, - { url = "https://files.pythonhosted.org/packages/84/67/6db6dff1ebc8965fd7661498aea0da5d7301074b85bba8606a28f47ede4d/black-25.9.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9101ee58ddc2442199a25cb648d46ba22cd580b00ca4b44234a324e3ec7a0f7e", size = 1655619, upload-time = "2025-09-19T00:30:49.241Z" }, - { url = "https://files.pythonhosted.org/packages/10/10/3faef9aa2a730306cf469d76f7f155a8cc1f66e74781298df0ba31f8b4c8/black-25.9.0-cp312-cp312-win_amd64.whl", hash = "sha256:77e7060a00c5ec4b3367c55f39cf9b06e68965a4f2e61cecacd6d0d9b7ec945a", size = 1342481, upload-time = "2025-09-19T00:31:29.625Z" }, - { url = "https://files.pythonhosted.org/packages/48/99/3acfea65f5e79f45472c45f87ec13037b506522719cd9d4ac86484ff51ac/black-25.9.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:0172a012f725b792c358d57fe7b6b6e8e67375dd157f64fa7a3097b3ed3e2175", size = 1742165, upload-time = "2025-09-19T00:34:10.402Z" }, - { url = "https://files.pythonhosted.org/packages/3a/18/799285282c8236a79f25d590f0222dbd6850e14b060dfaa3e720241fd772/black-25.9.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:3bec74ee60f8dfef564b573a96b8930f7b6a538e846123d5ad77ba14a8d7a64f", size = 1581259, upload-time = "2025-09-19T00:32:49.685Z" }, - { url = "https://files.pythonhosted.org/packages/f1/ce/883ec4b6303acdeca93ee06b7622f1fa383c6b3765294824165d49b1a86b/black-25.9.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b756fc75871cb1bcac5499552d771822fd9db5a2bb8db2a7247936ca48f39831", size = 1655583, upload-time = "2025-09-19T00:30:44.505Z" }, - { url = "https://files.pythonhosted.org/packages/21/17/5c253aa80a0639ccc427a5c7144534b661505ae2b5a10b77ebe13fa25334/black-25.9.0-cp313-cp313-win_amd64.whl", hash = "sha256:846d58e3ce7879ec1ffe816bb9df6d006cd9590515ed5d17db14e17666b2b357", size = 1343428, upload-time = "2025-09-19T00:32:13.839Z" }, - { url = "https://files.pythonhosted.org/packages/1b/46/863c90dcd3f9d41b109b7f19032ae0db021f0b2a81482ba0a1e28c84de86/black-25.9.0-py3-none-any.whl", hash = "sha256:474b34c1342cdc157d307b56c4c65bce916480c4a8f6551fdc6bf9b486a7c4ae", size = 203363, upload-time = "2025-09-19T00:27:35.724Z" }, -] - -[[package]] -name = "braintrust" -version = "0.2.9" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "chevron" }, - { name = "exceptiongroup" }, - { name = "gitpython" }, - { name = "python-dotenv" }, - { name = "python-slugify" }, - { name = "requests" }, - { name = "sseclient-py" }, - { name = "tqdm" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/32/40/d9931b0233f36fcf41316941022c44e8664d97a2ea6e8b973dee4ebf0749/braintrust-0.2.9.tar.gz", hash = "sha256:6874ab7aae8f9463c63ae8297927995f745807e2aed25c90f4c28dd11a5a90b6", size = 185157, upload-time = "2025-09-22T23:28:01.975Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/39/31/8a5e6534b53bf0a2e81ec008cce6d8e1cccd53912c404c008214b29684f5/braintrust-0.2.9-py3-none-any.whl", hash = "sha256:b0b9c50900f6cc44d997b58f33f3f1e4f2cd82e40f4557a625156bd31d042c78", size = 214728, upload-time = "2025-09-22T23:28:00.415Z" }, -] - -[[package]] -name = "braintrust-langchain" -version = "0.2.1" -source = { editable = "." } -dependencies = [ - { name = "braintrust" }, - { name = "langchain" }, -] - -[package.dev-dependencies] -dev = [ - { name = "black" }, - { name = "build" }, - { name = "flake8" }, - { name = "flake8-isort" }, - { name = "httpx" }, - { name = "isort" }, - { name = "langchain-anthropic" }, - { name = "langchain-openai" }, - { name = "langgraph" }, - { name = "pre-commit" }, - { name = "pytest" }, - { name = "pytest-asyncio" }, - { name = "pytest-vcr" }, - { name = "ruff" }, - { name = "tenacity" }, - { name = "twine" }, -] - -[package.metadata] -requires-dist = [ - { name = "braintrust", specifier = ">=0.2.1" }, - { name = "langchain", specifier = ">=0.3.27" }, -] - -[package.metadata.requires-dev] -dev = [ - { name = "black" }, - { name = "build" }, - { name = "flake8" }, - { name = "flake8-isort" }, - { name = "httpx" }, - { name = "isort", specifier = "==5.12.0" }, - { name = "langchain-anthropic", specifier = ">=0.3.20" }, - { name = "langchain-openai" }, - { name = "langgraph", specifier = ">=0.2.1,<0.4.0" }, - { name = "pre-commit" }, - { name = "pytest" }, - { name = "pytest-asyncio", specifier = ">=1.1.0" }, - { name = "pytest-vcr", specifier = ">=1.0.2" }, - { name = "ruff" }, - { name = "tenacity" }, - { name = "twine" }, -] - -[[package]] -name = "build" -version = "1.3.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "colorama", marker = "os_name == 'nt'" }, - { name = "importlib-metadata", marker = "python_full_version < '3.10.2'" }, - { name = "packaging" }, - { name = "pyproject-hooks" }, - { name = "tomli", marker = "python_full_version < '3.11'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/25/1c/23e33405a7c9eac261dff640926b8b5adaed6a6eb3e1767d441ed611d0c0/build-1.3.0.tar.gz", hash = "sha256:698edd0ea270bde950f53aed21f3a0135672206f3911e0176261a31e0e07b397", size = 48544, upload-time = "2025-08-01T21:27:09.268Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/cb/8c/2b30c12155ad8de0cf641d76a8b396a16d2c36bc6d50b621a62b7c4567c1/build-1.3.0-py3-none-any.whl", hash = "sha256:7145f0b5061ba90a1500d60bd1b13ca0a8a4cebdd0cc16ed8adf1c0e739f43b4", size = 23382, upload-time = "2025-08-01T21:27:07.844Z" }, -] - -[[package]] -name = "certifi" -version = "2025.8.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/dc/67/960ebe6bf230a96cda2e0abcf73af550ec4f090005363542f0765df162e0/certifi-2025.8.3.tar.gz", hash = "sha256:e564105f78ded564e3ae7c923924435e1daa7463faeab5bb932bc53ffae63407", size = 162386, upload-time = "2025-08-03T03:07:47.08Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e5/48/1549795ba7742c948d2ad169c1c8cdbae65bc450d6cd753d124b17c8cd32/certifi-2025.8.3-py3-none-any.whl", hash = "sha256:f6c12493cfb1b06ba2ff328595af9350c65d6644968e5d3a2ffd78699af217a5", size = 161216, upload-time = "2025-08-03T03:07:45.777Z" }, -] - -[[package]] -name = "cffi" -version = "2.0.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "pycparser", marker = "implementation_name != 'PyPy' and platform_python_implementation != 'PyPy'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/eb/56/b1ba7935a17738ae8453301356628e8147c79dbb825bcbc73dc7401f9846/cffi-2.0.0.tar.gz", hash = "sha256:44d1b5909021139fe36001ae048dbdde8214afa20200eda0f64c068cac5d5529", size = 523588, upload-time = "2025-09-08T23:24:04.541Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/50/bd/b1a6362b80628111e6653c961f987faa55262b4002fcec42308cad1db680/cffi-2.0.0-cp310-cp310-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:53f77cbe57044e88bbd5ed26ac1d0514d2acf0591dd6bb02a3ae37f76811b80c", size = 208811, upload-time = "2025-09-08T23:22:12.267Z" }, - { url = "https://files.pythonhosted.org/packages/4f/27/6933a8b2562d7bd1fb595074cf99cc81fc3789f6a6c05cdabb46284a3188/cffi-2.0.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:3e837e369566884707ddaf85fc1744b47575005c0a229de3327f8f9a20f4efeb", size = 216402, upload-time = "2025-09-08T23:22:13.455Z" }, - { url = "https://files.pythonhosted.org/packages/05/eb/b86f2a2645b62adcfff53b0dd97e8dfafb5c8aa864bd0d9a2c2049a0d551/cffi-2.0.0-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:5eda85d6d1879e692d546a078b44251cdd08dd1cfb98dfb77b670c97cee49ea0", size = 203217, upload-time = "2025-09-08T23:22:14.596Z" }, - { url = "https://files.pythonhosted.org/packages/9f/e0/6cbe77a53acf5acc7c08cc186c9928864bd7c005f9efd0d126884858a5fe/cffi-2.0.0-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:9332088d75dc3241c702d852d4671613136d90fa6881da7d770a483fd05248b4", size = 203079, upload-time = "2025-09-08T23:22:15.769Z" }, - { url = "https://files.pythonhosted.org/packages/98/29/9b366e70e243eb3d14a5cb488dfd3a0b6b2f1fb001a203f653b93ccfac88/cffi-2.0.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:fc7de24befaeae77ba923797c7c87834c73648a05a4bde34b3b7e5588973a453", size = 216475, upload-time = "2025-09-08T23:22:17.427Z" }, - { url = "https://files.pythonhosted.org/packages/21/7a/13b24e70d2f90a322f2900c5d8e1f14fa7e2a6b3332b7309ba7b2ba51a5a/cffi-2.0.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:cf364028c016c03078a23b503f02058f1814320a56ad535686f90565636a9495", size = 218829, upload-time = "2025-09-08T23:22:19.069Z" }, - { url = "https://files.pythonhosted.org/packages/60/99/c9dc110974c59cc981b1f5b66e1d8af8af764e00f0293266824d9c4254bc/cffi-2.0.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:e11e82b744887154b182fd3e7e8512418446501191994dbf9c9fc1f32cc8efd5", size = 211211, upload-time = "2025-09-08T23:22:20.588Z" }, - { url = "https://files.pythonhosted.org/packages/49/72/ff2d12dbf21aca1b32a40ed792ee6b40f6dc3a9cf1644bd7ef6e95e0ac5e/cffi-2.0.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:8ea985900c5c95ce9db1745f7933eeef5d314f0565b27625d9a10ec9881e1bfb", size = 218036, upload-time = "2025-09-08T23:22:22.143Z" }, - { url = "https://files.pythonhosted.org/packages/b1/b7/1200d354378ef52ec227395d95c2576330fd22a869f7a70e88e1447eb234/cffi-2.0.0-cp311-cp311-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:baf5215e0ab74c16e2dd324e8ec067ef59e41125d3eade2b863d294fd5035c92", size = 209613, upload-time = "2025-09-08T23:22:29.475Z" }, - { url = "https://files.pythonhosted.org/packages/b8/56/6033f5e86e8cc9bb629f0077ba71679508bdf54a9a5e112a3c0b91870332/cffi-2.0.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:730cacb21e1bdff3ce90babf007d0a0917cc3e6492f336c2f0134101e0944f93", size = 216476, upload-time = "2025-09-08T23:22:31.063Z" }, - { url = "https://files.pythonhosted.org/packages/dc/7f/55fecd70f7ece178db2f26128ec41430d8720f2d12ca97bf8f0a628207d5/cffi-2.0.0-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:6824f87845e3396029f3820c206e459ccc91760e8fa24422f8b0c3d1731cbec5", size = 203374, upload-time = "2025-09-08T23:22:32.507Z" }, - { url = "https://files.pythonhosted.org/packages/84/ef/a7b77c8bdc0f77adc3b46888f1ad54be8f3b7821697a7b89126e829e676a/cffi-2.0.0-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:9de40a7b0323d889cf8d23d1ef214f565ab154443c42737dfe52ff82cf857664", size = 202597, upload-time = "2025-09-08T23:22:34.132Z" }, - { url = "https://files.pythonhosted.org/packages/d7/91/500d892b2bf36529a75b77958edfcd5ad8e2ce4064ce2ecfeab2125d72d1/cffi-2.0.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:8941aaadaf67246224cee8c3803777eed332a19d909b47e29c9842ef1e79ac26", size = 215574, upload-time = "2025-09-08T23:22:35.443Z" }, - { url = "https://files.pythonhosted.org/packages/44/64/58f6255b62b101093d5df22dcb752596066c7e89dd725e0afaed242a61be/cffi-2.0.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:a05d0c237b3349096d3981b727493e22147f934b20f6f125a3eba8f994bec4a9", size = 218971, upload-time = "2025-09-08T23:22:36.805Z" }, - { url = "https://files.pythonhosted.org/packages/ab/49/fa72cebe2fd8a55fbe14956f9970fe8eb1ac59e5df042f603ef7c8ba0adc/cffi-2.0.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:94698a9c5f91f9d138526b48fe26a199609544591f859c870d477351dc7b2414", size = 211972, upload-time = "2025-09-08T23:22:38.436Z" }, - { url = "https://files.pythonhosted.org/packages/0b/28/dd0967a76aab36731b6ebfe64dec4e981aff7e0608f60c2d46b46982607d/cffi-2.0.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:5fed36fccc0612a53f1d4d9a816b50a36702c28a2aa880cb8a122b3466638743", size = 217078, upload-time = "2025-09-08T23:22:39.776Z" }, - { url = "https://files.pythonhosted.org/packages/ff/df/a4f0fbd47331ceeba3d37c2e51e9dfc9722498becbeec2bd8bc856c9538a/cffi-2.0.0-cp312-cp312-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:21d1152871b019407d8ac3985f6775c079416c282e431a4da6afe7aefd2bccbe", size = 212529, upload-time = "2025-09-08T23:22:47.349Z" }, - { url = "https://files.pythonhosted.org/packages/d5/72/12b5f8d3865bf0f87cf1404d8c374e7487dcf097a1c91c436e72e6badd83/cffi-2.0.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:b21e08af67b8a103c71a250401c78d5e0893beff75e28c53c98f4de42f774062", size = 220097, upload-time = "2025-09-08T23:22:48.677Z" }, - { url = "https://files.pythonhosted.org/packages/c2/95/7a135d52a50dfa7c882ab0ac17e8dc11cec9d55d2c18dda414c051c5e69e/cffi-2.0.0-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:1e3a615586f05fc4065a8b22b8152f0c1b00cdbc60596d187c2a74f9e3036e4e", size = 207983, upload-time = "2025-09-08T23:22:50.06Z" }, - { url = "https://files.pythonhosted.org/packages/3a/c8/15cb9ada8895957ea171c62dc78ff3e99159ee7adb13c0123c001a2546c1/cffi-2.0.0-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:81afed14892743bbe14dacb9e36d9e0e504cd204e0b165062c488942b9718037", size = 206519, upload-time = "2025-09-08T23:22:51.364Z" }, - { url = "https://files.pythonhosted.org/packages/78/2d/7fa73dfa841b5ac06c7b8855cfc18622132e365f5b81d02230333ff26e9e/cffi-2.0.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:3e17ed538242334bf70832644a32a7aae3d83b57567f9fd60a26257e992b79ba", size = 219572, upload-time = "2025-09-08T23:22:52.902Z" }, - { url = "https://files.pythonhosted.org/packages/07/e0/267e57e387b4ca276b90f0434ff88b2c2241ad72b16d31836adddfd6031b/cffi-2.0.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:3925dd22fa2b7699ed2617149842d2e6adde22b262fcbfada50e3d195e4b3a94", size = 222963, upload-time = "2025-09-08T23:22:54.518Z" }, - { url = "https://files.pythonhosted.org/packages/b6/75/1f2747525e06f53efbd878f4d03bac5b859cbc11c633d0fb81432d98a795/cffi-2.0.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:2c8f814d84194c9ea681642fd164267891702542f028a15fc97d4674b6206187", size = 221361, upload-time = "2025-09-08T23:22:55.867Z" }, - { url = "https://files.pythonhosted.org/packages/b0/1e/d22cc63332bd59b06481ceaac49d6c507598642e2230f201649058a7e704/cffi-2.0.0-cp313-cp313-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:07b271772c100085dd28b74fa0cd81c8fb1a3ba18b21e03d7c27f3436a10606b", size = 212446, upload-time = "2025-09-08T23:23:03.472Z" }, - { url = "https://files.pythonhosted.org/packages/a9/f5/a2c23eb03b61a0b8747f211eb716446c826ad66818ddc7810cc2cc19b3f2/cffi-2.0.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d48a880098c96020b02d5a1f7d9251308510ce8858940e6fa99ece33f610838b", size = 220101, upload-time = "2025-09-08T23:23:04.792Z" }, - { url = "https://files.pythonhosted.org/packages/f2/7f/e6647792fc5850d634695bc0e6ab4111ae88e89981d35ac269956605feba/cffi-2.0.0-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:f93fd8e5c8c0a4aa1f424d6173f14a892044054871c771f8566e4008eaa359d2", size = 207948, upload-time = "2025-09-08T23:23:06.127Z" }, - { url = "https://files.pythonhosted.org/packages/cb/1e/a5a1bd6f1fb30f22573f76533de12a00bf274abcdc55c8edab639078abb6/cffi-2.0.0-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:dd4f05f54a52fb558f1ba9f528228066954fee3ebe629fc1660d874d040ae5a3", size = 206422, upload-time = "2025-09-08T23:23:07.753Z" }, - { url = "https://files.pythonhosted.org/packages/98/df/0a1755e750013a2081e863e7cd37e0cdd02664372c754e5560099eb7aa44/cffi-2.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:c8d3b5532fc71b7a77c09192b4a5a200ea992702734a2e9279a37f2478236f26", size = 219499, upload-time = "2025-09-08T23:23:09.648Z" }, - { url = "https://files.pythonhosted.org/packages/50/e1/a969e687fcf9ea58e6e2a928ad5e2dd88cc12f6f0ab477e9971f2309b57c/cffi-2.0.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:d9b29c1f0ae438d5ee9acb31cadee00a58c46cc9c0b2f9038c6b0b3470877a8c", size = 222928, upload-time = "2025-09-08T23:23:10.928Z" }, - { url = "https://files.pythonhosted.org/packages/36/54/0362578dd2c9e557a28ac77698ed67323ed5b9775ca9d3fe73fe191bb5d8/cffi-2.0.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:6d50360be4546678fc1b79ffe7a66265e28667840010348dd69a314145807a1b", size = 221302, upload-time = "2025-09-08T23:23:12.42Z" }, - { url = "https://files.pythonhosted.org/packages/d6/43/0e822876f87ea8a4ef95442c3d766a06a51fc5298823f884ef87aaad168c/cffi-2.0.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:24b6f81f1983e6df8db3adc38562c83f7d4a0c36162885ec7f7b77c7dcbec97b", size = 220049, upload-time = "2025-09-08T23:23:20.853Z" }, - { url = "https://files.pythonhosted.org/packages/b4/89/76799151d9c2d2d1ead63c2429da9ea9d7aac304603de0c6e8764e6e8e70/cffi-2.0.0-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:12873ca6cb9b0f0d3a0da705d6086fe911591737a59f28b7936bdfed27c0d47c", size = 207793, upload-time = "2025-09-08T23:23:22.08Z" }, - { url = "https://files.pythonhosted.org/packages/bb/dd/3465b14bb9e24ee24cb88c9e3730f6de63111fffe513492bf8c808a3547e/cffi-2.0.0-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:d9b97165e8aed9272a6bb17c01e3cc5871a594a446ebedc996e2397a1c1ea8ef", size = 206300, upload-time = "2025-09-08T23:23:23.314Z" }, - { url = "https://files.pythonhosted.org/packages/47/d9/d83e293854571c877a92da46fdec39158f8d7e68da75bf73581225d28e90/cffi-2.0.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:afb8db5439b81cf9c9d0c80404b60c3cc9c3add93e114dcae767f1477cb53775", size = 219244, upload-time = "2025-09-08T23:23:24.541Z" }, - { url = "https://files.pythonhosted.org/packages/2b/0f/1f177e3683aead2bb00f7679a16451d302c436b5cbf2505f0ea8146ef59e/cffi-2.0.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:737fe7d37e1a1bffe70bd5754ea763a62a066dc5913ca57e957824b72a85e205", size = 222828, upload-time = "2025-09-08T23:23:26.143Z" }, - { url = "https://files.pythonhosted.org/packages/c6/0f/cafacebd4b040e3119dcb32fed8bdef8dfe94da653155f9d0b9dc660166e/cffi-2.0.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:38100abb9d1b1435bc4cc340bb4489635dc2f0da7456590877030c9b3d40b0c1", size = 220926, upload-time = "2025-09-08T23:23:27.873Z" }, - { url = "https://files.pythonhosted.org/packages/be/b4/c56878d0d1755cf9caa54ba71e5d049479c52f9e4afc230f06822162ab2f/cffi-2.0.0-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:7cc09976e8b56f8cebd752f7113ad07752461f48a58cbba644139015ac24954c", size = 221593, upload-time = "2025-09-08T23:23:31.91Z" }, - { url = "https://files.pythonhosted.org/packages/e0/0d/eb704606dfe8033e7128df5e90fee946bbcb64a04fcdaa97321309004000/cffi-2.0.0-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:92b68146a71df78564e4ef48af17551a5ddd142e5190cdf2c5624d0c3ff5b2e8", size = 209354, upload-time = "2025-09-08T23:23:33.214Z" }, - { url = "https://files.pythonhosted.org/packages/d8/19/3c435d727b368ca475fb8742ab97c9cb13a0de600ce86f62eab7fa3eea60/cffi-2.0.0-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:b1e74d11748e7e98e2f426ab176d4ed720a64412b6a15054378afdb71e0f37dc", size = 208480, upload-time = "2025-09-08T23:23:34.495Z" }, - { url = "https://files.pythonhosted.org/packages/d0/44/681604464ed9541673e486521497406fadcc15b5217c3e326b061696899a/cffi-2.0.0-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:28a3a209b96630bca57cce802da70c266eb08c6e97e5afd61a75611ee6c64592", size = 221584, upload-time = "2025-09-08T23:23:36.096Z" }, - { url = "https://files.pythonhosted.org/packages/25/8e/342a504ff018a2825d395d44d63a767dd8ebc927ebda557fecdaca3ac33a/cffi-2.0.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:7553fb2090d71822f02c629afe6042c299edf91ba1bf94951165613553984512", size = 224443, upload-time = "2025-09-08T23:23:37.328Z" }, - { url = "https://files.pythonhosted.org/packages/e1/5e/b666bacbbc60fbf415ba9988324a132c9a7a0448a9a8f125074671c0f2c3/cffi-2.0.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:6c6c373cfc5c83a975506110d17457138c8c63016b563cc9ed6e056a82f13ce4", size = 223437, upload-time = "2025-09-08T23:23:38.945Z" }, -] - -[[package]] -name = "cfgv" -version = "3.4.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/11/74/539e56497d9bd1d484fd863dd69cbbfa653cd2aa27abfe35653494d85e94/cfgv-3.4.0.tar.gz", hash = "sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560", size = 7114, upload-time = "2023-08-12T20:38:17.776Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/c5/55/51844dd50c4fc7a33b653bfaba4c2456f06955289ca770a5dbd5fd267374/cfgv-3.4.0-py2.py3-none-any.whl", hash = "sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9", size = 7249, upload-time = "2023-08-12T20:38:16.269Z" }, -] - -[[package]] -name = "charset-normalizer" -version = "3.4.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/83/2d/5fd176ceb9b2fc619e63405525573493ca23441330fcdaee6bef9460e924/charset_normalizer-3.4.3.tar.gz", hash = "sha256:6fce4b8500244f6fcb71465d4a4930d132ba9ab8e71a7859e6a5d59851068d14", size = 122371, upload-time = "2025-08-09T07:57:28.46Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d6/98/f3b8013223728a99b908c9344da3aa04ee6e3fa235f19409033eda92fb78/charset_normalizer-3.4.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:fb7f67a1bfa6e40b438170ebdc8158b78dc465a5a67b6dde178a46987b244a72", size = 207695, upload-time = "2025-08-09T07:55:36.452Z" }, - { url = "https://files.pythonhosted.org/packages/21/40/5188be1e3118c82dcb7c2a5ba101b783822cfb413a0268ed3be0468532de/charset_normalizer-3.4.3-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:cc9370a2da1ac13f0153780040f465839e6cccb4a1e44810124b4e22483c93fe", size = 147153, upload-time = "2025-08-09T07:55:38.467Z" }, - { url = "https://files.pythonhosted.org/packages/37/60/5d0d74bc1e1380f0b72c327948d9c2aca14b46a9efd87604e724260f384c/charset_normalizer-3.4.3-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:07a0eae9e2787b586e129fdcbe1af6997f8d0e5abaa0bc98c0e20e124d67e601", size = 160428, upload-time = "2025-08-09T07:55:40.072Z" }, - { url = "https://files.pythonhosted.org/packages/85/9a/d891f63722d9158688de58d050c59dc3da560ea7f04f4c53e769de5140f5/charset_normalizer-3.4.3-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:74d77e25adda8581ffc1c720f1c81ca082921329452eba58b16233ab1842141c", size = 157627, upload-time = "2025-08-09T07:55:41.706Z" }, - { url = "https://files.pythonhosted.org/packages/65/1a/7425c952944a6521a9cfa7e675343f83fd82085b8af2b1373a2409c683dc/charset_normalizer-3.4.3-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d0e909868420b7049dafd3a31d45125b31143eec59235311fc4c57ea26a4acd2", size = 152388, upload-time = "2025-08-09T07:55:43.262Z" }, - { url = "https://files.pythonhosted.org/packages/f0/c9/a2c9c2a355a8594ce2446085e2ec97fd44d323c684ff32042e2a6b718e1d/charset_normalizer-3.4.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:c6f162aabe9a91a309510d74eeb6507fab5fff92337a15acbe77753d88d9dcf0", size = 150077, upload-time = "2025-08-09T07:55:44.903Z" }, - { url = "https://files.pythonhosted.org/packages/3b/38/20a1f44e4851aa1c9105d6e7110c9d020e093dfa5836d712a5f074a12bf7/charset_normalizer-3.4.3-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:4ca4c094de7771a98d7fbd67d9e5dbf1eb73efa4f744a730437d8a3a5cf994f0", size = 161631, upload-time = "2025-08-09T07:55:46.346Z" }, - { url = "https://files.pythonhosted.org/packages/a4/fa/384d2c0f57edad03d7bec3ebefb462090d8905b4ff5a2d2525f3bb711fac/charset_normalizer-3.4.3-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:02425242e96bcf29a49711b0ca9f37e451da7c70562bc10e8ed992a5a7a25cc0", size = 159210, upload-time = "2025-08-09T07:55:47.539Z" }, - { url = "https://files.pythonhosted.org/packages/33/9e/eca49d35867ca2db336b6ca27617deed4653b97ebf45dfc21311ce473c37/charset_normalizer-3.4.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:78deba4d8f9590fe4dae384aeff04082510a709957e968753ff3c48399f6f92a", size = 153739, upload-time = "2025-08-09T07:55:48.744Z" }, - { url = "https://files.pythonhosted.org/packages/2a/91/26c3036e62dfe8de8061182d33be5025e2424002125c9500faff74a6735e/charset_normalizer-3.4.3-cp310-cp310-win32.whl", hash = "sha256:d79c198e27580c8e958906f803e63cddb77653731be08851c7df0b1a14a8fc0f", size = 99825, upload-time = "2025-08-09T07:55:50.305Z" }, - { url = "https://files.pythonhosted.org/packages/e2/c6/f05db471f81af1fa01839d44ae2a8bfeec8d2a8b4590f16c4e7393afd323/charset_normalizer-3.4.3-cp310-cp310-win_amd64.whl", hash = "sha256:c6e490913a46fa054e03699c70019ab869e990270597018cef1d8562132c2669", size = 107452, upload-time = "2025-08-09T07:55:51.461Z" }, - { url = "https://files.pythonhosted.org/packages/7f/b5/991245018615474a60965a7c9cd2b4efbaabd16d582a5547c47ee1c7730b/charset_normalizer-3.4.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:b256ee2e749283ef3ddcff51a675ff43798d92d746d1a6e4631bf8c707d22d0b", size = 204483, upload-time = "2025-08-09T07:55:53.12Z" }, - { url = "https://files.pythonhosted.org/packages/c7/2a/ae245c41c06299ec18262825c1569c5d3298fc920e4ddf56ab011b417efd/charset_normalizer-3.4.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:13faeacfe61784e2559e690fc53fa4c5ae97c6fcedb8eb6fb8d0a15b475d2c64", size = 145520, upload-time = "2025-08-09T07:55:54.712Z" }, - { url = "https://files.pythonhosted.org/packages/3a/a4/b3b6c76e7a635748c4421d2b92c7b8f90a432f98bda5082049af37ffc8e3/charset_normalizer-3.4.3-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:00237675befef519d9af72169d8604a067d92755e84fe76492fef5441db05b91", size = 158876, upload-time = "2025-08-09T07:55:56.024Z" }, - { url = "https://files.pythonhosted.org/packages/e2/e6/63bb0e10f90a8243c5def74b5b105b3bbbfb3e7bb753915fe333fb0c11ea/charset_normalizer-3.4.3-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:585f3b2a80fbd26b048a0be90c5aae8f06605d3c92615911c3a2b03a8a3b796f", size = 156083, upload-time = "2025-08-09T07:55:57.582Z" }, - { url = "https://files.pythonhosted.org/packages/87/df/b7737ff046c974b183ea9aa111b74185ac8c3a326c6262d413bd5a1b8c69/charset_normalizer-3.4.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0e78314bdc32fa80696f72fa16dc61168fda4d6a0c014e0380f9d02f0e5d8a07", size = 150295, upload-time = "2025-08-09T07:55:59.147Z" }, - { url = "https://files.pythonhosted.org/packages/61/f1/190d9977e0084d3f1dc169acd060d479bbbc71b90bf3e7bf7b9927dec3eb/charset_normalizer-3.4.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:96b2b3d1a83ad55310de8c7b4a2d04d9277d5591f40761274856635acc5fcb30", size = 148379, upload-time = "2025-08-09T07:56:00.364Z" }, - { url = "https://files.pythonhosted.org/packages/4c/92/27dbe365d34c68cfe0ca76f1edd70e8705d82b378cb54ebbaeabc2e3029d/charset_normalizer-3.4.3-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:939578d9d8fd4299220161fdd76e86c6a251987476f5243e8864a7844476ba14", size = 160018, upload-time = "2025-08-09T07:56:01.678Z" }, - { url = "https://files.pythonhosted.org/packages/99/04/baae2a1ea1893a01635d475b9261c889a18fd48393634b6270827869fa34/charset_normalizer-3.4.3-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:fd10de089bcdcd1be95a2f73dbe6254798ec1bda9f450d5828c96f93e2536b9c", size = 157430, upload-time = "2025-08-09T07:56:02.87Z" }, - { url = "https://files.pythonhosted.org/packages/2f/36/77da9c6a328c54d17b960c89eccacfab8271fdaaa228305330915b88afa9/charset_normalizer-3.4.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:1e8ac75d72fa3775e0b7cb7e4629cec13b7514d928d15ef8ea06bca03ef01cae", size = 151600, upload-time = "2025-08-09T07:56:04.089Z" }, - { url = "https://files.pythonhosted.org/packages/64/d4/9eb4ff2c167edbbf08cdd28e19078bf195762e9bd63371689cab5ecd3d0d/charset_normalizer-3.4.3-cp311-cp311-win32.whl", hash = "sha256:6cf8fd4c04756b6b60146d98cd8a77d0cdae0e1ca20329da2ac85eed779b6849", size = 99616, upload-time = "2025-08-09T07:56:05.658Z" }, - { url = "https://files.pythonhosted.org/packages/f4/9c/996a4a028222e7761a96634d1820de8a744ff4327a00ada9c8942033089b/charset_normalizer-3.4.3-cp311-cp311-win_amd64.whl", hash = "sha256:31a9a6f775f9bcd865d88ee350f0ffb0e25936a7f930ca98995c05abf1faf21c", size = 107108, upload-time = "2025-08-09T07:56:07.176Z" }, - { url = "https://files.pythonhosted.org/packages/e9/5e/14c94999e418d9b87682734589404a25854d5f5d0408df68bc15b6ff54bb/charset_normalizer-3.4.3-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:e28e334d3ff134e88989d90ba04b47d84382a828c061d0d1027b1b12a62b39b1", size = 205655, upload-time = "2025-08-09T07:56:08.475Z" }, - { url = "https://files.pythonhosted.org/packages/7d/a8/c6ec5d389672521f644505a257f50544c074cf5fc292d5390331cd6fc9c3/charset_normalizer-3.4.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:0cacf8f7297b0c4fcb74227692ca46b4a5852f8f4f24b3c766dd94a1075c4884", size = 146223, upload-time = "2025-08-09T07:56:09.708Z" }, - { url = "https://files.pythonhosted.org/packages/fc/eb/a2ffb08547f4e1e5415fb69eb7db25932c52a52bed371429648db4d84fb1/charset_normalizer-3.4.3-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:c6fd51128a41297f5409deab284fecbe5305ebd7e5a1f959bee1c054622b7018", size = 159366, upload-time = "2025-08-09T07:56:11.326Z" }, - { url = "https://files.pythonhosted.org/packages/82/10/0fd19f20c624b278dddaf83b8464dcddc2456cb4b02bb902a6da126b87a1/charset_normalizer-3.4.3-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:3cfb2aad70f2c6debfbcb717f23b7eb55febc0bb23dcffc0f076009da10c6392", size = 157104, upload-time = "2025-08-09T07:56:13.014Z" }, - { url = "https://files.pythonhosted.org/packages/16/ab/0233c3231af734f5dfcf0844aa9582d5a1466c985bbed6cedab85af9bfe3/charset_normalizer-3.4.3-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:1606f4a55c0fd363d754049cdf400175ee96c992b1f8018b993941f221221c5f", size = 151830, upload-time = "2025-08-09T07:56:14.428Z" }, - { url = "https://files.pythonhosted.org/packages/ae/02/e29e22b4e02839a0e4a06557b1999d0a47db3567e82989b5bb21f3fbbd9f/charset_normalizer-3.4.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:027b776c26d38b7f15b26a5da1044f376455fb3766df8fc38563b4efbc515154", size = 148854, upload-time = "2025-08-09T07:56:16.051Z" }, - { url = "https://files.pythonhosted.org/packages/05/6b/e2539a0a4be302b481e8cafb5af8792da8093b486885a1ae4d15d452bcec/charset_normalizer-3.4.3-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:42e5088973e56e31e4fa58eb6bd709e42fc03799c11c42929592889a2e54c491", size = 160670, upload-time = "2025-08-09T07:56:17.314Z" }, - { url = "https://files.pythonhosted.org/packages/31/e7/883ee5676a2ef217a40ce0bffcc3d0dfbf9e64cbcfbdf822c52981c3304b/charset_normalizer-3.4.3-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:cc34f233c9e71701040d772aa7490318673aa7164a0efe3172b2981218c26d93", size = 158501, upload-time = "2025-08-09T07:56:18.641Z" }, - { url = "https://files.pythonhosted.org/packages/c1/35/6525b21aa0db614cf8b5792d232021dca3df7f90a1944db934efa5d20bb1/charset_normalizer-3.4.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:320e8e66157cc4e247d9ddca8e21f427efc7a04bbd0ac8a9faf56583fa543f9f", size = 153173, upload-time = "2025-08-09T07:56:20.289Z" }, - { url = "https://files.pythonhosted.org/packages/50/ee/f4704bad8201de513fdc8aac1cabc87e38c5818c93857140e06e772b5892/charset_normalizer-3.4.3-cp312-cp312-win32.whl", hash = "sha256:fb6fecfd65564f208cbf0fba07f107fb661bcd1a7c389edbced3f7a493f70e37", size = 99822, upload-time = "2025-08-09T07:56:21.551Z" }, - { url = "https://files.pythonhosted.org/packages/39/f5/3b3836ca6064d0992c58c7561c6b6eee1b3892e9665d650c803bd5614522/charset_normalizer-3.4.3-cp312-cp312-win_amd64.whl", hash = "sha256:86df271bf921c2ee3818f0522e9a5b8092ca2ad8b065ece5d7d9d0e9f4849bcc", size = 107543, upload-time = "2025-08-09T07:56:23.115Z" }, - { url = "https://files.pythonhosted.org/packages/65/ca/2135ac97709b400c7654b4b764daf5c5567c2da45a30cdd20f9eefe2d658/charset_normalizer-3.4.3-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:14c2a87c65b351109f6abfc424cab3927b3bdece6f706e4d12faaf3d52ee5efe", size = 205326, upload-time = "2025-08-09T07:56:24.721Z" }, - { url = "https://files.pythonhosted.org/packages/71/11/98a04c3c97dd34e49c7d247083af03645ca3730809a5509443f3c37f7c99/charset_normalizer-3.4.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:41d1fc408ff5fdfb910200ec0e74abc40387bccb3252f3f27c0676731df2b2c8", size = 146008, upload-time = "2025-08-09T07:56:26.004Z" }, - { url = "https://files.pythonhosted.org/packages/60/f5/4659a4cb3c4ec146bec80c32d8bb16033752574c20b1252ee842a95d1a1e/charset_normalizer-3.4.3-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:1bb60174149316da1c35fa5233681f7c0f9f514509b8e399ab70fea5f17e45c9", size = 159196, upload-time = "2025-08-09T07:56:27.25Z" }, - { url = "https://files.pythonhosted.org/packages/86/9e/f552f7a00611f168b9a5865a1414179b2c6de8235a4fa40189f6f79a1753/charset_normalizer-3.4.3-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:30d006f98569de3459c2fc1f2acde170b7b2bd265dc1943e87e1a4efe1b67c31", size = 156819, upload-time = "2025-08-09T07:56:28.515Z" }, - { url = "https://files.pythonhosted.org/packages/7e/95/42aa2156235cbc8fa61208aded06ef46111c4d3f0de233107b3f38631803/charset_normalizer-3.4.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:416175faf02e4b0810f1f38bcb54682878a4af94059a1cd63b8747244420801f", size = 151350, upload-time = "2025-08-09T07:56:29.716Z" }, - { url = "https://files.pythonhosted.org/packages/c2/a9/3865b02c56f300a6f94fc631ef54f0a8a29da74fb45a773dfd3dcd380af7/charset_normalizer-3.4.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:6aab0f181c486f973bc7262a97f5aca3ee7e1437011ef0c2ec04b5a11d16c927", size = 148644, upload-time = "2025-08-09T07:56:30.984Z" }, - { url = "https://files.pythonhosted.org/packages/77/d9/cbcf1a2a5c7d7856f11e7ac2d782aec12bdfea60d104e60e0aa1c97849dc/charset_normalizer-3.4.3-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:fdabf8315679312cfa71302f9bd509ded4f2f263fb5b765cf1433b39106c3cc9", size = 160468, upload-time = "2025-08-09T07:56:32.252Z" }, - { url = "https://files.pythonhosted.org/packages/f6/42/6f45efee8697b89fda4d50580f292b8f7f9306cb2971d4b53f8914e4d890/charset_normalizer-3.4.3-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:bd28b817ea8c70215401f657edef3a8aa83c29d447fb0b622c35403780ba11d5", size = 158187, upload-time = "2025-08-09T07:56:33.481Z" }, - { url = "https://files.pythonhosted.org/packages/70/99/f1c3bdcfaa9c45b3ce96f70b14f070411366fa19549c1d4832c935d8e2c3/charset_normalizer-3.4.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:18343b2d246dc6761a249ba1fb13f9ee9a2bcd95decc767319506056ea4ad4dc", size = 152699, upload-time = "2025-08-09T07:56:34.739Z" }, - { url = "https://files.pythonhosted.org/packages/a3/ad/b0081f2f99a4b194bcbb1934ef3b12aa4d9702ced80a37026b7607c72e58/charset_normalizer-3.4.3-cp313-cp313-win32.whl", hash = "sha256:6fb70de56f1859a3f71261cbe41005f56a7842cc348d3aeb26237560bfa5e0ce", size = 99580, upload-time = "2025-08-09T07:56:35.981Z" }, - { url = "https://files.pythonhosted.org/packages/9a/8f/ae790790c7b64f925e5c953b924aaa42a243fb778fed9e41f147b2a5715a/charset_normalizer-3.4.3-cp313-cp313-win_amd64.whl", hash = "sha256:cf1ebb7d78e1ad8ec2a8c4732c7be2e736f6e5123a4146c5b89c9d1f585f8cef", size = 107366, upload-time = "2025-08-09T07:56:37.339Z" }, - { url = "https://files.pythonhosted.org/packages/8e/91/b5a06ad970ddc7a0e513112d40113e834638f4ca1120eb727a249fb2715e/charset_normalizer-3.4.3-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:3cd35b7e8aedeb9e34c41385fda4f73ba609e561faedfae0a9e75e44ac558a15", size = 204342, upload-time = "2025-08-09T07:56:38.687Z" }, - { url = "https://files.pythonhosted.org/packages/ce/ec/1edc30a377f0a02689342f214455c3f6c2fbedd896a1d2f856c002fc3062/charset_normalizer-3.4.3-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b89bc04de1d83006373429975f8ef9e7932534b8cc9ca582e4db7d20d91816db", size = 145995, upload-time = "2025-08-09T07:56:40.048Z" }, - { url = "https://files.pythonhosted.org/packages/17/e5/5e67ab85e6d22b04641acb5399c8684f4d37caf7558a53859f0283a650e9/charset_normalizer-3.4.3-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:2001a39612b241dae17b4687898843f254f8748b796a2e16f1051a17078d991d", size = 158640, upload-time = "2025-08-09T07:56:41.311Z" }, - { url = "https://files.pythonhosted.org/packages/f1/e5/38421987f6c697ee3722981289d554957c4be652f963d71c5e46a262e135/charset_normalizer-3.4.3-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:8dcfc373f888e4fb39a7bc57e93e3b845e7f462dacc008d9749568b1c4ece096", size = 156636, upload-time = "2025-08-09T07:56:43.195Z" }, - { url = "https://files.pythonhosted.org/packages/a0/e4/5a075de8daa3ec0745a9a3b54467e0c2967daaaf2cec04c845f73493e9a1/charset_normalizer-3.4.3-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:18b97b8404387b96cdbd30ad660f6407799126d26a39ca65729162fd810a99aa", size = 150939, upload-time = "2025-08-09T07:56:44.819Z" }, - { url = "https://files.pythonhosted.org/packages/02/f7/3611b32318b30974131db62b4043f335861d4d9b49adc6d57c1149cc49d4/charset_normalizer-3.4.3-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:ccf600859c183d70eb47e05a44cd80a4ce77394d1ac0f79dbd2dd90a69a3a049", size = 148580, upload-time = "2025-08-09T07:56:46.684Z" }, - { url = "https://files.pythonhosted.org/packages/7e/61/19b36f4bd67f2793ab6a99b979b4e4f3d8fc754cbdffb805335df4337126/charset_normalizer-3.4.3-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:53cd68b185d98dde4ad8990e56a58dea83a4162161b1ea9272e5c9182ce415e0", size = 159870, upload-time = "2025-08-09T07:56:47.941Z" }, - { url = "https://files.pythonhosted.org/packages/06/57/84722eefdd338c04cf3030ada66889298eaedf3e7a30a624201e0cbe424a/charset_normalizer-3.4.3-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:30a96e1e1f865f78b030d65241c1ee850cdf422d869e9028e2fc1d5e4db73b92", size = 157797, upload-time = "2025-08-09T07:56:49.756Z" }, - { url = "https://files.pythonhosted.org/packages/72/2a/aff5dd112b2f14bcc3462c312dce5445806bfc8ab3a7328555da95330e4b/charset_normalizer-3.4.3-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:d716a916938e03231e86e43782ca7878fb602a125a91e7acb8b5112e2e96ac16", size = 152224, upload-time = "2025-08-09T07:56:51.369Z" }, - { url = "https://files.pythonhosted.org/packages/b7/8c/9839225320046ed279c6e839d51f028342eb77c91c89b8ef2549f951f3ec/charset_normalizer-3.4.3-cp314-cp314-win32.whl", hash = "sha256:c6dbd0ccdda3a2ba7c2ecd9d77b37f3b5831687d8dc1b6ca5f56a4880cc7b7ce", size = 100086, upload-time = "2025-08-09T07:56:52.722Z" }, - { url = "https://files.pythonhosted.org/packages/ee/7a/36fbcf646e41f710ce0a563c1c9a343c6edf9be80786edeb15b6f62e17db/charset_normalizer-3.4.3-cp314-cp314-win_amd64.whl", hash = "sha256:73dc19b562516fc9bcf6e5d6e596df0b4eb98d87e4f79f3ae71840e6ed21361c", size = 107400, upload-time = "2025-08-09T07:56:55.172Z" }, - { url = "https://files.pythonhosted.org/packages/8a/1f/f041989e93b001bc4e44bb1669ccdcf54d3f00e628229a85b08d330615c5/charset_normalizer-3.4.3-py3-none-any.whl", hash = "sha256:ce571ab16d890d23b5c278547ba694193a45011ff86a9162a71307ed9f86759a", size = 53175, upload-time = "2025-08-09T07:57:26.864Z" }, -] - -[[package]] -name = "chevron" -version = "0.14.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/15/1f/ca74b65b19798895d63a6e92874162f44233467c9e7c1ed8afd19016ebe9/chevron-0.14.0.tar.gz", hash = "sha256:87613aafdf6d77b6a90ff073165a61ae5086e21ad49057aa0e53681601800ebf", size = 11440, upload-time = "2021-01-02T22:47:59.233Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/52/93/342cc62a70ab727e093ed98e02a725d85b746345f05d2b5e5034649f4ec8/chevron-0.14.0-py3-none-any.whl", hash = "sha256:fbf996a709f8da2e745ef763f482ce2d311aa817d287593a5b990d6d6e4f0443", size = 11595, upload-time = "2021-01-02T22:47:57.847Z" }, -] - -[[package]] -name = "click" -version = "8.3.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "colorama", marker = "sys_platform == 'win32'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/46/61/de6cd827efad202d7057d93e0fed9294b96952e188f7384832791c7b2254/click-8.3.0.tar.gz", hash = "sha256:e7b8232224eba16f4ebe410c25ced9f7875cb5f3263ffc93cc3e8da705e229c4", size = 276943, upload-time = "2025-09-18T17:32:23.696Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/db/d3/9dcc0f5797f070ec8edf30fbadfb200e71d9db6b84d211e3b2085a7589a0/click-8.3.0-py3-none-any.whl", hash = "sha256:9b9f285302c6e3064f4330c05f05b81945b2a39544279343e6e7c5f27a9baddc", size = 107295, upload-time = "2025-09-18T17:32:22.42Z" }, -] - -[[package]] -name = "colorama" -version = "0.4.6" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/d8/53/6f443c9a4a8358a93a6792e2acffb9d9d5cb0a5cfd8802644b7b1c9a02e4/colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44", size = 27697, upload-time = "2022-10-25T02:36:22.414Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335, upload-time = "2022-10-25T02:36:20.889Z" }, -] - -[[package]] -name = "cryptography" -version = "46.0.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "cffi", marker = "platform_python_implementation != 'PyPy'" }, - { name = "typing-extensions", marker = "python_full_version < '3.11'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/a9/62/e3664e6ffd7743e1694b244dde70b43a394f6f7fbcacf7014a8ff5197c73/cryptography-46.0.1.tar.gz", hash = "sha256:ed570874e88f213437f5cf758f9ef26cbfc3f336d889b1e592ee11283bb8d1c7", size = 749198, upload-time = "2025-09-17T00:10:35.797Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/22/59/9ae689a25047e0601adfcb159ec4f83c0b4149fdb5c3030cc94cd218141d/cryptography-46.0.1-cp311-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:0ff483716be32690c14636e54a1f6e2e1b7bf8e22ca50b989f88fa1b2d287080", size = 4308182, upload-time = "2025-09-17T00:08:39.388Z" }, - { url = "https://files.pythonhosted.org/packages/c4/ee/ca6cc9df7118f2fcd142c76b1da0f14340d77518c05b1ebfbbabca6b9e7d/cryptography-46.0.1-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9873bf7c1f2a6330bdfe8621e7ce64b725784f9f0c3a6a55c3047af5849f920e", size = 4572393, upload-time = "2025-09-17T00:08:41.663Z" }, - { url = "https://files.pythonhosted.org/packages/7f/a3/0f5296f63815d8e985922b05c31f77ce44787b3127a67c0b7f70f115c45f/cryptography-46.0.1-cp311-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:0dfb7c88d4462a0cfdd0d87a3c245a7bc3feb59de101f6ff88194f740f72eda6", size = 4308400, upload-time = "2025-09-17T00:08:43.559Z" }, - { url = "https://files.pythonhosted.org/packages/5d/8c/74fcda3e4e01be1d32775d5b4dd841acaac3c1b8fa4d0774c7ac8d52463d/cryptography-46.0.1-cp311-abi3-manylinux_2_28_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:e22801b61613ebdebf7deb18b507919e107547a1d39a3b57f5f855032dd7cfb8", size = 4015786, upload-time = "2025-09-17T00:08:45.758Z" }, - { url = "https://files.pythonhosted.org/packages/dc/b8/85d23287baeef273b0834481a3dd55bbed3a53587e3b8d9f0898235b8f91/cryptography-46.0.1-cp311-abi3-manylinux_2_28_ppc64le.whl", hash = "sha256:757af4f6341ce7a1e47c326ca2a81f41d236070217e5fbbad61bbfe299d55d28", size = 4982606, upload-time = "2025-09-17T00:08:47.602Z" }, - { url = "https://files.pythonhosted.org/packages/e5/d3/de61ad5b52433b389afca0bc70f02a7a1f074651221f599ce368da0fe437/cryptography-46.0.1-cp311-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:f7a24ea78de345cfa7f6a8d3bde8b242c7fac27f2bd78fa23474ca38dfaeeab9", size = 4604234, upload-time = "2025-09-17T00:08:49.879Z" }, - { url = "https://files.pythonhosted.org/packages/dc/1f/dbd4d6570d84748439237a7478d124ee0134bf166ad129267b7ed8ea6d22/cryptography-46.0.1-cp311-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:9e8776dac9e660c22241b6587fae51a67b4b0147daa4d176b172c3ff768ad736", size = 4307669, upload-time = "2025-09-17T00:08:52.321Z" }, - { url = "https://files.pythonhosted.org/packages/ec/fd/ca0a14ce7f0bfe92fa727aacaf2217eb25eb7e4ed513b14d8e03b26e63ed/cryptography-46.0.1-cp311-abi3-manylinux_2_34_ppc64le.whl", hash = "sha256:9f40642a140c0c8649987027867242b801486865277cbabc8c6059ddef16dc8b", size = 4947579, upload-time = "2025-09-17T00:08:54.697Z" }, - { url = "https://files.pythonhosted.org/packages/89/6b/09c30543bb93401f6f88fce556b3bdbb21e55ae14912c04b7bf355f5f96c/cryptography-46.0.1-cp311-abi3-manylinux_2_34_x86_64.whl", hash = "sha256:449ef2b321bec7d97ef2c944173275ebdab78f3abdd005400cc409e27cd159ab", size = 4603669, upload-time = "2025-09-17T00:08:57.16Z" }, - { url = "https://files.pythonhosted.org/packages/23/9a/38cb01cb09ce0adceda9fc627c9cf98eb890fc8d50cacbe79b011df20f8a/cryptography-46.0.1-cp311-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:2dd339ba3345b908fa3141ddba4025568fa6fd398eabce3ef72a29ac2d73ad75", size = 4435828, upload-time = "2025-09-17T00:08:59.606Z" }, - { url = "https://files.pythonhosted.org/packages/0f/53/435b5c36a78d06ae0bef96d666209b0ecd8f8181bfe4dda46536705df59e/cryptography-46.0.1-cp311-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:7411c910fb2a412053cf33cfad0153ee20d27e256c6c3f14d7d7d1d9fec59fd5", size = 4709553, upload-time = "2025-09-17T00:09:01.832Z" }, - { url = "https://files.pythonhosted.org/packages/26/34/0ff0bb2d2c79f25a2a63109f3b76b9108a906dd2a2eb5c1d460b9938adbb/cryptography-46.0.1-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:9babb7818fdd71394e576cf26c5452df77a355eac1a27ddfa24096665a27f8fd", size = 4293515, upload-time = "2025-09-17T00:09:12.861Z" }, - { url = "https://files.pythonhosted.org/packages/df/b7/d4f848aee24ecd1be01db6c42c4a270069a4f02a105d9c57e143daf6cf0f/cryptography-46.0.1-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9f2c4cc63be3ef43c0221861177cee5d14b505cd4d4599a89e2cd273c4d3542a", size = 4545619, upload-time = "2025-09-17T00:09:15.397Z" }, - { url = "https://files.pythonhosted.org/packages/44/a5/42fedefc754fd1901e2d95a69815ea4ec8a9eed31f4c4361fcab80288661/cryptography-46.0.1-cp314-cp314t-manylinux_2_28_aarch64.whl", hash = "sha256:41c281a74df173876da1dc9a9b6953d387f06e3d3ed9284e3baae3ab3f40883a", size = 4299160, upload-time = "2025-09-17T00:09:17.155Z" }, - { url = "https://files.pythonhosted.org/packages/86/a1/cd21174f56e769c831fbbd6399a1b7519b0ff6280acec1b826d7b072640c/cryptography-46.0.1-cp314-cp314t-manylinux_2_28_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:0a17377fa52563d730248ba1f68185461fff36e8bc75d8787a7dd2e20a802b7a", size = 3994491, upload-time = "2025-09-17T00:09:18.971Z" }, - { url = "https://files.pythonhosted.org/packages/8d/2f/a8cbfa1c029987ddc746fd966711d4fa71efc891d37fbe9f030fe5ab4eec/cryptography-46.0.1-cp314-cp314t-manylinux_2_28_ppc64le.whl", hash = "sha256:0d1922d9280e08cde90b518a10cd66831f632960a8d08cb3418922d83fce6f12", size = 4960157, upload-time = "2025-09-17T00:09:20.923Z" }, - { url = "https://files.pythonhosted.org/packages/67/ae/63a84e6789e0d5a2502edf06b552bcb0fa9ff16147265d5c44a211942abe/cryptography-46.0.1-cp314-cp314t-manylinux_2_28_x86_64.whl", hash = "sha256:af84e8e99f1a82cea149e253014ea9dc89f75b82c87bb6c7242203186f465129", size = 4577263, upload-time = "2025-09-17T00:09:23.356Z" }, - { url = "https://files.pythonhosted.org/packages/ef/8f/1b9fa8e92bd9cbcb3b7e1e593a5232f2c1e6f9bd72b919c1a6b37d315f92/cryptography-46.0.1-cp314-cp314t-manylinux_2_34_aarch64.whl", hash = "sha256:ef648d2c690703501714588b2ba640facd50fd16548133b11b2859e8655a69da", size = 4298703, upload-time = "2025-09-17T00:09:25.566Z" }, - { url = "https://files.pythonhosted.org/packages/c3/af/bb95db070e73fea3fae31d8a69ac1463d89d1c084220f549b00dd01094a8/cryptography-46.0.1-cp314-cp314t-manylinux_2_34_ppc64le.whl", hash = "sha256:e94eb5fa32a8a9f9bf991f424f002913e3dd7c699ef552db9b14ba6a76a6313b", size = 4926363, upload-time = "2025-09-17T00:09:27.451Z" }, - { url = "https://files.pythonhosted.org/packages/f5/3b/d8fb17ffeb3a83157a1cc0aa5c60691d062aceecba09c2e5e77ebfc1870c/cryptography-46.0.1-cp314-cp314t-manylinux_2_34_x86_64.whl", hash = "sha256:534b96c0831855e29fc3b069b085fd185aa5353033631a585d5cd4dd5d40d657", size = 4576958, upload-time = "2025-09-17T00:09:29.924Z" }, - { url = "https://files.pythonhosted.org/packages/d9/46/86bc3a05c10c8aa88c8ae7e953a8b4e407c57823ed201dbcba55c4d655f4/cryptography-46.0.1-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:f9b55038b5c6c47559aa33626d8ecd092f354e23de3c6975e4bb205df128a2a0", size = 4422507, upload-time = "2025-09-17T00:09:32.222Z" }, - { url = "https://files.pythonhosted.org/packages/a8/4e/387e5a21dfd2b4198e74968a541cfd6128f66f8ec94ed971776e15091ac3/cryptography-46.0.1-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:ec13b7105117dbc9afd023300fb9954d72ca855c274fe563e72428ece10191c0", size = 4683964, upload-time = "2025-09-17T00:09:34.118Z" }, - { url = "https://files.pythonhosted.org/packages/56/3e/13ce6eab9ad6eba1b15a7bd476f005a4c1b3f299f4c2f32b22408b0edccf/cryptography-46.0.1-cp38-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:9ed64e5083fa806709e74fc5ea067dfef9090e5b7a2320a49be3c9df3583a2d8", size = 4301110, upload-time = "2025-09-17T00:09:45.614Z" }, - { url = "https://files.pythonhosted.org/packages/a2/67/65dc233c1ddd688073cf7b136b06ff4b84bf517ba5529607c9d79720fc67/cryptography-46.0.1-cp38-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:341fb7a26bc9d6093c1b124b9f13acc283d2d51da440b98b55ab3f79f2522ead", size = 4562369, upload-time = "2025-09-17T00:09:47.601Z" }, - { url = "https://files.pythonhosted.org/packages/17/db/d64ae4c6f4e98c3dac5bf35dd4d103f4c7c345703e43560113e5e8e31b2b/cryptography-46.0.1-cp38-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:6ef1488967e729948d424d09c94753d0167ce59afba8d0f6c07a22b629c557b2", size = 4302126, upload-time = "2025-09-17T00:09:49.335Z" }, - { url = "https://files.pythonhosted.org/packages/3d/19/5f1eea17d4805ebdc2e685b7b02800c4f63f3dd46cfa8d4c18373fea46c8/cryptography-46.0.1-cp38-abi3-manylinux_2_28_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:7823bc7cdf0b747ecfb096d004cc41573c2f5c7e3a29861603a2871b43d3ef32", size = 4009431, upload-time = "2025-09-17T00:09:51.239Z" }, - { url = "https://files.pythonhosted.org/packages/81/b5/229ba6088fe7abccbfe4c5edb96c7a5ad547fac5fdd0d40aa6ea540b2985/cryptography-46.0.1-cp38-abi3-manylinux_2_28_ppc64le.whl", hash = "sha256:f736ab8036796f5a119ff8211deda416f8c15ce03776db704a7a4e17381cb2ef", size = 4980739, upload-time = "2025-09-17T00:09:54.181Z" }, - { url = "https://files.pythonhosted.org/packages/3a/9c/50aa38907b201e74bc43c572f9603fa82b58e831bd13c245613a23cff736/cryptography-46.0.1-cp38-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:e46710a240a41d594953012213ea8ca398cd2448fbc5d0f1be8160b5511104a0", size = 4592289, upload-time = "2025-09-17T00:09:56.731Z" }, - { url = "https://files.pythonhosted.org/packages/5a/33/229858f8a5bb22f82468bb285e9f4c44a31978d5f5830bb4ea1cf8a4e454/cryptography-46.0.1-cp38-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:84ef1f145de5aee82ea2447224dc23f065ff4cc5791bb3b506615957a6ba8128", size = 4301815, upload-time = "2025-09-17T00:09:58.548Z" }, - { url = "https://files.pythonhosted.org/packages/52/cb/b76b2c87fbd6ed4a231884bea3ce073406ba8e2dae9defad910d33cbf408/cryptography-46.0.1-cp38-abi3-manylinux_2_34_ppc64le.whl", hash = "sha256:9394c7d5a7565ac5f7d9ba38b2617448eba384d7b107b262d63890079fad77ca", size = 4943251, upload-time = "2025-09-17T00:10:00.475Z" }, - { url = "https://files.pythonhosted.org/packages/94/0f/f66125ecf88e4cb5b8017ff43f3a87ede2d064cb54a1c5893f9da9d65093/cryptography-46.0.1-cp38-abi3-manylinux_2_34_x86_64.whl", hash = "sha256:ed957044e368ed295257ae3d212b95456bd9756df490e1ac4538857f67531fcc", size = 4591247, upload-time = "2025-09-17T00:10:02.874Z" }, - { url = "https://files.pythonhosted.org/packages/f6/22/9f3134ae436b63b463cfdf0ff506a0570da6873adb4bf8c19b8a5b4bac64/cryptography-46.0.1-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:f7de12fa0eee6234de9a9ce0ffcfa6ce97361db7a50b09b65c63ac58e5f22fc7", size = 4428534, upload-time = "2025-09-17T00:10:04.994Z" }, - { url = "https://files.pythonhosted.org/packages/89/39/e6042bcb2638650b0005c752c38ea830cbfbcbb1830e4d64d530000aa8dc/cryptography-46.0.1-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:7fab1187b6c6b2f11a326f33b036f7168f5b996aedd0c059f9738915e4e8f53a", size = 4699541, upload-time = "2025-09-17T00:10:06.925Z" }, - { url = "https://files.pythonhosted.org/packages/db/32/6fc7250280920418651640d76cee34d91c1e0601d73acd44364570cf041f/cryptography-46.0.1-pp311-pypy311_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:0ca4be2af48c24df689a150d9cd37404f689e2968e247b6b8ff09bff5bcd786f", size = 4249030, upload-time = "2025-09-17T00:10:22.396Z" }, - { url = "https://files.pythonhosted.org/packages/32/33/8d5398b2da15a15110b2478480ab512609f95b45ead3a105c9a9c76f9980/cryptography-46.0.1-pp311-pypy311_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:13e67c4d3fb8b6bc4ef778a7ccdd8df4cd15b4bcc18f4239c8440891a11245cc", size = 4528009, upload-time = "2025-09-17T00:10:24.418Z" }, - { url = "https://files.pythonhosted.org/packages/fd/1c/4012edad2a8977ab386c36b6e21f5065974d37afa3eade83a9968cba4855/cryptography-46.0.1-pp311-pypy311_pp73-manylinux_2_34_aarch64.whl", hash = "sha256:15b5fd9358803b0d1cc42505a18d8bca81dabb35b5cfbfea1505092e13a9d96d", size = 4248902, upload-time = "2025-09-17T00:10:26.255Z" }, - { url = "https://files.pythonhosted.org/packages/58/a3/257cd5ae677302de8fa066fca9de37128f6729d1e63c04dd6a15555dd450/cryptography-46.0.1-pp311-pypy311_pp73-manylinux_2_34_x86_64.whl", hash = "sha256:e34da95e29daf8a71cb2841fd55df0511539a6cdf33e6f77c1e95e44006b9b46", size = 4527150, upload-time = "2025-09-17T00:10:28.28Z" }, -] - -[[package]] -name = "distlib" -version = "0.4.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/96/8e/709914eb2b5749865801041647dc7f4e6d00b549cfe88b65ca192995f07c/distlib-0.4.0.tar.gz", hash = "sha256:feec40075be03a04501a973d81f633735b4b69f98b05450592310c0f401a4e0d", size = 614605, upload-time = "2025-07-17T16:52:00.465Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/33/6b/e0547afaf41bf2c42e52430072fa5658766e3d65bd4b03a563d1b6336f57/distlib-0.4.0-py2.py3-none-any.whl", hash = "sha256:9659f7d87e46584a30b5780e43ac7a2143098441670ff0a49d5f9034c54a6c16", size = 469047, upload-time = "2025-07-17T16:51:58.613Z" }, -] - -[[package]] -name = "distro" -version = "1.9.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/fc/f8/98eea607f65de6527f8a2e8885fc8015d3e6f5775df186e443e0964a11c3/distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed", size = 60722, upload-time = "2023-12-24T09:54:32.31Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/12/b3/231ffd4ab1fc9d679809f356cebee130ac7daa00d6d6f3206dd4fd137e9e/distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2", size = 20277, upload-time = "2023-12-24T09:54:30.421Z" }, -] - -[[package]] -name = "docstring-parser" -version = "0.17.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/b2/9d/c3b43da9515bd270df0f80548d9944e389870713cc1fe2b8fb35fe2bcefd/docstring_parser-0.17.0.tar.gz", hash = "sha256:583de4a309722b3315439bb31d64ba3eebada841f2e2cee23b99df001434c912", size = 27442, upload-time = "2025-07-21T07:35:01.868Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/55/e2/2537ebcff11c1ee1ff17d8d0b6f4db75873e3b0fb32c2d4a2ee31ecb310a/docstring_parser-0.17.0-py3-none-any.whl", hash = "sha256:cf2569abd23dce8099b300f9b4fa8191e9582dda731fd533daf54c4551658708", size = 36896, upload-time = "2025-07-21T07:35:00.684Z" }, -] - -[[package]] -name = "docutils" -version = "0.22.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/4a/c0/89fe6215b443b919cb98a5002e107cb5026854ed1ccb6b5833e0768419d1/docutils-0.22.2.tar.gz", hash = "sha256:9fdb771707c8784c8f2728b67cb2c691305933d68137ef95a75db5f4dfbc213d", size = 2289092, upload-time = "2025-09-20T17:55:47.994Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/66/dd/f95350e853a4468ec37478414fc04ae2d61dad7a947b3015c3dcc51a09b9/docutils-0.22.2-py3-none-any.whl", hash = "sha256:b0e98d679283fc3bb0ead8a5da7f501baa632654e7056e9c5846842213d674d8", size = 632667, upload-time = "2025-09-20T17:55:43.052Z" }, -] - -[[package]] -name = "exceptiongroup" -version = "1.3.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/0b/9f/a65090624ecf468cdca03533906e7c69ed7588582240cfe7cc9e770b50eb/exceptiongroup-1.3.0.tar.gz", hash = "sha256:b241f5885f560bc56a59ee63ca4c6a8bfa46ae4ad651af316d4e81817bb9fd88", size = 29749, upload-time = "2025-05-10T17:42:51.123Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/36/f4/c6e662dade71f56cd2f3735141b265c3c79293c109549c1e6933b0651ffc/exceptiongroup-1.3.0-py3-none-any.whl", hash = "sha256:4d111e6e0c13d0644cad6ddaa7ed0261a0b36971f6d23e7ec9b4b9097da78a10", size = 16674, upload-time = "2025-05-10T17:42:49.33Z" }, -] - -[[package]] -name = "filelock" -version = "3.19.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/40/bb/0ab3e58d22305b6f5440629d20683af28959bf793d98d11950e305c1c326/filelock-3.19.1.tar.gz", hash = "sha256:66eda1888b0171c998b35be2bcc0f6d75c388a7ce20c3f3f37aa8e96c2dddf58", size = 17687, upload-time = "2025-08-14T16:56:03.016Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/42/14/42b2651a2f46b022ccd948bca9f2d5af0fd8929c4eec235b8d6d844fbe67/filelock-3.19.1-py3-none-any.whl", hash = "sha256:d38e30481def20772f5baf097c122c3babc4fcdb7e14e57049eb9d88c6dc017d", size = 15988, upload-time = "2025-08-14T16:56:01.633Z" }, -] - -[[package]] -name = "flake8" -version = "7.3.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "mccabe" }, - { name = "pycodestyle" }, - { name = "pyflakes" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/9b/af/fbfe3c4b5a657d79e5c47a2827a362f9e1b763336a52f926126aa6dc7123/flake8-7.3.0.tar.gz", hash = "sha256:fe044858146b9fc69b551a4b490d69cf960fcb78ad1edcb84e7fbb1b4a8e3872", size = 48326, upload-time = "2025-06-20T19:31:35.838Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/9f/56/13ab06b4f93ca7cac71078fbe37fcea175d3216f31f85c3168a6bbd0bb9a/flake8-7.3.0-py2.py3-none-any.whl", hash = "sha256:b9696257b9ce8beb888cdbe31cf885c90d31928fe202be0889a7cdafad32f01e", size = 57922, upload-time = "2025-06-20T19:31:34.425Z" }, -] - -[[package]] -name = "flake8-isort" -version = "6.1.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "flake8" }, - { name = "isort" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/7c/ea/2f2662d4fefa6ab335c7119cb28e5bc57c935a86a69a7f72df3ea5fe7b2c/flake8_isort-6.1.2.tar.gz", hash = "sha256:9d0452acdf0e1cd6f2d6848e3605e66b54d920e73471fb4744eef0f93df62d5d", size = 17756, upload-time = "2025-01-29T12:29:25.753Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b3/10/295e982874f2a94f309baf7c45f852a191c87d59bd846b1701332303783f/flake8_isort-6.1.2-py3-none-any.whl", hash = "sha256:549197dedf0273502fb74f04c080beed9e62a7eb70244610413d27052e78bd3b", size = 18385, upload-time = "2025-01-29T12:29:23.46Z" }, -] - -[[package]] -name = "gitdb" -version = "4.0.12" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "smmap" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/72/94/63b0fc47eb32792c7ba1fe1b694daec9a63620db1e313033d18140c2320a/gitdb-4.0.12.tar.gz", hash = "sha256:5ef71f855d191a3326fcfbc0d5da835f26b13fbcba60c32c21091c349ffdb571", size = 394684, upload-time = "2025-01-02T07:20:46.413Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a0/61/5c78b91c3143ed5c14207f463aecfc8f9dbb5092fb2869baf37c273b2705/gitdb-4.0.12-py3-none-any.whl", hash = "sha256:67073e15955400952c6565cc3e707c554a4eea2e428946f7a4c162fab9bd9bcf", size = 62794, upload-time = "2025-01-02T07:20:43.624Z" }, -] - -[[package]] -name = "gitpython" -version = "3.1.45" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "gitdb" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/9a/c8/dd58967d119baab745caec2f9d853297cec1989ec1d63f677d3880632b88/gitpython-3.1.45.tar.gz", hash = "sha256:85b0ee964ceddf211c41b9f27a49086010a190fd8132a24e21f362a4b36a791c", size = 215076, upload-time = "2025-07-24T03:45:54.871Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/01/61/d4b89fec821f72385526e1b9d9a3a0385dda4a72b206d28049e2c7cd39b8/gitpython-3.1.45-py3-none-any.whl", hash = "sha256:8908cb2e02fb3b93b7eb0f2827125cb699869470432cc885f019b8fd0fccff77", size = 208168, upload-time = "2025-07-24T03:45:52.517Z" }, -] - -[[package]] -name = "greenlet" -version = "3.3.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/c7/e5/40dbda2736893e3e53d25838e0f19a2b417dfc122b9989c91918db30b5d3/greenlet-3.3.0.tar.gz", hash = "sha256:a82bb225a4e9e4d653dd2fb7b8b2d36e4fb25bc0165422a11e48b88e9e6f78fb", size = 190651, upload-time = "2025-12-04T14:49:44.05Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/32/6a/33d1702184d94106d3cdd7bfb788e19723206fce152e303473ca3b946c7b/greenlet-3.3.0-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:6f8496d434d5cb2dce025773ba5597f71f5410ae499d5dd9533e0653258cdb3d", size = 273658, upload-time = "2025-12-04T14:23:37.494Z" }, - { url = "https://files.pythonhosted.org/packages/d6/b7/2b5805bbf1907c26e434f4e448cd8b696a0b71725204fa21a211ff0c04a7/greenlet-3.3.0-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b96dc7eef78fd404e022e165ec55327f935b9b52ff355b067eb4a0267fc1cffb", size = 574810, upload-time = "2025-12-04T14:50:04.154Z" }, - { url = "https://files.pythonhosted.org/packages/94/38/343242ec12eddf3d8458c73f555c084359883d4ddc674240d9e61ec51fd6/greenlet-3.3.0-cp310-cp310-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:73631cd5cccbcfe63e3f9492aaa664d278fda0ce5c3d43aeda8e77317e38efbd", size = 586248, upload-time = "2025-12-04T14:57:39.35Z" }, - { url = "https://files.pythonhosted.org/packages/f0/d0/0ae86792fb212e4384041e0ef8e7bc66f59a54912ce407d26a966ed2914d/greenlet-3.3.0-cp310-cp310-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:b299a0cb979f5d7197442dccc3aee67fce53500cd88951b7e6c35575701c980b", size = 597403, upload-time = "2025-12-04T15:07:10.831Z" }, - { url = "https://files.pythonhosted.org/packages/b6/a8/15d0aa26c0036a15d2659175af00954aaaa5d0d66ba538345bd88013b4d7/greenlet-3.3.0-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7dee147740789a4632cace364816046e43310b59ff8fb79833ab043aefa72fd5", size = 586910, upload-time = "2025-12-04T14:25:59.705Z" }, - { url = "https://files.pythonhosted.org/packages/e1/9b/68d5e3b7ccaba3907e5532cf8b9bf16f9ef5056a008f195a367db0ff32db/greenlet-3.3.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:39b28e339fc3c348427560494e28d8a6f3561c8d2bcf7d706e1c624ed8d822b9", size = 1547206, upload-time = "2025-12-04T15:04:21.027Z" }, - { url = "https://files.pythonhosted.org/packages/66/bd/e3086ccedc61e49f91e2cfb5ffad9d8d62e5dc85e512a6200f096875b60c/greenlet-3.3.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:b3c374782c2935cc63b2a27ba8708471de4ad1abaa862ffdb1ef45a643ddbb7d", size = 1613359, upload-time = "2025-12-04T14:27:26.548Z" }, - { url = "https://files.pythonhosted.org/packages/f4/6b/d4e73f5dfa888364bbf02efa85616c6714ae7c631c201349782e5b428925/greenlet-3.3.0-cp310-cp310-win_amd64.whl", hash = "sha256:b49e7ed51876b459bd645d83db257f0180e345d3f768a35a85437a24d5a49082", size = 300740, upload-time = "2025-12-04T14:47:52.773Z" }, - { url = "https://files.pythonhosted.org/packages/1f/cb/48e964c452ca2b92175a9b2dca037a553036cb053ba69e284650ce755f13/greenlet-3.3.0-cp311-cp311-macosx_11_0_universal2.whl", hash = "sha256:e29f3018580e8412d6aaf5641bb7745d38c85228dacf51a73bd4e26ddf2a6a8e", size = 274908, upload-time = "2025-12-04T14:23:26.435Z" }, - { url = "https://files.pythonhosted.org/packages/28/da/38d7bff4d0277b594ec557f479d65272a893f1f2a716cad91efeb8680953/greenlet-3.3.0-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:a687205fb22794e838f947e2194c0566d3812966b41c78709554aa883183fb62", size = 577113, upload-time = "2025-12-04T14:50:05.493Z" }, - { url = "https://files.pythonhosted.org/packages/3c/f2/89c5eb0faddc3ff014f1c04467d67dee0d1d334ab81fadbf3744847f8a8a/greenlet-3.3.0-cp311-cp311-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:4243050a88ba61842186cb9e63c7dfa677ec146160b0efd73b855a3d9c7fcf32", size = 590338, upload-time = "2025-12-04T14:57:41.136Z" }, - { url = "https://files.pythonhosted.org/packages/80/d7/db0a5085035d05134f8c089643da2b44cc9b80647c39e93129c5ef170d8f/greenlet-3.3.0-cp311-cp311-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:670d0f94cd302d81796e37299bcd04b95d62403883b24225c6b5271466612f45", size = 601098, upload-time = "2025-12-04T15:07:11.898Z" }, - { url = "https://files.pythonhosted.org/packages/dc/a6/e959a127b630a58e23529972dbc868c107f9d583b5a9f878fb858c46bc1a/greenlet-3.3.0-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:6cb3a8ec3db4a3b0eb8a3c25436c2d49e3505821802074969db017b87bc6a948", size = 590206, upload-time = "2025-12-04T14:26:01.254Z" }, - { url = "https://files.pythonhosted.org/packages/48/60/29035719feb91798693023608447283b266b12efc576ed013dd9442364bb/greenlet-3.3.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:2de5a0b09eab81fc6a382791b995b1ccf2b172a9fec934747a7a23d2ff291794", size = 1550668, upload-time = "2025-12-04T15:04:22.439Z" }, - { url = "https://files.pythonhosted.org/packages/0a/5f/783a23754b691bfa86bd72c3033aa107490deac9b2ef190837b860996c9f/greenlet-3.3.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:4449a736606bd30f27f8e1ff4678ee193bc47f6ca810d705981cfffd6ce0d8c5", size = 1615483, upload-time = "2025-12-04T14:27:28.083Z" }, - { url = "https://files.pythonhosted.org/packages/1d/d5/c339b3b4bc8198b7caa4f2bd9fd685ac9f29795816d8db112da3d04175bb/greenlet-3.3.0-cp311-cp311-win_amd64.whl", hash = "sha256:7652ee180d16d447a683c04e4c5f6441bae7ba7b17ffd9f6b3aff4605e9e6f71", size = 301164, upload-time = "2025-12-04T14:42:51.577Z" }, - { url = "https://files.pythonhosted.org/packages/f8/0a/a3871375c7b9727edaeeea994bfff7c63ff7804c9829c19309ba2e058807/greenlet-3.3.0-cp312-cp312-macosx_11_0_universal2.whl", hash = "sha256:b01548f6e0b9e9784a2c99c5651e5dc89ffcbe870bc5fb2e5ef864e9cc6b5dcb", size = 276379, upload-time = "2025-12-04T14:23:30.498Z" }, - { url = "https://files.pythonhosted.org/packages/43/ab/7ebfe34dce8b87be0d11dae91acbf76f7b8246bf9d6b319c741f99fa59c6/greenlet-3.3.0-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:349345b770dc88f81506c6861d22a6ccd422207829d2c854ae2af8025af303e3", size = 597294, upload-time = "2025-12-04T14:50:06.847Z" }, - { url = "https://files.pythonhosted.org/packages/a4/39/f1c8da50024feecd0793dbd5e08f526809b8ab5609224a2da40aad3a7641/greenlet-3.3.0-cp312-cp312-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:e8e18ed6995e9e2c0b4ed264d2cf89260ab3ac7e13555b8032b25a74c6d18655", size = 607742, upload-time = "2025-12-04T14:57:42.349Z" }, - { url = "https://files.pythonhosted.org/packages/77/cb/43692bcd5f7a0da6ec0ec6d58ee7cddb606d055ce94a62ac9b1aa481e969/greenlet-3.3.0-cp312-cp312-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:c024b1e5696626890038e34f76140ed1daf858e37496d33f2af57f06189e70d7", size = 622297, upload-time = "2025-12-04T15:07:13.552Z" }, - { url = "https://files.pythonhosted.org/packages/75/b0/6bde0b1011a60782108c01de5913c588cf51a839174538d266de15e4bf4d/greenlet-3.3.0-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:047ab3df20ede6a57c35c14bf5200fcf04039d50f908270d3f9a7a82064f543b", size = 609885, upload-time = "2025-12-04T14:26:02.368Z" }, - { url = "https://files.pythonhosted.org/packages/49/0e/49b46ac39f931f59f987b7cd9f34bfec8ef81d2a1e6e00682f55be5de9f4/greenlet-3.3.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:2d9ad37fc657b1102ec880e637cccf20191581f75c64087a549e66c57e1ceb53", size = 1567424, upload-time = "2025-12-04T15:04:23.757Z" }, - { url = "https://files.pythonhosted.org/packages/05/f5/49a9ac2dff7f10091935def9165c90236d8f175afb27cbed38fb1d61ab6b/greenlet-3.3.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:83cd0e36932e0e7f36a64b732a6f60c2fc2df28c351bae79fbaf4f8092fe7614", size = 1636017, upload-time = "2025-12-04T14:27:29.688Z" }, - { url = "https://files.pythonhosted.org/packages/6c/79/3912a94cf27ec503e51ba493692d6db1e3cd8ac7ac52b0b47c8e33d7f4f9/greenlet-3.3.0-cp312-cp312-win_amd64.whl", hash = "sha256:a7a34b13d43a6b78abf828a6d0e87d3385680eaf830cd60d20d52f249faabf39", size = 301964, upload-time = "2025-12-04T14:36:58.316Z" }, - { url = "https://files.pythonhosted.org/packages/02/2f/28592176381b9ab2cafa12829ba7b472d177f3acc35d8fbcf3673d966fff/greenlet-3.3.0-cp313-cp313-macosx_11_0_universal2.whl", hash = "sha256:a1e41a81c7e2825822f4e068c48cb2196002362619e2d70b148f20a831c00739", size = 275140, upload-time = "2025-12-04T14:23:01.282Z" }, - { url = "https://files.pythonhosted.org/packages/2c/80/fbe937bf81e9fca98c981fe499e59a3f45df2a04da0baa5c2be0dca0d329/greenlet-3.3.0-cp313-cp313-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:9f515a47d02da4d30caaa85b69474cec77b7929b2e936ff7fb853d42f4bf8808", size = 599219, upload-time = "2025-12-04T14:50:08.309Z" }, - { url = "https://files.pythonhosted.org/packages/c2/ff/7c985128f0514271b8268476af89aee6866df5eec04ac17dcfbc676213df/greenlet-3.3.0-cp313-cp313-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:7d2d9fd66bfadf230b385fdc90426fcd6eb64db54b40c495b72ac0feb5766c54", size = 610211, upload-time = "2025-12-04T14:57:43.968Z" }, - { url = "https://files.pythonhosted.org/packages/79/07/c47a82d881319ec18a4510bb30463ed6891f2ad2c1901ed5ec23d3de351f/greenlet-3.3.0-cp313-cp313-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:30a6e28487a790417d036088b3bcb3f3ac7d8babaa7d0139edbaddebf3af9492", size = 624311, upload-time = "2025-12-04T15:07:14.697Z" }, - { url = "https://files.pythonhosted.org/packages/fd/8e/424b8c6e78bd9837d14ff7df01a9829fc883ba2ab4ea787d4f848435f23f/greenlet-3.3.0-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:087ea5e004437321508a8d6f20efc4cfec5e3c30118e1417ea96ed1d93950527", size = 612833, upload-time = "2025-12-04T14:26:03.669Z" }, - { url = "https://files.pythonhosted.org/packages/b5/ba/56699ff9b7c76ca12f1cdc27a886d0f81f2189c3455ff9f65246780f713d/greenlet-3.3.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ab97cf74045343f6c60a39913fa59710e4bd26a536ce7ab2397adf8b27e67c39", size = 1567256, upload-time = "2025-12-04T15:04:25.276Z" }, - { url = "https://files.pythonhosted.org/packages/1e/37/f31136132967982d698c71a281a8901daf1a8fbab935dce7c0cf15f942cc/greenlet-3.3.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:5375d2e23184629112ca1ea89a53389dddbffcf417dad40125713d88eb5f96e8", size = 1636483, upload-time = "2025-12-04T14:27:30.804Z" }, - { url = "https://files.pythonhosted.org/packages/7e/71/ba21c3fb8c5dce83b8c01f458a42e99ffdb1963aeec08fff5a18588d8fd7/greenlet-3.3.0-cp313-cp313-win_amd64.whl", hash = "sha256:9ee1942ea19550094033c35d25d20726e4f1c40d59545815e1128ac58d416d38", size = 301833, upload-time = "2025-12-04T14:32:23.929Z" }, - { url = "https://files.pythonhosted.org/packages/d7/7c/f0a6d0ede2c7bf092d00bc83ad5bafb7e6ec9b4aab2fbdfa6f134dc73327/greenlet-3.3.0-cp314-cp314-macosx_11_0_universal2.whl", hash = "sha256:60c2ef0f578afb3c8d92ea07ad327f9a062547137afe91f38408f08aacab667f", size = 275671, upload-time = "2025-12-04T14:23:05.267Z" }, - { url = "https://files.pythonhosted.org/packages/44/06/dac639ae1a50f5969d82d2e3dd9767d30d6dbdbab0e1a54010c8fe90263c/greenlet-3.3.0-cp314-cp314-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:0a5d554d0712ba1de0a6c94c640f7aeba3f85b3a6e1f2899c11c2c0428da9365", size = 646360, upload-time = "2025-12-04T14:50:10.026Z" }, - { url = "https://files.pythonhosted.org/packages/e0/94/0fb76fe6c5369fba9bf98529ada6f4c3a1adf19e406a47332245ef0eb357/greenlet-3.3.0-cp314-cp314-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:3a898b1e9c5f7307ebbde4102908e6cbfcb9ea16284a3abe15cab996bee8b9b3", size = 658160, upload-time = "2025-12-04T14:57:45.41Z" }, - { url = "https://files.pythonhosted.org/packages/93/79/d2c70cae6e823fac36c3bbc9077962105052b7ef81db2f01ec3b9bf17e2b/greenlet-3.3.0-cp314-cp314-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:dcd2bdbd444ff340e8d6bdf54d2f206ccddbb3ccfdcd3c25bf4afaa7b8f0cf45", size = 671388, upload-time = "2025-12-04T15:07:15.789Z" }, - { url = "https://files.pythonhosted.org/packages/b8/14/bab308fc2c1b5228c3224ec2bf928ce2e4d21d8046c161e44a2012b5203e/greenlet-3.3.0-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:5773edda4dc00e173820722711d043799d3adb4f01731f40619e07ea2750b955", size = 660166, upload-time = "2025-12-04T14:26:05.099Z" }, - { url = "https://files.pythonhosted.org/packages/4b/d2/91465d39164eaa0085177f61983d80ffe746c5a1860f009811d498e7259c/greenlet-3.3.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:ac0549373982b36d5fd5d30beb8a7a33ee541ff98d2b502714a09f1169f31b55", size = 1615193, upload-time = "2025-12-04T15:04:27.041Z" }, - { url = "https://files.pythonhosted.org/packages/42/1b/83d110a37044b92423084d52d5d5a3b3a73cafb51b547e6d7366ff62eff1/greenlet-3.3.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:d198d2d977460358c3b3a4dc844f875d1adb33817f0613f663a656f463764ccc", size = 1683653, upload-time = "2025-12-04T14:27:32.366Z" }, - { url = "https://files.pythonhosted.org/packages/7c/9a/9030e6f9aa8fd7808e9c31ba4c38f87c4f8ec324ee67431d181fe396d705/greenlet-3.3.0-cp314-cp314-win_amd64.whl", hash = "sha256:73f51dd0e0bdb596fb0417e475fa3c5e32d4c83638296e560086b8d7da7c4170", size = 305387, upload-time = "2025-12-04T14:26:51.063Z" }, - { url = "https://files.pythonhosted.org/packages/a0/66/bd6317bc5932accf351fc19f177ffba53712a202f9df10587da8df257c7e/greenlet-3.3.0-cp314-cp314t-macosx_11_0_universal2.whl", hash = "sha256:d6ed6f85fae6cdfdb9ce04c9bf7a08d666cfcfb914e7d006f44f840b46741931", size = 282638, upload-time = "2025-12-04T14:25:20.941Z" }, - { url = "https://files.pythonhosted.org/packages/30/cf/cc81cb030b40e738d6e69502ccbd0dd1bced0588e958f9e757945de24404/greenlet-3.3.0-cp314-cp314t-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d9125050fcf24554e69c4cacb086b87b3b55dc395a8b3ebe6487b045b2614388", size = 651145, upload-time = "2025-12-04T14:50:11.039Z" }, - { url = "https://files.pythonhosted.org/packages/9c/ea/1020037b5ecfe95ca7df8d8549959baceb8186031da83d5ecceff8b08cd2/greenlet-3.3.0-cp314-cp314t-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:87e63ccfa13c0a0f6234ed0add552af24cc67dd886731f2261e46e241608bee3", size = 654236, upload-time = "2025-12-04T14:57:47.007Z" }, - { url = "https://files.pythonhosted.org/packages/69/cc/1e4bae2e45ca2fa55299f4e85854606a78ecc37fead20d69322f96000504/greenlet-3.3.0-cp314-cp314t-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:2662433acbca297c9153a4023fe2161c8dcfdcc91f10433171cf7e7d94ba2221", size = 662506, upload-time = "2025-12-04T15:07:16.906Z" }, - { url = "https://files.pythonhosted.org/packages/57/b9/f8025d71a6085c441a7eaff0fd928bbb275a6633773667023d19179fe815/greenlet-3.3.0-cp314-cp314t-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:3c6e9b9c1527a78520357de498b0e709fb9e2f49c3a513afd5a249007261911b", size = 653783, upload-time = "2025-12-04T14:26:06.225Z" }, - { url = "https://files.pythonhosted.org/packages/f6/c7/876a8c7a7485d5d6b5c6821201d542ef28be645aa024cfe1145b35c120c1/greenlet-3.3.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:286d093f95ec98fdd92fcb955003b8a3d054b4e2cab3e2707a5039e7b50520fd", size = 1614857, upload-time = "2025-12-04T15:04:28.484Z" }, - { url = "https://files.pythonhosted.org/packages/4f/dc/041be1dff9f23dac5f48a43323cd0789cb798342011c19a248d9c9335536/greenlet-3.3.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:6c10513330af5b8ae16f023e8ddbfb486ab355d04467c4679c5cfe4659975dd9", size = 1676034, upload-time = "2025-12-04T14:27:33.531Z" }, -] - -[[package]] -name = "h11" -version = "0.16.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/01/ee/02a2c011bdab74c6fb3c75474d40b3052059d95df7e73351460c8588d963/h11-0.16.0.tar.gz", hash = "sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1", size = 101250, upload-time = "2025-04-24T03:35:25.427Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86", size = 37515, upload-time = "2025-04-24T03:35:24.344Z" }, -] - -[[package]] -name = "httpcore" -version = "1.0.9" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "certifi" }, - { name = "h11" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/06/94/82699a10bca87a5556c9c59b5963f2d039dbd239f25bc2a63907a05a14cb/httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8", size = 85484, upload-time = "2025-04-24T22:06:22.219Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55", size = 78784, upload-time = "2025-04-24T22:06:20.566Z" }, -] - -[[package]] -name = "httpx" -version = "0.28.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "certifi" }, - { name = "httpcore" }, - { name = "idna" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/b1/df/48c586a5fe32a0f01324ee087459e112ebb7224f646c0b5023f5e79e9956/httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc", size = 141406, upload-time = "2024-12-06T15:37:23.222Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad", size = 73517, upload-time = "2024-12-06T15:37:21.509Z" }, -] - -[[package]] -name = "id" -version = "1.5.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "requests" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/22/11/102da08f88412d875fa2f1a9a469ff7ad4c874b0ca6fed0048fe385bdb3d/id-1.5.0.tar.gz", hash = "sha256:292cb8a49eacbbdbce97244f47a97b4c62540169c976552e497fd57df0734c1d", size = 15237, upload-time = "2024-12-04T19:53:05.575Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/9f/cb/18326d2d89ad3b0dd143da971e77afd1e6ca6674f1b1c3df4b6bec6279fc/id-1.5.0-py3-none-any.whl", hash = "sha256:f1434e1cef91f2cbb8a4ec64663d5a23b9ed43ef44c4c957d02583d61714c658", size = 13611, upload-time = "2024-12-04T19:53:03.02Z" }, -] - -[[package]] -name = "identify" -version = "2.6.14" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/52/c4/62963f25a678f6a050fb0505a65e9e726996171e6dbe1547f79619eefb15/identify-2.6.14.tar.gz", hash = "sha256:663494103b4f717cb26921c52f8751363dc89db64364cd836a9bf1535f53cd6a", size = 99283, upload-time = "2025-09-06T19:30:52.938Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e5/ae/2ad30f4652712c82f1c23423d79136fbce338932ad166d70c1efb86a5998/identify-2.6.14-py2.py3-none-any.whl", hash = "sha256:11a073da82212c6646b1f39bb20d4483bfb9543bd5566fec60053c4bb309bf2e", size = 99172, upload-time = "2025-09-06T19:30:51.759Z" }, -] - -[[package]] -name = "idna" -version = "3.10" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f1/70/7703c29685631f5a7590aa73f1f1d3fa9a380e654b86af429e0934a32f7d/idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9", size = 190490, upload-time = "2024-09-15T18:07:39.745Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/76/c6/c88e154df9c4e1a2a66ccf0005a88dfb2650c1dffb6f5ce603dfbd452ce3/idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3", size = 70442, upload-time = "2024-09-15T18:07:37.964Z" }, -] - -[[package]] -name = "importlib-metadata" -version = "8.7.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "zipp" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/76/66/650a33bd90f786193e4de4b3ad86ea60b53c89b669a5c7be931fac31cdb0/importlib_metadata-8.7.0.tar.gz", hash = "sha256:d13b81ad223b890aa16c5471f2ac3056cf76c5f10f82d6f9292f0b415f389000", size = 56641, upload-time = "2025-04-27T15:29:01.736Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/20/b0/36bd937216ec521246249be3bf9855081de4c5e06a0c9b4219dbeda50373/importlib_metadata-8.7.0-py3-none-any.whl", hash = "sha256:e5dd1551894c77868a30651cef00984d50e1002d06942a7101d34870c5f02afd", size = 27656, upload-time = "2025-04-27T15:29:00.214Z" }, -] - -[[package]] -name = "iniconfig" -version = "2.1.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f2/97/ebf4da567aa6827c909642694d71c9fcf53e5b504f2d96afea02718862f3/iniconfig-2.1.0.tar.gz", hash = "sha256:3abbd2e30b36733fee78f9c7f7308f2d0050e88f0087fd25c2645f63c773e1c7", size = 4793, upload-time = "2025-03-19T20:09:59.721Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/2c/e1/e6716421ea10d38022b952c159d5161ca1193197fb744506875fbb87ea7b/iniconfig-2.1.0-py3-none-any.whl", hash = "sha256:9deba5723312380e77435581c6bf4935c94cbfab9b1ed33ef8d238ea168eb760", size = 6050, upload-time = "2025-03-19T20:10:01.071Z" }, -] - -[[package]] -name = "isort" -version = "5.12.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a9/c4/dc00e42c158fc4dda2afebe57d2e948805c06d5169007f1724f0683010a9/isort-5.12.0.tar.gz", hash = "sha256:8bef7dde241278824a6d83f44a544709b065191b95b6e50894bdc722fcba0504", size = 174643, upload-time = "2023-01-28T17:10:22.636Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/0a/63/4036ae70eea279c63e2304b91ee0ac182f467f24f86394ecfe726092340b/isort-5.12.0-py3-none-any.whl", hash = "sha256:f84c2818376e66cf843d497486ea8fed8700b340f308f076c6fb1229dff318b6", size = 91198, upload-time = "2023-01-28T17:10:21.149Z" }, -] - -[[package]] -name = "jaraco-classes" -version = "3.4.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "more-itertools" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/06/c0/ed4a27bc5571b99e3cff68f8a9fa5b56ff7df1c2251cc715a652ddd26402/jaraco.classes-3.4.0.tar.gz", hash = "sha256:47a024b51d0239c0dd8c8540c6c7f484be3b8fcf0b2d85c13825780d3b3f3acd", size = 11780, upload-time = "2024-03-31T07:27:36.643Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7f/66/b15ce62552d84bbfcec9a4873ab79d993a1dd4edb922cbfccae192bd5b5f/jaraco.classes-3.4.0-py3-none-any.whl", hash = "sha256:f662826b6bed8cace05e7ff873ce0f9283b5c924470fe664fff1c2f00f581790", size = 6777, upload-time = "2024-03-31T07:27:34.792Z" }, -] - -[[package]] -name = "jaraco-context" -version = "6.0.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "backports-tarfile", marker = "python_full_version < '3.12'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/df/ad/f3777b81bf0b6e7bc7514a1656d3e637b2e8e15fab2ce3235730b3e7a4e6/jaraco_context-6.0.1.tar.gz", hash = "sha256:9bae4ea555cf0b14938dc0aee7c9f32ed303aa20a3b73e7dc80111628792d1b3", size = 13912, upload-time = "2024-08-20T03:39:27.358Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ff/db/0c52c4cf5e4bd9f5d7135ec7669a3a767af21b3a308e1ed3674881e52b62/jaraco.context-6.0.1-py3-none-any.whl", hash = "sha256:f797fc481b490edb305122c9181830a3a5b76d84ef6d1aef2fb9b47ab956f9e4", size = 6825, upload-time = "2024-08-20T03:39:25.966Z" }, -] - -[[package]] -name = "jaraco-functools" -version = "4.3.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "more-itertools" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/f7/ed/1aa2d585304ec07262e1a83a9889880701079dde796ac7b1d1826f40c63d/jaraco_functools-4.3.0.tar.gz", hash = "sha256:cfd13ad0dd2c47a3600b439ef72d8615d482cedcff1632930d6f28924d92f294", size = 19755, upload-time = "2025-08-18T20:05:09.91Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b4/09/726f168acad366b11e420df31bf1c702a54d373a83f968d94141a8c3fde0/jaraco_functools-4.3.0-py3-none-any.whl", hash = "sha256:227ff8ed6f7b8f62c56deff101545fa7543cf2c8e7b82a7c2116e672f29c26e8", size = 10408, upload-time = "2025-08-18T20:05:08.69Z" }, -] - -[[package]] -name = "jeepney" -version = "0.9.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/7b/6f/357efd7602486741aa73ffc0617fb310a29b588ed0fd69c2399acbb85b0c/jeepney-0.9.0.tar.gz", hash = "sha256:cf0e9e845622b81e4a28df94c40345400256ec608d0e55bb8a3feaa9163f5732", size = 106758, upload-time = "2025-02-27T18:51:01.684Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b2/a3/e137168c9c44d18eff0376253da9f1e9234d0239e0ee230d2fee6cea8e55/jeepney-0.9.0-py3-none-any.whl", hash = "sha256:97e5714520c16fc0a45695e5365a2e11b81ea79bba796e26f9f1d178cb182683", size = 49010, upload-time = "2025-02-27T18:51:00.104Z" }, -] - -[[package]] -name = "jiter" -version = "0.11.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/9d/c0/a3bb4cc13aced219dd18191ea66e874266bd8aa7b96744e495e1c733aa2d/jiter-0.11.0.tar.gz", hash = "sha256:1d9637eaf8c1d6a63d6562f2a6e5ab3af946c66037eb1b894e8fad75422266e4", size = 167094, upload-time = "2025-09-15T09:20:38.212Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/25/21/7dd1235a19e26979be6098e87e4cced2e061752f3a40a17bbce6dea7fae1/jiter-0.11.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:3893ce831e1c0094a83eeaf56c635a167d6fa8cc14393cc14298fd6fdc2a2449", size = 309875, upload-time = "2025-09-15T09:18:48.41Z" }, - { url = "https://files.pythonhosted.org/packages/71/f9/462b54708aa85b135733ccba70529dd68a18511bf367a87c5fd28676c841/jiter-0.11.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:25c625b9b61b5a8725267fdf867ef2e51b429687f6a4eef211f4612e95607179", size = 316505, upload-time = "2025-09-15T09:18:51.057Z" }, - { url = "https://files.pythonhosted.org/packages/bd/40/14e2eeaac6a47bff27d213834795472355fd39769272eb53cb7aa83d5aa8/jiter-0.11.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dd4ca85fb6a62cf72e1c7f5e34ddef1b660ce4ed0886ec94a1ef9777d35eaa1f", size = 337613, upload-time = "2025-09-15T09:18:52.358Z" }, - { url = "https://files.pythonhosted.org/packages/d3/ed/a5f1f8419c92b150a7c7fb5ccba1fb1e192887ad713d780e70874f0ce996/jiter-0.11.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:572208127034725e79c28437b82414028c3562335f2b4f451d98136d0fc5f9cd", size = 361438, upload-time = "2025-09-15T09:18:54.637Z" }, - { url = "https://files.pythonhosted.org/packages/dd/f5/70682c023dfcdd463a53faf5d30205a7d99c51d70d3e303c932d0936e5a2/jiter-0.11.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:494ba627c7f550ad3dabb21862864b8f2216098dc18ff62f37b37796f2f7c325", size = 486180, upload-time = "2025-09-15T09:18:56.158Z" }, - { url = "https://files.pythonhosted.org/packages/7c/39/020d08cbab4eab48142ad88b837c41eb08a15c0767fdb7c0d3265128a44b/jiter-0.11.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b8da18a99f58bca3ecc2d2bba99cac000a924e115b6c4f0a2b98f752b6fbf39a", size = 376681, upload-time = "2025-09-15T09:18:57.553Z" }, - { url = "https://files.pythonhosted.org/packages/52/10/b86733f6e594cf51dd142f37c602d8df87c554c5844958deaab0de30eb5d/jiter-0.11.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e4ffd3b0fff3fabbb02cc09910c08144db6bb5697a98d227a074401e01ee63dd", size = 348685, upload-time = "2025-09-15T09:18:59.208Z" }, - { url = "https://files.pythonhosted.org/packages/fb/ee/8861665e83a9e703aa5f65fddddb6225428e163e6b0baa95a7f9a8fb9aae/jiter-0.11.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:8fe6530aa738a4f7d4e4702aa8f9581425d04036a5f9e25af65ebe1f708f23be", size = 385573, upload-time = "2025-09-15T09:19:00.593Z" }, - { url = "https://files.pythonhosted.org/packages/25/74/05afec03600951f128293813b5a208c9ba1bf587c57a344c05a42a69e1b1/jiter-0.11.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e35d66681c133a03d7e974e7eedae89720fe8ca3bd09f01a4909b86a8adf31f5", size = 516669, upload-time = "2025-09-15T09:19:02.369Z" }, - { url = "https://files.pythonhosted.org/packages/93/d1/2e5bfe147cfbc2a5eef7f73eb75dc5c6669da4fa10fc7937181d93af9495/jiter-0.11.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:c59459beca2fbc9718b6f1acb7bfb59ebc3eb4294fa4d40e9cb679dafdcc6c60", size = 508767, upload-time = "2025-09-15T09:19:04.011Z" }, - { url = "https://files.pythonhosted.org/packages/87/50/597f71307e10426b5c082fd05d38c615ddbdd08c3348d8502963307f0652/jiter-0.11.0-cp310-cp310-win32.whl", hash = "sha256:b7b0178417b0dcfc5f259edbc6db2b1f5896093ed9035ee7bab0f2be8854726d", size = 205476, upload-time = "2025-09-15T09:19:05.594Z" }, - { url = "https://files.pythonhosted.org/packages/c7/86/1e5214b3272e311754da26e63edec93a183811d4fc2e0118addec365df8b/jiter-0.11.0-cp310-cp310-win_amd64.whl", hash = "sha256:11df2bf99fb4754abddd7f5d940a48e51f9d11624d6313ca4314145fcad347f0", size = 204708, upload-time = "2025-09-15T09:19:06.955Z" }, - { url = "https://files.pythonhosted.org/packages/38/55/a69fefeef09c2eaabae44b935a1aa81517e49639c0a0c25d861cb18cd7ac/jiter-0.11.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:cb5d9db02979c3f49071fce51a48f4b4e4cf574175fb2b11c7a535fa4867b222", size = 309503, upload-time = "2025-09-15T09:19:08.191Z" }, - { url = "https://files.pythonhosted.org/packages/bd/d5/a6aba9e6551f32f9c127184f398208e4eddb96c59ac065c8a92056089d28/jiter-0.11.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1dc6a123f3471c4730db7ca8ba75f1bb3dcb6faeb8d46dd781083e7dee88b32d", size = 317688, upload-time = "2025-09-15T09:19:09.918Z" }, - { url = "https://files.pythonhosted.org/packages/bb/f3/5e86f57c1883971cdc8535d0429c2787bf734840a231da30a3be12850562/jiter-0.11.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:09858f8d230f031c7b8e557429102bf050eea29c77ad9c34c8fe253c5329acb7", size = 337418, upload-time = "2025-09-15T09:19:11.078Z" }, - { url = "https://files.pythonhosted.org/packages/5e/4f/a71d8a24c2a70664970574a8e0b766663f5ef788f7fe1cc20ee0c016d488/jiter-0.11.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:dbe2196c4a0ce760925a74ab4456bf644748ab0979762139626ad138f6dac72d", size = 361423, upload-time = "2025-09-15T09:19:13.286Z" }, - { url = "https://files.pythonhosted.org/packages/8f/e5/b09076f4e7fd9471b91e16f9f3dc7330b161b738f3b39b2c37054a36e26a/jiter-0.11.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5beb56d22b63647bafd0b74979216fdee80c580c0c63410be8c11053860ffd09", size = 486367, upload-time = "2025-09-15T09:19:14.546Z" }, - { url = "https://files.pythonhosted.org/packages/fb/f1/98cb3a36f5e62f80cd860f0179f948d9eab5a316d55d3e1bab98d9767af5/jiter-0.11.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:97025d09ef549795d8dc720a824312cee3253c890ac73c621721ddfc75066789", size = 376335, upload-time = "2025-09-15T09:19:15.939Z" }, - { url = "https://files.pythonhosted.org/packages/9f/d8/ec74886497ea393c29dbd7651ddecc1899e86404a6b1f84a3ddab0ab59fd/jiter-0.11.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d50880a6da65d8c23a2cf53c412847d9757e74cc9a3b95c5704a1d1a24667347", size = 348981, upload-time = "2025-09-15T09:19:17.568Z" }, - { url = "https://files.pythonhosted.org/packages/24/93/d22ad7fa3b86ade66c86153ceea73094fc2af8b20c59cb7fceab9fea4704/jiter-0.11.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:452d80a1c86c095a242007bd9fc5d21b8a8442307193378f891cb8727e469648", size = 385797, upload-time = "2025-09-15T09:19:19.121Z" }, - { url = "https://files.pythonhosted.org/packages/c8/bd/e25ff4a4df226e9b885f7cb01ee4b9dc74e3000e612d6f723860d71a1f34/jiter-0.11.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:e84e58198d4894668eec2da660ffff60e0f3e60afa790ecc50cb12b0e02ca1d4", size = 516597, upload-time = "2025-09-15T09:19:20.301Z" }, - { url = "https://files.pythonhosted.org/packages/be/fb/beda613db7d93ffa2fdd2683f90f2f5dce8daf4bc2d0d2829e7de35308c6/jiter-0.11.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:df64edcfc5dd5279a791eea52aa113d432c933119a025b0b5739f90d2e4e75f1", size = 508853, upload-time = "2025-09-15T09:19:22.075Z" }, - { url = "https://files.pythonhosted.org/packages/20/64/c5b0d93490634e41e38e2a15de5d54fdbd2c9f64a19abb0f95305b63373c/jiter-0.11.0-cp311-cp311-win32.whl", hash = "sha256:144fc21337d21b1d048f7f44bf70881e1586401d405ed3a98c95a114a9994982", size = 205140, upload-time = "2025-09-15T09:19:23.351Z" }, - { url = "https://files.pythonhosted.org/packages/a1/e6/c347c0e6f5796e97d4356b7e5ff0ce336498b7f4ef848fae621a56f1ccf3/jiter-0.11.0-cp311-cp311-win_amd64.whl", hash = "sha256:b0f32e644d241293b892b1a6dd8f0b9cc029bfd94c97376b2681c36548aabab7", size = 204311, upload-time = "2025-09-15T09:19:24.591Z" }, - { url = "https://files.pythonhosted.org/packages/ba/b5/3009b112b8f673e568ef79af9863d8309a15f0a8cdcc06ed6092051f377e/jiter-0.11.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:2fb7b377688cc3850bbe5c192a6bd493562a0bc50cbc8b047316428fbae00ada", size = 305510, upload-time = "2025-09-15T09:19:25.893Z" }, - { url = "https://files.pythonhosted.org/packages/fe/82/15514244e03b9e71e086bbe2a6de3e4616b48f07d5f834200c873956fb8c/jiter-0.11.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:a1b7cbe3f25bd0d8abb468ba4302a5d45617ee61b2a7a638f63fee1dc086be99", size = 316521, upload-time = "2025-09-15T09:19:27.525Z" }, - { url = "https://files.pythonhosted.org/packages/92/94/7a2e905f40ad2d6d660e00b68d818f9e29fb87ffe82774f06191e93cbe4a/jiter-0.11.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c0a7f0ec81d5b7588c5cade1eb1925b91436ae6726dc2df2348524aeabad5de6", size = 338214, upload-time = "2025-09-15T09:19:28.727Z" }, - { url = "https://files.pythonhosted.org/packages/a8/9c/5791ed5bdc76f12110158d3316a7a3ec0b1413d018b41c5ed399549d3ad5/jiter-0.11.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:07630bb46ea2a6b9c6ed986c6e17e35b26148cce2c535454b26ee3f0e8dcaba1", size = 361280, upload-time = "2025-09-15T09:19:30.013Z" }, - { url = "https://files.pythonhosted.org/packages/d4/7f/b7d82d77ff0d2cb06424141000176b53a9e6b16a1125525bb51ea4990c2e/jiter-0.11.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7764f27d28cd4a9cbc61704dfcd80c903ce3aad106a37902d3270cd6673d17f4", size = 487895, upload-time = "2025-09-15T09:19:31.424Z" }, - { url = "https://files.pythonhosted.org/packages/42/44/10a1475d46f1fc1fd5cc2e82c58e7bca0ce5852208e0fa5df2f949353321/jiter-0.11.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:1d4a6c4a737d486f77f842aeb22807edecb4a9417e6700c7b981e16d34ba7c72", size = 378421, upload-time = "2025-09-15T09:19:32.746Z" }, - { url = "https://files.pythonhosted.org/packages/9a/5f/0dc34563d8164d31d07bc09d141d3da08157a68dcd1f9b886fa4e917805b/jiter-0.11.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cf408d2a0abd919b60de8c2e7bc5eeab72d4dafd18784152acc7c9adc3291591", size = 347932, upload-time = "2025-09-15T09:19:34.612Z" }, - { url = "https://files.pythonhosted.org/packages/f7/de/b68f32a4fcb7b4a682b37c73a0e5dae32180140cd1caf11aef6ad40ddbf2/jiter-0.11.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:cdef53eda7d18e799625023e1e250dbc18fbc275153039b873ec74d7e8883e09", size = 386959, upload-time = "2025-09-15T09:19:35.994Z" }, - { url = "https://files.pythonhosted.org/packages/76/0a/c08c92e713b6e28972a846a81ce374883dac2f78ec6f39a0dad9f2339c3a/jiter-0.11.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:53933a38ef7b551dd9c7f1064f9d7bb235bb3168d0fa5f14f0798d1b7ea0d9c5", size = 517187, upload-time = "2025-09-15T09:19:37.426Z" }, - { url = "https://files.pythonhosted.org/packages/89/b5/4a283bec43b15aad54fcae18d951f06a2ec3f78db5708d3b59a48e9c3fbd/jiter-0.11.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:11840d2324c9ab5162fc1abba23bc922124fedcff0d7b7f85fffa291e2f69206", size = 509461, upload-time = "2025-09-15T09:19:38.761Z" }, - { url = "https://files.pythonhosted.org/packages/34/a5/f8bad793010534ea73c985caaeef8cc22dfb1fedb15220ecdf15c623c07a/jiter-0.11.0-cp312-cp312-win32.whl", hash = "sha256:4f01a744d24a5f2bb4a11657a1b27b61dc038ae2e674621a74020406e08f749b", size = 206664, upload-time = "2025-09-15T09:19:40.096Z" }, - { url = "https://files.pythonhosted.org/packages/ed/42/5823ec2b1469395a160b4bf5f14326b4a098f3b6898fbd327366789fa5d3/jiter-0.11.0-cp312-cp312-win_amd64.whl", hash = "sha256:29fff31190ab3a26de026da2f187814f4b9c6695361e20a9ac2123e4d4378a4c", size = 203520, upload-time = "2025-09-15T09:19:41.798Z" }, - { url = "https://files.pythonhosted.org/packages/97/c4/d530e514d0f4f29b2b68145e7b389cbc7cac7f9c8c23df43b04d3d10fa3e/jiter-0.11.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:4441a91b80a80249f9a6452c14b2c24708f139f64de959943dfeaa6cb915e8eb", size = 305021, upload-time = "2025-09-15T09:19:43.523Z" }, - { url = "https://files.pythonhosted.org/packages/7a/77/796a19c567c5734cbfc736a6f987affc0d5f240af8e12063c0fb93990ffa/jiter-0.11.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:ff85fc6d2a431251ad82dbd1ea953affb5a60376b62e7d6809c5cd058bb39471", size = 314384, upload-time = "2025-09-15T09:19:44.849Z" }, - { url = "https://files.pythonhosted.org/packages/14/9c/824334de0b037b91b6f3fa9fe5a191c83977c7ec4abe17795d3cb6d174cf/jiter-0.11.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c5e86126d64706fd28dfc46f910d496923c6f95b395138c02d0e252947f452bd", size = 337389, upload-time = "2025-09-15T09:19:46.094Z" }, - { url = "https://files.pythonhosted.org/packages/a2/95/ed4feab69e6cf9b2176ea29d4ef9d01a01db210a3a2c8a31a44ecdc68c38/jiter-0.11.0-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4ad8bd82165961867a10f52010590ce0b7a8c53da5ddd8bbb62fef68c181b921", size = 360519, upload-time = "2025-09-15T09:19:47.494Z" }, - { url = "https://files.pythonhosted.org/packages/b5/0c/2ad00f38d3e583caba3909d95b7da1c3a7cd82c0aa81ff4317a8016fb581/jiter-0.11.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b42c2cd74273455ce439fd9528db0c6e84b5623cb74572305bdd9f2f2961d3df", size = 487198, upload-time = "2025-09-15T09:19:49.116Z" }, - { url = "https://files.pythonhosted.org/packages/ea/8b/919b64cf3499b79bdfba6036da7b0cac5d62d5c75a28fb45bad7819e22f0/jiter-0.11.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f0062dab98172dd0599fcdbf90214d0dcde070b1ff38a00cc1b90e111f071982", size = 377835, upload-time = "2025-09-15T09:19:50.468Z" }, - { url = "https://files.pythonhosted.org/packages/29/7f/8ebe15b6e0a8026b0d286c083b553779b4dd63db35b43a3f171b544de91d/jiter-0.11.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bb948402821bc76d1f6ef0f9e19b816f9b09f8577844ba7140f0b6afe994bc64", size = 347655, upload-time = "2025-09-15T09:19:51.726Z" }, - { url = "https://files.pythonhosted.org/packages/8e/64/332127cef7e94ac75719dda07b9a472af6158ba819088d87f17f3226a769/jiter-0.11.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:25a5b1110cca7329fd0daf5060faa1234be5c11e988948e4f1a1923b6a457fe1", size = 386135, upload-time = "2025-09-15T09:19:53.075Z" }, - { url = "https://files.pythonhosted.org/packages/20/c8/557b63527442f84c14774159948262a9d4fabb0d61166f11568f22fc60d2/jiter-0.11.0-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:bf11807e802a214daf6c485037778843fadd3e2ec29377ae17e0706ec1a25758", size = 516063, upload-time = "2025-09-15T09:19:54.447Z" }, - { url = "https://files.pythonhosted.org/packages/86/13/4164c819df4a43cdc8047f9a42880f0ceef5afeb22e8b9675c0528ebdccd/jiter-0.11.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:dbb57da40631c267861dd0090461222060960012d70fd6e4c799b0f62d0ba166", size = 508139, upload-time = "2025-09-15T09:19:55.764Z" }, - { url = "https://files.pythonhosted.org/packages/fa/70/6e06929b401b331d41ddb4afb9f91cd1168218e3371972f0afa51c9f3c31/jiter-0.11.0-cp313-cp313-win32.whl", hash = "sha256:8e36924dad32c48d3c5e188d169e71dc6e84d6cb8dedefea089de5739d1d2f80", size = 206369, upload-time = "2025-09-15T09:19:57.048Z" }, - { url = "https://files.pythonhosted.org/packages/f4/0d/8185b8e15de6dce24f6afae63380e16377dd75686d56007baa4f29723ea1/jiter-0.11.0-cp313-cp313-win_amd64.whl", hash = "sha256:452d13e4fd59698408087235259cebe67d9d49173b4dacb3e8d35ce4acf385d6", size = 202538, upload-time = "2025-09-15T09:19:58.35Z" }, - { url = "https://files.pythonhosted.org/packages/13/3a/d61707803260d59520721fa326babfae25e9573a88d8b7b9cb54c5423a59/jiter-0.11.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:089f9df9f69532d1339e83142438668f52c97cd22ee2d1195551c2b1a9e6cf33", size = 313737, upload-time = "2025-09-15T09:19:59.638Z" }, - { url = "https://files.pythonhosted.org/packages/cd/cc/c9f0eec5d00f2a1da89f6bdfac12b8afdf8d5ad974184863c75060026457/jiter-0.11.0-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:29ed1fe69a8c69bf0f2a962d8d706c7b89b50f1332cd6b9fbda014f60bd03a03", size = 346183, upload-time = "2025-09-15T09:20:01.442Z" }, - { url = "https://files.pythonhosted.org/packages/a6/87/fc632776344e7aabbab05a95a0075476f418c5d29ab0f2eec672b7a1f0ac/jiter-0.11.0-cp313-cp313t-win_amd64.whl", hash = "sha256:a4d71d7ea6ea8786291423fe209acf6f8d398a0759d03e7f24094acb8ab686ba", size = 204225, upload-time = "2025-09-15T09:20:03.102Z" }, - { url = "https://files.pythonhosted.org/packages/ee/3b/e7f45be7d3969bdf2e3cd4b816a7a1d272507cd0edd2d6dc4b07514f2d9a/jiter-0.11.0-cp314-cp314-macosx_10_12_x86_64.whl", hash = "sha256:9a6dff27eca70930bdbe4cbb7c1a4ba8526e13b63dc808c0670083d2d51a4a72", size = 304414, upload-time = "2025-09-15T09:20:04.357Z" }, - { url = "https://files.pythonhosted.org/packages/06/32/13e8e0d152631fcc1907ceb4943711471be70496d14888ec6e92034e2caf/jiter-0.11.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:b1ae2a7593a62132c7d4c2abbee80bbbb94fdc6d157e2c6cc966250c564ef774", size = 314223, upload-time = "2025-09-15T09:20:05.631Z" }, - { url = "https://files.pythonhosted.org/packages/0c/7e/abedd5b5a20ca083f778d96bba0d2366567fcecb0e6e34ff42640d5d7a18/jiter-0.11.0-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7b13a431dba4b059e9e43019d3022346d009baf5066c24dcdea321a303cde9f0", size = 337306, upload-time = "2025-09-15T09:20:06.917Z" }, - { url = "https://files.pythonhosted.org/packages/ac/e2/30d59bdc1204c86aa975ec72c48c482fee6633120ee9c3ab755e4dfefea8/jiter-0.11.0-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:af62e84ca3889604ebb645df3b0a3f3bcf6b92babbff642bd214616f57abb93a", size = 360565, upload-time = "2025-09-15T09:20:08.283Z" }, - { url = "https://files.pythonhosted.org/packages/fe/88/567288e0d2ed9fa8f7a3b425fdaf2cb82b998633c24fe0d98f5417321aa8/jiter-0.11.0-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c6f3b32bb723246e6b351aecace52aba78adb8eeb4b2391630322dc30ff6c773", size = 486465, upload-time = "2025-09-15T09:20:09.613Z" }, - { url = "https://files.pythonhosted.org/packages/18/6e/7b72d09273214cadd15970e91dd5ed9634bee605176107db21e1e4205eb1/jiter-0.11.0-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:adcab442f4a099a358a7f562eaa54ed6456fb866e922c6545a717be51dbed7d7", size = 377581, upload-time = "2025-09-15T09:20:10.884Z" }, - { url = "https://files.pythonhosted.org/packages/58/52/4db456319f9d14deed325f70102577492e9d7e87cf7097bda9769a1fcacb/jiter-0.11.0-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c9967c2ab338ee2b2c0102fd379ec2693c496abf71ffd47e4d791d1f593b68e2", size = 347102, upload-time = "2025-09-15T09:20:12.175Z" }, - { url = "https://files.pythonhosted.org/packages/ce/b4/433d5703c38b26083aec7a733eb5be96f9c6085d0e270a87ca6482cbf049/jiter-0.11.0-cp314-cp314-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e7d0bed3b187af8b47a981d9742ddfc1d9b252a7235471ad6078e7e4e5fe75c2", size = 386477, upload-time = "2025-09-15T09:20:13.428Z" }, - { url = "https://files.pythonhosted.org/packages/c8/7a/a60bfd9c55b55b07c5c441c5085f06420b6d493ce9db28d069cc5b45d9f3/jiter-0.11.0-cp314-cp314-musllinux_1_1_aarch64.whl", hash = "sha256:f6fe0283e903ebc55f1a6cc569b8c1f3bf4abd026fed85e3ff8598a9e6f982f0", size = 516004, upload-time = "2025-09-15T09:20:14.848Z" }, - { url = "https://files.pythonhosted.org/packages/2e/46/f8363e5ecc179b4ed0ca6cb0a6d3bfc266078578c71ff30642ea2ce2f203/jiter-0.11.0-cp314-cp314-musllinux_1_1_x86_64.whl", hash = "sha256:4ee5821e3d66606b29ae5b497230b304f1376f38137d69e35f8d2bd5f310ff73", size = 507855, upload-time = "2025-09-15T09:20:16.176Z" }, - { url = "https://files.pythonhosted.org/packages/90/33/396083357d51d7ff0f9805852c288af47480d30dd31d8abc74909b020761/jiter-0.11.0-cp314-cp314-win32.whl", hash = "sha256:c2d13ba7567ca8799f17c76ed56b1d49be30df996eb7fa33e46b62800562a5e2", size = 205802, upload-time = "2025-09-15T09:20:17.661Z" }, - { url = "https://files.pythonhosted.org/packages/e7/ab/eb06ca556b2551d41de7d03bf2ee24285fa3d0c58c5f8d95c64c9c3281b1/jiter-0.11.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:fb4790497369d134a07fc763cc88888c46f734abdd66f9fdf7865038bf3a8f40", size = 313405, upload-time = "2025-09-15T09:20:18.918Z" }, - { url = "https://files.pythonhosted.org/packages/af/22/7ab7b4ec3a1c1f03aef376af11d23b05abcca3fb31fbca1e7557053b1ba2/jiter-0.11.0-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6e2bbf24f16ba5ad4441a9845e40e4ea0cb9eed00e76ba94050664ef53ef4406", size = 347102, upload-time = "2025-09-15T09:20:20.16Z" }, - { url = "https://files.pythonhosted.org/packages/70/f3/ce100253c80063a7b8b406e1d1562657fd4b9b4e1b562db40e68645342fb/jiter-0.11.0-graalpy311-graalpy242_311_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:902b43386c04739229076bd1c4c69de5d115553d982ab442a8ae82947c72ede7", size = 336380, upload-time = "2025-09-15T09:20:36.867Z" }, -] - -[[package]] -name = "jsonpatch" -version = "1.33" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "jsonpointer" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/42/78/18813351fe5d63acad16aec57f94ec2b70a09e53ca98145589e185423873/jsonpatch-1.33.tar.gz", hash = "sha256:9fcd4009c41e6d12348b4a0ff2563ba56a2923a7dfee731d004e212e1ee5030c", size = 21699, upload-time = "2023-06-26T12:07:29.144Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/73/07/02e16ed01e04a374e644b575638ec7987ae846d25ad97bcc9945a3ee4b0e/jsonpatch-1.33-py2.py3-none-any.whl", hash = "sha256:0ae28c0cd062bbd8b8ecc26d7d164fbbea9652a1a3693f3b956c1eae5145dade", size = 12898, upload-time = "2023-06-16T21:01:28.466Z" }, -] - -[[package]] -name = "jsonpointer" -version = "3.0.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/6a/0a/eebeb1fa92507ea94016a2a790b93c2ae41a7e18778f85471dc54475ed25/jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef", size = 9114, upload-time = "2024-06-10T19:24:42.462Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl", hash = "sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942", size = 7595, upload-time = "2024-06-10T19:24:40.698Z" }, -] - -[[package]] -name = "keyring" -version = "25.6.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "importlib-metadata", marker = "python_full_version < '3.12'" }, - { name = "jaraco-classes" }, - { name = "jaraco-context" }, - { name = "jaraco-functools" }, - { name = "jeepney", marker = "sys_platform == 'linux'" }, - { name = "pywin32-ctypes", marker = "sys_platform == 'win32'" }, - { name = "secretstorage", marker = "sys_platform == 'linux'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/70/09/d904a6e96f76ff214be59e7aa6ef7190008f52a0ab6689760a98de0bf37d/keyring-25.6.0.tar.gz", hash = "sha256:0b39998aa941431eb3d9b0d4b2460bc773b9df6fed7621c2dfb291a7e0187a66", size = 62750, upload-time = "2024-12-25T15:26:45.782Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d3/32/da7f44bcb1105d3e88a0b74ebdca50c59121d2ddf71c9e34ba47df7f3a56/keyring-25.6.0-py3-none-any.whl", hash = "sha256:552a3f7af126ece7ed5c89753650eec89c7eaae8617d0aa4d9ad2b75111266bd", size = 39085, upload-time = "2024-12-25T15:26:44.377Z" }, -] - -[[package]] -name = "langchain" -version = "0.3.27" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "async-timeout", marker = "python_full_version < '3.11'" }, - { name = "langchain-core" }, - { name = "langchain-text-splitters" }, - { name = "langsmith" }, - { name = "pydantic" }, - { name = "pyyaml" }, - { name = "requests" }, - { name = "sqlalchemy" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/83/f6/f4f7f3a56626fe07e2bb330feb61254dbdf06c506e6b59a536a337da51cf/langchain-0.3.27.tar.gz", hash = "sha256:aa6f1e6274ff055d0fd36254176770f356ed0a8994297d1df47df341953cec62", size = 10233809, upload-time = "2025-07-24T14:42:32.959Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/f6/d5/4861816a95b2f6993f1360cfb605aacb015506ee2090433a71de9cca8477/langchain-0.3.27-py3-none-any.whl", hash = "sha256:7b20c4f338826acb148d885b20a73a16e410ede9ee4f19bb02011852d5f98798", size = 1018194, upload-time = "2025-07-24T14:42:30.23Z" }, -] - -[[package]] -name = "langchain-anthropic" -version = "0.3.22" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anthropic" }, - { name = "langchain-core" }, - { name = "pydantic" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/b8/ac/4791e4451e1972f80cb517e19d003678239921fc0685a4c4b265fe47e216/langchain_anthropic-0.3.22.tar.gz", hash = "sha256:6c440278bd8012bc94ae341f416bfc724fdc5d2d2b69630fe6e82fa6ee9682ac", size = 471312, upload-time = "2025-10-09T18:39:26.983Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d1/ac/019fd9d45716a4d74c154f160665074ae49885ff4764c8313737f5fda348/langchain_anthropic-0.3.22-py3-none-any.whl", hash = "sha256:17721b240342a1a3f70bf0b2ff33520ba60d69008e3b9433190a62a52ff87cf6", size = 32592, upload-time = "2025-10-09T18:39:25.766Z" }, -] - -[[package]] -name = "langchain-core" -version = "0.3.83" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "jsonpatch" }, - { name = "langsmith" }, - { name = "packaging" }, - { name = "pydantic" }, - { name = "pyyaml" }, - { name = "tenacity" }, - { name = "typing-extensions" }, - { name = "uuid-utils" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/21/a4/24f2d787bfcf56e5990924cacefe6f6e7971a3629f97c8162fc7a2a3d851/langchain_core-0.3.83.tar.gz", hash = "sha256:a0a4c7b6ea1c446d3b432116f405dc2afa1fe7891c44140d3d5acca221909415", size = 597965, upload-time = "2026-01-13T01:19:23.854Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/5a/db/d71b80d3bd6193812485acea4001cdf86cf95a44bbf942f7a240120ff762/langchain_core-0.3.83-py3-none-any.whl", hash = "sha256:8c92506f8b53fc1958b1c07447f58c5783eb8833dd3cb6dc75607c80891ab1ae", size = 458890, upload-time = "2026-01-13T01:19:21.748Z" }, -] - -[[package]] -name = "langchain-openai" -version = "0.3.35" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "openai" }, - { name = "tiktoken" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/fb/96/06d0d25a37e05a0ff2d918f0a4b0bf0732aed6a43b472b0b68426ce04ef8/langchain_openai-0.3.35.tar.gz", hash = "sha256:fa985fd041c3809da256a040c98e8a43e91c6d165b96dcfeb770d8bd457bf76f", size = 786635, upload-time = "2025-10-06T15:09:28.463Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d8/d5/c90c5478215c20ee71d8feaf676f7ffd78d0568f8c98bd83f81ce7562ed7/langchain_openai-0.3.35-py3-none-any.whl", hash = "sha256:76d5707e6e81fd461d33964ad618bd326cb661a1975cef7c1cb0703576bdada5", size = 75952, upload-time = "2025-10-06T15:09:27.137Z" }, -] - -[[package]] -name = "langchain-text-splitters" -version = "0.3.11" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/11/43/dcda8fd25f0b19cb2835f2f6bb67f26ad58634f04ac2d8eae00526b0fa55/langchain_text_splitters-0.3.11.tar.gz", hash = "sha256:7a50a04ada9a133bbabb80731df7f6ddac51bc9f1b9cab7fa09304d71d38a6cc", size = 46458, upload-time = "2025-08-31T23:02:58.316Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/58/0d/41a51b40d24ff0384ec4f7ab8dd3dcea8353c05c973836b5e289f1465d4f/langchain_text_splitters-0.3.11-py3-none-any.whl", hash = "sha256:cf079131166a487f1372c8ab5d0bfaa6c0a4291733d9c43a34a16ac9bcd6a393", size = 33845, upload-time = "2025-08-31T23:02:57.195Z" }, -] - -[[package]] -name = "langgraph" -version = "0.3.34" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "langgraph-checkpoint" }, - { name = "langgraph-prebuilt" }, - { name = "langgraph-sdk" }, - { name = "xxhash" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/3a/85/147f69a6b7cd3f91cc9d6d981ed25698b4dfda67ef8d004d938e8b79ab00/langgraph-0.3.34.tar.gz", hash = "sha256:d4107b2101ee4a6f93f33b0fac1064d46ac3491f783200affac29f229ab0b93c", size = 122551, upload-time = "2025-04-24T14:26:55.287Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/50/51/6a631ce322422b0b8944dac4d74c23bfa2ca52fbb3ee56c868c4ee033bdb/langgraph-0.3.34-py3-none-any.whl", hash = "sha256:4bf8af313ce7686e8a7597ca5441341ec89f9a9fe73ba1b07c116755efa3117d", size = 148191, upload-time = "2025-04-24T14:26:53.676Z" }, -] - -[[package]] -name = "langgraph-checkpoint" -version = "2.1.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "ormsgpack" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/73/3e/d00eb2b56c3846a0cabd2e5aa71c17a95f882d4f799a6ffe96a19b55eba9/langgraph_checkpoint-2.1.1.tar.gz", hash = "sha256:72038c0f9e22260cb9bff1f3ebe5eb06d940b7ee5c1e4765019269d4f21cf92d", size = 136256, upload-time = "2025-07-17T13:07:52.411Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/4c/dd/64686797b0927fb18b290044be12ae9d4df01670dce6bb2498d5ab65cb24/langgraph_checkpoint-2.1.1-py3-none-any.whl", hash = "sha256:5a779134fd28134a9a83d078be4450bbf0e0c79fdf5e992549658899e6fc5ea7", size = 43925, upload-time = "2025-07-17T13:07:51.023Z" }, -] - -[[package]] -name = "langgraph-prebuilt" -version = "0.1.8" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "langgraph-checkpoint" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/57/30/f31f0e076c37d097b53e4cff5d479a3686e1991f6c86a1a4727d5d1f5489/langgraph_prebuilt-0.1.8.tar.gz", hash = "sha256:4de7659151829b2b955b6798df6800e580e617782c15c2c5b29b139697491831", size = 24543, upload-time = "2025-04-03T16:04:19.932Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/36/72/9e092665502f8f52f2708065ed14fbbba3f95d1a1b65d62049b0c5fcdf00/langgraph_prebuilt-0.1.8-py3-none-any.whl", hash = "sha256:ae97b828ae00be2cefec503423aa782e1bff165e9b94592e224da132f2526968", size = 25903, upload-time = "2025-04-03T16:04:18.993Z" }, -] - -[[package]] -name = "langgraph-sdk" -version = "0.1.74" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "httpx" }, - { name = "orjson" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/6d/f7/3807b72988f7eef5e0eb41e7e695eca50f3ed31f7cab5602db3b651c85ff/langgraph_sdk-0.1.74.tar.gz", hash = "sha256:7450e0db5b226cc2e5328ca22c5968725873630ef47c4206a30707cb25dc3ad6", size = 72190, upload-time = "2025-07-21T16:36:50.032Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/1f/1a/3eacc4df8127781ee4b0b1e5cad7dbaf12510f58c42cbcb9d1e2dba2a164/langgraph_sdk-0.1.74-py3-none-any.whl", hash = "sha256:3a265c3757fe0048adad4391d10486db63ef7aa5a2cbd22da22d4503554cb890", size = 50254, upload-time = "2025-07-21T16:36:49.134Z" }, -] - -[[package]] -name = "langsmith" -version = "0.4.30" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "httpx" }, - { name = "orjson", marker = "platform_python_implementation != 'PyPy'" }, - { name = "packaging" }, - { name = "pydantic" }, - { name = "requests" }, - { name = "requests-toolbelt" }, - { name = "zstandard" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/fe/d5/4cc88f246ce615a518a715cd2bf40001d1678ad6805a3706a90570adca8f/langsmith-0.4.30.tar.gz", hash = "sha256:388fe1060aca6507be41f417c7d4168a92dffe27f28bb6ef8a1bfee4a59f3681", size = 958857, upload-time = "2025-09-22T19:05:14.156Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ae/d1/b2b2ea7b443c6b028aca209d2e653256912906900cc146e64c65201211b7/langsmith-0.4.30-py3-none-any.whl", hash = "sha256:110767eb83e6da2cc99cfc61958631b5c36624758b52e7af35ec5550ad846cb3", size = 386300, upload-time = "2025-09-22T19:05:11.819Z" }, -] - -[[package]] -name = "markdown-it-py" -version = "4.0.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "mdurl" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/5b/f5/4ec618ed16cc4f8fb3b701563655a69816155e79e24a17b651541804721d/markdown_it_py-4.0.0.tar.gz", hash = "sha256:cb0a2b4aa34f932c007117b194e945bd74e0ec24133ceb5bac59009cda1cb9f3", size = 73070, upload-time = "2025-08-11T12:57:52.854Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/94/54/e7d793b573f298e1c9013b8c4dade17d481164aa517d1d7148619c2cedbf/markdown_it_py-4.0.0-py3-none-any.whl", hash = "sha256:87327c59b172c5011896038353a81343b6754500a08cd7a4973bb48c6d578147", size = 87321, upload-time = "2025-08-11T12:57:51.923Z" }, -] - -[[package]] -name = "mccabe" -version = "0.7.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/e7/ff/0ffefdcac38932a54d2b5eed4e0ba8a408f215002cd178ad1df0f2806ff8/mccabe-0.7.0.tar.gz", hash = "sha256:348e0240c33b60bbdf4e523192ef919f28cb2c3d7d5c7794f74009290f236325", size = 9658, upload-time = "2022-01-24T01:14:51.113Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/27/1a/1f68f9ba0c207934b35b86a8ca3aad8395a3d6dd7921c0686e23853ff5a9/mccabe-0.7.0-py2.py3-none-any.whl", hash = "sha256:6c2d30ab6be0e4a46919781807b4f0d834ebdd6c6e3dca0bda5a15f863427b6e", size = 7350, upload-time = "2022-01-24T01:14:49.62Z" }, -] - -[[package]] -name = "mdurl" -version = "0.1.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/d6/54/cfe61301667036ec958cb99bd3efefba235e65cdeb9c84d24a8293ba1d90/mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba", size = 8729, upload-time = "2022-08-14T12:40:10.846Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b3/38/89ba8ad64ae25be8de66a6d463314cf1eb366222074cfda9ee839c56a4b4/mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8", size = 9979, upload-time = "2022-08-14T12:40:09.779Z" }, -] - -[[package]] -name = "more-itertools" -version = "10.8.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ea/5d/38b681d3fce7a266dd9ab73c66959406d565b3e85f21d5e66e1181d93721/more_itertools-10.8.0.tar.gz", hash = "sha256:f638ddf8a1a0d134181275fb5d58b086ead7c6a72429ad725c67503f13ba30bd", size = 137431, upload-time = "2025-09-02T15:23:11.018Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a4/8e/469e5a4a2f5855992e425f3cb33804cc07bf18d48f2db061aec61ce50270/more_itertools-10.8.0-py3-none-any.whl", hash = "sha256:52d4362373dcf7c52546bc4af9a86ee7c4579df9a8dc268be0a2f949d376cc9b", size = 69667, upload-time = "2025-09-02T15:23:09.635Z" }, -] - -[[package]] -name = "multidict" -version = "6.6.4" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions", marker = "python_full_version < '3.11'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/69/7f/0652e6ed47ab288e3756ea9c0df8b14950781184d4bd7883f4d87dd41245/multidict-6.6.4.tar.gz", hash = "sha256:d2d4e4787672911b48350df02ed3fa3fffdc2f2e8ca06dd6afdf34189b76a9dd", size = 101843, upload-time = "2025-08-11T12:08:48.217Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/eb/6b/86f353088c1358e76fd30b0146947fddecee812703b604ee901e85cd2a80/multidict-6.6.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:b8aa6f0bd8125ddd04a6593437bad6a7e70f300ff4180a531654aa2ab3f6d58f", size = 77054, upload-time = "2025-08-11T12:06:02.99Z" }, - { url = "https://files.pythonhosted.org/packages/19/5d/c01dc3d3788bb877bd7f5753ea6eb23c1beeca8044902a8f5bfb54430f63/multidict-6.6.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b9e5853bbd7264baca42ffc53391b490d65fe62849bf2c690fa3f6273dbcd0cb", size = 44914, upload-time = "2025-08-11T12:06:05.264Z" }, - { url = "https://files.pythonhosted.org/packages/46/44/964dae19ea42f7d3e166474d8205f14bb811020e28bc423d46123ddda763/multidict-6.6.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0af5f9dee472371e36d6ae38bde009bd8ce65ac7335f55dcc240379d7bed1495", size = 44601, upload-time = "2025-08-11T12:06:06.627Z" }, - { url = "https://files.pythonhosted.org/packages/31/20/0616348a1dfb36cb2ab33fc9521de1f27235a397bf3f59338e583afadd17/multidict-6.6.4-cp310-cp310-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:d24f351e4d759f5054b641c81e8291e5d122af0fca5c72454ff77f7cbe492de8", size = 224821, upload-time = "2025-08-11T12:06:08.06Z" }, - { url = "https://files.pythonhosted.org/packages/14/26/5d8923c69c110ff51861af05bd27ca6783011b96725d59ccae6d9daeb627/multidict-6.6.4-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:db6a3810eec08280a172a6cd541ff4a5f6a97b161d93ec94e6c4018917deb6b7", size = 242608, upload-time = "2025-08-11T12:06:09.697Z" }, - { url = "https://files.pythonhosted.org/packages/5c/cc/e2ad3ba9459aa34fa65cf1f82a5c4a820a2ce615aacfb5143b8817f76504/multidict-6.6.4-cp310-cp310-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:a1b20a9d56b2d81e2ff52ecc0670d583eaabaa55f402e8d16dd062373dbbe796", size = 222324, upload-time = "2025-08-11T12:06:10.905Z" }, - { url = "https://files.pythonhosted.org/packages/19/db/4ed0f65701afbc2cb0c140d2d02928bb0fe38dd044af76e58ad7c54fd21f/multidict-6.6.4-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:8c9854df0eaa610a23494c32a6f44a3a550fb398b6b51a56e8c6b9b3689578db", size = 253234, upload-time = "2025-08-11T12:06:12.658Z" }, - { url = "https://files.pythonhosted.org/packages/94/c1/5160c9813269e39ae14b73debb907bfaaa1beee1762da8c4fb95df4764ed/multidict-6.6.4-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:4bb7627fd7a968f41905a4d6343b0d63244a0623f006e9ed989fa2b78f4438a0", size = 251613, upload-time = "2025-08-11T12:06:13.97Z" }, - { url = "https://files.pythonhosted.org/packages/05/a9/48d1bd111fc2f8fb98b2ed7f9a115c55a9355358432a19f53c0b74d8425d/multidict-6.6.4-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:caebafea30ed049c57c673d0b36238b1748683be2593965614d7b0e99125c877", size = 241649, upload-time = "2025-08-11T12:06:15.204Z" }, - { url = "https://files.pythonhosted.org/packages/85/2a/f7d743df0019408768af8a70d2037546a2be7b81fbb65f040d76caafd4c5/multidict-6.6.4-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:ad887a8250eb47d3ab083d2f98db7f48098d13d42eb7a3b67d8a5c795f224ace", size = 239238, upload-time = "2025-08-11T12:06:16.467Z" }, - { url = "https://files.pythonhosted.org/packages/cb/b8/4f4bb13323c2d647323f7919201493cf48ebe7ded971717bfb0f1a79b6bf/multidict-6.6.4-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:ed8358ae7d94ffb7c397cecb62cbac9578a83ecefc1eba27b9090ee910e2efb6", size = 233517, upload-time = "2025-08-11T12:06:18.107Z" }, - { url = "https://files.pythonhosted.org/packages/33/29/4293c26029ebfbba4f574febd2ed01b6f619cfa0d2e344217d53eef34192/multidict-6.6.4-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:ecab51ad2462197a4c000b6d5701fc8585b80eecb90583635d7e327b7b6923eb", size = 243122, upload-time = "2025-08-11T12:06:19.361Z" }, - { url = "https://files.pythonhosted.org/packages/20/60/a1c53628168aa22447bfde3a8730096ac28086704a0d8c590f3b63388d0c/multidict-6.6.4-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:c5c97aa666cf70e667dfa5af945424ba1329af5dd988a437efeb3a09430389fb", size = 248992, upload-time = "2025-08-11T12:06:20.661Z" }, - { url = "https://files.pythonhosted.org/packages/a3/3b/55443a0c372f33cae5d9ec37a6a973802884fa0ab3586659b197cf8cc5e9/multidict-6.6.4-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:9a950b7cf54099c1209f455ac5970b1ea81410f2af60ed9eb3c3f14f0bfcf987", size = 243708, upload-time = "2025-08-11T12:06:21.891Z" }, - { url = "https://files.pythonhosted.org/packages/7c/60/a18c6900086769312560b2626b18e8cca22d9e85b1186ba77f4755b11266/multidict-6.6.4-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:163c7ea522ea9365a8a57832dea7618e6cbdc3cd75f8c627663587459a4e328f", size = 237498, upload-time = "2025-08-11T12:06:23.206Z" }, - { url = "https://files.pythonhosted.org/packages/11/3d/8bdd8bcaff2951ce2affccca107a404925a2beafedd5aef0b5e4a71120a6/multidict-6.6.4-cp310-cp310-win32.whl", hash = "sha256:17d2cbbfa6ff20821396b25890f155f40c986f9cfbce5667759696d83504954f", size = 41415, upload-time = "2025-08-11T12:06:24.77Z" }, - { url = "https://files.pythonhosted.org/packages/c0/53/cab1ad80356a4cd1b685a254b680167059b433b573e53872fab245e9fc95/multidict-6.6.4-cp310-cp310-win_amd64.whl", hash = "sha256:ce9a40fbe52e57e7edf20113a4eaddfacac0561a0879734e636aa6d4bb5e3fb0", size = 46046, upload-time = "2025-08-11T12:06:25.893Z" }, - { url = "https://files.pythonhosted.org/packages/cf/9a/874212b6f5c1c2d870d0a7adc5bb4cfe9b0624fa15cdf5cf757c0f5087ae/multidict-6.6.4-cp310-cp310-win_arm64.whl", hash = "sha256:01d0959807a451fe9fdd4da3e139cb5b77f7328baf2140feeaf233e1d777b729", size = 43147, upload-time = "2025-08-11T12:06:27.534Z" }, - { url = "https://files.pythonhosted.org/packages/6b/7f/90a7f01e2d005d6653c689039977f6856718c75c5579445effb7e60923d1/multidict-6.6.4-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:c7a0e9b561e6460484318a7612e725df1145d46b0ef57c6b9866441bf6e27e0c", size = 76472, upload-time = "2025-08-11T12:06:29.006Z" }, - { url = "https://files.pythonhosted.org/packages/54/a3/bed07bc9e2bb302ce752f1dabc69e884cd6a676da44fb0e501b246031fdd/multidict-6.6.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6bf2f10f70acc7a2446965ffbc726e5fc0b272c97a90b485857e5c70022213eb", size = 44634, upload-time = "2025-08-11T12:06:30.374Z" }, - { url = "https://files.pythonhosted.org/packages/a7/4b/ceeb4f8f33cf81277da464307afeaf164fb0297947642585884f5cad4f28/multidict-6.6.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:66247d72ed62d5dd29752ffc1d3b88f135c6a8de8b5f63b7c14e973ef5bda19e", size = 44282, upload-time = "2025-08-11T12:06:31.958Z" }, - { url = "https://files.pythonhosted.org/packages/03/35/436a5da8702b06866189b69f655ffdb8f70796252a8772a77815f1812679/multidict-6.6.4-cp311-cp311-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:105245cc6b76f51e408451a844a54e6823bbd5a490ebfe5bdfc79798511ceded", size = 229696, upload-time = "2025-08-11T12:06:33.087Z" }, - { url = "https://files.pythonhosted.org/packages/b6/0e/915160be8fecf1fca35f790c08fb74ca684d752fcba62c11daaf3d92c216/multidict-6.6.4-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:cbbc54e58b34c3bae389ef00046be0961f30fef7cb0dd9c7756aee376a4f7683", size = 246665, upload-time = "2025-08-11T12:06:34.448Z" }, - { url = "https://files.pythonhosted.org/packages/08/ee/2f464330acd83f77dcc346f0b1a0eaae10230291450887f96b204b8ac4d3/multidict-6.6.4-cp311-cp311-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:56c6b3652f945c9bc3ac6c8178cd93132b8d82dd581fcbc3a00676c51302bc1a", size = 225485, upload-time = "2025-08-11T12:06:35.672Z" }, - { url = "https://files.pythonhosted.org/packages/71/cc/9a117f828b4d7fbaec6adeed2204f211e9caf0a012692a1ee32169f846ae/multidict-6.6.4-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:b95494daf857602eccf4c18ca33337dd2be705bccdb6dddbfc9d513e6addb9d9", size = 257318, upload-time = "2025-08-11T12:06:36.98Z" }, - { url = "https://files.pythonhosted.org/packages/25/77/62752d3dbd70e27fdd68e86626c1ae6bccfebe2bb1f84ae226363e112f5a/multidict-6.6.4-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:e5b1413361cef15340ab9dc61523e653d25723e82d488ef7d60a12878227ed50", size = 254689, upload-time = "2025-08-11T12:06:38.233Z" }, - { url = "https://files.pythonhosted.org/packages/00/6e/fac58b1072a6fc59af5e7acb245e8754d3e1f97f4f808a6559951f72a0d4/multidict-6.6.4-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:e167bf899c3d724f9662ef00b4f7fef87a19c22b2fead198a6f68b263618df52", size = 246709, upload-time = "2025-08-11T12:06:39.517Z" }, - { url = "https://files.pythonhosted.org/packages/01/ef/4698d6842ef5e797c6db7744b0081e36fb5de3d00002cc4c58071097fac3/multidict-6.6.4-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:aaea28ba20a9026dfa77f4b80369e51cb767c61e33a2d4043399c67bd95fb7c6", size = 243185, upload-time = "2025-08-11T12:06:40.796Z" }, - { url = "https://files.pythonhosted.org/packages/aa/c9/d82e95ae1d6e4ef396934e9b0e942dfc428775f9554acf04393cce66b157/multidict-6.6.4-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:8c91cdb30809a96d9ecf442ec9bc45e8cfaa0f7f8bdf534e082c2443a196727e", size = 237838, upload-time = "2025-08-11T12:06:42.595Z" }, - { url = "https://files.pythonhosted.org/packages/57/cf/f94af5c36baaa75d44fab9f02e2a6bcfa0cd90acb44d4976a80960759dbc/multidict-6.6.4-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:1a0ccbfe93ca114c5d65a2471d52d8829e56d467c97b0e341cf5ee45410033b3", size = 246368, upload-time = "2025-08-11T12:06:44.304Z" }, - { url = "https://files.pythonhosted.org/packages/4a/fe/29f23460c3d995f6a4b678cb2e9730e7277231b981f0b234702f0177818a/multidict-6.6.4-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:55624b3f321d84c403cb7d8e6e982f41ae233d85f85db54ba6286f7295dc8a9c", size = 253339, upload-time = "2025-08-11T12:06:45.597Z" }, - { url = "https://files.pythonhosted.org/packages/29/b6/fd59449204426187b82bf8a75f629310f68c6adc9559dc922d5abe34797b/multidict-6.6.4-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:4a1fb393a2c9d202cb766c76208bd7945bc194eba8ac920ce98c6e458f0b524b", size = 246933, upload-time = "2025-08-11T12:06:46.841Z" }, - { url = "https://files.pythonhosted.org/packages/19/52/d5d6b344f176a5ac3606f7a61fb44dc746e04550e1a13834dff722b8d7d6/multidict-6.6.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:43868297a5759a845fa3a483fb4392973a95fb1de891605a3728130c52b8f40f", size = 242225, upload-time = "2025-08-11T12:06:48.588Z" }, - { url = "https://files.pythonhosted.org/packages/ec/d3/5b2281ed89ff4d5318d82478a2a2450fcdfc3300da48ff15c1778280ad26/multidict-6.6.4-cp311-cp311-win32.whl", hash = "sha256:ed3b94c5e362a8a84d69642dbeac615452e8af9b8eb825b7bc9f31a53a1051e2", size = 41306, upload-time = "2025-08-11T12:06:49.95Z" }, - { url = "https://files.pythonhosted.org/packages/74/7d/36b045c23a1ab98507aefd44fd8b264ee1dd5e5010543c6fccf82141ccef/multidict-6.6.4-cp311-cp311-win_amd64.whl", hash = "sha256:d8c112f7a90d8ca5d20213aa41eac690bb50a76da153e3afb3886418e61cb22e", size = 46029, upload-time = "2025-08-11T12:06:51.082Z" }, - { url = "https://files.pythonhosted.org/packages/0f/5e/553d67d24432c5cd52b49047f2d248821843743ee6d29a704594f656d182/multidict-6.6.4-cp311-cp311-win_arm64.whl", hash = "sha256:3bb0eae408fa1996d87247ca0d6a57b7fc1dcf83e8a5c47ab82c558c250d4adf", size = 43017, upload-time = "2025-08-11T12:06:52.243Z" }, - { url = "https://files.pythonhosted.org/packages/05/f6/512ffd8fd8b37fb2680e5ac35d788f1d71bbaf37789d21a820bdc441e565/multidict-6.6.4-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:0ffb87be160942d56d7b87b0fdf098e81ed565add09eaa1294268c7f3caac4c8", size = 76516, upload-time = "2025-08-11T12:06:53.393Z" }, - { url = "https://files.pythonhosted.org/packages/99/58/45c3e75deb8855c36bd66cc1658007589662ba584dbf423d01df478dd1c5/multidict-6.6.4-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:d191de6cbab2aff5de6c5723101705fd044b3e4c7cfd587a1929b5028b9714b3", size = 45394, upload-time = "2025-08-11T12:06:54.555Z" }, - { url = "https://files.pythonhosted.org/packages/fd/ca/e8c4472a93a26e4507c0b8e1f0762c0d8a32de1328ef72fd704ef9cc5447/multidict-6.6.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:38a0956dd92d918ad5feff3db8fcb4a5eb7dba114da917e1a88475619781b57b", size = 43591, upload-time = "2025-08-11T12:06:55.672Z" }, - { url = "https://files.pythonhosted.org/packages/05/51/edf414f4df058574a7265034d04c935aa84a89e79ce90fcf4df211f47b16/multidict-6.6.4-cp312-cp312-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:6865f6d3b7900ae020b495d599fcf3765653bc927951c1abb959017f81ae8287", size = 237215, upload-time = "2025-08-11T12:06:57.213Z" }, - { url = "https://files.pythonhosted.org/packages/c8/45/8b3d6dbad8cf3252553cc41abea09ad527b33ce47a5e199072620b296902/multidict-6.6.4-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:0a2088c126b6f72db6c9212ad827d0ba088c01d951cee25e758c450da732c138", size = 258299, upload-time = "2025-08-11T12:06:58.946Z" }, - { url = "https://files.pythonhosted.org/packages/3c/e8/8ca2e9a9f5a435fc6db40438a55730a4bf4956b554e487fa1b9ae920f825/multidict-6.6.4-cp312-cp312-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:0f37bed7319b848097085d7d48116f545985db988e2256b2e6f00563a3416ee6", size = 242357, upload-time = "2025-08-11T12:07:00.301Z" }, - { url = "https://files.pythonhosted.org/packages/0f/84/80c77c99df05a75c28490b2af8f7cba2a12621186e0a8b0865d8e745c104/multidict-6.6.4-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:01368e3c94032ba6ca0b78e7ccb099643466cf24f8dc8eefcfdc0571d56e58f9", size = 268369, upload-time = "2025-08-11T12:07:01.638Z" }, - { url = "https://files.pythonhosted.org/packages/0d/e9/920bfa46c27b05fb3e1ad85121fd49f441492dca2449c5bcfe42e4565d8a/multidict-6.6.4-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:8fe323540c255db0bffee79ad7f048c909f2ab0edb87a597e1c17da6a54e493c", size = 269341, upload-time = "2025-08-11T12:07:02.943Z" }, - { url = "https://files.pythonhosted.org/packages/af/65/753a2d8b05daf496f4a9c367fe844e90a1b2cac78e2be2c844200d10cc4c/multidict-6.6.4-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b8eb3025f17b0a4c3cd08cda49acf312a19ad6e8a4edd9dbd591e6506d999402", size = 256100, upload-time = "2025-08-11T12:07:04.564Z" }, - { url = "https://files.pythonhosted.org/packages/09/54/655be13ae324212bf0bc15d665a4e34844f34c206f78801be42f7a0a8aaa/multidict-6.6.4-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:bbc14f0365534d35a06970d6a83478b249752e922d662dc24d489af1aa0d1be7", size = 253584, upload-time = "2025-08-11T12:07:05.914Z" }, - { url = "https://files.pythonhosted.org/packages/5c/74/ab2039ecc05264b5cec73eb018ce417af3ebb384ae9c0e9ed42cb33f8151/multidict-6.6.4-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:75aa52fba2d96bf972e85451b99d8e19cc37ce26fd016f6d4aa60da9ab2b005f", size = 251018, upload-time = "2025-08-11T12:07:08.301Z" }, - { url = "https://files.pythonhosted.org/packages/af/0a/ccbb244ac848e56c6427f2392741c06302bbfba49c0042f1eb3c5b606497/multidict-6.6.4-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:4fefd4a815e362d4f011919d97d7b4a1e566f1dde83dc4ad8cfb5b41de1df68d", size = 251477, upload-time = "2025-08-11T12:07:10.248Z" }, - { url = "https://files.pythonhosted.org/packages/0e/b0/0ed49bba775b135937f52fe13922bc64a7eaf0a3ead84a36e8e4e446e096/multidict-6.6.4-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:db9801fe021f59a5b375ab778973127ca0ac52429a26e2fd86aa9508f4d26eb7", size = 263575, upload-time = "2025-08-11T12:07:11.928Z" }, - { url = "https://files.pythonhosted.org/packages/3e/d9/7fb85a85e14de2e44dfb6a24f03c41e2af8697a6df83daddb0e9b7569f73/multidict-6.6.4-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:a650629970fa21ac1fb06ba25dabfc5b8a2054fcbf6ae97c758aa956b8dba802", size = 259649, upload-time = "2025-08-11T12:07:13.244Z" }, - { url = "https://files.pythonhosted.org/packages/03/9e/b3a459bcf9b6e74fa461a5222a10ff9b544cb1cd52fd482fb1b75ecda2a2/multidict-6.6.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:452ff5da78d4720d7516a3a2abd804957532dd69296cb77319c193e3ffb87e24", size = 251505, upload-time = "2025-08-11T12:07:14.57Z" }, - { url = "https://files.pythonhosted.org/packages/86/a2/8022f78f041dfe6d71e364001a5cf987c30edfc83c8a5fb7a3f0974cff39/multidict-6.6.4-cp312-cp312-win32.whl", hash = "sha256:8c2fcb12136530ed19572bbba61b407f655e3953ba669b96a35036a11a485793", size = 41888, upload-time = "2025-08-11T12:07:15.904Z" }, - { url = "https://files.pythonhosted.org/packages/c7/eb/d88b1780d43a56db2cba24289fa744a9d216c1a8546a0dc3956563fd53ea/multidict-6.6.4-cp312-cp312-win_amd64.whl", hash = "sha256:047d9425860a8c9544fed1b9584f0c8bcd31bcde9568b047c5e567a1025ecd6e", size = 46072, upload-time = "2025-08-11T12:07:17.045Z" }, - { url = "https://files.pythonhosted.org/packages/9f/16/b929320bf5750e2d9d4931835a4c638a19d2494a5b519caaaa7492ebe105/multidict-6.6.4-cp312-cp312-win_arm64.whl", hash = "sha256:14754eb72feaa1e8ae528468f24250dd997b8e2188c3d2f593f9eba259e4b364", size = 43222, upload-time = "2025-08-11T12:07:18.328Z" }, - { url = "https://files.pythonhosted.org/packages/3a/5d/e1db626f64f60008320aab00fbe4f23fc3300d75892a3381275b3d284580/multidict-6.6.4-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:f46a6e8597f9bd71b31cc708195d42b634c8527fecbcf93febf1052cacc1f16e", size = 75848, upload-time = "2025-08-11T12:07:19.912Z" }, - { url = "https://files.pythonhosted.org/packages/4c/aa/8b6f548d839b6c13887253af4e29c939af22a18591bfb5d0ee6f1931dae8/multidict-6.6.4-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:22e38b2bc176c5eb9c0a0e379f9d188ae4cd8b28c0f53b52bce7ab0a9e534657", size = 45060, upload-time = "2025-08-11T12:07:21.163Z" }, - { url = "https://files.pythonhosted.org/packages/eb/c6/f5e97e5d99a729bc2aa58eb3ebfa9f1e56a9b517cc38c60537c81834a73f/multidict-6.6.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:5df8afd26f162da59e218ac0eefaa01b01b2e6cd606cffa46608f699539246da", size = 43269, upload-time = "2025-08-11T12:07:22.392Z" }, - { url = "https://files.pythonhosted.org/packages/dc/31/d54eb0c62516776f36fe67f84a732f97e0b0e12f98d5685bebcc6d396910/multidict-6.6.4-cp313-cp313-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:49517449b58d043023720aa58e62b2f74ce9b28f740a0b5d33971149553d72aa", size = 237158, upload-time = "2025-08-11T12:07:23.636Z" }, - { url = "https://files.pythonhosted.org/packages/c4/1c/8a10c1c25b23156e63b12165a929d8eb49a6ed769fdbefb06e6f07c1e50d/multidict-6.6.4-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:ae9408439537c5afdca05edd128a63f56a62680f4b3c234301055d7a2000220f", size = 257076, upload-time = "2025-08-11T12:07:25.049Z" }, - { url = "https://files.pythonhosted.org/packages/ad/86/90e20b5771d6805a119e483fd3d1e8393e745a11511aebca41f0da38c3e2/multidict-6.6.4-cp313-cp313-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:87a32d20759dc52a9e850fe1061b6e41ab28e2998d44168a8a341b99ded1dba0", size = 240694, upload-time = "2025-08-11T12:07:26.458Z" }, - { url = "https://files.pythonhosted.org/packages/e7/49/484d3e6b535bc0555b52a0a26ba86e4d8d03fd5587d4936dc59ba7583221/multidict-6.6.4-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:52e3c8d43cdfff587ceedce9deb25e6ae77daba560b626e97a56ddcad3756879", size = 266350, upload-time = "2025-08-11T12:07:27.94Z" }, - { url = "https://files.pythonhosted.org/packages/bf/b4/aa4c5c379b11895083d50021e229e90c408d7d875471cb3abf721e4670d6/multidict-6.6.4-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:ad8850921d3a8d8ff6fbef790e773cecfc260bbfa0566998980d3fa8f520bc4a", size = 267250, upload-time = "2025-08-11T12:07:29.303Z" }, - { url = "https://files.pythonhosted.org/packages/80/e5/5e22c5bf96a64bdd43518b1834c6d95a4922cc2066b7d8e467dae9b6cee6/multidict-6.6.4-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:497a2954adc25c08daff36f795077f63ad33e13f19bfff7736e72c785391534f", size = 254900, upload-time = "2025-08-11T12:07:30.764Z" }, - { url = "https://files.pythonhosted.org/packages/17/38/58b27fed927c07035abc02befacab42491e7388ca105e087e6e0215ead64/multidict-6.6.4-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:024ce601f92d780ca1617ad4be5ac15b501cc2414970ffa2bb2bbc2bd5a68fa5", size = 252355, upload-time = "2025-08-11T12:07:32.205Z" }, - { url = "https://files.pythonhosted.org/packages/d0/a1/dad75d23a90c29c02b5d6f3d7c10ab36c3197613be5d07ec49c7791e186c/multidict-6.6.4-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:a693fc5ed9bdd1c9e898013e0da4dcc640de7963a371c0bd458e50e046bf6438", size = 250061, upload-time = "2025-08-11T12:07:33.623Z" }, - { url = "https://files.pythonhosted.org/packages/b8/1a/ac2216b61c7f116edab6dc3378cca6c70dc019c9a457ff0d754067c58b20/multidict-6.6.4-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:190766dac95aab54cae5b152a56520fd99298f32a1266d66d27fdd1b5ac00f4e", size = 249675, upload-time = "2025-08-11T12:07:34.958Z" }, - { url = "https://files.pythonhosted.org/packages/d4/79/1916af833b800d13883e452e8e0977c065c4ee3ab7a26941fbfdebc11895/multidict-6.6.4-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:34d8f2a5ffdceab9dcd97c7a016deb2308531d5f0fced2bb0c9e1df45b3363d7", size = 261247, upload-time = "2025-08-11T12:07:36.588Z" }, - { url = "https://files.pythonhosted.org/packages/c5/65/d1f84fe08ac44a5fc7391cbc20a7cedc433ea616b266284413fd86062f8c/multidict-6.6.4-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:59e8d40ab1f5a8597abcef00d04845155a5693b5da00d2c93dbe88f2050f2812", size = 257960, upload-time = "2025-08-11T12:07:39.735Z" }, - { url = "https://files.pythonhosted.org/packages/13/b5/29ec78057d377b195ac2c5248c773703a6b602e132a763e20ec0457e7440/multidict-6.6.4-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:467fe64138cfac771f0e949b938c2e1ada2b5af22f39692aa9258715e9ea613a", size = 250078, upload-time = "2025-08-11T12:07:41.525Z" }, - { url = "https://files.pythonhosted.org/packages/c4/0e/7e79d38f70a872cae32e29b0d77024bef7834b0afb406ddae6558d9e2414/multidict-6.6.4-cp313-cp313-win32.whl", hash = "sha256:14616a30fe6d0a48d0a48d1a633ab3b8bec4cf293aac65f32ed116f620adfd69", size = 41708, upload-time = "2025-08-11T12:07:43.405Z" }, - { url = "https://files.pythonhosted.org/packages/9d/34/746696dffff742e97cd6a23da953e55d0ea51fa601fa2ff387b3edcfaa2c/multidict-6.6.4-cp313-cp313-win_amd64.whl", hash = "sha256:40cd05eaeb39e2bc8939451f033e57feaa2ac99e07dbca8afe2be450a4a3b6cf", size = 45912, upload-time = "2025-08-11T12:07:45.082Z" }, - { url = "https://files.pythonhosted.org/packages/c7/87/3bac136181e271e29170d8d71929cdeddeb77f3e8b6a0c08da3a8e9da114/multidict-6.6.4-cp313-cp313-win_arm64.whl", hash = "sha256:f6eb37d511bfae9e13e82cb4d1af36b91150466f24d9b2b8a9785816deb16605", size = 43076, upload-time = "2025-08-11T12:07:46.746Z" }, - { url = "https://files.pythonhosted.org/packages/64/94/0a8e63e36c049b571c9ae41ee301ada29c3fee9643d9c2548d7d558a1d99/multidict-6.6.4-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:6c84378acd4f37d1b507dfa0d459b449e2321b3ba5f2338f9b085cf7a7ba95eb", size = 82812, upload-time = "2025-08-11T12:07:48.402Z" }, - { url = "https://files.pythonhosted.org/packages/25/1a/be8e369dfcd260d2070a67e65dd3990dd635cbd735b98da31e00ea84cd4e/multidict-6.6.4-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:0e0558693063c75f3d952abf645c78f3c5dfdd825a41d8c4d8156fc0b0da6e7e", size = 48313, upload-time = "2025-08-11T12:07:49.679Z" }, - { url = "https://files.pythonhosted.org/packages/26/5a/dd4ade298674b2f9a7b06a32c94ffbc0497354df8285f27317c66433ce3b/multidict-6.6.4-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:3f8e2384cb83ebd23fd07e9eada8ba64afc4c759cd94817433ab8c81ee4b403f", size = 46777, upload-time = "2025-08-11T12:07:51.318Z" }, - { url = "https://files.pythonhosted.org/packages/89/db/98aa28bc7e071bfba611ac2ae803c24e96dd3a452b4118c587d3d872c64c/multidict-6.6.4-cp313-cp313t-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:f996b87b420995a9174b2a7c1a8daf7db4750be6848b03eb5e639674f7963773", size = 229321, upload-time = "2025-08-11T12:07:52.965Z" }, - { url = "https://files.pythonhosted.org/packages/c7/bc/01ddda2a73dd9d167bd85d0e8ef4293836a8f82b786c63fb1a429bc3e678/multidict-6.6.4-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:cc356250cffd6e78416cf5b40dc6a74f1edf3be8e834cf8862d9ed5265cf9b0e", size = 249954, upload-time = "2025-08-11T12:07:54.423Z" }, - { url = "https://files.pythonhosted.org/packages/06/78/6b7c0f020f9aa0acf66d0ab4eb9f08375bac9a50ff5e3edb1c4ccd59eafc/multidict-6.6.4-cp313-cp313t-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:dadf95aa862714ea468a49ad1e09fe00fcc9ec67d122f6596a8d40caf6cec7d0", size = 228612, upload-time = "2025-08-11T12:07:55.914Z" }, - { url = "https://files.pythonhosted.org/packages/00/44/3faa416f89b2d5d76e9d447296a81521e1c832ad6e40b92f990697b43192/multidict-6.6.4-cp313-cp313t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:7dd57515bebffd8ebd714d101d4c434063322e4fe24042e90ced41f18b6d3395", size = 257528, upload-time = "2025-08-11T12:07:57.371Z" }, - { url = "https://files.pythonhosted.org/packages/05/5f/77c03b89af0fcb16f018f668207768191fb9dcfb5e3361a5e706a11db2c9/multidict-6.6.4-cp313-cp313t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:967af5f238ebc2eb1da4e77af5492219fbd9b4b812347da39a7b5f5c72c0fa45", size = 256329, upload-time = "2025-08-11T12:07:58.844Z" }, - { url = "https://files.pythonhosted.org/packages/cf/e9/ed750a2a9afb4f8dc6f13dc5b67b514832101b95714f1211cd42e0aafc26/multidict-6.6.4-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:2a4c6875c37aae9794308ec43e3530e4aa0d36579ce38d89979bbf89582002bb", size = 247928, upload-time = "2025-08-11T12:08:01.037Z" }, - { url = "https://files.pythonhosted.org/packages/1f/b5/e0571bc13cda277db7e6e8a532791d4403dacc9850006cb66d2556e649c0/multidict-6.6.4-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:7f683a551e92bdb7fac545b9c6f9fa2aebdeefa61d607510b3533286fcab67f5", size = 245228, upload-time = "2025-08-11T12:08:02.96Z" }, - { url = "https://files.pythonhosted.org/packages/f3/a3/69a84b0eccb9824491f06368f5b86e72e4af54c3067c37c39099b6687109/multidict-6.6.4-cp313-cp313t-musllinux_1_2_armv7l.whl", hash = "sha256:3ba5aaf600edaf2a868a391779f7a85d93bed147854925f34edd24cc70a3e141", size = 235869, upload-time = "2025-08-11T12:08:04.746Z" }, - { url = "https://files.pythonhosted.org/packages/a9/9d/28802e8f9121a6a0804fa009debf4e753d0a59969ea9f70be5f5fdfcb18f/multidict-6.6.4-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:580b643b7fd2c295d83cad90d78419081f53fd532d1f1eb67ceb7060f61cff0d", size = 243446, upload-time = "2025-08-11T12:08:06.332Z" }, - { url = "https://files.pythonhosted.org/packages/38/ea/6c98add069b4878c1d66428a5f5149ddb6d32b1f9836a826ac764b9940be/multidict-6.6.4-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:37b7187197da6af3ee0b044dbc9625afd0c885f2800815b228a0e70f9a7f473d", size = 252299, upload-time = "2025-08-11T12:08:07.931Z" }, - { url = "https://files.pythonhosted.org/packages/3a/09/8fe02d204473e14c0af3affd50af9078839dfca1742f025cca765435d6b4/multidict-6.6.4-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:e1b93790ed0bc26feb72e2f08299691ceb6da5e9e14a0d13cc74f1869af327a0", size = 246926, upload-time = "2025-08-11T12:08:09.467Z" }, - { url = "https://files.pythonhosted.org/packages/37/3d/7b1e10d774a6df5175ecd3c92bff069e77bed9ec2a927fdd4ff5fe182f67/multidict-6.6.4-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:a506a77ddee1efcca81ecbeae27ade3e09cdf21a8ae854d766c2bb4f14053f92", size = 243383, upload-time = "2025-08-11T12:08:10.981Z" }, - { url = "https://files.pythonhosted.org/packages/50/b0/a6fae46071b645ae98786ab738447de1ef53742eaad949f27e960864bb49/multidict-6.6.4-cp313-cp313t-win32.whl", hash = "sha256:f93b2b2279883d1d0a9e1bd01f312d6fc315c5e4c1f09e112e4736e2f650bc4e", size = 47775, upload-time = "2025-08-11T12:08:12.439Z" }, - { url = "https://files.pythonhosted.org/packages/b2/0a/2436550b1520091af0600dff547913cb2d66fbac27a8c33bc1b1bccd8d98/multidict-6.6.4-cp313-cp313t-win_amd64.whl", hash = "sha256:6d46a180acdf6e87cc41dc15d8f5c2986e1e8739dc25dbb7dac826731ef381a4", size = 53100, upload-time = "2025-08-11T12:08:13.823Z" }, - { url = "https://files.pythonhosted.org/packages/97/ea/43ac51faff934086db9c072a94d327d71b7d8b40cd5dcb47311330929ef0/multidict-6.6.4-cp313-cp313t-win_arm64.whl", hash = "sha256:756989334015e3335d087a27331659820d53ba432befdef6a718398b0a8493ad", size = 45501, upload-time = "2025-08-11T12:08:15.173Z" }, - { url = "https://files.pythonhosted.org/packages/fd/69/b547032297c7e63ba2af494edba695d781af8a0c6e89e4d06cf848b21d80/multidict-6.6.4-py3-none-any.whl", hash = "sha256:27d8f8e125c07cb954e54d75d04905a9bba8a439c1d84aca94949d4d03d8601c", size = 12313, upload-time = "2025-08-11T12:08:46.891Z" }, -] - -[[package]] -name = "mypy-extensions" -version = "1.1.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a2/6e/371856a3fb9d31ca8dac321cda606860fa4548858c0cc45d9d1d4ca2628b/mypy_extensions-1.1.0.tar.gz", hash = "sha256:52e68efc3284861e772bbcd66823fde5ae21fd2fdb51c62a211403730b916558", size = 6343, upload-time = "2025-04-22T14:54:24.164Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/79/7b/2c79738432f5c924bef5071f933bcc9efd0473bac3b4aa584a6f7c1c8df8/mypy_extensions-1.1.0-py3-none-any.whl", hash = "sha256:1be4cccdb0f2482337c4743e60421de3a356cd97508abadd57d47403e94f5505", size = 4963, upload-time = "2025-04-22T14:54:22.983Z" }, -] - -[[package]] -name = "nh3" -version = "0.3.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/c3/a4/96cff0977357f60f06ec4368c4c7a7a26cccfe7c9fcd54f5378bf0428fd3/nh3-0.3.0.tar.gz", hash = "sha256:d8ba24cb31525492ea71b6aac11a4adac91d828aadeff7c4586541bf5dc34d2f", size = 19655, upload-time = "2025-07-17T14:43:37.05Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b4/11/340b7a551916a4b2b68c54799d710f86cf3838a4abaad8e74d35360343bb/nh3-0.3.0-cp313-cp313t-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:a537ece1bf513e5a88d8cff8a872e12fe8d0f42ef71dd15a5e7520fecd191bbb", size = 1427992, upload-time = "2025-07-17T14:43:06.848Z" }, - { url = "https://files.pythonhosted.org/packages/ad/7f/7c6b8358cf1222921747844ab0eef81129e9970b952fcb814df417159fb9/nh3-0.3.0-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7c915060a2c8131bef6a29f78debc29ba40859b6dbe2362ef9e5fd44f11487c2", size = 798194, upload-time = "2025-07-17T14:43:08.263Z" }, - { url = "https://files.pythonhosted.org/packages/63/da/c5fd472b700ba37d2df630a9e0d8cc156033551ceb8b4c49cc8a5f606b68/nh3-0.3.0-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ba0caa8aa184196daa6e574d997a33867d6d10234018012d35f86d46024a2a95", size = 837884, upload-time = "2025-07-17T14:43:09.233Z" }, - { url = "https://files.pythonhosted.org/packages/4c/3c/cba7b26ccc0ef150c81646478aa32f9c9535234f54845603c838a1dc955c/nh3-0.3.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:80fe20171c6da69c7978ecba33b638e951b85fb92059259edd285ff108b82a6d", size = 996365, upload-time = "2025-07-17T14:43:10.243Z" }, - { url = "https://files.pythonhosted.org/packages/f3/ba/59e204d90727c25b253856e456ea61265ca810cda8ee802c35f3fadaab00/nh3-0.3.0-cp313-cp313t-musllinux_1_2_armv7l.whl", hash = "sha256:e90883f9f85288f423c77b3f5a6f4486375636f25f793165112679a7b6363b35", size = 1071042, upload-time = "2025-07-17T14:43:11.57Z" }, - { url = "https://files.pythonhosted.org/packages/10/71/2fb1834c10fab6d9291d62c95192ea2f4c7518bd32ad6c46aab5d095cb87/nh3-0.3.0-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:0649464ac8eee018644aacbc103874ccbfac80e3035643c3acaab4287e36e7f5", size = 995737, upload-time = "2025-07-17T14:43:12.659Z" }, - { url = "https://files.pythonhosted.org/packages/33/c1/8f8ccc2492a000b6156dce68a43253fcff8b4ce70ab4216d08f90a2ac998/nh3-0.3.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:1adeb1062a1c2974bc75b8d1ecb014c5fd4daf2df646bbe2831f7c23659793f9", size = 980552, upload-time = "2025-07-17T14:43:13.763Z" }, - { url = "https://files.pythonhosted.org/packages/2f/d6/f1c6e091cbe8700401c736c2bc3980c46dca770a2cf6a3b48a175114058e/nh3-0.3.0-cp313-cp313t-win32.whl", hash = "sha256:7275fdffaab10cc5801bf026e3c089d8de40a997afc9e41b981f7ac48c5aa7d5", size = 593618, upload-time = "2025-07-17T14:43:15.098Z" }, - { url = "https://files.pythonhosted.org/packages/23/1e/80a8c517655dd40bb13363fc4d9e66b2f13245763faab1a20f1df67165a7/nh3-0.3.0-cp313-cp313t-win_amd64.whl", hash = "sha256:423201bbdf3164a9e09aa01e540adbb94c9962cc177d5b1cbb385f5e1e79216e", size = 598948, upload-time = "2025-07-17T14:43:16.064Z" }, - { url = "https://files.pythonhosted.org/packages/9a/e0/af86d2a974c87a4ba7f19bc3b44a8eaa3da480de264138fec82fe17b340b/nh3-0.3.0-cp313-cp313t-win_arm64.whl", hash = "sha256:16f8670201f7e8e0e05ed1a590eb84bfa51b01a69dd5caf1d3ea57733de6a52f", size = 580479, upload-time = "2025-07-17T14:43:17.038Z" }, - { url = "https://files.pythonhosted.org/packages/0c/e0/cf1543e798ba86d838952e8be4cb8d18e22999be2a24b112a671f1c04fd6/nh3-0.3.0-cp38-abi3-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:ec6cfdd2e0399cb79ba4dcffb2332b94d9696c52272ff9d48a630c5dca5e325a", size = 1442218, upload-time = "2025-07-17T14:43:18.087Z" }, - { url = "https://files.pythonhosted.org/packages/5c/86/a96b1453c107b815f9ab8fac5412407c33cc5c7580a4daf57aabeb41b774/nh3-0.3.0-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ce5e7185599f89b0e391e2f29cc12dc2e206167380cea49b33beda4891be2fe1", size = 823791, upload-time = "2025-07-17T14:43:19.721Z" }, - { url = "https://files.pythonhosted.org/packages/97/33/11e7273b663839626f714cb68f6eb49899da5a0d9b6bc47b41fe870259c2/nh3-0.3.0-cp38-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:389d93d59b8214d51c400fb5b07866c2a4f79e4e14b071ad66c92184fec3a392", size = 811143, upload-time = "2025-07-17T14:43:20.779Z" }, - { url = "https://files.pythonhosted.org/packages/6a/1b/b15bd1ce201a1a610aeb44afd478d55ac018b4475920a3118ffd806e2483/nh3-0.3.0-cp38-abi3-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:e9e6a7e4d38f7e8dda9edd1433af5170c597336c1a74b4693c5cb75ab2b30f2a", size = 1064661, upload-time = "2025-07-17T14:43:21.839Z" }, - { url = "https://files.pythonhosted.org/packages/8f/14/079670fb2e848c4ba2476c5a7a2d1319826053f4f0368f61fca9bb4227ae/nh3-0.3.0-cp38-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7852f038a054e0096dac12b8141191e02e93e0b4608c4b993ec7d4ffafea4e49", size = 997061, upload-time = "2025-07-17T14:43:23.179Z" }, - { url = "https://files.pythonhosted.org/packages/a3/e5/ac7fc565f5d8bce7f979d1afd68e8cb415020d62fa6507133281c7d49f91/nh3-0.3.0-cp38-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:af5aa8127f62bbf03d68f67a956627b1bd0469703a35b3dad28d0c1195e6c7fb", size = 924761, upload-time = "2025-07-17T14:43:24.23Z" }, - { url = "https://files.pythonhosted.org/packages/39/2c/6394301428b2017a9d5644af25f487fa557d06bc8a491769accec7524d9a/nh3-0.3.0-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f416c35efee3e6a6c9ab7716d9e57aa0a49981be915963a82697952cba1353e1", size = 803959, upload-time = "2025-07-17T14:43:26.377Z" }, - { url = "https://files.pythonhosted.org/packages/4e/9a/344b9f9c4bd1c2413a397f38ee6a3d5db30f1a507d4976e046226f12b297/nh3-0.3.0-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:37d3003d98dedca6cd762bf88f2e70b67f05100f6b949ffe540e189cc06887f9", size = 844073, upload-time = "2025-07-17T14:43:27.375Z" }, - { url = "https://files.pythonhosted.org/packages/66/3f/cd37f76c8ca277b02a84aa20d7bd60fbac85b4e2cbdae77cb759b22de58b/nh3-0.3.0-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:634e34e6162e0408e14fb61d5e69dbaea32f59e847cfcfa41b66100a6b796f62", size = 1000680, upload-time = "2025-07-17T14:43:28.452Z" }, - { url = "https://files.pythonhosted.org/packages/ee/db/7aa11b44bae4e7474feb1201d8dee04fabe5651c7cb51409ebda94a4ed67/nh3-0.3.0-cp38-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:b0612ccf5de8a480cf08f047b08f9d3fecc12e63d2ee91769cb19d7290614c23", size = 1076613, upload-time = "2025-07-17T14:43:30.031Z" }, - { url = "https://files.pythonhosted.org/packages/97/03/03f79f7e5178eb1ad5083af84faff471e866801beb980cc72943a4397368/nh3-0.3.0-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:c7a32a7f0d89f7d30cb8f4a84bdbd56d1eb88b78a2434534f62c71dac538c450", size = 1001418, upload-time = "2025-07-17T14:43:31.429Z" }, - { url = "https://files.pythonhosted.org/packages/ce/55/1974bcc16884a397ee699cebd3914e1f59be64ab305533347ca2d983756f/nh3-0.3.0-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:3f1b4f8a264a0c86ea01da0d0c390fe295ea0bcacc52c2103aca286f6884f518", size = 986499, upload-time = "2025-07-17T14:43:32.459Z" }, - { url = "https://files.pythonhosted.org/packages/c9/50/76936ec021fe1f3270c03278b8af5f2079038116b5d0bfe8538ffe699d69/nh3-0.3.0-cp38-abi3-win32.whl", hash = "sha256:6d68fa277b4a3cf04e5c4b84dd0c6149ff7d56c12b3e3fab304c525b850f613d", size = 599000, upload-time = "2025-07-17T14:43:33.852Z" }, - { url = "https://files.pythonhosted.org/packages/8c/ae/324b165d904dc1672eee5f5661c0a68d4bab5b59fbb07afb6d8d19a30b45/nh3-0.3.0-cp38-abi3-win_amd64.whl", hash = "sha256:bae63772408fd63ad836ec569a7c8f444dd32863d0c67f6e0b25ebbd606afa95", size = 604530, upload-time = "2025-07-17T14:43:34.95Z" }, - { url = "https://files.pythonhosted.org/packages/5b/76/3165e84e5266d146d967a6cc784ff2fbf6ddd00985a55ec006b72bc39d5d/nh3-0.3.0-cp38-abi3-win_arm64.whl", hash = "sha256:d97d3efd61404af7e5721a0e74d81cdbfc6e5f97e11e731bb6d090e30a7b62b2", size = 585971, upload-time = "2025-07-17T14:43:35.936Z" }, -] - -[[package]] -name = "nodeenv" -version = "1.9.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/43/16/fc88b08840de0e0a72a2f9d8c6bae36be573e475a6326ae854bcc549fc45/nodeenv-1.9.1.tar.gz", hash = "sha256:6ec12890a2dab7946721edbfbcd91f3319c6ccc9aec47be7c7e6b7011ee6645f", size = 47437, upload-time = "2024-06-04T18:44:11.171Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d2/1d/1b658dbd2b9fa9c4c9f32accbfc0205d532c8c6194dc0f2a4c0428e7128a/nodeenv-1.9.1-py2.py3-none-any.whl", hash = "sha256:ba11c9782d29c27c70ffbdda2d7415098754709be8a7056d79a737cd901155c9", size = 22314, upload-time = "2024-06-04T18:44:08.352Z" }, -] - -[[package]] -name = "openai" -version = "2.15.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "distro" }, - { name = "httpx" }, - { name = "jiter" }, - { name = "pydantic" }, - { name = "sniffio" }, - { name = "tqdm" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/94/f4/4690ecb5d70023ce6bfcfeabfe717020f654bde59a775058ec6ac4692463/openai-2.15.0.tar.gz", hash = "sha256:42eb8cbb407d84770633f31bf727d4ffb4138711c670565a41663d9439174fba", size = 627383, upload-time = "2026-01-09T22:10:08.603Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b5/df/c306f7375d42bafb379934c2df4c2fa3964656c8c782bac75ee10c102818/openai-2.15.0-py3-none-any.whl", hash = "sha256:6ae23b932cd7230f7244e52954daa6602716d6b9bf235401a107af731baea6c3", size = 1067879, upload-time = "2026-01-09T22:10:06.446Z" }, -] - -[[package]] -name = "orjson" -version = "3.11.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/be/4d/8df5f83256a809c22c4d6792ce8d43bb503be0fb7a8e4da9025754b09658/orjson-3.11.3.tar.gz", hash = "sha256:1c0603b1d2ffcd43a411d64797a19556ef76958aef1c182f22dc30860152a98a", size = 5482394, upload-time = "2025-08-26T17:46:43.171Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/9b/64/4a3cef001c6cd9c64256348d4c13a7b09b857e3e1cbb5185917df67d8ced/orjson-3.11.3-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:29cb1f1b008d936803e2da3d7cba726fc47232c45df531b29edf0b232dd737e7", size = 238600, upload-time = "2025-08-26T17:44:36.875Z" }, - { url = "https://files.pythonhosted.org/packages/10/ce/0c8c87f54f79d051485903dc46226c4d3220b691a151769156054df4562b/orjson-3.11.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:97dceed87ed9139884a55db8722428e27bd8452817fbf1869c58b49fecab1120", size = 123526, upload-time = "2025-08-26T17:44:39.574Z" }, - { url = "https://files.pythonhosted.org/packages/ef/d0/249497e861f2d438f45b3ab7b7b361484237414945169aa285608f9f7019/orjson-3.11.3-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:58533f9e8266cb0ac298e259ed7b4d42ed3fa0b78ce76860626164de49e0d467", size = 128075, upload-time = "2025-08-26T17:44:40.672Z" }, - { url = "https://files.pythonhosted.org/packages/e5/64/00485702f640a0fd56144042a1ea196469f4a3ae93681871564bf74fa996/orjson-3.11.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0c212cfdd90512fe722fa9bd620de4d46cda691415be86b2e02243242ae81873", size = 130483, upload-time = "2025-08-26T17:44:41.788Z" }, - { url = "https://files.pythonhosted.org/packages/64/81/110d68dba3909171bf3f05619ad0cf187b430e64045ae4e0aa7ccfe25b15/orjson-3.11.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5ff835b5d3e67d9207343effb03760c00335f8b5285bfceefd4dc967b0e48f6a", size = 132539, upload-time = "2025-08-26T17:44:43.12Z" }, - { url = "https://files.pythonhosted.org/packages/79/92/dba25c22b0ddfafa1e6516a780a00abac28d49f49e7202eb433a53c3e94e/orjson-3.11.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f5aa4682912a450c2db89cbd92d356fef47e115dffba07992555542f344d301b", size = 135390, upload-time = "2025-08-26T17:44:44.199Z" }, - { url = "https://files.pythonhosted.org/packages/44/1d/ca2230fd55edbd87b58a43a19032d63a4b180389a97520cc62c535b726f9/orjson-3.11.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d7d18dd34ea2e860553a579df02041845dee0af8985dff7f8661306f95504ddf", size = 132966, upload-time = "2025-08-26T17:44:45.719Z" }, - { url = "https://files.pythonhosted.org/packages/6e/b9/96bbc8ed3e47e52b487d504bd6861798977445fbc410da6e87e302dc632d/orjson-3.11.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d8b11701bc43be92ea42bd454910437b355dfb63696c06fe953ffb40b5f763b4", size = 131349, upload-time = "2025-08-26T17:44:46.862Z" }, - { url = "https://files.pythonhosted.org/packages/c4/3c/418fbd93d94b0df71cddf96b7fe5894d64a5d890b453ac365120daec30f7/orjson-3.11.3-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:90368277087d4af32d38bd55f9da2ff466d25325bf6167c8f382d8ee40cb2bbc", size = 404087, upload-time = "2025-08-26T17:44:48.079Z" }, - { url = "https://files.pythonhosted.org/packages/5b/a9/2bfd58817d736c2f63608dec0c34857339d423eeed30099b126562822191/orjson-3.11.3-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fd7ff459fb393358d3a155d25b275c60b07a2c83dcd7ea962b1923f5a1134569", size = 146067, upload-time = "2025-08-26T17:44:49.302Z" }, - { url = "https://files.pythonhosted.org/packages/33/ba/29023771f334096f564e48d82ed855a0ed3320389d6748a9c949e25be734/orjson-3.11.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:f8d902867b699bcd09c176a280b1acdab57f924489033e53d0afe79817da37e6", size = 135506, upload-time = "2025-08-26T17:44:50.558Z" }, - { url = "https://files.pythonhosted.org/packages/39/62/b5a1eca83f54cb3aa11a9645b8a22f08d97dbd13f27f83aae7c6666a0a05/orjson-3.11.3-cp310-cp310-win32.whl", hash = "sha256:bb93562146120bb51e6b154962d3dadc678ed0fce96513fa6bc06599bb6f6edc", size = 136352, upload-time = "2025-08-26T17:44:51.698Z" }, - { url = "https://files.pythonhosted.org/packages/e3/c0/7ebfaa327d9a9ed982adc0d9420dbce9a3fec45b60ab32c6308f731333fa/orjson-3.11.3-cp310-cp310-win_amd64.whl", hash = "sha256:976c6f1975032cc327161c65d4194c549f2589d88b105a5e3499429a54479770", size = 131539, upload-time = "2025-08-26T17:44:52.974Z" }, - { url = "https://files.pythonhosted.org/packages/cd/8b/360674cd817faef32e49276187922a946468579fcaf37afdfb6c07046e92/orjson-3.11.3-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:9d2ae0cc6aeb669633e0124531f342a17d8e97ea999e42f12a5ad4adaa304c5f", size = 238238, upload-time = "2025-08-26T17:44:54.214Z" }, - { url = "https://files.pythonhosted.org/packages/05/3d/5fa9ea4b34c1a13be7d9046ba98d06e6feb1d8853718992954ab59d16625/orjson-3.11.3-cp311-cp311-macosx_15_0_arm64.whl", hash = "sha256:ba21dbb2493e9c653eaffdc38819b004b7b1b246fb77bfc93dc016fe664eac91", size = 127713, upload-time = "2025-08-26T17:44:55.596Z" }, - { url = "https://files.pythonhosted.org/packages/e5/5f/e18367823925e00b1feec867ff5f040055892fc474bf5f7875649ecfa586/orjson-3.11.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:00f1a271e56d511d1569937c0447d7dce5a99a33ea0dec76673706360a051904", size = 123241, upload-time = "2025-08-26T17:44:57.185Z" }, - { url = "https://files.pythonhosted.org/packages/0f/bd/3c66b91c4564759cf9f473251ac1650e446c7ba92a7c0f9f56ed54f9f0e6/orjson-3.11.3-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b67e71e47caa6680d1b6f075a396d04fa6ca8ca09aafb428731da9b3ea32a5a6", size = 127895, upload-time = "2025-08-26T17:44:58.349Z" }, - { url = "https://files.pythonhosted.org/packages/82/b5/dc8dcd609db4766e2967a85f63296c59d4722b39503e5b0bf7fd340d387f/orjson-3.11.3-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d7d012ebddffcce8c85734a6d9e5f08180cd3857c5f5a3ac70185b43775d043d", size = 130303, upload-time = "2025-08-26T17:44:59.491Z" }, - { url = "https://files.pythonhosted.org/packages/48/c2/d58ec5fd1270b2aa44c862171891adc2e1241bd7dab26c8f46eb97c6c6f1/orjson-3.11.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dd759f75d6b8d1b62012b7f5ef9461d03c804f94d539a5515b454ba3a6588038", size = 132366, upload-time = "2025-08-26T17:45:00.654Z" }, - { url = "https://files.pythonhosted.org/packages/73/87/0ef7e22eb8dd1ef940bfe3b9e441db519e692d62ed1aae365406a16d23d0/orjson-3.11.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6890ace0809627b0dff19cfad92d69d0fa3f089d3e359a2a532507bb6ba34efb", size = 135180, upload-time = "2025-08-26T17:45:02.424Z" }, - { url = "https://files.pythonhosted.org/packages/bb/6a/e5bf7b70883f374710ad74faf99bacfc4b5b5a7797c1d5e130350e0e28a3/orjson-3.11.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f9d4a5e041ae435b815e568537755773d05dac031fee6a57b4ba70897a44d9d2", size = 132741, upload-time = "2025-08-26T17:45:03.663Z" }, - { url = "https://files.pythonhosted.org/packages/bd/0c/4577fd860b6386ffaa56440e792af01c7882b56d2766f55384b5b0e9d39b/orjson-3.11.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:2d68bf97a771836687107abfca089743885fb664b90138d8761cce61d5625d55", size = 131104, upload-time = "2025-08-26T17:45:04.939Z" }, - { url = "https://files.pythonhosted.org/packages/66/4b/83e92b2d67e86d1c33f2ea9411742a714a26de63641b082bdbf3d8e481af/orjson-3.11.3-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:bfc27516ec46f4520b18ef645864cee168d2a027dbf32c5537cb1f3e3c22dac1", size = 403887, upload-time = "2025-08-26T17:45:06.228Z" }, - { url = "https://files.pythonhosted.org/packages/6d/e5/9eea6a14e9b5ceb4a271a1fd2e1dec5f2f686755c0fab6673dc6ff3433f4/orjson-3.11.3-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:f66b001332a017d7945e177e282a40b6997056394e3ed7ddb41fb1813b83e824", size = 145855, upload-time = "2025-08-26T17:45:08.338Z" }, - { url = "https://files.pythonhosted.org/packages/45/78/8d4f5ad0c80ba9bf8ac4d0fc71f93a7d0dc0844989e645e2074af376c307/orjson-3.11.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:212e67806525d2561efbfe9e799633b17eb668b8964abed6b5319b2f1cfbae1f", size = 135361, upload-time = "2025-08-26T17:45:09.625Z" }, - { url = "https://files.pythonhosted.org/packages/0b/5f/16386970370178d7a9b438517ea3d704efcf163d286422bae3b37b88dbb5/orjson-3.11.3-cp311-cp311-win32.whl", hash = "sha256:6e8e0c3b85575a32f2ffa59de455f85ce002b8bdc0662d6b9c2ed6d80ab5d204", size = 136190, upload-time = "2025-08-26T17:45:10.962Z" }, - { url = "https://files.pythonhosted.org/packages/09/60/db16c6f7a41dd8ac9fb651f66701ff2aeb499ad9ebc15853a26c7c152448/orjson-3.11.3-cp311-cp311-win_amd64.whl", hash = "sha256:6be2f1b5d3dc99a5ce5ce162fc741c22ba9f3443d3dd586e6a1211b7bc87bc7b", size = 131389, upload-time = "2025-08-26T17:45:12.285Z" }, - { url = "https://files.pythonhosted.org/packages/3e/2a/bb811ad336667041dea9b8565c7c9faf2f59b47eb5ab680315eea612ef2e/orjson-3.11.3-cp311-cp311-win_arm64.whl", hash = "sha256:fafb1a99d740523d964b15c8db4eabbfc86ff29f84898262bf6e3e4c9e97e43e", size = 126120, upload-time = "2025-08-26T17:45:13.515Z" }, - { url = "https://files.pythonhosted.org/packages/3d/b0/a7edab2a00cdcb2688e1c943401cb3236323e7bfd2839815c6131a3742f4/orjson-3.11.3-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:8c752089db84333e36d754c4baf19c0e1437012242048439c7e80eb0e6426e3b", size = 238259, upload-time = "2025-08-26T17:45:15.093Z" }, - { url = "https://files.pythonhosted.org/packages/e1/c6/ff4865a9cc398a07a83342713b5932e4dc3cb4bf4bc04e8f83dedfc0d736/orjson-3.11.3-cp312-cp312-macosx_15_0_arm64.whl", hash = "sha256:9b8761b6cf04a856eb544acdd82fc594b978f12ac3602d6374a7edb9d86fd2c2", size = 127633, upload-time = "2025-08-26T17:45:16.417Z" }, - { url = "https://files.pythonhosted.org/packages/6e/e6/e00bea2d9472f44fe8794f523e548ce0ad51eb9693cf538a753a27b8bda4/orjson-3.11.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8b13974dc8ac6ba22feaa867fc19135a3e01a134b4f7c9c28162fed4d615008a", size = 123061, upload-time = "2025-08-26T17:45:17.673Z" }, - { url = "https://files.pythonhosted.org/packages/54/31/9fbb78b8e1eb3ac605467cb846e1c08d0588506028b37f4ee21f978a51d4/orjson-3.11.3-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:f83abab5bacb76d9c821fd5c07728ff224ed0e52d7a71b7b3de822f3df04e15c", size = 127956, upload-time = "2025-08-26T17:45:19.172Z" }, - { url = "https://files.pythonhosted.org/packages/36/88/b0604c22af1eed9f98d709a96302006915cfd724a7ebd27d6dd11c22d80b/orjson-3.11.3-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e6fbaf48a744b94091a56c62897b27c31ee2da93d826aa5b207131a1e13d4064", size = 130790, upload-time = "2025-08-26T17:45:20.586Z" }, - { url = "https://files.pythonhosted.org/packages/0e/9d/1c1238ae9fffbfed51ba1e507731b3faaf6b846126a47e9649222b0fd06f/orjson-3.11.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:bc779b4f4bba2847d0d2940081a7b6f7b5877e05408ffbb74fa1faf4a136c424", size = 132385, upload-time = "2025-08-26T17:45:22.036Z" }, - { url = "https://files.pythonhosted.org/packages/a3/b5/c06f1b090a1c875f337e21dd71943bc9d84087f7cdf8c6e9086902c34e42/orjson-3.11.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bd4b909ce4c50faa2192da6bb684d9848d4510b736b0611b6ab4020ea6fd2d23", size = 135305, upload-time = "2025-08-26T17:45:23.4Z" }, - { url = "https://files.pythonhosted.org/packages/a0/26/5f028c7d81ad2ebbf84414ba6d6c9cac03f22f5cd0d01eb40fb2d6a06b07/orjson-3.11.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:524b765ad888dc5518bbce12c77c2e83dee1ed6b0992c1790cc5fb49bb4b6667", size = 132875, upload-time = "2025-08-26T17:45:25.182Z" }, - { url = "https://files.pythonhosted.org/packages/fe/d4/b8df70d9cfb56e385bf39b4e915298f9ae6c61454c8154a0f5fd7efcd42e/orjson-3.11.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:84fd82870b97ae3cdcea9d8746e592b6d40e1e4d4527835fc520c588d2ded04f", size = 130940, upload-time = "2025-08-26T17:45:27.209Z" }, - { url = "https://files.pythonhosted.org/packages/da/5e/afe6a052ebc1a4741c792dd96e9f65bf3939d2094e8b356503b68d48f9f5/orjson-3.11.3-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:fbecb9709111be913ae6879b07bafd4b0785b44c1eb5cac8ac76da048b3885a1", size = 403852, upload-time = "2025-08-26T17:45:28.478Z" }, - { url = "https://files.pythonhosted.org/packages/f8/90/7bbabafeb2ce65915e9247f14a56b29c9334003536009ef5b122783fe67e/orjson-3.11.3-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:9dba358d55aee552bd868de348f4736ca5a4086d9a62e2bfbbeeb5629fe8b0cc", size = 146293, upload-time = "2025-08-26T17:45:29.86Z" }, - { url = "https://files.pythonhosted.org/packages/27/b3/2d703946447da8b093350570644a663df69448c9d9330e5f1d9cce997f20/orjson-3.11.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:eabcf2e84f1d7105f84580e03012270c7e97ecb1fb1618bda395061b2a84a049", size = 135470, upload-time = "2025-08-26T17:45:31.243Z" }, - { url = "https://files.pythonhosted.org/packages/38/70/b14dcfae7aff0e379b0119c8a812f8396678919c431efccc8e8a0263e4d9/orjson-3.11.3-cp312-cp312-win32.whl", hash = "sha256:3782d2c60b8116772aea8d9b7905221437fdf53e7277282e8d8b07c220f96cca", size = 136248, upload-time = "2025-08-26T17:45:32.567Z" }, - { url = "https://files.pythonhosted.org/packages/35/b8/9e3127d65de7fff243f7f3e53f59a531bf6bb295ebe5db024c2503cc0726/orjson-3.11.3-cp312-cp312-win_amd64.whl", hash = "sha256:79b44319268af2eaa3e315b92298de9a0067ade6e6003ddaef72f8e0bedb94f1", size = 131437, upload-time = "2025-08-26T17:45:34.949Z" }, - { url = "https://files.pythonhosted.org/packages/51/92/a946e737d4d8a7fd84a606aba96220043dcc7d6988b9e7551f7f6d5ba5ad/orjson-3.11.3-cp312-cp312-win_arm64.whl", hash = "sha256:0e92a4e83341ef79d835ca21b8bd13e27c859e4e9e4d7b63defc6e58462a3710", size = 125978, upload-time = "2025-08-26T17:45:36.422Z" }, - { url = "https://files.pythonhosted.org/packages/fc/79/8932b27293ad35919571f77cb3693b5906cf14f206ef17546052a241fdf6/orjson-3.11.3-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:af40c6612fd2a4b00de648aa26d18186cd1322330bd3a3cc52f87c699e995810", size = 238127, upload-time = "2025-08-26T17:45:38.146Z" }, - { url = "https://files.pythonhosted.org/packages/1c/82/cb93cd8cf132cd7643b30b6c5a56a26c4e780c7a145db6f83de977b540ce/orjson-3.11.3-cp313-cp313-macosx_15_0_arm64.whl", hash = "sha256:9f1587f26c235894c09e8b5b7636a38091a9e6e7fe4531937534749c04face43", size = 127494, upload-time = "2025-08-26T17:45:39.57Z" }, - { url = "https://files.pythonhosted.org/packages/a4/b8/2d9eb181a9b6bb71463a78882bcac1027fd29cf62c38a40cc02fc11d3495/orjson-3.11.3-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:61dcdad16da5bb486d7227a37a2e789c429397793a6955227cedbd7252eb5a27", size = 123017, upload-time = "2025-08-26T17:45:40.876Z" }, - { url = "https://files.pythonhosted.org/packages/b4/14/a0e971e72d03b509190232356d54c0f34507a05050bd026b8db2bf2c192c/orjson-3.11.3-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:11c6d71478e2cbea0a709e8a06365fa63da81da6498a53e4c4f065881d21ae8f", size = 127898, upload-time = "2025-08-26T17:45:42.188Z" }, - { url = "https://files.pythonhosted.org/packages/8e/af/dc74536722b03d65e17042cc30ae586161093e5b1f29bccda24765a6ae47/orjson-3.11.3-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ff94112e0098470b665cb0ed06efb187154b63649403b8d5e9aedeb482b4548c", size = 130742, upload-time = "2025-08-26T17:45:43.511Z" }, - { url = "https://files.pythonhosted.org/packages/62/e6/7a3b63b6677bce089fe939353cda24a7679825c43a24e49f757805fc0d8a/orjson-3.11.3-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ae8b756575aaa2a855a75192f356bbda11a89169830e1439cfb1a3e1a6dde7be", size = 132377, upload-time = "2025-08-26T17:45:45.525Z" }, - { url = "https://files.pythonhosted.org/packages/fc/cd/ce2ab93e2e7eaf518f0fd15e3068b8c43216c8a44ed82ac2b79ce5cef72d/orjson-3.11.3-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c9416cc19a349c167ef76135b2fe40d03cea93680428efee8771f3e9fb66079d", size = 135313, upload-time = "2025-08-26T17:45:46.821Z" }, - { url = "https://files.pythonhosted.org/packages/d0/b4/f98355eff0bd1a38454209bbc73372ce351ba29933cb3e2eba16c04b9448/orjson-3.11.3-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b822caf5b9752bc6f246eb08124c3d12bf2175b66ab74bac2ef3bbf9221ce1b2", size = 132908, upload-time = "2025-08-26T17:45:48.126Z" }, - { url = "https://files.pythonhosted.org/packages/eb/92/8f5182d7bc2a1bed46ed960b61a39af8389f0ad476120cd99e67182bfb6d/orjson-3.11.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:414f71e3bdd5573893bf5ecdf35c32b213ed20aa15536fe2f588f946c318824f", size = 130905, upload-time = "2025-08-26T17:45:49.414Z" }, - { url = "https://files.pythonhosted.org/packages/1a/60/c41ca753ce9ffe3d0f67b9b4c093bdd6e5fdb1bc53064f992f66bb99954d/orjson-3.11.3-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:828e3149ad8815dc14468f36ab2a4b819237c155ee1370341b91ea4c8672d2ee", size = 403812, upload-time = "2025-08-26T17:45:51.085Z" }, - { url = "https://files.pythonhosted.org/packages/dd/13/e4a4f16d71ce1868860db59092e78782c67082a8f1dc06a3788aef2b41bc/orjson-3.11.3-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:ac9e05f25627ffc714c21f8dfe3a579445a5c392a9c8ae7ba1d0e9fb5333f56e", size = 146277, upload-time = "2025-08-26T17:45:52.851Z" }, - { url = "https://files.pythonhosted.org/packages/8d/8b/bafb7f0afef9344754a3a0597a12442f1b85a048b82108ef2c956f53babd/orjson-3.11.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e44fbe4000bd321d9f3b648ae46e0196d21577cf66ae684a96ff90b1f7c93633", size = 135418, upload-time = "2025-08-26T17:45:54.806Z" }, - { url = "https://files.pythonhosted.org/packages/60/d4/bae8e4f26afb2c23bea69d2f6d566132584d1c3a5fe89ee8c17b718cab67/orjson-3.11.3-cp313-cp313-win32.whl", hash = "sha256:2039b7847ba3eec1f5886e75e6763a16e18c68a63efc4b029ddf994821e2e66b", size = 136216, upload-time = "2025-08-26T17:45:57.182Z" }, - { url = "https://files.pythonhosted.org/packages/88/76/224985d9f127e121c8cad882cea55f0ebe39f97925de040b75ccd4b33999/orjson-3.11.3-cp313-cp313-win_amd64.whl", hash = "sha256:29be5ac4164aa8bdcba5fa0700a3c9c316b411d8ed9d39ef8a882541bd452fae", size = 131362, upload-time = "2025-08-26T17:45:58.56Z" }, - { url = "https://files.pythonhosted.org/packages/e2/cf/0dce7a0be94bd36d1346be5067ed65ded6adb795fdbe3abd234c8d576d01/orjson-3.11.3-cp313-cp313-win_arm64.whl", hash = "sha256:18bd1435cb1f2857ceb59cfb7de6f92593ef7b831ccd1b9bfb28ca530e539dce", size = 125989, upload-time = "2025-08-26T17:45:59.95Z" }, - { url = "https://files.pythonhosted.org/packages/ef/77/d3b1fef1fc6aaeed4cbf3be2b480114035f4df8fa1a99d2dac1d40d6e924/orjson-3.11.3-cp314-cp314-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:cf4b81227ec86935568c7edd78352a92e97af8da7bd70bdfdaa0d2e0011a1ab4", size = 238115, upload-time = "2025-08-26T17:46:01.669Z" }, - { url = "https://files.pythonhosted.org/packages/e4/6d/468d21d49bb12f900052edcfbf52c292022d0a323d7828dc6376e6319703/orjson-3.11.3-cp314-cp314-macosx_15_0_arm64.whl", hash = "sha256:bc8bc85b81b6ac9fc4dae393a8c159b817f4c2c9dee5d12b773bddb3b95fc07e", size = 127493, upload-time = "2025-08-26T17:46:03.466Z" }, - { url = "https://files.pythonhosted.org/packages/67/46/1e2588700d354aacdf9e12cc2d98131fb8ac6f31ca65997bef3863edb8ff/orjson-3.11.3-cp314-cp314-manylinux_2_34_aarch64.whl", hash = "sha256:88dcfc514cfd1b0de038443c7b3e6a9797ffb1b3674ef1fd14f701a13397f82d", size = 122998, upload-time = "2025-08-26T17:46:04.803Z" }, - { url = "https://files.pythonhosted.org/packages/3b/94/11137c9b6adb3779f1b34fd98be51608a14b430dbc02c6d41134fbba484c/orjson-3.11.3-cp314-cp314-manylinux_2_34_x86_64.whl", hash = "sha256:d61cd543d69715d5fc0a690c7c6f8dcc307bc23abef9738957981885f5f38229", size = 132915, upload-time = "2025-08-26T17:46:06.237Z" }, - { url = "https://files.pythonhosted.org/packages/10/61/dccedcf9e9bcaac09fdabe9eaee0311ca92115699500efbd31950d878833/orjson-3.11.3-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:2b7b153ed90ababadbef5c3eb39549f9476890d339cf47af563aea7e07db2451", size = 130907, upload-time = "2025-08-26T17:46:07.581Z" }, - { url = "https://files.pythonhosted.org/packages/0e/fd/0e935539aa7b08b3ca0f817d73034f7eb506792aae5ecc3b7c6e679cdf5f/orjson-3.11.3-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:7909ae2460f5f494fecbcd10613beafe40381fd0316e35d6acb5f3a05bfda167", size = 403852, upload-time = "2025-08-26T17:46:08.982Z" }, - { url = "https://files.pythonhosted.org/packages/4a/2b/50ae1a5505cd1043379132fdb2adb8a05f37b3e1ebffe94a5073321966fd/orjson-3.11.3-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:2030c01cbf77bc67bee7eef1e7e31ecf28649353987775e3583062c752da0077", size = 146309, upload-time = "2025-08-26T17:46:10.576Z" }, - { url = "https://files.pythonhosted.org/packages/cd/1d/a473c158e380ef6f32753b5f39a69028b25ec5be331c2049a2201bde2e19/orjson-3.11.3-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:a0169ebd1cbd94b26c7a7ad282cf5c2744fce054133f959e02eb5265deae1872", size = 135424, upload-time = "2025-08-26T17:46:12.386Z" }, - { url = "https://files.pythonhosted.org/packages/da/09/17d9d2b60592890ff7382e591aa1d9afb202a266b180c3d4049b1ec70e4a/orjson-3.11.3-cp314-cp314-win32.whl", hash = "sha256:0c6d7328c200c349e3a4c6d8c83e0a5ad029bdc2d417f234152bf34842d0fc8d", size = 136266, upload-time = "2025-08-26T17:46:13.853Z" }, - { url = "https://files.pythonhosted.org/packages/15/58/358f6846410a6b4958b74734727e582ed971e13d335d6c7ce3e47730493e/orjson-3.11.3-cp314-cp314-win_amd64.whl", hash = "sha256:317bbe2c069bbc757b1a2e4105b64aacd3bc78279b66a6b9e51e846e4809f804", size = 131351, upload-time = "2025-08-26T17:46:15.27Z" }, - { url = "https://files.pythonhosted.org/packages/28/01/d6b274a0635be0468d4dbd9cafe80c47105937a0d42434e805e67cd2ed8b/orjson-3.11.3-cp314-cp314-win_arm64.whl", hash = "sha256:e8f6a7a27d7b7bec81bd5924163e9af03d49bbb63013f107b48eb5d16db711bc", size = 125985, upload-time = "2025-08-26T17:46:16.67Z" }, -] - -[[package]] -name = "ormsgpack" -version = "1.10.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/92/36/44eed5ef8ce93cded76a576780bab16425ce7876f10d3e2e6265e46c21ea/ormsgpack-1.10.0.tar.gz", hash = "sha256:7f7a27efd67ef22d7182ec3b7fa7e9d147c3ad9be2a24656b23c989077e08b16", size = 58629, upload-time = "2025-05-24T19:07:53.944Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/fc/74/c2dd5daf069e3798d09d5746000f9b210de04df83834e5cb47f0ace51892/ormsgpack-1.10.0-cp310-cp310-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:8a52c7ce7659459f3dc8dec9fd6a6c76f855a0a7e2b61f26090982ac10b95216", size = 376280, upload-time = "2025-05-24T19:06:51.3Z" }, - { url = "https://files.pythonhosted.org/packages/78/7b/30ff4bffb709e8a242005a8c4d65714fd96308ad640d31cff1b85c0d8cc4/ormsgpack-1.10.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:060f67fe927582f4f63a1260726d019204b72f460cf20930e6c925a1d129f373", size = 204335, upload-time = "2025-05-24T19:06:53.442Z" }, - { url = "https://files.pythonhosted.org/packages/8f/3f/c95b7d142819f801a0acdbd04280e8132e43b6e5a8920173e8eb92ea0e6a/ormsgpack-1.10.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e7058ef6092f995561bf9f71d6c9a4da867b6cc69d2e94cb80184f579a3ceed5", size = 215373, upload-time = "2025-05-24T19:06:55.153Z" }, - { url = "https://files.pythonhosted.org/packages/ef/1a/e30f4bcf386db2015d1686d1da6110c95110294d8ea04f86091dd5eb3361/ormsgpack-1.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:10f6f3509c1b0e51b15552d314b1d409321718122e90653122ce4b997f01453a", size = 216469, upload-time = "2025-05-24T19:06:56.555Z" }, - { url = "https://files.pythonhosted.org/packages/96/fc/7e44aeade22b91883586f45b7278c118fd210834c069774891447f444fc9/ormsgpack-1.10.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:51c1edafd5c72b863b1f875ec31c529f09c872a5ff6fe473b9dfaf188ccc3227", size = 384590, upload-time = "2025-05-24T19:06:58.286Z" }, - { url = "https://files.pythonhosted.org/packages/ec/78/f92c24e8446697caa83c122f10b6cf5e155eddf81ce63905c8223a260482/ormsgpack-1.10.0-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:c780b44107a547a9e9327270f802fa4d6b0f6667c9c03c3338c0ce812259a0f7", size = 478891, upload-time = "2025-05-24T19:07:00.126Z" }, - { url = "https://files.pythonhosted.org/packages/5a/75/87449690253c64bea2b663c7c8f2dbc9ad39d73d0b38db74bdb0f3947b16/ormsgpack-1.10.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:137aab0d5cdb6df702da950a80405eb2b7038509585e32b4e16289604ac7cb84", size = 390121, upload-time = "2025-05-24T19:07:01.777Z" }, - { url = "https://files.pythonhosted.org/packages/69/cc/c83257faf3a5169ec29dd87121317a25711da9412ee8c1e82f2e1a00c0be/ormsgpack-1.10.0-cp310-cp310-win_amd64.whl", hash = "sha256:3e666cb63030538fa5cd74b1e40cb55b6fdb6e2981f024997a288bf138ebad07", size = 121196, upload-time = "2025-05-24T19:07:03.47Z" }, - { url = "https://files.pythonhosted.org/packages/30/27/7da748bc0d7d567950a378dee5a32477ed5d15462ab186918b5f25cac1ad/ormsgpack-1.10.0-cp311-cp311-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:4bb7df307e17b36cbf7959cd642c47a7f2046ae19408c564e437f0ec323a7775", size = 376275, upload-time = "2025-05-24T19:07:05.128Z" }, - { url = "https://files.pythonhosted.org/packages/7b/65/c082cc8c74a914dbd05af0341c761c73c3d9960b7432bbf9b8e1e20811af/ormsgpack-1.10.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8817ae439c671779e1127ee62f0ac67afdeaeeacb5f0db45703168aa74a2e4af", size = 204335, upload-time = "2025-05-24T19:07:06.423Z" }, - { url = "https://files.pythonhosted.org/packages/46/62/17ef7e5d9766c79355b9c594cc9328c204f1677bc35da0595cc4e46449f0/ormsgpack-1.10.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:2f345f81e852035d80232e64374d3a104139d60f8f43c6c5eade35c4bac5590e", size = 215372, upload-time = "2025-05-24T19:07:08.149Z" }, - { url = "https://files.pythonhosted.org/packages/4e/92/7c91e8115fc37e88d1a35e13200fda3054ff5d2e5adf017345e58cea4834/ormsgpack-1.10.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:21de648a1c7ef692bdd287fb08f047bd5371d7462504c0a7ae1553c39fee35e3", size = 216470, upload-time = "2025-05-24T19:07:09.903Z" }, - { url = "https://files.pythonhosted.org/packages/2c/86/ce053c52e2517b90e390792d83e926a7a523c1bce5cc63d0a7cd05ce6cf6/ormsgpack-1.10.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:3a7d844ae9cbf2112c16086dd931b2acefce14cefd163c57db161170c2bfa22b", size = 384591, upload-time = "2025-05-24T19:07:11.24Z" }, - { url = "https://files.pythonhosted.org/packages/07/e8/2ad59f2ab222c6029e500bc966bfd2fe5cb099f8ab6b7ebeb50ddb1a6fe5/ormsgpack-1.10.0-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:e4d80585403d86d7f800cf3d0aafac1189b403941e84e90dd5102bb2b92bf9d5", size = 478892, upload-time = "2025-05-24T19:07:13.147Z" }, - { url = "https://files.pythonhosted.org/packages/f4/73/f55e4b47b7b18fd8e7789680051bf830f1e39c03f1d9ed993cd0c3e97215/ormsgpack-1.10.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:da1de515a87e339e78a3ccf60e39f5fb740edac3e9e82d3c3d209e217a13ac08", size = 390122, upload-time = "2025-05-24T19:07:14.557Z" }, - { url = "https://files.pythonhosted.org/packages/f7/87/073251cdb93d4c6241748568b3ad1b2a76281fb2002eed16a3a4043d61cf/ormsgpack-1.10.0-cp311-cp311-win_amd64.whl", hash = "sha256:57c4601812684024132cbb32c17a7d4bb46ffc7daf2fddf5b697391c2c4f142a", size = 121197, upload-time = "2025-05-24T19:07:15.981Z" }, - { url = "https://files.pythonhosted.org/packages/99/95/f3ab1a7638f6aa9362e87916bb96087fbbc5909db57e19f12ad127560e1e/ormsgpack-1.10.0-cp312-cp312-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:4e159d50cd4064d7540e2bc6a0ab66eab70b0cc40c618b485324ee17037527c0", size = 376806, upload-time = "2025-05-24T19:07:17.221Z" }, - { url = "https://files.pythonhosted.org/packages/6c/2b/42f559f13c0b0f647b09d749682851d47c1a7e48308c43612ae6833499c8/ormsgpack-1.10.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:eeb47c85f3a866e29279d801115b554af0fefc409e2ed8aa90aabfa77efe5cc6", size = 204433, upload-time = "2025-05-24T19:07:18.569Z" }, - { url = "https://files.pythonhosted.org/packages/45/42/1ca0cb4d8c80340a89a4af9e6d8951fb8ba0d076a899d2084eadf536f677/ormsgpack-1.10.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:c28249574934534c9bd5dce5485c52f21bcea0ee44d13ece3def6e3d2c3798b5", size = 215547, upload-time = "2025-05-24T19:07:20.245Z" }, - { url = "https://files.pythonhosted.org/packages/0a/38/184a570d7c44c0260bc576d1daaac35b2bfd465a50a08189518505748b9a/ormsgpack-1.10.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1957dcadbb16e6a981cd3f9caef9faf4c2df1125e2a1b702ee8236a55837ce07", size = 216746, upload-time = "2025-05-24T19:07:21.83Z" }, - { url = "https://files.pythonhosted.org/packages/69/2f/1aaffd08f6b7fdc2a57336a80bdfb8df24e6a65ada5aa769afecfcbc6cc6/ormsgpack-1.10.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:3b29412558c740bf6bac156727aa85ac67f9952cd6f071318f29ee72e1a76044", size = 384783, upload-time = "2025-05-24T19:07:23.674Z" }, - { url = "https://files.pythonhosted.org/packages/a9/63/3e53d6f43bb35e00c98f2b8ab2006d5138089ad254bc405614fbf0213502/ormsgpack-1.10.0-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:6933f350c2041ec189fe739f0ba7d6117c8772f5bc81f45b97697a84d03020dd", size = 479076, upload-time = "2025-05-24T19:07:25.047Z" }, - { url = "https://files.pythonhosted.org/packages/b8/19/fa1121b03b61402bb4d04e35d164e2320ef73dfb001b57748110319dd014/ormsgpack-1.10.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:9a86de06d368fcc2e58b79dece527dc8ca831e0e8b9cec5d6e633d2777ec93d0", size = 390447, upload-time = "2025-05-24T19:07:26.568Z" }, - { url = "https://files.pythonhosted.org/packages/b0/0d/73143ecb94ac4a5dcba223402139240a75dee0cc6ba8a543788a5646407a/ormsgpack-1.10.0-cp312-cp312-win_amd64.whl", hash = "sha256:35fa9f81e5b9a0dab42e09a73f7339ecffdb978d6dbf9deb2ecf1e9fc7808722", size = 121401, upload-time = "2025-05-24T19:07:28.308Z" }, - { url = "https://files.pythonhosted.org/packages/61/f8/ec5f4e03268d0097545efaab2893aa63f171cf2959cb0ea678a5690e16a1/ormsgpack-1.10.0-cp313-cp313-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:8d816d45175a878993b7372bd5408e0f3ec5a40f48e2d5b9d8f1cc5d31b61f1f", size = 376806, upload-time = "2025-05-24T19:07:29.555Z" }, - { url = "https://files.pythonhosted.org/packages/c1/19/b3c53284aad1e90d4d7ed8c881a373d218e16675b8b38e3569d5b40cc9b8/ormsgpack-1.10.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a90345ccb058de0f35262893751c603b6376b05f02be2b6f6b7e05d9dd6d5643", size = 204433, upload-time = "2025-05-24T19:07:30.977Z" }, - { url = "https://files.pythonhosted.org/packages/09/0b/845c258f59df974a20a536c06cace593698491defdd3d026a8a5f9b6e745/ormsgpack-1.10.0-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:144b5e88f1999433e54db9d637bae6fe21e935888be4e3ac3daecd8260bd454e", size = 215549, upload-time = "2025-05-24T19:07:32.345Z" }, - { url = "https://files.pythonhosted.org/packages/61/56/57fce8fb34ca6c9543c026ebebf08344c64dbb7b6643d6ddd5355d37e724/ormsgpack-1.10.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2190b352509d012915921cca76267db136cd026ddee42f1b0d9624613cc7058c", size = 216747, upload-time = "2025-05-24T19:07:34.075Z" }, - { url = "https://files.pythonhosted.org/packages/b8/3f/655b5f6a2475c8d209f5348cfbaaf73ce26237b92d79ef2ad439407dd0fa/ormsgpack-1.10.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:86fd9c1737eaba43d3bb2730add9c9e8b5fbed85282433705dd1b1e88ea7e6fb", size = 384785, upload-time = "2025-05-24T19:07:35.83Z" }, - { url = "https://files.pythonhosted.org/packages/4b/94/687a0ad8afd17e4bce1892145d6a1111e58987ddb176810d02a1f3f18686/ormsgpack-1.10.0-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:33afe143a7b61ad21bb60109a86bb4e87fec70ef35db76b89c65b17e32da7935", size = 479076, upload-time = "2025-05-24T19:07:37.533Z" }, - { url = "https://files.pythonhosted.org/packages/c8/34/68925232e81e0e062a2f0ac678f62aa3b6f7009d6a759e19324dbbaebae7/ormsgpack-1.10.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:f23d45080846a7b90feabec0d330a9cc1863dc956728412e4f7986c80ab3a668", size = 390446, upload-time = "2025-05-24T19:07:39.469Z" }, - { url = "https://files.pythonhosted.org/packages/12/ad/f4e1a36a6d1714afb7ffb74b3ababdcb96529cf4e7a216f9f7c8eda837b6/ormsgpack-1.10.0-cp313-cp313-win_amd64.whl", hash = "sha256:534d18acb805c75e5fba09598bf40abe1851c853247e61dda0c01f772234da69", size = 121399, upload-time = "2025-05-24T19:07:40.854Z" }, -] - -[[package]] -name = "packaging" -version = "25.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a1/d4/1fc4078c65507b51b96ca8f8c3ba19e6a61c8253c72794544580a7b6c24d/packaging-25.0.tar.gz", hash = "sha256:d443872c98d677bf60f6a1f2f8c1cb748e8fe762d2bf9d3148b5599295b0fc4f", size = 165727, upload-time = "2025-04-19T11:48:59.673Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/20/12/38679034af332785aac8774540895e234f4d07f7545804097de4b666afd8/packaging-25.0-py3-none-any.whl", hash = "sha256:29572ef2b1f17581046b3a2227d5c611fb25ec70ca1ba8554b24b0e69331a484", size = 66469, upload-time = "2025-04-19T11:48:57.875Z" }, -] - -[[package]] -name = "pathspec" -version = "0.12.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ca/bc/f35b8446f4531a7cb215605d100cd88b7ac6f44ab3fc94870c120ab3adbf/pathspec-0.12.1.tar.gz", hash = "sha256:a482d51503a1ab33b1c67a6c3813a26953dbdc71c31dacaef9a838c4e29f5712", size = 51043, upload-time = "2023-12-10T22:30:45Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/cc/20/ff623b09d963f88bfde16306a54e12ee5ea43e9b597108672ff3a408aad6/pathspec-0.12.1-py3-none-any.whl", hash = "sha256:a0d503e138a4c123b27490a4f7beda6a01c6f288df0e4a8b79c7eb0dc7b4cc08", size = 31191, upload-time = "2023-12-10T22:30:43.14Z" }, -] - -[[package]] -name = "platformdirs" -version = "4.4.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/23/e8/21db9c9987b0e728855bd57bff6984f67952bea55d6f75e055c46b5383e8/platformdirs-4.4.0.tar.gz", hash = "sha256:ca753cf4d81dc309bc67b0ea38fd15dc97bc30ce419a7f58d13eb3bf14c4febf", size = 21634, upload-time = "2025-08-26T14:32:04.268Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/40/4b/2028861e724d3bd36227adfa20d3fd24c3fc6d52032f4a93c133be5d17ce/platformdirs-4.4.0-py3-none-any.whl", hash = "sha256:abd01743f24e5287cd7a5db3752faf1a2d65353f38ec26d98e25a6db65958c85", size = 18654, upload-time = "2025-08-26T14:32:02.735Z" }, -] - -[[package]] -name = "pluggy" -version = "1.6.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f9/e2/3e91f31a7d2b083fe6ef3fa267035b518369d9511ffab804f839851d2779/pluggy-1.6.0.tar.gz", hash = "sha256:7dcc130b76258d33b90f61b658791dede3486c3e6bfb003ee5c9bfb396dd22f3", size = 69412, upload-time = "2025-05-15T12:30:07.975Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl", hash = "sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746", size = 20538, upload-time = "2025-05-15T12:30:06.134Z" }, -] - -[[package]] -name = "pre-commit" -version = "4.3.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "cfgv" }, - { name = "identify" }, - { name = "nodeenv" }, - { name = "pyyaml" }, - { name = "virtualenv" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/ff/29/7cf5bbc236333876e4b41f56e06857a87937ce4bf91e117a6991a2dbb02a/pre_commit-4.3.0.tar.gz", hash = "sha256:499fe450cc9d42e9d58e606262795ecb64dd05438943c62b66f6a8673da30b16", size = 193792, upload-time = "2025-08-09T18:56:14.651Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/5b/a5/987a405322d78a73b66e39e4a90e4ef156fd7141bf71df987e50717c321b/pre_commit-4.3.0-py2.py3-none-any.whl", hash = "sha256:2b0747ad7e6e967169136edffee14c16e148a778a54e4f967921aa1ebf2308d8", size = 220965, upload-time = "2025-08-09T18:56:13.192Z" }, -] - -[[package]] -name = "propcache" -version = "0.3.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a6/16/43264e4a779dd8588c21a70f0709665ee8f611211bdd2c87d952cfa7c776/propcache-0.3.2.tar.gz", hash = "sha256:20d7d62e4e7ef05f221e0db2856b979540686342e7dd9973b815599c7057e168", size = 44139, upload-time = "2025-06-09T22:56:06.081Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ab/14/510deed325e262afeb8b360043c5d7c960da7d3ecd6d6f9496c9c56dc7f4/propcache-0.3.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:22d9962a358aedbb7a2e36187ff273adeaab9743373a272976d2e348d08c7770", size = 73178, upload-time = "2025-06-09T22:53:40.126Z" }, - { url = "https://files.pythonhosted.org/packages/cd/4e/ad52a7925ff01c1325653a730c7ec3175a23f948f08626a534133427dcff/propcache-0.3.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0d0fda578d1dc3f77b6b5a5dce3b9ad69a8250a891760a548df850a5e8da87f3", size = 43133, upload-time = "2025-06-09T22:53:41.965Z" }, - { url = "https://files.pythonhosted.org/packages/63/7c/e9399ba5da7780871db4eac178e9c2e204c23dd3e7d32df202092a1ed400/propcache-0.3.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:3def3da3ac3ce41562d85db655d18ebac740cb3fa4367f11a52b3da9d03a5cc3", size = 43039, upload-time = "2025-06-09T22:53:43.268Z" }, - { url = "https://files.pythonhosted.org/packages/22/e1/58da211eb8fdc6fc854002387d38f415a6ca5f5c67c1315b204a5d3e9d7a/propcache-0.3.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9bec58347a5a6cebf239daba9bda37dffec5b8d2ce004d9fe4edef3d2815137e", size = 201903, upload-time = "2025-06-09T22:53:44.872Z" }, - { url = "https://files.pythonhosted.org/packages/c4/0a/550ea0f52aac455cb90111c8bab995208443e46d925e51e2f6ebdf869525/propcache-0.3.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:55ffda449a507e9fbd4aca1a7d9aa6753b07d6166140e5a18d2ac9bc49eac220", size = 213362, upload-time = "2025-06-09T22:53:46.707Z" }, - { url = "https://files.pythonhosted.org/packages/5a/af/9893b7d878deda9bb69fcf54600b247fba7317761b7db11fede6e0f28bd0/propcache-0.3.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:64a67fb39229a8a8491dd42f864e5e263155e729c2e7ff723d6e25f596b1e8cb", size = 210525, upload-time = "2025-06-09T22:53:48.547Z" }, - { url = "https://files.pythonhosted.org/packages/7c/bb/38fd08b278ca85cde36d848091ad2b45954bc5f15cce494bb300b9285831/propcache-0.3.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9da1cf97b92b51253d5b68cf5a2b9e0dafca095e36b7f2da335e27dc6172a614", size = 198283, upload-time = "2025-06-09T22:53:50.067Z" }, - { url = "https://files.pythonhosted.org/packages/78/8c/9fe55bd01d362bafb413dfe508c48753111a1e269737fa143ba85693592c/propcache-0.3.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5f559e127134b07425134b4065be45b166183fdcb433cb6c24c8e4149056ad50", size = 191872, upload-time = "2025-06-09T22:53:51.438Z" }, - { url = "https://files.pythonhosted.org/packages/54/14/4701c33852937a22584e08abb531d654c8bcf7948a8f87ad0a4822394147/propcache-0.3.2-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:aff2e4e06435d61f11a428360a932138d0ec288b0a31dd9bd78d200bd4a2b339", size = 199452, upload-time = "2025-06-09T22:53:53.229Z" }, - { url = "https://files.pythonhosted.org/packages/16/44/447f2253d859602095356007657ee535e0093215ea0b3d1d6a41d16e5201/propcache-0.3.2-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:4927842833830942a5d0a56e6f4839bc484785b8e1ce8d287359794818633ba0", size = 191567, upload-time = "2025-06-09T22:53:54.541Z" }, - { url = "https://files.pythonhosted.org/packages/f2/b3/e4756258749bb2d3b46defcff606a2f47410bab82be5824a67e84015b267/propcache-0.3.2-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:6107ddd08b02654a30fb8ad7a132021759d750a82578b94cd55ee2772b6ebea2", size = 193015, upload-time = "2025-06-09T22:53:56.44Z" }, - { url = "https://files.pythonhosted.org/packages/1e/df/e6d3c7574233164b6330b9fd697beeac402afd367280e6dc377bb99b43d9/propcache-0.3.2-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:70bd8b9cd6b519e12859c99f3fc9a93f375ebd22a50296c3a295028bea73b9e7", size = 204660, upload-time = "2025-06-09T22:53:57.839Z" }, - { url = "https://files.pythonhosted.org/packages/b2/53/e4d31dd5170b4a0e2e6b730f2385a96410633b4833dc25fe5dffd1f73294/propcache-0.3.2-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:2183111651d710d3097338dd1893fcf09c9f54e27ff1a8795495a16a469cc90b", size = 206105, upload-time = "2025-06-09T22:53:59.638Z" }, - { url = "https://files.pythonhosted.org/packages/7f/fe/74d54cf9fbe2a20ff786e5f7afcfde446588f0cf15fb2daacfbc267b866c/propcache-0.3.2-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:fb075ad271405dcad8e2a7ffc9a750a3bf70e533bd86e89f0603e607b93aa64c", size = 196980, upload-time = "2025-06-09T22:54:01.071Z" }, - { url = "https://files.pythonhosted.org/packages/22/ec/c469c9d59dada8a7679625e0440b544fe72e99311a4679c279562051f6fc/propcache-0.3.2-cp310-cp310-win32.whl", hash = "sha256:404d70768080d3d3bdb41d0771037da19d8340d50b08e104ca0e7f9ce55fce70", size = 37679, upload-time = "2025-06-09T22:54:03.003Z" }, - { url = "https://files.pythonhosted.org/packages/38/35/07a471371ac89d418f8d0b699c75ea6dca2041fbda360823de21f6a9ce0a/propcache-0.3.2-cp310-cp310-win_amd64.whl", hash = "sha256:7435d766f978b4ede777002e6b3b6641dd229cd1da8d3d3106a45770365f9ad9", size = 41459, upload-time = "2025-06-09T22:54:04.134Z" }, - { url = "https://files.pythonhosted.org/packages/80/8d/e8b436717ab9c2cfc23b116d2c297305aa4cd8339172a456d61ebf5669b8/propcache-0.3.2-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:0b8d2f607bd8f80ddc04088bc2a037fdd17884a6fcadc47a96e334d72f3717be", size = 74207, upload-time = "2025-06-09T22:54:05.399Z" }, - { url = "https://files.pythonhosted.org/packages/d6/29/1e34000e9766d112171764b9fa3226fa0153ab565d0c242c70e9945318a7/propcache-0.3.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:06766d8f34733416e2e34f46fea488ad5d60726bb9481d3cddf89a6fa2d9603f", size = 43648, upload-time = "2025-06-09T22:54:08.023Z" }, - { url = "https://files.pythonhosted.org/packages/46/92/1ad5af0df781e76988897da39b5f086c2bf0f028b7f9bd1f409bb05b6874/propcache-0.3.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a2dc1f4a1df4fecf4e6f68013575ff4af84ef6f478fe5344317a65d38a8e6dc9", size = 43496, upload-time = "2025-06-09T22:54:09.228Z" }, - { url = "https://files.pythonhosted.org/packages/b3/ce/e96392460f9fb68461fabab3e095cb00c8ddf901205be4eae5ce246e5b7e/propcache-0.3.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:be29c4f4810c5789cf10ddf6af80b041c724e629fa51e308a7a0fb19ed1ef7bf", size = 217288, upload-time = "2025-06-09T22:54:10.466Z" }, - { url = "https://files.pythonhosted.org/packages/c5/2a/866726ea345299f7ceefc861a5e782b045545ae6940851930a6adaf1fca6/propcache-0.3.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:59d61f6970ecbd8ff2e9360304d5c8876a6abd4530cb752c06586849ac8a9dc9", size = 227456, upload-time = "2025-06-09T22:54:11.828Z" }, - { url = "https://files.pythonhosted.org/packages/de/03/07d992ccb6d930398689187e1b3c718339a1c06b8b145a8d9650e4726166/propcache-0.3.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:62180e0b8dbb6b004baec00a7983e4cc52f5ada9cd11f48c3528d8cfa7b96a66", size = 225429, upload-time = "2025-06-09T22:54:13.823Z" }, - { url = "https://files.pythonhosted.org/packages/5d/e6/116ba39448753b1330f48ab8ba927dcd6cf0baea8a0ccbc512dfb49ba670/propcache-0.3.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c144ca294a204c470f18cf4c9d78887810d04a3e2fbb30eea903575a779159df", size = 213472, upload-time = "2025-06-09T22:54:15.232Z" }, - { url = "https://files.pythonhosted.org/packages/a6/85/f01f5d97e54e428885a5497ccf7f54404cbb4f906688a1690cd51bf597dc/propcache-0.3.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c5c2a784234c28854878d68978265617aa6dc0780e53d44b4d67f3651a17a9a2", size = 204480, upload-time = "2025-06-09T22:54:17.104Z" }, - { url = "https://files.pythonhosted.org/packages/e3/79/7bf5ab9033b8b8194cc3f7cf1aaa0e9c3256320726f64a3e1f113a812dce/propcache-0.3.2-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:5745bc7acdafa978ca1642891b82c19238eadc78ba2aaa293c6863b304e552d7", size = 214530, upload-time = "2025-06-09T22:54:18.512Z" }, - { url = "https://files.pythonhosted.org/packages/31/0b/bd3e0c00509b609317df4a18e6b05a450ef2d9a963e1d8bc9c9415d86f30/propcache-0.3.2-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:c0075bf773d66fa8c9d41f66cc132ecc75e5bb9dd7cce3cfd14adc5ca184cb95", size = 205230, upload-time = "2025-06-09T22:54:19.947Z" }, - { url = "https://files.pythonhosted.org/packages/7a/23/fae0ff9b54b0de4e819bbe559508da132d5683c32d84d0dc2ccce3563ed4/propcache-0.3.2-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:5f57aa0847730daceff0497f417c9de353c575d8da3579162cc74ac294c5369e", size = 206754, upload-time = "2025-06-09T22:54:21.716Z" }, - { url = "https://files.pythonhosted.org/packages/b7/7f/ad6a3c22630aaa5f618b4dc3c3598974a72abb4c18e45a50b3cdd091eb2f/propcache-0.3.2-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:eef914c014bf72d18efb55619447e0aecd5fb7c2e3fa7441e2e5d6099bddff7e", size = 218430, upload-time = "2025-06-09T22:54:23.17Z" }, - { url = "https://files.pythonhosted.org/packages/5b/2c/ba4f1c0e8a4b4c75910742f0d333759d441f65a1c7f34683b4a74c0ee015/propcache-0.3.2-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:2a4092e8549031e82facf3decdbc0883755d5bbcc62d3aea9d9e185549936dcf", size = 223884, upload-time = "2025-06-09T22:54:25.539Z" }, - { url = "https://files.pythonhosted.org/packages/88/e4/ebe30fc399e98572019eee82ad0caf512401661985cbd3da5e3140ffa1b0/propcache-0.3.2-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:85871b050f174bc0bfb437efbdb68aaf860611953ed12418e4361bc9c392749e", size = 211480, upload-time = "2025-06-09T22:54:26.892Z" }, - { url = "https://files.pythonhosted.org/packages/96/0a/7d5260b914e01d1d0906f7f38af101f8d8ed0dc47426219eeaf05e8ea7c2/propcache-0.3.2-cp311-cp311-win32.whl", hash = "sha256:36c8d9b673ec57900c3554264e630d45980fd302458e4ac801802a7fd2ef7897", size = 37757, upload-time = "2025-06-09T22:54:28.241Z" }, - { url = "https://files.pythonhosted.org/packages/e1/2d/89fe4489a884bc0da0c3278c552bd4ffe06a1ace559db5ef02ef24ab446b/propcache-0.3.2-cp311-cp311-win_amd64.whl", hash = "sha256:e53af8cb6a781b02d2ea079b5b853ba9430fcbe18a8e3ce647d5982a3ff69f39", size = 41500, upload-time = "2025-06-09T22:54:29.4Z" }, - { url = "https://files.pythonhosted.org/packages/a8/42/9ca01b0a6f48e81615dca4765a8f1dd2c057e0540f6116a27dc5ee01dfb6/propcache-0.3.2-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:8de106b6c84506b31c27168582cd3cb3000a6412c16df14a8628e5871ff83c10", size = 73674, upload-time = "2025-06-09T22:54:30.551Z" }, - { url = "https://files.pythonhosted.org/packages/af/6e/21293133beb550f9c901bbece755d582bfaf2176bee4774000bd4dd41884/propcache-0.3.2-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:28710b0d3975117239c76600ea351934ac7b5ff56e60953474342608dbbb6154", size = 43570, upload-time = "2025-06-09T22:54:32.296Z" }, - { url = "https://files.pythonhosted.org/packages/0c/c8/0393a0a3a2b8760eb3bde3c147f62b20044f0ddac81e9d6ed7318ec0d852/propcache-0.3.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:ce26862344bdf836650ed2487c3d724b00fbfec4233a1013f597b78c1cb73615", size = 43094, upload-time = "2025-06-09T22:54:33.929Z" }, - { url = "https://files.pythonhosted.org/packages/37/2c/489afe311a690399d04a3e03b069225670c1d489eb7b044a566511c1c498/propcache-0.3.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bca54bd347a253af2cf4544bbec232ab982f4868de0dd684246b67a51bc6b1db", size = 226958, upload-time = "2025-06-09T22:54:35.186Z" }, - { url = "https://files.pythonhosted.org/packages/9d/ca/63b520d2f3d418c968bf596839ae26cf7f87bead026b6192d4da6a08c467/propcache-0.3.2-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:55780d5e9a2ddc59711d727226bb1ba83a22dd32f64ee15594b9392b1f544eb1", size = 234894, upload-time = "2025-06-09T22:54:36.708Z" }, - { url = "https://files.pythonhosted.org/packages/11/60/1d0ed6fff455a028d678df30cc28dcee7af77fa2b0e6962ce1df95c9a2a9/propcache-0.3.2-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:035e631be25d6975ed87ab23153db6a73426a48db688070d925aa27e996fe93c", size = 233672, upload-time = "2025-06-09T22:54:38.062Z" }, - { url = "https://files.pythonhosted.org/packages/37/7c/54fd5301ef38505ab235d98827207176a5c9b2aa61939b10a460ca53e123/propcache-0.3.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ee6f22b6eaa39297c751d0e80c0d3a454f112f5c6481214fcf4c092074cecd67", size = 224395, upload-time = "2025-06-09T22:54:39.634Z" }, - { url = "https://files.pythonhosted.org/packages/ee/1a/89a40e0846f5de05fdc6779883bf46ba980e6df4d2ff8fb02643de126592/propcache-0.3.2-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7ca3aee1aa955438c4dba34fc20a9f390e4c79967257d830f137bd5a8a32ed3b", size = 212510, upload-time = "2025-06-09T22:54:41.565Z" }, - { url = "https://files.pythonhosted.org/packages/5e/33/ca98368586c9566a6b8d5ef66e30484f8da84c0aac3f2d9aec6d31a11bd5/propcache-0.3.2-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:7a4f30862869fa2b68380d677cc1c5fcf1e0f2b9ea0cf665812895c75d0ca3b8", size = 222949, upload-time = "2025-06-09T22:54:43.038Z" }, - { url = "https://files.pythonhosted.org/packages/ba/11/ace870d0aafe443b33b2f0b7efdb872b7c3abd505bfb4890716ad7865e9d/propcache-0.3.2-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:b77ec3c257d7816d9f3700013639db7491a434644c906a2578a11daf13176251", size = 217258, upload-time = "2025-06-09T22:54:44.376Z" }, - { url = "https://files.pythonhosted.org/packages/5b/d2/86fd6f7adffcfc74b42c10a6b7db721d1d9ca1055c45d39a1a8f2a740a21/propcache-0.3.2-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:cab90ac9d3f14b2d5050928483d3d3b8fb6b4018893fc75710e6aa361ecb2474", size = 213036, upload-time = "2025-06-09T22:54:46.243Z" }, - { url = "https://files.pythonhosted.org/packages/07/94/2d7d1e328f45ff34a0a284cf5a2847013701e24c2a53117e7c280a4316b3/propcache-0.3.2-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:0b504d29f3c47cf6b9e936c1852246c83d450e8e063d50562115a6be6d3a2535", size = 227684, upload-time = "2025-06-09T22:54:47.63Z" }, - { url = "https://files.pythonhosted.org/packages/b7/05/37ae63a0087677e90b1d14710e532ff104d44bc1efa3b3970fff99b891dc/propcache-0.3.2-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:ce2ac2675a6aa41ddb2a0c9cbff53780a617ac3d43e620f8fd77ba1c84dcfc06", size = 234562, upload-time = "2025-06-09T22:54:48.982Z" }, - { url = "https://files.pythonhosted.org/packages/a4/7c/3f539fcae630408d0bd8bf3208b9a647ccad10976eda62402a80adf8fc34/propcache-0.3.2-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:62b4239611205294cc433845b914131b2a1f03500ff3c1ed093ed216b82621e1", size = 222142, upload-time = "2025-06-09T22:54:50.424Z" }, - { url = "https://files.pythonhosted.org/packages/7c/d2/34b9eac8c35f79f8a962546b3e97e9d4b990c420ee66ac8255d5d9611648/propcache-0.3.2-cp312-cp312-win32.whl", hash = "sha256:df4a81b9b53449ebc90cc4deefb052c1dd934ba85012aa912c7ea7b7e38b60c1", size = 37711, upload-time = "2025-06-09T22:54:52.072Z" }, - { url = "https://files.pythonhosted.org/packages/19/61/d582be5d226cf79071681d1b46b848d6cb03d7b70af7063e33a2787eaa03/propcache-0.3.2-cp312-cp312-win_amd64.whl", hash = "sha256:7046e79b989d7fe457bb755844019e10f693752d169076138abf17f31380800c", size = 41479, upload-time = "2025-06-09T22:54:53.234Z" }, - { url = "https://files.pythonhosted.org/packages/dc/d1/8c747fafa558c603c4ca19d8e20b288aa0c7cda74e9402f50f31eb65267e/propcache-0.3.2-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:ca592ed634a73ca002967458187109265e980422116c0a107cf93d81f95af945", size = 71286, upload-time = "2025-06-09T22:54:54.369Z" }, - { url = "https://files.pythonhosted.org/packages/61/99/d606cb7986b60d89c36de8a85d58764323b3a5ff07770a99d8e993b3fa73/propcache-0.3.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:9ecb0aad4020e275652ba3975740f241bd12a61f1a784df044cf7477a02bc252", size = 42425, upload-time = "2025-06-09T22:54:55.642Z" }, - { url = "https://files.pythonhosted.org/packages/8c/96/ef98f91bbb42b79e9bb82bdd348b255eb9d65f14dbbe3b1594644c4073f7/propcache-0.3.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:7f08f1cc28bd2eade7a8a3d2954ccc673bb02062e3e7da09bc75d843386b342f", size = 41846, upload-time = "2025-06-09T22:54:57.246Z" }, - { url = "https://files.pythonhosted.org/packages/5b/ad/3f0f9a705fb630d175146cd7b1d2bf5555c9beaed54e94132b21aac098a6/propcache-0.3.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d1a342c834734edb4be5ecb1e9fb48cb64b1e2320fccbd8c54bf8da8f2a84c33", size = 208871, upload-time = "2025-06-09T22:54:58.975Z" }, - { url = "https://files.pythonhosted.org/packages/3a/38/2085cda93d2c8b6ec3e92af2c89489a36a5886b712a34ab25de9fbca7992/propcache-0.3.2-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8a544caaae1ac73f1fecfae70ded3e93728831affebd017d53449e3ac052ac1e", size = 215720, upload-time = "2025-06-09T22:55:00.471Z" }, - { url = "https://files.pythonhosted.org/packages/61/c1/d72ea2dc83ac7f2c8e182786ab0fc2c7bd123a1ff9b7975bee671866fe5f/propcache-0.3.2-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:310d11aa44635298397db47a3ebce7db99a4cc4b9bbdfcf6c98a60c8d5261cf1", size = 215203, upload-time = "2025-06-09T22:55:01.834Z" }, - { url = "https://files.pythonhosted.org/packages/af/81/b324c44ae60c56ef12007105f1460d5c304b0626ab0cc6b07c8f2a9aa0b8/propcache-0.3.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c1396592321ac83157ac03a2023aa6cc4a3cc3cfdecb71090054c09e5a7cce3", size = 206365, upload-time = "2025-06-09T22:55:03.199Z" }, - { url = "https://files.pythonhosted.org/packages/09/73/88549128bb89e66d2aff242488f62869014ae092db63ccea53c1cc75a81d/propcache-0.3.2-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8cabf5b5902272565e78197edb682017d21cf3b550ba0460ee473753f28d23c1", size = 196016, upload-time = "2025-06-09T22:55:04.518Z" }, - { url = "https://files.pythonhosted.org/packages/b9/3f/3bdd14e737d145114a5eb83cb172903afba7242f67c5877f9909a20d948d/propcache-0.3.2-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:0a2f2235ac46a7aa25bdeb03a9e7060f6ecbd213b1f9101c43b3090ffb971ef6", size = 205596, upload-time = "2025-06-09T22:55:05.942Z" }, - { url = "https://files.pythonhosted.org/packages/0f/ca/2f4aa819c357d3107c3763d7ef42c03980f9ed5c48c82e01e25945d437c1/propcache-0.3.2-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:92b69e12e34869a6970fd2f3da91669899994b47c98f5d430b781c26f1d9f387", size = 200977, upload-time = "2025-06-09T22:55:07.792Z" }, - { url = "https://files.pythonhosted.org/packages/cd/4a/e65276c7477533c59085251ae88505caf6831c0e85ff8b2e31ebcbb949b1/propcache-0.3.2-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:54e02207c79968ebbdffc169591009f4474dde3b4679e16634d34c9363ff56b4", size = 197220, upload-time = "2025-06-09T22:55:09.173Z" }, - { url = "https://files.pythonhosted.org/packages/7c/54/fc7152e517cf5578278b242396ce4d4b36795423988ef39bb8cd5bf274c8/propcache-0.3.2-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:4adfb44cb588001f68c5466579d3f1157ca07f7504fc91ec87862e2b8e556b88", size = 210642, upload-time = "2025-06-09T22:55:10.62Z" }, - { url = "https://files.pythonhosted.org/packages/b9/80/abeb4a896d2767bf5f1ea7b92eb7be6a5330645bd7fb844049c0e4045d9d/propcache-0.3.2-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:fd3e6019dc1261cd0291ee8919dd91fbab7b169bb76aeef6c716833a3f65d206", size = 212789, upload-time = "2025-06-09T22:55:12.029Z" }, - { url = "https://files.pythonhosted.org/packages/b3/db/ea12a49aa7b2b6d68a5da8293dcf50068d48d088100ac016ad92a6a780e6/propcache-0.3.2-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:4c181cad81158d71c41a2bce88edce078458e2dd5ffee7eddd6b05da85079f43", size = 205880, upload-time = "2025-06-09T22:55:13.45Z" }, - { url = "https://files.pythonhosted.org/packages/d1/e5/9076a0bbbfb65d1198007059c65639dfd56266cf8e477a9707e4b1999ff4/propcache-0.3.2-cp313-cp313-win32.whl", hash = "sha256:8a08154613f2249519e549de2330cf8e2071c2887309a7b07fb56098f5170a02", size = 37220, upload-time = "2025-06-09T22:55:15.284Z" }, - { url = "https://files.pythonhosted.org/packages/d3/f5/b369e026b09a26cd77aa88d8fffd69141d2ae00a2abaaf5380d2603f4b7f/propcache-0.3.2-cp313-cp313-win_amd64.whl", hash = "sha256:e41671f1594fc4ab0a6dec1351864713cb3a279910ae8b58f884a88a0a632c05", size = 40678, upload-time = "2025-06-09T22:55:16.445Z" }, - { url = "https://files.pythonhosted.org/packages/a4/3a/6ece377b55544941a08d03581c7bc400a3c8cd3c2865900a68d5de79e21f/propcache-0.3.2-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:9a3cf035bbaf035f109987d9d55dc90e4b0e36e04bbbb95af3055ef17194057b", size = 76560, upload-time = "2025-06-09T22:55:17.598Z" }, - { url = "https://files.pythonhosted.org/packages/0c/da/64a2bb16418740fa634b0e9c3d29edff1db07f56d3546ca2d86ddf0305e1/propcache-0.3.2-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:156c03d07dc1323d8dacaa221fbe028c5c70d16709cdd63502778e6c3ccca1b0", size = 44676, upload-time = "2025-06-09T22:55:18.922Z" }, - { url = "https://files.pythonhosted.org/packages/36/7b/f025e06ea51cb72c52fb87e9b395cced02786610b60a3ed51da8af017170/propcache-0.3.2-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:74413c0ba02ba86f55cf60d18daab219f7e531620c15f1e23d95563f505efe7e", size = 44701, upload-time = "2025-06-09T22:55:20.106Z" }, - { url = "https://files.pythonhosted.org/packages/a4/00/faa1b1b7c3b74fc277f8642f32a4c72ba1d7b2de36d7cdfb676db7f4303e/propcache-0.3.2-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f066b437bb3fa39c58ff97ab2ca351db465157d68ed0440abecb21715eb24b28", size = 276934, upload-time = "2025-06-09T22:55:21.5Z" }, - { url = "https://files.pythonhosted.org/packages/74/ab/935beb6f1756e0476a4d5938ff44bf0d13a055fed880caf93859b4f1baf4/propcache-0.3.2-cp313-cp313t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f1304b085c83067914721e7e9d9917d41ad87696bf70f0bc7dee450e9c71ad0a", size = 278316, upload-time = "2025-06-09T22:55:22.918Z" }, - { url = "https://files.pythonhosted.org/packages/f8/9d/994a5c1ce4389610838d1caec74bdf0e98b306c70314d46dbe4fcf21a3e2/propcache-0.3.2-cp313-cp313t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ab50cef01b372763a13333b4e54021bdcb291fc9a8e2ccb9c2df98be51bcde6c", size = 282619, upload-time = "2025-06-09T22:55:24.651Z" }, - { url = "https://files.pythonhosted.org/packages/2b/00/a10afce3d1ed0287cef2e09506d3be9822513f2c1e96457ee369adb9a6cd/propcache-0.3.2-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fad3b2a085ec259ad2c2842666b2a0a49dea8463579c606426128925af1ed725", size = 265896, upload-time = "2025-06-09T22:55:26.049Z" }, - { url = "https://files.pythonhosted.org/packages/2e/a8/2aa6716ffa566ca57c749edb909ad27884680887d68517e4be41b02299f3/propcache-0.3.2-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:261fa020c1c14deafd54c76b014956e2f86991af198c51139faf41c4d5e83892", size = 252111, upload-time = "2025-06-09T22:55:27.381Z" }, - { url = "https://files.pythonhosted.org/packages/36/4f/345ca9183b85ac29c8694b0941f7484bf419c7f0fea2d1e386b4f7893eed/propcache-0.3.2-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:46d7f8aa79c927e5f987ee3a80205c987717d3659f035c85cf0c3680526bdb44", size = 268334, upload-time = "2025-06-09T22:55:28.747Z" }, - { url = "https://files.pythonhosted.org/packages/3e/ca/fcd54f78b59e3f97b3b9715501e3147f5340167733d27db423aa321e7148/propcache-0.3.2-cp313-cp313t-musllinux_1_2_armv7l.whl", hash = "sha256:6d8f3f0eebf73e3c0ff0e7853f68be638b4043c65a70517bb575eff54edd8dbe", size = 255026, upload-time = "2025-06-09T22:55:30.184Z" }, - { url = "https://files.pythonhosted.org/packages/8b/95/8e6a6bbbd78ac89c30c225210a5c687790e532ba4088afb8c0445b77ef37/propcache-0.3.2-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:03c89c1b14a5452cf15403e291c0ccd7751d5b9736ecb2c5bab977ad6c5bcd81", size = 250724, upload-time = "2025-06-09T22:55:31.646Z" }, - { url = "https://files.pythonhosted.org/packages/ee/b0/0dd03616142baba28e8b2d14ce5df6631b4673850a3d4f9c0f9dd714a404/propcache-0.3.2-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:0cc17efde71e12bbaad086d679ce575268d70bc123a5a71ea7ad76f70ba30bba", size = 268868, upload-time = "2025-06-09T22:55:33.209Z" }, - { url = "https://files.pythonhosted.org/packages/c5/98/2c12407a7e4fbacd94ddd32f3b1e3d5231e77c30ef7162b12a60e2dd5ce3/propcache-0.3.2-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:acdf05d00696bc0447e278bb53cb04ca72354e562cf88ea6f9107df8e7fd9770", size = 271322, upload-time = "2025-06-09T22:55:35.065Z" }, - { url = "https://files.pythonhosted.org/packages/35/91/9cb56efbb428b006bb85db28591e40b7736847b8331d43fe335acf95f6c8/propcache-0.3.2-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:4445542398bd0b5d32df908031cb1b30d43ac848e20470a878b770ec2dcc6330", size = 265778, upload-time = "2025-06-09T22:55:36.45Z" }, - { url = "https://files.pythonhosted.org/packages/9a/4c/b0fe775a2bdd01e176b14b574be679d84fc83958335790f7c9a686c1f468/propcache-0.3.2-cp313-cp313t-win32.whl", hash = "sha256:f86e5d7cd03afb3a1db8e9f9f6eff15794e79e791350ac48a8c924e6f439f394", size = 41175, upload-time = "2025-06-09T22:55:38.436Z" }, - { url = "https://files.pythonhosted.org/packages/a4/ff/47f08595e3d9b5e149c150f88d9714574f1a7cbd89fe2817158a952674bf/propcache-0.3.2-cp313-cp313t-win_amd64.whl", hash = "sha256:9704bedf6e7cbe3c65eca4379a9b53ee6a83749f047808cbb5044d40d7d72198", size = 44857, upload-time = "2025-06-09T22:55:39.687Z" }, - { url = "https://files.pythonhosted.org/packages/cc/35/cc0aaecf278bb4575b8555f2b137de5ab821595ddae9da9d3cd1da4072c7/propcache-0.3.2-py3-none-any.whl", hash = "sha256:98f1ec44fb675f5052cccc8e609c46ed23a35a1cfd18545ad4e29002d858a43f", size = 12663, upload-time = "2025-06-09T22:56:04.484Z" }, -] - -[[package]] -name = "pycodestyle" -version = "2.14.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/11/e0/abfd2a0d2efe47670df87f3e3a0e2edda42f055053c85361f19c0e2c1ca8/pycodestyle-2.14.0.tar.gz", hash = "sha256:c4b5b517d278089ff9d0abdec919cd97262a3367449ea1c8b49b91529167b783", size = 39472, upload-time = "2025-06-20T18:49:48.75Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d7/27/a58ddaf8c588a3ef080db9d0b7e0b97215cee3a45df74f3a94dbbf5c893a/pycodestyle-2.14.0-py2.py3-none-any.whl", hash = "sha256:dd6bf7cb4ee77f8e016f9c8e74a35ddd9f67e1d5fd4184d86c3b98e07099f42d", size = 31594, upload-time = "2025-06-20T18:49:47.491Z" }, -] - -[[package]] -name = "pycparser" -version = "2.23" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/fe/cf/d2d3b9f5699fb1e4615c8e32ff220203e43b248e1dfcc6736ad9057731ca/pycparser-2.23.tar.gz", hash = "sha256:78816d4f24add8f10a06d6f05b4d424ad9e96cfebf68a4ddc99c65c0720d00c2", size = 173734, upload-time = "2025-09-09T13:23:47.91Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a0/e3/59cd50310fc9b59512193629e1984c1f95e5c8ae6e5d8c69532ccc65a7fe/pycparser-2.23-py3-none-any.whl", hash = "sha256:e5c6e8d3fbad53479cab09ac03729e0a9faf2bee3db8208a550daf5af81a5934", size = 118140, upload-time = "2025-09-09T13:23:46.651Z" }, -] - -[[package]] -name = "pydantic" -version = "2.11.9" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "annotated-types" }, - { name = "pydantic-core" }, - { name = "typing-extensions" }, - { name = "typing-inspection" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/ff/5d/09a551ba512d7ca404d785072700d3f6727a02f6f3c24ecfd081c7cf0aa8/pydantic-2.11.9.tar.gz", hash = "sha256:6b8ffda597a14812a7975c90b82a8a2e777d9257aba3453f973acd3c032a18e2", size = 788495, upload-time = "2025-09-13T11:26:39.325Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/3e/d3/108f2006987c58e76691d5ae5d200dd3e0f532cb4e5fa3560751c3a1feba/pydantic-2.11.9-py3-none-any.whl", hash = "sha256:c42dd626f5cfc1c6950ce6205ea58c93efa406da65f479dcb4029d5934857da2", size = 444855, upload-time = "2025-09-13T11:26:36.909Z" }, -] - -[[package]] -name = "pydantic-core" -version = "2.33.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/ad/88/5f2260bdfae97aabf98f1778d43f69574390ad787afb646292a638c923d4/pydantic_core-2.33.2.tar.gz", hash = "sha256:7cb8bc3605c29176e1b105350d2e6474142d7c1bd1d9327c4a9bdb46bf827acc", size = 435195, upload-time = "2025-04-23T18:33:52.104Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e5/92/b31726561b5dae176c2d2c2dc43a9c5bfba5d32f96f8b4c0a600dd492447/pydantic_core-2.33.2-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:2b3d326aaef0c0399d9afffeb6367d5e26ddc24d351dbc9c636840ac355dc5d8", size = 2028817, upload-time = "2025-04-23T18:30:43.919Z" }, - { url = "https://files.pythonhosted.org/packages/a3/44/3f0b95fafdaca04a483c4e685fe437c6891001bf3ce8b2fded82b9ea3aa1/pydantic_core-2.33.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0e5b2671f05ba48b94cb90ce55d8bdcaaedb8ba00cc5359f6810fc918713983d", size = 1861357, upload-time = "2025-04-23T18:30:46.372Z" }, - { url = "https://files.pythonhosted.org/packages/30/97/e8f13b55766234caae05372826e8e4b3b96e7b248be3157f53237682e43c/pydantic_core-2.33.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0069c9acc3f3981b9ff4cdfaf088e98d83440a4c7ea1bc07460af3d4dc22e72d", size = 1898011, upload-time = "2025-04-23T18:30:47.591Z" }, - { url = "https://files.pythonhosted.org/packages/9b/a3/99c48cf7bafc991cc3ee66fd544c0aae8dc907b752f1dad2d79b1b5a471f/pydantic_core-2.33.2-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:d53b22f2032c42eaaf025f7c40c2e3b94568ae077a606f006d206a463bc69572", size = 1982730, upload-time = "2025-04-23T18:30:49.328Z" }, - { url = "https://files.pythonhosted.org/packages/de/8e/a5b882ec4307010a840fb8b58bd9bf65d1840c92eae7534c7441709bf54b/pydantic_core-2.33.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0405262705a123b7ce9f0b92f123334d67b70fd1f20a9372b907ce1080c7ba02", size = 2136178, upload-time = "2025-04-23T18:30:50.907Z" }, - { url = "https://files.pythonhosted.org/packages/e4/bb/71e35fc3ed05af6834e890edb75968e2802fe98778971ab5cba20a162315/pydantic_core-2.33.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4b25d91e288e2c4e0662b8038a28c6a07eaac3e196cfc4ff69de4ea3db992a1b", size = 2736462, upload-time = "2025-04-23T18:30:52.083Z" }, - { url = "https://files.pythonhosted.org/packages/31/0d/c8f7593e6bc7066289bbc366f2235701dcbebcd1ff0ef8e64f6f239fb47d/pydantic_core-2.33.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6bdfe4b3789761f3bcb4b1ddf33355a71079858958e3a552f16d5af19768fef2", size = 2005652, upload-time = "2025-04-23T18:30:53.389Z" }, - { url = "https://files.pythonhosted.org/packages/d2/7a/996d8bd75f3eda405e3dd219ff5ff0a283cd8e34add39d8ef9157e722867/pydantic_core-2.33.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:efec8db3266b76ef9607c2c4c419bdb06bf335ae433b80816089ea7585816f6a", size = 2113306, upload-time = "2025-04-23T18:30:54.661Z" }, - { url = "https://files.pythonhosted.org/packages/ff/84/daf2a6fb2db40ffda6578a7e8c5a6e9c8affb251a05c233ae37098118788/pydantic_core-2.33.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:031c57d67ca86902726e0fae2214ce6770bbe2f710dc33063187a68744a5ecac", size = 2073720, upload-time = "2025-04-23T18:30:56.11Z" }, - { url = "https://files.pythonhosted.org/packages/77/fb/2258da019f4825128445ae79456a5499c032b55849dbd5bed78c95ccf163/pydantic_core-2.33.2-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:f8de619080e944347f5f20de29a975c2d815d9ddd8be9b9b7268e2e3ef68605a", size = 2244915, upload-time = "2025-04-23T18:30:57.501Z" }, - { url = "https://files.pythonhosted.org/packages/d8/7a/925ff73756031289468326e355b6fa8316960d0d65f8b5d6b3a3e7866de7/pydantic_core-2.33.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:73662edf539e72a9440129f231ed3757faab89630d291b784ca99237fb94db2b", size = 2241884, upload-time = "2025-04-23T18:30:58.867Z" }, - { url = "https://files.pythonhosted.org/packages/0b/b0/249ee6d2646f1cdadcb813805fe76265745c4010cf20a8eba7b0e639d9b2/pydantic_core-2.33.2-cp310-cp310-win32.whl", hash = "sha256:0a39979dcbb70998b0e505fb1556a1d550a0781463ce84ebf915ba293ccb7e22", size = 1910496, upload-time = "2025-04-23T18:31:00.078Z" }, - { url = "https://files.pythonhosted.org/packages/66/ff/172ba8f12a42d4b552917aa65d1f2328990d3ccfc01d5b7c943ec084299f/pydantic_core-2.33.2-cp310-cp310-win_amd64.whl", hash = "sha256:b0379a2b24882fef529ec3b4987cb5d003b9cda32256024e6fe1586ac45fc640", size = 1955019, upload-time = "2025-04-23T18:31:01.335Z" }, - { url = "https://files.pythonhosted.org/packages/3f/8d/71db63483d518cbbf290261a1fc2839d17ff89fce7089e08cad07ccfce67/pydantic_core-2.33.2-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:4c5b0a576fb381edd6d27f0a85915c6daf2f8138dc5c267a57c08a62900758c7", size = 2028584, upload-time = "2025-04-23T18:31:03.106Z" }, - { url = "https://files.pythonhosted.org/packages/24/2f/3cfa7244ae292dd850989f328722d2aef313f74ffc471184dc509e1e4e5a/pydantic_core-2.33.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:e799c050df38a639db758c617ec771fd8fb7a5f8eaaa4b27b101f266b216a246", size = 1855071, upload-time = "2025-04-23T18:31:04.621Z" }, - { url = "https://files.pythonhosted.org/packages/b3/d3/4ae42d33f5e3f50dd467761304be2fa0a9417fbf09735bc2cce003480f2a/pydantic_core-2.33.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dc46a01bf8d62f227d5ecee74178ffc448ff4e5197c756331f71efcc66dc980f", size = 1897823, upload-time = "2025-04-23T18:31:06.377Z" }, - { url = "https://files.pythonhosted.org/packages/f4/f3/aa5976e8352b7695ff808599794b1fba2a9ae2ee954a3426855935799488/pydantic_core-2.33.2-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a144d4f717285c6d9234a66778059f33a89096dfb9b39117663fd8413d582dcc", size = 1983792, upload-time = "2025-04-23T18:31:07.93Z" }, - { url = "https://files.pythonhosted.org/packages/d5/7a/cda9b5a23c552037717f2b2a5257e9b2bfe45e687386df9591eff7b46d28/pydantic_core-2.33.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:73cf6373c21bc80b2e0dc88444f41ae60b2f070ed02095754eb5a01df12256de", size = 2136338, upload-time = "2025-04-23T18:31:09.283Z" }, - { url = "https://files.pythonhosted.org/packages/2b/9f/b8f9ec8dd1417eb9da784e91e1667d58a2a4a7b7b34cf4af765ef663a7e5/pydantic_core-2.33.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3dc625f4aa79713512d1976fe9f0bc99f706a9dee21dfd1810b4bbbf228d0e8a", size = 2730998, upload-time = "2025-04-23T18:31:11.7Z" }, - { url = "https://files.pythonhosted.org/packages/47/bc/cd720e078576bdb8255d5032c5d63ee5c0bf4b7173dd955185a1d658c456/pydantic_core-2.33.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:881b21b5549499972441da4758d662aeea93f1923f953e9cbaff14b8b9565aef", size = 2003200, upload-time = "2025-04-23T18:31:13.536Z" }, - { url = "https://files.pythonhosted.org/packages/ca/22/3602b895ee2cd29d11a2b349372446ae9727c32e78a94b3d588a40fdf187/pydantic_core-2.33.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:bdc25f3681f7b78572699569514036afe3c243bc3059d3942624e936ec93450e", size = 2113890, upload-time = "2025-04-23T18:31:15.011Z" }, - { url = "https://files.pythonhosted.org/packages/ff/e6/e3c5908c03cf00d629eb38393a98fccc38ee0ce8ecce32f69fc7d7b558a7/pydantic_core-2.33.2-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:fe5b32187cbc0c862ee201ad66c30cf218e5ed468ec8dc1cf49dec66e160cc4d", size = 2073359, upload-time = "2025-04-23T18:31:16.393Z" }, - { url = "https://files.pythonhosted.org/packages/12/e7/6a36a07c59ebefc8777d1ffdaf5ae71b06b21952582e4b07eba88a421c79/pydantic_core-2.33.2-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:bc7aee6f634a6f4a95676fcb5d6559a2c2a390330098dba5e5a5f28a2e4ada30", size = 2245883, upload-time = "2025-04-23T18:31:17.892Z" }, - { url = "https://files.pythonhosted.org/packages/16/3f/59b3187aaa6cc0c1e6616e8045b284de2b6a87b027cce2ffcea073adf1d2/pydantic_core-2.33.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:235f45e5dbcccf6bd99f9f472858849f73d11120d76ea8707115415f8e5ebebf", size = 2241074, upload-time = "2025-04-23T18:31:19.205Z" }, - { url = "https://files.pythonhosted.org/packages/e0/ed/55532bb88f674d5d8f67ab121a2a13c385df382de2a1677f30ad385f7438/pydantic_core-2.33.2-cp311-cp311-win32.whl", hash = "sha256:6368900c2d3ef09b69cb0b913f9f8263b03786e5b2a387706c5afb66800efd51", size = 1910538, upload-time = "2025-04-23T18:31:20.541Z" }, - { url = "https://files.pythonhosted.org/packages/fe/1b/25b7cccd4519c0b23c2dd636ad39d381abf113085ce4f7bec2b0dc755eb1/pydantic_core-2.33.2-cp311-cp311-win_amd64.whl", hash = "sha256:1e063337ef9e9820c77acc768546325ebe04ee38b08703244c1309cccc4f1bab", size = 1952909, upload-time = "2025-04-23T18:31:22.371Z" }, - { url = "https://files.pythonhosted.org/packages/49/a9/d809358e49126438055884c4366a1f6227f0f84f635a9014e2deb9b9de54/pydantic_core-2.33.2-cp311-cp311-win_arm64.whl", hash = "sha256:6b99022f1d19bc32a4c2a0d544fc9a76e3be90f0b3f4af413f87d38749300e65", size = 1897786, upload-time = "2025-04-23T18:31:24.161Z" }, - { url = "https://files.pythonhosted.org/packages/18/8a/2b41c97f554ec8c71f2a8a5f85cb56a8b0956addfe8b0efb5b3d77e8bdc3/pydantic_core-2.33.2-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:a7ec89dc587667f22b6a0b6579c249fca9026ce7c333fc142ba42411fa243cdc", size = 2009000, upload-time = "2025-04-23T18:31:25.863Z" }, - { url = "https://files.pythonhosted.org/packages/a1/02/6224312aacb3c8ecbaa959897af57181fb6cf3a3d7917fd44d0f2917e6f2/pydantic_core-2.33.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:3c6db6e52c6d70aa0d00d45cdb9b40f0433b96380071ea80b09277dba021ddf7", size = 1847996, upload-time = "2025-04-23T18:31:27.341Z" }, - { url = "https://files.pythonhosted.org/packages/d6/46/6dcdf084a523dbe0a0be59d054734b86a981726f221f4562aed313dbcb49/pydantic_core-2.33.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4e61206137cbc65e6d5256e1166f88331d3b6238e082d9f74613b9b765fb9025", size = 1880957, upload-time = "2025-04-23T18:31:28.956Z" }, - { url = "https://files.pythonhosted.org/packages/ec/6b/1ec2c03837ac00886ba8160ce041ce4e325b41d06a034adbef11339ae422/pydantic_core-2.33.2-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:eb8c529b2819c37140eb51b914153063d27ed88e3bdc31b71198a198e921e011", size = 1964199, upload-time = "2025-04-23T18:31:31.025Z" }, - { url = "https://files.pythonhosted.org/packages/2d/1d/6bf34d6adb9debd9136bd197ca72642203ce9aaaa85cfcbfcf20f9696e83/pydantic_core-2.33.2-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c52b02ad8b4e2cf14ca7b3d918f3eb0ee91e63b3167c32591e57c4317e134f8f", size = 2120296, upload-time = "2025-04-23T18:31:32.514Z" }, - { url = "https://files.pythonhosted.org/packages/e0/94/2bd0aaf5a591e974b32a9f7123f16637776c304471a0ab33cf263cf5591a/pydantic_core-2.33.2-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:96081f1605125ba0855dfda83f6f3df5ec90c61195421ba72223de35ccfb2f88", size = 2676109, upload-time = "2025-04-23T18:31:33.958Z" }, - { url = "https://files.pythonhosted.org/packages/f9/41/4b043778cf9c4285d59742281a769eac371b9e47e35f98ad321349cc5d61/pydantic_core-2.33.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8f57a69461af2a5fa6e6bbd7a5f60d3b7e6cebb687f55106933188e79ad155c1", size = 2002028, upload-time = "2025-04-23T18:31:39.095Z" }, - { url = "https://files.pythonhosted.org/packages/cb/d5/7bb781bf2748ce3d03af04d5c969fa1308880e1dca35a9bd94e1a96a922e/pydantic_core-2.33.2-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:572c7e6c8bb4774d2ac88929e3d1f12bc45714ae5ee6d9a788a9fb35e60bb04b", size = 2100044, upload-time = "2025-04-23T18:31:41.034Z" }, - { url = "https://files.pythonhosted.org/packages/fe/36/def5e53e1eb0ad896785702a5bbfd25eed546cdcf4087ad285021a90ed53/pydantic_core-2.33.2-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:db4b41f9bd95fbe5acd76d89920336ba96f03e149097365afe1cb092fceb89a1", size = 2058881, upload-time = "2025-04-23T18:31:42.757Z" }, - { url = "https://files.pythonhosted.org/packages/01/6c/57f8d70b2ee57fc3dc8b9610315949837fa8c11d86927b9bb044f8705419/pydantic_core-2.33.2-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:fa854f5cf7e33842a892e5c73f45327760bc7bc516339fda888c75ae60edaeb6", size = 2227034, upload-time = "2025-04-23T18:31:44.304Z" }, - { url = "https://files.pythonhosted.org/packages/27/b9/9c17f0396a82b3d5cbea4c24d742083422639e7bb1d5bf600e12cb176a13/pydantic_core-2.33.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:5f483cfb75ff703095c59e365360cb73e00185e01aaea067cd19acffd2ab20ea", size = 2234187, upload-time = "2025-04-23T18:31:45.891Z" }, - { url = "https://files.pythonhosted.org/packages/b0/6a/adf5734ffd52bf86d865093ad70b2ce543415e0e356f6cacabbc0d9ad910/pydantic_core-2.33.2-cp312-cp312-win32.whl", hash = "sha256:9cb1da0f5a471435a7bc7e439b8a728e8b61e59784b2af70d7c169f8dd8ae290", size = 1892628, upload-time = "2025-04-23T18:31:47.819Z" }, - { url = "https://files.pythonhosted.org/packages/43/e4/5479fecb3606c1368d496a825d8411e126133c41224c1e7238be58b87d7e/pydantic_core-2.33.2-cp312-cp312-win_amd64.whl", hash = "sha256:f941635f2a3d96b2973e867144fde513665c87f13fe0e193c158ac51bfaaa7b2", size = 1955866, upload-time = "2025-04-23T18:31:49.635Z" }, - { url = "https://files.pythonhosted.org/packages/0d/24/8b11e8b3e2be9dd82df4b11408a67c61bb4dc4f8e11b5b0fc888b38118b5/pydantic_core-2.33.2-cp312-cp312-win_arm64.whl", hash = "sha256:cca3868ddfaccfbc4bfb1d608e2ccaaebe0ae628e1416aeb9c4d88c001bb45ab", size = 1888894, upload-time = "2025-04-23T18:31:51.609Z" }, - { url = "https://files.pythonhosted.org/packages/46/8c/99040727b41f56616573a28771b1bfa08a3d3fe74d3d513f01251f79f172/pydantic_core-2.33.2-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:1082dd3e2d7109ad8b7da48e1d4710c8d06c253cbc4a27c1cff4fbcaa97a9e3f", size = 2015688, upload-time = "2025-04-23T18:31:53.175Z" }, - { url = "https://files.pythonhosted.org/packages/3a/cc/5999d1eb705a6cefc31f0b4a90e9f7fc400539b1a1030529700cc1b51838/pydantic_core-2.33.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:f517ca031dfc037a9c07e748cefd8d96235088b83b4f4ba8939105d20fa1dcd6", size = 1844808, upload-time = "2025-04-23T18:31:54.79Z" }, - { url = "https://files.pythonhosted.org/packages/6f/5e/a0a7b8885c98889a18b6e376f344da1ef323d270b44edf8174d6bce4d622/pydantic_core-2.33.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0a9f2c9dd19656823cb8250b0724ee9c60a82f3cdf68a080979d13092a3b0fef", size = 1885580, upload-time = "2025-04-23T18:31:57.393Z" }, - { url = "https://files.pythonhosted.org/packages/3b/2a/953581f343c7d11a304581156618c3f592435523dd9d79865903272c256a/pydantic_core-2.33.2-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:2b0a451c263b01acebe51895bfb0e1cc842a5c666efe06cdf13846c7418caa9a", size = 1973859, upload-time = "2025-04-23T18:31:59.065Z" }, - { url = "https://files.pythonhosted.org/packages/e6/55/f1a813904771c03a3f97f676c62cca0c0a4138654107c1b61f19c644868b/pydantic_core-2.33.2-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1ea40a64d23faa25e62a70ad163571c0b342b8bf66d5fa612ac0dec4f069d916", size = 2120810, upload-time = "2025-04-23T18:32:00.78Z" }, - { url = "https://files.pythonhosted.org/packages/aa/c3/053389835a996e18853ba107a63caae0b9deb4a276c6b472931ea9ae6e48/pydantic_core-2.33.2-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0fb2d542b4d66f9470e8065c5469ec676978d625a8b7a363f07d9a501a9cb36a", size = 2676498, upload-time = "2025-04-23T18:32:02.418Z" }, - { url = "https://files.pythonhosted.org/packages/eb/3c/f4abd740877a35abade05e437245b192f9d0ffb48bbbbd708df33d3cda37/pydantic_core-2.33.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fdac5d6ffa1b5a83bca06ffe7583f5576555e6c8b3a91fbd25ea7780f825f7d", size = 2000611, upload-time = "2025-04-23T18:32:04.152Z" }, - { url = "https://files.pythonhosted.org/packages/59/a7/63ef2fed1837d1121a894d0ce88439fe3e3b3e48c7543b2a4479eb99c2bd/pydantic_core-2.33.2-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:04a1a413977ab517154eebb2d326da71638271477d6ad87a769102f7c2488c56", size = 2107924, upload-time = "2025-04-23T18:32:06.129Z" }, - { url = "https://files.pythonhosted.org/packages/04/8f/2551964ef045669801675f1cfc3b0d74147f4901c3ffa42be2ddb1f0efc4/pydantic_core-2.33.2-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:c8e7af2f4e0194c22b5b37205bfb293d166a7344a5b0d0eaccebc376546d77d5", size = 2063196, upload-time = "2025-04-23T18:32:08.178Z" }, - { url = "https://files.pythonhosted.org/packages/26/bd/d9602777e77fc6dbb0c7db9ad356e9a985825547dce5ad1d30ee04903918/pydantic_core-2.33.2-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:5c92edd15cd58b3c2d34873597a1e20f13094f59cf88068adb18947df5455b4e", size = 2236389, upload-time = "2025-04-23T18:32:10.242Z" }, - { url = "https://files.pythonhosted.org/packages/42/db/0e950daa7e2230423ab342ae918a794964b053bec24ba8af013fc7c94846/pydantic_core-2.33.2-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:65132b7b4a1c0beded5e057324b7e16e10910c106d43675d9bd87d4f38dde162", size = 2239223, upload-time = "2025-04-23T18:32:12.382Z" }, - { url = "https://files.pythonhosted.org/packages/58/4d/4f937099c545a8a17eb52cb67fe0447fd9a373b348ccfa9a87f141eeb00f/pydantic_core-2.33.2-cp313-cp313-win32.whl", hash = "sha256:52fb90784e0a242bb96ec53f42196a17278855b0f31ac7c3cc6f5c1ec4811849", size = 1900473, upload-time = "2025-04-23T18:32:14.034Z" }, - { url = "https://files.pythonhosted.org/packages/a0/75/4a0a9bac998d78d889def5e4ef2b065acba8cae8c93696906c3a91f310ca/pydantic_core-2.33.2-cp313-cp313-win_amd64.whl", hash = "sha256:c083a3bdd5a93dfe480f1125926afcdbf2917ae714bdb80b36d34318b2bec5d9", size = 1955269, upload-time = "2025-04-23T18:32:15.783Z" }, - { url = "https://files.pythonhosted.org/packages/f9/86/1beda0576969592f1497b4ce8e7bc8cbdf614c352426271b1b10d5f0aa64/pydantic_core-2.33.2-cp313-cp313-win_arm64.whl", hash = "sha256:e80b087132752f6b3d714f041ccf74403799d3b23a72722ea2e6ba2e892555b9", size = 1893921, upload-time = "2025-04-23T18:32:18.473Z" }, - { url = "https://files.pythonhosted.org/packages/a4/7d/e09391c2eebeab681df2b74bfe6c43422fffede8dc74187b2b0bf6fd7571/pydantic_core-2.33.2-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:61c18fba8e5e9db3ab908620af374db0ac1baa69f0f32df4f61ae23f15e586ac", size = 1806162, upload-time = "2025-04-23T18:32:20.188Z" }, - { url = "https://files.pythonhosted.org/packages/f1/3d/847b6b1fed9f8ed3bb95a9ad04fbd0b212e832d4f0f50ff4d9ee5a9f15cf/pydantic_core-2.33.2-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:95237e53bb015f67b63c91af7518a62a8660376a6a0db19b89acc77a4d6199f5", size = 1981560, upload-time = "2025-04-23T18:32:22.354Z" }, - { url = "https://files.pythonhosted.org/packages/6f/9a/e73262f6c6656262b5fdd723ad90f518f579b7bc8622e43a942eec53c938/pydantic_core-2.33.2-cp313-cp313t-win_amd64.whl", hash = "sha256:c2fc0a768ef76c15ab9238afa6da7f69895bb5d1ee83aeea2e3509af4472d0b9", size = 1935777, upload-time = "2025-04-23T18:32:25.088Z" }, - { url = "https://files.pythonhosted.org/packages/30/68/373d55e58b7e83ce371691f6eaa7175e3a24b956c44628eb25d7da007917/pydantic_core-2.33.2-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:5c4aa4e82353f65e548c476b37e64189783aa5384903bfea4f41580f255fddfa", size = 2023982, upload-time = "2025-04-23T18:32:53.14Z" }, - { url = "https://files.pythonhosted.org/packages/a4/16/145f54ac08c96a63d8ed6442f9dec17b2773d19920b627b18d4f10a061ea/pydantic_core-2.33.2-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:d946c8bf0d5c24bf4fe333af284c59a19358aa3ec18cb3dc4370080da1e8ad29", size = 1858412, upload-time = "2025-04-23T18:32:55.52Z" }, - { url = "https://files.pythonhosted.org/packages/41/b1/c6dc6c3e2de4516c0bb2c46f6a373b91b5660312342a0cf5826e38ad82fa/pydantic_core-2.33.2-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:87b31b6846e361ef83fedb187bb5b4372d0da3f7e28d85415efa92d6125d6e6d", size = 1892749, upload-time = "2025-04-23T18:32:57.546Z" }, - { url = "https://files.pythonhosted.org/packages/12/73/8cd57e20afba760b21b742106f9dbdfa6697f1570b189c7457a1af4cd8a0/pydantic_core-2.33.2-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aa9d91b338f2df0508606f7009fde642391425189bba6d8c653afd80fd6bb64e", size = 2067527, upload-time = "2025-04-23T18:32:59.771Z" }, - { url = "https://files.pythonhosted.org/packages/e3/d5/0bb5d988cc019b3cba4a78f2d4b3854427fc47ee8ec8e9eaabf787da239c/pydantic_core-2.33.2-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2058a32994f1fde4ca0480ab9d1e75a0e8c87c22b53a3ae66554f9af78f2fe8c", size = 2108225, upload-time = "2025-04-23T18:33:04.51Z" }, - { url = "https://files.pythonhosted.org/packages/f1/c5/00c02d1571913d496aabf146106ad8239dc132485ee22efe08085084ff7c/pydantic_core-2.33.2-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:0e03262ab796d986f978f79c943fc5f620381be7287148b8010b4097f79a39ec", size = 2069490, upload-time = "2025-04-23T18:33:06.391Z" }, - { url = "https://files.pythonhosted.org/packages/22/a8/dccc38768274d3ed3a59b5d06f59ccb845778687652daa71df0cab4040d7/pydantic_core-2.33.2-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:1a8695a8d00c73e50bff9dfda4d540b7dee29ff9b8053e38380426a85ef10052", size = 2237525, upload-time = "2025-04-23T18:33:08.44Z" }, - { url = "https://files.pythonhosted.org/packages/d4/e7/4f98c0b125dda7cf7ccd14ba936218397b44f50a56dd8c16a3091df116c3/pydantic_core-2.33.2-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:fa754d1850735a0b0e03bcffd9d4b4343eb417e47196e4485d9cca326073a42c", size = 2238446, upload-time = "2025-04-23T18:33:10.313Z" }, - { url = "https://files.pythonhosted.org/packages/ce/91/2ec36480fdb0b783cd9ef6795753c1dea13882f2e68e73bce76ae8c21e6a/pydantic_core-2.33.2-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:a11c8d26a50bfab49002947d3d237abe4d9e4b5bdc8846a63537b6488e197808", size = 2066678, upload-time = "2025-04-23T18:33:12.224Z" }, - { url = "https://files.pythonhosted.org/packages/7b/27/d4ae6487d73948d6f20dddcd94be4ea43e74349b56eba82e9bdee2d7494c/pydantic_core-2.33.2-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:dd14041875d09cc0f9308e37a6f8b65f5585cf2598a53aa0123df8b129d481f8", size = 2025200, upload-time = "2025-04-23T18:33:14.199Z" }, - { url = "https://files.pythonhosted.org/packages/f1/b8/b3cb95375f05d33801024079b9392a5ab45267a63400bf1866e7ce0f0de4/pydantic_core-2.33.2-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:d87c561733f66531dced0da6e864f44ebf89a8fba55f31407b00c2f7f9449593", size = 1859123, upload-time = "2025-04-23T18:33:16.555Z" }, - { url = "https://files.pythonhosted.org/packages/05/bc/0d0b5adeda59a261cd30a1235a445bf55c7e46ae44aea28f7bd6ed46e091/pydantic_core-2.33.2-pp311-pypy311_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2f82865531efd18d6e07a04a17331af02cb7a651583c418df8266f17a63c6612", size = 1892852, upload-time = "2025-04-23T18:33:18.513Z" }, - { url = "https://files.pythonhosted.org/packages/3e/11/d37bdebbda2e449cb3f519f6ce950927b56d62f0b84fd9cb9e372a26a3d5/pydantic_core-2.33.2-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2bfb5112df54209d820d7bf9317c7a6c9025ea52e49f46b6a2060104bba37de7", size = 2067484, upload-time = "2025-04-23T18:33:20.475Z" }, - { url = "https://files.pythonhosted.org/packages/8c/55/1f95f0a05ce72ecb02a8a8a1c3be0579bbc29b1d5ab68f1378b7bebc5057/pydantic_core-2.33.2-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:64632ff9d614e5eecfb495796ad51b0ed98c453e447a76bcbeeb69615079fc7e", size = 2108896, upload-time = "2025-04-23T18:33:22.501Z" }, - { url = "https://files.pythonhosted.org/packages/53/89/2b2de6c81fa131f423246a9109d7b2a375e83968ad0800d6e57d0574629b/pydantic_core-2.33.2-pp311-pypy311_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:f889f7a40498cc077332c7ab6b4608d296d852182211787d4f3ee377aaae66e8", size = 2069475, upload-time = "2025-04-23T18:33:24.528Z" }, - { url = "https://files.pythonhosted.org/packages/b8/e9/1f7efbe20d0b2b10f6718944b5d8ece9152390904f29a78e68d4e7961159/pydantic_core-2.33.2-pp311-pypy311_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:de4b83bb311557e439b9e186f733f6c645b9417c84e2eb8203f3f820a4b988bf", size = 2239013, upload-time = "2025-04-23T18:33:26.621Z" }, - { url = "https://files.pythonhosted.org/packages/3c/b2/5309c905a93811524a49b4e031e9851a6b00ff0fb668794472ea7746b448/pydantic_core-2.33.2-pp311-pypy311_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:82f68293f055f51b51ea42fafc74b6aad03e70e191799430b90c13d643059ebb", size = 2238715, upload-time = "2025-04-23T18:33:28.656Z" }, - { url = "https://files.pythonhosted.org/packages/32/56/8a7ca5d2cd2cda1d245d34b1c9a942920a718082ae8e54e5f3e5a58b7add/pydantic_core-2.33.2-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:329467cecfb529c925cf2bbd4d60d2c509bc2fb52a20c1045bf09bb70971a9c1", size = 2066757, upload-time = "2025-04-23T18:33:30.645Z" }, -] - -[[package]] -name = "pyflakes" -version = "3.4.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/45/dc/fd034dc20b4b264b3d015808458391acbf9df40b1e54750ef175d39180b1/pyflakes-3.4.0.tar.gz", hash = "sha256:b24f96fafb7d2ab0ec5075b7350b3d2d2218eab42003821c06344973d3ea2f58", size = 64669, upload-time = "2025-06-20T18:45:27.834Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/c2/2f/81d580a0fb83baeb066698975cb14a618bdbed7720678566f1b046a95fe8/pyflakes-3.4.0-py2.py3-none-any.whl", hash = "sha256:f742a7dbd0d9cb9ea41e9a24a918996e8170c799fa528688d40dd582c8265f4f", size = 63551, upload-time = "2025-06-20T18:45:26.937Z" }, -] - -[[package]] -name = "pygments" -version = "2.19.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/b0/77/a5b8c569bf593b0140bde72ea885a803b82086995367bf2037de0159d924/pygments-2.19.2.tar.gz", hash = "sha256:636cb2477cec7f8952536970bc533bc43743542f70392ae026374600add5b887", size = 4968631, upload-time = "2025-06-21T13:39:12.283Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl", hash = "sha256:86540386c03d588bb81d44bc3928634ff26449851e99741617ecb9037ee5ec0b", size = 1225217, upload-time = "2025-06-21T13:39:07.939Z" }, -] - -[[package]] -name = "pyproject-hooks" -version = "1.2.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/e7/82/28175b2414effca1cdac8dc99f76d660e7a4fb0ceefa4b4ab8f5f6742925/pyproject_hooks-1.2.0.tar.gz", hash = "sha256:1e859bd5c40fae9448642dd871adf459e5e2084186e8d2c2a79a824c970da1f8", size = 19228, upload-time = "2024-09-29T09:24:13.293Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/bd/24/12818598c362d7f300f18e74db45963dbcb85150324092410c8b49405e42/pyproject_hooks-1.2.0-py3-none-any.whl", hash = "sha256:9e5c6bfa8dcc30091c74b0cf803c81fdd29d94f01992a7707bc97babb1141913", size = 10216, upload-time = "2024-09-29T09:24:11.978Z" }, -] - -[[package]] -name = "pytest" -version = "8.4.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "colorama", marker = "sys_platform == 'win32'" }, - { name = "exceptiongroup", marker = "python_full_version < '3.11'" }, - { name = "iniconfig" }, - { name = "packaging" }, - { name = "pluggy" }, - { name = "pygments" }, - { name = "tomli", marker = "python_full_version < '3.11'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/a3/5c/00a0e072241553e1a7496d638deababa67c5058571567b92a7eaa258397c/pytest-8.4.2.tar.gz", hash = "sha256:86c0d0b93306b961d58d62a4db4879f27fe25513d4b969df351abdddb3c30e01", size = 1519618, upload-time = "2025-09-04T14:34:22.711Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a8/a4/20da314d277121d6534b3a980b29035dcd51e6744bd79075a6ce8fa4eb8d/pytest-8.4.2-py3-none-any.whl", hash = "sha256:872f880de3fc3a5bdc88a11b39c9710c3497a547cfa9320bc3c5e62fbf272e79", size = 365750, upload-time = "2025-09-04T14:34:20.226Z" }, -] - -[[package]] -name = "pytest-asyncio" -version = "1.2.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "backports-asyncio-runner", marker = "python_full_version < '3.11'" }, - { name = "pytest" }, - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/42/86/9e3c5f48f7b7b638b216e4b9e645f54d199d7abbbab7a64a13b4e12ba10f/pytest_asyncio-1.2.0.tar.gz", hash = "sha256:c609a64a2a8768462d0c99811ddb8bd2583c33fd33cf7f21af1c142e824ffb57", size = 50119, upload-time = "2025-09-12T07:33:53.816Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/04/93/2fa34714b7a4ae72f2f8dad66ba17dd9a2c793220719e736dda28b7aec27/pytest_asyncio-1.2.0-py3-none-any.whl", hash = "sha256:8e17ae5e46d8e7efe51ab6494dd2010f4ca8dae51652aa3c8d55acf50bfb2e99", size = 15095, upload-time = "2025-09-12T07:33:52.639Z" }, -] - -[[package]] -name = "pytest-vcr" -version = "1.0.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "pytest" }, - { name = "vcrpy" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/1a/60/104c619483c1a42775d3f8b27293f1ecfc0728014874d065e68cb9702d49/pytest-vcr-1.0.2.tar.gz", hash = "sha256:23ee51b75abbcc43d926272773aae4f39f93aceb75ed56852d0bf618f92e1896", size = 3810, upload-time = "2019-04-26T19:04:00.806Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/9d/d3/ff520d11e6ee400602711d1ece8168dcfc5b6d8146fb7db4244a6ad6a9c3/pytest_vcr-1.0.2-py2.py3-none-any.whl", hash = "sha256:2f316e0539399bea0296e8b8401145c62b6f85e9066af7e57b6151481b0d6d9c", size = 4137, upload-time = "2019-04-26T19:03:57.034Z" }, -] - -[[package]] -name = "python-dotenv" -version = "1.1.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f6/b0/4bc07ccd3572a2f9df7e6782f52b0c6c90dcbb803ac4a167702d7d0dfe1e/python_dotenv-1.1.1.tar.gz", hash = "sha256:a8a6399716257f45be6a007360200409fce5cda2661e3dec71d23dc15f6189ab", size = 41978, upload-time = "2025-06-24T04:21:07.341Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/5f/ed/539768cf28c661b5b068d66d96a2f155c4971a5d55684a514c1a0e0dec2f/python_dotenv-1.1.1-py3-none-any.whl", hash = "sha256:31f23644fe2602f88ff55e1f5c79ba497e01224ee7737937930c448e4d0e24dc", size = 20556, upload-time = "2025-06-24T04:21:06.073Z" }, -] - -[[package]] -name = "python-slugify" -version = "8.0.4" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "text-unidecode" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/87/c7/5e1547c44e31da50a460df93af11a535ace568ef89d7a811069ead340c4a/python-slugify-8.0.4.tar.gz", hash = "sha256:59202371d1d05b54a9e7720c5e038f928f45daaffe41dd10822f3907b937c856", size = 10921, upload-time = "2024-02-08T18:32:45.488Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a4/62/02da182e544a51a5c3ccf4b03ab79df279f9c60c5e82d5e8bec7ca26ac11/python_slugify-8.0.4-py2.py3-none-any.whl", hash = "sha256:276540b79961052b66b7d116620b36518847f52d5fd9e3a70164fc8c50faa6b8", size = 10051, upload-time = "2024-02-08T18:32:43.911Z" }, -] - -[[package]] -name = "pytokens" -version = "0.1.10" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/30/5f/e959a442435e24f6fb5a01aec6c657079ceaca1b3baf18561c3728d681da/pytokens-0.1.10.tar.gz", hash = "sha256:c9a4bfa0be1d26aebce03e6884ba454e842f186a59ea43a6d3b25af58223c044", size = 12171, upload-time = "2025-02-19T14:51:22.001Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/60/e5/63bed382f6a7a5ba70e7e132b8b7b8abbcf4888ffa6be4877698dcfbed7d/pytokens-0.1.10-py3-none-any.whl", hash = "sha256:db7b72284e480e69fb085d9f251f66b3d2df8b7166059261258ff35f50fb711b", size = 12046, upload-time = "2025-02-19T14:51:18.694Z" }, -] - -[[package]] -name = "pywin32-ctypes" -version = "0.2.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/85/9f/01a1a99704853cb63f253eea009390c88e7131c67e66a0a02099a8c917cb/pywin32-ctypes-0.2.3.tar.gz", hash = "sha256:d162dc04946d704503b2edc4d55f3dba5c1d539ead017afa00142c38b9885755", size = 29471, upload-time = "2024-08-14T10:15:34.626Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/de/3d/8161f7711c017e01ac9f008dfddd9410dff3674334c233bde66e7ba65bbf/pywin32_ctypes-0.2.3-py3-none-any.whl", hash = "sha256:8a1513379d709975552d202d942d9837758905c8d01eb82b8bcc30918929e7b8", size = 30756, upload-time = "2024-08-14T10:15:33.187Z" }, -] - -[[package]] -name = "pyyaml" -version = "6.0.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/54/ed/79a089b6be93607fa5cdaedf301d7dfb23af5f25c398d5ead2525b063e17/pyyaml-6.0.2.tar.gz", hash = "sha256:d584d9ec91ad65861cc08d42e834324ef890a082e591037abe114850ff7bbc3e", size = 130631, upload-time = "2024-08-06T20:33:50.674Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/9b/95/a3fac87cb7158e231b5a6012e438c647e1a87f09f8e0d123acec8ab8bf71/PyYAML-6.0.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0a9a2848a5b7feac301353437eb7d5957887edbf81d56e903999a75a3d743086", size = 184199, upload-time = "2024-08-06T20:31:40.178Z" }, - { url = "https://files.pythonhosted.org/packages/c7/7a/68bd47624dab8fd4afbfd3c48e3b79efe09098ae941de5b58abcbadff5cb/PyYAML-6.0.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:29717114e51c84ddfba879543fb232a6ed60086602313ca38cce623c1d62cfbf", size = 171758, upload-time = "2024-08-06T20:31:42.173Z" }, - { url = "https://files.pythonhosted.org/packages/49/ee/14c54df452143b9ee9f0f29074d7ca5516a36edb0b4cc40c3f280131656f/PyYAML-6.0.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8824b5a04a04a047e72eea5cec3bc266db09e35de6bdfe34c9436ac5ee27d237", size = 718463, upload-time = "2024-08-06T20:31:44.263Z" }, - { url = "https://files.pythonhosted.org/packages/4d/61/de363a97476e766574650d742205be468921a7b532aa2499fcd886b62530/PyYAML-6.0.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7c36280e6fb8385e520936c3cb3b8042851904eba0e58d277dca80a5cfed590b", size = 719280, upload-time = "2024-08-06T20:31:50.199Z" }, - { url = "https://files.pythonhosted.org/packages/6b/4e/1523cb902fd98355e2e9ea5e5eb237cbc5f3ad5f3075fa65087aa0ecb669/PyYAML-6.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ec031d5d2feb36d1d1a24380e4db6d43695f3748343d99434e6f5f9156aaa2ed", size = 751239, upload-time = "2024-08-06T20:31:52.292Z" }, - { url = "https://files.pythonhosted.org/packages/b7/33/5504b3a9a4464893c32f118a9cc045190a91637b119a9c881da1cf6b7a72/PyYAML-6.0.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:936d68689298c36b53b29f23c6dbb74de12b4ac12ca6cfe0e047bedceea56180", size = 695802, upload-time = "2024-08-06T20:31:53.836Z" }, - { url = "https://files.pythonhosted.org/packages/5c/20/8347dcabd41ef3a3cdc4f7b7a2aff3d06598c8779faa189cdbf878b626a4/PyYAML-6.0.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:23502f431948090f597378482b4812b0caae32c22213aecf3b55325e049a6c68", size = 720527, upload-time = "2024-08-06T20:31:55.565Z" }, - { url = "https://files.pythonhosted.org/packages/be/aa/5afe99233fb360d0ff37377145a949ae258aaab831bde4792b32650a4378/PyYAML-6.0.2-cp310-cp310-win32.whl", hash = "sha256:2e99c6826ffa974fe6e27cdb5ed0021786b03fc98e5ee3c5bfe1fd5015f42b99", size = 144052, upload-time = "2024-08-06T20:31:56.914Z" }, - { url = "https://files.pythonhosted.org/packages/b5/84/0fa4b06f6d6c958d207620fc60005e241ecedceee58931bb20138e1e5776/PyYAML-6.0.2-cp310-cp310-win_amd64.whl", hash = "sha256:a4d3091415f010369ae4ed1fc6b79def9416358877534caf6a0fdd2146c87a3e", size = 161774, upload-time = "2024-08-06T20:31:58.304Z" }, - { url = "https://files.pythonhosted.org/packages/f8/aa/7af4e81f7acba21a4c6be026da38fd2b872ca46226673c89a758ebdc4fd2/PyYAML-6.0.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:cc1c1159b3d456576af7a3e4d1ba7e6924cb39de8f67111c735f6fc832082774", size = 184612, upload-time = "2024-08-06T20:32:03.408Z" }, - { url = "https://files.pythonhosted.org/packages/8b/62/b9faa998fd185f65c1371643678e4d58254add437edb764a08c5a98fb986/PyYAML-6.0.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1e2120ef853f59c7419231f3bf4e7021f1b936f6ebd222406c3b60212205d2ee", size = 172040, upload-time = "2024-08-06T20:32:04.926Z" }, - { url = "https://files.pythonhosted.org/packages/ad/0c/c804f5f922a9a6563bab712d8dcc70251e8af811fce4524d57c2c0fd49a4/PyYAML-6.0.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5d225db5a45f21e78dd9358e58a98702a0302f2659a3c6cd320564b75b86f47c", size = 736829, upload-time = "2024-08-06T20:32:06.459Z" }, - { url = "https://files.pythonhosted.org/packages/51/16/6af8d6a6b210c8e54f1406a6b9481febf9c64a3109c541567e35a49aa2e7/PyYAML-6.0.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ac9328ec4831237bec75defaf839f7d4564be1e6b25ac710bd1a96321cc8317", size = 764167, upload-time = "2024-08-06T20:32:08.338Z" }, - { url = "https://files.pythonhosted.org/packages/75/e4/2c27590dfc9992f73aabbeb9241ae20220bd9452df27483b6e56d3975cc5/PyYAML-6.0.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3ad2a3decf9aaba3d29c8f537ac4b243e36bef957511b4766cb0057d32b0be85", size = 762952, upload-time = "2024-08-06T20:32:14.124Z" }, - { url = "https://files.pythonhosted.org/packages/9b/97/ecc1abf4a823f5ac61941a9c00fe501b02ac3ab0e373c3857f7d4b83e2b6/PyYAML-6.0.2-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:ff3824dc5261f50c9b0dfb3be22b4567a6f938ccce4587b38952d85fd9e9afe4", size = 735301, upload-time = "2024-08-06T20:32:16.17Z" }, - { url = "https://files.pythonhosted.org/packages/45/73/0f49dacd6e82c9430e46f4a027baa4ca205e8b0a9dce1397f44edc23559d/PyYAML-6.0.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:797b4f722ffa07cc8d62053e4cff1486fa6dc094105d13fea7b1de7d8bf71c9e", size = 756638, upload-time = "2024-08-06T20:32:18.555Z" }, - { url = "https://files.pythonhosted.org/packages/22/5f/956f0f9fc65223a58fbc14459bf34b4cc48dec52e00535c79b8db361aabd/PyYAML-6.0.2-cp311-cp311-win32.whl", hash = "sha256:11d8f3dd2b9c1207dcaf2ee0bbbfd5991f571186ec9cc78427ba5bd32afae4b5", size = 143850, upload-time = "2024-08-06T20:32:19.889Z" }, - { url = "https://files.pythonhosted.org/packages/ed/23/8da0bbe2ab9dcdd11f4f4557ccaf95c10b9811b13ecced089d43ce59c3c8/PyYAML-6.0.2-cp311-cp311-win_amd64.whl", hash = "sha256:e10ce637b18caea04431ce14fabcf5c64a1c61ec9c56b071a4b7ca131ca52d44", size = 161980, upload-time = "2024-08-06T20:32:21.273Z" }, - { url = "https://files.pythonhosted.org/packages/86/0c/c581167fc46d6d6d7ddcfb8c843a4de25bdd27e4466938109ca68492292c/PyYAML-6.0.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:c70c95198c015b85feafc136515252a261a84561b7b1d51e3384e0655ddf25ab", size = 183873, upload-time = "2024-08-06T20:32:25.131Z" }, - { url = "https://files.pythonhosted.org/packages/a8/0c/38374f5bb272c051e2a69281d71cba6fdb983413e6758b84482905e29a5d/PyYAML-6.0.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:ce826d6ef20b1bc864f0a68340c8b3287705cae2f8b4b1d932177dcc76721725", size = 173302, upload-time = "2024-08-06T20:32:26.511Z" }, - { url = "https://files.pythonhosted.org/packages/c3/93/9916574aa8c00aa06bbac729972eb1071d002b8e158bd0e83a3b9a20a1f7/PyYAML-6.0.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1f71ea527786de97d1a0cc0eacd1defc0985dcf6b3f17bb77dcfc8c34bec4dc5", size = 739154, upload-time = "2024-08-06T20:32:28.363Z" }, - { url = "https://files.pythonhosted.org/packages/95/0f/b8938f1cbd09739c6da569d172531567dbcc9789e0029aa070856f123984/PyYAML-6.0.2-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9b22676e8097e9e22e36d6b7bda33190d0d400f345f23d4065d48f4ca7ae0425", size = 766223, upload-time = "2024-08-06T20:32:30.058Z" }, - { url = "https://files.pythonhosted.org/packages/b9/2b/614b4752f2e127db5cc206abc23a8c19678e92b23c3db30fc86ab731d3bd/PyYAML-6.0.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:80bab7bfc629882493af4aa31a4cfa43a4c57c83813253626916b8c7ada83476", size = 767542, upload-time = "2024-08-06T20:32:31.881Z" }, - { url = "https://files.pythonhosted.org/packages/d4/00/dd137d5bcc7efea1836d6264f049359861cf548469d18da90cd8216cf05f/PyYAML-6.0.2-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:0833f8694549e586547b576dcfaba4a6b55b9e96098b36cdc7ebefe667dfed48", size = 731164, upload-time = "2024-08-06T20:32:37.083Z" }, - { url = "https://files.pythonhosted.org/packages/c9/1f/4f998c900485e5c0ef43838363ba4a9723ac0ad73a9dc42068b12aaba4e4/PyYAML-6.0.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8b9c7197f7cb2738065c481a0461e50ad02f18c78cd75775628afb4d7137fb3b", size = 756611, upload-time = "2024-08-06T20:32:38.898Z" }, - { url = "https://files.pythonhosted.org/packages/df/d1/f5a275fdb252768b7a11ec63585bc38d0e87c9e05668a139fea92b80634c/PyYAML-6.0.2-cp312-cp312-win32.whl", hash = "sha256:ef6107725bd54b262d6dedcc2af448a266975032bc85ef0172c5f059da6325b4", size = 140591, upload-time = "2024-08-06T20:32:40.241Z" }, - { url = "https://files.pythonhosted.org/packages/0c/e8/4f648c598b17c3d06e8753d7d13d57542b30d56e6c2dedf9c331ae56312e/PyYAML-6.0.2-cp312-cp312-win_amd64.whl", hash = "sha256:7e7401d0de89a9a855c839bc697c079a4af81cf878373abd7dc625847d25cbd8", size = 156338, upload-time = "2024-08-06T20:32:41.93Z" }, - { url = "https://files.pythonhosted.org/packages/ef/e3/3af305b830494fa85d95f6d95ef7fa73f2ee1cc8ef5b495c7c3269fb835f/PyYAML-6.0.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:efdca5630322a10774e8e98e1af481aad470dd62c3170801852d752aa7a783ba", size = 181309, upload-time = "2024-08-06T20:32:43.4Z" }, - { url = "https://files.pythonhosted.org/packages/45/9f/3b1c20a0b7a3200524eb0076cc027a970d320bd3a6592873c85c92a08731/PyYAML-6.0.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:50187695423ffe49e2deacb8cd10510bc361faac997de9efef88badc3bb9e2d1", size = 171679, upload-time = "2024-08-06T20:32:44.801Z" }, - { url = "https://files.pythonhosted.org/packages/7c/9a/337322f27005c33bcb656c655fa78325b730324c78620e8328ae28b64d0c/PyYAML-6.0.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0ffe8360bab4910ef1b9e87fb812d8bc0a308b0d0eef8c8f44e0254ab3b07133", size = 733428, upload-time = "2024-08-06T20:32:46.432Z" }, - { url = "https://files.pythonhosted.org/packages/a3/69/864fbe19e6c18ea3cc196cbe5d392175b4cf3d5d0ac1403ec3f2d237ebb5/PyYAML-6.0.2-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:17e311b6c678207928d649faa7cb0d7b4c26a0ba73d41e99c4fff6b6c3276484", size = 763361, upload-time = "2024-08-06T20:32:51.188Z" }, - { url = "https://files.pythonhosted.org/packages/04/24/b7721e4845c2f162d26f50521b825fb061bc0a5afcf9a386840f23ea19fa/PyYAML-6.0.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:70b189594dbe54f75ab3a1acec5f1e3faa7e8cf2f1e08d9b561cb41b845f69d5", size = 759523, upload-time = "2024-08-06T20:32:53.019Z" }, - { url = "https://files.pythonhosted.org/packages/2b/b2/e3234f59ba06559c6ff63c4e10baea10e5e7df868092bf9ab40e5b9c56b6/PyYAML-6.0.2-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:41e4e3953a79407c794916fa277a82531dd93aad34e29c2a514c2c0c5fe971cc", size = 726660, upload-time = "2024-08-06T20:32:54.708Z" }, - { url = "https://files.pythonhosted.org/packages/fe/0f/25911a9f080464c59fab9027482f822b86bf0608957a5fcc6eaac85aa515/PyYAML-6.0.2-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:68ccc6023a3400877818152ad9a1033e3db8625d899c72eacb5a668902e4d652", size = 751597, upload-time = "2024-08-06T20:32:56.985Z" }, - { url = "https://files.pythonhosted.org/packages/14/0d/e2c3b43bbce3cf6bd97c840b46088a3031085179e596d4929729d8d68270/PyYAML-6.0.2-cp313-cp313-win32.whl", hash = "sha256:bc2fa7c6b47d6bc618dd7fb02ef6fdedb1090ec036abab80d4681424b84c1183", size = 140527, upload-time = "2024-08-06T20:33:03.001Z" }, - { url = "https://files.pythonhosted.org/packages/fa/de/02b54f42487e3d3c6efb3f89428677074ca7bf43aae402517bc7cca949f3/PyYAML-6.0.2-cp313-cp313-win_amd64.whl", hash = "sha256:8388ee1976c416731879ac16da0aff3f63b286ffdd57cdeb95f3f2e085687563", size = 156446, upload-time = "2024-08-06T20:33:04.33Z" }, -] - -[[package]] -name = "readme-renderer" -version = "44.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "docutils" }, - { name = "nh3" }, - { name = "pygments" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/5a/a9/104ec9234c8448c4379768221ea6df01260cd6c2ce13182d4eac531c8342/readme_renderer-44.0.tar.gz", hash = "sha256:8712034eabbfa6805cacf1402b4eeb2a73028f72d1166d6f5cb7f9c047c5d1e1", size = 32056, upload-time = "2024-07-08T15:00:57.805Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e1/67/921ec3024056483db83953ae8e48079ad62b92db7880013ca77632921dd0/readme_renderer-44.0-py3-none-any.whl", hash = "sha256:2fbca89b81a08526aadf1357a8c2ae889ec05fb03f5da67f9769c9a592166151", size = 13310, upload-time = "2024-07-08T15:00:56.577Z" }, -] - -[[package]] -name = "regex" -version = "2025.9.18" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/49/d3/eaa0d28aba6ad1827ad1e716d9a93e1ba963ada61887498297d3da715133/regex-2025.9.18.tar.gz", hash = "sha256:c5ba23274c61c6fef447ba6a39333297d0c247f53059dba0bca415cac511edc4", size = 400917, upload-time = "2025-09-19T00:38:35.79Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7e/d8/7e06171db8e55f917c5b8e89319cea2d86982e3fc46b677f40358223dece/regex-2025.9.18-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:12296202480c201c98a84aecc4d210592b2f55e200a1d193235c4db92b9f6788", size = 484829, upload-time = "2025-09-19T00:35:05.215Z" }, - { url = "https://files.pythonhosted.org/packages/8d/70/bf91bb39e5bedf75ce730ffbaa82ca585584d13335306d637458946b8b9f/regex-2025.9.18-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:220381f1464a581f2ea988f2220cf2a67927adcef107d47d6897ba5a2f6d51a4", size = 288993, upload-time = "2025-09-19T00:35:08.154Z" }, - { url = "https://files.pythonhosted.org/packages/fe/89/69f79b28365eda2c46e64c39d617d5f65a2aa451a4c94de7d9b34c2dc80f/regex-2025.9.18-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:87f681bfca84ebd265278b5daa1dcb57f4db315da3b5d044add7c30c10442e61", size = 286624, upload-time = "2025-09-19T00:35:09.717Z" }, - { url = "https://files.pythonhosted.org/packages/44/31/81e62955726c3a14fcc1049a80bc716765af6c055706869de5e880ddc783/regex-2025.9.18-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:34d674cbba70c9398074c8a1fcc1a79739d65d1105de2a3c695e2b05ea728251", size = 780473, upload-time = "2025-09-19T00:35:11.013Z" }, - { url = "https://files.pythonhosted.org/packages/fb/23/07072b7e191fbb6e213dc03b2f5b96f06d3c12d7deaded84679482926fc7/regex-2025.9.18-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:385c9b769655cb65ea40b6eea6ff763cbb6d69b3ffef0b0db8208e1833d4e746", size = 849290, upload-time = "2025-09-19T00:35:12.348Z" }, - { url = "https://files.pythonhosted.org/packages/b3/f0/aec7f6a01f2a112210424d77c6401b9015675fb887ced7e18926df4ae51e/regex-2025.9.18-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:8900b3208e022570ae34328712bef6696de0804c122933414014bae791437ab2", size = 897335, upload-time = "2025-09-19T00:35:14.058Z" }, - { url = "https://files.pythonhosted.org/packages/cc/90/2e5f9da89d260de7d0417ead91a1bc897f19f0af05f4f9323313b76c47f2/regex-2025.9.18-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c204e93bf32cd7a77151d44b05eb36f469d0898e3fba141c026a26b79d9914a0", size = 789946, upload-time = "2025-09-19T00:35:15.403Z" }, - { url = "https://files.pythonhosted.org/packages/2b/d5/1c712c7362f2563d389be66bae131c8bab121a3fabfa04b0b5bfc9e73c51/regex-2025.9.18-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:3acc471d1dd7e5ff82e6cacb3b286750decd949ecd4ae258696d04f019817ef8", size = 780787, upload-time = "2025-09-19T00:35:17.061Z" }, - { url = "https://files.pythonhosted.org/packages/4f/92/c54cdb4aa41009632e69817a5aa452673507f07e341076735a2f6c46a37c/regex-2025.9.18-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:6479d5555122433728760e5f29edb4c2b79655a8deb681a141beb5c8a025baea", size = 773632, upload-time = "2025-09-19T00:35:18.57Z" }, - { url = "https://files.pythonhosted.org/packages/db/99/75c996dc6a2231a8652d7ad0bfbeaf8a8c77612d335580f520f3ec40e30b/regex-2025.9.18-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:431bd2a8726b000eb6f12429c9b438a24062a535d06783a93d2bcbad3698f8a8", size = 844104, upload-time = "2025-09-19T00:35:20.259Z" }, - { url = "https://files.pythonhosted.org/packages/1c/f7/25aba34cc130cb6844047dbfe9716c9b8f9629fee8b8bec331aa9241b97b/regex-2025.9.18-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:0cc3521060162d02bd36927e20690129200e5ac9d2c6d32b70368870b122db25", size = 834794, upload-time = "2025-09-19T00:35:22.002Z" }, - { url = "https://files.pythonhosted.org/packages/51/eb/64e671beafa0ae29712268421597596d781704973551312b2425831d4037/regex-2025.9.18-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:a021217b01be2d51632ce056d7a837d3fa37c543ede36e39d14063176a26ae29", size = 778535, upload-time = "2025-09-19T00:35:23.298Z" }, - { url = "https://files.pythonhosted.org/packages/26/33/c0ebc0b07bd0bf88f716cca240546b26235a07710ea58e271cfe390ae273/regex-2025.9.18-cp310-cp310-win32.whl", hash = "sha256:4a12a06c268a629cb67cc1d009b7bb0be43e289d00d5111f86a2efd3b1949444", size = 264115, upload-time = "2025-09-19T00:35:25.206Z" }, - { url = "https://files.pythonhosted.org/packages/59/39/aeb11a4ae68faaec2498512cadae09f2d8a91f1f65730fe62b9bffeea150/regex-2025.9.18-cp310-cp310-win_amd64.whl", hash = "sha256:47acd811589301298c49db2c56bde4f9308d6396da92daf99cba781fa74aa450", size = 276143, upload-time = "2025-09-19T00:35:26.785Z" }, - { url = "https://files.pythonhosted.org/packages/29/04/37f2d3fc334a1031fc2767c9d89cec13c2e72207c7e7f6feae8a47f4e149/regex-2025.9.18-cp310-cp310-win_arm64.whl", hash = "sha256:16bd2944e77522275e5ee36f867e19995bcaa533dcb516753a26726ac7285442", size = 268473, upload-time = "2025-09-19T00:35:28.39Z" }, - { url = "https://files.pythonhosted.org/packages/58/61/80eda662fc4eb32bfedc331f42390974c9e89c7eac1b79cd9eea4d7c458c/regex-2025.9.18-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:51076980cd08cd13c88eb7365427ae27f0d94e7cebe9ceb2bb9ffdae8fc4d82a", size = 484832, upload-time = "2025-09-19T00:35:30.011Z" }, - { url = "https://files.pythonhosted.org/packages/a6/d9/33833d9abddf3f07ad48504ddb53fe3b22f353214bbb878a72eee1e3ddbf/regex-2025.9.18-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:828446870bd7dee4e0cbeed767f07961aa07f0ea3129f38b3ccecebc9742e0b8", size = 288994, upload-time = "2025-09-19T00:35:31.733Z" }, - { url = "https://files.pythonhosted.org/packages/2a/b3/526ee96b0d70ea81980cbc20c3496fa582f775a52e001e2743cc33b2fa75/regex-2025.9.18-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c28821d5637866479ec4cc23b8c990f5bc6dd24e5e4384ba4a11d38a526e1414", size = 286619, upload-time = "2025-09-19T00:35:33.221Z" }, - { url = "https://files.pythonhosted.org/packages/65/4f/c2c096b02a351b33442aed5895cdd8bf87d372498d2100927c5a053d7ba3/regex-2025.9.18-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:726177ade8e481db669e76bf99de0b278783be8acd11cef71165327abd1f170a", size = 792454, upload-time = "2025-09-19T00:35:35.361Z" }, - { url = "https://files.pythonhosted.org/packages/24/15/b562c9d6e47c403c4b5deb744f8b4bf6e40684cf866c7b077960a925bdff/regex-2025.9.18-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:f5cca697da89b9f8ea44115ce3130f6c54c22f541943ac8e9900461edc2b8bd4", size = 858723, upload-time = "2025-09-19T00:35:36.949Z" }, - { url = "https://files.pythonhosted.org/packages/f2/01/dba305409849e85b8a1a681eac4c03ed327d8de37895ddf9dc137f59c140/regex-2025.9.18-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:dfbde38f38004703c35666a1e1c088b778e35d55348da2b7b278914491698d6a", size = 905899, upload-time = "2025-09-19T00:35:38.723Z" }, - { url = "https://files.pythonhosted.org/packages/fe/d0/c51d1e6a80eab11ef96a4cbad17fc0310cf68994fb01a7283276b7e5bbd6/regex-2025.9.18-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:f2f422214a03fab16bfa495cfec72bee4aaa5731843b771860a471282f1bf74f", size = 798981, upload-time = "2025-09-19T00:35:40.416Z" }, - { url = "https://files.pythonhosted.org/packages/c4/5e/72db90970887bbe02296612bd61b0fa31e6d88aa24f6a4853db3e96c575e/regex-2025.9.18-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:a295916890f4df0902e4286bc7223ee7f9e925daa6dcdec4192364255b70561a", size = 781900, upload-time = "2025-09-19T00:35:42.077Z" }, - { url = "https://files.pythonhosted.org/packages/50/ff/596be45eea8e9bc31677fde243fa2904d00aad1b32c31bce26c3dbba0b9e/regex-2025.9.18-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:5db95ff632dbabc8c38c4e82bf545ab78d902e81160e6e455598014f0abe66b9", size = 852952, upload-time = "2025-09-19T00:35:43.751Z" }, - { url = "https://files.pythonhosted.org/packages/e5/1b/2dfa348fa551e900ed3f5f63f74185b6a08e8a76bc62bc9c106f4f92668b/regex-2025.9.18-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:fb967eb441b0f15ae610b7069bdb760b929f267efbf522e814bbbfffdf125ce2", size = 844355, upload-time = "2025-09-19T00:35:45.309Z" }, - { url = "https://files.pythonhosted.org/packages/f4/bf/aefb1def27fe33b8cbbb19c75c13aefccfbef1c6686f8e7f7095705969c7/regex-2025.9.18-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:f04d2f20da4053d96c08f7fde6e1419b7ec9dbcee89c96e3d731fca77f411b95", size = 787254, upload-time = "2025-09-19T00:35:46.904Z" }, - { url = "https://files.pythonhosted.org/packages/e3/4e/8ef042e7cf0dbbb401e784e896acfc1b367b95dfbfc9ada94c2ed55a081f/regex-2025.9.18-cp311-cp311-win32.whl", hash = "sha256:895197241fccf18c0cea7550c80e75f185b8bd55b6924fcae269a1a92c614a07", size = 264129, upload-time = "2025-09-19T00:35:48.597Z" }, - { url = "https://files.pythonhosted.org/packages/b4/7d/c4fcabf80dcdd6821c0578ad9b451f8640b9110fb3dcb74793dd077069ff/regex-2025.9.18-cp311-cp311-win_amd64.whl", hash = "sha256:7e2b414deae99166e22c005e154a5513ac31493db178d8aec92b3269c9cce8c9", size = 276160, upload-time = "2025-09-19T00:36:00.45Z" }, - { url = "https://files.pythonhosted.org/packages/64/f8/0e13c8ae4d6df9d128afaba138342d532283d53a4c1e7a8c93d6756c8f4a/regex-2025.9.18-cp311-cp311-win_arm64.whl", hash = "sha256:fb137ec7c5c54f34a25ff9b31f6b7b0c2757be80176435bf367111e3f71d72df", size = 268471, upload-time = "2025-09-19T00:36:02.149Z" }, - { url = "https://files.pythonhosted.org/packages/b0/99/05859d87a66ae7098222d65748f11ef7f2dff51bfd7482a4e2256c90d72b/regex-2025.9.18-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:436e1b31d7efd4dcd52091d076482031c611dde58bf9c46ca6d0a26e33053a7e", size = 486335, upload-time = "2025-09-19T00:36:03.661Z" }, - { url = "https://files.pythonhosted.org/packages/97/7e/d43d4e8b978890932cf7b0957fce58c5b08c66f32698f695b0c2c24a48bf/regex-2025.9.18-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:c190af81e5576b9c5fdc708f781a52ff20f8b96386c6e2e0557a78402b029f4a", size = 289720, upload-time = "2025-09-19T00:36:05.471Z" }, - { url = "https://files.pythonhosted.org/packages/bb/3b/ff80886089eb5dcf7e0d2040d9aaed539e25a94300403814bb24cc775058/regex-2025.9.18-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:e4121f1ce2b2b5eec4b397cc1b277686e577e658d8f5870b7eb2d726bd2300ab", size = 287257, upload-time = "2025-09-19T00:36:07.072Z" }, - { url = "https://files.pythonhosted.org/packages/ee/66/243edf49dd8720cba8d5245dd4d6adcb03a1defab7238598c0c97cf549b8/regex-2025.9.18-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:300e25dbbf8299d87205e821a201057f2ef9aa3deb29caa01cd2cac669e508d5", size = 797463, upload-time = "2025-09-19T00:36:08.399Z" }, - { url = "https://files.pythonhosted.org/packages/df/71/c9d25a1142c70432e68bb03211d4a82299cd1c1fbc41db9409a394374ef5/regex-2025.9.18-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:7b47fcf9f5316c0bdaf449e879407e1b9937a23c3b369135ca94ebc8d74b1742", size = 862670, upload-time = "2025-09-19T00:36:10.101Z" }, - { url = "https://files.pythonhosted.org/packages/f8/8f/329b1efc3a64375a294e3a92d43372bf1a351aa418e83c21f2f01cf6ec41/regex-2025.9.18-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:57a161bd3acaa4b513220b49949b07e252165e6b6dc910ee7617a37ff4f5b425", size = 910881, upload-time = "2025-09-19T00:36:12.223Z" }, - { url = "https://files.pythonhosted.org/packages/35/9e/a91b50332a9750519320ed30ec378b74c996f6befe282cfa6bb6cea7e9fd/regex-2025.9.18-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4f130c3a7845ba42de42f380fff3c8aebe89a810747d91bcf56d40a069f15352", size = 802011, upload-time = "2025-09-19T00:36:13.901Z" }, - { url = "https://files.pythonhosted.org/packages/a4/1d/6be3b8d7856b6e0d7ee7f942f437d0a76e0d5622983abbb6d21e21ab9a17/regex-2025.9.18-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:5f96fa342b6f54dcba928dd452e8d8cb9f0d63e711d1721cd765bb9f73bb048d", size = 786668, upload-time = "2025-09-19T00:36:15.391Z" }, - { url = "https://files.pythonhosted.org/packages/cb/ce/4a60e53df58bd157c5156a1736d3636f9910bdcc271d067b32b7fcd0c3a8/regex-2025.9.18-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:0f0d676522d68c207828dcd01fb6f214f63f238c283d9f01d85fc664c7c85b56", size = 856578, upload-time = "2025-09-19T00:36:16.845Z" }, - { url = "https://files.pythonhosted.org/packages/86/e8/162c91bfe7217253afccde112868afb239f94703de6580fb235058d506a6/regex-2025.9.18-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:40532bff8a1a0621e7903ae57fce88feb2e8a9a9116d341701302c9302aef06e", size = 849017, upload-time = "2025-09-19T00:36:18.597Z" }, - { url = "https://files.pythonhosted.org/packages/35/34/42b165bc45289646ea0959a1bc7531733e90b47c56a72067adfe6b3251f6/regex-2025.9.18-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:039f11b618ce8d71a1c364fdee37da1012f5a3e79b1b2819a9f389cd82fd6282", size = 788150, upload-time = "2025-09-19T00:36:20.464Z" }, - { url = "https://files.pythonhosted.org/packages/79/5d/cdd13b1f3c53afa7191593a7ad2ee24092a5a46417725ffff7f64be8342d/regex-2025.9.18-cp312-cp312-win32.whl", hash = "sha256:e1dd06f981eb226edf87c55d523131ade7285137fbde837c34dc9d1bf309f459", size = 264536, upload-time = "2025-09-19T00:36:21.922Z" }, - { url = "https://files.pythonhosted.org/packages/e0/f5/4a7770c9a522e7d2dc1fa3ffc83ab2ab33b0b22b447e62cffef186805302/regex-2025.9.18-cp312-cp312-win_amd64.whl", hash = "sha256:3d86b5247bf25fa3715e385aa9ff272c307e0636ce0c9595f64568b41f0a9c77", size = 275501, upload-time = "2025-09-19T00:36:23.4Z" }, - { url = "https://files.pythonhosted.org/packages/df/05/9ce3e110e70d225ecbed455b966003a3afda5e58e8aec2964042363a18f4/regex-2025.9.18-cp312-cp312-win_arm64.whl", hash = "sha256:032720248cbeeae6444c269b78cb15664458b7bb9ed02401d3da59fe4d68c3a5", size = 268601, upload-time = "2025-09-19T00:36:25.092Z" }, - { url = "https://files.pythonhosted.org/packages/d2/c7/5c48206a60ce33711cf7dcaeaed10dd737733a3569dc7e1dce324dd48f30/regex-2025.9.18-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:2a40f929cd907c7e8ac7566ac76225a77701a6221bca937bdb70d56cb61f57b2", size = 485955, upload-time = "2025-09-19T00:36:26.822Z" }, - { url = "https://files.pythonhosted.org/packages/e9/be/74fc6bb19a3c491ec1ace943e622b5a8539068771e8705e469b2da2306a7/regex-2025.9.18-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:c90471671c2cdf914e58b6af62420ea9ecd06d1554d7474d50133ff26ae88feb", size = 289583, upload-time = "2025-09-19T00:36:28.577Z" }, - { url = "https://files.pythonhosted.org/packages/25/c4/9ceaa433cb5dc515765560f22a19578b95b92ff12526e5a259321c4fc1a0/regex-2025.9.18-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:1a351aff9e07a2dabb5022ead6380cff17a4f10e4feb15f9100ee56c4d6d06af", size = 287000, upload-time = "2025-09-19T00:36:30.161Z" }, - { url = "https://files.pythonhosted.org/packages/7d/e6/68bc9393cb4dc68018456568c048ac035854b042bc7c33cb9b99b0680afa/regex-2025.9.18-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:bc4b8e9d16e20ddfe16430c23468a8707ccad3365b06d4536142e71823f3ca29", size = 797535, upload-time = "2025-09-19T00:36:31.876Z" }, - { url = "https://files.pythonhosted.org/packages/6a/1c/ebae9032d34b78ecfe9bd4b5e6575b55351dc8513485bb92326613732b8c/regex-2025.9.18-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:4b8cdbddf2db1c5e80338ba2daa3cfa3dec73a46fff2a7dda087c8efbf12d62f", size = 862603, upload-time = "2025-09-19T00:36:33.344Z" }, - { url = "https://files.pythonhosted.org/packages/3b/74/12332c54b3882557a4bcd2b99f8be581f5c6a43cf1660a85b460dd8ff468/regex-2025.9.18-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:a276937d9d75085b2c91fb48244349c6954f05ee97bba0963ce24a9d915b8b68", size = 910829, upload-time = "2025-09-19T00:36:34.826Z" }, - { url = "https://files.pythonhosted.org/packages/86/70/ba42d5ed606ee275f2465bfc0e2208755b06cdabd0f4c7c4b614d51b57ab/regex-2025.9.18-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:92a8e375ccdc1256401c90e9dc02b8642894443d549ff5e25e36d7cf8a80c783", size = 802059, upload-time = "2025-09-19T00:36:36.664Z" }, - { url = "https://files.pythonhosted.org/packages/da/c5/fcb017e56396a7f2f8357412638d7e2963440b131a3ca549be25774b3641/regex-2025.9.18-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:0dc6893b1f502d73037cf807a321cdc9be29ef3d6219f7970f842475873712ac", size = 786781, upload-time = "2025-09-19T00:36:38.168Z" }, - { url = "https://files.pythonhosted.org/packages/c6/ee/21c4278b973f630adfb3bcb23d09d83625f3ab1ca6e40ebdffe69901c7a1/regex-2025.9.18-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:a61e85bfc63d232ac14b015af1261f826260c8deb19401c0597dbb87a864361e", size = 856578, upload-time = "2025-09-19T00:36:40.129Z" }, - { url = "https://files.pythonhosted.org/packages/87/0b/de51550dc7274324435c8f1539373ac63019b0525ad720132866fff4a16a/regex-2025.9.18-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:1ef86a9ebc53f379d921fb9a7e42b92059ad3ee800fcd9e0fe6181090e9f6c23", size = 849119, upload-time = "2025-09-19T00:36:41.651Z" }, - { url = "https://files.pythonhosted.org/packages/60/52/383d3044fc5154d9ffe4321696ee5b2ee4833a28c29b137c22c33f41885b/regex-2025.9.18-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:d3bc882119764ba3a119fbf2bd4f1b47bc56c1da5d42df4ed54ae1e8e66fdf8f", size = 788219, upload-time = "2025-09-19T00:36:43.575Z" }, - { url = "https://files.pythonhosted.org/packages/20/bd/2614fc302671b7359972ea212f0e3a92df4414aaeacab054a8ce80a86073/regex-2025.9.18-cp313-cp313-win32.whl", hash = "sha256:3810a65675845c3bdfa58c3c7d88624356dd6ee2fc186628295e0969005f928d", size = 264517, upload-time = "2025-09-19T00:36:45.503Z" }, - { url = "https://files.pythonhosted.org/packages/07/0f/ab5c1581e6563a7bffdc1974fb2d25f05689b88e2d416525271f232b1946/regex-2025.9.18-cp313-cp313-win_amd64.whl", hash = "sha256:16eaf74b3c4180ede88f620f299e474913ab6924d5c4b89b3833bc2345d83b3d", size = 275481, upload-time = "2025-09-19T00:36:46.965Z" }, - { url = "https://files.pythonhosted.org/packages/49/22/ee47672bc7958f8c5667a587c2600a4fba8b6bab6e86bd6d3e2b5f7cac42/regex-2025.9.18-cp313-cp313-win_arm64.whl", hash = "sha256:4dc98ba7dd66bd1261927a9f49bd5ee2bcb3660f7962f1ec02617280fc00f5eb", size = 268598, upload-time = "2025-09-19T00:36:48.314Z" }, - { url = "https://files.pythonhosted.org/packages/e8/83/6887e16a187c6226cb85d8301e47d3b73ecc4505a3a13d8da2096b44fd76/regex-2025.9.18-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:fe5d50572bc885a0a799410a717c42b1a6b50e2f45872e2b40f4f288f9bce8a2", size = 489765, upload-time = "2025-09-19T00:36:49.996Z" }, - { url = "https://files.pythonhosted.org/packages/51/c5/e2f7325301ea2916ff301c8d963ba66b1b2c1b06694191df80a9c4fea5d0/regex-2025.9.18-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:1b9d9a2d6cda6621551ca8cf7a06f103adf72831153f3c0d982386110870c4d3", size = 291228, upload-time = "2025-09-19T00:36:51.654Z" }, - { url = "https://files.pythonhosted.org/packages/91/60/7d229d2bc6961289e864a3a3cfebf7d0d250e2e65323a8952cbb7e22d824/regex-2025.9.18-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:13202e4c4ac0ef9a317fff817674b293c8f7e8c68d3190377d8d8b749f566e12", size = 289270, upload-time = "2025-09-19T00:36:53.118Z" }, - { url = "https://files.pythonhosted.org/packages/3c/d7/b4f06868ee2958ff6430df89857fbf3d43014bbf35538b6ec96c2704e15d/regex-2025.9.18-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:874ff523b0fecffb090f80ae53dc93538f8db954c8bb5505f05b7787ab3402a0", size = 806326, upload-time = "2025-09-19T00:36:54.631Z" }, - { url = "https://files.pythonhosted.org/packages/d6/e4/bca99034a8f1b9b62ccf337402a8e5b959dd5ba0e5e5b2ead70273df3277/regex-2025.9.18-cp313-cp313t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:d13ab0490128f2bb45d596f754148cd750411afc97e813e4b3a61cf278a23bb6", size = 871556, upload-time = "2025-09-19T00:36:56.208Z" }, - { url = "https://files.pythonhosted.org/packages/6d/df/e06ffaf078a162f6dd6b101a5ea9b44696dca860a48136b3ae4a9caf25e2/regex-2025.9.18-cp313-cp313t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:05440bc172bc4b4b37fb9667e796597419404dbba62e171e1f826d7d2a9ebcef", size = 913817, upload-time = "2025-09-19T00:36:57.807Z" }, - { url = "https://files.pythonhosted.org/packages/9e/05/25b05480b63292fd8e84800b1648e160ca778127b8d2367a0a258fa2e225/regex-2025.9.18-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:5514b8e4031fdfaa3d27e92c75719cbe7f379e28cacd939807289bce76d0e35a", size = 811055, upload-time = "2025-09-19T00:36:59.762Z" }, - { url = "https://files.pythonhosted.org/packages/70/97/7bc7574655eb651ba3a916ed4b1be6798ae97af30104f655d8efd0cab24b/regex-2025.9.18-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:65d3c38c39efce73e0d9dc019697b39903ba25b1ad45ebbd730d2cf32741f40d", size = 794534, upload-time = "2025-09-19T00:37:01.405Z" }, - { url = "https://files.pythonhosted.org/packages/b4/c2/d5da49166a52dda879855ecdba0117f073583db2b39bb47ce9a3378a8e9e/regex-2025.9.18-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:ae77e447ebc144d5a26d50055c6ddba1d6ad4a865a560ec7200b8b06bc529368", size = 866684, upload-time = "2025-09-19T00:37:03.441Z" }, - { url = "https://files.pythonhosted.org/packages/bd/2d/0a5c4e6ec417de56b89ff4418ecc72f7e3feca806824c75ad0bbdae0516b/regex-2025.9.18-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:e3ef8cf53dc8df49d7e28a356cf824e3623764e9833348b655cfed4524ab8a90", size = 853282, upload-time = "2025-09-19T00:37:04.985Z" }, - { url = "https://files.pythonhosted.org/packages/f4/8e/d656af63e31a86572ec829665d6fa06eae7e144771e0330650a8bb865635/regex-2025.9.18-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:9feb29817df349c976da9a0debf775c5c33fc1c8ad7b9f025825da99374770b7", size = 797830, upload-time = "2025-09-19T00:37:06.697Z" }, - { url = "https://files.pythonhosted.org/packages/db/ce/06edc89df8f7b83ffd321b6071be4c54dc7332c0f77860edc40ce57d757b/regex-2025.9.18-cp313-cp313t-win32.whl", hash = "sha256:168be0d2f9b9d13076940b1ed774f98595b4e3c7fc54584bba81b3cc4181742e", size = 267281, upload-time = "2025-09-19T00:37:08.568Z" }, - { url = "https://files.pythonhosted.org/packages/83/9a/2b5d9c8b307a451fd17068719d971d3634ca29864b89ed5c18e499446d4a/regex-2025.9.18-cp313-cp313t-win_amd64.whl", hash = "sha256:d59ecf3bb549e491c8104fea7313f3563c7b048e01287db0a90485734a70a730", size = 278724, upload-time = "2025-09-19T00:37:10.023Z" }, - { url = "https://files.pythonhosted.org/packages/3d/70/177d31e8089a278a764f8ec9a3faac8d14a312d622a47385d4b43905806f/regex-2025.9.18-cp313-cp313t-win_arm64.whl", hash = "sha256:dbef80defe9fb21310948a2595420b36c6d641d9bea4c991175829b2cc4bc06a", size = 269771, upload-time = "2025-09-19T00:37:13.041Z" }, - { url = "https://files.pythonhosted.org/packages/44/b7/3b4663aa3b4af16819f2ab6a78c4111c7e9b066725d8107753c2257448a5/regex-2025.9.18-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:c6db75b51acf277997f3adcd0ad89045d856190d13359f15ab5dda21581d9129", size = 486130, upload-time = "2025-09-19T00:37:14.527Z" }, - { url = "https://files.pythonhosted.org/packages/80/5b/4533f5d7ac9c6a02a4725fe8883de2aebc713e67e842c04cf02626afb747/regex-2025.9.18-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:8f9698b6f6895d6db810e0bda5364f9ceb9e5b11328700a90cae573574f61eea", size = 289539, upload-time = "2025-09-19T00:37:16.356Z" }, - { url = "https://files.pythonhosted.org/packages/b8/8d/5ab6797c2750985f79e9995fad3254caa4520846580f266ae3b56d1cae58/regex-2025.9.18-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:29cd86aa7cb13a37d0f0d7c21d8d949fe402ffa0ea697e635afedd97ab4b69f1", size = 287233, upload-time = "2025-09-19T00:37:18.025Z" }, - { url = "https://files.pythonhosted.org/packages/cb/1e/95afcb02ba8d3a64e6ffeb801718ce73471ad6440c55d993f65a4a5e7a92/regex-2025.9.18-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:7c9f285a071ee55cd9583ba24dde006e53e17780bb309baa8e4289cd472bcc47", size = 797876, upload-time = "2025-09-19T00:37:19.609Z" }, - { url = "https://files.pythonhosted.org/packages/c8/fb/720b1f49cec1f3b5a9fea5b34cd22b88b5ebccc8c1b5de9cc6f65eed165a/regex-2025.9.18-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:5adf266f730431e3be9021d3e5b8d5ee65e563fec2883ea8093944d21863b379", size = 863385, upload-time = "2025-09-19T00:37:21.65Z" }, - { url = "https://files.pythonhosted.org/packages/a9/ca/e0d07ecf701e1616f015a720dc13b84c582024cbfbb3fc5394ae204adbd7/regex-2025.9.18-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:1137cabc0f38807de79e28d3f6e3e3f2cc8cfb26bead754d02e6d1de5f679203", size = 910220, upload-time = "2025-09-19T00:37:23.723Z" }, - { url = "https://files.pythonhosted.org/packages/b6/45/bba86413b910b708eca705a5af62163d5d396d5f647ed9485580c7025209/regex-2025.9.18-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7cc9e5525cada99699ca9223cce2d52e88c52a3d2a0e842bd53de5497c604164", size = 801827, upload-time = "2025-09-19T00:37:25.684Z" }, - { url = "https://files.pythonhosted.org/packages/b8/a6/740fbd9fcac31a1305a8eed30b44bf0f7f1e042342be0a4722c0365ecfca/regex-2025.9.18-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:bbb9246568f72dce29bcd433517c2be22c7791784b223a810225af3b50d1aafb", size = 786843, upload-time = "2025-09-19T00:37:27.62Z" }, - { url = "https://files.pythonhosted.org/packages/80/a7/0579e8560682645906da640c9055506465d809cb0f5415d9976f417209a6/regex-2025.9.18-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:6a52219a93dd3d92c675383efff6ae18c982e2d7651c792b1e6d121055808743", size = 857430, upload-time = "2025-09-19T00:37:29.362Z" }, - { url = "https://files.pythonhosted.org/packages/8d/9b/4dc96b6c17b38900cc9fee254fc9271d0dde044e82c78c0811b58754fde5/regex-2025.9.18-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:ae9b3840c5bd456780e3ddf2f737ab55a79b790f6409182012718a35c6d43282", size = 848612, upload-time = "2025-09-19T00:37:31.42Z" }, - { url = "https://files.pythonhosted.org/packages/b3/6a/6f659f99bebb1775e5ac81a3fb837b85897c1a4ef5acffd0ff8ffe7e67fb/regex-2025.9.18-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:d488c236ac497c46a5ac2005a952c1a0e22a07be9f10c3e735bc7d1209a34773", size = 787967, upload-time = "2025-09-19T00:37:34.019Z" }, - { url = "https://files.pythonhosted.org/packages/61/35/9e35665f097c07cf384a6b90a1ac11b0b1693084a0b7a675b06f760496c6/regex-2025.9.18-cp314-cp314-win32.whl", hash = "sha256:0c3506682ea19beefe627a38872d8da65cc01ffa25ed3f2e422dffa1474f0788", size = 269847, upload-time = "2025-09-19T00:37:35.759Z" }, - { url = "https://files.pythonhosted.org/packages/af/64/27594dbe0f1590b82de2821ebfe9a359b44dcb9b65524876cd12fabc447b/regex-2025.9.18-cp314-cp314-win_amd64.whl", hash = "sha256:57929d0f92bebb2d1a83af372cd0ffba2263f13f376e19b1e4fa32aec4efddc3", size = 278755, upload-time = "2025-09-19T00:37:37.367Z" }, - { url = "https://files.pythonhosted.org/packages/30/a3/0cd8d0d342886bd7d7f252d701b20ae1a3c72dc7f34ef4b2d17790280a09/regex-2025.9.18-cp314-cp314-win_arm64.whl", hash = "sha256:6a4b44df31d34fa51aa5c995d3aa3c999cec4d69b9bd414a8be51984d859f06d", size = 271873, upload-time = "2025-09-19T00:37:39.125Z" }, - { url = "https://files.pythonhosted.org/packages/99/cb/8a1ab05ecf404e18b54348e293d9b7a60ec2bd7aa59e637020c5eea852e8/regex-2025.9.18-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:b176326bcd544b5e9b17d6943f807697c0cb7351f6cfb45bf5637c95ff7e6306", size = 489773, upload-time = "2025-09-19T00:37:40.968Z" }, - { url = "https://files.pythonhosted.org/packages/93/3b/6543c9b7f7e734d2404fa2863d0d710c907bef99d4598760ed4563d634c3/regex-2025.9.18-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:0ffd9e230b826b15b369391bec167baed57c7ce39efc35835448618860995946", size = 291221, upload-time = "2025-09-19T00:37:42.901Z" }, - { url = "https://files.pythonhosted.org/packages/cd/91/e9fdee6ad6bf708d98c5d17fded423dcb0661795a49cba1b4ffb8358377a/regex-2025.9.18-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:ec46332c41add73f2b57e2f5b642f991f6b15e50e9f86285e08ffe3a512ac39f", size = 289268, upload-time = "2025-09-19T00:37:44.823Z" }, - { url = "https://files.pythonhosted.org/packages/94/a6/bc3e8a918abe4741dadeaeb6c508e3a4ea847ff36030d820d89858f96a6c/regex-2025.9.18-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b80fa342ed1ea095168a3f116637bd1030d39c9ff38dc04e54ef7c521e01fc95", size = 806659, upload-time = "2025-09-19T00:37:46.684Z" }, - { url = "https://files.pythonhosted.org/packages/2b/71/ea62dbeb55d9e6905c7b5a49f75615ea1373afcad95830047e4e310db979/regex-2025.9.18-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:f4d97071c0ba40f0cf2a93ed76e660654c399a0a04ab7d85472239460f3da84b", size = 871701, upload-time = "2025-09-19T00:37:48.882Z" }, - { url = "https://files.pythonhosted.org/packages/6a/90/fbe9dedb7dad24a3a4399c0bae64bfa932ec8922a0a9acf7bc88db30b161/regex-2025.9.18-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:0ac936537ad87cef9e0e66c5144484206c1354224ee811ab1519a32373e411f3", size = 913742, upload-time = "2025-09-19T00:37:51.015Z" }, - { url = "https://files.pythonhosted.org/packages/f0/1c/47e4a8c0e73d41eb9eb9fdeba3b1b810110a5139a2526e82fd29c2d9f867/regex-2025.9.18-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:dec57f96d4def58c422d212d414efe28218d58537b5445cf0c33afb1b4768571", size = 811117, upload-time = "2025-09-19T00:37:52.686Z" }, - { url = "https://files.pythonhosted.org/packages/2a/da/435f29fddfd015111523671e36d30af3342e8136a889159b05c1d9110480/regex-2025.9.18-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:48317233294648bf7cd068857f248e3a57222259a5304d32c7552e2284a1b2ad", size = 794647, upload-time = "2025-09-19T00:37:54.626Z" }, - { url = "https://files.pythonhosted.org/packages/23/66/df5e6dcca25c8bc57ce404eebc7342310a0d218db739d7882c9a2b5974a3/regex-2025.9.18-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:274687e62ea3cf54846a9b25fc48a04459de50af30a7bd0b61a9e38015983494", size = 866747, upload-time = "2025-09-19T00:37:56.367Z" }, - { url = "https://files.pythonhosted.org/packages/82/42/94392b39b531f2e469b2daa40acf454863733b674481fda17462a5ffadac/regex-2025.9.18-cp314-cp314t-musllinux_1_2_s390x.whl", hash = "sha256:a78722c86a3e7e6aadf9579e3b0ad78d955f2d1f1a8ca4f67d7ca258e8719d4b", size = 853434, upload-time = "2025-09-19T00:37:58.39Z" }, - { url = "https://files.pythonhosted.org/packages/a8/f8/dcc64c7f7bbe58842a8f89622b50c58c3598fbbf4aad0a488d6df2c699f1/regex-2025.9.18-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:06104cd203cdef3ade989a1c45b6215bf42f8b9dd705ecc220c173233f7cba41", size = 798024, upload-time = "2025-09-19T00:38:00.397Z" }, - { url = "https://files.pythonhosted.org/packages/20/8d/edf1c5d5aa98f99a692313db813ec487732946784f8f93145e0153d910e5/regex-2025.9.18-cp314-cp314t-win32.whl", hash = "sha256:2e1eddc06eeaffd249c0adb6fafc19e2118e6308c60df9db27919e96b5656096", size = 273029, upload-time = "2025-09-19T00:38:02.383Z" }, - { url = "https://files.pythonhosted.org/packages/a7/24/02d4e4f88466f17b145f7ea2b2c11af3a942db6222429c2c146accf16054/regex-2025.9.18-cp314-cp314t-win_amd64.whl", hash = "sha256:8620d247fb8c0683ade51217b459cb4a1081c0405a3072235ba43a40d355c09a", size = 282680, upload-time = "2025-09-19T00:38:04.102Z" }, - { url = "https://files.pythonhosted.org/packages/1f/a3/c64894858aaaa454caa7cc47e2f225b04d3ed08ad649eacf58d45817fad2/regex-2025.9.18-cp314-cp314t-win_arm64.whl", hash = "sha256:b7531a8ef61de2c647cdf68b3229b071e46ec326b3138b2180acb4275f470b01", size = 273034, upload-time = "2025-09-19T00:38:05.807Z" }, -] - -[[package]] -name = "requests" -version = "2.32.5" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "certifi" }, - { name = "charset-normalizer" }, - { name = "idna" }, - { name = "urllib3", version = "1.26.20", source = { registry = "https://pypi.org/simple" }, marker = "platform_python_implementation == 'PyPy'" }, - { name = "urllib3", version = "2.5.0", source = { registry = "https://pypi.org/simple" }, marker = "platform_python_implementation != 'PyPy'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/c9/74/b3ff8e6c8446842c3f5c837e9c3dfcfe2018ea6ecef224c710c85ef728f4/requests-2.32.5.tar.gz", hash = "sha256:dbba0bac56e100853db0ea71b82b4dfd5fe2bf6d3754a8893c3af500cec7d7cf", size = 134517, upload-time = "2025-08-18T20:46:02.573Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl", hash = "sha256:2462f94637a34fd532264295e186976db0f5d453d1cdd31473c85a6a161affb6", size = 64738, upload-time = "2025-08-18T20:46:00.542Z" }, -] - -[[package]] -name = "requests-toolbelt" -version = "1.0.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "requests" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/f3/61/d7545dafb7ac2230c70d38d31cbfe4cc64f7144dc41f6e4e4b78ecd9f5bb/requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6", size = 206888, upload-time = "2023-05-01T04:11:33.229Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/3f/51/d4db610ef29373b879047326cbf6fa98b6c1969d6f6dc423279de2b1be2c/requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06", size = 54481, upload-time = "2023-05-01T04:11:28.427Z" }, -] - -[[package]] -name = "rfc3986" -version = "2.0.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/85/40/1520d68bfa07ab5a6f065a186815fb6610c86fe957bc065754e47f7b0840/rfc3986-2.0.0.tar.gz", hash = "sha256:97aacf9dbd4bfd829baad6e6309fa6573aaf1be3f6fa735c8ab05e46cecb261c", size = 49026, upload-time = "2022-01-10T00:52:30.832Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ff/9a/9afaade874b2fa6c752c36f1548f718b5b83af81ed9b76628329dab81c1b/rfc3986-2.0.0-py2.py3-none-any.whl", hash = "sha256:50b1502b60e289cb37883f3dfd34532b8873c7de9f49bb546641ce9cbd256ebd", size = 31326, upload-time = "2022-01-10T00:52:29.594Z" }, -] - -[[package]] -name = "rich" -version = "14.1.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "markdown-it-py" }, - { name = "pygments" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/fe/75/af448d8e52bf1d8fa6a9d089ca6c07ff4453d86c65c145d0a300bb073b9b/rich-14.1.0.tar.gz", hash = "sha256:e497a48b844b0320d45007cdebfeaeed8db2a4f4bcf49f15e455cfc4af11eaa8", size = 224441, upload-time = "2025-07-25T07:32:58.125Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e3/30/3c4d035596d3cf444529e0b2953ad0466f6049528a879d27534700580395/rich-14.1.0-py3-none-any.whl", hash = "sha256:536f5f1785986d6dbdea3c75205c473f970777b4a0d6c6dd1b696aa05a3fa04f", size = 243368, upload-time = "2025-07-25T07:32:56.73Z" }, -] - -[[package]] -name = "ruff" -version = "0.13.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ab/33/c8e89216845615d14d2d42ba2bee404e7206a8db782f33400754f3799f05/ruff-0.13.1.tar.gz", hash = "sha256:88074c3849087f153d4bb22e92243ad4c1b366d7055f98726bc19aa08dc12d51", size = 5397987, upload-time = "2025-09-18T19:52:44.33Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/f3/41/ca37e340938f45cfb8557a97a5c347e718ef34702546b174e5300dbb1f28/ruff-0.13.1-py3-none-linux_armv6l.whl", hash = "sha256:b2abff595cc3cbfa55e509d89439b5a09a6ee3c252d92020bd2de240836cf45b", size = 12304308, upload-time = "2025-09-18T19:51:56.253Z" }, - { url = "https://files.pythonhosted.org/packages/ff/84/ba378ef4129415066c3e1c80d84e539a0d52feb250685091f874804f28af/ruff-0.13.1-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:4ee9f4249bf7f8bb3984c41bfaf6a658162cdb1b22e3103eabc7dd1dc5579334", size = 12937258, upload-time = "2025-09-18T19:52:00.184Z" }, - { url = "https://files.pythonhosted.org/packages/8d/b6/ec5e4559ae0ad955515c176910d6d7c93edcbc0ed1a3195a41179c58431d/ruff-0.13.1-py3-none-macosx_11_0_arm64.whl", hash = "sha256:5c5da4af5f6418c07d75e6f3224e08147441f5d1eac2e6ce10dcce5e616a3bae", size = 12214554, upload-time = "2025-09-18T19:52:02.753Z" }, - { url = "https://files.pythonhosted.org/packages/70/d6/cb3e3b4f03b9b0c4d4d8f06126d34b3394f6b4d764912fe80a1300696ef6/ruff-0.13.1-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:80524f84a01355a59a93cef98d804e2137639823bcee2931f5028e71134a954e", size = 12448181, upload-time = "2025-09-18T19:52:05.279Z" }, - { url = "https://files.pythonhosted.org/packages/d2/ea/bf60cb46d7ade706a246cd3fb99e4cfe854efa3dfbe530d049c684da24ff/ruff-0.13.1-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ff7f5ce8d7988767dd46a148192a14d0f48d1baea733f055d9064875c7d50389", size = 12104599, upload-time = "2025-09-18T19:52:07.497Z" }, - { url = "https://files.pythonhosted.org/packages/2d/3e/05f72f4c3d3a69e65d55a13e1dd1ade76c106d8546e7e54501d31f1dc54a/ruff-0.13.1-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c55d84715061f8b05469cdc9a446aa6c7294cd4bd55e86a89e572dba14374f8c", size = 13791178, upload-time = "2025-09-18T19:52:10.189Z" }, - { url = "https://files.pythonhosted.org/packages/81/e7/01b1fc403dd45d6cfe600725270ecc6a8f8a48a55bc6521ad820ed3ceaf8/ruff-0.13.1-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:ac57fed932d90fa1624c946dc67a0a3388d65a7edc7d2d8e4ca7bddaa789b3b0", size = 14814474, upload-time = "2025-09-18T19:52:12.866Z" }, - { url = "https://files.pythonhosted.org/packages/fa/92/d9e183d4ed6185a8df2ce9faa3f22e80e95b5f88d9cc3d86a6d94331da3f/ruff-0.13.1-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c366a71d5b4f41f86a008694f7a0d75fe409ec298685ff72dc882f882d532e36", size = 14217531, upload-time = "2025-09-18T19:52:15.245Z" }, - { url = "https://files.pythonhosted.org/packages/3b/4a/6ddb1b11d60888be224d721e01bdd2d81faaf1720592858ab8bac3600466/ruff-0.13.1-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f4ea9d1b5ad3e7a83ee8ebb1229c33e5fe771e833d6d3dcfca7b77d95b060d38", size = 13265267, upload-time = "2025-09-18T19:52:17.649Z" }, - { url = "https://files.pythonhosted.org/packages/81/98/3f1d18a8d9ea33ef2ad508f0417fcb182c99b23258ec5e53d15db8289809/ruff-0.13.1-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b0f70202996055b555d3d74b626406476cc692f37b13bac8828acff058c9966a", size = 13243120, upload-time = "2025-09-18T19:52:20.332Z" }, - { url = "https://files.pythonhosted.org/packages/8d/86/b6ce62ce9c12765fa6c65078d1938d2490b2b1d9273d0de384952b43c490/ruff-0.13.1-py3-none-manylinux_2_31_riscv64.whl", hash = "sha256:f8cff7a105dad631085d9505b491db33848007d6b487c3c1979dd8d9b2963783", size = 13443084, upload-time = "2025-09-18T19:52:23.032Z" }, - { url = "https://files.pythonhosted.org/packages/a1/6e/af7943466a41338d04503fb5a81b2fd07251bd272f546622e5b1599a7976/ruff-0.13.1-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:9761e84255443316a258dd7dfbd9bfb59c756e52237ed42494917b2577697c6a", size = 12295105, upload-time = "2025-09-18T19:52:25.263Z" }, - { url = "https://files.pythonhosted.org/packages/3f/97/0249b9a24f0f3ebd12f007e81c87cec6d311de566885e9309fcbac5b24cc/ruff-0.13.1-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:3d376a88c3102ef228b102211ef4a6d13df330cb0f5ca56fdac04ccec2a99700", size = 12072284, upload-time = "2025-09-18T19:52:27.478Z" }, - { url = "https://files.pythonhosted.org/packages/f6/85/0b64693b2c99d62ae65236ef74508ba39c3febd01466ef7f354885e5050c/ruff-0.13.1-py3-none-musllinux_1_2_i686.whl", hash = "sha256:cbefd60082b517a82c6ec8836989775ac05f8991715d228b3c1d86ccc7df7dae", size = 12970314, upload-time = "2025-09-18T19:52:30.212Z" }, - { url = "https://files.pythonhosted.org/packages/96/fc/342e9f28179915d28b3747b7654f932ca472afbf7090fc0c4011e802f494/ruff-0.13.1-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:dd16b9a5a499fe73f3c2ef09a7885cb1d97058614d601809d37c422ed1525317", size = 13422360, upload-time = "2025-09-18T19:52:32.676Z" }, - { url = "https://files.pythonhosted.org/packages/37/54/6177a0dc10bce6f43e392a2192e6018755473283d0cf43cc7e6afc182aea/ruff-0.13.1-py3-none-win32.whl", hash = "sha256:55e9efa692d7cb18580279f1fbb525146adc401f40735edf0aaeabd93099f9a0", size = 12178448, upload-time = "2025-09-18T19:52:35.545Z" }, - { url = "https://files.pythonhosted.org/packages/64/51/c6a3a33d9938007b8bdc8ca852ecc8d810a407fb513ab08e34af12dc7c24/ruff-0.13.1-py3-none-win_amd64.whl", hash = "sha256:3a3fb595287ee556de947183489f636b9f76a72f0fa9c028bdcabf5bab2cc5e5", size = 13286458, upload-time = "2025-09-18T19:52:38.198Z" }, - { url = "https://files.pythonhosted.org/packages/fd/04/afc078a12cf68592345b1e2d6ecdff837d286bac023d7a22c54c7a698c5b/ruff-0.13.1-py3-none-win_arm64.whl", hash = "sha256:c0bae9ffd92d54e03c2bf266f466da0a65e145f298ee5b5846ed435f6a00518a", size = 12437893, upload-time = "2025-09-18T19:52:41.283Z" }, -] - -[[package]] -name = "secretstorage" -version = "3.4.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "cryptography" }, - { name = "jeepney" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/31/9f/11ef35cf1027c1339552ea7bfe6aaa74a8516d8b5caf6e7d338daf54fd80/secretstorage-3.4.0.tar.gz", hash = "sha256:c46e216d6815aff8a8a18706a2fbfd8d53fcbb0dce99301881687a1b0289ef7c", size = 19748, upload-time = "2025-09-09T16:42:13.859Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/91/ff/2e2eed29e02c14a5cb6c57f09b2d5b40e65d6cc71f45b52e0be295ccbc2f/secretstorage-3.4.0-py3-none-any.whl", hash = "sha256:0e3b6265c2c63509fb7415717607e4b2c9ab767b7f344a57473b779ca13bd02e", size = 15272, upload-time = "2025-09-09T16:42:12.744Z" }, -] - -[[package]] -name = "smmap" -version = "5.0.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/44/cd/a040c4b3119bbe532e5b0732286f805445375489fceaec1f48306068ee3b/smmap-5.0.2.tar.gz", hash = "sha256:26ea65a03958fa0c8a1c7e8c7a58fdc77221b8910f6be2131affade476898ad5", size = 22329, upload-time = "2025-01-02T07:14:40.909Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/04/be/d09147ad1ec7934636ad912901c5fd7667e1c858e19d355237db0d0cd5e4/smmap-5.0.2-py3-none-any.whl", hash = "sha256:b30115f0def7d7531d22a0fb6502488d879e75b260a9db4d0819cfb25403af5e", size = 24303, upload-time = "2025-01-02T07:14:38.724Z" }, -] - -[[package]] -name = "sniffio" -version = "1.3.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a2/87/a6771e1546d97e7e041b6ae58d80074f81b7d5121207425c964ddf5cfdbd/sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc", size = 20372, upload-time = "2024-02-25T23:20:04.057Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e9/44/75a9c9421471a6c4805dbf2356f7c181a29c1879239abab1ea2cc8f38b40/sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2", size = 10235, upload-time = "2024-02-25T23:20:01.196Z" }, -] - -[[package]] -name = "sqlalchemy" -version = "2.0.46" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "greenlet", marker = "platform_machine == 'AMD64' or platform_machine == 'WIN32' or platform_machine == 'aarch64' or platform_machine == 'amd64' or platform_machine == 'ppc64le' or platform_machine == 'win32' or platform_machine == 'x86_64'" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/06/aa/9ce0f3e7a9829ead5c8ce549392f33a12c4555a6c0609bb27d882e9c7ddf/sqlalchemy-2.0.46.tar.gz", hash = "sha256:cf36851ee7219c170bb0793dbc3da3e80c582e04a5437bc601bfe8c85c9216d7", size = 9865393, upload-time = "2026-01-21T18:03:45.119Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/40/26/66ba59328dc25e523bfcb0f8db48bdebe2035e0159d600e1f01c0fc93967/sqlalchemy-2.0.46-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:895296687ad06dc9b11a024cf68e8d9d3943aa0b4964278d2553b86f1b267735", size = 2155051, upload-time = "2026-01-21T18:27:28.965Z" }, - { url = "https://files.pythonhosted.org/packages/21/cd/9336732941df972fbbfa394db9caa8bb0cf9fe03656ec728d12e9cbd6edc/sqlalchemy-2.0.46-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:ab65cb2885a9f80f979b85aa4e9c9165a31381ca322cbde7c638fe6eefd1ec39", size = 3234666, upload-time = "2026-01-21T18:32:28.72Z" }, - { url = "https://files.pythonhosted.org/packages/38/62/865ae8b739930ec433cd4123760bee7f8dafdc10abefd725a025604fb0de/sqlalchemy-2.0.46-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:52fe29b3817bd191cc20bad564237c808967972c97fa683c04b28ec8979ae36f", size = 3232917, upload-time = "2026-01-21T18:44:54.064Z" }, - { url = "https://files.pythonhosted.org/packages/24/38/805904b911857f2b5e00fdea44e9570df62110f834378706939825579296/sqlalchemy-2.0.46-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:09168817d6c19954d3b7655da6ba87fcb3a62bb575fb396a81a8b6a9fadfe8b5", size = 3185790, upload-time = "2026-01-21T18:32:30.581Z" }, - { url = "https://files.pythonhosted.org/packages/69/4f/3260bb53aabd2d274856337456ea52f6a7eccf6cce208e558f870cec766b/sqlalchemy-2.0.46-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:be6c0466b4c25b44c5d82b0426b5501de3c424d7a3220e86cd32f319ba56798e", size = 3207206, upload-time = "2026-01-21T18:44:55.93Z" }, - { url = "https://files.pythonhosted.org/packages/ce/b3/67c432d7f9d88bb1a61909b67e29f6354d59186c168fb5d381cf438d3b73/sqlalchemy-2.0.46-cp310-cp310-win32.whl", hash = "sha256:1bc3f601f0a818d27bfe139f6766487d9c88502062a2cd3a7ee6c342e81d5047", size = 2115296, upload-time = "2026-01-21T18:33:12.498Z" }, - { url = "https://files.pythonhosted.org/packages/4a/8c/25fb284f570f9d48e6c240f0269a50cec9cf009a7e08be4c0aaaf0654972/sqlalchemy-2.0.46-cp310-cp310-win_amd64.whl", hash = "sha256:e0c05aff5c6b1bb5fb46a87e0f9d2f733f83ef6cbbbcd5c642b6c01678268061", size = 2138540, upload-time = "2026-01-21T18:33:14.22Z" }, - { url = "https://files.pythonhosted.org/packages/69/ac/b42ad16800d0885105b59380ad69aad0cce5a65276e269ce2729a2343b6a/sqlalchemy-2.0.46-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:261c4b1f101b4a411154f1da2b76497d73abbfc42740029205d4d01fa1052684", size = 2154851, upload-time = "2026-01-21T18:27:30.54Z" }, - { url = "https://files.pythonhosted.org/packages/a0/60/d8710068cb79f64d002ebed62a7263c00c8fd95f4ebd4b5be8f7ca93f2bc/sqlalchemy-2.0.46-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:181903fe8c1b9082995325f1b2e84ac078b1189e2819380c2303a5f90e114a62", size = 3311241, upload-time = "2026-01-21T18:32:33.45Z" }, - { url = "https://files.pythonhosted.org/packages/2b/0f/20c71487c7219ab3aa7421c7c62d93824c97c1460f2e8bb72404b0192d13/sqlalchemy-2.0.46-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:590be24e20e2424a4c3c1b0835e9405fa3d0af5823a1a9fc02e5dff56471515f", size = 3310741, upload-time = "2026-01-21T18:44:57.887Z" }, - { url = "https://files.pythonhosted.org/packages/65/80/d26d00b3b249ae000eee4db206fcfc564bf6ca5030e4747adf451f4b5108/sqlalchemy-2.0.46-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:7568fe771f974abadce52669ef3a03150ff03186d8eb82613bc8adc435a03f01", size = 3263116, upload-time = "2026-01-21T18:32:35.044Z" }, - { url = "https://files.pythonhosted.org/packages/da/ee/74dda7506640923821340541e8e45bd3edd8df78664f1f2e0aae8077192b/sqlalchemy-2.0.46-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ebf7e1e78af38047e08836d33502c7a278915698b7c2145d045f780201679999", size = 3285327, upload-time = "2026-01-21T18:44:59.254Z" }, - { url = "https://files.pythonhosted.org/packages/9f/25/6dcf8abafff1389a21c7185364de145107b7394ecdcb05233815b236330d/sqlalchemy-2.0.46-cp311-cp311-win32.whl", hash = "sha256:9d80ea2ac519c364a7286e8d765d6cd08648f5b21ca855a8017d9871f075542d", size = 2114564, upload-time = "2026-01-21T18:33:15.85Z" }, - { url = "https://files.pythonhosted.org/packages/93/5f/e081490f8523adc0088f777e4ebad3cac21e498ec8a3d4067074e21447a1/sqlalchemy-2.0.46-cp311-cp311-win_amd64.whl", hash = "sha256:585af6afe518732d9ccd3aea33af2edaae4a7aa881af5d8f6f4fe3a368699597", size = 2139233, upload-time = "2026-01-21T18:33:17.528Z" }, - { url = "https://files.pythonhosted.org/packages/b6/35/d16bfa235c8b7caba3730bba43e20b1e376d2224f407c178fbf59559f23e/sqlalchemy-2.0.46-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:3a9a72b0da8387f15d5810f1facca8f879de9b85af8c645138cba61ea147968c", size = 2153405, upload-time = "2026-01-21T19:05:54.143Z" }, - { url = "https://files.pythonhosted.org/packages/06/6c/3192e24486749862f495ddc6584ed730c0c994a67550ec395d872a2ad650/sqlalchemy-2.0.46-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:2347c3f0efc4de367ba00218e0ae5c4ba2306e47216ef80d6e31761ac97cb0b9", size = 3334702, upload-time = "2026-01-21T18:46:45.384Z" }, - { url = "https://files.pythonhosted.org/packages/ea/a2/b9f33c8d68a3747d972a0bb758c6b63691f8fb8a49014bc3379ba15d4274/sqlalchemy-2.0.46-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9094c8b3197db12aa6f05c51c05daaad0a92b8c9af5388569847b03b1007fb1b", size = 3347664, upload-time = "2026-01-21T18:40:09.979Z" }, - { url = "https://files.pythonhosted.org/packages/aa/d2/3e59e2a91eaec9db7e8dc6b37b91489b5caeb054f670f32c95bcba98940f/sqlalchemy-2.0.46-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:37fee2164cf21417478b6a906adc1a91d69ae9aba8f9533e67ce882f4bb1de53", size = 3277372, upload-time = "2026-01-21T18:46:47.168Z" }, - { url = "https://files.pythonhosted.org/packages/dd/dd/67bc2e368b524e2192c3927b423798deda72c003e73a1e94c21e74b20a85/sqlalchemy-2.0.46-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b1e14b2f6965a685c7128bd315e27387205429c2e339eeec55cb75ca4ab0ea2e", size = 3312425, upload-time = "2026-01-21T18:40:11.548Z" }, - { url = "https://files.pythonhosted.org/packages/43/82/0ecd68e172bfe62247e96cb47867c2d68752566811a4e8c9d8f6e7c38a65/sqlalchemy-2.0.46-cp312-cp312-win32.whl", hash = "sha256:412f26bb4ba942d52016edc8d12fb15d91d3cd46b0047ba46e424213ad407bcb", size = 2113155, upload-time = "2026-01-21T18:42:49.748Z" }, - { url = "https://files.pythonhosted.org/packages/bc/2a/2821a45742073fc0331dc132552b30de68ba9563230853437cac54b2b53e/sqlalchemy-2.0.46-cp312-cp312-win_amd64.whl", hash = "sha256:ea3cd46b6713a10216323cda3333514944e510aa691c945334713fca6b5279ff", size = 2140078, upload-time = "2026-01-21T18:42:51.197Z" }, - { url = "https://files.pythonhosted.org/packages/b3/4b/fa7838fe20bb752810feed60e45625a9a8b0102c0c09971e2d1d95362992/sqlalchemy-2.0.46-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:93a12da97cca70cea10d4b4fc602589c4511f96c1f8f6c11817620c021d21d00", size = 2150268, upload-time = "2026-01-21T19:05:56.621Z" }, - { url = "https://files.pythonhosted.org/packages/46/c1/b34dccd712e8ea846edf396e00973dda82d598cb93762e55e43e6835eba9/sqlalchemy-2.0.46-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:af865c18752d416798dae13f83f38927c52f085c52e2f32b8ab0fef46fdd02c2", size = 3276511, upload-time = "2026-01-21T18:46:49.022Z" }, - { url = "https://files.pythonhosted.org/packages/96/48/a04d9c94753e5d5d096c628c82a98c4793b9c08ca0e7155c3eb7d7db9f24/sqlalchemy-2.0.46-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:8d679b5f318423eacb61f933a9a0f75535bfca7056daeadbf6bd5bcee6183aee", size = 3292881, upload-time = "2026-01-21T18:40:13.089Z" }, - { url = "https://files.pythonhosted.org/packages/be/f4/06eda6e91476f90a7d8058f74311cb65a2fb68d988171aced81707189131/sqlalchemy-2.0.46-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:64901e08c33462acc9ec3bad27fc7a5c2b6491665f2aa57564e57a4f5d7c52ad", size = 3224559, upload-time = "2026-01-21T18:46:50.974Z" }, - { url = "https://files.pythonhosted.org/packages/ab/a2/d2af04095412ca6345ac22b33b89fe8d6f32a481e613ffcb2377d931d8d0/sqlalchemy-2.0.46-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e8ac45e8f4eaac0f9f8043ea0e224158855c6a4329fd4ee37c45c61e3beb518e", size = 3262728, upload-time = "2026-01-21T18:40:14.883Z" }, - { url = "https://files.pythonhosted.org/packages/31/48/1980c7caa5978a3b8225b4d230e69a2a6538a3562b8b31cea679b6933c83/sqlalchemy-2.0.46-cp313-cp313-win32.whl", hash = "sha256:8d3b44b3d0ab2f1319d71d9863d76eeb46766f8cf9e921ac293511804d39813f", size = 2111295, upload-time = "2026-01-21T18:42:52.366Z" }, - { url = "https://files.pythonhosted.org/packages/2d/54/f8d65bbde3d877617c4720f3c9f60e99bb7266df0d5d78b6e25e7c149f35/sqlalchemy-2.0.46-cp313-cp313-win_amd64.whl", hash = "sha256:77f8071d8fbcbb2dd11b7fd40dedd04e8ebe2eb80497916efedba844298065ef", size = 2137076, upload-time = "2026-01-21T18:42:53.924Z" }, - { url = "https://files.pythonhosted.org/packages/56/ba/9be4f97c7eb2b9d5544f2624adfc2853e796ed51d2bb8aec90bc94b7137e/sqlalchemy-2.0.46-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:a1e8cc6cc01da346dc92d9509a63033b9b1bda4fed7a7a7807ed385c7dccdc10", size = 3556533, upload-time = "2026-01-21T18:33:06.636Z" }, - { url = "https://files.pythonhosted.org/packages/20/a6/b1fc6634564dbb4415b7ed6419cdfeaadefd2c39cdab1e3aa07a5f2474c2/sqlalchemy-2.0.46-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:96c7cca1a4babaaf3bfff3e4e606e38578856917e52f0384635a95b226c87764", size = 3523208, upload-time = "2026-01-21T18:45:08.436Z" }, - { url = "https://files.pythonhosted.org/packages/a1/d8/41e0bdfc0f930ff236f86fccd12962d8fa03713f17ed57332d38af6a3782/sqlalchemy-2.0.46-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:b2a9f9aee38039cf4755891a1e50e1effcc42ea6ba053743f452c372c3152b1b", size = 3464292, upload-time = "2026-01-21T18:33:08.208Z" }, - { url = "https://files.pythonhosted.org/packages/f0/8b/9dcbec62d95bea85f5ecad9b8d65b78cc30fb0ffceeb3597961f3712549b/sqlalchemy-2.0.46-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:db23b1bf8cfe1f7fda19018e7207b20cdb5168f83c437ff7e95d19e39289c447", size = 3473497, upload-time = "2026-01-21T18:45:10.552Z" }, - { url = "https://files.pythonhosted.org/packages/e9/f8/5ecdfc73383ec496de038ed1614de9e740a82db9ad67e6e4514ebc0708a3/sqlalchemy-2.0.46-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:56bdd261bfd0895452006d5316cbf35739c53b9bb71a170a331fa0ea560b2ada", size = 2152079, upload-time = "2026-01-21T19:05:58.477Z" }, - { url = "https://files.pythonhosted.org/packages/e5/bf/eba3036be7663ce4d9c050bc3d63794dc29fbe01691f2bf5ccb64e048d20/sqlalchemy-2.0.46-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:33e462154edb9493f6c3ad2125931e273bbd0be8ae53f3ecd1c161ea9a1dd366", size = 3272216, upload-time = "2026-01-21T18:46:52.634Z" }, - { url = "https://files.pythonhosted.org/packages/05/45/1256fb597bb83b58a01ddb600c59fe6fdf0e5afe333f0456ed75c0f8d7bd/sqlalchemy-2.0.46-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9bcdce05f056622a632f1d44bb47dbdb677f58cad393612280406ce37530eb6d", size = 3277208, upload-time = "2026-01-21T18:40:16.38Z" }, - { url = "https://files.pythonhosted.org/packages/d9/a0/2053b39e4e63b5d7ceb3372cface0859a067c1ddbd575ea7e9985716f771/sqlalchemy-2.0.46-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:8e84b09a9b0f19accedcbeff5c2caf36e0dd537341a33aad8d680336152dc34e", size = 3221994, upload-time = "2026-01-21T18:46:54.622Z" }, - { url = "https://files.pythonhosted.org/packages/1e/87/97713497d9502553c68f105a1cb62786ba1ee91dea3852ae4067ed956a50/sqlalchemy-2.0.46-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:4f52f7291a92381e9b4de9050b0a65ce5d6a763333406861e33906b8aa4906bf", size = 3243990, upload-time = "2026-01-21T18:40:18.253Z" }, - { url = "https://files.pythonhosted.org/packages/a8/87/5d1b23548f420ff823c236f8bea36b1a997250fd2f892e44a3838ca424f4/sqlalchemy-2.0.46-cp314-cp314-win32.whl", hash = "sha256:70ed2830b169a9960193f4d4322d22be5c0925357d82cbf485b3369893350908", size = 2114215, upload-time = "2026-01-21T18:42:55.232Z" }, - { url = "https://files.pythonhosted.org/packages/3a/20/555f39cbcf0c10cf452988b6a93c2a12495035f68b3dbd1a408531049d31/sqlalchemy-2.0.46-cp314-cp314-win_amd64.whl", hash = "sha256:3c32e993bc57be6d177f7d5d31edb93f30726d798ad86ff9066d75d9bf2e0b6b", size = 2139867, upload-time = "2026-01-21T18:42:56.474Z" }, - { url = "https://files.pythonhosted.org/packages/3e/f0/f96c8057c982d9d8a7a68f45d69c674bc6f78cad401099692fe16521640a/sqlalchemy-2.0.46-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4dafb537740eef640c4d6a7c254611dca2df87eaf6d14d6a5fca9d1f4c3fc0fa", size = 3561202, upload-time = "2026-01-21T18:33:10.337Z" }, - { url = "https://files.pythonhosted.org/packages/d7/53/3b37dda0a5b137f21ef608d8dfc77b08477bab0fe2ac9d3e0a66eaeab6fc/sqlalchemy-2.0.46-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:42a1643dc5427b69aca967dae540a90b0fbf57eaf248f13a90ea5930e0966863", size = 3526296, upload-time = "2026-01-21T18:45:12.657Z" }, - { url = "https://files.pythonhosted.org/packages/33/75/f28622ba6dde79cd545055ea7bd4062dc934e0621f7b3be2891f8563f8de/sqlalchemy-2.0.46-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:ff33c6e6ad006bbc0f34f5faf941cfc62c45841c64c0a058ac38c799f15b5ede", size = 3470008, upload-time = "2026-01-21T18:33:11.725Z" }, - { url = "https://files.pythonhosted.org/packages/a9/42/4afecbbc38d5e99b18acef446453c76eec6fbd03db0a457a12a056836e22/sqlalchemy-2.0.46-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:82ec52100ec1e6ec671563bbd02d7c7c8d0b9e71a0723c72f22ecf52d1755330", size = 3476137, upload-time = "2026-01-21T18:45:15.001Z" }, - { url = "https://files.pythonhosted.org/packages/fc/a1/9c4efa03300926601c19c18582531b45aededfb961ab3c3585f1e24f120b/sqlalchemy-2.0.46-py3-none-any.whl", hash = "sha256:f9c11766e7e7c0a2767dda5acb006a118640c9fc0a4104214b96269bfb78399e", size = 1937882, upload-time = "2026-01-21T18:22:10.456Z" }, -] - -[[package]] -name = "sseclient-py" -version = "1.8.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/e8/ed/3df5ab8bb0c12f86c28d0cadb11ed1de44a92ed35ce7ff4fd5518a809325/sseclient-py-1.8.0.tar.gz", hash = "sha256:c547c5c1a7633230a38dc599a21a2dc638f9b5c297286b48b46b935c71fac3e8", size = 7791, upload-time = "2023-09-01T19:39:20.45Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/49/58/97655efdfeb5b4eeab85b1fc5d3fa1023661246c2ab2a26ea8e47402d4f2/sseclient_py-1.8.0-py2.py3-none-any.whl", hash = "sha256:4ecca6dc0b9f963f8384e9d7fd529bf93dd7d708144c4fb5da0e0a1a926fee83", size = 8828, upload-time = "2023-09-01T19:39:17.627Z" }, -] - -[[package]] -name = "tenacity" -version = "9.1.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/0a/d4/2b0cd0fe285e14b36db076e78c93766ff1d529d70408bd1d2a5a84f1d929/tenacity-9.1.2.tar.gz", hash = "sha256:1169d376c297e7de388d18b4481760d478b0e99a777cad3a9c86e556f4b697cb", size = 48036, upload-time = "2025-04-02T08:25:09.966Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e5/30/643397144bfbfec6f6ef821f36f33e57d35946c44a2352d3c9f0ae847619/tenacity-9.1.2-py3-none-any.whl", hash = "sha256:f77bf36710d8b73a50b2dd155c97b870017ad21afe6ab300326b0371b3b05138", size = 28248, upload-time = "2025-04-02T08:25:07.678Z" }, -] - -[[package]] -name = "text-unidecode" -version = "1.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ab/e2/e9a00f0ccb71718418230718b3d900e71a5d16e701a3dae079a21e9cd8f8/text-unidecode-1.3.tar.gz", hash = "sha256:bad6603bb14d279193107714b288be206cac565dfa49aa5b105294dd5c4aab93", size = 76885, upload-time = "2019-08-30T21:36:45.405Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a6/a5/c0b6468d3824fe3fde30dbb5e1f687b291608f9473681bbf7dabbf5a87d7/text_unidecode-1.3-py2.py3-none-any.whl", hash = "sha256:1311f10e8b895935241623731c2ba64f4c455287888b18189350b67134a822e8", size = 78154, upload-time = "2019-08-30T21:37:03.543Z" }, -] - -[[package]] -name = "tiktoken" -version = "0.11.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "regex" }, - { name = "requests" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/a7/86/ad0155a37c4f310935d5ac0b1ccf9bdb635dcb906e0a9a26b616dd55825a/tiktoken-0.11.0.tar.gz", hash = "sha256:3c518641aee1c52247c2b97e74d8d07d780092af79d5911a6ab5e79359d9b06a", size = 37648, upload-time = "2025-08-08T23:58:08.495Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/8b/4d/c6a2e7dca2b4f2e9e0bfd62b3fe4f114322e2c028cfba905a72bc76ce479/tiktoken-0.11.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:8a9b517d6331d7103f8bef29ef93b3cca95fa766e293147fe7bacddf310d5917", size = 1059937, upload-time = "2025-08-08T23:57:28.57Z" }, - { url = "https://files.pythonhosted.org/packages/41/54/3739d35b9f94cb8dc7b0db2edca7192d5571606aa2369a664fa27e811804/tiktoken-0.11.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b4ddb1849e6bf0afa6cc1c5d809fb980ca240a5fffe585a04e119519758788c0", size = 999230, upload-time = "2025-08-08T23:57:30.241Z" }, - { url = "https://files.pythonhosted.org/packages/dd/f4/ec8d43338d28d53513004ebf4cd83732a135d11011433c58bf045890cc10/tiktoken-0.11.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:10331d08b5ecf7a780b4fe4d0281328b23ab22cdb4ff65e68d56caeda9940ecc", size = 1130076, upload-time = "2025-08-08T23:57:31.706Z" }, - { url = "https://files.pythonhosted.org/packages/94/80/fb0ada0a882cb453caf519a4bf0d117c2a3ee2e852c88775abff5413c176/tiktoken-0.11.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b062c82300341dc87e0258c69f79bed725f87e753c21887aea90d272816be882", size = 1183942, upload-time = "2025-08-08T23:57:33.142Z" }, - { url = "https://files.pythonhosted.org/packages/2f/e9/6c104355b463601719582823f3ea658bc3aa7c73d1b3b7553ebdc48468ce/tiktoken-0.11.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:195d84bec46169af3b1349a1495c151d37a0ff4cba73fd08282736be7f92cc6c", size = 1244705, upload-time = "2025-08-08T23:57:34.594Z" }, - { url = "https://files.pythonhosted.org/packages/94/75/eaa6068f47e8b3f0aab9e05177cce2cf5aa2cc0ca93981792e620d4d4117/tiktoken-0.11.0-cp310-cp310-win_amd64.whl", hash = "sha256:fe91581b0ecdd8783ce8cb6e3178f2260a3912e8724d2f2d49552b98714641a1", size = 884152, upload-time = "2025-08-08T23:57:36.18Z" }, - { url = "https://files.pythonhosted.org/packages/8a/91/912b459799a025d2842566fe1e902f7f50d54a1ce8a0f236ab36b5bd5846/tiktoken-0.11.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:4ae374c46afadad0f501046db3da1b36cd4dfbfa52af23c998773682446097cf", size = 1059743, upload-time = "2025-08-08T23:57:37.516Z" }, - { url = "https://files.pythonhosted.org/packages/8c/e9/6faa6870489ce64f5f75dcf91512bf35af5864583aee8fcb0dcb593121f5/tiktoken-0.11.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:25a512ff25dc6c85b58f5dd4f3d8c674dc05f96b02d66cdacf628d26a4e4866b", size = 999334, upload-time = "2025-08-08T23:57:38.595Z" }, - { url = "https://files.pythonhosted.org/packages/a1/3e/a05d1547cf7db9dc75d1461cfa7b556a3b48e0516ec29dfc81d984a145f6/tiktoken-0.11.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2130127471e293d385179c1f3f9cd445070c0772be73cdafb7cec9a3684c0458", size = 1129402, upload-time = "2025-08-08T23:57:39.627Z" }, - { url = "https://files.pythonhosted.org/packages/34/9a/db7a86b829e05a01fd4daa492086f708e0a8b53952e1dbc9d380d2b03677/tiktoken-0.11.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:21e43022bf2c33f733ea9b54f6a3f6b4354b909f5a73388fb1b9347ca54a069c", size = 1184046, upload-time = "2025-08-08T23:57:40.689Z" }, - { url = "https://files.pythonhosted.org/packages/9d/bb/52edc8e078cf062ed749248f1454e9e5cfd09979baadb830b3940e522015/tiktoken-0.11.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:adb4e308eb64380dc70fa30493e21c93475eaa11669dea313b6bbf8210bfd013", size = 1244691, upload-time = "2025-08-08T23:57:42.251Z" }, - { url = "https://files.pythonhosted.org/packages/60/d9/884b6cd7ae2570ecdcaffa02b528522b18fef1cbbfdbcaa73799807d0d3b/tiktoken-0.11.0-cp311-cp311-win_amd64.whl", hash = "sha256:ece6b76bfeeb61a125c44bbefdfccc279b5288e6007fbedc0d32bfec602df2f2", size = 884392, upload-time = "2025-08-08T23:57:43.628Z" }, - { url = "https://files.pythonhosted.org/packages/e7/9e/eceddeffc169fc75fe0fd4f38471309f11cb1906f9b8aa39be4f5817df65/tiktoken-0.11.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:fd9e6b23e860973cf9526544e220b223c60badf5b62e80a33509d6d40e6c8f5d", size = 1055199, upload-time = "2025-08-08T23:57:45.076Z" }, - { url = "https://files.pythonhosted.org/packages/4f/cf/5f02bfefffdc6b54e5094d2897bc80efd43050e5b09b576fd85936ee54bf/tiktoken-0.11.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6a76d53cee2da71ee2731c9caa747398762bda19d7f92665e882fef229cb0b5b", size = 996655, upload-time = "2025-08-08T23:57:46.304Z" }, - { url = "https://files.pythonhosted.org/packages/65/8e/c769b45ef379bc360c9978c4f6914c79fd432400a6733a8afc7ed7b0726a/tiktoken-0.11.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6ef72aab3ea240646e642413cb363b73869fed4e604dcfd69eec63dc54d603e8", size = 1128867, upload-time = "2025-08-08T23:57:47.438Z" }, - { url = "https://files.pythonhosted.org/packages/d5/2d/4d77f6feb9292bfdd23d5813e442b3bba883f42d0ac78ef5fdc56873f756/tiktoken-0.11.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f929255c705efec7a28bf515e29dc74220b2f07544a8c81b8d69e8efc4578bd", size = 1183308, upload-time = "2025-08-08T23:57:48.566Z" }, - { url = "https://files.pythonhosted.org/packages/7a/65/7ff0a65d3bb0fc5a1fb6cc71b03e0f6e71a68c5eea230d1ff1ba3fd6df49/tiktoken-0.11.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:61f1d15822e4404953d499fd1dcc62817a12ae9fb1e4898033ec8fe3915fdf8e", size = 1244301, upload-time = "2025-08-08T23:57:49.642Z" }, - { url = "https://files.pythonhosted.org/packages/f5/6e/5b71578799b72e5bdcef206a214c3ce860d999d579a3b56e74a6c8989ee2/tiktoken-0.11.0-cp312-cp312-win_amd64.whl", hash = "sha256:45927a71ab6643dfd3ef57d515a5db3d199137adf551f66453be098502838b0f", size = 884282, upload-time = "2025-08-08T23:57:50.759Z" }, - { url = "https://files.pythonhosted.org/packages/cc/cd/a9034bcee638716d9310443818d73c6387a6a96db93cbcb0819b77f5b206/tiktoken-0.11.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:a5f3f25ffb152ee7fec78e90a5e5ea5b03b4ea240beed03305615847f7a6ace2", size = 1055339, upload-time = "2025-08-08T23:57:51.802Z" }, - { url = "https://files.pythonhosted.org/packages/f1/91/9922b345f611b4e92581f234e64e9661e1c524875c8eadd513c4b2088472/tiktoken-0.11.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:7dc6e9ad16a2a75b4c4be7208055a1f707c9510541d94d9cc31f7fbdc8db41d8", size = 997080, upload-time = "2025-08-08T23:57:53.442Z" }, - { url = "https://files.pythonhosted.org/packages/d0/9d/49cd047c71336bc4b4af460ac213ec1c457da67712bde59b892e84f1859f/tiktoken-0.11.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5a0517634d67a8a48fd4a4ad73930c3022629a85a217d256a6e9b8b47439d1e4", size = 1128501, upload-time = "2025-08-08T23:57:54.808Z" }, - { url = "https://files.pythonhosted.org/packages/52/d5/a0dcdb40dd2ea357e83cb36258967f0ae96f5dd40c722d6e382ceee6bba9/tiktoken-0.11.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7fb4effe60574675118b73c6fbfd3b5868e5d7a1f570d6cc0d18724b09ecf318", size = 1182743, upload-time = "2025-08-08T23:57:56.307Z" }, - { url = "https://files.pythonhosted.org/packages/3b/17/a0fc51aefb66b7b5261ca1314afa83df0106b033f783f9a7bcbe8e741494/tiktoken-0.11.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:94f984c9831fd32688aef4348803b0905d4ae9c432303087bae370dc1381a2b8", size = 1244057, upload-time = "2025-08-08T23:57:57.628Z" }, - { url = "https://files.pythonhosted.org/packages/50/79/bcf350609f3a10f09fe4fc207f132085e497fdd3612f3925ab24d86a0ca0/tiktoken-0.11.0-cp313-cp313-win_amd64.whl", hash = "sha256:2177ffda31dec4023356a441793fed82f7af5291120751dee4d696414f54db0c", size = 883901, upload-time = "2025-08-08T23:57:59.359Z" }, -] - -[[package]] -name = "tomli" -version = "2.2.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/18/87/302344fed471e44a87289cf4967697d07e532f2421fdaf868a303cbae4ff/tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff", size = 17175, upload-time = "2024-11-27T22:38:36.873Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/43/ca/75707e6efa2b37c77dadb324ae7d9571cb424e61ea73fad7c56c2d14527f/tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249", size = 131077, upload-time = "2024-11-27T22:37:54.956Z" }, - { url = "https://files.pythonhosted.org/packages/c7/16/51ae563a8615d472fdbffc43a3f3d46588c264ac4f024f63f01283becfbb/tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6", size = 123429, upload-time = "2024-11-27T22:37:56.698Z" }, - { url = "https://files.pythonhosted.org/packages/f1/dd/4f6cd1e7b160041db83c694abc78e100473c15d54620083dbd5aae7b990e/tomli-2.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ece47d672db52ac607a3d9599a9d48dcb2f2f735c6c2d1f34130085bb12b112a", size = 226067, upload-time = "2024-11-27T22:37:57.63Z" }, - { url = "https://files.pythonhosted.org/packages/a9/6b/c54ede5dc70d648cc6361eaf429304b02f2871a345bbdd51e993d6cdf550/tomli-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6972ca9c9cc9f0acaa56a8ca1ff51e7af152a9f87fb64623e31d5c83700080ee", size = 236030, upload-time = "2024-11-27T22:37:59.344Z" }, - { url = "https://files.pythonhosted.org/packages/1f/47/999514fa49cfaf7a92c805a86c3c43f4215621855d151b61c602abb38091/tomli-2.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c954d2250168d28797dd4e3ac5cf812a406cd5a92674ee4c8f123c889786aa8e", size = 240898, upload-time = "2024-11-27T22:38:00.429Z" }, - { url = "https://files.pythonhosted.org/packages/73/41/0a01279a7ae09ee1573b423318e7934674ce06eb33f50936655071d81a24/tomli-2.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8dd28b3e155b80f4d54beb40a441d366adcfe740969820caf156c019fb5c7ec4", size = 229894, upload-time = "2024-11-27T22:38:02.094Z" }, - { url = "https://files.pythonhosted.org/packages/55/18/5d8bc5b0a0362311ce4d18830a5d28943667599a60d20118074ea1b01bb7/tomli-2.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e59e304978767a54663af13c07b3d1af22ddee3bb2fb0618ca1593e4f593a106", size = 245319, upload-time = "2024-11-27T22:38:03.206Z" }, - { url = "https://files.pythonhosted.org/packages/92/a3/7ade0576d17f3cdf5ff44d61390d4b3febb8a9fc2b480c75c47ea048c646/tomli-2.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:33580bccab0338d00994d7f16f4c4ec25b776af3ffaac1ed74e0b3fc95e885a8", size = 238273, upload-time = "2024-11-27T22:38:04.217Z" }, - { url = "https://files.pythonhosted.org/packages/72/6f/fa64ef058ac1446a1e51110c375339b3ec6be245af9d14c87c4a6412dd32/tomli-2.2.1-cp311-cp311-win32.whl", hash = "sha256:465af0e0875402f1d226519c9904f37254b3045fc5084697cefb9bdde1ff99ff", size = 98310, upload-time = "2024-11-27T22:38:05.908Z" }, - { url = "https://files.pythonhosted.org/packages/6a/1c/4a2dcde4a51b81be3530565e92eda625d94dafb46dbeb15069df4caffc34/tomli-2.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:2d0f2fdd22b02c6d81637a3c95f8cd77f995846af7414c5c4b8d0545afa1bc4b", size = 108309, upload-time = "2024-11-27T22:38:06.812Z" }, - { url = "https://files.pythonhosted.org/packages/52/e1/f8af4c2fcde17500422858155aeb0d7e93477a0d59a98e56cbfe75070fd0/tomli-2.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:4a8f6e44de52d5e6c657c9fe83b562f5f4256d8ebbfe4ff922c495620a7f6cea", size = 132762, upload-time = "2024-11-27T22:38:07.731Z" }, - { url = "https://files.pythonhosted.org/packages/03/b8/152c68bb84fc00396b83e7bbddd5ec0bd3dd409db4195e2a9b3e398ad2e3/tomli-2.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8d57ca8095a641b8237d5b079147646153d22552f1c637fd3ba7f4b0b29167a8", size = 123453, upload-time = "2024-11-27T22:38:09.384Z" }, - { url = "https://files.pythonhosted.org/packages/c8/d6/fc9267af9166f79ac528ff7e8c55c8181ded34eb4b0e93daa767b8841573/tomli-2.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4e340144ad7ae1533cb897d406382b4b6fede8890a03738ff1683af800d54192", size = 233486, upload-time = "2024-11-27T22:38:10.329Z" }, - { url = "https://files.pythonhosted.org/packages/5c/51/51c3f2884d7bab89af25f678447ea7d297b53b5a3b5730a7cb2ef6069f07/tomli-2.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:db2b95f9de79181805df90bedc5a5ab4c165e6ec3fe99f970d0e302f384ad222", size = 242349, upload-time = "2024-11-27T22:38:11.443Z" }, - { url = "https://files.pythonhosted.org/packages/ab/df/bfa89627d13a5cc22402e441e8a931ef2108403db390ff3345c05253935e/tomli-2.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:40741994320b232529c802f8bc86da4e1aa9f413db394617b9a256ae0f9a7f77", size = 252159, upload-time = "2024-11-27T22:38:13.099Z" }, - { url = "https://files.pythonhosted.org/packages/9e/6e/fa2b916dced65763a5168c6ccb91066f7639bdc88b48adda990db10c8c0b/tomli-2.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:400e720fe168c0f8521520190686ef8ef033fb19fc493da09779e592861b78c6", size = 237243, upload-time = "2024-11-27T22:38:14.766Z" }, - { url = "https://files.pythonhosted.org/packages/b4/04/885d3b1f650e1153cbb93a6a9782c58a972b94ea4483ae4ac5cedd5e4a09/tomli-2.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:02abe224de6ae62c19f090f68da4e27b10af2b93213d36cf44e6e1c5abd19fdd", size = 259645, upload-time = "2024-11-27T22:38:15.843Z" }, - { url = "https://files.pythonhosted.org/packages/9c/de/6b432d66e986e501586da298e28ebeefd3edc2c780f3ad73d22566034239/tomli-2.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b82ebccc8c8a36f2094e969560a1b836758481f3dc360ce9a3277c65f374285e", size = 244584, upload-time = "2024-11-27T22:38:17.645Z" }, - { url = "https://files.pythonhosted.org/packages/1c/9a/47c0449b98e6e7d1be6cbac02f93dd79003234ddc4aaab6ba07a9a7482e2/tomli-2.2.1-cp312-cp312-win32.whl", hash = "sha256:889f80ef92701b9dbb224e49ec87c645ce5df3fa2cc548664eb8a25e03127a98", size = 98875, upload-time = "2024-11-27T22:38:19.159Z" }, - { url = "https://files.pythonhosted.org/packages/ef/60/9b9638f081c6f1261e2688bd487625cd1e660d0a85bd469e91d8db969734/tomli-2.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:7fc04e92e1d624a4a63c76474610238576942d6b8950a2d7f908a340494e67e4", size = 109418, upload-time = "2024-11-27T22:38:20.064Z" }, - { url = "https://files.pythonhosted.org/packages/04/90/2ee5f2e0362cb8a0b6499dc44f4d7d48f8fff06d28ba46e6f1eaa61a1388/tomli-2.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f4039b9cbc3048b2416cc57ab3bda989a6fcf9b36cf8937f01a6e731b64f80d7", size = 132708, upload-time = "2024-11-27T22:38:21.659Z" }, - { url = "https://files.pythonhosted.org/packages/c0/ec/46b4108816de6b385141f082ba99e315501ccd0a2ea23db4a100dd3990ea/tomli-2.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:286f0ca2ffeeb5b9bd4fcc8d6c330534323ec51b2f52da063b11c502da16f30c", size = 123582, upload-time = "2024-11-27T22:38:22.693Z" }, - { url = "https://files.pythonhosted.org/packages/a0/bd/b470466d0137b37b68d24556c38a0cc819e8febe392d5b199dcd7f578365/tomli-2.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a92ef1a44547e894e2a17d24e7557a5e85a9e1d0048b0b5e7541f76c5032cb13", size = 232543, upload-time = "2024-11-27T22:38:24.367Z" }, - { url = "https://files.pythonhosted.org/packages/d9/e5/82e80ff3b751373f7cead2815bcbe2d51c895b3c990686741a8e56ec42ab/tomli-2.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9316dc65bed1684c9a98ee68759ceaed29d229e985297003e494aa825ebb0281", size = 241691, upload-time = "2024-11-27T22:38:26.081Z" }, - { url = "https://files.pythonhosted.org/packages/05/7e/2a110bc2713557d6a1bfb06af23dd01e7dde52b6ee7dadc589868f9abfac/tomli-2.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e85e99945e688e32d5a35c1ff38ed0b3f41f43fad8df0bdf79f72b2ba7bc5272", size = 251170, upload-time = "2024-11-27T22:38:27.921Z" }, - { url = "https://files.pythonhosted.org/packages/64/7b/22d713946efe00e0adbcdfd6d1aa119ae03fd0b60ebed51ebb3fa9f5a2e5/tomli-2.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ac065718db92ca818f8d6141b5f66369833d4a80a9d74435a268c52bdfa73140", size = 236530, upload-time = "2024-11-27T22:38:29.591Z" }, - { url = "https://files.pythonhosted.org/packages/38/31/3a76f67da4b0cf37b742ca76beaf819dca0ebef26d78fc794a576e08accf/tomli-2.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:d920f33822747519673ee656a4b6ac33e382eca9d331c87770faa3eef562aeb2", size = 258666, upload-time = "2024-11-27T22:38:30.639Z" }, - { url = "https://files.pythonhosted.org/packages/07/10/5af1293da642aded87e8a988753945d0cf7e00a9452d3911dd3bb354c9e2/tomli-2.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a198f10c4d1b1375d7687bc25294306e551bf1abfa4eace6650070a5c1ae2744", size = 243954, upload-time = "2024-11-27T22:38:31.702Z" }, - { url = "https://files.pythonhosted.org/packages/5b/b9/1ed31d167be802da0fc95020d04cd27b7d7065cc6fbefdd2f9186f60d7bd/tomli-2.2.1-cp313-cp313-win32.whl", hash = "sha256:d3f5614314d758649ab2ab3a62d4f2004c825922f9e370b29416484086b264ec", size = 98724, upload-time = "2024-11-27T22:38:32.837Z" }, - { url = "https://files.pythonhosted.org/packages/c7/32/b0963458706accd9afcfeb867c0f9175a741bf7b19cd424230714d722198/tomli-2.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:a38aa0308e754b0e3c67e344754dff64999ff9b513e691d0e786265c93583c69", size = 109383, upload-time = "2024-11-27T22:38:34.455Z" }, - { url = "https://files.pythonhosted.org/packages/6e/c2/61d3e0f47e2b74ef40a68b9e6ad5984f6241a942f7cd3bbfbdbd03861ea9/tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc", size = 14257, upload-time = "2024-11-27T22:38:35.385Z" }, -] - -[[package]] -name = "tqdm" -version = "4.67.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "colorama", marker = "sys_platform == 'win32'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/a8/4b/29b4ef32e036bb34e4ab51796dd745cdba7ed47ad142a9f4a1eb8e0c744d/tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2", size = 169737, upload-time = "2024-11-24T20:12:22.481Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d0/30/dc54f88dd4a2b5dc8a0279bdd7270e735851848b762aeb1c1184ed1f6b14/tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2", size = 78540, upload-time = "2024-11-24T20:12:19.698Z" }, -] - -[[package]] -name = "twine" -version = "6.2.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "id" }, - { name = "keyring", marker = "platform_machine != 'ppc64le' and platform_machine != 's390x'" }, - { name = "packaging" }, - { name = "readme-renderer" }, - { name = "requests" }, - { name = "requests-toolbelt" }, - { name = "rfc3986" }, - { name = "rich" }, - { name = "urllib3", version = "1.26.20", source = { registry = "https://pypi.org/simple" }, marker = "platform_python_implementation == 'PyPy'" }, - { name = "urllib3", version = "2.5.0", source = { registry = "https://pypi.org/simple" }, marker = "platform_python_implementation != 'PyPy'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/e0/a8/949edebe3a82774c1ec34f637f5dd82d1cf22c25e963b7d63771083bbee5/twine-6.2.0.tar.gz", hash = "sha256:e5ed0d2fd70c9959770dce51c8f39c8945c574e18173a7b81802dab51b4b75cf", size = 172262, upload-time = "2025-09-04T15:43:17.255Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/3a/7a/882d99539b19b1490cac5d77c67338d126e4122c8276bf640e411650c830/twine-6.2.0-py3-none-any.whl", hash = "sha256:418ebf08ccda9a8caaebe414433b0ba5e25eb5e4a927667122fbe8f829f985d8", size = 42727, upload-time = "2025-09-04T15:43:15.994Z" }, -] - -[[package]] -name = "typing-extensions" -version = "4.15.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/72/94/1a15dd82efb362ac84269196e94cf00f187f7ed21c242792a923cdb1c61f/typing_extensions-4.15.0.tar.gz", hash = "sha256:0cea48d173cc12fa28ecabc3b837ea3cf6f38c6d1136f85cbaaf598984861466", size = 109391, upload-time = "2025-08-25T13:49:26.313Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl", hash = "sha256:f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548", size = 44614, upload-time = "2025-08-25T13:49:24.86Z" }, -] - -[[package]] -name = "typing-inspection" -version = "0.4.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/f8/b1/0c11f5058406b3af7609f121aaa6b609744687f1d158b3c3a5bf4cc94238/typing_inspection-0.4.1.tar.gz", hash = "sha256:6ae134cc0203c33377d43188d4064e9b357dba58cff3185f22924610e70a9d28", size = 75726, upload-time = "2025-05-21T18:55:23.885Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/17/69/cd203477f944c353c31bade965f880aa1061fd6bf05ded0726ca845b6ff7/typing_inspection-0.4.1-py3-none-any.whl", hash = "sha256:389055682238f53b04f7badcb49b989835495a96700ced5dab2d8feae4b26f51", size = 14552, upload-time = "2025-05-21T18:55:22.152Z" }, -] - -[[package]] -name = "urllib3" -version = "1.26.20" -source = { registry = "https://pypi.org/simple" } -resolution-markers = [ - "platform_python_implementation == 'PyPy'", -] -sdist = { url = "https://files.pythonhosted.org/packages/e4/e8/6ff5e6bc22095cfc59b6ea711b687e2b7ed4bdb373f7eeec370a97d7392f/urllib3-1.26.20.tar.gz", hash = "sha256:40c2dc0c681e47eb8f90e7e27bf6ff7df2e677421fd46756da1161c39ca70d32", size = 307380, upload-time = "2024-08-29T15:43:11.37Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/33/cf/8435d5a7159e2a9c83a95896ed596f68cf798005fe107cc655b5c5c14704/urllib3-1.26.20-py2.py3-none-any.whl", hash = "sha256:0ed14ccfbf1c30a9072c7ca157e4319b70d65f623e91e7b32fadb2853431016e", size = 144225, upload-time = "2024-08-29T15:43:08.921Z" }, -] - -[[package]] -name = "urllib3" -version = "2.5.0" -source = { registry = "https://pypi.org/simple" } -resolution-markers = [ - "platform_python_implementation != 'PyPy'", -] -sdist = { url = "https://files.pythonhosted.org/packages/15/22/9ee70a2574a4f4599c47dd506532914ce044817c7752a79b6a51286319bc/urllib3-2.5.0.tar.gz", hash = "sha256:3fc47733c7e419d4bc3f6b3dc2b4f890bb743906a30d56ba4a5bfa4bbff92760", size = 393185, upload-time = "2025-06-18T14:07:41.644Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a7/c2/fe1e52489ae3122415c51f387e221dd0773709bad6c6cdaa599e8a2c5185/urllib3-2.5.0-py3-none-any.whl", hash = "sha256:e6b01673c0fa6a13e374b50871808eb3bf7046c4b125b216f6bf1cc604cff0dc", size = 129795, upload-time = "2025-06-18T14:07:40.39Z" }, -] - -[[package]] -name = "uuid-utils" -version = "0.14.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/57/7c/3a926e847516e67bc6838634f2e54e24381105b4e80f9338dc35cca0086b/uuid_utils-0.14.0.tar.gz", hash = "sha256:fc5bac21e9933ea6c590433c11aa54aaca599f690c08069e364eb13a12f670b4", size = 22072, upload-time = "2026-01-20T20:37:15.729Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a7/42/42d003f4a99ddc901eef2fd41acb3694163835e037fb6dde79ad68a72342/uuid_utils-0.14.0-cp39-abi3-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:f6695c0bed8b18a904321e115afe73b34444bc8451d0ce3244a1ec3b84deb0e5", size = 601786, upload-time = "2026-01-20T20:37:09.843Z" }, - { url = "https://files.pythonhosted.org/packages/96/e6/775dfb91f74b18f7207e3201eb31ee666d286579990dc69dd50db2d92813/uuid_utils-0.14.0-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:4f0a730bbf2d8bb2c11b93e1005e91769f2f533fa1125ed1f00fd15b6fcc732b", size = 303943, upload-time = "2026-01-20T20:37:18.767Z" }, - { url = "https://files.pythonhosted.org/packages/17/82/ea5f5e85560b08a1f30cdc65f75e76494dc7aba9773f679e7eaa27370229/uuid_utils-0.14.0-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:40ce3fd1a4fdedae618fc3edc8faf91897012469169d600133470f49fd699ed3", size = 340467, upload-time = "2026-01-20T20:37:11.794Z" }, - { url = "https://files.pythonhosted.org/packages/ca/33/54b06415767f4569882e99b6470c6c8eeb97422686a6d432464f9967fd91/uuid_utils-0.14.0-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:09ae4a98416a440e78f7d9543d11b11cae4bab538b7ed94ec5da5221481748f2", size = 346333, upload-time = "2026-01-20T20:37:12.818Z" }, - { url = "https://files.pythonhosted.org/packages/cb/10/a6bce636b8f95e65dc84bf4a58ce8205b8e0a2a300a38cdbc83a3f763d27/uuid_utils-0.14.0-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:971e8c26b90d8ae727e7f2ac3ee23e265971d448b3672882f2eb44828b2b8c3e", size = 470859, upload-time = "2026-01-20T20:37:01.512Z" }, - { url = "https://files.pythonhosted.org/packages/8a/27/84121c51ea72f013f0e03d0886bcdfa96b31c9b83c98300a7bd5cc4fa191/uuid_utils-0.14.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d5cde1fa82804a8f9d2907b7aec2009d440062c63f04abbdb825fce717a5e860", size = 341988, upload-time = "2026-01-20T20:37:22.881Z" }, - { url = "https://files.pythonhosted.org/packages/90/a4/01c1c7af5e6a44f20b40183e8dac37d6ed83e7dc9e8df85370a15959b804/uuid_utils-0.14.0-cp39-abi3-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c7343862a2359e0bd48a7f3dfb5105877a1728677818bb694d9f40703264a2db", size = 365784, upload-time = "2026-01-20T20:37:10.808Z" }, - { url = "https://files.pythonhosted.org/packages/04/f0/65ee43ec617b8b6b1bf2a5aecd56a069a08cca3d9340c1de86024331bde3/uuid_utils-0.14.0-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:c51e4818fdb08ccec12dc7083a01f49507b4608770a0ab22368001685d59381b", size = 523750, upload-time = "2026-01-20T20:37:06.152Z" }, - { url = "https://files.pythonhosted.org/packages/95/d3/6bf503e3f135a5dfe705a65e6f89f19bccd55ac3fb16cb5d3ec5ba5388b8/uuid_utils-0.14.0-cp39-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:181bbcccb6f93d80a8504b5bd47b311a1c31395139596edbc47b154b0685b533", size = 615818, upload-time = "2026-01-20T20:37:21.816Z" }, - { url = "https://files.pythonhosted.org/packages/df/6c/99937dd78d07f73bba831c8dc9469dfe4696539eba2fc269ae1b92752f9e/uuid_utils-0.14.0-cp39-abi3-musllinux_1_2_i686.whl", hash = "sha256:5c8ae96101c3524ba8dbf762b6f05e9e9d896544786c503a727c5bf5cb9af1a7", size = 580831, upload-time = "2026-01-20T20:37:19.691Z" }, - { url = "https://files.pythonhosted.org/packages/44/fa/bbc9e2c25abd09a293b9b097a0d8fc16acd6a92854f0ec080f1ea7ad8bb3/uuid_utils-0.14.0-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:00ac3c6edfdaff7e1eed041f4800ae09a3361287be780d7610a90fdcde9befdc", size = 546333, upload-time = "2026-01-20T20:37:03.117Z" }, - { url = "https://files.pythonhosted.org/packages/e7/9b/e5e99b324b1b5f0c62882230455786df0bc66f67eff3b452447e703f45d2/uuid_utils-0.14.0-cp39-abi3-win32.whl", hash = "sha256:ec2fd80adf8e0e6589d40699e6f6df94c93edcc16dd999be0438dd007c77b151", size = 177319, upload-time = "2026-01-20T20:37:04.208Z" }, - { url = "https://files.pythonhosted.org/packages/d3/28/2c7d417ea483b6ff7820c948678fdf2ac98899dc7e43bb15852faa95acaf/uuid_utils-0.14.0-cp39-abi3-win_amd64.whl", hash = "sha256:efe881eb43a5504fad922644cb93d725fd8a6a6d949bd5a4b4b7d1a1587c7fd1", size = 182566, upload-time = "2026-01-20T20:37:16.868Z" }, - { url = "https://files.pythonhosted.org/packages/b8/86/49e4bdda28e962fbd7266684171ee29b3d92019116971d58783e51770745/uuid_utils-0.14.0-cp39-abi3-win_arm64.whl", hash = "sha256:32b372b8fd4ebd44d3a219e093fe981af4afdeda2994ee7db208ab065cfcd080", size = 182809, upload-time = "2026-01-20T20:37:05.139Z" }, - { url = "https://files.pythonhosted.org/packages/f1/03/1f1146e32e94d1f260dfabc81e1649102083303fb4ad549775c943425d9a/uuid_utils-0.14.0-pp311-pypy311_pp73-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:762e8d67992ac4d2454e24a141a1c82142b5bde10409818c62adbe9924ebc86d", size = 587430, upload-time = "2026-01-20T20:37:24.998Z" }, - { url = "https://files.pythonhosted.org/packages/87/ba/d5a7469362594d885fd9219fe9e851efbe65101d3ef1ef25ea321d7ce841/uuid_utils-0.14.0-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:40be5bf0b13aa849d9062abc86c198be6a25ff35316ce0b89fc25f3bac6d525e", size = 298106, upload-time = "2026-01-20T20:37:23.896Z" }, - { url = "https://files.pythonhosted.org/packages/8a/11/3dafb2a5502586f59fd49e93f5802cd5face82921b3a0f3abb5f357cb879/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:191a90a6f3940d1b7322b6e6cceff4dd533c943659e0a15f788674407856a515", size = 333423, upload-time = "2026-01-20T20:37:17.828Z" }, - { url = "https://files.pythonhosted.org/packages/7c/f2/c8987663f0cdcf4d717a36d85b5db2a5589df0a4e129aa10f16f4380ef48/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4aa4525f4ad82f9d9c842f9a3703f1539c1808affbaec07bb1b842f6b8b96aa5", size = 338659, upload-time = "2026-01-20T20:37:14.286Z" }, - { url = "https://files.pythonhosted.org/packages/d1/c8/929d81665d83f0b2ffaecb8e66c3091a50f62c7cb5b65e678bd75a96684e/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cdbd82ff20147461caefc375551595ecf77ebb384e46267f128aca45a0f2cdfc", size = 467029, upload-time = "2026-01-20T20:37:08.277Z" }, - { url = "https://files.pythonhosted.org/packages/8e/a0/27d7daa1bfed7163f4ccaf52d7d2f4ad7bb1002a85b45077938b91ee584f/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eff57e8a5d540006ce73cf0841a643d445afe78ba12e75ac53a95ca2924a56be", size = 333298, upload-time = "2026-01-20T20:37:07.271Z" }, - { url = "https://files.pythonhosted.org/packages/63/d4/acad86ce012b42ce18a12f31ee2aa3cbeeb98664f865f05f68c882945913/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3fd9112ca96978361201e669729784f26c71fecc9c13a7f8a07162c31bd4d1e2", size = 359217, upload-time = "2026-01-20T20:36:59.687Z" }, -] - -[[package]] -name = "vcrpy" -version = "7.0.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "pyyaml" }, - { name = "urllib3", version = "1.26.20", source = { registry = "https://pypi.org/simple" }, marker = "platform_python_implementation == 'PyPy'" }, - { name = "urllib3", version = "2.5.0", source = { registry = "https://pypi.org/simple" }, marker = "platform_python_implementation != 'PyPy'" }, - { name = "wrapt" }, - { name = "yarl" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/25/d3/856e06184d4572aada1dd559ddec3bedc46df1f2edc5ab2c91121a2cccdb/vcrpy-7.0.0.tar.gz", hash = "sha256:176391ad0425edde1680c5b20738ea3dc7fb942520a48d2993448050986b3a50", size = 85502, upload-time = "2024-12-31T00:07:57.894Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/13/5d/1f15b252890c968d42b348d1e9b0aa12d5bf3e776704178ec37cceccdb63/vcrpy-7.0.0-py2.py3-none-any.whl", hash = "sha256:55791e26c18daa363435054d8b35bd41a4ac441b6676167635d1b37a71dbe124", size = 42321, upload-time = "2024-12-31T00:07:55.277Z" }, -] - -[[package]] -name = "virtualenv" -version = "20.34.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "distlib" }, - { name = "filelock" }, - { name = "platformdirs" }, - { name = "typing-extensions", marker = "python_full_version < '3.11'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/1c/14/37fcdba2808a6c615681cd216fecae00413c9dab44fb2e57805ecf3eaee3/virtualenv-20.34.0.tar.gz", hash = "sha256:44815b2c9dee7ed86e387b842a84f20b93f7f417f95886ca1996a72a4138eb1a", size = 6003808, upload-time = "2025-08-13T14:24:07.464Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/76/06/04c8e804f813cf972e3262f3f8584c232de64f0cde9f703b46cf53a45090/virtualenv-20.34.0-py3-none-any.whl", hash = "sha256:341f5afa7eee943e4984a9207c025feedd768baff6753cd660c857ceb3e36026", size = 5983279, upload-time = "2025-08-13T14:24:05.111Z" }, -] - -[[package]] -name = "wrapt" -version = "1.17.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/95/8f/aeb76c5b46e273670962298c23e7ddde79916cb74db802131d49a85e4b7d/wrapt-1.17.3.tar.gz", hash = "sha256:f66eb08feaa410fe4eebd17f2a2c8e2e46d3476e9f8c783daa8e09e0faa666d0", size = 55547, upload-time = "2025-08-12T05:53:21.714Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/3f/23/bb82321b86411eb51e5a5db3fb8f8032fd30bd7c2d74bfe936136b2fa1d6/wrapt-1.17.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:88bbae4d40d5a46142e70d58bf664a89b6b4befaea7b2ecc14e03cedb8e06c04", size = 53482, upload-time = "2025-08-12T05:51:44.467Z" }, - { url = "https://files.pythonhosted.org/packages/45/69/f3c47642b79485a30a59c63f6d739ed779fb4cc8323205d047d741d55220/wrapt-1.17.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e6b13af258d6a9ad602d57d889f83b9d5543acd471eee12eb51f5b01f8eb1bc2", size = 38676, upload-time = "2025-08-12T05:51:32.636Z" }, - { url = "https://files.pythonhosted.org/packages/d1/71/e7e7f5670c1eafd9e990438e69d8fb46fa91a50785332e06b560c869454f/wrapt-1.17.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:fd341868a4b6714a5962c1af0bd44f7c404ef78720c7de4892901e540417111c", size = 38957, upload-time = "2025-08-12T05:51:54.655Z" }, - { url = "https://files.pythonhosted.org/packages/de/17/9f8f86755c191d6779d7ddead1a53c7a8aa18bccb7cea8e7e72dfa6a8a09/wrapt-1.17.3-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:f9b2601381be482f70e5d1051a5965c25fb3625455a2bf520b5a077b22afb775", size = 81975, upload-time = "2025-08-12T05:52:30.109Z" }, - { url = "https://files.pythonhosted.org/packages/f2/15/dd576273491f9f43dd09fce517f6c2ce6eb4fe21681726068db0d0467096/wrapt-1.17.3-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:343e44b2a8e60e06a7e0d29c1671a0d9951f59174f3709962b5143f60a2a98bd", size = 83149, upload-time = "2025-08-12T05:52:09.316Z" }, - { url = "https://files.pythonhosted.org/packages/0c/c4/5eb4ce0d4814521fee7aa806264bf7a114e748ad05110441cd5b8a5c744b/wrapt-1.17.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:33486899acd2d7d3066156b03465b949da3fd41a5da6e394ec49d271baefcf05", size = 82209, upload-time = "2025-08-12T05:52:10.331Z" }, - { url = "https://files.pythonhosted.org/packages/31/4b/819e9e0eb5c8dc86f60dfc42aa4e2c0d6c3db8732bce93cc752e604bb5f5/wrapt-1.17.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:e6f40a8aa5a92f150bdb3e1c44b7e98fb7113955b2e5394122fa5532fec4b418", size = 81551, upload-time = "2025-08-12T05:52:31.137Z" }, - { url = "https://files.pythonhosted.org/packages/f8/83/ed6baf89ba3a56694700139698cf703aac9f0f9eb03dab92f57551bd5385/wrapt-1.17.3-cp310-cp310-win32.whl", hash = "sha256:a36692b8491d30a8c75f1dfee65bef119d6f39ea84ee04d9f9311f83c5ad9390", size = 36464, upload-time = "2025-08-12T05:53:01.204Z" }, - { url = "https://files.pythonhosted.org/packages/2f/90/ee61d36862340ad7e9d15a02529df6b948676b9a5829fd5e16640156627d/wrapt-1.17.3-cp310-cp310-win_amd64.whl", hash = "sha256:afd964fd43b10c12213574db492cb8f73b2f0826c8df07a68288f8f19af2ebe6", size = 38748, upload-time = "2025-08-12T05:53:00.209Z" }, - { url = "https://files.pythonhosted.org/packages/bd/c3/cefe0bd330d389c9983ced15d326f45373f4073c9f4a8c2f99b50bfea329/wrapt-1.17.3-cp310-cp310-win_arm64.whl", hash = "sha256:af338aa93554be859173c39c85243970dc6a289fa907402289eeae7543e1ae18", size = 36810, upload-time = "2025-08-12T05:52:51.906Z" }, - { url = "https://files.pythonhosted.org/packages/52/db/00e2a219213856074a213503fdac0511203dceefff26e1daa15250cc01a0/wrapt-1.17.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:273a736c4645e63ac582c60a56b0acb529ef07f78e08dc6bfadf6a46b19c0da7", size = 53482, upload-time = "2025-08-12T05:51:45.79Z" }, - { url = "https://files.pythonhosted.org/packages/5e/30/ca3c4a5eba478408572096fe9ce36e6e915994dd26a4e9e98b4f729c06d9/wrapt-1.17.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:5531d911795e3f935a9c23eb1c8c03c211661a5060aab167065896bbf62a5f85", size = 38674, upload-time = "2025-08-12T05:51:34.629Z" }, - { url = "https://files.pythonhosted.org/packages/31/25/3e8cc2c46b5329c5957cec959cb76a10718e1a513309c31399a4dad07eb3/wrapt-1.17.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:0610b46293c59a3adbae3dee552b648b984176f8562ee0dba099a56cfbe4df1f", size = 38959, upload-time = "2025-08-12T05:51:56.074Z" }, - { url = "https://files.pythonhosted.org/packages/5d/8f/a32a99fc03e4b37e31b57cb9cefc65050ea08147a8ce12f288616b05ef54/wrapt-1.17.3-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:b32888aad8b6e68f83a8fdccbf3165f5469702a7544472bdf41f582970ed3311", size = 82376, upload-time = "2025-08-12T05:52:32.134Z" }, - { url = "https://files.pythonhosted.org/packages/31/57/4930cb8d9d70d59c27ee1332a318c20291749b4fba31f113c2f8ac49a72e/wrapt-1.17.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8cccf4f81371f257440c88faed6b74f1053eef90807b77e31ca057b2db74edb1", size = 83604, upload-time = "2025-08-12T05:52:11.663Z" }, - { url = "https://files.pythonhosted.org/packages/a8/f3/1afd48de81d63dd66e01b263a6fbb86e1b5053b419b9b33d13e1f6d0f7d0/wrapt-1.17.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:d8a210b158a34164de8bb68b0e7780041a903d7b00c87e906fb69928bf7890d5", size = 82782, upload-time = "2025-08-12T05:52:12.626Z" }, - { url = "https://files.pythonhosted.org/packages/1e/d7/4ad5327612173b144998232f98a85bb24b60c352afb73bc48e3e0d2bdc4e/wrapt-1.17.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:79573c24a46ce11aab457b472efd8d125e5a51da2d1d24387666cd85f54c05b2", size = 82076, upload-time = "2025-08-12T05:52:33.168Z" }, - { url = "https://files.pythonhosted.org/packages/bb/59/e0adfc831674a65694f18ea6dc821f9fcb9ec82c2ce7e3d73a88ba2e8718/wrapt-1.17.3-cp311-cp311-win32.whl", hash = "sha256:c31eebe420a9a5d2887b13000b043ff6ca27c452a9a22fa71f35f118e8d4bf89", size = 36457, upload-time = "2025-08-12T05:53:03.936Z" }, - { url = "https://files.pythonhosted.org/packages/83/88/16b7231ba49861b6f75fc309b11012ede4d6b0a9c90969d9e0db8d991aeb/wrapt-1.17.3-cp311-cp311-win_amd64.whl", hash = "sha256:0b1831115c97f0663cb77aa27d381237e73ad4f721391a9bfb2fe8bc25fa6e77", size = 38745, upload-time = "2025-08-12T05:53:02.885Z" }, - { url = "https://files.pythonhosted.org/packages/9a/1e/c4d4f3398ec073012c51d1c8d87f715f56765444e1a4b11e5180577b7e6e/wrapt-1.17.3-cp311-cp311-win_arm64.whl", hash = "sha256:5a7b3c1ee8265eb4c8f1b7d29943f195c00673f5ab60c192eba2d4a7eae5f46a", size = 36806, upload-time = "2025-08-12T05:52:53.368Z" }, - { url = "https://files.pythonhosted.org/packages/9f/41/cad1aba93e752f1f9268c77270da3c469883d56e2798e7df6240dcb2287b/wrapt-1.17.3-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:ab232e7fdb44cdfbf55fc3afa31bcdb0d8980b9b95c38b6405df2acb672af0e0", size = 53998, upload-time = "2025-08-12T05:51:47.138Z" }, - { url = "https://files.pythonhosted.org/packages/60/f8/096a7cc13097a1869fe44efe68dace40d2a16ecb853141394047f0780b96/wrapt-1.17.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:9baa544e6acc91130e926e8c802a17f3b16fbea0fd441b5a60f5cf2cc5c3deba", size = 39020, upload-time = "2025-08-12T05:51:35.906Z" }, - { url = "https://files.pythonhosted.org/packages/33/df/bdf864b8997aab4febb96a9ae5c124f700a5abd9b5e13d2a3214ec4be705/wrapt-1.17.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6b538e31eca1a7ea4605e44f81a48aa24c4632a277431a6ed3f328835901f4fd", size = 39098, upload-time = "2025-08-12T05:51:57.474Z" }, - { url = "https://files.pythonhosted.org/packages/9f/81/5d931d78d0eb732b95dc3ddaeeb71c8bb572fb01356e9133916cd729ecdd/wrapt-1.17.3-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:042ec3bb8f319c147b1301f2393bc19dba6e176b7da446853406d041c36c7828", size = 88036, upload-time = "2025-08-12T05:52:34.784Z" }, - { url = "https://files.pythonhosted.org/packages/ca/38/2e1785df03b3d72d34fc6252d91d9d12dc27a5c89caef3335a1bbb8908ca/wrapt-1.17.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:3af60380ba0b7b5aeb329bc4e402acd25bd877e98b3727b0135cb5c2efdaefe9", size = 88156, upload-time = "2025-08-12T05:52:13.599Z" }, - { url = "https://files.pythonhosted.org/packages/b3/8b/48cdb60fe0603e34e05cffda0b2a4adab81fd43718e11111a4b0100fd7c1/wrapt-1.17.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:0b02e424deef65c9f7326d8c19220a2c9040c51dc165cddb732f16198c168396", size = 87102, upload-time = "2025-08-12T05:52:14.56Z" }, - { url = "https://files.pythonhosted.org/packages/3c/51/d81abca783b58f40a154f1b2c56db1d2d9e0d04fa2d4224e357529f57a57/wrapt-1.17.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:74afa28374a3c3a11b3b5e5fca0ae03bef8450d6aa3ab3a1e2c30e3a75d023dc", size = 87732, upload-time = "2025-08-12T05:52:36.165Z" }, - { url = "https://files.pythonhosted.org/packages/9e/b1/43b286ca1392a006d5336412d41663eeef1ad57485f3e52c767376ba7e5a/wrapt-1.17.3-cp312-cp312-win32.whl", hash = "sha256:4da9f45279fff3543c371d5ababc57a0384f70be244de7759c85a7f989cb4ebe", size = 36705, upload-time = "2025-08-12T05:53:07.123Z" }, - { url = "https://files.pythonhosted.org/packages/28/de/49493f962bd3c586ab4b88066e967aa2e0703d6ef2c43aa28cb83bf7b507/wrapt-1.17.3-cp312-cp312-win_amd64.whl", hash = "sha256:e71d5c6ebac14875668a1e90baf2ea0ef5b7ac7918355850c0908ae82bcb297c", size = 38877, upload-time = "2025-08-12T05:53:05.436Z" }, - { url = "https://files.pythonhosted.org/packages/f1/48/0f7102fe9cb1e8a5a77f80d4f0956d62d97034bbe88d33e94699f99d181d/wrapt-1.17.3-cp312-cp312-win_arm64.whl", hash = "sha256:604d076c55e2fdd4c1c03d06dc1a31b95130010517b5019db15365ec4a405fc6", size = 36885, upload-time = "2025-08-12T05:52:54.367Z" }, - { url = "https://files.pythonhosted.org/packages/fc/f6/759ece88472157acb55fc195e5b116e06730f1b651b5b314c66291729193/wrapt-1.17.3-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:a47681378a0439215912ef542c45a783484d4dd82bac412b71e59cf9c0e1cea0", size = 54003, upload-time = "2025-08-12T05:51:48.627Z" }, - { url = "https://files.pythonhosted.org/packages/4f/a9/49940b9dc6d47027dc850c116d79b4155f15c08547d04db0f07121499347/wrapt-1.17.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:54a30837587c6ee3cd1a4d1c2ec5d24e77984d44e2f34547e2323ddb4e22eb77", size = 39025, upload-time = "2025-08-12T05:51:37.156Z" }, - { url = "https://files.pythonhosted.org/packages/45/35/6a08de0f2c96dcdd7fe464d7420ddb9a7655a6561150e5fc4da9356aeaab/wrapt-1.17.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:16ecf15d6af39246fe33e507105d67e4b81d8f8d2c6598ff7e3ca1b8a37213f7", size = 39108, upload-time = "2025-08-12T05:51:58.425Z" }, - { url = "https://files.pythonhosted.org/packages/0c/37/6faf15cfa41bf1f3dba80cd3f5ccc6622dfccb660ab26ed79f0178c7497f/wrapt-1.17.3-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:6fd1ad24dc235e4ab88cda009e19bf347aabb975e44fd5c2fb22a3f6e4141277", size = 88072, upload-time = "2025-08-12T05:52:37.53Z" }, - { url = "https://files.pythonhosted.org/packages/78/f2/efe19ada4a38e4e15b6dff39c3e3f3f73f5decf901f66e6f72fe79623a06/wrapt-1.17.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:0ed61b7c2d49cee3c027372df5809a59d60cf1b6c2f81ee980a091f3afed6a2d", size = 88214, upload-time = "2025-08-12T05:52:15.886Z" }, - { url = "https://files.pythonhosted.org/packages/40/90/ca86701e9de1622b16e09689fc24b76f69b06bb0150990f6f4e8b0eeb576/wrapt-1.17.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:423ed5420ad5f5529db9ce89eac09c8a2f97da18eb1c870237e84c5a5c2d60aa", size = 87105, upload-time = "2025-08-12T05:52:17.914Z" }, - { url = "https://files.pythonhosted.org/packages/fd/e0/d10bd257c9a3e15cbf5523025252cc14d77468e8ed644aafb2d6f54cb95d/wrapt-1.17.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e01375f275f010fcbf7f643b4279896d04e571889b8a5b3f848423d91bf07050", size = 87766, upload-time = "2025-08-12T05:52:39.243Z" }, - { url = "https://files.pythonhosted.org/packages/e8/cf/7d848740203c7b4b27eb55dbfede11aca974a51c3d894f6cc4b865f42f58/wrapt-1.17.3-cp313-cp313-win32.whl", hash = "sha256:53e5e39ff71b3fc484df8a522c933ea2b7cdd0d5d15ae82e5b23fde87d44cbd8", size = 36711, upload-time = "2025-08-12T05:53:10.074Z" }, - { url = "https://files.pythonhosted.org/packages/57/54/35a84d0a4d23ea675994104e667ceff49227ce473ba6a59ba2c84f250b74/wrapt-1.17.3-cp313-cp313-win_amd64.whl", hash = "sha256:1f0b2f40cf341ee8cc1a97d51ff50dddb9fcc73241b9143ec74b30fc4f44f6cb", size = 38885, upload-time = "2025-08-12T05:53:08.695Z" }, - { url = "https://files.pythonhosted.org/packages/01/77/66e54407c59d7b02a3c4e0af3783168fff8e5d61def52cda8728439d86bc/wrapt-1.17.3-cp313-cp313-win_arm64.whl", hash = "sha256:7425ac3c54430f5fc5e7b6f41d41e704db073309acfc09305816bc6a0b26bb16", size = 36896, upload-time = "2025-08-12T05:52:55.34Z" }, - { url = "https://files.pythonhosted.org/packages/02/a2/cd864b2a14f20d14f4c496fab97802001560f9f41554eef6df201cd7f76c/wrapt-1.17.3-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:cf30f6e3c077c8e6a9a7809c94551203c8843e74ba0c960f4a98cd80d4665d39", size = 54132, upload-time = "2025-08-12T05:51:49.864Z" }, - { url = "https://files.pythonhosted.org/packages/d5/46/d011725b0c89e853dc44cceb738a307cde5d240d023d6d40a82d1b4e1182/wrapt-1.17.3-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:e228514a06843cae89621384cfe3a80418f3c04aadf8a3b14e46a7be704e4235", size = 39091, upload-time = "2025-08-12T05:51:38.935Z" }, - { url = "https://files.pythonhosted.org/packages/2e/9e/3ad852d77c35aae7ddebdbc3b6d35ec8013af7d7dddad0ad911f3d891dae/wrapt-1.17.3-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:5ea5eb3c0c071862997d6f3e02af1d055f381b1d25b286b9d6644b79db77657c", size = 39172, upload-time = "2025-08-12T05:51:59.365Z" }, - { url = "https://files.pythonhosted.org/packages/c3/f7/c983d2762bcce2326c317c26a6a1e7016f7eb039c27cdf5c4e30f4160f31/wrapt-1.17.3-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:281262213373b6d5e4bb4353bc36d1ba4084e6d6b5d242863721ef2bf2c2930b", size = 87163, upload-time = "2025-08-12T05:52:40.965Z" }, - { url = "https://files.pythonhosted.org/packages/e4/0f/f673f75d489c7f22d17fe0193e84b41540d962f75fce579cf6873167c29b/wrapt-1.17.3-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:dc4a8d2b25efb6681ecacad42fca8859f88092d8732b170de6a5dddd80a1c8fa", size = 87963, upload-time = "2025-08-12T05:52:20.326Z" }, - { url = "https://files.pythonhosted.org/packages/df/61/515ad6caca68995da2fac7a6af97faab8f78ebe3bf4f761e1b77efbc47b5/wrapt-1.17.3-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:373342dd05b1d07d752cecbec0c41817231f29f3a89aa8b8843f7b95992ed0c7", size = 86945, upload-time = "2025-08-12T05:52:21.581Z" }, - { url = "https://files.pythonhosted.org/packages/d3/bd/4e70162ce398462a467bc09e768bee112f1412e563620adc353de9055d33/wrapt-1.17.3-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:d40770d7c0fd5cbed9d84b2c3f2e156431a12c9a37dc6284060fb4bec0b7ffd4", size = 86857, upload-time = "2025-08-12T05:52:43.043Z" }, - { url = "https://files.pythonhosted.org/packages/2b/b8/da8560695e9284810b8d3df8a19396a6e40e7518059584a1a394a2b35e0a/wrapt-1.17.3-cp314-cp314-win32.whl", hash = "sha256:fbd3c8319de8e1dc79d346929cd71d523622da527cca14e0c1d257e31c2b8b10", size = 37178, upload-time = "2025-08-12T05:53:12.605Z" }, - { url = "https://files.pythonhosted.org/packages/db/c8/b71eeb192c440d67a5a0449aaee2310a1a1e8eca41676046f99ed2487e9f/wrapt-1.17.3-cp314-cp314-win_amd64.whl", hash = "sha256:e1a4120ae5705f673727d3253de3ed0e016f7cd78dc463db1b31e2463e1f3cf6", size = 39310, upload-time = "2025-08-12T05:53:11.106Z" }, - { url = "https://files.pythonhosted.org/packages/45/20/2cda20fd4865fa40f86f6c46ed37a2a8356a7a2fde0773269311f2af56c7/wrapt-1.17.3-cp314-cp314-win_arm64.whl", hash = "sha256:507553480670cab08a800b9463bdb881b2edeed77dc677b0a5915e6106e91a58", size = 37266, upload-time = "2025-08-12T05:52:56.531Z" }, - { url = "https://files.pythonhosted.org/packages/77/ed/dd5cf21aec36c80443c6f900449260b80e2a65cf963668eaef3b9accce36/wrapt-1.17.3-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:ed7c635ae45cfbc1a7371f708727bf74690daedc49b4dba310590ca0bd28aa8a", size = 56544, upload-time = "2025-08-12T05:51:51.109Z" }, - { url = "https://files.pythonhosted.org/packages/8d/96/450c651cc753877ad100c7949ab4d2e2ecc4d97157e00fa8f45df682456a/wrapt-1.17.3-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:249f88ed15503f6492a71f01442abddd73856a0032ae860de6d75ca62eed8067", size = 40283, upload-time = "2025-08-12T05:51:39.912Z" }, - { url = "https://files.pythonhosted.org/packages/d1/86/2fcad95994d9b572db57632acb6f900695a648c3e063f2cd344b3f5c5a37/wrapt-1.17.3-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:5a03a38adec8066d5a37bea22f2ba6bbf39fcdefbe2d91419ab864c3fb515454", size = 40366, upload-time = "2025-08-12T05:52:00.693Z" }, - { url = "https://files.pythonhosted.org/packages/64/0e/f4472f2fdde2d4617975144311f8800ef73677a159be7fe61fa50997d6c0/wrapt-1.17.3-cp314-cp314t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:5d4478d72eb61c36e5b446e375bbc49ed002430d17cdec3cecb36993398e1a9e", size = 108571, upload-time = "2025-08-12T05:52:44.521Z" }, - { url = "https://files.pythonhosted.org/packages/cc/01/9b85a99996b0a97c8a17484684f206cbb6ba73c1ce6890ac668bcf3838fb/wrapt-1.17.3-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:223db574bb38637e8230eb14b185565023ab624474df94d2af18f1cdb625216f", size = 113094, upload-time = "2025-08-12T05:52:22.618Z" }, - { url = "https://files.pythonhosted.org/packages/25/02/78926c1efddcc7b3aa0bc3d6b33a822f7d898059f7cd9ace8c8318e559ef/wrapt-1.17.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:e405adefb53a435f01efa7ccdec012c016b5a1d3f35459990afc39b6be4d5056", size = 110659, upload-time = "2025-08-12T05:52:24.057Z" }, - { url = "https://files.pythonhosted.org/packages/dc/ee/c414501ad518ac3e6fe184753632fe5e5ecacdcf0effc23f31c1e4f7bfcf/wrapt-1.17.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:88547535b787a6c9ce4086917b6e1d291aa8ed914fdd3a838b3539dc95c12804", size = 106946, upload-time = "2025-08-12T05:52:45.976Z" }, - { url = "https://files.pythonhosted.org/packages/be/44/a1bd64b723d13bb151d6cc91b986146a1952385e0392a78567e12149c7b4/wrapt-1.17.3-cp314-cp314t-win32.whl", hash = "sha256:41b1d2bc74c2cac6f9074df52b2efbef2b30bdfe5f40cb78f8ca22963bc62977", size = 38717, upload-time = "2025-08-12T05:53:15.214Z" }, - { url = "https://files.pythonhosted.org/packages/79/d9/7cfd5a312760ac4dd8bf0184a6ee9e43c33e47f3dadc303032ce012b8fa3/wrapt-1.17.3-cp314-cp314t-win_amd64.whl", hash = "sha256:73d496de46cd2cdbdbcce4ae4bcdb4afb6a11234a1df9c085249d55166b95116", size = 41334, upload-time = "2025-08-12T05:53:14.178Z" }, - { url = "https://files.pythonhosted.org/packages/46/78/10ad9781128ed2f99dbc474f43283b13fea8ba58723e98844367531c18e9/wrapt-1.17.3-cp314-cp314t-win_arm64.whl", hash = "sha256:f38e60678850c42461d4202739f9bf1e3a737c7ad283638251e79cc49effb6b6", size = 38471, upload-time = "2025-08-12T05:52:57.784Z" }, - { url = "https://files.pythonhosted.org/packages/1f/f6/a933bd70f98e9cf3e08167fc5cd7aaaca49147e48411c0bd5ae701bb2194/wrapt-1.17.3-py3-none-any.whl", hash = "sha256:7171ae35d2c33d326ac19dd8facb1e82e5fd04ef8c6c0e394d7af55a55051c22", size = 23591, upload-time = "2025-08-12T05:53:20.674Z" }, -] - -[[package]] -name = "xxhash" -version = "3.5.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/00/5e/d6e5258d69df8b4ed8c83b6664f2b47d30d2dec551a29ad72a6c69eafd31/xxhash-3.5.0.tar.gz", hash = "sha256:84f2caddf951c9cbf8dc2e22a89d4ccf5d86391ac6418fe81e3c67d0cf60b45f", size = 84241, upload-time = "2024-08-17T09:20:38.972Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/bb/8a/0e9feca390d512d293afd844d31670e25608c4a901e10202aa98785eab09/xxhash-3.5.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ece616532c499ee9afbb83078b1b952beffef121d989841f7f4b3dc5ac0fd212", size = 31970, upload-time = "2024-08-17T09:17:35.675Z" }, - { url = "https://files.pythonhosted.org/packages/16/e6/be5aa49580cd064a18200ab78e29b88b1127e1a8c7955eb8ecf81f2626eb/xxhash-3.5.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:3171f693dbc2cef6477054a665dc255d996646b4023fe56cb4db80e26f4cc520", size = 30801, upload-time = "2024-08-17T09:17:37.353Z" }, - { url = "https://files.pythonhosted.org/packages/20/ee/b8a99ebbc6d1113b3a3f09e747fa318c3cde5b04bd9c197688fadf0eeae8/xxhash-3.5.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7c5d3e570ef46adaf93fc81b44aca6002b5a4d8ca11bd0580c07eac537f36680", size = 220927, upload-time = "2024-08-17T09:17:38.835Z" }, - { url = "https://files.pythonhosted.org/packages/58/62/15d10582ef159283a5c2b47f6d799fc3303fe3911d5bb0bcc820e1ef7ff4/xxhash-3.5.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7cb29a034301e2982df8b1fe6328a84f4b676106a13e9135a0d7e0c3e9f806da", size = 200360, upload-time = "2024-08-17T09:17:40.851Z" }, - { url = "https://files.pythonhosted.org/packages/23/41/61202663ea9b1bd8e53673b8ec9e2619989353dba8cfb68e59a9cbd9ffe3/xxhash-3.5.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5d0d307d27099bb0cbeea7260eb39ed4fdb99c5542e21e94bb6fd29e49c57a23", size = 428528, upload-time = "2024-08-17T09:17:42.545Z" }, - { url = "https://files.pythonhosted.org/packages/f2/07/d9a3059f702dec5b3b703737afb6dda32f304f6e9da181a229dafd052c29/xxhash-3.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c0342aafd421795d740e514bc9858ebddfc705a75a8c5046ac56d85fe97bf196", size = 194149, upload-time = "2024-08-17T09:17:44.361Z" }, - { url = "https://files.pythonhosted.org/packages/eb/58/27caadf78226ecf1d62dbd0c01d152ed381c14c1ee4ad01f0d460fc40eac/xxhash-3.5.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3dbbd9892c5ebffeca1ed620cf0ade13eb55a0d8c84e0751a6653adc6ac40d0c", size = 207703, upload-time = "2024-08-17T09:17:46.656Z" }, - { url = "https://files.pythonhosted.org/packages/b1/08/32d558ce23e1e068453c39aed7b3c1cdc690c177873ec0ca3a90d5808765/xxhash-3.5.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:4cc2d67fdb4d057730c75a64c5923abfa17775ae234a71b0200346bfb0a7f482", size = 216255, upload-time = "2024-08-17T09:17:48.031Z" }, - { url = "https://files.pythonhosted.org/packages/3f/d4/2b971e2d2b0a61045f842b622ef11e94096cf1f12cd448b6fd426e80e0e2/xxhash-3.5.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:ec28adb204b759306a3d64358a5e5c07d7b1dd0ccbce04aa76cb9377b7b70296", size = 202744, upload-time = "2024-08-17T09:17:50.045Z" }, - { url = "https://files.pythonhosted.org/packages/19/ae/6a6438864a8c4c39915d7b65effd85392ebe22710412902487e51769146d/xxhash-3.5.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:1328f6d8cca2b86acb14104e381225a3d7b42c92c4b86ceae814e5c400dbb415", size = 210115, upload-time = "2024-08-17T09:17:51.834Z" }, - { url = "https://files.pythonhosted.org/packages/48/7d/b3c27c27d1fc868094d02fe4498ccce8cec9fcc591825c01d6bcb0b4fc49/xxhash-3.5.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:8d47ebd9f5d9607fd039c1fbf4994e3b071ea23eff42f4ecef246ab2b7334198", size = 414247, upload-time = "2024-08-17T09:17:53.094Z" }, - { url = "https://files.pythonhosted.org/packages/a1/05/918f9e7d2fbbd334b829997045d341d6239b563c44e683b9a7ef8fe50f5d/xxhash-3.5.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:b96d559e0fcddd3343c510a0fe2b127fbff16bf346dd76280b82292567523442", size = 191419, upload-time = "2024-08-17T09:17:54.906Z" }, - { url = "https://files.pythonhosted.org/packages/08/29/dfe393805b2f86bfc47c290b275f0b7c189dc2f4e136fd4754f32eb18a8d/xxhash-3.5.0-cp310-cp310-win32.whl", hash = "sha256:61c722ed8d49ac9bc26c7071eeaa1f6ff24053d553146d5df031802deffd03da", size = 30114, upload-time = "2024-08-17T09:17:56.566Z" }, - { url = "https://files.pythonhosted.org/packages/7b/d7/aa0b22c4ebb7c3ccb993d4c565132abc641cd11164f8952d89eb6a501909/xxhash-3.5.0-cp310-cp310-win_amd64.whl", hash = "sha256:9bed5144c6923cc902cd14bb8963f2d5e034def4486ab0bbe1f58f03f042f9a9", size = 30003, upload-time = "2024-08-17T09:17:57.596Z" }, - { url = "https://files.pythonhosted.org/packages/69/12/f969b81541ee91b55f1ce469d7ab55079593c80d04fd01691b550e535000/xxhash-3.5.0-cp310-cp310-win_arm64.whl", hash = "sha256:893074d651cf25c1cc14e3bea4fceefd67f2921b1bb8e40fcfeba56820de80c6", size = 26773, upload-time = "2024-08-17T09:17:59.169Z" }, - { url = "https://files.pythonhosted.org/packages/b8/c7/afed0f131fbda960ff15eee7f304fa0eeb2d58770fade99897984852ef23/xxhash-3.5.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:02c2e816896dc6f85922ced60097bcf6f008dedfc5073dcba32f9c8dd786f3c1", size = 31969, upload-time = "2024-08-17T09:18:00.852Z" }, - { url = "https://files.pythonhosted.org/packages/8c/0c/7c3bc6d87e5235672fcc2fb42fd5ad79fe1033925f71bf549ee068c7d1ca/xxhash-3.5.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:6027dcd885e21581e46d3c7f682cfb2b870942feeed58a21c29583512c3f09f8", size = 30800, upload-time = "2024-08-17T09:18:01.863Z" }, - { url = "https://files.pythonhosted.org/packages/04/9e/01067981d98069eec1c20201f8c145367698e9056f8bc295346e4ea32dd1/xxhash-3.5.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1308fa542bbdbf2fa85e9e66b1077eea3a88bef38ee8a06270b4298a7a62a166", size = 221566, upload-time = "2024-08-17T09:18:03.461Z" }, - { url = "https://files.pythonhosted.org/packages/d4/09/d4996de4059c3ce5342b6e1e6a77c9d6c91acce31f6ed979891872dd162b/xxhash-3.5.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c28b2fdcee797e1c1961cd3bcd3d545cab22ad202c846235197935e1df2f8ef7", size = 201214, upload-time = "2024-08-17T09:18:05.616Z" }, - { url = "https://files.pythonhosted.org/packages/62/f5/6d2dc9f8d55a7ce0f5e7bfef916e67536f01b85d32a9fbf137d4cadbee38/xxhash-3.5.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:924361811732ddad75ff23e90efd9ccfda4f664132feecb90895bade6a1b4623", size = 429433, upload-time = "2024-08-17T09:18:06.957Z" }, - { url = "https://files.pythonhosted.org/packages/d9/72/9256303f10e41ab004799a4aa74b80b3c5977d6383ae4550548b24bd1971/xxhash-3.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:89997aa1c4b6a5b1e5b588979d1da048a3c6f15e55c11d117a56b75c84531f5a", size = 194822, upload-time = "2024-08-17T09:18:08.331Z" }, - { url = "https://files.pythonhosted.org/packages/34/92/1a3a29acd08248a34b0e6a94f4e0ed9b8379a4ff471f1668e4dce7bdbaa8/xxhash-3.5.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:685c4f4e8c59837de103344eb1c8a3851f670309eb5c361f746805c5471b8c88", size = 208538, upload-time = "2024-08-17T09:18:10.332Z" }, - { url = "https://files.pythonhosted.org/packages/53/ad/7fa1a109663366de42f724a1cdb8e796a260dbac45047bce153bc1e18abf/xxhash-3.5.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:dbd2ecfbfee70bc1a4acb7461fa6af7748ec2ab08ac0fa298f281c51518f982c", size = 216953, upload-time = "2024-08-17T09:18:11.707Z" }, - { url = "https://files.pythonhosted.org/packages/35/02/137300e24203bf2b2a49b48ce898ecce6fd01789c0fcd9c686c0a002d129/xxhash-3.5.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:25b5a51dc3dfb20a10833c8eee25903fd2e14059e9afcd329c9da20609a307b2", size = 203594, upload-time = "2024-08-17T09:18:13.799Z" }, - { url = "https://files.pythonhosted.org/packages/23/03/aeceb273933d7eee248c4322b98b8e971f06cc3880e5f7602c94e5578af5/xxhash-3.5.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:a8fb786fb754ef6ff8c120cb96629fb518f8eb5a61a16aac3a979a9dbd40a084", size = 210971, upload-time = "2024-08-17T09:18:15.824Z" }, - { url = "https://files.pythonhosted.org/packages/e3/64/ed82ec09489474cbb35c716b189ddc1521d8b3de12b1b5ab41ce7f70253c/xxhash-3.5.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:a905ad00ad1e1c34fe4e9d7c1d949ab09c6fa90c919860c1534ff479f40fd12d", size = 415050, upload-time = "2024-08-17T09:18:17.142Z" }, - { url = "https://files.pythonhosted.org/packages/71/43/6db4c02dcb488ad4e03bc86d70506c3d40a384ee73c9b5c93338eb1f3c23/xxhash-3.5.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:963be41bcd49f53af6d795f65c0da9b4cc518c0dd9c47145c98f61cb464f4839", size = 192216, upload-time = "2024-08-17T09:18:18.779Z" }, - { url = "https://files.pythonhosted.org/packages/22/6d/db4abec29e7a567455344433d095fdb39c97db6955bb4a2c432e486b4d28/xxhash-3.5.0-cp311-cp311-win32.whl", hash = "sha256:109b436096d0a2dd039c355fa3414160ec4d843dfecc64a14077332a00aeb7da", size = 30120, upload-time = "2024-08-17T09:18:20.009Z" }, - { url = "https://files.pythonhosted.org/packages/52/1c/fa3b61c0cf03e1da4767213672efe186b1dfa4fc901a4a694fb184a513d1/xxhash-3.5.0-cp311-cp311-win_amd64.whl", hash = "sha256:b702f806693201ad6c0a05ddbbe4c8f359626d0b3305f766077d51388a6bac58", size = 30003, upload-time = "2024-08-17T09:18:21.052Z" }, - { url = "https://files.pythonhosted.org/packages/6b/8e/9e6fc572acf6e1cc7ccb01973c213f895cb8668a9d4c2b58a99350da14b7/xxhash-3.5.0-cp311-cp311-win_arm64.whl", hash = "sha256:c4dcb4120d0cc3cc448624147dba64e9021b278c63e34a38789b688fd0da9bf3", size = 26777, upload-time = "2024-08-17T09:18:22.809Z" }, - { url = "https://files.pythonhosted.org/packages/07/0e/1bfce2502c57d7e2e787600b31c83535af83746885aa1a5f153d8c8059d6/xxhash-3.5.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:14470ace8bd3b5d51318782cd94e6f94431974f16cb3b8dc15d52f3b69df8e00", size = 31969, upload-time = "2024-08-17T09:18:24.025Z" }, - { url = "https://files.pythonhosted.org/packages/3f/d6/8ca450d6fe5b71ce521b4e5db69622383d039e2b253e9b2f24f93265b52c/xxhash-3.5.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:59aa1203de1cb96dbeab595ded0ad0c0056bb2245ae11fac11c0ceea861382b9", size = 30787, upload-time = "2024-08-17T09:18:25.318Z" }, - { url = "https://files.pythonhosted.org/packages/5b/84/de7c89bc6ef63d750159086a6ada6416cc4349eab23f76ab870407178b93/xxhash-3.5.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:08424f6648526076e28fae6ea2806c0a7d504b9ef05ae61d196d571e5c879c84", size = 220959, upload-time = "2024-08-17T09:18:26.518Z" }, - { url = "https://files.pythonhosted.org/packages/fe/86/51258d3e8a8545ff26468c977101964c14d56a8a37f5835bc0082426c672/xxhash-3.5.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:61a1ff00674879725b194695e17f23d3248998b843eb5e933007ca743310f793", size = 200006, upload-time = "2024-08-17T09:18:27.905Z" }, - { url = "https://files.pythonhosted.org/packages/02/0a/96973bd325412feccf23cf3680fd2246aebf4b789122f938d5557c54a6b2/xxhash-3.5.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f2f2c61bee5844d41c3eb015ac652a0229e901074951ae48581d58bfb2ba01be", size = 428326, upload-time = "2024-08-17T09:18:29.335Z" }, - { url = "https://files.pythonhosted.org/packages/11/a7/81dba5010f7e733de88af9555725146fc133be97ce36533867f4c7e75066/xxhash-3.5.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9d32a592cac88d18cc09a89172e1c32d7f2a6e516c3dfde1b9adb90ab5df54a6", size = 194380, upload-time = "2024-08-17T09:18:30.706Z" }, - { url = "https://files.pythonhosted.org/packages/fb/7d/f29006ab398a173f4501c0e4977ba288f1c621d878ec217b4ff516810c04/xxhash-3.5.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:70dabf941dede727cca579e8c205e61121afc9b28516752fd65724be1355cc90", size = 207934, upload-time = "2024-08-17T09:18:32.133Z" }, - { url = "https://files.pythonhosted.org/packages/8a/6e/6e88b8f24612510e73d4d70d9b0c7dff62a2e78451b9f0d042a5462c8d03/xxhash-3.5.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:e5d0ddaca65ecca9c10dcf01730165fd858533d0be84c75c327487c37a906a27", size = 216301, upload-time = "2024-08-17T09:18:33.474Z" }, - { url = "https://files.pythonhosted.org/packages/af/51/7862f4fa4b75a25c3b4163c8a873f070532fe5f2d3f9b3fc869c8337a398/xxhash-3.5.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:3e5b5e16c5a480fe5f59f56c30abdeba09ffd75da8d13f6b9b6fd224d0b4d0a2", size = 203351, upload-time = "2024-08-17T09:18:34.889Z" }, - { url = "https://files.pythonhosted.org/packages/22/61/8d6a40f288f791cf79ed5bb113159abf0c81d6efb86e734334f698eb4c59/xxhash-3.5.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:149b7914451eb154b3dfaa721315117ea1dac2cc55a01bfbd4df7c68c5dd683d", size = 210294, upload-time = "2024-08-17T09:18:36.355Z" }, - { url = "https://files.pythonhosted.org/packages/17/02/215c4698955762d45a8158117190261b2dbefe9ae7e5b906768c09d8bc74/xxhash-3.5.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:eade977f5c96c677035ff39c56ac74d851b1cca7d607ab3d8f23c6b859379cab", size = 414674, upload-time = "2024-08-17T09:18:38.536Z" }, - { url = "https://files.pythonhosted.org/packages/31/5c/b7a8db8a3237cff3d535261325d95de509f6a8ae439a5a7a4ffcff478189/xxhash-3.5.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:fa9f547bd98f5553d03160967866a71056a60960be00356a15ecc44efb40ba8e", size = 192022, upload-time = "2024-08-17T09:18:40.138Z" }, - { url = "https://files.pythonhosted.org/packages/78/e3/dd76659b2811b3fd06892a8beb850e1996b63e9235af5a86ea348f053e9e/xxhash-3.5.0-cp312-cp312-win32.whl", hash = "sha256:f7b58d1fd3551b8c80a971199543379be1cee3d0d409e1f6d8b01c1a2eebf1f8", size = 30170, upload-time = "2024-08-17T09:18:42.163Z" }, - { url = "https://files.pythonhosted.org/packages/d9/6b/1c443fe6cfeb4ad1dcf231cdec96eb94fb43d6498b4469ed8b51f8b59a37/xxhash-3.5.0-cp312-cp312-win_amd64.whl", hash = "sha256:fa0cafd3a2af231b4e113fba24a65d7922af91aeb23774a8b78228e6cd785e3e", size = 30040, upload-time = "2024-08-17T09:18:43.699Z" }, - { url = "https://files.pythonhosted.org/packages/0f/eb/04405305f290173acc0350eba6d2f1a794b57925df0398861a20fbafa415/xxhash-3.5.0-cp312-cp312-win_arm64.whl", hash = "sha256:586886c7e89cb9828bcd8a5686b12e161368e0064d040e225e72607b43858ba2", size = 26796, upload-time = "2024-08-17T09:18:45.29Z" }, - { url = "https://files.pythonhosted.org/packages/c9/b8/e4b3ad92d249be5c83fa72916c9091b0965cb0faeff05d9a0a3870ae6bff/xxhash-3.5.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:37889a0d13b0b7d739cfc128b1c902f04e32de17b33d74b637ad42f1c55101f6", size = 31795, upload-time = "2024-08-17T09:18:46.813Z" }, - { url = "https://files.pythonhosted.org/packages/fc/d8/b3627a0aebfbfa4c12a41e22af3742cf08c8ea84f5cc3367b5de2d039cce/xxhash-3.5.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:97a662338797c660178e682f3bc180277b9569a59abfb5925e8620fba00b9fc5", size = 30792, upload-time = "2024-08-17T09:18:47.862Z" }, - { url = "https://files.pythonhosted.org/packages/c3/cc/762312960691da989c7cd0545cb120ba2a4148741c6ba458aa723c00a3f8/xxhash-3.5.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7f85e0108d51092bdda90672476c7d909c04ada6923c14ff9d913c4f7dc8a3bc", size = 220950, upload-time = "2024-08-17T09:18:49.06Z" }, - { url = "https://files.pythonhosted.org/packages/fe/e9/cc266f1042c3c13750e86a535496b58beb12bf8c50a915c336136f6168dc/xxhash-3.5.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cd2fd827b0ba763ac919440042302315c564fdb797294d86e8cdd4578e3bc7f3", size = 199980, upload-time = "2024-08-17T09:18:50.445Z" }, - { url = "https://files.pythonhosted.org/packages/bf/85/a836cd0dc5cc20376de26b346858d0ac9656f8f730998ca4324921a010b9/xxhash-3.5.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:82085c2abec437abebf457c1d12fccb30cc8b3774a0814872511f0f0562c768c", size = 428324, upload-time = "2024-08-17T09:18:51.988Z" }, - { url = "https://files.pythonhosted.org/packages/b4/0e/15c243775342ce840b9ba34aceace06a1148fa1630cd8ca269e3223987f5/xxhash-3.5.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:07fda5de378626e502b42b311b049848c2ef38784d0d67b6f30bb5008642f8eb", size = 194370, upload-time = "2024-08-17T09:18:54.164Z" }, - { url = "https://files.pythonhosted.org/packages/87/a1/b028bb02636dfdc190da01951d0703b3d904301ed0ef6094d948983bef0e/xxhash-3.5.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c279f0d2b34ef15f922b77966640ade58b4ccdfef1c4d94b20f2a364617a493f", size = 207911, upload-time = "2024-08-17T09:18:55.509Z" }, - { url = "https://files.pythonhosted.org/packages/80/d5/73c73b03fc0ac73dacf069fdf6036c9abad82de0a47549e9912c955ab449/xxhash-3.5.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:89e66ceed67b213dec5a773e2f7a9e8c58f64daeb38c7859d8815d2c89f39ad7", size = 216352, upload-time = "2024-08-17T09:18:57.073Z" }, - { url = "https://files.pythonhosted.org/packages/b6/2a/5043dba5ddbe35b4fe6ea0a111280ad9c3d4ba477dd0f2d1fe1129bda9d0/xxhash-3.5.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:bcd51708a633410737111e998ceb3b45d3dbc98c0931f743d9bb0a209033a326", size = 203410, upload-time = "2024-08-17T09:18:58.54Z" }, - { url = "https://files.pythonhosted.org/packages/a2/b2/9a8ded888b7b190aed75b484eb5c853ddd48aa2896e7b59bbfbce442f0a1/xxhash-3.5.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:3ff2c0a34eae7df88c868be53a8dd56fbdf592109e21d4bfa092a27b0bf4a7bf", size = 210322, upload-time = "2024-08-17T09:18:59.943Z" }, - { url = "https://files.pythonhosted.org/packages/98/62/440083fafbc917bf3e4b67c2ade621920dd905517e85631c10aac955c1d2/xxhash-3.5.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:4e28503dccc7d32e0b9817aa0cbfc1f45f563b2c995b7a66c4c8a0d232e840c7", size = 414725, upload-time = "2024-08-17T09:19:01.332Z" }, - { url = "https://files.pythonhosted.org/packages/75/db/009206f7076ad60a517e016bb0058381d96a007ce3f79fa91d3010f49cc2/xxhash-3.5.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a6c50017518329ed65a9e4829154626f008916d36295b6a3ba336e2458824c8c", size = 192070, upload-time = "2024-08-17T09:19:03.007Z" }, - { url = "https://files.pythonhosted.org/packages/1f/6d/c61e0668943a034abc3a569cdc5aeae37d686d9da7e39cf2ed621d533e36/xxhash-3.5.0-cp313-cp313-win32.whl", hash = "sha256:53a068fe70301ec30d868ece566ac90d873e3bb059cf83c32e76012c889b8637", size = 30172, upload-time = "2024-08-17T09:19:04.355Z" }, - { url = "https://files.pythonhosted.org/packages/96/14/8416dce965f35e3d24722cdf79361ae154fa23e2ab730e5323aa98d7919e/xxhash-3.5.0-cp313-cp313-win_amd64.whl", hash = "sha256:80babcc30e7a1a484eab952d76a4f4673ff601f54d5142c26826502740e70b43", size = 30041, upload-time = "2024-08-17T09:19:05.435Z" }, - { url = "https://files.pythonhosted.org/packages/27/ee/518b72faa2073f5aa8e3262408d284892cb79cf2754ba0c3a5870645ef73/xxhash-3.5.0-cp313-cp313-win_arm64.whl", hash = "sha256:4811336f1ce11cac89dcbd18f3a25c527c16311709a89313c3acaf771def2d4b", size = 26801, upload-time = "2024-08-17T09:19:06.547Z" }, - { url = "https://files.pythonhosted.org/packages/ab/9a/233606bada5bd6f50b2b72c45de3d9868ad551e83893d2ac86dc7bb8553a/xxhash-3.5.0-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:2014c5b3ff15e64feecb6b713af12093f75b7926049e26a580e94dcad3c73d8c", size = 29732, upload-time = "2024-08-17T09:20:11.175Z" }, - { url = "https://files.pythonhosted.org/packages/0c/67/f75276ca39e2c6604e3bee6c84e9db8a56a4973fde9bf35989787cf6e8aa/xxhash-3.5.0-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fab81ef75003eda96239a23eda4e4543cedc22e34c373edcaf744e721a163986", size = 36214, upload-time = "2024-08-17T09:20:12.335Z" }, - { url = "https://files.pythonhosted.org/packages/0f/f8/f6c61fd794229cc3848d144f73754a0c107854372d7261419dcbbd286299/xxhash-3.5.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4e2febf914ace002132aa09169cc572e0d8959d0f305f93d5828c4836f9bc5a6", size = 32020, upload-time = "2024-08-17T09:20:13.537Z" }, - { url = "https://files.pythonhosted.org/packages/79/d3/c029c99801526f859e6b38d34ab87c08993bf3dcea34b11275775001638a/xxhash-3.5.0-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5d3a10609c51da2a1c0ea0293fc3968ca0a18bd73838455b5bca3069d7f8e32b", size = 40515, upload-time = "2024-08-17T09:20:14.669Z" }, - { url = "https://files.pythonhosted.org/packages/62/e3/bef7b82c1997579c94de9ac5ea7626d01ae5858aa22bf4fcb38bf220cb3e/xxhash-3.5.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:5a74f23335b9689b66eb6dbe2a931a88fcd7a4c2cc4b1cb0edba8ce381c7a1da", size = 30064, upload-time = "2024-08-17T09:20:15.925Z" }, -] - -[[package]] -name = "yarl" -version = "1.20.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "idna" }, - { name = "multidict" }, - { name = "propcache" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/3c/fb/efaa23fa4e45537b827620f04cf8f3cd658b76642205162e072703a5b963/yarl-1.20.1.tar.gz", hash = "sha256:d017a4997ee50c91fd5466cef416231bb82177b93b029906cefc542ce14c35ac", size = 186428, upload-time = "2025-06-10T00:46:09.923Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/cb/65/7fed0d774abf47487c64be14e9223749468922817b5e8792b8a64792a1bb/yarl-1.20.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:6032e6da6abd41e4acda34d75a816012717000fa6839f37124a47fcefc49bec4", size = 132910, upload-time = "2025-06-10T00:42:31.108Z" }, - { url = "https://files.pythonhosted.org/packages/8a/7b/988f55a52da99df9e56dc733b8e4e5a6ae2090081dc2754fc8fd34e60aa0/yarl-1.20.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:2c7b34d804b8cf9b214f05015c4fee2ebe7ed05cf581e7192c06555c71f4446a", size = 90644, upload-time = "2025-06-10T00:42:33.851Z" }, - { url = "https://files.pythonhosted.org/packages/f7/de/30d98f03e95d30c7e3cc093759982d038c8833ec2451001d45ef4854edc1/yarl-1.20.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0c869f2651cc77465f6cd01d938d91a11d9ea5d798738c1dc077f3de0b5e5fed", size = 89322, upload-time = "2025-06-10T00:42:35.688Z" }, - { url = "https://files.pythonhosted.org/packages/e0/7a/f2f314f5ebfe9200724b0b748de2186b927acb334cf964fd312eb86fc286/yarl-1.20.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:62915e6688eb4d180d93840cda4110995ad50c459bf931b8b3775b37c264af1e", size = 323786, upload-time = "2025-06-10T00:42:37.817Z" }, - { url = "https://files.pythonhosted.org/packages/15/3f/718d26f189db96d993d14b984ce91de52e76309d0fd1d4296f34039856aa/yarl-1.20.1-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:41ebd28167bc6af8abb97fec1a399f412eec5fd61a3ccbe2305a18b84fb4ca73", size = 319627, upload-time = "2025-06-10T00:42:39.937Z" }, - { url = "https://files.pythonhosted.org/packages/a5/76/8fcfbf5fa2369157b9898962a4a7d96764b287b085b5b3d9ffae69cdefd1/yarl-1.20.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:21242b4288a6d56f04ea193adde174b7e347ac46ce6bc84989ff7c1b1ecea84e", size = 339149, upload-time = "2025-06-10T00:42:42.627Z" }, - { url = "https://files.pythonhosted.org/packages/3c/95/d7fc301cc4661785967acc04f54a4a42d5124905e27db27bb578aac49b5c/yarl-1.20.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bea21cdae6c7eb02ba02a475f37463abfe0a01f5d7200121b03e605d6a0439f8", size = 333327, upload-time = "2025-06-10T00:42:44.842Z" }, - { url = "https://files.pythonhosted.org/packages/65/94/e21269718349582eee81efc5c1c08ee71c816bfc1585b77d0ec3f58089eb/yarl-1.20.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1f8a891e4a22a89f5dde7862994485e19db246b70bb288d3ce73a34422e55b23", size = 326054, upload-time = "2025-06-10T00:42:47.149Z" }, - { url = "https://files.pythonhosted.org/packages/32/ae/8616d1f07853704523519f6131d21f092e567c5af93de7e3e94b38d7f065/yarl-1.20.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:dd803820d44c8853a109a34e3660e5a61beae12970da479cf44aa2954019bf70", size = 315035, upload-time = "2025-06-10T00:42:48.852Z" }, - { url = "https://files.pythonhosted.org/packages/48/aa/0ace06280861ef055855333707db5e49c6e3a08840a7ce62682259d0a6c0/yarl-1.20.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:b982fa7f74c80d5c0c7b5b38f908971e513380a10fecea528091405f519b9ebb", size = 338962, upload-time = "2025-06-10T00:42:51.024Z" }, - { url = "https://files.pythonhosted.org/packages/20/52/1e9d0e6916f45a8fb50e6844f01cb34692455f1acd548606cbda8134cd1e/yarl-1.20.1-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:33f29ecfe0330c570d997bcf1afd304377f2e48f61447f37e846a6058a4d33b2", size = 335399, upload-time = "2025-06-10T00:42:53.007Z" }, - { url = "https://files.pythonhosted.org/packages/f2/65/60452df742952c630e82f394cd409de10610481d9043aa14c61bf846b7b1/yarl-1.20.1-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:835ab2cfc74d5eb4a6a528c57f05688099da41cf4957cf08cad38647e4a83b30", size = 338649, upload-time = "2025-06-10T00:42:54.964Z" }, - { url = "https://files.pythonhosted.org/packages/7b/f5/6cd4ff38dcde57a70f23719a838665ee17079640c77087404c3d34da6727/yarl-1.20.1-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:46b5e0ccf1943a9a6e766b2c2b8c732c55b34e28be57d8daa2b3c1d1d4009309", size = 358563, upload-time = "2025-06-10T00:42:57.28Z" }, - { url = "https://files.pythonhosted.org/packages/d1/90/c42eefd79d0d8222cb3227bdd51b640c0c1d0aa33fe4cc86c36eccba77d3/yarl-1.20.1-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:df47c55f7d74127d1b11251fe6397d84afdde0d53b90bedb46a23c0e534f9d24", size = 357609, upload-time = "2025-06-10T00:42:59.055Z" }, - { url = "https://files.pythonhosted.org/packages/03/c8/cea6b232cb4617514232e0f8a718153a95b5d82b5290711b201545825532/yarl-1.20.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:76d12524d05841276b0e22573f28d5fbcb67589836772ae9244d90dd7d66aa13", size = 350224, upload-time = "2025-06-10T00:43:01.248Z" }, - { url = "https://files.pythonhosted.org/packages/ce/a3/eaa0ab9712f1f3d01faf43cf6f1f7210ce4ea4a7e9b28b489a2261ca8db9/yarl-1.20.1-cp310-cp310-win32.whl", hash = "sha256:6c4fbf6b02d70e512d7ade4b1f998f237137f1417ab07ec06358ea04f69134f8", size = 81753, upload-time = "2025-06-10T00:43:03.486Z" }, - { url = "https://files.pythonhosted.org/packages/8f/34/e4abde70a9256465fe31c88ed02c3f8502b7b5dead693a4f350a06413f28/yarl-1.20.1-cp310-cp310-win_amd64.whl", hash = "sha256:aef6c4d69554d44b7f9d923245f8ad9a707d971e6209d51279196d8e8fe1ae16", size = 86817, upload-time = "2025-06-10T00:43:05.231Z" }, - { url = "https://files.pythonhosted.org/packages/b1/18/893b50efc2350e47a874c5c2d67e55a0ea5df91186b2a6f5ac52eff887cd/yarl-1.20.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:47ee6188fea634bdfaeb2cc420f5b3b17332e6225ce88149a17c413c77ff269e", size = 133833, upload-time = "2025-06-10T00:43:07.393Z" }, - { url = "https://files.pythonhosted.org/packages/89/ed/b8773448030e6fc47fa797f099ab9eab151a43a25717f9ac043844ad5ea3/yarl-1.20.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:d0f6500f69e8402d513e5eedb77a4e1818691e8f45e6b687147963514d84b44b", size = 91070, upload-time = "2025-06-10T00:43:09.538Z" }, - { url = "https://files.pythonhosted.org/packages/e3/e3/409bd17b1e42619bf69f60e4f031ce1ccb29bd7380117a55529e76933464/yarl-1.20.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:7a8900a42fcdaad568de58887c7b2f602962356908eedb7628eaf6021a6e435b", size = 89818, upload-time = "2025-06-10T00:43:11.575Z" }, - { url = "https://files.pythonhosted.org/packages/f8/77/64d8431a4d77c856eb2d82aa3de2ad6741365245a29b3a9543cd598ed8c5/yarl-1.20.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bad6d131fda8ef508b36be3ece16d0902e80b88ea7200f030a0f6c11d9e508d4", size = 347003, upload-time = "2025-06-10T00:43:14.088Z" }, - { url = "https://files.pythonhosted.org/packages/8d/d2/0c7e4def093dcef0bd9fa22d4d24b023788b0a33b8d0088b51aa51e21e99/yarl-1.20.1-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:df018d92fe22aaebb679a7f89fe0c0f368ec497e3dda6cb81a567610f04501f1", size = 336537, upload-time = "2025-06-10T00:43:16.431Z" }, - { url = "https://files.pythonhosted.org/packages/f0/f3/fc514f4b2cf02cb59d10cbfe228691d25929ce8f72a38db07d3febc3f706/yarl-1.20.1-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8f969afbb0a9b63c18d0feecf0db09d164b7a44a053e78a7d05f5df163e43833", size = 362358, upload-time = "2025-06-10T00:43:18.704Z" }, - { url = "https://files.pythonhosted.org/packages/ea/6d/a313ac8d8391381ff9006ac05f1d4331cee3b1efaa833a53d12253733255/yarl-1.20.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:812303eb4aa98e302886ccda58d6b099e3576b1b9276161469c25803a8db277d", size = 357362, upload-time = "2025-06-10T00:43:20.888Z" }, - { url = "https://files.pythonhosted.org/packages/00/70/8f78a95d6935a70263d46caa3dd18e1f223cf2f2ff2037baa01a22bc5b22/yarl-1.20.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98c4a7d166635147924aa0bf9bfe8d8abad6fffa6102de9c99ea04a1376f91e8", size = 348979, upload-time = "2025-06-10T00:43:23.169Z" }, - { url = "https://files.pythonhosted.org/packages/cb/05/42773027968968f4f15143553970ee36ead27038d627f457cc44bbbeecf3/yarl-1.20.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:12e768f966538e81e6e7550f9086a6236b16e26cd964cf4df35349970f3551cf", size = 337274, upload-time = "2025-06-10T00:43:27.111Z" }, - { url = "https://files.pythonhosted.org/packages/05/be/665634aa196954156741ea591d2f946f1b78ceee8bb8f28488bf28c0dd62/yarl-1.20.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:fe41919b9d899661c5c28a8b4b0acf704510b88f27f0934ac7a7bebdd8938d5e", size = 363294, upload-time = "2025-06-10T00:43:28.96Z" }, - { url = "https://files.pythonhosted.org/packages/eb/90/73448401d36fa4e210ece5579895731f190d5119c4b66b43b52182e88cd5/yarl-1.20.1-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:8601bc010d1d7780592f3fc1bdc6c72e2b6466ea34569778422943e1a1f3c389", size = 358169, upload-time = "2025-06-10T00:43:30.701Z" }, - { url = "https://files.pythonhosted.org/packages/c3/b0/fce922d46dc1eb43c811f1889f7daa6001b27a4005587e94878570300881/yarl-1.20.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:daadbdc1f2a9033a2399c42646fbd46da7992e868a5fe9513860122d7fe7a73f", size = 362776, upload-time = "2025-06-10T00:43:32.51Z" }, - { url = "https://files.pythonhosted.org/packages/f1/0d/b172628fce039dae8977fd22caeff3eeebffd52e86060413f5673767c427/yarl-1.20.1-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:03aa1e041727cb438ca762628109ef1333498b122e4c76dd858d186a37cec845", size = 381341, upload-time = "2025-06-10T00:43:34.543Z" }, - { url = "https://files.pythonhosted.org/packages/6b/9b/5b886d7671f4580209e855974fe1cecec409aa4a89ea58b8f0560dc529b1/yarl-1.20.1-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:642980ef5e0fa1de5fa96d905c7e00cb2c47cb468bfcac5a18c58e27dbf8d8d1", size = 379988, upload-time = "2025-06-10T00:43:36.489Z" }, - { url = "https://files.pythonhosted.org/packages/73/be/75ef5fd0fcd8f083a5d13f78fd3f009528132a1f2a1d7c925c39fa20aa79/yarl-1.20.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:86971e2795584fe8c002356d3b97ef6c61862720eeff03db2a7c86b678d85b3e", size = 371113, upload-time = "2025-06-10T00:43:38.592Z" }, - { url = "https://files.pythonhosted.org/packages/50/4f/62faab3b479dfdcb741fe9e3f0323e2a7d5cd1ab2edc73221d57ad4834b2/yarl-1.20.1-cp311-cp311-win32.whl", hash = "sha256:597f40615b8d25812f14562699e287f0dcc035d25eb74da72cae043bb884d773", size = 81485, upload-time = "2025-06-10T00:43:41.038Z" }, - { url = "https://files.pythonhosted.org/packages/f0/09/d9c7942f8f05c32ec72cd5c8e041c8b29b5807328b68b4801ff2511d4d5e/yarl-1.20.1-cp311-cp311-win_amd64.whl", hash = "sha256:26ef53a9e726e61e9cd1cda6b478f17e350fb5800b4bd1cd9fe81c4d91cfeb2e", size = 86686, upload-time = "2025-06-10T00:43:42.692Z" }, - { url = "https://files.pythonhosted.org/packages/5f/9a/cb7fad7d73c69f296eda6815e4a2c7ed53fc70c2f136479a91c8e5fbdb6d/yarl-1.20.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:bdcc4cd244e58593a4379fe60fdee5ac0331f8eb70320a24d591a3be197b94a9", size = 133667, upload-time = "2025-06-10T00:43:44.369Z" }, - { url = "https://files.pythonhosted.org/packages/67/38/688577a1cb1e656e3971fb66a3492501c5a5df56d99722e57c98249e5b8a/yarl-1.20.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:b29a2c385a5f5b9c7d9347e5812b6f7ab267193c62d282a540b4fc528c8a9d2a", size = 91025, upload-time = "2025-06-10T00:43:46.295Z" }, - { url = "https://files.pythonhosted.org/packages/50/ec/72991ae51febeb11a42813fc259f0d4c8e0507f2b74b5514618d8b640365/yarl-1.20.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:1112ae8154186dfe2de4732197f59c05a83dc814849a5ced892b708033f40dc2", size = 89709, upload-time = "2025-06-10T00:43:48.22Z" }, - { url = "https://files.pythonhosted.org/packages/99/da/4d798025490e89426e9f976702e5f9482005c548c579bdae792a4c37769e/yarl-1.20.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:90bbd29c4fe234233f7fa2b9b121fb63c321830e5d05b45153a2ca68f7d310ee", size = 352287, upload-time = "2025-06-10T00:43:49.924Z" }, - { url = "https://files.pythonhosted.org/packages/1a/26/54a15c6a567aac1c61b18aa0f4b8aa2e285a52d547d1be8bf48abe2b3991/yarl-1.20.1-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:680e19c7ce3710ac4cd964e90dad99bf9b5029372ba0c7cbfcd55e54d90ea819", size = 345429, upload-time = "2025-06-10T00:43:51.7Z" }, - { url = "https://files.pythonhosted.org/packages/d6/95/9dcf2386cb875b234353b93ec43e40219e14900e046bf6ac118f94b1e353/yarl-1.20.1-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4a979218c1fdb4246a05efc2cc23859d47c89af463a90b99b7c56094daf25a16", size = 365429, upload-time = "2025-06-10T00:43:53.494Z" }, - { url = "https://files.pythonhosted.org/packages/91/b2/33a8750f6a4bc224242a635f5f2cff6d6ad5ba651f6edcccf721992c21a0/yarl-1.20.1-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:255b468adf57b4a7b65d8aad5b5138dce6a0752c139965711bdcb81bc370e1b6", size = 363862, upload-time = "2025-06-10T00:43:55.766Z" }, - { url = "https://files.pythonhosted.org/packages/98/28/3ab7acc5b51f4434b181b0cee8f1f4b77a65919700a355fb3617f9488874/yarl-1.20.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a97d67108e79cfe22e2b430d80d7571ae57d19f17cda8bb967057ca8a7bf5bfd", size = 355616, upload-time = "2025-06-10T00:43:58.056Z" }, - { url = "https://files.pythonhosted.org/packages/36/a3/f666894aa947a371724ec7cd2e5daa78ee8a777b21509b4252dd7bd15e29/yarl-1.20.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8570d998db4ddbfb9a590b185a0a33dbf8aafb831d07a5257b4ec9948df9cb0a", size = 339954, upload-time = "2025-06-10T00:43:59.773Z" }, - { url = "https://files.pythonhosted.org/packages/f1/81/5f466427e09773c04219d3450d7a1256138a010b6c9f0af2d48565e9ad13/yarl-1.20.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:97c75596019baae7c71ccf1d8cc4738bc08134060d0adfcbe5642f778d1dca38", size = 365575, upload-time = "2025-06-10T00:44:02.051Z" }, - { url = "https://files.pythonhosted.org/packages/2e/e3/e4b0ad8403e97e6c9972dd587388940a032f030ebec196ab81a3b8e94d31/yarl-1.20.1-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:1c48912653e63aef91ff988c5432832692ac5a1d8f0fb8a33091520b5bbe19ef", size = 365061, upload-time = "2025-06-10T00:44:04.196Z" }, - { url = "https://files.pythonhosted.org/packages/ac/99/b8a142e79eb86c926f9f06452eb13ecb1bb5713bd01dc0038faf5452e544/yarl-1.20.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:4c3ae28f3ae1563c50f3d37f064ddb1511ecc1d5584e88c6b7c63cf7702a6d5f", size = 364142, upload-time = "2025-06-10T00:44:06.527Z" }, - { url = "https://files.pythonhosted.org/packages/34/f2/08ed34a4a506d82a1a3e5bab99ccd930a040f9b6449e9fd050320e45845c/yarl-1.20.1-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:c5e9642f27036283550f5f57dc6156c51084b458570b9d0d96100c8bebb186a8", size = 381894, upload-time = "2025-06-10T00:44:08.379Z" }, - { url = "https://files.pythonhosted.org/packages/92/f8/9a3fbf0968eac704f681726eff595dce9b49c8a25cd92bf83df209668285/yarl-1.20.1-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:2c26b0c49220d5799f7b22c6838409ee9bc58ee5c95361a4d7831f03cc225b5a", size = 383378, upload-time = "2025-06-10T00:44:10.51Z" }, - { url = "https://files.pythonhosted.org/packages/af/85/9363f77bdfa1e4d690957cd39d192c4cacd1c58965df0470a4905253b54f/yarl-1.20.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:564ab3d517e3d01c408c67f2e5247aad4019dcf1969982aba3974b4093279004", size = 374069, upload-time = "2025-06-10T00:44:12.834Z" }, - { url = "https://files.pythonhosted.org/packages/35/99/9918c8739ba271dcd935400cff8b32e3cd319eaf02fcd023d5dcd487a7c8/yarl-1.20.1-cp312-cp312-win32.whl", hash = "sha256:daea0d313868da1cf2fac6b2d3a25c6e3a9e879483244be38c8e6a41f1d876a5", size = 81249, upload-time = "2025-06-10T00:44:14.731Z" }, - { url = "https://files.pythonhosted.org/packages/eb/83/5d9092950565481b413b31a23e75dd3418ff0a277d6e0abf3729d4d1ce25/yarl-1.20.1-cp312-cp312-win_amd64.whl", hash = "sha256:48ea7d7f9be0487339828a4de0360d7ce0efc06524a48e1810f945c45b813698", size = 86710, upload-time = "2025-06-10T00:44:16.716Z" }, - { url = "https://files.pythonhosted.org/packages/8a/e1/2411b6d7f769a07687acee88a062af5833cf1966b7266f3d8dfb3d3dc7d3/yarl-1.20.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:0b5ff0fbb7c9f1b1b5ab53330acbfc5247893069e7716840c8e7d5bb7355038a", size = 131811, upload-time = "2025-06-10T00:44:18.933Z" }, - { url = "https://files.pythonhosted.org/packages/b2/27/584394e1cb76fb771371770eccad35de400e7b434ce3142c2dd27392c968/yarl-1.20.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:14f326acd845c2b2e2eb38fb1346c94f7f3b01a4f5c788f8144f9b630bfff9a3", size = 90078, upload-time = "2025-06-10T00:44:20.635Z" }, - { url = "https://files.pythonhosted.org/packages/bf/9a/3246ae92d4049099f52d9b0fe3486e3b500e29b7ea872d0f152966fc209d/yarl-1.20.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:f60e4ad5db23f0b96e49c018596707c3ae89f5d0bd97f0ad3684bcbad899f1e7", size = 88748, upload-time = "2025-06-10T00:44:22.34Z" }, - { url = "https://files.pythonhosted.org/packages/a3/25/35afe384e31115a1a801fbcf84012d7a066d89035befae7c5d4284df1e03/yarl-1.20.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:49bdd1b8e00ce57e68ba51916e4bb04461746e794e7c4d4bbc42ba2f18297691", size = 349595, upload-time = "2025-06-10T00:44:24.314Z" }, - { url = "https://files.pythonhosted.org/packages/28/2d/8aca6cb2cabc8f12efcb82749b9cefecbccfc7b0384e56cd71058ccee433/yarl-1.20.1-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:66252d780b45189975abfed839616e8fd2dbacbdc262105ad7742c6ae58f3e31", size = 342616, upload-time = "2025-06-10T00:44:26.167Z" }, - { url = "https://files.pythonhosted.org/packages/0b/e9/1312633d16b31acf0098d30440ca855e3492d66623dafb8e25b03d00c3da/yarl-1.20.1-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:59174e7332f5d153d8f7452a102b103e2e74035ad085f404df2e40e663a22b28", size = 361324, upload-time = "2025-06-10T00:44:27.915Z" }, - { url = "https://files.pythonhosted.org/packages/bc/a0/688cc99463f12f7669eec7c8acc71ef56a1521b99eab7cd3abb75af887b0/yarl-1.20.1-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e3968ec7d92a0c0f9ac34d5ecfd03869ec0cab0697c91a45db3fbbd95fe1b653", size = 359676, upload-time = "2025-06-10T00:44:30.041Z" }, - { url = "https://files.pythonhosted.org/packages/af/44/46407d7f7a56e9a85a4c207724c9f2c545c060380718eea9088f222ba697/yarl-1.20.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d1a4fbb50e14396ba3d375f68bfe02215d8e7bc3ec49da8341fe3157f59d2ff5", size = 352614, upload-time = "2025-06-10T00:44:32.171Z" }, - { url = "https://files.pythonhosted.org/packages/b1/91/31163295e82b8d5485d31d9cf7754d973d41915cadce070491778d9c9825/yarl-1.20.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:11a62c839c3a8eac2410e951301309426f368388ff2f33799052787035793b02", size = 336766, upload-time = "2025-06-10T00:44:34.494Z" }, - { url = "https://files.pythonhosted.org/packages/b4/8e/c41a5bc482121f51c083c4c2bcd16b9e01e1cf8729e380273a952513a21f/yarl-1.20.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:041eaa14f73ff5a8986b4388ac6bb43a77f2ea09bf1913df7a35d4646db69e53", size = 364615, upload-time = "2025-06-10T00:44:36.856Z" }, - { url = "https://files.pythonhosted.org/packages/e3/5b/61a3b054238d33d70ea06ebba7e58597891b71c699e247df35cc984ab393/yarl-1.20.1-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:377fae2fef158e8fd9d60b4c8751387b8d1fb121d3d0b8e9b0be07d1b41e83dc", size = 360982, upload-time = "2025-06-10T00:44:39.141Z" }, - { url = "https://files.pythonhosted.org/packages/df/a3/6a72fb83f8d478cb201d14927bc8040af901811a88e0ff2da7842dd0ed19/yarl-1.20.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:1c92f4390e407513f619d49319023664643d3339bd5e5a56a3bebe01bc67ec04", size = 369792, upload-time = "2025-06-10T00:44:40.934Z" }, - { url = "https://files.pythonhosted.org/packages/7c/af/4cc3c36dfc7c077f8dedb561eb21f69e1e9f2456b91b593882b0b18c19dc/yarl-1.20.1-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:d25ddcf954df1754ab0f86bb696af765c5bfaba39b74095f27eececa049ef9a4", size = 382049, upload-time = "2025-06-10T00:44:42.854Z" }, - { url = "https://files.pythonhosted.org/packages/19/3a/e54e2c4752160115183a66dc9ee75a153f81f3ab2ba4bf79c3c53b33de34/yarl-1.20.1-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:909313577e9619dcff8c31a0ea2aa0a2a828341d92673015456b3ae492e7317b", size = 384774, upload-time = "2025-06-10T00:44:45.275Z" }, - { url = "https://files.pythonhosted.org/packages/9c/20/200ae86dabfca89060ec6447649f219b4cbd94531e425e50d57e5f5ac330/yarl-1.20.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:793fd0580cb9664548c6b83c63b43c477212c0260891ddf86809e1c06c8b08f1", size = 374252, upload-time = "2025-06-10T00:44:47.31Z" }, - { url = "https://files.pythonhosted.org/packages/83/75/11ee332f2f516b3d094e89448da73d557687f7d137d5a0f48c40ff211487/yarl-1.20.1-cp313-cp313-win32.whl", hash = "sha256:468f6e40285de5a5b3c44981ca3a319a4b208ccc07d526b20b12aeedcfa654b7", size = 81198, upload-time = "2025-06-10T00:44:49.164Z" }, - { url = "https://files.pythonhosted.org/packages/ba/ba/39b1ecbf51620b40ab402b0fc817f0ff750f6d92712b44689c2c215be89d/yarl-1.20.1-cp313-cp313-win_amd64.whl", hash = "sha256:495b4ef2fea40596bfc0affe3837411d6aa3371abcf31aac0ccc4bdd64d4ef5c", size = 86346, upload-time = "2025-06-10T00:44:51.182Z" }, - { url = "https://files.pythonhosted.org/packages/43/c7/669c52519dca4c95153c8ad96dd123c79f354a376346b198f438e56ffeb4/yarl-1.20.1-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:f60233b98423aab21d249a30eb27c389c14929f47be8430efa7dbd91493a729d", size = 138826, upload-time = "2025-06-10T00:44:52.883Z" }, - { url = "https://files.pythonhosted.org/packages/6a/42/fc0053719b44f6ad04a75d7f05e0e9674d45ef62f2d9ad2c1163e5c05827/yarl-1.20.1-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:6f3eff4cc3f03d650d8755c6eefc844edde99d641d0dcf4da3ab27141a5f8ddf", size = 93217, upload-time = "2025-06-10T00:44:54.658Z" }, - { url = "https://files.pythonhosted.org/packages/4f/7f/fa59c4c27e2a076bba0d959386e26eba77eb52ea4a0aac48e3515c186b4c/yarl-1.20.1-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:69ff8439d8ba832d6bed88af2c2b3445977eba9a4588b787b32945871c2444e3", size = 92700, upload-time = "2025-06-10T00:44:56.784Z" }, - { url = "https://files.pythonhosted.org/packages/2f/d4/062b2f48e7c93481e88eff97a6312dca15ea200e959f23e96d8ab898c5b8/yarl-1.20.1-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3cf34efa60eb81dd2645a2e13e00bb98b76c35ab5061a3989c7a70f78c85006d", size = 347644, upload-time = "2025-06-10T00:44:59.071Z" }, - { url = "https://files.pythonhosted.org/packages/89/47/78b7f40d13c8f62b499cc702fdf69e090455518ae544c00a3bf4afc9fc77/yarl-1.20.1-cp313-cp313t-manylinux_2_17_armv7l.manylinux2014_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:8e0fe9364ad0fddab2688ce72cb7a8e61ea42eff3c7caeeb83874a5d479c896c", size = 323452, upload-time = "2025-06-10T00:45:01.605Z" }, - { url = "https://files.pythonhosted.org/packages/eb/2b/490d3b2dc66f52987d4ee0d3090a147ea67732ce6b4d61e362c1846d0d32/yarl-1.20.1-cp313-cp313t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8f64fbf81878ba914562c672024089e3401974a39767747691c65080a67b18c1", size = 346378, upload-time = "2025-06-10T00:45:03.946Z" }, - { url = "https://files.pythonhosted.org/packages/66/ad/775da9c8a94ce925d1537f939a4f17d782efef1f973039d821cbe4bcc211/yarl-1.20.1-cp313-cp313t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f6342d643bf9a1de97e512e45e4b9560a043347e779a173250824f8b254bd5ce", size = 353261, upload-time = "2025-06-10T00:45:05.992Z" }, - { url = "https://files.pythonhosted.org/packages/4b/23/0ed0922b47a4f5c6eb9065d5ff1e459747226ddce5c6a4c111e728c9f701/yarl-1.20.1-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:56dac5f452ed25eef0f6e3c6a066c6ab68971d96a9fb441791cad0efba6140d3", size = 335987, upload-time = "2025-06-10T00:45:08.227Z" }, - { url = "https://files.pythonhosted.org/packages/3e/49/bc728a7fe7d0e9336e2b78f0958a2d6b288ba89f25a1762407a222bf53c3/yarl-1.20.1-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c7d7f497126d65e2cad8dc5f97d34c27b19199b6414a40cb36b52f41b79014be", size = 329361, upload-time = "2025-06-10T00:45:10.11Z" }, - { url = "https://files.pythonhosted.org/packages/93/8f/b811b9d1f617c83c907e7082a76e2b92b655400e61730cd61a1f67178393/yarl-1.20.1-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:67e708dfb8e78d8a19169818eeb5c7a80717562de9051bf2413aca8e3696bf16", size = 346460, upload-time = "2025-06-10T00:45:12.055Z" }, - { url = "https://files.pythonhosted.org/packages/70/fd/af94f04f275f95da2c3b8b5e1d49e3e79f1ed8b6ceb0f1664cbd902773ff/yarl-1.20.1-cp313-cp313t-musllinux_1_2_armv7l.whl", hash = "sha256:595c07bc79af2494365cc96ddeb772f76272364ef7c80fb892ef9d0649586513", size = 334486, upload-time = "2025-06-10T00:45:13.995Z" }, - { url = "https://files.pythonhosted.org/packages/84/65/04c62e82704e7dd0a9b3f61dbaa8447f8507655fd16c51da0637b39b2910/yarl-1.20.1-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:7bdd2f80f4a7df852ab9ab49484a4dee8030023aa536df41f2d922fd57bf023f", size = 342219, upload-time = "2025-06-10T00:45:16.479Z" }, - { url = "https://files.pythonhosted.org/packages/91/95/459ca62eb958381b342d94ab9a4b6aec1ddec1f7057c487e926f03c06d30/yarl-1.20.1-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:c03bfebc4ae8d862f853a9757199677ab74ec25424d0ebd68a0027e9c639a390", size = 350693, upload-time = "2025-06-10T00:45:18.399Z" }, - { url = "https://files.pythonhosted.org/packages/a6/00/d393e82dd955ad20617abc546a8f1aee40534d599ff555ea053d0ec9bf03/yarl-1.20.1-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:344d1103e9c1523f32a5ed704d576172d2cabed3122ea90b1d4e11fe17c66458", size = 355803, upload-time = "2025-06-10T00:45:20.677Z" }, - { url = "https://files.pythonhosted.org/packages/9e/ed/c5fb04869b99b717985e244fd93029c7a8e8febdfcffa06093e32d7d44e7/yarl-1.20.1-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:88cab98aa4e13e1ade8c141daeedd300a4603b7132819c484841bb7af3edce9e", size = 341709, upload-time = "2025-06-10T00:45:23.221Z" }, - { url = "https://files.pythonhosted.org/packages/24/fd/725b8e73ac2a50e78a4534ac43c6addf5c1c2d65380dd48a9169cc6739a9/yarl-1.20.1-cp313-cp313t-win32.whl", hash = "sha256:b121ff6a7cbd4abc28985b6028235491941b9fe8fe226e6fdc539c977ea1739d", size = 86591, upload-time = "2025-06-10T00:45:25.793Z" }, - { url = "https://files.pythonhosted.org/packages/94/c3/b2e9f38bc3e11191981d57ea08cab2166e74ea770024a646617c9cddd9f6/yarl-1.20.1-cp313-cp313t-win_amd64.whl", hash = "sha256:541d050a355bbbc27e55d906bc91cb6fe42f96c01413dd0f4ed5a5240513874f", size = 93003, upload-time = "2025-06-10T00:45:27.752Z" }, - { url = "https://files.pythonhosted.org/packages/b4/2d/2345fce04cfd4bee161bf1e7d9cdc702e3e16109021035dbb24db654a622/yarl-1.20.1-py3-none-any.whl", hash = "sha256:83b8eb083fe4683c6115795d9fc1cfaf2cbbefb19b3a1cb68f6527460f483a77", size = 46542, upload-time = "2025-06-10T00:46:07.521Z" }, -] - -[[package]] -name = "zipp" -version = "3.23.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/e3/02/0f2892c661036d50ede074e376733dca2ae7c6eb617489437771209d4180/zipp-3.23.0.tar.gz", hash = "sha256:a07157588a12518c9d4034df3fbbee09c814741a33ff63c05fa29d26a2404166", size = 25547, upload-time = "2025-06-08T17:06:39.4Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/2e/54/647ade08bf0db230bfea292f893923872fd20be6ac6f53b2b936ba839d75/zipp-3.23.0-py3-none-any.whl", hash = "sha256:071652d6115ed432f5ce1d34c336c0adfd6a884660d1e9712a256d3d3bd4b14e", size = 10276, upload-time = "2025-06-08T17:06:38.034Z" }, -] - -[[package]] -name = "zstandard" -version = "0.25.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/fd/aa/3e0508d5a5dd96529cdc5a97011299056e14c6505b678fd58938792794b1/zstandard-0.25.0.tar.gz", hash = "sha256:7713e1179d162cf5c7906da876ec2ccb9c3a9dcbdffef0cc7f70c3667a205f0b", size = 711513, upload-time = "2025-09-14T22:15:54.002Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/56/7a/28efd1d371f1acd037ac64ed1c5e2b41514a6cc937dd6ab6a13ab9f0702f/zstandard-0.25.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e59fdc271772f6686e01e1b3b74537259800f57e24280be3f29c8a0deb1904dd", size = 795256, upload-time = "2025-09-14T22:15:56.415Z" }, - { url = "https://files.pythonhosted.org/packages/96/34/ef34ef77f1ee38fc8e4f9775217a613b452916e633c4f1d98f31db52c4a5/zstandard-0.25.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4d441506e9b372386a5271c64125f72d5df6d2a8e8a2a45a0ae09b03cb781ef7", size = 640565, upload-time = "2025-09-14T22:15:58.177Z" }, - { url = "https://files.pythonhosted.org/packages/9d/1b/4fdb2c12eb58f31f28c4d28e8dc36611dd7205df8452e63f52fb6261d13e/zstandard-0.25.0-cp310-cp310-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:ab85470ab54c2cb96e176f40342d9ed41e58ca5733be6a893b730e7af9c40550", size = 5345306, upload-time = "2025-09-14T22:16:00.165Z" }, - { url = "https://files.pythonhosted.org/packages/73/28/a44bdece01bca027b079f0e00be3b6bd89a4df180071da59a3dd7381665b/zstandard-0.25.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:e05ab82ea7753354bb054b92e2f288afb750e6b439ff6ca78af52939ebbc476d", size = 5055561, upload-time = "2025-09-14T22:16:02.22Z" }, - { url = "https://files.pythonhosted.org/packages/e9/74/68341185a4f32b274e0fc3410d5ad0750497e1acc20bd0f5b5f64ce17785/zstandard-0.25.0-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:78228d8a6a1c177a96b94f7e2e8d012c55f9c760761980da16ae7546a15a8e9b", size = 5402214, upload-time = "2025-09-14T22:16:04.109Z" }, - { url = "https://files.pythonhosted.org/packages/8b/67/f92e64e748fd6aaffe01e2b75a083c0c4fd27abe1c8747fee4555fcee7dd/zstandard-0.25.0-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:2b6bd67528ee8b5c5f10255735abc21aa106931f0dbaf297c7be0c886353c3d0", size = 5449703, upload-time = "2025-09-14T22:16:06.312Z" }, - { url = "https://files.pythonhosted.org/packages/fd/e5/6d36f92a197c3c17729a2125e29c169f460538a7d939a27eaaa6dcfcba8e/zstandard-0.25.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4b6d83057e713ff235a12e73916b6d356e3084fd3d14ced499d84240f3eecee0", size = 5556583, upload-time = "2025-09-14T22:16:08.457Z" }, - { url = "https://files.pythonhosted.org/packages/d7/83/41939e60d8d7ebfe2b747be022d0806953799140a702b90ffe214d557638/zstandard-0.25.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:9174f4ed06f790a6869b41cba05b43eeb9a35f8993c4422ab853b705e8112bbd", size = 5045332, upload-time = "2025-09-14T22:16:10.444Z" }, - { url = "https://files.pythonhosted.org/packages/b3/87/d3ee185e3d1aa0133399893697ae91f221fda79deb61adbe998a7235c43f/zstandard-0.25.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:25f8f3cd45087d089aef5ba3848cd9efe3ad41163d3400862fb42f81a3a46701", size = 5572283, upload-time = "2025-09-14T22:16:12.128Z" }, - { url = "https://files.pythonhosted.org/packages/0a/1d/58635ae6104df96671076ac7d4ae7816838ce7debd94aecf83e30b7121b0/zstandard-0.25.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:3756b3e9da9b83da1796f8809dd57cb024f838b9eeafde28f3cb472012797ac1", size = 4959754, upload-time = "2025-09-14T22:16:14.225Z" }, - { url = "https://files.pythonhosted.org/packages/75/d6/57e9cb0a9983e9a229dd8fd2e6e96593ef2aa82a3907188436f22b111ccd/zstandard-0.25.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:81dad8d145d8fd981b2962b686b2241d3a1ea07733e76a2f15435dfb7fb60150", size = 5266477, upload-time = "2025-09-14T22:16:16.343Z" }, - { url = "https://files.pythonhosted.org/packages/d1/a9/ee891e5edf33a6ebce0a028726f0bbd8567effe20fe3d5808c42323e8542/zstandard-0.25.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:a5a419712cf88862a45a23def0ae063686db3d324cec7edbe40509d1a79a0aab", size = 5440914, upload-time = "2025-09-14T22:16:18.453Z" }, - { url = "https://files.pythonhosted.org/packages/58/08/a8522c28c08031a9521f27abc6f78dbdee7312a7463dd2cfc658b813323b/zstandard-0.25.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:e7360eae90809efd19b886e59a09dad07da4ca9ba096752e61a2e03c8aca188e", size = 5819847, upload-time = "2025-09-14T22:16:20.559Z" }, - { url = "https://files.pythonhosted.org/packages/6f/11/4c91411805c3f7b6f31c60e78ce347ca48f6f16d552fc659af6ec3b73202/zstandard-0.25.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:75ffc32a569fb049499e63ce68c743155477610532da1eb38e7f24bf7cd29e74", size = 5363131, upload-time = "2025-09-14T22:16:22.206Z" }, - { url = "https://files.pythonhosted.org/packages/ef/d6/8c4bd38a3b24c4c7676a7a3d8de85d6ee7a983602a734b9f9cdefb04a5d6/zstandard-0.25.0-cp310-cp310-win32.whl", hash = "sha256:106281ae350e494f4ac8a80470e66d1fe27e497052c8d9c3b95dc4cf1ade81aa", size = 436469, upload-time = "2025-09-14T22:16:25.002Z" }, - { url = "https://files.pythonhosted.org/packages/93/90/96d50ad417a8ace5f841b3228e93d1bb13e6ad356737f42e2dde30d8bd68/zstandard-0.25.0-cp310-cp310-win_amd64.whl", hash = "sha256:ea9d54cc3d8064260114a0bbf3479fc4a98b21dffc89b3459edd506b69262f6e", size = 506100, upload-time = "2025-09-14T22:16:23.569Z" }, - { url = "https://files.pythonhosted.org/packages/2a/83/c3ca27c363d104980f1c9cee1101cc8ba724ac8c28a033ede6aab89585b1/zstandard-0.25.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:933b65d7680ea337180733cf9e87293cc5500cc0eb3fc8769f4d3c88d724ec5c", size = 795254, upload-time = "2025-09-14T22:16:26.137Z" }, - { url = "https://files.pythonhosted.org/packages/ac/4d/e66465c5411a7cf4866aeadc7d108081d8ceba9bc7abe6b14aa21c671ec3/zstandard-0.25.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a3f79487c687b1fc69f19e487cd949bf3aae653d181dfb5fde3bf6d18894706f", size = 640559, upload-time = "2025-09-14T22:16:27.973Z" }, - { url = "https://files.pythonhosted.org/packages/12/56/354fe655905f290d3b147b33fe946b0f27e791e4b50a5f004c802cb3eb7b/zstandard-0.25.0-cp311-cp311-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:0bbc9a0c65ce0eea3c34a691e3c4b6889f5f3909ba4822ab385fab9057099431", size = 5348020, upload-time = "2025-09-14T22:16:29.523Z" }, - { url = "https://files.pythonhosted.org/packages/3b/13/2b7ed68bd85e69a2069bcc72141d378f22cae5a0f3b353a2c8f50ef30c1b/zstandard-0.25.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:01582723b3ccd6939ab7b3a78622c573799d5d8737b534b86d0e06ac18dbde4a", size = 5058126, upload-time = "2025-09-14T22:16:31.811Z" }, - { url = "https://files.pythonhosted.org/packages/c9/dd/fdaf0674f4b10d92cb120ccff58bbb6626bf8368f00ebfd2a41ba4a0dc99/zstandard-0.25.0-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:5f1ad7bf88535edcf30038f6919abe087f606f62c00a87d7e33e7fc57cb69fcc", size = 5405390, upload-time = "2025-09-14T22:16:33.486Z" }, - { url = "https://files.pythonhosted.org/packages/0f/67/354d1555575bc2490435f90d67ca4dd65238ff2f119f30f72d5cde09c2ad/zstandard-0.25.0-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:06acb75eebeedb77b69048031282737717a63e71e4ae3f77cc0c3b9508320df6", size = 5452914, upload-time = "2025-09-14T22:16:35.277Z" }, - { url = "https://files.pythonhosted.org/packages/bb/1f/e9cfd801a3f9190bf3e759c422bbfd2247db9d7f3d54a56ecde70137791a/zstandard-0.25.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9300d02ea7c6506f00e627e287e0492a5eb0371ec1670ae852fefffa6164b072", size = 5559635, upload-time = "2025-09-14T22:16:37.141Z" }, - { url = "https://files.pythonhosted.org/packages/21/88/5ba550f797ca953a52d708c8e4f380959e7e3280af029e38fbf47b55916e/zstandard-0.25.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:bfd06b1c5584b657a2892a6014c2f4c20e0db0208c159148fa78c65f7e0b0277", size = 5048277, upload-time = "2025-09-14T22:16:38.807Z" }, - { url = "https://files.pythonhosted.org/packages/46/c0/ca3e533b4fa03112facbe7fbe7779cb1ebec215688e5df576fe5429172e0/zstandard-0.25.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:f373da2c1757bb7f1acaf09369cdc1d51d84131e50d5fa9863982fd626466313", size = 5574377, upload-time = "2025-09-14T22:16:40.523Z" }, - { url = "https://files.pythonhosted.org/packages/12/9b/3fb626390113f272abd0799fd677ea33d5fc3ec185e62e6be534493c4b60/zstandard-0.25.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:6c0e5a65158a7946e7a7affa6418878ef97ab66636f13353b8502d7ea03c8097", size = 4961493, upload-time = "2025-09-14T22:16:43.3Z" }, - { url = "https://files.pythonhosted.org/packages/cb/d3/23094a6b6a4b1343b27ae68249daa17ae0651fcfec9ed4de09d14b940285/zstandard-0.25.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:c8e167d5adf59476fa3e37bee730890e389410c354771a62e3c076c86f9f7778", size = 5269018, upload-time = "2025-09-14T22:16:45.292Z" }, - { url = "https://files.pythonhosted.org/packages/8c/a7/bb5a0c1c0f3f4b5e9d5b55198e39de91e04ba7c205cc46fcb0f95f0383c1/zstandard-0.25.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:98750a309eb2f020da61e727de7d7ba3c57c97cf6213f6f6277bb7fb42a8e065", size = 5443672, upload-time = "2025-09-14T22:16:47.076Z" }, - { url = "https://files.pythonhosted.org/packages/27/22/503347aa08d073993f25109c36c8d9f029c7d5949198050962cb568dfa5e/zstandard-0.25.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:22a086cff1b6ceca18a8dd6096ec631e430e93a8e70a9ca5efa7561a00f826fa", size = 5822753, upload-time = "2025-09-14T22:16:49.316Z" }, - { url = "https://files.pythonhosted.org/packages/e2/be/94267dc6ee64f0f8ba2b2ae7c7a2df934a816baaa7291db9e1aa77394c3c/zstandard-0.25.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:72d35d7aa0bba323965da807a462b0966c91608ef3a48ba761678cb20ce5d8b7", size = 5366047, upload-time = "2025-09-14T22:16:51.328Z" }, - { url = "https://files.pythonhosted.org/packages/7b/a3/732893eab0a3a7aecff8b99052fecf9f605cf0fb5fb6d0290e36beee47a4/zstandard-0.25.0-cp311-cp311-win32.whl", hash = "sha256:f5aeea11ded7320a84dcdd62a3d95b5186834224a9e55b92ccae35d21a8b63d4", size = 436484, upload-time = "2025-09-14T22:16:55.005Z" }, - { url = "https://files.pythonhosted.org/packages/43/a3/c6155f5c1cce691cb80dfd38627046e50af3ee9ddc5d0b45b9b063bfb8c9/zstandard-0.25.0-cp311-cp311-win_amd64.whl", hash = "sha256:daab68faadb847063d0c56f361a289c4f268706b598afbf9ad113cbe5c38b6b2", size = 506183, upload-time = "2025-09-14T22:16:52.753Z" }, - { url = "https://files.pythonhosted.org/packages/8c/3e/8945ab86a0820cc0e0cdbf38086a92868a9172020fdab8a03ac19662b0e5/zstandard-0.25.0-cp311-cp311-win_arm64.whl", hash = "sha256:22a06c5df3751bb7dc67406f5374734ccee8ed37fc5981bf1ad7041831fa1137", size = 462533, upload-time = "2025-09-14T22:16:53.878Z" }, - { url = "https://files.pythonhosted.org/packages/82/fc/f26eb6ef91ae723a03e16eddb198abcfce2bc5a42e224d44cc8b6765e57e/zstandard-0.25.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7b3c3a3ab9daa3eed242d6ecceead93aebbb8f5f84318d82cee643e019c4b73b", size = 795738, upload-time = "2025-09-14T22:16:56.237Z" }, - { url = "https://files.pythonhosted.org/packages/aa/1c/d920d64b22f8dd028a8b90e2d756e431a5d86194caa78e3819c7bf53b4b3/zstandard-0.25.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:913cbd31a400febff93b564a23e17c3ed2d56c064006f54efec210d586171c00", size = 640436, upload-time = "2025-09-14T22:16:57.774Z" }, - { url = "https://files.pythonhosted.org/packages/53/6c/288c3f0bd9fcfe9ca41e2c2fbfd17b2097f6af57b62a81161941f09afa76/zstandard-0.25.0-cp312-cp312-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:011d388c76b11a0c165374ce660ce2c8efa8e5d87f34996aa80f9c0816698b64", size = 5343019, upload-time = "2025-09-14T22:16:59.302Z" }, - { url = "https://files.pythonhosted.org/packages/1e/15/efef5a2f204a64bdb5571e6161d49f7ef0fffdbca953a615efbec045f60f/zstandard-0.25.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:6dffecc361d079bb48d7caef5d673c88c8988d3d33fb74ab95b7ee6da42652ea", size = 5063012, upload-time = "2025-09-14T22:17:01.156Z" }, - { url = "https://files.pythonhosted.org/packages/b7/37/a6ce629ffdb43959e92e87ebdaeebb5ac81c944b6a75c9c47e300f85abdf/zstandard-0.25.0-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:7149623bba7fdf7e7f24312953bcf73cae103db8cae49f8154dd1eadc8a29ecb", size = 5394148, upload-time = "2025-09-14T22:17:03.091Z" }, - { url = "https://files.pythonhosted.org/packages/e3/79/2bf870b3abeb5c070fe2d670a5a8d1057a8270f125ef7676d29ea900f496/zstandard-0.25.0-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:6a573a35693e03cf1d67799fd01b50ff578515a8aeadd4595d2a7fa9f3ec002a", size = 5451652, upload-time = "2025-09-14T22:17:04.979Z" }, - { url = "https://files.pythonhosted.org/packages/53/60/7be26e610767316c028a2cbedb9a3beabdbe33e2182c373f71a1c0b88f36/zstandard-0.25.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:5a56ba0db2d244117ed744dfa8f6f5b366e14148e00de44723413b2f3938a902", size = 5546993, upload-time = "2025-09-14T22:17:06.781Z" }, - { url = "https://files.pythonhosted.org/packages/85/c7/3483ad9ff0662623f3648479b0380d2de5510abf00990468c286c6b04017/zstandard-0.25.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:10ef2a79ab8e2974e2075fb984e5b9806c64134810fac21576f0668e7ea19f8f", size = 5046806, upload-time = "2025-09-14T22:17:08.415Z" }, - { url = "https://files.pythonhosted.org/packages/08/b3/206883dd25b8d1591a1caa44b54c2aad84badccf2f1de9e2d60a446f9a25/zstandard-0.25.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:aaf21ba8fb76d102b696781bddaa0954b782536446083ae3fdaa6f16b25a1c4b", size = 5576659, upload-time = "2025-09-14T22:17:10.164Z" }, - { url = "https://files.pythonhosted.org/packages/9d/31/76c0779101453e6c117b0ff22565865c54f48f8bd807df2b00c2c404b8e0/zstandard-0.25.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:1869da9571d5e94a85a5e8d57e4e8807b175c9e4a6294e3b66fa4efb074d90f6", size = 4953933, upload-time = "2025-09-14T22:17:11.857Z" }, - { url = "https://files.pythonhosted.org/packages/18/e1/97680c664a1bf9a247a280a053d98e251424af51f1b196c6d52f117c9720/zstandard-0.25.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:809c5bcb2c67cd0ed81e9229d227d4ca28f82d0f778fc5fea624a9def3963f91", size = 5268008, upload-time = "2025-09-14T22:17:13.627Z" }, - { url = "https://files.pythonhosted.org/packages/1e/73/316e4010de585ac798e154e88fd81bb16afc5c5cb1a72eeb16dd37e8024a/zstandard-0.25.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:f27662e4f7dbf9f9c12391cb37b4c4c3cb90ffbd3b1fb9284dadbbb8935fa708", size = 5433517, upload-time = "2025-09-14T22:17:16.103Z" }, - { url = "https://files.pythonhosted.org/packages/5b/60/dd0f8cfa8129c5a0ce3ea6b7f70be5b33d2618013a161e1ff26c2b39787c/zstandard-0.25.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:99c0c846e6e61718715a3c9437ccc625de26593fea60189567f0118dc9db7512", size = 5814292, upload-time = "2025-09-14T22:17:17.827Z" }, - { url = "https://files.pythonhosted.org/packages/fc/5f/75aafd4b9d11b5407b641b8e41a57864097663699f23e9ad4dbb91dc6bfe/zstandard-0.25.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:474d2596a2dbc241a556e965fb76002c1ce655445e4e3bf38e5477d413165ffa", size = 5360237, upload-time = "2025-09-14T22:17:19.954Z" }, - { url = "https://files.pythonhosted.org/packages/ff/8d/0309daffea4fcac7981021dbf21cdb2e3427a9e76bafbcdbdf5392ff99a4/zstandard-0.25.0-cp312-cp312-win32.whl", hash = "sha256:23ebc8f17a03133b4426bcc04aabd68f8236eb78c3760f12783385171b0fd8bd", size = 436922, upload-time = "2025-09-14T22:17:24.398Z" }, - { url = "https://files.pythonhosted.org/packages/79/3b/fa54d9015f945330510cb5d0b0501e8253c127cca7ebe8ba46a965df18c5/zstandard-0.25.0-cp312-cp312-win_amd64.whl", hash = "sha256:ffef5a74088f1e09947aecf91011136665152e0b4b359c42be3373897fb39b01", size = 506276, upload-time = "2025-09-14T22:17:21.429Z" }, - { url = "https://files.pythonhosted.org/packages/ea/6b/8b51697e5319b1f9ac71087b0af9a40d8a6288ff8025c36486e0c12abcc4/zstandard-0.25.0-cp312-cp312-win_arm64.whl", hash = "sha256:181eb40e0b6a29b3cd2849f825e0fa34397f649170673d385f3598ae17cca2e9", size = 462679, upload-time = "2025-09-14T22:17:23.147Z" }, - { url = "https://files.pythonhosted.org/packages/35/0b/8df9c4ad06af91d39e94fa96cc010a24ac4ef1378d3efab9223cc8593d40/zstandard-0.25.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:ec996f12524f88e151c339688c3897194821d7f03081ab35d31d1e12ec975e94", size = 795735, upload-time = "2025-09-14T22:17:26.042Z" }, - { url = "https://files.pythonhosted.org/packages/3f/06/9ae96a3e5dcfd119377ba33d4c42a7d89da1efabd5cb3e366b156c45ff4d/zstandard-0.25.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a1a4ae2dec3993a32247995bdfe367fc3266da832d82f8438c8570f989753de1", size = 640440, upload-time = "2025-09-14T22:17:27.366Z" }, - { url = "https://files.pythonhosted.org/packages/d9/14/933d27204c2bd404229c69f445862454dcc101cd69ef8c6068f15aaec12c/zstandard-0.25.0-cp313-cp313-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:e96594a5537722fdfb79951672a2a63aec5ebfb823e7560586f7484819f2a08f", size = 5343070, upload-time = "2025-09-14T22:17:28.896Z" }, - { url = "https://files.pythonhosted.org/packages/6d/db/ddb11011826ed7db9d0e485d13df79b58586bfdec56e5c84a928a9a78c1c/zstandard-0.25.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:bfc4e20784722098822e3eee42b8e576b379ed72cca4a7cb856ae733e62192ea", size = 5063001, upload-time = "2025-09-14T22:17:31.044Z" }, - { url = "https://files.pythonhosted.org/packages/db/00/87466ea3f99599d02a5238498b87bf84a6348290c19571051839ca943777/zstandard-0.25.0-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:457ed498fc58cdc12fc48f7950e02740d4f7ae9493dd4ab2168a47c93c31298e", size = 5394120, upload-time = "2025-09-14T22:17:32.711Z" }, - { url = "https://files.pythonhosted.org/packages/2b/95/fc5531d9c618a679a20ff6c29e2b3ef1d1f4ad66c5e161ae6ff847d102a9/zstandard-0.25.0-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:fd7a5004eb1980d3cefe26b2685bcb0b17989901a70a1040d1ac86f1d898c551", size = 5451230, upload-time = "2025-09-14T22:17:34.41Z" }, - { url = "https://files.pythonhosted.org/packages/63/4b/e3678b4e776db00f9f7b2fe58e547e8928ef32727d7a1ff01dea010f3f13/zstandard-0.25.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:8e735494da3db08694d26480f1493ad2cf86e99bdd53e8e9771b2752a5c0246a", size = 5547173, upload-time = "2025-09-14T22:17:36.084Z" }, - { url = "https://files.pythonhosted.org/packages/4e/d5/ba05ed95c6b8ec30bd468dfeab20589f2cf709b5c940483e31d991f2ca58/zstandard-0.25.0-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:3a39c94ad7866160a4a46d772e43311a743c316942037671beb264e395bdd611", size = 5046736, upload-time = "2025-09-14T22:17:37.891Z" }, - { url = "https://files.pythonhosted.org/packages/50/d5/870aa06b3a76c73eced65c044b92286a3c4e00554005ff51962deef28e28/zstandard-0.25.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:172de1f06947577d3a3005416977cce6168f2261284c02080e7ad0185faeced3", size = 5576368, upload-time = "2025-09-14T22:17:40.206Z" }, - { url = "https://files.pythonhosted.org/packages/5d/35/398dc2ffc89d304d59bc12f0fdd931b4ce455bddf7038a0a67733a25f550/zstandard-0.25.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:3c83b0188c852a47cd13ef3bf9209fb0a77fa5374958b8c53aaa699398c6bd7b", size = 4954022, upload-time = "2025-09-14T22:17:41.879Z" }, - { url = "https://files.pythonhosted.org/packages/9a/5c/36ba1e5507d56d2213202ec2b05e8541734af5f2ce378c5d1ceaf4d88dc4/zstandard-0.25.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:1673b7199bbe763365b81a4f3252b8e80f44c9e323fc42940dc8843bfeaf9851", size = 5267889, upload-time = "2025-09-14T22:17:43.577Z" }, - { url = "https://files.pythonhosted.org/packages/70/e8/2ec6b6fb7358b2ec0113ae202647ca7c0e9d15b61c005ae5225ad0995df5/zstandard-0.25.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:0be7622c37c183406f3dbf0cba104118eb16a4ea7359eeb5752f0794882fc250", size = 5433952, upload-time = "2025-09-14T22:17:45.271Z" }, - { url = "https://files.pythonhosted.org/packages/7b/01/b5f4d4dbc59ef193e870495c6f1275f5b2928e01ff5a81fecb22a06e22fb/zstandard-0.25.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:5f5e4c2a23ca271c218ac025bd7d635597048b366d6f31f420aaeb715239fc98", size = 5814054, upload-time = "2025-09-14T22:17:47.08Z" }, - { url = "https://files.pythonhosted.org/packages/b2/e5/fbd822d5c6f427cf158316d012c5a12f233473c2f9c5fe5ab1ae5d21f3d8/zstandard-0.25.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:4f187a0bb61b35119d1926aee039524d1f93aaf38a9916b8c4b78ac8514a0aaf", size = 5360113, upload-time = "2025-09-14T22:17:48.893Z" }, - { url = "https://files.pythonhosted.org/packages/8e/e0/69a553d2047f9a2c7347caa225bb3a63b6d7704ad74610cb7823baa08ed7/zstandard-0.25.0-cp313-cp313-win32.whl", hash = "sha256:7030defa83eef3e51ff26f0b7bfb229f0204b66fe18e04359ce3474ac33cbc09", size = 436936, upload-time = "2025-09-14T22:17:52.658Z" }, - { url = "https://files.pythonhosted.org/packages/d9/82/b9c06c870f3bd8767c201f1edbdf9e8dc34be5b0fbc5682c4f80fe948475/zstandard-0.25.0-cp313-cp313-win_amd64.whl", hash = "sha256:1f830a0dac88719af0ae43b8b2d6aef487d437036468ef3c2ea59c51f9d55fd5", size = 506232, upload-time = "2025-09-14T22:17:50.402Z" }, - { url = "https://files.pythonhosted.org/packages/d4/57/60c3c01243bb81d381c9916e2a6d9e149ab8627c0c7d7abb2d73384b3c0c/zstandard-0.25.0-cp313-cp313-win_arm64.whl", hash = "sha256:85304a43f4d513f5464ceb938aa02c1e78c2943b29f44a750b48b25ac999a049", size = 462671, upload-time = "2025-09-14T22:17:51.533Z" }, - { url = "https://files.pythonhosted.org/packages/3d/5c/f8923b595b55fe49e30612987ad8bf053aef555c14f05bb659dd5dbe3e8a/zstandard-0.25.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:e29f0cf06974c899b2c188ef7f783607dbef36da4c242eb6c82dcd8b512855e3", size = 795887, upload-time = "2025-09-14T22:17:54.198Z" }, - { url = "https://files.pythonhosted.org/packages/8d/09/d0a2a14fc3439c5f874042dca72a79c70a532090b7ba0003be73fee37ae2/zstandard-0.25.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:05df5136bc5a011f33cd25bc9f506e7426c0c9b3f9954f056831ce68f3b6689f", size = 640658, upload-time = "2025-09-14T22:17:55.423Z" }, - { url = "https://files.pythonhosted.org/packages/5d/7c/8b6b71b1ddd517f68ffb55e10834388d4f793c49c6b83effaaa05785b0b4/zstandard-0.25.0-cp314-cp314-manylinux2010_i686.manylinux_2_12_i686.manylinux_2_28_i686.whl", hash = "sha256:f604efd28f239cc21b3adb53eb061e2a205dc164be408e553b41ba2ffe0ca15c", size = 5379849, upload-time = "2025-09-14T22:17:57.372Z" }, - { url = "https://files.pythonhosted.org/packages/a4/86/a48e56320d0a17189ab7a42645387334fba2200e904ee47fc5a26c1fd8ca/zstandard-0.25.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:223415140608d0f0da010499eaa8ccdb9af210a543fac54bce15babbcfc78439", size = 5058095, upload-time = "2025-09-14T22:17:59.498Z" }, - { url = "https://files.pythonhosted.org/packages/f8/ad/eb659984ee2c0a779f9d06dbfe45e2dc39d99ff40a319895df2d3d9a48e5/zstandard-0.25.0-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:2e54296a283f3ab5a26fc9b8b5d4978ea0532f37b231644f367aa588930aa043", size = 5551751, upload-time = "2025-09-14T22:18:01.618Z" }, - { url = "https://files.pythonhosted.org/packages/61/b3/b637faea43677eb7bd42ab204dfb7053bd5c4582bfe6b1baefa80ac0c47b/zstandard-0.25.0-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:ca54090275939dc8ec5dea2d2afb400e0f83444b2fc24e07df7fdef677110859", size = 6364818, upload-time = "2025-09-14T22:18:03.769Z" }, - { url = "https://files.pythonhosted.org/packages/31/dc/cc50210e11e465c975462439a492516a73300ab8caa8f5e0902544fd748b/zstandard-0.25.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:e09bb6252b6476d8d56100e8147b803befa9a12cea144bbe629dd508800d1ad0", size = 5560402, upload-time = "2025-09-14T22:18:05.954Z" }, - { url = "https://files.pythonhosted.org/packages/c9/ae/56523ae9c142f0c08efd5e868a6da613ae76614eca1305259c3bf6a0ed43/zstandard-0.25.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:a9ec8c642d1ec73287ae3e726792dd86c96f5681eb8df274a757bf62b750eae7", size = 4955108, upload-time = "2025-09-14T22:18:07.68Z" }, - { url = "https://files.pythonhosted.org/packages/98/cf/c899f2d6df0840d5e384cf4c4121458c72802e8bda19691f3b16619f51e9/zstandard-0.25.0-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:a4089a10e598eae6393756b036e0f419e8c1d60f44a831520f9af41c14216cf2", size = 5269248, upload-time = "2025-09-14T22:18:09.753Z" }, - { url = "https://files.pythonhosted.org/packages/1b/c0/59e912a531d91e1c192d3085fc0f6fb2852753c301a812d856d857ea03c6/zstandard-0.25.0-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:f67e8f1a324a900e75b5e28ffb152bcac9fbed1cc7b43f99cd90f395c4375344", size = 5430330, upload-time = "2025-09-14T22:18:11.966Z" }, - { url = "https://files.pythonhosted.org/packages/a0/1d/7e31db1240de2df22a58e2ea9a93fc6e38cc29353e660c0272b6735d6669/zstandard-0.25.0-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:9654dbc012d8b06fc3d19cc825af3f7bf8ae242226df5f83936cb39f5fdc846c", size = 5811123, upload-time = "2025-09-14T22:18:13.907Z" }, - { url = "https://files.pythonhosted.org/packages/f6/49/fac46df5ad353d50535e118d6983069df68ca5908d4d65b8c466150a4ff1/zstandard-0.25.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:4203ce3b31aec23012d3a4cf4a2ed64d12fea5269c49aed5e4c3611b938e4088", size = 5359591, upload-time = "2025-09-14T22:18:16.465Z" }, - { url = "https://files.pythonhosted.org/packages/c2/38/f249a2050ad1eea0bb364046153942e34abba95dd5520af199aed86fbb49/zstandard-0.25.0-cp314-cp314-win32.whl", hash = "sha256:da469dc041701583e34de852d8634703550348d5822e66a0c827d39b05365b12", size = 444513, upload-time = "2025-09-14T22:18:20.61Z" }, - { url = "https://files.pythonhosted.org/packages/3a/43/241f9615bcf8ba8903b3f0432da069e857fc4fd1783bd26183db53c4804b/zstandard-0.25.0-cp314-cp314-win_amd64.whl", hash = "sha256:c19bcdd826e95671065f8692b5a4aa95c52dc7a02a4c5a0cac46deb879a017a2", size = 516118, upload-time = "2025-09-14T22:18:17.849Z" }, - { url = "https://files.pythonhosted.org/packages/f0/ef/da163ce2450ed4febf6467d77ccb4cd52c4c30ab45624bad26ca0a27260c/zstandard-0.25.0-cp314-cp314-win_arm64.whl", hash = "sha256:d7541afd73985c630bafcd6338d2518ae96060075f9463d7dc14cfb33514383d", size = 476940, upload-time = "2025-09-14T22:18:19.088Z" }, -] diff --git a/integrations/templates-nunjucks/smoke/scenarios/deno-node/deno.json b/integrations/templates-nunjucks/smoke/scenarios/deno-node/deno.json index deba541b0..e1923d957 100644 --- a/integrations/templates-nunjucks/smoke/scenarios/deno-node/deno.json +++ b/integrations/templates-nunjucks/smoke/scenarios/deno-node/deno.json @@ -8,9 +8,5 @@ "zod/": "npm:/zod@^4.2.1/" }, "nodeModulesDir": "auto", - "links": [ - "../../../../../js", - "../../../", - "../../../../../js/smoke/shared" - ] + "links": ["../../../../../js", "../../../", "../../../../../js/smoke/shared"] } diff --git a/integrations/templates-nunjucks/smoke/scenarios/nextjs/tsconfig.json b/integrations/templates-nunjucks/smoke/scenarios/nextjs/tsconfig.json index f619795e7..1d4f624ef 100644 --- a/integrations/templates-nunjucks/smoke/scenarios/nextjs/tsconfig.json +++ b/integrations/templates-nunjucks/smoke/scenarios/nextjs/tsconfig.json @@ -1,11 +1,7 @@ { "compilerOptions": { "target": "ES2017", - "lib": [ - "dom", - "dom.iterable", - "esnext" - ], + "lib": ["dom", "dom.iterable", "esnext"], "allowJs": true, "skipLibCheck": true, "strict": false, @@ -23,13 +19,6 @@ } ] }, - "include": [ - "next-env.d.ts", - ".next/types/**/*.ts", - "**/*.ts", - "**/*.tsx" - ], - "exclude": [ - "node_modules" - ] + "include": ["next-env.d.ts", ".next/types/**/*.ts", "**/*.ts", "**/*.tsx"], + "exclude": ["node_modules"] } diff --git a/internal/golden/adk-py-v1/google_adk.py b/internal/golden/adk-py-v1/google_adk.py deleted file mode 100644 index 5fcff824b..000000000 --- a/internal/golden/adk-py-v1/google_adk.py +++ /dev/null @@ -1,679 +0,0 @@ -# pyright: reportUnknownMemberType=none -# pyright: reportUnknownVariableType=none -# pyright: reportUnknownParameterType=none -# pyright: reportUnknownArgumentType=none -import asyncio -from pathlib import Path - -import braintrust -from braintrust_adk import setup_adk -from google.adk import Agent -from google.adk.planners import BuiltInPlanner -from google.adk.runners import Runner -from google.adk.sessions import InMemorySessionService -from google.genai import types - -setup_adk(project_name="golden-py-adk") - -FIXTURES_DIR = Path(__file__).parent.parent / "fixtures" - -# Session configuration -APP_NAME = "golden_test_app" -USER_ID = "test-user" - - -async def get_session_runner(agent: Agent, session_id: str) -> Runner: - """Helper to create a runner with session setup.""" - session_service = InMemorySessionService() - await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=session_id) - return Runner(agent=agent, app_name=APP_NAME, session_service=session_service) - - -# Test 1: Basic completion -async def test_basic_completion(): - with braintrust.start_span(name="test_basic_completion"): - print("\n=== Test 1: Basic Completion ===") - agent = Agent( - name="basic_agent", - model="gemini-2.0-flash-exp", - instruction="You are a helpful assistant.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=100, - ), - ) - - runner = await get_session_runner(agent, "session-basic") - - user_msg = types.Content(role="user", parts=[types.Part(text="What is the capital of France?")]) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id="session-basic", new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - if responses: - print(responses[0].content.parts[0].text) - return responses - - -# Test 2: Multi-turn conversation -async def test_multi_turn(): - with braintrust.start_span(name="test_multi_turn"): - print("\n=== Test 2: Multi-turn Conversation ===") - agent = Agent( - name="conversation_agent", - model="gemini-2.5-flash", - instruction="You are a helpful assistant with good memory.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - - runner = await get_session_runner(agent, "session-multi-turn") - - # First message - msg1 = types.Content(role="user", parts=[types.Part(text="Hi, my name is Alice.")]) - async for event in runner.run_async(user_id=USER_ID, session_id="session-multi-turn", new_message=msg1): - if event.is_final_response(): - print(f"Response 1: {event.content.parts[0].text}") - - # Second message - msg2 = types.Content(role="user", parts=[types.Part(text="What did I just tell you my name was?")]) - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id="session-multi-turn", new_message=msg2): - if event.is_final_response(): - responses.append(event) - print(f"Response 2: {event.content.parts[0].text}") - - return responses - - -# Test 3: System prompt -async def test_system_prompt(): - with braintrust.start_span(name="test_system_prompt"): - print("\n=== Test 3: System Prompt ===") - agent = Agent( - name="pirate_agent", - model="gemini-2.0-flash-exp", - instruction="You are a pirate. Always respond in pirate speak.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=150, - ), - ) - - runner = await get_session_runner(agent, "session-pirate") - - user_msg = types.Content(role="user", parts=[types.Part(text="Tell me about the weather.")]) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id="session-pirate", new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - if responses and responses[0].content and responses[0].content.parts: - print(responses[0].content.parts[0].text) - return responses - - -# Test 4: Streaming response -async def test_streaming(): - with braintrust.start_span(name="test_streaming"): - print("\n=== Test 4: Streaming ===") - agent = Agent( - name="counting_agent", - model="gemini-2.0-flash-exp", - instruction="You are a helpful assistant.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - - runner = await get_session_runner(agent, "session-streaming") - - user_msg = types.Content(role="user", parts=[types.Part(text="Count from 1 to 10 slowly.")]) - - full_text = "" - async for event in runner.run_async(user_id=USER_ID, session_id="session-streaming", new_message=user_msg): - if event.content and event.content.parts: - text = event.content.parts[0].text - if text: - print(text, end="") - full_text += text - - print("\n") - return full_text - - -# Test 5: Image input -async def test_image_input(): - with braintrust.start_span(name="test_image_input"): - print("\n=== Test 5: Image Input ===") - image_path = FIXTURES_DIR / "test-image.png" - - if not image_path.exists(): - print("Skipping: Image file not found") - return None - - agent = Agent( - name="vision_agent", - model="gemini-2.5-flash", - instruction="You are a helpful vision assistant that can analyze images.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=150, - ), - ) - - runner = await get_session_runner(agent, "session-vision") - - with open(image_path, "rb") as f: - image_data = f.read() - - user_msg = types.Content( - role="user", - parts=[ - types.Part.from_bytes(data=image_data, mime_type="image/png"), - types.Part(text="What color is this image?"), - ], - ) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id="session-vision", new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - if responses and responses[0].content and responses[0].content.parts: - print(responses[0].content.parts[0].text) - return responses - - -# Test 6: Document input -async def test_document_input(): - with braintrust.start_span(name="test_document_input"): - print("\n=== Test 6: Document Input ===") - pdf_path = FIXTURES_DIR / "test-document.pdf" - - if not pdf_path.exists(): - print("Skipping: PDF file not found") - return None - - agent = Agent( - name="doc_agent", - model="gemini-2.0-flash-exp", - instruction="You are a document analysis assistant.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=150, - ), - ) - - runner = await get_session_runner(agent, "session-document") - - with open(pdf_path, "rb") as f: - pdf_data = f.read() - - user_msg = types.Content( - role="user", - parts=[ - types.Part.from_bytes(data=pdf_data, mime_type="application/pdf"), - types.Part(text="What is in this document?"), - ], - ) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id="session-document", new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - if responses and responses[0].content and responses[0].content.parts: - print(responses[0].content.parts[0].text) - return responses - - -# Test 7: Temperature variations -async def test_temperature_variations(): - with braintrust.start_span(name="test_temperature_variations"): - print("\n=== Test 7: Temperature Variations ===") - - configs = [ - {"temperature": 0.0, "top_p": 1.0}, - {"temperature": 1.0, "top_p": 0.9}, - {"temperature": 0.7, "top_p": 0.95}, - ] - - responses = [] - for i, config in enumerate(configs): - print(f"\nConfig: temp={config['temperature']}, top_p={config['top_p']}") - - # Create a unique agent and session for each iteration to avoid state leakage - agent = Agent( - name=f"agent_temp_{str(config['temperature']).replace('.', '_')}", - model="gemini-2.0-flash-exp", - instruction="You are a creative storyteller.", - generate_content_config=types.GenerateContentConfig( - temperature=config["temperature"], - top_p=config["top_p"], - max_output_tokens=50, - ), - ) - - # Use unique session ID with iteration counter to ensure complete isolation - session_id = f"session-temp-{config['temperature']}-{i}" - runner = await get_session_runner(agent, session_id) - - user_msg = types.Content(role="user", parts=[types.Part(text="Say something creative.")]) - - accumulated_text = "" - async for event in runner.run_async(user_id=USER_ID, session_id=session_id, new_message=user_msg): - # Collect content from any event that has it - if event.content and event.content.parts: - for part in event.content.parts: - if hasattr(part, "text") and part.text: - accumulated_text += part.text - - if event.is_final_response(): - responses.append(event) - - # Print accumulated text if available - if accumulated_text: - print(accumulated_text) - - return responses - - -# Test 8: Stop sequences -async def test_stop_sequences(): - with braintrust.start_span(name="test_stop_sequences"): - print("\n=== Test 8: Stop Sequences ===") - agent = Agent( - name="story_agent", - model="gemini-2.0-flash-exp", - instruction="You are a creative writer.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=500, - stop_sequences=["END", "\n\n"], - ), - ) - - runner = await get_session_runner(agent, "session-stop") - - user_msg = types.Content(role="user", parts=[types.Part(text="Write a short story about a robot.")]) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id="session-stop", new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - if responses and responses[0].content and responses[0].content.parts: - print(responses[0].content.parts[0].text) - return responses - - -# Test 9: Metadata -async def test_metadata(): - with braintrust.start_span(name="test_metadata"): - print("\n=== Test 9: Metadata ===") - agent = Agent( - name="basic_agent", - model="gemini-2.0-flash-exp", - instruction="You are a helpful assistant.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=100, - labels={ - "user_id": "test_user_123", - "environment": "testing", - "feature": "metadata_test", - }, - ), - ) - - runner = await get_session_runner(agent, "session-metadata") - - user_msg = types.Content(role="user", parts=[types.Part(text="Hello!")]) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id="session-metadata", new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - if responses and responses[0].content and responses[0].content.parts: - print(responses[0].content.parts[0].text) - return responses - - -# Test 10: Long context -async def test_long_context(): - with braintrust.start_span(name="test_long_context"): - print("\n=== Test 10: Long Context ===") - agent = Agent( - name="analysis_agent", - model="gemini-2.0-flash-exp", - instruction="You are a text analysis assistant.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=100, - ), - ) - - runner = await get_session_runner(agent, "session-long") - - long_text = "The quick brown fox jumps over the lazy dog. " * 100 - user_msg = types.Content( - role="user", - parts=[ - types.Part(text=f"Here is a long text:\n\n{long_text}\n\nHow many times does the word 'fox' appear?") - ], - ) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id="session-long", new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - if responses and responses[0].content and responses[0].content.parts: - print(responses[0].content.parts[0].text) - return responses - - -# Test 11: Mixed content types -async def test_mixed_content(): - with braintrust.start_span(name="test_mixed_content"): - print("\n=== Test 11: Mixed Content Types ===") - image_path = FIXTURES_DIR / "test-image.png" - - if not image_path.exists(): - print("Skipping: Image file not found") - return None - - agent = Agent( - name="vision_agent", - model="gemini-2.0-flash-exp", - instruction="You are a helpful vision assistant.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - - runner = await get_session_runner(agent, "session-mixed") - - with open(image_path, "rb") as f: - image_data = f.read() - - user_msg = types.Content( - role="user", - parts=[ - types.Part(text="First, look at this image:"), - types.Part.from_bytes(data=image_data, mime_type="image/png"), - types.Part(text="Now describe what you see and explain why it matters."), - ], - ) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id="session-mixed", new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - if responses and responses[0].content and responses[0].content.parts: - print(responses[0].content.parts[0].text) - return responses - - -# Test 12: Empty assistant message (prefill) -async def test_prefill(): - with braintrust.start_span(name="test_prefill"): - print("\n=== Test 12: Prefill ===") - agent = Agent( - name="haiku_agent", - model="gemini-2.0-flash-exp", - instruction="You are a helpful assistant.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - - runner = await get_session_runner(agent, "session-prefill") - - # First send the user message - msg1 = types.Content(role="user", parts=[types.Part(text="Write a haiku about coding.")]) - async for event in runner.run_async(user_id=USER_ID, session_id="session-prefill", new_message=msg1): - if event.is_final_response(): - print(f"Response 1: {event.content.parts[0].text}") - - # Then send a prefill message - msg2 = types.Content(role="user", parts=[types.Part(text="Here is a haiku:")]) - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id="session-prefill", new_message=msg2): - if event.is_final_response(): - responses.append(event) - print(f"Response 2: {event.content.parts[0].text}") - - return responses - - -# Test 13: Very short max_tokens -async def test_short_max_tokens(): - with braintrust.start_span(name="test_short_max_tokens"): - print("\n=== Test 13: Very Short Max Tokens ===") - agent = Agent( - name="brief_agent", - model="gemini-2.0-flash-exp", - instruction="You are a helpful assistant.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=5, - ), - ) - - runner = await get_session_runner(agent, "session-brief") - - user_msg = types.Content(role="user", parts=[types.Part(text="What is AI?")]) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id="session-brief", new_message=user_msg): - if event.is_final_response(): - responses.append(event) - - if responses and responses[0].content and responses[0].content.parts: - print(responses[0].content.parts[0].text) - return responses - - -# Test 14: Tool use -async def test_tool_use(): - with braintrust.start_span(name="test_tool_use"): - print("\n=== Test 14: Tool Use ===") - - def get_weather(city_and_state: str, unit: str = "celsius"): - """Get the current weather for a location. - - Args: - city_and_state: The city and state, e.g. San Francisco, CA - unit: The unit of temperature (celsius or fahrenheit). Default to fahrenheit. - """ - return f"22 degrees {unit} and sunny in {city_and_state}" - - agent = Agent( - name="weather_agent", - model="gemini-2.0-flash-exp", - instruction="You are a helpful weather assistant. Use the get_weather tool to answer questions.", - tools=[get_weather], - generate_content_config=types.GenerateContentConfig( - max_output_tokens=500, - ), - ) - - runner = await get_session_runner(agent, "session-weather") - - user_msg = types.Content(role="user", parts=[types.Part(text="What is the weather like in Paris, France?")]) - - responses = [] - async for event in runner.run_async(user_id=USER_ID, session_id="session-weather", new_message=user_msg): - if event.is_final_response(): - responses.append(event) - print("Response content:") - if event.content and event.content.parts: - for i, part in enumerate(event.content.parts): - if hasattr(part, "function_call") and part.function_call: - print(f"Tool use block {i}:") - print(f" Tool: {part.function_call.name}") - print(f" Input: {part.function_call.args}") - elif hasattr(part, "text") and part.text: - print(f"Text: {part.text}") - - return responses - - -# Test 15: Tool use with result (multi-turn) -async def test_tool_use_with_result(): - with braintrust.start_span(name="test_tool_use_with_result"): - print("\n=== Test 15: Tool Use With Result ===") - - def calculate(operation: str, a: float, b: float): - """Perform a mathematical calculation. - - Args: - operation: The mathematical operation (add, subtract, multiply, divide) - a: First number - b: Second number - """ - ops = { - "add": a + b, - "subtract": a - b, - "multiply": a * b, - "divide": a / b if b != 0 else "Error: Division by zero", - } - return ops.get(operation, "Invalid operation") - - agent = Agent( - name="math_agent", - model="gemini-2.0-flash-exp", - instruction="You are a helpful math assistant. Use the calculate tool to perform calculations.", - tools=[calculate], - generate_content_config=types.GenerateContentConfig( - max_output_tokens=500, - ), - ) - - runner = await get_session_runner(agent, "session-calculator") - - user_msg = types.Content(role="user", parts=[types.Part(text="What is 127 multiplied by 49?")]) - - print("First response:") - async for event in runner.run_async(user_id=USER_ID, session_id="session-calculator", new_message=user_msg): - if event.is_final_response(): - if event.content and event.content.parts: - for part in event.content.parts: - if hasattr(part, "function_call") and part.function_call: - print(f"Tool called: {part.function_call.name}") - print(f"Input: {part.function_call.args}") - - # Note: In a real scenario, the agent would automatically execute the tool and continue - # For this test, we're just demonstrating the tool call initiation - responses = [] - return responses - - -# Test 16: Reasoning tokens generation and follow-up -async def test_reasoning(): - with braintrust.start_span(name="test_reasoning"): - print("\n=== Test 16: Reasoning Tokens & Follow-up ===") - - # First request: Analyze pattern and derive formula - print("\n--- First request (generate reasoning) ---") - agent = Agent( - name="reasoning_agent", - model="gemini-2.5-flash", - instruction="You are a mathematical reasoning assistant.", - generate_content_config=types.GenerateContentConfig( - max_output_tokens=2048, - ), - planner=BuiltInPlanner(thinking_config=types.ThinkingConfig(include_thoughts=True, thinking_budget=1024)), - ) - - runner = await get_session_runner(agent, "session-reasoning") - - user_msg = types.Content( - role="user", - parts=[ - types.Part( - text="Look at this sequence: 2, 6, 12, 20, 30. What is the pattern and what would be the formula for the nth term?" - ) - ], - ) - - print("First response:") - async for event in runner.run_async(user_id=USER_ID, session_id="session-reasoning", new_message=user_msg): - if event.is_final_response(): - if event.content and event.content.parts: - print(event.content.parts[0].text) - - # Second request: Apply the discovered pattern to solve a new problem - print("\n--- Follow-up request (using reasoning context) ---") - follow_up_msg = types.Content( - role="user", - parts=[ - types.Part( - text="Using the pattern you discovered, what would be the 10th term? And can you find the sum of the first 10 terms?" - ) - ], - ) - - responses = [] - print("Follow-up response:") - async for event in runner.run_async( - user_id=USER_ID, session_id="session-reasoning", new_message=follow_up_msg - ): - if event.is_final_response(): - responses.append(event) - if event.content and event.content.parts: - print(event.content.parts[0].text) - - return responses - - -async def run_async_tests(): - """Run all asynchronous tests.""" - tests = [ - test_basic_completion, - test_multi_turn, - test_system_prompt, - test_streaming, - test_image_input, - test_document_input, - test_temperature_variations, - test_stop_sequences, - test_metadata, - test_long_context, - test_mixed_content, - test_prefill, - test_short_max_tokens, - test_tool_use, - test_tool_use_with_result, - test_reasoning, - ] - - for test in tests: - try: - await test() - # Rate limiting - await asyncio.sleep(3) - except Exception as e: - print(f"Test {test.__name__} failed: {e}") - import traceback - - traceback.print_exc() - - -async def main(): - """Run all tests.""" - print("=" * 60) - print("Google ADK Golden Tests with Braintrust") - print("=" * 60) - - # Run all async tests - print("\n### Running ADK Agent Tests ###") - await run_async_tests() - - print("\n" + "=" * 60) - print("All tests completed!") - print("=" * 60) - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/internal/golden/adk-py-v1/pyproject.toml b/internal/golden/adk-py-v1/pyproject.toml deleted file mode 100644 index 7df1d4002..000000000 --- a/internal/golden/adk-py-v1/pyproject.toml +++ /dev/null @@ -1,15 +0,0 @@ -[project] -name = "golden" -version = "0.1.0" -description = "Add your description here" -readme = "README.md" -requires-python = ">=3.11" -dependencies = [ - "braintrust", - "braintrust-adk", - "google-adk>=1.14.1", -] - -[tool.uv.sources] -braintrust = { path = "../../py", editable = true } -braintrust-adk = { path = "../../integrations/adk-py", editable = true } diff --git a/internal/golden/genai-py-v1/google_genai.py b/internal/golden/genai-py-v1/google_genai.py deleted file mode 100644 index 79284096c..000000000 --- a/internal/golden/genai-py-v1/google_genai.py +++ /dev/null @@ -1,544 +0,0 @@ -# pyright: reportUnknownMemberType=none -# pyright: reportUnknownVariableType=none -# pyright: reportUnknownParameterType=none -# pyright: reportUnknownArgumentType=none -import asyncio -import time -from pathlib import Path - -import braintrust -from braintrust.wrappers.google_genai import setup_genai -from google.genai import types -from google.genai.client import Client - -setup_genai(project_name="golden-py-genai") - -FIXTURES_DIR = Path(__file__).parent.parent / "fixtures" - -client = Client() - - -# Test 1: Basic text completion -def test_basic_completion(): - with braintrust.start_span(name="test_basic_completion"): - print("\n=== Test 1: Basic Completion ===") - response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents="What is the capital of France?", - config=types.GenerateContentConfig( - max_output_tokens=100, - ), - ) - print(response.text) - return response - - -# Test 2: Multi-turn conversation -def test_multi_turn(): - with braintrust.start_span(name="test_multi_turn"): - print("\n=== Test 2: Multi-turn Conversation ===") - response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents=[ - types.Content(role="user", parts=[types.Part.from_text(text="Hi, my name is Alice.")]), - types.Content(role="model", parts=[types.Part.from_text(text="Hello Alice! Nice to meet you.")]), - types.Content(role="user", parts=[types.Part.from_text(text="What did I just tell you my name was?")]), - ], - config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - print(response.text) - return response - - -# Test 3: System prompt -def test_system_prompt(): - with braintrust.start_span(name="test_system_prompt"): - print("\n=== Test 3: System Prompt ===") - response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents="Tell me about the weather.", - config=types.GenerateContentConfig( - system_instruction="You are a pirate. Always respond in pirate speak.", - max_output_tokens=150, - ), - ) - print(response.text) - return response - - -# Test 4: Streaming response -def test_streaming(): - with braintrust.start_span(name="test_streaming"): - print("\n=== Test 4: Streaming ===") - stream = client.models.generate_content_stream( - model="gemini-2.0-flash-001", - contents="Count from 1 to 10 slowly.", - config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - - full_text = "" - for chunk in stream: - if chunk.text: - print(chunk.text, end="") - full_text += chunk.text - - print("\n") - return full_text - - -# Test 5: Image input (base64) -def test_image_input(): - with braintrust.start_span(name="test_image_input"): - print("\n=== Test 5: Image Input ===") - image_path = FIXTURES_DIR / "test-image.png" - - with open(image_path, "rb") as f: - image_data = f.read() - - response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents=[ - types.Part.from_bytes(data=image_data, mime_type="image/png"), - types.Part.from_text(text="What color is this image?"), - ], - config=types.GenerateContentConfig( - max_output_tokens=150, - ), - ) - print(response.text) - return response - - -# Test 6: Document input (PDF) -def test_document_input(): - with braintrust.start_span(name="test_document_input"): - print("\n=== Test 6: Document Input ===") - pdf_path = FIXTURES_DIR / "test-document.pdf" - - with open(pdf_path, "rb") as f: - pdf_data = f.read() - - response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents=[ - types.Part.from_bytes(data=pdf_data, mime_type="application/pdf"), - types.Part.from_text(text="What is in this document?"), - ], - config=types.GenerateContentConfig( - max_output_tokens=150, - ), - ) - print(response.text) - return response - - -# Test 7: Temperature and top_p variations -def test_temperature_variations(): - with braintrust.start_span(name="test_temperature_variations"): - print("\n=== Test 7: Temperature Variations ===") - configs = [ - {"temperature": 0.0, "top_p": 1.0}, - {"temperature": 1.0, "top_p": 0.9}, - {"temperature": 0.7, "top_p": 0.95}, - ] - - responses = [] - for config in configs: - print(f"\nConfig: temp={config['temperature']}, top_p={config['top_p']}") - response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents="Say something creative.", - config=types.GenerateContentConfig( - temperature=config["temperature"], - top_p=config["top_p"], - max_output_tokens=50, - ), - ) - print(response.text) - responses.append(response) - - return responses - - -# Test 8: Stop sequences -def test_stop_sequences(): - with braintrust.start_span(name="test_stop_sequences"): - print("\n=== Test 8: Stop Sequences ===") - response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents="Write a short story about a robot.", - config=types.GenerateContentConfig( - max_output_tokens=500, - stop_sequences=["END", "\n\n"], - ), - ) - print(response.text) - print(f"Stop reason: {response.candidates[0].finish_reason if response.candidates else 'unknown'}") - return response - - -# Test 9: Metadata -# not supported by genai - - -# Test 10: Long context -def test_long_context(): - with braintrust.start_span(name="test_long_context"): - print("\n=== Test 10: Long Context ===") - long_text = "The quick brown fox jumps over the lazy dog. " * 100 - response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents=f"Here is a long text:\n\n{long_text}\n\nHow many times does the word 'fox' appear?", - config=types.GenerateContentConfig( - max_output_tokens=100, - ), - ) - print(response.text) - return response - - -# Test 13: Mixed content types -def test_mixed_content(): - with braintrust.start_span(name="test_mixed_content"): - print("\n=== Test 13: Mixed Content Types ===") - # Skip if image doesn't exist - image_path = FIXTURES_DIR / "test-image.png" - - with open(image_path, "rb") as f: - image_data = f.read() - - response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents=[ - types.Part.from_text(text="First, look at this image:"), - types.Part.from_bytes(data=image_data, mime_type="image/png"), - types.Part.from_text(text="Now describe what you see and explain why it matters."), - ], - config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - print(response.text) - return response - - -# Test 14: Empty assistant message (prefill) -def test_prefill(): - with braintrust.start_span(name="test_prefill"): - print("\n=== Test 14: Prefill ===") - response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents=[ - types.Content(role="user", parts=[types.Part.from_text(text="Write a haiku about coding.")]), - types.Content(role="model", parts=[types.Part.from_text(text="Here is a haiku:")]), - ], - config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - print(response.text) - return response - - -# Test 15: Very short max_tokens -def test_short_max_tokens(): - with braintrust.start_span(name="test_short_max_tokens"): - print("\n=== Test 15: Very Short Max Tokens ===") - response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents="What is AI?", - config=types.GenerateContentConfig( - max_output_tokens=5, - ), - ) - print(response.text) - print(f"Stop reason: {response.candidates[0].finish_reason if response.candidates else 'unknown'}") - return response - - -# Test 16: Tool use -def test_tool_use(): - with braintrust.start_span(name="test_tool_use"): - print("\n=== Test 16: Tool Use ===") - - # Define a function for getting weather - def get_weather(city_and_state: str, unit: str = "celsius") -> str: - """Get the current weather for a location. - - Args: - city_and_state: The city and state, e.g. San Francisco, CA - unit: The unit of temperature (celsius or fahrenheit) - """ - # Simulate weather API response - return f"22 degrees {unit} and sunny in {city_and_state}" - - response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents="What is the weather like in Paris, France?", - config=types.GenerateContentConfig( - tools=[get_weather], - max_output_tokens=500, - ), - ) - - print("Response content:") - if response.text: - print(f"Text: {response.text}") - - if hasattr(response, "function_calls") and response.function_calls: - for i, call in enumerate(response.function_calls): - print(f"Tool use block {i}:") - print(f" Tool: {call.name}") - print(f" Input: {call.args}") - - return response - - -# Test 17: Tool use with result (multi-turn) -def test_tool_use_with_result(): - with braintrust.start_span(name="test_tool_use_with_result"): - print("\n=== Test 17: Tool Use With Result ===") - # Manually declare function - function = types.FunctionDeclaration( - name="calculate", - description="Perform a mathematical calculation", - parameters_json_schema={ - "type": "object", - "properties": { - "operation": { - "type": "string", - "enum": ["add", "subtract", "multiply", "divide"], - "description": "The mathematical operation", - }, - "a": { - "type": "number", - "description": "First number", - }, - "b": { - "type": "number", - "description": "Second number", - }, - }, - "required": ["operation", "a", "b"], - }, - ) - - tool = types.Tool(function_declarations=[function]) - - # First request - model will use the tool - first_response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents="What is 127 multiplied by 49?", - config=types.GenerateContentConfig( - tools=[tool], - max_output_tokens=500, - ), - ) - - print("First response:") - tool_call = None - if hasattr(first_response, "function_calls") and first_response.function_calls: - tool_call = first_response.function_calls[0] - print(f"Tool called: {tool_call.name}") - print(f"Input: {tool_call.args}") - - # Simulate tool execution - result = 127 * 49 - - assert first_response.candidates - assert tool_call and tool_call.name - - # Second request - provide tool result - second_response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents=[ - types.Content(role="user", parts=[types.Part.from_text(text="What is 127 multiplied by 49?")]), - first_response.candidates[0].content, - types.Content( - role="user", - parts=[ - types.Part.from_function_response( - name=tool_call.name, - response={"result": result}, - ) - ], - ), - ], - config=types.GenerateContentConfig( - tools=[tool], - max_output_tokens=500, - ), - ) - - print("\nSecond response (with tool result):") - print(second_response.text) - return second_response - - -# Async test example -async def test_async_generation(): - with braintrust.start_span(name="test_async_generation"): - print("\n=== Test 18: Async Generation ===") - response = await client.aio.models.generate_content( - model="gemini-2.0-flash-001", - contents="Tell me a joke about programming.", - config=types.GenerateContentConfig( - max_output_tokens=100, - ), - ) - print(response.text) - return response - - -# Async streaming test -async def test_async_streaming(): - with braintrust.start_span(name="test_async_streaming"): - print("\n=== Test 19: Async Streaming ===") - stream = await client.aio.models.generate_content_stream( - model="gemini-2.0-flash-001", - contents="List 5 programming languages and their main uses.", - config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - - full_text = "" - async for chunk in stream: - if chunk.text: - print(chunk.text, end="") - full_text += chunk.text - - print("\n") - return full_text - - -# Test 18: Reasoning tokens generation and follow-up -def test_reasoning(): - with braintrust.start_span(name="test_reasoning"): - print("\n=== Test 18: Reasoning Tokens & Follow-up ===") - - # First request: Analyze pattern and derive formula - print("\n--- First request (generate reasoning) ---") - first_response = client.models.generate_content( - model="gemini-2.0-flash-thinking-exp-1219", - contents="Look at this sequence: 2, 6, 12, 20, 30. What is the pattern and what would be the formula for the nth term?", - config=types.GenerateContentConfig( - max_output_tokens=2048, - thinking_config=types.ThinkingConfig(include_thoughts=True, thinking_budget=1024), - ), - ) - - print("First response:") - print(first_response.candidates) - - # Second request: Apply the discovered pattern to solve a new problem - print("\n--- Follow-up request (using reasoning context) ---") - follow_up_response = client.models.generate_content( - model="gemini-2.0-flash-thinking-exp-1219", - contents=[ - types.Content( - role="user", - parts=[ - types.Part.from_text( - text="Look at this sequence: 2, 6, 12, 20, 30. What is the pattern and what would be the formula for the nth term?" - ) - ], - ), - first_response.candidates[0].content if first_response.candidates else "", - types.Content( - role="user", - parts=[ - types.Part.from_text( - text="Using the pattern you discovered, what would be the 10th term? And can you find the sum of the first 10 terms?" - ) - ], - ), - ], - config=types.GenerateContentConfig( - max_output_tokens=2048, - thinking_config=types.ThinkingConfig(include_thoughts=True, thinking_budget=1024), - ), - ) - - print("Follow-up response:") - print(follow_up_response.candidates) - - return first_response, follow_up_response - - -def run_sync_tests(): - """Run all synchronous tests.""" - tests = [ - test_basic_completion, - test_multi_turn, - test_system_prompt, - test_streaming, - test_image_input, - test_document_input, - test_temperature_variations, - test_stop_sequences, - test_long_context, - test_mixed_content, - test_prefill, - test_short_max_tokens, - test_tool_use, - test_tool_use_with_result, - test_reasoning, - ] - - for test in tests: - try: - test() - # Rate limiting - time.sleep(1) - except Exception as e: - print(f"Test {test.__name__} failed: {e}") - - -async def run_async_tests(): - """Run all asynchronous tests.""" - tests = [ - test_async_generation, - test_async_streaming, - ] - - for test in tests: - try: - await test() - # Rate limiting - await asyncio.sleep(1) - except Exception as e: - print(f"Test {test.__name__} failed: {e}") - - -async def main(): - """Run all tests.""" - print("=" * 60) - print("Google GenAI Golden Tests with Braintrust") - print("=" * 60) - - # Run synchronous tests - print("\n### Running Synchronous Tests ###") - run_sync_tests() - - # Run asynchronous tests - print("\n### Running Asynchronous Tests ###") - await run_async_tests() - - # Clean up aiohttp session to prevent resource leak warnings - # This is a workaround for https://github.com/googleapis/python-genai/issues/1388 - if hasattr(client, "_api_client") and hasattr(client._api_client, "_aiohttp_session"): - if client._api_client._aiohttp_session: - await client._api_client._aiohttp_session.close() - - print("\n" + "=" * 60) - print("All tests completed!") - print("=" * 60) - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/internal/golden/genai-py-v1/pyproject.toml b/internal/golden/genai-py-v1/pyproject.toml deleted file mode 100644 index b76d982cf..000000000 --- a/internal/golden/genai-py-v1/pyproject.toml +++ /dev/null @@ -1,14 +0,0 @@ -[project] -name = "golden" -version = "0.1.0" -description = "Add your description here" -readme = "README.md" -requires-python = ">=3.11" -dependencies = [ - "braintrust", - "google-adk>=1.14.1", -] - -[tool.uv.sources] -braintrust = { path = "../../py", editable = true } -braintrust-adk = { path = "../../integrations/adk-py", editable = true } diff --git a/internal/golden/langchain-py-v0/.python-version b/internal/golden/langchain-py-v0/.python-version deleted file mode 100644 index 641602f44..000000000 --- a/internal/golden/langchain-py-v0/.python-version +++ /dev/null @@ -1 +0,0 @@ -3.11.14 diff --git a/internal/golden/langchain-py-v0/langchain.py b/internal/golden/langchain-py-v0/langchain.py deleted file mode 100644 index 93eac31e8..000000000 --- a/internal/golden/langchain-py-v0/langchain.py +++ /dev/null @@ -1,555 +0,0 @@ -import asyncio -import base64 -from pathlib import Path - -import braintrust -from braintrust import flush, init_logger, start_span -from braintrust_langchain import BraintrustCallbackHandler, set_global_handler -from langchain_anthropic import ChatAnthropic -from langchain_core.messages import AIMessage, HumanMessage, SystemMessage, ToolMessage -from langchain_core.prompts import ChatPromptTemplate -from langchain_core.tools import tool -from langchain_openai import ChatOpenAI - -init_logger(project="golden-py-langchain-v0") - -handler = BraintrustCallbackHandler() -set_global_handler(handler) - -FIXTURES_DIR = Path(__file__).parent.parent / "fixtures" - - -def test_basic_completion(): - print("\n=== Test 1: Basic Completion ===") - with start_span(name="test_basic_completion"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=100)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=100)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - prompt = ChatPromptTemplate.from_template("What is the capital of {country}?") - chain = prompt | model - result = chain.invoke({"country": "France"}) - print(result.content) - print() - - -def test_multi_turn(): - print("\n=== Test 2: Multi-turn Conversation ===") - with start_span(name="test_multi_turn"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=200)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=200)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - messages = [ - HumanMessage(content="Hi, my name is Alice."), - SystemMessage(content="Hello Alice! Nice to meet you."), - HumanMessage(content="What did I just tell you my name was?"), - ] - result = model.invoke(messages) - print(result.content) - print() - - -def test_system_prompt(): - print("\n=== Test 3: System Prompt ===") - with start_span(name="test_system_prompt"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=150)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=150)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - system_msg = "You are a pirate. Always respond in pirate speak." - prompt = ChatPromptTemplate.from_messages([("system", system_msg), ("human", "{input}")]) - chain = prompt | model - result = chain.invoke({"input": "Tell me about the weather."}) - print(result.content) - print() - - -def test_streaming(): - print("\n=== Test 4: Streaming ===") - with start_span(name="test_streaming"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=200, streaming=True)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=200, streaming=True)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - prompt_text = "Count from 1 to 10 slowly." - prompt = ChatPromptTemplate.from_template(prompt_text) - chain = prompt | model - - for chunk in chain.stream({}): - if chunk.content: - print(chunk.content, end="", flush=True) - print("\n") - - -def test_image_input(): - print("\n=== Test 5: Image Input ===") - with start_span(name="test_image_input"): - image_path = FIXTURES_DIR / "test-image.png" - with open(image_path, "rb") as f: - image_data = base64.b64encode(f.read()).decode("utf-8") - - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=150)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=150)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - - if provider == "openai": - messages = [ - HumanMessage( - content=[ - {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{image_data}"}}, - {"type": "text", "text": "What color is this image?"}, - ] - ) - ] - else: - messages = [ - HumanMessage( - content=[ - { - "type": "image", - "source": {"type": "base64", "media_type": "image/png", "data": image_data}, - }, - {"type": "text", "text": "What color is this image?"}, - ] - ) - ] - - result = model.invoke(messages) - print(result.content) - print() - - -def test_document_input(): - print("\n=== Test 6: Document Input ===") - with start_span(name="test_document_input"): - pdf_path = FIXTURES_DIR / "test-document.pdf" - with open(pdf_path, "rb") as f: - pdf_data = base64.b64encode(f.read()).decode("utf-8") - - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=150)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=150)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - - if provider == "openai": - messages = [ - HumanMessage( - content=[ - { - "type": "file", - "file": { - "file_data": f"data:application/pdf;base64,{pdf_data}", - "filename": "test-document.pdf", - }, - }, - {"type": "text", "text": "What is in this document?"}, - ] - ) - ] - else: - messages = [ - HumanMessage( - content=[ - { - "type": "document", - "source": {"type": "base64", "media_type": "application/pdf", "data": pdf_data}, - }, - {"type": "text", "text": "What is in this document?"}, - ] - ) - ] - - result = model.invoke(messages) - print(result.content) - print() - - -def test_temperature_variations(): - print("\n=== Test 7: Temperature Variations ===") - with start_span(name="test_temperature_variations"): - configs = [(0.0, 1.0), (1.0, 0.9), (0.7, 0.95)] - - for provider, models in ( - ( - "openai", - [ - ChatOpenAI(model="gpt-4o", max_completion_tokens=50, temperature=temp, top_p=top_p) - for temp, top_p in configs - ], - ), - ( - "anthropic", - [ - ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=50, temperature=temp, top_p=top_p) - for temp, top_p in configs - ], - ), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - for (temp, top_p), model in zip(configs, models): - print(f"Config: temp={temp}, top_p={top_p}") - prompt = ChatPromptTemplate.from_template("Say something {topic}.") - chain = prompt | model - result = chain.invoke({"topic": "creative"}) - print(result.content) - print() - - -def test_stop_sequences(): - print("\n=== Test 8: Stop Sequences ===") - with start_span(name="test_stop_sequences"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=500, stop_sequences=["END", "\n\n"])), - ( - "anthropic", - ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=500, stop_sequences=["END"]), - ), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - topic = "robot" - prompt = ChatPromptTemplate.from_template(f"Write a short story about a {topic}.") - chain = prompt | model - result = chain.invoke({}) - print(result.content) - print(f"Response metadata: {result.response_metadata}") - print() - - -def test_metadata(): - print("\n=== Test 9: Metadata ===") - with start_span(name="test_metadata"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=100, model_kwargs={"user": "test_user_123"})), - ( - "anthropic", - ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=100), - ), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - messages = [HumanMessage(content="Hello!")] - result = model.invoke(messages) - print(result.content) - print() - - -def test_long_context(): - print("\n=== Test 10: Long Context ===") - with start_span(name="test_long_context"): - long_text = "The quick brown fox jumps over the lazy dog. " * 100 - - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=100)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=100)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - prompt = ChatPromptTemplate.from_template( - "Here is a long text:\n\n{text}\n\nHow many times does the word 'fox' appear?" - ) - chain = prompt | model - result = chain.invoke({"text": long_text}) - print(result.content) - print() - - -def test_mixed_content(): - print("\n=== Test 11: Mixed Content Types ===") - with start_span(name="test_mixed_content"): - image_path = FIXTURES_DIR / "test-image.png" - with open(image_path, "rb") as f: - image_data = base64.b64encode(f.read()).decode("utf-8") - - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=200)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=200)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - - if provider == "openai": - messages = [ - HumanMessage( - content=[ - {"type": "text", "text": "First, look at this image:"}, - {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{image_data}"}}, - {"type": "text", "text": "Now describe what you see and explain why it matters."}, - ] - ) - ] - else: - messages = [ - HumanMessage( - content=[ - {"type": "text", "text": "First, look at this image:"}, - { - "type": "image", - "source": {"type": "base64", "media_type": "image/png", "data": image_data}, - }, - {"type": "text", "text": "Now describe what you see and explain why it matters."}, - ] - ) - ] - - result = model.invoke(messages) - print(result.content) - print() - - -def test_prefill(): - print("\n=== Test 12: Prefill ===") - with start_span(name="test_prefill"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=200)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=200)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - topic = "coding" - messages = [ - HumanMessage(content=f"Write a haiku about {topic}."), - SystemMessage(content="Here is a haiku:"), - ] - result = model.invoke(messages) - print(result.content) - print() - - -def test_short_max_tokens(): - print("\n=== Test 13: Very Short Max Tokens ===") - with start_span(name="test_short_max_tokens"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=5)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=5)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - prompt = ChatPromptTemplate.from_template("What is AI?") - chain = prompt | model - result = chain.invoke({}) - print(result.content) - print(f"Response metadata: {result.response_metadata}") - print() - - -def test_tool_use(): - print("\n=== Test 14: Tool Use ===") - with start_span(name="test_tool_use"): - - @tool - def get_weather(city_and_state: str, unit: str = "celsius") -> str: - """Get the current weather for a location. - - Args: - city_and_state: The city and state, e.g. San Francisco, CA - unit: The unit of temperature (celsius or fahrenheit) - """ - return f"22 degrees {unit} and sunny in {city_and_state}" - - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=500)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=500)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - - model_with_tools = model.bind_tools([get_weather]) - query = "What is the weather like in Paris, France?" - result = model_with_tools.invoke(query) - - print("Response content:") - if result.content: - print(f"Text: {result.content}") - - if hasattr(result, "tool_calls") and result.tool_calls: - for i, call in enumerate(result.tool_calls): - print(f"Tool use block {i}:") - print(f" Tool: {call['name']}") - print(f" Input: {call['args']}") - print() - - -def test_tool_use_with_result(): - print("\n=== Test 15: Tool Use With Result ===") - with start_span(name="test_tool_use_with_result"): - - @tool - def calculate(operation: str, a: float, b: float) -> float: - """Perform a mathematical calculation. - - Args: - operation: The mathematical operation (add, subtract, multiply, divide) - a: First number - b: Second number - """ - if operation == "add": - return a + b - elif operation == "subtract": - return a - b - elif operation == "multiply": - return a * b - elif operation == "divide": - return a / b if b != 0 else 0 - return 0 - - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=500)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=500)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - - model_with_tools = model.bind_tools([calculate]) - query = "What is 127 multiplied by 49?" - - # First request - model will use the tool - first_result = model_with_tools.invoke(query) - - print("First response:") - if hasattr(first_result, "tool_calls") and first_result.tool_calls: - tool_call = first_result.tool_calls[0] - print(f"Tool called: {tool_call['name']}") - print(f"Input: {tool_call['args']}") - - # Simulate tool execution - result = 127 * 49 - - # Second request - provide tool result - messages = [ - HumanMessage(content=query), - AIMessage(content="", tool_calls=[tool_call]), - ToolMessage(content=str(result), tool_call_id=tool_call["id"]), - ] - - second_result = model_with_tools.invoke(messages) - print("\nSecond response (with tool result):") - print(second_result.content) - print() - - -# Test 18: Reasoning with o1 model -def test_reasoning(): - with start_span(name="test_reasoning"): - braintrust.log(output="Responses API not supported and chat completions do not include (reasoning) summaries") - - -async def test_async_generation(): - print("\n=== Test 17: Async Generation ===") - with start_span(name="test_async_generation"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=100)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=100)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - topic = "programming" - prompt = ChatPromptTemplate.from_template("Tell me a joke about {topic}.") - chain = prompt | model - result = await chain.ainvoke({"topic": topic}) - print(result.content) - print() - - -async def test_async_streaming(): - print("\n=== Test 18: Async Streaming ===") - with start_span(name="test_async_streaming"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=200, streaming=True)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=200, streaming=True)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - category = "programming languages" - prompt = ChatPromptTemplate.from_template("List 3 {category}.") - chain = prompt | model - - full_content = "" - async for chunk in chain.astream({"category": category}): - if chunk.content: - print(chunk.content, end="", flush=True) - full_content += chunk.content - print("\n") - - -def run_sync_tests(): - tests = [ - test_basic_completion, - test_multi_turn, - test_system_prompt, - test_streaming, - test_image_input, - test_document_input, - test_temperature_variations, - test_stop_sequences, - test_metadata, - test_long_context, - test_mixed_content, - test_prefill, - test_short_max_tokens, - test_tool_use, - test_tool_use_with_result, - test_reasoning, - ] - - for test in tests: - try: - test() - flush() - except Exception as e: - print(f"Test {test.__name__} failed: {e}") - import traceback - - traceback.print_exc() - - -async def run_async_tests(): - tests = [ - test_async_generation, - test_async_streaming, - ] - - for test in tests: - try: - await test() - flush() - except Exception as e: - print(f"Test {test.__name__} failed: {e}") - import traceback - - traceback.print_exc() - - -async def main(): - print("=" * 60) - print("LangChain Golden Tests with Braintrust") - print("=" * 60) - - print("\n### Running Synchronous Tests ###") - run_sync_tests() - - print("\n### Running Asynchronous Tests ###") - await run_async_tests() - - print("\n" + "=" * 60) - print("All tests completed!") - print("=" * 60) - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/internal/golden/langchain-py-v0/pyproject.toml b/internal/golden/langchain-py-v0/pyproject.toml deleted file mode 100644 index 8736c8db0..000000000 --- a/internal/golden/langchain-py-v0/pyproject.toml +++ /dev/null @@ -1,18 +0,0 @@ -[project] -name = "langchain-py-v0" -version = "0.1.0" -description = "Add your description here" -readme = "README.md" -requires-python = ">=3.11.14" -dependencies = [ - "braintrust", - "braintrust-langchain", - "langchain>=0.3.11,<1.0.0", - "langchain-anthropic>=0.3.22", - "langchain-openai>=0.3.35", - "langgraph>=0.3.11,<1.0.0", -] - -[tool.uv.sources] -braintrust = { path = "../../../py", editable = true } -braintrust-langchain = { path = "../../../integrations/langchain-py", editable = true } diff --git a/internal/golden/langchain-py-v0/uv.lock b/internal/golden/langchain-py-v0/uv.lock deleted file mode 100644 index a7e561014..000000000 --- a/internal/golden/langchain-py-v0/uv.lock +++ /dev/null @@ -1,1588 +0,0 @@ -version = 1 -revision = 2 -requires-python = ">=3.11.14" - -[[package]] -name = "annotated-types" -version = "0.7.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" }, -] - -[[package]] -name = "anthropic" -version = "0.77.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "distro" }, - { name = "docstring-parser" }, - { name = "httpx" }, - { name = "jiter" }, - { name = "pydantic" }, - { name = "sniffio" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/88/61/50aef0587acd9dd8bf1b8b7fd7fbb25ba4c6ec5387a6ffc195a697951fcc/anthropic-0.77.1.tar.gz", hash = "sha256:a19d78ff6fff9e05d211e3a936051cd5b9462f0eac043d2d45b2372f455d11cd", size = 504691, upload-time = "2026-02-03T17:44:22.667Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/2b/54/e83babf9833547c5548b4e25230ef3d62492e45925b0d104a43e501918a0/anthropic-0.77.1-py3-none-any.whl", hash = "sha256:76fd6f2ab36033a5294d58182a5f712dab9573c3a54413a275ecdf29e727c1e0", size = 397856, upload-time = "2026-02-03T17:44:20.962Z" }, -] - -[[package]] -name = "anyio" -version = "4.12.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "idna" }, - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/96/f0/5eb65b2bb0d09ac6776f2eb54adee6abe8228ea05b20a5ad0e4945de8aac/anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703", size = 228685, upload-time = "2026-01-06T11:45:21.246Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c", size = 113592, upload-time = "2026-01-06T11:45:19.497Z" }, -] - -[[package]] -name = "braintrust" -version = "0.5.3" -source = { editable = "../../../py" } -dependencies = [ - { name = "chevron" }, - { name = "exceptiongroup" }, - { name = "gitpython" }, - { name = "python-dotenv" }, - { name = "python-slugify" }, - { name = "requests" }, - { name = "sseclient-py" }, - { name = "tqdm" }, - { name = "typing-extensions" }, - { name = "wrapt" }, -] - -[package.metadata] -requires-dist = [ - { name = "boto3", marker = "extra == 'all'" }, - { name = "boto3", marker = "extra == 'cli'" }, - { name = "chevron" }, - { name = "exceptiongroup", specifier = ">=1.2.0" }, - { name = "gitpython" }, - { name = "openai-agents", marker = "extra == 'all'" }, - { name = "openai-agents", marker = "extra == 'openai-agents'" }, - { name = "opentelemetry-api", marker = "extra == 'all'" }, - { name = "opentelemetry-api", marker = "extra == 'otel'" }, - { name = "opentelemetry-exporter-otlp-proto-http", marker = "extra == 'all'" }, - { name = "opentelemetry-exporter-otlp-proto-http", marker = "extra == 'otel'" }, - { name = "opentelemetry-sdk", marker = "extra == 'all'" }, - { name = "opentelemetry-sdk", marker = "extra == 'otel'" }, - { name = "psycopg2-binary", marker = "extra == 'all'" }, - { name = "psycopg2-binary", marker = "extra == 'cli'" }, - { name = "pydoc-markdown", marker = "extra == 'all'" }, - { name = "pydoc-markdown", marker = "extra == 'doc'" }, - { name = "python-dotenv" }, - { name = "python-slugify" }, - { name = "requests" }, - { name = "sseclient-py" }, - { name = "starlette", marker = "extra == 'all'" }, - { name = "starlette", marker = "extra == 'cli'" }, - { name = "temporalio", marker = "python_full_version >= '3.10' and extra == 'all'", specifier = ">=1.19.0" }, - { name = "temporalio", marker = "python_full_version >= '3.10' and extra == 'temporal'", specifier = ">=1.19.0" }, - { name = "tqdm" }, - { name = "typing-extensions", specifier = ">=4.1.0" }, - { name = "uv", marker = "extra == 'all'" }, - { name = "uv", marker = "extra == 'cli'" }, - { name = "uvicorn", marker = "extra == 'all'" }, - { name = "uvicorn", marker = "extra == 'cli'" }, - { name = "wrapt" }, -] -provides-extras = ["cli", "doc", "openai-agents", "otel", "temporal", "all"] - -[[package]] -name = "braintrust-langchain" -version = "0.2.1" -source = { editable = "../../../integrations/langchain-py" } -dependencies = [ - { name = "braintrust" }, - { name = "langchain" }, -] - -[package.metadata] -requires-dist = [ - { name = "braintrust", specifier = ">=0.2.1" }, - { name = "langchain", specifier = ">=0.3.27" }, -] - -[package.metadata.requires-dev] -dev = [ - { name = "black" }, - { name = "build" }, - { name = "flake8" }, - { name = "flake8-isort" }, - { name = "httpx" }, - { name = "isort", specifier = "==5.12.0" }, - { name = "langchain-anthropic", specifier = ">=0.3.20" }, - { name = "langchain-openai" }, - { name = "langgraph", specifier = ">=0.2.1,<0.4.0" }, - { name = "pre-commit" }, - { name = "pytest" }, - { name = "pytest-asyncio", specifier = ">=1.1.0" }, - { name = "pytest-vcr", specifier = ">=1.0.2" }, - { name = "ruff" }, - { name = "tenacity" }, - { name = "twine" }, -] - -[[package]] -name = "certifi" -version = "2026.1.4" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/e0/2d/a891ca51311197f6ad14a7ef42e2399f36cf2f9bd44752b3dc4eab60fdc5/certifi-2026.1.4.tar.gz", hash = "sha256:ac726dd470482006e014ad384921ed6438c457018f4b3d204aea4281258b2120", size = 154268, upload-time = "2026-01-04T02:42:41.825Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e6/ad/3cc14f097111b4de0040c83a525973216457bbeeb63739ef1ed275c1c021/certifi-2026.1.4-py3-none-any.whl", hash = "sha256:9943707519e4add1115f44c2bc244f782c0249876bf51b6599fee1ffbedd685c", size = 152900, upload-time = "2026-01-04T02:42:40.15Z" }, -] - -[[package]] -name = "charset-normalizer" -version = "3.4.4" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/13/69/33ddede1939fdd074bce5434295f38fae7136463422fe4fd3e0e89b98062/charset_normalizer-3.4.4.tar.gz", hash = "sha256:94537985111c35f28720e43603b8e7b43a6ecfb2ce1d3058bbe955b73404e21a", size = 129418, upload-time = "2025-10-14T04:42:32.879Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ed/27/c6491ff4954e58a10f69ad90aca8a1b6fe9c5d3c6f380907af3c37435b59/charset_normalizer-3.4.4-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:6e1fcf0720908f200cd21aa4e6750a48ff6ce4afe7ff5a79a90d5ed8a08296f8", size = 206988, upload-time = "2025-10-14T04:40:33.79Z" }, - { url = "https://files.pythonhosted.org/packages/94/59/2e87300fe67ab820b5428580a53cad894272dbb97f38a7a814a2a1ac1011/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5f819d5fe9234f9f82d75bdfa9aef3a3d72c4d24a6e57aeaebba32a704553aa0", size = 147324, upload-time = "2025-10-14T04:40:34.961Z" }, - { url = "https://files.pythonhosted.org/packages/07/fb/0cf61dc84b2b088391830f6274cb57c82e4da8bbc2efeac8c025edb88772/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:a59cb51917aa591b1c4e6a43c132f0cdc3c76dbad6155df4e28ee626cc77a0a3", size = 142742, upload-time = "2025-10-14T04:40:36.105Z" }, - { url = "https://files.pythonhosted.org/packages/62/8b/171935adf2312cd745d290ed93cf16cf0dfe320863ab7cbeeae1dcd6535f/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:8ef3c867360f88ac904fd3f5e1f902f13307af9052646963ee08ff4f131adafc", size = 160863, upload-time = "2025-10-14T04:40:37.188Z" }, - { url = "https://files.pythonhosted.org/packages/09/73/ad875b192bda14f2173bfc1bc9a55e009808484a4b256748d931b6948442/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d9e45d7faa48ee908174d8fe84854479ef838fc6a705c9315372eacbc2f02897", size = 157837, upload-time = "2025-10-14T04:40:38.435Z" }, - { url = "https://files.pythonhosted.org/packages/6d/fc/de9cce525b2c5b94b47c70a4b4fb19f871b24995c728e957ee68ab1671ea/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:840c25fb618a231545cbab0564a799f101b63b9901f2569faecd6b222ac72381", size = 151550, upload-time = "2025-10-14T04:40:40.053Z" }, - { url = "https://files.pythonhosted.org/packages/55/c2/43edd615fdfba8c6f2dfbd459b25a6b3b551f24ea21981e23fb768503ce1/charset_normalizer-3.4.4-cp311-cp311-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:ca5862d5b3928c4940729dacc329aa9102900382fea192fc5e52eb69d6093815", size = 149162, upload-time = "2025-10-14T04:40:41.163Z" }, - { url = "https://files.pythonhosted.org/packages/03/86/bde4ad8b4d0e9429a4e82c1e8f5c659993a9a863ad62c7df05cf7b678d75/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:d9c7f57c3d666a53421049053eaacdd14bbd0a528e2186fcb2e672effd053bb0", size = 150019, upload-time = "2025-10-14T04:40:42.276Z" }, - { url = "https://files.pythonhosted.org/packages/1f/86/a151eb2af293a7e7bac3a739b81072585ce36ccfb4493039f49f1d3cae8c/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:277e970e750505ed74c832b4bf75dac7476262ee2a013f5574dd49075879e161", size = 143310, upload-time = "2025-10-14T04:40:43.439Z" }, - { url = "https://files.pythonhosted.org/packages/b5/fe/43dae6144a7e07b87478fdfc4dbe9efd5defb0e7ec29f5f58a55aeef7bf7/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:31fd66405eaf47bb62e8cd575dc621c56c668f27d46a61d975a249930dd5e2a4", size = 162022, upload-time = "2025-10-14T04:40:44.547Z" }, - { url = "https://files.pythonhosted.org/packages/80/e6/7aab83774f5d2bca81f42ac58d04caf44f0cc2b65fc6db2b3b2e8a05f3b3/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:0d3d8f15c07f86e9ff82319b3d9ef6f4bf907608f53fe9d92b28ea9ae3d1fd89", size = 149383, upload-time = "2025-10-14T04:40:46.018Z" }, - { url = "https://files.pythonhosted.org/packages/4f/e8/b289173b4edae05c0dde07f69f8db476a0b511eac556dfe0d6bda3c43384/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:9f7fcd74d410a36883701fafa2482a6af2ff5ba96b9a620e9e0721e28ead5569", size = 159098, upload-time = "2025-10-14T04:40:47.081Z" }, - { url = "https://files.pythonhosted.org/packages/d8/df/fe699727754cae3f8478493c7f45f777b17c3ef0600e28abfec8619eb49c/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ebf3e58c7ec8a8bed6d66a75d7fb37b55e5015b03ceae72a8e7c74495551e224", size = 152991, upload-time = "2025-10-14T04:40:48.246Z" }, - { url = "https://files.pythonhosted.org/packages/1a/86/584869fe4ddb6ffa3bd9f491b87a01568797fb9bd8933f557dba9771beaf/charset_normalizer-3.4.4-cp311-cp311-win32.whl", hash = "sha256:eecbc200c7fd5ddb9a7f16c7decb07b566c29fa2161a16cf67b8d068bd21690a", size = 99456, upload-time = "2025-10-14T04:40:49.376Z" }, - { url = "https://files.pythonhosted.org/packages/65/f6/62fdd5feb60530f50f7e38b4f6a1d5203f4d16ff4f9f0952962c044e919a/charset_normalizer-3.4.4-cp311-cp311-win_amd64.whl", hash = "sha256:5ae497466c7901d54b639cf42d5b8c1b6a4fead55215500d2f486d34db48d016", size = 106978, upload-time = "2025-10-14T04:40:50.844Z" }, - { url = "https://files.pythonhosted.org/packages/7a/9d/0710916e6c82948b3be62d9d398cb4fcf4e97b56d6a6aeccd66c4b2f2bd5/charset_normalizer-3.4.4-cp311-cp311-win_arm64.whl", hash = "sha256:65e2befcd84bc6f37095f5961e68a6f077bf44946771354a28ad434c2cce0ae1", size = 99969, upload-time = "2025-10-14T04:40:52.272Z" }, - { url = "https://files.pythonhosted.org/packages/f3/85/1637cd4af66fa687396e757dec650f28025f2a2f5a5531a3208dc0ec43f2/charset_normalizer-3.4.4-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:0a98e6759f854bd25a58a73fa88833fba3b7c491169f86ce1180c948ab3fd394", size = 208425, upload-time = "2025-10-14T04:40:53.353Z" }, - { url = "https://files.pythonhosted.org/packages/9d/6a/04130023fef2a0d9c62d0bae2649b69f7b7d8d24ea5536feef50551029df/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b5b290ccc2a263e8d185130284f8501e3e36c5e02750fc6b6bdeb2e9e96f1e25", size = 148162, upload-time = "2025-10-14T04:40:54.558Z" }, - { url = "https://files.pythonhosted.org/packages/78/29/62328d79aa60da22c9e0b9a66539feae06ca0f5a4171ac4f7dc285b83688/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:74bb723680f9f7a6234dcf67aea57e708ec1fbdf5699fb91dfd6f511b0a320ef", size = 144558, upload-time = "2025-10-14T04:40:55.677Z" }, - { url = "https://files.pythonhosted.org/packages/86/bb/b32194a4bf15b88403537c2e120b817c61cd4ecffa9b6876e941c3ee38fe/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:f1e34719c6ed0b92f418c7c780480b26b5d9c50349e9a9af7d76bf757530350d", size = 161497, upload-time = "2025-10-14T04:40:57.217Z" }, - { url = "https://files.pythonhosted.org/packages/19/89/a54c82b253d5b9b111dc74aca196ba5ccfcca8242d0fb64146d4d3183ff1/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:2437418e20515acec67d86e12bf70056a33abdacb5cb1655042f6538d6b085a8", size = 159240, upload-time = "2025-10-14T04:40:58.358Z" }, - { url = "https://files.pythonhosted.org/packages/c0/10/d20b513afe03acc89ec33948320a5544d31f21b05368436d580dec4e234d/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:11d694519d7f29d6cd09f6ac70028dba10f92f6cdd059096db198c283794ac86", size = 153471, upload-time = "2025-10-14T04:40:59.468Z" }, - { url = "https://files.pythonhosted.org/packages/61/fa/fbf177b55bdd727010f9c0a3c49eefa1d10f960e5f09d1d887bf93c2e698/charset_normalizer-3.4.4-cp312-cp312-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:ac1c4a689edcc530fc9d9aa11f5774b9e2f33f9a0c6a57864e90908f5208d30a", size = 150864, upload-time = "2025-10-14T04:41:00.623Z" }, - { url = "https://files.pythonhosted.org/packages/05/12/9fbc6a4d39c0198adeebbde20b619790e9236557ca59fc40e0e3cebe6f40/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:21d142cc6c0ec30d2efee5068ca36c128a30b0f2c53c1c07bd78cb6bc1d3be5f", size = 150647, upload-time = "2025-10-14T04:41:01.754Z" }, - { url = "https://files.pythonhosted.org/packages/ad/1f/6a9a593d52e3e8c5d2b167daf8c6b968808efb57ef4c210acb907c365bc4/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:5dbe56a36425d26d6cfb40ce79c314a2e4dd6211d51d6d2191c00bed34f354cc", size = 145110, upload-time = "2025-10-14T04:41:03.231Z" }, - { url = "https://files.pythonhosted.org/packages/30/42/9a52c609e72471b0fc54386dc63c3781a387bb4fe61c20231a4ebcd58bdd/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:5bfbb1b9acf3334612667b61bd3002196fe2a1eb4dd74d247e0f2a4d50ec9bbf", size = 162839, upload-time = "2025-10-14T04:41:04.715Z" }, - { url = "https://files.pythonhosted.org/packages/c4/5b/c0682bbf9f11597073052628ddd38344a3d673fda35a36773f7d19344b23/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:d055ec1e26e441f6187acf818b73564e6e6282709e9bcb5b63f5b23068356a15", size = 150667, upload-time = "2025-10-14T04:41:05.827Z" }, - { url = "https://files.pythonhosted.org/packages/e4/24/a41afeab6f990cf2daf6cb8c67419b63b48cf518e4f56022230840c9bfb2/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:af2d8c67d8e573d6de5bc30cdb27e9b95e49115cd9baad5ddbd1a6207aaa82a9", size = 160535, upload-time = "2025-10-14T04:41:06.938Z" }, - { url = "https://files.pythonhosted.org/packages/2a/e5/6a4ce77ed243c4a50a1fecca6aaaab419628c818a49434be428fe24c9957/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:780236ac706e66881f3b7f2f32dfe90507a09e67d1d454c762cf642e6e1586e0", size = 154816, upload-time = "2025-10-14T04:41:08.101Z" }, - { url = "https://files.pythonhosted.org/packages/a8/ef/89297262b8092b312d29cdb2517cb1237e51db8ecef2e9af5edbe7b683b1/charset_normalizer-3.4.4-cp312-cp312-win32.whl", hash = "sha256:5833d2c39d8896e4e19b689ffc198f08ea58116bee26dea51e362ecc7cd3ed26", size = 99694, upload-time = "2025-10-14T04:41:09.23Z" }, - { url = "https://files.pythonhosted.org/packages/3d/2d/1e5ed9dd3b3803994c155cd9aacb60c82c331bad84daf75bcb9c91b3295e/charset_normalizer-3.4.4-cp312-cp312-win_amd64.whl", hash = "sha256:a79cfe37875f822425b89a82333404539ae63dbdddf97f84dcbc3d339aae9525", size = 107131, upload-time = "2025-10-14T04:41:10.467Z" }, - { url = "https://files.pythonhosted.org/packages/d0/d9/0ed4c7098a861482a7b6a95603edce4c0d9db2311af23da1fb2b75ec26fc/charset_normalizer-3.4.4-cp312-cp312-win_arm64.whl", hash = "sha256:376bec83a63b8021bb5c8ea75e21c4ccb86e7e45ca4eb81146091b56599b80c3", size = 100390, upload-time = "2025-10-14T04:41:11.915Z" }, - { url = "https://files.pythonhosted.org/packages/97/45/4b3a1239bbacd321068ea6e7ac28875b03ab8bc0aa0966452db17cd36714/charset_normalizer-3.4.4-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:e1f185f86a6f3403aa2420e815904c67b2f9ebc443f045edd0de921108345794", size = 208091, upload-time = "2025-10-14T04:41:13.346Z" }, - { url = "https://files.pythonhosted.org/packages/7d/62/73a6d7450829655a35bb88a88fca7d736f9882a27eacdca2c6d505b57e2e/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6b39f987ae8ccdf0d2642338faf2abb1862340facc796048b604ef14919e55ed", size = 147936, upload-time = "2025-10-14T04:41:14.461Z" }, - { url = "https://files.pythonhosted.org/packages/89/c5/adb8c8b3d6625bef6d88b251bbb0d95f8205831b987631ab0c8bb5d937c2/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:3162d5d8ce1bb98dd51af660f2121c55d0fa541b46dff7bb9b9f86ea1d87de72", size = 144180, upload-time = "2025-10-14T04:41:15.588Z" }, - { url = "https://files.pythonhosted.org/packages/91/ed/9706e4070682d1cc219050b6048bfd293ccf67b3d4f5a4f39207453d4b99/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:81d5eb2a312700f4ecaa977a8235b634ce853200e828fbadf3a9c50bab278328", size = 161346, upload-time = "2025-10-14T04:41:16.738Z" }, - { url = "https://files.pythonhosted.org/packages/d5/0d/031f0d95e4972901a2f6f09ef055751805ff541511dc1252ba3ca1f80cf5/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:5bd2293095d766545ec1a8f612559f6b40abc0eb18bb2f5d1171872d34036ede", size = 158874, upload-time = "2025-10-14T04:41:17.923Z" }, - { url = "https://files.pythonhosted.org/packages/f5/83/6ab5883f57c9c801ce5e5677242328aa45592be8a00644310a008d04f922/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a8a8b89589086a25749f471e6a900d3f662d1d3b6e2e59dcecf787b1cc3a1894", size = 153076, upload-time = "2025-10-14T04:41:19.106Z" }, - { url = "https://files.pythonhosted.org/packages/75/1e/5ff781ddf5260e387d6419959ee89ef13878229732732ee73cdae01800f2/charset_normalizer-3.4.4-cp313-cp313-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:bc7637e2f80d8530ee4a78e878bce464f70087ce73cf7c1caf142416923b98f1", size = 150601, upload-time = "2025-10-14T04:41:20.245Z" }, - { url = "https://files.pythonhosted.org/packages/d7/57/71be810965493d3510a6ca79b90c19e48696fb1ff964da319334b12677f0/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f8bf04158c6b607d747e93949aa60618b61312fe647a6369f88ce2ff16043490", size = 150376, upload-time = "2025-10-14T04:41:21.398Z" }, - { url = "https://files.pythonhosted.org/packages/e5/d5/c3d057a78c181d007014feb7e9f2e65905a6c4ef182c0ddf0de2924edd65/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:554af85e960429cf30784dd47447d5125aaa3b99a6f0683589dbd27e2f45da44", size = 144825, upload-time = "2025-10-14T04:41:22.583Z" }, - { url = "https://files.pythonhosted.org/packages/e6/8c/d0406294828d4976f275ffbe66f00266c4b3136b7506941d87c00cab5272/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:74018750915ee7ad843a774364e13a3db91682f26142baddf775342c3f5b1133", size = 162583, upload-time = "2025-10-14T04:41:23.754Z" }, - { url = "https://files.pythonhosted.org/packages/d7/24/e2aa1f18c8f15c4c0e932d9287b8609dd30ad56dbe41d926bd846e22fb8d/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:c0463276121fdee9c49b98908b3a89c39be45d86d1dbaa22957e38f6321d4ce3", size = 150366, upload-time = "2025-10-14T04:41:25.27Z" }, - { url = "https://files.pythonhosted.org/packages/e4/5b/1e6160c7739aad1e2df054300cc618b06bf784a7a164b0f238360721ab86/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:362d61fd13843997c1c446760ef36f240cf81d3ebf74ac62652aebaf7838561e", size = 160300, upload-time = "2025-10-14T04:41:26.725Z" }, - { url = "https://files.pythonhosted.org/packages/7a/10/f882167cd207fbdd743e55534d5d9620e095089d176d55cb22d5322f2afd/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:9a26f18905b8dd5d685d6d07b0cdf98a79f3c7a918906af7cc143ea2e164c8bc", size = 154465, upload-time = "2025-10-14T04:41:28.322Z" }, - { url = "https://files.pythonhosted.org/packages/89/66/c7a9e1b7429be72123441bfdbaf2bc13faab3f90b933f664db506dea5915/charset_normalizer-3.4.4-cp313-cp313-win32.whl", hash = "sha256:9b35f4c90079ff2e2edc5b26c0c77925e5d2d255c42c74fdb70fb49b172726ac", size = 99404, upload-time = "2025-10-14T04:41:29.95Z" }, - { url = "https://files.pythonhosted.org/packages/c4/26/b9924fa27db384bdcd97ab83b4f0a8058d96ad9626ead570674d5e737d90/charset_normalizer-3.4.4-cp313-cp313-win_amd64.whl", hash = "sha256:b435cba5f4f750aa6c0a0d92c541fb79f69a387c91e61f1795227e4ed9cece14", size = 107092, upload-time = "2025-10-14T04:41:31.188Z" }, - { url = "https://files.pythonhosted.org/packages/af/8f/3ed4bfa0c0c72a7ca17f0380cd9e4dd842b09f664e780c13cff1dcf2ef1b/charset_normalizer-3.4.4-cp313-cp313-win_arm64.whl", hash = "sha256:542d2cee80be6f80247095cc36c418f7bddd14f4a6de45af91dfad36d817bba2", size = 100408, upload-time = "2025-10-14T04:41:32.624Z" }, - { url = "https://files.pythonhosted.org/packages/2a/35/7051599bd493e62411d6ede36fd5af83a38f37c4767b92884df7301db25d/charset_normalizer-3.4.4-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:da3326d9e65ef63a817ecbcc0df6e94463713b754fe293eaa03da99befb9a5bd", size = 207746, upload-time = "2025-10-14T04:41:33.773Z" }, - { url = "https://files.pythonhosted.org/packages/10/9a/97c8d48ef10d6cd4fcead2415523221624bf58bcf68a802721a6bc807c8f/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8af65f14dc14a79b924524b1e7fffe304517b2bff5a58bf64f30b98bbc5079eb", size = 147889, upload-time = "2025-10-14T04:41:34.897Z" }, - { url = "https://files.pythonhosted.org/packages/10/bf/979224a919a1b606c82bd2c5fa49b5c6d5727aa47b4312bb27b1734f53cd/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:74664978bb272435107de04e36db5a9735e78232b85b77d45cfb38f758efd33e", size = 143641, upload-time = "2025-10-14T04:41:36.116Z" }, - { url = "https://files.pythonhosted.org/packages/ba/33/0ad65587441fc730dc7bd90e9716b30b4702dc7b617e6ba4997dc8651495/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:752944c7ffbfdd10c074dc58ec2d5a8a4cd9493b314d367c14d24c17684ddd14", size = 160779, upload-time = "2025-10-14T04:41:37.229Z" }, - { url = "https://files.pythonhosted.org/packages/67/ed/331d6b249259ee71ddea93f6f2f0a56cfebd46938bde6fcc6f7b9a3d0e09/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d1f13550535ad8cff21b8d757a3257963e951d96e20ec82ab44bc64aeb62a191", size = 159035, upload-time = "2025-10-14T04:41:38.368Z" }, - { url = "https://files.pythonhosted.org/packages/67/ff/f6b948ca32e4f2a4576aa129d8bed61f2e0543bf9f5f2b7fc3758ed005c9/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ecaae4149d99b1c9e7b88bb03e3221956f68fd6d50be2ef061b2381b61d20838", size = 152542, upload-time = "2025-10-14T04:41:39.862Z" }, - { url = "https://files.pythonhosted.org/packages/16/85/276033dcbcc369eb176594de22728541a925b2632f9716428c851b149e83/charset_normalizer-3.4.4-cp314-cp314-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:cb6254dc36b47a990e59e1068afacdcd02958bdcce30bb50cc1700a8b9d624a6", size = 149524, upload-time = "2025-10-14T04:41:41.319Z" }, - { url = "https://files.pythonhosted.org/packages/9e/f2/6a2a1f722b6aba37050e626530a46a68f74e63683947a8acff92569f979a/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:c8ae8a0f02f57a6e61203a31428fa1d677cbe50c93622b4149d5c0f319c1d19e", size = 150395, upload-time = "2025-10-14T04:41:42.539Z" }, - { url = "https://files.pythonhosted.org/packages/60/bb/2186cb2f2bbaea6338cad15ce23a67f9b0672929744381e28b0592676824/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:47cc91b2f4dd2833fddaedd2893006b0106129d4b94fdb6af1f4ce5a9965577c", size = 143680, upload-time = "2025-10-14T04:41:43.661Z" }, - { url = "https://files.pythonhosted.org/packages/7d/a5/bf6f13b772fbb2a90360eb620d52ed8f796f3c5caee8398c3b2eb7b1c60d/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:82004af6c302b5d3ab2cfc4cc5f29db16123b1a8417f2e25f9066f91d4411090", size = 162045, upload-time = "2025-10-14T04:41:44.821Z" }, - { url = "https://files.pythonhosted.org/packages/df/c5/d1be898bf0dc3ef9030c3825e5d3b83f2c528d207d246cbabe245966808d/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:2b7d8f6c26245217bd2ad053761201e9f9680f8ce52f0fcd8d0755aeae5b2152", size = 149687, upload-time = "2025-10-14T04:41:46.442Z" }, - { url = "https://files.pythonhosted.org/packages/a5/42/90c1f7b9341eef50c8a1cb3f098ac43b0508413f33affd762855f67a410e/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:799a7a5e4fb2d5898c60b640fd4981d6a25f1c11790935a44ce38c54e985f828", size = 160014, upload-time = "2025-10-14T04:41:47.631Z" }, - { url = "https://files.pythonhosted.org/packages/76/be/4d3ee471e8145d12795ab655ece37baed0929462a86e72372fd25859047c/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:99ae2cffebb06e6c22bdc25801d7b30f503cc87dbd283479e7b606f70aff57ec", size = 154044, upload-time = "2025-10-14T04:41:48.81Z" }, - { url = "https://files.pythonhosted.org/packages/b0/6f/8f7af07237c34a1defe7defc565a9bc1807762f672c0fde711a4b22bf9c0/charset_normalizer-3.4.4-cp314-cp314-win32.whl", hash = "sha256:f9d332f8c2a2fcbffe1378594431458ddbef721c1769d78e2cbc06280d8155f9", size = 99940, upload-time = "2025-10-14T04:41:49.946Z" }, - { url = "https://files.pythonhosted.org/packages/4b/51/8ade005e5ca5b0d80fb4aff72a3775b325bdc3d27408c8113811a7cbe640/charset_normalizer-3.4.4-cp314-cp314-win_amd64.whl", hash = "sha256:8a6562c3700cce886c5be75ade4a5db4214fda19fede41d9792d100288d8f94c", size = 107104, upload-time = "2025-10-14T04:41:51.051Z" }, - { url = "https://files.pythonhosted.org/packages/da/5f/6b8f83a55bb8278772c5ae54a577f3099025f9ade59d0136ac24a0df4bde/charset_normalizer-3.4.4-cp314-cp314-win_arm64.whl", hash = "sha256:de00632ca48df9daf77a2c65a484531649261ec9f25489917f09e455cb09ddb2", size = 100743, upload-time = "2025-10-14T04:41:52.122Z" }, - { url = "https://files.pythonhosted.org/packages/0a/4c/925909008ed5a988ccbb72dcc897407e5d6d3bd72410d69e051fc0c14647/charset_normalizer-3.4.4-py3-none-any.whl", hash = "sha256:7a32c560861a02ff789ad905a2fe94e3f840803362c84fecf1851cb4cf3dc37f", size = 53402, upload-time = "2025-10-14T04:42:31.76Z" }, -] - -[[package]] -name = "chevron" -version = "0.14.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/15/1f/ca74b65b19798895d63a6e92874162f44233467c9e7c1ed8afd19016ebe9/chevron-0.14.0.tar.gz", hash = "sha256:87613aafdf6d77b6a90ff073165a61ae5086e21ad49057aa0e53681601800ebf", size = 11440, upload-time = "2021-01-02T22:47:59.233Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/52/93/342cc62a70ab727e093ed98e02a725d85b746345f05d2b5e5034649f4ec8/chevron-0.14.0-py3-none-any.whl", hash = "sha256:fbf996a709f8da2e745ef763f482ce2d311aa817d287593a5b990d6d6e4f0443", size = 11595, upload-time = "2021-01-02T22:47:57.847Z" }, -] - -[[package]] -name = "colorama" -version = "0.4.6" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/d8/53/6f443c9a4a8358a93a6792e2acffb9d9d5cb0a5cfd8802644b7b1c9a02e4/colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44", size = 27697, upload-time = "2022-10-25T02:36:22.414Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335, upload-time = "2022-10-25T02:36:20.889Z" }, -] - -[[package]] -name = "distro" -version = "1.9.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/fc/f8/98eea607f65de6527f8a2e8885fc8015d3e6f5775df186e443e0964a11c3/distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed", size = 60722, upload-time = "2023-12-24T09:54:32.31Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/12/b3/231ffd4ab1fc9d679809f356cebee130ac7daa00d6d6f3206dd4fd137e9e/distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2", size = 20277, upload-time = "2023-12-24T09:54:30.421Z" }, -] - -[[package]] -name = "docstring-parser" -version = "0.17.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/b2/9d/c3b43da9515bd270df0f80548d9944e389870713cc1fe2b8fb35fe2bcefd/docstring_parser-0.17.0.tar.gz", hash = "sha256:583de4a309722b3315439bb31d64ba3eebada841f2e2cee23b99df001434c912", size = 27442, upload-time = "2025-07-21T07:35:01.868Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/55/e2/2537ebcff11c1ee1ff17d8d0b6f4db75873e3b0fb32c2d4a2ee31ecb310a/docstring_parser-0.17.0-py3-none-any.whl", hash = "sha256:cf2569abd23dce8099b300f9b4fa8191e9582dda731fd533daf54c4551658708", size = 36896, upload-time = "2025-07-21T07:35:00.684Z" }, -] - -[[package]] -name = "exceptiongroup" -version = "1.3.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/50/79/66800aadf48771f6b62f7eb014e352e5d06856655206165d775e675a02c9/exceptiongroup-1.3.1.tar.gz", hash = "sha256:8b412432c6055b0b7d14c310000ae93352ed6754f70fa8f7c34141f91c4e3219", size = 30371, upload-time = "2025-11-21T23:01:54.787Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl", hash = "sha256:a7a39a3bd276781e98394987d3a5701d0c4edffb633bb7a5144577f82c773598", size = 16740, upload-time = "2025-11-21T23:01:53.443Z" }, -] - -[[package]] -name = "gitdb" -version = "4.0.12" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "smmap" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/72/94/63b0fc47eb32792c7ba1fe1b694daec9a63620db1e313033d18140c2320a/gitdb-4.0.12.tar.gz", hash = "sha256:5ef71f855d191a3326fcfbc0d5da835f26b13fbcba60c32c21091c349ffdb571", size = 394684, upload-time = "2025-01-02T07:20:46.413Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a0/61/5c78b91c3143ed5c14207f463aecfc8f9dbb5092fb2869baf37c273b2705/gitdb-4.0.12-py3-none-any.whl", hash = "sha256:67073e15955400952c6565cc3e707c554a4eea2e428946f7a4c162fab9bd9bcf", size = 62794, upload-time = "2025-01-02T07:20:43.624Z" }, -] - -[[package]] -name = "gitpython" -version = "3.1.46" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "gitdb" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/df/b5/59d16470a1f0dfe8c793f9ef56fd3826093fc52b3bd96d6b9d6c26c7e27b/gitpython-3.1.46.tar.gz", hash = "sha256:400124c7d0ef4ea03f7310ac2fbf7151e09ff97f2a3288d64a440c584a29c37f", size = 215371, upload-time = "2026-01-01T15:37:32.073Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/6a/09/e21df6aef1e1ffc0c816f0522ddc3f6dcded766c3261813131c78a704470/gitpython-3.1.46-py3-none-any.whl", hash = "sha256:79812ed143d9d25b6d176a10bb511de0f9c67b1fa641d82097b0ab90398a2058", size = 208620, upload-time = "2026-01-01T15:37:30.574Z" }, -] - -[[package]] -name = "greenlet" -version = "3.3.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/8a/99/1cd3411c56a410994669062bd73dd58270c00cc074cac15f385a1fd91f8a/greenlet-3.3.1.tar.gz", hash = "sha256:41848f3230b58c08bb43dee542e74a2a2e34d3c59dc3076cec9151aeeedcae98", size = 184690, upload-time = "2026-01-23T15:31:02.076Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ec/e8/2e1462c8fdbe0f210feb5ac7ad2d9029af8be3bf45bd9fa39765f821642f/greenlet-3.3.1-cp311-cp311-macosx_11_0_universal2.whl", hash = "sha256:5fd23b9bc6d37b563211c6abbb1b3cab27db385a4449af5c32e932f93017080c", size = 274974, upload-time = "2026-01-23T15:31:02.891Z" }, - { url = "https://files.pythonhosted.org/packages/7e/a8/530a401419a6b302af59f67aaf0b9ba1015855ea7e56c036b5928793c5bd/greenlet-3.3.1-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:09f51496a0bfbaa9d74d36a52d2580d1ef5ed4fdfcff0a73730abfbbbe1403dd", size = 577175, upload-time = "2026-01-23T16:00:56.213Z" }, - { url = "https://files.pythonhosted.org/packages/8e/89/7e812bb9c05e1aaef9b597ac1d0962b9021d2c6269354966451e885c4e6b/greenlet-3.3.1-cp311-cp311-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:cb0feb07fe6e6a74615ee62a880007d976cf739b6669cce95daa7373d4fc69c5", size = 590401, upload-time = "2026-01-23T16:05:26.365Z" }, - { url = "https://files.pythonhosted.org/packages/70/ae/e2d5f0e59b94a2269b68a629173263fa40b63da32f5c231307c349315871/greenlet-3.3.1-cp311-cp311-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:67ea3fc73c8cd92f42467a72b75e8f05ed51a0e9b1d15398c913416f2dafd49f", size = 601161, upload-time = "2026-01-23T16:15:53.456Z" }, - { url = "https://files.pythonhosted.org/packages/5c/ae/8d472e1f5ac5efe55c563f3eabb38c98a44b832602e12910750a7c025802/greenlet-3.3.1-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:39eda9ba259cc9801da05351eaa8576e9aa83eb9411e8f0c299e05d712a210f2", size = 590272, upload-time = "2026-01-23T15:32:49.411Z" }, - { url = "https://files.pythonhosted.org/packages/a8/51/0fde34bebfcadc833550717eade64e35ec8738e6b097d5d248274a01258b/greenlet-3.3.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:e2e7e882f83149f0a71ac822ebf156d902e7a5d22c9045e3e0d1daf59cee2cc9", size = 1550729, upload-time = "2026-01-23T16:04:20.867Z" }, - { url = "https://files.pythonhosted.org/packages/16/c9/2fb47bee83b25b119d5a35d580807bb8b92480a54b68fef009a02945629f/greenlet-3.3.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:80aa4d79eb5564f2e0a6144fcc744b5a37c56c4a92d60920720e99210d88db0f", size = 1615552, upload-time = "2026-01-23T15:33:45.743Z" }, - { url = "https://files.pythonhosted.org/packages/1f/54/dcf9f737b96606f82f8dd05becfb8d238db0633dd7397d542a296fe9cad3/greenlet-3.3.1-cp311-cp311-win_amd64.whl", hash = "sha256:32e4ca9777c5addcbf42ff3915d99030d8e00173a56f80001fb3875998fe410b", size = 226462, upload-time = "2026-01-23T15:36:50.422Z" }, - { url = "https://files.pythonhosted.org/packages/91/37/61e1015cf944ddd2337447d8e97fb423ac9bc21f9963fb5f206b53d65649/greenlet-3.3.1-cp311-cp311-win_arm64.whl", hash = "sha256:da19609432f353fed186cc1b85e9440db93d489f198b4bdf42ae19cc9d9ac9b4", size = 225715, upload-time = "2026-01-23T15:33:17.298Z" }, - { url = "https://files.pythonhosted.org/packages/f9/c8/9d76a66421d1ae24340dfae7e79c313957f6e3195c144d2c73333b5bfe34/greenlet-3.3.1-cp312-cp312-macosx_11_0_universal2.whl", hash = "sha256:7e806ca53acf6d15a888405880766ec84721aa4181261cd11a457dfe9a7a4975", size = 276443, upload-time = "2026-01-23T15:30:10.066Z" }, - { url = "https://files.pythonhosted.org/packages/81/99/401ff34bb3c032d1f10477d199724f5e5f6fbfb59816ad1455c79c1eb8e7/greenlet-3.3.1-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d842c94b9155f1c9b3058036c24ffb8ff78b428414a19792b2380be9cecf4f36", size = 597359, upload-time = "2026-01-23T16:00:57.394Z" }, - { url = "https://files.pythonhosted.org/packages/2b/bc/4dcc0871ed557792d304f50be0f7487a14e017952ec689effe2180a6ff35/greenlet-3.3.1-cp312-cp312-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:20fedaadd422fa02695f82093f9a98bad3dab5fcda793c658b945fcde2ab27ba", size = 607805, upload-time = "2026-01-23T16:05:28.068Z" }, - { url = "https://files.pythonhosted.org/packages/3b/cd/7a7ca57588dac3389e97f7c9521cb6641fd8b6602faf1eaa4188384757df/greenlet-3.3.1-cp312-cp312-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:c620051669fd04ac6b60ebc70478210119c56e2d5d5df848baec4312e260e4ca", size = 622363, upload-time = "2026-01-23T16:15:54.754Z" }, - { url = "https://files.pythonhosted.org/packages/cf/05/821587cf19e2ce1f2b24945d890b164401e5085f9d09cbd969b0c193cd20/greenlet-3.3.1-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:14194f5f4305800ff329cbf02c5fcc88f01886cadd29941b807668a45f0d2336", size = 609947, upload-time = "2026-01-23T15:32:51.004Z" }, - { url = "https://files.pythonhosted.org/packages/a4/52/ee8c46ed9f8babaa93a19e577f26e3d28a519feac6350ed6f25f1afee7e9/greenlet-3.3.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:7b2fe4150a0cf59f847a67db8c155ac36aed89080a6a639e9f16df5d6c6096f1", size = 1567487, upload-time = "2026-01-23T16:04:22.125Z" }, - { url = "https://files.pythonhosted.org/packages/8f/7c/456a74f07029597626f3a6db71b273a3632aecb9afafeeca452cfa633197/greenlet-3.3.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:49f4ad195d45f4a66a0eb9c1ba4832bb380570d361912fa3554746830d332149", size = 1636087, upload-time = "2026-01-23T15:33:47.486Z" }, - { url = "https://files.pythonhosted.org/packages/34/2f/5e0e41f33c69655300a5e54aeb637cf8ff57f1786a3aba374eacc0228c1d/greenlet-3.3.1-cp312-cp312-win_amd64.whl", hash = "sha256:cc98b9c4e4870fa983436afa999d4eb16b12872fab7071423d5262fa7120d57a", size = 227156, upload-time = "2026-01-23T15:34:34.808Z" }, - { url = "https://files.pythonhosted.org/packages/c8/ab/717c58343cf02c5265b531384b248787e04d8160b8afe53d9eec053d7b44/greenlet-3.3.1-cp312-cp312-win_arm64.whl", hash = "sha256:bfb2d1763d777de5ee495c85309460f6fd8146e50ec9d0ae0183dbf6f0a829d1", size = 226403, upload-time = "2026-01-23T15:31:39.372Z" }, - { url = "https://files.pythonhosted.org/packages/ec/ab/d26750f2b7242c2b90ea2ad71de70cfcd73a948a49513188a0fc0d6fc15a/greenlet-3.3.1-cp313-cp313-macosx_11_0_universal2.whl", hash = "sha256:7ab327905cabb0622adca5971e488064e35115430cec2c35a50fd36e72a315b3", size = 275205, upload-time = "2026-01-23T15:30:24.556Z" }, - { url = "https://files.pythonhosted.org/packages/10/d3/be7d19e8fad7c5a78eeefb2d896a08cd4643e1e90c605c4be3b46264998f/greenlet-3.3.1-cp313-cp313-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:65be2f026ca6a176f88fb935ee23c18333ccea97048076aef4db1ef5bc0713ac", size = 599284, upload-time = "2026-01-23T16:00:58.584Z" }, - { url = "https://files.pythonhosted.org/packages/ae/21/fe703aaa056fdb0f17e5afd4b5c80195bbdab701208918938bd15b00d39b/greenlet-3.3.1-cp313-cp313-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:7a3ae05b3d225b4155bda56b072ceb09d05e974bc74be6c3fc15463cf69f33fd", size = 610274, upload-time = "2026-01-23T16:05:29.312Z" }, - { url = "https://files.pythonhosted.org/packages/06/00/95df0b6a935103c0452dad2203f5be8377e551b8466a29650c4c5a5af6cc/greenlet-3.3.1-cp313-cp313-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:12184c61e5d64268a160226fb4818af4df02cfead8379d7f8b99a56c3a54ff3e", size = 624375, upload-time = "2026-01-23T16:15:55.915Z" }, - { url = "https://files.pythonhosted.org/packages/cb/86/5c6ab23bb3c28c21ed6bebad006515cfe08b04613eb105ca0041fecca852/greenlet-3.3.1-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:6423481193bbbe871313de5fd06a082f2649e7ce6e08015d2a76c1e9186ca5b3", size = 612904, upload-time = "2026-01-23T15:32:52.317Z" }, - { url = "https://files.pythonhosted.org/packages/c2/f3/7949994264e22639e40718c2daf6f6df5169bf48fb038c008a489ec53a50/greenlet-3.3.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:33a956fe78bbbda82bfc95e128d61129b32d66bcf0a20a1f0c08aa4839ffa951", size = 1567316, upload-time = "2026-01-23T16:04:23.316Z" }, - { url = "https://files.pythonhosted.org/packages/8d/6e/d73c94d13b6465e9f7cd6231c68abde838bb22408596c05d9059830b7872/greenlet-3.3.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:4b065d3284be43728dd280f6f9a13990b56470b81be20375a207cdc814a983f2", size = 1636549, upload-time = "2026-01-23T15:33:48.643Z" }, - { url = "https://files.pythonhosted.org/packages/5e/b3/c9c23a6478b3bcc91f979ce4ca50879e4d0b2bd7b9a53d8ecded719b92e2/greenlet-3.3.1-cp313-cp313-win_amd64.whl", hash = "sha256:27289986f4e5b0edec7b5a91063c109f0276abb09a7e9bdab08437525977c946", size = 227042, upload-time = "2026-01-23T15:33:58.216Z" }, - { url = "https://files.pythonhosted.org/packages/90/e7/824beda656097edee36ab15809fd063447b200cc03a7f6a24c34d520bc88/greenlet-3.3.1-cp313-cp313-win_arm64.whl", hash = "sha256:2f080e028001c5273e0b42690eaf359aeef9cb1389da0f171ea51a5dc3c7608d", size = 226294, upload-time = "2026-01-23T15:30:52.73Z" }, - { url = "https://files.pythonhosted.org/packages/ae/fb/011c7c717213182caf78084a9bea51c8590b0afda98001f69d9f853a495b/greenlet-3.3.1-cp314-cp314-macosx_11_0_universal2.whl", hash = "sha256:bd59acd8529b372775cd0fcbc5f420ae20681c5b045ce25bd453ed8455ab99b5", size = 275737, upload-time = "2026-01-23T15:32:16.889Z" }, - { url = "https://files.pythonhosted.org/packages/41/2e/a3a417d620363fdbb08a48b1dd582956a46a61bf8fd27ee8164f9dfe87c2/greenlet-3.3.1-cp314-cp314-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b31c05dd84ef6871dd47120386aed35323c944d86c3d91a17c4b8d23df62f15b", size = 646422, upload-time = "2026-01-23T16:01:00.354Z" }, - { url = "https://files.pythonhosted.org/packages/b4/09/c6c4a0db47defafd2d6bab8ddfe47ad19963b4e30f5bed84d75328059f8c/greenlet-3.3.1-cp314-cp314-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:02925a0bfffc41e542c70aa14c7eda3593e4d7e274bfcccca1827e6c0875902e", size = 658219, upload-time = "2026-01-23T16:05:30.956Z" }, - { url = "https://files.pythonhosted.org/packages/e2/89/b95f2ddcc5f3c2bc09c8ee8d77be312df7f9e7175703ab780f2014a0e781/greenlet-3.3.1-cp314-cp314-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:3e0f3878ca3a3ff63ab4ea478585942b53df66ddde327b59ecb191b19dbbd62d", size = 671455, upload-time = "2026-01-23T16:15:57.232Z" }, - { url = "https://files.pythonhosted.org/packages/80/38/9d42d60dffb04b45f03dbab9430898352dba277758640751dc5cc316c521/greenlet-3.3.1-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:34a729e2e4e4ffe9ae2408d5ecaf12f944853f40ad724929b7585bca808a9d6f", size = 660237, upload-time = "2026-01-23T15:32:53.967Z" }, - { url = "https://files.pythonhosted.org/packages/96/61/373c30b7197f9e756e4c81ae90a8d55dc3598c17673f91f4d31c3c689c3f/greenlet-3.3.1-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:aec9ab04e82918e623415947921dea15851b152b822661cce3f8e4393c3df683", size = 1615261, upload-time = "2026-01-23T16:04:25.066Z" }, - { url = "https://files.pythonhosted.org/packages/fd/d3/ca534310343f5945316f9451e953dcd89b36fe7a19de652a1dc5a0eeef3f/greenlet-3.3.1-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:71c767cf281a80d02b6c1bdc41c9468e1f5a494fb11bc8688c360524e273d7b1", size = 1683719, upload-time = "2026-01-23T15:33:50.61Z" }, - { url = "https://files.pythonhosted.org/packages/52/cb/c21a3fd5d2c9c8b622e7bede6d6d00e00551a5ee474ea6d831b5f567a8b4/greenlet-3.3.1-cp314-cp314-win_amd64.whl", hash = "sha256:96aff77af063b607f2489473484e39a0bbae730f2ea90c9e5606c9b73c44174a", size = 228125, upload-time = "2026-01-23T15:32:45.265Z" }, - { url = "https://files.pythonhosted.org/packages/6a/8e/8a2db6d11491837af1de64b8aff23707c6e85241be13c60ed399a72e2ef8/greenlet-3.3.1-cp314-cp314-win_arm64.whl", hash = "sha256:b066e8b50e28b503f604fa538adc764a638b38cf8e81e025011d26e8a627fa79", size = 227519, upload-time = "2026-01-23T15:31:47.284Z" }, - { url = "https://files.pythonhosted.org/packages/28/24/cbbec49bacdcc9ec652a81d3efef7b59f326697e7edf6ed775a5e08e54c2/greenlet-3.3.1-cp314-cp314t-macosx_11_0_universal2.whl", hash = "sha256:3e63252943c921b90abb035ebe9de832c436401d9c45f262d80e2d06cc659242", size = 282706, upload-time = "2026-01-23T15:33:05.525Z" }, - { url = "https://files.pythonhosted.org/packages/86/2e/4f2b9323c144c4fe8842a4e0d92121465485c3c2c5b9e9b30a52e80f523f/greenlet-3.3.1-cp314-cp314t-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:76e39058e68eb125de10c92524573924e827927df5d3891fbc97bd55764a8774", size = 651209, upload-time = "2026-01-23T16:01:01.517Z" }, - { url = "https://files.pythonhosted.org/packages/d9/87/50ca60e515f5bb55a2fbc5f0c9b5b156de7d2fc51a0a69abc9d23914a237/greenlet-3.3.1-cp314-cp314t-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:c9f9d5e7a9310b7a2f416dd13d2e3fd8b42d803968ea580b7c0f322ccb389b97", size = 654300, upload-time = "2026-01-23T16:05:32.199Z" }, - { url = "https://files.pythonhosted.org/packages/7c/25/c51a63f3f463171e09cb586eb64db0861eb06667ab01a7968371a24c4f3b/greenlet-3.3.1-cp314-cp314t-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:4b9721549a95db96689458a1e0ae32412ca18776ed004463df3a9299c1b257ab", size = 662574, upload-time = "2026-01-23T16:15:58.364Z" }, - { url = "https://files.pythonhosted.org/packages/1d/94/74310866dfa2b73dd08659a3d18762f83985ad3281901ba0ee9a815194fb/greenlet-3.3.1-cp314-cp314t-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:92497c78adf3ac703b57f1e3813c2d874f27f71a178f9ea5887855da413cd6d2", size = 653842, upload-time = "2026-01-23T15:32:55.671Z" }, - { url = "https://files.pythonhosted.org/packages/97/43/8bf0ffa3d498eeee4c58c212a3905dd6146c01c8dc0b0a046481ca29b18c/greenlet-3.3.1-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:ed6b402bc74d6557a705e197d47f9063733091ed6357b3de33619d8a8d93ac53", size = 1614917, upload-time = "2026-01-23T16:04:26.276Z" }, - { url = "https://files.pythonhosted.org/packages/89/90/a3be7a5f378fc6e84abe4dcfb2ba32b07786861172e502388b4c90000d1b/greenlet-3.3.1-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:59913f1e5ada20fde795ba906916aea25d442abcc0593fba7e26c92b7ad76249", size = 1676092, upload-time = "2026-01-23T15:33:52.176Z" }, - { url = "https://files.pythonhosted.org/packages/e1/2b/98c7f93e6db9977aaee07eb1e51ca63bd5f779b900d362791d3252e60558/greenlet-3.3.1-cp314-cp314t-win_amd64.whl", hash = "sha256:301860987846c24cb8964bdec0e31a96ad4a2a801b41b4ef40963c1b44f33451", size = 233181, upload-time = "2026-01-23T15:33:00.29Z" }, -] - -[[package]] -name = "h11" -version = "0.16.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/01/ee/02a2c011bdab74c6fb3c75474d40b3052059d95df7e73351460c8588d963/h11-0.16.0.tar.gz", hash = "sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1", size = 101250, upload-time = "2025-04-24T03:35:25.427Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86", size = 37515, upload-time = "2025-04-24T03:35:24.344Z" }, -] - -[[package]] -name = "httpcore" -version = "1.0.9" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "certifi" }, - { name = "h11" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/06/94/82699a10bca87a5556c9c59b5963f2d039dbd239f25bc2a63907a05a14cb/httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8", size = 85484, upload-time = "2025-04-24T22:06:22.219Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55", size = 78784, upload-time = "2025-04-24T22:06:20.566Z" }, -] - -[[package]] -name = "httpx" -version = "0.28.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "certifi" }, - { name = "httpcore" }, - { name = "idna" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/b1/df/48c586a5fe32a0f01324ee087459e112ebb7224f646c0b5023f5e79e9956/httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc", size = 141406, upload-time = "2024-12-06T15:37:23.222Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad", size = 73517, upload-time = "2024-12-06T15:37:21.509Z" }, -] - -[[package]] -name = "idna" -version = "3.11" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/6f/6d/0703ccc57f3a7233505399edb88de3cbd678da106337b9fcde432b65ed60/idna-3.11.tar.gz", hash = "sha256:795dafcc9c04ed0c1fb032c2aa73654d8e8c5023a7df64a53f39190ada629902", size = 194582, upload-time = "2025-10-12T14:55:20.501Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl", hash = "sha256:771a87f49d9defaf64091e6e6fe9c18d4833f140bd19464795bc32d966ca37ea", size = 71008, upload-time = "2025-10-12T14:55:18.883Z" }, -] - -[[package]] -name = "jiter" -version = "0.13.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/0d/5e/4ec91646aee381d01cdb9974e30882c9cd3b8c5d1079d6b5ff4af522439a/jiter-0.13.0.tar.gz", hash = "sha256:f2839f9c2c7e2dffc1bc5929a510e14ce0a946be9365fd1219e7ef342dae14f4", size = 164847, upload-time = "2026-02-02T12:37:56.441Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/71/29/499f8c9eaa8a16751b1c0e45e6f5f1761d180da873d417996cc7bddc8eef/jiter-0.13.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ea026e70a9a28ebbdddcbcf0f1323128a8db66898a06eaad3a4e62d2f554d096", size = 311157, upload-time = "2026-02-02T12:35:37.758Z" }, - { url = "https://files.pythonhosted.org/packages/50/f6/566364c777d2ab450b92100bea11333c64c38d32caf8dc378b48e5b20c46/jiter-0.13.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:66aa3e663840152d18cc8ff1e4faad3dd181373491b9cfdc6004b92198d67911", size = 319729, upload-time = "2026-02-02T12:35:39.246Z" }, - { url = "https://files.pythonhosted.org/packages/73/dd/560f13ec5e4f116d8ad2658781646cca91b617ae3b8758d4a5076b278f70/jiter-0.13.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c3524798e70655ff19aec58c7d05adb1f074fecff62da857ea9be2b908b6d701", size = 354766, upload-time = "2026-02-02T12:35:40.662Z" }, - { url = "https://files.pythonhosted.org/packages/7c/0d/061faffcfe94608cbc28a0d42a77a74222bdf5055ccdbe5fd2292b94f510/jiter-0.13.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ec7e287d7fbd02cb6e22f9a00dd9c9cd504c40a61f2c61e7e1f9690a82726b4c", size = 362587, upload-time = "2026-02-02T12:35:42.025Z" }, - { url = "https://files.pythonhosted.org/packages/92/c9/c66a7864982fd38a9773ec6e932e0398d1262677b8c60faecd02ffb67bf3/jiter-0.13.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:47455245307e4debf2ce6c6e65a717550a0244231240dcf3b8f7d64e4c2f22f4", size = 487537, upload-time = "2026-02-02T12:35:43.459Z" }, - { url = "https://files.pythonhosted.org/packages/6c/86/84eb4352cd3668f16d1a88929b5888a3fe0418ea8c1dfc2ad4e7bf6e069a/jiter-0.13.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ee9da221dca6e0429c2704c1b3655fe7b025204a71d4d9b73390c759d776d165", size = 373717, upload-time = "2026-02-02T12:35:44.928Z" }, - { url = "https://files.pythonhosted.org/packages/6e/09/9fe4c159358176f82d4390407a03f506a8659ed13ca3ac93a843402acecf/jiter-0.13.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:24ab43126d5e05f3d53a36a8e11eb2f23304c6c1117844aaaf9a0aa5e40b5018", size = 362683, upload-time = "2026-02-02T12:35:46.636Z" }, - { url = "https://files.pythonhosted.org/packages/c9/5e/85f3ab9caca0c1d0897937d378b4a515cae9e119730563572361ea0c48ae/jiter-0.13.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9da38b4fedde4fb528c740c2564628fbab737166a0e73d6d46cb4bb5463ff411", size = 392345, upload-time = "2026-02-02T12:35:48.088Z" }, - { url = "https://files.pythonhosted.org/packages/12/4c/05b8629ad546191939e6f0c2f17e29f542a398f4a52fb987bc70b6d1eb8b/jiter-0.13.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:0b34c519e17658ed88d5047999a93547f8889f3c1824120c26ad6be5f27b6cf5", size = 517775, upload-time = "2026-02-02T12:35:49.482Z" }, - { url = "https://files.pythonhosted.org/packages/4d/88/367ea2eb6bc582c7052e4baf5ddf57ebe5ab924a88e0e09830dfb585c02d/jiter-0.13.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d2a6394e6af690d462310a86b53c47ad75ac8c21dc79f120714ea449979cb1d3", size = 551325, upload-time = "2026-02-02T12:35:51.104Z" }, - { url = "https://files.pythonhosted.org/packages/f3/12/fa377ffb94a2f28c41afaed093e0d70cfe512035d5ecb0cad0ae4792d35e/jiter-0.13.0-cp311-cp311-win32.whl", hash = "sha256:0f0c065695f616a27c920a56ad0d4fc46415ef8b806bf8fc1cacf25002bd24e1", size = 204709, upload-time = "2026-02-02T12:35:52.467Z" }, - { url = "https://files.pythonhosted.org/packages/cb/16/8e8203ce92f844dfcd3d9d6a5a7322c77077248dbb12da52d23193a839cd/jiter-0.13.0-cp311-cp311-win_amd64.whl", hash = "sha256:0733312953b909688ae3c2d58d043aa040f9f1a6a75693defed7bc2cc4bf2654", size = 204560, upload-time = "2026-02-02T12:35:53.925Z" }, - { url = "https://files.pythonhosted.org/packages/44/26/97cc40663deb17b9e13c3a5cf29251788c271b18ee4d262c8f94798b8336/jiter-0.13.0-cp311-cp311-win_arm64.whl", hash = "sha256:5d9b34ad56761b3bf0fbe8f7e55468704107608512350962d3317ffd7a4382d5", size = 189608, upload-time = "2026-02-02T12:35:55.304Z" }, - { url = "https://files.pythonhosted.org/packages/2e/30/7687e4f87086829955013ca12a9233523349767f69653ebc27036313def9/jiter-0.13.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:0a2bd69fc1d902e89925fc34d1da51b2128019423d7b339a45d9e99c894e0663", size = 307958, upload-time = "2026-02-02T12:35:57.165Z" }, - { url = "https://files.pythonhosted.org/packages/c3/27/e57f9a783246ed95481e6749cc5002a8a767a73177a83c63ea71f0528b90/jiter-0.13.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f917a04240ef31898182f76a332f508f2cc4b57d2b4d7ad2dbfebbfe167eb505", size = 318597, upload-time = "2026-02-02T12:35:58.591Z" }, - { url = "https://files.pythonhosted.org/packages/cf/52/e5719a60ac5d4d7c5995461a94ad5ef962a37c8bf5b088390e6fad59b2ff/jiter-0.13.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c1e2b199f446d3e82246b4fd9236d7cb502dc2222b18698ba0d986d2fecc6152", size = 348821, upload-time = "2026-02-02T12:36:00.093Z" }, - { url = "https://files.pythonhosted.org/packages/61/db/c1efc32b8ba4c740ab3fc2d037d8753f67685f475e26b9d6536a4322bcdd/jiter-0.13.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:04670992b576fa65bd056dbac0c39fe8bd67681c380cb2b48efa885711d9d726", size = 364163, upload-time = "2026-02-02T12:36:01.937Z" }, - { url = "https://files.pythonhosted.org/packages/55/8a/fb75556236047c8806995671a18e4a0ad646ed255276f51a20f32dceaeec/jiter-0.13.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5a1aff1fbdb803a376d4d22a8f63f8e7ccbce0b4890c26cc7af9e501ab339ef0", size = 483709, upload-time = "2026-02-02T12:36:03.41Z" }, - { url = "https://files.pythonhosted.org/packages/7e/16/43512e6ee863875693a8e6f6d532e19d650779d6ba9a81593ae40a9088ff/jiter-0.13.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3b3fb8c2053acaef8580809ac1d1f7481a0a0bdc012fd7f5d8b18fb696a5a089", size = 370480, upload-time = "2026-02-02T12:36:04.791Z" }, - { url = "https://files.pythonhosted.org/packages/f8/4c/09b93e30e984a187bc8aaa3510e1ec8dcbdcd71ca05d2f56aac0492453aa/jiter-0.13.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bdaba7d87e66f26a2c45d8cbadcbfc4bf7884182317907baf39cfe9775bb4d93", size = 360735, upload-time = "2026-02-02T12:36:06.994Z" }, - { url = "https://files.pythonhosted.org/packages/1a/1b/46c5e349019874ec5dfa508c14c37e29864ea108d376ae26d90bee238cd7/jiter-0.13.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:7b88d649135aca526da172e48083da915ec086b54e8e73a425ba50999468cc08", size = 391814, upload-time = "2026-02-02T12:36:08.368Z" }, - { url = "https://files.pythonhosted.org/packages/15/9e/26184760e85baee7162ad37b7912797d2077718476bf91517641c92b3639/jiter-0.13.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:e404ea551d35438013c64b4f357b0474c7abf9f781c06d44fcaf7a14c69ff9e2", size = 513990, upload-time = "2026-02-02T12:36:09.993Z" }, - { url = "https://files.pythonhosted.org/packages/e9/34/2c9355247d6debad57a0a15e76ab1566ab799388042743656e566b3b7de1/jiter-0.13.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:1f4748aad1b4a93c8bdd70f604d0f748cdc0e8744c5547798acfa52f10e79228", size = 548021, upload-time = "2026-02-02T12:36:11.376Z" }, - { url = "https://files.pythonhosted.org/packages/ac/4a/9f2c23255d04a834398b9c2e0e665382116911dc4d06b795710503cdad25/jiter-0.13.0-cp312-cp312-win32.whl", hash = "sha256:0bf670e3b1445fc4d31612199f1744f67f889ee1bbae703c4b54dc097e5dd394", size = 203024, upload-time = "2026-02-02T12:36:12.682Z" }, - { url = "https://files.pythonhosted.org/packages/09/ee/f0ae675a957ae5a8f160be3e87acea6b11dc7b89f6b7ab057e77b2d2b13a/jiter-0.13.0-cp312-cp312-win_amd64.whl", hash = "sha256:15db60e121e11fe186c0b15236bd5d18381b9ddacdcf4e659feb96fc6c969c92", size = 205424, upload-time = "2026-02-02T12:36:13.93Z" }, - { url = "https://files.pythonhosted.org/packages/1b/02/ae611edf913d3cbf02c97cdb90374af2082c48d7190d74c1111dde08bcdd/jiter-0.13.0-cp312-cp312-win_arm64.whl", hash = "sha256:41f92313d17989102f3cb5dd533a02787cdb99454d494344b0361355da52fcb9", size = 186818, upload-time = "2026-02-02T12:36:15.308Z" }, - { url = "https://files.pythonhosted.org/packages/91/9c/7ee5a6ff4b9991e1a45263bfc46731634c4a2bde27dfda6c8251df2d958c/jiter-0.13.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:1f8a55b848cbabf97d861495cd65f1e5c590246fabca8b48e1747c4dfc8f85bf", size = 306897, upload-time = "2026-02-02T12:36:16.748Z" }, - { url = "https://files.pythonhosted.org/packages/7c/02/be5b870d1d2be5dd6a91bdfb90f248fbb7dcbd21338f092c6b89817c3dbf/jiter-0.13.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:f556aa591c00f2c45eb1b89f68f52441a016034d18b65da60e2d2875bbbf344a", size = 317507, upload-time = "2026-02-02T12:36:18.351Z" }, - { url = "https://files.pythonhosted.org/packages/da/92/b25d2ec333615f5f284f3a4024f7ce68cfa0604c322c6808b2344c7f5d2b/jiter-0.13.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f7e1d61da332ec412350463891923f960c3073cf1aae93b538f0bb4c8cd46efb", size = 350560, upload-time = "2026-02-02T12:36:19.746Z" }, - { url = "https://files.pythonhosted.org/packages/be/ec/74dcb99fef0aca9fbe56b303bf79f6bd839010cb18ad41000bf6cc71eec0/jiter-0.13.0-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:3097d665a27bc96fd9bbf7f86178037db139f319f785e4757ce7ccbf390db6c2", size = 363232, upload-time = "2026-02-02T12:36:21.243Z" }, - { url = "https://files.pythonhosted.org/packages/1b/37/f17375e0bb2f6a812d4dd92d7616e41917f740f3e71343627da9db2824ce/jiter-0.13.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9d01ecc3a8cbdb6f25a37bd500510550b64ddf9f7d64a107d92f3ccb25035d0f", size = 483727, upload-time = "2026-02-02T12:36:22.688Z" }, - { url = "https://files.pythonhosted.org/packages/77/d2/a71160a5ae1a1e66c1395b37ef77da67513b0adba73b993a27fbe47eb048/jiter-0.13.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ed9bbc30f5d60a3bdf63ae76beb3f9db280d7f195dfcfa61af792d6ce912d159", size = 370799, upload-time = "2026-02-02T12:36:24.106Z" }, - { url = "https://files.pythonhosted.org/packages/01/99/ed5e478ff0eb4e8aa5fd998f9d69603c9fd3f32de3bd16c2b1194f68361c/jiter-0.13.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98fbafb6e88256f4454de33c1f40203d09fc33ed19162a68b3b257b29ca7f663", size = 359120, upload-time = "2026-02-02T12:36:25.519Z" }, - { url = "https://files.pythonhosted.org/packages/16/be/7ffd08203277a813f732ba897352797fa9493faf8dc7995b31f3d9cb9488/jiter-0.13.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:5467696f6b827f1116556cb0db620440380434591e93ecee7fd14d1a491b6daa", size = 390664, upload-time = "2026-02-02T12:36:26.866Z" }, - { url = "https://files.pythonhosted.org/packages/d1/84/e0787856196d6d346264d6dcccb01f741e5f0bd014c1d9a2ebe149caf4f3/jiter-0.13.0-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:2d08c9475d48b92892583df9da592a0e2ac49bcd41fae1fec4f39ba6cf107820", size = 513543, upload-time = "2026-02-02T12:36:28.217Z" }, - { url = "https://files.pythonhosted.org/packages/65/50/ecbd258181c4313cf79bca6c88fb63207d04d5bf5e4f65174114d072aa55/jiter-0.13.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:aed40e099404721d7fcaf5b89bd3b4568a4666358bcac7b6b15c09fb6252ab68", size = 547262, upload-time = "2026-02-02T12:36:29.678Z" }, - { url = "https://files.pythonhosted.org/packages/27/da/68f38d12e7111d2016cd198161b36e1f042bd115c169255bcb7ec823a3bf/jiter-0.13.0-cp313-cp313-win32.whl", hash = "sha256:36ebfbcffafb146d0e6ffb3e74d51e03d9c35ce7c625c8066cdbfc7b953bdc72", size = 200630, upload-time = "2026-02-02T12:36:31.808Z" }, - { url = "https://files.pythonhosted.org/packages/25/65/3bd1a972c9a08ecd22eb3b08a95d1941ebe6938aea620c246cf426ae09c2/jiter-0.13.0-cp313-cp313-win_amd64.whl", hash = "sha256:8d76029f077379374cf0dbc78dbe45b38dec4a2eb78b08b5194ce836b2517afc", size = 202602, upload-time = "2026-02-02T12:36:33.679Z" }, - { url = "https://files.pythonhosted.org/packages/15/fe/13bd3678a311aa67686bb303654792c48206a112068f8b0b21426eb6851e/jiter-0.13.0-cp313-cp313-win_arm64.whl", hash = "sha256:bb7613e1a427cfcb6ea4544f9ac566b93d5bf67e0d48c787eca673ff9c9dff2b", size = 185939, upload-time = "2026-02-02T12:36:35.065Z" }, - { url = "https://files.pythonhosted.org/packages/49/19/a929ec002ad3228bc97ca01dbb14f7632fffdc84a95ec92ceaf4145688ae/jiter-0.13.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:fa476ab5dd49f3bf3a168e05f89358c75a17608dbabb080ef65f96b27c19ab10", size = 316616, upload-time = "2026-02-02T12:36:36.579Z" }, - { url = "https://files.pythonhosted.org/packages/52/56/d19a9a194afa37c1728831e5fb81b7722c3de18a3109e8f282bfc23e587a/jiter-0.13.0-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ade8cb6ff5632a62b7dbd4757d8c5573f7a2e9ae285d6b5b841707d8363205ef", size = 346850, upload-time = "2026-02-02T12:36:38.058Z" }, - { url = "https://files.pythonhosted.org/packages/36/4a/94e831c6bf287754a8a019cb966ed39ff8be6ab78cadecf08df3bb02d505/jiter-0.13.0-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9950290340acc1adaded363edd94baebcee7dabdfa8bee4790794cd5cfad2af6", size = 358551, upload-time = "2026-02-02T12:36:39.417Z" }, - { url = "https://files.pythonhosted.org/packages/a2/ec/a4c72c822695fa80e55d2b4142b73f0012035d9fcf90eccc56bc060db37c/jiter-0.13.0-cp313-cp313t-win_amd64.whl", hash = "sha256:2b4972c6df33731aac0742b64fd0d18e0a69bc7d6e03108ce7d40c85fd9e3e6d", size = 201950, upload-time = "2026-02-02T12:36:40.791Z" }, - { url = "https://files.pythonhosted.org/packages/b6/00/393553ec27b824fbc29047e9c7cd4a3951d7fbe4a76743f17e44034fa4e4/jiter-0.13.0-cp313-cp313t-win_arm64.whl", hash = "sha256:701a1e77d1e593c1b435315ff625fd071f0998c5f02792038a5ca98899261b7d", size = 185852, upload-time = "2026-02-02T12:36:42.077Z" }, - { url = "https://files.pythonhosted.org/packages/6e/f5/f1997e987211f6f9bd71b8083047b316208b4aca0b529bb5f8c96c89ef3e/jiter-0.13.0-cp314-cp314-macosx_10_12_x86_64.whl", hash = "sha256:cc5223ab19fe25e2f0bf2643204ad7318896fe3729bf12fde41b77bfc4fafff0", size = 308804, upload-time = "2026-02-02T12:36:43.496Z" }, - { url = "https://files.pythonhosted.org/packages/cd/8f/5482a7677731fd44881f0204981ce2d7175db271f82cba2085dd2212e095/jiter-0.13.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:9776ebe51713acf438fd9b4405fcd86893ae5d03487546dae7f34993217f8a91", size = 318787, upload-time = "2026-02-02T12:36:45.071Z" }, - { url = "https://files.pythonhosted.org/packages/f3/b9/7257ac59778f1cd025b26a23c5520a36a424f7f1b068f2442a5b499b7464/jiter-0.13.0-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:879e768938e7b49b5e90b7e3fecc0dbec01b8cb89595861fb39a8967c5220d09", size = 353880, upload-time = "2026-02-02T12:36:47.365Z" }, - { url = "https://files.pythonhosted.org/packages/c3/87/719eec4a3f0841dad99e3d3604ee4cba36af4419a76f3cb0b8e2e691ad67/jiter-0.13.0-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:682161a67adea11e3aae9038c06c8b4a9a71023228767477d683f69903ebc607", size = 366702, upload-time = "2026-02-02T12:36:48.871Z" }, - { url = "https://files.pythonhosted.org/packages/d2/65/415f0a75cf6921e43365a1bc227c565cb949caca8b7532776e430cbaa530/jiter-0.13.0-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a13b68cd1cd8cc9de8f244ebae18ccb3e4067ad205220ef324c39181e23bbf66", size = 486319, upload-time = "2026-02-02T12:36:53.006Z" }, - { url = "https://files.pythonhosted.org/packages/54/a2/9e12b48e82c6bbc6081fd81abf915e1443add1b13d8fc586e1d90bb02bb8/jiter-0.13.0-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:87ce0f14c6c08892b610686ae8be350bf368467b6acd5085a5b65441e2bf36d2", size = 372289, upload-time = "2026-02-02T12:36:54.593Z" }, - { url = "https://files.pythonhosted.org/packages/4e/c1/e4693f107a1789a239c759a432e9afc592366f04e901470c2af89cfd28e1/jiter-0.13.0-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0c365005b05505a90d1c47856420980d0237adf82f70c4aff7aebd3c1cc143ad", size = 360165, upload-time = "2026-02-02T12:36:56.112Z" }, - { url = "https://files.pythonhosted.org/packages/17/08/91b9ea976c1c758240614bd88442681a87672eebc3d9a6dde476874e706b/jiter-0.13.0-cp314-cp314-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1317fdffd16f5873e46ce27d0e0f7f4f90f0cdf1d86bf6abeaea9f63ca2c401d", size = 389634, upload-time = "2026-02-02T12:36:57.495Z" }, - { url = "https://files.pythonhosted.org/packages/18/23/58325ef99390d6d40427ed6005bf1ad54f2577866594bcf13ce55675f87d/jiter-0.13.0-cp314-cp314-musllinux_1_1_aarch64.whl", hash = "sha256:c05b450d37ba0c9e21c77fef1f205f56bcee2330bddca68d344baebfc55ae0df", size = 514933, upload-time = "2026-02-02T12:36:58.909Z" }, - { url = "https://files.pythonhosted.org/packages/5b/25/69f1120c7c395fd276c3996bb8adefa9c6b84c12bb7111e5c6ccdcd8526d/jiter-0.13.0-cp314-cp314-musllinux_1_1_x86_64.whl", hash = "sha256:775e10de3849d0631a97c603f996f518159272db00fdda0a780f81752255ee9d", size = 548842, upload-time = "2026-02-02T12:37:00.433Z" }, - { url = "https://files.pythonhosted.org/packages/18/05/981c9669d86850c5fbb0d9e62bba144787f9fba84546ba43d624ee27ef29/jiter-0.13.0-cp314-cp314-win32.whl", hash = "sha256:632bf7c1d28421c00dd8bbb8a3bac5663e1f57d5cd5ed962bce3c73bf62608e6", size = 202108, upload-time = "2026-02-02T12:37:01.718Z" }, - { url = "https://files.pythonhosted.org/packages/8d/96/cdcf54dd0b0341db7d25413229888a346c7130bd20820530905fdb65727b/jiter-0.13.0-cp314-cp314-win_amd64.whl", hash = "sha256:f22ef501c3f87ede88f23f9b11e608581c14f04db59b6a801f354397ae13739f", size = 204027, upload-time = "2026-02-02T12:37:03.075Z" }, - { url = "https://files.pythonhosted.org/packages/fb/f9/724bcaaab7a3cd727031fe4f6995cb86c4bd344909177c186699c8dec51a/jiter-0.13.0-cp314-cp314-win_arm64.whl", hash = "sha256:07b75fe09a4ee8e0c606200622e571e44943f47254f95e2436c8bdcaceb36d7d", size = 187199, upload-time = "2026-02-02T12:37:04.414Z" }, - { url = "https://files.pythonhosted.org/packages/62/92/1661d8b9fd6a3d7a2d89831db26fe3c1509a287d83ad7838831c7b7a5c7e/jiter-0.13.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:964538479359059a35fb400e769295d4b315ae61e4105396d355a12f7fef09f0", size = 318423, upload-time = "2026-02-02T12:37:05.806Z" }, - { url = "https://files.pythonhosted.org/packages/4f/3b/f77d342a54d4ebcd128e520fc58ec2f5b30a423b0fd26acdfc0c6fef8e26/jiter-0.13.0-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e104da1db1c0991b3eaed391ccd650ae8d947eab1480c733e5a3fb28d4313e40", size = 351438, upload-time = "2026-02-02T12:37:07.189Z" }, - { url = "https://files.pythonhosted.org/packages/76/b3/ba9a69f0e4209bd3331470c723c2f5509e6f0482e416b612431a5061ed71/jiter-0.13.0-cp314-cp314t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0e3a5f0cde8ff433b8e88e41aa40131455420fb3649a3c7abdda6145f8cb7202", size = 364774, upload-time = "2026-02-02T12:37:08.579Z" }, - { url = "https://files.pythonhosted.org/packages/b3/16/6cdb31fa342932602458dbb631bfbd47f601e03d2e4950740e0b2100b570/jiter-0.13.0-cp314-cp314t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:57aab48f40be1db920a582b30b116fe2435d184f77f0e4226f546794cedd9cf0", size = 487238, upload-time = "2026-02-02T12:37:10.066Z" }, - { url = "https://files.pythonhosted.org/packages/ed/b1/956cc7abaca8d95c13aa8d6c9b3f3797241c246cd6e792934cc4c8b250d2/jiter-0.13.0-cp314-cp314t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7772115877c53f62beeb8fd853cab692dbc04374ef623b30f997959a4c0e7e95", size = 372892, upload-time = "2026-02-02T12:37:11.656Z" }, - { url = "https://files.pythonhosted.org/packages/26/c4/97ecde8b1e74f67b8598c57c6fccf6df86ea7861ed29da84629cdbba76c4/jiter-0.13.0-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1211427574b17b633cfceba5040de8081e5abf114f7a7602f73d2e16f9fdaa59", size = 360309, upload-time = "2026-02-02T12:37:13.244Z" }, - { url = "https://files.pythonhosted.org/packages/4b/d7/eabe3cf46715854ccc80be2cd78dd4c36aedeb30751dbf85a1d08c14373c/jiter-0.13.0-cp314-cp314t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:7beae3a3d3b5212d3a55d2961db3c292e02e302feb43fce6a3f7a31b90ea6dfe", size = 389607, upload-time = "2026-02-02T12:37:14.881Z" }, - { url = "https://files.pythonhosted.org/packages/df/2d/03963fc0804e6109b82decfb9974eb92df3797fe7222428cae12f8ccaa0c/jiter-0.13.0-cp314-cp314t-musllinux_1_1_aarch64.whl", hash = "sha256:e5562a0f0e90a6223b704163ea28e831bd3a9faa3512a711f031611e6b06c939", size = 514986, upload-time = "2026-02-02T12:37:16.326Z" }, - { url = "https://files.pythonhosted.org/packages/f6/6c/8c83b45eb3eb1c1e18d841fe30b4b5bc5619d781267ca9bc03e005d8fd0a/jiter-0.13.0-cp314-cp314t-musllinux_1_1_x86_64.whl", hash = "sha256:6c26a424569a59140fb51160a56df13f438a2b0967365e987889186d5fc2f6f9", size = 548756, upload-time = "2026-02-02T12:37:17.736Z" }, - { url = "https://files.pythonhosted.org/packages/47/66/eea81dfff765ed66c68fd2ed8c96245109e13c896c2a5015c7839c92367e/jiter-0.13.0-cp314-cp314t-win32.whl", hash = "sha256:24dc96eca9f84da4131cdf87a95e6ce36765c3b156fc9ae33280873b1c32d5f6", size = 201196, upload-time = "2026-02-02T12:37:19.101Z" }, - { url = "https://files.pythonhosted.org/packages/ff/32/4ac9c7a76402f8f00d00842a7f6b83b284d0cf7c1e9d4227bc95aa6d17fa/jiter-0.13.0-cp314-cp314t-win_amd64.whl", hash = "sha256:0a8d76c7524087272c8ae913f5d9d608bd839154b62c4322ef65723d2e5bb0b8", size = 204215, upload-time = "2026-02-02T12:37:20.495Z" }, - { url = "https://files.pythonhosted.org/packages/f9/8e/7def204fea9f9be8b3c21a6f2dd6c020cf56c7d5ff753e0e23ed7f9ea57e/jiter-0.13.0-cp314-cp314t-win_arm64.whl", hash = "sha256:2c26cf47e2cad140fa23b6d58d435a7c0161f5c514284802f25e87fddfe11024", size = 187152, upload-time = "2026-02-02T12:37:22.124Z" }, - { url = "https://files.pythonhosted.org/packages/79/b3/3c29819a27178d0e461a8571fb63c6ae38be6dc36b78b3ec2876bbd6a910/jiter-0.13.0-graalpy311-graalpy242_311_native-macosx_10_12_x86_64.whl", hash = "sha256:b1cbfa133241d0e6bdab48dcdc2604e8ba81512f6bbd68ec3e8e1357dd3c316c", size = 307016, upload-time = "2026-02-02T12:37:42.755Z" }, - { url = "https://files.pythonhosted.org/packages/eb/ae/60993e4b07b1ac5ebe46da7aa99fdbb802eb986c38d26e3883ac0125c4e0/jiter-0.13.0-graalpy311-graalpy242_311_native-macosx_11_0_arm64.whl", hash = "sha256:db367d8be9fad6e8ebbac4a7578b7af562e506211036cba2c06c3b998603c3d2", size = 305024, upload-time = "2026-02-02T12:37:44.774Z" }, - { url = "https://files.pythonhosted.org/packages/77/fa/2227e590e9cf98803db2811f172b2d6460a21539ab73006f251c66f44b14/jiter-0.13.0-graalpy311-graalpy242_311_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45f6f8efb2f3b0603092401dc2df79fa89ccbc027aaba4174d2d4133ed661434", size = 339337, upload-time = "2026-02-02T12:37:46.668Z" }, - { url = "https://files.pythonhosted.org/packages/2d/92/015173281f7eb96c0ef580c997da8ef50870d4f7f4c9e03c845a1d62ae04/jiter-0.13.0-graalpy311-graalpy242_311_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:597245258e6ad085d064780abfb23a284d418d3e61c57362d9449c6c7317ee2d", size = 346395, upload-time = "2026-02-02T12:37:48.09Z" }, - { url = "https://files.pythonhosted.org/packages/80/60/e50fa45dd7e2eae049f0ce964663849e897300433921198aef94b6ffa23a/jiter-0.13.0-graalpy312-graalpy250_312_native-macosx_10_12_x86_64.whl", hash = "sha256:3d744a6061afba08dd7ae375dcde870cffb14429b7477e10f67e9e6d68772a0a", size = 305169, upload-time = "2026-02-02T12:37:50.376Z" }, - { url = "https://files.pythonhosted.org/packages/d2/73/a009f41c5eed71c49bec53036c4b33555afcdee70682a18c6f66e396c039/jiter-0.13.0-graalpy312-graalpy250_312_native-macosx_11_0_arm64.whl", hash = "sha256:ff732bd0a0e778f43d5009840f20b935e79087b4dc65bd36f1cd0f9b04b8ff7f", size = 303808, upload-time = "2026-02-02T12:37:52.092Z" }, - { url = "https://files.pythonhosted.org/packages/c4/10/528b439290763bff3d939268085d03382471b442f212dca4ff5f12802d43/jiter-0.13.0-graalpy312-graalpy250_312_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ab44b178f7981fcaea7e0a5df20e773c663d06ffda0198f1a524e91b2fde7e59", size = 337384, upload-time = "2026-02-02T12:37:53.582Z" }, - { url = "https://files.pythonhosted.org/packages/67/8a/a342b2f0251f3dac4ca17618265d93bf244a2a4d089126e81e4c1056ac50/jiter-0.13.0-graalpy312-graalpy250_312_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7bb00b6d26db67a05fe3e12c76edc75f32077fb51deed13822dc648fa373bc19", size = 343768, upload-time = "2026-02-02T12:37:55.055Z" }, -] - -[[package]] -name = "jsonpatch" -version = "1.33" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "jsonpointer" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/42/78/18813351fe5d63acad16aec57f94ec2b70a09e53ca98145589e185423873/jsonpatch-1.33.tar.gz", hash = "sha256:9fcd4009c41e6d12348b4a0ff2563ba56a2923a7dfee731d004e212e1ee5030c", size = 21699, upload-time = "2023-06-26T12:07:29.144Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/73/07/02e16ed01e04a374e644b575638ec7987ae846d25ad97bcc9945a3ee4b0e/jsonpatch-1.33-py2.py3-none-any.whl", hash = "sha256:0ae28c0cd062bbd8b8ecc26d7d164fbbea9652a1a3693f3b956c1eae5145dade", size = 12898, upload-time = "2023-06-16T21:01:28.466Z" }, -] - -[[package]] -name = "jsonpointer" -version = "3.0.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/6a/0a/eebeb1fa92507ea94016a2a790b93c2ae41a7e18778f85471dc54475ed25/jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef", size = 9114, upload-time = "2024-06-10T19:24:42.462Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl", hash = "sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942", size = 7595, upload-time = "2024-06-10T19:24:40.698Z" }, -] - -[[package]] -name = "langchain" -version = "0.3.27" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "langchain-text-splitters" }, - { name = "langsmith" }, - { name = "pydantic" }, - { name = "pyyaml" }, - { name = "requests" }, - { name = "sqlalchemy" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/83/f6/f4f7f3a56626fe07e2bb330feb61254dbdf06c506e6b59a536a337da51cf/langchain-0.3.27.tar.gz", hash = "sha256:aa6f1e6274ff055d0fd36254176770f356ed0a8994297d1df47df341953cec62", size = 10233809, upload-time = "2025-07-24T14:42:32.959Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/f6/d5/4861816a95b2f6993f1360cfb605aacb015506ee2090433a71de9cca8477/langchain-0.3.27-py3-none-any.whl", hash = "sha256:7b20c4f338826acb148d885b20a73a16e410ede9ee4f19bb02011852d5f98798", size = 1018194, upload-time = "2025-07-24T14:42:30.23Z" }, -] - -[[package]] -name = "langchain-anthropic" -version = "0.3.22" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anthropic" }, - { name = "langchain-core" }, - { name = "pydantic" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/b8/ac/4791e4451e1972f80cb517e19d003678239921fc0685a4c4b265fe47e216/langchain_anthropic-0.3.22.tar.gz", hash = "sha256:6c440278bd8012bc94ae341f416bfc724fdc5d2d2b69630fe6e82fa6ee9682ac", size = 471312, upload-time = "2025-10-09T18:39:26.983Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d1/ac/019fd9d45716a4d74c154f160665074ae49885ff4764c8313737f5fda348/langchain_anthropic-0.3.22-py3-none-any.whl", hash = "sha256:17721b240342a1a3f70bf0b2ff33520ba60d69008e3b9433190a62a52ff87cf6", size = 32592, upload-time = "2025-10-09T18:39:25.766Z" }, -] - -[[package]] -name = "langchain-core" -version = "0.3.83" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "jsonpatch" }, - { name = "langsmith" }, - { name = "packaging" }, - { name = "pydantic" }, - { name = "pyyaml" }, - { name = "tenacity" }, - { name = "typing-extensions" }, - { name = "uuid-utils" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/21/a4/24f2d787bfcf56e5990924cacefe6f6e7971a3629f97c8162fc7a2a3d851/langchain_core-0.3.83.tar.gz", hash = "sha256:a0a4c7b6ea1c446d3b432116f405dc2afa1fe7891c44140d3d5acca221909415", size = 597965, upload-time = "2026-01-13T01:19:23.854Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/5a/db/d71b80d3bd6193812485acea4001cdf86cf95a44bbf942f7a240120ff762/langchain_core-0.3.83-py3-none-any.whl", hash = "sha256:8c92506f8b53fc1958b1c07447f58c5783eb8833dd3cb6dc75607c80891ab1ae", size = 458890, upload-time = "2026-01-13T01:19:21.748Z" }, -] - -[[package]] -name = "langchain-openai" -version = "0.3.35" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "openai" }, - { name = "tiktoken" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/fb/96/06d0d25a37e05a0ff2d918f0a4b0bf0732aed6a43b472b0b68426ce04ef8/langchain_openai-0.3.35.tar.gz", hash = "sha256:fa985fd041c3809da256a040c98e8a43e91c6d165b96dcfeb770d8bd457bf76f", size = 786635, upload-time = "2025-10-06T15:09:28.463Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d8/d5/c90c5478215c20ee71d8feaf676f7ffd78d0568f8c98bd83f81ce7562ed7/langchain_openai-0.3.35-py3-none-any.whl", hash = "sha256:76d5707e6e81fd461d33964ad618bd326cb661a1975cef7c1cb0703576bdada5", size = 75952, upload-time = "2025-10-06T15:09:27.137Z" }, -] - -[[package]] -name = "langchain-py-v0" -version = "0.1.0" -source = { virtual = "." } -dependencies = [ - { name = "braintrust" }, - { name = "braintrust-langchain" }, - { name = "langchain" }, - { name = "langchain-anthropic" }, - { name = "langchain-openai" }, - { name = "langgraph" }, -] - -[package.metadata] -requires-dist = [ - { name = "braintrust", editable = "../../../py" }, - { name = "braintrust-langchain", editable = "../../../integrations/langchain-py" }, - { name = "langchain", specifier = ">=0.3.11,<1.0.0" }, - { name = "langchain-anthropic", specifier = ">=0.3.22" }, - { name = "langchain-openai", specifier = ">=0.3.35" }, - { name = "langgraph", specifier = ">=0.3.11,<1.0.0" }, -] - -[[package]] -name = "langchain-text-splitters" -version = "0.3.11" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/11/43/dcda8fd25f0b19cb2835f2f6bb67f26ad58634f04ac2d8eae00526b0fa55/langchain_text_splitters-0.3.11.tar.gz", hash = "sha256:7a50a04ada9a133bbabb80731df7f6ddac51bc9f1b9cab7fa09304d71d38a6cc", size = 46458, upload-time = "2025-08-31T23:02:58.316Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/58/0d/41a51b40d24ff0384ec4f7ab8dd3dcea8353c05c973836b5e289f1465d4f/langchain_text_splitters-0.3.11-py3-none-any.whl", hash = "sha256:cf079131166a487f1372c8ab5d0bfaa6c0a4291733d9c43a34a16ac9bcd6a393", size = 33845, upload-time = "2025-08-31T23:02:57.195Z" }, -] - -[[package]] -name = "langgraph" -version = "0.6.11" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "langgraph-checkpoint" }, - { name = "langgraph-prebuilt" }, - { name = "langgraph-sdk" }, - { name = "pydantic" }, - { name = "xxhash" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/87/4d/8dfe5e0f9c69655dfb1f450922699ab683b3abbc038cfe38f769eaf871c2/langgraph-0.6.11.tar.gz", hash = "sha256:cd5373d0a59701ab39c9f8af33a33c5704553de815318387fa7f240511e0efd7", size = 492075, upload-time = "2025-10-21T00:04:14.608Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/df/94/430f0341c5c2fe3e3b9f5ab2622f35e2bda12c4a7d655c519468e853d1b0/langgraph-0.6.11-py3-none-any.whl", hash = "sha256:49268de69d85b7db3da9e2ca582a474516421c1c44be5cff390416cfa6967faa", size = 155424, upload-time = "2025-10-21T00:04:12.89Z" }, -] - -[[package]] -name = "langgraph-checkpoint" -version = "3.0.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "ormsgpack" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/0f/07/2b1c042fa87d40cf2db5ca27dc4e8dd86f9a0436a10aa4361a8982718ae7/langgraph_checkpoint-3.0.1.tar.gz", hash = "sha256:59222f875f85186a22c494aedc65c4e985a3df27e696e5016ba0b98a5ed2cee0", size = 137785, upload-time = "2025-11-04T21:55:47.774Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/48/e3/616e3a7ff737d98c1bbb5700dd62278914e2a9ded09a79a1fa93cf24ce12/langgraph_checkpoint-3.0.1-py3-none-any.whl", hash = "sha256:9b04a8d0edc0474ce4eaf30c5d731cee38f11ddff50a6177eead95b5c4e4220b", size = 46249, upload-time = "2025-11-04T21:55:46.472Z" }, -] - -[[package]] -name = "langgraph-prebuilt" -version = "0.6.5" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "langgraph-checkpoint" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/98/6a/76ed0f0d740b187ac2014beae929658881b8d18291bd107571aae5515b12/langgraph_prebuilt-0.6.5.tar.gz", hash = "sha256:9c63e9e867e62b345805fd1e8ea5c2df5cc112e939d714f277af84f2afe5950d", size = 125791, upload-time = "2025-10-21T00:14:50.431Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/8e/d1/e4727f4822943befc3b7046f79049b1086c9493a34b4d44a1adf78577693/langgraph_prebuilt-0.6.5-py3-none-any.whl", hash = "sha256:b6ceb5db31c16a30a3ee3c0b923667f02e7c9e27852621abf9d5bd5603534141", size = 28158, upload-time = "2025-10-21T00:14:49.192Z" }, -] - -[[package]] -name = "langgraph-sdk" -version = "0.2.15" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "httpx" }, - { name = "orjson" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/71/46/a0bc5914e4a418ad5e8558b19bccd6f0baf56d0c674d6d65a0acf4f22590/langgraph_sdk-0.2.15.tar.gz", hash = "sha256:8faaafe2c1193b89f782dd66c591060cd67862aa6aaf283749b7846f331d5334", size = 130343, upload-time = "2025-12-09T19:26:40.097Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/6b/c9/bf2bff18f85bb7973fa5280838580049574bd7649c36e3dd346c49304997/langgraph_sdk-0.2.15-py3-none-any.whl", hash = "sha256:746566a5d89aa47160eccc17d71682a78771c754126f6c235a68353d61ed7462", size = 66483, upload-time = "2025-12-09T19:26:39.198Z" }, -] - -[[package]] -name = "langsmith" -version = "0.6.8" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "httpx" }, - { name = "orjson", marker = "platform_python_implementation != 'PyPy'" }, - { name = "packaging" }, - { name = "pydantic" }, - { name = "requests" }, - { name = "requests-toolbelt" }, - { name = "uuid-utils" }, - { name = "xxhash" }, - { name = "zstandard" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/8e/15/35f49a0b2efd33002fdcb9a7b0bdb65d77e40b4739104ffe843a3479874a/langsmith-0.6.8.tar.gz", hash = "sha256:3a7eb7155f2839dc729a5aa5b0bfc4aa1cb617b09a2290cf77031041271a7cdf", size = 973475, upload-time = "2026-02-02T23:20:02.208Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/cd/2d/2389e65522ebeab17489df72b4fabcfc661fced8af178aa6c2bc3b9afff5/langsmith-0.6.8-py3-none-any.whl", hash = "sha256:d17da18aeef15fdb4c3baec348bad64056591d785629cd5ba4846fd93cab166b", size = 319165, upload-time = "2026-02-02T23:20:00.456Z" }, -] - -[[package]] -name = "openai" -version = "2.16.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "distro" }, - { name = "httpx" }, - { name = "jiter" }, - { name = "pydantic" }, - { name = "sniffio" }, - { name = "tqdm" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/b1/6c/e4c964fcf1d527fdf4739e7cc940c60075a4114d50d03871d5d5b1e13a88/openai-2.16.0.tar.gz", hash = "sha256:42eaa22ca0d8ded4367a77374104d7a2feafee5bd60a107c3c11b5243a11cd12", size = 629649, upload-time = "2026-01-27T23:28:02.579Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/16/83/0315bf2cfd75a2ce8a7e54188e9456c60cec6c0cf66728ed07bd9859ff26/openai-2.16.0-py3-none-any.whl", hash = "sha256:5f46643a8f42899a84e80c38838135d7038e7718333ce61396994f887b09a59b", size = 1068612, upload-time = "2026-01-27T23:28:00.356Z" }, -] - -[[package]] -name = "orjson" -version = "3.11.7" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/53/45/b268004f745ede84e5798b48ee12b05129d19235d0e15267aa57dcdb400b/orjson-3.11.7.tar.gz", hash = "sha256:9b1a67243945819ce55d24a30b59d6a168e86220452d2c96f4d1f093e71c0c49", size = 6144992, upload-time = "2026-02-02T15:38:49.29Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/37/02/da6cb01fc6087048d7f61522c327edf4250f1683a58a839fdcc435746dd5/orjson-3.11.7-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:9487abc2c2086e7c8eb9a211d2ce8855bae0e92586279d0d27b341d5ad76c85c", size = 228664, upload-time = "2026-02-02T15:37:25.542Z" }, - { url = "https://files.pythonhosted.org/packages/c1/c2/5885e7a5881dba9a9af51bc564e8967225a642b3e03d089289a35054e749/orjson-3.11.7-cp311-cp311-macosx_15_0_arm64.whl", hash = "sha256:79cacb0b52f6004caf92405a7e1f11e6e2de8bdf9019e4f76b44ba045125cd6b", size = 125344, upload-time = "2026-02-02T15:37:26.92Z" }, - { url = "https://files.pythonhosted.org/packages/a4/1d/4e7688de0a92d1caf600dfd5fb70b4c5bfff51dfa61ac555072ef2d0d32a/orjson-3.11.7-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c2e85fe4698b6a56d5e2ebf7ae87544d668eb6bde1ad1226c13f44663f20ec9e", size = 128404, upload-time = "2026-02-02T15:37:28.108Z" }, - { url = "https://files.pythonhosted.org/packages/2f/b2/ec04b74ae03a125db7bd69cffd014b227b7f341e3261bf75b5eb88a1aa92/orjson-3.11.7-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b8d14b71c0b12963fe8a62aac87119f1afdf4cb88a400f61ca5ae581449efcb5", size = 123677, upload-time = "2026-02-02T15:37:30.287Z" }, - { url = "https://files.pythonhosted.org/packages/4c/69/f95bdf960605f08f827f6e3291fe243d8aa9c5c9ff017a8d7232209184c3/orjson-3.11.7-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:91c81ef070c8f3220054115e1ef468b1c9ce8497b4e526cb9f68ab4dc0a7ac62", size = 128950, upload-time = "2026-02-02T15:37:31.595Z" }, - { url = "https://files.pythonhosted.org/packages/a4/1b/de59c57bae1d148ef298852abd31909ac3089cff370dfd4cd84cc99cbc42/orjson-3.11.7-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:411ebaf34d735e25e358a6d9e7978954a9c9d58cfb47bc6683cdc3964cd2f910", size = 141756, upload-time = "2026-02-02T15:37:32.985Z" }, - { url = "https://files.pythonhosted.org/packages/ee/9e/9decc59f4499f695f65c650f6cfa6cd4c37a3fbe8fa235a0a3614cb54386/orjson-3.11.7-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a16bcd08ab0bcdfc7e8801d9c4a9cc17e58418e4d48ddc6ded4e9e4b1a94062b", size = 130812, upload-time = "2026-02-02T15:37:34.204Z" }, - { url = "https://files.pythonhosted.org/packages/28/e6/59f932bcabd1eac44e334fe8e3281a92eacfcb450586e1f4bde0423728d8/orjson-3.11.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9c0b51672e466fd7e56230ffbae7f1639e18d0ce023351fb75da21b71bc2c960", size = 133444, upload-time = "2026-02-02T15:37:35.446Z" }, - { url = "https://files.pythonhosted.org/packages/f1/36/b0f05c0eaa7ca30bc965e37e6a2956b0d67adb87a9872942d3568da846ae/orjson-3.11.7-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:136dcd6a2e796dfd9ffca9fc027d778567b0b7c9968d092842d3c323cef88aa8", size = 138609, upload-time = "2026-02-02T15:37:36.657Z" }, - { url = "https://files.pythonhosted.org/packages/b8/03/58ec7d302b8d86944c60c7b4b82975d5161fcce4c9bc8c6cb1d6741b6115/orjson-3.11.7-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:7ba61079379b0ae29e117db13bda5f28d939766e410d321ec1624afc6a0b0504", size = 408918, upload-time = "2026-02-02T15:37:38.076Z" }, - { url = "https://files.pythonhosted.org/packages/06/3a/868d65ef9a8b99be723bd510de491349618abd9f62c826cf206d962db295/orjson-3.11.7-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:0527a4510c300e3b406591b0ba69b5dc50031895b0a93743526a3fc45f59d26e", size = 143998, upload-time = "2026-02-02T15:37:39.706Z" }, - { url = "https://files.pythonhosted.org/packages/5b/c7/1e18e1c83afe3349f4f6dc9e14910f0ae5f82eac756d1412ea4018938535/orjson-3.11.7-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:a709e881723c9b18acddcfb8ba357322491ad553e277cf467e1e7e20e2d90561", size = 134802, upload-time = "2026-02-02T15:37:41.002Z" }, - { url = "https://files.pythonhosted.org/packages/d4/0b/ccb7ee1a65b37e8eeb8b267dc953561d72370e85185e459616d4345bab34/orjson-3.11.7-cp311-cp311-win32.whl", hash = "sha256:c43b8b5bab288b6b90dac410cca7e986a4fa747a2e8f94615aea407da706980d", size = 127828, upload-time = "2026-02-02T15:37:42.241Z" }, - { url = "https://files.pythonhosted.org/packages/af/9e/55c776dffda3f381e0f07d010a4f5f3902bf48eaba1bb7684d301acd4924/orjson-3.11.7-cp311-cp311-win_amd64.whl", hash = "sha256:6543001328aa857187f905308a028935864aefe9968af3848401b6fe80dbb471", size = 124941, upload-time = "2026-02-02T15:37:43.444Z" }, - { url = "https://files.pythonhosted.org/packages/aa/8e/424a620fa7d263b880162505fb107ef5e0afaa765b5b06a88312ac291560/orjson-3.11.7-cp311-cp311-win_arm64.whl", hash = "sha256:1ee5cc7160a821dfe14f130bc8e63e7611051f964b463d9e2a3a573204446a4d", size = 126245, upload-time = "2026-02-02T15:37:45.18Z" }, - { url = "https://files.pythonhosted.org/packages/80/bf/76f4f1665f6983385938f0e2a5d7efa12a58171b8456c252f3bae8a4cf75/orjson-3.11.7-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:bd03ea7606833655048dab1a00734a2875e3e86c276e1d772b2a02556f0d895f", size = 228545, upload-time = "2026-02-02T15:37:46.376Z" }, - { url = "https://files.pythonhosted.org/packages/79/53/6c72c002cb13b5a978a068add59b25a8bdf2800ac1c9c8ecdb26d6d97064/orjson-3.11.7-cp312-cp312-macosx_15_0_arm64.whl", hash = "sha256:89e440ebc74ce8ab5c7bc4ce6757b4a6b1041becb127df818f6997b5c71aa60b", size = 125224, upload-time = "2026-02-02T15:37:47.697Z" }, - { url = "https://files.pythonhosted.org/packages/2c/83/10e48852865e5dd151bdfe652c06f7da484578ed02c5fca938e3632cb0b8/orjson-3.11.7-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5ede977b5fe5ac91b1dffc0a517ca4542d2ec8a6a4ff7b2652d94f640796342a", size = 128154, upload-time = "2026-02-02T15:37:48.954Z" }, - { url = "https://files.pythonhosted.org/packages/6e/52/a66e22a2b9abaa374b4a081d410edab6d1e30024707b87eab7c734afe28d/orjson-3.11.7-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b7b1dae39230a393df353827c855a5f176271c23434cfd2db74e0e424e693e10", size = 123548, upload-time = "2026-02-02T15:37:50.187Z" }, - { url = "https://files.pythonhosted.org/packages/de/38/605d371417021359f4910c496f764c48ceb8997605f8c25bf1dfe58c0ebe/orjson-3.11.7-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ed46f17096e28fb28d2975834836a639af7278aa87c84f68ab08fbe5b8bd75fa", size = 129000, upload-time = "2026-02-02T15:37:51.426Z" }, - { url = "https://files.pythonhosted.org/packages/44/98/af32e842b0ffd2335c89714d48ca4e3917b42f5d6ee5537832e069a4b3ac/orjson-3.11.7-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3726be79e36e526e3d9c1aceaadbfb4a04ee80a72ab47b3f3c17fefb9812e7b8", size = 141686, upload-time = "2026-02-02T15:37:52.607Z" }, - { url = "https://files.pythonhosted.org/packages/96/0b/fc793858dfa54be6feee940c1463370ece34b3c39c1ca0aa3845f5ba9892/orjson-3.11.7-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0724e265bc548af1dedebd9cb3d24b4e1c1e685a343be43e87ba922a5c5fff2f", size = 130812, upload-time = "2026-02-02T15:37:53.944Z" }, - { url = "https://files.pythonhosted.org/packages/dc/91/98a52415059db3f374757d0b7f0f16e3b5cd5976c90d1c2b56acaea039e6/orjson-3.11.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e7745312efa9e11c17fbd3cb3097262d079da26930ae9ae7ba28fb738367cbad", size = 133440, upload-time = "2026-02-02T15:37:55.615Z" }, - { url = "https://files.pythonhosted.org/packages/dc/b6/cb540117bda61791f46381f8c26c8f93e802892830a6055748d3bb1925ab/orjson-3.11.7-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f904c24bdeabd4298f7a977ef14ca2a022ca921ed670b92ecd16ab6f3d01f867", size = 138386, upload-time = "2026-02-02T15:37:56.814Z" }, - { url = "https://files.pythonhosted.org/packages/63/1a/50a3201c334a7f17c231eee5f841342190723794e3b06293f26e7cf87d31/orjson-3.11.7-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:b9fc4d0f81f394689e0814617aadc4f2ea0e8025f38c226cbf22d3b5ddbf025d", size = 408853, upload-time = "2026-02-02T15:37:58.291Z" }, - { url = "https://files.pythonhosted.org/packages/87/cd/8de1c67d0be44fdc22701e5989c0d015a2adf391498ad42c4dc589cd3013/orjson-3.11.7-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:849e38203e5be40b776ed2718e587faf204d184fc9a008ae441f9442320c0cab", size = 144130, upload-time = "2026-02-02T15:38:00.163Z" }, - { url = "https://files.pythonhosted.org/packages/0f/fe/d605d700c35dd55f51710d159fc54516a280923cd1b7e47508982fbb387d/orjson-3.11.7-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:4682d1db3bcebd2b64757e0ddf9e87ae5f00d29d16c5cdf3a62f561d08cc3dd2", size = 134818, upload-time = "2026-02-02T15:38:01.507Z" }, - { url = "https://files.pythonhosted.org/packages/e4/e4/15ecc67edb3ddb3e2f46ae04475f2d294e8b60c1825fbe28a428b93b3fbd/orjson-3.11.7-cp312-cp312-win32.whl", hash = "sha256:f4f7c956b5215d949a1f65334cf9d7612dde38f20a95f2315deef167def91a6f", size = 127923, upload-time = "2026-02-02T15:38:02.75Z" }, - { url = "https://files.pythonhosted.org/packages/34/70/2e0855361f76198a3965273048c8e50a9695d88cd75811a5b46444895845/orjson-3.11.7-cp312-cp312-win_amd64.whl", hash = "sha256:bf742e149121dc5648ba0a08ea0871e87b660467ef168a3a5e53bc1fbd64bb74", size = 125007, upload-time = "2026-02-02T15:38:04.032Z" }, - { url = "https://files.pythonhosted.org/packages/68/40/c2051bd19fc467610fed469dc29e43ac65891571138f476834ca192bc290/orjson-3.11.7-cp312-cp312-win_arm64.whl", hash = "sha256:26c3b9132f783b7d7903bf1efb095fed8d4a3a85ec0d334ee8beff3d7a4749d5", size = 126089, upload-time = "2026-02-02T15:38:05.297Z" }, - { url = "https://files.pythonhosted.org/packages/89/25/6e0e52cac5aab51d7b6dcd257e855e1dec1c2060f6b28566c509b4665f62/orjson-3.11.7-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:1d98b30cc1313d52d4af17d9c3d307b08389752ec5f2e5febdfada70b0f8c733", size = 228390, upload-time = "2026-02-02T15:38:06.8Z" }, - { url = "https://files.pythonhosted.org/packages/a5/29/a77f48d2fc8a05bbc529e5ff481fb43d914f9e383ea2469d4f3d51df3d00/orjson-3.11.7-cp313-cp313-macosx_15_0_arm64.whl", hash = "sha256:d897e81f8d0cbd2abb82226d1860ad2e1ab3ff16d7b08c96ca00df9d45409ef4", size = 125189, upload-time = "2026-02-02T15:38:08.181Z" }, - { url = "https://files.pythonhosted.org/packages/89/25/0a16e0729a0e6a1504f9d1a13cdd365f030068aab64cec6958396b9969d7/orjson-3.11.7-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:814be4b49b228cfc0b3c565acf642dd7d13538f966e3ccde61f4f55be3e20785", size = 128106, upload-time = "2026-02-02T15:38:09.41Z" }, - { url = "https://files.pythonhosted.org/packages/66/da/a2e505469d60666a05ab373f1a6322eb671cb2ba3a0ccfc7d4bc97196787/orjson-3.11.7-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:d06e5c5fed5caedd2e540d62e5b1c25e8c82431b9e577c33537e5fa4aa909539", size = 123363, upload-time = "2026-02-02T15:38:10.73Z" }, - { url = "https://files.pythonhosted.org/packages/23/bf/ed73f88396ea35c71b38961734ea4a4746f7ca0768bf28fd551d37e48dd0/orjson-3.11.7-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:31c80ce534ac4ea3739c5ee751270646cbc46e45aea7576a38ffec040b4029a1", size = 129007, upload-time = "2026-02-02T15:38:12.138Z" }, - { url = "https://files.pythonhosted.org/packages/73/3c/b05d80716f0225fc9008fbf8ab22841dcc268a626aa550561743714ce3bf/orjson-3.11.7-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f50979824bde13d32b4320eedd513431c921102796d86be3eee0b58e58a3ecd1", size = 141667, upload-time = "2026-02-02T15:38:13.398Z" }, - { url = "https://files.pythonhosted.org/packages/61/e8/0be9b0addd9bf86abfc938e97441dcd0375d494594b1c8ad10fe57479617/orjson-3.11.7-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9e54f3808e2b6b945078c41aa8d9b5834b28c50843846e97807e5adb75fa9705", size = 130832, upload-time = "2026-02-02T15:38:14.698Z" }, - { url = "https://files.pythonhosted.org/packages/c9/ec/c68e3b9021a31d9ec15a94931db1410136af862955854ed5dd7e7e4f5bff/orjson-3.11.7-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a12b80df61aab7b98b490fe9e4879925ba666fccdfcd175252ce4d9035865ace", size = 133373, upload-time = "2026-02-02T15:38:16.109Z" }, - { url = "https://files.pythonhosted.org/packages/d2/45/f3466739aaafa570cc8e77c6dbb853c48bf56e3b43738020e2661e08b0ac/orjson-3.11.7-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:996b65230271f1a97026fd0e6a753f51fbc0c335d2ad0c6201f711b0da32693b", size = 138307, upload-time = "2026-02-02T15:38:17.453Z" }, - { url = "https://files.pythonhosted.org/packages/e1/84/9f7f02288da1ffb31405c1be07657afd1eecbcb4b64ee2817b6fe0f785fa/orjson-3.11.7-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:ab49d4b2a6a1d415ddb9f37a21e02e0d5dbfe10b7870b21bf779fc21e9156157", size = 408695, upload-time = "2026-02-02T15:38:18.831Z" }, - { url = "https://files.pythonhosted.org/packages/18/07/9dd2f0c0104f1a0295ffbe912bc8d63307a539b900dd9e2c48ef7810d971/orjson-3.11.7-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:390a1dce0c055ddf8adb6aa94a73b45a4a7d7177b5c584b8d1c1947f2ba60fb3", size = 144099, upload-time = "2026-02-02T15:38:20.28Z" }, - { url = "https://files.pythonhosted.org/packages/a5/66/857a8e4a3292e1f7b1b202883bcdeb43a91566cf59a93f97c53b44bd6801/orjson-3.11.7-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:1eb80451a9c351a71dfaf5b7ccc13ad065405217726b59fdbeadbcc544f9d223", size = 134806, upload-time = "2026-02-02T15:38:22.186Z" }, - { url = "https://files.pythonhosted.org/packages/0a/5b/6ebcf3defc1aab3a338ca777214966851e92efb1f30dc7fc8285216e6d1b/orjson-3.11.7-cp313-cp313-win32.whl", hash = "sha256:7477aa6a6ec6139c5cb1cc7b214643592169a5494d200397c7fc95d740d5fcf3", size = 127914, upload-time = "2026-02-02T15:38:23.511Z" }, - { url = "https://files.pythonhosted.org/packages/00/04/c6f72daca5092e3117840a1b1e88dfc809cc1470cf0734890d0366b684a1/orjson-3.11.7-cp313-cp313-win_amd64.whl", hash = "sha256:b9f95dcdea9d4f805daa9ddf02617a89e484c6985fa03055459f90e87d7a0757", size = 124986, upload-time = "2026-02-02T15:38:24.836Z" }, - { url = "https://files.pythonhosted.org/packages/03/ba/077a0f6f1085d6b806937246860fafbd5b17f3919c70ee3f3d8d9c713f38/orjson-3.11.7-cp313-cp313-win_arm64.whl", hash = "sha256:800988273a014a0541483dc81021247d7eacb0c845a9d1a34a422bc718f41539", size = 126045, upload-time = "2026-02-02T15:38:26.216Z" }, - { url = "https://files.pythonhosted.org/packages/e9/1e/745565dca749813db9a093c5ebc4bac1a9475c64d54b95654336ac3ed961/orjson-3.11.7-cp314-cp314-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:de0a37f21d0d364954ad5de1970491d7fbd0fb1ef7417d4d56a36dc01ba0c0a0", size = 228391, upload-time = "2026-02-02T15:38:27.757Z" }, - { url = "https://files.pythonhosted.org/packages/46/19/e40f6225da4d3aa0c8dc6e5219c5e87c2063a560fe0d72a88deb59776794/orjson-3.11.7-cp314-cp314-macosx_15_0_arm64.whl", hash = "sha256:c2428d358d85e8da9d37cba18b8c4047c55222007a84f97156a5b22028dfbfc0", size = 125188, upload-time = "2026-02-02T15:38:29.241Z" }, - { url = "https://files.pythonhosted.org/packages/9d/7e/c4de2babef2c0817fd1f048fd176aa48c37bec8aef53d2fa932983032cce/orjson-3.11.7-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3c4bc6c6ac52cdaa267552544c73e486fecbd710b7ac09bc024d5a78555a22f6", size = 128097, upload-time = "2026-02-02T15:38:30.618Z" }, - { url = "https://files.pythonhosted.org/packages/eb/74/233d360632bafd2197f217eee7fb9c9d0229eac0c18128aee5b35b0014fe/orjson-3.11.7-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bd0d68edd7dfca1b2eca9361a44ac9f24b078de3481003159929a0573f21a6bf", size = 123364, upload-time = "2026-02-02T15:38:32.363Z" }, - { url = "https://files.pythonhosted.org/packages/79/51/af79504981dd31efe20a9e360eb49c15f06df2b40e7f25a0a52d9ae888e8/orjson-3.11.7-cp314-cp314-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:623ad1b9548ef63886319c16fa317848e465a21513b31a6ad7b57443c3e0dcf5", size = 129076, upload-time = "2026-02-02T15:38:33.68Z" }, - { url = "https://files.pythonhosted.org/packages/67/e2/da898eb68b72304f8de05ca6715870d09d603ee98d30a27e8a9629abc64b/orjson-3.11.7-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6e776b998ac37c0396093d10290e60283f59cfe0fc3fccbd0ccc4bd04dd19892", size = 141705, upload-time = "2026-02-02T15:38:34.989Z" }, - { url = "https://files.pythonhosted.org/packages/c5/89/15364d92acb3d903b029e28d834edb8780c2b97404cbf7929aa6b9abdb24/orjson-3.11.7-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:652c6c3af76716f4a9c290371ba2e390ede06f6603edb277b481daf37f6f464e", size = 130855, upload-time = "2026-02-02T15:38:36.379Z" }, - { url = "https://files.pythonhosted.org/packages/c2/8b/ecdad52d0b38d4b8f514be603e69ccd5eacf4e7241f972e37e79792212ec/orjson-3.11.7-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a56df3239294ea5964adf074c54bcc4f0ccd21636049a2cf3ca9cf03b5d03cf1", size = 133386, upload-time = "2026-02-02T15:38:37.704Z" }, - { url = "https://files.pythonhosted.org/packages/b9/0e/45e1dcf10e17d0924b7c9162f87ec7b4ca79e28a0548acf6a71788d3e108/orjson-3.11.7-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:bda117c4148e81f746655d5a3239ae9bd00cb7bc3ca178b5fc5a5997e9744183", size = 138295, upload-time = "2026-02-02T15:38:39.096Z" }, - { url = "https://files.pythonhosted.org/packages/63/d7/4d2e8b03561257af0450f2845b91fbd111d7e526ccdf737267108075e0ba/orjson-3.11.7-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:23d6c20517a97a9daf1d48b580fcdc6f0516c6f4b5038823426033690b4d2650", size = 408720, upload-time = "2026-02-02T15:38:40.634Z" }, - { url = "https://files.pythonhosted.org/packages/78/cf/d45343518282108b29c12a65892445fc51f9319dc3c552ceb51bb5905ed2/orjson-3.11.7-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:8ff206156006da5b847c9304b6308a01e8cdbc8cce824e2779a5ba71c3def141", size = 144152, upload-time = "2026-02-02T15:38:42.262Z" }, - { url = "https://files.pythonhosted.org/packages/a9/3a/d6001f51a7275aacd342e77b735c71fa04125a3f93c36fee4526bc8c654e/orjson-3.11.7-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:962d046ee1765f74a1da723f4b33e3b228fe3a48bd307acce5021dfefe0e29b2", size = 134814, upload-time = "2026-02-02T15:38:43.627Z" }, - { url = "https://files.pythonhosted.org/packages/1d/d3/f19b47ce16820cc2c480f7f1723e17f6d411b3a295c60c8ad3aa9ff1c96a/orjson-3.11.7-cp314-cp314-win32.whl", hash = "sha256:89e13dd3f89f1c38a9c9eba5fbf7cdc2d1feca82f5f290864b4b7a6aac704576", size = 127997, upload-time = "2026-02-02T15:38:45.06Z" }, - { url = "https://files.pythonhosted.org/packages/12/df/172771902943af54bf661a8d102bdf2e7f932127968080632bda6054b62c/orjson-3.11.7-cp314-cp314-win_amd64.whl", hash = "sha256:845c3e0d8ded9c9271cd79596b9b552448b885b97110f628fb687aee2eed11c1", size = 124985, upload-time = "2026-02-02T15:38:46.388Z" }, - { url = "https://files.pythonhosted.org/packages/6f/1c/f2a8d8a1b17514660a614ce5f7aac74b934e69f5abc2700cc7ced882a009/orjson-3.11.7-cp314-cp314-win_arm64.whl", hash = "sha256:4a2e9c5be347b937a2e0203866f12bba36082e89b402ddb9e927d5822e43088d", size = 126038, upload-time = "2026-02-02T15:38:47.703Z" }, -] - -[[package]] -name = "ormsgpack" -version = "1.12.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/12/0c/f1761e21486942ab9bb6feaebc610fa074f7c5e496e6962dea5873348077/ormsgpack-1.12.2.tar.gz", hash = "sha256:944a2233640273bee67521795a73cf1e959538e0dfb7ac635505010455e53b33", size = 39031, upload-time = "2026-01-18T20:55:28.023Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/4b/08/8b68f24b18e69d92238aa8f258218e6dfeacf4381d9d07ab8df303f524a9/ormsgpack-1.12.2-cp311-cp311-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:bd5f4bf04c37888e864f08e740c5a573c4017f6fd6e99fa944c5c935fabf2dd9", size = 378266, upload-time = "2026-01-18T20:55:59.876Z" }, - { url = "https://files.pythonhosted.org/packages/0d/24/29fc13044ecb7c153523ae0a1972269fcd613650d1fa1a9cec1044c6b666/ormsgpack-1.12.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:34d5b28b3570e9fed9a5a76528fc7230c3c76333bc214798958e58e9b79cc18a", size = 203035, upload-time = "2026-01-18T20:55:30.59Z" }, - { url = "https://files.pythonhosted.org/packages/ad/c2/00169fb25dd8f9213f5e8a549dfb73e4d592009ebc85fbbcd3e1dcac575b/ormsgpack-1.12.2-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:3708693412c28f3538fb5a65da93787b6bbab3484f6bc6e935bfb77a62400ae5", size = 210539, upload-time = "2026-01-18T20:55:48.569Z" }, - { url = "https://files.pythonhosted.org/packages/1b/33/543627f323ff3c73091f51d6a20db28a1a33531af30873ea90c5ac95a9b5/ormsgpack-1.12.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:43013a3f3e2e902e1d05e72c0f1aeb5bedbb8e09240b51e26792a3c89267e181", size = 212401, upload-time = "2026-01-18T20:56:10.101Z" }, - { url = "https://files.pythonhosted.org/packages/e8/5d/f70e2c3da414f46186659d24745483757bcc9adccb481a6eb93e2b729301/ormsgpack-1.12.2-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:7c8b1667a72cbba74f0ae7ecf3105a5e01304620ed14528b2cb4320679d2869b", size = 387082, upload-time = "2026-01-18T20:56:12.047Z" }, - { url = "https://files.pythonhosted.org/packages/c0/d6/06e8dc920c7903e051f30934d874d4afccc9bb1c09dcaf0bc03a7de4b343/ormsgpack-1.12.2-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:df6961442140193e517303d0b5d7bc2e20e69a879c2d774316125350c4a76b92", size = 482346, upload-time = "2026-01-18T20:56:05.152Z" }, - { url = "https://files.pythonhosted.org/packages/66/c4/f337ac0905eed9c393ef990c54565cd33644918e0a8031fe48c098c71dbf/ormsgpack-1.12.2-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:c6a4c34ddef109647c769d69be65fa1de7a6022b02ad45546a69b3216573eb4a", size = 425181, upload-time = "2026-01-18T20:55:37.83Z" }, - { url = "https://files.pythonhosted.org/packages/78/29/6d5758fabef3babdf4bbbc453738cc7de9cd3334e4c38dd5737e27b85653/ormsgpack-1.12.2-cp311-cp311-win_amd64.whl", hash = "sha256:73670ed0375ecc303858e3613f407628dd1fca18fe6ac57b7b7ce66cc7bb006c", size = 117182, upload-time = "2026-01-18T20:55:31.472Z" }, - { url = "https://files.pythonhosted.org/packages/c4/57/17a15549233c37e7fd054c48fe9207492e06b026dbd872b826a0b5f833b6/ormsgpack-1.12.2-cp311-cp311-win_arm64.whl", hash = "sha256:c2be829954434e33601ae5da328cccce3266b098927ca7a30246a0baec2ce7bd", size = 111464, upload-time = "2026-01-18T20:55:38.811Z" }, - { url = "https://files.pythonhosted.org/packages/4c/36/16c4b1921c308a92cef3bf6663226ae283395aa0ff6e154f925c32e91ff5/ormsgpack-1.12.2-cp312-cp312-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:7a29d09b64b9694b588ff2f80e9826bdceb3a2b91523c5beae1fab27d5c940e7", size = 378618, upload-time = "2026-01-18T20:55:50.835Z" }, - { url = "https://files.pythonhosted.org/packages/c0/68/468de634079615abf66ed13bb5c34ff71da237213f29294363beeeca5306/ormsgpack-1.12.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b39e629fd2e1c5b2f46f99778450b59454d1f901bc507963168985e79f09c5d", size = 203186, upload-time = "2026-01-18T20:56:11.163Z" }, - { url = "https://files.pythonhosted.org/packages/73/a9/d756e01961442688b7939bacd87ce13bfad7d26ce24f910f6028178b2cc8/ormsgpack-1.12.2-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:958dcb270d30a7cb633a45ee62b9444433fa571a752d2ca484efdac07480876e", size = 210738, upload-time = "2026-01-18T20:56:09.181Z" }, - { url = "https://files.pythonhosted.org/packages/7b/ba/795b1036888542c9113269a3f5690ab53dd2258c6fb17676ac4bd44fcf94/ormsgpack-1.12.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58d379d72b6c5e964851c77cfedfb386e474adee4fd39791c2c5d9efb53505cc", size = 212569, upload-time = "2026-01-18T20:56:06.135Z" }, - { url = "https://files.pythonhosted.org/packages/6c/aa/bff73c57497b9e0cba8837c7e4bcab584b1a6dbc91a5dd5526784a5030c8/ormsgpack-1.12.2-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8463a3fc5f09832e67bdb0e2fda6d518dc4281b133166146a67f54c08496442e", size = 387166, upload-time = "2026-01-18T20:55:36.738Z" }, - { url = "https://files.pythonhosted.org/packages/d3/cf/f8283cba44bcb7b14f97b6274d449db276b3a86589bdb363169b51bc12de/ormsgpack-1.12.2-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:eddffb77eff0bad4e67547d67a130604e7e2dfbb7b0cde0796045be4090f35c6", size = 482498, upload-time = "2026-01-18T20:55:29.626Z" }, - { url = "https://files.pythonhosted.org/packages/05/be/71e37b852d723dfcbe952ad04178c030df60d6b78eba26bfd14c9a40575e/ormsgpack-1.12.2-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:fcd55e5f6ba0dbce624942adf9f152062135f991a0126064889f68eb850de0dd", size = 425518, upload-time = "2026-01-18T20:55:49.556Z" }, - { url = "https://files.pythonhosted.org/packages/7a/0c/9803aa883d18c7ef197213cd2cbf73ba76472a11fe100fb7dab2884edf48/ormsgpack-1.12.2-cp312-cp312-win_amd64.whl", hash = "sha256:d024b40828f1dde5654faebd0d824f9cc29ad46891f626272dd5bfd7af2333a4", size = 117462, upload-time = "2026-01-18T20:55:47.726Z" }, - { url = "https://files.pythonhosted.org/packages/c8/9e/029e898298b2cc662f10d7a15652a53e3b525b1e7f07e21fef8536a09bb8/ormsgpack-1.12.2-cp312-cp312-win_arm64.whl", hash = "sha256:da538c542bac7d1c8f3f2a937863dba36f013108ce63e55745941dda4b75dbb6", size = 111559, upload-time = "2026-01-18T20:55:54.273Z" }, - { url = "https://files.pythonhosted.org/packages/eb/29/bb0eba3288c0449efbb013e9c6f58aea79cf5cb9ee1921f8865f04c1a9d7/ormsgpack-1.12.2-cp313-cp313-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:5ea60cb5f210b1cfbad8c002948d73447508e629ec375acb82910e3efa8ff355", size = 378661, upload-time = "2026-01-18T20:55:57.765Z" }, - { url = "https://files.pythonhosted.org/packages/6e/31/5efa31346affdac489acade2926989e019e8ca98129658a183e3add7af5e/ormsgpack-1.12.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f3601f19afdbea273ed70b06495e5794606a8b690a568d6c996a90d7255e51c1", size = 203194, upload-time = "2026-01-18T20:56:08.252Z" }, - { url = "https://files.pythonhosted.org/packages/eb/56/d0087278beef833187e0167f8527235ebe6f6ffc2a143e9de12a98b1ce87/ormsgpack-1.12.2-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:29a9f17a3dac6054c0dce7925e0f4995c727f7c41859adf9b5572180f640d172", size = 210778, upload-time = "2026-01-18T20:55:17.694Z" }, - { url = "https://files.pythonhosted.org/packages/1c/a2/072343e1413d9443e5a252a8eb591c2d5b1bffbe5e7bfc78c069361b92eb/ormsgpack-1.12.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:39c1bd2092880e413902910388be8715f70b9f15f20779d44e673033a6146f2d", size = 212592, upload-time = "2026-01-18T20:55:32.747Z" }, - { url = "https://files.pythonhosted.org/packages/a2/8b/a0da3b98a91d41187a63b02dda14267eefc2a74fcb43cc2701066cf1510e/ormsgpack-1.12.2-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:50b7249244382209877deedeee838aef1542f3d0fc28b8fe71ca9d7e1896a0d7", size = 387164, upload-time = "2026-01-18T20:55:40.853Z" }, - { url = "https://files.pythonhosted.org/packages/19/bb/6d226bc4cf9fc20d8eb1d976d027a3f7c3491e8f08289a2e76abe96a65f3/ormsgpack-1.12.2-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:5af04800d844451cf102a59c74a841324868d3f1625c296a06cc655c542a6685", size = 482516, upload-time = "2026-01-18T20:55:42.033Z" }, - { url = "https://files.pythonhosted.org/packages/fb/f1/bb2c7223398543dedb3dbf8bb93aaa737b387de61c5feaad6f908841b782/ormsgpack-1.12.2-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:cec70477d4371cd524534cd16472d8b9cc187e0e3043a8790545a9a9b296c258", size = 425539, upload-time = "2026-01-18T20:55:24.727Z" }, - { url = "https://files.pythonhosted.org/packages/7b/e8/0fb45f57a2ada1fed374f7494c8cd55e2f88ccd0ab0a669aa3468716bf5f/ormsgpack-1.12.2-cp313-cp313-win_amd64.whl", hash = "sha256:21f4276caca5c03a818041d637e4019bc84f9d6ca8baa5ea03e5cc8bf56140e9", size = 117459, upload-time = "2026-01-18T20:55:56.876Z" }, - { url = "https://files.pythonhosted.org/packages/7a/d4/0cfeea1e960d550a131001a7f38a5132c7ae3ebde4c82af1f364ccc5d904/ormsgpack-1.12.2-cp313-cp313-win_arm64.whl", hash = "sha256:baca4b6773d20a82e36d6fd25f341064244f9f86a13dead95dd7d7f996f51709", size = 111577, upload-time = "2026-01-18T20:55:43.605Z" }, - { url = "https://files.pythonhosted.org/packages/94/16/24d18851334be09c25e87f74307c84950f18c324a4d3c0b41dabdbf19c29/ormsgpack-1.12.2-cp314-cp314-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:bc68dd5915f4acf66ff2010ee47c8906dc1cf07399b16f4089f8c71733f6e36c", size = 378717, upload-time = "2026-01-18T20:55:26.164Z" }, - { url = "https://files.pythonhosted.org/packages/b5/a2/88b9b56f83adae8032ac6a6fa7f080c65b3baf9b6b64fd3d37bd202991d4/ormsgpack-1.12.2-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:46d084427b4132553940070ad95107266656cb646ea9da4975f85cb1a6676553", size = 203183, upload-time = "2026-01-18T20:55:18.815Z" }, - { url = "https://files.pythonhosted.org/packages/a9/80/43e4555963bf602e5bdc79cbc8debd8b6d5456c00d2504df9775e74b450b/ormsgpack-1.12.2-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:c010da16235806cf1d7bc4c96bf286bfa91c686853395a299b3ddb49499a3e13", size = 210814, upload-time = "2026-01-18T20:55:33.973Z" }, - { url = "https://files.pythonhosted.org/packages/78/e1/7cfbf28de8bca6efe7e525b329c31277d1b64ce08dcba723971c241a9d60/ormsgpack-1.12.2-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:18867233df592c997154ff942a6503df274b5ac1765215bceba7a231bea2745d", size = 212634, upload-time = "2026-01-18T20:55:28.634Z" }, - { url = "https://files.pythonhosted.org/packages/95/f8/30ae5716e88d792a4e879debee195653c26ddd3964c968594ddef0a3cc7e/ormsgpack-1.12.2-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:b009049086ddc6b8f80c76b3955df1aa22a5fbd7673c525cd63bf91f23122ede", size = 387139, upload-time = "2026-01-18T20:56:02.013Z" }, - { url = "https://files.pythonhosted.org/packages/dc/81/aee5b18a3e3a0e52f718b37ab4b8af6fae0d9d6a65103036a90c2a8ffb5d/ormsgpack-1.12.2-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:1dcc17d92b6390d4f18f937cf0b99054824a7815818012ddca925d6e01c2e49e", size = 482578, upload-time = "2026-01-18T20:55:35.117Z" }, - { url = "https://files.pythonhosted.org/packages/bd/17/71c9ba472d5d45f7546317f467a5fc941929cd68fb32796ca3d13dcbaec2/ormsgpack-1.12.2-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:f04b5e896d510b07c0ad733d7fce2d44b260c5e6c402d272128f8941984e4285", size = 425539, upload-time = "2026-01-18T20:56:04.009Z" }, - { url = "https://files.pythonhosted.org/packages/2e/a6/ac99cd7fe77e822fed5250ff4b86fa66dd4238937dd178d2299f10b69816/ormsgpack-1.12.2-cp314-cp314-win_amd64.whl", hash = "sha256:ae3aba7eed4ca7cb79fd3436eddd29140f17ea254b91604aa1eb19bfcedb990f", size = 117493, upload-time = "2026-01-18T20:56:07.343Z" }, - { url = "https://files.pythonhosted.org/packages/3a/67/339872846a1ae4592535385a1c1f93614138566d7af094200c9c3b45d1e5/ormsgpack-1.12.2-cp314-cp314-win_arm64.whl", hash = "sha256:118576ea6006893aea811b17429bfc561b4778fad393f5f538c84af70b01260c", size = 111579, upload-time = "2026-01-18T20:55:21.161Z" }, - { url = "https://files.pythonhosted.org/packages/49/c2/6feb972dc87285ad381749d3882d8aecbde9f6ecf908dd717d33d66df095/ormsgpack-1.12.2-cp314-cp314t-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:7121b3d355d3858781dc40dafe25a32ff8a8242b9d80c692fd548a4b1f7fd3c8", size = 378721, upload-time = "2026-01-18T20:55:52.12Z" }, - { url = "https://files.pythonhosted.org/packages/a3/9a/900a6b9b413e0f8a471cf07830f9cf65939af039a362204b36bd5b581d8b/ormsgpack-1.12.2-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4ee766d2e78251b7a63daf1cddfac36a73562d3ddef68cacfb41b2af64698033", size = 203170, upload-time = "2026-01-18T20:55:44.469Z" }, - { url = "https://files.pythonhosted.org/packages/87/4c/27a95466354606b256f24fad464d7c97ab62bce6cc529dd4673e1179b8fb/ormsgpack-1.12.2-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:292410a7d23de9b40444636b9b8f1e4e4b814af7f1ef476e44887e52a123f09d", size = 212816, upload-time = "2026-01-18T20:55:23.501Z" }, - { url = "https://files.pythonhosted.org/packages/73/cd/29cee6007bddf7a834e6cd6f536754c0535fcb939d384f0f37a38b1cddb8/ormsgpack-1.12.2-cp314-cp314t-win_amd64.whl", hash = "sha256:837dd316584485b72ef451d08dd3e96c4a11d12e4963aedb40e08f89685d8ec2", size = 117232, upload-time = "2026-01-18T20:55:45.448Z" }, -] - -[[package]] -name = "packaging" -version = "25.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a1/d4/1fc4078c65507b51b96ca8f8c3ba19e6a61c8253c72794544580a7b6c24d/packaging-25.0.tar.gz", hash = "sha256:d443872c98d677bf60f6a1f2f8c1cb748e8fe762d2bf9d3148b5599295b0fc4f", size = 165727, upload-time = "2025-04-19T11:48:59.673Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/20/12/38679034af332785aac8774540895e234f4d07f7545804097de4b666afd8/packaging-25.0-py3-none-any.whl", hash = "sha256:29572ef2b1f17581046b3a2227d5c611fb25ec70ca1ba8554b24b0e69331a484", size = 66469, upload-time = "2025-04-19T11:48:57.875Z" }, -] - -[[package]] -name = "pydantic" -version = "2.12.5" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "annotated-types" }, - { name = "pydantic-core" }, - { name = "typing-extensions" }, - { name = "typing-inspection" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/69/44/36f1a6e523abc58ae5f928898e4aca2e0ea509b5aa6f6f392a5d882be928/pydantic-2.12.5.tar.gz", hash = "sha256:4d351024c75c0f085a9febbb665ce8c0c6ec5d30e903bdb6394b7ede26aebb49", size = 821591, upload-time = "2025-11-26T15:11:46.471Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/5a/87/b70ad306ebb6f9b585f114d0ac2137d792b48be34d732d60e597c2f8465a/pydantic-2.12.5-py3-none-any.whl", hash = "sha256:e561593fccf61e8a20fc46dfc2dfe075b8be7d0188df33f221ad1f0139180f9d", size = 463580, upload-time = "2025-11-26T15:11:44.605Z" }, -] - -[[package]] -name = "pydantic-core" -version = "2.41.5" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/71/70/23b021c950c2addd24ec408e9ab05d59b035b39d97cdc1130e1bce647bb6/pydantic_core-2.41.5.tar.gz", hash = "sha256:08daa51ea16ad373ffd5e7606252cc32f07bc72b28284b6bc9c6df804816476e", size = 460952, upload-time = "2025-11-04T13:43:49.098Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e8/72/74a989dd9f2084b3d9530b0915fdda64ac48831c30dbf7c72a41a5232db8/pydantic_core-2.41.5-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:a3a52f6156e73e7ccb0f8cced536adccb7042be67cb45f9562e12b319c119da6", size = 2105873, upload-time = "2025-11-04T13:39:31.373Z" }, - { url = "https://files.pythonhosted.org/packages/12/44/37e403fd9455708b3b942949e1d7febc02167662bf1a7da5b78ee1ea2842/pydantic_core-2.41.5-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:7f3bf998340c6d4b0c9a2f02d6a400e51f123b59565d74dc60d252ce888c260b", size = 1899826, upload-time = "2025-11-04T13:39:32.897Z" }, - { url = "https://files.pythonhosted.org/packages/33/7f/1d5cab3ccf44c1935a359d51a8a2a9e1a654b744b5e7f80d41b88d501eec/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:378bec5c66998815d224c9ca994f1e14c0c21cb95d2f52b6021cc0b2a58f2a5a", size = 1917869, upload-time = "2025-11-04T13:39:34.469Z" }, - { url = "https://files.pythonhosted.org/packages/6e/6a/30d94a9674a7fe4f4744052ed6c5e083424510be1e93da5bc47569d11810/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e7b576130c69225432866fe2f4a469a85a54ade141d96fd396dffcf607b558f8", size = 2063890, upload-time = "2025-11-04T13:39:36.053Z" }, - { url = "https://files.pythonhosted.org/packages/50/be/76e5d46203fcb2750e542f32e6c371ffa9b8ad17364cf94bb0818dbfb50c/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6cb58b9c66f7e4179a2d5e0f849c48eff5c1fca560994d6eb6543abf955a149e", size = 2229740, upload-time = "2025-11-04T13:39:37.753Z" }, - { url = "https://files.pythonhosted.org/packages/d3/ee/fed784df0144793489f87db310a6bbf8118d7b630ed07aa180d6067e653a/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:88942d3a3dff3afc8288c21e565e476fc278902ae4d6d134f1eeda118cc830b1", size = 2350021, upload-time = "2025-11-04T13:39:40.94Z" }, - { url = "https://files.pythonhosted.org/packages/c8/be/8fed28dd0a180dca19e72c233cbf58efa36df055e5b9d90d64fd1740b828/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f31d95a179f8d64d90f6831d71fa93290893a33148d890ba15de25642c5d075b", size = 2066378, upload-time = "2025-11-04T13:39:42.523Z" }, - { url = "https://files.pythonhosted.org/packages/b0/3b/698cf8ae1d536a010e05121b4958b1257f0b5522085e335360e53a6b1c8b/pydantic_core-2.41.5-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c1df3d34aced70add6f867a8cf413e299177e0c22660cc767218373d0779487b", size = 2175761, upload-time = "2025-11-04T13:39:44.553Z" }, - { url = "https://files.pythonhosted.org/packages/b8/ba/15d537423939553116dea94ce02f9c31be0fa9d0b806d427e0308ec17145/pydantic_core-2.41.5-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:4009935984bd36bd2c774e13f9a09563ce8de4abaa7226f5108262fa3e637284", size = 2146303, upload-time = "2025-11-04T13:39:46.238Z" }, - { url = "https://files.pythonhosted.org/packages/58/7f/0de669bf37d206723795f9c90c82966726a2ab06c336deba4735b55af431/pydantic_core-2.41.5-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:34a64bc3441dc1213096a20fe27e8e128bd3ff89921706e83c0b1ac971276594", size = 2340355, upload-time = "2025-11-04T13:39:48.002Z" }, - { url = "https://files.pythonhosted.org/packages/e5/de/e7482c435b83d7e3c3ee5ee4451f6e8973cff0eb6007d2872ce6383f6398/pydantic_core-2.41.5-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:c9e19dd6e28fdcaa5a1de679aec4141f691023916427ef9bae8584f9c2fb3b0e", size = 2319875, upload-time = "2025-11-04T13:39:49.705Z" }, - { url = "https://files.pythonhosted.org/packages/fe/e6/8c9e81bb6dd7560e33b9053351c29f30c8194b72f2d6932888581f503482/pydantic_core-2.41.5-cp311-cp311-win32.whl", hash = "sha256:2c010c6ded393148374c0f6f0bf89d206bf3217f201faa0635dcd56bd1520f6b", size = 1987549, upload-time = "2025-11-04T13:39:51.842Z" }, - { url = "https://files.pythonhosted.org/packages/11/66/f14d1d978ea94d1bc21fc98fcf570f9542fe55bfcc40269d4e1a21c19bf7/pydantic_core-2.41.5-cp311-cp311-win_amd64.whl", hash = "sha256:76ee27c6e9c7f16f47db7a94157112a2f3a00e958bc626e2f4ee8bec5c328fbe", size = 2011305, upload-time = "2025-11-04T13:39:53.485Z" }, - { url = "https://files.pythonhosted.org/packages/56/d8/0e271434e8efd03186c5386671328154ee349ff0354d83c74f5caaf096ed/pydantic_core-2.41.5-cp311-cp311-win_arm64.whl", hash = "sha256:4bc36bbc0b7584de96561184ad7f012478987882ebf9f9c389b23f432ea3d90f", size = 1972902, upload-time = "2025-11-04T13:39:56.488Z" }, - { url = "https://files.pythonhosted.org/packages/5f/5d/5f6c63eebb5afee93bcaae4ce9a898f3373ca23df3ccaef086d0233a35a7/pydantic_core-2.41.5-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:f41a7489d32336dbf2199c8c0a215390a751c5b014c2c1c5366e817202e9cdf7", size = 2110990, upload-time = "2025-11-04T13:39:58.079Z" }, - { url = "https://files.pythonhosted.org/packages/aa/32/9c2e8ccb57c01111e0fd091f236c7b371c1bccea0fa85247ac55b1e2b6b6/pydantic_core-2.41.5-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:070259a8818988b9a84a449a2a7337c7f430a22acc0859c6b110aa7212a6d9c0", size = 1896003, upload-time = "2025-11-04T13:39:59.956Z" }, - { url = "https://files.pythonhosted.org/packages/68/b8/a01b53cb0e59139fbc9e4fda3e9724ede8de279097179be4ff31f1abb65a/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e96cea19e34778f8d59fe40775a7a574d95816eb150850a85a7a4c8f4b94ac69", size = 1919200, upload-time = "2025-11-04T13:40:02.241Z" }, - { url = "https://files.pythonhosted.org/packages/38/de/8c36b5198a29bdaade07b5985e80a233a5ac27137846f3bc2d3b40a47360/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed2e99c456e3fadd05c991f8f437ef902e00eedf34320ba2b0842bd1c3ca3a75", size = 2052578, upload-time = "2025-11-04T13:40:04.401Z" }, - { url = "https://files.pythonhosted.org/packages/00/b5/0e8e4b5b081eac6cb3dbb7e60a65907549a1ce035a724368c330112adfdd/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:65840751b72fbfd82c3c640cff9284545342a4f1eb1586ad0636955b261b0b05", size = 2208504, upload-time = "2025-11-04T13:40:06.072Z" }, - { url = "https://files.pythonhosted.org/packages/77/56/87a61aad59c7c5b9dc8caad5a41a5545cba3810c3e828708b3d7404f6cef/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e536c98a7626a98feb2d3eaf75944ef6f3dbee447e1f841eae16f2f0a72d8ddc", size = 2335816, upload-time = "2025-11-04T13:40:07.835Z" }, - { url = "https://files.pythonhosted.org/packages/0d/76/941cc9f73529988688a665a5c0ecff1112b3d95ab48f81db5f7606f522d3/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eceb81a8d74f9267ef4081e246ffd6d129da5d87e37a77c9bde550cb04870c1c", size = 2075366, upload-time = "2025-11-04T13:40:09.804Z" }, - { url = "https://files.pythonhosted.org/packages/d3/43/ebef01f69baa07a482844faaa0a591bad1ef129253ffd0cdaa9d8a7f72d3/pydantic_core-2.41.5-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d38548150c39b74aeeb0ce8ee1d8e82696f4a4e16ddc6de7b1d8823f7de4b9b5", size = 2171698, upload-time = "2025-11-04T13:40:12.004Z" }, - { url = "https://files.pythonhosted.org/packages/b1/87/41f3202e4193e3bacfc2c065fab7706ebe81af46a83d3e27605029c1f5a6/pydantic_core-2.41.5-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:c23e27686783f60290e36827f9c626e63154b82b116d7fe9adba1fda36da706c", size = 2132603, upload-time = "2025-11-04T13:40:13.868Z" }, - { url = "https://files.pythonhosted.org/packages/49/7d/4c00df99cb12070b6bccdef4a195255e6020a550d572768d92cc54dba91a/pydantic_core-2.41.5-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:482c982f814460eabe1d3bb0adfdc583387bd4691ef00b90575ca0d2b6fe2294", size = 2329591, upload-time = "2025-11-04T13:40:15.672Z" }, - { url = "https://files.pythonhosted.org/packages/cc/6a/ebf4b1d65d458f3cda6a7335d141305dfa19bdc61140a884d165a8a1bbc7/pydantic_core-2.41.5-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:bfea2a5f0b4d8d43adf9d7b8bf019fb46fdd10a2e5cde477fbcb9d1fa08c68e1", size = 2319068, upload-time = "2025-11-04T13:40:17.532Z" }, - { url = "https://files.pythonhosted.org/packages/49/3b/774f2b5cd4192d5ab75870ce4381fd89cf218af999515baf07e7206753f0/pydantic_core-2.41.5-cp312-cp312-win32.whl", hash = "sha256:b74557b16e390ec12dca509bce9264c3bbd128f8a2c376eaa68003d7f327276d", size = 1985908, upload-time = "2025-11-04T13:40:19.309Z" }, - { url = "https://files.pythonhosted.org/packages/86/45/00173a033c801cacf67c190fef088789394feaf88a98a7035b0e40d53dc9/pydantic_core-2.41.5-cp312-cp312-win_amd64.whl", hash = "sha256:1962293292865bca8e54702b08a4f26da73adc83dd1fcf26fbc875b35d81c815", size = 2020145, upload-time = "2025-11-04T13:40:21.548Z" }, - { url = "https://files.pythonhosted.org/packages/f9/22/91fbc821fa6d261b376a3f73809f907cec5ca6025642c463d3488aad22fb/pydantic_core-2.41.5-cp312-cp312-win_arm64.whl", hash = "sha256:1746d4a3d9a794cacae06a5eaaccb4b8643a131d45fbc9af23e353dc0a5ba5c3", size = 1976179, upload-time = "2025-11-04T13:40:23.393Z" }, - { url = "https://files.pythonhosted.org/packages/87/06/8806241ff1f70d9939f9af039c6c35f2360cf16e93c2ca76f184e76b1564/pydantic_core-2.41.5-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:941103c9be18ac8daf7b7adca8228f8ed6bb7a1849020f643b3a14d15b1924d9", size = 2120403, upload-time = "2025-11-04T13:40:25.248Z" }, - { url = "https://files.pythonhosted.org/packages/94/02/abfa0e0bda67faa65fef1c84971c7e45928e108fe24333c81f3bfe35d5f5/pydantic_core-2.41.5-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:112e305c3314f40c93998e567879e887a3160bb8689ef3d2c04b6cc62c33ac34", size = 1896206, upload-time = "2025-11-04T13:40:27.099Z" }, - { url = "https://files.pythonhosted.org/packages/15/df/a4c740c0943e93e6500f9eb23f4ca7ec9bf71b19e608ae5b579678c8d02f/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0cbaad15cb0c90aa221d43c00e77bb33c93e8d36e0bf74760cd00e732d10a6a0", size = 1919307, upload-time = "2025-11-04T13:40:29.806Z" }, - { url = "https://files.pythonhosted.org/packages/9a/e3/6324802931ae1d123528988e0e86587c2072ac2e5394b4bc2bc34b61ff6e/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:03ca43e12fab6023fc79d28ca6b39b05f794ad08ec2feccc59a339b02f2b3d33", size = 2063258, upload-time = "2025-11-04T13:40:33.544Z" }, - { url = "https://files.pythonhosted.org/packages/c9/d4/2230d7151d4957dd79c3044ea26346c148c98fbf0ee6ebd41056f2d62ab5/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dc799088c08fa04e43144b164feb0c13f9a0bc40503f8df3e9fde58a3c0c101e", size = 2214917, upload-time = "2025-11-04T13:40:35.479Z" }, - { url = "https://files.pythonhosted.org/packages/e6/9f/eaac5df17a3672fef0081b6c1bb0b82b33ee89aa5cec0d7b05f52fd4a1fa/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:97aeba56665b4c3235a0e52b2c2f5ae9cd071b8a8310ad27bddb3f7fb30e9aa2", size = 2332186, upload-time = "2025-11-04T13:40:37.436Z" }, - { url = "https://files.pythonhosted.org/packages/cf/4e/35a80cae583a37cf15604b44240e45c05e04e86f9cfd766623149297e971/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:406bf18d345822d6c21366031003612b9c77b3e29ffdb0f612367352aab7d586", size = 2073164, upload-time = "2025-11-04T13:40:40.289Z" }, - { url = "https://files.pythonhosted.org/packages/bf/e3/f6e262673c6140dd3305d144d032f7bd5f7497d3871c1428521f19f9efa2/pydantic_core-2.41.5-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b93590ae81f7010dbe380cdeab6f515902ebcbefe0b9327cc4804d74e93ae69d", size = 2179146, upload-time = "2025-11-04T13:40:42.809Z" }, - { url = "https://files.pythonhosted.org/packages/75/c7/20bd7fc05f0c6ea2056a4565c6f36f8968c0924f19b7d97bbfea55780e73/pydantic_core-2.41.5-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:01a3d0ab748ee531f4ea6c3e48ad9dac84ddba4b0d82291f87248f2f9de8d740", size = 2137788, upload-time = "2025-11-04T13:40:44.752Z" }, - { url = "https://files.pythonhosted.org/packages/3a/8d/34318ef985c45196e004bc46c6eab2eda437e744c124ef0dbe1ff2c9d06b/pydantic_core-2.41.5-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:6561e94ba9dacc9c61bce40e2d6bdc3bfaa0259d3ff36ace3b1e6901936d2e3e", size = 2340133, upload-time = "2025-11-04T13:40:46.66Z" }, - { url = "https://files.pythonhosted.org/packages/9c/59/013626bf8c78a5a5d9350d12e7697d3d4de951a75565496abd40ccd46bee/pydantic_core-2.41.5-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:915c3d10f81bec3a74fbd4faebe8391013ba61e5a1a8d48c4455b923bdda7858", size = 2324852, upload-time = "2025-11-04T13:40:48.575Z" }, - { url = "https://files.pythonhosted.org/packages/1a/d9/c248c103856f807ef70c18a4f986693a46a8ffe1602e5d361485da502d20/pydantic_core-2.41.5-cp313-cp313-win32.whl", hash = "sha256:650ae77860b45cfa6e2cdafc42618ceafab3a2d9a3811fcfbd3bbf8ac3c40d36", size = 1994679, upload-time = "2025-11-04T13:40:50.619Z" }, - { url = "https://files.pythonhosted.org/packages/9e/8b/341991b158ddab181cff136acd2552c9f35bd30380422a639c0671e99a91/pydantic_core-2.41.5-cp313-cp313-win_amd64.whl", hash = "sha256:79ec52ec461e99e13791ec6508c722742ad745571f234ea6255bed38c6480f11", size = 2019766, upload-time = "2025-11-04T13:40:52.631Z" }, - { url = "https://files.pythonhosted.org/packages/73/7d/f2f9db34af103bea3e09735bb40b021788a5e834c81eedb541991badf8f5/pydantic_core-2.41.5-cp313-cp313-win_arm64.whl", hash = "sha256:3f84d5c1b4ab906093bdc1ff10484838aca54ef08de4afa9de0f5f14d69639cd", size = 1981005, upload-time = "2025-11-04T13:40:54.734Z" }, - { url = "https://files.pythonhosted.org/packages/ea/28/46b7c5c9635ae96ea0fbb779e271a38129df2550f763937659ee6c5dbc65/pydantic_core-2.41.5-cp314-cp314-macosx_10_12_x86_64.whl", hash = "sha256:3f37a19d7ebcdd20b96485056ba9e8b304e27d9904d233d7b1015db320e51f0a", size = 2119622, upload-time = "2025-11-04T13:40:56.68Z" }, - { url = "https://files.pythonhosted.org/packages/74/1a/145646e5687e8d9a1e8d09acb278c8535ebe9e972e1f162ed338a622f193/pydantic_core-2.41.5-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:1d1d9764366c73f996edd17abb6d9d7649a7eb690006ab6adbda117717099b14", size = 1891725, upload-time = "2025-11-04T13:40:58.807Z" }, - { url = "https://files.pythonhosted.org/packages/23/04/e89c29e267b8060b40dca97bfc64a19b2a3cf99018167ea1677d96368273/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25e1c2af0fce638d5f1988b686f3b3ea8cd7de5f244ca147c777769e798a9cd1", size = 1915040, upload-time = "2025-11-04T13:41:00.853Z" }, - { url = "https://files.pythonhosted.org/packages/84/a3/15a82ac7bd97992a82257f777b3583d3e84bdb06ba6858f745daa2ec8a85/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:506d766a8727beef16b7adaeb8ee6217c64fc813646b424d0804d67c16eddb66", size = 2063691, upload-time = "2025-11-04T13:41:03.504Z" }, - { url = "https://files.pythonhosted.org/packages/74/9b/0046701313c6ef08c0c1cf0e028c67c770a4e1275ca73131563c5f2a310a/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4819fa52133c9aa3c387b3328f25c1facc356491e6135b459f1de698ff64d869", size = 2213897, upload-time = "2025-11-04T13:41:05.804Z" }, - { url = "https://files.pythonhosted.org/packages/8a/cd/6bac76ecd1b27e75a95ca3a9a559c643b3afcd2dd62086d4b7a32a18b169/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2b761d210c9ea91feda40d25b4efe82a1707da2ef62901466a42492c028553a2", size = 2333302, upload-time = "2025-11-04T13:41:07.809Z" }, - { url = "https://files.pythonhosted.org/packages/4c/d2/ef2074dc020dd6e109611a8be4449b98cd25e1b9b8a303c2f0fca2f2bcf7/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:22f0fb8c1c583a3b6f24df2470833b40207e907b90c928cc8d3594b76f874375", size = 2064877, upload-time = "2025-11-04T13:41:09.827Z" }, - { url = "https://files.pythonhosted.org/packages/18/66/e9db17a9a763d72f03de903883c057b2592c09509ccfe468187f2a2eef29/pydantic_core-2.41.5-cp314-cp314-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2782c870e99878c634505236d81e5443092fba820f0373997ff75f90f68cd553", size = 2180680, upload-time = "2025-11-04T13:41:12.379Z" }, - { url = "https://files.pythonhosted.org/packages/d3/9e/3ce66cebb929f3ced22be85d4c2399b8e85b622db77dad36b73c5387f8f8/pydantic_core-2.41.5-cp314-cp314-musllinux_1_1_aarch64.whl", hash = "sha256:0177272f88ab8312479336e1d777f6b124537d47f2123f89cb37e0accea97f90", size = 2138960, upload-time = "2025-11-04T13:41:14.627Z" }, - { url = "https://files.pythonhosted.org/packages/a6/62/205a998f4327d2079326b01abee48e502ea739d174f0a89295c481a2272e/pydantic_core-2.41.5-cp314-cp314-musllinux_1_1_armv7l.whl", hash = "sha256:63510af5e38f8955b8ee5687740d6ebf7c2a0886d15a6d65c32814613681bc07", size = 2339102, upload-time = "2025-11-04T13:41:16.868Z" }, - { url = "https://files.pythonhosted.org/packages/3c/0d/f05e79471e889d74d3d88f5bd20d0ed189ad94c2423d81ff8d0000aab4ff/pydantic_core-2.41.5-cp314-cp314-musllinux_1_1_x86_64.whl", hash = "sha256:e56ba91f47764cc14f1daacd723e3e82d1a89d783f0f5afe9c364b8bb491ccdb", size = 2326039, upload-time = "2025-11-04T13:41:18.934Z" }, - { url = "https://files.pythonhosted.org/packages/ec/e1/e08a6208bb100da7e0c4b288eed624a703f4d129bde2da475721a80cab32/pydantic_core-2.41.5-cp314-cp314-win32.whl", hash = "sha256:aec5cf2fd867b4ff45b9959f8b20ea3993fc93e63c7363fe6851424c8a7e7c23", size = 1995126, upload-time = "2025-11-04T13:41:21.418Z" }, - { url = "https://files.pythonhosted.org/packages/48/5d/56ba7b24e9557f99c9237e29f5c09913c81eeb2f3217e40e922353668092/pydantic_core-2.41.5-cp314-cp314-win_amd64.whl", hash = "sha256:8e7c86f27c585ef37c35e56a96363ab8de4e549a95512445b85c96d3e2f7c1bf", size = 2015489, upload-time = "2025-11-04T13:41:24.076Z" }, - { url = "https://files.pythonhosted.org/packages/4e/bb/f7a190991ec9e3e0ba22e4993d8755bbc4a32925c0b5b42775c03e8148f9/pydantic_core-2.41.5-cp314-cp314-win_arm64.whl", hash = "sha256:e672ba74fbc2dc8eea59fb6d4aed6845e6905fc2a8afe93175d94a83ba2a01a0", size = 1977288, upload-time = "2025-11-04T13:41:26.33Z" }, - { url = "https://files.pythonhosted.org/packages/92/ed/77542d0c51538e32e15afe7899d79efce4b81eee631d99850edc2f5e9349/pydantic_core-2.41.5-cp314-cp314t-macosx_10_12_x86_64.whl", hash = "sha256:8566def80554c3faa0e65ac30ab0932b9e3a5cd7f8323764303d468e5c37595a", size = 2120255, upload-time = "2025-11-04T13:41:28.569Z" }, - { url = "https://files.pythonhosted.org/packages/bb/3d/6913dde84d5be21e284439676168b28d8bbba5600d838b9dca99de0fad71/pydantic_core-2.41.5-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:b80aa5095cd3109962a298ce14110ae16b8c1aece8b72f9dafe81cf597ad80b3", size = 1863760, upload-time = "2025-11-04T13:41:31.055Z" }, - { url = "https://files.pythonhosted.org/packages/5a/f0/e5e6b99d4191da102f2b0eb9687aaa7f5bea5d9964071a84effc3e40f997/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3006c3dd9ba34b0c094c544c6006cc79e87d8612999f1a5d43b769b89181f23c", size = 1878092, upload-time = "2025-11-04T13:41:33.21Z" }, - { url = "https://files.pythonhosted.org/packages/71/48/36fb760642d568925953bcc8116455513d6e34c4beaa37544118c36aba6d/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:72f6c8b11857a856bcfa48c86f5368439f74453563f951e473514579d44aa612", size = 2053385, upload-time = "2025-11-04T13:41:35.508Z" }, - { url = "https://files.pythonhosted.org/packages/20/25/92dc684dd8eb75a234bc1c764b4210cf2646479d54b47bf46061657292a8/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5cb1b2f9742240e4bb26b652a5aeb840aa4b417c7748b6f8387927bc6e45e40d", size = 2218832, upload-time = "2025-11-04T13:41:37.732Z" }, - { url = "https://files.pythonhosted.org/packages/e2/09/f53e0b05023d3e30357d82eb35835d0f6340ca344720a4599cd663dca599/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bd3d54f38609ff308209bd43acea66061494157703364ae40c951f83ba99a1a9", size = 2327585, upload-time = "2025-11-04T13:41:40Z" }, - { url = "https://files.pythonhosted.org/packages/aa/4e/2ae1aa85d6af35a39b236b1b1641de73f5a6ac4d5a7509f77b814885760c/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2ff4321e56e879ee8d2a879501c8e469414d948f4aba74a2d4593184eb326660", size = 2041078, upload-time = "2025-11-04T13:41:42.323Z" }, - { url = "https://files.pythonhosted.org/packages/cd/13/2e215f17f0ef326fc72afe94776edb77525142c693767fc347ed6288728d/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d0d2568a8c11bf8225044aa94409e21da0cb09dcdafe9ecd10250b2baad531a9", size = 2173914, upload-time = "2025-11-04T13:41:45.221Z" }, - { url = "https://files.pythonhosted.org/packages/02/7a/f999a6dcbcd0e5660bc348a3991c8915ce6599f4f2c6ac22f01d7a10816c/pydantic_core-2.41.5-cp314-cp314t-musllinux_1_1_aarch64.whl", hash = "sha256:a39455728aabd58ceabb03c90e12f71fd30fa69615760a075b9fec596456ccc3", size = 2129560, upload-time = "2025-11-04T13:41:47.474Z" }, - { url = "https://files.pythonhosted.org/packages/3a/b1/6c990ac65e3b4c079a4fb9f5b05f5b013afa0f4ed6780a3dd236d2cbdc64/pydantic_core-2.41.5-cp314-cp314t-musllinux_1_1_armv7l.whl", hash = "sha256:239edca560d05757817c13dc17c50766136d21f7cd0fac50295499ae24f90fdf", size = 2329244, upload-time = "2025-11-04T13:41:49.992Z" }, - { url = "https://files.pythonhosted.org/packages/d9/02/3c562f3a51afd4d88fff8dffb1771b30cfdfd79befd9883ee094f5b6c0d8/pydantic_core-2.41.5-cp314-cp314t-musllinux_1_1_x86_64.whl", hash = "sha256:2a5e06546e19f24c6a96a129142a75cee553cc018ffee48a460059b1185f4470", size = 2331955, upload-time = "2025-11-04T13:41:54.079Z" }, - { url = "https://files.pythonhosted.org/packages/5c/96/5fb7d8c3c17bc8c62fdb031c47d77a1af698f1d7a406b0f79aaa1338f9ad/pydantic_core-2.41.5-cp314-cp314t-win32.whl", hash = "sha256:b4ececa40ac28afa90871c2cc2b9ffd2ff0bf749380fbdf57d165fd23da353aa", size = 1988906, upload-time = "2025-11-04T13:41:56.606Z" }, - { url = "https://files.pythonhosted.org/packages/22/ed/182129d83032702912c2e2d8bbe33c036f342cc735737064668585dac28f/pydantic_core-2.41.5-cp314-cp314t-win_amd64.whl", hash = "sha256:80aa89cad80b32a912a65332f64a4450ed00966111b6615ca6816153d3585a8c", size = 1981607, upload-time = "2025-11-04T13:41:58.889Z" }, - { url = "https://files.pythonhosted.org/packages/9f/ed/068e41660b832bb0b1aa5b58011dea2a3fe0ba7861ff38c4d4904c1c1a99/pydantic_core-2.41.5-cp314-cp314t-win_arm64.whl", hash = "sha256:35b44f37a3199f771c3eaa53051bc8a70cd7b54f333531c59e29fd4db5d15008", size = 1974769, upload-time = "2025-11-04T13:42:01.186Z" }, - { url = "https://files.pythonhosted.org/packages/11/72/90fda5ee3b97e51c494938a4a44c3a35a9c96c19bba12372fb9c634d6f57/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-macosx_10_12_x86_64.whl", hash = "sha256:b96d5f26b05d03cc60f11a7761a5ded1741da411e7fe0909e27a5e6a0cb7b034", size = 2115441, upload-time = "2025-11-04T13:42:39.557Z" }, - { url = "https://files.pythonhosted.org/packages/1f/53/8942f884fa33f50794f119012dc6a1a02ac43a56407adaac20463df8e98f/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-macosx_11_0_arm64.whl", hash = "sha256:634e8609e89ceecea15e2d61bc9ac3718caaaa71963717bf3c8f38bfde64242c", size = 1930291, upload-time = "2025-11-04T13:42:42.169Z" }, - { url = "https://files.pythonhosted.org/packages/79/c8/ecb9ed9cd942bce09fc888ee960b52654fbdbede4ba6c2d6e0d3b1d8b49c/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:93e8740d7503eb008aa2df04d3b9735f845d43ae845e6dcd2be0b55a2da43cd2", size = 1948632, upload-time = "2025-11-04T13:42:44.564Z" }, - { url = "https://files.pythonhosted.org/packages/2e/1b/687711069de7efa6af934e74f601e2a4307365e8fdc404703afc453eab26/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f15489ba13d61f670dcc96772e733aad1a6f9c429cc27574c6cdaed82d0146ad", size = 2138905, upload-time = "2025-11-04T13:42:47.156Z" }, - { url = "https://files.pythonhosted.org/packages/09/32/59b0c7e63e277fa7911c2fc70ccfb45ce4b98991e7ef37110663437005af/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-macosx_10_12_x86_64.whl", hash = "sha256:7da7087d756b19037bc2c06edc6c170eeef3c3bafcb8f532ff17d64dc427adfd", size = 2110495, upload-time = "2025-11-04T13:42:49.689Z" }, - { url = "https://files.pythonhosted.org/packages/aa/81/05e400037eaf55ad400bcd318c05bb345b57e708887f07ddb2d20e3f0e98/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-macosx_11_0_arm64.whl", hash = "sha256:aabf5777b5c8ca26f7824cb4a120a740c9588ed58df9b2d196ce92fba42ff8dc", size = 1915388, upload-time = "2025-11-04T13:42:52.215Z" }, - { url = "https://files.pythonhosted.org/packages/6e/0d/e3549b2399f71d56476b77dbf3cf8937cec5cd70536bdc0e374a421d0599/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c007fe8a43d43b3969e8469004e9845944f1a80e6acd47c150856bb87f230c56", size = 1942879, upload-time = "2025-11-04T13:42:56.483Z" }, - { url = "https://files.pythonhosted.org/packages/f7/07/34573da085946b6a313d7c42f82f16e8920bfd730665de2d11c0c37a74b5/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:76d0819de158cd855d1cbb8fcafdf6f5cf1eb8e470abe056d5d161106e38062b", size = 2139017, upload-time = "2025-11-04T13:42:59.471Z" }, - { url = "https://files.pythonhosted.org/packages/5f/9b/1b3f0e9f9305839d7e84912f9e8bfbd191ed1b1ef48083609f0dabde978c/pydantic_core-2.41.5-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:b2379fa7ed44ddecb5bfe4e48577d752db9fc10be00a6b7446e9663ba143de26", size = 2101980, upload-time = "2025-11-04T13:43:25.97Z" }, - { url = "https://files.pythonhosted.org/packages/a4/ed/d71fefcb4263df0da6a85b5d8a7508360f2f2e9b3bf5814be9c8bccdccc1/pydantic_core-2.41.5-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:266fb4cbf5e3cbd0b53669a6d1b039c45e3ce651fd5442eff4d07c2cc8d66808", size = 1923865, upload-time = "2025-11-04T13:43:28.763Z" }, - { url = "https://files.pythonhosted.org/packages/ce/3a/626b38db460d675f873e4444b4bb030453bbe7b4ba55df821d026a0493c4/pydantic_core-2.41.5-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58133647260ea01e4d0500089a8c4f07bd7aa6ce109682b1426394988d8aaacc", size = 2134256, upload-time = "2025-11-04T13:43:31.71Z" }, - { url = "https://files.pythonhosted.org/packages/83/d9/8412d7f06f616bbc053d30cb4e5f76786af3221462ad5eee1f202021eb4e/pydantic_core-2.41.5-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:287dad91cfb551c363dc62899a80e9e14da1f0e2b6ebde82c806612ca2a13ef1", size = 2174762, upload-time = "2025-11-04T13:43:34.744Z" }, - { url = "https://files.pythonhosted.org/packages/55/4c/162d906b8e3ba3a99354e20faa1b49a85206c47de97a639510a0e673f5da/pydantic_core-2.41.5-pp311-pypy311_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:03b77d184b9eb40240ae9fd676ca364ce1085f203e1b1256f8ab9984dca80a84", size = 2143141, upload-time = "2025-11-04T13:43:37.701Z" }, - { url = "https://files.pythonhosted.org/packages/1f/f2/f11dd73284122713f5f89fc940f370d035fa8e1e078d446b3313955157fe/pydantic_core-2.41.5-pp311-pypy311_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:a668ce24de96165bb239160b3d854943128f4334822900534f2fe947930e5770", size = 2330317, upload-time = "2025-11-04T13:43:40.406Z" }, - { url = "https://files.pythonhosted.org/packages/88/9d/b06ca6acfe4abb296110fb1273a4d848a0bfb2ff65f3ee92127b3244e16b/pydantic_core-2.41.5-pp311-pypy311_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f14f8f046c14563f8eb3f45f499cc658ab8d10072961e07225e507adb700e93f", size = 2316992, upload-time = "2025-11-04T13:43:43.602Z" }, - { url = "https://files.pythonhosted.org/packages/36/c7/cfc8e811f061c841d7990b0201912c3556bfeb99cdcb7ed24adc8d6f8704/pydantic_core-2.41.5-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:56121965f7a4dc965bff783d70b907ddf3d57f6eba29b6d2e5dabfaf07799c51", size = 2145302, upload-time = "2025-11-04T13:43:46.64Z" }, -] - -[[package]] -name = "python-dotenv" -version = "1.2.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f0/26/19cadc79a718c5edbec86fd4919a6b6d3f681039a2f6d66d14be94e75fb9/python_dotenv-1.2.1.tar.gz", hash = "sha256:42667e897e16ab0d66954af0e60a9caa94f0fd4ecf3aaf6d2d260eec1aa36ad6", size = 44221, upload-time = "2025-10-26T15:12:10.434Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/14/1b/a298b06749107c305e1fe0f814c6c74aea7b2f1e10989cb30f544a1b3253/python_dotenv-1.2.1-py3-none-any.whl", hash = "sha256:b81ee9561e9ca4004139c6cbba3a238c32b03e4894671e181b671e8cb8425d61", size = 21230, upload-time = "2025-10-26T15:12:09.109Z" }, -] - -[[package]] -name = "python-slugify" -version = "8.0.4" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "text-unidecode" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/87/c7/5e1547c44e31da50a460df93af11a535ace568ef89d7a811069ead340c4a/python-slugify-8.0.4.tar.gz", hash = "sha256:59202371d1d05b54a9e7720c5e038f928f45daaffe41dd10822f3907b937c856", size = 10921, upload-time = "2024-02-08T18:32:45.488Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a4/62/02da182e544a51a5c3ccf4b03ab79df279f9c60c5e82d5e8bec7ca26ac11/python_slugify-8.0.4-py2.py3-none-any.whl", hash = "sha256:276540b79961052b66b7d116620b36518847f52d5fd9e3a70164fc8c50faa6b8", size = 10051, upload-time = "2024-02-08T18:32:43.911Z" }, -] - -[[package]] -name = "pyyaml" -version = "6.0.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/05/8e/961c0007c59b8dd7729d542c61a4d537767a59645b82a0b521206e1e25c2/pyyaml-6.0.3.tar.gz", hash = "sha256:d76623373421df22fb4cf8817020cbb7ef15c725b9d5e45f17e189bfc384190f", size = 130960, upload-time = "2025-09-25T21:33:16.546Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/6d/16/a95b6757765b7b031c9374925bb718d55e0a9ba8a1b6a12d25962ea44347/pyyaml-6.0.3-cp311-cp311-macosx_10_13_x86_64.whl", hash = "sha256:44edc647873928551a01e7a563d7452ccdebee747728c1080d881d68af7b997e", size = 185826, upload-time = "2025-09-25T21:31:58.655Z" }, - { url = "https://files.pythonhosted.org/packages/16/19/13de8e4377ed53079ee996e1ab0a9c33ec2faf808a4647b7b4c0d46dd239/pyyaml-6.0.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:652cb6edd41e718550aad172851962662ff2681490a8a711af6a4d288dd96824", size = 175577, upload-time = "2025-09-25T21:32:00.088Z" }, - { url = "https://files.pythonhosted.org/packages/0c/62/d2eb46264d4b157dae1275b573017abec435397aa59cbcdab6fc978a8af4/pyyaml-6.0.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:10892704fc220243f5305762e276552a0395f7beb4dbf9b14ec8fd43b57f126c", size = 775556, upload-time = "2025-09-25T21:32:01.31Z" }, - { url = "https://files.pythonhosted.org/packages/10/cb/16c3f2cf3266edd25aaa00d6c4350381c8b012ed6f5276675b9eba8d9ff4/pyyaml-6.0.3-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:850774a7879607d3a6f50d36d04f00ee69e7fc816450e5f7e58d7f17f1ae5c00", size = 882114, upload-time = "2025-09-25T21:32:03.376Z" }, - { url = "https://files.pythonhosted.org/packages/71/60/917329f640924b18ff085ab889a11c763e0b573da888e8404ff486657602/pyyaml-6.0.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b8bb0864c5a28024fac8a632c443c87c5aa6f215c0b126c449ae1a150412f31d", size = 806638, upload-time = "2025-09-25T21:32:04.553Z" }, - { url = "https://files.pythonhosted.org/packages/dd/6f/529b0f316a9fd167281a6c3826b5583e6192dba792dd55e3203d3f8e655a/pyyaml-6.0.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:1d37d57ad971609cf3c53ba6a7e365e40660e3be0e5175fa9f2365a379d6095a", size = 767463, upload-time = "2025-09-25T21:32:06.152Z" }, - { url = "https://files.pythonhosted.org/packages/f2/6a/b627b4e0c1dd03718543519ffb2f1deea4a1e6d42fbab8021936a4d22589/pyyaml-6.0.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:37503bfbfc9d2c40b344d06b2199cf0e96e97957ab1c1b546fd4f87e53e5d3e4", size = 794986, upload-time = "2025-09-25T21:32:07.367Z" }, - { url = "https://files.pythonhosted.org/packages/45/91/47a6e1c42d9ee337c4839208f30d9f09caa9f720ec7582917b264defc875/pyyaml-6.0.3-cp311-cp311-win32.whl", hash = "sha256:8098f252adfa6c80ab48096053f512f2321f0b998f98150cea9bd23d83e1467b", size = 142543, upload-time = "2025-09-25T21:32:08.95Z" }, - { url = "https://files.pythonhosted.org/packages/da/e3/ea007450a105ae919a72393cb06f122f288ef60bba2dc64b26e2646fa315/pyyaml-6.0.3-cp311-cp311-win_amd64.whl", hash = "sha256:9f3bfb4965eb874431221a3ff3fdcddc7e74e3b07799e0e84ca4a0f867d449bf", size = 158763, upload-time = "2025-09-25T21:32:09.96Z" }, - { url = "https://files.pythonhosted.org/packages/d1/33/422b98d2195232ca1826284a76852ad5a86fe23e31b009c9886b2d0fb8b2/pyyaml-6.0.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7f047e29dcae44602496db43be01ad42fc6f1cc0d8cd6c83d342306c32270196", size = 182063, upload-time = "2025-09-25T21:32:11.445Z" }, - { url = "https://files.pythonhosted.org/packages/89/a0/6cf41a19a1f2f3feab0e9c0b74134aa2ce6849093d5517a0c550fe37a648/pyyaml-6.0.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:fc09d0aa354569bc501d4e787133afc08552722d3ab34836a80547331bb5d4a0", size = 173973, upload-time = "2025-09-25T21:32:12.492Z" }, - { url = "https://files.pythonhosted.org/packages/ed/23/7a778b6bd0b9a8039df8b1b1d80e2e2ad78aa04171592c8a5c43a56a6af4/pyyaml-6.0.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:9149cad251584d5fb4981be1ecde53a1ca46c891a79788c0df828d2f166bda28", size = 775116, upload-time = "2025-09-25T21:32:13.652Z" }, - { url = "https://files.pythonhosted.org/packages/65/30/d7353c338e12baef4ecc1b09e877c1970bd3382789c159b4f89d6a70dc09/pyyaml-6.0.3-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:5fdec68f91a0c6739b380c83b951e2c72ac0197ace422360e6d5a959d8d97b2c", size = 844011, upload-time = "2025-09-25T21:32:15.21Z" }, - { url = "https://files.pythonhosted.org/packages/8b/9d/b3589d3877982d4f2329302ef98a8026e7f4443c765c46cfecc8858c6b4b/pyyaml-6.0.3-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ba1cc08a7ccde2d2ec775841541641e4548226580ab850948cbfda66a1befcdc", size = 807870, upload-time = "2025-09-25T21:32:16.431Z" }, - { url = "https://files.pythonhosted.org/packages/05/c0/b3be26a015601b822b97d9149ff8cb5ead58c66f981e04fedf4e762f4bd4/pyyaml-6.0.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8dc52c23056b9ddd46818a57b78404882310fb473d63f17b07d5c40421e47f8e", size = 761089, upload-time = "2025-09-25T21:32:17.56Z" }, - { url = "https://files.pythonhosted.org/packages/be/8e/98435a21d1d4b46590d5459a22d88128103f8da4c2d4cb8f14f2a96504e1/pyyaml-6.0.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:41715c910c881bc081f1e8872880d3c650acf13dfa8214bad49ed4cede7c34ea", size = 790181, upload-time = "2025-09-25T21:32:18.834Z" }, - { url = "https://files.pythonhosted.org/packages/74/93/7baea19427dcfbe1e5a372d81473250b379f04b1bd3c4c5ff825e2327202/pyyaml-6.0.3-cp312-cp312-win32.whl", hash = "sha256:96b533f0e99f6579b3d4d4995707cf36df9100d67e0c8303a0c55b27b5f99bc5", size = 137658, upload-time = "2025-09-25T21:32:20.209Z" }, - { url = "https://files.pythonhosted.org/packages/86/bf/899e81e4cce32febab4fb42bb97dcdf66bc135272882d1987881a4b519e9/pyyaml-6.0.3-cp312-cp312-win_amd64.whl", hash = "sha256:5fcd34e47f6e0b794d17de1b4ff496c00986e1c83f7ab2fb8fcfe9616ff7477b", size = 154003, upload-time = "2025-09-25T21:32:21.167Z" }, - { url = "https://files.pythonhosted.org/packages/1a/08/67bd04656199bbb51dbed1439b7f27601dfb576fb864099c7ef0c3e55531/pyyaml-6.0.3-cp312-cp312-win_arm64.whl", hash = "sha256:64386e5e707d03a7e172c0701abfb7e10f0fb753ee1d773128192742712a98fd", size = 140344, upload-time = "2025-09-25T21:32:22.617Z" }, - { url = "https://files.pythonhosted.org/packages/d1/11/0fd08f8192109f7169db964b5707a2f1e8b745d4e239b784a5a1dd80d1db/pyyaml-6.0.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:8da9669d359f02c0b91ccc01cac4a67f16afec0dac22c2ad09f46bee0697eba8", size = 181669, upload-time = "2025-09-25T21:32:23.673Z" }, - { url = "https://files.pythonhosted.org/packages/b1/16/95309993f1d3748cd644e02e38b75d50cbc0d9561d21f390a76242ce073f/pyyaml-6.0.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:2283a07e2c21a2aa78d9c4442724ec1eb15f5e42a723b99cb3d822d48f5f7ad1", size = 173252, upload-time = "2025-09-25T21:32:25.149Z" }, - { url = "https://files.pythonhosted.org/packages/50/31/b20f376d3f810b9b2371e72ef5adb33879b25edb7a6d072cb7ca0c486398/pyyaml-6.0.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:ee2922902c45ae8ccada2c5b501ab86c36525b883eff4255313a253a3160861c", size = 767081, upload-time = "2025-09-25T21:32:26.575Z" }, - { url = "https://files.pythonhosted.org/packages/49/1e/a55ca81e949270d5d4432fbbd19dfea5321eda7c41a849d443dc92fd1ff7/pyyaml-6.0.3-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:a33284e20b78bd4a18c8c2282d549d10bc8408a2a7ff57653c0cf0b9be0afce5", size = 841159, upload-time = "2025-09-25T21:32:27.727Z" }, - { url = "https://files.pythonhosted.org/packages/74/27/e5b8f34d02d9995b80abcef563ea1f8b56d20134d8f4e5e81733b1feceb2/pyyaml-6.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0f29edc409a6392443abf94b9cf89ce99889a1dd5376d94316ae5145dfedd5d6", size = 801626, upload-time = "2025-09-25T21:32:28.878Z" }, - { url = "https://files.pythonhosted.org/packages/f9/11/ba845c23988798f40e52ba45f34849aa8a1f2d4af4b798588010792ebad6/pyyaml-6.0.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f7057c9a337546edc7973c0d3ba84ddcdf0daa14533c2065749c9075001090e6", size = 753613, upload-time = "2025-09-25T21:32:30.178Z" }, - { url = "https://files.pythonhosted.org/packages/3d/e0/7966e1a7bfc0a45bf0a7fb6b98ea03fc9b8d84fa7f2229e9659680b69ee3/pyyaml-6.0.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:eda16858a3cab07b80edaf74336ece1f986ba330fdb8ee0d6c0d68fe82bc96be", size = 794115, upload-time = "2025-09-25T21:32:31.353Z" }, - { url = "https://files.pythonhosted.org/packages/de/94/980b50a6531b3019e45ddeada0626d45fa85cbe22300844a7983285bed3b/pyyaml-6.0.3-cp313-cp313-win32.whl", hash = "sha256:d0eae10f8159e8fdad514efdc92d74fd8d682c933a6dd088030f3834bc8e6b26", size = 137427, upload-time = "2025-09-25T21:32:32.58Z" }, - { url = "https://files.pythonhosted.org/packages/97/c9/39d5b874e8b28845e4ec2202b5da735d0199dbe5b8fb85f91398814a9a46/pyyaml-6.0.3-cp313-cp313-win_amd64.whl", hash = "sha256:79005a0d97d5ddabfeeea4cf676af11e647e41d81c9a7722a193022accdb6b7c", size = 154090, upload-time = "2025-09-25T21:32:33.659Z" }, - { url = "https://files.pythonhosted.org/packages/73/e8/2bdf3ca2090f68bb3d75b44da7bbc71843b19c9f2b9cb9b0f4ab7a5a4329/pyyaml-6.0.3-cp313-cp313-win_arm64.whl", hash = "sha256:5498cd1645aa724a7c71c8f378eb29ebe23da2fc0d7a08071d89469bf1d2defb", size = 140246, upload-time = "2025-09-25T21:32:34.663Z" }, - { url = "https://files.pythonhosted.org/packages/9d/8c/f4bd7f6465179953d3ac9bc44ac1a8a3e6122cf8ada906b4f96c60172d43/pyyaml-6.0.3-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:8d1fab6bb153a416f9aeb4b8763bc0f22a5586065f86f7664fc23339fc1c1fac", size = 181814, upload-time = "2025-09-25T21:32:35.712Z" }, - { url = "https://files.pythonhosted.org/packages/bd/9c/4d95bb87eb2063d20db7b60faa3840c1b18025517ae857371c4dd55a6b3a/pyyaml-6.0.3-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:34d5fcd24b8445fadc33f9cf348c1047101756fd760b4dacb5c3e99755703310", size = 173809, upload-time = "2025-09-25T21:32:36.789Z" }, - { url = "https://files.pythonhosted.org/packages/92/b5/47e807c2623074914e29dabd16cbbdd4bf5e9b2db9f8090fa64411fc5382/pyyaml-6.0.3-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:501a031947e3a9025ed4405a168e6ef5ae3126c59f90ce0cd6f2bfc477be31b7", size = 766454, upload-time = "2025-09-25T21:32:37.966Z" }, - { url = "https://files.pythonhosted.org/packages/02/9e/e5e9b168be58564121efb3de6859c452fccde0ab093d8438905899a3a483/pyyaml-6.0.3-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:b3bc83488de33889877a0f2543ade9f70c67d66d9ebb4ac959502e12de895788", size = 836355, upload-time = "2025-09-25T21:32:39.178Z" }, - { url = "https://files.pythonhosted.org/packages/88/f9/16491d7ed2a919954993e48aa941b200f38040928474c9e85ea9e64222c3/pyyaml-6.0.3-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c458b6d084f9b935061bc36216e8a69a7e293a2f1e68bf956dcd9e6cbcd143f5", size = 794175, upload-time = "2025-09-25T21:32:40.865Z" }, - { url = "https://files.pythonhosted.org/packages/dd/3f/5989debef34dc6397317802b527dbbafb2b4760878a53d4166579111411e/pyyaml-6.0.3-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:7c6610def4f163542a622a73fb39f534f8c101d690126992300bf3207eab9764", size = 755228, upload-time = "2025-09-25T21:32:42.084Z" }, - { url = "https://files.pythonhosted.org/packages/d7/ce/af88a49043cd2e265be63d083fc75b27b6ed062f5f9fd6cdc223ad62f03e/pyyaml-6.0.3-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:5190d403f121660ce8d1d2c1bb2ef1bd05b5f68533fc5c2ea899bd15f4399b35", size = 789194, upload-time = "2025-09-25T21:32:43.362Z" }, - { url = "https://files.pythonhosted.org/packages/23/20/bb6982b26a40bb43951265ba29d4c246ef0ff59c9fdcdf0ed04e0687de4d/pyyaml-6.0.3-cp314-cp314-win_amd64.whl", hash = "sha256:4a2e8cebe2ff6ab7d1050ecd59c25d4c8bd7e6f400f5f82b96557ac0abafd0ac", size = 156429, upload-time = "2025-09-25T21:32:57.844Z" }, - { url = "https://files.pythonhosted.org/packages/f4/f4/a4541072bb9422c8a883ab55255f918fa378ecf083f5b85e87fc2b4eda1b/pyyaml-6.0.3-cp314-cp314-win_arm64.whl", hash = "sha256:93dda82c9c22deb0a405ea4dc5f2d0cda384168e466364dec6255b293923b2f3", size = 143912, upload-time = "2025-09-25T21:32:59.247Z" }, - { url = "https://files.pythonhosted.org/packages/7c/f9/07dd09ae774e4616edf6cda684ee78f97777bdd15847253637a6f052a62f/pyyaml-6.0.3-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:02893d100e99e03eda1c8fd5c441d8c60103fd175728e23e431db1b589cf5ab3", size = 189108, upload-time = "2025-09-25T21:32:44.377Z" }, - { url = "https://files.pythonhosted.org/packages/4e/78/8d08c9fb7ce09ad8c38ad533c1191cf27f7ae1effe5bb9400a46d9437fcf/pyyaml-6.0.3-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:c1ff362665ae507275af2853520967820d9124984e0f7466736aea23d8611fba", size = 183641, upload-time = "2025-09-25T21:32:45.407Z" }, - { url = "https://files.pythonhosted.org/packages/7b/5b/3babb19104a46945cf816d047db2788bcaf8c94527a805610b0289a01c6b/pyyaml-6.0.3-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6adc77889b628398debc7b65c073bcb99c4a0237b248cacaf3fe8a557563ef6c", size = 831901, upload-time = "2025-09-25T21:32:48.83Z" }, - { url = "https://files.pythonhosted.org/packages/8b/cc/dff0684d8dc44da4d22a13f35f073d558c268780ce3c6ba1b87055bb0b87/pyyaml-6.0.3-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:a80cb027f6b349846a3bf6d73b5e95e782175e52f22108cfa17876aaeff93702", size = 861132, upload-time = "2025-09-25T21:32:50.149Z" }, - { url = "https://files.pythonhosted.org/packages/b1/5e/f77dc6b9036943e285ba76b49e118d9ea929885becb0a29ba8a7c75e29fe/pyyaml-6.0.3-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:00c4bdeba853cc34e7dd471f16b4114f4162dc03e6b7afcc2128711f0eca823c", size = 839261, upload-time = "2025-09-25T21:32:51.808Z" }, - { url = "https://files.pythonhosted.org/packages/ce/88/a9db1376aa2a228197c58b37302f284b5617f56a5d959fd1763fb1675ce6/pyyaml-6.0.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:66e1674c3ef6f541c35191caae2d429b967b99e02040f5ba928632d9a7f0f065", size = 805272, upload-time = "2025-09-25T21:32:52.941Z" }, - { url = "https://files.pythonhosted.org/packages/da/92/1446574745d74df0c92e6aa4a7b0b3130706a4142b2d1a5869f2eaa423c6/pyyaml-6.0.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:16249ee61e95f858e83976573de0f5b2893b3677ba71c9dd36b9cf8be9ac6d65", size = 829923, upload-time = "2025-09-25T21:32:54.537Z" }, - { url = "https://files.pythonhosted.org/packages/f0/7a/1c7270340330e575b92f397352af856a8c06f230aa3e76f86b39d01b416a/pyyaml-6.0.3-cp314-cp314t-win_amd64.whl", hash = "sha256:4ad1906908f2f5ae4e5a8ddfce73c320c2a1429ec52eafd27138b7f1cbe341c9", size = 174062, upload-time = "2025-09-25T21:32:55.767Z" }, - { url = "https://files.pythonhosted.org/packages/f1/12/de94a39c2ef588c7e6455cfbe7343d3b2dc9d6b6b2f40c4c6565744c873d/pyyaml-6.0.3-cp314-cp314t-win_arm64.whl", hash = "sha256:ebc55a14a21cb14062aa4162f906cd962b28e2e9ea38f9b4391244cd8de4ae0b", size = 149341, upload-time = "2025-09-25T21:32:56.828Z" }, -] - -[[package]] -name = "regex" -version = "2026.1.15" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/0b/86/07d5056945f9ec4590b518171c4254a5925832eb727b56d3c38a7476f316/regex-2026.1.15.tar.gz", hash = "sha256:164759aa25575cbc0651bef59a0b18353e54300d79ace8084c818ad8ac72b7d5", size = 414811, upload-time = "2026-01-14T23:18:02.775Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d0/c9/0c80c96eab96948363d270143138d671d5731c3a692b417629bf3492a9d6/regex-2026.1.15-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:1ae6020fb311f68d753b7efa9d4b9a5d47a5d6466ea0d5e3b5a471a960ea6e4a", size = 488168, upload-time = "2026-01-14T23:14:16.129Z" }, - { url = "https://files.pythonhosted.org/packages/17/f0/271c92f5389a552494c429e5cc38d76d1322eb142fb5db3c8ccc47751468/regex-2026.1.15-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:eddf73f41225942c1f994914742afa53dc0d01a6e20fe14b878a1b1edc74151f", size = 290636, upload-time = "2026-01-14T23:14:17.715Z" }, - { url = "https://files.pythonhosted.org/packages/a0/f9/5f1fd077d106ca5655a0f9ff8f25a1ab55b92128b5713a91ed7134ff688e/regex-2026.1.15-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1e8cd52557603f5c66a548f69421310886b28b7066853089e1a71ee710e1cdc1", size = 288496, upload-time = "2026-01-14T23:14:19.326Z" }, - { url = "https://files.pythonhosted.org/packages/b5/e1/8f43b03a4968c748858ec77f746c286d81f896c2e437ccf050ebc5d3128c/regex-2026.1.15-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5170907244b14303edc5978f522f16c974f32d3aa92109fabc2af52411c9433b", size = 793503, upload-time = "2026-01-14T23:14:20.922Z" }, - { url = "https://files.pythonhosted.org/packages/8d/4e/a39a5e8edc5377a46a7c875c2f9a626ed3338cb3bb06931be461c3e1a34a/regex-2026.1.15-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:2748c1ec0663580b4510bd89941a31560b4b439a0b428b49472a3d9944d11cd8", size = 860535, upload-time = "2026-01-14T23:14:22.405Z" }, - { url = "https://files.pythonhosted.org/packages/dc/1c/9dce667a32a9477f7a2869c1c767dc00727284a9fa3ff5c09a5c6c03575e/regex-2026.1.15-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:2f2775843ca49360508d080eaa87f94fa248e2c946bbcd963bb3aae14f333413", size = 907225, upload-time = "2026-01-14T23:14:23.897Z" }, - { url = "https://files.pythonhosted.org/packages/a4/3c/87ca0a02736d16b6262921425e84b48984e77d8e4e572c9072ce96e66c30/regex-2026.1.15-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d9ea2604370efc9a174c1b5dcc81784fb040044232150f7f33756049edfc9026", size = 800526, upload-time = "2026-01-14T23:14:26.039Z" }, - { url = "https://files.pythonhosted.org/packages/4b/ff/647d5715aeea7c87bdcbd2f578f47b415f55c24e361e639fe8c0cc88878f/regex-2026.1.15-cp311-cp311-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:0dcd31594264029b57bf16f37fd7248a70b3b764ed9e0839a8f271b2d22c0785", size = 773446, upload-time = "2026-01-14T23:14:28.109Z" }, - { url = "https://files.pythonhosted.org/packages/af/89/bf22cac25cb4ba0fe6bff52ebedbb65b77a179052a9d6037136ae93f42f4/regex-2026.1.15-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c08c1f3e34338256732bd6938747daa3c0d5b251e04b6e43b5813e94d503076e", size = 783051, upload-time = "2026-01-14T23:14:29.929Z" }, - { url = "https://files.pythonhosted.org/packages/1e/f4/6ed03e71dca6348a5188363a34f5e26ffd5db1404780288ff0d79513bce4/regex-2026.1.15-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:e43a55f378df1e7a4fa3547c88d9a5a9b7113f653a66821bcea4718fe6c58763", size = 854485, upload-time = "2026-01-14T23:14:31.366Z" }, - { url = "https://files.pythonhosted.org/packages/d9/9a/8e8560bd78caded8eb137e3e47612430a05b9a772caf60876435192d670a/regex-2026.1.15-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:f82110ab962a541737bd0ce87978d4c658f06e7591ba899192e2712a517badbb", size = 762195, upload-time = "2026-01-14T23:14:32.802Z" }, - { url = "https://files.pythonhosted.org/packages/38/6b/61fc710f9aa8dfcd764fe27d37edfaa023b1a23305a0d84fccd5adb346ea/regex-2026.1.15-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:27618391db7bdaf87ac6c92b31e8f0dfb83a9de0075855152b720140bda177a2", size = 845986, upload-time = "2026-01-14T23:14:34.898Z" }, - { url = "https://files.pythonhosted.org/packages/fd/2e/fbee4cb93f9d686901a7ca8d94285b80405e8c34fe4107f63ffcbfb56379/regex-2026.1.15-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:bfb0d6be01fbae8d6655c8ca21b3b72458606c4aec9bbc932db758d47aba6db1", size = 788992, upload-time = "2026-01-14T23:14:37.116Z" }, - { url = "https://files.pythonhosted.org/packages/ed/14/3076348f3f586de64b1ab75a3fbabdaab7684af7f308ad43be7ef1849e55/regex-2026.1.15-cp311-cp311-win32.whl", hash = "sha256:b10e42a6de0e32559a92f2f8dc908478cc0fa02838d7dbe764c44dca3fa13569", size = 265893, upload-time = "2026-01-14T23:14:38.426Z" }, - { url = "https://files.pythonhosted.org/packages/0f/19/772cf8b5fc803f5c89ba85d8b1870a1ca580dc482aa030383a9289c82e44/regex-2026.1.15-cp311-cp311-win_amd64.whl", hash = "sha256:e9bf3f0bbdb56633c07d7116ae60a576f846efdd86a8848f8d62b749e1209ca7", size = 277840, upload-time = "2026-01-14T23:14:39.785Z" }, - { url = "https://files.pythonhosted.org/packages/78/84/d05f61142709474da3c0853222d91086d3e1372bcdab516c6fd8d80f3297/regex-2026.1.15-cp311-cp311-win_arm64.whl", hash = "sha256:41aef6f953283291c4e4e6850607bd71502be67779586a61472beacb315c97ec", size = 270374, upload-time = "2026-01-14T23:14:41.592Z" }, - { url = "https://files.pythonhosted.org/packages/92/81/10d8cf43c807d0326efe874c1b79f22bfb0fb226027b0b19ebc26d301408/regex-2026.1.15-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:4c8fcc5793dde01641a35905d6731ee1548f02b956815f8f1cab89e515a5bdf1", size = 489398, upload-time = "2026-01-14T23:14:43.741Z" }, - { url = "https://files.pythonhosted.org/packages/90/b0/7c2a74e74ef2a7c32de724658a69a862880e3e4155cba992ba04d1c70400/regex-2026.1.15-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:bfd876041a956e6a90ad7cdb3f6a630c07d491280bfeed4544053cd434901681", size = 291339, upload-time = "2026-01-14T23:14:45.183Z" }, - { url = "https://files.pythonhosted.org/packages/19/4d/16d0773d0c818417f4cc20aa0da90064b966d22cd62a8c46765b5bd2d643/regex-2026.1.15-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:9250d087bc92b7d4899ccd5539a1b2334e44eee85d848c4c1aef8e221d3f8c8f", size = 289003, upload-time = "2026-01-14T23:14:47.25Z" }, - { url = "https://files.pythonhosted.org/packages/c6/e4/1fc4599450c9f0863d9406e944592d968b8d6dfd0d552a7d569e43bceada/regex-2026.1.15-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c8a154cf6537ebbc110e24dabe53095e714245c272da9c1be05734bdad4a61aa", size = 798656, upload-time = "2026-01-14T23:14:48.77Z" }, - { url = "https://files.pythonhosted.org/packages/b2/e6/59650d73a73fa8a60b3a590545bfcf1172b4384a7df2e7fe7b9aab4e2da9/regex-2026.1.15-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:8050ba2e3ea1d8731a549e83c18d2f0999fbc99a5f6bd06b4c91449f55291804", size = 864252, upload-time = "2026-01-14T23:14:50.528Z" }, - { url = "https://files.pythonhosted.org/packages/6e/ab/1d0f4d50a1638849a97d731364c9a80fa304fec46325e48330c170ee8e80/regex-2026.1.15-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:0bf065240704cb8951cc04972cf107063917022511273e0969bdb34fc173456c", size = 912268, upload-time = "2026-01-14T23:14:52.952Z" }, - { url = "https://files.pythonhosted.org/packages/dd/df/0d722c030c82faa1d331d1921ee268a4e8fb55ca8b9042c9341c352f17fa/regex-2026.1.15-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c32bef3e7aeee75746748643667668ef941d28b003bfc89994ecf09a10f7a1b5", size = 803589, upload-time = "2026-01-14T23:14:55.182Z" }, - { url = "https://files.pythonhosted.org/packages/66/23/33289beba7ccb8b805c6610a8913d0131f834928afc555b241caabd422a9/regex-2026.1.15-cp312-cp312-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:d5eaa4a4c5b1906bd0d2508d68927f15b81821f85092e06f1a34a4254b0e1af3", size = 775700, upload-time = "2026-01-14T23:14:56.707Z" }, - { url = "https://files.pythonhosted.org/packages/e7/65/bf3a42fa6897a0d3afa81acb25c42f4b71c274f698ceabd75523259f6688/regex-2026.1.15-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:86c1077a3cc60d453d4084d5b9649065f3bf1184e22992bd322e1f081d3117fb", size = 787928, upload-time = "2026-01-14T23:14:58.312Z" }, - { url = "https://files.pythonhosted.org/packages/f4/f5/13bf65864fc314f68cdd6d8ca94adcab064d4d39dbd0b10fef29a9da48fc/regex-2026.1.15-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:2b091aefc05c78d286657cd4db95f2e6313375ff65dcf085e42e4c04d9c8d410", size = 858607, upload-time = "2026-01-14T23:15:00.657Z" }, - { url = "https://files.pythonhosted.org/packages/a3/31/040e589834d7a439ee43fb0e1e902bc81bd58a5ba81acffe586bb3321d35/regex-2026.1.15-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:57e7d17f59f9ebfa9667e6e5a1c0127b96b87cb9cede8335482451ed00788ba4", size = 763729, upload-time = "2026-01-14T23:15:02.248Z" }, - { url = "https://files.pythonhosted.org/packages/9b/84/6921e8129687a427edf25a34a5594b588b6d88f491320b9de5b6339a4fcb/regex-2026.1.15-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:c6c4dcdfff2c08509faa15d36ba7e5ef5fcfab25f1e8f85a0c8f45bc3a30725d", size = 850697, upload-time = "2026-01-14T23:15:03.878Z" }, - { url = "https://files.pythonhosted.org/packages/8a/87/3d06143d4b128f4229158f2de5de6c8f2485170c7221e61bf381313314b2/regex-2026.1.15-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:cf8ff04c642716a7f2048713ddc6278c5fd41faa3b9cab12607c7abecd012c22", size = 789849, upload-time = "2026-01-14T23:15:06.102Z" }, - { url = "https://files.pythonhosted.org/packages/77/69/c50a63842b6bd48850ebc7ab22d46e7a2a32d824ad6c605b218441814639/regex-2026.1.15-cp312-cp312-win32.whl", hash = "sha256:82345326b1d8d56afbe41d881fdf62f1926d7264b2fc1537f99ae5da9aad7913", size = 266279, upload-time = "2026-01-14T23:15:07.678Z" }, - { url = "https://files.pythonhosted.org/packages/f2/36/39d0b29d087e2b11fd8191e15e81cce1b635fcc845297c67f11d0d19274d/regex-2026.1.15-cp312-cp312-win_amd64.whl", hash = "sha256:4def140aa6156bc64ee9912383d4038f3fdd18fee03a6f222abd4de6357ce42a", size = 277166, upload-time = "2026-01-14T23:15:09.257Z" }, - { url = "https://files.pythonhosted.org/packages/28/32/5b8e476a12262748851fa8ab1b0be540360692325975b094e594dfebbb52/regex-2026.1.15-cp312-cp312-win_arm64.whl", hash = "sha256:c6c565d9a6e1a8d783c1948937ffc377dd5771e83bd56de8317c450a954d2056", size = 270415, upload-time = "2026-01-14T23:15:10.743Z" }, - { url = "https://files.pythonhosted.org/packages/f8/2e/6870bb16e982669b674cce3ee9ff2d1d46ab80528ee6bcc20fb2292efb60/regex-2026.1.15-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:e69d0deeb977ffe7ed3d2e4439360089f9c3f217ada608f0f88ebd67afb6385e", size = 489164, upload-time = "2026-01-14T23:15:13.962Z" }, - { url = "https://files.pythonhosted.org/packages/dc/67/9774542e203849b0286badf67199970a44ebdb0cc5fb739f06e47ada72f8/regex-2026.1.15-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:3601ffb5375de85a16f407854d11cca8fe3f5febbe3ac78fb2866bb220c74d10", size = 291218, upload-time = "2026-01-14T23:15:15.647Z" }, - { url = "https://files.pythonhosted.org/packages/b2/87/b0cda79f22b8dee05f774922a214da109f9a4c0eca5da2c9d72d77ea062c/regex-2026.1.15-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:4c5ef43b5c2d4114eb8ea424bb8c9cec01d5d17f242af88b2448f5ee81caadbc", size = 288895, upload-time = "2026-01-14T23:15:17.788Z" }, - { url = "https://files.pythonhosted.org/packages/3b/6a/0041f0a2170d32be01ab981d6346c83a8934277d82c780d60b127331f264/regex-2026.1.15-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:968c14d4f03e10b2fd960f1d5168c1f0ac969381d3c1fcc973bc45fb06346599", size = 798680, upload-time = "2026-01-14T23:15:19.342Z" }, - { url = "https://files.pythonhosted.org/packages/58/de/30e1cfcdbe3e891324aa7568b7c968771f82190df5524fabc1138cb2d45a/regex-2026.1.15-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:56a5595d0f892f214609c9f76b41b7428bed439d98dc961efafdd1354d42baae", size = 864210, upload-time = "2026-01-14T23:15:22.005Z" }, - { url = "https://files.pythonhosted.org/packages/64/44/4db2f5c5ca0ccd40ff052ae7b1e9731352fcdad946c2b812285a7505ca75/regex-2026.1.15-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:0bf650f26087363434c4e560011f8e4e738f6f3e029b85d4904c50135b86cfa5", size = 912358, upload-time = "2026-01-14T23:15:24.569Z" }, - { url = "https://files.pythonhosted.org/packages/79/b6/e6a5665d43a7c42467138c8a2549be432bad22cbd206f5ec87162de74bd7/regex-2026.1.15-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:18388a62989c72ac24de75f1449d0fb0b04dfccd0a1a7c1c43af5eb503d890f6", size = 803583, upload-time = "2026-01-14T23:15:26.526Z" }, - { url = "https://files.pythonhosted.org/packages/e7/53/7cd478222169d85d74d7437e74750005e993f52f335f7c04ff7adfda3310/regex-2026.1.15-cp313-cp313-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:6d220a2517f5893f55daac983bfa9fe998a7dbcaee4f5d27a88500f8b7873788", size = 775782, upload-time = "2026-01-14T23:15:29.352Z" }, - { url = "https://files.pythonhosted.org/packages/ca/b5/75f9a9ee4b03a7c009fe60500fe550b45df94f0955ca29af16333ef557c5/regex-2026.1.15-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:c9c08c2fbc6120e70abff5d7f28ffb4d969e14294fb2143b4b5c7d20e46d1714", size = 787978, upload-time = "2026-01-14T23:15:31.295Z" }, - { url = "https://files.pythonhosted.org/packages/72/b3/79821c826245bbe9ccbb54f6eadb7879c722fd3e0248c17bfc90bf54e123/regex-2026.1.15-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:7ef7d5d4bd49ec7364315167a4134a015f61e8266c6d446fc116a9ac4456e10d", size = 858550, upload-time = "2026-01-14T23:15:33.558Z" }, - { url = "https://files.pythonhosted.org/packages/4a/85/2ab5f77a1c465745bfbfcb3ad63178a58337ae8d5274315e2cc623a822fa/regex-2026.1.15-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:6e42844ad64194fa08d5ccb75fe6a459b9b08e6d7296bd704460168d58a388f3", size = 763747, upload-time = "2026-01-14T23:15:35.206Z" }, - { url = "https://files.pythonhosted.org/packages/6d/84/c27df502d4bfe2873a3e3a7cf1bdb2b9cc10284d1a44797cf38bed790470/regex-2026.1.15-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:cfecdaa4b19f9ca534746eb3b55a5195d5c95b88cac32a205e981ec0a22b7d31", size = 850615, upload-time = "2026-01-14T23:15:37.523Z" }, - { url = "https://files.pythonhosted.org/packages/7d/b7/658a9782fb253680aa8ecb5ccbb51f69e088ed48142c46d9f0c99b46c575/regex-2026.1.15-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:08df9722d9b87834a3d701f3fca570b2be115654dbfd30179f30ab2f39d606d3", size = 789951, upload-time = "2026-01-14T23:15:39.582Z" }, - { url = "https://files.pythonhosted.org/packages/fc/2a/5928af114441e059f15b2f63e188bd00c6529b3051c974ade7444b85fcda/regex-2026.1.15-cp313-cp313-win32.whl", hash = "sha256:d426616dae0967ca225ab12c22274eb816558f2f99ccb4a1d52ca92e8baf180f", size = 266275, upload-time = "2026-01-14T23:15:42.108Z" }, - { url = "https://files.pythonhosted.org/packages/4f/16/5bfbb89e435897bff28cf0352a992ca719d9e55ebf8b629203c96b6ce4f7/regex-2026.1.15-cp313-cp313-win_amd64.whl", hash = "sha256:febd38857b09867d3ed3f4f1af7d241c5c50362e25ef43034995b77a50df494e", size = 277145, upload-time = "2026-01-14T23:15:44.244Z" }, - { url = "https://files.pythonhosted.org/packages/56/c1/a09ff7392ef4233296e821aec5f78c51be5e91ffde0d163059e50fd75835/regex-2026.1.15-cp313-cp313-win_arm64.whl", hash = "sha256:8e32f7896f83774f91499d239e24cebfadbc07639c1494bb7213983842348337", size = 270411, upload-time = "2026-01-14T23:15:45.858Z" }, - { url = "https://files.pythonhosted.org/packages/3c/38/0cfd5a78e5c6db00e6782fdae70458f89850ce95baa5e8694ab91d89744f/regex-2026.1.15-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:ec94c04149b6a7b8120f9f44565722c7ae31b7a6d2275569d2eefa76b83da3be", size = 492068, upload-time = "2026-01-14T23:15:47.616Z" }, - { url = "https://files.pythonhosted.org/packages/50/72/6c86acff16cb7c959c4355826bbf06aad670682d07c8f3998d9ef4fee7cd/regex-2026.1.15-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:40c86d8046915bb9aeb15d3f3f15b6fd500b8ea4485b30e1bbc799dab3fe29f8", size = 292756, upload-time = "2026-01-14T23:15:49.307Z" }, - { url = "https://files.pythonhosted.org/packages/4e/58/df7fb69eadfe76526ddfce28abdc0af09ffe65f20c2c90932e89d705153f/regex-2026.1.15-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:726ea4e727aba21643205edad8f2187ec682d3305d790f73b7a51c7587b64bdd", size = 291114, upload-time = "2026-01-14T23:15:51.484Z" }, - { url = "https://files.pythonhosted.org/packages/ed/6c/a4011cd1cf96b90d2cdc7e156f91efbd26531e822a7fbb82a43c1016678e/regex-2026.1.15-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:1cb740d044aff31898804e7bf1181cc72c03d11dfd19932b9911ffc19a79070a", size = 807524, upload-time = "2026-01-14T23:15:53.102Z" }, - { url = "https://files.pythonhosted.org/packages/1d/25/a53ffb73183f69c3e9f4355c4922b76d2840aee160af6af5fac229b6201d/regex-2026.1.15-cp313-cp313t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:05d75a668e9ea16f832390d22131fe1e8acc8389a694c8febc3e340b0f810b93", size = 873455, upload-time = "2026-01-14T23:15:54.956Z" }, - { url = "https://files.pythonhosted.org/packages/66/0b/8b47fc2e8f97d9b4a851736f3890a5f786443aa8901061c55f24c955f45b/regex-2026.1.15-cp313-cp313t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d991483606f3dbec93287b9f35596f41aa2e92b7c2ebbb935b63f409e243c9af", size = 915007, upload-time = "2026-01-14T23:15:57.041Z" }, - { url = "https://files.pythonhosted.org/packages/c2/fa/97de0d681e6d26fabe71968dbee06dd52819e9a22fdce5dac7256c31ed84/regex-2026.1.15-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:194312a14819d3e44628a44ed6fea6898fdbecb0550089d84c403475138d0a09", size = 812794, upload-time = "2026-01-14T23:15:58.916Z" }, - { url = "https://files.pythonhosted.org/packages/22/38/e752f94e860d429654aa2b1c51880bff8dfe8f084268258adf9151cf1f53/regex-2026.1.15-cp313-cp313t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:fe2fda4110a3d0bc163c2e0664be44657431440722c5c5315c65155cab92f9e5", size = 781159, upload-time = "2026-01-14T23:16:00.817Z" }, - { url = "https://files.pythonhosted.org/packages/e9/a7/d739ffaef33c378fc888302a018d7f81080393d96c476b058b8c64fd2b0d/regex-2026.1.15-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:124dc36c85d34ef2d9164da41a53c1c8c122cfb1f6e1ec377a1f27ee81deb794", size = 795558, upload-time = "2026-01-14T23:16:03.267Z" }, - { url = "https://files.pythonhosted.org/packages/3e/c4/542876f9a0ac576100fc73e9c75b779f5c31e3527576cfc9cb3009dcc58a/regex-2026.1.15-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:a1774cd1981cd212506a23a14dba7fdeaee259f5deba2df6229966d9911e767a", size = 868427, upload-time = "2026-01-14T23:16:05.646Z" }, - { url = "https://files.pythonhosted.org/packages/fc/0f/d5655bea5b22069e32ae85a947aa564912f23758e112cdb74212848a1a1b/regex-2026.1.15-cp313-cp313t-musllinux_1_2_riscv64.whl", hash = "sha256:b5f7d8d2867152cdb625e72a530d2ccb48a3d199159144cbdd63870882fb6f80", size = 769939, upload-time = "2026-01-14T23:16:07.542Z" }, - { url = "https://files.pythonhosted.org/packages/20/06/7e18a4fa9d326daeda46d471a44ef94201c46eaa26dbbb780b5d92cbfdda/regex-2026.1.15-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:492534a0ab925d1db998defc3c302dae3616a2fc3fe2e08db1472348f096ddf2", size = 854753, upload-time = "2026-01-14T23:16:10.395Z" }, - { url = "https://files.pythonhosted.org/packages/3b/67/dc8946ef3965e166f558ef3b47f492bc364e96a265eb4a2bb3ca765c8e46/regex-2026.1.15-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:c661fc820cfb33e166bf2450d3dadbda47c8d8981898adb9b6fe24e5e582ba60", size = 799559, upload-time = "2026-01-14T23:16:12.347Z" }, - { url = "https://files.pythonhosted.org/packages/a5/61/1bba81ff6d50c86c65d9fd84ce9699dd106438ee4cdb105bf60374ee8412/regex-2026.1.15-cp313-cp313t-win32.whl", hash = "sha256:99ad739c3686085e614bf77a508e26954ff1b8f14da0e3765ff7abbf7799f952", size = 268879, upload-time = "2026-01-14T23:16:14.049Z" }, - { url = "https://files.pythonhosted.org/packages/e9/5e/cef7d4c5fb0ea3ac5c775fd37db5747f7378b29526cc83f572198924ff47/regex-2026.1.15-cp313-cp313t-win_amd64.whl", hash = "sha256:32655d17905e7ff8ba5c764c43cb124e34a9245e45b83c22e81041e1071aee10", size = 280317, upload-time = "2026-01-14T23:16:15.718Z" }, - { url = "https://files.pythonhosted.org/packages/b4/52/4317f7a5988544e34ab57b4bde0f04944c4786128c933fb09825924d3e82/regex-2026.1.15-cp313-cp313t-win_arm64.whl", hash = "sha256:b2a13dd6a95e95a489ca242319d18fc02e07ceb28fa9ad146385194d95b3c829", size = 271551, upload-time = "2026-01-14T23:16:17.533Z" }, - { url = "https://files.pythonhosted.org/packages/52/0a/47fa888ec7cbbc7d62c5f2a6a888878e76169170ead271a35239edd8f0e8/regex-2026.1.15-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:d920392a6b1f353f4aa54328c867fec3320fa50657e25f64abf17af054fc97ac", size = 489170, upload-time = "2026-01-14T23:16:19.835Z" }, - { url = "https://files.pythonhosted.org/packages/ac/c4/d000e9b7296c15737c9301708e9e7fbdea009f8e93541b6b43bdb8219646/regex-2026.1.15-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:b5a28980a926fa810dbbed059547b02783952e2efd9c636412345232ddb87ff6", size = 291146, upload-time = "2026-01-14T23:16:21.541Z" }, - { url = "https://files.pythonhosted.org/packages/f9/b6/921cc61982e538682bdf3bdf5b2c6ab6b34368da1f8e98a6c1ddc503c9cf/regex-2026.1.15-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:621f73a07595d83f28952d7bd1e91e9d1ed7625fb7af0064d3516674ec93a2a2", size = 288986, upload-time = "2026-01-14T23:16:23.381Z" }, - { url = "https://files.pythonhosted.org/packages/ca/33/eb7383dde0bbc93f4fb9d03453aab97e18ad4024ac7e26cef8d1f0a2cff0/regex-2026.1.15-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:3d7d92495f47567a9b1669c51fc8d6d809821849063d168121ef801bbc213846", size = 799098, upload-time = "2026-01-14T23:16:25.088Z" }, - { url = "https://files.pythonhosted.org/packages/27/56/b664dccae898fc8d8b4c23accd853f723bde0f026c747b6f6262b688029c/regex-2026.1.15-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:8dd16fba2758db7a3780a051f245539c4451ca20910f5a5e6ea1c08d06d4a76b", size = 864980, upload-time = "2026-01-14T23:16:27.297Z" }, - { url = "https://files.pythonhosted.org/packages/16/40/0999e064a170eddd237bae9ccfcd8f28b3aa98a38bf727a086425542a4fc/regex-2026.1.15-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:1e1808471fbe44c1a63e5f577a1d5f02fe5d66031dcbdf12f093ffc1305a858e", size = 911607, upload-time = "2026-01-14T23:16:29.235Z" }, - { url = "https://files.pythonhosted.org/packages/07/78/c77f644b68ab054e5a674fb4da40ff7bffb2c88df58afa82dbf86573092d/regex-2026.1.15-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0751a26ad39d4f2ade8fe16c59b2bf5cb19eb3d2cd543e709e583d559bd9efde", size = 803358, upload-time = "2026-01-14T23:16:31.369Z" }, - { url = "https://files.pythonhosted.org/packages/27/31/d4292ea8566eaa551fafc07797961c5963cf5235c797cc2ae19b85dfd04d/regex-2026.1.15-cp314-cp314-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:0f0c7684c7f9ca241344ff95a1de964f257a5251968484270e91c25a755532c5", size = 775833, upload-time = "2026-01-14T23:16:33.141Z" }, - { url = "https://files.pythonhosted.org/packages/ce/b2/cff3bf2fea4133aa6fb0d1e370b37544d18c8350a2fa118c7e11d1db0e14/regex-2026.1.15-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:74f45d170a21df41508cb67165456538425185baaf686281fa210d7e729abc34", size = 788045, upload-time = "2026-01-14T23:16:35.005Z" }, - { url = "https://files.pythonhosted.org/packages/8d/99/2cb9b69045372ec877b6f5124bda4eb4253bc58b8fe5848c973f752bc52c/regex-2026.1.15-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:f1862739a1ffb50615c0fde6bae6569b5efbe08d98e59ce009f68a336f64da75", size = 859374, upload-time = "2026-01-14T23:16:36.919Z" }, - { url = "https://files.pythonhosted.org/packages/09/16/710b0a5abe8e077b1729a562d2f297224ad079f3a66dce46844c193416c8/regex-2026.1.15-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:453078802f1b9e2b7303fb79222c054cb18e76f7bdc220f7530fdc85d319f99e", size = 763940, upload-time = "2026-01-14T23:16:38.685Z" }, - { url = "https://files.pythonhosted.org/packages/dd/d1/7585c8e744e40eb3d32f119191969b91de04c073fca98ec14299041f6e7e/regex-2026.1.15-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:a30a68e89e5a218b8b23a52292924c1f4b245cb0c68d1cce9aec9bbda6e2c160", size = 850112, upload-time = "2026-01-14T23:16:40.646Z" }, - { url = "https://files.pythonhosted.org/packages/af/d6/43e1dd85df86c49a347aa57c1f69d12c652c7b60e37ec162e3096194a278/regex-2026.1.15-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:9479cae874c81bf610d72b85bb681a94c95722c127b55445285fb0e2c82db8e1", size = 789586, upload-time = "2026-01-14T23:16:42.799Z" }, - { url = "https://files.pythonhosted.org/packages/93/38/77142422f631e013f316aaae83234c629555729a9fbc952b8a63ac91462a/regex-2026.1.15-cp314-cp314-win32.whl", hash = "sha256:d639a750223132afbfb8f429c60d9d318aeba03281a5f1ab49f877456448dcf1", size = 271691, upload-time = "2026-01-14T23:16:44.671Z" }, - { url = "https://files.pythonhosted.org/packages/4a/a9/ab16b4649524ca9e05213c1cdbb7faa85cc2aa90a0230d2f796cbaf22736/regex-2026.1.15-cp314-cp314-win_amd64.whl", hash = "sha256:4161d87f85fa831e31469bfd82c186923070fc970b9de75339b68f0c75b51903", size = 280422, upload-time = "2026-01-14T23:16:46.607Z" }, - { url = "https://files.pythonhosted.org/packages/be/2a/20fd057bf3521cb4791f69f869635f73e0aaf2b9ad2d260f728144f9047c/regex-2026.1.15-cp314-cp314-win_arm64.whl", hash = "sha256:91c5036ebb62663a6b3999bdd2e559fd8456d17e2b485bf509784cd31a8b1705", size = 273467, upload-time = "2026-01-14T23:16:48.967Z" }, - { url = "https://files.pythonhosted.org/packages/ad/77/0b1e81857060b92b9cad239104c46507dd481b3ff1fa79f8e7f865aae38a/regex-2026.1.15-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:ee6854c9000a10938c79238de2379bea30c82e4925a371711af45387df35cab8", size = 492073, upload-time = "2026-01-14T23:16:51.154Z" }, - { url = "https://files.pythonhosted.org/packages/70/f3/f8302b0c208b22c1e4f423147e1913fd475ddd6230565b299925353de644/regex-2026.1.15-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:2c2b80399a422348ce5de4fe40c418d6299a0fa2803dd61dc0b1a2f28e280fcf", size = 292757, upload-time = "2026-01-14T23:16:53.08Z" }, - { url = "https://files.pythonhosted.org/packages/bf/f0/ef55de2460f3b4a6da9d9e7daacd0cb79d4ef75c64a2af316e68447f0df0/regex-2026.1.15-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:dca3582bca82596609959ac39e12b7dad98385b4fefccb1151b937383cec547d", size = 291122, upload-time = "2026-01-14T23:16:55.383Z" }, - { url = "https://files.pythonhosted.org/packages/cf/55/bb8ccbacabbc3a11d863ee62a9f18b160a83084ea95cdfc5d207bfc3dd75/regex-2026.1.15-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:ef71d476caa6692eea743ae5ea23cde3260677f70122c4d258ca952e5c2d4e84", size = 807761, upload-time = "2026-01-14T23:16:57.251Z" }, - { url = "https://files.pythonhosted.org/packages/8f/84/f75d937f17f81e55679a0509e86176e29caa7298c38bd1db7ce9c0bf6075/regex-2026.1.15-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:c243da3436354f4af6c3058a3f81a97d47ea52c9bd874b52fd30274853a1d5df", size = 873538, upload-time = "2026-01-14T23:16:59.349Z" }, - { url = "https://files.pythonhosted.org/packages/b8/d9/0da86327df70349aa8d86390da91171bd3ca4f0e7c1d1d453a9c10344da3/regex-2026.1.15-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:8355ad842a7c7e9e5e55653eade3b7d1885ba86f124dd8ab1f722f9be6627434", size = 915066, upload-time = "2026-01-14T23:17:01.607Z" }, - { url = "https://files.pythonhosted.org/packages/2a/5e/f660fb23fc77baa2a61aa1f1fe3a4eea2bbb8a286ddec148030672e18834/regex-2026.1.15-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:f192a831d9575271a22d804ff1a5355355723f94f31d9eef25f0d45a152fdc1a", size = 812938, upload-time = "2026-01-14T23:17:04.366Z" }, - { url = "https://files.pythonhosted.org/packages/69/33/a47a29bfecebbbfd1e5cd3f26b28020a97e4820f1c5148e66e3b7d4b4992/regex-2026.1.15-cp314-cp314t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:166551807ec20d47ceaeec380081f843e88c8949780cd42c40f18d16168bed10", size = 781314, upload-time = "2026-01-14T23:17:06.378Z" }, - { url = "https://files.pythonhosted.org/packages/65/ec/7ec2bbfd4c3f4e494a24dec4c6943a668e2030426b1b8b949a6462d2c17b/regex-2026.1.15-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:f9ca1cbdc0fbfe5e6e6f8221ef2309988db5bcede52443aeaee9a4ad555e0dac", size = 795652, upload-time = "2026-01-14T23:17:08.521Z" }, - { url = "https://files.pythonhosted.org/packages/46/79/a5d8651ae131fe27d7c521ad300aa7f1c7be1dbeee4d446498af5411b8a9/regex-2026.1.15-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:b30bcbd1e1221783c721483953d9e4f3ab9c5d165aa709693d3f3946747b1aea", size = 868550, upload-time = "2026-01-14T23:17:10.573Z" }, - { url = "https://files.pythonhosted.org/packages/06/b7/25635d2809664b79f183070786a5552dd4e627e5aedb0065f4e3cf8ee37d/regex-2026.1.15-cp314-cp314t-musllinux_1_2_riscv64.whl", hash = "sha256:2a8d7b50c34578d0d3bf7ad58cde9652b7d683691876f83aedc002862a35dc5e", size = 769981, upload-time = "2026-01-14T23:17:12.871Z" }, - { url = "https://files.pythonhosted.org/packages/16/8b/fc3fcbb2393dcfa4a6c5ffad92dc498e842df4581ea9d14309fcd3c55fb9/regex-2026.1.15-cp314-cp314t-musllinux_1_2_s390x.whl", hash = "sha256:9d787e3310c6a6425eb346be4ff2ccf6eece63017916fd77fe8328c57be83521", size = 854780, upload-time = "2026-01-14T23:17:14.837Z" }, - { url = "https://files.pythonhosted.org/packages/d0/38/dde117c76c624713c8a2842530be9c93ca8b606c0f6102d86e8cd1ce8bea/regex-2026.1.15-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:619843841e220adca114118533a574a9cd183ed8a28b85627d2844c500a2b0db", size = 799778, upload-time = "2026-01-14T23:17:17.369Z" }, - { url = "https://files.pythonhosted.org/packages/e3/0d/3a6cfa9ae99606afb612d8fb7a66b245a9d5ff0f29bb347c8a30b6ad561b/regex-2026.1.15-cp314-cp314t-win32.whl", hash = "sha256:e90b8db97f6f2c97eb045b51a6b2c5ed69cedd8392459e0642d4199b94fabd7e", size = 274667, upload-time = "2026-01-14T23:17:19.301Z" }, - { url = "https://files.pythonhosted.org/packages/5b/b2/297293bb0742fd06b8d8e2572db41a855cdf1cae0bf009b1cb74fe07e196/regex-2026.1.15-cp314-cp314t-win_amd64.whl", hash = "sha256:5ef19071f4ac9f0834793af85bd04a920b4407715624e40cb7a0631a11137cdf", size = 284386, upload-time = "2026-01-14T23:17:21.231Z" }, - { url = "https://files.pythonhosted.org/packages/95/e4/a3b9480c78cf8ee86626cb06f8d931d74d775897d44201ccb813097ae697/regex-2026.1.15-cp314-cp314t-win_arm64.whl", hash = "sha256:ca89c5e596fc05b015f27561b3793dc2fa0917ea0d7507eebb448efd35274a70", size = 274837, upload-time = "2026-01-14T23:17:23.146Z" }, -] - -[[package]] -name = "requests" -version = "2.32.5" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "certifi" }, - { name = "charset-normalizer" }, - { name = "idna" }, - { name = "urllib3" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/c9/74/b3ff8e6c8446842c3f5c837e9c3dfcfe2018ea6ecef224c710c85ef728f4/requests-2.32.5.tar.gz", hash = "sha256:dbba0bac56e100853db0ea71b82b4dfd5fe2bf6d3754a8893c3af500cec7d7cf", size = 134517, upload-time = "2025-08-18T20:46:02.573Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl", hash = "sha256:2462f94637a34fd532264295e186976db0f5d453d1cdd31473c85a6a161affb6", size = 64738, upload-time = "2025-08-18T20:46:00.542Z" }, -] - -[[package]] -name = "requests-toolbelt" -version = "1.0.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "requests" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/f3/61/d7545dafb7ac2230c70d38d31cbfe4cc64f7144dc41f6e4e4b78ecd9f5bb/requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6", size = 206888, upload-time = "2023-05-01T04:11:33.229Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/3f/51/d4db610ef29373b879047326cbf6fa98b6c1969d6f6dc423279de2b1be2c/requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06", size = 54481, upload-time = "2023-05-01T04:11:28.427Z" }, -] - -[[package]] -name = "smmap" -version = "5.0.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/44/cd/a040c4b3119bbe532e5b0732286f805445375489fceaec1f48306068ee3b/smmap-5.0.2.tar.gz", hash = "sha256:26ea65a03958fa0c8a1c7e8c7a58fdc77221b8910f6be2131affade476898ad5", size = 22329, upload-time = "2025-01-02T07:14:40.909Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/04/be/d09147ad1ec7934636ad912901c5fd7667e1c858e19d355237db0d0cd5e4/smmap-5.0.2-py3-none-any.whl", hash = "sha256:b30115f0def7d7531d22a0fb6502488d879e75b260a9db4d0819cfb25403af5e", size = 24303, upload-time = "2025-01-02T07:14:38.724Z" }, -] - -[[package]] -name = "sniffio" -version = "1.3.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a2/87/a6771e1546d97e7e041b6ae58d80074f81b7d5121207425c964ddf5cfdbd/sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc", size = 20372, upload-time = "2024-02-25T23:20:04.057Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e9/44/75a9c9421471a6c4805dbf2356f7c181a29c1879239abab1ea2cc8f38b40/sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2", size = 10235, upload-time = "2024-02-25T23:20:01.196Z" }, -] - -[[package]] -name = "sqlalchemy" -version = "2.0.46" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "greenlet", marker = "platform_machine == 'AMD64' or platform_machine == 'WIN32' or platform_machine == 'aarch64' or platform_machine == 'amd64' or platform_machine == 'ppc64le' or platform_machine == 'win32' or platform_machine == 'x86_64'" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/06/aa/9ce0f3e7a9829ead5c8ce549392f33a12c4555a6c0609bb27d882e9c7ddf/sqlalchemy-2.0.46.tar.gz", hash = "sha256:cf36851ee7219c170bb0793dbc3da3e80c582e04a5437bc601bfe8c85c9216d7", size = 9865393, upload-time = "2026-01-21T18:03:45.119Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/69/ac/b42ad16800d0885105b59380ad69aad0cce5a65276e269ce2729a2343b6a/sqlalchemy-2.0.46-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:261c4b1f101b4a411154f1da2b76497d73abbfc42740029205d4d01fa1052684", size = 2154851, upload-time = "2026-01-21T18:27:30.54Z" }, - { url = "https://files.pythonhosted.org/packages/a0/60/d8710068cb79f64d002ebed62a7263c00c8fd95f4ebd4b5be8f7ca93f2bc/sqlalchemy-2.0.46-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:181903fe8c1b9082995325f1b2e84ac078b1189e2819380c2303a5f90e114a62", size = 3311241, upload-time = "2026-01-21T18:32:33.45Z" }, - { url = "https://files.pythonhosted.org/packages/2b/0f/20c71487c7219ab3aa7421c7c62d93824c97c1460f2e8bb72404b0192d13/sqlalchemy-2.0.46-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:590be24e20e2424a4c3c1b0835e9405fa3d0af5823a1a9fc02e5dff56471515f", size = 3310741, upload-time = "2026-01-21T18:44:57.887Z" }, - { url = "https://files.pythonhosted.org/packages/65/80/d26d00b3b249ae000eee4db206fcfc564bf6ca5030e4747adf451f4b5108/sqlalchemy-2.0.46-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:7568fe771f974abadce52669ef3a03150ff03186d8eb82613bc8adc435a03f01", size = 3263116, upload-time = "2026-01-21T18:32:35.044Z" }, - { url = "https://files.pythonhosted.org/packages/da/ee/74dda7506640923821340541e8e45bd3edd8df78664f1f2e0aae8077192b/sqlalchemy-2.0.46-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ebf7e1e78af38047e08836d33502c7a278915698b7c2145d045f780201679999", size = 3285327, upload-time = "2026-01-21T18:44:59.254Z" }, - { url = "https://files.pythonhosted.org/packages/9f/25/6dcf8abafff1389a21c7185364de145107b7394ecdcb05233815b236330d/sqlalchemy-2.0.46-cp311-cp311-win32.whl", hash = "sha256:9d80ea2ac519c364a7286e8d765d6cd08648f5b21ca855a8017d9871f075542d", size = 2114564, upload-time = "2026-01-21T18:33:15.85Z" }, - { url = "https://files.pythonhosted.org/packages/93/5f/e081490f8523adc0088f777e4ebad3cac21e498ec8a3d4067074e21447a1/sqlalchemy-2.0.46-cp311-cp311-win_amd64.whl", hash = "sha256:585af6afe518732d9ccd3aea33af2edaae4a7aa881af5d8f6f4fe3a368699597", size = 2139233, upload-time = "2026-01-21T18:33:17.528Z" }, - { url = "https://files.pythonhosted.org/packages/b6/35/d16bfa235c8b7caba3730bba43e20b1e376d2224f407c178fbf59559f23e/sqlalchemy-2.0.46-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:3a9a72b0da8387f15d5810f1facca8f879de9b85af8c645138cba61ea147968c", size = 2153405, upload-time = "2026-01-21T19:05:54.143Z" }, - { url = "https://files.pythonhosted.org/packages/06/6c/3192e24486749862f495ddc6584ed730c0c994a67550ec395d872a2ad650/sqlalchemy-2.0.46-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:2347c3f0efc4de367ba00218e0ae5c4ba2306e47216ef80d6e31761ac97cb0b9", size = 3334702, upload-time = "2026-01-21T18:46:45.384Z" }, - { url = "https://files.pythonhosted.org/packages/ea/a2/b9f33c8d68a3747d972a0bb758c6b63691f8fb8a49014bc3379ba15d4274/sqlalchemy-2.0.46-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9094c8b3197db12aa6f05c51c05daaad0a92b8c9af5388569847b03b1007fb1b", size = 3347664, upload-time = "2026-01-21T18:40:09.979Z" }, - { url = "https://files.pythonhosted.org/packages/aa/d2/3e59e2a91eaec9db7e8dc6b37b91489b5caeb054f670f32c95bcba98940f/sqlalchemy-2.0.46-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:37fee2164cf21417478b6a906adc1a91d69ae9aba8f9533e67ce882f4bb1de53", size = 3277372, upload-time = "2026-01-21T18:46:47.168Z" }, - { url = "https://files.pythonhosted.org/packages/dd/dd/67bc2e368b524e2192c3927b423798deda72c003e73a1e94c21e74b20a85/sqlalchemy-2.0.46-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b1e14b2f6965a685c7128bd315e27387205429c2e339eeec55cb75ca4ab0ea2e", size = 3312425, upload-time = "2026-01-21T18:40:11.548Z" }, - { url = "https://files.pythonhosted.org/packages/43/82/0ecd68e172bfe62247e96cb47867c2d68752566811a4e8c9d8f6e7c38a65/sqlalchemy-2.0.46-cp312-cp312-win32.whl", hash = "sha256:412f26bb4ba942d52016edc8d12fb15d91d3cd46b0047ba46e424213ad407bcb", size = 2113155, upload-time = "2026-01-21T18:42:49.748Z" }, - { url = "https://files.pythonhosted.org/packages/bc/2a/2821a45742073fc0331dc132552b30de68ba9563230853437cac54b2b53e/sqlalchemy-2.0.46-cp312-cp312-win_amd64.whl", hash = "sha256:ea3cd46b6713a10216323cda3333514944e510aa691c945334713fca6b5279ff", size = 2140078, upload-time = "2026-01-21T18:42:51.197Z" }, - { url = "https://files.pythonhosted.org/packages/b3/4b/fa7838fe20bb752810feed60e45625a9a8b0102c0c09971e2d1d95362992/sqlalchemy-2.0.46-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:93a12da97cca70cea10d4b4fc602589c4511f96c1f8f6c11817620c021d21d00", size = 2150268, upload-time = "2026-01-21T19:05:56.621Z" }, - { url = "https://files.pythonhosted.org/packages/46/c1/b34dccd712e8ea846edf396e00973dda82d598cb93762e55e43e6835eba9/sqlalchemy-2.0.46-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:af865c18752d416798dae13f83f38927c52f085c52e2f32b8ab0fef46fdd02c2", size = 3276511, upload-time = "2026-01-21T18:46:49.022Z" }, - { url = "https://files.pythonhosted.org/packages/96/48/a04d9c94753e5d5d096c628c82a98c4793b9c08ca0e7155c3eb7d7db9f24/sqlalchemy-2.0.46-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:8d679b5f318423eacb61f933a9a0f75535bfca7056daeadbf6bd5bcee6183aee", size = 3292881, upload-time = "2026-01-21T18:40:13.089Z" }, - { url = "https://files.pythonhosted.org/packages/be/f4/06eda6e91476f90a7d8058f74311cb65a2fb68d988171aced81707189131/sqlalchemy-2.0.46-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:64901e08c33462acc9ec3bad27fc7a5c2b6491665f2aa57564e57a4f5d7c52ad", size = 3224559, upload-time = "2026-01-21T18:46:50.974Z" }, - { url = "https://files.pythonhosted.org/packages/ab/a2/d2af04095412ca6345ac22b33b89fe8d6f32a481e613ffcb2377d931d8d0/sqlalchemy-2.0.46-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e8ac45e8f4eaac0f9f8043ea0e224158855c6a4329fd4ee37c45c61e3beb518e", size = 3262728, upload-time = "2026-01-21T18:40:14.883Z" }, - { url = "https://files.pythonhosted.org/packages/31/48/1980c7caa5978a3b8225b4d230e69a2a6538a3562b8b31cea679b6933c83/sqlalchemy-2.0.46-cp313-cp313-win32.whl", hash = "sha256:8d3b44b3d0ab2f1319d71d9863d76eeb46766f8cf9e921ac293511804d39813f", size = 2111295, upload-time = "2026-01-21T18:42:52.366Z" }, - { url = "https://files.pythonhosted.org/packages/2d/54/f8d65bbde3d877617c4720f3c9f60e99bb7266df0d5d78b6e25e7c149f35/sqlalchemy-2.0.46-cp313-cp313-win_amd64.whl", hash = "sha256:77f8071d8fbcbb2dd11b7fd40dedd04e8ebe2eb80497916efedba844298065ef", size = 2137076, upload-time = "2026-01-21T18:42:53.924Z" }, - { url = "https://files.pythonhosted.org/packages/56/ba/9be4f97c7eb2b9d5544f2624adfc2853e796ed51d2bb8aec90bc94b7137e/sqlalchemy-2.0.46-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:a1e8cc6cc01da346dc92d9509a63033b9b1bda4fed7a7a7807ed385c7dccdc10", size = 3556533, upload-time = "2026-01-21T18:33:06.636Z" }, - { url = "https://files.pythonhosted.org/packages/20/a6/b1fc6634564dbb4415b7ed6419cdfeaadefd2c39cdab1e3aa07a5f2474c2/sqlalchemy-2.0.46-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:96c7cca1a4babaaf3bfff3e4e606e38578856917e52f0384635a95b226c87764", size = 3523208, upload-time = "2026-01-21T18:45:08.436Z" }, - { url = "https://files.pythonhosted.org/packages/a1/d8/41e0bdfc0f930ff236f86fccd12962d8fa03713f17ed57332d38af6a3782/sqlalchemy-2.0.46-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:b2a9f9aee38039cf4755891a1e50e1effcc42ea6ba053743f452c372c3152b1b", size = 3464292, upload-time = "2026-01-21T18:33:08.208Z" }, - { url = "https://files.pythonhosted.org/packages/f0/8b/9dcbec62d95bea85f5ecad9b8d65b78cc30fb0ffceeb3597961f3712549b/sqlalchemy-2.0.46-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:db23b1bf8cfe1f7fda19018e7207b20cdb5168f83c437ff7e95d19e39289c447", size = 3473497, upload-time = "2026-01-21T18:45:10.552Z" }, - { url = "https://files.pythonhosted.org/packages/e9/f8/5ecdfc73383ec496de038ed1614de9e740a82db9ad67e6e4514ebc0708a3/sqlalchemy-2.0.46-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:56bdd261bfd0895452006d5316cbf35739c53b9bb71a170a331fa0ea560b2ada", size = 2152079, upload-time = "2026-01-21T19:05:58.477Z" }, - { url = "https://files.pythonhosted.org/packages/e5/bf/eba3036be7663ce4d9c050bc3d63794dc29fbe01691f2bf5ccb64e048d20/sqlalchemy-2.0.46-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:33e462154edb9493f6c3ad2125931e273bbd0be8ae53f3ecd1c161ea9a1dd366", size = 3272216, upload-time = "2026-01-21T18:46:52.634Z" }, - { url = "https://files.pythonhosted.org/packages/05/45/1256fb597bb83b58a01ddb600c59fe6fdf0e5afe333f0456ed75c0f8d7bd/sqlalchemy-2.0.46-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9bcdce05f056622a632f1d44bb47dbdb677f58cad393612280406ce37530eb6d", size = 3277208, upload-time = "2026-01-21T18:40:16.38Z" }, - { url = "https://files.pythonhosted.org/packages/d9/a0/2053b39e4e63b5d7ceb3372cface0859a067c1ddbd575ea7e9985716f771/sqlalchemy-2.0.46-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:8e84b09a9b0f19accedcbeff5c2caf36e0dd537341a33aad8d680336152dc34e", size = 3221994, upload-time = "2026-01-21T18:46:54.622Z" }, - { url = "https://files.pythonhosted.org/packages/1e/87/97713497d9502553c68f105a1cb62786ba1ee91dea3852ae4067ed956a50/sqlalchemy-2.0.46-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:4f52f7291a92381e9b4de9050b0a65ce5d6a763333406861e33906b8aa4906bf", size = 3243990, upload-time = "2026-01-21T18:40:18.253Z" }, - { url = "https://files.pythonhosted.org/packages/a8/87/5d1b23548f420ff823c236f8bea36b1a997250fd2f892e44a3838ca424f4/sqlalchemy-2.0.46-cp314-cp314-win32.whl", hash = "sha256:70ed2830b169a9960193f4d4322d22be5c0925357d82cbf485b3369893350908", size = 2114215, upload-time = "2026-01-21T18:42:55.232Z" }, - { url = "https://files.pythonhosted.org/packages/3a/20/555f39cbcf0c10cf452988b6a93c2a12495035f68b3dbd1a408531049d31/sqlalchemy-2.0.46-cp314-cp314-win_amd64.whl", hash = "sha256:3c32e993bc57be6d177f7d5d31edb93f30726d798ad86ff9066d75d9bf2e0b6b", size = 2139867, upload-time = "2026-01-21T18:42:56.474Z" }, - { url = "https://files.pythonhosted.org/packages/3e/f0/f96c8057c982d9d8a7a68f45d69c674bc6f78cad401099692fe16521640a/sqlalchemy-2.0.46-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4dafb537740eef640c4d6a7c254611dca2df87eaf6d14d6a5fca9d1f4c3fc0fa", size = 3561202, upload-time = "2026-01-21T18:33:10.337Z" }, - { url = "https://files.pythonhosted.org/packages/d7/53/3b37dda0a5b137f21ef608d8dfc77b08477bab0fe2ac9d3e0a66eaeab6fc/sqlalchemy-2.0.46-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:42a1643dc5427b69aca967dae540a90b0fbf57eaf248f13a90ea5930e0966863", size = 3526296, upload-time = "2026-01-21T18:45:12.657Z" }, - { url = "https://files.pythonhosted.org/packages/33/75/f28622ba6dde79cd545055ea7bd4062dc934e0621f7b3be2891f8563f8de/sqlalchemy-2.0.46-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:ff33c6e6ad006bbc0f34f5faf941cfc62c45841c64c0a058ac38c799f15b5ede", size = 3470008, upload-time = "2026-01-21T18:33:11.725Z" }, - { url = "https://files.pythonhosted.org/packages/a9/42/4afecbbc38d5e99b18acef446453c76eec6fbd03db0a457a12a056836e22/sqlalchemy-2.0.46-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:82ec52100ec1e6ec671563bbd02d7c7c8d0b9e71a0723c72f22ecf52d1755330", size = 3476137, upload-time = "2026-01-21T18:45:15.001Z" }, - { url = "https://files.pythonhosted.org/packages/fc/a1/9c4efa03300926601c19c18582531b45aededfb961ab3c3585f1e24f120b/sqlalchemy-2.0.46-py3-none-any.whl", hash = "sha256:f9c11766e7e7c0a2767dda5acb006a118640c9fc0a4104214b96269bfb78399e", size = 1937882, upload-time = "2026-01-21T18:22:10.456Z" }, -] - -[[package]] -name = "sseclient-py" -version = "1.9.0" -source = { registry = "https://pypi.org/simple" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/4d/2e/59920f7d66b7f9932a3d83dd0ec53fab001be1e058bf582606fe414a5198/sseclient_py-1.9.0-py3-none-any.whl", hash = "sha256:340062b1587fc2880892811e2ab5b176d98ef3eee98b3672ff3a3ba1e8ed0f6f", size = 8351, upload-time = "2026-01-02T23:39:30.995Z" }, -] - -[[package]] -name = "tenacity" -version = "9.1.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/0a/d4/2b0cd0fe285e14b36db076e78c93766ff1d529d70408bd1d2a5a84f1d929/tenacity-9.1.2.tar.gz", hash = "sha256:1169d376c297e7de388d18b4481760d478b0e99a777cad3a9c86e556f4b697cb", size = 48036, upload-time = "2025-04-02T08:25:09.966Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e5/30/643397144bfbfec6f6ef821f36f33e57d35946c44a2352d3c9f0ae847619/tenacity-9.1.2-py3-none-any.whl", hash = "sha256:f77bf36710d8b73a50b2dd155c97b870017ad21afe6ab300326b0371b3b05138", size = 28248, upload-time = "2025-04-02T08:25:07.678Z" }, -] - -[[package]] -name = "text-unidecode" -version = "1.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ab/e2/e9a00f0ccb71718418230718b3d900e71a5d16e701a3dae079a21e9cd8f8/text-unidecode-1.3.tar.gz", hash = "sha256:bad6603bb14d279193107714b288be206cac565dfa49aa5b105294dd5c4aab93", size = 76885, upload-time = "2019-08-30T21:36:45.405Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a6/a5/c0b6468d3824fe3fde30dbb5e1f687b291608f9473681bbf7dabbf5a87d7/text_unidecode-1.3-py2.py3-none-any.whl", hash = "sha256:1311f10e8b895935241623731c2ba64f4c455287888b18189350b67134a822e8", size = 78154, upload-time = "2019-08-30T21:37:03.543Z" }, -] - -[[package]] -name = "tiktoken" -version = "0.12.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "regex" }, - { name = "requests" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/7d/ab/4d017d0f76ec3171d469d80fc03dfbb4e48a4bcaddaa831b31d526f05edc/tiktoken-0.12.0.tar.gz", hash = "sha256:b18ba7ee2b093863978fcb14f74b3707cdc8d4d4d3836853ce7ec60772139931", size = 37806, upload-time = "2025-10-06T20:22:45.419Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/de/46/21ea696b21f1d6d1efec8639c204bdf20fde8bafb351e1355c72c5d7de52/tiktoken-0.12.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:6e227c7f96925003487c33b1b32265fad2fbcec2b7cf4817afb76d416f40f6bb", size = 1051565, upload-time = "2025-10-06T20:21:44.566Z" }, - { url = "https://files.pythonhosted.org/packages/c9/d9/35c5d2d9e22bb2a5f74ba48266fb56c63d76ae6f66e02feb628671c0283e/tiktoken-0.12.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c06cf0fcc24c2cb2adb5e185c7082a82cba29c17575e828518c2f11a01f445aa", size = 995284, upload-time = "2025-10-06T20:21:45.622Z" }, - { url = "https://files.pythonhosted.org/packages/01/84/961106c37b8e49b9fdcf33fe007bb3a8fdcc380c528b20cc7fbba80578b8/tiktoken-0.12.0-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:f18f249b041851954217e9fd8e5c00b024ab2315ffda5ed77665a05fa91f42dc", size = 1129201, upload-time = "2025-10-06T20:21:47.074Z" }, - { url = "https://files.pythonhosted.org/packages/6a/d0/3d9275198e067f8b65076a68894bb52fd253875f3644f0a321a720277b8a/tiktoken-0.12.0-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:47a5bc270b8c3db00bb46ece01ef34ad050e364b51d406b6f9730b64ac28eded", size = 1152444, upload-time = "2025-10-06T20:21:48.139Z" }, - { url = "https://files.pythonhosted.org/packages/78/db/a58e09687c1698a7c592e1038e01c206569b86a0377828d51635561f8ebf/tiktoken-0.12.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:508fa71810c0efdcd1b898fda574889ee62852989f7c1667414736bcb2b9a4bd", size = 1195080, upload-time = "2025-10-06T20:21:49.246Z" }, - { url = "https://files.pythonhosted.org/packages/9e/1b/a9e4d2bf91d515c0f74afc526fd773a812232dd6cda33ebea7f531202325/tiktoken-0.12.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:a1af81a6c44f008cba48494089dd98cccb8b313f55e961a52f5b222d1e507967", size = 1255240, upload-time = "2025-10-06T20:21:50.274Z" }, - { url = "https://files.pythonhosted.org/packages/9d/15/963819345f1b1fb0809070a79e9dd96938d4ca41297367d471733e79c76c/tiktoken-0.12.0-cp311-cp311-win_amd64.whl", hash = "sha256:3e68e3e593637b53e56f7237be560f7a394451cb8c11079755e80ae64b9e6def", size = 879422, upload-time = "2025-10-06T20:21:51.734Z" }, - { url = "https://files.pythonhosted.org/packages/a4/85/be65d39d6b647c79800fd9d29241d081d4eeb06271f383bb87200d74cf76/tiktoken-0.12.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:b97f74aca0d78a1ff21b8cd9e9925714c15a9236d6ceacf5c7327c117e6e21e8", size = 1050728, upload-time = "2025-10-06T20:21:52.756Z" }, - { url = "https://files.pythonhosted.org/packages/4a/42/6573e9129bc55c9bf7300b3a35bef2c6b9117018acca0dc760ac2d93dffe/tiktoken-0.12.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:2b90f5ad190a4bb7c3eb30c5fa32e1e182ca1ca79f05e49b448438c3e225a49b", size = 994049, upload-time = "2025-10-06T20:21:53.782Z" }, - { url = "https://files.pythonhosted.org/packages/66/c5/ed88504d2f4a5fd6856990b230b56d85a777feab84e6129af0822f5d0f70/tiktoken-0.12.0-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:65b26c7a780e2139e73acc193e5c63ac754021f160df919add909c1492c0fb37", size = 1129008, upload-time = "2025-10-06T20:21:54.832Z" }, - { url = "https://files.pythonhosted.org/packages/f4/90/3dae6cc5436137ebd38944d396b5849e167896fc2073da643a49f372dc4f/tiktoken-0.12.0-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:edde1ec917dfd21c1f2f8046b86348b0f54a2c0547f68149d8600859598769ad", size = 1152665, upload-time = "2025-10-06T20:21:56.129Z" }, - { url = "https://files.pythonhosted.org/packages/a3/fe/26df24ce53ffde419a42f5f53d755b995c9318908288c17ec3f3448313a3/tiktoken-0.12.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:35a2f8ddd3824608b3d650a000c1ef71f730d0c56486845705a8248da00f9fe5", size = 1194230, upload-time = "2025-10-06T20:21:57.546Z" }, - { url = "https://files.pythonhosted.org/packages/20/cc/b064cae1a0e9fac84b0d2c46b89f4e57051a5f41324e385d10225a984c24/tiktoken-0.12.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:83d16643edb7fa2c99eff2ab7733508aae1eebb03d5dfc46f5565862810f24e3", size = 1254688, upload-time = "2025-10-06T20:21:58.619Z" }, - { url = "https://files.pythonhosted.org/packages/81/10/b8523105c590c5b8349f2587e2fdfe51a69544bd5a76295fc20f2374f470/tiktoken-0.12.0-cp312-cp312-win_amd64.whl", hash = "sha256:ffc5288f34a8bc02e1ea7047b8d041104791d2ddbf42d1e5fa07822cbffe16bd", size = 878694, upload-time = "2025-10-06T20:21:59.876Z" }, - { url = "https://files.pythonhosted.org/packages/00/61/441588ee21e6b5cdf59d6870f86beb9789e532ee9718c251b391b70c68d6/tiktoken-0.12.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:775c2c55de2310cc1bc9a3ad8826761cbdc87770e586fd7b6da7d4589e13dab3", size = 1050802, upload-time = "2025-10-06T20:22:00.96Z" }, - { url = "https://files.pythonhosted.org/packages/1f/05/dcf94486d5c5c8d34496abe271ac76c5b785507c8eae71b3708f1ad9b45a/tiktoken-0.12.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a01b12f69052fbe4b080a2cfb867c4de12c704b56178edf1d1d7b273561db160", size = 993995, upload-time = "2025-10-06T20:22:02.788Z" }, - { url = "https://files.pythonhosted.org/packages/a0/70/5163fe5359b943f8db9946b62f19be2305de8c3d78a16f629d4165e2f40e/tiktoken-0.12.0-cp313-cp313-manylinux_2_28_aarch64.whl", hash = "sha256:01d99484dc93b129cd0964f9d34eee953f2737301f18b3c7257bf368d7615baa", size = 1128948, upload-time = "2025-10-06T20:22:03.814Z" }, - { url = "https://files.pythonhosted.org/packages/0c/da/c028aa0babf77315e1cef357d4d768800c5f8a6de04d0eac0f377cb619fa/tiktoken-0.12.0-cp313-cp313-manylinux_2_28_x86_64.whl", hash = "sha256:4a1a4fcd021f022bfc81904a911d3df0f6543b9e7627b51411da75ff2fe7a1be", size = 1151986, upload-time = "2025-10-06T20:22:05.173Z" }, - { url = "https://files.pythonhosted.org/packages/a0/5a/886b108b766aa53e295f7216b509be95eb7d60b166049ce2c58416b25f2a/tiktoken-0.12.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:981a81e39812d57031efdc9ec59fa32b2a5a5524d20d4776574c4b4bd2e9014a", size = 1194222, upload-time = "2025-10-06T20:22:06.265Z" }, - { url = "https://files.pythonhosted.org/packages/f4/f8/4db272048397636ac7a078d22773dd2795b1becee7bc4922fe6207288d57/tiktoken-0.12.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:9baf52f84a3f42eef3ff4e754a0db79a13a27921b457ca9832cf944c6be4f8f3", size = 1255097, upload-time = "2025-10-06T20:22:07.403Z" }, - { url = "https://files.pythonhosted.org/packages/8e/32/45d02e2e0ea2be3a9ed22afc47d93741247e75018aac967b713b2941f8ea/tiktoken-0.12.0-cp313-cp313-win_amd64.whl", hash = "sha256:b8a0cd0c789a61f31bf44851defbd609e8dd1e2c8589c614cc1060940ef1f697", size = 879117, upload-time = "2025-10-06T20:22:08.418Z" }, - { url = "https://files.pythonhosted.org/packages/ce/76/994fc868f88e016e6d05b0da5ac24582a14c47893f4474c3e9744283f1d5/tiktoken-0.12.0-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:d5f89ea5680066b68bcb797ae85219c72916c922ef0fcdd3480c7d2315ffff16", size = 1050309, upload-time = "2025-10-06T20:22:10.939Z" }, - { url = "https://files.pythonhosted.org/packages/f6/b8/57ef1456504c43a849821920d582a738a461b76a047f352f18c0b26c6516/tiktoken-0.12.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:b4e7ed1c6a7a8a60a3230965bdedba8cc58f68926b835e519341413370e0399a", size = 993712, upload-time = "2025-10-06T20:22:12.115Z" }, - { url = "https://files.pythonhosted.org/packages/72/90/13da56f664286ffbae9dbcfadcc625439142675845baa62715e49b87b68b/tiktoken-0.12.0-cp313-cp313t-manylinux_2_28_aarch64.whl", hash = "sha256:fc530a28591a2d74bce821d10b418b26a094bf33839e69042a6e86ddb7a7fb27", size = 1128725, upload-time = "2025-10-06T20:22:13.541Z" }, - { url = "https://files.pythonhosted.org/packages/05/df/4f80030d44682235bdaecd7346c90f67ae87ec8f3df4a3442cb53834f7e4/tiktoken-0.12.0-cp313-cp313t-manylinux_2_28_x86_64.whl", hash = "sha256:06a9f4f49884139013b138920a4c393aa6556b2f8f536345f11819389c703ebb", size = 1151875, upload-time = "2025-10-06T20:22:14.559Z" }, - { url = "https://files.pythonhosted.org/packages/22/1f/ae535223a8c4ef4c0c1192e3f9b82da660be9eb66b9279e95c99288e9dab/tiktoken-0.12.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:04f0e6a985d95913cabc96a741c5ffec525a2c72e9df086ff17ebe35985c800e", size = 1194451, upload-time = "2025-10-06T20:22:15.545Z" }, - { url = "https://files.pythonhosted.org/packages/78/a7/f8ead382fce0243cb625c4f266e66c27f65ae65ee9e77f59ea1653b6d730/tiktoken-0.12.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:0ee8f9ae00c41770b5f9b0bb1235474768884ae157de3beb5439ca0fd70f3e25", size = 1253794, upload-time = "2025-10-06T20:22:16.624Z" }, - { url = "https://files.pythonhosted.org/packages/93/e0/6cc82a562bc6365785a3ff0af27a2a092d57c47d7a81d9e2295d8c36f011/tiktoken-0.12.0-cp313-cp313t-win_amd64.whl", hash = "sha256:dc2dd125a62cb2b3d858484d6c614d136b5b848976794edfb63688d539b8b93f", size = 878777, upload-time = "2025-10-06T20:22:18.036Z" }, - { url = "https://files.pythonhosted.org/packages/72/05/3abc1db5d2c9aadc4d2c76fa5640134e475e58d9fbb82b5c535dc0de9b01/tiktoken-0.12.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:a90388128df3b3abeb2bfd1895b0681412a8d7dc644142519e6f0a97c2111646", size = 1050188, upload-time = "2025-10-06T20:22:19.563Z" }, - { url = "https://files.pythonhosted.org/packages/e3/7b/50c2f060412202d6c95f32b20755c7a6273543b125c0985d6fa9465105af/tiktoken-0.12.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:da900aa0ad52247d8794e307d6446bd3cdea8e192769b56276695d34d2c9aa88", size = 993978, upload-time = "2025-10-06T20:22:20.702Z" }, - { url = "https://files.pythonhosted.org/packages/14/27/bf795595a2b897e271771cd31cb847d479073497344c637966bdf2853da1/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_aarch64.whl", hash = "sha256:285ba9d73ea0d6171e7f9407039a290ca77efcdb026be7769dccc01d2c8d7fff", size = 1129271, upload-time = "2025-10-06T20:22:22.06Z" }, - { url = "https://files.pythonhosted.org/packages/f5/de/9341a6d7a8f1b448573bbf3425fa57669ac58258a667eb48a25dfe916d70/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_x86_64.whl", hash = "sha256:d186a5c60c6a0213f04a7a802264083dea1bbde92a2d4c7069e1a56630aef830", size = 1151216, upload-time = "2025-10-06T20:22:23.085Z" }, - { url = "https://files.pythonhosted.org/packages/75/0d/881866647b8d1be4d67cb24e50d0c26f9f807f994aa1510cb9ba2fe5f612/tiktoken-0.12.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:604831189bd05480f2b885ecd2d1986dc7686f609de48208ebbbddeea071fc0b", size = 1194860, upload-time = "2025-10-06T20:22:24.602Z" }, - { url = "https://files.pythonhosted.org/packages/b3/1e/b651ec3059474dab649b8d5b69f5c65cd8fcd8918568c1935bd4136c9392/tiktoken-0.12.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:8f317e8530bb3a222547b85a58583238c8f74fd7a7408305f9f63246d1a0958b", size = 1254567, upload-time = "2025-10-06T20:22:25.671Z" }, - { url = "https://files.pythonhosted.org/packages/80/57/ce64fd16ac390fafde001268c364d559447ba09b509181b2808622420eec/tiktoken-0.12.0-cp314-cp314-win_amd64.whl", hash = "sha256:399c3dd672a6406719d84442299a490420b458c44d3ae65516302a99675888f3", size = 921067, upload-time = "2025-10-06T20:22:26.753Z" }, - { url = "https://files.pythonhosted.org/packages/ac/a4/72eed53e8976a099539cdd5eb36f241987212c29629d0a52c305173e0a68/tiktoken-0.12.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:c2c714c72bc00a38ca969dae79e8266ddec999c7ceccd603cc4f0d04ccd76365", size = 1050473, upload-time = "2025-10-06T20:22:27.775Z" }, - { url = "https://files.pythonhosted.org/packages/e6/d7/0110b8f54c008466b19672c615f2168896b83706a6611ba6e47313dbc6e9/tiktoken-0.12.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:cbb9a3ba275165a2cb0f9a83f5d7025afe6b9d0ab01a22b50f0e74fee2ad253e", size = 993855, upload-time = "2025-10-06T20:22:28.799Z" }, - { url = "https://files.pythonhosted.org/packages/5f/77/4f268c41a3957c418b084dd576ea2fad2e95da0d8e1ab705372892c2ca22/tiktoken-0.12.0-cp314-cp314t-manylinux_2_28_aarch64.whl", hash = "sha256:dfdfaa5ffff8993a3af94d1125870b1d27aed7cb97aa7eb8c1cefdbc87dbee63", size = 1129022, upload-time = "2025-10-06T20:22:29.981Z" }, - { url = "https://files.pythonhosted.org/packages/4e/2b/fc46c90fe5028bd094cd6ee25a7db321cb91d45dc87531e2bdbb26b4867a/tiktoken-0.12.0-cp314-cp314t-manylinux_2_28_x86_64.whl", hash = "sha256:584c3ad3d0c74f5269906eb8a659c8bfc6144a52895d9261cdaf90a0ae5f4de0", size = 1150736, upload-time = "2025-10-06T20:22:30.996Z" }, - { url = "https://files.pythonhosted.org/packages/28/c0/3c7a39ff68022ddfd7d93f3337ad90389a342f761c4d71de99a3ccc57857/tiktoken-0.12.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:54c891b416a0e36b8e2045b12b33dd66fb34a4fe7965565f1b482da50da3e86a", size = 1194908, upload-time = "2025-10-06T20:22:32.073Z" }, - { url = "https://files.pythonhosted.org/packages/ab/0d/c1ad6f4016a3968c048545f5d9b8ffebf577774b2ede3e2e352553b685fe/tiktoken-0.12.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:5edb8743b88d5be814b1a8a8854494719080c28faaa1ccbef02e87354fe71ef0", size = 1253706, upload-time = "2025-10-06T20:22:33.385Z" }, - { url = "https://files.pythonhosted.org/packages/af/df/c7891ef9d2712ad774777271d39fdef63941ffba0a9d59b7ad1fd2765e57/tiktoken-0.12.0-cp314-cp314t-win_amd64.whl", hash = "sha256:f61c0aea5565ac82e2ec50a05e02a6c44734e91b51c10510b084ea1b8e633a71", size = 920667, upload-time = "2025-10-06T20:22:34.444Z" }, -] - -[[package]] -name = "tqdm" -version = "4.67.3" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "colorama", marker = "sys_platform == 'win32'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/09/a9/6ba95a270c6f1fbcd8dac228323f2777d886cb206987444e4bce66338dd4/tqdm-4.67.3.tar.gz", hash = "sha256:7d825f03f89244ef73f1d4ce193cb1774a8179fd96f31d7e1dcde62092b960bb", size = 169598, upload-time = "2026-02-03T17:35:53.048Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/16/e1/3079a9ff9b8e11b846c6ac5c8b5bfb7ff225eee721825310c91b3b50304f/tqdm-4.67.3-py3-none-any.whl", hash = "sha256:ee1e4c0e59148062281c49d80b25b67771a127c85fc9676d3be5f243206826bf", size = 78374, upload-time = "2026-02-03T17:35:50.982Z" }, -] - -[[package]] -name = "typing-extensions" -version = "4.15.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/72/94/1a15dd82efb362ac84269196e94cf00f187f7ed21c242792a923cdb1c61f/typing_extensions-4.15.0.tar.gz", hash = "sha256:0cea48d173cc12fa28ecabc3b837ea3cf6f38c6d1136f85cbaaf598984861466", size = 109391, upload-time = "2025-08-25T13:49:26.313Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl", hash = "sha256:f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548", size = 44614, upload-time = "2025-08-25T13:49:24.86Z" }, -] - -[[package]] -name = "typing-inspection" -version = "0.4.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/55/e3/70399cb7dd41c10ac53367ae42139cf4b1ca5f36bb3dc6c9d33acdb43655/typing_inspection-0.4.2.tar.gz", hash = "sha256:ba561c48a67c5958007083d386c3295464928b01faa735ab8547c5692e87f464", size = 75949, upload-time = "2025-10-01T02:14:41.687Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/dc/9b/47798a6c91d8bdb567fe2698fe81e0c6b7cb7ef4d13da4114b41d239f65d/typing_inspection-0.4.2-py3-none-any.whl", hash = "sha256:4ed1cacbdc298c220f1bd249ed5287caa16f34d44ef4e9c3d0cbad5b521545e7", size = 14611, upload-time = "2025-10-01T02:14:40.154Z" }, -] - -[[package]] -name = "urllib3" -version = "2.6.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/c7/24/5f1b3bdffd70275f6661c76461e25f024d5a38a46f04aaca912426a2b1d3/urllib3-2.6.3.tar.gz", hash = "sha256:1b62b6884944a57dbe321509ab94fd4d3b307075e0c2eae991ac71ee15ad38ed", size = 435556, upload-time = "2026-01-07T16:24:43.925Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl", hash = "sha256:bf272323e553dfb2e87d9bfd225ca7b0f467b919d7bbd355436d3fd37cb0acd4", size = 131584, upload-time = "2026-01-07T16:24:42.685Z" }, -] - -[[package]] -name = "uuid-utils" -version = "0.14.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/57/7c/3a926e847516e67bc6838634f2e54e24381105b4e80f9338dc35cca0086b/uuid_utils-0.14.0.tar.gz", hash = "sha256:fc5bac21e9933ea6c590433c11aa54aaca599f690c08069e364eb13a12f670b4", size = 22072, upload-time = "2026-01-20T20:37:15.729Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a7/42/42d003f4a99ddc901eef2fd41acb3694163835e037fb6dde79ad68a72342/uuid_utils-0.14.0-cp39-abi3-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:f6695c0bed8b18a904321e115afe73b34444bc8451d0ce3244a1ec3b84deb0e5", size = 601786, upload-time = "2026-01-20T20:37:09.843Z" }, - { url = "https://files.pythonhosted.org/packages/96/e6/775dfb91f74b18f7207e3201eb31ee666d286579990dc69dd50db2d92813/uuid_utils-0.14.0-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:4f0a730bbf2d8bb2c11b93e1005e91769f2f533fa1125ed1f00fd15b6fcc732b", size = 303943, upload-time = "2026-01-20T20:37:18.767Z" }, - { url = "https://files.pythonhosted.org/packages/17/82/ea5f5e85560b08a1f30cdc65f75e76494dc7aba9773f679e7eaa27370229/uuid_utils-0.14.0-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:40ce3fd1a4fdedae618fc3edc8faf91897012469169d600133470f49fd699ed3", size = 340467, upload-time = "2026-01-20T20:37:11.794Z" }, - { url = "https://files.pythonhosted.org/packages/ca/33/54b06415767f4569882e99b6470c6c8eeb97422686a6d432464f9967fd91/uuid_utils-0.14.0-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:09ae4a98416a440e78f7d9543d11b11cae4bab538b7ed94ec5da5221481748f2", size = 346333, upload-time = "2026-01-20T20:37:12.818Z" }, - { url = "https://files.pythonhosted.org/packages/cb/10/a6bce636b8f95e65dc84bf4a58ce8205b8e0a2a300a38cdbc83a3f763d27/uuid_utils-0.14.0-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:971e8c26b90d8ae727e7f2ac3ee23e265971d448b3672882f2eb44828b2b8c3e", size = 470859, upload-time = "2026-01-20T20:37:01.512Z" }, - { url = "https://files.pythonhosted.org/packages/8a/27/84121c51ea72f013f0e03d0886bcdfa96b31c9b83c98300a7bd5cc4fa191/uuid_utils-0.14.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d5cde1fa82804a8f9d2907b7aec2009d440062c63f04abbdb825fce717a5e860", size = 341988, upload-time = "2026-01-20T20:37:22.881Z" }, - { url = "https://files.pythonhosted.org/packages/90/a4/01c1c7af5e6a44f20b40183e8dac37d6ed83e7dc9e8df85370a15959b804/uuid_utils-0.14.0-cp39-abi3-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c7343862a2359e0bd48a7f3dfb5105877a1728677818bb694d9f40703264a2db", size = 365784, upload-time = "2026-01-20T20:37:10.808Z" }, - { url = "https://files.pythonhosted.org/packages/04/f0/65ee43ec617b8b6b1bf2a5aecd56a069a08cca3d9340c1de86024331bde3/uuid_utils-0.14.0-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:c51e4818fdb08ccec12dc7083a01f49507b4608770a0ab22368001685d59381b", size = 523750, upload-time = "2026-01-20T20:37:06.152Z" }, - { url = "https://files.pythonhosted.org/packages/95/d3/6bf503e3f135a5dfe705a65e6f89f19bccd55ac3fb16cb5d3ec5ba5388b8/uuid_utils-0.14.0-cp39-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:181bbcccb6f93d80a8504b5bd47b311a1c31395139596edbc47b154b0685b533", size = 615818, upload-time = "2026-01-20T20:37:21.816Z" }, - { url = "https://files.pythonhosted.org/packages/df/6c/99937dd78d07f73bba831c8dc9469dfe4696539eba2fc269ae1b92752f9e/uuid_utils-0.14.0-cp39-abi3-musllinux_1_2_i686.whl", hash = "sha256:5c8ae96101c3524ba8dbf762b6f05e9e9d896544786c503a727c5bf5cb9af1a7", size = 580831, upload-time = "2026-01-20T20:37:19.691Z" }, - { url = "https://files.pythonhosted.org/packages/44/fa/bbc9e2c25abd09a293b9b097a0d8fc16acd6a92854f0ec080f1ea7ad8bb3/uuid_utils-0.14.0-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:00ac3c6edfdaff7e1eed041f4800ae09a3361287be780d7610a90fdcde9befdc", size = 546333, upload-time = "2026-01-20T20:37:03.117Z" }, - { url = "https://files.pythonhosted.org/packages/e7/9b/e5e99b324b1b5f0c62882230455786df0bc66f67eff3b452447e703f45d2/uuid_utils-0.14.0-cp39-abi3-win32.whl", hash = "sha256:ec2fd80adf8e0e6589d40699e6f6df94c93edcc16dd999be0438dd007c77b151", size = 177319, upload-time = "2026-01-20T20:37:04.208Z" }, - { url = "https://files.pythonhosted.org/packages/d3/28/2c7d417ea483b6ff7820c948678fdf2ac98899dc7e43bb15852faa95acaf/uuid_utils-0.14.0-cp39-abi3-win_amd64.whl", hash = "sha256:efe881eb43a5504fad922644cb93d725fd8a6a6d949bd5a4b4b7d1a1587c7fd1", size = 182566, upload-time = "2026-01-20T20:37:16.868Z" }, - { url = "https://files.pythonhosted.org/packages/b8/86/49e4bdda28e962fbd7266684171ee29b3d92019116971d58783e51770745/uuid_utils-0.14.0-cp39-abi3-win_arm64.whl", hash = "sha256:32b372b8fd4ebd44d3a219e093fe981af4afdeda2994ee7db208ab065cfcd080", size = 182809, upload-time = "2026-01-20T20:37:05.139Z" }, - { url = "https://files.pythonhosted.org/packages/f1/03/1f1146e32e94d1f260dfabc81e1649102083303fb4ad549775c943425d9a/uuid_utils-0.14.0-pp311-pypy311_pp73-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:762e8d67992ac4d2454e24a141a1c82142b5bde10409818c62adbe9924ebc86d", size = 587430, upload-time = "2026-01-20T20:37:24.998Z" }, - { url = "https://files.pythonhosted.org/packages/87/ba/d5a7469362594d885fd9219fe9e851efbe65101d3ef1ef25ea321d7ce841/uuid_utils-0.14.0-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:40be5bf0b13aa849d9062abc86c198be6a25ff35316ce0b89fc25f3bac6d525e", size = 298106, upload-time = "2026-01-20T20:37:23.896Z" }, - { url = "https://files.pythonhosted.org/packages/8a/11/3dafb2a5502586f59fd49e93f5802cd5face82921b3a0f3abb5f357cb879/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:191a90a6f3940d1b7322b6e6cceff4dd533c943659e0a15f788674407856a515", size = 333423, upload-time = "2026-01-20T20:37:17.828Z" }, - { url = "https://files.pythonhosted.org/packages/7c/f2/c8987663f0cdcf4d717a36d85b5db2a5589df0a4e129aa10f16f4380ef48/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4aa4525f4ad82f9d9c842f9a3703f1539c1808affbaec07bb1b842f6b8b96aa5", size = 338659, upload-time = "2026-01-20T20:37:14.286Z" }, - { url = "https://files.pythonhosted.org/packages/d1/c8/929d81665d83f0b2ffaecb8e66c3091a50f62c7cb5b65e678bd75a96684e/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cdbd82ff20147461caefc375551595ecf77ebb384e46267f128aca45a0f2cdfc", size = 467029, upload-time = "2026-01-20T20:37:08.277Z" }, - { url = "https://files.pythonhosted.org/packages/8e/a0/27d7daa1bfed7163f4ccaf52d7d2f4ad7bb1002a85b45077938b91ee584f/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eff57e8a5d540006ce73cf0841a643d445afe78ba12e75ac53a95ca2924a56be", size = 333298, upload-time = "2026-01-20T20:37:07.271Z" }, - { url = "https://files.pythonhosted.org/packages/63/d4/acad86ce012b42ce18a12f31ee2aa3cbeeb98664f865f05f68c882945913/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3fd9112ca96978361201e669729784f26c71fecc9c13a7f8a07162c31bd4d1e2", size = 359217, upload-time = "2026-01-20T20:36:59.687Z" }, -] - -[[package]] -name = "wrapt" -version = "2.1.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f7/37/ae31f40bec90de2f88d9597d0b5281e23ffe85b893a47ca5d9c05c63a4f6/wrapt-2.1.1.tar.gz", hash = "sha256:5fdcb09bf6db023d88f312bd0767594b414655d58090fc1c46b3414415f67fac", size = 81329, upload-time = "2026-02-03T02:12:13.786Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b8/a8/9254e4da74b30a105935197015b18b31b7a298bf046e67d8952ef74967bd/wrapt-2.1.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6c366434a7fb914c7a5de508ed735ef9c133367114e1a7cb91dfb5cd806a1549", size = 60554, upload-time = "2026-02-03T02:11:13.038Z" }, - { url = "https://files.pythonhosted.org/packages/9e/a1/378579880cc7af226354054a2c255f69615b379d8adad482bfe2f22a0dc2/wrapt-2.1.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:5d6a2068bd2e1e19e5a317c8c0b288267eec4e7347c36bc68a6e378a39f19ee7", size = 61491, upload-time = "2026-02-03T02:12:56.077Z" }, - { url = "https://files.pythonhosted.org/packages/dc/72/957b51c56acca35701665878ad31626182199fc4afecfe67dea072210f95/wrapt-2.1.1-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:891ab4713419217b2aed7dd106c9200f64e6a82226775a0d2ebd6bef2ebd1747", size = 113949, upload-time = "2026-02-03T02:11:04.516Z" }, - { url = "https://files.pythonhosted.org/packages/cd/74/36bbebb4a3d2ae9c3e6929639721f8606cd0710a82a777c371aa69e36504/wrapt-2.1.1-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c8ef36a0df38d2dc9d907f6617f89e113c5892e0a35f58f45f75901af0ce7d81", size = 115989, upload-time = "2026-02-03T02:12:19.398Z" }, - { url = "https://files.pythonhosted.org/packages/ae/0d/f1177245a083c7be284bc90bddfe5aece32cdd5b858049cb69ce001a0e8d/wrapt-2.1.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:76e9af3ebd86f19973143d4d592cbf3e970cf3f66ddee30b16278c26ae34b8ab", size = 115242, upload-time = "2026-02-03T02:11:08.111Z" }, - { url = "https://files.pythonhosted.org/packages/62/3e/3b7cf5da27e59df61b1eae2d07dd03ff5d6f75b5408d694873cca7a8e33c/wrapt-2.1.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ff562067485ebdeaef2fa3fe9b1876bc4e7b73762e0a01406ad81e2076edcebf", size = 113676, upload-time = "2026-02-03T02:12:41.026Z" }, - { url = "https://files.pythonhosted.org/packages/f7/65/8248d3912c705f2c66f81cb97c77436f37abcbedb16d633b5ab0d795d8cd/wrapt-2.1.1-cp311-cp311-win32.whl", hash = "sha256:9e60a30aa0909435ec4ea2a3c53e8e1b50ac9f640c0e9fe3f21fd248a22f06c5", size = 57863, upload-time = "2026-02-03T02:12:18.112Z" }, - { url = "https://files.pythonhosted.org/packages/6b/31/d29310ab335f71f00c50466153b3dc985aaf4a9fc03263e543e136859541/wrapt-2.1.1-cp311-cp311-win_amd64.whl", hash = "sha256:7d79954f51fcf84e5ec4878ab4aea32610d70145c5bbc84b3370eabfb1e096c2", size = 60224, upload-time = "2026-02-03T02:12:29.289Z" }, - { url = "https://files.pythonhosted.org/packages/0c/90/a6ec319affa6e2894962a0cb9d73c67f88af1a726d15314bfb5c88b8a08d/wrapt-2.1.1-cp311-cp311-win_arm64.whl", hash = "sha256:d3ffc6b0efe79e08fd947605fd598515aebefe45e50432dc3b5cd437df8b1ada", size = 58643, upload-time = "2026-02-03T02:12:43.022Z" }, - { url = "https://files.pythonhosted.org/packages/df/cb/4d5255d19bbd12be7f8ee2c1fb4269dddec9cef777ef17174d357468efaa/wrapt-2.1.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:ab8e3793b239db021a18782a5823fcdea63b9fe75d0e340957f5828ef55fcc02", size = 61143, upload-time = "2026-02-03T02:11:46.313Z" }, - { url = "https://files.pythonhosted.org/packages/6f/07/7ed02daa35542023464e3c8b7cb937fa61f6c61c0361ecf8f5fecf8ad8da/wrapt-2.1.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:7c0300007836373d1c2df105b40777986accb738053a92fe09b615a7a4547e9f", size = 61740, upload-time = "2026-02-03T02:12:51.966Z" }, - { url = "https://files.pythonhosted.org/packages/c4/60/a237a4e4a36f6d966061ccc9b017627d448161b19e0a3ab80a7c7c97f859/wrapt-2.1.1-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:2b27c070fd1132ab23957bcd4ee3ba707a91e653a9268dc1afbd39b77b2799f7", size = 121327, upload-time = "2026-02-03T02:11:06.796Z" }, - { url = "https://files.pythonhosted.org/packages/ae/fe/9139058a3daa8818fc67e6460a2340e8bbcf3aef8b15d0301338bbe181ca/wrapt-2.1.1-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8b0e36d845e8b6f50949b6b65fc6cd279f47a1944582ed4ec8258cd136d89a64", size = 122903, upload-time = "2026-02-03T02:12:48.657Z" }, - { url = "https://files.pythonhosted.org/packages/91/10/b8479202b4164649675846a531763531f0a6608339558b5a0a718fc49a8d/wrapt-2.1.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:4aeea04a9889370fcfb1ef828c4cc583f36a875061505cd6cd9ba24d8b43cc36", size = 121333, upload-time = "2026-02-03T02:11:32.148Z" }, - { url = "https://files.pythonhosted.org/packages/5f/75/75fc793b791d79444aca2c03ccde64e8b99eda321b003f267d570b7b0985/wrapt-2.1.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:d88b46bb0dce9f74b6817bc1758ff2125e1ca9e1377d62ea35b6896142ab6825", size = 120458, upload-time = "2026-02-03T02:11:16.039Z" }, - { url = "https://files.pythonhosted.org/packages/d7/8f/c3f30d511082ca6d947c405f9d8f6c8eaf83cfde527c439ec2c9a30eb5ea/wrapt-2.1.1-cp312-cp312-win32.whl", hash = "sha256:63decff76ca685b5c557082dfbea865f3f5f6d45766a89bff8dc61d336348833", size = 58086, upload-time = "2026-02-03T02:12:35.041Z" }, - { url = "https://files.pythonhosted.org/packages/0a/c8/37625b643eea2849f10c3b90f69c7462faa4134448d4443234adaf122ae5/wrapt-2.1.1-cp312-cp312-win_amd64.whl", hash = "sha256:b828235d26c1e35aca4107039802ae4b1411be0fe0367dd5b7e4d90e562fcbcd", size = 60328, upload-time = "2026-02-03T02:12:45.808Z" }, - { url = "https://files.pythonhosted.org/packages/ce/79/56242f07572d5682ba8065a9d4d9c2218313f576e3c3471873c2a5355ffd/wrapt-2.1.1-cp312-cp312-win_arm64.whl", hash = "sha256:75128507413a9f1bcbe2db88fd18fbdbf80f264b82fa33a6996cdeaf01c52352", size = 58722, upload-time = "2026-02-03T02:12:27.949Z" }, - { url = "https://files.pythonhosted.org/packages/f7/ca/3cf290212855b19af9fcc41b725b5620b32f470d6aad970c2593500817eb/wrapt-2.1.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:ce9646e17fa7c3e2e7a87e696c7de66512c2b4f789a8db95c613588985a2e139", size = 61150, upload-time = "2026-02-03T02:12:50.575Z" }, - { url = "https://files.pythonhosted.org/packages/9d/33/5b8f89a82a9859ce82da4870c799ad11ce15648b6e1c820fec3e23f4a19f/wrapt-2.1.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:428cfc801925454395aa468ba7ddb3ed63dc0d881df7b81626cdd433b4e2b11b", size = 61743, upload-time = "2026-02-03T02:11:55.733Z" }, - { url = "https://files.pythonhosted.org/packages/1e/2f/60c51304fbdf47ce992d9eefa61fbd2c0e64feee60aaa439baf42ea6f40b/wrapt-2.1.1-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:5797f65e4d58065a49088c3b32af5410751cd485e83ba89e5a45e2aa8905af98", size = 121341, upload-time = "2026-02-03T02:11:20.461Z" }, - { url = "https://files.pythonhosted.org/packages/ad/03/ce5256e66dd94e521ad5e753c78185c01b6eddbed3147be541f4d38c0cb7/wrapt-2.1.1-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5a2db44a71202c5ae4bb5f27c6d3afbc5b23053f2e7e78aa29704541b5dad789", size = 122947, upload-time = "2026-02-03T02:11:33.596Z" }, - { url = "https://files.pythonhosted.org/packages/eb/ae/50ca8854b81b946a11a36fcd6ead32336e6db2c14b6e4a8b092b80741178/wrapt-2.1.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:8d5350c3590af09c1703dd60ec78a7370c0186e11eaafb9dda025a30eee6492d", size = 121370, upload-time = "2026-02-03T02:11:09.886Z" }, - { url = "https://files.pythonhosted.org/packages/fb/d9/d6a7c654e0043319b4cc137a4caaf7aa16b46b51ee8df98d1060254705b7/wrapt-2.1.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:2d9b076411bed964e752c01b49fd224cc385f3a96f520c797d38412d70d08359", size = 120465, upload-time = "2026-02-03T02:11:37.592Z" }, - { url = "https://files.pythonhosted.org/packages/55/90/65be41e40845d951f714b5a77e84f377a3787b1e8eee6555a680da6d0db5/wrapt-2.1.1-cp313-cp313-win32.whl", hash = "sha256:0bb7207130ce6486727baa85373503bf3334cc28016f6928a0fa7e19d7ecdc06", size = 58090, upload-time = "2026-02-03T02:12:53.342Z" }, - { url = "https://files.pythonhosted.org/packages/5f/66/6a09e0294c4fc8c26028a03a15191721c9271672467cc33e6617ee0d91d2/wrapt-2.1.1-cp313-cp313-win_amd64.whl", hash = "sha256:cbfee35c711046b15147b0ae7db9b976f01c9520e6636d992cd9e69e5e2b03b1", size = 60341, upload-time = "2026-02-03T02:12:36.384Z" }, - { url = "https://files.pythonhosted.org/packages/7a/f0/20ceb8b701e9a71555c87a5ddecbed76ec16742cf1e4b87bbaf26735f998/wrapt-2.1.1-cp313-cp313-win_arm64.whl", hash = "sha256:7d2756061022aebbf57ba14af9c16e8044e055c22d38de7bf40d92b565ecd2b0", size = 58731, upload-time = "2026-02-03T02:12:01.328Z" }, - { url = "https://files.pythonhosted.org/packages/80/b4/fe95beb8946700b3db371f6ce25115217e7075ca063663b8cca2888ba55c/wrapt-2.1.1-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:4814a3e58bc6971e46baa910ecee69699110a2bf06c201e24277c65115a20c20", size = 62969, upload-time = "2026-02-03T02:11:51.245Z" }, - { url = "https://files.pythonhosted.org/packages/b8/89/477b0bdc784e3299edf69c279697372b8bd4c31d9c6966eae405442899df/wrapt-2.1.1-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:106c5123232ab9b9f4903692e1fa0bdc231510098f04c13c3081f8ad71c3d612", size = 63606, upload-time = "2026-02-03T02:12:02.64Z" }, - { url = "https://files.pythonhosted.org/packages/ed/55/9d0c1269ab76de87715b3b905df54dd25d55bbffd0b98696893eb613469f/wrapt-2.1.1-cp313-cp313t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:1a40b83ff2535e6e56f190aff123821eea89a24c589f7af33413b9c19eb2c738", size = 152536, upload-time = "2026-02-03T02:11:24.492Z" }, - { url = "https://files.pythonhosted.org/packages/44/18/2004766030462f79ad86efaa62000b5e39b1ff001dcce86650e1625f40ae/wrapt-2.1.1-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:789cea26e740d71cf1882e3a42bb29052bc4ada15770c90072cb47bf73fb3dbf", size = 158697, upload-time = "2026-02-03T02:12:32.214Z" }, - { url = "https://files.pythonhosted.org/packages/e1/bb/0a880fa0f35e94ee843df4ee4dd52a699c9263f36881311cfb412c09c3e5/wrapt-2.1.1-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:ba49c14222d5e5c0ee394495a8655e991dc06cbca5398153aefa5ac08cd6ccd7", size = 155563, upload-time = "2026-02-03T02:11:49.737Z" }, - { url = "https://files.pythonhosted.org/packages/42/ff/cd1b7c4846c8678fac359a6eb975dc7ab5bd606030adb22acc8b4a9f53f1/wrapt-2.1.1-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:ac8cda531fe55be838a17c62c806824472bb962b3afa47ecbd59b27b78496f4e", size = 150161, upload-time = "2026-02-03T02:12:33.613Z" }, - { url = "https://files.pythonhosted.org/packages/38/ec/67c90a7082f452964b4621e4890e9a490f1add23cdeb7483cc1706743291/wrapt-2.1.1-cp313-cp313t-win32.whl", hash = "sha256:b8af75fe20d381dd5bcc9db2e86a86d7fcfbf615383a7147b85da97c1182225b", size = 59783, upload-time = "2026-02-03T02:11:39.863Z" }, - { url = "https://files.pythonhosted.org/packages/ec/08/466afe4855847d8febdfa2c57c87e991fc5820afbdef01a273683dfd15a0/wrapt-2.1.1-cp313-cp313t-win_amd64.whl", hash = "sha256:45c5631c9b6c792b78be2d7352129f776dd72c605be2c3a4e9be346be8376d83", size = 63082, upload-time = "2026-02-03T02:12:09.075Z" }, - { url = "https://files.pythonhosted.org/packages/9a/62/60b629463c28b15b1eeadb3a0691e17568622b12aa5bfa7ebe9b514bfbeb/wrapt-2.1.1-cp313-cp313t-win_arm64.whl", hash = "sha256:da815b9263947ac98d088b6414ac83507809a1d385e4632d9489867228d6d81c", size = 60251, upload-time = "2026-02-03T02:11:21.794Z" }, - { url = "https://files.pythonhosted.org/packages/95/a0/1c2396e272f91efe6b16a6a8bce7ad53856c8f9ae4f34ceaa711d63ec9e1/wrapt-2.1.1-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:9aa1765054245bb01a37f615503290d4e207e3fd59226e78341afb587e9c1236", size = 61311, upload-time = "2026-02-03T02:12:44.41Z" }, - { url = "https://files.pythonhosted.org/packages/b0/9a/d2faba7e61072a7507b5722db63562fdb22f5a24e237d460d18755627f15/wrapt-2.1.1-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:feff14b63a6d86c1eee33a57f77573649f2550935981625be7ff3cb7342efe05", size = 61805, upload-time = "2026-02-03T02:11:59.905Z" }, - { url = "https://files.pythonhosted.org/packages/db/56/073989deb4b5d7d6e7ea424476a4ae4bda02140f2dbeaafb14ba4864dd60/wrapt-2.1.1-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:81fc5f22d5fcfdbabde96bb3f5379b9f4476d05c6d524d7259dc5dfb501d3281", size = 120308, upload-time = "2026-02-03T02:12:04.46Z" }, - { url = "https://files.pythonhosted.org/packages/d1/b6/84f37261295e38167a29eb82affaf1dc15948dc416925fe2091beee8e4ac/wrapt-2.1.1-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:951b228ecf66def855d22e006ab9a1fc12535111ae7db2ec576c728f8ddb39e8", size = 122688, upload-time = "2026-02-03T02:11:23.148Z" }, - { url = "https://files.pythonhosted.org/packages/ea/80/32db2eec6671f80c65b7ff175be61bc73d7f5223f6910b0c921bbc4bd11c/wrapt-2.1.1-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:0ddf582a95641b9a8c8bd643e83f34ecbbfe1b68bc3850093605e469ab680ae3", size = 121115, upload-time = "2026-02-03T02:12:39.068Z" }, - { url = "https://files.pythonhosted.org/packages/49/ef/dcd00383df0cd696614127902153bf067971a5aabcd3c9dcb2d8ef354b2a/wrapt-2.1.1-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:fc5c500966bf48913f795f1984704e6d452ba2414207b15e1f8c339a059d5b16", size = 119484, upload-time = "2026-02-03T02:11:48.419Z" }, - { url = "https://files.pythonhosted.org/packages/76/29/0630280cdd2bd8f86f35cb6854abee1c9d6d1a28a0c6b6417cd15d378325/wrapt-2.1.1-cp314-cp314-win32.whl", hash = "sha256:4aa4baadb1f94b71151b8e44a0c044f6af37396c3b8bcd474b78b49e2130a23b", size = 58514, upload-time = "2026-02-03T02:11:58.616Z" }, - { url = "https://files.pythonhosted.org/packages/db/19/5bed84f9089ed2065f6aeda5dfc4f043743f642bc871454b261c3d7d322b/wrapt-2.1.1-cp314-cp314-win_amd64.whl", hash = "sha256:860e9d3fd81816a9f4e40812f28be4439ab01f260603c749d14be3c0a1170d19", size = 60763, upload-time = "2026-02-03T02:12:24.553Z" }, - { url = "https://files.pythonhosted.org/packages/e4/cb/b967f2f9669e4249b4fe82e630d2a01bc6b9e362b9b12ed91bbe23ae8df4/wrapt-2.1.1-cp314-cp314-win_arm64.whl", hash = "sha256:3c59e103017a2c1ea0ddf589cbefd63f91081d7ce9d491d69ff2512bb1157e23", size = 59051, upload-time = "2026-02-03T02:11:29.602Z" }, - { url = "https://files.pythonhosted.org/packages/eb/19/6fed62be29f97eb8a56aff236c3f960a4b4a86e8379dc7046a8005901a97/wrapt-2.1.1-cp314-cp314t-macosx_10_15_x86_64.whl", hash = "sha256:9fa7c7e1bee9278fc4f5dd8275bc8d25493281a8ec6c61959e37cc46acf02007", size = 63059, upload-time = "2026-02-03T02:12:06.368Z" }, - { url = "https://files.pythonhosted.org/packages/0a/1c/b757fd0adb53d91547ed8fad76ba14a5932d83dde4c994846a2804596378/wrapt-2.1.1-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:39c35e12e8215628984248bd9c8897ce0a474be2a773db207eb93414219d8469", size = 63618, upload-time = "2026-02-03T02:12:23.197Z" }, - { url = "https://files.pythonhosted.org/packages/10/fe/e5ae17b1480957c7988d991b93df9f2425fc51f128cf88144d6a18d0eb12/wrapt-2.1.1-cp314-cp314t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:94ded4540cac9125eaa8ddf5f651a7ec0da6f5b9f248fe0347b597098f8ec14c", size = 152544, upload-time = "2026-02-03T02:11:43.915Z" }, - { url = "https://files.pythonhosted.org/packages/3e/cc/99aed210c6b547b8a6e4cb9d1425e4466727158a6aeb833aa7997e9e08dd/wrapt-2.1.1-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:da0af328373f97ed9bdfea24549ac1b944096a5a71b30e41c9b8b53ab3eec04a", size = 158700, upload-time = "2026-02-03T02:12:30.684Z" }, - { url = "https://files.pythonhosted.org/packages/81/0e/d442f745f4957944d5f8ad38bc3a96620bfff3562533b87e486e979f3d99/wrapt-2.1.1-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:4ad839b55f0bf235f8e337ce060572d7a06592592f600f3a3029168e838469d3", size = 155561, upload-time = "2026-02-03T02:11:28.164Z" }, - { url = "https://files.pythonhosted.org/packages/51/ac/9891816280e0018c48f8dfd61b136af7b0dcb4a088895db2531acde5631b/wrapt-2.1.1-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:0d89c49356e5e2a50fa86b40e0510082abcd0530f926cbd71cf25bee6b9d82d7", size = 150188, upload-time = "2026-02-03T02:11:57.053Z" }, - { url = "https://files.pythonhosted.org/packages/24/98/e2f273b6d70d41f98d0739aa9a269d0b633684a5fb17b9229709375748d4/wrapt-2.1.1-cp314-cp314t-win32.whl", hash = "sha256:f4c7dd22cf7f36aafe772f3d88656559205c3af1b7900adfccb70edeb0d2abc4", size = 60425, upload-time = "2026-02-03T02:11:35.007Z" }, - { url = "https://files.pythonhosted.org/packages/1e/06/b500bfc38a4f82d89f34a13069e748c82c5430d365d9e6b75afb3ab74457/wrapt-2.1.1-cp314-cp314t-win_amd64.whl", hash = "sha256:f76bc12c583ab01e73ba0ea585465a41e48d968f6d1311b4daec4f8654e356e3", size = 63855, upload-time = "2026-02-03T02:12:15.47Z" }, - { url = "https://files.pythonhosted.org/packages/d9/cc/5f6193c32166faee1d2a613f278608e6f3b95b96589d020f0088459c46c9/wrapt-2.1.1-cp314-cp314t-win_arm64.whl", hash = "sha256:7ea74fc0bec172f1ae5f3505b6655c541786a5cabe4bbc0d9723a56ac32eb9b9", size = 60443, upload-time = "2026-02-03T02:11:30.869Z" }, - { url = "https://files.pythonhosted.org/packages/c4/da/5a086bf4c22a41995312db104ec2ffeee2cf6accca9faaee5315c790377d/wrapt-2.1.1-py3-none-any.whl", hash = "sha256:3b0f4629eb954394a3d7c7a1c8cca25f0b07cefe6aa8545e862e9778152de5b7", size = 43886, upload-time = "2026-02-03T02:11:45.048Z" }, -] - -[[package]] -name = "xxhash" -version = "3.6.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/02/84/30869e01909fb37a6cc7e18688ee8bf1e42d57e7e0777636bd47524c43c7/xxhash-3.6.0.tar.gz", hash = "sha256:f0162a78b13a0d7617b2845b90c763339d1f1d82bb04a4b07f4ab535cc5e05d6", size = 85160, upload-time = "2025-10-02T14:37:08.097Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/17/d4/cc2f0400e9154df4b9964249da78ebd72f318e35ccc425e9f403c392f22a/xxhash-3.6.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b47bbd8cf2d72797f3c2772eaaac0ded3d3af26481a26d7d7d41dc2d3c46b04a", size = 32844, upload-time = "2025-10-02T14:34:14.037Z" }, - { url = "https://files.pythonhosted.org/packages/5e/ec/1cc11cd13e26ea8bc3cb4af4eaadd8d46d5014aebb67be3f71fb0b68802a/xxhash-3.6.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2b6821e94346f96db75abaa6e255706fb06ebd530899ed76d32cd99f20dc52fa", size = 30809, upload-time = "2025-10-02T14:34:15.484Z" }, - { url = "https://files.pythonhosted.org/packages/04/5f/19fe357ea348d98ca22f456f75a30ac0916b51c753e1f8b2e0e6fb884cce/xxhash-3.6.0-cp311-cp311-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:d0a9751f71a1a65ce3584e9cae4467651c7e70c9d31017fa57574583a4540248", size = 194665, upload-time = "2025-10-02T14:34:16.541Z" }, - { url = "https://files.pythonhosted.org/packages/90/3b/d1f1a8f5442a5fd8beedae110c5af7604dc37349a8e16519c13c19a9a2de/xxhash-3.6.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8b29ee68625ab37b04c0b40c3fafdf24d2f75ccd778333cfb698f65f6c463f62", size = 213550, upload-time = "2025-10-02T14:34:17.878Z" }, - { url = "https://files.pythonhosted.org/packages/c4/ef/3a9b05eb527457d5db13a135a2ae1a26c80fecd624d20f3e8dcc4cb170f3/xxhash-3.6.0-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:6812c25fe0d6c36a46ccb002f40f27ac903bf18af9f6dd8f9669cb4d176ab18f", size = 212384, upload-time = "2025-10-02T14:34:19.182Z" }, - { url = "https://files.pythonhosted.org/packages/0f/18/ccc194ee698c6c623acbf0f8c2969811a8a4b6185af5e824cd27b9e4fd3e/xxhash-3.6.0-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:4ccbff013972390b51a18ef1255ef5ac125c92dc9143b2d1909f59abc765540e", size = 445749, upload-time = "2025-10-02T14:34:20.659Z" }, - { url = "https://files.pythonhosted.org/packages/a5/86/cf2c0321dc3940a7aa73076f4fd677a0fb3e405cb297ead7d864fd90847e/xxhash-3.6.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:297b7fbf86c82c550e12e8fb71968b3f033d27b874276ba3624ea868c11165a8", size = 193880, upload-time = "2025-10-02T14:34:22.431Z" }, - { url = "https://files.pythonhosted.org/packages/82/fb/96213c8560e6f948a1ecc9a7613f8032b19ee45f747f4fca4eb31bb6d6ed/xxhash-3.6.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:dea26ae1eb293db089798d3973a5fc928a18fdd97cc8801226fae705b02b14b0", size = 210912, upload-time = "2025-10-02T14:34:23.937Z" }, - { url = "https://files.pythonhosted.org/packages/40/aa/4395e669b0606a096d6788f40dbdf2b819d6773aa290c19e6e83cbfc312f/xxhash-3.6.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:7a0b169aafb98f4284f73635a8e93f0735f9cbde17bd5ec332480484241aaa77", size = 198654, upload-time = "2025-10-02T14:34:25.644Z" }, - { url = "https://files.pythonhosted.org/packages/67/74/b044fcd6b3d89e9b1b665924d85d3f400636c23590226feb1eb09e1176ce/xxhash-3.6.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:08d45aef063a4531b785cd72de4887766d01dc8f362a515693df349fdb825e0c", size = 210867, upload-time = "2025-10-02T14:34:27.203Z" }, - { url = "https://files.pythonhosted.org/packages/bc/fd/3ce73bf753b08cb19daee1eb14aa0d7fe331f8da9c02dd95316ddfe5275e/xxhash-3.6.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:929142361a48ee07f09121fe9e96a84950e8d4df3bb298ca5d88061969f34d7b", size = 414012, upload-time = "2025-10-02T14:34:28.409Z" }, - { url = "https://files.pythonhosted.org/packages/ba/b3/5a4241309217c5c876f156b10778f3ab3af7ba7e3259e6d5f5c7d0129eb2/xxhash-3.6.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:51312c768403d8540487dbbfb557454cfc55589bbde6424456951f7fcd4facb3", size = 191409, upload-time = "2025-10-02T14:34:29.696Z" }, - { url = "https://files.pythonhosted.org/packages/c0/01/99bfbc15fb9abb9a72b088c1d95219fc4782b7d01fc835bd5744d66dd0b8/xxhash-3.6.0-cp311-cp311-win32.whl", hash = "sha256:d1927a69feddc24c987b337ce81ac15c4720955b667fe9b588e02254b80446fd", size = 30574, upload-time = "2025-10-02T14:34:31.028Z" }, - { url = "https://files.pythonhosted.org/packages/65/79/9d24d7f53819fe301b231044ea362ce64e86c74f6e8c8e51320de248b3e5/xxhash-3.6.0-cp311-cp311-win_amd64.whl", hash = "sha256:26734cdc2d4ffe449b41d186bbeac416f704a482ed835d375a5c0cb02bc63fef", size = 31481, upload-time = "2025-10-02T14:34:32.062Z" }, - { url = "https://files.pythonhosted.org/packages/30/4e/15cd0e3e8772071344eab2961ce83f6e485111fed8beb491a3f1ce100270/xxhash-3.6.0-cp311-cp311-win_arm64.whl", hash = "sha256:d72f67ef8bf36e05f5b6c65e8524f265bd61071471cd4cf1d36743ebeeeb06b7", size = 27861, upload-time = "2025-10-02T14:34:33.555Z" }, - { url = "https://files.pythonhosted.org/packages/9a/07/d9412f3d7d462347e4511181dea65e47e0d0e16e26fbee2ea86a2aefb657/xxhash-3.6.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:01362c4331775398e7bb34e3ab403bc9ee9f7c497bc7dee6272114055277dd3c", size = 32744, upload-time = "2025-10-02T14:34:34.622Z" }, - { url = "https://files.pythonhosted.org/packages/79/35/0429ee11d035fc33abe32dca1b2b69e8c18d236547b9a9b72c1929189b9a/xxhash-3.6.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:b7b2df81a23f8cb99656378e72501b2cb41b1827c0f5a86f87d6b06b69f9f204", size = 30816, upload-time = "2025-10-02T14:34:36.043Z" }, - { url = "https://files.pythonhosted.org/packages/b7/f2/57eb99aa0f7d98624c0932c5b9a170e1806406cdbcdb510546634a1359e0/xxhash-3.6.0-cp312-cp312-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:dc94790144e66b14f67b10ac8ed75b39ca47536bf8800eb7c24b50271ea0c490", size = 194035, upload-time = "2025-10-02T14:34:37.354Z" }, - { url = "https://files.pythonhosted.org/packages/4c/ed/6224ba353690d73af7a3f1c7cdb1fc1b002e38f783cb991ae338e1eb3d79/xxhash-3.6.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:93f107c673bccf0d592cdba077dedaf52fe7f42dcd7676eba1f6d6f0c3efffd2", size = 212914, upload-time = "2025-10-02T14:34:38.6Z" }, - { url = "https://files.pythonhosted.org/packages/38/86/fb6b6130d8dd6b8942cc17ab4d90e223653a89aa32ad2776f8af7064ed13/xxhash-3.6.0-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:2aa5ee3444c25b69813663c9f8067dcfaa2e126dc55e8dddf40f4d1c25d7effa", size = 212163, upload-time = "2025-10-02T14:34:39.872Z" }, - { url = "https://files.pythonhosted.org/packages/ee/dc/e84875682b0593e884ad73b2d40767b5790d417bde603cceb6878901d647/xxhash-3.6.0-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:f7f99123f0e1194fa59cc69ad46dbae2e07becec5df50a0509a808f90a0f03f0", size = 445411, upload-time = "2025-10-02T14:34:41.569Z" }, - { url = "https://files.pythonhosted.org/packages/11/4f/426f91b96701ec2f37bb2b8cec664eff4f658a11f3fa9d94f0a887ea6d2b/xxhash-3.6.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:49e03e6fe2cac4a1bc64952dd250cf0dbc5ef4ebb7b8d96bce82e2de163c82a2", size = 193883, upload-time = "2025-10-02T14:34:43.249Z" }, - { url = "https://files.pythonhosted.org/packages/53/5a/ddbb83eee8e28b778eacfc5a85c969673e4023cdeedcfcef61f36731610b/xxhash-3.6.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:bd17fede52a17a4f9a7bc4472a5867cb0b160deeb431795c0e4abe158bc784e9", size = 210392, upload-time = "2025-10-02T14:34:45.042Z" }, - { url = "https://files.pythonhosted.org/packages/1e/c2/ff69efd07c8c074ccdf0a4f36fcdd3d27363665bcdf4ba399abebe643465/xxhash-3.6.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:6fb5f5476bef678f69db04f2bd1efbed3030d2aba305b0fc1773645f187d6a4e", size = 197898, upload-time = "2025-10-02T14:34:46.302Z" }, - { url = "https://files.pythonhosted.org/packages/58/ca/faa05ac19b3b622c7c9317ac3e23954187516298a091eb02c976d0d3dd45/xxhash-3.6.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:843b52f6d88071f87eba1631b684fcb4b2068cd2180a0224122fe4ef011a9374", size = 210655, upload-time = "2025-10-02T14:34:47.571Z" }, - { url = "https://files.pythonhosted.org/packages/d4/7a/06aa7482345480cc0cb597f5c875b11a82c3953f534394f620b0be2f700c/xxhash-3.6.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:7d14a6cfaf03b1b6f5f9790f76880601ccc7896aff7ab9cd8978a939c1eb7e0d", size = 414001, upload-time = "2025-10-02T14:34:49.273Z" }, - { url = "https://files.pythonhosted.org/packages/23/07/63ffb386cd47029aa2916b3d2f454e6cc5b9f5c5ada3790377d5430084e7/xxhash-3.6.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:418daf3db71e1413cfe211c2f9a528456936645c17f46b5204705581a45390ae", size = 191431, upload-time = "2025-10-02T14:34:50.798Z" }, - { url = "https://files.pythonhosted.org/packages/0f/93/14fde614cadb4ddf5e7cebf8918b7e8fac5ae7861c1875964f17e678205c/xxhash-3.6.0-cp312-cp312-win32.whl", hash = "sha256:50fc255f39428a27299c20e280d6193d8b63b8ef8028995323bf834a026b4fbb", size = 30617, upload-time = "2025-10-02T14:34:51.954Z" }, - { url = "https://files.pythonhosted.org/packages/13/5d/0d125536cbe7565a83d06e43783389ecae0c0f2ed037b48ede185de477c0/xxhash-3.6.0-cp312-cp312-win_amd64.whl", hash = "sha256:c0f2ab8c715630565ab8991b536ecded9416d615538be8ecddce43ccf26cbc7c", size = 31534, upload-time = "2025-10-02T14:34:53.276Z" }, - { url = "https://files.pythonhosted.org/packages/54/85/6ec269b0952ec7e36ba019125982cf11d91256a778c7c3f98a4c5043d283/xxhash-3.6.0-cp312-cp312-win_arm64.whl", hash = "sha256:eae5c13f3bc455a3bbb68bdc513912dc7356de7e2280363ea235f71f54064829", size = 27876, upload-time = "2025-10-02T14:34:54.371Z" }, - { url = "https://files.pythonhosted.org/packages/33/76/35d05267ac82f53ae9b0e554da7c5e281ee61f3cad44c743f0fcd354f211/xxhash-3.6.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:599e64ba7f67472481ceb6ee80fa3bd828fd61ba59fb11475572cc5ee52b89ec", size = 32738, upload-time = "2025-10-02T14:34:55.839Z" }, - { url = "https://files.pythonhosted.org/packages/31/a8/3fbce1cd96534a95e35d5120637bf29b0d7f5d8fa2f6374e31b4156dd419/xxhash-3.6.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:7d8b8aaa30fca4f16f0c84a5c8d7ddee0e25250ec2796c973775373257dde8f1", size = 30821, upload-time = "2025-10-02T14:34:57.219Z" }, - { url = "https://files.pythonhosted.org/packages/0c/ea/d387530ca7ecfa183cb358027f1833297c6ac6098223fd14f9782cd0015c/xxhash-3.6.0-cp313-cp313-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:d597acf8506d6e7101a4a44a5e428977a51c0fadbbfd3c39650cca9253f6e5a6", size = 194127, upload-time = "2025-10-02T14:34:59.21Z" }, - { url = "https://files.pythonhosted.org/packages/ba/0c/71435dcb99874b09a43b8d7c54071e600a7481e42b3e3ce1eb5226a5711a/xxhash-3.6.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:858dc935963a33bc33490128edc1c12b0c14d9c7ebaa4e387a7869ecc4f3e263", size = 212975, upload-time = "2025-10-02T14:35:00.816Z" }, - { url = "https://files.pythonhosted.org/packages/84/7a/c2b3d071e4bb4a90b7057228a99b10d51744878f4a8a6dd643c8bd897620/xxhash-3.6.0-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:ba284920194615cb8edf73bf52236ce2e1664ccd4a38fdb543506413529cc546", size = 212241, upload-time = "2025-10-02T14:35:02.207Z" }, - { url = "https://files.pythonhosted.org/packages/81/5f/640b6eac0128e215f177df99eadcd0f1b7c42c274ab6a394a05059694c5a/xxhash-3.6.0-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:4b54219177f6c6674d5378bd862c6aedf64725f70dd29c472eaae154df1a2e89", size = 445471, upload-time = "2025-10-02T14:35:03.61Z" }, - { url = "https://files.pythonhosted.org/packages/5e/1e/3c3d3ef071b051cc3abbe3721ffb8365033a172613c04af2da89d5548a87/xxhash-3.6.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:42c36dd7dbad2f5238950c377fcbf6811b1cdb1c444fab447960030cea60504d", size = 193936, upload-time = "2025-10-02T14:35:05.013Z" }, - { url = "https://files.pythonhosted.org/packages/2c/bd/4a5f68381939219abfe1c22a9e3a5854a4f6f6f3c4983a87d255f21f2e5d/xxhash-3.6.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f22927652cba98c44639ffdc7aaf35828dccf679b10b31c4ad72a5b530a18eb7", size = 210440, upload-time = "2025-10-02T14:35:06.239Z" }, - { url = "https://files.pythonhosted.org/packages/eb/37/b80fe3d5cfb9faff01a02121a0f4d565eb7237e9e5fc66e73017e74dcd36/xxhash-3.6.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:b45fad44d9c5c119e9c6fbf2e1c656a46dc68e280275007bbfd3d572b21426db", size = 197990, upload-time = "2025-10-02T14:35:07.735Z" }, - { url = "https://files.pythonhosted.org/packages/d7/fd/2c0a00c97b9e18f72e1f240ad4e8f8a90fd9d408289ba9c7c495ed7dc05c/xxhash-3.6.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:6f2580ffab1a8b68ef2b901cde7e55fa8da5e4be0977c68f78fc80f3c143de42", size = 210689, upload-time = "2025-10-02T14:35:09.438Z" }, - { url = "https://files.pythonhosted.org/packages/93/86/5dd8076a926b9a95db3206aba20d89a7fc14dd5aac16e5c4de4b56033140/xxhash-3.6.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:40c391dd3cd041ebc3ffe6f2c862f402e306eb571422e0aa918d8070ba31da11", size = 414068, upload-time = "2025-10-02T14:35:11.162Z" }, - { url = "https://files.pythonhosted.org/packages/af/3c/0bb129170ee8f3650f08e993baee550a09593462a5cddd8e44d0011102b1/xxhash-3.6.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:f205badabde7aafd1a31e8ca2a3e5a763107a71c397c4481d6a804eb5063d8bd", size = 191495, upload-time = "2025-10-02T14:35:12.971Z" }, - { url = "https://files.pythonhosted.org/packages/e9/3a/6797e0114c21d1725e2577508e24006fd7ff1d8c0c502d3b52e45c1771d8/xxhash-3.6.0-cp313-cp313-win32.whl", hash = "sha256:2577b276e060b73b73a53042ea5bd5203d3e6347ce0d09f98500f418a9fcf799", size = 30620, upload-time = "2025-10-02T14:35:14.129Z" }, - { url = "https://files.pythonhosted.org/packages/86/15/9bc32671e9a38b413a76d24722a2bf8784a132c043063a8f5152d390b0f9/xxhash-3.6.0-cp313-cp313-win_amd64.whl", hash = "sha256:757320d45d2fbcce8f30c42a6b2f47862967aea7bf458b9625b4bbe7ee390392", size = 31542, upload-time = "2025-10-02T14:35:15.21Z" }, - { url = "https://files.pythonhosted.org/packages/39/c5/cc01e4f6188656e56112d6a8e0dfe298a16934b8c47a247236549a3f7695/xxhash-3.6.0-cp313-cp313-win_arm64.whl", hash = "sha256:457b8f85dec5825eed7b69c11ae86834a018b8e3df5e77783c999663da2f96d6", size = 27880, upload-time = "2025-10-02T14:35:16.315Z" }, - { url = "https://files.pythonhosted.org/packages/f3/30/25e5321c8732759e930c555176d37e24ab84365482d257c3b16362235212/xxhash-3.6.0-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:a42e633d75cdad6d625434e3468126c73f13f7584545a9cf34e883aa1710e702", size = 32956, upload-time = "2025-10-02T14:35:17.413Z" }, - { url = "https://files.pythonhosted.org/packages/9f/3c/0573299560d7d9f8ab1838f1efc021a280b5ae5ae2e849034ef3dee18810/xxhash-3.6.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:568a6d743219e717b07b4e03b0a828ce593833e498c3b64752e0f5df6bfe84db", size = 31072, upload-time = "2025-10-02T14:35:18.844Z" }, - { url = "https://files.pythonhosted.org/packages/7a/1c/52d83a06e417cd9d4137722693424885cc9878249beb3a7c829e74bf7ce9/xxhash-3.6.0-cp313-cp313t-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:bec91b562d8012dae276af8025a55811b875baace6af510412a5e58e3121bc54", size = 196409, upload-time = "2025-10-02T14:35:20.31Z" }, - { url = "https://files.pythonhosted.org/packages/e3/8e/c6d158d12a79bbd0b878f8355432075fc82759e356ab5a111463422a239b/xxhash-3.6.0-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:78e7f2f4c521c30ad5e786fdd6bae89d47a32672a80195467b5de0480aa97b1f", size = 215736, upload-time = "2025-10-02T14:35:21.616Z" }, - { url = "https://files.pythonhosted.org/packages/bc/68/c4c80614716345d55071a396cf03d06e34b5f4917a467faf43083c995155/xxhash-3.6.0-cp313-cp313t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:3ed0df1b11a79856df5ffcab572cbd6b9627034c1c748c5566fa79df9048a7c5", size = 214833, upload-time = "2025-10-02T14:35:23.32Z" }, - { url = "https://files.pythonhosted.org/packages/7e/e9/ae27c8ffec8b953efa84c7c4a6c6802c263d587b9fc0d6e7cea64e08c3af/xxhash-3.6.0-cp313-cp313t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:0e4edbfc7d420925b0dd5e792478ed393d6e75ff8fc219a6546fb446b6a417b1", size = 448348, upload-time = "2025-10-02T14:35:25.111Z" }, - { url = "https://files.pythonhosted.org/packages/d7/6b/33e21afb1b5b3f46b74b6bd1913639066af218d704cc0941404ca717fc57/xxhash-3.6.0-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:fba27a198363a7ef87f8c0f6b171ec36b674fe9053742c58dd7e3201c1ab30ee", size = 196070, upload-time = "2025-10-02T14:35:26.586Z" }, - { url = "https://files.pythonhosted.org/packages/96/b6/fcabd337bc5fa624e7203aa0fa7d0c49eed22f72e93229431752bddc83d9/xxhash-3.6.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:794fe9145fe60191c6532fa95063765529770edcdd67b3d537793e8004cabbfd", size = 212907, upload-time = "2025-10-02T14:35:28.087Z" }, - { url = "https://files.pythonhosted.org/packages/4b/d3/9ee6160e644d660fcf176c5825e61411c7f62648728f69c79ba237250143/xxhash-3.6.0-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:6105ef7e62b5ac73a837778efc331a591d8442f8ef5c7e102376506cb4ae2729", size = 200839, upload-time = "2025-10-02T14:35:29.857Z" }, - { url = "https://files.pythonhosted.org/packages/0d/98/e8de5baa5109394baf5118f5e72ab21a86387c4f89b0e77ef3e2f6b0327b/xxhash-3.6.0-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:f01375c0e55395b814a679b3eea205db7919ac2af213f4a6682e01220e5fe292", size = 213304, upload-time = "2025-10-02T14:35:31.222Z" }, - { url = "https://files.pythonhosted.org/packages/7b/1d/71056535dec5c3177eeb53e38e3d367dd1d16e024e63b1cee208d572a033/xxhash-3.6.0-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:d706dca2d24d834a4661619dcacf51a75c16d65985718d6a7d73c1eeeb903ddf", size = 416930, upload-time = "2025-10-02T14:35:32.517Z" }, - { url = "https://files.pythonhosted.org/packages/dc/6c/5cbde9de2cd967c322e651c65c543700b19e7ae3e0aae8ece3469bf9683d/xxhash-3.6.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:5f059d9faeacd49c0215d66f4056e1326c80503f51a1532ca336a385edadd033", size = 193787, upload-time = "2025-10-02T14:35:33.827Z" }, - { url = "https://files.pythonhosted.org/packages/19/fa/0172e350361d61febcea941b0cc541d6e6c8d65d153e85f850a7b256ff8a/xxhash-3.6.0-cp313-cp313t-win32.whl", hash = "sha256:1244460adc3a9be84731d72b8e80625788e5815b68da3da8b83f78115a40a7ec", size = 30916, upload-time = "2025-10-02T14:35:35.107Z" }, - { url = "https://files.pythonhosted.org/packages/ad/e6/e8cf858a2b19d6d45820f072eff1bea413910592ff17157cabc5f1227a16/xxhash-3.6.0-cp313-cp313t-win_amd64.whl", hash = "sha256:b1e420ef35c503869c4064f4a2f2b08ad6431ab7b229a05cce39d74268bca6b8", size = 31799, upload-time = "2025-10-02T14:35:36.165Z" }, - { url = "https://files.pythonhosted.org/packages/56/15/064b197e855bfb7b343210e82490ae672f8bc7cdf3ddb02e92f64304ee8a/xxhash-3.6.0-cp313-cp313t-win_arm64.whl", hash = "sha256:ec44b73a4220623235f67a996c862049f375df3b1052d9899f40a6382c32d746", size = 28044, upload-time = "2025-10-02T14:35:37.195Z" }, - { url = "https://files.pythonhosted.org/packages/7e/5e/0138bc4484ea9b897864d59fce9be9086030825bc778b76cb5a33a906d37/xxhash-3.6.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:a40a3d35b204b7cc7643cbcf8c9976d818cb47befcfac8bbefec8038ac363f3e", size = 32754, upload-time = "2025-10-02T14:35:38.245Z" }, - { url = "https://files.pythonhosted.org/packages/18/d7/5dac2eb2ec75fd771957a13e5dda560efb2176d5203f39502a5fc571f899/xxhash-3.6.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:a54844be970d3fc22630b32d515e79a90d0a3ddb2644d8d7402e3c4c8da61405", size = 30846, upload-time = "2025-10-02T14:35:39.6Z" }, - { url = "https://files.pythonhosted.org/packages/fe/71/8bc5be2bb00deb5682e92e8da955ebe5fa982da13a69da5a40a4c8db12fb/xxhash-3.6.0-cp314-cp314-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:016e9190af8f0a4e3741343777710e3d5717427f175adfdc3e72508f59e2a7f3", size = 194343, upload-time = "2025-10-02T14:35:40.69Z" }, - { url = "https://files.pythonhosted.org/packages/e7/3b/52badfb2aecec2c377ddf1ae75f55db3ba2d321c5e164f14461c90837ef3/xxhash-3.6.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4f6f72232f849eb9d0141e2ebe2677ece15adfd0fa599bc058aad83c714bb2c6", size = 213074, upload-time = "2025-10-02T14:35:42.29Z" }, - { url = "https://files.pythonhosted.org/packages/a2/2b/ae46b4e9b92e537fa30d03dbc19cdae57ed407e9c26d163895e968e3de85/xxhash-3.6.0-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:63275a8aba7865e44b1813d2177e0f5ea7eadad3dd063a21f7cf9afdc7054063", size = 212388, upload-time = "2025-10-02T14:35:43.929Z" }, - { url = "https://files.pythonhosted.org/packages/f5/80/49f88d3afc724b4ac7fbd664c8452d6db51b49915be48c6982659e0e7942/xxhash-3.6.0-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:3cd01fa2aa00d8b017c97eb46b9a794fbdca53fc14f845f5a328c71254b0abb7", size = 445614, upload-time = "2025-10-02T14:35:45.216Z" }, - { url = "https://files.pythonhosted.org/packages/ed/ba/603ce3961e339413543d8cd44f21f2c80e2a7c5cfe692a7b1f2cccf58f3c/xxhash-3.6.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0226aa89035b62b6a86d3c68df4d7c1f47a342b8683da2b60cedcddb46c4d95b", size = 194024, upload-time = "2025-10-02T14:35:46.959Z" }, - { url = "https://files.pythonhosted.org/packages/78/d1/8e225ff7113bf81545cfdcd79eef124a7b7064a0bba53605ff39590b95c2/xxhash-3.6.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:c6e193e9f56e4ca4923c61238cdaced324f0feac782544eb4c6d55ad5cc99ddd", size = 210541, upload-time = "2025-10-02T14:35:48.301Z" }, - { url = "https://files.pythonhosted.org/packages/6f/58/0f89d149f0bad89def1a8dd38feb50ccdeb643d9797ec84707091d4cb494/xxhash-3.6.0-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:9176dcaddf4ca963d4deb93866d739a343c01c969231dbe21680e13a5d1a5bf0", size = 198305, upload-time = "2025-10-02T14:35:49.584Z" }, - { url = "https://files.pythonhosted.org/packages/11/38/5eab81580703c4df93feb5f32ff8fa7fe1e2c51c1f183ee4e48d4bb9d3d7/xxhash-3.6.0-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:c1ce4009c97a752e682b897aa99aef84191077a9433eb237774689f14f8ec152", size = 210848, upload-time = "2025-10-02T14:35:50.877Z" }, - { url = "https://files.pythonhosted.org/packages/5e/6b/953dc4b05c3ce678abca756416e4c130d2382f877a9c30a20d08ee6a77c0/xxhash-3.6.0-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:8cb2f4f679b01513b7adbb9b1b2f0f9cdc31b70007eaf9d59d0878809f385b11", size = 414142, upload-time = "2025-10-02T14:35:52.15Z" }, - { url = "https://files.pythonhosted.org/packages/08/a9/238ec0d4e81a10eb5026d4a6972677cbc898ba6c8b9dbaec12ae001b1b35/xxhash-3.6.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:653a91d7c2ab54a92c19ccf43508b6a555440b9be1bc8be553376778be7f20b5", size = 191547, upload-time = "2025-10-02T14:35:53.547Z" }, - { url = "https://files.pythonhosted.org/packages/f1/ee/3cf8589e06c2164ac77c3bf0aa127012801128f1feebf2a079272da5737c/xxhash-3.6.0-cp314-cp314-win32.whl", hash = "sha256:a756fe893389483ee8c394d06b5ab765d96e68fbbfe6fde7aa17e11f5720559f", size = 31214, upload-time = "2025-10-02T14:35:54.746Z" }, - { url = "https://files.pythonhosted.org/packages/02/5d/a19552fbc6ad4cb54ff953c3908bbc095f4a921bc569433d791f755186f1/xxhash-3.6.0-cp314-cp314-win_amd64.whl", hash = "sha256:39be8e4e142550ef69629c9cd71b88c90e9a5db703fecbcf265546d9536ca4ad", size = 32290, upload-time = "2025-10-02T14:35:55.791Z" }, - { url = "https://files.pythonhosted.org/packages/b1/11/dafa0643bc30442c887b55baf8e73353a344ee89c1901b5a5c54a6c17d39/xxhash-3.6.0-cp314-cp314-win_arm64.whl", hash = "sha256:25915e6000338999236f1eb68a02a32c3275ac338628a7eaa5a269c401995679", size = 28795, upload-time = "2025-10-02T14:35:57.162Z" }, - { url = "https://files.pythonhosted.org/packages/2c/db/0e99732ed7f64182aef4a6fb145e1a295558deec2a746265dcdec12d191e/xxhash-3.6.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:c5294f596a9017ca5a3e3f8884c00b91ab2ad2933cf288f4923c3fd4346cf3d4", size = 32955, upload-time = "2025-10-02T14:35:58.267Z" }, - { url = "https://files.pythonhosted.org/packages/55/f4/2a7c3c68e564a099becfa44bb3d398810cc0ff6749b0d3cb8ccb93f23c14/xxhash-3.6.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:1cf9dcc4ab9cff01dfbba78544297a3a01dafd60f3bde4e2bfd016cf7e4ddc67", size = 31072, upload-time = "2025-10-02T14:35:59.382Z" }, - { url = "https://files.pythonhosted.org/packages/c6/d9/72a29cddc7250e8a5819dad5d466facb5dc4c802ce120645630149127e73/xxhash-3.6.0-cp314-cp314t-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:01262da8798422d0685f7cef03b2bd3f4f46511b02830861df548d7def4402ad", size = 196579, upload-time = "2025-10-02T14:36:00.838Z" }, - { url = "https://files.pythonhosted.org/packages/63/93/b21590e1e381040e2ca305a884d89e1c345b347404f7780f07f2cdd47ef4/xxhash-3.6.0-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:51a73fb7cb3a3ead9f7a8b583ffd9b8038e277cdb8cb87cf890e88b3456afa0b", size = 215854, upload-time = "2025-10-02T14:36:02.207Z" }, - { url = "https://files.pythonhosted.org/packages/ce/b8/edab8a7d4fa14e924b29be877d54155dcbd8b80be85ea00d2be3413a9ed4/xxhash-3.6.0-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:b9c6df83594f7df8f7f708ce5ebeacfc69f72c9fbaaababf6cf4758eaada0c9b", size = 214965, upload-time = "2025-10-02T14:36:03.507Z" }, - { url = "https://files.pythonhosted.org/packages/27/67/dfa980ac7f0d509d54ea0d5a486d2bb4b80c3f1bb22b66e6a05d3efaf6c0/xxhash-3.6.0-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:627f0af069b0ea56f312fd5189001c24578868643203bca1abbc2c52d3a6f3ca", size = 448484, upload-time = "2025-10-02T14:36:04.828Z" }, - { url = "https://files.pythonhosted.org/packages/8c/63/8ffc2cc97e811c0ca5d00ab36604b3ea6f4254f20b7bc658ca825ce6c954/xxhash-3.6.0-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:aa912c62f842dfd013c5f21a642c9c10cd9f4c4e943e0af83618b4a404d9091a", size = 196162, upload-time = "2025-10-02T14:36:06.182Z" }, - { url = "https://files.pythonhosted.org/packages/4b/77/07f0e7a3edd11a6097e990f6e5b815b6592459cb16dae990d967693e6ea9/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:b465afd7909db30168ab62afe40b2fcf79eedc0b89a6c0ab3123515dc0df8b99", size = 213007, upload-time = "2025-10-02T14:36:07.733Z" }, - { url = "https://files.pythonhosted.org/packages/ae/d8/bc5fa0d152837117eb0bef6f83f956c509332ce133c91c63ce07ee7c4873/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_i686.whl", hash = "sha256:a881851cf38b0a70e7c4d3ce81fc7afd86fbc2a024f4cfb2a97cf49ce04b75d3", size = 200956, upload-time = "2025-10-02T14:36:09.106Z" }, - { url = "https://files.pythonhosted.org/packages/26/a5/d749334130de9411783873e9b98ecc46688dad5db64ca6e04b02acc8b473/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:9b3222c686a919a0f3253cfc12bb118b8b103506612253b5baeaac10d8027cf6", size = 213401, upload-time = "2025-10-02T14:36:10.585Z" }, - { url = "https://files.pythonhosted.org/packages/89/72/abed959c956a4bfc72b58c0384bb7940663c678127538634d896b1195c10/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_s390x.whl", hash = "sha256:c5aa639bc113e9286137cec8fadc20e9cd732b2cc385c0b7fa673b84fc1f2a93", size = 417083, upload-time = "2025-10-02T14:36:12.276Z" }, - { url = "https://files.pythonhosted.org/packages/0c/b3/62fd2b586283b7d7d665fb98e266decadf31f058f1cf6c478741f68af0cb/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:5c1343d49ac102799905e115aee590183c3921d475356cb24b4de29a4bc56518", size = 193913, upload-time = "2025-10-02T14:36:14.025Z" }, - { url = "https://files.pythonhosted.org/packages/9a/9a/c19c42c5b3f5a4aad748a6d5b4f23df3bed7ee5445accc65a0fb3ff03953/xxhash-3.6.0-cp314-cp314t-win32.whl", hash = "sha256:5851f033c3030dd95c086b4a36a2683c2ff4a799b23af60977188b057e467119", size = 31586, upload-time = "2025-10-02T14:36:15.603Z" }, - { url = "https://files.pythonhosted.org/packages/03/d6/4cc450345be9924fd5dc8c590ceda1db5b43a0a889587b0ae81a95511360/xxhash-3.6.0-cp314-cp314t-win_amd64.whl", hash = "sha256:0444e7967dac37569052d2409b00a8860c2135cff05502df4da80267d384849f", size = 32526, upload-time = "2025-10-02T14:36:16.708Z" }, - { url = "https://files.pythonhosted.org/packages/0f/c9/7243eb3f9eaabd1a88a5a5acadf06df2d83b100c62684b7425c6a11bcaa8/xxhash-3.6.0-cp314-cp314t-win_arm64.whl", hash = "sha256:bb79b1e63f6fd84ec778a4b1916dfe0a7c3fdb986c06addd5db3a0d413819d95", size = 28898, upload-time = "2025-10-02T14:36:17.843Z" }, - { url = "https://files.pythonhosted.org/packages/93/1e/8aec23647a34a249f62e2398c42955acd9b4c6ed5cf08cbea94dc46f78d2/xxhash-3.6.0-pp311-pypy311_pp73-macosx_10_15_x86_64.whl", hash = "sha256:0f7b7e2ec26c1666ad5fc9dbfa426a6a3367ceaf79db5dd76264659d509d73b0", size = 30662, upload-time = "2025-10-02T14:37:01.743Z" }, - { url = "https://files.pythonhosted.org/packages/b8/0b/b14510b38ba91caf43006209db846a696ceea6a847a0c9ba0a5b1adc53d6/xxhash-3.6.0-pp311-pypy311_pp73-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:5dc1e14d14fa0f5789ec29a7062004b5933964bb9b02aae6622b8f530dc40296", size = 41056, upload-time = "2025-10-02T14:37:02.879Z" }, - { url = "https://files.pythonhosted.org/packages/50/55/15a7b8a56590e66ccd374bbfa3f9ffc45b810886c8c3b614e3f90bd2367c/xxhash-3.6.0-pp311-pypy311_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:881b47fc47e051b37d94d13e7455131054b56749b91b508b0907eb07900d1c13", size = 36251, upload-time = "2025-10-02T14:37:04.44Z" }, - { url = "https://files.pythonhosted.org/packages/62/b2/5ac99a041a29e58e95f907876b04f7067a0242cb85b5f39e726153981503/xxhash-3.6.0-pp311-pypy311_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c6dc31591899f5e5666f04cc2e529e69b4072827085c1ef15294d91a004bc1bd", size = 32481, upload-time = "2025-10-02T14:37:05.869Z" }, - { url = "https://files.pythonhosted.org/packages/7b/d9/8d95e906764a386a3d3b596f3c68bb63687dfca806373509f51ce8eea81f/xxhash-3.6.0-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:15e0dac10eb9309508bfc41f7f9deaa7755c69e35af835db9cb10751adebc35d", size = 31565, upload-time = "2025-10-02T14:37:06.966Z" }, -] - -[[package]] -name = "zstandard" -version = "0.25.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/fd/aa/3e0508d5a5dd96529cdc5a97011299056e14c6505b678fd58938792794b1/zstandard-0.25.0.tar.gz", hash = "sha256:7713e1179d162cf5c7906da876ec2ccb9c3a9dcbdffef0cc7f70c3667a205f0b", size = 711513, upload-time = "2025-09-14T22:15:54.002Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/2a/83/c3ca27c363d104980f1c9cee1101cc8ba724ac8c28a033ede6aab89585b1/zstandard-0.25.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:933b65d7680ea337180733cf9e87293cc5500cc0eb3fc8769f4d3c88d724ec5c", size = 795254, upload-time = "2025-09-14T22:16:26.137Z" }, - { url = "https://files.pythonhosted.org/packages/ac/4d/e66465c5411a7cf4866aeadc7d108081d8ceba9bc7abe6b14aa21c671ec3/zstandard-0.25.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a3f79487c687b1fc69f19e487cd949bf3aae653d181dfb5fde3bf6d18894706f", size = 640559, upload-time = "2025-09-14T22:16:27.973Z" }, - { url = "https://files.pythonhosted.org/packages/12/56/354fe655905f290d3b147b33fe946b0f27e791e4b50a5f004c802cb3eb7b/zstandard-0.25.0-cp311-cp311-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:0bbc9a0c65ce0eea3c34a691e3c4b6889f5f3909ba4822ab385fab9057099431", size = 5348020, upload-time = "2025-09-14T22:16:29.523Z" }, - { url = "https://files.pythonhosted.org/packages/3b/13/2b7ed68bd85e69a2069bcc72141d378f22cae5a0f3b353a2c8f50ef30c1b/zstandard-0.25.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:01582723b3ccd6939ab7b3a78622c573799d5d8737b534b86d0e06ac18dbde4a", size = 5058126, upload-time = "2025-09-14T22:16:31.811Z" }, - { url = "https://files.pythonhosted.org/packages/c9/dd/fdaf0674f4b10d92cb120ccff58bbb6626bf8368f00ebfd2a41ba4a0dc99/zstandard-0.25.0-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:5f1ad7bf88535edcf30038f6919abe087f606f62c00a87d7e33e7fc57cb69fcc", size = 5405390, upload-time = "2025-09-14T22:16:33.486Z" }, - { url = "https://files.pythonhosted.org/packages/0f/67/354d1555575bc2490435f90d67ca4dd65238ff2f119f30f72d5cde09c2ad/zstandard-0.25.0-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:06acb75eebeedb77b69048031282737717a63e71e4ae3f77cc0c3b9508320df6", size = 5452914, upload-time = "2025-09-14T22:16:35.277Z" }, - { url = "https://files.pythonhosted.org/packages/bb/1f/e9cfd801a3f9190bf3e759c422bbfd2247db9d7f3d54a56ecde70137791a/zstandard-0.25.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9300d02ea7c6506f00e627e287e0492a5eb0371ec1670ae852fefffa6164b072", size = 5559635, upload-time = "2025-09-14T22:16:37.141Z" }, - { url = "https://files.pythonhosted.org/packages/21/88/5ba550f797ca953a52d708c8e4f380959e7e3280af029e38fbf47b55916e/zstandard-0.25.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:bfd06b1c5584b657a2892a6014c2f4c20e0db0208c159148fa78c65f7e0b0277", size = 5048277, upload-time = "2025-09-14T22:16:38.807Z" }, - { url = "https://files.pythonhosted.org/packages/46/c0/ca3e533b4fa03112facbe7fbe7779cb1ebec215688e5df576fe5429172e0/zstandard-0.25.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:f373da2c1757bb7f1acaf09369cdc1d51d84131e50d5fa9863982fd626466313", size = 5574377, upload-time = "2025-09-14T22:16:40.523Z" }, - { url = "https://files.pythonhosted.org/packages/12/9b/3fb626390113f272abd0799fd677ea33d5fc3ec185e62e6be534493c4b60/zstandard-0.25.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:6c0e5a65158a7946e7a7affa6418878ef97ab66636f13353b8502d7ea03c8097", size = 4961493, upload-time = "2025-09-14T22:16:43.3Z" }, - { url = "https://files.pythonhosted.org/packages/cb/d3/23094a6b6a4b1343b27ae68249daa17ae0651fcfec9ed4de09d14b940285/zstandard-0.25.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:c8e167d5adf59476fa3e37bee730890e389410c354771a62e3c076c86f9f7778", size = 5269018, upload-time = "2025-09-14T22:16:45.292Z" }, - { url = "https://files.pythonhosted.org/packages/8c/a7/bb5a0c1c0f3f4b5e9d5b55198e39de91e04ba7c205cc46fcb0f95f0383c1/zstandard-0.25.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:98750a309eb2f020da61e727de7d7ba3c57c97cf6213f6f6277bb7fb42a8e065", size = 5443672, upload-time = "2025-09-14T22:16:47.076Z" }, - { url = "https://files.pythonhosted.org/packages/27/22/503347aa08d073993f25109c36c8d9f029c7d5949198050962cb568dfa5e/zstandard-0.25.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:22a086cff1b6ceca18a8dd6096ec631e430e93a8e70a9ca5efa7561a00f826fa", size = 5822753, upload-time = "2025-09-14T22:16:49.316Z" }, - { url = "https://files.pythonhosted.org/packages/e2/be/94267dc6ee64f0f8ba2b2ae7c7a2df934a816baaa7291db9e1aa77394c3c/zstandard-0.25.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:72d35d7aa0bba323965da807a462b0966c91608ef3a48ba761678cb20ce5d8b7", size = 5366047, upload-time = "2025-09-14T22:16:51.328Z" }, - { url = "https://files.pythonhosted.org/packages/7b/a3/732893eab0a3a7aecff8b99052fecf9f605cf0fb5fb6d0290e36beee47a4/zstandard-0.25.0-cp311-cp311-win32.whl", hash = "sha256:f5aeea11ded7320a84dcdd62a3d95b5186834224a9e55b92ccae35d21a8b63d4", size = 436484, upload-time = "2025-09-14T22:16:55.005Z" }, - { url = "https://files.pythonhosted.org/packages/43/a3/c6155f5c1cce691cb80dfd38627046e50af3ee9ddc5d0b45b9b063bfb8c9/zstandard-0.25.0-cp311-cp311-win_amd64.whl", hash = "sha256:daab68faadb847063d0c56f361a289c4f268706b598afbf9ad113cbe5c38b6b2", size = 506183, upload-time = "2025-09-14T22:16:52.753Z" }, - { url = "https://files.pythonhosted.org/packages/8c/3e/8945ab86a0820cc0e0cdbf38086a92868a9172020fdab8a03ac19662b0e5/zstandard-0.25.0-cp311-cp311-win_arm64.whl", hash = "sha256:22a06c5df3751bb7dc67406f5374734ccee8ed37fc5981bf1ad7041831fa1137", size = 462533, upload-time = "2025-09-14T22:16:53.878Z" }, - { url = "https://files.pythonhosted.org/packages/82/fc/f26eb6ef91ae723a03e16eddb198abcfce2bc5a42e224d44cc8b6765e57e/zstandard-0.25.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7b3c3a3ab9daa3eed242d6ecceead93aebbb8f5f84318d82cee643e019c4b73b", size = 795738, upload-time = "2025-09-14T22:16:56.237Z" }, - { url = "https://files.pythonhosted.org/packages/aa/1c/d920d64b22f8dd028a8b90e2d756e431a5d86194caa78e3819c7bf53b4b3/zstandard-0.25.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:913cbd31a400febff93b564a23e17c3ed2d56c064006f54efec210d586171c00", size = 640436, upload-time = "2025-09-14T22:16:57.774Z" }, - { url = "https://files.pythonhosted.org/packages/53/6c/288c3f0bd9fcfe9ca41e2c2fbfd17b2097f6af57b62a81161941f09afa76/zstandard-0.25.0-cp312-cp312-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:011d388c76b11a0c165374ce660ce2c8efa8e5d87f34996aa80f9c0816698b64", size = 5343019, upload-time = "2025-09-14T22:16:59.302Z" }, - { url = "https://files.pythonhosted.org/packages/1e/15/efef5a2f204a64bdb5571e6161d49f7ef0fffdbca953a615efbec045f60f/zstandard-0.25.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:6dffecc361d079bb48d7caef5d673c88c8988d3d33fb74ab95b7ee6da42652ea", size = 5063012, upload-time = "2025-09-14T22:17:01.156Z" }, - { url = "https://files.pythonhosted.org/packages/b7/37/a6ce629ffdb43959e92e87ebdaeebb5ac81c944b6a75c9c47e300f85abdf/zstandard-0.25.0-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:7149623bba7fdf7e7f24312953bcf73cae103db8cae49f8154dd1eadc8a29ecb", size = 5394148, upload-time = "2025-09-14T22:17:03.091Z" }, - { url = "https://files.pythonhosted.org/packages/e3/79/2bf870b3abeb5c070fe2d670a5a8d1057a8270f125ef7676d29ea900f496/zstandard-0.25.0-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:6a573a35693e03cf1d67799fd01b50ff578515a8aeadd4595d2a7fa9f3ec002a", size = 5451652, upload-time = "2025-09-14T22:17:04.979Z" }, - { url = "https://files.pythonhosted.org/packages/53/60/7be26e610767316c028a2cbedb9a3beabdbe33e2182c373f71a1c0b88f36/zstandard-0.25.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:5a56ba0db2d244117ed744dfa8f6f5b366e14148e00de44723413b2f3938a902", size = 5546993, upload-time = "2025-09-14T22:17:06.781Z" }, - { url = "https://files.pythonhosted.org/packages/85/c7/3483ad9ff0662623f3648479b0380d2de5510abf00990468c286c6b04017/zstandard-0.25.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:10ef2a79ab8e2974e2075fb984e5b9806c64134810fac21576f0668e7ea19f8f", size = 5046806, upload-time = "2025-09-14T22:17:08.415Z" }, - { url = "https://files.pythonhosted.org/packages/08/b3/206883dd25b8d1591a1caa44b54c2aad84badccf2f1de9e2d60a446f9a25/zstandard-0.25.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:aaf21ba8fb76d102b696781bddaa0954b782536446083ae3fdaa6f16b25a1c4b", size = 5576659, upload-time = "2025-09-14T22:17:10.164Z" }, - { url = "https://files.pythonhosted.org/packages/9d/31/76c0779101453e6c117b0ff22565865c54f48f8bd807df2b00c2c404b8e0/zstandard-0.25.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:1869da9571d5e94a85a5e8d57e4e8807b175c9e4a6294e3b66fa4efb074d90f6", size = 4953933, upload-time = "2025-09-14T22:17:11.857Z" }, - { url = "https://files.pythonhosted.org/packages/18/e1/97680c664a1bf9a247a280a053d98e251424af51f1b196c6d52f117c9720/zstandard-0.25.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:809c5bcb2c67cd0ed81e9229d227d4ca28f82d0f778fc5fea624a9def3963f91", size = 5268008, upload-time = "2025-09-14T22:17:13.627Z" }, - { url = "https://files.pythonhosted.org/packages/1e/73/316e4010de585ac798e154e88fd81bb16afc5c5cb1a72eeb16dd37e8024a/zstandard-0.25.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:f27662e4f7dbf9f9c12391cb37b4c4c3cb90ffbd3b1fb9284dadbbb8935fa708", size = 5433517, upload-time = "2025-09-14T22:17:16.103Z" }, - { url = "https://files.pythonhosted.org/packages/5b/60/dd0f8cfa8129c5a0ce3ea6b7f70be5b33d2618013a161e1ff26c2b39787c/zstandard-0.25.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:99c0c846e6e61718715a3c9437ccc625de26593fea60189567f0118dc9db7512", size = 5814292, upload-time = "2025-09-14T22:17:17.827Z" }, - { url = "https://files.pythonhosted.org/packages/fc/5f/75aafd4b9d11b5407b641b8e41a57864097663699f23e9ad4dbb91dc6bfe/zstandard-0.25.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:474d2596a2dbc241a556e965fb76002c1ce655445e4e3bf38e5477d413165ffa", size = 5360237, upload-time = "2025-09-14T22:17:19.954Z" }, - { url = "https://files.pythonhosted.org/packages/ff/8d/0309daffea4fcac7981021dbf21cdb2e3427a9e76bafbcdbdf5392ff99a4/zstandard-0.25.0-cp312-cp312-win32.whl", hash = "sha256:23ebc8f17a03133b4426bcc04aabd68f8236eb78c3760f12783385171b0fd8bd", size = 436922, upload-time = "2025-09-14T22:17:24.398Z" }, - { url = "https://files.pythonhosted.org/packages/79/3b/fa54d9015f945330510cb5d0b0501e8253c127cca7ebe8ba46a965df18c5/zstandard-0.25.0-cp312-cp312-win_amd64.whl", hash = "sha256:ffef5a74088f1e09947aecf91011136665152e0b4b359c42be3373897fb39b01", size = 506276, upload-time = "2025-09-14T22:17:21.429Z" }, - { url = "https://files.pythonhosted.org/packages/ea/6b/8b51697e5319b1f9ac71087b0af9a40d8a6288ff8025c36486e0c12abcc4/zstandard-0.25.0-cp312-cp312-win_arm64.whl", hash = "sha256:181eb40e0b6a29b3cd2849f825e0fa34397f649170673d385f3598ae17cca2e9", size = 462679, upload-time = "2025-09-14T22:17:23.147Z" }, - { url = "https://files.pythonhosted.org/packages/35/0b/8df9c4ad06af91d39e94fa96cc010a24ac4ef1378d3efab9223cc8593d40/zstandard-0.25.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:ec996f12524f88e151c339688c3897194821d7f03081ab35d31d1e12ec975e94", size = 795735, upload-time = "2025-09-14T22:17:26.042Z" }, - { url = "https://files.pythonhosted.org/packages/3f/06/9ae96a3e5dcfd119377ba33d4c42a7d89da1efabd5cb3e366b156c45ff4d/zstandard-0.25.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a1a4ae2dec3993a32247995bdfe367fc3266da832d82f8438c8570f989753de1", size = 640440, upload-time = "2025-09-14T22:17:27.366Z" }, - { url = "https://files.pythonhosted.org/packages/d9/14/933d27204c2bd404229c69f445862454dcc101cd69ef8c6068f15aaec12c/zstandard-0.25.0-cp313-cp313-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:e96594a5537722fdfb79951672a2a63aec5ebfb823e7560586f7484819f2a08f", size = 5343070, upload-time = "2025-09-14T22:17:28.896Z" }, - { url = "https://files.pythonhosted.org/packages/6d/db/ddb11011826ed7db9d0e485d13df79b58586bfdec56e5c84a928a9a78c1c/zstandard-0.25.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:bfc4e20784722098822e3eee42b8e576b379ed72cca4a7cb856ae733e62192ea", size = 5063001, upload-time = "2025-09-14T22:17:31.044Z" }, - { url = "https://files.pythonhosted.org/packages/db/00/87466ea3f99599d02a5238498b87bf84a6348290c19571051839ca943777/zstandard-0.25.0-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:457ed498fc58cdc12fc48f7950e02740d4f7ae9493dd4ab2168a47c93c31298e", size = 5394120, upload-time = "2025-09-14T22:17:32.711Z" }, - { url = "https://files.pythonhosted.org/packages/2b/95/fc5531d9c618a679a20ff6c29e2b3ef1d1f4ad66c5e161ae6ff847d102a9/zstandard-0.25.0-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:fd7a5004eb1980d3cefe26b2685bcb0b17989901a70a1040d1ac86f1d898c551", size = 5451230, upload-time = "2025-09-14T22:17:34.41Z" }, - { url = "https://files.pythonhosted.org/packages/63/4b/e3678b4e776db00f9f7b2fe58e547e8928ef32727d7a1ff01dea010f3f13/zstandard-0.25.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:8e735494da3db08694d26480f1493ad2cf86e99bdd53e8e9771b2752a5c0246a", size = 5547173, upload-time = "2025-09-14T22:17:36.084Z" }, - { url = "https://files.pythonhosted.org/packages/4e/d5/ba05ed95c6b8ec30bd468dfeab20589f2cf709b5c940483e31d991f2ca58/zstandard-0.25.0-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:3a39c94ad7866160a4a46d772e43311a743c316942037671beb264e395bdd611", size = 5046736, upload-time = "2025-09-14T22:17:37.891Z" }, - { url = "https://files.pythonhosted.org/packages/50/d5/870aa06b3a76c73eced65c044b92286a3c4e00554005ff51962deef28e28/zstandard-0.25.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:172de1f06947577d3a3005416977cce6168f2261284c02080e7ad0185faeced3", size = 5576368, upload-time = "2025-09-14T22:17:40.206Z" }, - { url = "https://files.pythonhosted.org/packages/5d/35/398dc2ffc89d304d59bc12f0fdd931b4ce455bddf7038a0a67733a25f550/zstandard-0.25.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:3c83b0188c852a47cd13ef3bf9209fb0a77fa5374958b8c53aaa699398c6bd7b", size = 4954022, upload-time = "2025-09-14T22:17:41.879Z" }, - { url = "https://files.pythonhosted.org/packages/9a/5c/36ba1e5507d56d2213202ec2b05e8541734af5f2ce378c5d1ceaf4d88dc4/zstandard-0.25.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:1673b7199bbe763365b81a4f3252b8e80f44c9e323fc42940dc8843bfeaf9851", size = 5267889, upload-time = "2025-09-14T22:17:43.577Z" }, - { url = "https://files.pythonhosted.org/packages/70/e8/2ec6b6fb7358b2ec0113ae202647ca7c0e9d15b61c005ae5225ad0995df5/zstandard-0.25.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:0be7622c37c183406f3dbf0cba104118eb16a4ea7359eeb5752f0794882fc250", size = 5433952, upload-time = "2025-09-14T22:17:45.271Z" }, - { url = "https://files.pythonhosted.org/packages/7b/01/b5f4d4dbc59ef193e870495c6f1275f5b2928e01ff5a81fecb22a06e22fb/zstandard-0.25.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:5f5e4c2a23ca271c218ac025bd7d635597048b366d6f31f420aaeb715239fc98", size = 5814054, upload-time = "2025-09-14T22:17:47.08Z" }, - { url = "https://files.pythonhosted.org/packages/b2/e5/fbd822d5c6f427cf158316d012c5a12f233473c2f9c5fe5ab1ae5d21f3d8/zstandard-0.25.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:4f187a0bb61b35119d1926aee039524d1f93aaf38a9916b8c4b78ac8514a0aaf", size = 5360113, upload-time = "2025-09-14T22:17:48.893Z" }, - { url = "https://files.pythonhosted.org/packages/8e/e0/69a553d2047f9a2c7347caa225bb3a63b6d7704ad74610cb7823baa08ed7/zstandard-0.25.0-cp313-cp313-win32.whl", hash = "sha256:7030defa83eef3e51ff26f0b7bfb229f0204b66fe18e04359ce3474ac33cbc09", size = 436936, upload-time = "2025-09-14T22:17:52.658Z" }, - { url = "https://files.pythonhosted.org/packages/d9/82/b9c06c870f3bd8767c201f1edbdf9e8dc34be5b0fbc5682c4f80fe948475/zstandard-0.25.0-cp313-cp313-win_amd64.whl", hash = "sha256:1f830a0dac88719af0ae43b8b2d6aef487d437036468ef3c2ea59c51f9d55fd5", size = 506232, upload-time = "2025-09-14T22:17:50.402Z" }, - { url = "https://files.pythonhosted.org/packages/d4/57/60c3c01243bb81d381c9916e2a6d9e149ab8627c0c7d7abb2d73384b3c0c/zstandard-0.25.0-cp313-cp313-win_arm64.whl", hash = "sha256:85304a43f4d513f5464ceb938aa02c1e78c2943b29f44a750b48b25ac999a049", size = 462671, upload-time = "2025-09-14T22:17:51.533Z" }, - { url = "https://files.pythonhosted.org/packages/3d/5c/f8923b595b55fe49e30612987ad8bf053aef555c14f05bb659dd5dbe3e8a/zstandard-0.25.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:e29f0cf06974c899b2c188ef7f783607dbef36da4c242eb6c82dcd8b512855e3", size = 795887, upload-time = "2025-09-14T22:17:54.198Z" }, - { url = "https://files.pythonhosted.org/packages/8d/09/d0a2a14fc3439c5f874042dca72a79c70a532090b7ba0003be73fee37ae2/zstandard-0.25.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:05df5136bc5a011f33cd25bc9f506e7426c0c9b3f9954f056831ce68f3b6689f", size = 640658, upload-time = "2025-09-14T22:17:55.423Z" }, - { url = "https://files.pythonhosted.org/packages/5d/7c/8b6b71b1ddd517f68ffb55e10834388d4f793c49c6b83effaaa05785b0b4/zstandard-0.25.0-cp314-cp314-manylinux2010_i686.manylinux_2_12_i686.manylinux_2_28_i686.whl", hash = "sha256:f604efd28f239cc21b3adb53eb061e2a205dc164be408e553b41ba2ffe0ca15c", size = 5379849, upload-time = "2025-09-14T22:17:57.372Z" }, - { url = "https://files.pythonhosted.org/packages/a4/86/a48e56320d0a17189ab7a42645387334fba2200e904ee47fc5a26c1fd8ca/zstandard-0.25.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:223415140608d0f0da010499eaa8ccdb9af210a543fac54bce15babbcfc78439", size = 5058095, upload-time = "2025-09-14T22:17:59.498Z" }, - { url = "https://files.pythonhosted.org/packages/f8/ad/eb659984ee2c0a779f9d06dbfe45e2dc39d99ff40a319895df2d3d9a48e5/zstandard-0.25.0-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:2e54296a283f3ab5a26fc9b8b5d4978ea0532f37b231644f367aa588930aa043", size = 5551751, upload-time = "2025-09-14T22:18:01.618Z" }, - { url = "https://files.pythonhosted.org/packages/61/b3/b637faea43677eb7bd42ab204dfb7053bd5c4582bfe6b1baefa80ac0c47b/zstandard-0.25.0-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:ca54090275939dc8ec5dea2d2afb400e0f83444b2fc24e07df7fdef677110859", size = 6364818, upload-time = "2025-09-14T22:18:03.769Z" }, - { url = "https://files.pythonhosted.org/packages/31/dc/cc50210e11e465c975462439a492516a73300ab8caa8f5e0902544fd748b/zstandard-0.25.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:e09bb6252b6476d8d56100e8147b803befa9a12cea144bbe629dd508800d1ad0", size = 5560402, upload-time = "2025-09-14T22:18:05.954Z" }, - { url = "https://files.pythonhosted.org/packages/c9/ae/56523ae9c142f0c08efd5e868a6da613ae76614eca1305259c3bf6a0ed43/zstandard-0.25.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:a9ec8c642d1ec73287ae3e726792dd86c96f5681eb8df274a757bf62b750eae7", size = 4955108, upload-time = "2025-09-14T22:18:07.68Z" }, - { url = "https://files.pythonhosted.org/packages/98/cf/c899f2d6df0840d5e384cf4c4121458c72802e8bda19691f3b16619f51e9/zstandard-0.25.0-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:a4089a10e598eae6393756b036e0f419e8c1d60f44a831520f9af41c14216cf2", size = 5269248, upload-time = "2025-09-14T22:18:09.753Z" }, - { url = "https://files.pythonhosted.org/packages/1b/c0/59e912a531d91e1c192d3085fc0f6fb2852753c301a812d856d857ea03c6/zstandard-0.25.0-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:f67e8f1a324a900e75b5e28ffb152bcac9fbed1cc7b43f99cd90f395c4375344", size = 5430330, upload-time = "2025-09-14T22:18:11.966Z" }, - { url = "https://files.pythonhosted.org/packages/a0/1d/7e31db1240de2df22a58e2ea9a93fc6e38cc29353e660c0272b6735d6669/zstandard-0.25.0-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:9654dbc012d8b06fc3d19cc825af3f7bf8ae242226df5f83936cb39f5fdc846c", size = 5811123, upload-time = "2025-09-14T22:18:13.907Z" }, - { url = "https://files.pythonhosted.org/packages/f6/49/fac46df5ad353d50535e118d6983069df68ca5908d4d65b8c466150a4ff1/zstandard-0.25.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:4203ce3b31aec23012d3a4cf4a2ed64d12fea5269c49aed5e4c3611b938e4088", size = 5359591, upload-time = "2025-09-14T22:18:16.465Z" }, - { url = "https://files.pythonhosted.org/packages/c2/38/f249a2050ad1eea0bb364046153942e34abba95dd5520af199aed86fbb49/zstandard-0.25.0-cp314-cp314-win32.whl", hash = "sha256:da469dc041701583e34de852d8634703550348d5822e66a0c827d39b05365b12", size = 444513, upload-time = "2025-09-14T22:18:20.61Z" }, - { url = "https://files.pythonhosted.org/packages/3a/43/241f9615bcf8ba8903b3f0432da069e857fc4fd1783bd26183db53c4804b/zstandard-0.25.0-cp314-cp314-win_amd64.whl", hash = "sha256:c19bcdd826e95671065f8692b5a4aa95c52dc7a02a4c5a0cac46deb879a017a2", size = 516118, upload-time = "2025-09-14T22:18:17.849Z" }, - { url = "https://files.pythonhosted.org/packages/f0/ef/da163ce2450ed4febf6467d77ccb4cd52c4c30ab45624bad26ca0a27260c/zstandard-0.25.0-cp314-cp314-win_arm64.whl", hash = "sha256:d7541afd73985c630bafcd6338d2518ae96060075f9463d7dc14cfb33514383d", size = 476940, upload-time = "2025-09-14T22:18:19.088Z" }, -] diff --git a/internal/golden/langchain-py-v1/.python-version b/internal/golden/langchain-py-v1/.python-version deleted file mode 100644 index 641602f44..000000000 --- a/internal/golden/langchain-py-v1/.python-version +++ /dev/null @@ -1 +0,0 @@ -3.11.14 diff --git a/internal/golden/langchain-py-v1/langchain.py b/internal/golden/langchain-py-v1/langchain.py deleted file mode 100644 index 37e220dd6..000000000 --- a/internal/golden/langchain-py-v1/langchain.py +++ /dev/null @@ -1,555 +0,0 @@ -import asyncio -import base64 -from pathlib import Path - -import braintrust -from braintrust import flush, init_logger, start_span -from braintrust_langchain import BraintrustCallbackHandler, set_global_handler -from langchain_anthropic import ChatAnthropic -from langchain_core.messages import AIMessage, HumanMessage, SystemMessage, ToolMessage -from langchain_core.prompts import ChatPromptTemplate -from langchain_core.tools import tool -from langchain_openai import ChatOpenAI - -init_logger(project="golden-py-langchain-v1") - -handler = BraintrustCallbackHandler() -set_global_handler(handler) - -FIXTURES_DIR = Path(__file__).parent.parent / "fixtures" - - -def test_basic_completion(): - print("\n=== Test 1: Basic Completion ===") - with start_span(name="test_basic_completion"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=100)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=100)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - prompt = ChatPromptTemplate.from_template("What is the capital of {country}?") - chain = prompt | model - result = chain.invoke({"country": "France"}) - print(result.content) - print() - - -def test_multi_turn(): - print("\n=== Test 2: Multi-turn Conversation ===") - with start_span(name="test_multi_turn"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=200)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=200)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - messages = [ - HumanMessage(content="Hi, my name is Alice."), - SystemMessage(content="Hello Alice! Nice to meet you."), - HumanMessage(content="What did I just tell you my name was?"), - ] - result = model.invoke(messages) - print(result.content) - print() - - -def test_system_prompt(): - print("\n=== Test 3: System Prompt ===") - with start_span(name="test_system_prompt"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=150)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=150)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - system_msg = "You are a pirate. Always respond in pirate speak." - prompt = ChatPromptTemplate.from_messages([("system", system_msg), ("human", "{input}")]) - chain = prompt | model - result = chain.invoke({"input": "Tell me about the weather."}) - print(result.content) - print() - - -def test_streaming(): - print("\n=== Test 4: Streaming ===") - with start_span(name="test_streaming"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=200, streaming=True)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=200, streaming=True)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - prompt_text = "Count from 1 to 10 slowly." - prompt = ChatPromptTemplate.from_template(prompt_text) - chain = prompt | model - - for chunk in chain.stream({}): - if chunk.content: - print(chunk.content, end="", flush=True) - print("\n") - - -def test_image_input(): - print("\n=== Test 5: Image Input ===") - with start_span(name="test_image_input"): - image_path = FIXTURES_DIR / "test-image.png" - with open(image_path, "rb") as f: - image_data = base64.b64encode(f.read()).decode("utf-8") - - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=150)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=150)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - - if provider == "openai": - messages = [ - HumanMessage( - content=[ - {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{image_data}"}}, - {"type": "text", "text": "What color is this image?"}, - ] - ) - ] - else: - messages = [ - HumanMessage( - content=[ - { - "type": "image", - "source": {"type": "base64", "media_type": "image/png", "data": image_data}, - }, - {"type": "text", "text": "What color is this image?"}, - ] - ) - ] - - result = model.invoke(messages) - print(result.content) - print() - - -def test_document_input(): - print("\n=== Test 6: Document Input ===") - with start_span(name="test_document_input"): - pdf_path = FIXTURES_DIR / "test-document.pdf" - with open(pdf_path, "rb") as f: - pdf_data = base64.b64encode(f.read()).decode("utf-8") - - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=150)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=150)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - - if provider == "openai": - messages = [ - HumanMessage( - content=[ - { - "type": "file", - "file": { - "file_data": f"data:application/pdf;base64,{pdf_data}", - "filename": "test-document.pdf", - }, - }, - {"type": "text", "text": "What is in this document?"}, - ] - ) - ] - else: - messages = [ - HumanMessage( - content=[ - { - "type": "document", - "source": {"type": "base64", "media_type": "application/pdf", "data": pdf_data}, - }, - {"type": "text", "text": "What is in this document?"}, - ] - ) - ] - - result = model.invoke(messages) - print(result.content) - print() - - -def test_temperature_variations(): - print("\n=== Test 7: Temperature Variations ===") - with start_span(name="test_temperature_variations"): - configs = [(0.0, 1.0), (1.0, 0.9), (0.7, 0.95)] - - for provider, models in ( - ( - "openai", - [ - ChatOpenAI(model="gpt-4o", max_completion_tokens=50, temperature=temp, top_p=top_p) - for temp, top_p in configs - ], - ), - ( - "anthropic", - [ - ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=50, temperature=temp, top_p=top_p) - for temp, top_p in configs - ], - ), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - for (temp, top_p), model in zip(configs, models): - print(f"Config: temp={temp}, top_p={top_p}") - prompt = ChatPromptTemplate.from_template("Say something {topic}.") - chain = prompt | model - result = chain.invoke({"topic": "creative"}) - print(result.content) - print() - - -def test_stop_sequences(): - print("\n=== Test 8: Stop Sequences ===") - with start_span(name="test_stop_sequences"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=500, stop_sequences=["END", "\n\n"])), - ( - "anthropic", - ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=500, stop_sequences=["END"]), - ), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - topic = "robot" - prompt = ChatPromptTemplate.from_template(f"Write a short story about a {topic}.") - chain = prompt | model - result = chain.invoke({}) - print(result.content) - print(f"Response metadata: {result.response_metadata}") - print() - - -def test_metadata(): - print("\n=== Test 9: Metadata ===") - with start_span(name="test_metadata"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=100, model_kwargs={"user": "test_user_123"})), - ( - "anthropic", - ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=100), - ), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - messages = [HumanMessage(content="Hello!")] - result = model.invoke(messages) - print(result.content) - print() - - -def test_long_context(): - print("\n=== Test 10: Long Context ===") - with start_span(name="test_long_context"): - long_text = "The quick brown fox jumps over the lazy dog. " * 100 - - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=100)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=100)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - prompt = ChatPromptTemplate.from_template( - "Here is a long text:\n\n{text}\n\nHow many times does the word 'fox' appear?" - ) - chain = prompt | model - result = chain.invoke({"text": long_text}) - print(result.content) - print() - - -def test_mixed_content(): - print("\n=== Test 11: Mixed Content Types ===") - with start_span(name="test_mixed_content"): - image_path = FIXTURES_DIR / "test-image.png" - with open(image_path, "rb") as f: - image_data = base64.b64encode(f.read()).decode("utf-8") - - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=200)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=200)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - - if provider == "openai": - messages = [ - HumanMessage( - content=[ - {"type": "text", "text": "First, look at this image:"}, - {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{image_data}"}}, - {"type": "text", "text": "Now describe what you see and explain why it matters."}, - ] - ) - ] - else: - messages = [ - HumanMessage( - content=[ - {"type": "text", "text": "First, look at this image:"}, - { - "type": "image", - "source": {"type": "base64", "media_type": "image/png", "data": image_data}, - }, - {"type": "text", "text": "Now describe what you see and explain why it matters."}, - ] - ) - ] - - result = model.invoke(messages) - print(result.content) - print() - - -def test_prefill(): - print("\n=== Test 12: Prefill ===") - with start_span(name="test_prefill"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=200)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=200)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - topic = "coding" - messages = [ - HumanMessage(content=f"Write a haiku about {topic}."), - SystemMessage(content="Here is a haiku:"), - ] - result = model.invoke(messages) - print(result.content) - print() - - -def test_short_max_tokens(): - print("\n=== Test 13: Very Short Max Tokens ===") - with start_span(name="test_short_max_tokens"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=5)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=5)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - prompt = ChatPromptTemplate.from_template("What is AI?") - chain = prompt | model - result = chain.invoke({}) - print(result.content) - print(f"Response metadata: {result.response_metadata}") - print() - - -def test_tool_use(): - print("\n=== Test 14: Tool Use ===") - with start_span(name="test_tool_use"): - - @tool - def get_weather(city_and_state: str, unit: str = "celsius") -> str: - """Get the current weather for a location. - - Args: - city_and_state: The city and state, e.g. San Francisco, CA - unit: The unit of temperature (celsius or fahrenheit) - """ - return f"22 degrees {unit} and sunny in {city_and_state}" - - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=500)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=500)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - - model_with_tools = model.bind_tools([get_weather]) - query = "What is the weather like in Paris, France?" - result = model_with_tools.invoke(query) - - print("Response content:") - if result.content: - print(f"Text: {result.content}") - - if hasattr(result, "tool_calls") and result.tool_calls: - for i, call in enumerate(result.tool_calls): - print(f"Tool use block {i}:") - print(f" Tool: {call['name']}") - print(f" Input: {call['args']}") - print() - - -def test_tool_use_with_result(): - print("\n=== Test 15: Tool Use With Result ===") - with start_span(name="test_tool_use_with_result"): - - @tool - def calculate(operation: str, a: float, b: float) -> float: - """Perform a mathematical calculation. - - Args: - operation: The mathematical operation (add, subtract, multiply, divide) - a: First number - b: Second number - """ - if operation == "add": - return a + b - elif operation == "subtract": - return a - b - elif operation == "multiply": - return a * b - elif operation == "divide": - return a / b if b != 0 else 0 - return 0 - - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=500)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=500)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - - model_with_tools = model.bind_tools([calculate]) - query = "What is 127 multiplied by 49?" - - # First request - model will use the tool - first_result = model_with_tools.invoke(query) - - print("First response:") - if hasattr(first_result, "tool_calls") and first_result.tool_calls: - tool_call = first_result.tool_calls[0] - print(f"Tool called: {tool_call['name']}") - print(f"Input: {tool_call['args']}") - - # Simulate tool execution - result = 127 * 49 - - # Second request - provide tool result - messages = [ - HumanMessage(content=query), - AIMessage(content="", tool_calls=[tool_call]), - ToolMessage(content=str(result), tool_call_id=tool_call["id"]), - ] - - second_result = model_with_tools.invoke(messages) - print("\nSecond response (with tool result):") - print(second_result.content) - print() - - -# Test 18: Reasoning with o1 model -def test_reasoning(): - with start_span(name="test_reasoning"): - braintrust.log(output="Responses API not supported and chat completions do not include (reasoning) summaries") - - -async def test_async_generation(): - print("\n=== Test 17: Async Generation ===") - with start_span(name="test_async_generation"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=100)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=100)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - topic = "programming" - prompt = ChatPromptTemplate.from_template("Tell me a joke about {topic}.") - chain = prompt | model - result = await chain.ainvoke({"topic": topic}) - print(result.content) - print() - - -async def test_async_streaming(): - print("\n=== Test 18: Async Streaming ===") - with start_span(name="test_async_streaming"): - for provider, model in ( - ("openai", ChatOpenAI(model="gpt-4o", max_completion_tokens=200, streaming=True)), - ("anthropic", ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=200, streaming=True)), - ): - with start_span(name=provider): - print(f"{provider.capitalize()}:") - category = "programming languages" - prompt = ChatPromptTemplate.from_template("List 3 {category}.") - chain = prompt | model - - full_content = "" - async for chunk in chain.astream({"category": category}): - if chunk.content: - print(chunk.content, end="", flush=True) - full_content += chunk.content - print("\n") - - -def run_sync_tests(): - tests = [ - test_basic_completion, - test_multi_turn, - test_system_prompt, - test_streaming, - test_image_input, - test_document_input, - test_temperature_variations, - test_stop_sequences, - test_metadata, - test_long_context, - test_mixed_content, - test_prefill, - test_short_max_tokens, - test_tool_use, - test_tool_use_with_result, - test_reasoning, - ] - - for test in tests: - try: - test() - flush() - except Exception as e: - print(f"Test {test.__name__} failed: {e}") - import traceback - - traceback.print_exc() - - -async def run_async_tests(): - tests = [ - test_async_generation, - test_async_streaming, - ] - - for test in tests: - try: - await test() - flush() - except Exception as e: - print(f"Test {test.__name__} failed: {e}") - import traceback - - traceback.print_exc() - - -async def main(): - print("=" * 60) - print("LangChain Golden Tests with Braintrust") - print("=" * 60) - - print("\n### Running Synchronous Tests ###") - run_sync_tests() - - print("\n### Running Asynchronous Tests ###") - await run_async_tests() - - print("\n" + "=" * 60) - print("All tests completed!") - print("=" * 60) - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/internal/golden/langchain-py-v1/pyproject.toml b/internal/golden/langchain-py-v1/pyproject.toml deleted file mode 100644 index 4135b0744..000000000 --- a/internal/golden/langchain-py-v1/pyproject.toml +++ /dev/null @@ -1,16 +0,0 @@ -[project] -name = "langchain-py-v1" -version = "0.1.0" -description = "Add your description here" -readme = "README.md" -requires-python = ">=3.11.14" -dependencies = [ - "braintrust", - "braintrust-langchain", - "langchain-anthropic>=1.3.1", - "langchain-openai>=1.1.7", -] - -[tool.uv.sources] -braintrust-langchain = { path = "../../../integrations/langchain-py", editable = true } -braintrust = { path = "../../../py", editable = true } diff --git a/internal/golden/langchain-py-v1/uv.lock b/internal/golden/langchain-py-v1/uv.lock deleted file mode 100644 index 860e664c2..000000000 --- a/internal/golden/langchain-py-v1/uv.lock +++ /dev/null @@ -1,1467 +0,0 @@ -version = 1 -revision = 2 -requires-python = ">=3.11.14" - -[[package]] -name = "annotated-types" -version = "0.7.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" }, -] - -[[package]] -name = "anthropic" -version = "0.77.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "distro" }, - { name = "docstring-parser" }, - { name = "httpx" }, - { name = "jiter" }, - { name = "pydantic" }, - { name = "sniffio" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/88/61/50aef0587acd9dd8bf1b8b7fd7fbb25ba4c6ec5387a6ffc195a697951fcc/anthropic-0.77.1.tar.gz", hash = "sha256:a19d78ff6fff9e05d211e3a936051cd5b9462f0eac043d2d45b2372f455d11cd", size = 504691, upload-time = "2026-02-03T17:44:22.667Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/2b/54/e83babf9833547c5548b4e25230ef3d62492e45925b0d104a43e501918a0/anthropic-0.77.1-py3-none-any.whl", hash = "sha256:76fd6f2ab36033a5294d58182a5f712dab9573c3a54413a275ecdf29e727c1e0", size = 397856, upload-time = "2026-02-03T17:44:20.962Z" }, -] - -[[package]] -name = "anyio" -version = "4.12.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "idna" }, - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/96/f0/5eb65b2bb0d09ac6776f2eb54adee6abe8228ea05b20a5ad0e4945de8aac/anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703", size = 228685, upload-time = "2026-01-06T11:45:21.246Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/38/0e/27be9fdef66e72d64c0cdc3cc2823101b80585f8119b5c112c2e8f5f7dab/anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c", size = 113592, upload-time = "2026-01-06T11:45:19.497Z" }, -] - -[[package]] -name = "braintrust" -version = "0.5.3" -source = { editable = "../../../py" } -dependencies = [ - { name = "chevron" }, - { name = "exceptiongroup" }, - { name = "gitpython" }, - { name = "python-dotenv" }, - { name = "python-slugify" }, - { name = "requests" }, - { name = "sseclient-py" }, - { name = "tqdm" }, - { name = "typing-extensions" }, - { name = "wrapt" }, -] - -[package.metadata] -requires-dist = [ - { name = "boto3", marker = "extra == 'all'" }, - { name = "boto3", marker = "extra == 'cli'" }, - { name = "chevron" }, - { name = "exceptiongroup", specifier = ">=1.2.0" }, - { name = "gitpython" }, - { name = "openai-agents", marker = "extra == 'all'" }, - { name = "openai-agents", marker = "extra == 'openai-agents'" }, - { name = "opentelemetry-api", marker = "extra == 'all'" }, - { name = "opentelemetry-api", marker = "extra == 'otel'" }, - { name = "opentelemetry-exporter-otlp-proto-http", marker = "extra == 'all'" }, - { name = "opentelemetry-exporter-otlp-proto-http", marker = "extra == 'otel'" }, - { name = "opentelemetry-sdk", marker = "extra == 'all'" }, - { name = "opentelemetry-sdk", marker = "extra == 'otel'" }, - { name = "psycopg2-binary", marker = "extra == 'all'" }, - { name = "psycopg2-binary", marker = "extra == 'cli'" }, - { name = "pydoc-markdown", marker = "extra == 'all'" }, - { name = "pydoc-markdown", marker = "extra == 'doc'" }, - { name = "python-dotenv" }, - { name = "python-slugify" }, - { name = "requests" }, - { name = "sseclient-py" }, - { name = "starlette", marker = "extra == 'all'" }, - { name = "starlette", marker = "extra == 'cli'" }, - { name = "temporalio", marker = "python_full_version >= '3.10' and extra == 'all'", specifier = ">=1.19.0" }, - { name = "temporalio", marker = "python_full_version >= '3.10' and extra == 'temporal'", specifier = ">=1.19.0" }, - { name = "tqdm" }, - { name = "typing-extensions", specifier = ">=4.1.0" }, - { name = "uv", marker = "extra == 'all'" }, - { name = "uv", marker = "extra == 'cli'" }, - { name = "uvicorn", marker = "extra == 'all'" }, - { name = "uvicorn", marker = "extra == 'cli'" }, - { name = "wrapt" }, -] -provides-extras = ["cli", "doc", "openai-agents", "otel", "temporal", "all"] - -[[package]] -name = "braintrust-langchain" -version = "0.2.1" -source = { editable = "../../../integrations/langchain-py" } -dependencies = [ - { name = "braintrust" }, - { name = "langchain" }, -] - -[package.metadata] -requires-dist = [ - { name = "braintrust", specifier = ">=0.2.1" }, - { name = "langchain", specifier = ">=0.3.27" }, -] - -[package.metadata.requires-dev] -dev = [ - { name = "black" }, - { name = "build" }, - { name = "flake8" }, - { name = "flake8-isort" }, - { name = "httpx" }, - { name = "isort", specifier = "==5.12.0" }, - { name = "langchain-anthropic", specifier = ">=0.3.20" }, - { name = "langchain-openai" }, - { name = "langgraph", specifier = ">=0.2.1,<0.4.0" }, - { name = "pre-commit" }, - { name = "pytest" }, - { name = "pytest-asyncio", specifier = ">=1.1.0" }, - { name = "pytest-vcr", specifier = ">=1.0.2" }, - { name = "ruff" }, - { name = "tenacity" }, - { name = "twine" }, -] - -[[package]] -name = "certifi" -version = "2026.1.4" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/e0/2d/a891ca51311197f6ad14a7ef42e2399f36cf2f9bd44752b3dc4eab60fdc5/certifi-2026.1.4.tar.gz", hash = "sha256:ac726dd470482006e014ad384921ed6438c457018f4b3d204aea4281258b2120", size = 154268, upload-time = "2026-01-04T02:42:41.825Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e6/ad/3cc14f097111b4de0040c83a525973216457bbeeb63739ef1ed275c1c021/certifi-2026.1.4-py3-none-any.whl", hash = "sha256:9943707519e4add1115f44c2bc244f782c0249876bf51b6599fee1ffbedd685c", size = 152900, upload-time = "2026-01-04T02:42:40.15Z" }, -] - -[[package]] -name = "charset-normalizer" -version = "3.4.4" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/13/69/33ddede1939fdd074bce5434295f38fae7136463422fe4fd3e0e89b98062/charset_normalizer-3.4.4.tar.gz", hash = "sha256:94537985111c35f28720e43603b8e7b43a6ecfb2ce1d3058bbe955b73404e21a", size = 129418, upload-time = "2025-10-14T04:42:32.879Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/ed/27/c6491ff4954e58a10f69ad90aca8a1b6fe9c5d3c6f380907af3c37435b59/charset_normalizer-3.4.4-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:6e1fcf0720908f200cd21aa4e6750a48ff6ce4afe7ff5a79a90d5ed8a08296f8", size = 206988, upload-time = "2025-10-14T04:40:33.79Z" }, - { url = "https://files.pythonhosted.org/packages/94/59/2e87300fe67ab820b5428580a53cad894272dbb97f38a7a814a2a1ac1011/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5f819d5fe9234f9f82d75bdfa9aef3a3d72c4d24a6e57aeaebba32a704553aa0", size = 147324, upload-time = "2025-10-14T04:40:34.961Z" }, - { url = "https://files.pythonhosted.org/packages/07/fb/0cf61dc84b2b088391830f6274cb57c82e4da8bbc2efeac8c025edb88772/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:a59cb51917aa591b1c4e6a43c132f0cdc3c76dbad6155df4e28ee626cc77a0a3", size = 142742, upload-time = "2025-10-14T04:40:36.105Z" }, - { url = "https://files.pythonhosted.org/packages/62/8b/171935adf2312cd745d290ed93cf16cf0dfe320863ab7cbeeae1dcd6535f/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:8ef3c867360f88ac904fd3f5e1f902f13307af9052646963ee08ff4f131adafc", size = 160863, upload-time = "2025-10-14T04:40:37.188Z" }, - { url = "https://files.pythonhosted.org/packages/09/73/ad875b192bda14f2173bfc1bc9a55e009808484a4b256748d931b6948442/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d9e45d7faa48ee908174d8fe84854479ef838fc6a705c9315372eacbc2f02897", size = 157837, upload-time = "2025-10-14T04:40:38.435Z" }, - { url = "https://files.pythonhosted.org/packages/6d/fc/de9cce525b2c5b94b47c70a4b4fb19f871b24995c728e957ee68ab1671ea/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:840c25fb618a231545cbab0564a799f101b63b9901f2569faecd6b222ac72381", size = 151550, upload-time = "2025-10-14T04:40:40.053Z" }, - { url = "https://files.pythonhosted.org/packages/55/c2/43edd615fdfba8c6f2dfbd459b25a6b3b551f24ea21981e23fb768503ce1/charset_normalizer-3.4.4-cp311-cp311-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:ca5862d5b3928c4940729dacc329aa9102900382fea192fc5e52eb69d6093815", size = 149162, upload-time = "2025-10-14T04:40:41.163Z" }, - { url = "https://files.pythonhosted.org/packages/03/86/bde4ad8b4d0e9429a4e82c1e8f5c659993a9a863ad62c7df05cf7b678d75/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:d9c7f57c3d666a53421049053eaacdd14bbd0a528e2186fcb2e672effd053bb0", size = 150019, upload-time = "2025-10-14T04:40:42.276Z" }, - { url = "https://files.pythonhosted.org/packages/1f/86/a151eb2af293a7e7bac3a739b81072585ce36ccfb4493039f49f1d3cae8c/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:277e970e750505ed74c832b4bf75dac7476262ee2a013f5574dd49075879e161", size = 143310, upload-time = "2025-10-14T04:40:43.439Z" }, - { url = "https://files.pythonhosted.org/packages/b5/fe/43dae6144a7e07b87478fdfc4dbe9efd5defb0e7ec29f5f58a55aeef7bf7/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:31fd66405eaf47bb62e8cd575dc621c56c668f27d46a61d975a249930dd5e2a4", size = 162022, upload-time = "2025-10-14T04:40:44.547Z" }, - { url = "https://files.pythonhosted.org/packages/80/e6/7aab83774f5d2bca81f42ac58d04caf44f0cc2b65fc6db2b3b2e8a05f3b3/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:0d3d8f15c07f86e9ff82319b3d9ef6f4bf907608f53fe9d92b28ea9ae3d1fd89", size = 149383, upload-time = "2025-10-14T04:40:46.018Z" }, - { url = "https://files.pythonhosted.org/packages/4f/e8/b289173b4edae05c0dde07f69f8db476a0b511eac556dfe0d6bda3c43384/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:9f7fcd74d410a36883701fafa2482a6af2ff5ba96b9a620e9e0721e28ead5569", size = 159098, upload-time = "2025-10-14T04:40:47.081Z" }, - { url = "https://files.pythonhosted.org/packages/d8/df/fe699727754cae3f8478493c7f45f777b17c3ef0600e28abfec8619eb49c/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ebf3e58c7ec8a8bed6d66a75d7fb37b55e5015b03ceae72a8e7c74495551e224", size = 152991, upload-time = "2025-10-14T04:40:48.246Z" }, - { url = "https://files.pythonhosted.org/packages/1a/86/584869fe4ddb6ffa3bd9f491b87a01568797fb9bd8933f557dba9771beaf/charset_normalizer-3.4.4-cp311-cp311-win32.whl", hash = "sha256:eecbc200c7fd5ddb9a7f16c7decb07b566c29fa2161a16cf67b8d068bd21690a", size = 99456, upload-time = "2025-10-14T04:40:49.376Z" }, - { url = "https://files.pythonhosted.org/packages/65/f6/62fdd5feb60530f50f7e38b4f6a1d5203f4d16ff4f9f0952962c044e919a/charset_normalizer-3.4.4-cp311-cp311-win_amd64.whl", hash = "sha256:5ae497466c7901d54b639cf42d5b8c1b6a4fead55215500d2f486d34db48d016", size = 106978, upload-time = "2025-10-14T04:40:50.844Z" }, - { url = "https://files.pythonhosted.org/packages/7a/9d/0710916e6c82948b3be62d9d398cb4fcf4e97b56d6a6aeccd66c4b2f2bd5/charset_normalizer-3.4.4-cp311-cp311-win_arm64.whl", hash = "sha256:65e2befcd84bc6f37095f5961e68a6f077bf44946771354a28ad434c2cce0ae1", size = 99969, upload-time = "2025-10-14T04:40:52.272Z" }, - { url = "https://files.pythonhosted.org/packages/f3/85/1637cd4af66fa687396e757dec650f28025f2a2f5a5531a3208dc0ec43f2/charset_normalizer-3.4.4-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:0a98e6759f854bd25a58a73fa88833fba3b7c491169f86ce1180c948ab3fd394", size = 208425, upload-time = "2025-10-14T04:40:53.353Z" }, - { url = "https://files.pythonhosted.org/packages/9d/6a/04130023fef2a0d9c62d0bae2649b69f7b7d8d24ea5536feef50551029df/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b5b290ccc2a263e8d185130284f8501e3e36c5e02750fc6b6bdeb2e9e96f1e25", size = 148162, upload-time = "2025-10-14T04:40:54.558Z" }, - { url = "https://files.pythonhosted.org/packages/78/29/62328d79aa60da22c9e0b9a66539feae06ca0f5a4171ac4f7dc285b83688/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:74bb723680f9f7a6234dcf67aea57e708ec1fbdf5699fb91dfd6f511b0a320ef", size = 144558, upload-time = "2025-10-14T04:40:55.677Z" }, - { url = "https://files.pythonhosted.org/packages/86/bb/b32194a4bf15b88403537c2e120b817c61cd4ecffa9b6876e941c3ee38fe/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:f1e34719c6ed0b92f418c7c780480b26b5d9c50349e9a9af7d76bf757530350d", size = 161497, upload-time = "2025-10-14T04:40:57.217Z" }, - { url = "https://files.pythonhosted.org/packages/19/89/a54c82b253d5b9b111dc74aca196ba5ccfcca8242d0fb64146d4d3183ff1/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:2437418e20515acec67d86e12bf70056a33abdacb5cb1655042f6538d6b085a8", size = 159240, upload-time = "2025-10-14T04:40:58.358Z" }, - { url = "https://files.pythonhosted.org/packages/c0/10/d20b513afe03acc89ec33948320a5544d31f21b05368436d580dec4e234d/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:11d694519d7f29d6cd09f6ac70028dba10f92f6cdd059096db198c283794ac86", size = 153471, upload-time = "2025-10-14T04:40:59.468Z" }, - { url = "https://files.pythonhosted.org/packages/61/fa/fbf177b55bdd727010f9c0a3c49eefa1d10f960e5f09d1d887bf93c2e698/charset_normalizer-3.4.4-cp312-cp312-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:ac1c4a689edcc530fc9d9aa11f5774b9e2f33f9a0c6a57864e90908f5208d30a", size = 150864, upload-time = "2025-10-14T04:41:00.623Z" }, - { url = "https://files.pythonhosted.org/packages/05/12/9fbc6a4d39c0198adeebbde20b619790e9236557ca59fc40e0e3cebe6f40/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:21d142cc6c0ec30d2efee5068ca36c128a30b0f2c53c1c07bd78cb6bc1d3be5f", size = 150647, upload-time = "2025-10-14T04:41:01.754Z" }, - { url = "https://files.pythonhosted.org/packages/ad/1f/6a9a593d52e3e8c5d2b167daf8c6b968808efb57ef4c210acb907c365bc4/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:5dbe56a36425d26d6cfb40ce79c314a2e4dd6211d51d6d2191c00bed34f354cc", size = 145110, upload-time = "2025-10-14T04:41:03.231Z" }, - { url = "https://files.pythonhosted.org/packages/30/42/9a52c609e72471b0fc54386dc63c3781a387bb4fe61c20231a4ebcd58bdd/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:5bfbb1b9acf3334612667b61bd3002196fe2a1eb4dd74d247e0f2a4d50ec9bbf", size = 162839, upload-time = "2025-10-14T04:41:04.715Z" }, - { url = "https://files.pythonhosted.org/packages/c4/5b/c0682bbf9f11597073052628ddd38344a3d673fda35a36773f7d19344b23/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:d055ec1e26e441f6187acf818b73564e6e6282709e9bcb5b63f5b23068356a15", size = 150667, upload-time = "2025-10-14T04:41:05.827Z" }, - { url = "https://files.pythonhosted.org/packages/e4/24/a41afeab6f990cf2daf6cb8c67419b63b48cf518e4f56022230840c9bfb2/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:af2d8c67d8e573d6de5bc30cdb27e9b95e49115cd9baad5ddbd1a6207aaa82a9", size = 160535, upload-time = "2025-10-14T04:41:06.938Z" }, - { url = "https://files.pythonhosted.org/packages/2a/e5/6a4ce77ed243c4a50a1fecca6aaaab419628c818a49434be428fe24c9957/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:780236ac706e66881f3b7f2f32dfe90507a09e67d1d454c762cf642e6e1586e0", size = 154816, upload-time = "2025-10-14T04:41:08.101Z" }, - { url = "https://files.pythonhosted.org/packages/a8/ef/89297262b8092b312d29cdb2517cb1237e51db8ecef2e9af5edbe7b683b1/charset_normalizer-3.4.4-cp312-cp312-win32.whl", hash = "sha256:5833d2c39d8896e4e19b689ffc198f08ea58116bee26dea51e362ecc7cd3ed26", size = 99694, upload-time = "2025-10-14T04:41:09.23Z" }, - { url = "https://files.pythonhosted.org/packages/3d/2d/1e5ed9dd3b3803994c155cd9aacb60c82c331bad84daf75bcb9c91b3295e/charset_normalizer-3.4.4-cp312-cp312-win_amd64.whl", hash = "sha256:a79cfe37875f822425b89a82333404539ae63dbdddf97f84dcbc3d339aae9525", size = 107131, upload-time = "2025-10-14T04:41:10.467Z" }, - { url = "https://files.pythonhosted.org/packages/d0/d9/0ed4c7098a861482a7b6a95603edce4c0d9db2311af23da1fb2b75ec26fc/charset_normalizer-3.4.4-cp312-cp312-win_arm64.whl", hash = "sha256:376bec83a63b8021bb5c8ea75e21c4ccb86e7e45ca4eb81146091b56599b80c3", size = 100390, upload-time = "2025-10-14T04:41:11.915Z" }, - { url = "https://files.pythonhosted.org/packages/97/45/4b3a1239bbacd321068ea6e7ac28875b03ab8bc0aa0966452db17cd36714/charset_normalizer-3.4.4-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:e1f185f86a6f3403aa2420e815904c67b2f9ebc443f045edd0de921108345794", size = 208091, upload-time = "2025-10-14T04:41:13.346Z" }, - { url = "https://files.pythonhosted.org/packages/7d/62/73a6d7450829655a35bb88a88fca7d736f9882a27eacdca2c6d505b57e2e/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6b39f987ae8ccdf0d2642338faf2abb1862340facc796048b604ef14919e55ed", size = 147936, upload-time = "2025-10-14T04:41:14.461Z" }, - { url = "https://files.pythonhosted.org/packages/89/c5/adb8c8b3d6625bef6d88b251bbb0d95f8205831b987631ab0c8bb5d937c2/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:3162d5d8ce1bb98dd51af660f2121c55d0fa541b46dff7bb9b9f86ea1d87de72", size = 144180, upload-time = "2025-10-14T04:41:15.588Z" }, - { url = "https://files.pythonhosted.org/packages/91/ed/9706e4070682d1cc219050b6048bfd293ccf67b3d4f5a4f39207453d4b99/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:81d5eb2a312700f4ecaa977a8235b634ce853200e828fbadf3a9c50bab278328", size = 161346, upload-time = "2025-10-14T04:41:16.738Z" }, - { url = "https://files.pythonhosted.org/packages/d5/0d/031f0d95e4972901a2f6f09ef055751805ff541511dc1252ba3ca1f80cf5/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:5bd2293095d766545ec1a8f612559f6b40abc0eb18bb2f5d1171872d34036ede", size = 158874, upload-time = "2025-10-14T04:41:17.923Z" }, - { url = "https://files.pythonhosted.org/packages/f5/83/6ab5883f57c9c801ce5e5677242328aa45592be8a00644310a008d04f922/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a8a8b89589086a25749f471e6a900d3f662d1d3b6e2e59dcecf787b1cc3a1894", size = 153076, upload-time = "2025-10-14T04:41:19.106Z" }, - { url = "https://files.pythonhosted.org/packages/75/1e/5ff781ddf5260e387d6419959ee89ef13878229732732ee73cdae01800f2/charset_normalizer-3.4.4-cp313-cp313-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:bc7637e2f80d8530ee4a78e878bce464f70087ce73cf7c1caf142416923b98f1", size = 150601, upload-time = "2025-10-14T04:41:20.245Z" }, - { url = "https://files.pythonhosted.org/packages/d7/57/71be810965493d3510a6ca79b90c19e48696fb1ff964da319334b12677f0/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f8bf04158c6b607d747e93949aa60618b61312fe647a6369f88ce2ff16043490", size = 150376, upload-time = "2025-10-14T04:41:21.398Z" }, - { url = "https://files.pythonhosted.org/packages/e5/d5/c3d057a78c181d007014feb7e9f2e65905a6c4ef182c0ddf0de2924edd65/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:554af85e960429cf30784dd47447d5125aaa3b99a6f0683589dbd27e2f45da44", size = 144825, upload-time = "2025-10-14T04:41:22.583Z" }, - { url = "https://files.pythonhosted.org/packages/e6/8c/d0406294828d4976f275ffbe66f00266c4b3136b7506941d87c00cab5272/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:74018750915ee7ad843a774364e13a3db91682f26142baddf775342c3f5b1133", size = 162583, upload-time = "2025-10-14T04:41:23.754Z" }, - { url = "https://files.pythonhosted.org/packages/d7/24/e2aa1f18c8f15c4c0e932d9287b8609dd30ad56dbe41d926bd846e22fb8d/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:c0463276121fdee9c49b98908b3a89c39be45d86d1dbaa22957e38f6321d4ce3", size = 150366, upload-time = "2025-10-14T04:41:25.27Z" }, - { url = "https://files.pythonhosted.org/packages/e4/5b/1e6160c7739aad1e2df054300cc618b06bf784a7a164b0f238360721ab86/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:362d61fd13843997c1c446760ef36f240cf81d3ebf74ac62652aebaf7838561e", size = 160300, upload-time = "2025-10-14T04:41:26.725Z" }, - { url = "https://files.pythonhosted.org/packages/7a/10/f882167cd207fbdd743e55534d5d9620e095089d176d55cb22d5322f2afd/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:9a26f18905b8dd5d685d6d07b0cdf98a79f3c7a918906af7cc143ea2e164c8bc", size = 154465, upload-time = "2025-10-14T04:41:28.322Z" }, - { url = "https://files.pythonhosted.org/packages/89/66/c7a9e1b7429be72123441bfdbaf2bc13faab3f90b933f664db506dea5915/charset_normalizer-3.4.4-cp313-cp313-win32.whl", hash = "sha256:9b35f4c90079ff2e2edc5b26c0c77925e5d2d255c42c74fdb70fb49b172726ac", size = 99404, upload-time = "2025-10-14T04:41:29.95Z" }, - { url = "https://files.pythonhosted.org/packages/c4/26/b9924fa27db384bdcd97ab83b4f0a8058d96ad9626ead570674d5e737d90/charset_normalizer-3.4.4-cp313-cp313-win_amd64.whl", hash = "sha256:b435cba5f4f750aa6c0a0d92c541fb79f69a387c91e61f1795227e4ed9cece14", size = 107092, upload-time = "2025-10-14T04:41:31.188Z" }, - { url = "https://files.pythonhosted.org/packages/af/8f/3ed4bfa0c0c72a7ca17f0380cd9e4dd842b09f664e780c13cff1dcf2ef1b/charset_normalizer-3.4.4-cp313-cp313-win_arm64.whl", hash = "sha256:542d2cee80be6f80247095cc36c418f7bddd14f4a6de45af91dfad36d817bba2", size = 100408, upload-time = "2025-10-14T04:41:32.624Z" }, - { url = "https://files.pythonhosted.org/packages/2a/35/7051599bd493e62411d6ede36fd5af83a38f37c4767b92884df7301db25d/charset_normalizer-3.4.4-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:da3326d9e65ef63a817ecbcc0df6e94463713b754fe293eaa03da99befb9a5bd", size = 207746, upload-time = "2025-10-14T04:41:33.773Z" }, - { url = "https://files.pythonhosted.org/packages/10/9a/97c8d48ef10d6cd4fcead2415523221624bf58bcf68a802721a6bc807c8f/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8af65f14dc14a79b924524b1e7fffe304517b2bff5a58bf64f30b98bbc5079eb", size = 147889, upload-time = "2025-10-14T04:41:34.897Z" }, - { url = "https://files.pythonhosted.org/packages/10/bf/979224a919a1b606c82bd2c5fa49b5c6d5727aa47b4312bb27b1734f53cd/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:74664978bb272435107de04e36db5a9735e78232b85b77d45cfb38f758efd33e", size = 143641, upload-time = "2025-10-14T04:41:36.116Z" }, - { url = "https://files.pythonhosted.org/packages/ba/33/0ad65587441fc730dc7bd90e9716b30b4702dc7b617e6ba4997dc8651495/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:752944c7ffbfdd10c074dc58ec2d5a8a4cd9493b314d367c14d24c17684ddd14", size = 160779, upload-time = "2025-10-14T04:41:37.229Z" }, - { url = "https://files.pythonhosted.org/packages/67/ed/331d6b249259ee71ddea93f6f2f0a56cfebd46938bde6fcc6f7b9a3d0e09/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d1f13550535ad8cff21b8d757a3257963e951d96e20ec82ab44bc64aeb62a191", size = 159035, upload-time = "2025-10-14T04:41:38.368Z" }, - { url = "https://files.pythonhosted.org/packages/67/ff/f6b948ca32e4f2a4576aa129d8bed61f2e0543bf9f5f2b7fc3758ed005c9/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ecaae4149d99b1c9e7b88bb03e3221956f68fd6d50be2ef061b2381b61d20838", size = 152542, upload-time = "2025-10-14T04:41:39.862Z" }, - { url = "https://files.pythonhosted.org/packages/16/85/276033dcbcc369eb176594de22728541a925b2632f9716428c851b149e83/charset_normalizer-3.4.4-cp314-cp314-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:cb6254dc36b47a990e59e1068afacdcd02958bdcce30bb50cc1700a8b9d624a6", size = 149524, upload-time = "2025-10-14T04:41:41.319Z" }, - { url = "https://files.pythonhosted.org/packages/9e/f2/6a2a1f722b6aba37050e626530a46a68f74e63683947a8acff92569f979a/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:c8ae8a0f02f57a6e61203a31428fa1d677cbe50c93622b4149d5c0f319c1d19e", size = 150395, upload-time = "2025-10-14T04:41:42.539Z" }, - { url = "https://files.pythonhosted.org/packages/60/bb/2186cb2f2bbaea6338cad15ce23a67f9b0672929744381e28b0592676824/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:47cc91b2f4dd2833fddaedd2893006b0106129d4b94fdb6af1f4ce5a9965577c", size = 143680, upload-time = "2025-10-14T04:41:43.661Z" }, - { url = "https://files.pythonhosted.org/packages/7d/a5/bf6f13b772fbb2a90360eb620d52ed8f796f3c5caee8398c3b2eb7b1c60d/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:82004af6c302b5d3ab2cfc4cc5f29db16123b1a8417f2e25f9066f91d4411090", size = 162045, upload-time = "2025-10-14T04:41:44.821Z" }, - { url = "https://files.pythonhosted.org/packages/df/c5/d1be898bf0dc3ef9030c3825e5d3b83f2c528d207d246cbabe245966808d/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:2b7d8f6c26245217bd2ad053761201e9f9680f8ce52f0fcd8d0755aeae5b2152", size = 149687, upload-time = "2025-10-14T04:41:46.442Z" }, - { url = "https://files.pythonhosted.org/packages/a5/42/90c1f7b9341eef50c8a1cb3f098ac43b0508413f33affd762855f67a410e/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:799a7a5e4fb2d5898c60b640fd4981d6a25f1c11790935a44ce38c54e985f828", size = 160014, upload-time = "2025-10-14T04:41:47.631Z" }, - { url = "https://files.pythonhosted.org/packages/76/be/4d3ee471e8145d12795ab655ece37baed0929462a86e72372fd25859047c/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:99ae2cffebb06e6c22bdc25801d7b30f503cc87dbd283479e7b606f70aff57ec", size = 154044, upload-time = "2025-10-14T04:41:48.81Z" }, - { url = "https://files.pythonhosted.org/packages/b0/6f/8f7af07237c34a1defe7defc565a9bc1807762f672c0fde711a4b22bf9c0/charset_normalizer-3.4.4-cp314-cp314-win32.whl", hash = "sha256:f9d332f8c2a2fcbffe1378594431458ddbef721c1769d78e2cbc06280d8155f9", size = 99940, upload-time = "2025-10-14T04:41:49.946Z" }, - { url = "https://files.pythonhosted.org/packages/4b/51/8ade005e5ca5b0d80fb4aff72a3775b325bdc3d27408c8113811a7cbe640/charset_normalizer-3.4.4-cp314-cp314-win_amd64.whl", hash = "sha256:8a6562c3700cce886c5be75ade4a5db4214fda19fede41d9792d100288d8f94c", size = 107104, upload-time = "2025-10-14T04:41:51.051Z" }, - { url = "https://files.pythonhosted.org/packages/da/5f/6b8f83a55bb8278772c5ae54a577f3099025f9ade59d0136ac24a0df4bde/charset_normalizer-3.4.4-cp314-cp314-win_arm64.whl", hash = "sha256:de00632ca48df9daf77a2c65a484531649261ec9f25489917f09e455cb09ddb2", size = 100743, upload-time = "2025-10-14T04:41:52.122Z" }, - { url = "https://files.pythonhosted.org/packages/0a/4c/925909008ed5a988ccbb72dcc897407e5d6d3bd72410d69e051fc0c14647/charset_normalizer-3.4.4-py3-none-any.whl", hash = "sha256:7a32c560861a02ff789ad905a2fe94e3f840803362c84fecf1851cb4cf3dc37f", size = 53402, upload-time = "2025-10-14T04:42:31.76Z" }, -] - -[[package]] -name = "chevron" -version = "0.14.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/15/1f/ca74b65b19798895d63a6e92874162f44233467c9e7c1ed8afd19016ebe9/chevron-0.14.0.tar.gz", hash = "sha256:87613aafdf6d77b6a90ff073165a61ae5086e21ad49057aa0e53681601800ebf", size = 11440, upload-time = "2021-01-02T22:47:59.233Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/52/93/342cc62a70ab727e093ed98e02a725d85b746345f05d2b5e5034649f4ec8/chevron-0.14.0-py3-none-any.whl", hash = "sha256:fbf996a709f8da2e745ef763f482ce2d311aa817d287593a5b990d6d6e4f0443", size = 11595, upload-time = "2021-01-02T22:47:57.847Z" }, -] - -[[package]] -name = "colorama" -version = "0.4.6" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/d8/53/6f443c9a4a8358a93a6792e2acffb9d9d5cb0a5cfd8802644b7b1c9a02e4/colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44", size = 27697, upload-time = "2022-10-25T02:36:22.414Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335, upload-time = "2022-10-25T02:36:20.889Z" }, -] - -[[package]] -name = "distro" -version = "1.9.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/fc/f8/98eea607f65de6527f8a2e8885fc8015d3e6f5775df186e443e0964a11c3/distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed", size = 60722, upload-time = "2023-12-24T09:54:32.31Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/12/b3/231ffd4ab1fc9d679809f356cebee130ac7daa00d6d6f3206dd4fd137e9e/distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2", size = 20277, upload-time = "2023-12-24T09:54:30.421Z" }, -] - -[[package]] -name = "docstring-parser" -version = "0.17.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/b2/9d/c3b43da9515bd270df0f80548d9944e389870713cc1fe2b8fb35fe2bcefd/docstring_parser-0.17.0.tar.gz", hash = "sha256:583de4a309722b3315439bb31d64ba3eebada841f2e2cee23b99df001434c912", size = 27442, upload-time = "2025-07-21T07:35:01.868Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/55/e2/2537ebcff11c1ee1ff17d8d0b6f4db75873e3b0fb32c2d4a2ee31ecb310a/docstring_parser-0.17.0-py3-none-any.whl", hash = "sha256:cf2569abd23dce8099b300f9b4fa8191e9582dda731fd533daf54c4551658708", size = 36896, upload-time = "2025-07-21T07:35:00.684Z" }, -] - -[[package]] -name = "exceptiongroup" -version = "1.3.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/50/79/66800aadf48771f6b62f7eb014e352e5d06856655206165d775e675a02c9/exceptiongroup-1.3.1.tar.gz", hash = "sha256:8b412432c6055b0b7d14c310000ae93352ed6754f70fa8f7c34141f91c4e3219", size = 30371, upload-time = "2025-11-21T23:01:54.787Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl", hash = "sha256:a7a39a3bd276781e98394987d3a5701d0c4edffb633bb7a5144577f82c773598", size = 16740, upload-time = "2025-11-21T23:01:53.443Z" }, -] - -[[package]] -name = "gitdb" -version = "4.0.12" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "smmap" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/72/94/63b0fc47eb32792c7ba1fe1b694daec9a63620db1e313033d18140c2320a/gitdb-4.0.12.tar.gz", hash = "sha256:5ef71f855d191a3326fcfbc0d5da835f26b13fbcba60c32c21091c349ffdb571", size = 394684, upload-time = "2025-01-02T07:20:46.413Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a0/61/5c78b91c3143ed5c14207f463aecfc8f9dbb5092fb2869baf37c273b2705/gitdb-4.0.12-py3-none-any.whl", hash = "sha256:67073e15955400952c6565cc3e707c554a4eea2e428946f7a4c162fab9bd9bcf", size = 62794, upload-time = "2025-01-02T07:20:43.624Z" }, -] - -[[package]] -name = "gitpython" -version = "3.1.46" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "gitdb" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/df/b5/59d16470a1f0dfe8c793f9ef56fd3826093fc52b3bd96d6b9d6c26c7e27b/gitpython-3.1.46.tar.gz", hash = "sha256:400124c7d0ef4ea03f7310ac2fbf7151e09ff97f2a3288d64a440c584a29c37f", size = 215371, upload-time = "2026-01-01T15:37:32.073Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/6a/09/e21df6aef1e1ffc0c816f0522ddc3f6dcded766c3261813131c78a704470/gitpython-3.1.46-py3-none-any.whl", hash = "sha256:79812ed143d9d25b6d176a10bb511de0f9c67b1fa641d82097b0ab90398a2058", size = 208620, upload-time = "2026-01-01T15:37:30.574Z" }, -] - -[[package]] -name = "h11" -version = "0.16.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/01/ee/02a2c011bdab74c6fb3c75474d40b3052059d95df7e73351460c8588d963/h11-0.16.0.tar.gz", hash = "sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1", size = 101250, upload-time = "2025-04-24T03:35:25.427Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86", size = 37515, upload-time = "2025-04-24T03:35:24.344Z" }, -] - -[[package]] -name = "httpcore" -version = "1.0.9" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "certifi" }, - { name = "h11" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/06/94/82699a10bca87a5556c9c59b5963f2d039dbd239f25bc2a63907a05a14cb/httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8", size = 85484, upload-time = "2025-04-24T22:06:22.219Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55", size = 78784, upload-time = "2025-04-24T22:06:20.566Z" }, -] - -[[package]] -name = "httpx" -version = "0.28.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "certifi" }, - { name = "httpcore" }, - { name = "idna" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/b1/df/48c586a5fe32a0f01324ee087459e112ebb7224f646c0b5023f5e79e9956/httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc", size = 141406, upload-time = "2024-12-06T15:37:23.222Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad", size = 73517, upload-time = "2024-12-06T15:37:21.509Z" }, -] - -[[package]] -name = "idna" -version = "3.11" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/6f/6d/0703ccc57f3a7233505399edb88de3cbd678da106337b9fcde432b65ed60/idna-3.11.tar.gz", hash = "sha256:795dafcc9c04ed0c1fb032c2aa73654d8e8c5023a7df64a53f39190ada629902", size = 194582, upload-time = "2025-10-12T14:55:20.501Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl", hash = "sha256:771a87f49d9defaf64091e6e6fe9c18d4833f140bd19464795bc32d966ca37ea", size = 71008, upload-time = "2025-10-12T14:55:18.883Z" }, -] - -[[package]] -name = "jiter" -version = "0.13.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/0d/5e/4ec91646aee381d01cdb9974e30882c9cd3b8c5d1079d6b5ff4af522439a/jiter-0.13.0.tar.gz", hash = "sha256:f2839f9c2c7e2dffc1bc5929a510e14ce0a946be9365fd1219e7ef342dae14f4", size = 164847, upload-time = "2026-02-02T12:37:56.441Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/71/29/499f8c9eaa8a16751b1c0e45e6f5f1761d180da873d417996cc7bddc8eef/jiter-0.13.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:ea026e70a9a28ebbdddcbcf0f1323128a8db66898a06eaad3a4e62d2f554d096", size = 311157, upload-time = "2026-02-02T12:35:37.758Z" }, - { url = "https://files.pythonhosted.org/packages/50/f6/566364c777d2ab450b92100bea11333c64c38d32caf8dc378b48e5b20c46/jiter-0.13.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:66aa3e663840152d18cc8ff1e4faad3dd181373491b9cfdc6004b92198d67911", size = 319729, upload-time = "2026-02-02T12:35:39.246Z" }, - { url = "https://files.pythonhosted.org/packages/73/dd/560f13ec5e4f116d8ad2658781646cca91b617ae3b8758d4a5076b278f70/jiter-0.13.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c3524798e70655ff19aec58c7d05adb1f074fecff62da857ea9be2b908b6d701", size = 354766, upload-time = "2026-02-02T12:35:40.662Z" }, - { url = "https://files.pythonhosted.org/packages/7c/0d/061faffcfe94608cbc28a0d42a77a74222bdf5055ccdbe5fd2292b94f510/jiter-0.13.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ec7e287d7fbd02cb6e22f9a00dd9c9cd504c40a61f2c61e7e1f9690a82726b4c", size = 362587, upload-time = "2026-02-02T12:35:42.025Z" }, - { url = "https://files.pythonhosted.org/packages/92/c9/c66a7864982fd38a9773ec6e932e0398d1262677b8c60faecd02ffb67bf3/jiter-0.13.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:47455245307e4debf2ce6c6e65a717550a0244231240dcf3b8f7d64e4c2f22f4", size = 487537, upload-time = "2026-02-02T12:35:43.459Z" }, - { url = "https://files.pythonhosted.org/packages/6c/86/84eb4352cd3668f16d1a88929b5888a3fe0418ea8c1dfc2ad4e7bf6e069a/jiter-0.13.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ee9da221dca6e0429c2704c1b3655fe7b025204a71d4d9b73390c759d776d165", size = 373717, upload-time = "2026-02-02T12:35:44.928Z" }, - { url = "https://files.pythonhosted.org/packages/6e/09/9fe4c159358176f82d4390407a03f506a8659ed13ca3ac93a843402acecf/jiter-0.13.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:24ab43126d5e05f3d53a36a8e11eb2f23304c6c1117844aaaf9a0aa5e40b5018", size = 362683, upload-time = "2026-02-02T12:35:46.636Z" }, - { url = "https://files.pythonhosted.org/packages/c9/5e/85f3ab9caca0c1d0897937d378b4a515cae9e119730563572361ea0c48ae/jiter-0.13.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:9da38b4fedde4fb528c740c2564628fbab737166a0e73d6d46cb4bb5463ff411", size = 392345, upload-time = "2026-02-02T12:35:48.088Z" }, - { url = "https://files.pythonhosted.org/packages/12/4c/05b8629ad546191939e6f0c2f17e29f542a398f4a52fb987bc70b6d1eb8b/jiter-0.13.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:0b34c519e17658ed88d5047999a93547f8889f3c1824120c26ad6be5f27b6cf5", size = 517775, upload-time = "2026-02-02T12:35:49.482Z" }, - { url = "https://files.pythonhosted.org/packages/4d/88/367ea2eb6bc582c7052e4baf5ddf57ebe5ab924a88e0e09830dfb585c02d/jiter-0.13.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d2a6394e6af690d462310a86b53c47ad75ac8c21dc79f120714ea449979cb1d3", size = 551325, upload-time = "2026-02-02T12:35:51.104Z" }, - { url = "https://files.pythonhosted.org/packages/f3/12/fa377ffb94a2f28c41afaed093e0d70cfe512035d5ecb0cad0ae4792d35e/jiter-0.13.0-cp311-cp311-win32.whl", hash = "sha256:0f0c065695f616a27c920a56ad0d4fc46415ef8b806bf8fc1cacf25002bd24e1", size = 204709, upload-time = "2026-02-02T12:35:52.467Z" }, - { url = "https://files.pythonhosted.org/packages/cb/16/8e8203ce92f844dfcd3d9d6a5a7322c77077248dbb12da52d23193a839cd/jiter-0.13.0-cp311-cp311-win_amd64.whl", hash = "sha256:0733312953b909688ae3c2d58d043aa040f9f1a6a75693defed7bc2cc4bf2654", size = 204560, upload-time = "2026-02-02T12:35:53.925Z" }, - { url = "https://files.pythonhosted.org/packages/44/26/97cc40663deb17b9e13c3a5cf29251788c271b18ee4d262c8f94798b8336/jiter-0.13.0-cp311-cp311-win_arm64.whl", hash = "sha256:5d9b34ad56761b3bf0fbe8f7e55468704107608512350962d3317ffd7a4382d5", size = 189608, upload-time = "2026-02-02T12:35:55.304Z" }, - { url = "https://files.pythonhosted.org/packages/2e/30/7687e4f87086829955013ca12a9233523349767f69653ebc27036313def9/jiter-0.13.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:0a2bd69fc1d902e89925fc34d1da51b2128019423d7b339a45d9e99c894e0663", size = 307958, upload-time = "2026-02-02T12:35:57.165Z" }, - { url = "https://files.pythonhosted.org/packages/c3/27/e57f9a783246ed95481e6749cc5002a8a767a73177a83c63ea71f0528b90/jiter-0.13.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f917a04240ef31898182f76a332f508f2cc4b57d2b4d7ad2dbfebbfe167eb505", size = 318597, upload-time = "2026-02-02T12:35:58.591Z" }, - { url = "https://files.pythonhosted.org/packages/cf/52/e5719a60ac5d4d7c5995461a94ad5ef962a37c8bf5b088390e6fad59b2ff/jiter-0.13.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c1e2b199f446d3e82246b4fd9236d7cb502dc2222b18698ba0d986d2fecc6152", size = 348821, upload-time = "2026-02-02T12:36:00.093Z" }, - { url = "https://files.pythonhosted.org/packages/61/db/c1efc32b8ba4c740ab3fc2d037d8753f67685f475e26b9d6536a4322bcdd/jiter-0.13.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:04670992b576fa65bd056dbac0c39fe8bd67681c380cb2b48efa885711d9d726", size = 364163, upload-time = "2026-02-02T12:36:01.937Z" }, - { url = "https://files.pythonhosted.org/packages/55/8a/fb75556236047c8806995671a18e4a0ad646ed255276f51a20f32dceaeec/jiter-0.13.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5a1aff1fbdb803a376d4d22a8f63f8e7ccbce0b4890c26cc7af9e501ab339ef0", size = 483709, upload-time = "2026-02-02T12:36:03.41Z" }, - { url = "https://files.pythonhosted.org/packages/7e/16/43512e6ee863875693a8e6f6d532e19d650779d6ba9a81593ae40a9088ff/jiter-0.13.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:3b3fb8c2053acaef8580809ac1d1f7481a0a0bdc012fd7f5d8b18fb696a5a089", size = 370480, upload-time = "2026-02-02T12:36:04.791Z" }, - { url = "https://files.pythonhosted.org/packages/f8/4c/09b93e30e984a187bc8aaa3510e1ec8dcbdcd71ca05d2f56aac0492453aa/jiter-0.13.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bdaba7d87e66f26a2c45d8cbadcbfc4bf7884182317907baf39cfe9775bb4d93", size = 360735, upload-time = "2026-02-02T12:36:06.994Z" }, - { url = "https://files.pythonhosted.org/packages/1a/1b/46c5e349019874ec5dfa508c14c37e29864ea108d376ae26d90bee238cd7/jiter-0.13.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:7b88d649135aca526da172e48083da915ec086b54e8e73a425ba50999468cc08", size = 391814, upload-time = "2026-02-02T12:36:08.368Z" }, - { url = "https://files.pythonhosted.org/packages/15/9e/26184760e85baee7162ad37b7912797d2077718476bf91517641c92b3639/jiter-0.13.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:e404ea551d35438013c64b4f357b0474c7abf9f781c06d44fcaf7a14c69ff9e2", size = 513990, upload-time = "2026-02-02T12:36:09.993Z" }, - { url = "https://files.pythonhosted.org/packages/e9/34/2c9355247d6debad57a0a15e76ab1566ab799388042743656e566b3b7de1/jiter-0.13.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:1f4748aad1b4a93c8bdd70f604d0f748cdc0e8744c5547798acfa52f10e79228", size = 548021, upload-time = "2026-02-02T12:36:11.376Z" }, - { url = "https://files.pythonhosted.org/packages/ac/4a/9f2c23255d04a834398b9c2e0e665382116911dc4d06b795710503cdad25/jiter-0.13.0-cp312-cp312-win32.whl", hash = "sha256:0bf670e3b1445fc4d31612199f1744f67f889ee1bbae703c4b54dc097e5dd394", size = 203024, upload-time = "2026-02-02T12:36:12.682Z" }, - { url = "https://files.pythonhosted.org/packages/09/ee/f0ae675a957ae5a8f160be3e87acea6b11dc7b89f6b7ab057e77b2d2b13a/jiter-0.13.0-cp312-cp312-win_amd64.whl", hash = "sha256:15db60e121e11fe186c0b15236bd5d18381b9ddacdcf4e659feb96fc6c969c92", size = 205424, upload-time = "2026-02-02T12:36:13.93Z" }, - { url = "https://files.pythonhosted.org/packages/1b/02/ae611edf913d3cbf02c97cdb90374af2082c48d7190d74c1111dde08bcdd/jiter-0.13.0-cp312-cp312-win_arm64.whl", hash = "sha256:41f92313d17989102f3cb5dd533a02787cdb99454d494344b0361355da52fcb9", size = 186818, upload-time = "2026-02-02T12:36:15.308Z" }, - { url = "https://files.pythonhosted.org/packages/91/9c/7ee5a6ff4b9991e1a45263bfc46731634c4a2bde27dfda6c8251df2d958c/jiter-0.13.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:1f8a55b848cbabf97d861495cd65f1e5c590246fabca8b48e1747c4dfc8f85bf", size = 306897, upload-time = "2026-02-02T12:36:16.748Z" }, - { url = "https://files.pythonhosted.org/packages/7c/02/be5b870d1d2be5dd6a91bdfb90f248fbb7dcbd21338f092c6b89817c3dbf/jiter-0.13.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:f556aa591c00f2c45eb1b89f68f52441a016034d18b65da60e2d2875bbbf344a", size = 317507, upload-time = "2026-02-02T12:36:18.351Z" }, - { url = "https://files.pythonhosted.org/packages/da/92/b25d2ec333615f5f284f3a4024f7ce68cfa0604c322c6808b2344c7f5d2b/jiter-0.13.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f7e1d61da332ec412350463891923f960c3073cf1aae93b538f0bb4c8cd46efb", size = 350560, upload-time = "2026-02-02T12:36:19.746Z" }, - { url = "https://files.pythonhosted.org/packages/be/ec/74dcb99fef0aca9fbe56b303bf79f6bd839010cb18ad41000bf6cc71eec0/jiter-0.13.0-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:3097d665a27bc96fd9bbf7f86178037db139f319f785e4757ce7ccbf390db6c2", size = 363232, upload-time = "2026-02-02T12:36:21.243Z" }, - { url = "https://files.pythonhosted.org/packages/1b/37/f17375e0bb2f6a812d4dd92d7616e41917f740f3e71343627da9db2824ce/jiter-0.13.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9d01ecc3a8cbdb6f25a37bd500510550b64ddf9f7d64a107d92f3ccb25035d0f", size = 483727, upload-time = "2026-02-02T12:36:22.688Z" }, - { url = "https://files.pythonhosted.org/packages/77/d2/a71160a5ae1a1e66c1395b37ef77da67513b0adba73b993a27fbe47eb048/jiter-0.13.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ed9bbc30f5d60a3bdf63ae76beb3f9db280d7f195dfcfa61af792d6ce912d159", size = 370799, upload-time = "2026-02-02T12:36:24.106Z" }, - { url = "https://files.pythonhosted.org/packages/01/99/ed5e478ff0eb4e8aa5fd998f9d69603c9fd3f32de3bd16c2b1194f68361c/jiter-0.13.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:98fbafb6e88256f4454de33c1f40203d09fc33ed19162a68b3b257b29ca7f663", size = 359120, upload-time = "2026-02-02T12:36:25.519Z" }, - { url = "https://files.pythonhosted.org/packages/16/be/7ffd08203277a813f732ba897352797fa9493faf8dc7995b31f3d9cb9488/jiter-0.13.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:5467696f6b827f1116556cb0db620440380434591e93ecee7fd14d1a491b6daa", size = 390664, upload-time = "2026-02-02T12:36:26.866Z" }, - { url = "https://files.pythonhosted.org/packages/d1/84/e0787856196d6d346264d6dcccb01f741e5f0bd014c1d9a2ebe149caf4f3/jiter-0.13.0-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:2d08c9475d48b92892583df9da592a0e2ac49bcd41fae1fec4f39ba6cf107820", size = 513543, upload-time = "2026-02-02T12:36:28.217Z" }, - { url = "https://files.pythonhosted.org/packages/65/50/ecbd258181c4313cf79bca6c88fb63207d04d5bf5e4f65174114d072aa55/jiter-0.13.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:aed40e099404721d7fcaf5b89bd3b4568a4666358bcac7b6b15c09fb6252ab68", size = 547262, upload-time = "2026-02-02T12:36:29.678Z" }, - { url = "https://files.pythonhosted.org/packages/27/da/68f38d12e7111d2016cd198161b36e1f042bd115c169255bcb7ec823a3bf/jiter-0.13.0-cp313-cp313-win32.whl", hash = "sha256:36ebfbcffafb146d0e6ffb3e74d51e03d9c35ce7c625c8066cdbfc7b953bdc72", size = 200630, upload-time = "2026-02-02T12:36:31.808Z" }, - { url = "https://files.pythonhosted.org/packages/25/65/3bd1a972c9a08ecd22eb3b08a95d1941ebe6938aea620c246cf426ae09c2/jiter-0.13.0-cp313-cp313-win_amd64.whl", hash = "sha256:8d76029f077379374cf0dbc78dbe45b38dec4a2eb78b08b5194ce836b2517afc", size = 202602, upload-time = "2026-02-02T12:36:33.679Z" }, - { url = "https://files.pythonhosted.org/packages/15/fe/13bd3678a311aa67686bb303654792c48206a112068f8b0b21426eb6851e/jiter-0.13.0-cp313-cp313-win_arm64.whl", hash = "sha256:bb7613e1a427cfcb6ea4544f9ac566b93d5bf67e0d48c787eca673ff9c9dff2b", size = 185939, upload-time = "2026-02-02T12:36:35.065Z" }, - { url = "https://files.pythonhosted.org/packages/49/19/a929ec002ad3228bc97ca01dbb14f7632fffdc84a95ec92ceaf4145688ae/jiter-0.13.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:fa476ab5dd49f3bf3a168e05f89358c75a17608dbabb080ef65f96b27c19ab10", size = 316616, upload-time = "2026-02-02T12:36:36.579Z" }, - { url = "https://files.pythonhosted.org/packages/52/56/d19a9a194afa37c1728831e5fb81b7722c3de18a3109e8f282bfc23e587a/jiter-0.13.0-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ade8cb6ff5632a62b7dbd4757d8c5573f7a2e9ae285d6b5b841707d8363205ef", size = 346850, upload-time = "2026-02-02T12:36:38.058Z" }, - { url = "https://files.pythonhosted.org/packages/36/4a/94e831c6bf287754a8a019cb966ed39ff8be6ab78cadecf08df3bb02d505/jiter-0.13.0-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9950290340acc1adaded363edd94baebcee7dabdfa8bee4790794cd5cfad2af6", size = 358551, upload-time = "2026-02-02T12:36:39.417Z" }, - { url = "https://files.pythonhosted.org/packages/a2/ec/a4c72c822695fa80e55d2b4142b73f0012035d9fcf90eccc56bc060db37c/jiter-0.13.0-cp313-cp313t-win_amd64.whl", hash = "sha256:2b4972c6df33731aac0742b64fd0d18e0a69bc7d6e03108ce7d40c85fd9e3e6d", size = 201950, upload-time = "2026-02-02T12:36:40.791Z" }, - { url = "https://files.pythonhosted.org/packages/b6/00/393553ec27b824fbc29047e9c7cd4a3951d7fbe4a76743f17e44034fa4e4/jiter-0.13.0-cp313-cp313t-win_arm64.whl", hash = "sha256:701a1e77d1e593c1b435315ff625fd071f0998c5f02792038a5ca98899261b7d", size = 185852, upload-time = "2026-02-02T12:36:42.077Z" }, - { url = "https://files.pythonhosted.org/packages/6e/f5/f1997e987211f6f9bd71b8083047b316208b4aca0b529bb5f8c96c89ef3e/jiter-0.13.0-cp314-cp314-macosx_10_12_x86_64.whl", hash = "sha256:cc5223ab19fe25e2f0bf2643204ad7318896fe3729bf12fde41b77bfc4fafff0", size = 308804, upload-time = "2026-02-02T12:36:43.496Z" }, - { url = "https://files.pythonhosted.org/packages/cd/8f/5482a7677731fd44881f0204981ce2d7175db271f82cba2085dd2212e095/jiter-0.13.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:9776ebe51713acf438fd9b4405fcd86893ae5d03487546dae7f34993217f8a91", size = 318787, upload-time = "2026-02-02T12:36:45.071Z" }, - { url = "https://files.pythonhosted.org/packages/f3/b9/7257ac59778f1cd025b26a23c5520a36a424f7f1b068f2442a5b499b7464/jiter-0.13.0-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:879e768938e7b49b5e90b7e3fecc0dbec01b8cb89595861fb39a8967c5220d09", size = 353880, upload-time = "2026-02-02T12:36:47.365Z" }, - { url = "https://files.pythonhosted.org/packages/c3/87/719eec4a3f0841dad99e3d3604ee4cba36af4419a76f3cb0b8e2e691ad67/jiter-0.13.0-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:682161a67adea11e3aae9038c06c8b4a9a71023228767477d683f69903ebc607", size = 366702, upload-time = "2026-02-02T12:36:48.871Z" }, - { url = "https://files.pythonhosted.org/packages/d2/65/415f0a75cf6921e43365a1bc227c565cb949caca8b7532776e430cbaa530/jiter-0.13.0-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a13b68cd1cd8cc9de8f244ebae18ccb3e4067ad205220ef324c39181e23bbf66", size = 486319, upload-time = "2026-02-02T12:36:53.006Z" }, - { url = "https://files.pythonhosted.org/packages/54/a2/9e12b48e82c6bbc6081fd81abf915e1443add1b13d8fc586e1d90bb02bb8/jiter-0.13.0-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:87ce0f14c6c08892b610686ae8be350bf368467b6acd5085a5b65441e2bf36d2", size = 372289, upload-time = "2026-02-02T12:36:54.593Z" }, - { url = "https://files.pythonhosted.org/packages/4e/c1/e4693f107a1789a239c759a432e9afc592366f04e901470c2af89cfd28e1/jiter-0.13.0-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0c365005b05505a90d1c47856420980d0237adf82f70c4aff7aebd3c1cc143ad", size = 360165, upload-time = "2026-02-02T12:36:56.112Z" }, - { url = "https://files.pythonhosted.org/packages/17/08/91b9ea976c1c758240614bd88442681a87672eebc3d9a6dde476874e706b/jiter-0.13.0-cp314-cp314-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1317fdffd16f5873e46ce27d0e0f7f4f90f0cdf1d86bf6abeaea9f63ca2c401d", size = 389634, upload-time = "2026-02-02T12:36:57.495Z" }, - { url = "https://files.pythonhosted.org/packages/18/23/58325ef99390d6d40427ed6005bf1ad54f2577866594bcf13ce55675f87d/jiter-0.13.0-cp314-cp314-musllinux_1_1_aarch64.whl", hash = "sha256:c05b450d37ba0c9e21c77fef1f205f56bcee2330bddca68d344baebfc55ae0df", size = 514933, upload-time = "2026-02-02T12:36:58.909Z" }, - { url = "https://files.pythonhosted.org/packages/5b/25/69f1120c7c395fd276c3996bb8adefa9c6b84c12bb7111e5c6ccdcd8526d/jiter-0.13.0-cp314-cp314-musllinux_1_1_x86_64.whl", hash = "sha256:775e10de3849d0631a97c603f996f518159272db00fdda0a780f81752255ee9d", size = 548842, upload-time = "2026-02-02T12:37:00.433Z" }, - { url = "https://files.pythonhosted.org/packages/18/05/981c9669d86850c5fbb0d9e62bba144787f9fba84546ba43d624ee27ef29/jiter-0.13.0-cp314-cp314-win32.whl", hash = "sha256:632bf7c1d28421c00dd8bbb8a3bac5663e1f57d5cd5ed962bce3c73bf62608e6", size = 202108, upload-time = "2026-02-02T12:37:01.718Z" }, - { url = "https://files.pythonhosted.org/packages/8d/96/cdcf54dd0b0341db7d25413229888a346c7130bd20820530905fdb65727b/jiter-0.13.0-cp314-cp314-win_amd64.whl", hash = "sha256:f22ef501c3f87ede88f23f9b11e608581c14f04db59b6a801f354397ae13739f", size = 204027, upload-time = "2026-02-02T12:37:03.075Z" }, - { url = "https://files.pythonhosted.org/packages/fb/f9/724bcaaab7a3cd727031fe4f6995cb86c4bd344909177c186699c8dec51a/jiter-0.13.0-cp314-cp314-win_arm64.whl", hash = "sha256:07b75fe09a4ee8e0c606200622e571e44943f47254f95e2436c8bdcaceb36d7d", size = 187199, upload-time = "2026-02-02T12:37:04.414Z" }, - { url = "https://files.pythonhosted.org/packages/62/92/1661d8b9fd6a3d7a2d89831db26fe3c1509a287d83ad7838831c7b7a5c7e/jiter-0.13.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:964538479359059a35fb400e769295d4b315ae61e4105396d355a12f7fef09f0", size = 318423, upload-time = "2026-02-02T12:37:05.806Z" }, - { url = "https://files.pythonhosted.org/packages/4f/3b/f77d342a54d4ebcd128e520fc58ec2f5b30a423b0fd26acdfc0c6fef8e26/jiter-0.13.0-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e104da1db1c0991b3eaed391ccd650ae8d947eab1480c733e5a3fb28d4313e40", size = 351438, upload-time = "2026-02-02T12:37:07.189Z" }, - { url = "https://files.pythonhosted.org/packages/76/b3/ba9a69f0e4209bd3331470c723c2f5509e6f0482e416b612431a5061ed71/jiter-0.13.0-cp314-cp314t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0e3a5f0cde8ff433b8e88e41aa40131455420fb3649a3c7abdda6145f8cb7202", size = 364774, upload-time = "2026-02-02T12:37:08.579Z" }, - { url = "https://files.pythonhosted.org/packages/b3/16/6cdb31fa342932602458dbb631bfbd47f601e03d2e4950740e0b2100b570/jiter-0.13.0-cp314-cp314t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:57aab48f40be1db920a582b30b116fe2435d184f77f0e4226f546794cedd9cf0", size = 487238, upload-time = "2026-02-02T12:37:10.066Z" }, - { url = "https://files.pythonhosted.org/packages/ed/b1/956cc7abaca8d95c13aa8d6c9b3f3797241c246cd6e792934cc4c8b250d2/jiter-0.13.0-cp314-cp314t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7772115877c53f62beeb8fd853cab692dbc04374ef623b30f997959a4c0e7e95", size = 372892, upload-time = "2026-02-02T12:37:11.656Z" }, - { url = "https://files.pythonhosted.org/packages/26/c4/97ecde8b1e74f67b8598c57c6fccf6df86ea7861ed29da84629cdbba76c4/jiter-0.13.0-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1211427574b17b633cfceba5040de8081e5abf114f7a7602f73d2e16f9fdaa59", size = 360309, upload-time = "2026-02-02T12:37:13.244Z" }, - { url = "https://files.pythonhosted.org/packages/4b/d7/eabe3cf46715854ccc80be2cd78dd4c36aedeb30751dbf85a1d08c14373c/jiter-0.13.0-cp314-cp314t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:7beae3a3d3b5212d3a55d2961db3c292e02e302feb43fce6a3f7a31b90ea6dfe", size = 389607, upload-time = "2026-02-02T12:37:14.881Z" }, - { url = "https://files.pythonhosted.org/packages/df/2d/03963fc0804e6109b82decfb9974eb92df3797fe7222428cae12f8ccaa0c/jiter-0.13.0-cp314-cp314t-musllinux_1_1_aarch64.whl", hash = "sha256:e5562a0f0e90a6223b704163ea28e831bd3a9faa3512a711f031611e6b06c939", size = 514986, upload-time = "2026-02-02T12:37:16.326Z" }, - { url = "https://files.pythonhosted.org/packages/f6/6c/8c83b45eb3eb1c1e18d841fe30b4b5bc5619d781267ca9bc03e005d8fd0a/jiter-0.13.0-cp314-cp314t-musllinux_1_1_x86_64.whl", hash = "sha256:6c26a424569a59140fb51160a56df13f438a2b0967365e987889186d5fc2f6f9", size = 548756, upload-time = "2026-02-02T12:37:17.736Z" }, - { url = "https://files.pythonhosted.org/packages/47/66/eea81dfff765ed66c68fd2ed8c96245109e13c896c2a5015c7839c92367e/jiter-0.13.0-cp314-cp314t-win32.whl", hash = "sha256:24dc96eca9f84da4131cdf87a95e6ce36765c3b156fc9ae33280873b1c32d5f6", size = 201196, upload-time = "2026-02-02T12:37:19.101Z" }, - { url = "https://files.pythonhosted.org/packages/ff/32/4ac9c7a76402f8f00d00842a7f6b83b284d0cf7c1e9d4227bc95aa6d17fa/jiter-0.13.0-cp314-cp314t-win_amd64.whl", hash = "sha256:0a8d76c7524087272c8ae913f5d9d608bd839154b62c4322ef65723d2e5bb0b8", size = 204215, upload-time = "2026-02-02T12:37:20.495Z" }, - { url = "https://files.pythonhosted.org/packages/f9/8e/7def204fea9f9be8b3c21a6f2dd6c020cf56c7d5ff753e0e23ed7f9ea57e/jiter-0.13.0-cp314-cp314t-win_arm64.whl", hash = "sha256:2c26cf47e2cad140fa23b6d58d435a7c0161f5c514284802f25e87fddfe11024", size = 187152, upload-time = "2026-02-02T12:37:22.124Z" }, - { url = "https://files.pythonhosted.org/packages/79/b3/3c29819a27178d0e461a8571fb63c6ae38be6dc36b78b3ec2876bbd6a910/jiter-0.13.0-graalpy311-graalpy242_311_native-macosx_10_12_x86_64.whl", hash = "sha256:b1cbfa133241d0e6bdab48dcdc2604e8ba81512f6bbd68ec3e8e1357dd3c316c", size = 307016, upload-time = "2026-02-02T12:37:42.755Z" }, - { url = "https://files.pythonhosted.org/packages/eb/ae/60993e4b07b1ac5ebe46da7aa99fdbb802eb986c38d26e3883ac0125c4e0/jiter-0.13.0-graalpy311-graalpy242_311_native-macosx_11_0_arm64.whl", hash = "sha256:db367d8be9fad6e8ebbac4a7578b7af562e506211036cba2c06c3b998603c3d2", size = 305024, upload-time = "2026-02-02T12:37:44.774Z" }, - { url = "https://files.pythonhosted.org/packages/77/fa/2227e590e9cf98803db2811f172b2d6460a21539ab73006f251c66f44b14/jiter-0.13.0-graalpy311-graalpy242_311_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45f6f8efb2f3b0603092401dc2df79fa89ccbc027aaba4174d2d4133ed661434", size = 339337, upload-time = "2026-02-02T12:37:46.668Z" }, - { url = "https://files.pythonhosted.org/packages/2d/92/015173281f7eb96c0ef580c997da8ef50870d4f7f4c9e03c845a1d62ae04/jiter-0.13.0-graalpy311-graalpy242_311_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:597245258e6ad085d064780abfb23a284d418d3e61c57362d9449c6c7317ee2d", size = 346395, upload-time = "2026-02-02T12:37:48.09Z" }, - { url = "https://files.pythonhosted.org/packages/80/60/e50fa45dd7e2eae049f0ce964663849e897300433921198aef94b6ffa23a/jiter-0.13.0-graalpy312-graalpy250_312_native-macosx_10_12_x86_64.whl", hash = "sha256:3d744a6061afba08dd7ae375dcde870cffb14429b7477e10f67e9e6d68772a0a", size = 305169, upload-time = "2026-02-02T12:37:50.376Z" }, - { url = "https://files.pythonhosted.org/packages/d2/73/a009f41c5eed71c49bec53036c4b33555afcdee70682a18c6f66e396c039/jiter-0.13.0-graalpy312-graalpy250_312_native-macosx_11_0_arm64.whl", hash = "sha256:ff732bd0a0e778f43d5009840f20b935e79087b4dc65bd36f1cd0f9b04b8ff7f", size = 303808, upload-time = "2026-02-02T12:37:52.092Z" }, - { url = "https://files.pythonhosted.org/packages/c4/10/528b439290763bff3d939268085d03382471b442f212dca4ff5f12802d43/jiter-0.13.0-graalpy312-graalpy250_312_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ab44b178f7981fcaea7e0a5df20e773c663d06ffda0198f1a524e91b2fde7e59", size = 337384, upload-time = "2026-02-02T12:37:53.582Z" }, - { url = "https://files.pythonhosted.org/packages/67/8a/a342b2f0251f3dac4ca17618265d93bf244a2a4d089126e81e4c1056ac50/jiter-0.13.0-graalpy312-graalpy250_312_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7bb00b6d26db67a05fe3e12c76edc75f32077fb51deed13822dc648fa373bc19", size = 343768, upload-time = "2026-02-02T12:37:55.055Z" }, -] - -[[package]] -name = "jsonpatch" -version = "1.33" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "jsonpointer" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/42/78/18813351fe5d63acad16aec57f94ec2b70a09e53ca98145589e185423873/jsonpatch-1.33.tar.gz", hash = "sha256:9fcd4009c41e6d12348b4a0ff2563ba56a2923a7dfee731d004e212e1ee5030c", size = 21699, upload-time = "2023-06-26T12:07:29.144Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/73/07/02e16ed01e04a374e644b575638ec7987ae846d25ad97bcc9945a3ee4b0e/jsonpatch-1.33-py2.py3-none-any.whl", hash = "sha256:0ae28c0cd062bbd8b8ecc26d7d164fbbea9652a1a3693f3b956c1eae5145dade", size = 12898, upload-time = "2023-06-16T21:01:28.466Z" }, -] - -[[package]] -name = "jsonpointer" -version = "3.0.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/6a/0a/eebeb1fa92507ea94016a2a790b93c2ae41a7e18778f85471dc54475ed25/jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef", size = 9114, upload-time = "2024-06-10T19:24:42.462Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl", hash = "sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942", size = 7595, upload-time = "2024-06-10T19:24:40.698Z" }, -] - -[[package]] -name = "langchain" -version = "1.2.8" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "langgraph" }, - { name = "pydantic" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/52/b7/a1d95dbb58e5e82dbd05e3730e2d4b99f784a4c6d39435579a1c2b8a8d12/langchain-1.2.8.tar.gz", hash = "sha256:d2bc45f8279f6291b152f28df3bb060b27c9a71163fe2e2a1ac878bd314d0dec", size = 558326, upload-time = "2026-02-02T15:51:59.425Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/66/1a/e1cabc08d8b12349fa6a898f033cc6b00a9a031b470582f4a9eb4cf8e55b/langchain-1.2.8-py3-none-any.whl", hash = "sha256:74a9595420b90e2fd6dc42e323e5e6c9f2a5d059b0ab51e4ad383893b86f8fbe", size = 108986, upload-time = "2026-02-02T15:51:58.465Z" }, -] - -[[package]] -name = "langchain-anthropic" -version = "1.3.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anthropic" }, - { name = "langchain-core" }, - { name = "pydantic" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/0d/b6/ac5ee84e15bf79844c9c791f99a614c7ec7e1a63c2947e55977be01a81b4/langchain_anthropic-1.3.1.tar.gz", hash = "sha256:4f3d7a4a7729ab1aeaf62d32c87d4d227c1b5421668ca9e3734562b383470b07", size = 708940, upload-time = "2026-01-05T21:07:19.345Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/9a/4f/7a5b32764addf4b757545b89899b9d76688176f19e4ee89868e3b8bbfd0f/langchain_anthropic-1.3.1-py3-none-any.whl", hash = "sha256:1fc28cf8037c30597ee6172fc2ff9e345efe8149a8c2a39897b1eebba2948322", size = 46328, upload-time = "2026-01-05T21:07:18.261Z" }, -] - -[[package]] -name = "langchain-core" -version = "1.2.8" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "jsonpatch" }, - { name = "langsmith" }, - { name = "packaging" }, - { name = "pydantic" }, - { name = "pyyaml" }, - { name = "tenacity" }, - { name = "typing-extensions" }, - { name = "uuid-utils" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/75/cc/55bf57b83cbc164cbf84cbf0c5e4fb640d673546af131db70797b97b125b/langchain_core-1.2.8.tar.gz", hash = "sha256:76d933c3f4cfd8484d8131c39bf25f562e2df4d0d5fe3218e05ff773210713b6", size = 814506, upload-time = "2026-02-02T15:35:33.056Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/cc/d4/37fef9639b701c1fb1eea9e68447b72d86852ca3dc3253cdfd9c0afe228d/langchain_core-1.2.8-py3-none-any.whl", hash = "sha256:c732301272d63cfbcd75d114540257678627878f11b87046241272a25ba12ea7", size = 495753, upload-time = "2026-02-02T15:35:31.284Z" }, -] - -[[package]] -name = "langchain-openai" -version = "1.1.7" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "openai" }, - { name = "tiktoken" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/38/b7/30bfc4d1b658a9ee524bcce3b0b2ec9c45a11c853a13c4f0c9da9882784b/langchain_openai-1.1.7.tar.gz", hash = "sha256:f5ec31961ed24777548b63a5fe313548bc6e0eb9730d6552b8c6418765254c81", size = 1039134, upload-time = "2026-01-07T19:44:59.728Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/64/a1/50e7596aca775d8c3883eceeaf47489fac26c57c1abe243c00174f715a8a/langchain_openai-1.1.7-py3-none-any.whl", hash = "sha256:34e9cd686aac1a120d6472804422792bf8080a2103b5d21ee450c9e42d053815", size = 84753, upload-time = "2026-01-07T19:44:58.629Z" }, -] - -[[package]] -name = "langchain-py-v1" -version = "0.1.0" -source = { virtual = "." } -dependencies = [ - { name = "braintrust" }, - { name = "braintrust-langchain" }, - { name = "langchain-anthropic" }, - { name = "langchain-openai" }, -] - -[package.metadata] -requires-dist = [ - { name = "braintrust", editable = "../../../py" }, - { name = "braintrust-langchain", editable = "../../../integrations/langchain-py" }, - { name = "langchain-anthropic", specifier = ">=1.3.1" }, - { name = "langchain-openai", specifier = ">=1.1.7" }, -] - -[[package]] -name = "langgraph" -version = "1.0.7" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "langgraph-checkpoint" }, - { name = "langgraph-prebuilt" }, - { name = "langgraph-sdk" }, - { name = "pydantic" }, - { name = "xxhash" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/72/5b/f72655717c04e33d3b62f21b166dc063d192b53980e9e3be0e2a117f1c9f/langgraph-1.0.7.tar.gz", hash = "sha256:0cfdfee51e6e8cfe503ecc7367c73933437c505b03fa10a85c710975c8182d9a", size = 497098, upload-time = "2026-01-22T16:57:47.303Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7e/0e/fe80144e3e4048e5d19ccdb91ac547c1a7dc3da8dbd1443e210048194c14/langgraph-1.0.7-py3-none-any.whl", hash = "sha256:9d68e8f8dd8f3de2fec45f9a06de05766d9b075b78fb03171779893b7a52c4d2", size = 157353, upload-time = "2026-01-22T16:57:45.997Z" }, -] - -[[package]] -name = "langgraph-checkpoint" -version = "4.0.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "ormsgpack" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/98/76/55a18c59dedf39688d72c4b06af73a5e3ea0d1a01bc867b88fbf0659f203/langgraph_checkpoint-4.0.0.tar.gz", hash = "sha256:814d1bd050fac029476558d8e68d87bce9009a0262d04a2c14b918255954a624", size = 137320, upload-time = "2026-01-12T20:30:26.38Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/4a/de/ddd53b7032e623f3c7bcdab2b44e8bf635e468f62e10e5ff1946f62c9356/langgraph_checkpoint-4.0.0-py3-none-any.whl", hash = "sha256:3fa9b2635a7c5ac28b338f631abf6a030c3b508b7b9ce17c22611513b589c784", size = 46329, upload-time = "2026-01-12T20:30:25.2Z" }, -] - -[[package]] -name = "langgraph-prebuilt" -version = "1.0.7" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "langchain-core" }, - { name = "langgraph-checkpoint" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/a7/59/711aecd1a50999456850dc328f3cad72b4372d8218838d8d5326f80cb76f/langgraph_prebuilt-1.0.7.tar.gz", hash = "sha256:38e097e06de810de4d0e028ffc0e432bb56d1fb417620fb1dfdc76c5e03e4bf9", size = 163692, upload-time = "2026-01-22T16:45:22.801Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/47/49/5e37abb3f38a17a3487634abc2a5da87c208cc1d14577eb8d7184b25c886/langgraph_prebuilt-1.0.7-py3-none-any.whl", hash = "sha256:e14923516504405bb5edc3977085bc9622c35476b50c1808544490e13871fe7c", size = 35324, upload-time = "2026-01-22T16:45:21.784Z" }, -] - -[[package]] -name = "langgraph-sdk" -version = "0.3.3" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "httpx" }, - { name = "orjson" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/c3/0f/ed0634c222eed48a31ba48eab6881f94ad690d65e44fe7ca838240a260c1/langgraph_sdk-0.3.3.tar.gz", hash = "sha256:c34c3dce3b6848755eb61f0c94369d1ba04aceeb1b76015db1ea7362c544fb26", size = 130589, upload-time = "2026-01-13T00:30:43.894Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/6e/be/4ad511bacfdd854afb12974f407cb30010dceb982dc20c55491867b34526/langgraph_sdk-0.3.3-py3-none-any.whl", hash = "sha256:a52ebaf09d91143e55378bb2d0b033ed98f57f48c9ad35c8f81493b88705fc7b", size = 67021, upload-time = "2026-01-13T00:30:42.264Z" }, -] - -[[package]] -name = "langsmith" -version = "0.6.8" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "httpx" }, - { name = "orjson", marker = "platform_python_implementation != 'PyPy'" }, - { name = "packaging" }, - { name = "pydantic" }, - { name = "requests" }, - { name = "requests-toolbelt" }, - { name = "uuid-utils" }, - { name = "xxhash" }, - { name = "zstandard" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/8e/15/35f49a0b2efd33002fdcb9a7b0bdb65d77e40b4739104ffe843a3479874a/langsmith-0.6.8.tar.gz", hash = "sha256:3a7eb7155f2839dc729a5aa5b0bfc4aa1cb617b09a2290cf77031041271a7cdf", size = 973475, upload-time = "2026-02-02T23:20:02.208Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/cd/2d/2389e65522ebeab17489df72b4fabcfc661fced8af178aa6c2bc3b9afff5/langsmith-0.6.8-py3-none-any.whl", hash = "sha256:d17da18aeef15fdb4c3baec348bad64056591d785629cd5ba4846fd93cab166b", size = 319165, upload-time = "2026-02-02T23:20:00.456Z" }, -] - -[[package]] -name = "openai" -version = "2.16.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "distro" }, - { name = "httpx" }, - { name = "jiter" }, - { name = "pydantic" }, - { name = "sniffio" }, - { name = "tqdm" }, - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/b1/6c/e4c964fcf1d527fdf4739e7cc940c60075a4114d50d03871d5d5b1e13a88/openai-2.16.0.tar.gz", hash = "sha256:42eaa22ca0d8ded4367a77374104d7a2feafee5bd60a107c3c11b5243a11cd12", size = 629649, upload-time = "2026-01-27T23:28:02.579Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/16/83/0315bf2cfd75a2ce8a7e54188e9456c60cec6c0cf66728ed07bd9859ff26/openai-2.16.0-py3-none-any.whl", hash = "sha256:5f46643a8f42899a84e80c38838135d7038e7718333ce61396994f887b09a59b", size = 1068612, upload-time = "2026-01-27T23:28:00.356Z" }, -] - -[[package]] -name = "orjson" -version = "3.11.7" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/53/45/b268004f745ede84e5798b48ee12b05129d19235d0e15267aa57dcdb400b/orjson-3.11.7.tar.gz", hash = "sha256:9b1a67243945819ce55d24a30b59d6a168e86220452d2c96f4d1f093e71c0c49", size = 6144992, upload-time = "2026-02-02T15:38:49.29Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/37/02/da6cb01fc6087048d7f61522c327edf4250f1683a58a839fdcc435746dd5/orjson-3.11.7-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:9487abc2c2086e7c8eb9a211d2ce8855bae0e92586279d0d27b341d5ad76c85c", size = 228664, upload-time = "2026-02-02T15:37:25.542Z" }, - { url = "https://files.pythonhosted.org/packages/c1/c2/5885e7a5881dba9a9af51bc564e8967225a642b3e03d089289a35054e749/orjson-3.11.7-cp311-cp311-macosx_15_0_arm64.whl", hash = "sha256:79cacb0b52f6004caf92405a7e1f11e6e2de8bdf9019e4f76b44ba045125cd6b", size = 125344, upload-time = "2026-02-02T15:37:26.92Z" }, - { url = "https://files.pythonhosted.org/packages/a4/1d/4e7688de0a92d1caf600dfd5fb70b4c5bfff51dfa61ac555072ef2d0d32a/orjson-3.11.7-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c2e85fe4698b6a56d5e2ebf7ae87544d668eb6bde1ad1226c13f44663f20ec9e", size = 128404, upload-time = "2026-02-02T15:37:28.108Z" }, - { url = "https://files.pythonhosted.org/packages/2f/b2/ec04b74ae03a125db7bd69cffd014b227b7f341e3261bf75b5eb88a1aa92/orjson-3.11.7-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b8d14b71c0b12963fe8a62aac87119f1afdf4cb88a400f61ca5ae581449efcb5", size = 123677, upload-time = "2026-02-02T15:37:30.287Z" }, - { url = "https://files.pythonhosted.org/packages/4c/69/f95bdf960605f08f827f6e3291fe243d8aa9c5c9ff017a8d7232209184c3/orjson-3.11.7-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:91c81ef070c8f3220054115e1ef468b1c9ce8497b4e526cb9f68ab4dc0a7ac62", size = 128950, upload-time = "2026-02-02T15:37:31.595Z" }, - { url = "https://files.pythonhosted.org/packages/a4/1b/de59c57bae1d148ef298852abd31909ac3089cff370dfd4cd84cc99cbc42/orjson-3.11.7-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:411ebaf34d735e25e358a6d9e7978954a9c9d58cfb47bc6683cdc3964cd2f910", size = 141756, upload-time = "2026-02-02T15:37:32.985Z" }, - { url = "https://files.pythonhosted.org/packages/ee/9e/9decc59f4499f695f65c650f6cfa6cd4c37a3fbe8fa235a0a3614cb54386/orjson-3.11.7-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a16bcd08ab0bcdfc7e8801d9c4a9cc17e58418e4d48ddc6ded4e9e4b1a94062b", size = 130812, upload-time = "2026-02-02T15:37:34.204Z" }, - { url = "https://files.pythonhosted.org/packages/28/e6/59f932bcabd1eac44e334fe8e3281a92eacfcb450586e1f4bde0423728d8/orjson-3.11.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9c0b51672e466fd7e56230ffbae7f1639e18d0ce023351fb75da21b71bc2c960", size = 133444, upload-time = "2026-02-02T15:37:35.446Z" }, - { url = "https://files.pythonhosted.org/packages/f1/36/b0f05c0eaa7ca30bc965e37e6a2956b0d67adb87a9872942d3568da846ae/orjson-3.11.7-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:136dcd6a2e796dfd9ffca9fc027d778567b0b7c9968d092842d3c323cef88aa8", size = 138609, upload-time = "2026-02-02T15:37:36.657Z" }, - { url = "https://files.pythonhosted.org/packages/b8/03/58ec7d302b8d86944c60c7b4b82975d5161fcce4c9bc8c6cb1d6741b6115/orjson-3.11.7-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:7ba61079379b0ae29e117db13bda5f28d939766e410d321ec1624afc6a0b0504", size = 408918, upload-time = "2026-02-02T15:37:38.076Z" }, - { url = "https://files.pythonhosted.org/packages/06/3a/868d65ef9a8b99be723bd510de491349618abd9f62c826cf206d962db295/orjson-3.11.7-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:0527a4510c300e3b406591b0ba69b5dc50031895b0a93743526a3fc45f59d26e", size = 143998, upload-time = "2026-02-02T15:37:39.706Z" }, - { url = "https://files.pythonhosted.org/packages/5b/c7/1e18e1c83afe3349f4f6dc9e14910f0ae5f82eac756d1412ea4018938535/orjson-3.11.7-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:a709e881723c9b18acddcfb8ba357322491ad553e277cf467e1e7e20e2d90561", size = 134802, upload-time = "2026-02-02T15:37:41.002Z" }, - { url = "https://files.pythonhosted.org/packages/d4/0b/ccb7ee1a65b37e8eeb8b267dc953561d72370e85185e459616d4345bab34/orjson-3.11.7-cp311-cp311-win32.whl", hash = "sha256:c43b8b5bab288b6b90dac410cca7e986a4fa747a2e8f94615aea407da706980d", size = 127828, upload-time = "2026-02-02T15:37:42.241Z" }, - { url = "https://files.pythonhosted.org/packages/af/9e/55c776dffda3f381e0f07d010a4f5f3902bf48eaba1bb7684d301acd4924/orjson-3.11.7-cp311-cp311-win_amd64.whl", hash = "sha256:6543001328aa857187f905308a028935864aefe9968af3848401b6fe80dbb471", size = 124941, upload-time = "2026-02-02T15:37:43.444Z" }, - { url = "https://files.pythonhosted.org/packages/aa/8e/424a620fa7d263b880162505fb107ef5e0afaa765b5b06a88312ac291560/orjson-3.11.7-cp311-cp311-win_arm64.whl", hash = "sha256:1ee5cc7160a821dfe14f130bc8e63e7611051f964b463d9e2a3a573204446a4d", size = 126245, upload-time = "2026-02-02T15:37:45.18Z" }, - { url = "https://files.pythonhosted.org/packages/80/bf/76f4f1665f6983385938f0e2a5d7efa12a58171b8456c252f3bae8a4cf75/orjson-3.11.7-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:bd03ea7606833655048dab1a00734a2875e3e86c276e1d772b2a02556f0d895f", size = 228545, upload-time = "2026-02-02T15:37:46.376Z" }, - { url = "https://files.pythonhosted.org/packages/79/53/6c72c002cb13b5a978a068add59b25a8bdf2800ac1c9c8ecdb26d6d97064/orjson-3.11.7-cp312-cp312-macosx_15_0_arm64.whl", hash = "sha256:89e440ebc74ce8ab5c7bc4ce6757b4a6b1041becb127df818f6997b5c71aa60b", size = 125224, upload-time = "2026-02-02T15:37:47.697Z" }, - { url = "https://files.pythonhosted.org/packages/2c/83/10e48852865e5dd151bdfe652c06f7da484578ed02c5fca938e3632cb0b8/orjson-3.11.7-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5ede977b5fe5ac91b1dffc0a517ca4542d2ec8a6a4ff7b2652d94f640796342a", size = 128154, upload-time = "2026-02-02T15:37:48.954Z" }, - { url = "https://files.pythonhosted.org/packages/6e/52/a66e22a2b9abaa374b4a081d410edab6d1e30024707b87eab7c734afe28d/orjson-3.11.7-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b7b1dae39230a393df353827c855a5f176271c23434cfd2db74e0e424e693e10", size = 123548, upload-time = "2026-02-02T15:37:50.187Z" }, - { url = "https://files.pythonhosted.org/packages/de/38/605d371417021359f4910c496f764c48ceb8997605f8c25bf1dfe58c0ebe/orjson-3.11.7-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ed46f17096e28fb28d2975834836a639af7278aa87c84f68ab08fbe5b8bd75fa", size = 129000, upload-time = "2026-02-02T15:37:51.426Z" }, - { url = "https://files.pythonhosted.org/packages/44/98/af32e842b0ffd2335c89714d48ca4e3917b42f5d6ee5537832e069a4b3ac/orjson-3.11.7-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3726be79e36e526e3d9c1aceaadbfb4a04ee80a72ab47b3f3c17fefb9812e7b8", size = 141686, upload-time = "2026-02-02T15:37:52.607Z" }, - { url = "https://files.pythonhosted.org/packages/96/0b/fc793858dfa54be6feee940c1463370ece34b3c39c1ca0aa3845f5ba9892/orjson-3.11.7-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0724e265bc548af1dedebd9cb3d24b4e1c1e685a343be43e87ba922a5c5fff2f", size = 130812, upload-time = "2026-02-02T15:37:53.944Z" }, - { url = "https://files.pythonhosted.org/packages/dc/91/98a52415059db3f374757d0b7f0f16e3b5cd5976c90d1c2b56acaea039e6/orjson-3.11.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e7745312efa9e11c17fbd3cb3097262d079da26930ae9ae7ba28fb738367cbad", size = 133440, upload-time = "2026-02-02T15:37:55.615Z" }, - { url = "https://files.pythonhosted.org/packages/dc/b6/cb540117bda61791f46381f8c26c8f93e802892830a6055748d3bb1925ab/orjson-3.11.7-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f904c24bdeabd4298f7a977ef14ca2a022ca921ed670b92ecd16ab6f3d01f867", size = 138386, upload-time = "2026-02-02T15:37:56.814Z" }, - { url = "https://files.pythonhosted.org/packages/63/1a/50a3201c334a7f17c231eee5f841342190723794e3b06293f26e7cf87d31/orjson-3.11.7-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:b9fc4d0f81f394689e0814617aadc4f2ea0e8025f38c226cbf22d3b5ddbf025d", size = 408853, upload-time = "2026-02-02T15:37:58.291Z" }, - { url = "https://files.pythonhosted.org/packages/87/cd/8de1c67d0be44fdc22701e5989c0d015a2adf391498ad42c4dc589cd3013/orjson-3.11.7-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:849e38203e5be40b776ed2718e587faf204d184fc9a008ae441f9442320c0cab", size = 144130, upload-time = "2026-02-02T15:38:00.163Z" }, - { url = "https://files.pythonhosted.org/packages/0f/fe/d605d700c35dd55f51710d159fc54516a280923cd1b7e47508982fbb387d/orjson-3.11.7-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:4682d1db3bcebd2b64757e0ddf9e87ae5f00d29d16c5cdf3a62f561d08cc3dd2", size = 134818, upload-time = "2026-02-02T15:38:01.507Z" }, - { url = "https://files.pythonhosted.org/packages/e4/e4/15ecc67edb3ddb3e2f46ae04475f2d294e8b60c1825fbe28a428b93b3fbd/orjson-3.11.7-cp312-cp312-win32.whl", hash = "sha256:f4f7c956b5215d949a1f65334cf9d7612dde38f20a95f2315deef167def91a6f", size = 127923, upload-time = "2026-02-02T15:38:02.75Z" }, - { url = "https://files.pythonhosted.org/packages/34/70/2e0855361f76198a3965273048c8e50a9695d88cd75811a5b46444895845/orjson-3.11.7-cp312-cp312-win_amd64.whl", hash = "sha256:bf742e149121dc5648ba0a08ea0871e87b660467ef168a3a5e53bc1fbd64bb74", size = 125007, upload-time = "2026-02-02T15:38:04.032Z" }, - { url = "https://files.pythonhosted.org/packages/68/40/c2051bd19fc467610fed469dc29e43ac65891571138f476834ca192bc290/orjson-3.11.7-cp312-cp312-win_arm64.whl", hash = "sha256:26c3b9132f783b7d7903bf1efb095fed8d4a3a85ec0d334ee8beff3d7a4749d5", size = 126089, upload-time = "2026-02-02T15:38:05.297Z" }, - { url = "https://files.pythonhosted.org/packages/89/25/6e0e52cac5aab51d7b6dcd257e855e1dec1c2060f6b28566c509b4665f62/orjson-3.11.7-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:1d98b30cc1313d52d4af17d9c3d307b08389752ec5f2e5febdfada70b0f8c733", size = 228390, upload-time = "2026-02-02T15:38:06.8Z" }, - { url = "https://files.pythonhosted.org/packages/a5/29/a77f48d2fc8a05bbc529e5ff481fb43d914f9e383ea2469d4f3d51df3d00/orjson-3.11.7-cp313-cp313-macosx_15_0_arm64.whl", hash = "sha256:d897e81f8d0cbd2abb82226d1860ad2e1ab3ff16d7b08c96ca00df9d45409ef4", size = 125189, upload-time = "2026-02-02T15:38:08.181Z" }, - { url = "https://files.pythonhosted.org/packages/89/25/0a16e0729a0e6a1504f9d1a13cdd365f030068aab64cec6958396b9969d7/orjson-3.11.7-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:814be4b49b228cfc0b3c565acf642dd7d13538f966e3ccde61f4f55be3e20785", size = 128106, upload-time = "2026-02-02T15:38:09.41Z" }, - { url = "https://files.pythonhosted.org/packages/66/da/a2e505469d60666a05ab373f1a6322eb671cb2ba3a0ccfc7d4bc97196787/orjson-3.11.7-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:d06e5c5fed5caedd2e540d62e5b1c25e8c82431b9e577c33537e5fa4aa909539", size = 123363, upload-time = "2026-02-02T15:38:10.73Z" }, - { url = "https://files.pythonhosted.org/packages/23/bf/ed73f88396ea35c71b38961734ea4a4746f7ca0768bf28fd551d37e48dd0/orjson-3.11.7-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:31c80ce534ac4ea3739c5ee751270646cbc46e45aea7576a38ffec040b4029a1", size = 129007, upload-time = "2026-02-02T15:38:12.138Z" }, - { url = "https://files.pythonhosted.org/packages/73/3c/b05d80716f0225fc9008fbf8ab22841dcc268a626aa550561743714ce3bf/orjson-3.11.7-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f50979824bde13d32b4320eedd513431c921102796d86be3eee0b58e58a3ecd1", size = 141667, upload-time = "2026-02-02T15:38:13.398Z" }, - { url = "https://files.pythonhosted.org/packages/61/e8/0be9b0addd9bf86abfc938e97441dcd0375d494594b1c8ad10fe57479617/orjson-3.11.7-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9e54f3808e2b6b945078c41aa8d9b5834b28c50843846e97807e5adb75fa9705", size = 130832, upload-time = "2026-02-02T15:38:14.698Z" }, - { url = "https://files.pythonhosted.org/packages/c9/ec/c68e3b9021a31d9ec15a94931db1410136af862955854ed5dd7e7e4f5bff/orjson-3.11.7-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a12b80df61aab7b98b490fe9e4879925ba666fccdfcd175252ce4d9035865ace", size = 133373, upload-time = "2026-02-02T15:38:16.109Z" }, - { url = "https://files.pythonhosted.org/packages/d2/45/f3466739aaafa570cc8e77c6dbb853c48bf56e3b43738020e2661e08b0ac/orjson-3.11.7-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:996b65230271f1a97026fd0e6a753f51fbc0c335d2ad0c6201f711b0da32693b", size = 138307, upload-time = "2026-02-02T15:38:17.453Z" }, - { url = "https://files.pythonhosted.org/packages/e1/84/9f7f02288da1ffb31405c1be07657afd1eecbcb4b64ee2817b6fe0f785fa/orjson-3.11.7-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:ab49d4b2a6a1d415ddb9f37a21e02e0d5dbfe10b7870b21bf779fc21e9156157", size = 408695, upload-time = "2026-02-02T15:38:18.831Z" }, - { url = "https://files.pythonhosted.org/packages/18/07/9dd2f0c0104f1a0295ffbe912bc8d63307a539b900dd9e2c48ef7810d971/orjson-3.11.7-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:390a1dce0c055ddf8adb6aa94a73b45a4a7d7177b5c584b8d1c1947f2ba60fb3", size = 144099, upload-time = "2026-02-02T15:38:20.28Z" }, - { url = "https://files.pythonhosted.org/packages/a5/66/857a8e4a3292e1f7b1b202883bcdeb43a91566cf59a93f97c53b44bd6801/orjson-3.11.7-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:1eb80451a9c351a71dfaf5b7ccc13ad065405217726b59fdbeadbcc544f9d223", size = 134806, upload-time = "2026-02-02T15:38:22.186Z" }, - { url = "https://files.pythonhosted.org/packages/0a/5b/6ebcf3defc1aab3a338ca777214966851e92efb1f30dc7fc8285216e6d1b/orjson-3.11.7-cp313-cp313-win32.whl", hash = "sha256:7477aa6a6ec6139c5cb1cc7b214643592169a5494d200397c7fc95d740d5fcf3", size = 127914, upload-time = "2026-02-02T15:38:23.511Z" }, - { url = "https://files.pythonhosted.org/packages/00/04/c6f72daca5092e3117840a1b1e88dfc809cc1470cf0734890d0366b684a1/orjson-3.11.7-cp313-cp313-win_amd64.whl", hash = "sha256:b9f95dcdea9d4f805daa9ddf02617a89e484c6985fa03055459f90e87d7a0757", size = 124986, upload-time = "2026-02-02T15:38:24.836Z" }, - { url = "https://files.pythonhosted.org/packages/03/ba/077a0f6f1085d6b806937246860fafbd5b17f3919c70ee3f3d8d9c713f38/orjson-3.11.7-cp313-cp313-win_arm64.whl", hash = "sha256:800988273a014a0541483dc81021247d7eacb0c845a9d1a34a422bc718f41539", size = 126045, upload-time = "2026-02-02T15:38:26.216Z" }, - { url = "https://files.pythonhosted.org/packages/e9/1e/745565dca749813db9a093c5ebc4bac1a9475c64d54b95654336ac3ed961/orjson-3.11.7-cp314-cp314-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:de0a37f21d0d364954ad5de1970491d7fbd0fb1ef7417d4d56a36dc01ba0c0a0", size = 228391, upload-time = "2026-02-02T15:38:27.757Z" }, - { url = "https://files.pythonhosted.org/packages/46/19/e40f6225da4d3aa0c8dc6e5219c5e87c2063a560fe0d72a88deb59776794/orjson-3.11.7-cp314-cp314-macosx_15_0_arm64.whl", hash = "sha256:c2428d358d85e8da9d37cba18b8c4047c55222007a84f97156a5b22028dfbfc0", size = 125188, upload-time = "2026-02-02T15:38:29.241Z" }, - { url = "https://files.pythonhosted.org/packages/9d/7e/c4de2babef2c0817fd1f048fd176aa48c37bec8aef53d2fa932983032cce/orjson-3.11.7-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3c4bc6c6ac52cdaa267552544c73e486fecbd710b7ac09bc024d5a78555a22f6", size = 128097, upload-time = "2026-02-02T15:38:30.618Z" }, - { url = "https://files.pythonhosted.org/packages/eb/74/233d360632bafd2197f217eee7fb9c9d0229eac0c18128aee5b35b0014fe/orjson-3.11.7-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bd0d68edd7dfca1b2eca9361a44ac9f24b078de3481003159929a0573f21a6bf", size = 123364, upload-time = "2026-02-02T15:38:32.363Z" }, - { url = "https://files.pythonhosted.org/packages/79/51/af79504981dd31efe20a9e360eb49c15f06df2b40e7f25a0a52d9ae888e8/orjson-3.11.7-cp314-cp314-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:623ad1b9548ef63886319c16fa317848e465a21513b31a6ad7b57443c3e0dcf5", size = 129076, upload-time = "2026-02-02T15:38:33.68Z" }, - { url = "https://files.pythonhosted.org/packages/67/e2/da898eb68b72304f8de05ca6715870d09d603ee98d30a27e8a9629abc64b/orjson-3.11.7-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6e776b998ac37c0396093d10290e60283f59cfe0fc3fccbd0ccc4bd04dd19892", size = 141705, upload-time = "2026-02-02T15:38:34.989Z" }, - { url = "https://files.pythonhosted.org/packages/c5/89/15364d92acb3d903b029e28d834edb8780c2b97404cbf7929aa6b9abdb24/orjson-3.11.7-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:652c6c3af76716f4a9c290371ba2e390ede06f6603edb277b481daf37f6f464e", size = 130855, upload-time = "2026-02-02T15:38:36.379Z" }, - { url = "https://files.pythonhosted.org/packages/c2/8b/ecdad52d0b38d4b8f514be603e69ccd5eacf4e7241f972e37e79792212ec/orjson-3.11.7-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a56df3239294ea5964adf074c54bcc4f0ccd21636049a2cf3ca9cf03b5d03cf1", size = 133386, upload-time = "2026-02-02T15:38:37.704Z" }, - { url = "https://files.pythonhosted.org/packages/b9/0e/45e1dcf10e17d0924b7c9162f87ec7b4ca79e28a0548acf6a71788d3e108/orjson-3.11.7-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:bda117c4148e81f746655d5a3239ae9bd00cb7bc3ca178b5fc5a5997e9744183", size = 138295, upload-time = "2026-02-02T15:38:39.096Z" }, - { url = "https://files.pythonhosted.org/packages/63/d7/4d2e8b03561257af0450f2845b91fbd111d7e526ccdf737267108075e0ba/orjson-3.11.7-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:23d6c20517a97a9daf1d48b580fcdc6f0516c6f4b5038823426033690b4d2650", size = 408720, upload-time = "2026-02-02T15:38:40.634Z" }, - { url = "https://files.pythonhosted.org/packages/78/cf/d45343518282108b29c12a65892445fc51f9319dc3c552ceb51bb5905ed2/orjson-3.11.7-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:8ff206156006da5b847c9304b6308a01e8cdbc8cce824e2779a5ba71c3def141", size = 144152, upload-time = "2026-02-02T15:38:42.262Z" }, - { url = "https://files.pythonhosted.org/packages/a9/3a/d6001f51a7275aacd342e77b735c71fa04125a3f93c36fee4526bc8c654e/orjson-3.11.7-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:962d046ee1765f74a1da723f4b33e3b228fe3a48bd307acce5021dfefe0e29b2", size = 134814, upload-time = "2026-02-02T15:38:43.627Z" }, - { url = "https://files.pythonhosted.org/packages/1d/d3/f19b47ce16820cc2c480f7f1723e17f6d411b3a295c60c8ad3aa9ff1c96a/orjson-3.11.7-cp314-cp314-win32.whl", hash = "sha256:89e13dd3f89f1c38a9c9eba5fbf7cdc2d1feca82f5f290864b4b7a6aac704576", size = 127997, upload-time = "2026-02-02T15:38:45.06Z" }, - { url = "https://files.pythonhosted.org/packages/12/df/172771902943af54bf661a8d102bdf2e7f932127968080632bda6054b62c/orjson-3.11.7-cp314-cp314-win_amd64.whl", hash = "sha256:845c3e0d8ded9c9271cd79596b9b552448b885b97110f628fb687aee2eed11c1", size = 124985, upload-time = "2026-02-02T15:38:46.388Z" }, - { url = "https://files.pythonhosted.org/packages/6f/1c/f2a8d8a1b17514660a614ce5f7aac74b934e69f5abc2700cc7ced882a009/orjson-3.11.7-cp314-cp314-win_arm64.whl", hash = "sha256:4a2e9c5be347b937a2e0203866f12bba36082e89b402ddb9e927d5822e43088d", size = 126038, upload-time = "2026-02-02T15:38:47.703Z" }, -] - -[[package]] -name = "ormsgpack" -version = "1.12.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/12/0c/f1761e21486942ab9bb6feaebc610fa074f7c5e496e6962dea5873348077/ormsgpack-1.12.2.tar.gz", hash = "sha256:944a2233640273bee67521795a73cf1e959538e0dfb7ac635505010455e53b33", size = 39031, upload-time = "2026-01-18T20:55:28.023Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/4b/08/8b68f24b18e69d92238aa8f258218e6dfeacf4381d9d07ab8df303f524a9/ormsgpack-1.12.2-cp311-cp311-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:bd5f4bf04c37888e864f08e740c5a573c4017f6fd6e99fa944c5c935fabf2dd9", size = 378266, upload-time = "2026-01-18T20:55:59.876Z" }, - { url = "https://files.pythonhosted.org/packages/0d/24/29fc13044ecb7c153523ae0a1972269fcd613650d1fa1a9cec1044c6b666/ormsgpack-1.12.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:34d5b28b3570e9fed9a5a76528fc7230c3c76333bc214798958e58e9b79cc18a", size = 203035, upload-time = "2026-01-18T20:55:30.59Z" }, - { url = "https://files.pythonhosted.org/packages/ad/c2/00169fb25dd8f9213f5e8a549dfb73e4d592009ebc85fbbcd3e1dcac575b/ormsgpack-1.12.2-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:3708693412c28f3538fb5a65da93787b6bbab3484f6bc6e935bfb77a62400ae5", size = 210539, upload-time = "2026-01-18T20:55:48.569Z" }, - { url = "https://files.pythonhosted.org/packages/1b/33/543627f323ff3c73091f51d6a20db28a1a33531af30873ea90c5ac95a9b5/ormsgpack-1.12.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:43013a3f3e2e902e1d05e72c0f1aeb5bedbb8e09240b51e26792a3c89267e181", size = 212401, upload-time = "2026-01-18T20:56:10.101Z" }, - { url = "https://files.pythonhosted.org/packages/e8/5d/f70e2c3da414f46186659d24745483757bcc9adccb481a6eb93e2b729301/ormsgpack-1.12.2-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:7c8b1667a72cbba74f0ae7ecf3105a5e01304620ed14528b2cb4320679d2869b", size = 387082, upload-time = "2026-01-18T20:56:12.047Z" }, - { url = "https://files.pythonhosted.org/packages/c0/d6/06e8dc920c7903e051f30934d874d4afccc9bb1c09dcaf0bc03a7de4b343/ormsgpack-1.12.2-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:df6961442140193e517303d0b5d7bc2e20e69a879c2d774316125350c4a76b92", size = 482346, upload-time = "2026-01-18T20:56:05.152Z" }, - { url = "https://files.pythonhosted.org/packages/66/c4/f337ac0905eed9c393ef990c54565cd33644918e0a8031fe48c098c71dbf/ormsgpack-1.12.2-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:c6a4c34ddef109647c769d69be65fa1de7a6022b02ad45546a69b3216573eb4a", size = 425181, upload-time = "2026-01-18T20:55:37.83Z" }, - { url = "https://files.pythonhosted.org/packages/78/29/6d5758fabef3babdf4bbbc453738cc7de9cd3334e4c38dd5737e27b85653/ormsgpack-1.12.2-cp311-cp311-win_amd64.whl", hash = "sha256:73670ed0375ecc303858e3613f407628dd1fca18fe6ac57b7b7ce66cc7bb006c", size = 117182, upload-time = "2026-01-18T20:55:31.472Z" }, - { url = "https://files.pythonhosted.org/packages/c4/57/17a15549233c37e7fd054c48fe9207492e06b026dbd872b826a0b5f833b6/ormsgpack-1.12.2-cp311-cp311-win_arm64.whl", hash = "sha256:c2be829954434e33601ae5da328cccce3266b098927ca7a30246a0baec2ce7bd", size = 111464, upload-time = "2026-01-18T20:55:38.811Z" }, - { url = "https://files.pythonhosted.org/packages/4c/36/16c4b1921c308a92cef3bf6663226ae283395aa0ff6e154f925c32e91ff5/ormsgpack-1.12.2-cp312-cp312-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:7a29d09b64b9694b588ff2f80e9826bdceb3a2b91523c5beae1fab27d5c940e7", size = 378618, upload-time = "2026-01-18T20:55:50.835Z" }, - { url = "https://files.pythonhosted.org/packages/c0/68/468de634079615abf66ed13bb5c34ff71da237213f29294363beeeca5306/ormsgpack-1.12.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b39e629fd2e1c5b2f46f99778450b59454d1f901bc507963168985e79f09c5d", size = 203186, upload-time = "2026-01-18T20:56:11.163Z" }, - { url = "https://files.pythonhosted.org/packages/73/a9/d756e01961442688b7939bacd87ce13bfad7d26ce24f910f6028178b2cc8/ormsgpack-1.12.2-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:958dcb270d30a7cb633a45ee62b9444433fa571a752d2ca484efdac07480876e", size = 210738, upload-time = "2026-01-18T20:56:09.181Z" }, - { url = "https://files.pythonhosted.org/packages/7b/ba/795b1036888542c9113269a3f5690ab53dd2258c6fb17676ac4bd44fcf94/ormsgpack-1.12.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58d379d72b6c5e964851c77cfedfb386e474adee4fd39791c2c5d9efb53505cc", size = 212569, upload-time = "2026-01-18T20:56:06.135Z" }, - { url = "https://files.pythonhosted.org/packages/6c/aa/bff73c57497b9e0cba8837c7e4bcab584b1a6dbc91a5dd5526784a5030c8/ormsgpack-1.12.2-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8463a3fc5f09832e67bdb0e2fda6d518dc4281b133166146a67f54c08496442e", size = 387166, upload-time = "2026-01-18T20:55:36.738Z" }, - { url = "https://files.pythonhosted.org/packages/d3/cf/f8283cba44bcb7b14f97b6274d449db276b3a86589bdb363169b51bc12de/ormsgpack-1.12.2-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:eddffb77eff0bad4e67547d67a130604e7e2dfbb7b0cde0796045be4090f35c6", size = 482498, upload-time = "2026-01-18T20:55:29.626Z" }, - { url = "https://files.pythonhosted.org/packages/05/be/71e37b852d723dfcbe952ad04178c030df60d6b78eba26bfd14c9a40575e/ormsgpack-1.12.2-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:fcd55e5f6ba0dbce624942adf9f152062135f991a0126064889f68eb850de0dd", size = 425518, upload-time = "2026-01-18T20:55:49.556Z" }, - { url = "https://files.pythonhosted.org/packages/7a/0c/9803aa883d18c7ef197213cd2cbf73ba76472a11fe100fb7dab2884edf48/ormsgpack-1.12.2-cp312-cp312-win_amd64.whl", hash = "sha256:d024b40828f1dde5654faebd0d824f9cc29ad46891f626272dd5bfd7af2333a4", size = 117462, upload-time = "2026-01-18T20:55:47.726Z" }, - { url = "https://files.pythonhosted.org/packages/c8/9e/029e898298b2cc662f10d7a15652a53e3b525b1e7f07e21fef8536a09bb8/ormsgpack-1.12.2-cp312-cp312-win_arm64.whl", hash = "sha256:da538c542bac7d1c8f3f2a937863dba36f013108ce63e55745941dda4b75dbb6", size = 111559, upload-time = "2026-01-18T20:55:54.273Z" }, - { url = "https://files.pythonhosted.org/packages/eb/29/bb0eba3288c0449efbb013e9c6f58aea79cf5cb9ee1921f8865f04c1a9d7/ormsgpack-1.12.2-cp313-cp313-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:5ea60cb5f210b1cfbad8c002948d73447508e629ec375acb82910e3efa8ff355", size = 378661, upload-time = "2026-01-18T20:55:57.765Z" }, - { url = "https://files.pythonhosted.org/packages/6e/31/5efa31346affdac489acade2926989e019e8ca98129658a183e3add7af5e/ormsgpack-1.12.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f3601f19afdbea273ed70b06495e5794606a8b690a568d6c996a90d7255e51c1", size = 203194, upload-time = "2026-01-18T20:56:08.252Z" }, - { url = "https://files.pythonhosted.org/packages/eb/56/d0087278beef833187e0167f8527235ebe6f6ffc2a143e9de12a98b1ce87/ormsgpack-1.12.2-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:29a9f17a3dac6054c0dce7925e0f4995c727f7c41859adf9b5572180f640d172", size = 210778, upload-time = "2026-01-18T20:55:17.694Z" }, - { url = "https://files.pythonhosted.org/packages/1c/a2/072343e1413d9443e5a252a8eb591c2d5b1bffbe5e7bfc78c069361b92eb/ormsgpack-1.12.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:39c1bd2092880e413902910388be8715f70b9f15f20779d44e673033a6146f2d", size = 212592, upload-time = "2026-01-18T20:55:32.747Z" }, - { url = "https://files.pythonhosted.org/packages/a2/8b/a0da3b98a91d41187a63b02dda14267eefc2a74fcb43cc2701066cf1510e/ormsgpack-1.12.2-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:50b7249244382209877deedeee838aef1542f3d0fc28b8fe71ca9d7e1896a0d7", size = 387164, upload-time = "2026-01-18T20:55:40.853Z" }, - { url = "https://files.pythonhosted.org/packages/19/bb/6d226bc4cf9fc20d8eb1d976d027a3f7c3491e8f08289a2e76abe96a65f3/ormsgpack-1.12.2-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:5af04800d844451cf102a59c74a841324868d3f1625c296a06cc655c542a6685", size = 482516, upload-time = "2026-01-18T20:55:42.033Z" }, - { url = "https://files.pythonhosted.org/packages/fb/f1/bb2c7223398543dedb3dbf8bb93aaa737b387de61c5feaad6f908841b782/ormsgpack-1.12.2-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:cec70477d4371cd524534cd16472d8b9cc187e0e3043a8790545a9a9b296c258", size = 425539, upload-time = "2026-01-18T20:55:24.727Z" }, - { url = "https://files.pythonhosted.org/packages/7b/e8/0fb45f57a2ada1fed374f7494c8cd55e2f88ccd0ab0a669aa3468716bf5f/ormsgpack-1.12.2-cp313-cp313-win_amd64.whl", hash = "sha256:21f4276caca5c03a818041d637e4019bc84f9d6ca8baa5ea03e5cc8bf56140e9", size = 117459, upload-time = "2026-01-18T20:55:56.876Z" }, - { url = "https://files.pythonhosted.org/packages/7a/d4/0cfeea1e960d550a131001a7f38a5132c7ae3ebde4c82af1f364ccc5d904/ormsgpack-1.12.2-cp313-cp313-win_arm64.whl", hash = "sha256:baca4b6773d20a82e36d6fd25f341064244f9f86a13dead95dd7d7f996f51709", size = 111577, upload-time = "2026-01-18T20:55:43.605Z" }, - { url = "https://files.pythonhosted.org/packages/94/16/24d18851334be09c25e87f74307c84950f18c324a4d3c0b41dabdbf19c29/ormsgpack-1.12.2-cp314-cp314-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:bc68dd5915f4acf66ff2010ee47c8906dc1cf07399b16f4089f8c71733f6e36c", size = 378717, upload-time = "2026-01-18T20:55:26.164Z" }, - { url = "https://files.pythonhosted.org/packages/b5/a2/88b9b56f83adae8032ac6a6fa7f080c65b3baf9b6b64fd3d37bd202991d4/ormsgpack-1.12.2-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:46d084427b4132553940070ad95107266656cb646ea9da4975f85cb1a6676553", size = 203183, upload-time = "2026-01-18T20:55:18.815Z" }, - { url = "https://files.pythonhosted.org/packages/a9/80/43e4555963bf602e5bdc79cbc8debd8b6d5456c00d2504df9775e74b450b/ormsgpack-1.12.2-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:c010da16235806cf1d7bc4c96bf286bfa91c686853395a299b3ddb49499a3e13", size = 210814, upload-time = "2026-01-18T20:55:33.973Z" }, - { url = "https://files.pythonhosted.org/packages/78/e1/7cfbf28de8bca6efe7e525b329c31277d1b64ce08dcba723971c241a9d60/ormsgpack-1.12.2-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:18867233df592c997154ff942a6503df274b5ac1765215bceba7a231bea2745d", size = 212634, upload-time = "2026-01-18T20:55:28.634Z" }, - { url = "https://files.pythonhosted.org/packages/95/f8/30ae5716e88d792a4e879debee195653c26ddd3964c968594ddef0a3cc7e/ormsgpack-1.12.2-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:b009049086ddc6b8f80c76b3955df1aa22a5fbd7673c525cd63bf91f23122ede", size = 387139, upload-time = "2026-01-18T20:56:02.013Z" }, - { url = "https://files.pythonhosted.org/packages/dc/81/aee5b18a3e3a0e52f718b37ab4b8af6fae0d9d6a65103036a90c2a8ffb5d/ormsgpack-1.12.2-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:1dcc17d92b6390d4f18f937cf0b99054824a7815818012ddca925d6e01c2e49e", size = 482578, upload-time = "2026-01-18T20:55:35.117Z" }, - { url = "https://files.pythonhosted.org/packages/bd/17/71c9ba472d5d45f7546317f467a5fc941929cd68fb32796ca3d13dcbaec2/ormsgpack-1.12.2-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:f04b5e896d510b07c0ad733d7fce2d44b260c5e6c402d272128f8941984e4285", size = 425539, upload-time = "2026-01-18T20:56:04.009Z" }, - { url = "https://files.pythonhosted.org/packages/2e/a6/ac99cd7fe77e822fed5250ff4b86fa66dd4238937dd178d2299f10b69816/ormsgpack-1.12.2-cp314-cp314-win_amd64.whl", hash = "sha256:ae3aba7eed4ca7cb79fd3436eddd29140f17ea254b91604aa1eb19bfcedb990f", size = 117493, upload-time = "2026-01-18T20:56:07.343Z" }, - { url = "https://files.pythonhosted.org/packages/3a/67/339872846a1ae4592535385a1c1f93614138566d7af094200c9c3b45d1e5/ormsgpack-1.12.2-cp314-cp314-win_arm64.whl", hash = "sha256:118576ea6006893aea811b17429bfc561b4778fad393f5f538c84af70b01260c", size = 111579, upload-time = "2026-01-18T20:55:21.161Z" }, - { url = "https://files.pythonhosted.org/packages/49/c2/6feb972dc87285ad381749d3882d8aecbde9f6ecf908dd717d33d66df095/ormsgpack-1.12.2-cp314-cp314t-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:7121b3d355d3858781dc40dafe25a32ff8a8242b9d80c692fd548a4b1f7fd3c8", size = 378721, upload-time = "2026-01-18T20:55:52.12Z" }, - { url = "https://files.pythonhosted.org/packages/a3/9a/900a6b9b413e0f8a471cf07830f9cf65939af039a362204b36bd5b581d8b/ormsgpack-1.12.2-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4ee766d2e78251b7a63daf1cddfac36a73562d3ddef68cacfb41b2af64698033", size = 203170, upload-time = "2026-01-18T20:55:44.469Z" }, - { url = "https://files.pythonhosted.org/packages/87/4c/27a95466354606b256f24fad464d7c97ab62bce6cc529dd4673e1179b8fb/ormsgpack-1.12.2-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:292410a7d23de9b40444636b9b8f1e4e4b814af7f1ef476e44887e52a123f09d", size = 212816, upload-time = "2026-01-18T20:55:23.501Z" }, - { url = "https://files.pythonhosted.org/packages/73/cd/29cee6007bddf7a834e6cd6f536754c0535fcb939d384f0f37a38b1cddb8/ormsgpack-1.12.2-cp314-cp314t-win_amd64.whl", hash = "sha256:837dd316584485b72ef451d08dd3e96c4a11d12e4963aedb40e08f89685d8ec2", size = 117232, upload-time = "2026-01-18T20:55:45.448Z" }, -] - -[[package]] -name = "packaging" -version = "26.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/65/ee/299d360cdc32edc7d2cf530f3accf79c4fca01e96ffc950d8a52213bd8e4/packaging-26.0.tar.gz", hash = "sha256:00243ae351a257117b6a241061796684b084ed1c516a08c48a3f7e147a9d80b4", size = 143416, upload-time = "2026-01-21T20:50:39.064Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl", hash = "sha256:b36f1fef9334a5588b4166f8bcd26a14e521f2b55e6b9de3aaa80d3ff7a37529", size = 74366, upload-time = "2026-01-21T20:50:37.788Z" }, -] - -[[package]] -name = "pydantic" -version = "2.12.5" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "annotated-types" }, - { name = "pydantic-core" }, - { name = "typing-extensions" }, - { name = "typing-inspection" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/69/44/36f1a6e523abc58ae5f928898e4aca2e0ea509b5aa6f6f392a5d882be928/pydantic-2.12.5.tar.gz", hash = "sha256:4d351024c75c0f085a9febbb665ce8c0c6ec5d30e903bdb6394b7ede26aebb49", size = 821591, upload-time = "2025-11-26T15:11:46.471Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/5a/87/b70ad306ebb6f9b585f114d0ac2137d792b48be34d732d60e597c2f8465a/pydantic-2.12.5-py3-none-any.whl", hash = "sha256:e561593fccf61e8a20fc46dfc2dfe075b8be7d0188df33f221ad1f0139180f9d", size = 463580, upload-time = "2025-11-26T15:11:44.605Z" }, -] - -[[package]] -name = "pydantic-core" -version = "2.41.5" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/71/70/23b021c950c2addd24ec408e9ab05d59b035b39d97cdc1130e1bce647bb6/pydantic_core-2.41.5.tar.gz", hash = "sha256:08daa51ea16ad373ffd5e7606252cc32f07bc72b28284b6bc9c6df804816476e", size = 460952, upload-time = "2025-11-04T13:43:49.098Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e8/72/74a989dd9f2084b3d9530b0915fdda64ac48831c30dbf7c72a41a5232db8/pydantic_core-2.41.5-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:a3a52f6156e73e7ccb0f8cced536adccb7042be67cb45f9562e12b319c119da6", size = 2105873, upload-time = "2025-11-04T13:39:31.373Z" }, - { url = "https://files.pythonhosted.org/packages/12/44/37e403fd9455708b3b942949e1d7febc02167662bf1a7da5b78ee1ea2842/pydantic_core-2.41.5-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:7f3bf998340c6d4b0c9a2f02d6a400e51f123b59565d74dc60d252ce888c260b", size = 1899826, upload-time = "2025-11-04T13:39:32.897Z" }, - { url = "https://files.pythonhosted.org/packages/33/7f/1d5cab3ccf44c1935a359d51a8a2a9e1a654b744b5e7f80d41b88d501eec/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:378bec5c66998815d224c9ca994f1e14c0c21cb95d2f52b6021cc0b2a58f2a5a", size = 1917869, upload-time = "2025-11-04T13:39:34.469Z" }, - { url = "https://files.pythonhosted.org/packages/6e/6a/30d94a9674a7fe4f4744052ed6c5e083424510be1e93da5bc47569d11810/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e7b576130c69225432866fe2f4a469a85a54ade141d96fd396dffcf607b558f8", size = 2063890, upload-time = "2025-11-04T13:39:36.053Z" }, - { url = "https://files.pythonhosted.org/packages/50/be/76e5d46203fcb2750e542f32e6c371ffa9b8ad17364cf94bb0818dbfb50c/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6cb58b9c66f7e4179a2d5e0f849c48eff5c1fca560994d6eb6543abf955a149e", size = 2229740, upload-time = "2025-11-04T13:39:37.753Z" }, - { url = "https://files.pythonhosted.org/packages/d3/ee/fed784df0144793489f87db310a6bbf8118d7b630ed07aa180d6067e653a/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:88942d3a3dff3afc8288c21e565e476fc278902ae4d6d134f1eeda118cc830b1", size = 2350021, upload-time = "2025-11-04T13:39:40.94Z" }, - { url = "https://files.pythonhosted.org/packages/c8/be/8fed28dd0a180dca19e72c233cbf58efa36df055e5b9d90d64fd1740b828/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f31d95a179f8d64d90f6831d71fa93290893a33148d890ba15de25642c5d075b", size = 2066378, upload-time = "2025-11-04T13:39:42.523Z" }, - { url = "https://files.pythonhosted.org/packages/b0/3b/698cf8ae1d536a010e05121b4958b1257f0b5522085e335360e53a6b1c8b/pydantic_core-2.41.5-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c1df3d34aced70add6f867a8cf413e299177e0c22660cc767218373d0779487b", size = 2175761, upload-time = "2025-11-04T13:39:44.553Z" }, - { url = "https://files.pythonhosted.org/packages/b8/ba/15d537423939553116dea94ce02f9c31be0fa9d0b806d427e0308ec17145/pydantic_core-2.41.5-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:4009935984bd36bd2c774e13f9a09563ce8de4abaa7226f5108262fa3e637284", size = 2146303, upload-time = "2025-11-04T13:39:46.238Z" }, - { url = "https://files.pythonhosted.org/packages/58/7f/0de669bf37d206723795f9c90c82966726a2ab06c336deba4735b55af431/pydantic_core-2.41.5-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:34a64bc3441dc1213096a20fe27e8e128bd3ff89921706e83c0b1ac971276594", size = 2340355, upload-time = "2025-11-04T13:39:48.002Z" }, - { url = "https://files.pythonhosted.org/packages/e5/de/e7482c435b83d7e3c3ee5ee4451f6e8973cff0eb6007d2872ce6383f6398/pydantic_core-2.41.5-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:c9e19dd6e28fdcaa5a1de679aec4141f691023916427ef9bae8584f9c2fb3b0e", size = 2319875, upload-time = "2025-11-04T13:39:49.705Z" }, - { url = "https://files.pythonhosted.org/packages/fe/e6/8c9e81bb6dd7560e33b9053351c29f30c8194b72f2d6932888581f503482/pydantic_core-2.41.5-cp311-cp311-win32.whl", hash = "sha256:2c010c6ded393148374c0f6f0bf89d206bf3217f201faa0635dcd56bd1520f6b", size = 1987549, upload-time = "2025-11-04T13:39:51.842Z" }, - { url = "https://files.pythonhosted.org/packages/11/66/f14d1d978ea94d1bc21fc98fcf570f9542fe55bfcc40269d4e1a21c19bf7/pydantic_core-2.41.5-cp311-cp311-win_amd64.whl", hash = "sha256:76ee27c6e9c7f16f47db7a94157112a2f3a00e958bc626e2f4ee8bec5c328fbe", size = 2011305, upload-time = "2025-11-04T13:39:53.485Z" }, - { url = "https://files.pythonhosted.org/packages/56/d8/0e271434e8efd03186c5386671328154ee349ff0354d83c74f5caaf096ed/pydantic_core-2.41.5-cp311-cp311-win_arm64.whl", hash = "sha256:4bc36bbc0b7584de96561184ad7f012478987882ebf9f9c389b23f432ea3d90f", size = 1972902, upload-time = "2025-11-04T13:39:56.488Z" }, - { url = "https://files.pythonhosted.org/packages/5f/5d/5f6c63eebb5afee93bcaae4ce9a898f3373ca23df3ccaef086d0233a35a7/pydantic_core-2.41.5-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:f41a7489d32336dbf2199c8c0a215390a751c5b014c2c1c5366e817202e9cdf7", size = 2110990, upload-time = "2025-11-04T13:39:58.079Z" }, - { url = "https://files.pythonhosted.org/packages/aa/32/9c2e8ccb57c01111e0fd091f236c7b371c1bccea0fa85247ac55b1e2b6b6/pydantic_core-2.41.5-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:070259a8818988b9a84a449a2a7337c7f430a22acc0859c6b110aa7212a6d9c0", size = 1896003, upload-time = "2025-11-04T13:39:59.956Z" }, - { url = "https://files.pythonhosted.org/packages/68/b8/a01b53cb0e59139fbc9e4fda3e9724ede8de279097179be4ff31f1abb65a/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e96cea19e34778f8d59fe40775a7a574d95816eb150850a85a7a4c8f4b94ac69", size = 1919200, upload-time = "2025-11-04T13:40:02.241Z" }, - { url = "https://files.pythonhosted.org/packages/38/de/8c36b5198a29bdaade07b5985e80a233a5ac27137846f3bc2d3b40a47360/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed2e99c456e3fadd05c991f8f437ef902e00eedf34320ba2b0842bd1c3ca3a75", size = 2052578, upload-time = "2025-11-04T13:40:04.401Z" }, - { url = "https://files.pythonhosted.org/packages/00/b5/0e8e4b5b081eac6cb3dbb7e60a65907549a1ce035a724368c330112adfdd/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:65840751b72fbfd82c3c640cff9284545342a4f1eb1586ad0636955b261b0b05", size = 2208504, upload-time = "2025-11-04T13:40:06.072Z" }, - { url = "https://files.pythonhosted.org/packages/77/56/87a61aad59c7c5b9dc8caad5a41a5545cba3810c3e828708b3d7404f6cef/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e536c98a7626a98feb2d3eaf75944ef6f3dbee447e1f841eae16f2f0a72d8ddc", size = 2335816, upload-time = "2025-11-04T13:40:07.835Z" }, - { url = "https://files.pythonhosted.org/packages/0d/76/941cc9f73529988688a665a5c0ecff1112b3d95ab48f81db5f7606f522d3/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eceb81a8d74f9267ef4081e246ffd6d129da5d87e37a77c9bde550cb04870c1c", size = 2075366, upload-time = "2025-11-04T13:40:09.804Z" }, - { url = "https://files.pythonhosted.org/packages/d3/43/ebef01f69baa07a482844faaa0a591bad1ef129253ffd0cdaa9d8a7f72d3/pydantic_core-2.41.5-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d38548150c39b74aeeb0ce8ee1d8e82696f4a4e16ddc6de7b1d8823f7de4b9b5", size = 2171698, upload-time = "2025-11-04T13:40:12.004Z" }, - { url = "https://files.pythonhosted.org/packages/b1/87/41f3202e4193e3bacfc2c065fab7706ebe81af46a83d3e27605029c1f5a6/pydantic_core-2.41.5-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:c23e27686783f60290e36827f9c626e63154b82b116d7fe9adba1fda36da706c", size = 2132603, upload-time = "2025-11-04T13:40:13.868Z" }, - { url = "https://files.pythonhosted.org/packages/49/7d/4c00df99cb12070b6bccdef4a195255e6020a550d572768d92cc54dba91a/pydantic_core-2.41.5-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:482c982f814460eabe1d3bb0adfdc583387bd4691ef00b90575ca0d2b6fe2294", size = 2329591, upload-time = "2025-11-04T13:40:15.672Z" }, - { url = "https://files.pythonhosted.org/packages/cc/6a/ebf4b1d65d458f3cda6a7335d141305dfa19bdc61140a884d165a8a1bbc7/pydantic_core-2.41.5-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:bfea2a5f0b4d8d43adf9d7b8bf019fb46fdd10a2e5cde477fbcb9d1fa08c68e1", size = 2319068, upload-time = "2025-11-04T13:40:17.532Z" }, - { url = "https://files.pythonhosted.org/packages/49/3b/774f2b5cd4192d5ab75870ce4381fd89cf218af999515baf07e7206753f0/pydantic_core-2.41.5-cp312-cp312-win32.whl", hash = "sha256:b74557b16e390ec12dca509bce9264c3bbd128f8a2c376eaa68003d7f327276d", size = 1985908, upload-time = "2025-11-04T13:40:19.309Z" }, - { url = "https://files.pythonhosted.org/packages/86/45/00173a033c801cacf67c190fef088789394feaf88a98a7035b0e40d53dc9/pydantic_core-2.41.5-cp312-cp312-win_amd64.whl", hash = "sha256:1962293292865bca8e54702b08a4f26da73adc83dd1fcf26fbc875b35d81c815", size = 2020145, upload-time = "2025-11-04T13:40:21.548Z" }, - { url = "https://files.pythonhosted.org/packages/f9/22/91fbc821fa6d261b376a3f73809f907cec5ca6025642c463d3488aad22fb/pydantic_core-2.41.5-cp312-cp312-win_arm64.whl", hash = "sha256:1746d4a3d9a794cacae06a5eaaccb4b8643a131d45fbc9af23e353dc0a5ba5c3", size = 1976179, upload-time = "2025-11-04T13:40:23.393Z" }, - { url = "https://files.pythonhosted.org/packages/87/06/8806241ff1f70d9939f9af039c6c35f2360cf16e93c2ca76f184e76b1564/pydantic_core-2.41.5-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:941103c9be18ac8daf7b7adca8228f8ed6bb7a1849020f643b3a14d15b1924d9", size = 2120403, upload-time = "2025-11-04T13:40:25.248Z" }, - { url = "https://files.pythonhosted.org/packages/94/02/abfa0e0bda67faa65fef1c84971c7e45928e108fe24333c81f3bfe35d5f5/pydantic_core-2.41.5-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:112e305c3314f40c93998e567879e887a3160bb8689ef3d2c04b6cc62c33ac34", size = 1896206, upload-time = "2025-11-04T13:40:27.099Z" }, - { url = "https://files.pythonhosted.org/packages/15/df/a4c740c0943e93e6500f9eb23f4ca7ec9bf71b19e608ae5b579678c8d02f/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0cbaad15cb0c90aa221d43c00e77bb33c93e8d36e0bf74760cd00e732d10a6a0", size = 1919307, upload-time = "2025-11-04T13:40:29.806Z" }, - { url = "https://files.pythonhosted.org/packages/9a/e3/6324802931ae1d123528988e0e86587c2072ac2e5394b4bc2bc34b61ff6e/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:03ca43e12fab6023fc79d28ca6b39b05f794ad08ec2feccc59a339b02f2b3d33", size = 2063258, upload-time = "2025-11-04T13:40:33.544Z" }, - { url = "https://files.pythonhosted.org/packages/c9/d4/2230d7151d4957dd79c3044ea26346c148c98fbf0ee6ebd41056f2d62ab5/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dc799088c08fa04e43144b164feb0c13f9a0bc40503f8df3e9fde58a3c0c101e", size = 2214917, upload-time = "2025-11-04T13:40:35.479Z" }, - { url = "https://files.pythonhosted.org/packages/e6/9f/eaac5df17a3672fef0081b6c1bb0b82b33ee89aa5cec0d7b05f52fd4a1fa/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:97aeba56665b4c3235a0e52b2c2f5ae9cd071b8a8310ad27bddb3f7fb30e9aa2", size = 2332186, upload-time = "2025-11-04T13:40:37.436Z" }, - { url = "https://files.pythonhosted.org/packages/cf/4e/35a80cae583a37cf15604b44240e45c05e04e86f9cfd766623149297e971/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:406bf18d345822d6c21366031003612b9c77b3e29ffdb0f612367352aab7d586", size = 2073164, upload-time = "2025-11-04T13:40:40.289Z" }, - { url = "https://files.pythonhosted.org/packages/bf/e3/f6e262673c6140dd3305d144d032f7bd5f7497d3871c1428521f19f9efa2/pydantic_core-2.41.5-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b93590ae81f7010dbe380cdeab6f515902ebcbefe0b9327cc4804d74e93ae69d", size = 2179146, upload-time = "2025-11-04T13:40:42.809Z" }, - { url = "https://files.pythonhosted.org/packages/75/c7/20bd7fc05f0c6ea2056a4565c6f36f8968c0924f19b7d97bbfea55780e73/pydantic_core-2.41.5-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:01a3d0ab748ee531f4ea6c3e48ad9dac84ddba4b0d82291f87248f2f9de8d740", size = 2137788, upload-time = "2025-11-04T13:40:44.752Z" }, - { url = "https://files.pythonhosted.org/packages/3a/8d/34318ef985c45196e004bc46c6eab2eda437e744c124ef0dbe1ff2c9d06b/pydantic_core-2.41.5-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:6561e94ba9dacc9c61bce40e2d6bdc3bfaa0259d3ff36ace3b1e6901936d2e3e", size = 2340133, upload-time = "2025-11-04T13:40:46.66Z" }, - { url = "https://files.pythonhosted.org/packages/9c/59/013626bf8c78a5a5d9350d12e7697d3d4de951a75565496abd40ccd46bee/pydantic_core-2.41.5-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:915c3d10f81bec3a74fbd4faebe8391013ba61e5a1a8d48c4455b923bdda7858", size = 2324852, upload-time = "2025-11-04T13:40:48.575Z" }, - { url = "https://files.pythonhosted.org/packages/1a/d9/c248c103856f807ef70c18a4f986693a46a8ffe1602e5d361485da502d20/pydantic_core-2.41.5-cp313-cp313-win32.whl", hash = "sha256:650ae77860b45cfa6e2cdafc42618ceafab3a2d9a3811fcfbd3bbf8ac3c40d36", size = 1994679, upload-time = "2025-11-04T13:40:50.619Z" }, - { url = "https://files.pythonhosted.org/packages/9e/8b/341991b158ddab181cff136acd2552c9f35bd30380422a639c0671e99a91/pydantic_core-2.41.5-cp313-cp313-win_amd64.whl", hash = "sha256:79ec52ec461e99e13791ec6508c722742ad745571f234ea6255bed38c6480f11", size = 2019766, upload-time = "2025-11-04T13:40:52.631Z" }, - { url = "https://files.pythonhosted.org/packages/73/7d/f2f9db34af103bea3e09735bb40b021788a5e834c81eedb541991badf8f5/pydantic_core-2.41.5-cp313-cp313-win_arm64.whl", hash = "sha256:3f84d5c1b4ab906093bdc1ff10484838aca54ef08de4afa9de0f5f14d69639cd", size = 1981005, upload-time = "2025-11-04T13:40:54.734Z" }, - { url = "https://files.pythonhosted.org/packages/ea/28/46b7c5c9635ae96ea0fbb779e271a38129df2550f763937659ee6c5dbc65/pydantic_core-2.41.5-cp314-cp314-macosx_10_12_x86_64.whl", hash = "sha256:3f37a19d7ebcdd20b96485056ba9e8b304e27d9904d233d7b1015db320e51f0a", size = 2119622, upload-time = "2025-11-04T13:40:56.68Z" }, - { url = "https://files.pythonhosted.org/packages/74/1a/145646e5687e8d9a1e8d09acb278c8535ebe9e972e1f162ed338a622f193/pydantic_core-2.41.5-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:1d1d9764366c73f996edd17abb6d9d7649a7eb690006ab6adbda117717099b14", size = 1891725, upload-time = "2025-11-04T13:40:58.807Z" }, - { url = "https://files.pythonhosted.org/packages/23/04/e89c29e267b8060b40dca97bfc64a19b2a3cf99018167ea1677d96368273/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25e1c2af0fce638d5f1988b686f3b3ea8cd7de5f244ca147c777769e798a9cd1", size = 1915040, upload-time = "2025-11-04T13:41:00.853Z" }, - { url = "https://files.pythonhosted.org/packages/84/a3/15a82ac7bd97992a82257f777b3583d3e84bdb06ba6858f745daa2ec8a85/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:506d766a8727beef16b7adaeb8ee6217c64fc813646b424d0804d67c16eddb66", size = 2063691, upload-time = "2025-11-04T13:41:03.504Z" }, - { url = "https://files.pythonhosted.org/packages/74/9b/0046701313c6ef08c0c1cf0e028c67c770a4e1275ca73131563c5f2a310a/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4819fa52133c9aa3c387b3328f25c1facc356491e6135b459f1de698ff64d869", size = 2213897, upload-time = "2025-11-04T13:41:05.804Z" }, - { url = "https://files.pythonhosted.org/packages/8a/cd/6bac76ecd1b27e75a95ca3a9a559c643b3afcd2dd62086d4b7a32a18b169/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2b761d210c9ea91feda40d25b4efe82a1707da2ef62901466a42492c028553a2", size = 2333302, upload-time = "2025-11-04T13:41:07.809Z" }, - { url = "https://files.pythonhosted.org/packages/4c/d2/ef2074dc020dd6e109611a8be4449b98cd25e1b9b8a303c2f0fca2f2bcf7/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:22f0fb8c1c583a3b6f24df2470833b40207e907b90c928cc8d3594b76f874375", size = 2064877, upload-time = "2025-11-04T13:41:09.827Z" }, - { url = "https://files.pythonhosted.org/packages/18/66/e9db17a9a763d72f03de903883c057b2592c09509ccfe468187f2a2eef29/pydantic_core-2.41.5-cp314-cp314-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2782c870e99878c634505236d81e5443092fba820f0373997ff75f90f68cd553", size = 2180680, upload-time = "2025-11-04T13:41:12.379Z" }, - { url = "https://files.pythonhosted.org/packages/d3/9e/3ce66cebb929f3ced22be85d4c2399b8e85b622db77dad36b73c5387f8f8/pydantic_core-2.41.5-cp314-cp314-musllinux_1_1_aarch64.whl", hash = "sha256:0177272f88ab8312479336e1d777f6b124537d47f2123f89cb37e0accea97f90", size = 2138960, upload-time = "2025-11-04T13:41:14.627Z" }, - { url = "https://files.pythonhosted.org/packages/a6/62/205a998f4327d2079326b01abee48e502ea739d174f0a89295c481a2272e/pydantic_core-2.41.5-cp314-cp314-musllinux_1_1_armv7l.whl", hash = "sha256:63510af5e38f8955b8ee5687740d6ebf7c2a0886d15a6d65c32814613681bc07", size = 2339102, upload-time = "2025-11-04T13:41:16.868Z" }, - { url = "https://files.pythonhosted.org/packages/3c/0d/f05e79471e889d74d3d88f5bd20d0ed189ad94c2423d81ff8d0000aab4ff/pydantic_core-2.41.5-cp314-cp314-musllinux_1_1_x86_64.whl", hash = "sha256:e56ba91f47764cc14f1daacd723e3e82d1a89d783f0f5afe9c364b8bb491ccdb", size = 2326039, upload-time = "2025-11-04T13:41:18.934Z" }, - { url = "https://files.pythonhosted.org/packages/ec/e1/e08a6208bb100da7e0c4b288eed624a703f4d129bde2da475721a80cab32/pydantic_core-2.41.5-cp314-cp314-win32.whl", hash = "sha256:aec5cf2fd867b4ff45b9959f8b20ea3993fc93e63c7363fe6851424c8a7e7c23", size = 1995126, upload-time = "2025-11-04T13:41:21.418Z" }, - { url = "https://files.pythonhosted.org/packages/48/5d/56ba7b24e9557f99c9237e29f5c09913c81eeb2f3217e40e922353668092/pydantic_core-2.41.5-cp314-cp314-win_amd64.whl", hash = "sha256:8e7c86f27c585ef37c35e56a96363ab8de4e549a95512445b85c96d3e2f7c1bf", size = 2015489, upload-time = "2025-11-04T13:41:24.076Z" }, - { url = "https://files.pythonhosted.org/packages/4e/bb/f7a190991ec9e3e0ba22e4993d8755bbc4a32925c0b5b42775c03e8148f9/pydantic_core-2.41.5-cp314-cp314-win_arm64.whl", hash = "sha256:e672ba74fbc2dc8eea59fb6d4aed6845e6905fc2a8afe93175d94a83ba2a01a0", size = 1977288, upload-time = "2025-11-04T13:41:26.33Z" }, - { url = "https://files.pythonhosted.org/packages/92/ed/77542d0c51538e32e15afe7899d79efce4b81eee631d99850edc2f5e9349/pydantic_core-2.41.5-cp314-cp314t-macosx_10_12_x86_64.whl", hash = "sha256:8566def80554c3faa0e65ac30ab0932b9e3a5cd7f8323764303d468e5c37595a", size = 2120255, upload-time = "2025-11-04T13:41:28.569Z" }, - { url = "https://files.pythonhosted.org/packages/bb/3d/6913dde84d5be21e284439676168b28d8bbba5600d838b9dca99de0fad71/pydantic_core-2.41.5-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:b80aa5095cd3109962a298ce14110ae16b8c1aece8b72f9dafe81cf597ad80b3", size = 1863760, upload-time = "2025-11-04T13:41:31.055Z" }, - { url = "https://files.pythonhosted.org/packages/5a/f0/e5e6b99d4191da102f2b0eb9687aaa7f5bea5d9964071a84effc3e40f997/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3006c3dd9ba34b0c094c544c6006cc79e87d8612999f1a5d43b769b89181f23c", size = 1878092, upload-time = "2025-11-04T13:41:33.21Z" }, - { url = "https://files.pythonhosted.org/packages/71/48/36fb760642d568925953bcc8116455513d6e34c4beaa37544118c36aba6d/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:72f6c8b11857a856bcfa48c86f5368439f74453563f951e473514579d44aa612", size = 2053385, upload-time = "2025-11-04T13:41:35.508Z" }, - { url = "https://files.pythonhosted.org/packages/20/25/92dc684dd8eb75a234bc1c764b4210cf2646479d54b47bf46061657292a8/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5cb1b2f9742240e4bb26b652a5aeb840aa4b417c7748b6f8387927bc6e45e40d", size = 2218832, upload-time = "2025-11-04T13:41:37.732Z" }, - { url = "https://files.pythonhosted.org/packages/e2/09/f53e0b05023d3e30357d82eb35835d0f6340ca344720a4599cd663dca599/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bd3d54f38609ff308209bd43acea66061494157703364ae40c951f83ba99a1a9", size = 2327585, upload-time = "2025-11-04T13:41:40Z" }, - { url = "https://files.pythonhosted.org/packages/aa/4e/2ae1aa85d6af35a39b236b1b1641de73f5a6ac4d5a7509f77b814885760c/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2ff4321e56e879ee8d2a879501c8e469414d948f4aba74a2d4593184eb326660", size = 2041078, upload-time = "2025-11-04T13:41:42.323Z" }, - { url = "https://files.pythonhosted.org/packages/cd/13/2e215f17f0ef326fc72afe94776edb77525142c693767fc347ed6288728d/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d0d2568a8c11bf8225044aa94409e21da0cb09dcdafe9ecd10250b2baad531a9", size = 2173914, upload-time = "2025-11-04T13:41:45.221Z" }, - { url = "https://files.pythonhosted.org/packages/02/7a/f999a6dcbcd0e5660bc348a3991c8915ce6599f4f2c6ac22f01d7a10816c/pydantic_core-2.41.5-cp314-cp314t-musllinux_1_1_aarch64.whl", hash = "sha256:a39455728aabd58ceabb03c90e12f71fd30fa69615760a075b9fec596456ccc3", size = 2129560, upload-time = "2025-11-04T13:41:47.474Z" }, - { url = "https://files.pythonhosted.org/packages/3a/b1/6c990ac65e3b4c079a4fb9f5b05f5b013afa0f4ed6780a3dd236d2cbdc64/pydantic_core-2.41.5-cp314-cp314t-musllinux_1_1_armv7l.whl", hash = "sha256:239edca560d05757817c13dc17c50766136d21f7cd0fac50295499ae24f90fdf", size = 2329244, upload-time = "2025-11-04T13:41:49.992Z" }, - { url = "https://files.pythonhosted.org/packages/d9/02/3c562f3a51afd4d88fff8dffb1771b30cfdfd79befd9883ee094f5b6c0d8/pydantic_core-2.41.5-cp314-cp314t-musllinux_1_1_x86_64.whl", hash = "sha256:2a5e06546e19f24c6a96a129142a75cee553cc018ffee48a460059b1185f4470", size = 2331955, upload-time = "2025-11-04T13:41:54.079Z" }, - { url = "https://files.pythonhosted.org/packages/5c/96/5fb7d8c3c17bc8c62fdb031c47d77a1af698f1d7a406b0f79aaa1338f9ad/pydantic_core-2.41.5-cp314-cp314t-win32.whl", hash = "sha256:b4ececa40ac28afa90871c2cc2b9ffd2ff0bf749380fbdf57d165fd23da353aa", size = 1988906, upload-time = "2025-11-04T13:41:56.606Z" }, - { url = "https://files.pythonhosted.org/packages/22/ed/182129d83032702912c2e2d8bbe33c036f342cc735737064668585dac28f/pydantic_core-2.41.5-cp314-cp314t-win_amd64.whl", hash = "sha256:80aa89cad80b32a912a65332f64a4450ed00966111b6615ca6816153d3585a8c", size = 1981607, upload-time = "2025-11-04T13:41:58.889Z" }, - { url = "https://files.pythonhosted.org/packages/9f/ed/068e41660b832bb0b1aa5b58011dea2a3fe0ba7861ff38c4d4904c1c1a99/pydantic_core-2.41.5-cp314-cp314t-win_arm64.whl", hash = "sha256:35b44f37a3199f771c3eaa53051bc8a70cd7b54f333531c59e29fd4db5d15008", size = 1974769, upload-time = "2025-11-04T13:42:01.186Z" }, - { url = "https://files.pythonhosted.org/packages/11/72/90fda5ee3b97e51c494938a4a44c3a35a9c96c19bba12372fb9c634d6f57/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-macosx_10_12_x86_64.whl", hash = "sha256:b96d5f26b05d03cc60f11a7761a5ded1741da411e7fe0909e27a5e6a0cb7b034", size = 2115441, upload-time = "2025-11-04T13:42:39.557Z" }, - { url = "https://files.pythonhosted.org/packages/1f/53/8942f884fa33f50794f119012dc6a1a02ac43a56407adaac20463df8e98f/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-macosx_11_0_arm64.whl", hash = "sha256:634e8609e89ceecea15e2d61bc9ac3718caaaa71963717bf3c8f38bfde64242c", size = 1930291, upload-time = "2025-11-04T13:42:42.169Z" }, - { url = "https://files.pythonhosted.org/packages/79/c8/ecb9ed9cd942bce09fc888ee960b52654fbdbede4ba6c2d6e0d3b1d8b49c/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:93e8740d7503eb008aa2df04d3b9735f845d43ae845e6dcd2be0b55a2da43cd2", size = 1948632, upload-time = "2025-11-04T13:42:44.564Z" }, - { url = "https://files.pythonhosted.org/packages/2e/1b/687711069de7efa6af934e74f601e2a4307365e8fdc404703afc453eab26/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f15489ba13d61f670dcc96772e733aad1a6f9c429cc27574c6cdaed82d0146ad", size = 2138905, upload-time = "2025-11-04T13:42:47.156Z" }, - { url = "https://files.pythonhosted.org/packages/09/32/59b0c7e63e277fa7911c2fc70ccfb45ce4b98991e7ef37110663437005af/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-macosx_10_12_x86_64.whl", hash = "sha256:7da7087d756b19037bc2c06edc6c170eeef3c3bafcb8f532ff17d64dc427adfd", size = 2110495, upload-time = "2025-11-04T13:42:49.689Z" }, - { url = "https://files.pythonhosted.org/packages/aa/81/05e400037eaf55ad400bcd318c05bb345b57e708887f07ddb2d20e3f0e98/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-macosx_11_0_arm64.whl", hash = "sha256:aabf5777b5c8ca26f7824cb4a120a740c9588ed58df9b2d196ce92fba42ff8dc", size = 1915388, upload-time = "2025-11-04T13:42:52.215Z" }, - { url = "https://files.pythonhosted.org/packages/6e/0d/e3549b2399f71d56476b77dbf3cf8937cec5cd70536bdc0e374a421d0599/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c007fe8a43d43b3969e8469004e9845944f1a80e6acd47c150856bb87f230c56", size = 1942879, upload-time = "2025-11-04T13:42:56.483Z" }, - { url = "https://files.pythonhosted.org/packages/f7/07/34573da085946b6a313d7c42f82f16e8920bfd730665de2d11c0c37a74b5/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:76d0819de158cd855d1cbb8fcafdf6f5cf1eb8e470abe056d5d161106e38062b", size = 2139017, upload-time = "2025-11-04T13:42:59.471Z" }, - { url = "https://files.pythonhosted.org/packages/5f/9b/1b3f0e9f9305839d7e84912f9e8bfbd191ed1b1ef48083609f0dabde978c/pydantic_core-2.41.5-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:b2379fa7ed44ddecb5bfe4e48577d752db9fc10be00a6b7446e9663ba143de26", size = 2101980, upload-time = "2025-11-04T13:43:25.97Z" }, - { url = "https://files.pythonhosted.org/packages/a4/ed/d71fefcb4263df0da6a85b5d8a7508360f2f2e9b3bf5814be9c8bccdccc1/pydantic_core-2.41.5-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:266fb4cbf5e3cbd0b53669a6d1b039c45e3ce651fd5442eff4d07c2cc8d66808", size = 1923865, upload-time = "2025-11-04T13:43:28.763Z" }, - { url = "https://files.pythonhosted.org/packages/ce/3a/626b38db460d675f873e4444b4bb030453bbe7b4ba55df821d026a0493c4/pydantic_core-2.41.5-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58133647260ea01e4d0500089a8c4f07bd7aa6ce109682b1426394988d8aaacc", size = 2134256, upload-time = "2025-11-04T13:43:31.71Z" }, - { url = "https://files.pythonhosted.org/packages/83/d9/8412d7f06f616bbc053d30cb4e5f76786af3221462ad5eee1f202021eb4e/pydantic_core-2.41.5-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:287dad91cfb551c363dc62899a80e9e14da1f0e2b6ebde82c806612ca2a13ef1", size = 2174762, upload-time = "2025-11-04T13:43:34.744Z" }, - { url = "https://files.pythonhosted.org/packages/55/4c/162d906b8e3ba3a99354e20faa1b49a85206c47de97a639510a0e673f5da/pydantic_core-2.41.5-pp311-pypy311_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:03b77d184b9eb40240ae9fd676ca364ce1085f203e1b1256f8ab9984dca80a84", size = 2143141, upload-time = "2025-11-04T13:43:37.701Z" }, - { url = "https://files.pythonhosted.org/packages/1f/f2/f11dd73284122713f5f89fc940f370d035fa8e1e078d446b3313955157fe/pydantic_core-2.41.5-pp311-pypy311_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:a668ce24de96165bb239160b3d854943128f4334822900534f2fe947930e5770", size = 2330317, upload-time = "2025-11-04T13:43:40.406Z" }, - { url = "https://files.pythonhosted.org/packages/88/9d/b06ca6acfe4abb296110fb1273a4d848a0bfb2ff65f3ee92127b3244e16b/pydantic_core-2.41.5-pp311-pypy311_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f14f8f046c14563f8eb3f45f499cc658ab8d10072961e07225e507adb700e93f", size = 2316992, upload-time = "2025-11-04T13:43:43.602Z" }, - { url = "https://files.pythonhosted.org/packages/36/c7/cfc8e811f061c841d7990b0201912c3556bfeb99cdcb7ed24adc8d6f8704/pydantic_core-2.41.5-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:56121965f7a4dc965bff783d70b907ddf3d57f6eba29b6d2e5dabfaf07799c51", size = 2145302, upload-time = "2025-11-04T13:43:46.64Z" }, -] - -[[package]] -name = "python-dotenv" -version = "1.2.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f0/26/19cadc79a718c5edbec86fd4919a6b6d3f681039a2f6d66d14be94e75fb9/python_dotenv-1.2.1.tar.gz", hash = "sha256:42667e897e16ab0d66954af0e60a9caa94f0fd4ecf3aaf6d2d260eec1aa36ad6", size = 44221, upload-time = "2025-10-26T15:12:10.434Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/14/1b/a298b06749107c305e1fe0f814c6c74aea7b2f1e10989cb30f544a1b3253/python_dotenv-1.2.1-py3-none-any.whl", hash = "sha256:b81ee9561e9ca4004139c6cbba3a238c32b03e4894671e181b671e8cb8425d61", size = 21230, upload-time = "2025-10-26T15:12:09.109Z" }, -] - -[[package]] -name = "python-slugify" -version = "8.0.4" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "text-unidecode" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/87/c7/5e1547c44e31da50a460df93af11a535ace568ef89d7a811069ead340c4a/python-slugify-8.0.4.tar.gz", hash = "sha256:59202371d1d05b54a9e7720c5e038f928f45daaffe41dd10822f3907b937c856", size = 10921, upload-time = "2024-02-08T18:32:45.488Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a4/62/02da182e544a51a5c3ccf4b03ab79df279f9c60c5e82d5e8bec7ca26ac11/python_slugify-8.0.4-py2.py3-none-any.whl", hash = "sha256:276540b79961052b66b7d116620b36518847f52d5fd9e3a70164fc8c50faa6b8", size = 10051, upload-time = "2024-02-08T18:32:43.911Z" }, -] - -[[package]] -name = "pyyaml" -version = "6.0.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/05/8e/961c0007c59b8dd7729d542c61a4d537767a59645b82a0b521206e1e25c2/pyyaml-6.0.3.tar.gz", hash = "sha256:d76623373421df22fb4cf8817020cbb7ef15c725b9d5e45f17e189bfc384190f", size = 130960, upload-time = "2025-09-25T21:33:16.546Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/6d/16/a95b6757765b7b031c9374925bb718d55e0a9ba8a1b6a12d25962ea44347/pyyaml-6.0.3-cp311-cp311-macosx_10_13_x86_64.whl", hash = "sha256:44edc647873928551a01e7a563d7452ccdebee747728c1080d881d68af7b997e", size = 185826, upload-time = "2025-09-25T21:31:58.655Z" }, - { url = "https://files.pythonhosted.org/packages/16/19/13de8e4377ed53079ee996e1ab0a9c33ec2faf808a4647b7b4c0d46dd239/pyyaml-6.0.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:652cb6edd41e718550aad172851962662ff2681490a8a711af6a4d288dd96824", size = 175577, upload-time = "2025-09-25T21:32:00.088Z" }, - { url = "https://files.pythonhosted.org/packages/0c/62/d2eb46264d4b157dae1275b573017abec435397aa59cbcdab6fc978a8af4/pyyaml-6.0.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:10892704fc220243f5305762e276552a0395f7beb4dbf9b14ec8fd43b57f126c", size = 775556, upload-time = "2025-09-25T21:32:01.31Z" }, - { url = "https://files.pythonhosted.org/packages/10/cb/16c3f2cf3266edd25aaa00d6c4350381c8b012ed6f5276675b9eba8d9ff4/pyyaml-6.0.3-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:850774a7879607d3a6f50d36d04f00ee69e7fc816450e5f7e58d7f17f1ae5c00", size = 882114, upload-time = "2025-09-25T21:32:03.376Z" }, - { url = "https://files.pythonhosted.org/packages/71/60/917329f640924b18ff085ab889a11c763e0b573da888e8404ff486657602/pyyaml-6.0.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b8bb0864c5a28024fac8a632c443c87c5aa6f215c0b126c449ae1a150412f31d", size = 806638, upload-time = "2025-09-25T21:32:04.553Z" }, - { url = "https://files.pythonhosted.org/packages/dd/6f/529b0f316a9fd167281a6c3826b5583e6192dba792dd55e3203d3f8e655a/pyyaml-6.0.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:1d37d57ad971609cf3c53ba6a7e365e40660e3be0e5175fa9f2365a379d6095a", size = 767463, upload-time = "2025-09-25T21:32:06.152Z" }, - { url = "https://files.pythonhosted.org/packages/f2/6a/b627b4e0c1dd03718543519ffb2f1deea4a1e6d42fbab8021936a4d22589/pyyaml-6.0.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:37503bfbfc9d2c40b344d06b2199cf0e96e97957ab1c1b546fd4f87e53e5d3e4", size = 794986, upload-time = "2025-09-25T21:32:07.367Z" }, - { url = "https://files.pythonhosted.org/packages/45/91/47a6e1c42d9ee337c4839208f30d9f09caa9f720ec7582917b264defc875/pyyaml-6.0.3-cp311-cp311-win32.whl", hash = "sha256:8098f252adfa6c80ab48096053f512f2321f0b998f98150cea9bd23d83e1467b", size = 142543, upload-time = "2025-09-25T21:32:08.95Z" }, - { url = "https://files.pythonhosted.org/packages/da/e3/ea007450a105ae919a72393cb06f122f288ef60bba2dc64b26e2646fa315/pyyaml-6.0.3-cp311-cp311-win_amd64.whl", hash = "sha256:9f3bfb4965eb874431221a3ff3fdcddc7e74e3b07799e0e84ca4a0f867d449bf", size = 158763, upload-time = "2025-09-25T21:32:09.96Z" }, - { url = "https://files.pythonhosted.org/packages/d1/33/422b98d2195232ca1826284a76852ad5a86fe23e31b009c9886b2d0fb8b2/pyyaml-6.0.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7f047e29dcae44602496db43be01ad42fc6f1cc0d8cd6c83d342306c32270196", size = 182063, upload-time = "2025-09-25T21:32:11.445Z" }, - { url = "https://files.pythonhosted.org/packages/89/a0/6cf41a19a1f2f3feab0e9c0b74134aa2ce6849093d5517a0c550fe37a648/pyyaml-6.0.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:fc09d0aa354569bc501d4e787133afc08552722d3ab34836a80547331bb5d4a0", size = 173973, upload-time = "2025-09-25T21:32:12.492Z" }, - { url = "https://files.pythonhosted.org/packages/ed/23/7a778b6bd0b9a8039df8b1b1d80e2e2ad78aa04171592c8a5c43a56a6af4/pyyaml-6.0.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:9149cad251584d5fb4981be1ecde53a1ca46c891a79788c0df828d2f166bda28", size = 775116, upload-time = "2025-09-25T21:32:13.652Z" }, - { url = "https://files.pythonhosted.org/packages/65/30/d7353c338e12baef4ecc1b09e877c1970bd3382789c159b4f89d6a70dc09/pyyaml-6.0.3-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:5fdec68f91a0c6739b380c83b951e2c72ac0197ace422360e6d5a959d8d97b2c", size = 844011, upload-time = "2025-09-25T21:32:15.21Z" }, - { url = "https://files.pythonhosted.org/packages/8b/9d/b3589d3877982d4f2329302ef98a8026e7f4443c765c46cfecc8858c6b4b/pyyaml-6.0.3-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ba1cc08a7ccde2d2ec775841541641e4548226580ab850948cbfda66a1befcdc", size = 807870, upload-time = "2025-09-25T21:32:16.431Z" }, - { url = "https://files.pythonhosted.org/packages/05/c0/b3be26a015601b822b97d9149ff8cb5ead58c66f981e04fedf4e762f4bd4/pyyaml-6.0.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8dc52c23056b9ddd46818a57b78404882310fb473d63f17b07d5c40421e47f8e", size = 761089, upload-time = "2025-09-25T21:32:17.56Z" }, - { url = "https://files.pythonhosted.org/packages/be/8e/98435a21d1d4b46590d5459a22d88128103f8da4c2d4cb8f14f2a96504e1/pyyaml-6.0.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:41715c910c881bc081f1e8872880d3c650acf13dfa8214bad49ed4cede7c34ea", size = 790181, upload-time = "2025-09-25T21:32:18.834Z" }, - { url = "https://files.pythonhosted.org/packages/74/93/7baea19427dcfbe1e5a372d81473250b379f04b1bd3c4c5ff825e2327202/pyyaml-6.0.3-cp312-cp312-win32.whl", hash = "sha256:96b533f0e99f6579b3d4d4995707cf36df9100d67e0c8303a0c55b27b5f99bc5", size = 137658, upload-time = "2025-09-25T21:32:20.209Z" }, - { url = "https://files.pythonhosted.org/packages/86/bf/899e81e4cce32febab4fb42bb97dcdf66bc135272882d1987881a4b519e9/pyyaml-6.0.3-cp312-cp312-win_amd64.whl", hash = "sha256:5fcd34e47f6e0b794d17de1b4ff496c00986e1c83f7ab2fb8fcfe9616ff7477b", size = 154003, upload-time = "2025-09-25T21:32:21.167Z" }, - { url = "https://files.pythonhosted.org/packages/1a/08/67bd04656199bbb51dbed1439b7f27601dfb576fb864099c7ef0c3e55531/pyyaml-6.0.3-cp312-cp312-win_arm64.whl", hash = "sha256:64386e5e707d03a7e172c0701abfb7e10f0fb753ee1d773128192742712a98fd", size = 140344, upload-time = "2025-09-25T21:32:22.617Z" }, - { url = "https://files.pythonhosted.org/packages/d1/11/0fd08f8192109f7169db964b5707a2f1e8b745d4e239b784a5a1dd80d1db/pyyaml-6.0.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:8da9669d359f02c0b91ccc01cac4a67f16afec0dac22c2ad09f46bee0697eba8", size = 181669, upload-time = "2025-09-25T21:32:23.673Z" }, - { url = "https://files.pythonhosted.org/packages/b1/16/95309993f1d3748cd644e02e38b75d50cbc0d9561d21f390a76242ce073f/pyyaml-6.0.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:2283a07e2c21a2aa78d9c4442724ec1eb15f5e42a723b99cb3d822d48f5f7ad1", size = 173252, upload-time = "2025-09-25T21:32:25.149Z" }, - { url = "https://files.pythonhosted.org/packages/50/31/b20f376d3f810b9b2371e72ef5adb33879b25edb7a6d072cb7ca0c486398/pyyaml-6.0.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:ee2922902c45ae8ccada2c5b501ab86c36525b883eff4255313a253a3160861c", size = 767081, upload-time = "2025-09-25T21:32:26.575Z" }, - { url = "https://files.pythonhosted.org/packages/49/1e/a55ca81e949270d5d4432fbbd19dfea5321eda7c41a849d443dc92fd1ff7/pyyaml-6.0.3-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:a33284e20b78bd4a18c8c2282d549d10bc8408a2a7ff57653c0cf0b9be0afce5", size = 841159, upload-time = "2025-09-25T21:32:27.727Z" }, - { url = "https://files.pythonhosted.org/packages/74/27/e5b8f34d02d9995b80abcef563ea1f8b56d20134d8f4e5e81733b1feceb2/pyyaml-6.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0f29edc409a6392443abf94b9cf89ce99889a1dd5376d94316ae5145dfedd5d6", size = 801626, upload-time = "2025-09-25T21:32:28.878Z" }, - { url = "https://files.pythonhosted.org/packages/f9/11/ba845c23988798f40e52ba45f34849aa8a1f2d4af4b798588010792ebad6/pyyaml-6.0.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f7057c9a337546edc7973c0d3ba84ddcdf0daa14533c2065749c9075001090e6", size = 753613, upload-time = "2025-09-25T21:32:30.178Z" }, - { url = "https://files.pythonhosted.org/packages/3d/e0/7966e1a7bfc0a45bf0a7fb6b98ea03fc9b8d84fa7f2229e9659680b69ee3/pyyaml-6.0.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:eda16858a3cab07b80edaf74336ece1f986ba330fdb8ee0d6c0d68fe82bc96be", size = 794115, upload-time = "2025-09-25T21:32:31.353Z" }, - { url = "https://files.pythonhosted.org/packages/de/94/980b50a6531b3019e45ddeada0626d45fa85cbe22300844a7983285bed3b/pyyaml-6.0.3-cp313-cp313-win32.whl", hash = "sha256:d0eae10f8159e8fdad514efdc92d74fd8d682c933a6dd088030f3834bc8e6b26", size = 137427, upload-time = "2025-09-25T21:32:32.58Z" }, - { url = "https://files.pythonhosted.org/packages/97/c9/39d5b874e8b28845e4ec2202b5da735d0199dbe5b8fb85f91398814a9a46/pyyaml-6.0.3-cp313-cp313-win_amd64.whl", hash = "sha256:79005a0d97d5ddabfeeea4cf676af11e647e41d81c9a7722a193022accdb6b7c", size = 154090, upload-time = "2025-09-25T21:32:33.659Z" }, - { url = "https://files.pythonhosted.org/packages/73/e8/2bdf3ca2090f68bb3d75b44da7bbc71843b19c9f2b9cb9b0f4ab7a5a4329/pyyaml-6.0.3-cp313-cp313-win_arm64.whl", hash = "sha256:5498cd1645aa724a7c71c8f378eb29ebe23da2fc0d7a08071d89469bf1d2defb", size = 140246, upload-time = "2025-09-25T21:32:34.663Z" }, - { url = "https://files.pythonhosted.org/packages/9d/8c/f4bd7f6465179953d3ac9bc44ac1a8a3e6122cf8ada906b4f96c60172d43/pyyaml-6.0.3-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:8d1fab6bb153a416f9aeb4b8763bc0f22a5586065f86f7664fc23339fc1c1fac", size = 181814, upload-time = "2025-09-25T21:32:35.712Z" }, - { url = "https://files.pythonhosted.org/packages/bd/9c/4d95bb87eb2063d20db7b60faa3840c1b18025517ae857371c4dd55a6b3a/pyyaml-6.0.3-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:34d5fcd24b8445fadc33f9cf348c1047101756fd760b4dacb5c3e99755703310", size = 173809, upload-time = "2025-09-25T21:32:36.789Z" }, - { url = "https://files.pythonhosted.org/packages/92/b5/47e807c2623074914e29dabd16cbbdd4bf5e9b2db9f8090fa64411fc5382/pyyaml-6.0.3-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:501a031947e3a9025ed4405a168e6ef5ae3126c59f90ce0cd6f2bfc477be31b7", size = 766454, upload-time = "2025-09-25T21:32:37.966Z" }, - { url = "https://files.pythonhosted.org/packages/02/9e/e5e9b168be58564121efb3de6859c452fccde0ab093d8438905899a3a483/pyyaml-6.0.3-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:b3bc83488de33889877a0f2543ade9f70c67d66d9ebb4ac959502e12de895788", size = 836355, upload-time = "2025-09-25T21:32:39.178Z" }, - { url = "https://files.pythonhosted.org/packages/88/f9/16491d7ed2a919954993e48aa941b200f38040928474c9e85ea9e64222c3/pyyaml-6.0.3-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c458b6d084f9b935061bc36216e8a69a7e293a2f1e68bf956dcd9e6cbcd143f5", size = 794175, upload-time = "2025-09-25T21:32:40.865Z" }, - { url = "https://files.pythonhosted.org/packages/dd/3f/5989debef34dc6397317802b527dbbafb2b4760878a53d4166579111411e/pyyaml-6.0.3-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:7c6610def4f163542a622a73fb39f534f8c101d690126992300bf3207eab9764", size = 755228, upload-time = "2025-09-25T21:32:42.084Z" }, - { url = "https://files.pythonhosted.org/packages/d7/ce/af88a49043cd2e265be63d083fc75b27b6ed062f5f9fd6cdc223ad62f03e/pyyaml-6.0.3-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:5190d403f121660ce8d1d2c1bb2ef1bd05b5f68533fc5c2ea899bd15f4399b35", size = 789194, upload-time = "2025-09-25T21:32:43.362Z" }, - { url = "https://files.pythonhosted.org/packages/23/20/bb6982b26a40bb43951265ba29d4c246ef0ff59c9fdcdf0ed04e0687de4d/pyyaml-6.0.3-cp314-cp314-win_amd64.whl", hash = "sha256:4a2e8cebe2ff6ab7d1050ecd59c25d4c8bd7e6f400f5f82b96557ac0abafd0ac", size = 156429, upload-time = "2025-09-25T21:32:57.844Z" }, - { url = "https://files.pythonhosted.org/packages/f4/f4/a4541072bb9422c8a883ab55255f918fa378ecf083f5b85e87fc2b4eda1b/pyyaml-6.0.3-cp314-cp314-win_arm64.whl", hash = "sha256:93dda82c9c22deb0a405ea4dc5f2d0cda384168e466364dec6255b293923b2f3", size = 143912, upload-time = "2025-09-25T21:32:59.247Z" }, - { url = "https://files.pythonhosted.org/packages/7c/f9/07dd09ae774e4616edf6cda684ee78f97777bdd15847253637a6f052a62f/pyyaml-6.0.3-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:02893d100e99e03eda1c8fd5c441d8c60103fd175728e23e431db1b589cf5ab3", size = 189108, upload-time = "2025-09-25T21:32:44.377Z" }, - { url = "https://files.pythonhosted.org/packages/4e/78/8d08c9fb7ce09ad8c38ad533c1191cf27f7ae1effe5bb9400a46d9437fcf/pyyaml-6.0.3-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:c1ff362665ae507275af2853520967820d9124984e0f7466736aea23d8611fba", size = 183641, upload-time = "2025-09-25T21:32:45.407Z" }, - { url = "https://files.pythonhosted.org/packages/7b/5b/3babb19104a46945cf816d047db2788bcaf8c94527a805610b0289a01c6b/pyyaml-6.0.3-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6adc77889b628398debc7b65c073bcb99c4a0237b248cacaf3fe8a557563ef6c", size = 831901, upload-time = "2025-09-25T21:32:48.83Z" }, - { url = "https://files.pythonhosted.org/packages/8b/cc/dff0684d8dc44da4d22a13f35f073d558c268780ce3c6ba1b87055bb0b87/pyyaml-6.0.3-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:a80cb027f6b349846a3bf6d73b5e95e782175e52f22108cfa17876aaeff93702", size = 861132, upload-time = "2025-09-25T21:32:50.149Z" }, - { url = "https://files.pythonhosted.org/packages/b1/5e/f77dc6b9036943e285ba76b49e118d9ea929885becb0a29ba8a7c75e29fe/pyyaml-6.0.3-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:00c4bdeba853cc34e7dd471f16b4114f4162dc03e6b7afcc2128711f0eca823c", size = 839261, upload-time = "2025-09-25T21:32:51.808Z" }, - { url = "https://files.pythonhosted.org/packages/ce/88/a9db1376aa2a228197c58b37302f284b5617f56a5d959fd1763fb1675ce6/pyyaml-6.0.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:66e1674c3ef6f541c35191caae2d429b967b99e02040f5ba928632d9a7f0f065", size = 805272, upload-time = "2025-09-25T21:32:52.941Z" }, - { url = "https://files.pythonhosted.org/packages/da/92/1446574745d74df0c92e6aa4a7b0b3130706a4142b2d1a5869f2eaa423c6/pyyaml-6.0.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:16249ee61e95f858e83976573de0f5b2893b3677ba71c9dd36b9cf8be9ac6d65", size = 829923, upload-time = "2025-09-25T21:32:54.537Z" }, - { url = "https://files.pythonhosted.org/packages/f0/7a/1c7270340330e575b92f397352af856a8c06f230aa3e76f86b39d01b416a/pyyaml-6.0.3-cp314-cp314t-win_amd64.whl", hash = "sha256:4ad1906908f2f5ae4e5a8ddfce73c320c2a1429ec52eafd27138b7f1cbe341c9", size = 174062, upload-time = "2025-09-25T21:32:55.767Z" }, - { url = "https://files.pythonhosted.org/packages/f1/12/de94a39c2ef588c7e6455cfbe7343d3b2dc9d6b6b2f40c4c6565744c873d/pyyaml-6.0.3-cp314-cp314t-win_arm64.whl", hash = "sha256:ebc55a14a21cb14062aa4162f906cd962b28e2e9ea38f9b4391244cd8de4ae0b", size = 149341, upload-time = "2025-09-25T21:32:56.828Z" }, -] - -[[package]] -name = "regex" -version = "2026.1.15" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/0b/86/07d5056945f9ec4590b518171c4254a5925832eb727b56d3c38a7476f316/regex-2026.1.15.tar.gz", hash = "sha256:164759aa25575cbc0651bef59a0b18353e54300d79ace8084c818ad8ac72b7d5", size = 414811, upload-time = "2026-01-14T23:18:02.775Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d0/c9/0c80c96eab96948363d270143138d671d5731c3a692b417629bf3492a9d6/regex-2026.1.15-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:1ae6020fb311f68d753b7efa9d4b9a5d47a5d6466ea0d5e3b5a471a960ea6e4a", size = 488168, upload-time = "2026-01-14T23:14:16.129Z" }, - { url = "https://files.pythonhosted.org/packages/17/f0/271c92f5389a552494c429e5cc38d76d1322eb142fb5db3c8ccc47751468/regex-2026.1.15-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:eddf73f41225942c1f994914742afa53dc0d01a6e20fe14b878a1b1edc74151f", size = 290636, upload-time = "2026-01-14T23:14:17.715Z" }, - { url = "https://files.pythonhosted.org/packages/a0/f9/5f1fd077d106ca5655a0f9ff8f25a1ab55b92128b5713a91ed7134ff688e/regex-2026.1.15-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1e8cd52557603f5c66a548f69421310886b28b7066853089e1a71ee710e1cdc1", size = 288496, upload-time = "2026-01-14T23:14:19.326Z" }, - { url = "https://files.pythonhosted.org/packages/b5/e1/8f43b03a4968c748858ec77f746c286d81f896c2e437ccf050ebc5d3128c/regex-2026.1.15-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5170907244b14303edc5978f522f16c974f32d3aa92109fabc2af52411c9433b", size = 793503, upload-time = "2026-01-14T23:14:20.922Z" }, - { url = "https://files.pythonhosted.org/packages/8d/4e/a39a5e8edc5377a46a7c875c2f9a626ed3338cb3bb06931be461c3e1a34a/regex-2026.1.15-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:2748c1ec0663580b4510bd89941a31560b4b439a0b428b49472a3d9944d11cd8", size = 860535, upload-time = "2026-01-14T23:14:22.405Z" }, - { url = "https://files.pythonhosted.org/packages/dc/1c/9dce667a32a9477f7a2869c1c767dc00727284a9fa3ff5c09a5c6c03575e/regex-2026.1.15-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:2f2775843ca49360508d080eaa87f94fa248e2c946bbcd963bb3aae14f333413", size = 907225, upload-time = "2026-01-14T23:14:23.897Z" }, - { url = "https://files.pythonhosted.org/packages/a4/3c/87ca0a02736d16b6262921425e84b48984e77d8e4e572c9072ce96e66c30/regex-2026.1.15-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d9ea2604370efc9a174c1b5dcc81784fb040044232150f7f33756049edfc9026", size = 800526, upload-time = "2026-01-14T23:14:26.039Z" }, - { url = "https://files.pythonhosted.org/packages/4b/ff/647d5715aeea7c87bdcbd2f578f47b415f55c24e361e639fe8c0cc88878f/regex-2026.1.15-cp311-cp311-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:0dcd31594264029b57bf16f37fd7248a70b3b764ed9e0839a8f271b2d22c0785", size = 773446, upload-time = "2026-01-14T23:14:28.109Z" }, - { url = "https://files.pythonhosted.org/packages/af/89/bf22cac25cb4ba0fe6bff52ebedbb65b77a179052a9d6037136ae93f42f4/regex-2026.1.15-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:c08c1f3e34338256732bd6938747daa3c0d5b251e04b6e43b5813e94d503076e", size = 783051, upload-time = "2026-01-14T23:14:29.929Z" }, - { url = "https://files.pythonhosted.org/packages/1e/f4/6ed03e71dca6348a5188363a34f5e26ffd5db1404780288ff0d79513bce4/regex-2026.1.15-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:e43a55f378df1e7a4fa3547c88d9a5a9b7113f653a66821bcea4718fe6c58763", size = 854485, upload-time = "2026-01-14T23:14:31.366Z" }, - { url = "https://files.pythonhosted.org/packages/d9/9a/8e8560bd78caded8eb137e3e47612430a05b9a772caf60876435192d670a/regex-2026.1.15-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:f82110ab962a541737bd0ce87978d4c658f06e7591ba899192e2712a517badbb", size = 762195, upload-time = "2026-01-14T23:14:32.802Z" }, - { url = "https://files.pythonhosted.org/packages/38/6b/61fc710f9aa8dfcd764fe27d37edfaa023b1a23305a0d84fccd5adb346ea/regex-2026.1.15-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:27618391db7bdaf87ac6c92b31e8f0dfb83a9de0075855152b720140bda177a2", size = 845986, upload-time = "2026-01-14T23:14:34.898Z" }, - { url = "https://files.pythonhosted.org/packages/fd/2e/fbee4cb93f9d686901a7ca8d94285b80405e8c34fe4107f63ffcbfb56379/regex-2026.1.15-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:bfb0d6be01fbae8d6655c8ca21b3b72458606c4aec9bbc932db758d47aba6db1", size = 788992, upload-time = "2026-01-14T23:14:37.116Z" }, - { url = "https://files.pythonhosted.org/packages/ed/14/3076348f3f586de64b1ab75a3fbabdaab7684af7f308ad43be7ef1849e55/regex-2026.1.15-cp311-cp311-win32.whl", hash = "sha256:b10e42a6de0e32559a92f2f8dc908478cc0fa02838d7dbe764c44dca3fa13569", size = 265893, upload-time = "2026-01-14T23:14:38.426Z" }, - { url = "https://files.pythonhosted.org/packages/0f/19/772cf8b5fc803f5c89ba85d8b1870a1ca580dc482aa030383a9289c82e44/regex-2026.1.15-cp311-cp311-win_amd64.whl", hash = "sha256:e9bf3f0bbdb56633c07d7116ae60a576f846efdd86a8848f8d62b749e1209ca7", size = 277840, upload-time = "2026-01-14T23:14:39.785Z" }, - { url = "https://files.pythonhosted.org/packages/78/84/d05f61142709474da3c0853222d91086d3e1372bcdab516c6fd8d80f3297/regex-2026.1.15-cp311-cp311-win_arm64.whl", hash = "sha256:41aef6f953283291c4e4e6850607bd71502be67779586a61472beacb315c97ec", size = 270374, upload-time = "2026-01-14T23:14:41.592Z" }, - { url = "https://files.pythonhosted.org/packages/92/81/10d8cf43c807d0326efe874c1b79f22bfb0fb226027b0b19ebc26d301408/regex-2026.1.15-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:4c8fcc5793dde01641a35905d6731ee1548f02b956815f8f1cab89e515a5bdf1", size = 489398, upload-time = "2026-01-14T23:14:43.741Z" }, - { url = "https://files.pythonhosted.org/packages/90/b0/7c2a74e74ef2a7c32de724658a69a862880e3e4155cba992ba04d1c70400/regex-2026.1.15-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:bfd876041a956e6a90ad7cdb3f6a630c07d491280bfeed4544053cd434901681", size = 291339, upload-time = "2026-01-14T23:14:45.183Z" }, - { url = "https://files.pythonhosted.org/packages/19/4d/16d0773d0c818417f4cc20aa0da90064b966d22cd62a8c46765b5bd2d643/regex-2026.1.15-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:9250d087bc92b7d4899ccd5539a1b2334e44eee85d848c4c1aef8e221d3f8c8f", size = 289003, upload-time = "2026-01-14T23:14:47.25Z" }, - { url = "https://files.pythonhosted.org/packages/c6/e4/1fc4599450c9f0863d9406e944592d968b8d6dfd0d552a7d569e43bceada/regex-2026.1.15-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c8a154cf6537ebbc110e24dabe53095e714245c272da9c1be05734bdad4a61aa", size = 798656, upload-time = "2026-01-14T23:14:48.77Z" }, - { url = "https://files.pythonhosted.org/packages/b2/e6/59650d73a73fa8a60b3a590545bfcf1172b4384a7df2e7fe7b9aab4e2da9/regex-2026.1.15-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:8050ba2e3ea1d8731a549e83c18d2f0999fbc99a5f6bd06b4c91449f55291804", size = 864252, upload-time = "2026-01-14T23:14:50.528Z" }, - { url = "https://files.pythonhosted.org/packages/6e/ab/1d0f4d50a1638849a97d731364c9a80fa304fec46325e48330c170ee8e80/regex-2026.1.15-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:0bf065240704cb8951cc04972cf107063917022511273e0969bdb34fc173456c", size = 912268, upload-time = "2026-01-14T23:14:52.952Z" }, - { url = "https://files.pythonhosted.org/packages/dd/df/0d722c030c82faa1d331d1921ee268a4e8fb55ca8b9042c9341c352f17fa/regex-2026.1.15-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c32bef3e7aeee75746748643667668ef941d28b003bfc89994ecf09a10f7a1b5", size = 803589, upload-time = "2026-01-14T23:14:55.182Z" }, - { url = "https://files.pythonhosted.org/packages/66/23/33289beba7ccb8b805c6610a8913d0131f834928afc555b241caabd422a9/regex-2026.1.15-cp312-cp312-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:d5eaa4a4c5b1906bd0d2508d68927f15b81821f85092e06f1a34a4254b0e1af3", size = 775700, upload-time = "2026-01-14T23:14:56.707Z" }, - { url = "https://files.pythonhosted.org/packages/e7/65/bf3a42fa6897a0d3afa81acb25c42f4b71c274f698ceabd75523259f6688/regex-2026.1.15-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:86c1077a3cc60d453d4084d5b9649065f3bf1184e22992bd322e1f081d3117fb", size = 787928, upload-time = "2026-01-14T23:14:58.312Z" }, - { url = "https://files.pythonhosted.org/packages/f4/f5/13bf65864fc314f68cdd6d8ca94adcab064d4d39dbd0b10fef29a9da48fc/regex-2026.1.15-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:2b091aefc05c78d286657cd4db95f2e6313375ff65dcf085e42e4c04d9c8d410", size = 858607, upload-time = "2026-01-14T23:15:00.657Z" }, - { url = "https://files.pythonhosted.org/packages/a3/31/040e589834d7a439ee43fb0e1e902bc81bd58a5ba81acffe586bb3321d35/regex-2026.1.15-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:57e7d17f59f9ebfa9667e6e5a1c0127b96b87cb9cede8335482451ed00788ba4", size = 763729, upload-time = "2026-01-14T23:15:02.248Z" }, - { url = "https://files.pythonhosted.org/packages/9b/84/6921e8129687a427edf25a34a5594b588b6d88f491320b9de5b6339a4fcb/regex-2026.1.15-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:c6c4dcdfff2c08509faa15d36ba7e5ef5fcfab25f1e8f85a0c8f45bc3a30725d", size = 850697, upload-time = "2026-01-14T23:15:03.878Z" }, - { url = "https://files.pythonhosted.org/packages/8a/87/3d06143d4b128f4229158f2de5de6c8f2485170c7221e61bf381313314b2/regex-2026.1.15-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:cf8ff04c642716a7f2048713ddc6278c5fd41faa3b9cab12607c7abecd012c22", size = 789849, upload-time = "2026-01-14T23:15:06.102Z" }, - { url = "https://files.pythonhosted.org/packages/77/69/c50a63842b6bd48850ebc7ab22d46e7a2a32d824ad6c605b218441814639/regex-2026.1.15-cp312-cp312-win32.whl", hash = "sha256:82345326b1d8d56afbe41d881fdf62f1926d7264b2fc1537f99ae5da9aad7913", size = 266279, upload-time = "2026-01-14T23:15:07.678Z" }, - { url = "https://files.pythonhosted.org/packages/f2/36/39d0b29d087e2b11fd8191e15e81cce1b635fcc845297c67f11d0d19274d/regex-2026.1.15-cp312-cp312-win_amd64.whl", hash = "sha256:4def140aa6156bc64ee9912383d4038f3fdd18fee03a6f222abd4de6357ce42a", size = 277166, upload-time = "2026-01-14T23:15:09.257Z" }, - { url = "https://files.pythonhosted.org/packages/28/32/5b8e476a12262748851fa8ab1b0be540360692325975b094e594dfebbb52/regex-2026.1.15-cp312-cp312-win_arm64.whl", hash = "sha256:c6c565d9a6e1a8d783c1948937ffc377dd5771e83bd56de8317c450a954d2056", size = 270415, upload-time = "2026-01-14T23:15:10.743Z" }, - { url = "https://files.pythonhosted.org/packages/f8/2e/6870bb16e982669b674cce3ee9ff2d1d46ab80528ee6bcc20fb2292efb60/regex-2026.1.15-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:e69d0deeb977ffe7ed3d2e4439360089f9c3f217ada608f0f88ebd67afb6385e", size = 489164, upload-time = "2026-01-14T23:15:13.962Z" }, - { url = "https://files.pythonhosted.org/packages/dc/67/9774542e203849b0286badf67199970a44ebdb0cc5fb739f06e47ada72f8/regex-2026.1.15-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:3601ffb5375de85a16f407854d11cca8fe3f5febbe3ac78fb2866bb220c74d10", size = 291218, upload-time = "2026-01-14T23:15:15.647Z" }, - { url = "https://files.pythonhosted.org/packages/b2/87/b0cda79f22b8dee05f774922a214da109f9a4c0eca5da2c9d72d77ea062c/regex-2026.1.15-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:4c5ef43b5c2d4114eb8ea424bb8c9cec01d5d17f242af88b2448f5ee81caadbc", size = 288895, upload-time = "2026-01-14T23:15:17.788Z" }, - { url = "https://files.pythonhosted.org/packages/3b/6a/0041f0a2170d32be01ab981d6346c83a8934277d82c780d60b127331f264/regex-2026.1.15-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:968c14d4f03e10b2fd960f1d5168c1f0ac969381d3c1fcc973bc45fb06346599", size = 798680, upload-time = "2026-01-14T23:15:19.342Z" }, - { url = "https://files.pythonhosted.org/packages/58/de/30e1cfcdbe3e891324aa7568b7c968771f82190df5524fabc1138cb2d45a/regex-2026.1.15-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:56a5595d0f892f214609c9f76b41b7428bed439d98dc961efafdd1354d42baae", size = 864210, upload-time = "2026-01-14T23:15:22.005Z" }, - { url = "https://files.pythonhosted.org/packages/64/44/4db2f5c5ca0ccd40ff052ae7b1e9731352fcdad946c2b812285a7505ca75/regex-2026.1.15-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:0bf650f26087363434c4e560011f8e4e738f6f3e029b85d4904c50135b86cfa5", size = 912358, upload-time = "2026-01-14T23:15:24.569Z" }, - { url = "https://files.pythonhosted.org/packages/79/b6/e6a5665d43a7c42467138c8a2549be432bad22cbd206f5ec87162de74bd7/regex-2026.1.15-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:18388a62989c72ac24de75f1449d0fb0b04dfccd0a1a7c1c43af5eb503d890f6", size = 803583, upload-time = "2026-01-14T23:15:26.526Z" }, - { url = "https://files.pythonhosted.org/packages/e7/53/7cd478222169d85d74d7437e74750005e993f52f335f7c04ff7adfda3310/regex-2026.1.15-cp313-cp313-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:6d220a2517f5893f55daac983bfa9fe998a7dbcaee4f5d27a88500f8b7873788", size = 775782, upload-time = "2026-01-14T23:15:29.352Z" }, - { url = "https://files.pythonhosted.org/packages/ca/b5/75f9a9ee4b03a7c009fe60500fe550b45df94f0955ca29af16333ef557c5/regex-2026.1.15-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:c9c08c2fbc6120e70abff5d7f28ffb4d969e14294fb2143b4b5c7d20e46d1714", size = 787978, upload-time = "2026-01-14T23:15:31.295Z" }, - { url = "https://files.pythonhosted.org/packages/72/b3/79821c826245bbe9ccbb54f6eadb7879c722fd3e0248c17bfc90bf54e123/regex-2026.1.15-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:7ef7d5d4bd49ec7364315167a4134a015f61e8266c6d446fc116a9ac4456e10d", size = 858550, upload-time = "2026-01-14T23:15:33.558Z" }, - { url = "https://files.pythonhosted.org/packages/4a/85/2ab5f77a1c465745bfbfcb3ad63178a58337ae8d5274315e2cc623a822fa/regex-2026.1.15-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:6e42844ad64194fa08d5ccb75fe6a459b9b08e6d7296bd704460168d58a388f3", size = 763747, upload-time = "2026-01-14T23:15:35.206Z" }, - { url = "https://files.pythonhosted.org/packages/6d/84/c27df502d4bfe2873a3e3a7cf1bdb2b9cc10284d1a44797cf38bed790470/regex-2026.1.15-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:cfecdaa4b19f9ca534746eb3b55a5195d5c95b88cac32a205e981ec0a22b7d31", size = 850615, upload-time = "2026-01-14T23:15:37.523Z" }, - { url = "https://files.pythonhosted.org/packages/7d/b7/658a9782fb253680aa8ecb5ccbb51f69e088ed48142c46d9f0c99b46c575/regex-2026.1.15-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:08df9722d9b87834a3d701f3fca570b2be115654dbfd30179f30ab2f39d606d3", size = 789951, upload-time = "2026-01-14T23:15:39.582Z" }, - { url = "https://files.pythonhosted.org/packages/fc/2a/5928af114441e059f15b2f63e188bd00c6529b3051c974ade7444b85fcda/regex-2026.1.15-cp313-cp313-win32.whl", hash = "sha256:d426616dae0967ca225ab12c22274eb816558f2f99ccb4a1d52ca92e8baf180f", size = 266275, upload-time = "2026-01-14T23:15:42.108Z" }, - { url = "https://files.pythonhosted.org/packages/4f/16/5bfbb89e435897bff28cf0352a992ca719d9e55ebf8b629203c96b6ce4f7/regex-2026.1.15-cp313-cp313-win_amd64.whl", hash = "sha256:febd38857b09867d3ed3f4f1af7d241c5c50362e25ef43034995b77a50df494e", size = 277145, upload-time = "2026-01-14T23:15:44.244Z" }, - { url = "https://files.pythonhosted.org/packages/56/c1/a09ff7392ef4233296e821aec5f78c51be5e91ffde0d163059e50fd75835/regex-2026.1.15-cp313-cp313-win_arm64.whl", hash = "sha256:8e32f7896f83774f91499d239e24cebfadbc07639c1494bb7213983842348337", size = 270411, upload-time = "2026-01-14T23:15:45.858Z" }, - { url = "https://files.pythonhosted.org/packages/3c/38/0cfd5a78e5c6db00e6782fdae70458f89850ce95baa5e8694ab91d89744f/regex-2026.1.15-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:ec94c04149b6a7b8120f9f44565722c7ae31b7a6d2275569d2eefa76b83da3be", size = 492068, upload-time = "2026-01-14T23:15:47.616Z" }, - { url = "https://files.pythonhosted.org/packages/50/72/6c86acff16cb7c959c4355826bbf06aad670682d07c8f3998d9ef4fee7cd/regex-2026.1.15-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:40c86d8046915bb9aeb15d3f3f15b6fd500b8ea4485b30e1bbc799dab3fe29f8", size = 292756, upload-time = "2026-01-14T23:15:49.307Z" }, - { url = "https://files.pythonhosted.org/packages/4e/58/df7fb69eadfe76526ddfce28abdc0af09ffe65f20c2c90932e89d705153f/regex-2026.1.15-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:726ea4e727aba21643205edad8f2187ec682d3305d790f73b7a51c7587b64bdd", size = 291114, upload-time = "2026-01-14T23:15:51.484Z" }, - { url = "https://files.pythonhosted.org/packages/ed/6c/a4011cd1cf96b90d2cdc7e156f91efbd26531e822a7fbb82a43c1016678e/regex-2026.1.15-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:1cb740d044aff31898804e7bf1181cc72c03d11dfd19932b9911ffc19a79070a", size = 807524, upload-time = "2026-01-14T23:15:53.102Z" }, - { url = "https://files.pythonhosted.org/packages/1d/25/a53ffb73183f69c3e9f4355c4922b76d2840aee160af6af5fac229b6201d/regex-2026.1.15-cp313-cp313t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:05d75a668e9ea16f832390d22131fe1e8acc8389a694c8febc3e340b0f810b93", size = 873455, upload-time = "2026-01-14T23:15:54.956Z" }, - { url = "https://files.pythonhosted.org/packages/66/0b/8b47fc2e8f97d9b4a851736f3890a5f786443aa8901061c55f24c955f45b/regex-2026.1.15-cp313-cp313t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d991483606f3dbec93287b9f35596f41aa2e92b7c2ebbb935b63f409e243c9af", size = 915007, upload-time = "2026-01-14T23:15:57.041Z" }, - { url = "https://files.pythonhosted.org/packages/c2/fa/97de0d681e6d26fabe71968dbee06dd52819e9a22fdce5dac7256c31ed84/regex-2026.1.15-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:194312a14819d3e44628a44ed6fea6898fdbecb0550089d84c403475138d0a09", size = 812794, upload-time = "2026-01-14T23:15:58.916Z" }, - { url = "https://files.pythonhosted.org/packages/22/38/e752f94e860d429654aa2b1c51880bff8dfe8f084268258adf9151cf1f53/regex-2026.1.15-cp313-cp313t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:fe2fda4110a3d0bc163c2e0664be44657431440722c5c5315c65155cab92f9e5", size = 781159, upload-time = "2026-01-14T23:16:00.817Z" }, - { url = "https://files.pythonhosted.org/packages/e9/a7/d739ffaef33c378fc888302a018d7f81080393d96c476b058b8c64fd2b0d/regex-2026.1.15-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:124dc36c85d34ef2d9164da41a53c1c8c122cfb1f6e1ec377a1f27ee81deb794", size = 795558, upload-time = "2026-01-14T23:16:03.267Z" }, - { url = "https://files.pythonhosted.org/packages/3e/c4/542876f9a0ac576100fc73e9c75b779f5c31e3527576cfc9cb3009dcc58a/regex-2026.1.15-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:a1774cd1981cd212506a23a14dba7fdeaee259f5deba2df6229966d9911e767a", size = 868427, upload-time = "2026-01-14T23:16:05.646Z" }, - { url = "https://files.pythonhosted.org/packages/fc/0f/d5655bea5b22069e32ae85a947aa564912f23758e112cdb74212848a1a1b/regex-2026.1.15-cp313-cp313t-musllinux_1_2_riscv64.whl", hash = "sha256:b5f7d8d2867152cdb625e72a530d2ccb48a3d199159144cbdd63870882fb6f80", size = 769939, upload-time = "2026-01-14T23:16:07.542Z" }, - { url = "https://files.pythonhosted.org/packages/20/06/7e18a4fa9d326daeda46d471a44ef94201c46eaa26dbbb780b5d92cbfdda/regex-2026.1.15-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:492534a0ab925d1db998defc3c302dae3616a2fc3fe2e08db1472348f096ddf2", size = 854753, upload-time = "2026-01-14T23:16:10.395Z" }, - { url = "https://files.pythonhosted.org/packages/3b/67/dc8946ef3965e166f558ef3b47f492bc364e96a265eb4a2bb3ca765c8e46/regex-2026.1.15-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:c661fc820cfb33e166bf2450d3dadbda47c8d8981898adb9b6fe24e5e582ba60", size = 799559, upload-time = "2026-01-14T23:16:12.347Z" }, - { url = "https://files.pythonhosted.org/packages/a5/61/1bba81ff6d50c86c65d9fd84ce9699dd106438ee4cdb105bf60374ee8412/regex-2026.1.15-cp313-cp313t-win32.whl", hash = "sha256:99ad739c3686085e614bf77a508e26954ff1b8f14da0e3765ff7abbf7799f952", size = 268879, upload-time = "2026-01-14T23:16:14.049Z" }, - { url = "https://files.pythonhosted.org/packages/e9/5e/cef7d4c5fb0ea3ac5c775fd37db5747f7378b29526cc83f572198924ff47/regex-2026.1.15-cp313-cp313t-win_amd64.whl", hash = "sha256:32655d17905e7ff8ba5c764c43cb124e34a9245e45b83c22e81041e1071aee10", size = 280317, upload-time = "2026-01-14T23:16:15.718Z" }, - { url = "https://files.pythonhosted.org/packages/b4/52/4317f7a5988544e34ab57b4bde0f04944c4786128c933fb09825924d3e82/regex-2026.1.15-cp313-cp313t-win_arm64.whl", hash = "sha256:b2a13dd6a95e95a489ca242319d18fc02e07ceb28fa9ad146385194d95b3c829", size = 271551, upload-time = "2026-01-14T23:16:17.533Z" }, - { url = "https://files.pythonhosted.org/packages/52/0a/47fa888ec7cbbc7d62c5f2a6a888878e76169170ead271a35239edd8f0e8/regex-2026.1.15-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:d920392a6b1f353f4aa54328c867fec3320fa50657e25f64abf17af054fc97ac", size = 489170, upload-time = "2026-01-14T23:16:19.835Z" }, - { url = "https://files.pythonhosted.org/packages/ac/c4/d000e9b7296c15737c9301708e9e7fbdea009f8e93541b6b43bdb8219646/regex-2026.1.15-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:b5a28980a926fa810dbbed059547b02783952e2efd9c636412345232ddb87ff6", size = 291146, upload-time = "2026-01-14T23:16:21.541Z" }, - { url = "https://files.pythonhosted.org/packages/f9/b6/921cc61982e538682bdf3bdf5b2c6ab6b34368da1f8e98a6c1ddc503c9cf/regex-2026.1.15-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:621f73a07595d83f28952d7bd1e91e9d1ed7625fb7af0064d3516674ec93a2a2", size = 288986, upload-time = "2026-01-14T23:16:23.381Z" }, - { url = "https://files.pythonhosted.org/packages/ca/33/eb7383dde0bbc93f4fb9d03453aab97e18ad4024ac7e26cef8d1f0a2cff0/regex-2026.1.15-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:3d7d92495f47567a9b1669c51fc8d6d809821849063d168121ef801bbc213846", size = 799098, upload-time = "2026-01-14T23:16:25.088Z" }, - { url = "https://files.pythonhosted.org/packages/27/56/b664dccae898fc8d8b4c23accd853f723bde0f026c747b6f6262b688029c/regex-2026.1.15-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:8dd16fba2758db7a3780a051f245539c4451ca20910f5a5e6ea1c08d06d4a76b", size = 864980, upload-time = "2026-01-14T23:16:27.297Z" }, - { url = "https://files.pythonhosted.org/packages/16/40/0999e064a170eddd237bae9ccfcd8f28b3aa98a38bf727a086425542a4fc/regex-2026.1.15-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:1e1808471fbe44c1a63e5f577a1d5f02fe5d66031dcbdf12f093ffc1305a858e", size = 911607, upload-time = "2026-01-14T23:16:29.235Z" }, - { url = "https://files.pythonhosted.org/packages/07/78/c77f644b68ab054e5a674fb4da40ff7bffb2c88df58afa82dbf86573092d/regex-2026.1.15-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0751a26ad39d4f2ade8fe16c59b2bf5cb19eb3d2cd543e709e583d559bd9efde", size = 803358, upload-time = "2026-01-14T23:16:31.369Z" }, - { url = "https://files.pythonhosted.org/packages/27/31/d4292ea8566eaa551fafc07797961c5963cf5235c797cc2ae19b85dfd04d/regex-2026.1.15-cp314-cp314-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:0f0c7684c7f9ca241344ff95a1de964f257a5251968484270e91c25a755532c5", size = 775833, upload-time = "2026-01-14T23:16:33.141Z" }, - { url = "https://files.pythonhosted.org/packages/ce/b2/cff3bf2fea4133aa6fb0d1e370b37544d18c8350a2fa118c7e11d1db0e14/regex-2026.1.15-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:74f45d170a21df41508cb67165456538425185baaf686281fa210d7e729abc34", size = 788045, upload-time = "2026-01-14T23:16:35.005Z" }, - { url = "https://files.pythonhosted.org/packages/8d/99/2cb9b69045372ec877b6f5124bda4eb4253bc58b8fe5848c973f752bc52c/regex-2026.1.15-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:f1862739a1ffb50615c0fde6bae6569b5efbe08d98e59ce009f68a336f64da75", size = 859374, upload-time = "2026-01-14T23:16:36.919Z" }, - { url = "https://files.pythonhosted.org/packages/09/16/710b0a5abe8e077b1729a562d2f297224ad079f3a66dce46844c193416c8/regex-2026.1.15-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:453078802f1b9e2b7303fb79222c054cb18e76f7bdc220f7530fdc85d319f99e", size = 763940, upload-time = "2026-01-14T23:16:38.685Z" }, - { url = "https://files.pythonhosted.org/packages/dd/d1/7585c8e744e40eb3d32f119191969b91de04c073fca98ec14299041f6e7e/regex-2026.1.15-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:a30a68e89e5a218b8b23a52292924c1f4b245cb0c68d1cce9aec9bbda6e2c160", size = 850112, upload-time = "2026-01-14T23:16:40.646Z" }, - { url = "https://files.pythonhosted.org/packages/af/d6/43e1dd85df86c49a347aa57c1f69d12c652c7b60e37ec162e3096194a278/regex-2026.1.15-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:9479cae874c81bf610d72b85bb681a94c95722c127b55445285fb0e2c82db8e1", size = 789586, upload-time = "2026-01-14T23:16:42.799Z" }, - { url = "https://files.pythonhosted.org/packages/93/38/77142422f631e013f316aaae83234c629555729a9fbc952b8a63ac91462a/regex-2026.1.15-cp314-cp314-win32.whl", hash = "sha256:d639a750223132afbfb8f429c60d9d318aeba03281a5f1ab49f877456448dcf1", size = 271691, upload-time = "2026-01-14T23:16:44.671Z" }, - { url = "https://files.pythonhosted.org/packages/4a/a9/ab16b4649524ca9e05213c1cdbb7faa85cc2aa90a0230d2f796cbaf22736/regex-2026.1.15-cp314-cp314-win_amd64.whl", hash = "sha256:4161d87f85fa831e31469bfd82c186923070fc970b9de75339b68f0c75b51903", size = 280422, upload-time = "2026-01-14T23:16:46.607Z" }, - { url = "https://files.pythonhosted.org/packages/be/2a/20fd057bf3521cb4791f69f869635f73e0aaf2b9ad2d260f728144f9047c/regex-2026.1.15-cp314-cp314-win_arm64.whl", hash = "sha256:91c5036ebb62663a6b3999bdd2e559fd8456d17e2b485bf509784cd31a8b1705", size = 273467, upload-time = "2026-01-14T23:16:48.967Z" }, - { url = "https://files.pythonhosted.org/packages/ad/77/0b1e81857060b92b9cad239104c46507dd481b3ff1fa79f8e7f865aae38a/regex-2026.1.15-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:ee6854c9000a10938c79238de2379bea30c82e4925a371711af45387df35cab8", size = 492073, upload-time = "2026-01-14T23:16:51.154Z" }, - { url = "https://files.pythonhosted.org/packages/70/f3/f8302b0c208b22c1e4f423147e1913fd475ddd6230565b299925353de644/regex-2026.1.15-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:2c2b80399a422348ce5de4fe40c418d6299a0fa2803dd61dc0b1a2f28e280fcf", size = 292757, upload-time = "2026-01-14T23:16:53.08Z" }, - { url = "https://files.pythonhosted.org/packages/bf/f0/ef55de2460f3b4a6da9d9e7daacd0cb79d4ef75c64a2af316e68447f0df0/regex-2026.1.15-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:dca3582bca82596609959ac39e12b7dad98385b4fefccb1151b937383cec547d", size = 291122, upload-time = "2026-01-14T23:16:55.383Z" }, - { url = "https://files.pythonhosted.org/packages/cf/55/bb8ccbacabbc3a11d863ee62a9f18b160a83084ea95cdfc5d207bfc3dd75/regex-2026.1.15-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:ef71d476caa6692eea743ae5ea23cde3260677f70122c4d258ca952e5c2d4e84", size = 807761, upload-time = "2026-01-14T23:16:57.251Z" }, - { url = "https://files.pythonhosted.org/packages/8f/84/f75d937f17f81e55679a0509e86176e29caa7298c38bd1db7ce9c0bf6075/regex-2026.1.15-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:c243da3436354f4af6c3058a3f81a97d47ea52c9bd874b52fd30274853a1d5df", size = 873538, upload-time = "2026-01-14T23:16:59.349Z" }, - { url = "https://files.pythonhosted.org/packages/b8/d9/0da86327df70349aa8d86390da91171bd3ca4f0e7c1d1d453a9c10344da3/regex-2026.1.15-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:8355ad842a7c7e9e5e55653eade3b7d1885ba86f124dd8ab1f722f9be6627434", size = 915066, upload-time = "2026-01-14T23:17:01.607Z" }, - { url = "https://files.pythonhosted.org/packages/2a/5e/f660fb23fc77baa2a61aa1f1fe3a4eea2bbb8a286ddec148030672e18834/regex-2026.1.15-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:f192a831d9575271a22d804ff1a5355355723f94f31d9eef25f0d45a152fdc1a", size = 812938, upload-time = "2026-01-14T23:17:04.366Z" }, - { url = "https://files.pythonhosted.org/packages/69/33/a47a29bfecebbbfd1e5cd3f26b28020a97e4820f1c5148e66e3b7d4b4992/regex-2026.1.15-cp314-cp314t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:166551807ec20d47ceaeec380081f843e88c8949780cd42c40f18d16168bed10", size = 781314, upload-time = "2026-01-14T23:17:06.378Z" }, - { url = "https://files.pythonhosted.org/packages/65/ec/7ec2bbfd4c3f4e494a24dec4c6943a668e2030426b1b8b949a6462d2c17b/regex-2026.1.15-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:f9ca1cbdc0fbfe5e6e6f8221ef2309988db5bcede52443aeaee9a4ad555e0dac", size = 795652, upload-time = "2026-01-14T23:17:08.521Z" }, - { url = "https://files.pythonhosted.org/packages/46/79/a5d8651ae131fe27d7c521ad300aa7f1c7be1dbeee4d446498af5411b8a9/regex-2026.1.15-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:b30bcbd1e1221783c721483953d9e4f3ab9c5d165aa709693d3f3946747b1aea", size = 868550, upload-time = "2026-01-14T23:17:10.573Z" }, - { url = "https://files.pythonhosted.org/packages/06/b7/25635d2809664b79f183070786a5552dd4e627e5aedb0065f4e3cf8ee37d/regex-2026.1.15-cp314-cp314t-musllinux_1_2_riscv64.whl", hash = "sha256:2a8d7b50c34578d0d3bf7ad58cde9652b7d683691876f83aedc002862a35dc5e", size = 769981, upload-time = "2026-01-14T23:17:12.871Z" }, - { url = "https://files.pythonhosted.org/packages/16/8b/fc3fcbb2393dcfa4a6c5ffad92dc498e842df4581ea9d14309fcd3c55fb9/regex-2026.1.15-cp314-cp314t-musllinux_1_2_s390x.whl", hash = "sha256:9d787e3310c6a6425eb346be4ff2ccf6eece63017916fd77fe8328c57be83521", size = 854780, upload-time = "2026-01-14T23:17:14.837Z" }, - { url = "https://files.pythonhosted.org/packages/d0/38/dde117c76c624713c8a2842530be9c93ca8b606c0f6102d86e8cd1ce8bea/regex-2026.1.15-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:619843841e220adca114118533a574a9cd183ed8a28b85627d2844c500a2b0db", size = 799778, upload-time = "2026-01-14T23:17:17.369Z" }, - { url = "https://files.pythonhosted.org/packages/e3/0d/3a6cfa9ae99606afb612d8fb7a66b245a9d5ff0f29bb347c8a30b6ad561b/regex-2026.1.15-cp314-cp314t-win32.whl", hash = "sha256:e90b8db97f6f2c97eb045b51a6b2c5ed69cedd8392459e0642d4199b94fabd7e", size = 274667, upload-time = "2026-01-14T23:17:19.301Z" }, - { url = "https://files.pythonhosted.org/packages/5b/b2/297293bb0742fd06b8d8e2572db41a855cdf1cae0bf009b1cb74fe07e196/regex-2026.1.15-cp314-cp314t-win_amd64.whl", hash = "sha256:5ef19071f4ac9f0834793af85bd04a920b4407715624e40cb7a0631a11137cdf", size = 284386, upload-time = "2026-01-14T23:17:21.231Z" }, - { url = "https://files.pythonhosted.org/packages/95/e4/a3b9480c78cf8ee86626cb06f8d931d74d775897d44201ccb813097ae697/regex-2026.1.15-cp314-cp314t-win_arm64.whl", hash = "sha256:ca89c5e596fc05b015f27561b3793dc2fa0917ea0d7507eebb448efd35274a70", size = 274837, upload-time = "2026-01-14T23:17:23.146Z" }, -] - -[[package]] -name = "requests" -version = "2.32.5" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "certifi" }, - { name = "charset-normalizer" }, - { name = "idna" }, - { name = "urllib3" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/c9/74/b3ff8e6c8446842c3f5c837e9c3dfcfe2018ea6ecef224c710c85ef728f4/requests-2.32.5.tar.gz", hash = "sha256:dbba0bac56e100853db0ea71b82b4dfd5fe2bf6d3754a8893c3af500cec7d7cf", size = 134517, upload-time = "2025-08-18T20:46:02.573Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl", hash = "sha256:2462f94637a34fd532264295e186976db0f5d453d1cdd31473c85a6a161affb6", size = 64738, upload-time = "2025-08-18T20:46:00.542Z" }, -] - -[[package]] -name = "requests-toolbelt" -version = "1.0.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "requests" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/f3/61/d7545dafb7ac2230c70d38d31cbfe4cc64f7144dc41f6e4e4b78ecd9f5bb/requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6", size = 206888, upload-time = "2023-05-01T04:11:33.229Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/3f/51/d4db610ef29373b879047326cbf6fa98b6c1969d6f6dc423279de2b1be2c/requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06", size = 54481, upload-time = "2023-05-01T04:11:28.427Z" }, -] - -[[package]] -name = "smmap" -version = "5.0.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/44/cd/a040c4b3119bbe532e5b0732286f805445375489fceaec1f48306068ee3b/smmap-5.0.2.tar.gz", hash = "sha256:26ea65a03958fa0c8a1c7e8c7a58fdc77221b8910f6be2131affade476898ad5", size = 22329, upload-time = "2025-01-02T07:14:40.909Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/04/be/d09147ad1ec7934636ad912901c5fd7667e1c858e19d355237db0d0cd5e4/smmap-5.0.2-py3-none-any.whl", hash = "sha256:b30115f0def7d7531d22a0fb6502488d879e75b260a9db4d0819cfb25403af5e", size = 24303, upload-time = "2025-01-02T07:14:38.724Z" }, -] - -[[package]] -name = "sniffio" -version = "1.3.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a2/87/a6771e1546d97e7e041b6ae58d80074f81b7d5121207425c964ddf5cfdbd/sniffio-1.3.1.tar.gz", hash = "sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc", size = 20372, upload-time = "2024-02-25T23:20:04.057Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e9/44/75a9c9421471a6c4805dbf2356f7c181a29c1879239abab1ea2cc8f38b40/sniffio-1.3.1-py3-none-any.whl", hash = "sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2", size = 10235, upload-time = "2024-02-25T23:20:01.196Z" }, -] - -[[package]] -name = "sseclient-py" -version = "1.9.0" -source = { registry = "https://pypi.org/simple" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/4d/2e/59920f7d66b7f9932a3d83dd0ec53fab001be1e058bf582606fe414a5198/sseclient_py-1.9.0-py3-none-any.whl", hash = "sha256:340062b1587fc2880892811e2ab5b176d98ef3eee98b3672ff3a3ba1e8ed0f6f", size = 8351, upload-time = "2026-01-02T23:39:30.995Z" }, -] - -[[package]] -name = "tenacity" -version = "9.1.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/0a/d4/2b0cd0fe285e14b36db076e78c93766ff1d529d70408bd1d2a5a84f1d929/tenacity-9.1.2.tar.gz", hash = "sha256:1169d376c297e7de388d18b4481760d478b0e99a777cad3a9c86e556f4b697cb", size = 48036, upload-time = "2025-04-02T08:25:09.966Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/e5/30/643397144bfbfec6f6ef821f36f33e57d35946c44a2352d3c9f0ae847619/tenacity-9.1.2-py3-none-any.whl", hash = "sha256:f77bf36710d8b73a50b2dd155c97b870017ad21afe6ab300326b0371b3b05138", size = 28248, upload-time = "2025-04-02T08:25:07.678Z" }, -] - -[[package]] -name = "text-unidecode" -version = "1.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ab/e2/e9a00f0ccb71718418230718b3d900e71a5d16e701a3dae079a21e9cd8f8/text-unidecode-1.3.tar.gz", hash = "sha256:bad6603bb14d279193107714b288be206cac565dfa49aa5b105294dd5c4aab93", size = 76885, upload-time = "2019-08-30T21:36:45.405Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a6/a5/c0b6468d3824fe3fde30dbb5e1f687b291608f9473681bbf7dabbf5a87d7/text_unidecode-1.3-py2.py3-none-any.whl", hash = "sha256:1311f10e8b895935241623731c2ba64f4c455287888b18189350b67134a822e8", size = 78154, upload-time = "2019-08-30T21:37:03.543Z" }, -] - -[[package]] -name = "tiktoken" -version = "0.12.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "regex" }, - { name = "requests" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/7d/ab/4d017d0f76ec3171d469d80fc03dfbb4e48a4bcaddaa831b31d526f05edc/tiktoken-0.12.0.tar.gz", hash = "sha256:b18ba7ee2b093863978fcb14f74b3707cdc8d4d4d3836853ce7ec60772139931", size = 37806, upload-time = "2025-10-06T20:22:45.419Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/de/46/21ea696b21f1d6d1efec8639c204bdf20fde8bafb351e1355c72c5d7de52/tiktoken-0.12.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:6e227c7f96925003487c33b1b32265fad2fbcec2b7cf4817afb76d416f40f6bb", size = 1051565, upload-time = "2025-10-06T20:21:44.566Z" }, - { url = "https://files.pythonhosted.org/packages/c9/d9/35c5d2d9e22bb2a5f74ba48266fb56c63d76ae6f66e02feb628671c0283e/tiktoken-0.12.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c06cf0fcc24c2cb2adb5e185c7082a82cba29c17575e828518c2f11a01f445aa", size = 995284, upload-time = "2025-10-06T20:21:45.622Z" }, - { url = "https://files.pythonhosted.org/packages/01/84/961106c37b8e49b9fdcf33fe007bb3a8fdcc380c528b20cc7fbba80578b8/tiktoken-0.12.0-cp311-cp311-manylinux_2_28_aarch64.whl", hash = "sha256:f18f249b041851954217e9fd8e5c00b024ab2315ffda5ed77665a05fa91f42dc", size = 1129201, upload-time = "2025-10-06T20:21:47.074Z" }, - { url = "https://files.pythonhosted.org/packages/6a/d0/3d9275198e067f8b65076a68894bb52fd253875f3644f0a321a720277b8a/tiktoken-0.12.0-cp311-cp311-manylinux_2_28_x86_64.whl", hash = "sha256:47a5bc270b8c3db00bb46ece01ef34ad050e364b51d406b6f9730b64ac28eded", size = 1152444, upload-time = "2025-10-06T20:21:48.139Z" }, - { url = "https://files.pythonhosted.org/packages/78/db/a58e09687c1698a7c592e1038e01c206569b86a0377828d51635561f8ebf/tiktoken-0.12.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:508fa71810c0efdcd1b898fda574889ee62852989f7c1667414736bcb2b9a4bd", size = 1195080, upload-time = "2025-10-06T20:21:49.246Z" }, - { url = "https://files.pythonhosted.org/packages/9e/1b/a9e4d2bf91d515c0f74afc526fd773a812232dd6cda33ebea7f531202325/tiktoken-0.12.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:a1af81a6c44f008cba48494089dd98cccb8b313f55e961a52f5b222d1e507967", size = 1255240, upload-time = "2025-10-06T20:21:50.274Z" }, - { url = "https://files.pythonhosted.org/packages/9d/15/963819345f1b1fb0809070a79e9dd96938d4ca41297367d471733e79c76c/tiktoken-0.12.0-cp311-cp311-win_amd64.whl", hash = "sha256:3e68e3e593637b53e56f7237be560f7a394451cb8c11079755e80ae64b9e6def", size = 879422, upload-time = "2025-10-06T20:21:51.734Z" }, - { url = "https://files.pythonhosted.org/packages/a4/85/be65d39d6b647c79800fd9d29241d081d4eeb06271f383bb87200d74cf76/tiktoken-0.12.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:b97f74aca0d78a1ff21b8cd9e9925714c15a9236d6ceacf5c7327c117e6e21e8", size = 1050728, upload-time = "2025-10-06T20:21:52.756Z" }, - { url = "https://files.pythonhosted.org/packages/4a/42/6573e9129bc55c9bf7300b3a35bef2c6b9117018acca0dc760ac2d93dffe/tiktoken-0.12.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:2b90f5ad190a4bb7c3eb30c5fa32e1e182ca1ca79f05e49b448438c3e225a49b", size = 994049, upload-time = "2025-10-06T20:21:53.782Z" }, - { url = "https://files.pythonhosted.org/packages/66/c5/ed88504d2f4a5fd6856990b230b56d85a777feab84e6129af0822f5d0f70/tiktoken-0.12.0-cp312-cp312-manylinux_2_28_aarch64.whl", hash = "sha256:65b26c7a780e2139e73acc193e5c63ac754021f160df919add909c1492c0fb37", size = 1129008, upload-time = "2025-10-06T20:21:54.832Z" }, - { url = "https://files.pythonhosted.org/packages/f4/90/3dae6cc5436137ebd38944d396b5849e167896fc2073da643a49f372dc4f/tiktoken-0.12.0-cp312-cp312-manylinux_2_28_x86_64.whl", hash = "sha256:edde1ec917dfd21c1f2f8046b86348b0f54a2c0547f68149d8600859598769ad", size = 1152665, upload-time = "2025-10-06T20:21:56.129Z" }, - { url = "https://files.pythonhosted.org/packages/a3/fe/26df24ce53ffde419a42f5f53d755b995c9318908288c17ec3f3448313a3/tiktoken-0.12.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:35a2f8ddd3824608b3d650a000c1ef71f730d0c56486845705a8248da00f9fe5", size = 1194230, upload-time = "2025-10-06T20:21:57.546Z" }, - { url = "https://files.pythonhosted.org/packages/20/cc/b064cae1a0e9fac84b0d2c46b89f4e57051a5f41324e385d10225a984c24/tiktoken-0.12.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:83d16643edb7fa2c99eff2ab7733508aae1eebb03d5dfc46f5565862810f24e3", size = 1254688, upload-time = "2025-10-06T20:21:58.619Z" }, - { url = "https://files.pythonhosted.org/packages/81/10/b8523105c590c5b8349f2587e2fdfe51a69544bd5a76295fc20f2374f470/tiktoken-0.12.0-cp312-cp312-win_amd64.whl", hash = "sha256:ffc5288f34a8bc02e1ea7047b8d041104791d2ddbf42d1e5fa07822cbffe16bd", size = 878694, upload-time = "2025-10-06T20:21:59.876Z" }, - { url = "https://files.pythonhosted.org/packages/00/61/441588ee21e6b5cdf59d6870f86beb9789e532ee9718c251b391b70c68d6/tiktoken-0.12.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:775c2c55de2310cc1bc9a3ad8826761cbdc87770e586fd7b6da7d4589e13dab3", size = 1050802, upload-time = "2025-10-06T20:22:00.96Z" }, - { url = "https://files.pythonhosted.org/packages/1f/05/dcf94486d5c5c8d34496abe271ac76c5b785507c8eae71b3708f1ad9b45a/tiktoken-0.12.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a01b12f69052fbe4b080a2cfb867c4de12c704b56178edf1d1d7b273561db160", size = 993995, upload-time = "2025-10-06T20:22:02.788Z" }, - { url = "https://files.pythonhosted.org/packages/a0/70/5163fe5359b943f8db9946b62f19be2305de8c3d78a16f629d4165e2f40e/tiktoken-0.12.0-cp313-cp313-manylinux_2_28_aarch64.whl", hash = "sha256:01d99484dc93b129cd0964f9d34eee953f2737301f18b3c7257bf368d7615baa", size = 1128948, upload-time = "2025-10-06T20:22:03.814Z" }, - { url = "https://files.pythonhosted.org/packages/0c/da/c028aa0babf77315e1cef357d4d768800c5f8a6de04d0eac0f377cb619fa/tiktoken-0.12.0-cp313-cp313-manylinux_2_28_x86_64.whl", hash = "sha256:4a1a4fcd021f022bfc81904a911d3df0f6543b9e7627b51411da75ff2fe7a1be", size = 1151986, upload-time = "2025-10-06T20:22:05.173Z" }, - { url = "https://files.pythonhosted.org/packages/a0/5a/886b108b766aa53e295f7216b509be95eb7d60b166049ce2c58416b25f2a/tiktoken-0.12.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:981a81e39812d57031efdc9ec59fa32b2a5a5524d20d4776574c4b4bd2e9014a", size = 1194222, upload-time = "2025-10-06T20:22:06.265Z" }, - { url = "https://files.pythonhosted.org/packages/f4/f8/4db272048397636ac7a078d22773dd2795b1becee7bc4922fe6207288d57/tiktoken-0.12.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:9baf52f84a3f42eef3ff4e754a0db79a13a27921b457ca9832cf944c6be4f8f3", size = 1255097, upload-time = "2025-10-06T20:22:07.403Z" }, - { url = "https://files.pythonhosted.org/packages/8e/32/45d02e2e0ea2be3a9ed22afc47d93741247e75018aac967b713b2941f8ea/tiktoken-0.12.0-cp313-cp313-win_amd64.whl", hash = "sha256:b8a0cd0c789a61f31bf44851defbd609e8dd1e2c8589c614cc1060940ef1f697", size = 879117, upload-time = "2025-10-06T20:22:08.418Z" }, - { url = "https://files.pythonhosted.org/packages/ce/76/994fc868f88e016e6d05b0da5ac24582a14c47893f4474c3e9744283f1d5/tiktoken-0.12.0-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:d5f89ea5680066b68bcb797ae85219c72916c922ef0fcdd3480c7d2315ffff16", size = 1050309, upload-time = "2025-10-06T20:22:10.939Z" }, - { url = "https://files.pythonhosted.org/packages/f6/b8/57ef1456504c43a849821920d582a738a461b76a047f352f18c0b26c6516/tiktoken-0.12.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:b4e7ed1c6a7a8a60a3230965bdedba8cc58f68926b835e519341413370e0399a", size = 993712, upload-time = "2025-10-06T20:22:12.115Z" }, - { url = "https://files.pythonhosted.org/packages/72/90/13da56f664286ffbae9dbcfadcc625439142675845baa62715e49b87b68b/tiktoken-0.12.0-cp313-cp313t-manylinux_2_28_aarch64.whl", hash = "sha256:fc530a28591a2d74bce821d10b418b26a094bf33839e69042a6e86ddb7a7fb27", size = 1128725, upload-time = "2025-10-06T20:22:13.541Z" }, - { url = "https://files.pythonhosted.org/packages/05/df/4f80030d44682235bdaecd7346c90f67ae87ec8f3df4a3442cb53834f7e4/tiktoken-0.12.0-cp313-cp313t-manylinux_2_28_x86_64.whl", hash = "sha256:06a9f4f49884139013b138920a4c393aa6556b2f8f536345f11819389c703ebb", size = 1151875, upload-time = "2025-10-06T20:22:14.559Z" }, - { url = "https://files.pythonhosted.org/packages/22/1f/ae535223a8c4ef4c0c1192e3f9b82da660be9eb66b9279e95c99288e9dab/tiktoken-0.12.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:04f0e6a985d95913cabc96a741c5ffec525a2c72e9df086ff17ebe35985c800e", size = 1194451, upload-time = "2025-10-06T20:22:15.545Z" }, - { url = "https://files.pythonhosted.org/packages/78/a7/f8ead382fce0243cb625c4f266e66c27f65ae65ee9e77f59ea1653b6d730/tiktoken-0.12.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:0ee8f9ae00c41770b5f9b0bb1235474768884ae157de3beb5439ca0fd70f3e25", size = 1253794, upload-time = "2025-10-06T20:22:16.624Z" }, - { url = "https://files.pythonhosted.org/packages/93/e0/6cc82a562bc6365785a3ff0af27a2a092d57c47d7a81d9e2295d8c36f011/tiktoken-0.12.0-cp313-cp313t-win_amd64.whl", hash = "sha256:dc2dd125a62cb2b3d858484d6c614d136b5b848976794edfb63688d539b8b93f", size = 878777, upload-time = "2025-10-06T20:22:18.036Z" }, - { url = "https://files.pythonhosted.org/packages/72/05/3abc1db5d2c9aadc4d2c76fa5640134e475e58d9fbb82b5c535dc0de9b01/tiktoken-0.12.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:a90388128df3b3abeb2bfd1895b0681412a8d7dc644142519e6f0a97c2111646", size = 1050188, upload-time = "2025-10-06T20:22:19.563Z" }, - { url = "https://files.pythonhosted.org/packages/e3/7b/50c2f060412202d6c95f32b20755c7a6273543b125c0985d6fa9465105af/tiktoken-0.12.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:da900aa0ad52247d8794e307d6446bd3cdea8e192769b56276695d34d2c9aa88", size = 993978, upload-time = "2025-10-06T20:22:20.702Z" }, - { url = "https://files.pythonhosted.org/packages/14/27/bf795595a2b897e271771cd31cb847d479073497344c637966bdf2853da1/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_aarch64.whl", hash = "sha256:285ba9d73ea0d6171e7f9407039a290ca77efcdb026be7769dccc01d2c8d7fff", size = 1129271, upload-time = "2025-10-06T20:22:22.06Z" }, - { url = "https://files.pythonhosted.org/packages/f5/de/9341a6d7a8f1b448573bbf3425fa57669ac58258a667eb48a25dfe916d70/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_x86_64.whl", hash = "sha256:d186a5c60c6a0213f04a7a802264083dea1bbde92a2d4c7069e1a56630aef830", size = 1151216, upload-time = "2025-10-06T20:22:23.085Z" }, - { url = "https://files.pythonhosted.org/packages/75/0d/881866647b8d1be4d67cb24e50d0c26f9f807f994aa1510cb9ba2fe5f612/tiktoken-0.12.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:604831189bd05480f2b885ecd2d1986dc7686f609de48208ebbbddeea071fc0b", size = 1194860, upload-time = "2025-10-06T20:22:24.602Z" }, - { url = "https://files.pythonhosted.org/packages/b3/1e/b651ec3059474dab649b8d5b69f5c65cd8fcd8918568c1935bd4136c9392/tiktoken-0.12.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:8f317e8530bb3a222547b85a58583238c8f74fd7a7408305f9f63246d1a0958b", size = 1254567, upload-time = "2025-10-06T20:22:25.671Z" }, - { url = "https://files.pythonhosted.org/packages/80/57/ce64fd16ac390fafde001268c364d559447ba09b509181b2808622420eec/tiktoken-0.12.0-cp314-cp314-win_amd64.whl", hash = "sha256:399c3dd672a6406719d84442299a490420b458c44d3ae65516302a99675888f3", size = 921067, upload-time = "2025-10-06T20:22:26.753Z" }, - { url = "https://files.pythonhosted.org/packages/ac/a4/72eed53e8976a099539cdd5eb36f241987212c29629d0a52c305173e0a68/tiktoken-0.12.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:c2c714c72bc00a38ca969dae79e8266ddec999c7ceccd603cc4f0d04ccd76365", size = 1050473, upload-time = "2025-10-06T20:22:27.775Z" }, - { url = "https://files.pythonhosted.org/packages/e6/d7/0110b8f54c008466b19672c615f2168896b83706a6611ba6e47313dbc6e9/tiktoken-0.12.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:cbb9a3ba275165a2cb0f9a83f5d7025afe6b9d0ab01a22b50f0e74fee2ad253e", size = 993855, upload-time = "2025-10-06T20:22:28.799Z" }, - { url = "https://files.pythonhosted.org/packages/5f/77/4f268c41a3957c418b084dd576ea2fad2e95da0d8e1ab705372892c2ca22/tiktoken-0.12.0-cp314-cp314t-manylinux_2_28_aarch64.whl", hash = "sha256:dfdfaa5ffff8993a3af94d1125870b1d27aed7cb97aa7eb8c1cefdbc87dbee63", size = 1129022, upload-time = "2025-10-06T20:22:29.981Z" }, - { url = "https://files.pythonhosted.org/packages/4e/2b/fc46c90fe5028bd094cd6ee25a7db321cb91d45dc87531e2bdbb26b4867a/tiktoken-0.12.0-cp314-cp314t-manylinux_2_28_x86_64.whl", hash = "sha256:584c3ad3d0c74f5269906eb8a659c8bfc6144a52895d9261cdaf90a0ae5f4de0", size = 1150736, upload-time = "2025-10-06T20:22:30.996Z" }, - { url = "https://files.pythonhosted.org/packages/28/c0/3c7a39ff68022ddfd7d93f3337ad90389a342f761c4d71de99a3ccc57857/tiktoken-0.12.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:54c891b416a0e36b8e2045b12b33dd66fb34a4fe7965565f1b482da50da3e86a", size = 1194908, upload-time = "2025-10-06T20:22:32.073Z" }, - { url = "https://files.pythonhosted.org/packages/ab/0d/c1ad6f4016a3968c048545f5d9b8ffebf577774b2ede3e2e352553b685fe/tiktoken-0.12.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:5edb8743b88d5be814b1a8a8854494719080c28faaa1ccbef02e87354fe71ef0", size = 1253706, upload-time = "2025-10-06T20:22:33.385Z" }, - { url = "https://files.pythonhosted.org/packages/af/df/c7891ef9d2712ad774777271d39fdef63941ffba0a9d59b7ad1fd2765e57/tiktoken-0.12.0-cp314-cp314t-win_amd64.whl", hash = "sha256:f61c0aea5565ac82e2ec50a05e02a6c44734e91b51c10510b084ea1b8e633a71", size = 920667, upload-time = "2025-10-06T20:22:34.444Z" }, -] - -[[package]] -name = "tqdm" -version = "4.67.3" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "colorama", marker = "sys_platform == 'win32'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/09/a9/6ba95a270c6f1fbcd8dac228323f2777d886cb206987444e4bce66338dd4/tqdm-4.67.3.tar.gz", hash = "sha256:7d825f03f89244ef73f1d4ce193cb1774a8179fd96f31d7e1dcde62092b960bb", size = 169598, upload-time = "2026-02-03T17:35:53.048Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/16/e1/3079a9ff9b8e11b846c6ac5c8b5bfb7ff225eee721825310c91b3b50304f/tqdm-4.67.3-py3-none-any.whl", hash = "sha256:ee1e4c0e59148062281c49d80b25b67771a127c85fc9676d3be5f243206826bf", size = 78374, upload-time = "2026-02-03T17:35:50.982Z" }, -] - -[[package]] -name = "typing-extensions" -version = "4.15.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/72/94/1a15dd82efb362ac84269196e94cf00f187f7ed21c242792a923cdb1c61f/typing_extensions-4.15.0.tar.gz", hash = "sha256:0cea48d173cc12fa28ecabc3b837ea3cf6f38c6d1136f85cbaaf598984861466", size = 109391, upload-time = "2025-08-25T13:49:26.313Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl", hash = "sha256:f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548", size = 44614, upload-time = "2025-08-25T13:49:24.86Z" }, -] - -[[package]] -name = "typing-inspection" -version = "0.4.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/55/e3/70399cb7dd41c10ac53367ae42139cf4b1ca5f36bb3dc6c9d33acdb43655/typing_inspection-0.4.2.tar.gz", hash = "sha256:ba561c48a67c5958007083d386c3295464928b01faa735ab8547c5692e87f464", size = 75949, upload-time = "2025-10-01T02:14:41.687Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/dc/9b/47798a6c91d8bdb567fe2698fe81e0c6b7cb7ef4d13da4114b41d239f65d/typing_inspection-0.4.2-py3-none-any.whl", hash = "sha256:4ed1cacbdc298c220f1bd249ed5287caa16f34d44ef4e9c3d0cbad5b521545e7", size = 14611, upload-time = "2025-10-01T02:14:40.154Z" }, -] - -[[package]] -name = "urllib3" -version = "2.6.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/c7/24/5f1b3bdffd70275f6661c76461e25f024d5a38a46f04aaca912426a2b1d3/urllib3-2.6.3.tar.gz", hash = "sha256:1b62b6884944a57dbe321509ab94fd4d3b307075e0c2eae991ac71ee15ad38ed", size = 435556, upload-time = "2026-01-07T16:24:43.925Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl", hash = "sha256:bf272323e553dfb2e87d9bfd225ca7b0f467b919d7bbd355436d3fd37cb0acd4", size = 131584, upload-time = "2026-01-07T16:24:42.685Z" }, -] - -[[package]] -name = "uuid-utils" -version = "0.14.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/57/7c/3a926e847516e67bc6838634f2e54e24381105b4e80f9338dc35cca0086b/uuid_utils-0.14.0.tar.gz", hash = "sha256:fc5bac21e9933ea6c590433c11aa54aaca599f690c08069e364eb13a12f670b4", size = 22072, upload-time = "2026-01-20T20:37:15.729Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a7/42/42d003f4a99ddc901eef2fd41acb3694163835e037fb6dde79ad68a72342/uuid_utils-0.14.0-cp39-abi3-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:f6695c0bed8b18a904321e115afe73b34444bc8451d0ce3244a1ec3b84deb0e5", size = 601786, upload-time = "2026-01-20T20:37:09.843Z" }, - { url = "https://files.pythonhosted.org/packages/96/e6/775dfb91f74b18f7207e3201eb31ee666d286579990dc69dd50db2d92813/uuid_utils-0.14.0-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:4f0a730bbf2d8bb2c11b93e1005e91769f2f533fa1125ed1f00fd15b6fcc732b", size = 303943, upload-time = "2026-01-20T20:37:18.767Z" }, - { url = "https://files.pythonhosted.org/packages/17/82/ea5f5e85560b08a1f30cdc65f75e76494dc7aba9773f679e7eaa27370229/uuid_utils-0.14.0-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:40ce3fd1a4fdedae618fc3edc8faf91897012469169d600133470f49fd699ed3", size = 340467, upload-time = "2026-01-20T20:37:11.794Z" }, - { url = "https://files.pythonhosted.org/packages/ca/33/54b06415767f4569882e99b6470c6c8eeb97422686a6d432464f9967fd91/uuid_utils-0.14.0-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:09ae4a98416a440e78f7d9543d11b11cae4bab538b7ed94ec5da5221481748f2", size = 346333, upload-time = "2026-01-20T20:37:12.818Z" }, - { url = "https://files.pythonhosted.org/packages/cb/10/a6bce636b8f95e65dc84bf4a58ce8205b8e0a2a300a38cdbc83a3f763d27/uuid_utils-0.14.0-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:971e8c26b90d8ae727e7f2ac3ee23e265971d448b3672882f2eb44828b2b8c3e", size = 470859, upload-time = "2026-01-20T20:37:01.512Z" }, - { url = "https://files.pythonhosted.org/packages/8a/27/84121c51ea72f013f0e03d0886bcdfa96b31c9b83c98300a7bd5cc4fa191/uuid_utils-0.14.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d5cde1fa82804a8f9d2907b7aec2009d440062c63f04abbdb825fce717a5e860", size = 341988, upload-time = "2026-01-20T20:37:22.881Z" }, - { url = "https://files.pythonhosted.org/packages/90/a4/01c1c7af5e6a44f20b40183e8dac37d6ed83e7dc9e8df85370a15959b804/uuid_utils-0.14.0-cp39-abi3-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c7343862a2359e0bd48a7f3dfb5105877a1728677818bb694d9f40703264a2db", size = 365784, upload-time = "2026-01-20T20:37:10.808Z" }, - { url = "https://files.pythonhosted.org/packages/04/f0/65ee43ec617b8b6b1bf2a5aecd56a069a08cca3d9340c1de86024331bde3/uuid_utils-0.14.0-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:c51e4818fdb08ccec12dc7083a01f49507b4608770a0ab22368001685d59381b", size = 523750, upload-time = "2026-01-20T20:37:06.152Z" }, - { url = "https://files.pythonhosted.org/packages/95/d3/6bf503e3f135a5dfe705a65e6f89f19bccd55ac3fb16cb5d3ec5ba5388b8/uuid_utils-0.14.0-cp39-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:181bbcccb6f93d80a8504b5bd47b311a1c31395139596edbc47b154b0685b533", size = 615818, upload-time = "2026-01-20T20:37:21.816Z" }, - { url = "https://files.pythonhosted.org/packages/df/6c/99937dd78d07f73bba831c8dc9469dfe4696539eba2fc269ae1b92752f9e/uuid_utils-0.14.0-cp39-abi3-musllinux_1_2_i686.whl", hash = "sha256:5c8ae96101c3524ba8dbf762b6f05e9e9d896544786c503a727c5bf5cb9af1a7", size = 580831, upload-time = "2026-01-20T20:37:19.691Z" }, - { url = "https://files.pythonhosted.org/packages/44/fa/bbc9e2c25abd09a293b9b097a0d8fc16acd6a92854f0ec080f1ea7ad8bb3/uuid_utils-0.14.0-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:00ac3c6edfdaff7e1eed041f4800ae09a3361287be780d7610a90fdcde9befdc", size = 546333, upload-time = "2026-01-20T20:37:03.117Z" }, - { url = "https://files.pythonhosted.org/packages/e7/9b/e5e99b324b1b5f0c62882230455786df0bc66f67eff3b452447e703f45d2/uuid_utils-0.14.0-cp39-abi3-win32.whl", hash = "sha256:ec2fd80adf8e0e6589d40699e6f6df94c93edcc16dd999be0438dd007c77b151", size = 177319, upload-time = "2026-01-20T20:37:04.208Z" }, - { url = "https://files.pythonhosted.org/packages/d3/28/2c7d417ea483b6ff7820c948678fdf2ac98899dc7e43bb15852faa95acaf/uuid_utils-0.14.0-cp39-abi3-win_amd64.whl", hash = "sha256:efe881eb43a5504fad922644cb93d725fd8a6a6d949bd5a4b4b7d1a1587c7fd1", size = 182566, upload-time = "2026-01-20T20:37:16.868Z" }, - { url = "https://files.pythonhosted.org/packages/b8/86/49e4bdda28e962fbd7266684171ee29b3d92019116971d58783e51770745/uuid_utils-0.14.0-cp39-abi3-win_arm64.whl", hash = "sha256:32b372b8fd4ebd44d3a219e093fe981af4afdeda2994ee7db208ab065cfcd080", size = 182809, upload-time = "2026-01-20T20:37:05.139Z" }, - { url = "https://files.pythonhosted.org/packages/f1/03/1f1146e32e94d1f260dfabc81e1649102083303fb4ad549775c943425d9a/uuid_utils-0.14.0-pp311-pypy311_pp73-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:762e8d67992ac4d2454e24a141a1c82142b5bde10409818c62adbe9924ebc86d", size = 587430, upload-time = "2026-01-20T20:37:24.998Z" }, - { url = "https://files.pythonhosted.org/packages/87/ba/d5a7469362594d885fd9219fe9e851efbe65101d3ef1ef25ea321d7ce841/uuid_utils-0.14.0-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:40be5bf0b13aa849d9062abc86c198be6a25ff35316ce0b89fc25f3bac6d525e", size = 298106, upload-time = "2026-01-20T20:37:23.896Z" }, - { url = "https://files.pythonhosted.org/packages/8a/11/3dafb2a5502586f59fd49e93f5802cd5face82921b3a0f3abb5f357cb879/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:191a90a6f3940d1b7322b6e6cceff4dd533c943659e0a15f788674407856a515", size = 333423, upload-time = "2026-01-20T20:37:17.828Z" }, - { url = "https://files.pythonhosted.org/packages/7c/f2/c8987663f0cdcf4d717a36d85b5db2a5589df0a4e129aa10f16f4380ef48/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4aa4525f4ad82f9d9c842f9a3703f1539c1808affbaec07bb1b842f6b8b96aa5", size = 338659, upload-time = "2026-01-20T20:37:14.286Z" }, - { url = "https://files.pythonhosted.org/packages/d1/c8/929d81665d83f0b2ffaecb8e66c3091a50f62c7cb5b65e678bd75a96684e/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cdbd82ff20147461caefc375551595ecf77ebb384e46267f128aca45a0f2cdfc", size = 467029, upload-time = "2026-01-20T20:37:08.277Z" }, - { url = "https://files.pythonhosted.org/packages/8e/a0/27d7daa1bfed7163f4ccaf52d7d2f4ad7bb1002a85b45077938b91ee584f/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eff57e8a5d540006ce73cf0841a643d445afe78ba12e75ac53a95ca2924a56be", size = 333298, upload-time = "2026-01-20T20:37:07.271Z" }, - { url = "https://files.pythonhosted.org/packages/63/d4/acad86ce012b42ce18a12f31ee2aa3cbeeb98664f865f05f68c882945913/uuid_utils-0.14.0-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:3fd9112ca96978361201e669729784f26c71fecc9c13a7f8a07162c31bd4d1e2", size = 359217, upload-time = "2026-01-20T20:36:59.687Z" }, -] - -[[package]] -name = "wrapt" -version = "2.1.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f7/37/ae31f40bec90de2f88d9597d0b5281e23ffe85b893a47ca5d9c05c63a4f6/wrapt-2.1.1.tar.gz", hash = "sha256:5fdcb09bf6db023d88f312bd0767594b414655d58090fc1c46b3414415f67fac", size = 81329, upload-time = "2026-02-03T02:12:13.786Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b8/a8/9254e4da74b30a105935197015b18b31b7a298bf046e67d8952ef74967bd/wrapt-2.1.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6c366434a7fb914c7a5de508ed735ef9c133367114e1a7cb91dfb5cd806a1549", size = 60554, upload-time = "2026-02-03T02:11:13.038Z" }, - { url = "https://files.pythonhosted.org/packages/9e/a1/378579880cc7af226354054a2c255f69615b379d8adad482bfe2f22a0dc2/wrapt-2.1.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:5d6a2068bd2e1e19e5a317c8c0b288267eec4e7347c36bc68a6e378a39f19ee7", size = 61491, upload-time = "2026-02-03T02:12:56.077Z" }, - { url = "https://files.pythonhosted.org/packages/dc/72/957b51c56acca35701665878ad31626182199fc4afecfe67dea072210f95/wrapt-2.1.1-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:891ab4713419217b2aed7dd106c9200f64e6a82226775a0d2ebd6bef2ebd1747", size = 113949, upload-time = "2026-02-03T02:11:04.516Z" }, - { url = "https://files.pythonhosted.org/packages/cd/74/36bbebb4a3d2ae9c3e6929639721f8606cd0710a82a777c371aa69e36504/wrapt-2.1.1-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c8ef36a0df38d2dc9d907f6617f89e113c5892e0a35f58f45f75901af0ce7d81", size = 115989, upload-time = "2026-02-03T02:12:19.398Z" }, - { url = "https://files.pythonhosted.org/packages/ae/0d/f1177245a083c7be284bc90bddfe5aece32cdd5b858049cb69ce001a0e8d/wrapt-2.1.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:76e9af3ebd86f19973143d4d592cbf3e970cf3f66ddee30b16278c26ae34b8ab", size = 115242, upload-time = "2026-02-03T02:11:08.111Z" }, - { url = "https://files.pythonhosted.org/packages/62/3e/3b7cf5da27e59df61b1eae2d07dd03ff5d6f75b5408d694873cca7a8e33c/wrapt-2.1.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ff562067485ebdeaef2fa3fe9b1876bc4e7b73762e0a01406ad81e2076edcebf", size = 113676, upload-time = "2026-02-03T02:12:41.026Z" }, - { url = "https://files.pythonhosted.org/packages/f7/65/8248d3912c705f2c66f81cb97c77436f37abcbedb16d633b5ab0d795d8cd/wrapt-2.1.1-cp311-cp311-win32.whl", hash = "sha256:9e60a30aa0909435ec4ea2a3c53e8e1b50ac9f640c0e9fe3f21fd248a22f06c5", size = 57863, upload-time = "2026-02-03T02:12:18.112Z" }, - { url = "https://files.pythonhosted.org/packages/6b/31/d29310ab335f71f00c50466153b3dc985aaf4a9fc03263e543e136859541/wrapt-2.1.1-cp311-cp311-win_amd64.whl", hash = "sha256:7d79954f51fcf84e5ec4878ab4aea32610d70145c5bbc84b3370eabfb1e096c2", size = 60224, upload-time = "2026-02-03T02:12:29.289Z" }, - { url = "https://files.pythonhosted.org/packages/0c/90/a6ec319affa6e2894962a0cb9d73c67f88af1a726d15314bfb5c88b8a08d/wrapt-2.1.1-cp311-cp311-win_arm64.whl", hash = "sha256:d3ffc6b0efe79e08fd947605fd598515aebefe45e50432dc3b5cd437df8b1ada", size = 58643, upload-time = "2026-02-03T02:12:43.022Z" }, - { url = "https://files.pythonhosted.org/packages/df/cb/4d5255d19bbd12be7f8ee2c1fb4269dddec9cef777ef17174d357468efaa/wrapt-2.1.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:ab8e3793b239db021a18782a5823fcdea63b9fe75d0e340957f5828ef55fcc02", size = 61143, upload-time = "2026-02-03T02:11:46.313Z" }, - { url = "https://files.pythonhosted.org/packages/6f/07/7ed02daa35542023464e3c8b7cb937fa61f6c61c0361ecf8f5fecf8ad8da/wrapt-2.1.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:7c0300007836373d1c2df105b40777986accb738053a92fe09b615a7a4547e9f", size = 61740, upload-time = "2026-02-03T02:12:51.966Z" }, - { url = "https://files.pythonhosted.org/packages/c4/60/a237a4e4a36f6d966061ccc9b017627d448161b19e0a3ab80a7c7c97f859/wrapt-2.1.1-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:2b27c070fd1132ab23957bcd4ee3ba707a91e653a9268dc1afbd39b77b2799f7", size = 121327, upload-time = "2026-02-03T02:11:06.796Z" }, - { url = "https://files.pythonhosted.org/packages/ae/fe/9139058a3daa8818fc67e6460a2340e8bbcf3aef8b15d0301338bbe181ca/wrapt-2.1.1-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8b0e36d845e8b6f50949b6b65fc6cd279f47a1944582ed4ec8258cd136d89a64", size = 122903, upload-time = "2026-02-03T02:12:48.657Z" }, - { url = "https://files.pythonhosted.org/packages/91/10/b8479202b4164649675846a531763531f0a6608339558b5a0a718fc49a8d/wrapt-2.1.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:4aeea04a9889370fcfb1ef828c4cc583f36a875061505cd6cd9ba24d8b43cc36", size = 121333, upload-time = "2026-02-03T02:11:32.148Z" }, - { url = "https://files.pythonhosted.org/packages/5f/75/75fc793b791d79444aca2c03ccde64e8b99eda321b003f267d570b7b0985/wrapt-2.1.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:d88b46bb0dce9f74b6817bc1758ff2125e1ca9e1377d62ea35b6896142ab6825", size = 120458, upload-time = "2026-02-03T02:11:16.039Z" }, - { url = "https://files.pythonhosted.org/packages/d7/8f/c3f30d511082ca6d947c405f9d8f6c8eaf83cfde527c439ec2c9a30eb5ea/wrapt-2.1.1-cp312-cp312-win32.whl", hash = "sha256:63decff76ca685b5c557082dfbea865f3f5f6d45766a89bff8dc61d336348833", size = 58086, upload-time = "2026-02-03T02:12:35.041Z" }, - { url = "https://files.pythonhosted.org/packages/0a/c8/37625b643eea2849f10c3b90f69c7462faa4134448d4443234adaf122ae5/wrapt-2.1.1-cp312-cp312-win_amd64.whl", hash = "sha256:b828235d26c1e35aca4107039802ae4b1411be0fe0367dd5b7e4d90e562fcbcd", size = 60328, upload-time = "2026-02-03T02:12:45.808Z" }, - { url = "https://files.pythonhosted.org/packages/ce/79/56242f07572d5682ba8065a9d4d9c2218313f576e3c3471873c2a5355ffd/wrapt-2.1.1-cp312-cp312-win_arm64.whl", hash = "sha256:75128507413a9f1bcbe2db88fd18fbdbf80f264b82fa33a6996cdeaf01c52352", size = 58722, upload-time = "2026-02-03T02:12:27.949Z" }, - { url = "https://files.pythonhosted.org/packages/f7/ca/3cf290212855b19af9fcc41b725b5620b32f470d6aad970c2593500817eb/wrapt-2.1.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:ce9646e17fa7c3e2e7a87e696c7de66512c2b4f789a8db95c613588985a2e139", size = 61150, upload-time = "2026-02-03T02:12:50.575Z" }, - { url = "https://files.pythonhosted.org/packages/9d/33/5b8f89a82a9859ce82da4870c799ad11ce15648b6e1c820fec3e23f4a19f/wrapt-2.1.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:428cfc801925454395aa468ba7ddb3ed63dc0d881df7b81626cdd433b4e2b11b", size = 61743, upload-time = "2026-02-03T02:11:55.733Z" }, - { url = "https://files.pythonhosted.org/packages/1e/2f/60c51304fbdf47ce992d9eefa61fbd2c0e64feee60aaa439baf42ea6f40b/wrapt-2.1.1-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:5797f65e4d58065a49088c3b32af5410751cd485e83ba89e5a45e2aa8905af98", size = 121341, upload-time = "2026-02-03T02:11:20.461Z" }, - { url = "https://files.pythonhosted.org/packages/ad/03/ce5256e66dd94e521ad5e753c78185c01b6eddbed3147be541f4d38c0cb7/wrapt-2.1.1-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5a2db44a71202c5ae4bb5f27c6d3afbc5b23053f2e7e78aa29704541b5dad789", size = 122947, upload-time = "2026-02-03T02:11:33.596Z" }, - { url = "https://files.pythonhosted.org/packages/eb/ae/50ca8854b81b946a11a36fcd6ead32336e6db2c14b6e4a8b092b80741178/wrapt-2.1.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:8d5350c3590af09c1703dd60ec78a7370c0186e11eaafb9dda025a30eee6492d", size = 121370, upload-time = "2026-02-03T02:11:09.886Z" }, - { url = "https://files.pythonhosted.org/packages/fb/d9/d6a7c654e0043319b4cc137a4caaf7aa16b46b51ee8df98d1060254705b7/wrapt-2.1.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:2d9b076411bed964e752c01b49fd224cc385f3a96f520c797d38412d70d08359", size = 120465, upload-time = "2026-02-03T02:11:37.592Z" }, - { url = "https://files.pythonhosted.org/packages/55/90/65be41e40845d951f714b5a77e84f377a3787b1e8eee6555a680da6d0db5/wrapt-2.1.1-cp313-cp313-win32.whl", hash = "sha256:0bb7207130ce6486727baa85373503bf3334cc28016f6928a0fa7e19d7ecdc06", size = 58090, upload-time = "2026-02-03T02:12:53.342Z" }, - { url = "https://files.pythonhosted.org/packages/5f/66/6a09e0294c4fc8c26028a03a15191721c9271672467cc33e6617ee0d91d2/wrapt-2.1.1-cp313-cp313-win_amd64.whl", hash = "sha256:cbfee35c711046b15147b0ae7db9b976f01c9520e6636d992cd9e69e5e2b03b1", size = 60341, upload-time = "2026-02-03T02:12:36.384Z" }, - { url = "https://files.pythonhosted.org/packages/7a/f0/20ceb8b701e9a71555c87a5ddecbed76ec16742cf1e4b87bbaf26735f998/wrapt-2.1.1-cp313-cp313-win_arm64.whl", hash = "sha256:7d2756061022aebbf57ba14af9c16e8044e055c22d38de7bf40d92b565ecd2b0", size = 58731, upload-time = "2026-02-03T02:12:01.328Z" }, - { url = "https://files.pythonhosted.org/packages/80/b4/fe95beb8946700b3db371f6ce25115217e7075ca063663b8cca2888ba55c/wrapt-2.1.1-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:4814a3e58bc6971e46baa910ecee69699110a2bf06c201e24277c65115a20c20", size = 62969, upload-time = "2026-02-03T02:11:51.245Z" }, - { url = "https://files.pythonhosted.org/packages/b8/89/477b0bdc784e3299edf69c279697372b8bd4c31d9c6966eae405442899df/wrapt-2.1.1-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:106c5123232ab9b9f4903692e1fa0bdc231510098f04c13c3081f8ad71c3d612", size = 63606, upload-time = "2026-02-03T02:12:02.64Z" }, - { url = "https://files.pythonhosted.org/packages/ed/55/9d0c1269ab76de87715b3b905df54dd25d55bbffd0b98696893eb613469f/wrapt-2.1.1-cp313-cp313t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:1a40b83ff2535e6e56f190aff123821eea89a24c589f7af33413b9c19eb2c738", size = 152536, upload-time = "2026-02-03T02:11:24.492Z" }, - { url = "https://files.pythonhosted.org/packages/44/18/2004766030462f79ad86efaa62000b5e39b1ff001dcce86650e1625f40ae/wrapt-2.1.1-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:789cea26e740d71cf1882e3a42bb29052bc4ada15770c90072cb47bf73fb3dbf", size = 158697, upload-time = "2026-02-03T02:12:32.214Z" }, - { url = "https://files.pythonhosted.org/packages/e1/bb/0a880fa0f35e94ee843df4ee4dd52a699c9263f36881311cfb412c09c3e5/wrapt-2.1.1-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:ba49c14222d5e5c0ee394495a8655e991dc06cbca5398153aefa5ac08cd6ccd7", size = 155563, upload-time = "2026-02-03T02:11:49.737Z" }, - { url = "https://files.pythonhosted.org/packages/42/ff/cd1b7c4846c8678fac359a6eb975dc7ab5bd606030adb22acc8b4a9f53f1/wrapt-2.1.1-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:ac8cda531fe55be838a17c62c806824472bb962b3afa47ecbd59b27b78496f4e", size = 150161, upload-time = "2026-02-03T02:12:33.613Z" }, - { url = "https://files.pythonhosted.org/packages/38/ec/67c90a7082f452964b4621e4890e9a490f1add23cdeb7483cc1706743291/wrapt-2.1.1-cp313-cp313t-win32.whl", hash = "sha256:b8af75fe20d381dd5bcc9db2e86a86d7fcfbf615383a7147b85da97c1182225b", size = 59783, upload-time = "2026-02-03T02:11:39.863Z" }, - { url = "https://files.pythonhosted.org/packages/ec/08/466afe4855847d8febdfa2c57c87e991fc5820afbdef01a273683dfd15a0/wrapt-2.1.1-cp313-cp313t-win_amd64.whl", hash = "sha256:45c5631c9b6c792b78be2d7352129f776dd72c605be2c3a4e9be346be8376d83", size = 63082, upload-time = "2026-02-03T02:12:09.075Z" }, - { url = "https://files.pythonhosted.org/packages/9a/62/60b629463c28b15b1eeadb3a0691e17568622b12aa5bfa7ebe9b514bfbeb/wrapt-2.1.1-cp313-cp313t-win_arm64.whl", hash = "sha256:da815b9263947ac98d088b6414ac83507809a1d385e4632d9489867228d6d81c", size = 60251, upload-time = "2026-02-03T02:11:21.794Z" }, - { url = "https://files.pythonhosted.org/packages/95/a0/1c2396e272f91efe6b16a6a8bce7ad53856c8f9ae4f34ceaa711d63ec9e1/wrapt-2.1.1-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:9aa1765054245bb01a37f615503290d4e207e3fd59226e78341afb587e9c1236", size = 61311, upload-time = "2026-02-03T02:12:44.41Z" }, - { url = "https://files.pythonhosted.org/packages/b0/9a/d2faba7e61072a7507b5722db63562fdb22f5a24e237d460d18755627f15/wrapt-2.1.1-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:feff14b63a6d86c1eee33a57f77573649f2550935981625be7ff3cb7342efe05", size = 61805, upload-time = "2026-02-03T02:11:59.905Z" }, - { url = "https://files.pythonhosted.org/packages/db/56/073989deb4b5d7d6e7ea424476a4ae4bda02140f2dbeaafb14ba4864dd60/wrapt-2.1.1-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:81fc5f22d5fcfdbabde96bb3f5379b9f4476d05c6d524d7259dc5dfb501d3281", size = 120308, upload-time = "2026-02-03T02:12:04.46Z" }, - { url = "https://files.pythonhosted.org/packages/d1/b6/84f37261295e38167a29eb82affaf1dc15948dc416925fe2091beee8e4ac/wrapt-2.1.1-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:951b228ecf66def855d22e006ab9a1fc12535111ae7db2ec576c728f8ddb39e8", size = 122688, upload-time = "2026-02-03T02:11:23.148Z" }, - { url = "https://files.pythonhosted.org/packages/ea/80/32db2eec6671f80c65b7ff175be61bc73d7f5223f6910b0c921bbc4bd11c/wrapt-2.1.1-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:0ddf582a95641b9a8c8bd643e83f34ecbbfe1b68bc3850093605e469ab680ae3", size = 121115, upload-time = "2026-02-03T02:12:39.068Z" }, - { url = "https://files.pythonhosted.org/packages/49/ef/dcd00383df0cd696614127902153bf067971a5aabcd3c9dcb2d8ef354b2a/wrapt-2.1.1-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:fc5c500966bf48913f795f1984704e6d452ba2414207b15e1f8c339a059d5b16", size = 119484, upload-time = "2026-02-03T02:11:48.419Z" }, - { url = "https://files.pythonhosted.org/packages/76/29/0630280cdd2bd8f86f35cb6854abee1c9d6d1a28a0c6b6417cd15d378325/wrapt-2.1.1-cp314-cp314-win32.whl", hash = "sha256:4aa4baadb1f94b71151b8e44a0c044f6af37396c3b8bcd474b78b49e2130a23b", size = 58514, upload-time = "2026-02-03T02:11:58.616Z" }, - { url = "https://files.pythonhosted.org/packages/db/19/5bed84f9089ed2065f6aeda5dfc4f043743f642bc871454b261c3d7d322b/wrapt-2.1.1-cp314-cp314-win_amd64.whl", hash = "sha256:860e9d3fd81816a9f4e40812f28be4439ab01f260603c749d14be3c0a1170d19", size = 60763, upload-time = "2026-02-03T02:12:24.553Z" }, - { url = "https://files.pythonhosted.org/packages/e4/cb/b967f2f9669e4249b4fe82e630d2a01bc6b9e362b9b12ed91bbe23ae8df4/wrapt-2.1.1-cp314-cp314-win_arm64.whl", hash = "sha256:3c59e103017a2c1ea0ddf589cbefd63f91081d7ce9d491d69ff2512bb1157e23", size = 59051, upload-time = "2026-02-03T02:11:29.602Z" }, - { url = "https://files.pythonhosted.org/packages/eb/19/6fed62be29f97eb8a56aff236c3f960a4b4a86e8379dc7046a8005901a97/wrapt-2.1.1-cp314-cp314t-macosx_10_15_x86_64.whl", hash = "sha256:9fa7c7e1bee9278fc4f5dd8275bc8d25493281a8ec6c61959e37cc46acf02007", size = 63059, upload-time = "2026-02-03T02:12:06.368Z" }, - { url = "https://files.pythonhosted.org/packages/0a/1c/b757fd0adb53d91547ed8fad76ba14a5932d83dde4c994846a2804596378/wrapt-2.1.1-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:39c35e12e8215628984248bd9c8897ce0a474be2a773db207eb93414219d8469", size = 63618, upload-time = "2026-02-03T02:12:23.197Z" }, - { url = "https://files.pythonhosted.org/packages/10/fe/e5ae17b1480957c7988d991b93df9f2425fc51f128cf88144d6a18d0eb12/wrapt-2.1.1-cp314-cp314t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:94ded4540cac9125eaa8ddf5f651a7ec0da6f5b9f248fe0347b597098f8ec14c", size = 152544, upload-time = "2026-02-03T02:11:43.915Z" }, - { url = "https://files.pythonhosted.org/packages/3e/cc/99aed210c6b547b8a6e4cb9d1425e4466727158a6aeb833aa7997e9e08dd/wrapt-2.1.1-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:da0af328373f97ed9bdfea24549ac1b944096a5a71b30e41c9b8b53ab3eec04a", size = 158700, upload-time = "2026-02-03T02:12:30.684Z" }, - { url = "https://files.pythonhosted.org/packages/81/0e/d442f745f4957944d5f8ad38bc3a96620bfff3562533b87e486e979f3d99/wrapt-2.1.1-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:4ad839b55f0bf235f8e337ce060572d7a06592592f600f3a3029168e838469d3", size = 155561, upload-time = "2026-02-03T02:11:28.164Z" }, - { url = "https://files.pythonhosted.org/packages/51/ac/9891816280e0018c48f8dfd61b136af7b0dcb4a088895db2531acde5631b/wrapt-2.1.1-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:0d89c49356e5e2a50fa86b40e0510082abcd0530f926cbd71cf25bee6b9d82d7", size = 150188, upload-time = "2026-02-03T02:11:57.053Z" }, - { url = "https://files.pythonhosted.org/packages/24/98/e2f273b6d70d41f98d0739aa9a269d0b633684a5fb17b9229709375748d4/wrapt-2.1.1-cp314-cp314t-win32.whl", hash = "sha256:f4c7dd22cf7f36aafe772f3d88656559205c3af1b7900adfccb70edeb0d2abc4", size = 60425, upload-time = "2026-02-03T02:11:35.007Z" }, - { url = "https://files.pythonhosted.org/packages/1e/06/b500bfc38a4f82d89f34a13069e748c82c5430d365d9e6b75afb3ab74457/wrapt-2.1.1-cp314-cp314t-win_amd64.whl", hash = "sha256:f76bc12c583ab01e73ba0ea585465a41e48d968f6d1311b4daec4f8654e356e3", size = 63855, upload-time = "2026-02-03T02:12:15.47Z" }, - { url = "https://files.pythonhosted.org/packages/d9/cc/5f6193c32166faee1d2a613f278608e6f3b95b96589d020f0088459c46c9/wrapt-2.1.1-cp314-cp314t-win_arm64.whl", hash = "sha256:7ea74fc0bec172f1ae5f3505b6655c541786a5cabe4bbc0d9723a56ac32eb9b9", size = 60443, upload-time = "2026-02-03T02:11:30.869Z" }, - { url = "https://files.pythonhosted.org/packages/c4/da/5a086bf4c22a41995312db104ec2ffeee2cf6accca9faaee5315c790377d/wrapt-2.1.1-py3-none-any.whl", hash = "sha256:3b0f4629eb954394a3d7c7a1c8cca25f0b07cefe6aa8545e862e9778152de5b7", size = 43886, upload-time = "2026-02-03T02:11:45.048Z" }, -] - -[[package]] -name = "xxhash" -version = "3.6.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/02/84/30869e01909fb37a6cc7e18688ee8bf1e42d57e7e0777636bd47524c43c7/xxhash-3.6.0.tar.gz", hash = "sha256:f0162a78b13a0d7617b2845b90c763339d1f1d82bb04a4b07f4ab535cc5e05d6", size = 85160, upload-time = "2025-10-02T14:37:08.097Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/17/d4/cc2f0400e9154df4b9964249da78ebd72f318e35ccc425e9f403c392f22a/xxhash-3.6.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b47bbd8cf2d72797f3c2772eaaac0ded3d3af26481a26d7d7d41dc2d3c46b04a", size = 32844, upload-time = "2025-10-02T14:34:14.037Z" }, - { url = "https://files.pythonhosted.org/packages/5e/ec/1cc11cd13e26ea8bc3cb4af4eaadd8d46d5014aebb67be3f71fb0b68802a/xxhash-3.6.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2b6821e94346f96db75abaa6e255706fb06ebd530899ed76d32cd99f20dc52fa", size = 30809, upload-time = "2025-10-02T14:34:15.484Z" }, - { url = "https://files.pythonhosted.org/packages/04/5f/19fe357ea348d98ca22f456f75a30ac0916b51c753e1f8b2e0e6fb884cce/xxhash-3.6.0-cp311-cp311-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:d0a9751f71a1a65ce3584e9cae4467651c7e70c9d31017fa57574583a4540248", size = 194665, upload-time = "2025-10-02T14:34:16.541Z" }, - { url = "https://files.pythonhosted.org/packages/90/3b/d1f1a8f5442a5fd8beedae110c5af7604dc37349a8e16519c13c19a9a2de/xxhash-3.6.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8b29ee68625ab37b04c0b40c3fafdf24d2f75ccd778333cfb698f65f6c463f62", size = 213550, upload-time = "2025-10-02T14:34:17.878Z" }, - { url = "https://files.pythonhosted.org/packages/c4/ef/3a9b05eb527457d5db13a135a2ae1a26c80fecd624d20f3e8dcc4cb170f3/xxhash-3.6.0-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:6812c25fe0d6c36a46ccb002f40f27ac903bf18af9f6dd8f9669cb4d176ab18f", size = 212384, upload-time = "2025-10-02T14:34:19.182Z" }, - { url = "https://files.pythonhosted.org/packages/0f/18/ccc194ee698c6c623acbf0f8c2969811a8a4b6185af5e824cd27b9e4fd3e/xxhash-3.6.0-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:4ccbff013972390b51a18ef1255ef5ac125c92dc9143b2d1909f59abc765540e", size = 445749, upload-time = "2025-10-02T14:34:20.659Z" }, - { url = "https://files.pythonhosted.org/packages/a5/86/cf2c0321dc3940a7aa73076f4fd677a0fb3e405cb297ead7d864fd90847e/xxhash-3.6.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:297b7fbf86c82c550e12e8fb71968b3f033d27b874276ba3624ea868c11165a8", size = 193880, upload-time = "2025-10-02T14:34:22.431Z" }, - { url = "https://files.pythonhosted.org/packages/82/fb/96213c8560e6f948a1ecc9a7613f8032b19ee45f747f4fca4eb31bb6d6ed/xxhash-3.6.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:dea26ae1eb293db089798d3973a5fc928a18fdd97cc8801226fae705b02b14b0", size = 210912, upload-time = "2025-10-02T14:34:23.937Z" }, - { url = "https://files.pythonhosted.org/packages/40/aa/4395e669b0606a096d6788f40dbdf2b819d6773aa290c19e6e83cbfc312f/xxhash-3.6.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:7a0b169aafb98f4284f73635a8e93f0735f9cbde17bd5ec332480484241aaa77", size = 198654, upload-time = "2025-10-02T14:34:25.644Z" }, - { url = "https://files.pythonhosted.org/packages/67/74/b044fcd6b3d89e9b1b665924d85d3f400636c23590226feb1eb09e1176ce/xxhash-3.6.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:08d45aef063a4531b785cd72de4887766d01dc8f362a515693df349fdb825e0c", size = 210867, upload-time = "2025-10-02T14:34:27.203Z" }, - { url = "https://files.pythonhosted.org/packages/bc/fd/3ce73bf753b08cb19daee1eb14aa0d7fe331f8da9c02dd95316ddfe5275e/xxhash-3.6.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:929142361a48ee07f09121fe9e96a84950e8d4df3bb298ca5d88061969f34d7b", size = 414012, upload-time = "2025-10-02T14:34:28.409Z" }, - { url = "https://files.pythonhosted.org/packages/ba/b3/5a4241309217c5c876f156b10778f3ab3af7ba7e3259e6d5f5c7d0129eb2/xxhash-3.6.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:51312c768403d8540487dbbfb557454cfc55589bbde6424456951f7fcd4facb3", size = 191409, upload-time = "2025-10-02T14:34:29.696Z" }, - { url = "https://files.pythonhosted.org/packages/c0/01/99bfbc15fb9abb9a72b088c1d95219fc4782b7d01fc835bd5744d66dd0b8/xxhash-3.6.0-cp311-cp311-win32.whl", hash = "sha256:d1927a69feddc24c987b337ce81ac15c4720955b667fe9b588e02254b80446fd", size = 30574, upload-time = "2025-10-02T14:34:31.028Z" }, - { url = "https://files.pythonhosted.org/packages/65/79/9d24d7f53819fe301b231044ea362ce64e86c74f6e8c8e51320de248b3e5/xxhash-3.6.0-cp311-cp311-win_amd64.whl", hash = "sha256:26734cdc2d4ffe449b41d186bbeac416f704a482ed835d375a5c0cb02bc63fef", size = 31481, upload-time = "2025-10-02T14:34:32.062Z" }, - { url = "https://files.pythonhosted.org/packages/30/4e/15cd0e3e8772071344eab2961ce83f6e485111fed8beb491a3f1ce100270/xxhash-3.6.0-cp311-cp311-win_arm64.whl", hash = "sha256:d72f67ef8bf36e05f5b6c65e8524f265bd61071471cd4cf1d36743ebeeeb06b7", size = 27861, upload-time = "2025-10-02T14:34:33.555Z" }, - { url = "https://files.pythonhosted.org/packages/9a/07/d9412f3d7d462347e4511181dea65e47e0d0e16e26fbee2ea86a2aefb657/xxhash-3.6.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:01362c4331775398e7bb34e3ab403bc9ee9f7c497bc7dee6272114055277dd3c", size = 32744, upload-time = "2025-10-02T14:34:34.622Z" }, - { url = "https://files.pythonhosted.org/packages/79/35/0429ee11d035fc33abe32dca1b2b69e8c18d236547b9a9b72c1929189b9a/xxhash-3.6.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:b7b2df81a23f8cb99656378e72501b2cb41b1827c0f5a86f87d6b06b69f9f204", size = 30816, upload-time = "2025-10-02T14:34:36.043Z" }, - { url = "https://files.pythonhosted.org/packages/b7/f2/57eb99aa0f7d98624c0932c5b9a170e1806406cdbcdb510546634a1359e0/xxhash-3.6.0-cp312-cp312-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:dc94790144e66b14f67b10ac8ed75b39ca47536bf8800eb7c24b50271ea0c490", size = 194035, upload-time = "2025-10-02T14:34:37.354Z" }, - { url = "https://files.pythonhosted.org/packages/4c/ed/6224ba353690d73af7a3f1c7cdb1fc1b002e38f783cb991ae338e1eb3d79/xxhash-3.6.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:93f107c673bccf0d592cdba077dedaf52fe7f42dcd7676eba1f6d6f0c3efffd2", size = 212914, upload-time = "2025-10-02T14:34:38.6Z" }, - { url = "https://files.pythonhosted.org/packages/38/86/fb6b6130d8dd6b8942cc17ab4d90e223653a89aa32ad2776f8af7064ed13/xxhash-3.6.0-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:2aa5ee3444c25b69813663c9f8067dcfaa2e126dc55e8dddf40f4d1c25d7effa", size = 212163, upload-time = "2025-10-02T14:34:39.872Z" }, - { url = "https://files.pythonhosted.org/packages/ee/dc/e84875682b0593e884ad73b2d40767b5790d417bde603cceb6878901d647/xxhash-3.6.0-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:f7f99123f0e1194fa59cc69ad46dbae2e07becec5df50a0509a808f90a0f03f0", size = 445411, upload-time = "2025-10-02T14:34:41.569Z" }, - { url = "https://files.pythonhosted.org/packages/11/4f/426f91b96701ec2f37bb2b8cec664eff4f658a11f3fa9d94f0a887ea6d2b/xxhash-3.6.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:49e03e6fe2cac4a1bc64952dd250cf0dbc5ef4ebb7b8d96bce82e2de163c82a2", size = 193883, upload-time = "2025-10-02T14:34:43.249Z" }, - { url = "https://files.pythonhosted.org/packages/53/5a/ddbb83eee8e28b778eacfc5a85c969673e4023cdeedcfcef61f36731610b/xxhash-3.6.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:bd17fede52a17a4f9a7bc4472a5867cb0b160deeb431795c0e4abe158bc784e9", size = 210392, upload-time = "2025-10-02T14:34:45.042Z" }, - { url = "https://files.pythonhosted.org/packages/1e/c2/ff69efd07c8c074ccdf0a4f36fcdd3d27363665bcdf4ba399abebe643465/xxhash-3.6.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:6fb5f5476bef678f69db04f2bd1efbed3030d2aba305b0fc1773645f187d6a4e", size = 197898, upload-time = "2025-10-02T14:34:46.302Z" }, - { url = "https://files.pythonhosted.org/packages/58/ca/faa05ac19b3b622c7c9317ac3e23954187516298a091eb02c976d0d3dd45/xxhash-3.6.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:843b52f6d88071f87eba1631b684fcb4b2068cd2180a0224122fe4ef011a9374", size = 210655, upload-time = "2025-10-02T14:34:47.571Z" }, - { url = "https://files.pythonhosted.org/packages/d4/7a/06aa7482345480cc0cb597f5c875b11a82c3953f534394f620b0be2f700c/xxhash-3.6.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:7d14a6cfaf03b1b6f5f9790f76880601ccc7896aff7ab9cd8978a939c1eb7e0d", size = 414001, upload-time = "2025-10-02T14:34:49.273Z" }, - { url = "https://files.pythonhosted.org/packages/23/07/63ffb386cd47029aa2916b3d2f454e6cc5b9f5c5ada3790377d5430084e7/xxhash-3.6.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:418daf3db71e1413cfe211c2f9a528456936645c17f46b5204705581a45390ae", size = 191431, upload-time = "2025-10-02T14:34:50.798Z" }, - { url = "https://files.pythonhosted.org/packages/0f/93/14fde614cadb4ddf5e7cebf8918b7e8fac5ae7861c1875964f17e678205c/xxhash-3.6.0-cp312-cp312-win32.whl", hash = "sha256:50fc255f39428a27299c20e280d6193d8b63b8ef8028995323bf834a026b4fbb", size = 30617, upload-time = "2025-10-02T14:34:51.954Z" }, - { url = "https://files.pythonhosted.org/packages/13/5d/0d125536cbe7565a83d06e43783389ecae0c0f2ed037b48ede185de477c0/xxhash-3.6.0-cp312-cp312-win_amd64.whl", hash = "sha256:c0f2ab8c715630565ab8991b536ecded9416d615538be8ecddce43ccf26cbc7c", size = 31534, upload-time = "2025-10-02T14:34:53.276Z" }, - { url = "https://files.pythonhosted.org/packages/54/85/6ec269b0952ec7e36ba019125982cf11d91256a778c7c3f98a4c5043d283/xxhash-3.6.0-cp312-cp312-win_arm64.whl", hash = "sha256:eae5c13f3bc455a3bbb68bdc513912dc7356de7e2280363ea235f71f54064829", size = 27876, upload-time = "2025-10-02T14:34:54.371Z" }, - { url = "https://files.pythonhosted.org/packages/33/76/35d05267ac82f53ae9b0e554da7c5e281ee61f3cad44c743f0fcd354f211/xxhash-3.6.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:599e64ba7f67472481ceb6ee80fa3bd828fd61ba59fb11475572cc5ee52b89ec", size = 32738, upload-time = "2025-10-02T14:34:55.839Z" }, - { url = "https://files.pythonhosted.org/packages/31/a8/3fbce1cd96534a95e35d5120637bf29b0d7f5d8fa2f6374e31b4156dd419/xxhash-3.6.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:7d8b8aaa30fca4f16f0c84a5c8d7ddee0e25250ec2796c973775373257dde8f1", size = 30821, upload-time = "2025-10-02T14:34:57.219Z" }, - { url = "https://files.pythonhosted.org/packages/0c/ea/d387530ca7ecfa183cb358027f1833297c6ac6098223fd14f9782cd0015c/xxhash-3.6.0-cp313-cp313-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:d597acf8506d6e7101a4a44a5e428977a51c0fadbbfd3c39650cca9253f6e5a6", size = 194127, upload-time = "2025-10-02T14:34:59.21Z" }, - { url = "https://files.pythonhosted.org/packages/ba/0c/71435dcb99874b09a43b8d7c54071e600a7481e42b3e3ce1eb5226a5711a/xxhash-3.6.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:858dc935963a33bc33490128edc1c12b0c14d9c7ebaa4e387a7869ecc4f3e263", size = 212975, upload-time = "2025-10-02T14:35:00.816Z" }, - { url = "https://files.pythonhosted.org/packages/84/7a/c2b3d071e4bb4a90b7057228a99b10d51744878f4a8a6dd643c8bd897620/xxhash-3.6.0-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:ba284920194615cb8edf73bf52236ce2e1664ccd4a38fdb543506413529cc546", size = 212241, upload-time = "2025-10-02T14:35:02.207Z" }, - { url = "https://files.pythonhosted.org/packages/81/5f/640b6eac0128e215f177df99eadcd0f1b7c42c274ab6a394a05059694c5a/xxhash-3.6.0-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:4b54219177f6c6674d5378bd862c6aedf64725f70dd29c472eaae154df1a2e89", size = 445471, upload-time = "2025-10-02T14:35:03.61Z" }, - { url = "https://files.pythonhosted.org/packages/5e/1e/3c3d3ef071b051cc3abbe3721ffb8365033a172613c04af2da89d5548a87/xxhash-3.6.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:42c36dd7dbad2f5238950c377fcbf6811b1cdb1c444fab447960030cea60504d", size = 193936, upload-time = "2025-10-02T14:35:05.013Z" }, - { url = "https://files.pythonhosted.org/packages/2c/bd/4a5f68381939219abfe1c22a9e3a5854a4f6f6f3c4983a87d255f21f2e5d/xxhash-3.6.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f22927652cba98c44639ffdc7aaf35828dccf679b10b31c4ad72a5b530a18eb7", size = 210440, upload-time = "2025-10-02T14:35:06.239Z" }, - { url = "https://files.pythonhosted.org/packages/eb/37/b80fe3d5cfb9faff01a02121a0f4d565eb7237e9e5fc66e73017e74dcd36/xxhash-3.6.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:b45fad44d9c5c119e9c6fbf2e1c656a46dc68e280275007bbfd3d572b21426db", size = 197990, upload-time = "2025-10-02T14:35:07.735Z" }, - { url = "https://files.pythonhosted.org/packages/d7/fd/2c0a00c97b9e18f72e1f240ad4e8f8a90fd9d408289ba9c7c495ed7dc05c/xxhash-3.6.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:6f2580ffab1a8b68ef2b901cde7e55fa8da5e4be0977c68f78fc80f3c143de42", size = 210689, upload-time = "2025-10-02T14:35:09.438Z" }, - { url = "https://files.pythonhosted.org/packages/93/86/5dd8076a926b9a95db3206aba20d89a7fc14dd5aac16e5c4de4b56033140/xxhash-3.6.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:40c391dd3cd041ebc3ffe6f2c862f402e306eb571422e0aa918d8070ba31da11", size = 414068, upload-time = "2025-10-02T14:35:11.162Z" }, - { url = "https://files.pythonhosted.org/packages/af/3c/0bb129170ee8f3650f08e993baee550a09593462a5cddd8e44d0011102b1/xxhash-3.6.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:f205badabde7aafd1a31e8ca2a3e5a763107a71c397c4481d6a804eb5063d8bd", size = 191495, upload-time = "2025-10-02T14:35:12.971Z" }, - { url = "https://files.pythonhosted.org/packages/e9/3a/6797e0114c21d1725e2577508e24006fd7ff1d8c0c502d3b52e45c1771d8/xxhash-3.6.0-cp313-cp313-win32.whl", hash = "sha256:2577b276e060b73b73a53042ea5bd5203d3e6347ce0d09f98500f418a9fcf799", size = 30620, upload-time = "2025-10-02T14:35:14.129Z" }, - { url = "https://files.pythonhosted.org/packages/86/15/9bc32671e9a38b413a76d24722a2bf8784a132c043063a8f5152d390b0f9/xxhash-3.6.0-cp313-cp313-win_amd64.whl", hash = "sha256:757320d45d2fbcce8f30c42a6b2f47862967aea7bf458b9625b4bbe7ee390392", size = 31542, upload-time = "2025-10-02T14:35:15.21Z" }, - { url = "https://files.pythonhosted.org/packages/39/c5/cc01e4f6188656e56112d6a8e0dfe298a16934b8c47a247236549a3f7695/xxhash-3.6.0-cp313-cp313-win_arm64.whl", hash = "sha256:457b8f85dec5825eed7b69c11ae86834a018b8e3df5e77783c999663da2f96d6", size = 27880, upload-time = "2025-10-02T14:35:16.315Z" }, - { url = "https://files.pythonhosted.org/packages/f3/30/25e5321c8732759e930c555176d37e24ab84365482d257c3b16362235212/xxhash-3.6.0-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:a42e633d75cdad6d625434e3468126c73f13f7584545a9cf34e883aa1710e702", size = 32956, upload-time = "2025-10-02T14:35:17.413Z" }, - { url = "https://files.pythonhosted.org/packages/9f/3c/0573299560d7d9f8ab1838f1efc021a280b5ae5ae2e849034ef3dee18810/xxhash-3.6.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:568a6d743219e717b07b4e03b0a828ce593833e498c3b64752e0f5df6bfe84db", size = 31072, upload-time = "2025-10-02T14:35:18.844Z" }, - { url = "https://files.pythonhosted.org/packages/7a/1c/52d83a06e417cd9d4137722693424885cc9878249beb3a7c829e74bf7ce9/xxhash-3.6.0-cp313-cp313t-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:bec91b562d8012dae276af8025a55811b875baace6af510412a5e58e3121bc54", size = 196409, upload-time = "2025-10-02T14:35:20.31Z" }, - { url = "https://files.pythonhosted.org/packages/e3/8e/c6d158d12a79bbd0b878f8355432075fc82759e356ab5a111463422a239b/xxhash-3.6.0-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:78e7f2f4c521c30ad5e786fdd6bae89d47a32672a80195467b5de0480aa97b1f", size = 215736, upload-time = "2025-10-02T14:35:21.616Z" }, - { url = "https://files.pythonhosted.org/packages/bc/68/c4c80614716345d55071a396cf03d06e34b5f4917a467faf43083c995155/xxhash-3.6.0-cp313-cp313t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:3ed0df1b11a79856df5ffcab572cbd6b9627034c1c748c5566fa79df9048a7c5", size = 214833, upload-time = "2025-10-02T14:35:23.32Z" }, - { url = "https://files.pythonhosted.org/packages/7e/e9/ae27c8ffec8b953efa84c7c4a6c6802c263d587b9fc0d6e7cea64e08c3af/xxhash-3.6.0-cp313-cp313t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:0e4edbfc7d420925b0dd5e792478ed393d6e75ff8fc219a6546fb446b6a417b1", size = 448348, upload-time = "2025-10-02T14:35:25.111Z" }, - { url = "https://files.pythonhosted.org/packages/d7/6b/33e21afb1b5b3f46b74b6bd1913639066af218d704cc0941404ca717fc57/xxhash-3.6.0-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:fba27a198363a7ef87f8c0f6b171ec36b674fe9053742c58dd7e3201c1ab30ee", size = 196070, upload-time = "2025-10-02T14:35:26.586Z" }, - { url = "https://files.pythonhosted.org/packages/96/b6/fcabd337bc5fa624e7203aa0fa7d0c49eed22f72e93229431752bddc83d9/xxhash-3.6.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:794fe9145fe60191c6532fa95063765529770edcdd67b3d537793e8004cabbfd", size = 212907, upload-time = "2025-10-02T14:35:28.087Z" }, - { url = "https://files.pythonhosted.org/packages/4b/d3/9ee6160e644d660fcf176c5825e61411c7f62648728f69c79ba237250143/xxhash-3.6.0-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:6105ef7e62b5ac73a837778efc331a591d8442f8ef5c7e102376506cb4ae2729", size = 200839, upload-time = "2025-10-02T14:35:29.857Z" }, - { url = "https://files.pythonhosted.org/packages/0d/98/e8de5baa5109394baf5118f5e72ab21a86387c4f89b0e77ef3e2f6b0327b/xxhash-3.6.0-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:f01375c0e55395b814a679b3eea205db7919ac2af213f4a6682e01220e5fe292", size = 213304, upload-time = "2025-10-02T14:35:31.222Z" }, - { url = "https://files.pythonhosted.org/packages/7b/1d/71056535dec5c3177eeb53e38e3d367dd1d16e024e63b1cee208d572a033/xxhash-3.6.0-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:d706dca2d24d834a4661619dcacf51a75c16d65985718d6a7d73c1eeeb903ddf", size = 416930, upload-time = "2025-10-02T14:35:32.517Z" }, - { url = "https://files.pythonhosted.org/packages/dc/6c/5cbde9de2cd967c322e651c65c543700b19e7ae3e0aae8ece3469bf9683d/xxhash-3.6.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:5f059d9faeacd49c0215d66f4056e1326c80503f51a1532ca336a385edadd033", size = 193787, upload-time = "2025-10-02T14:35:33.827Z" }, - { url = "https://files.pythonhosted.org/packages/19/fa/0172e350361d61febcea941b0cc541d6e6c8d65d153e85f850a7b256ff8a/xxhash-3.6.0-cp313-cp313t-win32.whl", hash = "sha256:1244460adc3a9be84731d72b8e80625788e5815b68da3da8b83f78115a40a7ec", size = 30916, upload-time = "2025-10-02T14:35:35.107Z" }, - { url = "https://files.pythonhosted.org/packages/ad/e6/e8cf858a2b19d6d45820f072eff1bea413910592ff17157cabc5f1227a16/xxhash-3.6.0-cp313-cp313t-win_amd64.whl", hash = "sha256:b1e420ef35c503869c4064f4a2f2b08ad6431ab7b229a05cce39d74268bca6b8", size = 31799, upload-time = "2025-10-02T14:35:36.165Z" }, - { url = "https://files.pythonhosted.org/packages/56/15/064b197e855bfb7b343210e82490ae672f8bc7cdf3ddb02e92f64304ee8a/xxhash-3.6.0-cp313-cp313t-win_arm64.whl", hash = "sha256:ec44b73a4220623235f67a996c862049f375df3b1052d9899f40a6382c32d746", size = 28044, upload-time = "2025-10-02T14:35:37.195Z" }, - { url = "https://files.pythonhosted.org/packages/7e/5e/0138bc4484ea9b897864d59fce9be9086030825bc778b76cb5a33a906d37/xxhash-3.6.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:a40a3d35b204b7cc7643cbcf8c9976d818cb47befcfac8bbefec8038ac363f3e", size = 32754, upload-time = "2025-10-02T14:35:38.245Z" }, - { url = "https://files.pythonhosted.org/packages/18/d7/5dac2eb2ec75fd771957a13e5dda560efb2176d5203f39502a5fc571f899/xxhash-3.6.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:a54844be970d3fc22630b32d515e79a90d0a3ddb2644d8d7402e3c4c8da61405", size = 30846, upload-time = "2025-10-02T14:35:39.6Z" }, - { url = "https://files.pythonhosted.org/packages/fe/71/8bc5be2bb00deb5682e92e8da955ebe5fa982da13a69da5a40a4c8db12fb/xxhash-3.6.0-cp314-cp314-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:016e9190af8f0a4e3741343777710e3d5717427f175adfdc3e72508f59e2a7f3", size = 194343, upload-time = "2025-10-02T14:35:40.69Z" }, - { url = "https://files.pythonhosted.org/packages/e7/3b/52badfb2aecec2c377ddf1ae75f55db3ba2d321c5e164f14461c90837ef3/xxhash-3.6.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4f6f72232f849eb9d0141e2ebe2677ece15adfd0fa599bc058aad83c714bb2c6", size = 213074, upload-time = "2025-10-02T14:35:42.29Z" }, - { url = "https://files.pythonhosted.org/packages/a2/2b/ae46b4e9b92e537fa30d03dbc19cdae57ed407e9c26d163895e968e3de85/xxhash-3.6.0-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:63275a8aba7865e44b1813d2177e0f5ea7eadad3dd063a21f7cf9afdc7054063", size = 212388, upload-time = "2025-10-02T14:35:43.929Z" }, - { url = "https://files.pythonhosted.org/packages/f5/80/49f88d3afc724b4ac7fbd664c8452d6db51b49915be48c6982659e0e7942/xxhash-3.6.0-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:3cd01fa2aa00d8b017c97eb46b9a794fbdca53fc14f845f5a328c71254b0abb7", size = 445614, upload-time = "2025-10-02T14:35:45.216Z" }, - { url = "https://files.pythonhosted.org/packages/ed/ba/603ce3961e339413543d8cd44f21f2c80e2a7c5cfe692a7b1f2cccf58f3c/xxhash-3.6.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0226aa89035b62b6a86d3c68df4d7c1f47a342b8683da2b60cedcddb46c4d95b", size = 194024, upload-time = "2025-10-02T14:35:46.959Z" }, - { url = "https://files.pythonhosted.org/packages/78/d1/8e225ff7113bf81545cfdcd79eef124a7b7064a0bba53605ff39590b95c2/xxhash-3.6.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:c6e193e9f56e4ca4923c61238cdaced324f0feac782544eb4c6d55ad5cc99ddd", size = 210541, upload-time = "2025-10-02T14:35:48.301Z" }, - { url = "https://files.pythonhosted.org/packages/6f/58/0f89d149f0bad89def1a8dd38feb50ccdeb643d9797ec84707091d4cb494/xxhash-3.6.0-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:9176dcaddf4ca963d4deb93866d739a343c01c969231dbe21680e13a5d1a5bf0", size = 198305, upload-time = "2025-10-02T14:35:49.584Z" }, - { url = "https://files.pythonhosted.org/packages/11/38/5eab81580703c4df93feb5f32ff8fa7fe1e2c51c1f183ee4e48d4bb9d3d7/xxhash-3.6.0-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:c1ce4009c97a752e682b897aa99aef84191077a9433eb237774689f14f8ec152", size = 210848, upload-time = "2025-10-02T14:35:50.877Z" }, - { url = "https://files.pythonhosted.org/packages/5e/6b/953dc4b05c3ce678abca756416e4c130d2382f877a9c30a20d08ee6a77c0/xxhash-3.6.0-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:8cb2f4f679b01513b7adbb9b1b2f0f9cdc31b70007eaf9d59d0878809f385b11", size = 414142, upload-time = "2025-10-02T14:35:52.15Z" }, - { url = "https://files.pythonhosted.org/packages/08/a9/238ec0d4e81a10eb5026d4a6972677cbc898ba6c8b9dbaec12ae001b1b35/xxhash-3.6.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:653a91d7c2ab54a92c19ccf43508b6a555440b9be1bc8be553376778be7f20b5", size = 191547, upload-time = "2025-10-02T14:35:53.547Z" }, - { url = "https://files.pythonhosted.org/packages/f1/ee/3cf8589e06c2164ac77c3bf0aa127012801128f1feebf2a079272da5737c/xxhash-3.6.0-cp314-cp314-win32.whl", hash = "sha256:a756fe893389483ee8c394d06b5ab765d96e68fbbfe6fde7aa17e11f5720559f", size = 31214, upload-time = "2025-10-02T14:35:54.746Z" }, - { url = "https://files.pythonhosted.org/packages/02/5d/a19552fbc6ad4cb54ff953c3908bbc095f4a921bc569433d791f755186f1/xxhash-3.6.0-cp314-cp314-win_amd64.whl", hash = "sha256:39be8e4e142550ef69629c9cd71b88c90e9a5db703fecbcf265546d9536ca4ad", size = 32290, upload-time = "2025-10-02T14:35:55.791Z" }, - { url = "https://files.pythonhosted.org/packages/b1/11/dafa0643bc30442c887b55baf8e73353a344ee89c1901b5a5c54a6c17d39/xxhash-3.6.0-cp314-cp314-win_arm64.whl", hash = "sha256:25915e6000338999236f1eb68a02a32c3275ac338628a7eaa5a269c401995679", size = 28795, upload-time = "2025-10-02T14:35:57.162Z" }, - { url = "https://files.pythonhosted.org/packages/2c/db/0e99732ed7f64182aef4a6fb145e1a295558deec2a746265dcdec12d191e/xxhash-3.6.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:c5294f596a9017ca5a3e3f8884c00b91ab2ad2933cf288f4923c3fd4346cf3d4", size = 32955, upload-time = "2025-10-02T14:35:58.267Z" }, - { url = "https://files.pythonhosted.org/packages/55/f4/2a7c3c68e564a099becfa44bb3d398810cc0ff6749b0d3cb8ccb93f23c14/xxhash-3.6.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:1cf9dcc4ab9cff01dfbba78544297a3a01dafd60f3bde4e2bfd016cf7e4ddc67", size = 31072, upload-time = "2025-10-02T14:35:59.382Z" }, - { url = "https://files.pythonhosted.org/packages/c6/d9/72a29cddc7250e8a5819dad5d466facb5dc4c802ce120645630149127e73/xxhash-3.6.0-cp314-cp314t-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:01262da8798422d0685f7cef03b2bd3f4f46511b02830861df548d7def4402ad", size = 196579, upload-time = "2025-10-02T14:36:00.838Z" }, - { url = "https://files.pythonhosted.org/packages/63/93/b21590e1e381040e2ca305a884d89e1c345b347404f7780f07f2cdd47ef4/xxhash-3.6.0-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:51a73fb7cb3a3ead9f7a8b583ffd9b8038e277cdb8cb87cf890e88b3456afa0b", size = 215854, upload-time = "2025-10-02T14:36:02.207Z" }, - { url = "https://files.pythonhosted.org/packages/ce/b8/edab8a7d4fa14e924b29be877d54155dcbd8b80be85ea00d2be3413a9ed4/xxhash-3.6.0-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:b9c6df83594f7df8f7f708ce5ebeacfc69f72c9fbaaababf6cf4758eaada0c9b", size = 214965, upload-time = "2025-10-02T14:36:03.507Z" }, - { url = "https://files.pythonhosted.org/packages/27/67/dfa980ac7f0d509d54ea0d5a486d2bb4b80c3f1bb22b66e6a05d3efaf6c0/xxhash-3.6.0-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:627f0af069b0ea56f312fd5189001c24578868643203bca1abbc2c52d3a6f3ca", size = 448484, upload-time = "2025-10-02T14:36:04.828Z" }, - { url = "https://files.pythonhosted.org/packages/8c/63/8ffc2cc97e811c0ca5d00ab36604b3ea6f4254f20b7bc658ca825ce6c954/xxhash-3.6.0-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:aa912c62f842dfd013c5f21a642c9c10cd9f4c4e943e0af83618b4a404d9091a", size = 196162, upload-time = "2025-10-02T14:36:06.182Z" }, - { url = "https://files.pythonhosted.org/packages/4b/77/07f0e7a3edd11a6097e990f6e5b815b6592459cb16dae990d967693e6ea9/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:b465afd7909db30168ab62afe40b2fcf79eedc0b89a6c0ab3123515dc0df8b99", size = 213007, upload-time = "2025-10-02T14:36:07.733Z" }, - { url = "https://files.pythonhosted.org/packages/ae/d8/bc5fa0d152837117eb0bef6f83f956c509332ce133c91c63ce07ee7c4873/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_i686.whl", hash = "sha256:a881851cf38b0a70e7c4d3ce81fc7afd86fbc2a024f4cfb2a97cf49ce04b75d3", size = 200956, upload-time = "2025-10-02T14:36:09.106Z" }, - { url = "https://files.pythonhosted.org/packages/26/a5/d749334130de9411783873e9b98ecc46688dad5db64ca6e04b02acc8b473/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:9b3222c686a919a0f3253cfc12bb118b8b103506612253b5baeaac10d8027cf6", size = 213401, upload-time = "2025-10-02T14:36:10.585Z" }, - { url = "https://files.pythonhosted.org/packages/89/72/abed959c956a4bfc72b58c0384bb7940663c678127538634d896b1195c10/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_s390x.whl", hash = "sha256:c5aa639bc113e9286137cec8fadc20e9cd732b2cc385c0b7fa673b84fc1f2a93", size = 417083, upload-time = "2025-10-02T14:36:12.276Z" }, - { url = "https://files.pythonhosted.org/packages/0c/b3/62fd2b586283b7d7d665fb98e266decadf31f058f1cf6c478741f68af0cb/xxhash-3.6.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:5c1343d49ac102799905e115aee590183c3921d475356cb24b4de29a4bc56518", size = 193913, upload-time = "2025-10-02T14:36:14.025Z" }, - { url = "https://files.pythonhosted.org/packages/9a/9a/c19c42c5b3f5a4aad748a6d5b4f23df3bed7ee5445accc65a0fb3ff03953/xxhash-3.6.0-cp314-cp314t-win32.whl", hash = "sha256:5851f033c3030dd95c086b4a36a2683c2ff4a799b23af60977188b057e467119", size = 31586, upload-time = "2025-10-02T14:36:15.603Z" }, - { url = "https://files.pythonhosted.org/packages/03/d6/4cc450345be9924fd5dc8c590ceda1db5b43a0a889587b0ae81a95511360/xxhash-3.6.0-cp314-cp314t-win_amd64.whl", hash = "sha256:0444e7967dac37569052d2409b00a8860c2135cff05502df4da80267d384849f", size = 32526, upload-time = "2025-10-02T14:36:16.708Z" }, - { url = "https://files.pythonhosted.org/packages/0f/c9/7243eb3f9eaabd1a88a5a5acadf06df2d83b100c62684b7425c6a11bcaa8/xxhash-3.6.0-cp314-cp314t-win_arm64.whl", hash = "sha256:bb79b1e63f6fd84ec778a4b1916dfe0a7c3fdb986c06addd5db3a0d413819d95", size = 28898, upload-time = "2025-10-02T14:36:17.843Z" }, - { url = "https://files.pythonhosted.org/packages/93/1e/8aec23647a34a249f62e2398c42955acd9b4c6ed5cf08cbea94dc46f78d2/xxhash-3.6.0-pp311-pypy311_pp73-macosx_10_15_x86_64.whl", hash = "sha256:0f7b7e2ec26c1666ad5fc9dbfa426a6a3367ceaf79db5dd76264659d509d73b0", size = 30662, upload-time = "2025-10-02T14:37:01.743Z" }, - { url = "https://files.pythonhosted.org/packages/b8/0b/b14510b38ba91caf43006209db846a696ceea6a847a0c9ba0a5b1adc53d6/xxhash-3.6.0-pp311-pypy311_pp73-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:5dc1e14d14fa0f5789ec29a7062004b5933964bb9b02aae6622b8f530dc40296", size = 41056, upload-time = "2025-10-02T14:37:02.879Z" }, - { url = "https://files.pythonhosted.org/packages/50/55/15a7b8a56590e66ccd374bbfa3f9ffc45b810886c8c3b614e3f90bd2367c/xxhash-3.6.0-pp311-pypy311_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:881b47fc47e051b37d94d13e7455131054b56749b91b508b0907eb07900d1c13", size = 36251, upload-time = "2025-10-02T14:37:04.44Z" }, - { url = "https://files.pythonhosted.org/packages/62/b2/5ac99a041a29e58e95f907876b04f7067a0242cb85b5f39e726153981503/xxhash-3.6.0-pp311-pypy311_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c6dc31591899f5e5666f04cc2e529e69b4072827085c1ef15294d91a004bc1bd", size = 32481, upload-time = "2025-10-02T14:37:05.869Z" }, - { url = "https://files.pythonhosted.org/packages/7b/d9/8d95e906764a386a3d3b596f3c68bb63687dfca806373509f51ce8eea81f/xxhash-3.6.0-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:15e0dac10eb9309508bfc41f7f9deaa7755c69e35af835db9cb10751adebc35d", size = 31565, upload-time = "2025-10-02T14:37:06.966Z" }, -] - -[[package]] -name = "zstandard" -version = "0.25.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/fd/aa/3e0508d5a5dd96529cdc5a97011299056e14c6505b678fd58938792794b1/zstandard-0.25.0.tar.gz", hash = "sha256:7713e1179d162cf5c7906da876ec2ccb9c3a9dcbdffef0cc7f70c3667a205f0b", size = 711513, upload-time = "2025-09-14T22:15:54.002Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/2a/83/c3ca27c363d104980f1c9cee1101cc8ba724ac8c28a033ede6aab89585b1/zstandard-0.25.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:933b65d7680ea337180733cf9e87293cc5500cc0eb3fc8769f4d3c88d724ec5c", size = 795254, upload-time = "2025-09-14T22:16:26.137Z" }, - { url = "https://files.pythonhosted.org/packages/ac/4d/e66465c5411a7cf4866aeadc7d108081d8ceba9bc7abe6b14aa21c671ec3/zstandard-0.25.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a3f79487c687b1fc69f19e487cd949bf3aae653d181dfb5fde3bf6d18894706f", size = 640559, upload-time = "2025-09-14T22:16:27.973Z" }, - { url = "https://files.pythonhosted.org/packages/12/56/354fe655905f290d3b147b33fe946b0f27e791e4b50a5f004c802cb3eb7b/zstandard-0.25.0-cp311-cp311-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:0bbc9a0c65ce0eea3c34a691e3c4b6889f5f3909ba4822ab385fab9057099431", size = 5348020, upload-time = "2025-09-14T22:16:29.523Z" }, - { url = "https://files.pythonhosted.org/packages/3b/13/2b7ed68bd85e69a2069bcc72141d378f22cae5a0f3b353a2c8f50ef30c1b/zstandard-0.25.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:01582723b3ccd6939ab7b3a78622c573799d5d8737b534b86d0e06ac18dbde4a", size = 5058126, upload-time = "2025-09-14T22:16:31.811Z" }, - { url = "https://files.pythonhosted.org/packages/c9/dd/fdaf0674f4b10d92cb120ccff58bbb6626bf8368f00ebfd2a41ba4a0dc99/zstandard-0.25.0-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:5f1ad7bf88535edcf30038f6919abe087f606f62c00a87d7e33e7fc57cb69fcc", size = 5405390, upload-time = "2025-09-14T22:16:33.486Z" }, - { url = "https://files.pythonhosted.org/packages/0f/67/354d1555575bc2490435f90d67ca4dd65238ff2f119f30f72d5cde09c2ad/zstandard-0.25.0-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:06acb75eebeedb77b69048031282737717a63e71e4ae3f77cc0c3b9508320df6", size = 5452914, upload-time = "2025-09-14T22:16:35.277Z" }, - { url = "https://files.pythonhosted.org/packages/bb/1f/e9cfd801a3f9190bf3e759c422bbfd2247db9d7f3d54a56ecde70137791a/zstandard-0.25.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9300d02ea7c6506f00e627e287e0492a5eb0371ec1670ae852fefffa6164b072", size = 5559635, upload-time = "2025-09-14T22:16:37.141Z" }, - { url = "https://files.pythonhosted.org/packages/21/88/5ba550f797ca953a52d708c8e4f380959e7e3280af029e38fbf47b55916e/zstandard-0.25.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:bfd06b1c5584b657a2892a6014c2f4c20e0db0208c159148fa78c65f7e0b0277", size = 5048277, upload-time = "2025-09-14T22:16:38.807Z" }, - { url = "https://files.pythonhosted.org/packages/46/c0/ca3e533b4fa03112facbe7fbe7779cb1ebec215688e5df576fe5429172e0/zstandard-0.25.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:f373da2c1757bb7f1acaf09369cdc1d51d84131e50d5fa9863982fd626466313", size = 5574377, upload-time = "2025-09-14T22:16:40.523Z" }, - { url = "https://files.pythonhosted.org/packages/12/9b/3fb626390113f272abd0799fd677ea33d5fc3ec185e62e6be534493c4b60/zstandard-0.25.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:6c0e5a65158a7946e7a7affa6418878ef97ab66636f13353b8502d7ea03c8097", size = 4961493, upload-time = "2025-09-14T22:16:43.3Z" }, - { url = "https://files.pythonhosted.org/packages/cb/d3/23094a6b6a4b1343b27ae68249daa17ae0651fcfec9ed4de09d14b940285/zstandard-0.25.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:c8e167d5adf59476fa3e37bee730890e389410c354771a62e3c076c86f9f7778", size = 5269018, upload-time = "2025-09-14T22:16:45.292Z" }, - { url = "https://files.pythonhosted.org/packages/8c/a7/bb5a0c1c0f3f4b5e9d5b55198e39de91e04ba7c205cc46fcb0f95f0383c1/zstandard-0.25.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:98750a309eb2f020da61e727de7d7ba3c57c97cf6213f6f6277bb7fb42a8e065", size = 5443672, upload-time = "2025-09-14T22:16:47.076Z" }, - { url = "https://files.pythonhosted.org/packages/27/22/503347aa08d073993f25109c36c8d9f029c7d5949198050962cb568dfa5e/zstandard-0.25.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:22a086cff1b6ceca18a8dd6096ec631e430e93a8e70a9ca5efa7561a00f826fa", size = 5822753, upload-time = "2025-09-14T22:16:49.316Z" }, - { url = "https://files.pythonhosted.org/packages/e2/be/94267dc6ee64f0f8ba2b2ae7c7a2df934a816baaa7291db9e1aa77394c3c/zstandard-0.25.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:72d35d7aa0bba323965da807a462b0966c91608ef3a48ba761678cb20ce5d8b7", size = 5366047, upload-time = "2025-09-14T22:16:51.328Z" }, - { url = "https://files.pythonhosted.org/packages/7b/a3/732893eab0a3a7aecff8b99052fecf9f605cf0fb5fb6d0290e36beee47a4/zstandard-0.25.0-cp311-cp311-win32.whl", hash = "sha256:f5aeea11ded7320a84dcdd62a3d95b5186834224a9e55b92ccae35d21a8b63d4", size = 436484, upload-time = "2025-09-14T22:16:55.005Z" }, - { url = "https://files.pythonhosted.org/packages/43/a3/c6155f5c1cce691cb80dfd38627046e50af3ee9ddc5d0b45b9b063bfb8c9/zstandard-0.25.0-cp311-cp311-win_amd64.whl", hash = "sha256:daab68faadb847063d0c56f361a289c4f268706b598afbf9ad113cbe5c38b6b2", size = 506183, upload-time = "2025-09-14T22:16:52.753Z" }, - { url = "https://files.pythonhosted.org/packages/8c/3e/8945ab86a0820cc0e0cdbf38086a92868a9172020fdab8a03ac19662b0e5/zstandard-0.25.0-cp311-cp311-win_arm64.whl", hash = "sha256:22a06c5df3751bb7dc67406f5374734ccee8ed37fc5981bf1ad7041831fa1137", size = 462533, upload-time = "2025-09-14T22:16:53.878Z" }, - { url = "https://files.pythonhosted.org/packages/82/fc/f26eb6ef91ae723a03e16eddb198abcfce2bc5a42e224d44cc8b6765e57e/zstandard-0.25.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7b3c3a3ab9daa3eed242d6ecceead93aebbb8f5f84318d82cee643e019c4b73b", size = 795738, upload-time = "2025-09-14T22:16:56.237Z" }, - { url = "https://files.pythonhosted.org/packages/aa/1c/d920d64b22f8dd028a8b90e2d756e431a5d86194caa78e3819c7bf53b4b3/zstandard-0.25.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:913cbd31a400febff93b564a23e17c3ed2d56c064006f54efec210d586171c00", size = 640436, upload-time = "2025-09-14T22:16:57.774Z" }, - { url = "https://files.pythonhosted.org/packages/53/6c/288c3f0bd9fcfe9ca41e2c2fbfd17b2097f6af57b62a81161941f09afa76/zstandard-0.25.0-cp312-cp312-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:011d388c76b11a0c165374ce660ce2c8efa8e5d87f34996aa80f9c0816698b64", size = 5343019, upload-time = "2025-09-14T22:16:59.302Z" }, - { url = "https://files.pythonhosted.org/packages/1e/15/efef5a2f204a64bdb5571e6161d49f7ef0fffdbca953a615efbec045f60f/zstandard-0.25.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:6dffecc361d079bb48d7caef5d673c88c8988d3d33fb74ab95b7ee6da42652ea", size = 5063012, upload-time = "2025-09-14T22:17:01.156Z" }, - { url = "https://files.pythonhosted.org/packages/b7/37/a6ce629ffdb43959e92e87ebdaeebb5ac81c944b6a75c9c47e300f85abdf/zstandard-0.25.0-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:7149623bba7fdf7e7f24312953bcf73cae103db8cae49f8154dd1eadc8a29ecb", size = 5394148, upload-time = "2025-09-14T22:17:03.091Z" }, - { url = "https://files.pythonhosted.org/packages/e3/79/2bf870b3abeb5c070fe2d670a5a8d1057a8270f125ef7676d29ea900f496/zstandard-0.25.0-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:6a573a35693e03cf1d67799fd01b50ff578515a8aeadd4595d2a7fa9f3ec002a", size = 5451652, upload-time = "2025-09-14T22:17:04.979Z" }, - { url = "https://files.pythonhosted.org/packages/53/60/7be26e610767316c028a2cbedb9a3beabdbe33e2182c373f71a1c0b88f36/zstandard-0.25.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:5a56ba0db2d244117ed744dfa8f6f5b366e14148e00de44723413b2f3938a902", size = 5546993, upload-time = "2025-09-14T22:17:06.781Z" }, - { url = "https://files.pythonhosted.org/packages/85/c7/3483ad9ff0662623f3648479b0380d2de5510abf00990468c286c6b04017/zstandard-0.25.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:10ef2a79ab8e2974e2075fb984e5b9806c64134810fac21576f0668e7ea19f8f", size = 5046806, upload-time = "2025-09-14T22:17:08.415Z" }, - { url = "https://files.pythonhosted.org/packages/08/b3/206883dd25b8d1591a1caa44b54c2aad84badccf2f1de9e2d60a446f9a25/zstandard-0.25.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:aaf21ba8fb76d102b696781bddaa0954b782536446083ae3fdaa6f16b25a1c4b", size = 5576659, upload-time = "2025-09-14T22:17:10.164Z" }, - { url = "https://files.pythonhosted.org/packages/9d/31/76c0779101453e6c117b0ff22565865c54f48f8bd807df2b00c2c404b8e0/zstandard-0.25.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:1869da9571d5e94a85a5e8d57e4e8807b175c9e4a6294e3b66fa4efb074d90f6", size = 4953933, upload-time = "2025-09-14T22:17:11.857Z" }, - { url = "https://files.pythonhosted.org/packages/18/e1/97680c664a1bf9a247a280a053d98e251424af51f1b196c6d52f117c9720/zstandard-0.25.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:809c5bcb2c67cd0ed81e9229d227d4ca28f82d0f778fc5fea624a9def3963f91", size = 5268008, upload-time = "2025-09-14T22:17:13.627Z" }, - { url = "https://files.pythonhosted.org/packages/1e/73/316e4010de585ac798e154e88fd81bb16afc5c5cb1a72eeb16dd37e8024a/zstandard-0.25.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:f27662e4f7dbf9f9c12391cb37b4c4c3cb90ffbd3b1fb9284dadbbb8935fa708", size = 5433517, upload-time = "2025-09-14T22:17:16.103Z" }, - { url = "https://files.pythonhosted.org/packages/5b/60/dd0f8cfa8129c5a0ce3ea6b7f70be5b33d2618013a161e1ff26c2b39787c/zstandard-0.25.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:99c0c846e6e61718715a3c9437ccc625de26593fea60189567f0118dc9db7512", size = 5814292, upload-time = "2025-09-14T22:17:17.827Z" }, - { url = "https://files.pythonhosted.org/packages/fc/5f/75aafd4b9d11b5407b641b8e41a57864097663699f23e9ad4dbb91dc6bfe/zstandard-0.25.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:474d2596a2dbc241a556e965fb76002c1ce655445e4e3bf38e5477d413165ffa", size = 5360237, upload-time = "2025-09-14T22:17:19.954Z" }, - { url = "https://files.pythonhosted.org/packages/ff/8d/0309daffea4fcac7981021dbf21cdb2e3427a9e76bafbcdbdf5392ff99a4/zstandard-0.25.0-cp312-cp312-win32.whl", hash = "sha256:23ebc8f17a03133b4426bcc04aabd68f8236eb78c3760f12783385171b0fd8bd", size = 436922, upload-time = "2025-09-14T22:17:24.398Z" }, - { url = "https://files.pythonhosted.org/packages/79/3b/fa54d9015f945330510cb5d0b0501e8253c127cca7ebe8ba46a965df18c5/zstandard-0.25.0-cp312-cp312-win_amd64.whl", hash = "sha256:ffef5a74088f1e09947aecf91011136665152e0b4b359c42be3373897fb39b01", size = 506276, upload-time = "2025-09-14T22:17:21.429Z" }, - { url = "https://files.pythonhosted.org/packages/ea/6b/8b51697e5319b1f9ac71087b0af9a40d8a6288ff8025c36486e0c12abcc4/zstandard-0.25.0-cp312-cp312-win_arm64.whl", hash = "sha256:181eb40e0b6a29b3cd2849f825e0fa34397f649170673d385f3598ae17cca2e9", size = 462679, upload-time = "2025-09-14T22:17:23.147Z" }, - { url = "https://files.pythonhosted.org/packages/35/0b/8df9c4ad06af91d39e94fa96cc010a24ac4ef1378d3efab9223cc8593d40/zstandard-0.25.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:ec996f12524f88e151c339688c3897194821d7f03081ab35d31d1e12ec975e94", size = 795735, upload-time = "2025-09-14T22:17:26.042Z" }, - { url = "https://files.pythonhosted.org/packages/3f/06/9ae96a3e5dcfd119377ba33d4c42a7d89da1efabd5cb3e366b156c45ff4d/zstandard-0.25.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a1a4ae2dec3993a32247995bdfe367fc3266da832d82f8438c8570f989753de1", size = 640440, upload-time = "2025-09-14T22:17:27.366Z" }, - { url = "https://files.pythonhosted.org/packages/d9/14/933d27204c2bd404229c69f445862454dcc101cd69ef8c6068f15aaec12c/zstandard-0.25.0-cp313-cp313-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:e96594a5537722fdfb79951672a2a63aec5ebfb823e7560586f7484819f2a08f", size = 5343070, upload-time = "2025-09-14T22:17:28.896Z" }, - { url = "https://files.pythonhosted.org/packages/6d/db/ddb11011826ed7db9d0e485d13df79b58586bfdec56e5c84a928a9a78c1c/zstandard-0.25.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:bfc4e20784722098822e3eee42b8e576b379ed72cca4a7cb856ae733e62192ea", size = 5063001, upload-time = "2025-09-14T22:17:31.044Z" }, - { url = "https://files.pythonhosted.org/packages/db/00/87466ea3f99599d02a5238498b87bf84a6348290c19571051839ca943777/zstandard-0.25.0-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:457ed498fc58cdc12fc48f7950e02740d4f7ae9493dd4ab2168a47c93c31298e", size = 5394120, upload-time = "2025-09-14T22:17:32.711Z" }, - { url = "https://files.pythonhosted.org/packages/2b/95/fc5531d9c618a679a20ff6c29e2b3ef1d1f4ad66c5e161ae6ff847d102a9/zstandard-0.25.0-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:fd7a5004eb1980d3cefe26b2685bcb0b17989901a70a1040d1ac86f1d898c551", size = 5451230, upload-time = "2025-09-14T22:17:34.41Z" }, - { url = "https://files.pythonhosted.org/packages/63/4b/e3678b4e776db00f9f7b2fe58e547e8928ef32727d7a1ff01dea010f3f13/zstandard-0.25.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:8e735494da3db08694d26480f1493ad2cf86e99bdd53e8e9771b2752a5c0246a", size = 5547173, upload-time = "2025-09-14T22:17:36.084Z" }, - { url = "https://files.pythonhosted.org/packages/4e/d5/ba05ed95c6b8ec30bd468dfeab20589f2cf709b5c940483e31d991f2ca58/zstandard-0.25.0-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:3a39c94ad7866160a4a46d772e43311a743c316942037671beb264e395bdd611", size = 5046736, upload-time = "2025-09-14T22:17:37.891Z" }, - { url = "https://files.pythonhosted.org/packages/50/d5/870aa06b3a76c73eced65c044b92286a3c4e00554005ff51962deef28e28/zstandard-0.25.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:172de1f06947577d3a3005416977cce6168f2261284c02080e7ad0185faeced3", size = 5576368, upload-time = "2025-09-14T22:17:40.206Z" }, - { url = "https://files.pythonhosted.org/packages/5d/35/398dc2ffc89d304d59bc12f0fdd931b4ce455bddf7038a0a67733a25f550/zstandard-0.25.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:3c83b0188c852a47cd13ef3bf9209fb0a77fa5374958b8c53aaa699398c6bd7b", size = 4954022, upload-time = "2025-09-14T22:17:41.879Z" }, - { url = "https://files.pythonhosted.org/packages/9a/5c/36ba1e5507d56d2213202ec2b05e8541734af5f2ce378c5d1ceaf4d88dc4/zstandard-0.25.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:1673b7199bbe763365b81a4f3252b8e80f44c9e323fc42940dc8843bfeaf9851", size = 5267889, upload-time = "2025-09-14T22:17:43.577Z" }, - { url = "https://files.pythonhosted.org/packages/70/e8/2ec6b6fb7358b2ec0113ae202647ca7c0e9d15b61c005ae5225ad0995df5/zstandard-0.25.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:0be7622c37c183406f3dbf0cba104118eb16a4ea7359eeb5752f0794882fc250", size = 5433952, upload-time = "2025-09-14T22:17:45.271Z" }, - { url = "https://files.pythonhosted.org/packages/7b/01/b5f4d4dbc59ef193e870495c6f1275f5b2928e01ff5a81fecb22a06e22fb/zstandard-0.25.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:5f5e4c2a23ca271c218ac025bd7d635597048b366d6f31f420aaeb715239fc98", size = 5814054, upload-time = "2025-09-14T22:17:47.08Z" }, - { url = "https://files.pythonhosted.org/packages/b2/e5/fbd822d5c6f427cf158316d012c5a12f233473c2f9c5fe5ab1ae5d21f3d8/zstandard-0.25.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:4f187a0bb61b35119d1926aee039524d1f93aaf38a9916b8c4b78ac8514a0aaf", size = 5360113, upload-time = "2025-09-14T22:17:48.893Z" }, - { url = "https://files.pythonhosted.org/packages/8e/e0/69a553d2047f9a2c7347caa225bb3a63b6d7704ad74610cb7823baa08ed7/zstandard-0.25.0-cp313-cp313-win32.whl", hash = "sha256:7030defa83eef3e51ff26f0b7bfb229f0204b66fe18e04359ce3474ac33cbc09", size = 436936, upload-time = "2025-09-14T22:17:52.658Z" }, - { url = "https://files.pythonhosted.org/packages/d9/82/b9c06c870f3bd8767c201f1edbdf9e8dc34be5b0fbc5682c4f80fe948475/zstandard-0.25.0-cp313-cp313-win_amd64.whl", hash = "sha256:1f830a0dac88719af0ae43b8b2d6aef487d437036468ef3c2ea59c51f9d55fd5", size = 506232, upload-time = "2025-09-14T22:17:50.402Z" }, - { url = "https://files.pythonhosted.org/packages/d4/57/60c3c01243bb81d381c9916e2a6d9e149ab8627c0c7d7abb2d73384b3c0c/zstandard-0.25.0-cp313-cp313-win_arm64.whl", hash = "sha256:85304a43f4d513f5464ceb938aa02c1e78c2943b29f44a750b48b25ac999a049", size = 462671, upload-time = "2025-09-14T22:17:51.533Z" }, - { url = "https://files.pythonhosted.org/packages/3d/5c/f8923b595b55fe49e30612987ad8bf053aef555c14f05bb659dd5dbe3e8a/zstandard-0.25.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:e29f0cf06974c899b2c188ef7f783607dbef36da4c242eb6c82dcd8b512855e3", size = 795887, upload-time = "2025-09-14T22:17:54.198Z" }, - { url = "https://files.pythonhosted.org/packages/8d/09/d0a2a14fc3439c5f874042dca72a79c70a532090b7ba0003be73fee37ae2/zstandard-0.25.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:05df5136bc5a011f33cd25bc9f506e7426c0c9b3f9954f056831ce68f3b6689f", size = 640658, upload-time = "2025-09-14T22:17:55.423Z" }, - { url = "https://files.pythonhosted.org/packages/5d/7c/8b6b71b1ddd517f68ffb55e10834388d4f793c49c6b83effaaa05785b0b4/zstandard-0.25.0-cp314-cp314-manylinux2010_i686.manylinux_2_12_i686.manylinux_2_28_i686.whl", hash = "sha256:f604efd28f239cc21b3adb53eb061e2a205dc164be408e553b41ba2ffe0ca15c", size = 5379849, upload-time = "2025-09-14T22:17:57.372Z" }, - { url = "https://files.pythonhosted.org/packages/a4/86/a48e56320d0a17189ab7a42645387334fba2200e904ee47fc5a26c1fd8ca/zstandard-0.25.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:223415140608d0f0da010499eaa8ccdb9af210a543fac54bce15babbcfc78439", size = 5058095, upload-time = "2025-09-14T22:17:59.498Z" }, - { url = "https://files.pythonhosted.org/packages/f8/ad/eb659984ee2c0a779f9d06dbfe45e2dc39d99ff40a319895df2d3d9a48e5/zstandard-0.25.0-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:2e54296a283f3ab5a26fc9b8b5d4978ea0532f37b231644f367aa588930aa043", size = 5551751, upload-time = "2025-09-14T22:18:01.618Z" }, - { url = "https://files.pythonhosted.org/packages/61/b3/b637faea43677eb7bd42ab204dfb7053bd5c4582bfe6b1baefa80ac0c47b/zstandard-0.25.0-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:ca54090275939dc8ec5dea2d2afb400e0f83444b2fc24e07df7fdef677110859", size = 6364818, upload-time = "2025-09-14T22:18:03.769Z" }, - { url = "https://files.pythonhosted.org/packages/31/dc/cc50210e11e465c975462439a492516a73300ab8caa8f5e0902544fd748b/zstandard-0.25.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:e09bb6252b6476d8d56100e8147b803befa9a12cea144bbe629dd508800d1ad0", size = 5560402, upload-time = "2025-09-14T22:18:05.954Z" }, - { url = "https://files.pythonhosted.org/packages/c9/ae/56523ae9c142f0c08efd5e868a6da613ae76614eca1305259c3bf6a0ed43/zstandard-0.25.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:a9ec8c642d1ec73287ae3e726792dd86c96f5681eb8df274a757bf62b750eae7", size = 4955108, upload-time = "2025-09-14T22:18:07.68Z" }, - { url = "https://files.pythonhosted.org/packages/98/cf/c899f2d6df0840d5e384cf4c4121458c72802e8bda19691f3b16619f51e9/zstandard-0.25.0-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:a4089a10e598eae6393756b036e0f419e8c1d60f44a831520f9af41c14216cf2", size = 5269248, upload-time = "2025-09-14T22:18:09.753Z" }, - { url = "https://files.pythonhosted.org/packages/1b/c0/59e912a531d91e1c192d3085fc0f6fb2852753c301a812d856d857ea03c6/zstandard-0.25.0-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:f67e8f1a324a900e75b5e28ffb152bcac9fbed1cc7b43f99cd90f395c4375344", size = 5430330, upload-time = "2025-09-14T22:18:11.966Z" }, - { url = "https://files.pythonhosted.org/packages/a0/1d/7e31db1240de2df22a58e2ea9a93fc6e38cc29353e660c0272b6735d6669/zstandard-0.25.0-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:9654dbc012d8b06fc3d19cc825af3f7bf8ae242226df5f83936cb39f5fdc846c", size = 5811123, upload-time = "2025-09-14T22:18:13.907Z" }, - { url = "https://files.pythonhosted.org/packages/f6/49/fac46df5ad353d50535e118d6983069df68ca5908d4d65b8c466150a4ff1/zstandard-0.25.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:4203ce3b31aec23012d3a4cf4a2ed64d12fea5269c49aed5e4c3611b938e4088", size = 5359591, upload-time = "2025-09-14T22:18:16.465Z" }, - { url = "https://files.pythonhosted.org/packages/c2/38/f249a2050ad1eea0bb364046153942e34abba95dd5520af199aed86fbb49/zstandard-0.25.0-cp314-cp314-win32.whl", hash = "sha256:da469dc041701583e34de852d8634703550348d5822e66a0c827d39b05365b12", size = 444513, upload-time = "2025-09-14T22:18:20.61Z" }, - { url = "https://files.pythonhosted.org/packages/3a/43/241f9615bcf8ba8903b3f0432da069e857fc4fd1783bd26183db53c4804b/zstandard-0.25.0-cp314-cp314-win_amd64.whl", hash = "sha256:c19bcdd826e95671065f8692b5a4aa95c52dc7a02a4c5a0cac46deb879a017a2", size = 516118, upload-time = "2025-09-14T22:18:17.849Z" }, - { url = "https://files.pythonhosted.org/packages/f0/ef/da163ce2450ed4febf6467d77ccb4cd52c4c30ab45624bad26ca0a27260c/zstandard-0.25.0-cp314-cp314-win_arm64.whl", hash = "sha256:d7541afd73985c630bafcd6338d2518ae96060075f9463d7dc14cfb33514383d", size = 476940, upload-time = "2025-09-14T22:18:19.088Z" }, -] diff --git a/internal/golden/pydantic-ai-v1/pydantic_ai_test.py b/internal/golden/pydantic-ai-v1/pydantic_ai_test.py deleted file mode 100644 index c6d80a756..000000000 --- a/internal/golden/pydantic-ai-v1/pydantic_ai_test.py +++ /dev/null @@ -1,912 +0,0 @@ -# pyright: reportUnknownMemberType=none -# pyright: reportUnknownVariableType=none -# pyright: reportUnknownParameterType=none -# pyright: reportUnknownArgumentType=none -import asyncio -from collections.abc import AsyncIterator -from pathlib import Path - -import braintrust -from braintrust import traced -from braintrust.wrappers.pydantic_ai import setup_pydantic_ai -from pydantic import BaseModel -from pydantic_ai import Agent, BinaryContent, ModelSettings -from pydantic_ai.direct import model_request, model_request_stream -from pydantic_ai.messages import ( - ModelMessage, - ModelRequest, - ModelResponse, - TextPart, - UserPromptPart, -) -from pydantic_ai.models.openai import OpenAIChatModel, OpenAIResponsesModel, OpenAIResponsesModelSettings - -setup_pydantic_ai(project_name="golden-py-pydantic_ai") - -FIXTURES_DIR = Path(__file__).parent.parent / "fixtures" - - -# Test 1: Basic completion -@traced -async def test_basic_completion(): - print("\n=== Test 1: Basic Completion ===") - - # High-level Agent API - print("\n--- Agent completion ---") - agent = Agent( - "openai:gpt-4o", - model_settings=ModelSettings(max_tokens=100), - ) - result = await agent.run("What is the capital of France?") - print(result.output) - - # Another agent with different settings - print("\n--- Agent completion with different settings ---") - agent2 = Agent( - "openai:gpt-4o", - model_settings=ModelSettings(max_tokens=100, temperature=0.7), - ) - result2 = await agent2.run("What is the capital of Spain?") - print(result2.output) - - # Low-level Direct API - print("\n--- Direct API completion ---") - model = OpenAIChatModel("gpt-4o") - messages: list[ModelMessage] = [ModelRequest(parts=[UserPromptPart(content="What is the capital of Italy?")])] - direct_result = await model_request(model=model, messages=messages) - print(direct_result.parts[0].content) - - # Low-level Direct API with model_settings - print("\n--- Direct API with model_settings ---") - settings = ModelSettings(max_tokens=50, temperature=0.8) - messages_with_settings: list[ModelMessage] = [ModelRequest(parts=[UserPromptPart(content="Say hello in 5 words")])] - direct_result_settings = await model_request(model=model, messages=messages_with_settings, model_settings=settings) - print(f"Result: {direct_result_settings.parts[0].content}") - print( - f"Usage: input={direct_result_settings.usage.input_tokens}, output={direct_result_settings.usage.output_tokens}" - ) - - -# Test 2: Multi-turn conversation -@traced -async def test_multi_turn(): - print("\n=== Test 2: Multi-turn Conversation ===") - agent = Agent( - "openai:gpt-4o", - model_settings=ModelSettings(max_tokens=200), - ) - - # Simulate a multi-turn conversation by passing message history - message_history = [ - ModelRequest(parts=[UserPromptPart(content="Hi, my name is Alice.")]), - ModelResponse(parts=[TextPart(content="Hello Alice! Nice to meet you.")]), - ] - result = await agent.run( - "What did I just tell you my name was?", - message_history=message_history, - ) - print(result.output) - - -# Test 3: System prompt -@traced -async def test_system_prompt(): - print("\n=== Test 3: System Prompt ===") - - print("\n--- System prompt (pirate) ---") - agent = Agent( - "openai:gpt-4o", - system_prompt="You are a pirate. Always respond in pirate speak.", - model_settings=ModelSettings(max_tokens=150), - ) - result = await agent.run("Tell me about the weather.") - print(result.output) - - -# Test 4: Streaming response -@traced -async def test_streaming(): - print("\n=== Test 4: Streaming ===") - - # Use identical settings and prompt for all calls to verify offset consistency - IDENTICAL_PROMPT = "Count from 1 to 5." - IDENTICAL_SETTINGS = ModelSettings(max_tokens=100) - - # Group 1: Complete streaming (no early breaks) - with braintrust.start_span(name="Complete streaming (calls 1-4)") as complete_span: - # High-level Agent API - Call 1 - print("\n--- Agent streaming (call 1) ---") - agent1 = Agent( - "openai:gpt-4o", - model_settings=IDENTICAL_SETTINGS, - ) - full_text1 = "" - async with agent1.run_stream(IDENTICAL_PROMPT) as result1: - async for text in result1.stream_text(delta=True): - print(text, end="", flush=True) - full_text1 += text - print("\n") - - # High-level Agent API - Call 2 (identical to call 1) - print("\n--- Agent streaming (call 2 - identical) ---") - agent2 = Agent( - "openai:gpt-4o", - model_settings=IDENTICAL_SETTINGS, - ) - full_text2 = "" - async with agent2.run_stream(IDENTICAL_PROMPT) as result2: - async for text in result2.stream_text(delta=True): - print(text, end="", flush=True) - full_text2 += text - print("\n") - - print("\n--- Direct API streaming (call 3 - identical) ---") - model = OpenAIChatModel("gpt-4o") - messages: list[ModelMessage] = [ModelRequest(parts=[UserPromptPart(content=IDENTICAL_PROMPT)])] - - direct_text = "" - seen_delta = False - async with model_request_stream(model=model, messages=messages, model_settings=IDENTICAL_SETTINGS) as stream: - async for chunk in stream: - # Handle PartStartEvent which contains initial text (only if we haven't seen deltas yet) - if hasattr(chunk, "part") and hasattr(chunk.part, "content") and not seen_delta: - text = str(chunk.part.content) - print(text, end="", flush=True) - direct_text += text - # Handle PartDeltaEvent with delta content - elif hasattr(chunk, "delta") and chunk.delta: - seen_delta = True - # Extract content_delta from TextPartDelta - if hasattr(chunk.delta, "content_delta") and chunk.delta.content_delta: - text = chunk.delta.content_delta - print(text, end="", flush=True) - direct_text += text - elif isinstance(chunk.delta, str): - # Handle case where delta is already a string - print(chunk.delta, end="", flush=True) - direct_text += chunk.delta - - print("\n") - - print("\n--- Direct API streaming (call 4 - identical) ---") - messages_4: list[ModelMessage] = [ModelRequest(parts=[UserPromptPart(content=IDENTICAL_PROMPT)])] - - direct_text_4 = "" - seen_delta_4 = False - async with model_request_stream( - model=model, messages=messages_4, model_settings=IDENTICAL_SETTINGS - ) as stream_4: - async for chunk in stream_4: - # Handle PartStartEvent which contains initial text (only if we haven't seen deltas yet) - if hasattr(chunk, "part") and hasattr(chunk.part, "content") and not seen_delta_4: - text = str(chunk.part.content) - print(text, end="", flush=True) - direct_text_4 += text - # Handle PartDeltaEvent with delta content - elif hasattr(chunk, "delta") and chunk.delta: - seen_delta_4 = True - # Extract content_delta from TextPartDelta - if hasattr(chunk.delta, "content_delta") and chunk.delta.content_delta: - text = chunk.delta.content_delta - print(text, end="", flush=True) - direct_text_4 += text - elif isinstance(chunk.delta, str): - # Handle case where delta is already a string - print(chunk.delta, end="", flush=True) - direct_text_4 += chunk.delta - - print("\n") - - # Group 2: Streaming with early break (calls 5-6) - with braintrust.start_span(name="Streaming with early break (calls 5-6)") as break_span: - # Low-level Direct API with early break (same context - usually works) - print("\n--- Direct API streaming with early break (call 5 - identical) ---") - early_break_model = OpenAIChatModel("gpt-4o") - early_break_messages: list[ModelMessage] = [ModelRequest(parts=[UserPromptPart(content=IDENTICAL_PROMPT)])] - - early_break_status = "unknown" - early_break_text = "" - try: - async with model_request_stream( - model=early_break_model, messages=early_break_messages, model_settings=IDENTICAL_SETTINGS - ) as stream: - i = 0 - seen_delta_5 = False - async for chunk in stream: - # Handle PartStartEvent which contains initial text (only if we haven't seen deltas yet) - if hasattr(chunk, "part") and hasattr(chunk.part, "content") and not seen_delta_5: - text = str(chunk.part.content) - print(text, end="", flush=True) - early_break_text += text - # Handle PartDeltaEvent with delta content - elif hasattr(chunk, "delta") and chunk.delta: - seen_delta_5 = True - if hasattr(chunk.delta, "content_delta") and chunk.delta.content_delta: - text = chunk.delta.content_delta - print(text, end="", flush=True) - early_break_text += text - elif isinstance(chunk.delta, str): - print(chunk.delta, end="", flush=True) - early_break_text += chunk.delta - - i += 1 - - # Early break - within same context, usually OK - if i >= 3: - print("\nโš ๏ธ Breaking early from stream...") - break - - print("โœ“ Completed without error") - early_break_status = "success" - except Exception as e: - print(f"โœ— Error occurred: {type(e).__name__}: {e}") - early_break_status = f"error: {type(e).__name__}" - - # Customer's pattern: Async generator with early break (triggers context error!) - print("\n--- CUSTOMER PATTERN: Async generator with early break (call 6 - identical) ---") - print("(This reproduces: 'Token was created in a different Context' error)") - generator_status = "unknown" - generator_text = "" - try: - i = 0 - - # Inline the async generator pattern - model_gen = OpenAIChatModel("gpt-4o-mini") - messages_gen: list[ModelMessage] = [ModelRequest(parts=[UserPromptPart(content=IDENTICAL_PROMPT)])] - - seen_delta_6 = False - async with model_request_stream(model=model_gen, messages=messages_gen) as stream_gen: - # Yield streaming chunks - async for event in stream_gen: - # Handle PartStartEvent which contains initial text (only if we haven't seen deltas yet) - if hasattr(event, "part") and hasattr(event.part, "content") and not seen_delta_6: - text = str(event.part.content) - print(text, end="", flush=True) - generator_text += text - # Handle PartDeltaEvent with delta content - elif hasattr(event, "delta") and event.delta: - seen_delta_6 = True - if hasattr(event.delta, "content_delta") and event.delta.content_delta: - text = event.delta.content_delta - print(text, end="", flush=True) - generator_text += text - elif isinstance(event.delta, str): - print(event.delta, end="", flush=True) - generator_text += event.delta - - i += 1 - - # Early break - generator closed in different context โ†’ ERROR! - if i >= 3: - print("\nโš ๏ธ Breaking early from async generator...") - break - - print("โœ“ Completed without error") - generator_status = "success" - except Exception as e: - print(f"โœ— Error occurred: {type(e).__name__}: {e}") - generator_status = f"error: {type(e).__name__}" - - # Group 3: _stream_single/_buffer_stream pattern (call 7) - with braintrust.start_span(name="_stream_single/_buffer_stream pattern (call 7)"): - # Customer pattern 2: _stream_single/_buffer_stream pattern - # This pattern uses an async generator that yields chunks AND a final response, - # with a consumer that returns early when it sees the final ModelResponse - print("\n--- CUSTOMER PATTERN 2: _stream_single/_buffer_stream (call 7) ---") - print("(Generator yields chunks + final response, consumer returns on ModelResponse)") - - class LLMStreamResponse: - """Simple wrapper for streaming responses.""" - - def __init__(self, llm_response: object, is_final: bool = False): - self.llm_response = llm_response - self.is_final = is_final - - # @traced - async def _stream_single() -> AsyncIterator[LLMStreamResponse]: - """Async generator that yields streaming chunks and final response.""" - model_stream = OpenAIChatModel("gpt-4o-mini") - messages_stream: list[ModelMessage] = [ModelRequest(parts=[UserPromptPart(content=IDENTICAL_PROMPT)])] - - async with model_request_stream( - model=model_stream, messages=messages_stream, model_settings=IDENTICAL_SETTINGS - ) as stream: - async for chunk in stream: - yield LLMStreamResponse(llm_response=chunk, is_final=False) - - response = stream.get() - yield LLMStreamResponse(llm_response=response, is_final=True) - - async def _buffer_stream() -> LLMStreamResponse: - """Consumer that returns early when it gets a ModelResponse.""" - async for event in _stream_single(): - if isinstance(event.llm_response, ModelResponse): - return event - raise RuntimeError("No ModelResponse received") - - try: - result = await _buffer_stream() - print(f"โœ“ Received final response: {type(result.llm_response).__name__}") - except Exception as e: - print(f"โœ— Error occurred: {type(e).__name__}: {e}") - - -# Test 5: Image input -@traced -async def test_image_input(): - print("\n=== Test 5: Image Input ===") - image_path = FIXTURES_DIR / "test-image.png" - - agent = Agent( - "openai:gpt-4o", - model_settings=ModelSettings(max_tokens=150), - ) - - with open(image_path, "rb") as f: - image_data = f.read() - - result = await agent.run( - [ - BinaryContent(data=image_data, media_type="image/png"), - "What color is this image?", - ] - ) - print(result.output) - - -# Test 6: Document input -@traced -async def test_document_input(): - print("\n=== Test 6: Document Input ===") - pdf_path = FIXTURES_DIR / "test-document.pdf" - - agent = Agent( - "openai:gpt-4o", - model_settings=ModelSettings(max_tokens=150), - ) - - with open(pdf_path, "rb") as f: - pdf_data = f.read() - - result = await agent.run( - [ - BinaryContent(data=pdf_data, media_type="application/pdf"), - "What is in this document?", - ] - ) - print(result.output) - - -# Test 7: Temperature variations -@traced -async def test_temperature_variations(): - print("\n=== Test 7: Temperature Variations ===") - - configs = [ - {"temperature": 0.0, "top_p": 1.0}, - {"temperature": 1.0, "top_p": 0.9}, - {"temperature": 0.7, "top_p": 0.95}, - ] - - results = [] - for config in configs: - print(f"\nConfig: temp={config['temperature']}, top_p={config['top_p']}") - - agent = Agent( - "openai:gpt-4o", - ) - - result = await agent.run( - "Say something creative.", - model_settings=ModelSettings( - max_tokens=50, - temperature=config["temperature"], - top_p=config["top_p"], - ), - ) - print(result.output) - results.append(result) - - -# Test 8: Stop sequences -@traced -async def test_stop_sequences(): - print("\n=== Test 8: Stop Sequences ===") - agent = Agent( - "openai:gpt-4o", - model_settings=ModelSettings( - max_tokens=500, - stop_sequences=["END", "\n\n"], - ), - ) - - result = await agent.run("Write a short story about a robot.") - print(result.output) - - -# Test 9: Metadata -@traced -async def test_metadata(): - print("\n=== Test 9: Metadata ===") - agent = Agent( - "openai:gpt-4o", - model_settings=ModelSettings(max_tokens=100), - ) - - result = await agent.run("Hello!", deps="test_user_123") - print(result.output) - - -# Test 10: Long context -@traced -async def test_long_context(): - print("\n=== Test 10: Long Context ===") - agent = Agent( - "openai:gpt-4o", - model_settings=ModelSettings(max_tokens=100), - ) - - long_text = "The quick brown fox jumps over the lazy dog. " * 100 - result = await agent.run(f"Here is a long text:\n\n{long_text}\n\nHow many times does the word 'fox' appear?") - print(result.output) - - -# Test 11: Mixed content types -@traced -async def test_mixed_content(): - print("\n=== Test 11: Mixed Content Types ===") - image_path = FIXTURES_DIR / "test-image.png" - - agent = Agent( - "openai:gpt-4o", - model_settings=ModelSettings(max_tokens=200), - ) - - with open(image_path, "rb") as f: - image_data = f.read() - - result = await agent.run( - [ - "First, look at this image:", - BinaryContent(data=image_data, media_type="image/png"), - "Now describe what you see and explain why it matters.", - ] - ) - print(result.output) - - -# Test 12: Prefill -@traced -async def test_prefill(): - print("\n=== Test 12: Prefill ===") - agent = Agent( - "openai:gpt-4o", - model_settings=ModelSettings(max_tokens=200), - ) - - # Simulate prefill by providing partial assistant response in message history - prefill_history = [ - ModelRequest(parts=[UserPromptPart(content="Write a haiku about coding.")]), - ModelResponse(parts=[TextPart(content="Here is a haiku:")]), - ] - - result = await agent.run( - "Write a haiku about coding.", - message_history=prefill_history, - ) - print(f"Response: {result.output}") - - -# Test 13: Very short max_tokens -@traced -async def test_short_max_tokens(): - print("\n=== Test 13: Very Short Max Tokens ===") - agent = Agent( - "openai:gpt-4o", - ) - - result = await agent.run( - "What is AI?", - model_settings=ModelSettings(max_tokens=5), - ) - print(result.output) - - -# Test 14: Tool use -@traced -async def test_tool_use(): - print("\n=== Test 14: Tool Use ===") - - agent = Agent( - "openai:gpt-4o", - model_settings=ModelSettings(max_tokens=500), - ) - - @agent.tool_plain - def get_weather(city_and_state: str, unit: str = "celsius") -> str: - """Get the current weather for a location. - - Args: - city_and_state: The city and state, e.g. San Francisco, CA - unit: The unit of temperature (celsius or fahrenheit). Default to celsius. - """ - return f"22 degrees {unit} and sunny in {city_and_state}" - - result = await agent.run("What is the weather like in Paris, France?") - print("Response content:") - print(result.output) - - -# Test 15: Tool use with result (multi-turn) -@traced -async def test_tool_use_with_result(): - print("\n=== Test 15: Tool Use With Result ===") - - agent = Agent( - "openai:gpt-4o", - model_settings=ModelSettings(max_tokens=500), - ) - - @agent.tool_plain - def calculate(operation: str, a: float, b: float) -> str: - """Perform a mathematical calculation. - - Args: - operation: The mathematical operation (add, subtract, multiply, divide) - a: First number - b: Second number - """ - ops = { - "add": a + b, - "subtract": a - b, - "multiply": a * b, - "divide": a / b if b != 0 else "Error: Division by zero", - } - return str(ops.get(operation, "Invalid operation")) - - # First request - agent will use the tool - print("First request:") - first_result = await agent.run("What is 127 multiplied by 49?", message_history=[]) - - # Show the message history structure - messages = first_result.all_messages() - print(f"\nMessage history after first request contains {len(messages)} messages:") - for i, msg in enumerate(messages): - msg_type = type(msg).__name__ - if hasattr(msg, "parts") and len(msg.parts) > 0: - part = msg.parts[0] - if hasattr(part, "tool_name"): - print(f" {i}: {msg_type} - Tool call: {part.tool_name}") - elif hasattr(part, "content"): - content_preview = str(part.content)[:50] - print(f" {i}: {msg_type} - Content: {content_preview}") - else: - print(f" {i}: {msg_type}") - - # Second request - provide the message history so agent sees the tool result - print("\nSecond request (with tool result in history):") - second_result = await agent.run("Thanks! Can you also tell me what 127 plus 49 is?", message_history=messages) - print("Response (with previous tool result in context):") - print(second_result.output) - - -# Test 16: Reasoning tokens generation and follow-up -@traced -async def test_reasoning(): - print("\n=== Test 16: Reasoning Tokens & Follow-up ===") - - # First request: Analyze pattern and derive formula - print("\n--- First request (generate reasoning) ---") - model = OpenAIResponsesModel("gpt-5-codex") - agent = Agent( - model, - model_settings=OpenAIResponsesModelSettings( - openai_reasoning_effort="high", - openai_reasoning_summary="detailed", - ), - ) - - first_result = await agent.run( - "Look at this sequence: 2, 6, 12, 20, 30. What is the pattern and what would be the formula for the nth term?" - ) - print("First response:") - print(first_result.output) - - # Second request: Apply the discovered pattern to solve a new problem - # Get all_messages() which includes the user prompt, reasoning, and response - print("\n--- Follow-up request (using reasoning context) ---") - message_history = first_result.all_messages() - print(f"Message history contains {len(message_history)} messages") - - follow_up_result = await agent.run( - "Using the pattern you discovered, what would be the 10th term? And can you find the sum of the first 10 terms?", - message_history=message_history, - ) - print("Follow-up response:") - print(follow_up_result.output) - - -# Test 18: Embeddings -# Skipped - Pydantic AI focuses on agent/chat interactions and doesn't wrap the embeddings API. -# The OpenAI test includes embeddings because it tests the full OpenAI client wrapper. - - -# Test 19: Response format (JSON schema) -# Skipped - Pydantic AI handles structured output through result_type with Pydantic models, -# which is more type-safe than the OpenAI response_format parameter. We test this approach -# in Tests 21-23 (structured output tests). - - -# Test 20: Multiple completions (n > 1) -# Skipped - Pydantic AI is designed for agent-based workflows and doesn't support the OpenAI -# 'n' parameter for generating multiple completions in a single request. - - -# Test 21: Structured output -@traced -async def test_structured_output(): - print("\n=== Test 21: Structured Output ===") - - class Ingredient(BaseModel): - name: str - amount: str - - class Recipe(BaseModel): - name: str - ingredients: list[Ingredient] - steps: list[str] - - agent = Agent( - "openai:gpt-4o", - system_prompt="You extract structured information from user queries.", - output_type=Recipe, - model_settings=ModelSettings(max_tokens=500), - retries=3, - ) - - result = await agent.run("Generate a simple recipe for chocolate chip cookies.") - recipe = result.output - print("Parsed recipe:") - print(f"Name: {recipe.name}") - print(f"Ingredients: {len(recipe.ingredients)}") - print(f"Steps: {len(recipe.steps)}") - - -# Test 22: Streaming structured output -@traced -async def test_streaming_structured_output(): - print("\n=== Test 22: Streaming Structured Output ===") - - class Product(BaseModel): - name: str - description: str - price: float - features: list[str] - - agent = Agent( - "openai:gpt-4o", - output_type=Product, - model_settings=ModelSettings(max_tokens=500), - retries=3, - ) - - # With structured output, we can't stream text - we stream the structure - # The stream completes when the full structured output is validated - async with agent.run_stream("Generate a product description for a wireless bluetooth headphone.") as result: - # Wait for the stream to complete and get the structured result - product = await result.get_output() - - print("Streaming completed") - print(f"Product: {product.name}") - print(f"Price: ${product.price}") - print(f"Features: {len(product.features)}") - - -# Test 23: Structured output with context -@traced -async def test_structured_output_with_context(): - print("\n=== Test 23: Structured Output with Context ===") - - class PriceComparison(BaseModel): - cheaper: str - price_difference: float - - class Comparison(BaseModel): - recommendation: str - reasoning: str - price_comparison: PriceComparison - phone_rating: float - laptop_rating: float - - agent = Agent( - "openai:gpt-4o", - system_prompt="You are a helpful shopping assistant. Use the provided product information to make recommendations.", - output_type=Comparison, - model_settings=ModelSettings(max_tokens=500), - retries=3, - ) - - product_info = { - "phone-123": { - "name": "SuperPhone X", - "price": 999, - "specs": "6.5 inch display, 128GB storage, 12MP camera", - }, - "laptop-456": { - "name": "ProBook Ultra", - "price": 1499, - "specs": "15 inch display, 512GB SSD, 16GB RAM", - }, - } - - reviews = { - "phone-123": { - "rating": 4.5, - "comments": ["Great camera!", "Battery lasts all day", "A bit pricey"], - }, - "laptop-456": { - "rating": 4.2, - "comments": ["Fast performance", "Good display", "Heavy to carry"], - }, - } - - result = await agent.run( - f"""Compare phone-123 and laptop-456. Here is the product info and reviews: - -Product Info: -- phone-123: {product_info["phone-123"]} -- laptop-456: {product_info["laptop-456"]} - -Reviews: -- phone-123: {reviews["phone-123"]} -- laptop-456: {reviews["laptop-456"]} - -Give me a structured comparison with your recommendation.""" - ) - - comparison = result.output - print("Product comparison:") - print(f"Recommendation: {comparison.recommendation}") - print(f"Reasoning: {comparison.reasoning}") - print(f"Cheaper: {comparison.price_comparison.cheaper}") - print(f"Price difference: ${comparison.price_comparison.price_difference}") - print(f"Phone rating: {comparison.phone_rating}") - print(f"Laptop rating: {comparison.laptop_rating}") - - -# Test 24: Error handling -@traced -async def test_error_handling(): - print("\n=== Test 24: Error Handling ===") - - # Test 1: Invalid image URL (404) - # Note: Pydantic AI's BinaryContent doesn't have from_url, so we test with a simulated fetch - @traced(name="test_error_invalid_image_url") - async def test_invalid_image_url(): - print("\n--- Test 1: Invalid Image URL ---") - try: - import httpx - - # Attempt to fetch invalid image - will fail with 404 - async with httpx.AsyncClient() as client: - response = await client.get("https://example.com/nonexistent-image-404.jpg") - image_data = response.content - - agent = Agent( - "openai:gpt-4o", - model_settings=ModelSettings(max_tokens=100), - ) - await agent.run( - [ - BinaryContent(data=image_data, media_type="image/jpeg"), - "What's in this image?", - ], - ) - raise Exception("Should have thrown an error") - except httpx.HTTPStatusError as e: - print(f"Caught HTTP error (expected):") - print(f" Type: {type(e).__name__}") - print(f" Status: {e.response.status_code}") - except Exception as e: - print(f"Caught error:") - print(f" Type: {type(e).__name__}") - print(f" Message: {e}") - - await test_invalid_image_url() - - # Test 2: Tool choice for non-existent function - # Skipped - Pydantic AI doesn't expose low-level tool_choice parameter like OpenAI. - # Tool selection is handled automatically by the agent. - - # Test 3: Tool call ID mismatch - # Skipped - Pydantic AI abstracts away tool call IDs. This low-level OpenAI API - # detail is not exposed in Pydantic AI's agent interface. - - # Test 4: Corrupted base64 image data - @traced(name="test_error_corrupted_base64_image") - async def test_corrupted_image(): - print("\n--- Test 4: Corrupted Base64 Image ---") - try: - agent = Agent( - "openai:gpt-4o", - model_settings=ModelSettings(max_tokens=100), - ) - await agent.run( - [ - BinaryContent( - data=b"INVALID_BASE64_DATA!!!", - media_type="image/png", - ), - "What's in this image?", - ], - ) - raise Exception("Should have thrown an error") - except Exception as e: - print(f"Caught corrupted image error:") - print(f" Type: {type(e).__name__}") - print(f" Message: {e}") - - await test_corrupted_image() - - # Test 5: Invalid JSON schema in response_format - # Skipped - Pydantic AI uses Pydantic models for structured output, not JSON schemas. - # Schema validation errors would occur at the Pydantic model level, which is tested - # in the structured output tests (21-23). - - print("\nError handling tests completed") - - -async def run_async_tests(): - """Run all asynchronous tests.""" - tests = [ - test_basic_completion, - test_multi_turn, - test_system_prompt, - test_streaming, - test_image_input, - test_document_input, - test_temperature_variations, - test_stop_sequences, - test_metadata, - test_long_context, - test_mixed_content, - test_prefill, - test_short_max_tokens, - test_tool_use, - test_tool_use_with_result, - test_reasoning, - test_structured_output, - test_streaming_structured_output, - test_structured_output_with_context, - test_error_handling, - ] - - for test in tests: - try: - await test() - # Rate limiting - await asyncio.sleep(1) - except Exception as e: - print(f"Test {test.__name__} failed: {e}") - import traceback - - traceback.print_exc() - - -async def main(): - """Run all tests.""" - print("=" * 60) - print("Pydantic AI Golden Tests with Braintrust") - print("=" * 60) - - # Run all async tests - print("\n### Running Pydantic AI Agent Tests ###") - await run_async_tests() - - print("\n" + "=" * 60) - print("All tests completed!") - print("=" * 60) - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/internal/golden/pydantic-ai-v1/pyproject.toml b/internal/golden/pydantic-ai-v1/pyproject.toml deleted file mode 100644 index b10d3b49a..000000000 --- a/internal/golden/pydantic-ai-v1/pyproject.toml +++ /dev/null @@ -1,13 +0,0 @@ -[project] -name = "golden" -version = "0.1.0" -description = "Add your description here" -readme = "README.md" -requires-python = ">=3.11" -dependencies = [ - "braintrust", - "pydantic-ai", -] - -[tool.uv.sources] -braintrust = { path = "../../py", editable = true } diff --git a/js/.eslintignore b/js/.eslintignore deleted file mode 100644 index 65df30ef6..000000000 --- a/js/.eslintignore +++ /dev/null @@ -1,24 +0,0 @@ -# Dependencies -node_modules/ - -# Build outputs -dist/ -dev/dist/ -util/dist/ - -# Vendor libraries -vendor/ - -# Test files and examples -examples/ -scripts/ - -# Turbo cache -.turbo/ - -# Documentation -docs/ - -# Test wrapper directories -test-ai-sdk-wrapper/ -vercel/ diff --git a/js/CLAUDE.md b/js/CLAUDE.md index 69483485d..c4deea798 100644 --- a/js/CLAUDE.md +++ b/js/CLAUDE.md @@ -24,15 +24,15 @@ pnpm build ## Linting & Formatting -```bash -pnpm prettier --write -pnpm eslint -``` - -Or from sdk root: +From the sdk root: ```bash -make fixup # Run pre-commit hooks on all files +pnpm run lint # Check formatting + eslint +pnpm run fix # Auto-fix formatting + eslint +pnpm run lint:prettier # Check formatting only +pnpm run lint:eslint # Run eslint only +pnpm run fix:prettier # Auto-fix formatting only +pnpm run fix:eslint # Auto-fix eslint only ``` ## Before Committing @@ -40,12 +40,12 @@ make fixup # Run pre-commit hooks on all files Always run formatting before committing to avoid pre-commit hook failures: ```bash -pnpm prettier --write . # Format all files +pnpm run fix:prettier # Format all files ``` ## Test Framework -Uses Vitest. Config in `vitest.config.js`. Tests make real API calls (no VCR/cassettes). +Uses Vitest. Config in `vitest.config.js`. Tests make real API calls. ```bash # Required env vars for wrapper tests diff --git a/js/docs/interfaces/_meta.json b/js/docs/interfaces/_meta.json index 6fb386ead..8dcc4eec0 100644 --- a/js/docs/interfaces/_meta.json +++ b/js/docs/interfaces/_meta.json @@ -1,5 +1,5 @@ { - "ExperimentSummary": "ExperimentSummary", - "ScoreSummary": "ScoreSummary", - "Evaluator": "Evaluator" + "ExperimentSummary": "ExperimentSummary", + "ScoreSummary": "ScoreSummary", + "Evaluator": "Evaluator" } diff --git a/js/eslint.config.ts b/js/eslint.config.ts index 31b778ffd..d75d38091 100644 --- a/js/eslint.config.ts +++ b/js/eslint.config.ts @@ -19,6 +19,26 @@ const entryFiles = tsupConfig .filter((entry) => !entry.includes("cli")); export default [ + { + ignores: [ + "dist/**", + "dev/dist/**", + "util/dist/**", + "node_modules/**", + "vendor/**", + "examples/**", + "scripts/**", + ".turbo/**", + "docs/**", + "test-ai-sdk-wrapper/**", + "vercel/**", + // TODO: Add these back once tsconfig.json includes them, so that + // typed linting (and all other config blocks) can run on them too. + "**/*.test.ts", + "**/*.test.tsx", + "src/auto-instrumentations/**", + ], + }, { files: ["src/**/*.ts", "src/**/*.tsx"], languageOptions: { @@ -36,8 +56,11 @@ export default [ rules: { // Base TypeScript rules ...tseslint.configs.recommended.rules, + // TODO: Fix violations and re-enable as "error" + "@typescript-eslint/no-explicit-any": "warn", + // TODO: Fix violations and re-enable as "error" "@typescript-eslint/no-unused-vars": [ - "error", + "warn", { vars: "all", args: "none", @@ -46,16 +69,25 @@ export default [ varsIgnorePattern: "^_", }, ], - "prefer-const": "error", + // TODO: Fix violations and re-enable as "error" + "prefer-const": "warn", "@typescript-eslint/ban-types": "off", "@typescript-eslint/ban-ts-comment": "off", "@typescript-eslint/no-require-imports": "off", + // TODO: Fix violations and re-enable as "error" "@typescript-eslint/consistent-type-assertions": [ - "error", + "warn", { assertionStyle: "never" }, ], - "no-unused-expressions": ["error", { allowShortCircuit: true }], + // TODO: Fix violations and re-enable as "error" + "no-unused-expressions": ["warn", { allowShortCircuit: true }], "@typescript-eslint/no-unused-expressions": "off", + // TODO: Fix violations and re-enable as "error" + "@typescript-eslint/no-empty-object-type": "warn", + // TODO: Fix violations and re-enable as "error" + "@typescript-eslint/no-unsafe-function-type": "warn", + // TODO: Fix violations and re-enable as "error" + "@typescript-eslint/prefer-as-const": "warn", // Require node: protocol for Node.js built-in imports (for Deno compatibility) // This plugin automatically detects ALL Node.js built-ins - no manual list needed! "node-import/prefer-node-protocol": "error", @@ -121,8 +153,9 @@ export default [ "@typescript-eslint": tseslint, }, rules: { + // TODO: Fix violations and re-enable as "error" "no-restricted-syntax": [ - "error", + "warn", { selector: "ExportAllDeclaration[exported=null]", message: diff --git a/js/package.json b/js/package.json index e8fb48105..b808cce2c 100644 --- a/js/package.json +++ b/js/package.json @@ -40,7 +40,7 @@ "require": "./dist/workerd.js", "default": "./dist/workerd.mjs" }, - "./edge-light": { + "./edge-light": { "import": "./dist/edge-light.mjs", "require": "./dist/edge-light.js", "default": "./dist/edge-light.mjs" @@ -124,7 +124,9 @@ "test:zod-v4": "vitest run src/zod/zod-v4-serialization.test.ts", "test:mastra": "vitest run src/wrappers/mastra.test.ts", "test:claude-agent-sdk": "vitest run src/wrappers/claude-agent-sdk.test.ts", - "test:output": "tsx scripts/test-output.ts --with-comparison --with-metrics --with-progress" + "test:output": "tsx scripts/test-output.ts --with-comparison --with-metrics --with-progress", + "lint": "eslint .", + "fix:eslint": "eslint --fix ." }, "author": "", "license": "MIT", @@ -157,7 +159,6 @@ "jiti": "^2.6.1", "npm-run-all": "^4.1.5", "openapi-zod-client": "^1.18.3", - "prettier": "^3.5.3", "rollup": "^4.28.1", "vite": "^5.4.14", "webpack": "^5.97.1", diff --git a/js/smoke/scenarios/deno-browser/deno.json b/js/smoke/scenarios/deno-browser/deno.json index 2849e7456..4e38fc8f6 100644 --- a/js/smoke/scenarios/deno-browser/deno.json +++ b/js/smoke/scenarios/deno-browser/deno.json @@ -5,8 +5,5 @@ "braintrust": "npm:braintrust" }, "nodeModulesDir": "auto", - "links": [ - "../../..", - "../../shared" - ] + "links": ["../../..", "../../shared"] } diff --git a/js/smoke/scenarios/deno-node/deno.json b/js/smoke/scenarios/deno-node/deno.json index 2849e7456..4e38fc8f6 100644 --- a/js/smoke/scenarios/deno-node/deno.json +++ b/js/smoke/scenarios/deno-node/deno.json @@ -5,8 +5,5 @@ "braintrust": "npm:braintrust" }, "nodeModulesDir": "auto", - "links": [ - "../../..", - "../../shared" - ] + "links": ["../../..", "../../shared"] } diff --git a/js/smoke/shared/deno.json b/js/smoke/shared/deno.json index fd4550289..a9cbb8888 100644 --- a/js/smoke/shared/deno.json +++ b/js/smoke/shared/deno.json @@ -1,6 +1,6 @@ { - "name": "@braintrust/smoke-test-shared", - "exports": { - ".": "./src/index.ts" - } + "name": "@braintrust/smoke-test-shared", + "exports": { + ".": "./src/index.ts" + } } diff --git a/js/src/browser/config.ts b/js/src/browser/config.ts index 19173d442..c19cf9866 100644 --- a/js/src/browser/config.ts +++ b/js/src/browser/config.ts @@ -4,7 +4,7 @@ import { registry } from "../instrumentation/registry"; // This is copied from next.js. It seems they define AsyncLocalStorage in the edge // environment, even though it's not defined in the browser. -import type { AsyncLocalStorage as NodeAsyncLocalStorage } from "async_hooks"; +import type { AsyncLocalStorage as NodeAsyncLocalStorage } from "node:async_hooks"; declare global { var AsyncLocalStorage: typeof NodeAsyncLocalStorage; diff --git a/js/src/cli/functions/infer-source.ts b/js/src/cli/functions/infer-source.ts index d9c2a033a..563e57087 100644 --- a/js/src/cli/functions/infer-source.ts +++ b/js/src/cli/functions/infer-source.ts @@ -1,9 +1,9 @@ import { SourceMapConsumer } from "source-map"; -import * as fs from "fs/promises"; +import * as fs from "node:fs/promises"; import { EvaluatorFile, warning } from "../../framework"; import { loadModule } from "./load-module"; import { type CodeBundleType as CodeBundle } from "../../generated_types"; -import path from "path"; +import path from "node:path"; import type { Node } from "typescript"; interface SourceMapContext { diff --git a/js/src/cli/functions/load-module.ts b/js/src/cli/functions/load-module.ts index 8551da92c..593b45ae7 100644 --- a/js/src/cli/functions/load-module.ts +++ b/js/src/cli/functions/load-module.ts @@ -1,5 +1,5 @@ import nodeModulesPaths from "../jest/nodeModulesPaths"; -import path, { dirname } from "path"; +import path, { dirname } from "node:path"; import { _internalGetGlobalState } from "../../logger"; import { EvaluatorFile } from "../../framework"; diff --git a/js/src/cli/functions/upload.ts b/js/src/cli/functions/upload.ts index 3c63ecfc3..78b11a4ac 100644 --- a/js/src/cli/functions/upload.ts +++ b/js/src/cli/functions/upload.ts @@ -14,9 +14,9 @@ import { FailedHTTPResponse, } from "../../logger"; import * as esbuild from "esbuild"; -import fs from "fs"; -import path from "path"; -import { createGzip } from "zlib"; +import fs from "node:fs"; +import path from "node:path"; +import { createGzip } from "node:zlib"; import { addAzureBlobHeaders, isEmpty } from "../../util"; import { z } from "zod/v3"; import { capitalize } from "../../../util/index"; diff --git a/js/src/cli/index.ts b/js/src/cli/index.ts index af479d5a4..c6df48132 100755 --- a/js/src/cli/index.ts +++ b/js/src/cli/index.ts @@ -2,10 +2,10 @@ import * as esbuild from "esbuild"; import * as dotenv from "dotenv"; -import fs from "fs"; -import os from "os"; -import path from "path"; -import util from "util"; +import fs from "node:fs"; +import os from "node:os"; +import path from "node:path"; +import util from "node:util"; import * as fsWalk from "@nodelib/fs.walk"; import { minimatch } from "minimatch"; import { ArgumentParser } from "argparse"; diff --git a/js/src/cli/jest/nodeModulesPaths.ts b/js/src/cli/jest/nodeModulesPaths.ts index 4f3474e84..17deb466c 100644 --- a/js/src/cli/jest/nodeModulesPaths.ts +++ b/js/src/cli/jest/nodeModulesPaths.ts @@ -7,7 +7,7 @@ * Adapted from: https://github.com/substack/node-resolve */ -import * as path from "path"; +import * as path from "node:path"; // BRAINTRUST: This was changed to be a relative import import tryRealpath from "./tryRealpath"; diff --git a/js/src/cli/util/pull.ts b/js/src/cli/util/pull.ts index aa8461e83..91dbe3033 100644 --- a/js/src/cli/util/pull.ts +++ b/js/src/cli/util/pull.ts @@ -11,10 +11,10 @@ import { loadCLIEnv } from "./bundle"; import { PullArgs } from "./types"; import { warning } from "../../framework"; import { z } from "zod/v3"; -import fs from "fs/promises"; -import util from "util"; +import fs from "node:fs/promises"; +import util from "node:util"; import { slugify } from "../../../util/string_util"; -import path from "path"; +import path from "node:path"; import { currentRepo } from "../../gitutil"; import { isEmpty, loadPrettyXact, prettifyXact } from "../../../util/index"; import { diff --git a/js/src/edge-light/config.ts b/js/src/edge-light/config.ts index d4583f794..b5feeef37 100644 --- a/js/src/edge-light/config.ts +++ b/js/src/edge-light/config.ts @@ -1,7 +1,7 @@ import iso from "../isomorph"; import { _internalSetInitialState } from "../logger"; -import type { AsyncLocalStorage as NodeAsyncLocalStorage } from "async_hooks"; +import type { AsyncLocalStorage as NodeAsyncLocalStorage } from "node:async_hooks"; declare global { var AsyncLocalStorage: typeof NodeAsyncLocalStorage; diff --git a/js/src/framework.ts b/js/src/framework.ts index 98909c4a4..e7cfc9ee7 100644 --- a/js/src/framework.ts +++ b/js/src/framework.ts @@ -1043,7 +1043,7 @@ async function runEvaluatorInternal( objectId: parentComponents?.data.object_id ?? (experimentIdPromise - ? (await experimentIdPromise) ?? "" + ? ((await experimentIdPromise) ?? "") : ""), rootSpanId: rootSpan.rootSpanId, ensureSpansFlushed, diff --git a/js/src/logger.ts b/js/src/logger.ts index db0887a79..c348056c0 100644 --- a/js/src/logger.ts +++ b/js/src/logger.ts @@ -7535,7 +7535,6 @@ export class RemoteEvalParameters< typeof x === "object" && x !== null && "__braintrust_parameters_marker" in x && - // eslint-disable-next-line @typescript-eslint/consistent-type-assertions ( x as unknown as RemoteEvalParameters< boolean, diff --git a/js/src/workerd/config.ts b/js/src/workerd/config.ts index fe7be3659..53c84ce07 100644 --- a/js/src/workerd/config.ts +++ b/js/src/workerd/config.ts @@ -1,6 +1,6 @@ import iso from "../isomorph"; import { _internalSetInitialState } from "../logger"; -import type { AsyncLocalStorage as NodeAsyncLocalStorage } from "async_hooks"; +import type { AsyncLocalStorage as NodeAsyncLocalStorage } from "node:async_hooks"; declare global { var AsyncLocalStorage: typeof NodeAsyncLocalStorage; diff --git a/js/src/wrappers/anthropic.ts b/js/src/wrappers/anthropic.ts index c98315548..b778bd773 100644 --- a/js/src/wrappers/anthropic.ts +++ b/js/src/wrappers/anthropic.ts @@ -31,7 +31,6 @@ export function wrapAnthropic(anthropic: T): T { } } -// eslint-disable-next-line @typescript-eslint/no-explicit-any function anthropicProxy(anthropic: any): any { return new Proxy(anthropic, { get(target, prop, receiver) { @@ -47,7 +46,6 @@ function anthropicProxy(anthropic: any): any { }); } -// eslint-disable-next-line @typescript-eslint/no-explicit-any function betaProxy(beta: any) { return new Proxy(beta, { get(target, prop, receiver) { @@ -59,7 +57,6 @@ function betaProxy(beta: any) { }); } -// eslint-disable-next-line @typescript-eslint/no-explicit-any function messagesProxy(messages: any) { return new Proxy(messages, { get(target, prop, receiver) { @@ -77,7 +74,6 @@ function messagesProxy(messages: any) { }); } -// eslint-disable-next-line @typescript-eslint/no-explicit-any function createProxy(create: (params: any) => Promise) { return new Proxy(create, { apply(target, thisArg, argArray) { @@ -108,7 +104,6 @@ function createProxy(create: (params: any) => Promise) { // Actually do the call. const apiPromise = Reflect.apply(target, thisArg, argArray); - // eslint-disable-next-line @typescript-eslint/no-explicit-any const onThen: ThenFn = function (msgOrStream: any) { // handle the sync interface create(stream=False) if (!args["stream"]) { @@ -139,7 +134,6 @@ function createProxy(create: (params: any) => Promise) { type ThenFn = Promise["then"]; function apiPromiseProxy( - // eslint-disable-next-line @typescript-eslint/no-explicit-any apiPromise: any, span: StartedSpan, onThen: ThenFn, @@ -149,11 +143,11 @@ function apiPromiseProxy( if (prop === "then") { // This path is used with messages.create(stream=True) calls. const thenFunc = Reflect.get(target, prop, receiver); - // eslint-disable-next-line @typescript-eslint/no-explicit-any + return function (onFulfilled: any, onRejected: any) { return thenFunc.call( target, - // eslint-disable-next-line @typescript-eslint/no-explicit-any + async (result: any) => { try { const processed = onThen(result); @@ -169,7 +163,6 @@ function apiPromiseProxy( // This path is used with messages.stream(...) calls. const withResponseFunc = Reflect.get(target, prop, receiver); return () => { - // eslint-disable-next-line @typescript-eslint/no-explicit-any return withResponseFunc.call(target).then((withResponse: any) => { if (withResponse["data"]) { const { data: stream } = withResponse; @@ -246,18 +239,16 @@ function streamProxy( }); } -// eslint-disable-next-line @typescript-eslint/no-explicit-any function streamNextProxy(stream: AsyncIterator, sspan: StartedSpan) { // this is where we actually do the business of iterating the message stream let ttft = -1; let metadata = {}; let totals: Metrics = {}; const span = sspan.span; - // eslint-disable-next-line @typescript-eslint/no-explicit-any + const contentBlocks: any[] = []; const contentBlockDeltas: Record = {}; - // eslint-disable-next-line @typescript-eslint/no-explicit-any return async function (...args: [any]): Promise> { const result = await stream.next(...args); @@ -360,7 +351,7 @@ type Metrics = Record; type MetricsOrUndefined = Metrics | undefined; // Parse the event from given anthropic Message. -// eslint-disable-next-line @typescript-eslint/no-explicit-any + function parseEventFromMessage(message: any) { // FIXME[matt] the whole content or just the text? const output = message @@ -383,7 +374,7 @@ function parseEventFromMessage(message: any) { } // Parse the metrics from the usage object. -// eslint-disable-next-line @typescript-eslint/no-explicit-any + function parseMetricsFromUsage(usage: any): MetricsOrUndefined { if (!usage) { return undefined; @@ -476,7 +467,6 @@ function processAttachmentsInInput(input: any): any { return input; } -// eslint-disable-next-line @typescript-eslint/no-explicit-any function coalesceInput(messages: any[], system: string | undefined) { // convert anthropic args to the single "input" field Braintrust expects. diff --git a/js/src/wrappers/claude-agent-sdk/claude-agent-sdk.ts b/js/src/wrappers/claude-agent-sdk/claude-agent-sdk.ts index 36be7f882..d1dfb7f31 100644 --- a/js/src/wrappers/claude-agent-sdk/claude-agent-sdk.ts +++ b/js/src/wrappers/claude-agent-sdk/claude-agent-sdk.ts @@ -571,7 +571,7 @@ function wrapClaudeAgentQuery< // interrupt() right after query() without consuming any messages first. const invocationTarget: unknown = thisArg === proxy || thisArg === undefined - ? defaultThis ?? thisArg + ? (defaultThis ?? thisArg) : thisArg; // Track active tool spans for hook-based tracing diff --git a/js/src/wrappers/oai.ts b/js/src/wrappers/oai.ts index 39c1a9229..ae38c662c 100644 --- a/js/src/wrappers/oai.ts +++ b/js/src/wrappers/oai.ts @@ -34,7 +34,6 @@ interface OpenAILike { } declare global { - // eslint-disable-next-line no-var, @typescript-eslint/no-explicit-any var __inherited_braintrust_wrap_openai: ((openai: any) => any) | undefined; } diff --git a/js/util/span_identifier_v4.ts b/js/util/span_identifier_v4.ts index 8382bc9f1..8988087a4 100644 --- a/js/util/span_identifier_v4.ts +++ b/js/util/span_identifier_v4.ts @@ -334,7 +334,7 @@ export function makeScorerPropagatedEvent( parent: string | undefined, ): Record { const parentPropagatedEvent = parent - ? SpanComponentsV4.fromStr(parent).data.propagated_event ?? {} + ? (SpanComponentsV4.fromStr(parent).data.propagated_event ?? {}) : {}; return mergeDicts( { ...parentPropagatedEvent }, diff --git a/mise.toml b/mise.toml index 219098189..f328d72fe 100644 --- a/mise.toml +++ b/mise.toml @@ -4,16 +4,11 @@ experimental = true [env] -# Automatically activate our virtual environment -_.python.venv = { path = "venv", create = true, uv_create_args = ['--seed']} - # See env.example to configure API keys. _.file = ".env" [tools] -ruff = "0.12.7" -uv = "latest" pnpm = "10.26.2" [hooks] -postinstall = "make install-deps" +postinstall = "pnpm install" diff --git a/package.json b/package.json index 61f1bf8c0..5f6b55b62 100644 --- a/package.json +++ b/package.json @@ -12,17 +12,29 @@ "dev": "turbo run dev", "watch": "turbo run watch", "start": "turbo run start", - "lint": "turbo run lint", "clean": "turbo run clean", - "test": "turbo run test --filter=\"!@braintrust/otel\"" + "test": "turbo run test --filter=\"!@braintrust/otel\"", + "prepare": "husky", + "lint:prettier": "prettier --check .", + "lint:eslint": "turbo run lint", + "fix:prettier": "prettier --write .", + "fix:eslint": "turbo run fix:eslint", + "lint": "pnpm run lint:prettier && pnpm run lint:eslint", + "fix": "pnpm run fix:prettier && pnpm run fix:eslint" }, "devDependencies": { - "pyright": "^1.1.404", + "eslint": "^9.39.2", + "husky": "^9.1.7", + "lint-staged": "^16.2.7", + "prettier": "^3.5.3", "turbo": "^2.5.6" }, "overrides": { "zod": "3.25.34", "tsup": "8.4.0" }, + "lint-staged": { + "*.{js,jsx,ts,tsx,mjs,cjs,css,md,mdx,html,yaml,yml}": "prettier --write" + }, "packageManager": "pnpm@10.26.2" } diff --git a/pnpm-lock.yaml b/pnpm-lock.yaml index 1cce3e7d2..35550c5ed 100644 --- a/pnpm-lock.yaml +++ b/pnpm-lock.yaml @@ -8,9 +8,18 @@ importers: .: devDependencies: - pyright: - specifier: ^1.1.404 - version: 1.1.404 + eslint: + specifier: ^9.39.2 + version: 9.39.2(jiti@2.6.1) + husky: + specifier: ^9.1.7 + version: 9.1.7 + lint-staged: + specifier: ^16.2.7 + version: 16.2.7 + prettier: + specifier: ^3.5.3 + version: 3.5.3 turbo: specifier: ^2.5.6 version: 2.5.6 @@ -409,9 +418,6 @@ importers: openapi-zod-client: specifier: ^1.18.3 version: 1.18.3(react@19.1.1) - prettier: - specifier: ^3.5.3 - version: 3.5.3 rollup: specifier: ^4.28.1 version: 4.35.0 @@ -2730,6 +2736,10 @@ packages: resolution: {integrity: sha512-gKXj5ALrKWQLsYG9jlTRmR/xKluxHV+Z9QEwNIgCfM1/uwPMCuzVVnh5mwTd+OuBZcwSIMbqssNWRm1lE51QaQ==} engines: {node: '>=8'} + ansi-escapes@7.3.0: + resolution: {integrity: sha512-BvU8nYgGQBxcmMuEeUEmNTvrMVjJNSH7RgW24vXexN4Ven6qCvy4TntnvlnwnMLTVlcRQQdbRY8NKnaIoeWDNg==} + engines: {node: '>=18'} + ansi-regex@5.0.1: resolution: {integrity: sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ==} engines: {node: '>=8'} @@ -2878,10 +2888,6 @@ packages: brace-expansion@2.0.1: resolution: {integrity: sha512-XnAIvQ8eM+kC6aULx6wuQiwVsnzsi9d3WxzV3FpWTGA19F621kwdbsAcFKXgKUHZWsy+mY6iL1sHTxWEFCytDA==} - braces@3.0.2: - resolution: {integrity: sha512-b8um+L1RzM3WDSzvhm6gIz1yfTbBt6YTlcEKAvsmqCZZFw46z626lVj9j1yEPW33H5H+lBQpZMP1k8l+78Ha0A==} - engines: {node: '>=8'} - braces@3.0.3: resolution: {integrity: sha512-yQbXgO/OSZVD2IsiLlro+7Hf6Q18EJrKSEsdoMzKePKXct3gvD8oLcOQdIzGupr5Fj+EDe8gO/lxc1BzfMpxvA==} engines: {node: '>=8'} @@ -3007,6 +3013,10 @@ packages: resolution: {integrity: sha512-/lzGpEWL/8PfI0BmBOPRwp0c/wFNX1RdUML3jK/RcSBA9T8mZDdQpqYBKtCFTOfQbwPqWEOpjqW+Fnayc0969g==} engines: {node: '>=10'} + cli-cursor@5.0.0: + resolution: {integrity: sha512-aCj4O5wKyszjMmDT4tZj93kxyydN/K5zPWSCe6/0AV/AA1pqe5ZBIw0a2ZfPQV7lL5/yb5HsUreJ6UFAF1tEQw==} + engines: {node: '>=18'} + cli-progress@3.12.0: resolution: {integrity: sha512-tRkV3HJ1ASwm19THiiLIXLO7Im7wlTuKnvkYaTkyoAPefqjNg7W7DHKUlGRxy9vxDvbyCYQkQozvptuMkGCg8A==} engines: {node: '>=4'} @@ -3015,6 +3025,10 @@ packages: resolution: {integrity: sha512-+W/5efTR7y5HRD7gACw9yQjqMVvEMLBHmboM/kPWam+H+Hmyrgjh6YncVKK122YZkXrLudzTuAukUw9FnMf7IQ==} engines: {node: 10.* || >= 12.*} + cli-truncate@5.1.1: + resolution: {integrity: sha512-SroPvNHxUnk+vIW/dOSfNqdy1sPEFkrTk6TUtqLCnBlo3N7TNYYkzzN7uSD6+jVjrdO4+p8nH7JzH6cIvUem6A==} + engines: {node: '>=20'} + cli-width@4.1.0: resolution: {integrity: sha512-ouuZd4/dm2Sw5Gmqy6bGyNNNe1qt9RpmxveLSO7KcgsTnU7RXfsw+/bukWGo1abgBiMAic068rclZsO4IWmmxQ==} engines: {node: '>= 12'} @@ -3047,10 +3061,17 @@ packages: color-name@1.1.4: resolution: {integrity: sha512-dOy+3AuW3a2wNbZHIuMZpTcgjGuLU/uBL/ubcZF9OXbDo8ff4O8yVp5Bf0efS8uEoYo5q4Fx7dY9OgQGXgAsQA==} + colorette@2.0.20: + resolution: {integrity: sha512-IfEDxwoWIjkeXL1eXcDiow4UbKjhLdq6/EuSVR9GMN7KVH3r9gQ83e73hsz1Nd1T3ijd5xv1wcWRYO+D6kCI2w==} + combined-stream@1.0.8: resolution: {integrity: sha512-FQN4MRfuJeHf7cBbBMJFXhKSDq+2kAArBlmRBvcvFE5BB1HZKXtSFASDhdlz9zOYwxh8lDdnvmMOe/+5cdoEdg==} engines: {node: '>= 0.8'} + commander@14.0.3: + resolution: {integrity: sha512-H+y0Jo/T1RZ9qPP4Eh1pkcQcLRglraJaSLoyOtHxu6AapkjWVCy2Sit1QQ4x3Dng8qDlSsZEet7g5Pq06MvTgw==} + engines: {node: '>=20'} + commander@2.20.3: resolution: {integrity: sha512-GpVkmM8vF2vQUkj2LvZmD35JxeJOLCwJ9cUkugyk2nuhbv3+mJvpLYYt+0+USMxE+oj+ey/lJEnhZw75x/OMcQ==} @@ -3287,6 +3308,10 @@ packages: resolution: {integrity: sha512-V0hjH4dGPh9Ao5p0MoRY6BVqtwCjhz6vI5LT8AJ55H+4g9/4vbHx1I54fS0XuclLhDHArPQCiMjDxjaL8fPxhw==} engines: {node: '>=0.12'} + environment@1.1.0: + resolution: {integrity: sha512-xUtoPkMggbz0MPyPiIWr1Kp4aeWJjDZ6SMvURhimjdZgsRuDplF5/s9hcgGhyXMhs+6vpnuoiZ2kFiu3FMnS8Q==} + engines: {node: '>=18'} + error-ex@1.3.2: resolution: {integrity: sha512-7dFHNmqeFSEt2ZBsCriorKnn3Z2pj+fd9kmI6QoWw4//DL+icEBfc0U7qJCisqrTsKTjw4fNFy2pW9OqStD84g==} @@ -3453,6 +3478,9 @@ packages: eventemitter3@4.0.7: resolution: {integrity: sha512-8guHBZCwKnFhYdHr2ysuRWErTwhoN2X8XELRlrRwpmfeY2jjuUN4taQMsULKUVo1K4DvZl+0pgfyoysHxvmvEw==} + eventemitter3@5.0.4: + resolution: {integrity: sha512-mlsTRyGaPBjPedk6Bvw+aqbsXDtoAyAzm5MO7JgU+yVRyMQ5O8bD4Kcci7BS85f93veegeCPkL8R4GLClnjLFw==} + events@3.3.0: resolution: {integrity: sha512-mQw+2fkQbALzQ7V0MY0IqdnXNOeTtP4r0lN9z7AAawCXgqea7bDii20AYrIBrFd/Hx0M2Ocz6S111CaFkUcb0Q==} engines: {node: '>=0.8.x'} @@ -3544,10 +3572,6 @@ packages: resolution: {integrity: sha512-XXTUwCvisa5oacNGRP9SfNtYBNAMi+RPwBFmblZEF7N7swHYQS6/Zfk7SRwx4D5j3CH211YNRco1DEMNVfZCnQ==} engines: {node: '>=16.0.0'} - fill-range@7.0.1: - resolution: {integrity: sha512-qOo9F+dMUmC2Lcb4BbVvnKJxTPjCm+RRpe4gDuGrzkL7mEVl/djYSu2OdQ2Pa302N4oqkSg9ir6jaLWJ2USVpQ==} - engines: {node: '>=8'} - fill-range@7.1.1: resolution: {integrity: sha512-YsGpe3WHLK8ZYi4tWDg2Jy3ebRz2rXowDxnld4bkQB00cc/1Zw9AWnC0i9ztDJitivtQvaI9KaLyKrc+hBW0yg==} engines: {node: '>=8'} @@ -3662,6 +3686,10 @@ packages: resolution: {integrity: sha512-QZjmEOC+IT1uk6Rx0sX22V6uHWVwbdbxf1faPqJ1QhLdGgsRGCZoyaQBm/piRdJy/D2um6hM1UP7ZEeQ4EkP+Q==} engines: {node: '>=18'} + get-east-asian-width@1.5.0: + resolution: {integrity: sha512-CQ+bEO+Tva/qlmw24dCejulK5pMzVnUOFOijVogd3KQs07HnRIgp8TGipvCCRT06xeYEbpbgwaCxglFyiuIcmA==} + engines: {node: '>=18'} + get-intrinsic@1.2.2: resolution: {integrity: sha512-0gSo4ml/0j98Y3lngkFEot/zhiCeWsbYIlZ+uZOVgzLyLaUw7wxUL+nCTP0XJvJg1AXulJRI3UJi8GsbDuxdGA==} @@ -3703,11 +3731,12 @@ packages: glob@10.4.5: resolution: {integrity: sha512-7Bv8RF0k6xjo7d4A/PxYLbUCfb6c+Vpd2/mB2yRDlew7Jb5hEXiCD9ibfO7wpk8i4sevK6DFny9h7EYbM3/sHg==} + deprecated: Old versions of glob are not supported, and contain widely publicized security vulnerabilities, which have been fixed in the current version. Please update. Support for old versions may be purchased (at exorbitant rates) by contacting i@izs.me hasBin: true glob@7.2.3: resolution: {integrity: sha512-nFR0zLpU2YCaRxwoCJvL6UvCH2JFyFVIvwTLsIf21AuHlMskA1hhTdk+LlYJtOlYt9v6dvszD2BGRqBL+iQK9Q==} - deprecated: Glob versions prior to v9 are no longer supported + deprecated: Old versions of glob are not supported, and contain widely publicized security vulnerabilities, which have been fixed in the current version. Please update. Support for old versions may be purchased (at exorbitant rates) by contacting i@izs.me globals@11.12.0: resolution: {integrity: sha512-WOBp/EEGUiIsJSp7wcv/y6MO+lV9UoncWqxuFfm8eBwzWNgyfBd6Gz+IeKQ9jCmyhoH99g15M3T+QaVHFjizVA==} @@ -3821,6 +3850,11 @@ packages: humanize-ms@1.2.1: resolution: {integrity: sha512-Fl70vYtsAFb/C06PTS9dZBo7ihau+Tu/DNCk/OyHhea07S+aeMWpFFkUaXRa8fI+ScZbEI8dfSxwY7gxZ9SAVQ==} + husky@9.1.7: + resolution: {integrity: sha512-5gs5ytaNjBrh5Ow3zrvdUUY+0VxIuWVL4i9irt6friV+BqdCfmV11CQTWMiBYWHbXhco+J1kHfTOUkePhCDvMA==} + engines: {node: '>=18'} + hasBin: true + hyperdyperid@1.2.0: resolution: {integrity: sha512-Y93lCzHYgGWdrJ66yIktxiaGULYc6oGiABxhcO5AufBeOyoIdZF7bIfLaOrbM0iGIOXQQgxxRrFEnb+Y6w1n4A==} engines: {node: '>=10.18'} @@ -3912,6 +3946,10 @@ packages: resolution: {integrity: sha512-zymm5+u+sCsSWyD9qNaejV3DFvhCKclKdizYaJUuHA83RLjb7nSuGnddCHGv0hk+KY7BMAlsWeK4Ueg6EV6XQg==} engines: {node: '>=8'} + is-fullwidth-code-point@5.1.0: + resolution: {integrity: sha512-5XHYaSyiqADb4RnZ1Bdad6cPp8Toise4TzEjcOYDHZkTCbKgiUl7WTUCpNWHuxmDt91wnsZBc9xinNzopv3JMQ==} + engines: {node: '>=18'} + is-generator-fn@2.1.0: resolution: {integrity: sha512-cTIB4yPYL/Grw0EaSzASzg6bBy9gqCofvWN8okThAYIxKJZC+udlRAmGbM0XLeniEJSs8uEgHPGuHSe1XsOLSQ==} engines: {node: '>=6'} @@ -4268,6 +4306,15 @@ packages: linkify-it@5.0.0: resolution: {integrity: sha512-5aHCbzQRADcdP+ATqnDuhhJ/MRIqDkZX5pyjFHRRysS8vZ5AbqGEoFIb6pYHPZ+L/OC2Lc+xT8uHVVR5CAK/wQ==} + lint-staged@16.2.7: + resolution: {integrity: sha512-lDIj4RnYmK7/kXMya+qJsmkRFkGolciXjrsZ6PC25GdTfWOAWetR0ZbsNXRAj1EHHImRSalc+whZFg56F5DVow==} + engines: {node: '>=20.17'} + hasBin: true + + listr2@9.0.5: + resolution: {integrity: sha512-ME4Fb83LgEgwNw96RKNvKV4VTLuXfoKudAmm2lP8Kk87KaMK0/Xrx/aAkMWmT8mDb+3MlFDspfbCs7adjRxA2g==} + engines: {node: '>=20.0.0'} + load-json-file@4.0.0: resolution: {integrity: sha512-Kx8hMakjX03tiGTLAIdJ+lL0htKnXjEZN6hk/tozf/WOuYGdZBJrZ+rCJRbVCugsjB3jMLn9746NsQIf5VjBMw==} engines: {node: '>=4'} @@ -4303,6 +4350,10 @@ packages: lodash.sortby@4.7.0: resolution: {integrity: sha512-HDWXG8isMntAyRF5vZ7xKuEvOhT4AhlRt/3czTSjvGUxjYCBVRQY48ViDHyfYz9VIoBkW4TMGQNapx+l3RUwdA==} + log-update@6.1.0: + resolution: {integrity: sha512-9ie8ItPR6tjY5uYJh8K/Zrv/RMZ5VOlOWvtZdEHYSTFKZfIBPQa9tOAEeAWhd+AnIneLJ22w5fjOYtoutpWq5w==} + engines: {node: '>=18'} + long@5.3.2: resolution: {integrity: sha512-mNAgZ1GmyNhD7AuqnTG3/VQ26o760+ZYBPKjPvugO8+nLbYfX6TVpJPseBvopbdY+qpZ/lKUnmEc1LeZYS3QAA==} @@ -4376,10 +4427,6 @@ packages: resolution: {integrity: sha512-iclAHeNqNm68zFtnZ0e+1L2yUIdvzNoauKU4WBA3VvH/vPFieF7qfRlwUZU+DA9P9bPXIS90ulxoUoCH23sV2w==} engines: {node: '>= 0.6'} - micromatch@4.0.5: - resolution: {integrity: sha512-DMy+ERcEW2q8Z2Po+WNXuw3c5YaUSFjAO5GsJqfEl7UjvtIuFKO6ZrKvcItdy98dwFI2N1tg3zNIdKaQT+aNdA==} - engines: {node: '>=8.6'} - micromatch@4.0.8: resolution: {integrity: sha512-PXwfBhYu0hBCPw8Dn0E+WDYb7af3dSLVWKi3HGv84IdF4TyFoC0ysxFd0Goxw7nSv4T/PzEJQxsYsEiFCKo2BA==} engines: {node: '>=8.6'} @@ -4409,6 +4456,10 @@ packages: resolution: {integrity: sha512-OqbOk5oEQeAZ8WXWydlu9HJjz9WVdEIvamMCcXmuqUYjTknH/sqsWvhQ3vgwKFRR1HpjvNBKQ37nbJgYzGqGcg==} engines: {node: '>=6'} + mimic-function@5.0.1: + resolution: {integrity: sha512-VP79XUPxV2CigYP3jWwAUFSku2aKqBH7uTAapFWCBqutsbmDo96KY5o8uh6U+/YSIn5OxJnXp73beVkpqMIGhA==} + engines: {node: '>=18'} + minimatch@3.1.2: resolution: {integrity: sha512-J7p63hRiAjw1NDEww1W7i37+ByIrOWO5XQQAzZ3VOcL0PNybwpfmV/N05zFAzwQ9USyEcX6t3UO+K5aqBQOIHw==} @@ -4493,6 +4544,10 @@ packages: mz@2.7.0: resolution: {integrity: sha512-z81GNO7nnYMEhrGh9LeymoE4+Yr0Wn5McHIZMK5cfQCl+NDX08sCZgUc9/6MHni9IWuFLm1Z3HTCXu2z9fN62Q==} + nano-spawn@2.0.0: + resolution: {integrity: sha512-tacvGzUY5o2D8CBh2rrwxyNojUsZNU2zjNTzKQrkgGJQTbGAfArVWXSKMBokBeeg6C7OLRGUEyoFlYbfeWQIqw==} + engines: {node: '>=20.17'} + nanoid@3.3.11: resolution: {integrity: sha512-N8SpfPUnUp1bK+PMYW8qSWdl9U+wwNWI4QKxOYDy9JAro3WMX7p2OeVRF9v+347pnakNevPmiHhNmZ2HbFA76w==} engines: {node: ^10 || ^12 || ^13.7 || ^14 || >=15.0.1} @@ -4600,6 +4655,10 @@ packages: resolution: {integrity: sha512-kbpaSSGJTWdAY5KPVeMOKXSrPtr8C8C7wodJbcsd51jRnmD+GZu8Y0VoU6Dm5Z4vWr0Ig/1NKuWRKf7j5aaYSg==} engines: {node: '>=6'} + onetime@7.0.0: + resolution: {integrity: sha512-VXJjc87FScF88uafS3JllDgvAm+c/Slfz06lorj2uAY34rlUu0Nt+v8wreiImcrgAjjIHp1rXpTDlLOGw29WwQ==} + engines: {node: '>=18'} + openai@4.104.0: resolution: {integrity: sha512-p99EFNsA/yX6UhVO93f5kJsDRLAg+CTA2RBqdHK4RtK8u5IJw32Hyb2dTGKbnnFmnuoBv5r7Z2CURI9sGZpSuA==} hasBin: true @@ -4799,6 +4858,11 @@ packages: engines: {node: '>=0.10'} hasBin: true + pidtree@0.6.0: + resolution: {integrity: sha512-eG2dWTVw5bzqGRztnHExczNxt5VGsE6OwTeCG3fdUf9KBsZzO3R5OIIIzWR+iZA0NtZ+RDVdaoE2dK1cn6jH4g==} + engines: {node: '>=0.10'} + hasBin: true + pify@3.0.0: resolution: {integrity: sha512-C3FsVNH1udSEX48gGX1xfvwTWfsYWj5U+8/uK15BGzIGrKoUpghX8hWZwa/OFnakBiiVNmBvemTJR5mcy7iPcg==} engines: {node: '>=4'} @@ -4895,11 +4959,6 @@ packages: pure-rand@6.1.0: resolution: {integrity: sha512-bVWawvoZoBYpp6yIoQtQXHZjmz35RSVHnUOTefl8Vcjr8snTPY1wnpSPMWekcFwbxI6gtmT7rSYPFvz71ldiOA==} - pyright@1.1.404: - resolution: {integrity: sha512-Gr48RLeyis8uMjx04vXGIdj3OFe/WGGBMg53XIh9GH30KRyuyKYNAjfUZqj3r51Xrv5BFKyDyguJu/BV3hi7QA==} - engines: {node: '>=14.0.0'} - hasBin: true - qs@6.13.0: resolution: {integrity: sha512-+38qI9SOr8tfZ4QmJNplMUxqjbe7LKvvZgWdExBOmd+egZTtjLB67Gu0HRX3u/XOq7UU2Nx6nsjvS16Z9uwfpg==} engines: {node: '>=0.6'} @@ -4987,6 +5046,10 @@ packages: resolution: {integrity: sha512-oKWePCxqpd6FlLvGV1VU0x7bkPmmCNolxzjMf4NczoDnQcIWrAF+cPtZn5i6n+RfD2d9i0tzpKnG6Yk168yIyw==} hasBin: true + restore-cursor@5.1.0: + resolution: {integrity: sha512-oMA2dcrw6u0YfxJQXm342bFKX/E4sG9rbTzO9ptUcR/e8A33cHuvStiYOwH7fszkZlZ1z/ta9AAoPk2F4qIOHA==} + engines: {node: '>=18'} + retry@0.13.1: resolution: {integrity: sha512-XQBQ3I8W1Cge0Seh+6gjj03LbmRFWuoszgK9ooCpwYIrhhoO80pfq4cUkU5DkknwfOfFteRwlZ56PYOGYyFWdg==} engines: {node: '>= 4'} @@ -4995,6 +5058,9 @@ packages: resolution: {integrity: sha512-U9nH88a3fc/ekCF1l0/UP1IosiuIjyTh7hBvXVMHYgVcfGvt897Xguj2UOLDeI5BG2m7/uwyaLVT6fbtCwTyzw==} engines: {iojs: '>=1.0.0', node: '>=0.10.0'} + rfdc@1.4.1: + resolution: {integrity: sha512-q1b3N5QkRUWUl7iyylaaj3kOpIT0N2i9MqIEQXP73GVsN9cw3fdx8X63cEmWhJGi2PPCF23Ijp7ktmd39rawIA==} + rollup@4.35.0: resolution: {integrity: sha512-kg6oI4g+vc41vePJyO6dHt/yl0Rz3Thv0kJeVQ3D1kS3E5XSuKbPc29G4IpT/Kv1KQwgHVcN+HtyS+HYLNSvQg==} engines: {node: '>=18.0.0', npm: '>=8.0.0'} @@ -5048,6 +5114,11 @@ packages: engines: {node: '>=10'} hasBin: true + semver@7.7.4: + resolution: {integrity: sha512-vFKC2IEtQnVhpT78h1Yp8wzwrf8CM+MzKMHGJZfBtzhZNycRFnXsHk6E5TxIkkMsgNS7mdX3AGB7x2QM2di4lA==} + engines: {node: '>=10'} + hasBin: true + send@0.19.0: resolution: {integrity: sha512-dW41u5VfLXu8SJh5bwRmyYUbAoSB3c9uQh6L8h/KtsFREPWpbX1lrljJo186Jc4nmci/sGUZ9a0a0J2zgfq2hw==} engines: {node: '>= 0.8.0'} @@ -5142,6 +5213,10 @@ packages: resolution: {integrity: sha512-g9Q1haeby36OSStwb4ntCGGGaKsaVSjQ68fBxoQcutl5fS1vuY18H3wSt3jFyFtrkx+Kz0V1G85A4MyAdDMi2Q==} engines: {node: '>=8'} + slice-ansi@7.1.2: + resolution: {integrity: sha512-iOBWFgUX7caIZiuutICxVgX1SdxwAVFFKwt1EvMYYec/NWO5meOJ6K5uQxhrYBdQJne4KxiqZc+KptFOWFSI9w==} + engines: {node: '>=18'} + source-map-js@1.2.1: resolution: {integrity: sha512-UXWMKhLOwVKb728IUtQPXxfYU+usdybtUrK/8uGE8CQMvrhOpwvzDBwj0QhSL7MQc7vIsISBG8VQ8+IDQxpfQA==} engines: {node: '>=0.10.0'} @@ -5212,6 +5287,10 @@ packages: strict-event-emitter@0.5.1: resolution: {integrity: sha512-vMgjE/GGEPEFnhFub6pa4FmJBRBVOLpIII2hvCZ8Kzb7K0hlHo7mQv6xYrBvCL2LtAIBwFUK8wvuJgTVSQ5MFQ==} + string-argv@0.3.2: + resolution: {integrity: sha512-aqD2Q0144Z+/RqG52NeHEkZauTAUWJO8c6yTftGJKO3Tja5tUgIfmIl6kExvhtxSDP7fXB6DvzkfMpCd/F3G+Q==} + engines: {node: '>=0.6.19'} + string-length@4.0.2: resolution: {integrity: sha512-+l6rNN5fYHNhZZy41RXsYptCjA2Igmq4EG7kZAYFQI1E1VTXarr6ZPXBg6eq7Y6eK4FEhY6AJlyuFIb/v/S0VQ==} engines: {node: '>=10'} @@ -5228,6 +5307,10 @@ packages: resolution: {integrity: sha512-tsaTIkKW9b4N+AEj+SVA+WhJzV7/zMhcSu78mLKWSk7cXMOSHsBKFWUs0fWwq8QyK3MgJBQRX6Gbi4kYbdvGkQ==} engines: {node: '>=18'} + string-width@8.2.0: + resolution: {integrity: sha512-6hJPQ8N0V0P3SNmP6h2J99RLuzrWz2gvT7VnK5tKvrNqJoyS9W4/Fb8mo31UiPvy00z7DQXkP2hnKBVav76thw==} + engines: {node: '>=20'} + string.prototype.padend@3.1.5: resolution: {integrity: sha512-DOB27b/2UTTD+4myKUFh+/fXWcu/UDyASIXfg+7VzoCNNGOfWvoyU/x5pvVHr++ztyt/oSYI1BcWBBG/hmlNjA==} engines: {node: '>= 0.4'} @@ -5250,6 +5333,10 @@ packages: resolution: {integrity: sha512-iq6eVVI64nQQTRYq2KtEg2d2uU7LElhTJwsH4YzIHZshxlgZms/wIc4VoDQTlG/IvVIrBKG06CrZnp0qv7hkcQ==} engines: {node: '>=12'} + strip-ansi@7.1.2: + resolution: {integrity: sha512-gmBGslpoQJtgnMAvOVqGZpEz9dyoKTCzy2nfz/n8aIFhN/jCE/rCmcxabB6jOOHV+0WNnylOxaxBQPSvcWklhA==} + engines: {node: '>=12'} + strip-bom@3.0.0: resolution: {integrity: sha512-vavAMRXOgBVNF6nyEEmL3DBK19iRpDcoIwW+swQ+CbGiu7lju6t+JklA1MHweoWtadgt4ISVUsXLyDq34ddcwA==} engines: {node: '>=4'} @@ -5320,7 +5407,7 @@ packages: tar@7.5.2: resolution: {integrity: sha512-7NyxrTE4Anh8km8iEy7o0QYPs+0JKBTj5ZaqHg6B39erLg0qYXN3BijtShwbsNSvQ+LN75+KV+C4QR/f6Gwnpg==} engines: {node: '>=18'} - deprecated: Old versions of tar are not supported, and contain widely publicized security vulnerabilities, which have been fixed in the current version. Please update. Support for old versions may be purchased (at exhorbitant rates) by contacting i@izs.me + deprecated: Old versions of tar are not supported, and contain widely publicized security vulnerabilities, which have been fixed in the current version. Please update. Support for old versions may be purchased (at exorbitant rates) by contacting i@izs.me termi-link@1.1.0: resolution: {integrity: sha512-2qSN6TnomHgVLtk+htSWbaYs4Rd2MH/RU7VpHTy6MBstyNyWbM4yKd1DCYpE3fDg8dmGWojXCngNi/MHCzGuAA==} @@ -5953,11 +6040,6 @@ packages: resolution: {integrity: sha512-YgvUTfwqyc7UXVMrB+SImsVYSmTS8X/tSrtdNZMImM+n7+QTriRXyXim0mBrTXNeqzVF0KWGgHPeiyViFFrNDw==} engines: {node: '>=18'} - yaml@2.8.0: - resolution: {integrity: sha512-4lLa/EcQCB0cJkyts+FpIRx5G/llPxfP6VQU5KByHEhLxY3IJCH0f0Hy1MHI8sClTvsIb8qwRJ6R/ZdlDJ/leQ==} - engines: {node: '>= 14.6'} - hasBin: true - yaml@2.8.2: resolution: {integrity: sha512-mplynKqc1C2hTVYxd0PU2xQAc22TI1vShAYGksCCfxbn/dFwnHTNi1bvYsBTkhdUNtGIf5xNOg938rrSSYvS9A==} engines: {node: '>= 14.6'} @@ -7405,7 +7487,7 @@ snapshots: jest-haste-map: 29.7.0 jest-regex-util: 29.6.3 jest-util: 29.7.0 - micromatch: 4.0.5 + micromatch: 4.0.8 pirates: 4.0.6 slash: 3.0.0 write-file-atomic: 4.0.2 @@ -8670,6 +8752,10 @@ snapshots: dependencies: type-fest: 0.21.3 + ansi-escapes@7.3.0: + dependencies: + environment: 1.1.0 + ansi-regex@5.0.1: {} ansi-regex@6.1.0: {} @@ -8932,10 +9018,6 @@ snapshots: dependencies: balanced-match: 1.0.2 - braces@3.0.2: - dependencies: - fill-range: 7.0.1 - braces@3.0.3: dependencies: fill-range: 7.1.1 @@ -9072,6 +9154,10 @@ snapshots: cli-boxes@3.0.0: {} + cli-cursor@5.0.0: + dependencies: + restore-cursor: 5.1.0 + cli-progress@3.12.0: dependencies: string-width: 4.2.3 @@ -9082,6 +9168,11 @@ snapshots: optionalDependencies: '@colors/colors': 1.5.0 + cli-truncate@5.1.1: + dependencies: + slice-ansi: 7.1.2 + string-width: 8.2.0 + cli-width@4.1.0: {} cliui@8.0.1: @@ -9108,10 +9199,14 @@ snapshots: color-name@1.1.4: {} + colorette@2.0.20: {} + combined-stream@1.0.8: dependencies: delayed-stream: 1.0.0 + commander@14.0.3: {} + commander@2.20.3: {} commander@4.1.1: {} @@ -9302,6 +9397,8 @@ snapshots: entities@4.5.0: {} + environment@1.1.0: {} + error-ex@1.3.2: dependencies: is-arrayish: 0.2.1 @@ -9602,6 +9699,8 @@ snapshots: eventemitter3@4.0.7: {} + eventemitter3@5.0.4: {} + events@3.3.0: {} eventsource-parser@1.1.2: {} @@ -9743,10 +9842,6 @@ snapshots: dependencies: flat-cache: 4.0.1 - fill-range@7.0.1: - dependencies: - to-regex-range: 5.0.1 - fill-range@7.1.1: dependencies: to-regex-range: 5.0.1 @@ -9881,6 +9976,8 @@ snapshots: get-east-asian-width@1.4.0: {} + get-east-asian-width@1.5.0: {} + get-intrinsic@1.2.2: dependencies: function-bind: 1.1.2 @@ -10055,6 +10152,8 @@ snapshots: dependencies: ms: 2.1.3 + husky@9.1.7: {} + hyperdyperid@1.2.0: {} iconv-lite@0.4.24: @@ -10135,6 +10234,10 @@ snapshots: is-fullwidth-code-point@3.0.0: {} + is-fullwidth-code-point@5.1.0: + dependencies: + get-east-asian-width: 1.4.0 + is-generator-fn@2.1.0: {} is-glob@4.0.3: @@ -10207,7 +10310,7 @@ snapshots: '@babel/parser': 7.28.4 '@istanbuljs/schema': 0.1.3 istanbul-lib-coverage: 3.2.2 - semver: 7.7.2 + semver: 7.7.4 transitivePeerDependencies: - supports-color @@ -10390,7 +10493,7 @@ snapshots: jest-regex-util: 29.6.3 jest-util: 29.7.0 jest-worker: 29.7.0 - micromatch: 4.0.5 + micromatch: 4.0.8 walker: 1.0.8 optionalDependencies: fsevents: 2.3.3 @@ -10414,7 +10517,7 @@ snapshots: '@types/stack-utils': 2.0.3 chalk: 4.1.2 graceful-fs: 4.2.11 - micromatch: 4.0.5 + micromatch: 4.0.8 pretty-format: 29.7.0 slash: 3.0.0 stack-utils: 2.0.6 @@ -10524,7 +10627,7 @@ snapshots: jest-util: 29.7.0 natural-compare: 1.4.0 pretty-format: 29.7.0 - semver: 7.6.2 + semver: 7.7.2 transitivePeerDependencies: - supports-color @@ -10702,6 +10805,25 @@ snapshots: dependencies: uc.micro: 2.1.0 + lint-staged@16.2.7: + dependencies: + commander: 14.0.3 + listr2: 9.0.5 + micromatch: 4.0.8 + nano-spawn: 2.0.0 + pidtree: 0.6.0 + string-argv: 0.3.2 + yaml: 2.8.2 + + listr2@9.0.5: + dependencies: + cli-truncate: 5.1.1 + colorette: 2.0.20 + eventemitter3: 5.0.4 + log-update: 6.1.0 + rfdc: 1.4.1 + wrap-ansi: 9.0.2 + load-json-file@4.0.0: dependencies: graceful-fs: 4.2.11 @@ -10731,6 +10853,14 @@ snapshots: lodash.sortby@4.7.0: {} + log-update@6.1.0: + dependencies: + ansi-escapes: 7.3.0 + cli-cursor: 5.0.0 + slice-ansi: 7.1.2 + strip-ansi: 7.1.0 + wrap-ansi: 9.0.2 + long@5.3.2: {} loupe@3.1.3: {} @@ -10749,7 +10879,7 @@ snapshots: make-dir@4.0.0: dependencies: - semver: 7.7.2 + semver: 7.7.4 make-error@1.3.6: {} @@ -10797,11 +10927,6 @@ snapshots: methods@1.1.2: {} - micromatch@4.0.5: - dependencies: - braces: 3.0.2 - picomatch: 2.3.1 - micromatch@4.0.8: dependencies: braces: 3.0.3 @@ -10825,6 +10950,8 @@ snapshots: mimic-fn@2.1.0: {} + mimic-function@5.0.1: {} + minimatch@3.1.2: dependencies: brace-expansion: 1.1.11 @@ -11059,6 +11186,8 @@ snapshots: object-assign: 4.1.1 thenify-all: 1.6.0 + nano-spawn@2.0.0: {} + nanoid@3.3.11: {} nanoid@3.3.6: {} @@ -11144,6 +11273,10 @@ snapshots: dependencies: mimic-fn: 2.1.0 + onetime@7.0.0: + dependencies: + mimic-function: 5.0.1 + openai@4.104.0(ws@8.18.3)(zod@3.25.76): dependencies: '@types/node': 18.19.123 @@ -11216,7 +11349,7 @@ snapshots: openapi3-ts@3.1.0: dependencies: - yaml: 2.8.0 + yaml: 2.8.2 optionator@0.9.4: dependencies: @@ -11335,6 +11468,8 @@ snapshots: pidtree@0.3.1: {} + pidtree@0.6.0: {} + pify@3.0.0: {} pirates@4.0.6: {} @@ -11422,10 +11557,6 @@ snapshots: pure-rand@6.1.0: {} - pyright@1.1.404: - optionalDependencies: - fsevents: 2.3.3 - qs@6.13.0: dependencies: side-channel: 1.1.0 @@ -11508,10 +11639,17 @@ snapshots: path-parse: 1.0.7 supports-preserve-symlinks-flag: 1.0.0 + restore-cursor@5.1.0: + dependencies: + onetime: 7.0.0 + signal-exit: 4.1.0 + retry@0.13.1: {} reusify@1.0.4: {} + rfdc@1.4.1: {} + rollup@4.35.0: dependencies: '@types/estree': 1.0.6 @@ -11590,6 +11728,8 @@ snapshots: semver@7.7.2: {} + semver@7.7.4: {} + send@0.19.0: dependencies: debug: 2.6.9 @@ -11738,6 +11878,11 @@ snapshots: slash@3.0.0: {} + slice-ansi@7.1.2: + dependencies: + ansi-styles: 6.2.1 + is-fullwidth-code-point: 5.1.0 + source-map-js@1.2.1: {} source-map-loader@4.0.2(webpack@5.104.1(@swc/core@1.15.8)): @@ -11799,6 +11944,8 @@ snapshots: strict-event-emitter@0.5.1: {} + string-argv@0.3.2: {} + string-length@4.0.2: dependencies: char-regex: 1.0.2 @@ -11822,6 +11969,11 @@ snapshots: get-east-asian-width: 1.4.0 strip-ansi: 7.1.0 + string-width@8.2.0: + dependencies: + get-east-asian-width: 1.5.0 + strip-ansi: 7.1.2 + string.prototype.padend@3.1.5: dependencies: call-bind: 1.0.5 @@ -11854,6 +12006,10 @@ snapshots: dependencies: ansi-regex: 6.1.0 + strip-ansi@7.1.2: + dependencies: + ansi-regex: 6.1.0 + strip-bom@3.0.0: {} strip-bom@4.0.0: {} @@ -12947,8 +13103,6 @@ snapshots: yallist@5.0.0: {} - yaml@2.8.0: {} - yaml@2.8.2: {} yargs-parser@21.1.1: {} diff --git a/py/.envrc b/py/.envrc deleted file mode 100644 index 2c57cdac5..000000000 --- a/py/.envrc +++ /dev/null @@ -1 +0,0 @@ -dotenv_if_exists diff --git a/py/.gitignore b/py/.gitignore deleted file mode 100644 index 591c866da..000000000 --- a/py/.gitignore +++ /dev/null @@ -1,2 +0,0 @@ -src/braintrust.egg-info/ -dist diff --git a/py/CLAUDE.md b/py/CLAUDE.md deleted file mode 100644 index 45e0c601c..000000000 --- a/py/CLAUDE.md +++ /dev/null @@ -1,101 +0,0 @@ -# Python SDK - -## Setup - -To run examples or use optional integrations, install the extra dependencies: - -```bash -make install-dev # Development dependencies -make install-optional # Optional integration dependencies -``` - -## Running Tests - -```bash -make test # All tests via nox -make test-core # Core tests only -make lint # Pylint + formatting -make clean # Remove build artifacts -``` - -**Run a single test:** - -```bash -nox -s "test_openai(latest)" -- -k "test_chat_metrics" -``` - -**Common test sessions:** - -```bash -nox -l # List all sessions -nox -s "test_openai(latest)" # OpenAI wrapper (latest version) -nox -s "test_anthropic(latest)" # Anthropic wrapper -nox -s "test_temporal(latest)" # Temporal integration -nox -s test_openai # All OpenAI versions -``` - -- we use pytest, so you don't need to add extra messages to assert. `assert x -== 1` is usually enough. - -## VCR Cassettes - -Tests use VCR to record HTTP interactions so they run without live API calls. - -**Cassette location:** `src/braintrust/wrappers/cassettes/` - -**Using in tests:** - -```python -@pytest.mark.vcr -def test_openai_chat_metrics(memory_logger): - client = wrap_openai(openai.OpenAI()) - response = client.chat.completions.create(...) -``` - -**VCR commands:** - -```bash -# Run tests normally (play back from cassettes) -nox -s "test_openai(latest)" - -# Run with real API calls (no VCR) -export OPENAI_API_KEY="sk-..." -nox -s "test_openai(latest)" -- --disable-vcr - -# Record new cassettes (overwrites existing) -export OPENAI_API_KEY="sk-..." -nox -s "test_openai(latest)" -- --vcr-record=all - -# Record only missing cassettes -nox -s "test_openai(latest)" -- --vcr-record=once - -# Record a single test's cassette -nox -s "test_openai(latest)" -- --vcr-record=all -k "test_openai_chat_metrics" - -# Fail if cassette is missing (CI mode) -nox -s "test_openai(latest)" -- --vcr-record=none -``` - -**Recording modes:** - -- `once` (default) - record if cassette missing, play back otherwise -- `new_episodes` - record new interactions, play back existing -- `all` - always record, overwrite cassettes -- `none` - only play back, fail if missing - -## Test Fixtures - -**Memory logger** - test span recording without real logging: - -```python -def test_something(memory_logger): - # ... do work ... - spans = memory_logger.pop() - assert len(spans) == 1 -``` - -**Auto-applied fixtures** (conftest.py): - -- `override_app_url_for_tests` - sets BRAINTRUST_APP_URL -- `setup_braintrust` - sets API key env vars -- `reset_braintrust_state` - resets global state after each test diff --git a/py/Makefile b/py/Makefile deleted file mode 100644 index 3ee890cd6..000000000 --- a/py/Makefile +++ /dev/null @@ -1,71 +0,0 @@ -.PHONY: lint test test-wheel _template-version clean fixup build verify-build verify help install-build-deps install-dev _check-git-clean - -clean: - rm -rf build dist - -fixup: - # just run the whole repos fixup (aka pre-commit hooks) - cd .. && make fixup - -lint: fixup - nox -s pylint - -test: - nox -x - -test-wheel: - # This target runs a small set of sanity checks before we release our - # build artifact to pypi. We skip running the full test suite because - # (a) theoretically it should have been run before (b) it has - # integration tests and we don't want to block the release because - # some service is down, etc. This decision could be revisited anytime. - # Note: Caller must run 'make build' first. - nox -s test_core -- --wheel - -test-core: - nox -s test_core - -_template-version: - @bash scripts/template-version.sh - -build: clean _template-version - python -m build - # Restore the original version file after the build - git checkout src/braintrust/version.py - -_check-git-clean: - @if [ -n "$$(git status --porcelain)" ]; then \ - echo "Error: Git working directory is not clean."; \ - exit 1; \ - fi - -verify-build: _check-git-clean build test-wheel - -verify: lint test - -install-build-deps: - python -m pip install uv==0.7.8 - python -m uv pip install -e . - python -m uv pip install -r requirements-build.txt - -install-dev: install-build-deps - python -m uv pip install -r requirements-dev.txt - -install-optional: - python -m uv pip install anthropic openai pydantic_ai litellm agno google-genai dspy langsmith - python -m uv pip install -e .[temporal,otel] - -.DEFAULT_GOAL := help -help: - @echo "Available targets:" - @echo " build - Build Python package" - @echo " clean - Remove build artifacts" - @echo " help - Show this help message" - @echo " install-build-deps - Install build dependencies for CI" - @echo " install-dev - Install package in development mode with all dependencies" - @echo " lint - Run pylint checks" - @echo " test - Run all tests" - @echo " test-core - Run core tests only" - @echo " test-wheel - Run tests against built wheel" - @echo " verify - Run all CI checks" - @echo " verify-build - Verify git clean, build, and test wheel" diff --git a/py/README.md b/py/README.md deleted file mode 100644 index d01256fa6..000000000 --- a/py/README.md +++ /dev/null @@ -1,57 +0,0 @@ -## Braintrust - -A Python library for logging data to Braintrust. `braintrust` is distributed as -a [library on PyPI](https://pypi.org/project/braintrust/). It is open source and -[available on GitHub](https://github.com/braintrustdata/braintrust-sdk/tree/main/py). - -### Quickstart - -Install the library with pip. - -```bash -pip install braintrust -``` - -**Performance tip**: For 3-5x faster JSON serialization, install with the optional `performance` extra: - -```bash -pip install braintrust[performance] -``` - -Or install `orjson` separately: - -```bash -pip install orjson -``` - -The SDK automatically detects and uses orjson if available, with seamless fallback to standard json. See [ORJSON_OPTIMIZATION.md](ORJSON_OPTIMIZATION.md) for details. - -Then, run a simple experiment with the following code (replace `YOUR_API_KEY` with -your Braintrust API key): - -```python -from braintrust import Eval - -def is_equal(expected, output): - return expected == output - -Eval( - "Say Hi Bot", - data=lambda: [ - { - "input": "Foo", - "expected": "Hi Foo", - }, - { - "input": "Bar", - "expected": "Hello Bar", - }, - ], # Replace with your eval dataset - task=lambda input: "Hi " + input, # Replace with your LLM call - scores=[is_equal], -) -``` - -# Performance Optimization - -For 3-5x faster JSON serialization, install `orjson`. The SDK automatically detects and uses orjson if available, with seamless fallback to standard json. diff --git a/py/benchmarks/perf.py b/py/benchmarks/perf.py deleted file mode 100644 index a29d7c24e..000000000 --- a/py/benchmarks/perf.py +++ /dev/null @@ -1,34 +0,0 @@ -import time - -import braintrust -from braintrust import traced - -LOOPS = 2000 - -braintrust.init_logger(project="perf_test") - - -@traced -def root(input: int) -> int: - return input * 2 - - -@traced -def child(input: int) -> int: - with braintrust.start_span(name="child") as span: - span.log(metadata={"m1": "v1", "m2": "v2"}) - result = root(input) - span.log(metrics={"result": result}) - return result - - -def main(): - t = time.time() - for i in range(LOOPS): - child(i) - elapsed = time.time() - t - print(f"ran {LOOPS} in {elapsed:.3f}s") - - -if __name__ == "__main__": - main() diff --git a/py/examples/.gitignore b/py/examples/.gitignore deleted file mode 100644 index 245773fb9..000000000 --- a/py/examples/.gitignore +++ /dev/null @@ -1 +0,0 @@ -run.sh diff --git a/py/examples/agno/async_simple_agent_stream.py b/py/examples/agno/async_simple_agent_stream.py deleted file mode 100644 index e35316097..000000000 --- a/py/examples/agno/async_simple_agent_stream.py +++ /dev/null @@ -1,24 +0,0 @@ -import asyncio - -from braintrust.wrappers.agno import setup_agno - -setup_agno(project_name="simple-agent-project") - -from agno.agent import Agent -from agno.models.openai import OpenAIChat -from agno.tools.yfinance import YFinanceTools - - -async def main(): - agent = Agent( - name="Stock Price Agent", - model=OpenAIChat(id="gpt-4o-mini"), - tools=[YFinanceTools()], - instructions="You are a stock price agent. Answer questions in the style of a stock analyst.", - ) - - async for message in agent.arun("What is the current price of FIG?", stream=True): - print(message) - - -asyncio.run(main()) diff --git a/py/examples/agno/async_team_agent.py b/py/examples/agno/async_team_agent.py deleted file mode 100644 index 47a9b83d1..000000000 --- a/py/examples/agno/async_team_agent.py +++ /dev/null @@ -1,70 +0,0 @@ -import asyncio - -from braintrust.wrappers.agno import setup_agno - -# Set up Braintrust observability -setup_agno(project_name="async-team-agent-project") - -from agno.agent import Agent -from agno.models.openai import OpenAIChat -from agno.team import Team -from agno.tools.yfinance import YFinanceTools - - -async def main(): - # Create specialized agents for the team - research_agent = Agent( - name="Research Analyst", - model=OpenAIChat(id="gpt-4o-mini"), - tools=[YFinanceTools()], - instructions="""You are a financial research analyst. Your job is to: - 1. Gather financial data and market information - 2. Analyze stock performance and trends - 3. Provide factual, data-driven insights - Keep your responses concise and focused on the data.""", - debug_mode=True, - ) - - advisor_agent = Agent( - name="Investment Advisor", - model=OpenAIChat(id="gpt-4o-mini"), - instructions="""You are an investment advisor. Your job is to: - 1. Take research findings from the analyst - 2. Provide investment recommendations - 3. Explain risk factors and potential outcomes - Always base recommendations on the research data provided.""", - debug_mode=True, - ) - - # Create a team with both agents - investment_team = Team( - name="Investment Research Team", - model=OpenAIChat(id="gpt-4o-mini"), - members=[research_agent, advisor_agent], - instructions="""You are a team of financial experts working together. - The Research Analyst should first gather and analyze data. - The Investment Advisor should then provide recommendations based on that analysis. - Work collaboratively to provide comprehensive financial advice.""", - debug_mode=True, - ) - - await investment_team.aprint_response( - "I'm considering investing in Apple (AAPL). Can you analyze the current stock performance and give me investment advice?", - session_id="team_session_apple", - stream=True, - ) - - await investment_team.aprint_response( - "Compare Microsoft (MSFT) and Google (GOOGL) for a long-term investment. Which would be better for a conservative portfolio?", - session_id="team_session_comparison", - stream=True, - ) - - await investment_team.aprint_response( - "What are the current trends in the tech sector? Should I be worried about market volatility?", - session_id="team_session_trends", - stream=True, - ) - - -asyncio.run(main()) diff --git a/py/examples/agno/simple_agent.py b/py/examples/agno/simple_agent.py deleted file mode 100644 index ce8822a28..000000000 --- a/py/examples/agno/simple_agent.py +++ /dev/null @@ -1,18 +0,0 @@ -from braintrust.wrappers.agno import setup_agno - -setup_agno(project_name="simple-agent-project") - -from agno.agent import Agent -from agno.models.openai import OpenAIChat -from agno.tools.yfinance import YFinanceTools - -# Create and configure the agent -agent = Agent( - name="Stock Price Agent", - model=OpenAIChat(id="gpt-4o-mini"), - tools=[YFinanceTools()], - instructions="You are a stock price agent. Answer questions in the style of a stock analyst.", -) - -response = agent.run("What is the current price of FIG?") -print(response.content) diff --git a/py/examples/agno/simple_agent_stream.py b/py/examples/agno/simple_agent_stream.py deleted file mode 100644 index d842649cd..000000000 --- a/py/examples/agno/simple_agent_stream.py +++ /dev/null @@ -1,18 +0,0 @@ -from braintrust.wrappers.agno import setup_agno - -setup_agno(project_name="simple-agent-project") - -from agno.agent import Agent -from agno.models.openai import OpenAIChat -from agno.tools.yfinance import YFinanceTools - -# Create and configure the agent -agent = Agent( - name="Stock Price Agent", - model=OpenAIChat(id="gpt-4o-mini"), - tools=[YFinanceTools()], - instructions="You are a stock price agent. Answer questions in the style of a stock analyst.", -) - -for message in agent.run("What is the current price of FIG?", stream=True): - print(message) diff --git a/py/examples/agno/team_agent.py b/py/examples/agno/team_agent.py deleted file mode 100644 index c9bc86f60..000000000 --- a/py/examples/agno/team_agent.py +++ /dev/null @@ -1,61 +0,0 @@ -from braintrust.wrappers.agno import setup_agno - -# Set up Braintrust observability -setup_agno(project_name="team-agent-project") - -from agno.agent import Agent -from agno.models.openai import OpenAIChat -from agno.team import Team -from agno.tools.yfinance import YFinanceTools - -# Create specialized agents for the team -research_agent = Agent( - name="Research Analyst", - model=OpenAIChat(id="gpt-4o-mini"), - tools=[YFinanceTools()], - instructions="""You are a financial research analyst. Your job is to: - 1. Gather financial data and market information - 2. Analyze stock performance and trends - 3. Provide factual, data-driven insights - Keep your responses concise and focused on the data.""", - debug_mode=True, -) - -advisor_agent = Agent( - name="Investment Advisor", - model=OpenAIChat(id="gpt-4o-mini"), - instructions="""You are an investment advisor. Your job is to: - 1. Take research findings from the analyst - 2. Provide investment recommendations - 3. Explain risk factors and potential outcomes - Always base recommendations on the research data provided.""", - debug_mode=True, -) - -# Create a team with both agents -investment_team = Team( - name="Investment Research Team", - model=OpenAIChat(id="gpt-4o-mini"), - members=[research_agent, advisor_agent], - instructions="""You are a team of financial experts working together. - The Research Analyst should first gather and analyze data. - The Investment Advisor should then provide recommendations based on that analysis. - Work collaboratively to provide comprehensive financial advice.""", - debug_mode=True, -) - - -investment_team.print_response( - "I'm considering investing in Apple (AAPL). Can you analyze the current stock performance and give me investment advice?", - session_id="team_session_apple", -) - -investment_team.print_response( - "Compare Microsoft (MSFT) and Google (GOOGL) for a long-term investment. Which would be better for a conservative portfolio?", - session_id="team_session_comparison", -) - -investment_team.print_response( - "What are the current trends in the tech sector? Should I be worried about market volatility?", - session_id="team_session_trends", -) diff --git a/py/examples/anthropic_async.py b/py/examples/anthropic_async.py deleted file mode 100755 index 772084bbe..000000000 --- a/py/examples/anthropic_async.py +++ /dev/null @@ -1,72 +0,0 @@ -#!/usr/bin/env python - -import asyncio - -import braintrust -from anthropic import AsyncAnthropic - -# Initialize Anthropic client (needs ANTHROPIC_API_KEY) -client = braintrust.wrap_anthropic(AsyncAnthropic()) - -braintrust.init_logger(project="example-anthropic-app") - - -async def stream(): - async with client.messages.stream( - max_tokens=1024, - messages=[ - { - "role": "user", - "content": "Write me a haiku about a stream.", - } - ], - model="claude-3-5-sonnet-latest", - ) as stream: - # Process the stream - async for event in stream: - # You can process events here if needed - # For example: print(event) or handle specific event types - pass - - # Get the final message within the context manager - msg = await stream.get_final_message() - print(msg.to_json()) - - -async def create(): - msg = await client.messages.create( - model="claude-3-5-sonnet-latest", - max_tokens=1024, - messages=[ - {"role": "user", "content": "Write me a haiku about creation."}, - ], - ) - print(msg.to_json()) - - -async def create_with_stream(): - stream = await client.messages.create( - model="claude-3-5-sonnet-latest", - max_tokens=1024, - messages=[ - {"role": "user", "content": "Write me a haiku about creation."}, - ], - stream=True, - ) - - async for event in stream: - print(event.to_json()) - - -async def main() -> None: - promises = [] - for target in [stream, create, create_with_stream]: - print(f"Running {target.__name__}") - promises.append(target()) - - for promise in promises: - msg = await promise - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/py/examples/anthropic_sync.py b/py/examples/anthropic_sync.py deleted file mode 100755 index 23e70fdb3..000000000 --- a/py/examples/anthropic_sync.py +++ /dev/null @@ -1,57 +0,0 @@ -#!/usr/bin/env python -""" -An app demonstrating how to wrap the sync Anthropic Client. -""" - -import anthropic -import braintrust - -# Initialize Anthropic client (needs ANTHROPIC_API_KEY) -client = braintrust.wrap_anthropic(anthropic.Anthropic()) -braintrust.init_logger(project="example-anthropic-app") - - -@braintrust.traced -def ask_anthropic_sync(question, system=None): - args = { - "model": "claude-3-haiku-20240307", - "max_tokens": 300, - "temperature": 0.5, - "messages": [{"role": "user", "content": question}], - } - if system: - args["system"] = system - msg = client.messages.create(**args) - print(msg) - - -@braintrust.traced -def ask_anthropic_stream(question, system=None): - args = { - "max_tokens": 1024, - "model": "claude-3-haiku-20240307", - "messages": [{"role": "user", "content": question}], - } - if system: - args["system"] = system - with client.messages.stream(**args) as stream: - for msg in stream: - pass - message = stream.get_final_message() - print(message) - - -@braintrust.traced -def ask_anthropic(): - print("asking questions") - # Ask each question and display the response - ask_anthropic_sync("What is the capital of Canada?") - ask_anthropic_stream("What is the date tomrrow?", "today is 2025-03-26") - - -def main(): - ask_anthropic() - - -if __name__ == "__main__": - main() diff --git a/py/examples/auto_instrument.py b/py/examples/auto_instrument.py deleted file mode 100644 index 33fa278a8..000000000 --- a/py/examples/auto_instrument.py +++ /dev/null @@ -1,69 +0,0 @@ -""" -Example: Auto-instrumentation with Braintrust - -This example demonstrates one-line auto-instrumentation for multiple AI libraries. -Run with: python examples/auto_instrument.py - -Supported integrations: -- OpenAI -- Anthropic -- LiteLLM -- Pydantic AI -- Google GenAI -- Agno -- Claude Agent SDK -- DSPy -""" - -import braintrust - -# One-line instrumentation - call this BEFORE importing AI libraries -# This patches all supported libraries automatically -results = braintrust.auto_instrument() - -# Show what was instrumented -print("Instrumentation results:") -for lib, success in results.items(): - status = "yes" if success else "no (not installed)" - print(f" {lib}: {status}") -print() - -# Initialize Braintrust logging -logger = braintrust.init_logger(project="auto-instrument-demo") - -# Now import and use AI libraries normally - all calls are traced! -# IMPORTANT: Import AI libraries AFTER calling auto_instrument() -import anthropic -import openai - -# Create clients - they're automatically wrapped -openai_client = openai.OpenAI() -anthropic_client = anthropic.Anthropic() - -# Wrap in a manual span to get a link -with braintrust.start_span(name="auto_instrument_example") as span: - # OpenAI call - automatically traced as child span - print("Calling OpenAI...") - openai_response = openai_client.chat.completions.create( - model="gpt-4o-mini", - messages=[{"role": "user", "content": "Say hello in 3 words"}], - ) - print(f" OpenAI: {openai_response.choices[0].message.content}") - - # Anthropic call - automatically traced as child span - print("Calling Anthropic...") - anthropic_response = anthropic_client.messages.create( - model="claude-3-5-haiku-latest", - max_tokens=100, - messages=[{"role": "user", "content": "Say goodbye in 3 words"}], - ) - print(f" Anthropic: {anthropic_response.content[0].text}") - - span.log( - output={ - "openai": openai_response.choices[0].message.content, - "anthropic": anthropic_response.content[0].text, - } - ) - -print(f"\nView trace: {span.link()}") diff --git a/py/examples/dspy/example.py b/py/examples/dspy/example.py deleted file mode 100644 index 8a53b9aef..000000000 --- a/py/examples/dspy/example.py +++ /dev/null @@ -1,76 +0,0 @@ -#!/usr/bin/env python -""" -DSPy example with Braintrust observability - demonstrates all key features in one trace: -- Custom module with multi-step reasoning (ChainOfThought) -- Tool usage (ReAct agent with calculator) -- Rich span hierarchy and metrics - -Run with: OPENAI_API_KEY= BRAINTRUST_API_KEY= python examples/dspy/example.py -""" - -# IMPORTANT: Patch LiteLLM BEFORE importing DSPy to get detailed token metrics -from braintrust.wrappers.litellm import patch_litellm - -patch_litellm() - -# Now import DSPy -import dspy -from braintrust import init_logger -from braintrust.wrappers.dspy import BraintrustDSpyCallback - - -def main(): - # Initialize Braintrust logging - logger = init_logger(project="dspy-example") - print("๐Ÿ” Braintrust logging enabled - view traces at https://braintrust.dev") - - # Disable DSPy's disk cache (keep memory cache for performance) - dspy.configure_cache(enable_disk_cache=False, enable_memory_cache=True) - - # Configure DSPy with Braintrust callback - lm = dspy.LM("openai/gpt-4o-mini") - dspy.configure(lm=lm, callbacks=[BraintrustDSpyCallback()]) - - print("\n" + "=" * 60) - print("DSPy + Braintrust Example") - print("=" * 60) - - # ReAct agent with tools demonstrates: - # - Multi-step reasoning - # - Tool calling (calculator, get_current_year) - # - Rich nested span hierarchy - print("\nReAct Agent with Tools") - print("-" * 60) - - def calculator(expression: str) -> float: - """Evaluate a mathematical expression.""" - return eval(expression, {"__builtins__": {}}, {}) - - def get_current_year() -> int: - """Get the current year.""" - return 2025 - - react = dspy.ReAct("question -> answer", tools=[calculator, get_current_year]) - - # This single question creates a rich trace with: - # - Module span (ReAct) - # - Multiple LM spans (reasoning steps) - # - Tool spans (calculator, get_current_year, finish) - # - Complete token metrics from LiteLLM - question = "If I was born in 1990, how old will I be in the current year?" - result = react(question=question) - - print(f"Q: {question}") - print(f"A: {result.answer}") - - print("\n" + "=" * 60) - print("โœ“ Trace logged to Braintrust with full observability:") - print(" - Module execution (ReAct)") - print(" - LLM calls with token metrics") - print(" - Tool invocations (calculator, get_current_year)") - print(" - Complete span hierarchy") - print("=" * 60) - - -if __name__ == "__main__": - main() diff --git a/py/examples/evals/eval_example.py b/py/examples/evals/eval_example.py deleted file mode 100644 index 1d605a080..000000000 --- a/py/examples/evals/eval_example.py +++ /dev/null @@ -1,95 +0,0 @@ -import json - -from braintrust import Eval - -NUM_EXAMPLES = 10 - - -async def exact_match_scorer(input, output, expected, trace=None): - """Async scorer that prints trace spans.""" - score = 0.0 - if expected is not None: - score = 1.0 if output == expected else 0.0 - - if trace: - print("\n" + "="*80) - print(f"๐Ÿ” TRACE INFO for input: {input}") - print("="*80) - - # Print trace configuration - config = trace.get_configuration() - print(f"\n๐Ÿ“‹ Configuration:") - print(f" Object Type: {config.get('objectType')}") - print(f" Object ID: {config.get('objectId')}") - print(f" Root Span: {config.get('rootSpanId')}") - - # Fetch and print spans - try: - spans = await trace.get_spans() - print(f"\nโœจ Found {len(spans)} spans:") - print("-"*80) - - for i, span in enumerate(spans, 1): - print(f"\n Span {i}:") - print(f" ID: {span.span_id}") - span_type = span.span_attributes.get('type', 'N/A') if span.span_attributes else 'N/A' - span_name = span.span_attributes.get('name', 'N/A') if span.span_attributes else 'N/A' - print(f" Type: {span_type}") - print(f" Name: {span_name}") - - if span.input: - input_str = json.dumps(span.input) - if len(input_str) > 100: - input_str = input_str[:100] + "..." - print(f" Input: {input_str}") - if span.output: - output_str = json.dumps(span.output) - if len(output_str) > 100: - output_str = output_str[:100] + "..." - print(f" Output: {output_str}") - if span.metadata: - print(f" Metadata: {list(span.metadata.keys())}") - - print("\n" + "="*80 + "\n") - except Exception as e: - print(f"\nโš ๏ธ Error fetching spans: {e}") - import traceback - traceback.print_exc() - else: - print(f"โš ๏ธ No trace available for input: {input}") - - return score - - -def data_fn(): - data = [] - for i in range(NUM_EXAMPLES): - names = [ - "Foo", - "Bar", - "Alice", - "Bob", - "Charlie", - "Diana", - "Eve", - "Frank", - ] - greetings = ["Hi", "Hello", "Hey", "Greetings"] - - name = names[i % len(names)] - greeting = greetings[i % len(greetings)] - - data.append({"input": name, "expected": f"{greeting} {name}"}) - return data - - -def task_fn(input, hooks=None): - return f"Hi {input}" - - -Eval( - "queue-test", - data=data_fn, - task=task_fn, - scores=[exact_match_scorer], -) diff --git a/py/examples/evals/simple_eval.py b/py/examples/evals/simple_eval.py deleted file mode 100644 index 6d12e005e..000000000 --- a/py/examples/evals/simple_eval.py +++ /dev/null @@ -1,26 +0,0 @@ -import re - -from braintrust import Eval - - -def task(input: str, hooks) -> str: - match = re.search(r"(\d+)\+(\d+)", input) - if match: - return str(int(match.group(1)) + int(match.group(2))) - return "I don't know" - - -def simple_scorer(output, expected): - """Simple hardcoded scorer that always returns 0.5""" - return 0.5 - - -Eval( - "simple-math-eval", - data=[ - {"input": "What is 2+2?", "expected": "4"}, - {"input": "What is 3+3?", "expected": "6"}, - ], - task=task, - scores=[simple_scorer], -) diff --git a/py/examples/langsmith/README.md b/py/examples/langsmith/README.md deleted file mode 100644 index f9f706e0f..000000000 --- a/py/examples/langsmith/README.md +++ /dev/null @@ -1,81 +0,0 @@ -# LangSmith to Braintrust Migration Examples - -Examples demonstrating how to migrate from LangSmith to Braintrust using the compatibility wrapper. - -## Setup - -```bash -cd sdk/py/examples/langsmith - -# Install dependencies with uv -uv sync - -# Set your API key -export BRAINTRUST_API_KEY="your-braintrust-api-key" -``` - -## Migration Modes - -The wrapper supports two modes: - -### 1. Wrapping Mode (default) - -Both LangSmith and Braintrust tracing are active. Use this during migration to verify everything works before fully switching. - -```python -from braintrust.wrappers.langsmith import setup_langsmith - -setup_langsmith(project_name="my-project") -``` - -### 2. Standalone Mode - -Only Braintrust runs - LangSmith code is completely replaced. Use this when you're ready to fully migrate. - -```python -from braintrust.wrappers.langsmith import setup_langsmith - -setup_langsmith(project_name="my-project", standalone=True) -``` - -## Running the Examples - -### Tracing Example - -Shows how `@traceable` decorated functions work with Braintrust: - -```bash -# Wrapping mode (both LangSmith and Braintrust tracing) -python tracing_example.py - -# Standalone mode (Braintrust only) -BRAINTRUST_STANDALONE=1 python tracing_example.py -``` - -### Evaluation Example - -Shows how to migrate `client.evaluate()` calls to use Braintrust's evaluation framework: - -```bash -# Wrapping mode -python eval_example.py - -# Standalone mode -BRAINTRUST_STANDALONE=1 python eval_example.py -``` - -## What Gets Migrated - -| LangSmith | Braintrust | -| ------------------- | --------------------------------------------------------------------- | -| `@traceable` | `@traced` (runs both in wrapping mode, only Braintrust in standalone) | -| `client.evaluate()` | `Eval()` (always uses Braintrust) | -| `aevaluate()` | `EvalAsync()` (always uses Braintrust) | - -## Viewing Traces - -After running the examples, visit [https://www.braintrust.dev](https://www.braintrust.dev) and navigate to your project to see: - -- Function traces with inputs and outputs -- Evaluation results with scores -- Nested span hierarchies diff --git a/py/examples/langsmith/eval_example.py b/py/examples/langsmith/eval_example.py deleted file mode 100644 index 68c55152b..000000000 --- a/py/examples/langsmith/eval_example.py +++ /dev/null @@ -1,134 +0,0 @@ -#!/usr/bin/env python3 -# type: ignore -""" -Example showing how to migrate LangSmith evaluate() to Braintrust. - -This example demonstrates: -1. Setting up the LangSmith wrapper -2. Using client.evaluate() (redirects to Braintrust's Eval) -3. LangSmith-style evaluators working with Braintrust -""" - -import os - -# Enable LangSmith tracing (required for traces to be sent to LangSmith) -os.environ.setdefault("LANGCHAIN_TRACING_V2", "true") -os.environ.setdefault("LANGCHAIN_PROJECT", "examples-wrappers-langsmith-eval") - -# IMPORTANT: Call setup_langsmith BEFORE importing from langsmith -from braintrust.wrappers.langsmith_wrapper import setup_langsmith - -# Set BRAINTRUST_STANDALONE=1 to completely replace LangSmith with Braintrust -standalone = os.environ.get("BRAINTRUST_STANDALONE", "").lower() in ("1", "true", "yes") - -# project_name is automatically read from LANGCHAIN_PROJECT env var -setup_langsmith( - api_key=os.environ.get("BRAINTRUST_API_KEY"), - standalone=standalone, -) - -# Now import from langsmith - these are patched to use Braintrust -from langsmith import Client, traceable - - -# Define a target function (the function being evaluated) -# LangSmith requires the parameter to be named 'inputs' (or 'attachments'/'metadata') -@traceable(name="multiply") -def multiply(inputs: dict, **kwargs) -> int: - """Multiply two numbers. - - Args: - inputs: Dictionary with 'x' and 'y' keys - **kwargs: Additional arguments (e.g., langsmith_extra from LangSmith) - """ - return inputs["x"] * inputs["y"] - - -# Define LangSmith-style evaluators -# LangSmith evaluators use signature: (inputs, outputs, reference_outputs) -> bool | dict -# When target returns a plain value, LangSmith wraps it as {"output": value} -def exact_match_evaluator(inputs: dict, outputs: dict, reference_outputs: dict) -> dict: - """ - LangSmith-style evaluator that checks for exact match. - """ - expected = reference_outputs["output"] - actual = outputs["output"] - return { - "key": "exact_match", - "score": 1.0 if actual == expected else 0.0, - } - - -def range_evaluator(inputs: dict, outputs: dict, reference_outputs: dict) -> dict: - """ - LangSmith-style evaluator that checks if result is in expected range. - """ - actual = outputs["output"] - expected = reference_outputs["output"] - # Check if within 10% of expected - if expected == 0: - score = 1.0 if actual == 0 else 0.0 - else: - diff = abs(actual - expected) / abs(expected) - score = 1.0 if diff <= 0.1 else 0.0 - return { - "key": "within_range", - "score": score, - "metadata": {"actual": actual, "expected": expected}, - } - - -def main(): - print("LangSmith to Braintrust Evaluation Example") - print("=" * 50) - print() - - # Create a LangSmith client (patched to use Braintrust) - client = Client() - - # Create a dataset in LangSmith (proper LangSmith API usage) - dataset_name = "multiply-dataset-example" - - # Try to get or create the dataset - try: - dataset = client.read_dataset(dataset_name=dataset_name) - print(f"Using existing dataset: {dataset_name}") - except Exception: - # Create new dataset if it doesn't exist - dataset = client.create_dataset(dataset_name=dataset_name, description="Multiplication test dataset") - print(f"Created new dataset: {dataset_name}") - - # Create examples in the dataset (proper LangSmith API) - client.create_examples( - dataset_id=dataset.id, - examples=[ - {"inputs": {"x": 2, "y": 3}, "outputs": {"output": 6}}, - {"inputs": {"x": 5, "y": 5}, "outputs": {"output": 25}}, - {"inputs": {"x": 10, "y": 0}, "outputs": {"output": 0}}, - {"inputs": {"x": 7, "y": 8}, "outputs": {"output": 56}}, - ], - ) - print(f"Created {4} examples in dataset") - - print() - print("Running evaluation...") - print() - - # Run evaluation using LangSmith's API (redirects to Braintrust) - # Pass the dataset name - this is valid LangSmith API usage - client.evaluate( - multiply, # Target function - data=dataset_name, # Dataset name (valid LangSmith API) - evaluators=[exact_match_evaluator, range_evaluator], - experiment_prefix="multiply-test", - description="Testing multiplication function", - metadata={"version": "1.0", "migrated_from": "langsmith"}, - ) - print() - print("=" * 50) - print("โœ“ Evaluation completed!") - print("Check Braintrust to see the experiment results.") - - -if __name__ == "__main__": - main() diff --git a/py/examples/langsmith/pyproject.toml b/py/examples/langsmith/pyproject.toml deleted file mode 100644 index 059cdc670..000000000 --- a/py/examples/langsmith/pyproject.toml +++ /dev/null @@ -1,18 +0,0 @@ -[project] -name = "langsmith-migration-example" -version = "0.1.0" -description = "Example showing LangSmith to Braintrust migration" -readme = "README.md" -requires-python = ">=3.10" -dependencies = [ - "braintrust", - "langsmith", -] - -[tool.uv.sources] -braintrust = { path = "../..", editable = true } - -[dependency-groups] -dev = [ - "pytest>=9.0.2", -] diff --git a/py/examples/langsmith/tracing_example.py b/py/examples/langsmith/tracing_example.py deleted file mode 100644 index 242609f18..000000000 --- a/py/examples/langsmith/tracing_example.py +++ /dev/null @@ -1,84 +0,0 @@ -#!/usr/bin/env python3 -""" -Example showing how to migrate LangSmith @traceable to Braintrust. - -This example demonstrates: -1. Setting up the LangSmith wrapper -2. Using @traceable decorated functions (traces go to Braintrust) -3. Nested tracing with multiple functions -""" - -import os - -# Enable LangSmith tracing (required for traces to be sent to LangSmith) -os.environ.setdefault("LANGCHAIN_TRACING_V2", "true") -os.environ.setdefault("LANGCHAIN_PROJECT", "examples-wrappers-langsmith-tracing") - -# IMPORTANT: Call setup_langsmith BEFORE importing from langsmith -from braintrust.wrappers.langsmith_wrapper import setup_langsmith - -# Set BRAINTRUST_STANDALONE=1 to completely replace LangSmith with Braintrust -standalone = os.environ.get("BRAINTRUST_STANDALONE", "").lower() in ("1", "true", "yes") - -# project_name is automatically read from LANGCHAIN_PROJECT env var -setup_langsmith( - api_key=os.environ.get("BRAINTRUST_API_KEY"), - standalone=standalone, -) - -# Now import from langsmith - these are patched to use Braintrust -from langsmith import traceable - - -@traceable(name="format_prompt") -def format_prompt(question: str) -> str: - """Format a question into a prompt.""" - return f"Please answer the following question concisely:\n\n{question}" - - -@traceable(name="mock_llm_call") -def mock_llm_call(prompt: str) -> str: - """Simulate an LLM call (replace with real OpenAI/Anthropic call).""" - # In a real scenario, you'd call an LLM here - return f"This is a mock response to: {prompt[:50]}..." - - -@traceable(name="answer_question") -def answer_question(question: str) -> dict: - """ - Main function that answers a question. - - This creates a trace with nested spans for each step. - """ - prompt = format_prompt(question) - response = mock_llm_call(prompt) - return { - "question": question, - "answer": response, - } - - -def main(): - print("LangSmith to Braintrust Tracing Example") - print("=" * 50) - print() - - questions = [ - "What is the capital of France?", - "How does photosynthesis work?", - "What is 2 + 2?", - ] - - for question in questions: - print(f"Question: {question}") - result = answer_question(question) - print(f"Answer: {result['answer']}") - print() - - print("=" * 50) - print("โœ“ Example completed!") - print("Check Braintrust to see the traces.") - - -if __name__ == "__main__": - main() diff --git a/py/examples/langsmith/uv.lock b/py/examples/langsmith/uv.lock deleted file mode 100644 index 1618f3a1e..000000000 --- a/py/examples/langsmith/uv.lock +++ /dev/null @@ -1,966 +0,0 @@ -version = 1 -revision = 2 -requires-python = ">=3.10" - -[[package]] -name = "annotated-types" -version = "0.7.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" }, -] - -[[package]] -name = "anyio" -version = "4.12.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "exceptiongroup", marker = "python_full_version < '3.11'" }, - { name = "idna" }, - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/16/ce/8a777047513153587e5434fd752e89334ac33e379aa3497db860eeb60377/anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0", size = 228266, upload-time = "2025-11-28T23:37:38.911Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7f/9c/36c5c37947ebfb8c7f22e0eb6e4d188ee2d53aa3880f3f2744fb894f0cb1/anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb", size = 113362, upload-time = "2025-11-28T23:36:57.897Z" }, -] - -[[package]] -name = "braintrust" -version = "0.3.11" -source = { editable = "../../" } -dependencies = [ - { name = "chevron" }, - { name = "exceptiongroup" }, - { name = "gitpython" }, - { name = "python-dotenv" }, - { name = "python-slugify" }, - { name = "requests" }, - { name = "sseclient-py" }, - { name = "tqdm" }, - { name = "typing-extensions" }, - { name = "wrapt" }, -] - -[package.metadata] -requires-dist = [ - { name = "boto3", marker = "extra == 'all'" }, - { name = "boto3", marker = "extra == 'cli'" }, - { name = "chevron" }, - { name = "exceptiongroup", specifier = ">=1.2.0" }, - { name = "gitpython" }, - { name = "openai-agents", marker = "extra == 'all'" }, - { name = "openai-agents", marker = "extra == 'openai-agents'" }, - { name = "opentelemetry-api", marker = "extra == 'all'" }, - { name = "opentelemetry-api", marker = "extra == 'otel'" }, - { name = "opentelemetry-exporter-otlp-proto-http", marker = "extra == 'all'" }, - { name = "opentelemetry-exporter-otlp-proto-http", marker = "extra == 'otel'" }, - { name = "opentelemetry-sdk", marker = "extra == 'all'" }, - { name = "opentelemetry-sdk", marker = "extra == 'otel'" }, - { name = "psycopg2-binary", marker = "extra == 'all'" }, - { name = "psycopg2-binary", marker = "extra == 'cli'" }, - { name = "pydoc-markdown", marker = "extra == 'all'" }, - { name = "pydoc-markdown", marker = "extra == 'doc'" }, - { name = "python-dotenv" }, - { name = "python-slugify" }, - { name = "requests" }, - { name = "sseclient-py" }, - { name = "starlette", marker = "extra == 'all'" }, - { name = "starlette", marker = "extra == 'cli'" }, - { name = "temporalio", marker = "python_full_version >= '3.10' and extra == 'all'", specifier = ">=1.19.0" }, - { name = "temporalio", marker = "python_full_version >= '3.10' and extra == 'temporal'", specifier = ">=1.19.0" }, - { name = "tqdm" }, - { name = "typing-extensions", specifier = ">=4.1.0" }, - { name = "uv", marker = "extra == 'all'" }, - { name = "uv", marker = "extra == 'cli'" }, - { name = "uvicorn", marker = "extra == 'all'" }, - { name = "uvicorn", marker = "extra == 'cli'" }, - { name = "wrapt" }, -] -provides-extras = ["cli", "doc", "openai-agents", "otel", "temporal", "all"] - -[[package]] -name = "certifi" -version = "2025.11.12" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a2/8c/58f469717fa48465e4a50c014a0400602d3c437d7c0c468e17ada824da3a/certifi-2025.11.12.tar.gz", hash = "sha256:d8ab5478f2ecd78af242878415affce761ca6bc54a22a27e026d7c25357c3316", size = 160538, upload-time = "2025-11-12T02:54:51.517Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/70/7d/9bc192684cea499815ff478dfcdc13835ddf401365057044fb721ec6bddb/certifi-2025.11.12-py3-none-any.whl", hash = "sha256:97de8790030bbd5c2d96b7ec782fc2f7820ef8dba6db909ccf95449f2d062d4b", size = 159438, upload-time = "2025-11-12T02:54:49.735Z" }, -] - -[[package]] -name = "charset-normalizer" -version = "3.4.4" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/13/69/33ddede1939fdd074bce5434295f38fae7136463422fe4fd3e0e89b98062/charset_normalizer-3.4.4.tar.gz", hash = "sha256:94537985111c35f28720e43603b8e7b43a6ecfb2ce1d3058bbe955b73404e21a", size = 129418, upload-time = "2025-10-14T04:42:32.879Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/1f/b8/6d51fc1d52cbd52cd4ccedd5b5b2f0f6a11bbf6765c782298b0f3e808541/charset_normalizer-3.4.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:e824f1492727fa856dd6eda4f7cee25f8518a12f3c4a56a74e8095695089cf6d", size = 209709, upload-time = "2025-10-14T04:40:11.385Z" }, - { url = "https://files.pythonhosted.org/packages/5c/af/1f9d7f7faafe2ddfb6f72a2e07a548a629c61ad510fe60f9630309908fef/charset_normalizer-3.4.4-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4bd5d4137d500351a30687c2d3971758aac9a19208fc110ccb9d7188fbe709e8", size = 148814, upload-time = "2025-10-14T04:40:13.135Z" }, - { url = "https://files.pythonhosted.org/packages/79/3d/f2e3ac2bbc056ca0c204298ea4e3d9db9b4afe437812638759db2c976b5f/charset_normalizer-3.4.4-cp310-cp310-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:027f6de494925c0ab2a55eab46ae5129951638a49a34d87f4c3eda90f696b4ad", size = 144467, upload-time = "2025-10-14T04:40:14.728Z" }, - { url = "https://files.pythonhosted.org/packages/ec/85/1bf997003815e60d57de7bd972c57dc6950446a3e4ccac43bc3070721856/charset_normalizer-3.4.4-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:f820802628d2694cb7e56db99213f930856014862f3fd943d290ea8438d07ca8", size = 162280, upload-time = "2025-10-14T04:40:16.14Z" }, - { url = "https://files.pythonhosted.org/packages/3e/8e/6aa1952f56b192f54921c436b87f2aaf7c7a7c3d0d1a765547d64fd83c13/charset_normalizer-3.4.4-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:798d75d81754988d2565bff1b97ba5a44411867c0cf32b77a7e8f8d84796b10d", size = 159454, upload-time = "2025-10-14T04:40:17.567Z" }, - { url = "https://files.pythonhosted.org/packages/36/3b/60cbd1f8e93aa25d1c669c649b7a655b0b5fb4c571858910ea9332678558/charset_normalizer-3.4.4-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9d1bb833febdff5c8927f922386db610b49db6e0d4f4ee29601d71e7c2694313", size = 153609, upload-time = "2025-10-14T04:40:19.08Z" }, - { url = "https://files.pythonhosted.org/packages/64/91/6a13396948b8fd3c4b4fd5bc74d045f5637d78c9675585e8e9fbe5636554/charset_normalizer-3.4.4-cp310-cp310-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:9cd98cdc06614a2f768d2b7286d66805f94c48cde050acdbbb7db2600ab3197e", size = 151849, upload-time = "2025-10-14T04:40:20.607Z" }, - { url = "https://files.pythonhosted.org/packages/b7/7a/59482e28b9981d105691e968c544cc0df3b7d6133152fb3dcdc8f135da7a/charset_normalizer-3.4.4-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:077fbb858e903c73f6c9db43374fd213b0b6a778106bc7032446a8e8b5b38b93", size = 151586, upload-time = "2025-10-14T04:40:21.719Z" }, - { url = "https://files.pythonhosted.org/packages/92/59/f64ef6a1c4bdd2baf892b04cd78792ed8684fbc48d4c2afe467d96b4df57/charset_normalizer-3.4.4-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:244bfb999c71b35de57821b8ea746b24e863398194a4014e4c76adc2bbdfeff0", size = 145290, upload-time = "2025-10-14T04:40:23.069Z" }, - { url = "https://files.pythonhosted.org/packages/6b/63/3bf9f279ddfa641ffa1962b0db6a57a9c294361cc2f5fcac997049a00e9c/charset_normalizer-3.4.4-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:64b55f9dce520635f018f907ff1b0df1fdc31f2795a922fb49dd14fbcdf48c84", size = 163663, upload-time = "2025-10-14T04:40:24.17Z" }, - { url = "https://files.pythonhosted.org/packages/ed/09/c9e38fc8fa9e0849b172b581fd9803bdf6e694041127933934184e19f8c3/charset_normalizer-3.4.4-cp310-cp310-musllinux_1_2_riscv64.whl", hash = "sha256:faa3a41b2b66b6e50f84ae4a68c64fcd0c44355741c6374813a800cd6695db9e", size = 151964, upload-time = "2025-10-14T04:40:25.368Z" }, - { url = "https://files.pythonhosted.org/packages/d2/d1/d28b747e512d0da79d8b6a1ac18b7ab2ecfd81b2944c4c710e166d8dd09c/charset_normalizer-3.4.4-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:6515f3182dbe4ea06ced2d9e8666d97b46ef4c75e326b79bb624110f122551db", size = 161064, upload-time = "2025-10-14T04:40:26.806Z" }, - { url = "https://files.pythonhosted.org/packages/bb/9a/31d62b611d901c3b9e5500c36aab0ff5eb442043fb3a1c254200d3d397d9/charset_normalizer-3.4.4-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:cc00f04ed596e9dc0da42ed17ac5e596c6ccba999ba6bd92b0e0aef2f170f2d6", size = 155015, upload-time = "2025-10-14T04:40:28.284Z" }, - { url = "https://files.pythonhosted.org/packages/1f/f3/107e008fa2bff0c8b9319584174418e5e5285fef32f79d8ee6a430d0039c/charset_normalizer-3.4.4-cp310-cp310-win32.whl", hash = "sha256:f34be2938726fc13801220747472850852fe6b1ea75869a048d6f896838c896f", size = 99792, upload-time = "2025-10-14T04:40:29.613Z" }, - { url = "https://files.pythonhosted.org/packages/eb/66/e396e8a408843337d7315bab30dbf106c38966f1819f123257f5520f8a96/charset_normalizer-3.4.4-cp310-cp310-win_amd64.whl", hash = "sha256:a61900df84c667873b292c3de315a786dd8dac506704dea57bc957bd31e22c7d", size = 107198, upload-time = "2025-10-14T04:40:30.644Z" }, - { url = "https://files.pythonhosted.org/packages/b5/58/01b4f815bf0312704c267f2ccb6e5d42bcc7752340cd487bc9f8c3710597/charset_normalizer-3.4.4-cp310-cp310-win_arm64.whl", hash = "sha256:cead0978fc57397645f12578bfd2d5ea9138ea0fac82b2f63f7f7c6877986a69", size = 100262, upload-time = "2025-10-14T04:40:32.108Z" }, - { url = "https://files.pythonhosted.org/packages/ed/27/c6491ff4954e58a10f69ad90aca8a1b6fe9c5d3c6f380907af3c37435b59/charset_normalizer-3.4.4-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:6e1fcf0720908f200cd21aa4e6750a48ff6ce4afe7ff5a79a90d5ed8a08296f8", size = 206988, upload-time = "2025-10-14T04:40:33.79Z" }, - { url = "https://files.pythonhosted.org/packages/94/59/2e87300fe67ab820b5428580a53cad894272dbb97f38a7a814a2a1ac1011/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5f819d5fe9234f9f82d75bdfa9aef3a3d72c4d24a6e57aeaebba32a704553aa0", size = 147324, upload-time = "2025-10-14T04:40:34.961Z" }, - { url = "https://files.pythonhosted.org/packages/07/fb/0cf61dc84b2b088391830f6274cb57c82e4da8bbc2efeac8c025edb88772/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:a59cb51917aa591b1c4e6a43c132f0cdc3c76dbad6155df4e28ee626cc77a0a3", size = 142742, upload-time = "2025-10-14T04:40:36.105Z" }, - { url = "https://files.pythonhosted.org/packages/62/8b/171935adf2312cd745d290ed93cf16cf0dfe320863ab7cbeeae1dcd6535f/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:8ef3c867360f88ac904fd3f5e1f902f13307af9052646963ee08ff4f131adafc", size = 160863, upload-time = "2025-10-14T04:40:37.188Z" }, - { url = "https://files.pythonhosted.org/packages/09/73/ad875b192bda14f2173bfc1bc9a55e009808484a4b256748d931b6948442/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d9e45d7faa48ee908174d8fe84854479ef838fc6a705c9315372eacbc2f02897", size = 157837, upload-time = "2025-10-14T04:40:38.435Z" }, - { url = "https://files.pythonhosted.org/packages/6d/fc/de9cce525b2c5b94b47c70a4b4fb19f871b24995c728e957ee68ab1671ea/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:840c25fb618a231545cbab0564a799f101b63b9901f2569faecd6b222ac72381", size = 151550, upload-time = "2025-10-14T04:40:40.053Z" }, - { url = "https://files.pythonhosted.org/packages/55/c2/43edd615fdfba8c6f2dfbd459b25a6b3b551f24ea21981e23fb768503ce1/charset_normalizer-3.4.4-cp311-cp311-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:ca5862d5b3928c4940729dacc329aa9102900382fea192fc5e52eb69d6093815", size = 149162, upload-time = "2025-10-14T04:40:41.163Z" }, - { url = "https://files.pythonhosted.org/packages/03/86/bde4ad8b4d0e9429a4e82c1e8f5c659993a9a863ad62c7df05cf7b678d75/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:d9c7f57c3d666a53421049053eaacdd14bbd0a528e2186fcb2e672effd053bb0", size = 150019, upload-time = "2025-10-14T04:40:42.276Z" }, - { url = "https://files.pythonhosted.org/packages/1f/86/a151eb2af293a7e7bac3a739b81072585ce36ccfb4493039f49f1d3cae8c/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:277e970e750505ed74c832b4bf75dac7476262ee2a013f5574dd49075879e161", size = 143310, upload-time = "2025-10-14T04:40:43.439Z" }, - { url = "https://files.pythonhosted.org/packages/b5/fe/43dae6144a7e07b87478fdfc4dbe9efd5defb0e7ec29f5f58a55aeef7bf7/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:31fd66405eaf47bb62e8cd575dc621c56c668f27d46a61d975a249930dd5e2a4", size = 162022, upload-time = "2025-10-14T04:40:44.547Z" }, - { url = "https://files.pythonhosted.org/packages/80/e6/7aab83774f5d2bca81f42ac58d04caf44f0cc2b65fc6db2b3b2e8a05f3b3/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:0d3d8f15c07f86e9ff82319b3d9ef6f4bf907608f53fe9d92b28ea9ae3d1fd89", size = 149383, upload-time = "2025-10-14T04:40:46.018Z" }, - { url = "https://files.pythonhosted.org/packages/4f/e8/b289173b4edae05c0dde07f69f8db476a0b511eac556dfe0d6bda3c43384/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:9f7fcd74d410a36883701fafa2482a6af2ff5ba96b9a620e9e0721e28ead5569", size = 159098, upload-time = "2025-10-14T04:40:47.081Z" }, - { url = "https://files.pythonhosted.org/packages/d8/df/fe699727754cae3f8478493c7f45f777b17c3ef0600e28abfec8619eb49c/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ebf3e58c7ec8a8bed6d66a75d7fb37b55e5015b03ceae72a8e7c74495551e224", size = 152991, upload-time = "2025-10-14T04:40:48.246Z" }, - { url = "https://files.pythonhosted.org/packages/1a/86/584869fe4ddb6ffa3bd9f491b87a01568797fb9bd8933f557dba9771beaf/charset_normalizer-3.4.4-cp311-cp311-win32.whl", hash = "sha256:eecbc200c7fd5ddb9a7f16c7decb07b566c29fa2161a16cf67b8d068bd21690a", size = 99456, upload-time = "2025-10-14T04:40:49.376Z" }, - { url = "https://files.pythonhosted.org/packages/65/f6/62fdd5feb60530f50f7e38b4f6a1d5203f4d16ff4f9f0952962c044e919a/charset_normalizer-3.4.4-cp311-cp311-win_amd64.whl", hash = "sha256:5ae497466c7901d54b639cf42d5b8c1b6a4fead55215500d2f486d34db48d016", size = 106978, upload-time = "2025-10-14T04:40:50.844Z" }, - { url = "https://files.pythonhosted.org/packages/7a/9d/0710916e6c82948b3be62d9d398cb4fcf4e97b56d6a6aeccd66c4b2f2bd5/charset_normalizer-3.4.4-cp311-cp311-win_arm64.whl", hash = "sha256:65e2befcd84bc6f37095f5961e68a6f077bf44946771354a28ad434c2cce0ae1", size = 99969, upload-time = "2025-10-14T04:40:52.272Z" }, - { url = "https://files.pythonhosted.org/packages/f3/85/1637cd4af66fa687396e757dec650f28025f2a2f5a5531a3208dc0ec43f2/charset_normalizer-3.4.4-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:0a98e6759f854bd25a58a73fa88833fba3b7c491169f86ce1180c948ab3fd394", size = 208425, upload-time = "2025-10-14T04:40:53.353Z" }, - { url = "https://files.pythonhosted.org/packages/9d/6a/04130023fef2a0d9c62d0bae2649b69f7b7d8d24ea5536feef50551029df/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b5b290ccc2a263e8d185130284f8501e3e36c5e02750fc6b6bdeb2e9e96f1e25", size = 148162, upload-time = "2025-10-14T04:40:54.558Z" }, - { url = "https://files.pythonhosted.org/packages/78/29/62328d79aa60da22c9e0b9a66539feae06ca0f5a4171ac4f7dc285b83688/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:74bb723680f9f7a6234dcf67aea57e708ec1fbdf5699fb91dfd6f511b0a320ef", size = 144558, upload-time = "2025-10-14T04:40:55.677Z" }, - { url = "https://files.pythonhosted.org/packages/86/bb/b32194a4bf15b88403537c2e120b817c61cd4ecffa9b6876e941c3ee38fe/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:f1e34719c6ed0b92f418c7c780480b26b5d9c50349e9a9af7d76bf757530350d", size = 161497, upload-time = "2025-10-14T04:40:57.217Z" }, - { url = "https://files.pythonhosted.org/packages/19/89/a54c82b253d5b9b111dc74aca196ba5ccfcca8242d0fb64146d4d3183ff1/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:2437418e20515acec67d86e12bf70056a33abdacb5cb1655042f6538d6b085a8", size = 159240, upload-time = "2025-10-14T04:40:58.358Z" }, - { url = "https://files.pythonhosted.org/packages/c0/10/d20b513afe03acc89ec33948320a5544d31f21b05368436d580dec4e234d/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:11d694519d7f29d6cd09f6ac70028dba10f92f6cdd059096db198c283794ac86", size = 153471, upload-time = "2025-10-14T04:40:59.468Z" }, - { url = "https://files.pythonhosted.org/packages/61/fa/fbf177b55bdd727010f9c0a3c49eefa1d10f960e5f09d1d887bf93c2e698/charset_normalizer-3.4.4-cp312-cp312-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:ac1c4a689edcc530fc9d9aa11f5774b9e2f33f9a0c6a57864e90908f5208d30a", size = 150864, upload-time = "2025-10-14T04:41:00.623Z" }, - { url = "https://files.pythonhosted.org/packages/05/12/9fbc6a4d39c0198adeebbde20b619790e9236557ca59fc40e0e3cebe6f40/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:21d142cc6c0ec30d2efee5068ca36c128a30b0f2c53c1c07bd78cb6bc1d3be5f", size = 150647, upload-time = "2025-10-14T04:41:01.754Z" }, - { url = "https://files.pythonhosted.org/packages/ad/1f/6a9a593d52e3e8c5d2b167daf8c6b968808efb57ef4c210acb907c365bc4/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:5dbe56a36425d26d6cfb40ce79c314a2e4dd6211d51d6d2191c00bed34f354cc", size = 145110, upload-time = "2025-10-14T04:41:03.231Z" }, - { url = "https://files.pythonhosted.org/packages/30/42/9a52c609e72471b0fc54386dc63c3781a387bb4fe61c20231a4ebcd58bdd/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:5bfbb1b9acf3334612667b61bd3002196fe2a1eb4dd74d247e0f2a4d50ec9bbf", size = 162839, upload-time = "2025-10-14T04:41:04.715Z" }, - { url = "https://files.pythonhosted.org/packages/c4/5b/c0682bbf9f11597073052628ddd38344a3d673fda35a36773f7d19344b23/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:d055ec1e26e441f6187acf818b73564e6e6282709e9bcb5b63f5b23068356a15", size = 150667, upload-time = "2025-10-14T04:41:05.827Z" }, - { url = "https://files.pythonhosted.org/packages/e4/24/a41afeab6f990cf2daf6cb8c67419b63b48cf518e4f56022230840c9bfb2/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:af2d8c67d8e573d6de5bc30cdb27e9b95e49115cd9baad5ddbd1a6207aaa82a9", size = 160535, upload-time = "2025-10-14T04:41:06.938Z" }, - { url = "https://files.pythonhosted.org/packages/2a/e5/6a4ce77ed243c4a50a1fecca6aaaab419628c818a49434be428fe24c9957/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:780236ac706e66881f3b7f2f32dfe90507a09e67d1d454c762cf642e6e1586e0", size = 154816, upload-time = "2025-10-14T04:41:08.101Z" }, - { url = "https://files.pythonhosted.org/packages/a8/ef/89297262b8092b312d29cdb2517cb1237e51db8ecef2e9af5edbe7b683b1/charset_normalizer-3.4.4-cp312-cp312-win32.whl", hash = "sha256:5833d2c39d8896e4e19b689ffc198f08ea58116bee26dea51e362ecc7cd3ed26", size = 99694, upload-time = "2025-10-14T04:41:09.23Z" }, - { url = "https://files.pythonhosted.org/packages/3d/2d/1e5ed9dd3b3803994c155cd9aacb60c82c331bad84daf75bcb9c91b3295e/charset_normalizer-3.4.4-cp312-cp312-win_amd64.whl", hash = "sha256:a79cfe37875f822425b89a82333404539ae63dbdddf97f84dcbc3d339aae9525", size = 107131, upload-time = "2025-10-14T04:41:10.467Z" }, - { url = "https://files.pythonhosted.org/packages/d0/d9/0ed4c7098a861482a7b6a95603edce4c0d9db2311af23da1fb2b75ec26fc/charset_normalizer-3.4.4-cp312-cp312-win_arm64.whl", hash = "sha256:376bec83a63b8021bb5c8ea75e21c4ccb86e7e45ca4eb81146091b56599b80c3", size = 100390, upload-time = "2025-10-14T04:41:11.915Z" }, - { url = "https://files.pythonhosted.org/packages/97/45/4b3a1239bbacd321068ea6e7ac28875b03ab8bc0aa0966452db17cd36714/charset_normalizer-3.4.4-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:e1f185f86a6f3403aa2420e815904c67b2f9ebc443f045edd0de921108345794", size = 208091, upload-time = "2025-10-14T04:41:13.346Z" }, - { url = "https://files.pythonhosted.org/packages/7d/62/73a6d7450829655a35bb88a88fca7d736f9882a27eacdca2c6d505b57e2e/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6b39f987ae8ccdf0d2642338faf2abb1862340facc796048b604ef14919e55ed", size = 147936, upload-time = "2025-10-14T04:41:14.461Z" }, - { url = "https://files.pythonhosted.org/packages/89/c5/adb8c8b3d6625bef6d88b251bbb0d95f8205831b987631ab0c8bb5d937c2/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:3162d5d8ce1bb98dd51af660f2121c55d0fa541b46dff7bb9b9f86ea1d87de72", size = 144180, upload-time = "2025-10-14T04:41:15.588Z" }, - { url = "https://files.pythonhosted.org/packages/91/ed/9706e4070682d1cc219050b6048bfd293ccf67b3d4f5a4f39207453d4b99/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:81d5eb2a312700f4ecaa977a8235b634ce853200e828fbadf3a9c50bab278328", size = 161346, upload-time = "2025-10-14T04:41:16.738Z" }, - { url = "https://files.pythonhosted.org/packages/d5/0d/031f0d95e4972901a2f6f09ef055751805ff541511dc1252ba3ca1f80cf5/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:5bd2293095d766545ec1a8f612559f6b40abc0eb18bb2f5d1171872d34036ede", size = 158874, upload-time = "2025-10-14T04:41:17.923Z" }, - { url = "https://files.pythonhosted.org/packages/f5/83/6ab5883f57c9c801ce5e5677242328aa45592be8a00644310a008d04f922/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a8a8b89589086a25749f471e6a900d3f662d1d3b6e2e59dcecf787b1cc3a1894", size = 153076, upload-time = "2025-10-14T04:41:19.106Z" }, - { url = "https://files.pythonhosted.org/packages/75/1e/5ff781ddf5260e387d6419959ee89ef13878229732732ee73cdae01800f2/charset_normalizer-3.4.4-cp313-cp313-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:bc7637e2f80d8530ee4a78e878bce464f70087ce73cf7c1caf142416923b98f1", size = 150601, upload-time = "2025-10-14T04:41:20.245Z" }, - { url = "https://files.pythonhosted.org/packages/d7/57/71be810965493d3510a6ca79b90c19e48696fb1ff964da319334b12677f0/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f8bf04158c6b607d747e93949aa60618b61312fe647a6369f88ce2ff16043490", size = 150376, upload-time = "2025-10-14T04:41:21.398Z" }, - { url = "https://files.pythonhosted.org/packages/e5/d5/c3d057a78c181d007014feb7e9f2e65905a6c4ef182c0ddf0de2924edd65/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:554af85e960429cf30784dd47447d5125aaa3b99a6f0683589dbd27e2f45da44", size = 144825, upload-time = "2025-10-14T04:41:22.583Z" }, - { url = "https://files.pythonhosted.org/packages/e6/8c/d0406294828d4976f275ffbe66f00266c4b3136b7506941d87c00cab5272/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:74018750915ee7ad843a774364e13a3db91682f26142baddf775342c3f5b1133", size = 162583, upload-time = "2025-10-14T04:41:23.754Z" }, - { url = "https://files.pythonhosted.org/packages/d7/24/e2aa1f18c8f15c4c0e932d9287b8609dd30ad56dbe41d926bd846e22fb8d/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:c0463276121fdee9c49b98908b3a89c39be45d86d1dbaa22957e38f6321d4ce3", size = 150366, upload-time = "2025-10-14T04:41:25.27Z" }, - { url = "https://files.pythonhosted.org/packages/e4/5b/1e6160c7739aad1e2df054300cc618b06bf784a7a164b0f238360721ab86/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:362d61fd13843997c1c446760ef36f240cf81d3ebf74ac62652aebaf7838561e", size = 160300, upload-time = "2025-10-14T04:41:26.725Z" }, - { url = "https://files.pythonhosted.org/packages/7a/10/f882167cd207fbdd743e55534d5d9620e095089d176d55cb22d5322f2afd/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:9a26f18905b8dd5d685d6d07b0cdf98a79f3c7a918906af7cc143ea2e164c8bc", size = 154465, upload-time = "2025-10-14T04:41:28.322Z" }, - { url = "https://files.pythonhosted.org/packages/89/66/c7a9e1b7429be72123441bfdbaf2bc13faab3f90b933f664db506dea5915/charset_normalizer-3.4.4-cp313-cp313-win32.whl", hash = "sha256:9b35f4c90079ff2e2edc5b26c0c77925e5d2d255c42c74fdb70fb49b172726ac", size = 99404, upload-time = "2025-10-14T04:41:29.95Z" }, - { url = "https://files.pythonhosted.org/packages/c4/26/b9924fa27db384bdcd97ab83b4f0a8058d96ad9626ead570674d5e737d90/charset_normalizer-3.4.4-cp313-cp313-win_amd64.whl", hash = "sha256:b435cba5f4f750aa6c0a0d92c541fb79f69a387c91e61f1795227e4ed9cece14", size = 107092, upload-time = "2025-10-14T04:41:31.188Z" }, - { url = "https://files.pythonhosted.org/packages/af/8f/3ed4bfa0c0c72a7ca17f0380cd9e4dd842b09f664e780c13cff1dcf2ef1b/charset_normalizer-3.4.4-cp313-cp313-win_arm64.whl", hash = "sha256:542d2cee80be6f80247095cc36c418f7bddd14f4a6de45af91dfad36d817bba2", size = 100408, upload-time = "2025-10-14T04:41:32.624Z" }, - { url = "https://files.pythonhosted.org/packages/2a/35/7051599bd493e62411d6ede36fd5af83a38f37c4767b92884df7301db25d/charset_normalizer-3.4.4-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:da3326d9e65ef63a817ecbcc0df6e94463713b754fe293eaa03da99befb9a5bd", size = 207746, upload-time = "2025-10-14T04:41:33.773Z" }, - { url = "https://files.pythonhosted.org/packages/10/9a/97c8d48ef10d6cd4fcead2415523221624bf58bcf68a802721a6bc807c8f/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8af65f14dc14a79b924524b1e7fffe304517b2bff5a58bf64f30b98bbc5079eb", size = 147889, upload-time = "2025-10-14T04:41:34.897Z" }, - { url = "https://files.pythonhosted.org/packages/10/bf/979224a919a1b606c82bd2c5fa49b5c6d5727aa47b4312bb27b1734f53cd/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:74664978bb272435107de04e36db5a9735e78232b85b77d45cfb38f758efd33e", size = 143641, upload-time = "2025-10-14T04:41:36.116Z" }, - { url = "https://files.pythonhosted.org/packages/ba/33/0ad65587441fc730dc7bd90e9716b30b4702dc7b617e6ba4997dc8651495/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:752944c7ffbfdd10c074dc58ec2d5a8a4cd9493b314d367c14d24c17684ddd14", size = 160779, upload-time = "2025-10-14T04:41:37.229Z" }, - { url = "https://files.pythonhosted.org/packages/67/ed/331d6b249259ee71ddea93f6f2f0a56cfebd46938bde6fcc6f7b9a3d0e09/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d1f13550535ad8cff21b8d757a3257963e951d96e20ec82ab44bc64aeb62a191", size = 159035, upload-time = "2025-10-14T04:41:38.368Z" }, - { url = "https://files.pythonhosted.org/packages/67/ff/f6b948ca32e4f2a4576aa129d8bed61f2e0543bf9f5f2b7fc3758ed005c9/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ecaae4149d99b1c9e7b88bb03e3221956f68fd6d50be2ef061b2381b61d20838", size = 152542, upload-time = "2025-10-14T04:41:39.862Z" }, - { url = "https://files.pythonhosted.org/packages/16/85/276033dcbcc369eb176594de22728541a925b2632f9716428c851b149e83/charset_normalizer-3.4.4-cp314-cp314-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:cb6254dc36b47a990e59e1068afacdcd02958bdcce30bb50cc1700a8b9d624a6", size = 149524, upload-time = "2025-10-14T04:41:41.319Z" }, - { url = "https://files.pythonhosted.org/packages/9e/f2/6a2a1f722b6aba37050e626530a46a68f74e63683947a8acff92569f979a/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:c8ae8a0f02f57a6e61203a31428fa1d677cbe50c93622b4149d5c0f319c1d19e", size = 150395, upload-time = "2025-10-14T04:41:42.539Z" }, - { url = "https://files.pythonhosted.org/packages/60/bb/2186cb2f2bbaea6338cad15ce23a67f9b0672929744381e28b0592676824/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:47cc91b2f4dd2833fddaedd2893006b0106129d4b94fdb6af1f4ce5a9965577c", size = 143680, upload-time = "2025-10-14T04:41:43.661Z" }, - { url = "https://files.pythonhosted.org/packages/7d/a5/bf6f13b772fbb2a90360eb620d52ed8f796f3c5caee8398c3b2eb7b1c60d/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:82004af6c302b5d3ab2cfc4cc5f29db16123b1a8417f2e25f9066f91d4411090", size = 162045, upload-time = "2025-10-14T04:41:44.821Z" }, - { url = "https://files.pythonhosted.org/packages/df/c5/d1be898bf0dc3ef9030c3825e5d3b83f2c528d207d246cbabe245966808d/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:2b7d8f6c26245217bd2ad053761201e9f9680f8ce52f0fcd8d0755aeae5b2152", size = 149687, upload-time = "2025-10-14T04:41:46.442Z" }, - { url = "https://files.pythonhosted.org/packages/a5/42/90c1f7b9341eef50c8a1cb3f098ac43b0508413f33affd762855f67a410e/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:799a7a5e4fb2d5898c60b640fd4981d6a25f1c11790935a44ce38c54e985f828", size = 160014, upload-time = "2025-10-14T04:41:47.631Z" }, - { url = "https://files.pythonhosted.org/packages/76/be/4d3ee471e8145d12795ab655ece37baed0929462a86e72372fd25859047c/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:99ae2cffebb06e6c22bdc25801d7b30f503cc87dbd283479e7b606f70aff57ec", size = 154044, upload-time = "2025-10-14T04:41:48.81Z" }, - { url = "https://files.pythonhosted.org/packages/b0/6f/8f7af07237c34a1defe7defc565a9bc1807762f672c0fde711a4b22bf9c0/charset_normalizer-3.4.4-cp314-cp314-win32.whl", hash = "sha256:f9d332f8c2a2fcbffe1378594431458ddbef721c1769d78e2cbc06280d8155f9", size = 99940, upload-time = "2025-10-14T04:41:49.946Z" }, - { url = "https://files.pythonhosted.org/packages/4b/51/8ade005e5ca5b0d80fb4aff72a3775b325bdc3d27408c8113811a7cbe640/charset_normalizer-3.4.4-cp314-cp314-win_amd64.whl", hash = "sha256:8a6562c3700cce886c5be75ade4a5db4214fda19fede41d9792d100288d8f94c", size = 107104, upload-time = "2025-10-14T04:41:51.051Z" }, - { url = "https://files.pythonhosted.org/packages/da/5f/6b8f83a55bb8278772c5ae54a577f3099025f9ade59d0136ac24a0df4bde/charset_normalizer-3.4.4-cp314-cp314-win_arm64.whl", hash = "sha256:de00632ca48df9daf77a2c65a484531649261ec9f25489917f09e455cb09ddb2", size = 100743, upload-time = "2025-10-14T04:41:52.122Z" }, - { url = "https://files.pythonhosted.org/packages/0a/4c/925909008ed5a988ccbb72dcc897407e5d6d3bd72410d69e051fc0c14647/charset_normalizer-3.4.4-py3-none-any.whl", hash = "sha256:7a32c560861a02ff789ad905a2fe94e3f840803362c84fecf1851cb4cf3dc37f", size = 53402, upload-time = "2025-10-14T04:42:31.76Z" }, -] - -[[package]] -name = "chevron" -version = "0.14.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/15/1f/ca74b65b19798895d63a6e92874162f44233467c9e7c1ed8afd19016ebe9/chevron-0.14.0.tar.gz", hash = "sha256:87613aafdf6d77b6a90ff073165a61ae5086e21ad49057aa0e53681601800ebf", size = 11440, upload-time = "2021-01-02T22:47:59.233Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/52/93/342cc62a70ab727e093ed98e02a725d85b746345f05d2b5e5034649f4ec8/chevron-0.14.0-py3-none-any.whl", hash = "sha256:fbf996a709f8da2e745ef763f482ce2d311aa817d287593a5b990d6d6e4f0443", size = 11595, upload-time = "2021-01-02T22:47:57.847Z" }, -] - -[[package]] -name = "colorama" -version = "0.4.6" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/d8/53/6f443c9a4a8358a93a6792e2acffb9d9d5cb0a5cfd8802644b7b1c9a02e4/colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44", size = 27697, upload-time = "2022-10-25T02:36:22.414Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335, upload-time = "2022-10-25T02:36:20.889Z" }, -] - -[[package]] -name = "exceptiongroup" -version = "1.3.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions", marker = "python_full_version < '3.13'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/50/79/66800aadf48771f6b62f7eb014e352e5d06856655206165d775e675a02c9/exceptiongroup-1.3.1.tar.gz", hash = "sha256:8b412432c6055b0b7d14c310000ae93352ed6754f70fa8f7c34141f91c4e3219", size = 30371, upload-time = "2025-11-21T23:01:54.787Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl", hash = "sha256:a7a39a3bd276781e98394987d3a5701d0c4edffb633bb7a5144577f82c773598", size = 16740, upload-time = "2025-11-21T23:01:53.443Z" }, -] - -[[package]] -name = "gitdb" -version = "4.0.12" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "smmap" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/72/94/63b0fc47eb32792c7ba1fe1b694daec9a63620db1e313033d18140c2320a/gitdb-4.0.12.tar.gz", hash = "sha256:5ef71f855d191a3326fcfbc0d5da835f26b13fbcba60c32c21091c349ffdb571", size = 394684, upload-time = "2025-01-02T07:20:46.413Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a0/61/5c78b91c3143ed5c14207f463aecfc8f9dbb5092fb2869baf37c273b2705/gitdb-4.0.12-py3-none-any.whl", hash = "sha256:67073e15955400952c6565cc3e707c554a4eea2e428946f7a4c162fab9bd9bcf", size = 62794, upload-time = "2025-01-02T07:20:43.624Z" }, -] - -[[package]] -name = "gitpython" -version = "3.1.45" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "gitdb" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/9a/c8/dd58967d119baab745caec2f9d853297cec1989ec1d63f677d3880632b88/gitpython-3.1.45.tar.gz", hash = "sha256:85b0ee964ceddf211c41b9f27a49086010a190fd8132a24e21f362a4b36a791c", size = 215076, upload-time = "2025-07-24T03:45:54.871Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/01/61/d4b89fec821f72385526e1b9d9a3a0385dda4a72b206d28049e2c7cd39b8/gitpython-3.1.45-py3-none-any.whl", hash = "sha256:8908cb2e02fb3b93b7eb0f2827125cb699869470432cc885f019b8fd0fccff77", size = 208168, upload-time = "2025-07-24T03:45:52.517Z" }, -] - -[[package]] -name = "h11" -version = "0.16.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/01/ee/02a2c011bdab74c6fb3c75474d40b3052059d95df7e73351460c8588d963/h11-0.16.0.tar.gz", hash = "sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1", size = 101250, upload-time = "2025-04-24T03:35:25.427Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/04/4b/29cac41a4d98d144bf5f6d33995617b185d14b22401f75ca86f384e87ff1/h11-0.16.0-py3-none-any.whl", hash = "sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86", size = 37515, upload-time = "2025-04-24T03:35:24.344Z" }, -] - -[[package]] -name = "httpcore" -version = "1.0.9" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "certifi" }, - { name = "h11" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/06/94/82699a10bca87a5556c9c59b5963f2d039dbd239f25bc2a63907a05a14cb/httpcore-1.0.9.tar.gz", hash = "sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8", size = 85484, upload-time = "2025-04-24T22:06:22.219Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55", size = 78784, upload-time = "2025-04-24T22:06:20.566Z" }, -] - -[[package]] -name = "httpx" -version = "0.28.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "anyio" }, - { name = "certifi" }, - { name = "httpcore" }, - { name = "idna" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/b1/df/48c586a5fe32a0f01324ee087459e112ebb7224f646c0b5023f5e79e9956/httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc", size = 141406, upload-time = "2024-12-06T15:37:23.222Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad", size = 73517, upload-time = "2024-12-06T15:37:21.509Z" }, -] - -[[package]] -name = "idna" -version = "3.11" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/6f/6d/0703ccc57f3a7233505399edb88de3cbd678da106337b9fcde432b65ed60/idna-3.11.tar.gz", hash = "sha256:795dafcc9c04ed0c1fb032c2aa73654d8e8c5023a7df64a53f39190ada629902", size = 194582, upload-time = "2025-10-12T14:55:20.501Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl", hash = "sha256:771a87f49d9defaf64091e6e6fe9c18d4833f140bd19464795bc32d966ca37ea", size = 71008, upload-time = "2025-10-12T14:55:18.883Z" }, -] - -[[package]] -name = "iniconfig" -version = "2.3.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/72/34/14ca021ce8e5dfedc35312d08ba8bf51fdd999c576889fc2c24cb97f4f10/iniconfig-2.3.0.tar.gz", hash = "sha256:c76315c77db068650d49c5b56314774a7804df16fee4402c1f19d6d15d8c4730", size = 20503, upload-time = "2025-10-18T21:55:43.219Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl", hash = "sha256:f631c04d2c48c52b84d0d0549c99ff3859c98df65b3101406327ecc7d53fbf12", size = 7484, upload-time = "2025-10-18T21:55:41.639Z" }, -] - -[[package]] -name = "langsmith" -version = "0.4.56" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "httpx" }, - { name = "orjson", marker = "platform_python_implementation != 'PyPy'" }, - { name = "packaging" }, - { name = "pydantic" }, - { name = "requests" }, - { name = "requests-toolbelt" }, - { name = "uuid-utils" }, - { name = "zstandard" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/4b/e0/6d8a07b25a3ac308156707edaeffebbc30b2737bba8a75e65c40908beb94/langsmith-0.4.56.tar.gz", hash = "sha256:c3dc53509972689dbbc24f9ac92a095dcce00f76bb0db03ae385815945572540", size = 991755, upload-time = "2025-12-06T00:15:52.893Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b8/6f/d5f9c4f1e03c91045d3675dc99df0682bc657952ad158c92c1f423de04f4/langsmith-0.4.56-py3-none-any.whl", hash = "sha256:f2c61d3f10210e78f16f77e3115f407d40f562ab00ac8c76927c7dd55b5c17b2", size = 411849, upload-time = "2025-12-06T00:15:50.828Z" }, -] - -[[package]] -name = "langsmith-migration-example" -version = "0.1.0" -source = { virtual = "." } -dependencies = [ - { name = "braintrust" }, - { name = "langsmith" }, -] - -[package.dev-dependencies] -dev = [ - { name = "pytest" }, -] - -[package.metadata] -requires-dist = [ - { name = "braintrust", editable = "../../" }, - { name = "langsmith" }, -] - -[package.metadata.requires-dev] -dev = [{ name = "pytest", specifier = ">=9.0.2" }] - -[[package]] -name = "orjson" -version = "3.11.5" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/04/b8/333fdb27840f3bf04022d21b654a35f58e15407183aeb16f3b41aa053446/orjson-3.11.5.tar.gz", hash = "sha256:82393ab47b4fe44ffd0a7659fa9cfaacc717eb617c93cde83795f14af5c2e9d5", size = 5972347, upload-time = "2025-12-06T15:55:39.458Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/79/19/b22cf9dad4db20c8737041046054cbd4f38bb5a2d0e4bb60487832ce3d76/orjson-3.11.5-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:df9eadb2a6386d5ea2bfd81309c505e125cfc9ba2b1b99a97e60985b0b3665d1", size = 245719, upload-time = "2025-12-06T15:53:43.877Z" }, - { url = "https://files.pythonhosted.org/packages/03/2e/b136dd6bf30ef5143fbe76a4c142828b55ccc618be490201e9073ad954a1/orjson-3.11.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ccc70da619744467d8f1f49a8cadae5ec7bbe054e5232d95f92ed8737f8c5870", size = 132467, upload-time = "2025-12-06T15:53:45.379Z" }, - { url = "https://files.pythonhosted.org/packages/ae/fc/ae99bfc1e1887d20a0268f0e2686eb5b13d0ea7bbe01de2b566febcd2130/orjson-3.11.5-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:073aab025294c2f6fc0807201c76fdaed86f8fc4be52c440fb78fbb759a1ac09", size = 130702, upload-time = "2025-12-06T15:53:46.659Z" }, - { url = "https://files.pythonhosted.org/packages/6e/43/ef7912144097765997170aca59249725c3ab8ef6079f93f9d708dd058df5/orjson-3.11.5-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:835f26fa24ba0bb8c53ae2a9328d1706135b74ec653ed933869b74b6909e63fd", size = 135907, upload-time = "2025-12-06T15:53:48.487Z" }, - { url = "https://files.pythonhosted.org/packages/3f/da/24d50e2d7f4092ddd4d784e37a3fa41f22ce8ed97abc9edd222901a96e74/orjson-3.11.5-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:667c132f1f3651c14522a119e4dd631fad98761fa960c55e8e7430bb2a1ba4ac", size = 139935, upload-time = "2025-12-06T15:53:49.88Z" }, - { url = "https://files.pythonhosted.org/packages/02/4a/b4cb6fcbfff5b95a3a019a8648255a0fac9b221fbf6b6e72be8df2361feb/orjson-3.11.5-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:42e8961196af655bb5e63ce6c60d25e8798cd4dfbc04f4203457fa3869322c2e", size = 137541, upload-time = "2025-12-06T15:53:51.226Z" }, - { url = "https://files.pythonhosted.org/packages/a5/99/a11bd129f18c2377c27b2846a9d9be04acec981f770d711ba0aaea563984/orjson-3.11.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75412ca06e20904c19170f8a24486c4e6c7887dea591ba18a1ab572f1300ee9f", size = 139031, upload-time = "2025-12-06T15:53:52.309Z" }, - { url = "https://files.pythonhosted.org/packages/64/29/d7b77d7911574733a036bb3e8ad7053ceb2b7d6ea42208b9dbc55b23b9ed/orjson-3.11.5-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:6af8680328c69e15324b5af3ae38abbfcf9cbec37b5346ebfd52339c3d7e8a18", size = 141622, upload-time = "2025-12-06T15:53:53.606Z" }, - { url = "https://files.pythonhosted.org/packages/93/41/332db96c1de76b2feda4f453e91c27202cd092835936ce2b70828212f726/orjson-3.11.5-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:a86fe4ff4ea523eac8f4b57fdac319faf037d3c1be12405e6a7e86b3fbc4756a", size = 413800, upload-time = "2025-12-06T15:53:54.866Z" }, - { url = "https://files.pythonhosted.org/packages/76/e1/5a0d148dd1f89ad2f9651df67835b209ab7fcb1118658cf353425d7563e9/orjson-3.11.5-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:e607b49b1a106ee2086633167033afbd63f76f2999e9236f638b06b112b24ea7", size = 151198, upload-time = "2025-12-06T15:53:56.383Z" }, - { url = "https://files.pythonhosted.org/packages/0d/96/8db67430d317a01ae5cf7971914f6775affdcfe99f5bff9ef3da32492ecc/orjson-3.11.5-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:7339f41c244d0eea251637727f016b3d20050636695bc78345cce9029b189401", size = 141984, upload-time = "2025-12-06T15:53:57.746Z" }, - { url = "https://files.pythonhosted.org/packages/71/49/40d21e1aa1ac569e521069228bb29c9b5a350344ccf922a0227d93c2ed44/orjson-3.11.5-cp310-cp310-win32.whl", hash = "sha256:8be318da8413cdbbce77b8c5fac8d13f6eb0f0db41b30bb598631412619572e8", size = 135272, upload-time = "2025-12-06T15:53:59.769Z" }, - { url = "https://files.pythonhosted.org/packages/c4/7e/d0e31e78be0c100e08be64f48d2850b23bcb4d4c70d114f4e43b39f6895a/orjson-3.11.5-cp310-cp310-win_amd64.whl", hash = "sha256:b9f86d69ae822cabc2a0f6c099b43e8733dda788405cba2665595b7e8dd8d167", size = 133360, upload-time = "2025-12-06T15:54:01.25Z" }, - { url = "https://files.pythonhosted.org/packages/fd/68/6b3659daec3a81aed5ab47700adb1a577c76a5452d35b91c88efee89987f/orjson-3.11.5-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:9c8494625ad60a923af6b2b0bd74107146efe9b55099e20d7740d995f338fcd8", size = 245318, upload-time = "2025-12-06T15:54:02.355Z" }, - { url = "https://files.pythonhosted.org/packages/e9/00/92db122261425f61803ccf0830699ea5567439d966cbc35856fe711bfe6b/orjson-3.11.5-cp311-cp311-macosx_15_0_arm64.whl", hash = "sha256:7bb2ce0b82bc9fd1168a513ddae7a857994b780b2945a8c51db4ab1c4b751ebc", size = 129491, upload-time = "2025-12-06T15:54:03.877Z" }, - { url = "https://files.pythonhosted.org/packages/94/4f/ffdcb18356518809d944e1e1f77589845c278a1ebbb5a8297dfefcc4b4cb/orjson-3.11.5-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:67394d3becd50b954c4ecd24ac90b5051ee7c903d167459f93e77fc6f5b4c968", size = 132167, upload-time = "2025-12-06T15:54:04.944Z" }, - { url = "https://files.pythonhosted.org/packages/97/c6/0a8caff96f4503f4f7dd44e40e90f4d14acf80d3b7a97cb88747bb712d3e/orjson-3.11.5-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:298d2451f375e5f17b897794bcc3e7b821c0f32b4788b9bcae47ada24d7f3cf7", size = 130516, upload-time = "2025-12-06T15:54:06.274Z" }, - { url = "https://files.pythonhosted.org/packages/4d/63/43d4dc9bd9954bff7052f700fdb501067f6fb134a003ddcea2a0bb3854ed/orjson-3.11.5-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:aa5e4244063db8e1d87e0f54c3f7522f14b2dc937e65d5241ef0076a096409fd", size = 135695, upload-time = "2025-12-06T15:54:07.702Z" }, - { url = "https://files.pythonhosted.org/packages/87/6f/27e2e76d110919cb7fcb72b26166ee676480a701bcf8fc53ac5d0edce32f/orjson-3.11.5-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1db2088b490761976c1b2e956d5d4e6409f3732e9d79cfa69f876c5248d1baf9", size = 139664, upload-time = "2025-12-06T15:54:08.828Z" }, - { url = "https://files.pythonhosted.org/packages/d4/f8/5966153a5f1be49b5fbb8ca619a529fde7bc71aa0a376f2bb83fed248bcd/orjson-3.11.5-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c2ed66358f32c24e10ceea518e16eb3549e34f33a9d51f99ce23b0251776a1ef", size = 137289, upload-time = "2025-12-06T15:54:09.898Z" }, - { url = "https://files.pythonhosted.org/packages/a7/34/8acb12ff0299385c8bbcbb19fbe40030f23f15a6de57a9c587ebf71483fb/orjson-3.11.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c2021afda46c1ed64d74b555065dbd4c2558d510d8cec5ea6a53001b3e5e82a9", size = 138784, upload-time = "2025-12-06T15:54:11.022Z" }, - { url = "https://files.pythonhosted.org/packages/ee/27/910421ea6e34a527f73d8f4ee7bdffa48357ff79c7b8d6eb6f7b82dd1176/orjson-3.11.5-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:b42ffbed9128e547a1647a3e50bc88ab28ae9daa61713962e0d3dd35e820c125", size = 141322, upload-time = "2025-12-06T15:54:12.427Z" }, - { url = "https://files.pythonhosted.org/packages/87/a3/4b703edd1a05555d4bb1753d6ce44e1a05b7a6d7c164d5b332c795c63d70/orjson-3.11.5-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:8d5f16195bb671a5dd3d1dbea758918bada8f6cc27de72bd64adfbd748770814", size = 413612, upload-time = "2025-12-06T15:54:13.858Z" }, - { url = "https://files.pythonhosted.org/packages/1b/36/034177f11d7eeea16d3d2c42a1883b0373978e08bc9dad387f5074c786d8/orjson-3.11.5-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:c0e5d9f7a0227df2927d343a6e3859bebf9208b427c79bd31949abcc2fa32fa5", size = 150993, upload-time = "2025-12-06T15:54:15.189Z" }, - { url = "https://files.pythonhosted.org/packages/44/2f/ea8b24ee046a50a7d141c0227c4496b1180b215e728e3b640684f0ea448d/orjson-3.11.5-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:23d04c4543e78f724c4dfe656b3791b5f98e4c9253e13b2636f1af5d90e4a880", size = 141774, upload-time = "2025-12-06T15:54:16.451Z" }, - { url = "https://files.pythonhosted.org/packages/8a/12/cc440554bf8200eb23348a5744a575a342497b65261cd65ef3b28332510a/orjson-3.11.5-cp311-cp311-win32.whl", hash = "sha256:c404603df4865f8e0afe981aa3c4b62b406e6d06049564d58934860b62b7f91d", size = 135109, upload-time = "2025-12-06T15:54:17.73Z" }, - { url = "https://files.pythonhosted.org/packages/a3/83/e0c5aa06ba73a6760134b169f11fb970caa1525fa4461f94d76e692299d9/orjson-3.11.5-cp311-cp311-win_amd64.whl", hash = "sha256:9645ef655735a74da4990c24ffbd6894828fbfa117bc97c1edd98c282ecb52e1", size = 133193, upload-time = "2025-12-06T15:54:19.426Z" }, - { url = "https://files.pythonhosted.org/packages/cb/35/5b77eaebc60d735e832c5b1a20b155667645d123f09d471db0a78280fb49/orjson-3.11.5-cp311-cp311-win_arm64.whl", hash = "sha256:1cbf2735722623fcdee8e712cbaaab9e372bbcb0c7924ad711b261c2eccf4a5c", size = 126830, upload-time = "2025-12-06T15:54:20.836Z" }, - { url = "https://files.pythonhosted.org/packages/ef/a4/8052a029029b096a78955eadd68ab594ce2197e24ec50e6b6d2ab3f4e33b/orjson-3.11.5-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:334e5b4bff9ad101237c2d799d9fd45737752929753bf4faf4b207335a416b7d", size = 245347, upload-time = "2025-12-06T15:54:22.061Z" }, - { url = "https://files.pythonhosted.org/packages/64/67/574a7732bd9d9d79ac620c8790b4cfe0717a3d5a6eb2b539e6e8995e24a0/orjson-3.11.5-cp312-cp312-macosx_15_0_arm64.whl", hash = "sha256:ff770589960a86eae279f5d8aa536196ebda8273a2a07db2a54e82b93bc86626", size = 129435, upload-time = "2025-12-06T15:54:23.615Z" }, - { url = "https://files.pythonhosted.org/packages/52/8d/544e77d7a29d90cf4d9eecd0ae801c688e7f3d1adfa2ebae5e1e94d38ab9/orjson-3.11.5-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ed24250e55efbcb0b35bed7caaec8cedf858ab2f9f2201f17b8938c618c8ca6f", size = 132074, upload-time = "2025-12-06T15:54:24.694Z" }, - { url = "https://files.pythonhosted.org/packages/6e/57/b9f5b5b6fbff9c26f77e785baf56ae8460ef74acdb3eae4931c25b8f5ba9/orjson-3.11.5-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a66d7769e98a08a12a139049aac2f0ca3adae989817f8c43337455fbc7669b85", size = 130520, upload-time = "2025-12-06T15:54:26.185Z" }, - { url = "https://files.pythonhosted.org/packages/f6/6d/d34970bf9eb33f9ec7c979a262cad86076814859e54eb9a059a52f6dc13d/orjson-3.11.5-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:86cfc555bfd5794d24c6a1903e558b50644e5e68e6471d66502ce5cb5fdef3f9", size = 136209, upload-time = "2025-12-06T15:54:27.264Z" }, - { url = "https://files.pythonhosted.org/packages/e7/39/bc373b63cc0e117a105ea12e57280f83ae52fdee426890d57412432d63b3/orjson-3.11.5-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a230065027bc2a025e944f9d4714976a81e7ecfa940923283bca7bbc1f10f626", size = 139837, upload-time = "2025-12-06T15:54:28.75Z" }, - { url = "https://files.pythonhosted.org/packages/cb/aa/7c4818c8d7d324da220f4f1af55c343956003aa4d1ce1857bdc1d396ba69/orjson-3.11.5-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b29d36b60e606df01959c4b982729c8845c69d1963f88686608be9ced96dbfaa", size = 137307, upload-time = "2025-12-06T15:54:29.856Z" }, - { url = "https://files.pythonhosted.org/packages/46/bf/0993b5a056759ba65145effe3a79dd5a939d4a070eaa5da2ee3180fbb13f/orjson-3.11.5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c74099c6b230d4261fdc3169d50efc09abf38ace1a42ea2f9994b1d79153d477", size = 139020, upload-time = "2025-12-06T15:54:31.024Z" }, - { url = "https://files.pythonhosted.org/packages/65/e8/83a6c95db3039e504eda60fc388f9faedbb4f6472f5aba7084e06552d9aa/orjson-3.11.5-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:e697d06ad57dd0c7a737771d470eedc18e68dfdefcdd3b7de7f33dfda5b6212e", size = 141099, upload-time = "2025-12-06T15:54:32.196Z" }, - { url = "https://files.pythonhosted.org/packages/b9/b4/24fdc024abfce31c2f6812973b0a693688037ece5dc64b7a60c1ce69e2f2/orjson-3.11.5-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:e08ca8a6c851e95aaecc32bc44a5aa75d0ad26af8cdac7c77e4ed93acf3d5b69", size = 413540, upload-time = "2025-12-06T15:54:33.361Z" }, - { url = "https://files.pythonhosted.org/packages/d9/37/01c0ec95d55ed0c11e4cae3e10427e479bba40c77312b63e1f9665e0737d/orjson-3.11.5-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:e8b5f96c05fce7d0218df3fdfeb962d6b8cfff7e3e20264306b46dd8b217c0f3", size = 151530, upload-time = "2025-12-06T15:54:34.6Z" }, - { url = "https://files.pythonhosted.org/packages/f9/d4/f9ebc57182705bb4bbe63f5bbe14af43722a2533135e1d2fb7affa0c355d/orjson-3.11.5-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:ddbfdb5099b3e6ba6d6ea818f61997bb66de14b411357d24c4612cf1ebad08ca", size = 141863, upload-time = "2025-12-06T15:54:35.801Z" }, - { url = "https://files.pythonhosted.org/packages/0d/04/02102b8d19fdcb009d72d622bb5781e8f3fae1646bf3e18c53d1bc8115b5/orjson-3.11.5-cp312-cp312-win32.whl", hash = "sha256:9172578c4eb09dbfcf1657d43198de59b6cef4054de385365060ed50c458ac98", size = 135255, upload-time = "2025-12-06T15:54:37.209Z" }, - { url = "https://files.pythonhosted.org/packages/d4/fb/f05646c43d5450492cb387de5549f6de90a71001682c17882d9f66476af5/orjson-3.11.5-cp312-cp312-win_amd64.whl", hash = "sha256:2b91126e7b470ff2e75746f6f6ee32b9ab67b7a93c8ba1d15d3a0caaf16ec875", size = 133252, upload-time = "2025-12-06T15:54:38.401Z" }, - { url = "https://files.pythonhosted.org/packages/dc/a6/7b8c0b26ba18c793533ac1cd145e131e46fcf43952aa94c109b5b913c1f0/orjson-3.11.5-cp312-cp312-win_arm64.whl", hash = "sha256:acbc5fac7e06777555b0722b8ad5f574739e99ffe99467ed63da98f97f9ca0fe", size = 126777, upload-time = "2025-12-06T15:54:39.515Z" }, - { url = "https://files.pythonhosted.org/packages/10/43/61a77040ce59f1569edf38f0b9faadc90c8cf7e9bec2e0df51d0132c6bb7/orjson-3.11.5-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:3b01799262081a4c47c035dd77c1301d40f568f77cc7ec1bb7db5d63b0a01629", size = 245271, upload-time = "2025-12-06T15:54:40.878Z" }, - { url = "https://files.pythonhosted.org/packages/55/f9/0f79be617388227866d50edd2fd320cb8fb94dc1501184bb1620981a0aba/orjson-3.11.5-cp313-cp313-macosx_15_0_arm64.whl", hash = "sha256:61de247948108484779f57a9f406e4c84d636fa5a59e411e6352484985e8a7c3", size = 129422, upload-time = "2025-12-06T15:54:42.403Z" }, - { url = "https://files.pythonhosted.org/packages/77/42/f1bf1549b432d4a78bfa95735b79b5dac75b65b5bb815bba86ad406ead0a/orjson-3.11.5-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:894aea2e63d4f24a7f04a1908307c738d0dce992e9249e744b8f4e8dd9197f39", size = 132060, upload-time = "2025-12-06T15:54:43.531Z" }, - { url = "https://files.pythonhosted.org/packages/25/49/825aa6b929f1a6ed244c78acd7b22c1481fd7e5fda047dc8bf4c1a807eb6/orjson-3.11.5-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ddc21521598dbe369d83d4d40338e23d4101dad21dae0e79fa20465dbace019f", size = 130391, upload-time = "2025-12-06T15:54:45.059Z" }, - { url = "https://files.pythonhosted.org/packages/42/ec/de55391858b49e16e1aa8f0bbbb7e5997b7345d8e984a2dec3746d13065b/orjson-3.11.5-cp313-cp313-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7cce16ae2f5fb2c53c3eafdd1706cb7b6530a67cc1c17abe8ec747f5cd7c0c51", size = 135964, upload-time = "2025-12-06T15:54:46.576Z" }, - { url = "https://files.pythonhosted.org/packages/1c/40/820bc63121d2d28818556a2d0a09384a9f0262407cf9fa305e091a8048df/orjson-3.11.5-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e46c762d9f0e1cfb4ccc8515de7f349abbc95b59cb5a2bd68df5973fdef913f8", size = 139817, upload-time = "2025-12-06T15:54:48.084Z" }, - { url = "https://files.pythonhosted.org/packages/09/c7/3a445ca9a84a0d59d26365fd8898ff52bdfcdcb825bcc6519830371d2364/orjson-3.11.5-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d7345c759276b798ccd6d77a87136029e71e66a8bbf2d2755cbdde1d82e78706", size = 137336, upload-time = "2025-12-06T15:54:49.426Z" }, - { url = "https://files.pythonhosted.org/packages/9a/b3/dc0d3771f2e5d1f13368f56b339c6782f955c6a20b50465a91acb79fe961/orjson-3.11.5-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75bc2e59e6a2ac1dd28901d07115abdebc4563b5b07dd612bf64260a201b1c7f", size = 138993, upload-time = "2025-12-06T15:54:50.939Z" }, - { url = "https://files.pythonhosted.org/packages/d1/a2/65267e959de6abe23444659b6e19c888f242bf7725ff927e2292776f6b89/orjson-3.11.5-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:54aae9b654554c3b4edd61896b978568c6daa16af96fa4681c9b5babd469f863", size = 141070, upload-time = "2025-12-06T15:54:52.414Z" }, - { url = "https://files.pythonhosted.org/packages/63/c9/da44a321b288727a322c6ab17e1754195708786a04f4f9d2220a5076a649/orjson-3.11.5-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:4bdd8d164a871c4ec773f9de0f6fe8769c2d6727879c37a9666ba4183b7f8228", size = 413505, upload-time = "2025-12-06T15:54:53.67Z" }, - { url = "https://files.pythonhosted.org/packages/7f/17/68dc14fa7000eefb3d4d6d7326a190c99bb65e319f02747ef3ebf2452f12/orjson-3.11.5-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:a261fef929bcf98a60713bf5e95ad067cea16ae345d9a35034e73c3990e927d2", size = 151342, upload-time = "2025-12-06T15:54:55.113Z" }, - { url = "https://files.pythonhosted.org/packages/c4/c5/ccee774b67225bed630a57478529fc026eda33d94fe4c0eac8fe58d4aa52/orjson-3.11.5-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:c028a394c766693c5c9909dec76b24f37e6a1b91999e8d0c0d5feecbe93c3e05", size = 141823, upload-time = "2025-12-06T15:54:56.331Z" }, - { url = "https://files.pythonhosted.org/packages/67/80/5d00e4155d0cd7390ae2087130637671da713959bb558db9bac5e6f6b042/orjson-3.11.5-cp313-cp313-win32.whl", hash = "sha256:2cc79aaad1dfabe1bd2d50ee09814a1253164b3da4c00a78c458d82d04b3bdef", size = 135236, upload-time = "2025-12-06T15:54:57.507Z" }, - { url = "https://files.pythonhosted.org/packages/95/fe/792cc06a84808dbdc20ac6eab6811c53091b42f8e51ecebf14b540e9cfe4/orjson-3.11.5-cp313-cp313-win_amd64.whl", hash = "sha256:ff7877d376add4e16b274e35a3f58b7f37b362abf4aa31863dadacdd20e3a583", size = 133167, upload-time = "2025-12-06T15:54:58.71Z" }, - { url = "https://files.pythonhosted.org/packages/46/2c/d158bd8b50e3b1cfdcf406a7e463f6ffe3f0d167b99634717acdaf5e299f/orjson-3.11.5-cp313-cp313-win_arm64.whl", hash = "sha256:59ac72ea775c88b163ba8d21b0177628bd015c5dd060647bbab6e22da3aad287", size = 126712, upload-time = "2025-12-06T15:54:59.892Z" }, - { url = "https://files.pythonhosted.org/packages/c2/60/77d7b839e317ead7bb225d55bb50f7ea75f47afc489c81199befc5435b50/orjson-3.11.5-cp314-cp314-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:e446a8ea0a4c366ceafc7d97067bfd55292969143b57e3c846d87fc701e797a0", size = 245252, upload-time = "2025-12-06T15:55:01.127Z" }, - { url = "https://files.pythonhosted.org/packages/f1/aa/d4639163b400f8044cef0fb9aa51b0337be0da3a27187a20d1166e742370/orjson-3.11.5-cp314-cp314-macosx_15_0_arm64.whl", hash = "sha256:53deb5addae9c22bbe3739298f5f2196afa881ea75944e7720681c7080909a81", size = 129419, upload-time = "2025-12-06T15:55:02.723Z" }, - { url = "https://files.pythonhosted.org/packages/30/94/9eabf94f2e11c671111139edf5ec410d2f21e6feee717804f7e8872d883f/orjson-3.11.5-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:82cd00d49d6063d2b8791da5d4f9d20539c5951f965e45ccf4e96d33505ce68f", size = 132050, upload-time = "2025-12-06T15:55:03.918Z" }, - { url = "https://files.pythonhosted.org/packages/3d/c8/ca10f5c5322f341ea9a9f1097e140be17a88f88d1cfdd29df522970d9744/orjson-3.11.5-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:3fd15f9fc8c203aeceff4fda211157fad114dde66e92e24097b3647a08f4ee9e", size = 130370, upload-time = "2025-12-06T15:55:05.173Z" }, - { url = "https://files.pythonhosted.org/packages/25/d4/e96824476d361ee2edd5c6290ceb8d7edf88d81148a6ce172fc00278ca7f/orjson-3.11.5-cp314-cp314-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9df95000fbe6777bf9820ae82ab7578e8662051bb5f83d71a28992f539d2cda7", size = 136012, upload-time = "2025-12-06T15:55:06.402Z" }, - { url = "https://files.pythonhosted.org/packages/85/8e/9bc3423308c425c588903f2d103cfcfe2539e07a25d6522900645a6f257f/orjson-3.11.5-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:92a8d676748fca47ade5bc3da7430ed7767afe51b2f8100e3cd65e151c0eaceb", size = 139809, upload-time = "2025-12-06T15:55:07.656Z" }, - { url = "https://files.pythonhosted.org/packages/e9/3c/b404e94e0b02a232b957c54643ce68d0268dacb67ac33ffdee24008c8b27/orjson-3.11.5-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:aa0f513be38b40234c77975e68805506cad5d57b3dfd8fe3baa7f4f4051e15b4", size = 137332, upload-time = "2025-12-06T15:55:08.961Z" }, - { url = "https://files.pythonhosted.org/packages/51/30/cc2d69d5ce0ad9b84811cdf4a0cd5362ac27205a921da524ff42f26d65e0/orjson-3.11.5-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fa1863e75b92891f553b7922ce4ee10ed06db061e104f2b7815de80cdcb135ad", size = 138983, upload-time = "2025-12-06T15:55:10.595Z" }, - { url = "https://files.pythonhosted.org/packages/0e/87/de3223944a3e297d4707d2fe3b1ffb71437550e165eaf0ca8bbe43ccbcb1/orjson-3.11.5-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:d4be86b58e9ea262617b8ca6251a2f0d63cc132a6da4b5fcc8e0a4128782c829", size = 141069, upload-time = "2025-12-06T15:55:11.832Z" }, - { url = "https://files.pythonhosted.org/packages/65/30/81d5087ae74be33bcae3ff2d80f5ccaa4a8fedc6d39bf65a427a95b8977f/orjson-3.11.5-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:b923c1c13fa02084eb38c9c065afd860a5cff58026813319a06949c3af5732ac", size = 413491, upload-time = "2025-12-06T15:55:13.314Z" }, - { url = "https://files.pythonhosted.org/packages/d0/6f/f6058c21e2fc1efaf918986dbc2da5cd38044f1a2d4b7b91ad17c4acf786/orjson-3.11.5-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:1b6bd351202b2cd987f35a13b5e16471cf4d952b42a73c391cc537974c43ef6d", size = 151375, upload-time = "2025-12-06T15:55:14.715Z" }, - { url = "https://files.pythonhosted.org/packages/54/92/c6921f17d45e110892899a7a563a925b2273d929959ce2ad89e2525b885b/orjson-3.11.5-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:bb150d529637d541e6af06bbe3d02f5498d628b7f98267ff87647584293ab439", size = 141850, upload-time = "2025-12-06T15:55:15.94Z" }, - { url = "https://files.pythonhosted.org/packages/88/86/cdecb0140a05e1a477b81f24739da93b25070ee01ce7f7242f44a6437594/orjson-3.11.5-cp314-cp314-win32.whl", hash = "sha256:9cc1e55c884921434a84a0c3dd2699eb9f92e7b441d7f53f3941079ec6ce7499", size = 135278, upload-time = "2025-12-06T15:55:17.202Z" }, - { url = "https://files.pythonhosted.org/packages/e4/97/b638d69b1e947d24f6109216997e38922d54dcdcdb1b11c18d7efd2d3c59/orjson-3.11.5-cp314-cp314-win_amd64.whl", hash = "sha256:a4f3cb2d874e03bc7767c8f88adaa1a9a05cecea3712649c3b58589ec7317310", size = 133170, upload-time = "2025-12-06T15:55:18.468Z" }, - { url = "https://files.pythonhosted.org/packages/8f/dd/f4fff4a6fe601b4f8f3ba3aa6da8ac33d17d124491a3b804c662a70e1636/orjson-3.11.5-cp314-cp314-win_arm64.whl", hash = "sha256:38b22f476c351f9a1c43e5b07d8b5a02eb24a6ab8e75f700f7d479d4568346a5", size = 126713, upload-time = "2025-12-06T15:55:19.738Z" }, -] - -[[package]] -name = "packaging" -version = "25.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/a1/d4/1fc4078c65507b51b96ca8f8c3ba19e6a61c8253c72794544580a7b6c24d/packaging-25.0.tar.gz", hash = "sha256:d443872c98d677bf60f6a1f2f8c1cb748e8fe762d2bf9d3148b5599295b0fc4f", size = 165727, upload-time = "2025-04-19T11:48:59.673Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/20/12/38679034af332785aac8774540895e234f4d07f7545804097de4b666afd8/packaging-25.0-py3-none-any.whl", hash = "sha256:29572ef2b1f17581046b3a2227d5c611fb25ec70ca1ba8554b24b0e69331a484", size = 66469, upload-time = "2025-04-19T11:48:57.875Z" }, -] - -[[package]] -name = "pluggy" -version = "1.6.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f9/e2/3e91f31a7d2b083fe6ef3fa267035b518369d9511ffab804f839851d2779/pluggy-1.6.0.tar.gz", hash = "sha256:7dcc130b76258d33b90f61b658791dede3486c3e6bfb003ee5c9bfb396dd22f3", size = 69412, upload-time = "2025-05-15T12:30:07.975Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl", hash = "sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746", size = 20538, upload-time = "2025-05-15T12:30:06.134Z" }, -] - -[[package]] -name = "pydantic" -version = "2.12.5" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "annotated-types" }, - { name = "pydantic-core" }, - { name = "typing-extensions" }, - { name = "typing-inspection" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/69/44/36f1a6e523abc58ae5f928898e4aca2e0ea509b5aa6f6f392a5d882be928/pydantic-2.12.5.tar.gz", hash = "sha256:4d351024c75c0f085a9febbb665ce8c0c6ec5d30e903bdb6394b7ede26aebb49", size = 821591, upload-time = "2025-11-26T15:11:46.471Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/5a/87/b70ad306ebb6f9b585f114d0ac2137d792b48be34d732d60e597c2f8465a/pydantic-2.12.5-py3-none-any.whl", hash = "sha256:e561593fccf61e8a20fc46dfc2dfe075b8be7d0188df33f221ad1f0139180f9d", size = 463580, upload-time = "2025-11-26T15:11:44.605Z" }, -] - -[[package]] -name = "pydantic-core" -version = "2.41.5" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/71/70/23b021c950c2addd24ec408e9ab05d59b035b39d97cdc1130e1bce647bb6/pydantic_core-2.41.5.tar.gz", hash = "sha256:08daa51ea16ad373ffd5e7606252cc32f07bc72b28284b6bc9c6df804816476e", size = 460952, upload-time = "2025-11-04T13:43:49.098Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/c6/90/32c9941e728d564b411d574d8ee0cf09b12ec978cb22b294995bae5549a5/pydantic_core-2.41.5-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:77b63866ca88d804225eaa4af3e664c5faf3568cea95360d21f4725ab6e07146", size = 2107298, upload-time = "2025-11-04T13:39:04.116Z" }, - { url = "https://files.pythonhosted.org/packages/fb/a8/61c96a77fe28993d9a6fb0f4127e05430a267b235a124545d79fea46dd65/pydantic_core-2.41.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:dfa8a0c812ac681395907e71e1274819dec685fec28273a28905df579ef137e2", size = 1901475, upload-time = "2025-11-04T13:39:06.055Z" }, - { url = "https://files.pythonhosted.org/packages/5d/b6/338abf60225acc18cdc08b4faef592d0310923d19a87fba1faf05af5346e/pydantic_core-2.41.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5921a4d3ca3aee735d9fd163808f5e8dd6c6972101e4adbda9a4667908849b97", size = 1918815, upload-time = "2025-11-04T13:39:10.41Z" }, - { url = "https://files.pythonhosted.org/packages/d1/1c/2ed0433e682983d8e8cba9c8d8ef274d4791ec6a6f24c58935b90e780e0a/pydantic_core-2.41.5-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e25c479382d26a2a41b7ebea1043564a937db462816ea07afa8a44c0866d52f9", size = 2065567, upload-time = "2025-11-04T13:39:12.244Z" }, - { url = "https://files.pythonhosted.org/packages/b3/24/cf84974ee7d6eae06b9e63289b7b8f6549d416b5c199ca2d7ce13bbcf619/pydantic_core-2.41.5-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f547144f2966e1e16ae626d8ce72b4cfa0caedc7fa28052001c94fb2fcaa1c52", size = 2230442, upload-time = "2025-11-04T13:39:13.962Z" }, - { url = "https://files.pythonhosted.org/packages/fd/21/4e287865504b3edc0136c89c9c09431be326168b1eb7841911cbc877a995/pydantic_core-2.41.5-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6f52298fbd394f9ed112d56f3d11aabd0d5bd27beb3084cc3d8ad069483b8941", size = 2350956, upload-time = "2025-11-04T13:39:15.889Z" }, - { url = "https://files.pythonhosted.org/packages/a8/76/7727ef2ffa4b62fcab916686a68a0426b9b790139720e1934e8ba797e238/pydantic_core-2.41.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:100baa204bb412b74fe285fb0f3a385256dad1d1879f0a5cb1499ed2e83d132a", size = 2068253, upload-time = "2025-11-04T13:39:17.403Z" }, - { url = "https://files.pythonhosted.org/packages/d5/8c/a4abfc79604bcb4c748e18975c44f94f756f08fb04218d5cb87eb0d3a63e/pydantic_core-2.41.5-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:05a2c8852530ad2812cb7914dc61a1125dc4e06252ee98e5638a12da6cc6fb6c", size = 2177050, upload-time = "2025-11-04T13:39:19.351Z" }, - { url = "https://files.pythonhosted.org/packages/67/b1/de2e9a9a79b480f9cb0b6e8b6ba4c50b18d4e89852426364c66aa82bb7b3/pydantic_core-2.41.5-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:29452c56df2ed968d18d7e21f4ab0ac55e71dc59524872f6fc57dcf4a3249ed2", size = 2147178, upload-time = "2025-11-04T13:39:21Z" }, - { url = "https://files.pythonhosted.org/packages/16/c1/dfb33f837a47b20417500efaa0378adc6635b3c79e8369ff7a03c494b4ac/pydantic_core-2.41.5-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:d5160812ea7a8a2ffbe233d8da666880cad0cbaf5d4de74ae15c313213d62556", size = 2341833, upload-time = "2025-11-04T13:39:22.606Z" }, - { url = "https://files.pythonhosted.org/packages/47/36/00f398642a0f4b815a9a558c4f1dca1b4020a7d49562807d7bc9ff279a6c/pydantic_core-2.41.5-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:df3959765b553b9440adfd3c795617c352154e497a4eaf3752555cfb5da8fc49", size = 2321156, upload-time = "2025-11-04T13:39:25.843Z" }, - { url = "https://files.pythonhosted.org/packages/7e/70/cad3acd89fde2010807354d978725ae111ddf6d0ea46d1ea1775b5c1bd0c/pydantic_core-2.41.5-cp310-cp310-win32.whl", hash = "sha256:1f8d33a7f4d5a7889e60dc39856d76d09333d8a6ed0f5f1190635cbec70ec4ba", size = 1989378, upload-time = "2025-11-04T13:39:27.92Z" }, - { url = "https://files.pythonhosted.org/packages/76/92/d338652464c6c367e5608e4488201702cd1cbb0f33f7b6a85a60fe5f3720/pydantic_core-2.41.5-cp310-cp310-win_amd64.whl", hash = "sha256:62de39db01b8d593e45871af2af9e497295db8d73b085f6bfd0b18c83c70a8f9", size = 2013622, upload-time = "2025-11-04T13:39:29.848Z" }, - { url = "https://files.pythonhosted.org/packages/e8/72/74a989dd9f2084b3d9530b0915fdda64ac48831c30dbf7c72a41a5232db8/pydantic_core-2.41.5-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:a3a52f6156e73e7ccb0f8cced536adccb7042be67cb45f9562e12b319c119da6", size = 2105873, upload-time = "2025-11-04T13:39:31.373Z" }, - { url = "https://files.pythonhosted.org/packages/12/44/37e403fd9455708b3b942949e1d7febc02167662bf1a7da5b78ee1ea2842/pydantic_core-2.41.5-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:7f3bf998340c6d4b0c9a2f02d6a400e51f123b59565d74dc60d252ce888c260b", size = 1899826, upload-time = "2025-11-04T13:39:32.897Z" }, - { url = "https://files.pythonhosted.org/packages/33/7f/1d5cab3ccf44c1935a359d51a8a2a9e1a654b744b5e7f80d41b88d501eec/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:378bec5c66998815d224c9ca994f1e14c0c21cb95d2f52b6021cc0b2a58f2a5a", size = 1917869, upload-time = "2025-11-04T13:39:34.469Z" }, - { url = "https://files.pythonhosted.org/packages/6e/6a/30d94a9674a7fe4f4744052ed6c5e083424510be1e93da5bc47569d11810/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e7b576130c69225432866fe2f4a469a85a54ade141d96fd396dffcf607b558f8", size = 2063890, upload-time = "2025-11-04T13:39:36.053Z" }, - { url = "https://files.pythonhosted.org/packages/50/be/76e5d46203fcb2750e542f32e6c371ffa9b8ad17364cf94bb0818dbfb50c/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6cb58b9c66f7e4179a2d5e0f849c48eff5c1fca560994d6eb6543abf955a149e", size = 2229740, upload-time = "2025-11-04T13:39:37.753Z" }, - { url = "https://files.pythonhosted.org/packages/d3/ee/fed784df0144793489f87db310a6bbf8118d7b630ed07aa180d6067e653a/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:88942d3a3dff3afc8288c21e565e476fc278902ae4d6d134f1eeda118cc830b1", size = 2350021, upload-time = "2025-11-04T13:39:40.94Z" }, - { url = "https://files.pythonhosted.org/packages/c8/be/8fed28dd0a180dca19e72c233cbf58efa36df055e5b9d90d64fd1740b828/pydantic_core-2.41.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f31d95a179f8d64d90f6831d71fa93290893a33148d890ba15de25642c5d075b", size = 2066378, upload-time = "2025-11-04T13:39:42.523Z" }, - { url = "https://files.pythonhosted.org/packages/b0/3b/698cf8ae1d536a010e05121b4958b1257f0b5522085e335360e53a6b1c8b/pydantic_core-2.41.5-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:c1df3d34aced70add6f867a8cf413e299177e0c22660cc767218373d0779487b", size = 2175761, upload-time = "2025-11-04T13:39:44.553Z" }, - { url = "https://files.pythonhosted.org/packages/b8/ba/15d537423939553116dea94ce02f9c31be0fa9d0b806d427e0308ec17145/pydantic_core-2.41.5-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:4009935984bd36bd2c774e13f9a09563ce8de4abaa7226f5108262fa3e637284", size = 2146303, upload-time = "2025-11-04T13:39:46.238Z" }, - { url = "https://files.pythonhosted.org/packages/58/7f/0de669bf37d206723795f9c90c82966726a2ab06c336deba4735b55af431/pydantic_core-2.41.5-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:34a64bc3441dc1213096a20fe27e8e128bd3ff89921706e83c0b1ac971276594", size = 2340355, upload-time = "2025-11-04T13:39:48.002Z" }, - { url = "https://files.pythonhosted.org/packages/e5/de/e7482c435b83d7e3c3ee5ee4451f6e8973cff0eb6007d2872ce6383f6398/pydantic_core-2.41.5-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:c9e19dd6e28fdcaa5a1de679aec4141f691023916427ef9bae8584f9c2fb3b0e", size = 2319875, upload-time = "2025-11-04T13:39:49.705Z" }, - { url = "https://files.pythonhosted.org/packages/fe/e6/8c9e81bb6dd7560e33b9053351c29f30c8194b72f2d6932888581f503482/pydantic_core-2.41.5-cp311-cp311-win32.whl", hash = "sha256:2c010c6ded393148374c0f6f0bf89d206bf3217f201faa0635dcd56bd1520f6b", size = 1987549, upload-time = "2025-11-04T13:39:51.842Z" }, - { url = "https://files.pythonhosted.org/packages/11/66/f14d1d978ea94d1bc21fc98fcf570f9542fe55bfcc40269d4e1a21c19bf7/pydantic_core-2.41.5-cp311-cp311-win_amd64.whl", hash = "sha256:76ee27c6e9c7f16f47db7a94157112a2f3a00e958bc626e2f4ee8bec5c328fbe", size = 2011305, upload-time = "2025-11-04T13:39:53.485Z" }, - { url = "https://files.pythonhosted.org/packages/56/d8/0e271434e8efd03186c5386671328154ee349ff0354d83c74f5caaf096ed/pydantic_core-2.41.5-cp311-cp311-win_arm64.whl", hash = "sha256:4bc36bbc0b7584de96561184ad7f012478987882ebf9f9c389b23f432ea3d90f", size = 1972902, upload-time = "2025-11-04T13:39:56.488Z" }, - { url = "https://files.pythonhosted.org/packages/5f/5d/5f6c63eebb5afee93bcaae4ce9a898f3373ca23df3ccaef086d0233a35a7/pydantic_core-2.41.5-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:f41a7489d32336dbf2199c8c0a215390a751c5b014c2c1c5366e817202e9cdf7", size = 2110990, upload-time = "2025-11-04T13:39:58.079Z" }, - { url = "https://files.pythonhosted.org/packages/aa/32/9c2e8ccb57c01111e0fd091f236c7b371c1bccea0fa85247ac55b1e2b6b6/pydantic_core-2.41.5-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:070259a8818988b9a84a449a2a7337c7f430a22acc0859c6b110aa7212a6d9c0", size = 1896003, upload-time = "2025-11-04T13:39:59.956Z" }, - { url = "https://files.pythonhosted.org/packages/68/b8/a01b53cb0e59139fbc9e4fda3e9724ede8de279097179be4ff31f1abb65a/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e96cea19e34778f8d59fe40775a7a574d95816eb150850a85a7a4c8f4b94ac69", size = 1919200, upload-time = "2025-11-04T13:40:02.241Z" }, - { url = "https://files.pythonhosted.org/packages/38/de/8c36b5198a29bdaade07b5985e80a233a5ac27137846f3bc2d3b40a47360/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed2e99c456e3fadd05c991f8f437ef902e00eedf34320ba2b0842bd1c3ca3a75", size = 2052578, upload-time = "2025-11-04T13:40:04.401Z" }, - { url = "https://files.pythonhosted.org/packages/00/b5/0e8e4b5b081eac6cb3dbb7e60a65907549a1ce035a724368c330112adfdd/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:65840751b72fbfd82c3c640cff9284545342a4f1eb1586ad0636955b261b0b05", size = 2208504, upload-time = "2025-11-04T13:40:06.072Z" }, - { url = "https://files.pythonhosted.org/packages/77/56/87a61aad59c7c5b9dc8caad5a41a5545cba3810c3e828708b3d7404f6cef/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e536c98a7626a98feb2d3eaf75944ef6f3dbee447e1f841eae16f2f0a72d8ddc", size = 2335816, upload-time = "2025-11-04T13:40:07.835Z" }, - { url = "https://files.pythonhosted.org/packages/0d/76/941cc9f73529988688a665a5c0ecff1112b3d95ab48f81db5f7606f522d3/pydantic_core-2.41.5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eceb81a8d74f9267ef4081e246ffd6d129da5d87e37a77c9bde550cb04870c1c", size = 2075366, upload-time = "2025-11-04T13:40:09.804Z" }, - { url = "https://files.pythonhosted.org/packages/d3/43/ebef01f69baa07a482844faaa0a591bad1ef129253ffd0cdaa9d8a7f72d3/pydantic_core-2.41.5-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d38548150c39b74aeeb0ce8ee1d8e82696f4a4e16ddc6de7b1d8823f7de4b9b5", size = 2171698, upload-time = "2025-11-04T13:40:12.004Z" }, - { url = "https://files.pythonhosted.org/packages/b1/87/41f3202e4193e3bacfc2c065fab7706ebe81af46a83d3e27605029c1f5a6/pydantic_core-2.41.5-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:c23e27686783f60290e36827f9c626e63154b82b116d7fe9adba1fda36da706c", size = 2132603, upload-time = "2025-11-04T13:40:13.868Z" }, - { url = "https://files.pythonhosted.org/packages/49/7d/4c00df99cb12070b6bccdef4a195255e6020a550d572768d92cc54dba91a/pydantic_core-2.41.5-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:482c982f814460eabe1d3bb0adfdc583387bd4691ef00b90575ca0d2b6fe2294", size = 2329591, upload-time = "2025-11-04T13:40:15.672Z" }, - { url = "https://files.pythonhosted.org/packages/cc/6a/ebf4b1d65d458f3cda6a7335d141305dfa19bdc61140a884d165a8a1bbc7/pydantic_core-2.41.5-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:bfea2a5f0b4d8d43adf9d7b8bf019fb46fdd10a2e5cde477fbcb9d1fa08c68e1", size = 2319068, upload-time = "2025-11-04T13:40:17.532Z" }, - { url = "https://files.pythonhosted.org/packages/49/3b/774f2b5cd4192d5ab75870ce4381fd89cf218af999515baf07e7206753f0/pydantic_core-2.41.5-cp312-cp312-win32.whl", hash = "sha256:b74557b16e390ec12dca509bce9264c3bbd128f8a2c376eaa68003d7f327276d", size = 1985908, upload-time = "2025-11-04T13:40:19.309Z" }, - { url = "https://files.pythonhosted.org/packages/86/45/00173a033c801cacf67c190fef088789394feaf88a98a7035b0e40d53dc9/pydantic_core-2.41.5-cp312-cp312-win_amd64.whl", hash = "sha256:1962293292865bca8e54702b08a4f26da73adc83dd1fcf26fbc875b35d81c815", size = 2020145, upload-time = "2025-11-04T13:40:21.548Z" }, - { url = "https://files.pythonhosted.org/packages/f9/22/91fbc821fa6d261b376a3f73809f907cec5ca6025642c463d3488aad22fb/pydantic_core-2.41.5-cp312-cp312-win_arm64.whl", hash = "sha256:1746d4a3d9a794cacae06a5eaaccb4b8643a131d45fbc9af23e353dc0a5ba5c3", size = 1976179, upload-time = "2025-11-04T13:40:23.393Z" }, - { url = "https://files.pythonhosted.org/packages/87/06/8806241ff1f70d9939f9af039c6c35f2360cf16e93c2ca76f184e76b1564/pydantic_core-2.41.5-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:941103c9be18ac8daf7b7adca8228f8ed6bb7a1849020f643b3a14d15b1924d9", size = 2120403, upload-time = "2025-11-04T13:40:25.248Z" }, - { url = "https://files.pythonhosted.org/packages/94/02/abfa0e0bda67faa65fef1c84971c7e45928e108fe24333c81f3bfe35d5f5/pydantic_core-2.41.5-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:112e305c3314f40c93998e567879e887a3160bb8689ef3d2c04b6cc62c33ac34", size = 1896206, upload-time = "2025-11-04T13:40:27.099Z" }, - { url = "https://files.pythonhosted.org/packages/15/df/a4c740c0943e93e6500f9eb23f4ca7ec9bf71b19e608ae5b579678c8d02f/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0cbaad15cb0c90aa221d43c00e77bb33c93e8d36e0bf74760cd00e732d10a6a0", size = 1919307, upload-time = "2025-11-04T13:40:29.806Z" }, - { url = "https://files.pythonhosted.org/packages/9a/e3/6324802931ae1d123528988e0e86587c2072ac2e5394b4bc2bc34b61ff6e/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:03ca43e12fab6023fc79d28ca6b39b05f794ad08ec2feccc59a339b02f2b3d33", size = 2063258, upload-time = "2025-11-04T13:40:33.544Z" }, - { url = "https://files.pythonhosted.org/packages/c9/d4/2230d7151d4957dd79c3044ea26346c148c98fbf0ee6ebd41056f2d62ab5/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:dc799088c08fa04e43144b164feb0c13f9a0bc40503f8df3e9fde58a3c0c101e", size = 2214917, upload-time = "2025-11-04T13:40:35.479Z" }, - { url = "https://files.pythonhosted.org/packages/e6/9f/eaac5df17a3672fef0081b6c1bb0b82b33ee89aa5cec0d7b05f52fd4a1fa/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:97aeba56665b4c3235a0e52b2c2f5ae9cd071b8a8310ad27bddb3f7fb30e9aa2", size = 2332186, upload-time = "2025-11-04T13:40:37.436Z" }, - { url = "https://files.pythonhosted.org/packages/cf/4e/35a80cae583a37cf15604b44240e45c05e04e86f9cfd766623149297e971/pydantic_core-2.41.5-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:406bf18d345822d6c21366031003612b9c77b3e29ffdb0f612367352aab7d586", size = 2073164, upload-time = "2025-11-04T13:40:40.289Z" }, - { url = "https://files.pythonhosted.org/packages/bf/e3/f6e262673c6140dd3305d144d032f7bd5f7497d3871c1428521f19f9efa2/pydantic_core-2.41.5-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:b93590ae81f7010dbe380cdeab6f515902ebcbefe0b9327cc4804d74e93ae69d", size = 2179146, upload-time = "2025-11-04T13:40:42.809Z" }, - { url = "https://files.pythonhosted.org/packages/75/c7/20bd7fc05f0c6ea2056a4565c6f36f8968c0924f19b7d97bbfea55780e73/pydantic_core-2.41.5-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:01a3d0ab748ee531f4ea6c3e48ad9dac84ddba4b0d82291f87248f2f9de8d740", size = 2137788, upload-time = "2025-11-04T13:40:44.752Z" }, - { url = "https://files.pythonhosted.org/packages/3a/8d/34318ef985c45196e004bc46c6eab2eda437e744c124ef0dbe1ff2c9d06b/pydantic_core-2.41.5-cp313-cp313-musllinux_1_1_armv7l.whl", hash = "sha256:6561e94ba9dacc9c61bce40e2d6bdc3bfaa0259d3ff36ace3b1e6901936d2e3e", size = 2340133, upload-time = "2025-11-04T13:40:46.66Z" }, - { url = "https://files.pythonhosted.org/packages/9c/59/013626bf8c78a5a5d9350d12e7697d3d4de951a75565496abd40ccd46bee/pydantic_core-2.41.5-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:915c3d10f81bec3a74fbd4faebe8391013ba61e5a1a8d48c4455b923bdda7858", size = 2324852, upload-time = "2025-11-04T13:40:48.575Z" }, - { url = "https://files.pythonhosted.org/packages/1a/d9/c248c103856f807ef70c18a4f986693a46a8ffe1602e5d361485da502d20/pydantic_core-2.41.5-cp313-cp313-win32.whl", hash = "sha256:650ae77860b45cfa6e2cdafc42618ceafab3a2d9a3811fcfbd3bbf8ac3c40d36", size = 1994679, upload-time = "2025-11-04T13:40:50.619Z" }, - { url = "https://files.pythonhosted.org/packages/9e/8b/341991b158ddab181cff136acd2552c9f35bd30380422a639c0671e99a91/pydantic_core-2.41.5-cp313-cp313-win_amd64.whl", hash = "sha256:79ec52ec461e99e13791ec6508c722742ad745571f234ea6255bed38c6480f11", size = 2019766, upload-time = "2025-11-04T13:40:52.631Z" }, - { url = "https://files.pythonhosted.org/packages/73/7d/f2f9db34af103bea3e09735bb40b021788a5e834c81eedb541991badf8f5/pydantic_core-2.41.5-cp313-cp313-win_arm64.whl", hash = "sha256:3f84d5c1b4ab906093bdc1ff10484838aca54ef08de4afa9de0f5f14d69639cd", size = 1981005, upload-time = "2025-11-04T13:40:54.734Z" }, - { url = "https://files.pythonhosted.org/packages/ea/28/46b7c5c9635ae96ea0fbb779e271a38129df2550f763937659ee6c5dbc65/pydantic_core-2.41.5-cp314-cp314-macosx_10_12_x86_64.whl", hash = "sha256:3f37a19d7ebcdd20b96485056ba9e8b304e27d9904d233d7b1015db320e51f0a", size = 2119622, upload-time = "2025-11-04T13:40:56.68Z" }, - { url = "https://files.pythonhosted.org/packages/74/1a/145646e5687e8d9a1e8d09acb278c8535ebe9e972e1f162ed338a622f193/pydantic_core-2.41.5-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:1d1d9764366c73f996edd17abb6d9d7649a7eb690006ab6adbda117717099b14", size = 1891725, upload-time = "2025-11-04T13:40:58.807Z" }, - { url = "https://files.pythonhosted.org/packages/23/04/e89c29e267b8060b40dca97bfc64a19b2a3cf99018167ea1677d96368273/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:25e1c2af0fce638d5f1988b686f3b3ea8cd7de5f244ca147c777769e798a9cd1", size = 1915040, upload-time = "2025-11-04T13:41:00.853Z" }, - { url = "https://files.pythonhosted.org/packages/84/a3/15a82ac7bd97992a82257f777b3583d3e84bdb06ba6858f745daa2ec8a85/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:506d766a8727beef16b7adaeb8ee6217c64fc813646b424d0804d67c16eddb66", size = 2063691, upload-time = "2025-11-04T13:41:03.504Z" }, - { url = "https://files.pythonhosted.org/packages/74/9b/0046701313c6ef08c0c1cf0e028c67c770a4e1275ca73131563c5f2a310a/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4819fa52133c9aa3c387b3328f25c1facc356491e6135b459f1de698ff64d869", size = 2213897, upload-time = "2025-11-04T13:41:05.804Z" }, - { url = "https://files.pythonhosted.org/packages/8a/cd/6bac76ecd1b27e75a95ca3a9a559c643b3afcd2dd62086d4b7a32a18b169/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2b761d210c9ea91feda40d25b4efe82a1707da2ef62901466a42492c028553a2", size = 2333302, upload-time = "2025-11-04T13:41:07.809Z" }, - { url = "https://files.pythonhosted.org/packages/4c/d2/ef2074dc020dd6e109611a8be4449b98cd25e1b9b8a303c2f0fca2f2bcf7/pydantic_core-2.41.5-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:22f0fb8c1c583a3b6f24df2470833b40207e907b90c928cc8d3594b76f874375", size = 2064877, upload-time = "2025-11-04T13:41:09.827Z" }, - { url = "https://files.pythonhosted.org/packages/18/66/e9db17a9a763d72f03de903883c057b2592c09509ccfe468187f2a2eef29/pydantic_core-2.41.5-cp314-cp314-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:2782c870e99878c634505236d81e5443092fba820f0373997ff75f90f68cd553", size = 2180680, upload-time = "2025-11-04T13:41:12.379Z" }, - { url = "https://files.pythonhosted.org/packages/d3/9e/3ce66cebb929f3ced22be85d4c2399b8e85b622db77dad36b73c5387f8f8/pydantic_core-2.41.5-cp314-cp314-musllinux_1_1_aarch64.whl", hash = "sha256:0177272f88ab8312479336e1d777f6b124537d47f2123f89cb37e0accea97f90", size = 2138960, upload-time = "2025-11-04T13:41:14.627Z" }, - { url = "https://files.pythonhosted.org/packages/a6/62/205a998f4327d2079326b01abee48e502ea739d174f0a89295c481a2272e/pydantic_core-2.41.5-cp314-cp314-musllinux_1_1_armv7l.whl", hash = "sha256:63510af5e38f8955b8ee5687740d6ebf7c2a0886d15a6d65c32814613681bc07", size = 2339102, upload-time = "2025-11-04T13:41:16.868Z" }, - { url = "https://files.pythonhosted.org/packages/3c/0d/f05e79471e889d74d3d88f5bd20d0ed189ad94c2423d81ff8d0000aab4ff/pydantic_core-2.41.5-cp314-cp314-musllinux_1_1_x86_64.whl", hash = "sha256:e56ba91f47764cc14f1daacd723e3e82d1a89d783f0f5afe9c364b8bb491ccdb", size = 2326039, upload-time = "2025-11-04T13:41:18.934Z" }, - { url = "https://files.pythonhosted.org/packages/ec/e1/e08a6208bb100da7e0c4b288eed624a703f4d129bde2da475721a80cab32/pydantic_core-2.41.5-cp314-cp314-win32.whl", hash = "sha256:aec5cf2fd867b4ff45b9959f8b20ea3993fc93e63c7363fe6851424c8a7e7c23", size = 1995126, upload-time = "2025-11-04T13:41:21.418Z" }, - { url = "https://files.pythonhosted.org/packages/48/5d/56ba7b24e9557f99c9237e29f5c09913c81eeb2f3217e40e922353668092/pydantic_core-2.41.5-cp314-cp314-win_amd64.whl", hash = "sha256:8e7c86f27c585ef37c35e56a96363ab8de4e549a95512445b85c96d3e2f7c1bf", size = 2015489, upload-time = "2025-11-04T13:41:24.076Z" }, - { url = "https://files.pythonhosted.org/packages/4e/bb/f7a190991ec9e3e0ba22e4993d8755bbc4a32925c0b5b42775c03e8148f9/pydantic_core-2.41.5-cp314-cp314-win_arm64.whl", hash = "sha256:e672ba74fbc2dc8eea59fb6d4aed6845e6905fc2a8afe93175d94a83ba2a01a0", size = 1977288, upload-time = "2025-11-04T13:41:26.33Z" }, - { url = "https://files.pythonhosted.org/packages/92/ed/77542d0c51538e32e15afe7899d79efce4b81eee631d99850edc2f5e9349/pydantic_core-2.41.5-cp314-cp314t-macosx_10_12_x86_64.whl", hash = "sha256:8566def80554c3faa0e65ac30ab0932b9e3a5cd7f8323764303d468e5c37595a", size = 2120255, upload-time = "2025-11-04T13:41:28.569Z" }, - { url = "https://files.pythonhosted.org/packages/bb/3d/6913dde84d5be21e284439676168b28d8bbba5600d838b9dca99de0fad71/pydantic_core-2.41.5-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:b80aa5095cd3109962a298ce14110ae16b8c1aece8b72f9dafe81cf597ad80b3", size = 1863760, upload-time = "2025-11-04T13:41:31.055Z" }, - { url = "https://files.pythonhosted.org/packages/5a/f0/e5e6b99d4191da102f2b0eb9687aaa7f5bea5d9964071a84effc3e40f997/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3006c3dd9ba34b0c094c544c6006cc79e87d8612999f1a5d43b769b89181f23c", size = 1878092, upload-time = "2025-11-04T13:41:33.21Z" }, - { url = "https://files.pythonhosted.org/packages/71/48/36fb760642d568925953bcc8116455513d6e34c4beaa37544118c36aba6d/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:72f6c8b11857a856bcfa48c86f5368439f74453563f951e473514579d44aa612", size = 2053385, upload-time = "2025-11-04T13:41:35.508Z" }, - { url = "https://files.pythonhosted.org/packages/20/25/92dc684dd8eb75a234bc1c764b4210cf2646479d54b47bf46061657292a8/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5cb1b2f9742240e4bb26b652a5aeb840aa4b417c7748b6f8387927bc6e45e40d", size = 2218832, upload-time = "2025-11-04T13:41:37.732Z" }, - { url = "https://files.pythonhosted.org/packages/e2/09/f53e0b05023d3e30357d82eb35835d0f6340ca344720a4599cd663dca599/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:bd3d54f38609ff308209bd43acea66061494157703364ae40c951f83ba99a1a9", size = 2327585, upload-time = "2025-11-04T13:41:40Z" }, - { url = "https://files.pythonhosted.org/packages/aa/4e/2ae1aa85d6af35a39b236b1b1641de73f5a6ac4d5a7509f77b814885760c/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2ff4321e56e879ee8d2a879501c8e469414d948f4aba74a2d4593184eb326660", size = 2041078, upload-time = "2025-11-04T13:41:42.323Z" }, - { url = "https://files.pythonhosted.org/packages/cd/13/2e215f17f0ef326fc72afe94776edb77525142c693767fc347ed6288728d/pydantic_core-2.41.5-cp314-cp314t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d0d2568a8c11bf8225044aa94409e21da0cb09dcdafe9ecd10250b2baad531a9", size = 2173914, upload-time = "2025-11-04T13:41:45.221Z" }, - { url = "https://files.pythonhosted.org/packages/02/7a/f999a6dcbcd0e5660bc348a3991c8915ce6599f4f2c6ac22f01d7a10816c/pydantic_core-2.41.5-cp314-cp314t-musllinux_1_1_aarch64.whl", hash = "sha256:a39455728aabd58ceabb03c90e12f71fd30fa69615760a075b9fec596456ccc3", size = 2129560, upload-time = "2025-11-04T13:41:47.474Z" }, - { url = "https://files.pythonhosted.org/packages/3a/b1/6c990ac65e3b4c079a4fb9f5b05f5b013afa0f4ed6780a3dd236d2cbdc64/pydantic_core-2.41.5-cp314-cp314t-musllinux_1_1_armv7l.whl", hash = "sha256:239edca560d05757817c13dc17c50766136d21f7cd0fac50295499ae24f90fdf", size = 2329244, upload-time = "2025-11-04T13:41:49.992Z" }, - { url = "https://files.pythonhosted.org/packages/d9/02/3c562f3a51afd4d88fff8dffb1771b30cfdfd79befd9883ee094f5b6c0d8/pydantic_core-2.41.5-cp314-cp314t-musllinux_1_1_x86_64.whl", hash = "sha256:2a5e06546e19f24c6a96a129142a75cee553cc018ffee48a460059b1185f4470", size = 2331955, upload-time = "2025-11-04T13:41:54.079Z" }, - { url = "https://files.pythonhosted.org/packages/5c/96/5fb7d8c3c17bc8c62fdb031c47d77a1af698f1d7a406b0f79aaa1338f9ad/pydantic_core-2.41.5-cp314-cp314t-win32.whl", hash = "sha256:b4ececa40ac28afa90871c2cc2b9ffd2ff0bf749380fbdf57d165fd23da353aa", size = 1988906, upload-time = "2025-11-04T13:41:56.606Z" }, - { url = "https://files.pythonhosted.org/packages/22/ed/182129d83032702912c2e2d8bbe33c036f342cc735737064668585dac28f/pydantic_core-2.41.5-cp314-cp314t-win_amd64.whl", hash = "sha256:80aa89cad80b32a912a65332f64a4450ed00966111b6615ca6816153d3585a8c", size = 1981607, upload-time = "2025-11-04T13:41:58.889Z" }, - { url = "https://files.pythonhosted.org/packages/9f/ed/068e41660b832bb0b1aa5b58011dea2a3fe0ba7861ff38c4d4904c1c1a99/pydantic_core-2.41.5-cp314-cp314t-win_arm64.whl", hash = "sha256:35b44f37a3199f771c3eaa53051bc8a70cd7b54f333531c59e29fd4db5d15008", size = 1974769, upload-time = "2025-11-04T13:42:01.186Z" }, - { url = "https://files.pythonhosted.org/packages/11/72/90fda5ee3b97e51c494938a4a44c3a35a9c96c19bba12372fb9c634d6f57/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-macosx_10_12_x86_64.whl", hash = "sha256:b96d5f26b05d03cc60f11a7761a5ded1741da411e7fe0909e27a5e6a0cb7b034", size = 2115441, upload-time = "2025-11-04T13:42:39.557Z" }, - { url = "https://files.pythonhosted.org/packages/1f/53/8942f884fa33f50794f119012dc6a1a02ac43a56407adaac20463df8e98f/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-macosx_11_0_arm64.whl", hash = "sha256:634e8609e89ceecea15e2d61bc9ac3718caaaa71963717bf3c8f38bfde64242c", size = 1930291, upload-time = "2025-11-04T13:42:42.169Z" }, - { url = "https://files.pythonhosted.org/packages/79/c8/ecb9ed9cd942bce09fc888ee960b52654fbdbede4ba6c2d6e0d3b1d8b49c/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:93e8740d7503eb008aa2df04d3b9735f845d43ae845e6dcd2be0b55a2da43cd2", size = 1948632, upload-time = "2025-11-04T13:42:44.564Z" }, - { url = "https://files.pythonhosted.org/packages/2e/1b/687711069de7efa6af934e74f601e2a4307365e8fdc404703afc453eab26/pydantic_core-2.41.5-graalpy311-graalpy242_311_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f15489ba13d61f670dcc96772e733aad1a6f9c429cc27574c6cdaed82d0146ad", size = 2138905, upload-time = "2025-11-04T13:42:47.156Z" }, - { url = "https://files.pythonhosted.org/packages/09/32/59b0c7e63e277fa7911c2fc70ccfb45ce4b98991e7ef37110663437005af/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-macosx_10_12_x86_64.whl", hash = "sha256:7da7087d756b19037bc2c06edc6c170eeef3c3bafcb8f532ff17d64dc427adfd", size = 2110495, upload-time = "2025-11-04T13:42:49.689Z" }, - { url = "https://files.pythonhosted.org/packages/aa/81/05e400037eaf55ad400bcd318c05bb345b57e708887f07ddb2d20e3f0e98/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-macosx_11_0_arm64.whl", hash = "sha256:aabf5777b5c8ca26f7824cb4a120a740c9588ed58df9b2d196ce92fba42ff8dc", size = 1915388, upload-time = "2025-11-04T13:42:52.215Z" }, - { url = "https://files.pythonhosted.org/packages/6e/0d/e3549b2399f71d56476b77dbf3cf8937cec5cd70536bdc0e374a421d0599/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c007fe8a43d43b3969e8469004e9845944f1a80e6acd47c150856bb87f230c56", size = 1942879, upload-time = "2025-11-04T13:42:56.483Z" }, - { url = "https://files.pythonhosted.org/packages/f7/07/34573da085946b6a313d7c42f82f16e8920bfd730665de2d11c0c37a74b5/pydantic_core-2.41.5-graalpy312-graalpy250_312_native-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:76d0819de158cd855d1cbb8fcafdf6f5cf1eb8e470abe056d5d161106e38062b", size = 2139017, upload-time = "2025-11-04T13:42:59.471Z" }, - { url = "https://files.pythonhosted.org/packages/e6/b0/1a2aa41e3b5a4ba11420aba2d091b2d17959c8d1519ece3627c371951e73/pydantic_core-2.41.5-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:b5819cd790dbf0c5eb9f82c73c16b39a65dd6dd4d1439dcdea7816ec9adddab8", size = 2103351, upload-time = "2025-11-04T13:43:02.058Z" }, - { url = "https://files.pythonhosted.org/packages/a4/ee/31b1f0020baaf6d091c87900ae05c6aeae101fa4e188e1613c80e4f1ea31/pydantic_core-2.41.5-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:5a4e67afbc95fa5c34cf27d9089bca7fcab4e51e57278d710320a70b956d1b9a", size = 1925363, upload-time = "2025-11-04T13:43:05.159Z" }, - { url = "https://files.pythonhosted.org/packages/e1/89/ab8e86208467e467a80deaca4e434adac37b10a9d134cd2f99b28a01e483/pydantic_core-2.41.5-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ece5c59f0ce7d001e017643d8d24da587ea1f74f6993467d85ae8a5ef9d4f42b", size = 2135615, upload-time = "2025-11-04T13:43:08.116Z" }, - { url = "https://files.pythonhosted.org/packages/99/0a/99a53d06dd0348b2008f2f30884b34719c323f16c3be4e6cc1203b74a91d/pydantic_core-2.41.5-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:16f80f7abe3351f8ea6858914ddc8c77e02578544a0ebc15b4c2e1a0e813b0b2", size = 2175369, upload-time = "2025-11-04T13:43:12.49Z" }, - { url = "https://files.pythonhosted.org/packages/6d/94/30ca3b73c6d485b9bb0bc66e611cff4a7138ff9736b7e66bcf0852151636/pydantic_core-2.41.5-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:33cb885e759a705b426baada1fe68cbb0a2e68e34c5d0d0289a364cf01709093", size = 2144218, upload-time = "2025-11-04T13:43:15.431Z" }, - { url = "https://files.pythonhosted.org/packages/87/57/31b4f8e12680b739a91f472b5671294236b82586889ef764b5fbc6669238/pydantic_core-2.41.5-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:c8d8b4eb992936023be7dee581270af5c6e0697a8559895f527f5b7105ecd36a", size = 2329951, upload-time = "2025-11-04T13:43:18.062Z" }, - { url = "https://files.pythonhosted.org/packages/7d/73/3c2c8edef77b8f7310e6fb012dbc4b8551386ed575b9eb6fb2506e28a7eb/pydantic_core-2.41.5-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:242a206cd0318f95cd21bdacff3fcc3aab23e79bba5cac3db5a841c9ef9c6963", size = 2318428, upload-time = "2025-11-04T13:43:20.679Z" }, - { url = "https://files.pythonhosted.org/packages/2f/02/8559b1f26ee0d502c74f9cca5c0d2fd97e967e083e006bbbb4e97f3a043a/pydantic_core-2.41.5-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:d3a978c4f57a597908b7e697229d996d77a6d3c94901e9edee593adada95ce1a", size = 2147009, upload-time = "2025-11-04T13:43:23.286Z" }, - { url = "https://files.pythonhosted.org/packages/5f/9b/1b3f0e9f9305839d7e84912f9e8bfbd191ed1b1ef48083609f0dabde978c/pydantic_core-2.41.5-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:b2379fa7ed44ddecb5bfe4e48577d752db9fc10be00a6b7446e9663ba143de26", size = 2101980, upload-time = "2025-11-04T13:43:25.97Z" }, - { url = "https://files.pythonhosted.org/packages/a4/ed/d71fefcb4263df0da6a85b5d8a7508360f2f2e9b3bf5814be9c8bccdccc1/pydantic_core-2.41.5-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:266fb4cbf5e3cbd0b53669a6d1b039c45e3ce651fd5442eff4d07c2cc8d66808", size = 1923865, upload-time = "2025-11-04T13:43:28.763Z" }, - { url = "https://files.pythonhosted.org/packages/ce/3a/626b38db460d675f873e4444b4bb030453bbe7b4ba55df821d026a0493c4/pydantic_core-2.41.5-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58133647260ea01e4d0500089a8c4f07bd7aa6ce109682b1426394988d8aaacc", size = 2134256, upload-time = "2025-11-04T13:43:31.71Z" }, - { url = "https://files.pythonhosted.org/packages/83/d9/8412d7f06f616bbc053d30cb4e5f76786af3221462ad5eee1f202021eb4e/pydantic_core-2.41.5-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:287dad91cfb551c363dc62899a80e9e14da1f0e2b6ebde82c806612ca2a13ef1", size = 2174762, upload-time = "2025-11-04T13:43:34.744Z" }, - { url = "https://files.pythonhosted.org/packages/55/4c/162d906b8e3ba3a99354e20faa1b49a85206c47de97a639510a0e673f5da/pydantic_core-2.41.5-pp311-pypy311_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:03b77d184b9eb40240ae9fd676ca364ce1085f203e1b1256f8ab9984dca80a84", size = 2143141, upload-time = "2025-11-04T13:43:37.701Z" }, - { url = "https://files.pythonhosted.org/packages/1f/f2/f11dd73284122713f5f89fc940f370d035fa8e1e078d446b3313955157fe/pydantic_core-2.41.5-pp311-pypy311_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:a668ce24de96165bb239160b3d854943128f4334822900534f2fe947930e5770", size = 2330317, upload-time = "2025-11-04T13:43:40.406Z" }, - { url = "https://files.pythonhosted.org/packages/88/9d/b06ca6acfe4abb296110fb1273a4d848a0bfb2ff65f3ee92127b3244e16b/pydantic_core-2.41.5-pp311-pypy311_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f14f8f046c14563f8eb3f45f499cc658ab8d10072961e07225e507adb700e93f", size = 2316992, upload-time = "2025-11-04T13:43:43.602Z" }, - { url = "https://files.pythonhosted.org/packages/36/c7/cfc8e811f061c841d7990b0201912c3556bfeb99cdcb7ed24adc8d6f8704/pydantic_core-2.41.5-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:56121965f7a4dc965bff783d70b907ddf3d57f6eba29b6d2e5dabfaf07799c51", size = 2145302, upload-time = "2025-11-04T13:43:46.64Z" }, -] - -[[package]] -name = "pygments" -version = "2.19.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/b0/77/a5b8c569bf593b0140bde72ea885a803b82086995367bf2037de0159d924/pygments-2.19.2.tar.gz", hash = "sha256:636cb2477cec7f8952536970bc533bc43743542f70392ae026374600add5b887", size = 4968631, upload-time = "2025-06-21T13:39:12.283Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl", hash = "sha256:86540386c03d588bb81d44bc3928634ff26449851e99741617ecb9037ee5ec0b", size = 1225217, upload-time = "2025-06-21T13:39:07.939Z" }, -] - -[[package]] -name = "pytest" -version = "9.0.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "colorama", marker = "sys_platform == 'win32'" }, - { name = "exceptiongroup", marker = "python_full_version < '3.11'" }, - { name = "iniconfig" }, - { name = "packaging" }, - { name = "pluggy" }, - { name = "pygments" }, - { name = "tomli", marker = "python_full_version < '3.11'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/d1/db/7ef3487e0fb0049ddb5ce41d3a49c235bf9ad299b6a25d5780a89f19230f/pytest-9.0.2.tar.gz", hash = "sha256:75186651a92bd89611d1d9fc20f0b4345fd827c41ccd5c299a868a05d70edf11", size = 1568901, upload-time = "2025-12-06T21:30:51.014Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl", hash = "sha256:711ffd45bf766d5264d487b917733b453d917afd2b0ad65223959f59089f875b", size = 374801, upload-time = "2025-12-06T21:30:49.154Z" }, -] - -[[package]] -name = "python-dotenv" -version = "1.2.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/f0/26/19cadc79a718c5edbec86fd4919a6b6d3f681039a2f6d66d14be94e75fb9/python_dotenv-1.2.1.tar.gz", hash = "sha256:42667e897e16ab0d66954af0e60a9caa94f0fd4ecf3aaf6d2d260eec1aa36ad6", size = 44221, upload-time = "2025-10-26T15:12:10.434Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/14/1b/a298b06749107c305e1fe0f814c6c74aea7b2f1e10989cb30f544a1b3253/python_dotenv-1.2.1-py3-none-any.whl", hash = "sha256:b81ee9561e9ca4004139c6cbba3a238c32b03e4894671e181b671e8cb8425d61", size = 21230, upload-time = "2025-10-26T15:12:09.109Z" }, -] - -[[package]] -name = "python-slugify" -version = "8.0.4" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "text-unidecode" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/87/c7/5e1547c44e31da50a460df93af11a535ace568ef89d7a811069ead340c4a/python-slugify-8.0.4.tar.gz", hash = "sha256:59202371d1d05b54a9e7720c5e038f928f45daaffe41dd10822f3907b937c856", size = 10921, upload-time = "2024-02-08T18:32:45.488Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a4/62/02da182e544a51a5c3ccf4b03ab79df279f9c60c5e82d5e8bec7ca26ac11/python_slugify-8.0.4-py2.py3-none-any.whl", hash = "sha256:276540b79961052b66b7d116620b36518847f52d5fd9e3a70164fc8c50faa6b8", size = 10051, upload-time = "2024-02-08T18:32:43.911Z" }, -] - -[[package]] -name = "requests" -version = "2.32.5" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "certifi" }, - { name = "charset-normalizer" }, - { name = "idna" }, - { name = "urllib3" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/c9/74/b3ff8e6c8446842c3f5c837e9c3dfcfe2018ea6ecef224c710c85ef728f4/requests-2.32.5.tar.gz", hash = "sha256:dbba0bac56e100853db0ea71b82b4dfd5fe2bf6d3754a8893c3af500cec7d7cf", size = 134517, upload-time = "2025-08-18T20:46:02.573Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl", hash = "sha256:2462f94637a34fd532264295e186976db0f5d453d1cdd31473c85a6a161affb6", size = 64738, upload-time = "2025-08-18T20:46:00.542Z" }, -] - -[[package]] -name = "requests-toolbelt" -version = "1.0.0" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "requests" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/f3/61/d7545dafb7ac2230c70d38d31cbfe4cc64f7144dc41f6e4e4b78ecd9f5bb/requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6", size = 206888, upload-time = "2023-05-01T04:11:33.229Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/3f/51/d4db610ef29373b879047326cbf6fa98b6c1969d6f6dc423279de2b1be2c/requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06", size = 54481, upload-time = "2023-05-01T04:11:28.427Z" }, -] - -[[package]] -name = "smmap" -version = "5.0.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/44/cd/a040c4b3119bbe532e5b0732286f805445375489fceaec1f48306068ee3b/smmap-5.0.2.tar.gz", hash = "sha256:26ea65a03958fa0c8a1c7e8c7a58fdc77221b8910f6be2131affade476898ad5", size = 22329, upload-time = "2025-01-02T07:14:40.909Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/04/be/d09147ad1ec7934636ad912901c5fd7667e1c858e19d355237db0d0cd5e4/smmap-5.0.2-py3-none-any.whl", hash = "sha256:b30115f0def7d7531d22a0fb6502488d879e75b260a9db4d0819cfb25403af5e", size = 24303, upload-time = "2025-01-02T07:14:38.724Z" }, -] - -[[package]] -name = "sseclient-py" -version = "1.8.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/e8/ed/3df5ab8bb0c12f86c28d0cadb11ed1de44a92ed35ce7ff4fd5518a809325/sseclient-py-1.8.0.tar.gz", hash = "sha256:c547c5c1a7633230a38dc599a21a2dc638f9b5c297286b48b46b935c71fac3e8", size = 7791, upload-time = "2023-09-01T19:39:20.45Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/49/58/97655efdfeb5b4eeab85b1fc5d3fa1023661246c2ab2a26ea8e47402d4f2/sseclient_py-1.8.0-py2.py3-none-any.whl", hash = "sha256:4ecca6dc0b9f963f8384e9d7fd529bf93dd7d708144c4fb5da0e0a1a926fee83", size = 8828, upload-time = "2023-09-01T19:39:17.627Z" }, -] - -[[package]] -name = "text-unidecode" -version = "1.3" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/ab/e2/e9a00f0ccb71718418230718b3d900e71a5d16e701a3dae079a21e9cd8f8/text-unidecode-1.3.tar.gz", hash = "sha256:bad6603bb14d279193107714b288be206cac565dfa49aa5b105294dd5c4aab93", size = 76885, upload-time = "2019-08-30T21:36:45.405Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/a6/a5/c0b6468d3824fe3fde30dbb5e1f687b291608f9473681bbf7dabbf5a87d7/text_unidecode-1.3-py2.py3-none-any.whl", hash = "sha256:1311f10e8b895935241623731c2ba64f4c455287888b18189350b67134a822e8", size = 78154, upload-time = "2019-08-30T21:37:03.543Z" }, -] - -[[package]] -name = "tomli" -version = "2.3.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/52/ed/3f73f72945444548f33eba9a87fc7a6e969915e7b1acc8260b30e1f76a2f/tomli-2.3.0.tar.gz", hash = "sha256:64be704a875d2a59753d80ee8a533c3fe183e3f06807ff7dc2232938ccb01549", size = 17392, upload-time = "2025-10-08T22:01:47.119Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b3/2e/299f62b401438d5fe1624119c723f5d877acc86a4c2492da405626665f12/tomli-2.3.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:88bd15eb972f3664f5ed4b57c1634a97153b4bac4479dcb6a495f41921eb7f45", size = 153236, upload-time = "2025-10-08T22:01:00.137Z" }, - { url = "https://files.pythonhosted.org/packages/86/7f/d8fffe6a7aefdb61bced88fcb5e280cfd71e08939da5894161bd71bea022/tomli-2.3.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:883b1c0d6398a6a9d29b508c331fa56adbcdff647f6ace4dfca0f50e90dfd0ba", size = 148084, upload-time = "2025-10-08T22:01:01.63Z" }, - { url = "https://files.pythonhosted.org/packages/47/5c/24935fb6a2ee63e86d80e4d3b58b222dafaf438c416752c8b58537c8b89a/tomli-2.3.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d1381caf13ab9f300e30dd8feadb3de072aeb86f1d34a8569453ff32a7dea4bf", size = 234832, upload-time = "2025-10-08T22:01:02.543Z" }, - { url = "https://files.pythonhosted.org/packages/89/da/75dfd804fc11e6612846758a23f13271b76d577e299592b4371a4ca4cd09/tomli-2.3.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a0e285d2649b78c0d9027570d4da3425bdb49830a6156121360b3f8511ea3441", size = 242052, upload-time = "2025-10-08T22:01:03.836Z" }, - { url = "https://files.pythonhosted.org/packages/70/8c/f48ac899f7b3ca7eb13af73bacbc93aec37f9c954df3c08ad96991c8c373/tomli-2.3.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:0a154a9ae14bfcf5d8917a59b51ffd5a3ac1fd149b71b47a3a104ca4edcfa845", size = 239555, upload-time = "2025-10-08T22:01:04.834Z" }, - { url = "https://files.pythonhosted.org/packages/ba/28/72f8afd73f1d0e7829bfc093f4cb98ce0a40ffc0cc997009ee1ed94ba705/tomli-2.3.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:74bf8464ff93e413514fefd2be591c3b0b23231a77f901db1eb30d6f712fc42c", size = 245128, upload-time = "2025-10-08T22:01:05.84Z" }, - { url = "https://files.pythonhosted.org/packages/b6/eb/a7679c8ac85208706d27436e8d421dfa39d4c914dcf5fa8083a9305f58d9/tomli-2.3.0-cp311-cp311-win32.whl", hash = "sha256:00b5f5d95bbfc7d12f91ad8c593a1659b6387b43f054104cda404be6bda62456", size = 96445, upload-time = "2025-10-08T22:01:06.896Z" }, - { url = "https://files.pythonhosted.org/packages/0a/fe/3d3420c4cb1ad9cb462fb52967080575f15898da97e21cb6f1361d505383/tomli-2.3.0-cp311-cp311-win_amd64.whl", hash = "sha256:4dc4ce8483a5d429ab602f111a93a6ab1ed425eae3122032db7e9acf449451be", size = 107165, upload-time = "2025-10-08T22:01:08.107Z" }, - { url = "https://files.pythonhosted.org/packages/ff/b7/40f36368fcabc518bb11c8f06379a0fd631985046c038aca08c6d6a43c6e/tomli-2.3.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:d7d86942e56ded512a594786a5ba0a5e521d02529b3826e7761a05138341a2ac", size = 154891, upload-time = "2025-10-08T22:01:09.082Z" }, - { url = "https://files.pythonhosted.org/packages/f9/3f/d9dd692199e3b3aab2e4e4dd948abd0f790d9ded8cd10cbaae276a898434/tomli-2.3.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:73ee0b47d4dad1c5e996e3cd33b8a76a50167ae5f96a2607cbe8cc773506ab22", size = 148796, upload-time = "2025-10-08T22:01:10.266Z" }, - { url = "https://files.pythonhosted.org/packages/60/83/59bff4996c2cf9f9387a0f5a3394629c7efa5ef16142076a23a90f1955fa/tomli-2.3.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:792262b94d5d0a466afb5bc63c7daa9d75520110971ee269152083270998316f", size = 242121, upload-time = "2025-10-08T22:01:11.332Z" }, - { url = "https://files.pythonhosted.org/packages/45/e5/7c5119ff39de8693d6baab6c0b6dcb556d192c165596e9fc231ea1052041/tomli-2.3.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4f195fe57ecceac95a66a75ac24d9d5fbc98ef0962e09b2eddec5d39375aae52", size = 250070, upload-time = "2025-10-08T22:01:12.498Z" }, - { url = "https://files.pythonhosted.org/packages/45/12/ad5126d3a278f27e6701abde51d342aa78d06e27ce2bb596a01f7709a5a2/tomli-2.3.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:e31d432427dcbf4d86958c184b9bfd1e96b5b71f8eb17e6d02531f434fd335b8", size = 245859, upload-time = "2025-10-08T22:01:13.551Z" }, - { url = "https://files.pythonhosted.org/packages/fb/a1/4d6865da6a71c603cfe6ad0e6556c73c76548557a8d658f9e3b142df245f/tomli-2.3.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:7b0882799624980785240ab732537fcfc372601015c00f7fc367c55308c186f6", size = 250296, upload-time = "2025-10-08T22:01:14.614Z" }, - { url = "https://files.pythonhosted.org/packages/a0/b7/a7a7042715d55c9ba6e8b196d65d2cb662578b4d8cd17d882d45322b0d78/tomli-2.3.0-cp312-cp312-win32.whl", hash = "sha256:ff72b71b5d10d22ecb084d345fc26f42b5143c5533db5e2eaba7d2d335358876", size = 97124, upload-time = "2025-10-08T22:01:15.629Z" }, - { url = "https://files.pythonhosted.org/packages/06/1e/f22f100db15a68b520664eb3328fb0ae4e90530887928558112c8d1f4515/tomli-2.3.0-cp312-cp312-win_amd64.whl", hash = "sha256:1cb4ed918939151a03f33d4242ccd0aa5f11b3547d0cf30f7c74a408a5b99878", size = 107698, upload-time = "2025-10-08T22:01:16.51Z" }, - { url = "https://files.pythonhosted.org/packages/89/48/06ee6eabe4fdd9ecd48bf488f4ac783844fd777f547b8d1b61c11939974e/tomli-2.3.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:5192f562738228945d7b13d4930baffda67b69425a7f0da96d360b0a3888136b", size = 154819, upload-time = "2025-10-08T22:01:17.964Z" }, - { url = "https://files.pythonhosted.org/packages/f1/01/88793757d54d8937015c75dcdfb673c65471945f6be98e6a0410fba167ed/tomli-2.3.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:be71c93a63d738597996be9528f4abe628d1adf5e6eb11607bc8fe1a510b5dae", size = 148766, upload-time = "2025-10-08T22:01:18.959Z" }, - { url = "https://files.pythonhosted.org/packages/42/17/5e2c956f0144b812e7e107f94f1cc54af734eb17b5191c0bbfb72de5e93e/tomli-2.3.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c4665508bcbac83a31ff8ab08f424b665200c0e1e645d2bd9ab3d3e557b6185b", size = 240771, upload-time = "2025-10-08T22:01:20.106Z" }, - { url = "https://files.pythonhosted.org/packages/d5/f4/0fbd014909748706c01d16824eadb0307115f9562a15cbb012cd9b3512c5/tomli-2.3.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4021923f97266babc6ccab9f5068642a0095faa0a51a246a6a02fccbb3514eaf", size = 248586, upload-time = "2025-10-08T22:01:21.164Z" }, - { url = "https://files.pythonhosted.org/packages/30/77/fed85e114bde5e81ecf9bc5da0cc69f2914b38f4708c80ae67d0c10180c5/tomli-2.3.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a4ea38c40145a357d513bffad0ed869f13c1773716cf71ccaa83b0fa0cc4e42f", size = 244792, upload-time = "2025-10-08T22:01:22.417Z" }, - { url = "https://files.pythonhosted.org/packages/55/92/afed3d497f7c186dc71e6ee6d4fcb0acfa5f7d0a1a2878f8beae379ae0cc/tomli-2.3.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:ad805ea85eda330dbad64c7ea7a4556259665bdf9d2672f5dccc740eb9d3ca05", size = 248909, upload-time = "2025-10-08T22:01:23.859Z" }, - { url = "https://files.pythonhosted.org/packages/f8/84/ef50c51b5a9472e7265ce1ffc7f24cd4023d289e109f669bdb1553f6a7c2/tomli-2.3.0-cp313-cp313-win32.whl", hash = "sha256:97d5eec30149fd3294270e889b4234023f2c69747e555a27bd708828353ab606", size = 96946, upload-time = "2025-10-08T22:01:24.893Z" }, - { url = "https://files.pythonhosted.org/packages/b2/b7/718cd1da0884f281f95ccfa3a6cc572d30053cba64603f79d431d3c9b61b/tomli-2.3.0-cp313-cp313-win_amd64.whl", hash = "sha256:0c95ca56fbe89e065c6ead5b593ee64b84a26fca063b5d71a1122bf26e533999", size = 107705, upload-time = "2025-10-08T22:01:26.153Z" }, - { url = "https://files.pythonhosted.org/packages/19/94/aeafa14a52e16163008060506fcb6aa1949d13548d13752171a755c65611/tomli-2.3.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:cebc6fe843e0733ee827a282aca4999b596241195f43b4cc371d64fc6639da9e", size = 154244, upload-time = "2025-10-08T22:01:27.06Z" }, - { url = "https://files.pythonhosted.org/packages/db/e4/1e58409aa78eefa47ccd19779fc6f36787edbe7d4cd330eeeedb33a4515b/tomli-2.3.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:4c2ef0244c75aba9355561272009d934953817c49f47d768070c3c94355c2aa3", size = 148637, upload-time = "2025-10-08T22:01:28.059Z" }, - { url = "https://files.pythonhosted.org/packages/26/b6/d1eccb62f665e44359226811064596dd6a366ea1f985839c566cd61525ae/tomli-2.3.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c22a8bf253bacc0cf11f35ad9808b6cb75ada2631c2d97c971122583b129afbc", size = 241925, upload-time = "2025-10-08T22:01:29.066Z" }, - { url = "https://files.pythonhosted.org/packages/70/91/7cdab9a03e6d3d2bb11beae108da5bdc1c34bdeb06e21163482544ddcc90/tomli-2.3.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0eea8cc5c5e9f89c9b90c4896a8deefc74f518db5927d0e0e8d4a80953d774d0", size = 249045, upload-time = "2025-10-08T22:01:31.98Z" }, - { url = "https://files.pythonhosted.org/packages/15/1b/8c26874ed1f6e4f1fcfeb868db8a794cbe9f227299402db58cfcc858766c/tomli-2.3.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:b74a0e59ec5d15127acdabd75ea17726ac4c5178ae51b85bfe39c4f8a278e879", size = 245835, upload-time = "2025-10-08T22:01:32.989Z" }, - { url = "https://files.pythonhosted.org/packages/fd/42/8e3c6a9a4b1a1360c1a2a39f0b972cef2cc9ebd56025168c4137192a9321/tomli-2.3.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:b5870b50c9db823c595983571d1296a6ff3e1b88f734a4c8f6fc6188397de005", size = 253109, upload-time = "2025-10-08T22:01:34.052Z" }, - { url = "https://files.pythonhosted.org/packages/22/0c/b4da635000a71b5f80130937eeac12e686eefb376b8dee113b4a582bba42/tomli-2.3.0-cp314-cp314-win32.whl", hash = "sha256:feb0dacc61170ed7ab602d3d972a58f14ee3ee60494292d384649a3dc38ef463", size = 97930, upload-time = "2025-10-08T22:01:35.082Z" }, - { url = "https://files.pythonhosted.org/packages/b9/74/cb1abc870a418ae99cd5c9547d6bce30701a954e0e721821df483ef7223c/tomli-2.3.0-cp314-cp314-win_amd64.whl", hash = "sha256:b273fcbd7fc64dc3600c098e39136522650c49bca95df2d11cf3b626422392c8", size = 107964, upload-time = "2025-10-08T22:01:36.057Z" }, - { url = "https://files.pythonhosted.org/packages/54/78/5c46fff6432a712af9f792944f4fcd7067d8823157949f4e40c56b8b3c83/tomli-2.3.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:940d56ee0410fa17ee1f12b817b37a4d4e4dc4d27340863cc67236c74f582e77", size = 163065, upload-time = "2025-10-08T22:01:37.27Z" }, - { url = "https://files.pythonhosted.org/packages/39/67/f85d9bd23182f45eca8939cd2bc7050e1f90c41f4a2ecbbd5963a1d1c486/tomli-2.3.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:f85209946d1fe94416debbb88d00eb92ce9cd5266775424ff81bc959e001acaf", size = 159088, upload-time = "2025-10-08T22:01:38.235Z" }, - { url = "https://files.pythonhosted.org/packages/26/5a/4b546a0405b9cc0659b399f12b6adb750757baf04250b148d3c5059fc4eb/tomli-2.3.0-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:a56212bdcce682e56b0aaf79e869ba5d15a6163f88d5451cbde388d48b13f530", size = 268193, upload-time = "2025-10-08T22:01:39.712Z" }, - { url = "https://files.pythonhosted.org/packages/42/4f/2c12a72ae22cf7b59a7fe75b3465b7aba40ea9145d026ba41cb382075b0e/tomli-2.3.0-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c5f3ffd1e098dfc032d4d3af5c0ac64f6d286d98bc148698356847b80fa4de1b", size = 275488, upload-time = "2025-10-08T22:01:40.773Z" }, - { url = "https://files.pythonhosted.org/packages/92/04/a038d65dbe160c3aa5a624e93ad98111090f6804027d474ba9c37c8ae186/tomli-2.3.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:5e01decd096b1530d97d5d85cb4dff4af2d8347bd35686654a004f8dea20fc67", size = 272669, upload-time = "2025-10-08T22:01:41.824Z" }, - { url = "https://files.pythonhosted.org/packages/be/2f/8b7c60a9d1612a7cbc39ffcca4f21a73bf368a80fc25bccf8253e2563267/tomli-2.3.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:8a35dd0e643bb2610f156cca8db95d213a90015c11fee76c946aa62b7ae7e02f", size = 279709, upload-time = "2025-10-08T22:01:43.177Z" }, - { url = "https://files.pythonhosted.org/packages/7e/46/cc36c679f09f27ded940281c38607716c86cf8ba4a518d524e349c8b4874/tomli-2.3.0-cp314-cp314t-win32.whl", hash = "sha256:a1f7f282fe248311650081faafa5f4732bdbfef5d45fe3f2e702fbc6f2d496e0", size = 107563, upload-time = "2025-10-08T22:01:44.233Z" }, - { url = "https://files.pythonhosted.org/packages/84/ff/426ca8683cf7b753614480484f6437f568fd2fda2edbdf57a2d3d8b27a0b/tomli-2.3.0-cp314-cp314t-win_amd64.whl", hash = "sha256:70a251f8d4ba2d9ac2542eecf008b3c8a9fc5c3f9f02c56a9d7952612be2fdba", size = 119756, upload-time = "2025-10-08T22:01:45.234Z" }, - { url = "https://files.pythonhosted.org/packages/77/b8/0135fadc89e73be292b473cb820b4f5a08197779206b33191e801feeae40/tomli-2.3.0-py3-none-any.whl", hash = "sha256:e95b1af3c5b07d9e643909b5abbec77cd9f1217e6d0bca72b0234736b9fb1f1b", size = 14408, upload-time = "2025-10-08T22:01:46.04Z" }, -] - -[[package]] -name = "tqdm" -version = "4.67.1" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "colorama", marker = "sys_platform == 'win32'" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/a8/4b/29b4ef32e036bb34e4ab51796dd745cdba7ed47ad142a9f4a1eb8e0c744d/tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2", size = 169737, upload-time = "2024-11-24T20:12:22.481Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/d0/30/dc54f88dd4a2b5dc8a0279bdd7270e735851848b762aeb1c1184ed1f6b14/tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2", size = 78540, upload-time = "2024-11-24T20:12:19.698Z" }, -] - -[[package]] -name = "typing-extensions" -version = "4.15.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/72/94/1a15dd82efb362ac84269196e94cf00f187f7ed21c242792a923cdb1c61f/typing_extensions-4.15.0.tar.gz", hash = "sha256:0cea48d173cc12fa28ecabc3b837ea3cf6f38c6d1136f85cbaaf598984861466", size = 109391, upload-time = "2025-08-25T13:49:26.313Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl", hash = "sha256:f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548", size = 44614, upload-time = "2025-08-25T13:49:24.86Z" }, -] - -[[package]] -name = "typing-inspection" -version = "0.4.2" -source = { registry = "https://pypi.org/simple" } -dependencies = [ - { name = "typing-extensions" }, -] -sdist = { url = "https://files.pythonhosted.org/packages/55/e3/70399cb7dd41c10ac53367ae42139cf4b1ca5f36bb3dc6c9d33acdb43655/typing_inspection-0.4.2.tar.gz", hash = "sha256:ba561c48a67c5958007083d386c3295464928b01faa735ab8547c5692e87f464", size = 75949, upload-time = "2025-10-01T02:14:41.687Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/dc/9b/47798a6c91d8bdb567fe2698fe81e0c6b7cb7ef4d13da4114b41d239f65d/typing_inspection-0.4.2-py3-none-any.whl", hash = "sha256:4ed1cacbdc298c220f1bd249ed5287caa16f34d44ef4e9c3d0cbad5b521545e7", size = 14611, upload-time = "2025-10-01T02:14:40.154Z" }, -] - -[[package]] -name = "urllib3" -version = "2.6.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/1c/43/554c2569b62f49350597348fc3ac70f786e3c32e7f19d266e19817812dd3/urllib3-2.6.0.tar.gz", hash = "sha256:cb9bcef5a4b345d5da5d145dc3e30834f58e8018828cbc724d30b4cb7d4d49f1", size = 432585, upload-time = "2025-12-05T15:08:47.885Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/56/1a/9ffe814d317c5224166b23e7c47f606d6e473712a2fad0f704ea9b99f246/urllib3-2.6.0-py3-none-any.whl", hash = "sha256:c90f7a39f716c572c4e3e58509581ebd83f9b59cced005b7db7ad2d22b0db99f", size = 131083, upload-time = "2025-12-05T15:08:45.983Z" }, -] - -[[package]] -name = "uuid-utils" -version = "0.12.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/0b/0e/512fb221e4970c2f75ca9dae412d320b7d9ddc9f2b15e04ea8e44710396c/uuid_utils-0.12.0.tar.gz", hash = "sha256:252bd3d311b5d6b7f5dfce7a5857e27bb4458f222586bb439463231e5a9cbd64", size = 20889, upload-time = "2025-12-01T17:29:55.494Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/8a/43/de5cd49a57b6293b911b6a9a62fc03e55db9f964da7d5882d9edbee1e9d2/uuid_utils-0.12.0-cp39-abi3-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:3b9b30707659292f207b98f294b0e081f6d77e1fbc760ba5b41331a39045f514", size = 603197, upload-time = "2025-12-01T17:29:30.104Z" }, - { url = "https://files.pythonhosted.org/packages/02/fa/5fd1d8c9234e44f0c223910808cde0de43bb69f7df1349e49b1afa7f2baa/uuid_utils-0.12.0-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:add3d820c7ec14ed37317375bea30249699c5d08ff4ae4dbee9fc9bce3bfbf65", size = 305168, upload-time = "2025-12-01T17:29:31.384Z" }, - { url = "https://files.pythonhosted.org/packages/c8/c6/8633ac9942bf9dc97a897b5154e5dcffa58816ec4dd780b3b12b559ff05c/uuid_utils-0.12.0-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1b8fce83ecb3b16af29c7809669056c4b6e7cc912cab8c6d07361645de12dd79", size = 340580, upload-time = "2025-12-01T17:29:32.362Z" }, - { url = "https://files.pythonhosted.org/packages/f3/88/8a61307b04b4da1c576373003e6d857a04dade52ab035151d62cb84d5cb5/uuid_utils-0.12.0-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ec921769afcb905035d785582b0791d02304a7850fbd6ce924c1a8976380dfc6", size = 346771, upload-time = "2025-12-01T17:29:33.708Z" }, - { url = "https://files.pythonhosted.org/packages/1c/fb/aab2dcf94b991e62aa167457c7825b9b01055b884b888af926562864398c/uuid_utils-0.12.0-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6f3b060330f5899a92d5c723547dc6a95adef42433e9748f14c66859a7396664", size = 474781, upload-time = "2025-12-01T17:29:35.237Z" }, - { url = "https://files.pythonhosted.org/packages/5a/7a/dbd5e49c91d6c86dba57158bbfa0e559e1ddf377bb46dcfd58aea4f0d567/uuid_utils-0.12.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:908dfef7f0bfcf98d406e5dc570c25d2f2473e49b376de41792b6e96c1d5d291", size = 343685, upload-time = "2025-12-01T17:29:36.677Z" }, - { url = "https://files.pythonhosted.org/packages/1a/19/8c4b1d9f450159733b8be421a4e1fb03533709b80ed3546800102d085572/uuid_utils-0.12.0-cp39-abi3-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4c6a24148926bd0ca63e8a2dabf4cc9dc329a62325b3ad6578ecd60fbf926506", size = 366482, upload-time = "2025-12-01T17:29:37.979Z" }, - { url = "https://files.pythonhosted.org/packages/82/43/c79a6e45687647f80a159c8ba34346f287b065452cc419d07d2212d38420/uuid_utils-0.12.0-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:64a91e632669f059ef605f1771d28490b1d310c26198e46f754e8846dddf12f4", size = 523132, upload-time = "2025-12-01T17:29:39.293Z" }, - { url = "https://files.pythonhosted.org/packages/5a/a2/b2d75a621260a40c438aa88593827dfea596d18316520a99e839f7a5fb9d/uuid_utils-0.12.0-cp39-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:93c082212470bb4603ca3975916c205a9d7ef1443c0acde8fbd1e0f5b36673c7", size = 614218, upload-time = "2025-12-01T17:29:40.315Z" }, - { url = "https://files.pythonhosted.org/packages/13/6b/ba071101626edd5a6dabf8525c9a1537ff3d885dbc210540574a03901fef/uuid_utils-0.12.0-cp39-abi3-musllinux_1_2_i686.whl", hash = "sha256:431b1fb7283ba974811b22abd365f2726f8f821ab33f0f715be389640e18d039", size = 546241, upload-time = "2025-12-01T17:29:41.656Z" }, - { url = "https://files.pythonhosted.org/packages/01/12/9a942b81c0923268e6d85bf98d8f0a61fcbcd5e432fef94fdf4ce2ef8748/uuid_utils-0.12.0-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:2ffd7838c40149100299fa37cbd8bab5ee382372e8e65a148002a37d380df7c8", size = 511842, upload-time = "2025-12-01T17:29:43.107Z" }, - { url = "https://files.pythonhosted.org/packages/a9/a7/c326f5163dd48b79368b87d8a05f5da4668dd228a3f5ca9d79d5fee2fc40/uuid_utils-0.12.0-cp39-abi3-win32.whl", hash = "sha256:487f17c0fee6cbc1d8b90fe811874174a9b1b5683bf2251549e302906a50fed3", size = 179088, upload-time = "2025-12-01T17:29:44.492Z" }, - { url = "https://files.pythonhosted.org/packages/38/92/41c8734dd97213ee1d5ae435cf4499705dc4f2751e3b957fd12376f61784/uuid_utils-0.12.0-cp39-abi3-win_amd64.whl", hash = "sha256:9598e7c9da40357ae8fffc5d6938b1a7017f09a1acbcc95e14af8c65d48c655a", size = 183003, upload-time = "2025-12-01T17:29:45.47Z" }, - { url = "https://files.pythonhosted.org/packages/c9/f9/52ab0359618987331a1f739af837d26168a4b16281c9c3ab46519940c628/uuid_utils-0.12.0-cp39-abi3-win_arm64.whl", hash = "sha256:c9bea7c5b2aa6f57937ebebeee4d4ef2baad10f86f1b97b58a3f6f34c14b4e84", size = 182975, upload-time = "2025-12-01T17:29:46.444Z" }, - { url = "https://files.pythonhosted.org/packages/ef/f7/6c55b7722cede3b424df02ed5cddb25c19543abda2f95fa4cfc34a892ae5/uuid_utils-0.12.0-pp311-pypy311_pp73-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:e2209d361f2996966ab7114f49919eb6aaeabc6041672abbbbf4fdbb8ec1acc0", size = 593065, upload-time = "2025-12-01T17:29:47.507Z" }, - { url = "https://files.pythonhosted.org/packages/b8/40/ce5fe8e9137dbd5570e0016c2584fca43ad81b11a1cef809a1a1b4952ab7/uuid_utils-0.12.0-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:d9636bcdbd6cfcad2b549c352b669412d0d1eb09be72044a2f13e498974863cd", size = 300047, upload-time = "2025-12-01T17:29:48.596Z" }, - { url = "https://files.pythonhosted.org/packages/fb/9b/31c5d0736d7b118f302c50214e581f40e904305d8872eb0f0c921d50e138/uuid_utils-0.12.0-pp311-pypy311_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8cd8543a3419251fb78e703ce3b15fdfafe1b7c542cf40caf0775e01db7e7674", size = 335165, upload-time = "2025-12-01T17:29:49.755Z" }, - { url = "https://files.pythonhosted.org/packages/f6/5c/d80b4d08691c9d7446d0ad58fd41503081a662cfd2c7640faf68c64d8098/uuid_utils-0.12.0-pp311-pypy311_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:e98db2d8977c052cb307ae1cb5cc37a21715e8d415dbc65863b039397495a013", size = 341437, upload-time = "2025-12-01T17:29:51.112Z" }, - { url = "https://files.pythonhosted.org/packages/f6/b3/9dccdc6f3c22f6ef5bd381ae559173f8a1ae185ae89ed1f39f499d9d8b02/uuid_utils-0.12.0-pp311-pypy311_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f8f2bdf5e4ffeb259ef6d15edae92aed60a1d6f07cbfab465d836f6b12b48da8", size = 469123, upload-time = "2025-12-01T17:29:52.389Z" }, - { url = "https://files.pythonhosted.org/packages/fd/90/6c35ef65fbc49f8189729839b793a4a74a7dd8c5aa5eb56caa93f8c97732/uuid_utils-0.12.0-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8c3ec53c0cb15e1835870c139317cc5ec06e35aa22843e3ed7d9c74f23f23898", size = 335892, upload-time = "2025-12-01T17:29:53.44Z" }, - { url = "https://files.pythonhosted.org/packages/6b/c7/e3f3ce05c5af2bf86a0938d22165affe635f4dcbfd5687b1dacc042d3e0e/uuid_utils-0.12.0-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:84e5c0eba209356f7f389946a3a47b2cc2effd711b3fc7c7f155ad9f7d45e8a3", size = 360693, upload-time = "2025-12-01T17:29:54.558Z" }, -] - -[[package]] -name = "wrapt" -version = "2.0.1" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/49/2a/6de8a50cb435b7f42c46126cf1a54b2aab81784e74c8595c8e025e8f36d3/wrapt-2.0.1.tar.gz", hash = "sha256:9c9c635e78497cacb81e84f8b11b23e0aacac7a136e73b8e5b2109a1d9fc468f", size = 82040, upload-time = "2025-11-07T00:45:33.312Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/61/0d/12d8c803ed2ce4e5e7d5b9f5f602721f9dfef82c95959f3ce97fa584bb5c/wrapt-2.0.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:64b103acdaa53b7caf409e8d45d39a8442fe6dcfec6ba3f3d141e0cc2b5b4dbd", size = 77481, upload-time = "2025-11-07T00:43:11.103Z" }, - { url = "https://files.pythonhosted.org/packages/05/3e/4364ebe221ebf2a44d9fc8695a19324692f7dd2795e64bd59090856ebf12/wrapt-2.0.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:91bcc576260a274b169c3098e9a3519fb01f2989f6d3d386ef9cbf8653de1374", size = 60692, upload-time = "2025-11-07T00:43:13.697Z" }, - { url = "https://files.pythonhosted.org/packages/1f/ff/ae2a210022b521f86a8ddcdd6058d137c051003812b0388a5e9a03d3fe10/wrapt-2.0.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:ab594f346517010050126fcd822697b25a7031d815bb4fbc238ccbe568216489", size = 61574, upload-time = "2025-11-07T00:43:14.967Z" }, - { url = "https://files.pythonhosted.org/packages/c6/93/5cf92edd99617095592af919cb81d4bff61c5dbbb70d3c92099425a8ec34/wrapt-2.0.1-cp310-cp310-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:36982b26f190f4d737f04a492a68accbfc6fa042c3f42326fdfbb6c5b7a20a31", size = 113688, upload-time = "2025-11-07T00:43:18.275Z" }, - { url = "https://files.pythonhosted.org/packages/a0/0a/e38fc0cee1f146c9fb266d8ef96ca39fb14a9eef165383004019aa53f88a/wrapt-2.0.1-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:23097ed8bc4c93b7bf36fa2113c6c733c976316ce0ee2c816f64ca06102034ef", size = 115698, upload-time = "2025-11-07T00:43:19.407Z" }, - { url = "https://files.pythonhosted.org/packages/b0/85/bef44ea018b3925fb0bcbe9112715f665e4d5309bd945191da814c314fd1/wrapt-2.0.1-cp310-cp310-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:8bacfe6e001749a3b64db47bcf0341da757c95959f592823a93931a422395013", size = 112096, upload-time = "2025-11-07T00:43:16.5Z" }, - { url = "https://files.pythonhosted.org/packages/7c/0b/733a2376e413117e497aa1a5b1b78e8f3a28c0e9537d26569f67d724c7c5/wrapt-2.0.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:8ec3303e8a81932171f455f792f8df500fc1a09f20069e5c16bd7049ab4e8e38", size = 114878, upload-time = "2025-11-07T00:43:20.81Z" }, - { url = "https://files.pythonhosted.org/packages/da/03/d81dcb21bbf678fcda656495792b059f9d56677d119ca022169a12542bd0/wrapt-2.0.1-cp310-cp310-musllinux_1_2_riscv64.whl", hash = "sha256:3f373a4ab5dbc528a94334f9fe444395b23c2f5332adab9ff4ea82f5a9e33bc1", size = 111298, upload-time = "2025-11-07T00:43:22.229Z" }, - { url = "https://files.pythonhosted.org/packages/c9/d5/5e623040e8056e1108b787020d56b9be93dbbf083bf2324d42cde80f3a19/wrapt-2.0.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:f49027b0b9503bf6c8cdc297ca55006b80c2f5dd36cecc72c6835ab6e10e8a25", size = 113361, upload-time = "2025-11-07T00:43:24.301Z" }, - { url = "https://files.pythonhosted.org/packages/a1/f3/de535ccecede6960e28c7b722e5744846258111d6c9f071aa7578ea37ad3/wrapt-2.0.1-cp310-cp310-win32.whl", hash = "sha256:8330b42d769965e96e01fa14034b28a2a7600fbf7e8f0cc90ebb36d492c993e4", size = 58035, upload-time = "2025-11-07T00:43:28.96Z" }, - { url = "https://files.pythonhosted.org/packages/21/15/39d3ca5428a70032c2ec8b1f1c9d24c32e497e7ed81aed887a4998905fcc/wrapt-2.0.1-cp310-cp310-win_amd64.whl", hash = "sha256:1218573502a8235bb8a7ecaed12736213b22dcde9feab115fa2989d42b5ded45", size = 60383, upload-time = "2025-11-07T00:43:25.804Z" }, - { url = "https://files.pythonhosted.org/packages/43/c2/dfd23754b7f7a4dce07e08f4309c4e10a40046a83e9ae1800f2e6b18d7c1/wrapt-2.0.1-cp310-cp310-win_arm64.whl", hash = "sha256:eda8e4ecd662d48c28bb86be9e837c13e45c58b8300e43ba3c9b4fa9900302f7", size = 58894, upload-time = "2025-11-07T00:43:27.074Z" }, - { url = "https://files.pythonhosted.org/packages/98/60/553997acf3939079dab022e37b67b1904b5b0cc235503226898ba573b10c/wrapt-2.0.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:0e17283f533a0d24d6e5429a7d11f250a58d28b4ae5186f8f47853e3e70d2590", size = 77480, upload-time = "2025-11-07T00:43:30.573Z" }, - { url = "https://files.pythonhosted.org/packages/2d/50/e5b3d30895d77c52105c6d5cbf94d5b38e2a3dd4a53d22d246670da98f7c/wrapt-2.0.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:85df8d92158cb8f3965aecc27cf821461bb5f40b450b03facc5d9f0d4d6ddec6", size = 60690, upload-time = "2025-11-07T00:43:31.594Z" }, - { url = "https://files.pythonhosted.org/packages/f0/40/660b2898703e5cbbb43db10cdefcc294274458c3ca4c68637c2b99371507/wrapt-2.0.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c1be685ac7700c966b8610ccc63c3187a72e33cab53526a27b2a285a662cd4f7", size = 61578, upload-time = "2025-11-07T00:43:32.918Z" }, - { url = "https://files.pythonhosted.org/packages/5b/36/825b44c8a10556957bc0c1d84c7b29a40e05fcf1873b6c40aa9dbe0bd972/wrapt-2.0.1-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:df0b6d3b95932809c5b3fecc18fda0f1e07452d05e2662a0b35548985f256e28", size = 114115, upload-time = "2025-11-07T00:43:35.605Z" }, - { url = "https://files.pythonhosted.org/packages/83/73/0a5d14bb1599677304d3c613a55457d34c344e9b60eda8a737c2ead7619e/wrapt-2.0.1-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4da7384b0e5d4cae05c97cd6f94faaf78cc8b0f791fc63af43436d98c4ab37bb", size = 116157, upload-time = "2025-11-07T00:43:37.058Z" }, - { url = "https://files.pythonhosted.org/packages/01/22/1c158fe763dbf0a119f985d945711d288994fe5514c0646ebe0eb18b016d/wrapt-2.0.1-cp311-cp311-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:ec65a78fbd9d6f083a15d7613b2800d5663dbb6bb96003899c834beaa68b242c", size = 112535, upload-time = "2025-11-07T00:43:34.138Z" }, - { url = "https://files.pythonhosted.org/packages/5c/28/4f16861af67d6de4eae9927799b559c20ebdd4fe432e89ea7fe6fcd9d709/wrapt-2.0.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:7de3cc939be0e1174969f943f3b44e0d79b6f9a82198133a5b7fc6cc92882f16", size = 115404, upload-time = "2025-11-07T00:43:39.214Z" }, - { url = "https://files.pythonhosted.org/packages/a0/8b/7960122e625fad908f189b59c4aae2d50916eb4098b0fb2819c5a177414f/wrapt-2.0.1-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:fb1a5b72cbd751813adc02ef01ada0b0d05d3dcbc32976ce189a1279d80ad4a2", size = 111802, upload-time = "2025-11-07T00:43:40.476Z" }, - { url = "https://files.pythonhosted.org/packages/3e/73/7881eee5ac31132a713ab19a22c9e5f1f7365c8b1df50abba5d45b781312/wrapt-2.0.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:3fa272ca34332581e00bf7773e993d4f632594eb2d1b0b162a9038df0fd971dd", size = 113837, upload-time = "2025-11-07T00:43:42.921Z" }, - { url = "https://files.pythonhosted.org/packages/45/00/9499a3d14e636d1f7089339f96c4409bbc7544d0889f12264efa25502ae8/wrapt-2.0.1-cp311-cp311-win32.whl", hash = "sha256:fc007fdf480c77301ab1afdbb6ab22a5deee8885f3b1ed7afcb7e5e84a0e27be", size = 58028, upload-time = "2025-11-07T00:43:47.369Z" }, - { url = "https://files.pythonhosted.org/packages/70/5d/8f3d7eea52f22638748f74b102e38fdf88cb57d08ddeb7827c476a20b01b/wrapt-2.0.1-cp311-cp311-win_amd64.whl", hash = "sha256:47434236c396d04875180171ee1f3815ca1eada05e24a1ee99546320d54d1d1b", size = 60385, upload-time = "2025-11-07T00:43:44.34Z" }, - { url = "https://files.pythonhosted.org/packages/14/e2/32195e57a8209003587bbbad44d5922f13e0ced2a493bb46ca882c5b123d/wrapt-2.0.1-cp311-cp311-win_arm64.whl", hash = "sha256:837e31620e06b16030b1d126ed78e9383815cbac914693f54926d816d35d8edf", size = 58893, upload-time = "2025-11-07T00:43:46.161Z" }, - { url = "https://files.pythonhosted.org/packages/cb/73/8cb252858dc8254baa0ce58ce382858e3a1cf616acebc497cb13374c95c6/wrapt-2.0.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:1fdbb34da15450f2b1d735a0e969c24bdb8d8924892380126e2a293d9902078c", size = 78129, upload-time = "2025-11-07T00:43:48.852Z" }, - { url = "https://files.pythonhosted.org/packages/19/42/44a0db2108526ee6e17a5ab72478061158f34b08b793df251d9fbb9a7eb4/wrapt-2.0.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:3d32794fe940b7000f0519904e247f902f0149edbe6316c710a8562fb6738841", size = 61205, upload-time = "2025-11-07T00:43:50.402Z" }, - { url = "https://files.pythonhosted.org/packages/4d/8a/5b4b1e44b791c22046e90d9b175f9a7581a8cc7a0debbb930f81e6ae8e25/wrapt-2.0.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:386fb54d9cd903ee0012c09291336469eb7b244f7183d40dc3e86a16a4bace62", size = 61692, upload-time = "2025-11-07T00:43:51.678Z" }, - { url = "https://files.pythonhosted.org/packages/11/53/3e794346c39f462bcf1f58ac0487ff9bdad02f9b6d5ee2dc84c72e0243b2/wrapt-2.0.1-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:7b219cb2182f230676308cdcacd428fa837987b89e4b7c5c9025088b8a6c9faf", size = 121492, upload-time = "2025-11-07T00:43:55.017Z" }, - { url = "https://files.pythonhosted.org/packages/c6/7e/10b7b0e8841e684c8ca76b462a9091c45d62e8f2de9c4b1390b690eadf16/wrapt-2.0.1-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:641e94e789b5f6b4822bb8d8ebbdfc10f4e4eae7756d648b717d980f657a9eb9", size = 123064, upload-time = "2025-11-07T00:43:56.323Z" }, - { url = "https://files.pythonhosted.org/packages/0e/d1/3c1e4321fc2f5ee7fd866b2d822aa89b84495f28676fd976c47327c5b6aa/wrapt-2.0.1-cp312-cp312-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:fe21b118b9f58859b5ebaa4b130dee18669df4bd111daad082b7beb8799ad16b", size = 117403, upload-time = "2025-11-07T00:43:53.258Z" }, - { url = "https://files.pythonhosted.org/packages/a4/b0/d2f0a413cf201c8c2466de08414a15420a25aa83f53e647b7255cc2fab5d/wrapt-2.0.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:17fb85fa4abc26a5184d93b3efd2dcc14deb4b09edcdb3535a536ad34f0b4dba", size = 121500, upload-time = "2025-11-07T00:43:57.468Z" }, - { url = "https://files.pythonhosted.org/packages/bd/45/bddb11d28ca39970a41ed48a26d210505120f925918592283369219f83cc/wrapt-2.0.1-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:b89ef9223d665ab255ae42cc282d27d69704d94be0deffc8b9d919179a609684", size = 116299, upload-time = "2025-11-07T00:43:58.877Z" }, - { url = "https://files.pythonhosted.org/packages/81/af/34ba6dd570ef7a534e7eec0c25e2615c355602c52aba59413411c025a0cb/wrapt-2.0.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:a453257f19c31b31ba593c30d997d6e5be39e3b5ad9148c2af5a7314061c63eb", size = 120622, upload-time = "2025-11-07T00:43:59.962Z" }, - { url = "https://files.pythonhosted.org/packages/e2/3e/693a13b4146646fb03254636f8bafd20c621955d27d65b15de07ab886187/wrapt-2.0.1-cp312-cp312-win32.whl", hash = "sha256:3e271346f01e9c8b1130a6a3b0e11908049fe5be2d365a5f402778049147e7e9", size = 58246, upload-time = "2025-11-07T00:44:03.169Z" }, - { url = "https://files.pythonhosted.org/packages/a7/36/715ec5076f925a6be95f37917b66ebbeaa1372d1862c2ccd7a751574b068/wrapt-2.0.1-cp312-cp312-win_amd64.whl", hash = "sha256:2da620b31a90cdefa9cd0c2b661882329e2e19d1d7b9b920189956b76c564d75", size = 60492, upload-time = "2025-11-07T00:44:01.027Z" }, - { url = "https://files.pythonhosted.org/packages/ef/3e/62451cd7d80f65cc125f2b426b25fbb6c514bf6f7011a0c3904fc8c8df90/wrapt-2.0.1-cp312-cp312-win_arm64.whl", hash = "sha256:aea9c7224c302bc8bfc892b908537f56c430802560e827b75ecbde81b604598b", size = 58987, upload-time = "2025-11-07T00:44:02.095Z" }, - { url = "https://files.pythonhosted.org/packages/ad/fe/41af4c46b5e498c90fc87981ab2972fbd9f0bccda597adb99d3d3441b94b/wrapt-2.0.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:47b0f8bafe90f7736151f61482c583c86b0693d80f075a58701dd1549b0010a9", size = 78132, upload-time = "2025-11-07T00:44:04.628Z" }, - { url = "https://files.pythonhosted.org/packages/1c/92/d68895a984a5ebbbfb175512b0c0aad872354a4a2484fbd5552e9f275316/wrapt-2.0.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:cbeb0971e13b4bd81d34169ed57a6dda017328d1a22b62fda45e1d21dd06148f", size = 61211, upload-time = "2025-11-07T00:44:05.626Z" }, - { url = "https://files.pythonhosted.org/packages/e8/26/ba83dc5ae7cf5aa2b02364a3d9cf74374b86169906a1f3ade9a2d03cf21c/wrapt-2.0.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:eb7cffe572ad0a141a7886a1d2efa5bef0bf7fe021deeea76b3ab334d2c38218", size = 61689, upload-time = "2025-11-07T00:44:06.719Z" }, - { url = "https://files.pythonhosted.org/packages/cf/67/d7a7c276d874e5d26738c22444d466a3a64ed541f6ef35f740dbd865bab4/wrapt-2.0.1-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:c8d60527d1ecfc131426b10d93ab5d53e08a09c5fa0175f6b21b3252080c70a9", size = 121502, upload-time = "2025-11-07T00:44:09.557Z" }, - { url = "https://files.pythonhosted.org/packages/0f/6b/806dbf6dd9579556aab22fc92908a876636e250f063f71548a8660382184/wrapt-2.0.1-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c654eafb01afac55246053d67a4b9a984a3567c3808bb7df2f8de1c1caba2e1c", size = 123110, upload-time = "2025-11-07T00:44:10.64Z" }, - { url = "https://files.pythonhosted.org/packages/e5/08/cdbb965fbe4c02c5233d185d070cabed2ecc1f1e47662854f95d77613f57/wrapt-2.0.1-cp313-cp313-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:98d873ed6c8b4ee2418f7afce666751854d6d03e3c0ec2a399bb039cd2ae89db", size = 117434, upload-time = "2025-11-07T00:44:08.138Z" }, - { url = "https://files.pythonhosted.org/packages/2d/d1/6aae2ce39db4cb5216302fa2e9577ad74424dfbe315bd6669725569e048c/wrapt-2.0.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:c9e850f5b7fc67af856ff054c71690d54fa940c3ef74209ad9f935b4f66a0233", size = 121533, upload-time = "2025-11-07T00:44:12.142Z" }, - { url = "https://files.pythonhosted.org/packages/79/35/565abf57559fbe0a9155c29879ff43ce8bd28d2ca61033a3a3dd67b70794/wrapt-2.0.1-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:e505629359cb5f751e16e30cf3f91a1d3ddb4552480c205947da415d597f7ac2", size = 116324, upload-time = "2025-11-07T00:44:13.28Z" }, - { url = "https://files.pythonhosted.org/packages/e1/e0/53ff5e76587822ee33e560ad55876d858e384158272cd9947abdd4ad42ca/wrapt-2.0.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:2879af909312d0baf35f08edeea918ee3af7ab57c37fe47cb6a373c9f2749c7b", size = 120627, upload-time = "2025-11-07T00:44:14.431Z" }, - { url = "https://files.pythonhosted.org/packages/7c/7b/38df30fd629fbd7612c407643c63e80e1c60bcc982e30ceeae163a9800e7/wrapt-2.0.1-cp313-cp313-win32.whl", hash = "sha256:d67956c676be5a24102c7407a71f4126d30de2a569a1c7871c9f3cabc94225d7", size = 58252, upload-time = "2025-11-07T00:44:17.814Z" }, - { url = "https://files.pythonhosted.org/packages/85/64/d3954e836ea67c4d3ad5285e5c8fd9d362fd0a189a2db622df457b0f4f6a/wrapt-2.0.1-cp313-cp313-win_amd64.whl", hash = "sha256:9ca66b38dd642bf90c59b6738af8070747b610115a39af2498535f62b5cdc1c3", size = 60500, upload-time = "2025-11-07T00:44:15.561Z" }, - { url = "https://files.pythonhosted.org/packages/89/4e/3c8b99ac93527cfab7f116089db120fef16aac96e5f6cdb724ddf286086d/wrapt-2.0.1-cp313-cp313-win_arm64.whl", hash = "sha256:5a4939eae35db6b6cec8e7aa0e833dcca0acad8231672c26c2a9ab7a0f8ac9c8", size = 58993, upload-time = "2025-11-07T00:44:16.65Z" }, - { url = "https://files.pythonhosted.org/packages/f9/f4/eff2b7d711cae20d220780b9300faa05558660afb93f2ff5db61fe725b9a/wrapt-2.0.1-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:a52f93d95c8d38fed0669da2ebdb0b0376e895d84596a976c15a9eb45e3eccb3", size = 82028, upload-time = "2025-11-07T00:44:18.944Z" }, - { url = "https://files.pythonhosted.org/packages/0c/67/cb945563f66fd0f61a999339460d950f4735c69f18f0a87ca586319b1778/wrapt-2.0.1-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:4e54bbf554ee29fcceee24fa41c4d091398b911da6e7f5d7bffda963c9aed2e1", size = 62949, upload-time = "2025-11-07T00:44:20.074Z" }, - { url = "https://files.pythonhosted.org/packages/ec/ca/f63e177f0bbe1e5cf5e8d9b74a286537cd709724384ff20860f8f6065904/wrapt-2.0.1-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:908f8c6c71557f4deaa280f55d0728c3bca0960e8c3dd5ceeeafb3c19942719d", size = 63681, upload-time = "2025-11-07T00:44:21.345Z" }, - { url = "https://files.pythonhosted.org/packages/39/a1/1b88fcd21fd835dca48b556daef750952e917a2794fa20c025489e2e1f0f/wrapt-2.0.1-cp313-cp313t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:e2f84e9af2060e3904a32cea9bb6db23ce3f91cfd90c6b426757cf7cc01c45c7", size = 152696, upload-time = "2025-11-07T00:44:24.318Z" }, - { url = "https://files.pythonhosted.org/packages/62/1c/d9185500c1960d9f5f77b9c0b890b7fc62282b53af7ad1b6bd779157f714/wrapt-2.0.1-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e3612dc06b436968dfb9142c62e5dfa9eb5924f91120b3c8ff501ad878f90eb3", size = 158859, upload-time = "2025-11-07T00:44:25.494Z" }, - { url = "https://files.pythonhosted.org/packages/91/60/5d796ed0f481ec003220c7878a1d6894652efe089853a208ea0838c13086/wrapt-2.0.1-cp313-cp313t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:6d2d947d266d99a1477cd005b23cbd09465276e302515e122df56bb9511aca1b", size = 146068, upload-time = "2025-11-07T00:44:22.81Z" }, - { url = "https://files.pythonhosted.org/packages/04/f8/75282dd72f102ddbfba137e1e15ecba47b40acff32c08ae97edbf53f469e/wrapt-2.0.1-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:7d539241e87b650cbc4c3ac9f32c8d1ac8a54e510f6dca3f6ab60dcfd48c9b10", size = 155724, upload-time = "2025-11-07T00:44:26.634Z" }, - { url = "https://files.pythonhosted.org/packages/5a/27/fe39c51d1b344caebb4a6a9372157bdb8d25b194b3561b52c8ffc40ac7d1/wrapt-2.0.1-cp313-cp313t-musllinux_1_2_riscv64.whl", hash = "sha256:4811e15d88ee62dbf5c77f2c3ff3932b1e3ac92323ba3912f51fc4016ce81ecf", size = 144413, upload-time = "2025-11-07T00:44:27.939Z" }, - { url = "https://files.pythonhosted.org/packages/83/2b/9f6b643fe39d4505c7bf926d7c2595b7cb4b607c8c6b500e56c6b36ac238/wrapt-2.0.1-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:c1c91405fcf1d501fa5d55df21e58ea49e6b879ae829f1039faaf7e5e509b41e", size = 150325, upload-time = "2025-11-07T00:44:29.29Z" }, - { url = "https://files.pythonhosted.org/packages/bb/b6/20ffcf2558596a7f58a2e69c89597128781f0b88e124bf5a4cadc05b8139/wrapt-2.0.1-cp313-cp313t-win32.whl", hash = "sha256:e76e3f91f864e89db8b8d2a8311d57df93f01ad6bb1e9b9976d1f2e83e18315c", size = 59943, upload-time = "2025-11-07T00:44:33.211Z" }, - { url = "https://files.pythonhosted.org/packages/87/6a/0e56111cbb3320151eed5d3821ee1373be13e05b376ea0870711f18810c3/wrapt-2.0.1-cp313-cp313t-win_amd64.whl", hash = "sha256:83ce30937f0ba0d28818807b303a412440c4b63e39d3d8fc036a94764b728c92", size = 63240, upload-time = "2025-11-07T00:44:30.935Z" }, - { url = "https://files.pythonhosted.org/packages/1d/54/5ab4c53ea1f7f7e5c3e7c1095db92932cc32fd62359d285486d00c2884c3/wrapt-2.0.1-cp313-cp313t-win_arm64.whl", hash = "sha256:4b55cacc57e1dc2d0991dbe74c6419ffd415fb66474a02335cb10efd1aa3f84f", size = 60416, upload-time = "2025-11-07T00:44:32.002Z" }, - { url = "https://files.pythonhosted.org/packages/73/81/d08d83c102709258e7730d3cd25befd114c60e43ef3891d7e6877971c514/wrapt-2.0.1-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:5e53b428f65ece6d9dad23cb87e64506392b720a0b45076c05354d27a13351a1", size = 78290, upload-time = "2025-11-07T00:44:34.691Z" }, - { url = "https://files.pythonhosted.org/packages/f6/14/393afba2abb65677f313aa680ff0981e829626fed39b6a7e3ec807487790/wrapt-2.0.1-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:ad3ee9d0f254851c71780966eb417ef8e72117155cff04821ab9b60549694a55", size = 61255, upload-time = "2025-11-07T00:44:35.762Z" }, - { url = "https://files.pythonhosted.org/packages/c4/10/a4a1f2fba205a9462e36e708ba37e5ac95f4987a0f1f8fd23f0bf1fc3b0f/wrapt-2.0.1-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:d7b822c61ed04ee6ad64bc90d13368ad6eb094db54883b5dde2182f67a7f22c0", size = 61797, upload-time = "2025-11-07T00:44:37.22Z" }, - { url = "https://files.pythonhosted.org/packages/12/db/99ba5c37cf1c4fad35349174f1e38bd8d992340afc1ff27f526729b98986/wrapt-2.0.1-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:7164a55f5e83a9a0b031d3ffab4d4e36bbec42e7025db560f225489fa929e509", size = 120470, upload-time = "2025-11-07T00:44:39.425Z" }, - { url = "https://files.pythonhosted.org/packages/30/3f/a1c8d2411eb826d695fc3395a431757331582907a0ec59afce8fe8712473/wrapt-2.0.1-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e60690ba71a57424c8d9ff28f8d006b7ad7772c22a4af432188572cd7fa004a1", size = 122851, upload-time = "2025-11-07T00:44:40.582Z" }, - { url = "https://files.pythonhosted.org/packages/b3/8d/72c74a63f201768d6a04a8845c7976f86be6f5ff4d74996c272cefc8dafc/wrapt-2.0.1-cp314-cp314-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:3cd1a4bd9a7a619922a8557e1318232e7269b5fb69d4ba97b04d20450a6bf970", size = 117433, upload-time = "2025-11-07T00:44:38.313Z" }, - { url = "https://files.pythonhosted.org/packages/c7/5a/df37cf4042cb13b08256f8e27023e2f9b3d471d553376616591bb99bcb31/wrapt-2.0.1-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:b4c2e3d777e38e913b8ce3a6257af72fb608f86a1df471cb1d4339755d0a807c", size = 121280, upload-time = "2025-11-07T00:44:41.69Z" }, - { url = "https://files.pythonhosted.org/packages/54/34/40d6bc89349f9931e1186ceb3e5fbd61d307fef814f09fbbac98ada6a0c8/wrapt-2.0.1-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:3d366aa598d69416b5afedf1faa539fac40c1d80a42f6b236c88c73a3c8f2d41", size = 116343, upload-time = "2025-11-07T00:44:43.013Z" }, - { url = "https://files.pythonhosted.org/packages/70/66/81c3461adece09d20781dee17c2366fdf0cb8754738b521d221ca056d596/wrapt-2.0.1-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:c235095d6d090aa903f1db61f892fffb779c1eaeb2a50e566b52001f7a0f66ed", size = 119650, upload-time = "2025-11-07T00:44:44.523Z" }, - { url = "https://files.pythonhosted.org/packages/46/3a/d0146db8be8761a9e388cc9cc1c312b36d583950ec91696f19bbbb44af5a/wrapt-2.0.1-cp314-cp314-win32.whl", hash = "sha256:bfb5539005259f8127ea9c885bdc231978c06b7a980e63a8a61c8c4c979719d0", size = 58701, upload-time = "2025-11-07T00:44:48.277Z" }, - { url = "https://files.pythonhosted.org/packages/1a/38/5359da9af7d64554be63e9046164bd4d8ff289a2dd365677d25ba3342c08/wrapt-2.0.1-cp314-cp314-win_amd64.whl", hash = "sha256:4ae879acc449caa9ed43fc36ba08392b9412ee67941748d31d94e3cedb36628c", size = 60947, upload-time = "2025-11-07T00:44:46.086Z" }, - { url = "https://files.pythonhosted.org/packages/aa/3f/96db0619276a833842bf36343685fa04f987dd6e3037f314531a1e00492b/wrapt-2.0.1-cp314-cp314-win_arm64.whl", hash = "sha256:8639b843c9efd84675f1e100ed9e99538ebea7297b62c4b45a7042edb84db03e", size = 59359, upload-time = "2025-11-07T00:44:47.164Z" }, - { url = "https://files.pythonhosted.org/packages/71/49/5f5d1e867bf2064bf3933bc6cf36ade23505f3902390e175e392173d36a2/wrapt-2.0.1-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:9219a1d946a9b32bb23ccae66bdb61e35c62773ce7ca6509ceea70f344656b7b", size = 82031, upload-time = "2025-11-07T00:44:49.4Z" }, - { url = "https://files.pythonhosted.org/packages/2b/89/0009a218d88db66ceb83921e5685e820e2c61b59bbbb1324ba65342668bc/wrapt-2.0.1-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:fa4184e74197af3adad3c889a1af95b53bb0466bced92ea99a0c014e48323eec", size = 62952, upload-time = "2025-11-07T00:44:50.74Z" }, - { url = "https://files.pythonhosted.org/packages/ae/18/9b968e920dd05d6e44bcc918a046d02afea0fb31b2f1c80ee4020f377cbe/wrapt-2.0.1-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:c5ef2f2b8a53b7caee2f797ef166a390fef73979b15778a4a153e4b5fedce8fa", size = 63688, upload-time = "2025-11-07T00:44:52.248Z" }, - { url = "https://files.pythonhosted.org/packages/a6/7d/78bdcb75826725885d9ea26c49a03071b10c4c92da93edda612910f150e4/wrapt-2.0.1-cp314-cp314t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:e042d653a4745be832d5aa190ff80ee4f02c34b21f4b785745eceacd0907b815", size = 152706, upload-time = "2025-11-07T00:44:54.613Z" }, - { url = "https://files.pythonhosted.org/packages/dd/77/cac1d46f47d32084a703df0d2d29d47e7eb2a7d19fa5cbca0e529ef57659/wrapt-2.0.1-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:2afa23318136709c4b23d87d543b425c399887b4057936cd20386d5b1422b6fa", size = 158866, upload-time = "2025-11-07T00:44:55.79Z" }, - { url = "https://files.pythonhosted.org/packages/8a/11/b521406daa2421508903bf8d5e8b929216ec2af04839db31c0a2c525eee0/wrapt-2.0.1-cp314-cp314t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:6c72328f668cf4c503ffcf9434c2b71fdd624345ced7941bc6693e61bbe36bef", size = 146148, upload-time = "2025-11-07T00:44:53.388Z" }, - { url = "https://files.pythonhosted.org/packages/0c/c0/340b272bed297baa7c9ce0c98ef7017d9c035a17a6a71dce3184b8382da2/wrapt-2.0.1-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:3793ac154afb0e5b45d1233cb94d354ef7a983708cc3bb12563853b1d8d53747", size = 155737, upload-time = "2025-11-07T00:44:56.971Z" }, - { url = "https://files.pythonhosted.org/packages/f3/93/bfcb1fb2bdf186e9c2883a4d1ab45ab099c79cbf8f4e70ea453811fa3ea7/wrapt-2.0.1-cp314-cp314t-musllinux_1_2_riscv64.whl", hash = "sha256:fec0d993ecba3991645b4857837277469c8cc4c554a7e24d064d1ca291cfb81f", size = 144451, upload-time = "2025-11-07T00:44:58.515Z" }, - { url = "https://files.pythonhosted.org/packages/d2/6b/dca504fb18d971139d232652656180e3bd57120e1193d9a5899c3c0b7cdd/wrapt-2.0.1-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:949520bccc1fa227274da7d03bf238be15389cd94e32e4297b92337df9b7a349", size = 150353, upload-time = "2025-11-07T00:44:59.753Z" }, - { url = "https://files.pythonhosted.org/packages/1d/f6/a1de4bd3653afdf91d250ca5c721ee51195df2b61a4603d4b373aa804d1d/wrapt-2.0.1-cp314-cp314t-win32.whl", hash = "sha256:be9e84e91d6497ba62594158d3d31ec0486c60055c49179edc51ee43d095f79c", size = 60609, upload-time = "2025-11-07T00:45:03.315Z" }, - { url = "https://files.pythonhosted.org/packages/01/3a/07cd60a9d26fe73efead61c7830af975dfdba8537632d410462672e4432b/wrapt-2.0.1-cp314-cp314t-win_amd64.whl", hash = "sha256:61c4956171c7434634401db448371277d07032a81cc21c599c22953374781395", size = 64038, upload-time = "2025-11-07T00:45:00.948Z" }, - { url = "https://files.pythonhosted.org/packages/41/99/8a06b8e17dddbf321325ae4eb12465804120f699cd1b8a355718300c62da/wrapt-2.0.1-cp314-cp314t-win_arm64.whl", hash = "sha256:35cdbd478607036fee40273be8ed54a451f5f23121bd9d4be515158f9498f7ad", size = 60634, upload-time = "2025-11-07T00:45:02.087Z" }, - { url = "https://files.pythonhosted.org/packages/15/d1/b51471c11592ff9c012bd3e2f7334a6ff2f42a7aed2caffcf0bdddc9cb89/wrapt-2.0.1-py3-none-any.whl", hash = "sha256:4d2ce1bf1a48c5277d7969259232b57645aae5686dba1eaeade39442277afbca", size = 44046, upload-time = "2025-11-07T00:45:32.116Z" }, -] - -[[package]] -name = "zstandard" -version = "0.25.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/fd/aa/3e0508d5a5dd96529cdc5a97011299056e14c6505b678fd58938792794b1/zstandard-0.25.0.tar.gz", hash = "sha256:7713e1179d162cf5c7906da876ec2ccb9c3a9dcbdffef0cc7f70c3667a205f0b", size = 711513, upload-time = "2025-09-14T22:15:54.002Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/56/7a/28efd1d371f1acd037ac64ed1c5e2b41514a6cc937dd6ab6a13ab9f0702f/zstandard-0.25.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e59fdc271772f6686e01e1b3b74537259800f57e24280be3f29c8a0deb1904dd", size = 795256, upload-time = "2025-09-14T22:15:56.415Z" }, - { url = "https://files.pythonhosted.org/packages/96/34/ef34ef77f1ee38fc8e4f9775217a613b452916e633c4f1d98f31db52c4a5/zstandard-0.25.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4d441506e9b372386a5271c64125f72d5df6d2a8e8a2a45a0ae09b03cb781ef7", size = 640565, upload-time = "2025-09-14T22:15:58.177Z" }, - { url = "https://files.pythonhosted.org/packages/9d/1b/4fdb2c12eb58f31f28c4d28e8dc36611dd7205df8452e63f52fb6261d13e/zstandard-0.25.0-cp310-cp310-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:ab85470ab54c2cb96e176f40342d9ed41e58ca5733be6a893b730e7af9c40550", size = 5345306, upload-time = "2025-09-14T22:16:00.165Z" }, - { url = "https://files.pythonhosted.org/packages/73/28/a44bdece01bca027b079f0e00be3b6bd89a4df180071da59a3dd7381665b/zstandard-0.25.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:e05ab82ea7753354bb054b92e2f288afb750e6b439ff6ca78af52939ebbc476d", size = 5055561, upload-time = "2025-09-14T22:16:02.22Z" }, - { url = "https://files.pythonhosted.org/packages/e9/74/68341185a4f32b274e0fc3410d5ad0750497e1acc20bd0f5b5f64ce17785/zstandard-0.25.0-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:78228d8a6a1c177a96b94f7e2e8d012c55f9c760761980da16ae7546a15a8e9b", size = 5402214, upload-time = "2025-09-14T22:16:04.109Z" }, - { url = "https://files.pythonhosted.org/packages/8b/67/f92e64e748fd6aaffe01e2b75a083c0c4fd27abe1c8747fee4555fcee7dd/zstandard-0.25.0-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:2b6bd67528ee8b5c5f10255735abc21aa106931f0dbaf297c7be0c886353c3d0", size = 5449703, upload-time = "2025-09-14T22:16:06.312Z" }, - { url = "https://files.pythonhosted.org/packages/fd/e5/6d36f92a197c3c17729a2125e29c169f460538a7d939a27eaaa6dcfcba8e/zstandard-0.25.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4b6d83057e713ff235a12e73916b6d356e3084fd3d14ced499d84240f3eecee0", size = 5556583, upload-time = "2025-09-14T22:16:08.457Z" }, - { url = "https://files.pythonhosted.org/packages/d7/83/41939e60d8d7ebfe2b747be022d0806953799140a702b90ffe214d557638/zstandard-0.25.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:9174f4ed06f790a6869b41cba05b43eeb9a35f8993c4422ab853b705e8112bbd", size = 5045332, upload-time = "2025-09-14T22:16:10.444Z" }, - { url = "https://files.pythonhosted.org/packages/b3/87/d3ee185e3d1aa0133399893697ae91f221fda79deb61adbe998a7235c43f/zstandard-0.25.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:25f8f3cd45087d089aef5ba3848cd9efe3ad41163d3400862fb42f81a3a46701", size = 5572283, upload-time = "2025-09-14T22:16:12.128Z" }, - { url = "https://files.pythonhosted.org/packages/0a/1d/58635ae6104df96671076ac7d4ae7816838ce7debd94aecf83e30b7121b0/zstandard-0.25.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:3756b3e9da9b83da1796f8809dd57cb024f838b9eeafde28f3cb472012797ac1", size = 4959754, upload-time = "2025-09-14T22:16:14.225Z" }, - { url = "https://files.pythonhosted.org/packages/75/d6/57e9cb0a9983e9a229dd8fd2e6e96593ef2aa82a3907188436f22b111ccd/zstandard-0.25.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:81dad8d145d8fd981b2962b686b2241d3a1ea07733e76a2f15435dfb7fb60150", size = 5266477, upload-time = "2025-09-14T22:16:16.343Z" }, - { url = "https://files.pythonhosted.org/packages/d1/a9/ee891e5edf33a6ebce0a028726f0bbd8567effe20fe3d5808c42323e8542/zstandard-0.25.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:a5a419712cf88862a45a23def0ae063686db3d324cec7edbe40509d1a79a0aab", size = 5440914, upload-time = "2025-09-14T22:16:18.453Z" }, - { url = "https://files.pythonhosted.org/packages/58/08/a8522c28c08031a9521f27abc6f78dbdee7312a7463dd2cfc658b813323b/zstandard-0.25.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:e7360eae90809efd19b886e59a09dad07da4ca9ba096752e61a2e03c8aca188e", size = 5819847, upload-time = "2025-09-14T22:16:20.559Z" }, - { url = "https://files.pythonhosted.org/packages/6f/11/4c91411805c3f7b6f31c60e78ce347ca48f6f16d552fc659af6ec3b73202/zstandard-0.25.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:75ffc32a569fb049499e63ce68c743155477610532da1eb38e7f24bf7cd29e74", size = 5363131, upload-time = "2025-09-14T22:16:22.206Z" }, - { url = "https://files.pythonhosted.org/packages/ef/d6/8c4bd38a3b24c4c7676a7a3d8de85d6ee7a983602a734b9f9cdefb04a5d6/zstandard-0.25.0-cp310-cp310-win32.whl", hash = "sha256:106281ae350e494f4ac8a80470e66d1fe27e497052c8d9c3b95dc4cf1ade81aa", size = 436469, upload-time = "2025-09-14T22:16:25.002Z" }, - { url = "https://files.pythonhosted.org/packages/93/90/96d50ad417a8ace5f841b3228e93d1bb13e6ad356737f42e2dde30d8bd68/zstandard-0.25.0-cp310-cp310-win_amd64.whl", hash = "sha256:ea9d54cc3d8064260114a0bbf3479fc4a98b21dffc89b3459edd506b69262f6e", size = 506100, upload-time = "2025-09-14T22:16:23.569Z" }, - { url = "https://files.pythonhosted.org/packages/2a/83/c3ca27c363d104980f1c9cee1101cc8ba724ac8c28a033ede6aab89585b1/zstandard-0.25.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:933b65d7680ea337180733cf9e87293cc5500cc0eb3fc8769f4d3c88d724ec5c", size = 795254, upload-time = "2025-09-14T22:16:26.137Z" }, - { url = "https://files.pythonhosted.org/packages/ac/4d/e66465c5411a7cf4866aeadc7d108081d8ceba9bc7abe6b14aa21c671ec3/zstandard-0.25.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a3f79487c687b1fc69f19e487cd949bf3aae653d181dfb5fde3bf6d18894706f", size = 640559, upload-time = "2025-09-14T22:16:27.973Z" }, - { url = "https://files.pythonhosted.org/packages/12/56/354fe655905f290d3b147b33fe946b0f27e791e4b50a5f004c802cb3eb7b/zstandard-0.25.0-cp311-cp311-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:0bbc9a0c65ce0eea3c34a691e3c4b6889f5f3909ba4822ab385fab9057099431", size = 5348020, upload-time = "2025-09-14T22:16:29.523Z" }, - { url = "https://files.pythonhosted.org/packages/3b/13/2b7ed68bd85e69a2069bcc72141d378f22cae5a0f3b353a2c8f50ef30c1b/zstandard-0.25.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:01582723b3ccd6939ab7b3a78622c573799d5d8737b534b86d0e06ac18dbde4a", size = 5058126, upload-time = "2025-09-14T22:16:31.811Z" }, - { url = "https://files.pythonhosted.org/packages/c9/dd/fdaf0674f4b10d92cb120ccff58bbb6626bf8368f00ebfd2a41ba4a0dc99/zstandard-0.25.0-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:5f1ad7bf88535edcf30038f6919abe087f606f62c00a87d7e33e7fc57cb69fcc", size = 5405390, upload-time = "2025-09-14T22:16:33.486Z" }, - { url = "https://files.pythonhosted.org/packages/0f/67/354d1555575bc2490435f90d67ca4dd65238ff2f119f30f72d5cde09c2ad/zstandard-0.25.0-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:06acb75eebeedb77b69048031282737717a63e71e4ae3f77cc0c3b9508320df6", size = 5452914, upload-time = "2025-09-14T22:16:35.277Z" }, - { url = "https://files.pythonhosted.org/packages/bb/1f/e9cfd801a3f9190bf3e759c422bbfd2247db9d7f3d54a56ecde70137791a/zstandard-0.25.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9300d02ea7c6506f00e627e287e0492a5eb0371ec1670ae852fefffa6164b072", size = 5559635, upload-time = "2025-09-14T22:16:37.141Z" }, - { url = "https://files.pythonhosted.org/packages/21/88/5ba550f797ca953a52d708c8e4f380959e7e3280af029e38fbf47b55916e/zstandard-0.25.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:bfd06b1c5584b657a2892a6014c2f4c20e0db0208c159148fa78c65f7e0b0277", size = 5048277, upload-time = "2025-09-14T22:16:38.807Z" }, - { url = "https://files.pythonhosted.org/packages/46/c0/ca3e533b4fa03112facbe7fbe7779cb1ebec215688e5df576fe5429172e0/zstandard-0.25.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:f373da2c1757bb7f1acaf09369cdc1d51d84131e50d5fa9863982fd626466313", size = 5574377, upload-time = "2025-09-14T22:16:40.523Z" }, - { url = "https://files.pythonhosted.org/packages/12/9b/3fb626390113f272abd0799fd677ea33d5fc3ec185e62e6be534493c4b60/zstandard-0.25.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:6c0e5a65158a7946e7a7affa6418878ef97ab66636f13353b8502d7ea03c8097", size = 4961493, upload-time = "2025-09-14T22:16:43.3Z" }, - { url = "https://files.pythonhosted.org/packages/cb/d3/23094a6b6a4b1343b27ae68249daa17ae0651fcfec9ed4de09d14b940285/zstandard-0.25.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:c8e167d5adf59476fa3e37bee730890e389410c354771a62e3c076c86f9f7778", size = 5269018, upload-time = "2025-09-14T22:16:45.292Z" }, - { url = "https://files.pythonhosted.org/packages/8c/a7/bb5a0c1c0f3f4b5e9d5b55198e39de91e04ba7c205cc46fcb0f95f0383c1/zstandard-0.25.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:98750a309eb2f020da61e727de7d7ba3c57c97cf6213f6f6277bb7fb42a8e065", size = 5443672, upload-time = "2025-09-14T22:16:47.076Z" }, - { url = "https://files.pythonhosted.org/packages/27/22/503347aa08d073993f25109c36c8d9f029c7d5949198050962cb568dfa5e/zstandard-0.25.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:22a086cff1b6ceca18a8dd6096ec631e430e93a8e70a9ca5efa7561a00f826fa", size = 5822753, upload-time = "2025-09-14T22:16:49.316Z" }, - { url = "https://files.pythonhosted.org/packages/e2/be/94267dc6ee64f0f8ba2b2ae7c7a2df934a816baaa7291db9e1aa77394c3c/zstandard-0.25.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:72d35d7aa0bba323965da807a462b0966c91608ef3a48ba761678cb20ce5d8b7", size = 5366047, upload-time = "2025-09-14T22:16:51.328Z" }, - { url = "https://files.pythonhosted.org/packages/7b/a3/732893eab0a3a7aecff8b99052fecf9f605cf0fb5fb6d0290e36beee47a4/zstandard-0.25.0-cp311-cp311-win32.whl", hash = "sha256:f5aeea11ded7320a84dcdd62a3d95b5186834224a9e55b92ccae35d21a8b63d4", size = 436484, upload-time = "2025-09-14T22:16:55.005Z" }, - { url = "https://files.pythonhosted.org/packages/43/a3/c6155f5c1cce691cb80dfd38627046e50af3ee9ddc5d0b45b9b063bfb8c9/zstandard-0.25.0-cp311-cp311-win_amd64.whl", hash = "sha256:daab68faadb847063d0c56f361a289c4f268706b598afbf9ad113cbe5c38b6b2", size = 506183, upload-time = "2025-09-14T22:16:52.753Z" }, - { url = "https://files.pythonhosted.org/packages/8c/3e/8945ab86a0820cc0e0cdbf38086a92868a9172020fdab8a03ac19662b0e5/zstandard-0.25.0-cp311-cp311-win_arm64.whl", hash = "sha256:22a06c5df3751bb7dc67406f5374734ccee8ed37fc5981bf1ad7041831fa1137", size = 462533, upload-time = "2025-09-14T22:16:53.878Z" }, - { url = "https://files.pythonhosted.org/packages/82/fc/f26eb6ef91ae723a03e16eddb198abcfce2bc5a42e224d44cc8b6765e57e/zstandard-0.25.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7b3c3a3ab9daa3eed242d6ecceead93aebbb8f5f84318d82cee643e019c4b73b", size = 795738, upload-time = "2025-09-14T22:16:56.237Z" }, - { url = "https://files.pythonhosted.org/packages/aa/1c/d920d64b22f8dd028a8b90e2d756e431a5d86194caa78e3819c7bf53b4b3/zstandard-0.25.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:913cbd31a400febff93b564a23e17c3ed2d56c064006f54efec210d586171c00", size = 640436, upload-time = "2025-09-14T22:16:57.774Z" }, - { url = "https://files.pythonhosted.org/packages/53/6c/288c3f0bd9fcfe9ca41e2c2fbfd17b2097f6af57b62a81161941f09afa76/zstandard-0.25.0-cp312-cp312-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:011d388c76b11a0c165374ce660ce2c8efa8e5d87f34996aa80f9c0816698b64", size = 5343019, upload-time = "2025-09-14T22:16:59.302Z" }, - { url = "https://files.pythonhosted.org/packages/1e/15/efef5a2f204a64bdb5571e6161d49f7ef0fffdbca953a615efbec045f60f/zstandard-0.25.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:6dffecc361d079bb48d7caef5d673c88c8988d3d33fb74ab95b7ee6da42652ea", size = 5063012, upload-time = "2025-09-14T22:17:01.156Z" }, - { url = "https://files.pythonhosted.org/packages/b7/37/a6ce629ffdb43959e92e87ebdaeebb5ac81c944b6a75c9c47e300f85abdf/zstandard-0.25.0-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:7149623bba7fdf7e7f24312953bcf73cae103db8cae49f8154dd1eadc8a29ecb", size = 5394148, upload-time = "2025-09-14T22:17:03.091Z" }, - { url = "https://files.pythonhosted.org/packages/e3/79/2bf870b3abeb5c070fe2d670a5a8d1057a8270f125ef7676d29ea900f496/zstandard-0.25.0-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:6a573a35693e03cf1d67799fd01b50ff578515a8aeadd4595d2a7fa9f3ec002a", size = 5451652, upload-time = "2025-09-14T22:17:04.979Z" }, - { url = "https://files.pythonhosted.org/packages/53/60/7be26e610767316c028a2cbedb9a3beabdbe33e2182c373f71a1c0b88f36/zstandard-0.25.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:5a56ba0db2d244117ed744dfa8f6f5b366e14148e00de44723413b2f3938a902", size = 5546993, upload-time = "2025-09-14T22:17:06.781Z" }, - { url = "https://files.pythonhosted.org/packages/85/c7/3483ad9ff0662623f3648479b0380d2de5510abf00990468c286c6b04017/zstandard-0.25.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:10ef2a79ab8e2974e2075fb984e5b9806c64134810fac21576f0668e7ea19f8f", size = 5046806, upload-time = "2025-09-14T22:17:08.415Z" }, - { url = "https://files.pythonhosted.org/packages/08/b3/206883dd25b8d1591a1caa44b54c2aad84badccf2f1de9e2d60a446f9a25/zstandard-0.25.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:aaf21ba8fb76d102b696781bddaa0954b782536446083ae3fdaa6f16b25a1c4b", size = 5576659, upload-time = "2025-09-14T22:17:10.164Z" }, - { url = "https://files.pythonhosted.org/packages/9d/31/76c0779101453e6c117b0ff22565865c54f48f8bd807df2b00c2c404b8e0/zstandard-0.25.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:1869da9571d5e94a85a5e8d57e4e8807b175c9e4a6294e3b66fa4efb074d90f6", size = 4953933, upload-time = "2025-09-14T22:17:11.857Z" }, - { url = "https://files.pythonhosted.org/packages/18/e1/97680c664a1bf9a247a280a053d98e251424af51f1b196c6d52f117c9720/zstandard-0.25.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:809c5bcb2c67cd0ed81e9229d227d4ca28f82d0f778fc5fea624a9def3963f91", size = 5268008, upload-time = "2025-09-14T22:17:13.627Z" }, - { url = "https://files.pythonhosted.org/packages/1e/73/316e4010de585ac798e154e88fd81bb16afc5c5cb1a72eeb16dd37e8024a/zstandard-0.25.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:f27662e4f7dbf9f9c12391cb37b4c4c3cb90ffbd3b1fb9284dadbbb8935fa708", size = 5433517, upload-time = "2025-09-14T22:17:16.103Z" }, - { url = "https://files.pythonhosted.org/packages/5b/60/dd0f8cfa8129c5a0ce3ea6b7f70be5b33d2618013a161e1ff26c2b39787c/zstandard-0.25.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:99c0c846e6e61718715a3c9437ccc625de26593fea60189567f0118dc9db7512", size = 5814292, upload-time = "2025-09-14T22:17:17.827Z" }, - { url = "https://files.pythonhosted.org/packages/fc/5f/75aafd4b9d11b5407b641b8e41a57864097663699f23e9ad4dbb91dc6bfe/zstandard-0.25.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:474d2596a2dbc241a556e965fb76002c1ce655445e4e3bf38e5477d413165ffa", size = 5360237, upload-time = "2025-09-14T22:17:19.954Z" }, - { url = "https://files.pythonhosted.org/packages/ff/8d/0309daffea4fcac7981021dbf21cdb2e3427a9e76bafbcdbdf5392ff99a4/zstandard-0.25.0-cp312-cp312-win32.whl", hash = "sha256:23ebc8f17a03133b4426bcc04aabd68f8236eb78c3760f12783385171b0fd8bd", size = 436922, upload-time = "2025-09-14T22:17:24.398Z" }, - { url = "https://files.pythonhosted.org/packages/79/3b/fa54d9015f945330510cb5d0b0501e8253c127cca7ebe8ba46a965df18c5/zstandard-0.25.0-cp312-cp312-win_amd64.whl", hash = "sha256:ffef5a74088f1e09947aecf91011136665152e0b4b359c42be3373897fb39b01", size = 506276, upload-time = "2025-09-14T22:17:21.429Z" }, - { url = "https://files.pythonhosted.org/packages/ea/6b/8b51697e5319b1f9ac71087b0af9a40d8a6288ff8025c36486e0c12abcc4/zstandard-0.25.0-cp312-cp312-win_arm64.whl", hash = "sha256:181eb40e0b6a29b3cd2849f825e0fa34397f649170673d385f3598ae17cca2e9", size = 462679, upload-time = "2025-09-14T22:17:23.147Z" }, - { url = "https://files.pythonhosted.org/packages/35/0b/8df9c4ad06af91d39e94fa96cc010a24ac4ef1378d3efab9223cc8593d40/zstandard-0.25.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:ec996f12524f88e151c339688c3897194821d7f03081ab35d31d1e12ec975e94", size = 795735, upload-time = "2025-09-14T22:17:26.042Z" }, - { url = "https://files.pythonhosted.org/packages/3f/06/9ae96a3e5dcfd119377ba33d4c42a7d89da1efabd5cb3e366b156c45ff4d/zstandard-0.25.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a1a4ae2dec3993a32247995bdfe367fc3266da832d82f8438c8570f989753de1", size = 640440, upload-time = "2025-09-14T22:17:27.366Z" }, - { url = "https://files.pythonhosted.org/packages/d9/14/933d27204c2bd404229c69f445862454dcc101cd69ef8c6068f15aaec12c/zstandard-0.25.0-cp313-cp313-manylinux2010_i686.manylinux2014_i686.manylinux_2_12_i686.manylinux_2_17_i686.whl", hash = "sha256:e96594a5537722fdfb79951672a2a63aec5ebfb823e7560586f7484819f2a08f", size = 5343070, upload-time = "2025-09-14T22:17:28.896Z" }, - { url = "https://files.pythonhosted.org/packages/6d/db/ddb11011826ed7db9d0e485d13df79b58586bfdec56e5c84a928a9a78c1c/zstandard-0.25.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:bfc4e20784722098822e3eee42b8e576b379ed72cca4a7cb856ae733e62192ea", size = 5063001, upload-time = "2025-09-14T22:17:31.044Z" }, - { url = "https://files.pythonhosted.org/packages/db/00/87466ea3f99599d02a5238498b87bf84a6348290c19571051839ca943777/zstandard-0.25.0-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:457ed498fc58cdc12fc48f7950e02740d4f7ae9493dd4ab2168a47c93c31298e", size = 5394120, upload-time = "2025-09-14T22:17:32.711Z" }, - { url = "https://files.pythonhosted.org/packages/2b/95/fc5531d9c618a679a20ff6c29e2b3ef1d1f4ad66c5e161ae6ff847d102a9/zstandard-0.25.0-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:fd7a5004eb1980d3cefe26b2685bcb0b17989901a70a1040d1ac86f1d898c551", size = 5451230, upload-time = "2025-09-14T22:17:34.41Z" }, - { url = "https://files.pythonhosted.org/packages/63/4b/e3678b4e776db00f9f7b2fe58e547e8928ef32727d7a1ff01dea010f3f13/zstandard-0.25.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:8e735494da3db08694d26480f1493ad2cf86e99bdd53e8e9771b2752a5c0246a", size = 5547173, upload-time = "2025-09-14T22:17:36.084Z" }, - { url = "https://files.pythonhosted.org/packages/4e/d5/ba05ed95c6b8ec30bd468dfeab20589f2cf709b5c940483e31d991f2ca58/zstandard-0.25.0-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:3a39c94ad7866160a4a46d772e43311a743c316942037671beb264e395bdd611", size = 5046736, upload-time = "2025-09-14T22:17:37.891Z" }, - { url = "https://files.pythonhosted.org/packages/50/d5/870aa06b3a76c73eced65c044b92286a3c4e00554005ff51962deef28e28/zstandard-0.25.0-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:172de1f06947577d3a3005416977cce6168f2261284c02080e7ad0185faeced3", size = 5576368, upload-time = "2025-09-14T22:17:40.206Z" }, - { url = "https://files.pythonhosted.org/packages/5d/35/398dc2ffc89d304d59bc12f0fdd931b4ce455bddf7038a0a67733a25f550/zstandard-0.25.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:3c83b0188c852a47cd13ef3bf9209fb0a77fa5374958b8c53aaa699398c6bd7b", size = 4954022, upload-time = "2025-09-14T22:17:41.879Z" }, - { url = "https://files.pythonhosted.org/packages/9a/5c/36ba1e5507d56d2213202ec2b05e8541734af5f2ce378c5d1ceaf4d88dc4/zstandard-0.25.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:1673b7199bbe763365b81a4f3252b8e80f44c9e323fc42940dc8843bfeaf9851", size = 5267889, upload-time = "2025-09-14T22:17:43.577Z" }, - { url = "https://files.pythonhosted.org/packages/70/e8/2ec6b6fb7358b2ec0113ae202647ca7c0e9d15b61c005ae5225ad0995df5/zstandard-0.25.0-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:0be7622c37c183406f3dbf0cba104118eb16a4ea7359eeb5752f0794882fc250", size = 5433952, upload-time = "2025-09-14T22:17:45.271Z" }, - { url = "https://files.pythonhosted.org/packages/7b/01/b5f4d4dbc59ef193e870495c6f1275f5b2928e01ff5a81fecb22a06e22fb/zstandard-0.25.0-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:5f5e4c2a23ca271c218ac025bd7d635597048b366d6f31f420aaeb715239fc98", size = 5814054, upload-time = "2025-09-14T22:17:47.08Z" }, - { url = "https://files.pythonhosted.org/packages/b2/e5/fbd822d5c6f427cf158316d012c5a12f233473c2f9c5fe5ab1ae5d21f3d8/zstandard-0.25.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:4f187a0bb61b35119d1926aee039524d1f93aaf38a9916b8c4b78ac8514a0aaf", size = 5360113, upload-time = "2025-09-14T22:17:48.893Z" }, - { url = "https://files.pythonhosted.org/packages/8e/e0/69a553d2047f9a2c7347caa225bb3a63b6d7704ad74610cb7823baa08ed7/zstandard-0.25.0-cp313-cp313-win32.whl", hash = "sha256:7030defa83eef3e51ff26f0b7bfb229f0204b66fe18e04359ce3474ac33cbc09", size = 436936, upload-time = "2025-09-14T22:17:52.658Z" }, - { url = "https://files.pythonhosted.org/packages/d9/82/b9c06c870f3bd8767c201f1edbdf9e8dc34be5b0fbc5682c4f80fe948475/zstandard-0.25.0-cp313-cp313-win_amd64.whl", hash = "sha256:1f830a0dac88719af0ae43b8b2d6aef487d437036468ef3c2ea59c51f9d55fd5", size = 506232, upload-time = "2025-09-14T22:17:50.402Z" }, - { url = "https://files.pythonhosted.org/packages/d4/57/60c3c01243bb81d381c9916e2a6d9e149ab8627c0c7d7abb2d73384b3c0c/zstandard-0.25.0-cp313-cp313-win_arm64.whl", hash = "sha256:85304a43f4d513f5464ceb938aa02c1e78c2943b29f44a750b48b25ac999a049", size = 462671, upload-time = "2025-09-14T22:17:51.533Z" }, - { url = "https://files.pythonhosted.org/packages/3d/5c/f8923b595b55fe49e30612987ad8bf053aef555c14f05bb659dd5dbe3e8a/zstandard-0.25.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:e29f0cf06974c899b2c188ef7f783607dbef36da4c242eb6c82dcd8b512855e3", size = 795887, upload-time = "2025-09-14T22:17:54.198Z" }, - { url = "https://files.pythonhosted.org/packages/8d/09/d0a2a14fc3439c5f874042dca72a79c70a532090b7ba0003be73fee37ae2/zstandard-0.25.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:05df5136bc5a011f33cd25bc9f506e7426c0c9b3f9954f056831ce68f3b6689f", size = 640658, upload-time = "2025-09-14T22:17:55.423Z" }, - { url = "https://files.pythonhosted.org/packages/5d/7c/8b6b71b1ddd517f68ffb55e10834388d4f793c49c6b83effaaa05785b0b4/zstandard-0.25.0-cp314-cp314-manylinux2010_i686.manylinux_2_12_i686.manylinux_2_28_i686.whl", hash = "sha256:f604efd28f239cc21b3adb53eb061e2a205dc164be408e553b41ba2ffe0ca15c", size = 5379849, upload-time = "2025-09-14T22:17:57.372Z" }, - { url = "https://files.pythonhosted.org/packages/a4/86/a48e56320d0a17189ab7a42645387334fba2200e904ee47fc5a26c1fd8ca/zstandard-0.25.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:223415140608d0f0da010499eaa8ccdb9af210a543fac54bce15babbcfc78439", size = 5058095, upload-time = "2025-09-14T22:17:59.498Z" }, - { url = "https://files.pythonhosted.org/packages/f8/ad/eb659984ee2c0a779f9d06dbfe45e2dc39d99ff40a319895df2d3d9a48e5/zstandard-0.25.0-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:2e54296a283f3ab5a26fc9b8b5d4978ea0532f37b231644f367aa588930aa043", size = 5551751, upload-time = "2025-09-14T22:18:01.618Z" }, - { url = "https://files.pythonhosted.org/packages/61/b3/b637faea43677eb7bd42ab204dfb7053bd5c4582bfe6b1baefa80ac0c47b/zstandard-0.25.0-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:ca54090275939dc8ec5dea2d2afb400e0f83444b2fc24e07df7fdef677110859", size = 6364818, upload-time = "2025-09-14T22:18:03.769Z" }, - { url = "https://files.pythonhosted.org/packages/31/dc/cc50210e11e465c975462439a492516a73300ab8caa8f5e0902544fd748b/zstandard-0.25.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:e09bb6252b6476d8d56100e8147b803befa9a12cea144bbe629dd508800d1ad0", size = 5560402, upload-time = "2025-09-14T22:18:05.954Z" }, - { url = "https://files.pythonhosted.org/packages/c9/ae/56523ae9c142f0c08efd5e868a6da613ae76614eca1305259c3bf6a0ed43/zstandard-0.25.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:a9ec8c642d1ec73287ae3e726792dd86c96f5681eb8df274a757bf62b750eae7", size = 4955108, upload-time = "2025-09-14T22:18:07.68Z" }, - { url = "https://files.pythonhosted.org/packages/98/cf/c899f2d6df0840d5e384cf4c4121458c72802e8bda19691f3b16619f51e9/zstandard-0.25.0-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:a4089a10e598eae6393756b036e0f419e8c1d60f44a831520f9af41c14216cf2", size = 5269248, upload-time = "2025-09-14T22:18:09.753Z" }, - { url = "https://files.pythonhosted.org/packages/1b/c0/59e912a531d91e1c192d3085fc0f6fb2852753c301a812d856d857ea03c6/zstandard-0.25.0-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:f67e8f1a324a900e75b5e28ffb152bcac9fbed1cc7b43f99cd90f395c4375344", size = 5430330, upload-time = "2025-09-14T22:18:11.966Z" }, - { url = "https://files.pythonhosted.org/packages/a0/1d/7e31db1240de2df22a58e2ea9a93fc6e38cc29353e660c0272b6735d6669/zstandard-0.25.0-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:9654dbc012d8b06fc3d19cc825af3f7bf8ae242226df5f83936cb39f5fdc846c", size = 5811123, upload-time = "2025-09-14T22:18:13.907Z" }, - { url = "https://files.pythonhosted.org/packages/f6/49/fac46df5ad353d50535e118d6983069df68ca5908d4d65b8c466150a4ff1/zstandard-0.25.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:4203ce3b31aec23012d3a4cf4a2ed64d12fea5269c49aed5e4c3611b938e4088", size = 5359591, upload-time = "2025-09-14T22:18:16.465Z" }, - { url = "https://files.pythonhosted.org/packages/c2/38/f249a2050ad1eea0bb364046153942e34abba95dd5520af199aed86fbb49/zstandard-0.25.0-cp314-cp314-win32.whl", hash = "sha256:da469dc041701583e34de852d8634703550348d5822e66a0c827d39b05365b12", size = 444513, upload-time = "2025-09-14T22:18:20.61Z" }, - { url = "https://files.pythonhosted.org/packages/3a/43/241f9615bcf8ba8903b3f0432da069e857fc4fd1783bd26183db53c4804b/zstandard-0.25.0-cp314-cp314-win_amd64.whl", hash = "sha256:c19bcdd826e95671065f8692b5a4aa95c52dc7a02a4c5a0cac46deb879a017a2", size = 516118, upload-time = "2025-09-14T22:18:17.849Z" }, - { url = "https://files.pythonhosted.org/packages/f0/ef/da163ce2450ed4febf6467d77ccb4cd52c4c30ab45624bad26ca0a27260c/zstandard-0.25.0-cp314-cp314-win_arm64.whl", hash = "sha256:d7541afd73985c630bafcd6338d2518ae96060075f9463d7dc14cfb33514383d", size = 476940, upload-time = "2025-09-14T22:18:19.088Z" }, -] diff --git a/py/examples/openai_example.py b/py/examples/openai_example.py deleted file mode 100755 index a9c731ebb..000000000 --- a/py/examples/openai_example.py +++ /dev/null @@ -1,35 +0,0 @@ -#!/usr/bin/env python - -from braintrust import init_logger, traced, wrap_openai -from openai import OpenAI - -logger = init_logger(project="example-openai-project") -client = wrap_openai(OpenAI()) - - -# @traced automatically logs the input (args) and output (return value) -# of this function to a span. To ensure the span is named `answer_question`, -# you should name the function `answer_question`. -@traced -def answer_question(body: str) -> str: - prompt = [ - {"role": "system", "content": "You are a helpful assistant."}, - {"role": "user", "content": body}, - ] - - result = client.chat.completions.create( - model="gpt-4o", - messages=prompt, - temperature=0.5, - ) - return result.choices[0].message.content - - -def main(): - input_text = "What's the capital of Australia?" - result = answer_question(input_text) - print(result) - - -if __name__ == "__main__": - main() diff --git a/py/examples/otel/basic_otel_example.py b/py/examples/otel/basic_otel_example.py deleted file mode 100755 index cdec195cd..000000000 --- a/py/examples/otel/basic_otel_example.py +++ /dev/null @@ -1,57 +0,0 @@ -#!/usr/bin/env python3 -""" -Basic OpenTelemetry example with Braintrust integration. - -This example shows how to manually configure OpenTelemetry with BraintrustSpanProcessor -without any filtering enabled. All spans will be sent to Braintrust. -""" - -import os -import time - -# Set environment variables -os.environ.setdefault("BRAINTRUST_PARENT", "project_name:otel-examples") - -from braintrust.otel import BraintrustSpanProcessor -from openai import OpenAI -from opentelemetry import trace -from opentelemetry.instrumentation.openai import OpenAIInstrumentor -from opentelemetry.sdk.trace import TracerProvider - -# Set up the tracer provider -provider = TracerProvider() -trace.set_tracer_provider(provider) - -# Instrument OpenAI to automatically trace calls -OpenAIInstrumentor().instrument() - -# Create and add the Braintrust span processor -processor = BraintrustSpanProcessor( - # No filtering enabled by default - filter_ai_spans=False -) - -# Add the processor to the tracer provider -provider.add_span_processor(processor) - -# Create a tracer -tracer = trace.get_tracer(__name__) - -print("Creating spans to demonstrate basic OpenTelemetry configuration...") - -# Create some spans -with tracer.start_as_current_span("basic.otel.example") as main_span: - main_span.set_attribute("example_type", "basic_configure") - main_span.set_attribute("language", "python") - - # Add a simple OpenAI call - this will be automatically traced by OpenTelemetry - client = OpenAI() - response = client.chat.completions.create( - model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello, world!"}], max_tokens=10 - ) - - main_span.set_attribute("openai_response", response.choices[0].message.content) - time.sleep(0.5) - -# Force flush to ensure spans are sent -trace.get_tracer_provider().force_flush(30) diff --git a/py/examples/otel/bt-otel-context.py b/py/examples/otel/bt-otel-context.py deleted file mode 100644 index cd3084e45..000000000 --- a/py/examples/otel/bt-otel-context.py +++ /dev/null @@ -1,111 +0,0 @@ -#!/usr/bin/env python3 -""" -Example: Braintrust + OTEL Context Integration - -This example demonstrates how Braintrust spans automatically capture OTEL context -information when created within active OTEL spans, enabling correlation between -pure OTEL instrumentation and Braintrust observability. - -Key concept: No bridge needed - just pure OTEL + pure Braintrust with automatic correlation. -""" - -import os - -os.environ['BRAINTRUST_OTEL_COMPAT'] = 'true' - -import braintrust -from braintrust.otel import add_braintrust_span_processor - -PROJECT_NAME = "mixed-otel-braintrust-python-2" - -from opentelemetry import trace -from opentelemetry.sdk.trace import TracerProvider - - -def setup_otel(): - """Setup OTEL instrumentation with Braintrust processor to send OTEL spans to server.""" - provider = TracerProvider() - add_braintrust_span_processor(provider, parent=f"project_name:{PROJECT_NAME}") - trace.set_tracer_provider(provider) - - return trace.get_tracer(__name__, "1.0.0") - -def main(): - # Setup - braintrust.login() - - tracer = setup_otel() - project = braintrust.init_logger( - project=PROJECT_NAME - ) - - # Demo 1: BT project as root span with OTEL instrumentation inside - with project.start_span("trace1_root_bt") as session_span: - session_span.log(input="BT root span", metadata={"type": "root"}) - print(f"BT span link: {session_span.link()}") - - # OTEL spans inside BT context for system tracing - with tracer.start_as_current_span("trace1_child_otel") as otel_span: - otel_span.set_attribute("type", "otel_inside_bt") - otel_span.add_event("start") - - # Nested OTEL spans to test parent propagation - with tracer.start_as_current_span("trace1_grandchild_otel") as nested_otel: - nested_otel.set_attribute("type", "nested_otel") - - @braintrust.traced - def trace1_grandchild_bt_traced(): - pass - - trace1_grandchild_bt_traced() - - otel_span.add_event("end") - - @braintrust.traced - def trace1_child_bt_traced(): - pass - - trace1_child_bt_traced() - - - # Demo 2: OTEL as root span with BT spans inside - with tracer.start_as_current_span("trace2_root_otel") as otel_root: - otel_trace_id = format(otel_root.get_span_context().trace_id, '032x') - otel_root.set_attribute("type", "otel_root") - otel_root.add_event("otel_root_start") - - # BT spans inside OTEL context - should inherit OTEL trace ID - with project.start_span("trace2_child_bt") as bt_span: - bt_span.log(input="BT span inside OTEL", metadata={"type": "bt_inside_otel"}) - print(f"BT span link: {bt_span.link()}") - - with tracer.start_as_current_span("trace2_grandchild_otel") as otel_grandchild: - otel_grandchild.set_attribute("type", "otel_grandchild") - otel_grandchild.add_event("otel_grandchild_start") - - @braintrust.traced - def trace2_grandchild_bt1(): - pass - trace2_grandchild_bt1() - - # Nested BT span should also inherit same trace ID - with bt_span.start_span("trace2_grandchild_bt") as bt_grandchild: - bt_grandchild.log(input="Nested BT span", output="unified trace", scores={"accuracy": 0.88}) - - @braintrust.traced - def trace2_child_bt_traced(): - pass - trace2_child_bt_traced() - - otel_root.add_event("otel_root_end") - - # Flush BT data first to create the parent traces - project.flush() - - # Then flush OTEL spans so they can attach to existing parents - if hasattr(trace.get_tracer_provider(), 'force_flush'): - trace.get_tracer_provider().force_flush(timeout_millis=5000) - - -if __name__ == "__main__": - main() diff --git a/py/examples/otel/distributed-tracing.py b/py/examples/otel/distributed-tracing.py deleted file mode 100644 index f1c0bfebe..000000000 --- a/py/examples/otel/distributed-tracing.py +++ /dev/null @@ -1,141 +0,0 @@ -#!/usr/bin/env python3 -""" -Example: Distributed Tracing between Braintrust and OpenTelemetry - -This example demonstrates how to propagate trace context across service boundaries -using Braintrust span.export() and OpenTelemetry. This enables unified distributed -tracing where spans can be parents/children across different services and technologies. - -Key concepts: -- Service A (BT) creates a Braintrust span and exports the context -- Service B (OTEL) uses context_from_span_export() to create child OTEL spans -- Service B exports OTEL context as W3C trace headers -- Service C (BT) uses parent_from_headers() to create BT child span -- All spans share the same trace_id and maintain proper parent relationships -""" - -import os - -# Enable OTEL compatibility mode -os.environ['BRAINTRUST_OTEL_COMPAT'] = 'true' - -import braintrust -from braintrust.otel import ( - add_braintrust_span_processor, - add_span_parent_to_baggage, - context_from_span_export, - parent_from_headers, -) -from opentelemetry import context as otel_context -from opentelemetry import trace -from opentelemetry.propagate import inject -from opentelemetry.sdk.trace import TracerProvider - -PROJECT_NAME = "distributed-tracing-demo" - - -def setup_otel(): - """Setup OTEL instrumentation with Braintrust processor.""" - provider = TracerProvider() - add_braintrust_span_processor(provider, - parent=f"project_name:different-project") - trace.set_tracer_provider(provider) - return trace.get_tracer(__name__, "1.0.0") - - -def service_b_process_request(exported_context: str, tracer, project): - """ - Service B: Receives exported context from Service A and creates child OTEL spans. - - In a real distributed system, exported_context would be received via HTTP headers, - message queue metadata, or other inter-service communication mechanisms. - """ - print("\n=== Service B: User Service ===") - - # Import the context from Service A - ctx = context_from_span_export(exported_context) - - # Attach the context and create OTEL spans as children - token = otel_context.attach(ctx) - try: - with tracer.start_as_current_span("service_b.root") as fetch_span: - # Nested operation in Service B - with tracer.start_as_current_span("service_b.child"): - trace_id = format(fetch_span.get_span_context().trace_id, '032x') - print(f" Created OTEL child spans (trace_id: {trace_id})") - - - # Ensure 'braintrust.parent' is set on the baggage. - add_span_parent_to_baggage(fetch_span) - - # Export OTEL context as W3C trace headers for Service C - headers = {} - inject(headers) - # Call Service C with the headers - service_c_process_request(headers, project) - finally: - otel_context.detach(token) - - -def service_c_process_request(headers: dict, project): - """ - Service C: Receives W3C trace headers from Service B and creates child BT span. - - In a real distributed system, headers would be received via HTTP request headers - or message queue metadata. - """ - print("\n=== Service C: Analytics Service ===") - - # Extract Braintrust-compatible parent string from W3C trace headers - parent = parent_from_headers(headers) - - # Create BT span with OTEL parent - with project.start_span(name="service_c.root", parent=parent) as analytics_span: - span_id = analytics_span.span_id - print(f" Created BT span as child of OTEL parent (span_id: {span_id[:16]}...)") - analytics_span.log( - input="Analytics data from Service B", - output="Processed analytics", - metadata={"service": "analytics"} - ) - - -def main(): - print("Distributed Tracing Example: Braintrust โ†’ OpenTelemetry โ†’ Braintrust\n") - print("This example simulates a distributed system with 3 services:") - print(" 1. Service A (Braintrust span)") - print(" 2. Service B (OTEL span)") - print(" 3. Service C (Braintrust span)\n") - - # Setup - braintrust.login() - tracer = setup_otel() - project = braintrust.init_logger(project=PROJECT_NAME) - - print("=== Service A ===") - with project.start_span(name="service_a.root") as gateway_span: - trace_id = gateway_span.root_span_id - span_id = gateway_span.span_id - print(f" Created span (trace_id: {trace_id[:16]}..., span_id: {span_id[:8]}...)") - print(f" Link: {gateway_span.link()}") - - # Export context for distributed tracing - # In a real system, this would be sent as HTTP headers like: - # X-Braintrust-Context: - exported_context = gateway_span.export() - print(f"\n โ†’ Sending request to Service B with exported context") - - # Call Service B with the exported context - service_b_process_request(exported_context, tracer, project) - - # Flush all data - project.flush() - if hasattr(trace.get_tracer_provider(), 'force_flush'): - trace.get_tracer_provider().force_flush(timeout_millis=5000) - - print(f"\nโœ“ Trace complete! All 3 services share trace_id: {trace_id[:16]}...") - print(f" View in Braintrust: {gateway_span.link()}") - - -if __name__ == "__main__": - main() diff --git a/py/examples/otel/filtered_otel_example.py b/py/examples/otel/filtered_otel_example.py deleted file mode 100755 index 25910d224..000000000 --- a/py/examples/otel/filtered_otel_example.py +++ /dev/null @@ -1,76 +0,0 @@ -#!/usr/bin/env python3 -""" -Filtered OpenTelemetry example with Braintrust integration. - -This example shows how to use BraintrustSpanProcessor with AI span filtering enabled -and custom filter functions. Only AI-related spans and root spans will be sent to Braintrust. -""" - -import os -import time - -# Set environment variables -os.environ.setdefault("BRAINTRUST_PARENT", "project_name:otel-examples") -os.environ.setdefault("BRAINTRUST_OTEL_FILTER_AI_SPANS", "false") - -from braintrust.otel import BraintrustSpanProcessor -from openai import OpenAI -from opentelemetry import trace -from opentelemetry.instrumentation.openai import OpenAIInstrumentor -from opentelemetry.sdk.trace import TracerProvider - -# Set up the tracer provider -provider = TracerProvider() -trace.set_tracer_provider(provider) - -# Instrument OpenAI to automatically trace calls -OpenAIInstrumentor().instrument() - - -# Define a custom filter function -def my_custom_filter(span): - """Keep spans that start with 'custom_' in addition to LLM spans.""" - if span.name.startswith("custom_"): - return True - return None # Defer to default LLM filtering logic - - -# Create a single processor with all the available options -processor = BraintrustSpanProcessor( - api_url="https://api.braintrust.dev", # Base URL for Braintrust API - custom_filter=my_custom_filter, # Custom filter function -) - -# Add the processor to the tracer provider -provider.add_span_processor(processor) - -# Create a tracer and generate some spans -tracer = trace.get_tracer(__name__) - -print("Creating spans to demonstrate AI span filtering behavior...") - -# Create spans to test the filtering behavior -with tracer.start_as_current_span("filtered.otel.example") as main_span: - main_span.set_attribute("request_id", "12345") - main_span.set_attribute("user_id", "demo-user") - - # Add a simple OpenAI call - this will be automatically traced by OpenTelemetry - client = OpenAI() - response = client.chat.completions.create( - model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello, world!"}], max_tokens=10 - ) - - main_span.set_attribute("openai_response", response.choices[0].message.content) - - # This span will be kept (LLM-related) - with tracer.start_as_current_span("microservice-call") as llm_span: - llm_span.set_attribute("gen_ai.model", "gpt-4") - llm_span.set_attribute("gen_ai.tokens", 150) - time.sleep(0.1) - - # This span will be filtered out (not LLM-related) - with tracer.start_as_current_span("database_query"): - time.sleep(0.05) - -# Force flush to ensure spans are sent -trace.get_tracer_provider().force_flush(30) diff --git a/py/examples/otel/otel_eval.py b/py/examples/otel/otel_eval.py deleted file mode 100644 index 8fb72bfeb..000000000 --- a/py/examples/otel/otel_eval.py +++ /dev/null @@ -1,52 +0,0 @@ -#!/usr/bin/env python3 -""" -Simple OTEL Evaluation Example - -Shows how to add OTEL tracing to a Braintrust evaluation task. -""" - -import os - -# Enable OTEL compatibility -os.environ['BRAINTRUST_OTEL_COMPAT'] = 'true' - -from autoevals import Levenshtein -from braintrust import Eval -from braintrust.otel import BraintrustSpanProcessor -from opentelemetry import trace -from opentelemetry.sdk.trace import TracerProvider - -# Setup OTEL tracing -provider = TracerProvider() -processor = BraintrustSpanProcessor(parent="project_name:otel-eval-example") -provider.add_span_processor(processor) -trace.set_tracer_provider(provider) - -def task_with_otel_tracing(input): - tracer = trace.get_tracer(__name__) - - with tracer.start_as_current_span("otel.eval.task") as span: - span.set_attribute("input", input) - - # Simple task logic - result = "Hi " + input - - span.set_attribute("output", result) - return result - -# Run evaluation with OTEL tracing -Eval( - "Say Hi Bot", - data=lambda: [ - { - "input": "Foo", - "expected": "Hi Foo", - }, - { - "input": "Bar", - "expected": "Hello Bar", - }, - ], - task=task_with_otel_tracing, # Task function includes OTEL spans - scores=[Levenshtein], -) diff --git a/py/examples/pydantic_ai_example.py b/py/examples/pydantic_ai_example.py deleted file mode 100644 index 0092278dd..000000000 --- a/py/examples/pydantic_ai_example.py +++ /dev/null @@ -1,24 +0,0 @@ -#!/usr/bin/env python - -import asyncio - -import braintrust - -braintrust.auto_instrument() -logger = braintrust.init_logger(project="example-pydantic-ai-project") - -from pydantic_ai import Agent - -agent = Agent("openai:gpt-4o", system_prompt="You are a helpful assistant.") - - -async def main(): - with braintrust.start_span(name="pydantic_ai_example") as span: - result = await agent.run("What's the capital of Australia?") - print(result.output) - - print(f"\nView trace: {span.link()}") - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/py/examples/temporal/.env.example b/py/examples/temporal/.env.example deleted file mode 100644 index 26181c0cb..000000000 --- a/py/examples/temporal/.env.example +++ /dev/null @@ -1 +0,0 @@ -BRAINTRUST_API_KEY=your-braintrust-api-key-here diff --git a/py/examples/temporal/.gitignore b/py/examples/temporal/.gitignore deleted file mode 100644 index 1d17dae13..000000000 --- a/py/examples/temporal/.gitignore +++ /dev/null @@ -1 +0,0 @@ -.venv diff --git a/py/examples/temporal/Procfile b/py/examples/temporal/Procfile deleted file mode 100644 index a11e666fc..000000000 --- a/py/examples/temporal/Procfile +++ /dev/null @@ -1,4 +0,0 @@ -server: temporal server start-dev -worker1: python worker.py -worker2: python worker.py -worker3: python worker.py diff --git a/py/examples/temporal/README.md b/py/examples/temporal/README.md deleted file mode 100644 index d4f39055e..000000000 --- a/py/examples/temporal/README.md +++ /dev/null @@ -1,43 +0,0 @@ -# Braintrust Temporal Tracing Example - -This example demonstrates distributed tracing for Temporal workflows using Braintrust. - -## Setup - -1. Install Braintrust with Temporal support: - - ```bash - pip install "braintrust[temporal]" - ``` - - Or if using mise: - - ```bash - mise install - ``` - -2. Configure your Braintrust API key in `.env`: - ```bash - cp .env.example .env - # Edit .env and add your BRAINTRUST_API_KEY - ``` - -## Running - -1. Start the Temporal server and workers: - - ```bash - mise run server - ``` - -2. In another terminal, run the workflow: - - ```bash - mise run workflow - ``` - - Optional: Send a signal during workflow execution: - - ```bash - mise run workflow -- --signal - ``` diff --git a/py/examples/temporal/mise.toml b/py/examples/temporal/mise.toml deleted file mode 100644 index 2106ec593..000000000 --- a/py/examples/temporal/mise.toml +++ /dev/null @@ -1,26 +0,0 @@ -# Mise will automatically read and use .tool-versions files as well as this file. -[settings] -experimental=true - -[env] -# See env.example to configure API keys. -_.file = ".env" - -[tools] -uv = "latest" -temporal = "latest" -overmind = "latest" - -[hooks] -postinstall = "mise run install" - -[tasks.install] -description = "Install requirements" -run = "uv pip install -r requirements.txt" - -[tasks.server] -description = "Run temporal server" -run = "overmind s" - -[tasks.workflow] -run = "python run.py" diff --git a/py/examples/temporal/requirements.txt b/py/examples/temporal/requirements.txt deleted file mode 100644 index 3ea01cf18..000000000 --- a/py/examples/temporal/requirements.txt +++ /dev/null @@ -1,2 +0,0 @@ -temporalio -braintrust diff --git a/py/examples/temporal/run.py b/py/examples/temporal/run.py deleted file mode 100644 index 2ecbdfa71..000000000 --- a/py/examples/temporal/run.py +++ /dev/null @@ -1,51 +0,0 @@ -import asyncio -import sys -import uuid - -import braintrust -from braintrust.contrib.temporal import BraintrustPlugin -from temporalio.client import Client -from workflow import TASK_QUEUE_NAME, SimpleWorkflow, TaskInput - - -async def main() -> None: - """Execute a workflow.""" - braintrust.init_logger(project="temporal-example") - - client: Client = await Client.connect( - "localhost:7233", - plugins=[BraintrustPlugin()], - ) - - input_data = TaskInput(value=5) - workflow_id = f"simple-workflow-{uuid.uuid4().hex[:8]}" - - print(f"Starting workflow with value: {input_data.value}") - print(f"Workflow ID: {workflow_id}") - - # Start a span for the client call - with braintrust.start_span(name="example.temporal.workflow") as span: - # Start the workflow (non-blocking) - handle = await client.start_workflow( - SimpleWorkflow.run, - input_data, - id=workflow_id, - task_queue=TASK_QUEUE_NAME, - ) - - # Optionally send a signal if --signal argument is provided - if "--signal" in sys.argv: - signal_value = 100 - print(f"\nSending signal with value: {signal_value}") - await handle.signal(SimpleWorkflow.add_signal_value, signal_value) - - # Wait for workflow to complete - result = await handle.result() - - span.log(output=result) - print(f"\nResult: {result}") - print(f"\nView trace: {span.permalink()}") - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/py/examples/temporal/worker.py b/py/examples/temporal/worker.py deleted file mode 100644 index 631d6c218..000000000 --- a/py/examples/temporal/worker.py +++ /dev/null @@ -1,54 +0,0 @@ -import asyncio -import os - -from braintrust.contrib.temporal import BraintrustPlugin - -# Import only what we need to avoid loading optional dependencies -from braintrust.logger import init_logger - -# Initialize logger at module level before importing plugin -init_logger(project="temporal-example") - -from temporalio.client import Client -from temporalio.worker import Worker -from workflow import ( - TASK_QUEUE_NAME, - ChildWorkflow, - SimpleWorkflow, - add_ten, - add_three_local, - cube, - divide_by_two_with_retry, - multiply_by_two, - square, - subtract_five, -) - - -async def main() -> None: - worker_id = f"pid-{os.getpid()}" - - client: Client = await Client.connect("localhost:7233") - - worker: Worker = Worker( - client, - task_queue=TASK_QUEUE_NAME, - workflows=[SimpleWorkflow, ChildWorkflow], - activities=[ - add_ten, - multiply_by_two, - subtract_five, - add_three_local, - divide_by_two_with_retry, - square, - cube, - ], - plugins=[BraintrustPlugin()], - ) - - print(f"{worker_id} started on task queue: {TASK_QUEUE_NAME}") - await worker.run() - - -if __name__ == "__main__": - asyncio.run(main()) diff --git a/py/examples/temporal/workflow.py b/py/examples/temporal/workflow.py deleted file mode 100644 index db64a679d..000000000 --- a/py/examples/temporal/workflow.py +++ /dev/null @@ -1,252 +0,0 @@ -import asyncio -import os -from dataclasses import dataclass -from datetime import timedelta - -import braintrust -from temporalio import activity, workflow -from temporalio.common import RetryPolicy - -TASK_QUEUE_NAME = "braintrust-example-task-queue" - - -@dataclass -class TaskInput: - value: int - - -@activity.defn -async def add_ten(input: TaskInput) -> int: - worker_id = f"pid-{os.getpid()}" - print(f"[{worker_id}] Adding 10 to {input.value}") - - # Sleep to simulate realistic work - await asyncio.sleep(0.5) - - # Create child span within activity to test nested tracing - with braintrust.start_span(name="validate_input", type="task") as span: - span.log(input={"value": input.value, "operation": "add_ten"}) - await asyncio.sleep(0.2) - - result = input.value + 10 - print(f"[{worker_id}] Result: {input.value} + 10 = {result}") - return result - - -@activity.defn -async def multiply_by_two(input: TaskInput) -> int: - worker_id = f"pid-{os.getpid()}" - print(f"[{worker_id}] Multiplying {input.value} by 2") - - # Sleep to simulate realistic work - await asyncio.sleep(0.3) - - # Create child span to demonstrate nested tracing - with braintrust.start_span(name="perform_multiplication", type="task") as span: - span.log(input={"value": input.value, "multiplier": 2}) - await asyncio.sleep(0.2) - result = input.value * 2 - span.log(output={"result": result}) - - print(f"[{worker_id}] Result: {input.value} * 2 = {result}") - return result - - -@activity.defn -async def subtract_five(input: TaskInput) -> int: - worker_id = f"pid-{os.getpid()}" - print(f"[{worker_id}] Subtracting 5 from {input.value}") - - # Sleep to simulate realistic work - await asyncio.sleep(0.3) - - result = input.value - 5 - print(f"[{worker_id}] Result: {input.value} - 5 = {result}") - return result - - -# Local activity - runs in the same worker process as the workflow -@activity.defn -async def add_three_local(input: TaskInput) -> int: - worker_id = f"pid-{os.getpid()}" - print(f"[{worker_id}] [LOCAL] Adding 3 to {input.value}") - - # Sleep to simulate realistic work (local activities are typically faster) - await asyncio.sleep(0.1) - - # Create child span to verify local activity tracing works - with braintrust.start_span(name="local_calculation", type="task") as span: - span.log(input={"value": input.value, "operation": "add_three_local"}) - await asyncio.sleep(0.05) - result = input.value + 3 - span.log(output={"result": result}) - - print(f"[{worker_id}] [LOCAL] Result: {input.value} + 3 = {result}") - return result - - -# Activity with retry logic - fails first time, succeeds on retry -_divide_attempt_count = {} - - -@activity.defn -async def divide_by_two_with_retry(input: TaskInput) -> int: - worker_id = f"pid-{os.getpid()}" - activity_id = activity.info().activity_id - - # Track attempts per activity_id - if activity_id not in _divide_attempt_count: - _divide_attempt_count[activity_id] = 0 - _divide_attempt_count[activity_id] += 1 - - attempt = _divide_attempt_count[activity_id] - print(f"[{worker_id}] Attempt {attempt}: Dividing {input.value} by 2") - - # Sleep to simulate work - await asyncio.sleep(0.4) - - # Fail on first attempt to test retry tracing - if attempt == 1: - raise ValueError("Simulated error for retry testing") - - result = input.value // 2 - print(f"[{worker_id}] Result: {input.value} / 2 = {result}") - return result - - -# Parallel activities for testing concurrent execution -@activity.defn -async def square(input: TaskInput) -> int: - worker_id = f"pid-{os.getpid()}" - print(f"[{worker_id}] Squaring {input.value}") - - # Sleep to simulate work - should run in parallel with cube - await asyncio.sleep(0.6) - - result = input.value * input.value - print(f"[{worker_id}] Result: {input.value}^2 = {result}") - return result - - -@activity.defn -async def cube(input: TaskInput) -> int: - worker_id = f"pid-{os.getpid()}" - print(f"[{worker_id}] Cubing {input.value}") - - # Sleep to simulate work - should run in parallel with square - await asyncio.sleep(0.7) - - result = input.value * input.value * input.value - print(f"[{worker_id}] Result: {input.value}^3 = {result}") - return result - - -# Child workflow for testing nested workflow tracing -@workflow.defn -class ChildWorkflow: - @workflow.run - async def run(self, input: TaskInput) -> int: - workflow.logger.info(f"Child workflow processing: {input.value}") - - # Simple operation in child workflow - result = await workflow.execute_activity( - subtract_five, - input, - start_to_close_timeout=timedelta(seconds=10), - ) - - workflow.logger.info(f"Child workflow result: {result}") - return result - - -@workflow.defn -class SimpleWorkflow: - def __init__(self) -> None: - self._signal_value = 0 - - @workflow.signal - def add_signal_value(self, value: int) -> None: - """Signal handler for testing signal tracing.""" - workflow.logger.info(f"Received signal with value: {value}") - self._signal_value += value - - @workflow.run - async def run(self, input: TaskInput) -> str: - workflow.logger.info(f"Starting workflow with value: {input.value}") - - with braintrust.start_span(name="manual.workflow.span") as span: - pass - - # Step 1: Add 10 - step1 = await workflow.execute_activity( - add_ten, - input, - start_to_close_timeout=timedelta(seconds=10), - ) - workflow.logger.info(f"After step 1: {step1}") - - # Step 2: Multiply by 2 - step2 = await workflow.execute_activity( - multiply_by_two, - TaskInput(value=step1), - start_to_close_timeout=timedelta(seconds=10), - ) - workflow.logger.info(f"After step 2: {step2}") - - # Step 2.5: Local activity (fast operation in same worker) - workflow.logger.info("Executing local activity") - step2_5 = await workflow.execute_local_activity( - add_three_local, - TaskInput(value=step2), - start_to_close_timeout=timedelta(seconds=5), - ) - workflow.logger.info(f"After local activity: {step2_5}") - - # Step 3: Parallel activities (square and cube) - workflow.logger.info("Executing parallel activities") - square_result, cube_result = await asyncio.gather( - workflow.execute_activity( - square, - TaskInput(value=step2), - start_to_close_timeout=timedelta(seconds=10), - ), - workflow.execute_activity( - cube, - TaskInput(value=step2), - start_to_close_timeout=timedelta(seconds=10), - ), - ) - workflow.logger.info(f"Parallel results: square={square_result}, cube={cube_result}") - - # Step 4: Activity with retry - workflow.logger.info("Executing activity with retry") - step4 = await workflow.execute_activity( - divide_by_two_with_retry, - TaskInput(value=step2), - start_to_close_timeout=timedelta(seconds=10), - retry_policy=RetryPolicy( - maximum_attempts=3, - initial_interval=timedelta(seconds=1), - ), - ) - workflow.logger.info(f"After retry activity: {step4}") - - # Step 5: Child workflow - workflow.logger.info("Starting child workflow") - child_result = await workflow.execute_child_workflow( - ChildWorkflow.run, - TaskInput(value=step4), - id=f"child-{workflow.info().workflow_id}", - task_queue=TASK_QUEUE_NAME, - ) - workflow.logger.info(f"Child workflow result: {child_result}") - - # Include signal value in result - final_result = ( - f"Complete: {input.value} -> +10={step1} -> *2={step2} -> " - f"+3(local)={step2_5} -> parallel(^2={square_result}, ^3={cube_result}) -> " - f"/2={step4} -> child(-5={child_result}) + signal({self._signal_value}) = " - f"{child_result + self._signal_value}" - ) - workflow.logger.info(final_result) - return final_result diff --git a/py/noxfile.py b/py/noxfile.py deleted file mode 100644 index ddc1ee114..000000000 --- a/py/noxfile.py +++ /dev/null @@ -1,405 +0,0 @@ -""" -Nox scripts the environment our tests run in and it used to verify our library -works with and without different dependencies. A few commands to check out: - - nox Run all sessions. - nox -l List all sessions. - nox -s Run a specific session. - nox ... -- --no-vcr Run tests without vcrpy. - nox ... -- --wheel Run tests against the wheel in dist. - nox -h Get help. -""" - -import glob -import os -import sys -import tempfile - -import nox - -# much faster than pip -nox.options.default_venv_backend = "uv" - -SRC_DIR = "braintrust" -WRAPPER_DIR = "braintrust/wrappers" -CONTRIB_DIR = "braintrust/contrib" -DEVSERVER_DIR = "braintrust/devserver" - - -SILENT_INSTALLS = True -LATEST = "latest" -ERROR_CODES = tuple(range(1, 256)) - - -# The minimal set of dependencies we need to run tests. -BASE_TEST_DEPS = ("pytest", "pytest-asyncio", "pytest-vcr") - -# List your package here if it's not guaranteed to be installed. We'll (try to) -# validate things work with or without them. -VENDOR_PACKAGES = ( - "agno", - "anthropic", - "dspy", - "openai", - "openai-agents", - # pydantic_ai is NOT included here - it has dedicated test sessions with version-specific handling - "autoevals", - "braintrust_core", - "litellm", - "opentelemetry-api", - "opentelemetry-sdk", - "opentelemetry-exporter-otlp-proto-http", - "google.genai", - "temporalio", -) - -# Test matrix -ANTHROPIC_VERSIONS = (LATEST, "0.50.0", "0.49.0", "0.48.0") -OPENAI_VERSIONS = (LATEST, "1.77.0", "1.71", "1.91", "1.92") -# litellm latest requires Python >= 3.10 -LITELLM_VERSIONS = (LATEST, "1.74.0") -# CLI bundling started in 0.1.10 - older versions require external Claude Code installation -CLAUDE_AGENT_SDK_VERSIONS = (LATEST, "0.1.10") -AGNO_VERSIONS = (LATEST, "2.1.0") -# pydantic_ai 1.x requires Python >= 3.10 -# Two test suites with different version requirements: -# 1. wrap_openai approach: works with older versions (0.1.9+) -# 2. Direct wrapper (setup_pydantic_ai): requires 1.10.0+ for all features -PYDANTIC_AI_WRAP_OPENAI_VERSIONS = (LATEST, "1.0.1", "0.1.9") -PYDANTIC_AI_INTEGRATION_VERSIONS = (LATEST, "1.10.0") - -AUTOEVALS_VERSIONS = (LATEST, "0.0.129") -GENAI_VERSIONS = (LATEST,) -DSPY_VERSIONS = (LATEST,) -# temporalio 1.19.0+ requires Python >= 3.10; skip Python 3.9 entirely -TEMPORAL_VERSIONS = (LATEST, "1.20.0", "1.19.0") - - -@nox.session() -def test_core(session): - _install_test_deps(session) - # verify we haven't installed our 3p deps. - for p in VENDOR_PACKAGES: - session.run("python", "-c", f"import {p}", success_codes=ERROR_CODES, silent=True) - _run_core_tests(session) - - -@nox.session() -@nox.parametrize("version", PYDANTIC_AI_WRAP_OPENAI_VERSIONS, ids=PYDANTIC_AI_WRAP_OPENAI_VERSIONS) -def test_pydantic_ai_wrap_openai(session, version): - """Test pydantic_ai with wrap_openai() approach - supports older versions.""" - _install_test_deps(session) - _install(session, "pydantic_ai", version) - _run_tests(session, f"{WRAPPER_DIR}/test_pydantic_ai_wrap_openai.py") - _run_core_tests(session) - - -@nox.session() -@nox.parametrize("version", PYDANTIC_AI_INTEGRATION_VERSIONS, ids=PYDANTIC_AI_INTEGRATION_VERSIONS) -def test_pydantic_ai_integration(session, version): - """Test pydantic_ai with setup_pydantic_ai() wrapper - requires 1.10.0+.""" - # Skip on Python 3.9 - pydantic_ai 1.10.0+ requires Python 3.10+ - if sys.version_info < (3, 10): - session.skip("pydantic_ai integration tests require Python >= 3.10 (pydantic_ai 1.10.0+)") - _install_test_deps(session) - _install(session, "pydantic_ai", version) - _run_tests(session, f"{WRAPPER_DIR}/test_pydantic_ai_integration.py") - _run_core_tests(session) - - -@nox.session() -def test_pydantic_ai_logfire(session): - """Test pydantic_ai + logfire coexistence (issue #1324).""" - if sys.version_info < (3, 10): - session.skip("pydantic_ai + logfire tests require Python >= 3.10") - _install_test_deps(session) - _install(session, "pydantic_ai") - _install(session, "logfire") - _run_tests(session, f"{WRAPPER_DIR}/test_pydantic_ai_logfire.py") - - -@nox.session() -@nox.parametrize("version", CLAUDE_AGENT_SDK_VERSIONS, ids=CLAUDE_AGENT_SDK_VERSIONS) -def test_claude_agent_sdk(session, version): - # claude_agent_sdk requires Python >= 3.10 - _install_test_deps(session) - _install(session, "claude_agent_sdk", version) - _run_tests(session, f"{WRAPPER_DIR}/claude_agent_sdk/test_wrapper.py") - _run_core_tests(session) - - -@nox.session() -@nox.parametrize("version", AGNO_VERSIONS, ids=AGNO_VERSIONS) -def test_agno(session, version): - _install_test_deps(session) - _install(session, "agno", version) - _install(session, "openai") # Required for agno.models.openai - _run_tests(session, f"{WRAPPER_DIR}/test_agno.py") - _run_core_tests(session) - - -@nox.session() -@nox.parametrize("version", ANTHROPIC_VERSIONS, ids=ANTHROPIC_VERSIONS) -def test_anthropic(session, version): - _install_test_deps(session) - _install(session, "anthropic", version) - _run_tests(session, f"{WRAPPER_DIR}/test_anthropic.py") - _run_core_tests(session) - - -@nox.session() -@nox.parametrize("version", GENAI_VERSIONS, ids=GENAI_VERSIONS) -def test_google_genai(session, version): - _install_test_deps(session) - _install(session, "google-genai", version) - _run_tests(session, f"{WRAPPER_DIR}/test_google_genai.py") - _run_core_tests(session) - - -@nox.session() -@nox.parametrize("version", OPENAI_VERSIONS, ids=OPENAI_VERSIONS) -def test_openai(session, version): - _install_test_deps(session) - _install(session, "openai", version) - # openai-agents requires Python >= 3.10 - _install(session, "openai-agents") - _run_tests(session, f"{WRAPPER_DIR}/test_openai.py") - _run_core_tests(session) - - -@nox.session() -def test_openrouter(session): - """Test wrap_openai with OpenRouter. Requires OPENROUTER_API_KEY env var.""" - _install_test_deps(session) - _install(session, "openai") - _run_tests(session, f"{WRAPPER_DIR}/test_openrouter.py") - - -@nox.session() -@nox.parametrize("version", LITELLM_VERSIONS, ids=LITELLM_VERSIONS) -def test_litellm(session, version): - # litellm latest requires Python >= 3.10 - if version == LATEST and sys.version_info < (3, 10): - session.skip("litellm latest requires Python >= 3.10") - _install_test_deps(session) - # Install a compatible version of openai (1.99.9 or lower) to avoid the ResponseTextConfig removal in 1.100.0 - # https://github.com/BerriAI/litellm/issues/13711 - # Install fastapi and orjson as they're required by litellm for proxy/responses operations - session.install("openai<=1.99.9", "--force-reinstall", "fastapi", "orjson") - _install(session, "litellm", version) - _run_tests(session, f"{WRAPPER_DIR}/test_litellm.py") - _run_core_tests(session) - - -@nox.session() -@nox.parametrize("version", DSPY_VERSIONS, ids=DSPY_VERSIONS) -def test_dspy(session, version): - # dspy latest depends on litellm which requires Python >= 3.10 - if sys.version_info < (3, 10): - session.skip("dspy latest requires Python >= 3.10 (litellm dependency)") - _install_test_deps(session) - _install(session, "dspy", version) - _run_tests(session, f"{WRAPPER_DIR}/test_dspy.py") - - -@nox.session() -@nox.parametrize("version", AUTOEVALS_VERSIONS, ids=AUTOEVALS_VERSIONS) -def test_autoevals(session, version): - # Run all of our core tests with autoevals installed. Some tests - # specifically validate scores from autoevals work properly, so - # we need some tests with it installed. - _install_test_deps(session) - _install(session, "autoevals", version) - _run_core_tests(session) - - -@nox.session() -def test_braintrust_core(session): - # Some tests do specific things if braintrust_core is installed, so run our - # common tests with it installed. Testing the latest (aka the last ever version) - # is enough. - _install_test_deps(session) - _install(session, "braintrust_core") - _run_core_tests(session) - - -@nox.session() -def test_cli(session): - """Test CLI/devserver with starlette installed.""" - _install_test_deps(session) - session.install(".[cli]") - session.install("httpx") # Required for starlette.testclient - _run_tests(session, "braintrust/devserver/test_server_integration.py") - - -@nox.session() -def test_otel(session): - """Test OtelExporter with OpenTelemetry installed.""" - _install_test_deps(session) - session.install(".[otel]") - _run_tests(session, "braintrust/test_otel.py") - - -@nox.session() -@nox.parametrize("version", TEMPORAL_VERSIONS, ids=TEMPORAL_VERSIONS) -def test_temporal(session, version): - """Test Temporal integration with temporalio installed.""" - # temporalio 1.19.0+ requires Python >= 3.10 - if sys.version_info < (3, 10): - session.skip("temporalio 1.19.0+ requires Python >= 3.10") - _install_test_deps(session) - _install(session, "temporalio", version) - _run_tests(session, "braintrust/contrib/temporal") - - -@nox.session() -def test_otel_not_installed(session): - _install_test_deps(session) - otel_packages = ["opentelemetry", "opentelemetry.trace", "opentelemetry.exporter.otlp.proto.http.trace_exporter"] - for pkg in otel_packages: - session.run("python", "-c", f"import {pkg}", success_codes=ERROR_CODES, silent=True) - _run_tests(session, "braintrust/test_otel.py") - - -@nox.session() -def pylint(session): - # pylint needs everything so we don't trigger missing import errors - # Skip on Python < 3.10 because some deps (like temporalio 1.19+) require 3.10+ - if sys.version_info < (3, 10): - session.skip("pylint requires Python >= 3.10 for full dependency support") - session.install(".[all]") - session.install("-r", "requirements-dev.txt") - session.install(*VENDOR_PACKAGES) - # pydantic_ai is not in VENDOR_PACKAGES (has dedicated test sessions), - # but pylint needs it with minimum version constraint for proper API checking - session.install("pydantic_ai>=1.10.0") - session.install("opentelemetry.instrumentation.openai") - # langsmith is needed for the wrapper module but not in VENDOR_PACKAGES - session.install("langsmith") - - result = session.run("git", "ls-files", "**/*.py", silent=True, log=False) - files = result.strip().splitlines() - if not files: - return - session.run("pylint", "--errors-only", *files) - - -@nox.session() -def test_latest_wrappers_novcr(session): - """Run the latest wrapper tests without vcrpy.""" - # every test run we hit openai, anthropic, at least once so we balance CI speed (with vcrpy) - # with testing reality. - args = session.posargs.copy() - if "--disable-vcr" not in args: - args.append("--disable-vcr") - session.notify("test_openai(latest)", posargs=args) - session.notify("test_anthropic(latest)", posargs=args) - session.notify("test_pydantic_ai_wrap_openai(latest)", posargs=args) - session.notify("test_pydantic_ai_integration(latest)", posargs=args) - session.notify("test_claude_agent_sdk(latest)", posargs=args) - - -def _install_npm_in_session(session): - """Install Node.js and npm in the nox session using nodeenv.""" - session.install("nodeenv", silent=SILENT_INSTALLS) - # Create a node environment in the session's temporary directory - node_dir = os.path.join(session.create_tmp(), "node_env") - session.run("nodeenv", node_dir, silent=SILENT_INSTALLS) - # Return the path to npm binary for direct use - if sys.platform == "win32": - npm_bin = os.path.join(node_dir, "Scripts", "npm.cmd") - else: - npm_bin = os.path.join(node_dir, "bin", "npm") - return npm_bin - - -def _install_test_deps(session): - # Choose the way we'll install braintrust ... wheel or source. - install_wheel = "--wheel" in session.posargs - bt = _get_braintrust_wheel() if install_wheel else "." - - # Install _only_ the dependencies we need for testing (not lint, black, - # ipython, whatever). We want to carefully control the base - # testing environment so it should be truly minimal. - session.install(bt, *BASE_TEST_DEPS) - - # Sanity check we have installed braintrust (and that it is from a wheel if needed) - session.run("python", "-c", "import braintrust") - if install_wheel: - lines = [ - "import sys, braintrust as b", - "print(f'Using braintrust from: {b.__file__}')", - "sys.exit(0 if 'site-packages' in b.__file__ else 1)", - ] - session.run("python", "-c", ";".join(lines)) - - -def _get_braintrust_wheel(): - path = "dist/braintrust-*.whl" - wheels = glob.glob(path) - if len(wheels) != 1: - msg = f"There should be one wheel in {path}. Got {len(wheels)}" - raise Exception(msg) - return wheels[0] - - -def _run_core_tests(session): - """Run all tests which don't require optional dependencies.""" - _run_tests(session, SRC_DIR, ignore_paths=[WRAPPER_DIR, CONTRIB_DIR, DEVSERVER_DIR]) - - -def _run_tests(session, test_path, ignore_path="", ignore_paths=None, env=None): - """Run tests against a wheel or the source code. Paths should be relative and start with braintrust.""" - env = env.copy() if env else {} - wheel_flag = "--wheel" in session.posargs - common_args = ["--disable-vcr"] if "--disable-vcr" in session.posargs else [] - - # Support both ignore_path (for backward compatibility) and ignore_paths - paths_to_ignore = [] - if ignore_path: - paths_to_ignore.append(ignore_path) - if ignore_paths: - paths_to_ignore.extend(ignore_paths) - - if not wheel_flag: - # Run the tests in the src directory - test_args = [ - "pytest", - f"src/{test_path}", - ] - for path in paths_to_ignore: - test_args.append(f"--ignore=src/{path}") - session.run(*test_args, *common_args, env=env) - return - - # Running the tests from the wheel involves a bit of gymnastics to ensure we don't import - # local modules from the source directory. - # First, we need to absolute paths to all the binaries and libs in our venv that we'll see. - py = os.path.join(session.bin, "python") - site_packages = session.run(py, "-c", "import site; print(site.getsitepackages()[0])", silent=True).strip() - abs_test_path = os.path.abspath(os.path.join(site_packages, test_path)) - pytest_path = os.path.join(session.bin, "pytest") - - ignore_args = [] - for path in paths_to_ignore: - abs_ignore_path = os.path.abspath(os.path.join(site_packages, path)) - ignore_args.append(f"--ignore={abs_ignore_path}") - - # Lastly, change to a different directory to ensure we don't install local stuff. - with tempfile.TemporaryDirectory() as tmp: - os.chdir(tmp) - # This env var is used to detect if we're running from the wheel. - # It proved very helpful because it's very easy - # to accidentally import local modules from the source directory. - env["BRAINTRUST_TESTING_WHEEL"] = "1" - session.run(pytest_path, abs_test_path, *ignore_args, *common_args, env=env) - - # And a final note ... if it's not clear from above, we include test files in our wheel, which - # is perhaps not ideal? - - -def _install(session, package, version=LATEST): - pkg_version = f"{package}=={version}" - if version == LATEST or not version: - pkg_version = package - session.install(pkg_version, silent=SILENT_INSTALLS) diff --git a/py/requirements-build.txt b/py/requirements-build.txt deleted file mode 100644 index 9846b0b07..000000000 --- a/py/requirements-build.txt +++ /dev/null @@ -1,3 +0,0 @@ -# Build and packaging tools with pinned versions for reproducible builds -build==1.2.2.post1 -setuptools==80.7.1 diff --git a/py/requirements-dev.txt b/py/requirements-dev.txt deleted file mode 100644 index 48020b85a..000000000 --- a/py/requirements-dev.txt +++ /dev/null @@ -1,16 +0,0 @@ -# Also include build dependencies -black -datamodel-code-generator>=0.53.0 -flake8 -flake8-isort -isort==5.12.0 -nox -pre-commit -pydoc-markdown -pylint -pytest -pytest-asyncio -pytest-forked -pytest-vcr - --r requirements-build.txt diff --git a/py/scripts/generate_types.py b/py/scripts/generate_types.py deleted file mode 100755 index dcaa9e40b..000000000 --- a/py/scripts/generate_types.py +++ /dev/null @@ -1,117 +0,0 @@ -#!/usr/bin/env python3 - -import json -import os -import re -import subprocess -import sys - -SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__)) -OPENAPI_SPEC_PATH = os.path.join(SCRIPT_DIR, "../../generated_types.json") -INTERNAL_TYPES_OUTPUT_PATH = os.path.join(SCRIPT_DIR, "../src/braintrust/_generated_types.py") - - -def generate_internal_types(): - subprocess.run( - [ - "datamodel-codegen", - "--input", - OPENAPI_SPEC_PATH, - "--input-file-type", - "openapi", - "--output", - INTERNAL_TYPES_OUTPUT_PATH, - "--output-model-type", - "typing.TypedDict", - "--target-python-version", - "3.10", - "--use-union-operator", - "--custom-file-header", - '''""" -Do not import this file directly. See `generated_types.py` for the classes that have a stable API. - -Auto-generated file -- do not modify. -"""''', - "--special-field-name-prefix", - "", - "--enum-field-as-literal", - "all", - "--capitalize-enum-members", - "--use-generic-container-types", - "--use-field-description", - "--strict-nullable", - "--parent-scoped-naming", - "--no-use-closed-typed-dict", - ], - stdout=sys.stderr, - check=True, - ) - cleanup_internal_types() - - -def cleanup_internal_types(): - with open(INTERNAL_TYPES_OUTPUT_PATH, "r") as f: - contents = f.read() - - # Add `| None` to `NotRequired[...]` fields that aren't already nullable. - # - # This weakens optional-but-not-nullable OpenAPI types into - # optional-and-nullable TypedDicts. But this seems better than having - # optional-and-nullable OpenAPI types converted into - # optional-but-not-nullable TypedDicts. - contents = re.sub( - r"(\s[A-Za-z0-9_]+: NotRequired\[)(.+?)(\])\n", - lambda m: m.group(0) if m.group(2).rstrip().endswith("None") else f"{m.group(1)}{m.group(2)} | None{m.group(3)}\n", - contents, - ) - - # Replace `schema_` with `schema`; this happens because datamodel-codegen - # treats `schema` specially, expecting Pydantic. - contents = re.sub(r"(\s+)schema_:", r"\1schema:", contents) - - # Discourage direct imports. - contents += "\n__all__ = []" - - with open(INTERNAL_TYPES_OUTPUT_PATH, "w") as f: - f.write(contents) - - -def get_public_typenames() -> list[str]: - with open(OPENAPI_SPEC_PATH, "r") as f: - data = json.load(f) - ret = list(data["components"]["schemas"].keys()) - ret.sort() - return ret - - -def generate_public_types(): - public_types_output_path = os.path.join(SCRIPT_DIR, "../src/braintrust/generated_types.py") - public_typenames = get_public_typenames() - - with open(OPENAPI_SPEC_PATH, "r") as f: - openapi_spec = json.load(f) - internal_git_sha = openapi_spec.get("info", {}).get("x-internal-git-sha", "unknown") - - with open(public_types_output_path, "w") as f: - f.write( - f'''"""Auto-generated file (internal git SHA {internal_git_sha}) -- do not modify""" - -from ._generated_types import (''' - ) - for typename in public_typenames: - f.write(f"\n {typename},") - f.write("\n)") - - f.write( - """ - -__all__ = [""" - ) - for typename in public_typenames: - f.write(f'\n "{typename}",') - f.write("\n]") - - -if __name__ == "__main__": - generate_internal_types() - generate_public_types() diff --git a/py/scripts/get_version.sh b/py/scripts/get_version.sh deleted file mode 100755 index 51c0149eb..000000000 --- a/py/scripts/get_version.sh +++ /dev/null @@ -1,13 +0,0 @@ -#!/bin/bash -# Script to extract and print the version number from version.py - - -ROOT_DIR=$(git rev-parse --show-toplevel) - -VERSION_FILE="$ROOT_DIR/py/src/braintrust/version.py" - -# Extract the version using grep and cut -VERSION=$(grep -E '^VERSION\s*=' "$VERSION_FILE" | grep -o '".*"' | tr -d '"') - -# Print the version -echo "$VERSION" diff --git a/py/scripts/nox-matrix.sh b/py/scripts/nox-matrix.sh deleted file mode 100755 index 337297ea7..000000000 --- a/py/scripts/nox-matrix.sh +++ /dev/null @@ -1,68 +0,0 @@ -#!/bin/bash -# -# This is a very crude script to parallelize nox sessions into groups. -# It's used to run the nox tests in parallel on GitHub Actions. -# -# - -set -euo pipefail - -ROOT_DIR=$(git rev-parse --show-toplevel) -NOXFILE=$ROOT_DIR/py/noxfile.py - -# Parse command line arguments -if [ $# -lt 2 ]; then - echo "Usage: $0 [--dry-run]" - exit 1 -fi - -INDEX=$1 -TOTAL=$2 -DRY_RUN=false -shift 2 -while [[ $# -gt 0 ]]; do - case "$1" in - --dry-run) - DRY_RUN=true - shift - ;; - *) - echo "Unknown option: $1" - echo "Usage: $0 [--dry-run]" - exit 1 - ;; - esac -done - -if [ "$INDEX" -ge "$TOTAL" ]; then - echo "Error: shard_index ($INDEX) must be less than number_of_shards ($TOTAL)" - exit 1 -fi - -# Nox formats the sessions like: -# * test_foo -# * test_bar -> Optional description -# We need to strip the description part after " -> " -all_sessions=$(nox -l -f $NOXFILE | grep "^\* " | cut -c 3- | sed 's/ ->.*$//' | sort) -matches=$(echo "$all_sessions" | awk "NR % $TOTAL == $INDEX") -misses=$(echo "$all_sessions" | awk "NR % $TOTAL != $INDEX") -n_matches=$(echo "$matches" | wc -l | xargs) -n_all=$(echo "$all_sessions" | wc -l | xargs) - -printf "nox matrix idx:%d shards:%d running %d/%d sessions\n" "$INDEX" "$TOTAL" "$n_matches" "$n_all" - -if [ "$DRY_RUN" = true ]; then - echo "--------------------------------" - echo "Would run the following sessions:" - echo "$matches" - echo "" - echo "--------------------------------" - echo "Would skip the following sessions:" - echo "$misses" - exit 0 -fi - -# Build session list and run nox once -# Quote each session name to handle parentheses in names like test_openai(latest) -session_list=$(echo "$matches" | sed 's/.*/"&"/' | tr '\n' ' ') -eval "nox -f $NOXFILE -s $session_list" diff --git a/py/scripts/push-release-tag.sh b/py/scripts/push-release-tag.sh deleted file mode 100755 index 07d543801..000000000 --- a/py/scripts/push-release-tag.sh +++ /dev/null @@ -1,102 +0,0 @@ -#!/bin/bash -set -euo pipefail - -ROOT_DIR=$(git rev-parse --show-toplevel) - -# Parse command line arguments and environment variables -# Support both --flag and ENVVAR=1 syntax -DRY_RUN=${DRY_RUN:-false} -FORCE=${FORCE:-false} - -# Normalize environment variables (1, true, TRUE -> true) -[[ "$DRY_RUN" == "1" || "$DRY_RUN" == "true" || "$DRY_RUN" == "TRUE" ]] && DRY_RUN=true -[[ "$FORCE" == "1" || "$FORCE" == "true" || "$FORCE" == "TRUE" ]] && FORCE=true - -while [[ $# -gt 0 ]]; do - case "$1" in - --dry-run) - DRY_RUN=true - shift - ;; - --force) - FORCE=true - shift - ;; - *) - echo "Unknown option: $1" - echo "Usage: $0 [--dry-run] [--force]" - exit 1 - ;; - esac -done - -# Fetch latest tags -git fetch --tags --prune - -REPO_URL="https://github.com/braintrustdata/braintrust-sdk" -TAG_PREFIX="py-sdk-v" -COMMIT=$(git rev-parse --short HEAD) -VERSION=$(bash "$ROOT_DIR/py/scripts/get_version.sh") -TAG="${TAG_PREFIX}${VERSION}" - -# Check if version already exists on PyPI when using --force -if [ "$FORCE" = true ]; then - echo "Checking if version ${VERSION} exists on PyPI..." - if curl -s "https://pypi.org/pypi/braintrust/${VERSION}/json" | grep -q "\"version\""; then - echo "" - echo "Error: Version ${VERSION} already exists on PyPI" - echo "Cannot force-replace a tag that has already been published to PyPI" - echo "Please bump the version number instead" - exit 1 - fi - echo "Version ${VERSION} not found on PyPI, safe to proceed" - echo "" -fi - -# Find the most recent version tag for comparison -# If forcing and the tag exists, skip to the previous tag for changeset comparison -if [ "$FORCE" = true ] && git rev-parse "$TAG" >/dev/null 2>&1; then - LAST_RELEASE=$(git tag -l "${TAG_PREFIX}*" --sort=-v:refname | head -n 2 | tail -n 1) -else - LAST_RELEASE=$(git tag -l "${TAG_PREFIX}*" --sort=-v:refname | head -n 1) -fi - -echo "================================================" -echo " Python SDK Release" -echo "================================================" -echo "version: ${TAG}" -echo "commit: ${COMMIT}" -echo "code: ${REPO_URL}/commit/${COMMIT}" -echo "changeset: ${REPO_URL}/compare/${LAST_RELEASE}...${COMMIT}" - -if [ "$DRY_RUN" = true ]; then - exit 0 -fi - -echo "" -echo "" -echo "Are you ready to release version ${VERSION}? Type 'YOLO' to continue:" -read -r CONFIRMATION - -if [ "$CONFIRMATION" != "YOLO" ]; then - echo "Release cancelled." - exit 1 -fi - -# Create and push the tag -echo "" -echo "Creating and pushing tag ${TAG}" -echo "" - -if [ "$FORCE" = true ]; then - git tag -f "$TAG" "$COMMIT" - git push --force origin "$TAG" -else - git tag "$TAG" "$COMMIT" - git push origin "$TAG" -fi - -echo "" -echo "Tag ${TAG} has been created and pushed to origin. Check GitHub Actions for build progress:" -echo "https://github.com/braintrustdata/braintrust-sdk/actions/workflows/publish-py-sdk.yaml" -echo "" diff --git a/py/scripts/template-version.sh b/py/scripts/template-version.sh deleted file mode 100755 index f419ee742..000000000 --- a/py/scripts/template-version.sh +++ /dev/null @@ -1,28 +0,0 @@ -#!/usr/bin/env bash - -set -e - -VERSION_FILE="src/braintrust/version.py" - -GIT_COMMIT=$(git rev-parse HEAD) - -sed_inplace() { - if [[ "$OSTYPE" == "darwin"* ]]; then - sed -i '' "$@" - else - sed -i "$@" - fi -} - -# Update git commit hash -sed_inplace "s/__GIT_COMMIT__/$GIT_COMMIT/g" "$VERSION_FILE" - -# Get current version -CURRENT_VERSION=$(grep 'VERSION = ' "$VERSION_FILE" | cut -d'"' -f2) - -# If we're uploading to testpypi, add a run number to the version so we can -# test multiple times. -if [[ "$PYPI_REPO" == "testpypi" ]] && [[ -n "$GITHUB_RUN_NUMBER" ]]; then - NEW_VERSION="${CURRENT_VERSION}rc${GITHUB_RUN_NUMBER}" - sed_inplace "s/VERSION = \".*\"/VERSION = \"$NEW_VERSION\"/" "$VERSION_FILE" -fi diff --git a/py/scripts/validate-release-tag.sh b/py/scripts/validate-release-tag.sh deleted file mode 100755 index 246872f82..000000000 --- a/py/scripts/validate-release-tag.sh +++ /dev/null @@ -1,61 +0,0 @@ -#!/bin/bash -# Script to validate release requirements -# - Checks if the tag matches the version in the package -# - Ensures we're releasing from the main branch - -set -e - -# Get the tag from the first command line argument -if [ $# -eq 0 ]; then - echo "ERROR: Release tag argument not provided" - echo "Usage: $0 " - exit 1 -fi - -ROOT_DIR=$(git rev-parse --show-toplevel) - -# Fetch the latest tags to ensure we're up to date -git fetch --tags --prune --force - -TAG=$1 - -# Check if tag starts with py-sdk-v -if [[ ! "$TAG" =~ ^py-sdk-v ]]; then - echo "ERROR: Tag must start with 'py-sdk-v'" - exit 1 -fi - -# Extract version without the 'py-sdk-v' prefix -VERSION=${TAG#py-sdk-v} - -PACKAGE_VERSION=$(bash "$ROOT_DIR/py/scripts/get_version.sh") - -# Check if the tag version matches the package version -if [ "$VERSION" != "$PACKAGE_VERSION" ]; then - echo "ERROR: Tag version ($VERSION) does not match package version ($PACKAGE_VERSION)" - exit 1 -fi - -CURRENT_BRANCH=$(git rev-parse --abbrev-ref HEAD) -if [ "$CURRENT_BRANCH" != "main" ]; then - # If we're in detached HEAD state (which is likely in GitHub Actions with a tag), - # we need to check if the tag is on the main branch - if ! git rev-parse "$TAG" &>/dev/null; then - echo "ERROR: Tag $TAG does not exist in the repository" - exit 1 - fi - - TAG_COMMIT=$(git rev-parse "$TAG") - - # Ensure we have main branch history - git fetch origin main --depth=1000 - - # Check if tag is on main branch - if ! git merge-base --is-ancestor "$TAG_COMMIT" origin/main; then - echo "ERROR: Tag $TAG is not on the main branch" - exit 1 - fi -fi - -# All checks passed -exit 0 diff --git a/py/setup.py b/py/setup.py deleted file mode 100644 index cd95c2570..000000000 --- a/py/setup.py +++ /dev/null @@ -1,62 +0,0 @@ -import os - -import setuptools - -dir_name = os.path.abspath(os.path.dirname(__file__)) - -version_contents = {} -with open(os.path.join(dir_name, "src", "braintrust", "version.py"), encoding="utf-8") as f: - exec(f.read(), version_contents) - -with open(os.path.join(dir_name, "README.md"), "r", encoding="utf-8") as f: - long_description = f.read() - -install_requires = [ - "GitPython", - "requests", - "chevron", - "tqdm", - "exceptiongroup>=1.2.0", - "python-dotenv", - "sseclient-py", - "python-slugify", - "typing_extensions>=4.1.0", - "wrapt", -] - -extras_require = { - "cli": ["boto3", "psycopg2-binary", "uv", "starlette", "uvicorn"], - "doc": ["pydoc-markdown"], - "openai-agents": ["openai-agents"], - "otel": ["opentelemetry-api", "opentelemetry-sdk", "opentelemetry-exporter-otlp-proto-http"], - "temporal": ["temporalio>=1.19.0; python_version>='3.10'"], -} - -extras_require["all"] = sorted({package for packages in extras_require.values() for package in packages}) - -setuptools.setup( - name="braintrust", - version=version_contents["VERSION"], - author="Braintrust", - author_email="info@braintrust.dev", - description="SDK for integrating Braintrust", - long_description=long_description, - long_description_content_type="text/markdown", - url="https://www.braintrust.dev", - project_urls={ - "Source Code": "https://github.com/braintrustdata/braintrust-sdk", - "Bug Tracker": "https://github.com/braintrustdata/braintrust-sdk/issues", - }, - classifiers=[ - "Programming Language :: Python :: 3", - "Programming Language :: Python :: 3.10", - "Operating System :: OS Independent", - ], - package_dir={"": "src"}, - packages=setuptools.find_packages(where="src"), - package_data={"braintrust": ["py.typed"]}, - python_requires=">=3.10.0", - entry_points={"console_scripts": ["braintrust = braintrust.cli.__main__:main"]}, - install_requires=install_requires, - extras_require=extras_require, -) diff --git a/py/src/braintrust/__init__.py b/py/src/braintrust/__init__.py deleted file mode 100644 index a0c91ad89..000000000 --- a/py/src/braintrust/__init__.py +++ /dev/null @@ -1,93 +0,0 @@ -# pyright: reportUnusedImport=false -""" -A Python library for interacting with [Braintrust](https://braintrust.dev/). This library -contains functionality for running evaluations, logging completions, loading and invoking -functions, and more. - -`braintrust` is distributed as a [library on PyPI](https://pypi.org/project/braintrust/). It is open source and -[available on GitHub](https://github.com/braintrustdata/braintrust-sdk/tree/main/py). - -### Quickstart - -Install the library with pip. - -```bash -pip install braintrust -``` - -Then, create a file like `eval_hello.py` with the following content: - -```python -from braintrust import Eval - -def is_equal(expected, output): - return expected == output - -Eval( - "Say Hi Bot", - data=lambda: [ - { - "input": "Foo", - "expected": "Hi Foo", - }, - { - "input": "Bar", - "expected": "Hello Bar", - }, - ], # Replace with your eval dataset - task=lambda input: "Hi " + input, # Replace with your LLM call - scores=[is_equal], -) -``` - -Finally, run the script with `braintrust eval eval_hello.py`. - -```bash -BRAINTRUST_API_KEY= braintrust eval eval_hello.py -``` - -### API Reference -""" - -# Check env var at import time for auto-instrumentation -import os - -if os.getenv("BRAINTRUST_INSTRUMENT_THREADS", "").lower() in ("true", "1", "yes"): - try: - from .wrappers.threads import setup_threads - - setup_threads() - except Exception: - pass # Never break on import - -from .audit import * -from .auto import ( - auto_instrument, # noqa: F401 # type: ignore[reportUnusedImport] -) -from .framework import * -from .framework2 import * -from .functions.invoke import * -from .functions.stream import * -from .generated_types import * -from .logger import * -from .logger import ( - _internal_get_global_state, # noqa: F401 # type: ignore[reportUnusedImport] - _internal_reset_global_state, # noqa: F401 # type: ignore[reportUnusedImport] - _internal_with_custom_background_logger, # noqa: F401 # type: ignore[reportUnusedImport] -) -from .oai import ( - wrap_openai, # noqa: F401 # type: ignore[reportUnusedImport] -) -from .util import ( - BT_IS_ASYNC_ATTRIBUTE, # noqa: F401 # type: ignore[reportUnusedImport] - MarkAsyncWrapper, # noqa: F401 # type: ignore[reportUnusedImport] -) -from .wrappers.anthropic import ( - wrap_anthropic, # noqa: F401 # type: ignore[reportUnusedImport] -) -from .wrappers.litellm import ( - wrap_litellm, # noqa: F401 # type: ignore[reportUnusedImport] -) -from .wrappers.pydantic_ai import ( - setup_pydantic_ai, # noqa: F401 # type: ignore[reportUnusedImport] -) diff --git a/py/src/braintrust/_generated_types.py b/py/src/braintrust/_generated_types.py deleted file mode 100644 index 5a977983c..000000000 --- a/py/src/braintrust/_generated_types.py +++ /dev/null @@ -1,3925 +0,0 @@ -""" -Do not import this file directly. See `generated_types.py` for the classes that have a stable API. - -Auto-generated file -- do not modify. -""" - -from __future__ import annotations - -from collections.abc import Mapping, Sequence -from typing import Any, Literal, TypeAlias, TypedDict - -from typing_extensions import NotRequired - -AclObjectType: TypeAlias = Literal[ - 'organization', - 'project', - 'experiment', - 'dataset', - 'prompt', - 'prompt_session', - 'group', - 'role', - 'org_member', - 'project_log', - 'org_project', -] -""" -The object type that the ACL applies to -""" - - -class AISecret(TypedDict): - id: str - """ - Unique identifier for the AI secret - """ - created: NotRequired[str | None] - """ - Date of AI secret creation - """ - updated_at: NotRequired[str | None] - """ - Date of last AI secret update - """ - org_id: str - """ - Unique identifier for the organization - """ - name: str - """ - Name of the AI secret - """ - type: NotRequired[str | None] - metadata: NotRequired[Mapping[str, Any] | None] - preview_secret: NotRequired[str | None] - - -class AnyModelParamsToolChoiceFunction(TypedDict): - name: str - - -class AnyModelParamsToolChoice(TypedDict): - type: Literal['function'] - function: AnyModelParamsToolChoiceFunction - - -class AnyModelParamsFunctionCall(TypedDict): - name: str - - -class ApiKey(TypedDict): - id: str - """ - Unique identifier for the api key - """ - created: NotRequired[str | None] - """ - Date of api key creation - """ - name: str - """ - Name of the api key - """ - preview_name: str - user_id: NotRequired[str | None] - """ - Unique identifier for the user - """ - user_email: NotRequired[str | None] - """ - The user's email - """ - user_given_name: NotRequired[str | None] - """ - Given name of the user - """ - user_family_name: NotRequired[str | None] - """ - Family name of the user - """ - org_id: NotRequired[str | None] - """ - Unique identifier for the organization - """ - - -class AsyncScoringControlAsyncScoringControl(TypedDict): - kind: Literal['score_update'] - token: NotRequired[str | None] - - -class AsyncScoringControlAsyncScoringControl2(TypedDict): - kind: Literal['state_force_reselect'] - - -class AsyncScoringControlAsyncScoringControl3(TypedDict): - kind: Literal['state_enabled_force_rescore'] - - -class AsyncScoringControlAsyncScoringControl4TriggeredFunctionScope(TypedDict): - type: Literal['span'] - - -class AsyncScoringControlAsyncScoringControl4TriggeredFunctionScope1(TypedDict): - type: Literal['trace'] - - -class AsyncScoringControlAsyncScoringControl4TriggeredFunction(TypedDict): - function_id: NotRequired[Any | None] - scope: ( - AsyncScoringControlAsyncScoringControl4TriggeredFunctionScope - | AsyncScoringControlAsyncScoringControl4TriggeredFunctionScope1 - ) - idempotency_key: NotRequired[str | None] - - -class AsyncScoringControlAsyncScoringControl4(TypedDict): - kind: Literal['trigger_functions'] - triggered_functions: Sequence[AsyncScoringControlAsyncScoringControl4TriggeredFunction] - - -class AsyncScoringControlAsyncScoringControl5(TypedDict): - kind: Literal['complete_triggered_functions'] - function_ids: Sequence[Any] - triggered_xact_id: str - - -class AsyncScoringControlAsyncScoringControl6(TypedDict): - kind: Literal['mark_attempt_failed'] - function_ids: Sequence[Any] - - -class AsyncScoringStateAsyncScoringState(TypedDict): - status: Literal['enabled'] - token: str - function_ids: Sequence[Any] - skip_logging: NotRequired[bool | None] - triggered_functions: NotRequired[Mapping[str, Any] | None] - - -class AsyncScoringStateAsyncScoringState1(TypedDict): - status: Literal['disabled'] - - -AsyncScoringState: TypeAlias = AsyncScoringStateAsyncScoringState | AsyncScoringStateAsyncScoringState1 | None - - -class PreprocessorPreprocessor(TypedDict): - type: Literal['function'] - id: str - version: NotRequired[str | None] - """ - The version of the function - """ - - -class PreprocessorPreprocessor2(TypedDict): - pass - - -class PreprocessorPreprocessor3(PreprocessorPreprocessor, PreprocessorPreprocessor2): - pass - - -class BatchedFacetDataFacet(TypedDict): - name: str - """ - The name of the facet - """ - prompt: str - """ - The prompt to use for LLM extraction. The preprocessed text will be provided as context. - """ - model: NotRequired[str | None] - """ - The model to use for facet extraction - """ - embedding_model: NotRequired[str | None] - """ - The embedding model to use for vectorizing facet results. - """ - no_match_pattern: NotRequired[str | None] - """ - Regex pattern to identify outputs that do not match the facet. If the output matches, the facet will be saved as 'no_match' - """ - - -class BraintrustAttachmentReference(TypedDict): - type: Literal['braintrust_attachment'] - """ - An identifier to help disambiguate parsing. - """ - filename: str - """ - Human-readable filename for user interfaces. Not related to attachment storage. - """ - content_type: str - """ - MIME type of this file. - """ - key: str - """ - Key in the object store bucket for this attachment. - """ - - -class BraintrustModelParams(TypedDict): - use_cache: NotRequired[bool | None] - reasoning_enabled: NotRequired[bool | None] - reasoning_budget: NotRequired[float | None] - - -class CallEventCallEvent(TypedDict): - id: NotRequired[str | None] - data: str - event: Literal['text_delta'] - - -class CallEventCallEvent1(TypedDict): - id: NotRequired[str | None] - data: str - event: Literal['reasoning_delta'] - - -class CallEventCallEvent2(TypedDict): - id: NotRequired[str | None] - data: str - event: Literal['json_delta'] - - -class CallEventCallEvent3(TypedDict): - id: NotRequired[str | None] - data: str - event: Literal['progress'] - - -class CallEventCallEvent4(TypedDict): - id: NotRequired[str | None] - data: str - event: Literal['error'] - - -class CallEventCallEvent5(TypedDict): - id: NotRequired[str | None] - data: str - event: Literal['console'] - - -class CallEventCallEvent6(TypedDict): - id: NotRequired[str | None] - event: Literal['start'] - data: Literal[''] - - -class CallEventCallEvent7(TypedDict): - id: NotRequired[str | None] - event: Literal['done'] - data: Literal[''] - - -CallEvent: TypeAlias = ( - CallEventCallEvent - | CallEventCallEvent1 - | CallEventCallEvent2 - | CallEventCallEvent3 - | CallEventCallEvent4 - | CallEventCallEvent5 - | CallEventCallEvent6 - | CallEventCallEvent7 -) - - -class ChatCompletionContentPartFileFile(TypedDict): - file_data: NotRequired[str | None] - filename: NotRequired[str | None] - file_id: NotRequired[str | None] - - -class ChatCompletionContentPartFileWithTitle(TypedDict): - file: ChatCompletionContentPartFileFile - type: Literal['file'] - - -class ChatCompletionContentPartImageWithTitleImageUrl(TypedDict): - url: str - detail: NotRequired[Literal['auto'] | Literal['low'] | Literal['high'] | None] - - -class ChatCompletionContentPartImageWithTitle(TypedDict): - image_url: ChatCompletionContentPartImageWithTitleImageUrl - type: Literal['image_url'] - - -class ChatCompletionContentPartTextCacheControl(TypedDict): - type: Literal['ephemeral'] - - -class ChatCompletionContentPartText(TypedDict): - text: str - type: Literal['text'] - cache_control: NotRequired[ChatCompletionContentPartTextCacheControl | None] - - -class ChatCompletionContentPartTextWithTitleCacheControl(TypedDict): - type: Literal['ephemeral'] - - -class ChatCompletionContentPartTextWithTitle(TypedDict): - text: str - type: Literal['text'] - cache_control: NotRequired[ChatCompletionContentPartTextWithTitleCacheControl | None] - - -class ChatCompletionMessageParamChatCompletionMessageParam(TypedDict): - content: str | Sequence[ChatCompletionContentPartText] - role: Literal['system'] - name: NotRequired[str | None] - - -class ChatCompletionMessageParamChatCompletionMessageParam2FunctionCall(TypedDict): - arguments: str - name: str - - -class ChatCompletionMessageParamChatCompletionMessageParam3(TypedDict): - content: str | Sequence[ChatCompletionContentPartText] - role: Literal['tool'] - tool_call_id: str - - -class ChatCompletionMessageParamChatCompletionMessageParam4(TypedDict): - content: str | None - name: str - role: Literal['function'] - - -class ChatCompletionMessageParamChatCompletionMessageParam5(TypedDict): - content: str | Sequence[ChatCompletionContentPartText] - role: Literal['developer'] - name: NotRequired[str | None] - - -class ChatCompletionMessageParamChatCompletionMessageParam6(TypedDict): - role: Literal['model'] - content: NotRequired[str | None] - - -class ChatCompletionMessageReasoning(TypedDict): - id: NotRequired[str | None] - content: NotRequired[str | None] - - -class ChatCompletionMessageToolCallFunction(TypedDict): - arguments: str - name: str - - -class ChatCompletionMessageToolCall(TypedDict): - id: str - function: ChatCompletionMessageToolCallFunction - type: Literal['function'] - - -class ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam(TypedDict): - content: str | Sequence[ChatCompletionContentPartText] - role: Literal['system'] - name: NotRequired[str | None] - - -class ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam2FunctionCall(TypedDict): - arguments: str - name: str - - -class ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam2(TypedDict): - role: Literal['assistant'] - content: NotRequired[str | Sequence[ChatCompletionContentPartText] | None] - function_call: NotRequired[ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam2FunctionCall | None] - name: NotRequired[str | None] - tool_calls: NotRequired[Sequence[ChatCompletionMessageToolCall] | None] - reasoning: NotRequired[Sequence[ChatCompletionMessageReasoning] | None] - - -class ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam3(TypedDict): - content: str | Sequence[ChatCompletionContentPartText] - role: Literal['tool'] - tool_call_id: str - - -class ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam4(TypedDict): - content: str | None - name: str - role: Literal['function'] - - -class ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam5(TypedDict): - content: str | Sequence[ChatCompletionContentPartText] - role: Literal['developer'] - name: NotRequired[str | None] - - -class ChatCompletionToolFunction(TypedDict): - name: str - description: NotRequired[str | None] - parameters: NotRequired[Mapping[str, Any] | None] - - -class ChatCompletionTool(TypedDict): - function: ChatCompletionToolFunction - type: Literal['function'] - - -class CodeBundleRuntimeContext(TypedDict): - runtime: Literal['node', 'python', 'browser', 'quickjs'] - version: str - - -class CodeBundleLocationPosition(TypedDict): - type: Literal['task'] - - -class CodeBundleLocationPosition1(TypedDict): - type: Literal['scorer'] - index: int - - -class CodeBundleLocation(TypedDict): - type: Literal['experiment'] - eval_name: str - position: CodeBundleLocationPosition | CodeBundleLocationPosition1 - - -class CodeBundleLocation1(TypedDict): - type: Literal['function'] - index: int - - -class CodeBundleLocation2SandboxSpec(TypedDict): - provider: Literal['modal'] - snapshot_ref: str - """ - sandbox snapshot ref - """ - - -class CodeBundleLocation2SandboxSpec1(TypedDict): - provider: Literal['lambda'] - - -class CodeBundleLocation2(TypedDict): - type: Literal['sandbox'] - sandbox_spec: CodeBundleLocation2SandboxSpec | CodeBundleLocation2SandboxSpec1 - entrypoints: NotRequired[Sequence[str] | None] - """ - Which entrypoints to execute in the sandbox - """ - eval_name: str - parameters: NotRequired[Mapping[str, Any] | None] - """ - Parameter values for sandbox eval execution - """ - evaluator_definition: NotRequired[Any | None] - """ - Definition of current evaluator with parameters - """ - - -class CodeBundle(TypedDict): - runtime_context: CodeBundleRuntimeContext - location: CodeBundleLocation | CodeBundleLocation1 | CodeBundleLocation2 - bundle_id: NotRequired[str | None] - preview: NotRequired[str | None] - """ - A preview of the code - """ - - -class Dataset(TypedDict): - id: str - """ - Unique identifier for the dataset - """ - project_id: str - """ - Unique identifier for the project that the dataset belongs under - """ - name: str - """ - Name of the dataset. Within a project, dataset names are unique - """ - description: NotRequired[str | None] - """ - Textual description of the dataset - """ - created: NotRequired[str | None] - """ - Date of dataset creation - """ - deleted_at: NotRequired[str | None] - """ - Date of dataset deletion, or null if the dataset is still active - """ - user_id: NotRequired[str | None] - """ - Identifies the user who created the dataset - """ - metadata: NotRequired[Mapping[str, Any] | None] - """ - User-controlled metadata about the dataset - """ - url_slug: str - """ - URL slug for the dataset. used to construct dataset URLs - """ - - -class DatasetEventMetadata(TypedDict): - model: NotRequired[str | None] - """ - The model used for this example - """ - - -class EnvVar(TypedDict): - id: str - """ - Unique identifier for the environment variable - """ - object_type: Literal['organization', 'project', 'function'] - """ - The type of the object the environment variable is scoped for - """ - object_id: str - """ - The id of the object the environment variable is scoped for - """ - name: str - """ - The name of the environment variable - """ - created: NotRequired[str | None] - """ - Date of environment variable creation - """ - used: NotRequired[str | None] - """ - Date the environment variable was last used - """ - metadata: NotRequired[Mapping[str, Any] | None] - """ - Optional metadata associated with the environment variable when managed via the function secrets API - """ - secret_type: NotRequired[str | None] - """ - Optional classification for the secret (for example, the AI provider name) - """ - secret_category: NotRequired[Literal['env_var', 'ai_provider', 'sandbox_provider'] | None] - """ - The category of the secret: env_var for regular environment variables, ai_provider for AI provider API keys - """ - - -class EvalStatusPageConfig(TypedDict): - score_columns: NotRequired[Sequence[str] | None] - """ - The score columns to display on the page - """ - metric_columns: NotRequired[Sequence[str] | None] - """ - The metric columns to display on the page - """ - grouping_field: NotRequired[str | None] - """ - The metadata field to use for grouping experiments (model) - """ - filter: NotRequired[str | None] - """ - BTQL filter to apply to experiment data - """ - sort_by: NotRequired[str | None] - """ - Field to sort results by (format: 'score:' or 'metric:') - """ - sort_order: NotRequired[Literal['asc', 'desc'] | None] - """ - Sort order (ascending or descending) - """ - api_key: NotRequired[str | None] - """ - The API key used for fetching experiment data - """ - - -EvalStatusPageTheme: TypeAlias = Literal['light', 'dark'] -""" -The theme for the page -""" - - -class ExperimentEventMetadata(TypedDict): - model: NotRequired[str | None] - """ - The model used for this example - """ - - -class ExperimentEventMetrics(TypedDict): - start: NotRequired[float | None] - """ - A unix timestamp recording when the section of code which produced the experiment event started - """ - end: NotRequired[float | None] - """ - A unix timestamp recording when the section of code which produced the experiment event finished - """ - prompt_tokens: NotRequired[int | None] - """ - The number of tokens in the prompt used to generate the experiment event (only set if this is an LLM span) - """ - completion_tokens: NotRequired[int | None] - """ - The number of tokens in the completion generated by the model (only set if this is an LLM span) - """ - tokens: NotRequired[int | None] - """ - The total number of tokens in the input and output of the experiment event. - """ - caller_functionname: NotRequired[Any | None] - """ - This metric is deprecated - """ - caller_filename: NotRequired[Any | None] - """ - This metric is deprecated - """ - caller_lineno: NotRequired[Any | None] - """ - This metric is deprecated - """ - - -class ExperimentEventContext(TypedDict): - caller_functionname: NotRequired[str | None] - """ - The function in code which created the experiment event - """ - caller_filename: NotRequired[str | None] - """ - Name of the file in code where the experiment event was created - """ - caller_lineno: NotRequired[int | None] - """ - Line of code where the experiment event was created - """ - - -class ExtendedSavedFunctionIdExtendedSavedFunctionId(TypedDict): - type: Literal['function'] - id: str - version: NotRequired[str | None] - """ - The version of the function - """ - - -class ExtendedSavedFunctionIdExtendedSavedFunctionId2(TypedDict): - type: Literal['slug'] - project_id: str - slug: str - - -class ExternalAttachmentReference(TypedDict): - type: Literal['external_attachment'] - """ - An identifier to help disambiguate parsing. - """ - filename: str - """ - Human-readable filename for user interfaces. Not related to attachment storage. - """ - content_type: str - """ - MIME type of this file. - """ - url: str - """ - Fully qualified URL to the object in the external object store. - """ - - -class Preprocessor1Preprocessor1(TypedDict): - type: Literal['function'] - id: str - version: NotRequired[str | None] - """ - The version of the function - """ - - -class Preprocessor1Preprocessor12(TypedDict): - pass - - -class Preprocessor1Preprocessor13(Preprocessor1Preprocessor1, Preprocessor1Preprocessor12): - pass - - -class FunctionOrigin(TypedDict): - object_type: AclObjectType - object_id: str - """ - Id of the object the function is originating from - """ - internal: NotRequired[bool | None] - """ - The function exists for internal purposes and should not be displayed in the list of functions. - """ - - -class FunctionFunctionSchema(TypedDict): - parameters: NotRequired[Any | None] - returns: NotRequired[Any | None] - - -class FunctionDataFunctionData(TypedDict): - type: Literal['prompt'] - - -class Data(CodeBundle): - type: Literal['bundle'] - - -class FunctionDataFunctionData1DataRuntimeContext(TypedDict): - runtime: Literal['node', 'python', 'browser', 'quickjs'] - version: str - - -class FunctionDataFunctionData1Data(TypedDict): - type: Literal['inline'] - runtime_context: FunctionDataFunctionData1DataRuntimeContext - code: str - code_hash: NotRequired[str | None] - """ - SHA256 hash of the code, computed at save time - """ - - -class FunctionDataFunctionData1(TypedDict): - type: Literal['code'] - data: Data | FunctionDataFunctionData1Data - - -class FunctionDataFunctionData2(TypedDict): - type: Literal['remote_eval'] - endpoint: str - eval_name: str - parameters: Mapping[str, Any] - parameters_version: NotRequired[str | None] - """ - The version (transaction ID) of the parameters being used - """ - - -class FunctionDataFunctionData4Schema(TypedDict): - type: Literal['object'] - properties: Mapping[str, Mapping[str, Any]] - required: NotRequired[Sequence[str] | None] - additionalProperties: NotRequired[bool | None] - - -class FunctionDataFunctionData4(TypedDict): - type: Literal['parameters'] - data: Mapping[str, Any] - """ - The parameters data - """ - __schema: FunctionDataFunctionData4Schema - """ - JSON Schema format for parameters - """ - - -FunctionFormat: TypeAlias = Literal['llm', 'code', 'global', 'graph', 'topic_map'] - - -class FunctionIdFunctionId(TypedDict): - function_id: str - """ - The ID of the function - """ - version: NotRequired[str | None] - """ - The version of the function - """ - - -class FunctionIdFunctionId1(TypedDict): - project_name: str - """ - The name of the project containing the function - """ - slug: str - """ - The slug of the function - """ - version: NotRequired[str | None] - """ - The version of the function - """ - - -class FunctionIdFunctionId3(TypedDict): - prompt_session_id: str - """ - The ID of the prompt session - """ - prompt_session_function_id: str - """ - The ID of the function in the prompt session - """ - version: NotRequired[str | None] - """ - The version of the function - """ - - -class FunctionIdFunctionId4InlineContext(TypedDict): - runtime: Literal['node', 'python', 'browser', 'quickjs'] - version: str - - -class FunctionIdFunctionId4(TypedDict): - inline_context: FunctionIdFunctionId4InlineContext - code: str - """ - The inline code to execute - """ - name: NotRequired[str | None] - """ - The name of the inline code function - """ - - -FunctionIdRef: TypeAlias = Mapping[str, Any] - - -FunctionObjectType: TypeAlias = Literal[ - 'prompt', - 'tool', - 'scorer', - 'task', - 'workflow', - 'custom_view', - 'preprocessor', - 'facet', - 'classifier', - 'parameters', - 'sandbox', -] - - -FunctionOutputType: TypeAlias = Literal['completion', 'score', 'facet', 'classification', 'any'] - - -FunctionTypeEnum: TypeAlias = Literal[ - 'llm', - 'scorer', - 'task', - 'tool', - 'custom_view', - 'preprocessor', - 'facet', - 'classifier', - 'tag', - 'parameters', - 'sandbox', -] -""" -The type of global function. Defaults to 'scorer'. -""" - - -FunctionTypeEnumNullish: TypeAlias = Literal[ - 'llm', - 'scorer', - 'task', - 'tool', - 'custom_view', - 'preprocessor', - 'facet', - 'classifier', - 'tag', - 'parameters', - 'sandbox', -] - - -class GitMetadataSettings(TypedDict): - collect: Literal['all', 'none', 'some'] - fields: NotRequired[ - Sequence[ - Literal[ - 'commit', - 'branch', - 'tag', - 'dirty', - 'author_name', - 'author_email', - 'commit_message', - 'commit_time', - 'git_diff', - ] - ] - ] - - -class GraphEdgeSource(TypedDict): - node: str - """ - The id of the node in the graph - """ - variable: str - - -class GraphEdgeTarget(TypedDict): - node: str - """ - The id of the node in the graph - """ - variable: str - - -class GraphEdge(TypedDict): - source: GraphEdgeSource - target: GraphEdgeTarget - purpose: Literal['control', 'data', 'messages'] - """ - The purpose of the edge - """ - - -class GraphNodeGraphNodePosition(TypedDict): - x: float - """ - The x position of the node - """ - y: float - """ - The y position of the node - """ - - -class GraphNodeGraphNode(TypedDict): - description: NotRequired[str | None] - """ - The description of the node - """ - position: NotRequired[GraphNodeGraphNodePosition | None] - """ - The position of the node - """ - type: Literal['function'] - function: FunctionIdRef - - -class GraphNodeGraphNode1Position(TypedDict): - x: float - """ - The x position of the node - """ - y: float - """ - The y position of the node - """ - - -class GraphNodeGraphNode1(TypedDict): - description: NotRequired[str | None] - """ - The description of the node - """ - position: NotRequired[GraphNodeGraphNode1Position | None] - """ - The position of the node - """ - type: Literal['input'] - """ - The input to the graph - """ - - -class GraphNodeGraphNode2Position(TypedDict): - x: float - """ - The x position of the node - """ - y: float - """ - The y position of the node - """ - - -class GraphNodeGraphNode2(TypedDict): - description: NotRequired[str | None] - """ - The description of the node - """ - position: NotRequired[GraphNodeGraphNode2Position | None] - """ - The position of the node - """ - type: Literal['output'] - """ - The output of the graph - """ - - -class GraphNodeGraphNode3Position(TypedDict): - x: float - """ - The x position of the node - """ - y: float - """ - The y position of the node - """ - - -class GraphNodeGraphNode3(TypedDict): - description: NotRequired[str | None] - """ - The description of the node - """ - position: NotRequired[GraphNodeGraphNode3Position | None] - """ - The position of the node - """ - type: Literal['literal'] - value: NotRequired[Any | None] - """ - A literal value to be returned - """ - - -class GraphNodeGraphNode4Position(TypedDict): - x: float - """ - The x position of the node - """ - y: float - """ - The y position of the node - """ - - -class GraphNodeGraphNode4(TypedDict): - description: NotRequired[str | None] - """ - The description of the node - """ - position: NotRequired[GraphNodeGraphNode4Position | None] - """ - The position of the node - """ - type: Literal['btql'] - expr: str - """ - A BTQL expression to be evaluated - """ - - -class GraphNodeGraphNode5Position(TypedDict): - x: float - """ - The x position of the node - """ - y: float - """ - The y position of the node - """ - - -class GraphNodeGraphNode5(TypedDict): - description: NotRequired[str | None] - """ - The description of the node - """ - position: NotRequired[GraphNodeGraphNode5Position | None] - """ - The position of the node - """ - type: Literal['gate'] - condition: NotRequired[str | None] - """ - A BTQL expression to be evaluated - """ - - -class GraphNodeGraphNode6Position(TypedDict): - x: float - """ - The x position of the node - """ - y: float - """ - The y position of the node - """ - - -class GraphNodeGraphNode6(TypedDict): - description: NotRequired[str | None] - """ - The description of the node - """ - position: NotRequired[GraphNodeGraphNode6Position | None] - """ - The position of the node - """ - type: Literal['aggregator'] - - -class GraphNodeGraphNode7Position(TypedDict): - x: float - """ - The x position of the node - """ - y: float - """ - The y position of the node - """ - - -class Group(TypedDict): - id: str - """ - Unique identifier for the group - """ - org_id: str - """ - Unique id for the organization that the group belongs under - - It is forbidden to change the org after creating a group - """ - user_id: NotRequired[str | None] - """ - Identifies the user who created the group - """ - created: NotRequired[str | None] - """ - Date of group creation - """ - name: str - """ - Name of the group - """ - description: NotRequired[str | None] - """ - Textual description of the group - """ - deleted_at: NotRequired[str | None] - """ - Date of group deletion, or null if the group is still active - """ - member_users: NotRequired[Sequence[str] | None] - """ - Ids of users which belong to this group - """ - member_groups: NotRequired[Sequence[str] | None] - """ - Ids of the groups this group inherits from - - An inheriting group has all the users contained in its member groups, as well as all of their inherited users - """ - - -class GroupScope(TypedDict): - type: Literal['group'] - group_by: str - """ - Field path to group by, e.g. metadata.session_id - """ - idle_seconds: NotRequired[float | None] - """ - Optional: trigger after this many seconds of inactivity - """ - - -IfExists: TypeAlias = Literal['error', 'ignore', 'replace'] - - -ImageRenderingMode: TypeAlias = Literal['auto', 'click_to_load', 'blocked'] -""" -Controls how images are rendered in the UI: 'auto' loads images automatically, 'click_to_load' shows a placeholder until clicked, 'blocked' prevents image loading entirely -""" - - -class InvokeFunctionInvokeFunction(TypedDict): - function_id: str - """ - The ID of the function - """ - version: NotRequired[str | None] - """ - The version of the function - """ - - -class InvokeFunctionInvokeFunction1(TypedDict): - project_name: str - """ - The name of the project containing the function - """ - slug: str - """ - The slug of the function - """ - version: NotRequired[str | None] - """ - The version of the function - """ - - -class InvokeFunctionInvokeFunction2(TypedDict): - global_function: str - """ - The name of the global function. Currently, the global namespace includes the functions in autoevals - """ - function_type: NotRequired[FunctionTypeEnum | None] - - -class InvokeFunctionInvokeFunction3(TypedDict): - prompt_session_id: str - """ - The ID of the prompt session - """ - prompt_session_function_id: str - """ - The ID of the function in the prompt session - """ - version: NotRequired[str | None] - """ - The version of the function - """ - - -class InvokeFunctionInvokeFunction4InlineContext(TypedDict): - runtime: Literal['node', 'python', 'browser', 'quickjs'] - version: str - - -class InvokeFunctionInvokeFunction4(TypedDict): - inline_context: InvokeFunctionInvokeFunction4InlineContext - code: str - """ - The inline code to execute - """ - name: NotRequired[str | None] - """ - The name of the inline code function - """ - - -class InvokeFunctionMcpAuth(TypedDict): - oauth_token: NotRequired[str | None] - """ - The OAuth token to use - """ - - -class InvokeParentInvokeParentRowIds(TypedDict): - id: str - """ - The id of the row - """ - span_id: str - """ - The span_id of the row - """ - root_span_id: str - """ - The root_span_id of the row - """ - - -class InvokeParentInvokeParent(TypedDict): - object_type: Literal['project_logs', 'experiment', 'playground_logs'] - object_id: str - """ - The id of the container object you are logging to - """ - row_ids: NotRequired[InvokeParentInvokeParentRowIds | None] - """ - Identifiers for the row to to log a subspan under - """ - propagated_event: NotRequired[Mapping[str, Any] | None] - """ - Include these properties in every span created under this parent - """ - - -InvokeParent: TypeAlias = InvokeParentInvokeParent | str -""" -Options for tracing the function call -""" - - -class MCPServer(TypedDict): - id: str - """ - Unique identifier for the MCP server - """ - project_id: str - """ - Unique identifier for the project that the MCP server belongs under - """ - user_id: NotRequired[str | None] - """ - Identifies the user who created the MCP server - """ - created: NotRequired[str | None] - """ - Date of MCP server creation - """ - deleted_at: NotRequired[str | None] - """ - Date of MCP server deletion, or null if the MCP server is still active - """ - name: str - """ - Name of the MCP server. Within a project, MCP server names are unique - """ - description: NotRequired[str | None] - """ - Textual description of the MCP server - """ - url: str - """ - URL of the MCP server endpoint - """ - - -MessageRole: TypeAlias = Literal['system', 'user', 'assistant', 'function', 'tool', 'model', 'developer'] - - -class ModelParamsModelParamsToolChoiceFunction(TypedDict): - name: str - - -class ModelParamsModelParamsToolChoice(TypedDict): - type: Literal['function'] - function: ModelParamsModelParamsToolChoiceFunction - - -class ModelParamsModelParamsFunctionCall(TypedDict): - name: str - - -class ModelParamsModelParams1(TypedDict): - use_cache: NotRequired[bool | None] - reasoning_enabled: NotRequired[bool | None] - reasoning_budget: NotRequired[float | None] - max_tokens: float - temperature: float - top_p: NotRequired[float | None] - top_k: NotRequired[float | None] - stop_sequences: NotRequired[Sequence[str] | None] - max_tokens_to_sample: NotRequired[float | None] - """ - This is a legacy parameter that should not be used. - """ - - -class ModelParamsModelParams2(TypedDict): - use_cache: NotRequired[bool | None] - reasoning_enabled: NotRequired[bool | None] - reasoning_budget: NotRequired[float | None] - temperature: NotRequired[float | None] - maxOutputTokens: NotRequired[float | None] - topP: NotRequired[float | None] - topK: NotRequired[float | None] - - -class ModelParamsModelParams3(TypedDict): - use_cache: NotRequired[bool | None] - reasoning_enabled: NotRequired[bool | None] - reasoning_budget: NotRequired[float | None] - temperature: NotRequired[float | None] - topK: NotRequired[float | None] - - -class ModelParamsModelParams4(TypedDict): - use_cache: NotRequired[bool | None] - reasoning_enabled: NotRequired[bool | None] - reasoning_budget: NotRequired[float | None] - - -class NullableSavedFunctionIdNullableSavedFunctionId(TypedDict): - type: Literal['function'] - id: str - version: NotRequired[str | None] - """ - The version of the function - """ - - -class NullableSavedFunctionIdNullableSavedFunctionId1(TypedDict): - type: Literal['global'] - name: str - function_type: NotRequired[FunctionTypeEnum | None] - - -NullableSavedFunctionId: TypeAlias = ( - NullableSavedFunctionIdNullableSavedFunctionId | NullableSavedFunctionIdNullableSavedFunctionId1 | None -) -""" -Default preprocessor for this project. When set, functions that use preprocessors will use this instead of their built-in default. -""" - - -class ObjectReference(TypedDict): - object_type: Literal['project_logs', 'experiment', 'dataset', 'prompt', 'function', 'prompt_session'] - """ - Type of the object the event is originating from. - """ - object_id: str - """ - ID of the object the event is originating from. - """ - id: str - """ - ID of the original event. - """ - _xact_id: NotRequired[str | None] - """ - Transaction ID of the original event. - """ - created: NotRequired[str | None] - """ - Created timestamp of the original event. Used to help sort in the UI - """ - - -class ObjectReferenceNullish(TypedDict): - object_type: Literal['project_logs', 'experiment', 'dataset', 'prompt', 'function', 'prompt_session'] - """ - Type of the object the event is originating from. - """ - object_id: str - """ - ID of the object the event is originating from. - """ - id: str - """ - ID of the original event. - """ - _xact_id: NotRequired[str | None] - """ - Transaction ID of the original event. - """ - created: NotRequired[str | None] - """ - Created timestamp of the original event. Used to help sort in the UI - """ - - -class Organization(TypedDict): - id: str - """ - Unique identifier for the organization - """ - name: str - """ - Name of the organization - """ - api_url: NotRequired[str | None] - is_universal_api: NotRequired[bool | None] - is_dataplane_private: NotRequired[bool | None] - proxy_url: NotRequired[str | None] - realtime_url: NotRequired[str | None] - created: NotRequired[str | None] - """ - Date of organization creation - """ - image_rendering_mode: NotRequired[ImageRenderingMode | None] - - -Permission: TypeAlias = Literal[ - 'create', 'read', 'update', 'delete', 'create_acls', 'read_acls', 'update_acls', 'delete_acls' -] -""" -Each permission permits a certain type of operation on an object in the system - -Permissions can be assigned to to objects on an individual basis, or grouped into roles -""" - - -class ProjectAutomationConfigAction(TypedDict): - type: Literal['webhook'] - """ - The type of action to take - """ - url: str - """ - The webhook URL to send the request to - """ - - -class ProjectAutomationConfigAction1(TypedDict): - type: Literal['slack'] - """ - The type of action to take - """ - workspace_id: str - """ - The Slack workspace ID to post to - """ - channel: str - """ - The Slack channel ID to post to - """ - message_template: NotRequired[str | None] - """ - Custom message template for the alert - """ - - -class ProjectAutomationConfig(TypedDict): - event_type: Literal['logs'] - """ - The type of automation. - """ - btql_filter: str - """ - BTQL filter to identify rows for the automation rule - """ - interval_seconds: float - """ - Perform the triggered action at most once in this interval of seconds - """ - action: ProjectAutomationConfigAction | ProjectAutomationConfigAction1 - """ - The action to take when the automation rule is triggered - """ - - -class ProjectAutomationConfig1ExportDefinition(TypedDict): - type: Literal['log_traces'] - - -class ProjectAutomationConfig1ExportDefinition1(TypedDict): - type: Literal['log_spans'] - - -class ProjectAutomationConfig1ExportDefinition2(TypedDict): - type: Literal['btql_query'] - btql_query: str - """ - The BTQL query to export - """ - - -class ProjectAutomationConfig1Credentials(TypedDict): - type: Literal['aws_iam'] - role_arn: str - """ - The ARN of the IAM role to use - """ - external_id: str - """ - The automation-specific external id component (auto-generated by default) - """ - - -class ProjectAutomationConfig1(TypedDict): - event_type: Literal['btql_export'] - """ - The type of automation. - """ - export_definition: ( - ProjectAutomationConfig1ExportDefinition - | ProjectAutomationConfig1ExportDefinition1 - | ProjectAutomationConfig1ExportDefinition2 - ) - """ - The definition of what to export - """ - export_path: str - """ - The path to export the results to. It should include the storage protocol and prefix, e.g. s3://bucket-name/path/to/export - """ - format: Literal['jsonl', 'parquet'] - """ - The format to export the results in - """ - interval_seconds: float - """ - Perform the triggered action at most once in this interval of seconds - """ - credentials: ProjectAutomationConfig1Credentials - batch_size: NotRequired[float | None] - """ - The number of rows to export in each batch - """ - - -class ProjectAutomationConfig3Action(TypedDict): - type: Literal['webhook'] - """ - The type of action to take - """ - url: str - """ - The webhook URL to send the request to - """ - - -class ProjectAutomationConfig3Action1(TypedDict): - type: Literal['slack'] - """ - The type of action to take - """ - workspace_id: str - """ - The Slack workspace ID to post to - """ - channel: str - """ - The Slack channel ID to post to - """ - message_template: NotRequired[str | None] - """ - Custom message template for the alert - """ - - -class ProjectAutomationConfig3(TypedDict): - event_type: Literal['environment_update'] - """ - The type of automation. - """ - environment_filter: NotRequired[Sequence[str] | None] - """ - Optional list of environment slugs to filter by - """ - action: ProjectAutomationConfig3Action | ProjectAutomationConfig3Action1 - """ - The action to take when the automation rule is triggered - """ - - -class ProjectLogsEventMetadata(TypedDict): - model: NotRequired[str | None] - """ - The model used for this example - """ - - -class ProjectLogsEventMetrics(TypedDict): - start: NotRequired[float | None] - """ - A unix timestamp recording when the section of code which produced the project logs event started - """ - end: NotRequired[float | None] - """ - A unix timestamp recording when the section of code which produced the project logs event finished - """ - prompt_tokens: NotRequired[int | None] - """ - The number of tokens in the prompt used to generate the project logs event (only set if this is an LLM span) - """ - completion_tokens: NotRequired[int | None] - """ - The number of tokens in the completion generated by the model (only set if this is an LLM span) - """ - tokens: NotRequired[int | None] - """ - The total number of tokens in the input and output of the project logs event. - """ - caller_functionname: NotRequired[Any | None] - """ - This metric is deprecated - """ - caller_filename: NotRequired[Any | None] - """ - This metric is deprecated - """ - caller_lineno: NotRequired[Any | None] - """ - This metric is deprecated - """ - - -class ProjectLogsEventContext(TypedDict): - caller_functionname: NotRequired[str | None] - """ - The function in code which created the project logs event - """ - caller_filename: NotRequired[str | None] - """ - Name of the file in code where the project logs event was created - """ - caller_lineno: NotRequired[int | None] - """ - Line of code where the project logs event was created - """ - - -class ProjectScoreCategory(TypedDict): - name: str - """ - Name of the category - """ - value: float - """ - Numerical value of the category. Must be between 0 and 1, inclusive - """ - - -ProjectScoreType: TypeAlias = Literal['slider', 'categorical', 'weighted', 'minimum', 'maximum', 'online', 'free-form'] -""" -The type of the configured score -""" - - -class ProjectSettingsSpanFieldOrderItem(TypedDict): - object_type: str - column_id: str - position: str - layout: NotRequired[Literal['full'] | Literal['two_column'] | None] - - -class ProjectSettingsRemoteEvalSource(TypedDict): - url: str - name: NotRequired[str | None] - description: NotRequired[str | None] - - -class ProjectSettings(TypedDict): - comparison_key: NotRequired[str | None] - """ - The key used to join two experiments (defaults to `input`) - """ - baseline_experiment_id: NotRequired[str | None] - """ - The id of the experiment to use as the default baseline for comparisons - """ - spanFieldOrder: NotRequired[Sequence[ProjectSettingsSpanFieldOrderItem] | None] - """ - The order of the fields to display in the trace view - """ - remote_eval_sources: NotRequired[Sequence[ProjectSettingsRemoteEvalSource] | None] - """ - The remote eval sources to use for the project - """ - disable_realtime_queries: NotRequired[bool | None] - """ - If true, disable real-time queries for this project. This can improve query performance for high-volume logs. - """ - default_preprocessor: NotRequired[NullableSavedFunctionId | None] - - -class ProjectTag(TypedDict): - id: str - """ - Unique identifier for the project tag - """ - project_id: str - """ - Unique identifier for the project that the project tag belongs under - """ - user_id: str - created: NotRequired[str | None] - """ - Date of project tag creation - """ - name: str - """ - Name of the project tag - """ - description: NotRequired[str | None] - """ - Textual description of the project tag - """ - color: NotRequired[str | None] - """ - Color of the tag for the UI - """ - position: NotRequired[str | None] - """ - An optional LexoRank-based string that sets the sort position for the tag in the UI - """ - - -class PromptBlockDataPromptBlockData1(TypedDict): - type: Literal['completion'] - content: str - - -class PromptBlockDataNullishPromptBlockDataNullish1(TypedDict): - type: Literal['completion'] - content: str - - -class PromptDataOrigin(TypedDict): - prompt_id: NotRequired[str | None] - project_id: NotRequired[str | None] - prompt_version: NotRequired[str | None] - - -class PromptDataNullishOrigin(TypedDict): - prompt_id: NotRequired[str | None] - project_id: NotRequired[str | None] - prompt_version: NotRequired[str | None] - - -class PromptParserNullish(TypedDict): - type: Literal['llm_classifier'] - use_cot: bool - choice_scores: NotRequired[Mapping[str, float] | None] - """ - Map of choices to scores (0-1). Used by scorers. - """ - choice: NotRequired[Sequence[str] | None] - """ - List of valid choices without score mapping. Used by classifiers that deposit output to tags. - """ - allow_no_match: NotRequired[bool | None] - """ - If true, adds a 'No match' option. When selected, no tag is deposited. - """ - - -class PromptSessionEvent(TypedDict): - id: str - """ - A unique identifier for the prompt session event. If you don't provide one, Braintrust will generate one for you - """ - _xact_id: str - """ - The transaction id of an event is unique to the network operation that processed the event insertion. Transaction ids are monotonically increasing over time and can be used to retrieve a versioned snapshot of the prompt session (see the `version` parameter) - """ - created: str - """ - The timestamp the prompt session event was created - """ - _pagination_key: NotRequired[str | None] - """ - A stable, time-ordered key that can be used to paginate over prompt session events. This field is auto-generated by Braintrust and only exists in Brainstore. - """ - project_id: str - """ - Unique identifier for the project that the prompt belongs under - """ - prompt_session_id: str - """ - Unique identifier for the prompt - """ - prompt_session_data: NotRequired[Any | None] - """ - Data about the prompt session - """ - prompt_data: NotRequired[Any | None] - """ - Data about the prompt - """ - function_data: NotRequired[Any | None] - """ - Data about the function - """ - function_type: NotRequired[FunctionTypeEnumNullish | None] - object_data: NotRequired[Any | None] - """ - Data about the mapped data - """ - completion: NotRequired[Any | None] - """ - Data about the completion - """ - tags: NotRequired[Sequence[str] | None] - """ - A list of tags to log - """ - - -class RepoInfo(TypedDict): - commit: NotRequired[str | None] - """ - SHA of most recent commit - """ - branch: NotRequired[str | None] - """ - Name of the branch the most recent commit belongs to - """ - tag: NotRequired[str | None] - """ - Name of the tag on the most recent commit - """ - dirty: NotRequired[bool | None] - """ - Whether or not the repo had uncommitted changes when snapshotted - """ - author_name: NotRequired[str | None] - """ - Name of the author of the most recent commit - """ - author_email: NotRequired[str | None] - """ - Email of the author of the most recent commit - """ - commit_message: NotRequired[str | None] - """ - Most recent commit message - """ - commit_time: NotRequired[str | None] - """ - Time of the most recent commit - """ - git_diff: NotRequired[str | None] - """ - If the repo was dirty when run, this includes the diff between the current state of the repo and the most recent commit. - """ - - -class ResponseFormatResponseFormat(TypedDict): - type: Literal['json_object'] - - -class ResponseFormatResponseFormat2(TypedDict): - type: Literal['text'] - - -class ResponseFormatJsonSchema(TypedDict): - name: str - description: NotRequired[str | None] - schema: NotRequired[Mapping[str, Any] | str | None] - strict: NotRequired[bool | None] - - -class ResponseFormatNullishResponseFormatNullish(TypedDict): - type: Literal['json_object'] - - -class ResponseFormatNullishResponseFormatNullish1(TypedDict): - type: Literal['json_schema'] - json_schema: ResponseFormatJsonSchema - - -class ResponseFormatNullishResponseFormatNullish2(TypedDict): - type: Literal['text'] - - -ResponseFormatNullish: TypeAlias = ( - ResponseFormatNullishResponseFormatNullish - | ResponseFormatNullishResponseFormatNullish1 - | ResponseFormatNullishResponseFormatNullish2 - | None -) - - -RetentionObjectType: TypeAlias = Literal['project_logs', 'experiment', 'dataset'] -""" -The object type that the retention policy applies to -""" - - -class RoleMemberPermission(TypedDict): - permission: Permission - restrict_object_type: NotRequired[AclObjectType | None] - - -class Role(TypedDict): - id: str - """ - Unique identifier for the role - """ - org_id: NotRequired[str | None] - """ - Unique id for the organization that the role belongs under - - A null org_id indicates a system role, which may be assigned to anybody and inherited by any other role, but cannot be edited. - - It is forbidden to change the org after creating a role - """ - user_id: NotRequired[str | None] - """ - Identifies the user who created the role - """ - created: NotRequired[str | None] - """ - Date of role creation - """ - name: str - """ - Name of the role - """ - description: NotRequired[str | None] - """ - Textual description of the role - """ - deleted_at: NotRequired[str | None] - """ - Date of role deletion, or null if the role is still active - """ - member_permissions: NotRequired[Sequence[RoleMemberPermission] | None] - """ - (permission, restrict_object_type) tuples which belong to this role - """ - member_roles: NotRequired[Sequence[str] | None] - """ - Ids of the roles this role inherits from - - An inheriting role has all the permissions contained in its member roles, as well as all of their inherited permissions - """ - - -class RunEvalData(TypedDict): - dataset_id: str - _internal_btql: NotRequired[Mapping[str, Any] | None] - - -class RunEvalData1(TypedDict): - project_name: str - dataset_name: str - _internal_btql: NotRequired[Mapping[str, Any] | None] - - -class RunEvalData2(TypedDict): - data: Sequence[Any] - - -class TaskTask(TypedDict): - function_id: str - """ - The ID of the function - """ - version: NotRequired[str | None] - """ - The version of the function - """ - - -class TaskTask1(TypedDict): - project_name: str - """ - The name of the project containing the function - """ - slug: str - """ - The slug of the function - """ - version: NotRequired[str | None] - """ - The version of the function - """ - - -class TaskTask2(TypedDict): - global_function: str - """ - The name of the global function. Currently, the global namespace includes the functions in autoevals - """ - function_type: NotRequired[FunctionTypeEnum | None] - - -class TaskTask3(TypedDict): - prompt_session_id: str - """ - The ID of the prompt session - """ - prompt_session_function_id: str - """ - The ID of the function in the prompt session - """ - version: NotRequired[str | None] - """ - The version of the function - """ - - -class TaskTask4InlineContext(TypedDict): - runtime: Literal['node', 'python', 'browser', 'quickjs'] - version: str - - -class TaskTask4(TypedDict): - inline_context: TaskTask4InlineContext - code: str - """ - The inline code to execute - """ - name: NotRequired[str | None] - """ - The name of the inline code function - """ - - -class TaskTask7(TypedDict): - pass - - -class TaskTask8(TaskTask, TaskTask7): - pass - - -class TaskTask9(TaskTask1, TaskTask7): - pass - - -class TaskTask10(TaskTask2, TaskTask7): - pass - - -class TaskTask11(TaskTask3, TaskTask7): - pass - - -class TaskTask12(TaskTask4, TaskTask7): - pass - - -class ParentParentRowIds(TypedDict): - id: str - """ - The id of the row - """ - span_id: str - """ - The span_id of the row - """ - root_span_id: str - """ - The root_span_id of the row - """ - - -class ParentParent(TypedDict): - object_type: Literal['project_logs', 'experiment', 'playground_logs'] - object_id: str - """ - The id of the container object you are logging to - """ - row_ids: NotRequired[ParentParentRowIds | None] - """ - Identifiers for the row to to log a subspan under - """ - propagated_event: NotRequired[Mapping[str, Any] | None] - """ - Include these properties in every span created under this parent - """ - - -class ParentParent1(TypedDict): - pass - - -class ParentParent2(ParentParent, ParentParent1): - pass - - -Parent: TypeAlias = ParentParent2 - - -class RunEvalMcpAuth(TypedDict): - oauth_token: NotRequired[str | None] - """ - The OAuth token to use - """ - - -class SavedFunctionIdSavedFunctionId(TypedDict): - type: Literal['function'] - id: str - version: NotRequired[str | None] - """ - The version of the function - """ - - -class SavedFunctionIdSavedFunctionId1(TypedDict): - type: Literal['global'] - name: str - function_type: NotRequired[FunctionTypeEnum | None] - - -SavedFunctionId: TypeAlias = SavedFunctionIdSavedFunctionId | SavedFunctionIdSavedFunctionId1 - - -class ServiceToken(TypedDict): - id: str - """ - Unique identifier for the service token - """ - created: NotRequired[str | None] - """ - Date of service token creation - """ - name: str - """ - Name of the service token - """ - preview_name: str - service_account_id: NotRequired[str | None] - """ - Unique identifier for the service token - """ - service_account_email: NotRequired[str | None] - """ - The service account email (not routable) - """ - service_account_name: NotRequired[str | None] - """ - The service account name - """ - org_id: NotRequired[str | None] - """ - Unique identifier for the organization - """ - - -class SpanIFrame(TypedDict): - id: str - """ - Unique identifier for the span iframe - """ - project_id: str - """ - Unique identifier for the project that the span iframe belongs under - """ - user_id: NotRequired[str | None] - """ - Identifies the user who created the span iframe - """ - created: NotRequired[str | None] - """ - Date of span iframe creation - """ - deleted_at: NotRequired[str | None] - """ - Date of span iframe deletion, or null if the span iframe is still active - """ - name: str - """ - Name of the span iframe - """ - description: NotRequired[str | None] - """ - Textual description of the span iframe - """ - url: str - """ - URL to embed the project viewer in an iframe - """ - post_message: NotRequired[bool | None] - """ - Whether to post messages to the iframe containing the span's data. This is useful when you want to render more data than fits in the URL. - """ - - -class SpanScope(TypedDict): - type: Literal['span'] - - -SpanType: TypeAlias = Literal[ - 'llm', 'score', 'function', 'eval', 'task', 'tool', 'automation', 'facet', 'preprocessor', 'classifier', 'review' -] -""" -Type of the span, for display purposes only -""" - - -class SSEConsoleEventData(TypedDict): - stream: Literal['stderr', 'stdout'] - message: str - - -class SSEProgressEventData(TypedDict): - id: str - """ - The id of the span this event is for - """ - object_type: FunctionObjectType - origin: NotRequired[ObjectReferenceNullish | None] - format: FunctionFormat - output_type: FunctionOutputType - name: str - event: Literal['reasoning_delta', 'text_delta', 'json_delta', 'error', 'console', 'start', 'done', 'progress'] - data: str - - -StreamingMode: TypeAlias = Literal['auto', 'parallel', 'json', 'text'] -""" -The mode format of the returned value (defaults to 'auto') -""" - - -class ToolFunctionDefinitionFunction(TypedDict): - name: str - description: NotRequired[str | None] - parameters: NotRequired[Mapping[str, Any] | None] - strict: NotRequired[bool | None] - - -class ToolFunctionDefinition(TypedDict): - type: Literal['function'] - function: ToolFunctionDefinitionFunction - - -class TopicAutomationDataScopeTopicAutomationDataScope(TypedDict): - type: Literal['project_logs'] - - -class TopicAutomationDataScopeTopicAutomationDataScope1(TypedDict): - type: Literal['project_experiments'] - - -class TopicAutomationDataScopeTopicAutomationDataScope2(TypedDict): - type: Literal['experiment'] - experiment_id: str - - -TopicAutomationDataScope: TypeAlias = ( - TopicAutomationDataScopeTopicAutomationDataScope - | TopicAutomationDataScopeTopicAutomationDataScope1 - | TopicAutomationDataScopeTopicAutomationDataScope2 - | None -) -""" -Optional data scope for topic automation. -""" - - -class TopicMapData(TypedDict): - type: Literal['topic_map'] - source_facet: str - """ - The facet field name to use as input for classification - """ - embedding_model: str - """ - The embedding model to use for embedding facet values - """ - bundle_key: NotRequired[str | None] - """ - Key of the topic map bundle in code_bundles bucket - """ - report_key: NotRequired[str | None] - """ - Key of the clustering report in code_bundles bucket - """ - topic_names: NotRequired[Mapping[str, str] | None] - """ - Mapping from topic_id to topic name - """ - distance_threshold: NotRequired[float | None] - """ - Maximum distance to nearest centroid. If exceeded, returns no_match. - """ - - -class Function1Function1(TypedDict): - type: Literal['function'] - id: str - version: NotRequired[str | None] - """ - The version of the function - """ - - -class Function1Function11(TypedDict): - type: Literal['global'] - name: str - function_type: NotRequired[FunctionTypeEnum | None] - - -class Function1Function12(TypedDict): - pass - - -class Function1Function13(Function1Function1, Function1Function12): - pass - - -class Function1Function14(Function1Function11, Function1Function12): - pass - - -Function1: TypeAlias = Function1Function13 | Function1Function14 - - -class TopicMapFunctionAutomation(TypedDict): - function: Function1 - btql_filter: NotRequired[str | None] - """ - Per-topic-map BTQL filter. For trace scope, a topic map runs when max(filter) over the trace is truthy. For span scope, it runs when the current span matches. - """ - - -class TraceScope(TypedDict): - type: Literal['trace'] - idle_seconds: NotRequired[float | None] - """ - Consider trace complete after this many seconds of inactivity (default: 30) - """ - - -class TriggeredFunctionStateScope(TypedDict): - type: Literal['span'] - - -class TriggeredFunctionStateScope1(TypedDict): - type: Literal['trace'] - - -class TriggeredFunctionStateScope2(TypedDict): - type: Literal['group'] - key: str - value: str - - -class TriggeredFunctionState(TypedDict): - triggered_xact_id: str - """ - The xact_id when this function was triggered - """ - completed_xact_id: NotRequired[str | None] - """ - The xact_id when this function completed (matches triggered_xact_id if done) - """ - idempotency_key: NotRequired[str | None] - """ - Deterministic key of the function definition + input version used to skip unchanged reruns - """ - attempts: NotRequired[int | None] - """ - Number of execution attempts (for retry tracking) - """ - scope: TriggeredFunctionStateScope | TriggeredFunctionStateScope1 | TriggeredFunctionStateScope2 - """ - The scope of data this function operates on - """ - - -UploadStatus: TypeAlias = Literal['uploading', 'done', 'error'] - - -class User(TypedDict): - id: str - """ - Unique identifier for the user - """ - given_name: NotRequired[str | None] - """ - Given name of the user - """ - family_name: NotRequired[str | None] - """ - Family name of the user - """ - email: NotRequired[str | None] - """ - The user's email - """ - avatar_url: NotRequired[str | None] - """ - URL of the user's Avatar image - """ - created: NotRequired[str | None] - """ - Date of user creation - """ - - -class ViewDataSearch(TypedDict): - filter: NotRequired[Sequence[Any] | None] - tag: NotRequired[Sequence[Any] | None] - match: NotRequired[Sequence[Any] | None] - sort: NotRequired[Sequence[Any] | None] - - -class ViewOptionsViewOptionsOptions(TypedDict): - spanType: NotRequired[Literal['range', 'frame'] | None] - rangeValue: NotRequired[str | None] - frameStart: NotRequired[str | None] - frameEnd: NotRequired[str | None] - tzUTC: NotRequired[bool | None] - chartVisibility: NotRequired[Mapping[str, Any] | None] - projectId: NotRequired[str | None] - type: NotRequired[Literal['project', 'experiment'] | None] - groupBy: NotRequired[str | None] - - -class ViewOptionsViewOptions(TypedDict): - viewType: Literal['monitor'] - options: ViewOptionsViewOptionsOptions - freezeColumns: NotRequired[bool | None] - - -class ViewOptionsViewOptions1ExcludedMeasure(TypedDict): - type: Literal['none', 'score', 'metric', 'metadata'] - value: str - - -class ViewOptionsViewOptions1YMetric(TypedDict): - type: Literal['none', 'score', 'metric', 'metadata'] - value: str - - -class ViewOptionsViewOptions1XAxis(TypedDict): - type: Literal['none', 'score', 'metric', 'metadata'] - value: str - - -class ViewOptionsViewOptions1SymbolGrouping(TypedDict): - type: Literal['none', 'score', 'metric', 'metadata'] - value: str - - -class ViewOptionsViewOptions1ChartAnnotation(TypedDict): - id: str - text: str - - -ViewOptionsViewOptions1TimeRangeFilter = TypedDict( - 'ViewOptionsViewOptions1TimeRangeFilter', - { - 'from': str, - 'to': str, - }, -) - - -class ViewOptionsViewOptions1(TypedDict): - columnVisibility: NotRequired[Mapping[str, Any] | None] - columnOrder: NotRequired[Sequence[str] | None] - columnSizing: NotRequired[Mapping[str, Any] | None] - grouping: NotRequired[str | None] - rowHeight: NotRequired[str | None] - tallGroupRows: NotRequired[bool | None] - layout: NotRequired[str | None] - chartHeight: NotRequired[float | None] - excludedMeasures: NotRequired[Sequence[ViewOptionsViewOptions1ExcludedMeasure] | None] - yMetric: NotRequired[ViewOptionsViewOptions1YMetric | None] - xAxis: NotRequired[ViewOptionsViewOptions1XAxis | None] - symbolGrouping: NotRequired[ViewOptionsViewOptions1SymbolGrouping | None] - xAxisAggregation: NotRequired[str | None] - """ - One of 'avg', 'sum', 'min', 'max', 'median', 'all' - """ - chartAnnotations: NotRequired[Sequence[ViewOptionsViewOptions1ChartAnnotation] | None] - timeRangeFilter: NotRequired[str | ViewOptionsViewOptions1TimeRangeFilter | None] - queryShape: NotRequired[Literal['traces', 'spans'] | None] - freezeColumns: NotRequired[bool | None] - - -ViewOptions: TypeAlias = ViewOptionsViewOptions | ViewOptionsViewOptions1 | None -""" -Options for the view in the app -""" - - -class Acl(TypedDict): - id: str - """ - Unique identifier for the acl - """ - object_type: AclObjectType - object_id: str - """ - The id of the object the ACL applies to - """ - user_id: NotRequired[str | None] - """ - Id of the user the ACL applies to. Exactly one of `user_id` and `group_id` will be provided - """ - group_id: NotRequired[str | None] - """ - Id of the group the ACL applies to. Exactly one of `user_id` and `group_id` will be provided - """ - permission: NotRequired[Permission | None] - restrict_object_type: NotRequired[AclObjectType | None] - role_id: NotRequired[str | None] - """ - Id of the role the ACL grants. Exactly one of `permission` and `role_id` will be provided - """ - _object_org_id: str - """ - The organization the ACL's referred object belongs to - """ - created: NotRequired[str | None] - """ - Date of acl creation - """ - - -class AnyModelParams(TypedDict): - temperature: NotRequired[float | None] - top_p: NotRequired[float | None] - max_tokens: float - max_completion_tokens: NotRequired[float | None] - """ - The successor to max_tokens - """ - frequency_penalty: NotRequired[float | None] - presence_penalty: NotRequired[float | None] - response_format: NotRequired[ResponseFormatNullish | None] - tool_choice: NotRequired[Literal['auto'] | Literal['none'] | Literal['required'] | AnyModelParamsToolChoice | None] - function_call: NotRequired[Literal['auto'] | Literal['none'] | AnyModelParamsFunctionCall | None] - n: NotRequired[float | None] - stop: NotRequired[Sequence[str] | None] - reasoning_effort: NotRequired[Literal['none', 'minimal', 'low', 'medium', 'high'] | None] - verbosity: NotRequired[Literal['low', 'medium', 'high'] | None] - top_k: NotRequired[float | None] - stop_sequences: NotRequired[Sequence[str] | None] - reasoning_enabled: NotRequired[bool | None] - reasoning_budget: NotRequired[float | None] - max_tokens_to_sample: NotRequired[float | None] - """ - This is a legacy parameter that should not be used. - """ - maxOutputTokens: NotRequired[float | None] - topP: NotRequired[float | None] - topK: NotRequired[float | None] - use_cache: NotRequired[bool | None] - - -class AsyncScoringControlAsyncScoringControl1(TypedDict): - kind: Literal['state_override'] - state: AsyncScoringState - - -AsyncScoringControl: TypeAlias = ( - AsyncScoringControlAsyncScoringControl - | AsyncScoringControlAsyncScoringControl1 - | AsyncScoringControlAsyncScoringControl2 - | AsyncScoringControlAsyncScoringControl3 - | AsyncScoringControlAsyncScoringControl4 - | AsyncScoringControlAsyncScoringControl5 - | AsyncScoringControlAsyncScoringControl6 -) - - -AttachmentReference: TypeAlias = BraintrustAttachmentReference | ExternalAttachmentReference - - -class AttachmentStatus(TypedDict): - upload_status: UploadStatus - error_message: NotRequired[str | None] - """ - Describes the error encountered while uploading. - """ - - -class PreprocessorPreprocessor1(TypedDict): - type: Literal['global'] - name: str - function_type: NotRequired[FunctionTypeEnum | None] - - -class PreprocessorPreprocessor4(PreprocessorPreprocessor1, PreprocessorPreprocessor2): - pass - - -Preprocessor: TypeAlias = PreprocessorPreprocessor3 | PreprocessorPreprocessor4 - - -class BatchedFacetDataTopicMap(TypedDict): - function_name: str - """ - The name of the topic map function - """ - topic_map_id: NotRequired[str | None] - """ - The id of the topic map function - """ - topic_map_data: TopicMapData - - -class BatchedFacetData(TypedDict): - type: Literal['batched_facet'] - preprocessor: NotRequired[Preprocessor | None] - facets: Sequence[BatchedFacetDataFacet] - topic_maps: NotRequired[Mapping[str, Sequence[BatchedFacetDataTopicMap]] | None] - """ - Topic maps that depend on facets in this batch, keyed by source facet name. Each source facet can have multiple topic maps. - """ - - -ChatCompletionContentPart: TypeAlias = ( - ChatCompletionContentPartTextWithTitle - | ChatCompletionContentPartImageWithTitle - | ChatCompletionContentPartFileWithTitle -) - - -class ChatCompletionMessageParamChatCompletionMessageParam1(TypedDict): - content: str | Sequence[ChatCompletionContentPart] - role: Literal['user'] - name: NotRequired[str | None] - - -class ChatCompletionMessageParamChatCompletionMessageParam2(TypedDict): - role: Literal['assistant'] - content: NotRequired[str | Sequence[ChatCompletionContentPartText] | None] - function_call: NotRequired[ChatCompletionMessageParamChatCompletionMessageParam2FunctionCall | None] - name: NotRequired[str | None] - tool_calls: NotRequired[Sequence[ChatCompletionMessageToolCall] | None] - reasoning: NotRequired[Sequence[ChatCompletionMessageReasoning] | None] - - -ChatCompletionMessageParam: TypeAlias = ( - ChatCompletionMessageParamChatCompletionMessageParam - | ChatCompletionMessageParamChatCompletionMessageParam1 - | ChatCompletionMessageParamChatCompletionMessageParam2 - | ChatCompletionMessageParamChatCompletionMessageParam3 - | ChatCompletionMessageParamChatCompletionMessageParam4 - | ChatCompletionMessageParamChatCompletionMessageParam5 - | ChatCompletionMessageParamChatCompletionMessageParam6 -) - - -class ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam1(TypedDict): - content: str | Sequence[ChatCompletionContentPart] - role: Literal['user'] - name: NotRequired[str | None] - - -ChatCompletionOpenAIMessageParam: TypeAlias = ( - ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam - | ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam1 - | ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam2 - | ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam3 - | ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam4 - | ChatCompletionOpenAIMessageParamChatCompletionOpenAIMessageParam5 -) - - -class DatasetEvent(TypedDict): - id: str - """ - A unique identifier for the dataset event. If you don't provide one, Braintrust will generate one for you - """ - _xact_id: str - """ - The transaction id of an event is unique to the network operation that processed the event insertion. Transaction ids are monotonically increasing over time and can be used to retrieve a versioned snapshot of the dataset (see the `version` parameter) - """ - created: str - """ - The timestamp the dataset event was created - """ - _pagination_key: NotRequired[str | None] - """ - A stable, time-ordered key that can be used to paginate over dataset events. This field is auto-generated by Braintrust and only exists in Brainstore. - """ - project_id: str - """ - Unique identifier for the project that the dataset belongs under - """ - dataset_id: str - """ - Unique identifier for the dataset - """ - input: NotRequired[Any | None] - """ - The argument that uniquely define an input case (an arbitrary, JSON serializable object) - """ - expected: NotRequired[Any | None] - """ - The output of your application, including post-processing (an arbitrary, JSON serializable object) - """ - metadata: NotRequired[DatasetEventMetadata | None] - """ - A dictionary with additional data about the test example, model outputs, or just about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any JSON-serializable type, but its keys must be strings - """ - tags: NotRequired[Sequence[str] | None] - """ - A list of tags to log - """ - span_id: str - """ - A unique identifier used to link different dataset events together as part of a full trace. See the [tracing guide](https://www.braintrust.dev/docs/instrument) for full details on tracing - """ - root_span_id: str - """ - A unique identifier for the trace this dataset event belongs to - """ - is_root: NotRequired[bool | None] - """ - Whether this span is a root span - """ - origin: NotRequired[ObjectReferenceNullish | None] - comments: NotRequired[Sequence[Any] | None] - """ - Optional list of comments attached to this event - """ - audit_data: NotRequired[Sequence[Any] | None] - """ - Optional list of audit entries attached to this event - """ - facets: NotRequired[Mapping[str, Any] | None] - """ - Facets for categorization (dictionary from facet id to value) - """ - classifications: NotRequired[Mapping[str, Any] | None] - """ - Classifications for this event (dictionary from classification name to items) - """ - - -class EvalStatusPage(TypedDict): - id: str - """ - Unique identifier for the eval status page - """ - project_id: str - """ - Unique identifier for the project that the eval status page belongs under - """ - user_id: NotRequired[str | None] - """ - Identifies the user who created the eval status page - """ - created: NotRequired[str | None] - """ - Date of eval status page creation - """ - deleted_at: NotRequired[str | None] - """ - Date of eval status page deletion, or null if the eval status page is still active - """ - name: str - """ - Name of the eval status page - """ - description: NotRequired[str | None] - """ - Textual description of the eval status page - """ - logo_url: NotRequired[str | None] - """ - URL of the logo to display on the page - """ - theme: EvalStatusPageTheme - config: EvalStatusPageConfig - - -class Experiment(TypedDict): - id: str - """ - Unique identifier for the experiment - """ - project_id: str - """ - Unique identifier for the project that the experiment belongs under - """ - name: str - """ - Name of the experiment. Within a project, experiment names are unique - """ - description: NotRequired[str | None] - """ - Textual description of the experiment - """ - created: NotRequired[str | None] - """ - Date of experiment creation - """ - repo_info: NotRequired[RepoInfo | None] - commit: NotRequired[str | None] - """ - Commit, taken directly from `repo_info.commit` - """ - base_exp_id: NotRequired[str | None] - """ - Id of default base experiment to compare against when viewing this experiment - """ - deleted_at: NotRequired[str | None] - """ - Date of experiment deletion, or null if the experiment is still active - """ - dataset_id: NotRequired[str | None] - """ - Identifier of the linked dataset, or null if the experiment is not linked to a dataset - """ - dataset_version: NotRequired[str | None] - """ - Version number of the linked dataset the experiment was run against. This can be used to reproduce the experiment after the dataset has been modified. - """ - public: bool - """ - Whether or not the experiment is public. Public experiments can be viewed by anybody inside or outside the organization - """ - user_id: NotRequired[str | None] - """ - Identifies the user who created the experiment - """ - metadata: NotRequired[Mapping[str, Any] | None] - """ - User-controlled metadata about the experiment - """ - tags: NotRequired[Sequence[str] | None] - """ - A list of tags for the experiment - """ - - -class ExtendedSavedFunctionIdExtendedSavedFunctionId1(TypedDict): - type: Literal['global'] - name: str - function_type: NotRequired[FunctionTypeEnum | None] - - -ExtendedSavedFunctionId: TypeAlias = ( - ExtendedSavedFunctionIdExtendedSavedFunctionId - | ExtendedSavedFunctionIdExtendedSavedFunctionId1 - | ExtendedSavedFunctionIdExtendedSavedFunctionId2 -) - - -class Preprocessor1Preprocessor11(TypedDict): - type: Literal['global'] - name: str - function_type: NotRequired[FunctionTypeEnum | None] - - -class Preprocessor1Preprocessor14(Preprocessor1Preprocessor11, Preprocessor1Preprocessor12): - pass - - -Preprocessor1: TypeAlias = Preprocessor1Preprocessor13 | Preprocessor1Preprocessor14 - - -class FacetData(TypedDict): - type: Literal['facet'] - preprocessor: NotRequired[Preprocessor1 | None] - prompt: str - """ - The prompt to use for LLM extraction. The preprocessed text will be provided as context. - """ - model: NotRequired[str | None] - """ - The model to use for facet extraction - """ - embedding_model: NotRequired[str | None] - """ - The embedding model to use for vectorizing facet results. - """ - no_match_pattern: NotRequired[str | None] - """ - Regex pattern to identify outputs that do not match the facet. If the output matches, the facet will be saved as 'no_match' - """ - - -class FunctionDataFunctionData3(TypedDict): - type: Literal['global'] - name: str - function_type: NotRequired[FunctionTypeEnum | None] - config: NotRequired[Mapping[str, Any] | None] - """ - Configuration options to pass to the global function (e.g., for preprocessor customization) - """ - - -class FunctionIdFunctionId2(TypedDict): - global_function: str - """ - The name of the global function. Currently, the global namespace includes the functions in autoevals - """ - function_type: NotRequired[FunctionTypeEnum | None] - - -class InvokeFunctionInvokeFunction7(TypedDict): - input: NotRequired[Any | None] - """ - Argument to the function, which can be any JSON serializable value - """ - expected: NotRequired[Any | None] - """ - The expected output of the function - """ - metadata: NotRequired[Mapping[str, Any] | None] - """ - Any relevant metadata. This will be logged and available as the `metadata` argument. - """ - tags: NotRequired[Sequence[str] | None] - """ - Any relevant tags to log on the span. - """ - messages: NotRequired[Sequence[ChatCompletionMessageParam] | None] - """ - If the function is an LLM, additional messages to pass along to it - """ - parent: NotRequired[InvokeParent | None] - stream: NotRequired[bool | None] - """ - Whether to stream the response. If true, results will be returned in the Braintrust SSE format. - """ - mode: NotRequired[StreamingMode | None] - strict: NotRequired[bool | None] - """ - If true, throw an error if one of the variables in the prompt is not present in the input - """ - mcp_auth: NotRequired[Mapping[str, InvokeFunctionMcpAuth] | None] - """ - Map of MCP server URL to auth credentials - """ - overrides: NotRequired[Mapping[str, Any] | None] - """ - Partial function definition to merge with the function being invoked. Fields are validated against the function type's schema at runtime. For facets: { preprocessor?, prompt?, model? }. For prompts: { model?, ... }. - """ - - -class InvokeFunctionInvokeFunction8(InvokeFunctionInvokeFunction, InvokeFunctionInvokeFunction7): - pass - - -class InvokeFunctionInvokeFunction9(InvokeFunctionInvokeFunction1, InvokeFunctionInvokeFunction7): - pass - - -class InvokeFunctionInvokeFunction10(InvokeFunctionInvokeFunction2, InvokeFunctionInvokeFunction7): - pass - - -class InvokeFunctionInvokeFunction11(InvokeFunctionInvokeFunction3, InvokeFunctionInvokeFunction7): - pass - - -class InvokeFunctionInvokeFunction12(InvokeFunctionInvokeFunction4, InvokeFunctionInvokeFunction7): - pass - - -class ModelParamsModelParams(TypedDict): - use_cache: NotRequired[bool | None] - reasoning_enabled: NotRequired[bool | None] - reasoning_budget: NotRequired[float | None] - temperature: NotRequired[float | None] - top_p: NotRequired[float | None] - max_tokens: NotRequired[float | None] - max_completion_tokens: NotRequired[float | None] - """ - The successor to max_tokens - """ - frequency_penalty: NotRequired[float | None] - presence_penalty: NotRequired[float | None] - response_format: NotRequired[ResponseFormatNullish | None] - tool_choice: NotRequired[ - Literal['auto'] | Literal['none'] | Literal['required'] | ModelParamsModelParamsToolChoice - ] - function_call: NotRequired[Literal['auto'] | Literal['none'] | ModelParamsModelParamsFunctionCall | None] - n: NotRequired[float | None] - stop: NotRequired[Sequence[str] | None] - reasoning_effort: NotRequired[Literal['none', 'minimal', 'low', 'medium', 'high'] | None] - verbosity: NotRequired[Literal['low', 'medium', 'high'] | None] - - -ModelParams: TypeAlias = ( - ModelParamsModelParams - | ModelParamsModelParams1 - | ModelParamsModelParams2 - | ModelParamsModelParams3 - | ModelParamsModelParams4 -) - - -class OnlineScoreConfig(TypedDict): - sampling_rate: float - """ - The sampling rate for online scoring - """ - scorers: Sequence[SavedFunctionId] - """ - The list of functions to run for online scoring. Can include scorers, facets, or other function types. - """ - btql_filter: NotRequired[str | None] - """ - Filter logs using BTQL - """ - apply_to_root_span: NotRequired[bool | None] - """ - Whether to trigger online scoring on the root span of each trace. Only applies when scope is 'span' or unset. - """ - apply_to_span_names: NotRequired[Sequence[str] | None] - """ - Trigger online scoring on any spans with a name in this list. Only applies when scope is 'span' or unset. - """ - skip_logging: NotRequired[bool | None] - """ - Whether to skip adding scorer spans when computing scores - """ - scope: NotRequired[SpanScope | TraceScope | GroupScope | None] - """ - The scope at which to run the functions. Defaults to span-level execution. Trace/group scope requires all functions to be facets. - """ - - -class Project(TypedDict): - id: str - """ - Unique identifier for the project - """ - org_id: str - """ - Unique id for the organization that the project belongs under - """ - name: str - """ - Name of the project - """ - description: NotRequired[str | None] - """ - Textual description of the project - """ - created: NotRequired[str | None] - """ - Date of project creation - """ - deleted_at: NotRequired[str | None] - """ - Date of project deletion, or null if the project is still active - """ - user_id: NotRequired[str | None] - """ - Identifies the user who created the project - """ - settings: NotRequired[ProjectSettings | None] - - -class ProjectAutomationConfig2(TypedDict): - event_type: Literal['retention'] - """ - The type of automation. - """ - object_type: RetentionObjectType - retention_days: float - """ - The number of days to retain the object - """ - - -ProjectScoreCategories: TypeAlias = Sequence[ProjectScoreCategory] | Mapping[str, float] | Sequence[str] | None - - -class ProjectScoreConfig(TypedDict): - multi_select: NotRequired[bool | None] - destination: NotRequired[str | None] - online: NotRequired[OnlineScoreConfig | None] - - -class PromptBlockDataPromptBlockData(TypedDict): - type: Literal['chat'] - messages: Sequence[ChatCompletionMessageParam] - tools: NotRequired[str | None] - - -PromptBlockData: TypeAlias = PromptBlockDataPromptBlockData | PromptBlockDataPromptBlockData1 - - -class PromptBlockDataNullishPromptBlockDataNullish(TypedDict): - type: Literal['chat'] - messages: Sequence[ChatCompletionMessageParam] - tools: NotRequired[str | None] - - -PromptBlockDataNullish: TypeAlias = ( - PromptBlockDataNullishPromptBlockDataNullish | PromptBlockDataNullishPromptBlockDataNullish1 | None -) - - -class PromptOptions(TypedDict): - model: NotRequired[str | None] - params: NotRequired[ModelParams | None] - position: NotRequired[str | None] - - -class PromptOptionsNullish(TypedDict): - model: NotRequired[str | None] - params: NotRequired[ModelParams | None] - position: NotRequired[str | None] - - -class ResponseFormatResponseFormat1(TypedDict): - type: Literal['json_schema'] - json_schema: ResponseFormatJsonSchema - - -ResponseFormat: TypeAlias = ( - ResponseFormatResponseFormat | ResponseFormatResponseFormat1 | ResponseFormatResponseFormat2 -) - - -class SpanAttributes(TypedDict): - name: NotRequired[str | None] - """ - Name of the span, for display purposes only - """ - type: NotRequired[SpanType | None] - - -class TopicAutomationConfig(TypedDict): - event_type: Literal['topic'] - """ - The type of automation. - """ - sampling_rate: float - """ - The sampling rate for topic automation - """ - facet_functions: Sequence[SavedFunctionId] - """ - Facet functions used by the topic automation - """ - topic_map_functions: Sequence[TopicMapFunctionAutomation] - """ - Topic map functions with optional per-topic-map filters - """ - scope: NotRequired[SpanScope | TraceScope | GroupScope | None] - """ - Execution scope for topic automation. Defaults to span-level execution. - """ - data_scope: NotRequired[TopicAutomationDataScope | None] - btql_filter: NotRequired[str | None] - """ - Optional BTQL filter applied before topic automation. - """ - - -class ViewData(TypedDict): - search: NotRequired[ViewDataSearch | None] - custom_charts: NotRequired[Any | None] - - -class ExperimentEvent(TypedDict): - id: str - """ - A unique identifier for the experiment event. If you don't provide one, Braintrust will generate one for you - """ - _xact_id: str - """ - The transaction id of an event is unique to the network operation that processed the event insertion. Transaction ids are monotonically increasing over time and can be used to retrieve a versioned snapshot of the experiment (see the `version` parameter) - """ - created: str - """ - The timestamp the experiment event was created - """ - _pagination_key: NotRequired[str | None] - """ - A stable, time-ordered key that can be used to paginate over experiment events. This field is auto-generated by Braintrust and only exists in Brainstore. - """ - project_id: str - """ - Unique identifier for the project that the experiment belongs under - """ - experiment_id: str - """ - Unique identifier for the experiment - """ - input: NotRequired[Any | None] - """ - The arguments that uniquely define a test case (an arbitrary, JSON serializable object). Later on, Braintrust will use the `input` to know whether two test cases are the same between experiments, so they should not contain experiment-specific state. A simple rule of thumb is that if you run the same experiment twice, the `input` should be identical - """ - output: NotRequired[Any | None] - """ - The output of your application, including post-processing (an arbitrary, JSON serializable object), that allows you to determine whether the result is correct or not. For example, in an app that generates SQL queries, the `output` should be the _result_ of the SQL query generated by the model, not the query itself, because there may be multiple valid queries that answer a single question - """ - expected: NotRequired[Any | None] - """ - The ground truth value (an arbitrary, JSON serializable object) that you'd compare to `output` to determine if your `output` value is correct or not. Braintrust currently does not compare `output` to `expected` for you, since there are so many different ways to do that correctly. Instead, these values are just used to help you navigate your experiments while digging into analyses. However, we may later use these values to re-score outputs or fine-tune your models - """ - error: NotRequired[Any | None] - """ - The error that occurred, if any. - """ - scores: NotRequired[Mapping[str, Any] | None] - """ - A dictionary of numeric values (between 0 and 1) to log. The scores should give you a variety of signals that help you determine how accurate the outputs are compared to what you expect and diagnose failures. For example, a summarization app might have one score that tells you how accurate the summary is, and another that measures the word similarity between the generated and grouth truth summary. The word similarity score could help you determine whether the summarization was covering similar concepts or not. You can use these scores to help you sort, filter, and compare experiments - """ - metadata: NotRequired[ExperimentEventMetadata | None] - """ - A dictionary with additional data about the test example, model outputs, or just about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any JSON-serializable type, but its keys must be strings - """ - tags: NotRequired[Sequence[str] | None] - """ - A list of tags to log - """ - metrics: NotRequired[ExperimentEventMetrics | None] - """ - Metrics are numerical measurements tracking the execution of the code that produced the experiment event. Use "start" and "end" to track the time span over which the experiment event was produced - """ - context: NotRequired[ExperimentEventContext | None] - """ - Context is additional information about the code that produced the experiment event. It is essentially the textual counterpart to `metrics`. Use the `caller_*` attributes to track the location in code which produced the experiment event - """ - span_id: str - """ - A unique identifier used to link different experiment events together as part of a full trace. See the [tracing guide](https://www.braintrust.dev/docs/instrument) for full details on tracing - """ - span_parents: NotRequired[Sequence[str] | None] - """ - An array of the parent `span_ids` of this experiment event. This should be empty for the root span of a trace, and should most often contain just one parent element for subspans - """ - root_span_id: str - """ - A unique identifier for the trace this experiment event belongs to - """ - span_attributes: NotRequired[SpanAttributes | None] - is_root: NotRequired[bool | None] - """ - Whether this span is a root span - """ - origin: NotRequired[ObjectReferenceNullish | None] - comments: NotRequired[Sequence[Any] | None] - """ - Optional list of comments attached to this event - """ - audit_data: NotRequired[Sequence[Any] | None] - """ - Optional list of audit entries attached to this event - """ - facets: NotRequired[Mapping[str, Any] | None] - """ - Facets for categorization (dictionary from facet id to value) - """ - classifications: NotRequired[Mapping[str, Any] | None] - """ - Classifications for this event (dictionary from classification name to items) - """ - - -class GraphNodeGraphNode7(TypedDict): - description: NotRequired[str | None] - """ - The description of the node - """ - position: NotRequired[GraphNodeGraphNode7Position | None] - """ - The position of the node - """ - type: Literal['prompt_template'] - prompt: PromptBlockData - - -GraphNode: TypeAlias = ( - GraphNodeGraphNode - | GraphNodeGraphNode1 - | GraphNodeGraphNode2 - | GraphNodeGraphNode3 - | GraphNodeGraphNode4 - | GraphNodeGraphNode5 - | GraphNodeGraphNode6 - | GraphNodeGraphNode7 -) - - -class ProjectAutomation(TypedDict): - id: str - """ - Unique identifier for the project automation - """ - project_id: str - """ - Unique identifier for the project that the project automation belongs under - """ - user_id: NotRequired[str | None] - """ - Identifies the user who created the project automation - """ - created: NotRequired[str | None] - """ - Date of project automation creation - """ - name: str - """ - Name of the project automation - """ - description: NotRequired[str | None] - """ - Textual description of the project automation - """ - config: ( - ProjectAutomationConfig - | ProjectAutomationConfig1 - | ProjectAutomationConfig2 - | ProjectAutomationConfig3 - | TopicAutomationConfig - ) - """ - The configuration for the automation rule - """ - - -class ProjectLogsEvent(TypedDict): - id: str - """ - A unique identifier for the project logs event. If you don't provide one, Braintrust will generate one for you - """ - _xact_id: str - """ - The transaction id of an event is unique to the network operation that processed the event insertion. Transaction ids are monotonically increasing over time and can be used to retrieve a versioned snapshot of the project logs (see the `version` parameter) - """ - _pagination_key: NotRequired[str | None] - """ - A stable, time-ordered key that can be used to paginate over project logs events. This field is auto-generated by Braintrust and only exists in Brainstore. - """ - created: str - """ - The timestamp the project logs event was created - """ - org_id: str - """ - Unique id for the organization that the project belongs under - """ - project_id: str - """ - Unique identifier for the project - """ - log_id: Literal['g'] - """ - A literal 'g' which identifies the log as a project log - """ - input: NotRequired[Any | None] - """ - The arguments that uniquely define a user input (an arbitrary, JSON serializable object). - """ - output: NotRequired[Any | None] - """ - The output of your application, including post-processing (an arbitrary, JSON serializable object), that allows you to determine whether the result is correct or not. For example, in an app that generates SQL queries, the `output` should be the _result_ of the SQL query generated by the model, not the query itself, because there may be multiple valid queries that answer a single question. - """ - expected: NotRequired[Any | None] - """ - The ground truth value (an arbitrary, JSON serializable object) that you'd compare to `output` to determine if your `output` value is correct or not. Braintrust currently does not compare `output` to `expected` for you, since there are so many different ways to do that correctly. Instead, these values are just used to help you navigate while digging into analyses. However, we may later use these values to re-score outputs or fine-tune your models. - """ - error: NotRequired[Any | None] - """ - The error that occurred, if any. - """ - scores: NotRequired[Mapping[str, Any] | None] - """ - A dictionary of numeric values (between 0 and 1) to log. The scores should give you a variety of signals that help you determine how accurate the outputs are compared to what you expect and diagnose failures. For example, a summarization app might have one score that tells you how accurate the summary is, and another that measures the word similarity between the generated and grouth truth summary. The word similarity score could help you determine whether the summarization was covering similar concepts or not. You can use these scores to help you sort, filter, and compare logs. - """ - metadata: NotRequired[ProjectLogsEventMetadata | None] - """ - A dictionary with additional data about the test example, model outputs, or just about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any JSON-serializable type, but its keys must be strings - """ - tags: NotRequired[Sequence[str] | None] - """ - A list of tags to log - """ - metrics: NotRequired[ProjectLogsEventMetrics | None] - """ - Metrics are numerical measurements tracking the execution of the code that produced the project logs event. Use "start" and "end" to track the time span over which the project logs event was produced - """ - context: NotRequired[ProjectLogsEventContext | None] - """ - Context is additional information about the code that produced the project logs event. It is essentially the textual counterpart to `metrics`. Use the `caller_*` attributes to track the location in code which produced the project logs event - """ - span_id: str - """ - A unique identifier used to link different project logs events together as part of a full trace. See the [tracing guide](https://www.braintrust.dev/docs/instrument) for full details on tracing - """ - span_parents: NotRequired[Sequence[str] | None] - """ - An array of the parent `span_ids` of this project logs event. This should be empty for the root span of a trace, and should most often contain just one parent element for subspans - """ - root_span_id: str - """ - A unique identifier for the trace this project logs event belongs to - """ - is_root: NotRequired[bool | None] - """ - Whether this span is a root span - """ - span_attributes: NotRequired[SpanAttributes | None] - origin: NotRequired[ObjectReferenceNullish | None] - comments: NotRequired[Sequence[Any] | None] - """ - Optional list of comments attached to this event - """ - audit_data: NotRequired[Sequence[Any] | None] - """ - Optional list of audit entries attached to this event - """ - _async_scoring_state: NotRequired[Any | None] - """ - The async scoring state for this event - """ - facets: NotRequired[Mapping[str, Any] | None] - """ - Facets for categorization (dictionary from facet id to value) - """ - classifications: NotRequired[Mapping[str, Any] | None] - """ - Classifications for this event (dictionary from classification name to items) - """ - - -class ProjectScore(TypedDict): - id: str - """ - Unique identifier for the project score - """ - project_id: str - """ - Unique identifier for the project that the project score belongs under - """ - user_id: str - created: NotRequired[str | None] - """ - Date of project score creation - """ - name: str - """ - Name of the project score - """ - description: NotRequired[str | None] - """ - Textual description of the project score - """ - score_type: ProjectScoreType - categories: NotRequired[ProjectScoreCategories | None] - config: NotRequired[ProjectScoreConfig | None] - position: NotRequired[str | None] - """ - An optional LexoRank-based string that sets the sort position for the score in the UI - """ - - -class PromptData(TypedDict): - prompt: NotRequired[PromptBlockDataNullish | None] - options: NotRequired[PromptOptionsNullish | None] - parser: NotRequired[PromptParserNullish | None] - tool_functions: NotRequired[Sequence[SavedFunctionId] | None] - template_format: NotRequired[Literal['mustache', 'nunjucks', 'none'] | None] - mcp: NotRequired[Mapping[str, Any] | None] - origin: NotRequired[PromptDataOrigin | None] - - -class PromptDataNullish(TypedDict): - prompt: NotRequired[PromptBlockDataNullish | None] - options: NotRequired[PromptOptionsNullish | None] - parser: NotRequired[PromptParserNullish | None] - tool_functions: NotRequired[Sequence[SavedFunctionId] | None] - template_format: NotRequired[Literal['mustache', 'nunjucks', 'none'] | None] - mcp: NotRequired[Mapping[str, Any] | None] - origin: NotRequired[PromptDataNullishOrigin | None] - - -class TaskTask5(TypedDict): - inline_prompt: NotRequired[PromptData | None] - inline_function: Mapping[str, Any] - function_type: NotRequired[FunctionTypeEnum | None] - name: NotRequired[str | None] - """ - The name of the inline function - """ - - -class TaskTask6(TypedDict): - inline_prompt: PromptData - function_type: NotRequired[FunctionTypeEnum | None] - name: NotRequired[str | None] - """ - The name of the inline prompt - """ - - -class TaskTask13(TaskTask5, TaskTask7): - pass - - -class TaskTask14(TaskTask6, TaskTask7): - pass - - -Task: TypeAlias = TaskTask8 | TaskTask9 | TaskTask10 | TaskTask11 | TaskTask12 | TaskTask13 | TaskTask14 - - -class View(TypedDict): - id: str - """ - Unique identifier for the view - """ - object_type: AclObjectType - object_id: str - """ - The id of the object the view applies to - """ - view_type: Literal[ - 'projects', - 'experiments', - 'experiment', - 'playgrounds', - 'playground', - 'datasets', - 'dataset', - 'prompts', - 'parameters', - 'tools', - 'scorers', - 'classifiers', - 'logs', - 'monitor', - 'for_review_project_log', - 'for_review_experiments', - 'for_review_datasets', - ] - """ - Type of object that the view corresponds to. - """ - name: str - """ - Name of the view - """ - created: NotRequired[str | None] - """ - Date of view creation - """ - view_data: NotRequired[ViewData | None] - options: NotRequired[ViewOptions | None] - user_id: NotRequired[str | None] - """ - Identifies the user who created the view - """ - deleted_at: NotRequired[str | None] - """ - Date of role deletion, or null if the role is still active - """ - - -class FunctionIdFunctionId5(TypedDict): - inline_prompt: NotRequired[PromptData | None] - inline_function: Mapping[str, Any] - function_type: NotRequired[FunctionTypeEnum | None] - name: NotRequired[str | None] - """ - The name of the inline function - """ - - -class FunctionIdFunctionId6(TypedDict): - inline_prompt: PromptData - function_type: NotRequired[FunctionTypeEnum | None] - name: NotRequired[str | None] - """ - The name of the inline prompt - """ - - -FunctionId: TypeAlias = ( - FunctionIdFunctionId - | FunctionIdFunctionId1 - | FunctionIdFunctionId2 - | FunctionIdFunctionId3 - | FunctionIdFunctionId4 - | FunctionIdFunctionId5 - | FunctionIdFunctionId6 -) -""" -Options for identifying a function -""" - - -class GraphData(TypedDict): - type: Literal['graph'] - nodes: Mapping[str, GraphNode] - edges: Mapping[str, GraphEdge] - - -class InvokeFunctionInvokeFunction5(TypedDict): - inline_prompt: NotRequired[PromptData | None] - inline_function: Mapping[str, Any] - function_type: NotRequired[FunctionTypeEnum | None] - name: NotRequired[str | None] - """ - The name of the inline function - """ - - -class InvokeFunctionInvokeFunction6(TypedDict): - inline_prompt: PromptData - function_type: NotRequired[FunctionTypeEnum | None] - name: NotRequired[str | None] - """ - The name of the inline prompt - """ - - -class InvokeFunctionInvokeFunction13(InvokeFunctionInvokeFunction5, InvokeFunctionInvokeFunction7): - pass - - -class InvokeFunctionInvokeFunction14(InvokeFunctionInvokeFunction6, InvokeFunctionInvokeFunction7): - pass - - -InvokeFunction: TypeAlias = ( - InvokeFunctionInvokeFunction8 - | InvokeFunctionInvokeFunction9 - | InvokeFunctionInvokeFunction10 - | InvokeFunctionInvokeFunction11 - | InvokeFunctionInvokeFunction12 - | InvokeFunctionInvokeFunction13 - | InvokeFunctionInvokeFunction14 -) -""" -Options for identifying a function -""" - - -class Prompt(TypedDict): - id: str - """ - Unique identifier for the prompt - """ - _xact_id: str - """ - The transaction id of an event is unique to the network operation that processed the event insertion. Transaction ids are monotonically increasing over time and can be used to retrieve a versioned snapshot of the prompt (see the `version` parameter) - """ - project_id: str - """ - Unique identifier for the project that the prompt belongs under - """ - log_id: Literal['p'] - """ - A literal 'p' which identifies the object as a project prompt - """ - org_id: str - """ - Unique identifier for the organization - """ - name: str - """ - Name of the prompt - """ - slug: str - """ - Unique identifier for the prompt - """ - description: NotRequired[str | None] - """ - Textual description of the prompt - """ - created: NotRequired[str | None] - """ - Date of prompt creation - """ - prompt_data: NotRequired[PromptDataNullish | None] - tags: NotRequired[Sequence[str] | None] - """ - A list of tags for the prompt - """ - metadata: NotRequired[Mapping[str, Any] | None] - """ - User-controlled metadata about the prompt - """ - function_type: NotRequired[FunctionTypeEnumNullish | None] - - -class RunEval(TypedDict): - project_id: str - """ - Unique identifier for the project to run the eval in - """ - data: RunEvalData | RunEvalData1 | RunEvalData2 - """ - The dataset to use - """ - name: NotRequired[str | None] - """ - The name of the eval to run when multiple evals available - """ - parameters: NotRequired[Mapping[str, Any] | None] - """ - Values for any parameters used in the eval - """ - task: Task - scores: Sequence[FunctionId] - """ - The functions to score the eval on - """ - experiment_name: NotRequired[str | None] - """ - An optional name for the experiment created by this eval. If it conflicts with an existing experiment, it will be suffixed with a unique identifier. - """ - metadata: NotRequired[Mapping[str, Any] | None] - """ - Optional experiment-level metadata to store about the evaluation. You can later use this to slice & dice across experiments. - """ - parent: NotRequired[Parent | None] - stream: NotRequired[bool | None] - """ - Whether to stream the results of the eval. If true, the request will return two events: one to indicate the experiment has started, and another upon completion. If false, the request will return the evaluation's summary upon completion. - """ - trial_count: NotRequired[float | None] - """ - The number of times to run the evaluator per input. This is useful for evaluating applications that have non-deterministic behavior and gives you both a stronger aggregate measure and a sense of the variance in the results. - """ - is_public: NotRequired[bool | None] - """ - Whether the experiment should be public. Defaults to false. - """ - timeout: NotRequired[float | None] - """ - The maximum duration, in milliseconds, to run the evaluation. Defaults to undefined, in which case there is no timeout. - """ - max_concurrency: NotRequired[float | None] - """ - The maximum number of tasks/scorers that will be run concurrently. Defaults to 10. If null is provided, no max concurrency will be used. - """ - base_experiment_name: NotRequired[str | None] - """ - An optional experiment name to use as a base. If specified, the new experiment will be summarized and compared to this experiment. - """ - base_experiment_id: NotRequired[str | None] - """ - An optional experiment id to use as a base. If specified, the new experiment will be summarized and compared to this experiment. - """ - git_metadata_settings: NotRequired[GitMetadataSettings | None] - repo_info: NotRequired[RepoInfo | None] - strict: NotRequired[bool | None] - """ - If true, throw an error if one of the variables in the prompt is not present in the input - """ - stop_token: NotRequired[str | None] - """ - The token to stop the run - """ - extra_messages: NotRequired[str | None] - """ - A template path of extra messages to append to the conversion. These messages will be appended to the end of the conversation, after the last message. - """ - tags: NotRequired[Sequence[str] | None] - """ - Optional tags that will be added to the experiment. - """ - mcp_auth: NotRequired[Mapping[str, RunEvalMcpAuth] | None] - - -FunctionData: TypeAlias = ( - FunctionDataFunctionData - | FunctionDataFunctionData1 - | GraphData - | FunctionDataFunctionData2 - | FunctionDataFunctionData3 - | FacetData - | BatchedFacetData - | FunctionDataFunctionData4 - | TopicMapData -) - - -class Function(TypedDict): - id: str - """ - Unique identifier for the prompt - """ - _xact_id: str - """ - The transaction id of an event is unique to the network operation that processed the event insertion. Transaction ids are monotonically increasing over time and can be used to retrieve a versioned snapshot of the prompt (see the `version` parameter) - """ - project_id: str - """ - Unique identifier for the project that the prompt belongs under - """ - log_id: Literal['p'] - """ - A literal 'p' which identifies the object as a project prompt - """ - org_id: str - """ - Unique identifier for the organization - """ - name: str - """ - Name of the prompt - """ - slug: str - """ - Unique identifier for the prompt - """ - description: NotRequired[str | None] - """ - Textual description of the prompt - """ - created: NotRequired[str | None] - """ - Date of prompt creation - """ - prompt_data: NotRequired[PromptDataNullish | None] - tags: NotRequired[Sequence[str] | None] - """ - A list of tags for the prompt - """ - metadata: NotRequired[Mapping[str, Any] | None] - """ - User-controlled metadata about the prompt - """ - function_type: NotRequired[FunctionTypeEnumNullish | None] - function_data: FunctionData - origin: NotRequired[FunctionOrigin | None] - function_schema: NotRequired[FunctionFunctionSchema | None] - """ - JSON schema for the function's parameters and return type - """ - -__all__ = [] diff --git a/py/src/braintrust/audit.py b/py/src/braintrust/audit.py deleted file mode 100644 index 55344db29..000000000 --- a/py/src/braintrust/audit.py +++ /dev/null @@ -1,22 +0,0 @@ -""" -Utilities for working with audit headers. -""" - -import base64 -import gzip -import json -from typing import TypedDict - - -class AuditResource(TypedDict): - type: str - id: str - name: str - - -def parse_audit_resources(hdr: str) -> list[AuditResource]: - j = json.loads(hdr) - if j["v"] == 1: - return json.loads(gzip.decompress(base64.b64decode(j["p"]))) - else: - raise ValueError(f"Unsupported audit resources protocol version: {j['v']}") diff --git a/py/src/braintrust/auto.py b/py/src/braintrust/auto.py deleted file mode 100644 index b1b552f8c..000000000 --- a/py/src/braintrust/auto.py +++ /dev/null @@ -1,179 +0,0 @@ -""" -Auto-instrumentation for AI/ML libraries. - -Provides one-line instrumentation for supported libraries. -""" - -from __future__ import annotations - -import logging -from contextlib import contextmanager - -__all__ = ["auto_instrument"] - -logger = logging.getLogger(__name__) - - -@contextmanager -def _try_patch(): - """Context manager that suppresses ImportError and logs other exceptions.""" - try: - yield - except ImportError: - pass - except Exception: - logger.exception("Failed to instrument") - - -def auto_instrument( - *, - openai: bool = True, - anthropic: bool = True, - litellm: bool = True, - pydantic_ai: bool = True, - google_genai: bool = True, - agno: bool = True, - claude_agent_sdk: bool = True, - dspy: bool = True, -) -> dict[str, bool]: - """ - Auto-instrument supported AI/ML libraries for Braintrust tracing. - - Safe to call multiple times - already instrumented libraries are skipped. - - Note on import order: If you use `from openai import OpenAI` style imports, - call auto_instrument() first. If you use `import openai` style imports, - order doesn't matter since attribute lookup happens dynamically. - - Args: - openai: Enable OpenAI instrumentation (default: True) - anthropic: Enable Anthropic instrumentation (default: True) - litellm: Enable LiteLLM instrumentation (default: True) - pydantic_ai: Enable Pydantic AI instrumentation (default: True) - google_genai: Enable Google GenAI instrumentation (default: True) - agno: Enable Agno instrumentation (default: True) - claude_agent_sdk: Enable Claude Agent SDK instrumentation (default: True) - dspy: Enable DSPy instrumentation (default: True) - - Returns: - Dict mapping integration name to whether it was successfully instrumented. - - Example: - ```python - import braintrust - braintrust.auto_instrument() - - # OpenAI - import openai - client = openai.OpenAI() - client.chat.completions.create(model="gpt-4o-mini", messages=[...]) - - # Anthropic - import anthropic - client = anthropic.Anthropic() - client.messages.create(model="claude-sonnet-4-20250514", messages=[...]) - - # LiteLLM - import litellm - litellm.completion(model="gpt-4o-mini", messages=[...]) - - # DSPy - import dspy - lm = dspy.LM("openai/gpt-4o-mini") - dspy.configure(lm=lm) - - # Pydantic AI - from pydantic_ai import Agent - agent = Agent("openai:gpt-4o-mini") - result = agent.run_sync("Hello!") - - # Google GenAI - from google.genai import Client - client = Client() - client.models.generate_content(model="gemini-2.0-flash", contents="Hello!") - ``` - """ - results = {} - - if openai: - results["openai"] = _instrument_openai() - if anthropic: - results["anthropic"] = _instrument_anthropic() - if litellm: - results["litellm"] = _instrument_litellm() - if pydantic_ai: - results["pydantic_ai"] = _instrument_pydantic_ai() - if google_genai: - results["google_genai"] = _instrument_google_genai() - if agno: - results["agno"] = _instrument_agno() - if claude_agent_sdk: - results["claude_agent_sdk"] = _instrument_claude_agent_sdk() - if dspy: - results["dspy"] = _instrument_dspy() - - return results - - -def _instrument_openai() -> bool: - with _try_patch(): - from braintrust.oai import patch_openai - - return patch_openai() - return False - - -def _instrument_anthropic() -> bool: - with _try_patch(): - from braintrust.wrappers.anthropic import patch_anthropic - - return patch_anthropic() - return False - - -def _instrument_litellm() -> bool: - with _try_patch(): - from braintrust.wrappers.litellm import patch_litellm - - return patch_litellm() - return False - - -def _instrument_pydantic_ai() -> bool: - with _try_patch(): - from braintrust.wrappers.pydantic_ai import setup_pydantic_ai - - return setup_pydantic_ai() - return False - - -def _instrument_google_genai() -> bool: - with _try_patch(): - from braintrust.wrappers.google_genai import setup_genai - - return setup_genai() - return False - - -def _instrument_agno() -> bool: - with _try_patch(): - from braintrust.wrappers.agno import setup_agno - - return setup_agno() - return False - - -def _instrument_claude_agent_sdk() -> bool: - with _try_patch(): - from braintrust.wrappers.claude_agent_sdk import setup_claude_agent_sdk - - return setup_claude_agent_sdk() - return False - - -def _instrument_dspy() -> bool: - with _try_patch(): - from braintrust.wrappers.dspy import patch_dspy - - return patch_dspy() - return False diff --git a/py/src/braintrust/aws.py b/py/src/braintrust/aws.py deleted file mode 100644 index fe562631c..000000000 --- a/py/src/braintrust/aws.py +++ /dev/null @@ -1,16 +0,0 @@ -import boto3 - - -class LazyClient: - def __init__(self, client_name): - self.client_name = client_name - self.client = None - - def __getattr__(self, name): - if self.client is None: - self.client = boto3.client(self.client_name) - return getattr(self.client, name) - - -def __getattr__(name: str): - return LazyClient(name.replace("_", "-")) diff --git a/py/src/braintrust/bt_json.py b/py/src/braintrust/bt_json.py deleted file mode 100644 index 4fc36f8ce..000000000 --- a/py/src/braintrust/bt_json.py +++ /dev/null @@ -1,275 +0,0 @@ -import dataclasses -import json -import math -from typing import Any, Callable, Mapping, NamedTuple, cast, overload - -# Try to import orjson for better performance -# If not available, we'll use standard json -try: - import orjson - - _HAS_ORJSON = True -except ImportError: - _HAS_ORJSON = False - - - -def _to_bt_safe(v: Any) -> Any: - """ - Converts the object to a Braintrust-safe representation (i.e. Attachment objects are safe (specially handled by background logger)). - """ - # avoid circular imports - from braintrust.logger import BaseAttachment, Dataset, Experiment, Logger, ReadonlyAttachment, Span - - if isinstance(v, Span): - return "" - - if isinstance(v, Experiment): - return "" - - if isinstance(v, Dataset): - return "" - - if isinstance(v, Logger): - return "" - - if isinstance(v, BaseAttachment): - return v - - if isinstance(v, ReadonlyAttachment): - return v.reference - - if dataclasses.is_dataclass(v) and not isinstance(v, type): - # Use manual field iteration instead of dataclasses.asdict() because - # asdict() deep-copies values, which breaks objects like Attachment - # that contain non-copyable items (thread locks, file handles, etc.) - return {f.name: _to_bt_safe(getattr(v, f.name)) for f in dataclasses.fields(v)} - - # Pydantic model classes (not instances) with model_json_schema - if isinstance(v, type) and hasattr(v, "model_json_schema") and callable(cast(Any, v).model_json_schema): - try: - return cast(Any, v).model_json_schema() - except Exception: - pass - - # Attempt to dump a Pydantic v2 `BaseModel`. - try: - return cast(Any, v).model_dump(exclude_none=True) - except (AttributeError, TypeError): - pass - - # Attempt to dump a Pydantic v1 `BaseModel`. - try: - return cast(Any, v).dict(exclude_none=True) - except (AttributeError, TypeError): - pass - - if isinstance(v, float): - # Handle NaN and Infinity for JSON compatibility - if math.isnan(v): - return "NaN" - - if math.isinf(v): - return "Infinity" if v > 0 else "-Infinity" - - return v - - if isinstance(v, (int, str, bool)) or v is None: - # Skip roundtrip for primitive types. - return v - - # Note: we avoid using copy.deepcopy, because it's difficult to - # guarantee the independence of such copied types from their origin. - # E.g. the original type could have a `__del__` method that alters - # some shared internal state, and we need this deep copy to be - # fully-independent from the original. - - # We pass `encoder=_str_encoder` since we've already tried converting rich objects to json safe objects. - return bt_loads(bt_dumps(v, encoder=_str_encoder)) - -@overload -def bt_safe_deep_copy( - obj: Mapping[str, Any], - max_depth: int = ..., -) -> dict[str, Any]: ... - -@overload -def bt_safe_deep_copy( - obj: list[Any], - max_depth: int = ..., -) -> list[Any]: ... - -@overload -def bt_safe_deep_copy( - obj: Any, - max_depth: int = ..., -) -> Any: ... -def bt_safe_deep_copy(obj: Any, max_depth: int=200): - """ - Creates a deep copy of the given object and converts rich objects to Braintrust-safe representations. See `_to_bt_safe` for more details. - - Args: - obj: Object to deep copy and sanitize. - to_json_safe: Function to ensure the object is json safe. - max_depth: Maximum depth to copy. - - Returns: - Deep copy of the object. - """ - # Track visited objects to detect circular references - visited: set[int] = set() - - def _deep_copy_object(v: Any, depth: int = 0) -> Any: - # Check depth limit - use >= to stop before exceeding - if depth >= max_depth: - return "" - - # Check for circular references in mutable containers - # Use id() to track object identity - if isinstance(v, (Mapping, list, tuple, set)): - obj_id = id(v) - if obj_id in visited: - return "" - visited.add(obj_id) - try: - if isinstance(v, Mapping): - # Prevent dict keys from holding references to user data. Note that - # `bt_json` already coerces keys to string, a behavior that comes from - # `json.dumps`. However, that runs at log upload time, while we want to - # cut out all the references to user objects synchronously in this - # function. - result = {} - for k in v: - try: - key_str = str(k) - except Exception: - # If str() fails on the key, use a fallback representation - key_str = f"" - result[key_str] = _deep_copy_object(v[k], depth + 1) - return result - elif isinstance(v, (list, tuple, set)): - return [_deep_copy_object(x, depth + 1) for x in v] - finally: - # Remove from visited set after processing to allow the same object - # to appear in different branches of the tree - visited.discard(obj_id) - - try: - return _to_bt_safe(v) - except Exception: - return f"" - - return _deep_copy_object(obj) - -def _safe_str(obj: Any) -> str: - try: - return str(obj) - except Exception: - return f"" - - -def _to_json_safe(obj: Any) -> Any: - """ - Handler for non-JSON-serializable objects. Returns a string representation of the object. - """ - # avoid circular imports - from braintrust.logger import BaseAttachment - - try: - v = _to_bt_safe(obj) - - # JSON-safe representation of Attachment objects are their reference. - # If we get this object at this point, we have to assume someone has already uploaded the attachment! - if isinstance(v, BaseAttachment): - v = v.reference - - return v - except Exception: - pass - - # When everything fails, try to return the string representation of the object - return _safe_str(obj) - - -class BraintrustJSONEncoder(json.JSONEncoder): - """ - Custom JSON encoder for standard json library. - - This is used as a fallback when orjson is not available or fails. - """ - - def default(self, o: Any): - return _to_json_safe(o) - - -class BraintrustStrEncoder(json.JSONEncoder): - def default(self, o: Any): - return _safe_str(o) - - -class Encoder(NamedTuple): - native: type[json.JSONEncoder] - orjson: Callable[[Any], Any] - -_json_encoder = Encoder(native=BraintrustJSONEncoder, orjson=_to_json_safe) -_str_encoder = Encoder(native=BraintrustStrEncoder, orjson=_safe_str) - -def bt_dumps(obj: Any, encoder: Encoder | None=_json_encoder, **kwargs: Any) -> str: - """ - Serialize obj to a JSON-formatted string. - - Automatically uses orjson if available for better performance (3-5x faster), - with fallback to standard json library if orjson is not installed or fails. - - Args: - obj: Object to serialize - encoder: Encoder to use, defaults to `_default_encoder` - **kwargs: Additional arguments (passed to json.dumps in fallback path) - - Returns: - JSON string representation of obj - """ - if _HAS_ORJSON: - # Try orjson first for better performance - try: - # pylint: disable=no-member # orjson is a C extension, pylint can't introspect it - return orjson.dumps( # type: ignore[possibly-unbound] - obj, - default=encoder.orjson if encoder else None, - # options match json.dumps behavior for bc - option=orjson.OPT_SORT_KEYS | orjson.OPT_SERIALIZE_NUMPY | orjson.OPT_NON_STR_KEYS, # type: ignore[possibly-unbound] - ).decode("utf-8") - except Exception: - # If orjson fails, fall back to standard json - pass - - # Use standard json (either orjson not available or it failed) - # Use sort_keys=True for deterministic output (matches orjson OPT_SORT_KEYS) - return json.dumps(obj, cls=encoder.native if encoder else None, allow_nan=False, sort_keys=True, **kwargs) - - -def bt_loads(s: str, **kwargs) -> Any: - """ - Deserialize s (a str containing a JSON document) to a Python object. - - Automatically uses orjson if available for better performance (2-3x faster), - with fallback to standard json library if orjson is not installed or fails. - - Args: - s: JSON string to deserialize - **kwargs: Additional arguments (passed to json.loads in fallback path) - - Returns: - Python object representation of JSON string - """ - if _HAS_ORJSON: - # Try orjson first for better performance - try: - # pylint: disable=no-member # orjson is a C extension, pylint can't introspect it - return orjson.loads(s) # type: ignore[possibly-unbound] - except Exception: - # If orjson fails, fall back to standard json - pass - - # Use standard json (either orjson not available or it failed) - return json.loads(s, **kwargs) diff --git a/py/src/braintrust/cassettes/test_scorer_spans_have_purpose_attribute.yaml b/py/src/braintrust/cassettes/test_scorer_spans_have_purpose_attribute.yaml deleted file mode 100644 index a9981716e..000000000 --- a/py/src/braintrust/cassettes/test_scorer_spans_have_purpose_attribute.yaml +++ /dev/null @@ -1,76 +0,0 @@ -interactions: -- request: - body: '{"id": "test-scorer-purpose"}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '29' - Content-Type: - - application/json - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://www.braintrust.dev/api/base_experiment/get_id - response: - body: - string: "[\n {\n \"validation\": \"uuid\",\n \"code\": \"invalid_string\",\n - \ \"message\": \"Invalid uuid\",\n \"path\": [\n \"id\"\n ]\n - \ }\n] [user_email=___braintrust_anon_user___@braintrustdata.com] [timestamp=1768425457.184] - [request_id=iad1::6csht-1768425457143-aa189dce84b1]" - headers: - Cache-Control: - - public, max-age=0, must-revalidate - Content-Length: - - '267' - Content-Security-Policy: - - 'script-src ''self'' ''unsafe-eval'' ''wasm-unsafe-eval'' ''strict-dynamic'' - ''nonce-MTk3NTc4MTYtZTA3Zi00ZWI1LWI0NzUtNzIxZmUzYWQ0NWM3'' *.js.stripe.com - js.stripe.com maps.googleapis.com ; style-src ''self'' ''unsafe-inline'' *.braintrust.dev - btcm6qilbbhv4yi1.public.blob.vercel-storage.com fonts.googleapis.com www.gstatic.com - d4tuoctqmanu0.cloudfront.net; font-src ''self'' data: fonts.gstatic.com btcm6qilbbhv4yi1.public.blob.vercel-storage.com - cdn.jsdelivr.net d4tuoctqmanu0.cloudfront.net fonts.googleapis.com mintlify-assets.b-cdn.net - fonts.cdnfonts.com; object-src ''none''; base-uri ''self''; form-action ''self''; - frame-ancestors ''self''; worker-src ''self'' blob:; report-uri https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=16; - report-to csp-endpoint-0' - Content-Type: - - text/plain; charset=utf-8 - Date: - - Wed, 14 Jan 2026 21:17:37 GMT - Etag: - - '"1s0fpg0rx67f"' - Reporting-Endpoints: - - csp-endpoint-0="https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=16" - Server: - - Vercel - Set-Cookie: - - __Host-authjs.csrf-token=9a6048498082183115fcf2290e6cb6ed0429fff14433bd68c34e709d78817b13%7C27a7c08cfb55b7d29dd897d03d9fb00c07b536f29f9458829f96ca6d04fffbec; - Path=/; HttpOnly; Secure; SameSite=Lax - - __Secure-authjs.callback-url=https%3A%2F%2Fwww.braintrustdata.com; Path=/; - HttpOnly; Secure; SameSite=Lax - Strict-Transport-Security: - - max-age=63072000 - X-Clerk-Auth-Reason: - - session-token-and-uat-missing - X-Clerk-Auth-Status: - - signed-out - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-Matched-Path: - - /api/base_experiment/get_id - X-Nonce: - - MTk3NTc4MTYtZTA3Zi00ZWI1LWI0NzUtNzIxZmUzYWQ0NWM3 - X-Vercel-Cache: - - MISS - X-Vercel-Id: - - iad1::iad1::6csht-1768425457143-aa189dce84b1 - status: - code: 400 - message: Bad Request -version: 1 diff --git a/py/src/braintrust/cassettes/test_to_bt_safe_special_objects.yaml b/py/src/braintrust/cassettes/test_to_bt_safe_special_objects.yaml deleted file mode 100644 index 2c5f889ef..000000000 --- a/py/src/braintrust/cassettes/test_to_bt_safe_special_objects.yaml +++ /dev/null @@ -1,806 +0,0 @@ -interactions: -- request: - body: null - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '0' - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://www.braintrust.dev/api/apikey/login - response: - body: - string: '{"org_info":[{"id":"5ba6d482-b475-4c66-8cd2-5815694764e3","name":"matt-test-org","api_url":"https://api.braintrust.dev","git_metadata":null,"is_universal_api":null,"proxy_url":"https://api.braintrust.dev","realtime_url":"wss://realtime.braintrustapi.com"}]}' - headers: - Access-Control-Allow-Credentials: - - 'true' - Access-Control-Allow-Headers: - - X-CSRF-Token, X-Requested-With, Accept, Accept-Version, Content-Length, Content-MD5, - Content-Type, Date, X-Api-Version - Access-Control-Allow-Methods: - - GET,OPTIONS,PATCH,DELETE,POST,PUT - Access-Control-Allow-Origin: - - '*' - Cache-Control: - - public, max-age=0, must-revalidate - Content-Length: - - '257' - Content-Security-Policy: - - 'script-src ''self'' ''unsafe-eval'' ''wasm-unsafe-eval'' ''strict-dynamic'' - ''nonce-MTU4OGI3YWQtYmQyOS00YzVlLTlhNDMtMDQyODFhZGYxNjVi'' *.js.stripe.com - js.stripe.com maps.googleapis.com ; style-src ''self'' ''unsafe-inline'' *.braintrust.dev - btcm6qilbbhv4yi1.public.blob.vercel-storage.com fonts.googleapis.com www.gstatic.com - d4tuoctqmanu0.cloudfront.net; font-src ''self'' data: fonts.gstatic.com btcm6qilbbhv4yi1.public.blob.vercel-storage.com - cdn.jsdelivr.net d4tuoctqmanu0.cloudfront.net fonts.googleapis.com mintlify-assets.b-cdn.net - fonts.cdnfonts.com; object-src ''none''; base-uri ''self''; form-action ''self''; - frame-ancestors ''self''; worker-src ''self'' blob:; report-uri https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=16; - report-to csp-endpoint-0' - Content-Type: - - application/json; charset=utf-8 - Date: - - Wed, 14 Jan 2026 21:01:52 GMT - Etag: - - '"ubzjf1iqqj75"' - Reporting-Endpoints: - - csp-endpoint-0="https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=16" - Server: - - Vercel - Strict-Transport-Security: - - max-age=63072000 - X-Clerk-Auth-Message: - - Invalid JWT form. A JWT consists of three parts separated by dots. (reason=token-invalid, - token-carrier=header) - X-Clerk-Auth-Reason: - - token-invalid - X-Clerk-Auth-Status: - - signed-out - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-Matched-Path: - - /api/apikey/login - X-Nonce: - - MTU4OGI3YWQtYmQyOS00YzVlLTlhNDMtMDQyODFhZGYxNjVi - X-Vercel-Cache: - - MISS - X-Vercel-Id: - - iad1::iad1::vrm7n-1768424512685-82e509afcbe9 - status: - code: 200 - message: OK -- request: - body: '{"project_name": "test", "project_id": null, "org_id": "5ba6d482-b475-4c66-8cd2-5815694764e3", - "update": null, "experiment_name": "test", "repo_info": {"commit": "78db572d12b7573245b1a4dea6edefd2d7d3e939", - "branch": "speed", "tag": null, "dirty": true, "author_name": "Matt Perpick", - "author_email": "matt@braintrustdata.com", "commit_message": "Speed up OpenAI - tests 9x by adding VCR cassettes\n\n- Add VCR decorators to 3 tests that were - making real API calls:\n - test_agents_tool_openai_nested_spans (5.97s -> <0.1s)\n - - test_braintrust_tracing_processor_concurrency_bug (1.40s -> 0.1s)\n - test_braintrust_tracing_processor_current_span_detection - (0.67s -> <0.1s)\n- Record cassettes for these tests\n- Remove unnecessary time.sleep(0.2) - from test_openai_streaming_with_break\n- Centralize vcr_config in conftest.py - with CI enforcement:\n - record_mode=\"none\" in CI (fail if cassette missing)\n - - record_mode=\"once\" locally (record if missing)\n- Remove duplicate vcr_config - fixtures from individual test files\n- Keep Google-specific vcr_config for HTTP - method uppercase normalization\n\nOpenAI wrapper tests: 9s -> 1s (9x faster)\nFull - nox session: 18s -> 10s (44% faster)\n\nCo-Authored-By: Claude Opus 4.5 ", - "commit_time": "2026-01-14T15:58:12-05:00", "git_diff": "diff --git a/.claude/settings.json - b/.claude/settings.json\nindex cd426b62..9a367086 100644\n--- a/.claude/settings.json\n+++ - b/.claude/settings.json\n@@ -40,6 +40,8 @@\n \"Bash(jq:*)\",\n \"Bash(source:*)\",\n \"Bash(cd:*)\",\n+ \"Bash(set:*)\",\n+ \"Bash(sort:*)\",\n \"Bash(.nox/*/bin/pytest:*)\",\n \"Bash(.nox/*/bin/python:*)\",\n \"Bash(.nox/*/bin/pip:*)\",\ndiff - --git a/py/src/braintrust/test_bt_json.py b/py/src/braintrust/test_bt_json.py\nindex - 7ea161df..304957cf 100644\n--- a/py/src/braintrust/test_bt_json.py\n+++ b/py/src/braintrust/test_bt_json.py\n@@ - -2,9 +2,12 @@\n # pyright: reportUnknownArgumentType=false\n # pyright: reportPrivateUsage=false\n - import json\n+import os\n from typing import Any\n from unittest import TestCase\n - \n+import pytest\n+\n from braintrust.bt_json import bt_dumps, bt_safe_deep_copy\n - from braintrust.logger import Attachment, ExternalAttachment\n \n@@ -281,30 - +284,33 @@ class TestBTJson(TestCase):\n self.assertTrue(\"(1, 2)\" - in result or \"1, 2\" in result)\n self.assertIn(\"None\", result)\n - \n- def test_to_bt_safe_special_objects(self):\n- \"\"\"Test _to_bt_safe - handling of Span, Experiment, Dataset, Logger objects.\"\"\"\n- from - braintrust import init, init_dataset, init_logger\n+@pytest.mark.vcr\n+def test_to_bt_safe_special_objects():\n+ \"\"\"Test - _to_bt_safe handling of Span, Experiment, Dataset, Logger objects.\"\"\"\n+ from - braintrust import init, init_dataset, init_logger\n \n- # Create actual - objects\n- exp = init(project=\"test\", experiment=\"test\")\n- dataset - = init_dataset(project=\"test\", name=\"test\")\n- logger = init_logger(project=\"test\")\n- span - = exp.start_span()\n+ # Create actual objects\n+ exp = init(project=\"test\", - experiment=\"test\")\n+ dataset = init_dataset(project=\"test\", name=\"test\")\n+ logger - = init_logger(project=\"test\")\n+ span = exp.start_span()\n \n- # - Import _to_bt_safe\n- from braintrust.bt_json import _to_bt_safe\n+ # - Import _to_bt_safe\n+ from braintrust.bt_json import _to_bt_safe\n+\n+ # - Test each special object\n+ assert _to_bt_safe(span) == \"\"\n+ assert - _to_bt_safe(exp) == \"\"\n+ assert _to_bt_safe(dataset) == \"\"\n+ assert - _to_bt_safe(logger) == \"\"\n \n- # Test each special object\n- self.assertEqual(_to_bt_safe(span), - \"\")\n- self.assertEqual(_to_bt_safe(exp), \"\")\n- self.assertEqual(_to_bt_safe(dataset), - \"\")\n- self.assertEqual(_to_bt_safe(logger), \"\")\n+ # - Clean up\n+ exp.flush()\n+ dataset.flush()\n+ logger.flush()\n \n- # - Clean up\n- exp.flush()\n- dataset.flush()\n- logger.flush()\n - \n+class TestBTJsonAttachments(TestCase):\n def test_to_bt_safe_attachments(self):\n \"\"\"Test - _to_bt_safe preserves BaseAttachment and converts ReadonlyAttachment to reference.\"\"\"\n from - braintrust.bt_json import _to_bt_safe"}, "ancestor_commits": ["b017a02240f978dcfe7feec58aeb85f8cbc91892", - "072d3765416d78e465a728df1b4a812992fba58a", "1671a73c21d09a1b4b73debce7cb2fa1d1b9ee54", - "7b6371f41f6a109ea068fd547b17a131d109ee85", "530a4be0108ff8cc783a49c6390f59b238782e58", - "3ca420e53e77d4665b91ccc7631c95dc97ce566d", "41aceab354ed312d4758b5a5b5c32bbdac40da48", - "6f303beaf59f892b9ed86eb4338900c7f82f7a68", "2d2f7e260b2027576963fad1c432197b15f2811e", - "04acf467f93d2b1064ef648c6583f76d96864578", "3dcfc326ee12b116d919974ef8bbf3cf307ee7fd", - "0740dc169ac9f267e4ec2d435165ca882df0fbc1", "270970d692adaf5d204d336ecdb4ee7f51042187", - "37e49012471ef81326f1313583497f48d612eed1", "8d9100b8341085366c11a36d93faa6009ecd4837", - "f53d7b868f610f1b215c799f25d4af171b59a000", "23b9a8d6b977d6849503433f8b38c49cf90e8203", - "5a31cd02719a5a282825a0fec7cb8d0fc44d0884", "7079cb29799d9fb9fbc919b7ddd1224935a551c7", - "d9c624ea93ca6bf62c2412abce1b3a2ef1a2be67", "126c367b3002ad57bb6aa7e08d04657db6f61980", - "b610cd36638ace60bca2aed261165afbf1c8c081", "52a8fa6d53c58908d95bb865f5907d829987fb97", - "65c037efdffceeec554b2706e16621cfc1704202", "c3bc923fafbc33485c9173c2401fa20897cf4ef1", - "6d6cc2f1e8b5da316c409a754ee8c844b8d2b2ee", "0ecb05e34031941426e3b9ce76760add8af6fdfd", - "8ab13f3f48af6a4d3c0b053e4bbabfd4f24f23ec", "10c14b3688c6969ef55951d5d82e744b87d6c356", - "05f569c80bddb61414e8f9a8adf49f8ca6b821b4", "2311d67956183da8b31bf1fdbe6e09b3ec7e242d", - "0b0bdd77c012e3f51c6402edcad35c8ac7ddf4cd", "ca2eb28a0f22a63b2b748d04e17268d11d35e0b0", - "c20c808993bba8d5604c2ac7848037d7ce430e89", "dcd4f5a4be171b1cac28a5eb3534e4b55420cc06", - "74dd883f7c03ba5591ecee0b2b76e9250781e181", "4f94c9548a493de11cd663fc78db21a81fe6f23c", - "b3c2b6f7120402b3f5f0fce9b7a1e6b7f7d04d47", "476a66a5d09ec811c9856f0f0f289b189859721e", - "2468e8006b8edf9ef8f273e142380faf34d380a6", "b88964e5a1b124816771e2c9c0a628c104ecfddb", - "a05dc4df62a20e9715abe697584641f0032742b5", "ad3ca98e3530c7dbdbb07f63a04fe4912e17f85a", - "dbbc1894ef31143816e5913676301261bc44aa4c", "db388916a9bc42b02e26b519c3c5f116c919cafc", - "78753fa68806ca7478572a8b37c1f8d97f99eee3", "759f04ddc9522471b46d139ab347668c849ef8dc", - "3857983398d6c7278686c9f12fc2f841c628bc06", "11d9aff118de5f99bb0b5d55bca04d0efb36746a", - "38ea029efe156f07385cbea0a8743e07f418dd76", "39cc2896ef3cf7f9c2320fa513c645a972063697", - "e085b589790c05aa27f52ced4fb0480230db38b5", "5a0afe994e81c19a69ac9ce3a60529b5e7e7c529", - "e42f891ae64b8844c2d37bf29c25821382ed654f", "1fa9fe250443884c450e92ca44a73f1de6a4a5d3", - "0241b89c84097de0dcc7cf7abd65098ac3020578", "a735eedc1c421d2ef287fd1759e96699dc7aa75c", - "cef88a007fa60f4cd873f1d891a54ce5e173f3aa", "db634461703056448a77d669d907c3861cee6dac", - "bb13adf5fd90e4ca503b6980e737bb0f3396a63a", "b48a316abdb2fab1e7e3a797af20a7af3395587f", - "8ad895a40e7c6e7940aa464acf094e5c4ce2451a", "685755051290c901f95f5f29d8cb313c43833837", - "45e647b94bf47482695fc747a2b8b5575611aa6f", "b6a2d2d34371c5ddebd8ff6176aed0f5104e2d01", - "8c2b2995c2097f5699c101f4ab5e653ff40014a1", "db9aaff1052e5229ad6cef667543f9f6620b119b", - "be421874326c6922eb48277e347ccbd53099117d", "c6f2bf1b0331ef0f7d295e29a86717fa8b5698a1", - "d27524c41de17bec43692c05870d5dcb0f0458a1", "ed35e0ef407e405818bc218566fa79323d7329f7", - "f0473314bed3f901febe06355abe43cc73ea30d0", "7cffe54f8b960931055ae20f5983b4ea34515eff", - "d46056681f07ab1a435c625c2b46ed561240a573", "b58203e04d2cafa99307443c62f5063ca7d2e228", - "38c38c579147306770452db9f2405c2aaa8bcda2", "38f4356286376bb91a2464352b4cceaba3a3f6a0", - "79e066dbd2e0248345b032648c9310e2c7778d23", "160c352d87c121ef1ea43e49831453b9e8d4d0f8", - "be65342f97e4e7234a94ff6dc2e7c25f21f8660d", "058f4abcc85a2fd62fd3e5ff5b3b673824aa6004", - "5fc2dce168e2f622c8695ac0365b7ecf1309eb15", "6cb3c4075881492fe7189c502659caf20ed37a89", - "9860ef0921e59b2bd11767b5382f3815fff1baa0", "e8b9b463f80953fe29eb73b91468d30f5ef62c99", - "87992ef1fac6c582a28f3327f5d7f4ffc553fa78", "eefed6797eeb529dd376ea970c9c79a6ea017f99", - "b37c32b7e9326f350d3287e5870dbded1989e7d0", "990f2380b5c095d71eba74c595bf0535b500cd9c", - "238ae256a3a1ab93e682d603c4b53652fa0059f1", "9ed13156c47c637c5abc48ee20e6c6182c50f778", - "0f80700a25acea6dad9f5b726f220ee8cc227d7e", "dc628580c9eb037386b4e295db74b7f3daa74302", - "d2f914b6abf45a9bffc2823d7ed53a88ba231907", "133d19e1e5c4b0b87017942d4ca37f731af5a91e", - "1cbc14e38442cfbae772c080de6e17b3df09868f", "3106d7492fd3faba686f789ac5b42f2770a446ab", - "d868af0a96ae2ac8c5488c011397af20146017c0", "7db2d14148d17ed3ad5bdeec728cfe863a20f25a", - "feb813ec958af1823c42f4f5502677e38be72d8d", "0b2ee7336487a12eeda4ba66d8f34c332db30b8e", - "54de3627b1038f15d905c05f4c46a1d781b6b44e", "168702d959029c760f29c2ac9dbfe5ae501d7e8d", - "bd99b577781a7ed50e9049a292ac48d2fe33b983", "fede6ecee14c3842ab748664206bd633ea51c524", - "a1d968a1ff87035e1b4bcd5c4db2dfe15474c298", "93683071196fae3e0f92f10bc4533575ec4d058d", - "afc1500cce291ecd2c1bb748d7b627d11b1f03d1", "7a123d33d1a90683ee3df04e5900277519259c75", - "49a541549f2bf86d9bc6037db5a61f5f708756b8", "4a75b61b5f0cf472c5fb17e2c6a271f9c5ba770a", - "27a10de6ca27ebba2d9c667408538da980a85d5e", "3b7c0a467d849acba884de1a8c9a9334e8b7f9af", - "17001bf4ac840128c88152d0b1e6fd62d6a69f2f", "f9c27614dfa3934bffb1f69cc9623e8dcac9d0ec", - "30c615dafa30ea4ecc030e9d03265908f38eb389", "c6134d552ab4bd41e92fd8e2f4a8faad0c15b296", - "ebcaabe082cbe7c9a546a6f156a2fb67c9b98097", "f2a681ba398572b3a88051c1eef80994ddff009e", - "1c9f4f163e65cb4f0f061307d8b3686a042cc9e4", "3db2fc16ad04fc0bb32a41a9ecd013f9f5fa5c36", - "6d2dc1e53a6d16b466ef449fd8e14ebd3fa20f00", "a4dfb710896797d1ec1cab191e39cc51eba18b4d", - "0f51f6ef36ba16737589cab11ea2dd1742671c41", "fa85adab7bc82c5d14250a988664e0f65d23643a", - "2d8afda70e0f82176d7ee80bcb653ed09d4ada76", "17b618dbe38d1374435496778d3cbd0f3d3720a9", - "6116c86a6188a345cb430e55b48e660009a85799", "479f00719a1c04acda05bc52e8198c76b17b767b", - "41b9555dd4375ea0df23a0a6a2333f7f4d9e626e", "c3a3634129a36fb09c4b79e737582e33bd2a058b", - "7b1f9abab1067273355a38909e102fd2d3a5323c", "2cbf3503536ba11f94a975fc0c547529315caa9d", - "4aa4133193a8e8c3fdc766208be7bffb4983bae5", "436fe5351a1bc91413e903a2d2cbf2a8559a3c5f", - "c033d7aed97d788aa88220df3c8cb72fbe1ab96f", "f11265286454e2059d0de2a82ee4356601552bd2", - "f8c91c4de5c8d19881c4f8b0461bc1f8bfd01d94", "25912cd765f1ca1e19486411fb3de9963fd9f925", - "1026cbd8af888621a402e114a1c58c14da41bb72", "1cf1bf68a47746b2d23e4211c03a4b81e9626d10", - "c5980aae60fc5c3577e241a70c0798d8397e6a07", "9e4f93daa40369d2cdb97bfb01ee8c93bf23ec80", - "2b61d410af69dcfe59d11337df54412a7ed495b7", "d9dc67568e7a7147ea23e42083d2cb8632bdbe6c", - "21bb8edd05cc9d1142fabd4aba808d6a8157f4df", "258e8ec05412a73bb0a9e916db941c7af1b3e959", - "98ca8e2ec4264fb7c6a3a733c455f8d0ea089b07", "d6cc3a68587ba633190b18c083b7d56747b7a19d", - "3525059c8b3d3fadcff6f592c0e2ded7fc06294b", "e01077c19252f97215f6ed141d485f877506282f", - "8a4eb9ac7b33af6ffe3e980c685c290a68c93ca1", "567acfb3e9e9fda2c4051c038c6621bdb47ec823", - "675e293cfa98252cef4d8b7980066b038a901d04", "11e271cd1a3df6c75449e0c51a21a6c3b3d3fe22", - "ce4101fb55325aca6989ccfaebfa9992421c9e2b", "8e0211657949932ce0ed8da68e72b5c5981fc8f5", - "fa016eff3df324a5ff9f3d43d324a01177ec8939", "6f4426eac2c30baf20e09b51c5369156eff7abc1", - "2040109acbd819ebfa776fc97631815b122aa7d4", "30a65a2a2ce03eec847aa822f722a0d2f0f993bd", - "2f320a37a7ef0d32ae4fceb09057b1491eb1fc32", "25e7a079b6717ffd08ffbda3254fddb072160d82", - "146489482d21d37e7297d3b085ba786409e328a3", "555e44e3d20abf44db5780cc7fc8c95ae5593239", - "26b2a34cca8cf71e092eb3e7b02e53b88e6c03a5", "d6278e852f56fdb00ee5b9d97226be1589853166", - "5c61d67a3f8068020979f09c9f7be11f56e95c2a", "e0647fd778205f62b1956e5320f682af61fbf5ca", - "5d55b31e47053325b4a345c445c62413aa69177c", "a71670f60bd64ceec2b68fc07608d4ef05277ad5", - "e6751654101127f666768dfecd42fe9c6e0b47e3", "a45fabb93b9405dd04d2d944fef78dc424361698", - "5f31e95c53879bdcb5bd47276a8aff25673655d8", "fe3f9a83f7db420747f402841d25dd73f8b36d30", - "70dec2f04b7567d45d5a85b77c959623eefcfad2", "042f91e4b2b8067e6b672816182ba9ae2465812a", - "6e7aef5b4b4c6cf84ce51a4d8b947eda306a26b5", "3f01a409a7ecc34e825e8532e56d04613397cd13", - "893a546da4fd221501d3c865c7bf1d16ce9d933e", "f5410073902240fb94b50c30506aa02dbf9a1517", - "722657b05ed625309450f4f33953d7a694a1a414", "691d303ce7356e544cbfae5ad8054454c0f69652", - "a6f5a8bb856a84214811cd2b259edf0a30c6144f", "aba9adfef223a27e9ebee5f1e5896763adc71641", - "500c2fddb600fcbe7a7d8a48d4e1fe7c3bdcfea7", "ce957df3478f5f95b668a0dfc87956da190d74a6", - "3548dc0a4e272b21330ceefe9c8c63517941c034", "b252d68c0dc7bc599474380a7a185b9c5a9a5fb6", - "c2bcdec50527d1153a73a5e191d7bb4ab1f4a5f3", "552e48c600134179ece0d1aabd13d17f124338be", - "1a18ac6ef2f20cb3434d1db59bf4ae4c3a1f715d", "ad99dac6002a2975e445e8dc90f5d93c53991fdb", - "04f8a3f464061a9dba2d1c00dd7940488720974a", "b8c2d1ebc7b75ea604e9490fd265a6f797add415", - "4bf10cf4435ff85c7c3e2f50e7790b2eaa8861a4", "66091f34bf277d5491477085551afc1a8a361a0f", - "f7e1f2ac9f1767984bd125184f8b87563f249bfd", "61a1c51b48f7b278c73c13efeba86aa2484a33b5", - "3f54176089005fb6dc4b252b4dce34370ea8bcc6", "ff6f45ce65c0b32578fb92f842f123581413dfe9", - "6163138faeabb67eb3ef1b97d6a4b08a5c45caa9", "64cf4c6299cadfe4e5a7987c8db3383a69a108b9", - "e98267285f704dd8232dcfffc09616ffeda896fd", "61d4167d00783621e8a830f267b799b8f22969b1", - "12551cea0f20963404d37821d889c7b397ce29ba", "9aa042227f5625364418d20187dc76508c5c32fb", - "8213aad94904430b8165119337da1243fa7a88ab", "e8c47b170edc02abda540037fb4752ef03a21849", - "59a6092a06c163dfb2fa1deea179cd84a5e91083", "db2b8564a0ed5193a70c607f23e575c8f023454a", - "12048f9a795a901cab215f869b185d6e46e2a1e9", "98cd9913a99020f97a98297a8f085881e8ff21b7", - "76c1d436b2fba46a7ac7b7d285ee4b5e3a6660fa", "cb1c08bc56644e993505a2ab863c18ebc8a35cd2", - "f532f53f82e2fbd789b654ddd6eebe181c12d5ab", "1aaa6ce090e25893b7b8b46cc99fe8344eec653d", - "83d4ec39274f91989811f845c6fe805544bfa0ab", "0152b43193700d54d9826709132ac2bcb9ce5975", - "57291a113482eb4277f43c414b09afcb1bf8f0b7", "3d5ec4de453ab8ea873a6c8c0d0ef0b2110bd386", - "4168c8645f251d9584b25c5a57ccb089178a98a1", "0dafcc9a1aba7282e98d653730b496d83ba13c16", - "e45a7da9aba5144429cb9019acf99dc668ddadd5", "0844207c03327225f9913cc4b1a8702330841a96", - "329121933af05b575eee9c77bf13b9a4d3443dde", "4793325d739b2d9d0deb39d1118e33d76202e7a3", - "517ce4da9248bbbf77c7c9f9226054bc5412176b", "b9ec5a7fe95a0c7e32d65901da5d33ab8c30c779", - "cae143cbf533885d8bf978f287e9383bea46c3e6", "e2df632753bc6545d94b6f4c76af47a81ea3542b", - "eb3dcb724dfd1cc85e30594a63839ebd46c8a5a8", "c459f75f02d0c3444baef25d6fd228ce2929f924", - "b98731f2971b9ac5d0acda62cfb2cc32c141dc37", "6b1c69123acb73fd0cc23393bb165e99bab2508c", - "50159c19f26b9c1433e50f388b3fa759c92c0ff0", "08715a5559a18ec189f91421618e534344f342a0", - "2d4792e23d4104e5a89c17bf2195c7a8aded89a2", "27eb88f965e9d3df3a1cf219db7883093f339676", - "ee2acbc913cb75dccb8d1bb124b074bacae27ee1", "d9a2df31b1ff1ea6796a25558771ed1a38e6d1f9", - "b0c3bc7c96cd65435e9ff6b88040799959041972", "c340893e4dfd3cbeb4566cec5e8cd9a24c9982d5", - "cd361d820e14ee59bd8daa6bbe3321cc7d4fa436", "89c6916d89c4fec3cbe1ee6c780358cf51ba87e2", - "262aed06bd219cbfbb4e91c0fbdfb606883f74cd", "e32b82fabd2f29cdc9ac9e8b33966b10f8a0ce18", - "1e3688e139a11ce21f3a9e5c74d176c1ace5cd38", "b460d264e4ecde414ddb70e918a1adb48ae610b7", - "41bee95c0185b6c2521073565e11ede0885a7e8a", "22bfb85e284a90cf37d23354f56786941de27a99", - "59c7f2256d0b342d1cc08eeb3f4dd9c7e61e90f7", "6f791793df1d1124936ad53e9948cd221a184aec", - "e5c3b79336ede6948f3302d60de0fb8a1b7a138c", "666d1b61ab34647db7ab8e617a9497b87166d7e8", - "4d8966bad69bca5970ce0ed64c343fac0e1cf698", "852bc11787bae1ac6f99622dffc2eea32ef121e8", - "2b3067a1dfe1648d1e9be9f54f8e3af5ee9cbc3b", "1a001a96c0fd88b7884b9049a6d47f6ec4d086b3", - "740106ef9e67ae17393d081580f5c1493db372a1", "05e0f5184a2a0c6a003dd1654bdb4d1da4b1a847", - "8eeb1017e6f043e43d6eaaa99d2aec62d2aa2776", "1e34543f322aa94c5f5e679cc8713120002bee0c", - "d253a3c83f3a062f0a18220bdec2188a2445f2ff", "2548241b69cdc856b24ed8fe930ee5a608348b8c", - "47c83b2f5b8cc63496aa507f03babde7e79c730c", "1169d83904da1f140c52a51748d1f9920cadc304", - "2551edd52b168e0691cbc4a16b6f9762c42a2ee8", "b07d82b7fe426edc3ea57eca2e54dd1a7865e61d", - "fe52db5b57808551b30af34184e5f11fb12a1a69", "2b29dbd15c15e138057630527d19a67d9ea9198a", - "5cbc7715b58ac8a9d141cf95813149a09d7f323c", "918ea978ecc68b7f3ed541b7ed1e073848bf06f3", - "af49d808446f40d37d64c66517a45cc19a78de32", "f2fb962dacc2a7f1b1a9a075611e300970463a1e", - "a0ac9637dbc9b7b4af6d37256011e8e777379cb6", "3fefc0572263475219c149f4c54fe1b88f23c7e7", - "f227977b57b78fecd2db13ff2b231d0c22a3b274", "7e4c8a38b0fd82cc80df79b1daec14c1cdb58be8", - "ad3269310aba337feac5712f9621a5b8ffdb29b8", "4ad90d121a48a0390744035a7bc068f885abcf89", - "134fe22aeae849409671acc32e13a17a69681569", "4e0adb75d47a88366da89405264d87d88cf358c1", - "f1252436b3427e8fe87ea9ac07829f977ea12752", "0679d7794f638bc86e47ecf8e49b70482281c20c", - "c06dbe314d1f44c63b8bfe6edadef6ebf5c5ff20", "ad6e8fa9bbbe6f40621a826662b858c96eff4057", - "9756e3372243fd818c895910aa53f4148798b7a8", "dbb3e71028ba0573b07f6a39bee4a4ff7f39c486", - "6aaf30534ead2af6285ed5f3ff12f3680f401066", "5f7f1c1613ed4d17875a6d845e8cffd3fc0b0059", - "7c1432135a24132618b786ace67238029bec8591", "76290595b414a9c7ec3bf3cf5fa6ad32920d32bd", - "97d4988c8ccfb194a7d01d2c427e6796ed36c5e1", "344fbf8c2cab7917197614e4e974bb5478e4a653", - "6a2becd209341a5dd760515889e5aa27a26e1213", "997e1ee3a567f849865457e22be43aad5b84fcad", - "b0a9c6b95b650b90e69e3ea25f3ac2f583a9c622", "c830370439922abc9cef0763e9cae3387e549c42", - "9bb1447ddf4fbcd71f68096307fb5e222d38202d", "b862af307888af607c82d4d2a3a53e12d6265720", - "585e55bba7d4833272526051a7e2a47416f8556c", "99ac5bdc45f0bec78af9807ebcd8fd118155df93", - "c7e14a6aa34a6256944ea4d9be85777a0017415e", "cc2dda3439152bcabbc625f21d9251afbf15a076", - "4e84b51660d909910c0ce4cb014a23e20748ed05", "f43e4d0aca4ed483f9b2568f35e70dfbdfbecd7c", - "10039ee5b86d6ab30389abfafc4158da5e051410", "a212609775beaa7909f92b708b8348b920c34bc3", - "26ef38e22f884aabecbcdc02640beb2e8ec55abb", "4689201232928ffd29fa14a2bac10fa44f45a81a", - "fb2c9cb75fdb96ad4016a076773038a6081a4792", "d80b52a085881ac67c9c8748473991852f8a1113", - "47e4afb01417c95ae136318ce8d066c77402f30c", "2a256e4dec0180e6e27cd8bda8b4ef1bc3b1bdd9", - "fd4b1442c33a018cbfe42a859cb4bbbdb61eb54f", "f36d187c3fec787dd3d4128001c545de5551bc08", - "ef30b00ca626b1bc763427aed853246c0ab72534", "75eed65362b1370b90c3a032dac2f366f1469f1f", - "d0149fcec2d2e19ee8851b4ea2e328b2ee689184", "9e8eca00b251efc8bea606b3571208966fb2a2d7", - "28e3df3754c86e9809909aac9fe02515e231d60f", "5d4af1c155c639c81448f1d51db6cd33431f7fae", - "7e6a0c4ba45a0e692bbcf9456460aa56a974ed01", "63b04d5a98be1d3a23003f6518c4c8ee3b065ce6", - "31991c235b014fcf4fc9a99a7fa4824c705af5cd", "79231d6d3fb4196a482cf902439ff727eecb92ed", - "a8c246b8bf081182b08ad2a4ea478b7ba860d006", "33750764f3c324181451b38a1dc5219ab04a448e", - "370e22839b26494ce0ad1a88286f427434f3dcc5", "200b037c3083bd2e28e4e31f015bc87f9ab7196c", - "6a7573a61b2e15fd261863178f1f54d96ebdf408", "adfe5473bf50ce4f88c88826d4055b144ef42bb0", - "9d66b222b35f994a0d3ab6bbfb1c142d9f226d56", "ec03206161f942a59ea5bc91c08086a9b1fd2ae7", - "ca5bc0d3d6326e4df076624d826be350a89ed54a", "b8b6473dd4a5f93cd6eb1c0e41d659cb7bad0286", - "20162a0585c37d0c14b818eda6f695c40678bf65", "369ce701b448551b3b5b7156667687c68f7a4259", - "587b5c41554e3aed002f92535ef2179231f87e6d", "3b81c061b9efb1074e0dd9cbb5f11f71420e0832", - "6007cac67baac66d72a57c024260e9bda13c456d", "b1678a8e2c14c96405dc17557ca68d059ff68b8a", - "d5879f68ec23e30ca8882d93410073a0cd5db92d", "90a76730c4ccc74d3cce95abfff445d70bb98499", - "bce86716fa530eedc657bfd7cf18f045116a967d", "fc46a08726a7821ebccbd4d1492ee05c6bae89f7", - "d056f38506127e986b226fb5ff5683b6deeefe37", "1119b6ba9baba7c6511bd57f21eb642085932790", - "2d317fabf4f5e8d7a858a3d1dc79b88a2640b241", "498c2b6b4c0964e25a76cd8ef9e1e25dee1cda7d", - "803f7b6304b6fdc60bf08212fa280e31365d16a9", "5532c2bb541a785fd145aeaf624491e201ed7759", - "243023d8a29dffb528b567f37b5ef1d2d78f3fc7", "c0312dad18501b449812f9c9aca3c39fc1647432", - "9aa5151cb1622686f76e3e956dc9a6e48f43d3ef", "c9ac4a1dffd0a1fe7a0a339b156259884c54057c", - "cb53da91b05ac93ef8bb2dffb4f0ce8ddd06255e", "d25e73f15b3a94570b0a85e39df20d4f9d6a3ded", - "d0af00f950ccb83770035cd0db90fd8ebbe00d10", "ae260ec3ddf6bd62cb66ccb1c9ba3a6ca9d19ab8", - "846116d64285c2125f01ac2e06060b84ff9604a1", "2261c2c6e3edb6c2327046fa2d5b69d9a39ec10b", - "0c938db82253db2c09d40079dd15f0a1ad43345d", "4e5825c76b332b11e0e3af2ef74d9b98e3784809", - "83b5cadf47b3eaa15841e3815099ba5338a5f683", "2f11fc2b39f6889ae6720c0592344995b5942c37", - "3e43da7045388e7259414209b3baea7ee339bb9d", "4b71f161759ed105daaf49ad74f3306ef1710855", - "ae7070f6b723cb4c5055252017e5ce712ddbb649", "23cff857c47ae04884a1e522af2d5a836ea30f2d", - "424a8b8cd8ccd2ddbdf3c2d10ced6767b53a4ef2", "6391feb5cffcecf562f79be5c7b5c620cc1ff24d", - "9f1df5788377be4be03c705b21ffe72e3fca68b0", "607db9575d0fdcc02810ceab97c9b3faf9dcb601", - "ee0202713209fc3df5cc7c1c75812c325c94e280", "47905a7a246fc0ab81d6620820a96a283c6fe8d9", - "21ff79105eba8e77a638b42b2e18589a59033609", "28ba2f0f2967b8292a7071c3d99c9438b1db7963", - "e1fcdbf48c205c3a724151cf5008809615687dcb", "fe9755c8149d239696e010a0e92e2fab24da5aa5", - "e6b72cfddcaa930408e0d20800add718d44f30cc", "f341256a2cf06c968460034faa6d581f17af65a6", - "23791cd278e193ccedeb2ba80666c96e9152ae62", "f402a8f708787e8e97a9e096dbb47ccda9009c78", - "8dcac59f949b44e36ace133352ff4dad069e17e8", "f36f4c364f6f702f64cae7210f0d32a535e93bc2", - "8e110a0b274f6a11fc3773a1bd0933dca5cc962f", "745a2fe44d82669a5070791037da95a0d499ee3c", - "d1bda5b3a4ba7b9d7490d8511cce4a11bf76a8d9", "c2fb15525ed50bb529279aef0da1ad889a209760", - "ac5d73eea0dbddd6591c6254078018b894c74d9a", "150d6faa9cbb1ab06fda1d19606adc701633f24b", - "98f046a4f73ab3edd7f33d87279dc17c6009c844", "c0afac03a62235c223ef23a29e6f0f868aa89f4a", - "c19ecf91221af8e0d29e9d6693d8922989c8364d", "6cc04cca454e9610729586ce72ad276e8a8be962", - "5be4d55be3d8a516f8b9bfd8fa4b4b6fa072b3fb", "68e5dc0768d1143138b22a4dec7c0796211c515d", - "40b502f762b12d9008d67359a69427246dbf4590", "c7a0c0a1d86245d58f93578f5e71861850b20327", - "45e88dec3420a3081ed070a89974fade34a8cdd8", "a2cca480abdfd271d83ec53f32b9ca7c0534b1ea", - "eb5b56e00f7e3a3a93a151b04de322a54b478a1d", "ee726a3bd27fcd17373550a73f1265123f038e9b", - "ecbef3833e45ff4b51fcbd07be7ae083d0261106", "6ff3d878e2b0739195fef120f3e8920aae5b6c14", - "c8a254b1ae30d6d0372b9421cf164a2f92770bb3", "b6fe64434d331f92023b8ac4a0ae29a436ece676", - "6408dad003df5f902970c9a9b281bbdcab70513b", "b000f8b57d68abac68a8ba92d2e8af1f4cf04e3a", - "d70f6b719ab62e4d30947d46b48c4f86431e27f4", "d8b1b3fd5b14a37edfca20bafb53bb19b68034b5", - "54e2802c7dda0dc48297627148cb8080900b026c", "2a88231e4c45be17c7b59df395c88ad1de1f55fd", - "bd9541f3b7d18ba20fefb5725bd21f29c01a2fdf", "fb211cb3f8ec40bc8d34ef5da91173b85368ddb8", - "302c5986252fee81e024e43b3950ce0c03c1b19d", "c688626a38c6777646e4c5343903c5d3c39451d0", - "97e8d745c998aa9ca3c0402852cfbdebf38afeff", "512ca7ae1cc0043eee4b9fb24bc680e5e439a22c", - "8a1b18f3f1a52393779d7872132a261596718531", "f1f688ce752c4783753ded0c034de72056e5bf0a", - "cf404c790f1926de4fa92a90bc25bd3b89441ee9", "6f67fb37b601d81e607b4784b59a60f5da04ddc9", - "0358ae29870a0c0555826236454eee2a35460bb2", "267d40944d68c9fe031797824c83b7628ac21054", - "28999639cccbd7471536049556b7bb0445df968c", "96c339642cf640e219e83499b89b3f14c40c1a46", - "22ab4abcaeaab3dffd0a0eef49631c41feb35f01", "f3281e89aa93a9ff4b045c561960128ff02bd67f", - "ba7c3d3d19387b725dd93777e264c2d243c56985", "c06958105add69f9c1215959af1592100820f897", - "0246ace3db73d80516951169f697ab82de31935e", "3ed4aa3045ac0679828da5a36e6a159a76397b85", - "a9b3d7258a65a4ffc0188430f23a2b348bf3f71f", "3f80e737293fc727a2a5f5931afef5da8a108889", - "f5c4af7e6ca21899d603dc1c5d6dec724180a617", "83223c9cdcb837c03a1ee706a68c201c6f46aae1", - "7ebd59911482548ff28bc5257f092339747a9847", "a29e7d193abe5f905841b7dea04968b1c973775e", - "4df92c585a35462fd174a94fa6cc34cb104a3338", "480f1b18698079c345470f6eddf82dfe04f372bf", - "e93635e6ad4990b2037c1c42d96e5f4f5c382211", "f27588ba28c79a1abd36e9ab225006ef711bc2dc", - "0780639bded276d6de3f29a949974f9aad888f1e", "7649e12dadd9626c6aa55ce09bc5a77abbc1866c", - "10684acced018de4c9d795b4e3d17f85b831ed05", "1fd08bb5d65fb7deba4ce611c4e4ae61526f70f5", - "4ad405913be05105cfd8169727862962f73ba90c", "e622f46b8ab1a027717765dd7d392879941691c8", - "e53bc56ec46866426314e2214f39986f794f7ec7", "1ee4211e5bc419b24309bccc29d84c71d8153e33", - "13bf7fbafaffb9eb5305cc786ea5327b1bea8c84", "1b17359571b9a657d8c1c259f392bdca507f8048", - "f14bcf0c9d9d4441837089d9406a275ec7bae489", "650d0d424276a764869dfa6d5769e0d33dee29ab", - "9a51d909f6e0ea003b7bc31368889b34cbaf99db", "d25b13c8e67b29bedd33634693fd47107d79c386", - "d4791ab3fc5623770bd37a62f5847a3469ae62b5", "63cf95a96c6f9550a526c3f7c973b3bf77da1d99", - "0880631d8a31a2d656c214fd5326e86d72d99735", "c028799f0dc5cdd928ba41ed57758827d4c33960", - "09285b7758bced6de4de28adb839ce3707bc0801", "ff3ef6de1556d6a817b228634d9bd36c03f91b4c", - "7599af4e7f3c5038845232dc1c3460e757d29e76", "945656d9dd3e48ded82ae075761849b0b6de7d99", - "14d2b00bcdde27acd1e67707fdec920aaff41440", "bead8489f2f77870afbd190228724d8ba9525e77", - "ef888c5167e12709b33fcb9373476ce222d3a777", "11185717aa656979199228d4f134506f306ebe11", - "763619ad1c6fe756de2d6ea598f4a35b6b5d07f5", "de64195cf8f8e0a8a209993c12c37e6a0e9717fb", - "6fcd348a0817c5ba9f692e9f43b157ba53f61736", "184223aaddee8a795fb21a0298bca7cf9f24b86a", - "025924b72b369155a7dc79296b0fa1542b6cf66e", "00b6d09efea3b56ed30d3f626837c105415a2b9c", - "7fc27ae1ff5720a8632dc7180a62f93f0b240971", "68a1871cc2f4239c1e4c717d6cf5d50121aa24f7", - "d86a119c71e8f3db87ef84a3f2eaee3784e514eb", "bf6c04384c5ebbcbb7a2635e885ad48223000515", - "25df57cb358e1c55102d3eb05c633bbbc8d18ad7", "c2ed09db58daafd8711f0729136bcb4bdab4ee39", - "db9ff970f2394e5ddb70b05835e5cd2ceff1758f", "b5b0cdc6e2d0971f11ffb7b83eae62bd2f2e2a63", - "568a605393fdf0261752b980340b56a695993ca9", "53a7d40199c4cd3e0b61387708a5c4b2daaa6a04", - "d764e0dd4cc13227c90ea0dbdb7a17148a37362c", "2b0970782ff6fbc9b574d9af09c7f4387da71167", - "1a2f72aec014fc3b1c7a58660c15cdf8eb78c30a", "ea70291c158d9ac2e034f91837f3aebb9315e74f", - "ddeee68ef8756513d3c91e77705759282dc88f36", "c4c43e1c71a7693a257680b25c4cce05fa68139a", - "cb91e9590a1524dced13be78e13abde059a5358f", "8df5d8b31502fd506a59b0d15f61631dc5dc0d11", - "ef60833d075ac1aca48423ec296b18756a0907d6", "4bd51174d78af4c6afff4a3580c4380eaf53db03", - "f89f34968e6fb5c4400d4133e5b83eaad9ce1d81", "4926ebd2150fca495a5ebccb69d73a843c2a5c76", - "b7d7768027c43c4bb9178b59096058c827249ebe", "b18e01b7ab7b8fdd5e9093a4d10446ccb4c8b461", - "7c0cb0bf58b260d848be8b2fffc6ea81d45bd9ab", "65560b3113f1d79c241d64615c70a95a27a1295c", - "ef7de7cca843f688185aa44caaa11b8d9c5ba419", "577959df764fbe2295c7355420fb88e7259318f4", - "fb4e5fa6f2ea75bd25bf313675ace5ecfb09ce4b", "58c3bb9c95b2b18b54923c1c66a271c5103b5016", - "d15a9ce8720d18dfb1886de4ce23504c690f9849", "09b1961ea1fb0304ed7ad7c2c404af3113af532c", - "689943c3a6fe2d15706f588d5d192de09025f87e", "76c955116afc032044fa820077f0aa0077a9b221", - "e4e28d5880eb5a19eac4f2dafc94b87121315736", "f66dc5b1d3a36e518a2d7581534cf1eac1c0bb86", - "437d9bab241951c67ba4344ba60e7f8c8fe091fe", "d48f36d517120dec77f9f1383c6ff175e490957d", - "3595ca188c62c02f3a21616a40fce4063e5639e2", "9335fe0ddc8db4b8825b6a8e96f2ae314c3daea5", - "93b3baceba14eb826f0691ec927139eddd131418", "b081a6d644c99936ce2b53227aa949e61c1fc1a2", - "7c301a66f04090a5dfa9b97790c2398bebe8c658", "70e640c8b512f69cbf2d3815ade5e08acfdd6ea6", - "a5ff6189fcfa209df6073595ce8d048bb434142b", "865f86d6f58109166006154d4cb1f18d780afc7b", - "0b32bd194264f3d34f207e36da01747250f370b2", "160db72460b1d2cb57b71c5f5005c43b39344a08", - "ca17e8fc42c63b71a64943b2edc546cb483d4987", "62709ee11b06371980bbc365eade2cc09fb201e1", - "d42b892d83a19496adb8a51865d7786bf11cb51f", "151eda2239a8926cdfe11bddd08d4a68dfc06fce", - "48289268a75e7c551d8407da65a6a8d5e96bfeac", "76475e31fb20faa61548ca6c110bfaf0a8509333", - "ff45b9e590737c453377adfef746c419fd024214", "791336c9f92b920c36d87abfcd23717effeb2979", - "7cbdb028c46f69f69ad5b3870fb9976a339a88ea", "6dce9b85f8a4d116d780895772890e62ec554050", - "609a9ddb002e9e03ec1e01fc0d3273defd125f6a", "eb5cd823d83464a85d52abf6fb618ab6b0ceaf14", - "0b33f97dbe25690d5b395aec431714f326835761", "b3c0967b6cc938da94bbc24bbb4960c499eab996", - "55cc0375389bdbe9081930f6aed59e2d1b996d68", "3ab0dd9b211aa79f607aa18900021d331ffec108", - "8b8fc9dc6eaeab845218b9b42c9f1eadb85d9a76", "d95873f271a98500509514a3bd503e111b2eeff6", - "60c22d4758b2ab938d925ebca4195d388976ef0b", "4a71cb75be4c145468bfa41edeaec4cad48b35bb", - "674df8ed0814f769a01ea52a86b37a37db300fdc", "52cd156a808d638be19a621e77ce9d0b705ff959", - "893fae64443d115a0071088287f1047c9c85bd0c", "fe745f1136b3c2b4d5cc703cee8933de6357c502", - "7a9ed9c04bef62538916e432a74f44c034068c16", "c60540472bbd9473a78ffac3a071904552cfdd6e", - "dce6b37c643555216d24705885d35be6f1658323", "d25cd6e77dd4f8683333b68cd17e4ef161a10f82", - "ef59cd7b3e448c27b726dda2624e3a66bcb7c915", "caeb866326a82dacaf9b9ce21de180c99462b0ab", - "300bbd6765f353ca1f7a42c8db1edbe0fca9146f", "d476be09c2c9a67b065eb972d473c862d05520d7", - "f2692ec53c9eaeb976a81908a1ad9a8a6065eb56", "80a904cfc2637be47cf6db433896285c96642f28", - "b4e7c96d36534976b532f6a73d687ecebd20d3ce", "f442e491213973df215b4e5a13ac42dbf26a418d", - "4a990060a137b7405e90d674667b774c2ab3d9df", "ea028084a5ba60179ffcc5c2e7745a5137810674", - "946cd7b549d16cec7f31b99e31a5cd1f97ecb0a7", "f4d1570ca148a075ffea03034aa359a795a7a95d", - "b24a0df950d615d89a5c490856d9efe0c67e6807", "4a3a4973113c414789c798e3b279d04e68f18193", - "853861b52dff3d4e69cea17db319b578dfe36b57", "75cdf79a50fa9f54ee0abe8a7352983e4e15dc8f", - "d2172012e40b489a1b696aee59ee01beb94d2044", "c463cba55508e3410e6c938ca7f07cc49c69685f", - "298753c52149d58e36b63ae01437d7e9b1626550", "edf83ddead1b5bf94530280409c8f8d7a3566036", - "6ad9ebb63aaa22d5cac2c6ab68a8d044575531b8", "4c4e417f31a770c165848c34e9a1c03a88345923", - "01ac78c98a9e83a657895f330ac60b23df81aa19", "077b29278d6047812f8b65e158402f13dff2e638", - "6a3280cb4ecb45a4a949416106e707b4999e2491", "3de477994ebd5b7edf0a48ba6c5e799fe02a53f7", - "2ebbd703eb8308492ff7d0e3604b786931ad8617", "5fc0b82cdf849a6c424721cc5118a196c07caf43", - "851ed5018abedd4f527d5fc1f184016c2b9dcb20", "8271e8c30ed07e236d230df37635819f45b3adf5", - "794d1fbeb2f5f6e2ad81450602d53d232a2fcd66", "765e4955986ec0b20075669f5a7e2dca79a98ae9", - "f94426a7f4b9bd63aed0e75894ea80278dab4320", "c0006f951059f5aa58b4b898967d1dab70377178", - "414f4c053c7c9d294903806e748a132d54325f73", "a3dc4e32a5bb67c422822731ffbad447f2f89dd0", - "9dab95f8797ac80a22cd854761e2dd141be8f436", "c187e0b59cc8710d812cf24e9ad7191c5d0c6206", - "55cc88749fcd34f08c5d0fee8bee92dcaccfb010", "2c3d218a5428646b970895dd88e2f61739ba0732", - "4ad60738ad972e0cbca3e763b556937501c0973c", "543f72fea7ef066ea3111bdac8f0ac61134e0c24", - "a2bf3ec52c5d004e7e5329efdf6b5cd735618b87", "f483494815f89e80dc399163080052fff49031bb", - "3326ec457cfa6d30663eb0ce49a838d7bbb86415", "f6d5647f6b6923b5052619814a84b2e1bf8d0b85", - "f2dcd0fc70ca95f475b68f7335b2d0855534e5f1", "a50cd55ec2258557a20839a0d6219960c9b1a2b0", - "a34ae4d4326a0913d9af50546c558811565ec66a", "842e922b6252301d8df608a1a1a4a732686e2ff9", - "2b6cb59f7846a482432b4ac57fd960f73d2441ba", "e559e01ccf3cc35aee9732e3db97c23165f8a6d9", - "543085108d5513b9fe63eb96fb386ccc84a811d8", "c7474d0e9cfe5c1d8e56f3978eec6871706a38a8", - "fce05c355558c606a7ca815613c6ad3d8f8a1503", "30a17532024869bc353e28aa4c3da17dbbcab80f", - "13d54732573224d7879166a11857046c50e13626", "42868488cc892e63b13e7afbe157006ddc215258", - "94785fac47a5d2ce41d64269203f14de07995186", "82d752a38f9d5598685d58e5ce6080409b980442", - "96f99cdd47de4d5e4180c99bb7015fa77d329687", "e89a84828a38b552efd3095472eb39dd18be141c", - "5a37e8b4031b627270f06125f5c204eb28437c85", "30da9a8dfb0f65559be3f17a3d2f3be0cb297ba7", - "abba9bb98e64624543ac376fdce700ee5e33b392", "c19f87bb786c68bab429f594374c24d09dc98cd0", - "73754ef7ae4615cdfe881adea981bcc93b65e887", "44c25f0a9f3151efbb98056e1c2bae59f4aca0b3", - "51f465b5aa2a63568d0bd82232898b39fa429a14", "1ece6bad7a8d2492da84f5db5a94a9c81a94a3df", - "603617cb2ad5009c06dfc61432287ea41d4dd70a", "ec346b3231969799e3852cd7f4e951a25f3fbc0f", - "46af277dcaf4eed7cc96e021c96b266c24c1fcd3", "0965cb17b3b353174be301989ee8f5b77ab925da", - "b45319782274fd4841da3c70ad3b4754bf2b1b08", "2a2bcc98ea5b188049bd46b4e315ae55b359b7f2", - "cd09081ec384b747181bc2309a9485ee0888516c", "f636e931892c445a7ffb1aa0eae7499caa19932f", - "34ceb6f49765ac0d173d4a0cecc089f34dce2695", "9b18988eed2891623baa37468ef83dc6a9a93e14", - "087397f895ac78aa63b5b7413dd4c948cae4dc50", "98e1abd91d5502799931c25c1c19fa6605ff6dd1", - "279448c0f978c369797336bd660e457e2abccb3b", "20d76b4b81484d694731d6a2046661a025928bdd", - "7a69b783e3e747a0f7a5eff5cc23b9a00d53aa01", "f645296a6d289f80b9960679b8edfb6b0a4d96c7", - "9352d33e1d396110bedaf1906567a6d8139c98ad", "3a4cb9ed1c4e291a738f6a97ae82b7db616ed4f6", - "e97932a4ff925df81b844058a18f2da4f362edad", "2e9b3d733cb1d6a6fda98cfccfd179c35559671c", - "00e2b96be50f143abbaeaef1b42f502eb1c5eb38", "a3b8a036064eade54ac1a7e49a48b5228863f225", - "b050b6089b63a630ca1e102f27f1e33310bdc0f8", "91200850dde71fd5061890bae22cf6264f3a0ce9", - "c4c90fa787e28f241a6149c5706f67cb8c897c3b", "52cda4d77c07f76113b392291e947e02010a8ef8", - "949b21730e48bc645dca6c6a9dedf758035d0eed", "3e0509507736054281c0feb777b5beb62af98ed5", - "994993e838dda5b000ee4e75786a5a826f368f9f", "24e2e8a67ed9977de3c1373968d76736da3c800e", - "9c8374cdb61697a37bdc89b57ac5574af910138c", "7facfd4ee6d102ce1c2103b2bc0861865fffc07b", - "82f7d052e4d562b268730e8d66d4ac694d963f8d", "a5f79e4ae09eafe2892bff810ed21b1a7cbeff6a", - "7a66189f5b487392ddf3bde3b6b2f837711767c2", "756f813ee996e91c50dee3929035b81d5c2f5b7c", - "c0c98d3382858b9de30907003cb1b3f47bcb7e4c", "7a1f959994f3e8665589050ca2e07c5ed5579ff6", - "06944876fd90b41f439d337cfdbef2582caa4b56", "73e779de8b03c705726abbd686ab6f905fb2fe27", - "dd14f8315d4345a1482b6b5f581fefae03154e6f", "b4f629bddb661422c15c4b0459104b6a6387f3a1", - "a65dec2720ca334bb503079db5a5db4649c27c0a", "23d9c64b7d95c1d1c08ac83058dba6204537709c", - "0070ff46a8b72b79d011f59a770cdd2e3a7e52db", "39538c29808bc3b1c85b2f9555eb56296778e5b5", - "05235f2fda6b96b82d3b798f5c06d1c26fbf5556", "da9ac947e5272631161f7415583487cd5b81bd92", - "0afdc9abb0a921b0eb87256c34c2440d7bcdf748", "708eb61ae54de0fcccffafc686218a959fa0e12e", - "921d2ecf681cb2fa40d8cc9390591bdaeba5bddc", "d54e009ec45cfd47d90fa87926ff55f5668cd745", - "b66c3a482974a6950eb27fa2c83df33c0ddaee0f", "d11ee1996ea846c781624a6be16e2cf05c90a3ad", - "d1fafe49cdba1c135a157ab725caf6a73c44d413", "37add1833a4462b08f3d63ac3cfe2b29e8c19daa", - "54b9e091f1f4a2aecc9c3abef4785cd4116e59da", "2e7c5f1ca4868b1bf1681e852460d1a64f6730f4", - "fee6c7a1a74439ade1a4ba1102431cb16ffa40b4", "0b663b2c2e9813fd968ea4d53c27117a37af990a", - "2bcec290f45a8f707462a56e8cc468f5934fe57e", "2e77e56acb8a073a7164052b3015752f55748f13", - "56cc03e04970154b1ae9a3cb49eeb3d131118feb", "17819764b0cc55daa6f9a70e1b7cfbb082504a26", - "b9992bfe65ca57863517d1a44a5de4abff0d891a", "7cfd6ae2ae46bf951a84ab288fbf6381377e4fb5", - "44f321da361e4de492292e465ac2576625c2f04d", "14d021d38ede8d4fe6c55266ea1bc18471146ca2", - "dd5f008277ecf79acb0c32c88f459a46f556d235", "e712c5cfb5144ba8122f13b400324a3db3eb1131", - "2e3b8bdf70024acbd57dbd574b42d8081b22238f", "a27f805365b6074f96d0d72bd877158a6a2683fc", - "1777f7ceba2141c7725cae03325aad9015f5e0ba", "3ed72d7bfdaea45c7741c4adba22824729fccf93", - "1efd9d0cf3d575dceae0143ad80cdb36ae929f19", "ed1e3113a91cba66cb2bdd2fc62d221f0fe98720", - "56830484e8e3a9bb9c3c0e28d2e06c59c2f85814", "612f82971d281213f121bf3940fb3a22ef339b1a", - "9204cfa997dfafbe1d923cae857fd8772140d2b8", "bd7772cc8ad355a2edb8ca92d712bc6522f679e4", - "50013bba2f0c0daa2ba0601ad9d538b8945f49b3", "903166d464af4cbe28c3dcfe87e3b03d2d4361d4", - "498a0b6129cf4bbdfcd1fbe56f41a09711c81515", "4d82da411ae6922528a7e31ba0d9b7781ca7b140", - "d1a59d5be71487c46f1f13cca1329b890864e3a5", "0130298b9910153b918c24cd0305bf004c77f139", - "b4704585677546e3719b0167a48f7352c3135018", "bd2af11cf4b22ffaec8f0f81e41c7a200707984e", - "90bbdf000b6566e32e973a9ed13673babd3d5971", "53b76d4726ba14be0ff600d76f6e94af63bc76ac", - "98b92425f234019ae1a7d7fa763ee86d24a9d4b3", "402419c820cba29219805adb1b50909143962ab4", - "2507dd9d1d952d45d8e29e3da7d9b67261ddc8d6", "0eef7ee0455462714b4398429bc4e0b1e68aa807", - "c15af97c03e51bb5c7c23118564b21d37e41dc38", "5ff6527e38d98cdf140318d98828d7de099d1552", - "7d8d05ecfc3d87c0a798fbb28a7bd63d79317590", "d728b77adbe3f536b9211d9b26b0668cd796a549", - "ff936585cb1595e9b56e14b77c2a8605a312fc2f", "cee364e17aaa6f0d77dbcfe496b188de38123833", - "28f1af82eea595d5db3da22f4433c144fad620ef", "d5bc60e7980decfb5d5cd10ef9ea1bd0a3ce5fae", - "392ce37ce6411c30d436940506dc2cc8278f66e6", "38d291489369e7f222a2711e5afd7d6ac6afb574", - "479506b2cf7c7392c0a96d6e5d550556dfd20ba0", "c71e5676016de6a9b7dc27a123f403283fadec2b", - "5d03ade937932174a2f2b376efe6f761636a270f", "04302da411d5d79477463fa37de2f639afd5127f", - "d4e6cd7852b5b88d88afb1db0cc9d29d8484f143", "1dbdc1d3d9dba7ce5cac3bf7d2268ab237a4c5cb", - "3f263b23507300ad4dd7903e45876c2877e59ffb", "127d0081100e98843f16d26cbea527856d9a9ddb", - "dd5e22108dcceb35e1944813e2524ebfd0a53df9", "5d52758299b341021d135b5166614a46f3ecf2e3", - "a1b3da2881596c60f669fd80479e45a097b38707", "21a63be654b8e5df434d01d420ea2206c8d9a92b", - "36ea46c3da7dbc2bf4d304d81f86224dfe54444c", "29fcf933c2e58f6eb8fab04bf8c511f56896fe15", - "64737770ddca8995c64e1106bfb08ff0ff1fb144", "d8c191fa2b58539d83c7efc1c3346079ecdc566a", - "77f0910c39aa6108e0c2fdb32fe1832126c0489c", "af64db9a99bfd8ca4affe94dcd5cfea05e94e03c", - "71dd27e77432a2d5b446958707286d08097da244", "5ddedb0a995f06b295696a2a7b4551e404d0dd16", - "01f87385a24ece34ed8ddca801fd84f9c86e74e8", "09249256a87d4a90588b026d789fd3cb1aec856b", - "9240b4a3a946be297b435486d1f2a6d941422b93", "399ca25f86719994d4612fdb618983079d6a59ee", - "4db57eaeeec89f4a96d0f2727c15ff083482fbf2", "4a31d4c94a4c6ae379abe24c46817a1157eab07c", - "182f2002e4307f83c62e06dfa4164543fa7e814e", "97a0a7220c2b8e458641c3e6e56889254d2da049", - "3440a5e4b4e31f45c6adbae99b6214b8fbeebb2e", "6f94a7a5fe870501cdcea762e4a7a20631d48d62", - "9da3107576333b6c7f3e878e508e94a4c764e45e", "20cb94f57147f8372022885ac2356e464fdaf7e3", - "68803fd3ffbf592c0432eadf45fffa22e5afa8dc", "c538f4c3d9ed532f02458a7c863ddd549960902d", - "cd14b737781fb608698437bd2e6d20d691093874", "2db66f7bda4464a6f5342f5e021c29a38d42068d", - "37b12212ecc3a32ede8aa04eb0065fa80e3e821d", "887306035bf8e3f0963a254a6e46b52b55a04fcf", - "8747b40002f4a24a2330ee27f36ecc0880083827", "ee262c59ff4c66f77562ef879569193543838393", - "8282282c974675b044c071faf25996f4b6e4ebc3", "f9ca90f109c32ff5889c0c9d84ff11f9fb5b5924", - "e530847cf2aaa328e800919e6eed9739521a9b50", "ad726687605b280a0c190153654f4751ebba4c7c", - "93f6ba66b73bf972a3df6ba722a1d56782c59d47", "b40be55c3b541c1c3a6b46de02f45e3ab9dfad47", - "95ee9b8acb715971bd1abc137a9d54bc88139b8a", "61dc80eef767360c6d48572ca1bda65c693d5362", - "ba44c4692965b0d694c8fd015f1ec3fa4dfcc696", "418a1501e2a14efb4ab940cad4c898f09f92ee83", - "026029e19d4c6f0bcf239abe607026a5a27f5b86", "8cbd5f3c989185d9474f7b5767d7e6adabb2015c", - "55163a23b71b9a3d63f6e4695b07ebd07064c61f", "d9bde5278517a57ff7714edf98ab2361d1663219", - "9ad5f0871e1df9582ea14bf7ba22350086fcd055", "c57f5ae0aaa74eea99032b45f0dc5c927813d8b5", - "3e3f6f7661780b696501a397d8e95ec446fd1fc3", "03d94679ae1908d9a6f6a38c00ce7988c5afbcb1", - "4c8f526d899bf04b4ce3e088302680da64499e5d", "271ddfcd505226549f7674b7e539efc96c8be5b8", - "25708b2d11167437e6de01fa0406dfd3c26bd8d4", "dcf94a3cc15a85bc1dc2fc7e1751e6a343609049", - "f65dd5dea2e8bf5c90b8b093b4ae2db11fce3b5c", "b3722ffbf1e3287cee8109c82b7ab13d187a3d7b", - "ec3af0efeea2836f6a2fc5a2390232ff10e17cf0", "c7176c1b7df0676b474b4786a7e6ba25650df8aa", - "ad97c1b6ab4dcd3d4917cb59427490508523daf4", "7a8e2f675709ba76674a2903653b07d348de32d6", - "bdd754c4219ceadebaebab82c1dacb0a6d819e24", "31df56efa866faac4fced90b742b1800261ef46b", - "1e77fd0a0bd78293212c518291333d3554136b41", "99f906bf47a41245895867f76ad38fc9ca88921f", - "49dd5ec3406bda057407abe5c57e6a027b8c502d", "f36f65ae5480acecfb85d9b8d7a79603853f2115", - "5a29a9db5779e61efafc338b00be9d22efe2a181", "6b28f73e9097b7a7966aa9add138e3dc14c52e75", - "92571e06644eee1606759deeccb9875fdb454b81", "b291a60f954d1aaf1bf4d1a845f9838cde8a504e", - "47c1cfe13397789ea9681d8f464399e35b1f233f", "dfd9f01fed969c7b2baaa206a0a6435c5f41ca5c", - "de78a285a707e2026d3cfa36a0dc7d18d0c9a15e", "bce1807765d8a350ed04e8b525e83cab25db5879", - "b65a28145ce9d5d79d2b25ffabc905b854eddef6", "31e8adc8ca44176b5d5b91ba4892612f71ffc2bb", - "5a75300c606561e9039ceae4a707793f4317dbbb", "7ae8180913c01a668a0b0ba707f8550223d1721a", - "c7f9391c16e45ef0497f2b35af00180c72a7d91a", "9b14724732e6369051e8ee69db4f2ff4ab791869", - "f20a749be5b9be59f9228aefc4fc649492a272ba", "fb08711894409b26f7b8827fa0af15b96b6ca1f6", - "b8e4379b643d250498d9d7e83b461c8e1601e7db", "6f9895696ca5c5d76c1852dc169e38da22b2be3a", - "0b95e27f015c056bac9f3391b4ee0acde58aaecb", "9dbe2e2ed1b88739722da7e6ed5deed3a95195bf", - "eee23f5c052d9587fb7613de3f01901f14d6a450", "494d77b5348dd14272ae79d16aa456f4d14ca8c2", - "2e8d5bfc7b90389722952a2b67ffaf15f98068fc", "15e79975f6e8d07b3792dd9045688ebbcd903880", - "3d5646ba7b187dcda1e85727462e0f664b9b3f09", "24aa1622f6ce7c03fb4012ba7a36bb3bcdabb334", - "1369f20407850aeb075906f622357694dccc4c6f", "0871d5b44508d4a35b827a8ff55c88e828570b73", - "e9344cff34bbf55f0fb3eec57ea0e10d018f7152", "ba521a46f16e478b263d5384868422707f12dbbb", - "d9f8a5524a6e1a88e95b00b40471d0bcabf928ad", "6f869e42bc4c0830243807006b5e92ccaed987c5", - "1480066efe0215bdd44d633dbe1b7b36785ae8ca", "a02fad3fc638e1d1c10d3a604df4bb393d5a7930", - "59f7e9f29f14a28f3e06307a6d2c505d92bac672", "2c61bed25bd5d84c2773700540393dfb6019842b", - "c5cf5c31e822e883d2a1768bb7852e63be3bb4aa", "9a21e2e4f98b172f7203af861e68cd14b830a761", - "b4f17fbaec55a565c69c714a3b5d8f4ac490c3b4", "fc1e32643a0622afc3f5cdad86abd94369176f07", - "f83864fc3c2d7a2bfc82f7f2b0dbf3cda74714cb", "a5503e69b80b4ebbd6e12ca615318866d7f7953a", - "4fac6a6565e8c32f1f62396d698b6c23f0fc665b", "17f1ca6c1de1ff8aed107ba8b2247e5ec41ebcfc", - "4fc347c433d39d21c2dfe7db951eb3f43ef2c513", "b20eb22712349162b7390f10e5670acb5ec9cd12", - "77afe0fcc0019b81a87269bc20f5381519274e90", "3520ec2a803d1be3bb16b60177906b055c2fdd16", - "05a5f0b3822f27ef60fdd2011de152542de6ec2d", "ebbcfc6ba138ac549fa2f17dda86a75e5e26fd47", - "2917dff8446879fb28b6ee2a8e95d399eb81774e", "1c67e68f4ac7f4057c712bed7f6ea424f07dec9b", - "1b712367effbd03a9b8a8c9638db3b8a42d98b5d", "7788b8ffbd7bac813c525f043ae6c78b54bcc464", - "eb3ca7fdab9840c7f7c9d7d71e484760f9581cf0", "ee1df733ffddff78579fa89a8f146d67db61404a", - "fd55b52a62bdff753e1e5c467f23a8e2ed3de1ac", "8aa26fd4b2a06e9f928d7aa4886cbf28f40169f4", - "e4bd8c43fbafa9775d5f0acb9928a91fd8596cc6", "7adeb7c36de49d088380792883ab034467726724", - "08fe040864b8ef849c1cb653cd261204e3949ae7", "14d84590bd7db3221a3fff3b31bcd4026274f34b", - "547fc4c32bb307a16122e8427580b1d153950e43", "64f349705fcf35b551fb5bcc5d93aeecf9465aaf", - "422e5fc305b81df39f79e6646a06c9af4cf11bbb", "6a9c141dba2f8cfaad51b6c16ff0c433df9cff03", - "fa3c03c1e30bd67594a79bb3e2b08722a0dfc4a2", "3ded6ed3eda7b67101db34809a7983d08a8b68e0", - "56cdb055a9af97858e5d29f9bcb1356472e9003a", "4f9bab4228e3305be42c2967a6dc4ef773cc51d1", - "717391ac5d616f117321b00c07093150b82d8ee4", "9a746963265cdc3e2498b469975feead7f6f0b47", - "edcf69daf11ee8694be60e41536b9b6178e237e4", "ac65a586026184cdbc4647326b0efb838f171576", - "4c8dad3b562ec2db631186ab24e75d6f3783fdb4", "3c18ea2cec1339263859e1ece8ec2b14d6fa537a", - "c6c8518f756d7b5e238ebd34b0e78133c2801137", "47740650b6135a8f3557fca12f7bb0a0bff7d390", - "b1c15d576ab9f14f18d9b21aa27478cbcd00361a", "42fa9484a9f1caee066628deac108b19d6b93ec0", - "3f53d018e54f70921a36f7270cc133bcd264abaf", "8bc417c5a19b6d5f44fdb89a8a9f0b424fd68c6d", - "be26134b26b66aedeb77d959fc59df699a275679", "e7e335c12372a166de125321c9b30d5f63626307", - "7f6045ebc9ba2c9051f7c11eb018f2334e665444", "dd19cfdaee44125f56fe490fa37c35d016caf47c", - "06d8625b51411ffefc23daeaf6b355e19314f90e", "9ea86d6297a5922b8219f8af414fa0770f06a030", - "0ba5e5207de2887a4476a647dea9ae1317d5aa2e", "da56a105d965c4f23df0f3011a44e8358d81a602", - "4a754fadbc3f3fd7b346d7b64f5a3b17d271c7da", "a871c37d0a5e7e6648a6c16ab63c5bbd7d70a16a", - "fd23842b87d7a9180947ac06d181eeebe5dc2941", "555a2918452f3a04c4af1f68e7413f16cb595977", - "5b1b88aa3d57df4397071a9be26bc12108a1e481", "bd076901c68d96c3bf3f311ae647c1a37a773653", - "99c5033ff768805b91e19b47c08675a0263dd3f3", "5a54a65b1fac540c1e5883ebb1fbfeb165cabc09", - "cd115c1b9ad75fca9e914a67155b4c16c8065c77", "762ee5659b9187b42699c0c075476d25528d593d", - "7133c5be52c10a132ba76e9c4b3abe9b0b7b7ed6", "cb4e2ef91ad0d1809726ad282730a9a6d7faf26b", - "87cff5c69eb53813d255a48f8ae581a8bb3301af", "84e668ca517872198ad8efa92d70b6c4de97d409", - "88cc9dabd9a787283b3d4009c290b7300d475ef6", "cd2f8129d22b8e2f5812db78025ee168dba27888", - "36810d3cce461175f81169954f6c15d96cb8edcb", "a6290116a82a957194a7b47e7efc08db93813dd0", - "bb96a933ef02562aebf4613667e77051b9db92da", "d9364abbc26f8f75f6b257f36dab42be6fc499b1", - "8e73bcf5a12e602412dfe8e2461b85529c18e304", "3fc0507df7156da61c111807c2608cdbb71b8d85", - "4ebf9514f9dd7203a3bc467b1c4073b5db3d5589", "5c6fe9d08cd043b515732de1916616029b912bac", - "5bba055b5909daab370735260cd65e7950c456f0", "7a8f63294c940bd4587e2e29c5aee58708426ac8", - "985882796501408cf8de16d91a938045fcf544c4", "740a8b09820e1ea8e5d8c71a9df6c6f1d606d55f", - "c9e1dd02449f23eae2ed983632bb1048ba67c80b", "cbb201326c9d8621f2ed57b6c36edebc9405ba2a", - "4068e14444cd547d9c8557a69521bf127cbdb6fe", "06e3b6adcae7c833e84eeec5208bd9ffd8e7bd70", - "dcbeb76862ffa50e56423a7f556f7a3c7b279bf5", "556d08322b518cf02a9c29097900d7b16d2692cc", - "7550e1c3d068211d065be3676233b369c6d203d9", "2f95989adeec8c3f3fbf8645c616d1071a7363a7", - "ca06cf98b3d5fcc28a66d6bfdd0bac34a8d54737", "e9088616ec2fef76871de1f4affe67742915786e", - "42db27d937253393f68da84ef4d64e6d890d60f2", "7836f5aebb1a3962b3d987d6cffc1621d62e7031", - "52f8c06652c719cb54169981a309a8843ed64b9c", "9d2e19bd705a6c9330e3511d3605c3acf00d5ae6", - "8d72b848b85b63c34a886e64a5cabb53bf2c44c4", "97d35b990bd278de751bd95b311ede35ebf1dc7c", - "3bfb725c6d27358e24d05eb8b69258c47437ba16", "1a4e7ed04713b1585a663b62e799bd9133c47d28", - "41751d21de5c316c856968e2261146db0bcffa63", "cac1045bb2f08cbad3cf932c0d48d8484e62586a", - "f26f9979321cb3c40b12bcadbf1e4671f9ff5f5a", "baf156ea80f1613488b2973b105b0e5ec507fa40", - "1225c97bf1b3efa570d2c614fcce6431aed98da8", "4823ad32811a54c4e3d86d39d4eb722f0a5f7a03", - "4f64b0b47b2092fa9e2ff07620c2beff0de7ae39", "dde58a3b85f6f12b4cf7aff968a681928af64ff5", - "1f088cb0398d95fa9281b13d6d3400ed619bba24", "d9738aec244d520ee9123ee206ee954efc2bfd5e", - "4493e7e7a88d8da224af1aa8c5828dd319f86021", "1725d50bfdf81c3065aa061a9a49301f822844da", - "8f1c8a9f690279edd4a7fb37e0af4b1eeca3db17", "2dd431e6f6524c60780cb2d785130b69eab6b12c", - "30a47a979f60883359b902ccdf57989d5206b7b8", "f72242e0b21406e101bc74023700fa7ffa8c78ce", - "affd31998855a2e2c66e0fedd5f2a0368609073d", "d7bf882fcb963728e69252fffac173f153e1c9fa", - "d50e4560c01b71343b4300d08ef302d049466219", "235904923f703c3a95f74f55ebfba37385fb7761", - "e31e0b576ab331240fd4df0e6fa1ba70a1db33b9", "55da5f445c8e5dcbd75c522f8ebb50aa2c9bf38d", - "7124aad094d27d82b38c751c4f6069a31e50e1a8", "f4b2a6006d676c4202f936c3d3e455315c3cfd7c", - "9cc85a4fc2840adfa1850cd0b01c9fd1c986ab6b", "39efda7cffab3597dbaba91fb10ac0041b2d53da", - "e33fe3660eea113d53f45944e8489d54c00d4672", "72b08dc4fb03ca0e4763e528b320973db5ab947d", - "28b5b2b6e88d6eeff6ed047c8a7959a78bb6d8f6", "b0e8a7b86effe063533986d940aa2bfc3d270faa", - "371c9207ead2cff515884a1b6c6c0831dfe2eb26", "ab38fcfc415ab75e2ba3fe96cdaaa3ed51cd58f7", - "afcf173f583e25786dd094969aef55c7e942edd2", "f0852629be334cceaff80552c382bcc0a08a6acb", - "708ef99585a76555dc567f5f3a07616b30e6e6b1", "34a2614fab8f3e0ec25eb382db2e47ad4071b12d", - "3707a60de155026615d1c4d3b7bab12b0e154420", "055a2a97afcf45f8473e0cb3ba33f947e8eb828b", - "eaf05fb595c20bd0fb27da51db06dd4bceaa5413", "8f0b1c081f8efbb1ba661c29c5cd16d546d05f9f", - "64954d58a69e8aec72d8f1065dedc57430e9a935", "5990dfdf4cdf6a961fbec8a03b641840cccb8ea5", - "566dd607531adab0284af7d02c2aa0b31d3067c9", "d53ae4284cc7bab5f53aafde89538a50ec71bfbe", - "2c55bd4cc2ef2dc26a12c02c5f077a2b61270a59", "3385bf45d0d065d263d8e0934463695b37c718ad", - "0054112babaa8e635df79b63e2dd89dede1accd7", "9640b095837aecc45669aead3878eea9a5232e13", - "aa180c642973bbf58eeb08d142de517b1de64629", "7e4caa7466bf8fa28522dada3031b1907e5b019a", - "122dd7a86ca24c04cf60b1afc7baf4c7b120862d", "f84b3710bee3ce9d6c61633338de5335f8055120", - "2c58738817c223ba71a4cfdfc1e070dce095a76a", "3d9f4773b6c4675260f695d964a78669e1254213", - "86ea67ed19af6e3ce37af6160eb251cb47d0a536", "3134f576f5a85a80e055b501485d6e08b957e32e", - "b136d742bf25ae0917599f4ca623361ecaaf10e0", "f58b88b6e3cef4a11b6a04373b639dbc374f0d48", - "44893414ce5514ccb69451d6438aeee0a5ae3fa4", "d07a5141298a134bc7d56690cdcb51d22aac17d2", - "5c635c23aa70e436677220f0af95d80c1b075030", "3c9604661631e3984cb7fface67858cf8e16bfe8", - "c0329aa82069ff716df6885a9d42d67cc56f364f"], "public": false}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '48452' - Content-Type: - - application/json - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://www.braintrust.dev/api/experiment/register - response: - body: - string: '{"project":{"id":"6816a170-e20e-4854-b2a8-47d4ecbaa8f8","org_id":"5ba6d482-b475-4c66-8cd2-5815694764e3","name":"test","description":null,"created":"2025-11-20T16:26:47.806Z","deleted_at":null,"user_id":"855483c6-68f0-4df4-a147-df9b4ea32e0c","settings":null},"experiment":{"id":"552e3c85-e7ee-4e94-8162-d208d07b20fe","project_id":"6816a170-e20e-4854-b2a8-47d4ecbaa8f8","name":"test-a2206206","description":null,"created":"2026-01-14T21:01:53.205Z","repo_info":{"commit":"78db572d12b7573245b1a4dea6edefd2d7d3e939","branch":"speed","tag":null,"dirty":true,"author_name":"Matt - Perpick","author_email":"matt@braintrustdata.com","commit_message":"Speed - up OpenAI tests 9x by adding VCR cassettes\n\n- Add VCR decorators to 3 tests - that were making real API calls:\n - test_agents_tool_openai_nested_spans - (5.97s -> <0.1s)\n - test_braintrust_tracing_processor_concurrency_bug (1.40s - -> 0.1s)\n - test_braintrust_tracing_processor_current_span_detection (0.67s - -> <0.1s)\n- Record cassettes for these tests\n- Remove unnecessary time.sleep(0.2) - from test_openai_streaming_with_break\n- Centralize vcr_config in conftest.py - with CI enforcement:\n - record_mode=\"none\" in CI (fail if cassette missing)\n - - record_mode=\"once\" locally (record if missing)\n- Remove duplicate vcr_config - fixtures from individual test files\n- Keep Google-specific vcr_config for - HTTP method uppercase normalization\n\nOpenAI wrapper tests: 9s -> 1s (9x - faster)\nFull nox session: 18s -> 10s (44% faster)\n\nCo-Authored-By: Claude - Opus 4.5 ","commit_time":"2026-01-14T15:58:12-05:00","git_diff":"diff - --git a/.claude/settings.json b/.claude/settings.json\nindex cd426b62..9a367086 - 100644\n--- a/.claude/settings.json\n+++ b/.claude/settings.json\n@@ -40,6 - +40,8 @@\n \"Bash(jq:*)\",\n \"Bash(source:*)\",\n \"Bash(cd:*)\",\n+ \"Bash(set:*)\",\n+ \"Bash(sort:*)\",\n \"Bash(.nox/*/bin/pytest:*)\",\n \"Bash(.nox/*/bin/python:*)\",\n \"Bash(.nox/*/bin/pip:*)\",\ndiff - --git a/py/src/braintrust/test_bt_json.py b/py/src/braintrust/test_bt_json.py\nindex - 7ea161df..304957cf 100644\n--- a/py/src/braintrust/test_bt_json.py\n+++ b/py/src/braintrust/test_bt_json.py\n@@ - -2,9 +2,12 @@\n # pyright: reportUnknownArgumentType=false\n # pyright: reportPrivateUsage=false\n - import json\n+import os\n from typing import Any\n from unittest import TestCase\n - \n+import pytest\n+\n from braintrust.bt_json import bt_dumps, bt_safe_deep_copy\n - from braintrust.logger import Attachment, ExternalAttachment\n \n@@ -281,30 - +284,33 @@ class TestBTJson(TestCase):\n self.assertTrue(\"(1, 2)\" - in result or \"1, 2\" in result)\n self.assertIn(\"None\", result)\n - \n- def test_to_bt_safe_special_objects(self):\n- \"\"\"Test _to_bt_safe - handling of Span, Experiment, Dataset, Logger objects.\"\"\"\n- from - braintrust import init, init_dataset, init_logger\n+@pytest.mark.vcr\n+def - test_to_bt_safe_special_objects():\n+ \"\"\"Test _to_bt_safe handling of - Span, Experiment, Dataset, Logger objects.\"\"\"\n+ from braintrust import - init, init_dataset, init_logger\n \n- # Create actual objects\n- exp - = init(project=\"test\", experiment=\"test\")\n- dataset = init_dataset(project=\"test\", - name=\"test\")\n- logger = init_logger(project=\"test\")\n- span - = exp.start_span()\n+ # Create actual objects\n+ exp = init(project=\"test\", - experiment=\"test\")\n+ dataset = init_dataset(project=\"test\", name=\"test\")\n+ logger - = init_logger(project=\"test\")\n+ span = exp.start_span()\n \n- # - Import _to_bt_safe\n- from braintrust.bt_json import _to_bt_safe\n+ # - Import _to_bt_safe\n+ from braintrust.bt_json import _to_bt_safe\n+\n+ # - Test each special object\n+ assert _to_bt_safe(span) == \"\"\n+ assert - _to_bt_safe(exp) == \"\"\n+ assert _to_bt_safe(dataset) == - \"\"\n+ assert _to_bt_safe(logger) == \"\"\n \n- # - Test each special object\n- self.assertEqual(_to_bt_safe(span), \"\")\n- self.assertEqual(_to_bt_safe(exp), - \"\")\n- self.assertEqual(_to_bt_safe(dataset), \"\")\n- self.assertEqual(_to_bt_safe(logger), - \"\")\n+ # Clean up\n+ exp.flush()\n+ dataset.flush()\n+ logger.flush()\n - \n- # Clean up\n- exp.flush()\n- dataset.flush()\n- logger.flush()\n - \n+class TestBTJsonAttachments(TestCase):\n def test_to_bt_safe_attachments(self):\n \"\"\"Test - _to_bt_safe preserves BaseAttachment and converts ReadonlyAttachment to reference.\"\"\"\n from - braintrust.bt_json import _to_bt_safe"},"commit":"78db572d12b7573245b1a4dea6edefd2d7d3e939","base_exp_id":"bd8d8953-05e9-46f9-aa08-77cd1de9acfd","deleted_at":null,"dataset_id":null,"dataset_version":null,"public":false,"user_id":"855483c6-68f0-4df4-a147-df9b4ea32e0c","metadata":null,"tags":null}}' - headers: - Cache-Control: - - public, max-age=0, must-revalidate - Content-Encoding: - - gzip - Content-Security-Policy: - - 'script-src ''self'' ''unsafe-eval'' ''wasm-unsafe-eval'' ''strict-dynamic'' - ''nonce-YmEzY2M1MTUtNTQ3ZS00NDI2LTgwZTItYzUxZGVkYjIwMWYy'' *.js.stripe.com - js.stripe.com maps.googleapis.com ; style-src ''self'' ''unsafe-inline'' *.braintrust.dev - btcm6qilbbhv4yi1.public.blob.vercel-storage.com fonts.googleapis.com www.gstatic.com - d4tuoctqmanu0.cloudfront.net; font-src ''self'' data: fonts.gstatic.com btcm6qilbbhv4yi1.public.blob.vercel-storage.com - cdn.jsdelivr.net d4tuoctqmanu0.cloudfront.net fonts.googleapis.com mintlify-assets.b-cdn.net - fonts.cdnfonts.com; object-src ''none''; base-uri ''self''; form-action ''self''; - frame-ancestors ''self''; worker-src ''self'' blob:; report-uri https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=16; - report-to csp-endpoint-0' - Content-Type: - - application/json; charset=utf-8 - Date: - - Wed, 14 Jan 2026 21:01:53 GMT - Etag: - - W/"17e7t3k483r3tt" - Reporting-Endpoints: - - csp-endpoint-0="https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=16" - Server: - - Vercel - Strict-Transport-Security: - - max-age=63072000 - Transfer-Encoding: - - chunked - X-Clerk-Auth-Message: - - Invalid JWT form. A JWT consists of three parts separated by dots. (reason=token-invalid, - token-carrier=header) - X-Clerk-Auth-Reason: - - token-invalid - X-Clerk-Auth-Status: - - signed-out - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-Matched-Path: - - /api/experiment/register - X-Nonce: - - YmEzY2M1MTUtNTQ3ZS00NDI2LTgwZTItYzUxZGVkYjIwMWYy - X-Vercel-Cache: - - MISS - X-Vercel-Id: - - iad1::iad1::hv5tq-1768424513097-a3abfd2a6512 - status: - code: 200 - message: OK -- request: - body: '{"rows": [{"_is_merge": false, "context": {"caller_filename": "/Users/matt/code/braintrustdata/w_braintrust-sdk_speed/py/.nox/test_core/lib/python3.13/site-packages/_pytest/python.py", - "caller_functionname": "pytest_pyfunc_call", "caller_lineno": 166}, "created": - "2026-01-14T21:01:52.551602+00:00", "experiment_id": "552e3c85-e7ee-4e94-8162-d208d07b20fe", - "id": "6e0a5754-64f1-43cd-8c03-22e64771d020", "metrics": {"start": 1768424512.551599}, - "root_span_id": "84748fb4-1f9e-49f2-bf94-6ebd3b604bb8", "span_attributes": {"exec_counter": - 1, "name": "root", "type": "eval"}, "span_id": "84748fb4-1f9e-49f2-bf94-6ebd3b604bb8", - "span_parents": null}], "api_version": 2}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '664' - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://api.braintrust.dev/logs3 - response: - body: - string: '{"ids":["6e0a5754-64f1-43cd-8c03-22e64771d020"],"xact_id":"1000196487721888886"}' - headers: - Connection: - - keep-alive - Content-Length: - - '92' - Content-Type: - - application/json; charset=utf-8 - Date: - - Wed, 14 Jan 2026 21:01:53 GMT - Via: - - 1.1 9750f5ee94b45ad0faba87b3fac2aad6.cloudfront.net (CloudFront), 1.1 537c1727cc67e6d2567bb61ae0478182.cloudfront.net - (CloudFront) - X-Amz-Cf-Id: - - ZD_6xQ6OAr9LoAJ-AvUvN0ILT9f_xrYiTC6rkVlZY_8gfUrk7cVvlw== - X-Amz-Cf-Pop: - - JFK50-P5 - - JFK50-P2 - X-Amzn-Trace-Id: - - Root=1-69680441-696c693e6b09c0ac52d0ae70;Parent=08af0b526bdabf02;Sampled=0;Lineage=1:24be3d11:0 - X-Cache: - - Miss from cloudfront - access-control-allow-credentials: - - 'true' - access-control-expose-headers: - - x-bt-cursor,x-bt-found-existing,x-bt-query-plan - content-encoding: - - gzip - etag: - - W/"50-PMOPlqpTyDNUCSSoCG7IiztERIc" - vary: - - Origin, Accept-Encoding - x-amz-apigw-id: - - XMWaSG2eoAMEsPQ= - x-amzn-RequestId: - - b30af5ca-e21b-4458-afce-45bdddf10649 - x-bt-internal-trace-id: - - 6968044100000000495e5bbd4e29306b - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/cli/__init__.py b/py/src/braintrust/cli/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/py/src/braintrust/cli/__main__.py b/py/src/braintrust/cli/__main__.py deleted file mode 100644 index 231e260e6..000000000 --- a/py/src/braintrust/cli/__main__.py +++ /dev/null @@ -1,56 +0,0 @@ -import argparse -import logging -import os -import sys -import textwrap -import traceback - -from . import eval, install, push - - -def main(args=None): - """The main routine.""" - - # Add the current working directory to sys.path, similar to python's - # unittesting frameworks. - sys.path.insert(0, os.getcwd()) - - if args is None: - args = sys.argv[1:] - - parent_parser = argparse.ArgumentParser(add_help=False) - parent_parser.add_argument( - "--verbose", - "-v", - default=0, - action="count", - help="Include additional details, including full stack traces on errors. Pass twice (-vv) for debug logging.", - ) - - parser = argparse.ArgumentParser( - description=textwrap.dedent( - """braintrust is a cli tool to work with Braintrust. - To see help for a specific subcommand, run `braintrust --help`, - e.g. `braintrust eval --help`""" - ) - ) - subparsers = parser.add_subparsers(help="sub-command help", dest="subcommand", required=True) - - for module in [eval, install, push]: - module.build_parser(subparsers, parent_parser) - - args = parser.parse_args(args=args) - level = logging.DEBUG if args.verbose >= 2 else logging.INFO - logging.basicConfig(format="%(asctime)s %(levelname)s [%(name)s]: %(message)s", level=level) - - return args.func(args) - - -if __name__ == "__main__": - try: - ret = main() - if ret: - os._exit(1) - except: - traceback.print_exc() - os._exit(1) diff --git a/py/src/braintrust/cli/eval.py b/py/src/braintrust/cli/eval.py deleted file mode 100644 index 0a0eb229c..000000000 --- a/py/src/braintrust/cli/eval.py +++ /dev/null @@ -1,406 +0,0 @@ -import asyncio -import fnmatch -import importlib -import logging -import os -import sys -from dataclasses import dataclass, field -from threading import Lock - -from .. import login -from ..framework import ( - BaseExperiment, - Evaluator, - EvaluatorInstance, - ReporterDef, - _evals, - _set_lazy_load, - default_reporter, - init_experiment, - parse_filters, - run_evaluator, - set_thread_pool_max_workers, -) -from ..logger import Dataset -from ..util import eprint - -INCLUDE = [ - "**/eval_*.py", -] -EXCLUDE = ["**/site-packages/**"] - -_logger = logging.getLogger("braintrust.eval") - - -_import_lock = Lock() - - -@dataclass -class FileHandle: - in_file: str - - def rebuild(self): - in_file = os.path.abspath(self.in_file) - - with _import_lock: - with _set_lazy_load(True): - _evals.clear() - - try: - # https://stackoverflow.com/questions/67631/how-can-i-import-a-module-dynamically-given-the-full-path - spec = importlib.util.spec_from_file_location("eval", in_file) - module = importlib.util.module_from_spec(spec) - spec.loader.exec_module(module) - - ret = _evals.copy() - finally: - _evals.clear() - - return ret - - def watch(self): - raise NotImplementedError - - -@dataclass -class EvaluatorOpts: - verbose: bool - no_send_logs: bool - no_progress_bars: bool - terminate_on_failure: bool - watch: bool - filters: list[str] - list: bool - jsonl: bool - - -@dataclass -class LoadedEvaluator: - handle: FileHandle - evaluator: Evaluator - reporter: ReporterDef | str | None = None - - -@dataclass -class EvaluatorState: - evaluators: list[LoadedEvaluator] = field(default_factory=list) - reporters: dict[str, ReporterDef] = field(default_factory=dict) - - -def update_evaluators(eval_state: EvaluatorState, handles, terminate_on_failure): - for handle in handles: - try: - module_evals = handle.rebuild() - except Exception as e: - if terminate_on_failure: - raise - else: - eprint(f"Failed to import {handle.in_file}: {e}") - continue - - for evaluator in module_evals.evaluators.values(): - if not isinstance(evaluator, EvaluatorInstance): - continue - - eval_state.evaluators.append( - LoadedEvaluator(handle=handle, evaluator=evaluator.evaluator, reporter=evaluator.reporter) - ) - - for reporter_name, reporter in module_evals.reporters.items(): - if not isinstance(reporter, ReporterDef): - continue - - if reporter_name in eval_state.reporters: - _logger.warning( - f"Reporter {reporter_name} already exists (in {eval_state.reporters[reporter_name].module} and {handle.in_file}). Will skip {reporter_name} in {handle.in_file}." - ) - continue - - eval_state.reporters[reporter_name] = reporter - - -async def run_evaluator_task(evaluator, position, opts: EvaluatorOpts): - experiment = None - if not opts.no_send_logs: - base_experiment_name = None - if isinstance(evaluator.data, BaseExperiment): - base_experiment_name = evaluator.data.name - - dataset = None - if isinstance(evaluator.data, Dataset): - dataset = evaluator.data - - # NOTE: This code is duplicated with _EvalCommon in py/src/braintrust/framework.py. - # Make sure to update those arguments if you change this. - experiment = init_experiment( - project_name=evaluator.project_name, - project_id=evaluator.project_id, - experiment_name=evaluator.experiment_name, - description=evaluator.description, - metadata=evaluator.metadata, - is_public=evaluator.is_public, - update=evaluator.update, - base_experiment=base_experiment_name, - base_experiment_id=evaluator.base_experiment_id, - git_metadata_settings=evaluator.git_metadata_settings, - repo_info=evaluator.repo_info, - dataset=dataset, - ) - - try: - return await run_evaluator( - experiment, evaluator, position if not opts.no_progress_bars else None, opts.filters - ) - finally: - if experiment: - experiment.flush() - - -def resolve_reporter(reporter: ReporterDef | str | None, reporters: dict[str, ReporterDef]) -> ReporterDef: - if isinstance(reporter, str): - if reporter not in reporters: - raise ValueError(f"Reporter {reporter} not found") - return reporters[reporter] - elif reporter: - return reporter - elif not reporters: - return default_reporter - elif len(reporters) == 1: - return next(iter(reporters.values())) - else: - reporter_names = ", ".join(reporters.keys()) - raise ValueError(f"Multiple reporters found ({reporter_names}). Please specify a reporter explicitly.") - - -def add_report(eval_reports, reporter, report): - if reporter.name not in eval_reports: - eval_reports[reporter.name] = {"reporter": reporter, "results": []} - eval_reports[reporter.name]["results"].append(report) - - -async def run_once(handles: list[FileHandle], evaluator_opts: EvaluatorOpts) -> bool: - objects = EvaluatorState() - update_evaluators(objects, handles, terminate_on_failure=evaluator_opts.terminate_on_failure) - - if evaluator_opts.list: - for evaluator in objects.evaluators: - print(f"{evaluator.evaluator.eval_name}") - return True - - eval_promises = [ - asyncio.create_task(run_evaluator_task(evaluator.evaluator, idx, evaluator_opts)) - for idx, evaluator in enumerate(objects.evaluators) - ] - eval_results = [await p for p in eval_promises] - - eval_reports = {} - for evaluator, result in zip(objects.evaluators, eval_results): - resolved_reporter = resolve_reporter(evaluator.reporter, objects.reporters) - report = resolved_reporter._call_report_eval( - evaluator=evaluator.evaluator, result=result, verbose=evaluator_opts.verbose, jsonl=evaluator_opts.jsonl - ) - add_report(eval_reports, resolved_reporter, report) - - all_success = True - for report in eval_reports.values(): - reporter = report["reporter"] - results = [await r for r in report["results"]] - if not await reporter._call_report_run(results, verbose=evaluator_opts.verbose, jsonl=evaluator_opts.jsonl): - _logger.error(f"Reporter {reporter.name} failed") - all_success = False - - return all_success - - -def check_match(path_input, include_patterns, exclude_patterns): - p = os.path.abspath(path_input) - if include_patterns: - include = False - for pattern in include_patterns: - if fnmatch.fnmatch(p, pattern): - include = True - break - if not include: - return False - - if exclude_patterns: - exclude = False - for pattern in exclude_patterns: - if fnmatch.fnmatch(p, pattern): - exclude = True - break - return not exclude - - return True - - -def collect_files(input_path): - if os.path.isdir(input_path): - for root, dirs, files in os.walk(input_path): - for file in files: - fname = os.path.join(root, file) - if check_match(fname, INCLUDE, EXCLUDE): - yield fname - else: - if not check_match(input_path, INCLUDE, EXCLUDE): - _logger.warning( - f"Reading {input_path} because it was specified directly. Rename it to eval_*.py " - + "to include it automatically when you specify a directory." - ) - yield input_path - - -def initialize_handles(files): - input_paths = files if len(files) > 0 else ["."] - - fnames = set() - for path in input_paths: - for fname in collect_files(path): - fnames.add(os.path.abspath(fname)) - - return [FileHandle(in_file=fname) for fname in fnames] - - -def run(args): - if args.num_workers: - set_thread_pool_max_workers(args.num_workers) - - if args.env_file: - from dotenv import load_dotenv - - load_dotenv(args.env_file) - - evaluator_opts = EvaluatorOpts( - verbose=args.verbose > 0, - no_send_logs=args.no_send_logs, - no_progress_bars=args.no_progress_bars, - terminate_on_failure=args.terminate_on_failure, - watch=args.watch, - filters=parse_filters(args.filter) if args.filter else [], - list=args.list, - jsonl=args.jsonl, - ) - - if args.watch: - eprint("Watch mode is not yet implemented") - exit(1) - if args.watch and args.list: - eprint("Cannot specify both --list and --watch") - exit(1) - - handles = initialize_handles(args.files) - - if args.dev: - from braintrust.devserver.server import run_dev_server - - objects = EvaluatorState() - update_evaluators(objects, handles, terminate_on_failure=True) - evaluators = [e.evaluator for e in objects.evaluators] - run_dev_server( - evaluators, - host=args.dev_host, - port=args.dev_port, - org_name=args.dev_org_name, - ) - sys.exit(0) - - if not evaluator_opts.no_send_logs: - login( - api_key=args.api_key, - org_name=args.org_name, - app_url=args.app_url, - ) - - if not asyncio.run(run_once(handles, evaluator_opts)): - sys.exit(1) - - -def build_parser(subparsers, parent_parser): - parser = subparsers.add_parser( - "eval", - help="Run evals locally.", - parents=[parent_parser], - ) - - parser.add_argument( - "--api-key", - help="Specify a braintrust api key. If the parameter is not specified, the BRAINTRUST_API_KEY environment variable will be used.", - ) - parser.add_argument( - "--org-name", - help="The name of a specific organization to connect to. This is useful if you belong to multiple.", - ) - parser.add_argument( - "--app-url", - help="Specify a custom braintrust app url. Defaults to https://www.braintrust.dev. This is only necessary if you are using an experimental version of Braintrust", - ) - parser.add_argument( - "--watch", - action="store_true", - help="Watch files for changes and rerun evals when changes are detected", - ) - parser.add_argument( - "--filter", - help="Only run evaluators that match these filters. Each filter is a regular expression (https://docs.python.org/3/library/re.html). For example, --filter metadata.priority='^P0$' input.name='foo.*bar' will only run evaluators that have metadata.priority equal to 'P0' and input.name matching the regular expression 'foo.*bar'.", - nargs="*", - ) - parser.add_argument("--list", help="List, but do not execute, evaluators.", action="store_true") - parser.add_argument( - "--jsonl", - help="Format score summaries as jsonl, i.e. one JSON-formatted line per summary.", - action="store_true", - ) - parser.add_argument( - "--no-send-logs", - action="store_true", - help="Do not send logs to Braintrust. Useful for testing evaluators without uploading results.", - ) - parser.add_argument( - "--no-progress-bars", - action="store_true", - help="Do not show progress bars when processing evaluators.", - ) - parser.add_argument( - "--terminate-on-failure", - action="store_true", - help="If provided, terminates on a failing eval, instead of the default (moving onto the next one).", - ) - parser.add_argument( - "--env-file", - help="A path to a .env file containing environment variables to load (via dotenv).", - ) - parser.add_argument( - "--num-workers", - type=int, - help="Specify the number of concurrent worker threads to run evals over, if they are defined as synchronous functions. Async functions will be run in the single-threaded asyncio event loop. If not specified, defaults to the number of cores on the machine.", - ) - - parser.add_argument( - "--dev", - action="store_true", - help="Run the evaluators in dev mode. This will start a dev server which you can connect to via the playground's remote evals feature.", - ) - parser.add_argument( - "--dev-host", - help="The host to bind the dev server to. Defaults to localhost. Set to 0.0.0.0 to bind to all interfaces.", - type=str, - default="localhost", - ) - parser.add_argument( - "--dev-port", - help="The port to bind the dev server to. Defaults to 8300.", - type=int, - default=8300, - ) - parser.add_argument( - "--dev-org-name", - help="Only allow users that belong to this org name to run remote evals.", - type=str, - ) - parser.add_argument( - "files", - nargs="*", - help="A list of files or directories to run. If no files are specified, the current directory is used.", - ) - - parser.set_defaults(func=run) diff --git a/py/src/braintrust/cli/install/__init__.py b/py/src/braintrust/cli/install/__init__.py deleted file mode 100644 index d01ec8088..000000000 --- a/py/src/braintrust/cli/install/__init__.py +++ /dev/null @@ -1,38 +0,0 @@ -import argparse -import textwrap - -_module_not_found_error = None -try: - from . import api, bump_versions, logs, run_migrations -except ModuleNotFoundError as e: - _module_not_found_error = e - - -def fail_with_module_not_found_error(*args, **kwargs): - raise ModuleNotFoundError( - textwrap.dedent( - f"""\ - At least one dependency not found: {str(_module_not_found_error)!r} - It is possible that braintrust was installed without the CLI dependencies. Run: - - pip install 'braintrust[cli]' - - to install braintrust with the CLI dependencies (make sure to quote 'braintrust[cli]').""" - ) - ) - - -def build_parser(subparsers, parent_parser): - install_parser = subparsers.add_parser( - "install", - help="Tools to setup and verify Braintrust's installation in your environment.", - parents=[parent_parser], - ) - if _module_not_found_error: - install_parser.add_argument("args", nargs=argparse.REMAINDER) - install_parser.set_defaults(func=fail_with_module_not_found_error) - else: - install_subparsers = install_parser.add_subparsers(dest="install_subcommand", required=True) - - for module in [api, logs, bump_versions, run_migrations]: - module.build_parser(install_subparsers, parents=[parent_parser]) diff --git a/py/src/braintrust/cli/install/api.py b/py/src/braintrust/cli/install/api.py deleted file mode 100644 index 2538c605c..000000000 --- a/py/src/braintrust/cli/install/api.py +++ /dev/null @@ -1,514 +0,0 @@ -import logging -import os -import textwrap -import time - -from botocore.exceptions import ClientError -from braintrust.logger import app_conn, login - -# pylint: disable=no-name-in-module -from ...aws import cloudformation -from ...util import response_raise_for_status - -_logger = logging.getLogger("braintrust.install.api") - -PARAMS = { - "OrgName": "org_name", - "ProvisionedConcurrency": "provisioned_concurrency", - "EncryptDatabase": "encrypt_database", - "PostgresAlternativeHost": "postgres_alternative_host", - "APIHandlerMemorySize": "api_handler_memory_size", - "WhitelistedOrigins": "whitelisted_origins", - "PublicSubnet1AZ": "public_subnet_1_az", - "PrivateSubnet1AZ": "private_subnet_1_az", - "PrivateSubnet2AZ": "private_subnet_2_az", - "PrivateSubnet3AZ": "private_subnet_3_az", - "VPCCIDR": "vpc_cidr", - "PublicSubnet1CIDR": "public_subnet_1_cidr", - "PrivateSubnet1CIDR": "private_subnet_1_cidr", - "PrivateSubnet2CIDR": "private_subnet_2_cidr", - "PrivateSubnet3CIDR": "private_subnet_3_cidr", - "ManagedPostgres": "managed_postgres", - "PostgresVersion": "postgres_version", - "OutboundRateLimitWindowMinutes": "outbound_rate_limit_window_minutes", - "OutboundRateLimitMaxRequests": "outbound_rate_limit_max_requests", - "UseGlobalProxy": "use_global_proxy", - "EnableQuarantine": "enable_quarantine", - "EnableBrainstore": "enable_brainstore", - "BrainstoreInstanceKeyPairName": "brainstore_instance_key_pair_name", - "BrainstoreInstanceType": "brainstore_instance_type", - "BrainstoreInstanceCount": "brainstore_instance_count", - "BrainstoreMaxInstanceCount": "brainstore_max_instance_count", - "BrainstoreVersionOverride": "brainstore_version_override", - "BrainstoreLicenseKey": "brainstore_license_key", -} - -REMOVED_PARAMS = ["ThirdAZIndex"] - -DEFAULTS = { - "PrimaryOrgName": "", - "DwType": "Postgres", - "EncryptDatabase": "false", - "ProvisionedConcurrency": 0, - "APIHandlerMemorySize": 10240, -} - -CAPABILITIES = ["CAPABILITY_IAM", "CAPABILITY_AUTO_EXPAND"] - -LATEST_TEMPLATE = "https://braintrust-cf.s3.amazonaws.com/braintrust-latest.yaml" - - -def build_parser(subparsers, parents): - parser = subparsers.add_parser("api", help="Install the Braintrust function API", parents=parents) - - parser.add_argument("name", help="Name of the CloudFormation stack to create or update") - parser.add_argument( - "--create", - help="Create the stack if it does not exist", - action="store_true", - default=False, - ) - parser.add_argument( - "--vpc-connect", - help="Connect to an existing VPC", - action="store_true", - default=False, - ) - parser.add_argument( - "--template", - help="A specific CloudFormation template URL to use", - default=None, - ) - parser.add_argument( - "--update-template", - help="Update the CloudFormation to the latest version of the template", - action="store_true", - default=False, - ) - - # OrgName, ProvisionedConcurrency - parser.add_argument("--org-name", help="The name of your organization", default=None) - parser.add_argument( - "--provisioned-concurrency", - help="The amount of provisioned concurrency", - default=None, - type=int, - ) - parser.add_argument( - "--api-handler-memory-size", - help="The amount of memory to allocate to the API handler", - default=None, - type=int, - ) - parser.add_argument( - "--whitelisted-origins", - help="Comma-separated list of origins to whitelist", - default=None, - ) - parser.add_argument( - "--public-subnet-1-az", - help="The availability zone for the public subnet", - default=None, - ) - parser.add_argument( - "--private-subnet-1-az", - help="The availability zone for private subnet 1", - default=None, - ) - parser.add_argument( - "--private-subnet-2-az", - help="The availability zone for private subnet 2", - default=None, - ) - parser.add_argument( - "--private-subnet-3-az", - help="The availability zone for private subnet 3", - default=None, - ) - - parser.add_argument( - "--vpc-cidr", - help="The CIDR for the VPC", - default=None, - ) - parser.add_argument( - "--public-subnet-1-cidr", - help="The CIDR for the public subnet", - default=None, - ) - parser.add_argument( - "--private-subnet-1-cidr", - help="The CIDR for private subnet 1", - default=None, - ) - parser.add_argument( - "--private-subnet-2-cidr", - help="The CIDR for private subnet 2", - default=None, - ) - parser.add_argument( - "--private-subnet-3-cidr", - help="The CIDR for private subnet 3", - default=None, - ) - - # PostgresUrl - parser.add_argument( - "--managed-postgres", - help="Spin up an RDS instance to use as the datastore", - default=None, - choices=[None, "true", "false"], - ) - parser.add_argument( - "--encrypt-database", - help="Whether to encrypt the database", - default="false", - choices=[None, "true", "false"], - ) - parser.add_argument( - "--postgres-version", - help="The version of the postgres instance", - default=None, - ) - parser.add_argument( - "--postgres-alternative-host", - help="Use an external host for postgres (but the same secrets)", - default=None, - ) - - # ElastiCacheClusterId - parser.add_argument("--elasticache-cluster-host", help="The ElastiCacheCluster host to use", default=None) - parser.add_argument( - "--elasticache-cluster-port", help="The ElastiCacheCluster host to use", default=None, type=int - ) - - # SecurityGroupId, SubnetIds - parser.add_argument("--security-group-id", help="The security group ID to use", default=None) - parser.add_argument("--subnet-ids", help="The subnet IDs to use", default=None) - - # Rate limit configuration. - parser.add_argument( - "--outbound-rate-limit-window-minutes", - help="The time frame in minutes over which rate per-user rate limits are accumulated", - default=None, - type=int, - ) - parser.add_argument( - "--outbound-rate-limit-max-requests", - help="The maximum number of requests per user allowed in the time frame specified by OutboundRateLimitMaxRequests. Setting to 0 will disable rate limits", - default=None, - type=int, - ) - - parser.add_argument( - "--use-global-proxy", - help="Use the global cloudflare proxy (https://braintrustproxy.com)", - default=None, - choices=[None, "true", "false"], - ) - - parser.add_argument( - "--enable-quarantine", - help="Enable the quarantine feature (running typescript and python functions)", - default=None, - choices=[None, "true", "false"], - ) - - # Advancd use only - parser.add_argument( - "--postgres-url", - help="[Advanced] The postgres URL to use (if you are connecting to another VPC)", - default=None, - ) - - # To configure your org - parser.add_argument( - "--api-key", - help="The API key to use to configure your org's API URL and Proxy URL", - default=os.environ.get("BRAINTRUST_API_KEY", None), - ) - parser.add_argument( - "--update-stack-url", - help="Update the organization's API URL to match the stack's universal URL", - action="store_true", - default=False, - ) - - # Brainstore configuration - parser.add_argument( - "--enable-brainstore", - help="Enable Brainstore object-storage data backend", - choices=[None, "true", "false"], - default=None, - ) - parser.add_argument( - "--brainstore-license-key", - help="The license key to use for Brainstore", - default=None, - ) - parser.add_argument( - "--brainstore-instance-key-pair-name", - help="The EC2 Key Pair to allow SSH access to the Brainstore instance", - default=None, - ) - parser.add_argument( - "--brainstore-instance-type", - help="EC2 instance type for Brainstore. Must be a Graviton instance type.", - default=None, - ) - parser.add_argument( - "--brainstore-instance-count", - help="Number of Brainstore instances to run", - type=int, - default=None, - ) - parser.add_argument( - "--brainstore-max-instance-count", - help="Max scaling size for Brainstore instances", - type=int, - default=None, - ) - parser.add_argument( - "--brainstore-version-override", - help="Lock Brainstore to a specific docker tag", - default=None, - ) - - parser.set_defaults(func=main) - - -def main(args): - template = args.template or LATEST_TEMPLATE - - status = None - try: - statuses = cloudformation.describe_stacks(StackName=args.name)["Stacks"] - if len(statuses) == 1: - status = statuses[0] - _logger.debug(status) - except ClientError as e: - if "does not exist" not in str(e): - raise - - vpc_connect = args.vpc_connect - if status and not vpc_connect: - vpc_connect = "SecurityGroupId" in set(x["ParameterKey"] for x in status["Parameters"]) - - if vpc_connect: - PARAMS["SecurityGroupId"] = "security_group_id" - PARAMS["SubnetIds"] = "subnet_ids" - PARAMS["ElastiCacheClusterHost"] = "elasticache_cluster_host" - PARAMS["ElastiCacheClusterPort"] = "elasticache_cluster_port" - PARAMS["PostgresUrl"] = "postgres_url" - PARAMS["EnableBrainstore"] = "enable_brainstore" - PARAMS["BrainstoreInstanceKeyPairName"] = "brainstore_instance_key_pair_name" - PARAMS["BrainstoreLicenseKey"] = "brainstore_license_key" - PARAMS["BrainstoreInstanceType"] = "brainstore_instance_type" - PARAMS["BrainstoreInstanceCount"] = "brainstore_instance_count" - PARAMS["BrainstoreMaxInstanceCount"] = "brainstore_max_instance_count" - PARAMS["BrainstoreVersionOverride"] = "brainstore_version_override" - - if args.template is None: - template = "https://braintrust-cf.s3.amazonaws.com/braintrust-latest-vpc.yaml" - - exists = status is not None - if exists and args.create: - _logger.error( - textwrap.dedent( - f"""\ - Stack with name {args.name} already exists. Either delete it in the AWS console or - remove the --create flag.""" - ) - ) - exit(1) - elif not exists and not args.create: - _logger.error( - textwrap.dedent( - f"""\ - Stack with name {args.name} does not exist. Either create it manually by following - https://www.braintrust.dev/docs/admin/self-hosting/aws or use the --create flag.""" - ) - ) - exit(1) - - if not exists: - _logger.info(f"Creating stack with name {args.name}") - - params = [ - { - "ParameterKey": k, - "ParameterValue": str(v), - } - for (k, v) in [ - (param, args.__dict__[arg_name] or DEFAULTS.get(param, None)) for (param, arg_name) in PARAMS.items() - ] - if v is not None - ] - _logger.info("Using params:") - for param in params: - _logger.info(f" {param['ParameterKey']}: {param['ParameterValue']}") - - _logger.info(f"Typical stack creation takes 10-15 minutes.") - - cloudformation.create_stack( - StackName=args.name, - TemplateURL=template, - Parameters=params, - Capabilities=CAPABILITIES, - ) - - for _ in range(80): - status = cloudformation.describe_stacks(StackName=args.name)["Stacks"][0] - if status["StackStatus"] != "CREATE_IN_PROGRESS": - exists = True - break - _logger.info("Waiting for stack to be created...") - time.sleep(15) - else: - _logger.error( - textwrap.dedent( - """\ - Stack creation timed out. Please check the AWS console to see its status. You can also - re-run this command without --create to continue the setup process once it's done.""" - ) - ) - exit(1) - _logger.info(f"Stack with name {args.name} has been created with status: {status['StackStatus']}") - exit(0) - - _logger.info(f"Stack with name {args.name} has status: {status['StackStatus']}") - - if not ("_COMPLETE" in status["StackStatus"] or "_FAILED" in status["StackStatus"]): - _logger.info(f"Please re-run this command once the stack has finished creating or updating") - exit(0) - - # Update params that have changed - param_updates = {} - for param, arg_name in PARAMS.items(): - if args.__dict__[arg_name] is not None: - param_updates[param] = args.__dict__[arg_name] - if len(param_updates) > 0 or args.update_template: - template_kwargs = {"TemplateURL": template} if args.update_template else {"UsePreviousTemplate": True} - _logger.info(f"Updating stack with name {args.name} with template: {template_kwargs}") - - _logger.info("Using params:") - for param, value in param_updates.items(): - _logger.info(f" {param}: {value}") - - if args.template: - new_template = cloudformation.get_template_summary(TemplateURL=template) - new_params = set(x["ParameterKey"] for x in new_template["Parameters"]) - else: - new_params = set(x["ParameterKey"] for x in status["Parameters"]) - - stack = cloudformation.describe_stacks(StackName=args.name)["Stacks"][0] - try: - final_params = [ - {"ParameterKey": param, "ParameterValue": str(update)} - for (param, update) in param_updates.items() - if param in new_params and param not in REMOVED_PARAMS - ] + [ - {"ParameterKey": param["ParameterKey"], "UsePreviousValue": True} - for param in stack["Parameters"] - if param["ParameterKey"] not in param_updates - and param["ParameterKey"] not in REMOVED_PARAMS - and param["ParameterKey"] in new_params - ] - cloudformation.update_stack( - StackName=args.name, - Parameters=final_params, - Capabilities=CAPABILITIES, - **template_kwargs, - ) - except ClientError as e: - if "No updates are to be performed." in str(e): - _logger.warning("No updates are to be performed.") - else: - raise - - for _ in range(120): - status = cloudformation.describe_stacks(StackName=args.name)["Stacks"][0] - if status["StackStatus"] != "UPDATE_IN_PROGRESS": - exists = True - break - _logger.info("Waiting for stack to be updated...") - time.sleep(5) - else: - _logger.error( - textwrap.dedent( - """\ - Stack update timed out. Please check the AWS console to see its status. You can also - re-run this command to try again.""" - ) - ) - exit(1) - - universal_url = [x for x in status["Outputs"] if x["OutputKey"] == "UniversalURL"] - if universal_url: - universal_url = universal_url[0]["OutputValue"] - else: - universal_url = None - - org_name = [x for x in status["Parameters"] if x["ParameterKey"] == "OrgName"] - if org_name: - org_name = org_name[0]["ParameterValue"] - else: - org_name = None - - _logger.info(f"Stack with name {args.name} has been updated with status: {status['StackStatus']}") - _logger.info(f"Universal URL: {universal_url}") - - org_info = [] - if args.api_key: - login(api_key=args.api_key) - resp = app_conn().post("api/apikey/login") - if resp.ok: - org_info = resp.json()["org_info"] - else: - _logger.error(f"Failed to login with API key: {resp.text}") - - if len(org_info) > 0: - if org_name != "*": - org_info = [x for x in org_info if x["name"] == org_name] - if len(org_info) == 0: - _logger.error(f"Org with name {org_name} does not exist") - exit(1) - elif len(org_info) > 1: - names = ", ".join([x["name"] for x in org_info]) - _logger.error( - f"You belong to multiple orgs: {names}. Please use an API key that's scoped to a single org." - ) - org_info = [] - - if len(org_info) == 1: - org_info = org_info[0] - - if org_info and (universal_url and org_info["api_url"] != universal_url): - if args.update_stack_url: - _logger.info(f"Will update org {org_info['name']}'s urls.") - _logger.info(f" They are currently set to:") - _logger.info(f" API URL: {org_info['api_url']}") - _logger.info(f" Proxy URL: {org_info['proxy_url']}") - _logger.info(f"And will update them to:") - - patch_args = {"id": org_info["id"]} - if universal_url and org_info["api_url"] != universal_url: - patch_args["api_url"] = universal_url - patch_args["is_universal_api"] = True - _logger.info(f" API URL: {universal_url}") - _logger.warn( - f"\nNOTE: You can delete the proxy URL from your org settings now. It is no longer needed." - ) - - # Make the actual request - response_raise_for_status( - app_conn().post( - "api/organization/patch_id", - json=patch_args, - ) - ) - else: - _logger.info(f"Stack URL differs from organization API URL:") - _logger.info(f" Current API URL: {org_info['api_url']}") - _logger.info(f" Stack Universal URL: {universal_url}") - _logger.info(f"To update the organization's API URL, rerun with --update-stack-url flag") diff --git a/py/src/braintrust/cli/install/bump_versions.py b/py/src/braintrust/cli/install/bump_versions.py deleted file mode 100644 index e0954aa57..000000000 --- a/py/src/braintrust/cli/install/bump_versions.py +++ /dev/null @@ -1,40 +0,0 @@ -import logging - -# pylint: disable=no-name-in-module -from ...aws import LazyClient, cloudformation - -_logger = logging.getLogger("braintrust.install.logs") - - -def build_parser(subparsers, parents): - parser = subparsers.add_parser( - "bump-versions", help="Bump the version of each serverless function", parents=parents - ) - parser.add_argument("name", help="Name of the CloudFormation stack") - parser.set_defaults(func=main) - - -def main(args): - resources = cloudformation.describe_stack_resources(StackName=args.name) - lambda_ = LazyClient("lambda") - - # Then, publish the API handler lambdas just to bump their environment variable values - api_handler = [r for r in resources["StackResources"] if r["LogicalResourceId"] == "APIHandler"] - api_handler_js = [r for r in resources["StackResources"] if r["LogicalResourceId"] == "APIHandlerJS"] - proxy_handler = [r for r in resources["StackResources"] if r["LogicalResourceId"] == "AIProxyFn"] - - if not api_handler or not api_handler_js or not proxy_handler: - raise ValueError("No APIHandler, APIHandlerJS, or AIProxyFn found in the stack.") - - api_handler = api_handler[0] - api_handler_js = api_handler_js[0] - proxy_handler = proxy_handler[0] - - # Publish a new version of the API handler and re-point the "live2" alias to it - for resource, alias in [(api_handler, "live2"), (api_handler_js, "live"), (proxy_handler, "live")]: - new_version = lambda_.publish_version(FunctionName=resource["PhysicalResourceId"]) - lambda_.update_alias( - FunctionName=resource["PhysicalResourceId"], - Name=alias, - FunctionVersion=new_version["Version"], - ) diff --git a/py/src/braintrust/cli/install/logs.py b/py/src/braintrust/cli/install/logs.py deleted file mode 100644 index 3423c4c02..000000000 --- a/py/src/braintrust/cli/install/logs.py +++ /dev/null @@ -1,94 +0,0 @@ -import logging -import time -from concurrent.futures import ThreadPoolExecutor - -# pylint: disable=no-name-in-module -from ...aws import cloudformation, logs - -_logger = logging.getLogger("braintrust.install.logs") - - -def build_parser(subparsers, parents): - parser = subparsers.add_parser("logs", help="Capture recent logs", parents=parents) - parser.add_argument("name", help="Name of the CloudFormation stack to collect logs from") - parser.add_argument("--service", help="Name of the service", default="api", choices=["api", "brainstore", "all"]) - parser.add_argument("--hours", help="Number of hours in the past to collect logs from", default=1, type=float) - parser.set_defaults(func=main) - - -def main(args): - stacks = cloudformation.describe_stacks(StackName=args.name)["Stacks"] - if len(stacks) == 0: - raise ValueError(f"Stack with name {args.name} does not exist") - if len(stacks) > 1: - raise ValueError(f"Multiple stacks with name {args.name} exist") - stack = stacks[0] - _logger.debug(stack) - - if args.service == "all": - services = ["api", "brainstore"] - else: - services = [args.service] - - log_group_names = [] - for service in services: - if service == "api": - for name in ["APIHandlerJSName", "AIProxyFnName"]: - lambda_function = [x for x in stack["Outputs"] if x["OutputKey"] == name] - if len(lambda_function) > 1: - raise ValueError(f"Expected 1 APIHandlerName, found {len(lambda_function)} ({lambda_function}))") - if len(lambda_function) == 0: - _logger.warning(f"Could not find {name}, skipping...") - continue - log_group_names.append(f"/aws/lambda/{lambda_function[0]['OutputValue']}") - elif service == "brainstore": - log_group_names.append(f"/braintrust/{args.name}/brainstore") - - start_time = int(time.time() - 3600 * args.hours) * 1000 - - for log_group_name in log_group_names: - print(f"--- LOG GROUP: {log_group_name}") - - log_groups = logs.describe_log_groups(logGroupNamePrefix=log_group_name)["logGroups"] - if not any(group["logGroupName"] == log_group_name for group in log_groups): - print(f"Log group {log_group_name} does not exist") - continue - - all_streams = [] - first_start_time = None - nextToken = None - - while first_start_time is None or first_start_time >= start_time: - kwargs = {} - if nextToken is not None: - kwargs["nextToken"] = nextToken - - stream_resp = logs.describe_log_streams( - logGroupName=log_group_name, descending=True, orderBy="LastEventTime", **kwargs - ) - - first_start_time = min(s["firstEventTimestamp"] for s in stream_resp["logStreams"]) - nextToken = stream_resp.get("nextToken") - - streams = [s for s in stream_resp["logStreams"] if s["firstEventTimestamp"] >= start_time] - streams.sort(key=lambda x: x["firstEventTimestamp"]) - all_streams = streams + all_streams - - _logger.debug(all_streams) - - def get_events(stream): - return logs.get_log_events( - logGroupName=log_group_name, - logStreamName=stream["logStreamName"], - startTime=start_time, - startFromHead=True, - ) - - with ThreadPoolExecutor(8) as executor: - events = executor.map(get_events, all_streams) - - last_ts = None - for stream, log in zip(all_streams, events): - print(f"---- LOG STREAM: {stream['logStreamName']}") - for event in log["events"]: - print(event) diff --git a/py/src/braintrust/cli/install/redshift.py b/py/src/braintrust/cli/install/redshift.py deleted file mode 100644 index c30115916..000000000 --- a/py/src/braintrust/cli/install/redshift.py +++ /dev/null @@ -1,193 +0,0 @@ -import json -import logging -import re -from hashlib import md5 - -# pylint: disable=no-name-in-module -from ... import log_conn, login - -# pylint: disable=no-name-in-module -from ...aws import iam, redshift_serverless - -_logger = logging.getLogger("braintrust.install.redshift") - - -def build_parser(subparsers, parents): - parser = subparsers.add_parser( - "redshift", - help="Setup Redshift to ingest from Braintrust (Kafka)", - parents=parents, - ) - - parser.add_argument("name", help="Name of the Redshift cluster (or namespace) to create or update") - parser.add_argument( - "--create", - help="Create the Redshift instance if it does not exist", - action="store_true", - default=False, - ) - parser.add_argument( - "--serverless", - help="Use Serverless Redshift", - action="store_true", - default=False, - ) - parser.add_argument("--iam-role", help="IAM Role that can read from Kafka", default=None) - parser.add_argument( - "--iam-policy", - help="Inline IAM policy permitting access to Kafka", - default="BraintrustMSKReadPolicy", - ) - parser.add_argument( - "--msk-cluster-arn", - help="The ARN of a specific MSK cluster to allow access to. If this flag is unspecified, Redshift can read from any MSK cluster in this AWS account", - default=None, - required=True, - ) - parser.add_argument( - "--msk-topic-name", - help="The name of a specific MSK topic to map into Redshift. The policy will allow access to all topics in the cluster, to support future topics", - default="braintrust", - ) - - parser.add_argument( - "--org-name", - help="The name of your organization (optional, only needed if you belong to multiple orgs)", - ) - - parser.set_defaults(func=main) - - -def main(args): - if args.create: - raise NotImplementedError("Creating Redshift clusters is not yet supported") - - if args.msk_topic_name.lower() != args.msk_topic_name: - raise ValueError("Kafka topic names must be lowercase (b/c of Redshift case sensitivity issues)") - - role_name = args.iam_role or ("bt-redshift-" + md5(args.msk_cluster_arn.encode("utf-8")).hexdigest()) - role = None - try: - role = iam.get_role(RoleName=role_name) - except iam.exceptions.NoSuchEntityException: - pass - - if role is None: - _logger.info("Creating IAM Role %s", role_name) - role = iam.create_role( - RoleName=role_name, - AssumeRolePolicyDocument=json.dumps( - { - "Version": "2012-10-17", - "Statement": [ - { - "Effect": "Allow", - "Principal": {"Service": "redshift.amazonaws.com"}, - "Action": "sts:AssumeRole", - } - ], - } - ), - Description="Braintrust Redshift Kafka Reader", - ) - - role_policy = None - try: - role_policy = iam.get_role_policy(RoleName=role_name, PolicyName=args.iam_policy) - except iam.exceptions.NoSuchEntityException: - pass - - # See definitions here: https://docs.aws.amazon.com/msk/latest/developerguide/iam-access-control.html - msk_cluster_arn = args.msk_cluster_arn - account_info, path = msk_cluster_arn.rsplit(":", 1) - cluster_ident, cluster_name, cluster_uuid = path.split("/") - if cluster_ident != "cluster": - raise ValueError(f"Invalid MSK cluster ARN: {msk_cluster_arn}") - - # Allow access to all topics - msk_topic_arn = f"{account_info}:topic/{cluster_name}/{cluster_uuid}/*" - - if role_policy is None: - _logger.info(f"Creating inline IAM Policy {args.iam_policy} on {role_name}") - - policy = { - "Version": "2012-10-17", - "Statement": [ - { - "Sid": "MSKIAMpolicy", - "Effect": "Allow", - "Action": [ - "kafka-cluster:ReadData", - "kafka-cluster:DescribeTopic", - "kafka-cluster:Connect", - ], - "Resource": [ - msk_cluster_arn, - msk_topic_arn, - ], - }, - { - "Sid": "MSKPolicy", - "Effect": "Allow", - "Action": ["kafka:GetBootstrapBrokers"], - "Resource": "*", - }, - ], - } - role_policy = iam.put_role_policy( - RoleName=role_name, - PolicyName=args.iam_policy, - PolicyDocument=json.dumps(policy), - ) - - role_arn = role["Role"]["Arn"] - if args.serverless: - namespace = redshift_serverless.get_namespace(namespaceName=args.name) - if namespace is None: - raise ValueError(f"Serverless Redshift namespace {args.name} does not exist") - - existing_roles = [re.search(r"iamRoleArn=(.*)(,|\))", d).group(1) for d in namespace["namespace"]["iamRoles"]] - if role_arn not in existing_roles: - _logger.info( - "Adding IAM Role %s to Serverless Redshift namespace %s", - role_arn, - args.name, - ) - redshift_serverless.update_namespace(namespaceName=args.name, iamRoles=existing_roles + [role_arn]) - else: - raise NotImplementedError("Only Serverless Redshift is currently supported") - - # if args.serverless: - # workgroup = None - # next_token = {} - # while workgroup is None: - # workgroups = _redshift_serverless.list_workgroups(**next_token) - # for wg in workgroups["workgroups"]: - # if wg["namespaceName"] == args.name: - # workgroup = wg - # break - # - # if "nextToken" in workgroups: - # next_token = {"nextToken": workgroups["nextToken"]} - # else: - # break - # print(workgroup) - # - # def get_credentials(database=None): - # kwargs = {} - # if database: - # kwargs["dbName"] = database - # return _redshift_serverless.get_credentials(workgroupName=args.name, **kwargs) - # - # else: - # raise NotImplementedError("Only Serverless Redshift is currently supported") - - login_kwargs = {"org_name": args.org_name} if args.org_name else {} - login(**login_kwargs) - - resp = log_conn().get( - "/dw-test", - params={"iam_role": role["Role"]["Arn"], "msk_cluster_arn": msk_cluster_arn}, - ) - resp.raise_for_status() - _logger.info(f"Finished setting up Redshift: {resp.json()}") diff --git a/py/src/braintrust/cli/install/run_migrations.py b/py/src/braintrust/cli/install/run_migrations.py deleted file mode 100644 index 5235f7e99..000000000 --- a/py/src/braintrust/cli/install/run_migrations.py +++ /dev/null @@ -1,23 +0,0 @@ -import logging - -# pylint: disable=no-name-in-module -from ...aws import LazyClient, cloudformation - -_logger = logging.getLogger("braintrust.install.logs") - - -def build_parser(subparsers, parents): - parser = subparsers.add_parser("run-migrations", help="Run schema migrations", parents=parents) - parser.add_argument("name", help="Name of the CloudFormation stack") - parser.set_defaults(func=main) - - -def main(args): - resources = cloudformation.describe_stack_resources(StackName=args.name) - migration_lambda = [r for r in resources["StackResources"] if r["LogicalResourceId"] == "MigrateDatabaseFunction"] - if not migration_lambda: - raise ValueError("No MigrateDatabaseFunction found in the stack.") - migration_lambda = migration_lambda[0] - arn = migration_lambda["PhysicalResourceId"] - lambda_ = LazyClient("lambda") - lambda_.invoke(FunctionName=arn) diff --git a/py/src/braintrust/cli/push.py b/py/src/braintrust/cli/push.py deleted file mode 100644 index ff7af8d8a..000000000 --- a/py/src/braintrust/cli/push.py +++ /dev/null @@ -1,347 +0,0 @@ -"""Implements the braintrust push subcommand.""" - -import importlib.abc -import importlib.machinery -import importlib.metadata -import importlib.util -import inspect -import json -import os -import re -import subprocess -import sys -import tempfile -import textwrap -import zipfile -from typing import Any - -import requests -from braintrust.framework import _set_lazy_load - -from .. import api_conn, login, org_id, proxy_conn -from ..framework2 import ProjectIdCache, global_ -from ..generated_types import IfExists -from ..util import add_azure_blob_headers - - -def _pkg_install_arg(pkg) -> str | None: - try: - dist = importlib.metadata.distribution(pkg) - direct_url = dist._path / "direct_url.json" # type: ignore - if direct_url.exists(): - with open(direct_url) as f: - j = json.loads(f.read()) - if "url" in j: - return j["url"] - return f"{pkg}=={dist.version}" - except importlib.metadata.PackageNotFoundError as e: - print(f"Failed to find package {pkg}: {e}", file=sys.stderr) - return None - - -def _pydantic_to_json_schema(m): - if hasattr(m, "model_json_schema"): - # pydantic 2 - return m.model_json_schema() - # pydantic 1 - return m.schema() - - -def _check_uv(): - try: - import uv as _ # noqa: F401 # type: ignore[reportUnusedImport] - except ImportError: - raise ValueError( - textwrap.dedent( - f"""\ - The `uv` package is required to push to Braintrust. You can install it by including the - extra "cli" dependencies. Run: - - pip install 'braintrust[cli]' - - to install braintrust with the CLI dependencies (make sure to quote 'braintrust[cli]').""" - ), - ) - - -class _ProjectRootImporter(importlib.abc.MetaPathFinder): - """An importer that only resolves top-level modules from the project root and their submodules, - and collects the source files of all imported modules. - """ - - def __init__(self) -> None: - self._project_root, self._path_rest = sys.path[0], sys.path[1:] - self._sources = [] - - def _under_project_root(self, path: list[str]) -> bool: - """Returns true if all paths in `path` are under the project root.""" - return all(p.startswith(self._project_root) for p in path) - - def _under_rest(self, path: list[str]) -> bool: - """Returns true if any path in `path` is under one of the remaining paths in `sys.path`.""" - return any(p.startswith(pr) for p in path for pr in self._path_rest) - - def find_spec(self, fullname, path, target=None): - if path is None: - # Resolve top-level modules only from the project root. - path = [self._project_root] - elif not self._under_project_root(path) or self._under_rest(path): - # Defer paths that are not under the project root or covered by another sys.path entry - # to the subsequent importers. - return None - spec = importlib.machinery.PathFinder.find_spec(fullname, path, target) - if spec is not None and spec.origin is not None: - self._sources.append(spec.origin) - return spec - - def sources(self) -> list[str]: - return self._sources - - -def _import_module(name: str, path: str) -> list[str]: - """Imports the module and returns the list of source files - of all modules imported in the process. - - Args: - name: The fully qualified name of the module to import. - path: The absolute path to the module to import. - - Returns: - A list of absolute paths to source files of all modules imported in the process. - """ - importer = _ProjectRootImporter() - sys.meta_path.insert(0, importer) - - importlib.import_module(name) - return importer.sources() - - -def _py_version() -> str: - return f"{sys.version_info.major}.{sys.version_info.minor}" - - -def _run_install(install_args: list[str], packages_dir: str): - subprocess.run( - [ - "uv", - "pip", - "install", - *install_args, - "--target", - packages_dir, - "--python-platform", - os.environ.get("BRAINTRUST_INTERNAL_PY_BUNDLE_PLATFORM_OVERRIDE", "linux"), - "--python-version", - os.environ.get("BRAINTRUST_INTERNAL_PY_BUNDLE_VERSION_OVERRIDE", _py_version()), - ], - check=True, - ) - - -def _upload_bundle(entry_module_name: str, sources: list[str], requirements: str | None) -> str: - _check_uv() - - resp = proxy_conn().post_json( - "function/code", - { - "org_id": org_id(), - "runtime_context": { - "runtime": "python", - "version": _py_version(), - }, - }, - ) - bundle_upload_url = resp["url"] - bundle_id = resp["bundleId"] - - with tempfile.TemporaryDirectory() as td: - packages_dir = os.path.join(td, "pkg") - - # Though not strictly necessary, these packages should be those supported in the Python code editor - # with the exception of pydantic, which is necessary to allow the user to express function input schemas. - _run_install( - [ - arg - for arg in [ - _pkg_install_arg(pkg) - for pkg in [ - "pydantic", - "braintrust", - "autoevals", - "requests", - "openai", - ] - ] - if arg is not None - ], - packages_dir, - ) - if requirements: - # Overwrite any packages that are already installed. - _run_install(["--requirement", requirements], packages_dir) - - with zipfile.ZipFile( - os.path.join(td, "pkg.zip"), "w", compression=zipfile.ZIP_DEFLATED, compresslevel=9 - ) as zf: - for dirpath, dirnames, filenames in os.walk(packages_dir): - arcdirpath = os.path.relpath(dirpath, packages_dir) - arcdirpath = os.path.normpath(arcdirpath) - for name in sorted(dirnames): - path = os.path.join(dirpath, name) - arcname = os.path.join(arcdirpath, name) - zf.write(path, arcname) - for name in filenames: - path = os.path.join(dirpath, name) - path = os.path.normpath(path) - if os.path.isfile(path): - arcname = os.path.join(arcdirpath, name) - zf.write(path, arcname) - for source in sources: - zf.write(source, os.path.relpath(source)) - zf.writestr("register.py", f"import {entry_module_name} as _\n") - headers = {} - add_azure_blob_headers(headers, bundle_upload_url) - with open(os.path.join(td, "pkg.zip"), "rb") as zf: - requests.put( - bundle_upload_url, - data=zf.read(), - headers=headers, - ).raise_for_status() - - return bundle_id - - -def _collect_function_function_defs( - project_ids: ProjectIdCache, functions: list[dict[str, Any]], bundle_id: str, if_exists: IfExists -) -> None: - for i, f in enumerate(global_.functions): - source = inspect.getsource(f.handler) - if f.handler.__name__ == "": - m = re.search(r"handler\s*=\s*(.+)\s*[,)]", source) - if m is None: - raise ValueError(f"Failed to find handler for {f.name}") - source = m.group(1) - j = { - "project_id": project_ids.get(f.project), - "name": f.name, - "slug": f.slug, - "description": f.description, - "function_data": { - "type": "code", - "data": { - "type": "bundle", - "runtime_context": { - "runtime": "python", - "version": _py_version(), - }, - "location": { - "type": "function", - "index": i, - }, - "bundle_id": bundle_id, - "preview": source.strip(), - }, - }, - "function_type": f.type_, - "function_schema": { - "parameters": f.parameters, - "returns": f.returns, - }, - "if_exists": f.if_exists if f.if_exists else if_exists, - } - if f.metadata is not None: - j["metadata"] = f.metadata - if f.parameters is None: - raise ValueError(f"Function {f.name} has no supplied parameters") - j["function_schema"] = { - "parameters": _pydantic_to_json_schema(f.parameters), - } - if f.returns is not None: - j["function_schema"]["returns"] = _pydantic_to_json_schema(f.returns) - functions.append(j) - - -def _collect_prompt_function_defs( - project_ids: ProjectIdCache, functions: list[dict[str, Any]], if_exists: IfExists -) -> None: - for p in global_.prompts: - functions.append(p.to_function_definition(if_exists, project_ids)) - - -def run(args): - """Runs the braintrust push subcommand.""" - login( - api_key=args.api_key, - org_name=args.org_name, - app_url=args.app_url, - ) - - if sys.path[0] != os.getcwd(): - raise ValueError( - f"The current working directory ({os.getcwd()}) is not the project root. " - "Please run the push command from the project root." - ) - path = os.path.abspath(args.file) - module_name = re.sub(".py$", "", os.path.relpath(path).replace("-", "_").replace("/", ".")) - - try: - with _set_lazy_load(True): - sources = _import_module(module_name, path) - except ImportError as e: - if str(e) == "attempted relative import with no known parent package": - raise ImportError( - "Attempted to import a module using relative imports (e.g. from . import foo), but Python " - "cannot resolve these imports without a parent package. To fix this, either: " - "(1) combine all your code into a single file, or " - "(2) set up a proper Python package with an __init__.py file." - ) from e - raise - except Exception as e: - raise - - project_ids = ProjectIdCache() - functions: list[dict[str, Any]] = [] - if len(global_.functions) > 0: - bundle_id = _upload_bundle(module_name, sources, args.requirements) - _collect_function_function_defs(project_ids, functions, bundle_id, args.if_exists) - if len(global_.prompts) > 0: - _collect_prompt_function_defs(project_ids, functions, args.if_exists) - - if len(functions) > 0: - api_conn().post_json("insert-functions", {"functions": functions}) - else: - print("No functions found in the module. Nothing was pushed.", file=sys.stderr) - - -def build_parser(subparsers, parent_parser): - """Adds the parser for the push subcommand.""" - parser = subparsers.add_parser( - "push", - help="Push code to Braintrust", - parents=[parent_parser], - ) - parser.add_argument( - "--api-key", - help="Specify a Braintrust api key. If the parameter is not specified, the BRAINTRUST_API_KEY environment variable will be used.", - ) - parser.add_argument( - "--org-name", - help="The name of a specific organization to connect to. This is useful if you belong to multiple.", - ) - parser.add_argument( - "--app-url", - help="Specify a custom Braintrust app url. Defaults to https://www.braintrust.dev. This is only necessary if you are using an experimental version of Braintrust.", - ) - parser.add_argument( - "--if-exists", - default="error", - choices=["error", "replace", "ignore"], - help="What to do if a function with the same slug already exists. 'error' will cause an error and abort. 'replace' will overwrite the existing function. 'ignore' will ignore the push for this function and continue.", - ) - - parser.add_argument( - "file", - help="File to push.", - ) - parser.add_argument("--requirements", help="The requirements file to bundle dependencies from.") - parser.set_defaults(func=run) diff --git a/py/src/braintrust/conftest.py b/py/src/braintrust/conftest.py deleted file mode 100644 index 0a20821e9..000000000 --- a/py/src/braintrust/conftest.py +++ /dev/null @@ -1,156 +0,0 @@ -import os - -import pytest - - -def _patch_vcr_aiohttp_stubs(): - """Patch VCR.py's aiohttp stubs to fix bugs with google-genai >= 1.64.0. - - Problems fixed: - 1. Infinite loop: VCR's MockClientResponse.content is a @property that creates - a new MockStream on every access. google-genai reads streaming responses via - `while True: await response.content.readline()`, creating a fresh stream each - iteration that never reaches EOF. Fix: cache the stream per instance. - - 2. Gzip decoding: Cassettes store gzip-compressed response bodies (from - Accept-Encoding: gzip). VCR's httpx stubs handle decompression, but the - aiohttp stubs return raw gzip bytes, causing UnicodeDecodeError. - Fix: decompress gzip in text(), read(), and the content stream. - - 3. set_exception: aiohttp's close() sets a ClientConnectionError on the content - stream, which then raises on subsequent reads. Fix: no-op set_exception on - MockStream. - - See: https://github.com/kevin1024/vcrpy/issues/927 - """ - try: - from vcr.stubs import aiohttp_stubs - except ImportError: - return - - if getattr(aiohttp_stubs.MockClientResponse, "_bt_patched", False): - return - - import gzip - - def _decompress_body(body): - """Decompress gzip body if needed.""" - if body and body[:2] == b"\x1f\x8b": - return gzip.decompress(body) - return body - - aiohttp_stubs.MockStream.set_exception = lambda self, exc: None - - async def patched_text(self, encoding="utf-8", errors="strict"): - return _decompress_body(self._body).decode(encoding, errors=errors) - - aiohttp_stubs.MockClientResponse.text = patched_text - - async def patched_read(self): - return _decompress_body(self._body) - - aiohttp_stubs.MockClientResponse.read = patched_read - - @property - def cached_content(self): - if not hasattr(self, "_cached_content"): - stream = aiohttp_stubs.MockStream() - stream.feed_data(_decompress_body(self._body)) - stream.feed_eof() - self._cached_content = stream - return self._cached_content - - aiohttp_stubs.MockClientResponse.content = cached_content - aiohttp_stubs.MockClientResponse._bt_patched = True - - -_patch_vcr_aiohttp_stubs() - - -@pytest.fixture(autouse=True) -def override_app_url_for_tests(): - """ - Temporarily override BRAINTRUST_APP_URL to production URL for consistent test behavior. - - This fixture ensures that tests always use the production URL (https://www.braintrust.dev) - regardless of the local development environment settings. This prevents test failures - when BRAINTRUST_APP_URL is set to localhost for development. - """ - original_app_url = os.environ.get("BRAINTRUST_APP_URL") - original_app_public_url = os.environ.get("BRAINTRUST_APP_PUBLIC_URL") - - # Set to production URL for consistent test behavior - os.environ["BRAINTRUST_APP_URL"] = "https://www.braintrust.dev" - if "BRAINTRUST_APP_PUBLIC_URL" in os.environ: - del os.environ["BRAINTRUST_APP_PUBLIC_URL"] - - try: - yield - finally: - # Restore original environment variables - if original_app_url is not None: - os.environ["BRAINTRUST_APP_URL"] = original_app_url - elif "BRAINTRUST_APP_URL" in os.environ: - del os.environ["BRAINTRUST_APP_URL"] - - if original_app_public_url is not None: - os.environ["BRAINTRUST_APP_PUBLIC_URL"] = original_app_public_url - - -@pytest.fixture(autouse=True) -def setup_braintrust(): - os.environ.setdefault("GOOGLE_API_KEY", os.getenv("GEMINI_API_KEY", "your_google_api_key_here")) - os.environ.setdefault("OPENAI_API_KEY", "sk-test-dummy-api-key-for-vcr-tests") - - -@pytest.fixture(autouse=True) -def reset_braintrust_state(): - """Reset all Braintrust global state after each test.""" - yield - from braintrust import logger - - logger._state = logger.BraintrustState() - - -@pytest.fixture(autouse=True) -def skip_vcr_tests_in_wheel_mode(request): - """Skip VCR tests when running from an installed wheel. - - Wheel mode (BRAINTRUST_TESTING_WHEEL=1) is a pre-release sanity check - that verifies the built package installs and runs correctly. It's not - intended to be a full test suite - VCR cassettes are not included in - the wheel, so we skip those tests here. The full test suite with VCR - tests runs against source code during normal CI. - """ - if os.environ.get("BRAINTRUST_TESTING_WHEEL") == "1": - if request.node.get_closest_marker("vcr"): - pytest.skip("VCR tests skipped in wheel mode (pre-release sanity check only)") - - -def get_vcr_config(): - """ - Get VCR configuration for recording/playing back HTTP interactions. - - In CI, use "none" to fail if cassette is missing. - Locally, use "once" to record new cassettes if they don't exist. - """ - record_mode = "none" if (os.environ.get("CI") or os.environ.get("GITHUB_ACTIONS")) else "once" - return { - "record_mode": record_mode, - "decode_compressed_response": True, - "filter_headers": [ - "authorization", - "openai-organization", - "x-api-key", - "api-key", - "openai-api-key", - "x-goog-api-key", - "x-bt-auth-token", - ], - } - - -@pytest.fixture(scope="session") -def vcr_config(): - """Pytest fixture wrapper for get_vcr_config().""" - return get_vcr_config() diff --git a/py/src/braintrust/context.py b/py/src/braintrust/context.py deleted file mode 100644 index 0018f1a00..000000000 --- a/py/src/braintrust/context.py +++ /dev/null @@ -1,129 +0,0 @@ -"""Abstract context management interface for Braintrust.""" - -import logging -import os -from abc import ABC, abstractmethod -from contextvars import ContextVar -from dataclasses import dataclass -from typing import Any - - -@dataclass -class SpanInfo: - """Information about a span in the context.""" - - trace_id: str - span_id: str - span_object: Any = None - - -@dataclass -class ParentSpanIds: - root_span_id: str - span_parents: list[str] - - -class ContextManager(ABC): - """Abstract base class for managing span context in Braintrust. - - This provides a common interface for different context management - implementations (e.g., OTEL-based, native Braintrust, etc.). - """ - - @abstractmethod - def get_current_span_info(self) -> Any | None: - """Get information about the currently active span. - - Returns: - Information about the active span, or None if no span is active. - The format of the returned data depends on the implementation. - """ - pass - - @abstractmethod - def get_parent_span_ids(self) -> ParentSpanIds | None: - """Get parent span IDs for creating a new Braintrust span. - - Returns: - ParentSpanIds with root_span_id and span_parents if available, - None if no parent context exists. - """ - pass - - @abstractmethod - def set_current_span(self, span_object: Any) -> Any: - """Set the current active span. - - Args: - span_object: The span to set as current. Type depends on implementation. - - Returns: - Context token for cleanup, or None if no cleanup is needed. - """ - pass - - @abstractmethod - def unset_current_span(self, context_token: Any = None) -> None: - """Unset the current active span. - - Args: - context_token: Token returned by set_current_span for cleanup. - """ - pass - - -class BraintrustContextManager(ContextManager): - """Braintrust-only context manager using contextvars when OTEL is not available.""" - - def __init__(self): - self._current_span: ContextVar[Any | None] = ContextVar("braintrust_current_span", default=None) - - def get_current_span_info(self) -> SpanInfo | None: - """Get information about the currently active span.""" - current_span = self._current_span.get() - if not current_span: - return None - - # Return SpanInfo for BT spans - return SpanInfo(trace_id=current_span.root_span_id, span_id=current_span.span_id, span_object=current_span) - - def get_parent_span_ids(self) -> ParentSpanIds | None: - """Get parent information for creating a new Braintrust span.""" - current_span = self._current_span.get() - if not current_span: - return None - - # If current span is a BT span, use it as parent - return ParentSpanIds(root_span_id=current_span.root_span_id, span_parents=[current_span.span_id]) - - def set_current_span(self, span_object: Any) -> Any: - """Set the current active span.""" - return self._current_span.set(span_object) - - def unset_current_span(self, context_token: Any = None) -> None: - """Unset the current active span.""" - if context_token: - self._current_span.reset(context_token) - else: - self._current_span.set(None) - - -def get_context_manager() -> ContextManager: - """Get the appropriate context manager based on OTEL availability and configuration. - - Returns: - OTEL-based context manager if OTEL is explicitly enabled, - Braintrust-only context manager by default. - """ - - # Check if OTEL should be explicitly enabled via environment variable - if os.environ.get("BRAINTRUST_OTEL_COMPAT", "").lower() in ("1", "true", "yes"): - try: - from braintrust.otel.context import ContextManager as OtelContextManager - - return OtelContextManager() - except ImportError: - logging.warning("OTEL not available, falling back to Braintrust-only version") - - # Default to Braintrust-only context manager - return BraintrustContextManager() diff --git a/py/src/braintrust/contrib/__init__.py b/py/src/braintrust/contrib/__init__.py deleted file mode 100644 index 540795c50..000000000 --- a/py/src/braintrust/contrib/__init__.py +++ /dev/null @@ -1,5 +0,0 @@ -"""Braintrust contrib integrations. - -This module contains officially supported integrations with third-party frameworks. -These integrations are optional and require additional dependencies. -""" diff --git a/py/src/braintrust/contrib/temporal/__init__.py b/py/src/braintrust/contrib/temporal/__init__.py deleted file mode 100644 index 19cfc4ee5..000000000 --- a/py/src/braintrust/contrib/temporal/__init__.py +++ /dev/null @@ -1,440 +0,0 @@ -"""Braintrust integration for Temporal workflows and activities. - -This module provides Temporal integration that automatically traces workflow executions -and activities in Braintrust. To use this integration, install braintrust with the -temporal extra: - - pip install braintrust[temporal] - -Components ----------- - -There are two main components: - -- **BraintrustPlugin**: Use this for both Temporal clients and workers. It's a convenience - wrapper that automatically configures the interceptor and sandbox settings. - -- **BraintrustInterceptor**: The underlying interceptor. You can use this directly if you - need more control, but ``BraintrustPlugin`` is recommended for most use cases. - -Worker Setup ------------- - -Use ``BraintrustPlugin`` when creating a worker:: - - import braintrust - from braintrust.contrib.temporal import BraintrustPlugin - from temporalio.client import Client - from temporalio.worker import Worker - - braintrust.init_logger(project="my-project") - - client = await Client.connect("localhost:7233") - - worker = Worker( - client, - task_queue="my-queue", - workflows=[MyWorkflow], - activities=[my_activity], - plugins=[BraintrustPlugin()], - ) - - await worker.run() - -Client Setup ------------- - -Use ``BraintrustPlugin`` when creating a client to propagate span context to workflows:: - - import braintrust - from braintrust.contrib.temporal import BraintrustPlugin - from temporalio.client import Client - - braintrust.init_logger(project="my-project") - - client = await Client.connect( - "localhost:7233", - plugins=[BraintrustPlugin()], - ) - - # Spans created around workflow calls will be linked as parents - with braintrust.start_span(name="my-operation") as span: - result = await client.execute_workflow( - MyWorkflow.run, - args, - id="workflow-id", - task_queue="my-queue", - ) - -What Gets Traced ----------------- - -The integration will automatically: - -- Trace workflow executions -- Trace all activity executions -- Trace local activities -- Maintain parent-child relationships between client calls, workflows, and activities -- Handle child workflows -- Respect Temporal replay safety (no duplicate spans during replay) -""" - -import dataclasses -from collections.abc import Mapping -from typing import Any - -import braintrust -import temporalio.activity -import temporalio.api.common.v1 -import temporalio.client -import temporalio.converter -import temporalio.worker -import temporalio.workflow -from temporalio.plugin import SimplePlugin -from temporalio.worker import WorkflowRunner -from temporalio.worker.workflow_sandbox import SandboxedWorkflowRunner - -# Braintrust dynamically chooses its context implementation at runtime based on -# BRAINTRUST_OTEL_COMPAT environment variable. When first accessed, it reads -# os.environ which is restricted in the sandbox. Therefore if the first use -# is inside the sandbox, it will fail. So we eagerly reference it here to -# force initialization at import time (before sandbox evaluation). -try: - braintrust.current_span() -except Exception: - # It's okay if this fails (e.g., no logger initialized yet) - pass - -# Store module-level reference to braintrust.current_span to avoid re-importing -# inside extern functions (which can trigger sandbox restrictions) -_current_span = braintrust.current_span - -# Header key for passing span context between client, workflows, and activities -_HEADER_KEY = "_braintrust-span" - - -class BraintrustInterceptor(temporalio.client.Interceptor, temporalio.worker.Interceptor): - """Braintrust interceptor for tracing Temporal workflows and activities. - - This interceptor can be used with both Temporal clients and workers to automatically - trace workflow executions and activity runs. It maintains proper parent-child - relationships in the trace hierarchy and respects Temporal's replay safety requirements. - - The interceptor: - - Creates spans for workflow executions (using sandbox_unrestricted) - - Captures activity execution as spans with metadata - - Propagates span context from client โ†’ workflow โ†’ activities - - Handles both regular activities and local activities - - Supports child workflows - - Logs errors from failed activities and workflows - - Ensures replay safety (no duplicate spans during workflow replay) - """ - - def __init__(self, logger: Any | None = None) -> None: - """Initialize interceptor. - - Args: - logger: Optional background logger for testing. - """ - self.payload_converter = temporalio.converter.PayloadConverter.default - self._bg_logger = logger - # Capture logger instance at init time for cross-thread use - if logger: - braintrust.logger._state._override_bg_logger.logger = logger - self._logger = braintrust.current_logger() - - def _get_logger(self) -> Any | None: - """Get logger for creating spans. - - Sets thread-local override if background logger provided (for testing), - then returns captured logger instance. - """ - if self._bg_logger: - braintrust.logger._state._override_bg_logger.logger = self._bg_logger - return self._logger - - def intercept_client(self, next: temporalio.client.OutboundInterceptor) -> temporalio.client.OutboundInterceptor: - """Intercept client calls to propagate span context to workflows.""" - return _BraintrustClientOutboundInterceptor(next, self) - - def intercept_activity( - self, next: temporalio.worker.ActivityInboundInterceptor - ) -> temporalio.worker.ActivityInboundInterceptor: - """Intercept activity executions to create activity spans.""" - return _BraintrustActivityInboundInterceptor(next, self) - - def workflow_interceptor_class( - self, input: temporalio.worker.WorkflowInterceptorClassInput - ) -> type["BraintrustWorkflowInboundInterceptor"] | None: - """Return workflow interceptor class to propagate context to activities.""" - input.unsafe_extern_functions["__braintrust_get_logger"] = self._get_logger - return BraintrustWorkflowInboundInterceptor - - def _span_context_to_headers( - self, - span_context: dict[str, Any], - headers: Mapping[str, temporalio.api.common.v1.Payload], - ) -> Mapping[str, temporalio.api.common.v1.Payload]: - """Add span context to headers.""" - if span_context: - payloads = self.payload_converter.to_payloads([span_context]) - if payloads: - headers = { - **headers, - _HEADER_KEY: payloads[0], - } - return headers - - def _span_context_from_headers( - self, headers: Mapping[str, temporalio.api.common.v1.Payload] - ) -> dict[str, Any] | None: - """Extract span context from headers.""" - if _HEADER_KEY not in headers: - return None - header_payload = headers.get(_HEADER_KEY) - if not header_payload: - return None - payloads = self.payload_converter.from_payloads([header_payload]) - if not payloads: - return None - return payloads[0] if payloads[0] else None - - -class _BraintrustClientOutboundInterceptor(temporalio.client.OutboundInterceptor): - """Client interceptor that propagates span context to workflows.""" - - def __init__(self, next: temporalio.client.OutboundInterceptor, root: BraintrustInterceptor) -> None: - super().__init__(next) - self.root = root - - async def start_workflow( - self, input: temporalio.client.StartWorkflowInput - ) -> temporalio.client.WorkflowHandle[Any, Any]: - # Get current span context and add it to workflow headers - current_span = _current_span() - if current_span: - span_context = current_span.export() - input.headers = self.root._span_context_to_headers(span_context, input.headers) - - return await super().start_workflow(input) - - -class _BraintrustActivityInboundInterceptor(temporalio.worker.ActivityInboundInterceptor): - """Activity interceptor that creates spans for activity executions.""" - - def __init__( - self, - next: temporalio.worker.ActivityInboundInterceptor, - root: BraintrustInterceptor, - ) -> None: - super().__init__(next) - self.root = root - - async def execute_activity(self, input: temporalio.worker.ExecuteActivityInput) -> Any: - info = temporalio.activity.info() - - # Extract parent span context from headers - parent_span_context = self.root._span_context_from_headers(input.headers) - - logger = self.root._get_logger() - if not logger: - return await super().execute_activity(input) - - # Create Braintrust span for activity execution, linked to workflow span - span = logger.start_span( - name=f"temporal.activity.{info.activity_type}", - type="task", - parent=parent_span_context or None, - metadata={ - "temporal.activity_type": info.activity_type, - "temporal.activity_id": info.activity_id, - "temporal.workflow_id": info.workflow_id, - "temporal.workflow_run_id": info.workflow_run_id, - }, - ) - span.set_current() - - try: - result = await super().execute_activity(input) - return result - except Exception as e: - span.log(error=str(e)) - raise - finally: - span.unset_current() - span.end() - - -class BraintrustWorkflowInboundInterceptor(temporalio.worker.WorkflowInboundInterceptor): - """Workflow interceptor that creates workflow spans and propagates context to activities. - - This interceptor creates a span for the workflow execution using sandbox_unrestricted - to bypass Temporal's sandbox restrictions. The workflow span is the parent for all - activities and child workflows executed within it. - """ - - def __init__(self, next: temporalio.worker.WorkflowInboundInterceptor) -> None: - super().__init__(next) - self.payload_converter = temporalio.converter.PayloadConverter.default - self._parent_span_context: dict[str, Any] | None = None - - def init(self, outbound: temporalio.worker.WorkflowOutboundInterceptor) -> None: - super().init(_BraintrustWorkflowOutboundInterceptor(outbound, self)) - - async def execute_workflow(self, input: temporalio.worker.ExecuteWorkflowInput) -> Any: - # Extract parent span context from workflow headers (set by client) - parent_span_context = None - if _HEADER_KEY in input.headers: - header_payload = input.headers.get(_HEADER_KEY) - if header_payload: - payloads = self.payload_converter.from_payloads([header_payload]) - if payloads: - parent_span_context = payloads[0] - - # Store parent span context for activities (will be overwritten if we create a workflow span) - self._parent_span_context = parent_span_context - - # Create a span for the workflow execution using sandbox_unrestricted - # to bypass the sandbox restrictions on logger state access - span = None - if not temporalio.workflow.unsafe.is_replaying(): - with temporalio.workflow.unsafe.sandbox_unrestricted(): - # Get logger via extern function (supports test logger parameter) - get_logger = temporalio.workflow.extern_functions()["__braintrust_get_logger"] - logger = get_logger() - - if logger: - info = temporalio.workflow.info() - span = logger.start_span( - name=f"temporal.workflow.{info.workflow_type}", - type="task", - parent=parent_span_context or None, - metadata={ - "temporal.workflow_type": info.workflow_type, - "temporal.workflow_id": info.workflow_id, - "temporal.run_id": info.run_id, - }, - ) - span.set_current() - - # Update parent span context for activities - self._parent_span_context = span.export() - - try: - result = await super().execute_workflow(input) - return result - except Exception as e: - if span: - with temporalio.workflow.unsafe.sandbox_unrestricted(): - span.log(error=str(e)) - raise - finally: - if span: - with temporalio.workflow.unsafe.sandbox_unrestricted(): - span.unset_current() - span.end() - - -class _BraintrustWorkflowOutboundInterceptor(temporalio.worker.WorkflowOutboundInterceptor): - """Outbound workflow interceptor that propagates span context to activities.""" - - def __init__( - self, - next: temporalio.worker.WorkflowOutboundInterceptor, - root: BraintrustWorkflowInboundInterceptor, - ) -> None: - super().__init__(next) - self.root = root - - def _add_span_context_to_headers( - self, headers: Mapping[str, temporalio.api.common.v1.Payload] - ) -> Mapping[str, temporalio.api.common.v1.Payload]: - """Add parent span context to headers if available. - - Note: We always pass span context through headers, even during replay, - so activities can maintain proper parent-child relationships. The replay - safety is handled in the activity interceptor, which only creates spans - when the activity actually executes (not during replay). - """ - if self.root._parent_span_context: - payloads = self.root.payload_converter.to_payloads([self.root._parent_span_context]) - if payloads: - return {**headers, _HEADER_KEY: payloads[0]} - return headers - - def start_activity(self, input: temporalio.worker.StartActivityInput) -> temporalio.workflow.ActivityHandle: - input.headers = self._add_span_context_to_headers(input.headers) - return super().start_activity(input) - - def start_local_activity( - self, input: temporalio.worker.StartLocalActivityInput - ) -> temporalio.workflow.ActivityHandle: - input.headers = self._add_span_context_to_headers(input.headers) - return super().start_local_activity(input) - - def start_child_workflow( - self, input: temporalio.worker.StartChildWorkflowInput - ) -> temporalio.workflow.ChildWorkflowHandle: - input.headers = self._add_span_context_to_headers(input.headers) - return super().start_child_workflow(input) - - -def _modify_workflow_runner(existing: WorkflowRunner | None) -> WorkflowRunner | None: - """Add braintrust to sandbox passthrough modules.""" - if isinstance(existing, SandboxedWorkflowRunner): - new_restrictions = existing.restrictions.with_passthrough_modules("braintrust") - return dataclasses.replace(existing, restrictions=new_restrictions) - return existing - - -class BraintrustPlugin(SimplePlugin): - """Braintrust plugin for Temporal that automatically configures tracing. - - This plugin simplifies Braintrust integration with Temporal by: - - Automatically adding BraintrustInterceptor to the worker - - Configuring the sandbox to allow braintrust imports without unsafe.imports_passed_through() - - Example usage: - from braintrust.contrib.temporal import BraintrustPlugin - from temporalio.worker import Worker - - worker = Worker( - client, - task_queue="my-queue", - workflows=[MyWorkflow], - activities=[my_activity], - plugins=[BraintrustPlugin()], - ) - - Requires temporalio >= 1.19.0. - """ - - def __init__(self, logger: Any | None = None) -> None: - """Initialize the Braintrust plugin. - - Args: - logger: Optional background logger for testing. - """ - interceptor = BraintrustInterceptor(logger=logger) - import inspect - - params = inspect.signature(SimplePlugin.__init__).parameters - - # temporalio >= 1.23.0 merged client_interceptors/worker_interceptors - # into a single `interceptors` parameter. - if "interceptors" in params: - super().__init__( # pylint: disable=unexpected-keyword-arg - name="braintrust", - interceptors=[interceptor], - workflow_runner=_modify_workflow_runner, - ) - else: - super().__init__( - name="braintrust", - client_interceptors=[interceptor], - worker_interceptors=[interceptor], - workflow_runner=_modify_workflow_runner, - ) - - -__all__ = ["BraintrustInterceptor", "BraintrustPlugin"] diff --git a/py/src/braintrust/contrib/temporal/test_temporal.py b/py/src/braintrust/contrib/temporal/test_temporal.py deleted file mode 100644 index 5034612e3..000000000 --- a/py/src/braintrust/contrib/temporal/test_temporal.py +++ /dev/null @@ -1,507 +0,0 @@ -"""Unit tests for Braintrust Temporal interceptor.""" - -import asyncio -import uuid -from dataclasses import dataclass -from datetime import timedelta -from typing import Any, Dict - -import pytest -import pytest_asyncio - -pytest.importorskip("temporalio") - -import braintrust -import temporalio.activity -import temporalio.api.common.v1 -import temporalio.converter -import temporalio.testing -import temporalio.worker -import temporalio.workflow -from braintrust.contrib.temporal import BraintrustInterceptor, BraintrustPlugin -from braintrust.test_helpers import init_test_logger -from temporalio.common import RetryPolicy -from temporalio.worker import Worker - - -class TestHeaderSerialization: - """Unit tests for header serialization/deserialization.""" - - def test_span_context_to_headers_with_valid_context(self): - interceptor = BraintrustInterceptor() - span_context = {"trace_id": "test-trace-id", "span_id": "test-span-id"} - headers: Dict[str, temporalio.api.common.v1.Payload] = {} - - result_headers = interceptor._span_context_to_headers(span_context, headers) - - assert "_braintrust-span" in result_headers - assert len(result_headers) == 1 - - def test_span_context_to_headers_with_empty_context(self): - interceptor = BraintrustInterceptor() - span_context: Dict[str, Any] = {} - headers: Dict[str, temporalio.api.common.v1.Payload] = {} - - result_headers = interceptor._span_context_to_headers(span_context, headers) - - assert "_braintrust-span" not in result_headers - assert len(result_headers) == 0 - - def test_span_context_to_headers_preserves_existing_headers(self): - interceptor = BraintrustInterceptor() - span_context = {"trace_id": "test-trace-id"} - - # Create a payload for existing header - existing_payload = interceptor.payload_converter.to_payloads(["existing_value"])[0] - headers = {"existing_header": existing_payload} - - result_headers = interceptor._span_context_to_headers(span_context, headers) - - assert "existing_header" in result_headers - assert "_braintrust-span" in result_headers - assert len(result_headers) == 2 - - def test_span_context_from_headers_with_valid_header(self): - interceptor = BraintrustInterceptor() - span_context = {"trace_id": "test-trace-id", "span_id": "test-span-id"} - - # Serialize span context to header - payloads = interceptor.payload_converter.to_payloads([span_context]) - headers = {"_braintrust-span": payloads[0]} - - result = interceptor._span_context_from_headers(headers) - - assert result is not None - assert result["trace_id"] == "test-trace-id" - assert result["span_id"] == "test-span-id" - - def test_span_context_from_headers_with_missing_header(self): - interceptor = BraintrustInterceptor() - headers: Dict[str, temporalio.api.common.v1.Payload] = {} - - result = interceptor._span_context_from_headers(headers) - - assert result is None - - def test_span_context_roundtrip(self): - interceptor = BraintrustInterceptor() - original_context = { - "trace_id": "test-trace-id", - "span_id": "test-span-id", - "root_span_id": "test-root-span-id", - } - - # Serialize - headers = interceptor._span_context_to_headers(original_context, {}) - - # Deserialize - result_context = interceptor._span_context_from_headers(headers) - - assert result_context == original_context - - -# Integration Test Infrastructure - - -@dataclass -class TaskInput: - """Input for test activities and workflows.""" - - value: int - - -# Test Workflows and Activities - - -@temporalio.activity.defn -async def simple_activity(input: TaskInput) -> int: - """Simple test activity.""" - await asyncio.sleep(0.1) - return input.value + 10 - - -@temporalio.activity.defn -async def failing_activity(input: TaskInput) -> int: - """Activity that fails on first attempt.""" - info = temporalio.activity.info() - attempt = info.attempt - - if attempt == 1: - raise ValueError("Simulated failure on first attempt") - - return input.value + 20 - - -@temporalio.activity.defn -async def simple_local_activity(input: TaskInput) -> int: - """Simple local activity.""" - return input.value + 5 - - -@temporalio.workflow.defn -class TestWorkflow: - """Simple test workflow.""" - - @temporalio.workflow.run - async def run(self, input: TaskInput) -> int: - # Execute an activity - result = await temporalio.workflow.execute_activity( - simple_activity, - input, - start_to_close_timeout=timedelta(seconds=10), - ) - - return result - - -@temporalio.workflow.defn -class WorkflowWithRetry: - """Workflow that executes an activity with retries.""" - - @temporalio.workflow.run - async def run(self, input: TaskInput) -> int: - result = await temporalio.workflow.execute_activity( - failing_activity, - input, - start_to_close_timeout=timedelta(seconds=10), - retry_policy=RetryPolicy( - maximum_attempts=3, - initial_interval=timedelta(seconds=1), - ), - ) - - return result - - -@temporalio.workflow.defn -class WorkflowWithLocalActivity: - """Workflow that executes a local activity.""" - - @temporalio.workflow.run - async def run(self, input: TaskInput) -> int: - result = await temporalio.workflow.execute_local_activity( - simple_local_activity, - input, - start_to_close_timeout=timedelta(seconds=5), - ) - - return result - - -@temporalio.workflow.defn -class ChildWorkflow: - """Child workflow for testing child workflow tracing.""" - - @temporalio.workflow.run - async def run(self, input: TaskInput) -> int: - result = await temporalio.workflow.execute_activity( - simple_activity, - input, - start_to_close_timeout=timedelta(seconds=10), - ) - - return result - - -@temporalio.workflow.defn -class ParentWorkflow: - """Parent workflow that spawns a child workflow.""" - - @temporalio.workflow.run - async def run(self, input: TaskInput) -> int: - # Execute child workflow - child_result = await temporalio.workflow.execute_child_workflow( - ChildWorkflow.run, - input, - id=f"child-{temporalio.workflow.info().workflow_id}", - ) - - return child_result - - -# Integration Tests - - -@pytest_asyncio.fixture(scope="function") -async def temporal_env(): - """Create a Temporal test environment.""" - async with await temporalio.testing.WorkflowEnvironment.start_time_skipping() as env: - yield env - - -@pytest.fixture -def memory_logger(): - """Set up memory logger to capture spans for testing.""" - init_test_logger("temporal-test") - with braintrust.logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -class TestBraintrustPluginIntegration: - """Integration tests for BraintrustPlugin with real Temporal workflows.""" - - @pytest.mark.asyncio - async def test_plugin_basic_workflow_tracing(self, temporal_env, memory_logger): - """Test basic workflow and activity tracing with BraintrustPlugin. - - Verifies that: - 1. Braintrust can be imported directly in workflows (no unsafe.imports_passed_through) - 2. Spans are created for workflow execution - 3. Spans are created for activity execution - """ - # Create worker with BraintrustPlugin - async with Worker( - temporal_env.client, - task_queue="test-queue", - workflows=[TestWorkflow], - activities=[simple_activity], - plugins=[BraintrustPlugin(logger=memory_logger)], - ): - # Execute workflow - result = await temporal_env.client.execute_workflow( - TestWorkflow.run, - TaskInput(value=10), - id=f"test-workflow-{uuid.uuid4()}", - task_queue="test-queue", - ) - - # Verify workflow executed correctly - assert result == 20 # 10 + 10 from activity - - # Flush to ensure all spans are captured - braintrust.flush() - - # Get captured spans - spans = memory_logger.pop() - - # Verify spans were created - assert len(spans) > 0, f"Expected spans to be created, got {len(spans)} spans" - - # Verify workflow span was created - workflow_spans = [s for s in spans if "temporal.workflow" in s.get("span_attributes", {}).get("name", "")] - assert len(workflow_spans) > 0, ( - f"Expected workflow span to be created. Span names: {[s.get('span_attributes', {}).get('name', 'unknown') for s in spans]}" - ) - - # Verify activity span was created - activity_spans = [s for s in spans if "temporal.activity" in s.get("span_attributes", {}).get("name", "")] - assert len(activity_spans) > 0, ( - f"Expected activity span to be created. Span names: {[s.get('span_attributes', {}).get('name', 'unknown') for s in spans]}" - ) - - @pytest.mark.asyncio - async def test_plugin_context_propagation(self, temporal_env, memory_logger): - """Test that span context propagates from client to workflow to activity. - - Verifies that parent-child span relationships are maintained across - the execution chain. - """ - # Create a parent span at the client level - with braintrust.start_span(name="test.client_operation", type="task") as parent_span: - parent_context = parent_span.export() - - # Create worker with BraintrustPlugin - async with Worker( - temporal_env.client, - task_queue="test-queue-2", - workflows=[TestWorkflow], - activities=[simple_activity], - plugins=[BraintrustPlugin(logger=memory_logger)], - ): - # Execute workflow (context should propagate via headers) - result = await temporal_env.client.execute_workflow( - TestWorkflow.run, - TaskInput(value=15), - id=f"test-workflow-ctx-{uuid.uuid4()}", - task_queue="test-queue-2", - ) - - assert result == 25 # 15 + 10 - - # Get captured spans - spans = memory_logger.pop() - - # Verify spans were created - assert len(spans) > 0, "Expected spans to be created" - - # Verify client span exists - client_spans = [s for s in spans if "test.client_operation" in s.get("span_attributes", {}).get("name", "")] - assert len(client_spans) > 0, "Expected client span to be created" - - # Verify workflow and activity spans were created - workflow_spans = [s for s in spans if "temporal.workflow" in s.get("span_attributes", {}).get("name", "")] - activity_spans = [s for s in spans if "temporal.activity" in s.get("span_attributes", {}).get("name", "")] - - assert len(workflow_spans) > 0, "Expected workflow spans" - assert len(activity_spans) > 0, "Expected activity spans" - - @pytest.mark.asyncio - async def test_plugin_activity_retry_tracing(self, temporal_env, memory_logger): - """Test that activity retries are properly traced. - - Verifies that each retry attempt creates a span with appropriate - error information. - """ - async with Worker( - temporal_env.client, - task_queue="test-queue-3", - workflows=[WorkflowWithRetry], - activities=[failing_activity], - plugins=[BraintrustPlugin(logger=memory_logger)], - ): - # Execute workflow with failing activity - result = await temporal_env.client.execute_workflow( - WorkflowWithRetry.run, - TaskInput(value=30), - id=f"test-workflow-retry-{uuid.uuid4()}", - task_queue="test-queue-3", - ) - - # Should eventually succeed on retry - assert result == 50 # 30 + 20 - - # Get captured spans - spans = memory_logger.pop() - - # Verify spans were created - assert len(spans) > 0, "Expected spans to be created" - - # Verify activity spans (should have multiple attempts) - activity_spans = [s for s in spans if "temporal.activity" in s.get("span_attributes", {}).get("name", "")] - assert len(activity_spans) >= 1, "Expected at least one activity span for retries" - - @pytest.mark.asyncio - async def test_plugin_child_workflow_tracing(self, temporal_env, memory_logger): - """Test tracing of child workflows. - - Verifies that child workflows are traced and linked to parent workflows. - """ - async with Worker( - temporal_env.client, - task_queue="test-queue-4", - workflows=[ParentWorkflow, ChildWorkflow], - activities=[simple_activity], - plugins=[BraintrustPlugin(logger=memory_logger)], - ): - # Execute parent workflow which spawns child - result = await temporal_env.client.execute_workflow( - ParentWorkflow.run, - TaskInput(value=40), - id=f"test-workflow-parent-{uuid.uuid4()}", - task_queue="test-queue-4", - ) - - # Result should come from child workflow's activity - assert result == 50 # 40 + 10 - - # Get captured spans - spans = memory_logger.pop() - - # Verify spans were created - assert len(spans) > 0, "Expected spans to be created" - - # Verify both parent and child workflow spans - workflow_spans = [s for s in spans if "temporal.workflow" in s.get("span_attributes", {}).get("name", "")] - assert len(workflow_spans) >= 2, "Expected at least 2 workflow spans (parent and child)" - - # Verify activity span - activity_spans = [s for s in spans if "temporal.activity" in s.get("span_attributes", {}).get("name", "")] - assert len(activity_spans) > 0, "Expected activity spans" - - @pytest.mark.asyncio - async def test_plugin_local_activity_tracing(self, temporal_env, memory_logger): - """Test that local activities are traced correctly. - - Local activities execute in the same worker process and should - be traced like regular activities. - """ - async with Worker( - temporal_env.client, - task_queue="test-queue-5", - workflows=[WorkflowWithLocalActivity], - activities=[simple_local_activity], - plugins=[BraintrustPlugin(logger=memory_logger)], - ): - result = await temporal_env.client.execute_workflow( - WorkflowWithLocalActivity.run, - TaskInput(value=100), - id=f"test-workflow-local-{uuid.uuid4()}", - task_queue="test-queue-5", - ) - - assert result == 105 # 100 + 5 - - # Get captured spans - spans = memory_logger.pop() - - # Verify spans were created - assert len(spans) > 0, "Expected spans to be created" - - # Verify local activity span was created - activity_spans = [s for s in spans if "temporal.activity" in s.get("span_attributes", {}).get("name", "")] - assert len(activity_spans) > 0, "Expected local activity span to be created" - - @pytest.mark.asyncio - async def test_plugin_client_context_propagation(self, temporal_env, memory_logger): - """Test that BraintrustPlugin works with Client.connect for context propagation. - - Verifies that: - 1. Plugin can be passed to Client.connect (not just Worker) - 2. Client-side spans are linked to workflow/activity spans via headers - """ - from temporalio.client import Client - - # Create a NEW client with the plugin (simulates user doing Client.connect with plugin) - plugin = BraintrustPlugin(logger=memory_logger) - client = await Client.connect( - temporal_env.client.service_client.config.target_host, - namespace=temporal_env.client.namespace, - plugins=[plugin], - ) - - # Create worker (still needs plugin for worker-side tracing) - async with Worker( - client, - task_queue="test-queue-client-plugin", - workflows=[TestWorkflow], - activities=[simple_activity], - plugins=[BraintrustPlugin(logger=memory_logger)], - ): - # Create a parent span at the client level - with braintrust.start_span(name="test.client_with_plugin", type="task") as parent_span: - parent_context = parent_span.export() - - # Execute workflow - plugin should inject span context via client interceptor - result = await client.execute_workflow( - TestWorkflow.run, - TaskInput(value=25), - id=f"test-workflow-client-plugin-{uuid.uuid4()}", - task_queue="test-queue-client-plugin", - ) - - assert result == 35 # 25 + 10 - - # Get captured spans - spans = memory_logger.pop() - - # Verify spans were created - assert len(spans) > 0, "Expected spans to be created" - - # Verify client span exists - client_spans = [s for s in spans if "test.client_with_plugin" in s.get("span_attributes", {}).get("name", "")] - assert len(client_spans) > 0, "Expected client span to be created" - - # Verify workflow span was created and linked to client span - workflow_spans = [s for s in spans if "temporal.workflow" in s.get("span_attributes", {}).get("name", "")] - assert len(workflow_spans) > 0, "Expected workflow span to be created" - - # Verify activity span was created - activity_spans = [s for s in spans if "temporal.activity" in s.get("span_attributes", {}).get("name", "")] - assert len(activity_spans) > 0, "Expected activity span to be created" - - # Verify parent-child relationship: workflow should have client span as parent - workflow_span = workflow_spans[0] - client_span = client_spans[0] - assert workflow_span.get("root_span_id") == client_span.get("root_span_id"), ( - "Workflow span should be in same trace as client span" - ) diff --git a/py/src/braintrust/db_fields.py b/py/src/braintrust/db_fields.py deleted file mode 100644 index a89b97107..000000000 --- a/py/src/braintrust/db_fields.py +++ /dev/null @@ -1,27 +0,0 @@ -TRANSACTION_ID_FIELD = "_xact_id" -OBJECT_DELETE_FIELD = "_object_delete" -CREATED_FIELD = "created" -ID_FIELD = "id" - -IS_MERGE_FIELD = "_is_merge" -MERGE_PATHS_FIELD = "_merge_paths" -ARRAY_DELETE_FIELD = "_array_delete" - -AUDIT_SOURCE_FIELD = "_audit_source" -AUDIT_METADATA_FIELD = "_audit_metadata" -VALID_SOURCES = ["app", "api", "external"] - -PARENT_ID_FIELD = "_parent_id" - -ASYNC_SCORING_CONTROL_FIELD = "_async_scoring_control" -SKIP_ASYNC_SCORING_FIELD = "_skip_async_scoring" - -# Keys that identify which object (experiment, dataset, project logs, etc.) a row belongs to. -OBJECT_ID_KEYS = ( - "experiment_id", - "dataset_id", - "prompt_session_id", - "project_id", - "log_id", - "function_data", -) diff --git a/py/src/braintrust/devserver/__init__.py b/py/src/braintrust/devserver/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/py/src/braintrust/devserver/auth.py b/py/src/braintrust/devserver/auth.py deleted file mode 100644 index d1af03382..000000000 --- a/py/src/braintrust/devserver/auth.py +++ /dev/null @@ -1,83 +0,0 @@ -from collections.abc import Awaitable, Callable -from dataclasses import dataclass - -from starlette.middleware.base import BaseHTTPMiddleware -from starlette.requests import Request -from starlette.responses import JSONResponse, Response - -from ..logger import BraintrustState - -ORIGIN_HEADER = "origin" -BRAINTRUST_AUTH_TOKEN_HEADER = "x-bt-auth-token" -BRAINTRUST_ORG_NAME_HEADER = "x-bt-org-name" -BRAINTRUST_PROJECT_ID_HEADER = "x-bt-project-id" - - -@dataclass -class RequestContext: - app_origin: str | None - token: str | None - org_name: str | None - project_id: str | None - state: BraintrustState | None - - -def extract_allowed_origin(origin: str | None) -> str | None: - """Extract and validate the origin header.""" - # This should use the same check_origin logic from cors.py - from .cors import check_origin - - if origin and check_origin(origin): - return origin - return None - - -def parse_braintrust_auth_header(headers: dict[str, str]) -> str | None: - """Parse the authorization token from headers.""" - # Check x-bt-auth-token first - token = headers.get(BRAINTRUST_AUTH_TOKEN_HEADER) - if token: - return token - - # Check Authorization header - auth_header = headers.get("authorization") - if auth_header: - # Handle Bearer token format - if auth_header.lower().startswith("bearer "): - return auth_header[7:] # Remove "Bearer " prefix - return auth_header - - return None - - -class AuthorizationMiddleware(BaseHTTPMiddleware): - async def dispatch(self, request: Request, call_next: Callable[[Request], Awaitable[Response]]) -> Response: - try: - # Create context - ctx = RequestContext( - app_origin=extract_allowed_origin(request.headers.get(ORIGIN_HEADER)), - token=None, - org_name=request.headers.get(BRAINTRUST_ORG_NAME_HEADER), - project_id=request.headers.get(BRAINTRUST_PROJECT_ID_HEADER), - state=None, - ) - - # Extract token from headers - if "authorization" in request.headers or BRAINTRUST_AUTH_TOKEN_HEADER in request.headers: - token_text = parse_braintrust_auth_header(dict(request.headers)) - if not token_text: - return JSONResponse({"error": "Invalid authorization token format"}, status_code=400) - - # Handle "null" token - if token_text.lower() != "null": - ctx.token = token_text - - # Attach context to request state - request.state.ctx = ctx - - # Proceed to next middleware/handler - response = await call_next(request) - return response - - except Exception as e: - return JSONResponse({"error": str(e)}, status_code=500) diff --git a/py/src/braintrust/devserver/cache.py b/py/src/braintrust/devserver/cache.py deleted file mode 100644 index 60aa8f018..000000000 --- a/py/src/braintrust/devserver/cache.py +++ /dev/null @@ -1,53 +0,0 @@ -"""LRU cache implementation for the dev server.""" - -import json - -from ..logger import BraintrustState, login_to_state - - -class LRUCache: - """Simple LRU (Least Recently Used) cache implementation.""" - - def __init__(self, max_size: int = 32): - self.max_size = max_size - self.cache: dict[str, BraintrustState] = {} - self.access_order: list[str] = [] - - def get(self, key: str) -> BraintrustState | None: - """Get a value from the cache, updating access order.""" - if key in self.cache: - # Move to end to mark as recently used - self.access_order.remove(key) - self.access_order.append(key) - return self.cache[key] - return None - - def set(self, key: str, value: BraintrustState) -> None: - """Set a value in the cache, evicting LRU item if needed.""" - if key in self.cache: - # Update existing and move to end - self.access_order.remove(key) - elif len(self.cache) >= self.max_size: - # Remove least recently used - lru_key = self.access_order.pop(0) - del self.cache[lru_key] - - self.cache[key] = value - self.access_order.append(key) - - -# Global login cache -_login_cache = LRUCache(max_size=32) # TODO: Make this configurable - - -async def cached_login(api_key: str, app_url: str, org_name: str | None = None) -> BraintrustState: - """Login with caching to avoid repeated API calls.""" - cache_key = json.dumps({"api_key": api_key, "app_url": app_url, "org_name": org_name}) - - cached = _login_cache.get(cache_key) - if cached: - return cached - - state = login_to_state(api_key=api_key, app_url=app_url, org_name=org_name) - _login_cache.set(cache_key, state) - return state diff --git a/py/src/braintrust/devserver/cassettes/test_devserver_list_evaluators.yaml b/py/src/braintrust/devserver/cassettes/test_devserver_list_evaluators.yaml deleted file mode 100644 index f895c427b..000000000 --- a/py/src/braintrust/devserver/cassettes/test_devserver_list_evaluators.yaml +++ /dev/null @@ -1,105 +0,0 @@ -interactions: -- request: - body: null - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '0' - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://www.braintrust.dev/api/apikey/login - response: - body: - string: '{"org_info":[{"id":"5ba6d482-b475-4c66-8cd2-5815694764e3","name":"matt-test-org","api_url":"https://api.braintrust.dev","git_metadata":null,"is_universal_api":null,"proxy_url":"https://api.braintrust.dev","realtime_url":"wss://realtime.braintrustapi.com"}]}' - headers: - Access-Control-Allow-Credentials: - - 'true' - Access-Control-Allow-Headers: - - X-CSRF-Token, X-Requested-With, Accept, Accept-Version, Content-Length, Content-MD5, - Content-Type, Date, X-Api-Version - Access-Control-Allow-Methods: - - GET,OPTIONS,PATCH,DELETE,POST,PUT - Access-Control-Allow-Origin: - - '*' - Cache-Control: - - public, max-age=0, must-revalidate - Content-Length: - - '257' - Content-Security-Policy: - - 'script-src ''self'' ''unsafe-eval'' ''wasm-unsafe-eval'' ''strict-dynamic'' - ''nonce-OGUxYTg3ZTAtNDFiNy00ZTE5LWJjODAtMGVhYjk4OGZmNDlm'' *.js.stripe.com - js.stripe.com maps.googleapis.com ; style-src ''self'' ''unsafe-inline'' *.braintrust.dev - btcm6qilbbhv4yi1.public.blob.vercel-storage.com fonts.googleapis.com www.gstatic.com - d4tuoctqmanu0.cloudfront.net; font-src ''self'' data: fonts.gstatic.com btcm6qilbbhv4yi1.public.blob.vercel-storage.com; - object-src ''none''; base-uri ''self''; form-action ''self''; frame-ancestors - ''self''; worker-src ''self'' blob:; report-uri https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15; - report-to csp-endpoint-0' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 14:13:10 GMT - Etag: - - '"ubzjf1iqqj75"' - Reporting-Endpoints: - - csp-endpoint-0="https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15" - Server: - - Vercel - Strict-Transport-Security: - - max-age=63072000 - X-Clerk-Auth-Message: - - Invalid JWT form. A JWT consists of three parts separated by dots. (reason=token-invalid, - token-carrier=header) - X-Clerk-Auth-Reason: - - token-invalid - X-Clerk-Auth-Status: - - signed-out - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-Matched-Path: - - /api/apikey/login - X-Nonce: - - OGUxYTg3ZTAtNDFiNy00ZTE5LWJjODAtMGVhYjk4OGZmNDlm - X-Vercel-Cache: - - MISS - X-Vercel-Id: - - iad1::iad1::78nfv-1761833590850-bcfb530f403b - status: - code: 200 - message: OK -- request: - body: '' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - host: - - testserver - user-agent: - - testclient - x-bt-org-name: - - matt-test-org - method: GET - uri: http://testserver/list - response: - body: - string: '{"simple-math-eval":{"parameters":{},"scores":[{"name":"score_0"}]}}' - headers: - content-length: - - '68' - content-type: - - application/json - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/devserver/cassettes/test_eval_error_handling.yaml b/py/src/braintrust/devserver/cassettes/test_eval_error_handling.yaml deleted file mode 100644 index 740009695..000000000 --- a/py/src/braintrust/devserver/cassettes/test_eval_error_handling.yaml +++ /dev/null @@ -1,34 +0,0 @@ -interactions: -- request: - body: '{"name":"non-existent-eval","stream":false}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '43' - content-type: - - application/json - host: - - testserver - user-agent: - - testclient - x-bt-org-name: - - matt-test-org - method: POST - uri: http://testserver/eval - response: - body: - string: '{"error":"Evaluator ''non-existent-eval'' not found"}' - headers: - content-length: - - '51' - content-type: - - application/json - status: - code: 404 - message: Not Found -version: 1 diff --git a/py/src/braintrust/devserver/cassettes/test_eval_sse_streaming.yaml b/py/src/braintrust/devserver/cassettes/test_eval_sse_streaming.yaml deleted file mode 100644 index da436b543..000000000 --- a/py/src/braintrust/devserver/cassettes/test_eval_sse_streaming.yaml +++ /dev/null @@ -1,1177 +0,0 @@ -interactions: -- request: - body: null - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '0' - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://www.braintrust.dev/api/apikey/login - response: - body: - string: '{"org_info":[{"id":"5ba6d482-b475-4c66-8cd2-5815694764e3","name":"matt-test-org","api_url":"https://api.braintrust.dev","git_metadata":null,"is_universal_api":null,"proxy_url":"https://api.braintrust.dev","realtime_url":"wss://realtime.braintrustapi.com"}]}' - headers: - Access-Control-Allow-Credentials: - - 'true' - Access-Control-Allow-Headers: - - X-CSRF-Token, X-Requested-With, Accept, Accept-Version, Content-Length, Content-MD5, - Content-Type, Date, X-Api-Version - Access-Control-Allow-Methods: - - GET,OPTIONS,PATCH,DELETE,POST,PUT - Access-Control-Allow-Origin: - - '*' - Cache-Control: - - public, max-age=0, must-revalidate - Content-Length: - - '257' - Content-Security-Policy: - - 'script-src ''self'' ''unsafe-eval'' ''wasm-unsafe-eval'' ''strict-dynamic'' - ''nonce-OTM4YTEzMTQtNDFkNS00ZjRiLThiYmMtMGE1NGE2NjMyMjA4'' *.js.stripe.com - js.stripe.com maps.googleapis.com ; style-src ''self'' ''unsafe-inline'' *.braintrust.dev - btcm6qilbbhv4yi1.public.blob.vercel-storage.com fonts.googleapis.com www.gstatic.com - d4tuoctqmanu0.cloudfront.net; font-src ''self'' data: fonts.gstatic.com btcm6qilbbhv4yi1.public.blob.vercel-storage.com; - object-src ''none''; base-uri ''self''; form-action ''self''; frame-ancestors - ''self''; worker-src ''self'' blob:; report-uri https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15; - report-to csp-endpoint-0' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 15:14:52 GMT - Etag: - - '"ubzjf1iqqj75"' - Reporting-Endpoints: - - csp-endpoint-0="https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15" - Server: - - Vercel - Strict-Transport-Security: - - max-age=63072000 - X-Clerk-Auth-Message: - - Invalid JWT form. A JWT consists of three parts separated by dots. (reason=token-invalid, - token-carrier=header) - X-Clerk-Auth-Reason: - - token-invalid - X-Clerk-Auth-Status: - - signed-out - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-Matched-Path: - - /api/apikey/login - X-Nonce: - - OTM4YTEzMTQtNDFkNS00ZjRiLThiYmMtMGE1NGE2NjMyMjA4 - X-Vercel-Cache: - - MISS - X-Vercel-Id: - - iad1::iad1::56jrv-1761837292005-609120480622 - status: - code: 200 - message: OK -- request: - body: '{"project_name": "simple-math-eval", "project_id": null, "org_id": "5ba6d482-b475-4c66-8cd2-5815694764e3", - "update": false, "repo_info": {"commit": "38e569bb879b95a0ca322e2a576d7eb4aeb064cd", - "branch": "matt/re", "tag": null, "dirty": true, "author_name": "Matt Perpick", - "author_email": "matt@braintrustdata.com", "commit_message": "clean up debug - output", "commit_time": "2025-10-30T11:13:02-04:00", "git_diff": "diff --git - a/py/src/braintrust/devserver/test_server_integration.py b/py/src/braintrust/devserver/test_server_integration.py\nindex - 8171c20b8..f832cda1e 100644\n--- a/py/src/braintrust/devserver/test_server_integration.py\n+++ - b/py/src/braintrust/devserver/test_server_integration.py\n@@ -135,14 +135,16 - @@ def parse_sse_events(response_text: str) -> list[dict[str, Any]]:\n \n \n - @pytest.mark.vcr\n-def test_eval_sse_event_order(client, api_key, org_name):\n+def - test_eval_sse_streaming(client, api_key, org_name):\n \"\"\"\n- Test - that SSE events follow the correct order: start \u2192 progress* \u2192 summary - \u2192 done.\n-\n- This test verifies that the ''start'' event is always - the first event in the stream,\n- which is critical for the UI to properly - initialize and display progress.\n-\n- THIS TEST SHOULD FAIL before fixing - the race condition in on_start_fn.\n+ Comprehensive test for SSE streaming - during eval execution.\n+\n+ Verifies:\n+ 1. Event order: start \u2192 - progress* \u2192 summary \u2192 done\n+ 2. Progress events are emitted\n+ 3. - Start event has metadata (experimentName, projectName)\n+ 4. Summary event - has camelCase fields (not snake_case)\n+ 5. Response format is correct\n \"\"\"\n response - = client.post(\n \"/eval\",\n@@ -166,49 +168,37 @@ def test_eval_sse_event_order(client, - api_key, org_name):\n assert response.headers[\"Content-Type\"] == \"text/event-stream; - charset=utf-8\"\n \n events = parse_sse_events(response.text)\n-\n event_types - = [e[\"event\"] for e in events]\n \n+ # Verify event order\n assert - len(event_types) > 0, \"Should have at least one event\"\n assert event_types[0] - == \"start\", f\"First event should be ''start'', but got ''{event_types[0]}''\"\n assert - event_types[-1] == \"done\", f\"Last event should be ''done'', but got ''{event_types[-1]}''\"\n assert - \"summary\" in event_types, \"Should contain ''summary'' event\"\n \n- start_event - = next(e for e in events if e[\"event\"] == \"start\")\n- summary_event = - next(e for e in events if e[\"event\"] == \"summary\")\n+ # Verify progress - events exist\n+ progress_events = [e for e in events if e[\"event\"] == \"progress\"]\n+ assert - len(progress_events) > 0, \"Should emit progress events from task execution\"\n - \n- assert \"experimentName\" in start_event[\"data\"], \"Start event should - contain experiment metadata\"\n- assert \"projectName\" in start_event[\"data\"], - \"Start event should contain project name\"\n+ # Verify start event has metadata\n+ start_event - = next(e for e in events if e[\"event\"] == \"start\")\n+ assert \"experimentName\" - in start_event[\"data\"], \"Start event should contain experimentName\"\n+ assert - \"projectName\" in start_event[\"data\"], \"Start event should contain projectName\"\n - \n- # Summary event data can be None in some cases, but it should be present\n+ # - Verify summary event has camelCase fields\n+ summary_event = next(e for e - in events if e[\"event\"] == \"summary\")\n assert summary_event is not - None, \"Summary event should be present\"\n+ summary_data = summary_event[\"data\"]\n+ assert - summary_data is not None, \"Summary event data should not be None\"\n \n+ # - UI expects camelCase field names\n+ assert \"experimentName\" in summary_data, - \"Summary should have ''experimentName'' (camelCase)\"\n+ assert \"projectName\" - in summary_data, \"Summary should have ''projectName'' (camelCase)\"\n+ assert - \"scores\" in summary_data, \"Summary should have ''scores'' field\"\n \n-@pytest.mark.vcr\n-def - test_eval_sse_progress_events(client, api_key, org_name):\n- \"\"\"Test that - progress events are emitted during streaming.\"\"\"\n- response = client.post(\n- \"/eval\",\n- headers={\n- \"x-bt-auth-token\": - api_key,\n- \"x-bt-org-name\": org_name,\n- \"Content-Type\": - \"application/json\",\n- \"Accept\": \"text/event-stream\",\n- },\n- json={\n- \"name\": - \"simple-math-eval\",\n- \"stream\": True,\n- \"data\": - [\n- {\"input\": \"What is 2+2?\", \"expected\": \"4\"},\n- {\"input\": - \"What is 3+3?\", \"expected\": \"6\"},\n- ],\n- },\n- )\n-\n- events - = parse_sse_events(response.text)\n- progress_events = [e for e in events - if e[\"event\"] == \"progress\"]\n-\n- assert len(progress_events) > 0, \"Should - emit progress events from task execution\"\n+ # Should NOT have snake_case - fields\n+ assert \"experiment_name\" not in summary_data, \"Summary should - not have snake_case ''experiment_name''\"\n+ assert \"project_name\" not - in summary_data, \"Summary should not have snake_case ''project_name''\"\n \n - \n @pytest.mark.vcr\n@@ -230,98 +220,6 @@ def test_eval_error_handling(client, - api_key, org_name):\n assert \"not found\" in error[\"error\"].lower()\n - \n \n-@pytest.mark.vcr\n-def test_sse_message_format_matches_typescript(client, - api_key, org_name):\n- \"\"\"\n- Test that Python sends SSE messages in - the exact same format as TypeScript.\n-\n- This test captures the raw SSE - response and verifies:\n- 1. All events are present: start, progress*, summary, - done\n- 2. Each event has the correct format: \"event: \\\\ndata: \\\\n\\\\n\"\n- 3. - The summary event has camelCase fields\n- 4. The done event properly terminates - the stream\n- \"\"\"\n- response = client.post(\n- \"/eval\",\n- headers={\n- \"x-bt-auth-token\": - api_key,\n- \"x-bt-org-name\": org_name,\n- \"Content-Type\": - \"application/json\",\n- \"Accept\": \"text/event-stream\",\n- },\n- json={\n- \"name\": - \"simple-math-eval\",\n- \"stream\": True,\n- \"data\": - [\n- {\"input\": \"What is 2+2?\", \"expected\": \"4\"},\n- ],\n- },\n- )\n-\n- assert - response.status_code == 200\n-\n- events = parse_sse_events(response.text)\n- event_types - = [e[\"event\"] for e in events]\n-\n- # Verify event sequence\n- assert - event_types[0] == \"start\", f\"First event should be ''start'', got {event_types[0]}\"\n- assert - event_types[-1] == \"done\", f\"Last event should be ''done'', got {event_types[-1]}\"\n- assert - \"summary\" in event_types, \"Should have summary event\"\n-\n- # Verify - summary has camelCase fields\n- summary_event = next(e for e in events if - e[\"event\"] == \"summary\")\n- assert summary_event[\"data\"] is not None, - \"Summary data should not be None\"\n- assert \"experimentName\" in summary_event[\"data\"], - \"Summary should have camelCase experimentName\"\n- assert \"projectName\" - in summary_event[\"data\"], \"Summary should have camelCase projectName\"\n-\n-\n-@pytest.mark.vcr\n-def - test_summary_event_has_camelcase_fields(client, api_key, org_name):\n- \"\"\"\n- Test - that the summary event contains camelCase fields as expected by the UI.\n-\n- This - is critical because the UI expects camelCase field names like ''experimentName'',\n- ''projectName'', - etc. If the fields are in snake_case, the UI cannot parse them and\n- the - experiment will appear stuck in \"streaming...\" state.\n-\n- THIS TEST SHOULD - FAIL before fixing the format_summary call in server.py.\n- \"\"\"\n- response - = client.post(\n- \"/eval\",\n- headers={\n- \"x-bt-auth-token\": - api_key,\n- \"x-bt-org-name\": org_name,\n- \"Content-Type\": - \"application/json\",\n- \"Accept\": \"text/event-stream\",\n- },\n- json={\n- \"name\": - \"simple-math-eval\",\n- \"stream\": True,\n- \"data\": - [\n- {\"input\": \"What is 2+2?\", \"expected\": \"4\"},\n- ],\n- },\n- )\n-\n- assert - response.status_code == 200\n- events = parse_sse_events(response.text)\n-\n- summary_event - = next((e for e in events if e[\"event\"] == \"summary\"), None)\n- assert - summary_event is not None, \"Should have a summary event\"\n-\n- summary_data - = summary_event[\"data\"]\n- assert summary_data is not None, \"Summary event - data should not be None\"\n-\n- # The UI expects camelCase field names\n- assert - \"experimentName\" in summary_data, \"Summary should have ''experimentName'' - (camelCase)\"\n- assert \"projectName\" in summary_data, \"Summary should - have ''projectName'' (camelCase)\"\n- assert \"scores\" in summary_data, - \"Summary should have ''scores'' field\"\n-\n- # Should NOT have snake_case - fields\n- assert \"experiment_name\" not in summary_data, \"Summary should - not have snake_case ''experiment_name''\"\n- assert \"project_name\" not - in summary_data, \"Summary should not have snake_case ''project_name''\"\n-\n-\n - @pytest.mark.vcr\n def test_eval_with_dataset_id_completes_successfully(client, - api_key, org_name):\n \"\"\""}, "ancestor_commits": ["6d2dc1e53a6d16b466ef449fd8e14ebd3fa20f00", - "a4dfb710896797d1ec1cab191e39cc51eba18b4d", "0f51f6ef36ba16737589cab11ea2dd1742671c41", - "fa85adab7bc82c5d14250a988664e0f65d23643a", "2d8afda70e0f82176d7ee80bcb653ed09d4ada76", - "17b618dbe38d1374435496778d3cbd0f3d3720a9", "6116c86a6188a345cb430e55b48e660009a85799", - "479f00719a1c04acda05bc52e8198c76b17b767b", "41b9555dd4375ea0df23a0a6a2333f7f4d9e626e", - "c3a3634129a36fb09c4b79e737582e33bd2a058b", "7b1f9abab1067273355a38909e102fd2d3a5323c", - "2cbf3503536ba11f94a975fc0c547529315caa9d", "4aa4133193a8e8c3fdc766208be7bffb4983bae5", - "436fe5351a1bc91413e903a2d2cbf2a8559a3c5f", "c033d7aed97d788aa88220df3c8cb72fbe1ab96f", - "f11265286454e2059d0de2a82ee4356601552bd2", "f8c91c4de5c8d19881c4f8b0461bc1f8bfd01d94", - "25912cd765f1ca1e19486411fb3de9963fd9f925", "1026cbd8af888621a402e114a1c58c14da41bb72", - "1cf1bf68a47746b2d23e4211c03a4b81e9626d10", "c5980aae60fc5c3577e241a70c0798d8397e6a07", - "9e4f93daa40369d2cdb97bfb01ee8c93bf23ec80", "2b61d410af69dcfe59d11337df54412a7ed495b7", - "d9dc67568e7a7147ea23e42083d2cb8632bdbe6c", "21bb8edd05cc9d1142fabd4aba808d6a8157f4df", - "258e8ec05412a73bb0a9e916db941c7af1b3e959", "98ca8e2ec4264fb7c6a3a733c455f8d0ea089b07", - "d6cc3a68587ba633190b18c083b7d56747b7a19d", "3525059c8b3d3fadcff6f592c0e2ded7fc06294b", - "e01077c19252f97215f6ed141d485f877506282f", "8a4eb9ac7b33af6ffe3e980c685c290a68c93ca1", - "567acfb3e9e9fda2c4051c038c6621bdb47ec823", "675e293cfa98252cef4d8b7980066b038a901d04", - "11e271cd1a3df6c75449e0c51a21a6c3b3d3fe22", "ce4101fb55325aca6989ccfaebfa9992421c9e2b", - "8e0211657949932ce0ed8da68e72b5c5981fc8f5", "fa016eff3df324a5ff9f3d43d324a01177ec8939", - "6f4426eac2c30baf20e09b51c5369156eff7abc1", "2040109acbd819ebfa776fc97631815b122aa7d4", - "30a65a2a2ce03eec847aa822f722a0d2f0f993bd", "2f320a37a7ef0d32ae4fceb09057b1491eb1fc32", - "25e7a079b6717ffd08ffbda3254fddb072160d82", "146489482d21d37e7297d3b085ba786409e328a3", - "555e44e3d20abf44db5780cc7fc8c95ae5593239", "26b2a34cca8cf71e092eb3e7b02e53b88e6c03a5", - "d6278e852f56fdb00ee5b9d97226be1589853166", "5c61d67a3f8068020979f09c9f7be11f56e95c2a", - "e0647fd778205f62b1956e5320f682af61fbf5ca", "5d55b31e47053325b4a345c445c62413aa69177c", - "a71670f60bd64ceec2b68fc07608d4ef05277ad5", "e6751654101127f666768dfecd42fe9c6e0b47e3", - "a45fabb93b9405dd04d2d944fef78dc424361698", "5f31e95c53879bdcb5bd47276a8aff25673655d8", - "fe3f9a83f7db420747f402841d25dd73f8b36d30", "70dec2f04b7567d45d5a85b77c959623eefcfad2", - "042f91e4b2b8067e6b672816182ba9ae2465812a", "6e7aef5b4b4c6cf84ce51a4d8b947eda306a26b5", - "3f01a409a7ecc34e825e8532e56d04613397cd13", "893a546da4fd221501d3c865c7bf1d16ce9d933e", - "f5410073902240fb94b50c30506aa02dbf9a1517", "722657b05ed625309450f4f33953d7a694a1a414", - "691d303ce7356e544cbfae5ad8054454c0f69652", "a6f5a8bb856a84214811cd2b259edf0a30c6144f", - "aba9adfef223a27e9ebee5f1e5896763adc71641", "500c2fddb600fcbe7a7d8a48d4e1fe7c3bdcfea7", - "ce957df3478f5f95b668a0dfc87956da190d74a6", "3548dc0a4e272b21330ceefe9c8c63517941c034", - "b252d68c0dc7bc599474380a7a185b9c5a9a5fb6", "c2bcdec50527d1153a73a5e191d7bb4ab1f4a5f3", - "552e48c600134179ece0d1aabd13d17f124338be", "1a18ac6ef2f20cb3434d1db59bf4ae4c3a1f715d", - "ad99dac6002a2975e445e8dc90f5d93c53991fdb", "04f8a3f464061a9dba2d1c00dd7940488720974a", - "b8c2d1ebc7b75ea604e9490fd265a6f797add415", "4bf10cf4435ff85c7c3e2f50e7790b2eaa8861a4", - "66091f34bf277d5491477085551afc1a8a361a0f", "f7e1f2ac9f1767984bd125184f8b87563f249bfd", - "61a1c51b48f7b278c73c13efeba86aa2484a33b5", "3f54176089005fb6dc4b252b4dce34370ea8bcc6", - "ff6f45ce65c0b32578fb92f842f123581413dfe9", "6163138faeabb67eb3ef1b97d6a4b08a5c45caa9", - "64cf4c6299cadfe4e5a7987c8db3383a69a108b9", "e98267285f704dd8232dcfffc09616ffeda896fd", - "61d4167d00783621e8a830f267b799b8f22969b1", "12551cea0f20963404d37821d889c7b397ce29ba", - "9aa042227f5625364418d20187dc76508c5c32fb", "8213aad94904430b8165119337da1243fa7a88ab", - "e8c47b170edc02abda540037fb4752ef03a21849", "59a6092a06c163dfb2fa1deea179cd84a5e91083", - "db2b8564a0ed5193a70c607f23e575c8f023454a", "12048f9a795a901cab215f869b185d6e46e2a1e9", - "98cd9913a99020f97a98297a8f085881e8ff21b7", "76c1d436b2fba46a7ac7b7d285ee4b5e3a6660fa", - "cb1c08bc56644e993505a2ab863c18ebc8a35cd2", "f532f53f82e2fbd789b654ddd6eebe181c12d5ab", - "1aaa6ce090e25893b7b8b46cc99fe8344eec653d", "83d4ec39274f91989811f845c6fe805544bfa0ab", - "0152b43193700d54d9826709132ac2bcb9ce5975", "57291a113482eb4277f43c414b09afcb1bf8f0b7", - "3d5ec4de453ab8ea873a6c8c0d0ef0b2110bd386", "4168c8645f251d9584b25c5a57ccb089178a98a1", - "0dafcc9a1aba7282e98d653730b496d83ba13c16", "e45a7da9aba5144429cb9019acf99dc668ddadd5", - "0844207c03327225f9913cc4b1a8702330841a96", "329121933af05b575eee9c77bf13b9a4d3443dde", - "4793325d739b2d9d0deb39d1118e33d76202e7a3", "517ce4da9248bbbf77c7c9f9226054bc5412176b", - "b9ec5a7fe95a0c7e32d65901da5d33ab8c30c779", "cae143cbf533885d8bf978f287e9383bea46c3e6", - "e2df632753bc6545d94b6f4c76af47a81ea3542b", "eb3dcb724dfd1cc85e30594a63839ebd46c8a5a8", - "c459f75f02d0c3444baef25d6fd228ce2929f924", "b98731f2971b9ac5d0acda62cfb2cc32c141dc37", - "6b1c69123acb73fd0cc23393bb165e99bab2508c", "50159c19f26b9c1433e50f388b3fa759c92c0ff0", - "08715a5559a18ec189f91421618e534344f342a0", "2d4792e23d4104e5a89c17bf2195c7a8aded89a2", - "27eb88f965e9d3df3a1cf219db7883093f339676", "ee2acbc913cb75dccb8d1bb124b074bacae27ee1", - "d9a2df31b1ff1ea6796a25558771ed1a38e6d1f9", "b0c3bc7c96cd65435e9ff6b88040799959041972", - "c340893e4dfd3cbeb4566cec5e8cd9a24c9982d5", "cd361d820e14ee59bd8daa6bbe3321cc7d4fa436", - "89c6916d89c4fec3cbe1ee6c780358cf51ba87e2", "262aed06bd219cbfbb4e91c0fbdfb606883f74cd", - "e32b82fabd2f29cdc9ac9e8b33966b10f8a0ce18", "1e3688e139a11ce21f3a9e5c74d176c1ace5cd38", - "b460d264e4ecde414ddb70e918a1adb48ae610b7", "41bee95c0185b6c2521073565e11ede0885a7e8a", - "22bfb85e284a90cf37d23354f56786941de27a99", "59c7f2256d0b342d1cc08eeb3f4dd9c7e61e90f7", - "6f791793df1d1124936ad53e9948cd221a184aec", "e5c3b79336ede6948f3302d60de0fb8a1b7a138c", - "666d1b61ab34647db7ab8e617a9497b87166d7e8", "4d8966bad69bca5970ce0ed64c343fac0e1cf698", - "852bc11787bae1ac6f99622dffc2eea32ef121e8", "2b3067a1dfe1648d1e9be9f54f8e3af5ee9cbc3b", - "1a001a96c0fd88b7884b9049a6d47f6ec4d086b3", "740106ef9e67ae17393d081580f5c1493db372a1", - "05e0f5184a2a0c6a003dd1654bdb4d1da4b1a847", "8eeb1017e6f043e43d6eaaa99d2aec62d2aa2776", - "1e34543f322aa94c5f5e679cc8713120002bee0c", "d253a3c83f3a062f0a18220bdec2188a2445f2ff", - "2548241b69cdc856b24ed8fe930ee5a608348b8c", "47c83b2f5b8cc63496aa507f03babde7e79c730c", - "1169d83904da1f140c52a51748d1f9920cadc304", "2551edd52b168e0691cbc4a16b6f9762c42a2ee8", - "b07d82b7fe426edc3ea57eca2e54dd1a7865e61d", "fe52db5b57808551b30af34184e5f11fb12a1a69", - "2b29dbd15c15e138057630527d19a67d9ea9198a", "5cbc7715b58ac8a9d141cf95813149a09d7f323c", - "918ea978ecc68b7f3ed541b7ed1e073848bf06f3", "af49d808446f40d37d64c66517a45cc19a78de32", - "f2fb962dacc2a7f1b1a9a075611e300970463a1e", "a0ac9637dbc9b7b4af6d37256011e8e777379cb6", - "3fefc0572263475219c149f4c54fe1b88f23c7e7", "f227977b57b78fecd2db13ff2b231d0c22a3b274", - "7e4c8a38b0fd82cc80df79b1daec14c1cdb58be8", "ad3269310aba337feac5712f9621a5b8ffdb29b8", - "4ad90d121a48a0390744035a7bc068f885abcf89", "134fe22aeae849409671acc32e13a17a69681569", - "4e0adb75d47a88366da89405264d87d88cf358c1", "f1252436b3427e8fe87ea9ac07829f977ea12752", - "0679d7794f638bc86e47ecf8e49b70482281c20c", "c06dbe314d1f44c63b8bfe6edadef6ebf5c5ff20", - "ad6e8fa9bbbe6f40621a826662b858c96eff4057", "9756e3372243fd818c895910aa53f4148798b7a8", - "dbb3e71028ba0573b07f6a39bee4a4ff7f39c486", "6aaf30534ead2af6285ed5f3ff12f3680f401066", - "5f7f1c1613ed4d17875a6d845e8cffd3fc0b0059", "7c1432135a24132618b786ace67238029bec8591", - "76290595b414a9c7ec3bf3cf5fa6ad32920d32bd", "97d4988c8ccfb194a7d01d2c427e6796ed36c5e1", - "344fbf8c2cab7917197614e4e974bb5478e4a653", "6a2becd209341a5dd760515889e5aa27a26e1213", - "997e1ee3a567f849865457e22be43aad5b84fcad", "b0a9c6b95b650b90e69e3ea25f3ac2f583a9c622", - "c830370439922abc9cef0763e9cae3387e549c42", "9bb1447ddf4fbcd71f68096307fb5e222d38202d", - "b862af307888af607c82d4d2a3a53e12d6265720", "585e55bba7d4833272526051a7e2a47416f8556c", - "99ac5bdc45f0bec78af9807ebcd8fd118155df93", "c7e14a6aa34a6256944ea4d9be85777a0017415e", - "cc2dda3439152bcabbc625f21d9251afbf15a076", "4e84b51660d909910c0ce4cb014a23e20748ed05", - "f43e4d0aca4ed483f9b2568f35e70dfbdfbecd7c", "10039ee5b86d6ab30389abfafc4158da5e051410", - "a212609775beaa7909f92b708b8348b920c34bc3", "26ef38e22f884aabecbcdc02640beb2e8ec55abb", - "4689201232928ffd29fa14a2bac10fa44f45a81a", "fb2c9cb75fdb96ad4016a076773038a6081a4792", - "d80b52a085881ac67c9c8748473991852f8a1113", "47e4afb01417c95ae136318ce8d066c77402f30c", - "2a256e4dec0180e6e27cd8bda8b4ef1bc3b1bdd9", "fd4b1442c33a018cbfe42a859cb4bbbdb61eb54f", - "f36d187c3fec787dd3d4128001c545de5551bc08", "ef30b00ca626b1bc763427aed853246c0ab72534", - "75eed65362b1370b90c3a032dac2f366f1469f1f", "d0149fcec2d2e19ee8851b4ea2e328b2ee689184", - "9e8eca00b251efc8bea606b3571208966fb2a2d7", "28e3df3754c86e9809909aac9fe02515e231d60f", - "5d4af1c155c639c81448f1d51db6cd33431f7fae", "7e6a0c4ba45a0e692bbcf9456460aa56a974ed01", - "63b04d5a98be1d3a23003f6518c4c8ee3b065ce6", "31991c235b014fcf4fc9a99a7fa4824c705af5cd", - "79231d6d3fb4196a482cf902439ff727eecb92ed", "a8c246b8bf081182b08ad2a4ea478b7ba860d006", - "33750764f3c324181451b38a1dc5219ab04a448e", "370e22839b26494ce0ad1a88286f427434f3dcc5", - "200b037c3083bd2e28e4e31f015bc87f9ab7196c", "6a7573a61b2e15fd261863178f1f54d96ebdf408", - "adfe5473bf50ce4f88c88826d4055b144ef42bb0", "9d66b222b35f994a0d3ab6bbfb1c142d9f226d56", - "ec03206161f942a59ea5bc91c08086a9b1fd2ae7", "ca5bc0d3d6326e4df076624d826be350a89ed54a", - "b8b6473dd4a5f93cd6eb1c0e41d659cb7bad0286", "20162a0585c37d0c14b818eda6f695c40678bf65", - "369ce701b448551b3b5b7156667687c68f7a4259", "587b5c41554e3aed002f92535ef2179231f87e6d", - "3b81c061b9efb1074e0dd9cbb5f11f71420e0832", "6007cac67baac66d72a57c024260e9bda13c456d", - "b1678a8e2c14c96405dc17557ca68d059ff68b8a", "d5879f68ec23e30ca8882d93410073a0cd5db92d", - "90a76730c4ccc74d3cce95abfff445d70bb98499", "bce86716fa530eedc657bfd7cf18f045116a967d", - "fc46a08726a7821ebccbd4d1492ee05c6bae89f7", "d056f38506127e986b226fb5ff5683b6deeefe37", - "1119b6ba9baba7c6511bd57f21eb642085932790", "2d317fabf4f5e8d7a858a3d1dc79b88a2640b241", - "498c2b6b4c0964e25a76cd8ef9e1e25dee1cda7d", "803f7b6304b6fdc60bf08212fa280e31365d16a9", - "5532c2bb541a785fd145aeaf624491e201ed7759", "243023d8a29dffb528b567f37b5ef1d2d78f3fc7", - "c0312dad18501b449812f9c9aca3c39fc1647432", "9aa5151cb1622686f76e3e956dc9a6e48f43d3ef", - "c9ac4a1dffd0a1fe7a0a339b156259884c54057c", "cb53da91b05ac93ef8bb2dffb4f0ce8ddd06255e", - "d25e73f15b3a94570b0a85e39df20d4f9d6a3ded", "d0af00f950ccb83770035cd0db90fd8ebbe00d10", - "ae260ec3ddf6bd62cb66ccb1c9ba3a6ca9d19ab8", "846116d64285c2125f01ac2e06060b84ff9604a1", - "2261c2c6e3edb6c2327046fa2d5b69d9a39ec10b", "0c938db82253db2c09d40079dd15f0a1ad43345d", - "4e5825c76b332b11e0e3af2ef74d9b98e3784809", "83b5cadf47b3eaa15841e3815099ba5338a5f683", - "2f11fc2b39f6889ae6720c0592344995b5942c37", "3e43da7045388e7259414209b3baea7ee339bb9d", - "4b71f161759ed105daaf49ad74f3306ef1710855", "ae7070f6b723cb4c5055252017e5ce712ddbb649", - "23cff857c47ae04884a1e522af2d5a836ea30f2d", "424a8b8cd8ccd2ddbdf3c2d10ced6767b53a4ef2", - "6391feb5cffcecf562f79be5c7b5c620cc1ff24d", "9f1df5788377be4be03c705b21ffe72e3fca68b0", - "607db9575d0fdcc02810ceab97c9b3faf9dcb601", "ee0202713209fc3df5cc7c1c75812c325c94e280", - "47905a7a246fc0ab81d6620820a96a283c6fe8d9", "21ff79105eba8e77a638b42b2e18589a59033609", - "28ba2f0f2967b8292a7071c3d99c9438b1db7963", "e1fcdbf48c205c3a724151cf5008809615687dcb", - "fe9755c8149d239696e010a0e92e2fab24da5aa5", "e6b72cfddcaa930408e0d20800add718d44f30cc", - "f341256a2cf06c968460034faa6d581f17af65a6", "23791cd278e193ccedeb2ba80666c96e9152ae62", - "f402a8f708787e8e97a9e096dbb47ccda9009c78", "8dcac59f949b44e36ace133352ff4dad069e17e8", - "f36f4c364f6f702f64cae7210f0d32a535e93bc2", "8e110a0b274f6a11fc3773a1bd0933dca5cc962f", - "745a2fe44d82669a5070791037da95a0d499ee3c", "d1bda5b3a4ba7b9d7490d8511cce4a11bf76a8d9", - "c2fb15525ed50bb529279aef0da1ad889a209760", "ac5d73eea0dbddd6591c6254078018b894c74d9a", - "150d6faa9cbb1ab06fda1d19606adc701633f24b", "98f046a4f73ab3edd7f33d87279dc17c6009c844", - "c0afac03a62235c223ef23a29e6f0f868aa89f4a", "c19ecf91221af8e0d29e9d6693d8922989c8364d", - "6cc04cca454e9610729586ce72ad276e8a8be962", "5be4d55be3d8a516f8b9bfd8fa4b4b6fa072b3fb", - "68e5dc0768d1143138b22a4dec7c0796211c515d", "40b502f762b12d9008d67359a69427246dbf4590", - "c7a0c0a1d86245d58f93578f5e71861850b20327", "45e88dec3420a3081ed070a89974fade34a8cdd8", - "a2cca480abdfd271d83ec53f32b9ca7c0534b1ea", "eb5b56e00f7e3a3a93a151b04de322a54b478a1d", - "ee726a3bd27fcd17373550a73f1265123f038e9b", "ecbef3833e45ff4b51fcbd07be7ae083d0261106", - "6ff3d878e2b0739195fef120f3e8920aae5b6c14", "c8a254b1ae30d6d0372b9421cf164a2f92770bb3", - "b6fe64434d331f92023b8ac4a0ae29a436ece676", "6408dad003df5f902970c9a9b281bbdcab70513b", - "b000f8b57d68abac68a8ba92d2e8af1f4cf04e3a", "d70f6b719ab62e4d30947d46b48c4f86431e27f4", - "d8b1b3fd5b14a37edfca20bafb53bb19b68034b5", "54e2802c7dda0dc48297627148cb8080900b026c", - "2a88231e4c45be17c7b59df395c88ad1de1f55fd", "bd9541f3b7d18ba20fefb5725bd21f29c01a2fdf", - "fb211cb3f8ec40bc8d34ef5da91173b85368ddb8", "302c5986252fee81e024e43b3950ce0c03c1b19d", - "c688626a38c6777646e4c5343903c5d3c39451d0", "97e8d745c998aa9ca3c0402852cfbdebf38afeff", - "512ca7ae1cc0043eee4b9fb24bc680e5e439a22c", "8a1b18f3f1a52393779d7872132a261596718531", - "f1f688ce752c4783753ded0c034de72056e5bf0a", "cf404c790f1926de4fa92a90bc25bd3b89441ee9", - "6f67fb37b601d81e607b4784b59a60f5da04ddc9", "0358ae29870a0c0555826236454eee2a35460bb2", - "267d40944d68c9fe031797824c83b7628ac21054", "28999639cccbd7471536049556b7bb0445df968c", - "96c339642cf640e219e83499b89b3f14c40c1a46", "22ab4abcaeaab3dffd0a0eef49631c41feb35f01", - "f3281e89aa93a9ff4b045c561960128ff02bd67f", "ba7c3d3d19387b725dd93777e264c2d243c56985", - "c06958105add69f9c1215959af1592100820f897", "0246ace3db73d80516951169f697ab82de31935e", - "3ed4aa3045ac0679828da5a36e6a159a76397b85", "a9b3d7258a65a4ffc0188430f23a2b348bf3f71f", - "3f80e737293fc727a2a5f5931afef5da8a108889", "f5c4af7e6ca21899d603dc1c5d6dec724180a617", - "83223c9cdcb837c03a1ee706a68c201c6f46aae1", "7ebd59911482548ff28bc5257f092339747a9847", - "a29e7d193abe5f905841b7dea04968b1c973775e", "4df92c585a35462fd174a94fa6cc34cb104a3338", - "480f1b18698079c345470f6eddf82dfe04f372bf", "e93635e6ad4990b2037c1c42d96e5f4f5c382211", - "f27588ba28c79a1abd36e9ab225006ef711bc2dc", "0780639bded276d6de3f29a949974f9aad888f1e", - "7649e12dadd9626c6aa55ce09bc5a77abbc1866c", "10684acced018de4c9d795b4e3d17f85b831ed05", - "1fd08bb5d65fb7deba4ce611c4e4ae61526f70f5", "4ad405913be05105cfd8169727862962f73ba90c", - "e622f46b8ab1a027717765dd7d392879941691c8", "e53bc56ec46866426314e2214f39986f794f7ec7", - "1ee4211e5bc419b24309bccc29d84c71d8153e33", "13bf7fbafaffb9eb5305cc786ea5327b1bea8c84", - "1b17359571b9a657d8c1c259f392bdca507f8048", "f14bcf0c9d9d4441837089d9406a275ec7bae489", - "650d0d424276a764869dfa6d5769e0d33dee29ab", "9a51d909f6e0ea003b7bc31368889b34cbaf99db", - "d25b13c8e67b29bedd33634693fd47107d79c386", "d4791ab3fc5623770bd37a62f5847a3469ae62b5", - "63cf95a96c6f9550a526c3f7c973b3bf77da1d99", "0880631d8a31a2d656c214fd5326e86d72d99735", - "c028799f0dc5cdd928ba41ed57758827d4c33960", "09285b7758bced6de4de28adb839ce3707bc0801", - "ff3ef6de1556d6a817b228634d9bd36c03f91b4c", "7599af4e7f3c5038845232dc1c3460e757d29e76", - "945656d9dd3e48ded82ae075761849b0b6de7d99", "14d2b00bcdde27acd1e67707fdec920aaff41440", - "bead8489f2f77870afbd190228724d8ba9525e77", "ef888c5167e12709b33fcb9373476ce222d3a777", - "11185717aa656979199228d4f134506f306ebe11", "763619ad1c6fe756de2d6ea598f4a35b6b5d07f5", - "de64195cf8f8e0a8a209993c12c37e6a0e9717fb", "6fcd348a0817c5ba9f692e9f43b157ba53f61736", - "184223aaddee8a795fb21a0298bca7cf9f24b86a", "025924b72b369155a7dc79296b0fa1542b6cf66e", - "00b6d09efea3b56ed30d3f626837c105415a2b9c", "7fc27ae1ff5720a8632dc7180a62f93f0b240971", - "68a1871cc2f4239c1e4c717d6cf5d50121aa24f7", "d86a119c71e8f3db87ef84a3f2eaee3784e514eb", - "bf6c04384c5ebbcbb7a2635e885ad48223000515", "25df57cb358e1c55102d3eb05c633bbbc8d18ad7", - "c2ed09db58daafd8711f0729136bcb4bdab4ee39", "db9ff970f2394e5ddb70b05835e5cd2ceff1758f", - "b5b0cdc6e2d0971f11ffb7b83eae62bd2f2e2a63", "568a605393fdf0261752b980340b56a695993ca9", - "53a7d40199c4cd3e0b61387708a5c4b2daaa6a04", "d764e0dd4cc13227c90ea0dbdb7a17148a37362c", - "2b0970782ff6fbc9b574d9af09c7f4387da71167", "1a2f72aec014fc3b1c7a58660c15cdf8eb78c30a", - "ea70291c158d9ac2e034f91837f3aebb9315e74f", "ddeee68ef8756513d3c91e77705759282dc88f36", - "c4c43e1c71a7693a257680b25c4cce05fa68139a", "cb91e9590a1524dced13be78e13abde059a5358f", - "8df5d8b31502fd506a59b0d15f61631dc5dc0d11", "ef60833d075ac1aca48423ec296b18756a0907d6", - "4bd51174d78af4c6afff4a3580c4380eaf53db03", "f89f34968e6fb5c4400d4133e5b83eaad9ce1d81", - "4926ebd2150fca495a5ebccb69d73a843c2a5c76", "b7d7768027c43c4bb9178b59096058c827249ebe", - "b18e01b7ab7b8fdd5e9093a4d10446ccb4c8b461", "7c0cb0bf58b260d848be8b2fffc6ea81d45bd9ab", - "65560b3113f1d79c241d64615c70a95a27a1295c", "ef7de7cca843f688185aa44caaa11b8d9c5ba419", - "577959df764fbe2295c7355420fb88e7259318f4", "fb4e5fa6f2ea75bd25bf313675ace5ecfb09ce4b", - "58c3bb9c95b2b18b54923c1c66a271c5103b5016", "d15a9ce8720d18dfb1886de4ce23504c690f9849", - "09b1961ea1fb0304ed7ad7c2c404af3113af532c", "689943c3a6fe2d15706f588d5d192de09025f87e", - "76c955116afc032044fa820077f0aa0077a9b221", "e4e28d5880eb5a19eac4f2dafc94b87121315736", - "f66dc5b1d3a36e518a2d7581534cf1eac1c0bb86", "437d9bab241951c67ba4344ba60e7f8c8fe091fe", - "d48f36d517120dec77f9f1383c6ff175e490957d", "3595ca188c62c02f3a21616a40fce4063e5639e2", - "9335fe0ddc8db4b8825b6a8e96f2ae314c3daea5", "93b3baceba14eb826f0691ec927139eddd131418", - "b081a6d644c99936ce2b53227aa949e61c1fc1a2", "7c301a66f04090a5dfa9b97790c2398bebe8c658", - "70e640c8b512f69cbf2d3815ade5e08acfdd6ea6", "a5ff6189fcfa209df6073595ce8d048bb434142b", - "865f86d6f58109166006154d4cb1f18d780afc7b", "0b32bd194264f3d34f207e36da01747250f370b2", - "160db72460b1d2cb57b71c5f5005c43b39344a08", "ca17e8fc42c63b71a64943b2edc546cb483d4987", - "62709ee11b06371980bbc365eade2cc09fb201e1", "d42b892d83a19496adb8a51865d7786bf11cb51f", - "151eda2239a8926cdfe11bddd08d4a68dfc06fce", "48289268a75e7c551d8407da65a6a8d5e96bfeac", - "76475e31fb20faa61548ca6c110bfaf0a8509333", "ff45b9e590737c453377adfef746c419fd024214", - "791336c9f92b920c36d87abfcd23717effeb2979", "7cbdb028c46f69f69ad5b3870fb9976a339a88ea", - "6dce9b85f8a4d116d780895772890e62ec554050", "609a9ddb002e9e03ec1e01fc0d3273defd125f6a", - "eb5cd823d83464a85d52abf6fb618ab6b0ceaf14", "0b33f97dbe25690d5b395aec431714f326835761", - "b3c0967b6cc938da94bbc24bbb4960c499eab996", "55cc0375389bdbe9081930f6aed59e2d1b996d68", - "3ab0dd9b211aa79f607aa18900021d331ffec108", "8b8fc9dc6eaeab845218b9b42c9f1eadb85d9a76", - "d95873f271a98500509514a3bd503e111b2eeff6", "60c22d4758b2ab938d925ebca4195d388976ef0b", - "4a71cb75be4c145468bfa41edeaec4cad48b35bb", "674df8ed0814f769a01ea52a86b37a37db300fdc", - "52cd156a808d638be19a621e77ce9d0b705ff959", "893fae64443d115a0071088287f1047c9c85bd0c", - "fe745f1136b3c2b4d5cc703cee8933de6357c502", "7a9ed9c04bef62538916e432a74f44c034068c16", - "c60540472bbd9473a78ffac3a071904552cfdd6e", "dce6b37c643555216d24705885d35be6f1658323", - "d25cd6e77dd4f8683333b68cd17e4ef161a10f82", "ef59cd7b3e448c27b726dda2624e3a66bcb7c915", - "caeb866326a82dacaf9b9ce21de180c99462b0ab", "300bbd6765f353ca1f7a42c8db1edbe0fca9146f", - "d476be09c2c9a67b065eb972d473c862d05520d7", "f2692ec53c9eaeb976a81908a1ad9a8a6065eb56", - "80a904cfc2637be47cf6db433896285c96642f28", "b4e7c96d36534976b532f6a73d687ecebd20d3ce", - "f442e491213973df215b4e5a13ac42dbf26a418d", "4a990060a137b7405e90d674667b774c2ab3d9df", - "ea028084a5ba60179ffcc5c2e7745a5137810674", "946cd7b549d16cec7f31b99e31a5cd1f97ecb0a7", - "f4d1570ca148a075ffea03034aa359a795a7a95d", "b24a0df950d615d89a5c490856d9efe0c67e6807", - "4a3a4973113c414789c798e3b279d04e68f18193", "853861b52dff3d4e69cea17db319b578dfe36b57", - "75cdf79a50fa9f54ee0abe8a7352983e4e15dc8f", "d2172012e40b489a1b696aee59ee01beb94d2044", - "c463cba55508e3410e6c938ca7f07cc49c69685f", "298753c52149d58e36b63ae01437d7e9b1626550", - "edf83ddead1b5bf94530280409c8f8d7a3566036", "6ad9ebb63aaa22d5cac2c6ab68a8d044575531b8", - "4c4e417f31a770c165848c34e9a1c03a88345923", "01ac78c98a9e83a657895f330ac60b23df81aa19", - "077b29278d6047812f8b65e158402f13dff2e638", "6a3280cb4ecb45a4a949416106e707b4999e2491", - "3de477994ebd5b7edf0a48ba6c5e799fe02a53f7", "2ebbd703eb8308492ff7d0e3604b786931ad8617", - "5fc0b82cdf849a6c424721cc5118a196c07caf43", "851ed5018abedd4f527d5fc1f184016c2b9dcb20", - "8271e8c30ed07e236d230df37635819f45b3adf5", "794d1fbeb2f5f6e2ad81450602d53d232a2fcd66", - "765e4955986ec0b20075669f5a7e2dca79a98ae9", "f94426a7f4b9bd63aed0e75894ea80278dab4320", - "c0006f951059f5aa58b4b898967d1dab70377178", "414f4c053c7c9d294903806e748a132d54325f73", - "a3dc4e32a5bb67c422822731ffbad447f2f89dd0", "9dab95f8797ac80a22cd854761e2dd141be8f436", - "c187e0b59cc8710d812cf24e9ad7191c5d0c6206", "55cc88749fcd34f08c5d0fee8bee92dcaccfb010", - "2c3d218a5428646b970895dd88e2f61739ba0732", "4ad60738ad972e0cbca3e763b556937501c0973c", - "543f72fea7ef066ea3111bdac8f0ac61134e0c24", "a2bf3ec52c5d004e7e5329efdf6b5cd735618b87", - "f483494815f89e80dc399163080052fff49031bb", "3326ec457cfa6d30663eb0ce49a838d7bbb86415", - "f6d5647f6b6923b5052619814a84b2e1bf8d0b85", "f2dcd0fc70ca95f475b68f7335b2d0855534e5f1", - "a50cd55ec2258557a20839a0d6219960c9b1a2b0", "a34ae4d4326a0913d9af50546c558811565ec66a", - "842e922b6252301d8df608a1a1a4a732686e2ff9", "2b6cb59f7846a482432b4ac57fd960f73d2441ba", - "e559e01ccf3cc35aee9732e3db97c23165f8a6d9", "543085108d5513b9fe63eb96fb386ccc84a811d8", - "c7474d0e9cfe5c1d8e56f3978eec6871706a38a8", "fce05c355558c606a7ca815613c6ad3d8f8a1503", - "30a17532024869bc353e28aa4c3da17dbbcab80f", "13d54732573224d7879166a11857046c50e13626", - "42868488cc892e63b13e7afbe157006ddc215258", "94785fac47a5d2ce41d64269203f14de07995186", - "82d752a38f9d5598685d58e5ce6080409b980442", "96f99cdd47de4d5e4180c99bb7015fa77d329687", - "e89a84828a38b552efd3095472eb39dd18be141c", "5a37e8b4031b627270f06125f5c204eb28437c85", - "30da9a8dfb0f65559be3f17a3d2f3be0cb297ba7", "abba9bb98e64624543ac376fdce700ee5e33b392", - "c19f87bb786c68bab429f594374c24d09dc98cd0", "73754ef7ae4615cdfe881adea981bcc93b65e887", - "44c25f0a9f3151efbb98056e1c2bae59f4aca0b3", "51f465b5aa2a63568d0bd82232898b39fa429a14", - "1ece6bad7a8d2492da84f5db5a94a9c81a94a3df", "603617cb2ad5009c06dfc61432287ea41d4dd70a", - "ec346b3231969799e3852cd7f4e951a25f3fbc0f", "46af277dcaf4eed7cc96e021c96b266c24c1fcd3", - "0965cb17b3b353174be301989ee8f5b77ab925da", "b45319782274fd4841da3c70ad3b4754bf2b1b08", - "2a2bcc98ea5b188049bd46b4e315ae55b359b7f2", "cd09081ec384b747181bc2309a9485ee0888516c", - "f636e931892c445a7ffb1aa0eae7499caa19932f", "34ceb6f49765ac0d173d4a0cecc089f34dce2695", - "9b18988eed2891623baa37468ef83dc6a9a93e14", "087397f895ac78aa63b5b7413dd4c948cae4dc50", - "98e1abd91d5502799931c25c1c19fa6605ff6dd1", "279448c0f978c369797336bd660e457e2abccb3b", - "20d76b4b81484d694731d6a2046661a025928bdd", "7a69b783e3e747a0f7a5eff5cc23b9a00d53aa01", - "f645296a6d289f80b9960679b8edfb6b0a4d96c7", "9352d33e1d396110bedaf1906567a6d8139c98ad", - "3a4cb9ed1c4e291a738f6a97ae82b7db616ed4f6", "e97932a4ff925df81b844058a18f2da4f362edad", - "2e9b3d733cb1d6a6fda98cfccfd179c35559671c", "00e2b96be50f143abbaeaef1b42f502eb1c5eb38", - "a3b8a036064eade54ac1a7e49a48b5228863f225", "b050b6089b63a630ca1e102f27f1e33310bdc0f8", - "91200850dde71fd5061890bae22cf6264f3a0ce9", "c4c90fa787e28f241a6149c5706f67cb8c897c3b", - "52cda4d77c07f76113b392291e947e02010a8ef8", "949b21730e48bc645dca6c6a9dedf758035d0eed", - "3e0509507736054281c0feb777b5beb62af98ed5", "994993e838dda5b000ee4e75786a5a826f368f9f", - "24e2e8a67ed9977de3c1373968d76736da3c800e", "9c8374cdb61697a37bdc89b57ac5574af910138c", - "7facfd4ee6d102ce1c2103b2bc0861865fffc07b", "82f7d052e4d562b268730e8d66d4ac694d963f8d", - "a5f79e4ae09eafe2892bff810ed21b1a7cbeff6a", "7a66189f5b487392ddf3bde3b6b2f837711767c2", - "756f813ee996e91c50dee3929035b81d5c2f5b7c", "c0c98d3382858b9de30907003cb1b3f47bcb7e4c", - "7a1f959994f3e8665589050ca2e07c5ed5579ff6", "06944876fd90b41f439d337cfdbef2582caa4b56", - "73e779de8b03c705726abbd686ab6f905fb2fe27", "dd14f8315d4345a1482b6b5f581fefae03154e6f", - "b4f629bddb661422c15c4b0459104b6a6387f3a1", "a65dec2720ca334bb503079db5a5db4649c27c0a", - "23d9c64b7d95c1d1c08ac83058dba6204537709c", "0070ff46a8b72b79d011f59a770cdd2e3a7e52db", - "39538c29808bc3b1c85b2f9555eb56296778e5b5", "05235f2fda6b96b82d3b798f5c06d1c26fbf5556", - "da9ac947e5272631161f7415583487cd5b81bd92", "0afdc9abb0a921b0eb87256c34c2440d7bcdf748", - "708eb61ae54de0fcccffafc686218a959fa0e12e", "921d2ecf681cb2fa40d8cc9390591bdaeba5bddc", - "d54e009ec45cfd47d90fa87926ff55f5668cd745", "b66c3a482974a6950eb27fa2c83df33c0ddaee0f", - "d11ee1996ea846c781624a6be16e2cf05c90a3ad", "d1fafe49cdba1c135a157ab725caf6a73c44d413", - "37add1833a4462b08f3d63ac3cfe2b29e8c19daa", "54b9e091f1f4a2aecc9c3abef4785cd4116e59da", - "2e7c5f1ca4868b1bf1681e852460d1a64f6730f4", "fee6c7a1a74439ade1a4ba1102431cb16ffa40b4", - "0b663b2c2e9813fd968ea4d53c27117a37af990a", "2bcec290f45a8f707462a56e8cc468f5934fe57e", - "2e77e56acb8a073a7164052b3015752f55748f13", "56cc03e04970154b1ae9a3cb49eeb3d131118feb", - "17819764b0cc55daa6f9a70e1b7cfbb082504a26", "b9992bfe65ca57863517d1a44a5de4abff0d891a", - "7cfd6ae2ae46bf951a84ab288fbf6381377e4fb5", "44f321da361e4de492292e465ac2576625c2f04d", - "14d021d38ede8d4fe6c55266ea1bc18471146ca2", "dd5f008277ecf79acb0c32c88f459a46f556d235", - "e712c5cfb5144ba8122f13b400324a3db3eb1131", "2e3b8bdf70024acbd57dbd574b42d8081b22238f", - "a27f805365b6074f96d0d72bd877158a6a2683fc", "1777f7ceba2141c7725cae03325aad9015f5e0ba", - "3ed72d7bfdaea45c7741c4adba22824729fccf93", "1efd9d0cf3d575dceae0143ad80cdb36ae929f19", - "ed1e3113a91cba66cb2bdd2fc62d221f0fe98720", "56830484e8e3a9bb9c3c0e28d2e06c59c2f85814", - "612f82971d281213f121bf3940fb3a22ef339b1a", "9204cfa997dfafbe1d923cae857fd8772140d2b8", - "bd7772cc8ad355a2edb8ca92d712bc6522f679e4", "50013bba2f0c0daa2ba0601ad9d538b8945f49b3", - "903166d464af4cbe28c3dcfe87e3b03d2d4361d4", "498a0b6129cf4bbdfcd1fbe56f41a09711c81515", - "4d82da411ae6922528a7e31ba0d9b7781ca7b140", "d1a59d5be71487c46f1f13cca1329b890864e3a5", - "0130298b9910153b918c24cd0305bf004c77f139", "b4704585677546e3719b0167a48f7352c3135018", - "bd2af11cf4b22ffaec8f0f81e41c7a200707984e", "90bbdf000b6566e32e973a9ed13673babd3d5971", - "53b76d4726ba14be0ff600d76f6e94af63bc76ac", "98b92425f234019ae1a7d7fa763ee86d24a9d4b3", - "402419c820cba29219805adb1b50909143962ab4", "2507dd9d1d952d45d8e29e3da7d9b67261ddc8d6", - "0eef7ee0455462714b4398429bc4e0b1e68aa807", "c15af97c03e51bb5c7c23118564b21d37e41dc38", - "5ff6527e38d98cdf140318d98828d7de099d1552", "7d8d05ecfc3d87c0a798fbb28a7bd63d79317590", - "d728b77adbe3f536b9211d9b26b0668cd796a549", "ff936585cb1595e9b56e14b77c2a8605a312fc2f", - "cee364e17aaa6f0d77dbcfe496b188de38123833", "28f1af82eea595d5db3da22f4433c144fad620ef", - "d5bc60e7980decfb5d5cd10ef9ea1bd0a3ce5fae", "392ce37ce6411c30d436940506dc2cc8278f66e6", - "38d291489369e7f222a2711e5afd7d6ac6afb574", "479506b2cf7c7392c0a96d6e5d550556dfd20ba0", - "c71e5676016de6a9b7dc27a123f403283fadec2b", "5d03ade937932174a2f2b376efe6f761636a270f", - "04302da411d5d79477463fa37de2f639afd5127f", "d4e6cd7852b5b88d88afb1db0cc9d29d8484f143", - "1dbdc1d3d9dba7ce5cac3bf7d2268ab237a4c5cb", "3f263b23507300ad4dd7903e45876c2877e59ffb", - "127d0081100e98843f16d26cbea527856d9a9ddb", "dd5e22108dcceb35e1944813e2524ebfd0a53df9", - "5d52758299b341021d135b5166614a46f3ecf2e3", "a1b3da2881596c60f669fd80479e45a097b38707", - "21a63be654b8e5df434d01d420ea2206c8d9a92b", "36ea46c3da7dbc2bf4d304d81f86224dfe54444c", - "29fcf933c2e58f6eb8fab04bf8c511f56896fe15", "64737770ddca8995c64e1106bfb08ff0ff1fb144", - "d8c191fa2b58539d83c7efc1c3346079ecdc566a", "77f0910c39aa6108e0c2fdb32fe1832126c0489c", - "af64db9a99bfd8ca4affe94dcd5cfea05e94e03c", "71dd27e77432a2d5b446958707286d08097da244", - "5ddedb0a995f06b295696a2a7b4551e404d0dd16", "01f87385a24ece34ed8ddca801fd84f9c86e74e8", - "09249256a87d4a90588b026d789fd3cb1aec856b", "9240b4a3a946be297b435486d1f2a6d941422b93", - "399ca25f86719994d4612fdb618983079d6a59ee", "4db57eaeeec89f4a96d0f2727c15ff083482fbf2", - "4a31d4c94a4c6ae379abe24c46817a1157eab07c", "182f2002e4307f83c62e06dfa4164543fa7e814e", - "97a0a7220c2b8e458641c3e6e56889254d2da049", "3440a5e4b4e31f45c6adbae99b6214b8fbeebb2e", - "6f94a7a5fe870501cdcea762e4a7a20631d48d62", "9da3107576333b6c7f3e878e508e94a4c764e45e", - "20cb94f57147f8372022885ac2356e464fdaf7e3", "68803fd3ffbf592c0432eadf45fffa22e5afa8dc", - "c538f4c3d9ed532f02458a7c863ddd549960902d", "cd14b737781fb608698437bd2e6d20d691093874", - "2db66f7bda4464a6f5342f5e021c29a38d42068d", "37b12212ecc3a32ede8aa04eb0065fa80e3e821d", - "887306035bf8e3f0963a254a6e46b52b55a04fcf", "8747b40002f4a24a2330ee27f36ecc0880083827", - "ee262c59ff4c66f77562ef879569193543838393", "8282282c974675b044c071faf25996f4b6e4ebc3", - "f9ca90f109c32ff5889c0c9d84ff11f9fb5b5924", "e530847cf2aaa328e800919e6eed9739521a9b50", - "ad726687605b280a0c190153654f4751ebba4c7c", "93f6ba66b73bf972a3df6ba722a1d56782c59d47", - "b40be55c3b541c1c3a6b46de02f45e3ab9dfad47", "95ee9b8acb715971bd1abc137a9d54bc88139b8a", - "61dc80eef767360c6d48572ca1bda65c693d5362", "ba44c4692965b0d694c8fd015f1ec3fa4dfcc696", - "418a1501e2a14efb4ab940cad4c898f09f92ee83", "026029e19d4c6f0bcf239abe607026a5a27f5b86", - "8cbd5f3c989185d9474f7b5767d7e6adabb2015c", "55163a23b71b9a3d63f6e4695b07ebd07064c61f", - "d9bde5278517a57ff7714edf98ab2361d1663219", "9ad5f0871e1df9582ea14bf7ba22350086fcd055", - "c57f5ae0aaa74eea99032b45f0dc5c927813d8b5", "3e3f6f7661780b696501a397d8e95ec446fd1fc3", - "03d94679ae1908d9a6f6a38c00ce7988c5afbcb1", "4c8f526d899bf04b4ce3e088302680da64499e5d", - "271ddfcd505226549f7674b7e539efc96c8be5b8", "25708b2d11167437e6de01fa0406dfd3c26bd8d4", - "dcf94a3cc15a85bc1dc2fc7e1751e6a343609049", "f65dd5dea2e8bf5c90b8b093b4ae2db11fce3b5c", - "b3722ffbf1e3287cee8109c82b7ab13d187a3d7b", "ec3af0efeea2836f6a2fc5a2390232ff10e17cf0", - "c7176c1b7df0676b474b4786a7e6ba25650df8aa", "ad97c1b6ab4dcd3d4917cb59427490508523daf4", - "7a8e2f675709ba76674a2903653b07d348de32d6", "bdd754c4219ceadebaebab82c1dacb0a6d819e24", - "31df56efa866faac4fced90b742b1800261ef46b", "1e77fd0a0bd78293212c518291333d3554136b41", - "99f906bf47a41245895867f76ad38fc9ca88921f", "49dd5ec3406bda057407abe5c57e6a027b8c502d", - "f36f65ae5480acecfb85d9b8d7a79603853f2115", "5a29a9db5779e61efafc338b00be9d22efe2a181", - "6b28f73e9097b7a7966aa9add138e3dc14c52e75", "92571e06644eee1606759deeccb9875fdb454b81", - "b291a60f954d1aaf1bf4d1a845f9838cde8a504e", "47c1cfe13397789ea9681d8f464399e35b1f233f", - "dfd9f01fed969c7b2baaa206a0a6435c5f41ca5c", "de78a285a707e2026d3cfa36a0dc7d18d0c9a15e", - "bce1807765d8a350ed04e8b525e83cab25db5879", "b65a28145ce9d5d79d2b25ffabc905b854eddef6", - "31e8adc8ca44176b5d5b91ba4892612f71ffc2bb", "5a75300c606561e9039ceae4a707793f4317dbbb", - "7ae8180913c01a668a0b0ba707f8550223d1721a", "c7f9391c16e45ef0497f2b35af00180c72a7d91a", - "9b14724732e6369051e8ee69db4f2ff4ab791869", "f20a749be5b9be59f9228aefc4fc649492a272ba", - "fb08711894409b26f7b8827fa0af15b96b6ca1f6", "b8e4379b643d250498d9d7e83b461c8e1601e7db", - "6f9895696ca5c5d76c1852dc169e38da22b2be3a", "0b95e27f015c056bac9f3391b4ee0acde58aaecb", - "9dbe2e2ed1b88739722da7e6ed5deed3a95195bf", "eee23f5c052d9587fb7613de3f01901f14d6a450", - "494d77b5348dd14272ae79d16aa456f4d14ca8c2", "2e8d5bfc7b90389722952a2b67ffaf15f98068fc", - "15e79975f6e8d07b3792dd9045688ebbcd903880", "3d5646ba7b187dcda1e85727462e0f664b9b3f09", - "24aa1622f6ce7c03fb4012ba7a36bb3bcdabb334", "1369f20407850aeb075906f622357694dccc4c6f", - "0871d5b44508d4a35b827a8ff55c88e828570b73", "e9344cff34bbf55f0fb3eec57ea0e10d018f7152", - "ba521a46f16e478b263d5384868422707f12dbbb", "d9f8a5524a6e1a88e95b00b40471d0bcabf928ad", - "6f869e42bc4c0830243807006b5e92ccaed987c5", "1480066efe0215bdd44d633dbe1b7b36785ae8ca", - "a02fad3fc638e1d1c10d3a604df4bb393d5a7930", "59f7e9f29f14a28f3e06307a6d2c505d92bac672", - "2c61bed25bd5d84c2773700540393dfb6019842b", "c5cf5c31e822e883d2a1768bb7852e63be3bb4aa", - "9a21e2e4f98b172f7203af861e68cd14b830a761", "b4f17fbaec55a565c69c714a3b5d8f4ac490c3b4", - "fc1e32643a0622afc3f5cdad86abd94369176f07", "f83864fc3c2d7a2bfc82f7f2b0dbf3cda74714cb", - "a5503e69b80b4ebbd6e12ca615318866d7f7953a", "4fac6a6565e8c32f1f62396d698b6c23f0fc665b", - "17f1ca6c1de1ff8aed107ba8b2247e5ec41ebcfc", "4fc347c433d39d21c2dfe7db951eb3f43ef2c513", - "b20eb22712349162b7390f10e5670acb5ec9cd12", "77afe0fcc0019b81a87269bc20f5381519274e90", - "3520ec2a803d1be3bb16b60177906b055c2fdd16", "05a5f0b3822f27ef60fdd2011de152542de6ec2d", - "ebbcfc6ba138ac549fa2f17dda86a75e5e26fd47", "2917dff8446879fb28b6ee2a8e95d399eb81774e", - "1c67e68f4ac7f4057c712bed7f6ea424f07dec9b", "1b712367effbd03a9b8a8c9638db3b8a42d98b5d", - "7788b8ffbd7bac813c525f043ae6c78b54bcc464", "eb3ca7fdab9840c7f7c9d7d71e484760f9581cf0", - "ee1df733ffddff78579fa89a8f146d67db61404a", "fd55b52a62bdff753e1e5c467f23a8e2ed3de1ac", - "8aa26fd4b2a06e9f928d7aa4886cbf28f40169f4", "e4bd8c43fbafa9775d5f0acb9928a91fd8596cc6", - "7adeb7c36de49d088380792883ab034467726724", "08fe040864b8ef849c1cb653cd261204e3949ae7", - "14d84590bd7db3221a3fff3b31bcd4026274f34b", "547fc4c32bb307a16122e8427580b1d153950e43", - "64f349705fcf35b551fb5bcc5d93aeecf9465aaf", "422e5fc305b81df39f79e6646a06c9af4cf11bbb", - "6a9c141dba2f8cfaad51b6c16ff0c433df9cff03", "fa3c03c1e30bd67594a79bb3e2b08722a0dfc4a2", - "3ded6ed3eda7b67101db34809a7983d08a8b68e0", "56cdb055a9af97858e5d29f9bcb1356472e9003a", - "4f9bab4228e3305be42c2967a6dc4ef773cc51d1", "717391ac5d616f117321b00c07093150b82d8ee4", - "9a746963265cdc3e2498b469975feead7f6f0b47", "edcf69daf11ee8694be60e41536b9b6178e237e4", - "ac65a586026184cdbc4647326b0efb838f171576", "4c8dad3b562ec2db631186ab24e75d6f3783fdb4", - "3c18ea2cec1339263859e1ece8ec2b14d6fa537a", "c6c8518f756d7b5e238ebd34b0e78133c2801137", - "47740650b6135a8f3557fca12f7bb0a0bff7d390", "b1c15d576ab9f14f18d9b21aa27478cbcd00361a", - "42fa9484a9f1caee066628deac108b19d6b93ec0", "3f53d018e54f70921a36f7270cc133bcd264abaf", - "8bc417c5a19b6d5f44fdb89a8a9f0b424fd68c6d", "be26134b26b66aedeb77d959fc59df699a275679", - "e7e335c12372a166de125321c9b30d5f63626307", "7f6045ebc9ba2c9051f7c11eb018f2334e665444", - "dd19cfdaee44125f56fe490fa37c35d016caf47c", "06d8625b51411ffefc23daeaf6b355e19314f90e", - "9ea86d6297a5922b8219f8af414fa0770f06a030", "0ba5e5207de2887a4476a647dea9ae1317d5aa2e", - "da56a105d965c4f23df0f3011a44e8358d81a602", "4a754fadbc3f3fd7b346d7b64f5a3b17d271c7da", - "a871c37d0a5e7e6648a6c16ab63c5bbd7d70a16a", "fd23842b87d7a9180947ac06d181eeebe5dc2941", - "555a2918452f3a04c4af1f68e7413f16cb595977", "5b1b88aa3d57df4397071a9be26bc12108a1e481", - "bd076901c68d96c3bf3f311ae647c1a37a773653", "99c5033ff768805b91e19b47c08675a0263dd3f3", - "5a54a65b1fac540c1e5883ebb1fbfeb165cabc09", "cd115c1b9ad75fca9e914a67155b4c16c8065c77", - "762ee5659b9187b42699c0c075476d25528d593d", "7133c5be52c10a132ba76e9c4b3abe9b0b7b7ed6", - "cb4e2ef91ad0d1809726ad282730a9a6d7faf26b", "87cff5c69eb53813d255a48f8ae581a8bb3301af", - "84e668ca517872198ad8efa92d70b6c4de97d409", "88cc9dabd9a787283b3d4009c290b7300d475ef6", - "cd2f8129d22b8e2f5812db78025ee168dba27888", "36810d3cce461175f81169954f6c15d96cb8edcb", - "a6290116a82a957194a7b47e7efc08db93813dd0", "bb96a933ef02562aebf4613667e77051b9db92da", - "d9364abbc26f8f75f6b257f36dab42be6fc499b1", "8e73bcf5a12e602412dfe8e2461b85529c18e304", - "3fc0507df7156da61c111807c2608cdbb71b8d85", "4ebf9514f9dd7203a3bc467b1c4073b5db3d5589", - "5c6fe9d08cd043b515732de1916616029b912bac", "5bba055b5909daab370735260cd65e7950c456f0", - "7a8f63294c940bd4587e2e29c5aee58708426ac8", "985882796501408cf8de16d91a938045fcf544c4", - "740a8b09820e1ea8e5d8c71a9df6c6f1d606d55f", "c9e1dd02449f23eae2ed983632bb1048ba67c80b", - "cbb201326c9d8621f2ed57b6c36edebc9405ba2a", "4068e14444cd547d9c8557a69521bf127cbdb6fe", - "06e3b6adcae7c833e84eeec5208bd9ffd8e7bd70", "dcbeb76862ffa50e56423a7f556f7a3c7b279bf5", - "556d08322b518cf02a9c29097900d7b16d2692cc", "7550e1c3d068211d065be3676233b369c6d203d9", - "2f95989adeec8c3f3fbf8645c616d1071a7363a7", "ca06cf98b3d5fcc28a66d6bfdd0bac34a8d54737", - "e9088616ec2fef76871de1f4affe67742915786e", "42db27d937253393f68da84ef4d64e6d890d60f2", - "7836f5aebb1a3962b3d987d6cffc1621d62e7031", "52f8c06652c719cb54169981a309a8843ed64b9c", - "9d2e19bd705a6c9330e3511d3605c3acf00d5ae6", "8d72b848b85b63c34a886e64a5cabb53bf2c44c4", - "97d35b990bd278de751bd95b311ede35ebf1dc7c", "3bfb725c6d27358e24d05eb8b69258c47437ba16", - "1a4e7ed04713b1585a663b62e799bd9133c47d28", "41751d21de5c316c856968e2261146db0bcffa63", - "cac1045bb2f08cbad3cf932c0d48d8484e62586a", "f26f9979321cb3c40b12bcadbf1e4671f9ff5f5a", - "baf156ea80f1613488b2973b105b0e5ec507fa40", "1225c97bf1b3efa570d2c614fcce6431aed98da8", - "4823ad32811a54c4e3d86d39d4eb722f0a5f7a03", "4f64b0b47b2092fa9e2ff07620c2beff0de7ae39", - "dde58a3b85f6f12b4cf7aff968a681928af64ff5", "1f088cb0398d95fa9281b13d6d3400ed619bba24", - "d9738aec244d520ee9123ee206ee954efc2bfd5e", "4493e7e7a88d8da224af1aa8c5828dd319f86021", - "1725d50bfdf81c3065aa061a9a49301f822844da", "8f1c8a9f690279edd4a7fb37e0af4b1eeca3db17", - "2dd431e6f6524c60780cb2d785130b69eab6b12c", "30a47a979f60883359b902ccdf57989d5206b7b8", - "f72242e0b21406e101bc74023700fa7ffa8c78ce", "affd31998855a2e2c66e0fedd5f2a0368609073d", - "d7bf882fcb963728e69252fffac173f153e1c9fa", "d50e4560c01b71343b4300d08ef302d049466219", - "235904923f703c3a95f74f55ebfba37385fb7761", "e31e0b576ab331240fd4df0e6fa1ba70a1db33b9", - "55da5f445c8e5dcbd75c522f8ebb50aa2c9bf38d", "7124aad094d27d82b38c751c4f6069a31e50e1a8", - "f4b2a6006d676c4202f936c3d3e455315c3cfd7c", "9cc85a4fc2840adfa1850cd0b01c9fd1c986ab6b", - "39efda7cffab3597dbaba91fb10ac0041b2d53da", "e33fe3660eea113d53f45944e8489d54c00d4672", - "72b08dc4fb03ca0e4763e528b320973db5ab947d", "28b5b2b6e88d6eeff6ed047c8a7959a78bb6d8f6", - "b0e8a7b86effe063533986d940aa2bfc3d270faa", "371c9207ead2cff515884a1b6c6c0831dfe2eb26", - "ab38fcfc415ab75e2ba3fe96cdaaa3ed51cd58f7", "afcf173f583e25786dd094969aef55c7e942edd2", - "f0852629be334cceaff80552c382bcc0a08a6acb", "708ef99585a76555dc567f5f3a07616b30e6e6b1", - "34a2614fab8f3e0ec25eb382db2e47ad4071b12d", "3707a60de155026615d1c4d3b7bab12b0e154420", - "055a2a97afcf45f8473e0cb3ba33f947e8eb828b", "eaf05fb595c20bd0fb27da51db06dd4bceaa5413", - "8f0b1c081f8efbb1ba661c29c5cd16d546d05f9f", "64954d58a69e8aec72d8f1065dedc57430e9a935", - "5990dfdf4cdf6a961fbec8a03b641840cccb8ea5", "566dd607531adab0284af7d02c2aa0b31d3067c9", - "d53ae4284cc7bab5f53aafde89538a50ec71bfbe", "2c55bd4cc2ef2dc26a12c02c5f077a2b61270a59", - "3385bf45d0d065d263d8e0934463695b37c718ad", "0054112babaa8e635df79b63e2dd89dede1accd7", - "9640b095837aecc45669aead3878eea9a5232e13", "aa180c642973bbf58eeb08d142de517b1de64629", - "7e4caa7466bf8fa28522dada3031b1907e5b019a", "122dd7a86ca24c04cf60b1afc7baf4c7b120862d", - "f84b3710bee3ce9d6c61633338de5335f8055120", "2c58738817c223ba71a4cfdfc1e070dce095a76a", - "3d9f4773b6c4675260f695d964a78669e1254213", "86ea67ed19af6e3ce37af6160eb251cb47d0a536", - "3134f576f5a85a80e055b501485d6e08b957e32e", "b136d742bf25ae0917599f4ca623361ecaaf10e0", - "f58b88b6e3cef4a11b6a04373b639dbc374f0d48", "44893414ce5514ccb69451d6438aeee0a5ae3fa4", - "d07a5141298a134bc7d56690cdcb51d22aac17d2", "5c635c23aa70e436677220f0af95d80c1b075030", - "3c9604661631e3984cb7fface67858cf8e16bfe8", "c0329aa82069ff716df6885a9d42d67cc56f364f", - "35c4e1870c134a52c29d87dba164882e375df3b4", "98a4e8b78dd62517cbc5dcfc897f31c79efa5410", - "0fa890a5a0ddbf30f2d8d006ced0f6b13ab0def2", "acaa6ff749a7f6ff56fda52267ad386bb656d5a2", - "8e2d5dd30aae427d060a92367f4a66e900be6538", "e27890dde0a5faf7447e1b145d5744f75e7c9660", - "fdc4be3ca621086bad2f6cc4e71853ef2efb3d27", "98222ee5d7d348b8a609590479dc12fe5a93c7dd", - "61accffbe91cb659a710aed578bb850483e9faff", "149c77518168e9a85553f0e43388cd86ec8b5fc9", - "5ca35d08582a8c73ff833f7bc27ceb161f0ff0d5", "c7c8a61af24907f251c595738c1f7273c6d388f9", - "16ee28a886029f3a6078e0270a88d028d0639ef0", "f08466d0d7e2d83bb6e8bb999369c0f55cf59eba", - "5c77587fca5eaa0f8342f151064d59125236e9a9", "878fd133756ff811d91148597bf0a8ba10aeddaf", - "e99c8365aaf85d8a96af3162a5b04472a89b9ac1", "198217ce4363e8cd71d2a7011c1855d6b54e3075", - "44665c2e1d5c6300bd6749854a3d789ad69f0473", "9029f6e4d8e41168afb51784e127532bf5b0f40a", - "e804a6424cedfd3fbb1c860824462f0088cc6da0", "50f668241b5d6a54fa4f8b3a64f1f01a25669a68", - "97dd2e337d8636723695b43effd7c4070e8307f4", "312f88c527009980e8057a8a076e2770b1d7f935", - "25a24104abd54682a82eaa03690201a82137a271", "f66af150dbe38ff37c28de228b3ab4088ef8da7a", - "306665947a783ec1bc3f155cc9f452a392af96d9", "de977cb9176990f1a3cd6edbecd64826121d764f", - "a24cc91bacc28c73d065ec44e53fa99609ed287b", "2fe4e36ea5f73b5bcec070f9b0abe859d20fc4b6", - "5975beebdcbba4fff6fa4c94377244d3494cfea1", "265308b11a9279ec3afeb00b39a296dc5e0e6427", - "17e05a8f9b3aa0e17fa989289aad48a2890ee451", "40407986bac58a481f0ea86ffb1aa22313a03e3b", - "261593c170055034700d0e34a061eeb594d6b62e", "3f1a2ceaf810b47890761392d771c049841b76e6", - "a4f564b28ec5fea80a3945abbd531baff77f00e8", "af4174a3dd10760cd22054253abb6915713d3141", - "d99beb57a50763266a1bb56c26e2f86812ab3832", "16704488ffed948d86fd5cbb26fbc9072a044211", - "f311ee02782bed10a16cff452a798f1eb7f3683b", "ad923db2aa8f0f0c1e48dfd0e2c702e63654e151", - "844d83b7df2de4b09dd03176391964fa25cae046", "abb2a6d6e6904cd43deb9e2c8ec4b7d02597eccb", - "2ba20bd1955a16b23b24025f580d5873c425f420", "6da1284b78ac00f2f53df42547fed0e2c9d1fe15", - "293edb3e3e77950d6f2c2d35af601aec81aa65ea", "edddfacc53bda442bd19834f96597549942c51bf", - "a9de735ebebe9ad9e5e40edf11aee2222bcbc64b", "3b9b7ab7101a19832204be06498f28bc2b1eb6f0", - "e8e05ee85693562744e35b07300191c0fe3535fe", "aa64beaac06e1cd9b7351a90bf6938925f183dce", - "faae18cae6868a535666e3fafa89795dae4ab4ca", "c0e3af4a8b831af93a29d065e9aaf47f65872e64", - "aaf78bf6e62795356e9fee152797fbfa0df63431", "44d071bed7e256b42081cdb5b8f8f901871ca814", - "24a2b38efaae2f843f6ea2e12931ee08b50b28f0", "54cef1220c285c348c07827b78437dcc78a7d1d8", - "038a3994227ab8e272cbc522a19423805e785965", "cd30166c95121eeb42089e0a5232bfef92897db5", - "90714936a735e9dc3f357d4f305a336e6c150657", "f2eacfe8657dfc1c08d037ecd4f4927969566ffa", - "5b90a912b110dac1d53ea2a3b90de7b6489b2854", "0b9b80df76668ec8dafb82b58a8719156a5364f8", - "9559fd1280bc82b46d8fb577e64051c356b2d7ae", "eec8a74c5dbf04b7eab0d1718e695664382a0d99", - "373e6ee68eae05c29125f2ce7faf3f471f6a9fa9", "77192fbb2111d35b9832760de5c6bca67699e2c4", - "79da714069c63482925568e98367f14545fd04b5", "0a5cf1cb82b7d6c42a1df9a3020564a1bd3e9466", - "512d96d689efdf47b816ebb4a0122db26a22ea2b", "ee2cd357d6f796396402657086acd7db7f397cae", - "414232aa7f80620feae4b9b9115840d48d90d89b", "c0695cf0ec9c5756abcf9374f533615f06053d4c", - "b67e102b0ab38b4fd7111c8ccd84de9e0f53d8d0", "d883383bede721c0040586d6ee7430468c07fd05", - "9aabc7ece7bf957f7d8d6beae5ff1720180f7c79", "0d67470db467538f061e6356714cdd461cb9cbe2", - "ef529b6a77117c651541de32c2505f76307444d5", "2d9dd11a3e5820bebdb0ae3786d3b6f3ff639f9c", - "b91974301a875595e455b29433eb00fd278037f6", "fa5eae0c00fd4d4e494631eba2c6a4f695097462", - "75d795314c210f32d27f23706334c2f1d4522818", "14599fe1d9c66e058095b318cb2c8361867eff76", - "a1032508521f4967a5d1cdf9d1330afce97b7a4e", "98de10b6e8b44e13f65010cbf170f2b448728c46", - "ad0b18fd250e8e2b0e78f8405b4323a4abb3f7ce", "322aba85bbf0b75948cc97ef750d405710a8c9f1", - "1ea8e1bb3de83cf0021af6488d06710aa6835d7b", "86316b6622c23ef4f702289b8ada30ab50417f2d", - "6d673760205b29d0fb9f22e40ea93af32382cf05", "2be97f0d6d60e962c3d9bdeda1cd1d87ae27d90e", - "18cfbbaec2091ec71b22e29abbb782d39dfd822e", "2ce4b0a7a206928c88c24f1ccc7e3d26e3a42dc1", - "9692b2145b1eed391cc8fac85f2cf3c62ee726b7", "f1d2694cdbbe02c137a30cc1e11fd616d37004c2", - "4d7cbf8a715b16c1e4acedd15d2f50f0e316a09d", "04c860819c06c0ac8101985face4492e33f95b20", - "01ea0bdb6a8da5b10001bbe9637d38185063b553", "c6b0836ae73ddd088f32167228c6691978193809", - "42a98df6e52abf067f96ecda4aa830cff0a8209e", "9dc0ec09029c8a6430bbe4eaf0be495ea2fb465c", - "0b24b71e70566e86411e18afc6058b64ff1d5a33", "664a2c715b1b9c55e04b2b8a2935e7c9414af30a", - "6d4dc412387871633c605b628f48b128b993cf3b", "ee5ee654101d5cb985e0b4d73aff7c61ebb4e0e5", - "f5eb3d61d52b51f16d7a1e5a23f25daa0b975dfb", "7e34b6c5ce03487fb17e459ad2b0076f5a8c371a", - "2ec46155cef251efc1ba898e8b6097da77fede3a", "c57e41d3e9a003cdc90db2f03bf3d15662fb00e4", - "6d9e16649b5e8dd0a3968bd573c668260005bd48", "60e9455d95786206764d6bed2d689f6e282e40f4", - "1d4014e9f95080c6accac7756148301c4443155e", "a42ee177d3f5ff6737efa701d90e257e4cf527ca", - "760ca68601182c86b1a41a7ff0a6c467ccc3d0d2", "e9145b2a1269da56e5ac4418339b3c18135601b1", - "798d296f70a1f39801be7bad13736b6a1806b0c0", "ffb0222b379ccebe04a7d893fc1d15a3cc23d864", - "13037016264f48d707a147eef128afec502a646d", "0c624b2b0bcc7b0c13d9743f76ba359fbeb82a8f", - "80ad9a45ea68da615c1d8cb5e110d667710b4a61"], "public": false}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '53435' - Content-Type: - - application/json - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://www.braintrust.dev/api/experiment/register - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//7FrpctvIEX6VKewPShEAASDAK5Fjl9db6yrH64q0SVVEF2s4GIhYgQCC - GUjiuvx3HyCPmCdJz4GThylZ/pMyLZnCoKev6fl6uoFPRl5kv1HCjdknIw6NmeHQsT/xncAKydC3 - fH8SWpNoiS0aReHUGQejcBwYppEVNwtJHyzxKPQnnrX0x4Hlk9HImpDQs4KJG4ym/njk0yHQp3hN - gZrF6zyh1hrzlUXvcAJ3SEExp4KV53iB5TqWN71yJ7NgOgsCO3CG/wKikCYUiBYYFE3LJDGNktFC - aTAJAn8yJCNrNIkcyw8j38KuP7bCaLr0KR561CHAglHO4/SGKQafTYM+5LSI1zRtjPdcbwQOWFpD - 6oLxkQfGk4haIzdy/WBIhuOpB6y0zxaPcZh2AFjOzwtqueOROxmOvelQWsdIEec8ztLKvG2vDJ0r - N5i5/izw7CAYCa8UNM8WcRplwgCSrdcxmGIMJxQ8v1xOxtPlNMAOARd41MPBGFShSx/TpTPySQgM - lgVOyapRC4Y4vql0COOCb4wZL0pqGrjkq6xYaDP+BvToAy3ymNwa9U26xnGiub0E3nEKcxkPMcc2 - qCcWWyq5WFPG8I1gRBKKU1TmKKTL8gZlJc9L3hDyWIpr+8CducOZ41mOP3McoLwBsjCOIiATX8iy - YATh83xzzgpy3qhxHtI7CJo7WpxzyvhC/Q3+4/SmwML5dr5ByydOnKdxGtIHNHHHLvGc5cS2o8nQ - IyF2KXId8Lg/Ty3LerJm8/Ts7Owr1Hv5ElnuMDBdH53J7xGCoZBGKMcFowsGv/QOdgM7KSjLsxSu - OX3gM8R4cYqsFyiJGb8OY8KvYcREr9LNx4+zeYrUz8t8I8Tba1zc2nekAGsFc6mS2OqNgEVWhLQ4 - IUkMFybCeby4pRsTCUwR8XUKTM+254JQitewhQ/PROIzN+S/1BIXV8AG8RXm6PLyDVI2oihLkuwe - hikiWVHAdkZSLWEuLjj67x//QbDPb8AX7E/yipVrsG0j/w6zlNrAvpKwipnUFoHn4yimTMkT3AeS - 30DJRUCHk3u8YfJeFBcwR99J5ZCy0tSM71cxWYlJgA88JjgBvQtJ9+tbxDOhIYBYsoHZcB8n8e8U - 4TREYczyBG9qC9q6/vz2El29ubxClz//8uu7H9FPr96+Q0sKjIVCD+BgKaDARLgmDWMRQkK9LF1I - WxZRCvzOBLPX2Tov6IqmLL6jygNCQeHnerlQWBbiSywkog+UlDImgYNm8g/ts5m+dm30RrrkkQui - p3s2+qDpqsXGYBoFPAFE1URDG11Ktsr5K8zQmnIsoAqdNJnhPQSViTTei4tTPd+H+Vp8w4EAQfIa - M+FHmoQMnaQZRyzFt3RBYLiaHNjo73qLCXcBXMolVmHYi2B5UW1IdIFU7Nt5xviJvqvIz4V/54ap - d/poZPpT2OmjiTkcVzv9iZtRSsAwBfxVqWKvKIaJ7HpuvM4AalJuXW1yOjc+oosLUEdAx7mUYKlI - +DMiKwE0/KLkkTWRtmnWepUu9iORLdidyiBuZiw4CBTTriloIYeEeBGAVMSr4vFRypF+/0GFWrVk - 0vKudQlNT1q8T9EL5JhgzeUqK5MQFhmiHAsyDJEOIYe01C6XFodrR/tDBjEsD4rmxk+tbc8U52UN - FCZalhzdQOAMPnUZfR4cEmS5WpLcCkrQO7xLjiDYKwbYbMsB9VWwz43asYq+5RzACg45CexQtIOW - czT2KPhQCl2gFNb0hPbXC8UR6qxn232nFSMl4mmsKlNO+2GR92CDPkDG00TVvUUdrNdHyqtmwoDm - 1Qq2Htt+wAnQ2lIrKrI14pjdNmjadnK9Zl0YU0vXWgFQVMAdqCUFttCQdRe04VNjZJ1ba2EtjHy6 - JM0EpZJLf3nYHsDWdM8RXGff2IHv24Z9E99VEqpo+KGXp2SGI3DmBiR4LxBMiMvWkOohQTGFCnEb - LiC/M+Gs/mJ8MftVy/JMW7WNR12ekDtFnhXWSB91NNs2xOgpJj1y0eXZeL27Vp05B+VKCi1cUGl3 - 66XRvoRDnIgNwre8J7cAOyogWyq11WCtlDXoThygk1rc6THheIyI1qwv8Gdw0gHbjmetJgyUZ6rg - Pqre6MHr4WOO3C/q3NWUDH3wbR0lq4NtfdK1O2XH3kObvKtkNYe2elCfqy4+tcYU8YO15JYotS2e - 3VLA/Fltx25aMM5SUDqrDd0m7R7fZjCC8zyBYkMklvPfmMgu27NeEUJzrui3znrdCZ/bF4LfDtsq - NedbLaJdwispM3QlmhNb99XenaHr3h3x+TQ34jQvter/XKnDt3fm/VUcmtQeI6JQkPf9ufG5z38/ - l+HZcCeX0Q4uH3e66LQp1OqDxpdPxYL8mQ4olfRvc0bRuKdnvv/lSu3wpkTq5o4dwLdQkSIx9cv4 - Iaj6EgY9ZoO9CPgMstqcBlXNs7NbIqo2b+iY0wk68zzHHG0XbbQosmKxggI/Oa4NUhskdIuyMg31 - AV4wEnEgvmHZ7SS7hyLwtFLvILiKQNQNvIWqXhfwS1aUqZJAtjKPRlp90QDuhw1fZeBsmkIBLRoJ - WharOiT0AcMRkQGrqniGw4cAr0speWdbhuCclwVlurNxLxnXAC06JlXjptLOtdGrJGmjvj4/6H6E - 2TQjzCoyTN2GkAw8G73BZNU6ILV7TUpzgQ3y/gz9RfjuxRw+qYgvGBBIqQbUf5WrhjYYRo86gEl6 - X9GHdbnadI04LSBvYa4do2F1x/J8z2X68/+Wy76YhfptHwh+XrIFyUIqsofnOPOnZix57+gmTiWk - 18Rh9N8lTQntqtti/ZQOjGiL9Jsv/ZK3ffvRvZctAaLtsl1UH9F1URmnjQWSTd9ZFcUBnHiuQq1t - wp6ial/pdKBo6jrmUCHUk7Wvqmi8sF2ed4XtrYceLalXo1vq52CybYuC1A87T3ATh4uFWr2nZ1q+ - lUV0L2FHJxszVIEJWm70E4h+qm0/p1hSgkuYr59VHCxzURLfbhepFRh1KksTUU5s9DbSz0+UcoVq - Y9TnLrMSS3Aq4kjikRhbi1yv+aqzRN3auo8h3UO2oLiARFiSW8GygmdR3NlQ3oncz+kTnqbog1Ll - bvBQIlWWz+rsfGPvWqrvWVd/vmfdXVlXED4i5c4PwPzjcd6UyHwI7rdAvv0MZX/K6rTYDrTldsn9 - qrZckzOvjsCsrgLfrjV3ZCp6cmuuy//rW3ONF48o8ve58BkK711F/k5fPoOsrSJfJfYdRX6voL+P - +UpKYlS8TQT7WyAX3IdEAejIWFQmyeaIQl+lDQCap70GJE4T4DD5QpN+92frhatGzf4IZDDWenUp - L5eA/cYswglk4se/qFU91qn4cVy/tPX5fwAAAP//AwDiTwj5sCYAAA== - headers: - Cache-Control: - - public, max-age=0, must-revalidate - Content-Encoding: - - gzip - Content-Security-Policy: - - 'script-src ''self'' ''unsafe-eval'' ''wasm-unsafe-eval'' ''strict-dynamic'' - ''nonce-YmMzOTc4NDktYzcxMy00ZmFiLThlMDktNWM0YTYwYzM0NjU3'' *.js.stripe.com - js.stripe.com maps.googleapis.com ; style-src ''self'' ''unsafe-inline'' *.braintrust.dev - btcm6qilbbhv4yi1.public.blob.vercel-storage.com fonts.googleapis.com www.gstatic.com - d4tuoctqmanu0.cloudfront.net; font-src ''self'' data: fonts.gstatic.com btcm6qilbbhv4yi1.public.blob.vercel-storage.com; - object-src ''none''; base-uri ''self''; form-action ''self''; frame-ancestors - ''self''; worker-src ''self'' blob:; report-uri https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15; - report-to csp-endpoint-0' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 15:14:52 GMT - Etag: - - W/"k2orjbigav7ms" - Reporting-Endpoints: - - csp-endpoint-0="https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15" - Server: - - Vercel - Strict-Transport-Security: - - max-age=63072000 - Transfer-Encoding: - - chunked - X-Clerk-Auth-Message: - - Invalid JWT form. A JWT consists of three parts separated by dots. (reason=token-invalid, - token-carrier=header) - X-Clerk-Auth-Reason: - - token-invalid - X-Clerk-Auth-Status: - - signed-out - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-Matched-Path: - - /api/experiment/register - X-Nonce: - - YmMzOTc4NDktYzcxMy00ZmFiLThlMDktNWM0YTYwYzM0NjU3 - X-Vercel-Cache: - - MISS - X-Vercel-Id: - - iad1::iad1::j6dfl-1761837292348-cf8af5bac89a - status: - code: 200 - message: OK -- request: - body: '{"rows": [{"id": "3fa51eff-2d3f-4107-a751-55edc214b4ed", "span_id": "5942c0fb-85cf-4b01-bd64-73962df090c3", - "root_span_id": "5942c0fb-85cf-4b01-bd64-73962df090c3", "span_parents": null, - "metrics": {"start": 1761837292.69887}, "span_attributes": {"type": "eval", - "name": "eval", "exec_counter": 1}, "created": "2025-10-30T15:14:52.698882+00:00", - "context": {"caller_functionname": "_run", "caller_filename": "/Users/matt/.local/share/mise/installs/python/3.9.24/lib/python3.9/asyncio/events.py", - "caller_lineno": 80}, "input": "What is 2+2?", "expected": "4", "_is_merge": - false, "experiment_id": "21260e7b-3e14-4f2d-8cfe-61f1453c3792"}], "api_version": - 2}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '655' - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://api.braintrust.dev/logs3 - response: - body: - string: !!binary | - H4sIAAAAAAAAAwXBwQqAMAgA0H/xnKCmW+1XImLNCTvXIYj+vfdeGH5B2WCOatwjUHwOVKaMNRuj - WfcmrKd2h32Cp7b7GA4FmIh4TWSJhBfNpALfD0CtHJlQAAAA - headers: - Connection: - - keep-alive - Content-Length: - - '93' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 15:14:53 GMT - Via: - - 1.1 e80aeefdda01afc3c41fc332ff42e7ac.cloudfront.net (CloudFront), 1.1 76d4de5b65bdf749a3f97445d1b9f4d2.cloudfront.net - (CloudFront) - X-Amz-Cf-Id: - - LqLfEL5QqqtmzvIYxxCJ_zyC7F3IbRttpjb3QjBDqq1F6WfWp9DBwA== - X-Amz-Cf-Pop: - - JFK50-P5 - - JFK50-P2 - X-Amzn-Trace-Id: - - Root=1-690380ec-1f0ffb461d06d6b67e000a47;Parent=4d3bae85527cf344;Sampled=0;Lineage=1:24be3d11:0 - X-Cache: - - Miss from cloudfront - access-control-allow-credentials: - - 'true' - access-control-expose-headers: - - x-bt-cursor,x-bt-found-existing,x-bt-query-plan - content-encoding: - - gzip - etag: - - W/"50-V1T/emJm7xRJIXFefwtxs5MKM7M" - vary: - - Origin, Accept-Encoding - x-amz-apigw-id: - - TREVDEmRIAMEtYg= - x-amzn-RequestId: - - 155e9532-a0dd-4f3f-843c-d206b620fd81 - x-bt-internal-trace-id: - - 690380ec000000002f68a21f826ad984 - status: - code: 200 - message: OK -- request: - body: '{"rows": [{"id": "76f312a6-5896-4fbc-9f91-319a493f8254", "metrics": {"start": - 1761837292.700928, "end": 1761837292.7026}, "span_attributes": {"type": "task", - "name": "task", "exec_counter": 2}, "context": {"caller_functionname": "_run", - "caller_filename": "/Users/matt/.local/share/mise/installs/python/3.9.24/lib/python3.9/asyncio/events.py", - "caller_lineno": 80}, "experiment_id": "21260e7b-3e14-4f2d-8cfe-61f1453c3792", - "input": "What is 2+2?", "output": "4", "created": "2025-10-30T15:14:52.700931+00:00", - "span_id": "01e26b8c-185a-4220-91c4-c864b5f28448", "root_span_id": "5942c0fb-85cf-4b01-bd64-73962df090c3", - "span_parents": ["5942c0fb-85cf-4b01-bd64-73962df090c3"]},{"id": "3fa51eff-2d3f-4107-a751-55edc214b4ed", - "output": "4", "metadata": {}, "_is_merge": true, "experiment_id": "21260e7b-3e14-4f2d-8cfe-61f1453c3792", - "metrics": {"end": 1761837292.7094321}, "span_id": "5942c0fb-85cf-4b01-bd64-73962df090c3", - "root_span_id": "5942c0fb-85cf-4b01-bd64-73962df090c3", "span_parents": null},{"id": - "f1d96e99-9119-49ec-8014-9c14a7d7e8a9", "metrics": {"start": 1761837292.7028182, - "end": 1761837292.710861}, "span_attributes": {"type": "eval", "name": "eval", - "exec_counter": 3}, "context": {"caller_functionname": "_run", "caller_filename": - "/Users/matt/.local/share/mise/installs/python/3.9.24/lib/python3.9/asyncio/events.py", - "caller_lineno": 80}, "input": "What is 3+3?", "expected": "6", "experiment_id": - "21260e7b-3e14-4f2d-8cfe-61f1453c3792", "output": "6", "metadata": {}, "created": - "2025-10-30T15:14:52.702822+00:00", "span_id": "16a5f348-4fd7-4695-8100-cdacf4b08102", - "root_span_id": "16a5f348-4fd7-4695-8100-cdacf4b08102", "span_parents": null},{"id": - "b28213d2-ac58-403b-8453-19cfb6432f4e", "metrics": {"start": 1761837292.703093, - "end": 1761837292.703538}, "span_attributes": {"type": "task", "name": "task", - "exec_counter": 4}, "context": {"caller_functionname": "_run", "caller_filename": - "/Users/matt/.local/share/mise/installs/python/3.9.24/lib/python3.9/asyncio/events.py", - "caller_lineno": 80}, "experiment_id": "21260e7b-3e14-4f2d-8cfe-61f1453c3792", - "input": "What is 3+3?", "output": "6", "created": "2025-10-30T15:14:52.703095+00:00", - "span_id": "c98c1ccb-996c-47dd-8f45-4a9e01e98210", "root_span_id": "16a5f348-4fd7-4695-8100-cdacf4b08102", - "span_parents": ["16a5f348-4fd7-4695-8100-cdacf4b08102"]},{"id": "aaa21495-09b2-44aa-a669-95ebc1490519", - "metrics": {"start": 1761837292.7055721, "end": 1761837292.7091331}, "span_attributes": - {"type": "score", "name": "scorer", "exec_counter": 5}, "context": {"caller_functionname": - "_run", "caller_filename": "/Users/matt/.local/share/mise/installs/python/3.9.24/lib/python3.9/asyncio/events.py", - "caller_lineno": 80}, "input": {"input": "What is 2+2?", "expected": "4", "metadata": - {}, "output": "4"}, "experiment_id": "21260e7b-3e14-4f2d-8cfe-61f1453c3792", - "output": {"score": 1.0}, "metadata": {}, "scores": {"scorer": 1.0}, "created": - "2025-10-30T15:14:52.705577+00:00", "span_id": "d4c9c6d2-dfdc-4a99-a26c-43dd43d7c51b", - "root_span_id": "5942c0fb-85cf-4b01-bd64-73962df090c3", "span_parents": ["5942c0fb-85cf-4b01-bd64-73962df090c3"]},{"id": - "702a9c38-e137-4a67-9e4d-54b921be5a94", "metrics": {"start": 1761837292.707482, - "end": 1761837292.709783}, "span_attributes": {"type": "score", "name": "scorer", - "exec_counter": 6}, "context": {"caller_functionname": "_run", "caller_filename": - "/Users/matt/.local/share/mise/installs/python/3.9.24/lib/python3.9/asyncio/events.py", - "caller_lineno": 80}, "input": {"input": "What is 3+3?", "expected": "6", "metadata": - {}, "output": "6"}, "experiment_id": "21260e7b-3e14-4f2d-8cfe-61f1453c3792", - "output": {"score": 1.0}, "metadata": {}, "scores": {"scorer": 1.0}, "created": - "2025-10-30T15:14:52.707488+00:00", "span_id": "95f791e4-655b-4404-bf8b-662f647fa377", - "root_span_id": "16a5f348-4fd7-4695-8100-cdacf4b08102", "span_parents": ["16a5f348-4fd7-4695-8100-cdacf4b08102"]}], - "api_version": 2}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '3917' - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://api.braintrust.dev/logs3 - response: - body: - string: !!binary | - H4sIAAAAAAAAAxXMS0pAMQwF0L1k/C40adL2uhURSX/gWAeCuHfxLOD8yMf+lJdX6e1WtWyIwQa/ - c4GXiqpMZ73DwuWRejP03Avb9cK1dGQPRcTZy9Snny2PXN1shwRVCedZGEUdXOrZdz8jKY9MG6Z1 - G3LFgJc6MTwqlOvO5tWuH3kkM02dgcJpcM9EtkYwzlzqLKH/Wy+WXHXgaO3wbB08vhE+aTpPJF3e - HvnO9fX+seVFtJSibCVaMR3eTZv8/gHB238/EwEAAA== - headers: - Connection: - - keep-alive - Content-Length: - - '202' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 15:14:53 GMT - Via: - - 1.1 b5fe18267507cb61755963d8928a60f4.cloudfront.net (CloudFront), 1.1 76d4de5b65bdf749a3f97445d1b9f4d2.cloudfront.net - (CloudFront) - X-Amz-Cf-Id: - - dYv-mmsoaoHrBRa-VTICofXpSAvYfsiBuee7Z26grL3_c1EQjuMSiQ== - X-Amz-Cf-Pop: - - JFK50-P5 - - JFK50-P2 - X-Amzn-Trace-Id: - - Root=1-690380ed-4eeab5573db34056590b97a5;Parent=5195c3917cdef836;Sampled=0;Lineage=1:24be3d11:0 - X-Cache: - - Miss from cloudfront - access-control-allow-credentials: - - 'true' - access-control-expose-headers: - - x-bt-cursor,x-bt-found-existing,x-bt-query-plan - content-encoding: - - gzip - etag: - - W/"113-TSF5yHGTkNsNSmz7EotHhns6FNk" - vary: - - Origin, Accept-Encoding - x-amz-apigw-id: - - TREVHF--oAMERFg= - x-amzn-RequestId: - - 00a87697-739f-45a2-9119-21642367cc96 - x-bt-internal-trace-id: - - 690380ed000000004fe0953e2057521a - status: - code: 200 - message: OK -- request: - body: '{"id": "21260e7b-3e14-4f2d-8cfe-61f1453c3792"}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '46' - Content-Type: - - application/json - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://www.braintrust.dev/api/base_experiment/get_id - response: - body: - string: '{"id":"21260e7b-3e14-4f2d-8cfe-61f1453c3792","project_id":"0e748405-dc34-448d-8fba-effd90756d75","name":"matt/re-1761837293","base_exp_id":"91e6b5a2-2bc6-43c4-ade1-eb111361a8a3","base_exp_name":"matt/re-1761834844"}' - headers: - Cache-Control: - - public, max-age=0, must-revalidate - Content-Length: - - '215' - Content-Security-Policy: - - 'script-src ''self'' ''unsafe-eval'' ''wasm-unsafe-eval'' ''strict-dynamic'' - ''nonce-MzUzMDY5NDktNmQ5MC00YTJiLWJkNWYtNzc3N2ZiOGVkMTk1'' *.js.stripe.com - js.stripe.com maps.googleapis.com ; style-src ''self'' ''unsafe-inline'' *.braintrust.dev - btcm6qilbbhv4yi1.public.blob.vercel-storage.com fonts.googleapis.com www.gstatic.com - d4tuoctqmanu0.cloudfront.net; font-src ''self'' data: fonts.gstatic.com btcm6qilbbhv4yi1.public.blob.vercel-storage.com; - object-src ''none''; base-uri ''self''; form-action ''self''; frame-ancestors - ''self''; worker-src ''self'' blob:; report-uri https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15; - report-to csp-endpoint-0' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 15:14:53 GMT - Etag: - - '"37gswqpph45z"' - Reporting-Endpoints: - - csp-endpoint-0="https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15" - Server: - - Vercel - Strict-Transport-Security: - - max-age=63072000 - X-Clerk-Auth-Message: - - Invalid JWT form. A JWT consists of three parts separated by dots. (reason=token-invalid, - token-carrier=header) - X-Clerk-Auth-Reason: - - token-invalid - X-Clerk-Auth-Status: - - signed-out - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-Matched-Path: - - /api/base_experiment/get_id - X-Nonce: - - MzUzMDY5NDktNmQ5MC00YTJiLWJkNWYtNzc3N2ZiOGVkMTk1 - X-Vercel-Cache: - - MISS - X-Vercel-Id: - - iad1::iad1::bq7gh-1761837293446-61662ee42a79 - status: - code: 200 - message: OK -- request: - body: null - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - User-Agent: - - python-requests/2.32.5 - method: GET - uri: https://api.braintrust.dev/experiment-comparison2?experiment_id=21260e7b-3e14-4f2d-8cfe-61f1453c3792&base_experiment_id=91e6b5a2-2bc6-43c4-ade1-eb111361a8a3 - response: - body: - string: !!binary | - H4sIAAAAAAAAA62Q227CMAxA/8XP0dQy2Ep+poqCtUUkceUYXlD/HbUMlirsQsubcxydo+QEyRJj - An26TDxM0QQEfQXqMoCuFbjQMR0xYJQEulLA+MGYkqM4nPteQUBhZ0ej96G1xvuUSb/Z9eroOUQn - oAH+TigQIl94MzhbjMzEufQLzBYOjy2kGVz2BYU5p7PVHVPopBXaY8zlU35PL7R/pGCN/cTdj6Hp - +lm91jIacRR/7xbXlvQthc7j/Wi5W1ISEuPLyAQv8e8OPP5K5r6hzPtSVXW1adab7aqpt6v6tXl7 - v7XSP0p9fwa9VYRgmQQAAA== - headers: - Connection: - - keep-alive - Content-Length: - - '244' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 15:14:54 GMT - Via: - - 1.1 68f2eed06d7ecb02b863cacb0da2fc28.cloudfront.net (CloudFront), 1.1 76d4de5b65bdf749a3f97445d1b9f4d2.cloudfront.net - (CloudFront) - X-Amz-Cf-Id: - - vLF9GGzE7AMZBFaWPCJirv5ur5S6ExB1oyCODJtihYJYSLdegfc_gA== - X-Amz-Cf-Pop: - - JFK50-P5 - - JFK50-P2 - X-Amzn-Trace-Id: - - Root=1-690380ed-0462a9241db6b67e4dea944e;Parent=0e9a6b3214707c50;Sampled=0;Lineage=1:24be3d11:0 - X-Cache: - - Miss from cloudfront - access-control-allow-credentials: - - 'true' - access-control-expose-headers: - - x-bt-cursor,x-bt-found-existing,x-bt-query-plan - content-encoding: - - gzip - etag: - - W/"499-AIbqeKAtyP2Nv/u49yv/rayBkuM" - vary: - - Origin, Accept-Encoding - x-amz-apigw-id: - - TREVLGoOoAMEeMA= - x-amzn-RequestId: - - f6ef9349-116a-46ff-b2fb-301427a5e62f - x-bt-internal-trace-id: - - 690380ed0000000062b4d5dc47ea4d0d - status: - code: 200 - message: OK -- request: - body: '{"name":"simple-math-eval","stream":true,"data":[{"input":"What is 2+2?","expected":"4"},{"input":"What - is 3+3?","expected":"6"}]}' - headers: - accept: - - text/event-stream - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '130' - content-type: - - application/json - host: - - testserver - user-agent: - - testclient - x-bt-org-name: - - matt-test-org - method: POST - uri: http://testserver/eval - response: - body: - string: "event: start\ndata: {\"projectName\": \"simple-math-eval\", \"projectId\": - \"0e748405-dc34-448d-8fba-effd90756d75\", \"experimentId\": \"21260e7b-3e14-4f2d-8cfe-61f1453c3792\", - \"experimentName\": \"matt/re-1761837293\", \"projectUrl\": \"https://www.braintrust.dev/app/matt-test-org/p/simple-math-eval\", - \"experimentUrl\": \"https://www.braintrust.dev/app/matt-test-org/p/simple-math-eval/experiments/matt%2Fre-1761837293\"}\n\nevent: - progress\ndata: {\"id\": \"3fa51eff-2d3f-4107-a751-55edc214b4ed\", \"origin\": - null, \"name\": \"simple-math-eval\", \"object_type\": \"task\", \"format\": - \"code\", \"output_type\": \"completion\", \"event\": \"json_delta\", \"data\": - \"\\\"4\\\"\"}\n\nevent: progress\ndata: {\"id\": \"f1d96e99-9119-49ec-8014-9c14a7d7e8a9\", - \"origin\": null, \"name\": \"simple-math-eval\", \"object_type\": \"task\", - \"format\": \"code\", \"output_type\": \"completion\", \"event\": \"json_delta\", - \"data\": \"\\\"6\\\"\"}\n\nevent: summary\ndata: {\"projectName\": \"simple-math-eval\", - \"projectId\": \"0e748405-dc34-448d-8fba-effd90756d75\", \"experimentId\": - \"21260e7b-3e14-4f2d-8cfe-61f1453c3792\", \"experimentName\": \"matt/re-1761837293\", - \"projectUrl\": \"https://www.braintrust.dev/app/matt-test-org/p/simple-math-eval\", - \"experimentUrl\": \"https://www.braintrust.dev/app/matt-test-org/p/simple-math-eval/experiments/matt%2Fre-1761837293\", - \"comparisonExperimentName\": \"matt/re-1761834844\", \"scores\": {\"scorer\": - {\"name\": \"scorer\", \"score\": 1, \"improvements\": 0, \"regressions\": - 0}}, \"metrics\": {\"llm_calls\": {\"name\": \"llm_calls\", \"_longest_metric_name\": - 28, \"metric\": 0, \"unit\": \"\", \"improvements\": 0, \"regressions\": 0, - \"diff\": null}, \"tool_calls\": {\"name\": \"tool_calls\", \"_longest_metric_name\": - 28, \"metric\": 0, \"unit\": \"\", \"improvements\": 0, \"regressions\": 0, - \"diff\": null}, \"errors\": {\"name\": \"errors\", \"_longest_metric_name\": - 28, \"metric\": 0, \"unit\": \"\", \"improvements\": 0, \"regressions\": 0, - \"diff\": null}, \"llm_errors\": {\"name\": \"llm_errors\", \"_longest_metric_name\": - 28, \"metric\": 0, \"unit\": \"\", \"improvements\": 0, \"regressions\": 0, - \"diff\": null}, \"tool_errors\": {\"name\": \"tool_errors\", \"_longest_metric_name\": - 28, \"metric\": 0, \"unit\": \"\", \"improvements\": 0, \"regressions\": 0, - \"diff\": null}, \"prompt_tokens\": {\"name\": \"prompt_tokens\", \"_longest_metric_name\": - 28, \"metric\": 0, \"unit\": \"tok\", \"improvements\": 0, \"regressions\": - 0, \"diff\": null}, \"prompt_cached_tokens\": {\"name\": \"prompt_cached_tokens\", - \"_longest_metric_name\": 28, \"metric\": 0, \"unit\": \"tok\", \"improvements\": - 0, \"regressions\": 0, \"diff\": null}, \"prompt_cache_creation_tokens\": - {\"name\": \"prompt_cache_creation_tokens\", \"_longest_metric_name\": 28, - \"metric\": 0, \"unit\": \"tok\", \"improvements\": 0, \"regressions\": 0, - \"diff\": null}, \"completion_tokens\": {\"name\": \"completion_tokens\", - \"_longest_metric_name\": 28, \"metric\": 0, \"unit\": \"tok\", \"improvements\": - 0, \"regressions\": 0, \"diff\": null}, \"total_tokens\": {\"name\": \"total_tokens\", - \"_longest_metric_name\": 28, \"metric\": 0, \"unit\": \"tok\", \"improvements\": - 0, \"regressions\": 0, \"diff\": null}, \"duration\": {\"name\": \"duration\", - \"_longest_metric_name\": 28, \"metric\": 0.0010584592819213867, \"unit\": - \"s\", \"improvements\": 0, \"regressions\": 0, \"diff\": null}}}\n\nevent: - done\ndata: \n\n" - headers: - cache-control: - - no-cache - connection: - - keep-alive - content-type: - - text/event-stream; charset=utf-8 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/devserver/cassettes/test_eval_with_dataset_id_completes_successfully.yaml b/py/src/braintrust/devserver/cassettes/test_eval_with_dataset_id_completes_successfully.yaml deleted file mode 100644 index 27fa5cd0a..000000000 --- a/py/src/braintrust/devserver/cassettes/test_eval_with_dataset_id_completes_successfully.yaml +++ /dev/null @@ -1,1425 +0,0 @@ -interactions: -- request: - body: null - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - User-Agent: - - python-requests/2.32.5 - method: GET - uri: https://api.braintrust.dev/v1/dataset/f1423e15-4b70-4c62-9760-42c61eea29d9 - response: - body: - string: '{"id":"f1423e15-4b70-4c62-9760-42c61eea29d9","project_id":"be859ba0-1274-4df9-8261-68b52806558c","name":"Dataset - 1","description":null,"created":"2025-10-29T17:03:15.632Z","deleted_at":null,"user_id":"855483c6-68f0-4df4-a147-df9b4ea32e0c","metadata":null}' - headers: - Connection: - - keep-alive - Content-Length: - - '204' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 14:13:31 GMT - Via: - - 1.1 53a1f042d35b1ad7e45dd18908041b36.cloudfront.net (CloudFront), 1.1 bd3e3884ce6fe1fd36336541cce9ec7e.cloudfront.net - (CloudFront) - X-Amz-Cf-Id: - - PDpcgczG5dsho4__HhyyhTWQ4A0QqNbuqAzM7kqAR3qiynn4Io5A2w== - X-Amz-Cf-Pop: - - JFK50-P5 - - JFK50-P2 - X-Amzn-Trace-Id: - - Root=1-6903728a-7e1a6ef9405a1d224d67009a;Parent=24358e2b87a9904b;Sampled=0;Lineage=1:24be3d11:0 - X-Cache: - - Miss from cloudfront - access-control-allow-credentials: - - 'true' - access-control-expose-headers: - - x-bt-cursor,x-bt-found-existing,x-bt-query-plan - content-encoding: - - gzip - etag: - - W/"ff-UE8UxnaCqYIExTQrbR9Yfm1FhR8" - vary: - - Origin, Accept-Encoding - x-amz-apigw-id: - - TQ7VwEu_IAMEEcQ= - x-amzn-RequestId: - - 39a0c8df-9b6a-49b3-aac0-88184d9534a4 - x-bt-internal-trace-id: - - 6903728a0000000056f39397b33220be - status: - code: 200 - message: OK -- request: - body: '{"project_name": null, "project_id": "be859ba0-1274-4df9-8261-68b52806558c", - "org_id": "5ba6d482-b475-4c66-8cd2-5815694764e3", "dataset_name": "Dataset 1"}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '155' - Content-Type: - - application/json - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://www.braintrust.dev/api/dataset/register - response: - body: - string: '{"project":{"id":"be859ba0-1274-4df9-8261-68b52806558c","org_id":"5ba6d482-b475-4c66-8cd2-5815694764e3","name":"remote-eval-test","created":"2025-10-29T17:00:07.602Z","deleted_at":null,"user_id":"855483c6-68f0-4df4-a147-df9b4ea32e0c","settings":{"remote_eval_sources":[{"url":"http://localhost:8300","name":"http://localhost:8300","description":null},{"url":"http://localhost:8301","name":"http://localhost:8301","description":null}]}},"dataset":{"id":"f1423e15-4b70-4c62-9760-42c61eea29d9","project_id":"be859ba0-1274-4df9-8261-68b52806558c","name":"Dataset - 1","description":null,"created":"2025-10-29T17:03:15.632Z","deleted_at":null,"user_id":"855483c6-68f0-4df4-a147-df9b4ea32e0c","metadata":null},"found_existing":true}' - headers: - Cache-Control: - - public, max-age=0, must-revalidate - Content-Length: - - '724' - Content-Security-Policy: - - 'script-src ''self'' ''unsafe-eval'' ''wasm-unsafe-eval'' ''strict-dynamic'' - ''nonce-NDBmNDEwMWQtYTc3My00MWU1LWI5ZjAtZTQ3MmI1ODlmZDNl'' *.js.stripe.com - js.stripe.com maps.googleapis.com ; style-src ''self'' ''unsafe-inline'' *.braintrust.dev - btcm6qilbbhv4yi1.public.blob.vercel-storage.com fonts.googleapis.com www.gstatic.com - d4tuoctqmanu0.cloudfront.net; font-src ''self'' data: fonts.gstatic.com btcm6qilbbhv4yi1.public.blob.vercel-storage.com; - object-src ''none''; base-uri ''self''; form-action ''self''; frame-ancestors - ''self''; worker-src ''self'' blob:; report-uri https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15; - report-to csp-endpoint-0' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 14:13:31 GMT - Etag: - - '"13eviqmtr1tk4"' - Reporting-Endpoints: - - csp-endpoint-0="https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15" - Server: - - Vercel - Strict-Transport-Security: - - max-age=63072000 - X-Clerk-Auth-Message: - - Invalid JWT form. A JWT consists of three parts separated by dots. (reason=token-invalid, - token-carrier=header) - X-Clerk-Auth-Reason: - - token-invalid - X-Clerk-Auth-Status: - - signed-out - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-Matched-Path: - - /api/dataset/register - X-Nonce: - - NDBmNDEwMWQtYTc3My00MWU1LWI5ZjAtZTQ3MmI1ODlmZDNl - X-Vercel-Cache: - - MISS - X-Vercel-Id: - - iad1::iad1::vprq8-1761833611231-169a4372aa3b - status: - code: 200 - message: OK -- request: - body: '{"query": {"select": [{"op": "star"}], "from": {"op": "function", "name": - {"op": "ident", "name": ["dataset"]}, "args": [{"op": "literal", "value": "f1423e15-4b70-4c62-9760-42c61eea29d9"}]}, - "cursor": null, "limit": 1000}, "use_columnstore": false, "brainstore_realtime": - true}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip - Connection: - - keep-alive - Content-Length: - - '277' - Content-Type: - - application/json - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://api.braintrust.dev/btql - response: - body: - string: '{"data":[{"_pagination_key":"p07566690732597968896","_xact_id":"1000196050791148460","created":"2025-10-29T17:04:33.010Z","dataset_id":"f1423e15-4b70-4c62-9760-42c61eea29d9","expected":null,"id":"34dc9bc0-9b0a-47fa-8eb5-426f18634232","input":"joe","is_root":true,"metadata":null,"origin":null,"project_id":"be859ba0-1274-4df9-8261-68b52806558c","root_span_id":"34dc9bc0-9b0a-47fa-8eb5-426f18634232","span_id":"34dc9bc0-9b0a-47fa-8eb5-426f18634232","tags":null},{"_pagination_key":"p07566690484853997568","_xact_id":"1000196050791546372","created":"2025-10-29T17:03:34.896Z","dataset_id":"f1423e15-4b70-4c62-9760-42c61eea29d9","expected":null,"id":"34b693a2-8943-44cd-8570-e84cc6c1470e","input":"matt","is_root":true,"metadata":null,"origin":null,"project_id":"be859ba0-1274-4df9-8261-68b52806558c","root_span_id":"34b693a2-8943-44cd-8570-e84cc6c1470e","span_id":"34b693a2-8943-44cd-8570-e84cc6c1470e","tags":null}],"schema":{"type":"array","items":{"type":"object","properties":{"id":{"type":"string","description":"A - unique identifier for the dataset event. If you don''t provide one, Braintrust - will generate one for you"},"_xact_id":{"type":"string","description":"The - transaction id of an event is unique to the network operation that processed - the event insertion. Transaction ids are monotonically increasing over time - and can be used to retrieve a versioned snapshot of the dataset (see the `version` - parameter)"},"created":{"type":"string","format":"date-time","description":"The - timestamp the dataset event was created"},"_pagination_key":{"type":["string","null"],"description":"A - stable, time-ordered key that can be used to paginate over dataset events. - This field is auto-generated by Braintrust and only exists in Brainstore."},"project_id":{"type":"string","format":"uuid","description":"Unique - identifier for the project that the dataset belongs under"},"dataset_id":{"type":"string","format":"uuid","description":"Unique - identifier for the dataset"},"input":{"description":"The argument that uniquely - define an input case (an arbitrary, JSON serializable object)"},"expected":{"description":"The - output of your application, including post-processing (an arbitrary, JSON - serializable object)"},"metadata":{"anyOf":[{"type":"object","properties":{"model":{"description":"The - model used for this example","type":["string","null"]}},"additionalProperties":{}},{"type":"null"}]},"tags":{"anyOf":[{"type":"array","items":{"type":"string"}},{"type":"null"}]},"span_id":{"type":"string","description":"A - unique identifier used to link different dataset events together as part of - a full trace. See the [tracing guide](https://www.braintrust.dev/docs/instrument) - for full details on tracing"},"root_span_id":{"type":"string","description":"A - unique identifier for the trace this dataset event belongs to"},"is_root":{"type":["boolean","null"],"description":"Whether - this span is a root span"},"origin":{"anyOf":[{"type":"object","properties":{"object_type":{"description":"Type - of the object the event is originating from.","enum":["project_logs","experiment","dataset","prompt","function","prompt_session"],"type":"string"},"object_id":{"description":"ID - of the object the event is originating from.","type":"string","format":"uuid"},"id":{"description":"ID - of the original event.","type":"string"},"_xact_id":{"description":"Transaction - ID of the original event.","type":["string","null"]},"created":{"description":"Created - timestamp of the original event. Used to help sort in the UI","type":["string","null"]}},"required":["object_type","object_id","id"],"description":"Reference - to the original object and event this was copied from."},{"type":"null"}]}}}},"cursor":"aQJI5+sNAAA","realtime_state":{"type":"on","minimum_xact_id":"1000196050791546372","read_bytes":0,"actual_xact_id":"1000196050791546372"},"freshness_state":{"last_processed_xact_id":"1000196050791546372","last_considered_xact_id":"1000196050791546372"}}' - headers: - Connection: - - keep-alive - Content-Length: - - '1377' - Content-Type: - - application/json - Date: - - Thu, 30 Oct 2025 14:13:31 GMT - Via: - - 1.1 241db89625f6ef70a00b0e19e0cfc332.cloudfront.net (CloudFront), 1.1 e42e8491a089e2183879e26e61dae708.cloudfront.net - (CloudFront) - X-Amz-Cf-Id: - - RJ9aeBPDDGPh41S24odetiQOdT_lkcSbyofET7LTaTOX2I7zbeZTmg== - X-Amz-Cf-Pop: - - JFK50-P5 - - JFK50-P2 - X-Amzn-Trace-Id: - - Root=1-6903728b-3131e5bf757f9272631beba8;Parent=55157b80cd208d85;Sampled=0;Lineage=1:24be3d11:0 - X-Cache: - - Miss from cloudfront - access-control-allow-credentials: - - 'true' - access-control-expose-headers: - - x-bt-cursor,x-bt-found-existing,x-bt-query-plan - content-encoding: - - gzip - vary: - - Origin - x-amz-apigw-id: - - TQ7V3Gw_IAMEMbg= - x-amzn-RequestId: - - f69de1b3-3903-4dd5-9e79-01c58dbe4a58 - x-bt-cursor: - - aQJI5+sNAAA - x-bt-internal-trace-id: - - 6903728b0000000037975adbedd8bbec - status: - code: 200 - message: OK -- request: - body: '{"query": {"select": [{"op": "star"}], "from": {"op": "function", "name": - {"op": "ident", "name": ["dataset"]}, "args": [{"op": "literal", "value": "f1423e15-4b70-4c62-9760-42c61eea29d9"}]}, - "cursor": "aQJI5+sNAAA", "limit": 1000}, "use_columnstore": false, "brainstore_realtime": - true}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip - Connection: - - keep-alive - Content-Length: - - '286' - Content-Type: - - application/json - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://api.braintrust.dev/btql - response: - body: - string: '{"data":[],"schema":{"type":"array","items":{"type":"object","properties":{"id":{"type":"string","description":"A - unique identifier for the dataset event. If you don''t provide one, Braintrust - will generate one for you"},"_xact_id":{"type":"string","description":"The - transaction id of an event is unique to the network operation that processed - the event insertion. Transaction ids are monotonically increasing over time - and can be used to retrieve a versioned snapshot of the dataset (see the `version` - parameter)"},"created":{"type":"string","format":"date-time","description":"The - timestamp the dataset event was created"},"_pagination_key":{"type":["string","null"],"description":"A - stable, time-ordered key that can be used to paginate over dataset events. - This field is auto-generated by Braintrust and only exists in Brainstore."},"project_id":{"type":"string","format":"uuid","description":"Unique - identifier for the project that the dataset belongs under"},"dataset_id":{"type":"string","format":"uuid","description":"Unique - identifier for the dataset"},"input":{"description":"The argument that uniquely - define an input case (an arbitrary, JSON serializable object)"},"expected":{"description":"The - output of your application, including post-processing (an arbitrary, JSON - serializable object)"},"metadata":{"anyOf":[{"type":"object","properties":{"model":{"description":"The - model used for this example","type":["string","null"]}},"additionalProperties":{}},{"type":"null"}]},"tags":{"anyOf":[{"type":"array","items":{"type":"string"}},{"type":"null"}]},"span_id":{"type":"string","description":"A - unique identifier used to link different dataset events together as part of - a full trace. See the [tracing guide](https://www.braintrust.dev/docs/instrument) - for full details on tracing"},"root_span_id":{"type":"string","description":"A - unique identifier for the trace this dataset event belongs to"},"is_root":{"type":["boolean","null"],"description":"Whether - this span is a root span"},"origin":{"anyOf":[{"type":"object","properties":{"object_type":{"description":"Type - of the object the event is originating from.","enum":["project_logs","experiment","dataset","prompt","function","prompt_session"],"type":"string"},"object_id":{"description":"ID - of the object the event is originating from.","type":"string","format":"uuid"},"id":{"description":"ID - of the original event.","type":"string"},"_xact_id":{"description":"Transaction - ID of the original event.","type":["string","null"]},"created":{"description":"Created - timestamp of the original event. Used to help sort in the UI","type":["string","null"]}},"required":["object_type","object_id","id"],"description":"Reference - to the original object and event this was copied from."},{"type":"null"}]}}}},"realtime_state":{"type":"on","minimum_xact_id":"1000196050791546372","read_bytes":0,"actual_xact_id":"1000196050791546372"},"freshness_state":{"last_processed_xact_id":"1000196050791546372","last_considered_xact_id":"1000196050791546372"}}' - headers: - Connection: - - keep-alive - Content-Length: - - '1074' - Content-Type: - - application/json - Date: - - Thu, 30 Oct 2025 14:13:31 GMT - Via: - - 1.1 241db89625f6ef70a00b0e19e0cfc332.cloudfront.net (CloudFront), 1.1 8ca36406fe3aa11c1641e5bc917c8a74.cloudfront.net - (CloudFront) - X-Amz-Cf-Id: - - 3z5O6TNqvTUMip1F6w0-TdJIAJIZ3tVY6nDWtruxBvHanCWDDP1uBw== - X-Amz-Cf-Pop: - - JFK50-P5 - - JFK50-P2 - X-Amzn-Trace-Id: - - Root=1-6903728b-6ab15c427a0df73c0ddac4ba;Parent=59c8c31c19b3b2c1;Sampled=0;Lineage=1:24be3d11:0 - X-Cache: - - Miss from cloudfront - access-control-allow-credentials: - - 'true' - access-control-expose-headers: - - x-bt-cursor,x-bt-found-existing,x-bt-query-plan - content-encoding: - - gzip - vary: - - Origin - x-amz-apigw-id: - - TQ7V5EOHIAMEVcg= - x-amzn-RequestId: - - 1b73ca7e-505d-47ae-b1e7-613ac793df4d - x-bt-internal-trace-id: - - 6903728b000000006e3d5ea41fcb2b2f - status: - code: 200 - message: OK -- request: - body: '{"project_name": "simple-math-eval", "project_id": null, "org_id": "5ba6d482-b475-4c66-8cd2-5815694764e3", - "update": false, "repo_info": {"commit": "951428110ab8ea1db6427c9a51d086dcd665349c", - "branch": "matt/re", "tag": null, "dirty": true, "author_name": "Matt Perpick", - "author_email": "matt@braintrustdata.com", "commit_message": "fix remote evals", - "commit_time": "2025-10-29T16:53:55-04:00", "git_diff": "diff --git a/py/noxfile.py - b/py/noxfile.py\nindex 1f27e1cf3..d15abdca3 100644\n--- a/py/noxfile.py\n+++ - b/py/noxfile.py\n@@ -174,6 +174,15 @@ def test_braintrust_core(session):\n _run_core_tests(session)\n - \n \n+@nox.session()\n+def test_cli(session):\n+ \"\"\"Test CLI/devserver - with starlette installed.\"\"\"\n+ _install_test_deps(session)\n+ session.install(\".[cli]\")\n+ session.install(\"httpx\") # - Required for starlette.testclient\n+ _run_tests(session, \"braintrust/devserver/test_server_integration.py\")\n+\n+\n - @nox.session()\n def test_otel(session):\n \"\"\"Test OtelExporter with - OpenTelemetry installed.\"\"\"\ndiff --git a/py/src/braintrust/devserver/server.py - b/py/src/braintrust/devserver/server.py\nindex a382097ae..c3ef31b22 100644\n--- - a/py/src/braintrust/devserver/server.py\n+++ b/py/src/braintrust/devserver/server.py\n@@ - -220,7 +220,6 @@ async def run_eval(request: Request) -> Union[JSONResponse, - StreamingResponse]:\n async def run_and_complete():\n try:\n result - = await eval_task\n- # Send summary event with formatted - (camelCase) fields\n await sse_queue.put_event(\"summary\", - format_summary(result.summary))\n except Exception as e:\n print(f\"Error - running eval: {e}\", file=sys.stderr)\ndiff --git a/py/src/braintrust/devserver/test_server_integration.py - b/py/src/braintrust/devserver/test_server_integration.py\nindex 2f6953d97..21d166bc5 - 100644\n--- a/py/src/braintrust/devserver/test_server_integration.py\n+++ b/py/src/braintrust/devserver/test_server_integration.py\n@@ - -4,15 +4,33 @@ from pathlib import Path\n from typing import Any\n \n import - pytest\n-from starlette.testclient import TestClient\n \n-from braintrust.devserver.server - import create_app\n from braintrust.framework import _evals\n+from braintrust.test_helpers - import has_cli_installed\n+\n+\n+@pytest.fixture(scope=\"module\")\n+def vcr_config():\n+ \"\"\"VCR - configuration to filter sensitive headers.\"\"\"\n+ return {\n+ \"filter_headers\": - [\n+ \"x-bt-auth-token\",\n+ \"authorization\",\n+ ]\n+ }\n - \n \n @pytest.fixture\n def client():\n \"\"\"Create test client using the - real simple_eval.py example.\"\"\"\n+ # Skip if CLI dependencies are not - installed\n+ if not has_cli_installed():\n+ pytest.skip(\"CLI dependencies - not installed (requires .[cli])\")\n+\n+ # Import CLI dependencies inside - the fixture\n+ from starlette.testclient import TestClient\n+ from braintrust.devserver.server - import create_app\n+\n # Use the real simple_eval.py example\n eval_file - = Path(__file__).parent.parent.parent.parent / \"examples\" / \"evals\" / \"simple_eval.py\"\n - \n@@ -78,6 +96,7 @@ def test_devserver_health_check(client):\n assert response.text - == \"Hello, world!\"\n \n \n+@pytest.mark.vcr\n def test_devserver_list_evaluators(client, - api_key, org_name):\n \"\"\"Test listing evaluators endpoint.\"\"\"\n response - = client.get(\"/list\", headers={\"x-bt-auth-token\": api_key, \"x-bt-org-name\": - org_name})\n@@ -114,6 +133,7 @@ def parse_sse_events(response_text: str) -> - list[dict[str, Any]]:\n return events\n \n \n+@pytest.mark.vcr\n def test_eval_sse_event_order(client, - api_key, org_name):\n \"\"\"\n Test that SSE events follow the correct - order: start \u2192 progress* \u2192 summary \u2192 done.\n@@ -168,6 +188,7 - @@ def test_eval_sse_event_order(client, api_key, org_name):\n assert summary_event - is not None, \"Summary event should be present\"\n \n \n+@pytest.mark.vcr\n - def test_eval_sse_progress_events(client, api_key, org_name):\n \"\"\"Test - that progress events are emitted during streaming.\"\"\"\n response = client.post(\n@@ - -194,6 +215,7 @@ def test_eval_sse_progress_events(client, api_key, org_name):\n assert - len(progress_events) > 0, \"Should emit progress events from task execution\"\n - \n \n+@pytest.mark.vcr\n def test_eval_error_handling(client, api_key, org_name):\n \"\"\"Test - error handling for non-existent evaluator.\"\"\"\n response = client.post(\n@@ - -212,6 +234,7 @@ def test_eval_error_handling(client, api_key, org_name):\n assert - \"not found\" in error[\"error\"].lower()\n \n \n+@pytest.mark.vcr\n def test_sse_message_format_matches_typescript(client, - api_key, org_name):\n \"\"\"\n Test that Python sends SSE messages in - the exact same format as TypeScript.\n@@ -261,6 +284,7 @@ def test_sse_message_format_matches_typescript(client, - api_key, org_name):\n assert \"projectName\" in summary_event[\"data\"], - \"Summary should have camelCase projectName\"\n \n \n+@pytest.mark.vcr\n def - test_summary_event_has_camelcase_fields(client, api_key, org_name):\n \"\"\"\n Test - that the summary event contains camelCase fields as expected by the UI.\n@@ - -307,6 +331,7 @@ def test_summary_event_has_camelcase_fields(client, api_key, - org_name):\n assert \"project_name\" not in summary_data, \"Summary should - not have snake_case ''project_name''\"\n \n \n+@pytest.mark.vcr\n def test_eval_with_dataset_id_completes_successfully(client, - api_key, org_name):\n \"\"\"\n Test that when using a dataset_id (like - the UI does), the eval completes successfully\ndiff --git a/py/src/braintrust/framework.py - b/py/src/braintrust/framework.py\nindex ee9afed31..3f141929b 100644\n--- a/py/src/braintrust/framework.py\n+++ - b/py/src/braintrust/framework.py\n@@ -1548,7 +1548,7 @@ async def _run_evaluator_internal(\n ) - as pbar:\n async for datum in pbar:\n for trial_index in - range(evaluator.trial_count):\n- # Copy the current context to - the task so that parent_context is preserved\n+ # FIX 1: Copy - the current context to the task so that parent_context is preserved\n ctx - = contextvars.copy_context()\n tasks.append(asyncio.create_task(with_max_concurrency(run_evaluator_task(datum, - trial_index)), context=ctx))\n \n@@ -1582,6 +1582,7 @@ def build_local_summary(\n }\n return - ExperimentSummary(\n experiment_id=None,\n+ # FIX 2: Use eval_name - instead of experiment_name to match TypeScript behavior\n experiment_name=evaluator.eval_name,\n project_name=evaluator.project_name,\n project_id=None,\ndiff - --git a/py/src/braintrust/test_helpers.py b/py/src/braintrust/test_helpers.py\nindex - 08a9b7d04..bff30554f 100644\n--- a/py/src/braintrust/test_helpers.py\n+++ b/py/src/braintrust/test_helpers.py\n@@ - -12,6 +12,16 @@ TEST_ORG_ID = \"test-org-id\"\n TEST_ORG_NAME = \"test-org-name\"\n - \n \n+def has_cli_installed() -> bool:\n+ \"\"\"Check if CLI dependencies - (starlette, uvicorn) are installed.\"\"\"\n+ try:\n+ import starlette\n+ import - uvicorn\n+ return True\n+ except ImportError:\n+ return False\n+\n+\n - def simulate_login() -> None:\n \"\"\"\n Simulate a successful login - for testing purposes."}, "ancestor_commits": ["6d2dc1e53a6d16b466ef449fd8e14ebd3fa20f00", - "a4dfb710896797d1ec1cab191e39cc51eba18b4d", "0f51f6ef36ba16737589cab11ea2dd1742671c41", - "fa85adab7bc82c5d14250a988664e0f65d23643a", "2d8afda70e0f82176d7ee80bcb653ed09d4ada76", - "17b618dbe38d1374435496778d3cbd0f3d3720a9", "6116c86a6188a345cb430e55b48e660009a85799", - "479f00719a1c04acda05bc52e8198c76b17b767b", "41b9555dd4375ea0df23a0a6a2333f7f4d9e626e", - "c3a3634129a36fb09c4b79e737582e33bd2a058b", "7b1f9abab1067273355a38909e102fd2d3a5323c", - "2cbf3503536ba11f94a975fc0c547529315caa9d", "4aa4133193a8e8c3fdc766208be7bffb4983bae5", - "436fe5351a1bc91413e903a2d2cbf2a8559a3c5f", "c033d7aed97d788aa88220df3c8cb72fbe1ab96f", - "f11265286454e2059d0de2a82ee4356601552bd2", "f8c91c4de5c8d19881c4f8b0461bc1f8bfd01d94", - "25912cd765f1ca1e19486411fb3de9963fd9f925", "1026cbd8af888621a402e114a1c58c14da41bb72", - "1cf1bf68a47746b2d23e4211c03a4b81e9626d10", "c5980aae60fc5c3577e241a70c0798d8397e6a07", - "9e4f93daa40369d2cdb97bfb01ee8c93bf23ec80", "2b61d410af69dcfe59d11337df54412a7ed495b7", - "d9dc67568e7a7147ea23e42083d2cb8632bdbe6c", "21bb8edd05cc9d1142fabd4aba808d6a8157f4df", - "258e8ec05412a73bb0a9e916db941c7af1b3e959", "98ca8e2ec4264fb7c6a3a733c455f8d0ea089b07", - "d6cc3a68587ba633190b18c083b7d56747b7a19d", "3525059c8b3d3fadcff6f592c0e2ded7fc06294b", - "e01077c19252f97215f6ed141d485f877506282f", "8a4eb9ac7b33af6ffe3e980c685c290a68c93ca1", - "567acfb3e9e9fda2c4051c038c6621bdb47ec823", "675e293cfa98252cef4d8b7980066b038a901d04", - "11e271cd1a3df6c75449e0c51a21a6c3b3d3fe22", "ce4101fb55325aca6989ccfaebfa9992421c9e2b", - "8e0211657949932ce0ed8da68e72b5c5981fc8f5", "fa016eff3df324a5ff9f3d43d324a01177ec8939", - "6f4426eac2c30baf20e09b51c5369156eff7abc1", "2040109acbd819ebfa776fc97631815b122aa7d4", - "30a65a2a2ce03eec847aa822f722a0d2f0f993bd", "2f320a37a7ef0d32ae4fceb09057b1491eb1fc32", - "25e7a079b6717ffd08ffbda3254fddb072160d82", "146489482d21d37e7297d3b085ba786409e328a3", - "555e44e3d20abf44db5780cc7fc8c95ae5593239", "26b2a34cca8cf71e092eb3e7b02e53b88e6c03a5", - "d6278e852f56fdb00ee5b9d97226be1589853166", "5c61d67a3f8068020979f09c9f7be11f56e95c2a", - "e0647fd778205f62b1956e5320f682af61fbf5ca", "5d55b31e47053325b4a345c445c62413aa69177c", - "a71670f60bd64ceec2b68fc07608d4ef05277ad5", "e6751654101127f666768dfecd42fe9c6e0b47e3", - "a45fabb93b9405dd04d2d944fef78dc424361698", "5f31e95c53879bdcb5bd47276a8aff25673655d8", - "fe3f9a83f7db420747f402841d25dd73f8b36d30", "70dec2f04b7567d45d5a85b77c959623eefcfad2", - "042f91e4b2b8067e6b672816182ba9ae2465812a", "6e7aef5b4b4c6cf84ce51a4d8b947eda306a26b5", - "3f01a409a7ecc34e825e8532e56d04613397cd13", "893a546da4fd221501d3c865c7bf1d16ce9d933e", - "f5410073902240fb94b50c30506aa02dbf9a1517", "722657b05ed625309450f4f33953d7a694a1a414", - "691d303ce7356e544cbfae5ad8054454c0f69652", "a6f5a8bb856a84214811cd2b259edf0a30c6144f", - "aba9adfef223a27e9ebee5f1e5896763adc71641", "500c2fddb600fcbe7a7d8a48d4e1fe7c3bdcfea7", - "ce957df3478f5f95b668a0dfc87956da190d74a6", "3548dc0a4e272b21330ceefe9c8c63517941c034", - "b252d68c0dc7bc599474380a7a185b9c5a9a5fb6", "c2bcdec50527d1153a73a5e191d7bb4ab1f4a5f3", - "552e48c600134179ece0d1aabd13d17f124338be", "1a18ac6ef2f20cb3434d1db59bf4ae4c3a1f715d", - "ad99dac6002a2975e445e8dc90f5d93c53991fdb", "04f8a3f464061a9dba2d1c00dd7940488720974a", - "b8c2d1ebc7b75ea604e9490fd265a6f797add415", "4bf10cf4435ff85c7c3e2f50e7790b2eaa8861a4", - "66091f34bf277d5491477085551afc1a8a361a0f", "f7e1f2ac9f1767984bd125184f8b87563f249bfd", - "61a1c51b48f7b278c73c13efeba86aa2484a33b5", "3f54176089005fb6dc4b252b4dce34370ea8bcc6", - "ff6f45ce65c0b32578fb92f842f123581413dfe9", "6163138faeabb67eb3ef1b97d6a4b08a5c45caa9", - "64cf4c6299cadfe4e5a7987c8db3383a69a108b9", "e98267285f704dd8232dcfffc09616ffeda896fd", - "61d4167d00783621e8a830f267b799b8f22969b1", "12551cea0f20963404d37821d889c7b397ce29ba", - "9aa042227f5625364418d20187dc76508c5c32fb", "8213aad94904430b8165119337da1243fa7a88ab", - "e8c47b170edc02abda540037fb4752ef03a21849", "59a6092a06c163dfb2fa1deea179cd84a5e91083", - "db2b8564a0ed5193a70c607f23e575c8f023454a", "12048f9a795a901cab215f869b185d6e46e2a1e9", - "98cd9913a99020f97a98297a8f085881e8ff21b7", "76c1d436b2fba46a7ac7b7d285ee4b5e3a6660fa", - "cb1c08bc56644e993505a2ab863c18ebc8a35cd2", "f532f53f82e2fbd789b654ddd6eebe181c12d5ab", - "1aaa6ce090e25893b7b8b46cc99fe8344eec653d", "83d4ec39274f91989811f845c6fe805544bfa0ab", - "0152b43193700d54d9826709132ac2bcb9ce5975", "57291a113482eb4277f43c414b09afcb1bf8f0b7", - "3d5ec4de453ab8ea873a6c8c0d0ef0b2110bd386", "4168c8645f251d9584b25c5a57ccb089178a98a1", - "0dafcc9a1aba7282e98d653730b496d83ba13c16", "e45a7da9aba5144429cb9019acf99dc668ddadd5", - "0844207c03327225f9913cc4b1a8702330841a96", "329121933af05b575eee9c77bf13b9a4d3443dde", - "4793325d739b2d9d0deb39d1118e33d76202e7a3", "517ce4da9248bbbf77c7c9f9226054bc5412176b", - "b9ec5a7fe95a0c7e32d65901da5d33ab8c30c779", "cae143cbf533885d8bf978f287e9383bea46c3e6", - "e2df632753bc6545d94b6f4c76af47a81ea3542b", "eb3dcb724dfd1cc85e30594a63839ebd46c8a5a8", - "c459f75f02d0c3444baef25d6fd228ce2929f924", "b98731f2971b9ac5d0acda62cfb2cc32c141dc37", - "6b1c69123acb73fd0cc23393bb165e99bab2508c", "50159c19f26b9c1433e50f388b3fa759c92c0ff0", - "08715a5559a18ec189f91421618e534344f342a0", "2d4792e23d4104e5a89c17bf2195c7a8aded89a2", - "27eb88f965e9d3df3a1cf219db7883093f339676", "ee2acbc913cb75dccb8d1bb124b074bacae27ee1", - "d9a2df31b1ff1ea6796a25558771ed1a38e6d1f9", "b0c3bc7c96cd65435e9ff6b88040799959041972", - "c340893e4dfd3cbeb4566cec5e8cd9a24c9982d5", "cd361d820e14ee59bd8daa6bbe3321cc7d4fa436", - "89c6916d89c4fec3cbe1ee6c780358cf51ba87e2", "262aed06bd219cbfbb4e91c0fbdfb606883f74cd", - "e32b82fabd2f29cdc9ac9e8b33966b10f8a0ce18", "1e3688e139a11ce21f3a9e5c74d176c1ace5cd38", - "b460d264e4ecde414ddb70e918a1adb48ae610b7", "41bee95c0185b6c2521073565e11ede0885a7e8a", - "22bfb85e284a90cf37d23354f56786941de27a99", "59c7f2256d0b342d1cc08eeb3f4dd9c7e61e90f7", - "6f791793df1d1124936ad53e9948cd221a184aec", "e5c3b79336ede6948f3302d60de0fb8a1b7a138c", - "666d1b61ab34647db7ab8e617a9497b87166d7e8", "4d8966bad69bca5970ce0ed64c343fac0e1cf698", - "852bc11787bae1ac6f99622dffc2eea32ef121e8", "2b3067a1dfe1648d1e9be9f54f8e3af5ee9cbc3b", - "1a001a96c0fd88b7884b9049a6d47f6ec4d086b3", "740106ef9e67ae17393d081580f5c1493db372a1", - "05e0f5184a2a0c6a003dd1654bdb4d1da4b1a847", "8eeb1017e6f043e43d6eaaa99d2aec62d2aa2776", - "1e34543f322aa94c5f5e679cc8713120002bee0c", "d253a3c83f3a062f0a18220bdec2188a2445f2ff", - "2548241b69cdc856b24ed8fe930ee5a608348b8c", "47c83b2f5b8cc63496aa507f03babde7e79c730c", - "1169d83904da1f140c52a51748d1f9920cadc304", "2551edd52b168e0691cbc4a16b6f9762c42a2ee8", - "b07d82b7fe426edc3ea57eca2e54dd1a7865e61d", "fe52db5b57808551b30af34184e5f11fb12a1a69", - "2b29dbd15c15e138057630527d19a67d9ea9198a", "5cbc7715b58ac8a9d141cf95813149a09d7f323c", - "918ea978ecc68b7f3ed541b7ed1e073848bf06f3", "af49d808446f40d37d64c66517a45cc19a78de32", - "f2fb962dacc2a7f1b1a9a075611e300970463a1e", "a0ac9637dbc9b7b4af6d37256011e8e777379cb6", - "3fefc0572263475219c149f4c54fe1b88f23c7e7", "f227977b57b78fecd2db13ff2b231d0c22a3b274", - "7e4c8a38b0fd82cc80df79b1daec14c1cdb58be8", "ad3269310aba337feac5712f9621a5b8ffdb29b8", - "4ad90d121a48a0390744035a7bc068f885abcf89", "134fe22aeae849409671acc32e13a17a69681569", - "4e0adb75d47a88366da89405264d87d88cf358c1", "f1252436b3427e8fe87ea9ac07829f977ea12752", - "0679d7794f638bc86e47ecf8e49b70482281c20c", "c06dbe314d1f44c63b8bfe6edadef6ebf5c5ff20", - "ad6e8fa9bbbe6f40621a826662b858c96eff4057", "9756e3372243fd818c895910aa53f4148798b7a8", - "dbb3e71028ba0573b07f6a39bee4a4ff7f39c486", "6aaf30534ead2af6285ed5f3ff12f3680f401066", - "5f7f1c1613ed4d17875a6d845e8cffd3fc0b0059", "7c1432135a24132618b786ace67238029bec8591", - "76290595b414a9c7ec3bf3cf5fa6ad32920d32bd", "97d4988c8ccfb194a7d01d2c427e6796ed36c5e1", - "344fbf8c2cab7917197614e4e974bb5478e4a653", "6a2becd209341a5dd760515889e5aa27a26e1213", - "997e1ee3a567f849865457e22be43aad5b84fcad", "b0a9c6b95b650b90e69e3ea25f3ac2f583a9c622", - "c830370439922abc9cef0763e9cae3387e549c42", "9bb1447ddf4fbcd71f68096307fb5e222d38202d", - "b862af307888af607c82d4d2a3a53e12d6265720", "585e55bba7d4833272526051a7e2a47416f8556c", - "99ac5bdc45f0bec78af9807ebcd8fd118155df93", "c7e14a6aa34a6256944ea4d9be85777a0017415e", - "cc2dda3439152bcabbc625f21d9251afbf15a076", "4e84b51660d909910c0ce4cb014a23e20748ed05", - "f43e4d0aca4ed483f9b2568f35e70dfbdfbecd7c", "10039ee5b86d6ab30389abfafc4158da5e051410", - "a212609775beaa7909f92b708b8348b920c34bc3", "26ef38e22f884aabecbcdc02640beb2e8ec55abb", - "4689201232928ffd29fa14a2bac10fa44f45a81a", "fb2c9cb75fdb96ad4016a076773038a6081a4792", - "d80b52a085881ac67c9c8748473991852f8a1113", "47e4afb01417c95ae136318ce8d066c77402f30c", - "2a256e4dec0180e6e27cd8bda8b4ef1bc3b1bdd9", "fd4b1442c33a018cbfe42a859cb4bbbdb61eb54f", - "f36d187c3fec787dd3d4128001c545de5551bc08", "ef30b00ca626b1bc763427aed853246c0ab72534", - "75eed65362b1370b90c3a032dac2f366f1469f1f", "d0149fcec2d2e19ee8851b4ea2e328b2ee689184", - "9e8eca00b251efc8bea606b3571208966fb2a2d7", "28e3df3754c86e9809909aac9fe02515e231d60f", - "5d4af1c155c639c81448f1d51db6cd33431f7fae", "7e6a0c4ba45a0e692bbcf9456460aa56a974ed01", - "63b04d5a98be1d3a23003f6518c4c8ee3b065ce6", "31991c235b014fcf4fc9a99a7fa4824c705af5cd", - "79231d6d3fb4196a482cf902439ff727eecb92ed", "a8c246b8bf081182b08ad2a4ea478b7ba860d006", - "33750764f3c324181451b38a1dc5219ab04a448e", "370e22839b26494ce0ad1a88286f427434f3dcc5", - "200b037c3083bd2e28e4e31f015bc87f9ab7196c", "6a7573a61b2e15fd261863178f1f54d96ebdf408", - "adfe5473bf50ce4f88c88826d4055b144ef42bb0", "9d66b222b35f994a0d3ab6bbfb1c142d9f226d56", - "ec03206161f942a59ea5bc91c08086a9b1fd2ae7", "ca5bc0d3d6326e4df076624d826be350a89ed54a", - "b8b6473dd4a5f93cd6eb1c0e41d659cb7bad0286", "20162a0585c37d0c14b818eda6f695c40678bf65", - "369ce701b448551b3b5b7156667687c68f7a4259", "587b5c41554e3aed002f92535ef2179231f87e6d", - "3b81c061b9efb1074e0dd9cbb5f11f71420e0832", "6007cac67baac66d72a57c024260e9bda13c456d", - "b1678a8e2c14c96405dc17557ca68d059ff68b8a", "d5879f68ec23e30ca8882d93410073a0cd5db92d", - "90a76730c4ccc74d3cce95abfff445d70bb98499", "bce86716fa530eedc657bfd7cf18f045116a967d", - "fc46a08726a7821ebccbd4d1492ee05c6bae89f7", "d056f38506127e986b226fb5ff5683b6deeefe37", - "1119b6ba9baba7c6511bd57f21eb642085932790", "2d317fabf4f5e8d7a858a3d1dc79b88a2640b241", - "498c2b6b4c0964e25a76cd8ef9e1e25dee1cda7d", "803f7b6304b6fdc60bf08212fa280e31365d16a9", - "5532c2bb541a785fd145aeaf624491e201ed7759", "243023d8a29dffb528b567f37b5ef1d2d78f3fc7", - "c0312dad18501b449812f9c9aca3c39fc1647432", "9aa5151cb1622686f76e3e956dc9a6e48f43d3ef", - "c9ac4a1dffd0a1fe7a0a339b156259884c54057c", "cb53da91b05ac93ef8bb2dffb4f0ce8ddd06255e", - "d25e73f15b3a94570b0a85e39df20d4f9d6a3ded", "d0af00f950ccb83770035cd0db90fd8ebbe00d10", - "ae260ec3ddf6bd62cb66ccb1c9ba3a6ca9d19ab8", "846116d64285c2125f01ac2e06060b84ff9604a1", - "2261c2c6e3edb6c2327046fa2d5b69d9a39ec10b", "0c938db82253db2c09d40079dd15f0a1ad43345d", - "4e5825c76b332b11e0e3af2ef74d9b98e3784809", "83b5cadf47b3eaa15841e3815099ba5338a5f683", - "2f11fc2b39f6889ae6720c0592344995b5942c37", "3e43da7045388e7259414209b3baea7ee339bb9d", - "4b71f161759ed105daaf49ad74f3306ef1710855", "ae7070f6b723cb4c5055252017e5ce712ddbb649", - "23cff857c47ae04884a1e522af2d5a836ea30f2d", "424a8b8cd8ccd2ddbdf3c2d10ced6767b53a4ef2", - "6391feb5cffcecf562f79be5c7b5c620cc1ff24d", "9f1df5788377be4be03c705b21ffe72e3fca68b0", - "607db9575d0fdcc02810ceab97c9b3faf9dcb601", "ee0202713209fc3df5cc7c1c75812c325c94e280", - "47905a7a246fc0ab81d6620820a96a283c6fe8d9", "21ff79105eba8e77a638b42b2e18589a59033609", - "28ba2f0f2967b8292a7071c3d99c9438b1db7963", "e1fcdbf48c205c3a724151cf5008809615687dcb", - "fe9755c8149d239696e010a0e92e2fab24da5aa5", "e6b72cfddcaa930408e0d20800add718d44f30cc", - "f341256a2cf06c968460034faa6d581f17af65a6", "23791cd278e193ccedeb2ba80666c96e9152ae62", - "f402a8f708787e8e97a9e096dbb47ccda9009c78", "8dcac59f949b44e36ace133352ff4dad069e17e8", - "f36f4c364f6f702f64cae7210f0d32a535e93bc2", "8e110a0b274f6a11fc3773a1bd0933dca5cc962f", - "745a2fe44d82669a5070791037da95a0d499ee3c", "d1bda5b3a4ba7b9d7490d8511cce4a11bf76a8d9", - "c2fb15525ed50bb529279aef0da1ad889a209760", "ac5d73eea0dbddd6591c6254078018b894c74d9a", - "150d6faa9cbb1ab06fda1d19606adc701633f24b", "98f046a4f73ab3edd7f33d87279dc17c6009c844", - "c0afac03a62235c223ef23a29e6f0f868aa89f4a", "c19ecf91221af8e0d29e9d6693d8922989c8364d", - "6cc04cca454e9610729586ce72ad276e8a8be962", "5be4d55be3d8a516f8b9bfd8fa4b4b6fa072b3fb", - "68e5dc0768d1143138b22a4dec7c0796211c515d", "40b502f762b12d9008d67359a69427246dbf4590", - "c7a0c0a1d86245d58f93578f5e71861850b20327", "45e88dec3420a3081ed070a89974fade34a8cdd8", - "a2cca480abdfd271d83ec53f32b9ca7c0534b1ea", "eb5b56e00f7e3a3a93a151b04de322a54b478a1d", - "ee726a3bd27fcd17373550a73f1265123f038e9b", "ecbef3833e45ff4b51fcbd07be7ae083d0261106", - "6ff3d878e2b0739195fef120f3e8920aae5b6c14", "c8a254b1ae30d6d0372b9421cf164a2f92770bb3", - "b6fe64434d331f92023b8ac4a0ae29a436ece676", "6408dad003df5f902970c9a9b281bbdcab70513b", - "b000f8b57d68abac68a8ba92d2e8af1f4cf04e3a", "d70f6b719ab62e4d30947d46b48c4f86431e27f4", - "d8b1b3fd5b14a37edfca20bafb53bb19b68034b5", "54e2802c7dda0dc48297627148cb8080900b026c", - "2a88231e4c45be17c7b59df395c88ad1de1f55fd", "bd9541f3b7d18ba20fefb5725bd21f29c01a2fdf", - "fb211cb3f8ec40bc8d34ef5da91173b85368ddb8", "302c5986252fee81e024e43b3950ce0c03c1b19d", - "c688626a38c6777646e4c5343903c5d3c39451d0", "97e8d745c998aa9ca3c0402852cfbdebf38afeff", - "512ca7ae1cc0043eee4b9fb24bc680e5e439a22c", "8a1b18f3f1a52393779d7872132a261596718531", - "f1f688ce752c4783753ded0c034de72056e5bf0a", "cf404c790f1926de4fa92a90bc25bd3b89441ee9", - "6f67fb37b601d81e607b4784b59a60f5da04ddc9", "0358ae29870a0c0555826236454eee2a35460bb2", - "267d40944d68c9fe031797824c83b7628ac21054", "28999639cccbd7471536049556b7bb0445df968c", - "96c339642cf640e219e83499b89b3f14c40c1a46", "22ab4abcaeaab3dffd0a0eef49631c41feb35f01", - "f3281e89aa93a9ff4b045c561960128ff02bd67f", "ba7c3d3d19387b725dd93777e264c2d243c56985", - "c06958105add69f9c1215959af1592100820f897", "0246ace3db73d80516951169f697ab82de31935e", - "3ed4aa3045ac0679828da5a36e6a159a76397b85", "a9b3d7258a65a4ffc0188430f23a2b348bf3f71f", - "3f80e737293fc727a2a5f5931afef5da8a108889", "f5c4af7e6ca21899d603dc1c5d6dec724180a617", - "83223c9cdcb837c03a1ee706a68c201c6f46aae1", "7ebd59911482548ff28bc5257f092339747a9847", - "a29e7d193abe5f905841b7dea04968b1c973775e", "4df92c585a35462fd174a94fa6cc34cb104a3338", - "480f1b18698079c345470f6eddf82dfe04f372bf", "e93635e6ad4990b2037c1c42d96e5f4f5c382211", - "f27588ba28c79a1abd36e9ab225006ef711bc2dc", "0780639bded276d6de3f29a949974f9aad888f1e", - "7649e12dadd9626c6aa55ce09bc5a77abbc1866c", "10684acced018de4c9d795b4e3d17f85b831ed05", - "1fd08bb5d65fb7deba4ce611c4e4ae61526f70f5", "4ad405913be05105cfd8169727862962f73ba90c", - "e622f46b8ab1a027717765dd7d392879941691c8", "e53bc56ec46866426314e2214f39986f794f7ec7", - "1ee4211e5bc419b24309bccc29d84c71d8153e33", "13bf7fbafaffb9eb5305cc786ea5327b1bea8c84", - "1b17359571b9a657d8c1c259f392bdca507f8048", "f14bcf0c9d9d4441837089d9406a275ec7bae489", - "650d0d424276a764869dfa6d5769e0d33dee29ab", "9a51d909f6e0ea003b7bc31368889b34cbaf99db", - "d25b13c8e67b29bedd33634693fd47107d79c386", "d4791ab3fc5623770bd37a62f5847a3469ae62b5", - "63cf95a96c6f9550a526c3f7c973b3bf77da1d99", "0880631d8a31a2d656c214fd5326e86d72d99735", - "c028799f0dc5cdd928ba41ed57758827d4c33960", "09285b7758bced6de4de28adb839ce3707bc0801", - "ff3ef6de1556d6a817b228634d9bd36c03f91b4c", "7599af4e7f3c5038845232dc1c3460e757d29e76", - "945656d9dd3e48ded82ae075761849b0b6de7d99", "14d2b00bcdde27acd1e67707fdec920aaff41440", - "bead8489f2f77870afbd190228724d8ba9525e77", "ef888c5167e12709b33fcb9373476ce222d3a777", - "11185717aa656979199228d4f134506f306ebe11", "763619ad1c6fe756de2d6ea598f4a35b6b5d07f5", - "de64195cf8f8e0a8a209993c12c37e6a0e9717fb", "6fcd348a0817c5ba9f692e9f43b157ba53f61736", - "184223aaddee8a795fb21a0298bca7cf9f24b86a", "025924b72b369155a7dc79296b0fa1542b6cf66e", - "00b6d09efea3b56ed30d3f626837c105415a2b9c", "7fc27ae1ff5720a8632dc7180a62f93f0b240971", - "68a1871cc2f4239c1e4c717d6cf5d50121aa24f7", "d86a119c71e8f3db87ef84a3f2eaee3784e514eb", - "bf6c04384c5ebbcbb7a2635e885ad48223000515", "25df57cb358e1c55102d3eb05c633bbbc8d18ad7", - "c2ed09db58daafd8711f0729136bcb4bdab4ee39", "db9ff970f2394e5ddb70b05835e5cd2ceff1758f", - "b5b0cdc6e2d0971f11ffb7b83eae62bd2f2e2a63", "568a605393fdf0261752b980340b56a695993ca9", - "53a7d40199c4cd3e0b61387708a5c4b2daaa6a04", "d764e0dd4cc13227c90ea0dbdb7a17148a37362c", - "2b0970782ff6fbc9b574d9af09c7f4387da71167", "1a2f72aec014fc3b1c7a58660c15cdf8eb78c30a", - "ea70291c158d9ac2e034f91837f3aebb9315e74f", "ddeee68ef8756513d3c91e77705759282dc88f36", - "c4c43e1c71a7693a257680b25c4cce05fa68139a", "cb91e9590a1524dced13be78e13abde059a5358f", - "8df5d8b31502fd506a59b0d15f61631dc5dc0d11", "ef60833d075ac1aca48423ec296b18756a0907d6", - "4bd51174d78af4c6afff4a3580c4380eaf53db03", "f89f34968e6fb5c4400d4133e5b83eaad9ce1d81", - "4926ebd2150fca495a5ebccb69d73a843c2a5c76", "b7d7768027c43c4bb9178b59096058c827249ebe", - "b18e01b7ab7b8fdd5e9093a4d10446ccb4c8b461", "7c0cb0bf58b260d848be8b2fffc6ea81d45bd9ab", - "65560b3113f1d79c241d64615c70a95a27a1295c", "ef7de7cca843f688185aa44caaa11b8d9c5ba419", - "577959df764fbe2295c7355420fb88e7259318f4", "fb4e5fa6f2ea75bd25bf313675ace5ecfb09ce4b", - "58c3bb9c95b2b18b54923c1c66a271c5103b5016", "d15a9ce8720d18dfb1886de4ce23504c690f9849", - "09b1961ea1fb0304ed7ad7c2c404af3113af532c", "689943c3a6fe2d15706f588d5d192de09025f87e", - "76c955116afc032044fa820077f0aa0077a9b221", "e4e28d5880eb5a19eac4f2dafc94b87121315736", - "f66dc5b1d3a36e518a2d7581534cf1eac1c0bb86", "437d9bab241951c67ba4344ba60e7f8c8fe091fe", - "d48f36d517120dec77f9f1383c6ff175e490957d", "3595ca188c62c02f3a21616a40fce4063e5639e2", - "9335fe0ddc8db4b8825b6a8e96f2ae314c3daea5", "93b3baceba14eb826f0691ec927139eddd131418", - "b081a6d644c99936ce2b53227aa949e61c1fc1a2", "7c301a66f04090a5dfa9b97790c2398bebe8c658", - "70e640c8b512f69cbf2d3815ade5e08acfdd6ea6", "a5ff6189fcfa209df6073595ce8d048bb434142b", - "865f86d6f58109166006154d4cb1f18d780afc7b", "0b32bd194264f3d34f207e36da01747250f370b2", - "160db72460b1d2cb57b71c5f5005c43b39344a08", "ca17e8fc42c63b71a64943b2edc546cb483d4987", - "62709ee11b06371980bbc365eade2cc09fb201e1", "d42b892d83a19496adb8a51865d7786bf11cb51f", - "151eda2239a8926cdfe11bddd08d4a68dfc06fce", "48289268a75e7c551d8407da65a6a8d5e96bfeac", - "76475e31fb20faa61548ca6c110bfaf0a8509333", "ff45b9e590737c453377adfef746c419fd024214", - "791336c9f92b920c36d87abfcd23717effeb2979", "7cbdb028c46f69f69ad5b3870fb9976a339a88ea", - "6dce9b85f8a4d116d780895772890e62ec554050", "609a9ddb002e9e03ec1e01fc0d3273defd125f6a", - "eb5cd823d83464a85d52abf6fb618ab6b0ceaf14", "0b33f97dbe25690d5b395aec431714f326835761", - "b3c0967b6cc938da94bbc24bbb4960c499eab996", "55cc0375389bdbe9081930f6aed59e2d1b996d68", - "3ab0dd9b211aa79f607aa18900021d331ffec108", "8b8fc9dc6eaeab845218b9b42c9f1eadb85d9a76", - "d95873f271a98500509514a3bd503e111b2eeff6", "60c22d4758b2ab938d925ebca4195d388976ef0b", - "4a71cb75be4c145468bfa41edeaec4cad48b35bb", "674df8ed0814f769a01ea52a86b37a37db300fdc", - "52cd156a808d638be19a621e77ce9d0b705ff959", "893fae64443d115a0071088287f1047c9c85bd0c", - "fe745f1136b3c2b4d5cc703cee8933de6357c502", "7a9ed9c04bef62538916e432a74f44c034068c16", - "c60540472bbd9473a78ffac3a071904552cfdd6e", "dce6b37c643555216d24705885d35be6f1658323", - "d25cd6e77dd4f8683333b68cd17e4ef161a10f82", "ef59cd7b3e448c27b726dda2624e3a66bcb7c915", - "caeb866326a82dacaf9b9ce21de180c99462b0ab", "300bbd6765f353ca1f7a42c8db1edbe0fca9146f", - "d476be09c2c9a67b065eb972d473c862d05520d7", "f2692ec53c9eaeb976a81908a1ad9a8a6065eb56", - "80a904cfc2637be47cf6db433896285c96642f28", "b4e7c96d36534976b532f6a73d687ecebd20d3ce", - "f442e491213973df215b4e5a13ac42dbf26a418d", "4a990060a137b7405e90d674667b774c2ab3d9df", - "ea028084a5ba60179ffcc5c2e7745a5137810674", "946cd7b549d16cec7f31b99e31a5cd1f97ecb0a7", - "f4d1570ca148a075ffea03034aa359a795a7a95d", "b24a0df950d615d89a5c490856d9efe0c67e6807", - "4a3a4973113c414789c798e3b279d04e68f18193", "853861b52dff3d4e69cea17db319b578dfe36b57", - "75cdf79a50fa9f54ee0abe8a7352983e4e15dc8f", "d2172012e40b489a1b696aee59ee01beb94d2044", - "c463cba55508e3410e6c938ca7f07cc49c69685f", "298753c52149d58e36b63ae01437d7e9b1626550", - "edf83ddead1b5bf94530280409c8f8d7a3566036", "6ad9ebb63aaa22d5cac2c6ab68a8d044575531b8", - "4c4e417f31a770c165848c34e9a1c03a88345923", "01ac78c98a9e83a657895f330ac60b23df81aa19", - "077b29278d6047812f8b65e158402f13dff2e638", "6a3280cb4ecb45a4a949416106e707b4999e2491", - "3de477994ebd5b7edf0a48ba6c5e799fe02a53f7", "2ebbd703eb8308492ff7d0e3604b786931ad8617", - "5fc0b82cdf849a6c424721cc5118a196c07caf43", "851ed5018abedd4f527d5fc1f184016c2b9dcb20", - "8271e8c30ed07e236d230df37635819f45b3adf5", "794d1fbeb2f5f6e2ad81450602d53d232a2fcd66", - "765e4955986ec0b20075669f5a7e2dca79a98ae9", "f94426a7f4b9bd63aed0e75894ea80278dab4320", - "c0006f951059f5aa58b4b898967d1dab70377178", "414f4c053c7c9d294903806e748a132d54325f73", - "a3dc4e32a5bb67c422822731ffbad447f2f89dd0", "9dab95f8797ac80a22cd854761e2dd141be8f436", - "c187e0b59cc8710d812cf24e9ad7191c5d0c6206", "55cc88749fcd34f08c5d0fee8bee92dcaccfb010", - "2c3d218a5428646b970895dd88e2f61739ba0732", "4ad60738ad972e0cbca3e763b556937501c0973c", - "543f72fea7ef066ea3111bdac8f0ac61134e0c24", "a2bf3ec52c5d004e7e5329efdf6b5cd735618b87", - "f483494815f89e80dc399163080052fff49031bb", "3326ec457cfa6d30663eb0ce49a838d7bbb86415", - "f6d5647f6b6923b5052619814a84b2e1bf8d0b85", "f2dcd0fc70ca95f475b68f7335b2d0855534e5f1", - "a50cd55ec2258557a20839a0d6219960c9b1a2b0", "a34ae4d4326a0913d9af50546c558811565ec66a", - "842e922b6252301d8df608a1a1a4a732686e2ff9", "2b6cb59f7846a482432b4ac57fd960f73d2441ba", - "e559e01ccf3cc35aee9732e3db97c23165f8a6d9", "543085108d5513b9fe63eb96fb386ccc84a811d8", - "c7474d0e9cfe5c1d8e56f3978eec6871706a38a8", "fce05c355558c606a7ca815613c6ad3d8f8a1503", - "30a17532024869bc353e28aa4c3da17dbbcab80f", "13d54732573224d7879166a11857046c50e13626", - "42868488cc892e63b13e7afbe157006ddc215258", "94785fac47a5d2ce41d64269203f14de07995186", - "82d752a38f9d5598685d58e5ce6080409b980442", "96f99cdd47de4d5e4180c99bb7015fa77d329687", - "e89a84828a38b552efd3095472eb39dd18be141c", "5a37e8b4031b627270f06125f5c204eb28437c85", - "30da9a8dfb0f65559be3f17a3d2f3be0cb297ba7", "abba9bb98e64624543ac376fdce700ee5e33b392", - "c19f87bb786c68bab429f594374c24d09dc98cd0", "73754ef7ae4615cdfe881adea981bcc93b65e887", - "44c25f0a9f3151efbb98056e1c2bae59f4aca0b3", "51f465b5aa2a63568d0bd82232898b39fa429a14", - "1ece6bad7a8d2492da84f5db5a94a9c81a94a3df", "603617cb2ad5009c06dfc61432287ea41d4dd70a", - "ec346b3231969799e3852cd7f4e951a25f3fbc0f", "46af277dcaf4eed7cc96e021c96b266c24c1fcd3", - "0965cb17b3b353174be301989ee8f5b77ab925da", "b45319782274fd4841da3c70ad3b4754bf2b1b08", - "2a2bcc98ea5b188049bd46b4e315ae55b359b7f2", "cd09081ec384b747181bc2309a9485ee0888516c", - "f636e931892c445a7ffb1aa0eae7499caa19932f", "34ceb6f49765ac0d173d4a0cecc089f34dce2695", - "9b18988eed2891623baa37468ef83dc6a9a93e14", "087397f895ac78aa63b5b7413dd4c948cae4dc50", - "98e1abd91d5502799931c25c1c19fa6605ff6dd1", "279448c0f978c369797336bd660e457e2abccb3b", - "20d76b4b81484d694731d6a2046661a025928bdd", "7a69b783e3e747a0f7a5eff5cc23b9a00d53aa01", - "f645296a6d289f80b9960679b8edfb6b0a4d96c7", "9352d33e1d396110bedaf1906567a6d8139c98ad", - "3a4cb9ed1c4e291a738f6a97ae82b7db616ed4f6", "e97932a4ff925df81b844058a18f2da4f362edad", - "2e9b3d733cb1d6a6fda98cfccfd179c35559671c", "00e2b96be50f143abbaeaef1b42f502eb1c5eb38", - "a3b8a036064eade54ac1a7e49a48b5228863f225", "b050b6089b63a630ca1e102f27f1e33310bdc0f8", - "91200850dde71fd5061890bae22cf6264f3a0ce9", "c4c90fa787e28f241a6149c5706f67cb8c897c3b", - "52cda4d77c07f76113b392291e947e02010a8ef8", "949b21730e48bc645dca6c6a9dedf758035d0eed", - "3e0509507736054281c0feb777b5beb62af98ed5", "994993e838dda5b000ee4e75786a5a826f368f9f", - "24e2e8a67ed9977de3c1373968d76736da3c800e", "9c8374cdb61697a37bdc89b57ac5574af910138c", - "7facfd4ee6d102ce1c2103b2bc0861865fffc07b", "82f7d052e4d562b268730e8d66d4ac694d963f8d", - "a5f79e4ae09eafe2892bff810ed21b1a7cbeff6a", "7a66189f5b487392ddf3bde3b6b2f837711767c2", - "756f813ee996e91c50dee3929035b81d5c2f5b7c", "c0c98d3382858b9de30907003cb1b3f47bcb7e4c", - "7a1f959994f3e8665589050ca2e07c5ed5579ff6", "06944876fd90b41f439d337cfdbef2582caa4b56", - "73e779de8b03c705726abbd686ab6f905fb2fe27", "dd14f8315d4345a1482b6b5f581fefae03154e6f", - "b4f629bddb661422c15c4b0459104b6a6387f3a1", "a65dec2720ca334bb503079db5a5db4649c27c0a", - "23d9c64b7d95c1d1c08ac83058dba6204537709c", "0070ff46a8b72b79d011f59a770cdd2e3a7e52db", - "39538c29808bc3b1c85b2f9555eb56296778e5b5", "05235f2fda6b96b82d3b798f5c06d1c26fbf5556", - "da9ac947e5272631161f7415583487cd5b81bd92", "0afdc9abb0a921b0eb87256c34c2440d7bcdf748", - "708eb61ae54de0fcccffafc686218a959fa0e12e", "921d2ecf681cb2fa40d8cc9390591bdaeba5bddc", - "d54e009ec45cfd47d90fa87926ff55f5668cd745", "b66c3a482974a6950eb27fa2c83df33c0ddaee0f", - "d11ee1996ea846c781624a6be16e2cf05c90a3ad", "d1fafe49cdba1c135a157ab725caf6a73c44d413", - "37add1833a4462b08f3d63ac3cfe2b29e8c19daa", "54b9e091f1f4a2aecc9c3abef4785cd4116e59da", - "2e7c5f1ca4868b1bf1681e852460d1a64f6730f4", "fee6c7a1a74439ade1a4ba1102431cb16ffa40b4", - "0b663b2c2e9813fd968ea4d53c27117a37af990a", "2bcec290f45a8f707462a56e8cc468f5934fe57e", - "2e77e56acb8a073a7164052b3015752f55748f13", "56cc03e04970154b1ae9a3cb49eeb3d131118feb", - "17819764b0cc55daa6f9a70e1b7cfbb082504a26", "b9992bfe65ca57863517d1a44a5de4abff0d891a", - "7cfd6ae2ae46bf951a84ab288fbf6381377e4fb5", "44f321da361e4de492292e465ac2576625c2f04d", - "14d021d38ede8d4fe6c55266ea1bc18471146ca2", "dd5f008277ecf79acb0c32c88f459a46f556d235", - "e712c5cfb5144ba8122f13b400324a3db3eb1131", "2e3b8bdf70024acbd57dbd574b42d8081b22238f", - "a27f805365b6074f96d0d72bd877158a6a2683fc", "1777f7ceba2141c7725cae03325aad9015f5e0ba", - "3ed72d7bfdaea45c7741c4adba22824729fccf93", "1efd9d0cf3d575dceae0143ad80cdb36ae929f19", - "ed1e3113a91cba66cb2bdd2fc62d221f0fe98720", "56830484e8e3a9bb9c3c0e28d2e06c59c2f85814", - "612f82971d281213f121bf3940fb3a22ef339b1a", "9204cfa997dfafbe1d923cae857fd8772140d2b8", - "bd7772cc8ad355a2edb8ca92d712bc6522f679e4", "50013bba2f0c0daa2ba0601ad9d538b8945f49b3", - "903166d464af4cbe28c3dcfe87e3b03d2d4361d4", "498a0b6129cf4bbdfcd1fbe56f41a09711c81515", - "4d82da411ae6922528a7e31ba0d9b7781ca7b140", "d1a59d5be71487c46f1f13cca1329b890864e3a5", - "0130298b9910153b918c24cd0305bf004c77f139", "b4704585677546e3719b0167a48f7352c3135018", - "bd2af11cf4b22ffaec8f0f81e41c7a200707984e", "90bbdf000b6566e32e973a9ed13673babd3d5971", - "53b76d4726ba14be0ff600d76f6e94af63bc76ac", "98b92425f234019ae1a7d7fa763ee86d24a9d4b3", - "402419c820cba29219805adb1b50909143962ab4", "2507dd9d1d952d45d8e29e3da7d9b67261ddc8d6", - "0eef7ee0455462714b4398429bc4e0b1e68aa807", "c15af97c03e51bb5c7c23118564b21d37e41dc38", - "5ff6527e38d98cdf140318d98828d7de099d1552", "7d8d05ecfc3d87c0a798fbb28a7bd63d79317590", - "d728b77adbe3f536b9211d9b26b0668cd796a549", "ff936585cb1595e9b56e14b77c2a8605a312fc2f", - "cee364e17aaa6f0d77dbcfe496b188de38123833", "28f1af82eea595d5db3da22f4433c144fad620ef", - "d5bc60e7980decfb5d5cd10ef9ea1bd0a3ce5fae", "392ce37ce6411c30d436940506dc2cc8278f66e6", - "38d291489369e7f222a2711e5afd7d6ac6afb574", "479506b2cf7c7392c0a96d6e5d550556dfd20ba0", - "c71e5676016de6a9b7dc27a123f403283fadec2b", "5d03ade937932174a2f2b376efe6f761636a270f", - "04302da411d5d79477463fa37de2f639afd5127f", "d4e6cd7852b5b88d88afb1db0cc9d29d8484f143", - "1dbdc1d3d9dba7ce5cac3bf7d2268ab237a4c5cb", "3f263b23507300ad4dd7903e45876c2877e59ffb", - "127d0081100e98843f16d26cbea527856d9a9ddb", "dd5e22108dcceb35e1944813e2524ebfd0a53df9", - "5d52758299b341021d135b5166614a46f3ecf2e3", "a1b3da2881596c60f669fd80479e45a097b38707", - "21a63be654b8e5df434d01d420ea2206c8d9a92b", "36ea46c3da7dbc2bf4d304d81f86224dfe54444c", - "29fcf933c2e58f6eb8fab04bf8c511f56896fe15", "64737770ddca8995c64e1106bfb08ff0ff1fb144", - "d8c191fa2b58539d83c7efc1c3346079ecdc566a", "77f0910c39aa6108e0c2fdb32fe1832126c0489c", - "af64db9a99bfd8ca4affe94dcd5cfea05e94e03c", "71dd27e77432a2d5b446958707286d08097da244", - "5ddedb0a995f06b295696a2a7b4551e404d0dd16", "01f87385a24ece34ed8ddca801fd84f9c86e74e8", - "09249256a87d4a90588b026d789fd3cb1aec856b", "9240b4a3a946be297b435486d1f2a6d941422b93", - "399ca25f86719994d4612fdb618983079d6a59ee", "4db57eaeeec89f4a96d0f2727c15ff083482fbf2", - "4a31d4c94a4c6ae379abe24c46817a1157eab07c", "182f2002e4307f83c62e06dfa4164543fa7e814e", - "97a0a7220c2b8e458641c3e6e56889254d2da049", "3440a5e4b4e31f45c6adbae99b6214b8fbeebb2e", - "6f94a7a5fe870501cdcea762e4a7a20631d48d62", "9da3107576333b6c7f3e878e508e94a4c764e45e", - "20cb94f57147f8372022885ac2356e464fdaf7e3", "68803fd3ffbf592c0432eadf45fffa22e5afa8dc", - "c538f4c3d9ed532f02458a7c863ddd549960902d", "cd14b737781fb608698437bd2e6d20d691093874", - "2db66f7bda4464a6f5342f5e021c29a38d42068d", "37b12212ecc3a32ede8aa04eb0065fa80e3e821d", - "887306035bf8e3f0963a254a6e46b52b55a04fcf", "8747b40002f4a24a2330ee27f36ecc0880083827", - "ee262c59ff4c66f77562ef879569193543838393", "8282282c974675b044c071faf25996f4b6e4ebc3", - "f9ca90f109c32ff5889c0c9d84ff11f9fb5b5924", "e530847cf2aaa328e800919e6eed9739521a9b50", - "ad726687605b280a0c190153654f4751ebba4c7c", "93f6ba66b73bf972a3df6ba722a1d56782c59d47", - "b40be55c3b541c1c3a6b46de02f45e3ab9dfad47", "95ee9b8acb715971bd1abc137a9d54bc88139b8a", - "61dc80eef767360c6d48572ca1bda65c693d5362", "ba44c4692965b0d694c8fd015f1ec3fa4dfcc696", - "418a1501e2a14efb4ab940cad4c898f09f92ee83", "026029e19d4c6f0bcf239abe607026a5a27f5b86", - "8cbd5f3c989185d9474f7b5767d7e6adabb2015c", "55163a23b71b9a3d63f6e4695b07ebd07064c61f", - "d9bde5278517a57ff7714edf98ab2361d1663219", "9ad5f0871e1df9582ea14bf7ba22350086fcd055", - "c57f5ae0aaa74eea99032b45f0dc5c927813d8b5", "3e3f6f7661780b696501a397d8e95ec446fd1fc3", - "03d94679ae1908d9a6f6a38c00ce7988c5afbcb1", "4c8f526d899bf04b4ce3e088302680da64499e5d", - "271ddfcd505226549f7674b7e539efc96c8be5b8", "25708b2d11167437e6de01fa0406dfd3c26bd8d4", - "dcf94a3cc15a85bc1dc2fc7e1751e6a343609049", "f65dd5dea2e8bf5c90b8b093b4ae2db11fce3b5c", - "b3722ffbf1e3287cee8109c82b7ab13d187a3d7b", "ec3af0efeea2836f6a2fc5a2390232ff10e17cf0", - "c7176c1b7df0676b474b4786a7e6ba25650df8aa", "ad97c1b6ab4dcd3d4917cb59427490508523daf4", - "7a8e2f675709ba76674a2903653b07d348de32d6", "bdd754c4219ceadebaebab82c1dacb0a6d819e24", - "31df56efa866faac4fced90b742b1800261ef46b", "1e77fd0a0bd78293212c518291333d3554136b41", - "99f906bf47a41245895867f76ad38fc9ca88921f", "49dd5ec3406bda057407abe5c57e6a027b8c502d", - "f36f65ae5480acecfb85d9b8d7a79603853f2115", "5a29a9db5779e61efafc338b00be9d22efe2a181", - "6b28f73e9097b7a7966aa9add138e3dc14c52e75", "92571e06644eee1606759deeccb9875fdb454b81", - "b291a60f954d1aaf1bf4d1a845f9838cde8a504e", "47c1cfe13397789ea9681d8f464399e35b1f233f", - "dfd9f01fed969c7b2baaa206a0a6435c5f41ca5c", "de78a285a707e2026d3cfa36a0dc7d18d0c9a15e", - "bce1807765d8a350ed04e8b525e83cab25db5879", "b65a28145ce9d5d79d2b25ffabc905b854eddef6", - "31e8adc8ca44176b5d5b91ba4892612f71ffc2bb", "5a75300c606561e9039ceae4a707793f4317dbbb", - "7ae8180913c01a668a0b0ba707f8550223d1721a", "c7f9391c16e45ef0497f2b35af00180c72a7d91a", - "9b14724732e6369051e8ee69db4f2ff4ab791869", "f20a749be5b9be59f9228aefc4fc649492a272ba", - "fb08711894409b26f7b8827fa0af15b96b6ca1f6", "b8e4379b643d250498d9d7e83b461c8e1601e7db", - "6f9895696ca5c5d76c1852dc169e38da22b2be3a", "0b95e27f015c056bac9f3391b4ee0acde58aaecb", - "9dbe2e2ed1b88739722da7e6ed5deed3a95195bf", "eee23f5c052d9587fb7613de3f01901f14d6a450", - "494d77b5348dd14272ae79d16aa456f4d14ca8c2", "2e8d5bfc7b90389722952a2b67ffaf15f98068fc", - "15e79975f6e8d07b3792dd9045688ebbcd903880", "3d5646ba7b187dcda1e85727462e0f664b9b3f09", - "24aa1622f6ce7c03fb4012ba7a36bb3bcdabb334", "1369f20407850aeb075906f622357694dccc4c6f", - "0871d5b44508d4a35b827a8ff55c88e828570b73", "e9344cff34bbf55f0fb3eec57ea0e10d018f7152", - "ba521a46f16e478b263d5384868422707f12dbbb", "d9f8a5524a6e1a88e95b00b40471d0bcabf928ad", - "6f869e42bc4c0830243807006b5e92ccaed987c5", "1480066efe0215bdd44d633dbe1b7b36785ae8ca", - "a02fad3fc638e1d1c10d3a604df4bb393d5a7930", "59f7e9f29f14a28f3e06307a6d2c505d92bac672", - "2c61bed25bd5d84c2773700540393dfb6019842b", "c5cf5c31e822e883d2a1768bb7852e63be3bb4aa", - "9a21e2e4f98b172f7203af861e68cd14b830a761", "b4f17fbaec55a565c69c714a3b5d8f4ac490c3b4", - "fc1e32643a0622afc3f5cdad86abd94369176f07", "f83864fc3c2d7a2bfc82f7f2b0dbf3cda74714cb", - "a5503e69b80b4ebbd6e12ca615318866d7f7953a", "4fac6a6565e8c32f1f62396d698b6c23f0fc665b", - "17f1ca6c1de1ff8aed107ba8b2247e5ec41ebcfc", "4fc347c433d39d21c2dfe7db951eb3f43ef2c513", - "b20eb22712349162b7390f10e5670acb5ec9cd12", "77afe0fcc0019b81a87269bc20f5381519274e90", - "3520ec2a803d1be3bb16b60177906b055c2fdd16", "05a5f0b3822f27ef60fdd2011de152542de6ec2d", - "ebbcfc6ba138ac549fa2f17dda86a75e5e26fd47", "2917dff8446879fb28b6ee2a8e95d399eb81774e", - "1c67e68f4ac7f4057c712bed7f6ea424f07dec9b", "1b712367effbd03a9b8a8c9638db3b8a42d98b5d", - "7788b8ffbd7bac813c525f043ae6c78b54bcc464", "eb3ca7fdab9840c7f7c9d7d71e484760f9581cf0", - "ee1df733ffddff78579fa89a8f146d67db61404a", "fd55b52a62bdff753e1e5c467f23a8e2ed3de1ac", - "8aa26fd4b2a06e9f928d7aa4886cbf28f40169f4", "e4bd8c43fbafa9775d5f0acb9928a91fd8596cc6", - "7adeb7c36de49d088380792883ab034467726724", "08fe040864b8ef849c1cb653cd261204e3949ae7", - "14d84590bd7db3221a3fff3b31bcd4026274f34b", "547fc4c32bb307a16122e8427580b1d153950e43", - "64f349705fcf35b551fb5bcc5d93aeecf9465aaf", "422e5fc305b81df39f79e6646a06c9af4cf11bbb", - "6a9c141dba2f8cfaad51b6c16ff0c433df9cff03", "fa3c03c1e30bd67594a79bb3e2b08722a0dfc4a2", - "3ded6ed3eda7b67101db34809a7983d08a8b68e0", "56cdb055a9af97858e5d29f9bcb1356472e9003a", - "4f9bab4228e3305be42c2967a6dc4ef773cc51d1", "717391ac5d616f117321b00c07093150b82d8ee4", - "9a746963265cdc3e2498b469975feead7f6f0b47", "edcf69daf11ee8694be60e41536b9b6178e237e4", - "ac65a586026184cdbc4647326b0efb838f171576", "4c8dad3b562ec2db631186ab24e75d6f3783fdb4", - "3c18ea2cec1339263859e1ece8ec2b14d6fa537a", "c6c8518f756d7b5e238ebd34b0e78133c2801137", - "47740650b6135a8f3557fca12f7bb0a0bff7d390", "b1c15d576ab9f14f18d9b21aa27478cbcd00361a", - "42fa9484a9f1caee066628deac108b19d6b93ec0", "3f53d018e54f70921a36f7270cc133bcd264abaf", - "8bc417c5a19b6d5f44fdb89a8a9f0b424fd68c6d", "be26134b26b66aedeb77d959fc59df699a275679", - "e7e335c12372a166de125321c9b30d5f63626307", "7f6045ebc9ba2c9051f7c11eb018f2334e665444", - "dd19cfdaee44125f56fe490fa37c35d016caf47c", "06d8625b51411ffefc23daeaf6b355e19314f90e", - "9ea86d6297a5922b8219f8af414fa0770f06a030", "0ba5e5207de2887a4476a647dea9ae1317d5aa2e", - "da56a105d965c4f23df0f3011a44e8358d81a602", "4a754fadbc3f3fd7b346d7b64f5a3b17d271c7da", - "a871c37d0a5e7e6648a6c16ab63c5bbd7d70a16a", "fd23842b87d7a9180947ac06d181eeebe5dc2941", - "555a2918452f3a04c4af1f68e7413f16cb595977", "5b1b88aa3d57df4397071a9be26bc12108a1e481", - "bd076901c68d96c3bf3f311ae647c1a37a773653", "99c5033ff768805b91e19b47c08675a0263dd3f3", - "5a54a65b1fac540c1e5883ebb1fbfeb165cabc09", "cd115c1b9ad75fca9e914a67155b4c16c8065c77", - "762ee5659b9187b42699c0c075476d25528d593d", "7133c5be52c10a132ba76e9c4b3abe9b0b7b7ed6", - "cb4e2ef91ad0d1809726ad282730a9a6d7faf26b", "87cff5c69eb53813d255a48f8ae581a8bb3301af", - "84e668ca517872198ad8efa92d70b6c4de97d409", "88cc9dabd9a787283b3d4009c290b7300d475ef6", - "cd2f8129d22b8e2f5812db78025ee168dba27888", "36810d3cce461175f81169954f6c15d96cb8edcb", - "a6290116a82a957194a7b47e7efc08db93813dd0", "bb96a933ef02562aebf4613667e77051b9db92da", - "d9364abbc26f8f75f6b257f36dab42be6fc499b1", "8e73bcf5a12e602412dfe8e2461b85529c18e304", - "3fc0507df7156da61c111807c2608cdbb71b8d85", "4ebf9514f9dd7203a3bc467b1c4073b5db3d5589", - "5c6fe9d08cd043b515732de1916616029b912bac", "5bba055b5909daab370735260cd65e7950c456f0", - "7a8f63294c940bd4587e2e29c5aee58708426ac8", "985882796501408cf8de16d91a938045fcf544c4", - "740a8b09820e1ea8e5d8c71a9df6c6f1d606d55f", "c9e1dd02449f23eae2ed983632bb1048ba67c80b", - "cbb201326c9d8621f2ed57b6c36edebc9405ba2a", "4068e14444cd547d9c8557a69521bf127cbdb6fe", - "06e3b6adcae7c833e84eeec5208bd9ffd8e7bd70", "dcbeb76862ffa50e56423a7f556f7a3c7b279bf5", - "556d08322b518cf02a9c29097900d7b16d2692cc", "7550e1c3d068211d065be3676233b369c6d203d9", - "2f95989adeec8c3f3fbf8645c616d1071a7363a7", "ca06cf98b3d5fcc28a66d6bfdd0bac34a8d54737", - "e9088616ec2fef76871de1f4affe67742915786e", "42db27d937253393f68da84ef4d64e6d890d60f2", - "7836f5aebb1a3962b3d987d6cffc1621d62e7031", "52f8c06652c719cb54169981a309a8843ed64b9c", - "9d2e19bd705a6c9330e3511d3605c3acf00d5ae6", "8d72b848b85b63c34a886e64a5cabb53bf2c44c4", - "97d35b990bd278de751bd95b311ede35ebf1dc7c", "3bfb725c6d27358e24d05eb8b69258c47437ba16", - "1a4e7ed04713b1585a663b62e799bd9133c47d28", "41751d21de5c316c856968e2261146db0bcffa63", - "cac1045bb2f08cbad3cf932c0d48d8484e62586a", "f26f9979321cb3c40b12bcadbf1e4671f9ff5f5a", - "baf156ea80f1613488b2973b105b0e5ec507fa40", "1225c97bf1b3efa570d2c614fcce6431aed98da8", - "4823ad32811a54c4e3d86d39d4eb722f0a5f7a03", "4f64b0b47b2092fa9e2ff07620c2beff0de7ae39", - "dde58a3b85f6f12b4cf7aff968a681928af64ff5", "1f088cb0398d95fa9281b13d6d3400ed619bba24", - "d9738aec244d520ee9123ee206ee954efc2bfd5e", "4493e7e7a88d8da224af1aa8c5828dd319f86021", - "1725d50bfdf81c3065aa061a9a49301f822844da", "8f1c8a9f690279edd4a7fb37e0af4b1eeca3db17", - "2dd431e6f6524c60780cb2d785130b69eab6b12c", "30a47a979f60883359b902ccdf57989d5206b7b8", - "f72242e0b21406e101bc74023700fa7ffa8c78ce", "affd31998855a2e2c66e0fedd5f2a0368609073d", - "d7bf882fcb963728e69252fffac173f153e1c9fa", "d50e4560c01b71343b4300d08ef302d049466219", - "235904923f703c3a95f74f55ebfba37385fb7761", "e31e0b576ab331240fd4df0e6fa1ba70a1db33b9", - "55da5f445c8e5dcbd75c522f8ebb50aa2c9bf38d", "7124aad094d27d82b38c751c4f6069a31e50e1a8", - "f4b2a6006d676c4202f936c3d3e455315c3cfd7c", "9cc85a4fc2840adfa1850cd0b01c9fd1c986ab6b", - "39efda7cffab3597dbaba91fb10ac0041b2d53da", "e33fe3660eea113d53f45944e8489d54c00d4672", - "72b08dc4fb03ca0e4763e528b320973db5ab947d", "28b5b2b6e88d6eeff6ed047c8a7959a78bb6d8f6", - "b0e8a7b86effe063533986d940aa2bfc3d270faa", "371c9207ead2cff515884a1b6c6c0831dfe2eb26", - "ab38fcfc415ab75e2ba3fe96cdaaa3ed51cd58f7", "afcf173f583e25786dd094969aef55c7e942edd2", - "f0852629be334cceaff80552c382bcc0a08a6acb", "708ef99585a76555dc567f5f3a07616b30e6e6b1", - "34a2614fab8f3e0ec25eb382db2e47ad4071b12d", "3707a60de155026615d1c4d3b7bab12b0e154420", - "055a2a97afcf45f8473e0cb3ba33f947e8eb828b", "eaf05fb595c20bd0fb27da51db06dd4bceaa5413", - "8f0b1c081f8efbb1ba661c29c5cd16d546d05f9f", "64954d58a69e8aec72d8f1065dedc57430e9a935", - "5990dfdf4cdf6a961fbec8a03b641840cccb8ea5", "566dd607531adab0284af7d02c2aa0b31d3067c9", - "d53ae4284cc7bab5f53aafde89538a50ec71bfbe", "2c55bd4cc2ef2dc26a12c02c5f077a2b61270a59", - "3385bf45d0d065d263d8e0934463695b37c718ad", "0054112babaa8e635df79b63e2dd89dede1accd7", - "9640b095837aecc45669aead3878eea9a5232e13", "aa180c642973bbf58eeb08d142de517b1de64629", - "7e4caa7466bf8fa28522dada3031b1907e5b019a", "122dd7a86ca24c04cf60b1afc7baf4c7b120862d", - "f84b3710bee3ce9d6c61633338de5335f8055120", "2c58738817c223ba71a4cfdfc1e070dce095a76a", - "3d9f4773b6c4675260f695d964a78669e1254213", "86ea67ed19af6e3ce37af6160eb251cb47d0a536", - "3134f576f5a85a80e055b501485d6e08b957e32e", "b136d742bf25ae0917599f4ca623361ecaaf10e0", - "f58b88b6e3cef4a11b6a04373b639dbc374f0d48", "44893414ce5514ccb69451d6438aeee0a5ae3fa4", - "d07a5141298a134bc7d56690cdcb51d22aac17d2", "5c635c23aa70e436677220f0af95d80c1b075030", - "3c9604661631e3984cb7fface67858cf8e16bfe8", "c0329aa82069ff716df6885a9d42d67cc56f364f", - "35c4e1870c134a52c29d87dba164882e375df3b4", "98a4e8b78dd62517cbc5dcfc897f31c79efa5410", - "0fa890a5a0ddbf30f2d8d006ced0f6b13ab0def2", "acaa6ff749a7f6ff56fda52267ad386bb656d5a2", - "8e2d5dd30aae427d060a92367f4a66e900be6538", "e27890dde0a5faf7447e1b145d5744f75e7c9660", - "fdc4be3ca621086bad2f6cc4e71853ef2efb3d27", "98222ee5d7d348b8a609590479dc12fe5a93c7dd", - "61accffbe91cb659a710aed578bb850483e9faff", "149c77518168e9a85553f0e43388cd86ec8b5fc9", - "5ca35d08582a8c73ff833f7bc27ceb161f0ff0d5", "c7c8a61af24907f251c595738c1f7273c6d388f9", - "16ee28a886029f3a6078e0270a88d028d0639ef0", "f08466d0d7e2d83bb6e8bb999369c0f55cf59eba", - "5c77587fca5eaa0f8342f151064d59125236e9a9", "878fd133756ff811d91148597bf0a8ba10aeddaf", - "e99c8365aaf85d8a96af3162a5b04472a89b9ac1", "198217ce4363e8cd71d2a7011c1855d6b54e3075", - "44665c2e1d5c6300bd6749854a3d789ad69f0473", "9029f6e4d8e41168afb51784e127532bf5b0f40a", - "e804a6424cedfd3fbb1c860824462f0088cc6da0", "50f668241b5d6a54fa4f8b3a64f1f01a25669a68", - "97dd2e337d8636723695b43effd7c4070e8307f4", "312f88c527009980e8057a8a076e2770b1d7f935", - "25a24104abd54682a82eaa03690201a82137a271", "f66af150dbe38ff37c28de228b3ab4088ef8da7a", - "306665947a783ec1bc3f155cc9f452a392af96d9", "de977cb9176990f1a3cd6edbecd64826121d764f", - "a24cc91bacc28c73d065ec44e53fa99609ed287b", "2fe4e36ea5f73b5bcec070f9b0abe859d20fc4b6", - "5975beebdcbba4fff6fa4c94377244d3494cfea1", "265308b11a9279ec3afeb00b39a296dc5e0e6427", - "17e05a8f9b3aa0e17fa989289aad48a2890ee451", "40407986bac58a481f0ea86ffb1aa22313a03e3b", - "261593c170055034700d0e34a061eeb594d6b62e", "3f1a2ceaf810b47890761392d771c049841b76e6", - "a4f564b28ec5fea80a3945abbd531baff77f00e8", "af4174a3dd10760cd22054253abb6915713d3141", - "d99beb57a50763266a1bb56c26e2f86812ab3832", "16704488ffed948d86fd5cbb26fbc9072a044211", - "f311ee02782bed10a16cff452a798f1eb7f3683b", "ad923db2aa8f0f0c1e48dfd0e2c702e63654e151", - "844d83b7df2de4b09dd03176391964fa25cae046", "abb2a6d6e6904cd43deb9e2c8ec4b7d02597eccb", - "2ba20bd1955a16b23b24025f580d5873c425f420", "6da1284b78ac00f2f53df42547fed0e2c9d1fe15", - "293edb3e3e77950d6f2c2d35af601aec81aa65ea", "edddfacc53bda442bd19834f96597549942c51bf", - "a9de735ebebe9ad9e5e40edf11aee2222bcbc64b", "3b9b7ab7101a19832204be06498f28bc2b1eb6f0", - "e8e05ee85693562744e35b07300191c0fe3535fe", "aa64beaac06e1cd9b7351a90bf6938925f183dce", - "faae18cae6868a535666e3fafa89795dae4ab4ca", "c0e3af4a8b831af93a29d065e9aaf47f65872e64", - "aaf78bf6e62795356e9fee152797fbfa0df63431", "44d071bed7e256b42081cdb5b8f8f901871ca814", - "24a2b38efaae2f843f6ea2e12931ee08b50b28f0", "54cef1220c285c348c07827b78437dcc78a7d1d8", - "038a3994227ab8e272cbc522a19423805e785965", "cd30166c95121eeb42089e0a5232bfef92897db5", - "90714936a735e9dc3f357d4f305a336e6c150657", "f2eacfe8657dfc1c08d037ecd4f4927969566ffa", - "5b90a912b110dac1d53ea2a3b90de7b6489b2854", "0b9b80df76668ec8dafb82b58a8719156a5364f8", - "9559fd1280bc82b46d8fb577e64051c356b2d7ae", "eec8a74c5dbf04b7eab0d1718e695664382a0d99", - "373e6ee68eae05c29125f2ce7faf3f471f6a9fa9", "77192fbb2111d35b9832760de5c6bca67699e2c4", - "79da714069c63482925568e98367f14545fd04b5", "0a5cf1cb82b7d6c42a1df9a3020564a1bd3e9466", - "512d96d689efdf47b816ebb4a0122db26a22ea2b", "ee2cd357d6f796396402657086acd7db7f397cae", - "414232aa7f80620feae4b9b9115840d48d90d89b", "c0695cf0ec9c5756abcf9374f533615f06053d4c", - "b67e102b0ab38b4fd7111c8ccd84de9e0f53d8d0", "d883383bede721c0040586d6ee7430468c07fd05", - "9aabc7ece7bf957f7d8d6beae5ff1720180f7c79", "0d67470db467538f061e6356714cdd461cb9cbe2", - "ef529b6a77117c651541de32c2505f76307444d5", "2d9dd11a3e5820bebdb0ae3786d3b6f3ff639f9c", - "b91974301a875595e455b29433eb00fd278037f6", "fa5eae0c00fd4d4e494631eba2c6a4f695097462", - "75d795314c210f32d27f23706334c2f1d4522818", "14599fe1d9c66e058095b318cb2c8361867eff76", - "a1032508521f4967a5d1cdf9d1330afce97b7a4e", "98de10b6e8b44e13f65010cbf170f2b448728c46", - "ad0b18fd250e8e2b0e78f8405b4323a4abb3f7ce", "322aba85bbf0b75948cc97ef750d405710a8c9f1", - "1ea8e1bb3de83cf0021af6488d06710aa6835d7b", "86316b6622c23ef4f702289b8ada30ab50417f2d", - "6d673760205b29d0fb9f22e40ea93af32382cf05", "2be97f0d6d60e962c3d9bdeda1cd1d87ae27d90e", - "18cfbbaec2091ec71b22e29abbb782d39dfd822e", "2ce4b0a7a206928c88c24f1ccc7e3d26e3a42dc1", - "9692b2145b1eed391cc8fac85f2cf3c62ee726b7", "f1d2694cdbbe02c137a30cc1e11fd616d37004c2", - "4d7cbf8a715b16c1e4acedd15d2f50f0e316a09d", "04c860819c06c0ac8101985face4492e33f95b20", - "01ea0bdb6a8da5b10001bbe9637d38185063b553", "c6b0836ae73ddd088f32167228c6691978193809", - "42a98df6e52abf067f96ecda4aa830cff0a8209e", "9dc0ec09029c8a6430bbe4eaf0be495ea2fb465c", - "0b24b71e70566e86411e18afc6058b64ff1d5a33", "664a2c715b1b9c55e04b2b8a2935e7c9414af30a", - "6d4dc412387871633c605b628f48b128b993cf3b", "ee5ee654101d5cb985e0b4d73aff7c61ebb4e0e5", - "f5eb3d61d52b51f16d7a1e5a23f25daa0b975dfb", "7e34b6c5ce03487fb17e459ad2b0076f5a8c371a", - "2ec46155cef251efc1ba898e8b6097da77fede3a", "c57e41d3e9a003cdc90db2f03bf3d15662fb00e4", - "6d9e16649b5e8dd0a3968bd573c668260005bd48", "60e9455d95786206764d6bed2d689f6e282e40f4", - "1d4014e9f95080c6accac7756148301c4443155e", "a42ee177d3f5ff6737efa701d90e257e4cf527ca", - "760ca68601182c86b1a41a7ff0a6c467ccc3d0d2", "e9145b2a1269da56e5ac4418339b3c18135601b1", - "798d296f70a1f39801be7bad13736b6a1806b0c0", "ffb0222b379ccebe04a7d893fc1d15a3cc23d864", - "13037016264f48d707a147eef128afec502a646d", "0c624b2b0bcc7b0c13d9743f76ba359fbeb82a8f", - "80ad9a45ea68da615c1d8cb5e110d667710b4a61"], "dataset_id": "f1423e15-4b70-4c62-9760-42c61eea29d9", - "dataset_version": "1000196050791546372", "public": false}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '51593' - Content-Type: - - application/json - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://www.braintrust.dev/api/experiment/register - response: - body: - string: "{\"project\":{\"id\":\"0e748405-dc34-448d-8fba-effd90756d75\",\"org_id\":\"5ba6d482-b475-4c66-8cd2-5815694764e3\",\"name\":\"simple-math-eval\",\"created\":\"2025-10-29T18:59:55.503Z\",\"deleted_at\":null,\"user_id\":\"855483c6-68f0-4df4-a147-df9b4ea32e0c\",\"settings\":null},\"experiment\":{\"id\":\"735629b8-83ca-49d8-82ec-2182edb4b1b7\",\"project_id\":\"0e748405-dc34-448d-8fba-effd90756d75\",\"name\":\"matt/re-1761833612\",\"description\":null,\"created\":\"2025-10-30T14:13:32.320Z\",\"repo_info\":{\"commit\":\"951428110ab8ea1db6427c9a51d086dcd665349c\",\"branch\":\"matt/re\",\"tag\":null,\"dirty\":true,\"author_name\":\"Matt - Perpick\",\"author_email\":\"matt@braintrustdata.com\",\"commit_message\":\"fix - remote evals\",\"commit_time\":\"2025-10-29T16:53:55-04:00\",\"git_diff\":\"diff - --git a/py/noxfile.py b/py/noxfile.py\\nindex 1f27e1cf3..d15abdca3 100644\\n--- - a/py/noxfile.py\\n+++ b/py/noxfile.py\\n@@ -174,6 +174,15 @@ def test_braintrust_core(session):\\n - \ _run_core_tests(session)\\n \\n \\n+@nox.session()\\n+def test_cli(session):\\n+ - \ \\\"\\\"\\\"Test CLI/devserver with starlette installed.\\\"\\\"\\\"\\n+ - \ _install_test_deps(session)\\n+ session.install(\\\".[cli]\\\")\\n+ - \ session.install(\\\"httpx\\\") # Required for starlette.testclient\\n+ - \ _run_tests(session, \\\"braintrust/devserver/test_server_integration.py\\\")\\n+\\n+\\n - @nox.session()\\n def test_otel(session):\\n \\\"\\\"\\\"Test OtelExporter - with OpenTelemetry installed.\\\"\\\"\\\"\\ndiff --git a/py/src/braintrust/devserver/server.py - b/py/src/braintrust/devserver/server.py\\nindex a382097ae..c3ef31b22 100644\\n--- - a/py/src/braintrust/devserver/server.py\\n+++ b/py/src/braintrust/devserver/server.py\\n@@ - -220,7 +220,6 @@ async def run_eval(request: Request) -> Union[JSONResponse, - StreamingResponse]:\\n async def run_and_complete():\\n try:\\n - \ result = await eval_task\\n- # - Send summary event with formatted (camelCase) fields\\n await - sse_queue.put_event(\\\"summary\\\", format_summary(result.summary))\\n except - Exception as e:\\n print(f\\\"Error running eval: - {e}\\\", file=sys.stderr)\\ndiff --git a/py/src/braintrust/devserver/test_server_integration.py - b/py/src/braintrust/devserver/test_server_integration.py\\nindex 2f6953d97..21d166bc5 - 100644\\n--- a/py/src/braintrust/devserver/test_server_integration.py\\n+++ - b/py/src/braintrust/devserver/test_server_integration.py\\n@@ -4,15 +4,33 - @@ from pathlib import Path\\n from typing import Any\\n \\n import pytest\\n-from - starlette.testclient import TestClient\\n \\n-from braintrust.devserver.server - import create_app\\n from braintrust.framework import _evals\\n+from braintrust.test_helpers - import has_cli_installed\\n+\\n+\\n+@pytest.fixture(scope=\\\"module\\\")\\n+def - vcr_config():\\n+ \\\"\\\"\\\"VCR configuration to filter sensitive headers.\\\"\\\"\\\"\\n+ - \ return {\\n+ \\\"filter_headers\\\": [\\n+ \\\"x-bt-auth-token\\\",\\n+ - \ \\\"authorization\\\",\\n+ ]\\n+ }\\n \\n \\n @pytest.fixture\\n - def client():\\n \\\"\\\"\\\"Create test client using the real simple_eval.py - example.\\\"\\\"\\\"\\n+ # Skip if CLI dependencies are not installed\\n+ - \ if not has_cli_installed():\\n+ pytest.skip(\\\"CLI dependencies - not installed (requires .[cli])\\\")\\n+\\n+ # Import CLI dependencies - inside the fixture\\n+ from starlette.testclient import TestClient\\n+ - \ from braintrust.devserver.server import create_app\\n+\\n # Use the - real simple_eval.py example\\n eval_file = Path(__file__).parent.parent.parent.parent - / \\\"examples\\\" / \\\"evals\\\" / \\\"simple_eval.py\\\"\\n \\n@@ -78,6 - +96,7 @@ def test_devserver_health_check(client):\\n assert response.text - == \\\"Hello, world!\\\"\\n \\n \\n+@pytest.mark.vcr\\n def test_devserver_list_evaluators(client, - api_key, org_name):\\n \\\"\\\"\\\"Test listing evaluators endpoint.\\\"\\\"\\\"\\n - \ response = client.get(\\\"/list\\\", headers={\\\"x-bt-auth-token\\\": - api_key, \\\"x-bt-org-name\\\": org_name})\\n@@ -114,6 +133,7 @@ def parse_sse_events(response_text: - str) -> list[dict[str, Any]]:\\n return events\\n \\n \\n+@pytest.mark.vcr\\n - def test_eval_sse_event_order(client, api_key, org_name):\\n \\\"\\\"\\\"\\n - \ Test that SSE events follow the correct order: start \u2192 progress* - \u2192 summary \u2192 done.\\n@@ -168,6 +188,7 @@ def test_eval_sse_event_order(client, - api_key, org_name):\\n assert summary_event is not None, \\\"Summary event - should be present\\\"\\n \\n \\n+@pytest.mark.vcr\\n def test_eval_sse_progress_events(client, - api_key, org_name):\\n \\\"\\\"\\\"Test that progress events are emitted - during streaming.\\\"\\\"\\\"\\n response = client.post(\\n@@ -194,6 +215,7 - @@ def test_eval_sse_progress_events(client, api_key, org_name):\\n assert - len(progress_events) > 0, \\\"Should emit progress events from task execution\\\"\\n - \\n \\n+@pytest.mark.vcr\\n def test_eval_error_handling(client, api_key, - org_name):\\n \\\"\\\"\\\"Test error handling for non-existent evaluator.\\\"\\\"\\\"\\n - \ response = client.post(\\n@@ -212,6 +234,7 @@ def test_eval_error_handling(client, - api_key, org_name):\\n assert \\\"not found\\\" in error[\\\"error\\\"].lower()\\n - \\n \\n+@pytest.mark.vcr\\n def test_sse_message_format_matches_typescript(client, - api_key, org_name):\\n \\\"\\\"\\\"\\n Test that Python sends SSE - messages in the exact same format as TypeScript.\\n@@ -261,6 +284,7 @@ def - test_sse_message_format_matches_typescript(client, api_key, org_name):\\n - \ assert \\\"projectName\\\" in summary_event[\\\"data\\\"], \\\"Summary - should have camelCase projectName\\\"\\n \\n \\n+@pytest.mark.vcr\\n def test_summary_event_has_camelcase_fields(client, - api_key, org_name):\\n \\\"\\\"\\\"\\n Test that the summary event - contains camelCase fields as expected by the UI.\\n@@ -307,6 +331,7 @@ def - test_summary_event_has_camelcase_fields(client, api_key, org_name):\\n assert - \\\"project_name\\\" not in summary_data, \\\"Summary should not have snake_case - 'project_name'\\\"\\n \\n \\n+@pytest.mark.vcr\\n def test_eval_with_dataset_id_completes_successfully(client, - api_key, org_name):\\n \\\"\\\"\\\"\\n Test that when using a dataset_id - (like the UI does), the eval completes successfully\\ndiff --git a/py/src/braintrust/framework.py - b/py/src/braintrust/framework.py\\nindex ee9afed31..3f141929b 100644\\n--- - a/py/src/braintrust/framework.py\\n+++ b/py/src/braintrust/framework.py\\n@@ - -1548,7 +1548,7 @@ async def _run_evaluator_internal(\\n ) as pbar:\\n - \ async for datum in pbar:\\n for trial_index in range(evaluator.trial_count):\\n- - \ # Copy the current context to the task so that parent_context - is preserved\\n+ # FIX 1: Copy the current context to the task - so that parent_context is preserved\\n ctx = contextvars.copy_context()\\n - \ tasks.append(asyncio.create_task(with_max_concurrency(run_evaluator_task(datum, - trial_index)), context=ctx))\\n \\n@@ -1582,6 +1582,7 @@ def build_local_summary(\\n - \ }\\n return ExperimentSummary(\\n experiment_id=None,\\n+ - \ # FIX 2: Use eval_name instead of experiment_name to match TypeScript - behavior\\n experiment_name=evaluator.eval_name,\\n project_name=evaluator.project_name,\\n - \ project_id=None,\\ndiff --git a/py/src/braintrust/test_helpers.py - b/py/src/braintrust/test_helpers.py\\nindex 08a9b7d04..bff30554f 100644\\n--- - a/py/src/braintrust/test_helpers.py\\n+++ b/py/src/braintrust/test_helpers.py\\n@@ - -12,6 +12,16 @@ TEST_ORG_ID = \\\"test-org-id\\\"\\n TEST_ORG_NAME = \\\"test-org-name\\\"\\n - \\n \\n+def has_cli_installed() -> bool:\\n+ \\\"\\\"\\\"Check if CLI dependencies - (starlette, uvicorn) are installed.\\\"\\\"\\\"\\n+ try:\\n+ import - starlette\\n+ import uvicorn\\n+ return True\\n+ except ImportError:\\n+ - \ return False\\n+\\n+\\n def simulate_login() -> None:\\n \\\"\\\"\\\"\\n - \ Simulate a successful login for testing purposes.\"},\"commit\":\"951428110ab8ea1db6427c9a51d086dcd665349c\",\"base_exp_id\":null,\"deleted_at\":null,\"dataset_id\":\"f1423e15-4b70-4c62-9760-42c61eea29d9\",\"dataset_version\":\"1000196050791546372\",\"public\":false,\"user_id\":\"855483c6-68f0-4df4-a147-df9b4ea32e0c\",\"metadata\":null,\"tags\":null}}" - headers: - Cache-Control: - - public, max-age=0, must-revalidate - Content-Encoding: - - gzip - Content-Security-Policy: - - 'script-src ''self'' ''unsafe-eval'' ''wasm-unsafe-eval'' ''strict-dynamic'' - ''nonce-ZjA2Y2ZjMmEtOGY4NC00NWM2LThjYzktYTcyZmE5MDM4Y2I3'' *.js.stripe.com - js.stripe.com maps.googleapis.com ; style-src ''self'' ''unsafe-inline'' *.braintrust.dev - btcm6qilbbhv4yi1.public.blob.vercel-storage.com fonts.googleapis.com www.gstatic.com - d4tuoctqmanu0.cloudfront.net; font-src ''self'' data: fonts.gstatic.com btcm6qilbbhv4yi1.public.blob.vercel-storage.com; - object-src ''none''; base-uri ''self''; form-action ''self''; frame-ancestors - ''self''; worker-src ''self'' blob:; report-uri https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15; - report-to csp-endpoint-0' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 14:13:32 GMT - Etag: - - W/"q80ltkthip66s" - Reporting-Endpoints: - - csp-endpoint-0="https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15" - Server: - - Vercel - Strict-Transport-Security: - - max-age=63072000 - Transfer-Encoding: - - chunked - X-Clerk-Auth-Message: - - Invalid JWT form. A JWT consists of three parts separated by dots. (reason=token-invalid, - token-carrier=header) - X-Clerk-Auth-Reason: - - token-invalid - X-Clerk-Auth-Status: - - signed-out - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-Matched-Path: - - /api/experiment/register - X-Nonce: - - ZjA2Y2ZjMmEtOGY4NC00NWM2LThjYzktYTcyZmE5MDM4Y2I3 - X-Vercel-Cache: - - MISS - X-Vercel-Id: - - iad1::iad1::jrd5t-1761833612092-19688ff3bc25 - status: - code: 200 - message: OK -- request: - body: '{"rows": [{"id": "6b362891-2dea-4f7d-a3bc-7243c2fd2128", "metrics": {"start": - 1761833612.362972}, "span_attributes": {"type": "eval", "name": "eval", "exec_counter": - 19}, "context": {"caller_functionname": "_run", "caller_filename": "/Users/matt/.local/share/mise/installs/python/3.13.3/lib/python3.13/asyncio/events.py", - "caller_lineno": 89}, "input": "joe", "origin": {"object_type": "dataset", "object_id": - "f1423e15-4b70-4c62-9760-42c61eea29d9", "id": "34dc9bc0-9b0a-47fa-8eb5-426f18634232", - "created": "2025-10-29T17:04:33.010Z", "_xact_id": "1000196050791148460"}, "experiment_id": - "735629b8-83ca-49d8-82ec-2182edb4b1b7", "output": "I don''t know", "metadata": - {}, "created": "2025-10-30T14:13:32.362981+00:00", "span_id": "d41130e4-0c3a-435b-9d4d-dd8752d66532", - "root_span_id": "d41130e4-0c3a-435b-9d4d-dd8752d66532", "span_parents": null},{"id": - "d18e5824-1f52-4e2c-adf7-02815f806c33", "metrics": {"start": 1761833612.363771, - "end": 1761833612.364296}, "span_attributes": {"type": "task", "name": "task", - "exec_counter": 20}, "context": {"caller_functionname": "_run", "caller_filename": - "/Users/matt/.local/share/mise/installs/python/3.13.3/lib/python3.13/asyncio/events.py", - "caller_lineno": 89}, "experiment_id": "735629b8-83ca-49d8-82ec-2182edb4b1b7", - "input": "joe", "output": "I don''t know", "created": "2025-10-30T14:13:32.363775+00:00", - "span_id": "4d020555-4fef-425e-b030-f78671b25a92", "root_span_id": "d41130e4-0c3a-435b-9d4d-dd8752d66532", - "span_parents": ["d41130e4-0c3a-435b-9d4d-dd8752d66532"]},{"id": "fa69ed17-cf7e-4c38-b681-fa5b9b4d670b", - "metrics": {"start": 1761833612.364563}, "span_attributes": {"type": "eval", - "name": "eval", "exec_counter": 21}, "context": {"caller_functionname": "_run", - "caller_filename": "/Users/matt/.local/share/mise/installs/python/3.13.3/lib/python3.13/asyncio/events.py", - "caller_lineno": 89}, "input": "matt", "origin": {"object_type": "dataset", - "object_id": "f1423e15-4b70-4c62-9760-42c61eea29d9", "id": "34b693a2-8943-44cd-8570-e84cc6c1470e", - "created": "2025-10-29T17:03:34.896Z", "_xact_id": "1000196050791546372"}, "experiment_id": - "735629b8-83ca-49d8-82ec-2182edb4b1b7", "output": "I don''t know", "metadata": - {}, "created": "2025-10-30T14:13:32.364567+00:00", "span_id": "231b1094-4999-4e83-b09a-d68b5b44f0cc", - "root_span_id": "231b1094-4999-4e83-b09a-d68b5b44f0cc", "span_parents": null},{"id": - "219408ef-ffd4-445a-b0e3-036bb8cb49ea", "metrics": {"start": 1761833612.364929, - "end": 1761833612.365291}, "span_attributes": {"type": "task", "name": "task", - "exec_counter": 22}, "context": {"caller_functionname": "_run", "caller_filename": - "/Users/matt/.local/share/mise/installs/python/3.13.3/lib/python3.13/asyncio/events.py", - "caller_lineno": 89}, "experiment_id": "735629b8-83ca-49d8-82ec-2182edb4b1b7", - "input": "matt", "output": "I don''t know", "created": "2025-10-30T14:13:32.364933+00:00", - "span_id": "f3c0da3c-4761-4f19-8942-1112ad8247df", "root_span_id": "231b1094-4999-4e83-b09a-d68b5b44f0cc", - "span_parents": ["231b1094-4999-4e83-b09a-d68b5b44f0cc"]}], "api_version": 2}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '3045' - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://api.braintrust.dev/logs3 - response: - body: - string: '{"ids":["6b362891-2dea-4f7d-a3bc-7243c2fd2128","d18e5824-1f52-4e2c-adf7-02815f806c33","fa69ed17-cf7e-4c38-b681-fa5b9b4d670b","219408ef-ffd4-445a-b0e3-036bb8cb49ea"],"xact_id":"1000196055780607558"}' - headers: - Connection: - - keep-alive - Content-Length: - - '160' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 14:13:32 GMT - Via: - - 1.1 eb2e4893b47f0d155cd51b82c2a8d596.cloudfront.net (CloudFront), 1.1 92672fff57a11d8cf4f64313a69242d0.cloudfront.net - (CloudFront) - X-Amz-Cf-Id: - - fc4ogLobFM3iHBmVQG80K4TBYSDWRYx4UcQdZQQEHci0YWx4YwGYKw== - X-Amz-Cf-Pop: - - JFK50-P5 - - JFK50-P2 - X-Amzn-Trace-Id: - - Root=1-6903728c-3de6e7f4461bc43276df68dc;Parent=22b4df6ec6a7d74a;Sampled=0;Lineage=1:24be3d11:0 - X-Cache: - - Miss from cloudfront - access-control-allow-credentials: - - 'true' - access-control-expose-headers: - - x-bt-cursor,x-bt-found-existing,x-bt-query-plan - content-encoding: - - gzip - etag: - - W/"c5-Yb964FTtMmwqHfnvvd6GNxKYXTM" - vary: - - Origin, Accept-Encoding - x-amz-apigw-id: - - TQ7WBFtsIAMEESQ= - x-amzn-RequestId: - - 59d67658-a638-4317-a48c-e770b367e405 - x-bt-internal-trace-id: - - 6903728c000000002a12755bbefa6656 - status: - code: 200 - message: OK -- request: - body: '{"rows": [{"id": "77c72af6-52fc-49ad-ada9-952effc49f05", "metrics": {"start": - 1761833612.3665621, "end": 1761833612.3690062}, "span_attributes": {"type": - "score", "name": "scorer", "exec_counter": 23}, "context": {"caller_functionname": - "_run", "caller_filename": "/Users/matt/.local/share/mise/installs/python/3.13.3/lib/python3.13/asyncio/events.py", - "caller_lineno": 89}, "input": {"input": "joe", "expected": null, "metadata": - {}, "output": "I don''t know"}, "experiment_id": "735629b8-83ca-49d8-82ec-2182edb4b1b7", - "output": {"score": 0.0}, "metadata": {}, "scores": {"scorer": 0.0}, "created": - "2025-10-30T14:13:32.366566+00:00", "span_id": "df01d9fd-6a4e-4a0d-b594-fe3c6e687014", - "root_span_id": "d41130e4-0c3a-435b-9d4d-dd8752d66532", "span_parents": ["d41130e4-0c3a-435b-9d4d-dd8752d66532"]},{"id": - "df0786da-4db7-494f-a923-8ac7b34d2acd", "metrics": {"start": 1761833612.367109, - "end": 1761833612.369248}, "span_attributes": {"type": "score", "name": "scorer", - "exec_counter": 24}, "context": {"caller_functionname": "_run", "caller_filename": - "/Users/matt/.local/share/mise/installs/python/3.13.3/lib/python3.13/asyncio/events.py", - "caller_lineno": 89}, "input": {"input": "matt", "expected": null, "metadata": - {}, "output": "I don''t know"}, "experiment_id": "735629b8-83ca-49d8-82ec-2182edb4b1b7", - "output": {"score": 0.0}, "metadata": {}, "scores": {"scorer": 0.0}, "created": - "2025-10-30T14:13:32.367112+00:00", "span_id": "5145020f-1700-48c8-a578-4690fb383646", - "root_span_id": "231b1094-4999-4e83-b09a-d68b5b44f0cc", "span_parents": ["231b1094-4999-4e83-b09a-d68b5b44f0cc"]},{"id": - "6b362891-2dea-4f7d-a3bc-7243c2fd2128", "span_id": "d41130e4-0c3a-435b-9d4d-dd8752d66532", - "root_span_id": "d41130e4-0c3a-435b-9d4d-dd8752d66532", "span_parents": null, - "metrics": {"end": 1761833612.370018}, "_is_merge": true, "experiment_id": "735629b8-83ca-49d8-82ec-2182edb4b1b7"},{"id": - "fa69ed17-cf7e-4c38-b681-fa5b9b4d670b", "span_id": "231b1094-4999-4e83-b09a-d68b5b44f0cc", - "root_span_id": "231b1094-4999-4e83-b09a-d68b5b44f0cc", "span_parents": null, - "metrics": {"end": 1761833612.3701708}, "_is_merge": true, "experiment_id": - "735629b8-83ca-49d8-82ec-2182edb4b1b7"}], "api_version": 2}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '2191' - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://api.braintrust.dev/logs3 - response: - body: - string: '{"ids":["77c72af6-52fc-49ad-ada9-952effc49f05","df0786da-4db7-494f-a923-8ac7b34d2acd","6b362891-2dea-4f7d-a3bc-7243c2fd2128","fa69ed17-cf7e-4c38-b681-fa5b9b4d670b"],"xact_id":"1000196055780673286"}' - headers: - Connection: - - keep-alive - Content-Length: - - '159' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 14:13:33 GMT - Via: - - 1.1 c50e3f7de0b772d07240015272b1aff6.cloudfront.net (CloudFront), 1.1 d3041c3025b9205db460853b5b9626bc.cloudfront.net - (CloudFront) - X-Amz-Cf-Id: - - CwbMyYKUFST06Bds2NGK_8fAnM54AFWfyVY24D-V1FE1k27XSaFIyA== - X-Amz-Cf-Pop: - - JFK50-P5 - - JFK50-P2 - X-Amzn-Trace-Id: - - Root=1-6903728d-537e23342caaa1a13cf5e5bc;Parent=0125361ef098a1d4;Sampled=0;Lineage=1:24be3d11:0 - X-Cache: - - Miss from cloudfront - access-control-allow-credentials: - - 'true' - access-control-expose-headers: - - x-bt-cursor,x-bt-found-existing,x-bt-query-plan - content-encoding: - - gzip - etag: - - W/"c5-swa0FM1D+h+NnuQOWCMJA2Flvjk" - vary: - - Origin, Accept-Encoding - x-amz-apigw-id: - - TQ7WGHqQoAMEjhg= - x-amzn-RequestId: - - 2c5afcf3-3b94-4d0e-ae63-5932b93a474f - x-bt-internal-trace-id: - - 6903728d0000000051ebe80b882da7fc - status: - code: 200 - message: OK -- request: - body: '{"id": "735629b8-83ca-49d8-82ec-2182edb4b1b7"}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '46' - Content-Type: - - application/json - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://www.braintrust.dev/api/base_experiment/get_id - response: - body: - string: '{"id":"735629b8-83ca-49d8-82ec-2182edb4b1b7","project_id":"0e748405-dc34-448d-8fba-effd90756d75","name":"matt/re-1761833612","base_exp_id":"699db184-3cf1-4aa0-b008-4dc7bdbd0fef","base_exp_name":"matt/re-1761833608"}' - headers: - Cache-Control: - - public, max-age=0, must-revalidate - Content-Length: - - '215' - Content-Security-Policy: - - 'script-src ''self'' ''unsafe-eval'' ''wasm-unsafe-eval'' ''strict-dynamic'' - ''nonce-ZGE0ODNkYzItMTExMC00NDRlLTg0M2ItZjdkZmJkMzhhNTVl'' *.js.stripe.com - js.stripe.com maps.googleapis.com ; style-src ''self'' ''unsafe-inline'' *.braintrust.dev - btcm6qilbbhv4yi1.public.blob.vercel-storage.com fonts.googleapis.com www.gstatic.com - d4tuoctqmanu0.cloudfront.net; font-src ''self'' data: fonts.gstatic.com btcm6qilbbhv4yi1.public.blob.vercel-storage.com; - object-src ''none''; base-uri ''self''; form-action ''self''; frame-ancestors - ''self''; worker-src ''self'' blob:; report-uri https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15; - report-to csp-endpoint-0' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 14:13:33 GMT - Etag: - - '"12w53piuo4c5z"' - Reporting-Endpoints: - - csp-endpoint-0="https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=15" - Server: - - Vercel - Strict-Transport-Security: - - max-age=63072000 - X-Clerk-Auth-Message: - - Invalid JWT form. A JWT consists of three parts separated by dots. (reason=token-invalid, - token-carrier=header) - X-Clerk-Auth-Reason: - - token-invalid - X-Clerk-Auth-Status: - - signed-out - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-Matched-Path: - - /api/base_experiment/get_id - X-Nonce: - - ZGE0ODNkYzItMTExMC00NDRlLTg0M2ItZjdkZmJkMzhhNTVl - X-Vercel-Cache: - - MISS - X-Vercel-Id: - - iad1::iad1::j46nn-1761833613424-5509d2a2c9ab - status: - code: 200 - message: OK -- request: - body: null - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - User-Agent: - - python-requests/2.32.5 - method: GET - uri: https://api.braintrust.dev/experiment-comparison2?experiment_id=735629b8-83ca-49d8-82ec-2182edb4b1b7&base_experiment_id=699db184-3cf1-4aa0-b008-4dc7bdbd0fef - response: - body: - string: '{"scores":{"scorer":{"name":"scorer","score":0,"improvements":0,"regressions":0}},"metrics":{"llm_calls":{"name":"llm_calls","metric":0,"unit":"","improvements":0,"regressions":0},"tool_calls":{"name":"tool_calls","metric":0,"unit":"","improvements":0,"regressions":0},"errors":{"name":"errors","metric":0,"unit":"","improvements":0,"regressions":0},"llm_errors":{"name":"llm_errors","metric":0,"unit":"","improvements":0,"regressions":0},"tool_errors":{"name":"tool_errors","metric":0,"unit":"","improvements":0,"regressions":0},"prompt_tokens":{"name":"prompt_tokens","metric":0,"unit":"tok","improvements":0,"regressions":0},"prompt_cached_tokens":{"name":"prompt_cached_tokens","metric":0,"unit":"tok","improvements":0,"regressions":0},"prompt_cache_creation_tokens":{"name":"prompt_cache_creation_tokens","metric":0,"unit":"tok","improvements":0,"regressions":0},"completion_tokens":{"name":"completion_tokens","metric":0,"unit":"tok","improvements":0,"regressions":0},"total_tokens":{"name":"total_tokens","metric":0,"unit":"tok","improvements":0,"regressions":0},"duration":{"name":"duration","metric":0.00044357776641845703,"unit":"s","improvements":0,"regressions":0}}}' - headers: - Connection: - - keep-alive - Content-Length: - - '242' - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 30 Oct 2025 14:13:34 GMT - Via: - - 1.1 48fa2d8b9525abe889eff7ccc8591f7e.cloudfront.net (CloudFront), 1.1 50670fc09f8465be7ae4adcf6e33ab7a.cloudfront.net - (CloudFront) - X-Amz-Cf-Id: - - ZLSOwTiwq5psLKaxbihRmkRkypLetRhWuj8xhCs9LxDDneIeIsQdQA== - X-Amz-Cf-Pop: - - JFK50-P5 - - JFK50-P2 - X-Amzn-Trace-Id: - - Root=1-6903728d-4121e65e4f814ff44122c3ba;Parent=409dacd132bebc22;Sampled=0;Lineage=1:24be3d11:0 - X-Cache: - - Miss from cloudfront - access-control-allow-credentials: - - 'true' - access-control-expose-headers: - - x-bt-cursor,x-bt-found-existing,x-bt-query-plan - content-encoding: - - gzip - etag: - - W/"49a-wU5UK66a/69oWu3gmOSKSrIx0T0" - vary: - - Origin, Accept-Encoding - x-amz-apigw-id: - - TQ7WMEjZIAMEBoQ= - x-amzn-RequestId: - - f5c816b2-0c90-4aea-a032-3cee25b30a82 - x-bt-internal-trace-id: - - 6903728d00000000468fe44c9548cf84 - status: - code: 200 - message: OK -- request: - body: '{"name":"simple-math-eval","stream":true,"data":{"dataset_id":"f1423e15-4b70-4c62-9760-42c61eea29d9"}}' - headers: - accept: - - text/event-stream - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '102' - content-type: - - application/json - host: - - testserver - user-agent: - - testclient - x-bt-org-name: - - matt-test-org - method: POST - uri: http://testserver/eval - response: - body: - string: "event: start\ndata: {\"projectName\": \"simple-math-eval\", \"projectId\": - \"0e748405-dc34-448d-8fba-effd90756d75\", \"experimentId\": \"735629b8-83ca-49d8-82ec-2182edb4b1b7\", - \"experimentName\": \"matt/re-1761833612\", \"projectUrl\": \"https://www.braintrust.dev/app/matt-test-org/p/simple-math-eval\", - \"experimentUrl\": \"https://www.braintrust.dev/app/matt-test-org/p/simple-math-eval/experiments/matt%2Fre-1761833612\"}\n\nevent: - progress\ndata: {\"id\": \"6b362891-2dea-4f7d-a3bc-7243c2fd2128\", \"origin\": - {\"object_type\": \"dataset\", \"object_id\": \"f1423e15-4b70-4c62-9760-42c61eea29d9\", - \"id\": \"34dc9bc0-9b0a-47fa-8eb5-426f18634232\", \"created\": \"2025-10-29T17:04:33.010Z\", - \"_xact_id\": \"1000196050791148460\"}, \"name\": \"simple-math-eval\", \"object_type\": - \"task\", \"format\": \"code\", \"output_type\": \"completion\", \"event\": - \"json_delta\", \"data\": \"\\\"I don't know\\\"\"}\n\nevent: progress\ndata: - {\"id\": \"fa69ed17-cf7e-4c38-b681-fa5b9b4d670b\", \"origin\": {\"object_type\": - \"dataset\", \"object_id\": \"f1423e15-4b70-4c62-9760-42c61eea29d9\", \"id\": - \"34b693a2-8943-44cd-8570-e84cc6c1470e\", \"created\": \"2025-10-29T17:03:34.896Z\", - \"_xact_id\": \"1000196050791546372\"}, \"name\": \"simple-math-eval\", \"object_type\": - \"task\", \"format\": \"code\", \"output_type\": \"completion\", \"event\": - \"json_delta\", \"data\": \"\\\"I don't know\\\"\"}\n\nevent: summary\ndata: - {\"projectName\": \"simple-math-eval\", \"projectId\": \"0e748405-dc34-448d-8fba-effd90756d75\", - \"experimentId\": \"735629b8-83ca-49d8-82ec-2182edb4b1b7\", \"experimentName\": - \"matt/re-1761833612\", \"projectUrl\": \"https://www.braintrust.dev/app/matt-test-org/p/simple-math-eval\", - \"experimentUrl\": \"https://www.braintrust.dev/app/matt-test-org/p/simple-math-eval/experiments/matt%2Fre-1761833612\", - \"comparisonExperimentName\": \"matt/re-1761833608\", \"scores\": {\"scorer\": - {\"name\": \"scorer\", \"score\": 0, \"improvements\": 0, \"regressions\": - 0}}, \"metrics\": {\"llm_calls\": {\"name\": \"llm_calls\", \"_longest_metric_name\": - 28, \"metric\": 0, \"unit\": \"\", \"improvements\": 0, \"regressions\": 0, - \"diff\": null}, \"tool_calls\": {\"name\": \"tool_calls\", \"_longest_metric_name\": - 28, \"metric\": 0, \"unit\": \"\", \"improvements\": 0, \"regressions\": 0, - \"diff\": null}, \"errors\": {\"name\": \"errors\", \"_longest_metric_name\": - 28, \"metric\": 0, \"unit\": \"\", \"improvements\": 0, \"regressions\": 0, - \"diff\": null}, \"llm_errors\": {\"name\": \"llm_errors\", \"_longest_metric_name\": - 28, \"metric\": 0, \"unit\": \"\", \"improvements\": 0, \"regressions\": 0, - \"diff\": null}, \"tool_errors\": {\"name\": \"tool_errors\", \"_longest_metric_name\": - 28, \"metric\": 0, \"unit\": \"\", \"improvements\": 0, \"regressions\": 0, - \"diff\": null}, \"prompt_tokens\": {\"name\": \"prompt_tokens\", \"_longest_metric_name\": - 28, \"metric\": 0, \"unit\": \"tok\", \"improvements\": 0, \"regressions\": - 0, \"diff\": null}, \"prompt_cached_tokens\": {\"name\": \"prompt_cached_tokens\", - \"_longest_metric_name\": 28, \"metric\": 0, \"unit\": \"tok\", \"improvements\": - 0, \"regressions\": 0, \"diff\": null}, \"prompt_cache_creation_tokens\": - {\"name\": \"prompt_cache_creation_tokens\", \"_longest_metric_name\": 28, - \"metric\": 0, \"unit\": \"tok\", \"improvements\": 0, \"regressions\": 0, - \"diff\": null}, \"completion_tokens\": {\"name\": \"completion_tokens\", - \"_longest_metric_name\": 28, \"metric\": 0, \"unit\": \"tok\", \"improvements\": - 0, \"regressions\": 0, \"diff\": null}, \"total_tokens\": {\"name\": \"total_tokens\", - \"_longest_metric_name\": 28, \"metric\": 0, \"unit\": \"tok\", \"improvements\": - 0, \"regressions\": 0, \"diff\": null}, \"duration\": {\"name\": \"duration\", - \"_longest_metric_name\": 28, \"metric\": 0.00044357776641845703, \"unit\": - \"s\", \"improvements\": 0, \"regressions\": 0, \"diff\": null}}}\n\nevent: - done\ndata: \n\n" - headers: - cache-control: - - no-cache - connection: - - keep-alive - content-type: - - text/event-stream; charset=utf-8 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/devserver/cors.py b/py/src/braintrust/devserver/cors.py deleted file mode 100644 index e014d4a2c..000000000 --- a/py/src/braintrust/devserver/cors.py +++ /dev/null @@ -1,148 +0,0 @@ -import os -import re -from collections.abc import Awaitable, Callable -from typing import Any - -# CORS configuration -ALLOWED_ORIGINS: list[str | re.Pattern] = [ - "https://www.braintrust.dev", - "https://www.braintrustdata.com", - re.compile(r"https://.*\.preview\.braintrust\.dev"), -] - -ALLOWED_HEADERS = [ - "Content-Type", - "X-Amz-Date", - "Authorization", - "X-Api-Key", - "X-Amz-Security-Token", - "x-bt-auth-token", - "x-bt-parent", - "x-bt-org-name", - "x-bt-project-id", - "x-bt-stream-fmt", - "x-bt-use-cache", - "x-stainless-os", - "x-stainless-lang", - "x-stainless-package-version", - "x-stainless-runtime", - "x-stainless-runtime-version", - "x-stainless-arch", -] - -EXPOSED_HEADERS = [ - "x-bt-cursor", - "x-bt-found-existing-experiment", - "x-bt-span-id", - "x-bt-span-export", -] - - -def check_origin(origin: str) -> bool: - """Check if the origin is allowed.""" - if not origin: - return False - - # Check environment variables - whitelisted_origin = os.environ.get("WHITELISTED_ORIGIN") - if whitelisted_origin and origin == whitelisted_origin: - return True - - braintrust_app_url = os.environ.get("BRAINTRUST_APP_URL") - if braintrust_app_url and origin == braintrust_app_url: - return True - - # Check static and regex patterns - for allowed in ALLOWED_ORIGINS: - if isinstance(allowed, str) and origin == allowed: - return True - elif isinstance(allowed, re.Pattern) and allowed.match(origin): - return True - - return False - - -def create_cors_middleware() -> type: - """Create a Starlette CORS middleware class.""" - - class CORSMiddleware: - def __init__(self, app: Any) -> None: - self.app = app - - async def __call__( - self, - scope: dict[str, Any], - receive: Callable[[], Awaitable[dict[str, Any]]], - send: Callable[[dict[str, Any]], Awaitable[None]], - ) -> None: - if scope["type"] == "http": - headers = dict(scope["headers"]) - origin = headers.get(b"origin", b"").decode("utf-8") - - # Handle OPTIONS requests - if scope["method"] == "OPTIONS": - - async def send_options_wrapper(message: dict[str, Any]) -> None: - if message["type"] == "http.response.start": - headers_dict = dict(message.get("headers", [])) - - if origin and check_origin(origin): - headers_dict[b"access-control-allow-origin"] = origin.encode() - headers_dict[b"access-control-allow-methods"] = ( - b"GET, POST, PUT, DELETE, OPTIONS, PATCH" - ) - headers_dict[b"access-control-allow-headers"] = ", ".join(ALLOWED_HEADERS).encode() - headers_dict[b"access-control-expose-headers"] = ", ".join(EXPOSED_HEADERS).encode() - headers_dict[b"access-control-allow-credentials"] = b"true" - headers_dict[b"access-control-max-age"] = b"86400" - - # Handle private network access - if headers.get(b"access-control-request-private-network"): - headers_dict[b"access-control-allow-private-network"] = b"true" - - message["headers"] = list(headers_dict.items()) - - await send(message) - - # Send empty response for OPTIONS - await send_options_wrapper( - { - "type": "http.response.start", - "status": 200, - "headers": [], - } - ) - await send( - { - "type": "http.response.body", - "body": b"", - } - ) - return - - # For other requests, add CORS headers if origin is valid - async def send_wrapper(message: dict[str, Any]) -> None: - if message["type"] == "http.response.start" and origin and check_origin(origin): - headers_dict = dict(message.get("headers", [])) - - # Add CORS headers - headers_dict[b"access-control-allow-origin"] = origin.encode() - headers_dict[b"access-control-allow-methods"] = b"GET, POST, PUT, DELETE, OPTIONS, PATCH" - headers_dict[b"access-control-allow-headers"] = ", ".join(ALLOWED_HEADERS).encode() - headers_dict[b"access-control-expose-headers"] = ", ".join(EXPOSED_HEADERS).encode() - headers_dict[b"access-control-allow-credentials"] = b"true" - headers_dict[b"access-control-max-age"] = b"86400" - - # Handle private network access - if headers.get(b"access-control-request-private-network"): - headers_dict[b"access-control-allow-private-network"] = b"true" - - message["headers"] = list(headers_dict.items()) - - await send(message) - - await self.app(scope, receive, send_wrapper) - else: - await self.app(scope, receive, send) - - return CORSMiddleware diff --git a/py/src/braintrust/devserver/dataset.py b/py/src/braintrust/devserver/dataset.py deleted file mode 100644 index de222efb5..000000000 --- a/py/src/braintrust/devserver/dataset.py +++ /dev/null @@ -1,61 +0,0 @@ -from typing import Any - -from braintrust import init_dataset -from braintrust._generated_types import RunEvalData, RunEvalData1, RunEvalData2 -from braintrust.logger import BraintrustState - - -async def get_dataset_by_id(state: BraintrustState, dataset_id: str) -> dict[str, str]: - """Fetch dataset information by ID.""" - # Make API call to get dataset info - conn = state.api_conn() - # Note: The Python SDK doesn't have async API calls yet, so we use sync - response = conn.get_json(f"v1/dataset/{dataset_id}") - - if response is None: - raise ValueError(f"Dataset with id {dataset_id} not found") - - # Extract project_id and dataset name from response - return { - "project_id": response.get("project_id"), - "dataset": response.get("name"), - } - - -# NOTE: To make this performant, we'll have to make these functions work with async i/o -async def get_dataset(state: BraintrustState, data: RunEvalData | RunEvalData1 | RunEvalData2 | dict[str, Any]) -> Any: - """ - Get dataset from various data sources. - - Handles: - - Dataset reference by project_name/dataset_name - - Dataset reference by dataset_id - - Inline data array - """ - # Handle dict-based data (common case) - if isinstance(data, dict): - if "project_name" in data and "dataset_name" in data: - # Dataset reference by name - return init_dataset( - state=state, - project=data["project_name"], - name=data["dataset_name"], - # _internal_btql is optional - **({"_internal_btql": data["_internal_btql"]} if "_internal_btql" in data else {}), - ) - elif "dataset_id" in data: - # Dataset reference by ID - dataset_info = await get_dataset_by_id(state, data["dataset_id"]) - return init_dataset( - state=state, - project_id=dataset_info["project_id"], - name=dataset_info["dataset"], - # _internal_btql is optional - **({"_internal_btql": data["_internal_btql"]} if "_internal_btql" in data else {}), - ) - elif "data" in data: - # Inline data - return data["data"] - - # If it's not a dict, assume it's inline data - return data diff --git a/py/src/braintrust/devserver/eval_hooks.py b/py/src/braintrust/devserver/eval_hooks.py deleted file mode 100644 index ad520ec32..000000000 --- a/py/src/braintrust/devserver/eval_hooks.py +++ /dev/null @@ -1,62 +0,0 @@ -""" -Evaluation hooks and progress reporting for the dev server. - -Similar to the JavaScript implementation, this provides callbacks -for reporting progress during evaluation execution. -""" - -import asyncio -import json -from collections.abc import Callable -from typing import Any - - -class EvalHooks: - """Hooks provided to eval tasks for progress reporting.""" - - def __init__( - self, - report_progress: Callable[[dict[str, Any]], None] | None = None, - parameters: dict[str, Any] | None = None, - ): - self._report_progress = report_progress - self.parameters = parameters or {} - - def report_progress(self, event: dict[str, Any]) -> None: - """Report progress during task execution.""" - if self._report_progress: - self._report_progress(event) - - -def serialize_sse_event(event: str, data: Any) -> str: - """ - Serialize data into SSE format. - - This follows the same format as the SSEClient expects to parse. - """ - if isinstance(data, dict) or isinstance(data, list): - data_str = json.dumps(data) - else: - data_str = str(data) - - return f"event: {event}\ndata: {data_str}\n\n" - - -class SSEQueue: - """Simple wrapper around asyncio.Queue for SSE events.""" - - def __init__(self): - self.queue: asyncio.Queue[str | None] = asyncio.Queue() - - async def put_event(self, event: str, data: Any) -> None: - """Add an SSE event to the queue.""" - sse_data = serialize_sse_event(event, data) - await self.queue.put(sse_data) - - async def close(self) -> None: - """Signal end of stream.""" - await self.queue.put(None) - - async def get(self) -> str | None: - """Get the next event from the queue.""" - return await self.queue.get() diff --git a/py/src/braintrust/devserver/schemas.py b/py/src/braintrust/devserver/schemas.py deleted file mode 100644 index 841daffd7..000000000 --- a/py/src/braintrust/devserver/schemas.py +++ /dev/null @@ -1,264 +0,0 @@ -import json -from collections.abc import Sequence -from typing import Any, Union, get_args, get_origin, get_type_hints - -from typing_extensions import TypedDict - -# This is not beautiful code, but it saves us from introducing Pydantic as a dependency, and it is fairly -# straightforward for an LLM to keep it up to date with runEvalBodySchema in JS. - - -class ValidationError(Exception): - """Raised when validation fails.""" - - pass - - -class ParsedFunctionId(TypedDict, total=False): - """Parsed function identifier.""" - - function_id: str | None - version: str | None - name: str | None - prompt_session_id: str | None - inline_code: str | None - global_function: str | None - - -class ParsedParent(TypedDict): - """Parsed parent reference.""" - - object_type: str - object_id: str - - -class ParsedEvalBody(TypedDict, total=False): - """Type for parsed eval request body.""" - - name: str # Required - parameters: dict[str, Any] - data: Any - scores: list[ParsedFunctionId] - experiment_name: str - project_id: str - parent: str | ParsedParent - stream: bool - - -def validate_typed_dict(data: Any, typed_dict_class: type, path: str = "") -> dict[str, Any]: - """Validate data against a TypedDict definition.""" - if not isinstance(data, dict): - raise ValidationError(f"{path or 'Root'} must be a dictionary, got {type(data).__name__}") - - # Get type hints for the TypedDict - hints = get_type_hints(typed_dict_class, include_extras=True) - required_fields = getattr(typed_dict_class, "__required_keys__", set()) - - validated = {} - - # Check required fields - for field in required_fields: - if field not in data: - raise ValidationError(f"{path}.{field} is required" if path else f"{field} is required") - - # Validate each field - for field_name, field_type in hints.items(): - if field_name not in data: - continue - - value = data[field_name] - field_path = f"{path}.{field_name}" if path else field_name - - try: - validated[field_name] = validate_value(value, field_type, field_path) - except ValidationError: - raise - except Exception as e: - raise ValidationError(f"Error validating {field_path}: {e}") - - return validated - - -def validate_value(value: Any, expected_type: type, path: str) -> Any: - """Validate a value against a type annotation.""" - # Handle None - if value is None: - if type(None) in get_args(expected_type): - return None - raise ValidationError(f"{path} cannot be None") - - # Get the origin type (e.g., Union, List, Dict) - origin = get_origin(expected_type) - - # Handle Union types - if origin is Union: - # Try each type in the union - for arg_type in get_args(expected_type): - try: - return validate_value(value, arg_type, path) - except ValidationError: - continue - raise ValidationError(f"{path} does not match any of the expected types") - - # Handle Optional (which is Union[T, None]) - if origin is Union and type(None) in get_args(expected_type): # Check for Optional[T] which is Union[T, None] - inner_type = get_args(expected_type)[0] - if value is None: - return None - return validate_value(value, inner_type, path) - - # Handle List/Sequence - if origin in (list, list, Sequence): - if not isinstance(value, list): - raise ValidationError(f"{path} must be a list, got {type(value).__name__}") - - item_type = get_args(expected_type)[0] if get_args(expected_type) else Any - return [validate_value(item, item_type, f"{path}[{i}]") for i, item in enumerate(value)] - - # Handle Dict/Mapping - if origin in (dict, dict): - if not isinstance(value, dict): - raise ValidationError(f"{path} must be a dict, got {type(value).__name__}") - - if get_args(expected_type): - key_type, value_type = get_args(expected_type) - validated_dict = {} - for k, v in value.items(): - validated_key = validate_value(k, key_type, f"{path}.{k} (key)") - validated_value = validate_value(v, value_type, f"{path}.{k}") - validated_dict[validated_key] = validated_value - return validated_dict - return value - - # Handle TypedDict - if hasattr(expected_type, "__annotations__"): - return validate_typed_dict(value, expected_type, path) - - # Handle basic types - if expected_type in (str, int, float, bool): - if not isinstance(value, expected_type): - raise ValidationError(f"{path} must be {expected_type.__name__}, got {type(value).__name__}") - return value - - # Handle Any - if expected_type is Any: - return value - - # For complex types we can't validate, just return the value - return value - - -def parse_function_id(data: Any, path: str = "function") -> ParsedFunctionId: - """Parse a FunctionId from various formats.""" - if isinstance(data, dict): - result: ParsedFunctionId = {} - # Accept various function specifications - if "function_id" in data: - result["function_id"] = data["function_id"] - if "version" in data: - result["version"] = data["version"] - return result - elif "name" in data: - result["name"] = data["name"] - return result - elif "prompt_session_id" in data: - result["prompt_session_id"] = data["prompt_session_id"] - return result - elif "inline_code" in data: - result["inline_code"] = data["inline_code"] - return result - elif "global_function" in data: - result["global_function"] = data["global_function"] - return result - raise ValidationError(f"{path} must specify function_id, name, prompt_session_id, or inline_code") - - -def parse_eval_body(request_data: str | bytes | dict) -> ParsedEvalBody: - """ - Parse request body for eval execution. - - This validates against a subset of the RunEval schema that makes sense - for the dev server use case. - """ - # Handle different input types - if isinstance(request_data, (str, bytes)): - try: - data = json.loads(request_data) - except json.JSONDecodeError as e: - raise ValidationError(f"Invalid JSON: {e}") - else: - data = request_data - - if not isinstance(data, dict): - raise ValidationError("Request body must be a JSON object") - - # Required fields - if "name" not in data: - raise ValidationError("name is required") - - name = data["name"] - if not isinstance(name, str): - raise ValidationError(f"name must be a string, got {type(name).__name__}") - - # Build the parsed body - parsed: ParsedEvalBody = {"name": name} - - # Optional fields with validation - if "parameters" in data: - if not isinstance(data["parameters"], dict): - raise ValidationError("parameters must be a dictionary") - parsed["parameters"] = data["parameters"] - - if "data" in data: - # For dev server, we accept inline data arrays or dataset references - parsed["data"] = data["data"] - - if "scores" in data: - scores_data = data["scores"] - if not isinstance(scores_data, list): - raise ValidationError("scores must be an array") - - # Parse each score function - parsed_scores = [] - for i, score in enumerate(scores_data): - try: - parsed_scores.append( - { - "name": score["name"], - "function_id": parse_function_id(score["function_id"], f"scores[{i}]"), - } - ) - except ValidationError as e: - raise ValidationError(f"Invalid score at index {i}: {e}") - - parsed["scores"] = parsed_scores - - if "experiment_name" in data: - if not isinstance(data["experiment_name"], str): - raise ValidationError("experiment_name must be a string") - parsed["experiment_name"] = data["experiment_name"] - - if "project_id" in data: - if not isinstance(data["project_id"], str): - raise ValidationError("project_id must be a string") - parsed["project_id"] = data["project_id"] - - if "parent" in data: - parent = data["parent"] - # InvokeParent can be a string or a complex object - if isinstance(parent, str): - parsed["parent"] = parent - elif isinstance(parent, dict): - # Validate it has the right structure - if "object_type" not in parent or "object_id" not in parent: - raise ValidationError("parent object must have object_type and object_id") - parsed["parent"] = parent - else: - raise ValidationError("parent must be a string or object") - - if "stream" in data: - if not isinstance(data["stream"], bool): - raise ValidationError("stream must be a boolean") - parsed["stream"] = data["stream"] - - return parsed diff --git a/py/src/braintrust/devserver/server.py b/py/src/braintrust/devserver/server.py deleted file mode 100644 index 96f981c47..000000000 --- a/py/src/braintrust/devserver/server.py +++ /dev/null @@ -1,339 +0,0 @@ -import asyncio -import json -import sys -import textwrap -from typing import Any - -try: - import uvicorn - from starlette.applications import Starlette - from starlette.middleware.base import BaseHTTPMiddleware - from starlette.requests import Request - from starlette.responses import JSONResponse, PlainTextResponse, StreamingResponse - from starlette.routing import Route -except ModuleNotFoundError as e: - raise ModuleNotFoundError( - textwrap.dedent( - f"""\ - At least one dependency not found: {str(e)!r} - It is possible that braintrust was installed without the CLI dependencies. Run: - - pip install 'braintrust[cli]' - - to install braintrust with the CLI dependencies (make sure to quote 'braintrust[cli]').""" - ) - ) - -from ..framework import EvalAsync, EvalScorer, Evaluator, ExperimentSummary, SSEProgressEvent -from ..generated_types import FunctionId -from ..logger import BraintrustState, bt_iscoroutinefunction -from ..parameters import parameters_to_json_schema, validate_parameters -from ..span_identifier_v4 import parse_parent -from .auth import AuthorizationMiddleware -from .cache import cached_login -from .cors import create_cors_middleware -from .dataset import get_dataset -from .eval_hooks import SSEQueue -from .schemas import ValidationError, parse_eval_body - -_all_evaluators: dict[str, Evaluator[Any, Any]] = {} - - -class CheckAuthorizedMiddleware(BaseHTTPMiddleware): - def __init__(self, app, allowed_org_name: str | None = None): - super().__init__(app) - self.allowed_org_name = allowed_org_name - self.protected_paths = ["/list", "/eval"] - - async def dispatch(self, request: Request, call_next): - # Only check auth for protected paths - if request.url.path in self.protected_paths: - ctx = getattr(request.state, "ctx", None) - if not ctx or not ctx.token: - return JSONResponse({"error": "Unauthorized"}, status_code=401) - - try: - org_name = ctx.org_name - - if not org_name: - return JSONResponse({"error": "Missing x-bt-org-name header"}, status_code=400) - - if self.allowed_org_name and self.allowed_org_name != org_name: - error_message = f"Org '{org_name}' is not allowed. Only org '{self.allowed_org_name}' is allowed." - return JSONResponse({"error": error_message}, status_code=403) - - state = await cached_login( - api_key=ctx.token, - app_url=ctx.app_origin, - org_name=org_name, - ) - ctx.state = state - except Exception as e: - print(f"Authorization error: {e}", file=sys.stderr) - return JSONResponse({"error": "Unauthorized"}, status_code=401) - - return await call_next(request) - - -async def index(request: Request) -> PlainTextResponse: - return PlainTextResponse("Hello, world!") - - -async def list_evaluators(request: Request) -> JSONResponse: - # Get the authenticated context - ctx = getattr(request.state, "ctx", None) - - if not ctx or not ctx.token: - return JSONResponse({"error": "Unauthorized"}, status_code=401) - - if not ctx.state: - print("Braintrust state not initialized in request", file=sys.stderr) - return JSONResponse({"error": "Unauthorized"}, status_code=401) - - evaluator_list = {} - for name, evaluator in _all_evaluators.items(): - evaluator_list[name] = { - "parameters": parameters_to_json_schema(evaluator.parameters) if evaluator.parameters else {}, - "scores": [{"name": getattr(score, "name", f"score_{i}")} for i, score in enumerate(evaluator.scores)], - } - - return JSONResponse(evaluator_list) - - -async def run_eval(request: Request) -> JSONResponse | StreamingResponse: - """Handle eval execution requests.""" - try: - # Get request body - body = await request.body() - - # Parse and validate the request - eval_data = parse_eval_body(body) - except ValidationError as e: - return JSONResponse({"error": str(e)}, status_code=400) - except Exception as e: - return JSONResponse({"error": f"Internal error: {str(e)}"}, status_code=500) - - # Access the context if needed - ctx = getattr(request.state, "ctx", None) - - if not ctx or not ctx.token: - return JSONResponse({"error": "Unauthorized"}, status_code=401) - - if not ctx.state: - print("Braintrust state not initialized in request", file=sys.stderr) - return JSONResponse({"error": "Unauthorized"}, status_code=401) - - state = ctx.state - - # Check if the evaluator exists - evaluator = _all_evaluators.get(eval_data["name"]) - if not evaluator: - return JSONResponse({"error": f"Evaluator '{eval_data['name']}' not found"}, status_code=404) - - # Get the dataset if data is provided - try: - dataset = await get_dataset(state, eval_data["data"]) - except Exception as e: - print(f"Error loading dataset: {e}", file=sys.stderr) - return JSONResponse({"error": f"Failed to load dataset: {str(e)}"}, status_code=400) - - # Validate parameters if provided - validated_parameters = None - if evaluator.parameters: - request_parameters = eval_data.get("parameters", {}) - try: - validated_parameters = validate_parameters(request_parameters, evaluator.parameters) - except ValueError as e: - return JSONResponse({"error": f"Invalid parameters: {str(e)}"}, status_code=400) - - # Check if streaming is requested - stream = eval_data.get("stream", False) - - # Set up SSE headers for streaming - sse_queue = SSEQueue() - - async def task(input, hooks): - if bt_iscoroutinefunction(evaluator.task): - result = await evaluator.task(input, hooks) - else: - result = evaluator.task(input, hooks) - hooks.report_progress( - { - "format": "code", - "output_type": "completion", - "event": "json_delta", - "data": json.dumps(result), - } - ) - return result - - def on_start_fn(summary: ExperimentSummary): - """Synchronous stream function that schedules async writes.""" - if stream: - summary_json = format_summary(summary) - # Use create_task to schedule the async write without blocking - asyncio.create_task(sse_queue.put_event("start", json.dumps(summary_json))) - - def stream_fn(event: SSEProgressEvent): - """Synchronous stream function that schedules async writes.""" - if stream: - # Use create_task to schedule the async write without blocking - asyncio.create_task(sse_queue.put_event("progress", event)) - - parent = eval_data.get("parent") - if parent: - parent = parse_parent(parent) - - # Override evaluator parameters with validated ones if provided - eval_kwargs = {k: v for (k, v) in evaluator.__dict__.items() if k not in ["eval_name", "project_name"]} - if validated_parameters is not None: - eval_kwargs["parameters"] = validated_parameters - - try: - eval_task = asyncio.create_task( - EvalAsync( - name=eval_data["name"], - **{ - **eval_kwargs, - "state": state, - "scores": evaluator.scores - + [ - make_scorer(state, score["name"], score["function_id"], ctx.project_id) - for score in eval_data.get("scores", []) - ], - "stream": stream_fn, - "on_start": on_start_fn, - "data": dataset, - "task": task, - "experiment_name": eval_data.get("experiment_name"), - "parent": parent, - "project_id": eval_data.get("project_id"), - }, - ) - ) - - if stream: - - async def event_generator(): - """Generate SSE events from the queue.""" - - # Create a task to run the eval and signal completion - async def run_and_complete(): - try: - result = await eval_task - await sse_queue.put_event("summary", format_summary(result.summary)) - except Exception as e: - print(f"Error running eval: {e}", file=sys.stderr) - await sse_queue.put_event("error", str(e)) - finally: - # Send done event and close the queue - await sse_queue.put_event("done", "") - await sse_queue.close() - - # Start the eval task - asyncio.create_task(run_and_complete()) - - # Stream events from the queue - while True: - event = await sse_queue.get() - if event is None: # End of stream - break - yield event - - return StreamingResponse( - event_generator(), - media_type="text/event-stream", - headers={ - "Cache-Control": "no-cache", - "Connection": "keep-alive", - }, - ) - else: - # Wait for the evaluation to complete - result = await eval_task - # Return the summary as JSON - return JSONResponse(format_summary(result.summary)) - except Exception as e: - print(f"Failed to run evaluation: {e}", file=sys.stderr) - return JSONResponse({"error": f"Failed to run evaluation: {str(e)}"}, status_code=500) - - -def create_app(evaluators: list[Evaluator[Any, Any]], org_name: str | None = None): - """Create and configure the Starlette app for the dev server. - - Args: - evaluators: List of evaluators to make available - org_name: Optional organization name to restrict access to - - Returns: - Configured Starlette app - """ - global _all_evaluators - _all_evaluators = {evaluator.eval_name: evaluator for evaluator in evaluators} - - routes = [ - Route("/", endpoint=index), - Route("/list", endpoint=list_evaluators), - Route("/eval", endpoint=run_eval, methods=["POST"]), - ] - - app = Starlette(routes=routes) - # Add middlewares in reverse order (last added is executed first) - app.add_middleware(CheckAuthorizedMiddleware, allowed_org_name=org_name) - app.add_middleware(AuthorizationMiddleware) - app.add_middleware(create_cors_middleware()) - - return app - - -def run_dev_server( - evaluators: list[Evaluator[Any, Any]], host: str = "localhost", port: int = 8300, org_name: str | None = None -): - """Start the dev server. - - Args: - evaluators: List of evaluators to make available - host: Host to bind to - port: Port to bind to - org_name: Optional organization name to restrict access to - """ - print(f"Starting dev server on http://{host}:{port}") - print(f"Loaded {len(evaluators)} evaluator(s): {[e.eval_name for e in evaluators]}") - - app = create_app(evaluators, org_name=org_name) - uvicorn.run(app, host=host, port=port) - - -def snake_to_camel(snake_str: str) -> str: - """Convert snake_case to camelCase.""" - components = snake_str.split("_") - return components[0] + "".join(x.title() for x in components[1:]) if components else snake_str - - -def make_scorer( - state: BraintrustState, name: str, score: FunctionId, project_id: str | None = None -) -> EvalScorer[Any, Any]: - def scorer_fn(input, output, expected, metadata): - request = { - **score, - "input": dict(input=input, output=output, expected=expected, metadata=metadata), - "parent": state.current_span.get().export(), - "stream": False, - "mode": "auto", - "strict": True, - } - headers = {"Accept": "application/json"} - if project_id: - headers["x-bt-project-id"] = project_id - result = state.proxy_conn().post("function/invoke", json=request, headers=headers) - result.raise_for_status() - data = result.json() - return data - - scorer_fn.__name__ = name - return scorer_fn - - -def format_summary(summary: ExperimentSummary) -> dict: - """Format the summary for JSON serialization with camelCase keys.""" - return {snake_to_camel(k): v for (k, v) in summary.as_dict().items()} diff --git a/py/src/braintrust/devserver/test_cached_login.py b/py/src/braintrust/devserver/test_cached_login.py deleted file mode 100644 index e75b1677a..000000000 --- a/py/src/braintrust/devserver/test_cached_login.py +++ /dev/null @@ -1,89 +0,0 @@ -import asyncio -import unittest -from unittest.mock import MagicMock, patch - -from braintrust.devserver import cache - - -class TestCachedLogin(unittest.TestCase): - def setUp(self): - """Clear the cache before each test.""" - cache._login_cache = cache.LRUCache(max_size=32) - - @patch("braintrust.devserver.cache.login_to_state") - def test_cached_login_caches_results(self, mock_login): - """Test that cached_login caches and reuses results.""" - mock_state = MagicMock() - mock_login.return_value = mock_state - - # First call should invoke login_to_state - result1 = asyncio.run(cache.cached_login("api_key_1", "https://app.braintrust.com")) - self.assertEqual(result1, mock_state) - self.assertEqual(mock_login.call_count, 1) - - # Second call with same parameters should use cache - result2 = asyncio.run(cache.cached_login("api_key_1", "https://app.braintrust.com")) - self.assertEqual(result2, mock_state) - self.assertEqual(mock_login.call_count, 1) # Still 1, not called again - - @patch("braintrust.devserver.cache.login_to_state") - def test_cached_login_different_keys(self, mock_login): - """Test that different cache keys create separate entries.""" - mock_state1 = MagicMock() - mock_state2 = MagicMock() - mock_state3 = MagicMock() - - mock_login.side_effect = [mock_state1, mock_state2, mock_state3] - - # Different API keys - result1 = asyncio.run(cache.cached_login("api_key_1", "https://app.braintrust.com")) - result2 = asyncio.run(cache.cached_login("api_key_2", "https://app.braintrust.com")) - - self.assertEqual(result1, mock_state1) - self.assertEqual(result2, mock_state2) - self.assertEqual(mock_login.call_count, 2) - - # Different org_name - result3 = asyncio.run(cache.cached_login("api_key_1", "https://app.braintrust.com", org_name="org1")) - self.assertEqual(result3, mock_state3) - self.assertEqual(mock_login.call_count, 3) - - @patch("braintrust.devserver.cache.login_to_state") - def test_cached_login_with_org_name(self, mock_login): - """Test caching with org_name parameter.""" - mock_state = MagicMock() - mock_login.return_value = mock_state - - # Call with org_name - result1 = asyncio.run(cache.cached_login("api_key_1", "https://app.braintrust.com", org_name="test_org")) - self.assertEqual(result1, mock_state) - self.assertEqual(mock_login.call_count, 1) - - # Same call should use cache - result2 = asyncio.run(cache.cached_login("api_key_1", "https://app.braintrust.com", org_name="test_org")) - self.assertEqual(result2, mock_state) - self.assertEqual(mock_login.call_count, 1) - - # Different org_name should not use cache - result3 = asyncio.run(cache.cached_login("api_key_1", "https://app.braintrust.com", org_name="other_org")) - self.assertEqual(mock_login.call_count, 2) - - @patch("braintrust.devserver.cache.login_to_state") - def test_cached_login_propagates_exceptions(self, mock_login): - """Test that exceptions from login_to_state are propagated.""" - mock_login.side_effect = ValueError("Invalid API key") - - with self.assertRaises(ValueError) as cm: - asyncio.run(cache.cached_login("bad_key", "https://app.braintrust.com")) - - self.assertEqual(str(cm.exception), "Invalid API key") - - # Verify exception is not cached - second call should try again - with self.assertRaises(ValueError): - asyncio.run(cache.cached_login("bad_key", "https://app.braintrust.com")) - - self.assertEqual(mock_login.call_count, 2) - - -if __name__ == "__main__": - unittest.main() diff --git a/py/src/braintrust/devserver/test_lru_cache.py b/py/src/braintrust/devserver/test_lru_cache.py deleted file mode 100644 index de2c51572..000000000 --- a/py/src/braintrust/devserver/test_lru_cache.py +++ /dev/null @@ -1,117 +0,0 @@ -import unittest -from unittest.mock import MagicMock - -from braintrust.devserver.cache import LRUCache - - -class TestDevServerLRUCache(unittest.TestCase): - def test_store_and_retrieve_values(self): - """Test storing and retrieving values.""" - cache = LRUCache(max_size=3) - mock_state = MagicMock() - cache.set("key1", mock_state) - self.assertEqual(cache.get("key1"), mock_state) - - def test_return_none_for_missing_keys(self): - """Test returning None for missing keys.""" - cache = LRUCache() - self.assertIsNone(cache.get("missing")) - - def test_respect_max_size_evicts_lru(self): - """Test respecting max size and evicting least recently used.""" - cache = LRUCache(max_size=2) - state1, state2, state3 = MagicMock(), MagicMock(), MagicMock() - - cache.set("a", state1) - cache.set("b", state2) - cache.set("c", state3) # Should evict "a" - - self.assertIsNone(cache.get("a")) - self.assertEqual(cache.get("b"), state2) - self.assertEqual(cache.get("c"), state3) - - def test_access_order_updates_on_get(self): - """Test that accessing an item moves it to the end (most recently used).""" - cache = LRUCache(max_size=3) - state1, state2, state3, state4 = MagicMock(), MagicMock(), MagicMock(), MagicMock() - - cache.set("a", state1) - cache.set("b", state2) - cache.set("c", state3) - - # Access "a" to make it most recently used - self.assertEqual(cache.get("a"), state1) - - # Add "d", should evict "b" (least recently used) - cache.set("d", state4) - - self.assertEqual(cache.get("a"), state1) # Still present - self.assertIsNone(cache.get("b")) # Evicted - self.assertEqual(cache.get("c"), state3) - self.assertEqual(cache.get("d"), state4) - - def test_update_existing_key_maintains_position(self): - """Test updating an existing key moves it to the end.""" - cache = LRUCache(max_size=3) - state1, state2, state3, state1_updated = MagicMock(), MagicMock(), MagicMock(), MagicMock() - - cache.set("a", state1) - cache.set("b", state2) - cache.set("c", state3) - - # Update "a" with new value - cache.set("a", state1_updated) - - # Add new item, should evict "b" not "a" - state4 = MagicMock() - cache.set("d", state4) - - self.assertEqual(cache.get("a"), state1_updated) - self.assertIsNone(cache.get("b")) - self.assertEqual(cache.get("c"), state3) - self.assertEqual(cache.get("d"), state4) - - def test_cache_with_size_one(self): - """Test cache behavior with max_size=1.""" - cache = LRUCache(max_size=1) - state1, state2 = MagicMock(), MagicMock() - - cache.set("a", state1) - self.assertEqual(cache.get("a"), state1) - - cache.set("b", state2) - self.assertIsNone(cache.get("a")) - self.assertEqual(cache.get("b"), state2) - - def test_empty_cache_operations(self): - """Test operations on empty cache.""" - cache = LRUCache(max_size=5) - self.assertIsNone(cache.get("any_key")) - self.assertEqual(len(cache.cache), 0) - self.assertEqual(len(cache.access_order), 0) - - def test_access_order_consistency(self): - """Test that access_order list stays consistent with cache dict.""" - cache = LRUCache(max_size=3) - states = [MagicMock() for _ in range(5)] - - # Add items - for i, state in enumerate(states[:3]): - cache.set(f"key{i}", state) - - # Verify consistency - self.assertEqual(len(cache.cache), len(cache.access_order)) - self.assertEqual(set(cache.cache.keys()), set(cache.access_order)) - - # Add more items to trigger evictions - for i, state in enumerate(states[3:], start=3): - cache.set(f"key{i}", state) - - # Verify consistency after evictions - self.assertEqual(len(cache.cache), len(cache.access_order)) - self.assertEqual(set(cache.cache.keys()), set(cache.access_order)) - self.assertEqual(len(cache.cache), cache.max_size) - - -if __name__ == "__main__": - unittest.main() diff --git a/py/src/braintrust/devserver/test_server_integration.py b/py/src/braintrust/devserver/test_server_integration.py deleted file mode 100644 index 26dc4dd46..000000000 --- a/py/src/braintrust/devserver/test_server_integration.py +++ /dev/null @@ -1,207 +0,0 @@ -import json -import os -from pathlib import Path -from typing import Any - -import pytest -from braintrust.framework import _evals -from braintrust.test_helpers import has_devserver_installed - - -@pytest.fixture -def client(): - """Create test client using the real simple_eval.py example.""" - # Skip if devserver dependencies are not installed - if not has_devserver_installed(): - pytest.skip("Devserver dependencies not installed (requires .[cli])") - - # Import CLI dependencies inside the fixture - from braintrust.devserver.server import create_app - from starlette.testclient import TestClient - - # Use the real simple_eval.py example - eval_file = Path(__file__).parent.parent.parent.parent / "examples" / "evals" / "simple_eval.py" - - # Clear any existing evaluators - _evals.clear() - - # Load the eval file to register evaluators (but don't run them) - spec = __import__("importlib.util").util.spec_from_file_location("simple_eval", str(eval_file)) - module = __import__("importlib.util").util.module_from_spec(spec) - - # Get evaluators from the module without executing Eval() - # We need to parse the file and extract the Evaluator definition - import re - - from braintrust import Evaluator - - def task(input: str, hooks) -> str: - """Simple math task.""" - match = re.search(r"(\d+)\+(\d+)", input) - if match: - return str(int(match.group(1)) + int(match.group(2))) - return "I don't know" - - def scorer(input: str, output: str, expected: str) -> float: - """Simple exact match scorer.""" - return 1.0 if output == expected else 0.0 - - evaluator = Evaluator( - project_name="test-math-eval", - eval_name="simple-math-eval", - data=lambda: [ - {"input": "What is 2+2?", "expected": "4"}, - {"input": "What is 3+3?", "expected": "6"}, - {"input": "What is 5+5?", "expected": "10"}, - ], - task=task, - scores=[scorer], - experiment_name=None, - metadata=None, - ) - - # Create app with the evaluator - app = create_app([evaluator]) - return TestClient(app) - - -@pytest.fixture -def api_key(): - """Provide test API key.""" - return os.getenv("BRAINTRUST_API_KEY", "test-api-key") - - -@pytest.fixture -def org_name(): - """Provide test org name.""" - return os.getenv("BRAINTRUST_ORG_NAME", "matt-test-org") - - -def test_devserver_health_check(client): - """Test that server responds to health check.""" - response = client.get("/") - assert response.status_code == 200 - assert response.text == "Hello, world!" - - -@pytest.mark.vcr -def test_devserver_list_evaluators(client, api_key, org_name): - """Test listing evaluators endpoint.""" - response = client.get("/list", headers={"x-bt-auth-token": api_key, "x-bt-org-name": org_name}) - assert response.status_code == 200 - evaluators = response.json() - assert "simple-math-eval" in evaluators - - -def parse_sse_events(response_text: str) -> list[dict[str, Any]]: - """Parse SSE events from response text.""" - events = [] - lines = response_text.strip().split("\n") - i = 0 - - while i < len(lines): - if lines[i].startswith("event: "): - event_type = lines[i][7:].strip() - i += 1 - - if i < len(lines) and lines[i].startswith("data: "): - data_str = lines[i][6:].strip() - try: - data = json.loads(data_str) if data_str else None - except json.JSONDecodeError: - data = data_str - - events.append({"event": event_type, "data": data}) - i += 1 - else: - events.append({"event": event_type, "data": None}) - else: - i += 1 - - return events - - -@pytest.mark.skip -@pytest.mark.vcr -def test_eval_sse_streaming(client, api_key, org_name): - """ - Comprehensive test for SSE streaming during eval execution. - - Verifies: - 1. Event order: start โ†’ progress* โ†’ summary โ†’ done - 2. Progress events are emitted - 3. Start event has metadata (experimentName, projectName) - 4. Summary event has camelCase fields (not snake_case) - 5. Response format is correct - """ - response = client.post( - "/eval", - headers={ - "x-bt-auth-token": api_key, - "x-bt-org-name": org_name, - "Content-Type": "application/json", - "Accept": "text/event-stream", - }, - json={ - "name": "simple-math-eval", - "stream": True, - "data": [ - {"input": "What is 2+2?", "expected": "4"}, - {"input": "What is 3+3?", "expected": "6"}, - ], - }, - ) - - assert response.status_code == 200 - assert response.headers["Content-Type"] == "text/event-stream; charset=utf-8" - - events = parse_sse_events(response.text) - event_types = [e["event"] for e in events] - - # Verify event order - assert len(event_types) > 0 - assert event_types[0] == "start" - assert event_types[-1] == "done" - assert "summary" in event_types - - # Verify progress events exist - progress_events = [e for e in events if e["event"] == "progress"] - assert len(progress_events) > 0 - - # Verify start event has metadata - start_event = next(e for e in events if e["event"] == "start") - assert "experimentName" in start_event["data"] - assert "projectName" in start_event["data"] - - # Verify summary event has camelCase fields - summary_event = next(e for e in events if e["event"] == "summary") - assert summary_event is not None - summary_data = summary_event["data"] - assert summary_data is not None - - assert "experimentName" in summary_data - assert "projectName" in summary_data - assert "scores" in summary_data - - # Should NOT have snake_case fields - assert "experiment_name" not in summary_data - assert "project_name" not in summary_data - - -@pytest.mark.vcr -def test_eval_error_handling(client, api_key, org_name): - """Test error handling for non-existent evaluator.""" - response = client.post( - "/eval", - headers={ - "x-bt-auth-token": api_key, - "x-bt-org-name": org_name, - "Content-Type": "application/json", - }, - json={"name": "non-existent-eval", "stream": False}, - ) - - assert response.status_code == 404 - error = response.json() - assert "error" in error - assert "not found" in error["error"].lower() diff --git a/py/src/braintrust/framework.py b/py/src/braintrust/framework.py deleted file mode 100644 index 4aac7dc7d..000000000 --- a/py/src/braintrust/framework.py +++ /dev/null @@ -1,1701 +0,0 @@ -import abc -import asyncio -import contextvars -import dataclasses -import inspect -import json -import re -import sys -import traceback -import warnings -from collections import defaultdict -from collections.abc import Awaitable, Callable, Coroutine, Iterable, Iterator, Sequence -from concurrent.futures import ThreadPoolExecutor -from contextlib import contextmanager -from multiprocessing import cpu_count -from typing import ( - Any, - Generic, - Literal, - Optional, - TypeVar, - Union, -) - -from tqdm.asyncio import tqdm as async_tqdm -from tqdm.auto import tqdm as std_tqdm -from typing_extensions import NotRequired, Protocol, TypedDict - -from .generated_types import FunctionFormat, FunctionOutputType, ObjectReference -from .git_fields import GitMetadataSettings, RepoInfo -from .logger import ( - BraintrustState, - Dataset, - Experiment, - ExperimentSummary, - Metadata, - ScoreSummary, - Span, - _ExperimentDatasetEvent, - parent_context, - start_span, - stringify_exception, -) -from .logger import init as _init_experiment -from .parameters import EvalParameters -from .resource_manager import ResourceManager -from .score import Score, is_score, is_scorer -from .serializable_data_class import SerializableDataClass -from .span_types import SpanTypeAttribute -from .util import bt_iscoroutinefunction, eprint, merge_dicts - -Input = TypeVar("Input") -Output = TypeVar("Output") - - -# https://stackoverflow.com/questions/287871/how-do-i-print-colored-text-to-the-terminal -class bcolors: - HEADER = "\033[95m" - OKBLUE = "\033[94m" - OKCYAN = "\033[96m" - OKGREEN = "\033[92m" - WARNING = "\033[93m" - FAIL = "\033[91m" - ENDC = "\033[0m" - BOLD = "\033[1m" - UNDERLINE = "\033[4m" - - -@dataclasses.dataclass -class EvalCase(SerializableDataClass, Generic[Input, Output]): - """ - An evaluation case. This is a single input to the evaluation task, along with an optional expected - output, metadata, and tags. - """ - - input: Input - expected: Output | None = None - metadata: Metadata | None = None - tags: Sequence[str] | None = None - - # These fields are only set if the EvalCase is part of a Dataset. - id: str | None = None - _xact_id: str | None = None - created: str | None = None - - -class _EvalCaseDictNoOutput(Generic[Input], TypedDict): - """ - Workaround for the Pyright type checker handling of generics. Specifically, - the type checker doesn't know that a dict which is missing the key - "expected" can be used to satisfy `_EvalCaseDict[Input, Output]` for any - `Output` type. - """ - - input: Input - metadata: NotRequired[Metadata | None] - tags: NotRequired[Sequence[str] | None] - - id: NotRequired[str | None] - _xact_id: NotRequired[str | None] - - -class _EvalCaseDict(Generic[Input, Output], _EvalCaseDictNoOutput[Input]): - """ - Mirrors EvalCase for callers who pass a dict instead of dataclass. - """ - - expected: NotRequired[Output | None] - - -# Inheritance doesn't quite work for dataclasses, so we redefine the fields -# from EvalCase here. -@dataclasses.dataclass -class EvalResult(SerializableDataClass, Generic[Input, Output]): - """The result of an evaluation. This includes the input, expected output, actual output, and metadata.""" - - input: Input - output: Output - scores: dict[str, float | None] - expected: Output | None = None - metadata: Metadata | None = None - tags: list[str] | None = None - error: Exception | None = None - exc_info: str | None = None - - -@dataclasses.dataclass -class TaskProgressEvent(TypedDict): - """Progress event that can be reported during task execution.""" - - format: FunctionFormat - output_type: FunctionOutputType - event: Literal[ - "reasoning_delta", - "text_delta", - "json_delta", - "error", - "console", - "start", - "done", - "progress", - ] - data: str - - -class SSEProgressEvent(TaskProgressEvent): - """ - A progress event that can be reported during task execution, specifically for SSE (Server-Sent Events) streams. - This is a subclass of TaskProgressEvent with additional fields for SSE-specific metadata. - """ - - id: str - object_type: str - origin: ObjectReference - name: str - - -class EvalHooks(abc.ABC, Generic[Output]): - """ - An object that can be used to add metadata to an evaluation. This is passed to the `task` function. - """ - - @property - @abc.abstractmethod - def metadata(self) -> Metadata: - """ - The metadata object for the current evaluation. You can mutate this object to add or remove metadata. - """ - - @property - @abc.abstractmethod - def expected(self) -> Output | None: - """ - The expected output for the current evaluation. - """ - - @property - @abc.abstractmethod - def span(self) -> Span: - """ - Access the span under which the task is run. Also accessible via braintrust.current_span() - """ - - @property - @abc.abstractmethod - def trial_index(self) -> int: - """ - The index of the current trial (0-based). This is useful when trial_count > 1. - """ - - @property - @abc.abstractmethod - def tags(self) -> Sequence[str]: - """ - The tags for the current evaluation. You can mutate this object to add or remove tags. - """ - - @abc.abstractmethod - def report_progress(self, progress: TaskProgressEvent) -> None: - """ - Report progress that will show up in the playground. - """ - ... - - @abc.abstractmethod - def meta(self, **info: Any) -> None: - """ - DEPRECATED: Use the metadata field on the hook directly. - - Adds metadata to the evaluation. This metadata will be logged to the Braintrust. You can pass in metadaa - as keyword arguments, e.g. `hooks.meta(foo="bar")`. - """ - ... - - @property - @abc.abstractmethod - def parameters(self) -> dict[str, Any] | None: - """ - The parameters for the current evaluation. These are the validated parameter values - that were passed to the evaluator. - """ - - -class EvalScorerArgs(SerializableDataClass, Generic[Input, Output]): - """ - Arguments passed to an evaluator scorer. This includes the input, expected output, actual output, and metadata. - """ - - input: Input - output: Output - expected: Output | None = None - metadata: Metadata | None = None - - -OneOrMoreScores = Union[float, int, bool, None, Score, list[Score]] - - -# Synchronous scorer interface - implements callable -class SyncScorerLike(Protocol, Generic[Input, Output]): - """ - Protocol for synchronous scorers that implement the callable interface. - This is the most common interface and is used when no async version is available. - """ - - def __call__( - self, input: Input, output: Output, expected: Output | None = None, **kwargs: Any - ) -> OneOrMoreScores: ... - - -# Asynchronous scorer interface -class AsyncScorerLike(Protocol, Generic[Input, Output]): - """ - Protocol for asynchronous scorers that implement the eval_async interface. - The framework will prefer this interface if available. - """ - - async def eval_async(self, output: Output, expected: Output | None = None, **kwargs: Any) -> OneOrMoreScores: ... - - -# Union type for any kind of scorer (for typing) -ScorerLike = Union[SyncScorerLike[Input, Output], AsyncScorerLike[Input, Output]] - -EvalScorer = Union[ - ScorerLike[Input, Output], - type[ScorerLike[Input, Output]], - Callable[[Input, Output, Output], OneOrMoreScores], - Callable[[Input, Output, Output], Awaitable[OneOrMoreScores]], -] - - -@dataclasses.dataclass -class BaseExperiment: - """ - Use this to specify that the dataset should actually be the data from a previous (base) experiment. - If you do not specify a name, Braintrust will automatically figure out the best base experiment to - use based on your git history (or fall back to timestamps). - """ - - name: str | None = None - """ - The name of the base experiment to use. If unspecified, Braintrust will automatically figure out the best base - using your git history (or fall back to timestamps). - """ - - -_AnyEvalCase = Union[ - EvalCase[Input, Output], - _EvalCaseDict[Input, Output], - _EvalCaseDictNoOutput[Input], - _ExperimentDatasetEvent, -] - -_EvalDataObject = Union[ - Iterable[_AnyEvalCase[Input, Output]], - Iterator[_AnyEvalCase[Input, Output]], - Awaitable[Iterator[_AnyEvalCase[Input, Output]]], - Callable[[], Union[Iterator[_AnyEvalCase[Input, Output]], Awaitable[Iterator[_AnyEvalCase[Input, Output]]]]], - BaseExperiment, -] - -EvalData = Union[_EvalDataObject[Input, Output], type[_EvalDataObject[Input, Output]], Dataset] - -EvalTask = Union[ - Callable[[Input], Union[Output, Awaitable[Output]]], - Callable[[Input, EvalHooks[Output]], Union[Output, Awaitable[Output]]], -] - -ErrorScoreHandler = Callable[[Span, EvalCase[Input, Output], list[str]], Optional[dict[str, float]]] - - -@dataclasses.dataclass -class Evaluator(Generic[Input, Output]): - """ - An evaluator is an abstraction that defines an evaluation dataset, a task to run on the dataset, and a set of - scorers to evaluate the results of the task. Each method attribute can be synchronous or asynchronous (for - optimal performance, it is recommended to provide asynchronous implementations). - - You should not create Evaluators directly if you plan to use the Braintrust eval framework. Instead, you should - create them using the `Eval()` method, which will register them so that `braintrust eval ...` can find them. - """ - - project_name: str - """ - The name of the project the eval falls under. - """ - - eval_name: str - """ - A name that describes the experiment. You do not need to change it each time the experiment runs. - """ - - data: EvalData[Input, Output] - """ - Returns an iterator over the evaluation dataset. Each element of the iterator should be an `EvalCase` or a dict - with the same fields as an `EvalCase` (`input`, `expected`, `metadata`). - """ - - task: EvalTask[Input, Output] - """ - Runs the evaluation task on a single input. The `hooks` object can be used to add metadata to the evaluation. - """ - - scores: list[EvalScorer[Input, Output]] - """ - A list of scorers to evaluate the results of the task. Each scorer can be a Scorer object or a function - that takes `input`, `output`, and `expected` arguments and returns a `Score` object. The function can be async. - """ - - experiment_name: str | None - """ - Optional experiment name. If not specified, a name will be generated automatically. - """ - - metadata: Metadata | None - """ - A dictionary with additional data about the test example, model outputs, or just about anything else that's - relevant, that you can use to help find and analyze examples later. For example, you could log the `prompt`, - example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any - JSON-serializable type, but its keys must be strings. - """ - - trial_count: int = 1 - """ - The number of times to run the evaluator per input. This is useful for evaluating applications that - have non-deterministic behavior and gives you both a stronger aggregate measure and a sense of the - variance in the results. - """ - - is_public: bool = False - """ - Whether the experiment should be public. Defaults to false. - """ - - update: bool = False - """ - Whether to update an existing experiment with `experiment_name` if one exists. Defaults to false. - """ - - timeout: float | None = None - """ - The duration, in seconds, after which to time out the evaluation. - Defaults to None, in which case there is no timeout. - """ - - max_concurrency: int | None = None - """ - The maximum number of tasks/scorers that will be run concurrently. - Defaults to None, in which case there is no max concurrency. - """ - - project_id: str | None = None - """ - If specified, uses the given project ID instead of the evaluator's name to identify the project. - """ - - base_experiment_name: str | None = None - """ - An optional experiment name to use as a base. If specified, the new experiment will be summarized and - compared to this experiment. - """ - - base_experiment_id: str | None = None - """ - An optional experiment id to use as a base. If specified, the new experiment will be summarized and - compared to this experiment. This takes precedence over `base_experiment_name` if specified. - """ - - git_metadata_settings: GitMetadataSettings | None = None - """ - Optional settings for collecting git metadata. By default, will collect all - git metadata fields allowed in org-level settings. - """ - - repo_info: RepoInfo | None = None - """ - Optionally explicitly specify the git metadata for this experiment. This - takes precedence over `git_metadata_settings` if specified. - """ - - error_score_handler: ErrorScoreHandler | None = None - """ - Optionally supply a custom function to specifically handle score values when tasks or scoring functions have errored. - A default implementation is exported as `default_error_score_handler` which will log a 0 score to the root span for any scorer that was not run. - """ - - description: str | None = None - """ - An optional description for the experiment. - """ - - summarize_scores: bool = True - """ - Whether to summarize the scores of the experiment after it has run. - """ - - parameters: EvalParameters | None = None - """ - A set of parameters that will be passed to the evaluator. - Can be used to define prompts or other configurable values. - """ - - -@dataclasses.dataclass -class EvalResultWithSummary(SerializableDataClass, Generic[Input, Output]): - summary: ExperimentSummary - results: list[EvalResult[Input, Output]] - - def _repr_pretty_(self, p, cycle): - p.text(f'EvalResultWithSummary(summary="...", results=[...])') - - -EvalReport = TypeVar("EvalReport") - - -async def await_or_run(event_loop, f, *args, **kwargs): - if bt_iscoroutinefunction(f): - return await f(*args, **kwargs) - else: - - def run_f(args, kwargs, ctx): - tokens = [(var, var.set(value)) for var, value in ctx.items()] - try: - return f(*args, **kwargs) - finally: - for var, tok in tokens: - var.reset(tok) - - with _THREAD_POOL_SINGLETON.get() as thread_pool: - return await event_loop.run_in_executor( - thread_pool.thread_pool(), run_f, args, kwargs, contextvars.copy_context() - ) - - -def _call_user_fn_args(fn, kwargs): - try: - signature = inspect.signature(fn) - except: - return [], kwargs - - accepts_kwargs = any(p.kind == inspect.Parameter.VAR_KEYWORD for p in signature.parameters.values()) - - positional_args = [] - final_kwargs = {} - - for name, param in signature.parameters.items(): - # VAR_POSITIONAL is *args - # VAR_KEYWORD is **kwargs - # We don't want to use eithers' name - if param.kind == inspect.Parameter.VAR_POSITIONAL or param.kind == inspect.Parameter.VAR_KEYWORD: - continue - - if name in kwargs: - final_kwargs[name] = kwargs.pop(name) - else: - next_arg = list(kwargs.keys())[0] - final_kwargs[name] = kwargs.pop(next_arg) - - if accepts_kwargs: - final_kwargs.update(kwargs) - - return positional_args, final_kwargs - - -async def call_user_fn(event_loop, fn, **kwargs): - positional_args, final_kwargs = _call_user_fn_args(fn, kwargs) - return await await_or_run(event_loop, fn, *positional_args, **final_kwargs) - - -@dataclasses.dataclass -class ReporterDef(SerializableDataClass, Generic[Input, Output, EvalReport]): - """ - A reporter takes an evaluator and its result and returns a report. - """ - - name: str - """ - The name of the reporter. - """ - - report_eval: Callable[ - [Evaluator[Input, Output], EvalResultWithSummary[Input, Output], bool, bool], - EvalReport | Awaitable[EvalReport], - ] - """ - A function that takes an evaluator and its result and returns a report. - """ - - report_run: Callable[[list[EvalReport], bool, bool], bool | Awaitable[bool]] - """ - A function that takes all evaluator results and returns a boolean indicating whether the run was successful. - If you return false, the `braintrust eval` command will exit with a non-zero status code. - """ - - async def _call_report_eval( - self, - evaluator: Evaluator[Input, Output], - result: EvalResultWithSummary[Input, Output], - verbose: bool, - jsonl: bool, - ) -> EvalReport | Awaitable[EvalReport]: - event_loop = asyncio.get_event_loop() - return await call_user_fn( - event_loop, self.report_eval, evaluator=evaluator, result=result, verbose=verbose, jsonl=jsonl - ) - - async def _call_report_run(self, results: list[EvalReport], verbose: bool, jsonl: bool) -> bool | Awaitable[bool]: - event_loop = asyncio.get_event_loop() - return await call_user_fn(event_loop, self.report_run, results=results, verbose=verbose, jsonl=jsonl) - - -@dataclasses.dataclass -class EvaluatorInstance(SerializableDataClass, Generic[Input, Output, EvalReport]): - evaluator: Evaluator[Input, Output] - reporter: ReporterDef[Input, Output, EvalReport] | str | None - - -@dataclasses.dataclass -class EvaluatorFile(SerializableDataClass): - evaluators: dict[str, EvaluatorInstance] = dataclasses.field(default_factory=dict) - reporters: dict[str, ReporterDef] = dataclasses.field(default_factory=dict) - - def clear(self): - self.evaluators.clear() - self.reporters.clear() - - def copy(self): - return EvaluatorFile( - evaluators={k: v for k, v in self.evaluators.items()}, - reporters={k: v for k, v in self.reporters.items()}, - ) - - -_evals = EvaluatorFile() -_lazy_load = False - - -@contextmanager -def _set_lazy_load(lazy_load: bool): - global _lazy_load - current = _lazy_load - try: - _lazy_load = lazy_load - yield - finally: - _lazy_load = current - - -def _is_lazy_load(): - return _lazy_load - - -def pluralize(n, singular, plural): - if n == 1: - return singular - else: - return plural - - -def report_failures(evaluator: Evaluator, failing_results: Iterable[EvalResult], verbose: bool, jsonl: bool) -> None: - eprint( - f"{bcolors.FAIL}Evaluator {evaluator.eval_name} failed with {len(failing_results)} {pluralize(len(failing_results), 'error', 'errors')}{bcolors.ENDC}" - ) - - errors = [ - ( - result.exc_info - if verbose or jsonl - else "\n".join(traceback.format_exception_only(type(result.error), result.error)) - ) - for result in failing_results - ] - - if jsonl: - print(json.dumps({"eval_name": evaluator.eval_name, "errors": errors})) - else: - info = "".join(errors).rstrip() - eprint(f"{bcolors.FAIL}{info}{bcolors.ENDC}") - - eprint(f"{bcolors.FAIL}Add --verbose to see full stack traces.{bcolors.ENDC}") - - -def report_evaluator_result(evaluator: Evaluator, result: EvalResultWithSummary, verbose: bool, jsonl: bool) -> bool: - results = result.results - summary = result.summary - - failing_results = [x for x in results if x.error] - if len(failing_results) > 0: - report_failures(evaluator, failing_results, verbose=verbose, jsonl=jsonl) - else: - print(json.dumps(summary.as_dict()) if jsonl else f"{summary}") - - return len(failing_results) == 0 - - -default_reporter = ReporterDef( - name="default", - report_eval=report_evaluator_result, - report_run=lambda results, verbose, jsonl: all(x for x in results), -) - - -def _make_eval_name(name: str, experiment_name: str | None): - out = name - if experiment_name is not None: - out += f" [experiment_name={experiment_name}]" - return out - - -def _EvalCommon( - name: str, - data: EvalData[Input, Output], - task: EvalTask[Input, Output], - scores: Sequence[EvalScorer[Input, Output]], - experiment_name: str | None, - trial_count: int, - metadata: Metadata | None, - is_public: bool, - update: bool, - reporter: ReporterDef[Input, Output, EvalReport] | None, - timeout: float | None, - max_concurrency: int | None, - project_id: str | None, - base_experiment_name: str | None, - base_experiment_id: str | None, - git_metadata_settings: GitMetadataSettings | None, - repo_info: RepoInfo | None, - description: str | None, - summarize_scores: bool, - no_send_logs: bool, - error_score_handler: ErrorScoreHandler | None = None, - parameters: EvalParameters | None = None, - on_start: Callable[[ExperimentSummary], None] | None = None, - stream: Callable[[SSEProgressEvent], None] | None = None, - parent: str | None = None, - state: BraintrustState | None = None, - enable_cache: bool = True, -) -> Callable[[], Coroutine[Any, Any, EvalResultWithSummary[Input, Output]]]: - """ - This helper is needed because in case of `_lazy_load`, we need to update - the `_evals` global immediately instead of whenever the coroutine is - awaited. - """ - eval_name = _make_eval_name(name, experiment_name) - - global _evals - if eval_name in _evals.evaluators: - eval_name = f"{eval_name}_{len(_evals.evaluators)}" - - evaluator = Evaluator( - eval_name=eval_name, - project_name=name, - data=data, - task=task, - scores=scores, - experiment_name=experiment_name, - trial_count=trial_count, - metadata=metadata, - is_public=is_public, - update=update, - timeout=timeout, - max_concurrency=max_concurrency, - project_id=project_id, - base_experiment_name=base_experiment_name, - base_experiment_id=base_experiment_id, - git_metadata_settings=git_metadata_settings, - repo_info=repo_info, - error_score_handler=error_score_handler, - description=description, - summarize_scores=summarize_scores, - parameters=parameters, - ) - - if _lazy_load: - _evals.evaluators[eval_name] = EvaluatorInstance(evaluator=evaluator, reporter=reporter) - - # Better to return this empty object than have an annoying-to-use signature. - async def make_empty_summary(): - return EvalResultWithSummary(summary=build_local_summary(evaluator, []), results=[]) - - return make_empty_summary - else: - if isinstance(reporter, str): - raise ValueError( - "Must specify a reporter object, not a name. Can only specify reporter names when running 'braintrust eval'" - ) - - reporter = reporter or default_reporter - - if base_experiment_name is None and isinstance(evaluator.data, BaseExperiment): - base_experiment_name = evaluator.data.name - - dataset = None - if isinstance(evaluator.data, Dataset): - dataset = evaluator.data - - # NOTE: This code is duplicated with run_evaluator_task in py/src/braintrust/cli/eval.py. - # Make sure to update those arguments if you change this. - experiment = None - if not no_send_logs and parent is None: - experiment = init_experiment( - project_name=evaluator.project_name if evaluator.project_id is None else None, - project_id=evaluator.project_id, - experiment_name=evaluator.experiment_name, - description=evaluator.description, - metadata=evaluator.metadata, - is_public=evaluator.is_public, - update=evaluator.update, - base_experiment=base_experiment_name, - base_experiment_id=base_experiment_id, - git_metadata_settings=evaluator.git_metadata_settings, - repo_info=evaluator.repo_info, - dataset=dataset, - state=state, - ) - - if on_start: - summary = experiment.summarize(summarize_scores=False) - on_start(summary) - - async def run_to_completion(): - with parent_context(parent, state): - try: - ret = await run_evaluator(experiment, evaluator, 0, [], stream, state, enable_cache) - reporter.report_eval(evaluator, ret, verbose=True, jsonl=False) - return ret - finally: - if experiment: - experiment.flush() - elif state is not None: - state.flush() - - return run_to_completion - - -async def EvalAsync( - name: str, - data: EvalData[Input, Output], - task: EvalTask[Input, Output], - scores: Sequence[EvalScorer[Input, Output]], - experiment_name: str | None = None, - trial_count: int = 1, - metadata: Metadata | None = None, - is_public: bool = False, - update: bool = False, - reporter: ReporterDef[Input, Output, EvalReport] | None = None, - timeout: float | None = None, - max_concurrency: int | None = None, - project_id: str | None = None, - base_experiment_name: str | None = None, - base_experiment_id: str | None = None, - git_metadata_settings: GitMetadataSettings | None = None, - repo_info: RepoInfo | None = None, - error_score_handler: ErrorScoreHandler | None = None, - description: str | None = None, - summarize_scores: bool = True, - no_send_logs: bool = False, - parameters: EvalParameters | None = None, - on_start: Callable[[ExperimentSummary], None] | None = None, - stream: Callable[[SSEProgressEvent], None] | None = None, - parent: str | None = None, - state: BraintrustState | None = None, - enable_cache: bool = True, -) -> EvalResultWithSummary[Input, Output]: - """ - A function you can use to define an evaluator. This is a convenience wrapper around the `Evaluator` class. - - Use this function over `Eval()` when you are running in an async context, including in a Jupyter notebook. - - Example: - ```python - await EvalAsync( - name="my-evaluator", - data=lambda: [ - EvalCase(input=1, expected=2), - EvalCase(input=2, expected=4), - ], - task=lambda input, hooks: input * 2, - scores=[ - NumericDiff, - ], - ) - ``` - - :param name: The name of the evaluator. This corresponds to a project name in Braintrust. - :param data: Returns an iterator over the evaluation dataset. Each element of the iterator should be a `EvalCase`. - :param task: Runs the evaluation task on a single input. The `hooks` object can be used to add metadata to the evaluation. - :param scores: A list of scorers to evaluate the results of the task. Each scorer can be a Scorer object or a function - that takes an `EvalScorerArgs` object and returns a `Score` object. - :param experiment_name: (Optional) Experiment name. If not specified, a name will be generated automatically. - :param trial_count: The number of times to run the evaluator per input. This is useful for evaluating applications that - have non-deterministic behavior and gives you both a stronger aggregate measure and a sense of the variance in the results. - :param metadata: (Optional) A dictionary with additional data about the test example, model outputs, or just about - anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log - the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` - can be any JSON-serializable type, but its keys must be strings. - :param is_public: (Optional) Whether the experiment should be public. Defaults to false. - :param reporter: (Optional) A reporter that takes an evaluator and its result and returns a report. - :param timeout: (Optional) The duration, in seconds, after which to time out the evaluation. - Defaults to None, in which case there is no timeout. - :param project_id: (Optional) If specified, uses the given project ID instead of the evaluator's name to identify the project. - :param base_experiment_name: An optional experiment name to use as a base. If specified, the new experiment will be - summarized and compared to this experiment. - :param base_experiment_id: An optional experiment id to use as a base. If specified, the new experiment will be - summarized and compared to this experiment. This takes precedence over `base_experiment_name` if specified. - :param git_metadata_settings: Optional settings for collecting git metadata. By default, will collect all git metadata fields allowed in org-level settings. - :param repo_info: Optionally explicitly specify the git metadata for this experiment. This takes precedence over `git_metadata_settings` if specified. - :param error_score_handler: Optionally supply a custom function to specifically handle score values when tasks or scoring functions have errored. - :param description: An optional description for the experiment. - :param summarize_scores: Whether to summarize the scores of the experiment after it has run. - :param no_send_logs: Do not send logs to Braintrust. When True, the evaluation runs locally - and builds a local summary instead of creating an experiment. Defaults to False. - :param parameters: A set of parameters that will be passed to the evaluator. - :param on_start: An optional callback that will be called when the evaluation starts. It receives the - `ExperimentSummary` object, which can be used to display metadata about the experiment. - :param stream: A function that will be called with progress events, which can be used to - display intermediate progress. - :param parent: If specified, instead of creating a new experiment object, the Eval() will populate - the object or span specified by this parent. - :param state: Optional BraintrustState to use for the evaluation. If not specified, the global login state will be used. - :param enable_cache: Whether to enable the span cache for this evaluation. Defaults to True. The span cache stores - span data on disk to minimize memory usage and allow scorers to read spans without server round-trips. - :return: An `EvalResultWithSummary` object, which contains all results and a summary. - """ - f = _EvalCommon( - name=name, - data=data, - task=task, - scores=scores, - experiment_name=experiment_name, - trial_count=trial_count, - metadata=metadata, - is_public=is_public, - update=update, - reporter=reporter, - timeout=timeout, - max_concurrency=max_concurrency, - project_id=project_id, - base_experiment_name=base_experiment_name, - base_experiment_id=base_experiment_id, - git_metadata_settings=git_metadata_settings, - repo_info=repo_info, - description=description, - summarize_scores=summarize_scores, - no_send_logs=no_send_logs, - parameters=parameters, - on_start=on_start, - stream=stream, - parent=parent, - state=state, - enable_cache=enable_cache, - ) - - return await f() - - -_has_printed_eval_async_warning = False - - -def Eval( - name: str, - data: EvalData[Input, Output], - task: EvalTask[Input, Output], - scores: Sequence[EvalScorer[Input, Output]], - experiment_name: str | None = None, - trial_count: int = 1, - metadata: Metadata | None = None, - is_public: bool = False, - update: bool = False, - reporter: ReporterDef[Input, Output, EvalReport] | None = None, - timeout: float | None = None, - max_concurrency: int | None = None, - project_id: str | None = None, - base_experiment_name: str | None = None, - base_experiment_id: str | None = None, - git_metadata_settings: GitMetadataSettings | None = None, - repo_info: RepoInfo | None = None, - error_score_handler: ErrorScoreHandler | None = None, - description: str | None = None, - summarize_scores: bool = True, - no_send_logs: bool = False, - parameters: EvalParameters | None = None, - on_start: Callable[[ExperimentSummary], None] | None = None, - stream: Callable[[SSEProgressEvent], None] | None = None, - parent: str | None = None, - state: BraintrustState | None = None, - enable_cache: bool = True, -) -> EvalResultWithSummary[Input, Output]: - """ - A function you can use to define an evaluator. This is a convenience wrapper around the `Evaluator` class. - - For callers running in an async context, use `EvalAsync()` instead. - - Example: - ```python - Eval( - name="my-evaluator", - data=lambda: [ - EvalCase(input=1, expected=2), - EvalCase(input=2, expected=4), - ], - task=lambda input, hooks: input * 2, - scores=[ - NumericDiff, - ], - ) - ``` - - :param name: The name of the evaluator. This corresponds to a project name in Braintrust. - :param data: Returns an iterator over the evaluation dataset. Each element of the iterator should be a `EvalCase`. - :param task: Runs the evaluation task on a single input. The `hooks` object can be used to add metadata to the evaluation. - :param scores: A list of scorers to evaluate the results of the task. Each scorer can be a Scorer object or a function - that takes an `EvalScorerArgs` object and returns a `Score` object. - :param experiment_name: (Optional) Experiment name. If not specified, a name will be generated automatically. - :param trial_count: The number of times to run the evaluator per input. This is useful for evaluating applications that - have non-deterministic behavior and gives you both a stronger aggregate measure and a sense of the variance in the results. - :param metadata: (Optional) A dictionary with additional data about the test example, model outputs, or just about - anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log - the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` - can be any JSON-serializable type, but its keys must be strings. - :param is_public: (Optional) Whether the experiment should be public. Defaults to false. - :param reporter: (Optional) A reporter that takes an evaluator and its result and returns a report. - :param timeout: (Optional) The duration, in seconds, after which to time out the evaluation. - Defaults to None, in which case there is no timeout. - :param project_id: (Optional) If specified, uses the given project ID instead of the evaluator's name to identify the project. - :param base_experiment_name: An optional experiment name to use as a base. If specified, the new experiment will be - summarized and compared to this experiment. - :param base_experiment_id: An optional experiment id to use as a base. If specified, the new experiment will be - summarized and compared to this experiment. This takes precedence over `base_experiment_name` if specified. - :param git_metadata_settings: Optional settings for collecting git metadata. By default, will collect all git metadata fields allowed in org-level settings. - :param repo_info: Optionally explicitly specify the git metadata for this experiment. This takes precedence over `git_metadata_settings` if specified. - :param error_score_handler: Optionally supply a custom function to specifically handle score values when tasks or scoring functions have errored. - :param description: An optional description for the experiment. - :param summarize_scores: Whether to summarize the scores of the experiment after it has run. - :param no_send_logs: Do not send logs to Braintrust. When True, the evaluation runs locally - and builds a local summary instead of creating an experiment. Defaults to False. - :param parameters: A set of parameters that will be passed to the evaluator. - :param on_start: An optional callback that will be called when the evaluation starts. It receives the - `ExperimentSummary` object, which can be used to display metadata about the experiment. - :param stream: A function that will be called with progress events, which can be used to - display intermediate progress. - :param parent: If specified, instead of creating a new experiment object, the Eval() will populate - the object or span specified by this parent. - :param state: Optional BraintrustState to use for the evaluation. If not specified, the global login state will be used. - :param enable_cache: Whether to enable the span cache for this evaluation. Defaults to True. The span cache stores - span data on disk to minimize memory usage and allow scorers to read spans without server round-trips. - :return: An `EvalResultWithSummary` object, which contains all results and a summary. - """ - - f = _EvalCommon( - name=name, - data=data, - task=task, - scores=scores, - experiment_name=experiment_name, - trial_count=trial_count, - metadata=metadata, - is_public=is_public, - update=update, - reporter=reporter, - timeout=timeout, - max_concurrency=max_concurrency, - project_id=project_id, - base_experiment_name=base_experiment_name, - base_experiment_id=base_experiment_id, - git_metadata_settings=git_metadata_settings, - repo_info=repo_info, - error_score_handler=error_score_handler, - description=description, - summarize_scores=summarize_scores, - no_send_logs=no_send_logs, - parameters=parameters, - on_start=on_start, - stream=stream, - parent=parent, - state=state, - enable_cache=enable_cache, - ) - - # https://stackoverflow.com/questions/55409641/asyncio-run-cannot-be-called-from-a-running-event-loop-when-using-jupyter-no - try: - loop = asyncio.get_running_loop() - except RuntimeError: # 'RuntimeError: There is no current event loop...' - loop = None - if loop: - # Notebook or existing async context. - global _has_printed_eval_async_warning - global _lazy_load - if not _has_printed_eval_async_warning and not _lazy_load: - _has_printed_eval_async_warning = True - eprint( - "`Eval()` was called from an async context. For better " - "performance, it is recommended to use `await EvalAsync()` " - "instead." - ) - # Return a `Task` to be compatible with a previous signature where the - # return type included `Awaitable`. - return loop.create_task(f()) # type: ignore - else: - return asyncio.run(f()) - - -def Reporter( - name: str, - report_eval: Callable[ - [Evaluator[Input, Output], EvalResultWithSummary[Input, Output], bool, bool], - EvalReport | Awaitable[EvalReport], - ], - report_run: Callable[[list[EvalReport], bool, bool], bool | Awaitable[bool]], -): - """ - A function you can use to define a reporter. This is a convenience wrapper around the `ReporterDef` class. - - Example: - ```python - def report_eval(evaluator, result, verbose, jsonl): - return str(result.summary) - - def report_run(results, verbose, jsonl): - return True - - Reporter( - name="my-reporter", - report_eval=report_eval, - report_run=report_run, - ) - ``` - - :param name: The name of the reporter. - :param report_eval: A function that takes an evaluator and its result and returns a report. - :param report_run: A function that takes all evaluator results and returns a boolean indicating whether the run was successful. - """ - ret = ReporterDef(name=name, report_eval=report_eval, report_run=report_run) - - global _evals - if name in _evals.reporters: - raise ValueError(f"Reporter {name} already exists") - - if _lazy_load: - _evals.reporters[name] = ret - - return ret - - -@dataclasses.dataclass -class Filter: - path: list[str] - pattern: re.Pattern - - -def serialize_json_with_plain_string(v: Any) -> str: - if isinstance(v, str): - return v - else: - return json.dumps(v) - - -def deserialize_plain_string_as_json(s: str) -> Any: - try: - return {"value": json.loads(s)} - except json.JSONDecodeError as e: - return {"value": s, "error": e} - - -def parse_filters(filters: list[str]) -> list[Filter]: - result = [] - for f in filters: - equals_idx = f.index("=") - if equals_idx == -1: - raise ValueError(f"Invalid filter {f}") - path, value = f[:equals_idx], f[equals_idx + 1 :] - deserialized_value = deserialize_plain_string_as_json(value)["value"] - if not isinstance(deserialized_value, str): - deserialized_value = value - result.append( - Filter( - path=path.split("."), - pattern=re.compile(deserialized_value), - ) - ) - - return result - - -def evaluate_filter(object, filter: Filter): - key = object - for p in filter.path: - key = key.get(p) - if key is None: - return False - return filter.pattern.match(serialize_json_with_plain_string(key)) is not None - - -class DictEvalHooks(dict[str, Any]): - def __init__( - self, - metadata: Any | None = None, - expected: Any | None = None, - trial_index: int = 0, - tags: Sequence[str] | None = None, - report_progress: Callable[[TaskProgressEvent], None] = None, - parameters: dict[str, Any] | None = None, - ): - if metadata is not None: - self.update({"metadata": metadata}) - if expected is not None: - self.update({"expected": expected}) - self.update({"trial_index": trial_index}) - self._span = None - if tags is not None: - self.update({"tags": tags}) - else: - self.update({"tags": []}) - - self._report_progress = report_progress - self._parameters = parameters - - @property - def metadata(self): - return self.get("metadata") - - @property - def expected(self): - return self.get("expected") - - @property - def trial_index(self) -> int: - return self.get("trial_index", 0) - - @property - def span(self) -> Span | None: - return self._span - - def set_span(self, span: Span | None): - self._span = span - - @property - def tags(self) -> Sequence[str]: - return self["tags"] - - @tags.setter - def tags(self, tags: Sequence[str] | None) -> None: - self["tags"] = [] if tags is None else list(tags) - - def meta(self, **info: Any): - warnings.warn( - "meta() is deprecated. Use the metadata field directly instead.", DeprecationWarning, stacklevel=2 - ) - - if self.get("metadata") is None: - self.update({"metadata": {}}) - - self.get("metadata").update(info) # type: ignore - - def report_progress(self, event: TaskProgressEvent): - if self._report_progress: - return self._report_progress(event) - - @property - def parameters(self) -> dict[str, Any] | None: - return self._parameters - - -def init_experiment( - project_name: str | None = None, experiment_name: str | None = None, set_current: bool = False, **kwargs: Any -) -> Experiment: - ret = _init_experiment(project=project_name, experiment=experiment_name, set_current=set_current, **kwargs) - summary = ret.summarize(summarize_scores=False) - eprint(f"Experiment {ret.name} is running at {summary.experiment_url}") - return ret - - -class EvalThreadPoolSingleton: - def __init__(self): - self._thread_pool = None - self._max_workers = cpu_count() - - def set_max_workers(self, max_workers): - assert self._thread_pool is None, "Cannot set max_workers. Thread pool has already been initialized" - self._max_workers = max_workers - - def thread_pool(self): - if self._thread_pool is None: - self._thread_pool = ThreadPoolExecutor(max_workers=self._max_workers) - return self._thread_pool - - -_THREAD_POOL_SINGLETON = ResourceManager(EvalThreadPoolSingleton()) - - -def set_thread_pool_max_workers(max_workers): - """ - Set the maximum number of threads to use for running evaluators. By default, this is the number of - CPUs on the machine. - """ - with _THREAD_POOL_SINGLETON.get() as obj: - obj.set_max_workers(max_workers) - - -def _scorer_name(scorer, scorer_idx): - def helper(): - if hasattr(scorer, "_name"): - return scorer._name() - elif hasattr(scorer, "__name__"): - return scorer.__name__ - else: - return type(scorer).__name__ - - ret = helper() - if ret == "": - ret = f"scorer_{scorer_idx}" - return ret - - -async def run_evaluator( - experiment: Experiment | None, - evaluator: Evaluator[Input, Output], - position: int | None, - filters: list[Filter], - stream: Callable[[SSEProgressEvent], None] | None = None, - state: BraintrustState | None = None, - enable_cache: bool = True, -) -> EvalResultWithSummary[Input, Output]: - """Wrapper on _run_evaluator_internal that times out execution after evaluator.timeout.""" - results = await asyncio.wait_for( - _run_evaluator_internal(experiment, evaluator, position, filters, stream, state, enable_cache), evaluator.timeout - ) - - if experiment: - summary = experiment.summarize(summarize_scores=evaluator.summarize_scores) - else: - summary = build_local_summary(evaluator, results) - - return EvalResultWithSummary(results=results, summary=summary) - - -def default_error_score_handler( - root_span: Span, - data: EvalCase[Input, Output], - unhandled_scores: list[str], -): - scores = {s: 0 for s in unhandled_scores} - root_span.log(scores=scores) - return scores - - -async def _run_evaluator_internal( - experiment, - evaluator: Evaluator, - position: int | None, - filters: list[Filter], - stream: Callable[[SSEProgressEvent], None] | None = None, - state: BraintrustState | None = None, - enable_cache: bool = True, -): - # Start span cache for this eval (it's disabled by default to avoid temp files outside of evals) - if state is None: - from braintrust.logger import _internal_get_global_state - - state = _internal_get_global_state() - - if enable_cache: - state.span_cache.start() - try: - return await _run_evaluator_internal_impl(experiment, evaluator, position, filters, stream, state) - finally: - # Clean up disk-based span cache after eval completes and stop caching - if enable_cache: - state.span_cache.dispose() - state.span_cache.stop() - - -async def _run_evaluator_internal_impl( - experiment, - evaluator: Evaluator, - position: int | None, - filters: list[Filter], - stream: Callable[[SSEProgressEvent], None] | None = None, - state: BraintrustState | None = None, -): - event_loop = asyncio.get_event_loop() - - async def await_or_run_scorer(root_span, scorer, name, **kwargs): - # Merge purpose into parent's propagated_event rather than replacing it - parent_propagated = root_span.propagated_event or {} - merged_propagated = merge_dicts( - {**parent_propagated}, - {"span_attributes": {"purpose": "scorer"}}, - ) - # Strip trace from logged input - it's internal plumbing that shouldn't appear in spans - logged_input = {k: v for k, v in kwargs.items() if k != "trace"} - with root_span.start_span( - name=name, - span_attributes={"type": SpanTypeAttribute.SCORE, "purpose": "scorer"}, - propagated_event=merged_propagated, - input=logged_input, - ) as span: - score = scorer - if hasattr(scorer, "eval_async"): - score = scorer.eval_async - - scorer_args = kwargs - - result = await call_user_fn(event_loop, score, **scorer_args) - if isinstance(result, dict): - try: - result = Score.from_dict(result) - except Exception as e: - raise ValueError(f"When returning a dict, it must be a valid Score object. Got: {result}") from e - - if isinstance(result, Iterable): - for s in result: - if not is_score(s): - raise ValueError( - f"When returning an array of scores, each score must be a valid Score object. Got: {s}" - ) - result = list(result) - elif is_score(result): - result = [result] - else: - result = [Score(name=name, score=result)] - - def get_other_fields(s): - return {k: v for k, v in s.as_dict().items() if k not in ["metadata", "name"]} - - result_metadata = {r.name: r.metadata for r in result} if len(result) != 1 else result[0].metadata - result_output = ( - {r.name: get_other_fields(r) for r in result} if len(result) != 1 else get_other_fields(result[0]) - ) - - scores = {r.name: r.score for r in result} - span.log(output=result_output, metadata=result_metadata, scores=scores) - return result - - # First, resolve the scorers if they are classes - scorers = [scorer() if inspect.isclass(scorer) and is_scorer(scorer) else scorer for scorer in evaluator.scores] - scorer_names = [_scorer_name(scorer, i) for i, scorer in enumerate(scorers)] - unhandled_scores = scorer_names - - async def run_evaluator_task(datum, trial_index=0): - if isinstance(datum, dict): - datum = EvalCase.from_dict(datum) - - metadata = {**(datum.metadata or {})} - output = None - error = None - exc_info = None - scores = {} - tags = datum.tags - - event_dataset = ( - experiment.dataset if experiment else evaluator.data if isinstance(evaluator.data, Dataset) else None - ) - - origin = ( - { - "object_type": "dataset", - "object_id": event_dataset.id, - "id": datum.id, - "created": datum.created, - "_xact_id": datum._xact_id, - } - if event_dataset and datum.id and datum._xact_id - else None - ) - base_event = dict( - name="eval", - span_attributes={"type": SpanTypeAttribute.EVAL}, - input=datum.input, - expected=datum.expected, - tags=tags, - origin=origin, - ) - - if experiment: - root_span = experiment.start_span(**base_event) - else: - # In most cases this will be a no-op span, but if the parent is set, it will use that ctx. - root_span = start_span(state=state, **base_event) - - with root_span: - try: - - def report_progress(event: TaskProgressEvent): - if not stream: - return - stream( - SSEProgressEvent( - id=root_span.id, origin=origin, name=evaluator.eval_name, object_type="task", **event - ) - ) - - hooks = DictEvalHooks( - metadata, - expected=datum.expected, - trial_index=trial_index, - tags=tags, - report_progress=report_progress, - parameters=evaluator.parameters, - ) - - # Check if the task takes a hooks argument - task_args = [datum.input] - try: - if len(inspect.signature(evaluator.task).parameters) == 2: - task_args.append(hooks) - except: - pass - - with root_span.start_span("task", span_attributes={"type": SpanTypeAttribute.TASK}) as span: - hooks.set_span(span) - output = await await_or_run(event_loop, evaluator.task, *task_args) - span.log(input=task_args[0], output=output) - tags = hooks.tags if hooks.tags else None - root_span.log(output=output, metadata=metadata, tags=tags) - - # Create trace object for scorers - from braintrust.trace import LocalTrace - - async def ensure_spans_flushed(): - # Flush native Braintrust spans - if experiment: - await asyncio.get_event_loop().run_in_executor( - None, lambda: experiment.state.flush() - ) - elif state: - await asyncio.get_event_loop().run_in_executor(None, lambda: state.flush()) - else: - from braintrust.logger import flush as flush_logger - - await asyncio.get_event_loop().run_in_executor(None, flush_logger) - - # Also flush OTEL spans if registered - if state: - await state.flush_otel() - - experiment_id = None - if experiment: - try: - experiment_id = experiment.id - except: - experiment_id = None - - trace = None - if state or experiment: - # Get the state to use - trace_state = state - if not trace_state and experiment: - trace_state = experiment.state - if not trace_state: - # Fall back to global state - from braintrust.logger import _internal_get_global_state - - trace_state = _internal_get_global_state() - - # Access root_span_id from the concrete SpanImpl instance - # The Span interface doesn't expose this but SpanImpl has it - root_span_id_value = getattr(root_span, "root_span_id", root_span.id) - - # Check if there's a parent in the context to determine object_type and object_id - from braintrust.span_identifier_v3 import SpanComponentsV3, span_object_type_v3_to_typed_string - - parent_str = trace_state.current_parent.get() - parent_components = None - if parent_str: - try: - parent_components = SpanComponentsV3.from_str(parent_str) - except Exception: - # If parsing fails, parent_components stays None - pass - - # Determine object_type and object_id based on parent or experiment - if parent_components: - trace_object_type = span_object_type_v3_to_typed_string(parent_components.object_type) - trace_object_id = parent_components.object_id or "" - else: - trace_object_type = "experiment" - trace_object_id = experiment_id or "" - - trace = LocalTrace( - object_type=trace_object_type, - object_id=trace_object_id, - root_span_id=root_span_id_value, - ensure_spans_flushed=ensure_spans_flushed, - state=trace_state, - ) - - score_promises = [ - asyncio.create_task( - await_or_run_scorer( - root_span, - score, - name, - **{ - "input": datum.input, - "expected": datum.expected, - "metadata": metadata, - "output": output, - "trace": trace, - }, - ) - ) - for score, name in zip(scorers, scorer_names) - ] - passing_scorers_and_results = [] - failing_scorers_and_exceptions = [] - for name, p in zip(scorer_names, score_promises): - try: - score_results = await p - for score in score_results: - passing_scorers_and_results.append((score.name, score)) - scores[score.name] = score.score - except Exception as e: - exc_info = traceback.format_exc() - failing_scorers_and_exceptions.append((name, e, exc_info)) - - nonlocal unhandled_scores - unhandled_scores = None - if failing_scorers_and_exceptions: - scorer_errors = { - scorer_name: exc_info for scorer_name, _, exc_info in failing_scorers_and_exceptions - } - metadata["scorer_errors"] = scorer_errors - root_span.log(metadata=metadata, tags=tags) - names = ", ".join(scorer_errors.keys()) - exceptions = [x[1] for x in failing_scorers_and_exceptions] - unhandled_scores = list(scorer_errors.keys()) - eprint( - f"Found exceptions for the following scorers: {names}", - exceptions, - ) - except Exception as e: - exc_type, exc_value, tb = sys.exc_info() - root_span.log(error=stringify_exception(exc_type, exc_value, tb)) - - error = e - # Python3.10 has a different set of arguments to format_exception than earlier versions, - # so just capture the stack trace here. - exc_info = traceback.format_exc() - - return EvalResult( - input=datum.input, - expected=datum.expected, - metadata=metadata, - tags=tags, - output=output, - scores={ - **( - evaluator.error_score_handler(root_span, datum, unhandled_scores) or {} - if evaluator.error_score_handler is not None and unhandled_scores - else {} - ), - **scores, - }, - error=error, - exc_info=exc_info, - ) - - data_iterator = evaluator.data - - if inspect.isclass(data_iterator): - data_iterator = data_iterator() - - if isinstance(data_iterator, BaseExperiment): - if experiment is None: - raise ValueError( - "Cannot use BaseExperiment() without connecting to Braintrust (you most likely set --no-send-logs)" - ) - base_experiment_name = data_iterator.name - if base_experiment_name is None: - base_experiment = experiment.fetch_base_experiment() - if base_experiment is None: - raise Exception("BaseExperiment() failed to fetch base experiment") - base_experiment_name = base_experiment.name - data_iterator = _init_experiment( - project=evaluator.project_name if evaluator.project_id is None else None, - project_id=evaluator.project_id, - experiment=base_experiment_name, - open=True, - set_current=False, - ).as_dataset() - - if inspect.isfunction(data_iterator) or inspect.isroutine(data_iterator): - data_iterator = data_iterator() - - if not inspect.isasyncgen(data_iterator): - - async def to_async(it): - for d in it: - yield d - - data_iterator = to_async(data_iterator) - - async def filtered_iterator(it): - async for datum in it: - if all(evaluate_filter(datum, f) for f in filters): - yield datum - - max_concurrency_semaphore = ( - asyncio.Semaphore(evaluator.max_concurrency) if evaluator.max_concurrency is not None else None - ) - - async def with_max_concurrency(coro): - if max_concurrency_semaphore: - async with max_concurrency_semaphore: - return await coro - else: - return await coro - - tasks = [] - with async_tqdm( - filtered_iterator(data_iterator), - desc=f"{evaluator.eval_name} (data)", - position=position, - disable=position is None, - ) as pbar: - async for datum in pbar: - for trial_index in range(evaluator.trial_count): - tasks.append(asyncio.create_task(with_max_concurrency(run_evaluator_task(datum, trial_index)))) - - results = [] - for task in std_tqdm(tasks, desc=f"{evaluator.eval_name} (tasks)", position=position, disable=position is None): - results.append(await task) - return results - - -def build_local_summary( - evaluator: Evaluator[Input, Output], results: list[EvalResultWithSummary[Input, Output]] -) -> ExperimentSummary: - scores_by_name = defaultdict(lambda: (0, 0)) - for result in results: - for name, score in result.scores.items(): - if score is None: - continue - curr = scores_by_name[name] - scores_by_name[name] = (curr[0] + score, curr[1] + 1) - longest_score_name = max(len(name) for name in scores_by_name) if scores_by_name else 0 - avg_scores = { - name: ScoreSummary( - name=name, - score=total / count, - diff=None, - improvements=0, - regressions=0, - _longest_score_name=longest_score_name, - ) - for name, (total, count) in scores_by_name.items() - } - return ExperimentSummary( - experiment_id=None, - experiment_name=evaluator.eval_name, - project_name=evaluator.project_name, - project_id=None, - project_url=None, - experiment_url=None, - comparison_experiment_name=None, - scores=avg_scores, - metrics={}, - ) - - -__all__ = ["Evaluator", "Eval", "EvalAsync", "Score", "EvalCase", "EvalHooks", "BaseExperiment", "Reporter"] diff --git a/py/src/braintrust/framework2.py b/py/src/braintrust/framework2.py deleted file mode 100644 index b54508855..000000000 --- a/py/src/braintrust/framework2.py +++ /dev/null @@ -1,506 +0,0 @@ -import dataclasses -import json -from collections.abc import Callable -from typing import Any, overload - -import slugify -from braintrust.logger import api_conn, app_conn, login - -from .framework import _is_lazy_load, bcolors # type: ignore -from .generated_types import ( - ChatCompletionMessageParam, - IfExists, - ModelParams, - PromptData, - PromptOptions, - SavedFunctionId, - ToolFunctionDefinition, -) -from .util import eprint - - -class ProjectIdCache: - def __init__(self): - self._cache: dict[Project, str] = {} - - def get(self, project: "Project") -> str: - if project not in self._cache: - resp = app_conn().post_json("api/project/register", {"project_name": project.name}) - self._cache[project] = resp["project"]["id"] - return self._cache[project] - - -class _GlobalState: - def __init__(self): - self.functions: list[CodeFunction] = [] - self.prompts: list[CodePrompt] = [] - - -global_ = _GlobalState() - - -@dataclasses.dataclass -class CodeFunction: - """A generic callable, with metadata.""" - - project: "Project" - handler: Callable[..., Any] - name: str - slug: str - type_: str - description: str | None - parameters: Any - returns: Any - if_exists: IfExists | None - metadata: dict[str, Any] | None = None - - -@dataclasses.dataclass -class CodePrompt: - """A prompt defined in code, with metadata.""" - - project: "Project" - name: str - slug: str - prompt: PromptData - tool_functions: list[CodeFunction | SavedFunctionId] - description: str | None - function_type: str | None - id: str | None - if_exists: IfExists | None - metadata: dict[str, Any] | None = None - - def to_function_definition(self, if_exists: IfExists | None, project_ids: ProjectIdCache) -> dict[str, Any]: - prompt_data = self.prompt - if len(self.tool_functions) > 0: - resolvable_tool_functions: list[Any] = [] - for f in self.tool_functions: - if isinstance(f, CodeFunction): - resolvable_tool_functions.append( - { - "type": "slug", - "project_id": project_ids.get(f.project), - "slug": f.slug, - } - ) - else: - resolvable_tool_functions.append(f) - prompt_data["tool_functions"] = resolvable_tool_functions - j: dict[str, Any] = { - "project_id": project_ids.get(self.project), - "name": self.name, - "slug": self.slug, - "function_data": { - "type": "prompt", - }, - "prompt_data": prompt_data, - "if_exists": self.if_exists if self.if_exists is not None else if_exists, - } - if self.description is not None: - j["description"] = self.description - if self.function_type is not None: - j["function_type"] = self.function_type - if self.metadata is not None: - j["metadata"] = self.metadata - - return j - - -class ToolBuilder: - """Builder to create a tool in Braintrust.""" - - def __init__(self, project: "Project"): - self.project = project - self._task_counter = 0 - - def create( - self, - *, - handler: Callable[..., Any], - name: str | None = None, - slug: str | None = None, - description: str | None = None, - parameters: Any = None, - returns: Any = None, - if_exists: IfExists | None = None, - metadata: dict[str, Any] | None = None, - ) -> CodeFunction: - """Creates a tool. - - Args: - handler: The function that is called when the tool is used. - name: The name of the tool. - slug: A unique identifier for the tool. - description: The description of the tool. - parameters: The tool's input schema, as a Pydantic model. - returns: The tool's output schema, as a Pydantic model. - if_exists: What to do if the tool already exists. - metadata: Custom metadata to attach to the tool. - - Returns: - A handle to the created tool, that can be used in a prompt. - """ - self._task_counter += 1 - if not name: - if handler.__name__ and handler.__name__ != "": - name = handler.__name__ - else: - name = f"Tool {self._task_counter}" - assert name is not None - if not slug: - slug = slugify.slugify(name) - f = CodeFunction( - project=self.project, - handler=handler, - name=name, - slug=slug, - type_="tool", - description=description, - parameters=parameters, - returns=returns, - if_exists=if_exists, - metadata=metadata, - ) - self.project.add_code_function(f) - return f - - -class PromptBuilder: - """Builder to create a prompt in Braintrust.""" - - def __init__(self, project: "Project"): - self.project = project - self._task_counter = 0 - - @overload # prompt only, no messages - def create( - self, - *, - name: str | None = None, - slug: str | None = None, - description: str | None = None, - id: str | None = None, - prompt: str, - model: str, - params: ModelParams | None = None, - tools: list[CodeFunction | SavedFunctionId | ToolFunctionDefinition] | None = None, - if_exists: IfExists | None = None, - metadata: dict[str, Any] | None = None, - ) -> CodePrompt: ... - - @overload # messages only, no prompt - def create( - self, - *, - name: str | None = None, - slug: str | None = None, - description: str | None = None, - id: str | None = None, - messages: list[ChatCompletionMessageParam], - model: str, - params: ModelParams | None = None, - tools: list[CodeFunction | SavedFunctionId | ToolFunctionDefinition] | None = None, - if_exists: IfExists | None = None, - metadata: dict[str, Any] | None = None, - ) -> CodePrompt: ... - - def create( - self, - *, - name: str | None = None, - slug: str | None = None, - description: str | None = None, - id: str | None = None, - prompt: str | None = None, - messages: list[ChatCompletionMessageParam] | None = None, - model: str, - params: ModelParams | None = None, - tools: list[CodeFunction | SavedFunctionId | ToolFunctionDefinition] | None = None, - if_exists: IfExists | None = None, - metadata: dict[str, Any] | None = None, - ): - """Creates a prompt. - - Args: - name: The name of the prompt. - slug: A unique identifier for the prompt. - description: The description of the prompt. - id: The ID of the prompt. - prompt: The prompt text. Exactly one of prompt or messages must be provided. - messages: The messages to send to the model. Exactly one of prompt or messages must be provided. - model: The model to use for the prompt. - params: The model parameters to use for the prompt. - tools: The tools to use for the prompt. - if_exists: What to do if the prompt already exists. - metadata: Custom metadata to attach to the prompt. - """ - self._task_counter += 1 - if not name: - name = f"Prompt {self._task_counter}" - if not slug: - slug = slugify.slugify(name) - - tool_functions: list[CodeFunction | SavedFunctionId] = [] - raw_tools: list[ToolFunctionDefinition] = [] - for tool in tools or []: - if isinstance(tool, CodeFunction): - tool_functions.append(tool) - elif "type" in tool and "function" not in tool: - # SavedFunctionId - tool_functions.append(tool) - else: - # ToolFunctionDefinition - raw_tools.append(tool) - - prompt_data: PromptData = {} - if messages is not None: - prompt_data["prompt"] = { - "type": "chat", - "messages": messages, - } - if len(raw_tools) > 0: - prompt_data["prompt"]["tools"] = json.dumps(raw_tools) - else: - assert prompt is not None - prompt_data["prompt"] = { - "type": "completion", - "content": prompt, - } - options: PromptOptions = {"model": model} - if params is not None: - options["params"] = params - prompt_data["options"] = options - - p = CodePrompt( - project=self.project, - name=name, - slug=slug, - prompt=prompt_data, - tool_functions=tool_functions, - description=description, - function_type=None, - id=id, - if_exists=if_exists, - metadata=metadata, - ) - self.project.add_prompt(p) - return p - - -class ScorerBuilder: - """Builder to create a scorer in Braintrust.""" - - def __init__(self, project: "Project"): - self.project = project - self._task_counter = 0 - - # Code scorer. - @overload - def create( - self, - *, - name: str | None = None, - slug: str | None = None, - description: str | None = None, - if_exists: IfExists | None = None, - metadata: dict[str, Any] | None = None, - handler: Callable[..., Any], - parameters: Any, - returns: Any = None, - ) -> CodeFunction: ... - - # LLM scorer with prompt. - @overload - def create( - self, - *, - name: str | None = None, - slug: str | None = None, - description: str | None = None, - if_exists: IfExists | None = None, - metadata: dict[str, Any] | None = None, - prompt: str, - model: str, - params: ModelParams | None = None, - use_cot: bool, - choice_scores: dict[str, float], - ) -> CodePrompt: ... - - # LLM scorer with messages. - @overload - def create( - self, - *, - name: str | None = None, - slug: str | None = None, - description: str | None = None, - if_exists: IfExists | None = None, - metadata: dict[str, Any] | None = None, - messages: list[ChatCompletionMessageParam], - model: str, - params: ModelParams | None = None, - use_cot: bool, - choice_scores: dict[str, float], - ) -> CodePrompt: ... - - def create( - self, - *, - name: str | None = None, - slug: str | None = None, - description: str | None = None, - if_exists: IfExists | None = None, - metadata: dict[str, Any] | None = None, - # Code scorer params. - handler: Callable[..., Any] | None = None, - parameters: Any = None, - returns: Any = None, - # LLM scorer params. - prompt: str | None = None, - messages: list[ChatCompletionMessageParam] | None = None, - model: str | None = None, - params: ModelParams | None = None, - use_cot: bool | None = None, - choice_scores: dict[str, float] | None = None, - ) -> CodeFunction | CodePrompt: - """Creates a scorer. - - Args: - name: The name of the scorer. - slug: A unique identifier for the scorer. - description: The description of the scorer. - if_exists: What to do if the scorer already exists. - metadata: Custom metadata to attach to the scorer. - - The remaining args are mutually exclusive; that is, - the function will only accept args from one of the following overloads. - - Code scorer: - handler: The function that is called when the scorer is used. Required. - parameters: The scorer's input schema, as a Pydantic model. Required. - returns: The scorer's output schema, as a Pydantic model. - - LLM scorer: - prompt: The prompt to use for the scorer. Either prompt or messages is required. - messages: The messages to use for the scorer. Either prompt or messages is required. - model: The model to use for the scorer. Required. - params: The model parameters to use for the scorer. - use_cot: Whether to use chain-of-thought for the scorer. Required. - choice_scores: The scores for each choice. Required. - """ - self._task_counter += 1 - if name is None or len(name) == 0: - if handler and handler.__name__ and handler.__name__ != "": - name = handler.__name__ - else: - name = f"Scorer {self._task_counter}" - if slug is None or len(slug) == 0: - slug = slugify.slugify(name) - - if handler is not None: # code scorer - assert parameters is not None - f = CodeFunction( - project=self.project, - handler=handler, - name=name, - slug=slug, - type_="scorer", - description=description, - parameters=parameters, - returns=returns, - if_exists=if_exists, - metadata=metadata, - ) - self.project.add_code_function(f) - return f - else: # LLM scorer - assert model is not None - assert use_cot is not None - assert choice_scores is not None - prompt_data: PromptData = {} - if messages is not None: - assert prompt is None - prompt_data["prompt"] = { - "type": "chat", - "messages": messages, - } - else: - assert prompt is not None - prompt_data["prompt"] = { - "type": "completion", - "content": prompt, - } - prompt_data["options"] = {"model": model} - if params is not None: - prompt_data["options"]["params"] = params - prompt_data["parser"] = { - "type": "llm_classifier", - "use_cot": use_cot, - "choice_scores": choice_scores, - } - p = CodePrompt( - project=self.project, - name=name, - slug=slug, - prompt=prompt_data, - tool_functions=[], - description=description, - function_type="scorer", - id=None, - if_exists=if_exists, - metadata=metadata, - ) - self.project.add_prompt(p) - return p - - -class Project: - """A handle to a Braintrust project.""" - - def __init__(self, name: str): - self.name = name - self.tools = ToolBuilder(self) - self.prompts = PromptBuilder(self) - self.scorers = ScorerBuilder(self) - - self._publishable_code_functions: list[CodeFunction] = [] - self._publishable_prompts: list[CodePrompt] = [] - - def add_code_function(self, fn: CodeFunction): - self._publishable_code_functions.append(fn) - if _is_lazy_load(): - global_.functions.append(fn) - - def add_prompt(self, prompt: CodePrompt): - self._publishable_prompts.append(prompt) - if _is_lazy_load(): - global_.prompts.append(prompt) - - def publish(self): - if _is_lazy_load(): - eprint(f"{bcolors.WARNING}publish() is a no-op when running `braintrust push`.{bcolors.ENDC}") - return - - login() - project_id_cache = ProjectIdCache() - - definitions: list[dict[str, Any]] = [] - if self._publishable_code_functions: - eprint( - f"{bcolors.WARNING}Code functions cannot be published directly. Use `braintrust push` instead.{bcolors.ENDC}" - ) - - for prompt in self._publishable_prompts: - prompt_definition = prompt.to_function_definition(None, project_id_cache) - definitions.append(prompt_definition) - return api_conn().post_json("insert-functions", {"functions": definitions}) - - -class ProjectBuilder: - """Creates handles to Braintrust projects.""" - - def create(self, name: str) -> Project: - return Project(name) - - -projects = ProjectBuilder() diff --git a/py/src/braintrust/functions/__init__.py b/py/src/braintrust/functions/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/py/src/braintrust/functions/constants.py b/py/src/braintrust/functions/constants.py deleted file mode 100644 index 48310be01..000000000 --- a/py/src/braintrust/functions/constants.py +++ /dev/null @@ -1 +0,0 @@ -INVOKE_API_VERSION = 1 diff --git a/py/src/braintrust/functions/invoke.py b/py/src/braintrust/functions/invoke.py deleted file mode 100644 index 5c566c3f9..000000000 --- a/py/src/braintrust/functions/invoke.py +++ /dev/null @@ -1,258 +0,0 @@ -from typing import Any, Literal, TypedDict, TypeVar, overload - -from sseclient import SSEClient - -from .._generated_types import FunctionTypeEnum -from ..logger import Exportable, _internal_get_global_state, get_span_parent_object, login, proxy_conn -from ..util import response_raise_for_status -from .constants import INVOKE_API_VERSION -from .stream import BraintrustInvokeError, BraintrustStream - -T = TypeVar("T") -ModeType = Literal["auto", "parallel", "json", "text"] -ObjectType = Literal["project_logs", "experiment", "dataset", "playground_logs"] - - -class SpanScope(TypedDict): - """Scope for operating on a single span.""" - - type: Literal["span"] - id: str - root_span_id: str - - -class TraceScope(TypedDict): - """Scope for operating on an entire trace.""" - - type: Literal["trace"] - root_span_id: str - - -@overload -def invoke( - # the permutations of arguments for a function id - function_id: str | None = None, - version: str | None = None, - prompt_session_id: str | None = None, - prompt_session_function_id: str | None = None, - project_name: str | None = None, - project_id: str | None = None, - slug: str | None = None, - global_function: str | None = None, - function_type: FunctionTypeEnum | None = None, - # arguments to the function - input: Any = None, - messages: list[Any] | None = None, - metadata: dict[str, Any] | None = None, - tags: list[str] | None = None, - parent: Exportable | str | None = None, - stream: Literal[False] | None = None, - mode: ModeType | None = None, - strict: bool | None = None, - org_name: str | None = None, - api_key: str | None = None, - app_url: str | None = None, - force_login: bool = False, -) -> T: ... - - -@overload -def invoke( - # the permutations of arguments for a function id - function_id: str | None = None, - version: str | None = None, - prompt_session_id: str | None = None, - prompt_session_function_id: str | None = None, - project_name: str | None = None, - project_id: str | None = None, - slug: str | None = None, - global_function: str | None = None, - function_type: FunctionTypeEnum | None = None, - # arguments to the function - input: Any = None, - messages: list[Any] | None = None, - metadata: dict[str, Any] | None = None, - tags: list[str] | None = None, - parent: Exportable | str | None = None, - stream: Literal[True] = True, - mode: ModeType | None = None, - strict: bool | None = None, - org_name: str | None = None, - api_key: str | None = None, - app_url: str | None = None, - force_login: bool = False, -) -> BraintrustStream: ... - - -def invoke( - # the permutations of arguments for a function id - function_id: str | None = None, - version: str | None = None, - prompt_session_id: str | None = None, - prompt_session_function_id: str | None = None, - project_name: str | None = None, - project_id: str | None = None, - slug: str | None = None, - global_function: str | None = None, - function_type: FunctionTypeEnum | None = None, - # arguments to the function - input: Any = None, - messages: list[Any] | None = None, - metadata: dict[str, Any] | None = None, - tags: list[str] | None = None, - parent: Exportable | str | None = None, - stream: bool = False, - mode: ModeType | None = None, - strict: bool | None = None, - org_name: str | None = None, - api_key: str | None = None, - app_url: str | None = None, - force_login: bool = False, -) -> BraintrustStream | T: - """ - Invoke a Braintrust function, returning a `BraintrustStream` or the value as a plain - Python object. - - Args: - input: The input to the function. This will be logged as the `input` field in the span. - messages: Additional OpenAI-style messages to add to the prompt (only works for llm functions). - metadata: Additional metadata to add to the span. This will be logged as the `metadata` field in the span. - It will also be available as the {{metadata}} field in the prompt and as the `metadata` argument - to the function. - tags: Tags to add to the span. This will be logged as the `tags` field in the span. - parent: The parent of the function. This can be an existing span, logger, or experiment, or - the output of `.export()` if you are distributed tracing. If unspecified, will use - the same semantics as `traced()` to determine the parent and no-op if not in a tracing - context. - stream: Whether to stream the function's output. If True, the function will return a - `BraintrustStream`, otherwise it will return the output of the function as a JSON - object. - mode: The response shape of the function if returning tool calls. If "auto", will return - a string if the function returns a string, and a JSON object otherwise. If "parallel", - will return an array of JSON objects with one object per tool call. - strict: Whether to use strict mode for the function. If true, the function will throw an - error if the variable names in the prompt do not match the input keys. - org_name: The name of the Braintrust organization to use. - api_key: The API key to use for authentication. - app_url: The URL of the Braintrust application. - force_login: Whether to force a new login even if already logged in. - function_id: The ID of the function to invoke. - version: The version of the function to invoke. - prompt_session_id: The ID of the prompt session to invoke the function from. - prompt_session_function_id: The ID of the function in the prompt session to invoke. - project_name: The name of the project containing the function to invoke. - project_id: The ID of the project to use for execution context (API keys, project defaults, etc.). - This is not the project the function belongs to, but the project context for the invocation. - slug: The slug of the function to invoke. - global_function: The name of the global function to invoke. - function_type: The type of the global function to invoke. If unspecified, defaults to 'scorer' - for backward compatibility. - - Returns: - The output of the function. If `stream` is True, returns a `BraintrustStream`, - otherwise returns the output as a Python object. - """ - login( - org_name=org_name, - api_key=api_key, - app_url=app_url, - force_login=force_login, - ) - - parent = parent if isinstance(parent, str) else parent.export() if parent else get_span_parent_object().export() - - function_id_args = {} - if function_id is not None: - function_id_args["function_id"] = function_id - if version is not None: - function_id_args["version"] = version - if prompt_session_id is not None: - function_id_args["prompt_session_id"] = prompt_session_id - if prompt_session_function_id is not None: - function_id_args["prompt_session_function_id"] = prompt_session_function_id - if project_name is not None: - function_id_args["project_name"] = project_name - if slug is not None: - function_id_args["slug"] = slug - if global_function is not None: - function_id_args["global_function"] = global_function - if function_type is not None: - function_id_args["function_type"] = function_type - - request = dict( - input=input, - metadata=metadata, - tags=tags, - parent=parent, - stream=stream, - api_version=INVOKE_API_VERSION, - **function_id_args, - ) - if messages is not None: - request["messages"] = messages - if mode is not None: - request["mode"] = mode - if strict is not None: - request["strict"] = strict - - headers = {"Accept": "text/event-stream" if stream else "application/json"} - if project_id is not None: - headers["x-bt-project-id"] = project_id - if org_name is not None: - headers["x-bt-org-name"] = org_name - - resp = proxy_conn().post("function/invoke", json=request, headers=headers, stream=stream) - if resp.status_code == 500: - raise BraintrustInvokeError(resp.text) - - response_raise_for_status(resp) - - if stream: - return BraintrustStream(SSEClient(resp)) - else: - return resp.json() - - -def init_function(project_name: str, slug: str, version: str | None = None): - """ - Creates a function that can be used as either a task or scorer in the Eval framework. - When used as a task, it will invoke the specified Braintrust function with the input. - When used as a scorer, it will invoke the function with the scorer arguments. - - Example: - ```python - # As a task - Eval( - name="my-evaluator", - data=data, - task=init_function("my-project", "my-function"), - scores=[...] - ) - - # As a scorer - Eval( - name="my-evaluator", - data=data, - task=task, - scores=[init_function("my-project", "my-scorer")] - ) - ``` - - :param project_name: The name of the project containing the function. - :param slug: The slug of the function to invoke. - :param version: Optional version of the function to use. Defaults to latest. - :return: A function that can be used as a task or scorer. - """ - # Disable span cache since remote function spans won't be in the local cache - _internal_get_global_state().span_cache.disable() - - def f(*args: Any, **kwargs: Any) -> Any: - if len(args) > 0: - # Task. - return invoke(project_name=project_name, slug=slug, version=version, input=args[0]) - else: - # Scorer. - return invoke(project_name=project_name, slug=slug, version=version, input=kwargs) - - f.__name__ = f"init_function-{project_name}-{slug}-{version or 'latest'}" - return f diff --git a/py/src/braintrust/functions/stream.py b/py/src/braintrust/functions/stream.py deleted file mode 100644 index 0295b25ca..000000000 --- a/py/src/braintrust/functions/stream.py +++ /dev/null @@ -1,208 +0,0 @@ -""" -This module provides classes and functions for handling Braintrust streams. - -A Braintrust stream is a wrapper around a generator of `BraintrustStreamChunk`, -with utility methods to make them easy to log and convert into various formats. -""" - -import dataclasses -import json -from collections.abc import Generator -from itertools import tee -from typing import Literal, Union - -from sseclient import SSEClient - - -@dataclasses.dataclass -class BraintrustTextChunk: - """ - A chunk of text data from a Braintrust stream. - """ - - data: str - type: Literal["text_delta"] = "text_delta" - - -@dataclasses.dataclass -class BraintrustJsonChunk: - """ - A chunk of JSON data from a Braintrust stream. - """ - - data: str - type: Literal["json_delta"] = "json_delta" - - -@dataclasses.dataclass -class BraintrustErrorChunk: - """ - An error chunk from a Braintrust stream. - """ - - data: str - type: Literal["error"] = "error" - - -@dataclasses.dataclass -class BraintrustConsoleChunk: - """ - A console chunk from a Braintrust stream. - """ - - message: str - stream: Literal["stderr", "stdout"] - type: Literal["console"] = "console" - - -@dataclasses.dataclass -class BraintrustProgressChunk: - """ - A progress chunk from a Braintrust stream. - """ - - data: str - id: str - object_type: str - format: str - output_type: str - name: str - event: Literal["json_delta", "text_delta", "reasoning_delta"] - type: Literal["progress"] = "progress" - - -class BraintrustInvokeError(ValueError): - """ - An error that occurs during a Braintrust stream. - """ - - pass - - -BraintrustStreamChunk = Union[BraintrustTextChunk, BraintrustJsonChunk, BraintrustErrorChunk] - - -class BraintrustStream: - """ - A Braintrust stream. This is a wrapper around a generator of `BraintrustStreamChunk`, - with utility methods to make them easy to log and convert into various formats. - """ - - def __init__(self, base_stream: SSEClient | list[BraintrustStreamChunk]): - """ - Initialize a BraintrustStream. - - Args: - base_stream: Either an SSEClient or a list of BraintrustStreamChunks. - """ - if isinstance(base_stream, SSEClient): - self.stream = self._parse_sse_stream(base_stream) - else: - self.stream = base_stream - self._memoized_final_value = None - - def _parse_sse_stream(self, sse_client: SSEClient) -> Generator[BraintrustStreamChunk, None, None]: - """ - Parse an SSE stream into BraintrustStreamChunks. - - Args: - sse_client: The SSEClient to parse. - - Yields: - BraintrustStreamChunk: Parsed chunks from the SSE stream. - """ - for event in sse_client.events(): - if event.event == "text_delta": - yield BraintrustTextChunk(data=json.loads(event.data)) - elif event.event == "json_delta": - yield BraintrustJsonChunk(data=event.data) - elif event.event == "error": - yield BraintrustErrorChunk(data=json.loads(event.data)) - elif event.event == "console": - event_data = json.loads(event.data) - yield BraintrustConsoleChunk( - message=event_data["message"], - stream=event_data["stream"], - ) - elif event.event == "progress": - event_data = json.loads(event.data) - yield BraintrustProgressChunk( - data=event_data["data"], - id=event_data["id"], - object_type=event_data["object_type"], - format=event_data["format"], - output_type=event_data["output_type"], - name=event_data["name"], - event=event_data["event"], - ) - - def copy(self): - """ - Copy the stream. This returns a new stream that shares the same underlying - generator (via `tee`). Since generators are consumed in Python, use `copy()` if you - need to use the stream multiple times. - - Returns: - BraintrustStream: A new stream that you can independently consume. - """ - current_stream = self.stream - self.stream, new_stream = tee(current_stream) - return BraintrustStream(new_stream) - - def final_value(self): - """ - Get the final value of the stream. The final value is the concatenation of all - the chunks in the stream, deserialized into a string or object, depending on - the value's type. - - This function consumes the stream, so if you need to use the stream multiple - times, you should call `copy()` first. - - Returns: - The final value of the stream. - """ - if self._memoized_final_value is None: - self._memoized_final_value = parse_stream(self) - return self._memoized_final_value - - def __iter__(self): - """ - Iterate over the stream chunks. - - Yields: - BraintrustStreamChunk: The next chunk in the stream. - """ - yield from self.stream - - -def parse_stream(stream: BraintrustStream): - """ - Parse a BraintrustStream into its final value. - - Args: - stream: The BraintrustStream to parse. - - Returns: - The final value of the stream. - """ - text_chunks = [] - json_chunks = [] - - for chunk in stream: - if isinstance(chunk, BraintrustTextChunk): - text_chunks.append(chunk.data) - elif isinstance(chunk, BraintrustJsonChunk): - json_chunks.append(chunk.data) - elif isinstance(chunk, BraintrustErrorChunk): - raise BraintrustInvokeError(chunk.data) - elif isinstance(chunk, BraintrustProgressChunk) or isinstance(chunk, BraintrustConsoleChunk): - pass - else: - raise ValueError(f"Unknown chunk type (you may need to update the SDK): {type(chunk)}") - - if json_chunks: - return json.loads("".join(json_chunks)) - elif text_chunks: - return "".join(text_chunks) - else: - return None diff --git a/py/src/braintrust/functions/test_invoke.py b/py/src/braintrust/functions/test_invoke.py deleted file mode 100644 index c38e2e105..000000000 --- a/py/src/braintrust/functions/test_invoke.py +++ /dev/null @@ -1,61 +0,0 @@ -"""Tests for the invoke module, particularly init_function.""" - - -from braintrust.functions.invoke import init_function -from braintrust.logger import _internal_get_global_state, _internal_reset_global_state - - -class TestInitFunction: - """Tests for init_function.""" - - def setup_method(self): - """Reset state before each test.""" - _internal_reset_global_state() - - def teardown_method(self): - """Clean up after each test.""" - _internal_reset_global_state() - - def test_init_function_disables_span_cache(self): - """Test that init_function disables the span cache.""" - state = _internal_get_global_state() - - # Cache should be disabled by default (it's only enabled during evals) - assert state.span_cache.disabled is True - - # Enable the cache (simulating what happens during eval) - state.span_cache.start() - assert state.span_cache.disabled is False - - # Call init_function - f = init_function("test-project", "test-function") - - # Cache should now be disabled (init_function explicitly disables it) - assert state.span_cache.disabled is True - assert f.__name__ == "init_function-test-project-test-function-latest" - - def test_init_function_with_version(self): - """Test that init_function creates a function with the correct name including version.""" - f = init_function("my-project", "my-scorer", version="v1") - assert f.__name__ == "init_function-my-project-my-scorer-v1" - - def test_init_function_without_version_uses_latest(self): - """Test that init_function uses 'latest' in name when version not specified.""" - f = init_function("my-project", "my-scorer") - assert f.__name__ == "init_function-my-project-my-scorer-latest" - - def test_init_function_permanently_disables_cache(self): - """Test that init_function permanently disables the cache (can't be re-enabled).""" - state = _internal_get_global_state() - - # Enable the cache - state.span_cache.start() - assert state.span_cache.disabled is False - - # Call init_function - init_function("test-project", "test-function") - assert state.span_cache.disabled is True - - # Try to start again - should still be disabled because of explicit disable - state.span_cache.start() - assert state.span_cache.disabled is True diff --git a/py/src/braintrust/generated_types.py b/py/src/braintrust/generated_types.py deleted file mode 100644 index d7a9920e1..000000000 --- a/py/src/braintrust/generated_types.py +++ /dev/null @@ -1,231 +0,0 @@ -"""Auto-generated file (internal git SHA 7cc4507a2a809d3d0bcaea7cb53cb89c1bde1a91) -- do not modify""" - -from ._generated_types import ( - Acl, - AclObjectType, - AISecret, - AnyModelParams, - ApiKey, - AsyncScoringControl, - AsyncScoringState, - AttachmentReference, - AttachmentStatus, - BatchedFacetData, - BraintrustAttachmentReference, - BraintrustModelParams, - CallEvent, - ChatCompletionContentPart, - ChatCompletionContentPartFileFile, - ChatCompletionContentPartFileWithTitle, - ChatCompletionContentPartImageWithTitle, - ChatCompletionContentPartText, - ChatCompletionContentPartTextWithTitle, - ChatCompletionMessageParam, - ChatCompletionMessageReasoning, - ChatCompletionMessageToolCall, - ChatCompletionOpenAIMessageParam, - ChatCompletionTool, - CodeBundle, - Dataset, - DatasetEvent, - EnvVar, - EvalStatusPage, - EvalStatusPageConfig, - EvalStatusPageTheme, - Experiment, - ExperimentEvent, - ExtendedSavedFunctionId, - ExternalAttachmentReference, - FacetData, - Function, - FunctionData, - FunctionFormat, - FunctionId, - FunctionIdRef, - FunctionObjectType, - FunctionOutputType, - FunctionTypeEnum, - FunctionTypeEnumNullish, - GitMetadataSettings, - GraphData, - GraphEdge, - GraphNode, - Group, - GroupScope, - IfExists, - ImageRenderingMode, - InvokeFunction, - InvokeParent, - MCPServer, - MessageRole, - ModelParams, - NullableSavedFunctionId, - ObjectReference, - ObjectReferenceNullish, - OnlineScoreConfig, - Organization, - Permission, - Project, - ProjectAutomation, - ProjectLogsEvent, - ProjectScore, - ProjectScoreCategories, - ProjectScoreCategory, - ProjectScoreConfig, - ProjectScoreType, - ProjectSettings, - ProjectTag, - Prompt, - PromptBlockData, - PromptBlockDataNullish, - PromptData, - PromptDataNullish, - PromptOptions, - PromptOptionsNullish, - PromptParserNullish, - PromptSessionEvent, - RepoInfo, - ResponseFormat, - ResponseFormatJsonSchema, - ResponseFormatNullish, - RetentionObjectType, - Role, - RunEval, - SavedFunctionId, - ServiceToken, - SpanAttributes, - SpanIFrame, - SpanScope, - SpanType, - SSEConsoleEventData, - SSEProgressEventData, - StreamingMode, - ToolFunctionDefinition, - TopicAutomationConfig, - TopicAutomationDataScope, - TopicMapData, - TopicMapFunctionAutomation, - TraceScope, - TriggeredFunctionState, - UploadStatus, - User, - View, - ViewData, - ViewDataSearch, - ViewOptions, -) - -__all__ = [ - "AISecret", - "Acl", - "AclObjectType", - "AnyModelParams", - "ApiKey", - "AsyncScoringControl", - "AsyncScoringState", - "AttachmentReference", - "AttachmentStatus", - "BatchedFacetData", - "BraintrustAttachmentReference", - "BraintrustModelParams", - "CallEvent", - "ChatCompletionContentPart", - "ChatCompletionContentPartFileFile", - "ChatCompletionContentPartFileWithTitle", - "ChatCompletionContentPartImageWithTitle", - "ChatCompletionContentPartText", - "ChatCompletionContentPartTextWithTitle", - "ChatCompletionMessageParam", - "ChatCompletionMessageReasoning", - "ChatCompletionMessageToolCall", - "ChatCompletionOpenAIMessageParam", - "ChatCompletionTool", - "CodeBundle", - "Dataset", - "DatasetEvent", - "EnvVar", - "EvalStatusPage", - "EvalStatusPageConfig", - "EvalStatusPageTheme", - "Experiment", - "ExperimentEvent", - "ExtendedSavedFunctionId", - "ExternalAttachmentReference", - "FacetData", - "Function", - "FunctionData", - "FunctionFormat", - "FunctionId", - "FunctionIdRef", - "FunctionObjectType", - "FunctionOutputType", - "FunctionTypeEnum", - "FunctionTypeEnumNullish", - "GitMetadataSettings", - "GraphData", - "GraphEdge", - "GraphNode", - "Group", - "GroupScope", - "IfExists", - "ImageRenderingMode", - "InvokeFunction", - "InvokeParent", - "MCPServer", - "MessageRole", - "ModelParams", - "NullableSavedFunctionId", - "ObjectReference", - "ObjectReferenceNullish", - "OnlineScoreConfig", - "Organization", - "Permission", - "Project", - "ProjectAutomation", - "ProjectLogsEvent", - "ProjectScore", - "ProjectScoreCategories", - "ProjectScoreCategory", - "ProjectScoreConfig", - "ProjectScoreType", - "ProjectSettings", - "ProjectTag", - "Prompt", - "PromptBlockData", - "PromptBlockDataNullish", - "PromptData", - "PromptDataNullish", - "PromptOptions", - "PromptOptionsNullish", - "PromptParserNullish", - "PromptSessionEvent", - "RepoInfo", - "ResponseFormat", - "ResponseFormatJsonSchema", - "ResponseFormatNullish", - "RetentionObjectType", - "Role", - "RunEval", - "SSEConsoleEventData", - "SSEProgressEventData", - "SavedFunctionId", - "ServiceToken", - "SpanAttributes", - "SpanIFrame", - "SpanScope", - "SpanType", - "StreamingMode", - "ToolFunctionDefinition", - "TopicAutomationConfig", - "TopicAutomationDataScope", - "TopicMapData", - "TopicMapFunctionAutomation", - "TraceScope", - "TriggeredFunctionState", - "UploadStatus", - "User", - "View", - "ViewData", - "ViewDataSearch", - "ViewOptions", -] diff --git a/py/src/braintrust/git_fields.py b/py/src/braintrust/git_fields.py deleted file mode 100644 index 264102fa0..000000000 --- a/py/src/braintrust/git_fields.py +++ /dev/null @@ -1,45 +0,0 @@ -from dataclasses import dataclass, field -from typing import Literal - -from .serializable_data_class import SerializableDataClass - - -@dataclass -class RepoInfo(SerializableDataClass): - """Information about the current HEAD of the repo.""" - - commit: str | None = None - branch: str | None = None - tag: str | None = None - dirty: bool | None = None - author_name: str | None = None - author_email: str | None = None - commit_message: str | None = None - commit_time: str | None = None - git_diff: str | None = None - - -@dataclass -class GitMetadataSettings(SerializableDataClass): - collect: Literal["all", "some", "none"] = "all" - fields: list[str] | None = field(default_factory=list) - - @classmethod - def merge(cls, s1: "GitMetadataSettings", s2: "GitMetadataSettings") -> "GitMetadataSettings": - # If either is all, then return the other - # If either is none, then return that one - if s1.collect == "all": - return s2 - elif s2.collect == "all": - return s1 - elif s1.collect == "none": - return s1 - elif s2.collect == "none": - return s2 - - assert s1.collect == "some" and s2.collect == "some" - # intersect the fields - ret = GitMetadataSettings(collect="some", fields=list(set(s1.fields or []).intersection(s2.fields or []))) - if not ret.fields: - ret.collect = "none" - return ret diff --git a/py/src/braintrust/gitutil.py b/py/src/braintrust/gitutil.py deleted file mode 100644 index 4ab875e5e..000000000 --- a/py/src/braintrust/gitutil.py +++ /dev/null @@ -1,176 +0,0 @@ -import logging -import os -import re -import subprocess -import threading -from functools import lru_cache as _cache - -from .git_fields import GitMetadataSettings, RepoInfo - -# https://stackoverflow.com/questions/48399498/git-executable-not-found-in-python -os.environ["GIT_PYTHON_REFRESH"] = "quiet" -try: - import git -except ImportError: - git = None - -_logger = logging.getLogger("braintrust.gitutil") -_gitlock = threading.RLock() - - -@_cache(1) -def _current_repo(): - if git is None: - # If the git module is not available, we can't do anything. - return None - - try: - return git.Repo(search_parent_directories=True) - except git.exc.InvalidGitRepositoryError: - return None - - -@_cache(1) -def _get_base_branch(remote=None): - repo = _current_repo() - remote = repo.remote(**({} if remote is None else {"name": remote})).name - - # NOTE: This should potentially be configuration that we derive from the project, - # instead of spending a second or two computing it each time we run an experiment. - - # To speed this up in the short term, we pick from a list of common names - # and only fall back to the remote origin if required. - COMMON_BASE_BRANCHES = ["main", "master", "develop"] - repo_branches = {b.name for b in repo.branches} - if sum(b in repo_branches for b in COMMON_BASE_BRANCHES) == 1: - for b in COMMON_BASE_BRANCHES: - if b in repo_branches: - return (remote, b) - raise RuntimeError("Impossible") - - try: - s = subprocess.check_output(["git", "remote", "show", "origin"]).decode() - match = re.search(r"\s*HEAD branch:\s*(.*)$", s, re.MULTILINE) - if match is None: - raise RuntimeError("Could not find HEAD branch in remote " + remote) - branch = match.group(1) - except Exception as e: - _logger.warning(f"Could not find base branch for remote {remote}", e) - branch = "main" - return (remote, branch) - - -def _get_base_branch_ancestor(remote=None): - try: - remote_name, base_branch = _get_base_branch(remote) - except Exception as e: - _logger.warning( - f"Skipping git metadata. This is likely because the repository has not been published to a remote yet. {e}" - ) - return None - - try: - head = "HEAD" if _current_repo().is_dirty() else "HEAD^" - return subprocess.check_output(["git", "merge-base", head, f"{remote_name}/{base_branch}"]).decode().strip() - except (subprocess.CalledProcessError, git.GitCommandError) as e: - # _logger.warning(f"Could not find a common ancestor with {remote_name}/{base_branch}") - return None - - -def get_past_n_ancestors(n=1000, remote=None): - with _gitlock: - repo = _current_repo() - if repo is None: - return - - ancestor_output = _get_base_branch_ancestor() - if ancestor_output is None: - return - ancestor = repo.commit(ancestor_output) - count = 0 - for _ in range(n): - if count >= n: - break - yield ancestor.hexsha - count += 1 - try: - if ancestor.parents: - ancestor = ancestor.parents[0] - else: - break - except ValueError: - # Since parents are fetched on-demand, this can happen if the - # downloaded repo does not have information for this commit's - # parent. - break - - -def attempt(op): - try: - return op() - # OSError covers FileNotFoundError, FileExistsError, etc. - except (TypeError, ValueError, OSError, git.GitCommandError): - return None - - -def truncate_to_byte_limit(input_string, byte_limit=65536): - encoded = input_string.encode("utf-8") - if len(encoded) <= byte_limit: - return input_string - return encoded[:byte_limit].decode("utf-8", errors="ignore") - - -def get_repo_info(settings: GitMetadataSettings | None = None): - if settings is None: - settings = GitMetadataSettings() - - if settings.collect == "none": - return None - - repo = repo_info() - if repo is None or settings.collect == "all": - return repo - - return RepoInfo(**{k: v if k in settings.fields else None for k, v in repo.as_dict().items()}) - - -def repo_info(): - with _gitlock: - repo = _current_repo() - if repo is None: - return None - - commit = None - commit_message = None - commit_time = None - author_name = None - author_email = None - tag = None - branch = None - git_diff = None - - dirty = attempt(lambda: repo.is_dirty()) - - commit = attempt(lambda: repo.head.commit.hexsha.strip()) - commit_message = attempt(lambda: repo.head.commit.message.strip()) - commit_time = attempt(lambda: repo.head.commit.committed_datetime.isoformat()) - author_name = attempt(lambda: repo.head.commit.author.name.strip()) - author_email = attempt(lambda: repo.head.commit.author.email.strip()) - tag = attempt(lambda: repo.git.describe("--tags", "--exact-match", "--always")) - - branch = attempt(lambda: repo.active_branch.name) - - if dirty: - git_diff = attempt(lambda: truncate_to_byte_limit(repo.git.diff("HEAD", no_ext_diff=True))) - - return RepoInfo( - commit=commit, - branch=branch, - tag=tag, - dirty=dirty, - author_name=author_name, - author_email=author_email, - commit_message=commit_message, - commit_time=commit_time, - git_diff=git_diff, - ) diff --git a/py/src/braintrust/http_headers.py b/py/src/braintrust/http_headers.py deleted file mode 100644 index 138a1f03d..000000000 --- a/py/src/braintrust/http_headers.py +++ /dev/null @@ -1,4 +0,0 @@ -BT_FOUND_EXISTING_HEADER = "x-bt-found-existing" -BT_CURSOR_HEADER = "x-bt-cursor" -BT_IMPERSONATE_USER = "x-bt-impersonate-user" -BT_PARENT = "x-bt-parent" diff --git a/py/src/braintrust/id_gen.py b/py/src/braintrust/id_gen.py deleted file mode 100644 index 9aab15176..000000000 --- a/py/src/braintrust/id_gen.py +++ /dev/null @@ -1,61 +0,0 @@ -import os -import secrets -import uuid -from abc import ABC, abstractmethod - - -def get_id_generator(): - """Factory function that creates a new ID generator instance each time. - - This eliminates global state and makes tests parallelizable. - Each caller gets their own generator instance. - """ - use_otel = os.getenv("BRAINTRUST_OTEL_COMPAT", "false").lower() == "true" - return OTELIDGenerator() if use_otel else UUIDGenerator() - - -class IDGenerator(ABC): - """Abstract base class for ID generators.""" - - @abstractmethod - def get_span_id(self): - pass - - @abstractmethod - def get_trace_id(self): - pass - - @abstractmethod - def share_root_span_id(self): - """Return True if the generator should use span_id as root_span_id for backwards compatibility.""" - pass - - -class UUIDGenerator(IDGenerator): - """ID generator that uses UUID4 for both span and trace IDs.""" - - def get_span_id(self): - return str(uuid.uuid4()) - - def get_trace_id(self): - return str(uuid.uuid4()) - - def share_root_span_id(self): - return True - - -class OTELIDGenerator(IDGenerator): - """ID generator that generates OpenTelemetry-compatible IDs. We use this to have ids that can - seamlessly flow between Braintrust and OpenTelemetry. - """ - - def get_span_id(self): - # Generate 8 random bytes and convert to hex - return secrets.token_hex(8) - - def get_trace_id(self): - # Generate 16 random bytes and convert to hex - return secrets.token_hex(16) - - def share_root_span_id(self): - return False diff --git a/py/src/braintrust/logger.py b/py/src/braintrust/logger.py deleted file mode 100644 index 645446a04..000000000 --- a/py/src/braintrust/logger.py +++ /dev/null @@ -1,5550 +0,0 @@ -import atexit -import base64 -import concurrent.futures -import contextlib -import contextvars -import dataclasses -import datetime -import inspect -import io -import json -import logging -import os -import sys -import textwrap -import threading -import time -import traceback -import types -import uuid -from abc import ABC, abstractmethod -from collections.abc import Callable, Iterator, Mapping, MutableMapping, Sequence -from functools import partial, wraps -from multiprocessing import cpu_count -from types import TracebackType -from typing import ( - Any, - Dict, - Generic, - Literal, - Optional, - TypedDict, - TypeVar, - Union, - cast, - overload, -) -from urllib.parse import urlencode - -import chevron -import exceptiongroup -import requests -import urllib3 -from braintrust.functions.stream import BraintrustStream -from requests.adapters import HTTPAdapter -from urllib3.util.retry import Retry - -from . import context, id_gen -from .bt_json import bt_dumps, bt_safe_deep_copy -from .db_fields import ( - AUDIT_METADATA_FIELD, - AUDIT_SOURCE_FIELD, - IS_MERGE_FIELD, - OBJECT_DELETE_FIELD, - OBJECT_ID_KEYS, - TRANSACTION_ID_FIELD, - VALID_SOURCES, -) -from .generated_types import ( - AttachmentReference, - AttachmentStatus, - DatasetEvent, - ExperimentEvent, - PromptOptions, - SpanAttributes, -) -from .git_fields import GitMetadataSettings, RepoInfo -from .gitutil import get_past_n_ancestors, get_repo_info -from .merge_row_batch import batch_items, merge_row_batch -from .object import DEFAULT_IS_LEGACY_DATASET, ensure_dataset_record -from .prompt import BRAINTRUST_PARAMS, ImagePart, PromptBlockData, PromptData, PromptMessage, PromptSchema, TextPart -from .prompt_cache.disk_cache import DiskCache -from .prompt_cache.lru_cache import LRUCache -from .prompt_cache.prompt_cache import PromptCache -from .queue import DEFAULT_QUEUE_SIZE, LogQueue -from .serializable_data_class import SerializableDataClass -from .span_identifier_v3 import SpanComponentsV3, SpanObjectTypeV3 -from .span_identifier_v4 import SpanComponentsV4 -from .span_types import SpanTypeAttribute -from .util import ( - GLOBAL_PROJECT, - AugmentedHTTPError, - LazyValue, - _urljoin, - add_azure_blob_headers, - bt_iscoroutinefunction, - coalesce, - encode_uri_component, - eprint, - get_caller_location, - mask_api_key, - merge_dicts, - parse_env_var_float, - response_raise_for_status, -) - -# Fields that should be passed to the masking function -# Note: "tags" field is intentionally excluded, but can be added if needed -REDACTION_FIELDS = ["input", "output", "expected", "metadata", "context", "scores", "metrics"] -from .xact_ids import prettify_xact - -Metadata = dict[str, Any] -DATA_API_VERSION = 2 -LOGS3_OVERFLOW_REFERENCE_TYPE = "logs3_overflow" -# 6 MB for the AWS lambda gateway (from our own testing). -DEFAULT_MAX_REQUEST_SIZE = 6 * 1024 * 1024 - - -@dataclasses.dataclass -class Logs3OverflowInputRow: - object_ids: dict[str, Any] - has_comment: bool - is_delete: bool - byte_size: int - - -@dataclasses.dataclass -class LogItemWithMeta: - str_value: str - overflow_meta: Logs3OverflowInputRow - - -class DatasetRef(TypedDict, total=False): - """Reference to a dataset by ID and optional version.""" - - id: str - version: str - - -T = TypeVar("T") -TMapping = TypeVar("TMapping", bound=Mapping[str, Any]) -TMutableMapping = TypeVar("TMutableMapping", bound=MutableMapping[str, Any]) - - -TEST_API_KEY = "___TEST_API_KEY__" - -DEFAULT_APP_URL = "https://www.braintrust.dev" - - -def _get_exporter(): - """Return the active exporter (e.g. the version of SpanComponentsv*)""" - use_v4 = os.getenv("BRAINTRUST_OTEL_COMPAT", "false").lower() == "true" - return SpanComponentsV4 if use_v4 else SpanComponentsV3 - - -class Exportable(ABC): - @abstractmethod - def export(self) -> str: - """Return a serialized representation of the object that can be used to start subspans in other places. See `Span.start_span` for more details.""" - - -class Span(Exportable, contextlib.AbstractContextManager, ABC): - """ - A Span encapsulates logged data and metrics for a unit of work. This interface is shared by all span implementations. - - We suggest using one of the various `start_span` methods, instead of creating Spans directly. See `Span.start_span` for full details. - """ - - @property - @abstractmethod - def id(self) -> str: - """Row ID of the span.""" - - @property - @abstractmethod - def name(self) -> str: - """Name of the span, for display purposes only.""" - - @abstractmethod - def log(self, **event: Any) -> None: - """Incrementally update the current span with new data. The event will be batched and uploaded behind the scenes. - - :param **event: Data to be logged. See `Experiment.log` for full details. - """ - - @abstractmethod - def log_feedback(self, **event: Any) -> None: - """Add feedback to the current span. Unlike `Experiment.log_feedback` and `Logger.log_feedback`, this method does not accept an id parameter, because it logs feedback to the current span. - - :param **event: Data to be logged. See `Experiment.log_feedback` for full details. - """ - - @abstractmethod - def start_span( - self, - name: str | None = None, - type: SpanTypeAttribute | None = None, - span_attributes: SpanAttributes | Mapping[str, Any] | None = None, - start_time: float | None = None, - set_current: bool | None = None, - parent: str | None = None, - **event: Any, - ) -> "Span": - """Create a new span. This is useful if you want to log more detailed trace information beyond the scope of a single log event. Data logged over several calls to `Span.log` will be merged into one logical row. - - We recommend running spans within context managers (`with start_span(...) as span`) to automatically mark them as current and ensure they are ended. Only spans run within a context manager will be marked current, so they can be accessed using `braintrust.current_span()`. If you wish to start a span outside a context manager, be sure to end it with `span.end()`. - - :param name: Optional name of the span. If not provided, a name will be inferred from the call stack. - :param type: Optional type of the span. Use the `SpanTypeAttribute` enum or just provide a string directly. - If not provided, the type will be unset. - :param span_attributes: Optional additional attributes to attach to the span, such as a type name. - :param start_time: Optional start time of the span, as a timestamp in seconds. - :param set_current: If true (the default), the span will be marked as the currently-active span for the duration of the context manager. - :param parent: Optional parent info string for the span. The string can be generated from `[Span,Experiment,Logger].export`. If not provided, the current span will be used (depending on context). This is useful for adding spans to an existing trace. - :param **event: Data to be logged. See `Experiment.log` for full details. - :returns: The newly-created `Span` - """ - - @abstractmethod - def export(self) -> str: - """ - Serialize the identifiers of this span. The return value can be used to identify this span when starting a subspan elsewhere, such as another process or service, without needing to access this `Span` object. See the parameters of `Span.start_span` for usage details. - - Callers should treat the return value as opaque. The serialization format may change from time to time. If parsing is needed, use `SpanComponentsV4.from_str`. - - :returns: Serialized representation of this span's identifiers. - """ - - @abstractmethod - def link(self) -> str: - """ - Format a link to the Braintrust application for viewing this span. - - Links can be generated at any time, but they will only become viewable - after the span and its root have been flushed to the server and ingested. - - There are some conditions when a Span doesn't have enough information - to return a stable link (e.g. during an unresolved experiment). In this case - or if there's an error generating link, we'll return a placeholder link. - - :returns: A link to the span. - """ - - @abstractmethod - def permalink(self) -> str: - """ - Format a permalink to the Braintrust application for viewing this span. - - Links can be generated at any time, but they will only become viewable after the span and its root have been flushed to the server and ingested. - - This function can block resolving data with the server. For production - applications it's preferable to call `Span.link` instead. - - - :returns: A permalink to the span. - """ - - @abstractmethod - def end(self, end_time: float | None = None) -> float: - """Log an end time to the span (defaults to the current time). Returns the logged time. - - Will be invoked automatically if the span is bound to a context manager. - - :param end_time: Optional end time of the span, as a timestamp in seconds. - :returns: The end time logged to the span metrics. - """ - - @abstractmethod - def flush(self) -> None: - """Flush any pending rows to the server.""" - - @abstractmethod - def close(self, end_time: float | None = None) -> float: - """Alias for `end`.""" - - @abstractmethod - def set_attributes( - self, - name: str | None = None, - type: SpanTypeAttribute | None = None, - span_attributes: SpanAttributes | Mapping[str, Any] | None = None, - ) -> None: - """Set the span's name, type, or other attributes. These attributes will be attached to all log events within the span. - The attributes are equivalent to the arguments to start_span. - - :param name: Optional name of the span. If not provided, a name will be inferred from the call stack. - :param type: Optional type of the span. Use the `SpanTypeAttribute` enum or just provide a string directly. - If not provided, the type will be unset. - :param span_attributes: Optional additional attributes to attach to the span, such as a type name. - """ - pass - - @abstractmethod - def set_current(self) -> None: - """Set the span as the current span. This is used to mark the span as the active span for the current thread.""" - pass - - @abstractmethod - def unset_current(self) -> None: - """Unset the span as the current span.""" - pass - - -class _NoopSpan(Span): - """A fake implementation of the Span API which does nothing. This can be used as the default span.""" - - def __init__(self, *args: Any, **kwargs: Any): - pass - - @property - def id(self): - return "" - - @property - def name(self): - return "" - - @property - def propagated_event(self): - return None - - def log(self, **event: Any): - pass - - def log_feedback(self, **event: Any): - pass - - def start_span( - self, - name: str | None = None, - type: SpanTypeAttribute | None = None, - span_attributes: SpanAttributes | Mapping[str, Any] | None = None, - start_time: float | None = None, - set_current: bool | None = None, - parent: str | None = None, - **event: Any, - ): - return self - - def end(self, end_time: float | None = None) -> float: - return end_time or time.time() - - def export(self): - return "" - - def link(self) -> str: - return NOOP_SPAN_PERMALINK - - def permalink(self) -> str: - return NOOP_SPAN_PERMALINK - - def flush(self): - pass - - def close(self, end_time: float | None = None) -> float: - return self.end(end_time) - - def set_attributes( - self, - name: str | None = None, - type: SpanTypeAttribute | None = None, - span_attributes: SpanAttributes | Mapping[str, Any] | None = None, - ): - pass - - def set_current(self): - pass - - def unset_current(self): - pass - - def __enter__(self): - return super().__enter__() - - def __exit__( - self, - exc_type: type[BaseException] | None, - exc_value: BaseException | None, - traceback: TracebackType | None, - ): - pass - - -NOOP_SPAN: Span = _NoopSpan() -NOOP_SPAN_PERMALINK = "https://www.braintrust.dev/noop-span" - - -class BraintrustState: - def __init__(self): - self.id = str(uuid.uuid4()) - self.current_experiment: Experiment | None = None - # We use both a ContextVar and a plain attribute for the current logger: - # - _cv_logger (ContextVar): Provides async context isolation so different - # async tasks can have different loggers without affecting each other. - # - _local_logger (plain attribute): Fallback for threads, since ContextVars - # don't propagate to new threads. This way if users don't want to do - # anything specific they'll always have a "global logger" - self._cv_logger: contextvars.ContextVar[Logger | None] = contextvars.ContextVar( - "braintrust_current_logger", default=None - ) - self._local_logger: Logger | None = None - self.current_parent: contextvars.ContextVar[str | None] = contextvars.ContextVar( - "braintrust_current_parent", default=None - ) - self.current_span: contextvars.ContextVar[Span] = contextvars.ContextVar( - "braintrust_current_span", default=NOOP_SPAN - ) - - # Context manager is dynamically selected based on current environment - self._context_manager = None - self._context_manager_lock = threading.Lock() - - def default_get_api_conn(): - self.login() - return self.api_conn() - - # Any time we re-log in, we directly update the api_conn inside the - # logger. This is preferable to replacing the whole logger, which would - # create the possibility of multiple loggers floating around. - # - # We lazily-initialize the logger so that it does any initialization - # (including reading env variables) upon the first actual usage. - self._global_bg_logger = LazyValue( - lambda: _HTTPBackgroundLogger(LazyValue(default_get_api_conn, use_mutex=True)), use_mutex=True - ) - - self._id_generator = None - - # For unit-testing, tests may wish to temporarily override the global - # logger with a custom one. We allow this but keep the override variable - # thread-local to prevent the possibility that tests running on - # different threads unintentionally use the same override. - self._override_bg_logger = threading.local() - - self.reset_login_info() - - self._prompt_cache = PromptCache( - memory_cache=LRUCache( - max_size=int(os.environ.get("BRAINTRUST_PROMPT_CACHE_MEMORY_MAX_SIZE", str(1 << 10))) - ), - disk_cache=DiskCache( - cache_dir=os.environ.get( - "BRAINTRUST_PROMPT_CACHE_DIR", f"{os.environ.get('HOME')}/.braintrust/prompt_cache" - ), - max_size=int(os.environ.get("BRAINTRUST_PROMPT_CACHE_DISK_MAX_SIZE", str(1 << 20))), - serializer=lambda x: x.as_dict(), - deserializer=PromptSchema.from_dict_deep, - ), - ) - - from braintrust.span_cache import SpanCache - - self.span_cache = SpanCache() - self._otel_flush_callback: Any | None = None - - def reset_login_info(self): - self.app_url: str | None = None - self.app_public_url: str | None = None - self.login_token: str | None = None - self.org_id: str | None = None - self.org_name: str | None = None - self.api_url: str | None = None - self.proxy_url: str | None = None - self.logged_in: bool = False - self.git_metadata_settings: GitMetadataSettings | None = None - - self._app_conn: HTTPConnection | None = None - self._api_conn: HTTPConnection | None = None - self._proxy_conn: HTTPConnection | None = None - self._user_info: Mapping[str, Any] | None = None - - def reset_parent_state(self): - # reset possible parent state for tests - self.current_experiment = None - self._cv_logger.set(None) - self._local_logger = None - self.current_parent.set(None) - self.current_span.set(NOOP_SPAN) - - def _reset_id_generator(self): - # used in tests when we want to test with a different id generators - # which are controlled by env vars. - self._id_generator = None - - def _reset_context_manager(self): - # used in tests when we want to test with a different context manager - # which is controlled by BRAINTRUST_OTEL_COMPAT env var. - self._context_manager = None - - @property - def id_generator(self): - """Return the active id generator.""" - # While we probably only need one id generator per process (and it's configured with env vars), it's part of state - # so that we could possibly have parallel tests using different id generators. - if self._id_generator is None: - self._id_generator = id_gen.get_id_generator() - return self._id_generator - - @property - def context_manager(self): - """Get the appropriate context manager based on current environment.""" - # Cache the context manager on first access - if self._context_manager is None: - with self._context_manager_lock: - # Double-check after acquiring lock - if self._context_manager is None: - from braintrust.context import get_context_manager - - self._context_manager = get_context_manager() - - return self._context_manager - - def register_otel_flush(self, callback: Any) -> None: - """ - Register an OTEL flush callback. This is called by the OTEL integration - when it initializes a span processor/exporter. - """ - self._otel_flush_callback = callback - - async def flush_otel(self) -> None: - """ - Flush OTEL spans if a callback is registered. - Called during ensure_spans_flushed to ensure OTEL spans are visible in BTQL. - """ - if self._otel_flush_callback: - await self._otel_flush_callback() - - def copy_state(self, other: "BraintrustState"): - """Copy login information from another BraintrustState instance.""" - self.__dict__.update( - { - k: v - for (k, v) in other.__dict__.items() - if k - not in ( - "current_experiment", - "_cv_logger", - "_local_logger", - "current_parent", - "current_span", - "_global_bg_logger", - "_override_bg_logger", - "_context_manager", - "_last_otel_setting", - "_context_manager_lock", - ) - } - ) - - def login( - self, - app_url: str | None = None, - api_key: str | None = None, - org_name: str | None = None, - force_login: bool = False, - ) -> None: - if not force_login and self.logged_in: - # We have already logged in. If any provided login inputs disagree - # with our existing settings, raise an Exception warning the user to - # try again with `force_login=True`. - def check_updated_param(varname, arg, orig): - if arg is not None and orig is not None and arg != orig: - raise Exception( - f"Re-logging in with different {varname} ({arg}) than original ({orig}). To force re-login, pass `force_login=True`" - ) - - sanitized_api_key = HTTPConnection.sanitize_token(api_key) if api_key else None - check_updated_param("app_url", app_url, self.app_url) - check_updated_param("api_key", sanitized_api_key, self.login_token) - check_updated_param("org_name", org_name, self.org_name) - return - - state = login_to_state( - app_url=app_url, - api_key=api_key, - org_name=org_name, - ) - self.copy_state(state) - - def app_conn(self): - if not self._app_conn: - if not self.app_url: - raise RuntimeError("Must initialize app_url before requesting app_conn") - self._app_conn = HTTPConnection(self.app_url, adapter=_http_adapter) - return self._app_conn - - def api_conn(self): - if not self._api_conn: - if not self.api_url: - raise RuntimeError("Must initialize api_url before requesting api_conn") - self._api_conn = HTTPConnection(self.api_url, adapter=_http_adapter) - return self._api_conn - - def proxy_conn(self): - if not self.proxy_url: - return self.api_conn() - - if not self._proxy_conn: - if not self.proxy_url: - raise RuntimeError("Must initialize proxy_url before requesting proxy_conn") - self._proxy_conn = HTTPConnection(self.proxy_url, adapter=_http_adapter) - return self._proxy_conn - - def user_info(self) -> Mapping[str, Any]: - if not self._user_info: - self._user_info = self.api_conn().get_json("ping") - return self._user_info - - def global_bg_logger(self) -> "_BackgroundLogger": - return getattr(self._override_bg_logger, "logger", None) or self._global_bg_logger.get() - - # Should only be called by the login function. - def login_replace_api_conn(self, api_conn: "HTTPConnection"): - self._global_bg_logger.get().internal_replace_api_conn(api_conn) - - def flush(self): - self._global_bg_logger.get().flush() - - def enforce_queue_size_limit(self, enforce: bool) -> None: - """ - Set queue size limit enforcement for the global background logger. - """ - bg_logger = self._global_bg_logger.get() - bg_logger.enforce_queue_size_limit(enforce) - - def set_masking_function(self, masking_function: Callable[[Any], Any] | None) -> None: - """Set the masking function on the background logger.""" - self.global_bg_logger().set_masking_function(masking_function) - - -_state: BraintrustState = None # type: ignore - - -_http_adapter: HTTPAdapter | None = None - - -def set_http_adapter(adapter: HTTPAdapter) -> None: - """ - Specify a custom HTTP adapter to use for all network requests. This is useful for setting custom retry policies, timeouts, etc. - Braintrust uses the `requests` library, so the adapter should be an instance of `requests.adapters.HTTPAdapter`. Alternatively, consider - sub-classing our `RetryRequestExceptionsAdapter` to get automatic retries on network-related exceptions. - - :param adapter: The adapter to use. - """ - - global _http_adapter - - _http_adapter = adapter - - if _state._app_conn: - _state._app_conn._set_adapter(adapter=adapter) - _state._app_conn._reset() - if _state._api_conn: - _state._api_conn._set_adapter(adapter=adapter) - _state._api_conn._reset() - - -class RetryRequestExceptionsAdapter(HTTPAdapter): - """An HTTP adapter that automatically retries requests on connection exceptions. - - This adapter extends requests' HTTPAdapter to add retry logic for common network-related - exceptions including connection errors, timeouts, and other HTTP errors. It implements - an exponential backoff strategy between retries to avoid overwhelming servers during - intermittent connectivity issues. - - Attributes: - base_num_retries: Maximum number of retries before giving up and re-raising the exception. - backoff_factor: A multiplier used to determine the time to wait between retries. - The actual wait time is calculated as: backoff_factor * (2 ** retry_count). - default_timeout_secs: Default timeout in seconds for requests that don't specify one. - Prevents indefinite hangs on stale connections. - """ - - def __init__( - self, - *args: Any, - base_num_retries: int = 0, - backoff_factor: float = 0.5, - default_timeout_secs: float = 60, - **kwargs: Any, - ): - self.base_num_retries = base_num_retries - self.backoff_factor = backoff_factor - self.default_timeout_secs = default_timeout_secs - super().__init__(*args, **kwargs) - - def send(self, *args, **kwargs): - # Apply default timeout if none provided to prevent indefinite hangs - if kwargs.get("timeout") is None: - kwargs["timeout"] = self.default_timeout_secs - - num_prev_retries = 0 - while True: - try: - response = super().send(*args, **kwargs) - # Fully-download the content to ensure we catch any errors from - # downloading. - if not response.is_redirect and response.content: - pass - return response - except (urllib3.exceptions.HTTPError, requests.exceptions.RequestException) as e: - if num_prev_retries < self.base_num_retries: - if isinstance(e, requests.exceptions.ReadTimeout): - # Clear all connection pools to discard stale connections. This - # fixes hangs caused by NAT gateways silently dropping idle TCP - # connections (e.g., Azure's ~4 min timeout). close() calls - # PoolManager.clear() which is thread-safe: in-flight requests - # keep their checked-out connections, and new requests create - # fresh pools on demand. - self.close() - # Emulates the sleeping logic in the backoff_factor of urllib3 Retry - sleep_s = self.backoff_factor * (2**num_prev_retries) - print("Retrying request after error:", e, file=sys.stderr) - print("Sleeping for", sleep_s, "seconds", file=sys.stderr) - time.sleep(sleep_s) - num_prev_retries += 1 - else: - raise e - - -class HTTPConnection: - def __init__(self, base_url: str, adapter: HTTPAdapter | None = None): - self.base_url = base_url - self.token = None - self.adapter = adapter - - self._reset(total=0) - - def ping(self) -> bool: - try: - resp = self.get("ping") - return resp.ok - except requests.exceptions.ConnectionError: - return False - - def make_long_lived(self) -> None: - if not self.adapter: - timeout_secs = parse_env_var_float("BRAINTRUST_HTTP_TIMEOUT", 60.0) - self.adapter = RetryRequestExceptionsAdapter( - base_num_retries=10, backoff_factor=0.5, default_timeout_secs=timeout_secs - ) - self._reset() - - @staticmethod - def sanitize_token(token: str) -> str: - return token.rstrip("\n") - - def set_token(self, token: str) -> None: - token = HTTPConnection.sanitize_token(token) - self.token = token - self._set_session_token() - - def _set_adapter(self, adapter: HTTPAdapter | None) -> None: - self.adapter = adapter - - def _reset(self, **retry_kwargs: Any) -> None: - self.session = requests.Session() - - adapter = self.adapter - if adapter is None: - retry = Retry(**retry_kwargs) - adapter = HTTPAdapter(max_retries=retry) - - self.session.mount("http://", adapter) - self.session.mount("https://", adapter) - - self._set_session_token() - - def _set_session_token(self) -> None: - if self.token: - self.session.headers.update({"Authorization": f"Bearer {self.token}"}) - - def get(self, path: str, *args: Any, **kwargs: Any) -> requests.Response: - return self.session.get(_urljoin(self.base_url, path), *args, **kwargs) - - def post(self, path: str, *args: Any, **kwargs: Any) -> requests.Response: - return self.session.post(_urljoin(self.base_url, path), *args, **kwargs) - - def put(self, path: str, *args: Any, **kwargs: Any) -> requests.Response: - return self.session.put(_urljoin(self.base_url, path), *args, **kwargs) - - def delete(self, path: str, *args: Any, **kwargs: Any) -> requests.Response: - return self.session.delete(_urljoin(self.base_url, path), *args, **kwargs) - - def get_json(self, object_type: str, args: Mapping[str, Any] | None = None) -> Mapping[str, Any]: - resp = self.get(f"/{object_type}", params=args) - response_raise_for_status(resp) - return resp.json() - - def post_json(self, object_type: str, args: Mapping[str, Any] | None = None) -> Any: - resp = self.post(f"/{object_type.lstrip('/')}", json=args) - response_raise_for_status(resp) - return resp.json() - - -# Sometimes we'd like to launch network requests concurrently. We provide a -# thread pool to accomplish this. Use a multiple of number of CPU cores to limit -# concurrency. -HTTP_REQUEST_THREAD_POOL = concurrent.futures.ThreadPoolExecutor(max_workers=cpu_count()) - - -def api_conn(): - return _state.api_conn() - - -def app_conn(): - return _state.app_conn() - - -def proxy_conn(): - return _state.proxy_conn() - - -def user_info(): - return _state.user_info() - - -def org_id(): - return _state.org_id - - -def construct_json_array(items: Sequence[str]): - return "[" + ",".join(items) + "]" - - -def construct_logs3_data(items: Sequence[LogItemWithMeta]): - rowsS = construct_json_array([item.str_value for item in items]) - return '{"rows": ' + rowsS + ', "api_version": ' + str(DATA_API_VERSION) + "}" - - -def construct_logs3_overflow_request(key: str, size_bytes: int | None = None) -> dict[str, Any]: - rows: dict[str, Any] = {"type": LOGS3_OVERFLOW_REFERENCE_TYPE, "key": key} - if size_bytes is not None: - rows["size_bytes"] = size_bytes - return {"rows": rows, "api_version": DATA_API_VERSION} - - -def pick_logs3_overflow_object_ids(row: Mapping[str, Any]) -> dict[str, Any]: - object_ids: dict[str, Any] = {} - for key in OBJECT_ID_KEYS: - if key in row: - object_ids[key] = row[key] - return object_ids - - -def stringify_with_overflow_meta(item: dict[str, Any]) -> LogItemWithMeta: - str_value = bt_dumps(item) - return LogItemWithMeta( - str_value=str_value, - overflow_meta=Logs3OverflowInputRow( - object_ids=pick_logs3_overflow_object_ids(item), - has_comment="comment" in item, - is_delete=item.get(OBJECT_DELETE_FIELD) is True, - byte_size=utf8_byte_length(str_value), - ), - ) - - -def utf8_byte_length(value: str) -> int: - return len(value.encode("utf-8")) - - -class _MaskingError: - """Internal class to signal masking errors that need special handling.""" - - def __init__(self, field_name: str, error_type: str): - self.field_name = field_name - self.error_type = error_type - self.error_msg = f"ERROR: Failed to mask field '{field_name}' - {error_type}" - - -def _apply_masking_to_field(masking_function: Callable[[Any], Any], data: Any, field_name: str) -> Any: - """Apply masking function to data and handle errors gracefully. - - If the masking function raises an exception, returns an error message. - Returns _MaskingError for scores/metrics fields to signal they should be dropped. - """ - try: - return masking_function(data) - except Exception as mask_error: - # Return a generic error message without the stack trace to avoid leaking PII - error_type = type(mask_error).__name__ - - # For scores and metrics fields, return a special error object - # to signal the field should be dropped and error logged - if field_name in ["scores", "metrics"]: - return _MaskingError(field_name, error_type) - - # For metadata field that expects dict type, return a dict with error key - if field_name == "metadata": - return {"error": f"ERROR: Failed to mask field '{field_name}' - {error_type}"} - - # For other fields, return the error message as a string - return f"ERROR: Failed to mask field '{field_name}' - {error_type}" - - -class _BackgroundLogger(ABC): - @abstractmethod - def log(self, *args: LazyValue[dict[str, Any]]) -> None: - pass - - @abstractmethod - def flush(self, batch_size: int | None = None): - pass - - -class _MemoryBackgroundLogger(_BackgroundLogger): - def __init__(self): - self.lock = threading.Lock() - self.logs = [] - self.masking_function: Callable[[Any], Any] | None = None - self.upload_attempts: list[BaseAttachment] = [] # Track upload attempts - - def enforce_queue_size_limit(self, enforce: bool) -> None: - pass - - def log(self, *args: LazyValue[dict[str, Any]]) -> None: - with self.lock: - self.logs.extend(args) - - def set_masking_function(self, masking_function: Callable[[Any], Any] | None) -> None: - """Set the masking function for the memory logger.""" - self.masking_function = masking_function - - def flush(self, batch_size: int | None = None): - """Flush the memory logger, extracting attachments and tracking upload attempts.""" - with self.lock: - if not self.logs: - return - - # Unwrap lazy values and extract attachments - logs = [l.get() for l in self.logs] - - # Extract attachments from all logs - attachments: list[BaseAttachment] = [] - for log in logs: - _extract_attachments(log, attachments) - - # Track upload attempts (don't actually call upload() in tests) - self.upload_attempts.extend(attachments) - - def pop(self): - with self.lock: - logs = [l.get() for l in self.logs] # unwrap the LazyValues - self.logs = [] - - if not logs: - return [] - - # all the logs get merged before gettig sent to the server, so simulate that - # here - batch = merge_row_batch(logs) - - # Apply masking after merge, similar to HTTPBackgroundLogger - if self.masking_function: - for i in range(len(batch)): - item = batch[i] - masked_item = item.copy() - - # Only mask specific fields if they exist - for field in REDACTION_FIELDS: - if field in item: - masked_value = _apply_masking_to_field(self.masking_function, item[field], field) - if isinstance(masked_value, _MaskingError): - # Drop the field and add error message - if field in masked_item: - del masked_item[field] - if "error" in masked_item: - masked_item["error"] = f"{masked_item['error']}; {masked_value.error_msg}" - else: - masked_item["error"] = masked_value.error_msg - else: - masked_item[field] = masked_value - - batch[i] = masked_item - - return batch - - -BACKGROUND_LOGGER_BASE_SLEEP_TIME_S = 1.0 - - -# We should only have one instance of this object in -# 'BraintrustState._global_bg_logger'. Be careful about spawning multiple -# instances of this class, because concurrent _BackgroundLoggers will not log to -# the backend in a deterministic order. -class _HTTPBackgroundLogger: - def __init__(self, api_conn: LazyValue[HTTPConnection]): - self.api_conn = api_conn - self.masking_function: Callable[[Any], Any] | None = None - self.outfile = sys.stderr - self.flush_lock = threading.RLock() - self._max_request_size_override: int | None = None - self._max_request_size_result: dict[str, Any] | None = None - self._max_request_size_lock = threading.Lock() - - try: - self.sync_flush = bool(int(os.environ["BRAINTRUST_SYNC_FLUSH"])) - except: - self.sync_flush = False - - try: - self._max_request_size_override = int(os.environ["BRAINTRUST_MAX_REQUEST_SIZE"]) - except: - pass - - try: - self.default_batch_size = int(os.environ["BRAINTRUST_DEFAULT_BATCH_SIZE"]) - except: - self.default_batch_size = 100 - - try: - self.num_tries = int(os.environ["BRAINTRUST_NUM_RETRIES"]) + 1 - except: - self.num_tries = 3 - - try: - self.queue_maxsize = int(os.environ["BRAINTRUST_QUEUE_SIZE"]) - except: - self.queue_maxsize = DEFAULT_QUEUE_SIZE - - try: - self.queue_drop_logging_period = float(os.environ["BRAINTRUST_QUEUE_DROP_LOGGING_PERIOD"]) - except: - self.queue_drop_logging_period = 60 - - self._queue_drop_logging_state = dict(lock=threading.Lock(), num_dropped=0, last_logged_timestamp=0) - - try: - self.failed_publish_payloads_dir = os.environ["BRAINTRUST_FAILED_PUBLISH_PAYLOADS_DIR"] - except: - self.failed_publish_payloads_dir = None - - try: - self.all_publish_payloads_dir = os.environ["BRAINTRUST_ALL_PUBLISH_PAYLOADS_DIR"] - except: - self.all_publish_payloads_dir = None - - self.start_thread_lock = threading.RLock() - self.thread = threading.Thread(target=self._publisher, daemon=True) - self.started = False - - self.logger = logging.getLogger("braintrust") - self.queue: "LogQueue[LazyValue[Dict[str, Any]]]" = LogQueue(maxsize=self.queue_maxsize) - - # Counter for tracking overflow uploads (useful for testing) - self._overflow_upload_count = 0 - - atexit.register(self._finalize) - - def enforce_queue_size_limit(self, enforce: bool) -> None: - """ - Set queue size limit enforcement. When enabled, the queue will drop new items - when it reaches maxsize. When disabled (default), the queue can grow unlimited. - """ - self.queue.enforce_queue_size_limit(enforce) - - def log(self, *args: LazyValue[dict[str, Any]]) -> None: - self._start() - dropped_items = [] - for event in args: - dropped = self.queue.put(event) - dropped_items.extend(dropped) - - if dropped_items: - self._register_dropped_item_count(len(dropped_items)) - if self.all_publish_payloads_dir or self.failed_publish_payloads_dir: - try: - HTTP_REQUEST_THREAD_POOL.submit(self._dump_dropped_events, dropped_items) - except Exception as e: - traceback.print_exc(file=self.outfile) - - def _start(self): - # Double read to avoid contention in the common case. - if not self.started: - with self.start_thread_lock: - if not self.started: - self.thread.start() - self.started = True - - def _finalize(self): - self.logger.debug("Flushing final log events...") - self.flush() - - def _publisher(self): - while True: - # Wait for some data on the queue before trying to flush. - self.queue.wait_for_items() - - while self.sync_flush: - time.sleep(0.1) - - try: - self.flush() - except: - # Print exception but don't worry if stderr is closed because the process is shutting down. - try: - traceback.print_exc(file=self.outfile) - except ValueError as e: - if "operation on closed file" in str(e): - pass - else: - raise - - def _get_max_request_size(self) -> dict[str, Any]: - if self._max_request_size_result is not None: - return self._max_request_size_result - with self._max_request_size_lock: - if self._max_request_size_result is not None: - return self._max_request_size_result - server_limit: int | None = None - try: - conn = self.api_conn.get() - info = conn.get_json("version") - limit = info.get("logs3_payload_max_bytes") - if isinstance(limit, (int, float)) and int(limit) > 0: - server_limit = int(limit) - except Exception as e: - print(f"Failed to fetch version info for payload limit: {e}", file=self.outfile) - valid_server_limit = server_limit if server_limit is not None and server_limit > 0 else None - can_use_overflow = valid_server_limit is not None - max_request_size = DEFAULT_MAX_REQUEST_SIZE - if self._max_request_size_override is not None: - max_request_size = ( - min(self._max_request_size_override, valid_server_limit) - if valid_server_limit is not None - else self._max_request_size_override - ) - elif valid_server_limit is not None: - max_request_size = valid_server_limit - self._max_request_size_result = { - "max_request_size": max_request_size, - "can_use_overflow": can_use_overflow, - } - return self._max_request_size_result - - def flush(self, batch_size: int | None = None): - if batch_size is None: - batch_size = self.default_batch_size - - # We cannot have multiple threads flushing in parallel, because the - # order of published elements would be undefined. - with self.flush_lock: - # Drain the queue. - wrapped_items = self.queue.drain_all() - - all_items, attachments = self._unwrap_lazy_values(wrapped_items) - if len(all_items) == 0: - return - - # Construct batches of records to flush in parallel. - all_items_with_meta = [stringify_with_overflow_meta(item) for item in all_items] - max_request_size_result = self._get_max_request_size() - batches = batch_items( - items=all_items_with_meta, - batch_max_num_items=batch_size, - batch_max_num_bytes=max_request_size_result["max_request_size"] // 2, - get_byte_size=lambda item: len(item.str_value), - ) - - post_promises = [] - try: - post_promises = [ - HTTP_REQUEST_THREAD_POOL.submit(self._submit_logs_request, batch, max_request_size_result) - for batch in batches - ] - except RuntimeError: - # If the thread pool has shut down, e.g. because the process - # is terminating, run the requests the old fashioned way. - for batch in batches: - self._submit_logs_request(batch, max_request_size_result) - - concurrent.futures.wait(post_promises) - # Raise any exceptions from the promises as one group. - post_promise_exceptions = [e for e in (f.exception() for f in post_promises) if e is not None] - if post_promise_exceptions: - raise exceptiongroup.BaseExceptionGroup( - f"Encountered the following errors while logging:", post_promise_exceptions - ) - - attachment_errors: list[Exception] = [] - for attachment in attachments: - try: - result = attachment.upload() - if result["upload_status"] == "error": - raise RuntimeError(result.get("error_message")) - except Exception as e: - attachment_errors.append(e) - - if len(attachment_errors) == 1: - raise attachment_errors[0] - elif len(attachment_errors) > 1: - raise exceptiongroup.ExceptionGroup( - "Encountered errors while uploading attachments", - attachment_errors, - ) - - def _unwrap_lazy_values( - self, wrapped_items: Sequence[LazyValue[dict[str, Any]]] - ) -> tuple[list[dict[str, Any]], list["BaseAttachment"]]: - for i in range(self.num_tries): - try: - unwrapped_items = [item.get() for item in wrapped_items] - merged_items = merge_row_batch(unwrapped_items) - - # Apply masking after merging but before sending to backend - if self.masking_function: - for item_idx in range(len(merged_items)): - item = merged_items[item_idx] - masked_item = item.copy() - - # Only mask specific fields if they exist - for field in REDACTION_FIELDS: - if field in item: - masked_value = _apply_masking_to_field(self.masking_function, item[field], field) - if isinstance(masked_value, _MaskingError): - # Drop the field and add error message - if field in masked_item: - del masked_item[field] - if "error" in masked_item: - masked_item["error"] = f"{masked_item['error']}; {masked_value.error_msg}" - else: - masked_item["error"] = masked_value.error_msg - else: - masked_item[field] = masked_value - - merged_items[item_idx] = masked_item - - attachments: list["BaseAttachment"] = [] - for item in merged_items: - _extract_attachments(item, attachments) - - return merged_items, attachments - except Exception as e: - errmsg = "Encountered error when constructing records to flush" - is_retrying = i + 1 < self.num_tries - if is_retrying: - errmsg += ". Retrying" - - if not is_retrying and self.sync_flush: - raise Exception(errmsg) from e - else: - print(errmsg, file=self.outfile) - traceback.print_exc(file=self.outfile) - if is_retrying: - sleep_time_s = BACKGROUND_LOGGER_BASE_SLEEP_TIME_S * (2**i) - print(f"Sleeping for {sleep_time_s}s", file=self.outfile) - time.sleep(sleep_time_s) - - print( - f"Failed to construct log records to flush after {self.num_tries} attempts. Dropping batch", - file=self.outfile, - ) - return [], [] - - def _request_logs3_overflow_upload( - self, conn: HTTPConnection, payload_size_bytes: int, rows: list[dict[str, Any]] - ) -> dict[str, Any]: - try: - resp = conn.post( - "/logs3/overflow", - json={"content_type": "application/json", "size_bytes": payload_size_bytes, "rows": rows}, - ) - resp.raise_for_status() - payload = resp.json() - except Exception as e: - raise RuntimeError(f"Failed to request logs3 overflow upload URL: {e}") from e - - method = payload.get("method") - if method not in ("PUT", "POST"): - raise RuntimeError(f"Invalid response from API server (method must be PUT or POST): {payload}") - signed_url = payload.get("signedUrl") - headers = payload.get("headers") - fields = payload.get("fields") - key = payload.get("key") - if not isinstance(signed_url, str) or not isinstance(key, str): - raise RuntimeError(f"Invalid response from API server: {payload}") - if method == "PUT" and not isinstance(headers, dict): - raise RuntimeError(f"Invalid response from API server: {payload}") - if method == "POST" and not isinstance(fields, dict): - raise RuntimeError(f"Invalid response from API server: {payload}") - - if method == "PUT": - add_azure_blob_headers(headers, signed_url) - - return { - "method": method, - "signed_url": signed_url, - "headers": headers if isinstance(headers, dict) else {}, - "fields": fields if isinstance(fields, dict) else {}, - "key": key, - } - - def _upload_logs3_overflow_payload(self, upload: dict[str, Any], payload: str) -> None: - obj_conn = HTTPConnection(base_url="", adapter=_http_adapter) - method = upload["method"] - if method == "POST": - fields = upload.get("fields") - if not isinstance(fields, dict): - raise RuntimeError("Missing logs3 overflow upload fields") - content_type = fields.get("Content-Type", "application/json") - headers = {k: v for k, v in upload.get("headers", {}).items() if k.lower() != "content-type"} - obj_response = obj_conn.post( - upload["signed_url"], - headers=headers, - data=fields, - files={"file": ("logs3.json", payload.encode("utf-8"), content_type)}, - ) - else: - obj_response = obj_conn.put( - upload["signed_url"], - headers=upload["headers"], - data=payload.encode("utf-8"), - ) - obj_response.raise_for_status() - - def _submit_logs_request(self, items: Sequence[LogItemWithMeta], max_request_size_result: dict[str, Any]): - conn = self.api_conn.get() - dataStr = construct_logs3_data(items) - payload_bytes = utf8_byte_length(dataStr) - max_request_size = max_request_size_result["max_request_size"] - can_use_overflow = max_request_size_result["can_use_overflow"] - use_overflow = can_use_overflow and payload_bytes > max_request_size - if self.all_publish_payloads_dir: - _HTTPBackgroundLogger._write_payload_to_dir(payload_dir=self.all_publish_payloads_dir, payload=dataStr) - overflow_upload: dict[str, Any] | None = None - overflow_rows = ( - [ - { - "object_ids": item.overflow_meta.object_ids, - "has_comment": item.overflow_meta.has_comment, - "is_delete": item.overflow_meta.is_delete, - "input_row": {"byte_size": item.overflow_meta.byte_size}, - } - for item in items - ] - if use_overflow - else None - ) - for i in range(self.num_tries): - start_time = time.time() - resp = None - error = None - try: - if overflow_rows: - if overflow_upload is None: - current_upload = self._request_logs3_overflow_upload(conn, payload_bytes, overflow_rows) - self._upload_logs3_overflow_payload(current_upload, dataStr) - overflow_upload = current_upload - resp = conn.post( - "/logs3", - json=construct_logs3_overflow_request(overflow_upload["key"], payload_bytes), - ) - else: - resp = conn.post("/logs3", data=dataStr.encode("utf-8")) - except Exception as e: - error = e - if error is None and resp is not None and resp.ok: - if overflow_rows: - self._overflow_upload_count += 1 - return - if error is None and resp is not None: - resp_errmsg = f"{resp.status_code}: {resp.text}" - else: - resp_errmsg = str(error) - - is_retrying = i + 1 < self.num_tries - retrying_text = "" if is_retrying else " Retrying" - errmsg = f"log request failed. Elapsed time: {time.time() - start_time} seconds. Payload size: {payload_bytes}.{retrying_text}\nError: {resp_errmsg}" - - if not is_retrying and self.failed_publish_payloads_dir: - _HTTPBackgroundLogger._write_payload_to_dir( - payload_dir=self.failed_publish_payloads_dir, payload=dataStr - ) - self._log_failed_payloads_dir() - - if not is_retrying and self.sync_flush: - raise Exception(errmsg) - else: - print(errmsg, file=self.outfile) - if is_retrying: - sleep_time_s = BACKGROUND_LOGGER_BASE_SLEEP_TIME_S * (2**i) - print(f"Sleeping for {sleep_time_s}s", file=self.outfile) - time.sleep(sleep_time_s) - - print(f"log request failed after {self.num_tries} retries. Dropping batch", file=self.outfile) - - def _dump_dropped_events(self, wrapped_items): - publish_payloads_dir = [x for x in [self.all_publish_payloads_dir, self.failed_publish_payloads_dir] if x] - if not (wrapped_items and publish_payloads_dir): - return - try: - all_items, attachments = self._unwrap_lazy_values(wrapped_items) - items_with_meta = [stringify_with_overflow_meta(item) for item in all_items] - dataStr = construct_logs3_data(items_with_meta) - attachment_str = bt_dumps([a.debug_info() for a in attachments]) - payload = "{" + f""""data": {dataStr}, "attachments": {attachment_str}""" + "}" - for output_dir in publish_payloads_dir: - if not output_dir: - continue - _HTTPBackgroundLogger._write_payload_to_dir(payload_dir=output_dir, payload=payload) - except Exception: - traceback.print_exc(file=self.outfile) - - def _register_dropped_item_count(self, num_items): - if num_items <= 0: - return - with self._queue_drop_logging_state["lock"]: - self._queue_drop_logging_state["num_dropped"] += num_items - time_now = time.time() - if time_now - self._queue_drop_logging_state["last_logged_timestamp"] >= self.queue_drop_logging_period: - print( - f"Dropped {self._queue_drop_logging_state['num_dropped']} elements due to full queue", - file=self.outfile, - ) - if self.failed_publish_payloads_dir: - self._log_failed_payloads_dir() - self._queue_drop_logging_state["num_dropped"] = 0 - self._queue_drop_logging_state["last_logged_timestamp"] = time_now - - @staticmethod - def _write_payload_to_dir(payload_dir, payload, debug_logging_adjective=None): - payload_file = os.path.join(payload_dir, f"payload_{time.time()}_{str(uuid.uuid4())[:8]}.json") - try: - os.makedirs(payload_dir, exist_ok=True) - with open(payload_file, "w") as f: - f.write(payload) - except Exception as e: - eprint(f"Failed to write failed payload to output file {payload_file}:\n", e) - - def _log_failed_payloads_dir(self): - print(f"Logging failed payloads to {self.failed_publish_payloads_dir}", file=self.outfile) - - # Should only be called by BraintrustState. - def internal_replace_api_conn(self, api_conn: HTTPConnection): - self.api_conn = LazyValue(lambda: api_conn, use_mutex=False) - - def set_masking_function(self, masking_function: Callable[[Any], Any] | None): - """Set or update the masking function.""" - self.masking_function = masking_function - - -def _internal_reset_global_state() -> None: - global _state - _state = BraintrustState() - - -def _internal_get_global_state() -> BraintrustState: - return _state - - -_internal_reset_global_state() -_logger = logging.getLogger("braintrust") - - -@contextlib.contextmanager -def _internal_with_custom_background_logger(): - custom_logger = _HTTPBackgroundLogger(LazyValue(lambda: _state.api_conn(), use_mutex=True)) - _state._override_bg_logger.logger = custom_logger - try: - yield custom_logger - finally: - _state._override_bg_logger.logger = None - - -@contextlib.contextmanager -def _internal_with_memory_background_logger(): - memory_logger = _MemoryBackgroundLogger() - _state._override_bg_logger.logger = memory_logger - try: - yield memory_logger - finally: - _state._override_bg_logger.logger = None - - -@dataclasses.dataclass -class ObjectMetadata: - id: str - name: str - full_info: dict[str, Any] - - -@dataclasses.dataclass -class ProjectExperimentMetadata: - project: ObjectMetadata - experiment: ObjectMetadata - - -@dataclasses.dataclass -class ProjectDatasetMetadata: - project: ObjectMetadata - dataset: ObjectMetadata - - -@dataclasses.dataclass -class OrgProjectMetadata: - org_id: str - project: ObjectMetadata - - -# Pyright produces an error for overlapping overloads -# (reportOverlappingOverload) because of the default argument to `open`. It -# thinks a call like `init()` with no arguments could match both overloads. -# However, Pyright is also able to use both overloads properly when type -# checking the caller. We can eventually add `type: ignore` if we cannot resolve -# this. -@overload -def init( - project: str | None = ..., - experiment: str | None = ..., - description: str | None = ..., - dataset: Optional["Dataset"] = ..., - open: Literal[False] = ..., - base_experiment: str | None = ..., - is_public: bool = ..., - app_url: str | None = ..., - api_key: str | None = ..., - org_name: str | None = ..., - metadata: Metadata | None = ..., - git_metadata_settings: GitMetadataSettings | None = ..., - set_current: bool = ..., - update: bool | None = ..., - project_id: str | None = ..., - base_experiment_id: str | None = ..., - repo_info: RepoInfo | None = ..., - state: BraintrustState | None = ..., -) -> "Experiment": ... - - -@overload -def init( - project: str | None = ..., - experiment: str | None = ..., - description: str | None = ..., - dataset: Optional["Dataset"] = ..., - open: Literal[True] = ..., - base_experiment: str | None = ..., - is_public: bool = ..., - app_url: str | None = ..., - api_key: str | None = ..., - org_name: str | None = ..., - metadata: Metadata | None = ..., - git_metadata_settings: GitMetadataSettings | None = ..., - set_current: bool = ..., - update: bool | None = ..., - project_id: str | None = ..., - base_experiment_id: str | None = ..., - repo_info: RepoInfo | None = ..., - state: BraintrustState | None = ..., -) -> "ReadonlyExperiment": ... - - -def init( - project: str | None = None, - experiment: str | None = None, - description: str | None = None, - dataset: Optional["Dataset"] | DatasetRef = None, - open: bool = False, - base_experiment: str | None = None, - is_public: bool = False, - app_url: str | None = None, - api_key: str | None = None, - org_name: str | None = None, - metadata: Metadata | None = None, - git_metadata_settings: GitMetadataSettings | None = None, - set_current: bool = True, - update: bool | None = None, - project_id: str | None = None, - base_experiment_id: str | None = None, - repo_info: RepoInfo | None = None, - state: BraintrustState | None = None, -) -> Union["Experiment", "ReadonlyExperiment"]: - """ - Log in, and then initialize a new experiment in a specified project. If the project does not exist, it will be created. - - :param project: The name of the project to create the experiment in. Must specify at least one of `project` or `project_id`. - :param experiment: The name of the experiment to create. If not specified, a name will be generated automatically. - :param description: (Optional) An optional description of the experiment. - :param dataset: (Optional) A dataset to associate with the experiment. The dataset must be initialized with `braintrust.init_dataset` before passing - it into the experiment. - :param update: If the experiment already exists, continue logging to it. If it does not exist, creates the experiment with the specified arguments. - :param base_experiment: An optional experiment name to use as a base. If specified, the new experiment will be summarized and compared to this experiment. Otherwise, it will pick an experiment by finding the closest ancestor on the default (e.g. main) branch. - :param is_public: An optional parameter to control whether the experiment is publicly visible to anybody with the link or privately visible to only members of the organization. Defaults to private. - :param app_url: The URL of the Braintrust App. Defaults to https://www.braintrust.dev. - :param api_key: The API key to use. If the parameter is not specified, will try to use the `BRAINTRUST_API_KEY` environment variable. If no API - key is specified, will prompt the user to login. - :param org_name: (Optional) The name of a specific organization to connect to. This is useful if you belong to multiple. - :param metadata: (Optional) a dictionary with additional data about the test example, model outputs, or just about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any JSON-serializable type, but its keys must be strings. - :param git_metadata_settings: (Optional) Settings for collecting git metadata. By default, will collect all git metadata fields allowed in org-level settings. - :param set_current: If true (the default), set the global current-experiment to the newly-created one. - :param open: If the experiment already exists, open it in read-only mode. Throws an error if the experiment does not already exist. - :param project_id: The id of the project to create the experiment in. This takes precedence over `project` if specified. - :param base_experiment_id: An optional experiment id to use as a base. If specified, the new experiment will be summarized and compared to this. This takes precedence over `base_experiment` if specified. - :param repo_info: (Optional) Explicitly specify the git metadata for this experiment. This takes precedence over `git_metadata_settings` if specified. - :param state: (Optional) A BraintrustState object to use. If not specified, will use the global state. This is for advanced use only. - :returns: The experiment object. - """ - - state: BraintrustState = state or _state - - if project is None and project_id is None: - raise ValueError("Must specify at least one of project or project_id") - - if open and update: - raise ValueError("Cannot open and update an experiment at the same time") - - if open: - if experiment is None: - raise ValueError(f"Cannot open an experiment without specifying its name") - - def compute_metadata(): - state.login(org_name=org_name, api_key=api_key, app_url=app_url) - args = { - "experiment_name": experiment, - "project_name": project, - "project_id": project_id, - "org_name": state.org_name, - } - - response = state.app_conn().post_json("api/experiment/get", args) - if len(response) == 0: - raise ValueError(f"Experiment {experiment} not found in project {project}.") - - info = response[0] - return ProjectExperimentMetadata( - project=ObjectMetadata(id=info["project_id"], name=project or "UNKNOWN_PROJECT", full_info=dict()), - experiment=ObjectMetadata( - id=info["id"], - name=info["name"], - full_info=info, - ), - ) - - lazy_metadata = LazyValue(compute_metadata, use_mutex=True) - return ReadonlyExperiment(lazy_metadata=lazy_metadata, state=state) - - # pylint: disable=function-redefined - def compute_metadata(): - state.login(org_name=org_name, api_key=api_key, app_url=app_url) - args = { - "project_name": project, - "project_id": project_id, - "org_id": state.org_id, - "update": update, - } - - if experiment is not None: - args["experiment_name"] = experiment - - if description is not None: - args["description"] = description - - if repo_info: - repo_info_arg = repo_info - else: - merged_git_metadata_settings = state.git_metadata_settings - if git_metadata_settings is not None: - merged_git_metadata_settings = GitMetadataSettings.merge( - merged_git_metadata_settings, git_metadata_settings - ) - repo_info_arg = get_repo_info(merged_git_metadata_settings) - - if repo_info_arg: - args["repo_info"] = repo_info_arg.as_dict() - - if base_experiment_id is not None: - args["base_exp_id"] = base_experiment_id - elif base_experiment is not None: - args["base_experiment"] = base_experiment - elif merged_git_metadata_settings and merged_git_metadata_settings.collect != "none": - args["ancestor_commits"] = list(get_past_n_ancestors()) - - if dataset is not None: - if isinstance(dataset, dict): - # Simple {"id": ..., "version": ...} dict - args["dataset_id"] = dataset["id"] - if "version" in dataset: - args["dataset_version"] = dataset["version"] - else: - # Full Dataset object - args["dataset_id"] = dataset.id - args["dataset_version"] = dataset.version - - if is_public is not None: - args["public"] = is_public - - if metadata is not None: - args["metadata"] = metadata - - while True: - try: - response = state.app_conn().post_json("api/experiment/register", args) - break - except AugmentedHTTPError as e: - if args.get("base_experiment") is not None and "base experiment" in str(e): - _logger.warning(f"Base experiment {args['base_experiment']} not found.") - args["base_experiment"] = None - else: - raise - - resp_project = response["project"] - resp_experiment = response["experiment"] - return ProjectExperimentMetadata( - project=ObjectMetadata(id=resp_project["id"], name=resp_project["name"], full_info=resp_project), - experiment=ObjectMetadata( - id=resp_experiment["id"], name=resp_experiment["name"], full_info=resp_experiment - ), - ) - - # For experiments, disable queue size limit enforcement (unlimited queue) - state.enforce_queue_size_limit(False) - - ret = Experiment( - lazy_metadata=LazyValue(compute_metadata, use_mutex=True), - dataset=dataset if isinstance(dataset, Dataset) else None, - state=state, - ) - if set_current: - state.current_experiment = ret - return ret - - -def init_experiment(*args, **kwargs) -> Union["Experiment", "ReadonlyExperiment"]: - """Alias for `init`""" - - return init(*args, **kwargs) - - -def init_dataset( - project: str | None = None, - name: str | None = None, - description: str | None = None, - version: str | int | None = None, - app_url: str | None = None, - api_key: str | None = None, - org_name: str | None = None, - project_id: str | None = None, - metadata: Metadata | None = None, - use_output: bool = DEFAULT_IS_LEGACY_DATASET, - _internal_btql: dict[str, Any] | None = None, - state: BraintrustState | None = None, -) -> "Dataset": - """ - Create a new dataset in a specified project. If the project does not exist, it will be created. - - :param project_name: The name of the project to create the dataset in. Must specify at least one of `project_name` or `project_id`. - :param name: The name of the dataset to create. If not specified, a name will be generated automatically. - :param description: An optional description of the dataset. - :param version: An optional version of the dataset (to read). If not specified, the latest version will be used. - :param app_url: The URL of the Braintrust App. Defaults to https://www.braintrust.dev. - :param api_key: The API key to use. If the parameter is not specified, will try to use the `BRAINTRUST_API_KEY` environment variable. If no API - key is specified, will prompt the user to login. - :param org_name: (Optional) The name of a specific organization to connect to. This is useful if you belong to multiple. - :param project_id: The id of the project to create the dataset in. This takes precedence over `project` if specified. - :param metadata: (Optional) a dictionary with additional data about the dataset. The values in `metadata` can be any JSON-serializable type, but its keys must be strings. - :param use_output: (Deprecated) If True, records will be fetched from this dataset in the legacy format, with the "expected" field renamed to "output". This option will be removed in a future version of Braintrust. - :param _internal_btql: (Internal) If specified, the dataset will be created with the given BTQL filters. - :param state: (Internal) The Braintrust state to use. If not specified, will use the global state. For advanced use only. - :returns: The dataset object. - """ - - state = state or _state - - def compute_metadata(): - state.login(org_name=org_name, api_key=api_key, app_url=app_url) - args = _populate_args( - {"project_name": project, "project_id": project_id, "org_id": state.org_id}, - dataset_name=name, - description=description, - metadata=metadata, - ) - response = state.app_conn().post_json("api/dataset/register", args) - resp_project = response["project"] - resp_dataset = response["dataset"] - return ProjectDatasetMetadata( - project=ObjectMetadata(id=resp_project["id"], name=resp_project["name"], full_info=resp_project), - dataset=ObjectMetadata(id=resp_dataset["id"], name=resp_dataset["name"], full_info=resp_dataset), - ) - - return Dataset( - lazy_metadata=LazyValue(compute_metadata, use_mutex=True), - version=version, - legacy=use_output, - _internal_btql=_internal_btql, - state=state, - ) - - -def _compute_logger_metadata(project_name: str | None = None, project_id: str | None = None): - login() - org_id = _state.org_id - if project_id is None: - response = _state.app_conn().post_json( - "api/project/register", - { - "project_name": project_name or GLOBAL_PROJECT, - "org_id": org_id, - }, - ) - resp_project = response["project"] - return OrgProjectMetadata( - org_id=org_id, - project=ObjectMetadata(id=resp_project["id"], name=resp_project["name"], full_info=resp_project), - ) - elif project_name is None: - response = _state.app_conn().get_json("api/project", {"id": project_id}) - return OrgProjectMetadata( - org_id=org_id, project=ObjectMetadata(id=project_id, name=response["name"], full_info=response) - ) - else: - return OrgProjectMetadata( - org_id=org_id, project=ObjectMetadata(id=project_id, name=project_name, full_info=dict()) - ) - - -def init_logger( - project: str | None = None, - project_id: str | None = None, - async_flush: bool = True, - app_url: str | None = None, - api_key: str | None = None, - org_name: str | None = None, - force_login: bool = False, - set_current: bool = True, - state: BraintrustState | None = None, -) -> "Logger": - """ - Create a new logger in a specified project. If the project does not exist, it will be created. - - :param project: The name of the project to log into. If unspecified, will default to the Global project. - :param project_id: The id of the project to log into. This takes precedence over project if specified. - :param async_flush: If true (the default), log events will be batched and sent asynchronously in a background thread. If false, log events will be sent synchronously. Set to false in serverless environments. - :param app_url: The URL of the Braintrust API. Defaults to https://www.braintrust.dev. - :param api_key: The API key to use. If the parameter is not specified, will try to use the `BRAINTRUST_API_KEY` environment variable. If no API - key is specified, will prompt the user to login. - :param org_name: (Optional) The name of a specific organization to connect to. This is useful if you belong to multiple. - :param force_login: Login again, even if you have already logged in (by default, the logger will not login if you are already logged in) - :param set_current: If true (the default), set the global current-experiment to the newly-created one. - :returns: The newly created Logger. - """ - - state = state or _state - compute_metadata_args = dict(project_name=project, project_id=project_id) - - link_args = { - "app_url": app_url, - "org_name": org_name, - "project_name": project, - "project_id": project_id, - } - - def compute_metadata(): - state.login(org_name=org_name, api_key=api_key, app_url=app_url, force_login=force_login) - return _compute_logger_metadata(**compute_metadata_args) - - # For loggers, enable queue size limit enforcement (bounded queue) - state.enforce_queue_size_limit(True) - - ret = Logger( - lazy_metadata=LazyValue(compute_metadata, use_mutex=True), - async_flush=async_flush, - compute_metadata_args=compute_metadata_args, - link_args=link_args, - state=state, - ) - if set_current: - if _state is None: - raise RuntimeError("_state is None in init_logger. This should never happen.") - _state._cv_logger.set(ret) - _state._local_logger = ret - return ret - - -def load_prompt( - project: str | None = None, - slug: str | None = None, - version: str | int | None = None, - project_id: str | None = None, - id: str | None = None, - defaults: Mapping[str, Any] | None = None, - no_trace: bool = False, - environment: str | None = None, - app_url: str | None = None, - api_key: str | None = None, - org_name: str | None = None, -) -> "Prompt": - """ - Loads a prompt from the specified project. - - :param project: The name of the project to load the prompt from. Must specify at least one of `project` or `project_id`. - :param slug: The slug of the prompt to load. - :param version: An optional version of the prompt (to read). If not specified, the latest version will be used. - :param project_id: The id of the project to load the prompt from. This takes precedence over `project` if specified. - :param id: The id of a specific prompt to load. If specified, this takes precedence over all other parameters (project, slug, version). - :param defaults: (Optional) A dictionary of default values to use when rendering the prompt. Prompt values will override these defaults. - :param no_trace: If true, do not include logging metadata for this prompt when build() is called. - :param environment: The environment to load the prompt from. Cannot be used together with version. - :param app_url: The URL of the Braintrust App. Defaults to https://www.braintrust.dev. - :param api_key: The API key to use. If the parameter is not specified, will try to use the `BRAINTRUST_API_KEY` environment variable. If no API - key is specified, will prompt the user to login. - :param org_name: (Optional) The name of a specific organization to connect to. This is useful if you belong to multiple. - :returns: The prompt object. - """ - if version is not None and environment is not None: - raise ValueError( - "Cannot specify both 'version' and 'environment' parameters. Please use only one (remove the other)." - ) - - if id: - # When loading by ID, we don't need project or slug - pass - elif not project and not project_id: - raise ValueError("Must specify at least one of project or project_id") - elif not slug: - raise ValueError("Must specify slug") - - def compute_metadata(): - try: - login(org_name=org_name, api_key=api_key, app_url=app_url) - if id: - # Load prompt by ID using the /v1/prompt/{id} endpoint - prompt_args = {} - if version is not None: - prompt_args["version"] = version - if environment is not None: - prompt_args["environment"] = environment - response = _state.api_conn().get_json(f"/v1/prompt/{id}", prompt_args) - # Wrap single prompt response in objects array to match list API format - if response is not None: - response = {"objects": [response]} - else: - args = _populate_args( - { - "project_name": project, - "project_id": project_id, - "slug": slug, - "version": version, - "environment": environment, - }, - ) - response = _state.api_conn().get_json("/v1/prompt", args) - except Exception as server_error: - # If environment or version was specified, don't fall back to cache - if environment is not None or version is not None: - raise ValueError(f"Prompt not found with specified parameters") from server_error - - eprint(f"Failed to load prompt, attempting to fall back to cache: {server_error}") - try: - if id: - return _state._prompt_cache.get(id=id) - else: - return _state._prompt_cache.get( - slug, - version=str(version) if version else "latest", - project_id=project_id, - project_name=project, - ) - except Exception as cache_error: - if id: - raise ValueError( - f"Prompt with id {id} not found (not found on server or in local cache): {cache_error}" - ) from server_error - else: - raise ValueError( - f"Prompt {slug} (version {version or 'latest'}) not found in {project or project_id} (not found on server or in local cache): {cache_error}" - ) from server_error - if response is None or "objects" not in response or len(response["objects"]) == 0: - if id: - raise ValueError(f"Prompt with id {id} not found.") - else: - raise ValueError(f"Prompt {slug} not found in project {project or project_id}.") - elif len(response["objects"]) > 1: - if id: - raise ValueError(f"Multiple prompts found with id {id}. This should never happen.") - else: - raise ValueError( - f"Multiple prompts found with slug {slug} in project {project or project_id}. This should never happen." - ) - resp_prompt = response["objects"][0] - prompt = PromptSchema.from_dict_deep(resp_prompt) - try: - if id: - _state._prompt_cache.set( - prompt, - id=id, - ) - elif slug: - _state._prompt_cache.set( - prompt, - slug=slug, - version=str(version) if version else "latest", - project_id=project_id, - project_name=project, - ) - except Exception as e: - eprint(f"Failed to store prompt in cache: {e}") - return prompt - - return Prompt( - lazy_metadata=LazyValue(compute_metadata, use_mutex=True), defaults=defaults or {}, no_trace=no_trace - ) - - -login_lock = threading.RLock() - - -def login( - app_url: str | None = None, - api_key: str | None = None, - org_name: str | None = None, - force_login: bool = False, -) -> None: - """ - Log into Braintrust. This will prompt you for your API token, which you can find at - https://www.braintrust.dev/app/token. This method is called automatically by `init()`. - - :param app_url: The URL of the Braintrust App. Defaults to https://www.braintrust.dev. - :param api_key: The API key to use. If the parameter is not specified, will try to use the `BRAINTRUST_API_KEY` environment variable. If no API - key is specified, will prompt the user to login. - :param org_name: (Optional) The name of a specific organization to connect to. This is useful if you belong to multiple. - :param force_login: Login again, even if you have already logged in (by default, this function will exit quickly if you have already logged in) - """ - # FIXME[matt] Remove thrown exceptions from this method. Perhaps a better pattern is (is_success, message) = login() - # to guarantee we don't throw into userland. - - global _state - - # Only permit one thread to login at a time - with login_lock: - _state.login(app_url=app_url, api_key=api_key, org_name=org_name, force_login=force_login) - - -def register_otel_flush(callback: Any) -> None: - """ - Register a callback to flush OTEL spans. This is called by the OTEL integration - when it initializes a span processor/exporter. - - When ensure_spans_flushed is called (e.g., before a BTQL query in scorers), - this callback will be invoked to ensure OTEL spans are flushed to the server. - - Also disables the span cache, since OTEL spans aren't in the local cache - and we need BTQL to see the complete span tree (both native + OTEL spans). - - :param callback: The async callback function to flush OTEL spans. - """ - global _state - _state.register_otel_flush(callback) - # Disable span cache since OTEL spans aren't in the local cache - _state.span_cache.disable() - - -def login_to_state( - app_url: str | None = None, - api_key: str | None = None, - org_name: str | None = None, -) -> BraintrustState: - app_url = _get_app_url(app_url) - - app_public_url = os.environ.get("BRAINTRUST_APP_PUBLIC_URL", app_url) - - if api_key is None: - api_key = os.environ.get("BRAINTRUST_API_KEY") - - org_name = _get_org_name(org_name) - - state = BraintrustState() - - state.app_url = app_url - state.app_public_url = app_public_url - state.org_name = org_name - - conn = None - if api_key == TEST_API_KEY: - # a small hook for pseudo-logins - test_org_info = [ - { - "id": "test-org-id", - "name": org_name or "test-org-name", - "api_url": "https://api.braintrust.ai", - "proxy_url": "https://proxy.braintrust.ai", - } - ] - _check_org_info(state, test_org_info, org_name) - state.login_token = TEST_API_KEY - state.logged_in = True - return state - elif api_key is not None: - app_conn = HTTPConnection(state.app_url, adapter=_http_adapter) - app_conn.set_token(api_key) - resp = app_conn.post("api/apikey/login") - if not resp.ok: - masked_api_key = mask_api_key(api_key) - raise ValueError(f"Invalid API key {masked_api_key}: [{resp.status_code}] {resp.text}") - info = resp.json() - - _check_org_info(state, info["org_info"], org_name) - - if not state.api_url: - if org_name: - raise ValueError( - f"Unable to log into organization '{org_name}'." - " Are you sure this credential is scoped to the organization?" - ) - else: - raise ValueError("Unable to log into any organization with the provided credential.") - - conn = state.api_conn() - conn.set_token(api_key) - - if not conn: - raise ValueError("Could not login to Braintrust. You may need to set BRAINTRUST_API_KEY in your environment.") - - # make_long_lived() allows the connection to retry if it breaks, which we're okay with after - # this point because we know the connection _can_ successfully ping. - conn.make_long_lived() - - # Same for the app conn, which we know is valid because we have - # successfully logged in. - state.app_conn().make_long_lived() - - # Set the same token in the API - state.app_conn().set_token(conn.token) - if state.proxy_url: - state.proxy_conn().set_token(conn.token) - state.proxy_conn().make_long_lived() - state.login_token = conn.token - state.logged_in = True - - # Replace the global logger's api_conn with this one. - state.login_replace_api_conn(conn) - - return state - - -def set_masking_function(masking_function: Callable[[Any], Any] | None) -> None: - """ - Set a global masking function that will be applied to all logged data before sending to Braintrust. - The masking function will be applied after records are merged but before they are sent to the backend. - - :param masking_function: A function that takes a JSON-serializable object and returns a masked version. - Set to None to disable masking. - """ - _state.set_masking_function(masking_function) - - -def log(**event: Any) -> str: - """ - Log a single event to the current experiment. The event will be batched and uploaded behind the scenes. - - :param **event: Data to be logged. See `Experiment.log` for full details. - :returns: The `id` of the logged event. - """ - eprint( - "braintrust.log is deprecated and will be removed in a future version of braintrust. Use `experiment.log` instead." - ) - e = current_experiment() - if not e: - raise Exception("Not initialized. Please call init() first") - return e.log(**event) - - -def summarize(summarize_scores: bool = True, comparison_experiment_id: str | None = None) -> "ExperimentSummary": - """ - Summarize the current experiment, including the scores (compared to the closest reference experiment) and metadata. - - :param summarize_scores: Whether to summarize the scores. If False, only the metadata will be returned. - :param comparison_experiment_id: The experiment to compare against. If None, the most recent experiment on the comparison_commit will be used. - :returns: `ExperimentSummary` - """ - eprint( - "braintrust.summarize is deprecated and will be removed in a future version of braintrust. Use `experiment.summarize` instead." - ) - e = current_experiment() - if e is None: - raise Exception("Not initialized. Please call init() first") - return e.summarize( - summarize_scores=summarize_scores, - comparison_experiment_id=comparison_experiment_id, - ) - - -def current_experiment() -> Optional["Experiment"]: - """Returns the currently-active experiment (set by `braintrust.init(...)`). Returns None if no current experiment has been set.""" - - return _state.current_experiment - - -def current_logger() -> Optional["Logger"]: - """Returns the currently-active logger (set by `braintrust.init_logger(...)`). Returns None if no current logger has been set.""" - - return _state._cv_logger.get() or _state._local_logger - - -def current_span() -> Span: - """Return the currently-active span for logging (set by running a span under a context manager). If there is no active span, returns a no-op span object, which supports the same interface as spans but does no logging. - - See `Span` for full details. - """ - - span_info = _state.context_manager.get_current_span_info() - if span_info and hasattr(span_info.span_object, "span_id"): - # This is a BT span - return span_info.span_object - return NOOP_SPAN - - -@contextlib.contextmanager -def parent_context(parent: str | None, state: BraintrustState | None = None): - """ - Context manager to temporarily set the parent context for spans. - - Args: - parent: The parent string to set during the context - state: Optional BraintrustState to use. If not provided, uses the global state. - - Example: - with parent_context('parent-id-123', state=state): - # Any spans created here will use 'parent-id-123' as their parent - span = start_span("my-span") - """ - state = state or _state - token = state.current_parent.set(parent) - try: - yield - finally: - state.current_parent.reset(token) - - -def get_span_parent_object( - parent: str | None = None, state: BraintrustState | None = None -) -> Union[SpanComponentsV4, "Logger", "Experiment", Span]: - """Mainly for internal use. Return the parent object for starting a span in a global context. - Applies precedence: current span > propagated parent string > experiment > logger.""" - - if state is None: - state = _state - - span = current_span() - if span != NOOP_SPAN: - return span - - parent = parent or state.current_parent.get() - if parent: - return SpanComponentsV4.from_str(parent) - - experiment = current_experiment() - if experiment: - return experiment - - logger = current_logger() - if logger: - return logger - - return NOOP_SPAN - - -def _try_log_input(span, f_sig, f_args, f_kwargs): - if f_sig: - input_data = f_sig.bind(*f_args, **f_kwargs).arguments - else: - input_data = dict(args=f_args, kwargs=f_kwargs) - span.log(input=input_data) - - -def _try_log_output(span, output): - span.log(output=output) - - -F = TypeVar("F", bound=Callable[..., Any]) - - -@overload -def traced(f: F) -> F: - """Decorator to trace the wrapped function when used without parentheses.""" - - -@overload -def traced(*span_args: Any, **span_kwargs: Any) -> Callable[[F], F]: - """Decorator to trace the wrapped function when used with arguments.""" - - -def traced(*span_args: Any, **span_kwargs: Any) -> Callable[[F], F]: - """Decorator to trace the wrapped function. Can either be applied bare (`@traced`) or by providing arguments (`@traced(*span_args, **span_kwargs)`), which will be forwarded to the created span. See `Span.start_span` for full details on the span arguments. - - It checks the following (in precedence order): - - * Currently-active span - * Currently-active experiment - * Currently-active logger - - and creates a span in the first one that is active. If none of these are active, it returns a no-op span object. - - The decorator will automatically log the input and output of the wrapped function to the corresponding fields of the created span. Pass the kwarg `notrace_io=True` to the decorator to prevent this. - - Unless a name is explicitly provided in `span_args` or `span_kwargs`, the name of the span will be the name of the decorated function. - """ - - trace_io = not span_kwargs.pop("notrace_io", False) - - def decorator(span_args, span_kwargs, f: F): - # We assume 'name' is the first positional argument in `start_span`. - if len(span_args) == 0 and span_kwargs.get("name") is None: - span_args += (f.__name__,) - - try: - f_sig = inspect.signature(f) - except: - f_sig = None - - if "span_attributes" not in span_kwargs: - span_kwargs["span_attributes"] = {} - if "type" not in span_kwargs["span_attributes"] and "type" not in span_kwargs: - span_kwargs["span_attributes"]["type"] = SpanTypeAttribute.FUNCTION - - @wraps(f) - def wrapper_sync(*f_args, **f_kwargs): - with start_span(*span_args, **span_kwargs) as span: - if trace_io: - _try_log_input(span, f_sig, f_args, f_kwargs) - ret = f(*f_args, **f_kwargs) - if trace_io: - _try_log_output(span, ret) - return ret - - @wraps(f) - async def wrapper_async(*f_args, **f_kwargs): - with start_span(*span_args, **span_kwargs) as span: - if trace_io: - _try_log_input(span, f_sig, f_args, f_kwargs) - ret = await f(*f_args, **f_kwargs) - if trace_io: - _try_log_output(span, ret) - return ret - - @wraps(f) - async def wrapper_async_gen(*f_args, **f_kwargs): - with start_span(*span_args, **span_kwargs) as span: - if trace_io: - _try_log_input(span, f_sig, f_args, f_kwargs) - - # Get max items from environment or default - max_items = int(os.environ.get("BRAINTRUST_MAX_GENERATOR_ITEMS", "1000")) - - if trace_io and max_items != 0: - # Collect output up to limit - collected = [] - truncated = False - - async_gen = f(*f_args, **f_kwargs) - try: - async for value in async_gen: - if max_items == -1 or (not truncated and len(collected) < max_items): - collected.append(value) - else: - truncated = True - collected = [] - _logger.warning( - f"Generator output exceeded limit of {max_items} items, output not logged. " - "Increase BRAINTRUST_MAX_GENERATOR_ITEMS or set to -1 to disable limit." - ) - yield value - - if not truncated: - _try_log_output(span, collected) - except Exception as e: - # Log partial output on error - if collected and not truncated: - _try_log_output(span, collected) - raise - else: - # Original behavior - no collection - async_gen = f(*f_args, **f_kwargs) - async for value in async_gen: - yield value - - @wraps(f) - def wrapper_sync_gen(*f_args, **f_kwargs): - with start_span(*span_args, **span_kwargs) as span: - if trace_io: - _try_log_input(span, f_sig, f_args, f_kwargs) - - # Get max items from environment or default - max_items = int(os.environ.get("BRAINTRUST_MAX_GENERATOR_ITEMS", "1000")) - - if trace_io and max_items != 0: - # Collect output up to limit - collected = [] - truncated = False - - sync_gen = f(*f_args, **f_kwargs) - try: - for value in sync_gen: - if max_items == -1 or (not truncated and len(collected) < max_items): - collected.append(value) - else: - truncated = True - collected = [] - _logger.warning( - f"Generator output exceeded limit of {max_items} items, output not logged. " - "Increase BRAINTRUST_MAX_GENERATOR_ITEMS or set to -1 to disable limit." - ) - yield value - - if not truncated: - _try_log_output(span, collected) - except Exception as e: - # Log partial output on error - if collected and not truncated: - _try_log_output(span, collected) - raise - else: - # Original behavior - no collection - sync_gen = f(*f_args, **f_kwargs) - for value in sync_gen: - yield value - - if inspect.isasyncgenfunction(f): - return cast(F, wrapper_async_gen) - elif inspect.isgeneratorfunction(f): - return cast(F, wrapper_sync_gen) - elif bt_iscoroutinefunction(f): - return cast(F, wrapper_async) - else: - return cast(F, wrapper_sync) - - # We determine if the decorator is invoked bare or with arguments by - # checking if the first positional argument to the decorator is a callable. - if len(span_args) == 1 and len(span_kwargs) == 0 and callable(span_args[0]): - return decorator(span_args[1:], span_kwargs, cast(F, span_args[0])) - else: - return cast(Callable[[F], F], partial(decorator, span_args, span_kwargs)) - - -def start_span( - name: str | None = None, - type: SpanTypeAttribute | None = None, - span_attributes: SpanAttributes | Mapping[str, Any] | None = None, - start_time: float | None = None, - set_current: bool | None = None, - parent: str | None = None, - propagated_event: dict[str, Any] | None = None, - state: BraintrustState | None = None, - **event: Any, -) -> Span: - """Lower-level alternative to `@traced` for starting a span at the toplevel. It creates a span under the first active object (using the same precedence order as `@traced`), or if `parent` is specified, under the specified parent row, or returns a no-op span object. - - We recommend running spans bound to a context manager (`with start_span`) to automatically mark them as current and ensure they are terminated. If you wish to start a span outside a context manager, be sure to terminate it with `span.end()`. - - See `Span.start_span` for full details. - """ - - if not state: - state = _state - - parent_obj = get_span_parent_object(parent, state) - - if isinstance(parent_obj, SpanComponentsV4): - if parent_obj.row_id and parent_obj.span_id and parent_obj.root_span_id: - parent_span_ids = ParentSpanIds(span_id=parent_obj.span_id, root_span_id=parent_obj.root_span_id) - else: - parent_span_ids = None - return SpanImpl( - parent_object_type=parent_obj.object_type, - parent_object_id=LazyValue(_span_components_to_object_id_lambda(parent_obj), use_mutex=False), - parent_compute_object_metadata_args=parent_obj.compute_object_metadata_args, - parent_span_ids=parent_span_ids, - name=name, - type=type, - span_attributes=span_attributes, - start_time=start_time, - set_current=set_current, - propagated_event=coalesce(propagated_event, parent_obj.propagated_event), - event=event, - state=state, - lookup_span_parent=False, - ) - else: - return parent_obj.start_span( - name=name, - type=type, - span_attributes=span_attributes, - start_time=start_time, - set_current=set_current, - parent=parent, - propagated_event=propagated_event, - **event, - ) - - -def flush(): - """Flush any pending rows to the server.""" - - _state.global_bg_logger().flush() - - -def _check_org_info(state, org_info, org_name): - if len(org_info) == 0: - raise ValueError("This user is not part of any organizations.") - - for orgs in org_info: - if org_name is None or orgs["name"] == org_name: - state.org_id = orgs["id"] - state.org_name = orgs["name"] - state.api_url = os.environ.get("BRAINTRUST_API_URL", orgs["api_url"]) - state.proxy_url = os.environ.get("BRAINTRUST_PROXY_URL", orgs["proxy_url"]) - state.git_metadata_settings = GitMetadataSettings(**(orgs.get("git_metadata") or {})) - break - - if state.org_id is None: - raise ValueError( - f"Organization {org_name} not found. Must be one of {', '.join([x['name'] for x in org_info])}" - ) - - -def _populate_args(d, **kwargs): - for k, v in kwargs.items(): - if v is not None: - d[k] = v - - return d - - -def _filter_none_args(args): - new_args = {} - for k, v in args.items(): - if v is not None: - new_args[k] = v - return new_args - - -def validate_tags(tags: Sequence[str]) -> None: - # Tag should be a list, set, or tuple, not a dict or string - if not isinstance(tags, (list, set, tuple)): - raise ValueError("tags must be a list, set, or tuple of strings") - - seen = set() - for tag in tags: - if not isinstance(tag, str): - raise ValueError("tags must be strings") - if tag in seen: - raise ValueError(f"duplicate tag: {tag}") - seen.add(tag) - - -def _extract_attachments(event: dict[str, Any], attachments: list["BaseAttachment"]) -> None: - """ - Helper function for uploading attachments. Recursively extracts `Attachment` - and `ExternalAttachment` values and replaces them with their associated - `AttachmentReference` objects. - - :param event: The event to filter. Will be modified in-place. - :param attachments: Flat array of extracted attachments (output parameter). - """ - - def _helper(v: Any) -> Any: - # Base case: Attachment or ExternalAttachment. - if isinstance(v, BaseAttachment): - attachments.append(v) - return v.reference # Attachment cannot be nested. - - # Recursive case: object. - if isinstance(v, dict): - for k, v2 in v.items(): - v[k] = _helper(v2) - return v - - # Recursive case: array. - if isinstance(v, list): - for i in range(len(v)): - v[i] = _helper(v[i]) - return v - - # Base case: non object. - return v # Nothing to explore recursively. - - for k, v in event.items(): - event[k] = _helper(v) - - -def _enrich_attachments(event: TMutableMapping) -> TMutableMapping: - """ - Recursively hydrates any `AttachmentReference` into `ReadonlyAttachment` by modifying the input in-place. - - :returns: The same event instance as the input. - """ - - def _helper(v: Any) -> Any: - if isinstance(v, dict): - # Base case: AttachmentReference. - if v.get("type") == "braintrust_attachment" or v.get("type") == "external_attachment": - return ReadonlyAttachment(cast(AttachmentReference, v)) - else: - # Recursive case: object. - for k, v2 in v.items(): - v[k] = _helper(v2) - return v - - # Recursive case: array. - if isinstance(v, list): - for i in range(len(v)): - v[i] = _helper(v[i]) - return v - - # Base case: non object. - return v # Nothing to explore recursively. - - for k, v in event.items(): - event[k] = _helper(v) - - return event - - -def _validate_and_sanitize_experiment_log_partial_args(event: Mapping[str, Any]) -> dict[str, Any]: - scores = event.get("scores") - if scores: - for name, score in scores.items(): - if not isinstance(name, str): - raise ValueError("score names must be strings") - - if score is None: - continue - - if isinstance(score, bool): - score = 1 if score else 0 - scores[name] = score - - if not isinstance(score, (int, float)): - raise ValueError("score values must be numbers") - if score < 0 or score > 1: - raise ValueError("score values must be between 0 and 1") - - metadata = event.get("metadata") - if metadata: - if not isinstance(metadata, dict): - raise ValueError("metadata must be a dictionary") - for key in metadata.keys(): - if not isinstance(key, str): - raise ValueError("metadata keys must be strings") - - metrics = event.get("metrics") - if metrics: - if not isinstance(metrics, dict): - raise ValueError("metrics must be a dictionary") - for key in metrics.keys(): - if not isinstance(key, str): - raise ValueError("metric keys must be strings") - - for value in metrics.values(): - if not isinstance(value, (int, float)): - raise ValueError("metric values must be numbers") - - tags = event.get("tags") - if tags: - validate_tags(tags) - - span_attributes = event.get("span_attributes") - if span_attributes: - if not isinstance(span_attributes, dict): - raise ValueError("span_attributes must be a dictionary") - for key in span_attributes.keys(): - if not isinstance(key, str): - raise ValueError("span_attributes keys must be strings") - - input = event.get("input") - inputs = event.get("inputs") - if input is not None and inputs is not None: - raise ValueError("Only one of input or inputs (deprecated) can be specified. Prefer input.") - if inputs is not None: - return dict(**{k: v for k, v in event.items() if k not in ["input", "inputs"]}, input=inputs) - else: - return {k: v for k, v in event.items()} - - -# Note that this only checks properties that are expected of a complete event. -# _validate_and_sanitize_experiment_log_partial_args should still be invoked -# (after handling special fields like 'id'). -def _validate_and_sanitize_experiment_log_full_args(event: Mapping[str, Any], has_dataset: bool) -> Mapping[str, Any]: - input = event.get("input") - inputs = event.get("inputs") - if (input is not None and inputs is not None) or (input is None and inputs is None): - raise ValueError("Exactly one of input or inputs (deprecated) must be specified. Prefer input.") - - if event.get("output") is None: - raise ValueError("output must be specified") - if event.get("scores") is None: - raise ValueError("scores must be specified") - elif not isinstance(event["scores"], dict): - raise ValueError("scores must be a dictionary of names with scores") - - return event - - -class ObjectIterator(Generic[T]): - def __init__(self, refetch_fn: Callable[[], Sequence[T]]): - self.refetch_fn = refetch_fn - self.idx = 0 - - def __iter__(self): - return self - - def __next__(self) -> T: - data = self.refetch_fn() - if self.idx >= len(data): - raise StopIteration - value = data[self.idx] - self.idx += 1 - - return value - - -DEFAULT_FETCH_BATCH_SIZE = 1000 -MAX_BTQL_ITERATIONS = 10000 - - -class ObjectFetcher(ABC, Generic[TMapping]): - def __init__( - self, - object_type: str, - pinned_version: None | int | str = None, - mutate_record: Callable[[TMapping], TMapping] | None = None, - _internal_btql: dict[str, Any] | None = None, - ): - self.object_type = object_type - - if pinned_version is not None: - try: - pv = int(pinned_version) - assert pv >= 0 - except (ValueError, AssertionError): - raise ValueError(f"version ({pinned_version}) must be a positive integer") - - self._pinned_version = str(pinned_version) if pinned_version is not None else None - self._mutate_record = mutate_record - - self._fetched_data: list[TMapping] | None = None - self._internal_btql = _internal_btql - - def fetch(self, batch_size: int | None = None) -> Iterator[TMapping]: - """ - Fetch all records. - - ```python - for record in object.fetch(): - print(record) - - # You can also iterate over the object directly. - for record in object: - print(record) - ``` - - :param batch_size: The number of records to fetch per request. Defaults to 1000. - :returns: An iterator over the records. - """ - return ObjectIterator(lambda: self._refetch(batch_size=batch_size)) - - def __iter__(self) -> Iterator[TMapping]: - return self.fetch() - - @property - def fetched_data(self): - eprint( - ".fetched_data is deprecated and will be removed in a future version of braintrust. Use .fetch() or the iterator instead" - ) - return self._refetch() - - @abstractmethod - def _get_state(self) -> BraintrustState: ... - - @property - @abstractmethod - def id(self) -> str: ... - - def _refetch(self, batch_size: int | None = None) -> list[TMapping]: - state = self._get_state() - limit = batch_size if batch_size is not None else DEFAULT_FETCH_BATCH_SIZE - if self._fetched_data is None: - cursor = None - data = None - iterations = 0 - while True: - resp = state.api_conn().post( - f"btql", - json={ - "query": { - "select": [{"op": "star"}], - "from": { - "op": "function", - "name": { - "op": "ident", - "name": [self.object_type], - }, - "args": [ - { - "op": "literal", - "value": self.id, - }, - ], - }, - "cursor": cursor, - "limit": limit, - **(self._internal_btql or {}), - }, - "use_columnstore": False, - "brainstore_realtime": True, - "query_source": f"py_sdk_object_fetcher_{self.object_type}", - **({"version": self._pinned_version} if self._pinned_version is not None else {}), - }, - headers={ - "Accept-Encoding": "gzip", - }, - ) - response_raise_for_status(resp) - resp_json = resp.json() - data = (data or []) + cast(list[TMapping], resp_json["data"]) - if not resp_json.get("cursor", None): - break - cursor = resp_json.get("cursor", None) - iterations += 1 - if iterations > MAX_BTQL_ITERATIONS: - raise RuntimeError("Too many BTQL iterations") - - if not isinstance(data, list): - raise ValueError(f"Expected a list in the response, got {type(data)}") - if self._mutate_record is not None: - self._fetched_data = [self._mutate_record(r) for r in data] - else: - self._fetched_data = data - - return self._fetched_data - - def _clear_cache(self) -> None: - self._fetched_data = None - - @property - def version(self) -> str: - if self._pinned_version is not None: - return self._pinned_version - else: - return max([str(record.get(TRANSACTION_ID_FIELD, "0")) for record in self._refetch()] or ["0"]) - - -class BaseAttachment(ABC): - @property - @abstractmethod - def reference(self) -> AttachmentReference: ... - - @property - @abstractmethod - def data(self) -> bytes: ... - - @abstractmethod - def upload(self) -> AttachmentStatus: ... - - @abstractmethod - def debug_info(self) -> Mapping[str, Any]: ... - - -class Attachment(BaseAttachment): - """ - Represents an attachment to be uploaded and the associated metadata. - - `Attachment` objects can be inserted anywhere in an event, allowing you to - log arbitrary file data. The SDK will asynchronously upload the file to - object storage and replace the `Attachment` object with an - `AttachmentReference`. - """ - - def __init__( - self, - *, - data: str | bytes | bytearray, - filename: str, - content_type: str, - ): - """ - Construct an attachment. - - :param data: A string representing the path of the file on disk, or a `bytes`/`bytearray` with the file's contents. The caller is responsible for ensuring the file on disk or mutable `bytearray` is not modified until upload is complete. - - :param filename: The desired name of the file in Braintrust after uploading. This parameter is for visualization purposes only and has no effect on attachment storage. - - :param content_type: The MIME type of the file. - """ - self._reference: AttachmentReference = { - "type": "braintrust_attachment", - "filename": filename, - "content_type": content_type, - "key": str(uuid.uuid4()), - } - self._data_debug_string = data if isinstance(data, str) else "" - - self._data = self._init_data(data) - self._uploader = self._init_uploader() - - @property - def reference(self) -> AttachmentReference: - """The object that replaces this `Attachment` at upload time.""" - return self._reference - - @property - def data(self) -> bytes: - """The attachment contents. This is a lazy value that will read the attachment contents from disk or memory on first access.""" - return self._data.get() - - def upload(self) -> AttachmentStatus: - """ - On first access, (1) reads the attachment from disk if needed, (2) authenticates with the data plane to request a signed URL, (3) uploads to object store, and (4) updates the attachment. - - :returns: The attachment status. - """ - return self._uploader.get() - - def debug_info(self) -> Mapping[str, Any]: - """ - A human-readable description for logging and debugging. - - :returns: The debug object. The return type is not stable and may change in a future release. - """ - return {"input_data": self._data_debug_string, "reference": self._reference} - - def _init_uploader(self) -> LazyValue[AttachmentStatus]: - def do_upload(api_conn: HTTPConnection, org_id: str) -> Mapping[str, Any]: - assert self._reference["type"] == "braintrust_attachment" - - request_params = { - "key": self._reference["key"], - "filename": self._reference["filename"], - "content_type": self._reference["content_type"], - "org_id": org_id, - } - - try: - metadata_response = api_conn.post("/attachment", json=request_params) - metadata_response.raise_for_status() - metadata = metadata_response.json() - except Exception as e: - raise RuntimeError(f"Failed to request signed URL from API server: {e}") from e - - try: - data = self._data.get() - except Exception as e: - raise OSError(f"Failed to read file: {e}") from e - - signed_url = metadata.get("signedUrl") - headers = metadata.get("headers") - if not isinstance(signed_url, str) or not isinstance(headers, dict): - raise RuntimeError(f"Invalid response from API server: {metadata}") - - add_azure_blob_headers(headers, signed_url) - - # TODO multipart upload. - try: - obj_conn = HTTPConnection(base_url="", adapter=_http_adapter) - obj_response = obj_conn.put(signed_url, headers=headers, data=data) - obj_response.raise_for_status() - except Exception as e: - raise RuntimeError(f"Failed to upload attachment to object store: {e}") from e - - return { - "signed_url": signed_url, - "metadata_response": metadata_response, - "object_store_response": obj_response, - } - - def error_wrapper() -> AttachmentStatus: - """Catches error messages and updates the attachment status.""" - status = AttachmentStatus(upload_status="uploading") - - login() - api_conn = _state.api_conn() - org_id = _state.org_id or "" - - try: - do_upload(api_conn, org_id) - status["upload_status"] = "done" - except Exception as e: - status["upload_status"] = "error" - status["error_message"] = str(e) - - request_params = { - "key": self._reference["key"], - "org_id": org_id, - "status": status, - } - try: - status_response = api_conn.post("/attachment/status", json=request_params) - status_response.raise_for_status() - except Exception as e: - raise RuntimeError(f"Couldn't log attachment status: {e}") from e - - return status - - return LazyValue(error_wrapper, use_mutex=True) - - def _init_data(self, data: str | bytes | bytearray) -> LazyValue[bytes]: - if isinstance(data, str): - self._ensure_file_readable(data) - - def read_file() -> bytes: - with open(data, "rb") as f: - return f.read() - - return LazyValue(read_file, use_mutex=True) - else: - return LazyValue(lambda: bytes(data), use_mutex=False) - - def _ensure_file_readable(self, data: str) -> None: - try: - os.stat(data) - except Exception as e: - _logger.warning(f"Failed to read file: {e}") - - -class JSONAttachment(Attachment): - """ - A convenience class for creating attachments from JSON-serializable objects. - - `JSONAttachment` objects can be inserted anywhere in an event, allowing you to - log JSON data as an attachment. The SDK will serialize the object to JSON and - upload it asynchronously to object storage. - """ - - def __init__( - self, - data: Any, - *, - filename: str = "data.json", - pretty: bool = False, - ): - """ - Construct a JSONAttachment from a JSON-serializable object. - - :param data: The JSON object to attach. Must be JSON-serializable. - :param filename: The filename for the attachment (defaults to "data.json") - :param pretty: Whether to pretty-print the JSON (defaults to False) - - Example: - ```python - large_transcript = [ - {"role": "user", "content": "..."}, - {"role": "assistant", "content": "..."}, - # ... many more messages - ] - - logger.log( - input={ - "type": "chat", - "transcript": JSONAttachment(large_transcript, filename="transcript.json") - } - ) - ``` - """ - json_string = json.dumps(data, indent=2 if pretty else None) - json_bytes = json_string.encode("utf-8") - - super().__init__( - data=json_bytes, - filename=filename, - content_type="application/json", - ) - - -class ExternalAttachment(BaseAttachment): - """ - Represents an attachment that resides in an external object store and the associated metadata. - - `ExternalAttachment` objects can be inserted anywhere in an event, similar to - `Attachment` objects, but they reference files that already exist in an external - object store rather than requiring upload. The SDK will replace the `ExternalAttachment` - object with an `AttachmentReference` during logging. - """ - - def __init__( - self, - *, - url: str, - filename: str, - content_type: str, - ): - """ - Construct an external attachment reference. - - :param url: A fully qualified URL to the object in the external object store. - - :param filename: The desired name of the file in Braintrust. This parameter is for visualization - purposes only and has no effect on attachment storage. - - :param content_type: The MIME type of the file. - """ - self._reference: AttachmentReference = { - "type": "external_attachment", - "filename": filename, - "content_type": content_type, - "url": url, - } - self._data = self._init_downloader() - - @property - def reference(self) -> AttachmentReference: - """The object that replaces this `Attachment` at upload time.""" - return self._reference - - @property - def data(self) -> bytes: - """The attachment contents. This is a lazy value that will read the attachment contents from the external object store on first access.""" - return self._data.get() - - def upload(self) -> AttachmentStatus: - """ - For ExternalAttachment, this is a no-op since the data already resides - in the external object store. It marks the attachment as already uploaded. - - :returns: The attachment status, which will always indicate success. - """ - return AttachmentStatus(upload_status="done") - - def debug_info(self) -> Mapping[str, Any]: - """ - A human-readable description for logging and debugging. - - :returns: The debug object. The return type is not stable and may change in a future release. - """ - return {"reference": self._reference} - - def _init_downloader(self) -> LazyValue[bytes]: - def download() -> bytes: - readonly = ReadonlyAttachment(self.reference) - return readonly.data - - return LazyValue(download, use_mutex=True) - - -class AttachmentMetadata(TypedDict): - downloadUrl: str - status: AttachmentStatus - - -class ReadonlyAttachment: - """ - A readonly alternative to `Attachment`, which can be used for fetching - already-uploaded Attachments. - """ - - def __init__(self, reference: AttachmentReference): - self.reference = reference - self._data = self._init_downloader() - - @property - def data(self) -> bytes: - """The attachment contents. This is a lazy value that will read the attachment contents from the object store on first access.""" - return self._data.get() - - def metadata(self) -> AttachmentMetadata: - """Fetch the attachment metadata, which includes a downloadUrl and a status. This will re-fetch the status each time in case it changes over time.""" - login() - api_conn = _state.api_conn() - org_id = _state.org_id or "" - - params = { - "filename": self.reference["filename"], - "content_type": self.reference["content_type"], - "org_id": org_id, - } - if self.reference["type"] == "braintrust_attachment": - params["key"] = self.reference["key"] - elif self.reference["type"] == "external_attachment": - params["url"] = self.reference["url"] - else: - raise RuntimeError(f"Unknown attachment type: {self.reference['type']}") - - response = api_conn.get("/attachment", params=params) - response.raise_for_status() - metadata = response.json() - try: - if not isinstance(metadata["downloadUrl"], str) or not isinstance(metadata["status"], dict): - raise RuntimeError() - except Exception: - raise RuntimeError(f"Invalid response from API server: {metadata}") - return metadata - - def status(self) -> AttachmentStatus: - """Fetch the attachment upload status. This will re-fetch the status each time in case it changes over time.""" - return self.metadata()["status"] - - def _init_downloader(self) -> LazyValue[bytes]: - def download() -> bytes: - metadata = self.metadata() - download_url = metadata["downloadUrl"] - status = metadata["status"] - try: - if status["upload_status"] != "done": - raise RuntimeError(f"""Expected attachment status "done", got \"{status["upload_status"]}\"""") - - obj_conn = HTTPConnection(base_url="", adapter=_http_adapter) - obj_response = obj_conn.get(download_url) - obj_response.raise_for_status() - except Exception as e: - raise RuntimeError(f"Couldn't download attachment: {e}") from e - - return obj_response.content - - return LazyValue(download, use_mutex=True) - - def __str__(self) -> str: - b64_content = base64.b64encode(self.data).decode("utf-8") - return f"data:{self.reference['content_type']};base64,{b64_content}" - - -def _log_feedback_impl( - parent_object_type: SpanObjectTypeV3, - parent_object_id: LazyValue[str], - id: str, - scores: Mapping[str, int | float] | None = None, - expected: Any | None = None, - tags: Sequence[str] | None = None, - comment: str | None = None, - metadata: Mapping[str, Any] | None = None, - source: Literal["external", "app", "api", None] = None, -): - if source is None: - source = "external" - elif source not in VALID_SOURCES: - raise ValueError(f"source must be one of {VALID_SOURCES}") - - if scores is None and expected is None and tags is None and comment is None: - raise ValueError("At least one of scores, expected, tags, or comment must be specified") - - update_event = _validate_and_sanitize_experiment_log_partial_args( - event=dict( - scores=scores, - metadata=metadata, - expected=expected, - tags=tags, - ) - ) - - # Although we validate metadata the normal way, we want to save it as audit metadata, - # not ordinary metadata - metadata = update_event.pop("metadata") - update_event = {k: v for k, v in update_event.items() if v is not None} - - update_event = bt_safe_deep_copy(update_event) - - def parent_ids(): - exporter = _get_exporter() - return exporter( - object_type=parent_object_type, - object_id=parent_object_id.get(), - ).object_id_fields() - - if len(update_event) > 0: - - def compute_update_record(): - return dict( - id=id, - **update_event, - **parent_ids(), - **{ - AUDIT_SOURCE_FIELD: source, - AUDIT_METADATA_FIELD: metadata, - IS_MERGE_FIELD: True, - }, - ) - - _state.global_bg_logger().log(LazyValue(compute_update_record, use_mutex=False)) - - if comment is not None: - # pylint: disable=function-redefined - def compute_comment_record(): - return dict( - id=str(uuid.uuid4()), - created=datetime.datetime.now(datetime.timezone.utc).isoformat(), - origin={ - # NOTE: We do not know (or care?) what the transaction id of the row that - # we're commenting on is here, so we omit it. - "id": id, - }, - comment={ - "text": comment, - }, - **parent_ids(), - **{AUDIT_SOURCE_FIELD: source, AUDIT_METADATA_FIELD: metadata}, - ) - - _state.global_bg_logger().log(LazyValue(compute_comment_record, use_mutex=False)) - - -def _update_span_impl( - parent_object_type: SpanObjectTypeV3, - parent_object_id: LazyValue[str], - id: str, - root_span_id: str | None, - span_id: str | None, - **event: Any, -): - if (root_span_id is None) != (span_id is None): - raise ValueError("both root_span_id and span_id must be set, or neither") - - update_payload = {**event} - if root_span_id is not None and span_id is not None: - update_payload["root_span_id"] = root_span_id - update_payload["span_id"] = span_id - - update_event = _validate_and_sanitize_experiment_log_partial_args( - event=update_payload, - ) - - update_event = bt_safe_deep_copy(update_event) - - def parent_ids(): - exporter = _get_exporter() - return exporter( - object_type=parent_object_type, - object_id=parent_object_id.get(), - ).object_id_fields() - - def compute_record(): - return dict( - id=id, - **update_event, - **parent_ids(), - **{ - IS_MERGE_FIELD: True, - }, - ) - - _state.global_bg_logger().log(LazyValue(compute_record, use_mutex=False)) - - -def update_span(exported: str, **event: Any) -> None: - """ - Update a span using the output of `span.export()`. It is important that you only resume updating - to a span once the original span has been fully written and flushed, since otherwise updates to - the span may conflict with the original span. - - :param exported: The output of `span.export()`. - :param **event: Data to update. See `Experiment.log` for a full list of valid fields. - """ - if event.get("id") is not None: - raise ValueError( - "Cannot specify id when updating a span with `update_span`. Use the output of `span.export()` instead." - ) - - components = SpanComponentsV4.from_str(exported) - if not components.row_id: - raise ValueError("Exported span must have a row_id") - - event_without_span_ids = {**event} - event_without_span_ids.pop("span_id", None) - event_without_span_ids.pop("root_span_id", None) - - return _update_span_impl( - parent_object_type=components.object_type, - parent_object_id=LazyValue(_span_components_to_object_id_lambda(components), use_mutex=False), - id=components.row_id, - root_span_id=components.root_span_id, - span_id=components.span_id, - **event_without_span_ids, - ) - - -@dataclasses.dataclass -class ParentSpanIds: - span_id: str - root_span_id: str - - -@dataclasses.dataclass -class SpanIds: - """The three IDs that define a span's position in the trace tree.""" - - span_id: str - root_span_id: str - span_parents: list[str] | None - - -def _resolve_span_ids( - span_id: str | None, - root_span_id: str | None, - parent_span_ids: ParentSpanIds | None, - lookup_span_parent: bool, - id_generator: "id_gen.IDGenerator", - context_manager: "context.ContextManager", -) -> SpanIds: - """Resolve all span IDs (span_id, root_span_id, span_parents) from explicit values, parent info, or context. - - Args: - span_id: Optional explicit span_id (from public API) - root_span_id: Optional explicit root_span_id (from public API) - parent_span_ids: Optional explicit parent span IDs (from parent string or parent span) - lookup_span_parent: Whether to look up parent from context manager if no explicit parent. - - True (default): start_span() inherits parent/root ids from the active span (if it exists) - - False: don't look up parent in context (e.g. logger.log() .. ) - id_generator: ID generator for creating new span/trace IDs - context_manager: Context manager for looking up parent spans - - Returns: - SpanIds with resolved span_id, root_span_id, and span_parents - 3. Otherwise โ†’ create new root span (generate or use explicit root_span_id) - """ - # Generate span_id if not provided - if span_id is None: - span_id = id_generator.get_span_id() - - # If we have explicit parent span ids, use them. - if parent_span_ids: - return SpanIds( - span_id=span_id, root_span_id=parent_span_ids.root_span_id, span_parents=[parent_span_ids.span_id] - ) - - # If we're using the context manager, get to see if there's an active parent - # span. - if lookup_span_parent: - parent_info = context_manager.get_parent_span_ids() - if parent_info: - return SpanIds( - span_id=span_id, root_span_id=parent_info.root_span_id, span_parents=parent_info.span_parents - ) - - # No parent - create new root span - if root_span_id: - resolved_root_span_id = root_span_id - elif id_generator.share_root_span_id(): - resolved_root_span_id = span_id # Backwards compat for UUID mode - else: - resolved_root_span_id = id_generator.get_trace_id() - - return SpanIds(span_id=span_id, root_span_id=resolved_root_span_id, span_parents=None) - - -def _span_components_to_object_id_lambda(components: SpanComponentsV4) -> Callable[[], str]: - if components.object_id: - captured_object_id = components.object_id - return lambda: captured_object_id - assert components.compute_object_metadata_args - if components.object_type == SpanObjectTypeV3.EXPERIMENT: - raise Exception("Impossible: compute_object_metadata_args not supported for experiments") - elif components.object_type == SpanObjectTypeV3.PROJECT_LOGS: - captured_compute_object_metadata_args = components.compute_object_metadata_args - return lambda: _compute_logger_metadata(**captured_compute_object_metadata_args).project.id - else: - raise Exception(f"Unknown object type: {components.object_type}") - - -def span_components_to_object_id(components: SpanComponentsV4) -> str: - """ - Utility function to resolve the object ID of a SpanComponentsV4 object. This - function may trigger a login to braintrust if the object ID is encoded - lazily. - """ - return _span_components_to_object_id_lambda(components)() - - -def permalink(slug: str, org_name: str | None = None, app_url: str | None = None) -> str: - """ - Format a permalink to the Braintrust application for viewing the span represented by the provided `slug`. - - Links can be generated at any time, but they will only become viewable after the span and its root have been flushed to the server and ingested. - - If you have a `Span` object, use `Span.permalink` instead. - - :param slug: The identifier generated from `Span.export`. - :param org_name: The org name to use. If not provided, the org name will be inferred from the global login state. - :param app_url: The app URL to use. If not provided, the app URL will be inferred from the global login state. - :returns: A permalink to the exported span. - """ - if not slug: - # Noop spans have an empty slug, so return a dummy permalink. - return NOOP_SPAN_PERMALINK - - try: - if not org_name: - login() - if not _state.org_name: - raise Exception("Must either provide org_name explicitly or be logged in to a specific org") - org_name = _state.org_name - - if not app_url: - login() - if not _state.app_url: - raise Exception("Must either provide app_url explicitly or be logged in") - app_url = _state.app_url - - components = SpanComponentsV4.from_str(slug) - - object_type = str(components.object_type) - object_id = span_components_to_object_id(components) - id = components.row_id - - if not id: - raise ValueError("Span slug does not refer to an individual row") - - url_params = urlencode({"object_type": object_type, "object_id": object_id, "id": id}) - return f"{app_url}/app/{org_name}/object?{url_params}" - except Exception as e: - if "BRAINTRUST_API_KEY" in str(e): - return _get_error_link("login-or-provide-org-name") - else: - return _get_error_link() - - -def _start_span_parent_args( - parent: str | None, - parent_object_type: SpanObjectTypeV3, - parent_object_id: LazyValue[str], - parent_compute_object_metadata_args: dict[str, Any] | None, - parent_span_ids: ParentSpanIds | None, - propagated_event: dict[str, Any] | None, -) -> dict[str, Any]: - if parent: - assert parent_span_ids is None, "Cannot specify both parent and parent_span_ids" - parent_components = SpanComponentsV4.from_str(parent) - assert ( - parent_object_type == parent_components.object_type - ), f"Mismatch between expected span parent object type {parent_object_type} and provided type {parent_components.object_type}" - - parent_components_object_id_lambda = _span_components_to_object_id_lambda(parent_components) - - def compute_parent_object_id(): - parent_components_object_id = parent_components_object_id_lambda() - assert ( - parent_object_id.get() == parent_components_object_id - ), f"Mismatch between expected span parent object id {parent_object_id.get()} and provided id {parent_components_object_id}" - return parent_object_id.get() - - arg_parent_object_id = LazyValue(compute_parent_object_id, use_mutex=False) - if parent_components.row_id: - arg_parent_span_ids = ParentSpanIds( - span_id=parent_components.span_id, root_span_id=parent_components.root_span_id - ) - else: - arg_parent_span_ids = None - arg_propagated_event = coalesce(propagated_event, parent_components.propagated_event) - else: - arg_parent_object_id = parent_object_id - arg_parent_span_ids = parent_span_ids - arg_propagated_event = propagated_event - - return dict( - parent_object_type=parent_object_type, - parent_object_id=arg_parent_object_id, - parent_compute_object_metadata_args=parent_compute_object_metadata_args, - parent_span_ids=arg_parent_span_ids, - propagated_event=arg_propagated_event, - ) - - -@dataclasses.dataclass -class ExperimentIdentifier: - id: str - name: str - - -class _ExperimentDatasetEvent(TypedDict): - """ - TODO: This could be unified with `framework._EvalCaseDict` like we do in the - TypeScript SDK, or generated from OpenAPI spec. For now, marking as internal - to exclude it from the docs. - """ - - id: str - _xact_id: str - input: Any | None - expected: Any | None - tags: Sequence[str] | None - - -class ExperimentDatasetIterator: - def __init__(self, iterator: Iterator[ExperimentEvent]): - self.iterator = iterator - - def __iter__(self): - return self - - def __next__(self) -> _ExperimentDatasetEvent: - while True: - value = next(self.iterator) - if value["root_span_id"] != value["span_id"]: - continue - - output, expected = value.get("output"), value.get("expected") - ret: _ExperimentDatasetEvent = { - "input": value.get("input"), - "expected": expected if expected is not None else output, - "tags": value.get("tags"), - "metadata": value.get("metadata"), - "id": value["id"], - "_xact_id": value["_xact_id"], - } - return ret - - -class Experiment(ObjectFetcher[ExperimentEvent], Exportable): - """ - An experiment is a collection of logged events, such as model inputs and outputs, which represent - a snapshot of your application at a particular point in time. An experiment is meant to capture more - than just the model you use, and includes the data you use to test, pre- and post- processing code, - comparison metrics (scores), and any other metadata you want to include. - - Experiments are associated with a project, and two experiments are meant to be easily comparable via - their `input`. You can change the attributes of the experiments in a project (e.g. scoring functions) - over time, simply by changing what you log. - - You should not create `Experiment` objects directly. Instead, use the `braintrust.init()` method. - """ - - def __init__( - self, - lazy_metadata: LazyValue[ProjectExperimentMetadata], - dataset: Optional["Dataset"] = None, - state: BraintrustState | None = None, - ): - self._lazy_metadata = lazy_metadata - self.dataset = dataset - self.last_start_time = time.time() - self._lazy_id = LazyValue(lambda: self.id, use_mutex=False) - self._called_start_span = False - self.state = state or _state - - ObjectFetcher.__init__( - self, - object_type="experiment", - pinned_version=None, - mutate_record=_enrich_attachments, - ) - - @property - def id(self) -> str: - return self._lazy_metadata.get().experiment.id - - @property - def name(self) -> str: - return self._lazy_metadata.get().experiment.name - - @property - def data(self) -> Mapping[str, Any]: - return self._lazy_metadata.get().experiment.full_info - - @property - def project(self) -> ObjectMetadata: - return self._lazy_metadata.get().project - - @property - def logging_state(self) -> BraintrustState: - return self.state - - @staticmethod - def _parent_object_type(): - return SpanObjectTypeV3.EXPERIMENT - - # Capture all metadata attributes which aren't covered by existing methods. - def __getattr__(self, name: str) -> Any: - return self._lazy_metadata.get().experiment.full_info[name] - - def _get_state(self) -> BraintrustState: - # Ensure the login state is populated by fetching the lazy_metadata. - self._lazy_metadata.get() - return self.state - - def log( - self, - input: Any | None = None, - output: Any | None = None, - expected: Any | None = None, - error: str | None = None, - tags: Sequence[str] | None = None, - scores: Mapping[str, int | float] | None = None, - metadata: Mapping[str, Any] | None = None, - metrics: Mapping[str, int | float] | None = None, - id: str | None = None, - dataset_record_id: str | None = None, - allow_concurrent_with_spans: bool = False, - ) -> str: - """ - Log a single event to the experiment. The event will be batched and uploaded behind the scenes. - - :param input: The arguments that uniquely define a test case (an arbitrary, JSON serializable object). Later on, Braintrust will use the `input` to know whether two test cases are the same between experiments, so they should not contain experiment-specific state. A simple rule of thumb is that if you run the same experiment twice, the `input` should be identical. - :param output: The output of your application, including post-processing (an arbitrary, JSON serializable object), that allows you to determine whether the result is correct or not. For example, in an app that generates SQL queries, the `output` should be the _result_ of the SQL query generated by the model, not the query itself, because there may be multiple valid queries that answer a single question. - :param expected: (Optional) the ground truth value (an arbitrary, JSON serializable object) that you'd compare to `output` to determine if your `output` value is correct or not. Braintrust currently does not compare `output` to `expected` for you, since there are so many different ways to do that correctly. Instead, these values are just used to help you navigate your experiments while digging into analyses. However, we may later use these values to re-score outputs or fine-tune your models. - :param error: (Optional) The error that occurred, if any. If you use tracing to run an experiment, errors are automatically logged when your code throws an exception. - :param scores: A dictionary of numeric values (between 0 and 1) to log. The scores should give you a variety of signals that help you determine how accurate the outputs are compared to what you expect and diagnose failures. For example, a summarization app might have one score that tells you how accurate the summary is, and another that measures the word similarity between the generated and grouth truth summary. The word similarity score could help you determine whether the summarization was covering similar concepts or not. You can use these scores to help you sort, filter, and compare experiments. - :param metadata: (Optional) a dictionary with additional data about the test example, model outputs, or just about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any JSON-serializable type, but its keys must be strings. - :param tags: (Optional) a list of strings that you can use to filter and group records later. - :param metrics: (Optional) a dictionary of metrics to log. The following keys are populated automatically: "start", "end". - :param id: (Optional) a unique identifier for the event. If you don't provide one, BrainTrust will generate one for you. - :param allow_concurrent_with_spans: (Optional) in rare cases where you need to log at the top level separately from using spans on the experiment elsewhere, set this to True. - :param dataset_record_id: (Deprecated) the id of the dataset record that this event is associated with. This field is required if and only if the experiment is associated with a dataset. This field is unused and will be removed in a future version. - :returns: The `id` of the logged event. - """ - if self._called_start_span and not allow_concurrent_with_spans: - raise Exception( - "Cannot run toplevel `log` method while using spans. To log to the span, call `experiment.start_span` and then log with `span.log`" - ) - - event = _validate_and_sanitize_experiment_log_full_args( - dict( - input=input, - output=output, - expected=expected, - error=error, - tags=tags, - scores=scores, - metadata=metadata, - metrics=metrics, - id=id, - ), - self.dataset is not None, - ) - span = self._start_span_impl(start_time=self.last_start_time, lookup_span_parent=False, **event) - self.last_start_time = span.end() - return span.id - - def log_feedback( - self, - id: str, - scores: Mapping[str, int | float] | None = None, - expected: Any | None = None, - tags: Sequence[str] | None = None, - comment: str | None = None, - metadata: Mapping[str, Any] | None = None, - source: Literal["external", "app", "api", None] = None, - ) -> None: - """ - Log feedback to an event in the experiment. Feedback is used to save feedback scores, set an expected value, or add a comment. - - :param id: The id of the event to log feedback for. This is the `id` returned by `log` or accessible as the `id` field of a span. - :param scores: (Optional) a dictionary of numeric values (between 0 and 1) to log. These scores will be merged into the existing scores for the event. - :param expected: (Optional) the ground truth value (an arbitrary, JSON serializable object) that you'd compare to `output` to determine if your `output` value is correct or not. - :param tags: (Optional) a list of strings that you can use to filter and group records later. - :param comment: (Optional) an optional comment string to log about the event. - :param metadata: (Optional) a dictionary with additional data about the feedback. If you have a `user_id`, you can log it here and access it in the Braintrust UI. Note, this metadata does not correspond to the main event itself, but rather the audit log attached to the event. - :param source: (Optional) the source of the feedback. Must be one of "external" (default), "app", or "api". - """ - return _log_feedback_impl( - parent_object_type=self._parent_object_type(), - parent_object_id=self._lazy_id, - id=id, - scores=scores, - expected=expected, - tags=tags, - comment=comment, - metadata=metadata, - source=source, - ) - - def start_span( - self, - name: str | None = None, - type: SpanTypeAttribute | None = None, - span_attributes: SpanAttributes | Mapping[str, Any] | None = None, - start_time: float | None = None, - set_current: bool | None = None, - parent: str | None = None, - propagated_event: dict[str, Any] | None = None, - **event: Any, - ) -> Span: - """Create a new toplevel span underneath the experiment. The name defaults to "root" and the span type to "eval". - - See `Span.start_span` for full details - """ - self._called_start_span = True - return self._start_span_impl( - name=name, - type=type, - span_attributes=span_attributes, - start_time=start_time, - set_current=set_current, - parent=parent, - propagated_event=propagated_event, - **event, - ) - - def update_span(self, id: str, **event: Any) -> None: - """ - Update a span in the experiment using its id. It is important that you only update a span once the original span has been fully written and flushed, - since otherwise updates to the span may conflict with the original span. - - :param id: The id of the span to update. - :param **event: Data to update. See `Experiment.log` for a full list of valid fields. - """ - root_span_id = event.pop("root_span_id", None) - span_id = event.pop("span_id", None) - return _update_span_impl( - parent_object_type=self._parent_object_type(), - parent_object_id=self._lazy_id, - id=id, - root_span_id=root_span_id, - span_id=span_id, - **event, - ) - - def fetch_base_experiment(self) -> ExperimentIdentifier | None: - state = self._get_state() - conn = state.app_conn() - - resp = conn.post("/api/base_experiment/get_id", json={"id": self.id}) - if resp.status_code == 400: - # No base experiment - return None - - response_raise_for_status(resp) - base = resp.json() - if base: - return ExperimentIdentifier(id=base["base_exp_id"], name=base["base_exp_name"]) - else: - return None - - def summarize( - self, summarize_scores: bool = True, comparison_experiment_id: str | None = None - ) -> "ExperimentSummary": - """ - Summarize the experiment, including the scores (compared to the closest reference experiment) and metadata. - - :param summarize_scores: Whether to summarize the scores. If False, only the metadata will be returned. - :param comparison_experiment_id: The experiment to compare against. If None, the most recent experiment on the origin's main branch will be used. - :returns: `ExperimentSummary` - """ - # Flush our events to the API, and to the data warehouse, to ensure that the link we print - # includes the new experiment. - self.flush() - - state = self._get_state() - project_url = f"{state.app_public_url}/app/{encode_uri_component(state.org_name)}/p/{encode_uri_component(self.project.name)}" - experiment_url = f"{project_url}/experiments/{encode_uri_component(self.name)}" - - score_summary = {} - metric_summary = {} - comparison_experiment_name = None - if summarize_scores: - # Get the comparison experiment - if comparison_experiment_id is None: - base_experiment = self.fetch_base_experiment() - if base_experiment: - comparison_experiment_id = base_experiment.id - comparison_experiment_name = base_experiment.name - - try: - summary_items = state.api_conn().get_json( - "experiment-comparison2", - args={ - "experiment_id": self.id, - "base_experiment_id": comparison_experiment_id, - }, - ) - except Exception as e: - _logger.warning( - f"Failed to fetch experiment scores and metrics: {e}\n\nView complete results in Braintrust or run experiment.summarize() again." - ) - summary_items = {} - - score_items = summary_items.get("scores", {}) - metric_items = summary_items.get("metrics", {}) - - longest_score_name = max(len(k) for k in score_items.keys()) if score_items else 0 - score_summary = { - k: ScoreSummary(_longest_score_name=longest_score_name, **v) for (k, v) in score_items.items() - } - - longest_metric_name = max(len(k) for k in metric_items.keys()) if metric_items else 0 - metric_summary = { - k: MetricSummary(_longest_metric_name=longest_metric_name, **v) for (k, v) in metric_items.items() - } - - return ExperimentSummary( - project_name=self.project.name, - project_id=self.project.id, - experiment_id=self.id, - experiment_name=self.name, - project_url=project_url, - experiment_url=experiment_url, - comparison_experiment_name=comparison_experiment_name, - scores=score_summary, - metrics=metric_summary, - ) - - def export(self) -> str: - exporter = _get_exporter() - return exporter(object_type=self._parent_object_type(), object_id=self.id).to_str() - - def close(self) -> str: - """This function is deprecated. You can simply remove it from your code.""" - - eprint( - "close is deprecated and will be removed in a future version of braintrust. It is now a no-op and can be removed" - ) - return self.id - - def flush(self) -> None: - """Flush any pending rows to the server.""" - - self.state.global_bg_logger().flush() - - def _start_span_impl( - self, - name: str | None = None, - type: SpanTypeAttribute | None = None, - span_attributes: SpanAttributes | Mapping[str, Any] | None = None, - start_time: float | None = None, - set_current: bool | None = None, - parent: str | None = None, - propagated_event: dict[str, Any] | None = None, - lookup_span_parent: bool = True, - **event: Any, - ) -> Span: - parent_args = _start_span_parent_args( - parent=parent, - parent_object_type=self._parent_object_type(), - parent_object_id=self._lazy_id, - parent_compute_object_metadata_args=None, - parent_span_ids=None, - propagated_event=propagated_event, - ) - return SpanImpl( - **parent_args, - name=name, - type=type, - lookup_span_parent=lookup_span_parent, - default_root_type=SpanTypeAttribute.EVAL, - span_attributes=span_attributes, - start_time=start_time, - set_current=set_current, - event=event, - state=self.state, - ) - - def __enter__(self) -> "Experiment": - return self - - def __exit__( - self, - exc_type: type[BaseException] | None, - exc_value: BaseException | None, - traceback: TracebackType | None, - ) -> None: - del exc_type, exc_value, traceback - - -class ReadonlyExperiment(ObjectFetcher[ExperimentEvent]): - """ - A read-only view of an experiment, initialized by passing `open=True` to `init()`. - """ - - def __init__( - self, - lazy_metadata: LazyValue[ProjectExperimentMetadata], - state: BraintrustState | None = None, - ): - self._lazy_metadata = lazy_metadata - self.state = state or _state - - ObjectFetcher.__init__( - self, - object_type="experiment", - pinned_version=None, - mutate_record=_enrich_attachments, - ) - - @property - def id(self) -> str: - return self._lazy_metadata.get().experiment.id - - @property - def logging_state(self) -> BraintrustState: - return self.state - - def _get_state(self) -> BraintrustState: - # Ensure the login state is populated by fetching the lazy_metadata. - self._lazy_metadata.get() - return self.state - - def as_dataset(self, batch_size: int | None = None) -> Iterator[_ExperimentDatasetEvent]: - """ - Return the experiment's data as a dataset iterator. - - :param batch_size: The number of records to fetch per request. Defaults to 1000. - :returns: An iterator over the experiment data as dataset records. - """ - return ExperimentDatasetIterator(self.fetch(batch_size=batch_size)) - - -_EXEC_COUNTER_LOCK = threading.Lock() -_EXEC_COUNTER = 0 - - -class SpanImpl(Span): - """Primary implementation of the `Span` interface. See the `Span` interface for full details on each method. - - We suggest using one of the various `start_span` methods, instead of creating Spans directly. See `Span.start_span` for full details. - """ - - can_set_current: bool - - def __init__( - self, - parent_object_type: SpanObjectTypeV3, - parent_object_id: LazyValue[str], - parent_compute_object_metadata_args: dict[str, Any] | None, - parent_span_ids: ParentSpanIds | None, - name: str | None = None, - type: SpanTypeAttribute | None = None, - default_root_type: SpanTypeAttribute | None = None, - span_attributes: SpanAttributes | Mapping[str, Any] | None = None, - start_time: float | None = None, - set_current: bool | None = None, - event: dict[str, Any] | None = None, - propagated_event: dict[str, Any] | None = None, - span_id: str | None = None, - root_span_id: str | None = None, - state: BraintrustState | None = None, - lookup_span_parent: bool = True, - ): - if span_attributes is None: - span_attributes = SpanAttributes() - if event is None: - event = {} - if type is None and not parent_span_ids: - type = default_root_type - - self.state = state or _state - - self.can_set_current = cast(bool, coalesce(set_current, True)) - self._logged_end_time: float | None = None - - # Context token for proper cleanup - used by both OTEL and Braintrust context managers - # This is set by the context manager when the span becomes active - self._context_token: Any | None = None - - self.parent_object_type = parent_object_type - self.parent_object_id = parent_object_id - self.parent_compute_object_metadata_args = parent_compute_object_metadata_args - - # Merge propagated_event into event. The propagated_event data will get - # propagated-and-merged into every subspan. - self.propagated_event = propagated_event - if self.propagated_event: - merge_dicts(event, self.propagated_event) - - caller_location = get_caller_location() - if name is None: - if not parent_span_ids: - name = "root" - elif caller_location: - filename = os.path.basename(caller_location["caller_filename"]) - name = ":".join( - [caller_location["caller_functionname"]] - + ([f"{filename}:{caller_location['caller_lineno']}"] if filename else []) - ) - else: - name = "subspan" - - self._name = name - - # `internal_data` contains fields that are not part of the - # "user-sanitized" set of fields which we want to log in just one of the - # span rows. - global _EXEC_COUNTER - with _EXEC_COUNTER_LOCK: - _EXEC_COUNTER += 1 - exec_counter = _EXEC_COUNTER - - internal_data: dict[str, Any] = dict( - metrics=dict( - start=start_time or time.time(), - ), - # Set type first, in case they override it in `span_attributes`. - span_attributes=dict(**{"type": type, "name": name, **span_attributes}, exec_counter=exec_counter), - created=datetime.datetime.now(datetime.timezone.utc).isoformat(), - ) - if caller_location: - internal_data["context"] = caller_location - - # TODO: can be simplified after `event` is typed. - id = event.pop("id", None) - if id is None or not isinstance(id, str): - id = str(uuid.uuid4()) - self._id = id - - # Resolve all span IDs (span_id, root_span_id, span_parents) - span_ids = _resolve_span_ids( - span_id=span_id, - root_span_id=root_span_id, - parent_span_ids=parent_span_ids, - lookup_span_parent=lookup_span_parent, - id_generator=self.state.id_generator, - context_manager=self.state.context_manager, - ) - self.span_id = span_ids.span_id - self.root_span_id = span_ids.root_span_id - self.span_parents = span_ids.span_parents - - # The first log is a replacement, but subsequent logs to the same span - # object will be merges. - self._is_merge = False - self.log_internal(event=event, internal_data=internal_data) - self._is_merge = True - - @property - def id(self) -> str: - return self._id - - @property - def name(self) -> str: - return self._name - - def set_attributes( - self, - name: str | None = None, - type: SpanTypeAttribute | None = None, - span_attributes: Mapping[str, Any] | None = None, - ) -> None: - if name is not None: - self._name = name - self.log_internal( - internal_data={ - "span_attributes": _strip_nones( - { - "name": name, - "type": type, - **(span_attributes or {}), - }, - deep=False, - ), - } - ) - - def log(self, **event: Any) -> None: - return self.log_internal(event=event, internal_data=None) - - def log_internal(self, event: dict[str, Any] | None = None, internal_data: dict[str, Any] | None = None) -> None: - serializable_partial_record, lazy_partial_record = split_logging_data(event, internal_data) - - # We both check for serializability and round-trip `partial_record` - # through JSON in order to create a "deep copy". This has the benefit of - # cutting out any reference to user objects when the object is logged - # asynchronously, so that in case the objects are modified, the logging - # is unaffected. - partial_record: dict[str, Any] = dict( - id=self.id, - span_id=self.span_id, - root_span_id=self.root_span_id, - span_parents=self.span_parents, - **serializable_partial_record, - **{IS_MERGE_FIELD: self._is_merge}, - ) - - serializable_partial_record = bt_safe_deep_copy(partial_record) - if serializable_partial_record.get("metrics", {}).get("end") is not None: - self._logged_end_time = serializable_partial_record["metrics"]["end"] - - # Write to local span cache for scorer access - # Only cache experiment spans - regular logs don't need caching - if self.parent_object_type == SpanObjectTypeV3.EXPERIMENT: - from braintrust.span_cache import CachedSpan - - cached_span = CachedSpan( - span_id=self.span_id, - input=serializable_partial_record.get("input"), - output=serializable_partial_record.get("output"), - metadata=serializable_partial_record.get("metadata"), - span_parents=self.span_parents, - span_attributes=serializable_partial_record.get("span_attributes"), - ) - self.state.span_cache.queue_write(self.root_span_id, self.span_id, cached_span) - - def compute_record() -> dict[str, Any]: - exporter = _get_exporter() - return dict( - **serializable_partial_record, - **{k: v.get() for k, v in lazy_partial_record.items()}, - **exporter( - object_type=self.parent_object_type, - object_id=self.parent_object_id.get(), - ).object_id_fields(), - ) - - self.state.global_bg_logger().log(LazyValue(compute_record, use_mutex=False)) - - def log_feedback(self, **event: Any) -> None: - return _log_feedback_impl( - parent_object_type=self.parent_object_type, - parent_object_id=self.parent_object_id, - id=self.id, - **event, - ) - - def start_span( - self, - name: str | None = None, - type: SpanTypeAttribute | None = None, - span_attributes: SpanAttributes | Mapping[str, Any] | None = None, - start_time: float | None = None, - set_current: bool | None = None, - parent: str | None = None, - propagated_event: dict[str, Any] | None = None, - **event: Any, - ) -> Span: - if parent: - parent_span_ids = None - else: - parent_span_ids = ParentSpanIds(span_id=self.span_id, root_span_id=self.root_span_id) - - # Always set lookup_span_parent=False because: - # - If parent is provided, _start_span_parent_args will extract parent info from it - # - If parent is not provided, we explicitly set parent_span_ids from self - # Either way, we don't want to look up parent from context manager - lookup_span_parent = False - return SpanImpl( - **_start_span_parent_args( - parent=parent, - parent_object_type=self.parent_object_type, - parent_object_id=self.parent_object_id, - parent_compute_object_metadata_args=self.parent_compute_object_metadata_args, - parent_span_ids=parent_span_ids, - propagated_event=coalesce(propagated_event, self.propagated_event), - ), - name=name, - type=type, - span_attributes=span_attributes, - start_time=start_time, - set_current=set_current, - event=event, - lookup_span_parent=lookup_span_parent, - state=self.state, - ) - - def end(self, end_time: float | None = None) -> float: - internal_data = {} - if not self._logged_end_time: - end_time = end_time or time.time() - internal_data = dict(metrics=dict(end=end_time)) - else: - end_time = self._logged_end_time - self.log_internal(internal_data=internal_data) - return end_time - - def export(self) -> str: - if self.parent_compute_object_metadata_args and not self.parent_object_id.has_succeeded: - object_id = None - compute_object_metadata_args = self.parent_compute_object_metadata_args - else: - object_id = self.parent_object_id.get() - compute_object_metadata_args = None - - # Choose SpanComponents version based on BRAINTRUST_OTEL_COMPAT env var - use_v4 = os.getenv("BRAINTRUST_OTEL_COMPAT", "false").lower() == "true" - span_components_class = SpanComponentsV4 if use_v4 else SpanComponentsV3 - - # Disable span cache since remote function spans won't be in the local cache - self.state.span_cache.disable() - - return span_components_class( - object_type=self.parent_object_type, - object_id=object_id, - compute_object_metadata_args=compute_object_metadata_args, - row_id=self.id, - span_id=self.span_id, - root_span_id=self.root_span_id, - propagated_event=self.propagated_event, - ).to_str() - - def link(self) -> str: - parent_type, info = self._get_parent_info() - if parent_type == SpanObjectTypeV3.PROJECT_LOGS: - cur_logger = self.state._cv_logger.get() or self.state._local_logger - if not cur_logger: - return NOOP_SPAN_PERMALINK - base_url = cur_logger._get_link_base_url() - if not base_url: - return _get_error_link("login-or-provide-org-name") - - project_id = info.get("id") - project_name = info.get("name") - if project_id: - return f"{base_url}/object?object_type=project_logs&object_id={project_id}&id={self._id}" - elif project_name: - return f"{base_url}/p/{project_name}/logs?oid={self._id}" - else: - return _get_error_link("no-project-id-or-name") - elif parent_type == SpanObjectTypeV3.EXPERIMENT: - app_url = self.state.app_url or _get_app_url() - org_name = self.state.org_name or _get_org_name() - if not app_url or not org_name: - return _get_error_link("provide-app-url-or-org-name") - base_url = f"{app_url}/app/{org_name}" - - exp_id = info.get("id") - if exp_id: - return f"{base_url}/object?object_type=experiment&object_id={exp_id}&id={self._id}" - else: - return _get_error_link("resolve-experiment-id") - - return NOOP_SPAN_PERMALINK - - def permalink(self) -> str: - try: - return permalink(self.export()) - except Exception as e: - if "BRAINTRUST_API_KEY" in str(e): - return _get_error_link("login-or-provide-org-name") - else: - return _get_error_link("") - - def close(self, end_time=None) -> float: - return self.end(end_time) - - def flush(self) -> None: - """Flush any pending rows to the server.""" - - self.state.global_bg_logger().flush() - - def set_current(self): - if self.can_set_current: - # Get token from context manager and store it - self._context_token = self.state.context_manager.set_current_span(self) - - def unset_current(self): - """ - Unset current span context. - - Note: self._context_token may be None if set_current() failed. - This is safe - context_manager.unset_current_span() handles None. - """ - if self.can_set_current: - try: - self.state.context_manager.unset_current_span(self._context_token) - except Exception as e: - logging.debug(f"Failed to unset current span: {e}") - finally: - # Always clear the token reference - self._context_token = None - - def __enter__(self) -> Span: - self.set_current() - return self - - def __exit__(self, exc_type, exc_value, tb) -> None: - try: - if exc_type is not None: - self.log_internal(dict(error=stringify_exception(exc_type, exc_value, tb))) - finally: - try: - self.unset_current() - except Exception as e: - logging.debug(f"Failed to unset current in __exit__: {e}") - - try: - self.end() - except Exception as e: - logging.warning(f"Error ending span: {e}") - - def _get_parent_info(self): - if self.parent_object_type == SpanObjectTypeV3.PROJECT_LOGS: - is_resolved, id1 = self.parent_object_id.get_sync() - meta = self.parent_compute_object_metadata_args or {} - id2 = meta.get("project_id") - name = meta.get("project_name") - _id = id1 if is_resolved else id2 - return self.parent_object_type, {"name": name, "id": _id} - elif self.parent_object_type == SpanObjectTypeV3.EXPERIMENT: - is_resolved, experiment_id = self.parent_object_id.get_sync() - if is_resolved: - return self.parent_object_type, {"id": experiment_id} - # For experiments, we resolve the ID by calling get(). We can't pass - # along the "lazy compuete metadata args" because we can't tell OTel to do that. - # We must pass along an explicit resolved parent. - try: - experiment_id = self.parent_object_id.get() - return self.parent_object_type, {"id": experiment_id} - except Exception: - return self.parent_object_type, {} - else: - return None, {} - - def _get_otel_parent(self): - parent_type, info = self._get_parent_info() - if parent_type == SpanObjectTypeV3.PROJECT_LOGS: - _id = info.get("id") - _name = info.get("name") - if _id: - return f"project_id:{_id}" - elif _name: - return f"project_name:{_name}" - if parent_type == SpanObjectTypeV3.EXPERIMENT: - _id = info.get("id") - if _id: - return f"experiment_id:{_id}" - return None - - -def log_exc_info_to_span( - span: Span, exc_type: type[BaseException], exc_value: BaseException, tb: TracebackType | None -) -> None: - error = stringify_exception(exc_type, exc_value, tb) - span.log(error=error) - - -def stringify_exception(exc_type: type[BaseException], exc_value: BaseException, tb: TracebackType | None) -> str: - return "".join( - traceback.format_exception_only(exc_type, exc_value) - + ["\nTraceback (most recent call last):\n"] - + traceback.format_tb(tb) - ) - - -def _strip_nones(d: T, deep: bool) -> T: - if not isinstance(d, dict): - return d - return {k: (_strip_nones(v, deep) if deep else v) for (k, v) in d.items() if v is not None} # type: ignore - - -def split_logging_data( - event: dict[str, Any] | None, internal_data: dict[str, Any] | None -) -> tuple[dict[str, Any], dict[str, Any]]: - # There should be no overlap between the dictionaries being merged, - # except for `sanitized` and `internal_data`, where the former overrides - # the latter. - sanitized = _validate_and_sanitize_experiment_log_partial_args(event or {}) - sanitized_and_internal_data = _strip_nones(internal_data or {}, deep=True) - merge_dicts(sanitized_and_internal_data, _strip_nones(sanitized, deep=False)) - - serializable_partial_record: dict[str, Any] = {} - lazy_partial_record: dict[str, Any] = {} - for k, v in sanitized_and_internal_data.items(): - if isinstance(v, BraintrustStream): - # Python has weird semantics with loop variables and lambda functions, so we - # capture `v` by plugging it through a closure that itself returns the LazyValue - def make_final_value_callback(v): - return LazyValue(lambda: v.copy().final_value(), use_mutex=False) - - lazy_partial_record[k] = make_final_value_callback(v) - else: - serializable_partial_record[k] = v - - return serializable_partial_record, lazy_partial_record - - -class Dataset(ObjectFetcher[DatasetEvent]): - """ - A dataset is a collection of records, such as model inputs and outputs, which represent - data you can use to evaluate and fine-tune models. You can log production data to datasets, - curate them with interesting examples, edit/delete records, and run evaluations against them. - - You should not create `Dataset` objects directly. Instead, use the `braintrust.init_dataset()` method. - """ - - def __init__( - self, - lazy_metadata: LazyValue[ProjectDatasetMetadata], - version: None | int | str = None, - legacy: bool = DEFAULT_IS_LEGACY_DATASET, - _internal_btql: dict[str, Any] | None = None, - state: BraintrustState | None = None, - ): - if legacy: - eprint( - f"""Records will be fetched from this dataset in the legacy format, with the "expected" field renamed to "output". Please update your code to use "expected", and use `braintrust.init_dataset()` with `use_output=False`, which will become the default in a future version of Braintrust.""" - ) - - def mutate_record(r: DatasetEvent) -> DatasetEvent: - _enrich_attachments(cast(dict[str, Any], r)) - return ensure_dataset_record(r, legacy) - - self._lazy_metadata = lazy_metadata - self.new_records = 0 - - ObjectFetcher.__init__( - self, - object_type="dataset", - pinned_version=version, - mutate_record=mutate_record, - _internal_btql=_internal_btql, - ) - - self.state = state or _state - - @property - def id(self) -> str: - return self._lazy_metadata.get().dataset.id - - @property - def name(self) -> str: - return self._lazy_metadata.get().dataset.name - - @property - def data(self): - return self._lazy_metadata.get().dataset.full_info - - @property - def project(self): - return self._lazy_metadata.get().project - - @property - def logging_state(self) -> BraintrustState: - return self.state - - # Capture all metadata attributes which aren't covered by existing methods. - def __getattr__(self, name: str) -> Any: - return self._lazy_metadata.get().dataset.full_info[name] - - def _get_state(self) -> BraintrustState: - # Ensure the login state is populated by fetching the lazy_metadata. - self._lazy_metadata.get() - return self.state - - def _validate_event( - self, - metadata: dict[str, Any] | None = None, - expected: Any | None = None, - output: Any | None = None, - tags: Sequence[str] | None = None, - ): - if metadata is not None: - if not isinstance(metadata, dict): - raise ValueError("metadata must be a dictionary") - for key in metadata.keys(): - if not isinstance(key, str): - raise ValueError("metadata keys must be strings") - - if expected is not None and output is not None: - raise ValueError("Only one of expected or output (deprecated) can be specified. Prefer expected.") - - if tags: - validate_tags(tags) - - def _create_args( - self, id, input=None, expected=None, metadata=None, tags=None, output=None, is_merge=False - ) -> LazyValue[dict[str, Any]]: - expected_value = expected if expected is not None else output - - args = _populate_args( - { - "id": id, - "input": input, - "expected": expected_value, - "tags": tags, - "created": None if is_merge else datetime.datetime.now(datetime.timezone.utc).isoformat(), - }, - metadata=metadata, - ) - - if is_merge: - args[IS_MERGE_FIELD] = True - args = _filter_none_args(args) # If merging, then remove None values to prevent null value writes - - args = bt_safe_deep_copy(args) - - def compute_args() -> dict[str, Any]: - return dict( - **args, - dataset_id=self.id, - ) - - return LazyValue(compute_args, use_mutex=False) - - def insert( - self, - input: Any | None = None, - expected: Any | None = None, - tags: Sequence[str] | None = None, - metadata: dict[str, Any] | None = None, - id: str | None = None, - output: Any | None = None, - ) -> str: - """ - Insert a single record to the dataset. The record will be batched and uploaded behind the scenes. If you pass in an `id`, - and a record with that `id` already exists, it will be overwritten (upsert). - - :param input: The argument that uniquely define an input case (an arbitrary, JSON serializable object). - :param expected: The output of your application, including post-processing (an arbitrary, JSON serializable object). - :param tags: (Optional) a list of strings that you can use to filter and group records later. - :param metadata: (Optional) a dictionary with additional data about the test example, model outputs, or just - about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the - `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any - JSON-serializable type, but its keys must be strings. - :param id: (Optional) a unique identifier for the event. If you don't provide one, Braintrust will generate one for you. - :param output: (Deprecated) The output of your application. Use `expected` instead. - :returns: The `id` of the logged record. - """ - self._validate_event(metadata=metadata, expected=expected, output=output, tags=tags) - - row_id = id or str(uuid.uuid4()) - - args = self._create_args( - id=row_id, - input=input, - expected=expected, - metadata=metadata, - tags=tags, - output=output, - is_merge=False, - ) - - self._clear_cache() # We may be able to optimize this - self.new_records += 1 - self.state.global_bg_logger().log(args) - return row_id - - def update( - self, - id: str, - input: Any | None = None, - expected: Any | None = None, - tags: Sequence[str] | None = None, - metadata: dict[str, Any] | None = None, - ) -> str: - """ - Update fields of a single record in the dataset. The updated fields will be batched and uploaded behind the scenes. - You must pass in an `id` of the record to update. Only the fields provided will be updated; other fields will remain unchanged. - - :param id: The unique identifier of the record to update. - :param input: (Optional) The new input value for the record (an arbitrary, JSON serializable object). - :param expected: (Optional) The new expected output value for the record (an arbitrary, JSON serializable object). - :param tags: (Optional) A list of strings to update the tags of the record. - :param metadata: (Optional) A dictionary to update the metadata of the record. The values in `metadata` can be any - JSON-serializable type, but its keys must be strings. - :returns: The `id` of the updated record. - """ - self._validate_event(metadata=metadata, expected=expected, tags=tags) - - args = self._create_args( - id=id, - input=input, - expected=expected, - metadata=metadata, - tags=tags, - is_merge=True, - ) - - self._clear_cache() # We may be able to optimize this - self.state.global_bg_logger().log(args) - return id - - def delete(self, id: str) -> str: - """ - Delete a record from the dataset. - - :param id: The `id` of the record to delete. - """ - - # Validate the non-lazily-computed part of the record-to-log. - partial_args = _populate_args( - { - "id": id, - "created": datetime.datetime.now(datetime.timezone.utc).isoformat(), - "_object_delete": True, # XXX potentially place this in the logging endpoint - }, - ) - partial_args = bt_safe_deep_copy(partial_args) - - def compute_args(): - return dict( - **partial_args, - dataset_id=self.id, - ) - - self.state.global_bg_logger().log(LazyValue(compute_args, use_mutex=False)) - return id - - def summarize(self, summarize_data: bool = True) -> "DatasetSummary": - """ - Summarize the dataset, including high level metrics about its size and other metadata. - - :param summarize_data: Whether to summarize the data. If False, only the metadata will be returned. - :returns: `DatasetSummary` - """ - # Flush our events to the API, and to the data warehouse, to ensure that the link we print - # includes the new experiment. - self.flush() - state = self._get_state() - project_url = f"{state.app_public_url}/app/{encode_uri_component(state.org_name)}/p/{encode_uri_component(self.project.name)}" - dataset_url = f"{project_url}/datasets/{encode_uri_component(self.name)}" - - data_summary = None - if summarize_data: - data_summary_d = state.api_conn().get_json( - "dataset-summary", - args={ - "dataset_id": self.id, - }, - ) - data_summary = DataSummary(new_records=self.new_records, **data_summary_d) - - return DatasetSummary( - project_name=self.project.name, - dataset_name=self.name, - project_url=project_url, - dataset_url=dataset_url, - data_summary=data_summary, - ) - - def close(self) -> str: - """This function is deprecated. You can simply remove it from your code.""" - - eprint( - "close is deprecated and will be removed in a future version of braintrust. It is now a no-op and can be removed" - ) - return self.id - - def flush(self) -> None: - """Flush any pending rows to the server.""" - - self.state.global_bg_logger().flush() - - def __enter__(self) -> "Dataset": - return self - - def __exit__(self, exc_type, exc_value, traceback) -> None: - del exc_type, exc_value, traceback - - -def render_message(render: Callable[[str], str], message: PromptMessage): - base = {k: v for (k, v) in message.as_dict().items() if v is not None} - # TODO: shouldn't load_prompt guarantee content is a PromptMessage? - content = cast(Union[str, list[Union[TextPart, ImagePart]], dict[str, Any]], message.content) - if content is not None: - if isinstance(content, str): - base["content"] = render(content) - else: - rendered_content = [] - for c in content: - if isinstance(c, str): - rendered_content.append(c) - continue - - if not isinstance(c, dict): - c = c.as_dict() - - if c["type"] == "text": - rendered_content.append({**c, "text": render(c["text"])}) - elif c["type"] == "image_url": - rendered_content.append( - { - **c, - "image_url": {**c["image_url"], "url": render(c["image_url"]["url"])}, - } - ) - elif c["type"] == "file": - rendered_content.append( - { - **c, - "file": { - **c["file"], - "file_data": render(c["file"]["file_data"]), - **({} if "file_id" not in c["file"] else {"file_id": render(c["file"]["file_id"])}), - **({} if "filename" not in c["file"] else {"filename": render(c["file"]["filename"])}), - }, - } - ) - else: - raise ValueError(f"Unknown content type: {c['type']}") - - base["content"] = rendered_content - else: - base["content"] = None - - tool_calls = getattr(message, "tool_calls", None) - if tool_calls is not None: - base["tool_calls"] = [ - { - "type": t.type, - "id": render(t.id), - "function": { - "name": render(t.function.name), - "arguments": render(t.function.arguments), - }, - } - for t in tool_calls - ] - - tool_call_id = getattr(message, "tool_call_id", None) - if tool_call_id is not None: - base["tool_call_id"] = render(tool_call_id) - - return base - - -def _create_custom_render(): - def _get_key(key: str, scopes: list[dict[str, Any]], warn: bool) -> Any: - thing = chevron.renderer._get_key(key, scopes, warn) # type: ignore - if isinstance(thing, str): - return thing - return json.dumps(thing) - - def _html_escape(x: Any) -> Any: - return x - - custom_render = types.FunctionType( - chevron.render.__code__, - { - **chevron.render.__globals__, - **{ - "_get_key": _get_key, - "_html_escape": _html_escape, - }, - }, - chevron.render.__name__, - chevron.render.__defaults__, - chevron.render.__closure__, - ) - custom_render.__kwdefaults__ = chevron.render.__kwdefaults__ - return custom_render - - -_custom_render = _create_custom_render() - - -def render_templated_object(obj: Any, args: Any) -> Any: - strict = args.get("strict", False) if isinstance(args, dict) else False - if isinstance(obj, str): - return render_mustache(obj, data=args, renderer=_custom_render, strict=strict) - elif isinstance(obj, list): - return [render_templated_object(item, args) for item in obj] # type: ignore - elif isinstance(obj, dict): - return {str(k): render_templated_object(v, args) for k, v in obj.items()} # type: ignore - return obj - - -def render_prompt_params(params: dict[str, Any], args: Any) -> dict[str, Any]: - if not params: - return params - - response_format = params.get("response_format") - if not response_format or not isinstance(response_format, dict): - return params - - if response_format.get("type") != "json_schema": - return params - - json_schema = response_format.get("json_schema") - if not json_schema or not isinstance(json_schema, dict): - return params - - raw_schema = json_schema.get("schema") - if raw_schema is None: - return params - - templated_schema = render_templated_object(raw_schema, args) - parsed_schema = json.loads(templated_schema) if isinstance(templated_schema, str) else templated_schema - - return {**params, "response_format": {**response_format, "json_schema": {**json_schema, "schema": parsed_schema}}} - - -def render_mustache(template: str, data: Any, *, strict: bool = False, renderer: Callable[..., Any] | None = None): - if renderer is None: - renderer = chevron.render - - if not strict: - return renderer(template, data=data) - - # Capture stderr to check for missing keys - stderr_capture = io.StringIO() - with contextlib.redirect_stderr(stderr_capture): - result = renderer(template, data=data, warn=True) - - stderr_output = stderr_capture.getvalue() - - # Check if there are missing keys in the stderr output - if "Could not find key" in stderr_output: - raise ValueError(f"Template rendering failed: {stderr_output.strip()}") - - return result - - -class Prompt: - """ - A prompt object consists of prompt text, a model, and model parameters (such as temperature), which - can be used to generate completions or chat messages. The prompt object supports calling `.build()` - which uses mustache templating to build the prompt with the given formatting options and returns a - plain dictionary that includes the built prompt and arguments. The dictionary can be passed as - kwargs to the OpenAI client or modified as you see fit. - - You should not create `Prompt` objects directly. Instead, use the `braintrust.load_prompt()` method. - """ - - def __init__( - self, - lazy_metadata: LazyValue[PromptSchema], - defaults: Mapping[str, Any], - no_trace: bool, - ): - self._lazy_metadata = lazy_metadata - self.defaults = defaults - self.no_trace = no_trace - - @classmethod - def from_prompt_data( - cls, - name: str, - prompt_data: PromptData, - ) -> "Prompt": - """ - Create a `Prompt` object from the given `PromptSchema` data. - """ - prompt_schema = PromptSchema( - name=name, - slug=name, - prompt_data=prompt_data, - id=None, - project_id=None, - _xact_id=None, - description=None, - tags=None, - ) - lazy_metadata = LazyValue(lambda: prompt_schema, use_mutex=False) - return cls(lazy_metadata, {}, False) - - @property - def id(self) -> str: - return self._lazy_metadata.get().id - - @property - def name(self) -> str: - return self._lazy_metadata.get().name - - @property - def slug(self) -> str: - return self._lazy_metadata.get().slug - - @property - def prompt(self) -> PromptBlockData | None: - return self._lazy_metadata.get().prompt_data.prompt - - @property - def version(self) -> str: - return self._lazy_metadata.get()._xact_id - - @property - def options(self) -> PromptOptions: - return self._lazy_metadata.get().prompt_data.options or {} - - # Capture all metadata attributes which aren't covered by existing methods. - def __getattr__(self, name: str) -> Any: - return getattr(self._lazy_metadata.get(), name) - - def build(self, **build_args: Any) -> Mapping[str, Any]: - """ - Build the prompt with the given formatting options. The args you pass in will - be forwarded to the mustache template that defines the prompt and rendered with - the `chevron` library. - - :param build_args: Arguments to forward to the prompt template. Can include 'strict=True' to enable strict mode validation. - :returns: A dictionary that includes the rendered prompt and arguments, that can be passed as kwargs to the OpenAI client. - """ - - # Extract strict mode setting from build_args (using get to avoid modifying the original dict) - strict = build_args.get("strict", False) - - params = self.options.get("params") or {} - params = {k: v for (k, v) in params.items() if k not in BRAINTRUST_PARAMS} - - ret = { - **self.defaults, - **render_prompt_params(params, build_args), - **({"model": self.options["model"]} if "model" in self.options else {}), - } - - if ret.get("model") is None: - raise ValueError("No model specified. Either specify it in the prompt or as a default") - - if not self.no_trace: - ret["span_info"] = { - "metadata": { - "prompt": { - "variables": build_args, - "id": self.id, - "project_id": self.project_id, - "version": self.version, - }, - } - } - - if not self.prompt: - raise ValueError("Empty prompt") - - if self.prompt.type == "completion": - ret["prompt"] = render_mustache(self.prompt.content, data=build_args, strict=strict) - elif self.prompt.type == "chat": - - def render(template: str): - return render_mustache(template, data=build_args, strict=strict) - - ret["messages"] = [render_message(render, m) for m in (self.prompt.messages or [])] - - if self.prompt.tools and self.prompt.tools.strip(): - ret["tools"] = json.loads(render_mustache(self.prompt.tools, data=build_args, strict=strict)) - - return ret - - def _make_iter_list(self) -> Sequence[str]: - meta_keys = list(self.options.keys()) - if self.prompt.type == "completion": - meta_keys.append("prompt") - else: - meta_keys.append("chat") - meta_keys.append("tools") - - return meta_keys - - def __iter__(self) -> Iterator[str]: - return iter(self._make_iter_list()) - - def __len__(self) -> int: - return len(self._make_iter_list()) - - def __getitem__(self, x): - if x == "prompt": - return self.prompt.prompt - elif x == "chat": - return self.prompt.messages - elif x == "tools": - return self.prompt.tools - else: - return self.options[x] - - -class Project: - def __init__(self, name: str | None = None, id: str | None = None): - self._name = name - self._id = id - self.init_lock = threading.RLock() - - def lazy_init(self): - if self._id is None or self._name is None: - with self.init_lock: - if self._id is None: - response = _state.app_conn().post_json( - "api/project/register", - { - "project_name": self._name or GLOBAL_PROJECT, - "org_id": _state.org_id, - }, - ) - self._id = response["project"]["id"] - self._name = response["project"]["name"] - elif self._name is None: - response = _state.app_conn().get_json("api/project", {"id": self._id}) - self._name = response["name"] - - return self - - @property - def id(self) -> str: - self.lazy_init() - return self._id - - @property - def name(self): - self.lazy_init() - return self._name - - -class Logger(Exportable): - def __init__( - self, - lazy_metadata: LazyValue[OrgProjectMetadata], - async_flush: bool = True, - compute_metadata_args: dict | None = None, - link_args: dict | None = None, - state: BraintrustState | None = None, - ): - self._lazy_metadata = lazy_metadata - self.async_flush = async_flush - self._compute_metadata_args = compute_metadata_args - self.last_start_time = time.time() - self._lazy_id = LazyValue(lambda: self.id, use_mutex=False) - self._called_start_span = False - # unresolved args about the org / project. Use these as potential - # fallbacks when generating links - self._link_args = link_args - self.state = state or _state - - @property - def org_id(self) -> str: - return self._lazy_metadata.get().org_id - - @property - def project(self) -> ObjectMetadata: - return self._lazy_metadata.get().project - - @property - def id(self) -> str: - return self.project.id - - @property - def logging_state(self) -> BraintrustState: - return self.state - - @staticmethod - def _parent_object_type(): - return SpanObjectTypeV3.PROJECT_LOGS - - def _get_state(self) -> BraintrustState: - # Ensure the login state is populated by fetching the lazy_metadata. - self._lazy_metadata.get() - return self.state - - def log( - self, - input: Any | None = None, - output: Any | None = None, - expected: Any | None = None, - error: str | None = None, - tags: Sequence[str] | None = None, - scores: Mapping[str, int | float] | None = None, - metadata: Mapping[str, Any] | None = None, - metrics: Mapping[str, int | float] | None = None, - id: str | None = None, - allow_concurrent_with_spans: bool = False, - ) -> str: - """ - Log a single event. The event will be batched and uploaded behind the scenes. - - :param input: (Optional) the arguments that uniquely define a user input (an arbitrary, JSON serializable object). - :param output: (Optional) the output of your application, including post-processing (an arbitrary, JSON serializable object), that allows you to determine whether the result is correct or not. For example, in an app that generates SQL queries, the `output` should be the _result_ of the SQL query generated by the model, not the query itself, because there may be multiple valid queries that answer a single question. - :param expected: (Optional) the ground truth value (an arbitrary, JSON serializable object) that you'd compare to `output` to determine if your `output` value is correct or not. Braintrust currently does not compare `output` to `expected` for you, since there are so many different ways to do that correctly. Instead, these values are just used to help you navigate while digging into analyses. However, we may later use these values to re-score outputs or fine-tune your models. - :param error: (Optional) The error that occurred, if any. If you use tracing to run an experiment, errors are automatically logged when your code throws an exception. - :param tags: (Optional) a list of strings that you can use to filter and group records later. - :param scores: (Optional) a dictionary of numeric values (between 0 and 1) to log. The scores should give you a variety of signals that help you determine how accurate the outputs are compared to what you expect and diagnose failures. For example, a summarization app might have one score that tells you how accurate the summary is, and another that measures the word similarity between the generated and grouth truth summary. The word similarity score could help you determine whether the summarization was covering similar concepts or not. You can use these scores to help you sort, filter, and compare logs. - :param metadata: (Optional) a dictionary with additional data about the test example, model outputs, or just about anything else that's relevant, that you can use to help find and analyze examples later. For example, you could log the `prompt`, example's `id`, or anything else that would be useful to slice/dice later. The values in `metadata` can be any JSON-serializable type, but its keys must be strings. - :param metrics: (Optional) a dictionary of metrics to log. The following keys are populated automatically: "start", "end". - :param id: (Optional) a unique identifier for the event. If you don't provide one, BrainTrust will generate one for you. - :param allow_concurrent_with_spans: (Optional) in rare cases where you need to log at the top level separately from using spans on the logger elsewhere, set this to True. - """ - if self._called_start_span and not allow_concurrent_with_spans: - raise Exception( - "Cannot run toplevel `log` method while using spans. To log to the span, call `logger.start_span` and then log with `span.log`" - ) - - span = self._start_span_impl( - start_time=self.last_start_time, - lookup_span_parent=False, - input=input, - output=output, - expected=expected, - error=error, - tags=tags, - scores=scores, - metadata=metadata, - metrics=metrics, - id=id, - ) - self.last_start_time = span.end() - - if not self.async_flush: - self.flush() - - return span.id - - def log_feedback( - self, - id: str, - scores: Mapping[str, int | float] | None = None, - expected: Any | None = None, - tags: Sequence[str] | None = None, - comment: str | None = None, - metadata: Mapping[str, Any] | None = None, - source: Literal["external", "app", "api", None] = None, - ) -> None: - """ - Log feedback to an event. Feedback is used to save feedback scores, set an expected value, or add a comment. - - :param id: The id of the event to log feedback for. This is the `id` returned by `log` or accessible as the `id` field of a span. - :param scores: (Optional) a dictionary of numeric values (between 0 and 1) to log. These scores will be merged into the existing scores for the event. - :param expected: (Optional) the ground truth value (an arbitrary, JSON serializable object) that you'd compare to `output` to determine if your `output` value is correct or not. - :param tags: (Optional) a list of strings that you can use to filter and group records later. - :param comment: (Optional) an optional comment string to log about the event. - :param metadata: (Optional) a dictionary with additional data about the feedback. If you have a `user_id`, you can log it here and access it in the Braintrust UI. Note, this metadata does not correspond to the main event itself, but rather the audit log attached to the event. - :param source: (Optional) the source of the feedback. Must be one of "external" (default), "app", or "api". - """ - return _log_feedback_impl( - parent_object_type=self._parent_object_type(), - parent_object_id=self._lazy_id, - id=id, - scores=scores, - expected=expected, - tags=tags, - comment=comment, - metadata=metadata, - source=source, - ) - - def start_span( - self, - name: str | None = None, - type: SpanTypeAttribute | None = None, - span_attributes: SpanAttributes | Mapping[str, Any] | None = None, - start_time: float | None = None, - set_current: bool | None = None, - parent: str | None = None, - propagated_event: dict[str, Any] | None = None, - span_id: str | None = None, - root_span_id: str | None = None, - **event: Any, - ) -> Span: - """Create a new toplevel span underneath the logger. The name defaults to "root" and the span type to "task". - - See `Span.start_span` for full details - """ - self._called_start_span = True - return self._start_span_impl( - name=name, - type=type, - span_attributes=span_attributes, - start_time=start_time, - set_current=set_current, - parent=parent, - propagated_event=propagated_event, - span_id=span_id, - root_span_id=root_span_id, - **event, - ) - - def update_span(self, id: str, **event: Any) -> None: - """ - Update a span in the experiment using its id. It is important that you only update a span once the original span - has been fully written and flushed, since otherwise updates to the span may conflict with the original span. - - :param id: The id of the span to update. - :param **event: Data to update. See `Experiment.log` for a full list of valid fields. - """ - root_span_id = event.pop("root_span_id", None) - span_id = event.pop("span_id", None) - return _update_span_impl( - parent_object_type=self._parent_object_type(), - parent_object_id=self._lazy_id, - id=id, - root_span_id=root_span_id, - span_id=span_id, - **event, - ) - - def _start_span_impl( - self, - name: str | None = None, - type: SpanTypeAttribute | None = None, - span_attributes: SpanAttributes | Mapping[str, Any] | None = None, - start_time: float | None = None, - set_current: bool | None = None, - parent: str | None = None, - propagated_event: dict[str, Any] | None = None, - span_id: str | None = None, - root_span_id: str | None = None, - lookup_span_parent: bool = True, - **event: Any, - ) -> Span: - parent_args = _start_span_parent_args( - parent=parent, - parent_object_type=self._parent_object_type(), - parent_object_id=self._lazy_id, - parent_compute_object_metadata_args=self._compute_metadata_args, - parent_span_ids=None, - propagated_event=propagated_event, - ) - return SpanImpl( - **parent_args, - name=name, - type=type, - default_root_type=SpanTypeAttribute.TASK, - span_attributes=span_attributes, - start_time=start_time, - set_current=set_current, - event=event, - span_id=span_id, - root_span_id=root_span_id, - lookup_span_parent=lookup_span_parent, - state=self.state, - ) - - def export(self) -> str: - """Return a serialized representation of the logger that can be used to start subspans in other places. See `Span.start_span` for more details.""" - # Note: it is important that the object id we are checking for - # `has_succeeded` is the same as the one we are passing into the span - # logging functions. So that if the spans actually do get logged, then - # this `_lazy_id` object specifically will also be marked as computed. - if self._compute_metadata_args and not self._lazy_id.has_succeeded: - object_id = None - compute_object_metadata_args = self._compute_metadata_args - else: - object_id = self._lazy_id.get() - compute_object_metadata_args = None - - exporter = _get_exporter() - return exporter( - object_type=self._parent_object_type(), - object_id=object_id, - compute_object_metadata_args=compute_object_metadata_args, - ).to_str() - - def __enter__(self) -> "Logger": - return self - - def _get_link_base_url(self) -> str | None: - """Return the base of link urls (e.g. https://braintrust.dev/app/my-org-name/) if we have the info - otherwise return None. - """ - # the url and org name can be passed into init_logger, resolved by login or provided as env variables - # so this resolves all of those things. It's possible we never have an org name if the user has not - # yet logged in and there is nothing else configured. - app_url = self.state.app_url or self._link_args.get("app_url") or _get_app_url() - org_name = self.state.org_name or self._link_args.get("org_name") or _get_org_name() - if not app_url or not org_name: - return None - return f"{app_url}/app/{org_name}" - - def __exit__(self, exc_type, exc_value, traceback) -> None: - del exc_type, exc_value, traceback - - def flush(self) -> None: - """ - Flush any pending logs to the server. - """ - self.state.global_bg_logger().flush() - - -@dataclasses.dataclass -class ScoreSummary(SerializableDataClass): - """Summary of a score's performance.""" - - name: str - """Name of the score.""" - - # Used to help with formatting - _longest_score_name: int - - score: float - """Average score across all examples.""" - - improvements: int | None - """Number of improvements in the score.""" - regressions: int | None - """Number of regressions in the score.""" - diff: float | None = None - """Difference in score between the current and reference experiment.""" - - def __str__(self): - # format with 2 decimal points and pad so that it's exactly 2 characters then 2 decimals - score_pct = f"{self.score * 100:05.2f}%" - - # pad the name with spaces so that its length is self._longest_score_name + 2 - score_name = f"'{self.name}'".ljust(self._longest_score_name + 2) - - if self.diff is not None: - diff_pct = f"{abs(self.diff) * 100:05.2f}%" - diff_score = f"+{diff_pct}" if self.diff > 0 else f"-{diff_pct}" if self.diff < 0 else "-" - - return textwrap.dedent( - f"""{score_pct} ({diff_score}) {score_name} score\t({self.improvements} improvements, {self.regressions} regressions)""" - ) - else: - return textwrap.dedent(f"""{score_pct} {score_name} score""") - - -@dataclasses.dataclass -class MetricSummary(SerializableDataClass): - """Summary of a metric's performance.""" - - name: str - """Name of the metric.""" - - # Used to help with formatting - _longest_metric_name: int - - metric: float | int - """Average metric across all examples.""" - unit: str - """Unit label for the metric.""" - improvements: int | None - """Number of improvements in the metric.""" - regressions: int | None - """Number of regressions in the metric.""" - diff: float | None = None - """Difference in metric between the current and reference experiment.""" - - def __str__(self): - number_fmt = "{:d}" if isinstance(self.metric, int) else "{:.2f}" - metric = number_fmt.format(self.metric) - if self.diff is None: - return textwrap.dedent(f"""{metric}{self.unit} {self.name}""") - - diff_pct = f"{abs(self.diff) * 100:05.2f}%" - diff_score = f"+{diff_pct}" if self.diff > 0 else f"-{diff_pct}" if self.diff < 0 else "-" - - # pad the name with spaces so that its length is self._longest_score_name + 2 - metric_name = f"'{self.name}'".ljust(self._longest_metric_name + 2) - - return textwrap.dedent( - f"""{metric}{self.unit} ({diff_score}) {metric_name}\t({self.improvements} improvements, {self.regressions} regressions)""" - ) - - -@dataclasses.dataclass -class ExperimentSummary(SerializableDataClass): - """Summary of an experiment's scores and metadata.""" - - project_name: str - """Name of the project that the experiment belongs to.""" - project_id: str | None - """ID of the project. May be `None` if the eval was run locally.""" - experiment_id: str | None - """ID of the experiment. May be `None` if the eval was run locally.""" - experiment_name: str - """Name of the experiment.""" - project_url: str | None - """URL to the project's page in the Braintrust app.""" - experiment_url: str | None - """URL to the experiment's page in the Braintrust app.""" - comparison_experiment_name: str | None - """The experiment scores are baselined against.""" - scores: dict[str, ScoreSummary] - """Summary of the experiment's scores.""" - metrics: dict[str, MetricSummary] - """Summary of the experiment's metrics.""" - - def __str__(self): - comparison_line = "" - if self.comparison_experiment_name: - comparison_line = f"""{self.experiment_name} compared to {self.comparison_experiment_name}:\n""" - return ( - f"""\n=========================SUMMARY=========================\n{comparison_line}""" - + "\n".join([str(score) for score in self.scores.values()]) - + ("\n\n" if self.scores else "") - + "\n".join([str(metric) for metric in self.metrics.values()]) - + ("\n\n" if self.metrics else "") - + ( - textwrap.dedent( - f"""\ - See results for {self.experiment_name} at {self.experiment_url}""" - ) - if self.experiment_url is not None - else "" - ) - ) - - -@dataclasses.dataclass -class DataSummary(SerializableDataClass): - """Summary of a dataset's data.""" - - new_records: int - """New or updated records added in this session.""" - total_records: int - """Total records in the dataset.""" - - def __str__(self): - return textwrap.dedent(f"""Total records: {self.total_records} ({self.new_records} new or updated records)""") - - -@dataclasses.dataclass -class DatasetSummary(SerializableDataClass): - """Summary of a dataset's scores and metadata.""" - - project_name: str - """Name of the project that the dataset belongs to.""" - dataset_name: str - """Name of the dataset.""" - project_url: str - """URL to the project's page in the Braintrust app.""" - dataset_url: str - """URL to the experiment's page in the Braintrust app.""" - data_summary: DataSummary | None - """Summary of the dataset's data.""" - - def __str__(self): - return textwrap.dedent( - f"""\ - - =========================SUMMARY========================= - {str(self.data_summary)} - See results for all datasets in {self.project_name} at {self.project_url} - See results for {self.dataset_name} at {self.dataset_url}""" - ) - - -class TracedThreadPoolExecutor(concurrent.futures.ThreadPoolExecutor): - # Returns Any because Future[T] generic typing was stabilized in Python 3.9, - # but we maintain compatibility with older type checkers. - def submit(self, fn: Callable[..., Any], *args: Any, **kwargs: Any) -> Any: - # Capture all current context variables - context = contextvars.copy_context() - - def wrapped_fn(*args, **kwargs): - # Run the function inside the captured context - return context.run(fn, *args, **kwargs) - - return super().submit(wrapped_fn, *args, **kwargs) - - -def get_prompt_versions(project_id: str, prompt_id: str) -> list[str]: - """ - Get the versions for a specific prompt. - - Args: - project_id: The ID of the project to query - prompt_id: The ID of the prompt to get versions for - - Returns: - List of transaction IDs (_xact_id) for entries where audit_data.action is "upsert" - """ - - query = { - "from": { - "op": "function", - "name": { - "op": "ident", - "name": ["project_prompts"], - }, - "args": [ - { - "op": "literal", - "value": project_id, - }, - ], - }, - "select": [ - { - "op": "star", - }, - ], - "filter": { - "op": "eq", - "left": {"op": "ident", "name": ["id"]}, - "right": {"op": "literal", "value": prompt_id}, - }, - } - - resp = _state.api_conn().post( - "btql", - json={ - "query": query, - "audit_log": True, - "use_columnstore": False, - "brainstore_realtime": True, - }, - headers={"Accept-Encoding": "gzip"}, - ) - - response_raise_for_status(resp) - result = resp.json() - - # Filter for entries where audit_data.action is "upsert" or "merge" and return prettified _xact_id fields - return [ - prettify_xact(entry["_xact_id"]) - for entry in result.get("data", []) - if entry.get("audit_data", {}).get("action") in ["upsert", "merge"] - ] - - -def _get_app_url(app_url: str | None = None) -> str: - if app_url: - return app_url - return os.getenv("BRAINTRUST_APP_URL", DEFAULT_APP_URL) - - -def _get_org_name(org_name: str | None = None) -> str | None: - if org_name: - return org_name - return os.getenv("BRAINTRUST_ORG_NAME") - - -def _get_error_link(msg="") -> str: - return f"https://www.braintrust.dev/error-generating-link?msg={encode_uri_component(msg)}" diff --git a/py/src/braintrust/merge_row_batch.py b/py/src/braintrust/merge_row_batch.py deleted file mode 100644 index 07d40578b..000000000 --- a/py/src/braintrust/merge_row_batch.py +++ /dev/null @@ -1,183 +0,0 @@ -from collections.abc import Callable, Sequence -from typing import Any, Optional, TypeVar - -from .db_fields import IS_MERGE_FIELD - -T = TypeVar("T") -from .util import merge_dicts - -_MergedRowKey = tuple[Optional[Any], ...] - - -def _generate_merged_row_key(row: dict[str, Any]) -> _MergedRowKey: - return tuple( - row.get(k) - for k in [ - "org_id", - "project_id", - "experiment_id", - "dataset_id", - "prompt_session_id", - "log_id", - "id", - ] - ) - - -# These fields will be retained as-is when merging rows. -MERGE_ROW_SKIP_FIELDS = [ - "created", - "span_id", - "root_span_id", - "span_parents", - "_parent_id", - # TODO: handle merge paths. -] - - -def _pop_merge_row_skip_fields(row: dict[str, Any]) -> dict[str, Any]: - popped = {} - for field in MERGE_ROW_SKIP_FIELDS: - if field in row: - popped[field] = row.pop(field) - return popped - - -def _restore_merge_row_skip_fields(row: dict[str, Any], skip_fields: dict[str, Any]): - for field in MERGE_ROW_SKIP_FIELDS: - row.pop(field, None) - if field in skip_fields: - row[field] = skip_fields[field] - - -def merge_row_batch(rows: Sequence[dict[str, Any]]) -> list[dict[str, Any]]: - """Given a batch of rows, merges conflicting rows together to end up with a - set of rows to insert. Returns a set of de-conflicted rows as a flat list. - - Note that the returned rows will be the same objects as the input `rows`, - meaning they are mutated in place. - - There are a few important considerations for the merge procedure: - - - Ensuring we only log one version of each row to the DB: - - Imagine we have several rows in the batch with the same ID: - - [{"make_object_id(..)": "xyz", "id": 1, "value": 1}, - {"make_object_id(...)": "xyz", "id": 1, "value": 2}] - - If we log both rows and assign them both the same transaction ID, future - queries will not be able to disamgiguate ordering here (i.e that `value: 2` - is the "later" value). So we must consolidate these rows into one before - logging. - - - Merging rows with IS_MERGE_FIELD == True: - - Rows can either be incrementally updated or replaced entirely. For a - particular row, we use the IS_MERGE_FIELD to determine whether we merge or - replace. In case there are several incremental updates to the same row - within the batch, we merge them into one incremental update here, so that we - only need to do one merge in the DB. - - We need to be careful to preserve the correct value of IS_MERGE_FIELD with - respect to the DB. For instance, if we have one batch of rows: - - [{"make_object_id(...)": "xyz", "id": 1, "value": {"a": 12}}, - {"make_object_id(...)": "xyz", "id": 1, "value": {"b": 13}, - IS_MERGE_FIELD: True}] - - We need to make sure the row inserted into the DB has IS_MERGE_FIELD == False, - otherwise we might merge it with a previous existing version of the row. - """ - - # Check that no row is missing an ID. - for row in rows: - if row.get("id") is None: - raise Exception( - "Logged row is missing an id. This is an internal braintrust error. Please contact us at info@braintrust.dev for help" - ) - - row_groups: dict[_MergedRowKey, dict[str, Any]] = {} - for row in rows: - key = _generate_merged_row_key(row) - existing_row = row_groups.get(key) - # If there is an existing row and the new row has the IS_MERGE_FIELD == - # True property, we merge it with the existing row. Otherwise we can - # replace it. - if existing_row is not None and row.get(IS_MERGE_FIELD): - skip_fields = _pop_merge_row_skip_fields(existing_row) - # Preserve IS_MERGE_FIELD == False if the existing_row had it set to - # false. - preserve_nomerge = not existing_row.get(IS_MERGE_FIELD) - merge_dicts(existing_row, row) - _restore_merge_row_skip_fields(existing_row, skip_fields) - if preserve_nomerge: - del existing_row[IS_MERGE_FIELD] - else: - row_groups[key] = row - - return list(row_groups.values()) - - -def batch_items( - items: list[T], - batch_max_num_items: int | None = None, - batch_max_num_bytes: int | None = None, - get_byte_size: Callable[[T], int] | None = None, -) -> list[list[T]]: - """Repartition the given list of items into batches. - - Arguments: - - - `items` is a list of items to batch. - - - `batch_max_num_items` is the maximum number of items in each batch. - If not provided, there is no limit on the number of items. - - - `batch_max_num_bytes` is the maximum number of bytes in each batch. - If an individual item exceeds `batch_max_num_bytes` in size, we - will place it in its own batch. If not provided, there is no limit on - the number of bytes. - - - `get_byte_size` is a function that returns the byte size of an item. - If not provided, defaults to `len(item)` (works for strings). - """ - - if batch_max_num_items is not None and batch_max_num_items <= 0: - raise ValueError(f"batch_max_num_items must be positive; got {batch_max_num_items}") - if batch_max_num_bytes is not None and batch_max_num_bytes < 0: - raise ValueError(f"batch_max_num_bytes must be nonnegative; got {batch_max_num_bytes}") - - if get_byte_size is None: - - def get_byte_size(item: T) -> int: - return len(item) # type: ignore[arg-type] - - output: list[list[T]] = [] - batch: list[T] = [] - batch_len = 0 - - def add_to_batch(item: T) -> None: - nonlocal batch_len - batch.append(item) - batch_len += get_byte_size(item) - - def flush_batch() -> None: - nonlocal batch, batch_len - output.append(batch) - batch = [] - batch_len = 0 - - for item in items: - item_size = get_byte_size(item) - if len(batch) > 0 and not ( - (batch_max_num_bytes is None or item_size + batch_len < batch_max_num_bytes) - and (batch_max_num_items is None or len(batch) < batch_max_num_items) - ): - flush_batch() - add_to_batch(item) - - if len(batch) > 0: - flush_batch() - - return output diff --git a/py/src/braintrust/oai.py b/py/src/braintrust/oai.py deleted file mode 100644 index df848f46d..000000000 --- a/py/src/braintrust/oai.py +++ /dev/null @@ -1,1045 +0,0 @@ -import abc -import base64 -import re -import time -from collections.abc import Callable -from typing import Any - -from wrapt import wrap_function_wrapper - -from .logger import Attachment, Span, start_span -from .span_types import SpanTypeAttribute -from .util import is_numeric, merge_dicts - -X_LEGACY_CACHED_HEADER = "x-cached" -X_CACHED_HEADER = "x-bt-cached" - - -class NamedWrapper: - def __init__(self, wrapped: Any): - self.__wrapped = wrapped - - def __getattr__(self, name: str) -> Any: - return getattr(self.__wrapped, name) - - -class AsyncResponseWrapper: - """Wrapper that properly preserves async context manager behavior for OpenAI responses.""" - - def __init__(self, response: Any): - self._response = response - - async def __aenter__(self): - if hasattr(self._response, "__aenter__"): - return await self._response.__aenter__() - return self._response - - async def __aexit__(self, exc_type, exc_val, exc_tb): - if hasattr(self._response, "__aexit__"): - return await self._response.__aexit__(exc_type, exc_val, exc_tb) - - def __aiter__(self): - if hasattr(self._response, "__aiter__"): - return self._response.__aiter__() - raise TypeError("Response object is not an async iterator") - - async def __anext__(self): - if hasattr(self._response, "__anext__"): - return await self._response.__anext__() - raise StopAsyncIteration - - def __getattr__(self, name: str) -> Any: - return getattr(self._response, name) - - @property - def __class__(self): # type: ignore - return self._response.__class__ - - def __str__(self) -> str: - return str(self._response) - - def __repr__(self) -> str: - return repr(self._response) - - -def log_headers(response: Any, span: Span): - cached_value = response.headers.get(X_CACHED_HEADER) or response.headers.get(X_LEGACY_CACHED_HEADER) - - if cached_value: - span.log( - metrics={ - "cached": 1 if cached_value.lower() in ["true", "hit"] else 0, - } - ) - - -def _convert_data_url_to_attachment(data_url: str, filename: str | None = None) -> Attachment | str: - """Helper function to convert data URL to an Attachment.""" - data_url_match = re.match(r"^data:([^;]+);base64,(.+)$", data_url) - if not data_url_match: - return data_url - - mime_type, base64_data = data_url_match.groups() - - try: - binary_data = base64.b64decode(base64_data) - - if filename is None: - extension = mime_type.split("/")[1] if "/" in mime_type else "bin" - prefix = "image" if mime_type.startswith("image/") else "document" - filename = f"{prefix}.{extension}" - - attachment = Attachment(data=binary_data, filename=filename, content_type=mime_type) - - return attachment - except Exception: - return data_url - - -def _process_attachments_in_input(input_data: Any) -> Any: - """Process input to convert data URL images and base64 documents to Attachment objects.""" - if isinstance(input_data, list): - return [_process_attachments_in_input(item) for item in input_data] - - if isinstance(input_data, dict): - # Check for OpenAI's image_url format with data URLs - if ( - input_data.get("type") == "image_url" - and isinstance(input_data.get("image_url"), dict) - and isinstance(input_data["image_url"].get("url"), str) - ): - processed_url = _convert_data_url_to_attachment(input_data["image_url"]["url"]) - return { - **input_data, - "image_url": { - **input_data["image_url"], - "url": processed_url, - }, - } - - # Check for OpenAI's file format with data URL (e.g., PDFs) - if ( - input_data.get("type") == "file" - and isinstance(input_data.get("file"), dict) - and isinstance(input_data["file"].get("file_data"), str) - ): - file_filename = input_data["file"].get("filename") - processed_file_data = _convert_data_url_to_attachment( - input_data["file"]["file_data"], - filename=file_filename if isinstance(file_filename, str) else None, - ) - return { - **input_data, - "file": { - **input_data["file"], - "file_data": processed_file_data, - }, - } - - # Recursively process nested objects - return {key: _process_attachments_in_input(value) for key, value in input_data.items()} - - return input_data - - -class ChatCompletionWrapper: - def __init__(self, create_fn: Callable[..., Any] | None, acreate_fn: Callable[..., Any] | None): - self.create_fn = create_fn - self.acreate_fn = acreate_fn - - def create(self, *args: Any, **kwargs: Any) -> Any: - params = self._parse_params(kwargs) - stream = kwargs.get("stream", False) - - span = start_span( - **merge_dicts(dict(name="Chat Completion", span_attributes={"type": SpanTypeAttribute.LLM}), params) - ) - should_end = True - - try: - start = time.time() - create_response = self.create_fn(*args, **kwargs) - if hasattr(create_response, "parse"): - raw_response = create_response.parse() - log_headers(create_response, span) - else: - raw_response = create_response - if stream: - - def gen(): - try: - first = True - all_results = [] - for item in raw_response: - if first: - span.log( - metrics={ - "time_to_first_token": time.time() - start, - } - ) - first = False - all_results.append(_try_to_dict(item)) - yield item - - span.log(**self._postprocess_streaming_results(all_results)) - finally: - span.end() - - should_end = False - return gen() - else: - log_response = _try_to_dict(raw_response) - metrics = _parse_metrics_from_usage(log_response.get("usage", {})) - metrics["time_to_first_token"] = time.time() - start - span.log( - metrics=metrics, - output=log_response["choices"], - ) - return raw_response - finally: - if should_end: - span.end() - - async def acreate(self, *args: Any, **kwargs: Any) -> Any: - params = self._parse_params(kwargs) - stream = kwargs.get("stream", False) - - span = start_span( - **merge_dicts(dict(name="Chat Completion", span_attributes={"type": SpanTypeAttribute.LLM}), params) - ) - should_end = True - - try: - start = time.time() - create_response = await self.acreate_fn(*args, **kwargs) - - if hasattr(create_response, "parse"): - raw_response = create_response.parse() - log_headers(create_response, span) - else: - raw_response = create_response - - if stream: - - async def gen(): - try: - first = True - all_results = [] - async for item in raw_response: - if first: - span.log( - metrics={ - "time_to_first_token": time.time() - start, - } - ) - first = False - all_results.append(_try_to_dict(item)) - yield item - - span.log(**self._postprocess_streaming_results(all_results)) - finally: - span.end() - - should_end = False - streamer = gen() - return AsyncResponseWrapper(streamer) - else: - log_response = _try_to_dict(raw_response) - metrics = _parse_metrics_from_usage(log_response.get("usage")) - metrics["time_to_first_token"] = time.time() - start - span.log( - metrics=metrics, - output=log_response["choices"], - ) - return raw_response - finally: - if should_end: - span.end() - - @classmethod - def _parse_params(cls, params: dict[str, Any]) -> dict[str, Any]: - # First, destructively remove span_info - ret = params.pop("span_info", {}) - - # Then, copy the rest of the params - params = prettify_params(params) - messages = params.pop("messages", None) - - # Process attachments in input (convert data URLs to Attachment objects) - processed_input = _process_attachments_in_input(messages) - - return merge_dicts( - ret, - { - "input": processed_input, - "metadata": {**params, "provider": "openai"}, - }, - ) - - @classmethod - def _postprocess_streaming_results(cls, all_results: list[dict[str, Any]]) -> dict[str, Any]: - role = None - content = None - tool_calls: list[Any] | None = None - finish_reason = None - metrics: dict[str, float] = {} - for result in all_results: - usage = result.get("usage") - if usage: - metrics.update(_parse_metrics_from_usage(usage)) - - choices = result["choices"] - if not choices: - continue - delta = choices[0]["delta"] - if not delta: - continue - - if role is None and delta.get("role") is not None: - role = delta.get("role") - - if delta.get("finish_reason") is not None: - finish_reason = delta.get("finish_reason") - - if delta.get("content") is not None: - content = (content or "") + delta.get("content") - - if delta.get("tool_calls") is not None: - delta_tool_calls = delta.get("tool_calls") - if not delta_tool_calls: - continue - tool_delta = delta_tool_calls[0] - - # pylint: disable=unsubscriptable-object - if not tool_calls or (tool_delta.get("id") and tool_calls[-1]["id"] != tool_delta.get("id")): - function_arg = tool_delta.get("function", {}) - tool_calls = (tool_calls or []) + [ - { - "id": tool_delta.get("id"), - "type": tool_delta.get("type"), - "function": { - "name": function_arg.get("name"), - "arguments": function_arg.get("arguments") or "", - }, - } - ] - else: - # pylint: disable=unsubscriptable-object - # append to existing tool call - function_arg = tool_delta.get("function", {}) - args = function_arg.get("arguments") or "" - if isinstance(args, str): - # pylint: disable=unsubscriptable-object - tool_calls[-1]["function"]["arguments"] += args - - return { - "metrics": metrics, - "output": [ - { - "index": 0, - "message": { - "role": role, - "content": content, - "tool_calls": tool_calls, - }, - "logprobs": None, - "finish_reason": finish_reason, - } - ], - } - - -class ResponseWrapper: - def __init__(self, create_fn: Callable[..., Any] | None, acreate_fn: Callable[..., Any] | None, name: str = "openai.responses.create"): - self.create_fn = create_fn - self.acreate_fn = acreate_fn - self.name = name - - def create(self, *args: Any, **kwargs: Any) -> Any: - params = self._parse_params(kwargs) - stream = kwargs.get("stream", False) - - span = start_span( - **merge_dicts(dict(name=self.name, span_attributes={"type": SpanTypeAttribute.LLM}), params) - ) - should_end = True - - try: - start = time.time() - create_response = self.create_fn(*args, **kwargs) - if hasattr(create_response, "parse"): - raw_response = create_response.parse() - log_headers(create_response, span) - else: - raw_response = create_response - if stream: - def gen(): - try: - first = True - all_results = [] - for item in raw_response: - if first: - span.log( - metrics={ - "time_to_first_token": time.time() - start, - } - ) - first = False - all_results.append(item) - yield item - - span.log(**self._postprocess_streaming_results(all_results)) - finally: - span.end() - - should_end = False - return gen() - else: - log_response = _try_to_dict(raw_response) - event_data = self._parse_event_from_result(log_response) - if "metrics" not in event_data: - event_data["metrics"] = {} - event_data["metrics"]["time_to_first_token"] = time.time() - start - span.log(**event_data) - return raw_response - finally: - if should_end: - span.end() - - async def acreate(self, *args: Any, **kwargs: Any) -> Any: - params = self._parse_params(kwargs) - stream = kwargs.get("stream", False) - - span = start_span( - **merge_dicts(dict(name=self.name, span_attributes={"type": SpanTypeAttribute.LLM}), params) - ) - should_end = True - - try: - start = time.time() - create_response = await self.acreate_fn(*args, **kwargs) - if hasattr(create_response, "parse"): - raw_response = create_response.parse() - log_headers(create_response, span) - else: - raw_response = create_response - if stream: - async def gen(): - try: - first = True - all_results = [] - async for item in raw_response: - if first: - span.log( - metrics={ - "time_to_first_token": time.time() - start, - } - ) - first = False - all_results.append(item) - yield item - - span.log(**self._postprocess_streaming_results(all_results)) - finally: - span.end() - - should_end = False - streamer = gen() - return AsyncResponseWrapper(streamer) - else: - log_response = _try_to_dict(raw_response) - event_data = self._parse_event_from_result(log_response) - if "metrics" not in event_data: - event_data["metrics"] = {} - event_data["metrics"]["time_to_first_token"] = time.time() - start - span.log(**event_data) - return raw_response - finally: - if should_end: - span.end() - - @classmethod - def _parse_params(cls, params: dict[str, Any]) -> dict[str, Any]: - # First, destructively remove span_info - ret = params.pop("span_info", {}) - - # Then, copy the rest of the params - params = prettify_params(params) - input_data = params.pop("input", None) - - # Process attachments in input (convert data URLs to Attachment objects) - processed_input = _process_attachments_in_input(input_data) - - return merge_dicts( - ret, - { - "input": processed_input, - "metadata": {**params, "provider": "openai"}, - }, - ) - - @classmethod - def _parse_event_from_result(cls, result: dict[str, Any]) -> dict[str, Any]: - """Parse event from response result""" - data = {"metrics": {}} - - if not result: - return data - - if "output" in result: - data["output"] = result["output"] - - metadata = {k: v for k, v in result.items() if k not in ["output", "usage"]} - if metadata: - data["metadata"] = metadata - - if "usage" in result: - data["metrics"] = _parse_metrics_from_usage(result["usage"]) - - return data - - @classmethod - def _postprocess_streaming_results(cls, all_results: list[Any]) -> dict[str, Any]: - """Process streaming results - minimal version focused on metrics extraction.""" - metrics = {} - output = [] - - for result in all_results: - usage = getattr(result, "usage", None) - if not usage and hasattr(result, "type") and result.type == "response.completed" and hasattr(result, "response"): - # Handle summaries from completed response if present - if hasattr(result.response, "output") and result.response.output: - for output_item in result.response.output: - if hasattr(output_item, "summary") and output_item.summary: - for item in output: - if item.get("id") == output_item.id: - item["summary"] = output_item.summary - usage = getattr(result.response, "usage", None) - - if usage: - parsed_metrics = _parse_metrics_from_usage(usage) - metrics.update(parsed_metrics) - - # Skip processing if result doesn't have a type attribute - if not hasattr(result, "type"): - continue - - if result.type == "response.output_item.added": - item_data = {"id": result.item.id, "type": result.item.type} - if hasattr(result.item, "role"): - item_data["role"] = result.item.role - output.append(item_data) - continue - - if result.type == "response.completed": - if hasattr(result, "response") and hasattr(result.response, "output"): - return { - "metrics": metrics, - "output": result.response.output, - } - continue - - # Handle output_index based updates - if hasattr(result, "output_index"): - output_index = result.output_index - if output_index < len(output): - current_output = output[output_index] - - if result.type == "response.output_item.done": - current_output["status"] = result.item.status - continue - - if result.type == "response.output_item.delta": - current_output["delta"] = result.delta - continue - - # Handle content_index based updates - if hasattr(result, "content_index"): - if "content" not in current_output: - current_output["content"] = [] - content_index = result.content_index - # Fill any gaps in the content array - while len(current_output["content"]) <= content_index: - current_output["content"].append({}) - current_content = current_output["content"][content_index] - current_content["type"] = "output_text" - if hasattr(result, "delta") and result.delta: - current_content["text"] = (current_content.get("text") or "") + result.delta - - if result.type == "response.output_text.annotation.added": - annotation_index = result.annotation_index - if "annotations" not in current_content: - current_content["annotations"] = [] - # Fill any gaps in the annotations array - while len(current_content["annotations"]) <= annotation_index: - current_content["annotations"].append({}) - current_content["annotations"][annotation_index] = _try_to_dict(result.annotation) - - return { - "metrics": metrics, - "output": output, - } - - -class BaseWrapper(abc.ABC): - def __init__(self, create_fn: Callable[..., Any] | None, acreate_fn: Callable[..., Any] | None, name: str): - self._create_fn = create_fn - self._acreate_fn = acreate_fn - self._name = name - - @abc.abstractmethod - def process_output(self, response: dict[str, Any], span: Span): - """Process the API response and log relevant information to the span.""" - pass - - def create(self, *args: Any, **kwargs: Any) -> Any: - params = self._parse_params(kwargs) - - with start_span( - **merge_dicts(dict(name=self._name, span_attributes={"type": SpanTypeAttribute.LLM}), params) - ) as span: - create_response = self._create_fn(*args, **kwargs) - if hasattr(create_response, "parse"): - raw_response = create_response.parse() - log_headers(create_response, span) - else: - raw_response = create_response - - log_response = _try_to_dict(raw_response) - self.process_output(log_response, span) - return raw_response - - async def acreate(self, *args: Any, **kwargs: Any) -> Any: - params = self._parse_params(kwargs) - - with start_span( - **merge_dicts(dict(name=self._name, span_attributes={"type": SpanTypeAttribute.LLM}), params) - ) as span: - create_response = await self._acreate_fn(*args, **kwargs) - if hasattr(create_response, "parse"): - raw_response = create_response.parse() - log_headers(create_response, span) - else: - raw_response = create_response - log_response = _try_to_dict(raw_response) - self.process_output(log_response, span) - return raw_response - - @classmethod - def _parse_params(cls, params: dict[str, Any]) -> dict[str, Any]: - # First, destructively remove span_info - ret = params.pop("span_info", {}) - - params = prettify_params(params) - input_data = params.pop("input", None) - - # Process attachments in input (convert data URLs to Attachment objects) - processed_input = _process_attachments_in_input(input_data) - - return merge_dicts( - ret, - { - "input": processed_input, - "metadata": {**params, "provider": "openai"}, - }, - ) - - -class EmbeddingWrapper(BaseWrapper): - def __init__(self, create_fn: Callable[..., Any] | None, acreate_fn: Callable[..., Any] | None): - super().__init__(create_fn, acreate_fn, "Embedding") - - def process_output(self, response: dict[str, Any], span: Span): - usage = response.get("usage") - metrics = _parse_metrics_from_usage(usage) - span.log( - metrics=metrics, - # TODO: Add a flag to control whether to log the full embedding vector, - # possibly w/ JSON compression. - output={"embedding_length": len(response["data"][0]["embedding"])}, - ) - - -class ModerationWrapper(BaseWrapper): - def __init__(self, create_fn: Callable[..., Any] | None, acreate_fn: Callable[..., Any] | None): - super().__init__(create_fn, acreate_fn, "Moderation") - - def process_output(self, response: Any, span: Span): - span.log( - output=response["results"], - ) - - -class ChatCompletionV0Wrapper(NamedWrapper): - def __init__(self, chat: Any): - self.__chat = chat - super().__init__(chat) - - def create(self, *args: Any, **kwargs: Any) -> Any: - return ChatCompletionWrapper(self.__chat.create, self.__chat.acreate).create(*args, **kwargs) - - async def acreate(self, *args: Any, **kwargs: Any) -> Any: - return await ChatCompletionWrapper(self.__chat.create, self.__chat.acreate).acreate(*args, **kwargs) - - -class EmbeddingV0Wrapper(NamedWrapper): - def __init__(self, embedding: Any): - self.__embedding = embedding - super().__init__(embedding) - - def create(self, *args: Any, **kwargs: Any) -> Any: - return EmbeddingWrapper(self.__embedding.create, self.__embedding.acreate).create(*args, **kwargs) - - async def acreate(self, *args: Any, **kwargs: Any) -> Any: - return await ChatCompletionWrapper(self.__embedding.create, self.__embedding.acreate).acreate(*args, **kwargs) - - -class ModerationV0Wrapper(NamedWrapper): - def __init__(self, moderation: Any): - self.__moderation = moderation - super().__init__(moderation) - - def create(self, *args: Any, **kwargs: Any) -> Any: - return ModerationWrapper(self.__moderation.create, self.__moderation.acreate).create(*args, **kwargs) - - async def acreate(self, *args: Any, **kwargs: Any) -> Any: - return await ModerationWrapper(self.__moderation.create, self.__moderation.acreate).acreate(*args, **kwargs) - - -# This wraps 0.*.* versions of the openai module, eg https://github.com/openai/openai-python/tree/v0.28.1 -class OpenAIV0Wrapper(NamedWrapper): - def __init__(self, openai: Any): - super().__init__(openai) - self.ChatCompletion = ChatCompletionV0Wrapper(openai.ChatCompletion) - self.Embedding = EmbeddingV0Wrapper(openai.Embedding) - self.Moderation = ModerationV0Wrapper(openai.Moderation) - - -class CompletionsV1Wrapper(NamedWrapper): - def __init__(self, completions: Any): - self.__completions = completions - super().__init__(completions) - - def create(self, *args: Any, **kwargs: Any) -> Any: - return ChatCompletionWrapper(self.__completions.with_raw_response.create, None).create(*args, **kwargs) - - -class EmbeddingV1Wrapper(NamedWrapper): - def __init__(self, embedding: Any): - self.__embedding = embedding - super().__init__(embedding) - - def create(self, *args: Any, **kwargs: Any) -> Any: - return EmbeddingWrapper(self.__embedding.with_raw_response.create, None).create(*args, **kwargs) - - -class ModerationV1Wrapper(NamedWrapper): - def __init__(self, moderation: Any): - self.__moderation = moderation - super().__init__(moderation) - - def create(self, *args: Any, **kwargs: Any) -> Any: - return ModerationWrapper(self.__moderation.with_raw_response.create, None).create(*args, **kwargs) - - -class AsyncCompletionsV1Wrapper(NamedWrapper): - def __init__(self, completions: Any): - self.__completions = completions - super().__init__(completions) - - async def create(self, *args: Any, **kwargs: Any) -> Any: - response = await ChatCompletionWrapper(None, self.__completions.with_raw_response.create).acreate( - *args, **kwargs - ) - return AsyncResponseWrapper(response) - - -class AsyncEmbeddingV1Wrapper(NamedWrapper): - def __init__(self, embedding: Any): - self.__embedding = embedding - super().__init__(embedding) - - async def create(self, *args: Any, **kwargs: Any) -> Any: - response = await EmbeddingWrapper(None, self.__embedding.with_raw_response.create).acreate(*args, **kwargs) - return AsyncResponseWrapper(response) - - -class AsyncModerationV1Wrapper(NamedWrapper): - def __init__(self, moderation: Any): - self.__moderation = moderation - super().__init__(moderation) - - async def create(self, *args: Any, **kwargs: Any) -> Any: - response = await ModerationWrapper(None, self.__moderation.with_raw_response.create).acreate(*args, **kwargs) - return AsyncResponseWrapper(response) - - -class ChatV1Wrapper(NamedWrapper): - def __init__(self, chat: Any): - super().__init__(chat) - - import openai - - if type(chat.completions) == openai.resources.chat.completions.AsyncCompletions: - self.completions = AsyncCompletionsV1Wrapper(chat.completions) - else: - self.completions = CompletionsV1Wrapper(chat.completions) - - -class ResponsesV1Wrapper(NamedWrapper): - def __init__(self, responses: Any): - self.__responses = responses - super().__init__(responses) - - def create(self, *args: Any, **kwargs: Any) -> Any: - return ResponseWrapper(self.__responses.with_raw_response.create, None).create(*args, **kwargs) - - def parse(self, *args: Any, **kwargs: Any) -> Any: - return ResponseWrapper(self.__responses.with_raw_response.parse, None, "openai.responses.parse").create(*args, **kwargs) - - -class AsyncResponsesV1Wrapper(NamedWrapper): - def __init__(self, responses: Any): - self.__responses = responses - super().__init__(responses) - - async def create(self, *args: Any, **kwargs: Any) -> Any: - response = await ResponseWrapper(None, self.__responses.with_raw_response.create).acreate(*args, **kwargs) - return AsyncResponseWrapper(response) - - async def parse(self, *args: Any, **kwargs: Any) -> Any: - response = await ResponseWrapper(None, self.__responses.with_raw_response.parse, "openai.responses.parse").acreate(*args, **kwargs) - return AsyncResponseWrapper(response) - - -class BetaCompletionsV1Wrapper(NamedWrapper): - def __init__(self, completions: Any): - self.__completions = completions - super().__init__(completions) - - def parse(self, *args: Any, **kwargs: Any) -> Any: - return ChatCompletionWrapper(self.__completions.parse, None).create(*args, **kwargs) - - -class AsyncBetaCompletionsV1Wrapper(NamedWrapper): - def __init__(self, completions: Any): - self.__completions = completions - super().__init__(completions) - - async def parse(self, *args: Any, **kwargs: Any) -> Any: - response = await ChatCompletionWrapper(None, self.__completions.parse).acreate(*args, **kwargs) - return AsyncResponseWrapper(response) - - -class BetaChatV1Wrapper(NamedWrapper): - def __init__(self, chat: Any): - super().__init__(chat) - - if "AsyncCompletions" in type(chat.completions).__name__: - self.completions = AsyncBetaCompletionsV1Wrapper(chat.completions) - else: - self.completions = BetaCompletionsV1Wrapper(chat.completions) - - -class BetaV1Wrapper(NamedWrapper): - def __init__(self, beta: Any): - super().__init__(beta) - if hasattr(beta, "chat"): - self.chat = BetaChatV1Wrapper(beta.chat) - - -# This wraps 1.*.* versions of the openai module, eg https://github.com/openai/openai-python/tree/v1.1.0 -class OpenAIV1Wrapper(NamedWrapper): - def __init__(self, openai: Any): - super().__init__(openai) - import openai as oai - - self.chat = ChatV1Wrapper(openai.chat) - - if hasattr(openai, "beta"): - self.beta = BetaV1Wrapper(openai.beta) - - if hasattr(openai, "responses"): - if type(openai.responses) == oai.resources.responses.responses.AsyncResponses: - self.responses = AsyncResponsesV1Wrapper(openai.responses) - else: - self.responses = ResponsesV1Wrapper(openai.responses) - - if type(openai.embeddings) == oai.resources.embeddings.AsyncEmbeddings: - self.embeddings = AsyncEmbeddingV1Wrapper(openai.embeddings) - else: - self.embeddings = EmbeddingV1Wrapper(openai.embeddings) - - if type(openai.moderations) == oai.resources.moderations.AsyncModerations: - self.moderations = AsyncModerationV1Wrapper(openai.moderations) - else: - self.moderations = ModerationV1Wrapper(openai.moderations) - - -def wrap_openai(openai: Any): - """ - Wrap the openai module (pre v1) or OpenAI instance (post v1) to add tracing. - If Braintrust is not configured, nothing will be traced. If this is not an - `OpenAI` object, this function is a no-op. - - :param openai: The openai module or OpenAI object - """ - if hasattr(openai, "chat") and hasattr(openai.chat, "completions"): - return OpenAIV1Wrapper(openai) - else: - return OpenAIV0Wrapper(openai) - - -# OpenAI's representation to Braintrust's representation -TOKEN_NAME_MAP = { - # chat API - "total_tokens": "tokens", - "prompt_tokens": "prompt_tokens", - "completion_tokens": "completion_tokens", - # responses API - "tokens": "tokens", - "input_tokens": "prompt_tokens", - "output_tokens": "completion_tokens", -} - -TOKEN_PREFIX_MAP = { - "input": "prompt", - "output": "completion", -} - - -def _parse_metrics_from_usage(usage: Any) -> dict[str, Any]: - # For simplicity, this function handles all the different APIs - metrics = {} - - if not usage: - return metrics - - # This might be a dict or a Usage object that can be cast to a dict - # to a dict - usage = _try_to_dict(usage) - if not isinstance(usage, dict): - return metrics # unexpected - - for oai_name, value in usage.items(): - if oai_name.endswith("_tokens_details"): - # handle `_tokens_detail` dicts - if not isinstance(value, dict): - continue # unexpected - raw_prefix = oai_name[: -len("_tokens_details")] - prefix = TOKEN_PREFIX_MAP.get(raw_prefix, raw_prefix) - for k, v in value.items(): - if is_numeric(v): - metrics[f"{prefix}_{k}"] = v - elif is_numeric(value): - name = TOKEN_NAME_MAP.get(oai_name, oai_name) - metrics[name] = value - - return metrics - - - -def prettify_params(params: dict[str, Any]) -> dict[str, Any]: - # Filter out NOT_GIVEN parameters - # https://linear.app/braintrustdata/issue/BRA-2467 - ret = {k: v for k, v in params.items() if not _is_not_given(v)} - - if "response_format" in ret: - ret["response_format"] = serialize_response_format(ret["response_format"]) - return ret - - -def _try_to_dict(obj: Any) -> dict[str, Any]: - if isinstance(obj, dict): - return obj - # convert a pydantic object to a dict - if hasattr(obj, "model_dump") and callable(obj.model_dump): - try: - return obj.model_dump() - except Exception: - pass - # deprecated pydantic method, try model_dump first. - if hasattr(obj, "dict") and callable(obj.dict): - try: - return obj.dict() - except Exception: - pass - return obj - - -def serialize_response_format(response_format: Any) -> Any: - try: - from pydantic import BaseModel - except ImportError: - return response_format - - if isinstance(response_format, type) and issubclass(response_format, BaseModel): - return dict( - type="json_schema", - json_schema=dict( - name=response_format.__name__, - schema=response_format.model_json_schema(), - ), - ) - else: - return response_format - - -def _is_not_given(value: Any) -> bool: - if value is None: - return False - try: - # Check by type name and repr to avoid import dependency - type_name = type(value).__name__ - return type_name == "NotGiven" - except Exception: - return False - - -def _openai_init_wrapper(wrapped, instance, args, kwargs): - """Wrapper for OpenAI.__init__ that applies tracing after initialization.""" - wrapped(*args, **kwargs) - _apply_openai_wrapper(instance) - - -def patch_openai() -> bool: - """ - Patch OpenAI to add Braintrust tracing globally. - - After calling this, all new OpenAI() and AsyncOpenAI() clients - will automatically have tracing enabled. - - Returns: - True if OpenAI was patched (or already patched), False if OpenAI is not installed. - - Example: - ```python - import braintrust - braintrust.patch_openai() - - import openai - client = openai.OpenAI() - # All calls are now traced! - ``` - """ - try: - import openai - - if getattr(openai, "__braintrust_wrapped__", False): - return True # Already patched - - wrap_function_wrapper("openai", "OpenAI.__init__", _openai_init_wrapper) - wrap_function_wrapper("openai", "AsyncOpenAI.__init__", _openai_init_wrapper) - openai.__braintrust_wrapped__ = True - return True - - except ImportError: - return False - - -def _apply_openai_wrapper(client): - """Apply tracing wrapper to an OpenAI client instance in-place.""" - wrapped = wrap_openai(client) - for attr in ("chat", "responses", "embeddings", "moderations", "beta"): - if hasattr(wrapped, attr): - setattr(client, attr, getattr(wrapped, attr)) diff --git a/py/src/braintrust/object.py b/py/src/braintrust/object.py deleted file mode 100644 index f241a5893..000000000 --- a/py/src/braintrust/object.py +++ /dev/null @@ -1,26 +0,0 @@ -from .generated_types import DatasetEvent - -DEFAULT_IS_LEGACY_DATASET = False - - -def ensure_dataset_record(r: DatasetEvent, legacy: bool) -> DatasetEvent: - if legacy: - return ensure_legacy_dataset_record(r) - else: - return ensure_new_dataset_record(r) - - -def ensure_legacy_dataset_record(r: DatasetEvent) -> DatasetEvent: - if "output" in r: - return r - row = r.copy() - row["output"] = row.pop("expected") - return row - - -def ensure_new_dataset_record(r: DatasetEvent) -> DatasetEvent: - if "expected" in r: - return r - row = r.copy() - row["expected"] = row.pop("output") - return row diff --git a/py/src/braintrust/otel/__init__.py b/py/src/braintrust/otel/__init__.py deleted file mode 100644 index 71648f01f..000000000 --- a/py/src/braintrust/otel/__init__.py +++ /dev/null @@ -1,654 +0,0 @@ -import logging -import os -import warnings -from urllib.parse import urljoin - -INSTALL_ERR_MSG = ( - "OpenTelemetry packages are not installed. " - "Install optional OpenTelemetry dependencies with: pip install braintrust[otel]" -) - -try: - from opentelemetry import trace - from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter - from opentelemetry.sdk.trace.export import BatchSpanProcessor - - OTEL_AVAILABLE = True -except ImportError: - # Don't warn in tests, it's annoying. - if not os.environ.get("PYTEST_VERSION"): - warnings.warn( - INSTALL_ERR_MSG, - UserWarning, - stacklevel=2, - ) - - # Create stub classes if OpenTelemetry is not available - class OTLPSpanExporter: - def __init__(self, *args, **kwargs): - raise ImportError(INSTALL_ERR_MSG) - - class BatchSpanProcessor: - def __init__(self, *args, **kwargs): - raise ImportError(INSTALL_ERR_MSG) - - class trace: - @staticmethod - def get_tracer_provider(): - raise ImportError(INSTALL_ERR_MSG) - - OTEL_AVAILABLE = False - - -FILTER_PREFIXES = ("gen_ai.", "braintrust.", "llm.", "ai.", "traceloop.") - - -class AISpanProcessor: - """ - A span processor that filters spans to only export filtered telemetry. - - Only filtered spans and root spans will be forwarded to the inner processor. - This dramatically reduces telemetry volume while preserving important observability. - - Example: - > processor = AISpanProcessor(BatchSpanProcessor(OTLPSpanExporter())) - > provider = TracerProvider() - > provider.add_span_processor(processor) - """ - - def __init__(self, processor, custom_filter=None): - """ - Initialize the filter span processor. - - Args: - processor: The wrapped span processor that will receive filtered spans - (e.g., BatchSpanProcessor, SimpleSpanProcessor) - custom_filter: Optional callable that takes a span and returns: - True to keep, False to drop, - None to not influence the decision - """ - self._processor = processor - self._custom_filter = custom_filter - - def on_start(self, span, parent_context=None): - """Forward span start events to the inner processor.""" - self._processor.on_start(span, parent_context) - - def on_end(self, span): - """Apply filtering logic and conditionally forward span end events.""" - if self._should_keep_filtered_span(span): - self._processor.on_end(span) - - def shutdown(self): - """Shutdown the inner processor.""" - self._processor.shutdown() - - def force_flush(self, timeout_millis=30000): - """Force flush the inner processor.""" - return self._processor.force_flush(timeout_millis) - - def _should_keep_filtered_span(self, span): - """ - Keep spans if: - 1. Custom filter returns True/False (if provided) - 2. Span name starts with 'gen_ai.', 'braintrust.', 'llm.', 'ai.', or 'traceloop.' - 3. Any attribute name starts with those prefixes - """ - if not span: - return False - - # Apply custom filter if provided - if self._custom_filter: - custom_result = self._custom_filter(span) - if custom_result is True: - return True - elif custom_result is False: - return False - # custom_result is None - continue with default logic - - if span.name.startswith(FILTER_PREFIXES): - return True - - if span.attributes: - for attr_name in span.attributes.keys(): - if attr_name.startswith(FILTER_PREFIXES): - return True - - return False - - -class OtelExporter(OTLPSpanExporter): - """ - A subclass of OTLPSpanExporter configured for Braintrust. - - For most use cases, consider using the Processor class instead, which provides - a more convenient all-in-one interface. - - Environment Variables: - - BRAINTRUST_API_KEY: Your Braintrust API key. - - BRAINTRUST_PARENT: Parent identifier (e.g., "project_name:test"). - - BRAINTRUST_API_URL: Base URL for Braintrust API (defaults to https://api.braintrust.dev). - """ - - def __init__( - self, - url: str | None = None, - api_key: str | None = None, - parent: str | None = None, - headers: dict[str, str] | None = None, - **kwargs, - ): - """ - Initialize the OtelExporter. - - Args: - url: OTLP endpoint URL. Defaults to {BRAINTRUST_API_URL}/otel/v1/traces. - api_key: Braintrust API key. Defaults to BRAINTRUST_API_KEY env var. - parent: Parent identifier (e.g., "project_name:test"). Defaults to BRAINTRUST_PARENT env var. - headers: Additional headers to include in requests. - **kwargs: Additional arguments passed to OTLPSpanExporter. - """ - base_url = os.environ.get("BRAINTRUST_API_URL", "https://api.braintrust.dev") - # Ensure base_url ends with / for proper joining - if not base_url.endswith("/"): - base_url += "/" - endpoint = url or urljoin(base_url, "otel/v1/traces") - api_key = api_key or os.environ.get("BRAINTRUST_API_KEY") - parent = parent or os.environ.get("BRAINTRUST_PARENT") - headers = headers or {} - - if not api_key: - raise ValueError( - "API key is required. Provide it via api_key parameter or BRAINTRUST_API_KEY environment variable." - ) - - # Default parent if not provided - if not parent: - parent = "project_name:default-otel-project" - logging.info( - f"No parent specified, using default: {parent}. " - "Configure with BRAINTRUST_PARENT environment variable or parent parameter." - ) - - exporter_headers = { - "Authorization": f"Bearer {api_key}", - **headers, - } - - if parent: - exporter_headers["x-bt-parent"] = parent - - self.parent = parent - - super().__init__(endpoint=endpoint, headers=exporter_headers, **kwargs) - - -def add_braintrust_span_processor( - tracer_provider, - api_key: str | None = None, - parent: str | None = None, - api_url: str | None = None, - filter_ai_spans: bool = False, - custom_filter=None, - headers: dict[str, str] | None = None, -): - processor = BraintrustSpanProcessor( - api_key=api_key, - parent=parent, - api_url=api_url, - filter_ai_spans=filter_ai_spans, - custom_filter=custom_filter, - headers=headers, - ) - tracer_provider.add_span_processor(processor) - - -class BraintrustSpanProcessor: - """ - A convenient all-in-one span processor for Braintrust OpenTelemetry integration. - - This class combines the OtelExporter, BatchSpanProcessor, and optionally AISpanProcessor - into a single easy-to-use processor that can be directly added to a TracerProvider. - - Example: - > processor = BraintrustSpanProcessor() - > provider.add_span_processor(processor) - - > processor = BraintrustSpanProcessor(filter_ai_spans=True) - > provider.add_span_processor(processor) - """ - - def __init__( - self, - api_key: str | None = None, - parent: str | None = None, - api_url: str | None = None, - filter_ai_spans: bool = False, - custom_filter=None, - headers: dict[str, str] | None = None, - SpanProcessor: type | None = None, - ): - """ - Initialize the BraintrustSpanProcessor. - - Args: - api_key: Braintrust API key. Defaults to BRAINTRUST_API_KEY env var. - parent: Parent identifier (e.g., "project_name:test"). Defaults to BRAINTRUST_PARENT env var. - api_url: Base URL for Braintrust API. Defaults to BRAINTRUST_API_URL env var or https://api.braintrust.dev. - filter_ai_spans: Whether to enable AI span filtering. Defaults to False. - custom_filter: Optional custom filter function for filtering. - headers: Additional headers to include in requests. - SpanProcessor: Optional span processor class (BatchSpanProcessor or SimpleSpanProcessor). Defaults to BatchSpanProcessor. - """ - # Create the exporter - # Convert api_url to the full endpoint URL that OtelExporter expects - exporter_url = None - if api_url: - exporter_url = f"{api_url.rstrip('/')}/otel/v1/traces" - - self._exporter = OtelExporter(url=exporter_url, api_key=api_key, parent=parent, headers=headers) - - # Create the processor chain - if not OTEL_AVAILABLE: - raise ImportError( - "OpenTelemetry packages are not installed. " - "Install optional OpenTelemetry dependencies with: pip install braintrust[otel]" - ) - - if SpanProcessor is None: - SpanProcessor = BatchSpanProcessor - - # Always create a BatchSpanProcessor first - processor = SpanProcessor(self._exporter) - - if filter_ai_spans: - # Wrap the BatchSpanProcessor with filtering - self._processor = AISpanProcessor(processor, custom_filter=custom_filter) - else: - # Use BatchSpanProcessor directly - self._processor = processor - - def on_start(self, span, parent_context=None): - try: - parent_value = None - - # Priority 1: Check if braintrust.parent is in current OTEL context - from opentelemetry import baggage, context - - current_context = context.get_current() - parent_value = context.get_value("braintrust.parent", current_context) - - # Priority 2: Check OTEL baggage (propagates automatically across contexts) - if not parent_value: - parent_value = baggage.get_baggage("braintrust.parent", context=current_context) - - # Priority 3: Check if parent_context has braintrust.parent (backup) - if not parent_value and parent_context: - parent_value = context.get_value("braintrust.parent", parent_context) - - # Priority 4: Check if parent OTEL span has braintrust.parent attribute - if not parent_value and parent_context: - parent_value = self._get_parent_otel_braintrust_parent(parent_context) - - # Set the attribute if we found a parent value - if parent_value: - span.set_attribute("braintrust.parent", parent_value) - - except Exception as e: - # If there's an exception, just don't set braintrust.parent - pass - - self._processor.on_start(span, parent_context) - - def _get_parent_otel_braintrust_parent(self, parent_context): - """Get braintrust.parent attribute from parent OTEL span if it exists.""" - try: - from opentelemetry import trace - - # Get the current span from the parent context - current_span = trace.get_current_span(parent_context) - - if current_span and hasattr(current_span, "attributes") and current_span.attributes: - # Check if parent span has braintrust.parent attribute - attributes = dict(current_span.attributes) - return attributes.get("braintrust.parent") - - return None - - except Exception: - return None - - def on_end(self, span): - """Forward span end events to the inner processor.""" - self._processor.on_end(span) - - def shutdown(self): - """Shutdown the inner processor.""" - self._processor.shutdown() - - def force_flush(self, timeout_millis=30000): - """Force flush the inner processor.""" - return self._processor.force_flush(timeout_millis) - - @property - def exporter(self): - """Access to the underlying OtelExporter.""" - return self._exporter - - @property - def processor(self): - """Access to the underlying span processor.""" - return self._processor - - -def _get_braintrust_parent(object_type, object_id: str | None = None, compute_args: dict | None = None) -> str | None: - """ - Construct a braintrust.parent identifier string from span components. - - Args: - object_type: Type of parent object (PROJECT_LOGS or EXPERIMENT) - object_id: Resolved object ID (project_id or experiment_id) - compute_args: Optional dict with project_name/project_id for unresolved cases - - Returns: - String like "project_id:abc", "project_name:my-proj", "experiment_id:exp-123", or None - """ - from braintrust.span_identifier_v3 import SpanObjectTypeV3 - - if not object_type: - return None - - if object_type == SpanObjectTypeV3.PROJECT_LOGS: - if object_id: - return f"project_id:{object_id}" - elif compute_args: - # Check compute args for project_id or project_name - _id = compute_args.get("project_id") - _name = compute_args.get("project_name") - if _id: - return f"project_id:{_id}" - elif _name: - return f"project_name:{_name}" - elif object_type == SpanObjectTypeV3.EXPERIMENT: - if object_id: - return f"experiment_id:{object_id}" - elif compute_args: - _id = compute_args.get("experiment_id") - if _id: - return f"experiment_id:{_id}" - - return None - -def is_root_span(span) -> bool: - """Returns True if the span is a root span (no parent span).""" - return getattr(span, "parent", None) is None - -def context_from_span_export(export_str: str): - """ - Create an OTEL context from a Braintrust span export string. - - Used for distributed tracing scenarios where a Braintrust span in one service - needs to be the parent of an OTEL span in another service. - - Args: - export_str: The string returned from span.export() - - Returns: - OTEL context that can be used when creating child spans - """ - if not OTEL_AVAILABLE: - raise ImportError(INSTALL_ERR_MSG) - - from braintrust.span_identifier_v4 import SpanComponentsV4 - from opentelemetry import baggage, trace - from opentelemetry.trace import NonRecordingSpan, SpanContext, TraceFlags - - # Parse the export string (handles V3/V4 automatically) - components = SpanComponentsV4.from_str(export_str) - - # Construct braintrust.parent from object_type and object_id - braintrust_parent = _get_braintrust_parent( - object_type=components.object_type, - object_id=components.object_id, - compute_args=components.compute_object_metadata_args, - ) - - # Convert hex strings to OTEL integers - trace_id_int = int(components.root_span_id, 16) - span_id_int = int(components.span_id, 16) - - # Create OTEL SpanContext marked as remote - span_context = SpanContext( - trace_id=trace_id_int, - span_id=span_id_int, - is_remote=True, # Critical: mark as remote for distributed tracing - trace_flags=TraceFlags(TraceFlags.SAMPLED), - ) - - # Create NonRecordingSpan and set in context - non_recording_span = NonRecordingSpan(span_context) - ctx = trace.set_span_in_context(non_recording_span) - - # Set braintrust.parent in OTEL baggage so it propagates automatically - if braintrust_parent: - ctx = baggage.set_baggage("braintrust.parent", braintrust_parent, context=ctx) - - return ctx - - -def add_parent_to_baggage(parent: str, ctx=None): - """ - Add braintrust.parent to OTEL baggage. - - This ensures that when using inject() for distributed tracing, the braintrust.parent - will be propagated via baggage to downstream services. - - Args: - parent: Braintrust parent identifier (e.g., "project_name:my-project", - "project_id:abc123", "experiment_id:exp-456") - ctx: Optional OTEL context to use. If None, uses current context. - - Returns: - Context token that can be used to detach later (optional) - - Example: - >>> from braintrust.otel import add_parent_to_baggage - >>> from opentelemetry.propagate import inject - >>> - >>> # Set braintrust.parent in baggage - >>> add_parent_to_baggage("project_name:my-project") - >>> - >>> # Export headers (will include braintrust.parent in baggage) - >>> headers = {} - >>> inject(headers) - """ - if not OTEL_AVAILABLE: - raise ImportError(INSTALL_ERR_MSG) - - from opentelemetry import baggage, context - - # Set in baggage so it propagates via inject() - new_ctx = baggage.set_baggage("braintrust.parent", parent, context=ctx) - token = context.attach(new_ctx) - return token - - -def add_span_parent_to_baggage(span, ctx=None): - """ - Copy braintrust.parent from span attribute to OTEL baggage. - - BraintrustSpanProcessor automatically sets braintrust.parent as a span attribute - when OTEL spans are created within Braintrust contexts. This function copies that - attribute to OTEL baggage so it propagates when using inject() for distributed tracing. - - Args: - span: OTEL span that has braintrust.parent attribute set - ctx: Optional OTEL context to use. If None, uses current context. - - Returns: - Context token that can be used to detach later (optional) - - Example: - >>> from braintrust.otel import add_span_parent_to_baggage - >>> from opentelemetry.propagate import inject - >>> - >>> with tracer.start_as_current_span("service_b") as span: - >>> # Copy braintrust.parent from span attribute to baggage - >>> add_span_parent_to_baggage(span) - >>> - >>> # Export headers (will include braintrust.parent in baggage) - >>> headers = {} - >>> inject(headers) - """ - if not OTEL_AVAILABLE: - raise ImportError(INSTALL_ERR_MSG) - - # Get braintrust.parent from span attributes - if not span or not hasattr(span, "attributes") or not span.attributes: - logging.warning("add_span_parent_to_baggage: span has no attributes") - return None - - parent_value = span.attributes.get("braintrust.parent") - if not parent_value: - logging.warning( - "add_span_parent_to_baggage: braintrust.parent attribute not found. " - "Ensure BraintrustSpanProcessor is configured or span is created within Braintrust context." - ) - return None - - # Use add_parent_to_baggage to set in baggage - return add_parent_to_baggage(parent_value, ctx=ctx) - - -def parent_from_headers(headers: dict[str, str], propagator=None) -> str | None: - """ - Extract a Braintrust-compatible parent string from trace context headers. - - This converts OTEL trace context headers into a format that can be passed - as the 'parent' parameter to Braintrust's start_span() method. - - Args: - headers: Dictionary with trace context headers (e.g., 'traceparent'/'baggage' for W3C) - propagator: Optional custom TextMapPropagator. If not provided, uses the - globally registered propagator (W3C TraceContext by default). - - Returns: - Braintrust V4 export string that can be used as parent parameter, - or None if no valid span context is found or braintrust.parent is missing. - - When None is returned due to missing braintrust.parent, a warning is logged. - The OTEL span should set braintrust.parent in baggage to specify the target project. - - Example: - >>> # Service C receives headers from Service B - >>> headers = {'traceparent': '00-trace_id-span_id-01', 'baggage': '...'} - >>> parent = parent_from_headers(headers) - >>> with project.start_span(name="service_c", parent=parent) as span: - >>> span.log(input="BT span as child of OTEL parent") - - >>> # Using a custom propagator (e.g., B3 format) - >>> from opentelemetry.propagators.b3 import B3MultiFormat - >>> propagator = B3MultiFormat() - >>> headers = {'X-B3-TraceId': '...', 'X-B3-SpanId': '...', 'baggage': '...'} - >>> parent = parent_from_headers(headers, propagator=propagator) - """ - if not OTEL_AVAILABLE: - raise ImportError(INSTALL_ERR_MSG) - - from braintrust.span_identifier_v4 import SpanComponentsV4 - from opentelemetry import baggage, trace - from opentelemetry.propagate import extract - - # Extract context from headers using provided propagator or global propagator - if propagator is not None: - ctx = propagator.extract(headers) - else: - ctx = extract(headers) - - # Get span from context - span = trace.get_current_span(ctx) - if not span or not hasattr(span, "get_span_context"): - logging.error("parent_from_headers: No valid span found in headers") - return None - - span_context = span.get_span_context() - if not span_context or span_context.span_id == 0: - logging.error("parent_from_headers: Invalid span context (span_id is 0)") - return None - - # Convert OTEL IDs to hex strings - trace_id_hex = format(span_context.trace_id, "032x") - span_id_hex = format(span_context.span_id, "016x") - - # Validate trace_id and span_id are not all zeros - if trace_id_hex == "00000000000000000000000000000000": - logging.error("parent_from_headers: Invalid trace_id (all zeros)") - return None - if span_id_hex == "0000000000000000": - logging.error("parent_from_headers: Invalid span_id (all zeros)") - return None - - # Get braintrust.parent from baggage if present - braintrust_parent = baggage.get_baggage("braintrust.parent", context=ctx) - - # Parse braintrust.parent to extract object_type and object_id - object_type = None - object_id = None - compute_args = None - - if not braintrust_parent: - logging.warning( - "braintrust.parent not found in OTEL baggage. " - "Cannot create Braintrust parent without project information. " - "Ensure the OTEL span sets braintrust.parent in baggage before exporting headers." - ) - return None - - if braintrust_parent: - from braintrust.span_identifier_v3 import SpanObjectTypeV3 - - # Parse braintrust.parent format: "project_id:abc", "project_name:xyz", or "experiment_id:123" - if braintrust_parent.startswith("project_id:"): - object_type = SpanObjectTypeV3.PROJECT_LOGS - object_id = braintrust_parent[len("project_id:") :] - if not object_id: - logging.error( - f"parent_from_headers: Invalid braintrust.parent format (empty project_id): {braintrust_parent}" - ) - return None - elif braintrust_parent.startswith("project_name:"): - object_type = SpanObjectTypeV3.PROJECT_LOGS - project_name = braintrust_parent[len("project_name:") :] - if not project_name: - logging.error( - f"parent_from_headers: Invalid braintrust.parent format (empty project_name): {braintrust_parent}" - ) - return None - compute_args = {"project_name": project_name} - elif braintrust_parent.startswith("experiment_id:"): - object_type = SpanObjectTypeV3.EXPERIMENT - object_id = braintrust_parent[len("experiment_id:") :] - if not object_id: - logging.error( - f"parent_from_headers: Invalid braintrust.parent format (empty experiment_id): {braintrust_parent}" - ) - return None - else: - logging.error( - f"parent_from_headers: Invalid braintrust.parent format: {braintrust_parent}. " - "Expected format: 'project_id:ID', 'project_name:NAME', or 'experiment_id:ID'" - ) - return None - - # Create SpanComponentsV4 and export as string - # Set row_id to enable span_id/root_span_id (required for parent linking) - components = SpanComponentsV4( - object_type=object_type, - object_id=object_id, - compute_object_metadata_args=compute_args, - row_id="otel", # Dummy row_id to enable span_id/root_span_id fields - span_id=span_id_hex, - root_span_id=trace_id_hex, - ) - - return components.to_str() diff --git a/py/src/braintrust/otel/context.py b/py/src/braintrust/otel/context.py deleted file mode 100644 index 4299c619e..000000000 --- a/py/src/braintrust/otel/context.py +++ /dev/null @@ -1,114 +0,0 @@ -"""Unified context management using OTEL's built-in context.""" - -import logging -from typing import Any, Optional - -from braintrust.context import ParentSpanIds, SpanInfo -from braintrust.logger import Span -from opentelemetry import context, trace -from opentelemetry.trace import SpanContext, TraceFlags - -log = logging.getLogger(__name__) - - -class ContextManager: - """Context manager that uses OTEL's built-in context as single storage.""" - - def __init__(self): - pass - - def get_current_span_info(self) -> Optional["SpanInfo"]: - """Get information about the currently active span from OTEL context.""" - - # Get the current span from OTEL context - current_span = trace.get_current_span() - if not current_span: - return None - - if not _is_otel_span(current_span): - # FIXME[matt] This should never happen, but we'll handle it anyway - return None - - span_context = current_span.get_span_context() - if span_context and span_context.span_id != 0: - # Always prioritize the actual current OTEL span over stored BT span - # Only use stored BT span if the current OTEL span IS the BT span wrapper - bt_span = context.get_value("braintrust_span") - - # If there's a BT span stored AND the current OTEL span is a NonRecordingSpan - # (which means it's our BT->OTEL wrapper), then return BT span info - if bt_span and isinstance(current_span, trace.NonRecordingSpan): - return SpanInfo(trace_id=bt_span.root_span_id, span_id=bt_span.span_id, span_object=bt_span) - else: - # Return OTEL span info - this is a real OTEL span, not our wrapper - otel_trace_id = format(span_context.trace_id, "032x") - otel_span_id = format(span_context.span_id, "016x") - return SpanInfo(trace_id=otel_trace_id, span_id=otel_span_id, span_object=current_span) - - return None - - def set_current_span(self, span: Span) -> Any: - """Set the current active span in OTEL context.""" - from opentelemetry import context, trace - - if hasattr(span, "get_span_context"): - # This is an OTEL span - it will manage its own context - return None - else: - try: - trace_id_int = int(span.root_span_id, 16) - except ValueError: - log.debug(f"Invalid root_span_id: {span.root_span_id}") - return None - - try: - span_id_int = int(span.span_id, 16) - except ValueError: - log.debug(f"Invalid span_id: {span.span_id}") - return None - - # This is a BT span - store it in OTEL context AND set as current OTEL span - # First store the BT span - ctx = context.set_value("braintrust_span", span) - parent_value = span._get_otel_parent() - ctx = context.set_value("braintrust.parent", parent_value, ctx) - - otel_span_context = SpanContext( - trace_id=trace_id_int, span_id=span_id_int, is_remote=False, trace_flags=TraceFlags(TraceFlags.SAMPLED) - ) - - # Create a non-recording span to represent the BT span in OTEL context - non_recording_span = trace.NonRecordingSpan(otel_span_context) - - # Set this as the current OTEL span - ctx = context.set_value(trace._SPAN_KEY, non_recording_span, ctx) - token = context.attach(ctx) - # Return the token for the caller to store - return token - - def unset_current_span(self, context_token: Any = None) -> None: - """Unset the current active span from OTEL context.""" - from opentelemetry import context - - if context_token: - # Detaching the token restores the previous context - context.detach(context_token) - else: - # No token means we need to explicitly clear the span - # This shouldn't normally happen, but handle it gracefully - context.attach(context.set_value("braintrust_span", None)) - - def get_parent_span_ids(self) -> ParentSpanIds | None: - """Get parent information for creating a new BT span.""" - span_info = self.get_current_span_info() - if not span_info: - return None - return ParentSpanIds( - root_span_id=span_info.trace_id, - span_parents=[span_info.span_id], - ) - - -def _is_otel_span(span: Any) -> bool: - """Check if the span object is an OTEL span.""" - return hasattr(span, "get_span_context") diff --git a/py/src/braintrust/otel/test_distributed_tracing.py b/py/src/braintrust/otel/test_distributed_tracing.py deleted file mode 100644 index 2610f81b5..000000000 --- a/py/src/braintrust/otel/test_distributed_tracing.py +++ /dev/null @@ -1,150 +0,0 @@ -""" -Unit tests for distributed tracing between Braintrust and OpenTelemetry. - -Tests simulated cross-service/cross-process scenarios where trace context -is exported from one service and imported in another service. -""" - -import os - -import pytest -from braintrust.logger import _internal_with_memory_background_logger -from braintrust.otel import BraintrustSpanProcessor, context_from_span_export -from braintrust.test_helpers import init_test_logger, preserve_env_vars - -OTEL_AVAILABLE = True -try: - from opentelemetry.sdk.trace import TracerProvider - from opentelemetry.sdk.trace.export import SimpleSpanProcessor - from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter -except ImportError: - - class InMemorySpanExporter: - def __init__(self): - pass - - def get_finished_spans(self): - return [] - - def clear(self): - pass - - OTEL_AVAILABLE = False - -from dataclasses import dataclass - - -@dataclass -class OtelFixture: - tracer: object - exporter: InMemorySpanExporter - memory_logger: object - - -@pytest.fixture -def otel_fixture(): - """OTEL fixture for distributed tracing tests with memory exporters.""" - if not OTEL_AVAILABLE: - pytest.skip("OpenTelemetry not installed") - - with preserve_env_vars("BRAINTRUST_OTEL_COMPAT", "BRAINTRUST_API_KEY"): - # Enable OTEL compatibility mode - os.environ["BRAINTRUST_OTEL_COMPAT"] = "true" - os.environ["BRAINTRUST_API_KEY"] = "test-api-key-for-fixture" - - # Set up memory logger for BT spans - with _internal_with_memory_background_logger() as memory_logger: - # Set up OTEL components - parent = "project_name:distributed-tracing-test" - exporter = InMemorySpanExporter() - processor = SimpleSpanProcessor(exporter) - - # Wrap with BraintrustSpanProcessor to handle braintrust.parent - btsp = BraintrustSpanProcessor(parent=parent) - btsp._processor = processor - - tp = TracerProvider() - tp.add_span_processor(btsp) - tracer = tp.get_tracer("distributed-tracing-test") - - fixture = OtelFixture(exporter=exporter, tracer=tracer, memory_logger=memory_logger) - yield fixture - tp.shutdown() - - -def test_bt_to_otel_simple_distributed_trace(otel_fixture): - """ - Test simple distributed trace: BT span in Service A, OTEL span in Service B. - - Simulates: - - Service A: Creates BT span, exports context - - Service B: Imports context, creates OTEL child span - - Verifies exported spans have: - - Unified trace_id - - Correct parent relationship - - braintrust.parent attribute - """ - project_name = "service-a-project" - tracer = otel_fixture.tracer - otel_exporter = otel_fixture.exporter - memory_logger = otel_fixture.memory_logger - - logger = init_test_logger(project_name) - - # ===== Service A: Create BT span and export ===== - with logger.start_span(name="service_a_span") as service_a_span: - # Export context for sending to Service B - exported_context = service_a_span.export() - - service_a_trace_id = service_a_span.root_span_id - service_a_span_id = service_a_span.span_id - - # ===== Service B: Import context and create OTEL child span ===== - # Simulate receiving exported_context over network (e.g., in HTTP header) - from opentelemetry import context as otel_context - - ctx = context_from_span_export(exported_context) - - # Attach the context to make it current, then create the span - token = otel_context.attach(ctx) - try: - with tracer.start_as_current_span("service_b_span") as service_b_span: - service_b_span.set_attribute("service", "service_b") - finally: - otel_context.detach(token) - - # ===== Verify exported spans ===== - bt_spans = memory_logger.pop() - assert len(bt_spans) == 1, "Should have 1 BT span from Service A" - - otel_spans = otel_exporter.get_finished_spans() - assert len(otel_spans) == 1, "Should have 1 OTEL span from Service B" - - # Get the spans - service_a_exported = bt_spans[0] - service_b_exported = otel_spans[0] - - # Convert OTEL IDs to hex for comparison - service_b_trace_id = format(service_b_exported.context.trace_id, "032x") - service_b_parent_span_id = format(service_b_exported.parent.span_id, "016x") if service_b_exported.parent else None - - # Assert unified trace ID - assert service_a_trace_id == service_b_trace_id, ( - f"Trace IDs should match: {service_a_trace_id} != {service_b_trace_id}" - ) - - # Assert Service B span has Service A span as parent - assert service_b_parent_span_id == service_a_span_id, ( - f"Service B parent should be Service A span: {service_b_parent_span_id} != {service_a_span_id}" - ) - - # Assert braintrust.parent attribute is set on OTEL span - assert "braintrust.parent" in service_b_exported.attributes, "OTEL span should have braintrust.parent attribute" - assert service_b_exported.attributes["braintrust.parent"] == f"project_name:{project_name}", ( - f"braintrust.parent should be 'project_name:{project_name}'" - ) - - -if __name__ == "__main__": - pytest.main([__file__, "-v"]) diff --git a/py/src/braintrust/otel/test_otel_bt_integration.py b/py/src/braintrust/otel/test_otel_bt_integration.py deleted file mode 100644 index 9ca1acc9a..000000000 --- a/py/src/braintrust/otel/test_otel_bt_integration.py +++ /dev/null @@ -1,374 +0,0 @@ -""" -Unit tests for OTEL + Braintrust context integration using memory exporters. - -Tests that OTEL and Braintrust spans are properly grouped in unified traces -when created in mixed contexts. -""" - -import os - -import pytest -from braintrust import current_span -from braintrust.logger import _internal_with_memory_background_logger -from braintrust.otel import BraintrustSpanProcessor -from braintrust.test_helpers import init_test_exp, init_test_logger, preserve_env_vars - -OTEL_AVAILABLE = True -try: - from opentelemetry.sdk.trace import TracerProvider - from opentelemetry.sdk.trace.export import SimpleSpanProcessor - from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter -except ImportError: - - class InMemorySpanExporter: - def __init__(self): - pass - - def get_finished_spans(self): - return [] - - def clear(self): - pass - - OTEL_AVAILABLE = False - -from dataclasses import dataclass - - -@dataclass -class OtelFixture: - tracer: object - exporter: InMemorySpanExporter - memory_logger: object - - -@pytest.fixture -def otel_fixture(): - """otel fixture configures everything we need to run mixed otel/bt tracing tests - that export to memory. - """ - if not OTEL_AVAILABLE: - pytest.skip("OpenTelemetry not installed") - - with preserve_env_vars("BRAINTRUST_OTEL_COMPAT", "BRAINTRUST_API_KEY"): - # 1. Set environment variable first - os.environ["BRAINTRUST_OTEL_COMPAT"] = "true" - # Set dummy API key for tests - os.environ["BRAINTRUST_API_KEY"] = "test-api-key-for-fixture" - - # 2. Set up memory logger with proper context manager - with _internal_with_memory_background_logger() as memory_logger: - # 3. Set up OTEL components - parent = "project_name:otel-fixture-test" - exporter = InMemorySpanExporter() - processor = SimpleSpanProcessor(exporter) - - # FIXME[matt]: this is a hack to get the test to pass. Refactor BraintrustSpanProcessor to use - # an instance of the processor instead of the exporter - btsp = BraintrustSpanProcessor(parent=parent) - btsp._processor = processor - - tp = TracerProvider() - tp.add_span_processor(btsp) - tracer = tp.get_tracer("otel-fixture-test") - - fixture = OtelFixture(exporter=exporter, tracer=tracer, memory_logger=memory_logger) - yield fixture - tp.shutdown() - - -def test_mixed_otel_bt_tracing_with_bt_logger_first(otel_fixture): - project_name = "mixed-tracing-with-bt-logger-first" - tracer = otel_fixture.tracer - otel_mem_exporter = otel_fixture.exporter - memory_logger = otel_fixture.memory_logger - - logger = init_test_logger(project_name) - - with logger.start_span(name="1") as span1: - assert current_span() == span1 - with tracer.start_as_current_span("2"): - with logger.start_span(name="3") as span3: - assert current_span() == span3 - pass - - bt_spans = memory_logger.pop() - assert len(bt_spans) == 2 - bt_spans_by_name = {span["span_attributes"]["name"]: span for span in bt_spans} - - otel_spans = otel_mem_exporter.get_finished_spans() - assert len(otel_spans) == 1 - otel_spans_by_name = {span.name: span for span in otel_spans} - for span in otel_spans: - assert span.attributes["braintrust.parent"] == f"project_name:{project_name}" - - # All spans accounted for - assert len(bt_spans_by_name) + len(otel_spans_by_name) == 3 - - s1, s3 = bt_spans_by_name["1"], bt_spans_by_name["3"] - s2 = otel_spans_by_name["2"] - - # Verify unified trace IDs - convert OTEL trace to hex string for comparison - s2_trace_id = format(s2.context.trace_id, "032x") - s2_span_id = format(s2.context.span_id, "016x") - - assert s1["root_span_id"] == s2_trace_id - assert s1["root_span_id"] == s3["root_span_id"] - assert s2_trace_id == s3["root_span_id"] - - # Verify parent relationships - assert s3["span_parents"] == [s2_span_id] - assert s2_span_id in s3["span_parents"] - - -def test_mixed_otel_bt_tracing_with_experiment_parent(otel_fixture): - experiment = init_test_exp("otel-bt-mixed", "test-mixed-tracing-experiment") - tracer = otel_fixture.tracer - otel_memory_exporter = otel_fixture.exporter - memory_logger = otel_fixture.memory_logger - - with experiment.start_span(name="1") as span1: - assert current_span() == span1 - with tracer.start_as_current_span("2"): - with experiment.start_span(name="3") as span3: - assert current_span() == span3 - - bt_spans = memory_logger.pop() - assert len(bt_spans) == 2 - - otel_spans = otel_memory_exporter.get_finished_spans() - assert len(otel_spans) == 1 - - # Create one dict of spans by name - spans_by_name = {} - for span in bt_spans: - spans_by_name[span["span_attributes"]["name"]] = span - for span in otel_spans: - spans_by_name[span.name] = span - - assert len(spans_by_name) == 3 - - s1, s2, s3 = spans_by_name["1"], spans_by_name["2"], spans_by_name["3"] - - # Verify unified trace IDs - convert OTEL trace to hex string for comparison - s2_trace_id = format(s2.context.trace_id, "032x") - s2_span_id = format(s2.context.span_id, "016x") - - assert s1["root_span_id"] == s2_trace_id - assert s1["root_span_id"] == s3["root_span_id"] - assert s2_trace_id == s3["root_span_id"] - - # Verify parent relationships - assert s3["span_parents"] == [s2_span_id] - assert s2_span_id in s3["span_parents"] - - -def test_mixed_otel_bt_tracing_with_otel_first(otel_fixture): - logger = init_test_logger(__name__) - tracer = otel_fixture.tracer - otel_memory_exporter = otel_fixture.exporter - memory_logger = otel_fixture.memory_logger - - with tracer.start_as_current_span("1"): - with logger.start_span(name="2") as span2: - assert current_span() == span2 - with tracer.start_as_current_span("3"): - pass - - bt_spans = memory_logger.pop() - assert len(bt_spans) == 1 - - otel_spans = otel_memory_exporter.get_finished_spans() - assert len(otel_spans) == 2 - - # Create one dict of spans by name - spans_by_name = {} - for span in bt_spans: - spans_by_name[span["span_attributes"]["name"]] = span - for span in otel_spans: - spans_by_name[span.name] = span - - assert len(spans_by_name) == 3 - - s1, s2, s3 = spans_by_name["1"], spans_by_name["2"], spans_by_name["3"] - - # Verify unified trace IDs - convert OTEL traces to hex string for comparison - s1_trace_id = format(s1.context.trace_id, "032x") - s1_span_id = format(s1.context.span_id, "016x") - s3_trace_id = format(s3.context.trace_id, "032x") - s3_span_id = format(s3.context.span_id, "016x") - - assert s1_trace_id == s2["root_span_id"] - assert s1_trace_id == s3_trace_id - assert s2["root_span_id"] == s3_trace_id - - # Verify parent relationships - BT span should have OTEL span as parent - assert s2["span_parents"] == [s1_span_id] - assert s1_span_id in s2["span_parents"] - - -def test_separate_traces_should_not_be_unified(otel_fixture): - """Test that separate, non-nested traces should remain separate (this should currently FAIL).""" - logger = init_test_logger(__name__) - tracer = otel_fixture.tracer - memory_logger = otel_fixture.memory_logger - - # First trace: BT only - trace1_spans = [] - with logger.start_span(name="bt_trace1") as bt_span1: - trace1_spans.append(bt_span1.root_span_id) - bt_span1.log(input="First trace") - - # Second trace: OTEL only - trace2_spans = [] - with tracer.start_as_current_span("otel_trace2") as otel_span2: - trace2_id = format(otel_span2.context.trace_id, "032x") - trace2_spans.append(trace2_id) - otel_span2.set_attribute("test", "second_trace") - - # Third trace: OTEL root with BT child - trace3_spans = [] - with tracer.start_as_current_span("otel_trace3_root") as otel_span3: - otel3_trace_id = format(otel_span3.context.trace_id, "032x") - trace3_spans.append(otel3_trace_id) - - # BT span inside OTEL - should inherit OTEL trace ID, not previous BT trace - with logger.start_span(name="bt_inside_otel3") as bt_span3: - trace3_spans.append(bt_span3.root_span_id) - - # Verify we have 3 separate traces - all_trace_ids = trace1_spans + trace2_spans + trace3_spans - assert len(set(all_trace_ids)) == 3 - - # Verify each trace has different root_span_id/trace_id - trace1_id = trace1_spans[0] - trace2_id = trace2_spans[0] - trace3_id = trace3_spans[0] - - assert trace1_id != trace2_id - assert trace1_id != trace3_id - assert trace2_id != trace3_id - - # Specifically check that trace3 BT span uses OTEL trace ID, not trace1 BT trace ID - assert trace3_spans[0] == trace3_spans[1] - assert trace1_spans[0] != trace3_spans[1] - - -def test_otel_spans_inherit_parent_attribute(otel_fixture): - """Test that OTEL spans created inside BT contexts get braintrust.parent attribute.""" - test_cases = [ - ("exp-666", "experiment_id:exp-666", lambda parent_name: init_test_exp(parent_name, "test-project")), - ("name-777", "project_name:name-777", lambda parent_name: init_test_logger(parent_name)), - ] - - tracer = otel_fixture.tracer - otel_memory_exporter = otel_fixture.exporter - memory_logger = otel_fixture.memory_logger - - for parent_name, expected_parent, parent_factory in test_cases: - parent = parent_factory(parent_name) - otel_memory_exporter.clear() - - with parent.start_span(name=f"bt_{parent_name}_span"): - with tracer.start_as_current_span("otel_child"): - with tracer.start_as_current_span("otel_child2"): - pass - - otel_spans = otel_memory_exporter.get_finished_spans() - assert len(otel_spans) == 2 - - for span in otel_spans: - attrs = dict(span.attributes or {}) - assert "braintrust.parent" in attrs - assert attrs["braintrust.parent"] == expected_parent - - bt_spans = memory_logger.pop() - assert len(bt_spans) == 1 - - -def test_uses_braintrust_context_manager_when_otel_disabled(): - """Test that BraintrustContextManager is used when OTEL is not enabled.""" - # Ensure OTEL is disabled - os.environ.pop("BRAINTRUST_OTEL_COMPAT", None) - - try: - from braintrust.context import get_context_manager - - cm = get_context_manager() - - # Should be BraintrustContextManager, not OTEL ContextManager - assert type(cm).__name__ == "BraintrustContextManager" - - # Verify it has the expected interface - assert hasattr(cm, "get_current_span_info") - assert hasattr(cm, "get_parent_span_ids") - assert hasattr(cm, "set_current_span") - assert hasattr(cm, "unset_current_span") - - finally: - # Clean up - remove any environment variable we might have set - os.environ.pop("BRAINTRUST_OTEL_COMPAT", None) - - -def test_uses_otel_context_manager_when_enabled(): - """Test that OTEL ContextManager is used when BRAINTRUST_OTEL_COMPAT=1.""" - if not OTEL_AVAILABLE: - pytest.skip("OpenTelemetry not installed") - - with preserve_env_vars("BRAINTRUST_OTEL_COMPAT"): - # Enable OTEL - os.environ["BRAINTRUST_OTEL_COMPAT"] = "true" - - from braintrust.context import get_context_manager - - cm = get_context_manager() - - # Should be OTEL ContextManager, not BraintrustContextManager - assert type(cm).__name__ == "ContextManager" - - # Verify it has the expected interface - assert hasattr(cm, "get_current_span_info") - assert hasattr(cm, "get_parent_span_ids") - assert hasattr(cm, "set_current_span") - assert hasattr(cm, "unset_current_span") - - -def test_bt_span_without_explicit_parent_inherits_from_otel(otel_fixture): - """Test that a BT span created without explicit parent inherits from OTEL context. - - This test specifically exercises get_parent_span_ids() which should - retrieve parent information from the OTEL context manager. - """ - logger = init_test_logger(__name__) - tracer = otel_fixture.tracer - otel_memory_exporter = otel_fixture.exporter - memory_logger = otel_fixture.memory_logger - - # Create an OTEL span, then create a BT span WITHOUT using start_span's parent parameter - with tracer.start_as_current_span("otel_parent") as otel_span: - # Create BT span without explicit parent - should inherit from OTEL context - bt_span = logger.start_span(name="bt_child") - bt_span.end() - - bt_spans = memory_logger.pop() - assert len(bt_spans) == 1 - - otel_spans = otel_memory_exporter.get_finished_spans() - assert len(otel_spans) == 1 - - bt_child = bt_spans[0] - otel_parent = otel_spans[0] - - # Convert OTEL IDs to hex for comparison - otel_trace_id = format(otel_parent.context.trace_id, "032x") - otel_span_id = format(otel_parent.context.span_id, "016x") - - # BT span should have inherited OTEL parent's trace ID as root_span_id - assert bt_child["root_span_id"] == otel_trace_id - - # BT span should have OTEL span as parent - assert bt_child["span_parents"] == [otel_span_id] - - -if __name__ == "__main__": - pytest.main([__file__, "-v"]) diff --git a/py/src/braintrust/parameters.py b/py/src/braintrust/parameters.py deleted file mode 100644 index 9af61b7f3..000000000 --- a/py/src/braintrust/parameters.py +++ /dev/null @@ -1,155 +0,0 @@ -"""Evaluation parameters support for Python SDK.""" - -from typing import Any, TypedDict - -from typing_extensions import NotRequired - -from .logger import Prompt -from .prompt import PromptData - - -class PromptParameter(TypedDict): - """A prompt parameter specification.""" - - type: str # Literal["prompt"] but using str for flexibility - default: NotRequired[PromptData | None] - description: NotRequired[str | None] - - -# EvalParameters is a dict where values can be either: -# - A PromptParameter (dict with type="prompt") -# - A pydantic model class (typed as Any for now) -EvalParameters = dict[str, PromptParameter | Any] - - -def _pydantic_to_json_schema(model: Any) -> dict[str, Any]: - """Convert a pydantic model to JSON schema.""" - if hasattr(model, "model_json_schema"): - # pydantic 2 - return model.model_json_schema() - elif hasattr(model, "schema"): - # pydantic 1 - return model.schema() - else: - raise ValueError(f"Cannot convert {model} to JSON schema - not a pydantic model") - - -def validate_parameters( - parameters: dict[str, Any], - parameter_schema: EvalParameters, -) -> dict[str, Any]: - """ - Validate parameters against the schema. - - Args: - parameters: The parameters to validate - parameter_schema: The schema to validate against - - Returns: - Validated parameters - - Raises: - ValueError: If validation fails - """ - result = {} - - for name, schema in parameter_schema.items(): - value = parameters.get(name) - - try: - if isinstance(schema, dict) and schema.get("type") == "prompt": - # Handle prompt parameter - prompt_data = None - if value is not None: - # TODO: Validate that value is a valid PromptData - prompt_data = value - elif schema.get("default") is not None: - prompt_data = schema["default"] - else: - raise ValueError(f"Parameter '{name}' is required") - result[name] = Prompt.from_prompt_data(schema.get("name"), PromptData.from_dict_deep(prompt_data)) - elif schema is None: - # No schema defined, pass through the value - result[name] = value - else: - # Check if it's a pydantic model - if hasattr(schema, "parse_obj") or hasattr(schema, "model_validate"): - # Check if this is a single-field validator model - # Support both Pydantic v1 (__fields__) and v2 (model_fields) - fields = getattr(schema, "__fields__", None) or getattr(schema, "model_fields", {}) - if len(fields) == 1 and "value" in fields: - # This is a single-field validator, validate the value directly - if value is None: - # Try to get default value - try: - if hasattr(schema, "__call__"): - default_instance = schema() - result[name] = default_instance.value - else: - raise ValueError(f"Parameter '{name}' is required") - except Exception: - raise ValueError(f"Parameter '{name}' is required") - else: - # Validate by creating a model instance with the value - if hasattr(schema, "parse_obj"): - validated = schema.parse_obj({"value": value}) - else: - validated = schema.model_validate({"value": value}) - result[name] = validated.value - else: - # Regular pydantic model - if value is None: - # No value provided, try to create default instance - if hasattr(schema, "__call__"): - result[name] = schema() - else: - raise ValueError(f"Parameter '{name}' is required") - elif hasattr(schema, "parse_obj"): - # pydantic v1 - result[name] = schema.parse_obj(value) - elif hasattr(schema, "model_validate"): - # pydantic v2 - result[name] = schema.model_validate(value) - else: - # Not a pydantic model, just pass through - result[name] = value - - except Exception as e: - raise ValueError(f"Invalid parameter '{name}': {str(e)}") - - return result - - -def parameters_to_json_schema(parameters: EvalParameters) -> dict[str, Any]: - """ - Convert EvalParameters to JSON schema format for serialization. - - Args: - parameters: The parameters to convert - - Returns: - JSON schema representation - """ - result = {} - - for name, schema in parameters.items(): - if isinstance(schema, dict) and schema.get("type") == "prompt": - # Prompt parameter - result[name] = { - "type": "prompt", - "default": schema.get("default"), - "description": schema.get("description"), - } - else: - # Pydantic model - try: - result[name] = { - "type": "data", - "schema": _pydantic_to_json_schema(schema), - # TODO: Extract default and description from pydantic model - } - except ValueError: - # Not a pydantic model, skip - pass - - return result diff --git a/py/src/braintrust/prompt.py b/py/src/braintrust/prompt.py deleted file mode 100644 index 242cee435..000000000 --- a/py/src/braintrust/prompt.py +++ /dev/null @@ -1,84 +0,0 @@ -from dataclasses import dataclass -from typing import Literal, Union - -from .generated_types import PromptOptions -from .serializable_data_class import SerializableDataClass - -# Keep these definitions in sync with sdk/core/js/typespecs/prompt.ts. - - -@dataclass -class PromptCompletionBlock(SerializableDataClass): - content: str - type: Literal["completion"] = "completion" - - -@dataclass -class FunctionCall(SerializableDataClass): - name: str - arguments: str - - -@dataclass -class ToolCall(SerializableDataClass): - id: str - function: FunctionCall - type: Literal["function"] = "function" - - -@dataclass -class TextPart(SerializableDataClass): - text: str - type: Literal["text"] = "text" - - -@dataclass -class ImageURL(SerializableDataClass): - url: str - detail: Literal["auto", "low", "high"] = "auto" - - -@dataclass -class ImagePart(SerializableDataClass): - image_url: ImageURL - type: Literal["image_url"] = "image_url" - - -@dataclass -class PromptMessage(SerializableDataClass): - content: str | list[TextPart | ImagePart] - role: Literal["system", "user", "assistant", "function", "tool", "model"] - name: str | None = None - function_call: str | FunctionCall | None = None - tool_calls: list[ToolCall] | None = None - - -@dataclass -class PromptChatBlock(SerializableDataClass): - messages: list[PromptMessage] - tools: str | None = None - type: Literal["chat"] = "chat" - - -PromptBlockData = Union[PromptCompletionBlock, PromptChatBlock] - - -@dataclass -class PromptData(SerializableDataClass): - prompt: PromptBlockData | None = None - options: PromptOptions | None = None - - -@dataclass -class PromptSchema(SerializableDataClass): - id: str | None - project_id: str | None - _xact_id: str | None - name: str - slug: str - description: str | None - prompt_data: PromptData - tags: list[str] | None - - -BRAINTRUST_PARAMS = ["use_cache"] diff --git a/py/src/braintrust/prompt_cache/__init__.py b/py/src/braintrust/prompt_cache/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/py/src/braintrust/prompt_cache/disk_cache.py b/py/src/braintrust/prompt_cache/disk_cache.py deleted file mode 100644 index 3bf400efb..000000000 --- a/py/src/braintrust/prompt_cache/disk_cache.py +++ /dev/null @@ -1,154 +0,0 @@ -""" -A module providing a persistent disk-based cache implementation. - -This module contains a generic disk cache that can store serializable objects of any type. -The cache persists entries as compressed files on disk and implements an LRU (Least Recently Used) -eviction policy based on file modification times. It provides thread-safe access to cached items -and handles file system errors gracefully. -""" - -import gzip -import hashlib -import json -import logging -import os -from collections.abc import Callable -from typing import Any, Generic, TypeVar - -T = TypeVar("T") - - -log = logging.getLogger(__name__) - - -class DiskCache(Generic[T]): - """ - A persistent filesystem-based cache implementation. - - This cache stores entries as compressed files on disk and implements an LRU eviction - policy based on file modification times (mtime). While access times (atime) would be more - semantically accurate for LRU, we use mtime because: - - 1. Many modern filesystems mount with noatime for performance reasons. - 2. Even when atime updates are enabled, they may be subject to update delays. - 3. mtime updates are more reliably supported across different filesystems. - """ - - def __init__( - self, - cache_dir: str, - max_size: int | None = None, - serializer: Callable[[T], Any] | None = None, - deserializer: Callable[[Any], T] | None = None, - log_warnings: bool = True, - mkdirs: bool = True, - ): - """ - Creates a new DiskCache instance. - - Args: - cache_dir: Directory where cache files will be stored. - max_size: Maximum number of entries to store in the cache. - If not specified, the cache will grow unbounded. - serializer: Optional function to convert values to JSON-serializable format. - deserializer: Optional function to convert JSON-deserialized data back to original type. - Should be the inverse of serializer. - - Example: - # Create a cache for PromptSchema objects using its serialization methods. - cache = DiskCache[PromptSchema]( - cache_dir="cache", - serializer=lambda x: x.as_dict(), - deserializer=PromptSchema.from_dict_deep - ) - """ - self._dir = cache_dir - self._max_size = max_size - self._serializer = serializer - self._deserializer = deserializer - self._log_warnings = log_warnings - self._mkdirs = mkdirs - - def _get_entry_path(self, key: str) -> str: - """Gets the file path for a cache entry.""" - k = hashlib.sha256(key.encode("utf-8")).hexdigest() - return os.path.join(self._dir, k) - - def get(self, key: str) -> T: - """ - Retrieves a value from the cache. - Updates the entry's access time when read. - - Args: - key: The key to look up in the cache. - - Returns: - The cached value. - - Raises: - KeyError: If the key is not found in the cache. - RuntimeError: If there is an error reading from the disk cache. - """ - try: - file_path = self._get_entry_path(key) - with gzip.open(file_path, "rb") as f: - data = json.loads(f.read().decode("utf-8")) - if self._deserializer is not None: - data = self._deserializer(data) - - # Update both access and modification times. - os.utime(file_path, None) - return data - except FileNotFoundError: - raise KeyError(f"Cache key not found: {key}") - except Exception as e: - # if we have any other error, it's unexpected, but we won't want to crash an app, - # so log and treat it like a cache miss. - if self._log_warnings: - log.warning(f"Unexpected error reading from disk cache: {e}") - raise KeyError(f"Cache key not found: {key}") from e - - def set(self, key: str, value: T) -> None: - """ - Stores a value in the cache. - If the cache is at its maximum size, the least recently used entries will be evicted. - - Args: - key: The key to store the value under. - value: The value to store in the cache. - - Raises: - RuntimeError: If there is an error writing to the disk cache. - """ - try: - # mkdirs exists only to make it easy to simulate cross-platform write errors - # (permissions, etc wouldn't work on github actions on windows) - if self._mkdirs: - os.makedirs(self._dir, exist_ok=True) - file_path = self._get_entry_path(key) - - with gzip.open(file_path, "wb") as f: - if self._serializer is not None: - value = self._serializer(value) - f.write(json.dumps(value).encode("utf-8")) - - self._evict_if_full() - except Exception as e: - # Swallow any cache write errors. Don't crash the app. - if self._log_warnings: - log.warning(f"Failed to write to disk cache: {e}") - - def _evict_if_full(self): - if self._max_size is None or self._max_size <= 0: - return None - - paths = [os.path.join(self._dir, f) for f in os.listdir(self._dir)] - if not paths or len(paths) <= self._max_size: - return - - stats = [(p, os.path.getmtime(p)) for p in paths] - stats.sort(key=lambda x: x[1]) - oldest_paths = stats[0 : len(stats) - self._max_size] - - for path in oldest_paths: - os.unlink(path[0]) diff --git a/py/src/braintrust/prompt_cache/lru_cache.py b/py/src/braintrust/prompt_cache/lru_cache.py deleted file mode 100644 index e6023f0b8..000000000 --- a/py/src/braintrust/prompt_cache/lru_cache.py +++ /dev/null @@ -1,78 +0,0 @@ -""" -A module providing an LRU (Least Recently Used) cache implementation. - -This module contains a generic LRU cache that can store key-value pairs of any type. -The cache maintains items in order of use and can optionally evict least recently -used items when it reaches a maximum size. The implementation uses an OrderedDict -for O(1) access and update operations. -""" - -from collections import OrderedDict -from typing import Generic, TypeVar - -K = TypeVar("K") -V = TypeVar("V") - - -class LRUCache(Generic[K, V]): - """ - A Least Recently Used (LRU) cache implementation. - - This cache maintains items in order of use, evicting the least recently used item - when the cache reaches its maximum size (if specified). Items are considered "used" - when they are either added to the cache or retrieved from it. - - If no maximum size is specified, the cache will grow unbounded. - - Args: - max_size: Maximum number of items to store in the cache. - If not specified, the cache will grow unbounded. - """ - - def __init__(self, max_size: int | None = None): - self._cache: OrderedDict[K, V] = OrderedDict() - self._max_size = max_size - - def get(self, key: K) -> V: - """ - Retrieves a value from the cache. - If the key exists, the item is marked as most recently used. - - Args: - key: The key to look up. - - Returns: - The cached value. - - Raises: - KeyError: If the key is not found in the cache. - """ - if key not in self._cache: - raise KeyError(f"Cache key not found: {key}") - - # Refresh key by moving to end of OrderedDict. - value = self._cache.pop(key) - self._cache[key] = value - return value - - def set(self, key: K, value: V) -> None: - """ - Stores a value in the cache. - If the key already exists, the value is updated and marked as most recently used. - If the cache is at its maximum size, the least recently used item is evicted. - - Args: - key: The key to store. - value: The value to store. - """ - if key in self._cache: - self._cache.pop(key) - elif self._max_size and len(self._cache) >= self._max_size: - # Remove oldest item (first item in ordered dict). - self._cache.popitem(last=False) - - self._cache[key] = value - - def clear(self) -> None: - """Removes all items from the cache.""" - self._cache.clear() diff --git a/py/src/braintrust/prompt_cache/prompt_cache.py b/py/src/braintrust/prompt_cache/prompt_cache.py deleted file mode 100644 index 273138497..000000000 --- a/py/src/braintrust/prompt_cache/prompt_cache.py +++ /dev/null @@ -1,137 +0,0 @@ -""" -This module implements a two-layer caching system for Braintrust prompts. - -The caching system consists of: -1. A fast in-memory LRU cache for frequently accessed prompts -2. A persistent disk-based cache that serves as a backing store - -This allows for efficient prompt retrieval while maintaining persistence across sessions. -The cache is keyed by project identifier (ID or name), prompt slug, and version. -""" - - -from braintrust import prompt -from braintrust.prompt_cache import disk_cache, lru_cache - - -def _create_cache_key( - project_id: str | None, - project_name: str | None, - slug: str | None, - version: str = "latest", - id: str | None = None, -) -> str: - """Creates a unique cache key from project identifier, slug and version, or from ID.""" - if id: - # When caching by ID, we don't need project or slug - return f"id:{id}" - - prefix = project_id or project_name - if not prefix: - raise ValueError("Either project_id or project_name must be provided") - if not slug: - raise ValueError("Slug must be provided when not using ID") - return f"{prefix}:{slug}:{version}" - - -class PromptCache: - """ - A two-layer cache for Braintrust prompts with both in-memory and filesystem storage. - - This cache implements either a one or two-layer caching strategy: - 1. A fast in-memory LRU cache for frequently accessed prompts. - 2. An optional persistent filesystem-based cache that serves as a backing store. - """ - - def __init__( - self, - memory_cache: lru_cache.LRUCache[str, prompt.PromptSchema], - disk_cache: disk_cache.DiskCache[prompt.PromptSchema] | None = None, - ): - """ - Initialize the prompt cache. - - Args: - memory_cache: The memory cache to use. - disk_cache: Optional disk cache to use as backing store. - """ - self.memory_cache = memory_cache - self.disk_cache = disk_cache - - def get( - self, - slug: str | None = None, - version: str = "latest", - project_id: str | None = None, - project_name: str | None = None, - id: str | None = None, - ) -> prompt.PromptSchema: - """ - Retrieve a prompt from the cache. - - Args: - slug: The unique identifier for the prompt within its project. Required if id is not provided. - version: The version of the prompt. Defaults to "latest". - project_id: The ID of the project containing the prompt. - project_name: The name of the project containing the prompt. - id: The ID of a specific prompt. If provided, slug and project parameters are ignored. - - Returns: - The cached Prompt object. - - Raises: - ValueError: If neither project_id nor project_name is provided (when not using id). - KeyError: If the prompt is not found in the cache. - """ - cache_key = _create_cache_key(project_id, project_name, slug, version, id) - - # First check memory cache. - try: - return self.memory_cache.get(cache_key) - except KeyError: - pass - - # If not in memory and disk cache exists, check disk cache. - if self.disk_cache: - prompt = self.disk_cache.get(cache_key) - if prompt is None: - raise KeyError(f"Prompt not found in cache: {cache_key}") - - # Store in memory cache. - self.memory_cache.set(cache_key, prompt) - return prompt - - raise KeyError(f"Prompt not found in cache: {cache_key}") - - def set( - self, - value: prompt.PromptSchema, - slug: str | None = None, - version: str = "latest", - project_id: str | None = None, - project_name: str | None = None, - id: str | None = None, - ) -> None: - """ - Store a prompt in the cache. - - Args: - slug: The unique identifier for the prompt within its project. Required if id is not provided. - version: The version of the prompt. Defaults to "latest". - value: The Prompt object to store. - project_id: The ID of the project containing the prompt. - project_name: The name of the project containing the prompt. - id: The ID of a specific prompt. If provided, slug and project parameters are ignored. - - Raises: - ValueError: If neither project_id nor project_name is provided (when not using id). - RuntimeError: If there is an error writing to the disk cache. - """ - cache_key = _create_cache_key(project_id, project_name, slug, version, id) - - # Update memory cache. - self.memory_cache.set(cache_key, value) - - # Update disk cache if available. - if self.disk_cache: - self.disk_cache.set(cache_key, value) diff --git a/py/src/braintrust/prompt_cache/test_disk_cache.py b/py/src/braintrust/prompt_cache/test_disk_cache.py deleted file mode 100644 index 7f49986ed..000000000 --- a/py/src/braintrust/prompt_cache/test_disk_cache.py +++ /dev/null @@ -1,234 +0,0 @@ -import os -import shutil -import tempfile -import time -import unittest -from typing import Any - -from braintrust import prompt -from braintrust.prompt_cache import disk_cache - - -class TestDiskCache(unittest.TestCase): - def setUp(self): - self.cache_dir = tempfile.mkdtemp() - self.cache = disk_cache.DiskCache[dict]( - cache_dir=self.cache_dir, - max_size=3, - log_warnings=False, - ) - - def tearDown(self): - try: - shutil.rmtree(self.cache_dir, ignore_errors=True) - except Exception: - pass - - def test_keys_with_invalid_paths(self): - data = {"1": "2"} - weird_keys = [ - ".", - "..", - "a/b/c", - "my\0file.txt", - "file*.txT", - "what?.txt", - " asdf ", - "invalid/name", - "my.txt", - "a\nb", - ] - for k in weird_keys: - time.sleep(0.01) # make sure the mtimes are different - self.cache.set(k, data) - result = self.cache.get(k) - assert data == result - - def test_store_and_retrieve_values(self): - test_data = {"foo": "bar"} - self.cache.set("test-key", test_data) - result = self.cache.get("test-key") - self.assertEqual(result, test_data) - - def test_raise_keyerror_for_missing_keys(self): - """Test raising KeyError for missing keys.""" - with self.assertRaises(KeyError) as cm: - self.cache.get("missing-key") - self.assertEqual(str(cm.exception), "'Cache key not found: missing-key'") - - def test_raise_keyerror_after_eviction(self): - """Test that accessing evicted entries raises KeyError.""" - # Fill cache beyond max size (3). - for i in range(3): - self.cache.set(f"key{i}", {"value": i}) - time.sleep(0.01) # wait to ensure different mtimes - - # Add one more to trigger eviction. - self.cache.set("key3", {"value": 3}) - - # The oldest entry should raise KeyError. - with self.assertRaises(KeyError) as cm: - self.cache.get("key0") - self.assertEqual(str(cm.exception), "'Cache key not found: key0'") - - def test_evict_oldest_entries_when_cache_is_full(self): - # Fill cache beyond max size (3). - for i in range(3): - self.cache.set(f"key{i}", {"value": i}) - time.sleep(0.01) # wait to ensure different mtimes - - # Add one more to trigger eviction. - self.cache.set("key3", {"value": 3}) - - # The oldest entry should be evicted. - with self.assertRaises(KeyError) as cm: - self.cache.get("key0") - self.assertEqual(str(cm.exception), "'Cache key not found: key0'") - - # Newer entries should still exist. - newer = self.cache.get("key2") - self.assertEqual(newer, {"value": 2}) - - def test_dont_throw_when_write_fails(self): - # Make cache directory read-only. - non_existent_dir = os.path.join(self.cache_dir, "non-existent-dir") - # Don't throw when writing fails. - broken_cache = disk_cache.DiskCache[dict]( - cache_dir=non_existent_dir, - max_size=3, - log_warnings=False, - mkdirs=False, - ) - broken_cache.set("test", {"foo": "bar"}) - - try: - broken_cache.get("test") - except KeyError: - pass - - def test_dont_throw_when_read_fails(self): - self.cache.set("test-key", {"foo": "bar"}) - assert self.cache.get("test-key") == {"foo": "bar"} - - # Make cache directory unreadable. - shutil.rmtree(self.cache_dir) - - try: - self.cache.get("test-key") - except KeyError: - pass - else: - assert False, "shouldn't fail" - - def test_throw_on_corrupted_data(self): - self.cache.set("test-key", {"foo": "bar"}) - assert self.cache.get("test-key") == {"foo": "bar"} - - # Corrupt the file. - file_path = self.cache._get_entry_path("test-key") - with open(file_path, "w") as f: - f.write("invalid data") - - # if the data is corrupted, pretend like its not cached - try: - self.cache.get("test-key") - except KeyError: - pass - else: - assert 0 - - # we should be able to write and read again. - self.cache.set("test-key", {"foo": "bar"}) - assert self.cache.get("test-key") == {"foo": "bar"} - - def test_store_and_retrieve_with_serialization(self): - """Test storing and retrieving objects using custom serialization.""" - cache = disk_cache.DiskCache[prompt.PromptSchema]( - cache_dir=self.cache_dir, - max_size=3, - serializer=lambda x: x.as_dict(), - deserializer=prompt.PromptSchema.from_dict_deep, - log_warnings=False, - ) - - # Create a test prompt. - test_prompt = prompt.PromptSchema( - id="456", - project_id="123", - _xact_id="789", - name="test-prompt", - slug="test-prompt", - description=None, - prompt_data=prompt.PromptData(), - tags=None, - ) - - # Store and retrieve. - cache.set("test-key", test_prompt) - result = cache.get("test-key") - - # Should get back a PromptSchema instance. - self.assertIsInstance(result, prompt.PromptSchema) - self.assertEqual(result.as_dict(), test_prompt.as_dict()) - - def test_serializer_handles_complex_objects(self): - """Test that serializer is used for complex nested objects.""" - cache = disk_cache.DiskCache[prompt.PromptSchema]( - cache_dir=self.cache_dir, - serializer=lambda x: x.as_dict(), - deserializer=prompt.PromptSchema.from_dict_deep, - log_warnings=False, - ) - - # Create a prompt with nested data. - test_prompt = prompt.PromptSchema( - id="456", - project_id="123", - _xact_id="789", - name="test-prompt", - slug="test-prompt", - description="test description", - prompt_data=prompt.PromptData( - prompt=prompt.PromptCompletionBlock( - content="test", - ) - ), - tags=["tag1", "tag2"], - ) - - # Store and retrieve. - cache.set("test-key", test_prompt) - result = cache.get("test-key") - - self.assertEqual(result.as_dict(), test_prompt.as_dict()) - - def test_throw_on_deserializer_error(self): - """Test that deserializer errors are propagated.""" - - def bad_deserializer(data: Any) -> prompt.PromptSchema: - raise ValueError("Deserialization failed") - - cache = disk_cache.DiskCache[prompt.PromptSchema]( - cache_dir=self.cache_dir, serializer=lambda x: x.as_dict(), deserializer=bad_deserializer - ) - - # Store a prompt. - test_prompt = prompt.PromptSchema( - id="456", - project_id="123", - _xact_id="789", - name="test-prompt", - slug="test-prompt", - description=None, - prompt_data=prompt.PromptData(), - tags=None, - ) - cache.set("test-key", test_prompt) - - # assert a serde error is treated like a cache miss. - try: - cache.get("test-key") - except KeyError: - pass - else: - assert False, "should fail" diff --git a/py/src/braintrust/prompt_cache/test_lru_cache.py b/py/src/braintrust/prompt_cache/test_lru_cache.py deleted file mode 100644 index 6fb286e57..000000000 --- a/py/src/braintrust/prompt_cache/test_lru_cache.py +++ /dev/null @@ -1,72 +0,0 @@ -import unittest - -from braintrust.prompt_cache import lru_cache - - -class TestLRUCache(unittest.TestCase): - def test_store_and_retrieve_values(self): - """Test storing and retrieving values.""" - cache = lru_cache.LRUCache[str, int]() - cache.set("a", 1) - self.assertEqual(cache.get("a"), 1) - - def test_raise_keyerror_for_missing_keys(self): - """Test raising KeyError for missing keys.""" - cache = lru_cache.LRUCache[str, int]() - with self.assertRaises(KeyError): - cache.get("missing") - - def test_respect_max_size_when_specified(self): - """Test respecting max size when specified.""" - cache = lru_cache.LRUCache[str, int](max_size=2) - cache.set("a", 1) - cache.set("b", 2) - cache.set("c", 3) - with self.assertRaises(KeyError): - cache.get("a") - self.assertEqual(cache.get("b"), 2) - self.assertEqual(cache.get("c"), 3) - - def test_grow_unbounded_when_no_max_size_specified(self): - """Test growing unbounded when no max size specified.""" - cache = lru_cache.LRUCache[int, int]() - # Add many items. - for i in range(1000): - cache.set(i, i) - # Should keep all items. - for i in range(1000): - self.assertEqual(cache.get(i), i) - - def test_refresh_items_on_get(self): - """Test refreshing items on get.""" - cache = lru_cache.LRUCache[str, int](max_size=2) - cache.set("a", 1) - cache.set("b", 2) - cache.get("a") # refresh "a" - cache.set("c", 3) - self.assertEqual(cache.get("a"), 1) - with self.assertRaises(KeyError): - cache.get("b") - self.assertEqual(cache.get("c"), 3) - - def test_update_existing_keys(self): - """Test updating existing keys.""" - cache = lru_cache.LRUCache[str, int]() - cache.set("a", 1) - cache.set("a", 2) - self.assertEqual(cache.get("a"), 2) - - def test_clear_all_items(self): - """Test clearing all items.""" - cache = lru_cache.LRUCache[str, int]() - cache.set("a", 1) - cache.set("b", 2) - cache.clear() - with self.assertRaises(KeyError): - cache.get("a") - with self.assertRaises(KeyError): - cache.get("b") - - -if __name__ == "__main__": - unittest.main() diff --git a/py/src/braintrust/prompt_cache/test_prompt_cache.py b/py/src/braintrust/prompt_cache/test_prompt_cache.py deleted file mode 100644 index 0e0d70c8f..000000000 --- a/py/src/braintrust/prompt_cache/test_prompt_cache.py +++ /dev/null @@ -1,193 +0,0 @@ -import os -import shutil -import tempfile -import unittest - -from braintrust import prompt -from braintrust.prompt_cache import disk_cache, lru_cache, prompt_cache - - -class TestPromptCache(unittest.TestCase): - def setUp(self): - # Create a temporary directory for each test - self.cache_dir = tempfile.mkdtemp() - mc = lru_cache.LRUCache[str, prompt.PromptSchema](max_size=2) - dc = disk_cache.DiskCache[prompt.PromptSchema]( - cache_dir=self.cache_dir, - max_size=5, - serializer=lambda x: x.as_dict(), - deserializer=prompt.PromptSchema.from_dict_deep, - log_warnings=False, - ) - self.cache = prompt_cache.PromptCache(memory_cache=mc, disk_cache=dc) - - self.test_prompt = prompt.PromptSchema( - id="456", - project_id="123", - _xact_id="789", - name="test-prompt", - slug="test-prompt", - description=None, - prompt_data=prompt.PromptData(), - tags=None, - ) - - def tearDown(self): - # Clean up the temporary directory. - try: - shutil.rmtree(self.cache_dir, ignore_errors=True) - except Exception: - pass - - def test_prompts_with_weird_names(self): - # tests BRA-2326 - names = [ - "a/b/c", - "managed/insights", - "a b c d", - ] - for n in names: - p = prompt.PromptSchema( - id="123", - project_id="456", - name=n, - description="blah", - tags=None, - slug=f"test-prompt-{n}", - prompt_data=prompt.PromptData(), - _xact_id="666666", - ) - self.cache.set(p, slug=n, version="666666", project_id="456") - result = self.cache.get(slug=n, version="666666", project_id="456") - self.assertEqual(result.as_dict(), p.as_dict()) - - def test_store_and_retrieve_from_memory_cache(self): - self.cache.set(self.test_prompt, slug="test-prompt", version="789", project_id="123") - result = self.cache.get(slug="test-prompt", version="789", project_id="123") - self.assertEqual(result.as_dict(), self.test_prompt.as_dict()) - - def test_work_with_project_name(self): - self.cache.set(self.test_prompt, slug="test-prompt", version="789", project_name="test-project") - result = self.cache.get(slug="test-prompt", version="789", project_name="test-project") - self.assertEqual(result.as_dict(), self.test_prompt.as_dict()) - - def test_throw_error_if_no_project_identifier(self): - with self.assertRaisesRegex(ValueError, "Either project_id or project_name must be provided"): - self.cache.get(slug="test-prompt", version="789") - - with self.assertRaisesRegex(ValueError, "Either project_id or project_name must be provided"): - self.cache.set(self.test_prompt, slug="test-prompt", version="789") - - def test_store_and_retrieve_from_disk_after_memory_eviction(self): - # Fill memory cache (max size is 2). - self.cache.set(self.test_prompt, slug="test-prompt", version="789", project_id="123") - self.cache.set(self.test_prompt, slug="prompt2", version="789", project_id="123") - self.cache.set(self.test_prompt, slug="prompt3", version="789", project_id="123") - - # Original prompt should now be on disk but not in memory. - result = self.cache.get(slug="test-prompt", version="789", project_id="123") - self.assertEqual(result.as_dict(), self.test_prompt.as_dict()) - - def test_raise_for_nonexistent_prompts(self): - with self.assertRaises(KeyError): - self.cache.get(slug="missing-prompt", version="789", project_id="123") - - def test_handle_different_projects_with_same_slug(self): - self.cache.set(self.test_prompt, slug="test-prompt", version="789", project_id="123") - - different_prompt = prompt.PromptSchema.from_dict_deep(self.test_prompt.as_dict()) - different_prompt.project_id = "different-project" - self.cache.set(different_prompt, slug="test-prompt", version="789", project_id="different-project") - - result1 = self.cache.get(slug="test-prompt", version="789", project_id="123") - result2 = self.cache.get(slug="test-prompt", version="789", project_id="different-project") - - self.assertEqual(result1.project_id, "123") - self.assertEqual(result2.project_id, "different-project") - - def test_memory_only_cache(self): - memory_only_cache = prompt_cache.PromptCache(memory_cache=lru_cache.LRUCache(max_size=2)) - - memory_only_cache.set(self.test_prompt, slug="test-prompt", version="789", project_id="123") - result = memory_only_cache.get(slug="test-prompt", version="789", project_id="123") - self.assertEqual(result.as_dict(), self.test_prompt.as_dict()) - - # Fill memory cache beyond capacity. - memory_only_cache.set(self.test_prompt, slug="prompt2", version="789", project_id="123") - memory_only_cache.set(self.test_prompt, slug="prompt3", version="789", project_id="123") - - # First prompt should be gone since there's no disk backup. - with self.assertRaises(KeyError): - memory_only_cache.get(slug="test-prompt", version="789", project_id="123") - - def test_dont_throw_when_disk_write_fails(self): - # Make cache directory read-only. - os.chmod(self.cache_dir, 0o444) - - self.cache.set(self.test_prompt, slug="test-prompt", version="789", project_id="123") - - # Memory cache should still be updated despite disk failure. - result = self.cache.get("test-prompt", version="789", project_id="123") - self.assertEqual(result.as_dict(), self.test_prompt.as_dict()) - - # Restore permissions so cleanup can happen. - os.chmod(self.cache_dir, 0o777) - - def test_store_and_retrieve_by_id(self): - # Test storing and retrieving a prompt by ID - prompt_id = "test-prompt-id-123" - self.cache.set(self.test_prompt, id=prompt_id) - result = self.cache.get(id=prompt_id) - self.assertEqual(result.as_dict(), self.test_prompt.as_dict()) - - def test_id_based_cache_independent_of_slug(self): - # Test that ID-based caching is independent of slug-based caching - prompt_id = "test-prompt-id-456" - - # Store by ID - self.cache.set(self.test_prompt, id=prompt_id) - - # Store same prompt by slug - self.cache.set(self.test_prompt, slug="test-prompt", version="789", project_id="123") - - # Retrieve by ID - result_by_id = self.cache.get(id=prompt_id) - self.assertEqual(result_by_id.as_dict(), self.test_prompt.as_dict()) - - # Retrieve by slug - result_by_slug = self.cache.get(slug="test-prompt", version="789", project_id="123") - self.assertEqual(result_by_slug.as_dict(), self.test_prompt.as_dict()) - - # Modify the prompt stored by ID - modified_prompt = prompt.PromptSchema.from_dict_deep(self.test_prompt.as_dict()) - modified_prompt.description = "Modified description" - self.cache.set(modified_prompt, id=prompt_id) - - # Verify ID-based retrieval gets modified version - result_by_id_modified = self.cache.get(id=prompt_id) - self.assertEqual(result_by_id_modified.description, "Modified description") - - # Verify slug-based retrieval still gets original - result_by_slug_unchanged = self.cache.get(slug="test-prompt", version="789", project_id="123") - self.assertIsNone(result_by_slug_unchanged.description) - - def test_raise_for_nonexistent_id(self): - with self.assertRaises(KeyError): - self.cache.get(id="missing-prompt-id") - - def test_id_cache_with_disk_persistence(self): - # Test that ID-based caching works with disk persistence - prompt_id = "persistent-prompt-id" - - # Fill memory cache to force disk storage - self.cache.set(self.test_prompt, slug="prompt1", version="v1", project_id="123") - self.cache.set(self.test_prompt, slug="prompt2", version="v1", project_id="123") - self.cache.set(self.test_prompt, id=prompt_id) - - # The ID-based prompt should be retrievable (from disk if evicted from memory) - result = self.cache.get(id=prompt_id) - self.assertEqual(result.as_dict(), self.test_prompt.as_dict()) - - -if __name__ == "__main__": - unittest.main() diff --git a/py/src/braintrust/py.typed b/py/src/braintrust/py.typed deleted file mode 100644 index e69de29bb..000000000 diff --git a/py/src/braintrust/queue.py b/py/src/braintrust/queue.py deleted file mode 100644 index 4629c3a3b..000000000 --- a/py/src/braintrust/queue.py +++ /dev/null @@ -1,119 +0,0 @@ -import threading -from collections import deque -from typing import TypeVar - -from .util import eprint - -T = TypeVar("T") - -DEFAULT_QUEUE_SIZE = 25000 - - -class LogQueue: - """A thread-safe queue with a fixed size that drops oldest items when full. - - When enforcement is disabled (default), drops happen silently. - When enforcement is enabled, dropped items are tracked and returned. - """ - - def __init__(self, maxsize: int = 0): - """ - Initialize the LogQueue. - - Args: - maxsize: Maximum size of the queue. If 0 or negative, defaults to DEFAULT_QUEUE_SIZE. - """ - if maxsize < 1: - eprint(f"Queue maxsize {maxsize} is invalid, using default size {DEFAULT_QUEUE_SIZE}") - maxsize = DEFAULT_QUEUE_SIZE - - self.maxsize = maxsize - self._mutex = threading.Lock() - self._queue: deque[T] = deque(maxlen=maxsize) - self._has_items_event = threading.Event() - self._total_dropped = 0 - self._enforce_size_limit = False - - def enforce_queue_size_limit(self, enforce: bool) -> None: - """ - Set queue size limit enforcement. When enabled, the queue will drop oldest items - when it reaches maxsize and return them from put(). When disabled (default), - the queue will still drop oldest items when full but won't track or return them. - - Args: - enforce: Whether to track and return dropped items. - """ - with self._mutex: - self._enforce_size_limit = enforce - - def put(self, item: T) -> list[T]: - """ - Put an item in the queue. - - Args: - item: The item to add to the queue. - - Returns: - List of items that were dropped (empty if no items were dropped). - """ - with self._mutex: - dropped = [] - - if not self._enforce_size_limit: - # For queues with enforcement disabled, deque auto-drops silently - self._queue.append(item) - else: - # For bounded queues with enforcement, explicitly track drops - while len(self._queue) >= self.maxsize: - dropped_item = self._queue.popleft() - dropped.append(dropped_item) - self._total_dropped += 1 - self._queue.append(item) - - # Signal that items are available if queue was not empty before or item was added - if len(self._queue) > 0: - self._has_items_event.set() - - return dropped - - def drain_all(self) -> list[T]: - """ - Drain all items from the queue. - - Returns: - List of all items that were in the queue. - """ - old_queue = None - with self._mutex: - if len(self._queue) == 0: - return [] - - old_queue = self._queue - self._queue = deque(maxlen=self.maxsize) - - # Clear the event since queue is now empty - self._has_items_event.clear() - - return list(old_queue) if old_queue else [] - - def size(self) -> int: - """ - Get the current size of the queue. - - Returns: - Number of items currently in the queue. - """ - return len(self._queue) - - def wait_for_items(self, timeout: float | None = None) -> bool: - """ - Will block until the queue has at least one item in it. Might be empty by the time - you read though. - - Args: - timeout: Maximum time to wait in seconds. None means wait forever. - - Returns: - True if items became available, False if timeout occurred. - """ - return self._has_items_event.wait(timeout=timeout) diff --git a/py/src/braintrust/resource_manager.py b/py/src/braintrust/resource_manager.py deleted file mode 100644 index 72a799bf8..000000000 --- a/py/src/braintrust/resource_manager.py +++ /dev/null @@ -1,22 +0,0 @@ -from contextlib import contextmanager -from threading import RLock - - -class ResourceManager: - """A ResourceManager is a simple class to hold onto a shared resource. Local - chalice is not thread-safe, so accessing shared memory across threads is not - necessarily safe. But production AWS lambda will guarantee that memory is - not shared across threads, so this synchronization is unnecessary. - - The ResourceManager controls access to a shared resource, optionally - applying synchronization when run locally. - """ - - def __init__(self, resource): - self.lock = RLock() - self.resource = resource - - @contextmanager - def get(self): - with self.lock: - yield self.resource diff --git a/py/src/braintrust/score.py b/py/src/braintrust/score.py deleted file mode 100644 index cd5fe720a..000000000 --- a/py/src/braintrust/score.py +++ /dev/null @@ -1,93 +0,0 @@ -import dataclasses -import inspect -import warnings -from abc import ABC, abstractmethod -from typing import Any - -from .serializable_data_class import SerializableDataClass - -# ========================================================================= -# !!!!!!!!!!!!!!!! READ THIS BEFORE CHANGING THIS FILE !!!!!!!!!!!!!!!! -# -# Scores and Scorer classes can be defined in autoevals, braintrust_core -# or this library or potentially user code. If you make changes here, -# ensure they are backwards compatible with the existing interfaces. -# ========================================================================= - - -@dataclasses.dataclass -class Score(SerializableDataClass): - """A score for an evaluation. The score is a float between 0 and 1.""" - - name: str - """The name of the score. This should be a unique name for the scorer.""" - - score: float | None = None - """The score for the evaluation. This should be a float between 0 and 1. If the score is None, the evaluation is considered to be skipped.""" - - metadata: dict[str, Any] = dataclasses.field(default_factory=dict) - """Metadata for the score. This can be used to store additional information about the score.""" - - # DEPRECATION_NOTICE: this field is deprecated, as errors are propagated up to the caller. - error: Exception | None = None - """Deprecated: The error field is deprecated, as errors are now propagated to the caller. The field will be removed in a future version of the library.""" - - def as_dict(self): - return { - "name": self.name, - "score": self.score, - "metadata": self.metadata, - } - - def __post_init__(self): - if self.score is not None and (self.score < 0 or self.score > 1): - raise ValueError(f"score ({self.score}) must be between 0 and 1") - if self.error is not None: - warnings.warn( - "The error field is deprecated, as errors are now propagated to the caller." - " The field will be removed in a future version of the library" - ) - - -def is_score(obj): - return hasattr(obj, "name") and hasattr(obj, "score") and hasattr(obj, "metadata") and hasattr(obj, "as_dict") - - -class Scorer(ABC): - async def eval_async(self, output: Any, expected: Any = None, **kwargs: Any) -> Score: - return await self._run_eval_async(output, expected, **kwargs) - - def eval(self, output: Any, expected: Any = None, **kwargs: Any) -> Score: - return self._run_eval_sync(output, expected, **kwargs) - - def __call__(self, output: Any, expected: Any = None, **kwargs: Any) -> Score: - return self.eval(output, expected, **kwargs) - - async def _run_eval_async(self, output: Any, expected: Any = None, **kwargs: Any) -> Score: - # By default we just run the sync version in a thread - return self._run_eval_sync(output, expected, **kwargs) - - def _name(self) -> str: - return self.__class__.__name__ - - @abstractmethod - def _run_eval_sync(self, output: Any, expected: Any = None, **kwargs: Any) -> Score: ... - - -def is_scorer(obj): - # For class objects, check for appropriate methods - if inspect.isclass(obj): - return ( - hasattr(obj, "eval") - or hasattr(obj, "eval_async") - or hasattr(obj, "_run_eval_sync") - or hasattr(obj, "_run_eval_async") - ) - # For instances, check for appropriate methods - elif hasattr(obj, "eval") or hasattr(obj, "eval_async"): - return True - # For functions/callables, we rely on the type system - return callable(obj) - - -__all__ = ["Score", "Scorer", "is_score", "is_scorer"] diff --git a/py/src/braintrust/serializable_data_class.py b/py/src/braintrust/serializable_data_class.py deleted file mode 100644 index 8f9eeefc1..000000000 --- a/py/src/braintrust/serializable_data_class.py +++ /dev/null @@ -1,65 +0,0 @@ -import dataclasses -import json -from typing import Union, get_origin - - -class SerializableDataClass: - def as_dict(self): - """Serialize the object to a dictionary.""" - return dataclasses.asdict(self) - - def as_json(self, **kwargs): - """Serialize the object to JSON.""" - return json.dumps(self.as_dict(), **kwargs) - - def __getitem__(self, item: str): - return getattr(self, item) - - @classmethod - def from_dict(cls, d: dict): - """Deserialize the object from a dictionary. This method - is shallow and will not call from_dict() on nested objects.""" - fields = {f.name for f in dataclasses.fields(cls)} - filtered = {k: v for k, v in d.items() if k in fields} - return cls(**filtered) - - @classmethod - def from_dict_deep(cls, d: dict): - """Deserialize the object from a dictionary. This method - is deep and will call from_dict_deep() on nested objects.""" - fields = {f.name: f for f in dataclasses.fields(cls)} - filtered = {} - for k, v in d.items(): - if k not in fields: - continue - - if ( - isinstance(v, dict) - and isinstance(fields[k].type, type) - and issubclass(fields[k].type, SerializableDataClass) - ): - filtered[k] = fields[k].type.from_dict_deep(v) - elif get_origin(fields[k].type) == Union: - for t in fields[k].type.__args__: - if t == type(None) and v is None: - filtered[k] = None - break - if isinstance(t, type) and issubclass(t, SerializableDataClass) and v is not None: - try: - filtered[k] = t.from_dict_deep(v) - break - except TypeError: - pass - else: - filtered[k] = v - elif ( - isinstance(v, list) - and get_origin(fields[k].type) == list - and len(fields[k].type.__args__) == 1 - and isinstance(fields[k].type.__args__[0], type) - and issubclass(fields[k].type.__args__[0], SerializableDataClass) - ): - filtered[k] = [fields[k].type.__args__[0].from_dict_deep(i) for i in v] - else: - filtered[k] = v - return cls(**filtered) diff --git a/py/src/braintrust/span_cache.py b/py/src/braintrust/span_cache.py deleted file mode 100644 index 17148cdec..000000000 --- a/py/src/braintrust/span_cache.py +++ /dev/null @@ -1,337 +0,0 @@ -""" -SpanCache provides a disk-based cache for span data, allowing -scorers to read spans without making server round-trips when possible. - -Spans are stored on disk to minimize memory usage during evaluations. -The cache file is automatically cleaned up when dispose() is called. -""" - -import atexit -import json -import os -import tempfile -import uuid -from typing import Any, Optional - -from braintrust.util import merge_dicts - -# Global registry of active span caches for process exit cleanup -_active_caches: set["SpanCache"] = set() -_exit_handlers_registered = False - - -class CachedSpan: - """Cached span data structure.""" - - def __init__( - self, - span_id: str, - input: Optional[Any] = None, - output: Optional[Any] = None, - metadata: Optional[dict[str, Any]] = None, - span_parents: Optional[list[str]] = None, - span_attributes: Optional[dict[str, Any]] = None, - ): - self.span_id = span_id - self.input = input - self.output = output - self.metadata = metadata - self.span_parents = span_parents - self.span_attributes = span_attributes - - def to_dict(self) -> dict[str, Any]: - """Convert to dictionary for serialization.""" - result = {"span_id": self.span_id} - if self.input is not None: - result["input"] = self.input - if self.output is not None: - result["output"] = self.output - if self.metadata is not None: - result["metadata"] = self.metadata - if self.span_parents is not None: - result["span_parents"] = self.span_parents - if self.span_attributes is not None: - result["span_attributes"] = self.span_attributes - return result - - @classmethod - def from_dict(cls, data: dict[str, Any]) -> "CachedSpan": - """Create from dictionary.""" - return cls( - span_id=data["span_id"], - input=data.get("input"), - output=data.get("output"), - metadata=data.get("metadata"), - span_parents=data.get("span_parents"), - span_attributes=data.get("span_attributes"), - ) - - -class DiskSpanRecord: - """Record structure for disk storage.""" - - def __init__(self, root_span_id: str, span_id: str, data: CachedSpan): - self.root_span_id = root_span_id - self.span_id = span_id - self.data = data - - def to_dict(self) -> dict[str, Any]: - """Convert to dictionary for JSON serialization.""" - return { - "rootSpanId": self.root_span_id, - "spanId": self.span_id, - "data": self.data.to_dict(), - } - - @classmethod - def from_dict(cls, data: dict[str, Any]) -> "DiskSpanRecord": - """Create from dictionary.""" - return cls( - root_span_id=data["rootSpanId"], - span_id=data["spanId"], - data=CachedSpan.from_dict(data["data"]), - ) - - -class SpanCache: - """ - Disk-based cache for span data, keyed by rootSpanId. - - This cache writes spans to a temporary file to minimize memory usage. - It uses append-only writes and reads the full file when querying. - """ - - def __init__(self, disabled: bool = False): - self._cache_file_path: Optional[str] = None - self._initialized = False - # Tracks whether the cache was explicitly disabled (via constructor or disable()) - self._explicitly_disabled = disabled - # Tracks whether the cache has been enabled (for evals only) - self._enabled = False - # Reference count of active evals using this cache - self._active_eval_count = 0 - # Small in-memory index tracking which rootSpanIds have data - self._root_span_index: set[str] = set() - # Buffer for pending writes - self._write_buffer: list[DiskSpanRecord] = [] - - def disable(self) -> None: - """ - Disable the cache at runtime. This is called automatically when - OTEL is registered, since OTEL spans won't be in the cache. - """ - self._explicitly_disabled = True - - def start(self) -> None: - """ - Start caching spans for use during evaluations. - This only starts caching if the cache wasn't permanently disabled. - Called by Eval() to turn on caching for the duration of the eval. - Uses reference counting to support parallel evals. - """ - if not self._explicitly_disabled: - self._enabled = True - self._active_eval_count += 1 - - def stop(self) -> None: - """ - Stop caching spans and return to the default disabled state. - Unlike disable(), this allows start() to work again for future evals. - Called after an eval completes to return to the default state. - Uses reference counting - only disables when all evals are complete. - """ - self._active_eval_count -= 1 - if self._active_eval_count <= 0: - self._active_eval_count = 0 - self._enabled = False - - @property - def disabled(self) -> bool: - """Check if cache is disabled.""" - return self._explicitly_disabled or not self._enabled - - def _ensure_initialized(self) -> None: - """Initialize the cache file if not already done.""" - if self.disabled or self._initialized: - return - - try: - # Create temporary file - unique_id = f"{int(os.times().elapsed * 1000000)}-{uuid.uuid4().hex[:8]}" - self._cache_file_path = os.path.join(tempfile.gettempdir(), f"braintrust-span-cache-{unique_id}.jsonl") - - # Create the file - with open(self._cache_file_path, "w") as f: - pass - - self._initialized = True - self._register_exit_handler() - except Exception: - # Silently fail if filesystem is unavailable - cache is best-effort - # This can happen if temp directory is not writable or disk is full - self._explicitly_disabled = True - return - - def _register_exit_handler(self) -> None: - """Register a handler to clean up the temp file on process exit.""" - global _exit_handlers_registered - _active_caches.add(self) - - if not _exit_handlers_registered: - _exit_handlers_registered = True - - def cleanup_all_caches(): - """Clean up all active caches.""" - for cache in _active_caches: - if cache._cache_file_path and os.path.exists(cache._cache_file_path): - try: - os.unlink(cache._cache_file_path) - except Exception: - # Ignore cleanup errors - file might not exist or already deleted - pass - - atexit.register(cleanup_all_caches) - - def queue_write(self, root_span_id: str, span_id: str, data: CachedSpan) -> None: - """ - Write a span to the cache. - In Python, we write synchronously (no async queue like in TS). - """ - if self.disabled: - return - - self._ensure_initialized() - - record = DiskSpanRecord(root_span_id, span_id, data) - self._write_buffer.append(record) - self._root_span_index.add(root_span_id) - - # Write to disk immediately (simplified compared to TS async version) - self._flush_write_buffer() - - def _flush_write_buffer(self) -> None: - """Flush the write buffer to disk.""" - if not self._write_buffer or not self._cache_file_path: - return - - try: - with open(self._cache_file_path, "a") as f: - for record in self._write_buffer: - f.write(json.dumps(record.to_dict()) + "\n") - self._write_buffer.clear() - except Exception: - # Silently fail if write fails - cache is best-effort - # This can happen if disk is full or file permissions changed - pass - - def get_by_root_span_id(self, root_span_id: str) -> Optional[list[CachedSpan]]: - """ - Get all cached spans for a given rootSpanId. - - This reads the file and merges all records for the given rootSpanId. - - Args: - root_span_id: The root span ID to look up - - Returns: - List of cached spans, or None if not in cache - """ - if self.disabled: - return None - - # Quick check using in-memory index - if root_span_id not in self._root_span_index: - return None - - # Accumulate spans by spanId, merging updates - span_map: dict[str, dict[str, Any]] = {} - - # Read from disk if initialized - if self._initialized and self._cache_file_path and os.path.exists(self._cache_file_path): - try: - with open(self._cache_file_path, "r") as f: - for line in f: - line = line.strip() - if not line: - continue - try: - record_dict = json.loads(line) - record = DiskSpanRecord.from_dict(record_dict) - if record.root_span_id != root_span_id: - continue - - if record.span_id in span_map: - merge_dicts(span_map[record.span_id], record.data.to_dict()) - else: - span_map[record.span_id] = record.data.to_dict() - except Exception: - # Skip malformed lines - may occur if file was corrupted or truncated - pass - except Exception: - # Continue to check buffer even if disk read fails - # This can happen if file was deleted or permissions changed - pass - - # Also check the in-memory write buffer for unflushed data - for record in self._write_buffer: - if record.root_span_id != root_span_id: - continue - if record.span_id in span_map: - merge_dicts(span_map[record.span_id], record.data.to_dict()) - else: - span_map[record.span_id] = record.data.to_dict() - - if not span_map: - return None - - return [CachedSpan.from_dict(data) for data in span_map.values()] - - def has(self, root_span_id: str) -> bool: - """Check if a rootSpanId has cached data.""" - if self.disabled: - return False - return root_span_id in self._root_span_index - - def clear(self, root_span_id: str) -> None: - """ - Clear all cached spans for a given rootSpanId. - Note: This only removes from the index. The data remains in the file - but will be ignored on reads. - """ - self._root_span_index.discard(root_span_id) - - def clear_all(self) -> None: - """Clear all cached data and remove the cache file.""" - self._root_span_index.clear() - self.dispose() - - @property - def size(self) -> int: - """Get the number of root spans currently tracked.""" - return len(self._root_span_index) - - def dispose(self) -> None: - """ - Clean up the cache file. Call this when the eval is complete. - Only performs cleanup when all active evals have completed (refcount = 0). - """ - # Only dispose if no active evals are using this cache - if self._active_eval_count > 0: - return - - # Remove from global registry - _active_caches.discard(self) - - # Clear pending writes - self._write_buffer.clear() - - if self._cache_file_path and os.path.exists(self._cache_file_path): - try: - os.unlink(self._cache_file_path) - except Exception: - # Ignore cleanup errors - file might not exist or already deleted - pass - self._cache_file_path = None - - self._initialized = False - self._root_span_index.clear() diff --git a/py/src/braintrust/span_identifier_v1.py b/py/src/braintrust/span_identifier_v1.py deleted file mode 100644 index 4c0a9f586..000000000 --- a/py/src/braintrust/span_identifier_v1.py +++ /dev/null @@ -1,138 +0,0 @@ -# Serialization format for capturing all relevant information about a span -# necessary for distributed logging / tracing. Meant to be passed around as an -# opaque string. - -import base64 -import dataclasses -from enum import Enum, auto -from uuid import UUID - - -def _try_make_uuid(s): - try: - ret = UUID(s).bytes - assert len(ret) == 16 - return ret, True - except Exception: - return s.encode("utf-8"), False - - -ENCODING_VERSION_NUMBER = 1 - -INVALID_ENCODING_ERRMSG = "SpanComponentsV1 string is not properly encoded. This may be due to a version mismatch between the SDK library used to export the span and the library used to decode it. Please make sure you are using the same SDK version across the board" - - -class SpanObjectTypeV1(Enum): - EXPERIMENT = auto() - PROJECT_LOGS = auto() - - def __str__(self): - return {SpanObjectTypeV1.EXPERIMENT: "experiment", SpanObjectTypeV1.PROJECT_LOGS: "project_logs"}[self] - - -@dataclasses.dataclass -class SpanRowIdsV1: - row_id: str - span_id: str - root_span_id: str - - def __post_init__(self): - assert isinstance(self.row_id, str) - assert isinstance(self.span_id, str) - assert isinstance(self.root_span_id, str) - assert self.row_id - assert self.span_id - assert self.root_span_id - - -@dataclasses.dataclass -class SpanComponentsV1: - object_type: SpanObjectTypeV1 - object_id: str - row_ids: SpanRowIdsV1 | None = None - - def __post_init__(self): - assert isinstance(self.object_type, SpanObjectTypeV1) - assert isinstance(self.object_id, str) - if self.row_ids is not None: - assert isinstance(self.row_ids, SpanRowIdsV1) - - def to_str(self) -> str: - # Our binary object format is as follows: - # - Byte 0 encodes the version number of the encoded string. This is - # used to check for incompatibilities with previous iterations. - # - Byte 1 encodes the SpanObjectTypeV1. - # - Byte 2 (0 or 1) describes whether or not the (row_id, - # span_id, root_span_id) triple is present. - # - Byte 3 (0 or 1) describes whether or not the row_id component - # is a UUID. If not, it is assumed to be a utf-8 encoded string. - # - Bytes 4-19 encode the object_id as a UUID - # - If the row triple is present, bytes 20-51 encode the span_id + - # root_span_id as a UUID. - # - If the row triple is present, the remaining bytes encode the - # row_id either as UUID or as UTF-8. - - if self.row_ids: - row_id_bytes, row_id_is_uuid = _try_make_uuid(self.row_ids.row_id) - else: - row_id_bytes, row_id_is_uuid = None, False - - raw_bytes = bytes( - [ - ENCODING_VERSION_NUMBER, - self.object_type.value, - 1 if self.row_ids else 0, - 1 if row_id_is_uuid else 0, - ] - ) - - object_id_bytes, object_id_is_uuid = _try_make_uuid(self.object_id) - if not object_id_is_uuid: - raise Exception("object_id component must be a valid UUID") - raw_bytes += object_id_bytes - - if self.row_ids: - span_id_bytes, span_id_is_uuid = _try_make_uuid(self.row_ids.span_id) - if not span_id_is_uuid: - raise Exception("span_id component must be a valid UUID") - root_span_id_bytes, root_span_id_is_uuid = _try_make_uuid(self.row_ids.root_span_id) - if not root_span_id_is_uuid: - raise Exception("root_span_id component must be a valid UUID") - raw_bytes += span_id_bytes - raw_bytes += root_span_id_bytes - raw_bytes += row_id_bytes - - return base64.b64encode(raw_bytes).decode() - - @staticmethod - def from_str(s: str) -> "SpanComponentsV1": - try: - raw_bytes = base64.b64decode(s.encode()) - assert raw_bytes[0] == ENCODING_VERSION_NUMBER - object_type = SpanObjectTypeV1(raw_bytes[1]) - assert raw_bytes[2] in [0, 1] - assert raw_bytes[3] in [0, 1] - has_row_id = raw_bytes[2] == 1 - row_id_is_uuid = raw_bytes[3] == 1 - - object_id = str(UUID(bytes=raw_bytes[4:20])) - if has_row_id: - span_id = str(UUID(bytes=raw_bytes[20:36])) - root_span_id = str(UUID(bytes=raw_bytes[36:52])) - if row_id_is_uuid: - row_id = str(UUID(bytes=raw_bytes[52:])) - else: - row_id = raw_bytes[52:].decode("utf-8") - row_ids = SpanRowIdsV1(row_id=row_id, span_id=span_id, root_span_id=root_span_id) - else: - row_ids = None - - return SpanComponentsV1(object_type=object_type, object_id=object_id, row_ids=row_ids) - except Exception: - raise Exception(INVALID_ENCODING_ERRMSG) - - def object_id_fields(self): - if self.object_type == SpanObjectTypeV1.EXPERIMENT: - return dict(experiment_id=self.object_id) - elif self.object_type == SpanObjectTypeV1.PROJECT_LOGS: - return dict(project_id=self.object_id, log_id="g") diff --git a/py/src/braintrust/span_identifier_v2.py b/py/src/braintrust/span_identifier_v2.py deleted file mode 100644 index 389db18ba..000000000 --- a/py/src/braintrust/span_identifier_v2.py +++ /dev/null @@ -1,217 +0,0 @@ -# Serialization format for capturing all relevant information about a span -# necessary for distributed logging / tracing. Meant to be passed around as an -# opaque string. - -import base64 -import dataclasses -import json -from enum import Enum -from uuid import UUID - -from .span_identifier_v1 import SpanComponentsV1 - - -def _try_make_uuid(s): - try: - ret = UUID(s).bytes - assert len(ret) == 16 - return ret, True - except Exception: - return s.encode("utf-8"), False - - -ENCODING_VERSION_NUMBER = 2 -INTEGER_ENCODING_NUM_BYTES = 4 -INTEGER_ENCODING_BYTEORDER = "big" - -INVALID_ENCODING_ERRMSG = f"SpanComponents string is not properly encoded. This library only supports encoding versions up to {ENCODING_VERSION_NUMBER}. Please make sure the SDK library used to decode the SpanComponents is at least as new as any library used to encode it." - - -class SpanObjectTypeV2(Enum): - EXPERIMENT = 1 - PROJECT_LOGS = 2 - - def __str__(self): - return {SpanObjectTypeV2.EXPERIMENT: "experiment", SpanObjectTypeV2.PROJECT_LOGS: "project_logs"}[self] - - -@dataclasses.dataclass -class SpanRowIdsV2: - row_id: str - span_id: str - root_span_id: str - - def __post_init__(self): - assert isinstance(self.row_id, str) - assert isinstance(self.span_id, str) - assert isinstance(self.root_span_id, str) - assert self.row_id - assert self.span_id - assert self.root_span_id - - -@dataclasses.dataclass -class SpanComponentsV2: - object_type: SpanObjectTypeV2 - object_id: str | None = None - compute_object_metadata_args: dict | None = None - row_ids: SpanRowIdsV2 | None = None - - def __post_init__(self): - assert isinstance(self.object_type, SpanObjectTypeV2) - assert self.object_id or self.compute_object_metadata_args, ( - "Must provide either object_id or compute_object_metadata_args" - ) - if self.object_id: - assert isinstance(self.object_id, str) - else: - assert isinstance(self.compute_object_metadata_args, dict) - if self.row_ids is not None: - assert isinstance(self.row_ids, SpanRowIdsV2) - - def to_str(self) -> str: - # Our binary object format is as follows: - # - Byte 0 encodes the version number of the encoded string. This is - # used to check for incompatibilities with previous iterations. - # - Byte 1 encodes the SpanObjectTypeV2. - # - Byte 2 (0 or 1) encodes whether or not we have an object_id. - # - Byte 3 (0 or 1) encodes whether or not we have - # compute_object_metadata_args. - # - Byte 4 (0 or 1) describes whether or not the (row_id, - # span_id, root_span_id) triple is present. - # - Byte 5 (0 or 1) describes whether or not the row_id component - # is a UUID. If not, it is assumed to be a utf-8 encoded string. - # - If [byte 2] == 1, the next 16 bytes encode the object_id as a UUID. - # - If [byte 3] == 1, the next [INTEGER_ENCODING_NUM_BYTES] bytes - # encode the length of the serialized compute_object_metadata_args. The next - # [length] bytes contain the serialized compute_object_metadata_args. - # - If [byte 4] == 1, the next 32 bytes encode the span_id + - # root_span_id as UUIDs. - # - If the row triple is present, the remaining bytes encode the - # row_id either as UUID or as UTF-8. - - if self.row_ids: - row_id_bytes, row_id_is_uuid = _try_make_uuid(self.row_ids.row_id) - else: - row_id_bytes, row_id_is_uuid = None, False - - raw_bytes = bytes( - [ - ENCODING_VERSION_NUMBER, - self.object_type.value, - 1 if self.object_id else 0, - 1 if self.compute_object_metadata_args else 0, - 1 if self.row_ids else 0, - 1 if row_id_is_uuid else 0, - ] - ) - - if self.object_id: - object_id_bytes, object_id_is_uuid = _try_make_uuid(self.object_id) - if not object_id_is_uuid: - raise Exception("object_id component must be a valid UUID") - raw_bytes += object_id_bytes - - if self.compute_object_metadata_args: - compute_object_metadata_bytes = bytes(json.dumps(self.compute_object_metadata_args).encode()) - serialized_len_bytes = len(compute_object_metadata_bytes).to_bytes( - INTEGER_ENCODING_NUM_BYTES, byteorder=INTEGER_ENCODING_BYTEORDER - ) - raw_bytes += serialized_len_bytes - raw_bytes += compute_object_metadata_bytes - - if self.row_ids: - span_id_bytes, span_id_is_uuid = _try_make_uuid(self.row_ids.span_id) - if not span_id_is_uuid: - raise Exception("span_id component must be a valid UUID") - root_span_id_bytes, root_span_id_is_uuid = _try_make_uuid(self.row_ids.root_span_id) - if not root_span_id_is_uuid: - raise Exception("root_span_id component must be a valid UUID") - raw_bytes += span_id_bytes - raw_bytes += root_span_id_bytes - raw_bytes += row_id_bytes - - return base64.b64encode(raw_bytes).decode() - - @staticmethod - def from_str(s: str) -> "SpanComponentsV2": - try: - raw_bytes = base64.b64decode(s.encode()) - - if raw_bytes[0] < ENCODING_VERSION_NUMBER: - span_components_old = SpanComponentsV1.from_str(s) - object_type = SpanObjectTypeV2(span_components_old.object_type.value) - if span_components_old.row_ids: - row_ids = SpanRowIdsV2( - row_id=span_components_old.row_ids.row_id, - span_id=span_components_old.row_ids.span_id, - root_span_id=span_components_old.row_ids.root_span_id, - ) - else: - row_ids = None - return SpanComponentsV2( - object_type=object_type, object_id=span_components_old.object_id, row_ids=row_ids - ) - - assert raw_bytes[0] == ENCODING_VERSION_NUMBER - object_type = SpanObjectTypeV2(raw_bytes[1]) - for i in range(2, 6): - assert raw_bytes[i] in [0, 1] - has_object_id = raw_bytes[2] - has_compute_object_metadata_args = raw_bytes[3] - has_row_id = raw_bytes[4] == 1 - row_id_is_uuid = raw_bytes[5] == 1 - - byte_cursor = 6 - if has_object_id: - next_byte_cursor = byte_cursor + 16 - object_id = str(UUID(bytes=raw_bytes[byte_cursor:next_byte_cursor])) - byte_cursor = next_byte_cursor - else: - object_id = None - - if has_compute_object_metadata_args: - next_byte_cursor = byte_cursor + INTEGER_ENCODING_NUM_BYTES - serialized_len_bytes = int.from_bytes( - raw_bytes[byte_cursor:next_byte_cursor], byteorder=INTEGER_ENCODING_BYTEORDER - ) - byte_cursor = next_byte_cursor - next_byte_cursor = byte_cursor + serialized_len_bytes - compute_object_metadata_args = json.loads(raw_bytes[byte_cursor:next_byte_cursor].decode()) - byte_cursor = next_byte_cursor - else: - compute_object_metadata_args = None - - if has_row_id: - next_byte_cursor = byte_cursor + 16 - span_id = str(UUID(bytes=raw_bytes[byte_cursor:next_byte_cursor])) - byte_cursor = next_byte_cursor - next_byte_cursor = byte_cursor + 16 - root_span_id = str(UUID(bytes=raw_bytes[byte_cursor:next_byte_cursor])) - byte_cursor = next_byte_cursor - if row_id_is_uuid: - row_id = str(UUID(bytes=raw_bytes[byte_cursor:])) - else: - row_id = raw_bytes[byte_cursor:].decode("utf-8") - row_ids = SpanRowIdsV2(row_id=row_id, span_id=span_id, root_span_id=root_span_id) - else: - row_ids = None - - return SpanComponentsV2( - object_type=object_type, - object_id=object_id, - compute_object_metadata_args=compute_object_metadata_args, - row_ids=row_ids, - ) - except Exception: - raise Exception(INVALID_ENCODING_ERRMSG) - - def object_id_fields(self): - if not self.object_id: - raise Exception( - "Impossible: cannot invoke `object_id_fields` unless SpanComponentsV2 is initialized with an `object_id`" - ) - if self.object_type == SpanObjectTypeV2.EXPERIMENT: - return dict(experiment_id=self.object_id) - elif self.object_type == SpanObjectTypeV2.PROJECT_LOGS: - return dict(project_id=self.object_id, log_id="g") diff --git a/py/src/braintrust/span_identifier_v3.py b/py/src/braintrust/span_identifier_v3.py deleted file mode 100644 index d86903153..000000000 --- a/py/src/braintrust/span_identifier_v3.py +++ /dev/null @@ -1,280 +0,0 @@ -# Serialization format for capturing all relevant information about a span -# necessary for distributed logging / tracing. Meant to be passed around as an -# opaque string. - -import base64 -import dataclasses -import json -from enum import Enum -from uuid import UUID - -from .span_identifier_v2 import SpanComponentsV2 - - -def _try_make_uuid(s): - try: - ret = UUID(s).bytes - assert len(ret) == 16 - return ret, True - except Exception: - return None, False - - -ENCODING_VERSION_NUMBER = 3 - -INVALID_ENCODING_ERRMSG = f"SpanComponents string is not properly encoded. This library only supports encoding versions up to {ENCODING_VERSION_NUMBER}. Please make sure the SDK library used to decode the SpanComponents is at least as new as any library used to encode it." - - -class SpanObjectTypeV3(Enum): - EXPERIMENT = 1 - PROJECT_LOGS = 2 - PLAYGROUND_LOGS = 3 - - def __str__(self): - return { - SpanObjectTypeV3.EXPERIMENT: "experiment", - SpanObjectTypeV3.PROJECT_LOGS: "project_logs", - SpanObjectTypeV3.PLAYGROUND_LOGS: "playground_logs", - }[self] - - -def span_object_type_v3_to_typed_string( - object_type: SpanObjectTypeV3, -) -> str: - """Convert SpanObjectTypeV3 enum to typed string literal. - - Args: - object_type: The SpanObjectTypeV3 enum value - - Returns: - One of "experiment", "project_logs", or "playground_logs" - """ - if object_type == SpanObjectTypeV3.EXPERIMENT: - return "experiment" - elif object_type == SpanObjectTypeV3.PROJECT_LOGS: - return "project_logs" - elif object_type == SpanObjectTypeV3.PLAYGROUND_LOGS: - return "playground_logs" - else: - raise ValueError(f"Unknown SpanObjectTypeV3: {object_type}") - - -class InternalSpanComponentUUIDFields(Enum): - OBJECT_ID = 1 - ROW_ID = 2 - SPAN_ID = 3 - ROOT_SPAN_ID = 4 - - -_INTERNAL_SPAN_COMPONENT_UUID_FIELDS_ID_TO_NAME = { - InternalSpanComponentUUIDFields.OBJECT_ID: "object_id", - InternalSpanComponentUUIDFields.ROW_ID: "row_id", - InternalSpanComponentUUIDFields.SPAN_ID: "span_id", - InternalSpanComponentUUIDFields.ROOT_SPAN_ID: "root_span_id", -} - - -@dataclasses.dataclass -class SpanComponentsV3: - object_type: SpanObjectTypeV3 - - # Must provide one or the other. - object_id: str | None = None - compute_object_metadata_args: dict | None = None - - # Either all of these must be provided or none. - row_id: str | None = None - span_id: str | None = None - root_span_id: str | None = None - - # Additional span properties. - propagated_event: dict | None = None - - def __post_init__(self): - assert isinstance(self.object_type, SpanObjectTypeV3) - - assert not (self.object_id and self.compute_object_metadata_args) - assert self.object_id or self.compute_object_metadata_args - if self.object_id is not None: - assert isinstance(self.object_id, str) - elif self.compute_object_metadata_args: - assert isinstance(self.compute_object_metadata_args, dict) - - if self.row_id: - assert isinstance(self.row_id, str) - assert self.span_id - assert isinstance(self.span_id, str) - assert self.root_span_id - assert isinstance(self.root_span_id, str) - else: - assert not self.span_id - assert not self.root_span_id - - def to_str(self) -> str: - # Our binary object format is as follows: - # - Byte 0 encodes the version number of the encoded string. This is - # used to check for incompatibilities with previous iterations. - # - Byte 1 encodes the SpanObjectTypeV3. - # - Byte 2 encodes the number of UUID fields we have serialized in a - # compressed form. - # - For each of the specially-serialized UUID fields, we encode one - # byte for InternalSpanComponentUUIDFields, denoting which field it - # is, followed by the 16 bytes of the UUID. - # - The remaining bytes encode the remaining object properties in JSON - # format, or nothing if the JSON object is empty. - json_obj = dict( - compute_object_metadata_args=self.compute_object_metadata_args or None, - propagated_event=self.propagated_event or None, - ) - json_obj = {k: v for k, v in json_obj.items() if v is not None} - raw_bytes = bytes( - [ - ENCODING_VERSION_NUMBER, - self.object_type.value, - ] - ) - - uuid_entries = [] - - def add_uuid_field(orig_val, field_id): - nonlocal uuid_entries - - uuid_bytes, is_uuid = _try_make_uuid(orig_val) - if is_uuid: - uuid_entries.append(bytes([field_id.value]) + uuid_bytes) - else: - json_obj[_INTERNAL_SPAN_COMPONENT_UUID_FIELDS_ID_TO_NAME[field_id]] = orig_val - - if self.object_id: - add_uuid_field(self.object_id, InternalSpanComponentUUIDFields.OBJECT_ID) - if self.row_id: - add_uuid_field(self.row_id, InternalSpanComponentUUIDFields.ROW_ID) - if self.span_id: - add_uuid_field(self.span_id, InternalSpanComponentUUIDFields.SPAN_ID) - if self.root_span_id: - add_uuid_field(self.root_span_id, InternalSpanComponentUUIDFields.ROOT_SPAN_ID) - - if len(uuid_entries) > 255: - raise Exception("Impossible: too many UUID entries to encode") - raw_bytes += bytes([len(uuid_entries)]) - for entry in uuid_entries: - raw_bytes += entry - if json_obj: - raw_bytes += bytes(json.dumps(json_obj, separators=(",", ":")).encode()) - return base64.b64encode(raw_bytes).decode() - - @staticmethod - def from_str(s: str) -> "SpanComponentsV3": - try: - raw_bytes = base64.b64decode(s.encode()) - json_obj = {} - if raw_bytes[0] < ENCODING_VERSION_NUMBER: - span_components_old = SpanComponentsV2.from_str(s) - json_obj["object_type"] = span_components_old.object_type.value - json_obj["object_id"] = span_components_old.object_id - json_obj["compute_object_metadata_args"] = span_components_old.compute_object_metadata_args - if span_components_old.row_ids: - json_obj["row_id"] = span_components_old.row_ids.row_id - json_obj["span_id"] = span_components_old.row_ids.span_id - json_obj["root_span_id"] = span_components_old.row_ids.root_span_id - else: - json_obj["object_type"] = SpanObjectTypeV3(raw_bytes[1]) - num_uuid_entries = raw_bytes[2] - byte_offset = 3 - for i in range(num_uuid_entries): - field_id = InternalSpanComponentUUIDFields(raw_bytes[byte_offset]) - uuid_bytes = raw_bytes[byte_offset + 1 : byte_offset + 17] - byte_offset += 17 - json_obj[_INTERNAL_SPAN_COMPONENT_UUID_FIELDS_ID_TO_NAME[field_id]] = str(UUID(bytes=uuid_bytes)) - if byte_offset < len(raw_bytes): - remaining_json_obj = json.loads(raw_bytes[byte_offset:].decode()) - json_obj.update(remaining_json_obj) - return SpanComponentsV3._from_json_obj(json_obj) - except Exception: - raise Exception(INVALID_ENCODING_ERRMSG) - - def object_id_fields(self) -> dict[str, str]: - if not self.object_id: - raise Exception( - "Impossible: cannot invoke `object_id_fields` unless SpanComponentsV3 is initialized with an `object_id`" - ) - if self.object_type == SpanObjectTypeV3.EXPERIMENT: - return dict(experiment_id=self.object_id) - elif self.object_type == SpanObjectTypeV3.PROJECT_LOGS: - return dict(project_id=self.object_id, log_id="g") - elif self.object_type == SpanObjectTypeV3.PLAYGROUND_LOGS: - return dict(prompt_session_id=self.object_id, log_id="x") - else: - raise Exception(f"Invalid object_type {self.object_type}") - - def export(self) -> str: - """Return a serialized representation compatible with other exportable objects.""" - return self.to_str() - - @staticmethod - def _from_json_obj(json_obj: dict) -> "SpanComponentsV3": - kwargs = { - **json_obj, - "object_type": SpanObjectTypeV3(json_obj["object_type"]), - } - return SpanComponentsV3(**kwargs) - - -def parse_parent(parent: str | dict | None) -> str | None: - """ - Parse a parent object into a string representation. - - Args: - parent: Can be: - - A string (returned as-is) - - A dict with object_type, object_id, and optional row_ids - - None (returns None) - - Returns: - String representation of the parent or None - """ - if isinstance(parent, str): - return parent - elif parent: - # Map object_type strings to SpanObjectTypeV3 enum values - object_type_map = { - "experiment": SpanObjectTypeV3.EXPERIMENT, - "playground_logs": SpanObjectTypeV3.PLAYGROUND_LOGS, - "project_logs": SpanObjectTypeV3.PROJECT_LOGS, - } - - object_type = object_type_map.get(parent.get("object_type")) - if not object_type: - raise ValueError(f"Invalid object_type: {parent.get('object_type')}") - - kwargs = { - "object_type": object_type, - "object_id": parent.get("object_id"), - } - - # Handle row_ids if present - row_ids = parent.get("row_ids") - if row_ids: - kwargs.update( - { - "row_id": row_ids.get("id"), - "span_id": row_ids.get("span_id"), - "root_span_id": row_ids.get("root_span_id"), - } - ) - else: - kwargs.update( - { - "row_id": None, - "span_id": None, - "root_span_id": None, - } - ) - - # Include propagated_event if present - if "propagated_event" in parent: - kwargs["propagated_event"] = parent.get("propagated_event") - - return SpanComponentsV3(**kwargs).to_str() - else: - return None diff --git a/py/src/braintrust/span_identifier_v4.py b/py/src/braintrust/span_identifier_v4.py deleted file mode 100644 index a3db4c80d..000000000 --- a/py/src/braintrust/span_identifier_v4.py +++ /dev/null @@ -1,279 +0,0 @@ -# SpanComponentsV4: Binary serialization like V3 but with hex string compression -# Uses 16-byte encoding for trace IDs and 8-byte encoding for span IDs - -import base64 -import dataclasses -import json -from enum import Enum - -from .span_identifier_v3 import ( - SpanComponentsV3, - SpanObjectTypeV3, -) - -ENCODING_VERSION_NUMBER_V4 = 4 - - -def _try_make_hex_trace_id(s): - """Try to convert hex string to 16-byte binary (for trace IDs)""" - try: - if isinstance(s, str) and len(s) == 32: # 32 hex chars = 16 bytes - ret = bytes.fromhex(s) - assert len(ret) == 16 - return ret, True - except Exception: - pass - return None, False - - -def _try_make_hex_span_id(s): - """Try to convert hex string to 8-byte binary (for span IDs)""" - try: - if isinstance(s, str) and len(s) == 16: # 16 hex chars = 8 bytes - ret = bytes.fromhex(s) - assert len(ret) == 8 - return ret, True - except Exception: - pass - return None, False - - -INVALID_ENCODING_ERRMSG_V4 = f"SpanComponents string is not properly encoded. This library only supports encoding versions up to {ENCODING_VERSION_NUMBER_V4}. Please make sure the SDK library used to decode the SpanComponents is at least as new as any library used to encode it." - - -class Fields(Enum): - OBJECT_ID = 1 - ROW_ID = 2 - SPAN_ID = 3 # 8-byte hex - ROOT_SPAN_ID = 4 # 16-byte hex - - -_FIELDS_ID_TO_NAME = { - Fields.OBJECT_ID: "object_id", - Fields.ROW_ID: "row_id", - Fields.SPAN_ID: "span_id", - Fields.ROOT_SPAN_ID: "root_span_id", -} - - -@dataclasses.dataclass -class SpanComponentsV4: - object_type: SpanObjectTypeV3 - - # Must provide one or the other. - object_id: str | None = None - compute_object_metadata_args: dict | None = None - - # Either all of these must be provided or none. - row_id: str | None = None - span_id: str | None = None - root_span_id: str | None = None - - # Additional span properties. - propagated_event: dict | None = None - - def __post_init__(self): - # Reuse V3 validation logic - assert isinstance(self.object_type, SpanObjectTypeV3) - - assert not (self.object_id and self.compute_object_metadata_args) - assert self.object_id or self.compute_object_metadata_args - if self.object_id is not None: - assert isinstance(self.object_id, str) - elif self.compute_object_metadata_args: - assert isinstance(self.compute_object_metadata_args, dict) - - if self.row_id: - assert isinstance(self.row_id, str) - assert self.span_id - assert isinstance(self.span_id, str) - assert self.root_span_id - assert isinstance(self.root_span_id, str) - else: - assert not self.span_id - assert not self.root_span_id - - def to_str(self) -> str: - # V3-style binary encoding with hex string compression - # Binary format: version_byte + object_type_byte + num_hex_fields + hex_entries + json_remainder - json_obj = dict( - compute_object_metadata_args=self.compute_object_metadata_args or None, - propagated_event=self.propagated_event or None, - ) - json_obj = {k: v for k, v in json_obj.items() if v is not None} - - raw_bytes = bytes( - [ - ENCODING_VERSION_NUMBER_V4, - self.object_type.value, - ] - ) - - hex_entries = [] - - def add_hex_field(orig_val, field_id): - nonlocal hex_entries - - if field_id == Fields.SPAN_ID: - hex_bytes, is_hex = _try_make_hex_span_id(orig_val) - elif field_id == Fields.ROOT_SPAN_ID: - hex_bytes, is_hex = _try_make_hex_trace_id(orig_val) - else: - hex_bytes, is_hex = None, False - - if is_hex: - hex_entries.append(bytes([field_id.value]) + hex_bytes) - else: - json_obj[_FIELDS_ID_TO_NAME[field_id]] = orig_val - - if self.object_id: - add_hex_field(self.object_id, Fields.OBJECT_ID) - if self.row_id: - add_hex_field(self.row_id, Fields.ROW_ID) - if self.span_id: - add_hex_field(self.span_id, Fields.SPAN_ID) - if self.root_span_id: - add_hex_field(self.root_span_id, Fields.ROOT_SPAN_ID) - - if len(hex_entries) > 255: - raise Exception("Impossible: too many hex entries to encode") - raw_bytes += bytes([len(hex_entries)]) - for entry in hex_entries: - raw_bytes += entry - if json_obj: - raw_bytes += bytes(json.dumps(json_obj, separators=(",", ":")).encode()) - return base64.b64encode(raw_bytes).decode() - - @staticmethod - def get_version(slug: str) -> int: - """ - Extract the encoding version number from a serialized span components slug. - - :param slug: Base64-encoded span components string - :returns: Version number (3 for V3, 4 for V4, etc.) - """ - raw_bytes = base64.b64decode(slug) - return raw_bytes[0] - - @staticmethod - def from_str(s: str) -> "SpanComponentsV4": - try: - raw_bytes = base64.b64decode(s.encode()) - json_obj = {} - - if raw_bytes[0] < ENCODING_VERSION_NUMBER_V4: - # Handle older versions by delegating to V3 - v3_components = SpanComponentsV3.from_str(s) - return SpanComponentsV4( - object_type=v3_components.object_type, - object_id=v3_components.object_id, - compute_object_metadata_args=v3_components.compute_object_metadata_args, - row_id=v3_components.row_id, - span_id=v3_components.span_id, - root_span_id=v3_components.root_span_id, - propagated_event=v3_components.propagated_event, - ) - else: - # V4 binary format - json_obj["object_type"] = SpanObjectTypeV3(raw_bytes[1]) - num_hex_entries = raw_bytes[2] - byte_offset = 3 - - for i in range(num_hex_entries): - field_id = Fields(raw_bytes[byte_offset]) - if field_id == Fields.SPAN_ID: - # 8-byte span ID - hex_bytes = raw_bytes[byte_offset + 1 : byte_offset + 9] - byte_offset += 9 - json_obj[_FIELDS_ID_TO_NAME[field_id]] = hex_bytes.hex() - elif field_id == Fields.ROOT_SPAN_ID: - # 16-byte trace ID - hex_bytes = raw_bytes[byte_offset + 1 : byte_offset + 17] - byte_offset += 17 - json_obj[_FIELDS_ID_TO_NAME[field_id]] = hex_bytes.hex() - else: - # Should not happen for object_id/row_id in V4, but handle gracefully - hex_bytes = raw_bytes[byte_offset + 1 : byte_offset + 17] # assume 16 bytes - byte_offset += 17 - json_obj[_FIELDS_ID_TO_NAME[field_id]] = hex_bytes.hex() - - if byte_offset < len(raw_bytes): - remaining_json_obj = json.loads(raw_bytes[byte_offset:].decode()) - json_obj.update(remaining_json_obj) - - return SpanComponentsV4._from_json_obj(json_obj) - except Exception: - raise Exception(INVALID_ENCODING_ERRMSG_V4) - - def object_id_fields(self) -> dict[str, str]: - # Reuse V3 logic - if not self.object_id: - raise Exception( - "Impossible: cannot invoke `object_id_fields` unless SpanComponentsV4 is initialized with an `object_id`" - ) - if self.object_type == SpanObjectTypeV3.EXPERIMENT: - return dict(experiment_id=self.object_id) - elif self.object_type == SpanObjectTypeV3.PROJECT_LOGS: - return dict(project_id=self.object_id, log_id="g") - elif self.object_type == SpanObjectTypeV3.PLAYGROUND_LOGS: - return dict(prompt_session_id=self.object_id, log_id="x") - else: - raise Exception(f"Invalid object_type {self.object_type}") - - def export(self) -> str: - return self.to_str() - - @staticmethod - def _from_json_obj(json_obj: dict) -> "SpanComponentsV4": - kwargs = { - **json_obj, - "object_type": SpanObjectTypeV3(json_obj["object_type"]), - } - return SpanComponentsV4(**kwargs) - - -def parse_parent(parent: str | dict | None) -> str | None: - """Parse a parent object into a string representation using V4 format.""" - # Reuse V3 logic but with V4 components - if isinstance(parent, str): - return parent - elif parent: - object_type_map = { - "experiment": SpanObjectTypeV3.EXPERIMENT, - "playground_logs": SpanObjectTypeV3.PLAYGROUND_LOGS, - "project_logs": SpanObjectTypeV3.PROJECT_LOGS, - } - - object_type = object_type_map.get(parent.get("object_type")) - if not object_type: - raise ValueError(f"Invalid object_type: {parent.get('object_type')}") - - kwargs = { - "object_type": object_type, - "object_id": parent.get("object_id"), - } - - row_ids = parent.get("row_ids") - if row_ids: - kwargs.update( - { - "row_id": row_ids.get("id"), - "span_id": row_ids.get("span_id"), - "root_span_id": row_ids.get("root_span_id"), - } - ) - else: - kwargs.update( - { - "row_id": None, - "span_id": None, - "root_span_id": None, - } - ) - - if "propagated_event" in parent: - kwargs["propagated_event"] = parent.get("propagated_event") - - return SpanComponentsV4(**kwargs).to_str() - else: - return None diff --git a/py/src/braintrust/span_types.py b/py/src/braintrust/span_types.py deleted file mode 100644 index d77a071ca..000000000 --- a/py/src/braintrust/span_types.py +++ /dev/null @@ -1,23 +0,0 @@ -from enum import Enum - - -class SpanTypeAttribute(str, Enum): - """ - Use `SpanType` instead. - :deprecated: - """ - - LLM = "llm" - SCORE = "score" - FUNCTION = "function" - EVAL = "eval" - TASK = "task" - TOOL = "tool" - AUTOMATION = "automation" - FACET = "facet" - PREPROCESSOR = "preprocessor" - REVIEW = "review" - - -class SpanPurpose(str, Enum): - SCORER = "scorer" diff --git a/py/src/braintrust/test_bt_json.py b/py/src/braintrust/test_bt_json.py deleted file mode 100644 index f67f7c69f..000000000 --- a/py/src/braintrust/test_bt_json.py +++ /dev/null @@ -1,643 +0,0 @@ -# pyright: reportUnknownVariableType=false -# pyright: reportUnknownArgumentType=false -# pyright: reportPrivateUsage=false -import json -from typing import Any -from unittest import TestCase - -import pytest -from braintrust.bt_json import bt_dumps, bt_safe_deep_copy -from braintrust.logger import Attachment, ExternalAttachment - - -class TestBTJson(TestCase): - def testdeep_copy_event_basic(self): - original = { - "input": {"foo": "bar", "null": None, "empty": {}}, - "output": [1, 2, "3", None, {}], - } - copy = bt_safe_deep_copy(original) - self.assertEqual(copy, original) - self.assertIsNot(copy, original) - self.assertIsNot(copy["input"], original["input"]) - self.assertIsNot(copy["output"], original["output"]) - - def test_deep_copy_mutation_independence(self): - """Test that mutating the copy doesn't affect the original (true dereferencing).""" - original = { - "top_level": "value", - "nested_dict": {"inner": "data", "deep": {"level": 3}}, - "nested_list": [1, 2, [3, 4]], - "nested_in_list": [{"key": "val"}], - } - - copy = bt_safe_deep_copy(original) - - # Mutate the copy at various levels - copy["top_level"] = "MODIFIED" - copy["nested_dict"]["inner"] = "MODIFIED" - copy["nested_dict"]["deep"]["level"] = 999 - copy["nested_list"][0] = 999 - copy["nested_list"][2][0] = 999 - copy["nested_in_list"][0]["key"] = "MODIFIED" - - # Verify original is unchanged - self.assertEqual(original["top_level"], "value") - self.assertEqual(original["nested_dict"]["inner"], "data") - self.assertEqual(original["nested_dict"]["deep"]["level"], 3) - self.assertEqual(original["nested_list"][0], 1) - self.assertEqual(original["nested_list"][2][0], 3) - self.assertEqual(original["nested_in_list"][0]["key"], "val") - - # Add new keys to copy - copy["new_key"] = "new_value" - copy["nested_dict"]["new_inner"] = "new" - - # Verify original doesn't have these keys - self.assertNotIn("new_key", original) - self.assertNotIn("new_inner", original["nested_dict"]) - - def testdeep_copy_event_with_attachments(self): - attachment1 = Attachment( - data=b"data", - filename="filename", - content_type="text/plain", - ) - attachment2 = Attachment( - data=b"data2", - filename="filename2", - content_type="text/plain", - ) - attachment3 = ExternalAttachment( - url="s3://bucket/path/to/key.pdf", - filename="filename3", - content_type="application/pdf", - ) - date = "2024-10-23T05:02:48.796Z" - - original = { - "input": "Testing", - "output": { - "span": "", - "myIllegalObjects": ["", "", ""], - "myOtherWeirdObjects": [None, date, None, None], - "attachment": attachment1, - "another_attachment": attachment3, - "attachmentList": [attachment1, attachment2, "string", attachment3], - "nestedAttachment": { - "attachment": attachment2, - "another_attachment": attachment3, - }, - "fake": { - "_bt_internal_saved_attachment": "not a number", - }, - }, - } - - copy = bt_safe_deep_copy(original) - - self.assertEqual( - copy, - { - "input": "Testing", - "output": { - "span": "", - "myIllegalObjects": ["", "", ""], - "myOtherWeirdObjects": [None, date, None, None], - "attachment": attachment1, - "another_attachment": attachment3, - "attachmentList": [attachment1, attachment2, "string", attachment3], - "nestedAttachment": { - "attachment": attachment2, - "another_attachment": attachment3, - }, - "fake": { - "_bt_internal_saved_attachment": "not a number", - }, - }, - }, - ) - - self.assertIsNot(copy, original) - - self.assertIs(copy["output"]["attachment"], attachment1) - self.assertIs(copy["output"]["another_attachment"], attachment3) - self.assertIs(copy["output"]["nestedAttachment"]["attachment"], attachment2) - self.assertIs(copy["output"]["nestedAttachment"]["another_attachment"], attachment3) - self.assertIs(copy["output"]["attachmentList"][0], attachment1) - self.assertIs(copy["output"]["attachmentList"][1], attachment2) - self.assertIs(copy["output"]["attachmentList"][3], attachment3) - - def test_bt_dumps_circular_references_raises(self): - """Test that bt_dumps raises on circular references in raw data. - - Note: bt_dumps without bt_safe_deep_copy will raise ValueError on circular refs. - Use bt_safe_deep_copy first to handle circular references gracefully. - """ - data: dict[str, Any] = {"a": "b"} - data["self"] = data - - with self.assertRaises(ValueError) as ctx: - bt_dumps(data) - self.assertIn("Circular reference", str(ctx.exception)) - - def test_deep_copy_binary_types(self): - """Test current handling of bytes, bytearray, memoryview through bt_dumps/bt_loads roundtrip.""" - data = { - "bytes": b"hello world", - "bytearray": bytearray(b"test data"), - "memoryview": memoryview(b"memory"), - "nested": {"embedded": b"\x00\x01\x02\x03"}, - } - result = bt_safe_deep_copy(data) - - # The function uses bt_dumps/bt_loads for non-container types, so binary - # gets JSON-serialized. Check what actually comes back: - self.assertIn("bytes", result) - self.assertIn("bytearray", result) - self.assertIn("memoryview", result) - self.assertIn("nested", result) - self.assertIn("embedded", result["nested"]) - - # Verify it's JSON-serializable (main goal of the function) - json_str = json.dumps(result) - self.assertIsInstance(json_str, str) - - def test_deep_copy_frozenset(self): - """Test current frozenset handling through JSON roundtrip.""" - data = {"frozen": frozenset([1, 2, 3])} - result = bt_safe_deep_copy(data) - - # frozenset goes through bt_dumps/bt_loads - it becomes a string representation - # since frozenset is not JSON-serializable, bt_dumps converts it to str - self.assertIn("frozen", result) - self.assertIsInstance(result["frozen"], str) - self.assertIn("frozenset", result["frozen"]) - - def test_deep_copy_empty_containers(self): - """Test handling of empty containers.""" - data = { - "empty_list": [], - "empty_dict": {}, - "empty_set": set(), - "nested": {"also_empty": {}}, - } - result = bt_safe_deep_copy(data) - - self.assertEqual(result["empty_list"], []) - self.assertEqual(result["empty_dict"], {}) - # empty set becomes empty list via JSON roundtrip - self.assertEqual(result["empty_set"], []) - self.assertEqual(result["nested"]["also_empty"], {}) - - def test_deep_copy_exactly_max_depth(self): - """Test behavior at exactly MAX_DEPTH (200).""" - # Create nested structure at depth 199 (just under limit) - nested = {"level": 0} - current = nested - for i in range(1, 199): - current["child"] = {"level": i} - current = current["child"] - - result = bt_safe_deep_copy(nested) - - # Should succeed - verify structure is preserved - self.assertEqual(result["level"], 0) - self.assertIn("child", result) - - # Walk down and verify depth - current_result = result - depth_reached = 0 - while "child" in current_result: - current_result = current_result["child"] - depth_reached += 1 - self.assertEqual(depth_reached, 198) # 199 levels total (0 to 198) - - def test_deep_copy_exceeds_max_depth(self): - """Test behavior exceeding MAX_DEPTH (200).""" - # Create nested structure at depth 201 (exceeds limit) - nested = {"level": 0} - current = nested - for i in range(1, 201): - current["child"] = {"level": i} - current = current["child"] - - result = bt_safe_deep_copy(nested) - - # Should have root level preserved - self.assertEqual(result["level"], 0) - - # Walk down until we find the truncation marker - current_result = result - depth_reached = 0 - truncation_found = False - while isinstance(current_result, dict) and "child" in current_result: - current_result = current_result["child"] - depth_reached += 1 - if current_result == "": - truncation_found = True - break - - self.assertTrue(truncation_found, f"Expected truncation marker at depth {depth_reached}") - self.assertLessEqual(depth_reached, 200) # Should truncate at or before MAX_DEPTH - - def test_deep_copy_non_stringifiable_keys(self): - """Test dict with keys that can't be converted to string.""" - - class BadKey: - def __str__(self): - raise RuntimeError("Cannot stringify") - - data = {BadKey(): "value"} - result = bt_safe_deep_copy(data) - - # Should have fallback key from exception handler - keys = list(result.keys()) - self.assertEqual(len(keys), 1) - - # The fallback should contain type name and indicate it's non-stringifiable - key = keys[0] - self.assertTrue("non-stringifiable" in key.lower() or "BadKey" in key) - self.assertEqual(result[key], "value") - - def test_deep_copy_numeric_and_special_keys(self): - """Test dict with various key types that need coercion.""" - data = { - 1: "int_key", - 2.5: "float_key", - True: "bool_key", - (1, 2): "tuple_key", - None: "none_key", - } - result = bt_safe_deep_copy(data) - - # All keys should be coerced to strings - self.assertTrue(all(isinstance(k, str) for k in result.keys())) - - # Verify values are preserved - # bool True coerces to "True", int 1 to "1" - they may conflict - self.assertTrue("1" in result or "True" in result) - self.assertIn("2.5", result) - # tuple str representation - self.assertTrue("(1, 2)" in result or "1, 2" in result) - self.assertIn("None", result) - -@pytest.mark.vcr -def test_to_bt_safe_special_objects(): - """Test _to_bt_safe handling of Span, Experiment, Dataset, Logger objects.""" - from braintrust import init, init_dataset, init_logger - - # Create actual objects - exp = init(project="test", experiment="test") - dataset = init_dataset(project="test", name="test") - logger = init_logger(project="test") - span = exp.start_span() - - # Import _to_bt_safe - from braintrust.bt_json import _to_bt_safe - - # Test each special object - assert _to_bt_safe(span) == "" - assert _to_bt_safe(exp) == "" - assert _to_bt_safe(dataset) == "" - assert _to_bt_safe(logger) == "" - - -class TestBTJsonAttachments(TestCase): - def test_to_bt_safe_attachments(self): - """Test _to_bt_safe preserves BaseAttachment and converts ReadonlyAttachment to reference.""" - from braintrust.bt_json import _to_bt_safe - - # Test BaseAttachment preservation - attachment = Attachment(data=b"test", filename="test.txt", content_type="text/plain") - result = _to_bt_safe(attachment) - self.assertIs(result, attachment) - - # Test ExternalAttachment preservation - ext_attachment = ExternalAttachment( - url="s3://bucket/key", filename="ext.pdf", content_type="application/pdf" - ) - result_ext = _to_bt_safe(ext_attachment) - self.assertIs(result_ext, ext_attachment) - - # Test ReadonlyAttachment conversion to reference - from braintrust.logger import ReadonlyAttachment - - reference = { - "type": "braintrust_attachment", - "key": "test-key", - "filename": "readonly.txt", - "content_type": "text/plain", - } - readonly = ReadonlyAttachment(reference) - result_readonly = _to_bt_safe(readonly) - self.assertEqual(result_readonly, reference) - self.assertIsNot(result_readonly, readonly) - - def test_to_bt_safe_pydantic_models(self): - """Test _to_bt_safe handling of Pydantic v1 and v2 models.""" - from braintrust.bt_json import _to_bt_safe - - try: - from pydantic import BaseModel - - class TestModel(BaseModel): - name: str - value: int - - model = TestModel(name="test", value=42) - result = _to_bt_safe(model) - - # Should convert to dict - self.assertIsInstance(result, dict) - self.assertEqual(result["name"], "test") - self.assertEqual(result["value"], 42) - except ImportError: - self.skipTest("Pydantic not available") - - def test_to_bt_safe_dataclasses(self): - """Test _to_bt_safe handling of dataclasses with attachment fields.""" - from dataclasses import dataclass - - from braintrust.bt_json import _to_bt_safe - - @dataclass - class SimpleData: - text: str - number: int - - @dataclass - class DataWithAttachment: - name: str - file: Attachment - - # Test simple dataclass - simple = SimpleData(text="hello", number=123) - result = _to_bt_safe(simple) - self.assertIsInstance(result, dict) - self.assertEqual(result["text"], "hello") - self.assertEqual(result["number"], 123) - - # Test dataclass with attachment field - attachment = Attachment(data=b"data", filename="file.txt", content_type="text/plain") - with_attachment = DataWithAttachment(name="test", file=attachment) - result_with_att = _to_bt_safe(with_attachment) - - self.assertIsInstance(result_with_att, dict) - self.assertEqual(result_with_att["name"], "test") - # The attachment should be preserved in the dict - self.assertIs(result_with_att["file"], attachment) - - def test_to_bt_safe_special_floats(self): - """Test _to_bt_safe handling of NaN, Infinity, -Infinity.""" - from braintrust.bt_json import _to_bt_safe - - self.assertEqual(_to_bt_safe(float("nan")), "NaN") - self.assertEqual(_to_bt_safe(float("inf")), "Infinity") - self.assertEqual(_to_bt_safe(float("-inf")), "-Infinity") - self.assertEqual(_to_bt_safe(1.5), 1.5) - self.assertEqual(_to_bt_safe(0.0), 0.0) - - def test_to_bt_safe_fallback_exceptions(self): - """Test _to_bt_safe graceful handling when serialization fails in bt_safe_deep_copy.""" - - class UnserializableObject: - def __init__(self): - self.data = "test" - - obj = UnserializableObject() - - # When called through bt_safe_deep_copy, exceptions are caught - result = bt_safe_deep_copy({"key": obj}) - - # The object should be in the result (after roundtrip through bt_dumps/bt_loads) - self.assertIn("key", result) - # The value might be stringified or converted depending on fallback behavior - self.assertIsNotNone(result["key"]) - - def test_bt_safe_deep_copy_attachment_identity(self): - """Test bt_safe_deep_copy preserves attachment object identity.""" - attachment1 = Attachment(data=b"data1", filename="file1.txt", content_type="text/plain") - attachment2 = ExternalAttachment( - url="s3://bucket/key", filename="file2.pdf", content_type="application/pdf" - ) - - original = { - "field1": attachment1, - "nested": {"field2": attachment2}, - "list": [attachment1, "string", attachment2], - } - - result = bt_safe_deep_copy(original) - - # Verify attachment identity is preserved (same object) - self.assertIs(result["field1"], attachment1) - self.assertIs(result["nested"]["field2"], attachment2) - self.assertIs(result["list"][0], attachment1) - self.assertIs(result["list"][2], attachment2) - - # But container objects are copied - self.assertIsNot(result, original) - self.assertIsNot(result["nested"], original["nested"]) - self.assertIsNot(result["list"], original["list"]) - - def test_bt_safe_deep_copy_mixed_attachment_types(self): - """Test bt_safe_deep_copy with BaseAttachment and ReadonlyAttachment together.""" - from braintrust.logger import ReadonlyAttachment - - base_attachment = Attachment(data=b"base", filename="base.txt", content_type="text/plain") - - reference = { - "type": "braintrust_attachment", - "key": "readonly-key", - "filename": "readonly.txt", - "content_type": "text/plain", - } - readonly_attachment = ReadonlyAttachment(reference) - - original = { - "base": base_attachment, - "readonly": readonly_attachment, - "mixed_list": [base_attachment, readonly_attachment], - } - - result = bt_safe_deep_copy(original) - - # BaseAttachment preserved as-is - self.assertIs(result["base"], base_attachment) - self.assertIs(result["mixed_list"][0], base_attachment) - - # ReadonlyAttachment converted to reference dict - self.assertEqual(result["readonly"], reference) - self.assertIsInstance(result["readonly"], dict) - self.assertEqual(result["mixed_list"][1], reference) - - def test_bt_safe_deep_copy_circular_with_attachments(self): - """Test circular reference detection with attachments in the structure.""" - attachment = Attachment(data=b"data", filename="file.txt", content_type="text/plain") - - # Create circular structure with attachment - circular: dict[str, Any] = {"attachment": attachment, "data": "test"} - circular["self"] = circular - - result = bt_safe_deep_copy(circular) - - # Attachment should be preserved - self.assertIs(result["attachment"], attachment) - self.assertEqual(result["data"], "test") - - # Circular reference should be detected - self.assertEqual(result["self"], "") - - def test_bt_safe_deep_copy_containers_with_attachments(self): - """Test tuple, set, and nested containers with attachments.""" - attachment = Attachment(data=b"data", filename="file.txt", content_type="text/plain") - - original = { - "tuple_with_attachment": (attachment, "string", 123), - "set_with_attachment": {attachment, "value"}, - "nested": {"inner_tuple": (1, 2, attachment)}, - } - - result = bt_safe_deep_copy(original) - - # Tuples and sets are converted to lists - self.assertIsInstance(result["tuple_with_attachment"], list) - self.assertIsInstance(result["set_with_attachment"], list) - - # Attachment preserved in converted list - self.assertIs(result["tuple_with_attachment"][0], attachment) - self.assertIn(attachment, result["set_with_attachment"]) - - # Nested tuple also converted - self.assertIsInstance(result["nested"]["inner_tuple"], list) - self.assertIs(result["nested"]["inner_tuple"][2], attachment) - - def test_bt_safe_deep_copy_pydantic_with_attachments(self): - """Test Pydantic model with attachment field.""" - try: - from pydantic import BaseModel - - attachment = Attachment(data=b"data", filename="file.txt", content_type="text/plain") - - class ModelWithAttachment(BaseModel): - name: str - file: Any # Pydantic doesn't have built-in type for our Attachment - - model = ModelWithAttachment(name="test", file=attachment) - - result = bt_safe_deep_copy(model) - - # Model should be converted to dict - self.assertIsInstance(result, dict) - self.assertEqual(result["name"], "test") - - # Attachment should be preserved - self.assertIs(result["file"], attachment) - except ImportError: - self.skipTest("Pydantic not available") - - def test_bt_safe_deep_copy_dataclass_with_attachments(self): - """Test that dataclasses with attachments are handled correctly.""" - from dataclasses import dataclass - - attachment = Attachment(data=b"data", filename="file.txt", content_type="text/plain") - - @dataclass - class DataWithAttachment: - name: str - value: int - file: Attachment - - data = DataWithAttachment(name="test", value=42, file=attachment) - - result = bt_safe_deep_copy({"data": data}) - - # Dataclasses with Attachment fields are now properly converted by - # recursively applying _to_bt_safe to each field instead of using - # dataclasses.asdict() which would try to deepcopy the Attachment. - self.assertIsInstance(result["data"], dict) - self.assertEqual(result["data"]["name"], "test") - self.assertEqual(result["data"]["value"], 42) - self.assertIs(result["data"]["file"], attachment) - - # Attachments in regular dicts also work fine - dict_with_attachment = {"name": "test", "value": 42, "file": attachment} - result2 = bt_safe_deep_copy({"data": dict_with_attachment}) - self.assertIsInstance(result2["data"], dict) - self.assertIs(result2["data"]["file"], attachment) - - def test_bt_safe_deep_copy_circular_in_pydantic_deferred_to_bt_dumps(self): - """Test that circular references inside Pydantic model results bypass bt_safe_deep_copy detection. - - Current behavior: model_dump() preserves the circular structure (with different object - identity). bt_safe_deep_copy passes it through, and bt_dumps catches it at serialization. - This differs from plain dicts where circular refs are caught and replaced with - ''. - """ - try: - from pydantic import BaseModel - except ImportError: - self.skipTest("Pydantic not available") - - class ModelWithObject(BaseModel): - data: object - model_config = {"arbitrary_types_allowed": True} - - circular: dict[str, Any] = {"value": 1} - circular["self"] = circular - - model = ModelWithObject(data=circular) - - # bt_safe_deep_copy passes through the circular structure from model_dump() - result = bt_safe_deep_copy({"model": model}) - self.assertIsInstance(result["model"], dict) - # model_dump() preserves circular structure but NOT object identity - self.assertIsInstance(result["model"]["data"]["self"], dict) - self.assertEqual(result["model"]["data"]["self"]["value"], 1) - - # bt_dumps catches the circular reference at serialization time - with self.assertRaises(ValueError) as ctx: - bt_dumps(result) - self.assertIn("Circular reference", str(ctx.exception)) - - def test_bt_safe_deep_copy_pydantic_with_attachment_field(self): - """Test Pydantic model with a Braintrust Attachment field. - - Pydantic models with Attachment fields should work correctly through - bt_safe_deep_copy, with the Attachment object preserved. - """ - try: - from pydantic import BaseModel - except ImportError: - self.skipTest("Pydantic not available") - - attachment = Attachment(data=b"data", filename="file.txt", content_type="text/plain") - - class ModelWithAttachment(BaseModel): - name: str - file: object - model_config = {"arbitrary_types_allowed": True} - - model = ModelWithAttachment(name="test", file=attachment) - - result = bt_safe_deep_copy({"model": model}) - - self.assertIsInstance(result["model"], dict) - self.assertEqual(result["model"]["name"], "test") - # Attachment should be preserved through model_dump() - self.assertIs(result["model"]["file"], attachment) - - def test_bt_safe_deep_copy_circular_in_plain_dict_is_caught(self): - """Contrast test: circular references in plain dicts ARE caught by bt_safe_deep_copy.""" - circular: dict[str, Any] = {"value": 1} - circular["self"] = circular - - result = bt_safe_deep_copy({"data": circular}) - - # Circular reference IS detected and replaced - self.assertEqual(result["data"]["self"], "") - - # bt_dumps succeeds because the circular ref was sanitized - json_str = bt_dumps(result) - self.assertIn("", json_str) diff --git a/py/src/braintrust/test_context.py b/py/src/braintrust/test_context.py deleted file mode 100644 index 5a1d9ece4..000000000 --- a/py/src/braintrust/test_context.py +++ /dev/null @@ -1,1264 +0,0 @@ -""" -Context Propagation Tests for Braintrust SDK - -This test suite validates context propagation behavior across various concurrency patterns. - -TEST ISOLATION STRATEGY: -- Tests use pytest-forked to run each test in an isolated process -- This ensures setup_threads() patches don't leak between tests -- Use unpatched(scenario) for xfail tests (documents context loss) -- Use patched(scenario) for tests that prove setup_threads() fixes it - -Example: - def _threadpool_scenario(test_logger, with_memory_logger): - # test logic... - - test_threadpool_loses_context = unpatched(_threadpool_scenario) - test_threadpool_with_patch = patched(_threadpool_scenario) - -Run with: pytest --forked src/braintrust/test_context.py -""" - -import asyncio -import concurrent.futures -import functools -import sys -import threading -from typing import AsyncGenerator, Callable, Generator, TypeVar - -import braintrust -import pytest -from braintrust import current_span, start_span -from braintrust.test_helpers import init_test_logger, with_memory_logger # noqa: F401 -from braintrust.wrappers.threads import setup_threads - -F = TypeVar("F", bound=Callable) - - -def isolate(instrument: bool) -> Callable[[F], F]: - """ - Decorator for isolated context propagation tests. - - - Always runs in forked process (pytest-forked) - - If instrument=True: calls setup_threads() before test - - If instrument=False: marks test as xfail (context loss expected) - """ - - def decorator(fn: F) -> F: - if asyncio.iscoroutinefunction(fn): - - @functools.wraps(fn) - async def async_wrapper(*args, **kwargs): - if instrument: - setup_threads() - return await fn(*args, **kwargs) - - wrapped = pytest.mark.forked(async_wrapper) - else: - - @functools.wraps(fn) - def wrapper(*args, **kwargs): - if instrument: - setup_threads() - return fn(*args, **kwargs) - - wrapped = pytest.mark.forked(wrapper) - - if not instrument: - wrapped = pytest.mark.xfail(reason="context lost without patch")(wrapped) - return wrapped # type: ignore - - return decorator - - -patched = isolate(instrument=True) -unpatched = isolate(instrument=False) - - -@pytest.fixture -def test_logger(with_memory_logger): - """Provide a test logger for each test with memory logger.""" - logger = init_test_logger("test-context-project") - yield logger - - -# ============================================================================ -# CONTEXT MANAGER PATTERN: with start_span(...) -# ============================================================================ - - -def _threadpool_scenario(test_logger, with_memory_logger): - """ThreadPoolExecutor context propagation.""" - parent_seen_by_worker = None - - def worker_task(): - nonlocal parent_seen_by_worker - parent_seen_by_worker = current_span() - - with start_span(name="parent") as parent_span: - parent_id = parent_span.id - with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor: - future = executor.submit(worker_task) - future.result() - - assert parent_seen_by_worker is not None - assert parent_seen_by_worker.id == parent_id - - -test_threadpool_loses_context = unpatched(_threadpool_scenario) -test_threadpool_with_patch = patched(_threadpool_scenario) - - -def _thread_scenario(test_logger, with_memory_logger): - """threading.Thread context propagation.""" - parent_seen_by_worker = None - - def worker_task(): - nonlocal parent_seen_by_worker - parent_seen_by_worker = current_span() - - with start_span(name="parent") as parent_span: - parent_id = parent_span.id - thread = threading.Thread(target=worker_task) - thread.start() - thread.join() - - assert parent_seen_by_worker is not None - assert parent_seen_by_worker.id == parent_id - - -test_thread_loses_context = unpatched(_thread_scenario) -test_thread_with_patch = patched(_thread_scenario) - - -def _nested_threadpool_scenario(test_logger, with_memory_logger): - """Nested ThreadPoolExecutor context propagation.""" - root_seen_by_level1 = None - level1_seen_by_level2 = None - - def level2_task(): - nonlocal level1_seen_by_level2 - level1_seen_by_level2 = current_span() - - def level1_task(): - nonlocal root_seen_by_level1 - root_seen_by_level1 = current_span() - - with start_span(name="level1") as level1_span: - with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor: - future = executor.submit(level2_task) - future.result() - return level1_span.id - - with start_span(name="root") as root_span: - root_id = root_span.id - with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor: - future = executor.submit(level1_task) - level1_id = future.result() - - assert root_seen_by_level1 is not None - assert root_seen_by_level1.id == root_id - assert level1_seen_by_level2 is not None - assert level1_seen_by_level2.id == level1_id - - -test_nested_threadpool_loses_context = unpatched(_nested_threadpool_scenario) -test_nested_threadpool_with_patch = patched(_nested_threadpool_scenario) - - -@pytest.mark.asyncio -async def _run_in_executor_scenario(test_logger, with_memory_logger): - """loop.run_in_executor context propagation.""" - parent_seen_by_worker = None - - def blocking_work(): - nonlocal parent_seen_by_worker - parent_seen_by_worker = current_span() - - with start_span(name="parent") as parent_span: - parent_id = parent_span.id - loop = asyncio.get_running_loop() - await loop.run_in_executor(None, blocking_work) - - assert parent_seen_by_worker is not None - assert parent_seen_by_worker.id == parent_id - - -test_run_in_executor_loses_context = unpatched(_run_in_executor_scenario) -test_run_in_executor_with_patch = patched(_run_in_executor_scenario) - - -# ============================================================================ -# ASYNCIO PATTERNS (Should Work) -# ============================================================================ - - -@pytest.mark.asyncio -async def test_asyncio_create_task_preserves_context(test_logger, with_memory_logger): - """ - WORKS: asyncio.create_task() DOES preserve Braintrust context. - """ - - async def async_worker(): - span = current_span() - worker_span = start_span(name="async_worker") - await asyncio.sleep(0.001) - worker_span.end() - return span - - # Create parent span - with start_span(name="parent") as parent_span: - parent_id = parent_span.id - - # Create async task - task = asyncio.create_task(async_worker()) - result_span = await task - - # Task SHOULD see the parent span - assert result_span.id == parent_id, "create_task() should preserve context" - - test_logger.flush() - logs = with_memory_logger.pop() - assert len(logs) == 2 - - parent_log = next(l for l in logs if l["span_attributes"]["name"] == "parent") - worker_log = next(l for l in logs if l["span_attributes"]["name"] == "async_worker") - - # Worker should have parent as its parent (same trace) - assert worker_log["root_span_id"] == parent_log["root_span_id"], "Should be in same trace" - assert parent_log["span_id"] in worker_log.get("span_parents", []), "Worker should have parent as parent" - - -@pytest.mark.skipif(sys.version_info < (3, 9), reason="to_thread requires Python 3.9+") -@pytest.mark.asyncio -async def test_to_thread_preserves_context(test_logger, with_memory_logger): - """ - WORKS: asyncio.to_thread() DOES preserve Braintrust context. - """ - - def blocking_work(): - span = current_span() - worker_span = start_span(name="to_thread_worker") - worker_span.end() - return span - - # Create parent span - with start_span(name="parent") as parent_span: - parent_id = parent_span.id - - # Use to_thread - result_span = await asyncio.to_thread(blocking_work) - - # to_thread SHOULD preserve context - assert result_span.id == parent_id, "to_thread() should preserve context" - - test_logger.flush() - logs = with_memory_logger.pop() - - # SURPRISING: Even to_thread() loses logger context (logger is a ContextVar too!) - # Only parent span is logged - # However, to_thread() DOES preserve span parent context - assert len(logs) >= 1 - - # If both spans logged (logger context preserved), verify parent chain - if len(logs) == 2: - parent_log = next(l for l in logs if l["span_attributes"]["name"] == "parent") - worker_log = next(l for l in logs if l["span_attributes"]["name"] == "to_thread_worker") - assert worker_log["root_span_id"] == parent_log["root_span_id"] - assert parent_log["span_id"] in worker_log.get("span_parents", []) - - -# ============================================================================ -# DECORATOR PATTERN: @traced -# ============================================================================ - - -def _traced_decorator_scenario(test_logger, with_memory_logger): - """@traced with ThreadPoolExecutor context propagation.""" - parent_seen_by_worker = None - - def worker_function(): - nonlocal parent_seen_by_worker - parent_seen_by_worker = current_span() - - with start_span(name="parent") as parent_span: - parent_id = parent_span.id - with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor: - future = executor.submit(worker_function) - future.result() - - assert parent_seen_by_worker is not None - assert parent_seen_by_worker.id == parent_id - - -test_traced_decorator_loses_context = unpatched(_traced_decorator_scenario) -test_traced_decorator_with_patch = patched(_traced_decorator_scenario) - - -@pytest.mark.asyncio -async def test_traced_decorator_with_async(test_logger, with_memory_logger): - """@traced decorator works with async functions (no patching needed).""" - - @braintrust.traced - async def child_function(): - await asyncio.sleep(0.01) - return "child_result" - - @braintrust.traced - async def parent_function(): - return await child_function() - - await parent_function() - - test_logger.flush() - logs = with_memory_logger.pop() - - assert len(logs) == 2 - parent_log = next(l for l in logs if l["span_attributes"]["name"] == "parent_function") - child_log = next(l for l in logs if l["span_attributes"]["name"] == "child_function") - assert child_log["root_span_id"] == parent_log["root_span_id"] - assert parent_log["span_id"] in child_log.get("span_parents", []) - - -# ============================================================================ -# MANUAL PATTERN: start_span() + .end() -# ============================================================================ - - -def _manual_span_scenario(test_logger, with_memory_logger): - """Manual span with ThreadPoolExecutor context propagation.""" - parent_seen_by_worker = None - - def worker_task(): - nonlocal parent_seen_by_worker - parent_seen_by_worker = current_span() - - parent_span = start_span(name="parent", set_current=True) - parent_span.set_current() - try: - parent_id = parent_span.id - with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor: - future = executor.submit(worker_task) - future.result() - finally: - parent_span.unset_current() - parent_span.end() - - assert parent_seen_by_worker is not None - assert parent_seen_by_worker.id == parent_id - - -test_manual_span_loses_context = unpatched(_manual_span_scenario) -test_manual_span_with_patch = patched(_manual_span_scenario) - - -@pytest.mark.asyncio -async def test_manual_span_with_async(test_logger, with_memory_logger): - """ - Manual span management with explicit set_current()/unset_current() calls. - - โš ๏ธ IMPORTANT: This pattern is MORE VERBOSE and ERROR-PRONE than context managers. - - Incorrect pattern (DOES NOT WORK): - parent_span = start_span("parent", set_current=True) # โŒ Just creates span - # parent is NOT current yet! - - Correct pattern (WORKS but verbose): - parent_span = start_span("parent", set_current=True) - parent_span.set_current() # โœ… Actually set as current - try: - await child() - finally: - parent_span.unset_current() # โœ… Clean up - parent_span.end() - - Recommended pattern (BEST): - with start_span("parent"): # โœ… Automatic set/unset - await child() - """ - - async def child_work(): - child_span = start_span(name="child", set_current=True) - child_span.set_current() # โœ… Must call explicitly! - try: - await asyncio.sleep(0.01) - return "result" - finally: - child_span.unset_current() # โœ… Must clean up! - child_span.end() - - parent_span = start_span(name="parent", set_current=True) - parent_span.set_current() # โœ… Must call explicitly! - parent_id = parent_span.id - try: - result = await child_work() - finally: - parent_span.unset_current() # โœ… Must clean up! - parent_span.end() - - test_logger.flush() - logs = with_memory_logger.pop() - - # Expected: Both spans should be logged - assert len(logs) == 2, f"Expected 2 spans, got {len(logs)}" - - parent_log = next(l for l in logs if l["span_attributes"]["name"] == "parent") - child_log = next(l for l in logs if l["span_attributes"]["name"] == "child") - - # Child should be child of parent - assert child_log["root_span_id"] == parent_log["root_span_id"], ( - f"Child root {child_log['root_span_id']} != parent root {parent_log['root_span_id']}" - ) - assert parent_log["span_id"] in child_log.get("span_parents", []), ( - f"Parent {parent_log['span_id']} not in child parents {child_log.get('span_parents', [])}" - ) - - -# ============================================================================ -# INTEGRATION PATTERNS (Based on Real SDK Integrations) -# ============================================================================ - - -@pytest.mark.asyncio -async def test_async_generator_wrapper_pattern(test_logger, with_memory_logger): - """ - Expected: Async generators wrapping spans should maintain parent relationships. - - Real-world pattern: Wrapping SDK streams in async generators (common in pydantic-ai, etc.) - - Pattern: - with start_span("consumer"): - async def stream_wrapper(): - with start_span("stream_source"): - async for item in source(): - yield item - - async for item in stream_wrapper(): - process(item) - - Expected trace: - consumer - โ””โ”€ stream_source - โ””โ”€ processing spans - """ - - async def simulated_stream(): - """Simulates an async stream source.""" - for i in range(3): - await asyncio.sleep(0.001) - yield f"item_{i}" - - async def stream_wrapper(): - """Wraps stream in async generator (common customer pattern).""" - with start_span(name="stream_source") as source_span: - async for item in simulated_stream(): - yield item - - with start_span(name="consumer") as consumer_span: - async for item in stream_wrapper(): - # Process each item - item_span = start_span(name=f"process_{item}") - await asyncio.sleep(0.001) - item_span.end() - - test_logger.flush() - logs = with_memory_logger.pop() - - # Expected: consumer + stream_source + 3 process spans = 5 - assert len(logs) == 5, f"Expected 5 spans, got {len(logs)}" - - consumer_log = next(l for l in logs if l["span_attributes"]["name"] == "consumer") - stream_log = next(l for l in logs if l["span_attributes"]["name"] == "stream_source") - process_logs = [l for l in logs if l["span_attributes"]["name"].startswith("process_")] - - # All should share same root - assert stream_log["root_span_id"] == consumer_log["root_span_id"] - for p in process_logs: - assert p["root_span_id"] == consumer_log["root_span_id"] - - # stream_source should be child of consumer - assert consumer_log["span_id"] in stream_log.get("span_parents", []) - - -def test_library_doing_context_right(test_logger, with_memory_logger): - """ - Test: Well-behaved library (like LangChain) that properly propagates context. - - This test works WITHOUT auto-instrumentation because the library correctly - captures context at call time using copy_context(). - - Real-world example - LangChain-style pattern: - class WellBehavedSDK: - def run_async(self, fn): - ctx = contextvars.copy_context() # Captured at call time! - return self._pool.submit(lambda: ctx.run(fn)) - """ - import contextvars - - class WellBehavedSDK: - def __init__(self): - self._pool = concurrent.futures.ThreadPoolExecutor(max_workers=1) - - def run_async(self, fn): - ctx = contextvars.copy_context() - return self._pool.submit(lambda: ctx.run(fn)) - - def shutdown(self): - self._pool.shutdown(wait=True) - - sdk = WellBehavedSDK() - - parent_seen_by_worker = None - - def worker_function(): - nonlocal parent_seen_by_worker - parent_seen_by_worker = current_span() - - try: - with start_span(name="user_parent") as parent_span: - parent_id = parent_span.id - future = sdk.run_async(worker_function) - future.result() - finally: - sdk.shutdown() - - assert parent_seen_by_worker is not None - assert parent_seen_by_worker.id == parent_id, "Well-behaved library preserves context" - - -def _integration_forgot_context_scenario(test_logger, with_memory_logger): - """Integration without context propagation.""" - parent_seen_by_worker = None - - class NaiveIntegration: - def __init__(self): - self._pool = concurrent.futures.ThreadPoolExecutor(max_workers=1) - - def process(self, fn): - return self._pool.submit(fn) - - def shutdown(self): - self._pool.shutdown(wait=True) - - integration = NaiveIntegration() - - def worker_function(): - nonlocal parent_seen_by_worker - parent_seen_by_worker = current_span() - - try: - with start_span(name="user_parent") as parent_span: - parent_id = parent_span.id - future = integration.process(worker_function) - future.result() - finally: - integration.shutdown() - - assert parent_seen_by_worker is not None - assert parent_seen_by_worker.id == parent_id - - -test_integration_forgot_context_loses = unpatched(_integration_forgot_context_scenario) -test_integration_forgot_context_with_patch = patched(_integration_forgot_context_scenario) - - -def test_integration_early_context_not_fixable(test_logger, with_memory_logger): - """ - Documents: Integration that captured context too early CANNOT be fixed by auto-instrumentation. - - This pattern explicitly switches to a stale context using self._ctx.run(fn), - which overrides our auto-instrumentation. The integration's explicit context - switch happens AFTER our wrapper, so the stale context wins. - - Pattern: - class EagerContextIntegration: - def __init__(self): - self._ctx = copy_context() # Stale context captured here - - def process(self, fn): - return self._pool.submit(lambda: self._ctx.run(fn)) # Explicit switch to stale - - Auto-instrumentation wraps submit(), but the lambda then switches to stale context. - - This is NOT fixable by auto-instrumentation - the integration must be fixed - to capture context at call time, not at __init__ time. - """ - import contextvars - - parent_seen_by_worker = None - - class EagerContextIntegration: - def __init__(self): - self._pool = concurrent.futures.ThreadPoolExecutor(max_workers=1) - self._ctx = contextvars.copy_context() - - def process(self, fn): - return self._pool.submit(lambda: self._ctx.run(fn)) - - def shutdown(self): - self._pool.shutdown(wait=True) - - integration = EagerContextIntegration() - - def worker_function(): - nonlocal parent_seen_by_worker - parent_seen_by_worker = current_span() - - try: - with start_span(name="user_parent") as parent_span: - parent_id = parent_span.id - future = integration.process(worker_function) - future.result() - finally: - integration.shutdown() - - assert parent_seen_by_worker is not None, "Worker runs" - assert parent_seen_by_worker.id != parent_id, "Worker sees STALE context, not parent (not fixable)" - - -def _integration_thread_scenario(test_logger, with_memory_logger): - """Integration using Thread directly.""" - parent_seen_by_worker = None - - class ThreadIntegration: - def process(self, fn): - thread = threading.Thread(target=fn) - thread.start() - return thread - - def wait(self, thread): - thread.join() - - integration = ThreadIntegration() - - def worker_function(): - nonlocal parent_seen_by_worker - parent_seen_by_worker = current_span() - - with start_span(name="user_parent") as parent_span: - parent_id = parent_span.id - thread = integration.process(worker_function) - integration.wait(thread) - - assert parent_seen_by_worker is not None - assert parent_seen_by_worker.id == parent_id - - -test_integration_thread_loses_context = unpatched(_integration_thread_scenario) -test_integration_thread_with_patch = patched(_integration_thread_scenario) - - -def _integration_decorator_scenario(test_logger, with_memory_logger): - """Decorator pattern loses context.""" - parent_seen_by_worker = None - - def async_retry_decorator(fn): - pool = concurrent.futures.ThreadPoolExecutor(max_workers=1) - - def wrapper(*args, **kwargs): - future = pool.submit(fn, *args, **kwargs) - return future.result() - - return wrapper - - @async_retry_decorator - def user_function(): - nonlocal parent_seen_by_worker - parent_seen_by_worker = current_span() - - with start_span(name="user_parent") as parent_span: - parent_id = parent_span.id - user_function() - - assert parent_seen_by_worker is not None - assert parent_seen_by_worker.id == parent_id - - -test_integration_decorator_loses_context = unpatched(_integration_decorator_scenario) -test_integration_decorator_with_patch = patched(_integration_decorator_scenario) - - -@pytest.mark.asyncio -async def test_copy_context_token_error_across_async_tasks(test_logger, with_memory_logger): - """ - Expected: Span lifecycle should work even when started in one async context - and ended in another (copied) context. - - Real-world pattern: LangChain creates parallel async tasks using asyncio.create_task(), - which gives each task a COPY of the context. If a span is started in the main - context but ended in a task context, we get: - "ValueError: Token was created in a different Context" - - This is what LangChain's Braintrust integration silently handles! - - Pattern: - async with start_span("parent"): - # Span sets ContextVar token in context A - - async def task_work(): - # Task runs in context B (copy of A) - # Try to end parent span - # ValueError: Token from context A can't be reset in context B - - task = asyncio.create_task(task_work()) # Context copy - await task - - Expected: Should work without errors (or handle them gracefully) - Actual: May raise ValueError (which integrations must handle) - """ - import asyncio - - with start_span(name="parent"): - parent_log = with_memory_logger.pop()[0] - parent_span = current_span() - - # Simulate what happens in LangChain: - # Span is started in main context, but callback happens in task context - - async def task_work(): - # This runs in a COPIED context - # If we try to manipulate parent_span here, we might hit token errors - - # This is what LangChain callbacks do: - # 1. Create child span (works - parent_span accessible) - with start_span(name="child"): - await asyncio.sleep(0.01) - - # 2. Try to unset current (might fail with token error) - try: - parent_span.unset_current() - token_error = None - except ValueError as e: - token_error = str(e) - - return token_error - - # Create task - this copies the context - task = asyncio.create_task(task_work()) - error = await task - - # We might see token error here - if error and "was created in a different Context" in error: - # This is the error LangChain's integration silently handles! - # It's not a bug, it's an expected consequence of context copies - pass # Expected in async contexts - - # Child span should still be logged correctly despite token error - child_log = with_memory_logger.pop()[0] - - # The child span should maintain parent relationship - # (Braintrust SDK handles this correctly even across context boundaries) - assert child_log["span_parents"] == [parent_log["span_id"]], ( - f"Child span should have parent relationship despite context copy. Got: {child_log.get('span_parents')}" - ) - - -@pytest.mark.asyncio -async def test_async_generator_early_break_context_token(test_logger, with_memory_logger): - """ - Expected: Early breaks from async generators shouldn't cause context token errors. - - Real-world issue: Breaking early from async generators causes cleanup in different - async context, leading to "Token was created in a different Context" errors. - - Pattern (from pydantic-ai integration): - async def stream_wrapper(): - with start_span("stream"): - async for chunk in source(): - yield chunk - if condition: - break # Early break triggers cleanup in different context - - async for chunk in stream_wrapper(): - process(chunk) - if done: - break # Consumer breaks early - - Expected: Spans logged correctly, no context token errors - """ - - async def simulated_long_stream(): - """Simulates a long stream.""" - for i in range(100): - await asyncio.sleep(0.001) - yield f"chunk_{i}" - - async def stream_wrapper(): - """Wraps stream, may break early (triggers cleanup in different context).""" - with start_span(name="wrapped_stream") as stream_span: - count = 0 - async for chunk in simulated_long_stream(): - yield chunk - count += 1 - if count >= 3: - # Break early - this triggers cleanup in different context - break - - with start_span(name="consumer") as consumer_span: - chunk_count = 0 - - # Consumer breaks early too - async for chunk in stream_wrapper(): - chunk_count += 1 - if chunk_count >= 2: - break - - # Should not raise ValueError about "Token was created in a different Context" - test_logger.flush() - logs = with_memory_logger.pop() - - # Expected: At least consumer and wrapped_stream spans - assert len(logs) >= 2, f"Expected at least 2 spans, got {len(logs)}" - - consumer_log = next((l for l in logs if l["span_attributes"]["name"] == "consumer"), None) - stream_log = next((l for l in logs if l["span_attributes"]["name"] == "wrapped_stream"), None) - - assert consumer_log is not None, "Consumer span should be logged" - assert stream_log is not None, "Wrapped stream span should be logged despite early break" - - # wrapped_stream should be child of consumer - if stream_log: - assert stream_log["root_span_id"] == consumer_log["root_span_id"] - assert consumer_log["span_id"] in stream_log.get("span_parents", []) - - -# ============================================================================ -# ASYNC GENERATOR TESTS -# ============================================================================ - - -@pytest.mark.asyncio -async def test_async_generator_context_behavior(test_logger, with_memory_logger): - """ - Test how Braintrust spans behave with async generators. - """ - - async def my_async_gen() -> AsyncGenerator[int, None]: - gen_span = start_span(name="generator_span") - - try: - for i in range(3): - yield i - await asyncio.sleep(0.001) - finally: - gen_span.end() - - # Consumer with parent span - with start_span(name="consumer") as consumer_span: - results = [] - async for value in my_async_gen(): - results.append(value) - # Consumer does work between iterations - item_span = start_span(name=f"process_{value}") - await asyncio.sleep(0.001) - item_span.end() - - assert results == [0, 1, 2] - - test_logger.flush() - logs = with_memory_logger.pop() - # Should have consumer + generator_span + 3 process spans - assert len(logs) == 5 - - -@pytest.mark.asyncio -async def test_async_generator_finalization(test_logger, with_memory_logger): - """ - Test context during async generator cleanup. - """ - - async def generator_with_finally() -> AsyncGenerator[int, None]: - gen_span = start_span(name="gen_with_finally") - - try: - yield 1 - yield 2 - finally: - # What context do we have during cleanup? - cleanup_span = current_span() - gen_span.end() - - # Consumer - with start_span(name="consumer") as consumer_span: - gen = generator_with_finally() - await gen.__anext__() # Get first value only - - # Explicitly close generator - await gen.aclose() - - test_logger.flush() - logs = with_memory_logger.pop() - assert len(logs) == 2 # consumer + gen_with_finally - - -# ============================================================================ -# TEST CATEGORY 4: Sync Generator Context -# ============================================================================ - - -def test_sync_generator_context_sharing(test_logger, with_memory_logger): - """ - Sync generators share caller's context - changes are visible. - """ - - def sync_gen() -> Generator[int, None, None]: - for i in range(3): - # Check current span at each iteration - span = current_span() - yield i - - # Create parent span - with start_span(name="parent") as parent_span: - gen = sync_gen() - - for i, value in enumerate(gen): - # Create new span for each iteration - item_span = start_span(name=f"item_{i}") - item_span.end() - - test_logger.flush() - logs = with_memory_logger.pop() - assert len(logs) == 4 # parent + 3 items - - -# ============================================================================ -# REAL-WORLD PATTERN TESTS -# ============================================================================ - - -def _thread_wrapped_async_scenario(test_logger, with_memory_logger): - """Thread-wrapped async (Google ADK, Pydantic AI pattern).""" - import queue as queue_module - - event_queue = queue_module.Queue() - parent_seen_in_thread = None - - async def _invoke_async(): - nonlocal parent_seen_in_thread - parent_seen_in_thread = current_span() - event_queue.put("done") - - def _thread_main(): - asyncio.run(_invoke_async()) - event_queue.put(None) - - with start_span(name="parent") as parent_span: - parent_id = parent_span.id - thread = threading.Thread(target=_thread_main) - thread.start() - while True: - event = event_queue.get() - if event is None: - break - thread.join() - - assert parent_seen_in_thread is not None - assert parent_seen_in_thread.id == parent_id - - -test_thread_wrapped_async_loses_context = unpatched(_thread_wrapped_async_scenario) -test_thread_wrapped_async_with_patch = patched(_thread_wrapped_async_scenario) - - -async def _fastapi_background_scenario(test_logger, with_memory_logger): - """FastAPI background tasks (run_in_executor).""" - parent_seen_by_background = None - - def background_work(): - nonlocal parent_seen_by_background - parent_seen_by_background = current_span() - - with start_span(name="http_request") as request_span: - request_id = request_span.id - loop = asyncio.get_running_loop() - await loop.run_in_executor(None, background_work) - - assert parent_seen_by_background is not None - assert parent_seen_by_background.id == request_id - - -test_fastapi_background_loses_context = unpatched(pytest.mark.asyncio(_fastapi_background_scenario)) -test_fastapi_background_with_patch = patched(pytest.mark.asyncio(_fastapi_background_scenario)) - - -def _data_pipeline_scenario(test_logger, with_memory_logger): - """Data pipeline with parallel ThreadPoolExecutor.""" - parents_seen = [] - - def process_item(item: int): - parent = current_span() - parents_seen.append(parent) - return item - - with start_span(name="pipeline") as pipeline_span: - pipeline_id = pipeline_span.id - data = list(range(3)) - - with concurrent.futures.ThreadPoolExecutor(max_workers=2) as executor: - futures = [executor.submit(process_item, item) for item in data] - [f.result() for f in futures] - - assert len(parents_seen) == 3 - for i, parent in enumerate(parents_seen): - assert parent is not None - assert parent.id == pipeline_id - - -test_data_pipeline_loses_context = unpatched(_data_pipeline_scenario) -test_data_pipeline_with_patch = patched(_data_pipeline_scenario) - - -@pytest.mark.asyncio -async def test_streaming_llm_pattern(test_logger, with_memory_logger): - """ - Simulates streaming LLM responses with async generator. - """ - - async def llm_stream_generator() -> AsyncGenerator[str, None]: - llm_span = start_span(name="llm_generation") - - try: - for i in range(3): - yield f"chunk_{i}" - await asyncio.sleep(0.001) - finally: - llm_span.end() - - # Consumer - with start_span(name="http_request") as request_span: - async for chunk in llm_stream_generator(): - # Process each chunk - chunk_span = start_span(name=f"process_{chunk}") - await asyncio.sleep(0.001) - chunk_span.end() - - test_logger.flush() - logs = with_memory_logger.pop() - assert len(logs) == 5 # request + llm_generation + 3 process chunks - - -# ============================================================================ -# TEST CATEGORY 6: Context Isolation Tests -# ============================================================================ - - -@pytest.mark.asyncio -async def test_parallel_tasks_context_isolation(test_logger, with_memory_logger): - """ - Test that concurrent asyncio tasks have isolated contexts. - """ - parent_ids = [] - - async def task_work(task_id: int): - # Each task should see the root span as parent - parent = current_span() - parent_ids.append(parent.id) - - task_span = start_span(name=f"task_{task_id}") - - await asyncio.sleep(0.01) - task_span.end() - - # Root span - with start_span(name="root") as root_span: - root_id = root_span.id - - # Spawn multiple concurrent tasks - tasks = [asyncio.create_task(task_work(i)) for i in range(5)] - await asyncio.gather(*tasks) - - # All tasks should have seen root as parent - assert all(pid == root_id for pid in parent_ids), "Tasks should see root as parent" - - test_logger.flush() - logs = with_memory_logger.pop() - assert len(logs) == 6 # root + 5 tasks - - root_log = next(l for l in logs if l["span_attributes"]["name"] == "root") - task_logs = [l for l in logs if l["span_attributes"]["name"].startswith("task_")] - - # All tasks should have root as parent - for task_log in task_logs: - assert task_log["root_span_id"] == root_log["root_span_id"] - assert root_log["span_id"] in task_log.get("span_parents", []) - - -@pytest.mark.skipif(sys.version_info < (3, 11), reason="TaskGroup requires Python 3.11+") -@pytest.mark.asyncio -async def test_taskgroup_context_propagation(test_logger, with_memory_logger): - """ - Test that TaskGroup properly propagates context (Python 3.11+). - """ - - async def child_task(task_id: int): - child_span = start_span(name=f"child_{task_id}") - await asyncio.sleep(0.001) - child_span.end() - - # Root span - with start_span(name="root") as root_span: - async with asyncio.TaskGroup() as tg: # pylint: disable=no-member - for i in range(3): - tg.create_task(child_task(i)) - - test_logger.flush() - logs = with_memory_logger.pop() - assert len(logs) == 4 # root + 3 children - - root_log = next(l for l in logs if l["span_attributes"]["name"] == "root") - child_logs = [l for l in logs if l["span_attributes"]["name"].startswith("child_")] - - # All children should have root as parent - for child_log in child_logs: - assert child_log["root_span_id"] == root_log["root_span_id"] - assert root_log["span_id"] in child_log.get("span_parents", []) - - -# ============================================================================ -# TEST CATEGORY 7: Nested Context Tests -# ============================================================================ - - -def test_nested_spans_same_thread(test_logger, with_memory_logger): - """ - Test that nested spans work correctly in the same thread. - """ - # Root span - with start_span(name="root") as root_span: - # Verify root is current - assert current_span().id == root_span.id - - # Child span - with start_span(name="child") as child_span: - child_id = child_span.id - - # Verify child is now current - assert current_span().id == child_span.id - - # Grandchild span - with start_span(name="grandchild") as grandchild_span: - grandchild_id = grandchild_span.id - assert current_span().id == grandchild_span.id - - # After grandchild closes, child should be current - assert current_span().id == child_span.id - - # After child closes, root should be current - assert current_span().id == root_span.id - - test_logger.flush() - logs = with_memory_logger.pop() - assert len(logs) == 3 - - root_log = next(l for l in logs if l["span_attributes"]["name"] == "root") - child_log = next(l for l in logs if l["span_attributes"]["name"] == "child") - grandchild_log = next(l for l in logs if l["span_attributes"]["name"] == "grandchild") - - # Verify parent chain - assert root_log["span_id"] == root_log["root_span_id"], "Root is root" - assert child_log["root_span_id"] == root_log["root_span_id"], "Child same root" - assert grandchild_log["root_span_id"] == root_log["root_span_id"], "Grandchild same root" - assert root_log["span_id"] in child_log.get("span_parents", []), "Child parent is root" - assert child_log["span_id"] in grandchild_log.get("span_parents", []), "Grandchild parent is child" - - -@pytest.mark.asyncio -async def test_deeply_nested_async_context(test_logger, with_memory_logger): - """ - Test deeply nested spans to ensure no corruption. - """ - - async def nested_span(depth: int): - span = start_span(name=f"depth_{depth}") - - if depth > 0: - await nested_span(depth - 1) - - span.end() - - with start_span(name="root") as root_span: - root_id = root_span.id - await nested_span(10) # 10 levels deep - - test_logger.flush() - logs = with_memory_logger.pop() - - # Should be 11 spans: root + 10 nested - assert len(logs) >= 11 # Allow for timing variations - - # Get the actual root (first span created) - root_log = next((l for l in logs if l["span_attributes"]["name"] == "root"), None) - assert root_log is not None - actual_root_id = root_log["root_span_id"] - - # All should share same root - for log in logs: - assert log["root_span_id"] == actual_root_id - - -# ============================================================================ -# TEST CATEGORY 8: Exception Handling -# ============================================================================ - - -def test_context_with_exception_propagation(test_logger, with_memory_logger): - """ - Test that context is properly maintained during exception propagation. - """ - fail_span_id = None - - def failing_function(): - nonlocal fail_span_id - # Use context manager for proper span lifecycle - with start_span(name="failing_span") as fail_span: - fail_span_id = fail_span.id - # During this context, fail_span should be current - assert current_span().id == fail_span.id - raise ValueError("Expected error") - - with start_span(name="parent") as parent_span: - parent_id = parent_span.id - - try: - failing_function() - except ValueError: - pass - - # After exception, parent should be restored as current - assert current_span().id == parent_id - - test_logger.flush() - logs = with_memory_logger.pop() - assert len(logs) == 2 - - parent_log = next(l for l in logs if l["span_attributes"]["name"] == "parent") - fail_log = next(l for l in logs if l["span_attributes"]["name"] == "failing_span") - - # Verify parent chain - assert fail_log["root_span_id"] == parent_log["root_span_id"] - assert parent_log["span_id"] in fail_log.get("span_parents", []) - - -# ============================================================================ -# AUTO-INSTRUMENTATION SPECIFIC TESTS -# ============================================================================ - - -@pytest.mark.forked -def test_setup_threads_returns_true(): - """setup_threads() returns True on success.""" - result = setup_threads() - assert result is True - - -@pytest.mark.forked -def test_setup_threads_idempotent(): - """Calling setup_threads() multiple times is safe.""" - result1 = setup_threads() - result2 = setup_threads() - assert result1 is True - assert result2 is True - - -if __name__ == "__main__": - pytest.main([__file__, "-v", "-s"]) diff --git a/py/src/braintrust/test_framework.py b/py/src/braintrust/test_framework.py deleted file mode 100644 index 9acf284b0..000000000 --- a/py/src/braintrust/test_framework.py +++ /dev/null @@ -1,566 +0,0 @@ -from typing import List -from unittest.mock import MagicMock - -import pytest -from braintrust.logger import BraintrustState - -from .framework import ( - Eval, - EvalCase, - EvalHooks, - EvalResultWithSummary, - Evaluator, - run_evaluator, -) -from .score import Score, Scorer -from .test_helpers import init_test_exp, with_memory_logger, with_simulate_login # noqa: F401 - - -@pytest.mark.asyncio -async def test_run_evaluator_basic(): - """Test that run_evaluator correctly processes a simple evaluation.""" - # Define test data - data = [ - EvalCase(input=1, expected=2), - EvalCase(input=2, expected=4), - EvalCase(input=3, expected=6), - ] - - # Define a simple task function - def multiply_by_two(input_value): - return input_value * 2 - - # Define a simple scoring function - def exact_match(input_value, output, expected): - return 1.0 if output == expected else 0.0 - - # Create evaluator - evaluator = Evaluator( - project_name="test-project", - eval_name="test-evaluator", - data=data, - task=multiply_by_two, - scores=[exact_match], - experiment_name=None, - metadata=None, - ) - - # Run evaluator - result = await run_evaluator(experiment=None, evaluator=evaluator, position=None, filters=[]) - - # Verify results - assert isinstance(result, EvalResultWithSummary) - assert len(result.results) == 3 - - # Check individual results - for i, eval_result in enumerate(result.results): - input_value = i + 1 - expected_value = input_value * 2 - - assert eval_result.input == input_value - assert eval_result.expected == expected_value - assert eval_result.output == expected_value - assert eval_result.scores.get("exact_match") == 1.0 - assert eval_result.error is None - - # Verify summary - assert result.summary.project_name == "test-project" - assert "exact_match" in result.summary.scores - assert result.summary.scores["exact_match"].score == 1.0 - - -@pytest.mark.asyncio -async def test_run_evaluator_with_many_scorers(): - # This test validates that we can process scores from any sources. It is nox's job - # to ensure this test runs with and without autoevals and braintrust_core installed. - try: - from braintrust_core.score import Score as BraintrustCoreScore - except ImportError: - from .score import Score as BraintrustCoreScore - - # Define test data - data = [ - EvalCase(input="abc", expected="abc"), - EvalCase(input="def", expected="def"), - ] - - def simple_task(input_value): - return input_value - - def dict_scorer(input_value, output, expected): - return {"name": "dict_scorer", "score": 1.0} - - def core_scorer(input_value, output, expected): - return BraintrustCoreScore(name="core_scorer", score=1.0) - - def scorer(input_value, output, expected): - return Score(name="scorer", score=1.0) - - class CustomScorer(Scorer): - def _run_eval_sync(self, *args, **kwargs): - return Score(name="custom_scorer", score=1.0) - - class CustomScorerAsync(Scorer): - async def eval_async(self, *args, **kwargs): - return Score(name="custom_async_scorer", score=1.0) - - def _run_eval_sync(self, *args, **kwargs): - return Score(name="custom_async_scorer", score=1.0) - - scorers = [ - dict_scorer, - core_scorer, - scorer, - CustomScorer(), - CustomScorerAsync(), - ] - scorer_names = [ - "core_scorer", - "scorer", - "dict_scorer", - "custom_scorer", - "custom_async_scorer", - ] - - # if autoevals is installed, use it. This verifies our scoring duck typing works - try: - from autoevals import Levenshtein - - scorers.append(Levenshtein()) - scorer_names.append("Levenshtein") - scorers.append(Levenshtein) - scorer_names.append("Levenshtein") - except ImportError: - pass - - # Create evaluator with all scorers - evaluator = Evaluator( - project_name="test-project", - eval_name="test-multiple-score-classes", - data=data, - task=simple_task, - scores=scorers, - experiment_name=None, - metadata=None, - ) - - # Run evaluator - result = await run_evaluator(None, evaluator, None, []) - - assert isinstance(result, EvalResultWithSummary) - assert len(result.results) == 2 - - # All scorers should produce the same scores - for eval_result in result.results: - for scorer_name in scorer_names: - print(eval_result.scores) - assert scorer_name in eval_result.scores - assert eval_result.scores[scorer_name] == 1.0 - - assert result.summary.project_name == "test-project" - for scorer_name in scorer_names: - assert scorer_name in result.summary.scores - assert result.summary.scores[scorer_name].score == 1.0 - - -@pytest.mark.asyncio -async def test_hooks_trial_index(): - """Test that trial_index is correctly passed to task via hooks.""" - trial_indices: List[int] = [] - - # Task that captures trial indices - def task_with_hooks(input_value: int, hooks: EvalHooks) -> int: - trial_indices.append(hooks.trial_index) - return input_value * 2 - - # Create evaluator with trial_count > 1 - evaluator = Evaluator( - project_name="test-project", - eval_name="test-trial-index", - data=[EvalCase(input=1, expected=2)], - task=task_with_hooks, - scores=[], # No scoring needed for this test - experiment_name=None, - metadata=None, - trial_count=3, # Run 3 trials - ) - - # Run evaluator - result = await run_evaluator(experiment=None, evaluator=evaluator, position=None, filters=[]) - - # Verify we got 3 results (one for each trial) - assert len(result.results) == 3 - - # Verify trial indices were captured correctly - assert len(trial_indices) == 3 - assert sorted(trial_indices) == [0, 1, 2] - - # Verify all results are correct - for eval_result in result.results: - assert eval_result.input == 1 - assert eval_result.expected == 2 - assert eval_result.output == 2 # 1 * 2 - assert eval_result.error is None - - -@pytest.mark.asyncio -async def test_hooks_trial_index_multiple_inputs(): - """Test trial_index with multiple inputs to ensure proper indexing.""" - trial_data: List[tuple] = [] # (input, trial_index) - - def task_with_hooks(input_value: int, hooks: EvalHooks) -> int: - trial_data.append((input_value, hooks.trial_index)) - return input_value * 2 - - # Create evaluator with multiple inputs and trials - evaluator = Evaluator( - project_name="test-project", - eval_name="test-trial-index-multiple", - data=[ - EvalCase(input=1, expected=2), - EvalCase(input=2, expected=4), - ], - task=task_with_hooks, - scores=[], - experiment_name=None, - metadata=None, - trial_count=2, # 2 trials per input - ) - - # Run evaluator - result = await run_evaluator(experiment=None, evaluator=evaluator, position=None, filters=[]) - - # Should have 4 results total (2 inputs ร— 2 trials) - assert len(result.results) == 4 - assert len(trial_data) == 4 - - # Group by input to verify trial indices - input_1_trials = [trial_idx for inp, trial_idx in trial_data if inp == 1] - input_2_trials = [trial_idx for inp, trial_idx in trial_data if inp == 2] - - # Each input should have been run with trial indices 0 and 1 - assert sorted(input_1_trials) == [0, 1] - assert sorted(input_2_trials) == [0, 1] - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_scorer_spans_have_purpose_attribute(with_memory_logger, with_simulate_login): - """Test that scorer spans have span_attributes.purpose='scorer' and propagate to subspans.""" - # Define test data - data = [ - EvalCase(input="hello", expected="hello"), - ] - - def simple_task(input_value): - return input_value - - def purpose_scorer(input_value, output, expected): - return 1.0 if output == expected else 0.0 - - evaluator = Evaluator( - project_name="test-project", - eval_name="test-scorer-purpose", - data=data, - task=simple_task, - scores=[purpose_scorer], - experiment_name="test-scorer-purpose", - metadata=None, - ) - - # Create experiment so spans get logged - exp = init_test_exp("test-scorer-purpose", "test-project") - - # Run evaluator - result = await run_evaluator(experiment=exp, evaluator=evaluator, position=None, filters=[]) - - assert len(result.results) == 1 - assert result.results[0].scores.get("purpose_scorer") == 1.0 - - # Check the logged spans - logs = with_memory_logger.pop() - - # Find the scorer span (has type="score") - scorer_spans = [log for log in logs if log.get("span_attributes", {}).get("type") == "score"] - assert len(scorer_spans) == 1, f"Expected 1 scorer span, found {len(scorer_spans)}" - - scorer_span = scorer_spans[0] - - # Verify the scorer span has purpose='scorer' - assert scorer_span["span_attributes"].get("purpose") == "scorer", ( - f"Scorer span should have purpose='scorer', got: {scorer_span['span_attributes']}" - ) - - # Verify that non-scorer spans (task, eval) do NOT have purpose='scorer' - non_scorer_spans = [log for log in logs if log.get("span_attributes", {}).get("type") != "score"] - assert len(non_scorer_spans) > 0, "Expected at least one non-scorer span" - for span in non_scorer_spans: - assert span.get("span_attributes", {}).get("purpose") != "scorer", ( - f"Non-scorer span should NOT have purpose='scorer', got: {span['span_attributes']}" - ) - - -@pytest.fixture -def simple_scorer(): - def simple_scorer_function(input, output, expected): - return {"name": "simple_scorer", "score": 0.8} - - return simple_scorer_function - - -@pytest.mark.asyncio -async def test_eval_no_send_logs_true(with_memory_logger, simple_scorer): - """Test that Eval with no_send_logs=True runs locally without creating experiment.""" - - def exact_match(input, output, expected): - return {"name": "exact_match", "score": 1.0 if output == expected else 0.0} - - result = await Eval( - "test-no-logs", - data=[{"input": "hello", "expected": "hello world"}, {"input": "test", "expected": "test world"}], - task=lambda input_val: input_val + " world", - scores=[exact_match, simple_scorer], - no_send_logs=True, - ) - - # Verify it returns results - assert len(result.results) == 2 - assert result.results[0].input == "hello" - assert result.results[0].output == "hello world" - assert result.results[0].scores["exact_match"] == 1.0 - assert result.results[0].scores["simple_scorer"] == 0.8 - - assert result.results[1].input == "test" - assert result.results[1].output == "test world" - assert result.results[1].scores["exact_match"] == 1.0 - assert result.results[1].scores["simple_scorer"] == 0.8 - - # Verify it builds a local summary (no experiment_url means local run) - assert result.summary.project_name == "test-no-logs" - assert result.summary.experiment_url is None - assert result.summary.scores["exact_match"].score == 1.0 - assert result.summary.scores["simple_scorer"].score == 0.8 - - # Most importantly: verify that no logs were sent (should be empty) - logs = with_memory_logger.pop() - assert len(logs) == 0 - - -@pytest.mark.asyncio -async def test_eval_no_send_logs_with_none_score(with_memory_logger): - """Test that scorers returning None don't crash local mode.""" - - def sometimes_none_scorer(input, output, expected): - # Return None for first input, score for second - if input == "hello": - return {"name": "conditional", "score": None} - return {"name": "conditional", "score": 1.0} - - result = await Eval( - "test-none-score", - data=[ - {"input": "hello", "expected": "hello world"}, - {"input": "test", "expected": "test world"}, - ], - task=lambda input_val: input_val + " world", - scores=[sometimes_none_scorer], - no_send_logs=True, - ) - - # Should not crash and should calculate average from non-None scores only - assert result.summary.scores["conditional"].score == 1.0 # Only the second score counts - - -@pytest.mark.asyncio -async def test_hooks_tags_append(with_memory_logger, with_simulate_login, simple_scorer): - """Test that hooks.tags can be appended to and logged.""" - - initial_tags = ["cookies n cream"] - appended_tags = ["chocolate", "vanilla", "strawberry"] - expected_tags = ["cookies n cream", "chocolate", "vanilla", "strawberry"] - - def task_with_hooks(input, hooks): - for x in appended_tags: - hooks.tags.append(x) - return input - - evaluator = Evaluator( - project_name=__name__, - eval_name=__name__, - data=[EvalCase(input="hello", expected="hello world", tags=initial_tags)], - task=task_with_hooks, - scores=[simple_scorer], - experiment_name=__name__, - metadata=None, - summarize_scores=False, - ) - exp = init_test_exp(__name__) - result = await run_evaluator(experiment=exp, evaluator=evaluator, position=None, filters=[]) - assert result.results[0].tags == expected_tags - - logs = with_memory_logger.pop() - assert len(logs) == 3 - - # assert root span contains tags - root_span = [log for log in logs if not log["span_parents"]] - assert len(root_span) == 1 - assert root_span[0].get("tags") == expected_tags - - -@pytest.mark.asyncio -@pytest.mark.parametrize( - ("tags", "expected_tags"), - [(None, None), ([], None), (["chocolate", "vanilla", "strawberry"], ["chocolate", "vanilla", "strawberry"])], -) -async def test_hooks_tags_list(with_memory_logger, with_simulate_login, simple_scorer, tags, expected_tags): - """Test that hooks.tags can be set to a list.""" - - def task_with_hooks(input, hooks): - hooks.tags = tags - return input - - evaluator = Evaluator( - project_name=__name__, - eval_name=__name__, - data=[EvalCase(input="hello", expected="hello world")], - task=task_with_hooks, - scores=[simple_scorer], - experiment_name=__name__, - metadata=None, - summarize_scores=False, - ) - exp = init_test_exp(__name__) - result = await run_evaluator(experiment=exp, evaluator=evaluator, position=None, filters=[]) - assert result.results[0].tags == expected_tags - - logs = with_memory_logger.pop() - assert len(logs) == 3 - - # assert root span contains tags - root_span = [log for log in logs if not log["span_parents"]] - assert len(root_span) == 1 - assert root_span[0].get("tags") == expected_tags - - -@pytest.mark.asyncio -async def test_hooks_tags_with_failing_scorer(with_memory_logger, with_simulate_login, simple_scorer): - """Test that hooks.tags can be set to a list.""" - - expected_tags = ["chocolate", "vanilla", "strawberry"] - - def task_with_hooks(input, hooks): - hooks.tags = expected_tags - return input - - def failing_scorer(input, output, expected): - raise Exception("test error") - - evaluator = Evaluator( - project_name=__name__, - eval_name=__name__, - data=[EvalCase(input="hello", expected="hello world")], - task=task_with_hooks, - scores=[simple_scorer, failing_scorer], - experiment_name=__name__, - metadata=None, - summarize_scores=False, - ) - exp = init_test_exp(__name__) - result = await run_evaluator(experiment=exp, evaluator=evaluator, position=None, filters=[]) - assert result.results[0].tags == expected_tags - - logs = with_memory_logger.pop() - assert len(logs) == 4 - - # assert root span contains tags - root_span = [log for log in logs if not log["span_parents"]] - assert len(root_span) == 1 - assert root_span[0].get("tags") == expected_tags - - -@pytest.mark.asyncio -async def test_hooks_tags_with_invalid_type(with_memory_logger, with_simulate_login, simple_scorer): - """Test that result contains an error for cases where hooks.tags is set to an invalid type.""" - - def task_with_hooks(input, hooks): - hooks.tags = 123 - return input - - evaluator = Evaluator( - project_name=__name__, - eval_name=__name__, - data=[EvalCase(input="hello", expected="hello world")], - task=task_with_hooks, - scores=[simple_scorer], - experiment_name=__name__, - metadata=None, - summarize_scores=False, - ) - exp = init_test_exp(__name__) - result = await run_evaluator(experiment=exp, evaluator=evaluator, position=None, filters=[]) - assert len(result.results) == 1 - assert isinstance(result.results[0].error, TypeError) - - -@pytest.mark.asyncio -async def test_hooks_without_setting_tags(with_memory_logger, with_simulate_login, simple_scorer): - """Test where hooks.tags is not set""" - - def task_with_hooks(input, hooks): - return input - - evaluator = Evaluator( - project_name=__name__, - eval_name=__name__, - data=[EvalCase(input="hello", expected="hello world")], - task=task_with_hooks, - scores=[simple_scorer], - experiment_name=__name__, - metadata=None, - summarize_scores=False, - ) - exp = init_test_exp(__name__) - result = await run_evaluator(experiment=exp, evaluator=evaluator, position=None, filters=[]) - assert result.results[0].tags == None - - logs = with_memory_logger.pop() - assert len(logs) == 3 - - # assert root span contains tags - root_span = [log for log in logs if not log["span_parents"]] - assert len(root_span) == 1 - assert root_span[0].get("tags") == None - -@pytest.mark.asyncio -async def test_eval_enable_cache(): - state = BraintrustState() - state.span_cache = MagicMock() - - # Test enable_cache=False - await Eval( - "test-enable-cache-false", - data=[EvalCase(input=1, expected=1)], - task=lambda x: x, - scores=[], - state=state, - no_send_logs=True, - enable_cache=False, - ) - state.span_cache.start.assert_not_called() - state.span_cache.stop.assert_not_called() - - # Test enable_cache=True (default) - state.span_cache.start.reset_mock() - state.span_cache.stop.reset_mock() - - await Eval( - "test-enable-cache-true", - data=[EvalCase(input=1, expected=1)], - task=lambda x: x, - scores=[], - state=state, - no_send_logs=True, - # enable_cache defaults to True - ) - state.span_cache.start.assert_called() - state.span_cache.stop.assert_called() diff --git a/py/src/braintrust/test_framework2.py b/py/src/braintrust/test_framework2.py deleted file mode 100644 index 8f86eedf5..000000000 --- a/py/src/braintrust/test_framework2.py +++ /dev/null @@ -1,233 +0,0 @@ -"""Tests for framework2 module, specifically metadata support.""" - -import importlib.util -from unittest.mock import MagicMock - -import pytest - -from .framework2 import ( - ProjectIdCache, - projects, -) - -# Check if pydantic is available -HAS_PYDANTIC = importlib.util.find_spec("pydantic") is not None - - -class TestCodeFunctionMetadata: - """Tests for CodeFunction metadata support.""" - - def test_code_function_with_metadata(self): - """Test that CodeFunction stores metadata correctly.""" - project = projects.create("test-project") - metadata = {"version": "1.0", "author": "test"} - - tool = project.tools.create( - handler=lambda x: x, - name="test-tool", - parameters=None, - metadata=metadata, - ) - - assert tool.metadata == metadata - assert tool.name == "test-tool" - assert tool.slug == "test-tool" - - def test_code_function_without_metadata(self): - """Test that CodeFunction works without metadata.""" - project = projects.create("test-project") - - tool = project.tools.create( - handler=lambda x: x, - name="test-tool", - parameters=None, - ) - - assert tool.metadata is None - - -class TestCodePromptMetadata: - """Tests for CodePrompt metadata support.""" - - def test_code_prompt_with_metadata(self): - """Test that CodePrompt stores metadata correctly.""" - project = projects.create("test-project") - metadata = {"category": "greeting", "priority": "high"} - - prompt = project.prompts.create( - name="test-prompt", - prompt="Hello {{name}}", - model="gpt-4", - metadata=metadata, - ) - - assert prompt.metadata == metadata - assert prompt.name == "test-prompt" - - def test_code_prompt_without_metadata(self): - """Test that CodePrompt works without metadata.""" - project = projects.create("test-project") - - prompt = project.prompts.create( - name="test-prompt", - prompt="Hello {{name}}", - model="gpt-4", - ) - - assert prompt.metadata is None - - def test_code_prompt_to_function_definition_includes_metadata(self): - """Test that to_function_definition includes metadata when present.""" - project = projects.create("test-project") - metadata = {"version": "2.0", "tag": "production"} - - prompt = project.prompts.create( - name="test-prompt", - prompt="Hello {{name}}", - model="gpt-4", - metadata=metadata, - ) - - mock_project_ids = MagicMock(spec=ProjectIdCache) - mock_project_ids.get.return_value = "project-123" - - func_def = prompt.to_function_definition(None, mock_project_ids) - - assert func_def["metadata"] == metadata - assert func_def["name"] == "test-prompt" - assert func_def["project_id"] == "project-123" - - def test_code_prompt_to_function_definition_excludes_metadata_when_none(self): - """Test that to_function_definition excludes metadata when None.""" - project = projects.create("test-project") - - prompt = project.prompts.create( - name="test-prompt", - prompt="Hello {{name}}", - model="gpt-4", - ) - - mock_project_ids = MagicMock(spec=ProjectIdCache) - mock_project_ids.get.return_value = "project-123" - - func_def = prompt.to_function_definition(None, mock_project_ids) - - assert "metadata" not in func_def - - -class TestScorerMetadata: - """Tests for Scorer metadata support.""" - - @pytest.mark.skipif(not HAS_PYDANTIC, reason="pydantic not installed") - def test_code_scorer_with_metadata(self): - """Test that code scorer stores metadata correctly.""" - from pydantic import BaseModel - - class ScorerInput(BaseModel): - output: str - expected: str - - project = projects.create("test-project") - metadata = {"type": "accuracy", "version": "1.0"} - - def my_scorer(output: str, expected: str) -> float: - return 1.0 if output == expected else 0.0 - - scorer = project.scorers.create( - handler=my_scorer, - name="test-scorer", - parameters=ScorerInput, - metadata=metadata, - ) - - assert scorer.metadata == metadata - assert scorer.name == "test-scorer" - - def test_llm_scorer_with_metadata(self): - """Test that LLM scorer stores metadata correctly.""" - project = projects.create("test-project") - metadata = {"type": "llm_classifier", "version": "2.0"} - - scorer = project.scorers.create( - name="llm-scorer", - prompt="Is this correct?", - model="gpt-4", - use_cot=True, - choice_scores={"yes": 1.0, "no": 0.0}, - metadata=metadata, - ) - - assert scorer.metadata == metadata - assert scorer.name == "llm-scorer" - - -@pytest.mark.skipif(not HAS_PYDANTIC, reason="pydantic not installed") -class TestPushMetadata: - """Tests for metadata in push command serialization.""" - - def test_collect_function_function_defs_includes_metadata(self): - """Test that _collect_function_function_defs includes metadata.""" - from pydantic import BaseModel - - from .cli.push import _collect_function_function_defs - from .framework2 import global_ - - class ToolInput(BaseModel): - value: int - - project = projects.create("test-project") - metadata = {"version": "1.0", "author": "test"} - - global_.functions.clear() - - tool = project.tools.create( - handler=lambda x: x, - name="test-tool", - parameters=ToolInput, - metadata=metadata, - ) - global_.functions.append(tool) - - mock_project_ids = MagicMock(spec=ProjectIdCache) - mock_project_ids.get.return_value = "project-123" - - functions = [] - _collect_function_function_defs(mock_project_ids, functions, "bundle-123", "error") - - assert len(functions) == 1 - assert functions[0]["metadata"] == metadata - assert functions[0]["name"] == "test-tool" - - global_.functions.clear() - - def test_collect_function_function_defs_excludes_metadata_when_none(self): - """Test that _collect_function_function_defs excludes metadata when None.""" - from pydantic import BaseModel - - from .cli.push import _collect_function_function_defs - from .framework2 import global_ - - class ToolInput(BaseModel): - value: int - - project = projects.create("test-project") - - global_.functions.clear() - - tool = project.tools.create( - handler=lambda x: x, - name="test-tool", - parameters=ToolInput, - ) - global_.functions.append(tool) - - mock_project_ids = MagicMock(spec=ProjectIdCache) - mock_project_ids.get.return_value = "project-123" - - functions = [] - _collect_function_function_defs(mock_project_ids, functions, "bundle-123", "error") - - assert len(functions) == 1 - assert "metadata" not in functions[0] - - global_.functions.clear() diff --git a/py/src/braintrust/test_helpers.py b/py/src/braintrust/test_helpers.py deleted file mode 100644 index 7e24bb238..000000000 --- a/py/src/braintrust/test_helpers.py +++ /dev/null @@ -1,382 +0,0 @@ -import os -from contextlib import contextmanager - -import pytest -from braintrust import logger -from braintrust.logger import ObjectMetadata, OrgProjectMetadata, ProjectExperimentMetadata -from braintrust.util import LazyValue - -# Fake API key for testing only - this will not work with actual API calls -TEST_ORG_ID = "test-org-id" -TEST_ORG_NAME = "test-org-name" - - -def has_devserver_installed() -> bool: - """Check if devserver dependencies (starlette, uvicorn) are installed.""" - import importlib.util - - return importlib.util.find_spec("starlette") is not None and importlib.util.find_spec("uvicorn") is not None - - -def simulate_login() -> None: - """ - Simulate a successful login for testing purposes. - - This lets you use Braintrust features that require login without actually - connecting to the Braintrust service. Logs will be stored locally - rather than sent to Braintrust. - """ - simulate_logout() - logger.login(api_key=logger.TEST_API_KEY) - - -def simulate_logout() -> None: - """ - Simulate logging out for testing purposes. - - This resets the login state after using simulate_login_for_tests. - """ - # Reset login state - logger._state.reset_login_info() - logger._state.reset_parent_state() - - -def assert_logged_out(): - assert not logger._state.logged_in - assert logger._state.login_token is None - assert logger._state.org_id is None - assert logger._state.org_name is None - - -@pytest.fixture -def with_simulate_login(): - simulate_login() - try: - yield - finally: - simulate_logout() - - -@pytest.fixture -def with_memory_logger(): - logger._state.reset_parent_state() - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - # Clean up global state to prevent test contamination - logger._state.reset_parent_state() - - -@pytest.fixture -def memory_logger(): - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - logger._state.current_experiment = None - - -@contextmanager -def preserve_env_vars(*vars): - original_env = {v: os.environ.get(v) for v in vars} - try: - yield - finally: - for v in vars: - os.environ.pop(v, None) - for v, val in original_env.items(): - if val: - os.environ[v] = val - - -def init_test_logger(project_name: str): - """ - Initialize a logger for testing with a fake project and org. - - This sets up a logger with fake metadata to avoid requiring actual - API calls. This is useful for testing wrappers. - - Args: - project_name: The name to use for the test project. - """ - project_metadata = ObjectMetadata(id=project_name, name=project_name, full_info=dict()) - metadata = OrgProjectMetadata(org_id=TEST_ORG_ID, project=project_metadata) - lazy_metadata = LazyValue(lambda: metadata, use_mutex=False) - l = logger.init_logger(project=project_name) - l._lazy_metadata = lazy_metadata # Skip actual login by setting fake metadata directly - - # Replace the global _compute_logger_metadata function with a resolved LazyValue - def fake_compute_logger_metadata(project_name=None, project_id=None): - if project_id: - project_metadata = ObjectMetadata(id=project_id, name=project_name, full_info=dict()) - else: - project_metadata = ObjectMetadata(id=project_name, name=project_name, full_info=dict()) - return OrgProjectMetadata(org_id=TEST_ORG_ID, project=project_metadata) - - logger._compute_logger_metadata = fake_compute_logger_metadata - return l - - -def init_test_exp(experiment_name: str, project_name: str = None): - """ - Initialize an experiment for testing with fake project and experiment metadata. - - This sets up an experiment with fake metadata to avoid requiring actual - API calls. This is useful for testing experiment validation behavior. - - Args: - experiment_name: The name to use for the test experiment. - project_name: The name to use for the test project. Defaults to experiment_name. - """ - if project_name is None: - project_name = experiment_name - - import braintrust - - project_metadata = ObjectMetadata(id=project_name, name=project_name, full_info=dict()) - experiment_metadata = ObjectMetadata(id=experiment_name, name=experiment_name, full_info=dict()) - metadata = ProjectExperimentMetadata(project=project_metadata, experiment=experiment_metadata) - lazy_metadata = LazyValue(lambda: metadata, use_mutex=False) - - exp = braintrust.init(project=project_name, experiment=experiment_name) - exp._lazy_metadata = lazy_metadata # Skip actual login by setting fake metadata directly - return exp - - -# ---------------------------------------------------------------------- -# Tests for the helper functions -# ---------------------------------------------------------------------- - - -def test_without_login_pre(): - assert not logger._state.logged_in - - -def test_with_simulate_login(with_simulate_login): - assert logger._state.logged_in - - -def test_without_login_post(): - assert not logger._state.logged_in - - -def test_simulate_login_logout(): - """Test that simulate_login and simulate_logout work properly.""" - # Test that we're not logged in initially - for i in range(4): - assert not logger._state.logged_in - - # Simulate login - simulate_login() - - # Verify we're now logged in with the expected test values - assert logger._state.logged_in - assert logger._state.login_token == logger.TEST_API_KEY - assert logger._state.org_id == TEST_ORG_ID - assert logger._state.org_name == TEST_ORG_NAME - assert logger._state.app_url == "https://www.braintrust.dev" - assert logger._state.app_public_url == "https://www.braintrust.dev" - - assert logger.org_id() == TEST_ORG_ID - - # Simulate logout - simulate_logout() - - # Verify we're logged out - assert not logger._state.logged_in - assert logger._state.login_token is None - assert logger._state.org_id is None - assert logger._state.org_name is None - - -def test_memory_logger(): - init_test_logger(__name__) - with logger._internal_with_memory_background_logger() as bgl: - assert not bgl.pop() - - @logger.traced - def thing(): - return "hello" - - thing() - logs = bgl.pop() - assert len(logs) == 1 - assert logs - - -def assert_dict_matches(actual, expected, exact_keys=False): - """Assert that actual dictionary matches expected dictionary. - - The expected dictionary can be a subset of actual (i.e. actual can have additional keys). - Values in expected can be functions that validate the actual value. - - Args: - actual: The actual dictionary to check - expected: The expected dictionary pattern to match - exact_keys: If True, actual and expected must have exactly the same keys. - If False (default), actual can have keys not in expected. - - + assert_dict_matches({"a":"a", "b":2, "c":3}, { - + "a": "a", # Values match exactly - + "b": lambda x: isinstance(x, int) # Custom validation with lambda - + }) # => passes - """ - if exact_keys: - actual_keys = set(actual.keys()) - expected_keys = set(expected.keys()) - assert actual_keys == expected_keys, f"Key sets do not match. Actual: {actual_keys}, Expected: {expected_keys}" - - for key, expected_val in expected.items(): - assert key in actual, f"Expected key '{key}' not found" - - actual_val = actual[key] - - if callable(expected_val): - # Expected value is a validation function - assert expected_val(actual_val), f"Validation failed for key '{key}': {actual_val}" - elif isinstance(expected_val, dict) and isinstance(actual_val, dict): - # Recursively validate nested dictionaries - assert_dict_matches(actual_val, expected_val, exact_keys) - elif isinstance(expected_val, (list, tuple)) and isinstance(actual_val, (list, tuple)): - # Handle lists and tuples - must match exactly - _assert_sequence_matches(actual_val, expected_val, key, exact_keys) - else: - # Direct value comparison - assert actual_val == expected_val, ( - f"Value mismatch for key '{key}': expected {expected_val}, got {actual_val}" - ) - - -def _assert_sequence_matches(actual_seq, expected_seq, key, exact_keys=False): - """Helper function to match sequences (lists/tuples) exactly.""" - assert len(expected_seq) == len(actual_seq), ( - f"Sequence length mismatch for key '{key}': expected {len(expected_seq)} items, got {len(actual_seq)}" - ) - - for i, (expected_item, actual_item) in enumerate(zip(expected_seq, actual_seq)): - if isinstance(expected_item, dict) and isinstance(actual_item, dict): - # Recursively validate nested dictionaries - assert_dict_matches(actual_item, expected_item, exact_keys) - elif isinstance(expected_item, (list, tuple)) and isinstance(actual_item, (list, tuple)): - # Recursively validate nested sequences - _assert_sequence_matches(actual_item, expected_item, f"{key}[{i}]", exact_keys) - else: - # Direct value comparison - assert actual_item == expected_item, ( - f"Sequence item mismatch for key '{key}' at index {i}: expected {expected_item}, got {actual_item}" - ) - - -def test_assert_dict_matches(): - d = {"a": 1, "b": 2, "c": 3} - assert_dict_matches(d, d) - assert_dict_matches(d, d.copy()) - assert_dict_matches(d, {"a": 1, "b": 2}) - assert_dict_matches(d, {"b": 2, "c": 3}) - assert_dict_matches(d, {"b": lambda x: x == 2, "c": 3}) - assert_dict_matches(d, {"b": lambda x: isinstance(x, int), "c": 3}) - - e = {"1": 1, "2": d} - assert_dict_matches(e, e) - - # Test mismatched values - with pytest.raises(AssertionError): - assert_dict_matches(d, {"a": 2}) - - # Test missing required key - with pytest.raises(AssertionError): - assert_dict_matches(d, {"d": 4}) - - # Test lambda validation failure - with pytest.raises(AssertionError): - assert_dict_matches(d, {"a": lambda x: x > 10}) - - # Test nested dict mismatch - with pytest.raises(AssertionError): - assert_dict_matches(e, {"1": 1, "2": {"a": 999}}) - - # Test type mismatch - with pytest.raises(AssertionError): - assert_dict_matches(d, {"a": "1"}) - - # Test empty expected dict should pass (matches any actual dict) - assert_dict_matches(d, {}) - - -def test_assert_dict_matches_exact_keys(): - """Test exact key matching.""" - actual = {"a": 1, "b": 2, "c": 3} - - # Exact match should pass - assert_dict_matches(actual, {"a": 1, "b": 2, "c": 3}, exact_keys=True) - - # Missing key in expected should fail - with pytest.raises(AssertionError, match="Key sets do not match"): - assert_dict_matches(actual, {"a": 1, "b": 2}, exact_keys=True) - - # Extra key in expected should fail - with pytest.raises(AssertionError, match="Key sets do not match"): - assert_dict_matches(actual, {"a": 1, "b": 2, "c": 3, "d": 4}, exact_keys=True) - - # Test with nested dictionaries - actual_nested = {"outer": {"a": 1, "b": 2}} - - # Exact nested match should pass - assert_dict_matches(actual_nested, {"outer": {"a": 1, "b": 2}}, exact_keys=True) - - # Missing nested key should fail - with pytest.raises(AssertionError, match="Key sets do not match"): - assert_dict_matches(actual_nested, {"outer": {"a": 1}}, exact_keys=True) - - -def test_assert_dict_matches_with_lists_and_tuples(): - """Test that assert_dict_matches correctly handles lists and tuples.""" - - # Test with lists - exact match - actual_with_list = { - "messages": [{"role": "user", "content": "Hello"}, {"role": "assistant", "content": "Hi there"}], - "model": "gpt-4", - } - - # Should match exact list - assert_dict_matches( - actual_with_list, - {"messages": [{"role": "user", "content": "Hello"}, {"role": "assistant", "content": "Hi there"}]}, - ) - - # Test with tuples - actual_with_tuple = {"coords": (1, 2, 3), "name": "point"} - - assert_dict_matches(actual_with_tuple, {"coords": (1, 2, 3)}) - - # Test with mixed nested structures - complex_actual = {"data": {"items": [{"id": 1, "tags": ("a", "b")}, {"id": 2, "tags": ("c", "d")}]}} - - assert_dict_matches( - complex_actual, {"data": {"items": [{"id": 1, "tags": ("a", "b")}, {"id": 2, "tags": ("c", "d")}]}} - ) - - # Test partial dictionary match within list items - assert_dict_matches( - complex_actual, - { - "data": { - "items": [{"id": 1}, {"tags": ("c", "d")}] # Only checking id, not tags # Only checking tags, not id - } - }, - ) - - # Test list length mismatch - with pytest.raises(AssertionError): - assert_dict_matches( - actual_with_list, - {"messages": [{"role": "user", "content": "Hello"}]}, # Expected only 1 item, actual has 2 - ) - - # Test list content mismatch - with pytest.raises(AssertionError): - assert_dict_matches( - actual_with_list, - {"messages": [{"role": "user", "content": "Wrong content"}, {"role": "assistant", "content": "Hi there"}]}, - ) - - # Test tuple mismatch - with pytest.raises(AssertionError): - assert_dict_matches(actual_with_tuple, {"coords": (1, 2, 4)}) # Wrong third element diff --git a/py/src/braintrust/test_http.py b/py/src/braintrust/test_http.py deleted file mode 100644 index b9ede8d84..000000000 --- a/py/src/braintrust/test_http.py +++ /dev/null @@ -1,444 +0,0 @@ -"""Tests for HTTP connection handling, retries, and timeouts.""" - -import http.server -import os -import socketserver -import threading -import time - -import pytest -import requests -from braintrust.logger import HTTPConnection, RetryRequestExceptionsAdapter - - -class HangingConnectionHandler(http.server.BaseHTTPRequestHandler): - """HTTP handler that simulates stale connections by HANGING (not responding). - - This simulates what happens when a NAT gateway silently drops packets: - - The TCP connection appears open - - Packets are sent but never acknowledged - - The client waits forever for a response - """ - - request_count = 0 - hang_count = 1 - - def log_message(self, format, *args): - pass - - def do_POST(self): - HangingConnectionHandler.request_count += 1 - - if HangingConnectionHandler.request_count <= HangingConnectionHandler.hang_count: - # Simulate stale connection: hang long enough for client to timeout - for _ in range(100): # 10 seconds total, interruptible - time.sleep(0.1) - return - - self.send_response(200) - self.send_header("Content-Type", "application/json") - self.end_headers() - self.wfile.write(b'{"status": "ok"}') - - def do_GET(self): - self.do_POST() - - -class CloseConnectionHandler(http.server.BaseHTTPRequestHandler): - """HTTP handler that closes connection immediately (triggers ConnectionError).""" - - request_count = 0 - fail_count = 1 - - def log_message(self, format, *args): - pass - - def do_POST(self): - CloseConnectionHandler.request_count += 1 - - if CloseConnectionHandler.request_count <= CloseConnectionHandler.fail_count: - self.connection.close() - return - - self.send_response(200) - self.send_header("Content-Type", "application/json") - self.end_headers() - self.wfile.write(b'{"status": "ok"}') - - def do_GET(self): - self.do_POST() - - -@pytest.fixture -def hanging_server(): - """Fixture that creates a server that HANGS on first request (simulates stale NAT).""" - HangingConnectionHandler.request_count = 0 - HangingConnectionHandler.hang_count = 1 - - server = socketserver.ThreadingTCPServer(("127.0.0.1", 0), HangingConnectionHandler) - server.daemon_threads = True - port = server.server_address[1] - - thread = threading.Thread(target=server.serve_forever) - thread.daemon = True - thread.start() - - yield f"http://127.0.0.1:{port}" - - server.shutdown() - server.server_close() - - -@pytest.fixture -def closing_server(): - """Fixture that creates a server that CLOSES connection on first request.""" - CloseConnectionHandler.request_count = 0 - CloseConnectionHandler.fail_count = 1 - - server = socketserver.ThreadingTCPServer(("127.0.0.1", 0), CloseConnectionHandler) - server.daemon_threads = True - port = server.server_address[1] - - thread = threading.Thread(target=server.serve_forever) - thread.daemon = True - thread.start() - - yield f"http://127.0.0.1:{port}" - - server.shutdown() - server.server_close() - - -class TestRetryRequestExceptionsAdapter: - """Tests for RetryRequestExceptionsAdapter timeout and retry behavior.""" - - def test_adapter_has_default_timeout(self): - """Adapter should have a default_timeout_secs attribute.""" - adapter = RetryRequestExceptionsAdapter(base_num_retries=3, backoff_factor=0.1) - - assert hasattr(adapter, "default_timeout_secs") - assert adapter.default_timeout_secs == 60 - - def test_adapter_applies_default_timeout_to_requests(self, hanging_server): - """Requests without explicit timeout should use default_timeout_secs.""" - adapter = RetryRequestExceptionsAdapter( - base_num_retries=3, - backoff_factor=0.05, - default_timeout_secs=0.2, - ) - session = requests.Session() - session.mount("http://", adapter) - - start = time.time() - resp = session.post(f"{hanging_server}/test", json={"hello": "world"}) - elapsed = time.time() - start - - assert resp.status_code == 200 - assert elapsed < 2.0, f"Should complete within 2s, took {elapsed:.2f}s" - assert HangingConnectionHandler.request_count >= 2 - - def test_adapter_retries_on_connection_close(self, closing_server): - """Adapter retries on connection close errors.""" - adapter = RetryRequestExceptionsAdapter(base_num_retries=5, backoff_factor=0.05) - session = requests.Session() - session.mount("http://", adapter) - - start = time.time() - resp = session.post(f"{closing_server}/test", json={"hello": "world"}) - elapsed = time.time() - start - - assert resp.status_code == 200 - assert elapsed < 5.0 - assert CloseConnectionHandler.request_count >= 2 - - def test_adapter_resets_pool_on_timeout(self, hanging_server): - """Adapter resets connection pool on timeout errors via self.close(). - - This is the key fix for stale NAT connections: when a request times out, - we reset the connection pool to ensure the next retry uses a fresh connection. - """ - adapter = RetryRequestExceptionsAdapter( - base_num_retries=10, - backoff_factor=0.05, - default_timeout_secs=0.2, - ) - session = requests.Session() - session.mount("http://", adapter) - - start = time.time() - resp = session.post(f"{hanging_server}/test", json={"hello": "world"}) - elapsed = time.time() - start - - assert resp.status_code == 200 - assert elapsed < 10.0, f"Request took too long: {elapsed:.2f}s" - assert HangingConnectionHandler.request_count >= 2 - - -class TestHTTPConnection: - """Tests for HTTPConnection timeout configuration.""" - - def test_make_long_lived_uses_default_timeout(self, hanging_server): - """HTTPConnection.make_long_lived() should use default_timeout_secs. - - This tests the exact scenario from the stale connection bug: - - Long eval run (15+ minutes) - - app_conn() becomes stale due to NAT gateway idle timeout - - summarize() calls fetch_base_experiment() - - Request hangs forever because no timeout - - With the fix, make_long_lived() uses default_timeout_secs (60s by default). - """ - os.environ["BRAINTRUST_HTTP_TIMEOUT"] = "0.2" - try: - conn = HTTPConnection(hanging_server) - conn.make_long_lived() - - assert hasattr(conn.adapter, "default_timeout_secs") - assert conn.adapter.default_timeout_secs == 0.2 - - start = time.time() - resp = conn.post("/test", json={"hello": "world"}) - elapsed = time.time() - start - - assert resp.status_code == 200 - # Allow more time due to backoff_factor=0.5 in make_long_lived() - assert elapsed < 15.0, f"Should complete within 15s, took {elapsed:.2f}s" - finally: - del os.environ["BRAINTRUST_HTTP_TIMEOUT"] - - def test_env_var_configures_timeout(self): - """BRAINTRUST_HTTP_TIMEOUT env var configures timeout via make_long_lived().""" - os.environ["BRAINTRUST_HTTP_TIMEOUT"] = "30" - try: - conn = HTTPConnection("http://localhost:8080") - conn.make_long_lived() - - assert hasattr(conn.adapter, "default_timeout_secs") - assert conn.adapter.default_timeout_secs == 30 - finally: - del os.environ["BRAINTRUST_HTTP_TIMEOUT"] - - -class TestAdapterCloseAndReuse: - """Tests verifying that adapter.close() allows subsequent requests. - - This addresses the review concern about whether calling self.close() - (which calls PoolManager.clear()) breaks subsequent request handling. - """ - - @pytest.fixture - def simple_server(self): - """Fixture that creates a server that always succeeds.""" - - class SimpleHandler(http.server.BaseHTTPRequestHandler): - request_count = 0 - - def log_message(self, format, *args): - pass - - def do_GET(self): - SimpleHandler.request_count += 1 - self.send_response(200) - self.send_header("Content-Type", "application/json") - self.end_headers() - self.wfile.write(b'{"status": "ok"}') - - SimpleHandler.request_count = 0 - server = socketserver.ThreadingTCPServer(("127.0.0.1", 0), SimpleHandler) - server.daemon_threads = True - port = server.server_address[1] - - thread = threading.Thread(target=server.serve_forever) - thread.daemon = True - thread.start() - - yield f"http://127.0.0.1:{port}", SimpleHandler - - server.shutdown() - server.server_close() - - def test_adapter_works_after_close(self, simple_server): - """Verify adapter.close() does not break subsequent requests. - - This is the key test for the PR feedback: after calling close(), - the PoolManager should create new connection pools on demand. - """ - url, handler = simple_server - - adapter = RetryRequestExceptionsAdapter(base_num_retries=3, backoff_factor=0.1) - session = requests.Session() - session.mount("http://", adapter) - - # First request works - resp1 = session.get(f"{url}/test1") - assert resp1.status_code == 200 - assert handler.request_count == 1 - - # Explicitly close the adapter (simulates what happens on timeout) - adapter.close() - - # Second request should still work after close() - resp2 = session.get(f"{url}/test2") - assert resp2.status_code == 200 - assert handler.request_count == 2 - - def test_adapter_works_after_multiple_closes(self, simple_server): - """Verify adapter works even after multiple close() calls.""" - url, handler = simple_server - - adapter = RetryRequestExceptionsAdapter(base_num_retries=3, backoff_factor=0.1) - session = requests.Session() - session.mount("http://", adapter) - - for i in range(3): - resp = session.get(f"{url}/test{i}") - assert resp.status_code == 200 - adapter.close() - - assert handler.request_count == 3 - - def test_concurrent_requests_with_close(self): - """Test thread safety: close() called while requests are in-flight. - - This tests a potential race condition where one thread calls close() - while another thread is mid-request. Requests are staggered to ensure - close() happens while some requests are in-flight. - """ - import concurrent.futures - - class SlowHandler(http.server.BaseHTTPRequestHandler): - request_count = 0 - - def log_message(self, format, *args): - pass - - def do_GET(self): - SlowHandler.request_count += 1 - # Simulate slow response - time.sleep(0.1) - self.send_response(200) - self.send_header("Content-Type", "application/json") - self.end_headers() - self.wfile.write(b'{"status": "ok"}') - - SlowHandler.request_count = 0 - server = socketserver.ThreadingTCPServer(("127.0.0.1", 0), SlowHandler) - server.daemon_threads = True - port = server.server_address[1] - url = f"http://127.0.0.1:{port}" - - server_thread = threading.Thread(target=server.serve_forever) - server_thread.daemon = True - server_thread.start() - - try: - adapter = RetryRequestExceptionsAdapter(base_num_retries=3, backoff_factor=0.1) - session = requests.Session() - session.mount("http://", adapter) - - errors = [] - - def make_request(i): - try: - time.sleep(i * 0.02) # Stagger requests - resp = session.get(f"{url}/test{i}") - return resp.status_code - except Exception as e: - errors.append(e) - return None - - def close_adapter(): - time.sleep(0.05) # Close while requests are in-flight - adapter.close() - - # Launch concurrent requests and a close() call - with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor: - # Start several requests (staggered) - request_futures = [executor.submit(make_request, i) for i in range(5)] - # Start close() call mid-flight - close_future = executor.submit(close_adapter) - - close_future.result() - results = [f.result() for f in request_futures] - - # All requests should succeed (retry on failure) - assert all(r == 200 for r in results), f"Some requests failed: {results}, errors: {errors}" - - finally: - server.shutdown() - server.server_close() - - def test_stress_concurrent_close_and_requests(self): - """Stress test: many close() calls interleaved with requests. - - Requests are staggered to ensure close() calls happen during requests. - """ - import concurrent.futures - - class FastHandler(http.server.BaseHTTPRequestHandler): - request_count = 0 - - def log_message(self, format, *args): - pass - - def do_GET(self): - FastHandler.request_count += 1 - self.send_response(200) - self.send_header("Content-Type", "application/json") - self.end_headers() - self.wfile.write(b'{"status": "ok"}') - - FastHandler.request_count = 0 - server = socketserver.ThreadingTCPServer(("127.0.0.1", 0), FastHandler) - server.daemon_threads = True - port = server.server_address[1] - url = f"http://127.0.0.1:{port}" - - server_thread = threading.Thread(target=server.serve_forever) - server_thread.daemon = True - server_thread.start() - - try: - adapter = RetryRequestExceptionsAdapter(base_num_retries=5, backoff_factor=0.01) - session = requests.Session() - session.mount("http://", adapter) - - errors = [] - success_count = 0 - lock = threading.Lock() - - def make_request(i): - nonlocal success_count - try: - time.sleep(i * 0.005) # Stagger requests - resp = session.get(f"{url}/test{i}") - if resp.status_code == 200: - with lock: - success_count += 1 - return resp.status_code - except Exception as e: - with lock: - errors.append(str(e)) - return None - - def close_repeatedly(): - for _ in range(20): - time.sleep(0.01) # Close throughout the request window - adapter.close() - - # Launch many concurrent requests while repeatedly closing - with concurrent.futures.ThreadPoolExecutor(max_workers=20) as executor: - request_futures = [executor.submit(make_request, i) for i in range(50)] - close_futures = [executor.submit(close_repeatedly) for _ in range(3)] - - # Wait for all - for f in close_futures: - f.result() - results = [f.result() for f in request_futures] - - failed = [r for r in results if r != 200] - assert len(failed) == 0, f"Failed requests: {len(failed)}, errors: {errors[:5]}" - - finally: - server.shutdown() - server.server_close() diff --git a/py/src/braintrust/test_id_gen.py b/py/src/braintrust/test_id_gen.py deleted file mode 100644 index b5633979f..000000000 --- a/py/src/braintrust/test_id_gen.py +++ /dev/null @@ -1,81 +0,0 @@ -import os -import uuid - -import pytest -from braintrust import id_gen - - -@pytest.fixture(autouse=True) -def reset_id_generator_state(): - """Reset ID generator state and environment variables before each test""" - original_env = os.getenv("BRAINTRUST_OTEL_COMPAT") - - try: - yield - finally: - os.environ.pop("BRAINTRUST_OTEL_COMPAT", None) - if original_env: - os.environ["BRAINTRUST_OTEL_COMPAT"] = original_env - - -def test_uuid_generator(): - """Test that UUIDGenerator implements IDGenerator interface and generates valid UUIDs""" - # Test interface implementation - generator = id_gen.UUIDGenerator() - - # Test that UUID generators should share root_span_id for backwards compatibility - assert generator.share_root_span_id() == True - - for gen_func in [generator.get_span_id, generator.get_trace_id]: - ids = gen_func(), gen_func() - assert ids[0] != ids[1] - assert all(isinstance(id_val, str) for id_val in ids) - assert all(uuid.UUID(id_val) for id_val in ids) - - -def test_otel_id_generator(): - generator = id_gen.OTELIDGenerator() - - # Test that OTEL generators should not share root_span_id - assert generator.share_root_span_id() == False - - # Test ID generation with regular loops - test_cases = [ - (generator.get_span_id, 16), - (generator.get_trace_id, 32), - ] - for gen_func, expected_length in test_cases: - id1 = gen_func() - id2 = gen_func() - # Test uniqueness, type, length, and hex format - assert id1 != id2 - assert len(id1) == len(id2) == expected_length - assert _is_hex(id1) - assert _is_hex(id2) - - -def test_id_get_env_var(reset_id_generator_state): - cases = [ - (None, lambda _id: uuid.UUID(_id)), - ("true", lambda _id: _assert_is_hex(_id)), - ("True", lambda _id: _assert_is_hex(_id)), - ("TRUE", lambda _id: _assert_is_hex(_id)), - ("false", lambda _id: uuid.UUID(_id)), - ("False", lambda _id: uuid.UUID(_id)), - ] - - for env_var_value, assert_func in cases: - os.environ.pop("BRAINTRUST_OTEL_COMPAT", None) - if env_var_value is not None: - os.environ["BRAINTRUST_OTEL_COMPAT"] = env_var_value - generator = id_gen.get_id_generator() - assert_func(generator.get_span_id()) - assert_func(generator.get_trace_id()) - - -def _is_hex(s): - return all(c in "0123456789abcdef" for c in s.lower()) - - -def _assert_is_hex(x): - assert _is_hex(x) diff --git a/py/src/braintrust/test_logger.py b/py/src/braintrust/test_logger.py deleted file mode 100644 index 66d45068e..000000000 --- a/py/src/braintrust/test_logger.py +++ /dev/null @@ -1,3284 +0,0 @@ -# pyright: reportUnknownVariableType=false -# pyright: reportPrivateUsage=false -import asyncio -import json -import logging -import os -import time -from typing import AsyncGenerator, List -from unittest import TestCase -from unittest.mock import MagicMock, patch - -import braintrust -import pytest -from braintrust import ( - Attachment, - BaseAttachment, - ExternalAttachment, - JSONAttachment, - LazyValue, - Prompt, - init_logger, - logger, -) -from braintrust.id_gen import OTELIDGenerator, get_id_generator -from braintrust.logger import ( - _extract_attachments, - parent_context, - render_message, - render_mustache, -) -from braintrust.prompt import PromptChatBlock, PromptData, PromptMessage, PromptSchema -from braintrust.test_helpers import ( - assert_dict_matches, - assert_logged_out, - init_test_exp, - init_test_logger, - preserve_env_vars, - simulate_login, # noqa: F401 # type: ignore[reportUnusedImport] - simulate_logout, - with_memory_logger, # noqa: F401 # type: ignore[reportUnusedImport] - with_simulate_login, # noqa: F401 # type: ignore[reportUnusedImport] -) - - -class TestInit(TestCase): - def test_init_validation(self): - with self.assertRaises(ValueError) as cm: - braintrust.init() - - assert str(cm.exception) == "Must specify at least one of project or project_id" - - with self.assertRaises(ValueError) as cm: - braintrust.init(project="project", open=True, update=True) - - assert str(cm.exception) == "Cannot open and update an experiment at the same time" - - with self.assertRaises(ValueError) as cm: - braintrust.init(project="project", open=True) - - assert str(cm.exception) == "Cannot open an experiment without specifying its name" - - def test_init_with_dataset_id_only(self): - """Test that init accepts dataset={'id': '...'} parameter""" - # Test the logic that extracts dataset_id from the dict - from braintrust.logger import Dataset - - # Test 1: dict with only id - dataset_dict = {"id": "dataset-id-123"} - assert isinstance(dataset_dict, dict) - assert not isinstance(dataset_dict, Dataset) - assert dataset_dict["id"] == "dataset-id-123" - - # Test 2: full Dataset object has different behavior - # (We can't easily instantiate a Dataset here, but we can verify - # that the isinstance check distinguishes them) - - def test_init_with_dataset_id_and_version(self): - """Test that init accepts dataset={'id': '...', 'version': '...'} parameter""" - # Test the logic that extracts both dataset_id and dataset_version from the dict - from braintrust.logger import Dataset - - # Test: dict with id and version - dataset_dict = {"id": "dataset-id-123", "version": "v2"} - assert isinstance(dataset_dict, dict) - assert not isinstance(dataset_dict, Dataset) - assert dataset_dict["id"] == "dataset-id-123" - assert dataset_dict["version"] == "v2" - - -class TestLogger(TestCase): - def test_extract_attachments_no_op(self): - attachments: List[BaseAttachment] = [] - - _extract_attachments({}, attachments) - self.assertEqual(len(attachments), 0) - - event = {"foo": "foo", "bar": None, "baz": [1, 2, 3]} - _extract_attachments(event, attachments) - self.assertEqual(len(attachments), 0) - # Same instance - self.assertIs(event["baz"], event["baz"]) - # Same content - self.assertEqual(event, {"foo": "foo", "bar": None, "baz": [1, 2, 3]}) - - def test_extract_attachments_with_attachments(self): - attachment1 = Attachment( - data=b"data", - filename="filename", - content_type="text/plain", - ) - attachment2 = Attachment( - data=b"data2", - filename="filename2", - content_type="text/plain", - ) - attachment3 = ExternalAttachment( - url="s3://bucket/path/to/key.pdf", - filename="filename3", - content_type="application/pdf", - ) - date = "2024-10-23T05:02:48.796Z" - event = { - "foo": "bar", - "baz": [1, 2], - "attachment1": attachment1, - "attachment3": attachment3, - "nested": { - "attachment2": attachment2, - "attachment3": attachment3, - "info": "another string", - "anArray": [ - attachment1, - None, - "string", - attachment2, - attachment1, - attachment3, - attachment3, - ], - }, - "null": None, - "undefined": None, - "date": date, - "f": "Math.max", - "empty": {}, - } - saved_nested = event["nested"] - - attachments: List[BaseAttachment] = [] - _extract_attachments(event, attachments) - - self.assertEqual( - attachments, - [ - attachment1, - attachment3, - attachment2, - attachment3, - attachment1, - attachment2, - attachment1, - attachment3, - attachment3, - ], - ) - self.assertIs(attachments[0], attachment1) - self.assertIs(attachments[1], attachment3) - self.assertIs(attachments[2], attachment2) - self.assertIs(attachments[3], attachment3) - self.assertIs(attachments[4], attachment1) - self.assertIs(attachments[5], attachment2) - self.assertIs(attachments[6], attachment1) - self.assertIs(attachments[7], attachment3) - self.assertIs(attachments[8], attachment3) - - self.assertIs(event["nested"], saved_nested) - - self.assertEqual( - event, - { - "foo": "bar", - "baz": [1, 2], - "attachment1": attachment1.reference, - "attachment3": attachment3.reference, - "nested": { - "attachment2": attachment2.reference, - "attachment3": attachment3.reference, - "info": "another string", - "anArray": [ - attachment1.reference, - None, - "string", - attachment2.reference, - attachment1.reference, - attachment3.reference, - attachment3.reference, - ], - }, - "null": None, - "undefined": None, - "date": date, - "f": "Math.max", - "empty": {}, - }, - ) - - - - def test_prompt_build_with_structured_output_templating(self): - self.maxDiff = None - prompt = Prompt( - LazyValue( - lambda: PromptSchema( - id="id", - project_id="project_id", - _xact_id="_xact_id", - name="name", - slug="slug", - description="description", - prompt_data=PromptData( - prompt=PromptChatBlock( - messages=[ - PromptMessage( - role="system", - content="Please compute {{input.expression}} and return the result in JSON.", - ), - ], - ), - options={ - "model": "gpt-4o", - "params": { - "response_format": { - "type": "json_schema", - "json_schema": { - "name": "schema", - "schema": "{{input.schema}}", - "strict": True, - }, - }, - }, - }, - ), - tags=None, - ), - use_mutex=True, - ), - {}, - False, - ) - - result = prompt.build( - **{ - "input": { - "expression": "2 + 3", - "schema": { - "type": "object", - "properties": { - "final_answer": { - "type": "string", - }, - }, - "required": ["final_answer"], - "additionalProperties": False, - }, - }, - } - ) - - self.assertEqual( - result["response_format"], - { - "type": "json_schema", - "json_schema": { - "name": "schema", - "schema": { - "type": "object", - "properties": { - "final_answer": {"type": "string"}, - }, - "required": ["final_answer"], - "additionalProperties": False, - }, - "strict": True, - }, - }, - ) - - def test_lint_template_valid_variables(self): - """Test lint_template passes with all variables present.""" - - template = "Hello {{name}}, you are {{age}} years old" - args = {"name": "John", "age": 30} - - # Should not raise any exception - try: - render_mustache(template, args, strict=True) - except ValueError: - self.fail("lint_template raised ValueError unexpectedly") - - def test_lint_template_missing_variable(self): - template = "Hello {{name}}, you are {{age}} years old" - args = {"name": "John"} # Missing 'age' - - with self.assertRaises(ValueError) as context: - render_mustache(template, args, strict=True) - - self.assertIn("Template rendering failed: Could not find key 'age'", str(context.exception)) - - def test_prompt_build_strict_mode_enabled(self): - """Test Prompt.build with strict mode enabled validates variables.""" - from braintrust.prompt import PromptChatBlock, PromptData, PromptMessage, PromptSchema - - # Create prompt using the proper structure - prompt_schema = PromptSchema( - id="test-id", - project_id="test-project", - _xact_id="test-xact", - name="test-prompt", - slug="test-prompt", - description="test", - prompt_data=PromptData( - prompt=PromptChatBlock( - messages=[PromptMessage(role="user", content="Hello {{name}}, please help with {{task}}")] - ), - options={"model": "gpt-4o"}, - ), - tags=None, - ) - lazy_prompt = LazyValue(lambda: prompt_schema, use_mutex=False) - prompt = Prompt(lazy_prompt, {}, False) - - # Valid build with all variables - result = prompt.build(name="John", task="coding", strict=True) - self.assertEqual(result["messages"][0]["content"], "Hello John, please help with coding") - - # Invalid build missing variables should raise ValueError - with self.assertRaises(ValueError) as context: - prompt.build(name="John", strict=True) # Missing 'task' - - self.assertIn("Template rendering failed: Could not find key 'task'", str(context.exception)) - - def test_prompt_build_strict_mode_disabled(self): - """Test Prompt.build with strict mode disabled allows missing variables.""" - from braintrust.prompt import PromptChatBlock, PromptData, PromptMessage, PromptSchema - - prompt_schema = PromptSchema( - id="test-id", - project_id="test-project", - _xact_id="test-xact", - name="test-prompt", - slug="test-prompt", - description="test", - prompt_data=PromptData( - prompt=PromptChatBlock( - messages=[PromptMessage(role="user", content="Hello {{name}}, please help with {{task}}")] - ), - options={"model": "gpt-4o"}, - ), - tags=None, - ) - lazy_prompt = LazyValue(lambda: prompt_schema, use_mutex=False) - prompt = Prompt(lazy_prompt, {}, False) - - # Should work even with missing variables when strict=False (default) - result = prompt.build(name="John") - # Missing variables render as empty strings in chevron - self.assertEqual(result["messages"][0]["content"], "Hello John, please help with ") - - def _create_test_prompt(self, content: str): - """Helper to create a test prompt with the proper structure.""" - from braintrust.prompt import PromptChatBlock, PromptData, PromptMessage, PromptSchema - - prompt_schema = PromptSchema( - id="test-id", - project_id="test-project", - _xact_id="test-xact", - name="test-prompt", - slug="test-prompt", - description="test", - prompt_data=PromptData( - prompt=PromptChatBlock(messages=[PromptMessage(role="user", content=content)]), - options={"model": "gpt-4o"}, - ), - tags=None, - ) - lazy_prompt = LazyValue(lambda: prompt_schema, use_mutex=False) - return Prompt(lazy_prompt, {}, False) - - def test_prompt_build_nested_variables_strict(self): - """Test Prompt.build with nested object variables in strict mode.""" - prompt = self._create_test_prompt("User {{user.name}} with email {{user.profile.email}}") - - # Valid nested data - user_data = {"user": {"name": "John", "profile": {"email": "john@example.com"}}} - result = prompt.build(strict=True, **user_data) - expected = "User John with email john@example.com" - self.assertEqual(result["messages"][0]["content"], expected) - - # Missing nested property should fail in strict mode - invalid_data = {"user": {"name": "John"}} # Missing profile.email - with self.assertRaises(ValueError): - prompt.build(strict=True, **invalid_data) - - def test_prompt_build_array_variables_strict(self): - """Test Prompt.build with array variables in strict mode.""" - prompt = self._create_test_prompt("Items: {{items.0}}, {{items.1}}") - - # Valid array with enough items - result = prompt.build(items=["first", "second", "third"], strict=True) - self.assertEqual(result["messages"][0]["content"], "Items: first, second") - - # Array too short should fail in strict mode - with self.assertRaises(ValueError): - prompt.build(items=["only_one"], strict=True) - - def test_render_message_with_file_content_parts(self): - """Test render_message with mixed text, image, and file content parts including all file fields.""" - message = PromptMessage( - role="user", - content=[ - {"type": "text", "text": "Here is a {{item}}:"}, - {"type": "image_url", "image_url": {"url": "{{image_url}}"}}, - { - "type": "file", - "file": { - "file_data": "{{file_data}}", - "file_id": "{{file_id}}", - "filename": "{{filename}}", - }, - }, - ], - ) - - rendered = render_message( - lambda template: template.replace("{{item}}", "document") - .replace("{{image_url}}", "https://example.com/image.png") - .replace("{{file_data}}", "base64data") - .replace("{{file_id}}", "file-456") - .replace("{{filename}}", "report.pdf"), - message, - ) - - assert rendered["content"] == [ - {"type": "text", "text": "Here is a document:"}, - {"type": "image_url", "image_url": {"url": "https://example.com/image.png"}}, - { - "type": "file", - "file": { - "file_data": "base64data", - "file_id": "file-456", - "filename": "report.pdf", - }, - }, - ] - - -def test_noop_permalink_issue_1837(): - # fixes issue #BRA-1837 - span = braintrust.NOOP_SPAN - assert span.permalink() == "https://www.braintrust.dev/noop-span" - - link = braintrust.permalink(span.export()) - assert link == "https://www.braintrust.dev/noop-span" - - assert span.link() == "https://www.braintrust.dev/noop-span" - - -def test_span_log_with_simple_circular_reference(with_memory_logger): - """Test that span.log() with simple circular reference works gracefully.""" - logger = init_test_logger(__name__) - - with logger.start_span(name="test_span") as span: - # Create simple circular reference - data = {"key": "value"} - data["self"] = data - - # Should handle circular reference gracefully - span.log( - input={"test": "simple circular ref"}, - output=data, - ) - - # Verify the log was recorded with circular reference replaced by placeholder - logs = with_memory_logger.pop() - assert len(logs) == 1 - - logged_output = logs[0]["output"] - assert logged_output["key"] == "value" - # Circular reference should be replaced with a placeholder string - assert isinstance(logged_output["self"], str) - assert "circular" in logged_output["self"].lower() - - -def test_span_log_with_nested_circular_reference(with_memory_logger): - """Test that span.log() with nested circular reference works gracefully.""" - logger = init_test_logger(__name__) - - with logger.start_span(name="test_span") as span: - # Create nested structure with circular reference - page = {"page_number": 1, "content": "text"} - document = {"pages": [page]} - page["document"] = document - - # Should handle circular reference gracefully - span.log( - input={"file": "test.pdf"}, - output=document, - ) - - # Verify the log was recorded with nested circular reference handled - logs = with_memory_logger.pop() - assert len(logs) == 1 - - logged_output = logs[0]["output"] - assert len(logged_output["pages"]) == 1 - assert logged_output["pages"][0]["page_number"] == 1 - assert logged_output["pages"][0]["content"] == "text" - # Circular reference should be replaced with a placeholder - assert isinstance(logged_output["pages"][0]["document"], str) - assert "circular" in logged_output["pages"][0]["document"].lower() - - -def test_span_log_with_deep_document_structure(with_memory_logger): - """Test that span.log() with deeply nested document structure works gracefully.""" - logger = init_test_logger(__name__) - - with logger.start_span(name="test_span") as span: - # Create deeply nested document structure with circular reference - doc_data = { - "model_id": "document-model", - "content": "Document content", - "pages": [], - } - - page = { - "page_number": 1, - "lines": [{"content": "Line 1"}], - } - - # Create circular reference - page["document"] = doc_data - doc_data["pages"].append(page) - - # Should handle circular reference gracefully - span.log( - input={"file": "test.pdf"}, - output=doc_data, - metadata={"source": "document_processor"}, - ) - - # Verify the log was recorded with proper structure - logs = with_memory_logger.pop() - assert len(logs) == 1 - - logged_output = logs[0]["output"] - assert logged_output["model_id"] == "document-model" - assert logged_output["content"] == "Document content" - assert len(logged_output["pages"]) == 1 - assert logged_output["pages"][0]["page_number"] == 1 - assert len(logged_output["pages"][0]["lines"]) == 1 - assert logged_output["pages"][0]["lines"][0]["content"] == "Line 1" - # Circular reference should be replaced with placeholder - assert isinstance(logged_output["pages"][0]["document"], str) - assert "circular" in logged_output["pages"][0]["document"].lower() - - -def test_span_log_with_extremely_deep_nesting(with_memory_logger): - """Test that span.log() with extremely deep nesting works gracefully.""" - import sys - - logger = init_test_logger(__name__) - - with logger.start_span(name="test_span") as span: - recursion_limit = sys.getrecursionlimit() - - # Create structure deeper than recursion limit - deeply_nested = {"level": 0} - current = deeply_nested - for i in range(1, recursion_limit + 100): - current["nested"] = {"level": i} - current = current["nested"] - - # Should handle extremely deep nesting without RecursionError - span.log( - input={"test": "deep nesting"}, - output=deeply_nested, - ) - - # Verify the log was recorded (may be truncated or have placeholder for deep nesting) - logs = with_memory_logger.pop() - assert len(logs) == 1 - - logged_output = logs[0]["output"] - assert logged_output["level"] == 0 - # Either the structure is preserved up to a safe depth, or replaced with placeholder - assert "nested" in logged_output - - -def test_span_log_with_large_document_many_pages(with_memory_logger): - """Test that span.log() with large multi-page document works gracefully.""" - logger = init_test_logger(__name__) - - with logger.start_span(name="test_span") as span: - # Create realistic large document: 20 pages ร— 30 lines ร— 10 words - pages = [] - for page_num in range(20): - lines = [] - for line_num in range(30): - words = [] - for word_num in range(10): - words.append( - { - "content": f"word_{word_num}", - "confidence": 0.98, - } - ) - lines.append( - { - "content": f"line_{line_num}", - "words": words, - } - ) - pages.append( - { - "page_number": page_num + 1, - "lines": lines, - } - ) - - # Should handle large document structure - span.log( - input={"file": "large_document.pdf"}, - output={"pages": pages}, - ) - - # Verify the log was recorded with full structure intact (no circular refs) - logs = with_memory_logger.pop() - assert len(logs) == 1 - - logged_output = logs[0]["output"] - assert len(logged_output["pages"]) == 20 - assert len(logged_output["pages"][0]["lines"]) == 30 - assert len(logged_output["pages"][0]["lines"][0]["words"]) == 10 - assert logged_output["pages"][0]["lines"][0]["words"][0]["content"] == "word_0" - - -def test_span_log_handles_nan_gracefully(with_memory_logger): - """Test that span.log() handles NaN values by converting them to "NaN" string.""" - logger = init_test_logger(__name__) - - with logger.start_span(name="test_span") as span: - # Should NOT raise - should handle NaN gracefully - span.log( - input={"test": "input"}, - output={"value": float("nan")}, - ) - - # Verify the log was recorded with NaN handled appropriately - logs = with_memory_logger.pop() - assert len(logs) == 1 - assert logs[0]["input"]["test"] == "input" - # NaN should be converted to "NaN" string for JSON compatibility - output_value = logs[0]["output"]["value"] - assert output_value == "NaN" - - -def test_span_log_handles_infinity_gracefully(with_memory_logger): - """Test that span.log() handles Infinity values by converting them to "Infinity"/"-Infinity" strings.""" - logger = init_test_logger(__name__) - - with logger.start_span(name="test_span") as span: - # Should NOT raise - should handle Infinity gracefully - span.log( - input={"test": "input"}, - output={"value": float("inf"), "neg": float("-inf")}, - ) - - # Verify the log was recorded with Infinity handled appropriately - logs = with_memory_logger.pop() - assert len(logs) == 1 - assert logs[0]["input"]["test"] == "input" - # Infinity should be converted to string representations for JSON compatibility - assert logs[0]["output"]["value"] == "Infinity" - assert logs[0]["output"]["neg"] == "-Infinity" - - -def test_span_log_with_binary_data(with_memory_logger): - """Test how span.log() currently handles binary data.""" - logger = init_test_logger(__name__) - - with logger.start_span(name="test_span") as span: - span.log( - input={"file": "image.png"}, - output={"embedding": b"\x00\x01\x02\x03" * 100}, - ) - - logs = with_memory_logger.pop() - assert len(logs) == 1 - # Document actual behavior - binary data goes through deep_copy_and_sanitize_dict - # which uses bt_dumps/bt_loads roundtrip - assert logs[0]["input"]["file"] == "image.png" - # The embedding should be present (converted to some serializable form) - assert "embedding" in logs[0]["output"] - - -def test_span_log_handles_unstringifiable_object_gracefully(with_memory_logger): - """Test that span.log() should handle objects with bad __str__ gracefully without raising. - - This test currently FAILS - it demonstrates the desired behavior after the fix. - """ - logger = init_test_logger(__name__) - - class BadStrObject: - def __str__(self): - raise RuntimeError("Cannot convert to string!") - - def __repr__(self): - raise RuntimeError("Cannot convert to repr!") - - with logger.start_span(name="test_span") as span: - # Should NOT raise - should handle gracefully - span.log( - input={"test": "input"}, - output={"result": BadStrObject()}, - ) - - # Verify the log was recorded with a fallback representation - logs = with_memory_logger.pop() - assert len(logs) == 1 - assert logs[0]["input"]["test"] == "input" - # The bad object should have been replaced with some error placeholder - assert "result" in logs[0]["output"] - output_str = str(logs[0]["output"]["result"]) - # Should contain some indication of serialization failure - assert "error" in output_str.lower() or "serializ" in output_str.lower() - - -def test_span_log_handles_bad_dict_keys_gracefully(with_memory_logger): - """Test that span.log() should handle non-stringifiable dict keys gracefully. - - This test currently FAILS - it demonstrates the desired behavior after the fix. - """ - logger = init_test_logger(__name__) - - class BadKey: - def __str__(self): - raise ValueError("Key cannot be stringified!") - - def __repr__(self): - raise ValueError("Key cannot be stringified!") - - with logger.start_span(name="test_span") as span: - # Should NOT raise - should handle gracefully - span.log( - input={"test": "input"}, - output={BadKey(): "value"}, - ) - - # Verify the log was recorded with the problematic key handled - logs = with_memory_logger.pop() - assert len(logs) == 1 - assert logs[0]["input"]["test"] == "input" - # The output should exist but the bad key should be replaced - assert "output" in logs[0] - - -def test_span_link_logged_out(with_memory_logger): - simulate_logout() - assert_logged_out() - logger = init_logger( - project="test-project", - project_id="test-project-id", - ) - span = logger.start_span(name="test-span") - span.end() - link = span.link() - assert link == "https://www.braintrust.dev/error-generating-link?msg=login-or-provide-org-name" - - -def test_span_link_logged_out_org_name(with_memory_logger): - simulate_logout() - assert_logged_out() - logger = init_logger( - project_id="test-project-id", - org_name="test-org-name", - ) - span = logger.start_span(name="test-span") - span.end() - link = span.link() - assert ( - link - == f"https://www.braintrust.dev/app/test-org-name/object?object_type=project_logs&object_id=test-project-id&id={span._id}" - ) - - -def test_span_link_logged_out_org_name_env_vars(with_memory_logger): - simulate_logout() - assert_logged_out() - keys = ["BRAINTRUST_APP_URL", "BRAINTRUST_ORG_NAME"] - originals = {k: os.environ.get(k) for k in keys} - try: - os.environ["BRAINTRUST_APP_URL"] = "https://my-own-thing.ca/foo/bar" - os.environ["BRAINTRUST_ORG_NAME"] = "my-own-thing" - - logger = init_logger(project_id="test-project-id") - span = logger.start_span(name="test-span") - span.end() - link = span.link() - assert ( - link - == f"https://my-own-thing.ca/foo/bar/app/my-own-thing/object?object_type=project_logs&object_id=test-project-id&id={span._id}" - ) - finally: - for k, v in originals.items(): - os.environ.pop(k, None) - if v: - os.environ[k] = v - - -def test_span_project_id_logged_in(with_memory_logger, with_simulate_login): - logger = init_logger( - project="test-project", - project_id="test-project-id", - ) - - span = logger.start_span(name="test-span") - span.end() - - link = span.link() - assert ( - link - == f"https://www.braintrust.dev/app/test-org-name/object?object_type=project_logs&object_id=test-project-id&id={span._id}" - ) - - -def test_span_export_disables_cache(with_memory_logger): - """Test that span.export() disables the span cache.""" - logger = init_test_logger(__name__) - - with logger.start_span(name="test_span") as span: - # Exporting should disable the span cache - span.export() - assert logger.state.span_cache.disabled - - -def test_span_project_name_logged_in(with_simulate_login, with_memory_logger): - init_logger(project="test-project") - span = logger.start_span(name="test-span") - span.end() - - link = span.link() - assert link == f"https://www.braintrust.dev/app/test-org-name/p/test-project/logs?oid={span._id}" - - -def test_span_link_with_resolved_experiment(with_simulate_login, with_memory_logger): - experiment = braintrust.init( - project="test-project", - experiment="test-experiment", - ) - - id_lazy_value = LazyValue(lambda: "test-experiment-id", use_mutex=False) - eid = id_lazy_value.get() - assert eid == "test-experiment-id" - - span = experiment.start_span(name="test-span") - span.parent_object_id = id_lazy_value - span.end() - - link = span.link() - assert ( - link - == f"https://www.braintrust.dev/app/test-org-name/object?object_type=experiment&object_id=test-experiment-id&id={span._id}" - ) - - -def test_span_link_with_unresolved_experiment(with_simulate_login, with_memory_logger): - experiment = braintrust.init( - project="test-project", - experiment="test-experiment", - ) - - span = experiment.start_span(name="test-span") - span.end() - - link = span.link() - assert link == "https://www.braintrust.dev/error-generating-link?msg=resolve-experiment-id" - - -def test_experiment_span_link_uses_env_vars_when_logged_out(with_memory_logger): - """Verify EXPERIMENT spans use BRAINTRUST_ORG_NAME env var when not logged in.""" - simulate_logout() - assert_logged_out() - - keys = ["BRAINTRUST_APP_URL", "BRAINTRUST_ORG_NAME"] - originals = {k: os.environ.get(k) for k in keys} - try: - os.environ["BRAINTRUST_APP_URL"] = "https://test-app.example.com" - os.environ["BRAINTRUST_ORG_NAME"] = "env-org-name" - - experiment = braintrust.init( - project="test-project", - experiment="test-experiment", - ) - - # Create span with resolved experiment ID - span = experiment.start_span(name="test-span") - span.parent_object_id = LazyValue(lambda: "test-exp-id", use_mutex=False) - span.end() - - link = span.link() - - # Should use env var org name and app url - assert "env-org-name" in link - assert "test-app.example.com" in link - assert "test-exp-id" in link - finally: - for k, v in originals.items(): - os.environ.pop(k, None) - if v: - os.environ[k] = v - - -def test_permalink_with_valid_span_logged_in(with_simulate_login, with_memory_logger): - logger = init_logger( - project="test-project", - project_id="test-project-id", - ) - - span = logger.start_span(name="test-span") - span.end() - - span_export = span.export() - - link = braintrust.permalink(span_export, org_name="test-org-name", app_url="https://www.braintrust.dev") - - expected_link = f"https://www.braintrust.dev/app/test-org-name/object?object_type=project_logs&object_id=test-project-id&id={span._id}" - assert link == expected_link - - -@pytest.mark.asyncio -async def test_span_link_in_async_context(with_simulate_login, with_memory_logger): - """Test that span.link() works correctly when called from within an async function.""" - import asyncio - - logger = init_logger( - project="test-project", - project_id="test-project-id", - ) - - # Create a span in the main context - span = logger.start_span(name="test-span") - # Make it the current span so current_span() returns it - span.set_current() - - # Define an async function that calls span.link() - async def get_link_in_async(): - # Simulate some async work - await asyncio.sleep(0.01) - # This should return a valid link, not the noop link - return braintrust.current_span().link() - - # Call the async function - link = await get_link_in_async() - - span.end() - - # The link should NOT be the noop link - assert link != "https://www.braintrust.dev/noop-span" - # The link should contain the span ID - assert span._id in link - # The link should contain the project ID - assert "test-project-id" in link - - -@pytest.mark.asyncio -async def test_current_logger_after_multiple_awaits(with_simulate_login, with_memory_logger): - """Test that current_logger() works after multiple await points.""" - import asyncio - - logger = init_logger(project="test-project", project_id="test-project-id") - - async def check_logger_after_awaits(): - assert braintrust.current_logger() is logger - await asyncio.sleep(0.01) - assert braintrust.current_logger() is logger - await asyncio.sleep(0.01) - assert braintrust.current_logger() is logger - return braintrust.current_logger() - - result = await check_logger_after_awaits() - assert result is logger - - -@pytest.mark.asyncio -async def test_current_logger_in_async_generator(with_simulate_login, with_memory_logger): - """Test that current_logger() works within an async generator (yield).""" - import asyncio - - logger = init_logger(project="test-project", project_id="test-project-id") - - async def logger_generator(): - for i in range(3): - await asyncio.sleep(0.01) - yield braintrust.current_logger() - - results = [] - async for log in logger_generator(): - results.append(log) - - assert len(results) == 3 - assert all(r is logger for r in results) - - -@pytest.mark.asyncio -async def test_current_logger_in_separate_task(with_simulate_login, with_memory_logger): - """Test that current_logger() works in a separately created asyncio task.""" - import asyncio - - logger = init_logger(project="test-project", project_id="test-project-id") - - async def get_logger_in_task(): - await asyncio.sleep(0.01) - return braintrust.current_logger() - - # Create a separate task - task = asyncio.create_task(get_logger_in_task()) - result = await task - - assert result is logger - - -@pytest.mark.asyncio -async def test_span_link_in_nested_async(with_simulate_login, with_memory_logger): - """Test that span.link() works in deeply nested async calls.""" - import asyncio - - logger = init_logger(project="test-project", project_id="test-project-id") - span = logger.start_span(name="test-span") - - async def level3(): - await asyncio.sleep(0.01) - return span.link() - - async def level2(): - await asyncio.sleep(0.01) - return await level3() - - async def level1(): - await asyncio.sleep(0.01) - return await level2() - - link = await level1() - span.end() - - assert link != "https://www.braintrust.dev/noop-span" - assert span._id in link - - -def test_current_logger_in_thread(with_simulate_login, with_memory_logger): - """Test that current_logger() works correctly when called from a new thread. - - Regression test: ContextVar values don't propagate to new threads, - so current_logger must be a plain attribute for thread access. - """ - import threading - - logger = init_logger(project="test-project", project_id="test-project-id") - assert braintrust.current_logger() is logger - - thread_result = {} - - def check_logger_in_thread(): - thread_result["logger"] = braintrust.current_logger() - - thread = threading.Thread(target=check_logger_in_thread) - thread.start() - thread.join() - - assert thread_result["logger"] is logger - - -def test_span_link_in_thread(with_simulate_login, with_memory_logger): - """Test that span.link() works correctly when called from a new thread. - - The span should be able to generate a valid link even when link() is called - from a different thread than where the span was created. - """ - import threading - - logger = init_logger(project="test-project", project_id="test-project-id") - span = logger.start_span(name="test-span") - - thread_result = {} - - def get_link_in_thread(): - # Call link() on the span directly (not via current_span() which uses ContextVar) - thread_result["link"] = span.link() - - thread = threading.Thread(target=get_link_in_thread) - thread.start() - thread.join() - span.end() - - # The link should NOT be the noop link - assert thread_result["link"] != "https://www.braintrust.dev/noop-span" - # The link should contain the span ID - assert span._id in thread_result["link"] - - -@pytest.mark.asyncio -async def test_current_logger_async_context_isolation(with_simulate_login, with_memory_logger): - """Test that different async contexts can have different loggers. - - When a child task sets its own logger, it should not affect the parent context. - This ensures async context isolation via ContextVar. - """ - import asyncio - - parent_logger = init_logger(project="parent-project", project_id="parent-project-id") - assert braintrust.current_logger() is parent_logger - - child_result = {} - - async def child_task(): - # Child initially inherits parent's logger - assert braintrust.current_logger() is parent_logger - - # Child sets its own logger - child_logger = init_logger(project="child-project", project_id="child-project-id") - child_result["logger"] = braintrust.current_logger() - return child_logger - - # Run child task - child_logger = await asyncio.create_task(child_task()) - - # Child should have seen its own logger - assert child_result["logger"] is child_logger - - # Parent should still see parent logger (not affected by child) - assert braintrust.current_logger() is parent_logger - - -def test_span_set_current(with_memory_logger): - """Test that span.set_current() makes the span accessible via current_span().""" - init_test_logger(__name__) - - # Store initial current span - initial_current = braintrust.current_span() - - # Start a span that can be set as current (default behavior) - span1 = logger.start_span(name="test-span-1") - - # Initially, it should not be the current span - assert braintrust.current_span() != span1 - - # Call set_current() on the span - span1.set_current() - - # Verify it's now the current span - assert braintrust.current_span() == span1 - - # Test that spans with set_current=False cannot be set as current - span2 = logger.start_span(name="test-span-2", set_current=False) - span2.set_current() # This should not change the current span - - # Current span should still be span1 - assert braintrust.current_span() == span1 - - span1.end() - span2.end() - - -@pytest.mark.asyncio -async def test_traced_async_generator_with_exception(with_memory_logger): - """Test tracing when async generator raises an exception.""" - init_test_logger(__name__) - - @logger.traced - async def failing_async_generator() -> AsyncGenerator[int, None]: - """An async generator that fails.""" - yield 1 - yield 2 - raise ValueError("Something went wrong") - - results = [] - start_time = time.time() - with pytest.raises(ValueError, match="Something went wrong"): - async for value in failing_async_generator(): - results.append(value) - end_time = time.time() - - assert results == [1, 2] # Should have yielded these before failing - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - assert_dict_matches( - log, - { - "metrics": { - "start": lambda x: start_time <= x <= end_time, - "end": lambda x: start_time <= x <= end_time, - }, - "error": lambda e: "ValueError" in str(e), - }, - ) - - -@pytest.mark.asyncio -async def test_traced_async_generator_with_subtasks(with_memory_logger): - """ - Test async generator with current_span().log() calls - similar to user's failing case. - Set notrace_io so we do not automatically log output and clobber the manually logged - output "testing" - """ - - init_test_logger(__name__) - - num_loops = 3 - - @logger.traced(notrace_io=True) - async def foo(i: int) -> int: - """Simulate some async work.""" - await asyncio.sleep(0.001) # Small delay to simulate work - return i * 2 - - @logger.traced("main", notrace_io=True) - async def main(): - yield 1 - logger.current_span().log(metadata={"a": "b"}) - tasks = [asyncio.create_task(foo(i)) for i in range(num_loops)] - done, _ = await asyncio.wait(tasks, return_when=asyncio.ALL_COMPLETED) - total = sum(task.result() for task in done) - logger.current_span().log(metadata=dict(total=total), output="testing") - yield total - - # consume the generator - results: list[int] = [] - start_time = time.time() - async for value in main(): - results.append(value) - end_time = time.time() - - assert results == [1, 6] - - # Check logs - logs = with_memory_logger.pop() - assert len(logs) == num_loops + 1 - - # Find the main span - main_spans = [l for l in logs if l["span_attributes"]["name"] == "main"] - assert len(main_spans) == 1 - main_span = main_spans[0] - - assert_dict_matches( - main_span, - { - # no input because notrace_io - "output": "testing", - "metadata": {"a": "b", "total": 6}, # Manual metadata logging - "metrics": { - "start": lambda x: start_time <= x <= end_time, - "end": lambda x: start_time <= x <= end_time, - }, - }, - ) - - -@pytest.mark.asyncio -async def test_traced_async_function(with_memory_logger): - """Test tracing async functions.""" - init_test_logger(__name__) - - @logger.traced - async def async_multiply(x: int, y: int) -> int: - """An async function that multiplies two numbers.""" - await asyncio.sleep(0.001) # Small delay to simulate async work - result = x * y - logger.current_span().log(metadata={"operation": "multiply"}) - return result - - start_time = time.time() - result = await async_multiply(3, 4) - end_time = time.time() - - assert result == 12 - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - assert_dict_matches( - log, - { - "input": {"x": 3, "y": 4}, - "output": 12, - "metadata": {"operation": "multiply"}, - "metrics": { - "start": lambda x: start_time <= x <= end_time, - "end": lambda x: start_time <= x <= end_time, - }, - "span_attributes": { - "name": "async_multiply", - "type": "function", - }, - }, - ) - - @logger.traced() - async def async_multiply(x: int, y: int) -> int: # pylint: disable=function-redefined - """An async function that multiplies two numbers.""" - await asyncio.sleep(0.001) # Small delay to simulate async work - result = x * y - logger.current_span().log(metadata={"operation": "multiply"}) - return result - - start_time = time.time() - result = await async_multiply(3, 4) - end_time = time.time() - - assert result == 12 - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - assert_dict_matches( - log, - { - "input": {"x": 3, "y": 4}, - "output": 12, - "metadata": {"operation": "multiply"}, - "metrics": { - "start": lambda x: start_time <= x <= end_time, - "end": lambda x: start_time <= x <= end_time, - }, - "span_attributes": { - "name": "async_multiply", - "type": "function", - }, - }, - ) - - @logger.traced(name="async_multiply_with_name") - async def async_multiply(x: int, y: int) -> int: # pylint: disable=function-redefined - """An async function that multiplies two numbers.""" - await asyncio.sleep(0.001) # Small delay to simulate async work - result = x * y - logger.current_span().log(metadata={"operation": "multiply"}) - return result - - start_time = time.time() - result = await async_multiply(3, 4) - end_time = time.time() - - assert result == 12 - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - assert_dict_matches( - log, - { - "input": {"x": 3, "y": 4}, - "output": 12, - "metadata": {"operation": "multiply"}, - "metrics": { - "start": lambda x: start_time <= x <= end_time, - "end": lambda x: start_time <= x <= end_time, - }, - "span_attributes": { - "name": "async_multiply_with_name", - "type": "function", - }, - }, - ) - - -def test_traced_sync_function(with_memory_logger): - """Test tracing synchronous functions.""" - init_test_logger(__name__) - - @logger.traced - def sync_add(a: int, b: int) -> int: - """A sync function that adds two numbers.""" - result = a + b - logger.current_span().log(metadata={"operation": "add"}) - return result - - start_time = time.time() - result = sync_add(5, 7) - end_time = time.time() - - assert result == 12 - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - assert_dict_matches( - log, - { - "input": {"a": 5, "b": 7}, - "output": 12, - "metadata": {"operation": "add"}, - "metrics": { - "start": lambda x: start_time <= x <= end_time, - "end": lambda x: start_time <= x <= end_time, - }, - "span_attributes": { - "name": "sync_add", - "type": "function", - }, - }, - ) - - -def test_traced_sync_generator(with_memory_logger): - """Test tracing synchronous generators.""" - init_test_logger(__name__) - - @logger.traced - def sync_number_generator(n: int): - """A sync generator that yields numbers.""" - for i in range(n): - yield i * 2 - - results = [] - start_time = time.time() - for value in sync_number_generator(3): - results.append(value) - end_time = time.time() - - assert results == [0, 2, 4] - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - # Should log the complete output as a list - assert log.get("output") == [0, 2, 4] - assert log.get("input") == {"n": 3} - assert_dict_matches( - log, - { - "metrics": { - "start": lambda x: start_time <= x <= end_time, - "end": lambda x: start_time <= x <= end_time, - }, - "span_attributes": { - "name": "sync_number_generator", - "type": "function", - }, - }, - ) - - -def test_traced_sync_generator_with_exception(with_memory_logger): - """Test sync generator that raises an exception.""" - init_test_logger(__name__) - - @logger.traced - def failing_generator(): - yield "first" - yield "second" - raise RuntimeError("Generator failed") - - results = [] - start_time = time.time() - with pytest.raises(RuntimeError, match="Generator failed"): - for value in failing_generator(): - results.append(value) - end_time = time.time() - - assert results == ["first", "second"] - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - # Should have partial output and error - assert log.get("output") == ["first", "second"] - assert "RuntimeError" in str(log.get("error", "")) - assert_dict_matches( - log, - { - "metrics": { - "start": lambda x: start_time <= x <= end_time, - "end": lambda x: start_time <= x <= end_time, - }, - }, - ) - - -def test_traced_sync_generator_with_subtasks(with_memory_logger): - """ - Test sync generator with current_span().log() calls - Set notrace_io so we do not automatically log output and clobber the manually logged - output "testing" - """ - - init_test_logger(__name__) - - num_loops = 3 - - @logger.traced(notrace_io=True) - def foo(i: int) -> int: - """Simulate some sync work.""" - time.sleep(0.001) - return i * 2 - - @logger.traced("main", notrace_io=True) - def main(): - yield 1 - logger.current_span().log(metadata={"a": "b"}) - tasks = [foo(i) for i in range(num_loops)] - total = sum(tasks) - logger.current_span().log(metadata=dict(total=total), output="testing") - yield total - - # consume the generator - results: list[int] = [] - start_time = time.time() - for value in main(): - results.append(value) - end_time = time.time() - - assert results == [1, 6] - - # Check logs - logs = with_memory_logger.pop() - assert len(logs) == num_loops + 1 - - # Find the main span - main_spans = [l for l in logs if l["span_attributes"]["name"] == "main"] - assert len(main_spans) == 1 - main_span = main_spans[0] - - assert_dict_matches( - main_span, - { - # no input because notrace_io - "output": "testing", - "metadata": {"a": "b", "total": 6}, # Manual metadata logging - "metrics": { - "start": lambda x: start_time <= x <= end_time, - "end": lambda x: start_time <= x <= end_time, - }, - }, - ) - - -@pytest.mark.asyncio -async def test_traced_async_generator(with_memory_logger): - """Test async generator version of sync generator test.""" - init_test_logger(__name__) - - @logger.traced - async def async_number_generator(n: int): - """An async generator that yields numbers.""" - for i in range(n): - await asyncio.sleep(0.001) - yield i * 2 - - results = [] - start_time = time.time() - async for value in async_number_generator(3): - results.append(value) - end_time = time.time() - - assert results == [0, 2, 4] - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - # Should log the complete output as a list - assert log.get("output") == [0, 2, 4] - assert log.get("input") == {"n": 3} - assert_dict_matches( - log, - { - "metrics": { - "start": lambda x: start_time <= x <= end_time, - "end": lambda x: start_time <= x <= end_time, - }, - "span_attributes": { - "name": "async_number_generator", - "type": "function", - }, - }, - ) - - -def test_traced_sync_generator_truncation(with_memory_logger, caplog): - """Test sync generator truncation behavior.""" - init_test_logger(__name__) - - original = os.environ.get("BRAINTRUST_MAX_GENERATOR_ITEMS") - try: - os.environ["BRAINTRUST_MAX_GENERATOR_ITEMS"] = "3" - - @logger.traced - def large_generator(): - """A generator that yields more items than the limit.""" - for i in range(10): - yield i - - results = [] - with caplog.at_level(logging.WARNING): - for value in large_generator(): - results.append(value) - - # All values should still be yielded - assert results == list(range(10)) - - # Check warning was logged - assert any("Generator output exceeded limit of 3 items" in record.message for record in caplog.records) - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - # Output should not be logged when truncated - assert "output" not in log or log.get("output") is None - assert log.get("input") == {} - - finally: - os.environ.pop("BRAINTRUST_MAX_GENERATOR_ITEMS", None) - if original: - os.environ["BRAINTRUST_MAX_GENERATOR_ITEMS"] = original - - -@pytest.mark.asyncio -async def test_traced_async_generator_truncation(with_memory_logger, caplog): - """Test async generator truncation behavior.""" - init_test_logger(__name__) - - original = os.environ.get("BRAINTRUST_MAX_GENERATOR_ITEMS") - try: - os.environ["BRAINTRUST_MAX_GENERATOR_ITEMS"] = "3" - - @logger.traced - async def large_async_generator(): - """An async generator that yields more items than the limit.""" - for i in range(10): - await asyncio.sleep(0.001) - yield i - - results = [] - with caplog.at_level(logging.WARNING): - async for value in large_async_generator(): - results.append(value) - - # All values should still be yielded - assert results == list(range(10)) - - # Check warning was logged - assert any("Generator output exceeded limit of 3 items" in record.message for record in caplog.records) - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - # Output should not be logged when truncated - assert "output" not in log or log.get("output") is None - assert log.get("input") == {} - - finally: - os.environ.pop("BRAINTRUST_MAX_GENERATOR_ITEMS", None) - if original: - os.environ["BRAINTRUST_MAX_GENERATOR_ITEMS"] = original - - -def test_traced_sync_generator_zero_limit_drops_output(with_memory_logger): - """Test sync generator with limit=0 drops all output but still yields values.""" - init_test_logger(__name__) - - original = os.environ.get("BRAINTRUST_MAX_GENERATOR_ITEMS") - try: - os.environ["BRAINTRUST_MAX_GENERATOR_ITEMS"] = "0" - - @logger.traced - def no_output_logged_generator(): - """Generator whose output won't be logged due to limit=0.""" - for i in range(10): - yield i - - results = [] - for value in no_output_logged_generator(): - results.append(value) - - # Generator still yields all values - assert results == list(range(10)) - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - # Output is not logged when limit is 0 - assert "output" not in log or log.get("output") is None - - finally: - os.environ.pop("BRAINTRUST_MAX_GENERATOR_ITEMS", None) - if original: - os.environ["BRAINTRUST_MAX_GENERATOR_ITEMS"] = original - - -def test_traced_sync_generator_unlimited_with_minus_one(with_memory_logger): - """Test sync generator with limit=-1 buffers all output.""" - init_test_logger(__name__) - - original = os.environ.get("BRAINTRUST_MAX_GENERATOR_ITEMS") - try: - os.environ["BRAINTRUST_MAX_GENERATOR_ITEMS"] = "-1" - - @logger.traced - def unlimited_buffer_generator(): - """Generator that buffers all output with limit=-1.""" - for i in range(3): - yield i * 2 - - results = [] - for value in unlimited_buffer_generator(): - results.append(value) - - assert results == [0, 2, 4] - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - # All output should be logged when limit is -1 - assert log.get("output") == [0, 2, 4] - - finally: - os.environ.pop("BRAINTRUST_MAX_GENERATOR_ITEMS", None) - if original: - os.environ["BRAINTRUST_MAX_GENERATOR_ITEMS"] = original - - -@pytest.mark.asyncio -async def test_traced_async_generator_zero_limit_drops_output(with_memory_logger): - """Test async generator with limit=0 drops all output but still yields values.""" - init_test_logger(__name__) - - original = os.environ.get("BRAINTRUST_MAX_GENERATOR_ITEMS") - try: - os.environ["BRAINTRUST_MAX_GENERATOR_ITEMS"] = "0" - - @logger.traced - async def no_output_logged_async_generator(): - """Async generator whose output won't be logged due to limit=0.""" - for i in range(10): - await asyncio.sleep(0.001) - yield i - - results = [] - async for value in no_output_logged_async_generator(): - results.append(value) - - # Generator still yields all values - assert results == list(range(10)) - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - # Output is not logged when limit is 0 - assert "output" not in log or log.get("output") is None - - finally: - os.environ.pop("BRAINTRUST_MAX_GENERATOR_ITEMS", None) - if original: - os.environ["BRAINTRUST_MAX_GENERATOR_ITEMS"] = original - - -@pytest.mark.asyncio -async def test_traced_async_generator_unlimited_with_minus_one(with_memory_logger): - """Test async generator with limit=-1 buffers all output.""" - init_test_logger(__name__) - - original = os.environ.get("BRAINTRUST_MAX_GENERATOR_ITEMS") - try: - os.environ["BRAINTRUST_MAX_GENERATOR_ITEMS"] = "-1" - - @logger.traced - async def unlimited_buffer_async_generator(): - """Async generator that buffers all output with limit=-1.""" - for i in range(3): - await asyncio.sleep(0.001) - yield i * 2 - - results = [] - async for value in unlimited_buffer_async_generator(): - results.append(value) - - assert results == [0, 2, 4] - - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - # All output should be logged when limit is -1 - assert log.get("output") == [0, 2, 4] - - finally: - os.environ.pop("BRAINTRUST_MAX_GENERATOR_ITEMS", None) - if original: - os.environ["BRAINTRUST_MAX_GENERATOR_ITEMS"] = original - - -def test_masking_function_logger(with_memory_logger, with_simulate_login): - """Test that masking function is applied to logged data in Logger.""" - - def masking_function(data): - """Replace any occurrence of 'sensitive' with 'REDACTED'""" - if isinstance(data, str): - return data.replace("sensitive", "REDACTED") - elif isinstance(data, dict): - masked = {} - for k, v in data.items(): - if isinstance(v, str) and "sensitive" in v: - masked[k] = v.replace("sensitive", "REDACTED") - elif isinstance(v, dict): - masked[k] = masking_function(v) - elif isinstance(v, list): - masked[k] = [masking_function(item) if isinstance(item, (dict, list)) else item for item in v] - else: - masked[k] = v - return masked - elif isinstance(data, list): - return [masking_function(item) if isinstance(item, (dict, list)) else item for item in data] - return data - - # Set masking function globally - braintrust.set_masking_function(masking_function) - - # Create test logger - test_logger = init_test_logger("test_project") - - # Log some data with sensitive information - test_logger.log( - input="This is a sensitive input", - output={"message": "This contains sensitive data", "count": 42}, - metadata={"user": "sensitive_user", "safe": "normal_data"}, - ) - - # Check the logged data - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - # Verify masking was applied - assert log["input"] == "This is a REDACTED input" - assert log["output"]["message"] == "This contains REDACTED data" - assert log["output"]["count"] == 42 - assert log["metadata"]["user"] == "REDACTED_user" - assert log["metadata"]["safe"] == "normal_data" - - # Clean up - braintrust.set_masking_function(None) - - -def test_masking_function_experiment(with_memory_logger, with_simulate_login): - """Test that masking function is applied to logged data in Experiment.""" - - def masking_function(data): - """Replace any occurrence of 'password' with 'XXX'""" - if isinstance(data, str): - return data.replace("password", "XXX") - elif isinstance(data, dict): - masked = {} - for k, v in data.items(): - if k == "password": - # Mask the value when the key is "password" - masked[k] = "XXX" - elif isinstance(v, str) and "password" in v: - masked[k] = v.replace("password", "XXX") - elif isinstance(v, dict): - masked[k] = masking_function(v) - elif isinstance(v, list): - masked[k] = [masking_function(item) if isinstance(item, (dict, list)) else item for item in v] - else: - masked[k] = v - return masked - elif isinstance(data, list): - return [masking_function(item) if isinstance(item, (dict, list)) else item for item in data] - return data - - # Set masking function globally - braintrust.set_masking_function(masking_function) - - # Create test experiment - from braintrust.logger import Experiment, ObjectMetadata, ProjectExperimentMetadata - - project_metadata = ObjectMetadata(id="test_project", name="test_project", full_info=dict()) - experiment_metadata = ObjectMetadata(id="test_experiment", name="test_experiment", full_info=dict()) - metadata = ProjectExperimentMetadata(project=project_metadata, experiment=experiment_metadata) - lazy_metadata = LazyValue(lambda: metadata, use_mutex=False) - experiment = Experiment(lazy_metadata=lazy_metadata) - - # Log some data with passwords - experiment.log( - input={"command": "login", "password": "secret123"}, - output="Login successful with password validation", - scores={"accuracy": 0.95}, - ) - - # Check the logged data - logs = with_memory_logger.pop() - assert len(logs) > 0 # Should have at least one log entry - - # Debug: Print all logs to see what's there - print(f"Number of logs: {len(logs)}") - for i, log in enumerate(logs): - print(f"Log {i}: {log}") - - # Find the main log entry (not the end span) - main_log = None - for log in logs: - if log.get("input") is not None: - main_log = log - break - - assert main_log is not None, "Could not find main log entry" - - # Verify masking was applied - assert main_log["input"]["command"] == "login" - assert main_log["input"]["password"] == "XXX" - assert main_log["output"] == "Login successful with XXX validation" - assert main_log["scores"]["accuracy"] == 0.95 - - # Clean up - braintrust.set_masking_function(None) - - -def test_masking_function_propagates_to_spans(with_memory_logger, with_simulate_login): - """Test that masking function propagates from parent to child spans.""" - - def masking_function(data): - """Replace any 'api_key' field with 'HIDDEN'""" - if isinstance(data, dict): - masked = {} - for k, v in data.items(): - if k == "api_key": - masked[k] = "HIDDEN" - elif isinstance(v, dict): - masked[k] = masking_function(v) - elif isinstance(v, list): - masked[k] = [masking_function(item) if isinstance(item, (dict, list)) else item for item in v] - else: - masked[k] = v - return masked - elif isinstance(data, list): - return [masking_function(item) if isinstance(item, (dict, list)) else item for item in data] - return data - - # Set masking function globally - braintrust.set_masking_function(masking_function) - - # Create test logger - test_logger = init_test_logger("test_project") - - # Create parent span - with test_logger.start_span(name="parent_span") as parent: - parent.log(input={"api_key": "sk-12345", "query": "test"}) - - # Create child span - with parent.start_span(name="child_span") as child: - child.log(output={"response": "data", "api_key": "sk-67890"}) - - # Check the logged data - logs = with_memory_logger.pop() - - # Find parent and child logs - parent_log = next((log for log in logs if log.get("span_attributes", {}).get("name") == "parent_span"), None) - child_log = next((log for log in logs if log.get("span_attributes", {}).get("name") == "child_span"), None) - - assert parent_log is not None - assert child_log is not None - - # Verify masking was applied to both spans - assert parent_log["input"]["api_key"] == "HIDDEN" - assert parent_log["input"]["query"] == "test" - assert child_log["output"]["api_key"] == "HIDDEN" - assert child_log["output"]["response"] == "data" - - -def test_masking_function_dataset(with_memory_logger, with_simulate_login): - """Test that masking function is applied to dataset operations.""" - - def masking_function(data): - """Replace email addresses with 'EMAIL_REDACTED'""" - if isinstance(data, dict): - masked = {} - for k, v in data.items(): - if isinstance(v, str) and "@" in v and "." in v: - # Simple email detection - masked[k] = "EMAIL_REDACTED" - elif isinstance(v, dict): - masked[k] = masking_function(v) - elif isinstance(v, list): - masked[k] = [masking_function(item) if isinstance(item, (dict, list)) else item for item in v] - else: - masked[k] = v - return masked - elif isinstance(data, list): - return [masking_function(item) if isinstance(item, (dict, list)) else item for item in data] - return data - - # Set masking function globally - braintrust.set_masking_function(masking_function) - - # Create test dataset - from braintrust.logger import Dataset, ObjectMetadata, ProjectDatasetMetadata - - project_metadata = ObjectMetadata(id="test_project", name="test_project", full_info=dict()) - dataset_metadata = ObjectMetadata(id="test_dataset", name="test_dataset", full_info=dict()) - metadata = ProjectDatasetMetadata(project=project_metadata, dataset=dataset_metadata) - lazy_metadata = LazyValue(lambda: metadata, use_mutex=False) - dataset = Dataset(lazy_metadata=lazy_metadata) - - # Insert data with email addresses - dataset.insert( - input={"user": "john@example.com", "action": "login"}, - expected={"status": "success", "email": "john@example.com"}, - metadata={"admin_email": "admin@example.com"}, - ) - - # Check the logged data - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - # Verify masking was applied - assert log["input"]["user"] == "EMAIL_REDACTED" - assert log["input"]["action"] == "login" - assert log["expected"]["status"] == "success" - assert log["expected"]["email"] == "EMAIL_REDACTED" - assert log["metadata"]["admin_email"] == "EMAIL_REDACTED" - - # Clean up - braintrust.set_masking_function(None) - - -def test_masking_function_with_error(with_memory_logger, with_simulate_login): - """Test that masking errors are handled gracefully and stack traces are captured.""" - - def broken_masking_function(data): - """A masking function that throws errors for certain data types.""" - if isinstance(data, dict): - # This will throw an error when trying to iterate - for key in data: - if key == "password": - # Simulate a complex error - raise ValueError(f"Cannot mask sensitive field '{key}' - internal masking error") - elif key == "accuracy": - # Trigger error for scores field - raise TypeError("Cannot process numeric score") - return data - elif isinstance(data, str): - if "secret" in data.lower(): - # Another type of error - result = 1 / 0 # ZeroDivisionError - return data - elif isinstance(data, list): - # Try to access non-existent index - if len(data) > 0: - _ = data[100] # IndexError - return data - return data - - # Set the broken masking function - braintrust.set_masking_function(broken_masking_function) - - # Create test experiment - from braintrust.logger import Experiment, ObjectMetadata, ProjectExperimentMetadata - - project_metadata = ObjectMetadata(id="test_project", name="test_project", full_info=dict()) - experiment_metadata = ObjectMetadata(id="test_experiment", name="test_experiment", full_info=dict()) - metadata = ProjectExperimentMetadata(project=project_metadata, experiment=experiment_metadata) - lazy_metadata = LazyValue(lambda: metadata, use_mutex=False) - experiment = Experiment(lazy_metadata=lazy_metadata) - - # Log data that will trigger various errors - experiment.log( - input={"password": "my-password", "user": "test"}, - output="This contains SECRET information", - expected=["item1", "item2"], - metadata={"safe": "data"}, - scores={"score": 1.0}, # Add a safe score that won't trigger error - ) - - experiment.flush() - - # Check the logged data - logs = with_memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - - # Verify error handling - # The input should have an error message because of the password field - assert log["input"] == "ERROR: Failed to mask field 'input' - ValueError" - - # The output should have an error message because of division by zero - assert log["output"] == "ERROR: Failed to mask field 'output' - ZeroDivisionError" - - # The expected should have an error message because of index error - assert log["expected"] == "ERROR: Failed to mask field 'expected' - IndexError" - - # Metadata should be fine since it doesn't trigger any errors - assert log["metadata"] == {"safe": "data"} - - # Test with scores that triggers an error - experiment.log( - input={"data": "test"}, - output="result", - scores={"accuracy": 0.95}, # This will trigger an error - ) - - logs2 = with_memory_logger.pop() - assert len(logs2) == 1 - log2 = logs2[0] - - # Scores should be dropped and error should be logged - assert "scores" not in log2 - assert "error" in log2 - assert log2["error"] == "ERROR: Failed to mask field 'scores' - TypeError" - - # Test with metrics that triggers an error - experiment.log( - input={"data": "test2"}, - output="result2", - scores={"score": 1.0}, # Safe score - metrics={"accuracy": 0.95}, # This will trigger an error - ) - - logs3 = with_memory_logger.pop() - assert len(logs3) == 1 - log3 = logs3[0] - - # Metrics should be dropped and error should be logged - assert "metrics" not in log3 - assert "error" in log3 - assert log3["error"] == "ERROR: Failed to mask field 'metrics' - TypeError" - - # Test with both scores and metrics failing - experiment.log( - input={"data": "test3"}, - output="result3", - scores={"accuracy": 0.85}, # This will trigger an error - metrics={"accuracy": 0.95}, # This will also trigger an error - ) - - logs4 = with_memory_logger.pop() - assert len(logs4) == 1 - log4 = logs4[0] - - # Both should be dropped and errors should be concatenated - assert "scores" not in log4 - assert "metrics" not in log4 - assert "error" in log4 - assert "ERROR: Failed to mask field 'scores' - TypeError" in log4["error"] - assert "ERROR: Failed to mask field 'metrics' - TypeError" in log4["error"] - assert "; " in log4["error"] # Check that errors are joined with semicolon - - # Test with logger and nested spans - test_logger = init_test_logger("test_masking_errors_logger") - - with test_logger.start_span("parent") as parent: - parent.log(input={"api_key": "key123", "password": "secret"}, metadata={"request_id": "req-123"}) - - with parent.start_span("child") as child: - child.log(output="Result with secret data", expected=[1, 2, 3]) - - test_logger.flush() - - # Check nested span logs - logs = with_memory_logger.pop() - assert len(logs) == 2 # parent and child - - # Find parent and child by span_attributes - parent_log = next(log for log in logs if log.get("span_attributes", {}).get("name") == "parent") - child_log = next(log for log in logs if log.get("span_attributes", {}).get("name") == "child") - - # Parent should have error in input - assert parent_log["input"] == "ERROR: Failed to mask field 'input' - ValueError" - - # Child should have errors in output and expected - assert child_log["output"] == "ERROR: Failed to mask field 'output' - ZeroDivisionError" - assert child_log["expected"] == "ERROR: Failed to mask field 'expected' - IndexError" - - # Clean up - braintrust.set_masking_function(None) - - -def test_attachment_unreadable_path_logs_warning(caplog): - with caplog.at_level(logging.WARNING, logger="braintrust"): - Attachment( - data="unreadable.txt", - filename="unreadable.txt", - content_type="text/plain", - ) - - assert len(caplog.records) == 1 - assert caplog.records[0].levelname == "WARNING" - assert "Failed to read file" in caplog.records[0].message - - -def test_attachment_readable_path_returns_data(tmp_path): - file_path = tmp_path / "attachments" / "hello.txt" - file_path.parent.mkdir(parents=True) - file_path.write_bytes(b"hello world") - - a = Attachment(data=str(file_path), filename="hello.txt", content_type="text/plain") - assert a.data == b"hello world" - - -def test_parent_precedence_with_parent_context_and_traced(with_memory_logger, with_simulate_login): - """Test that with parent_context + traced, child spans attach to current span (not directly to parent context).""" - init_test_logger(__name__) - - # Create exported parent context - with logger.start_span(name="outer") as outer: - outer_export = outer.export() - - @logger.traced("inner", notrace_io=True) - def inner(): - s = logger.start_span(name="child") - s.end() - - with parent_context(outer_export): - inner() - - logs = with_memory_logger.pop() - outer_log = next(l for l in logs if l.get("span_attributes", {}).get("name") == "outer") - inner_log = next(l for l in logs if l.get("span_attributes", {}).get("name") == "inner") - child_log = next(l for l in logs if l.get("span_attributes", {}).get("name") == "child") - - # child should have inner as a parent - assert inner_log["span_id"] in (child_log.get("span_parents") or []) - # child and outer should share the same root - assert child_log["root_span_id"] == outer_log["root_span_id"] - - -def test_parent_precedence_traced_baseline(with_memory_logger, with_simulate_login): - """Test that traced baseline nests child under current span.""" - init_test_logger(__name__) - - @logger.traced("top", notrace_io=True) - def top(): - s = logger.start_span(name="child") - s.end() - - top() - logs = with_memory_logger.pop() - top_log = next(l for l in logs if l.get("span_attributes", {}).get("name") == "top") - child_log = next(l for l in logs if l.get("span_attributes", {}).get("name") == "child") - - assert top_log["span_id"] in (child_log.get("span_parents") or []) - - -def test_parent_precedence_explicit_parent_overrides(with_memory_logger, with_simulate_login): - """Test that explicit parent overrides current span.""" - init_test_logger(__name__) - - with logger.start_span(name="outer") as outer: - outer_export = outer.export() - - @logger.traced("inner", notrace_io=True) - def inner(): - s = braintrust.start_span(name="forced", parent=outer_export) - s.end() - - inner() - logs = with_memory_logger.pop() - outer_log = next(l for l in logs if l.get("span_attributes", {}).get("name") == "outer") - inner_log = next(l for l in logs if l.get("span_attributes", {}).get("name") == "inner") - forced_log = next(l for l in logs if l.get("span_attributes", {}).get("name") == "forced") - - parents = forced_log.get("span_parents") or [] - assert outer_log["span_id"] in parents - assert inner_log["span_id"] not in parents - - -@pytest.fixture -def reset_id_generator_state(): - """Reset ID generator state and environment variables before each test""" - logger._state._reset_id_generator() - logger._state._reset_context_manager() - original_env = os.getenv("BRAINTRUST_OTEL_COMPAT") - try: - yield - finally: - logger._state._reset_id_generator() - logger._state._reset_context_manager() - if "BRAINTRUST_OTEL_COMPAT" in os.environ: - del os.environ["BRAINTRUST_OTEL_COMPAT"] - if original_env: - os.environ["BRAINTRUST_OTEL_COMPAT"] = original_env - - -def test_otel_compatible_span_export_import(): - """Test that spans with OTEL-compatible IDs can be exported and imported correctly.""" - from braintrust.span_identifier_v4 import SpanComponentsV4, SpanObjectTypeV3 - - # Generate OTEL-compatible IDs - otel_gen = OTELIDGenerator() - trace_id = otel_gen.get_trace_id() # 32-char hex (16 bytes) - span_id = otel_gen.get_span_id() # 16-char hex (8 bytes) - - # Test that trace_id is 32 chars and span_id is 16 chars - assert len(trace_id) == 32 - assert len(span_id) == 16 - assert all(c in "0123456789abcdef" for c in trace_id) - assert all(c in "0123456789abcdef" for c in span_id) - - # Create span components - components = SpanComponentsV4( - object_type=SpanObjectTypeV3.PROJECT_LOGS, - object_id="test-project-id", - row_id="test-row-id", - span_id=span_id, - root_span_id=trace_id, - ) - - # Test export/import cycle - exported = components.to_str() - imported = SpanComponentsV4.from_str(exported) - - # Verify all fields match exactly - assert imported.object_type == components.object_type - assert imported.object_id == components.object_id - assert imported.row_id == components.row_id - assert imported.span_id == span_id - assert imported.root_span_id == trace_id - - -def test_span_with_otel_ids_export_import(reset_id_generator_state): - """Test that actual Span objects with OTEL IDs can export and be used as parent context.""" - init_test_logger(__name__) - os.environ["BRAINTRUST_OTEL_COMPAT"] = "true" - - # Test that OTEL generator should not share root_span_id - generator = get_id_generator() - assert generator.share_root_span_id() == False - - with logger.start_span(name="test") as span: - # Debug what we actually got - print(f"span_id: {span.span_id} (len={len(span.span_id)})") - print(f"root_span_id: {span.root_span_id} (len={len(span.root_span_id)})") - - # Test that OTEL spans should not share span_id and root_span_id - assert span.span_id != span.root_span_id - - # Verify the span has OTEL-compatible IDs - assert len(span.span_id) == 16 # 8-byte hex - assert len(span.root_span_id) == 32 # 16-byte hex - assert all(c in "0123456789abcdef" for c in span.span_id) - assert all(c in "0123456789abcdef" for c in span.root_span_id) - - # Export the span - exported = span.export() - - # Parse it back - from braintrust.span_identifier_v4 import SpanComponentsV4 - - imported = SpanComponentsV4.from_str(exported) - - # Verify IDs are preserved exactly - assert imported.span_id == span.span_id - assert imported.root_span_id == span.root_span_id - - -def test_span_with_uuid_ids_share_root_span_id(reset_id_generator_state): - """Test that UUID generators share span_id as root_span_id for backwards compatibility.""" - import os - - # Ensure UUID generator is used (default behavior) - if "BRAINTRUST_OTEL_COMPAT" in os.environ: - del os.environ["BRAINTRUST_OTEL_COMPAT"] - - init_test_logger(__name__) - - # Test that UUID generator should share root_span_id - generator = get_id_generator() - assert generator.share_root_span_id() == True - - with logger.start_span(name="test") as span: - # Test that UUID spans should share span_id and root_span_id for backwards compatibility - assert span.span_id == span.root_span_id - - -def test_parent_context_with_otel_ids(with_memory_logger, reset_id_generator_state): - """Test that parent_context works correctly with OTEL-compatible IDs.""" - os.environ["BRAINTRUST_OTEL_COMPAT"] = "true" - init_test_logger(__name__) - - # Create a span and export it - with logger.start_span(name="parent") as parent_span: - parent_export = parent_span.export() - original_span_id = parent_span.span_id - original_root_span_id = parent_span.root_span_id - - def is_hex(s): - return all(c in "0123456789abcdef" for c in s.lower()) - - assert is_hex(original_span_id) - assert is_hex(original_root_span_id) - - # Use the exported span as parent context - with parent_context(parent_export): - with logger.start_span(name="child") as child_span: - # Child should inherit the root_span_id from parent - assert child_span.root_span_id == original_root_span_id - assert original_span_id in child_span.span_parents - - # Verify logs were created correctly - logs = with_memory_logger.pop() - parent_log = next(l for l in logs if l.get("span_attributes", {}).get("name") == "parent") - child_log = next(l for l in logs if l.get("span_attributes", {}).get("name") == "child") - - assert parent_log["span_id"] == original_span_id - assert parent_log["root_span_id"] == original_root_span_id - assert child_log["root_span_id"] == original_root_span_id - assert parent_log["span_id"] in child_log.get("span_parents", []) - - -def test_nested_spans_with_export(with_memory_logger): - """Test nested spans with login triggered during span execution. - - This reproduces a bug where calling state.login() during an active span - calls copy_state(), which would overwrite _context_manager with None, - causing a ContextVar token mismatch error when the span exits. - """ - from braintrust import logger - from braintrust.test_helpers import init_test_exp - - experiment = init_test_exp("test-experiment", "test-project") - - # Start a span, then trigger login which calls copy_state() - with experiment.start_span(name="s1") as span1: - span1.log(input="one") - # Trigger login with TEST_API_KEY and force_login=True - # This calls copy_state() which should NOT overwrite _context_manager - experiment.state.login(api_key=logger.TEST_API_KEY, force_login=True) - # Continue with nested spans to ensure context manager still works - with experiment.start_span(name="s2") as span2: - span2.log(input="two") - - -def test_span_start_span_with_explicit_parent(with_memory_logger): - """Test that span.start_span() with explicit parent doesn't inherit from context. - - This verifies the fix where span.start_span(parent=exported) should use the - exported parent, not the current span from the context manager. - """ - from braintrust.test_helpers import init_test_exp - - experiment = init_test_exp("test-experiment", "test-project") - - # Create a root span, log to it (creates row_id), and export it - with experiment.start_span(name="root") as root_span: - root_span.log(input="root input") - root_export = root_span.export() - root_span_id = root_span.span_id - root_root_span_id = root_span.root_span_id - - # Create another span - with experiment.start_span(name="span2") as span2: - span2_span_id = span2.span_id - - # Within span2's context, create span3 with explicit parent=root_export - # span3 should NOT inherit from span2 (the active context) - # span3 should inherit from root (because root_export has row_id after logging) - with span2.start_span(parent=root_export, name="span3") as span3: - span3.log(input="test") - - logs = with_memory_logger.pop() - span3_log = next(l for l in logs if l.get("span_attributes", {}).get("name") == "span3") - - # span3 should NOT have span2 as parent (would happen if it inherited from context) - assert span2_span_id not in span3_log.get("span_parents", []), ( - "span3 should not inherit from span2 context when explicit parent is provided" - ) - - # span3 should inherit from root (the explicit parent) - assert root_span_id in span3_log.get("span_parents", []), ( - "span3 should have root_span_id in span_parents from explicit parent" - ) - assert span3_log["root_span_id"] == root_root_span_id, "span3 should have root's root_span_id" - - -def test_span_start_span_inherits_from_self(with_memory_logger): - """Test that span.start_span() without explicit parent inherits from self. - - When no explicit parent is provided, the child should inherit from the current span. - """ - from braintrust.test_helpers import init_test_exp - - experiment = init_test_exp("test-experiment", "test-project") - - # Create a parent span - with experiment.start_span(name="parent") as parent_span: - parent_span_id = parent_span.span_id - parent_root_span_id = parent_span.root_span_id - - # Create a child span without explicit parent - should inherit from parent_span - with parent_span.start_span(name="child") as child_span: - child_span.log(input="test") - - logs = with_memory_logger.pop() - child_log = next(l for l in logs if l.get("span_attributes", {}).get("name") == "child") - - # Child should inherit parent's root_span_id and have parent_span_id in span_parents - assert child_log["root_span_id"] == parent_root_span_id - assert parent_span_id in child_log.get("span_parents", []), ( - "child should have parent_span_id in span_parents when no explicit parent is provided" - ) - - -def test_span_start_span_with_exported_span_parent(with_memory_logger): - """Test that span.start_span() with exported span parent uses the exported span. - - When an exported span (with row_id) is provided as parent, it should be used - instead of the context manager's current span. - """ - from braintrust.test_helpers import init_test_exp - - experiment = init_test_exp("test-experiment", "test-project") - - # Create and export a span with row_id - with experiment.start_span(name="exported_parent") as exported_parent: - exported_parent.log(input="parent") - exported_parent_export = exported_parent.export() - exported_parent_span_id = exported_parent.span_id - exported_parent_root_span_id = exported_parent.root_span_id - - # Create another span that will be the active context - with experiment.start_span(name="active_context") as active_context: - active_context_span_id = active_context.span_id - - # Within active_context, create a child with explicit parent=exported_parent_export - # Should use exported_parent, not active_context - with active_context.start_span(parent=exported_parent_export, name="child") as child: - child.log(input="test") - - logs = with_memory_logger.pop() - child_log = next(l for l in logs if l.get("span_attributes", {}).get("name") == "child") - - # Child should inherit from exported_parent, not active_context - assert child_log["root_span_id"] == exported_parent_root_span_id - assert exported_parent_span_id in child_log.get("span_parents", []), ( - "child should have exported_parent_span_id in span_parents" - ) - assert active_context_span_id not in child_log.get("span_parents", []), ( - "child should NOT have active_context_span_id in span_parents" - ) - - -def test_update_span_includes_span_id_and_root_span_id_from_export(with_memory_logger): - experiment = init_test_exp("test-experiment", "test-project") - - with experiment.start_span(name="span") as span: - span.log(input="input") - exported = span.export() - span_id = span.span_id - root_span_id = span.root_span_id - - with_memory_logger.pop() - - braintrust.update_span(exported=exported, output="updated output") - - logs = with_memory_logger.pop() - updated_log = next(log for log in logs if log.get("output") == "updated output") - assert updated_log["span_id"] == span_id - assert updated_log["root_span_id"] == root_span_id - - -def test_get_exporter_returns_v3_by_default(): - """Test that _get_exporter() returns SpanComponentsV3 when OTEL_COMPAT is not set.""" - with preserve_env_vars("BRAINTRUST_OTEL_COMPAT"): - os.environ.pop("BRAINTRUST_OTEL_COMPAT", None) - from braintrust.logger import _get_exporter - from braintrust.span_identifier_v3 import SpanComponentsV3 - - exporter = _get_exporter() - assert exporter == SpanComponentsV3, "Should return V3 by default" - - -def test_get_exporter_returns_v4_when_otel_enabled(): - """Test that _get_exporter() returns SpanComponentsV4 when OTEL_COMPAT is true.""" - with preserve_env_vars("BRAINTRUST_OTEL_COMPAT"): - os.environ["BRAINTRUST_OTEL_COMPAT"] = "true" - from braintrust.logger import _get_exporter - from braintrust.span_identifier_v4 import SpanComponentsV4 - - exporter = _get_exporter() - assert exporter == SpanComponentsV4, "Should return V4 when OTEL_COMPAT=true" - - -def test_experiment_export_respects_otel_compat_default(): - """Test that Experiment.export() uses V3 by default.""" - with preserve_env_vars("BRAINTRUST_OTEL_COMPAT"): - os.environ.pop("BRAINTRUST_OTEL_COMPAT", None) - experiment = init_test_exp("test-exp") - exported = experiment.export() - - from braintrust.span_identifier_v4 import SpanComponentsV4 - - version = SpanComponentsV4.get_version(exported) - assert version == 3, f"Expected V3 encoding (version=3), got version={version}" - - -def test_experiment_export_respects_otel_compat_enabled(): - """Test that Experiment.export() uses V4 when OTEL_COMPAT is true.""" - with preserve_env_vars("BRAINTRUST_OTEL_COMPAT"): - os.environ["BRAINTRUST_OTEL_COMPAT"] = "true" - experiment = init_test_exp("test-exp") - exported = experiment.export() - - from braintrust.span_identifier_v4 import SpanComponentsV4 - - version = SpanComponentsV4.get_version(exported) - assert version == 4, f"Expected V4 encoding (version=4), got version={version}" - - -def test_logger_export_respects_otel_compat_default(): - """Test that Logger.export() uses V3 by default.""" - with preserve_env_vars("BRAINTRUST_OTEL_COMPAT"): - os.environ.pop("BRAINTRUST_OTEL_COMPAT", None) - test_logger = init_test_logger(__name__) - exported = test_logger.export() - - from braintrust.span_identifier_v4 import SpanComponentsV4 - - version = SpanComponentsV4.get_version(exported) - assert version == 3, f"Expected V3 encoding (version=3), got version={version}" - - -def test_logger_export_respects_otel_compat_enabled(): - """Test that Logger.export() uses V4 when OTEL_COMPAT is true.""" - with preserve_env_vars("BRAINTRUST_OTEL_COMPAT"): - os.environ["BRAINTRUST_OTEL_COMPAT"] = "true" - test_logger = init_test_logger(__name__) - exported = test_logger.export() - - from braintrust.span_identifier_v4 import SpanComponentsV4 - - version = SpanComponentsV4.get_version(exported) - assert version == 4, f"Expected V4 encoding (version=4), got version={version}" - - -def test_register_otel_flush_callback(): - """Test that register_otel_flush registers a callback correctly.""" - import asyncio - - from braintrust import register_otel_flush - from braintrust.logger import _internal_get_global_state - from braintrust.test_helpers import init_test_logger - - init_test_logger(__name__) - state = _internal_get_global_state() - - # Track if callback was invoked - callback_invoked = False - - async def mock_flush(): - nonlocal callback_invoked - callback_invoked = True - - # Register the callback - register_otel_flush(mock_flush) - - # Calling flush_otel should invoke the registered callback - asyncio.run(state.flush_otel()) - - assert callback_invoked is True - - -def test_register_otel_flush_disables_span_cache(): - """Test that register_otel_flush disables the span cache.""" - from braintrust import register_otel_flush - from braintrust.logger import _internal_get_global_state - from braintrust.test_helpers import init_test_logger - - init_test_logger(__name__) - state = _internal_get_global_state() - - # Enable the cache (simulating what happens during eval) - state.span_cache.start() - assert state.span_cache.disabled is False - - async def mock_flush(): - pass - - # Register OTEL flush - register_otel_flush(mock_flush) - - # Cache should now be disabled - assert state.span_cache.disabled is True - - -def test_flush_otel_noop_when_no_callback(): - """Test that flush_otel is a no-op when no callback is registered.""" - import asyncio - - from braintrust.logger import _internal_get_global_state - from braintrust.test_helpers import init_test_logger - - init_test_logger(__name__) - state = _internal_get_global_state() - - # Should not throw even with no callback registered - asyncio.run(state.flush_otel()) - - -def test_register_otel_flush_permanently_disables_cache(): - """Test that register_otel_flush permanently disables the cache.""" - from braintrust import register_otel_flush - from braintrust.logger import _internal_get_global_state - from braintrust.test_helpers import init_test_logger - - init_test_logger(__name__) - state = _internal_get_global_state() - - # Enable the cache - state.span_cache.start() - assert state.span_cache.disabled is False - - async def mock_flush(): - pass - - # Register OTEL flush - register_otel_flush(mock_flush) - assert state.span_cache.disabled is True - - # Try to start again - should still be disabled because of explicit disable - state.span_cache.start() - assert state.span_cache.disabled is True - - -class TestJSONAttachment(TestCase): - def test_create_attachment_from_json_data(self): - """Test creating an attachment from JSON data.""" - test_data = { - "foo": "bar", - "nested": { - "array": [1, 2, 3], - "bool": True, - }, - } - - attachment = JSONAttachment(test_data) - - self.assertEqual(attachment.reference["type"], "braintrust_attachment") - self.assertEqual(attachment.reference["filename"], "data.json") - self.assertEqual(attachment.reference["content_type"], "application/json") - self.assertIn("key", attachment.reference) - - data = attachment.data - parsed = json.loads(data.decode("utf-8")) - self.assertEqual(parsed, test_data) - - def test_custom_filename(self): - """Test that custom filename is respected.""" - attachment = JSONAttachment({"test": "data"}, filename="custom.json") - - self.assertEqual(attachment.reference["filename"], "custom.json") - - def test_pretty_print(self): - """Test pretty printing JSON data.""" - test_data = {"a": 1, "b": 2} - attachment = JSONAttachment(test_data, pretty=True) - - data = attachment.data - text = data.decode("utf-8") - self.assertEqual(text, '{\n "a": 1,\n "b": 2\n}') - - def test_large_transcript_scenario(self): - """Test handling large transcript data.""" - large_transcript = [ - { - "role": "user" if i % 2 == 0 else "assistant", - "content": f"Message {i}", - "timestamp": time.time() + i, - } - for i in range(1000) - ] - - attachment = JSONAttachment(large_transcript, filename="transcript.json") - - self.assertEqual(attachment.reference["filename"], "transcript.json") - self.assertEqual(attachment.reference["content_type"], "application/json") - - def test_arrays_and_primitives(self): - """Test handling arrays and primitive values.""" - array_data = [1, 2, 3, 4, 5] - attachment = JSONAttachment(array_data) - - data = attachment.data - parsed = json.loads(data.decode("utf-8")) - self.assertEqual(parsed, array_data) - - def test_integration_with_logger_patterns(self): - """Test the intended usage pattern with logger.""" - log_data = { - "input": { - "type": "nameOfPrompt", - "transcript": JSONAttachment( - [ - {"role": "user", "content": "Hello"}, - {"role": "assistant", "content": "Hi there!"}, - ] - ), - "configValue1": 123, - "configValue2": True, - }, - "output": [{"type": "text", "value": "Generated response"}], - "metadata": { - "sessionId": "123", - "userId": "456", - "renderedPrompt": JSONAttachment( - "This is a very long prompt template...", - filename="prompt.json", - ), - }, - } - - self.assertIsInstance(log_data["input"]["transcript"], JSONAttachment) - self.assertIsInstance(log_data["metadata"]["renderedPrompt"], JSONAttachment) - - def test_extract_attachments_with_json_attachment(self): - """Test that JSONAttachment works with _extract_attachments.""" - json_attachment = JSONAttachment({"foo": "bar"}, filename="test.json") - event = { - "input": { - "data": json_attachment, - }, - } - - attachments: List[BaseAttachment] = [] - _extract_attachments(event, attachments) - - self.assertEqual(len(attachments), 1) - self.assertIs(attachments[0], json_attachment) - self.assertEqual(event["input"]["data"], json_attachment.reference) - - -class TestDatasetInternalBtql(TestCase): - """Test that _internal_btql parameters (especially limit) are properly passed through to BTQL queries.""" - - @patch("braintrust.logger.BraintrustState") - def test_dataset_internal_btql_limit_not_overwritten(self, mock_state_class): - """Test that custom limit in _internal_btql is not overwritten by DEFAULT_FETCH_BATCH_SIZE.""" - # Set up mock state - mock_state = MagicMock() - mock_state_class.return_value = mock_state - - # Mock the API connection and response - mock_api_conn = MagicMock() - mock_state.api_conn.return_value = mock_api_conn - - # Mock response object - mock_response = MagicMock() - mock_response.json.return_value = { - "data": [ - {"id": "1", "input": "test1", "expected": "output1"}, - {"id": "2", "input": "test2", "expected": "output2"}, - ], - "cursor": None, - } - mock_api_conn.post.return_value = mock_response - - # Create dataset with custom limit in _internal_btql - from braintrust.logger import Dataset, LazyValue, ObjectMetadata, ProjectDatasetMetadata - - project_metadata = ObjectMetadata(id="test-project", name="test-project", full_info={}) - dataset_metadata = ObjectMetadata(id="test-dataset", name="test-dataset", full_info={}) - lazy_metadata = LazyValue( - lambda: ProjectDatasetMetadata(project=project_metadata, dataset=dataset_metadata), - use_mutex=False, - ) - - custom_limit = 50 - dataset = Dataset( - lazy_metadata=lazy_metadata, - _internal_btql={"limit": custom_limit, "where": {"op": "eq", "left": "foo", "right": "bar"}}, - state=mock_state, - ) - - # Trigger a fetch which will make the BTQL query - list(dataset.fetch()) - - # Verify the API was called - mock_api_conn.post.assert_called_once() - - # Get the actual call arguments - call_args = mock_api_conn.post.call_args - query_json = call_args[1]["json"]["query"] - - # Verify that the custom limit is present (not overwritten by DEFAULT_FETCH_BATCH_SIZE) - self.assertEqual(query_json["limit"], custom_limit) - - # Verify that other _internal_btql fields are also present - self.assertEqual(query_json["where"], {"op": "eq", "left": "foo", "right": "bar"}) - - @patch("braintrust.logger.BraintrustState") - def test_dataset_default_limit_when_not_specified(self, mock_state_class): - """Test that DEFAULT_FETCH_BATCH_SIZE is used when no custom limit is specified.""" - from braintrust.logger import ( - DEFAULT_FETCH_BATCH_SIZE, - Dataset, - LazyValue, - ObjectMetadata, - ProjectDatasetMetadata, - ) - - # Set up mock state - mock_state = MagicMock() - mock_state_class.return_value = mock_state - - # Mock the API connection and response - mock_api_conn = MagicMock() - mock_state.api_conn.return_value = mock_api_conn - - # Mock response object - mock_response = MagicMock() - mock_response.json.return_value = { - "data": [], - "cursor": None, - } - mock_api_conn.post.return_value = mock_response - - # Create dataset without custom limit - project_metadata = ObjectMetadata(id="test-project", name="test-project", full_info={}) - dataset_metadata = ObjectMetadata(id="test-dataset", name="test-dataset", full_info={}) - lazy_metadata = LazyValue( - lambda: ProjectDatasetMetadata(project=project_metadata, dataset=dataset_metadata), - use_mutex=False, - ) - - dataset = Dataset( - lazy_metadata=lazy_metadata, - _internal_btql=None, - state=mock_state, - ) - - # Trigger a fetch which will make the BTQL query - list(dataset.fetch()) - - # Verify the API was called - mock_api_conn.post.assert_called_once() - - # Get the actual call arguments - call_args = mock_api_conn.post.call_args - query_json = call_args[1]["json"]["query"] - - # Verify that the default limit is used - self.assertEqual(query_json["limit"], DEFAULT_FETCH_BATCH_SIZE) - - @patch("braintrust.logger.BraintrustState") - def test_dataset_custom_batch_size_in_fetch(self, mock_state_class): - """Test that custom batch_size in fetch() is properly passed to BTQL query.""" - from braintrust.logger import Dataset, LazyValue, ObjectMetadata, ProjectDatasetMetadata - - # Set up mock state - mock_state = MagicMock() - mock_state_class.return_value = mock_state - - # Mock the API connection and response - mock_api_conn = MagicMock() - mock_state.api_conn.return_value = mock_api_conn - - # Mock response object - mock_response = MagicMock() - mock_response.json.return_value = { - "data": [{"id": "1", "input": "test1", "expected": "output1"}], - "cursor": None, - } - mock_api_conn.post.return_value = mock_response - - # Create dataset - project_metadata = ObjectMetadata(id="test-project", name="test-project", full_info={}) - dataset_metadata = ObjectMetadata(id="test-dataset", name="test-dataset", full_info={}) - lazy_metadata = LazyValue( - lambda: ProjectDatasetMetadata(project=project_metadata, dataset=dataset_metadata), - use_mutex=False, - ) - - dataset = Dataset( - lazy_metadata=lazy_metadata, - state=mock_state, - ) - - # Trigger a fetch with custom batch_size - custom_batch_size = 250 - list(dataset.fetch(batch_size=custom_batch_size)) - - # Verify the API was called - mock_api_conn.post.assert_called_once() - - # Get the actual call arguments - call_args = mock_api_conn.post.call_args - query_json = call_args[1]["json"]["query"] - - # Verify that the custom batch_size is used - self.assertEqual(query_json["limit"], custom_batch_size) - - -def test_attachment_identity_preserved_through_bt_safe_deep_copy(): - """Test that attachment object identity is preserved through bt_safe_deep_copy.""" - from braintrust.bt_json import bt_safe_deep_copy - - attachment = Attachment(data=b"data", filename="file.txt", content_type="text/plain") - original_id = id(attachment) - - # Simulate what happens in Span.log - partial_record = {"input": {"file": attachment}} - copied = bt_safe_deep_copy(partial_record) - - # Verify identity preserved - assert copied["input"]["file"] is attachment - assert id(copied["input"]["file"]) == original_id - - -def test_extract_attachments_collects_and_replaces(): - """Test that _extract_attachments properly collects attachments and replaces them with references.""" - from braintrust.logger import _extract_attachments - - attachment1 = Attachment(data=b"data1", filename="file1.txt", content_type="text/plain") - attachment2 = Attachment(data=b"data2", filename="file2.txt", content_type="text/plain") - ext_attachment = ExternalAttachment(url="s3://bucket/key", filename="file3.pdf", content_type="application/pdf") - - event = { - "input": {"file": attachment1}, - "output": {"file": attachment2}, - "metadata": {"files": [attachment1, ext_attachment]} - } - - attachments = [] - _extract_attachments(event, attachments) - - # Should have collected all 4 attachment instances (attachment1 appears twice) - assert len(attachments) == 4 - assert attachments[0] is attachment1 - assert attachments[1] is attachment2 - assert attachments[2] is attachment1 # Same instance collected again - assert attachments[3] is ext_attachment - - # Event should have been modified to contain references - assert event["input"]["file"] == attachment1.reference - assert event["output"]["file"] == attachment2.reference - assert event["metadata"]["files"][0] == attachment1.reference - assert event["metadata"]["files"][1] == ext_attachment.reference - - -def test_extract_attachments_preserves_identity(): - """Test that the same attachment instance is collected multiple times when it appears in different places.""" - from braintrust.logger import _extract_attachments - - attachment = Attachment(data=b"data", filename="file.txt", content_type="text/plain") - original_id = id(attachment) - - event = { - "input": attachment, - "output": attachment, # Same instance - "metadata": {"file": attachment} # Same instance again - } - - attachments = [] - _extract_attachments(event, attachments) - - # Should collect the same instance 3 times - assert len(attachments) == 3 - assert all(att is attachment for att in attachments) - assert all(id(att) == original_id for att in attachments) - - -def test_attachment_upload_tracked_on_flush(with_memory_logger, with_simulate_login): - """Test that attachment upload is tracked when attachments are logged and flushed.""" - attachment = Attachment(data=b"test data", filename="test.txt", content_type="text/plain") - - logger = init_test_logger(__name__) - span = logger.start_span(name="test_span") - span.log(input={"file": attachment}) - span.end() - - # No upload attempts yet - assert len(with_memory_logger.upload_attempts) == 0 - - # Flush should track upload attempt - logger.flush() - - # Now upload should be tracked - assert len(with_memory_logger.upload_attempts) == 1 - assert with_memory_logger.upload_attempts[0] is attachment - - -def test_multiple_attachments_upload_tracked(with_memory_logger, with_simulate_login): - """Test that upload is tracked for multiple attachments.""" - attachment1 = Attachment(data=b"data1", filename="file1.txt", content_type="text/plain") - attachment2 = Attachment(data=b"data2", filename="file2.txt", content_type="text/plain") - - logger = init_test_logger(__name__) - span = logger.start_span(name="test_span") - span.log( - input={"file1": attachment1}, - output={"file2": attachment2} - ) - span.end() - logger.flush() - - # Both attachments should be tracked - assert len(with_memory_logger.upload_attempts) == 2 - assert attachment1 in with_memory_logger.upload_attempts - assert attachment2 in with_memory_logger.upload_attempts - - -def test_same_attachment_logged_twice_tracked_twice(with_memory_logger, with_simulate_login): - """Test that same attachment logged twice appears twice in upload attempts.""" - attachment = Attachment(data=b"data", filename="file.txt", content_type="text/plain") - - logger = init_test_logger(__name__) - span = logger.start_span(name="test_span") - span.log(input={"file": attachment}) - span.log(metadata={"same_file": attachment}) - span.end() - logger.flush() - - # Same attachment should be tracked twice (once for each log call) - assert len(with_memory_logger.upload_attempts) == 2 - assert with_memory_logger.upload_attempts[0] is attachment - assert with_memory_logger.upload_attempts[1] is attachment - - -def test_external_attachment_upload_tracked(with_memory_logger, with_simulate_login): - """Test that ExternalAttachment upload is also tracked.""" - ext_attachment = ExternalAttachment( - url="s3://bucket/key.pdf", - filename="external.pdf", - content_type="application/pdf" - ) - - logger = init_test_logger(__name__) - span = logger.start_span(name="test_span") - span.log(input={"file": ext_attachment}) - span.end() - logger.flush() - - # ExternalAttachment should be tracked - assert len(with_memory_logger.upload_attempts) == 1 - assert with_memory_logger.upload_attempts[0] is ext_attachment - - -def test_json_attachment_upload_tracked(with_memory_logger, with_simulate_login): - """Test that JSONAttachment upload is tracked.""" - data = {"key": "value", "nested": {"array": [1, 2, 3]}} - json_attachment = JSONAttachment(data, filename="data.json") - - logger = init_test_logger(__name__) - span = logger.start_span(name="test_span") - span.log(output={"data": json_attachment}) - span.end() - logger.flush() - - # JSONAttachment should be tracked - assert len(with_memory_logger.upload_attempts) == 1 - assert with_memory_logger.upload_attempts[0] is json_attachment - - -def test_multiple_attachment_types_tracked(with_memory_logger, with_simulate_login): - """Test that different attachment types are all tracked.""" - attachment = Attachment(data=b"data", filename="file.txt", content_type="text/plain") - json_attachment = JSONAttachment({"key": "value"}, filename="data.json") - ext_attachment = ExternalAttachment(url="s3://bucket/key", filename="file.pdf", content_type="application/pdf") - - logger = init_test_logger(__name__) - span = logger.start_span(name="test_span") - span.log( - input=attachment, - output=json_attachment, - metadata={"file": ext_attachment} - ) - span.end() - logger.flush() - - # All three types should be tracked - assert len(with_memory_logger.upload_attempts) == 3 - assert attachment in with_memory_logger.upload_attempts - assert json_attachment in with_memory_logger.upload_attempts - assert ext_attachment in with_memory_logger.upload_attempts - - -# --- Tests for Span.name property --- - - -def test_span_name_returns_explicit_name(with_memory_logger): - """Test that span.name returns the name passed to start_span().""" - test_logger = init_test_logger(__name__) - - with test_logger.start_span(name="my-span") as span: - assert span.name == "my-span" - - -def test_span_name_returns_inferred_root_name(with_memory_logger): - """Test that a root span with no explicit name gets the default 'root' name.""" - test_logger = init_test_logger(__name__) - - span = test_logger.start_span() - assert span.name == "root" - span.end() - - -def test_span_name_returns_inferred_subspan_name(with_memory_logger): - """Test that a child span with no explicit name gets a caller-location-based name.""" - test_logger = init_test_logger(__name__) - - with test_logger.start_span(name="parent") as parent: - child = parent.start_span() - # The inferred name is based on caller location: "funcname:filename:lineno" - assert child.name is not None - assert len(child.name) > 0 - child.end() - - -def test_span_name_updated_by_set_attributes(with_memory_logger): - """Test that span.name reflects changes made via set_attributes().""" - test_logger = init_test_logger(__name__) - - with test_logger.start_span(name="original") as span: - assert span.name == "original" - span.set_attributes(name="renamed") - assert span.name == "renamed" - - -def test_span_name_consistent_with_logged_data(with_memory_logger): - """Test that span.name matches the name in the logged span_attributes.""" - test_logger = init_test_logger(__name__) - - with test_logger.start_span(name="logged-name") as span: - assert span.name == "logged-name" - - logs = with_memory_logger.pop() - logged_name = logs[0].get("span_attributes", {}).get("name") - assert logged_name == "logged-name" - - -def test_noop_span_name_returns_none(): - """Test that the noop span's name property returns None.""" - span = braintrust.NOOP_SPAN - assert span.name == "" - - -def test_current_span_name_accessible(with_memory_logger): - """Test that current_span().name works inside a traced context.""" - test_logger = init_test_logger(__name__) - - captured_name = None - with test_logger.start_span(name="active-span") as span: - span.set_current() - captured_name = braintrust.current_span().name - - assert captured_name == "active-span" - - -def test_traced_decorator_span_name(with_memory_logger): - """Test that @traced sets span name to the function name by default.""" - test_logger = init_test_logger(__name__) - - captured_name = None - - @logger.traced - def my_traced_function(): - nonlocal captured_name - captured_name = braintrust.current_span().name - return "done" - - my_traced_function() - - assert captured_name == "my_traced_function" diff --git a/py/src/braintrust/test_merge_row_batch.py b/py/src/braintrust/test_merge_row_batch.py deleted file mode 100644 index 7e373a3c3..000000000 --- a/py/src/braintrust/test_merge_row_batch.py +++ /dev/null @@ -1,160 +0,0 @@ -import unittest - -from braintrust.db_fields import IS_MERGE_FIELD -from braintrust.merge_row_batch import batch_items, merge_row_batch - - -class MergeRowBatchTest(unittest.TestCase): - def test_basic(self): - rows = [ - # These rows should get merged together, ending up as a merge. - dict( - experiment_id="e0", - id="x", - inputs=dict(a=12), - **{IS_MERGE_FIELD: True}, - ), - dict( - experiment_id="e0", - id="x", - inputs=dict(b=10), - **{IS_MERGE_FIELD: True}, - ), - dict( - experiment_id="e0", - id="x", - inputs=dict(c="hello"), - **{IS_MERGE_FIELD: True}, - ), - # The first row should be clobbered by the second, but the third - # merged with the second, ending up as a replacement. - dict( - experiment_id="e0", - id="y", - inputs=dict(a="hello"), - ), - dict( - experiment_id="e0", - id="y", - inputs=dict(b=10), - ), - dict( - experiment_id="e0", - id="y", - inputs=dict(c=12), - **{IS_MERGE_FIELD: True}, - ), - # These rows should be clobbered separately from the last batch. - dict( - dataset_id="d0", - id="y", - inputs=dict(a="hello"), - ), - dict( - dataset_id="d0", - id="y", - inputs=dict(b=10), - ), - dict( - dataset_id="d0", - id="y", - inputs=dict(c=12), - ), - ] - - merged_rows = merge_row_batch(rows) - key_to_rows = {(row.get("experiment_id"), row.get("dataset_id"), row.get("id")): row for row in merged_rows} - self.assertEqual( - { - ("e0", None, "x"): dict( - experiment_id="e0", - id="x", - inputs=dict(a=12, b=10, c="hello"), - **{IS_MERGE_FIELD: True}, - ), - ("e0", None, "y"): dict( - experiment_id="e0", - id="y", - inputs=dict(b=10, c=12), - ), - (None, "d0", "y"): dict( - dataset_id="d0", - id="y", - inputs=dict(c=12), - ), - }, - key_to_rows, - ) - - def test_skip_fields(self): - rows = [ - # These rows should get merged together, ending up as a merge. But - # the original fields should be retained, regardless of whether we - # populated them or not. - dict( - experiment_id="e0", - id="x", - inputs=dict(a=12), - **{IS_MERGE_FIELD: True}, - created=123, - root_span_id="abc", - _parent_id="baz", - span_parents=["foo", "bar"], - ), - dict( - experiment_id="e0", - id="x", - inputs=dict(b=10), - **{IS_MERGE_FIELD: True}, - created=456, - span_id="foo", - root_span_id="bar", - _parent_id="boop", - span_parents=[], - ), - ] - - merged_rows = merge_row_batch(rows) - self.assertEqual( - merged_rows, - [ - dict( - experiment_id="e0", - id="x", - inputs=dict(a=12, b=10), - **{IS_MERGE_FIELD: True}, - created=123, - root_span_id="abc", - _parent_id="baz", - span_parents=["foo", "bar"], - ), - ], - ) - - -class BatchItemsTest(unittest.TestCase): - def test_basic(self): - a = "x" * 1 - b = "x" * 2 - c = "x" * 4 - d = "y" * 1 - e = "y" * 2 - f = "y" * 4 - - items = [a, b, c, f, e, d] - - # No limits. - output = batch_items(items) - self.assertEqual(output, [[a, b, c, f, e, d]]) - - # Num items limit. - output = batch_items(items, batch_max_num_items=2) - self.assertEqual(output, [[a, b], [c, f], [e, d]]) - - # Num bytes limit. - output = batch_items(items, batch_max_num_bytes=2) - self.assertEqual(output, [[a], [b], [c], [f], [e], [d]]) - - # Both items and num bytes limit. - output = batch_items(items, batch_max_num_items=2, batch_max_num_bytes=5) - self.assertEqual(output, [[a, b], [c], [f], [e, d]]) diff --git a/py/src/braintrust/test_otel.py b/py/src/braintrust/test_otel.py deleted file mode 100644 index a0aa4fb18..000000000 --- a/py/src/braintrust/test_otel.py +++ /dev/null @@ -1,810 +0,0 @@ -# pylint: disable=not-context-manager -import sys - -import pytest - - -def _check_otel_installed(): - """Check if OpenTelemetry SDK is fully installed.""" - try: - from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter # noqa: F401 - from opentelemetry.sdk.trace import TracerProvider # noqa: F401 - from opentelemetry.sdk.trace.export import SimpleSpanProcessor # noqa: F401 - - return True - except ImportError: - return False - - -OTEL_INSTALLED = _check_otel_installed() - - -@pytest.fixture -def uninstall_braintrust_otel(): - sys.modules.pop("braintrust.otel", None) - yield - sys.modules.pop("braintrust.otel", None) - - -def test_otel_import_behavior(): - """Test that OtelExporter can be imported and behaves correctly based on OpenTelemetry availability.""" - from braintrust.otel import OtelExporter - - if _check_otel_installed(): - # Should be able to create an instance with proper params - assert hasattr(OtelExporter, "__init__") - else: - # Import succeeds but instantiation should raise ImportError - assert hasattr(OtelExporter, "__init__") - - -def test_otel_exporter_creation(): - """Test OtelExporter creation with and without full OpenTelemetry SDK.""" - from braintrust.otel import OtelExporter - - if _check_otel_installed(): - with pytest.MonkeyPatch.context() as m: - # Clear any existing environment variables first - m.delenv("BRAINTRUST_API_KEY", raising=False) - m.delenv("BRAINTRUST_PARENT", raising=False) - - # Set test environment variables - m.setenv("BRAINTRUST_API_KEY", "test-api-key") - m.setenv("BRAINTRUST_PARENT", "project_name:test") - - exporter = OtelExporter() - assert exporter.parent == "project_name:test" - - with pytest.MonkeyPatch.context() as m: - m.delenv("BRAINTRUST_API_KEY", raising=False) - m.delenv("BRAINTRUST_PARENT", raising=False) - - with pytest.raises(ValueError, match="API key is required"): - OtelExporter() - else: - # When SDK is not fully installed, instantiation should raise ImportError - with pytest.raises(ImportError, match="OpenTelemetry packages are not installed"): - OtelExporter(api_key="fake-key") - - -def test_otel_exporter_with_explicit_params(): - if not _check_otel_installed(): - pytest.skip("OpenTelemetry SDK not fully installed, skipping test") - - from braintrust.otel import OtelExporter - - exporter = OtelExporter( - url="https://custom.example.com/otel/v1/traces", - api_key="explicit-api-key", - parent="project_name:explicit-test", - headers={"custom-header": "custom-value"}, - ) - - assert exporter.parent == "project_name:explicit-test" - - # Check endpoint and headers - assert exporter._endpoint == "https://custom.example.com/otel/v1/traces" - expected_headers = { - "Authorization": "Bearer explicit-api-key", - "x-bt-parent": "project_name:explicit-test", - "custom-header": "custom-value", - } - assert exporter._headers == expected_headers - - -def test_otel_exporter_no_parent(caplog): - if not _check_otel_installed(): - pytest.skip("OpenTelemetry SDK not fully installed, skipping test") - - import logging - - from braintrust.otel import OtelExporter - - with pytest.MonkeyPatch.context() as m: - m.setenv("BRAINTRUST_API_KEY", "test-api-key") - m.delenv("BRAINTRUST_PARENT", raising=False) - - # Capture log messages - with caplog.at_level(logging.INFO): - exporter = OtelExporter() - - # Check that default parent is set - assert exporter.parent == "project_name:default-otel-project" - - # Check that logging message is shown - assert "No parent specified, using default: project_name:default-otel-project" in caplog.text - assert "Configure with BRAINTRUST_PARENT environment variable or parent parameter" in caplog.text - - -def test_braintrust_api_url_env_var(): - if not _check_otel_installed(): - pytest.skip("OpenTelemetry SDK not fully installed, skipping test") - - from braintrust.otel import OtelExporter - - # Test default URL - with pytest.MonkeyPatch.context() as m: - m.setenv("BRAINTRUST_API_KEY", "test-api-key") - m.setenv("BRAINTRUST_PARENT", "project_name:test") - - exporter = OtelExporter() - - assert exporter._endpoint == "https://api.braintrust.dev/otel/v1/traces" - expected_headers = {"Authorization": "Bearer test-api-key", "x-bt-parent": "project_name:test"} - assert exporter._headers == expected_headers - - # Test custom API URL - with pytest.MonkeyPatch.context() as m: - m.setenv("BRAINTRUST_API_KEY", "custom-key") - m.setenv("BRAINTRUST_API_URL", "https://custom.braintrust.dev") - m.delenv("BRAINTRUST_PARENT", raising=False) - - exporter = OtelExporter() - - assert exporter._endpoint == "https://custom.braintrust.dev/otel/v1/traces" - expected_headers = {"Authorization": "Bearer custom-key", "x-bt-parent": "project_name:default-otel-project"} - assert exporter._headers == expected_headers - - # Test custom API URL with trailing slash - with pytest.MonkeyPatch.context() as m: - m.setenv("BRAINTRUST_API_KEY", "custom-key") - m.setenv("BRAINTRUST_API_URL", "https://custom.example.com/") - m.delenv("BRAINTRUST_PARENT", raising=False) - - exporter = OtelExporter() - - assert exporter._endpoint == "https://custom.example.com/otel/v1/traces" - - -def test_braintrust_otel_filter_ai_spans_environment_variable(): - if not _check_otel_installed(): - pytest.skip("OpenTelemetry SDK not fully installed, skipping test") - - import os - - from braintrust.otel import AISpanProcessor - - # Test that the environment variable is properly read - original_value = os.environ.get("BRAINTRUST_OTEL_FILTER_AI_SPANS") - - try: - # Test true value - os.environ["BRAINTRUST_OTEL_FILTER_AI_SPANS"] = "true" - assert os.environ.get("BRAINTRUST_OTEL_FILTER_AI_SPANS", "").lower() == "true" - - # Test false value - os.environ["BRAINTRUST_OTEL_FILTER_AI_SPANS"] = "false" - assert os.environ.get("BRAINTRUST_OTEL_FILTER_AI_SPANS", "").lower() == "false" - - # Test empty value - os.environ["BRAINTRUST_OTEL_FILTER_AI_SPANS"] = "" - assert os.environ.get("BRAINTRUST_OTEL_FILTER_AI_SPANS", "").lower() == "" - - # Test FilterSpanProcessor can be instantiated - from opentelemetry.sdk.trace.export import SimpleSpanProcessor - from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter - - memory_exporter = InMemorySpanExporter() - simple_processor = SimpleSpanProcessor(memory_exporter) - filter_processor = AISpanProcessor(simple_processor) - - # Verify it has the expected attributes - assert hasattr(filter_processor, "_processor") - assert hasattr(filter_processor, "_custom_filter") - assert hasattr(filter_processor, "_should_keep_filtered_span") - assert callable(filter_processor._should_keep_filtered_span) - - finally: - # Restore original value - if original_value is not None: - os.environ["BRAINTRUST_OTEL_FILTER_AI_SPANS"] = original_value - else: - os.environ.pop("BRAINTRUST_OTEL_FILTER_AI_SPANS", None) - - -def test_braintrust_span_processor_class(): - if not _check_otel_installed(): - pytest.skip("OpenTelemetry SDK not fully installed, skipping test") - - from braintrust.otel import BraintrustSpanProcessor - - # Test basic processor without filtering - with pytest.MonkeyPatch.context() as m: - m.setenv("BRAINTRUST_API_KEY", "test-api-key") - processor = BraintrustSpanProcessor() - - # Should have the span processor interface - assert hasattr(processor, "on_start") - assert hasattr(processor, "on_end") - assert hasattr(processor, "shutdown") - assert hasattr(processor, "force_flush") - assert callable(processor.on_start) - assert callable(processor.on_end) - assert callable(processor.shutdown) - assert callable(processor.force_flush) - - # Should have access to underlying components - assert hasattr(processor, "exporter") - assert hasattr(processor, "processor") - - # Test processor with LLM filtering - with pytest.MonkeyPatch.context() as m: - m.setenv("BRAINTRUST_API_KEY", "test-api-key") - processor_with_filtering = BraintrustSpanProcessor(filter_ai_spans=True) - - # Should have the same interface - assert hasattr(processor_with_filtering, "on_start") - assert hasattr(processor_with_filtering, "on_end") - assert hasattr(processor_with_filtering, "shutdown") - assert hasattr(processor_with_filtering, "force_flush") - - # Test processor with custom parameters - with pytest.MonkeyPatch.context() as m: - m.setenv("BRAINTRUST_API_KEY", "test-api-key") - - def custom_filter(span): - return span.name.startswith("test_") - - processor_custom = BraintrustSpanProcessor( - api_key="explicit-key", - parent="project:test", - api_url="https://custom.example.com", - filter_ai_spans=True, - custom_filter=custom_filter, - headers={"X-Test-Header": "test"}, - ) - - # Should have the same interface - assert hasattr(processor_custom, "on_start") - assert hasattr(processor_custom, "on_end") - assert hasattr(processor_custom, "shutdown") - assert hasattr(processor_custom, "force_flush") - - # Check that the exporter was created with the right parameters - exporter = processor_custom.exporter - assert exporter.parent == "project:test" - assert exporter._endpoint == "https://custom.example.com/otel/v1/traces" - assert exporter._headers["Authorization"] == "Bearer explicit-key" - - -class TestSpanFiltering: - def setup_method(self): - try: - from opentelemetry.sdk.trace import TracerProvider # noqa: F401 - except ImportError: - pytest.skip("OpenTelemetry SDK not fully installed, skipping AISpanProcessor tests") - - from braintrust.otel import AISpanProcessor - from opentelemetry.sdk.trace import TracerProvider - from opentelemetry.sdk.trace.export import SimpleSpanProcessor - from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter - - self.memory_exporter = InMemorySpanExporter() - self.provider = TracerProvider() - - # Create processor with our filtering logic - base_processor = SimpleSpanProcessor(self.memory_exporter) - self.filtering_processor = AISpanProcessor(base_processor) - - self.provider.add_span_processor(self.filtering_processor) - self.tracer = self.provider.get_tracer("test_tracer") - - def teardown_method(self): - if OTEL_INSTALLED: - self.provider.shutdown() - self.memory_exporter.clear() - - def test_filters_out_root_spans(self): - with self.tracer.start_as_current_span("root_operation"): - pass - - spans = self.memory_exporter.get_finished_spans() - assert len(spans) == 0 - - def test_keeps_gen_ai_spans(self): - with self.tracer.start_as_current_span("root"): - with self.tracer.start_as_current_span("gen_ai.completion"): - pass - with self.tracer.start_as_current_span("regular_operation"): - pass - - spans = self.memory_exporter.get_finished_spans() - span_names = [span.name for span in spans] - - assert "root" not in span_names - assert "gen_ai.completion" in span_names - assert "regular_operation" not in span_names - - def test_keeps_braintrust_spans(self): - with self.tracer.start_as_current_span("root"): - with self.tracer.start_as_current_span("braintrust.eval"): - pass - with self.tracer.start_as_current_span("database_query"): - pass - - spans = self.memory_exporter.get_finished_spans() - span_names = [span.name for span in spans] - - assert "braintrust.eval" in span_names - assert "database_query" not in span_names - - def test_keeps_traceloop_spans(self): - with self.tracer.start_as_current_span("root"): - with self.tracer.start_as_current_span("traceloop.agent"): - pass - with self.tracer.start_as_current_span("traceloop.workflow.step"): - pass - - spans = self.memory_exporter.get_finished_spans() - span_names = [span.name for span in spans] - assert "root" not in span_names - assert "traceloop.agent" in span_names - assert "traceloop.workflow.step" in span_names - - def test_keeps_llm_spans(self): - with self.tracer.start_as_current_span("root"): - with self.tracer.start_as_current_span("llm.generate"): - pass - - spans = self.memory_exporter.get_finished_spans() - span_names = [span.name for span in spans] - assert "llm.generate" in span_names - - def test_keeps_ai_spans(self): - with self.tracer.start_as_current_span("root"): - with self.tracer.start_as_current_span("ai.model_call"): - pass - - spans = self.memory_exporter.get_finished_spans() - span_names = [span.name for span in spans] - assert "root" not in span_names - assert "ai.model_call" in span_names - - def test_keeps_spans_with_llm_attributes(self): - with self.tracer.start_as_current_span("root"): - with self.tracer.start_as_current_span("some_operation") as span: - span.set_attribute("gen_ai.model", "gpt-4") - span.set_attribute("regular_data", "value") - with self.tracer.start_as_current_span("another_operation") as span: - span.set_attribute("llm.tokens", 100) - with self.tracer.start_as_current_span("traceloop_operation") as span: - span.set_attribute("traceloop.agent_id", "agent-123") - with self.tracer.start_as_current_span("third_operation") as span: - span.set_attribute("database.connection", "postgres") - - spans = self.memory_exporter.get_finished_spans() - span_names = [span.name for span in spans] - - assert "root" not in span_names - assert "some_operation" in span_names # has gen_ai.model attribute - assert "another_operation" in span_names # has llm.tokens attribute - assert "traceloop_operation" in span_names # has traceloop.agent_id attribute - assert "third_operation" not in span_names # no LLM attributes - - def test_drops_non_llm_spans(self): - with self.tracer.start_as_current_span("root"): - with self.tracer.start_as_current_span("database_query"): - pass - with self.tracer.start_as_current_span("http_request"): - pass - with self.tracer.start_as_current_span("file_operation"): - pass - - spans = self.memory_exporter.get_finished_spans() - assert len(spans) == 0 - - def test_custom_filter_keeps_spans(self): - def custom_filter(span): - if span.name == "custom_keep": - return True - return None # Don't influence decision - - # Create processor with custom filter - from braintrust.otel import AISpanProcessor - from opentelemetry.sdk.trace import TracerProvider - from opentelemetry.sdk.trace.export import SimpleSpanProcessor - from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter - - memory_exporter = InMemorySpanExporter() - processor = AISpanProcessor(SimpleSpanProcessor(memory_exporter), custom_filter=custom_filter) - provider = TracerProvider() - provider.add_span_processor(processor) - tracer = provider.get_tracer(__name__) - - with tracer.start_as_current_span("root"): - with tracer.start_as_current_span("custom_keep"): - pass - with tracer.start_as_current_span("regular_operation"): - pass - - spans = memory_exporter.get_finished_spans() - span_names = [span.name for span in spans] - - assert "custom_keep" in span_names # kept by custom filter - assert "regular_operation" not in span_names # dropped by default logic - assert "root" not in span_names - - def test_custom_filter_drops_spans(self): - def custom_filter(span): - if span.name == "gen_ai.drop_this": - return False - return None # Don't influence decision - - # Create processor with custom filter - from braintrust.otel import AISpanProcessor - from opentelemetry.sdk.trace import TracerProvider - from opentelemetry.sdk.trace.export import SimpleSpanProcessor - from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter - - memory_exporter = InMemorySpanExporter() - processor = AISpanProcessor(SimpleSpanProcessor(memory_exporter), custom_filter=custom_filter) - provider = TracerProvider() - provider.add_span_processor(processor) - tracer = provider.get_tracer(__name__) - - with tracer.start_as_current_span("root"): - with tracer.start_as_current_span("gen_ai.drop_this"): - pass - with tracer.start_as_current_span("gen_ai.keep_this"): - pass - - spans = memory_exporter.get_finished_spans() - span_names = [span.name for span in spans] - - assert "gen_ai.drop_this" not in span_names # dropped by custom filter - assert "gen_ai.keep_this" in span_names # kept by default LLM logic - assert "root" not in span_names - - def test_custom_filter_none_uses_default_logic(self): - def custom_filter(span): - return None # Always defer to default logic - - # Create processor with custom filter - from braintrust.otel import AISpanProcessor - from opentelemetry.sdk.trace import TracerProvider - from opentelemetry.sdk.trace.export import SimpleSpanProcessor - from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter - - memory_exporter = InMemorySpanExporter() - processor = AISpanProcessor(SimpleSpanProcessor(memory_exporter), custom_filter=custom_filter) - provider = TracerProvider() - provider.add_span_processor(processor) - tracer = provider.get_tracer(__name__) - - with tracer.start_as_current_span("root"): - with tracer.start_as_current_span("gen_ai.completion"): - pass - with tracer.start_as_current_span("regular_operation"): - pass - - spans = memory_exporter.get_finished_spans() - span_names = [span.name for span in spans] - - assert "root" not in span_names - assert "gen_ai.completion" in span_names # kept by default LLM logic - assert "regular_operation" not in span_names # dropped by default logic - - def test_filtering_vs_unfiltered_comparison(self): - # Set up two separate exporters and processors - from braintrust.otel import AISpanProcessor - from opentelemetry.sdk.trace import TracerProvider - from opentelemetry.sdk.trace.export import SimpleSpanProcessor - from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter - - all_spans_exporter = InMemorySpanExporter() - filtered_spans_exporter = InMemorySpanExporter() - - # Processor that captures everything - all_processor = SimpleSpanProcessor(all_spans_exporter) - - # Processor that filters LLM spans - filtered_processor = AISpanProcessor(SimpleSpanProcessor(filtered_spans_exporter)) - - # Set up provider with both processors - provider = TracerProvider() - provider.add_span_processor(all_processor) - provider.add_span_processor(filtered_processor) - tracer = provider.get_tracer("comparison_test") - - # Create a mix of spans - some LLM-related, some not - with tracer.start_as_current_span("user_request") as root: - root.set_attribute("request.id", "123") - - with tracer.start_as_current_span("database_query"): - pass - - with tracer.start_as_current_span("gen_ai.completion") as llm_span: - llm_span.set_attribute("gen_ai.model", "gpt-4") - - with tracer.start_as_current_span("cache_lookup"): - pass - - with tracer.start_as_current_span("response_formatting") as resp_span: - resp_span.set_attribute("llm.tokens", 150) - - with tracer.start_as_current_span("http_response"): - pass - - # Clean up - provider.shutdown() - - # Verify all spans were captured by the unfiltered exporter - all_spans = all_spans_exporter.get_finished_spans() - all_span_names = [span.name for span in all_spans] - - assert len(all_spans) == 6 - assert "user_request" in all_span_names - assert "database_query" in all_span_names - assert "gen_ai.completion" in all_span_names - assert "cache_lookup" in all_span_names - assert "response_formatting" in all_span_names - assert "http_response" in all_span_names - - # Verify only LLM spans were captured by the filtered exporter - filtered_spans = filtered_spans_exporter.get_finished_spans() - filtered_span_names = [span.name for span in filtered_spans] - - assert len(filtered_spans) == 2 - assert "user_request" not in filtered_span_names # root span - assert "gen_ai.completion" in filtered_span_names # LLM name - assert "response_formatting" in filtered_span_names # LLM attribute - - def test_custom_filter_is_root_span(self): - from braintrust.otel import AISpanProcessor, is_root_span - from opentelemetry.sdk.trace import TracerProvider - from opentelemetry.sdk.trace.export import SimpleSpanProcessor - from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter - - memory_exporter = InMemorySpanExporter() - processor = AISpanProcessor(SimpleSpanProcessor(memory_exporter), custom_filter=is_root_span) - provider = TracerProvider() - provider.add_span_processor(processor) - tracer = provider.get_tracer("test-braintrust-root-filter") - - with tracer.start_as_current_span("root_span"): - with tracer.start_as_current_span("child_span"): - pass - - provider.shutdown() - spans = memory_exporter.get_finished_spans() - names = [span.name for span in spans] - assert "root_span" in names - assert "child_span" not in names - -def test_parent_from_headers_invalid_inputs(): - """Test parent_from_headers with various invalid inputs.""" - if not _check_otel_installed(): - pytest.skip("OpenTelemetry SDK not fully installed, skipping test") - - from braintrust.otel import parent_from_headers - - # Test 1: Empty headers - result = parent_from_headers({}) - assert result is None - - # Test 2: Invalid traceparent (malformed) - result = parent_from_headers({"traceparent": "invalid"}) - assert result is None - - # Test 3: Valid traceparent but invalid braintrust.parent format - result = parent_from_headers( - { - "traceparent": "00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01", - "baggage": "braintrust.parent=invalid_format", - } - ) - assert result is None - - # Test 4: Empty project_id - result = parent_from_headers( - { - "traceparent": "00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01", - "baggage": "braintrust.parent=project_id:", - } - ) - assert result is None - - # Test 5: Empty project_name - result = parent_from_headers( - { - "traceparent": "00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01", - "baggage": "braintrust.parent=project_name:", - } - ) - assert result is None - - # Test 6: Empty experiment_id - result = parent_from_headers( - { - "traceparent": "00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01", - "baggage": "braintrust.parent=experiment_id:", - } - ) - assert result is None - - # Test 7: Invalid trace_id length (too short) - result = parent_from_headers( - {"traceparent": "00-4bf92f3577b34da6-00f067aa0ba902b7-01", "baggage": "braintrust.parent=project_name:test"} - ) - assert result is None - - # Test 8: Invalid span_id length (too short) - result = parent_from_headers( - { - "traceparent": "00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa-01", - "baggage": "braintrust.parent=project_name:test", - } - ) - assert result is None - - -def test_parent_from_headers_valid_input(): - """Test parent_from_headers with valid inputs.""" - if not _check_otel_installed(): - pytest.skip("OpenTelemetry SDK not fully installed, skipping test") - - from braintrust.otel import parent_from_headers - - # Test with valid project_name - result = parent_from_headers( - { - "traceparent": "00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01", - "baggage": "braintrust.parent=project_name:test-project", - } - ) - assert result is not None - # Result is base64 encoded, so just check it's a non-empty string - assert isinstance(result, str) - assert len(result) > 0 - - # Test with valid project_id - result = parent_from_headers( - { - "traceparent": "00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01", - "baggage": "braintrust.parent=project_id:abc123", - } - ) - assert result is not None - assert isinstance(result, str) - assert len(result) > 0 - - # Test with valid experiment_id - result = parent_from_headers( - { - "traceparent": "00-4bf92f3577b34da6a3ce929d0e0e4736-00f067aa0ba902b7-01", - "baggage": "braintrust.parent=experiment_id:exp-456", - } - ) - assert result is not None - assert isinstance(result, str) - assert len(result) > 0 - - -def test_add_parent_to_baggage(): - """Test add_parent_to_baggage function.""" - if not _check_otel_installed(): - pytest.skip("OpenTelemetry SDK not fully installed, skipping test") - - from braintrust.otel import add_parent_to_baggage - from opentelemetry import baggage, context - - # Test adding parent to baggage - token = add_parent_to_baggage("project_name:test-project") - assert token is not None - - # Verify it's in baggage - parent_value = baggage.get_baggage("braintrust.parent") - assert parent_value == "project_name:test-project" - - # Clean up - context.detach(token) - - -def test_add_span_parent_to_baggage(): - """Test add_span_parent_to_baggage function.""" - if not _check_otel_installed(): - pytest.skip("OpenTelemetry SDK not fully installed, skipping test") - - from braintrust.otel import add_span_parent_to_baggage - from opentelemetry import baggage, context, trace - from opentelemetry.sdk.trace import TracerProvider - - # Setup tracer - provider = TracerProvider() - trace.set_tracer_provider(provider) - tracer = trace.get_tracer(__name__) - - # Test with span that has braintrust.parent attribute - with tracer.start_as_current_span("test_span") as span: - span.set_attribute("braintrust.parent", "project_name:test") - - token = add_span_parent_to_baggage(span) - assert token is not None - - # Verify it's in baggage - parent_value = baggage.get_baggage("braintrust.parent") - assert parent_value == "project_name:test" - - context.detach(token) - - # Test with span that doesn't have braintrust.parent attribute (should return None and warn) - with tracer.start_as_current_span("test_span_no_attr") as span: - token = add_span_parent_to_baggage(span) - assert token is None - - # Test with None span (should return None and warn) - token = add_span_parent_to_baggage(None) - assert token is None - - -def test_parent_from_headers_with_custom_propagator(): - """Test parent_from_headers with a custom propagator.""" - if not _check_otel_installed(): - pytest.skip("OpenTelemetry SDK not fully installed, skipping test") - - from braintrust.otel import parent_from_headers - from opentelemetry import baggage as otel_baggage - from opentelemetry import context as otel_context - from opentelemetry import trace - from opentelemetry.propagators.textmap import CarrierT, Getter, TextMapPropagator, default_getter - from opentelemetry.trace import NonRecordingSpan, SpanContext, TraceFlags - - class CustomHeaderPropagator(TextMapPropagator): - """Custom propagator that reads trace context from X-Custom-* headers.""" - - def extract( - self, - carrier: CarrierT, - context: otel_context.Context | None = None, - getter: Getter = default_getter, - ) -> otel_context.Context: - if context is None: - context = otel_context.get_current() - - trace_id = getter.get(carrier, "X-Custom-Trace-Id") - span_id = getter.get(carrier, "X-Custom-Span-Id") - - if trace_id and span_id: - trace_id_list = trace_id if isinstance(trace_id, list) else [trace_id] - span_id_list = span_id if isinstance(span_id, list) else [span_id] - - span_context = SpanContext( - trace_id=int(trace_id_list[0], 16), - span_id=int(span_id_list[0], 16), - is_remote=True, - trace_flags=TraceFlags.SAMPLED, - ) - span = NonRecordingSpan(span_context) - context = trace.set_span_in_context(span, context) - - # Also extract baggage from standard baggage header - baggage_header = getter.get(carrier, "baggage") - if baggage_header: - baggage_list = baggage_header if isinstance(baggage_header, list) else [baggage_header] - for item in baggage_list[0].split(","): - if "=" in item: - key, value = item.split("=", 1) - context = otel_baggage.set_baggage(key.strip(), value.strip(), context) - - return context - - def inject(self, carrier, context=None, setter=None): - pass # Not needed for this test - - @property - def fields(self): - return {"X-Custom-Trace-Id", "X-Custom-Span-Id", "baggage"} - - propagator = CustomHeaderPropagator() - - # Custom header format - headers = { - "X-Custom-Trace-Id": "4bf92f3577b34da6a3ce929d0e0e4736", - "X-Custom-Span-Id": "00f067aa0ba902b7", - "baggage": "braintrust.parent=project_name:test-project", - } - - result = parent_from_headers(headers, propagator=propagator) - assert result is not None - assert isinstance(result, str) - assert len(result) > 0 diff --git a/py/src/braintrust/test_queue.py b/py/src/braintrust/test_queue.py deleted file mode 100644 index ab26e46ab..000000000 --- a/py/src/braintrust/test_queue.py +++ /dev/null @@ -1,281 +0,0 @@ -import asyncio -import threading -import time - -import pytest -from braintrust.queue import DEFAULT_QUEUE_SIZE, LogQueue - - -def test_log_queue_basic_operations(): - """Test basic push/pop operations and size reporting of LogQueue""" - queue = LogQueue(maxsize=5) - - # Test empty queue - items = queue.drain_all() - assert items == [] - assert queue.size() == 0 - - # Test adding items - queue.put("item1") - queue.put("item2") - assert queue.size() == 2 - - # Test draining items - items = queue.drain_all() - assert items == ["item1", "item2"] - - # Queue should be empty after draining - items = queue.drain_all() - assert items == [] - assert queue.size() == 0 - - -def test_log_queue_drop_behavior(): - """Test queue drops oldest items when full, including single and multiple drops""" - # Test basic drop behavior with size 2 - queue = LogQueue(maxsize=2) - # Enable size limit enforcement for this test - queue.enforce_queue_size_limit(True) - - # Fill queue to capacity - d1 = queue.put("item1") - d2 = queue.put("item2") - assert not d1 - assert not d2 - - # Adding more should drop the oldest items (with enforcement enabled) - d3 = queue.put("item3") - assert d3 == ["item1"] # Oldest item is dropped - - d4 = queue.put("item4") - assert d4 == ["item2"] # Next oldest item is dropped - - # Queue should contain the newest items - items = queue.drain_all() - assert items == ["item3", "item4"] - - # Test size limit with maxsize=1 - queue_small = LogQueue(maxsize=1) - queue_small.enforce_queue_size_limit(True) - - d1 = queue_small.put("item1") - assert d1 == [] - assert queue_small.size() == 1 - - # Adding another item should drop the oldest item (with enforcement enabled) - d2 = queue_small.put("item2") - assert d2 == ["item1"] # Oldest item is dropped - assert queue_small.size() == 1 - - items = queue_small.drain_all() - assert items == ["item2"] # Newest item remains - - # Test multiple drops in sequence - queue_multi = LogQueue(maxsize=2) - queue_multi.enforce_queue_size_limit(True) - - # Fill queue - queue_multi.put("item1") - queue_multi.put("item2") - - # Add multiple items that will cause drops - dropped1 = queue_multi.put("item3") - dropped2 = queue_multi.put("item4") - - assert dropped1 == ["item1"] # Oldest items are dropped - assert dropped2 == ["item2"] # Next oldest items are dropped - - # Queue should contain the newest items - items = queue_multi.drain_all() - assert items == ["item3", "item4"] - - -def test_log_queue_wait_for_items_semaphore_reset(): - """Test that wait_for_items semaphore resets after drain, not accumulates""" - queue = LogQueue(maxsize=5) - - assert queue.wait_for_items(timeout=0.05) is False - - # multiple puts should start - queue.put("item1") - queue.put("item2") - queue.put("item3") - - # First wait should succeed - assert queue.wait_for_items(timeout=0.05) is True - items = queue.drain_all() - assert len(items) == 3 - - # After drain, should block - assert queue.wait_for_items(timeout=0.05) is False - - -def test_log_queue_default_size(): - queue = LogQueue(maxsize=0) - assert queue.maxsize == DEFAULT_QUEUE_SIZE - - # Should be able to add many items without drops (up to 5000) - for i in range(100): - dropped = queue.put(f"item{i}") - assert dropped == [] # No drops when under capacity - - # All items should be there - items = queue.drain_all() - assert len(items) == 100 - assert items[0] == "item0" - assert items[99] == "item99" - - # Test negative maxsize also defaults - queue_neg = LogQueue(maxsize=-5) - assert queue_neg.maxsize == DEFAULT_QUEUE_SIZE - - # Should be able to add items without drops (when under capacity) - for i in range(10): - dropped = queue_neg.put(f"item{i}") - assert dropped == [] - - assert queue_neg.size() == 10 - - items = queue_neg.drain_all() - assert len(items) == 10 - - -@pytest.mark.asyncio -async def test_queue_never_blocks_event_loop(): - """Test that queue operations don't block the asyncio event loop""" - queue = LogQueue(maxsize=1) - queue.enforce_queue_size_limit(True) # Enable enforcement - - # Fill the queue - queue.put("item1") - - # Flag to prove event loop stays responsive - flag_set = False - - async def set_flag(): - nonlocal flag_set - flag_set = True - - # Start queue operation and flag setter concurrently - flag_task = asyncio.create_task(set_flag()) - - # This should not block since we drop when full - dropped = queue.put("item2") - assert dropped == ["item1"] # Oldest item is dropped - - # Wait for flag task to complete - await flag_task - - # Flag should be set, proving event loop wasn't blocked - assert flag_set is True - - # Clean up - queue.drain_all() - - -@pytest.mark.asyncio -async def test_queue_concurrent_drops_and_drains(): - """Test concurrent producer/consumer with drops and drains in asyncio""" - queue = LogQueue(maxsize=3) - queue.enforce_queue_size_limit(True) # Enable enforcement to ensure drops - - total_pushed = 0 - total_dropped = 0 - total_drained = 0 - - async def producer(): - nonlocal total_pushed, total_dropped - # Push many items to guarantee some drops - for i in range(15): - dropped = queue.put(f"item{i}") - total_pushed += 1 - total_dropped += len(dropped) - - async def consumer(): - nonlocal total_drained - # Periodically drain, but not fast enough to prevent all drops - for _ in range(3): - await asyncio.sleep(0) # Yield control - items = queue.drain_all() - total_drained += len(items) - - # Run both concurrently - await asyncio.gather(producer(), consumer()) - - # Final drain to get remaining items - final_items = queue.drain_all() - total_drained += len(final_items) - - # Verify the accounting works out - assert total_pushed == 15 - assert total_dropped > 0 # Some items should have been dropped - assert total_drained > 0 # Some items should have been drained - assert total_drained + total_dropped == total_pushed # Conservation of items - - -def test_log_queue_thread_safety(): - """Test that queue operations are thread-safe under concurrent access""" - - queue = LogQueue(maxsize=5) - total_added = 0 - total_dropped = 0 - total_drained = 0 - errors = [] - - def producer(thread_id): - nonlocal total_added, total_dropped - try: - for i in range(20): - dropped = queue.put(f"t{thread_id}_item{i}") - with threading.Lock(): # Protect shared counters - total_added += 1 - total_dropped += len(dropped) - time.sleep(0.001) # Small delay to encourage interleaving - except Exception as e: - errors.append(f"Producer {thread_id}: {e}") - - def consumer(): - nonlocal total_drained - try: - for _ in range(10): - time.sleep(0.005) # Let producers add some items - items = queue.drain_all() - with threading.Lock(): # Protect shared counter - total_drained += len(items) - except Exception as e: - errors.append(f"Consumer: {e}") - - # Start multiple producer threads and one consumer - threads = [] - for i in range(3): - t = threading.Thread(target=producer, args=(i,)) - threads.append(t) - t.start() - - consumer_thread = threading.Thread(target=consumer) - threads.append(consumer_thread) - consumer_thread.start() - - # Wait for all threads to complete - for t in threads: - t.join() - - # Final drain to get any remaining items - final_items = queue.drain_all() - total_drained += len(final_items) - - # Check for errors - assert not errors, f"Thread safety errors: {errors}" - - # Verify conservation of items - assert total_added == 60 # 3 threads * 20 items each - assert total_dropped >= 0 - assert total_drained >= 0 - - # With enforcement disabled, items are silently dropped by deque - # We can only verify that we drained at most maxsize items at any time - assert total_drained <= total_added - assert total_dropped == 0 # No tracked drops with enforcement disabled - - # Verify queue is in a consistent state - assert queue.size() == 0 # Should be empty after final drain diff --git a/py/src/braintrust/test_score.py b/py/src/braintrust/test_score.py deleted file mode 100644 index 53fccba70..000000000 --- a/py/src/braintrust/test_score.py +++ /dev/null @@ -1,155 +0,0 @@ -import json -import unittest - -from .score import Score - - -class TestScore(unittest.TestCase): - def test_as_dict_includes_all_required_fields(self): - """Test that as_dict() includes name, score, and metadata fields.""" - score = Score(name="test_scorer", score=0.85, metadata={"key": "value"}) - result = score.as_dict() - - self.assertIn("name", result) - self.assertIn("score", result) - self.assertIn("metadata", result) - - self.assertEqual(result["name"], "test_scorer") - self.assertEqual(result["score"], 0.85) - self.assertEqual(result["metadata"], {"key": "value"}) - - def test_as_dict_with_null_score(self): - """Test that as_dict() works correctly with null score.""" - score = Score(name="null_scorer", score=None, metadata={}) - result = score.as_dict() - - self.assertEqual(result["name"], "null_scorer") - self.assertIsNone(result["score"]) - self.assertEqual(result["metadata"], {}) - - def test_as_dict_with_empty_metadata(self): - """Test that as_dict() works correctly with empty metadata.""" - score = Score(name="empty_metadata_scorer", score=1.0) - result = score.as_dict() - - self.assertEqual(result["name"], "empty_metadata_scorer") - self.assertEqual(result["score"], 1.0) - self.assertEqual(result["metadata"], {}) - - def test_as_dict_with_complex_metadata(self): - """Test that as_dict() works correctly with complex nested metadata.""" - complex_metadata = { - "reason": "Test reason", - "details": {"nested": {"deeply": "value"}}, - "list": [1, 2, 3], - "bool": True, - } - score = Score(name="complex_scorer", score=0.5, metadata=complex_metadata) - result = score.as_dict() - - self.assertEqual(result["name"], "complex_scorer") - self.assertEqual(result["score"], 0.5) - self.assertEqual(result["metadata"], complex_metadata) - - def test_as_json_serialization(self): - """Test that as_json() produces valid JSON string.""" - score = Score(name="json_scorer", score=0.75, metadata={"test": "data"}) - json_str = score.as_json() - - # Should be valid JSON - parsed = json.loads(json_str) - - self.assertEqual(parsed["name"], "json_scorer") - self.assertEqual(parsed["score"], 0.75) - self.assertEqual(parsed["metadata"], {"test": "data"}) - - def test_from_dict_round_trip(self): - """Test that Score can be serialized to dict and deserialized back.""" - original = Score(name="round_trip_scorer", score=0.95, metadata={"info": "test"}) - - # Serialize to dict - as_dict = original.as_dict() - - # Deserialize from dict - restored = Score.from_dict(as_dict) - - self.assertEqual(restored.name, original.name) - self.assertEqual(restored.score, original.score) - self.assertEqual(restored.metadata, original.metadata) - - def test_array_of_scores_serialization(self): - """Test that arrays of Score objects can be serialized correctly.""" - scores = [ - Score(name="score_1", score=0.8, metadata={"index": 1}), - Score(name="score_2", score=0.6, metadata={"index": 2}), - Score(name="score_3", score=None, metadata={}), - ] - - # Serialize each score - serialized = [s.as_dict() for s in scores] - - # Check that all scores have required fields - for i, s_dict in enumerate(serialized): - self.assertIn("name", s_dict) - self.assertIn("score", s_dict) - self.assertIn("metadata", s_dict) - self.assertEqual(s_dict["name"], f"score_{i + 1}") - - # Check specific values - self.assertEqual(serialized[0]["score"], 0.8) - self.assertEqual(serialized[1]["score"], 0.6) - self.assertIsNone(serialized[2]["score"]) - - def test_array_of_scores_json_serialization(self): - """Test that arrays of Score objects can be JSON serialized.""" - scores = [ - Score(name="json_score_1", score=0.9), - Score(name="json_score_2", score=0.7), - ] - - # Serialize to JSON - serialized = [s.as_dict() for s in scores] - json_str = json.dumps(serialized) - - # Parse back - parsed = json.loads(json_str) - - self.assertEqual(len(parsed), 2) - self.assertEqual(parsed[0]["name"], "json_score_1") - self.assertEqual(parsed[0]["score"], 0.9) - self.assertEqual(parsed[1]["name"], "json_score_2") - self.assertEqual(parsed[1]["score"], 0.7) - - def test_score_validation_enforces_bounds(self): - """Test that Score validates score values are between 0 and 1.""" - # Valid scores - Score(name="valid_0", score=0.0) - Score(name="valid_1", score=1.0) - Score(name="valid_mid", score=0.5) - Score(name="valid_null", score=None) - - # Invalid scores - with self.assertRaises(ValueError): - Score(name="invalid_negative", score=-0.1) - - with self.assertRaises(ValueError): - Score(name="invalid_over_one", score=1.1) - - def test_score_does_not_include_deprecated_error_field(self): - """Test that as_dict() does not include the deprecated error field.""" - score = Score(name="test_scorer", score=0.5) - result = score.as_dict() - - # The error field should not be in the serialized output - self.assertNotIn("error", result) - - # Even if error was set (though deprecated), it shouldn't be in as_dict - score_with_error = Score(name="error_scorer", score=0.5) - score_with_error.error = Exception("test") # Set after construction - result_with_error = score_with_error.as_dict() - - self.assertNotIn("error", result_with_error) - - -if __name__ == "__main__": - unittest.main() diff --git a/py/src/braintrust/test_serializable_data_class.py b/py/src/braintrust/test_serializable_data_class.py deleted file mode 100644 index 0cade6aee..000000000 --- a/py/src/braintrust/test_serializable_data_class.py +++ /dev/null @@ -1,62 +0,0 @@ -import unittest -from dataclasses import dataclass -from typing import List, Optional - -from .serializable_data_class import SerializableDataClass - - -@dataclass -class PromptData(SerializableDataClass): - prompt: Optional[str] = None - options: Optional[dict] = None - - -@dataclass -class PromptSchema(SerializableDataClass): - id: str - project_id: str - _xact_id: str - name: str - slug: str - description: Optional[str] - prompt_data: PromptData - tags: Optional[List[str]] - - -class TestSerializableDataClass(unittest.TestCase): - def test_from_dict_deep_with_none_values(self): - """Test that from_dict_deep correctly handles None values in nested objects.""" - test_dict = { - "id": "456", - "project_id": "123", - "_xact_id": "789", - "name": "test-prompt", - "slug": "test-prompt", - "description": None, - "prompt_data": {"prompt": None, "options": None}, - "tags": None, - } - - prompt = PromptSchema.from_dict_deep(test_dict) - - # Verify all fields were set correctly. - self.assertEqual(prompt.id, "456") - self.assertEqual(prompt.project_id, "123") - self.assertEqual(prompt._xact_id, "789") - self.assertEqual(prompt.name, "test-prompt") - self.assertEqual(prompt.slug, "test-prompt") - self.assertIsNone(prompt.description) - self.assertIsNone(prompt.tags) - - # Verify nested object was created and its fields are None. - self.assertIsInstance(prompt.prompt_data, PromptData) - self.assertIsNone(prompt.prompt_data.prompt) - self.assertIsNone(prompt.prompt_data.options) - - # Verify round-trip serialization works. - round_trip = PromptSchema.from_dict_deep(prompt.as_dict()) - self.assertEqual(round_trip.as_dict(), test_dict) - - -if __name__ == "__main__": - unittest.main() diff --git a/py/src/braintrust/test_span_cache.py b/py/src/braintrust/test_span_cache.py deleted file mode 100644 index fc0b6c7ef..000000000 --- a/py/src/braintrust/test_span_cache.py +++ /dev/null @@ -1,344 +0,0 @@ -"""Tests for SpanCache (disk-based cache).""" - - -from braintrust.span_cache import CachedSpan, SpanCache - - -def test_span_cache_write_and_read(): - """Test storing and retrieving spans by rootSpanId.""" - cache = SpanCache() - cache.start() # Start for testing (cache is disabled by default) - - root_span_id = "root-123" - span1 = CachedSpan( - span_id="span-1", - input={"text": "hello"}, - output={"response": "world"}, - ) - span2 = CachedSpan( - span_id="span-2", - input={"text": "foo"}, - output={"response": "bar"}, - ) - - cache.queue_write(root_span_id, span1.span_id, span1) - cache.queue_write(root_span_id, span2.span_id, span2) - - spans = cache.get_by_root_span_id(root_span_id) - assert spans is not None - assert len(spans) == 2 - - span_ids = {s.span_id for s in spans} - assert "span-1" in span_ids - assert "span-2" in span_ids - - cache.stop() - cache.dispose() - - -def test_span_cache_return_none_for_unknown(): - """Test that unknown rootSpanId returns None.""" - cache = SpanCache() - cache.start() - - spans = cache.get_by_root_span_id("nonexistent") - assert spans is None - - cache.stop() - cache.dispose() - - -def test_span_cache_merge_on_duplicate_writes(): - """Test that subsequent writes to same spanId merge data.""" - cache = SpanCache() - cache.start() - - root_span_id = "root-123" - span_id = "span-1" - - cache.queue_write( - root_span_id, - span_id, - CachedSpan(span_id=span_id, input={"text": "hello"}), - ) - - cache.queue_write( - root_span_id, - span_id, - CachedSpan(span_id=span_id, output={"response": "world"}), - ) - - spans = cache.get_by_root_span_id(root_span_id) - assert spans is not None - assert len(spans) == 1 - assert spans[0].span_id == span_id - assert spans[0].input == {"text": "hello"} - assert spans[0].output == {"response": "world"} - - cache.stop() - cache.dispose() - - -def test_span_cache_merge_metadata(): - """Test that metadata objects are merged.""" - cache = SpanCache() - cache.start() - - root_span_id = "root-123" - span_id = "span-1" - - cache.queue_write( - root_span_id, - span_id, - CachedSpan(span_id=span_id, metadata={"key1": "value1"}), - ) - - cache.queue_write( - root_span_id, - span_id, - CachedSpan(span_id=span_id, metadata={"key2": "value2"}), - ) - - spans = cache.get_by_root_span_id(root_span_id) - assert spans is not None - assert spans[0].metadata == {"key1": "value1", "key2": "value2"} - - cache.stop() - cache.dispose() - - -def test_span_cache_has(): - """Test the has() method.""" - cache = SpanCache() - cache.start() - - cache.queue_write("root-123", "span-1", CachedSpan(span_id="span-1")) - assert cache.has("root-123") is True - assert cache.has("nonexistent") is False - - cache.stop() - cache.dispose() - - -def test_span_cache_clear(): - """Test clearing spans for a specific rootSpanId.""" - cache = SpanCache() - cache.start() - - cache.queue_write("root-1", "span-1", CachedSpan(span_id="span-1")) - cache.queue_write("root-2", "span-2", CachedSpan(span_id="span-2")) - - cache.clear("root-1") - - assert cache.has("root-1") is False - assert cache.has("root-2") is True - - cache.stop() - cache.dispose() - - -def test_span_cache_clear_all(): - """Test clearing all cached spans.""" - cache = SpanCache() - cache.start() - - cache.queue_write("root-1", "span-1", CachedSpan(span_id="span-1")) - cache.queue_write("root-2", "span-2", CachedSpan(span_id="span-2")) - - cache.clear_all() - - assert cache.size == 0 - - cache.stop() - cache.dispose() - - -def test_span_cache_size(): - """Test the size property.""" - cache = SpanCache() - cache.start() - - assert cache.size == 0 - - cache.queue_write("root-1", "span-1", CachedSpan(span_id="span-1")) - assert cache.size == 1 - - cache.queue_write("root-1", "span-2", CachedSpan(span_id="span-2")) # Same root - assert cache.size == 1 - - cache.queue_write("root-2", "span-3", CachedSpan(span_id="span-3")) # Different root - assert cache.size == 2 - - cache.stop() - cache.dispose() - - -def test_span_cache_dispose(): - """Test that dispose cleans up and allows reuse.""" - cache = SpanCache() - cache.start() - - cache.queue_write("root-1", "span-1", CachedSpan(span_id="span-1")) - assert cache.size == 1 - - # Stop first to decrement refcount, then dispose - cache.stop() - cache.dispose() - - assert cache.size == 0 - assert cache.has("root-1") is False - - # Should be able to write again after dispose (if we start again) - cache.start() - cache.queue_write("root-2", "span-2", CachedSpan(span_id="span-2")) - assert cache.size == 1 - - cache.stop() - cache.dispose() - - -def test_span_cache_disable(): - """Test that disable() prevents writes.""" - cache = SpanCache() - cache.start() - - cache.queue_write("root-1", "span-1", CachedSpan(span_id="span-1")) - assert cache.size == 1 - - cache.disable() - - # Writes after disable should be no-ops - cache.queue_write("root-2", "span-2", CachedSpan(span_id="span-2")) - assert cache.size == 1 # Still 1, not 2 - - cache.stop() - cache.dispose() - - -def test_span_cache_disabled_getter(): - """Test the disabled property.""" - # Cache is disabled by default until start() is called - cache = SpanCache() - assert cache.disabled is True - - cache.start() - assert cache.disabled is False - - cache.disable() - assert cache.disabled is True - - cache.dispose() - - -def test_span_cache_disabled_from_constructor(): - """Test that cache can be disabled via constructor.""" - cache = SpanCache(disabled=True) - assert cache.disabled is True - - # Writes should be no-ops - cache.queue_write("root-1", "span-1", CachedSpan(span_id="span-1")) - assert cache.size == 0 - assert cache.get_by_root_span_id("root-1") is None - - cache.dispose() - - -def test_span_cache_start_stop_lifecycle(): - """Test that stop() allows start() to work again.""" - cache = SpanCache() - - # Initially disabled by default - assert cache.disabled is True - - # Start for first "eval" - cache.start() - assert cache.disabled is False - cache.queue_write("root-1", "span-1", CachedSpan(span_id="span-1")) - assert cache.size == 1 - - # Stop after first "eval" - cache.stop() - cache.dispose() - assert cache.disabled is True - - # Start for second "eval" - should work! - cache.start() - assert cache.disabled is False - cache.queue_write("root-2", "span-2", CachedSpan(span_id="span-2")) - assert cache.size == 1 - - cache.stop() - cache.dispose() - - -def test_span_cache_disable_prevents_start(): - """Test that disable() prevents start() from working.""" - cache = SpanCache() - - # Simulate disable being called - cache.disable() - assert cache.disabled is True - - # start() should be a no-op after disable() - cache.start() - assert cache.disabled is True - - # Writes should still be no-ops - cache.queue_write("root-1", "span-1", CachedSpan(span_id="span-1")) - assert cache.size == 0 - - cache.dispose() - - -def test_span_cache_parallel_eval_refcount(): - """Test reference counting for parallel evals.""" - cache = SpanCache() - - # Simulate two evals starting - cache.start() # Eval 1 - assert cache.disabled is False - - cache.start() # Eval 2 - assert cache.disabled is False - - # Write data from both evals - cache.queue_write("root-1", "span-1", CachedSpan(span_id="span-1")) - cache.queue_write("root-2", "span-2", CachedSpan(span_id="span-2")) - assert cache.size == 2 - - # Eval 1 finishes first - cache.dispose() # Should NOT dispose (refcount = 2) - cache.stop() # Decrements to 1 - - # Cache should still be enabled and data intact - assert cache.disabled is False - assert cache.size == 2 - assert cache.get_by_root_span_id("root-1") is not None - assert cache.get_by_root_span_id("root-2") is not None - - # Eval 2 finishes - cache.dispose() # Should NOT dispose yet (refcount = 1) - cache.stop() # Decrements to 0, disables cache - - # Now cache should be disabled - assert cache.disabled is True - - # Final dispose should now work - cache.dispose() # NOW it disposes (refcount = 0) - assert cache.size == 0 - - -def test_span_cache_refcount_underflow(): - """Test that refcount handles underflow gracefully.""" - cache = SpanCache() - - # Call stop without start - cache.stop() - - # Should work normally after - cache.start() - cache.queue_write("root-1", "span-1", CachedSpan(span_id="span-1")) - assert cache.size == 1 - - cache.stop() - cache.dispose() diff --git a/py/src/braintrust/test_span_components.py b/py/src/braintrust/test_span_components.py deleted file mode 100644 index 51b89db24..000000000 --- a/py/src/braintrust/test_span_components.py +++ /dev/null @@ -1,404 +0,0 @@ -""" -Comprehensive tests for SpanComponents versions V3 and V4. -Tests serialization, deserialization, OTEL compatibility, and backward compatibility. -""" - -from uuid import uuid4 - -import pytest -from braintrust.id_gen import OTELIDGenerator -from braintrust.span_identifier_v3 import SpanComponentsV3, SpanObjectTypeV3 -from braintrust.span_identifier_v4 import SpanComponentsV4 - - -class TestSpanComponentsV3: - """Test SpanComponentsV3 functionality.""" - - def test_basic_serialization(self): - """Test basic V3 serialization/deserialization with UUIDs.""" - components = SpanComponentsV3( - object_type=SpanObjectTypeV3.PROJECT_LOGS, - object_id=str(uuid4()), - row_id=str(uuid4()), - span_id=str(uuid4()), - root_span_id=str(uuid4()), - ) - - exported = components.to_str() - imported = SpanComponentsV3.from_str(exported) - - assert imported.object_type == components.object_type - assert imported.object_id == components.object_id - assert imported.row_id == components.row_id - assert imported.span_id == components.span_id - assert imported.root_span_id == components.root_span_id - - def test_with_metadata(self): - """Test V3 with additional metadata.""" - components = SpanComponentsV3( - object_type=SpanObjectTypeV3.EXPERIMENT, - object_id=str(uuid4()), - propagated_event={"key": "value", "nested": {"a": 1}}, - ) - - exported = components.to_str() - imported = SpanComponentsV3.from_str(exported) - - assert imported.object_type == components.object_type - assert imported.object_id == components.object_id - assert imported.propagated_event == components.propagated_event - - def test_otel_ids_fail_roundtrip(self): - """Test that V3 fails to preserve OTEL hex strings for 16-byte IDs (converts to UUID format).""" - otel_gen = OTELIDGenerator() - trace_id = otel_gen.get_trace_id() # 32-char hex (16 bytes) - span_id = otel_gen.get_span_id() # 16-char hex (8 bytes) - - # Use 16-byte hex strings for object_id and root_span_id to see UUID conversion - components = SpanComponentsV3( - object_type=SpanObjectTypeV3.PROJECT_LOGS, - object_id=trace_id, # 16-byte hex should get converted to UUID format - row_id="test-row-id", - span_id=span_id, # 8-byte hex might be preserved - root_span_id=trace_id, # 16-byte hex should get converted to UUID format - ) - - exported = components.to_str() - imported = SpanComponentsV3.from_str(exported) - - # V3 should convert 16-byte hex strings to UUID format (with dashes) - # Note: span_id (8 bytes) may or may not be converted depending on whether UUID parsing succeeds - assert imported.root_span_id != trace_id # 16-byte should have dashes added - - -class TestSpanComponentsV4: - """Test SpanComponentsV4 functionality and OTEL compatibility.""" - - def test_otel_hex_strings_preserved(self): - """Test that V4 preserves OTEL hex strings exactly.""" - otel_gen = OTELIDGenerator() - trace_id = otel_gen.get_trace_id() # 32-char hex - span_id = otel_gen.get_span_id() # 16-char hex - - components = SpanComponentsV4( - object_type=SpanObjectTypeV3.PROJECT_LOGS, - object_id="test-project-id", - row_id="test-row-id", - span_id=span_id, - root_span_id=trace_id, - ) - - exported = components.to_str() - imported = SpanComponentsV4.from_str(exported) - - # V4 should preserve hex strings exactly - assert imported.span_id == span_id - assert imported.root_span_id == trace_id - assert imported.object_type == components.object_type - assert imported.object_id == components.object_id - assert imported.row_id == components.row_id - - def test_uuid_strings_stored_in_json(self): - """Test that V4 stores UUID strings in JSON (not converted to binary).""" - uuid_object_id = str(uuid4()) - uuid_span_id = str(uuid4()) - uuid_root_span_id = str(uuid4()) - - components = SpanComponentsV4( - object_type=SpanObjectTypeV3.PROJECT_LOGS, - object_id=uuid_object_id, - row_id="test-row-id", - span_id=uuid_span_id, - root_span_id=uuid_root_span_id, - ) - - exported = components.to_str() - imported = SpanComponentsV4.from_str(exported) - - # V4 should preserve UUID strings exactly (stored in JSON, not converted) - assert imported.object_type == components.object_type - assert imported.object_id == uuid_object_id - assert imported.row_id == components.row_id - assert imported.span_id == uuid_span_id - assert imported.root_span_id == uuid_root_span_id - - def test_mixed_formats(self): - """Test V4 with mixed UUID and hex string formats.""" - uuid_object_id = str(uuid4()) # UUID format - otel_gen = OTELIDGenerator() - hex_span_id = otel_gen.get_span_id() # Hex format - hex_trace_id = otel_gen.get_trace_id() # Hex format - - components = SpanComponentsV4( - object_type=SpanObjectTypeV3.EXPERIMENT, - object_id=uuid_object_id, - row_id="test-row-id", - span_id=hex_span_id, - root_span_id=hex_trace_id, - ) - - exported = components.to_str() - imported = SpanComponentsV4.from_str(exported) - - # V4 preserves all strings exactly as provided (no conversion) - assert imported.object_id == uuid_object_id - assert imported.span_id == hex_span_id - assert imported.root_span_id == hex_trace_id - - def test_parse_interop_with_js_slug(self): - """Test that Python can parse slug generated by JavaScript.""" - # generated by this code in JS: - # const components = new SpanComponentsV4({ - # object_type: SpanObjectTypeV3.EXPERIMENT, - # object_id: 'js-test-experiment-id', - # row_id: 'js-test-row-id', - # span_id: 'abcdef1234567890', - # root_span_id: 'fedcba0987654321fedcba0987654321' - # }); - # console.log(components.toStr()); - js_slug = "BAECA6vN7xI0VniQBP7cugmHZUMh/ty6CYdlQyF7Im9iamVjdF9pZCI6ImpzLXRlc3QtZXhwZXJpbWVudC1pZCIsInJvd19pZCI6ImpzLXRlc3Qtcm93LWlkIn0=" - - # Create equivalent Python object - py_components = SpanComponentsV4( - object_type=SpanObjectTypeV3.EXPERIMENT, - object_id="js-test-experiment-id", - row_id="js-test-row-id", - span_id="abcdef1234567890", - root_span_id="fedcba0987654321fedcba0987654321", - ) - - # Python should generate the same slug - py_serialized = py_components.to_str() - assert py_serialized == js_slug - - # Python should be able to parse the JS-generated slug - parsed_from_js = SpanComponentsV4.from_str(js_slug) - assert parsed_from_js.object_type == py_components.object_type - assert parsed_from_js.object_id == py_components.object_id - assert parsed_from_js.row_id == py_components.row_id - assert parsed_from_js.span_id == py_components.span_id - assert parsed_from_js.root_span_id == py_components.root_span_id - - def test_with_metadata(self): - """Test V4 with additional metadata.""" - components = SpanComponentsV4( - object_type=SpanObjectTypeV3.PLAYGROUND_LOGS, - object_id="test-session-id", - propagated_event={"user": "test", "data": [1, 2, 3]}, - ) - - exported = components.to_str() - imported = SpanComponentsV4.from_str(exported) - - assert imported.object_type == components.object_type - assert imported.object_id == components.object_id - assert imported.propagated_event == components.propagated_event - - def test_non_serializable_ids_stored_in_json(self): - """Test that non-UUID/hex strings are stored in JSON portion.""" - components = SpanComponentsV4( - object_type=SpanObjectTypeV3.PROJECT_LOGS, - object_id="not-a-uuid-or-hex", # Will be stored in JSON - # Don't test row_id alone - if present, span_id and root_span_id must also be present - ) - - exported = components.to_str() - imported = SpanComponentsV4.from_str(exported) - - assert imported.object_id == "not-a-uuid-or-hex" - - -class TestBackwardCompatibility: - """Test backward compatibility between V3 and V4.""" - - def test_v4_can_read_v3_data(self): - """Test that V4 can read data serialized by V3.""" - # Create V3 component - v3_components = SpanComponentsV3( - object_type=SpanObjectTypeV3.PROJECT_LOGS, - object_id=str(uuid4()), - row_id=str(uuid4()), - span_id=str(uuid4()), - root_span_id=str(uuid4()), - propagated_event={"version": "v3"}, - ) - - # Serialize with V3 - v3_exported = v3_components.to_str() - - # Deserialize with V4 - v4_imported = SpanComponentsV4.from_str(v3_exported) - - assert v4_imported.object_type == v3_components.object_type - assert v4_imported.object_id == v3_components.object_id - assert v4_imported.row_id == v3_components.row_id - assert v4_imported.span_id == v3_components.span_id - assert v4_imported.root_span_id == v3_components.root_span_id - assert v4_imported.propagated_event == v3_components.propagated_event - - -class TestErrorHandling: - """Test error handling and edge cases.""" - - def test_invalid_object_type(self): - """Test that invalid object types raise errors.""" - with pytest.raises(AssertionError): - SpanComponentsV4( - object_type="invalid_type", # Should be SpanObjectTypeV3 enum - object_id="test-id", - ) - - def test_missing_required_fields(self): - """Test that missing required fields raise errors.""" - with pytest.raises(AssertionError): - SpanComponentsV4( - object_type=SpanObjectTypeV3.PROJECT_LOGS, - # Missing object_id or compute_object_metadata_args - ) - - def test_partial_span_ids(self): - """Test that partial span ID fields raise errors.""" - with pytest.raises(AssertionError): - SpanComponentsV4( - object_type=SpanObjectTypeV3.PROJECT_LOGS, - object_id="test-id", - row_id="test-row", - # Missing span_id and root_span_id - ) - - def test_invalid_base64(self): - """Test that invalid base64 strings raise errors.""" - with pytest.raises(Exception) as exc_info: - SpanComponentsV4.from_str("invalid-base64!") - - assert "not properly encoded" in str(exc_info.value) - - def test_corrupted_data(self): - """Test that corrupted serialized data raises errors.""" - import base64 - - # Create valid data then corrupt it - components = SpanComponentsV4(object_type=SpanObjectTypeV3.PROJECT_LOGS, object_id="test-id") - valid_exported = components.to_str() - - # Decode, corrupt, re-encode - decoded = base64.b64decode(valid_exported) - corrupted = decoded[:-5] + b"XXXXX" # Corrupt the end - corrupted_encoded = base64.b64encode(corrupted).decode() - - with pytest.raises(Exception) as exc_info: - SpanComponentsV4.from_str(corrupted_encoded) - - assert "not properly encoded" in str(exc_info.value) - - -class TestObjectIdFields: - """Test object_id_fields method.""" - - def test_experiment_object_id_fields(self): - """Test object_id_fields for experiment type.""" - components = SpanComponentsV4(object_type=SpanObjectTypeV3.EXPERIMENT, object_id="test-experiment-id") - - fields = components.object_id_fields() - assert fields == {"experiment_id": "test-experiment-id"} - - def test_project_logs_object_id_fields(self): - """Test object_id_fields for project_logs type.""" - components = SpanComponentsV4(object_type=SpanObjectTypeV3.PROJECT_LOGS, object_id="test-project-id") - - fields = components.object_id_fields() - assert fields == {"project_id": "test-project-id", "log_id": "g"} - - def test_playground_logs_object_id_fields(self): - """Test object_id_fields for playground_logs type.""" - components = SpanComponentsV4(object_type=SpanObjectTypeV3.PLAYGROUND_LOGS, object_id="test-session-id") - - fields = components.object_id_fields() - assert fields == {"prompt_session_id": "test-session-id", "log_id": "x"} - - def test_object_id_fields_without_object_id(self): - """Test that object_id_fields raises error without object_id.""" - components = SpanComponentsV4( - object_type=SpanObjectTypeV3.PROJECT_LOGS, compute_object_metadata_args={"key": "value"} - ) - - with pytest.raises(Exception) as exc_info: - components.object_id_fields() - - assert "cannot invoke `object_id_fields`" in str(exc_info.value) - - -class TestExportFormatSelection: - """Test that span export format is selected based on BRAINTRUST_OTEL_COMPAT environment variable.""" - - def test_export_format_based_on_env_variable(self): - """Test that export format changes based on BRAINTRUST_OTEL_COMPAT environment variable.""" - import os - - from braintrust.test_helpers import init_test_logger - - # Test with OTEL_COMPAT=false (should use V3) - original_env = os.environ.get("BRAINTRUST_OTEL_COMPAT") - try: - os.environ["BRAINTRUST_OTEL_COMPAT"] = "false" - - # Initialize test logger and create a span - l = init_test_logger("test_export_v3") - with l.start_span(name="test_span") as span: - export_v3_mode = span.export() - - # Verify it can be parsed by V3 - parsed_as_v3 = SpanComponentsV3.from_str(export_v3_mode) - assert parsed_as_v3 is not None - - # Test with OTEL_COMPAT=true (should use V4) - os.environ["BRAINTRUST_OTEL_COMPAT"] = "true" - - # Initialize test logger and create a span - l = init_test_logger("test_export_v4") - with l.start_span(name="test_span") as span: - export_v4_mode = span.export() - - # Verify it can be parsed by V4 - parsed_as_v4 = SpanComponentsV4.from_str(export_v4_mode) - assert parsed_as_v4 is not None - - # Both should be parseable by V4 (backward compatibility) - v4_from_v3 = SpanComponentsV4.from_str(export_v3_mode) - v4_from_v4 = SpanComponentsV4.from_str(export_v4_mode) - assert v4_from_v3 is not None - assert v4_from_v4 is not None - - finally: - # Clean up environment - if original_env is not None: - os.environ["BRAINTRUST_OTEL_COMPAT"] = original_env - elif "BRAINTRUST_OTEL_COMPAT" in os.environ: - del os.environ["BRAINTRUST_OTEL_COMPAT"] - - def test_export_uses_v3_by_default(self): - """Test that export uses V3 format by default when BRAINTRUST_OTEL_COMPAT is not set.""" - import os - - from braintrust.test_helpers import init_test_logger - - # Ensure environment variable is not set - original_env = os.environ.get("BRAINTRUST_OTEL_COMPAT") - try: - if "BRAINTRUST_OTEL_COMPAT" in os.environ: - del os.environ["BRAINTRUST_OTEL_COMPAT"] - - # Initialize test logger and create a span - l = init_test_logger("test_default_v3") - with l.start_span(name="test_span") as span: - export_default = span.export() - - # Should be parseable by V3 since V3 is the default - parsed_as_v3 = SpanComponentsV3.from_str(export_default) - assert parsed_as_v3 is not None - assert parsed_as_v3.object_type is not None - - finally: - # Restore environment - if original_env is not None: - os.environ["BRAINTRUST_OTEL_COMPAT"] = original_env diff --git a/py/src/braintrust/test_trace.py b/py/src/braintrust/test_trace.py deleted file mode 100644 index c1bfeb9aa..000000000 --- a/py/src/braintrust/test_trace.py +++ /dev/null @@ -1,391 +0,0 @@ -"""Tests for Trace functionality.""" - -import pytest -from braintrust.trace import CachedSpanFetcher, LocalTrace, SpanData - - -# Helper to create mock spans -def make_span(span_id: str, span_type: str, **extra) -> SpanData: - return SpanData( - span_id=span_id, - input={"text": f"input-{span_id}"}, - output={"text": f"output-{span_id}"}, - span_attributes={"type": span_type}, - **extra, - ) - - -class TestCachedSpanFetcher: - """Test CachedSpanFetcher caching behavior.""" - - @pytest.mark.asyncio - async def test_fetch_all_spans_without_filter(self): - """Test fetching all spans when no filter specified.""" - mock_spans = [ - make_span("span-1", "llm"), - make_span("span-2", "function"), - make_span("span-3", "llm"), - ] - - call_count = 0 - - async def fetch_fn(span_type): - nonlocal call_count - call_count += 1 - return mock_spans - - fetcher = CachedSpanFetcher(fetch_fn=fetch_fn) - result = await fetcher.get_spans() - - assert call_count == 1 - assert len(result) == 3 - assert {s.span_id for s in result} == {"span-1", "span-2", "span-3"} - - @pytest.mark.asyncio - async def test_fetch_specific_span_types(self): - """Test fetching specific span types when filter specified.""" - llm_spans = [make_span("span-1", "llm"), make_span("span-2", "llm")] - - call_count = 0 - - async def fetch_fn(span_type): - nonlocal call_count - call_count += 1 - assert span_type == ["llm"] - return llm_spans - - fetcher = CachedSpanFetcher(fetch_fn=fetch_fn) - result = await fetcher.get_spans(span_type=["llm"]) - - assert call_count == 1 - assert len(result) == 2 - - @pytest.mark.asyncio - async def test_return_cached_spans_after_fetching_all(self): - """Test that cached spans are returned without re-fetching after fetching all.""" - mock_spans = [ - make_span("span-1", "llm"), - make_span("span-2", "function"), - ] - - call_count = 0 - - async def fetch_fn(span_type): - nonlocal call_count - call_count += 1 - return mock_spans - - fetcher = CachedSpanFetcher(fetch_fn=fetch_fn) - - # First call - fetches - await fetcher.get_spans() - assert call_count == 1 - - # Second call - should use cache - result = await fetcher.get_spans() - assert call_count == 1 # Still 1 - assert len(result) == 2 - - @pytest.mark.asyncio - async def test_return_cached_spans_for_previously_fetched_types(self): - """Test that previously fetched types are returned from cache.""" - llm_spans = [make_span("span-1", "llm"), make_span("span-2", "llm")] - - call_count = 0 - - async def fetch_fn(span_type): - nonlocal call_count - call_count += 1 - return llm_spans - - fetcher = CachedSpanFetcher(fetch_fn=fetch_fn) - - # First call - fetches llm spans - await fetcher.get_spans(span_type=["llm"]) - assert call_count == 1 - - # Second call for same type - should use cache - result = await fetcher.get_spans(span_type=["llm"]) - assert call_count == 1 # Still 1 - assert len(result) == 2 - - @pytest.mark.asyncio - async def test_only_fetch_missing_span_types(self): - """Test that only missing span types are fetched.""" - llm_spans = [make_span("span-1", "llm")] - function_spans = [make_span("span-2", "function")] - - call_count = 0 - - async def fetch_fn(span_type): - nonlocal call_count - call_count += 1 - if span_type == ["llm"]: - return llm_spans - elif span_type == ["function"]: - return function_spans - return [] - - fetcher = CachedSpanFetcher(fetch_fn=fetch_fn) - - # First call - fetches llm spans - await fetcher.get_spans(span_type=["llm"]) - assert call_count == 1 - - # Second call for both types - should only fetch function - result = await fetcher.get_spans(span_type=["llm", "function"]) - assert call_count == 2 - assert len(result) == 2 - - @pytest.mark.asyncio - async def test_no_refetch_after_fetching_all_spans(self): - """Test that no re-fetching occurs after fetching all spans.""" - all_spans = [ - make_span("span-1", "llm"), - make_span("span-2", "function"), - make_span("span-3", "tool"), - ] - - call_count = 0 - - async def fetch_fn(span_type): - nonlocal call_count - call_count += 1 - return all_spans - - fetcher = CachedSpanFetcher(fetch_fn=fetch_fn) - - # Fetch all spans - await fetcher.get_spans() - assert call_count == 1 - - # Subsequent filtered calls should use cache - llm_result = await fetcher.get_spans(span_type=["llm"]) - assert call_count == 1 # Still 1 - assert len(llm_result) == 1 - assert llm_result[0].span_id == "span-1" - - function_result = await fetcher.get_spans(span_type=["function"]) - assert call_count == 1 # Still 1 - assert len(function_result) == 1 - assert function_result[0].span_id == "span-2" - - @pytest.mark.asyncio - async def test_filter_by_multiple_span_types_from_cache(self): - """Test filtering by multiple span types from cache.""" - all_spans = [ - make_span("span-1", "llm"), - make_span("span-2", "function"), - make_span("span-3", "tool"), - make_span("span-4", "llm"), - ] - - async def fetch_fn(span_type): - return all_spans - - fetcher = CachedSpanFetcher(fetch_fn=fetch_fn) - - # Fetch all first - await fetcher.get_spans() - - # Filter for llm and tool - result = await fetcher.get_spans(span_type=["llm", "tool"]) - assert len(result) == 3 - assert {s.span_id for s in result} == {"span-1", "span-3", "span-4"} - - @pytest.mark.asyncio - async def test_return_empty_for_nonexistent_span_type(self): - """Test that empty array is returned for non-existent span type.""" - all_spans = [make_span("span-1", "llm")] - - async def fetch_fn(span_type): - return all_spans - - fetcher = CachedSpanFetcher(fetch_fn=fetch_fn) - - # Fetch all first - await fetcher.get_spans() - - # Query for non-existent type - result = await fetcher.get_spans(span_type=["nonexistent"]) - assert len(result) == 0 - - @pytest.mark.asyncio - async def test_handle_spans_with_no_type(self): - """Test handling spans without type (empty string type).""" - spans = [ - make_span("span-1", "llm"), - SpanData(span_id="span-2", input={}, span_attributes={}), # No type - SpanData(span_id="span-3", input={}), # No span_attributes - ] - - async def fetch_fn(span_type): - return spans - - fetcher = CachedSpanFetcher(fetch_fn=fetch_fn) - - # Fetch all - result = await fetcher.get_spans() - assert len(result) == 3 - - # Spans without type go into "" bucket - no_type_result = await fetcher.get_spans(span_type=[""]) - assert len(no_type_result) == 2 - - @pytest.mark.asyncio - async def test_handle_empty_results(self): - """Test handling empty results.""" - - async def fetch_fn(span_type): - return [] - - fetcher = CachedSpanFetcher(fetch_fn=fetch_fn) - - result = await fetcher.get_spans() - assert len(result) == 0 - - # Should still mark as fetched - await fetcher.get_spans(span_type=["llm"]) - # No additional assertions, just making sure it doesn't crash - - @pytest.mark.asyncio - async def test_handle_empty_span_type_array(self): - """Test that empty spanType array is handled same as undefined.""" - mock_spans = [make_span("span-1", "llm")] - - call_args = [] - - async def fetch_fn(span_type): - call_args.append(span_type) - return mock_spans - - fetcher = CachedSpanFetcher(fetch_fn=fetch_fn) - - result = await fetcher.get_spans(span_type=[]) - - assert call_args[0] is None or call_args[0] == [] - assert len(result) == 1 - - -class _DummySpanCache: - def get_by_root_span_id(self, root_span_id: str): - return None - - -class _DummyState: - def __init__(self): - self.span_cache = _DummySpanCache() - - def login(self): - return None - - -class TestLocalTraceGetThread: - @pytest.mark.asyncio - async def test_calls_invoke_with_correct_parameters(self, monkeypatch): - mock_thread = [ - {"role": "user", "content": "Hello"}, - {"role": "assistant", "content": "Hi there!"}, - ] - calls = [] - - def fake_invoke(**kwargs): - calls.append(kwargs) - return mock_thread - - monkeypatch.setattr("braintrust.trace.invoke", fake_invoke) - - trace = LocalTrace( - object_type="experiment", - object_id="exp-123", - root_span_id="root-456", - ensure_spans_flushed=None, - state=_DummyState(), - ) - - result = await trace.get_thread() - - assert len(calls) == 1 - assert calls[0]["global_function"] == "project_default" - assert calls[0]["function_type"] == "preprocessor" - assert calls[0]["mode"] == "json" - assert calls[0]["input"] == { - "trace_ref": { - "object_type": "experiment", - "object_id": "exp-123", - "root_span_id": "root-456", - } - } - assert result == mock_thread - - @pytest.mark.asyncio - async def test_uses_custom_preprocessor(self, monkeypatch): - calls = [] - - def fake_invoke(**kwargs): - calls.append(kwargs) - return [{"role": "user", "content": "Test"}] - - monkeypatch.setattr("braintrust.trace.invoke", fake_invoke) - - trace = LocalTrace( - object_type="project_logs", - object_id="proj-789", - root_span_id="root-abc", - ensure_spans_flushed=None, - state=_DummyState(), - ) - - await trace.get_thread(options={"preprocessor": "custom_preprocessor"}) - assert calls[0]["global_function"] == "custom_preprocessor" - assert calls[0]["function_type"] == "preprocessor" - - @pytest.mark.asyncio - async def test_caches_by_preprocessor(self, monkeypatch): - call_count = 0 - - def fake_invoke(**kwargs): - nonlocal call_count - call_count += 1 - if kwargs["global_function"] == "project_default": - return [{"role": "user", "content": "Default"}] - return [{"role": "user", "content": "Custom"}] - - monkeypatch.setattr("braintrust.trace.invoke", fake_invoke) - - trace = LocalTrace( - object_type="experiment", - object_id="exp-123", - root_span_id="root-456", - ensure_spans_flushed=None, - state=_DummyState(), - ) - - result1 = await trace.get_thread() - result2 = await trace.get_thread() - result3 = await trace.get_thread(options={"preprocessor": "custom"}) - result4 = await trace.get_thread() - - assert result1 == [{"role": "user", "content": "Default"}] - assert result2 == [{"role": "user", "content": "Default"}] - assert result3 == [{"role": "user", "content": "Custom"}] - assert result4 == [{"role": "user", "content": "Default"}] - assert call_count == 2 - - @pytest.mark.asyncio - async def test_returns_empty_array_for_non_array_invoke_result(self, monkeypatch): - def fake_invoke(**kwargs): - return "not-an-array" - - monkeypatch.setattr("braintrust.trace.invoke", fake_invoke) - - trace = LocalTrace( - object_type="experiment", - object_id="exp-123", - root_span_id="root-456", - ensure_spans_flushed=None, - state=_DummyState(), - ) - - result = await trace.get_thread() - assert result == [] diff --git a/py/src/braintrust/test_util.py b/py/src/braintrust/test_util.py deleted file mode 100644 index 90f18602a..000000000 --- a/py/src/braintrust/test_util.py +++ /dev/null @@ -1,269 +0,0 @@ -import os -import unittest -from typing import List - -import pytest - -from .util import LazyValue, mask_api_key, merge_dicts_with_paths, parse_env_var_float - - -class TestParseEnvVarFloat: - """Tests for parse_env_var_float helper.""" - - def test_returns_default_when_env_not_set(self): - assert parse_env_var_float("NONEXISTENT_VAR_12345", 42.0) == 42.0 - - def test_parses_valid_float(self): - os.environ["TEST_FLOAT"] = "123.45" - try: - assert parse_env_var_float("TEST_FLOAT", 0.0) == 123.45 - finally: - del os.environ["TEST_FLOAT"] - - def test_returns_default_for_nan(self): - os.environ["TEST_FLOAT"] = "nan" - try: - assert parse_env_var_float("TEST_FLOAT", 99.0) == 99.0 - finally: - del os.environ["TEST_FLOAT"] - - def test_returns_default_for_inf(self): - os.environ["TEST_FLOAT"] = "inf" - try: - assert parse_env_var_float("TEST_FLOAT", 99.0) == 99.0 - finally: - del os.environ["TEST_FLOAT"] - - def test_returns_default_for_negative_inf(self): - os.environ["TEST_FLOAT"] = "-inf" - try: - assert parse_env_var_float("TEST_FLOAT", 99.0) == 99.0 - finally: - del os.environ["TEST_FLOAT"] - - def test_returns_default_for_empty_string(self): - os.environ["TEST_FLOAT"] = "" - try: - assert parse_env_var_float("TEST_FLOAT", 99.0) == 99.0 - finally: - del os.environ["TEST_FLOAT"] - - def test_returns_default_for_invalid_string(self): - os.environ["TEST_FLOAT"] = "not_a_number" - try: - assert parse_env_var_float("TEST_FLOAT", 99.0) == 99.0 - finally: - del os.environ["TEST_FLOAT"] - - def test_allows_negative_values(self): - os.environ["TEST_FLOAT"] = "-5.5" - try: - assert parse_env_var_float("TEST_FLOAT", 0.0) == -5.5 - finally: - del os.environ["TEST_FLOAT"] - - -class TestLazyValue(unittest.TestCase): - def test_evaluates_exactly_once(self): - call_count = 0 - - def compute_value(): - nonlocal call_count - call_count += 1 - return "test" - - lazy = LazyValue(compute_value, use_mutex=True) - - self.assertEqual(call_count, 0) - self.assertFalse(lazy.has_succeeded) - - # First access should compute - value1 = lazy.get() - self.assertEqual(value1, "test") - self.assertEqual(call_count, 1) - self.assertTrue(lazy.has_succeeded) - - # Second access should use cached value - value2 = lazy.get() - self.assertEqual(value2, "test") - self.assertEqual(call_count, 1) - self.assertTrue(lazy.has_succeeded) - - def test_has_succeeded_only_set_after_success(self): - def failing_compute(): - raise ValueError("test error") - - lazy = LazyValue(failing_compute, use_mutex=True) - - self.assertFalse(lazy.has_succeeded) - self.assertIsNone(lazy.value) - - with self.assertRaises(ValueError) as ctx: - lazy.get() - - self.assertEqual(str(ctx.exception), "test error") - self.assertFalse(lazy.has_succeeded) - self.assertIsNone(lazy.value) - - def test_thread_safety(self): - import threading - import time - - # This will be used to track if multiple threads try to compute simultaneously - computing = threading.Event() - - def compute_value(): - # If computing is already set when we enter, another thread - # is also trying to compute - this should never happen - if computing.is_set(): - raise RuntimeError("Concurrent computation detected!") - - computing.set() - try: - # Sleep briefly to increase chance of race conditions - time.sleep(0.1) - return "test result" - finally: - computing.clear() - - lazy = LazyValue(compute_value, use_mutex=True) - - # Launch multiple threads that all try to get() simultaneously - threads: List[threading.Thread] = [] - results: List[str] = [] - errors: List[Exception] = [] - - def worker(): - try: - results.append(lazy.get()) - except Exception as e: - errors.append(e) - - for _ in range(10): - t = threading.Thread(target=worker) - threads.append(t) - t.start() - - # Wait for all threads to complete - for t in threads: - t.join() - - # Verify no errors occurred - self.assertEqual(errors, []) - - # Verify all threads got the same result - self.assertEqual(len(results), 10) - self.assertTrue(all(r == "test result" for r in results)) - - # Verify the computation is marked succeeded. - self.assertTrue(lazy.has_succeeded) - - -if __name__ == "__main__": - unittest.main() - - -def test_get_sync(): - call_count = 0 - - def compute_value(): - nonlocal call_count - call_count += 1 - return "test" - - lazy = LazyValue(compute_value, use_mutex=True) - - # Before resolution - is_resolved, value = lazy.get_sync() - assert is_resolved is False - assert value is None - assert call_count == 0 # Should not call the function - - # Resolve with get() - result = lazy.get() - assert result == "test" - assert call_count == 1 - - # After resolution - is_resolved, value = lazy.get_sync() - assert is_resolved is True - assert value == "test" - assert call_count == 1 # Should not call the function again - - -def test_get_sync_error(): - def failing_compute(): - raise ValueError("test error") - - lazy = LazyValue(failing_compute, use_mutex=True) - - # Before attempting to resolve - is_resolved, value = lazy.get_sync() - assert is_resolved is False - assert value is None - - # Try to resolve with get() (which should fail) - with pytest.raises(ValueError, match="test error"): - lazy.get() - - # get_sync() should still return unresolved after failed resolution - is_resolved, value = lazy.get_sync() - assert is_resolved is False - assert value is None - - -def test_mask_api_key(): - assert mask_api_key("1234567890") == "12******90" - assert mask_api_key("12345") == "12*45" - for i in ["", "1", "12", "123", "1234"]: - assert mask_api_key(i) == "*" * len(i) - - -class TestTagsSetUnionMerge: - def test_tags_arrays_are_merged_as_sets_by_default(self): - a = {"tags": ["a", "b"]} - b = {"tags": ["b", "c"]} - merge_dicts_with_paths(a, b, (), set()) - assert set(a["tags"]) == {"a", "b", "c"} - - def test_tags_merge_deduplicates_values(self): - a = {"tags": ["a", "b", "c"]} - b = {"tags": ["a", "b", "c", "d"]} - merge_dicts_with_paths(a, b, (), set()) - assert set(a["tags"]) == {"a", "b", "c", "d"} - - def test_tags_merge_works_when_merge_into_has_no_tags(self): - a = {"other": "data"} - b = {"tags": ["a", "b"]} - merge_dicts_with_paths(a, b, (), set()) - assert set(a["tags"]) == {"a", "b"} - - def test_tags_merge_works_when_merge_from_has_no_tags(self): - a = {"tags": ["a", "b"]} - b = {"other": "data"} - merge_dicts_with_paths(a, b, (), set()) - assert set(a["tags"]) == {"a", "b"} - - def test_tags_are_replaced_when_included_in_merge_paths(self): - a = {"tags": ["a", "b"]} - b = {"tags": ["c", "d"]} - merge_dicts_with_paths(a, b, (), {("tags",)}) - assert a["tags"] == ["c", "d"] - - def test_empty_tags_array_clears_tags_when_in_merge_paths(self): - a = {"tags": ["a", "b"]} - b = {"tags": []} - merge_dicts_with_paths(a, b, (), {("tags",)}) - assert a["tags"] == [] - - def test_none_tags_replaces_tags(self): - a = {"tags": ["a", "b"]} - b = {"tags": None} - merge_dicts_with_paths(a, b, (), set()) - assert a["tags"] is None - - def test_set_union_only_applies_to_top_level_tags_field(self): - a = {"metadata": {"tags": ["a", "b"]}} - b = {"metadata": {"tags": ["c", "d"]}} - merge_dicts_with_paths(a, b, (), set()) - assert a["metadata"]["tags"] == ["c", "d"] diff --git a/py/src/braintrust/test_version.py b/py/src/braintrust/test_version.py deleted file mode 100644 index 1324cbe85..000000000 --- a/py/src/braintrust/test_version.py +++ /dev/null @@ -1,27 +0,0 @@ -import os - -from braintrust import version - - -def test_version(): - """Test the version module and verify templating works correctly.""" - # Detect wheel testing environment in multiple ways for robustness. - # The env variable makes sure we're not running from source - wheel_env = os.environ.get("BRAINTRUST_TESTING_WHEEL") == "1" - is_wheel_in_path = "site-packages" in version.__file__ - is_from_wheel = wheel_env or is_wheel_in_path - - # Basic assertions that should always pass - assert version.VERSION - assert version.GIT_COMMIT - assert isinstance(version.VERSION, str) - assert isinstance(version.GIT_COMMIT, str) - assert len(version.VERSION) > 0 - assert len(version.GIT_COMMIT) > 0 - if is_from_wheel: - # When testing from the wheel, GIT_COMMIT - # should be the actual commit hash, not the placeholder - assert version.GIT_COMMIT != "__GIT_COMMIT__" - else: - # When testing from source directly, we expect to see the placeholder - assert version.GIT_COMMIT == "__GIT_COMMIT__" diff --git a/py/src/braintrust/trace.py b/py/src/braintrust/trace.py deleted file mode 100644 index ef7044e86..000000000 --- a/py/src/braintrust/trace.py +++ /dev/null @@ -1,438 +0,0 @@ -""" -Trace objects for accessing spans in evaluations. - -This module provides the LocalTrace class which allows scorers to access -spans from the current evaluation task without making server round-trips. -""" - -import asyncio -from typing import Any, Awaitable, Callable, Optional, Protocol, TypedDict - -from braintrust.functions.invoke import invoke -from braintrust.logger import BraintrustState, ObjectFetcher - - -class SpanData: - """Span data returned by get_spans().""" - - def __init__( - self, - input: Optional[Any] = None, - output: Optional[Any] = None, - metadata: Optional[dict[str, Any]] = None, - span_id: Optional[str] = None, - span_parents: Optional[list[str]] = None, - span_attributes: Optional[dict[str, Any]] = None, - **kwargs: Any, - ): - self.input = input - self.output = output - self.metadata = metadata - self.span_id = span_id - self.span_parents = span_parents - self.span_attributes = span_attributes - # Store any additional fields - for key, value in kwargs.items(): - setattr(self, key, value) - - @classmethod - def from_dict(cls, data: dict[str, Any]) -> "SpanData": - """Create SpanData from a dictionary.""" - return cls(**data) - - def to_dict(self) -> dict[str, Any]: - """Convert to dictionary.""" - result = {} - for key, value in self.__dict__.items(): - if value is not None: - result[key] = value - return result - - -class SpanFetcher(ObjectFetcher[dict[str, Any]]): - """ - Fetcher for spans by root_span_id, using the ObjectFetcher pattern. - Handles pagination automatically via cursor-based iteration. - """ - - def __init__( - self, - object_type: str, # Literal["experiment", "project_logs", "playground_logs"] - object_id: str, - root_span_id: str, - state: BraintrustState, - span_type_filter: Optional[list[str]] = None, - ): - # Build the filter expression for root_span_id and optionally span_attributes.type - filter_expr = self._build_filter(root_span_id, span_type_filter) - - super().__init__( - object_type=object_type, - _internal_btql={"filter": filter_expr}, - ) - self._object_id = object_id - self._state = state - - @staticmethod - def _build_filter(root_span_id: str, span_type_filter: Optional[list[str]] = None) -> dict[str, Any]: - """Build BTQL filter expression.""" - children = [ - # Base filter: root_span_id = 'value' - { - "op": "eq", - "left": {"op": "ident", "name": ["root_span_id"]}, - "right": {"op": "literal", "value": root_span_id}, - }, - # Exclude span_attributes.purpose = 'scorer' - { - "op": "or", - "children": [ - { - "op": "isnull", - "expr": {"op": "ident", "name": ["span_attributes", "purpose"]}, - }, - { - "op": "ne", - "left": {"op": "ident", "name": ["span_attributes", "purpose"]}, - "right": {"op": "literal", "value": "scorer"}, - }, - ], - }, - ] - - # If span type filter specified, add it - if span_type_filter and len(span_type_filter) > 0: - children.append( - { - "op": "in", - "left": {"op": "ident", "name": ["span_attributes", "type"]}, - "right": {"op": "literal", "value": span_type_filter}, - } - ) - - return {"op": "and", "children": children} - - @property - def id(self) -> str: - return self._object_id - - def _get_state(self) -> BraintrustState: - return self._state - - -SpanFetchFn = Callable[[Optional[list[str]]], Awaitable[list[SpanData]]] - - -class GetThreadOptions(TypedDict, total=False): - preprocessor: str - - -class CachedSpanFetcher: - """ - Cached span fetcher that handles fetching and caching spans by type. - - Caching strategy: - - Cache spans by span type (dict[spanType, list[SpanData]]) - - Track if all spans have been fetched (all_fetched flag) - - When filtering by spanType, only fetch types not already in cache - """ - - def __init__( - self, - object_type: Optional[str] = None, # Literal["experiment", "project_logs", "playground_logs"] - object_id: Optional[str] = None, - root_span_id: Optional[str] = None, - get_state: Optional[Callable[[], Awaitable[BraintrustState]]] = None, - fetch_fn: Optional[SpanFetchFn] = None, - ): - self._span_cache: dict[str, list[SpanData]] = {} - self._all_fetched = False - - if fetch_fn is not None: - # Direct fetch function injection (for testing) - self._fetch_fn = fetch_fn - else: - # Standard constructor with SpanFetcher - if object_type is None or object_id is None or root_span_id is None or get_state is None: - raise ValueError("Must provide either fetch_fn or all of object_type, object_id, root_span_id, get_state") - - async def _fetch_fn(span_type: Optional[list[str]]) -> list[SpanData]: - state = await get_state() - fetcher = SpanFetcher( - object_type=object_type, - object_id=object_id, - root_span_id=root_span_id, - state=state, - span_type_filter=span_type, - ) - rows = list(fetcher.fetch()) - # Filter out scorer spans - filtered = [ - row - for row in rows - if not ( - isinstance(row.get("span_attributes"), dict) - and row.get("span_attributes", {}).get("purpose") == "scorer" - ) - ] - return [ - SpanData( - input=row.get("input"), - output=row.get("output"), - metadata=row.get("metadata"), - span_id=row.get("span_id"), - span_parents=row.get("span_parents"), - span_attributes=row.get("span_attributes"), - id=row.get("id"), - _xact_id=row.get("_xact_id"), - _pagination_key=row.get("_pagination_key"), - root_span_id=row.get("root_span_id"), - ) - for row in filtered - ] - - self._fetch_fn = _fetch_fn - - async def get_spans(self, span_type: Optional[list[str]] = None) -> list[SpanData]: - """ - Get spans, using cache when possible. - - Args: - span_type: Optional list of span types to filter by - - Returns: - List of matching spans - """ - # If we've fetched all spans, just filter from cache - if self._all_fetched: - return self._get_from_cache(span_type) - - # If no filter requested, fetch everything - if not span_type or len(span_type) == 0: - await self._fetch_spans(None) - self._all_fetched = True - return self._get_from_cache(None) - - # Find which spanTypes we don't have in cache yet - missing_types = [t for t in span_type if t not in self._span_cache] - - # If all requested types are cached, return from cache - if not missing_types: - return self._get_from_cache(span_type) - - # Fetch only the missing types - await self._fetch_spans(missing_types) - return self._get_from_cache(span_type) - - async def _fetch_spans(self, span_type: Optional[list[str]]) -> None: - """Fetch spans from the server.""" - spans = await self._fetch_fn(span_type) - - for span in spans: - span_attrs = span.span_attributes or {} - span_type_str = span_attrs.get("type", "") - if span_type_str not in self._span_cache: - self._span_cache[span_type_str] = [] - self._span_cache[span_type_str].append(span) - - def _get_from_cache(self, span_type: Optional[list[str]]) -> list[SpanData]: - """Get spans from cache, optionally filtering by type.""" - if not span_type or len(span_type) == 0: - # Return all spans - result = [] - for spans in self._span_cache.values(): - result.extend(spans) - return result - - # Return only requested types - result = [] - for type_str in span_type: - if type_str in self._span_cache: - result.extend(self._span_cache[type_str]) - return result - - -class Trace(Protocol): - """ - Interface for trace objects that can be used by scorers. - Both the SDK's LocalTrace class and the API wrapper's WrapperTrace implement this. - """ - - def get_configuration(self) -> dict[str, str]: - """Get the trace configuration (object_type, object_id, root_span_id).""" - ... - - async def get_spans(self, span_type: Optional[list[str]] = None) -> list[SpanData]: - """ - Fetch all spans for this root span. - - Args: - span_type: Optional list of span types to filter by - - Returns: - List of matching spans - """ - ... - - async def get_thread(self, options: GetThreadOptions | None = None) -> list[Any]: - """ - Get the thread (preprocessed messages) for this trace. - - Args: - options: Optional options object. Supports "preprocessor". - - Returns: - The preprocessed thread as an array of messages. - """ - ... - - -class LocalTrace(dict): - """ - SDK implementation of Trace that uses local span cache and falls back to BTQL. - Carries identifying information about the evaluation so scorers can perform - richer logging or side effects. - - Inherits from dict so that it serializes to {"trace_ref": {...}} when passed - to json.dumps(). This allows LocalTrace to be transparently serialized when - passed through invoke() or other JSON-serializing code paths. - """ - - def __init__( - self, - object_type: str, # Literal["experiment", "project_logs", "playground_logs"] - object_id: str, - root_span_id: str, - ensure_spans_flushed: Optional[Callable[[], Awaitable[None]]], - state: BraintrustState, - ): - # Initialize dict with trace_ref for JSON serialization - super().__init__({ - "trace_ref": { - "object_type": object_type, - "object_id": object_id, - "root_span_id": root_span_id, - } - }) - - self._object_type = object_type - self._object_id = object_id - self._root_span_id = root_span_id - self._ensure_spans_flushed = ensure_spans_flushed - self._state = state - self._spans_flushed = False - self._spans_flush_promise: Optional[asyncio.Task[None]] = None - self._thread_cache: dict[str, asyncio.Task[list[Any]]] = {} - - async def get_state() -> BraintrustState: - await self._ensure_spans_ready() - # Ensure state is logged in - await asyncio.get_event_loop().run_in_executor(None, lambda: state.login()) - return state - - self._cached_fetcher = CachedSpanFetcher( - object_type=object_type, - object_id=object_id, - root_span_id=root_span_id, - get_state=get_state, - ) - - def get_configuration(self) -> dict[str, str]: - """Get the trace configuration.""" - return { - "object_type": self._object_type, - "object_id": self._object_id, - "root_span_id": self._root_span_id, - } - - async def get_spans(self, span_type: Optional[list[str]] = None) -> list[SpanData]: - """ - Fetch all rows for this root span from its parent object (experiment or project logs). - First checks the local span cache for recently logged spans, then falls - back to CachedSpanFetcher which handles BTQL fetching and caching. - - Args: - span_type: Optional list of span types to filter by - - Returns: - List of matching spans - """ - # Try local span cache first (for recently logged spans not yet flushed) - cached_spans = self._state.span_cache.get_by_root_span_id(self._root_span_id) - if cached_spans and len(cached_spans) > 0: - # Filter by purpose - spans = [span for span in cached_spans if not (span.span_attributes or {}).get("purpose") == "scorer"] - - # Filter by span type if requested - if span_type and len(span_type) > 0: - spans = [span for span in spans if (span.span_attributes or {}).get("type", "") in span_type] - - # Convert to SpanData - return [ - SpanData( - input=span.input, - output=span.output, - metadata=span.metadata, - span_id=span.span_id, - span_parents=span.span_parents, - span_attributes=span.span_attributes, - ) - for span in spans - ] - - # Fall back to CachedSpanFetcher for BTQL fetching with caching - return await self._cached_fetcher.get_spans(span_type) - - async def get_thread(self, options: GetThreadOptions | None = None) -> list[Any]: - """ - Get the thread (preprocessed messages) for this trace. - Uses the project default preprocessor, falling back to global "thread". - """ - preprocessor = options.get("preprocessor") if options and options.get("preprocessor") else None - cache_key = preprocessor or "project_default" - if cache_key not in self._thread_cache: - self._thread_cache[cache_key] = asyncio.create_task(self._fetch_thread(options)) - return await self._thread_cache[cache_key] - - async def _fetch_thread(self, options: GetThreadOptions | None = None) -> list[Any]: - """Fetch thread messages via preprocessor invocation.""" - await self._ensure_spans_ready() - await asyncio.get_event_loop().run_in_executor(None, lambda: self._state.login()) - preprocessor = options.get("preprocessor") if options and options.get("preprocessor") else None - - result = await asyncio.get_event_loop().run_in_executor( - None, - lambda: invoke( - global_function=preprocessor or "project_default", - function_type="preprocessor", - mode="json", - input={ - "trace_ref": { - "object_type": self._object_type, - "object_id": self._object_id, - "root_span_id": self._root_span_id, - } - }, - ), - ) - - return result if isinstance(result, list) else [] - - async def _ensure_spans_ready(self) -> None: - """Ensure spans are flushed before fetching.""" - if self._spans_flushed or not self._ensure_spans_flushed: - return - - if self._spans_flush_promise is None: - - async def flush_and_mark(): - try: - await self._ensure_spans_flushed() - self._spans_flushed = True - except Exception as err: - self._spans_flush_promise = None - raise err - - self._spans_flush_promise = asyncio.create_task(flush_and_mark()) - - await self._spans_flush_promise diff --git a/py/src/braintrust/util.py b/py/src/braintrust/util.py deleted file mode 100644 index 5ed1ccd27..000000000 --- a/py/src/braintrust/util.py +++ /dev/null @@ -1,259 +0,0 @@ -import inspect -import json -import math -import os -import sys -import threading -import urllib.parse -from collections.abc import Callable, Mapping -from dataclasses import dataclass -from typing import Any, Generic, Literal, TypedDict, TypeVar, Union - -from requests import HTTPError, Response - - -def parse_env_var_float(name: str, default: float) -> float: - """Parse a float from an environment variable, returning default if invalid. - - Returns the default value if the env var is missing, empty, not a valid - float, NaN, or infinity. - """ - value = os.environ.get(name) - if value is None: - return default - try: - result = float(value) - if math.isnan(result) or math.isinf(result): - return default - return result - except (ValueError, TypeError): - return default - -GLOBAL_PROJECT = "Global" -BT_IS_ASYNC_ATTRIBUTE = "_BT_IS_ASYNC" - - -# Taken from -# https://stackoverflow.com/questions/5574702/how-do-i-print-to-stderr-in-python. -def is_numeric(v): - return isinstance(v, (int, float, complex)) and not isinstance(v, bool) - - -def eprint(*args, **kwargs) -> None: - print(*args, file=sys.stderr, **kwargs) - - -def coalesce(*args): - """Returns the first non-None value in the list of `args`, or `None` if they - are all `None`. - """ - - for a in args: - if a is not None: - return a - return None - - -# Fields that automatically use set-union merge semantics (unless in merge_paths). -_SET_UNION_FIELDS = frozenset(["tags"]) - - -def merge_dicts_with_paths( - merge_into: dict[str, Any], merge_from: Mapping[str, Any], path: tuple[str, ...], merge_paths: set[tuple[str, ...]] -) -> dict[str, Any]: - """Merges merge_from into merge_into, destructively updating merge_into. Does not merge any further than - merge_paths. For fields in _SET_UNION_FIELDS (like "tags"), arrays are merged as sets (union) - unless the field is explicitly listed in merge_paths (opt-out to replacement).""" - - if not isinstance(merge_into, dict): - raise ValueError("merge_into must be a dictionary") - if not isinstance(merge_from, dict): - raise ValueError("merge_from must be a dictionary") - - for k, merge_from_v in merge_from.items(): - full_path = path + (k,) - merge_into_v = merge_into.get(k) - - # Check if this field should use set-union merge (e.g., "tags" at top level) - is_set_union_field = len(path) == 0 and k in _SET_UNION_FIELDS and full_path not in merge_paths - - if is_set_union_field and isinstance(merge_into_v, list) and isinstance(merge_from_v, list): - # Set-union merge: combine arrays, deduplicate using JSON for objects - seen: set[str] = set() - combined = [] - for item in merge_into_v + list(merge_from_v): - # Use JSON serialization for consistent object comparison - item_key = json.dumps(item, sort_keys=True) if isinstance(item, (dict, list)) else str(item) - if item_key not in seen: - seen.add(item_key) - combined.append(item) - merge_into[k] = combined - elif isinstance(merge_into_v, dict) and isinstance(merge_from_v, dict) and full_path not in merge_paths: - merge_dicts_with_paths(merge_into_v, merge_from_v, full_path, merge_paths) - else: - merge_into[k] = merge_from_v - - return merge_into - - -def merge_dicts(merge_into: dict[str, Any], merge_from: Mapping[str, Any]) -> dict[str, Any]: - """Merges merge_from into merge_into, destructively updating merge_into.""" - - return merge_dicts_with_paths(merge_into, merge_from, (), set()) - - -def encode_uri_component(name: str) -> str: - """Encode a single component of a URI. Slashes are encoded as well, so this - should not be used for multiple slash-separated URI components.""" - - return urllib.parse.quote(name, safe="") - - -def mask_api_key(api_key: str) -> str: - if len(api_key) <= 4: - return "*" * len(api_key) - return api_key[:2] + "*" * (len(api_key) - 4) + api_key[-2:] - - -def _urljoin(*parts: str) -> str: - return "/".join( - p for p in [x.strip("/") if i < len(parts) - 1 else x.lstrip("/") for i, x in enumerate(parts)] if p.strip() - ) - - -class AugmentedHTTPError(Exception): - pass - - -def response_raise_for_status(resp: Response) -> None: - try: - resp.raise_for_status() - except HTTPError as e: - raise AugmentedHTTPError(f"{resp.text}") from e - - -class CallerLocation(TypedDict): - caller_functionname: str - caller_filename: str - caller_lineno: int - - -def get_caller_location() -> CallerLocation | None: - frame = inspect.currentframe() - while frame: - frame = frame.f_back - if frame is None: - return None - - mod = frame.f_globals.get("__name__") - # NOTE[matt] we know this is only called from braintrust code, - # so we can iterate up the callstack until we a frame that isn't - # braintrust code and know that's our first user caller. - if mod and not mod.startswith("braintrust."): - return CallerLocation( - caller_functionname=frame.f_code.co_name, - caller_filename=frame.f_code.co_filename, - caller_lineno=frame.f_lineno, - ) - - return None - - -T = TypeVar("T") - - -@dataclass -class _LazyValueResolvedState(Generic[T]): - value: T - has_succeeded: Literal[True] = True - - -@dataclass -class _LazyValuePendingState: - has_succeeded: Literal[False] = False - - -_LazyValueState = Union[_LazyValueResolvedState[T], _LazyValuePendingState] - - -class LazyValue(Generic[T]): - """A simple wrapper around a callable object which computes the value - on-demand and saves it for future retrievals. - """ - - def __init__(self, callable: Callable[[], T], use_mutex: bool): - self.callable = callable - self.mutex = threading.Lock() if use_mutex else None - self._state: _LazyValueState[T] = _LazyValuePendingState() - - @property - def has_succeeded(self) -> bool: - return self._state.has_succeeded - - @property - def value(self) -> T | None: - return self._state.value if self._state.has_succeeded == True else None - - def get(self) -> T: - # Short-circuit check `has_succeeded`. This should be fine because - # setting `_state` is atomic and python should have sequentially - # consistent semantics, so we'll observe the write to - # `self._state.value` as well. - # https://docs.python.org/3/faq/library.html#what-kinds-of-global-value-mutation-are-thread-safe - if self._state.has_succeeded == True: - return self._state.value - if self.mutex: - self.mutex.acquire() - try: - if self._state.has_succeeded == False: - res = self.callable() - self._state = _LazyValueResolvedState(value=res) - return self._state.value - finally: - if self.mutex: - self.mutex.release() - - def get_sync(self) -> tuple[bool, T | None]: - """Returns a tuple of (has_succeeded, value) without triggering evaluation.""" - if self._state.has_succeeded: - # should be fine without the mutex check - return (True, self._state.value) - return (False, None) - - -_MARK_ASYNC_WRAPPER_UNDERLYING_CALLABLE_ATTRIBUTE = "_MarkAsyncWrapper_underlying_callable" - - -# A wrapper class to enable explicitly marking a callable object as async. This -# can be useful for scenarios where the user wants to provide an awaitable -# function that is not recognized as async with `inspect.iscoroutinefunction`. -# -# Note: Python 3.12 provides a `inspect.markcoroutinefunction` function which -# serves a similar purpose, but we do this ourselves in case this function is -# not available. -class MarkAsyncWrapper: - def __init__(self, callable): - setattr(self, _MARK_ASYNC_WRAPPER_UNDERLYING_CALLABLE_ATTRIBUTE, callable) - setattr(self, BT_IS_ASYNC_ATTRIBUTE, True) - - def __getattribute__(self, name): - if name in [_MARK_ASYNC_WRAPPER_UNDERLYING_CALLABLE_ATTRIBUTE, BT_IS_ASYNC_ATTRIBUTE]: - return object.__getattribute__(self, name) - else: - return object.__getattribute__( - object.__getattribute__(self, _MARK_ASYNC_WRAPPER_UNDERLYING_CALLABLE_ATTRIBUTE), name - ) - - def __call__(self, *args, **kwargs): - return object.__getattribute__(self, _MARK_ASYNC_WRAPPER_UNDERLYING_CALLABLE_ATTRIBUTE)(*args, **kwargs) - - -def bt_iscoroutinefunction(f): - return inspect.iscoroutinefunction(f) or inspect.isasyncgenfunction(f) or getattr(f, BT_IS_ASYNC_ATTRIBUTE, False) - - -def add_azure_blob_headers(headers: dict[str, str], url: str) -> None: - # According to https://stackoverflow.com/questions/37824136/put-on-sas-blob-url-without-specifying-x-ms-blob-type-header, - # there is no way to avoid including this. - if "blob.core.windows.net" in url: - headers["x-ms-blob-type"] = "BlockBlob" diff --git a/py/src/braintrust/version.py b/py/src/braintrust/version.py deleted file mode 100644 index b189937b6..000000000 --- a/py/src/braintrust/version.py +++ /dev/null @@ -1,4 +0,0 @@ -VERSION = "0.5.6" - -# this will be templated during the build -GIT_COMMIT = "__GIT_COMMIT__" diff --git a/py/src/braintrust/wrappers/__init__.py b/py/src/braintrust/wrappers/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/py/src/braintrust/wrappers/_anthropic_utils.py b/py/src/braintrust/wrappers/_anthropic_utils.py deleted file mode 100644 index 12f72a4dd..000000000 --- a/py/src/braintrust/wrappers/_anthropic_utils.py +++ /dev/null @@ -1,98 +0,0 @@ -"""Shared utilities for Anthropic API wrappers.""" - -from typing import Any - - -class Wrapper: - """Base wrapper class with __getattr__ delegation to preserve original types.""" - - def __init__(self, wrapped: Any): - self.__wrapped = wrapped - - def __getattr__(self, name: str) -> Any: - return getattr(self.__wrapped, name) - - -def extract_anthropic_usage(usage: Any) -> dict[str, float]: - """Extract and normalize usage metrics from Anthropic usage object or dict. - - Converts Anthropic's usage format to Braintrust's standard token metric names. - Handles both object attributes and dictionary keys. - - Args: - usage: Anthropic usage object (from Message.usage) or dict - - Returns: - Dictionary with normalized metric names: - - prompt_tokens (from input_tokens) - - completion_tokens (from output_tokens) - - prompt_cached_tokens (from cache_read_input_tokens) - - prompt_cache_creation_tokens (from cache_creation_input_tokens) - """ - metrics: dict[str, float] = {} - - if not usage: - return metrics - - # Handle both dict and object with attributes - def get_value(key: str) -> Any: - if isinstance(usage, dict): - return usage.get(key) - return getattr(usage, key, None) - - # Standard token counts - input_tokens = get_value("input_tokens") - if input_tokens is not None: - try: - metrics["prompt_tokens"] = float(input_tokens) - except (ValueError, TypeError): - pass - - output_tokens = get_value("output_tokens") - if output_tokens is not None: - try: - metrics["completion_tokens"] = float(output_tokens) - except (ValueError, TypeError): - pass - - # Anthropic cache tokens - cache_read_tokens = get_value("cache_read_input_tokens") - if cache_read_tokens is not None: - try: - metrics["prompt_cached_tokens"] = float(cache_read_tokens) - except (ValueError, TypeError): - pass - - cache_creation_tokens = get_value("cache_creation_input_tokens") - if cache_creation_tokens is not None: - try: - metrics["prompt_cache_creation_tokens"] = float(cache_creation_tokens) - except (ValueError, TypeError): - pass - - return metrics - - -def finalize_anthropic_tokens(metrics: dict[str, float]) -> dict[str, float]: - """Finalize Anthropic token calculations. - - Anthropic doesn't include cache tokens in the total, so we need to sum them. - Updates 'prompt_tokens' to include cache tokens and adds 'tokens' field with the total. - - Args: - metrics: Dictionary with token metrics - - Returns: - Updated metrics with total prompt tokens and total tokens fields - """ - total_prompt_tokens = ( - metrics.get("prompt_tokens", 0) - + metrics.get("prompt_cached_tokens", 0) - + metrics.get("prompt_cache_creation_tokens", 0) - ) - - return { - **metrics, - "prompt_tokens": total_prompt_tokens, - "tokens": total_prompt_tokens + metrics.get("completion_tokens", 0), - } diff --git a/py/src/braintrust/wrappers/agno/__init__.py b/py/src/braintrust/wrappers/agno/__init__.py deleted file mode 100644 index 6e695eca1..000000000 --- a/py/src/braintrust/wrappers/agno/__init__.py +++ /dev/null @@ -1,67 +0,0 @@ -""" -Braintrust wrapper for Agno - provides observability for agent workflows. - -This integration provides: -- Agent execution tracing with proper root spans -- LLM call tracing with proper nesting -- Tool call tracing with correct parent-child relationships - -Usage: - from braintrust.wrappers.agno import setup_agno - - # Initialize the integration - setup_agno(project_name="my-project") - - # Your Agno agent code will now be automatically traced - import agno - agent = agno.Agent(...) - response = agent.run(...) -""" - -__all__ = ["setup_agno", "wrap_agent", "wrap_function_call", "wrap_model", "wrap_team"] - -import logging - -from braintrust.logger import NOOP_SPAN, current_span, init_logger - -from .agent import wrap_agent -from .function_call import wrap_function_call -from .model import wrap_model -from .team import wrap_team - -logger = logging.getLogger(__name__) - - -def setup_agno( - api_key: str | None = None, - project_id: str | None = None, - project_name: str | None = None, -) -> bool: - """ - Setup Braintrust integration with Agno. Will automatically patch Agno agents, models, and function calls for tracing. - - This function is called by init_agno() and can also be used directly for more control. - - Args: - api_key: Braintrust API key (optional, can use env var BRAINTRUST_API_KEY) - project_id: Braintrust project ID (optional) - project_name: Braintrust project name (optional, can use env var BRAINTRUST_PROJECT) - - Returns: - True if setup was successful, False otherwise - """ - span = current_span() - if span == NOOP_SPAN: - init_logger(project=project_name, api_key=api_key, project_id=project_id) - - try: - from agno import agent, models, team, tools # pyright: ignore - - agent.Agent = wrap_agent(agent.Agent) # pyright: ignore[reportUnknownMemberType] - team.Team = wrap_team(team.Team) # pyright: ignore[reportUnknownMemberType] - models.base.Model = wrap_model(models.base.Model) # pyright: ignore[reportUnknownMemberType] - tools.function.FunctionCall = wrap_function_call(tools.function.FunctionCall) # pyright: ignore[reportUnknownMemberType] - return True - except ImportError: - # Not installed - this is expected when using auto_instrument() - return False diff --git a/py/src/braintrust/wrappers/agno/agent.py b/py/src/braintrust/wrappers/agno/agent.py deleted file mode 100644 index 31b020b69..000000000 --- a/py/src/braintrust/wrappers/agno/agent.py +++ /dev/null @@ -1,216 +0,0 @@ -import time -from typing import Any - -from braintrust.logger import start_span -from braintrust.span_types import SpanTypeAttribute -from wrapt import wrap_function_wrapper - -from .utils import ( - _aggregate_agent_chunks, - extract_metadata, - extract_metrics, - extract_streaming_metrics, - is_patched, - mark_patched, - omit, -) - - -def wrap_agent(Agent: Any) -> Any: - if is_patched(Agent): - return Agent - - def _create_run_span(wrapped: Any, instance: Any, args: Any, kwargs: Any, input_data: dict): - """Shared logic to create span and execute run method.""" - agent_name = getattr(instance, "name", None) or "Agent" - span_name = f"{agent_name}.run" - - with start_span( - name=span_name, - type=SpanTypeAttribute.TASK, - input=input_data, - metadata={**omit(kwargs, list(input_data.keys())), **extract_metadata(instance, "agent")}, - ) as span: - result = wrapped(*args, **kwargs) - span.log( - output=result, - metrics=extract_metrics(result), - ) - return result - - def _run_wrapper_private(wrapped: Any, instance: Any, args: Any, kwargs: Any): - """Entry point for private _run(run_response, run_messages).""" - run_response = args[0] if len(args) > 0 else kwargs.get("run_response") - run_messages = args[1] if len(args) > 1 else kwargs.get("run_messages") - input_data = {"run_response": run_response, "run_messages": run_messages} - return _create_run_span(wrapped, instance, args, kwargs, input_data) - - def _run_wrapper_public(wrapped: Any, instance: Any, args: Any, kwargs: Any): - """Entry point for public run(input).""" - input_arg = args[0] if len(args) > 0 else kwargs.get("input") - input_data = {"input": input_arg} - return _create_run_span(wrapped, instance, args, kwargs, input_data) - - # Wrap private method if it exists, otherwise wrap public method - if hasattr(Agent, "_run"): - wrap_function_wrapper(Agent, "_run", _run_wrapper_private) - elif hasattr(Agent, "run"): - wrap_function_wrapper(Agent, "run", _run_wrapper_public) - - async def _create_arun_span(wrapped: Any, instance: Any, args: Any, kwargs: Any, input_data: dict): - """Shared logic to create span and execute arun method.""" - agent_name = getattr(instance, "name", None) or "Agent" - span_name = f"{agent_name}.arun" - - with start_span( - name=span_name, - type=SpanTypeAttribute.TASK, - input=input_data, - metadata={**omit(kwargs, list(input_data.keys())), **extract_metadata(instance, "agent")}, - ) as span: - result = await wrapped(*args, **kwargs) - span.log( - output=result, - metrics=extract_metrics(result), - ) - return result - - async def _arun_wrapper_private(wrapped: Any, instance: Any, args: Any, kwargs: Any): - """Entry point for private _arun(run_response, input).""" - run_response = args[0] if len(args) > 0 else kwargs.get("run_response") - input_arg = args[1] if len(args) > 1 else kwargs.get("input") - input_data = {"run_response": run_response, "input": input_arg} - return await _create_arun_span(wrapped, instance, args, kwargs, input_data) - - async def _arun_wrapper_public(wrapped: Any, instance: Any, args: Any, kwargs: Any): - """Entry point for public arun(input).""" - input_arg = args[0] if len(args) > 0 else kwargs.get("input") - input_data = {"input": input_arg} - return await _create_arun_span(wrapped, instance, args, kwargs, input_data) - - # Wrap private method if it exists, otherwise wrap public method - if hasattr(Agent, "_arun"): - wrap_function_wrapper(Agent, "_arun", _arun_wrapper_private) - elif hasattr(Agent, "arun"): - wrap_function_wrapper(Agent, "arun", _arun_wrapper_public) - - def run_stream_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - agent_name = getattr(instance, "name", None) or "Agent" - span_name = f"{agent_name}.run_stream" - - run_response = args[0] if args else kwargs.get("run_response") - run_messages = args[1] if args else kwargs.get("run_messages") - - def _trace_stream(): - start = time.time() - span = start_span( - name=span_name, - type=SpanTypeAttribute.TASK, - input={"run_response": run_response, "run_messages": run_messages}, - metadata={**omit(kwargs, ["run_response", "run_messages"]), **extract_metadata(instance, "agent")}, - ) - span.set_current() - - should_unset = True - try: - first = True - all_chunks = [] - - for chunk in wrapped(*args, **kwargs): - if first: - span.log( - metrics={ - "time_to_first_token": time.time() - start, - } - ) - first = False - all_chunks.append(chunk) - yield chunk - - aggregated = _aggregate_agent_chunks(all_chunks) - - span.log( - output=aggregated, - metrics=extract_streaming_metrics(aggregated, start), - ) - except GeneratorExit: - # Generator was closed early (e.g., break from for loop) - # Don't call unset_current() as context may have changed - should_unset = False - raise - except Exception as e: - span.log( - error=str(e), - ) - raise - finally: - if should_unset: - span.unset_current() - span.end() - - return _trace_stream() - - if hasattr(Agent, "_run_stream"): - wrap_function_wrapper(Agent, "_run_stream", run_stream_wrapper) - - def arun_stream_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - agent_name = getattr(instance, "name", None) or "Agent" - span_name = f"{agent_name}.arun_stream" - - run_response = args[0] if args else kwargs.get("run_response") - input = args[2] if args else kwargs.get("input") - - async def _trace_stream(): - start = time.time() - span = start_span( - name=span_name, - type=SpanTypeAttribute.TASK, - input={"run_response": run_response, "input": input}, - metadata={**omit(kwargs, ["run_response", "input"]), **extract_metadata(instance, "agent")}, - ) - span.set_current() - - should_unset = True - try: - first = True - all_chunks = [] - - async for chunk in wrapped(*args, **kwargs): - if first: - span.log( - metrics={ - "time_to_first_token": time.time() - start, - } - ) - first = False - all_chunks.append(chunk) - yield chunk - - aggregated = _aggregate_agent_chunks(all_chunks) - - span.log( - output=aggregated, - metrics=extract_streaming_metrics(aggregated, start), - ) - except GeneratorExit: - # Generator was closed early (e.g., break from async for loop) - # Don't call unset_current() as context may have changed - should_unset = False - raise - except Exception as e: - span.log( - error=str(e), - ) - raise - finally: - if should_unset: - span.unset_current() - span.end() - - return _trace_stream() - - if hasattr(Agent, "_arun_stream"): - wrap_function_wrapper(Agent, "_arun_stream", arun_stream_wrapper) - - mark_patched(Agent) - return Agent diff --git a/py/src/braintrust/wrappers/agno/function_call.py b/py/src/braintrust/wrappers/agno/function_call.py deleted file mode 100644 index e4104866c..000000000 --- a/py/src/braintrust/wrappers/agno/function_call.py +++ /dev/null @@ -1,67 +0,0 @@ -from typing import Any - -from braintrust.logger import start_span -from braintrust.span_types import SpanTypeAttribute -from wrapt import wrap_function_wrapper - -from .utils import is_patched - - -def wrap_function_call(FunctionCall: Any) -> Any: - if is_patched(FunctionCall): - return FunctionCall - - def execute_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - function_name = _get_function_name(instance) - span_name = f"{function_name}.execute" - - entrypoint_args = instance._build_entrypoint_args() - - with start_span( - name=span_name, - type=SpanTypeAttribute.TOOL, - input=(instance.arguments or {}), - metadata={ - "name": instance.function.name, - "entrypoint": instance.function.entrypoint.__name__, - **(entrypoint_args or {}), - }, - ) as span: - result = wrapped(*args, **kwargs) - span.log(output=result) - return result - - if hasattr(FunctionCall, "execute"): - wrap_function_wrapper(FunctionCall, "execute", execute_wrapper) - - async def aexecute_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - function_name = _get_function_name(instance) - span_name = f"{function_name}.aexecute" - - entrypoint_args = instance._build_entrypoint_args() - - with start_span( - name=span_name, - type=SpanTypeAttribute.TOOL, - input=(instance.arguments or {}), - metadata={ - "name": instance.function.name, - "entrypoint": instance.function.entrypoint.__name__, - **(entrypoint_args or {}), - }, - ) as span: - result = await wrapped(*args, **kwargs) - span.log(output=result) - return result - - if hasattr(FunctionCall, "aexecute"): - wrap_function_wrapper(FunctionCall, "aexecute", aexecute_wrapper) - - FunctionCall._braintrust_patched = True - return FunctionCall - - -def _get_function_name(instance) -> str: - if hasattr(instance, "function") and hasattr(instance.function, "name"): - return instance.function.name - return "Unknown" diff --git a/py/src/braintrust/wrappers/agno/model.py b/py/src/braintrust/wrappers/agno/model.py deleted file mode 100644 index 8b789bc32..000000000 --- a/py/src/braintrust/wrappers/agno/model.py +++ /dev/null @@ -1,315 +0,0 @@ -""" -ModelWrapper class for Braintrust-Agno model observability. -""" - -import time -from typing import Any - -from braintrust.logger import start_span -from braintrust.span_types import SpanTypeAttribute -from wrapt import wrap_function_wrapper - -from .utils import ( - _aggregate_model_chunks, - _aggregate_response_stream_chunks, - extract_metadata, - extract_metrics, - extract_streaming_metrics, - get_args_kwargs, - is_patched, - mark_patched, -) - - -def wrap_model(Model: Any) -> Any: - if is_patched(Model): - return Model - - def invoke_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - model_name = _get_model_name(instance) - span_name = f"{model_name}.invoke" - - input, clean_kwargs = get_args_kwargs( - args, kwargs, ["assistant_message", "messages", "response_format", "tools", "tool_choice"] - ) - - with start_span( - name=span_name, - type=SpanTypeAttribute.LLM, - input=input, - metadata={ - **clean_kwargs, - **extract_metadata(instance, "model"), - }, - ) as span: - result = wrapped(*args, **kwargs) - span.log( - output=result, - metrics=extract_metrics(result, kwargs.get("messages", [])), - ) - return result - - if hasattr(Model, "invoke"): - wrap_function_wrapper(Model, "invoke", invoke_wrapper) - - async def ainvoke_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - model_name = _get_model_name(instance) - span_name = f"{model_name}.ainvoke" - - input, clean_kwargs = get_args_kwargs( - args, kwargs, ["messages", "assistant_message", "response_format", "tools", "tool_choice"] - ) - - with start_span( - name=span_name, - type=SpanTypeAttribute.LLM, - input=input, - metadata={ - **clean_kwargs, - **extract_metadata(instance, "model"), - }, - ) as span: - result = await wrapped(*args, **kwargs) - span.log( - output=result, - metrics=extract_metrics(result, kwargs.get("messages", [])), - ) - return result - - if hasattr(Model, "ainvoke"): - wrap_function_wrapper(Model, "ainvoke", ainvoke_wrapper) - - def invoke_stream_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - model_name = _get_model_name(instance) - span_name = f"{model_name}.invoke_stream" - - input, clean_kwargs = get_args_kwargs( - args, kwargs, ["messages", "assistant_messages", "response_format", "tools", "tool_choice"] - ) - - def _trace_stream(): - start = time.time() - with start_span( - name=span_name, - type=SpanTypeAttribute.LLM, - input=input, - metadata={ - **clean_kwargs, - **extract_metadata(instance, "model"), - }, - ) as span: - first = True - collected_chunks = [] - for chunk in wrapped(*args, **kwargs): - if first: - span.log( - metrics={ - "time_to_first_token": time.time() - start, - } - ) - first = False - - collected_chunks.append(chunk) - yield chunk - - aggregated = _aggregate_model_chunks(collected_chunks) - - span.log( - output=aggregated, - metrics=extract_streaming_metrics(aggregated, start), - ) - - return _trace_stream() - - if hasattr(Model, "invoke_stream"): - wrap_function_wrapper(Model, "invoke_stream", invoke_stream_wrapper) - - def ainvoke_stream_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - model_name = _get_model_name(instance) - span_name = f"{model_name}.ainvoke_stream" - - input, clean_kwargs = get_args_kwargs( - args, kwargs, ["messages", "assistant_messages", "response_format", "tools", "tool_choice"] - ) - - async def _trace_astream(): - start = time.time() - with start_span( - name=span_name, - type=SpanTypeAttribute.LLM, - input=input, - metadata={ - **clean_kwargs, - **extract_metadata(instance, "model"), - }, - ) as span: - first = True - collected_chunks = [] - async for chunk in wrapped(*args, **kwargs): - if first: - span.log( - metrics={ - "time_to_first_token": time.time() - start, - } - ) - first = False - - collected_chunks.append(chunk) - yield chunk - - aggregated = _aggregate_model_chunks(collected_chunks) - - span.log( - output=aggregated, - metrics=extract_streaming_metrics(aggregated, start), - ) - - return _trace_astream() - - if hasattr(Model, "ainvoke_stream"): - wrap_function_wrapper(Model, "ainvoke_stream", ainvoke_stream_wrapper) - - def response_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - model_name = _get_model_name(instance) - span_name = f"{model_name}.response" - - input, clean_kwargs = get_args_kwargs( - args, kwargs, ["messages", "response_format", "tools", "functions", "tool_chocie", "tool_call_limit"] - ) - - with start_span( - name=span_name, - # TODO: should be LLM? - type=SpanTypeAttribute.LLM, - input=input, - metadata={**clean_kwargs, **extract_metadata(instance, "model")}, - ) as span: - result = wrapped(*args, **kwargs) - span.log( - output=result, - metrics=extract_metrics(result, kwargs.get("messages", [])), - ) - return result - - if hasattr(Model, "response"): - wrap_function_wrapper(Model, "response", response_wrapper) - - async def aresponse_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - model_name = _get_model_name(instance) - span_name = f"{model_name}.aresponse" - - input, clean_kwargs = get_args_kwargs( - args, kwargs, ["messages", "response_format", "tools", "functions", "tool_chocie", "tool_call_limit"] - ) - - with start_span( - name=span_name, - # TODO: should be LLM? - type=SpanTypeAttribute.LLM, - input=input, - metadata={**clean_kwargs, **extract_metadata(instance, "model")}, - ) as span: - result = await wrapped(*args, **kwargs) - span.log( - output=result, - metrics=extract_metrics(result, kwargs.get("messages", [])), - ) - return result - - if hasattr(Model, "aresponse"): - wrap_function_wrapper(Model, "aresponse", aresponse_wrapper) - - def response_stream_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - model_name = _get_model_name(instance) - span_name = f"{model_name}.response_stream" - - input, clean_kwargs = get_args_kwargs( - args, kwargs, ["messages", "response_format", "tools", "functions", "tool_chocie", "tool_call_limit"] - ) - - def _trace_stream(): - start = time.time() - with start_span( - name=span_name, - type=SpanTypeAttribute.LLM, - input=input, - metadata={**clean_kwargs, **extract_metadata(instance, "model")}, - ) as span: - first = True - collected_chunks = [] - - for chunk in wrapped(*args, **kwargs): - if first: - span.log( - metrics={ - "time_to_first_token": time.time() - start, - } - ) - first = False - - collected_chunks.append(chunk) - yield chunk - - aggregated = _aggregate_response_stream_chunks(collected_chunks) - - span.log( - output=aggregated, - metrics=extract_streaming_metrics(aggregated, start), - ) - - return _trace_stream() - - if hasattr(Model, "response_stream"): - wrap_function_wrapper(Model, "response_stream", response_stream_wrapper) - - def aresponse_stream_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - model_name = _get_model_name(instance) - span_name = f"{model_name}.aresponse_stream" - - input, clean_kwargs = get_args_kwargs( - args, kwargs, ["messages", "response_format", "tools", "functions", "tool_chocie", "tool_call_limit"] - ) - - async def _trace_astream(): - start = time.time() - with start_span( - name=span_name, - type=SpanTypeAttribute.LLM, - input=input, - metadata={**clean_kwargs, **extract_metadata(instance, "model")}, - ) as span: - first = True - collected_chunks = [] - - async for chunk in wrapped(*args, **kwargs): - if first: - span.log( - metrics={ - "time_to_first_token": time.time() - start, - } - ) - first = False - - collected_chunks.append(chunk) - yield chunk - - aggregated = _aggregate_response_stream_chunks(collected_chunks) - - span.log( - output=aggregated, - metrics=extract_streaming_metrics(aggregated, start), - ) - - return _trace_astream() - - if hasattr(Model, "aresponse_stream"): - wrap_function_wrapper(Model, "aresponse_stream", aresponse_stream_wrapper) - - mark_patched(Model) - return Model - - -def _get_model_name(instance: Any) -> str: - if hasattr(instance, "get_provider") and callable(instance.get_provider): - return str(instance.get_provider()) - return getattr(instance.__class__, "__name__", "Model") diff --git a/py/src/braintrust/wrappers/agno/team.py b/py/src/braintrust/wrappers/agno/team.py deleted file mode 100644 index 294fbc08b..000000000 --- a/py/src/braintrust/wrappers/agno/team.py +++ /dev/null @@ -1,216 +0,0 @@ -import time -from typing import Any - -from braintrust.logger import start_span -from braintrust.span_types import SpanTypeAttribute -from wrapt import wrap_function_wrapper - -from .utils import ( - _aggregate_agent_chunks, - extract_metadata, - extract_metrics, - extract_streaming_metrics, - is_patched, - mark_patched, - omit, -) - - -def wrap_team(Team: Any) -> Any: - if is_patched(Team): - return Team - - def _create_run_span(wrapped: Any, instance: Any, args: Any, kwargs: Any, input_data: dict): - """Shared logic to create span and execute run method.""" - agent_name = getattr(instance, "name", None) or "Team" - span_name = f"{agent_name}.run" - - with start_span( - name=span_name, - type=SpanTypeAttribute.TASK, - input=input_data, - metadata={**omit(kwargs, list(input_data.keys())), **extract_metadata(instance, "team")}, - ) as span: - result = wrapped(*args, **kwargs) - span.log( - output=result, - metrics=extract_metrics(result), - ) - return result - - def _run_wrapper_private(wrapped: Any, instance: Any, args: Any, kwargs: Any): - """Entry point for private _run(run_response, run_messages).""" - run_response = args[0] if len(args) > 0 else kwargs.get("run_response") - run_messages = args[1] if len(args) > 1 else kwargs.get("run_messages") - input_data = {"run_response": run_response, "run_messages": run_messages} - return _create_run_span(wrapped, instance, args, kwargs, input_data) - - def _run_wrapper_public(wrapped: Any, instance: Any, args: Any, kwargs: Any): - """Entry point for public run(input).""" - input_arg = args[0] if len(args) > 0 else kwargs.get("input") - input_data = {"input": input_arg} - return _create_run_span(wrapped, instance, args, kwargs, input_data) - - # Wrap private method if it exists, otherwise wrap public method - if hasattr(Team, "_run"): - wrap_function_wrapper(Team, "_run", _run_wrapper_private) - elif hasattr(Team, "run"): - wrap_function_wrapper(Team, "run", _run_wrapper_public) - - async def _create_arun_span(wrapped: Any, instance: Any, args: Any, kwargs: Any, input_data: dict): - """Shared logic to create span and execute arun method.""" - agent_name = getattr(instance, "name", None) or "Team" - span_name = f"{agent_name}.arun" - - with start_span( - name=span_name, - type=SpanTypeAttribute.TASK, - input=input_data, - metadata={**omit(kwargs, list(input_data.keys())), **extract_metadata(instance, "team")}, - ) as span: - result = await wrapped(*args, **kwargs) - span.log( - output=result, - metrics=extract_metrics(result), - ) - return result - - async def _arun_wrapper_private(wrapped: Any, instance: Any, args: Any, kwargs: Any): - """Entry point for private _arun(run_response, input).""" - run_response = args[0] if len(args) > 0 else kwargs.get("run_response") - input_arg = args[1] if len(args) > 1 else kwargs.get("input") - input_data = {"run_response": run_response, "input": input_arg} - return await _create_arun_span(wrapped, instance, args, kwargs, input_data) - - async def _arun_wrapper_public(wrapped: Any, instance: Any, args: Any, kwargs: Any): - """Entry point for public arun(input).""" - input_arg = args[0] if len(args) > 0 else kwargs.get("input") - input_data = {"input": input_arg} - return await _create_arun_span(wrapped, instance, args, kwargs, input_data) - - # Wrap private method if it exists, otherwise wrap public method - if hasattr(Team, "_arun"): - wrap_function_wrapper(Team, "_arun", _arun_wrapper_private) - elif hasattr(Team, "arun"): - wrap_function_wrapper(Team, "arun", _arun_wrapper_public) - - def run_stream_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - agent_name = getattr(instance, "name", None) or "Team" - span_name = f"{agent_name}.run_stream" - - run_response = args[0] if args else kwargs.get("run_response") - run_messages = args[1] if args else kwargs.get("run_messages") - - def _trace_stream(): - start = time.time() - span = start_span( - name=span_name, - type=SpanTypeAttribute.TASK, - input={"run_response": run_response, "run_messages": run_messages}, - metadata={**omit(kwargs, ["run_response", "run_messages"]), **extract_metadata(instance, "team")}, - ) - span.set_current() - - should_unset = True - try: - first = True - all_chunks = [] - - for chunk in wrapped(*args, **kwargs): - if first: - span.log( - metrics={ - "time_to_first_token": time.time() - start, - } - ) - first = False - all_chunks.append(chunk) - yield chunk - - aggregated = _aggregate_agent_chunks(all_chunks) - - span.log( - output=aggregated, - metrics=extract_streaming_metrics(aggregated, start), - ) - except GeneratorExit: - # Generator was closed early (e.g., break from for loop) - # Don't call unset_current() as context may have changed - should_unset = False - raise - except Exception as e: - span.log( - error=str(e), - ) - raise - finally: - if should_unset: - span.unset_current() - span.end() - - return _trace_stream() - - if hasattr(Team, "_run_stream"): - wrap_function_wrapper(Team, "_run_stream", run_stream_wrapper) - - def arun_stream_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - agent_name = getattr(instance, "name", None) or "Team" - span_name = f"{agent_name}.arun_stream" - - run_response = args[0] if args else kwargs.get("run_response") - input = args[2] if args else kwargs.get("input") - - async def _trace_stream(): - start = time.time() - span = start_span( - name=span_name, - type=SpanTypeAttribute.TASK, - input={"run_response": run_response, "input": input}, - metadata={**omit(kwargs, ["run_response", "input"]), **extract_metadata(instance, "team")}, - ) - span.set_current() - - should_unset = True - try: - first = True - all_chunks = [] - - async for chunk in wrapped(*args, **kwargs): - if first: - span.log( - metrics={ - "time_to_first_token": time.time() - start, - } - ) - first = False - all_chunks.append(chunk) - yield chunk - - aggregated = _aggregate_agent_chunks(all_chunks) - - span.log( - output=aggregated, - metrics=extract_streaming_metrics(aggregated, start), - ) - except GeneratorExit: - # Generator was closed early (e.g., break from async for loop) - # Don't call unset_current() as context may have changed - should_unset = False - raise - except Exception as e: - span.log( - error=str(e), - ) - raise - finally: - if should_unset: - span.unset_current() - span.end() - - return _trace_stream() - - if hasattr(Team, "_arun_stream"): - wrap_function_wrapper(Team, "_arun_stream", arun_stream_wrapper) - - mark_patched(Team) - return Team diff --git a/py/src/braintrust/wrappers/agno/utils.py b/py/src/braintrust/wrappers/agno/utils.py deleted file mode 100644 index 8aabe989e..000000000 --- a/py/src/braintrust/wrappers/agno/utils.py +++ /dev/null @@ -1,409 +0,0 @@ -import time -from typing import Any - -from braintrust.util import is_numeric - - -def omit(obj: dict[str, Any], keys: list[str]): - return {k: v for k, v in obj.items() if k not in keys} - - -def is_patched(obj: Any) -> bool: - return getattr(obj, "_braintrust_patched", False) - - -def mark_patched(obj: Any): - setattr(obj, "_braintrust_patched", True) - - -def clean(obj: dict[str, Any]) -> dict[str, Any]: - return {k: v for k, v in obj.items() if v is not None} - - -def get_args_kwargs(args: list[str], kwargs: dict[str, Any], keys: list[str]): - return {k: args[i] if args else kwargs.get(k) for i, k in enumerate(keys)}, omit(kwargs, keys) - - - -def _try_to_dict(obj: Any) -> Any: - """Convert object to dict, handling different object types like OpenAI wrapper.""" - if isinstance(obj, dict): - return obj - # convert a pydantic object to a dict - if hasattr(obj, "model_dump") and callable(obj.model_dump): - try: - return obj.model_dump() - except Exception: - pass - # deprecated pydantic method, try model_dump first. - if hasattr(obj, "dict") and callable(obj.dict): - try: - return obj.dict() - except Exception: - pass - # handle objects with __dict__ (like Agno Metrics objects) - if hasattr(obj, "__dict__"): - try: - return obj.__dict__.copy() - except Exception: - pass - return obj - - -# Agno field names to canonical Braintrust field names (following OpenAI wrapper pattern) -AGNO_METRICS_MAP = { - # Core token metrics - using OpenAI wrapper naming - "input_tokens": "prompt_tokens", - "output_tokens": "completion_tokens", - "total_tokens": "tokens", - # Reasoning and audio tokens - "reasoning_tokens": "completion_reasoning_tokens", - "audio_input_tokens": "prompt_audio_tokens", - "audio_output_tokens": "completion_audio_tokens", - # Cache tokens - "cache_read_tokens": "prompt_cached_tokens", - "cache_write_tokens": "prompt_cache_creation_tokens", - # Timing metrics - "duration": "duration", - "time_to_first_token": "time_to_first_token", -} - - -def extract_metadata(instance: Any, component: str) -> dict[str, Any]: - """Extract metadata from any component (model, agent, team).""" - metadata = {"component": component} - - # Component-specific name fields - if component == "model": - if hasattr(instance, "id") and instance.id: - metadata["model"] = instance.id - metadata["model_id"] = instance.id - if hasattr(instance, "provider") and instance.provider: - metadata["provider"] = instance.provider - if hasattr(instance, "name") and instance.name: - metadata["model_name"] = instance.name - if hasattr(instance, "__class__"): - metadata["model_class"] = instance.__class__.__name__ - elif component == "agent": - metadata["agent_name"] = getattr(instance, "name", None) - model = getattr(instance, "model", None) - if model: - metadata["model"] = getattr(model, "id", None) or model.__class__.__name__ - elif component == "team": - metadata["team_name"] = getattr(instance, "name", None) - model = getattr(instance, "model", None) - if model: - metadata["model"] = getattr(model, "id", None) or model.__class__.__name__ - - return metadata - - -def parse_metrics_from_agno(usage: Any) -> dict[str, Any]: - """Parse metrics from Agno usage object, following OpenAI wrapper pattern.""" - metrics = {} - - if not usage: - return metrics - - # Convert to dict like OpenAI wrapper - usage_dict = _try_to_dict(usage) - if not isinstance(usage_dict, dict): - return metrics - - # Simple loop through Agno fields and map to Braintrust names - for agno_name, value in usage_dict.items(): - if agno_name in AGNO_METRICS_MAP and is_numeric(value) and value != 0: - braintrust_name = AGNO_METRICS_MAP[agno_name] - metrics[braintrust_name] = value - - return metrics - - -def extract_metrics(result: Any, messages: list | None = None) -> dict[str, Any]: - """ - Unified metrics extraction for all components. - - Handles: - - Model responses with response_usage - - Agent/Team responses with metrics - - Messages with metrics (for model responses) - """ - # For model responses with response_usage - if hasattr(result, "response_usage") and result.response_usage: - return parse_metrics_from_agno(result.response_usage) - - # For agent/team responses with metrics - if hasattr(result, "metrics") and result.metrics: - agno_metrics = result.metrics - metrics = {} - - # Direct field mapping for agent/team metrics - if hasattr(agno_metrics, "input_tokens") and agno_metrics.input_tokens: - metrics["prompt_tokens"] = agno_metrics.input_tokens - if hasattr(agno_metrics, "output_tokens") and agno_metrics.output_tokens: - metrics["completion_tokens"] = agno_metrics.output_tokens - if hasattr(agno_metrics, "total_tokens") and agno_metrics.total_tokens: - metrics["total_tokens"] = agno_metrics.total_tokens - if hasattr(agno_metrics, "duration") and agno_metrics.duration: - metrics["duration"] = agno_metrics.duration - if hasattr(agno_metrics, "time_to_first_token") and agno_metrics.time_to_first_token: - metrics["time_to_first_token"] = agno_metrics.time_to_first_token - - return metrics if metrics else None - - # If no metrics found and we have messages, look for metrics in assistant messages (model-specific) - if messages: - for msg in messages: - # Look for assistant messages with metrics - if hasattr(msg, "role") and msg.role == "assistant" and hasattr(msg, "metrics") and msg.metrics: - return parse_metrics_from_agno(msg.metrics) - - return {} - - -def extract_streaming_metrics(aggregated: dict[str, Any], start_time: float) -> dict[str, Any] | None: - """Extract metrics from aggregated streaming response.""" - metrics = {} - - # Add duration - metrics["duration"] = time.time() - start_time - - # Extract metrics from aggregated data - # The metrics are already in Braintrust format from _aggregate_model_chunks - if aggregated.get("metrics") and isinstance(aggregated["metrics"], dict): - # Merge the aggregated metrics - metrics.update(aggregated["metrics"]) - # Also check response_usage for backward compatibility - elif aggregated.get("response_usage"): - response_metrics = parse_metrics_from_agno(aggregated["response_usage"]) - if response_metrics: - metrics.update(response_metrics) - - # Ensure we have the duration calculated from start_time - metrics["duration"] = time.time() - start_time - - return metrics if metrics else None - - -def _aggregate_metrics(target: dict[str, Any], source: dict[str, Any]) -> None: - """Aggregate metrics from source into target dict.""" - for key, value in source.items(): - if is_numeric(value): - if key in target: - # For timing metrics, we keep the latest - if "time" in key.lower() or "duration" in key.lower(): - target[key] = value - # For token counts, we sum them - elif "token" in key.lower() or key == "tokens": - target[key] = (target.get(key, 0) or 0) + value - # For other metrics, keep the latest - else: - target[key] = value - else: - target[key] = value - - -def _aggregate_model_chunks(chunks: list[Any]) -> dict[str, Any]: - """Aggregate ModelResponse chunks from invoke_stream into a complete response.""" - aggregated = { - "content": "", - "reasoning_content": "", - "tool_calls": [], - "role": None, - "audio": None, - "images": [], - "videos": [], - "files": [], - "citations": None, - "metrics": {}, - } - - for chunk in chunks: - if hasattr(chunk, "content") and chunk.content: - aggregated["content"] += str(chunk.content) - - if hasattr(chunk, "reasoning_content") and chunk.reasoning_content: - aggregated["reasoning_content"] += chunk.reasoning_content - - if hasattr(chunk, "role") and chunk.role and not aggregated["role"]: - aggregated["role"] = chunk.role - - if hasattr(chunk, "tool_calls") and chunk.tool_calls: - aggregated["tool_calls"].extend(chunk.tool_calls) - - if hasattr(chunk, "audio") and chunk.audio: - aggregated["audio"] = chunk.audio - - if hasattr(chunk, "images") and chunk.images: - aggregated["images"].extend(chunk.images) - - if hasattr(chunk, "videos") and chunk.videos: - aggregated["videos"].extend(chunk.videos) - - if hasattr(chunk, "files") and chunk.files: - aggregated["files"].extend(chunk.files) - - if hasattr(chunk, "citations") and chunk.citations: - aggregated["citations"] = chunk.citations - - if hasattr(chunk, "response_usage") and chunk.response_usage: - # Parse and aggregate metrics from each chunk - chunk_metrics = parse_metrics_from_agno(chunk.response_usage) - if chunk_metrics: - _aggregate_metrics(aggregated["metrics"], chunk_metrics) - - # Convert aggregated metrics dict to the response_usage format for backward compatibility - if aggregated["metrics"]: - aggregated["response_usage"] = aggregated["metrics"] - else: - aggregated["metrics"] = None - - return aggregated - - -def _aggregate_response_stream_chunks(chunks: list[Any]) -> dict[str, Any]: - """ - Aggregate chunks from response_stream which can be ModelResponse, RunOutputEvent, or TeamRunOutputEvent. - - This is more robust than _aggregate_model_chunks as it handles different event types. - """ - aggregated = { - "content": "", - "reasoning_content": "", - "tool_calls": [], - "role": None, - "audio": None, - "images": [], - "videos": [], - "files": [], - "citations": None, - "metrics": {}, - } - - for chunk in chunks: - # Handle ModelResponse chunks - if hasattr(chunk, "__class__") and "ModelResponse" in chunk.__class__.__name__: - if hasattr(chunk, "content") and chunk.content: - aggregated["content"] += str(chunk.content) - - if hasattr(chunk, "reasoning_content") and chunk.reasoning_content: - aggregated["reasoning_content"] += chunk.reasoning_content - - if hasattr(chunk, "role") and chunk.role and not aggregated["role"]: - aggregated["role"] = chunk.role - - if hasattr(chunk, "tool_calls") and chunk.tool_calls: - aggregated["tool_calls"].extend(chunk.tool_calls) - - if hasattr(chunk, "audio") and chunk.audio: - aggregated["audio"] = chunk.audio - - if hasattr(chunk, "images") and chunk.images: - aggregated["images"].extend(chunk.images) - - if hasattr(chunk, "videos") and chunk.videos: - aggregated["videos"].extend(chunk.videos) - - if hasattr(chunk, "files") and chunk.files: - aggregated["files"].extend(chunk.files) - - if hasattr(chunk, "citations") and chunk.citations: - aggregated["citations"] = chunk.citations - - if hasattr(chunk, "response_usage") and chunk.response_usage: - # Parse and aggregate metrics from each chunk - chunk_metrics = parse_metrics_from_agno(chunk.response_usage) - if chunk_metrics: - _aggregate_metrics(aggregated["metrics"], chunk_metrics) - - # Also check for metrics attribute directly (for some response types) - elif hasattr(chunk, "metrics") and chunk.metrics: - chunk_metrics = parse_metrics_from_agno(chunk.metrics) - if chunk_metrics: - _aggregate_metrics(aggregated["metrics"], chunk_metrics) - - # Handle RunOutputEvent/TeamRunOutputEvent chunks - these typically contain content - elif hasattr(chunk, "content"): - if chunk.content: - aggregated["content"] += str(chunk.content) - - # Handle other event types that might have metrics - if hasattr(chunk, "metrics") and chunk.metrics and "metrics" not in str(type(chunk)): - chunk_metrics = parse_metrics_from_agno(chunk.metrics) - if chunk_metrics: - _aggregate_metrics(aggregated["metrics"], chunk_metrics) - - # Convert aggregated metrics dict to the response_usage format for backward compatibility - if aggregated["metrics"]: - aggregated["response_usage"] = aggregated["metrics"] - else: - aggregated["metrics"] = None - - return aggregated - - -def _aggregate_agent_chunks(chunks: list[Any]) -> dict[str, Any]: - """Aggregate BaseAgentRunEvent/BaseTeamRunEvent chunks into a complete response.""" - aggregated = { - "content": "", - "reasoning_content": "", - "model": "", - "model_provider": "", - "tool_calls": [], - "citations": None, - "references": None, - "metrics": None, - "finish_reason": None, - } - - for chunk in chunks: - # Handle RunStartedEvent - if hasattr(chunk, "event") and chunk.event == "RunStarted": - if hasattr(chunk, "model"): - aggregated["model"] = chunk.model - if hasattr(chunk, "model_provider"): - aggregated["model_provider"] = chunk.model_provider - - # Handle RunContentEvent - elif hasattr(chunk, "event") and chunk.event == "RunContent": - if hasattr(chunk, "content") and chunk.content: - aggregated["content"] += str(chunk.content) # type: ignore - if hasattr(chunk, "reasoning_content") and chunk.reasoning_content: - aggregated["reasoning_content"] += chunk.reasoning_content - if hasattr(chunk, "citations"): - aggregated["citations"] = chunk.citations - if hasattr(chunk, "references"): - aggregated["references"] = chunk.references - - # Handle RunCompletedEvent - elif hasattr(chunk, "event") and chunk.event == "RunCompleted": - if hasattr(chunk, "metrics"): - aggregated["metrics"] = chunk.metrics - aggregated["finish_reason"] = "stop" - - # Handle RunError - elif hasattr(chunk, "event") and chunk.event == "RunError": - aggregated["finish_reason"] = "error" - - # Handle tool calls - elif hasattr(chunk, "event") and chunk.event == "ToolCallStarted": - if hasattr(chunk, "tool_call"): - aggregated["tool_calls"].append( # type:ignore - { - "id": getattr(chunk.tool_call, "id", None), - "type": "function", - "function": { - "name": getattr(chunk.tool_call, "name", None), - "arguments": getattr(chunk.tool_call, "arguments", ""), - }, - } - ) - - return {k: v for k, v in aggregated.items() if v not in (None, "")} - - -# Legacy aliases for backward compatibility -_extract_run_metrics = extract_metrics -_extract_streaming_metrics = extract_streaming_metrics -_extract_model_metrics = extract_metrics -_parse_metrics_from_agno = parse_metrics_from_agno diff --git a/py/src/braintrust/wrappers/anthropic.py b/py/src/braintrust/wrappers/anthropic.py deleted file mode 100644 index 26033536d..000000000 --- a/py/src/braintrust/wrappers/anthropic.py +++ /dev/null @@ -1,424 +0,0 @@ -import logging -import time -import warnings -from contextlib import contextmanager - -from braintrust.logger import NOOP_SPAN, log_exc_info_to_span, start_span -from braintrust.wrappers._anthropic_utils import Wrapper, extract_anthropic_usage, finalize_anthropic_tokens -from wrapt import wrap_function_wrapper - -log = logging.getLogger(__name__) - - -# This tracer depends on an internal anthropic method used to merge -# streamed messages together. It's a bit tricky so I'm opting to use it -# here. If it goes away, this polyfill will make it a no-op and the only -# result will be missing `output` and metrics in our spans. Our tests always -# run against the latest version of anthropic's SDK, so we'll know. -# anthropic-sdk-python/blob/main/src/anthropic/lib/streaming/_messages.py#L392 -try: - from anthropic.lib.streaming._messages import accumulate_event -except ImportError: - - def accumulate_event(event=None, current_snapshot=None, **kwargs): - warnings.warn("braintrust: missing method: anthropic.lib.streaming._messages.accumulate_event") - return current_snapshot - - -# Anthropic model parameters that we want to track as span metadata. -METADATA_PARAMS = ( - "model", - "max_tokens", - "temperature", - "top_k", - "top_p", - "stop_sequences", - "tool_choice", - "tools", - "stream", -) - - -class TracedAsyncAnthropic(Wrapper): - def __init__(self, client): - super().__init__(client) - self.__client = client - - @property - def messages(self): - return AsyncMessages(self.__client.messages) - - @property - def beta(self): - return AsyncBeta(self.__client.beta) - - -class AsyncMessages(Wrapper): - def __init__(self, messages): - super().__init__(messages) - self.__messages = messages - - async def create(self, *args, **kwargs): - if kwargs.get("stream", False): - return await self.__create_with_stream_true(*args, **kwargs) - else: - return await self.__create_with_stream_false(*args, **kwargs) - - async def __create_with_stream_false(self, *args, **kwargs): - span = _start_span("anthropic.messages.create", kwargs) - request_start_time = time.time() - try: - result = await self.__messages.create(*args, **kwargs) - ttft = time.time() - request_start_time - with _catch_exceptions(): - _log_message_to_span(result, span, time_to_first_token=ttft) - return result - except Exception as e: - with _catch_exceptions(): - span.log(error=e) - raise - finally: - span.end() - - async def __create_with_stream_true(self, *args, **kwargs): - span = _start_span("anthropic.messages.stream", kwargs) - request_start_time = time.time() - try: - stream = await self.__messages.create(*args, **kwargs) - except Exception as e: - with _catch_exceptions(): - span.log(error=e) - span.end() - raise - - traced_stream = TracedMessageStream(stream, span, request_start_time) - - async def async_stream(): - try: - async for msg in traced_stream: - yield msg - except Exception as e: - with _catch_exceptions(): - span.log(error=e) - raise - finally: - with _catch_exceptions(): - msg = traced_stream._get_final_traced_message() - if msg: - ttft = traced_stream._get_time_to_first_token() - _log_message_to_span(msg, span, time_to_first_token=ttft) - span.end() - - return async_stream() - - def stream(self, *args, **kwargs): - span = _start_span("anthropic.messages.stream", kwargs) - request_start_time = time.time() - stream = self.__messages.stream(*args, **kwargs) - return TracedMessageStreamManager(stream, span, request_start_time) - - -class AsyncBeta(Wrapper): - def __init__(self, beta): - super().__init__(beta) - self.__beta = beta - - @property - def messages(self): - return AsyncMessages(self.__beta.messages) - - -class TracedAnthropic(Wrapper): - def __init__(self, client): - super().__init__(client) - self.__client = client - - @property - def messages(self): - return Messages(self.__client.messages) - - @property - def beta(self): - return Beta(self.__client.beta) - - -class Messages(Wrapper): - def __init__(self, messages): - super().__init__(messages) - self.__messages = messages - - def stream(self, *args, **kwargs): - return self.__trace_stream(self.__messages.stream, *args, **kwargs) - - def create(self, *args, **kwargs): - # If stream is True, we need to trace the stream function - if kwargs.get("stream"): - return self.__trace_stream(self.__messages.create, *args, **kwargs) - - span = _start_span("anthropic.messages.create", kwargs) - request_start_time = time.time() - try: - msg = self.__messages.create(*args, **kwargs) - ttft = time.time() - request_start_time - _log_message_to_span(msg, span, time_to_first_token=ttft) - return msg - except Exception as e: - span.log(error=e) - raise - finally: - span.end() - - def __trace_stream(self, stream_func, *args, **kwargs): - span = _start_span("anthropic.messages.stream", kwargs) - request_start_time = time.time() - s = stream_func(*args, **kwargs) - return TracedMessageStreamManager(s, span, request_start_time) - - -class Beta(Wrapper): - def __init__(self, beta): - super().__init__(beta) - self.__beta = beta - - @property - def messages(self): - return Messages(self.__beta.messages) - - -class TracedMessageStreamManager(Wrapper): - def __init__(self, msg_stream_mgr, span, request_start_time: float): - super().__init__(msg_stream_mgr) - self.__msg_stream_mgr = msg_stream_mgr - self.__traced_message_stream = None - self.__span = span - self.__request_start_time = request_start_time - - async def __aenter__(self): - ms = await self.__msg_stream_mgr.__aenter__() - self.__traced_message_stream = TracedMessageStream(ms, self.__span, self.__request_start_time) - return self.__traced_message_stream - - def __enter__(self): - ms = self.__msg_stream_mgr.__enter__() - self.__traced_message_stream = TracedMessageStream(ms, self.__span, self.__request_start_time) - return self.__traced_message_stream - - def __aexit__(self, exc_type, exc_value, traceback): - try: - return self.__msg_stream_mgr.__aexit__(exc_type, exc_value, traceback) - finally: - with _catch_exceptions(): - self.__close(exc_type, exc_value, traceback) - - def __exit__(self, exc_type, exc_value, traceback): - try: - return self.__msg_stream_mgr.__exit__(exc_type, exc_value, traceback) - finally: - with _catch_exceptions(): - self.__close(exc_type, exc_value, traceback) - - def __close(self, exc_type, exc_value, traceback): - with _catch_exceptions(): - tms = self.__traced_message_stream - msg = tms._get_final_traced_message() - if msg: - ttft = tms._get_time_to_first_token() - _log_message_to_span(msg, self.__span, time_to_first_token=ttft) - if exc_type: - log_exc_info_to_span(self.__span, exc_type, exc_value, traceback) - self.__span.end() - - -class TracedMessageStream(Wrapper): - """TracedMessageStream wraps both sync and async message streams. Obviously only one - makes sense at a time - """ - - def __init__(self, msg_stream, span, request_start_time: float): - super().__init__(msg_stream) - self.__msg_stream = msg_stream - self.__span = span - self.__metrics = {} - self.__snapshot = None - self.__request_start_time = request_start_time - self.__time_to_first_token: float | None = None - - def _get_final_traced_message(self): - return self.__snapshot - - def _get_time_to_first_token(self): - return self.__time_to_first_token - - def __await__(self): - return self.__msg_stream.__await__() - - def __aiter__(self): - return self - - def __iter__(self): - return self - - async def __anext__(self): - m = await self.__msg_stream.__anext__() - with _catch_exceptions(): - self.__process_message(m) - return m - - def __next__(self): - m = next(self.__msg_stream) - with _catch_exceptions(): - self.__process_message(m) - return m - - def __process_message(self, m): - # Track time to first token on the first message - if self.__time_to_first_token is None: - self.__time_to_first_token = time.time() - self.__request_start_time - - with _catch_exceptions(): - self.__snapshot = accumulate_event(event=m, current_snapshot=self.__snapshot) - - -def _get_input_from_kwargs(kwargs): - msgs = list(kwargs.get("messages", [])) - # save a copy of the messages because it might be a generator - # and we may mutate it. - kwargs["messages"] = msgs.copy() - - system = kwargs.get("system", None) - if system: - msgs.append({"role": "system", "content": system}) - return msgs - - -def _get_metadata_from_kwargs(kwargs): - metadata = {"provider": "anthropic"} - for k in METADATA_PARAMS: - v = kwargs.get(k, None) - if v is not None: - metadata[k] = v - return metadata - - -def _start_span(name, kwargs): - """Start a span with the given name, tagged with all of the relevant data from kwargs. kwargs is the dictionary of options - passed into anthropic.messages.create or anthropic.messages.stream. - """ - with _catch_exceptions(): - _input = _get_input_from_kwargs(kwargs) - metadata = _get_metadata_from_kwargs(kwargs) - return start_span(name=name, type="llm", metadata=metadata, input=_input) - - # if this failed, maintain the API. - return NOOP_SPAN - - -def _log_message_to_span(message, span, time_to_first_token: float | None = None): - """Log telemetry from the given anthropic.Message to the given span.""" - with _catch_exceptions(): - usage = getattr(message, "usage", {}) - metrics = finalize_anthropic_tokens(extract_anthropic_usage(usage)) - - # Add time_to_first_token if provided - if time_to_first_token is not None: - metrics["time_to_first_token"] = time_to_first_token - - # Create output dict with only truthy values for role and content - output = { - k: v - for k, v in {"role": getattr(message, "role", None), "content": getattr(message, "content", None)}.items() - if v - } or None - - span.log(output=output, metrics=metrics) - - -@contextmanager -def _catch_exceptions(): - try: - yield - except Exception as e: - log.warning("swallowing exception in tracing code", exc_info=e) - - -def wrap_anthropic(client): - """Wrap an `Anthropic` object (or AsyncAnthropic) to add tracing. If Braintrust - is not configured, this is a no-op. If this is not an `Anthropic` object, this - function is a no-op. - """ - type_name = getattr(type(client), "__name__") - # We use 'in' because it could be AsyncAnthropicBedrock - if "AsyncAnthropic" in type_name: - return TracedAsyncAnthropic(client) - elif "Anthropic" in type_name: - return TracedAnthropic(client) - else: - # Unexpected. - return client - - -def wrap_anthropic_client(client): - return wrap_anthropic(client) - - -def _apply_anthropic_wrapper(client): - """Apply tracing wrapper to an Anthropic client instance in-place.""" - wrapped = wrap_anthropic(client) - client.messages = wrapped.messages - if hasattr(wrapped, "beta"): - client.beta = wrapped.beta - - -def _apply_async_anthropic_wrapper(client): - """Apply tracing wrapper to an AsyncAnthropic client instance in-place.""" - wrapped = wrap_anthropic(client) - client.messages = wrapped.messages - if hasattr(wrapped, "beta"): - client.beta = wrapped.beta - - -def _anthropic_init_wrapper(wrapped, instance, args, kwargs): - """Wrapper for Anthropic.__init__ that applies tracing after initialization.""" - wrapped(*args, **kwargs) - _apply_anthropic_wrapper(instance) - - -def _async_anthropic_init_wrapper(wrapped, instance, args, kwargs): - """Wrapper for AsyncAnthropic.__init__ that applies tracing after initialization.""" - wrapped(*args, **kwargs) - _apply_async_anthropic_wrapper(instance) - - -def patch_anthropic() -> bool: - """ - Patch Anthropic to add Braintrust tracing globally. - - After calling this, all new Anthropic() and AsyncAnthropic() clients - will automatically have tracing enabled. - - Returns: - True if Anthropic was patched (or already patched), False if Anthropic is not installed. - - Example: - ```python - import braintrust - braintrust.patch_anthropic() - - import anthropic - client = anthropic.Anthropic() - # All calls are now traced! - ``` - """ - try: - import anthropic - - if getattr(anthropic, "__braintrust_wrapped__", False): - return True # Already patched - - wrap_function_wrapper("anthropic", "Anthropic.__init__", _anthropic_init_wrapper) - wrap_function_wrapper("anthropic", "AsyncAnthropic.__init__", _async_anthropic_init_wrapper) - anthropic.__braintrust_wrapped__ = True - return True - - except ImportError: - return False diff --git a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_agno.py b/py/src/braintrust/wrappers/auto_test_scripts/test_auto_agno.py deleted file mode 100644 index ecfca75e8..000000000 --- a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_agno.py +++ /dev/null @@ -1,117 +0,0 @@ -"""Test auto_instrument for Agno (no uninstrument available).""" - -from braintrust.auto import auto_instrument -from braintrust.wrappers.test_utils import autoinstrument_test_context - -# 1. Instrument -results = auto_instrument() -assert results.get("agno") == True, "auto_instrument should return True for agno" - -# 2. Idempotent -results2 = auto_instrument() -assert results2.get("agno") == True, "auto_instrument should still return True on second call" - -# 3. Verify methods are wrapped -from agno.agent import Agent -from agno.models.base import Model -from agno.team import Team -from agno.tools.function import FunctionCall - - -def check_wrapped(klass, private_method, public_method, required=True): - """Check if at least one method (private or public) is wrapped.""" - wrapped = False - if private_method and hasattr(klass, private_method): - if hasattr(getattr(klass, private_method), "__wrapped__"): - wrapped = True - if not wrapped and public_method and hasattr(klass, public_method): - if hasattr(getattr(klass, public_method), "__wrapped__"): - wrapped = True - - if required: - assert wrapped, f"{klass.__name__} should have {private_method or public_method} wrapped" - # If not required and nothing is wrapped, that's okay (method doesn't exist in this version) - - -# Agent methods -check_wrapped(Agent, "_run", "run", required=True) -check_wrapped(Agent, "_arun", "arun", required=True) -check_wrapped(Agent, "_run_stream", None, required=False) # Optional - only in 2.4.0 -check_wrapped(Agent, "_arun_stream", None, required=False) # Optional - only in 2.4.0 - -# Team methods -check_wrapped(Team, "_run", "run", required=True) -check_wrapped(Team, "_arun", "arun", required=True) -check_wrapped(Team, "_run_stream", None, required=False) -check_wrapped(Team, "_arun_stream", None, required=False) - -# Model methods (all public, all required) -assert hasattr(Model, "invoke") and hasattr(Model.invoke, "__wrapped__"), "Model.invoke should be wrapped" -assert hasattr(Model, "ainvoke") and hasattr(Model.ainvoke, "__wrapped__"), "Model.ainvoke should be wrapped" -assert hasattr(Model, "invoke_stream") and hasattr( - Model.invoke_stream, "__wrapped__" -), "Model.invoke_stream should be wrapped" -assert hasattr(Model, "ainvoke_stream") and hasattr( - Model.ainvoke_stream, "__wrapped__" -), "Model.ainvoke_stream should be wrapped" -assert hasattr(Model, "response") and hasattr(Model.response, "__wrapped__"), "Model.response should be wrapped" -assert hasattr(Model, "aresponse") and hasattr(Model.aresponse, "__wrapped__"), "Model.aresponse should be wrapped" -assert hasattr(Model, "response_stream") and hasattr( - Model.response_stream, "__wrapped__" -), "Model.response_stream should be wrapped" -assert hasattr(Model, "aresponse_stream") and hasattr( - Model.aresponse_stream, "__wrapped__" -), "Model.aresponse_stream should be wrapped" - -# FunctionCall methods (all public, all required) -assert hasattr(FunctionCall, "execute") and hasattr( - FunctionCall.execute, "__wrapped__" -), "FunctionCall.execute should be wrapped" -assert hasattr(FunctionCall, "aexecute") and hasattr( - FunctionCall.aexecute, "__wrapped__" -), "FunctionCall.aexecute should be wrapped" - -# 4. Make API call and verify spans -with autoinstrument_test_context("test_auto_agno") as memory_logger: - from agno.models.openai import OpenAIChat - - agent = Agent( - name="Test Agent", - model=OpenAIChat(id="gpt-4o-mini"), - instructions="You are a helpful assistant. Be brief.", - ) - - response = agent.run("Say hi") - assert response, "Agent should return a response" - assert response.content, "Response should have content" - - spans = memory_logger.pop() - assert len(spans) >= 2, f"Expected at least 2 spans (agent + model), got {len(spans)}" - - # Verify we have an agent span (type: task) - agent_spans = [s for s in spans if "Test Agent" in s.get("span_attributes", {}).get("name", "")] - assert len(agent_spans) >= 1, "Should have at least one agent span" - - # Verify agent span is type TASK - agent_span = agent_spans[0] - assert agent_span.get("span_attributes", {}).get("type", {}).value == "task", "Agent span should be type 'task'" - - # Verify we have a model span (type: llm) - llm_spans = [s for s in spans if s.get("span_attributes", {}).get("type", {}).value == "llm"] - assert len(llm_spans) >= 1, f"Should have at least one LLM span, got {len(llm_spans)}" - - # Verify model span has expected attributes - llm_span = llm_spans[0] - assert "OpenAI" in llm_span.get("span_attributes", {}).get("name", ""), "LLM span should contain 'OpenAI'" - assert llm_span.get("metadata", {}).get("provider") == "OpenAI", "LLM span should have OpenAI provider" - - # Verify span hierarchy - LLM span should be child of agent span - llm_parents = llm_span.get("span_parents", []) - agent_span_id = agent_span.get("span_id") - assert agent_span_id in llm_parents, f"LLM span should be child of agent span. Agent ID: {agent_span_id}, LLM parents: {llm_parents}" - - print("Agent span created (type: task)") - print("Model span created (type: llm)") - print("Span hierarchy verified (model is child of agent)") - -print("SUCCESS") diff --git a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_anthropic.py b/py/src/braintrust/wrappers/auto_test_scripts/test_auto_anthropic.py deleted file mode 100644 index 6a6b32f86..000000000 --- a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_anthropic.py +++ /dev/null @@ -1,35 +0,0 @@ -"""Test auto_instrument for Anthropic.""" - -import anthropic -from braintrust.auto import auto_instrument -from braintrust.wrappers.test_utils import autoinstrument_test_context - -# 1. Verify not patched initially -assert not getattr(anthropic, "__braintrust_wrapped__", False) - -# 2. Instrument -results = auto_instrument() -assert results.get("anthropic") == True -assert getattr(anthropic, "__braintrust_wrapped__", False) - -# 3. Idempotent -results2 = auto_instrument() -assert results2.get("anthropic") == True - -# 4. Make API call and verify span -with autoinstrument_test_context("test_auto_anthropic") as memory_logger: - client = anthropic.Anthropic() - response = client.messages.create( - model="claude-3-5-haiku-20241022", - max_tokens=100, - messages=[{"role": "user", "content": "Say hi"}], - ) - assert response.content[0].text - - spans = memory_logger.pop() - assert len(spans) == 1, f"Expected 1 span, got {len(spans)}" - span = spans[0] - assert span["metadata"]["provider"] == "anthropic" - assert "claude" in span["metadata"]["model"] - -print("SUCCESS") diff --git a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_claude_agent_sdk.py b/py/src/braintrust/wrappers/auto_test_scripts/test_auto_claude_agent_sdk.py deleted file mode 100644 index 48a2915fe..000000000 --- a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_claude_agent_sdk.py +++ /dev/null @@ -1,35 +0,0 @@ -"""Test auto_instrument for Claude Agent SDK (no uninstrument available).""" - -from braintrust.auto import auto_instrument -from braintrust.wrappers.test_utils import autoinstrument_test_context - -# 1. Instrument -results = auto_instrument() -assert results.get("claude_agent_sdk") == True - -# 2. Idempotent -results2 = auto_instrument() -assert results2.get("claude_agent_sdk") == True - -# 3. Make API call and verify span -with autoinstrument_test_context("test_auto_claude_agent_sdk") as memory_logger: - import claude_agent_sdk # pylint: disable=import-error - - options = claude_agent_sdk.ClaudeAgentOptions(model="claude-3-5-haiku-20241022") - - async def run_agent(): - async with claude_agent_sdk.ClaudeSDKClient(options=options) as client: - await client.query("Say hi") - async for message in client.receive_response(): - if type(message).__name__ == "ResultMessage": - return message - return None - - import asyncio - result = asyncio.run(run_agent()) - assert result is not None - - spans = memory_logger.pop() - assert len(spans) >= 1, f"Expected at least 1 span, got {len(spans)}" - -print("SUCCESS") diff --git a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_dspy.py b/py/src/braintrust/wrappers/auto_test_scripts/test_auto_dspy.py deleted file mode 100644 index 4a2fccdfd..000000000 --- a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_dspy.py +++ /dev/null @@ -1,31 +0,0 @@ -"""Test auto_instrument for DSPy. - -Note: This test focuses on patching behavior only. Span verification for DSPy -is done in test_dspy.py::test_dspy_callback which uses pytest-vcr (supports httpx). -The standalone VCR in test_utils doesn't capture httpx used by litellm/dspy. -""" - -import dspy -from braintrust.auto import auto_instrument -from braintrust.wrappers.dspy import BraintrustDSpyCallback - -# 1. Verify not patched initially -assert not getattr(dspy, "__braintrust_wrapped__", False) - -# 2. Instrument -results = auto_instrument() -assert results.get("dspy") == True -assert getattr(dspy, "__braintrust_wrapped__", False) - -# 3. Idempotent -results2 = auto_instrument() -assert results2.get("dspy") == True - -# 4. Verify callback is added when configure() is called -dspy.configure(lm=None) -from dspy.dsp.utils.settings import settings - -has_bt_callback = any(isinstance(cb, BraintrustDSpyCallback) for cb in settings.callbacks) -assert has_bt_callback, f"Expected BraintrustDSpyCallback in callbacks after configure()" - -print("SUCCESS") diff --git a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_google_genai.py b/py/src/braintrust/wrappers/auto_test_scripts/test_auto_google_genai.py deleted file mode 100644 index 4645ae0db..000000000 --- a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_google_genai.py +++ /dev/null @@ -1,32 +0,0 @@ -"""Test auto_instrument for Google GenAI (no uninstrument available).""" - -from braintrust.auto import auto_instrument -from braintrust.wrappers.test_utils import autoinstrument_test_context - -# 1. Instrument -results = auto_instrument() -assert results.get("google_genai") == True - -# 2. Idempotent -results2 = auto_instrument() -assert results2.get("google_genai") == True - -# 3. Make API call and verify span -with autoinstrument_test_context("test_auto_google_genai") as memory_logger: - from google.genai import types - from google.genai.client import Client - - client = Client() - response = client.models.generate_content( - model="gemini-2.0-flash-001", - contents="Say hi", - config=types.GenerateContentConfig(max_output_tokens=100), - ) - assert response.text - - spans = memory_logger.pop() - assert len(spans) == 1, f"Expected 1 span, got {len(spans)}" - span = spans[0] - assert "gemini" in span["metadata"]["model"] - -print("SUCCESS") diff --git a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_litellm.py b/py/src/braintrust/wrappers/auto_test_scripts/test_auto_litellm.py deleted file mode 100644 index 2aeeb9218..000000000 --- a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_litellm.py +++ /dev/null @@ -1,32 +0,0 @@ -"""Test auto_instrument for LiteLLM.""" - -import litellm -from braintrust.auto import auto_instrument -from braintrust.wrappers.test_utils import autoinstrument_test_context - -# 1. Verify not patched initially -assert not hasattr(litellm, "_braintrust_wrapped") - -# 2. Instrument -results = auto_instrument() -assert results.get("litellm") == True -assert hasattr(litellm, "_braintrust_wrapped") - -# 3. Idempotent -results2 = auto_instrument() -assert results2.get("litellm") == True - -# 4. Make API call and verify span -with autoinstrument_test_context("test_auto_litellm") as memory_logger: - response = litellm.completion( - model="gpt-4o-mini", - messages=[{"role": "user", "content": "Say hi"}], - ) - assert response.choices[0].message.content - - spans = memory_logger.pop() - assert len(spans) == 1, f"Expected 1 span, got {len(spans)}" - span = spans[0] - assert span["metadata"]["provider"] == "litellm" - -print("SUCCESS") diff --git a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_openai.py b/py/src/braintrust/wrappers/auto_test_scripts/test_auto_openai.py deleted file mode 100644 index 4fb5f4c82..000000000 --- a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_openai.py +++ /dev/null @@ -1,34 +0,0 @@ -"""Test auto_instrument for OpenAI.""" - -import openai -from braintrust.auto import auto_instrument -from braintrust.wrappers.test_utils import autoinstrument_test_context - -# 1. Verify not patched initially -assert not getattr(openai, "__braintrust_wrapped__", False) - -# 2. Instrument -results = auto_instrument() -assert results.get("openai") == True -assert getattr(openai, "__braintrust_wrapped__", False) - -# 3. Idempotent -results2 = auto_instrument() -assert results2.get("openai") == True - -# 4. Make API call and verify span -with autoinstrument_test_context("test_auto_openai") as memory_logger: - client = openai.OpenAI() - response = client.chat.completions.create( - model="gpt-4o-mini", - messages=[{"role": "user", "content": "Say hi"}], - ) - assert response.choices[0].message.content - - spans = memory_logger.pop() - assert len(spans) == 1, f"Expected 1 span, got {len(spans)}" - span = spans[0] - assert span["metadata"]["provider"] == "openai" - assert "gpt-4o-mini" in span["metadata"]["model"] - -print("SUCCESS") diff --git a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_pydantic_ai.py b/py/src/braintrust/wrappers/auto_test_scripts/test_auto_pydantic_ai.py deleted file mode 100644 index c6b874845..000000000 --- a/py/src/braintrust/wrappers/auto_test_scripts/test_auto_pydantic_ai.py +++ /dev/null @@ -1,35 +0,0 @@ -"""Test auto_instrument for Pydantic AI (no uninstrument available).""" - -from braintrust.auto import auto_instrument -from braintrust.wrappers.test_utils import autoinstrument_test_context - -# 1. Instrument -results = auto_instrument() -assert results.get("pydantic_ai") == True - -# 2. Idempotent -results2 = auto_instrument() -assert results2.get("pydantic_ai") == True - -# 3. Make API call and verify span -with autoinstrument_test_context("test_auto_pydantic_ai") as memory_logger: - from pydantic_ai import Agent - from pydantic_ai.models.openai import OpenAIChatModel - from pydantic_ai.settings import ModelSettings - - agent = Agent( - OpenAIChatModel("gpt-4o-mini"), - model_settings=ModelSettings(max_tokens=100), - ) - - import asyncio - result = asyncio.run(agent.run("Say hi")) - assert result.output - - spans = memory_logger.pop() - assert len(spans) >= 1, f"Expected at least 1 span, got {len(spans)}" - # Find the agent_run span - agent_spans = [s for s in spans if "agent_run" in s["span_attributes"]["name"]] - assert len(agent_spans) >= 1, f"Expected agent_run span, got {[s['span_attributes']['name'] for s in spans]}" - -print("SUCCESS") diff --git a/py/src/braintrust/wrappers/auto_test_scripts/test_patch_litellm_aresponses.py b/py/src/braintrust/wrappers/auto_test_scripts/test_patch_litellm_aresponses.py deleted file mode 100644 index 49867b369..000000000 --- a/py/src/braintrust/wrappers/auto_test_scripts/test_patch_litellm_aresponses.py +++ /dev/null @@ -1,37 +0,0 @@ -"""Test that patch_litellm() patches aresponses.""" - -import asyncio - -import litellm -from braintrust.wrappers.litellm import patch_litellm -from braintrust.wrappers.test_utils import autoinstrument_test_context - -patch_litellm() - - -async def main(): - with autoinstrument_test_context("test_patch_litellm_aresponses") as memory_logger: - response = await litellm.aresponses( - model="gpt-4o-mini", - input="What's 12 + 12?", - instructions="Just the number please", - ) - assert response - assert response.output - assert len(response.output) > 0 - content = response.output[0].content[0].text - assert "24" in content or "twenty-four" in content.lower() - - spans = memory_logger.pop() - assert len(spans) == 1, f"Expected 1 span, got {len(spans)}" - span = spans[0] - assert span["metrics"] - for key, value in span["metrics"].items(): - assert isinstance(value, (int, float)) and not isinstance(value, bool) - assert span["metadata"]["model"] == "gpt-4o-mini" - assert span["metadata"]["provider"] == "litellm" - assert "What's 12 + 12?" in str(span["input"]) - - -asyncio.run(main()) -print("SUCCESS") diff --git a/py/src/braintrust/wrappers/auto_test_scripts/test_patch_litellm_responses.py b/py/src/braintrust/wrappers/auto_test_scripts/test_patch_litellm_responses.py deleted file mode 100644 index e25b2f86a..000000000 --- a/py/src/braintrust/wrappers/auto_test_scripts/test_patch_litellm_responses.py +++ /dev/null @@ -1,31 +0,0 @@ -"""Test that patch_litellm() patches responses.""" - -import litellm -from braintrust.wrappers.litellm import patch_litellm -from braintrust.wrappers.test_utils import autoinstrument_test_context - -patch_litellm() - -with autoinstrument_test_context("test_patch_litellm_responses") as memory_logger: - response = litellm.responses( - model="gpt-4o-mini", - input="What's 12 + 12?", - instructions="Just the number please", - ) - assert response - assert response.output - assert len(response.output) > 0 - content = response.output[0].content[0].text - assert "24" in content or "twenty-four" in content.lower() - - spans = memory_logger.pop() - assert len(spans) == 1, f"Expected 1 span, got {len(spans)}" - span = spans[0] - assert span["metrics"] - for key, value in span["metrics"].items(): - assert isinstance(value, (int, float)) and not isinstance(value, bool) - assert span["metadata"]["model"] == "gpt-4o-mini" - assert span["metadata"]["provider"] == "litellm" - assert "What's 12 + 12?" in str(span["input"]) - -print("SUCCESS") diff --git a/py/src/braintrust/wrappers/cassettes/TestPatchAnthropicAsyncSpans.test_patch_anthropic_async_creates_spans.yaml b/py/src/braintrust/wrappers/cassettes/TestPatchAnthropicAsyncSpans.test_patch_anthropic_async_creates_spans.yaml deleted file mode 100644 index ac5b8caa6..000000000 --- a/py/src/braintrust/wrappers/cassettes/TestPatchAnthropicAsyncSpans.test_patch_anthropic_async_creates_spans.yaml +++ /dev/null @@ -1,107 +0,0 @@ -interactions: -- request: - body: '{"max_tokens":100,"messages":[{"role":"user","content":"Say hi async"}],"model":"claude-3-5-haiku-latest"}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '106' - Content-Type: - - application/json - Host: - - api.anthropic.com - User-Agent: - - PatchedAsyncAnthropic/Python 0.76.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 0.76.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - anthropic-version: - - '2023-06-01' - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - x-stainless-timeout: - - '600' - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAA/3VRTW8TMRD9K8YXQEqk7NIKtBduKAcuSKCqJcix7GltxTuz2GPaVZT/zjj9blVf - bL335s288V6P5CHpQbtkq4flp+XpMti4q8t+1Z90q77XCx29CMZyZVZdf/795ny6oPWP67N48WXq - fo3ffnrR8DxBU0Ep9goEyJQaYEuJhS2yQI6QQV7D7/29nuGmMcdr0GvI8L4oi8qWGV3IhFSLuqzo - OBIqJlXsrEIcNrjB7XY7zRxInke58nDZeBPih4+iUHIycM2oNnodFQexf7fRx8pmcEY1eTVTVSnu - QI3QGngYCQtny6ACXTfI2ZSkOpbbsR7m+aoPfxa6ME0mgy2EEgHQm9ZS3xEF/lZAJ1mxprTQ9bie - Ya8jTpUN0w6w6KFbyXqsC2CcWDVz81zwwAvt3+Lua5s/TAFGyDaZ0/G1/pHtwkv2sNBU+Sl08lnS - QP4XHRiOkCVn+1Nvs9eHw3/q92SIRQIAAA== - headers: - CF-RAY: - - 9be009abe8aa4e4d-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 14 Jan 2026 20:56:04 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - '5000000' - anthropic-ratelimit-input-tokens-remaining: - - '5000000' - anthropic-ratelimit-input-tokens-reset: - - '2026-01-14T20:56:03Z' - anthropic-ratelimit-output-tokens-limit: - - '1000000' - anthropic-ratelimit-output-tokens-remaining: - - '1000000' - anthropic-ratelimit-output-tokens-reset: - - '2026-01-14T20:56:04Z' - anthropic-ratelimit-requests-limit: - - '10000' - anthropic-ratelimit-requests-remaining: - - '9999' - anthropic-ratelimit-requests-reset: - - '2026-01-14T20:56:03Z' - anthropic-ratelimit-tokens-limit: - - '6000000' - anthropic-ratelimit-tokens-remaining: - - '6000000' - anthropic-ratelimit-tokens-reset: - - '2026-01-14T20:56:03Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CX7wMPtPdemQvSMv8LCMY - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - '1286' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/TestPatchAnthropicSpans.test_patch_anthropic_creates_spans.yaml b/py/src/braintrust/wrappers/cassettes/TestPatchAnthropicSpans.test_patch_anthropic_creates_spans.yaml deleted file mode 100644 index b1f532c29..000000000 --- a/py/src/braintrust/wrappers/cassettes/TestPatchAnthropicSpans.test_patch_anthropic_creates_spans.yaml +++ /dev/null @@ -1,105 +0,0 @@ -interactions: -- request: - body: '{"max_tokens":100,"messages":[{"role":"user","content":"Say hi"}],"model":"claude-3-5-haiku-latest"}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '100' - Content-Type: - - application/json - Host: - - api.anthropic.com - User-Agent: - - PatchedAnthropic/Python 0.76.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - 'false' - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 0.76.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - anthropic-version: - - '2023-06-01' - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - x-stainless-timeout: - - '600' - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAA/3WQT0/DMAzFv0rxuZXabjusFyTgsMMucEGAUBQS00RLky5xYFXV7046UfFPnGy9 - 3/OT7RE6J9FAA8LwKLFYFZtCcX2IRV3W66qsa8hBy2ToQsvKar8V69Xu5ebx9Xhd9VcP96e7W7VP - Hhp6nF0YAm8xCd6ZWeAh6EDcUpKEs4Spa57GxU94msm5NLDTGSn0eJHt3HvGPWaDi5l02rYZOcmH - S5iecwjkeuaRB2fTEFrJKHoLnyDgMaIVKd1GY3KI54WaEbTtIzFyB7QBmm3ahwuFTKQk0s6yn7xc - eMLyP7bMzvHYK+zQc8M23V//F63Ubzrl4CJ9l6o6HYP+TQtkpNGnM+cnSu4lTNMHasIXYLYBAAA= - headers: - CF-RAY: - - 9bde85cdffba42f2-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 14 Jan 2026 16:31:16 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - '5000000' - anthropic-ratelimit-input-tokens-remaining: - - '5000000' - anthropic-ratelimit-input-tokens-reset: - - '2026-01-14T16:31:16Z' - anthropic-ratelimit-output-tokens-limit: - - '1000000' - anthropic-ratelimit-output-tokens-remaining: - - '1000000' - anthropic-ratelimit-output-tokens-reset: - - '2026-01-14T16:31:16Z' - anthropic-ratelimit-requests-limit: - - '10000' - anthropic-ratelimit-requests-remaining: - - '9999' - anthropic-ratelimit-requests-reset: - - '2026-01-14T16:31:16Z' - anthropic-ratelimit-tokens-limit: - - '6000000' - anthropic-ratelimit-tokens-remaining: - - '6000000' - anthropic-ratelimit-tokens-reset: - - '2026-01-14T16:31:16Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CX7bAJ22sddhVB8Eb2N2U - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - '731' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/TestPatchOpenAIAsyncSpans.test_patch_openai_async_creates_spans.yaml b/py/src/braintrust/wrappers/cassettes/TestPatchOpenAIAsyncSpans.test_patch_openai_async_creates_spans.yaml deleted file mode 100644 index b1ce141d9..000000000 --- a/py/src/braintrust/wrappers/cassettes/TestPatchOpenAIAsyncSpans.test_patch_openai_async_creates_spans.yaml +++ /dev/null @@ -1,112 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Say hi async"}],"model":"gpt-4o-mini"}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '77' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - PatchedAsyncOpenAI/Python 2.15.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Raw-Response: - - 'true' - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA4ySwW6cMBCG7zyF6/NSAUELu5eqSiMlr9AoQl57ALfGY9lD21W07x4Zdhe2TaRe - OMw3//D/43lNGONa8T3jshckB2fS+2Nx/1QVpdJ1/u1hyA62ol5V4vvDjr7yTVTg4QdIuqg+Sxyc - AdJoZyw9CII4Na+2dVmU+baYwIAKTJR1jtIS00FbnRZZUaZZleb1Wd2jlhD4nj0njDH2On2jT6vg - D9+zbHOpDBCC6IDvr02McY8mVrgIQQcSlvhmgRItgZ2sP4Ix+Ik94m8mhWVPbBawI46MUInjl7XQ - QzsGEc3b0ZgVENYiiRh+svxyJqerSYOd83gIf0l5q60OfeNBBLTRUCB0fKKnhLGXaRnjTT7uPA6O - GsKfMP0uP++CL0+wwN2ZEZIwK82lfjOsUUBCm7DaJZdC9qAW5bJ4MSqNK5CsIv/r5b3Zc2xtu/8Z - vwApwRGoxnlQWt7mXdo8xPv8qO264skwD+B/aQkNafDxGRS0YjTz1fBwDARD02rbgXdez6fTuqbY - 3d1lYreta56ckjcAAAD//wMAcecg90gDAAA= - headers: - CF-RAY: - - 9be009a69b7bc953-IAD - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 14 Jan 2026 20:56:03 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=B4Tkg3SnpDC1kPZyqRMwNFDkjxxXdNwEYILIz1sZ2vg-1768424163-1.0.1.1-3hI_Dc.bZ7eOoXFnJGbbo3CYX_Ymg8L7.RsTw7UKobrTx7_WCJTzdLC_7mihNSoRbCKTa.wQaTn9kzidpz7YxJVU6GsW4iXN8BirBkqsk4M; - path=/; expires=Wed, 14-Jan-26 21:26:03 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=G5fjKK1baClvzyT8pEAmWLEIkYd89xShJDBbQCQ_NIo-1768424163079-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '404' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '661' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_90096f2452fb405da5a26f82019e4ff4 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/TestPatchOpenAISpans.test_patch_openai_creates_spans.yaml b/py/src/braintrust/wrappers/cassettes/TestPatchOpenAISpans.test_patch_openai_creates_spans.yaml deleted file mode 100644 index 2d569eea7..000000000 --- a/py/src/braintrust/wrappers/cassettes/TestPatchOpenAISpans.test_patch_openai_creates_spans.yaml +++ /dev/null @@ -1,112 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Say hi"}],"model":"gpt-4o-mini"}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '71' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - PatchedOpenAI/Python 2.15.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - 'false' - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Raw-Response: - - 'true' - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA4xSy27bMBC86yu2PFuF7cqJ4ksPPdQJ2kMvLYoiEGhyJbGhuAS5Sm0E/veCUmIp - jwK96LCzM5oZ7kMGIIwWWxCqlaw6b/NPh+OH+CPusLtb3pQ/v17X3777w+bzl/u2vBGLxKD9b1T8 - xHqvqPMW2ZAbYRVQMibV1eVFWSzL9UUxAB1ptInWeM4LyjvjTL5erot8eZmvykd2S0ZhFFv4lQEA - PAzf5NNpPIgtLBdPkw5jlA2K7XkJQASyaSJkjCaydCwWE6jIMbrB+s68gx39ASUdXMO4DUfqgUnL - 48c5K2DdR5mcu97aGSCdI5Yp+eD39hE5nR1aanygfXxBFbVxJrZVQBnJJTeRyYsBPWUAt0MT/bNw - wgfqPFdMdzj87mpUE1P9rzEmlnYar8rFG1qVRpbGxlmPQknVop6YU+my14ZmQDZL/NrLW9pjauOa - /5GfAKXQM+rKB9RGPc87rQVMt/mvtXPDg2ERMdwbhRUbDOkVNNayt+PFiHiMjF1VG9dg8MGMZ1P7 - ShWbcrPf7K+UyE7ZXwAAAP//AwCuvReaRAMAAA== - headers: - CF-RAY: - - 9bde85857d3a8191-IAD - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 14 Jan 2026 16:31:05 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=WC8qx7XxkvNS5wuwlfQhz1YXRyMLnO27mFg6CLFQsBA-1768408265-1.0.1.1-CYX0R1gm_JLPDaW7XX1DXFIeIJcSzOBeQt8GvdCwva0SF6kpS7rj822yvepm_lCRzCmfG4LdKQMzdL6iJwxli_Hn5FpXoHbcVT65fyweftE; - path=/; expires=Wed, 14-Jan-26 17:01:05 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=wyzjAd4Rg15mG6l4SO3Ptarr8MXdf2XE6SjjYZWnlPc-1768408265199-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '525' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '547' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_3a43c0bbc3274bf4b365b54caa285598 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_run_async.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_run_async.yaml deleted file mode 100644 index d8cbce6c6..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_run_async.yaml +++ /dev/null @@ -1,111 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 2+2? Answer with just the - number."}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '148' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJNb9swDIbv/hUCz/EQe6nb5LgN27GXoEBRFIYq0Y42SRQkemha5L8P - cj7s7APYxQc+fKn3pfleCAFGw0aA2klWLtjyM+0fP9HX5v7+2/KL3zqXttsHj33zcU9vsMgKevmO - is+qD4pcsMiG/BGriJIxT61um6Zubqp1NQJHGm2W9YHLFZXOeFPWy3pVLm/L6u6k3pFRmGAjngoh - hHgfv9mn1/gKG7FcnCsOU5I9wubSJAREsrkCMiWTWHqGxQQVeUY/Wl/N6xG7IcnszQ/WzoD0nljm - bKOj5xM5XDxY6kOkl/SbFDrjTdq1EWUin99LTAFGeiiEeB6zDlf2IURygVumHzg+V5+iwrThCVYn - xsTSzjTn+tWwViNLY9NsVaCk2qGelNNe5aANzUAxi/ynl7/NPsY2vv+f8RNQCgOjbkNEbdR13qkt - Yj6/f7VdVjwahoTxp1HYssGYf4PGTg72eBSQ9onRtZ3xPcYQzfEyutAiNmtVY7e6g+JQ/AIAAP// - AwDuaeQPJwMAAA== - headers: - CF-RAY: - - 9b12245f08957e95-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:11 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - path=/; expires=Sat, 20-Dec-25 21:43:11 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '157' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '431' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999987' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_33be6e1c06474f88aa886351e283ddd7 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_run_stream.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_run_stream.yaml deleted file mode 100644 index df0a9eb10..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_run_stream.yaml +++ /dev/null @@ -1,155 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 5"}],"model":"gpt-4o-mini","max_completion_tokens":100,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '164' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"AdmWDxOKK"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"99PF7nJyxt"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"PwQJtYjWkW"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"RWDd73VIGm"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"k9VcEaTPe8"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"UbeAPy03Nm"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ZPEZJoyoEX"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"SxJvohEmis"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"PI7a8tVNM5"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"2XRGzzU6oQ"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"4"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Q2nugXZUaQ"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"hZ24zrrpjf"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"dxzuS0d72f"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"KQ60YPfF8R"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"BIXonJxprK"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"SXpgc"} - - - data: {"id":"chatcmpl-CoyYIJD9oebTHQSO9Cv4CtTZen2g4","object":"chat.completion.chunk","created":1766265198,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":14,"total_tokens":28,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"ah4xZweSQB"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b12248a4ae8c8c1-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:18 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '156' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '397' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_a86fc882a88544e99a2b0c6ddc4bde91 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_run_stream_events.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_run_stream_events.yaml deleted file mode 100644 index 3a43dcb6c..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_run_stream_events.yaml +++ /dev/null @@ -1,137 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 5+5?"}],"model":"gpt-4o-mini","max_completion_tokens":100,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '159' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYYeUWSXMSmrqMmtP4fxamq4vM2","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"NUHnuwR08"} - - - data: {"id":"chatcmpl-CoyYYeUWSXMSmrqMmtP4fxamq4vM2","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ZxdaiRZ15E"} - - - data: {"id":"chatcmpl-CoyYYeUWSXMSmrqMmtP4fxamq4vM2","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - +"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"7rq4MBlNH"} - - - data: {"id":"chatcmpl-CoyYYeUWSXMSmrqMmtP4fxamq4vM2","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ObRsp96GEh"} - - - data: {"id":"chatcmpl-CoyYYeUWSXMSmrqMmtP4fxamq4vM2","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"5XlMYqCpfe"} - - - data: {"id":"chatcmpl-CoyYYeUWSXMSmrqMmtP4fxamq4vM2","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - equals"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"7n2I"} - - - data: {"id":"chatcmpl-CoyYYeUWSXMSmrqMmtP4fxamq4vM2","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"MWAuNaxyKW"} - - - data: {"id":"chatcmpl-CoyYYeUWSXMSmrqMmtP4fxamq4vM2","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"10"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ogW5F7bn3"} - - - data: {"id":"chatcmpl-CoyYYeUWSXMSmrqMmtP4fxamq4vM2","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"HwNpcoLKIK"} - - - data: {"id":"chatcmpl-CoyYYeUWSXMSmrqMmtP4fxamq4vM2","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"eBByw"} - - - data: {"id":"chatcmpl-CoyYYeUWSXMSmrqMmtP4fxamq4vM2","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":8,"total_tokens":22,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"lNcNmJTv02s"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b1224f70f467b5d-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:34 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '117' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '138' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_a039650e8c8d4f6b87f790ee240c501b - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_run_stream_structured_output.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_run_stream_structured_output.yaml deleted file mode 100644 index 8b83f68d3..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_run_stream_structured_output.yaml +++ /dev/null @@ -1,148 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Create a product: wireless mouse - for $29.99"}],"model":"gpt-4o-mini","max_completion_tokens":200,"stream":true,"stream_options":{"include_usage":true},"tool_choice":"required","tools":[{"type":"function","function":{"name":"final_result","description":"The - final response which ends this conversation","parameters":{"properties":{"name":{"type":"string"},"price":{"type":"number"}},"required":["name","price"],"type":"object","additionalProperties":false},"strict":true}}]}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '512' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"role":"assistant","content":null,"tool_calls":[{"index":0,"id":"call_A7KZPr5kGAGlQ8C14181Vvhy","type":"function","function":{"name":"final_result","arguments":""}}],"refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"yV5"} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"{\""}}]},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"j76iAcp9Zs3oMK"} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"name"}}]},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"2MtYagUE81M7o"} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"\":\""}}]},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"FasttgVbZD6W"} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"Wireless"}}]},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"l1SBzPzwz"} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":" - Mouse"}}]},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"evH1cpoojIm"} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"\",\""}}]},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"fT6Didfgz79L"} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"price"}}]},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"i8p4r5f2lT24"} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"\":"}}]},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"HaIM50EfiNrPrj"} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"29"}}]},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"0V8wqhtTL1LTzP6"} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"."}}]},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":""} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"99"}}]},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"gZKaSe6ldngLtzx"} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"}"}}]},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":""} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"tool_calls"}],"usage":null,"obfuscation":"58dnVPO5fMDckIz"} - - - data: {"id":"chatcmpl-CoyYfvJOAErG7o9IjpyQTI56Jm26M","object":"chat.completion.chunk","created":1766265221,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[],"usage":{"prompt_tokens":60,"completion_tokens":21,"total_tokens":81,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"vIuzr9NdNr"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b12251efed97bbc-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:41 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '332' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '346' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999987' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_f46c423eba984813a50f693c8688b0e1 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_run_stream_sync.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_run_stream_sync.yaml deleted file mode 100644 index 74a0267e8..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_run_stream_sync.yaml +++ /dev/null @@ -1,135 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 3"}],"model":"gpt-4o-mini","max_completion_tokens":100,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '164' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYYrogfLrG7d51VXOhGpHq4gnt5","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"oe7NKLwxb"} - - - data: {"id":"chatcmpl-CoyYYrogfLrG7d51VXOhGpHq4gnt5","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"zo9uTp8rAl"} - - - data: {"id":"chatcmpl-CoyYYrogfLrG7d51VXOhGpHq4gnt5","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"7XCXxDmcSS"} - - - data: {"id":"chatcmpl-CoyYYrogfLrG7d51VXOhGpHq4gnt5","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"orSNgjHbts"} - - - data: {"id":"chatcmpl-CoyYYrogfLrG7d51VXOhGpHq4gnt5","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"o9b0bnf5qQ"} - - - data: {"id":"chatcmpl-CoyYYrogfLrG7d51VXOhGpHq4gnt5","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"6BUHljfKiI"} - - - data: {"id":"chatcmpl-CoyYYrogfLrG7d51VXOhGpHq4gnt5","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"RnwAlJA5TO"} - - - data: {"id":"chatcmpl-CoyYYrogfLrG7d51VXOhGpHq4gnt5","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"JmdjUZhcL8"} - - - data: {"id":"chatcmpl-CoyYYrogfLrG7d51VXOhGpHq4gnt5","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"rymGleA07L"} - - - data: {"id":"chatcmpl-CoyYYrogfLrG7d51VXOhGpHq4gnt5","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"D7TJg"} - - - data: {"id":"chatcmpl-CoyYYrogfLrG7d51VXOhGpHq4gnt5","object":"chat.completion.chunk","created":1766265214,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":8,"total_tokens":22,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"wiavNQU8pii"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b1224f44c3edb9e-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:34 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '135' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '149' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_29dbb17aab2d4dcc9b5ee70fc1abbf4d - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_run_sync.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_run_sync.yaml deleted file mode 100644 index 9113bfa2a..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_run_sync.yaml +++ /dev/null @@ -1,108 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 2+2? Answer with just the - number."}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '148' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA4ySz27bMAzG734Kged4iJ0sbXLLdiv6Au1QGIpE21pkUZXobkGRdx/k/LGztcAu - PvDHj/o+mu+ZEGA0bASoVrLqvM2/0+Hp2yJS9/DIu8au94vXUm77X9tnWbcwSwra/UTFF9UXRZ23 - yIbcCauAkjFNLe5Wq3L1tVgXA+hIo02yxnO+pLwzzuTlvFzm87u8uD+rWzIKI2zEj0wIId6Hb/Lp - NP6GjZjPLpUOY5QNwubaJAQEsqkCMkYTWTqG2QgVOUY3WF9O6wHrPsrkzfXWToB0jlimbIOjlzM5 - Xj1YanygXfxLCrVxJrZVQBnJpfcik4eBHjMhXoas/Y198IE6zxXTHofnynNUGDc8wuLMmFjaieZS - vxlWaWRpbJysCpRULepROe5V9trQBGSTyP96+Wj2KbZxzf+MH4FS6Bl15QNqo27zjm0B0/l91nZd - 8WAYIoY3o7BigyH9Bo217O3pKCAeImNX1cY1GHwwp8uofYW4WqsS6+U9ZMfsDwAAAP//AwC3+s74 - JwMAAA== - headers: - CF-RAY: - - 9b1224663bb9a2b3-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:12 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '203' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '327' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999985' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_471863fd12ea4712a0185373c2a05e92 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_stream_buffer_pattern_early_return.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_stream_buffer_pattern_early_return.yaml deleted file mode 100644 index 7fde16c6b..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_stream_buffer_pattern_early_return.yaml +++ /dev/null @@ -1,155 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 5"}],"model":"gpt-4o-mini","max_completion_tokens":100,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '164' - Content-Type: - - application/json - Cookie: - - __cf_bm=32b.VMplxNQj3L4u_1uDEw4mJbFkX7XgxbW0AIaO4WI-1767741983-1.0.1.1-ngrHAoGsRus82vIYthILxaNTwRrSgq6MT17VyVyBWlwIdCX8AvWXc.5O8aoDYcvvfwwO.wkKSuvDVkjIkcKdBrusGxL1HyXKUH5Xfk3NhOU; - _cfuvid=beFRqK6f.Kw4Ih5NqMjxVqYpI9KKqCHTmRCh_PSGRiw-1767741983214-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.36.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.13.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"bcINBiIzl"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"DCree7eBPf"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"pvpGblJa0X"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"zRnt5XEcWz"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"UtcHdzjdyH"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"A4GU9GCwHo"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"m2BBvPGr6j"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"UbxH3vm9ow"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Y1BpRkh1BN"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"2vNoNGTR1h"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":"4"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"GOZPS2oFlB"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"y3icxduW8C"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"qmGHVCeBOa"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"PhMdSCHOag"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"CsnAjtFZFs"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"ckCs2"} - - - data: {"id":"chatcmpl-CvAjPgfJoxisksYFBHrXJqNM9GHNG","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":14,"total_tokens":28,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"SaUfw2TISU"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b9efae57a0fed40-SJC - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Tue, 06 Jan 2026 23:26:23 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '157' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '170' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_78143cd211f04c098aa5fe0c40067451 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_stream_early_break.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_stream_early_break.yaml deleted file mode 100644 index fd6646850..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_stream_early_break.yaml +++ /dev/null @@ -1,230 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 10"}],"model":"gpt-4o-mini","max_completion_tokens":100,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '165' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"4pQPbm5sP"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"Sure"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"wrvJkdl"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"!"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"A2vKajCbCQ"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - Here"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"bC0UbU"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - you"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"BDapODD"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - go"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"YDXHLAr8"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":":"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"cL9BEeScpw"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"kf4hXtU8II"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Tff3zmLZyx"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"svWLZ07ECm"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"VfjmbYCm8f"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"X8Q1CXgcd4"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"udNT2lSgTS"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"jWwKJ2GgAh"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"KrLIOlJR3v"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"bH26cIHKyt"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"LlOvHHhjtf"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"4"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"pA0yAxQg5g"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ZCxMVAVuth"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"crhyHB7U1I"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ssgOE7sSk6"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"modwaj7i7y"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"9fU2BvvFtU"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"6"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"FJBqC1w2pl"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"HS9kSQFA1R"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"iGnOI7Jy3e"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"7"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"iKxFMYIhFG"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"LtlwQXjWJ5"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"leamnKRf87"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"8"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"U5UoyjZdqc"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"76CDhGsCQ1"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"fRyotHGhbg"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"9"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"LSe7QhEaMZ"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"BmBnuWlc1i"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"mlUCXZHbke"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"10"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"AEcwdXOyQ"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"tGgCDyMBr7"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"VMIGo"} - - - data: {"id":"chatcmpl-CoyYaXx5R6G5GRkk9MNIAWNELLPmb","object":"chat.completion.chunk","created":1766265216,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":36,"total_tokens":50,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"oJyVAU56Sv"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b122500fc37f554-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:36 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '143' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '156' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_bc33e098e9454cf38129178ac688bf90 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_structured_output.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_structured_output.yaml deleted file mode 100644 index b9c80df3f..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_structured_output.yaml +++ /dev/null @@ -1,117 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 10 + 15?"}],"model":"gpt-4o-mini","max_completion_tokens":200,"stream":false,"tool_choice":"required","tools":[{"type":"function","function":{"name":"final_result","description":"The - final response which ends this conversation","parameters":{"properties":{"answer":{"type":"integer"},"explanation":{"type":"string"}},"required":["answer","explanation"],"type":"object","additionalProperties":false},"strict":true}}]}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '463' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.10.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFPLbtswELzrKxZ7rR1YrmQnAnpqegh6aNMWaY06EGhyLbGhSIakmgqG - /72gHFvKo0B1EIgdzuzsg7sEAKXAApDXLPDGqul701X3Fyt/933hL7vu6vrmQ37NV6kOl/YBJ5Fh - Nr+IhyPrjJvGKgrS6APMHbFAUTVdLhbzRb6cn/dAYwSpSKtsmGZm2kgtp/PZPJvOltP0/JFdG8nJ - YwE/EwCAXf+PPrWgP1jAbHKMNOQ9qwiL0yUAdEbFCDLvpQ9MB5wMIDc6kI7WdavUCAjGqJIzpYbE - h283Og/NYkqVqy8XX1f3QrD0x1vx+arLbj7dZM1HO8p3kO5sb2jban5q0gg/xYtnyQBQs+bAlZqp - 0pFvVXjGB0DmqrYhHaJ33K2Raf9Abo3FPJ+skf5YxTSLKdZYrPFbTeDbBswW0hkwLSDNQXrgTPFW - xcnBpgMmhNQVhJogPBjQbbMh5yGYikJNrojcN5H5Dub52Rr3+MTVPnntfDvquKNt65l6OQqmtQm9 - 3X4Wt4/I/jR2ZSrrzMY/o8YmSV+XjpjvuzkeanI00lvA9sneoHWmsaEM5o76pPnyIIrDag9glj2C - wQSmhng6SyevyJWCApP9Xp1WmTNekxiow0qzVkgzApJR6S/dvKZ9KF/q6n/kB4BzsoFEaR0JyZ9W - PFxzFF/+v66dmtwbRk/ut+RUBkkujkPQlh33F33nAzXlVuqKnHWyf5S4tSXP8vN8k28uOCb75C8A - AAD//wMAKCKONqIEAAA= - headers: - CF-RAY: - - 9b1231843ca711d4-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:22:10 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=tjfDIbVtlGKAySVR9I771x5d5TWJXazLALWLBWelkn0-1766265730-1.0.1.1-HqfmmM2hjszgNJVDnEr3.JxzdI19yHvDV.USX_bmGPcPu98d5uB53IXS8BksoX1IiWnwdm5byGI0XFP_aigP1sJV05q360okqKwIfMssHtA; - path=/; expires=Sat, 20-Dec-25 21:52:10 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=VQg4i_utDK73HtVZX9MnimdbFMrcTwHiGTkj8zvaxBM-1766265730198-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '1443' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '1464' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_d19b9ce7cbd7481b87acf1bb92d8e5b9 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_with_binary_content.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_with_binary_content.yaml deleted file mode 100644 index 88a06ad1f..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_with_binary_content.yaml +++ /dev/null @@ -1,115 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":[{"image_url":{"url":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAACklEQVR4nGMAAQAABQABDQottAAAAABJRU5ErkJggg=="},"type":"image_url"},{"text":"What - color is this image?","type":"text"}]}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '315' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFLBbtswDL37Kwid4yJ20yTNcTsMKDAMA4aixVAYskTbXGVJk+gtRZF/ - H+Sksdt1wC468PFR7z3yOQMQpMUOhOokq96b/KN7uq9vbvf3d58/fOIv+5/t9ba4qcvyrrn9KhaJ - 4eofqPiFdaFc7w0yOXuEVUDJmKYWm/W6XF+VxWYEeqfRJFrrOV+5vCdLebksV/lykxfbE7tzpDCK - HXzPAACexzfptBr3YgfLxUulxxhli2J3bgIQwZlUETJGiiwti8UEKmcZ7Sj9W4dAvWwRKEJtpHoE - aTX87ohxAQ1KHgLZFiRESv5OPW5gQxbBNSDBY4jOXsx/CNgMUSaXdjBmBkhrHcuU0ujt4YQczm6M - a31wdXxDFQ1Zil0VUEZnk/LIzosRPWQAD2Nqw6sghA+u91yxe8Txu+1VcXkcKKZtTXCxPoHsWJo5 - rbxevDOx0siSTJwlL5RUHeqJO61JDprcDMhmvv+W897so3ey7f+MnwCl0DPqygfUpF5bntoCpmv+ - V9s551GwiBh+kcKKCUPahcZGDuZ4YyI+Rca+asi2GHyg46E1vtrWtbrc1itdi+yQ/QEAAP//AwAU - sfncdgMAAA== - headers: - CF-RAY: - - 9b1225071c71102c-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:38 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '1288' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '1306' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-input-images: - - '50000' - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-input-images: - - '49999' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999227' - x-ratelimit-reset-input-images: - - 1ms - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_4c8353513e384112a1594c46e28d4db5 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_with_custom_settings.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_with_custom_settings.yaml deleted file mode 100644 index 3b1f1e7ee..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_with_custom_settings.yaml +++ /dev/null @@ -1,107 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Say hello"}],"model":"gpt-4o-mini","max_completion_tokens":20,"stream":false,"temperature":0.5,"top_p":0.9}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '146' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFJNb9swDL37V3A6x0PiZkmaSw/b0I9t520YCkORaEerLAoSnc0r8t8H - 2W3srh3Qiw58fE/vkbzPAITRYgtC7SWrxtv8PXXfv/nPl4cvuz+Hg/741XY36x3qT+HGfBCzxKDd - T1T8yHqrqPEW2ZAbYBVQMibVxXq1KlbvisVZDzSk0SZa7TlfUt4YZ/JiXizz+TpfbB7YezIKo9jC - jwwA4L5/k0+n8bfYwnz2WGkwRlmj2J6aAEQgmypCxmgiS8diNoKKHKPrrV+htfQGrugXKOngGgYC - dNQCk5bdxZQYsGqjTOZda+0EkM4RyxS+t3z7gBxPJi3VPtAu/kMVlXEm7suAMpJLhiKTFz16zABu - +2G0T/IJH6jxXDLdYf/d+aAmxg08x5hY2rG82Mxe0Co1sjQ2TkYplFR71CNznLtstaEJkE0SP/fy - kvaQ2rj6NfIjoBR6Rl36gNqop3nHtoDpPP/Xdppwb1hEDAejsGSDIW1BYyVbOxyNiF1kbMrKuBqD - D2a4nMqXiKtzVWC13IjsmP0FAAD//wMA+CXNH0cDAAA= - headers: - CF-RAY: - - 9b1224f15fb22b78-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:34 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '279' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '294' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_46866b81830e435ea4b5749d64ff9f96 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_with_document_input.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_with_document_input.yaml deleted file mode 100644 index de52bd727..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_with_document_input.yaml +++ /dev/null @@ -1,110 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":[{"file":{"file_data":"data:application/pdf;base64,JVBERi0xLjQKMSAwIG9iajw8L1R5cGUvQ2F0YWxvZy9QYWdlcyAyIDAgUj4+ZW5kb2JqIDIgMCBvYmo8PC9UeXBlL1BhZ2VzL0tpZHNbMyAwIFJdL0NvdW50IDE+PmVuZG9iaiAzIDAgb2JqPDwvVHlwZS9QYWdlL1BhcmVudCAyIDAgUi9NZWRpYUJveFswIDAgNjEyIDc5Ml0vQ29udGVudHMgNCAwIFI+PmVuZG9iaiA0IDAgb2JqPDwvTGVuZ3RoIDQ0Pj5zdHJlYW0KQlQgL0YxIDEyIFRmIDEwMCA3MDAgVGQgKFRlc3QgRG9jdW1lbnQpIFRqIEVUCmVuZHN0cmVhbQplbmRvYmoKeHJlZgowIDUKMDAwMDAwMDAwMCA2NTUzNSBmCjAwMDAwMDAwMDkgMDAwMDAgbgowMDAwMDAwMDU4IDAwMDAwIG4KMDAwMDAwMDExNSAwMDAwMCBuCjAwMDAwMDAyMTQgMDAwMDAgbgp0cmFpbGVyPDwvU2l6ZSA1L1Jvb3QgMSAwIFI+PgpzdGFydHhyZWYKMzA3CiUlRU9G","filename":"filename.pdf"},"type":"file"},{"text":"What - is in this document?","type":"text"}]}],"model":"gpt-4o-mini","max_completion_tokens":150,"stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '816' - Content-Type: - - application/json - Cookie: - - __cf_bm=32b.VMplxNQj3L4u_1uDEw4mJbFkX7XgxbW0AIaO4WI-1767741983-1.0.1.1-ngrHAoGsRus82vIYthILxaNTwRrSgq6MT17VyVyBWlwIdCX8AvWXc.5O8aoDYcvvfwwO.wkKSuvDVkjIkcKdBrusGxL1HyXKUH5Xfk3NhOU; - _cfuvid=beFRqK6f.Kw4Ih5NqMjxVqYpI9KKqCHTmRCh_PSGRiw-1767741983214-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.36.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.13.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA4xTTW/bMAy9+1cQOidBkjofzW1dDsutA3bZ1sJQJDpWJ4uaRKcJivz3QU4au10H - 7KIDH98j+Ui9ZADCaLECoSrJqvZ2+Hn/6enrvf8dVL6eo1wfljK/+65dae5+zMUgMWj7hIpfWSNF - tbfIhtwZVgElY1KdLOaLRT65XeYtUJNGm2g7z8OchrVxZjgdT/PheDGcLC/siozCKFbwMwMAeGnf - 1KfTeBArGA9eIzXGKHcoVtckABHIpoiQMZrI0rEYdKAix+ja1jcM0nuUIcKRGmi8JalRgwRNqqnR - MbBhixoexDeMDOtLePQg4As94x7DADbgEDUwAR5kbRyC4QiXMjHFfaC90QgSYlPXMhyBAmhkaZK2 - cSWFWibzRnBvUUaEiqwGcvBcGYuwAU3Ayef+IAHLJspkpmus7QHSOeJWr7Xw8YKcrqZZ2vlA2/iO - KkrjTKyKgDKSSwZFJi9a9JQBPLbLad74LXyg2nPB9AvbctObyVlPdDfRoTezC8jE0vZY8/ngA73i - bFLsrVcoqSrUHbW7BdloQz0g6039dzcfaZ8nN273P/IdoBR6Rl34gNqotxN3aQHTl/lX2tXltmER - MeyNwoINhrQJjaVs7PmQRTxGxroojdth8MGcr7n0hcpny9l2tr1VIjtlfwAAAP//AwD1PbbW2wMA - AA== - headers: - CF-RAY: - - 9b9efaeb3fe9138a-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Tue, 06 Jan 2026 23:26:25 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '835' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '1111' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999225' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_90966cd622374d94b813aa9155f7f12e - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_with_message_history.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_with_message_history.yaml deleted file mode 100644 index d1a3a0c46..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_with_message_history.yaml +++ /dev/null @@ -1,214 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"My name is Alice"}],"model":"gpt-4o-mini","max_completion_tokens":100,"stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '124' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFLBatwwEL37K6Y622VtvJt0L6EUSpfCUtpCaUowijz2aiNrhDROs4T9 - 9yJ7s3baFHLRYd68p/dm5jEBELoWaxBqJ1l1zmQf6PDzx/7+7svD9iO1n5eb7/3X6367Kb+p/UKk - kUG3e1T8xHqrqHMGWZMdYeVRMkbV/GK1KlbLIi8GoKMaTaS1jrOSsk5bnRWLoswWF1l+eWLvSCsM - Yg2/EgCAx+GNPm2ND2INi/Sp0mEIskWxPjcBCE8mVoQMQQeWlkU6gYosox2sb7VCYIIOkeFAfQrv - jVb4Bj7Rb1DSwgZGiQgCUy0PV3Mpj00fZIxje2NmgLSWWMZxDCFuTsjxbNtQ6zzdhr+ootFWh13l - UQay0WJgcmJAjwnAzTCe/lli4Tx1jiumOxy+y/NRTkxLmYHlCWRiaaZ6sUxfUKtqZKlNmI1XKKl2 - WE/MaReyrzXNgGSW+V8zL2mPubVtXyM/AUqhY6wr57HW6nngqc1jPNn/tZ1nPBgWAf29VlixRh/3 - UGMjezMekgiHwNhVjbYteuf1eE2NqxBX71SBTXkpkmPyBwAA//8DAFoRD7VbAwAA - headers: - CF-RAY: - - 9b1224eaa865da6c-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:33 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '406' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '424' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_56a4aaae17c246a2819c52c253e8af1b - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"role":"user","content":"My name is Alice"},{"role":"assistant","content":"Nice - to meet you, Alice! How can I assist you today?"},{"role":"user","content":"What - is my name?"}],"model":"gpt-4o-mini","max_completion_tokens":100,"stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '255' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFLBbtswDL37Kwid4yJx0jTNZRiGdRvQ64AGQ2GoEm1rlUVNorelRf59 - kJ3GzrYCvejAx/f0HsnnDEAYLbYgVCNZtd7mH2i/u7tZPrrN7a6Z39zJT+rph/pqnz7SbS1miUEP - 31HxC+tCUestsiE3wCqgZEyqi6v1ulhfFotlD7Sk0SZa7TlfUd4aZ/JiXqzy+VW+2BzZDRmFUWzh - WwYA8Ny/yafT+FtsYT57qbQYo6xRbE9NACKQTRUhYzSRpWMxG0FFjtH11nfUBXCyRTAR3luj8AI+ - 0y9Q0sEXGNiwpw6qLnCD4d1UJ2DVRZmyuM7aCSCdI5ZpFn2C+yNyOHm2VPtAD/EvqqiMM7EpA8pI - LvmLTF706CEDuO9n053FFT5Q67lkesT+u+VmkBPjRkZwURxBJpZ2rF8e53muVmpkaWyczFYoqRrU - I3NchOy0oQmQTTL/a+Z/2kNu4+q3yI+AUugZdekDaqPOA49tAdO9vtZ2mnFvWEQMP43Ckg2GtAeN - lezscEUi7iNjW1bG1Rh8MMMpVb5EXF+rAqvVRmSH7A8AAAD//wMAzG2kQVgDAAA= - headers: - CF-RAY: - - 9b1224ee1fcb08e0-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:33 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '327' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '342' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999975' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_05e924c6ff604d268b4bd3917d32300c - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_with_model_settings_in_metadata.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_with_model_settings_in_metadata.yaml deleted file mode 100644 index 84589d533..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_with_model_settings_in_metadata.yaml +++ /dev/null @@ -1,107 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Say hello"}],"model":"gpt-4o-mini","max_completion_tokens":100,"stream":false,"temperature":0.5}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '135' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFJNT+MwEL3nVww+N6iNSmh7QWIv5bYrpEUrhCJjT1KzjseyJ0CF+t+R - E2jCx0p78WHevOf3ZuYlAxBGiw0ItZOsWm/zH7T/84uWi6v482Z97YPbrm5+P18+sKZgxCwx6P4B - Fb+zThW13iIbcgOsAkrGpLo4L8uiPCvmZQ+0pNEmWuM5X1LeGmfyYl4s8/l5vli9sXdkFEaxgdsM - AOClf5NPp/FZbGA+e6+0GKNsUGyOTQAikE0VIWM0kaVjMRtBRY7R9da3aC2dwJaeQEkHVzAQYE8d - MGm5v5gSA9ZdlMm866ydANI5YpnC95bv3pDD0aSlxge6j5+oojbOxF0VUEZyyVBk8qJHDxnAXT+M - 7kM+4QO1niumv9h/tx7UxLiBrxgTSzuWF6vZN1qVRpbGxskohZJqh3pkjnOXnTY0AbJJ4q9evtMe - UhvX/I/8CCiFnlFXPqA26mPesS1gOs9/tR0n3BsWEcOjUVixwZC2oLGWnR2ORsR9ZGyr2rgGgw9m - uJzaV4jlWhVYL1ciO2SvAAAA//8DAKWg15BHAwAA - headers: - CF-RAY: - - 9b1224c43cc18e7d-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:26 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '260' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '276' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_09e3cce93c3b47698c8d076d2303e281 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_with_model_settings_override_in_input.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_with_model_settings_override_in_input.yaml deleted file mode 100644 index da99005ee..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_with_model_settings_override_in_input.yaml +++ /dev/null @@ -1,116 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Tell me a story"}],"model":"gpt-4o-mini","max_completion_tokens":200,"stream":false,"temperature":0.9}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '141' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFXbbttGEH3XVxzwWRIk1bVTvxZFAzRFgKZo6zaBMNodkmMtd5ndoRQi - MJAPSX8uX1LsUrbkXoC+CBTPXM45Mxp9nAGV2OoWlWlJTde7xbdhvPvJ1rT6+ft+/cPu11fDvfnt - 93791c3d3bGa54ywu2ejj1lLE7resUrwE2wik3Kuur65vt5cf71Z3RSgC5ZdTmt6XVyFRSdeFpvV - 5mqxulmsX5yy2yCGU3WLP2YA8LF8Zp7e8ofqFqv545uOU6KGq9unIKCKweU3FaUkSclrNT+DJnhl - X6i/9oYx9MGDoNIxJD+9H0i8womqYxzEOWoYnpM6ttixHpk93JBaNDE/tuJcAnkLQuop7p34BlEO - HOfQliPDyYEtyCM4C+OC2Xe05whPHVt854TSEi8l4RjiPrWhx5FSZhWZ0hAZGsOBEWqomH0uX4ok - aEsKsiF6trkXjuRcmoPJtDiKthBNCEePwcv7gdFzTMGTEx2XeBM6hmklk+jYBSthSG6c49iKY4RM - PsE4MftC32YgRrZz7AYFOQfNinLjnsokJo6Tl9qyRKSejZDDkcblW//WF7VF395nYjXFqbRYhg+K - +yEp6hDRSkLai3O5mIlU61n5xCBH5eZJQxROyAZko8RrmDwomyjBL/GSsWMnfChOkYIPHMepHFoq - 09MQR2iAsnPzwmoKyq6Xr1qC2eXojrsQxyV+mVYk5ukNziLUyj7X6rEbJxF5olla8K7U3w0j6NQ6 - 69CA1FKec7HMRqZuWin+0HMU9obTHG3oswOF/cnG0tFQr8OU3ZWpT+ajYYopTySTeHQilSm89gxL - 4xyEMQy+QSPRnfbxlTjCQZLo41KdtnKJN2XFEnZRmlYXPJ72wgwx787kWcsRjoamVY6w5A1bONkz - 0uBdzjstB0jiEl8+ff4xLic98y+f/kTKAyWx8wwZ8png5S84cj0kylfED85dAOR90Eljvh3vTsjD - 07Vwoelj2KW/pVa1eEntNv/Ygs+XwbFvtK0K/jAD3pW7NDw7NVUfQ9frVsOeS8P1eipYna/hGdys - Tker0qDkLoCntGf1tpaVxKWLy1YZMi3bc+r5DNJgJVwAswvd/6Tzb7Un7eKb/1P+DBjDvbLd9pGt - mOeSz2GR87/Ff4U9uVwIV4njQQxvVTjmWViuaXDTDa/SmJS7bS2+4dhHmQ553W+Zr78xG66vXlSz - h9lfAAAA//8DAHvMFjzWBgAA - headers: - CF-RAY: - - 9b1224c73cd50fb5-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:30 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '3933' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '3947' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_cbcce6e1408a47d4b5e8fc61315d4b21 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_with_system_prompt_in_metadata.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_with_system_prompt_in_metadata.yaml deleted file mode 100644 index d998ca7b6..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_with_system_prompt_in_metadata.yaml +++ /dev/null @@ -1,110 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"system","content":"You are a helpful AI assistant - who speaks like a pirate."},{"role":"user","content":"What is the weather?"}],"model":"gpt-4o-mini","max_completion_tokens":100,"stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '215' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFNdSxwxFH3fX3HN82zZneq67ktpC4VC6UNRixYZspkzM3EzSUjuaBcR - /Bv+PX+JZEadtbXQl0Duuefk3I/cTIiELsWKhGokq9ab6We3PTu1aK++/Dg+O96cu/z75tv5p5PT - 2ftwIrLEcOtLKH5mvVOu9QasnR1gFSAZSXV+uFjki4N8Pu+B1pUwiVZ7nu67aautnuazfH86O5zO - l0/sxmmFKFb0a0JEdNOfyact8VusaJY9R1rEKGuI1UsSkQjOpIiQMerI0rLIRlA5y7C99Y8hhIxa - ydju0VdS0j7c3TOtQR7wOt1IMnEDihuNSNpSgDTEukVG645JV7QFMYyhFnTdICAF1qAI5kEiSm2y - QZ+i15YkbWWw9HB3v3bdoF/DIkhD15DcIJCXzAg2JrFW1w0TrHKdZYQ9+tnI3mUiGsmauxIkbUnG - 2Xq4ueQr0KXrgsX2w24DAqouyjQE2xmzA0hrHcs0xL71F0/I7Uuzjat9cOv4B1VU2urYFAEyOpsa - G9l50aO3E6KLfqjdqzkJH1zruWC3Qf9cvhzkxLhKI3hw9ASyY2nG+PIwe0OtKMFSm7izFEJJ1aAc - meMGya7UbgeY7NT8t5m3tIe6ta3/R34ElIJnlIUPKLV6XfCYFpA+2r/SXnrcGxYR4UorFKwR0hxK - VLIzw/qLuI2Mtqi0rRF80MMfqHwBLI5Ujmp/KSa3k0cAAAD//wMAkHTj3xEEAAA= - headers: - CF-RAY: - - 9b1224e1294f9a4f-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:32 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '1332' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '1346' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999977' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_3dde0d17015c4cd588c2dc14b4bc82b8 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_with_tool_execution.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_with_tool_execution.yaml deleted file mode 100644 index 72025974c..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_with_tool_execution.yaml +++ /dev/null @@ -1,220 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 127 multiplied by 49?"}],"model":"gpt-4o-mini","max_completion_tokens":200,"stream":false,"tool_choice":"auto","tools":[{"type":"function","function":{"name":"calculate","description":"Perform - a mathematical calculation.","parameters":{"additionalProperties":false,"properties":{"operation":{"description":"The - mathematical operation (add, subtract, multiply, divide)","type":"string"},"a":{"description":"First - number","type":"number"},"b":{"description":"Second number","type":"number"}},"required":["operation","a","b"],"type":"object"},"strict":true}}]}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '604' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFNNj5swEL3zK6w5Q5XQJCTc2q2iHnrZVqq0Kitk7AGcNbZlm3bTKP+9 - ApJAslmpHJA1z+/Nmw8fAkJAcEgJsJp61hgZPej9E6u+/1D1dqc451/Z489vvJx91n/qRwg7hi52 - yPyZ9YHpxkj0QqsBZhapx051nqxW8WoZz9c90GiOsqNVxkcLHTVCiSiexYtolkTz9Ylda8HQQUp+ - BYQQcuj/nU/F8RVSMgvPkQadoxVCerlECFgtuwhQ54TzVHkIR5Bp5VF11lUr5QTwWsucUSnHxMN3 - mJzHZlEp82S/e4q3n8S6WG/lw99XW8++fEzsyyTfIL03vaGyVezSpAl+iac3yQgBRRs8JWStpB5v - yIQAtVXboPKdcThkoA1a2ullkGbQtNILI/cZhBnQDNJ5nIQZFBmki80RrsSOwb3z86RLFsvWUfm2 - fVQp7fusff+eT8jxMiqpK2N14W6oUAolXJ1bpK7vwHQQwdlIbwHaq1mDsboxPvf6BfukSTKIwriO - IxjPT6DXnsoxvlmHd9Ryjp6KfhUu28coq5GPzHELacuFngDBpPK3Zu5pD9ULVf2P/AgwhsYjz41F - Lth1weM1i91jfe/apce9YXBofwuGuRdou2lwLGkrhycEbu88NnkpVIXWWNG/IyhNzhbL9bJYFhsG - wTH4BwAA//8DAOTijx1VBAAA - headers: - CF-RAY: - - 9b1225104cbc2b8d-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:39 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '577' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '590' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999990' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_509940fcc6bb40bd8804ce82553ceacf - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"role":"user","content":"What is 127 multiplied by 49?"},{"role":"assistant","content":null,"tool_calls":[{"id":"call_7yjY2FAi8b8FlCzxrh0D37rk","type":"function","function":{"name":"calculate","arguments":"{\"operation\":\"multiply\",\"a\":127,\"b\":49}"}}]},{"role":"tool","tool_call_id":"call_7yjY2FAi8b8FlCzxrh0D37rk","content":"6223.0"}],"model":"gpt-4o-mini","max_completion_tokens":200,"stream":false,"tool_choice":"auto","tools":[{"type":"function","function":{"name":"calculate","description":"Perform - a mathematical calculation.","parameters":{"additionalProperties":false,"properties":{"operation":{"description":"The - mathematical operation (add, subtract, multiply, divide)","type":"string"},"a":{"description":"First - number","type":"number"},"b":{"description":"Second number","type":"number"}},"required":["operation","a","b"],"type":"object"},"strict":true}}]}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '888' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFLBjtMwFLznKyyfm1VimrbpjeXAkSssWkWO/ZI+cGxjvyCqVf8dOek2 - 6QISlxzevJnMjN9LxhhHzY+Mq5MkNXiTf3DnL/pTUR+eoH3U+sf7x737XLUYnz6Klm8Sw7XfQNEr - 60G5wRsgdHaGVQBJkFTL/W4ndpUo6wkYnAaTaL2nfOvyAS3mohDbvNjn5eHKPjlUEPmRfc0YY+xl - +iafVsMvfmTF5nUyQIyyB368LTHGgzNpwmWMGEla4psFVM4S2Ml6KfZsGA2hNwiatWe2rRlGthPi - 3cOaE6Abo0y+7WjMCpDWOpIp9+T2+Ypcbv6M631wbXxD5R1ajKcmgIzOJi+RnOcTeskYe556GO+i - cR/c4Kkh9x2m35VFPevxpf4VWl5BciTNai6u7d3rNRpIoomrJrmS6gR6oS61y1GjWwHZKvWfbv6m - PSdH2/+P/AIoBZ5ANz6ARnWfeFkLkK7zX2u3lifDPEL4iQoaQgjpJTR0cjTzzfB4jgRD06HtIfiA - 8+F0vlHb6lC1VVsrnl2y3wAAAP//AwARJ00jRgMAAA== - headers: - CF-RAY: - - 9b122514ccebbd64-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:39 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '442' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '454' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999987' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_220c103a9c1a4326853c15b5dae82105 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agent_with_tools.yaml b/py/src/braintrust/wrappers/cassettes/test_agent_with_tools.yaml deleted file mode 100644 index fa1d41741..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agent_with_tools.yaml +++ /dev/null @@ -1,219 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What''s the weather in Paris?"}],"model":"gpt-4o-mini","max_completion_tokens":200,"stream":false,"tool_choice":"auto","tools":[{"type":"function","function":{"name":"get_weather","description":"Get - weather for a city.","parameters":{"additionalProperties":false,"properties":{"city":{"description":"The - city name","type":"string"}},"required":["city"],"type":"object"},"strict":true}}]}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '425' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFNdb9swDHz3rxD4HA9JkKSJ37YVG5Z1xT6KDt1SGKpM2+pkSZPotl6Q - /z7YbmwnzYD5wRB4PPJ4lLYBYyATiBiInJMorArfmupmffFUXVzTe3pQX88v1/aK5p+ub/LVDxjV - DHN3j4L2rFfCFFYhSaNbWDjkhHXVydliMV3MJ6tVAxQmQVXTMkvhzISF1DKcjqezcHwWTpbP7NxI - gR4i9jNgjLFt86916gSfIGLj0T5SoPc8Q4i6JMbAGVVHgHsvPXFNMOpBYTShrqXrUqkBQMaoWHCl - +sbttx2ce7O4UnE6//569ebx/qr4clmt/7h3v6ffPn7Izwf92tKVbQSlpRadSQO8i0dHzRgDzYuG - myHFj8gpR3dEZwy4y8oCNdXSYbsBIanaQLSBz9xJv4EdHDB2wanz7cAMh2npuXrpEtfaEK/FNjbd - PiO7biPKZNaZO39EhVRq6fPYIffNoEO/g72QRgKUBysF60xhKSbzC5um81lbFPpb14OTPUiGuOrj - i+XoRLU4QeKy2Xh3yQQXOSY9s79svEykGQDBYPKXYk7VbqeXOvuf8j0gBFrCJLYOEykOB+7THNZv - 8l9pnceNYPDoHqTAmCS6ehsJprxU7UsBX3nCIk6lztBZJ5vnAqmNERcrMcV0toRgF/wFAAD//wMA - zweDvDwEAAA= - headers: - CF-RAY: - - 9b12249359272b52-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:19 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '494' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '755' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_66c078817a964b1db9ca9f64a13fb7ee - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"role":"user","content":"What''s the weather in Paris?"},{"role":"assistant","content":null,"tool_calls":[{"id":"call_f5WA9BwjTmQNyJzrFq2SKIhD","type":"function","function":{"name":"get_weather","arguments":"{\"city\":\"Paris\"}"}}]},{"role":"tool","tool_call_id":"call_f5WA9BwjTmQNyJzrFq2SKIhD","content":"It''s - sunny in Paris"}],"model":"gpt-4o-mini","max_completion_tokens":200,"stream":false,"tool_choice":"auto","tools":[{"type":"function","function":{"name":"get_weather","description":"Get - weather for a city.","parameters":{"additionalProperties":false,"properties":{"city":{"description":"The - city name","type":"string"}},"required":["city"],"type":"object"},"strict":true}}]}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '697' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFLLbtswELzrKwieLcM2VDnwtYcg7aFF0UsQBAJNrqRNKS5Brto6gf89 - IO1Ych9ALjrs7IxmhvtSCCHRyJ2QulesB2/Lj3S4/2yelf/UKTqY+tbtb0f97W67/RLu5CIxaP8E - mt9YS02Dt8BI7gTrAIohqa63db2pP2xWqwwMZMAmWue5rKgc0GG5WW2qcrUt1zdndk+oIcqdeCiE - EOIlf5NPZ+C33ImslScDxKg6kLvLkhAykE0TqWLEyMqxXEygJsfgsvXvPYhfoLiHINCJrypgFBhF - HJ07LOekAO0YVTLuRmtngHKOWKXg2e7jGTleDFrqfKB9/IMqW3QY+yaAiuSSmcjkZUaPhRCPuYjx - Kpv0gQbPDdMPyL+7Ofcgp/pn4BljYmVn47f5lVhjgBXaOOtRaqV7MBNzKl2NBmkGFLPIf3v5l/Yp - NrruPfIToDV4BtP4AAb1dd5pLUC6zf+tXSrOhmWE8BM1NIwQ0jMYaNVoTxcj4yEyDE2LroPgA57O - pvVNXVXtem1MZWRxLF4BAAD//wMAShjuZEQDAAA= - headers: - CF-RAY: - - 9b12249c3e4e1e0f-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:20 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '261' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '275' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999985' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_abb5b9aeb2e14981a3eb63e7b04aed6b - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agents_tool_openai_nested_spans.yaml b/py/src/braintrust/wrappers/cassettes/test_agents_tool_openai_nested_spans.yaml deleted file mode 100644 index fe69dd17e..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agents_tool_openai_nested_spans.yaml +++ /dev/null @@ -1,436 +0,0 @@ -interactions: -- request: - body: '{"include":[],"input":[{"content":"Please analyze this text: ''Artificial - intelligence is transforming industries worldwide. Companies are adopting AI - technologies to improve efficiency and innovation. However, challenges like - ethics and job displacement remain concerns.''","role":"user"}],"instructions":"You - are a helpful assistant that analyzes text. When asked to analyze text, you - MUST use the analyze_text tool. Always call the tool with the exact text provided - by the user. After using the tool, provide a two sentence summary of what the - tool returned.","model":"gpt-4.1","tools":[{"name":"analyze_text","parameters":{"properties":{"text":{"title":"Text","type":"string"}},"required":["text"],"title":"analyze_text_args","type":"object"},"strict":false,"type":"function","description":"Analyze - text and return a structured summary with key points, sentiment, and statistics."}]}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '885' - Content-Type: - - application/json - Cookie: - - __cf_bm=IwSSJ.RHOyrDHy71t190C0u4EL9HMgUY2jiVoTE3Rx0-1768424037-1.0.1.1-ZID4mvxCwpZVRzFS1fLdN1Y2IWkkn_wazHoPQBolLYHzMoZNRkTFDL0fqX4m.0FY97.b95rhiBzBDf3ubnonNwcnYBcTqnrX4_OgE7Fq6Lw; - _cfuvid=RePkKlnxLbAHj0ymuEQEUhV2_qf3Ejhb0yEUFttOP24-1768424037764-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - Agents/Python 0.6.5 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA4RVTW/jNhC9+1cMdHYM2XH8kVtQYNEeiqLILoqiWQhjcmRzTZEMObTXG/i/F6Rs - WfYm2Js0j/PBxzczbwOAQsniEQpPwVXldHkvJ2Mc1+WynE0mZTlbzhblZDZDpMVivLxfziere5pJ - UT5McToTxTCFsKtvJPgcxppArV14QiZZYcLG89liOpmW94uMBUaOIfkI2zhNTLJ1WqHYrr2NJtVV - ow7UmpXWyqyLR3gbAAAUDg/kk7+kHWnryBcDgGOb+BzyJvUyo+S9TZ4map0NtafXSEYcKkcGNR+K - RyhHZcaUOQerJDEqHfqeygT2UbCyJt/lXxsBPQHChrSrowYMQQVGw8AbZECD+vCDAjB95xH8syED - GLYkge0ZzNgQDjbCn1+eP0MMBLyhM1wlGNhaPYInvcdDAIFa5yPJCnvFm/xH31FwjgbO252SJGF1 - yFAM5EfwVDN5iEGZdec+PJ8FBN5bCGSYjCAIsWnQH8DWsE9X6fJ54ugNyVH7gA1+r2xkF7liuyVz - RVgCk1OVSr5GrCSdOFw7vpuOxneTcvJwV07vxtOTynLM4hH+ywJoZdAJuBYfy3c+Jpnlu1jO6gd6 - GK9mU0FzOc+BcxA+OMphosmvmeu7wB+pNYPo17Ehwxl/eykS4S/F40vx5FnVSijUoAyT1mqdmVQB - 2KMJtfVNol4ZGQN7RQH21mu5V5JG8JttHJpkzIqS1nE6/PQHMImNsdquE8gWVJOejIDqlC0JGdBI - UMbYHabbjOB3u6cd+SGIDWpNZk0BtNoSEG+UCPn8N7sCqYLTKCjdBzw1qAwIawR5E0YvxfFy60RQ - 1XKfP1/94q85zT5N5vPn+y/POx6/fgr67x8XD4NN5riv4yKDxwHA1/zIDn2qT1+LhH1sp4DzFBKF - 7zSq87RTNobqPIPa4jp9OW8bx5VAsaFqS4cPMU9MJrHWP+EJgzVXA4jq2nruHUo6aXvkZOzmUcCa - +FApmQLXiq6mTyC/U4IqVud5VmPUXJzGpPXUZ4CpceSRYzaPT5fPVHaVJV3h5b8n7x7lp4p35Fc2 - qExl0ZBUsbnM0fYRNlaJ9uEi26IDws+teNtFl7eXFIRX7kRr8dSbdFl77QwBhHaeRk+yGzh5nm3p - AM4qw2GYR5JKCh1m39ScKrASYfQLsXVokllDTD70WGqF4Mizomv7LcMXq2Kd03zuh79hI7W2WRc9 - 8Nh9Hy8+RdpCypPseO2n7gxfex5d+v4tK/TrUPRPneo4renBTeZcX17fedveNCRbV2m7dt6uEidl - Z3R9+floBJ4fV6qAK33e5zHgmi7aVOZqMYyns+HPQG/Vvl3mjdiQvHiWVzK+XTjT6XvAe3G7zv4o - NFtG3at4WXb9kbbo1Q4jRomMKf5xcPwfAAD//wMA3nkxFGAJAAA= - headers: - CF-RAY: - - 9be006a14e44823c-IAD - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 14 Jan 2026 20:53:59 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '921' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '923' - x-ratelimit-limit-requests: - - '10000' - x-ratelimit-limit-tokens: - - '30000000' - x-ratelimit-remaining-requests: - - '9999' - x-ratelimit-remaining-tokens: - - '30000000' - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_f123f2742f0942de816ad96a756cdbd7 - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"role":"user","content":"Analyze this text briefly: Artificial - intelligence is transforming industries worldwide. Companies are adopting AI - technologies to improve efficiency and innovation. However, challenges like - ethics and job displacement remain concerns."}],"model":"gpt-4o-mini"}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '300' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - OpenAI/Python 2.15.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - 'false' - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Raw-Response: - - 'true' - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFTLbhsxDLz7Kwhd2gJ2YDtG4uRm9IGmx6JAD0VhyBJXS0dLChLXqVvk - 3wutndh9Ab0sBA5JzYzI/TECMOTNLRjXWnVdipPX+/nqw+ertH1/OX/rme275fs3H7er7dsPNzsz - rhWy2aLTp6oLJ12KqCR8gF1Gq1i7zq6vlov5Ynp5MwCdeIy1LCSdLGTSEdNkPp0vJtPryWx5rG6F - HBZzC19GAAA/hm/lyR6/mVuYjp8iHZZiA5rb5yQAkyXWiLGlUFHLasYn0Akr8kD9U4ug+E2hpdBG - Cq0W0BahUGBqyFlWoC5ZpyAN2Kw1SDYCsWKMFJAdwsvV3SsQhhBlM2C+L5oJyxhYlDiAtlZBcrBM - 3201qYDNCBF3mG2oGas7UAHk1taOG9EWsKmXIbs9WPZAzLIbii/gTsG6e5aHiD7ggfMGGRvSMjD1 - ko4XY6kSXcsSJRAWeGgpIthYBDI6CUzfayZ1SXK1ClxrY0QOlX9J6AYjYtwDaltP4IQLecxPStgP - BJJUW6s7jWTYygY8lRStww5ZL6CaLVVwjKDCCKUPAYsWsLCxsQr3sCN8GEPPHnNxko8awPc2Alvt - M1Z9q7sXBYib2A8PIDwkPUi+byQ7HCgVcYS6vzh/+oxNX2wdP+5jPAMss+hBTx26r0fk8XnMooSU - ZVN+KzUNMZV2ndEW4TpSRSWZAX0cAXwdxrn/ZUJNytIlXavc43DdYnZoZ05LdAKvr4+gitp4is9m - y/Ff2q09qqVYzvbBOOta9KfS0/LY3pOcAaMz0X+y+Vvvg3Di8D/tT4BzmBT9OmX05H5VfErLWP8x - /0p7NnkgbArmHTlcK2GuD+GxsX08bL4p+6LYrRvigDllOqx/k9bzm8vLqb25Wi7N6HH0EwAA//8D - APVKo5cMBQAA - headers: - CF-RAY: - - 9be006a818f7f272-IAD - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 14 Jan 2026 20:54:01 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=I0BZkhsUPY3DLfzpbwc9OWeppp07t5QFeRu_m00wgog-1768424041-1.0.1.1-gETSipnxLLc0Ghg6dXXsg1IQakBeH94nd_g9cm85Mqk_VLyb4xcziyOgojXuiw.UR2pUSGYqt0Spk59fpXI66AfO3SY8pT5922lFcQiChGg; - path=/; expires=Wed, 14-Jan-26 21:24:01 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=MNlPFDZf9.vuvIjQV4efb5fyMc312F16NmfSey.xJwg-1768424041558-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '1749' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '1776' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999937' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_4807fef8d5fd407fb648cb38247dd532 - status: - code: 200 - message: OK -- request: - body: '{"data":[{"object":"trace","id":"trace_77059e8449aa48a7ab8b95a280cacb4a","workflow_name":"Agent - workflow","group_id":null,"metadata":null},{"object":"trace.span","id":"span_a1310ceb4e8e4846ada194e7","trace_id":"trace_77059e8449aa48a7ab8b95a280cacb4a","parent_id":"span_d7511d04da724181b44594a8","started_at":"2026-01-14T20:53:56.946594+00:00","ended_at":"2026-01-14T20:53:57.797427+00:00","span_data":{"type":"response","response_id":"resp_0da6aa3826c6950a00696802652e548195ad3a811162e4909c"},"error":null},{"object":"trace.span","id":"span_d7511d04da724181b44594a8","trace_id":"trace_77059e8449aa48a7ab8b95a280cacb4a","parent_id":null,"started_at":"2026-01-14T20:53:56.937476+00:00","ended_at":"2026-01-14T20:53:57.798899+00:00","span_data":{"type":"agent","name":"test-agent","handoffs":[],"tools":[],"output_type":"str"},"error":null},{"object":"trace","id":"trace_53ea0713a8bf4a0b8f59a0d885e1cc5d","workflow_name":"Agent - workflow","group_id":null,"metadata":null},{"object":"trace","id":"trace_35aed2860f7b4703932f1502aa329afc","workflow_name":"Agent - workflow","group_id":null,"metadata":null},{"object":"trace.span","id":"span_838ffe7b3f3045cbbef994df","trace_id":"trace_53ea0713a8bf4a0b8f59a0d885e1cc5d","parent_id":"span_301d4d97ffd34f0b9a247668","started_at":"2026-01-14T20:53:57.804773+00:00","ended_at":"2026-01-14T20:53:58.397553+00:00","span_data":{"type":"response","response_id":"resp_09c189e8ef3ec9020069680265e94c8195be83ab2f06345b49"},"error":null},{"object":"trace.span","id":"span_301d4d97ffd34f0b9a247668","trace_id":"trace_53ea0713a8bf4a0b8f59a0d885e1cc5d","parent_id":null,"started_at":"2026-01-14T20:53:57.804133+00:00","ended_at":"2026-01-14T20:53:58.398525+00:00","span_data":{"type":"agent","name":"agent-a","handoffs":[],"tools":[],"output_type":"str"},"error":null},{"object":"trace.span","id":"span_7d58da841ace461aa1ead190","trace_id":"trace_35aed2860f7b4703932f1502aa329afc","parent_id":"span_1db31ac16c1445428e08dfbb","started_at":"2026-01-14T20:53:57.805195+00:00","ended_at":"2026-01-14T20:53:58.543287+00:00","span_data":{"type":"response","response_id":"resp_043aff85cc8ff2850069680265e8c08194a26ada1e305d4981"},"error":null},{"object":"trace.span","id":"span_1db31ac16c1445428e08dfbb","trace_id":"trace_35aed2860f7b4703932f1502aa329afc","parent_id":null,"started_at":"2026-01-14T20:53:57.804370+00:00","ended_at":"2026-01-14T20:53:58.544328+00:00","span_data":{"type":"agent","name":"agent-b","handoffs":[],"tools":[],"output_type":"str"},"error":null}]}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '2491' - Content-Type: - - application/json - Host: - - api.openai.com - OpenAI-Beta: - - traces=v1 - User-Agent: - - python-httpx/0.28.1 - method: POST - uri: https://api.openai.com/v1/traces/ingest - response: - body: - string: '' - headers: - CF-RAY: - - 9be006b5ae683b92-IAD - Connection: - - keep-alive - Date: - - Wed, 14 Jan 2026 20:54:02 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=eIA31fCLRTVyDCgitQLonvU0q.gZ9FMb.axNF5KHAOM-1768424042-1.0.1.1-FHSCThp6LycbpvtcrA21tGEyF5pTfRJTgTy9ZCaDLzCTEyuq8Xi27jN54eVW4OMcKIdOUL0oZpPucWsaBAnzBI4oiHWo61Bbskg7hgCak9o; - path=/; expires=Wed, 14-Jan-26 21:24:02 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=hEtZSoG7Ssq9XjEFJ71G3C.SdGKcdFQAfb_c_qXS2LM-1768424042060-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '105' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - '107' - x-openai-proxy-wasm: - - v0.1 - x-request-id: - - req_4b033eb97e9750bfbaf34e5d64ed69ed - status: - code: 204 - message: No Content -- request: - body: '{"include":[],"input":[{"content":"Please analyze this text: ''Artificial - intelligence is transforming industries worldwide. Companies are adopting AI - technologies to improve efficiency and innovation. However, challenges like - ethics and job displacement remain concerns.''","role":"user"},{"arguments":"{\"text\":\"Artificial - intelligence is transforming industries worldwide. Companies are adopting AI - technologies to improve efficiency and innovation. However, challenges like - ethics and job displacement remain concerns.\"}","call_id":"call_qr8O7e6F277S3USvt1qFslQz","name":"analyze_text","type":"function_call","id":"fc_0493d21a1f09062200696802671ed88193896f5e51b64ce7d7","status":"completed"},{"call_id":"call_qr8O7e6F277S3USvt1qFslQz","output":"The - text highlights the significant impact of artificial intelligence (AI) on global - industries, noting that organizations are leveraging AI to enhance both efficiency - and innovation. It acknowledges the benefits of adopting these technologies - while also recognizing important challenges, specifically ethical considerations - and the potential for job displacement. The overall tone suggests a balanced - view, underscoring the dual nature of AI''s influence on the workforce and society.","type":"function_call_output"}],"instructions":"You - are a helpful assistant that analyzes text. When asked to analyze text, you - MUST use the analyze_text tool. Always call the tool with the exact text provided - by the user. After using the tool, provide a two sentence summary of what the - tool returned.","model":"gpt-4.1","tools":[{"name":"analyze_text","parameters":{"properties":{"text":{"title":"Text","type":"string"}},"required":["text"],"title":"analyze_text_args","type":"object"},"strict":false,"type":"function","description":"Analyze - text and return a structured summary with key points, sentiment, and statistics."}]}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '1864' - Content-Type: - - application/json - Cookie: - - __cf_bm=IwSSJ.RHOyrDHy71t190C0u4EL9HMgUY2jiVoTE3Rx0-1768424037-1.0.1.1-ZID4mvxCwpZVRzFS1fLdN1Y2IWkkn_wazHoPQBolLYHzMoZNRkTFDL0fqX4m.0FY97.b95rhiBzBDf3ubnonNwcnYBcTqnrX4_OgE7Fq6Lw; - _cfuvid=RePkKlnxLbAHj0ymuEQEUhV2_qf3Ejhb0yEUFttOP24-1768424037764-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - Agents/Python 0.6.5 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//fFZNb+M2EL3nVwx0dgz5I944txz30FO3KIpFIYzIkc01RbLk0I66yH8v - SFmy5E16k/jmSzNvHvXzAaBQsniBwlNwVbndb+R6haum3Je79bosd/vdc7ne7WuU2+fVfvMsnla1 - lE97sdk9rfZPxSKFsPUPEjyEsSZQfy48IZOsMGGrL7vn7XpbblcZC4wcQ/IRtnWamGTvVKM4HbyN - JtXVoA7UHyutlTkUL/DzAQCgcNiRT/6SzqStI188ALz3iYeQd6k3GSXvbfI0Uet80Hj6J5IRXeXI - oOaueIFyWWZMmSFYJYlR6TD1VCawj4KVNflb/rIR0BMgHEm7JmrAEFRgNAx8RAY0qLt/KQDTGy/h - zyMZwHAiCWwHMGML6GyE3/74/RvEQMBHGuAqwcDW6iW86gt2AQRqnU3SKVwUH/MbvaHgHA2ct2cl - SULdZSgG8kt4bZg8xKDMYXRfDLaAwBcLgQyTEQQhti36DmwDl/QpYz5PHL0huewH2OJbZSO7yBXb - E5lZwxKYnKpU8hyxknTq4cHx43a5elyX66fHcvu42l5ZlmMWL/A9E6CnwUjgNhz+h7+NlCLxt97g - altunuu6rLGRmxw5R+HOUY5DIeCBbsBnRM2gsKk5t6Kmhc3CDg2hNx69swEaYxkHAn3/ewZqe3De - 1h8gOdALFN+GITRpY3qO5cGkoUsVRAyBAtT2Sglng2J1JlCtS+SwDbx+BWuAmkYJlZYA0EhQxthz - LmsBGOBCOlEZhDWCvAmAtY0MxEclQnb4YeuUz2kU1JLhJXzlbK5jot1YmD2Tz2y1hkAFqFGjESQX - gOJk7EWTPCQ6jhWjPKNhPFCfRxxRazLpta8dpXWpzmUx9uf9+jS2rPBW5zGM29gbJ8NsVDhMVZGe - k5N97NXHeQppCT4QCOfprGwM1aB9VSbkyGvnbeu4EiiOVJ2o+xTzlKikrJlaeMJgzUz4qGms54lR - Imm/m9fDUQcDNsRdpWQK3CiaqV4gf1aCKlaDjjYYdU/PIrD1NO0AU+vII8d8vLp+/JWG18oa61u8 - vU/on+36ll8rPpOvExe7fumkiu1Nv/shHK0S/dQi22IEwq8SMKRposlafFtQSUF45a5tLV4nCpvp - 1GsXIPQ6Hj3JUeiyjp6oA2eV4bDIUqgSuRfZNymDCqxEWN4SGmz7midifUMTzVpi8mHSpZ4Ijjwr - mp/fd/h2qrgn9Ld7QZl0I7BPxJmA77cVufkU6fZTnuRMxWA6tNkyTdNPv7JCfwjF1GrQvv734OEu - c64v/zbkW/5uIdm6aiJ/5XjopvTz0QgchitVwFoP/xExy/jITWVmF9L6y27xKzC54kdu5eWUN89y - RuP7i267/wj4KO642Z+FZsuob+Bm/TTuR7q9Z3cnMUpkTPHfH97/AwAA//8DAG1C7ibYCQAA - headers: - CF-RAY: - - 9be006b469231fdf-IAD - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 14 Jan 2026 20:54:03 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '1621' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '1623' - x-ratelimit-limit-requests: - - '10000' - x-ratelimit-limit-tokens: - - '30000000' - x-ratelimit-remaining-requests: - - '9999' - x-ratelimit-remaining-tokens: - - '30000000' - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_27c452732f6e400bb7923aba68411a23 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_agno_simple_agent_execution.yaml b/py/src/braintrust/wrappers/cassettes/test_agno_simple_agent_execution.yaml deleted file mode 100644 index 971b532ff..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_agno_simple_agent_execution.yaml +++ /dev/null @@ -1,222 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"developer","content":"\nYou are librarian. - Answer the questions by only replying with the author that wrote the book.\n"},{"role":"user","content":"Charlotte''s - Web"}],"model":"gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '240' - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.108.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.108.1 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJPb9swDMXv/hQCz3HgJnGd5LhhlyHYYRvQAUNhKBJtq5NFTaL3r8h3 - H+Sksbt1wC4+8MdHvUfzMRMCjIa9ANVJVr23+evDr/fF+uHD8fAW6fC1e/dp03ws9F2odqvvsEgK - Oj6g4ifVUlHvLbIhd8YqoGRMU2+qcrcuq6LajqAnjTbJWs/5hvLeOJOvitUmL6r8ZntRd2QURtiL - z5kQQjyO3+TTafwBe1Esnio9xihbhP21SQgIZFMFZIwmsnQMiwkqcoxutP5m+Wop7jrDOG8I2AxR - JpNusHYGpHPEMoUcrd1fyOlqxlLrAx3jH1JojDOxqwPKSC49HJk8jPSUCXE/hh6e5QAfqPdcM33B - 8bn19jwOplVPcHNhTCztrLxavDCs1sjS2DjbGSipOtSTclqwHLShGchmkf/28tLsc2zj2v8ZPwGl - 0DPq2gfURj3PO7UFTHf4r7brikfDEDF8MwprNhjSb9DYyMGerwPiz8jY141xLQYfzPlEGl+Xt4Vs - brEsd5Cdst8AAAD//wMAJyWzWTADAAA= - headers: - CF-RAY: - - 987f554e5b55ed3c-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 01 Oct 2025 22:18:00 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=hcP43Qh2L1NmVba3p7bErUjmQnjP7aAHjxbdi3YHlSw-1759357080-1.0.1.1-8lhFSz7gZOGmJhJLooy4aIunu_qoN4YhRCj0zmupYIjqXXCX2Hvq.AOFHyT4KwyU6e3Ed60sqf3kEaO58i9.Hiyg_ypMsUb_JLDwcIhZkro; - path=/; expires=Wed, 01-Oct-25 22:48:00 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=sxcyYSaXBUdm2NblWZQycFNkWcCM4XTXuXWvDWLEwtg-1759357080461-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '1597' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '1616' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999960' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_1ee4f672ec8d4c6bb285a1f47593a93d - status: - code: 200 - message: OK -- request: - body: '{"session_id":"357dd826-17fc-4dd4-9a6a-2f49dbc876ed","run_id":"3a5a3da7-69a5-45c6-b2c3-110fb2ebc3e9","data":{"agent_id":"author-agent","db_type":null,"model_provider":"OpenAI","model_name":"OpenAIChat","model_id":"gpt-4o-mini","parser_model":null,"output_model":null,"has_tools":true,"has_memory":false,"has_reasoning":false,"has_knowledge":false,"has_input_schema":false,"has_output_schema":false,"has_team":false},"sdk_version":"2.1.0","type":"agent"}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '453' - content-type: - - application/json - host: - - os-api.agno.com - user-agent: - - agno/2.1.0 - method: POST - uri: https://os-api.agno.com/telemetry/runs - response: - body: - string: '{"message":"Run creation acknowledged: 3a5a3da7-69a5-45c6-b2c3-110fb2ebc3e9","status":"success"}' - headers: - Connection: - - keep-alive - Content-Length: - - '96' - Content-Type: - - application/json - Date: - - Wed, 01 Oct 2025 22:18:00 GMT - server: - - uvicorn - status: - code: 201 - message: Created -- request: - body: null - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '0' - User-Agent: - - python-requests/2.32.5 - method: POST - uri: https://www.braintrust.dev/api/apikey/login - response: - body: - string: '{"org_info":[{"id":"5d7c97d7-fef1-4cb7-bda6-7e3756a0ca8e","name":"braintrustdata.com","api_url":"https://staging-api.braintrust.dev","git_metadata":{"fields":["commit","branch","tag","author_name","author_email","commit_message","commit_time","dirty"],"collect":"some"},"is_universal_api":true,"proxy_url":"https://staging-api.braintrust.dev","realtime_url":"wss://realtime.braintrustapi.com"}]}' - headers: - Access-Control-Allow-Credentials: - - 'true' - Access-Control-Allow-Headers: - - X-CSRF-Token, X-Requested-With, Accept, Accept-Version, Content-Length, Content-MD5, - Content-Type, Date, X-Api-Version - Access-Control-Allow-Methods: - - GET,OPTIONS,PATCH,DELETE,POST,PUT - Access-Control-Allow-Origin: - - '*' - Cache-Control: - - public, max-age=0, must-revalidate - Content-Length: - - '395' - Content-Security-Policy: - - 'script-src ''self'' ''unsafe-eval'' ''wasm-unsafe-eval'' ''strict-dynamic'' - ''nonce-YzU3MWQyYjktYjQ4Mi00NTVmLTg0N2ItN2Y2OGRkMDZkNmQ2'' *.js.stripe.com - js.stripe.com maps.googleapis.com ; style-src ''self'' ''unsafe-inline'' *.braintrust.dev - fonts.googleapis.com www.gstatic.com; font-src ''self'' data: fonts.gstatic.com; - object-src ''none''; base-uri ''self''; form-action ''self''; frame-ancestors - ''self''; worker-src ''self'' blob:; report-uri https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=14; - report-to csp-endpoint-0' - Content-Type: - - application/json; charset=utf-8 - Date: - - Wed, 01 Oct 2025 22:18:01 GMT - Etag: - - '"12n7ok4b5phaz"' - Reporting-Endpoints: - - csp-endpoint-0="https://o4507221741076480.ingest.us.sentry.io/api/4507221754380288/security/?sentry_key=27fa5ac907cf7c6ce4a1ab2a03f805b4&sentry_environment=production&sentry_release=14" - Server: - - Vercel - Strict-Transport-Security: - - max-age=63072000 - X-Clerk-Auth-Message: - - Invalid JWT form. A JWT consists of three parts separated by dots. (reason=token-invalid, - token-carrier=header) - X-Clerk-Auth-Reason: - - token-invalid - X-Clerk-Auth-Status: - - signed-out - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-Matched-Path: - - /api/apikey/login - X-Nonce: - - YzU3MWQyYjktYjQ4Mi00NTVmLTg0N2ItN2Y2OGRkMDZkNmQ2 - X-Vercel-Cache: - - MISS - X-Vercel-Id: - - sfo1::iad1::mml49-1759357081072-795a0b8d968a - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_beta_messages_create_async.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_beta_messages_create_async.yaml deleted file mode 100644 index a8b962bcf..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_beta_messages_create_async.yaml +++ /dev/null @@ -1,108 +0,0 @@ -interactions: -- request: - body: '{"max_tokens":100,"messages":[{"role":"user","content":"what is 8+2?, just - return the number"}],"model":"claude-3-haiku-20240307"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - '2023-06-01' - connection: - - keep-alive - content-length: - - '130' - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - AsyncAnthropic/Python 0.66.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.66.0 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-timeout: - - '600' - method: POST - uri: https://api.anthropic.com/v1/messages?beta=true - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//dJDLasMwEEX/5a4VsBO7SbUsFLrqqptQihDSEIvIkiuN3Abjfy8ONX3R - 1cA9Z2bgTuijJQ8J43WxtNltOu3OZbOttk21q/YQcBYSfT6pqr6/PR6ap7vUj8fUjI+Xm7f0sG8h - wJeBFoty1ieCQIp+CXTOLrMODAETA1NgyOdp9ZneF3IdEnWF+UUgcxxUIp1jgAQFq7ikgE+Q6bVQ - MAQZivcC5fpQTnBhKKw4nilkyPogYLTpSJlEml0M6qdQrTyRtv+xdXe5T0NHPSXtVdv/9b9o3f2m - s0As/D1qBTKl0RlS7ChBYinJ6mQxzx8AAAD//wMAVE6fz5QBAAA= - headers: - CF-RAY: - - 9923959fbaa5c152-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Tue, 21 Oct 2025 20:42:58 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - '8000000' - anthropic-ratelimit-input-tokens-remaining: - - '8000000' - anthropic-ratelimit-input-tokens-reset: - - '2025-10-21T20:42:58Z' - anthropic-ratelimit-output-tokens-limit: - - '1500000' - anthropic-ratelimit-output-tokens-remaining: - - '1500000' - anthropic-ratelimit-output-tokens-reset: - - '2025-10-21T20:42:58Z' - anthropic-ratelimit-requests-limit: - - '10000' - anthropic-ratelimit-requests-remaining: - - '9999' - anthropic-ratelimit-requests-reset: - - '2025-10-21T20:42:57Z' - anthropic-ratelimit-tokens-limit: - - '9500000' - anthropic-ratelimit-tokens-remaining: - - '9500000' - anthropic-ratelimit-tokens-reset: - - '2025-10-21T20:42:58Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CULzbgD376cX4UYWh8NnN - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - x-envoy-upstream-service-time: - - '529' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_beta_messages_stream_sync.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_beta_messages_stream_sync.yaml deleted file mode 100644 index 5a5750279..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_beta_messages_stream_sync.yaml +++ /dev/null @@ -1,136 +0,0 @@ -interactions: -- request: - body: '{"max_tokens":300,"messages":[{"role":"user","content":"what is 5+5? (just - the number)"}],"model":"claude-3-haiku-20240307","stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - '2023-06-01' - connection: - - keep-alive - content-length: - - '138' - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.66.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.66.0 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-stream-helper: - - beta.messages - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages?beta=true - response: - body: - string: 'event: message_start - - data: {"type":"message_start","message":{"model":"claude-3-haiku-20240307","id":"msg_01S5kL8QE9V6vWV2bW3ammYD","type":"message","role":"assistant","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":19,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard"}} - } - - - event: content_block_start - - data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""} } - - - event: content_block_delta - - data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"10"} } - - - event: content_block_stop - - data: {"type":"content_block_stop","index":0 } - - - event: message_delta - - data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"input_tokens":19,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"output_tokens":5} } - - - event: message_stop - - data: {"type":"message_stop" } - - - ' - headers: - CF-RAY: - - 9923959aa9b3ad1b-EWR - Cache-Control: - - no-cache - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Tue, 21 Oct 2025 20:42:57 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - '8000000' - anthropic-ratelimit-input-tokens-remaining: - - '8000000' - anthropic-ratelimit-input-tokens-reset: - - '2025-10-21T20:42:57Z' - anthropic-ratelimit-output-tokens-limit: - - '1500000' - anthropic-ratelimit-output-tokens-remaining: - - '1500000' - anthropic-ratelimit-output-tokens-reset: - - '2025-10-21T20:42:57Z' - anthropic-ratelimit-requests-limit: - - '10000' - anthropic-ratelimit-requests-remaining: - - '9999' - anthropic-ratelimit-requests-reset: - - '2025-10-21T20:42:57Z' - anthropic-ratelimit-tokens-limit: - - '9500000' - anthropic-ratelimit-tokens-remaining: - - '9500000' - anthropic-ratelimit-tokens-reset: - - '2025-10-21T20:42:57Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CULzbciC4vzCFVf7AWTfX - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - x-envoy-upstream-service-time: - - '377' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_beta_messages_streaming_async.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_beta_messages_streaming_async.yaml deleted file mode 100644 index 5ee5fb0e4..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_beta_messages_streaming_async.yaml +++ /dev/null @@ -1,138 +0,0 @@ -interactions: -- request: - body: '{"max_tokens":1024,"messages":[{"role":"user","content":"what is 9+1?, - just return the number"}],"model":"claude-3-haiku-20240307","stream":true}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '145' - Content-Type: - - application/json - Host: - - api.anthropic.com - User-Agent: - - AsyncAnthropic/Python 0.48.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 0.48.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - X-Stainless-Stream-Helper: - - beta.messages - anthropic-version: - - '2023-06-01' - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: 'event: message_start - - data: {"type":"message_start","message":{"model":"claude-3-haiku-20240307","id":"msg_015PAQz666KsYA2YR2AaXesp","type":"message","role":"assistant","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":18,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":4,"service_tier":"standard"}} } - - - event: content_block_start - - data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""} } - - - event: ping - - data: {"type": "ping"} - - - event: content_block_delta - - data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"10"} } - - - event: content_block_stop - - data: {"type":"content_block_stop","index":0 } - - - event: message_delta - - data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"input_tokens":18,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"output_tokens":5} } - - - event: message_stop - - data: {"type":"message_stop" } - - - ' - headers: - CF-RAY: - - 9be043f8bae741d8-EWR - Cache-Control: - - no-cache - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Wed, 14 Jan 2026 21:35:51 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - '8000000' - anthropic-ratelimit-input-tokens-remaining: - - '8000000' - anthropic-ratelimit-input-tokens-reset: - - '2026-01-14T21:35:51Z' - anthropic-ratelimit-output-tokens-limit: - - '1500000' - anthropic-ratelimit-output-tokens-remaining: - - '1500000' - anthropic-ratelimit-output-tokens-reset: - - '2026-01-14T21:35:51Z' - anthropic-ratelimit-requests-limit: - - '10000' - anthropic-ratelimit-requests-remaining: - - '9999' - anthropic-ratelimit-requests-reset: - - '2026-01-14T21:35:51Z' - anthropic-ratelimit-tokens-limit: - - '9500000' - anthropic-ratelimit-tokens-remaining: - - '9500000' - anthropic-ratelimit-tokens-reset: - - '2026-01-14T21:35:51Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CX7zPRWXSZGowdHKzQqYc - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - '297' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_beta_messages_sync.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_beta_messages_sync.yaml deleted file mode 100644 index 44c84d749..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_beta_messages_sync.yaml +++ /dev/null @@ -1,107 +0,0 @@ -interactions: -- request: - body: '{"max_tokens":300,"messages":[{"role":"user","content":"what''s 3+3?"}],"model":"claude-3-haiku-20240307"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - '2023-06-01' - connection: - - keep-alive - content-length: - - '105' - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.66.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.66.0 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-timeout: - - '600' - method: POST - uri: https://api.anthropic.com/v1/messages?beta=true - response: - body: - string: !!binary | - H4sIAAAAAAAAA3SQXUvDMBSG/0p5b82kXecHAW8cghdeiF6KhJAc1mxt0iUnzlH636XDIk68OnCe - 53zwDuiCpRYSptXZ0qJeNNrt8mJZLldlXd5AwFlIdGmjyurl+fUp6Nv11h62h/2D8cfD+vEeAnzs - abIoJb0hCMTQTg2dkkusPUPABM/kGfJtmH2mz4mcikRdXBR1cVdcX2J8F0gcehVJp+AhQd4qztHj - GyTaZ/KGIH1uW4F8OiwHON9nVhx25BNktRIw2jSkTCTNLnj1WyhnHknb/9g8O+2nvqGOom7VVffX - /6FVc05HgZD5/LtE8cMZUuwoQmJKy+poMY5fAAAA//8DAF8SioadAQAA - headers: - CF-RAY: - - 992395963d177cb1-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Tue, 21 Oct 2025 20:42:56 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - '8000000' - anthropic-ratelimit-input-tokens-remaining: - - '8000000' - anthropic-ratelimit-input-tokens-reset: - - '2025-10-21T20:42:56Z' - anthropic-ratelimit-output-tokens-limit: - - '1500000' - anthropic-ratelimit-output-tokens-remaining: - - '1500000' - anthropic-ratelimit-output-tokens-reset: - - '2025-10-21T20:42:56Z' - anthropic-ratelimit-requests-limit: - - '10000' - anthropic-ratelimit-requests-remaining: - - '9999' - anthropic-ratelimit-requests-reset: - - '2025-10-21T20:42:56Z' - anthropic-ratelimit-tokens-limit: - - '9500000' - anthropic-ratelimit-tokens-remaining: - - '9500000' - anthropic-ratelimit-tokens-reset: - - '2025-10-21T20:42:56Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CULzbZj74L6N6BM5hSNab - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - x-envoy-upstream-service-time: - - '495' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_client_error.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_client_error.yaml deleted file mode 100644 index 85d220faa..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_client_error.yaml +++ /dev/null @@ -1,80 +0,0 @@ -interactions: - - request: - body: '{"max_tokens":999,"messages":[{"role":"user","content":"who are you?"}],"model":"there-is-no-such-model"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - "2023-06-01" - connection: - - keep-alive - content-length: - - "105" - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.52.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.52.1 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-timeout: - - "600" - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//qlYqqSxIVbJSSi0qyi9S0oHSVtUw8bz8kvi0/NK8lHiYitzU4uLEdJBc - bn5Kao6VQklGalGqbmaxbl6+bnFpcoYuWFypthYAAAD//wMAowdmMl0AAAA= - headers: - CF-RAY: - - 9472c8a12ade1b53-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:07:49 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - cf-cache-status: - - DYNAMIC - request-id: - - req_011CPb5rA13qiZ2bwi1DTVZp - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - x-should-retry: - - "false" - status: - code: 404 - message: Not Found -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_create_async.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_create_async.yaml deleted file mode 100644 index c25643be0..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_create_async.yaml +++ /dev/null @@ -1,107 +0,0 @@ -interactions: - - request: - body: - '{"max_tokens":100,"messages":[{"role":"user","content":"what is 6+1?, just - return the number"}],"model":"claude-3-haiku-20240307"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - "2023-06-01" - connection: - - keep-alive - content-length: - - "130" - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - AsyncAnthropic/Python 0.52.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.52.1 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-timeout: - - "600" - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//ZI9RS8QwEIT/yzyn0OuplTwKouiLiOCDSAjJchevt6nZjXiW/nfp4YHi - 08J8M8POhBRhsZeNa1ePV28X5frp5vn+Iekd3XaRv/oDDPQw0uIiEb8hGJQ8LIIXSaKeFQb7HGmA - RRh8jdSsm61Pu9p0bXfWrtseBiGzEivsy3RqVPpcssdj0WN+NRDNoyvkJTMsiKPTWhg/QOi9EgeC - 5ToMBvX4kZ2QeKzqNO+IBXZ1aRB82JILhbymzO6voT3xQj7+Z7nqb+XcQKh8pEBOExVYLLOjLxHz - /A0AAP//AwAb9FnuRAEAAA== - headers: - CF-RAY: - - 9472c8992b3941cf-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:07:48 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - "8000000" - anthropic-ratelimit-input-tokens-remaining: - - "8000000" - anthropic-ratelimit-input-tokens-reset: - - "2025-05-29T03:07:48Z" - anthropic-ratelimit-output-tokens-limit: - - "1500000" - anthropic-ratelimit-output-tokens-remaining: - - "1500000" - anthropic-ratelimit-output-tokens-reset: - - "2025-05-29T03:07:48Z" - anthropic-ratelimit-requests-limit: - - "10000" - anthropic-ratelimit-requests-remaining: - - "9999" - anthropic-ratelimit-requests-reset: - - "2025-05-29T03:07:48Z" - anthropic-ratelimit-tokens-limit: - - "9500000" - anthropic-ratelimit-tokens-remaining: - - "9500000" - anthropic-ratelimit-tokens-reset: - - "2025-05-29T03:07:48Z" - cf-cache-status: - - DYNAMIC - request-id: - - req_011CPb5r4YP1DCcYkkUYE4am - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_create_async_stream_true.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_create_async_stream_true.yaml deleted file mode 100644 index 02a1aec3e..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_create_async_stream_true.yaml +++ /dev/null @@ -1,137 +0,0 @@ -interactions: - - request: - body: - '{"max_tokens":100,"messages":[{"role":"user","content":"what is 6+1?, just - return the number"}],"model":"claude-3-haiku-20240307","stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - "2023-06-01" - connection: - - keep-alive - content-length: - - "144" - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - AsyncAnthropic/Python 0.52.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.52.1 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: 'event: message_start - - data: {"type":"message_start","message":{"id":"msg_01MWFaVNqKdU45YCBTgbHDLj","type":"message","role":"assistant","model":"claude-3-haiku-20240307","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":18,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"output_tokens":2,"service_tier":"standard"}} } - - - event: content_block_start - - data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""} } - - - event: ping - - data: {"type": "ping"} - - - event: content_block_delta - - data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"7"} } - - - event: content_block_stop - - data: {"type":"content_block_stop","index":0 } - - - event: message_delta - - data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":5} } - - - event: message_stop - - data: {"type":"message_stop" } - - - ' - headers: - CF-RAY: - - 9472c89bd9c932e8-EWR - Cache-Control: - - no-cache - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:07:48 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - "8000000" - anthropic-ratelimit-input-tokens-remaining: - - "8000000" - anthropic-ratelimit-input-tokens-reset: - - "2025-05-29T03:07:48Z" - anthropic-ratelimit-output-tokens-limit: - - "1500000" - anthropic-ratelimit-output-tokens-remaining: - - "1500000" - anthropic-ratelimit-output-tokens-reset: - - "2025-05-29T03:07:48Z" - anthropic-ratelimit-requests-limit: - - "10000" - anthropic-ratelimit-requests-remaining: - - "9999" - anthropic-ratelimit-requests-reset: - - "2025-05-29T03:07:48Z" - anthropic-ratelimit-tokens-limit: - - "9500000" - anthropic-ratelimit-tokens-remaining: - - "9500000" - anthropic-ratelimit-tokens-reset: - - "2025-05-29T03:07:48Z" - cf-cache-status: - - DYNAMIC - request-id: - - req_011CPb5r6N2HCkaPWJii33N1 - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_create_stream_true.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_create_stream_true.yaml deleted file mode 100644 index c34401395..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_create_stream_true.yaml +++ /dev/null @@ -1,148 +0,0 @@ -interactions: - - request: - body: '{"max_tokens":300,"messages":[{"role":"user","content":"What is 3*4?"}],"model":"claude-3-haiku-20240307","stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - "2023-06-01" - connection: - - keep-alive - content-length: - - "120" - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.52.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.52.1 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: 'event: message_start - - data: {"type":"message_start","message":{"id":"msg_012gPZeSmoemYgX2fdPcZFVH","type":"message","role":"assistant","model":"claude-3-haiku-20240307","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":14,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"output_tokens":4,"service_tier":"standard"}} } - - - event: content_block_start - - data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""} } - - - event: ping - - data: {"type": "ping"} - - - event: content_block_delta - - data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"3 - *"} } - - - event: content_block_delta - - data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":" - 4 ="} } - - - event: content_block_delta - - data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":" - 12"} } - - - event: content_block_stop - - data: {"type":"content_block_stop","index":0 } - - - event: message_delta - - data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":13} } - - - event: message_stop - - data: {"type":"message_stop" } - - - ' - headers: - CF-RAY: - - 9472c88a8f806a50-EWR - Cache-Control: - - no-cache - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:07:45 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - "8000000" - anthropic-ratelimit-input-tokens-remaining: - - "8000000" - anthropic-ratelimit-input-tokens-reset: - - "2025-05-29T03:07:45Z" - anthropic-ratelimit-output-tokens-limit: - - "1500000" - anthropic-ratelimit-output-tokens-remaining: - - "1500000" - anthropic-ratelimit-output-tokens-reset: - - "2025-05-29T03:07:45Z" - anthropic-ratelimit-requests-limit: - - "10000" - anthropic-ratelimit-requests-remaining: - - "9999" - anthropic-ratelimit-requests-reset: - - "2025-05-29T03:07:45Z" - anthropic-ratelimit-tokens-limit: - - "9500000" - anthropic-ratelimit-tokens-remaining: - - "9500000" - anthropic-ratelimit-tokens-reset: - - "2025-05-29T03:07:45Z" - cf-cache-status: - - DYNAMIC - request-id: - - req_011CPb5qta7AfiZd2KcxncsY - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_model_params_inputs.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_model_params_inputs.yaml deleted file mode 100644 index 339b2d9b6..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_model_params_inputs.yaml +++ /dev/null @@ -1,244 +0,0 @@ -interactions: - - request: - body: - '{"max_tokens":300,"messages":[{"role":"user","content":"what is 1+1?"}],"model":"claude-3-haiku-20240307","system":"just - return the number","temperature":0.5,"top_p":0.5}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - "2023-06-01" - connection: - - keep-alive - content-length: - - "170" - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.52.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.52.1 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-timeout: - - "600" - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAAA2SPUUsDMRCE/8s8p3B3VSp5E6QF0ae+CCIhJEsb77o5sxuxHPff5YoFxaeF+WaG - nQkpwuIkB9e09y/1/L7dbfqH8tw/7vb7J9rWFgZ6HmlxkYg/EAxKHhbBiyRRzwqDU440wCIMvkZa - rVdHn/q66pruplk3GxiEzEqssK/TtVHpa8lejkWH+c1ANI+ukJfMsCCOTmth/AChj0ocCJbrMBjU - y0d2QuKxqtPcEwtse2cQfDiSC4W8pszur6G58kI+/me56m/l1kCofKZAThMVWCyzoy8R8/wNAAD/ - /wMAqgv+NkQBAAA= - headers: - CF-RAY: - - 9472c88d58827864-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:07:46 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - "8000000" - anthropic-ratelimit-input-tokens-remaining: - - "8000000" - anthropic-ratelimit-input-tokens-reset: - - "2025-05-29T03:07:46Z" - anthropic-ratelimit-output-tokens-limit: - - "1500000" - anthropic-ratelimit-output-tokens-remaining: - - "1500000" - anthropic-ratelimit-output-tokens-reset: - - "2025-05-29T03:07:46Z" - anthropic-ratelimit-requests-limit: - - "10000" - anthropic-ratelimit-requests-remaining: - - "9999" - anthropic-ratelimit-requests-reset: - - "2025-05-29T03:07:46Z" - anthropic-ratelimit-tokens-limit: - - "9500000" - anthropic-ratelimit-tokens-remaining: - - "9500000" - anthropic-ratelimit-tokens-reset: - - "2025-05-29T03:07:46Z" - cf-cache-status: - - DYNAMIC - request-id: - - req_011CPb5qvTxhUkgwBuYcB2SN - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - status: - code: 200 - message: OK - - request: - body: - '{"max_tokens":300,"messages":[{"role":"user","content":"what is 1+1?"}],"model":"claude-3-haiku-20240307","system":"just - return the number","temperature":0.5,"top_p":0.5,"stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - "2023-06-01" - connection: - - keep-alive - content-length: - - "184" - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.52.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.52.1 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-stream-helper: - - messages - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: 'event: message_start - - data: {"type":"message_start","message":{"id":"msg_01FGmwpHyhVL53CxVbrx6KCD","type":"message","role":"assistant","model":"claude-3-haiku-20240307","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":18,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"output_tokens":4,"service_tier":"standard"}} } - - - event: content_block_start - - data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""} } - - - event: ping - - data: {"type": "ping"} - - - event: content_block_delta - - data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"2"} } - - - event: content_block_stop - - data: {"type":"content_block_stop","index":0 } - - - event: message_delta - - data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":5} } - - - event: message_stop - - data: {"type":"message_stop" } - - - ' - headers: - CF-RAY: - - 9472c88fee7e7864-EWR - Cache-Control: - - no-cache - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:07:46 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - "8000000" - anthropic-ratelimit-input-tokens-remaining: - - "8000000" - anthropic-ratelimit-input-tokens-reset: - - "2025-05-29T03:07:46Z" - anthropic-ratelimit-output-tokens-limit: - - "1500000" - anthropic-ratelimit-output-tokens-remaining: - - "1500000" - anthropic-ratelimit-output-tokens-reset: - - "2025-05-29T03:07:46Z" - anthropic-ratelimit-requests-limit: - - "10000" - anthropic-ratelimit-requests-remaining: - - "9999" - anthropic-ratelimit-requests-reset: - - "2025-05-29T03:07:46Z" - anthropic-ratelimit-tokens-limit: - - "9500000" - anthropic-ratelimit-tokens-remaining: - - "9500000" - anthropic-ratelimit-tokens-reset: - - "2025-05-29T03:07:46Z" - cf-cache-status: - - DYNAMIC - request-id: - - req_011CPb5qxBQ9po6M9MsWga8m - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_stream_errors.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_stream_errors.yaml deleted file mode 100644 index e26cb87c5..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_stream_errors.yaml +++ /dev/null @@ -1,139 +0,0 @@ -interactions: - - request: - body: - '{"max_tokens":300,"messages":[{"role":"user","content":"what is 2+2? (just - the number)"}],"model":"claude-3-haiku-20240307","stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - "2023-06-01" - connection: - - keep-alive - content-length: - - "138" - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.52.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.52.1 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-stream-helper: - - messages - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: 'event: message_start - - data: {"type":"message_start","message":{"id":"msg_019YzLeF9bnSTwHRpHPNEbid","type":"message","role":"assistant","model":"claude-3-haiku-20240307","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":19,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"output_tokens":3,"service_tier":"standard"}} } - - - event: content_block_start - - data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""} } - - - event: ping - - data: {"type": "ping"} - - - event: content_block_delta - - data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"4"} } - - - event: content_block_stop - - data: {"type":"content_block_stop","index":0 } - - - event: message_delta - - data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":5} } - - - event: message_stop - - data: {"type":"message_stop" } - - - ' - headers: - CF-RAY: - - 9472c8a1fea943f1-EWR - Cache-Control: - - no-cache - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:07:50 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - "8000000" - anthropic-ratelimit-input-tokens-remaining: - - "8000000" - anthropic-ratelimit-input-tokens-reset: - - "2025-05-29T03:07:50Z" - anthropic-ratelimit-output-tokens-limit: - - "1500000" - anthropic-ratelimit-output-tokens-remaining: - - "1500000" - anthropic-ratelimit-output-tokens-reset: - - "2025-05-29T03:07:50Z" - anthropic-ratelimit-requests-limit: - - "10000" - anthropic-ratelimit-requests-remaining: - - "9999" - anthropic-ratelimit-requests-reset: - - "2025-05-29T03:07:50Z" - anthropic-ratelimit-tokens-limit: - - "9500000" - anthropic-ratelimit-tokens-remaining: - - "9500000" - anthropic-ratelimit-tokens-reset: - - "2025-05-29T03:07:50Z" - cf-cache-status: - - DYNAMIC - request-id: - - req_011CPb5rAezEMDtahaZ57coa - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_streaming_async.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_streaming_async.yaml deleted file mode 100644 index acd6bf5c7..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_streaming_async.yaml +++ /dev/null @@ -1,140 +0,0 @@ -interactions: - - request: - body: - '{"max_tokens":1024,"messages":[{"role":"user","content":"what is 1+1?, - just return the number"}],"model":"claude-3-haiku-20240307","stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - "2023-06-01" - connection: - - keep-alive - content-length: - - "145" - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - AsyncAnthropic/Python 0.52.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.52.1 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-stream-helper: - - messages - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: 'event: message_start - - data: {"type":"message_start","message":{"id":"msg_01Hwq7nXVJreMkdBttJ9H46B","type":"message","role":"assistant","model":"claude-3-haiku-20240307","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":18,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"output_tokens":2,"service_tier":"standard"}} } - - - event: content_block_start - - data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""} } - - - event: ping - - data: {"type": "ping"} - - - event: content_block_delta - - data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"2"} - } - - - event: content_block_stop - - data: {"type":"content_block_stop","index":0 } - - - event: message_delta - - data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":5} } - - - event: message_stop - - data: {"type":"message_stop" } - - - ' - headers: - CF-RAY: - - 9472c89e6a908c63-EWR - Cache-Control: - - no-cache - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:07:49 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - "8000000" - anthropic-ratelimit-input-tokens-remaining: - - "8000000" - anthropic-ratelimit-input-tokens-reset: - - "2025-05-29T03:07:48Z" - anthropic-ratelimit-output-tokens-limit: - - "1500000" - anthropic-ratelimit-output-tokens-remaining: - - "1499000" - anthropic-ratelimit-output-tokens-reset: - - "2025-05-29T03:07:49Z" - anthropic-ratelimit-requests-limit: - - "10000" - anthropic-ratelimit-requests-remaining: - - "9999" - anthropic-ratelimit-requests-reset: - - "2025-05-29T03:07:48Z" - anthropic-ratelimit-tokens-limit: - - "9500000" - anthropic-ratelimit-tokens-remaining: - - "9499000" - anthropic-ratelimit-tokens-reset: - - "2025-05-29T03:07:48Z" - cf-cache-status: - - DYNAMIC - request-id: - - req_011CPb5r8E8kny9TZdxz4Q6v - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_streaming_sync.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_streaming_sync.yaml deleted file mode 100644 index 583281690..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_streaming_sync.yaml +++ /dev/null @@ -1,139 +0,0 @@ -interactions: - - request: - body: - '{"max_tokens":300,"messages":[{"role":"user","content":"what is 2+2? (just - the number)"}],"model":"claude-3-haiku-20240307","stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - "2023-06-01" - connection: - - keep-alive - content-length: - - "138" - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.52.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.52.1 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-stream-helper: - - messages - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: 'event: message_start - - data: {"type":"message_start","message":{"id":"msg_01NR8LiXqHhf3PCEc3k3m3hJ","type":"message","role":"assistant","model":"claude-3-haiku-20240307","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":19,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"output_tokens":4,"service_tier":"standard"}} } - - - event: content_block_start - - data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""} } - - - event: ping - - data: {"type": "ping"} - - - event: content_block_delta - - data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"4"} } - - - event: content_block_stop - - data: {"type":"content_block_stop","index":0 } - - - event: message_delta - - data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":5} } - - - event: message_stop - - data: {"type":"message_stop" } - - - ' - headers: - CF-RAY: - - 9472c8a8e81323dd-EWR - Cache-Control: - - no-cache - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:07:50 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - "8000000" - anthropic-ratelimit-input-tokens-remaining: - - "8000000" - anthropic-ratelimit-input-tokens-reset: - - "2025-05-29T03:07:50Z" - anthropic-ratelimit-output-tokens-limit: - - "1500000" - anthropic-ratelimit-output-tokens-remaining: - - "1500000" - anthropic-ratelimit-output-tokens-reset: - - "2025-05-29T03:07:50Z" - anthropic-ratelimit-requests-limit: - - "10000" - anthropic-ratelimit-requests-remaining: - - "9999" - anthropic-ratelimit-requests-reset: - - "2025-05-29T03:07:50Z" - anthropic-ratelimit-tokens-limit: - - "9500000" - anthropic-ratelimit-tokens-remaining: - - "9500000" - anthropic-ratelimit-tokens-reset: - - "2025-05-29T03:07:50Z" - cf-cache-status: - - DYNAMIC - request-id: - - req_011CPb5rFK3186WDZPzKJEuC - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_sync.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_sync.yaml deleted file mode 100644 index 95676479a..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_sync.yaml +++ /dev/null @@ -1,105 +0,0 @@ -interactions: - - request: - body: '{"max_tokens":300,"messages":[{"role":"user","content":"what''s 2+2?"}],"model":"claude-3-haiku-20240307"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - "2023-06-01" - connection: - - keep-alive - content-length: - - "105" - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.52.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.52.1 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-timeout: - - "600" - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAAA2SPQUsDMRSE/8ucs2W7XRRyKx4KVYseeqlICMljG7tN1rwXUZb977LFguLpwXwz - w5sRwUPjzJ2pl0/dw/5wv2n228fd3fN6sw4+H96gIF8DzS5ith1BIad+FixzYLFRoHBOnnpouN4W - T9WqOtpwKlVTN229qm+h4FIUigL9Ml4bhT7n7OVotAtMrwosaTCZLKcIDYreSMkRP4DpvVB0BB1L - 3yuUy0t6RIhDESPpRJGhl62Cs+5IxmWyElI0fw31lWey/j9LRX4rNwpM+SM4MhIoQ2Pe7W32mKZv - AAAA//8DAOBQupxFAQAA - headers: - CF-RAY: - - 9472c8abe82e4346-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:07:51 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - "8000000" - anthropic-ratelimit-input-tokens-remaining: - - "8000000" - anthropic-ratelimit-input-tokens-reset: - - "2025-05-29T03:07:51Z" - anthropic-ratelimit-output-tokens-limit: - - "1500000" - anthropic-ratelimit-output-tokens-remaining: - - "1500000" - anthropic-ratelimit-output-tokens-reset: - - "2025-05-29T03:07:51Z" - anthropic-ratelimit-requests-limit: - - "10000" - anthropic-ratelimit-requests-remaining: - - "9999" - anthropic-ratelimit-requests-reset: - - "2025-05-29T03:07:51Z" - anthropic-ratelimit-tokens-limit: - - "9500000" - anthropic-ratelimit-tokens-remaining: - - "9500000" - anthropic-ratelimit-tokens-reset: - - "2025-05-29T03:07:51Z" - cf-cache-status: - - DYNAMIC - request-id: - - req_011CPb5rJW239uEPcCN6bpZm - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_system_prompt_inputs.yaml b/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_system_prompt_inputs.yaml deleted file mode 100644 index c674abbcd..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_anthropic_messages_system_prompt_inputs.yaml +++ /dev/null @@ -1,252 +0,0 @@ -interactions: - - request: - body: - '{"max_tokens":300,"messages":[{"role":"user","content":"what is tomorrow''s - date? only return the date"}],"model":"claude-3-haiku-20240307","system":"Today''s - date is 2024-03-26. Only return the date","temperature":0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - "2023-06-01" - connection: - - keep-alive - content-length: - - "215" - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.52.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.52.1 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-timeout: - - "600" - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//ZJBBS8QwEIX/yzunkDbuFnPWo6CsehEJIRm2cdukJhNRSv+7dHFB8TTw - vm+G4S0IHhpTORrZ9je7/fXh7enhcL+fdurxrn2+HToI8NdMm0Wl2CNBIKdxC2wpobCNDIEpeRqh - 4UZbPTWqGWw41aaT3ZVUsoeAS5EpMvTLcrnI9LntnofG5jZSNV2P9VWgcJpNJltShAZFb7jmiB9Q - 6L1SdAQd6zgK1PNrekGIc2XD6USxQCsl4KwbyLhMlkOK5q8gLzyT9f9Zqvw7aaVAofwRHBkOlKGx - FeBt9ljXbwAAAP//AwBr6Z3cTgEAAA== - headers: - CF-RAY: - - 9472c8932947f834-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:07:47 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - "8000000" - anthropic-ratelimit-input-tokens-remaining: - - "8000000" - anthropic-ratelimit-input-tokens-reset: - - "2025-05-29T03:07:47Z" - anthropic-ratelimit-output-tokens-limit: - - "1500000" - anthropic-ratelimit-output-tokens-remaining: - - "1500000" - anthropic-ratelimit-output-tokens-reset: - - "2025-05-29T03:07:47Z" - anthropic-ratelimit-requests-limit: - - "10000" - anthropic-ratelimit-requests-remaining: - - "9999" - anthropic-ratelimit-requests-reset: - - "2025-05-29T03:07:47Z" - anthropic-ratelimit-tokens-limit: - - "9500000" - anthropic-ratelimit-tokens-remaining: - - "9500000" - anthropic-ratelimit-tokens-reset: - - "2025-05-29T03:07:47Z" - cf-cache-status: - - DYNAMIC - request-id: - - req_011CPb5qzRayPPoo8L1mPdh1 - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - status: - code: 200 - message: OK - - request: - body: - '{"max_tokens":300,"messages":[{"role":"user","content":"what is tomorrow''s - date? only return the date"}],"model":"claude-3-haiku-20240307","system":"Today''s - date is 2024-03-26. Only return the date","temperature":0,"stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - anthropic-version: - - "2023-06-01" - connection: - - keep-alive - content-length: - - "229" - content-type: - - application/json - host: - - api.anthropic.com - user-agent: - - Anthropic/Python 0.52.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 0.52.1 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - x-stainless-stream-helper: - - messages - x-stainless-timeout: - - NOT_GIVEN - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: 'event: message_start - - data: {"type":"message_start","message":{"id":"msg_016SfgyEMZw26QGn6irgmFJL","type":"message","role":"assistant","model":"claude-3-haiku-20240307","content":[],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":33,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"output_tokens":1,"service_tier":"standard"}} - } - - - event: content_block_start - - data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""} } - - - event: ping - - data: {"type": "ping"} - - - event: content_block_delta - - data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"2024-03"} } - - - event: content_block_delta - - data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"-27"} } - - - event: content_block_stop - - data: {"type":"content_block_stop","index":0 } - - - event: message_delta - - data: {"type":"message_delta","delta":{"stop_reason":"end_turn","stop_sequence":null},"usage":{"output_tokens":10} } - - - event: message_stop - - data: {"type":"message_stop" } - - - ' - headers: - CF-RAY: - - 9472c8964fd2f834-EWR - Cache-Control: - - no-cache - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:07:47 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - "8000000" - anthropic-ratelimit-input-tokens-remaining: - - "8000000" - anthropic-ratelimit-input-tokens-reset: - - "2025-05-29T03:07:47Z" - anthropic-ratelimit-output-tokens-limit: - - "1500000" - anthropic-ratelimit-output-tokens-remaining: - - "1500000" - anthropic-ratelimit-output-tokens-reset: - - "2025-05-29T03:07:47Z" - anthropic-ratelimit-requests-limit: - - "10000" - anthropic-ratelimit-requests-remaining: - - "9999" - anthropic-ratelimit-requests-reset: - - "2025-05-29T03:07:47Z" - anthropic-ratelimit-tokens-limit: - - "9500000" - anthropic-ratelimit-tokens-remaining: - - "9500000" - anthropic-ratelimit-tokens-reset: - - "2025-05-29T03:07:47Z" - cf-cache-status: - - DYNAMIC - request-id: - - req_011CPb5r2ZpUAFf1mRX9YxyY - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - 1.1 google - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_async_generator_pattern_call_6.yaml b/py/src/braintrust/wrappers/cassettes/test_async_generator_pattern_call_6.yaml deleted file mode 100644 index f8ed38ee9..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_async_generator_pattern_call_6.yaml +++ /dev/null @@ -1,155 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 5."}],"model":"gpt-4o","max_completion_tokens":100,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '160' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"bP8xUwj1V3LQGR"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"5kb5kSXVNZsFZnz"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"nVAhilA2LmFDLdo"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"d04zpUwb8oumo4x"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"qrVDkKdqD7Duo6y"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"fbNyhzjL4YIbizT"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Ia3dR8pZy6Ujsze"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"B9wfd5rsmjmmmAN"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"W490zj1Xn6JMJp4"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"qKXdgqMlOgMwJ19"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"4"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"jpPMES1xQtsrgGu"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Sb8yLzP1Q3sfFaU"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"NBDTwavxfl0B047"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"3m30VRIYp0W1IJd"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"TVcAd3tLTieoGaw"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"UHXnXfNOZv"} - - - data: {"id":"chatcmpl-CoyYQYXu6ig6CwPKlZrZtvLzx2Lfg","object":"chat.completion.chunk","created":1766265206,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[],"usage":{"prompt_tokens":15,"completion_tokens":14,"total_tokens":29,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"Pd5zRlJDqgG0D0z"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b1224c19b2a7c97-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:26 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '124' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '139' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '10000' - x-ratelimit-limit-tokens: - - '30000000' - x-ratelimit-remaining-requests: - - '9999' - x-ratelimit-remaining-tokens: - - '29999993' - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_fe99d838006d43c2bf7d54f2be91331e - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_auto_agno.yaml b/py/src/braintrust/wrappers/cassettes/test_auto_agno.yaml deleted file mode 100644 index 338d68c22..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_auto_agno.yaml +++ /dev/null @@ -1,147 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"developer","content":"You are a helpful assistant. - Be brief."},{"role":"user","content":"Say hi"}],"model":"gpt-4o-mini"}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate, zstd - Connection: - - keep-alive - Content-Length: - - '143' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - PatchedOpenAI/Python 2.15.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - 'false' - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Raw-Response: - - 'true' - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFJBbtswELzrFVuerUKWjdjyJZcWSBG0QC9F0SIQaHIls6G4LLlqawT+ - e0HJsZQ0BXLRYWdnNDPchwxAGC12INRBsuq8zd8Vunj/8RPef9k3n5tN87W3+ue3Zh1u+TaKRWLQ - /gcqfmS9VdR5i2zIjbAKKBmT6nJzVRXrsqy2A9CRRptored8TXlnnMnLolznxSZfbs/sAxmFUezg - ewYA8DB8k0+n8Y/YQbF4nHQYo2xR7C5LACKQTRMhYzSRpWOxmEBFjtEN1m/MG7ih36Ckgw8wbsOR - emDS8ng9ZwVs+iiTc9dbOwOkc8QyJR/83p2R08WhpdYH2sdnVNEYZ+KhDigjueQmMnkxoKcM4G5o - on8STvhAneea6R6H35XlKCem/iewOmNMLO00Xi0XL4jVGlkaG2dFCiXVAfXEnFqXvTY0A7JZ5H+9 - vKQ9xjaufY38BCiFnlHXPqA26mneaS1gOs7/rV0qHgyLiOGXUVizwZCeQWMjezuejIjHyNjVjXEt - Bh/MeDeNr8tqtSpkdbXdiuyU/QUAAP//AwBBs78WRQMAAA== - headers: - CF-RAY: - - 9c1afcdd3f36b231-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 22 Jan 2026 00:38:19 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=Jw95ZRGfTr6qO8YVvMCpB1aMAiti.HWb9WM0o.EAG4M-1769042299-1.0.1.1-F0ol4YtLGC1.t2DHb1Hj435gvyQ_nGNudwYUErS.pg4aWKbU4O68f4wJthw2GUCv2BYU7cC4ZcIA0B6TvaUN7VYsBM5OS7Ccc46cnb7zQ9Y; - path=/; expires=Thu, 22-Jan-26 01:08:19 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=gxrFvllhyUbQeecWVXMHkFhdg_IAJ7CO467JJDSyVA8-1769042299331-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '438' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '490' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999985' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_c68836a69b1549819fb6a5eecfd10be7 - status: - code: 200 - message: OK -- request: - body: '{"session_id":"3ed01154-18cc-4648-b766-73f60e3e08c2","run_id":"4ebf7a0f-31fa-4a69-9500-f3f3f21d350d","data":{"agent_id":"test-agent","db_type":null,"model_provider":"OpenAI","model_name":"OpenAIChat","model_id":"gpt-4o-mini","parser_model":null,"output_model":null,"has_tools":true,"has_memory":false,"has_learnings":false,"has_culture":false,"has_reasoning":false,"has_knowledge":false,"has_input_schema":false,"has_output_schema":false,"has_team":false},"sdk_version":"2.4.1","type":"agent"}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate, zstd - Connection: - - keep-alive - Content-Length: - - '493' - Content-Type: - - application/json - Host: - - os-api.agno.com - user-agent: - - agno/2.4.1 - method: POST - uri: https://os-api.agno.com/telemetry/runs - response: - body: - string: '{"message":"Run creation acknowledged: 4ebf7a0f-31fa-4a69-9500-f3f3f21d350d","status":"success"}' - headers: - content-length: - - '96' - content-type: - - application/json - date: - - Thu, 22 Jan 2026 00:38:19 GMT - server: - - uvicorn - status: - code: 201 - message: null -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_auto_anthropic.yaml b/py/src/braintrust/wrappers/cassettes/test_auto_anthropic.yaml deleted file mode 100644 index 73ee01336..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_auto_anthropic.yaml +++ /dev/null @@ -1,105 +0,0 @@ -interactions: -- request: - body: '{"max_tokens":100,"messages":[{"role":"user","content":"Say hi"}],"model":"claude-3-5-haiku-20241022"}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate, zstd - Connection: - - keep-alive - Content-Length: - - '102' - Content-Type: - - application/json - Host: - - api.anthropic.com - User-Agent: - - PatchedAnthropic/Python 0.76.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - 'false' - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 0.76.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - anthropic-version: - - '2023-06-01' - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - x-stainless-timeout: - - '600' - method: POST - uri: https://api.anthropic.com/v1/messages - response: - body: - string: !!binary | - H4sIAAAAAAAA/3WQT0vEMBDFv0qdcwtt1x7sRQSFBS9eBFeREJOhjdtmajJxt5R+d9PF4j88zfB+ - bx4zM0FPGjuoQXUyaMw2WZW10uxDVubleZGXJaRgdDT0vhF58bB5fTzcq92Ojrf9XfEy3FxdV030 - 8Djg4kLvZYNRcNQtgvTeeJaWo6TIMsaufppWP+NxIadSw9Yk3KLDs2RLh0Q6TEYKiSZjm4RJy/ES - 5ucUPNMgHEpPNg6h1YKDs/AJPL4FtCqm29B1KYTTQvUExg6BBdMerYf6Iu4jVYtCxSQ2ZMVPnq88 - Yv0fW2eXeBxa7NHJTlT9X/8XLdrfdE6BAn+XijIeg+7dKBRs0MUzlydq6TTM8wcGNCA4tgEAAA== - headers: - CF-RAY: - - 9c1afefa18588183-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 22 Jan 2026 00:39:45 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Robots-Tag: - - none - anthropic-organization-id: - - 27796668-7351-40ac-acc4-024aee8995a5 - anthropic-ratelimit-input-tokens-limit: - - '5000000' - anthropic-ratelimit-input-tokens-remaining: - - '5000000' - anthropic-ratelimit-input-tokens-reset: - - '2026-01-22T00:39:45Z' - anthropic-ratelimit-output-tokens-limit: - - '1000000' - anthropic-ratelimit-output-tokens-remaining: - - '1000000' - anthropic-ratelimit-output-tokens-reset: - - '2026-01-22T00:39:45Z' - anthropic-ratelimit-requests-limit: - - '10000' - anthropic-ratelimit-requests-remaining: - - '9999' - anthropic-ratelimit-requests-reset: - - '2026-01-22T00:39:45Z' - anthropic-ratelimit-tokens-limit: - - '6000000' - anthropic-ratelimit-tokens-remaining: - - '6000000' - anthropic-ratelimit-tokens-reset: - - '2026-01-22T00:39:45Z' - cf-cache-status: - - DYNAMIC - request-id: - - req_011CXMV5BfWXZENVYoJwiZfW - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - '859' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_auto_google_genai.yaml b/py/src/braintrust/wrappers/cassettes/test_auto_google_genai.yaml deleted file mode 100644 index edeb2b682..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_auto_google_genai.yaml +++ /dev/null @@ -1,62 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "Say hi"}], "role": "user"}], "generationConfig": - {"maxOutputTokens": 100}}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate, zstd - Connection: - - keep-alive - Content-Length: - - '109' - Content-Type: - - application/json - Host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.60.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.60.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61Ry07DMBC85yuMz03lpA8eF4QKUgtUVBDxRpUh28TCtSPboURV/x0naVoHrvhg - rXZmd3Zn1x5C+IOKmMXUgMYn6MVmEFpXf4lJYUAYCzQpm8yoMntu/dZObCkGvssiPGbIpKDgAI3l - ClklNEEp8AwVMkdGxrQ4fRXYqd3s4rfOXlFJDmW7pYyBN/RNQ8ALJphOb4FqKUraXXQzwzuUfiXX - MsmUfC+H9kmXBIMjQsKgPwyHg8Ow1z/2GulKFOeaJjAFQ60rdLc7ti2WmYnkJ4iRzCtXwlrF8bAF - B8EWN9JQ3oZ6nT9d9bnVZNz11rHdLk85M0W5YXTxGGHHINMaqjHIc3z8PeI/aQVBW8zb3qU+1T0o - zeqbJLC0V/LDLvEXnOrUJySoumIFOpNCwyQuebNBVtDnq4fLp3k6z6czrUaKnCXY23g/hhi4Mq4C - AAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Thu, 22 Jan 2026 21:44:31 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=430 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_auto_litellm.yaml b/py/src/braintrust/wrappers/cassettes/test_auto_litellm.yaml deleted file mode 100644 index 3bf357149..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_auto_litellm.yaml +++ /dev/null @@ -1,112 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Say hi"}],"model":"gpt-4o-mini"}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate, zstd - Connection: - - keep-alive - Content-Length: - - '71' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - OpenAI/Python 2.15.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - 'false' - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Raw-Response: - - 'true' - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600.0' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFLLbtswELzrK7Y8W4X8qGP5UiAI0PRSoGiAACkCgSZXElOKy5Krpm7g - fy8k2ZbctEAvOuzsjGaG+5IACKPFFoSqJavG2/QmU/uH3Yfq88Ove97cPT1f46f75Zq/f6ncnZh1 - DNo9oeIT662ixltkQ26AVUDJ2KnOr9Z5tlrM83c90JBG29Eqz+mK0sY4ky6yxSrNrtL55siuySiM - YgtfEwCAl/7b+XQaf4otZLPTpMEYZYVie14CEIFsNxEyRhNZOhazEVTkGF1v/dYA1xjwDdzSMyjp - 4CMMHNhTC0xa7t9PuQHLNsrOv2utnQDSOWLZ5e9dPx6Rw9mnpcoH2sU/qKI0zsS6CCgjuc5TZPKi - Rw8JwGPfR3sRUfhAjeeC6Rv2v8sHNTE+wojNj1UJJpZ2Mj+RLsQKjSyNjZM6hZKqRj0yx+5lqw1N - gGQS+bWZv2kPsY2r/kd+BJRCz6gLH1AbdRl4XAvYnei/1s4V94ZFxPDDKCzYYOieQWMpWzscjoj7 - yNgUpXEVBh/McD2lLxb5cpnJfL3ZiOSQ/AYAAP//AwBh+pUaSwMAAA== - headers: - CF-RAY: - - 9c1afa59ad603c7d-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 22 Jan 2026 00:36:35 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=PlzuDRlMMRbycTVjQsnyVm0JzX1xPYSyfWiyV5.ss4o-1769042195-1.0.1.1-GskZbYzH2xdkjFqL_95fGPrEWYDuIHME.G7z1.ZxpgFhV2FYfEYQX7YnLTDCsB4X57NZ52umXVrUpyC8I3FJEa4mT_NvYMPW8qHYS6VMdNA; - path=/; expires=Thu, 22-Jan-26 01:06:35 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=MkSLqw_rIIh52wU3OUETJXSQhjelNm048divbvks86A-1769042195907-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '345' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '368' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999997' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_a0a74895c71242c28a1312c77cc466eb - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_auto_openai.yaml b/py/src/braintrust/wrappers/cassettes/test_auto_openai.yaml deleted file mode 100644 index fa8f6cca9..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_auto_openai.yaml +++ /dev/null @@ -1,112 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Say hi"}],"model":"gpt-4o-mini"}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate, zstd - Connection: - - keep-alive - Content-Length: - - '71' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - PatchedOpenAI/Python 2.15.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - 'false' - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Raw-Response: - - 'true' - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA4xSTY/TMBC951cMPjcoXZpu2wsX0O7CgRsSQqvItSeJWcdj7AlQVv3vyEnbpHxI - XHKYN+/lved5zgCE0WIHQrWSVedt/qZQ/tVdQbX8+HD38/2H9VPfvftafnrb1xsnFolB+y+o+Mx6 - qajzFtnQCVYBJWNSXd6ut8VquS7KAehIo020xnO+orwzzuQ3xc0qL27z5ebEbskojGIHnzMAgOfh - m3w6jT/EDorFedJhjLJBsbssAYhANk2EjNFElo7FYgIVOUY3WL83wC0GfAH39B2UdPAAIwcO1AOT - lofXc27Auo8y+Xe9tTNAOkcsU/7B9eMJOV58Wmp8oH38jSpq40xsq4AykkueIpMXA3rMAB6HPvqr - iMIH6jxXTE84/G47qonpESZseapKMLG0s/mZdCVWaWRpbJzVKZRULeqJOXUve21oBmSzyH+a+Zv2 - GNu45n/kJ0Ap9Iy68gG1UdeBp7WA6UT/tXapeDAsIoZvRmHFBkN6Bo217O14OCIeImNX1cY1GHww - 4/XUvlKrclPuy/1WieyY/QIAAP//AwCD9W0XSwMAAA== - headers: - CF-RAY: - - 9c1aebf06c2bdf9a-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 22 Jan 2026 00:26:46 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=3BmepJS69LHQgVvyFWNjigRlQzFvRa9D27MfU_V1GW0-1769041606-1.0.1.1-DoMWqhIcGyYxaxjFWjcV4tR47V69QGDpBRdKxV_H6ljJ.oOmgsyMCJ26sIf6OFlSFbBKcDcWPXjN8qq.t3Ug7JVypduDXLaQCkFHFsBEA7o; - path=/; expires=Thu, 22-Jan-26 00:56:46 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=bOlyGVzoZ0UIzrB2Mfoafdr89NZcKOJbtyu6_aNBhmc-1769041606331-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '510' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '736' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_7a9c72bf01b245829c035470f37565dc - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_auto_pydantic_ai.yaml b/py/src/braintrust/wrappers/cassettes/test_auto_pydantic_ai.yaml deleted file mode 100644 index 32c50c9d2..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_auto_pydantic_ai.yaml +++ /dev/null @@ -1,112 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Say hi"}],"model":"gpt-4o-mini","max_completion_tokens":100,"stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate, zstd - Connection: - - keep-alive - Content-Length: - - '114' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.44.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Raw-Response: - - 'true' - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFLLbtswELzrK7Y8W4Vsq4ntSw8tmvTUBuihDwQCQ64kJhSXIFdtjcD/ - XlCyLbkPoBcddnZGM8N9zgCE0WIHQrWSVedt/rbQhW8/lF/iHX69a8q9evOx+fzp6fGdu7kRi8Sg - h0dUfGK9VNR5i2zIjbAKKBmT6vL6aluUq/X61QB0pNEmWuM5LynvjDP5qliVeXGdLzdHdktGYRQ7 - +JYBADwP3+TTafwpdlAsTpMOY5QNit15CUAEsmkiZIwmsnQsFhOoyDG6wfqtAW4x4Au4pR+gpIP3 - MHJgTz0wabl/PecGrPsok3/XWzsDpHPEMuUfXN8fkcPZp6XGB3qIv1FFbZyJbRVQRnLJU2TyYkAP - GcD90Ed/EVH4QJ3niukJh99tRzUxPcKELY9VCSaWdjY/kS7EKo0sjY2zOoWSqkU9MafuZa8NzYBs - FvlPM3/THmMb1/yP/AQohZ5RVz6gNuoy8LQWMJ3ov9bOFQ+GRcTw3Sis2GBIz6Cxlr0dD0fEfWTs - qtq4BoMPZrye2ler7XpdyO3VZiOyQ/YLAAD//wMAbBhxq0sDAAA= - headers: - CF-RAY: - - 9c1afdbedfc4cf0a-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 22 Jan 2026 00:38:55 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=.v4HHKHusX6vziKsYW5cyVzZRrAsCxp4XT463GaX0yQ-1769042335-1.0.1.1-InjFtjx7UOJ8ivwZeShYpDg8mc4QGt.4kpoe9GlkrPwH7LBqBZxH.e.oLUSXSkyh_t0ETNUXh6C5G5zGSAXLYT6oNyc6cef0jwB2ADi_S.w; - path=/; expires=Thu, 22-Jan-26 01:08:55 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=bHlkcNsEuGGe.AQuXN6zbPWK8MJ2dKBjLFcSS263aVQ-1769042335390-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '395' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '412' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999997' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_0cc555f0b9354a85a3b0f965716d99de - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_basic_completion[stream].yaml b/py/src/braintrust/wrappers/cassettes/test_basic_completion[stream].yaml deleted file mode 100644 index 4e47ddff8..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_basic_completion[stream].yaml +++ /dev/null @@ -1,68 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "What is the capital of France?"}], "role": - "user"}], "generationConfig": {"maxOutputTokens": 100}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '133' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:streamGenerateContent?alt=sse - response: - body: - string: "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"The\"}],\"role\": - \"model\"}}],\"usageMetadata\": {\"promptTokenCount\": 8,\"totalTokenCount\": - 8,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 8}]},\"modelVersion\": - \"gemini-2.0-flash-001\",\"responseId\": \"_qTiaLjwK6vpgbUP2uvA-QU\"}\r\n\r\ndata: - {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" capital of France\"}],\"role\": - \"model\"}}],\"usageMetadata\": {\"promptTokenCount\": 8,\"totalTokenCount\": - 8,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 8}]},\"modelVersion\": - \"gemini-2.0-flash-001\",\"responseId\": \"_qTiaLjwK6vpgbUP2uvA-QU\"}\r\n\r\ndata: - {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" is Paris.\\n\"}],\"role\": - \"model\"},\"finishReason\": \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": - 7,\"candidatesTokenCount\": 8,\"totalTokenCount\": 15,\"promptTokensDetails\": - [{\"modality\": \"TEXT\",\"tokenCount\": 7}],\"candidatesTokensDetails\": - [{\"modality\": \"TEXT\",\"tokenCount\": 8}]},\"modelVersion\": \"gemini-2.0-flash-001\",\"responseId\": - \"_qTiaLjwK6vpgbUP2uvA-QU\"}\r\n\r\n" - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Disposition: - - attachment - Content-Type: - - text/event-stream - Date: - - Sun, 05 Oct 2025 17:03:58 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=391 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_basic_completion[sync].yaml b/py/src/braintrust/wrappers/cassettes/test_basic_completion[sync].yaml deleted file mode 100644 index de86b9765..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_basic_completion[sync].yaml +++ /dev/null @@ -1,61 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "What is the capital of France?"}], "role": - "user"}], "generationConfig": {"maxOutputTokens": 100}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '133' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61RTU/DMAy991dEOa9T1jFWcYMNJhCICSqEBAiZ1uuitUlJsvEx7b+TtmuXwpUc - Isvv2c9+3nqE0BhEwhMwqOkJebIZQrbVX2JSGBTGAk3KJgtQ5sCt39aJLcXgZ1lEoyWSGApuICNy - QS4UiBgJ12QOiuv+s6BO3a6NX3oHNSUzLFvlMsGsoe8aAl1wwfXyDkFLUdLuo9s5bVHYpNcyLZR8 - Kwf2WZ8Nw+NwfDRkwyAYjFkwCr1GuhKlaw0p3qAB6wi0e1PbIi9MJFcoJnJdOTKuVRz/OnC4h420 - y3eQwaj3p6meWkmeubY6jtvdIePmq7L0/DGijj+mM1Pjj+fY+HvCf9IKu1re/ir1oR5QaV5fJMXc - 3sgP+sxfZKCXPmODqilVqAspNF4mJe/1PeJwNZudQf6dm9WcbSbTj1NGvZ33A7z5p7+oAgAA - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Sun, 05 Oct 2025 17:03:58 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=390 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_basic_completion_async[async].yaml b/py/src/braintrust/wrappers/cassettes/test_basic_completion_async[async].yaml deleted file mode 100644 index 645a276e7..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_basic_completion_async[async].yaml +++ /dev/null @@ -1,61 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "What is the capital of France?"}], "role": - "user"}], "generationConfig": {"maxOutputTokens": 100}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '133' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61RUUvDMBB+768IeV5H2rG1+iZTQdjY0CLCFDnXaxfWJjXJxDH2303bdUv11TyE - 477v7rv77uARQtcgUp6CQU2vycpmCDk0f41JYVAYC3Qpm6xAmQu3fQcnthSD33URTTZI1lBxAwWR - GblXINZIuCZLUFwPXwV16o7n+G1wUVOywLpVKVMsOvqxI9CMC643jwhaipr2lCyW9IzCVz6TeaXk - Rz2wz4ZsHMfhKIhHQRRfsWAShV4n3YjSnYYc52jAOgLnvaltUVYmkVsUU7lrHIlaFce/HhyfYCPt - 8j0kGA/+NNW3VpIXrq2O43Z3KLjZN5bevSTU8cf0Zur88Rwbf0/4T1pxX8s7XaU91DMqzduL5Fja - G/nhkPlZAXrjMxY0TalCXUmh8SGtee+ThMOinE8/J/vSbJcRwmx/w6h39H4AjvRKC6gCAAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Sun, 05 Oct 2025 17:03:59 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=321 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_basic_completion_async[async_stream].yaml b/py/src/braintrust/wrappers/cassettes/test_basic_completion_async[async_stream].yaml deleted file mode 100644 index 3dd5a250f..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_basic_completion_async[async_stream].yaml +++ /dev/null @@ -1,68 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "What is the capital of France?"}], "role": - "user"}], "generationConfig": {"maxOutputTokens": 100}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '133' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:streamGenerateContent?alt=sse - response: - body: - string: "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"The\"}],\"role\": - \"model\"}}],\"usageMetadata\": {\"promptTokenCount\": 8,\"totalTokenCount\": - 8,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 8}]},\"modelVersion\": - \"gemini-2.0-flash-001\",\"responseId\": \"_6TiaLjOJ7yBn9kPy5aNyQg\"}\r\n\r\ndata: - {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" capital of France\"}],\"role\": - \"model\"}}],\"usageMetadata\": {\"promptTokenCount\": 8,\"totalTokenCount\": - 8,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 8}]},\"modelVersion\": - \"gemini-2.0-flash-001\",\"responseId\": \"_6TiaLjOJ7yBn9kPy5aNyQg\"}\r\n\r\ndata: - {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" is Paris.\\n\"}],\"role\": - \"model\"},\"finishReason\": \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": - 7,\"candidatesTokenCount\": 8,\"totalTokenCount\": 15,\"promptTokensDetails\": - [{\"modality\": \"TEXT\",\"tokenCount\": 7}],\"candidatesTokensDetails\": - [{\"modality\": \"TEXT\",\"tokenCount\": 8}]},\"modelVersion\": \"gemini-2.0-flash-001\",\"responseId\": - \"_6TiaLjOJ7yBn9kPy5aNyQg\"}\r\n\r\n" - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Disposition: - - attachment - Content-Type: - - text/event-stream - Date: - - Sun, 05 Oct 2025 17:03:59 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=393 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_braintrust_tracing_processor_concurrency_bug.yaml b/py/src/braintrust/wrappers/cassettes/test_braintrust_tracing_processor_concurrency_bug.yaml deleted file mode 100644 index 76fadf73b..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_braintrust_tracing_processor_concurrency_bug.yaml +++ /dev/null @@ -1,214 +0,0 @@ -interactions: -- request: - body: '{"include":[],"input":[{"content":"What''s your name?","role":"user"}],"instructions":"You - are agent A. Just respond with ''A'' and nothing else.","model":"gpt-4o-mini","tools":[]}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '177' - Content-Type: - - application/json - Cookie: - - __cf_bm=IwSSJ.RHOyrDHy71t190C0u4EL9HMgUY2jiVoTE3Rx0-1768424037-1.0.1.1-ZID4mvxCwpZVRzFS1fLdN1Y2IWkkn_wazHoPQBolLYHzMoZNRkTFDL0fqX4m.0FY97.b95rhiBzBDf3ubnonNwcnYBcTqnrX4_OgE7Fq6Lw; - _cfuvid=RePkKlnxLbAHj0ymuEQEUhV2_qf3Ejhb0yEUFttOP24-1768424037764-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - Agents/Python 0.6.5 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3RUwW6jMBC95yssX3ppKkJoArn1un+wqlZoMAPx1thee5xtVOXfV5hAoJvcYN7M - 88x7Hn+tGOOy5gfGHXpbJoXY5AXm2GxRFEmaJLtilyfp7hWLTOSb4rXCfAtV2iS7bfZaZQV/7ilM - 9RsFjTRGexziwiEQ1iX02Ga/y7M0S7b7iHkCCr6vEaazCgnroagC8dE6E3TfVwPK4xCWSknd8gP7 - WjHGGLdwRtfX13hCZSw6vmLsMhw8Un47Oo8oOmf6Sh2UioHG4Z+AWpxLixoUnfmBJS9JxKQeycoa - CaTy80qpPbkgSBodZ/lpAgOHDFrUxN5e2I/giQ2q1OyvpCN7entioGumDR2lbhkqjy/D6B18liaQ - DVSS+UC9OKoHyRhVClDLJjpTo+pPby2tM7PupJbrNEmzdbJfb/KrR5GXH9h7lG8QcbK/8+1j93fb - bZP37ueZKHLM9vtCIIhicDmy0Nli5EHvoZ0Bj2yOoDCaUN+amje2oB1FwU+aqmMCaG0IRvnffy1A - ZVrrTHUHiUQHxt/4FL1cv6ZE7oyKh4P30hNoGpL7xJjELThQCtXSFnJhuLHWoUct8M6lsg5P0gRf - jvtSRhsmR60znaVSgDhi+YHnh5jDXkBp9DzDIXijF8uCTWMczZJ6a0LXgRu5p93x0CCdS1n3xI3E - xaZ4dCcpsCQ57l4DQQ2mcE/G4VwBws6iAwoxvLkOfxX/2lljXAe3/5npMW+Q/NrxCV1lvIxS8g5r - Gbrbzg8mHI0Ug2uBDJ+A2x3gZGw5uxnJFLTzHl3QAq7C8lp6qNT4QIV4w6cBpF7s6zZ5/j8+ezqm - MaOB9a0wWYz6/RlI78Xv0U7mP2ImQ6Bm/aaTgsEvze6QoAaCnv6yuvwDAAD//wMABfpPzy4GAAA= - headers: - CF-RAY: - - 9be0069c9e0fa3be-IAD - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 14 Jan 2026 20:53:58 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '458' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '463' - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999950' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_2ed2447bbb924a109ffff829941e504f - status: - code: 200 - message: OK -- request: - body: '{"include":[],"input":[{"content":"Who are you?","role":"user"}],"instructions":"You - are agent B. Just respond with ''B'' and nothing else.","model":"gpt-4o-mini","tools":[]}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '172' - Content-Type: - - application/json - Cookie: - - __cf_bm=IwSSJ.RHOyrDHy71t190C0u4EL9HMgUY2jiVoTE3Rx0-1768424037-1.0.1.1-ZID4mvxCwpZVRzFS1fLdN1Y2IWkkn_wazHoPQBolLYHzMoZNRkTFDL0fqX4m.0FY97.b95rhiBzBDf3ubnonNwcnYBcTqnrX4_OgE7Fq6Lw; - _cfuvid=RePkKlnxLbAHj0ymuEQEUhV2_qf3Ejhb0yEUFttOP24-1768424037764-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - Agents/Python 0.6.5 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3RUwW6jMBC95yssX3ppKiCEkhx73D9YVSs0mCHx1thee5xtVOXfV5hAoJvcYN7M - 88x7Hn+tGOOy4XvGHXpbJfkG2rbcClG2bVZuk6TYFWWSFVssRVKmuxyyAhpIcZNsm3xXpvy5pzD1 - bxQ00hjtcYgLh0DYVNBj6WtR5lmebF4j5gko+L5GmM4qJGyGohrEx8GZoPu+WlAeh7BUSuoD37Ov - FWOMcQtndH19gydUxqLjK8Yuw8Ej5bejy4iic6av1EGpGGgd/gmoxbmyqEHRme9Z8pJETOqRrGqQ - QCo/r5TakwuCpNFxlp8mMHDI4ICa2NsL+xE8sUGVhv2VdGRPb08MdMO0oaPUB4bK48swegeflQlk - A1VkPlAvjupBMkZVAtSyic40qPrTD5bWuVl3Ust1lmT5Onldp+XVo8jL9+w9yjeIONnf+cNj94tt - kuW9+7t0lxRNm9Yix7qAOjJHFjpbjDzoPRzwBjyyOYLCaEJ9a2re2IJ2FAU/aaqOCaC1IRjlf/+1 - AJU5WGfqO0gk2jP+xqfo5fo1JXJnVDwcvJeeQNOQ3CfGJG7BgVKolraQC8ONtQ49aoF3LpV1eJIm - +GrclyraMDlqneksVQLEEasPPD/EHPYCSqPnGQ7BG71YFmxb42iW1FsTug7cyD3tjocW6VzJpidu - JS42xaM7SYEVyXH3WghqMIV7Mg7nChB2Fh1QiOH0OvxV/GtnrXEd3P5npse8QfJrxyd0tfEySsk7 - bGTobjs/mHA0UgyuBTJ8Am53gJOx1exmJFPQznt0QQu4Cssb6aFW4wMV4g2fBpB6sa+b5Pn/+Ozp - mMaMBja3wmQx6vdnILsXv0c7mf+ImQyBmvWbTQoGvzS7Q4IGCHr6y+ryDwAA//8DAJHmPlYuBgAA - headers: - CF-RAY: - - 9be0069c9e92e637-IAD - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 14 Jan 2026 20:53:58 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '594' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '596' - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999950' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_ea321d2a288b42beb45e94f44b291ab6 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_braintrust_tracing_processor_current_span_detection.yaml b/py/src/braintrust/wrappers/cassettes/test_braintrust_tracing_processor_current_span_detection.yaml deleted file mode 100644 index fb433203b..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_braintrust_tracing_processor_current_span_detection.yaml +++ /dev/null @@ -1,111 +0,0 @@ -interactions: -- request: - body: '{"include":[],"input":[{"content":"What is 2+2? Just the number.","role":"user"}],"instructions":"You - are a helpful assistant. Be very concise.","model":"gpt-4o-mini","tools":[]}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '178' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - Agents/Python 0.6.5 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3xUy47bMAy85ysEnTcL23Gcx7F/USwKg5HprLqyqEpUsEGRfy8sx47dZnuz+RiS - M6R+r4SQupFHIT0GV2cNVACbfVGp6rDNIMuqQ7XPimpb4Lbc54ctNBvY53leFVgesoOSLz0EnX6i - 4hGGbMDBrjwCY1ND78t31b4symyzS77AwDH0OYo6Z5CxGZJOoD7OnqLt+2rBBBzM2hhtz/Iofq+E - EEI6uKLv8xu8oCGHXq6EuA2FR8inpdF76jNtNCYZWo+/Ilp1rR1aMHyVR5G9Zsmn7QhWN8igTZhn - ahvYR8WabJrlO0UBHgWIdzSujUZACDowWH4V31Bc0F+FIqt0wNdh3g4+a4rsItdMH2gX+L2TiUyt - wCwrd9Sg6UueHa9LWnfa6nWRFeU6263z/V2YhCuP4i1xNjA3ad6F838k32OV9ZLvt1lVtgpxVzSb - XV4m5ITCV4cJB0OAMz4cX2mbnIoso300NW9sATuSgp88ZacAsJYYRs7ffiychs7O0+mJJwEdhSzl - ZL3dv6ZA6cmk4pNsQ3AfmIKkAw/GoFnKwj4Oa+o8BrQKn2yS83jRFEM9HkmdZJgUdZ46x7UC9Y71 - B16/9HnsCdRk5xEeIZBdXAi2LXmeBfXSxK4DP2JPBxOgRb7WuumBW42L8wjoL1phzXo8uBaiGUSR - gcnjnAHGzqEHjsmc34e/k3/vrCXfweN/JnqKGyi/d3xBf6KgE5Wyw0bH7nHogwjvpNWgWmSSk+Ox - A5LJ1bPNyCajm/foo1VwJ1Y2OsDJjK9STBs+DaDt4l43xcu/9tl7MY2ZBGweidli1L+fgeKZ/Rns - JP5XyEwMZtZvOTEYw1LsDhkaYOjhb6vbHwAAAP//AwCbn65uIwYAAA== - headers: - CF-RAY: - - 9be006980c67e60f-IAD - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 14 Jan 2026 20:53:57 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=IwSSJ.RHOyrDHy71t190C0u4EL9HMgUY2jiVoTE3Rx0-1768424037-1.0.1.1-ZID4mvxCwpZVRzFS1fLdN1Y2IWkkn_wazHoPQBolLYHzMoZNRkTFDL0fqX4m.0FY97.b95rhiBzBDf3ubnonNwcnYBcTqnrX4_OgE7Fq6Lw; - path=/; expires=Wed, 14-Jan-26 21:23:57 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=RePkKlnxLbAHj0ymuEQEUhV2_qf3Ejhb0yEUFttOP24-1768424037764-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '560' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '565' - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999950' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_d8b831ee46ec9bc399abd66e9591fa2f - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_call_3.yaml b/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_call_3.yaml deleted file mode 100644 index 3c1974fca..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_call_3.yaml +++ /dev/null @@ -1,152 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 5."}],"model":"gpt-4o","max_completion_tokens":100,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '160' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"AfRM5x2jSIPKFT"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"fWhRKnLl1XL1Asx"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ZFHDosUggutGCRq"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"17JtvC7OQDgGhMM"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"iIp51vChbkTv67v"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Nz9X8J55STM7HKM"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ieRE2s31JOWT9v0"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"V4Mnvf94sP9r3eG"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"0VfhBJw1aA89ibp"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"uDoSaOF8V7ptxeO"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"4"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"pQVE4CprAYIn6up"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"0R3cAW32W4kBTkE"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"8uvUQ14zmT1TuwT"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"FCBUjzWcpg61ymJ"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"iRMyskpOEM"} - - - data: {"id":"chatcmpl-CoyYOqlEPe5d5ZDp8ke9WKiuDZwVD","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[],"usage":{"prompt_tokens":15,"completion_tokens":13,"total_tokens":28,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"bEShcED16fgY7iB"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b1224b51fd9c3a8-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:24 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '162' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '176' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '10000' - x-ratelimit-limit-tokens: - - '30000000' - x-ratelimit-remaining-requests: - - '9999' - x-ratelimit-remaining-tokens: - - '29999993' - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_11c7b6e0df7c43119f8667039f15f1ae - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_call_4.yaml b/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_call_4.yaml deleted file mode 100644 index 09ecba265..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_call_4.yaml +++ /dev/null @@ -1,155 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 5."}],"model":"gpt-4o","max_completion_tokens":100,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '160' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"1IQJweBejE0jiq"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"pr5bD6rFTdUVY14"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Za4X0eSTFd2tyv9"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"7eqqbRb2EIUxEE3"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"RWYQBkCmTAMWyCN"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"QHUv9PRoRpFG4MM"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"PRErQ0TA40ETgvg"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"bm8kCsDS60TLD6w"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"4gxtIXXWpxfwfJD"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"5vbACFvyYQv3U8R"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"4"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"WJ8BMmx3WByBLRI"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"D4HhV3WPsW2zWrt"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"jhr1P0FDqIDhhYB"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"E5SO6ZkU39JuIuy"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"QlzOuL58KwnUT2n"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"DKc4NCr9Aw"} - - - data: {"id":"chatcmpl-CoyYOlquYO6yEiF3DKuGWpHrQcO26","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[],"usage":{"prompt_tokens":15,"completion_tokens":14,"total_tokens":29,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"GcqbmusHh2PG4rj"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b1224b77d762ee7-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:24 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '99' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '113' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '10000' - x-ratelimit-limit-tokens: - - '30000000' - x-ratelimit-remaining-requests: - - '9999' - x-ratelimit-remaining-tokens: - - '29999993' - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_162d8d3020134d778b022cfa02f50c0a - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_early_break_call_5.yaml b/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_early_break_call_5.yaml deleted file mode 100644 index 66a22c572..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_early_break_call_5.yaml +++ /dev/null @@ -1,180 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 5."}],"model":"gpt-4o","max_completion_tokens":100,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '160' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Cvh6mhywE6Bodo"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"Sure"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"mlWC6jeJjq2r"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"eM8fd4r4SUyxfvW"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - here"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"JCgwmcMehDI"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - you"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"or87db3NSRul"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - go"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"0D8iadE5vCwmP"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":":"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"R8AnkpgQtC41bar"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Gfl0xB9sDIqQzxK"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"2TpJG3Ml6wF9iJw"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"MaVHLitsvCCOrVM"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"xkxy1Q6ikbybFVD"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Q73dFpKN8pgf2UL"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ZStRsKfZ5PRjQrJ"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"tX4eRUREFaFcTvn"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"YrZInzPpxsIHRyy"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"CwSbv4rXd70J5hq"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"1SqXllkSFEGFtuO"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"4"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"9dsFS4URVYEoOIP"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"yY8i7OmxYrKXaF1"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"SHxoSByU0RHTUZU"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"EsLnSnYacJno2aH"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"qOkCFSRzrVpHtI1"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"0lrL0230iH"} - - - data: {"id":"chatcmpl-CoyYOwxrRGfBDZv4IGsibzttWzEgK","object":"chat.completion.chunk","created":1766265204,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[],"usage":{"prompt_tokens":15,"completion_tokens":21,"total_tokens":36,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"eUVJ0dEZbIFeI7e"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b1224b9981be66c-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:24 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '112' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '128' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '10000' - x-ratelimit-limit-tokens: - - '30000000' - x-ratelimit-remaining-requests: - - '9999' - x-ratelimit-remaining-tokens: - - '29999993' - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_cfdb75052cb14da9a0efc6e586f4cb9e - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_no_duplication.yaml b/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_no_duplication.yaml deleted file mode 100644 index 86b9f6dc1..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_no_duplication.yaml +++ /dev/null @@ -1,153 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 5, separated by - commas."}],"model":"gpt-4o","max_completion_tokens":100,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '181' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ZybMV0ahzLorcX"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"2GTvzNx3o9sStl8"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"WKjzDz5EOrYePo1"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"NiZIrTa3CTcMAWD"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"f0rwJzNNBb3Irgc"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"LIluWqpB1hFepqt"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"fAUwJ9cCbfscabK"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"aqJX0oJYlZPtRU6"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"WQkw9dIMfshPhpk"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"1zYHelUlnknT3XZ"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"4"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Cdq9lzkgcv4aPNU"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"sV1lD2RNwzdp0Kx"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"26AvvC4eQRJEZX3"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Gk9Fc7UB6yaGU6o"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"dvZJrclN8G"} - - - data: {"id":"chatcmpl-CoyYP3XVgISP9Q1RKuBcK25uYYfpd","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[],"usage":{"prompt_tokens":19,"completion_tokens":13,"total_tokens":32,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"GWSVgnn4VcJYnMn"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b1224bc7e6ad183-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:25 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '129' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '146' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '10000' - x-ratelimit-limit-tokens: - - '30000000' - x-ratelimit-remaining-requests: - - '9999' - x-ratelimit-remaining-tokens: - - '29999988' - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_6fdb88fd42554b3097f75a97fe69c383 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_no_duplication_comprehensive.yaml b/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_no_duplication_comprehensive.yaml deleted file mode 100644 index 59c6621aa..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_direct_api_streaming_no_duplication_comprehensive.yaml +++ /dev/null @@ -1,173 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 5."}],"model":"gpt-4o","max_completion_tokens":100,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '160' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"c9xrM6OdDP8jwC"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"Sure"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"732E7e5mpKuG"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"!"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"yQpRQUUWhgPVoON"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - Here"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"WAxL7wu4sni"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - you"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"BVNQX2UGxVrg"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - go"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"vzbkHK5myMtsU"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":":\n\n"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"C4jT6ZXS1Qz"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"FtVHmz4I9wCNhdv"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"igPATFCF0O7vQJ8"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"RTIjbzPqUFMHa6x"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"YO2uHvMw637keJC"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"vFlzXPyj17xKzKV"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"VBTuSUjivFfrjw1"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"FvoatS6RiNuGi4z"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"l5L8JDbmpWwasDI"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"bZBuKSY2n4bKn1r"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"4"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"997Ox8leP6UJnxX"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"I0MDr56dihVZAJz"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"0rLU1RyZuaSgz2y"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"VC04yDed3ImP2hQ"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"CsWeDAgKsz"} - - - data: {"id":"chatcmpl-CoyYP6Zb8k1p7BZSZX6hNr3YehXbN","object":"chat.completion.chunk","created":1766265205,"model":"gpt-4o-2024-08-06","service_tier":"default","system_fingerprint":"fp_e413f45763","choices":[],"usage":{"prompt_tokens":15,"completion_tokens":19,"total_tokens":34,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"P7IgFwbPEqq4aZ9"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b1224bedbf0d938-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:25 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '125' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '141' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '10000' - x-ratelimit-limit-tokens: - - '30000000' - x-ratelimit-remaining-requests: - - '9999' - x-ratelimit-remaining-tokens: - - '29999993' - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_4f3d0eec7d744f5bb08533b6b473ebbd - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_direct_model_request.yaml b/py/src/braintrust/wrappers/cassettes/test_direct_model_request.yaml deleted file mode 100644 index a5c794049..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_direct_model_request.yaml +++ /dev/null @@ -1,108 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 2+2? Answer with just the - number."}],"model":"gpt-4o-mini","stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '121' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJPb9swDMXv/hQCz/XgGGma5dY/hwHtYZdhHYbCUCXaUSeLqkQHy4p8 - 90FKGjtbC/TiA3981Hs0XwohwGhYCVBryar3trym7Y/b+/bb/XKz+XL1/epPdb293Hy9uXuWW4Kz - pKDHJ1T8qvqkqPcW2ZDbYxVQMqaps4vFol6c11WVQU8abZJ1nss5lb1xpqyrel5WF+VseVCvySiM - sBI/CyGEeMnf5NNp/A0rkWflSo8xyg5hdWwSAgLZVAEZo4ksHcPZCBU5Rpetz6f1gO0QZfLmBmsn - QDpHLFO27OjhQHZHD5Y6H+gx/iOF1jgT101AGcml9yKTh0x3hRAPOetwYh98oN5zw/QL83P1ISqM - Gx7h7MCYWNqJ5rV+MqzRyNLYOFkVKKnWqEfluFc5aEMTUEwi/+/lrdn72MZ1Hxk/AqXQM+rGB9RG - neYd2wKm83uv7bjibBgiho1R2LDBkH6DxlYOdn8UELeRsW9a4zoMPpj9ZbS+QVx8VjW28yUUu+Iv - AAAA//8DAGzyyx0nAwAA - headers: - CF-RAY: - - 9b12249eb844cb86-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:20 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '215' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '231' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999985' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_bb6ba9cfa6d14b23972cb655212d4423 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_direct_model_request_stream.yaml b/py/src/braintrust/wrappers/cassettes/test_direct_model_request_stream.yaml deleted file mode 100644 index bfaf7c631..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_direct_model_request_stream.yaml +++ /dev/null @@ -1,135 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 3"}],"model":"gpt-4o-mini","stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '136' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYNSCz3qcm9wC9cHlROUUKcFtXi","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"MPeP4cTzj"} - - - data: {"id":"chatcmpl-CoyYNSCz3qcm9wC9cHlROUUKcFtXi","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Bs27rTjKBx"} - - - data: {"id":"chatcmpl-CoyYNSCz3qcm9wC9cHlROUUKcFtXi","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"X84rqwUSyS"} - - - data: {"id":"chatcmpl-CoyYNSCz3qcm9wC9cHlROUUKcFtXi","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"8N28G51ySR"} - - - data: {"id":"chatcmpl-CoyYNSCz3qcm9wC9cHlROUUKcFtXi","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"2g8tmbh4LX"} - - - data: {"id":"chatcmpl-CoyYNSCz3qcm9wC9cHlROUUKcFtXi","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"wOL2L3mpTZ"} - - - data: {"id":"chatcmpl-CoyYNSCz3qcm9wC9cHlROUUKcFtXi","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"pbsyokiCs4"} - - - data: {"id":"chatcmpl-CoyYNSCz3qcm9wC9cHlROUUKcFtXi","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"e3bkAGq7YZ"} - - - data: {"id":"chatcmpl-CoyYNSCz3qcm9wC9cHlROUUKcFtXi","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"aSlrtmsM67"} - - - data: {"id":"chatcmpl-CoyYNSCz3qcm9wC9cHlROUUKcFtXi","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"S4tkp"} - - - data: {"id":"chatcmpl-CoyYNSCz3qcm9wC9cHlROUUKcFtXi","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":8,"total_tokens":22,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"EbbD8S3NFhz"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b1224afa86a2f02-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:23 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '139' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '151' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_f350c8c0bd7e45cd8820c4ad923f3ed7 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_direct_model_request_stream_complete_output.yaml b/py/src/braintrust/wrappers/cassettes/test_direct_model_request_stream_complete_output.yaml deleted file mode 100644 index 521f76025..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_direct_model_request_stream_complete_output.yaml +++ /dev/null @@ -1,132 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Say exactly: 1, 2, 3"}],"model":"gpt-4o-mini","stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '139' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYNH7Wi5k0CKXtkOCr79LW8yB5k","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"HvUSOrR1X"} - - - data: {"id":"chatcmpl-CoyYNH7Wi5k0CKXtkOCr79LW8yB5k","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"3XRNwrHSZ4"} - - - data: {"id":"chatcmpl-CoyYNH7Wi5k0CKXtkOCr79LW8yB5k","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"g4LuFspFjU"} - - - data: {"id":"chatcmpl-CoyYNH7Wi5k0CKXtkOCr79LW8yB5k","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"iJzlYW6sHx"} - - - data: {"id":"chatcmpl-CoyYNH7Wi5k0CKXtkOCr79LW8yB5k","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"u54Cu0s3Ah"} - - - data: {"id":"chatcmpl-CoyYNH7Wi5k0CKXtkOCr79LW8yB5k","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"N4TsEWOfAa"} - - - data: {"id":"chatcmpl-CoyYNH7Wi5k0CKXtkOCr79LW8yB5k","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"P0Yrb0mxLr"} - - - data: {"id":"chatcmpl-CoyYNH7Wi5k0CKXtkOCr79LW8yB5k","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"oRPi8xgdex"} - - - data: {"id":"chatcmpl-CoyYNH7Wi5k0CKXtkOCr79LW8yB5k","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"v0uti"} - - - data: {"id":"chatcmpl-CoyYNH7Wi5k0CKXtkOCr79LW8yB5k","object":"chat.completion.chunk","created":1766265203,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[],"usage":{"prompt_tokens":18,"completion_tokens":7,"total_tokens":25,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"ucDxMBoVkf5"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b1224b27c7c7650-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:23 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '127' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '144' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_a705aa58e1074dc69f92a9b61c0d25f4 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_direct_model_request_stream_sync.yaml b/py/src/braintrust/wrappers/cassettes/test_direct_model_request_stream_sync.yaml deleted file mode 100644 index 36b6250d8..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_direct_model_request_stream_sync.yaml +++ /dev/null @@ -1,135 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 3"}],"model":"gpt-4o-mini","stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '136' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYZrJy9JYFY664IA2WgzVOsQSmj","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"n4wIfDywj"} - - - data: {"id":"chatcmpl-CoyYZrJy9JYFY664IA2WgzVOsQSmj","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"M7nBs8tJ4w"} - - - data: {"id":"chatcmpl-CoyYZrJy9JYFY664IA2WgzVOsQSmj","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"3AKnil79q5"} - - - data: {"id":"chatcmpl-CoyYZrJy9JYFY664IA2WgzVOsQSmj","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"tj0YRKsPzd"} - - - data: {"id":"chatcmpl-CoyYZrJy9JYFY664IA2WgzVOsQSmj","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"3G9IJGTD7B"} - - - data: {"id":"chatcmpl-CoyYZrJy9JYFY664IA2WgzVOsQSmj","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ury0XoZd21"} - - - data: {"id":"chatcmpl-CoyYZrJy9JYFY664IA2WgzVOsQSmj","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"mJX6hpQnaM"} - - - data: {"id":"chatcmpl-CoyYZrJy9JYFY664IA2WgzVOsQSmj","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"qhlqTCCpyt"} - - - data: {"id":"chatcmpl-CoyYZrJy9JYFY664IA2WgzVOsQSmj","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"2JL0YHl8QJ"} - - - data: {"id":"chatcmpl-CoyYZrJy9JYFY664IA2WgzVOsQSmj","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"DgeyW"} - - - data: {"id":"chatcmpl-CoyYZrJy9JYFY664IA2WgzVOsQSmj","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":8,"total_tokens":22,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"pdj6Hh5uLUK"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b1224f9cc5cdbe5-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:35 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '159' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '171' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_fac92d6c619a4d7e94154752dd20d282 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_direct_model_request_sync.yaml b/py/src/braintrust/wrappers/cassettes/test_direct_model_request_sync.yaml deleted file mode 100644 index b66d2c659..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_direct_model_request_sync.yaml +++ /dev/null @@ -1,108 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 2+2? Answer with just the - number."}],"model":"gpt-4o-mini","stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '121' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJNj9MwEIbv+RXWnBvUhtLd7Y0PCSGQENwQWkWuPUkGHI9lT1ZbVv3v - yOlH0gUkLjnMM+/4fSfzVCgFZGGrwHRaTB9c+Zb33z49fPja7j7ufnXODO8e929e0+eX7++aL7DI - Ct79QCNn1QvDfXAoxP6ITUQtmKeubjabavOqWq5G0LNFl2VtkHLNZU+eympZrcvlTbm6Pak7JoMJ - tup7oZRST+M3+/QWH2GrlotzpceUdIuwvTQpBZFdroBOiZJoL7CYoGEv6Efr63k9YjMknb35wbkZ - 0N6z6JxtdHR/IoeLB8dtiLxLz6TQkKfU1RF1Yp/fS8IBRnoolLofsw5X9iFE7oPUwj9xfK46RYVp - wxNcnZiwaDfTnOtXw2qLosml2arAaNOhnZTTXvVgiWegmEX+08vfZh9jk2//Z/wEjMEgaOsQ0ZK5 - zju1Rczn96+2y4pHw5AwPpDBWghj/g0WGz2441FA2ifBvm7ItxhDpONlNKFG3NyZCpv1LRSH4jcA - AAD//wMAv4j40CcDAAA= - headers: - CF-RAY: - - 9b1224a12d343511-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:21 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '176' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '393' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999987' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_56901365decf422e9e92f5cb16e01f86 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_direct_model_request_with_settings.yaml b/py/src/braintrust/wrappers/cassettes/test_direct_model_request_with_settings.yaml deleted file mode 100644 index 6be528c5a..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_direct_model_request_with_settings.yaml +++ /dev/null @@ -1,107 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Say hello"}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":false,"temperature":0.7}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '134' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFLBatwwEL37K6Y6r8uuu3U2ewmhJWwPpaUESijBKNLYViJrhDRuu4T9 - 9yJ7s3aaFHrRYd68p/dm5jEDEEaLLQjVSladt/kH2t98/nL1kfR3df/u+jqWXy9bz3K37r+xWCQG - 3d2j4ifWW0Wdt8iG3AirgJIxqa7OyrIo3xfLYgA60mgTrfGcrynvjDN5sSzW+fIsX22O7JaMwii2 - 8CMDAHgc3uTTafwttrBcPFU6jFE2KLanJgARyKaKkDGayNKNno+gIsfoBus7tJbewI5+gZIOPsFI - gD31wKTl/mJODFj3USbzrrd2BkjniGUKP1i+PSKHk0lLjQ90F/+iito4E9sqoIzkkqHI5MWAHjKA - 22EY/bN8wgfqPFdMDzh8dz6qiWkDLzEmlnYqrzaLV7QqjSyNjbNRCiVVi3piTnOXvTY0A7JZ4pde - XtMeUxvX/I/8BCiFnlFXPqA26nneqS1gOs9/tZ0mPBgWEcNPo7BigyFtQWMte3s89LiPjF1VG9dg - 8MGMl1P7CrE8VwXW643IDtkfAAAA//8DADvObQFHAwAA - headers: - CF-RAY: - - 9b1224a7794ad7a7-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:23 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '291' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '565' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_06add87a83a4411fabd32d429f347145 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_dspy_callback.yaml b/py/src/braintrust/wrappers/cassettes/test_dspy_callback.yaml deleted file mode 100644 index 4759ff5ff..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_dspy_callback.yaml +++ /dev/null @@ -1,123 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"system","content":"Your input fields are:\n1. `question` - (str):\nYour output fields are:\n1. `reasoning` (str): \n2. `answer` (str):\nAll - interactions will be structured in the following way, with the appropriate values - filled in.\n\n[[ ## question ## ]]\n{question}\n\n[[ ## reasoning ## ]]\n{reasoning}\n\n[[ - ## answer ## ]]\n{answer}\n\n[[ ## completed ## ]]\nIn adhering to this structure, - your objective is: \n Given the fields `question`, produce the fields - `answer`."},{"role":"user","content":"[[ ## question ## ]]\nWhat is 2+2?\n\nRespond - with the corresponding output fields, starting with the field `[[ ## reasoning - ## ]]`, then `[[ ## answer ## ]]`, and then ending with the marker for `[[ ## - completed ## ]]`."}],"model":"gpt-4o-mini","max_tokens":4000,"temperature":0.0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '813' - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 2.6.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 2.6.0 - x-stainless-raw-response: - - 'true' - x-stainless-read-timeout: - - '600.0' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.9.21 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJPJbtswEIbveooBc6xk2KqX2NciB7cFgiZGEcA2BJocSWwokuFiNwjy - 7gUl27K7AL0I0Hzzj/5Z9JYAEMHJAgirqWeNkdmnR/twd/d1L748scl9ODzRh9vlo/l2/3n1fUnS - qNC7H8j8STVgujESvdCqw8wi9RirjmbT4Xw+nn6ctqDRHGWUVcZnY501QoksH+bjbDjLRrdHda0F - Q0cWsE4AAN7aZ/SpOP4kCximp0iDztEKyeKcBECsljFCqHPCeao8SXvItPKoWuvrNdzcgEXqtBKq - ii/b7UataoSXgC62A9Q9Oyi1BV8juNCALiEHqjjkA1gq2FEnGFArfN2gFyyFQ40KXnUAyjn4gwYV - mh1aB15X6Gu0aUuZbnZCYawrLOypDOgGsKrRYqktppDDB8gBXwKVDsaDjdqozjBV7oD25Hbcg+MW - kHfssmuLZXA0Tl4FKS8AVUp7Gltt5709kvfzhKWujNU795uUlEIJVxfd9OI0ndeGtPQ9Adi2mwxX - yyHG6sb4wutnbD83mh03SfoD6ulkdoReeyr7eJ6fwFW9gqOnQrqLWyCMshp5L+0PhwYu9AVILrr+ - 083fap/v5n/K94AxNB55YSxywa477tMsxv/rX2nnKbeGiUO7FwwLL9DGTXAsaZDd1RP36jw2RSlU - hdZY0Z1+aYrJdEjLKU4mc5K8J78AAAD//wMAHmfYmwgEAAA= - headers: - CF-RAY: - - 991b80ba5f531dd5-IAD - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Mon, 20 Oct 2025 21:10:37 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=NCarHmYOyIz1ZAIOne5DFJej0ZWtyIkscrsY1JN2xgU-1760994637-1.0.1.1-S4ijZSTcO6mty21tIa9pLH.RT_PbGhLHllaxLNjL.qAfWfKv8CzxzsKMrOwqSNdcr8XrFQZqX0N0k7NXrH129pMDQ8PsNZMyn1FG241fvS4; - path=/; expires=Mon, 20-Oct-25 21:40:37 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=Mp.a7GDzqU0CGQVrU3qeUynTdP6UBCXjJeHOoQ6jEDI-1760994637165-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '1008' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '1171' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999832' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_3350c1e2f2d54aaf9923d2481dfaff3c - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_error_handling.yaml b/py/src/braintrust/wrappers/cassettes/test_error_handling.yaml deleted file mode 100644 index d78ff2754..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_error_handling.yaml +++ /dev/null @@ -1,59 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "Hello"}], "role": "user"}], "generationConfig": - {"maxOutputTokens": 100}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '108' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/there-is-no-such-model:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/02PMWvDUAyEd/+K481x2kKmbiWlUGiTDu1clFiJHzw/BUn2EvLfq8QZugjuu0Mn - nRsgsapoesY5RMi9dBxq9bhazGBgMzpeWRrCK/bgPSu32doqrY37vr1xZEMVx0HG2sVUvHy9Y2K1 - LBXT046dFgh8z9l4Ook6z9kjV1ZyXkt1rr7EmkrBRzb/vJXCBcaM6EYJCjmAJsqFdoUxHwaK4ghk - /bd8YO+ls2W6v2NOPtr1m832+/dt+7N5TeFcmkvzB5MWqKEPAQAA - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Sun, 05 Oct 2025 17:04:14 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=42 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 404 - message: Not Found -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_litellm_aresponses_streaming_async.yaml b/py/src/braintrust/wrappers/cassettes/test_litellm_aresponses_streaming_async.yaml deleted file mode 100644 index b84c297dc..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_litellm_aresponses_streaming_async.yaml +++ /dev/null @@ -1,210 +0,0 @@ -interactions: - - request: - body: '{"model": "gpt-4o-mini", "input": "What''s 12 + 12?", "stream": true}' - headers: - accept: - - "*/*" - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "68" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - litellm/1.74.0.post1 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: 'event: response.created - - data: {"type":"response.created","sequence_number":0,"response":{"id":"resp_686ee2bc312c819a87159efd24db25c20d1bf9987998b543","object":"response","created_at":1752097468,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}} - - - event: response.in_progress - - data: {"type":"response.in_progress","sequence_number":1,"response":{"id":"resp_686ee2bc312c819a87159efd24db25c20d1bf9987998b543","object":"response","created_at":1752097468,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}} - - - event: response.output_item.added - - data: {"type":"response.output_item.added","sequence_number":2,"output_index":0,"item":{"id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","type":"message","status":"in_progress","content":[],"role":"assistant"}} - - - event: response.content_part.added - - data: {"type":"response.content_part.added","sequence_number":3,"item_id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":""}} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":4,"item_id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","output_index":0,"content_index":0,"delta":"12","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":5,"item_id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","output_index":0,"content_index":0,"delta":" - +","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":6,"item_id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","output_index":0,"content_index":0,"delta":" - ","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":7,"item_id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","output_index":0,"content_index":0,"delta":"12","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":8,"item_id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","output_index":0,"content_index":0,"delta":" - equals","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":9,"item_id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","output_index":0,"content_index":0,"delta":" - ","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":10,"item_id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","output_index":0,"content_index":0,"delta":"24","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":11,"item_id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","output_index":0,"content_index":0,"delta":".","logprobs":[]} - - - event: response.output_text.done - - data: {"type":"response.output_text.done","sequence_number":12,"item_id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","output_index":0,"content_index":0,"text":"12 - + 12 equals 24.","logprobs":[]} - - - event: response.content_part.done - - data: {"type":"response.content_part.done","sequence_number":13,"item_id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":"12 - + 12 equals 24."}} - - - event: response.output_item.done - - data: {"type":"response.output_item.done","sequence_number":14,"output_index":0,"item":{"id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"12 - + 12 equals 24."}],"role":"assistant"}} - - - event: response.completed - - data: {"type":"response.completed","sequence_number":15,"response":{"id":"resp_686ee2bc312c819a87159efd24db25c20d1bf9987998b543","object":"response","created_at":1752097468,"status":"completed","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-mini-2024-07-18","output":[{"id":"msg_686ee2bc9144819ab006d750e17d312c0d1bf9987998b543","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"12 - + 12 equals 24."}],"role":"assistant"}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"default","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":14,"input_tokens_details":{"cached_tokens":0},"output_tokens":9,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":23},"user":null,"metadata":{}}} - - - ' - headers: - CF-RAY: - - 95cb00b7dbc12aa4-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Wed, 09 Jul 2025 21:44:28 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=tS6sjs7mcjoero8TwOe6k61qdofnkJzrHrabQ4yUYqM-1752097468-1.0.1.1-WVKoCchkncTTl1G_AD1k7OhEa5M_ElsbcZ3.ObIMnJR6zKP4KA.eqWFh58u9Y.IQrG7R7E355WFBPjItx.9V2689qVnw_QZb0zd.YNtv0n4; - path=/; expires=Wed, 09-Jul-25 22:14:28 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=wm8dpBRxaQ_NU66txFhVBBvemrWkoRFFhZ2UF5PAjwo-1752097468279-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "41" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-request-id: - - req_296275fcb31ed143e8a2129040dc0d1f - status: - code: 200 - message: OK - - request: - body: '{"model": "gpt-4o-mini", "input": "What''s 12 + 12?", "stream": true}' - headers: - accept: - - "*/*" - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "68" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - litellm/1.74.0.post1 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: "" - headers: - CF-RAY: - - 95cb00b7dbc12aa4-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Wed, 09 Jul 2025 21:44:28 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=tS6sjs7mcjoero8TwOe6k61qdofnkJzrHrabQ4yUYqM-1752097468-1.0.1.1-WVKoCchkncTTl1G_AD1k7OhEa5M_ElsbcZ3.ObIMnJR6zKP4KA.eqWFh58u9Y.IQrG7R7E355WFBPjItx.9V2689qVnw_QZb0zd.YNtv0n4; - path=/; expires=Wed, 09-Jul-25 22:14:28 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=wm8dpBRxaQ_NU66txFhVBBvemrWkoRFFhZ2UF5PAjwo-1752097468279-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "41" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-request-id: - - req_296275fcb31ed143e8a2129040dc0d1f - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_litellm_async_streaming_with_break.yaml b/py/src/braintrust/wrappers/cassettes/test_litellm_async_streaming_with_break.yaml deleted file mode 100644 index 63ca7c8ba..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_litellm_async_streaming_with_break.yaml +++ /dev/null @@ -1,239 +0,0 @@ -interactions: - - request: - body: - '{"messages": [{"role": "user", "content": "What''s 12 + 12?"}], "model": - "gpt-4o-mini", "stream": true, "stream_options": {"include_usage": true}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "145" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.92.3 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.3 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600.0" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: - 'data: {"id":"chatcmpl-BrWsXRHqtbdAy3XAlgLYEcLkF9afc","object":"chat.completion.chunk","created":1752097469,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsXRHqtbdAy3XAlgLYEcLkF9afc","object":"chat.completion.chunk","created":1752097469,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsXRHqtbdAy3XAlgLYEcLkF9afc","object":"chat.completion.chunk","created":1752097469,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":" - +"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsXRHqtbdAy3XAlgLYEcLkF9afc","object":"chat.completion.chunk","created":1752097469,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsXRHqtbdAy3XAlgLYEcLkF9afc","object":"chat.completion.chunk","created":1752097469,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsXRHqtbdAy3XAlgLYEcLkF9afc","object":"chat.completion.chunk","created":1752097469,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":" - ="},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsXRHqtbdAy3XAlgLYEcLkF9afc","object":"chat.completion.chunk","created":1752097469,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsXRHqtbdAy3XAlgLYEcLkF9afc","object":"chat.completion.chunk","created":1752097469,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":"24"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsXRHqtbdAy3XAlgLYEcLkF9afc","object":"chat.completion.chunk","created":1752097469,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsXRHqtbdAy3XAlgLYEcLkF9afc","object":"chat.completion.chunk","created":1752097469,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null} - - - data: {"id":"chatcmpl-BrWsXRHqtbdAy3XAlgLYEcLkF9afc","object":"chat.completion.chunk","created":1752097469,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":8,"total_tokens":22,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}}} - - - data: [DONE] - - - ' - headers: - Access-Control-Expose-Headers: - - X-Request-ID - CF-RAY: - - 95cb00bc980d2f73-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Wed, 09 Jul 2025 21:44:29 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=daiLzX2aYvlq5_YLmg3N1AnJtc_FLNWvnAW9q6vHTi4-1752097469-1.0.1.1-7cAT44X65S9TwWGkYsHcwz2GRSWjx2Hird1GW_UqCrFV3FwcuSXqo1FY52f628XVHwcggSuA3Hw7yKHclS0MQVybDyzJkEKeGlkpRZwkSqw; - path=/; expires=Wed, 09-Jul-25 22:14:29 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=IDIm7EZoj1C5auaId89G.uB0_3ZN0yKcSazXH87PkI8-1752097469267-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "303" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "306" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_a199be75e7c67047dd45593efd7f15ea - status: - code: 200 - message: OK - - request: - body: - '{"messages": [{"role": "user", "content": "What''s 12 + 12?"}], "model": - "gpt-4o-mini", "stream": true, "stream_options": {"include_usage": true}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "145" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.92.3 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.3 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600.0" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: "" - headers: - Access-Control-Expose-Headers: - - X-Request-ID - CF-RAY: - - 95cb00bc980d2f73-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Wed, 09 Jul 2025 21:44:29 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=daiLzX2aYvlq5_YLmg3N1AnJtc_FLNWvnAW9q6vHTi4-1752097469-1.0.1.1-7cAT44X65S9TwWGkYsHcwz2GRSWjx2Hird1GW_UqCrFV3FwcuSXqo1FY52f628XVHwcggSuA3Hw7yKHclS0MQVybDyzJkEKeGlkpRZwkSqw; - path=/; expires=Wed, 09-Jul-25 22:14:29 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=IDIm7EZoj1C5auaId89G.uB0_3ZN0yKcSazXH87PkI8-1752097469267-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "303" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "306" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_a199be75e7c67047dd45593efd7f15ea - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_litellm_completion_metrics.yaml b/py/src/braintrust/wrappers/cassettes/test_litellm_completion_metrics.yaml deleted file mode 100644 index f2443b2cd..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_litellm_completion_metrics.yaml +++ /dev/null @@ -1,215 +0,0 @@ -interactions: - - request: - body: - '{"messages": [{"role": "user", "content": "What''s 12 + 12?"}], "model": - "gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "86" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.92.3 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.3 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600.0" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJBb9QwEIXv+RXWXNlUiderbfdGj/SA4IJUVEWuPUlcHNvYExZU7X9H - TrabFIrEJYf55k3eG89zwRgYDQcGqpekhmDL2/gl3d5X20/HnaW7u/cfno497+7lx89JHGGTFf7x - CRW9qK6UH4JFMt7NWEWUhHlqvd/x6mYvxH4Cg9dos6wLVApfDsaZkldclNW+rK/P6t4bhQkO7GvB - GGPP0zf7dBp/woFVm5fKgCnJDuFwaWIMore5AjIlk0g6gs0ClXeEbrJec/aO1Zzh91HaxLi4WjdG - bMcks1k3WrsC0jlPMoedLD6cyeliyvouRP+Y/pBCa5xJfRNRJu+ygUQ+wERPBWMPU/jxVR4I0Q+B - GvLfcPpdLeZxsKx8gddnRp6kXcqcb94Y1mgkaWxa7Q6UVD3qRbksWo7a+BUoVpH/9vLW7Dm2cd3/ - jF+AUhgIdRMiaqNe513aIuZ7/FfbZcWTYUgYfxiFDRmM+Rk0tnK085VA+pUIh6Y1rsMYoplPpQ3N - VsidkHizVVCcit8AAAD//wMA0gHr9zgDAAA= - headers: - CF-RAY: - - 95cb00386a5a14f6-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 09 Jul 2025 21:44:08 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=LhJr7iTKhj3HkuIqsYYQzHnLMYlAsrPO_8DONvOoa1s-1752097448-1.0.1.1-3QZBiExLtV3A83cyPK4CeYqjpSygQ6uYDZ0v7kYNlmEHZIOldYiM088zk99s107ShpZgiHzSJwcw0Fviy3roAk.Ifv1OH0UzhIx2VTAKaS4; - path=/; expires=Wed, 09-Jul-25 22:14:08 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=1FpkTfHv2KC0I5jKg65yXzjPU21dBkiuyT323kob89c-1752097448243-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "319" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "322" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_0c9ffafb565ae4556d4374eaba259452 - status: - code: 200 - message: OK - - request: - body: - '{"messages": [{"role": "user", "content": "What''s 12 + 12?"}], "model": - "gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "86" - content-type: - - application/json - cookie: - - __cf_bm=LhJr7iTKhj3HkuIqsYYQzHnLMYlAsrPO_8DONvOoa1s-1752097448-1.0.1.1-3QZBiExLtV3A83cyPK4CeYqjpSygQ6uYDZ0v7kYNlmEHZIOldYiM088zk99s107ShpZgiHzSJwcw0Fviy3roAk.Ifv1OH0UzhIx2VTAKaS4; - _cfuvid=1FpkTfHv2KC0I5jKg65yXzjPU21dBkiuyT323kob89c-1752097448243-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.92.3 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.3 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600.0" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJPb9QwEMXv+RSWr2yqxOtq/xxZcQIhTnBAVeS1J4nB8Rh7gkDVfnfk - ZLtJS5G45DC/eZP3xvNYMMat4UfGda9ID8GVb+OXdHq3/STfG1F9FP2Hz1tvxEnWJzyc+SYr8PwN - ND2p7jQOwQFZ9DPWERRBnlrv7kV12Em5n8CABlyWdYFKieVgvS1FJWRZ7cp6f1X3aDUkfmRfC8YY - e5y+2ac38IsfWbV5qgyQkuqAH29NjPGILle4SskmUp74ZoEaPYGfrNeCvWG1YPBjVC4xIe/WjRHa - Mals1o/OrYDyHknlsJPFhyu53Ew57ELEc3oh5a31NvVNBJXQZwOJMPCJXgrGHqbw47M8PEQcAjWE - 32H6XS3ncXxZ+QL3V0ZIyi1lITavDGsMkLIurXbHtdI9mEW5LFqNxuIKFKvIf3t5bfYc2/ruf8Yv - QGsIBKYJEYzVz/MubRHyPf6r7bbiyTBPEH9aDQ1ZiPkZDLRqdPOV8PQ7EQxNa30HMUQ7n0obmq1U - 91LBYat5cSn+AAAA//8DAN/D0ms4AwAA - headers: - CF-RAY: - - 95cb003c2e2414f6-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 09 Jul 2025 21:44:09 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "675" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "693" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_8eb436911ec46aaf3095f96c82730abe - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_litellm_completion_streaming_sync.yaml b/py/src/braintrust/wrappers/cassettes/test_litellm_completion_streaming_sync.yaml deleted file mode 100644 index 1a6b3a9f7..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_litellm_completion_streaming_sync.yaml +++ /dev/null @@ -1,274 +0,0 @@ -interactions: - - request: - body: - '{"messages": [{"role": "user", "content": "What''s 12 + 12?"}], "model": - "gpt-4o-mini", "stream": true, "stream_options": {"include_usage": true}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "145" - content-type: - - application/json - cookie: - - __cf_bm=LhJr7iTKhj3HkuIqsYYQzHnLMYlAsrPO_8DONvOoa1s-1752097448-1.0.1.1-3QZBiExLtV3A83cyPK4CeYqjpSygQ6uYDZ0v7kYNlmEHZIOldYiM088zk99s107ShpZgiHzSJwcw0Fviy3roAk.Ifv1OH0UzhIx2VTAKaS4; - _cfuvid=1FpkTfHv2KC0I5jKg65yXzjPU21dBkiuyT323kob89c-1752097448243-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.92.3 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.3 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600.0" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: - 'data: {"id":"chatcmpl-BrWsECewLnZpwYk2y6TeJIT6H7F48","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsECewLnZpwYk2y6TeJIT6H7F48","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsECewLnZpwYk2y6TeJIT6H7F48","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - +"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsECewLnZpwYk2y6TeJIT6H7F48","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsECewLnZpwYk2y6TeJIT6H7F48","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsECewLnZpwYk2y6TeJIT6H7F48","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - equals"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsECewLnZpwYk2y6TeJIT6H7F48","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsECewLnZpwYk2y6TeJIT6H7F48","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"24"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsECewLnZpwYk2y6TeJIT6H7F48","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsECewLnZpwYk2y6TeJIT6H7F48","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null} - - - data: {"id":"chatcmpl-BrWsECewLnZpwYk2y6TeJIT6H7F48","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":8,"total_tokens":22,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}}} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 95cb00484b3214f6-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Wed, 09 Jul 2025 21:44:10 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "327" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "332" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_82e49575f67bda7dced7355056a8aef0 - status: - code: 200 - message: OK - - request: - body: - '{"messages": [{"role": "user", "content": "What''s 12 + 12?"}], "model": - "gpt-4o-mini", "stream": true, "stream_options": {"include_usage": true}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "145" - content-type: - - application/json - cookie: - - __cf_bm=LhJr7iTKhj3HkuIqsYYQzHnLMYlAsrPO_8DONvOoa1s-1752097448-1.0.1.1-3QZBiExLtV3A83cyPK4CeYqjpSygQ6uYDZ0v7kYNlmEHZIOldYiM088zk99s107ShpZgiHzSJwcw0Fviy3roAk.Ifv1OH0UzhIx2VTAKaS4; - _cfuvid=1FpkTfHv2KC0I5jKg65yXzjPU21dBkiuyT323kob89c-1752097448243-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.92.3 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.3 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600.0" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: - 'data: {"id":"chatcmpl-BrWsEMMFl7DBEVA7ID65Tklpkbnbs","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsEMMFl7DBEVA7ID65Tklpkbnbs","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsEMMFl7DBEVA7ID65Tklpkbnbs","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - +"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsEMMFl7DBEVA7ID65Tklpkbnbs","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsEMMFl7DBEVA7ID65Tklpkbnbs","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsEMMFl7DBEVA7ID65Tklpkbnbs","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - equals"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsEMMFl7DBEVA7ID65Tklpkbnbs","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsEMMFl7DBEVA7ID65Tklpkbnbs","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"24"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsEMMFl7DBEVA7ID65Tklpkbnbs","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BrWsEMMFl7DBEVA7ID65Tklpkbnbs","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null} - - - data: {"id":"chatcmpl-BrWsEMMFl7DBEVA7ID65Tklpkbnbs","object":"chat.completion.chunk","created":1752097450,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":8,"total_tokens":22,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}}} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 95cb004baed214f6-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Wed, 09 Jul 2025 21:44:11 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "203" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "208" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_6a6ea838af6542b8572e83b621c03f90 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_litellm_completion_with_system_prompt.yaml b/py/src/braintrust/wrappers/cassettes/test_litellm_completion_with_system_prompt.yaml deleted file mode 100644 index 1292ea3e6..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_litellm_completion_with_system_prompt.yaml +++ /dev/null @@ -1,108 +0,0 @@ -interactions: - - request: - body: - '{"messages": [{"role": "system", "content": "You are a helpful assistant - that only responds with numbers."}, {"role": "user", "content": "What''s 12 - + 12?"}], "model": "gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "181" - content-type: - - application/json - cookie: - - __cf_bm=LhJr7iTKhj3HkuIqsYYQzHnLMYlAsrPO_8DONvOoa1s-1752097448-1.0.1.1-3QZBiExLtV3A83cyPK4CeYqjpSygQ6uYDZ0v7kYNlmEHZIOldYiM088zk99s107ShpZgiHzSJwcw0Fviy3roAk.Ifv1OH0UzhIx2VTAKaS4; - _cfuvid=1FpkTfHv2KC0I5jKg65yXzjPU21dBkiuyT323kob89c-1752097448243-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.92.3 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.3 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600.0" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJBb9swDIXv/hUCz/GQOG695Fj0trUo0GA7DIWhSrSjVhZViR5WFPnv - g+w0droN2MUHfnzU4zPfMiHAaNgKUHvJqvM2vwrf4/3trnrdfb152pX8rcWX+7tLvLv+Uj3DIino - 8QkVv6s+Keq8RTbkRqwCSsY0dVVdFMtNVV6WA+hIo02y1nNeUt4ZZ/JiWZT5sspXn4/qPRmFEbbi - RyaEEG/DN/l0Gn/BViwX75UOY5QtwvbUJAQEsqkCMkYTWTqGxQQVOUY3WC/KOQjY9FEmc663dgak - c8QyLTdYejiSw8mEpdYHeowfpNAYZ+K+DigjufRgZPIw0EMmxMOwbH/mH3ygznPN9IzDc8VmHAdT - xBNcHRkTSzuV18d8zofVGlkaG2dZgZJqj3pSTsHKXhuagWy28p9e/jZ7XNu49n/GT0Ap9Iy69gG1 - Uef7Tm0B0/39q+0U8WAYIoafRmHNBkP6DRob2dvxKiC+RsauboxrMfhgxtNofL0u5UUpcbNWkB2y - 3wAAAP//AwBNbrh5KAMAAA== - headers: - CF-RAY: - - 95cb00a28da22ac0-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 09 Jul 2025 21:44:25 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "324" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "329" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999978" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_37ef8069103aa00e519f87fb02a7f31e - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_litellm_moderation.yaml b/py/src/braintrust/wrappers/cassettes/test_litellm_moderation.yaml deleted file mode 100644 index 1e4675c31..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_litellm_moderation.yaml +++ /dev/null @@ -1,178 +0,0 @@ -interactions: - - request: - body: '{"input": "This is a test message", "model": "text-moderation-latest"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "70" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.92.3 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.3 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/moderations - response: - body: - string: !!binary | - H4sIAAAAAAAAA4ySTW/bMAyG7/kVgs+1Q0qiKPW2YrtuCDagh2EYjISJvfpjkJShQ9H/PrhrsDWz - s14IiHwpfjx8WClVtLviWhX9uIvlTbxNm7vdtySy2bwP+zcfP4R3b1sfb5tPXFxN6n7cSTclZLnP - 5fSKdW7HoQR4VkRJxy6n4lp9Ximl1MOTVarYd/XhIFO1fd0luTr5t3WWwxhbmXJOaqWKJPfHujuX - K1U0dZZZd6xT6mXIM8Ek3b5s6tjPxqZC674dxpgW6q1zE6XOMrTDYUbyox07GbayPsT6e9NuL3Ww - bof8nybX7ZByPG6nzaaLo76yr1PoOfJ4vvyfX9N2jIsEoAIABO8sezaaKaAx/xJ5kgEaqxmCxuCD - h8B6iZGtHLKFgGACsWUgKd0CM1+x1V4bZ7zxxNZKyRcQ2soDcCDS2gfnwb38eYYoV2A9kweNjGCJ - pAyXAWOlPQRnDFvrjQuAC+3/AW4qNNpaQHJIQITnUyzwx4otaQ1oHbIjYCn9a86BKtQ40aIACJrM - y3p/XcdvdAE0UtAhkCcwfLqW1cl+WT3+AgAA//8DAOLPZJ40BAAA - headers: - CF-RAY: - - 95cb009578ca964b-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 09 Jul 2025 21:44:22 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=ldaJXZHcRfZezUdPq5ALaHKdUQy72qnha5eMS7WlkM0-1752097462-1.0.1.1-sr6WeGVyNhiz_KP2Lk_.fA3kLI0cJ.SpHxCFISvi22KKahdPLnnGUU6wFf9er3ccyNjwbi.vPFOgxqQLtOqmXgLWAa3B8SMaNVuJIS0wU78; - path=/; expires=Wed, 09-Jul-25 22:14:22 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=eCkXR5wyooQ2qFREVv0FqyORwTycuziWmJAxvkwXBCM-1752097462868-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "168" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-request-id: - - req_906e1e562ce7296e8e4ea6118065535d - status: - code: 200 - message: OK - - request: - body: '{"input": "This is a test message", "model": "text-moderation-latest"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "70" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.92.3 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.3 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/moderations - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJLNbtswDMfveQrB59ohJVGUelsfoDt0wA7DMBiO4mjwRyspQ4qi7z64 - nbE1s9NeCIj8U/z48WkjRBF2xbUo+nEXy5v4Nd19aQC7B3fTxz3fhk9J/3z0p8+3d8XVpO7Hne+m - hOxPuZxesc5hHEoAflVEn45dTsW1+LYRQoinFytEse/qtvVTtX3dJX81+5s6+3aMwU85s1qIIvnT - se7O5UIUhzr7RXesU+r9kBeCyXf78lDHfjE2Fdr2YRhjWqm3zYfo6+yHMLQLkl9h7PzQ+G0b6/tD - aC51sA1DfqfJbRhSjsdm2my6OOoH+5pDfyLP58t//JGaMa4SgAoAEKzRbFlJJodK/U/kRQaotGRw - Ep11FhzLNUa6MsgaHIJyxJqBfGlWmNmKtbRSGWWVJdbal3wBoa4sADsiKa0zFszbnxeIcgXaMlmQ - yAiayJfuMmCspAVnlGKtrTIOcKX9v8BVhUpqDUgGCYjwfIoV/lixJikBtUE2BOxL+5FzoAolTrTI - AYIk9bbeP9fxis6BRHLSObIEiudr2cz2++b5NwAAAP//AwC9WqDuNAQAAA== - headers: - CF-RAY: - - 95cb00980e464896-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 09 Jul 2025 21:44:24 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=VQ8b7SImQKVNCIRiMnfxH9.VG3iHeyazbvGOjIXA.qM-1752097464-1.0.1.1-XxY1zHj4dDcIvzE.saBV8uG7R62ARV7U24xTVGKz2Avhl0vz3bmuvZajl9t3blNdf9XEN69FSWuNYfMeTGNjIgkwiKRGg3uDzZpq1PobzkU; - path=/; expires=Wed, 09-Jul-25 22:14:24 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=0pvwsu4lhmDmwRvRF5PRcQD3zZ06mdYREXQ8lSIbpBA-1752097464624-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "1501" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-request-id: - - req_3dbafe89ead9b5efcfac20878a15ec19 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_litellm_openrouter_no_booleans_in_metrics.yaml b/py/src/braintrust/wrappers/cassettes/test_litellm_openrouter_no_booleans_in_metrics.yaml deleted file mode 100644 index ea09ddaa2..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_litellm_openrouter_no_booleans_in_metrics.yaml +++ /dev/null @@ -1,66 +0,0 @@ -interactions: -- request: - body: '{"model": "openai/gpt-4o-mini", "messages": [{"role": "user", "content": - "What is 2+2? Reply with just the number."}], "max_tokens": 10, "usage": {"include": - true}}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '164' - Content-Type: - - application/json - HTTP-Referer: - - https://litellm.ai - Host: - - openrouter.ai - User-Agent: - - litellm/1.81.10 - X-Title: - - liteLLM - method: POST - uri: https://openrouter.ai/api/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA+JSgAEuAAAAAP//fJBPT+MwEMW/yzs7bApRC77BjcuuxIGutEKR60xSU8djeZxq - UZXvjkL/gVTwcfzm/d68HVwDjY5CMVssytub2eJuVjwt7x+2vx9s8+o38e/yafn8fA2FmHjrGkrQ - +BMp3D9CoeeGPDQ4UjDuVxdzUXHRu+CgwKtXshkadm3yleU+esqOAxRsIpOpgT5jFeyanSWB/reD - 5y4mXgl0GLxXaF1wsq4TGeEADckcoRBMdluqv/l1oaH/0KVCTyKmI+gdEnuChhFxkk3IUxoOmcKU - tIJConYQ44/kvakL3X4wji8K8iaZ+gnbUYrJfey2sW4rQ7dVNb+bfIYjMSbuY64zbygI9HU5EY9l - nMYzhczZ+LNuqoQlfxzgpF698QY6p4HUV8u6oWycl4lljV1Tc/IoFczQOD4Pxr3p550hSk5k+tqF - lhIFS/WBe1VO72auLmkOGb5K1WW347VykM+pWIwXavgc61T8T9eM4zsAAAD//wMATEiLMc8CAAA= - headers: - Access-Control-Allow-Origin: - - '*' - CF-RAY: - - 9cc5a5a678259471-MIA - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 11 Feb 2026 17:43:11 GMT - Permissions-Policy: - - payment=(self "https://checkout.stripe.com" "https://connect-js.stripe.com" - "https://js.stripe.com" "https://*.js.stripe.com" "https://hooks.stripe.com") - Referrer-Policy: - - no-referrer, strict-origin-when-cross-origin - Server: - - cloudflare - Transfer-Encoding: - - chunked - Vary: - - Accept-Encoding - X-Content-Type-Options: - - nosniff - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_litellm_responses_metrics.yaml b/py/src/braintrust/wrappers/cassettes/test_litellm_responses_metrics.yaml deleted file mode 100644 index 6ff40d53a..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_litellm_responses_metrics.yaml +++ /dev/null @@ -1,171 +0,0 @@ -interactions: - - request: - body: - '{"model": "gpt-4o-mini", "input": "What''s 12 + 12?", "instructions": "Just - the number please"}' - headers: - accept: - - "*/*" - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "94" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - litellm/1.74.0.post1 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//dFRbbuMwDPzPKQR9NwtHsfM6Qq9QLAxaphNtZdGQqKJFkbsvLD9i76Y/ - QTJDDskhle+NENLU8iKkx9CVh9MBUYGGJstPu3N1OmUKq/O+LtRR6eaQ1fu6OGuNVbNXRXOUL70A - VX9Q8yRCLuCAa4/AWJfQc7tjobLzMS9U4gIDx9DnaGo7i4z1kFSBfr96iq7vqgEbMMHoPXl5ES5a - mwDjpsSyRgZjw5oN7KNmQy4VeY2BBd9QuNhW6EVnEaY2W/gsKXIXuWR6R7cS6kkmsqUGuy7RUo22 - 1752vM1p2xpntipT+TY7bnen0ZqkKy/ibSOEEN/pc/a8DdfR8kpleaGT5epwQGyyXIFqMK+eWp40 - +KvDpIIhwBUfxE/eJlKTY3SPlpZtrWQnS/CT5+wUAM4Rw2Tt2+8VaenaeaqeMEnoIqTK5Qzfx29z - pPRkU3UIwQQGx0NwH5iCZAcerEW73gr7ONxJ5/HDUAzldIplsnremkcI5Iy7yss4tsSmIc+LoN7C - 2Lbgv0ZwI8R9uFr0H0ZjyQb7Y5Q1NhDt4I8MTB6XvTC2HXrgmODdr2xEkw9j8YZ8C4/fC/9T3Dz8 - UH+Y+UZGDyZFJjkTD88lU1cuNpHNYLdsxEen0x7TKCZAZadXGNNFzV0at3odSr38jy+e4TyLBn3D - +pGYDfOM2f8+OvUMfyY7L/EnZSYGuxDOZwdjwNXfSIsMNTD08vfN/S8AAAD//wMAgZcEoxEFAAA= - headers: - CF-RAY: - - 95cb0056befb2b4d-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 09 Jul 2025 21:44:18 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=.a_i4x2pM4E8VvtpvgDLS_gUCW9V1maiL8fgpHihVmc-1752097458-1.0.1.1-NuvCq9dUlaAS6wrbxXXsbkVjtdhZHxmHmrDnpmLFfkeonCyyDg3gXv7U7HIUHm7YlvL0vt8yVErOl38C3yx5I0vZv9nT05Q3baFTj2uv1DA; - path=/; expires=Wed, 09-Jul-25 22:14:18 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=p0pkm7Hdk9Et0Ip8OlwrOSFo07x.aFcl0AxUMV_mRBc-1752097458702-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "6054" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999959" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_93c2e083b4fc6c5a0dcea290411430d4 - status: - code: 200 - message: OK - - request: - body: - '{"model": "gpt-4o-mini", "input": "What''s 12 + 12?", "instructions": "Just - the number please"}' - headers: - accept: - - "*/*" - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "94" - content-type: - - application/json - cookie: - - __cf_bm=.a_i4x2pM4E8VvtpvgDLS_gUCW9V1maiL8fgpHihVmc-1752097458-1.0.1.1-NuvCq9dUlaAS6wrbxXXsbkVjtdhZHxmHmrDnpmLFfkeonCyyDg3gXv7U7HIUHm7YlvL0vt8yVErOl38C3yx5I0vZv9nT05Q3baFTj2uv1DA; - _cfuvid=p0pkm7Hdk9Et0Ip8OlwrOSFo07x.aFcl0AxUMV_mRBc-1752097458702-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - litellm/1.74.0.post1 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3RUW47bMAz8zykEfW8KW3nYyRF6hUVh0DKdVVcWDYla7GKRuxeWH7Hb9CdIZsgh - OaTyvRNCmkZehfQY+upcnhFVrXRZZGV+gfp8aorigEV+OOQKiwxPdX25QHtR56zOT/JlEKD6N2qe - RcgFHHHtERibCgYuL04quxTHU5m4wMAxDDmaut4iYzMm1aDfb56iG7pqwQZMMHpPXl6Fi9YmwLg5 - sWqQwdiwZQP7qNmQS0V+xsCC31C42NXoRW8R5jY7+Kwoch+5YnpHtxEaSCaylQa7LdFRg3bQvvW8 - P9K+M87sVaaO+6zY5+VkTdKVV/G6E0KI7/S5eN6F22z54dKcy8HyEo4K26bNlD432QGeWp40+KvH - pIIhwA0fxP+8TaQmx+geLa3b2sjOluAnL9kpAJwjhtna118b0tKt91Q/YZLQVUh1lAt8n74tkdKT - TdUhBBMYHI/BQ2AKkj14sBbtdivs43gnvccPQzFU8ylWyeplax4hkDPuJq/T2BLbljyvggYLY9eB - /5rAnRD38WrRfxiNFRscjlE22EK0oz8yMHlc98LY9eiBY4LzH9mEJh+m4i35Dh6/V/6nuGX4sf44 - 8xsZPZoUmeRCPDyXTH212kS2gP26ER+dTntMo5gAtZ1fYUwXtXRp3OZ1KPXyL756hsssGvQbNo/E - bJxnyv770aln+DPZZYn/U2ZisCvh4+JgDLj5G+mQoQGGQf6+u/8BAAD//wMAYrV2IREFAAA= - headers: - CF-RAY: - - 95cb007d0bd42b4d-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 09 Jul 2025 21:44:19 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "998" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999959" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_be3af56d2d9472ef83e71f8638878b53 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_litellm_responses_streaming_sync.yaml b/py/src/braintrust/wrappers/cassettes/test_litellm_responses_streaming_sync.yaml deleted file mode 100644 index c18dbcca0..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_litellm_responses_streaming_sync.yaml +++ /dev/null @@ -1,147 +0,0 @@ -interactions: - - request: - body: '{"model": "gpt-4o-mini", "input": "What''s 12 + 12?", "stream": true}' - headers: - accept: - - "*/*" - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "68" - content-type: - - application/json - cookie: - - __cf_bm=.a_i4x2pM4E8VvtpvgDLS_gUCW9V1maiL8fgpHihVmc-1752097458-1.0.1.1-NuvCq9dUlaAS6wrbxXXsbkVjtdhZHxmHmrDnpmLFfkeonCyyDg3gXv7U7HIUHm7YlvL0vt8yVErOl38C3yx5I0vZv9nT05Q3baFTj2uv1DA; - _cfuvid=p0pkm7Hdk9Et0Ip8OlwrOSFo07x.aFcl0AxUMV_mRBc-1752097458702-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - litellm/1.74.0.post1 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: 'event: response.created - - data: {"type":"response.created","sequence_number":0,"response":{"id":"resp_686ee2bb6c10819a83bc4883af6c59a4066dd0ada07cd9bc","object":"response","created_at":1752097467,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}} - - - event: response.in_progress - - data: {"type":"response.in_progress","sequence_number":1,"response":{"id":"resp_686ee2bb6c10819a83bc4883af6c59a4066dd0ada07cd9bc","object":"response","created_at":1752097467,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}} - - - event: response.output_item.added - - data: {"type":"response.output_item.added","sequence_number":2,"output_index":0,"item":{"id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","type":"message","status":"in_progress","content":[],"role":"assistant"}} - - - event: response.content_part.added - - data: {"type":"response.content_part.added","sequence_number":3,"item_id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":""}} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":4,"item_id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","output_index":0,"content_index":0,"delta":"12","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":5,"item_id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","output_index":0,"content_index":0,"delta":" - +","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":6,"item_id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","output_index":0,"content_index":0,"delta":" - ","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":7,"item_id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","output_index":0,"content_index":0,"delta":"12","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":8,"item_id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","output_index":0,"content_index":0,"delta":" - equals","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":9,"item_id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","output_index":0,"content_index":0,"delta":" - ","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":10,"item_id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","output_index":0,"content_index":0,"delta":"24","logprobs":[]} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":11,"item_id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","output_index":0,"content_index":0,"delta":".","logprobs":[]} - - - event: response.output_text.done - - data: {"type":"response.output_text.done","sequence_number":12,"item_id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","output_index":0,"content_index":0,"text":"12 - + 12 equals 24.","logprobs":[]} - - - event: response.content_part.done - - data: {"type":"response.content_part.done","sequence_number":13,"item_id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":"12 - + 12 equals 24."}} - - - event: response.output_item.done - - data: {"type":"response.output_item.done","sequence_number":14,"output_index":0,"item":{"id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"12 - + 12 equals 24."}],"role":"assistant"}} - - - event: response.completed - - data: {"type":"response.completed","sequence_number":15,"response":{"id":"resp_686ee2bb6c10819a83bc4883af6c59a4066dd0ada07cd9bc","object":"response","created_at":1752097467,"status":"completed","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-mini-2024-07-18","output":[{"id":"msg_686ee2bbcc24819a81f5c4b8f705593e066dd0ada07cd9bc","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"12 - + 12 equals 24."}],"role":"assistant"}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"default","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":14,"input_tokens_details":{"cached_tokens":0},"output_tokens":9,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":23},"user":null,"metadata":{}}} - - - ' - headers: - CF-RAY: - - 95cb00b30e1e7c36-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Wed, 09 Jul 2025 21:44:27 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "73" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-request-id: - - req_dc8e0570e155cf43006ae751aa905bc3 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_litellm_tool_calls.yaml b/py/src/braintrust/wrappers/cassettes/test_litellm_tool_calls.yaml deleted file mode 100644 index c8fe43c58..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_litellm_tool_calls.yaml +++ /dev/null @@ -1,112 +0,0 @@ -interactions: - - request: - body: - '{"messages": [{"role": "user", "content": "What''s the weather in New York?"}], - "model": "gpt-4o-mini", "temperature": 0, "tools": [{"type": "function", "function": - {"name": "get_weather", "description": "Get the weather for a location", "parameters": - {"type": "object", "properties": {"location": {"type": "string", "description": - "The location to get weather for"}}, "required": ["location"]}}}]}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - "397" - content-type: - - application/json - cookie: - - __cf_bm=LhJr7iTKhj3HkuIqsYYQzHnLMYlAsrPO_8DONvOoa1s-1752097448-1.0.1.1-3QZBiExLtV3A83cyPK4CeYqjpSygQ6uYDZ0v7kYNlmEHZIOldYiM088zk99s107ShpZgiHzSJwcw0Fviy3roAk.Ifv1OH0UzhIx2VTAKaS4; - _cfuvid=1FpkTfHv2KC0I5jKg65yXzjPU21dBkiuyT323kob89c-1752097448243-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.92.3 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.3 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600.0" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA4xTwW7bMAy9+ysEnuMhSZ1k8W1FgV26YkXnrcVSGIpM22plSZDktEGQfy8sJ7aT - ZsB8MAQ+vsdHUtoFhADPICbASupYpUV4bf7YJHl63OjfD/W32f31XZ7cJO+3L/eJ5TBqGGr9gswd - WV+YqrRAx5VsYWaQOmxUJ4vZdLxcRPO5ByqVoWhohXZhpMKKSx5Ox9MoHC/CydcDu1ScoYWY/A0I - IWTn/41PmeE7xGQ8OkYqtJYWCHGXRAgYJZoIUGu5dVQ6GPUgU9KhbKzLWogB4JQSKaNC9IXbbzc4 - 98OiQqTmNindr0ex3XL94+dE25v1w2b+vRjUa6W32hvKa8m6IQ3wLh6fFSMEJK08t0CXviF1JZoz - OiFATVFXKF1jHXYrEIrRRnAF8Qru8I08KfO6gj2cEPfBpfPzYCYG89pS8XlYVErlfAk/recDsu8W - I1ShjVrbMyrkXHJbpgap9f0Oxx4cjXgLUJ9sFrRRlXapU6/oi86WrSj0l68HJ7MD6JSjoo8votEF - tTRDR7lffHfXGGUlZj2zv3O0zrgaAMGg889mLmm33XNZ/I98DzCG2mGWaoMZZ6cN92kGm6f5r7Ru - xt4wWDQbzjB1HE2zjQxzWov2wYDdWodVmnNZoNGG+1cDuU6vIjqLKC6vGAT74AMAAP//AwBOf92H - QwQAAA== - headers: - CF-RAY: - - 95cb00ae49452ac0-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 09 Jul 2025 21:44:27 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "591" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "604" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999990" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_da2ecab7819e8df314992a8787e2fff0 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_mixed_content[stream].yaml b/py/src/braintrust/wrappers/cassettes/test_mixed_content[stream].yaml deleted file mode 100644 index 5ecfc0ce2..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_mixed_content[stream].yaml +++ /dev/null @@ -1,68 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "First, look at this image:"}, {"inlineData": - {"data": "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", - "mimeType": "image/png"}}, {"text": "What color is this image?"}], "role": "user"}], - "generationConfig": {"maxOutputTokens": 200}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '2611647' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:streamGenerateContent?alt=sse - response: - body: - string: "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"The\"}],\"role\": - \"model\"}}],\"usageMetadata\": {\"promptTokenCount\": 272,\"totalTokenCount\": - 272,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 14},{\"modality\": - \"IMAGE\",\"tokenCount\": 258}]},\"modelVersion\": \"gemini-2.0-flash-001\",\"responseId\": - \"AqXiaImDB5mdnvgPr864oAw\"}\r\n\r\ndata: {\"candidates\": [{\"content\": - {\"parts\": [{\"text\": \" image is predominantly blue, with shades of turquoise - and white.\\n\"}],\"role\": \"model\"},\"finishReason\": \"STOP\"}],\"usageMetadata\": - {\"promptTokenCount\": 1303,\"candidatesTokenCount\": 14,\"totalTokenCount\": - 1317,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 13},{\"modality\": - \"IMAGE\",\"tokenCount\": 1290}],\"candidatesTokensDetails\": [{\"modality\": - \"TEXT\",\"tokenCount\": 14}]},\"modelVersion\": \"gemini-2.0-flash-001\",\"responseId\": - \"AqXiaImDB5mdnvgPr864oAw\"}\r\n\r\n" - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Disposition: - - attachment - Content-Type: - - text/event-stream - Date: - - Sun, 05 Oct 2025 17:04:03 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=1446 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_mixed_content[sync].yaml b/py/src/braintrust/wrappers/cassettes/test_mixed_content[sync].yaml deleted file mode 100644 index 41e20429d..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_mixed_content[sync].yaml +++ /dev/null @@ -1,64 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "First, look at this image:"}, {"inlineData": - {"data": "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", - "mimeType": "image/png"}}, {"text": "What color is this image?"}], "role": "user"}], - "generationConfig": {"maxOutputTokens": 200}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '2611647' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61SwW6CQBC98xWbPYsBsVh7M9Y2xhpNJa1J08NaBtgUdik7aK3x37uAKNp4K4fN - ZubtezPvsTMIoR9M+NxnCIrekTddIWRXnkVPCgSBulGXdDFlGZ6w1bdr3DUE4bt4RL0ICE9YqE9F - 0gx8mXDBBMZbsopzIFqabCKO0CIbjhFREfNBERkQzLOvXHKlXwqCmmbD1qDatKGzP97fW6fpMhlD - IZ1IH+Iavq8BNOCCq+gZmJKigC282Zweu2wdPskwzeSqWNC02t1u13LdnuPYHfu2Z/dvjFq51KS5 - 0stNAZk2kB1topohSdGTnyCGMi8NtB3LqXQajp8j3EMfJbL44rHdb/2hVvdamMfNLBoxaQNYzHFb - 5jBaerRhEp6TX7p0hWU8HTyOrtN0+lZNZDRSuVz3v6Z2z8WMw/xV8C+QKV4lHIL+57jZaVtmEDMV - mZZll6w0A5VKoWDsF7jBZMnZ7HXxMBkGP73xPMQgSAYbauyNXy0Q7OgoAwAA - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Sun, 05 Oct 2025 17:04:01 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=1531 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_mixed_content_async[async].yaml b/py/src/braintrust/wrappers/cassettes/test_mixed_content_async[async].yaml deleted file mode 100644 index 3c7848fbc..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_mixed_content_async[async].yaml +++ /dev/null @@ -1,65 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "First, look at this image:"}, {"inlineData": - {"data": "iVBORw0KGgoAAAANSUhEUgAABAAAAAQACAIAAADwf7zUAAEAAElEQVR42lT9yZJl25IsCqmq2VweJ-8FHpeiQSUg_AAt_v-LAEEEMrevYaY0dMzI5DTODtnh2335nKMwU9OC__3_-n_756uS2Q_B3SkSlAnCAGCQxo6e3vGsSdIjEaLXID0j0rsgWc_OsU0vRZRmVip4Rc73qBpd8_tV0ee3ugwYsrcoG7tDkpSlOaefz36_rMIaVXOmn_JZqHaXguidUfVZG3hKO4cSjB2zRI9AULu2R6LPYQkAQNCEqVoTVn4d2BTZvWdFgN5ZVcMAgTwXQJS9u1BpQZD0Ep6xuu0hSMn27lbV7EoFwDtV2l1W2YYNr7q8Bmt3RBDYtaoM7g5tioBM2ksS-TLShkkDIrwDAobqM7sCKewZdX-_hwV5vauqnVU96zwTYdZeeEFQ5TXU3iVlL5nvShsSdxdrlgDDAIldFrEwZVswyTwaewjvLklWYbE2Cdr5JCB3VpJ9KO0YVdgVKWl3AYL0TqkAWpV1CBtEde0ZYyXuWba8-UhHVXsGVWB-4BKA6BmqAMyxitgBprt2xiAhsLyWYNAwKYDwAABlA6QxokjdZfa-mrw7EJ5Vlc3dI4kAu-CBFxCkev5A9T1HZMPrtQEvSQOgdk8VvRYFYGfUbZvAOWu4S5uP6PwD8BqATd7f9-zAriqv2e0ZqDCHIswFINJLL0gv1pDk_ZKmatcGaXqOSjvLKtgkZlelWSzwFHcOq3YNc3dL2DkAoLIJmDa8lNYm8nmdLeVdAmSdBZSHgCyUu6d2QYKCYVgEDRI2TXpHJUJ7jsmq8izEnVELgGco2cjGsp1XA3J3SYj0LJXHvlB5viXdIw4ABRiwDdiUvCMJsE0DyOrKV1AExisJYE4Nz2TvSDRyji52DLAKpO0sHNjIvpI8u97qIrW-bxYUAJKADAMgAa_qmRlSILBDAqBtVuejkxS5MyrChLhjwvBC-bZaL9dUvq3WNEDs3XCkDVLeQ5gkQBO7UBW8pDADktLulgjAayOH9cnx_l4uXK9UJL1rw9j8ghR9Tk4n1Wd9lzZ2Vdr7IUBhnGOKVtFHJEXPLiCVvdxlTrzuM1sEvLj_y3_rv-uR5G52OgHuWiXMAbGzqtq7SSFgd2zreWzsHO-qRGNBiTtLmNV7F57v7s57zkEBe62uPSNyDFbtHGRt7ZAEuTYl7JLwrqrn7nELZNV-D7tgi9q5D3ltSTsDsUozc9_XXceAt56eM3lQ-fxnls8H328Rcw7wX968BzkfzOxzteaspPUCVLfPPTolro1dFb2mioDnmBC1oG2J8ALMEgGgktfMNnxX9t1WORaMzb_3Mgf7LkX7nggGbcIrIR84SxG5_QFYzre2yWxw7q6Byu7ogg0DkucwZZBBPbsGVrz3j2FKyEe_ez-fjfez4--Puh8vy96zIiAZ9qy6PUZ2HZz_8O9S2awr0Du5e6B7F6fuyr5gaWch3Uv574dwfjjXNikY8N9lnyeJv48ZoJRzI9ce7le-X0Jhc1ksxRwCBnaWEkzbUJ4tsnDujwdt3-pF8oyqUhjk3DOJBVU7w658AVg2gNRpgheqfF6SM0ddJA3lg-8O16y230oJyEoja3aowo5Ee8G6Jcwei6p6D7fFDgHWY8AekJi3EJLm-62nPAtyl6i7N2F4Fvd0VZYovKkJMd8Sd-8hDnjPVyWyJt_czvpf0yB21HIKxQGw3qPqfcsd3rc3Yr0v-T7kKu2CLMymbF9AQlaIhut_19nuT0kPCXO7xa4sHlaRBKx6gEpRVSpJO7tLr7NRc71JBZRtsJSra3MV1l1ldj_t3ZS5oghinRXjMf3e5-SmLUjnUCKd--k2Jip1SZCJgSjYAmXMd4giKFG5fCCw-LdYANMeZD8C2DO2dw2aYpWqK8culdILVWJh7L27CuoyjLEosghlzQPsp7OobNqmxNtOiVWUlGOYwoIsg_AtFFgSlc9ZXZRI0qguslgyQEiS8n1BG4TEsulBsQgRELBnvVS1AbFoeVDVuAUQPOkeSACzlLw57pQHcI_fBSmm3FlT5dsI0SDS1dgAVP2ecqAq1xwX3eW1dzdnkkTdB2GJKkrenBc5nwRpd0AuSJXyNcztBYjO6oftUQ7olg11KgphrS68JUzOkPclM7_d_Yc53wGErF-REqAsbKooeIaUAXaZRpoQQEUCuwt4z8AERCrNxu0xgd31esc0JWK83y92iqLhtb9LKQ3GXSeq_W6pcXc1N-uPFFEl26pemMUqgmnAgJzg6_v5wb-3Sv5oUF3O6Y3U2FlTvEXt2PveViCLKpKs7jw04P5EUDR34OXtbshSYVxQV6diuBeSbidjY22_f8XFfxZbeM8NUblCdrvvYkeRSgHp-0vx70a1SipBtACs_rPPJ2UKFLB_N9v9G1aByN_e8p1Udb5vvkO-VW4qin8fVMpM6p7oqnxHoHIF0rdBcJUIC77HWKrcurtgUxdkWd7OAfk3VeLbOQC-m6ZyTgAUc_qA4PK-FN5zoygJuaXJtENiTnjdnyhIUsmEieqmmPWXl38PGUsiS-9Ty1NmtjrzxYYENlWEBCiddravs2-pHM7vmlT6n6wTQjlF84m7GyCwaX1UrBZLVSW-R4kkCbcOE5yPlAfCnBsSc3pIgkhQJe_SNLKV01cRa-6taaC3fgAJVMvY7A9Ruznmama9rm6RInP1E2bq7729XKocKnXYbQzvPbsW76-SHV456kkWTYhUlSTZSsW2ASIEgtjsCN-nVBTxFnpIbzyrHM3CwrvOMp4ZlUz7jHThBi0AYt0tVXYZIBGqEpQbPq31uwaVdQiKgvO6uZaY4zil9l2vfB_If_7Rek9NSumNlBoEUN3bLlXAi3kxXylBRXiZR1IC7wah70cizHvD65bX_R7N6bdLEHNFk_u27SBYefYUBOQXrBwLd0sSriL5FqkEhHz_3GhZKlQW-b3VUXqrAlFgEfL7I4D_3Aa5TrIwoApCJTDHM6i0MICtum_hPYjSDksCBVbOqf_yEGjk80r_pZ_nGu9RzIBZaXLu2fuegWAOc9-jilDlu-cQfauEHCN5nlKeIZQfRZAQDao6lWL-xV0MxVsUqnxWSAEFlNLOkLlKbHvOYqwqEizaWSHpOII1iMX7Bgy9b3kpLG3s3jo6p0ouWa-kJoldwN4VlctOrJzYexbGGux8QJPcMXbBkopwjiYSmA0cUMrJaTJ99a1EWZU1_58XmFKR5LS4hVgKs5y8QYvuNXqRQEMC3A_XmwuYlPoZngL5r__L__2tp-3j1DelWkzOPI5T1UIwC4JnXnDkdoyBe72ehaoJzPergkrj2QGb-J6qSktNfdaz339KNAwBKO9mdTkPLh31DgyUsPl_ktxz2M9b-Fn9XhbA-sJsF11KWTqgIFUQhltAelQ9v99bmagWMIsOPJJykbsrLKld86mFDRaA3NcmRGy5yBlIO8vO7yATNIC9PTQMC3ZOIgh3yuEFihhhL3qQ8hlvYQ_bC997e9MKeTimZNFURijw5kim5Cw1Nd72H5Ln63NUd5NT5d33WQe2su2ZZb8Ya-6MexLcKg0U6FKvvxcPyDlBEPJOkEZ7c-btrPIAqoLyCXh_bh624GFuf8PgzDwlApsrYs07OCirDAu0z33TLdrfr9mpg0xjZ_nUBVHo98Eag3swldYWYa89-f47rs-_oIyk-Lb4q_spArhDxJ6jC1XKKjBn1WCMvGISxQAt5K19fQ526_MYZH3657_t_HO-00Wsh9g5qvyC90KHJHF9X4HnggoSzxmIXqrvlWlwzxGFndz-Xu85Vrpf7C1wAQmBQWY8W6WAMOiPzz-BbSlM9mXAUdG73ItVO8MO9c7BWkVgM0LCjFLjA2Oy5B0EMSJsLJwPmcMT6TSqgirNTG47A5hV0XMsmWWvAO5QsnSbgFQ-GVKlAvDe-nvtXaQsznoMbFEXBTbonbt6RfMeoDll_05jnNM93co5kjDD6gkoZvOCyjaU80P5by-gcielF8q8QNrogrvc_9wJe_s9kCrMwfvZApTCssFPU7XELVjv5QNXXVRmJ7CaS_eSz_nyn2AeLc66mIOJmwMBUL6hagH24x3PKB8Z9xXK3J1cKLMDy5jUBoahyjlOL1kL6Kkd7E4xF-7ttzDvGZOL0MgDgdfnvBcm-Py5wDwCTxiTX2QBrch-vGusXjiW1TvDDQ4KVK0Xvnin3nnNkqlKvF-8o0XDE1w59-iYurOg_IKbQvy-zdSXmeGZqYNewHQDy53zt-dMl55BiHczXEkfBZoqY3Mh2ma9LUiOscCBeWLknKMXQb3T4HHlHhPz-S1ilrv343ZdvDcA_N5xk_-WazMg5mw1sVzCLcwSxveo5ZQlf4GVF3W_5WJ9ds0iWJ7tgI6-6AptKjfhnahdnDjI650CZOy-Fz63807uGFwcY9Yi5X1bdtu5Cpdk2hJ47rCO2IzZ_5a9edF7YfgF7trYTS9hXMCL-fCw1TkwhDvxzle9C-YiEm_f8D5NO4V-APXgMulhmONrB9n80oXVS5iBoZIzhMxYIA-YsiHi70zvQvzOhHm9vgep_464SHjrfUW3FclPRf7yguzE3U1755nviMB33dvQHUP-__0vj7S0M8qoajMaFMRg4ya4diD_F-kL3eDWuXY-g6g9w9sHFCpzvEBroR1oAT0P5pBm1xjME54c2nQ9wMJDy7RKe1FgMHc0BIH92blwF_We1b_f1N4UWX12CHgGusiMd7EGy7gN8JzJLIrpLRb3umQvlil4bBZgLkxpZ3yGLUpOEbVmyeKt37zeAQQRy4yv0NqwRrwlY04waauAAgGfDCtM2enlKjM2vMXt7qJWKqFAZQhFYw0j3a2CEZoFtkyraWC5xoA7HtB4enbXy1Z9nqCc9fOBaFoqPZXmHkUTC4y_i4WC1Kdj9uwxtbTBAaAMlIcFiSh4h_0xFk17L3BShnoulvizczLbWto0u0GwfVdiyR4TO7PAePjpvXDIpMder4so4NHsgcBuiHzyPVD6n1BaYIlgneshgBIEcACzH_uYOzmHumbGBusDZs1RXfm5FtbjbDiCz7OEafUDEXIYLMayuVh1QwWLT5mYWWQQsgfFwVgyrOdh6Zwvq1zpue0wIsiF7bUyk_aKLqFpcmFwld82Y6j0H6LveqBpiOMzmbAW2fXddFp10UgxlIDdNbyghTm_FFS9uyig6KLJfFvIM2Z_WF1P3UGuDckEKsPyAUeqKokWtx7CY7H_NOBMbwjXwz3rWYqbwZO0C4tsrbywqsGyF5mSlfg0pMFdovp8Vtj8pMx15WpiTy7m6rbXGHtYGi9SzBVYAN-SdxfGzqKglr2S1-P9B5JaO2YXZXXZW3VBpkA0Z9aCiaWHdKmef6HEJoXn508qiF1bYml3XBwCpe5HXbsIqw3K8vF4zUX3guxS_eQOT-kBGEIuctUnlY0JdRtemI9Q2DvAUWZgGR1BXOyKWVes9D9W14X73gmdhc2RKX6DJBVnB8hzW-8JcJezYufLSscFMEjMT5gJJlZk09nFArpw16olgDTXtIWzu2nR9ZDLEPDg8Rqb3zFgUCrvvbgQTO8u-8lHWg9pqZwmGICEouUl1guRcuhmt8_NsLJkjNMu1TviL95dGZ6ROHvQgoAinOUKy1s0-f0ew-xG3YMaQWmk3XkXLS3ag3cwoi6IK_Ap03eS9TwDwKvnAWkRT-e-NXpnSKifMaALl6xSSmJJ9qNPp6ZBC11DHhhd7EJdhGoxmTz4HpRkPRac_6pKz48FexZem59Hn9IjlKpIvfi-DGnpJfh8_ASqp7m2gx-uONmwLTyVkr_6wyC43RYhDbUmyPHm9DPpqs0dpDvfs4DS5XsIZ76-VZMnJVXVEqCVeTBmcIYYbG5VllikCjQ8VX8CkWxKfNE0u0xYuzuAq1rFPAqUFmsucl_ssHo25_k9PN9BllkClzTQxnrGOYCaKKzHc7K_biuF9R5gJuVUdZA1OWXL2mFUQV2TS0Mf6I5B12A3W0aKvkHBtAsWDoCnXH5x8bRhpv7NgcaljHPdsmD57JhGt6UNtn2n7Jg9i819QXl3rYDEhDweFCGyc_YqS32wi1kvipMJYOD_wj1wlNlmtssHgV4V6uqdNhhLZUS5KUveUcBOPvA9ooHie0vauDfgxaQxtlONTGi3Vfe3o0mpggRSrdm1F0qpsFZAVaOIIjOxuBw7QwjRJPTjHOAkoGVx71hdVHhEF2xky57NUhaQK4xmCxks4C9qY5fYTK0clP32cLP59WcHLYhGBiAcXLLO7uzc2esSbqKEIKWtW9DeEhiDZZMFFMC5d0ooikxna2h3vybZ9T237tpdy-hegvLusaHnD8XJsVpPzlh24Uknf_Ih6_PAZuiFJT5EpZ97gL3VoLApukiIZ7-Xy-KFjxdMFU3cMpWBwMFqV_5KORC-oWg3DM_3yyopFI981b8uOfB5oJTt95LaXalYwJ5dL-WulVH47lmaKmRij7XDIt6dAwJFiSCqueN6_pf_BxKsP5DfiYvWYGd7DW8bpPcIsLoymGd_DOMYmY4hZNwN78OAW3iKl7KXQqFJzMxKYGpZL-BdPW1v__y5zDavd9lF6eyqmiDlmVVlVOZZq0VYzRXsoxJVK7M63ap3VQ9AlL7fb30EgiW1wLoMXZJdCzNT-dsbq6ovN5QkO4Qn-59MVqgCqvQDgWzD5xx13pUhUPVOmFh19-vuy6zFwkBR3bzD9WC-XmRs_SxyUiKbCqD08aZOuiNvPbWe_Eb_ZejGYp2z9TxGeIK2F48MoAsAq8J6hKj-7-f8QkA93qmnGKRzzOotVn121-TMsqgSS6RVbayqsNTTAVMXtCdDvTt0KpmmWlU0Peu6zTWlPZuWgQK6HBJSjjSJ1V5jV-pMc2cuRdK7t402dmbt1P47s-8g_i9FhGp7AfTzOWfUvcbi9tIo1edn9zIoWNIdg1-Wi2H9_FzWsBdGZQirS4UhNWdAVD-4pGp5dzf_so1lMfykv1ypRW6aBllPMUOkCybRXj0_zr6tolyRvrSW6zNATvZR16WPNHf9_HxMzFmLGeH9PJ-ZCTWh67kjW2hnsmLtYdUSpKvLtorqn91BTjSy9If3FsnQKbWvU8iul133NmlSimgnnE6ocCuevZDYHBooUWWwns5bnYv8LSCEw3ORH0qdgc0l5ZCLY0P1OGRuiXYF60JYis5wI2iXJNYTzYbEPd-w8Ry6SibDV85UYWhcnkn15WFX2fY6Uz6pZid_SLcM1aUvkhIzPTc0C3SxetYohdxoWKr0ABkMhuLHrplRtVQO2ir5BCUhPw8ptVoFeL4nh3dkEuHgVjczUq-qfrA7c1BF3YZsdthVkloQpSqV0zFLqgfBujj1iNQWVCJpcjDVLT0QEOxgswgz0C-UQp_acx_mhqDVTTmUP5VA7gKli6bnbZdYYDcMqHNLzwmeGQpAZ_JQ6tmRei6R26xSd3iD1aS0QyoklJo942_eJqRUVO-hafUnIFsAs1LNObuGCpf2oIX3TD1PsdCouixN75yMs64kYNDtIoCuJ2Xgi_Nt5D1X0yLaW_WJ2iSao2CMYYOEsvB3-fLCK2W9fLlLGfizc3YvE0DkmV0MiqVLR2TI0yWp8Lcx2NuVqVgSggXfiREksntmu8WqtVUFajHZ_qHk5ShVFYpe6GkI8zvqYtWeQ3VgfNbde_YvSHSFkeKX1Xf5WiXv2s7SjfgnNERIgdDvLDP70UB1aGFnxtFg2MdAF1qU6mnsVj-5Ynf2Lw8vs1m_XFi_fDYwFGijRFPVc34v4B3SRQYxXQLD_L5EjtBrJV7Ug7uOns0CW5ZeinJGXmEcDFQhN20GkpdiRNVl6vwV9swdpmfgplTJGVwGd6cKf7lSJKj12qsupoXGqwGQyApLKXK1tXcWGazoUukiZDKYRRtgjiQKl9OLiuKRXVLtrp4e3ysjjBZWRWfgfSnE73wrUzvb1f9CGOTKEbFesx8VIxuI0o5VwYOkCmPNpOrZqCx2041bo-LlsGJAVXXYHJfGUanxzC7DTIVpElT3uSAU1PWqIEhlNaYW3T3LUpAdvHOeUHmrKrOlM8tS-vNLRW9iKUn98a43Qqywx4-96mfPqJqXQpIhoJbe81UX74yIoryu1v3KGRC7o9aGE0hWP7ldw_4QXM__9L_zPR1QL1H96mq-RxS43WVgd-tpewq2ze49J-DISzfN0bDeraKFHXC939_qtvD9Lku7rifcH3tOZvThJt4KphgSS-bjf2m39QQ3pbqo8mx1e8y66G0Qw0sDhQCLhmRbz2d-_6nP411JFHzm7t4Q1peeVXX4YTlW_lLu2DltLsvjTrzq6hGz_2e_9_4LIsYO5y8LvCoEZYKu0jq6TO1GshY1T9ot6_IoQ1kwQoymqMZ-SySugu2KqyDvyYmVkS6LnuGnDT79ARcA5Hpno6XHtnin1RK7741zf6OM3zLyjuhIArcl7ssIxdVrYjdUzKvh0xUKZ359p25w6bFHf8m5JXirPlCes-4GEHGGrLlcdkBESdL4MqAZ5FgZ9r3k9gjJrgTHWZzepdsA5hTldaYHE6rDcyfgrzjkr15CgQYiT7gT-miyJc_250n9PRfgKO-qRRJKue9KoyWK7CpjFUFElq4XprohqRqesHMMq241qeq9nARExdMdLPSCkgLqKVAXX1btTuQepaeVsTHEKK7kteqyKq3QwVndIVzaW1UIxSTK-P0qMjC_ohVH31mqD-UKHqardwsl49JKZ3nJ8e_oFvtqaO-4K0hnoNQN22pGtHTLfEX1RRtQ9SWZ8K8Uf3GHx5vH8rJIaQ_r1eONCe0lyypndHXvzr1h_w67L02BsEtCWGyv5uSVO5kzVxp00QL_pa567wCsojvaQOQCGb07_hKV7rQZUTGGEiH1vXRf_cHl6-q9z6RFUAMq3eMOaCoUGkSJWdWbSr4KKuyS7K5ihWlSndGqSwh__UrfAh6wgnCzc-ZHKsdKO4QwwRn-Upj0vAwNWWRV9WfPEVD9VqAyF56NKizNmLH1lNj91M5cLnX6jrp7PyW1-m5FSqqasyV1lUow9Ojvw8RCXSLEEMQvUuszLNUtZaKUg6oAVq6Jl3GZxuwFf1D12HPpQplfRa0_2bFXP1aX234hhUtqDxnvVYKBDjQYyv9lhlD6VIhP0c5ddt46I3JvZEOr-454xc0h5qUr80k1IumSG6tAl2FgfTnxL6_dmAUmOA69-z2R0dred9GrsWdgkZcVFpZRlB802bUzeEV3VxEUOdZOPx-s67n6pHo-rxYpC_sVTV5iMKC04ZcEqwgoaVYZmzMkMhJdDTte9tPVmgkKjpx6-BIZJGMxISzpUjFxicGiNtpibl16B-7NfulIuVjjjJJ9rLRpWQ-Xm0TCqKaxZMFbqSb9kj8jdkdU2psfHcSPxVf8P8B_sUaITcFlWy8cAcB1e2AA_jv0ekEz8K8FRZ7H7VzfsyviMFz45lX95hgVmm1uDs3_JLLfxVPrQe4wgMDMMtq7l8B2jyzfNebi-U5V2yvs39-MlWd-FXivxPkiMFchlVFd6QobcnWel66sl0kVVTReTaIAs57O6aGr3KXwMjRBmK2-Ov5S6saA3zNpLgSFJqqYukjAXAOGvUyajLKl0noiiNggRxkaYqu4l8ctY-N04PE9DXLmx1qCyxkJoRDdCwWMYHFjDHDyJK1qwBV266zqj339SGDfsjT8XGnOIbQLqbzDHVK2dkdi_flf_x8jApTp0FSiEZ9RTiJyfufpP6bObKnpExb9papHZnH18AbQ_Xy_X-SmgevzmbNSNA3hjmfxqWhRNLpEoFTf3wUbps8VXLPC4KM3Ux3N95uNl4J7Ns_JvON0Z1KLzbScu5aaNMFx3bE8rjYrCA2xtHx9CZ4dG5wN-39JbER4RUZChWd_HQicxJzDl7N0ZVmh1O3yPm8A_J4jhiqEUq0hlg2ZHnMBoxxVy6SGEy1fybIAzN75Vf-3DOpD3A5KxMm-XK_CxjlneIV8wprRv5nwchcIt34hSZ3hKQwMJv4VIlUyqLz9eknWCJI03xEvzL62x3URnRzKOcyzLq6Ea-Zrolg-S9XMUKCVonCv8OAKrq7JwywhE_r0Xzz42l88z2X4qiPZycCqqsJWU_VVGiK2QhX6bzbnVY6-BgVV5WNR5_erUIcziQqHL-O5lyaoR3Zu4lvMBW2f3_MSx62qzN7hlZ45AMtLmfZQYtXvAYrPp5_q8z27KEb9jKd_SLSaosD5DtShbPhk7dELmSqVxIxEvilKhmDx8cs5j4Kfi-8__87-zDlerLe7vYu7w8hFDk3aBe5C1VLX50-EBzDOMdmOGwCBA2XNOVLp_CxwF9COdeHyGLdYgKoxwysPE2CH5H8BztziWk9QGsMvuec3-pVoXAQX85VxTCFszzJDavGd1cBm557ZCx6m3rUzjeHdTLuX0kTQeG24Xl-0cP3XdRf2hD8W8WiurBDOBIl8icWmXNW7hlD9iUnQK6lPE3XPn5iR3RHIvr3OZXBGx8xrgmGcf763nLK6_s1G9dNqOQSS2l1FDTpbjEaLkh79GFt8K5IDqI_H65_-n4tbXQqNM4I9UYbPAuV1SxAk_dRPhh5VHV4njsk639_-PFVPzJFSEpjMEOdVlZLjqidXd9Qm8TrBq2Cd2wo96W26n2zKpx-J5kSqt7NX0b5-24MGsb-nuoPGudCqrLfqjkYUBKIsWMQGBsCOM2mM-Br7rb9Ds5e3D95aiFdOsIwqgJvx6X8SRzbik9tsXGsgiLi90o53fGs0Y8dSpR7KUbpztf_FT3rxa_d1vemYEUl0vXdIexc0QrAm9P33X_JarlE5kW4_pfg6vMUZxVLBQ_POkGd5SSUNYn5_O6qnKvXDeuZ8qfa5HIlCVEBDan6H4Lk6qF4S1pl8_bIFyIsMtoUCVm_VG_OoHYsVDvmFCg2E45aac5eQ9sIrV5p0lex3fMicVOPzHVI7uIpjR6exNKujTDf7SeHckgyud_6ifaYkbFzNcuJcrea8eP5flDh_8ovKw_RGgxfU6_udQEaR8yo3enW9mIpYOScvpMLYG27Q6ABk7zDtotPRZrDKc3kwQb52oauqS5-50VQwhPrXXAnEzCrg--XjAy7vXh4pMnqKMQlIcR0xPeZ6ximkZVH17CwNzwrEOKZGl3mBV_Hh3FC3odgUhmEA71_XINfTYU-pntiZFSDwfC-TUWzsPs9nNzL3q59jXQH8XeCxYjGWFiumRqUKYeGcr_Tsd8gKKaCDl4MUz6CqijK88yV7d-9u8us2eAKzEwFHYOxWXF_yynyNbvbqcNZeqlmP4f3nvAsb4U-3PjFDieYLO9dPIsgjRWhek7R7y1Q5hFdKbL7-OdEFPc_Hnvr8j_8DK8ymoLB1KXddDBwYHXVr56tucDGHXRcIj3q8Hqqg2MuI_WSmfKf2vH4L1_Hj0nLkGUlzvvFJkNrUqlD3y7o44-Af9aQoIAIwfZ7onUOajw4MA3V8_bAqg11F9DUluMet4iCEuL2oI-aTgrnGKNBi7Zx6vUH2mtx18afiIlJSP6WnFMfD4gv1zVXpsku0XaBRz8cwWa0_8NCDi-OEcRLZFmzUU692cDnnFrevDlNPUTXOBj60A5PNWbAg7mw_zcuXYF2K4rki6LDPYsiWZo_U54_tOaP6nO-oVAhnOvPRP-HX3AdV-M8mfjdq-8iVXlvJ155sFruXwnFNea53jM2KzrWei92K16GzntuYG91_UjuoW1KKnuD3cbTwX0siZD7cu3NNMIMxVZO9VxgQgVp_55B1dZ-wx7w116o6pL1uFplqUaLH0cDt9-hlgF3LN2LHlRN09vUWup6c8d_cc1L4Zk1UNQsZhaOg57m4Gh_M9qfETbEU59PX5JNswu7u9YQDUOpLElsqyFCWUPV15Xu452Sq5QsaSc8PgKqO8hi-xruLYdCaKnjrKZADXwIeDLqf_w6y-hE5XrZwtp94r97uMNSp3XQ7joPkzm-m_KonzgERlZJ1lWzX5gv3jYBzjjoN2zsIh9mfXXc_s1PFljILr_6T8TEJFkIhiF2VL_87zB9ST07e2OLc-bM69ZPqQRWNjx7H8TZ7SU1Y_fxdOaTZPXOkUlVG5ECAiKzAjeuVhWgiULVrXo6HM47_6880i-qn_u6lF62MoV4A4OuC2n1X1_Nw-XRlnK5WdVdIC6-76Jy9QO-rVhTrsoR3EZXYpwJZtXo9iL4JpDM76pDA1AVuV0GaDCRY8O5sKcAe6vPQfroxxk4_8WLkrruLZrAGVVNd9WnVzKCYsdjbJUJq6vXG4VUdxnGS2Gy_43gqFbg-rm4Ia_TPJ-Kj5_Oh8fn5ZOQEk1UvQyTaOgN4WnnK4WL186xP3cc9d3QllqrpHUNSfUCn9yDMOSmdd-a6VKpj35lfwXMkGWCRekg99Ucyjv084Yh29e7p59kzevp7JoJgdeMCEBNl6vL6n1SoDh2now677w7Do3sKFXK3Pj-KWaJedfD6tTpdk1DvXFrGZWORY2YwW9VrX-SlH-2CWlT1Z85RfwTrSbEeoxpzIYHVsLsq5GlVe7_1eTyunydOJt2ZzZFdIeBdN0H1Av38EduYQIcoGNE0x0_pAjFpkopg4W7bvZR77DSVIr4evXurvMv4CnR7brdt1DlfVacoKtUGSiSlmvkGFIeq-pOrI87j14mI99hH_LXDZImJpxHjrLBWbtFPxo05zIzdr3jJkFS_lqMkGHSXKooev5rQCEsYZXmxcp-S5QCs13zJrHhAcefcwXQKtZw2ekwItbtqYS_3wgfqT4qKALgxLg5rBNfzKUg21R9hCde1Z0i1cK90_HUnJL3ueoBBSBh2BdQ3TQ7_H_S_idAdorL6R_KLpsE2Zwk-3Viyq56f6BIq9lw7upubKwtKLVH9Y-8F0QxTM9vFjIgXFkr1aX3YJKEuUDsnJmkL6WlJMEo_oWEaJ61K9BvOvMibgR5K3C1vhN85e_x6hkYLB0L1fL-o-nBH_dCsboDsj0LPiLo9MiejBIi7B-o7ztcD-TpiLxGf9wXZJPcscW0VX8_lqc__9L-7Po80GTY_uQALA_KwmyI5XV1xcVbNWP2wKy6WCo4bCgo58-VPwYvZPSPJGKhjdghf21pJwMa-C3cUG-U9wxMGtqrwXK02Yj4zo9Kuu1rd2CUOJ8UsuObzM3BMs-DxfotlTxgaGVzs-aXiNB9pQ7wFrv-aumd--8l2HmDFFlFe-jKGaWvHPLsTs2HapUser3ruCAA0Cnwir6RXBWpKVfWvAEQ7_zCGA2wvXm9-S3i6w5nW8xPfALDXwy7vKWUIVNKDJ5zaO9a_A6CUyByAqkc0UbcWz-SBonQ8wYvmTJcqTfj33NJKE1YPFbx1Pv2vxTBO-VFvVakr4yqEU7HLkvoBXPWxJ56Sd8THtPUNuNSswk49z6uAyOQL2HGYsji6PcKKPv_8Vvf-frvD0r62o_VRmABXhT9XRQddfebuMTuSnbA0iGWJXtbrpBG56MYjjIsNJ9kzgKvz6EIMCGluW6j4EF0P5FWpqkiL5Tl1Id7Coj8_l31wTVe3-1-Csa6qIvb8o2v6S_JZT1VR_J5vPS119TOTQvpaSEodSsX397hul10xPldmb7Vefj4mNrjaLul8sFDAgO3qnVPsq2aVYpaf-cJ6Wfr95_8ravY7M4q8k5lHd3jxYUbO4Er6YzjLvSWR7Z0MKERx5lItBGAo31cvYM30If3xTuxsi8_dtjjdDzxxXK_nZ3EkzfyGxQRDLatiZqDrWi1L-0qXgRUvxd-FvFMgRrU458t7vBHYVrieX3YQB4eXXNXrJeuysW09n51TrzkLuaUHe2wutliS90zU6l6yxHpMVD0xBzlzTLI6FEFVYyfm_qprT4mrzO84PbAaVclLWSEm8ZK8W89HdfE0Ph_bT3embfX0z-dfiz3f_fn8i3NYiD_Bpe8BKsGu5wOjqDOrItWXLEybeJ4PBuiKHZb3YFf9eQ8ioUrSh_-LqsW66zPXjwMQ-vNRPfP9j8_nJyzwGMyU2oaeZ731NBBWF-Dtblz4gX15aAmnab7IPmOHQOt5drefz8Kl7qfi7Oyd-Q7V18DM_3XutFLZYxGqNUqFGa_r-VwnkqjhGW5nhmfkX9pSeNKAuq6SUo-5FIoff_-hj3fWtAfQ7llvVduHqp3Fp9eupz0B-ersb9cHNrf2yqL2r5n6neGLOXN8LapX_Sz9uhkDY3-_CLoXYQDtViacrQpCeU2rYqgF7o66DKgeZVbY8fLf52mlvA7UU7r-vtKNvrlGnB0zqgqTDBiMukuZL92LA8vunxji-0w9j88_xtVOlHhmLq3rzmD6GoUHpNiRuKx8sTdE_0qhrCp7YhPkugbYrHLu8cskhrpvl3CFxiY6DnCRIFI6lwd4Nf0Z_gcpE_TanYcoUqHF4vLK-WYgxM_POUZDIql-7HOVvTPBvN5hKi1B8LWo1_VcgH0mBMJSw4e7rylq9I-Zn1xLoDtfuvkd3j2qz-z3PqQk2vw1CLriomUpLujXEzzOkPbMxO1aCCi5sYLzjNTXaYrw9-ruMs28xqOvv-eVp74009L_PAE3a3c1YHAi5AokhLSx3sxN4nJ49v9J_EQYDe_zaQFLRN33PD-kvVPVoVF96sdYQq32Dqq6PuL6HF4nno2JoVTf7_58_s0-EcgkQobAfP-5M-uzqkbdwu_aqkZbsBP7dlZDFvfazHYZo_t2XM8jH3UJ8V0910t993zjUfJk0kjWGqp_AxdYdVrHffHrl30Bgpmr4B5BXZF5eKZL9a__zf_R6z0b2rln-3ligBnn5vM7YVPteqOWVqjnIFDd2UrqYvX19Rf29wCQXX3zKuaMSF5jtcvYXiYbK1SIfOqK2iW6_xh5XWoHF3x5-F3ndwK64pI3XIqxlPko01gJO4f3l28vS_8z-Cu7GMVbQGXsWeY-Jn_PUZcnTNAtPed8W2kQoo2JzCv41nNmHMLfLqupvt7vvAECT2v2yzJyrEvn_Ieq9uIXVTnBRVZwULJiC7ivwdj19a4b6HPtrUs1wBLXIx9bqjg5pJI3F7OsZ5OpEaJ-Gm349lqsXe93-qnMmoV0rQvJenM0rsamwGGVrzELVLVnM-xm3b0d-WAiny6cA_Snvcvn_dlZ0PSm0sJe1Pz8IzbmkIMZcn2-NxjC61mp6K0uzLnoCFXUzET_EG0z6CLh2fMVpRbMqsd21YcYr32WfafG9QpOrvVobIOroiqWyKf3XEA3doUxZd45IneOWnd6k-sK12wpgU16fiLGYLlKaeIJvQFbc2ed5CXgSQb6588lE1flDBjPz-enhACZd9bw6TPneX5CXJ8ZSij4RAuxVfU93xSOUafPmVtNXu-e6LcfwfXpzVVs19OIBwViOfMTCcrzfCL_iLDH0sTeNFrJENND9fW8DscmW4K_J8VZIK5ESl3fndfy8N3rL_yqssP2SXCVdo4-gf1Ckq75_rIfrvt5_JdEHkHCJaVxZzBDX6b-m8l29U8CW8_CM1tPOeOevYaPwehy07-FnW8mgrQX8qFiWx6O8uZK-4Zvi8va3dul6bYINyZJkX_tjbPg7T1im0pgPS-DD9fP-nLNrul-Fan6_nOenydRF_3z451Q3RZcS8_jm14gIL4Mfj4PvMU6cxGsuJT8PB9k5i6DZsfZNs0_9LcT4qeexs4nYBUZDtVln1RnkkeeLvqJKdkH3hjLbzSyLK-rytrQQqp06cLinoT3rSHVk7F7Kpu1paruCEGjm7xXIO-rfvpz5hCUKgmL46Wh7tgQjZeqn_6J6c013kMAGNmszMt81ZmJJuTLXrjS7Zjf3-MvsE_CGBkvZxmYoY8KNwCrLsBbT-PYE8XkNY9Vf3xORyYEq9o7CuHxGil6o0wQcpt8f_9dVdfyHOuqf37_o55nvyfsuLS4SizGzW8R1qFLZB645ySrYb6nn0qhliut7osz1VhXfzBb9eQ9Fq-TuosLu_rf5_dTn-tlBHJHVj_PtU76nuq6saERsD1tzQ13qJdO-7KooxtMWfnXCxXX4ey5LsRXLCuPAaubeu6tOnEsfJjUyGtXcs_saHV1TSf_umImbkXBd6CrwBPlc66CabdKwT9EqyPu_0sF444LCIySs8gq7pb6nhs3E-16rcUE8wZ9vHkycRrmrCLXWGeIcT15LuI51-tZjOFSaCN_7XNv3N9NCXtFd5x7bzr-F0QasFl1xSDmfCcO1HE2qGxbm4Wlsei6azruF_o8-w3rDHUdUE60-urwQ_e1LAldei64GgpwVfrnS1xJgtmNzLlTLxW_s6tcjCU-dIwJTT72dis2IarCxqQ4Q4WlhHrsofh5iuLs3kO7ZSPn5540Y1ZRWAnqZ4FL7ItM2SbEMr3Rjak7Ys77LrzVtfaZZcvnUsSSqpnQLmzmFkPvzpeiutaaOYaTruD51RvssaQ9LbHKewU_8KmrbocqXlH3sjBfd-RXewZvPf_jf8_LBEkcBWL9P0EUYvMMcHcCzcI-cRnzJWezYhtN-_v7G9RT2oQa-gxVVFMmHAk5JfVbYfCOJSNF-f5zXiux64ycmdDt46slzgGJSBxV8p4EcHjXqjWSdUV4f38ryouzqmLROFFlxOTENzgFuBOA_FMKjh0jVITZveHYuz9v8ILjRMVSPU05dgSqZzw7W6XqxzMFjWE7U5D4Vc35Qgq32DhsRR43Z-pJ9MYEwFDX9bGvvjowO6K8-U6YizOTlOXz_a07AZ6qx3unxH_Ve_aGMpE8nJtsxiz6JVj9wDtn-DSqLncc9J7uLmWlcmxAJ-LCqhjVJ9tyvmGSJPjgAv-EAjsfh8JQ8x0C3t96Oq0OdE0ZCHOtbpUwLjVvWswbPRhNzFMwdufaJICk9hypcdw3u6WlZychBH_sIXXOv3coMXcu-Uazqa8EaeJs8LIO6qX7Ps_O6afoSNM4M8_zmUsYI8F6nvTG3t3s7fhy0izt8R3x62pFfJ220E9HNGxgVyae5ydQ0uCiubCrPuf3tz8XMbnisXt7oZl9LHiuVI5k1Yl1PRXKCh2F8VyNM8zSAp5JK2u4-4mQlDGqc_QsY8DHrAe84Z3snl3V8_0eSMmf4iYVcao_JHUTjuMWQknjnfnmuK94ISchMGt7vlX3GL0U_iqI82rlwVo7c5716xWYWn73RYodde6uiUCbfsWKb59aNTMJwI7sbkMvRBxxVM_PzMSB-7pch9Z7bbYvqHU1W6z1xvs9_jYpV-7t-3w8Rx2RKdgdAvFNdHrN8HTdTQo-11hcoH0xi9s1MBB03AhuEJiERdgLj2T1Ofs8z54DEvVEBnL-45dxphpPZtfPv5393udyr_gQ3Xj1hZJitr2X3vT0M2e665IeL1rIzfaxSY35PD_A4tymQvXQMuv7u093V6s6zJkrRnyl6wwgExfgRRoV1bN7un5UDfG5UUoga87W50lXvABGpZD-Jep8f_vzb_MdM8aME9a7iDmbvI6EhMOY9dlv9RNabCLfObvW92w_HyegJmOtTCDfRGGFwSc0K7bulWBBKPdcXGUI7TpWnXo6whpW3eg-9U0l3hXk9ZuWzVdm7xvc1A_MOYek-uM9_fNHs7B3DgpvJtp2WP50EH0HKb_JMzcIEmss7NNV3rCorpIfg9IzCTC6aICTqpGIqfDJBO8Mwtzrh4tP_QhbKstZanZ2JLBEy2OWZia5Dps8n9iKeTf2TzawnsN6A08uSXL758mNfHYATBKgQ7sK9Zza8fpGW1xJEZIEk4eI4hsryasomNcfLlLUzdvxX7FxVvil3_yVukWGv4bquTZC6UjePLlXWq6QAxMfyWuRf4nJt0q7oAl2JyZa17PjCtYZ0CGRLp69usqn3wwkeybojLoTx7bfEwzoousv7IGqYKZF7Ynn0l6mDWLrw0y2DeOs6uY1GS4wy3UzQ0s8dwu_v7rPrZGag7rj2ZvtoNn_MjuNz4izBmMQKJ_JVPMmq6jSR166lckufT7XhDk6fkL1zBk9l4WtfmamJF1OcpiBq-J-58X5Xd3fc9InzXc2ceYJmSUwfv2m6OHMdt8NDt1lhkw66zO_J_z2fv51JcuxFu1-cyvrSqx1Kah52oHk-udn7N_fCZXAoQ-cXz3Pfn_1xJ4Wl8l9EhiCme2nZ0aVaIXI04nFeFCSenfjo-vIcf_1v_k_z8Yy8WYXzW51v7OGkVFVuyO4YlClRJK-Magq7FaX54ixs7d3z7H0xOE1SpRrR1L3hm6pCpgtKZQfBr8hsKh-IPyn_yPuZbTjejoaHcPvfWzMIInrUjhMnimiqnZOPU1pvl-EVpXACVYiCi1g0yOzdRV2lLgoac78FxOrtuizIqs_5nVNqc4Vm3pgEFNOMOHzN1a3yrNd5fEbLOruJgdn48VAsYvznevOLymtb9Toi3p-1isuSbLRn-5PYIx6eneqQ20KliqGkaUfom7u-vvW7l-TVc9NIw-nZY_ViWr2npt8Ylf1o_L4aq_SMlJP_cseRwXkxWx40pLC9F1brK4K1vzWrX6emCQs5hDYhCIlbdfLaoNrdzdSk8VfT_dEuyP4XfWDq6X73gQ_smjP3NAjQ0JVzfnq5wf-4jXvi1E-KJtmTTyVqMAbt3ar58I5qOBkicQ9f3M6Z6NNjGY0B_3G8yvGJEW_kj6VYtPhRcZj7A7SfWZVLWqWfGoteOtRRGW7_nk-qsfi5-fP7-8tUJgRsd239rW_U1J8XSYLe10_P949v_98fv7sd34-fyKuMAFpNrz77PG3791RNC2gZ-JWabymEYy1SLF6vtOfJtBVijHCjf2qq_DdxcWU4k6tN_oUFHD26nIrqil45sZpX1At8k68VNOQ61ZVVb07d8RO7m5VBSgKTfr1zYjzyWBRXfjPEqB4J47BxlIUUpU43tqz2PXOTWe7oRxOJGLSIRkR9jVqehNtkDBFWW1JLKh2pp6PGOdvYaHnc7nn0dI0C3_DTm9E1W5chnS1KxJUG9SnC5KerksB6muT_T5cO24nQpWBev7AqOe5XL-uftKrL4A7CusK6bxw5dAmrecQVc2Sf08_H0rJvkXrd0_zEa9NJB8arP7o6f2e6pZZn49NQM_nX2v0Ey9PQPX7z-_T0vOMo6-gRfbDUvcTbKiqbzxMpq_ICDZRnNJTK2QO8Pt7Pj8_uHmp3NuZ1cXFq8Apas75_DzNvy5nzVtOGaLVb5XV3ilDXbP782__LVwyVjTel-eDihvKzc3UmyFIyRPU0eq2tU5YCwHX87kqkdBM4k9zu55CVYxWbhh3Vyw7u_tKZqvuvVrXixTQnn8YATeMRfdPMhZ9xrZPpJlYj01WvUj1-mz1E97OVXQU2dqZSlZoDu5xf54Lf4YCroL3AAGPpMLZ6ioW15dMGa_Qs6LqqT1TPwXV93v6eajQGdGhsHVLPL_f2zSGa1aBYyaLM1Y11Z_9TlUf4HyPSBb-ChzCXoyTmMJ_uvLTqzN8Wf49x07BJFF1Zm4o8KM9mwT0HCEssrjHsNXa88sS5lQ9ly0jorjfvYygjhxLu_S6Stf1LCXNtU2CxZ24IQUWxNkpNSsecVb09CXsnaxmX9jXDTyLJ4ctb2wCRejpnSXpb_I977jSSo24qtoz-s_45Zsta7hutvM1wMFZ6bpUbiDA0psHu0VWavSZzEOuwfr3qDq1kdj2Dq7onFLnPg3aoI7D1I5ZEuu6ggZ-T1KkV-y8zI5Dzrr7SVh4Pz1jsNiFpF9XclUaaz0NFKsSqYt1Pc9i-9MJM4D9_HwIqLo_D4BQVMIFHTvR7Q4BGCjWDqoLjD-LAXmnqkqP1K_02GSpfxQdYtyoM8KiVc_GmY0gfdYJM65PX7PacTVd3Dl4tCs7npyCGhxJO3OztgOXIP7pm8TZtYLUX3ISrrdEff7H_-Fyu8XdTXleqrheYodO5u0yQDjfPJpc56DqATnnWxkkeFTwLp_elE3CztHTYeZfd6pc4guT55wYYZ5zKtaFccBcc1FV5_ut2HQQ9fnJIgAxcyiolRKPSYZKaHw45XOdXK6Koh_wEpA-nz9rUJz5qnudY_DZ3cRHsDuSf9VrLmpXN86p1h1EqhQT2flKqqqrFKzCHBpsze9J5-tdFhmHUzF87z2X4R3391g48-kgsv6e_jwJkI6pdWJjzvrz-bffPVLbZ3d2zo1-n1FYV89DyRb6k9Ue57IdkzIzmHJIiDkNs8VwVWVssmypd0Yoz8QxbSDEjPK2UnGBhOdbYlguVbctnO9kUlS688ewl1X1JqLG-IPqwOpy7NLZ0FL0jJ9WqzIJWaL6nH_Uj6DSszlV57vAmd9P_YHvMHG_k3CWfh7ved9pzRmyuv4Yg7P6NFjX-v265iWM-7mKtPVL0sQbOhkdEXenn8_eKBX9Z9gTUbmVeWO83xz0AmX6_A7Jfv7YUHf1jXRR19j1KbCl4o6X_fyB-enHhM3vfCeIWZHC00_M--aM1GpWab43LqGrryqZUn9Is2q9HaFwtB-fR6-9fz81N6DI4bDpib8pIr8x-Dw_AYTg0E-vRgKvamVnWDq_X-mj2MCfo_7cMWjJtIT1ppsUOWNswp2gKn-_evoalNmId94TLfrUp5vvPPhyP55XmKHXWjTRwr5hk_Hofl3tUqer6mSunXh2x8ptS51seTUT0VHSesKn3DN3yqEYzMXnfXJ13UY6DMn6ObP1ed4xY_nmgwcFVvI3vztUm5EaEqwoL_e6HiK2j3d8K7E64g6T30l1gt39Z36f_hG9x677ZZC663U0iml4kdBTa0h6Ps94UVUqVQGq-pGMr6sfGNTznalq2lg8n0-pZpfd7gLU_bkRt92J04SwtKq6-83GTFxUzY7hUu_Oes5OP0Uv6kl4SLJmbaoa6oi_M-cg1d3B0oBo36jnmV2xySL286_PJkmMgDi_258eeEVVw6dYicgIe3ivu-WZs6kYN8NYD97U7LP2-Pn5md__qO7v-frvSdsV4x10e7dDuYgCLzPVp-4pt0vTG8OJVffOdhddcSywUZ9HKKnWu7NM9HR0eAGhF1Wfa4K7ISPs32PmihG7MrxCNWYJfc__9xVI7dXHsyIC85yNz0w_vrXDpWGs6YPneQDOiVgizaU8X5D9-cyZ-jRU7P7-80uy63mNTV5jRmPmQHq6a1-vDtaeTSrAzm8VMefO_-wNw562V8VMp23XHQFDBqqWW1Xf2TlTHRgteT6ASvXJbPkWQ7ziYHXBLseMDoioPBal17iHJZ1ZXDTkpvCCwM51BKOMVT8Vr57ELlHn-63Pf2f7dSzCX5S3RPuwFeeemfNKF50mA2H9NIH3LTu2OQgcEPpLmsm47MepJWOiTOASdcqbNX6jq2kMVzeMetE5Ehn_kvhBeMbQ3Fv43DxdQ_Ukwi_WtNcINDHhGbcu6E3Tn-73nF9WT35P1l9AIvp1LKR-ZyYONBjrrYxTVdSajE96Ag69YQ1JOyabnqDPUoLTUxtQEsx6JPUSFbFo3i2uKL-qQcxxwme-_xwlXRuW7ljInnP-nf1I7KfPWkXOzu9BPSA7IVeRJOxAmsXb7d75s4XP8yd2rrGr39muxmRmwezf2QAUmp3IhvH9pl-Nt6qxVMNT0RtZnmX1zAE85x89n8BZtJWw4y_0fCBaBW8G_SfHAnDzRj__y_9dFi7uoJdcPc_10p75Jtw0bWiYvoF5PKi-8JrPocRzlNTC2BWF2GrjfJPlUK9tWvFJqzKzUFibgaDy6e-60qX450KNj8iwe37_wS52qoANKdYgPV_u0lv95FEnEhhhJkZ5ree62sUYb776S8GUzverDooUm3ZVP7iSI0nA92ScWv0EM6vnZ77_vNyvyC_83AnhuTEPT-tumpvLTlVw2X565iBVRpGLS3jdCLZIFmywXkPhIt3dM6MEQOIwk-QdxiLuurtxxihJ_wLHoZhR8LDoE1RqML9hkPB2KRPeBffGd84rEb4L0esqCtxoRie0IpxtwXNSe8Ur7zqXJ74zfgjxrUuHIM-5Bi3f2SvICo3BAqZwHbtfB8Y3H0uyVPXE19Ke63Baj1BPNbF7tuvBozg8xyj6e0zxqeeTZgKLXdXjZakuA2Su2f89MTD0xjP-evrnikrwk70YQaHNiI5SSiL3StYQXfGNMKin_817kAjPBM48D-iKi8VQ2Cff7aa-LFU7J6qDnTVMlZpvTBnP729MLRI04fVTD4t17dguchcrOhPz-8Wl2IWwmAo8KkEmosjY5-m0NZity9LL-VwO1vL9FYD9VonCzHpOpHtXi54R3G58jT3GTlXZp0LH39v-veZxUVZdV6fgUojyJJb2a9FF0eBuIqXj1Okb6pMkGldkMSFT466CV2EOXi-vfFvumWsb74k507VbsQmk1iFwA149lQJCwgxj4SVuIu-q7clYxmdZ6ufxmfqrFYUZqbFEQvrYS6ZpcAYw872pk8FMuHHVuJBfPLw7FNWIRM-Esfo8fyS0Ys4oz2SikmAKLGf283ksI7aAlR3EUlU1_8suBKGnqz4B6Kolb2e0ueYncCGZ62CdXLME8mJOaMqKKU1iMQjp8ST0EM_zLA6l3a20KWoUSzS2pIJ2Z77H2nqZ4JU3rgp5PTfD7qJUwL_-fJK1zeLf9Vqt9LrJcfNcP_sqnd_DV1NIU8GZQo6OL-Gj83uSr4qo08nZQ7vjBxXyQFXs1cRrZwPKJSAGd5Vou-5nvcKGP3tJtbfGE7zdz-4KPGdyevx8HmJDuiBQjav4J2ZPUopUzcQnR3eaWXrRm4gpANvPz85eoqaB_hMlgMcQ-mmS96g37O0S1npKhlav6qzX5_WbXCAqCKrab8vwX4M7AKCTw9MHmyDALoGcdX0ezDdDpPgkBhFX99ikn6eNoSf3WWiTjAmmQj9O8gwKisuzz1Yc2a4V65L0VY5pz1HJNx4QEWxccv_NwmK0s0893qPrjXFAhatzge21uq6PNiBwY0qoxB38wXxhzhne2MKbNEQs5vLNrrBb7y9BMWOknes1vSvzOqEqiQGISkNvFlGsW5KcZpwQk1MCQFeMk_NzZ6ufmfmb9vRKDsNelEO1yJzzfu-_ySjjGx-VIkcA5yrm43Z8qiuW_AGDWOIZPh3LnXMG-x7sdxueTv95lV9mItn9ugPY-_2-jt6hg8UJbaormkMkCmAW0vPcusI7nRzYC0i50DHlNVwdv_-5QckE7OfP55zfgvt59rv1BBpT9efGeIH1_Lka7Krqp8Q9X6jCU6sqruvzSY6Bv1MPpZokLLPgqae8rv5UpgiXsUJ5q5kVRMkz9DWTi05v78E_z9NxXopG1z5xiYvExTs3jToBSUAgBuqhh8JJIE4Q57ME6l__2_9T-ENKNnNoHYlZGjOqo2v1fyUYMEtP3d46cq_43xt1Pa-ep-mtmwF73RoIEDXfkNuCJNbzYhXVpd2mdq6u942VEFnz6-qn__z5_sdvPwWQCMU5Gj5FkRYhtu0Qb9jkrljXVKMe3tj36e7ZRYg4mzSVR6rL1R0Ha9prltJcExhbqn7-NftNtTRzBZpIZqEX4DH-lmMXkmQ9z7-tN4GbaWGT8cTqVaT68pwqSc8C19Mt6kDGRY4tAdiZz-e_nfkHO319USIGFJPfuXFNj723Q8lSFwuU92w9xT2cw-5k6fkGx4RRuBgnjcPUGk_9sb-XKR6HuMXMUQjaO-TlpIKh3t_3GM6iDKnDVsn8MJyWeOc4SXVVjqi4m8ajwqaVeK3DwDlT3aH7wyvw-_3WNZ4QbrbIFtr1uTIuPXd8SYrxbDE7o_4oq5QRhne9rIuVtknst_vnRjrEAKg-e05iEhWnHNdTCWPmtXo2cKwqDsS6xVSat3U1IwxoVl17AFK1kbrmbtiVJPbu6OdPvEHi7myhnz6_347rf5q3ftQ9c254LTk3X3tV2u8p1trVtat6FEpu_JB3V3jmnK6e8887_82IZruKOxFbX8T6JWP8_sc_IOZ8qxoeQjO_rBSoSY8f2ZgDZhxsJWdtR2uoDXo2a-m2CxlZiqXPevWGXIJUtzdr7GbYLzRA9UfIoksMaH6j3BCujKhn9UQkl-Y_8XyxmFK8Vrk736mk0W3ERVsVvj-IQpRIAFVhMoStEY7CBvc2sPOfkbzV90bcWKFeaWg4wuTlA-NO_nMZ2XamtfTVsoaW6Oud9rmmqZnRGiW9owhdybLKFdYQVXyeJ0y5hKFuRCDpw0WSz-fPzuzZ_tNxNI0vyefzL9Nztj9hyhQ8HzWoc1Z1MwfDza3u9B64JNKWnvANg-x9Pi3QVD-tN31txx3LjqeICExI6umuIoxW_1Q_9Wk9a6B4fMJF47rEsiT6u-GYPM9n7Jlvpnllsno8VX9oFLmzNyw5UHTyGQ2fvdrIa0JFCv4eJc6P6KeTepaooGKDQ6Lqg7WAghIjQEB8Zga7ie6u6t1wi__pz0-67le7Ey5zqvYndgL9uVdVXCCB4IwXh5Z4vofVKNbznN9vuPjVnwR6YO_S9O4eXpsR3iBlsNP_XfC4PliCDbv7D_ZGxETLkfp4eWvlDKC8q6cdq7eq-edbn2fmED3f4echrJ_Pzu6YnQyjPzEeUT3HS9Z856lPoef3q6TDQibOLiVV-wTvTNoxYDP95A1dUaTDOxT2L_kqwLbqkXR25vfU00kdecm_1qNAG17bskclzLkpcuCe7w0aIWIe-DcfUCyGqipwb9jnLgwZq-QnFG92al3PE2J1SacvvSI-7ggKfoM1vSsWwT1vKhleFtOe-OXHFYevNyhdXJxAGDH1V61TULxzp2q9eipfFS_vYoBj0IeKB9BjDFnnLJjzOeFHFAuJkbo-JRZZNs5Wtc9WPWdMfTZ9IOMBTxpVkm-m05VQxvjUixji9xXEQVY15qQ89wKJ5qyy3c8Dm77y_rCnUNxFP9XdAYzO_Hb_zGyVWo_h8_1_1_NvRVzfXqq6H1FEP885R9DfoEiqMq6dGbKqAmAWoD1Wf0gVm0WmATCprnp8RiXshLp9ud8huVTFrSVWickBgy7ME__MuNbgSljK63qeq8y8uXYaK6eK5x8jtpOdGNAOzYQ8X7CaVZfiBe83PLZrlKWbiMr6_I__0y4iwMAkwaSdht7XQDdqmtdRAaiHfOeScTAFfb5erALFo8CotmcO1bOL5YZz3nXm-yYSOmxPgjrzOlAVSnp6D7p_mPvjKbD2nHqisTv8O2N0uuUhdcWIqk20RVohQ_UBPztnz13_Z45b4cGgKoOfuObXtWS5UU1r7Zz-87Nr9XMxOHbxQaYN2P2e8J7VBWmpzbjeokvq73d2v4xqXs8d6qKMGPrqBViDChSkGGIA3DX0YA6vYWob3P1i47D5LV1sMBNL6WOg-MCoFjxJ39kZVWo4AuuTYIcQEk0W-hOXaCVV9IZxx1N17LNXMBsnClUR5xDwLEubKwdXHRSS3MaxOjFlNxxbkA2cM8lHhqSWNxi5ip8L2UYLzjA4kTyMXXzqQ0Os3al-rkWPTWlmwQpGfukE8SSFuVvPh_WcM766xdSccr16iJtFUnmOBkuxWRSYNNXrYNSUL6D1eL5UbJjdT2bU0dnmgL-9s5RuyhnoZUiN0vOvD-B6aHAS1V1SNVUobUy6fPrp8W7uFaO8sOtRVZ3fqY5s68ZHKhxY1U1vFb_nZD7FFPdJsN0VWXC36EPq-3v9N7Cv98RZdfng-qItBi7csVvyK0iWPpbnfBUX1u-5AT-XubL0fH__CXwt6swAc4X43RDs1WuAFkZ1Sn2V7ORoKlaWsVi2gWqaCRyNBOOKwEgxphaLXQQvlGRLiYwZGHe4_9ai4pWvsl4GhW9gTX7irFVilMpvxsklQ_I_CbjJmQO1Sbw39FqjJzbOeyE9vtoDz_xNxlExGT1SVyF-nQklhHSuzQZEmWC3HSmRrhykar31PA71tT-S-Dy2P3_-5d3n-VMt21ECpLsIiTKAHFT3o56pp1l1bMM5AOOmoG5VUWXjeR6YVR-oZqA_nzApunS-2z9dfWF7i_1zGfwoMQ7atueAZWFzo7FAjSfT-PZi7QIFPh0KghTaMEni5g-G01I7MxcdWql3vo7cAj7_8R-xjAwbynY9FXuczJh5fZCuKg_VwfOruDNzjoQMasHl9WzaS86-9JhQHHIlC-uqPt_5fP5l4u0JEW7DzFf9Kan6ATjYGzOVMbgA43y3Iow25krCc3JNLM8Tqf6pn_E30hrFPSO5pE3uVN83y5spt6xKLjTfHIp-endLUZFmKGGSZwZS1R8kMy5OXaGC7yYQ6nx_Fbgjur5-9gxUanWC4bnRiZ85TIhHt-0ffRIpBmOQ6kEYYKY-T-6fHV8_huzNvVnCvi3Uv7f-FQed_MvkLZxUbx9VaoXdGB9J3O8gpWTVhc6wfLNbruaeFXMXem8Ek6DWzrk5Hzd8K0mjRRE7Je7Orr1bioNqyPD1svw96QVvsX7pshlBJJXSCZ8xGFXoDlWY78UIYtEfx2xdSK-6d9YKs0t_1eTYfd8lMnaIDWPknPHniINBfKfsc_VRaTaamcwkECScnL_P6BU5Xx8ZS3PNcxSCq8fJfnnZUAVoMg676eX3MgLM6I4oX1UMpGLX5OTHUkKSYdIbSPYhWVXVTz4XwQC7mRiHEI-Zfv47PWjuWJVcr_8Uhl9hZIIaURuSjVjdO3wCF-6KyPwqrGs9z87EImkNcpJDOjfbURk57muUUn2j5V0hTPmc_xBqvVnNqMdz4mprQs_z_V61VT6eAfVPoDJWz97zhMjY2m89-6D4_f0nmO9-RwIL-z3VH6nDNCBRz__4PwS5BEmZkcmp_jlHRaVXVV0F3TH75_v99-fz39dzaZbS-f1VxTU6IBVnB09_z2-87TaOjF2ZlUUR1Pr5G6lT1Yv9ni_UQcUREDSsEmaQKpXO9z9SHvOKzQsv6zGmk6onmDycoMSrQw1_JWHppNiFCv-kFduTSOd3PVuf5zraJDqj2_FfXXye1-Of10fPkgV2ruXCJny0yHrq3xbeq1akBIce-lxoUGreNMGCc2LXvsGyezmITwCbuIVc-WCYJZWyiRB30Z8HF1cUfOL1SE8wWoVSfCO9Divedv3uUJkYb6nHOzvX20JU6YlRKbxzsMkuxs2klMBc_-kk0c8P4Lo6uSIUD0d2WbK39LGnFJZWzvWYvCbLfUB6ObsuFXvWKUS8gMOFmH2PoUy9-vO5z8Twlel8NhzxEnJQwjM3sHNJiN3Pwp2uIAOw6PaEBPrsvRw15-jpuC7cBEMKSFzUhES8E0dN3YAwup8nYtl-PotNMEJXX0IoRG9_GiKrzu-3fp6UsXMc6l1Qa24QyyJZ7RY96zP1CLvdtVEMVMfA_tPPfhONGGuLVfV8fz-f3p05SwHtM_OpDKNvdHxVw6znQZAVO2oqxgEqpMfnIaa7ZbyMKf7OP7F7k01MGMpoOsYRf8NxQh4QsdP97B5UxaMgZmpO2Fay26TXzizpHKNusqo-FwNU8S-kRM0ifM09cYX_6xddsb_mrmditWgb6hs0EcHknPp8rnZNBWk8u0aHYhHfsHjaVoRMVtlEaRevjF7YisHXlcze8fOSndo3DhYxx6QSGBSqwBt1mrybC6dgduMwG6epa1kFUD2hzNEssTocWbICqpSep3s84-1cV9Lv9xcGnitLsaOKRgEQu3rtmf35-emfB8LMYeezaNOkxS0uwOgacHWZ82ah7udfHxVY-PzbH0m7J6THsKrq88w5MfSIEyj1UPpnjp4nhE9zoYrL_s_zrwX0xGER2MUkc5d5Yv00q9ber9ff6-WVObDQn-f888umd7q7GhkXAIl3Ncldq6XgRU6aL-dAAjde0vS6HmFP1Uu1f57xvo0TZ38dZ6YxqrgofQY29vPzZ-ZQmnD_Kjoc988f7FL6zgmNxBFfCgDn69fhHmhZ98ljprvwTlHyGnYPaQ8IV5Nelf46uZCk67JRYFTtbwo7wcIdB_XM8esAPymVQKkhRfwFLgrqEL32b81amdNqxU6bvhN9jq6RL0HiqY8vJF5XJF_l0L1Fe1lPfp0IcpLWhK6E__bnT-LAuMm5rF1U_cHNCo-wMxflQBAW3y-wYNISDiObFlGZAGw2wX4Pi9Wdat6z8ZHk-lV5-3VMjU-cfXyTPbrtQxvXjF9JtNf7CiRRWCbxQxWOf4TAqGA12POya66HY4S3LqKy7-r1m72MLCRvIZp5aWm3LgMs4-Ir_MpFfCl7eOsM4I50_jo0MDlC1742uZELab5mV6JxrJcnQe5Z20SFQ2jEsfCmlF_2Zdf11hQHPmMW6qeMO1O-th9vqLZz_FZdC1WY6vAq97sVe6IEWm-GPrqTmZLJ3_OtTxP_hopaIyNKkjzfb_80WOvp7ixysL4HbF5n_eczcI5Z2BX1caiyANmGqz-Zk5_fb1WlP1JHEsmJsJxit2l2046lsp7HIfaRs6dL_fz4uoVa4syB6F0-mTrGNnAEGjpjPe0d72TidO1JKnx1ewaynjKWBX2exAiPp8XEX8Tt2warvVN__lf_JwilcqZ83-HTMYlvKWTWGLmzKv5lT_-566ME4Q4wbnqoSWDG5GCrO_6GccDzjuB-nhsV4XMjx2-0GYNm8e_1Ruw__-h5TKubwJxTVZ6VMlH9GX_1hrEEv8kZx0RvYOO3MLv7_SdUEaktePfpH-1extFaZvWPPfo84Ss8z-fC8N6LlTJB8Rs51E0b8zXHhUk2bhCwwj8xjp5nb-EQA7Vo36OHJd_Jf5I756i6eFUPlpQ-tch6EnTKM9MqJ9sIYRcEAClaJnD-32J7Jjbr8KJShUU_Yie4LY5L1O5tl2emq3Z37eqHqkhzkj5Gky0DlR0a1fu1TiWqYKaqi9Ga39h6JgBRjOyISaZkGOun-ll4vF3V1RljqYpPRwDSBa9LN8I7qRRxqlF9KJ7vdtWZ6eeB9P0Oqg0bXSWT53z783M7ae_TFYL65ii85musp3CGxTkTP8pEs3nONRGKtd-s-knq8DI1D98pmdKenRn1c5M1Y-raHRYn6kkL63V_nvM71T_n-4VRpR_dwyJ0lN_fr-nqn2sNbqhqfr8S2MkR0-yCDbGfz3y__Xn2O5UwvvDCqmx_Pr3fU_UQw8V8D3Nrd61PUuEM6tE5k2C43BuxDku-gLj7_f_SvDmjVXsGsD2l8ozMOIWyMAukqnhNwyjMuaHtXlfwtbUANu2X1q_y2b9U7hjGZc4TRg6srCt1wiuuQCOMC1YYOr4YTKilrxAH9Z_iPBBcVLc9rMczepLjgfM9Gc1eBG5fS7jnwfLpn2tYDIeNxtgrvLaKcSgaz7WC9ZSkkvcbFYLnGPZObD0o7vXAgXKfvamivhgBSXZXxnMkivUiAgkp_rNYtSxIzw4_P__N_o2-p5-f7t7d7l4l41LpozOaU9f88__qP__dnqc_1Z_5_Z5zPK74ZlDdQvj2N5Jzu9Qqn1NFvRdmmCq2MDz__k89n8rUE0iGYzI0dueJnENauJ8fsbq0xypUP5RkzXxDaVPyZILzV9XnMXbBKr2xSkAzYhJc4rgvTDHpD9Y7-jzeiVnK1XxCped7TkxvVAVsPSXgnG-V5nwjeQ-B34bUu1P14J3iRtBZeqLtZjTo8VO9tmnY74Suc10Pd5j81WqD_XnONwbB2mimrwFLahAaOP_xfbp2jmNhXPQc77DiYU_sub7vvlO13aWp7j2DG4DIekos0NU_Znm_mULg76WkyudGAmFsMsx7-5zIyUKPse1dnJOYWXux010U5rifn8GKWt4U2dfWSbFL3_UYoTl57GOs9Ty0q3p-v4ZmLoXhOg0qMSzOK65W0hvMlfDhY0dflPqE3vlLObsTxb24M07ClYXSzMTRUhKAkkF7tvo6pF9s8Vacdb20w-O4ccK4GeExKb72XbkIeFNBnHHfBZt21wKvpYAuxelvvOPVUsS0uuP0ucDS7Jeym0GEbxr4jRm4cdoZfMLjp_61_vqmFFuiz1f1LDYRafP7BetGNEZCmQSSrkh09-rqE6A6l3QZiIoMQS5xs1SolZ8932iVzhm0LvQey5MiKKirdUfwwM4EQr4uriT7568oXGFNjXPs1_NgN57gqud8T1fjd0oTSGtnuSyShUgXYzbLRV8ZTHwyJHXS2Ur0HLFCHyCw1HFIUikqSPb3-_v58xF0Jh7dQRhRVbGrSg3jORhTZmvO9PPsza0vxtL8LQ_uKX89Xq_CwS_wzRuhEVoLnn6cNIPbMuEq-7HA7gy75p9_CCQ5N7Yo4_-gG9TeTBtU_0__-0SyIVm58qc-u26R8y09MyOy-1MEYuLP7X5sf79HRoR1mJvNnpljDrhiKE2m2rP9n7H2qdERI-AMfG1XKWGTXtwq8Cr2es45Z0SqH3rIHCgLGMfdYl2sVs8T067vP_-USkFKJNbDlS9Qp1j3XMUwTLG710Pp_C6o8504sGYLZXBa17RKGW9JNbPX6jEip6R8KG7IKYOCW48IzJAIlufZGyj4_VU84Om6MqQ7u4uzkHeres6pfvAm50n8RB6SunODPhoEBvX8S_V6W2_iJhFvn1s-HddPXzvxqqq6kp93CbY6My8QVc-cqSeJFQ9skZ7jrnRqVZ22gnd8rJsnn3wWFbyzA9Z_Mikl7-hRvHXDPBPf914P4FJhJydCdKIxb408g2A_P7PHMboRk-WRxPIw_B32TbVUwMLyoMANQ-m6HNN0dyvg4jrohWDs6crMt-71fk1GbzLOFS0zzSeSVK8ui-ouqat___kGYX2qdsAqxSXWVj0qGVwZ8PN59vtN_g1SK0FUPZ8fr_nphCfai6F39mtQ53eruxszHsdURIFcvNHhaHd2vmkg9mzpGU_FsaGaxIwrvY1vilbMqRJKlW4Pu3P-A4x9r5Urx941iQK9yz15xYy3Mrn0X8FaVWOGFPQYU_WzXjneuLuJpwOl3tj25UCR_ALwV5tYz83svMZw0PNJI11dgWPj1SiV4ykRpHNHhL-54XXvyZDy4_30Kltj7Kg4fqsie7g10HW4H1ahQvxVPEpD30_TfmfkJlmYaRL2fEf9YJfyVRq8gSS-UaVXNsdcq76dua6rX6USmnMMsFhdRZbqeT5JrARRrEpItA9lPT-BUrP3W-GzJimoSoLQkUs9_21_9_k8cyYe3t1P2KWA600RKiVC2lEeiyLr83xwk4wI-Pn5V9x-nuePz-6ZOFNSdbMg-tndrudoLVXrpz6LEfw8nzja8vZSMTt5EgEdcVLcmiA-__qZGT2Z8vl6dEWfPV91WRulwWVNm_4mB0Dz-80FodLu6c8PMP2vTygc9s5cJ9YLOJaY3Nrw_K69NY1NrfDRZ_dcjYFRyTCux_G53a2nuuoazF_8fqtj8UTvPF2ilmA_hQ8Zo_Q3i21PV3m-Vfr-M5L2_MJGUr19WYcDoRt6csLpGiFcY-Ib2LDCkqpJcJfoQamqnrtdR9UfPg_IUtPzXhdIdjtV-P6qm_UxwP4kASSxzT6GrKd3B6Q9RK3dn0dkd3lAs6sXO4Pqx_NtFWTuFCe-N1U3Xi_8NAE-GewyhNKAmjFAwo5nFscxajtfiLPffj6XYRRPt5QEMff4G6ohhQhd1J6T-8FD0KD1Evb2XDAj5YEz2IkrIAjtTUfnvInUqSEvYBHLVzhCIF1ZhjqtYxrnN-kgzGyAnHGe-U19jqzoMjdCu-iAtpjvHYmSnklusBTH-iMmdcZFFBAnIqnnAMBTFQ4pIzuaGKyZepNHYUaokSw5XhkUKqKIN1XdS1rSfEd1c3vuLOg2xo2ZXX3P_6fqz-6I5ZndUXU0Xdfyw2MVKy6F5tpF9gNCzw0QIFz9GGNtS_RcP-4UWIht7rdK6s-cbz2VmB0ALNUjhKnUJJT8pXRiXRkGxpxJqjLNzHXPxMjzeTrvNP5poBWfxxsqfSE0UfXp88_35_PnnPNmoxI7ZdqjzkzZykz6Ld4uBAmrlNzm-nx2J9b2MLs-6zPny0eqCHZ4vqNPiQPa43o-6yM-C_L53A6TU3_-t_-nWGVGVh_spp7rhTDX99r0xqIRtGyAZ-Z5muSeUSkhAEkG8w3k3rpGs5eFS3KuHCqnap-zlkxJ5aTX3ZOF7D-wZVW1KZP1eTBHAPZ0t-e8KcfMx4P6ToWAnenPE-PDKymG9DwCWgV4vgNbaoJORG6M6kQQ1T_1dCWGhtHEGhT7WSPpeiyF4lsVzZBS0yfN4maF8DXlBfe7NxfuhlZpzdntPx_AQsH79FtpXtusyO0nQzF7uEhwb7EaKeejrWSS4a9ABpds5iCdT2eqtueECKqqM8OnmYwFoHnjbXPBYqek_Z3IdlW139OKETVjoDwgleSpAsvhQcLzdV8uPAU8-hwPu3NiUDpnuh6T64Uesz5dLXLTpoPSbD564_W63teI077Yc6yo49zsPVG3LMhdifP77aBfVOwg9syNoPr-sv947T2C9Yq2mPwquOD5_U0QIBJ7pxsCdec4G2Kid407mDrVvfD3BUevteunvO7nM7v1PGrtXOF6NGQAf3__wUxiA94wGWyrVE8_O-Pc1U-f74mJr8D6VC787ly6PyhmyJYkYL4wUx7X04_J683a_R-e5_OJvK4_1yC1-5Pb4kzsprFLJVUDUD8AbjRHYOy16bp6jDLWC5S5NjnXOimBhLEyWADGgTR7XhoHANbzdD0Uz-_egF5e6ufGpiwN9fOYPGOoOmi9tDNV1wKpq5M6V2_SmWN9eybi8Qu-wjPDXeqJcTC7UJjvlPqOTi6Dv_Z7OmzDZGPz0qE2tuLXkignD4IRxq0_A1QqYoOA001MtniMeTGHbNDdPxOosP-GARVvBvD14J_zraeJOKxdEk_VzyxY5d0_P_9iRvdpyeA903cggucJ94mSMPt5nrgaCtbToPrPE9vVcLux-_TP9_erTqN-n0CMsQ2wHpPP52f25j2rIoi1AbEkdIU2AD3FWxaIu1INDqPFGpLXVKe72J36frU_9QkL_Oz2p6Viq37-xDLK95SrW05_z_P5Q7jU6o-tnfP5_HhPrGZJ4nMlf7f7_d473t-vVN9__vmv0UIUc8xMnM8BsDPNDqsUugz1GEmx6LjEkKAVs905N6HJl9my56tXSL45D5N1CpH9e35D69idM4sOpJSOaLARS1wkinTpmd_fuOtaXHHW8cr3G2qqR_v9qqT-QUg3VdXFuO6IHV-_17qku0B9A_YnlGryOTcBI6hif1L_xU4A5Hr1fEJzTXAeukCC-3THFKcAe9h959ux5ryxVGY6g792n8lgkgbmFcUTQtCpClc--NWZFpG4OrLU-NC88clJrjJQT4fl7lndyOawYpLNHWbFucwKWDTOOOSTW3Tnv54bSeFrpG7GljWd4f1KRl6S3KHw9S_YHcv2jR1y6fEeLBLuS8mA6mPccKMb3BkXdeybLsbY49-md09JfjPjbjx5xUIwTombmSWvjw6h9qVJBnKivbQFmNgbp7jhgIXHEX1gbBIAXrPU0mIxg8vHWhav2f6MvdeCbdfmnlU3JdWfAkHvOYyOKUo7-85hns_GDiaJzms-xQXYwM5MZo5V9DnJjJXA7rPbqpntFnwu5cogF6gkzql61u8KYALuyDuFGJjA5_OziyfO7ABU_9__-I9PxXJan0_vdyn18-ff_-M_KHrPnGVXVJEevxYOnLPVHzVpq2vjouPrXHRd6Qy1QM2-vqvheJS8o00vZ9jnnABrnkOvHhE832-oJdUKy-PmzRf3jAE9z_n9j-rGDvbU87_836Nu5PxeR3zaCgJybapBd4qwG1O4qzg_ZJEAe0XBEqikv3bLY735Dbf2qz6_maXSLBbFXmNmIpomGDJ9FPrV2vlC17WDiZkg16hSsfds6DLzHReXtpfoS8sJo2626oMDtVqdFK7Yy2BpQf3jWRbr-cDuz4_nl4szX6YG9ao6h2A_vI4dtpPZBNeT66e6Gx48z-xEghotrBN4noah-wz0KYqreyUEeYzR6m5CjcsGSutRdVUjjo1G6Ul3zB2ohrbaG0PeYQwgO8Z0r43xLT6Y6ND7JME1CVfVzFR9do69peQCpkwIGfB5NbJ1rvlPjKNQEs0D__prs_vDa7GzRNT9Gnpu7FJEtsWbgyHoAyTN9zLIumtDMAGXy1LnU8QN4_MTWEbJvNA9LOhT2BtadkIYQP5AYL8Hu2TtnqoiO1YZfgNhSTi4-u-XHuw9633PQMJHqjmregJhxgW1-E5zL3f5-vBx96nP-R7RMfnp_mQALWnG3a0uFFx6WE_8aYCJ-UzRThrlPD-fe7nO4VOIhuX5BO-sahr6eeasur_nkM9dniVcC2uwdNVjUj2FrupWxcSmSM8JgzPeS-bzLH1zKnbeoExCZF83_T0bdmkQ6p2VridVuu64PdBQzLiwN4Jnr6Hd69ohX-vPWO-3Mi604yeGRRXJYiZ9oLrz6urpyAbif5TpQVJN0s-_iZbwzkVukdGhdaNmfb22oAXCNozphF97UPGF71Ans8Y4hWX2eo4iFjR50QTZnBuZErspeo9K5lb6J-F8Tyue4ynk1uQMb9YcxHrgjZ2IRc_0nz_7PTFPrXr2TGzaE68OV14oKrbuh0wgnyupIIpNqkD051kvksmQAOMuG2zx0dPt3xE58-1P5laFElBjV1U6G6jZNefbn885Q5WKz_PZmOeO61MshT9kQWzFvjf2uD8_IEr11LOL5_lQmssvLVQXy_bP57PYeuL0X12B9NJoujJUeUdNXkufwSYlaV978Nntz086hV3vbD0vjT5Mq92b7zwxhQfW1T-s_KGL74k4vnFUxvcXrBI5517hG2EtMOvzPRDewd1NUJwz9TyJ3DNQ9ewuUV7W8yy3n4cs1NbPk3Ba3KDAEKO5Zn3-Z_D6fDPvjP-QqmbcUlcsa1glgqlgSWllD9OZiQuLNQeKtWKqnyqVTIcIau75_gcSHTdzy8puVlNlIKn2Wflm0IFUv5HqleEWK0eILD6JnHkNWOfpi8ZTGiyVcG6dRZdK-s6xV4WSvA47xNbl19sxomDiWRZUUgUucF-q-R4qZdmGMFNVmFHLr6NBUgpTfvlaw97JHF67yb-5bCye7_fm1sFMAEQCrdZXlB8IIwoheHe6OgkSuPPs8JKbe0p9Y4OL1BMPFoL0VWNHOu-N2QG5F_gvlT0pJHLc9tP0vcTYZXN3q_tS869c9v_H1B8tS5YsyXWgqZq5R2TdBjjNASkgGhz-_5_xbWQIoCtPbDfTeVCPvHhAyxX0rerMcyL2djdTXYsj9YyXli6yt-0WLSx3Aq_s7bLMcCW-wWtvCSavIFbTSv8ecRUxd-pjt4bu3CAkloPTiTmgf2EulksKVUYGnHcP5l2biFcuH1x-sU3lIiMepVk6XDMTjPk2NcjLkEdxRlmZF76ZGZHmX0dc0FbeBES99pWvFGfmSI9m7wuAee0NqfZ-Pp1lZsB8Pn_vv36ByL2y6lJhzkTEd6EKFMcNsPs6sDa4ns8JyKXhCDTi6X_3NvgyyTJHig4gbJuBveiQF0RjRLHNEx5yOIzqTK9nB5VY6-45-2AaZK5__bcgUHueD5k-93Onh9yhyQSKj2lo5Hm61g41Mub5AelyrJvEuIdQxzHHzba7GEHemDtRFy16Wa5egiMFRKzVPbZuxYyLU_Du-W79fA24N_f7PxHIbKnWNrGP5njYgfrHYfQ8XzWmq_bKygmETpY3dCJTz8fU1dqv53lqM6RkkWRl9Oxc009W9UxWgqI0BrzkpYIcnYsnb2UtemOg44S9C3yKIcq7dT2nFu-xNoPEdN-G_RWvqPLb2-tR8gt2NPjBNpHJ9XJbCSwdWUrvdfPlKLtJl8sQrYikcfjMCXrHDbCK4zN4-ucnI9U96_I6OsCsnJ8f1s3kGDi41oK-t09RBAoRjvfKael55j42YjSj0cCx2umA4e5W3tPulbgBj2t0AgU8n49BDDOip-7nbykyy9N5JvvcCrxnaAEk7Di95r-0CuccIOZ83CYJqWqF2hDiENQHCXD1aUY41Y1vZsnvUeesHGOztWjXXrlm7hMpaXijUCUNI-a0XWmMmvNEBgNVqYhEgrK4rWfWeqnHaDd1hOEtwP71qyEpVpVikCRpKzPJoPqc_Mbb_NlILoMpoy_UOXqSOT1JPp-PpX9fWS8skoygkk-3L-3wfeXusDHngIBO4qtryG_ZxrIbo6JGEJkc6X5iq2LdosiXLB5-pMCJbdq3h9sEWAuO-lg3EfL08Ua5WSLOp2uxx2RefVdGZah2INLOI_tZHOEN400vH00OghWJW0rRjPOyvn_MHG8kYCPHHX9EkKcHmVe5OBM9HgszNMa-GlfYx-fF7-wj4H9RRNUKp7oVcxrJyj0SCpirBfA8NGtHIOs1EQS5lyNLCpx5EImqZE73wDn7ysrIYDFBJM9pZg2lQdXOrOkmUjNkINdQ-Y2Ds7bnH6vqlth9QqjtW4TGGKPY77fO1F7dht5DULKYOaF-nl0L1ET60cFRlAnxk0YMRdRKG9Jz1_0hnV7LGZg60q6tcYxv_AgEA4nWw2Crn-dTue75RZDa30F943TWvsfpr_3JCtR2BslBel5sYxB53NRl2NYpOHV2o_OZ2aetkD1u3RHJmNatqkusFWlQt7uPdwzsxGcQzrBU1efzkMs1mD5nVUYPsgJi5qgjGhnq-7b2_ecOEkYEOZHfPFsIYGTmfQNG-pRLkJVzDlH688qOO7abczjHcrjvVZ-BnBFBNz1ZV0yWK2PCLmGH4x2uu7x7l6q8qU3oK7gGUq2168zokiC_QOnE5_NRKJNxbV2IsPkVIM8cowXmZrGCSehC5O7TKUItFEOTnv7ONd760e13HJH-VGjaCWnMzV_5RIIst5OdjbwKKIMqPO_z20X6ovbYintSzi2p6orGb0j2D0NDLZm5ncI3kzRtHu3i-lIgrnjAxwCH_PgFed5-HDgX9nrdyZaZBBRyKtPwSQRGX4Wc8e1zLIIYFucc019we-IGJw-v5MrzuvRuVuEneaoP5sb3mdl3OZDOsstM0gs-C3zV9b4qGOs5lyJI_XxumMIIztR40-4CtIMV0wZL3lAGBGHgM0bqTNXyfal7FMqsRiA3mblWn165fep3kHiumu37PSJ2Ll9Vlx0dDotlArNf78_n8_rrPdN7lyyIC0wrV27aDC3N1N59Tq7lMMfOClm2Xec5uTJiBE-snDmtjJr2cCdub7dFj3X8ZmnN6XsnkghKzcsrCt4tB-77KtM9pbgpnXCePH_97__XCH2OXMnM5F5zGgn6oQzEyCKrmb41CMMir18tpjX8th5jpudaGG7BPNTG8Of5PDGQVLix19HJSlotDV8wls9tfrCKeboRClLdBo2GlLmeT5NA7p4QItdWn3L0maWeUGSlJrCq6oXKQOYqhQWjbfWlc9zJd3fXVcy0TR-5qs-z9-uWpBvgPufHKhO_L6r4dGO5uKEER5Mru5uZSMYMy4xzjO6cNUHrgXUVpXXVpKD3lSiu9Y8_v1Ri6EmDseiZY6z-ReLJzmWiXcZwuDHxp9OGzOVuZK7VrcrM3P2c22qorUD3iaxABsVAViKgZwzinRHzNXNInxCladNhbJMormsBg5v1rm16lga7nyqTGHr4tItG0S-Dw68w3lpnjwRMUJ4ZJPrpy9KKONHJgjzhVPzztV6jUD_OjOZy5rh9ijdzrc-JpB1eER0Ssv0rRohBtQy8n-OUzfxTDPlNW4Vh2KSMPIoA60zXWjFaVYjLTRXDE12HzAT2OdczxZSaZf1dZNaq1b8_c-YOml2jbr3eu6cR5KpwfLeIyu4O5u-f_-e-vcfXG9R6jbpqRSZCq7ZOE9ir5nmySk7guG_AYIxMT0wgosjFrWm_FWYiF885q5a_WebVptFpZjkH5iu6VkRrznks7YpvIg4mVGnsKMhk90HWedpFG5fW7n8RDOZ8Z3FmsWMcnyTd80-DOy7B2dPAa4O8XNoJC_H4EgPBoV9mkhQ5rIy-DsW4cONsqaWkn9T8TiowrrhAFzaqy34Kv8rDjst0xOhrSrlhwJCuegaY6ACpcuDOd_txS_B2jvQlNH6zB4w53ha6B5Q0NbfqTLOW0Z_BCkJC5Svr1_QPGOASYq3NIHP1KJl_7V8TqpVDkYlaM2CwyvvAzMxuodbEZARZR6NQepRqr3UVs0h8Pj_12lmVlYZ4RABVXxlwZFYCxXpCuTcRWTXA8zFZ6GKxqkrdBow69hYiyM_5CSKz-jSr-jzPtC9UUvfnRCJfKYWkrOxzmFW5MFMrn24wRh0TPX3O3DrpBSXfSsboiRHSXQv6mDghn1mNRZ4z688vOJR-OZ52-tQ6wXsGMc6MpcqZqFr-vghUB5mKcKElM1mc42FOmCfIoqQ-x1nmO_aO9lNKwEzTetQk6BdK3DYsiPHh092VCn_Bc92-geuPr1ercS_Z8Y0nHUB9DmMQbXWsUUQt04FWEtN3JGf3xXRQQTi7x34aChvji-ifT2StVXKqAcpagUCWTCS2ZyJiegy9AeS2w3fYB4SYHOg5BxuBqJXdLcSfNkqc8V84Wbc7GwRTlzfFxGDCePuYCKZayTo_z3W7mvaLP6U4T2VyugkwCd14hgfzDBN6Sx0aGRcdqPkGce7X_lvk999jLsWWblKBGfASNUdhsqe6c71m-o8RxSni-HI7v7Gx73WnBzf0qe4L2oLdXjfXPpTUH6ePsipi5mnczdLctcz1o8W9Hjz2wNyQQ0jMdR_Lt3Zyse4uWAO8wbzrnIZpQfpqDfRHFHc3CoPKUIcAJq5gpK6WoV46cznOILm-dawthNSjmIm1l1N55i8wbkeMma0ZqXb1c7D2-Ryy_CS31sPUhT6zLIENnHOdMD6UO2kWBgW7H6g43Vg5LXJ1z1rlG4vnfWdOkNMiOdEGZmcl2ssF9szcBuJtN9faBM5zTAgJOlAaYDJvDKo_jXQy2ZlrRExlqY8XHxHyJ4d2iiEV2a1aFdNxwVYIZMwk_-N_pon0SX--DWRA-RDHzJ1Z8Q09G8xkn2s_Z_ogEcWZzv16nh_fPJkZjNNeZV6xUT-HqzxwiLmf7Kzy6opVZBYzRn0GScYEpBnU6meqdoTI8rdoRvcpyfhK78LLUStCbr0SIWagZkbiuA8x7bFcP4PMPop6dRhxA01j1-mpV5oWZrOhSHBNKaKzVl-pj6yjmxEju49xxNOnaismJv7cwCx8sUdGQLj8DXupWKtMxcqsgex39In4cgAmVKu_xi7frSgBMf242oRresvP81RVhFh1RuWWpITgDBU3OhIVYLSiqZG-1cEjl--QQCiJnRHIWs85lsP6--NtJMRIAhms049hlDMYTWTlSoOHGVFr3QTr15VkzLbOJCgdX3eh0WnUTUp2j6Wu6YnB-Rjgjeksh_-c_FdmZq6g5vS1w9k4q0GCpJE1SPbzABnnkbqfz50_OwEAWytcZrpjFcHUPzkGQDsYdfPBbj92TFm5-iU5zEQ7eQVIUVWe6zDBwvQh7--3skjEeaTJdUvGtrOBAqr7c_PuEplfX7ZlZiq8EkQGM9t6TmbPxNxDq0fkmQx6T_U1B4Wkgx5PCJ3V1lGI5_nbY8-go7R5jyygfdVPN7OscjSGRRnP-TBfE8LNecUIAyVWxpJaM34892mL4hSqyrzhjLbOHpU9g6wgoypsyGM6wN5nEiZJ-3wNy8L87fv6PyKsibWAL1oIKx7nz4m9nQiA1fS89taWrSV20fSM4qby5nwP9JZ_D0NRdJEy13ZCw1cDaWATUB9oTP8T8OjDeqHDtu2L4u4BV8d4BdF9IinDTcbchUNwWkj_fJi1oxi5nN72mVFSkupPnEfn9-2GXmtdRsbzfNbebtIwsGp7WAzX3OgTJ7MKgUhMdARXbU9OM-P9ep_n1C6bWGpVKNbrV5yp8kspfbsDaZWfByts4ZbLY611TmMVEivrV227FH2TBpWVCiriWz275jPWGnXtNxQcB26Ue_UMk35mGuZIgoq11vPzkT3zYb8SRscPk-kxSiHiv0UU8q5WfIT24Kp7iJzzWNNr51x4ft4xM3xV90lkP5-rQ772Whnv6kTCLaZnXn-UD5f3U3bNnf1pn-wQec4T6rsPl2LaD_BzTv3j1WM9sAGR1n5xxqNCuvd1rsYlfZvMvTxDCjq4T7fjfGz1whFu8miqGOfEDKvi3urNO6clbQ7GQKSmklZ_etV2e2uEl5Yzyv3CWs_zMBNfrJUE0FI5FmtmpjvTL_Ho5zBL3RFesWfLVhzD7yMUXMslV9wFZjr0wqpjdcZMVrkarvmeySMyccU-YEBJsNyps3nSL3bd43Dga4rQvWCN2yRX4zvWiWLoGvp8-fhjqbqfo3CpNXBtXMW60wo7wh1YSc50MK1h7W4w2wX0uMI4p0BNFI5rjDLX8uYLvAkhONM36y99dcLtq7ZrLW4zTk_Mlahm3XC_b33-ybPSsH_vw_s0bBarpfP4XOhLRSC7vzO7y8oO0kAhPxhtQ6f_2GobA8YaLm8pTBo39ryfJ9fWjBUsZrdLcWaEq1z1mz3LnDdoEILzEbioU9tCdj-9Xtt_psgLgAENLo3yvAnMlUwoxMxk9ueArKyeYS3mjlu-yr3fz88PM5N1es4zuVJ0RQ7O-5znuRZzDQJ9BiZcpMPx9wAZiJhmRDqWdkF1kflqK9gyIsY0y2lxQLBI9SPcjOW0X9F58yz6OjsQoXSGymZrMvLX__Z_akwJne8P01gAxNMGwna3mD1dmX3uZMgZLLNw_QOc8_EKM4F5HCoshkaPDEpa23uuc5rrLmBPf41RPx9c9FELShtMd00EhaqKc3RNBwfJkUn2FwBomfw8g2RcEUNUrWCy6uv_BDN1jkJXJk-l_5gIVCp0zjCY65fCZ-BwhidqZa0O9edTVZiAUODE8EbH4s9NPOue0CspAZmeWsmbZRdKcAVnTIJ5syOuF80Uk6Bao6ALJSNmPWeSWWu1-jsomlBzVUhIPN1j3g3TgjrT6OccktOjACqY_EYyZpBZ--a7KjkgklVV63T3yCKYPq0MQWCsqkTEmISAAFB_mGjyi4TXMBDdnkiBqG5v0MdjZk3kSgDoMUL9nJN53-PO_V81KPGlhqfLdTHtbdLeb2PR7gV1zpcydEXoxkPpac-RvZhzwTW5rAWIiDmT9bo-1sQl30X--Qo42B62dNMRrOoYfqsy3xtIGesbpOAYA8RS5iV8MRFlWm6uPafLBKerUSCQuMxKTkuItd5CMzjHHo0IirdsMZjgdNKLcNbO6YvXqiy3Dwla8D0jrnp-TlZKn5gmcqRgZC7kN_HJ4AjMtX51Hx_yvBadK59PMM2rOe7lXx5uhVKI82nGdxb-hX6ZL_RFnnk-GNGTqAgx7wk-TLOp7RROzG0QefMWyKqNTK5sQ72QXm7PxMysvUJ6noe16DdNoufALQ6vLkdZgBt7XxVct24y4M9rJOaCekPMMP-GnsQ-p9ay2EQI1jbQ-OvXG1_xffbz__tuJXax_HrzfDI0OhrrM4qMm-hUKBhJzvk4kpGVzBVZa-3W3Lobohj7_caNyR13RCs3ggqu9yuzDPxZ-6WYNG4G2ep7OQAZ-XotJ0eranry9fZnSTED1SoOkbCxN9fuZ8hYtbyhLkYhIlh716KFEkz2j7mQKUS-MpOa3mtFkEW1kOBKW5-yCKCqnNDrp_fakVGZThJzrdPHZCqSXjymIiainVKgWnGL7LZ74jxP3ilp6jRMzUNcv2m8e4RW0pyYDIKrzvMkOXOyVmVFd4b5QIdIa5e80PNXLMa_1ZJGR8xyqs_z0cyEPCPPPpO1-plvI4bnObnLGAzxz0GdiPEWyOriKPbXU6PPo7jxGGfEK7chVMaHssqn1dGsWuY_Ts_dzubFDnqf6fsugGSGx4dIsADOsTtseQahvFBxj__Vn8vLJjsayDAEb2Lt11B9OqrG-b_ImLj5-oTaS8qx-bFCDIZE3zQAVu7XOo-ykk5mMioLBn9OA2ULvWxDlyLg8fZ9woTgIZLCvkjcldcEI5755sBpKxwN7QGU1LivH6NP8mUwms_HkBIlCUXp3MjNPaAnQ1clHigXxnE_ig5muPI9cnglAjka_-5croseZy4umOyYp-rCRcn2Q1NFnKVxN4jO0O74QrcRSp_Ob88142vq9W70prJs4jltaq0sLDTXd87Vw829X_mJ3D-PocC2ModRJcZ8Z_p4_bU0utzg7QrDQR03IXxbMkhtdH8VlsNEZC3nJ41kxbavNUhUpv_WV1OPu17zKM_KViYskXTYjFUmBjIBcs6QMPRs1QakzJ_nWWvpnMxqe5y8D8oIJMjWzJlcS-5DExCO0ZeVfSavrg7dvfbbDqULicvMnWLQBPw-tXd789OT6SXn-PymM6jqc3K9n89Dxt3yBRgZo0BQarvH8i0EWV_I50wfCPegMMJ3xRTkRW6-_td_k2S6WlZGdwJm3lUWA4nqmc8cIqen1q_TT9HYctJsVUvvRqnIL4KKtvrdiH8CPM_vC-ImEXN-Pn9KGHHZTOe2MCKAyWQ_nWvZtufuU7pD-fm5k62LeNFMZ76QaeB6X8Oc-wJeIbUtuSBjIis7JqrUXWtd8J-4MheTUCUSnH5q15FRXIcxFVx8xzyvxXl-UO9zHuSSIs7nS8i5eIEbxUR1-1kA3TcSgpgjgmWhQ7dTlwms1w5FXgoB_wTpvL9ca5_nY_en5xG5XqM2qEwRjtKEIpm2dTCcZnnIFcAcMZdX9Ffg4Id-FiZ2ethm6sVkFTKYfrQgYjBEcMWYjQp4yLe6ByH26Bwy1J_E3fGZ4L5XjY4_hW4eI3CeIy8WjS3zNMudEkWfZsWXmZA640-vudj4Qks9Dbr5QpjLH6GIumPl76nNe1vollXGIk9epJmfit6Sma2Hr2U5FwAPkkEX1MDs8xTYT_Mynb_t3ask_2ZakN39JUEhYpgM2KJwshKKXDXXYk9r5OcxjW9yrX4-6T0Jc36aiEI6tRmDFDAzM7X3nOMF3cX_TZA8z0NELjoNLNt1e9y_zBswCCaeZ2r_mhA1BGYGHCbVgeAiZiZGlzWhm1jLyi__MaIDzJleta7Qo5YrR0c3q3BvaB7m-EHRAvKch_hGWbnCovN83URm5oxyr9vZlZ7P76q1ssIsUb-5e_zXGk2thY7Q6EzQS0-qW-dJZjZJzoSUsXx_jaHkm-3cB44kRBsDBY3z8ZiJlXFOLcflL3HI4P4-beMb4no_XYp4pivToDTmMlRWY5VsTl5jsTXx4cjlMXIBc69M8ESAyLX3hIuymZ4ley7Y2LW8gmCma5BBOK3Xo_K1c60xt3yCEa5mVTJwZ2q19zkDaNUKTTQzuPcydA1VUNRi1Yqevfe4q55Za0dErUVYQRnrtRARaQVBTsRrFQH_Aw4NnNHpYaU0JiwnOedkVZ_HtjbYrj4DYn6eBM7zBISYS92LL2xR8WeJPz3e08INaEQVA7oRxw5e15Jo8N0lC9E7OuckJemcjFGGTtd-nzmKTq57eD3Hi7U7duhxvE6GNn6xoU6Zp9eEIwudbxj6m4z1U6yfySzEhMdgpkNN9KN8vaGZzyevLE8FkxYsnGaRK3P6OKcEwNeYW73PO4BRD0awvlpTtejNZ0wMJhxS2hOdVcCatsqTen48Vbn2JruAzFlnrnpbrV21-jwxs_bSKAZQZBWZfU6-N2ZqbfURNI8ixLVmHscs-7TG3kdwJXmPictYW6QzSK_9a-b4Sx0zXPum28U5YybufVghzjO5Xq0ABix1ZyUDrqZrGmVluEuZF-oJMfAnfXDtq-5-GER6nWUKVkYo7f67c9ygzzk-7o6yKro9iL1a5dMocy2bGTEX5pZrgbcO57u0gez2AfpqUr7bf3HLXyHxzNwZLgLR7dlo1ruf4zoNWDeL40-7Ysa5x5gWLUsW0g_eRNp7iNsgj5742ooATsed9bRyObjokjZ8ybSjydap-DJfvGaRV2DJMKf4z9_lqm88P4JJo9-I_qSH220ZHwQE8fl4i6Xc63q1xn1TaMI_eb9KTuu9k1BVqVVga7p_dr1ButDoVXAS-7Vb8ifZvax-Hlb19Gv_mphAgdyLSPQlzVIBz4B86BYqyMw6nxOCy22aybVCQZYJLZU1M06yJtIRlyR9qs9aUOjIvc_IQMKN-JDgK81zbmfDksfKbwgiQqrc1020__W_IDERtfack3ufGZCjUE9lPp-fLFZmEsGcc1iUTtUKRPcxMcMQhjnmbzRZ5zwgR7abIzC5Fq-Nagw_vrJqp8kdhKgXojV9Ke7u7c30KDR7vWz0ILPAG3ysV0Qzd_eRutbSiLn6M_iDopxJcmJ02p2_qIi6L9f-OUwiMWcwQTP7JUQk1znn9f6r-_fXGpPIYbHVqnVkO6kndvSg1GH3CE4Khr6baWJVHhRHMVp7X3tEWOhgHplInj7PueS4zORyI_KCVV7rdT4HfrkEgUEhSE28KtERM24UZn7FnSOPv0PKLOBEjB1hjAnk9IBBMRjIUJrZ6kbUXdhe04K8ZrbZTpWFrD5dO6kO-ZUQlG_MMfOtsVscHlxZTplLqlwReT7P-rX7WL3ESKcJlatu-SwZbZqyImHYCVCfz-dWOJ1z9dLwSxm7NoLpqIqWc4HX22RFQ3dVtiO793oKmXE0w2R_DjOL24nJ83lwD6N13PEw9ep_yp2Yb_DPmpn8pkCMaiUUA0xMer1raC7znIm7HnUMd8IVmLsTmpjROSzXCnPUr_3q02uR8QXQGdcD5GurtV9b_WicYrvLbNIyDRVT4s7_-Pf5qUSuCgBZP_G4xDYeXD-8h6o7VpyMPKefdhgGX4uf33TIECEGzpld76e9IJ5-TnKZsKbvNjd86Oddnt1xFeALIRR_niQBx98zAnVB9FerOGoP0C66A5FAn0cTqDyfT1UanhDT0Y_P3JkVlpKW_QKYHuMEzkzZ4GjB0NwPXmb-cYJe3SY4PazlXCeCmSUFNVyp7lCw1ty1AJ1JoCByFODy1CMyp0EuI8-7WxOeqng9nVUTlMDNaYlJZuWvHvE6gzBmL4R5LdJKmdCB9JZWJFfpAivhxLDZBgAMXf6Yb82otQUnx3Q-p5KvveAUHwK1nPOstdOsCRJZWXW7UZI1BZ5xMpG1Z7B3Zl7W32u9hoQPFt9te4Erd_fJ5MwDXc3TLdD8k_pybFKs-2Sf-bbcvoVYtNo_8vu1fFzf7DCZgGxHPJgeoNV9Ojj1kJ4NnedUWuT8vSfw4tK9j54-0485cj6dVNm_iHv4y7StSacRGWG83r2RJG2ksRvwwmE9sWPyeqOnnUzQOf4aYzjGb2DmnCDV42vgvbqEjFIYqdYLjQixjLpS__wGGdd_bDAAgvk8z83ORQqBtXBVKZMoBP0pW4DUGURGaJiYOcb9kpy-FYORH6VK5jwna2kmRF8_Xr9eEejv0dn1iUpoFFlrv4LEWmBwvxx0XMiZnnP4LWWH5tJ7SIXNVI7rpsL5TD9X22Jv03tM_EfA1nkiozv4pSja1nmJTwbo9_1d2p_lqrG1ZXG7tnBGOqieZMolaWulv01ov6fiK-8M0_IzSWbt8O00K9pRWEXltBwKgr01uBZABQNOUbLPA4JJdYemz21gM1dowIsDRgzLTk9a-m5BGByrO9-y9mWXp2dgFskRiMENmgdm5hqQCFn7MAd-U7sQ4IJ3oM8TBoLy4i_1fWwifeqApKiKmES6Sgv09Rs48OO3mxTgzLXYhvR8GglaCxB-XEe-F0JOT9xqwsRyhaM4OrleLmqMkEIqmMyqvjeZwj81DHdlE0wpmMvjw3uwulPLeM5nQs-Z2iX1xernrXFbZ2QMkT8e9Jf6zs8DLKSDT-NOAgICnt9dK32Lu6d5mxZ0GWUmUTuhC__xuAFFf-zgjTM3te93lhgeRIYrt5H7__1vPiBZfv48z42RtaNjXTvV2lmaAw1orOlAc5HoETJoZbqqzulY5fDrqKGpvfo8IWF81Z15HmY6JSKpZyKNvom5HNnOpJJ9zoXL86Zj3J5PoruvM6jbJwYmA6meXC9PCle-2rPFtfzjU6VnOREXSkB3PWPUndws1FrndHDFLVYnRuNhKIji6VFPJHua3FdjHQPejIeepiVB4w8NLCP7joQrWJkrEYlQH48SIoaVubezcrkL37LMta3NVK0voQw2MDrE8HUhB30pZ6GWGW3G7yDvyo-kg5UJ8Lsn9cPxTtqSPd7d_Sn3unWdl6CfjKV2EBnr4qhJYOIMgFzL1nS1RsO1rEO_Pno7YOeY8x_uMmbqHFz6imOpXzWT_3NL8B2bGvQ5AUJJ51vKdHNDm7FfvzRGRL4HEmiPBhWheEaoVKB70qsbj65H7S4fb9mnTzPLyMCq_fn5qbXtBu8eLMffx39ixRf5asaCE0GVAMecIpQP4HcyYkiff6EYayeBySr3bj2_z70mok8EUZndjUSQE5QSV8ltkIVGA682k3IcwekUQoGqzP-pfQU3DGn0XaqVyRYipshQnAgyV5nEIuw9o1f96jllPzNkz_k5hqIOLSz6flYvDXrGL85iwc6VCbPDA0JxetbaVqjEzXVujGq9gspb_qFa5QPBPyepxh_t0yfSBo_VfbwRR_L5PBFSP4kMdTxe01-QwBDTun-RECvVVyibqHCIoQMGCcBztI9Pb3HdXBahw4TNQNzTSQdiWCnfyjIxzt11rVdIrN19wHSOAwpWkjaaDLlN2j49sQt3BJC5sqpYW-FB2qm1WDl99uuv__Hz3xCVZUJcIvOfc8OLH0nwDtk0Wq8XKr-dwmgFXy8W--kIHIX1z1VVq6zNzlfGyPlyn3T__vu_7_evnqlcYiTr9frr9Pn116s7Wsh9kaU-rGdmT6zCrtVztaVWGgK8II67-moyzzHaXCZ2nzN6Dsq7-2Al2p2rqVdm7vHxLP8atB_Z06ORO0oT8yVZaxBInucg2RbYzYmWhWdpnJTL-jEaWyvRR4FYzNYxMQ2yAcMBTk-7bjFIaIc_oQtNMI3UqYdz_ntoXYy9bGwYmwTxB8-isIKPWTES3G7C1cDLdRpDs8WsSASzu9vM5S9p0_CD0M11o4qXmmruFI-VymvPzOlhmmoyfqYxi4YphWGRB6You4IMma12y3sXhJPhosSM80yjgyr48hXQIPfr-Xk878xklKfji1km05gXrOf4hWJHckBMnGeCMHOvXq_TT-bXx5C84F0r0vym9mmrfSP4Ailn7MIDqfQ56R6ORgNQaqm9Orib2_GCWV_bJb5eI29uzWKUJSSmll897034mjqvqx7yf2fsT_E_OzAWJQa5DP2f84M7vPK8hSZle57oYZlmkAyNqTL3xgJqTtxC8AR4E_z4Zsi-FMwbGzCvA0FrRGccaTbyDl6Su8TKuHN3fwBcr9KXh8UaYxYy4w5vIobf0yi_KMzOewP1wbIvVSICEyTl80zwnK7KSz-XOzGRi4F4njYk3eBUnwmZyapzngjwjiEEwqge0ddMJJHJz3MTJpmJ-Dr70nrp8KvTX1-FWsrENiKylpHGryoPHggG4S-p_42WwHar3i8puAqM5ddlZnE5bH66Z6Z2ZuZzWqFcQD8Bthzk8y__hAOi3z6AwbgGFRzfHnxdCznGOHFj-vg22l3IJiLf_-n_vFQshDS1ClD0MK2godMVMsY4tIrnNCNZDAfKwoKLmG4pYuc546h9ljVMMFkloNYgVPs1feyXRtFMXY0yKzL7GWZN90jcG0C0CvlPQlNgglgViBjT2TvSlGG6vkIn58w7yIxcKJ9_azRJJNf0sfupn2ftl_UcHY1aI4F8no_fT7kWM0eoV2mu5WHzHQh0A3POATLrFR4O_3rLD1kWIwNoBZCYWRZCmbzFywu7DujytGXC40YimdAkzdO8mxaSkYTBZa7p1-qjymvmIKjJXEtzbtRdmOmOMA4yLHB9DpitZlX3sCpGK_MYPuUKZQbIOFNZPkuZEyopsYwCyMT1qhj2ghxec0nWsr0ojEPlSkMVC_4LxCAym8HyohBJByq-UbJcCmXtZ9qTHilQibAv4wZdjVsJUINCIrrWUsTTZ27kLPt8Z1Rr3U1lFjT3QrsyLjSb6F5VmgnUPRcGAHGlq19XUZ45c6DJegHAUd64uXu9f14xM4Paa7q5yq7iXGn5yzdDPxPBrP5pGzbUwyIL7qhy7eI2FDXzdd-9RJbPGdHjJHFmVa41c0gn0YVgbis7ytOj54grX1wEJ6OYkvLF6GGtn9-f9_qrkOfp7_CfkfmcE9DRh5mRGHUookXqhjItWZdvUXi6pXZ5TucJhmTcxH03nfPJXOZUBAS_c5JEKu6EXlXtIRYI1Od5aq2R2sC-GLK6D2vPOfl-jTr6OOkRiaAuAPZ81K6Vo8-AiGJYWnTmGzDrrN2nPU5y__C6iHFFgZlVXLd5ROpiQ8kqB8HL5lL1LZZdQQoyvyht3stweAj9E7lWrm2ljiiboqE-I67FdPuiujurpCArkXPmxn7Aer3mOa_XO-_9y8bqb9M03JPL2utaR5hkVS0P5vbrhczae9Qzqlq1KouKqJW8xWxwZ2aOlJGjqPci4tc__sN0r3ehrqivpyvLZutYiVwkfq0agcSJOC0Gyciq5xzCp_B1VxGZCu3ai3WmL9-pduZCzH0uGJ9ZdXuCSNfyzznBFCPSxWanM8YnmEQO2KeddZlRj7iSqzJSfUia4OLd0oTg2EwuTOjCSWxTOQxrOk6090ZlzqIDqSJnJrOSqZ4-_z6xvF9ApTAOe14S3rVnE0lTR8e7CfNNwBjFNLM0k4HMV6MjThb9cR0FkbZbTHs4YvbMVRMEBreAxJnOMBUHtwrsT7On2tc6HFXE8TA2FJzRWC1kMYcEiJVCJMKoecMqeoa0Tf32fH1kES9LK9fKDIFj2i_BzHMelzthXCV1nuFKO8ZJ-mwNF-MH9V4A22hdmssQWSX5XXcZNos5p9d-9zk0ah2utwpJ-ZpC_xAGmptUubNtSWIuST4ZenZgxpB9TMYsAdmO9WcGL5ucuCsCPy0iglly2iV3XE6NcdWWxFvaY_zL1OsVmmh7T5DpY_2fW6stTf6wgRf6qT9cSBCaRgyzXJvzls7UBYQp6-MSSCRA6bSLy2Nf-z0EIGZ8BXasztrjcWwM8BTGgLUbPJ-LgXHIczCh4Nq-LpM1hoLAdq0vsfreDbwKru8PsawWNqboTl0y_EclAlJmhk6ydBqs83wMb5VOGJbGbyQ4gpWMeNVbl3kV5BoA7tpgsNP_kEZ23cYYQY_IQPKcee1_PM_v3KtvTTpQ5Zn66c5MMucRCZyZ06pSMPcbZFUy-Pwcx1ON5vbGZq2t031dq313axb_jReMY9sGXdTuYH7708oTykVy9TkRMTO4iwggGDP9nCtbAitX6OT61_96-3iVSPh-XJXqNkAjKzN5-oxPePdqOw4dXJWMOS3uLANtk5R5xoqs5fNK953l-D5qwaduQMK7Df-hIUYQrBUKdVcRVCZHJ4Taa-4dEN6FsMoJ5Lu3yvLvlreKY9hGPX3sHo_4EohrSb1-vfrpzDr91NqtzrXUvfeWOnN9Po8CVdt30-gAcvoHo1p0Cp-kNX7dj2sXXkNXvVt9eddV0V1rWyUK8nnaIlu3y3smEHE6AU1flpM6i_04miVknW71VMyNKUZmWY-lLyMgSMw1-XlyfO7B4OvnyL35ncW6oLPXa6Jzvz_PZzM10VERWj627oKQLE2s2sSyqcCBvPmSB24MxKP8gHvonswgFyqR9c_P9zJYMBA5z3F0H99nd0TGSMD5TK0ELIW1FlOMNEnAfVkSVVtAcAF6njMtuuORyxyEu5mW54BgIroBKf2KCvQfw7nn5hhzk7qRflP5visUTHMiqTmJlQmawBVDpN9zPVNr-YqemaLIdKzV_U6FsKqq7h9kJcC93z0doUAeXXWB5tip1NNABrRqJXH6oPaEamfS-rcIFDJWpvk9_XM8Nb-DNL_xYhZtOVYfw6NzZt6vf0hi6pUFDKrk2gadQWYE-8zlAt2YvxMyvE8qeuQtizqhg1AQp_tKCkahYK7C3dlfUHGm5W6hWevtTm2uOk9X7QBy5Z9vvUs73gubMqw2HW9uf_p01ltz1A-pkFC87HVv0FlqZxGRWVyr-3h8mJlzV21O8LdPgfDRBjRYXRO59yUxV7pnbyiA13N3FKqL7fPtbjHHO34gV4Gp6WvQ6Qeg-rnl1eBe29Z3Hw5QNockPJm7WkL849evz-cpVuV93qJqRrVfMi00K7mfOUGutZHfnWZ6rMpRY5Rr9XMo6Hk8mVu1uC4kUIr1a5vVChATJN7vX-c87rRlZhXFyFdNzLte3WMj0cr8fJ5grMzKkuJ__Pxe9VoruTjSr_evcw4ijz7t9ftKRbAqguc8-7XyprWz1goMVt4z2WjXy4G5zO853h3gjvE52FpMG6wUDK3ktBIVoHMra79GT9wnqQBgUJmjE4F5lAn1MDPcDPYx8UbmXYkZa1Oso47jNGZ9NQB-_HrEmNdpI31HsBHTOgeFc9OqBuBYKXV5QKZlYMyl9u_fdyCDS0SF8QbjSEmoz3gwf-14OtYFTE98HZc3lEhA0FFi-wj8XGaxi1vRM4LZdvRqN5GYCQpr66IX6w7gY9A-O_StX15kXvYZY5Six4Tq6alViJnT_UwW43TE-G8eMV_acqBSNuYGci1E7_2anjMTl1fGaO1VLsr1Nw2F0Ko0Sdgab9SNuT5Pe2KzPBe75J-wjgoxefeXpsE69nkP--PcWy71udkVpqAvtYckxoJeXKZcm-zv1aLnsQL87vDSxrPOGwHyD3-PYs5J40pDecXMNgRjzu9bbw19Gf-eRhPBSHjaBFrvo1yJGIDztDFoEfeWaAiepbk0sFQRq3waQQTIabMAjSe4RIogI8Ph30s89Rxirhfs3nvc2_Mxzqg4L1nd7_NIccS1p89V1M0A0WP3X0ZfBd6ciZuyCtbqOZVcuRVDX7l17dFApHV15hIqKm3IudCN7rYaGQHk1hgmKa4ae7Wk19pFTszTzf2aPtPDla4xd49X1uW-zijqUputLJweVOUqqSM6nCNC6OCOI2NYASlrn-kQqv5yFS0uLygyy6ubW4Nd1R3r_Z5P2ysMKsuvaWBZBB9-X99dkCI0uf5f_4Zk5rbIfVqyAsCUcZA2JYXy5thHd1f77u7pE0R_2i8SEkaaxFj8SoLqRuaEcu-ZU5lhEKlubh7jgULIOz1FR9TecU7CG2oSvHVvpK3akdHPySy1shLEGB9XWbWQOM-Je2WsCCjsAU31ZNVcfAGCFWPtua78gXl-nr0XdQg-_bzevwKhc7LsF9O9YcpHMXO87P2JWtvb9uIlc4lWZm3NAalzfDDSiCsdzbwHR8vorr7gC0n0jOv1Ck4WHUfKhdAYr-7a1nM6ELtekV6ho6Wwt-E8ydKokgR82jPVMS4OLr3sQr48wOvnqbXsX4XFVXM7steFKIPGDIHVWr-c4I8QWMma9opwCdHnVGZWPt2RDPrxxB7lr7e6Mw1zwOJSjObIbMQ5jMCCr-f-9t7loMFq8ikwar2cx3j6kDnqLDCUiDvXEYAKyPFx78qSGeDXIvqV0uOmd9STtTqGTCb7efqZm9K_q1xCzeCE5e2jiJaGkayZznL9N4I4n75MawOSFfNljZ_nkCKjmI15fn5y5_eWWOrzfi80hugWpEJ4l0LATc21NgMvw-GZ4fJ20vknksX8umMoaHrs5Z2AoKqaNmTQh0Kc057FSgqiZyJkyr2svc-0t_eyKOKKcxTt0Gr6Q3g-WeWTMVnneZh352hQGiqD5U8ks64z7U9qizndxja7KoBFAnrGrO5pY_4WGclgUH2v91wrYmI6I9S3ZuOTHTXXoWgCt_x5oLpHEZrvAwFIzmnUsq6ux5kQxJ9MuujCiceG_pwlaBibIlipHi6fltIvBfxhOJ-unf4oGfmPCJ1771v7PT3BPE_bghdN2aa4MqtgxpS_SntNKHex0h7x2jsyMksRmLvJXLXPOWtlrvLK_nyOV_sSmCCrnyercuWqvOfgmz0OZ81r7dEgUYmJYO7PeV7vNwTWYuT59Jk5cV8r4b0Fc2ZWrojIlYu7kt3H2AlpjDchF5HdM7BvphCz9h7FWm-Fh14TYCuYS5NGuxu4jAjSfFu9a3t8qEv0vltTTYeGEMEZtUZMSRdLIQP8MC0Gn5-fXJyezMScoE_nNNYwy7WKxEh9Lq9shj7U3WNQqB-_gHGV13M7oOR0U1CEpnNlzESMzfHdR97jmu5yDiJmTpi86RLkXLZMdytUpJ941ytTeaHNRkxibmcPkZlOeQQZ8n8CBLjWz1EKV0t-twvBKL4vr1kC0s1v05DHWvkqzNXeFcuvidfaTgZBqMxzHmseCKezynXG83OQmh5NWMuHK5k0JpNE6Uym1U7XD0JR8tEwpgekR7a4KC1HdiDJvLYvOxCsOk-zLO2BQsn0KlWhtZZzNYlUT3x_ohflpWj17RQwQw6VIUYUwkBGMWt7OUp8BYgJI0mulgsZdzwUYcHGiE5iKGLd1zTB0QkM3HmbL6c2IQtbJTJxs_epAOt1tVnJ-RKubxXZboFuMESkOYamptv0bEQmmN494rJleo7n65cu6UfgaasSL4BxPE53s9cFyYH-hPj1xZp3Vtl46EjzJS5cGGRHprqd8jXw-ZtlD83JzDnHOedaFSNUnT5eUd38v6kPAZtCoSDTS5Okt-IO-uaq9Evc_4g5H7WLzAB_f37vv36NpS_Tw6hdc8L_zco1fWUmZMynHUIxuou-HwbsU8-1f__8XEY86gxY9EgghOnxtiwYoRTQ_YCKmIBqUWcsOJqbJYuRsborIZJ3hHTuy-vKJwTrGDz49EE-qdz_-n-4hH2P3oAVSHFJ7zIVm4oER80EBpmv0z9OgjmHFH3U4yQWr2C2vPS7BVl5IcU5bbCUO349U8UkHykQlQnqnAkGBSpcdbU3QSyhSJ7neN_nG6cjy9Nt5-W9LFqB-BzrQbwU82PkzAkgCWZVck6HdEbGVaMjSZwGeE7X-_35-UkmMhHDuNyD6bE86x6Ga-vPDzdu7VrxZQkjGO5_pq1yQcz1_8U42NNmOtknFyDlSWEmsuiHIahWApkcQ4WZcx4kMtNo0UuwcVZkDifsNwFingN32qExn8SZtb4j8e42TD2zJuRx-AVazcTxvgIxsat8Kvh2Ym3C_CpPMgFkLVy08L6vGpZa_XQlLQ1xbXF0YezdzVXKlxDqx-B8RM55MDFSZjEzopF5zrFHbL3e5_fvYN7vYYTmUA79I0J9Pqhq9M33zYe15IsSAVDfBFL7nkmvHdfXO-jjIllJOwF8CZLNI18yc6YkLw1uq9t_hAGG3wo7YC1ufGPfPe-15bW1f5537Ec34DPrRmuEY_OaovYGk8Wraw9h5mn3WIOFQP57P8hECqI0TL7q3epQMDluG39xDAmGmpbey6OX0ZmsPKdXZVjxGArFHGc3fYeX-gLr_UjSaPvdqWF-RejMK7lKmtuAYguo9ZzJLBhjd2Mbsrf4G6ked5T7NHOliw72xDH-6DnhlJE88Yo7BpPus8ygOl0gzHg6QlpnlGT3g4hcJDgO6PcgUMxAqMXyDcoKY2t0vPcvnbs0jxlZd_yN6zoq3E9fs0DAl9tw5_r19rtcYv_8TiDO4_iNn3-5tvcS1GRW0JGtqbV-Pg-y8Cfq44kNFPYQV-1aaoG59q5KQVWZxdorBpmJldMDjLrdK8ikUiCR9XV1kFU9p1Zy1chCK2NzC8japTi1CnCvjUz8er0f1wTP2buQHNM8ro15VqaiR896rdNunK40ED00_WSRmX7EeECX5XwgqozjyonwvuU8HQxGFDOSrfl-L69h1OlmMNRtHnzaJpGvnh5o1arkdH-tsdEzN8SQuISlP2HbldPtjo2l9YGv8jYcdFD0uCTMvFhC06LO59ysdUyW9_V2kfruN2FaIaunyay6yvRwSHrljTufSV4uvvN_ooCM5yQTYYYfI1T5Hisb1EzGaQDTJ6BQKtPo1bBmtUx4QZ9njrXHpiOu9tnN3VAyfDkkz_lv4MKiD6BhpTpdIB4ax86R2DP1dkMMEeEelLs1_RyPwzEeMyGpvoNiZNZI1zfiirMUqDnPXm-yIjl9srxRnO8MXSH2tG2KV_TBAAL2XcZVoTPpoIvIGVniOac9-dJ0MJTQJfqkFznMctTKNXN_-4m8Bi6imD3HPez4qppDyrVCjYmISC6E62mYf95hcB9v5EVD-BQZDmrmheT4b6qLzdQl2dE5Pyd5FBhbqyX1JMKTygjeQbBrb_bE4UJaFK59e1A51-E9baqm_TPGIyEG5NOP98HefTKXr5MITU-os8ob78y6htrL40ZLExzK9LY7SSH5fS_7kmyUNC6QJhTSNWCkewfdXWubStef_57r5aW09xgRWlXP5_GrRND49LjXTc4zvz9Srcy7Jo8gq3J_TZMBxDFZCPQzcPqsX-_zebyBr7V65nw-SMrl-0xmTjdq-XDFW7UnCjrWSkTuNee5APeI0QMMM0wl1v0HfFkatfpMLVuWc1XqtAMhzO3xlCTIkcLDApN9X9LmLirf_-n_46ZzYvS0reBQpE0CJpMg1t6n7SPMaLNgYqbXWnM6wIghatQA5_kAvEHbL8vDLjp5mKdZa-k7IkZEy37NbB3WVgAzjPC_BEV9XT_TMyHPpjQjBXMrrpnPie2YYfoHTWRE0L2AqhXQdK_9TlRIat04rgdgo_P8rP0Ll0JcR-ZgYcZwDIWviRHMGkXtlCJZCj3nv40P15ZdU1Fp4n7O5Bd7mJmjznwLyr1JIJd61i57ZYBEss_s1_8S0T1BpAz5cJ0T7J7MynpDpi1p8ReiIwOouzLWZMgVgjNSTK409AnIZPka4VAKM0WILLqA0ZWFqNZkJcxYqBXXKyyydKtuTODn79_2nCNyxMHXbRFClqCsYmb3AXyfv16SWus8T4RyebXgjsFBA4rM9w0iMoG0N9epwc-nWaS5wtP1foFRr1c8H-mENQl-cBKxzENIzYdIBSysmc_nDm-exykgVokZ4ZZyziWvQWon_32Xjlxyl0Py49VHztH1WphjY9lFshQNHNfKkZSQpNQx1wnr4yLI5_PoGOkT_TSKEbHXq9WDU6vQKqthFhVgJRC7loNflfWcdjvq059XbiJPd1Um8ZyPyFf-FalurFoj1cpVLk5Vn6nX6zxn-sd3RjjZBNRao8i1-nNWZUwHUhHGGoCs2tevcFmGEfCVMoOciJ5OMr456yheYOjeIHJthwf6jMudyJSm7n-uQKBKmHtZinvAhhQsq1X6ad5TVJhzYjOKmZI6HUkJGqCyWK7gx8yc9vBYPdEdrz19cq1--rKAJECJ9FaBtaeP_atQVCWTfYaMy7UIrNcGzcbABcAngoi5qUUgpQnG-fyEDkM6w-IdAGQG4pi0hottDJaJkEjmWsZN9s8zLUgY9ZEBDB555CIJ592v0ydvtU4983lOHwbmdK51_4TBrF0vm9Hu5jpALr-EiJ6fn8_7r79wpuolRdZWzF-__hEZAZ3pSVSSo4qcc0JykGNGa69gYiXADsqL-Onrm1vr8_OTVadPZZVn8oVj0JxmZdHyDS5P-Twc_mocnPE2PKR3Lfpo18q9vtkCj3gRvK1WT09H7c3M5_wN8hwFJu9NY2jYKO4w5YZpEmC5ONhzkjlHDgoHLzUIdFHZY76n1roFWcfpEgyez3E-Wy5ZdkeMjmY6ogG4UjndJu9gImv1c3JtT45JZa5oETUDMNtYJPKoae5WgZAfOE6-ez6VZCIvbCJ0_MqpNADDEEdk-eBRmfAtOnNCc3qvN2UFfLKIQE-wdmCQ6cJsu7vF0hkk6C0QmcxgqjtptrlLEQZNKlwRCD7nIGnF4solSEGnEIMZDDdwEPQDRwrzDBqKiDLvHvk8Z-XS8JyDSoai2y90qO8eL23BUzAxrnQLVo-NMpIRPRdCZbCyX8Gh8GVCcqIvEINVuuQ4TJtJ4X1U4ApmB0bEZkSlemqtCEwE11If57jDIHoEy7GJWyW3mCVuyJYKybs6E9N9Iw3_Wi-GXn8AObhLGMliDzN5fbRnjHAp--nlwXVFRwQ5z_itB8NacMNIlsRPn_AvKakYOH9FRJvqeDy2uEU5eEuRUGhm-oAVrtT4J0QqlFVxw3maVqi6p9bbTSv9ERcrIFa90gCkkGEeSXlIKSm9YCTq9ernyV1tVmJ_1KOj9f4ltVo9g7o18c_ncxs1n-N8Aa7FxVUETI_3me4P-PZLInrUAvn8_OTed6dKwIlVNTwut8DB4_fPTyUA6pnKdMTLx5KBvopqbzsrriMafZqvV5-n9mus6ruBKqO-08hCD8ojIvM__mcHA5xnK8_Vggqg2-u_ObPSdl1Md5ITkiaG0nHI_g6YQ_q2jvzg8__GfGJjEJwjiOhbxM8YKWthhmC3EqmZtcoJyyzachtk8h-BJvNiH9N8y4mQgcSIOM_fcFY6K3QCPAJrk6npYvoVQExlRkQGsvI8g0zReSkgNM9P7hfK2zykpDg6R9-IQkiZa4SRKn-pD16b4qpCNCaKrzM9Z9aqm-b0lp-XLRA0d8CtIkzfyVDmBm-xxzayVb8UjXQcQpTIFdF6fryzg2Bnex85CYp55vk4XufG0nUbIWPgnUNhz7Qa-bXloTKsdw29csW1RN-0Je4T5zr6kBQzMjRR-xXSsps513mevbY0TIR0ntN9gpj2lzoA9oyLpLmWryvwVWduGSuzPp__kfWyPcoLbsTkqpnBSkpxTq48zxPAdPTnkdrB0FD7sirdVnLFCxOYSBdkm7WKCGKhMpl3bzuXPKOQIfoxhlfCzbnpiw5auRSRmTFK4IyPFhXizEHk6SYhNbzi67byhaad4Auuo_fhKxSotDIpur0hEKLnAFjxwjkEwJrQKJ6PIplZ6lnr_fn9rFrgNW2u2qYQVqb3hM3bZO3zgLF2aRyZYatDs96v7p4vW1rRUFSuiTmnGxzNtjAlMOmyjp9Eacucc3cTOhJBZHafyAzH9J_j9JQUdiGt10ujNHzsO0Hy6GDmfKtgXjXX-RxYXHOkkUZ-NFsaasU0EtONyy2IWtSMEBnfoznsmZiItpLkFj9h_hgkXSVFNzTTT2pIRAtqZvrgnsuqnbzeANeOeA-YtnmFcM5IUbRzoFuRe_0xOiO6z5OVfmiAEXNY-UUjmOlxyTRCmH6GCxLJngfdK6-5J9Rr5_P5ibmrQPbtMmQEh7twfj-V6_P374zByEdsAMU0zrzq1_Q5P59cq8j3e4fGkVNmrlcF4v0f_jqf5_3rhQJXOQvh51hEMFOhMG7cDGfF6fOc387M9DmmBNOjKpOQFIF4fj6s0NN77TTnbZQrHcFaVZoI8NH8e_9_F961F206BsMrXdoZx7Ve1Lzy5UmqedIRIrcixqXq0N10JQfqwap_iUJ0770AAzilMxGKM9SA7GcIJLPPwFteRebyxiBZjY7bw2ZMsPbM-A-m04Ts3Pyy8yfp61KP8a8X6etFoqYblepTien2GS4kVFkln85wjgBm5jliAgVbh8_xNMfXlGtlCXg4CvtiYsRKsGYOktxf4nYlMj-exAX8LriqMhn1Sg4g1nopMOdZ-xWCC9zqiLLVDHFmre0Ds88Ct_Z2OfkIqB_rwCJCuarlZKpT_eW6w3nadYX9ekco1NEDKXdF5IRPxmYETF5kQTA05-RabiGtqu7BRW7c6Iuek-vts7Wj0vCmgT6OEgn0ARIMe3x9HPM46WsBG408-x3d44n1lMlLq_d214GZYcQMMtTSGWZiVFmK6KfX62WFEwC1geq6CRNci6B_LEYaegHLKvV8jYWTmdOHC5r-0pT8D1o9a2zRcu7DVCKNL1dxd_qBcVVXdx7qV-e3g-hLd8bMXru7wQI3E6G-DMObB1YMuOqLUKJ6WEuh9EkazNzOm9xOsAwxwNUaRCBIu9huYQV3rcM_lwp--bDSDLnk-9dzEMxXSapVz6eTiO-uLljznCwSPM8nshLIvZ6fHwNX1P1-vcJ7JOmck6tQzoMdB_-uwS394_pSOxlJYFW9XrZI9BEzz-djrn_e6fKQVsIOi1CGxn7PCETeeJszh2EQ3MeGLqX_3snzPMw1_SHQZoNcD1r0GWbhCuioUP71v_1Xv4wtpLhw9Bk3gKGYkNnCo8G4TG4y0sW_-GEyZ_zmIy9ujBGsdWPHPRZhkCnM5f3NIDB9IlKavFVOEgag32VfRDOv9ztibg6GYOW0Qtp7OQzNxZvDcKRvr8g1o9xvcAAhUqB6YKKOZOm0MqO8yV9zJm59l5E5RoD9PISSxHoFueqXABedrzlcykTx3fNJjI_t3c1cLGsa4S8zvjyzbwjKa3FbhK9JTjGZNDewzeo5nSvP52hM0p0_QABEINOpicoS2gBauol5_ZCXzmjtOeoayKVmLTKTqQgul9-nuKjpGGS1nDkTkUpU0T4OAcz335-fXMuj8TmdADAE9trQUUuQNJVpolASakdv5ZKJdwKavoH1CM8nNENUlVPzoWsQtBwkRTIy5pDsT9de00eApnO_x8h0jGmNRhAGIi_XHIA_7XabzxgQdLWsuAkQoKr6PExcqNQq17INMSN5zjFV7CId3PWJAZIp-P-cz0S3_hWV9yjjSGSfrtrnfHysGTXEc1oR6TyEz8MzREZM7eVfOG8-hN7-Gy1Su2bajHgjh10jiK8cbXxH12QxL5FQtdY5Jxzv5g5PfBfnsnaSCVSi8v7ERkHlLs2oW1dKg-E8P8_e-zKbk0JEf1YuL7-8MbphqjREkYwg08OwMV-8KuBvWDIEQpUSY3nMyTlHI6Yr5rpV1qszv1FG4LosvHey1SuIy0T2y7kn_GCLTkO_47u5yJro0TDLuaQEpREcICCulNUgtJJnHZLUTFqsKfXdthOGpHgXfCm3HbKYSVI_mPEP4PKGnM-rYkQye3x3CzKySKD7RI66Qyi-hRZDMTGTke2PAdKxgn5OJv1heO199HAaikwQK8RR1y4wWejpQNRaCWZm6LIqKtfzdFY58Lf2ntFaa3yEBXRmZloXD92nnS5g5mBYpaNf733OA4Z-evpEwUCCgFYlguxYyAzOTNXVgp_zCFMsZ0GjiMCL_8L7cqUjnor4D_lyfjd4yVLP83R6bJGV6Tkmzf4xcv8ubSZzCer5QOExldXNppc4Zmt7YMiazk9V9XOQZuL5pDgKWdFuuYg7ABdC0K5_j-ZyG_s0sjCDMiFDRDyfT1a1zmgiDfHs61Gq6p5cpYhb-JHLLNIXAX2FM2R7fipECNOwur7uOC_X625QRiQb6HPKoj11II6JdZm0FNRrW3ObGWCNHCD3kVSZW8ECIyYvY803U_uJcuYEGUyuLUkdQApycDduVzJumO4IRBpWpkMuhWZOZmZG1tLcQmoIOuMBuRAziIybBQipW6ZYAgienlyF5H0mh-aMpaHIPM8HmT0959x-d0zmTb1f2SFChjQovJcAMny2Dl5p5l0HJNJ71EuHhUaAns5aSCqGcupJUZbGOAYVcAP1nBussa34uibgjWXcALcyGXObdd8PdGjaG0IX011yIynQ9LkLq7XBcMa0_iDCLJZzAA6kGZ_lYjTRjmdNd3BI6syXf4UxZ5am0nqOYxbChU8LCJjREsmXYcfTA4UnYjHeHAz39nuF5OhKS2IUN0qaCoH6Ztzn2vRavkuM5C48wGDMEYpVBYUmPmf2r3-Ez40mBxSjWxrM9BP1q7IqYMvYdXW5xeyTJ9SKwVxG0PRoJleZj0SucBHFn5YHiuBaEYaigUnXGBDo0xGDjIjsmczlkY0m7XIeJJJeO-JbLbNTzmGwzAVvIu6bz0dBK6WZTujUlsiQnjMn6AjQ_td_u-Rad1hbMxHJPpNFy0xGQdb0GCV2PEGrlG_JMeoIx0bjOqlvNb4Da2tOJkmc8-MSGEkDEwZE5VXS-uYTYly1bxAXIjzDVUFU1pwT37ilpKqcc5wll8R6jVEPq6YdP4L8VbGSLoI0diNYlAKrWrcEmrgIc2cE--msv3QeYmrVozgzXPv0CcVa5W80FRnivSF5NxMhcG2femoxIqtWTdB7Gfj1tiH1GUpVkHQGrD0taFbu40R-RFWaGu7ISa6X7s0SJvoNAKL4K6hzPsUy6MCNNGbqjIIKxhWhI3M50Jl1y0x-MSW5gpE4viQguNYXUSJQREmotQaqBMGYvsZPyCd2xyFr7-MffsTz46ICWBUzlQxhWnaMk5TBjtNfQxQrON1XJZjQCFlXfG45iI9WJGspJjSYgboQiE5j4udEDJxrmv5OUgQ7yHQgkQWE_fD3UetL8_xRc8rO1KotqwedU-Kl1s-MAiuXNOU0TkBzAOkcRo7LowowBZ55qpbUZYcjGLLN2uHOaLUAVA4yo3JxcX_mMJlc7SMFk8zM7J5V789zvqpE5Frn8ykmq57nrPV6nuNbd2XqzEUtrYoInTOfZiBrPeeBkzk3lRdrGQGT_oTodETb8GAi0koqZKNzFeOmzm5BfTmNBJvQRi3intJ9lQTSBQqnv0IqIzMCdQU7g7t1NIN15pxaS47zC8byMu8rvp9DpG8v3dIMYwgDE2_p43Lxv2KMnp_IPbJwFe5ynMvv78oa1xwYCsxlBqXLhcxleZOLtuautMse7sDFnH58kXCdJrN6plYi2Z-fyu25gwG7sAvJo9weZpmVwfT4ENNyVWOkIkM45zEx1k2b6cP16m4ie4ZOWlSex6bt66hGonsmlMnnc_Z7z0jIlmqt8skyC0gk1FqrXn_91af_8dc_euY-Aw3kjckqnYlMUOo-nzskZuCcE4ETQ5JcP38_yT06MT0aruxxHhpzTiJnTsx83FNz_KlYQURMN4pM6oiYJEZoRQi2Z3RPem3rVF4Yma_rSjsOcCqEVJzpduJCJqb52kmdyVW6pboGFKfv-to_E7N35cQ6oMB0JkIzo-m5HMMv-UlzfIc8087EB4MuojguEnPOQZLwy0hO4s9MSHNOfEnzpg_M445Qf20wRmndWPaZydpYdU7f_bytdpa1KniHiKOOqm1osgWgRKx8B5p1LTAeI1WVbSxIhi5P3fnDupj8dFOfZtdHMPJue8VMxlevNu7cZwp4Pn_v98tWL8UdimvGm0-N1sqZw1VOfoZRS0eVtao-vz8-ynKVB0d2OHqC6WmHh0enH-ZCIldNz0j9PB5vf2seEZafzjGXLC4RbiKGugP4G8bwKrHy2GXhn7D7wYg7jcL9vtsNhVxmZnqdYXaHNz8SxmvPoL652vGw6qY4vCO1Jclnv7gV59sGDkmWx5kUfAtaJr6lGSrIvAYuf4r6mOvqk57_O3kx_CEk5wYUeDvfdEt2rnf4tLOKV4444470ZY9rLho-wjh1DzAE11kQGqfdal3NE3FT4SPNefyT-HozrpSdYKjvdcJ34hn7kcMtb4XFhmb-rlJ6LezfJGH153SzEm5CI9VHXxjM5QtrEAnb5XnpDlVL3bmrf_9e742MeNypA5g3lE4GtF471-pnqgpM54IcVC9mOwfbnQkW-3Mq95m2Si7cNK6afnpGQA_6jBkSHv-FQo0Zcb1mdKm_SURajnFjRW6dofyjCg2BrH36IJSv__W_4G4cA-GUudsPvrvZq1kdHWpmRdHOD6kNbfCvnuR5PkZHGetEpMvmweyeMaYzF6hUhNSncQWBlCbXQsy0w53098pUnpgolkIDp1mojPtZ7y7v8hBcW5qsJbmLtkaTtcDl4ayYbmb0mcw0NKSPuyqoqomemVo1I1uGdQOmC8yoUlZgKssfCJ-uIxDQ3r-EyLXwzypw282kIfFGzKWY1EuW3p3H806_qljlaTUDtWssmQeezxOMeu82EsdiphEUYt5Nk03RcW6cLmvC368iw7WbXFlGMrtc50lpMlkeY2gGtRh4790hpGW6anf882aSRs40cojArKrpI_nsmQq3wKf7x3tuhRSz9mKgfY6Gvli0XnvdYWcE7NvxhZvZ7jAJn_NhrlzrmXG1xY2uBOwZmJnI0n1PJKERJiif54p_fDftj4Qjg3Odn18CGVzl6m6_XKteE4-vUVnL1EgGMU4jKVnuuw9EZlwLyYgKtc4T4cdW5yJGeU2jxhNn90OU_9IeK845HaNRrWWrQAx6Hp_hSELJ5O_fn6wCpEox9l5zC9Py63ki1t5rF5iP6VWaBFqdLI-Cuq8OQjG2vlgk5Hvm5faAzhwrpp9H05rwqzFEnUjyfH4ctsnMOf0nWjpPZJbBeecxWjGqFmJu5Nol0WSQ3MuVktt2dOfSgwBA3SyGglL6r3kJKF_T6ygyp9v0d8cYrkYwrj3nkvjDCVqnEqk5AUYtRkZmaK7WB3a4iERVCYr7ZKdJzJUlxHOQ1lIGMjnTJNrQUrebzlOV33uHgY-YaWb6chlfIo0PVrSmJzO8IslkMi8AV30ttXTbKhBxJjNRUd9yeRCB7J76693PJ9eaVu0XYqquIWjO1Gu1yfwKjV7_eHusg8rKZTB0kv2cE6pVa5ciZNDCnLU34lYre5S1-_OJCT1zfv_gKlmaYRw-a--fn08lR80li3XnCBOeZfYoV-bKnoe7GpGv7e_lrndrnvNxazlugPC4DGc1AVcWV4ymGKAVx2pfOJlJIWbGb9O47OJ_zi3TMlH7jFrIOj-nXu_n-SknoCRgdCbIgcK4aU_0GZUJ4y5oB9YyIf5CGnTjzH0aSY2JWPj2F4FQVrVipjVzfd4pdx2dGLdF1Ryeix10mlyqWuMv5iXqQcI5jyIYUVnwiRZsKYqZb0-DPWC1X8xSF1rSZP3lTYr8UwRPz94dMpG-SUP6NaGvLuB2taO6nffTOcNkkrlWMDKzzPONqNoxTfB8nrVf_RxX3v3tcF-ib4Ngf04TXpKZAPYYDufK-5dyhtBkkkmPHMDCLgZ1NIgYH60OeePMRLo1S2BCZnaHOvroSzvygsLXj4ibWrlSuWNHqh1el23o21vtt6b9RXZ7MJFj5MaFO998F8A5Tp0gc9nL51gRrrknkMjcY12c5HzXPVCey5gyqgvJ6dG4cOhL7_i24MC6JI2qVoSS71sp5l1k5aqb0swEMjBeOaar6q5ruBdxtej059wAmJtNh89IRDe-l0kQtzthnLOHmPqK0SKq6vN5spYQJPtzUMlEzGSuUN9PZF50oc9UjpYg85uOd1a5WEAor94svaft7ryhgMsudZe9uM48GRYnsBWs7cF0bg-HWeQ5HZi138_nudSWylrbCEqisjIXowPUJW6vhVTl6pG5JkGeo9plFD7TmaXLe51zcq_A-CQZVTqd5it4zjrNm0Ax4gbP57mjotEILCCmn3Zjvp9hrTkfC6f6dK1STNb_8n8onNBwoiqCmKe9Vcz16tFzJslMGIF3ngcYg6umz5iN7VBg3Llz1vYrM8sBMxUzMJpeRPsTs5O4ctPMNQoIriC7zkhfM0f0vWw0AqpmOoSI4cjkhKwVZHJrbln4XhnXclXFNrXu3nuD5mc7opPeUPtOedqTB-X-5cHMeR5WhcligT69clHyFibXPtMTZNVoZmTWSnwnAfCN6jaK-Dm_FfX0Jxi3MRFUdJBCjSIzyocn75l7uBHFqurTydB9RAkaLm8-ysldRJDs04GEKheFmJ4v9pgBqE9E5Hrd72JyxkFkOFsWMHDLz7ZsdcSsygBPz8qK0Omhy_WQY-5JZvEWidKTmmFtGC1oxsXp-y0deL7ec4w8iytm0U0AFsNj7CrXOLlfAD1fPM_Hb00GctXzfK71iNVz9AQYpgpEsnHzoHMeCPedVw4hePs3rR6FaHv4jPncmBivZm_Zw_PjGLPdx1mOUN9SYcQ10tvkEopzKr1_bjCgqD8uxssSIDOz1nM-tw-UqUCttao4ip6btjAyXknm3vv0qZ353Y_ZtKD0pi9CMT1ZnDOaeM45PUw578LKmRM936hei5FgEGd0wbyYO08tYATqPJ84rWkfnUyNYxrnM4aRF7Ofk1XqNjOqagWmn0-QVSuxQog-ezEywxFUO_tw9U-hYS6Gghhj6oGkDUrmDiiz7vSr2A9yJReZ7L6cH0Kt8ZfCpHOF_UERgZHgbwQvDbo1ZE5IfbwQ5lcUWh4rhl-3dQ3KdhsjBXCRRF7ylMPA4kqAmXw-D1fOeAZKTz3nNNaKP6y158y0WpnhMH4QLuogrXiPYt2UWt79aFV9yRXemg8r-_lcfYXGU_k_sENAc0aBM1OkncTIvDy8LAK5tiJcsPHKoFatV621YsIGodzLjuczx_gUD1Oe50MgJZLYzmqrT18qSWRDdU8oiBiII-UqB1XNCCeRSGemq25k9Ewb_3dGlfWuV_jZkyBi1T7Pqb1Deue_HNtr_ROvtLeIK-doRlnFe9KS2609l8ffpy_oC1fHul4rpnmPVtXnuPtow3cENM2wFsAQMAdmjTQ7BB06aikQK4ssda9dgLjTtL5QeF3msqP9PpmBiHPmxtgNaUHoNOrOoUO3Ih_knMeTXVbdQlGIUMaQ7PMQzJUTyqxbZWdUldu4vuv2gCsRycpopWf7nkuYVR_UKPfq8_gbwiqf5V7rXz7nQyZZuVccD_VcjUQrrBPvPrqhoJiZYEbE3m-n4CxOPucgEcvcJ9_f09mm38-T5eiO5LBAsnuQ9vE94URiN-iXEO1uJTHPmG5n8-b5HFdahVC3F-k-jftb7PS_LyH3YGMs_TV6xYV9zXinCiO79MWXxbU-T7cTmDejf1lYiawZIWs0loE5Sv_F8IdOc9X02euX1CzyK2PV3fw78lB3rFs1ujzNr47aSww_wHztN8TPrF9nguX_NYgJ3LIBPWjH9aCDpm2afBr8OpZ8LfWVL_dzusrXBosTOFfRc7EHPtU55v09wNeltd2II-6Vfi37KEKRe8987UAwZVp_lMneCcxtEkX31Gv7Zynev45Lie2BFxHthlUA0WbRgs_zk0jkcmtj_frrPC1GtFyohOfrAIDcy2MEU-Cy8nyUq7LujsMD-NfrLXUldP1medNWlaNR4NwpAABqGtJzTtLTpYyZnmZkgI4qmWBpdHj3ZH6X2FlquxCT6cWRO-uO6bo7qqqlaJlpflEdk3_97_9X2Cyi6LE77TuAs89SY4WCE06KWcWwB1sNpozQuiMARx7l3vMwLu4uEDN5CeseZyDCnte4zRKEunk5kt6FXfHTPdHTEZXOTMZUsj9P1mpd00R_cUu5iIgCdU6wBPR5MrNqG9lW-yVTbMmZtkwbRCYZkazTH1ZJHrSwigEyayctIlKLK2fE2pDWynHT2gpJ6YzcbYWdi4kJcRXpHAFH2vtts2vViign9aVBVt-FciDznEnE2q_n56SNe3KSgu_9jq_usY-tX8ikpcAKRKBqOUrpL54v4QvOQSmvufDaugziCnJ0zJFbe81zAlkr12bfCprqtSL5_Hxql8cAd0Og7hOut8Y5lsVOKJEKrfLgUDMdyGCI_lvLk6RUeQJqY_Y5isTMRIIJddcqt0LP6UBklroNDwgAtD-LCp7nQyJZocMvlskYN1Sez5NrGc3OWjEnPh8mI4zacLPqi2SNQCquBniqlnsC5V2jkGsV61ufmq93OyaI5K2LeZaUF7NQtfr5-LloV6xclZk7WgvFAg1rq7189fv0SELWM51robUCmPh5_p_IncshMe2soM6cTL7ea55n7_X5fMjUedZrO4hrNDVCVWt6atFXxAi5LjCtawtCJNJdoff-NbRhGLJh5-fQa_SeG-yHmGg1M6kMfAO_lUD0yDZROikBytSpkU57sIb9a57fjmxdM5sGta7DQfC1AbG8ERrEPL1e2yKw6UlX0GI0k7YJziQ5pyNoSGtgXcU9iIjUn9fGjQZYPQNkzCCrct2KTma3GBk3bx3P708WGbdDHJ7ftrgdazbVB5EZI648_UBy0oE-UfaJgCrDS2fTQnEVNh7bZWQxKX03IAF15WIymLV29Lxe2zHEypxnlvNOlcGA9Hrt7lYGWQZ11Mpd9fM5r3_5q88wkJVczgm4VgUma-8-h8yfz-_MNbKKWI6nA-tbeonTJ3yY6sjMc55RoweB8zw7c56HLPXp08jIBeNWu49xZH4rRWjVa6azNt0yZsRM1ismKBDhB0L0NBuZLvMwOc9F6aMc5A4SjJyJSttpMNFFrpUejDGpGRh-wQSRRIjuDvsA_QeNmojp3us96gRlipHALLu3yBxJCPYEJ6ja2X3X4UHOEe-S1Tnpycy50almVZ--56f4CqUJyHTb6bk8On9fbawftct1l9zAcqbxQhB8tnD0DanMn9Npoup6Idgaa9YyV1Dz8aQjsraVPPtlWWQheLqtIBO-UOOykRZWcTPzHE_tcuZwlzR1FTg4p1n1-fldy82vHo1DlfocfT493X1qrZ5TtaJoHWFEVK5aeM7gtSIGLcRglGhggKiq8zy3heGrf1zLz42NEzAIyqP70y6MmuavPqazYxqhmUuGdTbjDpjvAim-anjabKL_SSLn_38TDIKhx3RRRdpi2eOPOXl8psy8HsNAP12r-jzTlygs6PvILWiujiQE4hwXoydiwFSPBKlReRUjHoCYag3G_fddTKPukdpDvEvdQdJMzBs6dws8Bkg9D0jkVXCGOrO-B2_IV9rMINpByrtEmXs5mfgT9XVO131IP3S9SWPleDSejHZm2FTUNBU_NKMIrkDs2ohLP_exSUjA12y4Rm7MZ-Ui-fn5cOXVupmMTj4_P0zqiXpvhfZa11QRfnTrXvgD57SM-1MowhUZS1oJ7n23QJ_p4nIgPIBB7NfWzHuv08qEmYoy4guqugfk2p5rlBRzOkLqOC2AjjLWWqO5O8_2mtwfP0njJGJ30yVwNBHn_ATFSvVxGDKJrP_wn5FQ5GiY-LPcIUJnKu893gT08zxe3Mv91JtsY_s_GTqByMKcI0ZE9ETWCnVmdj-ut6HSmtqOa3fTtDEOau8lcyJmfla9iXHhZno8DvWrOs6Ta4mKSn9uzCgMmYOZzlsDUWnSCzHtN0JIfSbInpO7FIFcGiLTCbR7gV-lHmSS5SGegyPMnATLHx0Uicjn05krK-Y8nsPp1nMJktvkovGHOAuR2eHMbRIZc8p8uVqnzwVxVYZUa490Pp1VpKg-Aa7y_oq8UEQUo3jDEyHUCqj2ColVurO6yLUcDDT9NRB9zlqv281gRmIkkpmbUTpP7eW68zMdMSuX6W8zKnqmBgVW0QPFIBKY5-Fa9ibmqpC40rz_0dTe18k7w3QK3BNA5t4KMOvn83xlFpeOb55fIs7nWXuf5-gcJvwgJcYP9h4FuRaT6a8m4p_b6jONgAsYK3M8LY5BFs4g5dWAnge4CN4JTTcistwPtj3VWbKqcuMiZy5x3NLiHnkfkpXdrmSUPeqeMiXR5-EMJN6amqsN6Luh2ZfDjewelLexkUSfpgxdHIzW6x_zNIDnnL2WddRzJhnz9-f9fp3PZ7_e5_mw6vz9XFKeVUvAvcz0MOqcp-e431ZZ063AWtvpAK_aJ0ZXFem3GqXT3ShTDXkzjs4RJTPZEpmK1LXPXnsOiyYaTI95JJZARRxH3mWm7QyrhPy6zClFrQ0obB3uU1XztN2I6iONehCByujjhUDxBXxfJDMg4owjZV_VjBPDJ2tFssfYHwO8s-8Q7PIKSEjx_PRoygzyW7i_zifns3nB_zTO2Rq7RNG7qcsgcnqHF9rdmns0dOAH8HV3ZldNTGiqVgRq_zUxpzsNfV-vzzme2hoM0KdR5Snka695Tr2WQjqX8jmjXNdxULV8WspdpNaqPuPh0swAJpkZE83nOVez6nPFYs9zV6nyREArU4zWsa02FNHHmZ8bctbdhhGpCf_Z2uyOEetysvo5e-_uSa6YDjXIz3NqrZZipf55jPNpLFZa8FTn6bTZo6i7JrZHEJlrRpsvYc55DFbQo2t7dcnNxzh_pGWz71W5OpJtWZ6utPEumkYh9TLbx-CNwcxELOaXVe-qtMEbwpzjLYkU5gewbmzjBsZ8AwmCd9h7-pO5_MnrOT69mbCc4EzjFlJ5q0pweTfIfD4_-1UEBeh0rQWaRlbP5xFQezk8OaYBpAF97vQHyCqTYfX1e0YmpVivV1zVDqHx6rrPJC6tBOVbVCVtcR1UzTl05Q_QPFgEcX4-ppDxejSUbkrYa-TpSQSJ8_kbmvP5sQU8Ljrma9JNOrrqagFGmoBVU7k0HWbL3t-y5pz0w_zrLPLDxIQreKoNmHYY3u_hu1dwYRdeLCBrOz6UXoQWwj7amdyXRHwD4qYz2R59Jylgpfs_Cpscarp9NjPp1bUBzSDLDBnwVn1wby3ODJHQtFB5Cy2nyQoNjAAylc75itE3-gTFXAzGKIJxmqt8cnfA_M6MvT3ouTfw_p98LFKMXKby__VkBCY6UPSLVaNIVOb0QLB3Lyw7CtfyI-qvu5EqMnmb_gEZaVDL1QW7akeTRQQGlE8mEUXcK41iApkFcHrUXZUonPPU-3WLMmu5WB-K6Nj73iqzGIrXXoKkqPeeGb4yM6nIVd2qvfv03mVl-0zXWpLSu5G7bgyd4zZXJDB90RSh9dpzpi8_CSCiwq2m-A4TXW0PIsqXzJhz1tozBxDpRO21m92uPjeAe1Nn5Ptf_4vdbLRtpFvztcoBgziKqnWe80daLgl3gV9-l-XlYSnpE_xFvDrN7wnq5-eHlYo2aUW46yEv3M0VchczmZpjCs_Nzd9Z3V0deqUCpaE5xrfnft2dOiKQIx3NnMnMrMg_UZPbMUgWcyVNr7qOsPj5_I_rMoPvQqY4BXzbVLPYT3Clox9qsVKhwFy6tg6TQLFq7TcL-jm5luyUYaQ9Jc5s2Dahya9Dae-1kLo6dRuU0o3SvDuWCYC5QZCLVeecXCtz-dLnX0Ew_WJVWFOK8zyv1_aoP5n9mXplmPM98Vq_dEOHPL9Pvr4AUFvsGIkSFZjMLQzB3C-cn5Wpc5mYvvRP6DxP1mJQ5MSUxU-OKi1237kMFyVxYnrywvJyuk_3aLpPvl5QEKUWFPH8hDqmR-J-AVGJUBOWeU9yQ30rQf7Qa2LayNsLBinYUBhS8TU6wdJ8wDTQhQYRudaTTjRSjFHkyuljXNrpTwSZ5ZgJMo8UgXptkppA0eBLRJzz5ErLjIgMUs4j3pyYu4YqQzkA5vJKypmSXOUTBSItIEtWxGBC5_H3yK95FruPTtf6dfqjaZ_Mfj4Pa985oYN3uDJLkIEctaYdp67cd81yg83kTr8M4u5U5eH9uQ7X4xyn62atvukOmriMOOM7EphI9Iz3TO5XnU-zSqfDw5txoV0KYLDqP8Ych74y6p58wtrIujhBRD8fSAzl4nP6yixnEi91y3yJ-NK9oMue1Phg7zGey1CREURWzbSFoLcQVgViZCABzRea87mLAoZmVr56DpnW6qD7VgAFgLlfz-dzx8znIE4_v2lMT0QkgTRIigEuphWJzOmo9UL0jHLvngbYRyhMuJBpNBZODwqZS-os5spxkpW657Zi7du-kLD3ImCQWjEZKlTurKrE5eSkY5lyAxT96cwNaCF9UrDbhJnP-TDL-IuqxRi_04hUS60zH0QCAONcpgqSdEkiFlZlyBsHztH79c68PapV2d2eQ960M_Hr118Rk6x___n79fpL0QZHxRd9s9YScEey3zfE0ydyufF9-gTYfRRzQVXyXjYH-vef_x_zhYjl92fEC3RaUZQzFKvyzzfZdUCFkDlHzLrPIR_fdSJTc-6iwr5eUtHMgoMVcdn51wXpb6i7rBbd3W9KTIhgcV8oDQByzpioOX00ytfb8kT_O3HpepNVwdl7RwvIKA9__D8SAAoGtcgj-bh2R2aBSLcYg6j4GnioPlkLQSS6Tyaf88HF3H1bAuFxtl_ciHMg9OeRNP3E3WvoUTCXncS1Urr8UIIxMTN7rccVJqM3yDntLBNzhyL_CPLipolujMBmEhmDGTHHxFXBBOrbM44ZH7bMAXJqyU8JXLmn-_EW6HpiBJDTQiYyWen8jKHH47V4UDGOILovpOmqihkmzMKOZCBsZQCrZ0JNFhgXY3-aCZ1HhE0W9LYn01aa763Ff33XYi1ZLF0CPcf02J1Sh2yk6WjRn2VGXBv7zHfvjVvvVSR19-0XVew9hDPQrItHo2PTcefTQUtQMefQbxbF3GZLx1eT1k6yeffZVxaE7-om5vGNu7idyOXKuLRN6mtn7x4M_vDWWIsBna6s4_k3kSstWLNIq5KI6BaRWTszHT18JaWouqhNBUNMymUYsPpMrp1lDzYqL9tC44y04Z7pLqv7Nt2t6xTsYiqmTzPuDzkDBM7zA-b5PJkL3eoTFVSn201WIZz2_TCY8zxZGZjpJ32XTgRCHOSaadKdp_6eRRHR-f5P_7WfxyvLQkLHvd4bCz7HTbhVy0iv6Sdxm4z392k0axAMMxtcs1q1ZjQ-sMNYnl7lOnh8tafJUHt868R3qPtElhGAMZPJ0wNwgOmuSjEUiuWxUelcvltGAnU9cNNczMyZmed0m99HxUDKfHU_Sa5MwxMYI2mxFn8hBiGLTphb56mVYQchlWuhuF-vIK1pVPc8kYz0iNkkrVrdh1lVqzLnOUGgJyu7XfjNipIaI-xlh4rUp48y1spr5go4BMLo0PEPymDkpxtgFc_z49ThPbLCw1Em1uccVs7ptQoTVcuI5HqXYirfHWf_ercOFgWSuV7LexgWzs8nknNOVsUEUZpTWZJmGiGMVrKnI2sQ_nHtvTBCwhRACUy-sFszJ5AkYjo0tIiNlfOcvZYm2tbcpEaczhm7ZqOP-sl0HAVg5tr9-SSzn7m1-GOHcxR-eSF1tSyhcBAppDar_yI1es6ck0yH3_wNFNjXMQtAvj9AvkBTmii3qxPAWinETDDza2IPgv30ze9_hzleUBJrIj74v5f-AzBUGjHORPclBxvxGXdJ6-8QImS2aH-GcZcho5ljJL6Ya56DbiD68-N32PN5kBfT-fvvj3c_6S_5yF2OcSLPLryeiCHQkh80ZPY5TFvOh5XWFbltU1ijcbwtkEGyyhUrd5uSrGU0KqPuuzOsJ9T_n6m_W5JsSY4zUVX78RVZuxsAm0JyCM7VOS8wl_P-L3SGHGDvzHA3s3OhHgWKQCCCRvfuqsyItdzNVL_vav6gU4JGsrL5zJDOCHDTfYaxVuOKSJWkMn_EYDVf8_42THWfPmY2Z2uBg9pmI09Zz02d1f4pbNCXvbo3P9vv0VTBbHp-yzvN7rm8e-A0OmbQMI8-75uaxXCKRNUetEWePqe2aU3giIgemMeHjgJVtDQhhRtuLEMm73cKkgib6jktgYCl0bxPeSSJcD8tzWobzcCIhWvYJMNVgoiMqx-hprOEuWr9ae5uGdnoWOkZNvTnRYyUXrly77Z0vdp1mBbExkA6pnvlGsxv4N37XaH84T4fMAl1Vr69FxnHp063e7rfJFpR9dFYz6umSb6-nulC9dfrNZhzTqk3ioZZndKXw2mGWZ51KuP5eb_V6V8hHG3t99YNr7pzrfd-a04Z7vIf092s9z7QJb_HPLvKzMN_-VSSs99NVLUI5aeGxhFojjeWqbycPCGfeIV5hh6e8lEam-zuxhhMzJfb6eojD6tCJoZpDLvlbR2jwa8tKC2qS2YXp9c5uVadxrQUP7Qx-pifGgkfQXajapZQExYYm1PxZFVdoJdUBuyVX-fs53n26XzlFDBDmZzN__r5ofbatHlvXX1uLJvWV5TJ_f6JXL3PNWQTU7vRtPGIT70AwLi7u08dzDCmz7E05wTRp1AFQzUsnu6qU1c45bdeeHPwn4ycrQCdsZqoXUijG4cZwWsSozG6D0b9JatTHhqcXQXbvdBr82J2akNqQb0CNP23K2F1j4t7llIV_5ECvd7PUq1f-2R2aWE8sqddrPqMXlWn6s4ISDES7-i9tDMyzDijxVy8d2eN3o-eLWb2mdeMCJXSCN4w_ZiY75iLv_cMdN3fnrwS6hucupCkTxoZM9NbXPjPQGV4OdA3bWVo9E0YEJ_COgBad-Hzc6Nz7j1f719imh5D2FWqkSZEHgDrcwRYxanMNft9-eAXdQ-7emBdmNvcggaxE6HelE9XxGr1BmxhajQtuuAH0sCuf_rjP8OJDGXaQ2Og5YOxTHanhtaCEAoY1VgR63lqlz9-PR4CmLtPibsQ4q3BGbFOH6Oe3nzymemunn1cVeY-Kx6QtX8iXDdTAwBrOa2ptKF1jav8A573XzSHOOoidJPT7brK9b8TQWZJUDzt8c__x80RGkb_ahXIEomUV3IUpuZbW4_fnMkn8A8O2WLpaLd6b7rS71CLaeXi7kHG7o8an3GmTKhmmrRlV19weUSdE8866kq4Awh_COkRr7FXFh73sO406910C7i6a-5SfR0LbZIIa3fWmX2qztFwqOqOHskamuI3VW_XccxIp5VpCPDX95thpP38-3fkMs6V-llMdzzuZq19N_j-eXu60fWnsQy_31sDiTSdESWmKtAsz64BbD0zFREcITOnx8OwVtaMKd4zRVhXezpKf043s8c46HjW9El3AbmHTaZULEFTXOS8D1cMuN8_udbd8pP75x2vjAjxkFqkXmPVMcs6W7sM5jWkwKxmjEyu7qbDPVAzpSbSxj1H31WGpkdTW9FmmlhsQgJvVBvgOmXsrf1ydTHCPQZz9jDSwyZ45tyArEAoFDXPPV6nNt0H7fHb_SwOzG1QynDu8bqEgYucyBsoJNkjCJ3R-_YKg5peggoczEWttQtr62ZXtuB777sNEwaZwIz331_2FI7hllHpEALNBggqz3jOT0p6PcIjyyyoAs8BxiKAiQjJCaoKt1x83wf6mJlbz1HvK8Lr_V6vVEjbTNs-QWs0-puDNo-qyvWqOhxgRN216Xl3iyl_9ZQwwAcVDBjntA57Va3NG91KiUnFkaWodL-YKTIicDMPjrHMNW6KrNhVewbd5NPqGicv8z7CBl1n6n2xJF1nb3eRoQe7yKGFlMmmA6mHWfJeztAzjHWzBL5E-XCF_qnYsSufzd_FskGf7eFGgWvvoUQYFjLOlHLqqhX1fbsbOSv-2Oet5rUNrhRFRXmhA-xRoro1RSPd1EPzASO89lESVCmk2aOn6bNeoPC-E2qdKlvrTvrZtZ4vNRQw9AicghvD4ebuTXimjEu7z_paBHy55AiPfkew6o4I0npq5WvXUYxMkI8wEwHrvvvduw7HiO4SMLFoHrYy10yZeffVb3i4EoPUdI3wFffy3SjeTIK65_vnp6rfJQNg0W2I9_sNs_1Wyq6nylaYXwq0ZmzmNgXrMQwvdar3-5in1kpa-Xu-9vsv5xB1w8kAydpvut9wi_wYn0OYKyHUBV-gxVraR5996BRez0h3N1qd7b5aFlSPPm_ZPXQTVyIIH7ep9HBTVfoc6rrVo5SZmWnSQgsZmtzX3gch1YbjE1LyiDBn3wEzjEWGrxXJm_oemJ-qyHBNX5sz0ugy1tNoc0-Lkl0YfQ_fTvOwuCCd_f7J1yPlxsx4rOEhbK0vu8cE1Gm6k9b1JpTyHRNb6bSpnsv7I_CIn_dbf47IrO6VOX00Y93vzbC7Sx0XX-e-YWf6nIyXSk2DdrPu3WdLLjs4LhwNrqJBhPFLXVOFF7c2IFtT48Nflze123MN0aWn6Nzir3mdN93cHPd1Q_PbY_Ybthn0SEPEcF2G9Fl1xtQ2C4XW7qCdY2mySEwffGLftbd5mqV0Lqb3l6uoaVqKmeuTNTTC4eESRY9UP407GiLrvZVm4gxlsnHONPq6ez9UJKX6VTeK6abaIGTX73KzYYbJEc25KjzunMI41ZE-M7yYXxECr4rqQrgH2qk6yB4j55xcj6SPun3pjz2NiNXT5kmMmd7agk7eAd7naqJ719BpH8N0o7GbBvt6EJ6w97uaHSuNUVW-QvBT1lhyOB4uHS1mTrcZc-V513sfFQvmKLnN6vEwjxiSw7PfbjYczrhb98Z8UAIG2FQb3ZpNdYsvipzDMYe4wPU-sBaVsafqnNsglzzIbnHczKaOZwCJHrPoy4YeX__413tVM8wud9IAF8RjAS34Sc10nw_sdVopYADmLQNUSmTHqaLFZS6q3U_atTfM0KoxLXWFn3Nws5W6hGjJdrdp1XNbeT0uHNItmcBt3GCI6dZ-c-zeOC1Ti1wFsjSZ6xozsxDhFNZtFuccC6fJaKZdITBnMA2f65TuSJejkf74hx2Uz6oqoH0FB13FzCZ72pcHomTfzOw-mTkE3FvRKgzNlLDa_T9X_JOhbzKlx3Nd9klEn7PWC_vHp2fGV4y1kRwbu6E9ToeHkkiaJhZhnqGGP13T1a-vV6OoJu5abphqFWvzebrbwjIetJZupJmlq-q6IiRMs2UE9bt2yO7KOgVXgyeUDzEPs64rGdE9X4_8lvpzeZ679hq7LSLIx0mpcMyGHF4dJmbMdUgwEL0Pc4lJKpCCFEuCM4iK0y1ez9Fm0RhzWi5GUAxVi1jqj2pP6Z9KF9zzY_GQeG6qxH3TgTVzQRn9DN0TAKInMwezd9UAtXVMvM8cNdQ_ytO5eIGjvPKQJdAKtGLN6sEgMqcpIqcLH87h3NoHQ8CW1LWn7SYNPPy8d2QOER4wgaPgZPXM9PrK9_dmUhYrT1eXS10eX3eZZR5TbcEPzLRTHf1AFb7ij5o9pTmHpo_3ekMzNiID06GLkPtMr1iNJkOAuZ6Z6lyy79mQvhbjs_saPM-XMywfDvUDFP86jGZ-6k4SzvnmoN8bbIPB4LRzipgIU0ZFahIT4nrGLsv4GulbHC2dqqpttIGGDuX3oA0aY35flS5GaMTvvxC74ee9fsnmc_UdbCBy7WliyD570ygflBzhYUxP0DwcoOnWV20eWqXzY40JQXzdLGPOWWuRHw60ua9wd4-srliLERamWqQ0OZ7JHl8OMJ8lBtfr61f1ZKaWmGtFCAMz1DBSpdiaXuF3sjgDINK7ziteBUFs0KP9meLcrUAoLwTJPNaRnaE3BiHvtQxpEenRA8PlLv711w_Nzzn13lOtNBTBPjVDOW1qd-1zqt_vXWindZ2Z2n--fc3-ecPsvLcuJN0ldr5Y46DNzRfSjStX1TYbOkv1wR6aKQxgvlQiv2CZGqlGIbq7ZjMzjBSjA4OINaYqZgh25ulDn5aNEcwchWPu3I6Yhor-eqwY27Rvx11k7aOMtUqoIHqaTvTFqIW7XvAwmkJcegSboeFGc6-Sp49uHgzDJZPqGWvu530yFs13lbuLNM0bCGWu1X2uAlGDAA-EK_GI7hQx2QWBbLj3TOZzft7PWufUwPV9HxyQ_W67_C3AJBlgnxLOvM_0iO5-00i9WwzafFa_T0RM98x4hH4UpA06yFDz00RdV_TmcOajADvsJpP3XcOewdUtyI8-ED0J8ocqyij51_0FjVl39Wm7Gy5cxgAuwsDp84lFd_fn8DvT9xnx0TLIL9Da1XcXIAXV0hGru2w0cuY92dP0vjP9CU2Sy2v8FWlB-gzzkDQQhj7b3OeUgVV16TZhGtSR8JRVfSx0e8TvvYARp1pDf21ddMHUMVRVh1sttpHC52NXvNdo_mYN6aaNW26YkLMBfdqve2_Q7IZF2P1f2rB7z8z4XNXGPeaq0TQz0-X5NHqm3fKWfaXCrFZGUeMVSkfbM8q954t23u-zvv7JwIyk8b333_74u2Kltcvd56AFgprxFZnPTNPSIjKCptaGExMe2rBZuOxs0lHVdLjxolcwNBnugO77GzFBVURIxDk0eOR413vLeiPGu2Tr7PZM9FuGaY2ONPatc5jRc-kZ08c1zTnHn__0P2CaCfVlpt5xguQsQ3fdzKSTAOb0mCeCApy3_GcjDkBcb0WjZxT8c43kVRaZ8ViY9hCALEimdrWHHHg8d5FnDovrtubHElUtxCwlBh5Y5KmmQinDwtRQlKuuo0VNdSHcbUir0_RL9bJU2hEkmYbpFX7qqAbmzmowbFpgHJ-xmZ0RFyEKiLAhbzNulZx12sMRH9Ze0-OpKTdjxJ1gXWVghv_KjEFfLdLHWNFAWDb77BOmg4jBDQjT_SoJlJN12sIGQ4N7iqPZfTcjjcnw00e7Z02pCG_d62cyc_exyKs2uVYaXO7htNwBcw1mLqVfnxOXkmJF0lK3TvPP9x93kwJUhGC38uNqyPw0z7A_c3GNQzhV6a4kvvvStGameaNlU6c9QidMtf7Bu1Du07ESfsdyYPYu-AfAPgVABCaLZ65wwRvHwkcgyK5z9-qXjgDZBMyHhKc2FJRdFyR8RiwwxHoIXiGAG6cYhlPGSdnrpNY2RzWulJlQnElghMj7A3U_XZGPVGBMG8KC_PTKpG2BmTPp1l10lhJ1nuLj5_No3zoD2VgIRLi4KAbX6LlOpYdgurs6w93ggNO7i2NGx5wB-mNgcXP1fLq0gjDV4XzJjkQzVXgpvW_PuGdXDaynV6SZT2DkcydRbb4KE2spGDrmNZ3roTyRl1IGwsSBkKfM9basQ7RfrqVNlWd0bYGopOfBxe4KrelG0pqiaHsMx-ia-d2gsPRPIotrMC8CA62qCWtcr4k5FWYysnf9rv5a3NnHnTADdG-wu3v6DhfvWNFlqAmLmaabGJcjrIQR51guVTsHlPpU2gzeThgiQic7MXtoERnnqKHRcxq0CIXtLcKvIAPMZ3m4bERmlpkRnh5rPVVj7pn5fp8Mf7_PBzoy6HH3FU5DVwH86U3zc3bNeb93up_aTCPh6tgpeWhRc4wOHPOoQYSmMvRbu-I90YayAfbeP32OebQyykYzvN_HgoPKdJ_p93d3nbPNvfaZbi9Mna7Tp87755z6_vc_z_u897sHaOlhiU-YVjmZUydiiaKD2-jlDN2DmJ5zTl0Curl7uLYxvGoUDoR3NLXoiPe7lMICEPESTnFmzgzd6N7doNdpizQazlCBH62j3LRXqQ-HEe5zr55AHxncZ6bmeKQgNcJPkcTB_ZmODc1gGUmgeiJfYjmm593iy1Et9wjg0lzUyWf1vdtzBpZOTS4xGaHuWj5LBVIM4HqPm5aWFgYwY810n8r0837bek63IpRXbAUQqkWhZqRT085Nn_F2oBEruho2WmC897vrmNPG5hM9ujnBahUhdCARAbMHQD8r6zQ506WObL1_8HkTgWDkCABtly9pigLqRWC6a41QGSD22XDqFKQCoc6jPe3aibhR1lHJH0h3F91BBPoborFr-lPj_EPzvDrpwZj7AJbXDOhkn-5TVG3l8hXVJiJ6PEP4HfRFd7Z-QVpTqNFkNhdChemJldWlusZc0r92vGK0jOnVSQN6avCpIJubCkHX6GwaWkqwejsY05D7DIP_qME2NJe0cP3W7AMo93DhO8xNFI4Z9EwNkabI-71ngt2j4q9il9PtNNDO-zB8hkXqiwmXkJsermuIbM1nt-uh67G-_l51PJ10ehI8-3S_Mxf6uKlaaT2txCPlGJ77YfbwsKjSfsy7J0PfRNzIUqvnWH0aTjOvfWjK0fjsywbUfq97yA63nn37Dj305gg9q4eh_p0bLpC9U5bAa0WgpZ9zXDSIFjaPnv_y3wF4PEDdPaHH_IZAQYfmiYh9yuMpnGs2aUXNWsaOjx-kwlJtKjW3aDZdFq42SDp6GvQ-UqZ95vqA62B9Sn8TxF1OiSIi1Q-NplEK4LFk5XRPs5g5dLi7eaDbLMyV2K7qMkRPj4ERfZnT9innTR91vq2qIn81J82rysyc0TNulsZhwRzE6fZIR4dM3ap9kALSKt0goQNDEXcPlZI0jQ5FOT1iufnP-x0ecCclBOAA4U_1YY-nfdy0NFvhq8_JJ3edGZFAXj09hDMEHdJrGrC6HRQCMKVlph0TmadK52EH4fbzfs_7WN5llghBKnGykLFKaY9pM_s5J9ZrTsOINLsRIZfJETA4c33d4jK0sMseFlAzpBVr0AarUzCRrWZqIrPOZlhpAE7wKl1dZVR7EhIbT7NV_x77nUeDGbhLwD89ZPmhjfFTRfK-aQ2vPpdr3I3TJrCAW3iQtt8_sR4za7Z77gbHPILm5snINvm06ZFX8UPFf4LTvYu4FXPTSi2968iXPgNPxdJcwXpcN64GeUoC0YwtNp2wNczrJdGnSbEgtgbVIuBj6P6cOiC6S8UvS8X2vM8QMZivJykqWbWnZyyYIJ6zhBOu8XTz6eruycz7OLg1E78_YwkB3Kvb6OGLBjePCGIYoTtNz0Qu2YsAdAMec-ZarntiPYDTbT0pTRppK2L_bA2XBJa5dWeZvLT6PL2e1_v9AxtOR3h1uar5H2KPQsp1jsQc0ld2VQ9nEB4z7eZj1hQc2Bi-u241kqHSnxTjOpkrAVZb5GKdE_8j1nijaKIbD5iruzMfdJlzGqEHpgYiGNIyV1dXdzwv0qqOu5sxPKYxopytJAwNj1RHUz9ehoM2YxYBs7VedU5EWBi6PNI95Rha6xlIeImVqa_Q83qp_P58_aJbPKk65Tl96kSumiMIQYSf7rXWXbgq6TO11lcdMW0lljxaRZuZttXugnKo1Pjp9YWZUxq15jTZwDmtizfczul5Fz_ghDqnes4pS-Gb7exy2rt37QNj_7wtn73fNh0RVTXg-fn-iJAGGJEDuqve3_Q4P-_1elXV3m9QwTn2lFlWHbiKlNNH2zEbE9vNq_pU6SIgOxJhTdB85S-R6vWTDL-LSs9UtYZmp9RGS5EY6pywGPQlXN1gOGcG1ZY2Xcoa9emPtlCju6bFNO_whdaDEfFdJlo3nDPu7qHkfgNrPcapqvU8NX1EgxhQUA3Sw5Rfx9DdI2O6VUi4828twSJAmscQkTGKYmP6fWjeynWF1TkOwn3OGci8Ie8sMtfZ28zODRvphm42qt5eKzKBiDTg_Oz0YF1I8XB0Uevr6hm0-tj0iHIqnN8cgNU73PY5prf-RQs63W-qsO6JheZVGqpoy-hCvPfdLZChPF5SrXbY1DaFhGSdm7FMZdJ3N3mHklD5Q_jGgbkmq5eNMT10Fzq8dWx373OU0_7MEzjVNz40RTedKy3uEdzMjaEeqnKqH-bbfKAmAUxVE3I--kWL8j8O_WYc_I6QCiCuNXubfFV2U9lKk_PGTn5bcUbbAN7-yA3kkBdQPm7dBTgJ2Rj1u9DxRU2_OSPw1GDoF-QnOKm7oa7lOtwBkejGQLdUTNM8FPbXByOfX1N7wD6l2YR0xe5W3VNl4a4IzfSvv_9LRgDItUDAECv2X8cjhmP6N3roh9Y1z-uh0_U0qOqjNhq76-LsqxuT8fX9_e2OcFfL_3KjqqEvVbWgEgC7RnDLnoK2bzf8f1cuSO8-cteJDaX-6iiOpr9hy3PcNx06goPpKQR__ad_HdxGh8Dz-pRX3xgGPml4X9ldbgvdQZ_u34YLkbUwhh6i0VMHnhYuEkjTWOd6Z_uK2c0ujQXCGjRHbqF8XlUFu39Hd1No7JIZqiB8uIzNMndgQKaFYPDxrHpvDwfm533iFRwJa2eqCDePPrXWl-xrGq6aBX11HQfO3pGP0Kq877rGcNeFQ9WurtLfXEW-e2r2vMyTRmuRKbvi_F7q4PSEecq-LmGHvAQwmAGeaeGvmfdrPWcf450gGp04uRY4Kx80MrynfD3hgYFbnDNjyEjjrPWlI8izVnfB3MJNxE1fdIa7llJunhlO90ii13JRM2xoY90H5qd75a-a44KIgRbLzOa0iHfKDKQHnd9__qUK6UWqzdCz0e7uIIzVnRE2cMgVp6eddPTjTrcYG4sArao8vmjAMQvjFcIDfeaU2mNz2i0GRfP93gov0AIFj-u3tgwpBzV-ht0Z8k0uXQ33kI6B50P4_anDLFMbPqeNMPyx5sKajq_shgC6tXeIvmwOJ8wajLU0RDczaZeq-xMlMgiIMHpmzfN86QQQqo7cNOXQCcqaXJT9YnrFc6o8QlBZMLoP3c_ZKx-nVRXHnDkNOiOMbqfOfZdfJDZRE0RY7D2n2lS_Ma8e0fHhHHTEs7GnocZVagzMcU_5984-KgFHxky7X9mC02VEzfVAv3K5nzx8pZECWd5fUM_lQ2sOajB3FwzU5_3zvgnL2hYcjrsgfeNc1W9tWnUc1fxKzc7I4N2zX1WFzBtiS1cX9LAnjOFmhEml6aY36O0liAtkCvsKp6pgQF-IEaQXV8XVYzAWWfsnIqANrZAHpPgMHnEpNSYIZpmH5eIItq1-FNfry3wR9Axzt1vSNWG4fCXd19evmc5MPcDXSkPUbgsT584i0Mjniz4Zae6W6WG5Hs68Xl8fJfeYcT1L-gglzidMJ9rLtKxKPj0d9OpzGWvdYLQmcLIFlZ6vLuOK_ONh4-m1K54vplm4KIHTY5B9Ync3RkX30uOlqjxNycPuA5uf81Onu8d9bDjT-_2jLNdR0dzZp5zGPjz1-zglDe-MUgGkG7o-tr6ZqcjY73c8S7U8MwdZu2TSYQSGFm4hENUwwvQZYCk2dn2otLN_4utvl4Lt3ueYYJ11pj8JJMIM1aMfdVXxjoCBaTQQtE8j01oR8y1K9WB0amuz--QRXtnNSM_HjH0OzH_e3_E8PUcG-trNyL_OX24RHlOtRXaECn4-XSaNI2nm3e3mPZNr9Rlf0fcem9OznmcaA3i6B8EQ_DZzWfj-_l7rF7wvFQF09zrbI0S0Tl-UGXU3OX0KkmtVyVMlIBVqT1dJqljtK263V2BNarniKlXqwSJ1XZDknDrdwsICJMJoPlMfD6rO_AnSaXd2TrtWHYXZINrkbRLTw3osXHnOmjFP8rq7YMYwgH1EWPldeXEVjXT_dw_CQEdLAdqZORz1gKmoVdU9lU9LHInrUDN1yZX6pirormYwaooZLaobbya4TslsqBModRCgEXbxtsp30amAGVyChOshBYTuESlJ687pkvhWK-JLEb3YTc6AmriYdyvRNPp5ij41oh-CHF1UaSuny9ydd6qiFhy7vdrNT5V9-gjAGJ2j_jRALd4xW_lCVm_V_0zAi2mnQwEiM_0oCFRXxhPP1705zBixcv18v7_--OVBN6vTlo4umumgG74aExloUCTctcTm8hUEv57X6ZouX1613eJ0QY1C2mAs1NGAcWhgw8PO1MpV01XlkdXdaNid99W0XdksPgrJmR5qGTxQ--vjRjZtT9BHiENM-fOPf_2dPYPAxO6Y0WKfsNknZDNT1LqPXQ0hVSzWcvCcpsWYGKCkCveXOJZzk9nFe2-F8Pig1alcy9ynxAO1KcGkcjDqfctxiMEY3dZFNvXvMalrcayJ79HaxVh9gHE3zsy0RcxYeK5YR7VCYdEE19KHkiL4fL4rxi7Aoma674_RaDOl9OEM6Q_cASHqYqxjRRNdlevxCM88p5jZmMz1wWj71ORa0k5hEO7T53k9--ed61WfCnfk6oYJJG-GsCbG78WRIFzf3OGlqqeHr0wjMW0zEamiibYOZtJAcgj6nYbaTISP8b2VpwTMBWtVm2Qw5tG9c63aJ_RtLNAJpZ8yRq5DkarD3Hj2gd5BbvLIqsgrLBZvkz0b3YSFTIccqC5tB6jd7j7CUs0wnFVoPezcLxzWBscj52yjzd7Clle3qdKJS_aToo9x7TsWa3__KRWaIrfKxqnaT_OBHmSc1pErSNJCTW6FDt3ZNPOAcdDW1NjZkcNbDsWHsXNOJcP8QTjNc70osQYwESMkzqjPNBe8QK8b-uT5Ob5SHogCwszp4eYWIO8d3-zUmemw7FNMmtEjxuZm4nXxdro5ZGG7RT2SFhEwi3RzWMS7brHpo5xR4FgVyLsD2DpMCQVIxIqZ8UxBwsKXnlYeWRhjdpWqeUYbXa4szPisR22_G2zp0TzodGMs7LpizMMexzT29mmaxvPo6anp3iYM3GWJ3smVZaArPLRlV9pZ7sL-KAuUsYrw7tZsxo2mCeNA3y_Fa-UJ5sdkMTNwCII2oLsssKoNOltJYa3Q1Km4JW-jqdgwd-5LGOKJ64YE3G16ugbs5-tFt8bkemjhGUNaWDfQMHeOrdcvYp71NdOerj8MSc8LOQkPzLh90Iq09XpipbmF--uVEeYedDmted_cBm2iAYsMPRbO6cjsObhE6olcc9dgjLCf72-LBMbSfelwqXOxSzkbZnSrqeuttDznCNTNnlPduzNScfOp0lIrIzHQQKeqqgs1eDcGU33qOO9cs9l1CnKTvg_OUX0eY4Lq0nn2OyKqNumzT7_fCkycc2SNJVm73KOrPYLh0nqO_k9j736tv50uoR16YHR0h3k3LBfc8vmlSqv4FgTrHAz6sh3Z_UYT-r3rCyCC7yn3GxCfG6RyouDCbsa9J7sPr8aa18UpKIV43F7dlouczPXz15-5XoLP5oo6lb7OKZuhMVdAzToSgLtPdb4WAPoNkkWEcSxWT0euyLxgH2efngK70fLxIb9euk-6G6mrzEUl6jKdHmcfktDe8hy7BOZLXXMy0vsUbpS_-pQ5RIA9p-SLqOnMVHVKjnQE93uvJ-t9IoM1L3vJvF77N6VeFkmc2uo9ijKsmPUAbl4aTovH-ttKI29I_84w0UVbAiPSxfzxGJgIFtJI4UI6b7ReY8OrJZm5Pk4iV3Y3B1Ot36kmNaM9vBsxtxUzLTWFiaBvDszZBz3XB8z7YtXcd4QxUJHJZFnGkA3U5R_CwvU55DRbrr-WvXJ0o64r3etSB85UDrnWW7HPNOO5FyfvgQBQ04M0vWFl45BFS_MghWikcha1N-K5fjJd-bqF164-Cg-2W9dEPB_KEMGoUc3EPMzMzs87Vk6Vmu1TkD3jVLeYKBFVbaSvjPWVr19002FY35HXH1-9N0b9b55zGNGgZ3pk807wTb94oPZhuJr9IrkfQcyuK0S_HIjLWTXvevfAzfVOeblXN1zu6d-poYEPGu6rqy2WfUqDXcfCG8VuzoDSJ1zGVFeTDsfU4Zh6Esbx_Of_fgURLqrSHamb1hzD8LBpp_Xt1Fe6q1NoEbc4Z1dS2I3ugakZqcXckTu6q9w40wyyaYM652rp9ALsUq6AmMslso-uoluPIbOY7pq62BkMaH_Vd0TQQy8SpwIgjMzax3VXuBRIPRRrlLoj6PwwvBDuhbGRChtT9CDdhq3368x85a-xRrcG2QJ01vSe_5_Hy_QP2Q0yn0fzsGmRJUQU5nVmPnlBXPsnc-l6oT7q6-tLrzq4lAkOI9juEZl0j0i3eL93riyU5XIGiTp_Ps8fAEplO7PzfSxCQB7eidMooioi8vf3ztfSr6rZSHqGFOyjU3Mo20fGhCVohbIIat6U4ufkNMzXuwvD9PWetwZ_erYpWGnh00A3nFUn6Q501eEU0D251kea6LzpUCGBhIa8ayZiLLMBXRGFN8ZwToUF7ipNcjLu75_IpUQjBEGKwBx01_T5-cm1nKs1G9CkHTxVcMuvl-plJg80jYwD2eJojKqxcMWGNBKYapzLy4cmNB-XFTE1eNZjaTDs94_n2mdbmmfAAYsxq12ZKTqg6205faau2HWFccy8esapVk_ZIC5BGUD3oYoQGA_OICLiaiwbNq_82nUgiIlZdxvoOqy4Vx1ZGPXCaNEwMJo6ZCQo7yc9Ul4Q88sZjQjAnKYRaSvvyPZMN29d1miGvqq1oWWcajOLjD4dIUAEbijcYsAxfc3O2cc9pqfJ_X4rRdP7rQev7FqCLk-1MtNmjAj0vXIrUdZKsetNAFjmAIriSHuo3C2vWZuiFONTjBm0w6YPZ6rLKJ3RlUw7fThV4_nHdBHq3phlgJzSc_WeJ6ZhmQzWGVncfT2Ya-4UHJIRmhei-uvXH6WftdHcQdvnvJ6HgNNSSYy1SPjKfO4XpOrouUGjeyqjtdYTT2Ymgef1S1emzGD47wivCX46bXTUmHtETJXuIfzf-g9nn1ivmcObuSJmcuVNX-Gq30Y2HB1Buv86mxaNUpZaj5rI3O8fLb3MfKr07RfnCjXv97u7v3--z9lp_v3XN2wMnLO7jtx0Q_aUw-dsDUdpQ7NGNzpWAPKQXY5VG87PjzYPxLhFzVY29Xy_3YVXBAxTjVOKFKPL4Q1oL-oejQ7lo8DG6BxrHvvsTEHoZEJ7u5t4WXcYaTG7aJ_gt3ufJqS7KhU0zX5fIzEDy6Vs6MC6x81scE5hxMHRnvMaUWqmpgeYPmu96v1D9zqF6fV89XlraSlLjIePmXvYR5st_IswAEZXcWMAjdIyFmQTb0lCpR4jzWM9tfd6vX5-fqb7Wc_ZG8DZPUCxRWZQEPPsH-WUppvo7u6SX3n6k0o_9TazgXcdqgNp5MzULdSHW-095F_7DBDhpv8wOOTuI_9c15gnxEfXA90fVOmyJDqrbgKNCa1qr61WzHQ9bZyfjvtcaD37flQJjz6l8A5QuHbv2zCrU_jAR_Tm0XcqIxVShVmfE27EuKb-qg5L_tXjkUDJNWbmo_SvYiI3qKUjYN-kljIvkJ8YysxgOPU5a3czwl25QdcDCOihw81TEtlBt7l97LMqy7WlQyiFj7Zc_-VuDnTfQOb9l3ounBQzhlZVbEqViegjNp3CLuzaFk_tvyIfBaF6ShkxNGrgscytznEPhll4T1dVxq86b08nxjxn6uI0MqTR6Do3wAlHl-Se6Hr9_e_hz4AZq85BDT1iebg12iPieZS9NPf19UWM58KUDt0w5-3hmNyFRoPh5_vn6-vVd9TNqXLKDAiPkP0EUKvKanqM7_emO1Bi9mgigb5R7T7vuJfVIU2WcT19b0Glu0_DRd7DnNKfegaeL0z76x__w9NU8uuau612IzGnPbXFsCEKl9t9A8nuPWMgLHTRE3D0U7m8kayWPsN85M0mu8p1j7wCUJEEmuQ5x0jU-UxKdJ-cyOg6ayXvPTs_9I9jZm4hlalFzjkE-3wTXj8_Gave2-hma-8dYSu8GzXSarJ3iSqisJomjFW1nvtfUaX0ngXv5czNesa0VvKLrkz_WwBG5k242EzpzrAyMU3QIz2su0OjUUUeT2nrIs1LriVs4vn5WZ6DDjgKTnvWM10rnq5jwHoWAY_nVEcsN1oso5lP5rqIwOWSWBXGxA2eLoznivwaIo2hwe20RRhST6TfmT8CYWy09SUu95AtFx9rGmEEM589gkXYzPvibsTc5H06G617ZhgZGFgXg2McC5Vw-hzlUbqg_jEGXfAwl9HDrappXnNMvwU32NR5W5gtH87VgYTJf5yvB9NG2_ubPeZ-ft5GH5ZCVVptk3XR7O9Dp9HQJg0qxmStzAxGvPv_zfzDDFdPrNcgxuVvnom1ZmoGFytj1rXX8zJPQUXco-uQgy4au6v2NnNMRbr1mMd5v0l8NJodoVB-OWx6Mv7W0wN6hhsG7LpBNjevmmBK6gfzEHQFiAzPfO_bVTAzcnItzNygykopbnMpuK-FE6baPKbL7xLPMO0WKOWegYHreTRl4Csl4tHHIZweHwvQnEFrm48w13gvPePxc7bRqk-9N26rA90N96k958gZrAGBh88pVn9UvKxz1rNUdtKktrVdDyfRgxUpZfi95H0GObezdmmwo2n5THPMPT6nZ13I5lZRialz_1Jaf3eHwH0znokhzlh22KOZLV2h29FBuGGckTupTv_es_GKfTR6a_5vO0oz-_X3f_77P_5Rp6YQ6ea2Xk_PhLt4AiSZMdW-HlWJZoY1z-t1W552SabmWK8nMiRKjyfI-fV6Wdj7_fZwsqbK4Ptnr5URIsG46Pjf3z9m3nW6m7CqbZcqFiQbfd7HI1ekhXn4Wo97eEastU-vJy8YNaPq6MLmFpgOs90l9EVfD7KdmurxeK46OAhwnzcw1jh1AAhNxwjgdNU550Oahqa_faabFiS9z9E9nx9m_202s1E1p6t-Bnp8oc8xzJw22uy3fSheHrrp-oe453K06Xv7UTuaq45PTvWcwsHeRYMDY2JKNu5riDrxTwFGTFl__L4DsWl4P87kwC-ST2iyUZMKxoy85FTyvA_9Az9FW7hgaJAiUMspWJ3m1WsKP2oj9E1jSmiHsjDSGxd9NcR0r-eBcm8e7_c7X0tgMRjMEtCQwaoKNZ5p1_gBSyXv3SPniBEyFuvso6x7mheE0lN79XYrUcUZoj1iUBoed7dh0r3R9f4xz542wI1hPPvc2pjx7Lee2HTb750rZQSeoRJ9--cnPv1O3mCeO3xF9C0XgbCwQNg5ZbfMg4gY2PR4piBRnqnCF05p5t7nODTthDR_DvmMaREzRyN4acfmfjXKjFJk3qXBPTPdsP1N6usjJ3S126fG_Xnzymqs33uoBWd9hn5x2Toc0zlHvvaZuth5mA_B0pTFB3XvPB-i981z9tHznHN3qnr-SPoj_TmNXeXmvbcOBu4GWLUqfiF_n6X6AEE0R9R4F-xOfCdoqpJ6CTtG1-32fKqP6pjua6bccVccUrzrcHwOnU3VQq-XHaoE6M76-hszpwmUaU9xJl_5_t4Z2YV-b6HYvr6-AKhUOQNMR4Y4sX3aPfrs1_NUlRl9RZ3j7i2wvlHdMyc_SG7b758Zdles50zDoJf-1Dvk8wJMxcg2pnNomNN128PV7lJK-EjO7TeHNj2u8Y0NYDOHaI9_-j9wIX03LaMR_LUAzgxwmnCY0DW8wnOzhEBIfYycanElLgTj9hTODULeaj5nLizvmpkJjqE-GayIqfK4GgVgXN154DeiYbQvAasP3dL1IIW7194kIwyKnZmpy898nfpJw5wSJFFLOPH93X3XGTAzusuCDKtStAlydDvoYtR6vM-2CPToljR3JlCmMI_Bg24-I7hsKJFpNt4907mCAwebc857rVWCT3d7mg0Z9u9__tvreV78OgpcmQUDtWO9airW2kdoecYKM4s0hjusTrnKFcCpi4IxWubr1MmIGXy9vmD2s3_syfRgMdPFv6eWdJBvd8zSHOmmaokKzjPlNxPSmo2Het659s9bOOEPLK9REIiX7o3yTFUiNBFEAOa1m2NmfNaqHks3zlSjhg64YfSspLm12EmZbq4XUfeEFhp3ijBgs-WpUrOtZkpBarId7Dp0dje62T1TbBhQ-3iGCkbyT-vUMz2mnCi44uueNUCjq4ASEXdfMUaWZdxSuxEzZtHEcKaGjemjh-DsIkps_Onp3ZodkZhTDvYuBPWg6epLwrWo2cIp_natf3DhQMMj0hbZHGN4n0P3uis5QWiRy93NaTNFtbCfwJn0rOm0VUfK9tfMCV_sCU8dr41w897IFe4fiBbRl8Fnw0s4qe7pCVL9156eU5KI1CeBIQpaWpZwp8aVj6bUc3UNgzm9xdOEOkVonPf7VpJNfwNC6JQIVSqdpoLPx2cSPUOPqRK-EA01IJTrI9hAnXKhunhtjhFhFCLOZsZX1t5OOG0aZsItasOvFCJETekDuLjGQ_KaQDRkdXc3TN1UsdN0ORF3HL3_fBtG2EH7YJr_6T_9449__Mt5n1haLXvPRHhEnC2JhK-vPzwsVwr3FEpd1I61YDT3jIxc4WEeM3i-vtytdYj8LJHmtIhG3ZNPrnQa3_tYsMHz_fOsl3xAy1KnIoquLDAxGel3az1wc7M8pTj_hHvtAxtdhk0kZkNXicxFt7kR5-hdBsjqOJyaqj6Enfe7z646--fHnHPQ3ZBf8JSudN1dfYuhjTIOLXFnzU1OwPqcXMtnpg67UY3u27Zr_PH8895_RsRnPNTSArKh8qXO6df1I4EqEXlZ7FSI_Gx3q-p6H_I289Q7mukB-mdnhk9jRqRU-J2gwRxmnktbFLkIUQ3AblAO0huYG693TfdQ2fZaEc2MNd1sdB272WBvXeDNuw_D9s92t8wHMF_PTNEoZIK7KZ0i0gABAABJREFUxVrKAAtnHhlDQR4V5aWyE3p994xH1vtYyMIUc7GbeH-_PYMwow90_yfdzlv_wf7gE6fnw-qEaURt7uhBH86Ye5-LdWng5_yv4Apmnfda6-yjZDmEuHc_72PO3jsj0bVUcApvNEBd0KZb00lqCdikBQYOA9lowPVdJn3E83UxAP0TlSPkvPIQmXBaJV1oD-MZg0aTfgUjMvrp4cOBOGS89AsJvLq6Z9qcOgvd3BEuAUwQDnE-6rSA9qYI9Iegr0WcRnh1KkKyCz1QVTL2Lrgl75Jqeto8huySrPt-blVDl_YdNN0xZkRq64glDpU2DFoX0HAzwKRmRqof3PlGN0215_JUGUNPzqFQw0O4doQKYxhGS36XXNPd1d3re4Y8NPZ-X5seDRdI0vUuiat1fHA66VUlk5VFwGP90z-bO-iZ6YMZ5PPQzcPX16veW8ttJTnQEyvDSPfpycj-eUdGdRtZ-1j46bPWMyq7XvcI3CzIGT-6EVWBs-soppER-1uGE5ib4kkOdPc5R7mmOm1ufUofiYv7EoYpROzrPmV39W03eaSGPdnVRvjzj3-9F1BqMWTuWTPVNkMPYdKgT-ot_erxcWpGmZxyEzgPxLjnbasbMRPmnKk9FrwXRONgLFh1UIjwWxUVE01IWHQ-Lz017v8o66-KhDJHhIft_TalqAdw4aIORTY1tlY_KGJS1233ft-Ar8CZtMZg2oGmEAHmEtENblTOiHR_76b7u-ojOhXnzNBNdGaOYchz-rPyRjciHDNWc_NxM-E-ZA9zPWxkhFsb2acaHGOG95nxbh-PaBwzPM_X6Sqyulbmr_XVKCOCNHnbm6_XMhHL3PXJz5UqQoEdkWYx52Q-jQkapp_X6-wfF2I1gyFlg6-QG9ss1u4CXRk_d5f_6lesmbMip7FeT1UJJZhhM7jofzfYTIp_TCeMkxGFNjeFJ4PUH3nuVe96VzC9PFrZ6Bo39E3Hwz3ZPB_plfLiVL4OI_8OPc5-0wNsA3sfh5331h0AaMtVe5vRpjUIYQbcP5VyjkxBZjAr7VtngnZ0d4VM6ZDwQV0vTuNWoATKkKAE7llVamWAWGtNH5V3eh-QgzYHMX36Ix8ArEUCVTiEZtUNWBnCcurQ7JzG5xOcsaaBmrGj98jZExlGeKY2IZiJVCaR6V_AuBqdOrzahIUC39qugLx7J-B9jkdaGME7DpxSNdbdVixxS3qQz1NVU82rQpar5qafRyObCH0Fjb74jDV6FNsD6R7CH5v7-esd6TDu73dN20eXwN8Vzuv2ItwUFlWM3W-twTWEn3saH2JUTzUzMZhBb9za7gd7f2HgMn9dXUSDsDrv68K8Fld0N41VYx590QWhexfdhwaP98871mpMrqXm8LSSvjNA9_jKCyIcuDMd00D6YNazCPv7v_zn__Rf_9u__9ufX78eMSi_vl5nmkZ7PUzL9epBxEqPXGuf7TNu9HxOda4V6aSJ_b-eJZ6gWZ79Y-ZuWVPVs9_b0sX6jgh9uN2tTtfPez15aiucNtM1R9alRgmoKqUMgAxNk3je78FwRpU10ZynW7cFdxuUeUQGeFdDfYV9hm6GZu6DGhK1j7nVeZuS-nV_TzYz06zubvMFm3NO5uo6rdARMXU0J8L7fN41uIVzUfhxTncsH_jpHwv8Hv5get5FWAQs_JzW6tLMqmf9-sXplc9UhzDnfYlBVRpm-fl5G3owQLmxp3wANHd5mGb819557wetGdn0sO_3V3faaiE2qW6GWQ7ac3nw7I6l3p2JIfJhTertObf6H4HqsNh7i10jptP09NmMqBqdxnvUwyQ461l1zm9DVEbSECu757xPRF5wCmbueIU17ZG9j65GVX35zmgFnpUgcA-d2El281T7DXK2ipsaRwqgVFUuM-ClxySqI2TansZIBlIfY-0dUzjRZ6Z6n1zJZrgPoCqjm8FU7XA9Ij5hTr1AOT0WIXurh9unN0nhmWam283lC54h0djbLVs5OTeMVcP8unYULHSZkuUGwIhtCOOcI3PX5fQD6uZdIou6v3IoDQDvMx7-cT_55XqXOsxWR8TPqy9Q7NpI-eR6Bppoflg7WpXeycqwdtFQ5-gA7W6yCsyMUgSfNvGtRUkUKNFhV0EDCnDGZB6YKrjNlIpes5tO5ZqqD2d0tKXDlk81jIi8TmW1IHuz5TWTb2A8ova-0pi17E7Wy8hz3nMqnzDO6KxyV8y4eBaD5-Lk83rl-uUrw4guj-iRADrf33_VVjkTzCCxvh6TxJY26myQdS7f1Mxp_v3e5q78HZr75-icOUrmGf_n9_-T8Qxm9I9SofmiYyftqfMm4eFdVwgDttnwYmMnLHsK1TRqRKI1u0d0lVsMh2Z9lOTDDMwx3b7-8a_azvQ0W3web126IqZrTmc-mK467tnV7Fti0JVd5KaAD9roNXoe29mbwPT5DAjwydrxo262C7rSB3J-_90Qkai67-BTFtHVETlzZnBlVQqJRla93aLqRKyuw3AGUWNuaLg7p3m6ukjrA49YETSZC7z2yQhNHWDwXJruG1HNag9LDIeTz6qplTHVRtRMRMKNBv9AM-9IcC433e0-1kSlak5m7tpj3t1JoivSp2YoHxPNfPZkRs3O5-uvn37Wg6G51rKeqYpbXO6DWeYzkHF9DNx7ejqVtDHzjNqd6ZozeqpUalKN9PRFOprTafl8_1U0R20zwH3jWIYZguZ37kKa7TqmaVQQxlNN4vGv6jdpMGp_WwQscHNGo7C2CkVGr6F1G12iWYBKK573kSVYjyG1IY_uW9NGO9Nn2t1Rwyl-tvg2LnC7aA426HddaliXzHRGWHgr6gAMxi0HcE99I7sl3CUvNQgeqZ6MqP8Do3ntH89AH1ECQWOY0_uU9JO8rDxFiqv2iYt-Gly43G1K8cpcFAK0z1TdCPOIsw-hyJN7LtMgpsfTY31BuH4XIWPuTFuOlViKsNc54TeuiqGnA1a163SEk3ZpISv3-2gsPQ2m487pUdbPHy9zSmlpbvLZ9EUNqIauEo9NVabvKvVNOew6V8ajydEouTRO74YOca_n67AGPW3nHHMHp7o9nUTtBhpd0sTMTK51fo7lbfta-qA8FjHnHHeN433A-pwI-5SitFN9deS6b_odi3Lg4So4na7R5QrjnmO3NuDu_VOel48u0gyN_iQI2Bjd3aeK7nPaVpiJlQ4dMuS3bC30M3GtECTw9eufzikdk8nYeqmDDP7Lf_qvv_547Wn2Bc4MsHvgFq_H3WE3Zxihs1FGSFkb8by6KtxzrV0nnxf9BnQVtSandnUXbMg2X4369QpVkwaoXRzMNJQYNKuuM51mT_xTcY9mtKEMsqC2NtdSqShjoeb8lD-RHqMFTNnMEZns6_niHY50Zp6jYVuf3RbWPe_vn_M-NOzaPUK6YbqN7cAAZ5cOVo0DjiQ7wATjnHKj6gefHlTV9OhxQVb96LBndKqWndGnNSzX84EcWZt1ahDCaob59TfDuCWAyDXdPcOZ2rW7dabHFKqm0VU0m7ODXoogauLK6ZtKGwy7b4VMLlhAi2W4x_828YNab3VK42pekaYoii1cu76AtNjn7ZERT_UZzP0R6VGXAaKEGrQxN0pnFK4WqXK_YEVGnRMeYVldz_OiX5jYyuCwh9VN3D_q2RVu-nLBOI5QgbcofpEuYj2fuMJvl8zcrLOiVmdvS-spyF2H0sp9QGt2lWQ7P399w_ycTZOypvXk79p1Tp9Do0LpPdVAYfgBigguN5R2jTfcZNEzutJ3Vd9tgFp7Kkw671zSx1rWJ_0_xVJ3c6lICVyYiPs99IsZesktLoQ-r7rLXO90Ut4K83CP-SydBMJ29bjMLHy61SJRgVgVYRpwo8qXmCOHydQYTbT2iLyRX1HpxGszg-4S95B2H4CwiyvVloWjKQmk1aPDIua3AlIhMHO0WIrNT-EnPO9SQ6nUG6iYqwZK0zbS3KaFZzPy8rxVjhqjRwBtdLhQxuMmGRoGDQcIz8c4EeGAGhSc6er_4CkLd2D-fH29Xl-uXTYwNBXlp3uM0-fJvLU3uD-RmVNzGtX1O4rTN5vQirGo3ta9PUXapZkU9ojl59TKL2vIn9MNTMeTNSJd68JfUD1PWvoeY3S9e6QVH8xxmv5Pwgx-kbVG99X7WKwuxFpX5fY-ypn6-k__SrOzhQVVHpvqd4ohrwMZpprT1fSgyxCplrm3lArgEFWHV9NzjM3QPvwmbtBjGIw17g3SLHpwwf83PgRq-mlWp5o0z-myyF0DJXww5KRZN6bKyO4KT0xhDA18SsTadICA57U0z4Gz-zjhLmqk2Rh6PPjIS2-GmYj4qYPwTBPTd783Te5hsT8vPlxgYHFyzhmlr8wjI5ys3fqw18yY73PW11Pd4YY5seLf__2HKZ_L5bLnK6sqIhqTK8PseVL_wa5e4fedmrLQN4bVcI9caQFf4WGyDYA3ybpeL3Yzvfbkeu3vbWn0ybXgMBMjYWZ6PQ9ncgXcbyWtxj1Ns3NiPTEm-riNmcX6eb_djE1wI3S2Ky0T18omVNCJuIOS51ktMZZMNUHB29bzOn0GLQnxfVoN4KaICIMrcu89hEskHtH1BrD3T6wMaoQ_XVOtHLNyfiI1DHrgukO6PpAUqtA9zXW5j7U0I7GVFn7drrzBEDRo06eMqPcejbpXEt0_h7DpOvuda-nAfbbY0m0WWpnrYqZzRKt3laFxaJ_2dM880x6O4akSkjlWugUafcbj5nEw7J6qUsTlPyyMo7WVDaZHsVRbK6sqMt9768aUX6umx2CMRu_3e60gmZlSk1q6epLuwXG3iMwBH0V6VCkiIMfkXDP0Wqur13oytUyDZ9inShsZMExPfj3TJ2JBCGCy2QO_Ap7ZZlEKcngY5uIC7Q6TztkgPPOujLo_gSBypSpajUGk0wZ4__xEmlDjGmxCxLzMXcdNDI24HIkukro41Sl5QDFdR55On9qgiVcTmftM5DM3Jxj7bJWEIjL9Md6YH_tGRCCEKK0OTOPVESKjnOwqI2gOQ6QDcNj_9X__X2d3PLZ3aW_ew7XCItzyj5VXXUly8Hy9uk6uGDPQLdzdX-s1pGekR7iVFsRdU7ck2U1WZzwSkxnZzV3HaNMFHEM0oG1S9awM56p5azl8p4s1pgq3ya4YnosC3oX7c83El9eMFlxcrLCeHv3YOTXcP1vd6trnvDeJYTdO7SGzzsYpqe_kzu07QtWESi5ElY-vNs2okyZrN2KEIJvqtCUSdUaEoFKKwrakExN5eSnSrdryKtSMrZTDMSLM7OenEKw6-_u4W6O6QB_rmu5LT5ddWefCGbvMRbT-Ei5JZ6mxAdrMUYSX4aT1yO87v0VarfmqFHHG-oj_NOrziJly90FbBoaGlvgWYvcNCLMITShE7OmeEPSMOO_Dj2FNYzUlXsypiGysrOr0IBARc3uoMoLCVkguFu4zolDEzGQmjO9TpztjVXVXu1OJEtD6dC6frnpX4UyX5r0taruZBatLL5GeCnVUJIAnUEdTIfaE2dSh8E2yFU3T1s_5fyOeMAuzm3rCtPxWHKPdoLKZmTc0hDGBgsFxBm5Zf-gx3XSH_uag_r6QficTQO9zUUJwGt3j9FR_IIdDanCgZNfMoD2yNVJWVkJJ6huad3RNjSv06HGbG-zPpmj0ejOzOfJY6GZCcUWlBxOMcjAGrPzqrnuzkYJRuRr9M-nzeyTw-ZBpbicIq13O4zBC6mhFKbR6rToXYkvjWHfx0kf991KLHkKuf84GmmOy7xZnzRRnPOSuDuWXYNSMuLrQA_O-QujriJDfVssgi2fvbbmoT2w6VMGEr-cr4sueR5xdOnvMw-6t_pzX1ysi-5T7BeVa5PQ5VR7uK0D-fB8SpRwjo0_pt0_AU-uj6LON1ug-TSLDqw84mHGweuCu1dPZP9LCcIDPBcMjmnBPws7PptkumKXB2Xe0ZGag9S7h4Ohpg25FrbKnifH45_-GCyGmcloWAbf63rQF1bncq4-b68sw1bjiOpoZ0REOm0GJ0z_3zipp6KAhJK4bdDrXsN-NNS28n5v1AZh6arOKFrz71dUCC1BcecivNVMcpmWfHZGDvoiSocFat7-b1g58isj5WmdvZk4DtIHNTISSeVbdA0iBKRlKeJ79JlhVguVhylaADmiCq5gjegi3fPLOsV1-WcPtTsAygI5nTY-799nP66melWsKEf5af5zzAyeIiEVeycCgdaInkJl1dmbQHBaZTFfm0h0w8uv17HNeX6-eiZRKiCv8vQ_d6WbrqfOTYaxe6QI0DeDh6_X6_uu9ItGQ18HS-nRYoEoJZo-43Y3iZSbOMbd80oHhLcTQ6bYw5Nh0LTn9AEGmb8wQ8LC1XntvwQqpoRwm_ZkuA6bajRFOt3PKeA2CfcrDYc1pCXQinxG-wQl0uBH3EkLB0yR3JwhFSdsjLoLNqYisR-BG2d3vSUCNF4uVSpoxqP4rMFPHpqtL6m1Nkat2ZNTZsVbXicyuCjc3q66IcLtSE_OAO2gkPF6NjlgWWXVouff2CFshoZJNG7nPsXTTLBljYc0Os64e-DknDBzb-2hwBVcPhrKxmhttwu9kuE9bz6nTU-lPd5u7m2ni4xmCfYalqZkXq6oG3r0lwkV3eDjxxAMMVKxsuPt-b3OXNNc9lWcAcE7VdD4LVa43McmI7pPr67y327jR6eExCnyqy1uVz3P2prF2u3ohN5-hfzbNLXOBrI9f1Ej3mD5Lh2PojxcSTDL8JmjVXoChus6PmaNOPuvy_oVXkhPdnXXgn_fafcaYRpiCvZrbnPZI3WryeRkQnoS93z9mWdW8d2Y1_sZdJ4NZz0N3NTtjPTgVuf7lv_zn__Kv__18n9RFgqR7hL1er3O2wTETuWi-1vIIlYJbPRY3zjgViXJNldzcLVKaiB7RuiwE6Z_nla9MfgR2cwqn3XNOW5g84kYabhxS1-PedcngQj0aItMQ3RXPar9QVmp6Ii7C4wxb5mlWg6G9v9_v-umerrbwfU3An3EriHOmtgj6ILokhZoZlMxcGrWegzoic9SlFWEwlrdibrCL2QGDD-p07ZnZfcZpuF1eW4kND00-M93uZTN8_fqagWekez5R05H-_vkmBmxMwcwi-_12TncpJ-00-cvf702j8IWeORIBzk3Kscd8mhy6r1e4q0FnuYStk_wExhJQoVp4X95KjEAr3l2874H_ENtMl765Ku9FLlGCPpBfAoiI19fz0bHPzOTKoJtnnUJjPY_4SpmpSpV7dDfDbXq_DwA643lwM-rZJrQ3hd2Xg8lpQIsQ9jHCShFIfQbgds6Rgq8H7HEj5uj9fr5_7t-3W7UooztmRZz9xi3jKpxSopsoj94zEY-Olo1WGI_zSZOeoZP-CQfek66RyIiaISRenAtUI8ODxj5nzJrSLd_Ym1bE6tJToL2PoIoWNhRSGZ9x9CgwaaahaqsA_anS6j2KKdWEZso99t6iNVQPpiOeRgmoer-v9yStxGiD47EEZ69z5DZRQqyrzMhwOI2YqjoHBFMhNNMAS_K4vrxJMezNjPcEWgPTAWBUDJM0VPcpMVan596X_IqQ5xxS_9UuZYJcRuqudG2G_cavc9ojFJNlxNn7xswMDckV4lqIb7yYjDzdkav3wcXSCEe-2Hz9_Z898v3-ifyi-evrV5jN3JJPuNfPZi7iDhcGGMN0mcf-6_vsmp6udrD2-fUsufNuls8-FBDhSqVuJlZ4dSn_wqa7W_hNLfawpwGzmNpOm2o337ss3YYE7oXNOQ2hxoSHNoogCd0ZTBZwlWxHLY7x13_-19pl4dp0g1ancf_d48bINI6Z1METLidAT49FostNhJiWmFCFfeeQVO7ZREeuhtlAu2neuzIlDiTFynQ14XzsAvjMjRwPXtbBB89F8pRusp0R52eLH4wBHc1L0HO3OkcFjtbVEAGbqQmLwT1GdBcjCyi2tplrhYGoS5S3MIuYAbvN7LwL4WZwX6e6Tpv5cO5VYCYkbwLff77pFiu02tHzw9SaNZz3rF9_667nyZ7uOhZ2t80RwKx4RvxIitrO-jn5hBhYbhlGN3P3mU4PzJw-zqhzlnv1TI9150o1yfTwOVUrg0TS6myLmJ7957un83mAspgzbW79rowwt2vYFt_OIBufVPAcuAXqmLlidRHZ0mgbmwyPdEUaaPSeeT1PTYX7DJyISDczs-o2Y59Kv3QEcNSCrR43J_n-68cMK7PPlmMQlNrMqBcCh5Go0phf43CI8SIlJ-aGlMRNM-uB5Xr3ScHCXP4avygvkdxBGPbe_NQSpmrOprKYn82qgVMtF0ntc7krc2MDrdkcoSxQTVuGy289o9sRh7ayUG5ukHnHIgSrpYV3l76eRjvneKbOJnOOnOtKVwvCsU-tXLFiZfpasRLmPz_v9TzgkEPzQOLaM4UNdEx5xtwLO8OtUSvzVBOTK2uXXuPh-RGLtwob60nRrNdKuv_5_bMy9aDf-1iEEWYeGnCHX0dyD8SV0lHA1QKePhskqpzSMB3MTIuIgpEs_PQATAc-uAwIrKkpvMqFIi9fkPc5x8OqSv9-tzjnhIXzmo8kBJ5TgqDWe0c-PWhh96ZP7aJYTHmjpOZd3VWxghiXBTmkWYDH04qcOCODEaO4UbcA-b1PPJnuM_RYiuBq0hLP67_8n_8nx_b7PI_H9K4Z8uvX69__15-vP14Woc0DxSZL73MyQ1U8jpGWkRkZkcPOfPb7O-hn76nKV9KtZug3teiRdONoKtRB6I0yHBmBGmPDjKzZjXm_N4NXM0uYuyDOM5NmsOlu0Actq48Z_3ieqQbHLeu0W7blu97oZk3vNtrZ5-xu7dRnzrzf32-CtY8CGNoinl2aAa_Xw7l2YoR7OMx2lWHCc-4hXGBl-oVDRs_0bM5dxYw8mFrQAQZ7_nhohjF3n7PhMe75Wta0XKKXYEimkr7__ufPMj9nd_XUma7661sIFLXpunuuKKBgMzZdx0SHEaLLqetHSywEOl0zk8ylQR4GEa-b2wYY0Vtw6Ub3aJcoN-dppfyrWme0aTlPbnqwd_nzfH470u3ZHEVMfcB6nydXVet9XT0e0TWWgZ7wkFhQ8a2fv75jLRrX-pouTeXdvc-JXF1z9jZ39gwZGgkdmbmkQh50g6wqzUT77Dp7etAb1zzVJYoD7n0HWq0QfbbOF_UxCUola06L6HOmB6E3AKdHQcuhIqiUb1RyG8kZh04luz4koj7lEVogCiAgQBb9g14NB-6P8QZrPAlY-FTRYogg6VnTISGXsXcrHSnzw9QYZAI0WSAskvZJRt04EdD3BShqC-OG8VvUy54L9eYoKqb0tDibOqprjA0Ajer6WINEHMpBc8oza_cF0ZLTV9iFq5oAZlwzPJ1qdcvmKOUlbtAc9Z7lSRw04HFjmLyx9Y9vbgjKuYERDsFhRONWKPu4a3nFFudUPHq9090Ac1sUtq4B4-m55zRdny_-Ik6pRRD5x9_Nnkh_vn49KbqXNloEaWGotvDTnSvX81y1aBe0QTWQqG432qCq3fH919vTuoawWwTaWzfN_a7IQM_Pzy7le82m6_3zc1SHneEcEvu9IbFxtRg2Y6hTkTlVqB72ReiLYCA25t0Bflol3aB3N9m0HMAMnv_y33nvlCKzNGdcujg1uuaoJMVPRXP6Bi7p2dWYEj78ZuD0LgQJzRWk54wxtr4odhNEDJvRyheni3SgIvPUgRvog9E_mQDptQukRypBSyNdcNwYpxkjHlz2A0CtCENOivM-JOxJIVYULxY-78Yfp2kwJs7czpdd4O51pHNQ4kvcb6QzqgvGWE9cHlw_-cjLDZsB_ZVqYrmZe0zzdLtHVZvZer322bmc1pny4_jdFKU2kUD383yRnU-4mwdzPfMpIkso5OERCc6zlvBbqTgyfDDh3gL3oh1mRPja32e9HrpNumKk6e6ZaQ_QtzE2YBtRXR3h4Rbu5vZ-t8dCgTa5slsKQJ45dHHkRlu5eF7G7pk-wg8TuCGQHjt1Vqo0OXo3zzW-yUEsm6oBdmpfsDWdRNB7n8tvCQOwq-Rcug-ByxYwWqS9-jZijORU012dS_OkjLKxzC2Wh1m-HpQe90rXjGSu3b1-varbzW-RbnqO9muQYyUjzvu9IkaiiouInJtJu_ur0fWpq3tUXhqnD_27_qd7Gv10ldxo4SBRbEl_lE51Pv73M2-M3vXV-332sdAeyjwesvcpI9fXr-_v71ypEtv75-fUAfj-2RFP76qDjJb3wZfR5eVyGh02xPtdK9ZVwSRpXppAzzgMXbrUbT3Clvdn-Wjkrkp3d4-M1qL_HNJ718oFclcNeerQPsoWEIPd7Wv99f6TjN5vGztVDK99Yq25QLqpn2ZPvtY1aonqrqdwpj4hgO9pYMx9PhN7Nwf5PE8PLvSQ6mf2Da8rcaphGM1cOC8TLM5WwpNhbYZGZnyGsh2hjlDiekXdJZ4zdoOOXM_7fWyFQsTCFlkYCDMbzQ4MJdSuM_PJ5_U__j__XxflyTzD6GmZMv5qoG5qEIX7MoOZ8ZGWUrG9lXXKMsYQ2nkDNmNGulVVXOiCpm9h4QCAQg_ldr0SB93S_fpBDOINrKXIvo5z5pndlWql2OR6JOzA6T4dbqfray1Rm97vMzPvn-93vd_fe6aqCj3n7GoI8DfDZrt4-LvqnBk2tDJp9xyUmZ-9gYmVB03N53r8Dm5I8_DURBItJDLHFKooAcq0_KI5zFYsDi30dI9uDCdyEbHbcmWuVAByPfnz8-6us3-OjDcyi6EwNft94YCyYwpgr1K59sPGbuX1NRqOixDwRMODMi1QCD4JtsDuY0awNWcRvtmm1WzHtR6a5G1z6Z1W3SRe69f3X39ZeJ9WJOBUl7SXT-7vLYozTKzaTWeG6xbBsO4RbdDDIljTMGZE16kz-SwpOs_Z4Y5r_4DUAnNlf-YR1V1VLeFIgeZTp_dbjS5U7T592kze91JCh-4t4wDhWqd2D9mndMIWiuBUZwa7BYknbeoo4Hf2EURShJPuYfiFf1ig1Jymqll094i78Bw5v0Nj17lTcGl39R-y8Jwap9Mcg1yP1NJKxmuCNrvUuhYOV_Z5vSB0NAecaLprXHVrxne1Zlp3fkRD5fnUlEde3ou2B5cpDA2kpJYD6aJJER89kTon2qJJcDTmgVMgq95qlOKjTZRFfT5JfZ35OUSP0WdafpLWEEqxKBpmuuD3qUJVC0Cr0ljLyIs9U6lCvUFZGMz8M3OGh5FwhpaxhAsJ80m_DizmRuCMaLGRNTmzcL0dBR0BvGtwsz6weJ5__pd4lihqM0hPz1BhzyOri-4DRq71vMyGHjPoU70bLPfUiq13a9-2944IGFxjHWO9T2TWmZ55Xq_IqDquLxR4znZ3htFY522454fIpX4gMX2OHhdrpQXPz451zZkBg3kD1Xdfqmk-AMtVNZ4LnxdL7yLG17_8t-6rzrXueR8zoDZQEv_O2TcjNN09UGt-YO77lCnYUJv3X6UYFjAthrxrqzg_Yp6BnLZP6-eGpE-FvKoDdJnF_QRjfjsE7ijrworGzE8fu3wr9gzMBWJXumFOZ7B7am6iRqwBNZL7nGJXHRmMMOM27FYSINwa6KrneXX3qVPvt2i087H2TWu37tNtZGDMSYuz97oaVZju8TM-3lUrnvfsvpt6atu7IgYgY58jm7kqhOD8-vWre9brmS66Zucw-s_Pt7tFWHXJKbGe15kzM7_W671PeHYVGWRorU_YOSfC1_PodPzr16-aFnS4d2XYEO7MsNHw0vx0h5m5pefM8BbE25_08HBdKQ0zTlWRZjgE_rb-XjiEE9ZTuZbaKMBY0DTRV_gqs97vqUaV2mjAVLf7ZZ65uZ6tqNJoD3dkQ5yDmzM2V8z3Nog-iX066K0LqszB4ddPsx5t2CKzTsdKkXh0f8jnNUANPNOf8PCp-vr1689_-zN1dmpoKtxdXaXgHDFH756zzUwVHjWk9TGITFYbp0-pWGAkBeeh9VTm6_zUK5f-qvHk-SlPHydpozONYWp6ttAWYJsB07m8z9xlXY1gU-bRddaT9XPq5w2izjFngEYZWKymXpnv8_ZQ-98ApppHPQRerxRSwjwJWrpbGIfT7l6D9Xrubpzk6fzKUctHZHsN2DDuuc9hkK5MF7XHHBz21O7n9eucbUDk6ur3z7d71PvkShTqTKE93cPCHWA-f58pc9NgYTDxPJGr0fHxSHw2h4WZqhI33YA-28zJgFnNlAJtWs-RMHh4s7satJl2u8J2sdN1OjDP89e_WTxT5SkeseklSjfzpHl-vWjoag9fTxCae15jsMaxPaMXA9XxDzv79PvoDmYrY72qdkb8_R__tF5rmedag3aP6oqMcI-V7pYZAc50Rn49j3lwsF4rQMsYjA5Pv76es4_dbWnRnTr59Xmt11qyB1qYCbov5U18yOV6hohA3j2qxysmpkHULXFi9JAUu0lXL7spZm3DjeOnTsv6e46Ej3W6ZlePjU-dqT3dGNTZc3a3WNe9_OnamKna0te4O8ZO1ZzuaVaxe06H296HZkS-f94Gn1IOXgLSsYE8daE6fubhzLTjUrVjRbxe-5Q0gM8fKTMaLWjsOuw9-6f0up3pOsDUOehyY53DiKptkE61qPiveXjQrPe-pEa97K5zJrovhkghBH2lVBExOjWcu0hFse16zmBGm_mrvTCKqZXx9HtbZO1tF6Nu5_cTzLDfR3xCo1Wdmena56cin8GstcTAEUfSQmTCi6PBMDP0DOfAVhDoqhk3WqTLH9cFMxPm6_u9SXg6rnEKqKZNn1n-T6f-nHMiYupI5jgK8Fw1C7sHXXqU6swuPJe5DzpizTkDjHZg2vvJg6GCXGsuwx6LcHeNRVl9pChARNMUvi3x2dyUEQA5VR431lyn6NGXot6hY6hMdlMahovCfiMi1ycd-gd2991e9_3t97QiD2qbn73v-N-sjppmbUr5kd2lwp40KTqTYMSEtCsCm74MSrVlLgGL06WnpU5TCsty-uqoMcIEo1tPLQEZB22wKV2f74-X5nrWKeNEQoDluRnu6yuwy3s1W6kcrADWU3UbcpcVYVOKGHKIu9kQaveecMz8_hwuh6fmRl_ohvHIrpJwZPp4hn78TnltQU-QdMu13PL59cqVMlWI1GCwU8cy632Ml_WnE0a4V9c-G9Nr2Tm9d5-zpc64ZAWz51n7Z6eH_hK_vv72Pu_MELb8_bOrpt-1_AJtz66MdfbmjDumGxi36C7DTB2420zkgvgHkDPeHBYWp_tI2ew5UARUtN5rISZd8ohwkuPPP_47naMtoyaV4sO6sPXy8OmgCIZ31ahoF3Ermi0vqJ40YxZdg4Znks3Rk6FJhEvTa7XPJyJPTHvk7BOemszNOfZJLOqeWreVoidEh6py7lODakbAAEedTbPuEgCbH56tZ8y0TXdb_fzYcvc0mnkq1jJgwwuUz1lllKvYIHReVAF0ZnL58BMLBA3Ru9bK0z1jNQODWezuczqWORxAPrl705Cels6BE565u83o_moUpmxoofa_u98kwqeD5EMM8ayVEX_92ztfGRHPin22hdNsn3emPU_qORJ5mcoZy8Pd6ALSY8DOjPf75BNmtGF47r1hBleFNHXR-pVKYd-ctBnfuz2ju15_vLq6u9OJQayXe9jnwO7hjcpUxMJJbTF50ZhoDzv7zS72FayrSM1Q03Pc4rqW7jVGMmp66rIBuqsz4HKfEMQwYshwtxVNvv74Ze7xPDqy0WzoUx2Z7kkw1xd67BOLl4cTxsgctF6pcN_f37_--Ptff_7FmYY0oEdsNppV3aJP3zHq3MQUKL-eRsg446S7z9xAqg6UoQUrho6eMngfuJtlDDCHIFYuvXv8fktvo6Kr3B8b0d8YFtNjjjDv5kH3KTGzlU6aIjRr7LHwwXzvrU6Pfr-zK8Pb4J4RTNrPqYicnvRQGtZ0Cd-b9HHQzfRwpIPQrkjfLF-uXa0KMBBuq4WDYP38OGOqMZjzF6blB9d5-mZeZxzw0GPGPN1Imp_6gbTmfQmymQ84U9C2lEQ8q2vzItmFquAA-UpFVb7fJ9IzX4qu3ZGwYghC4snPRUgdNZ83Jz7r9XC7xUGQ8Xg4QHqSVGsZcOoOx-jL1-B0710eEc-6dK_n5RH75y3oCjRBd1u_XvG8_vj73_7xX_4rMc_X18ql0-f3n1scjBUxlzJMTmeEuf-837bC0khvtkdEBLvDvQF30yBfIQYzWC5wXs8DQ64Mi3Ok6GFYglNsDRrVc4gQypNtbNSTD27b625e0gQlRDyr-nBuplMpYQiFzjnvXZpZzYgdd743zavK3Wdmv8-K1XMUeKUZu91m6khuasqhyRCEMbrgv2hAako3wDISPj2Hronj0NLI8_32CI8AraFKrc_gdCsEe2r8eXi9Vl4DyWgz12D297vnoLrqzAGM56-_4iLcC2yaaexmYZqH19l6zA1oYZg2BiMUAkTfjSIzm6U30VQBs89xpTWAiNA7WyIrnflIuBu7MWWZInJHugZuNjNOIy1suufzH-lTQJtR1UOp9Gio937c2d0DyzQPd0ePp40BxpBsfCYi3B83r-nX8-yuT7raQSWLmubjPHurjFGnXLh3QjADVE_JONqcd0OthMbMOaUJKPyTtmy1vW5fVVgbIeNp3tN9CsZ-V2nerASwrVFyW3xQwNzEMcMM3JWsoPkM9ylmVrd7hAVn5lQo8je_kQaruzMD3Ry6BQ1V7ekqts1vT8utyc_1GFyLfchnLEba51GDuY0mj_AZMFPx29rlEYQun5juay4HqgZ-N0rTfbUxfv0wGLol7Bp5JTdUwn4wZjGNa3GJmPP7H6v5OeQB0i15VDzYlWGf_w-nhjYCyuk1LTGWDg649xAfAlMGvnfV_Rhn1dHik9A0zOmcz5hMb1W7BPAPA2da8S0lV1tpbXeS6YluA7oaGTArtK_U7l1pHD3A4beP4-7L1-tvf3--_iDpGRIG57My4t_-17-5bhpmdF8RXdDFtdGkiQPXVwo14V9AI-jBOseIOg3Cw7_3z3l3E9PdU3N3OO2C146KKm99DBw2jTAvwMy6UefWNICJFd3YP8fCz3sQV9UkXxvvO3VmH7DhpFmY93lPnZnfJM9_-m-XmaBonRmA0uQM9-1LY50a49wRe6DHnN2VmY1WPYAcZUYZQbP59Dl6ivSL0wZ7tAHUX6ntBtdCBVz1zJ1G4HSdRqNuXI9XeoKZ9Ow5oCNUSy9UO4xKZ-iWY95nGFGn43kUorJISqQBzlg3LLIHP2fckB5N-QQ41WZOlahmiDYFaKa7K9dzTx027qGn3vXAM2B4VtIoSpI_q6fcNS-isgoW3jX7VESc_fM8D80i3Cwik0D9_LwiNTNzj5k675PPq2vP8OvXM4PIYFc-X9_f3896zs-bsJmyJQQigQkzCjHnbJErLKrGXX_8UVYqgpHrLh5X9PttM4U6BTp1qjczD_O8AvuIqF0MijJOtlA_IpuHBwh2py9MrVxj7EMzZ89UsxucnjGMh568cYtYykRWk7b3tqG-RZSV0Ii0GZzT61nmJiMdXVRKU8J-Bp5Py4Z9j8yKGNI8QmRPKFlEVwrfnWYeQTAiwr2nMxeGNVOz3VNfQVHtu2qkcyLNQrkjneDRk6r3yfrUPYCTmlftvfNZMzC3vYdB9V8wrD0ehCZEeYfEmT4fn7o26tWd-dQ5BjunPMzczhGQvmneDZg1RhGC6T7VsVL-0LNrZmj-_fPzPE94ZmRVVY1nmJpeBJtrRVsHVA5kl4JvdxcckVV1fko2Lrq56mwquJr3-6T7dFm48j-age1z-hx3c-f5OVX7fL_l2fXMqbqzJRQ43WUmm_nlFLvF1OnalhHrMVE_Z2hRU5Q7-Tb7dPFkutfemodNtVlUV4ajxbhDZFr43jtzDdCii9zaqur-DmOsEIMR1XoeaXsAwMO6xnNVl8GftUQKyifNZNm-ewYPj1wqIKG5nlf3nh4QU-WRMOu2fB7CUfWf_8c_ltkrMp0___bv-cTXeuBYr9Xd7iYi-_d7g_zj66X2Q-qbndqnKXaCaQ2Ds6fPB_AXsQi81isiIsIypmqlh7mv6C6Tbjjyz5830OuVilxTqBqz3z8H84BZOF7rwXSBdTam-yhxINM8T3UsP7tqV0_31Gn8_OyqLX4vgr1_k6AOjX16SvqB7kbNYOaJUP30Z79vGTqyTxUURgQ9eujhWuYMrU6lWaTDOV228sa9ZHoAM77qxvwMY56pPkZ47PeB0zKpmen0-f4u9s9fb3PjNLp1nvaVf_75b6CVrvpDGS4vclfE5xm0dZdHyEgrELjCNgKG6pkl16y5Fq8kxlR9lo5cFwaimteZZF5NmuXK32lSMzfn6NGqEKN4kR-ynH64uV51CtPW-B3IXM86712a-s18mGj3j8oe9UQjYigqRpOY3R5Rp8zsdFfPJW7PdXHUOWjtQsemOT11Zg5U2CXJoc2pH5vbBB22gTwl5FePJtSV-TXnkNbUMpokLMwzNAA1ug4j0gZa-AfpqCrtxMoeXGSJeajG82nx2ow7u7ZuxWqQfMba10cIR_es54Up0j1T8Xp374IUuYp93sKJbEfDqrrh5Olz2tMLUCR4iJDHkL9bBFanLZJXbAI6b6V04JkfyYbXaQ8DZjAqxc0l3gCjb6KeCWpTUIkczZI0TzCmFgMwG3Ls5sDtk7zRc4_AVaGNUO8Nigequ8zoETlH_kVSSAZa7SNRrPbFM921cR0gMDetWxX3kuHnk6dVJmZirelOD9LaMVUMUnR6QJktgIQDnHobg4bG7NPxfKERr5W54tff3Syep_Z7_fHHzE0VgMjwczrWs9YaQiMbQTlPlUwIbqxqZ_717_-Pm6OnT1dPd2U-VbswBJ4nu-sJ152sz3k9zi7S3u8fDKpP1WlMfYqje5-zN4AQy9Vs77PPtsyGsExNos58jhH61thMi3NQrclGVP2Yy8zbQPv6z_86IzOiNgPDuKpWYV8v-0wCRcmxRo4DuFvVu7tU4-hzInK6q4pE66Ds6kWpi24FnANzukdLPGta7vG2Q-5DqS0TztBXlJpodOTT6olWgdg99LxPMTObMcFkq6d5ps3DbdxJRcScGU9NDZ0h5LBJmW7hCpaITPnz81651OezaV9pbuHLYITT1q5TdV8wTjf339ZJDErOUfW7q1TU-f4u2Yn2Pku91whFq2i6Yw_Iccy0wZ71wPq1cggLOz8nPfpsp--_ynLoVu-9nlVduQLTz5PPkzR3sva5e4yGeoCe8e5OY2as9L_-_PPr68mIqTIXhmwAxnIPr32-8hnQmTNjkaPiZWSfEZnn-6-fSEam-zp7Z65T5V8Bg5DVfc7r629T7Z4_veFGo1VJxoTpsFejbt07Ll5tMBpHK8DoHhig21eovNOEvE6fSvoIh2yEec6YPxFPSqpqMxzW3rgASZr7vXaK94cC-Hp96WSm-tKAbrHPMYuemWkjf75_FEs872P3rVx6C44ZiPTVU7jmVlTtgeQm97qiHKYQXRp4NMYzCA4VoaMGJJr-7Hc9z8MCaEwXQq6qhWGWunh6Ii4cQp1mmJ-qWM-pH3ef3UcTCJmE5v9P1L_tynIk2ZagyBQRNfO1ySAjIiMvdU6hgUK_9FP3__9SV9epOpXkXm4ql36Y6pFAIpFgMBmbvpabqYrMOUYb06HAroplBhNMdg6p2NJiyK5Yyw01MjJ-VB6uKiUVHmoWviKcDhkHpmWAr_sv5udYID3OKJK7yIhbZoV6T4eZ7Jqu_ezKirVeP171JPtl4ddM64jK7PeelpypTgubmb1rMGaO9eJieWTc3My_n-efGwhh1pvPM9WqzaKTMib-3jg1srO8IL7QPPg3fI6zpqZ-reQeUiSft4xIJq2TZmiSQ_Uj7QJX0GpAVgtMA6xY8-d8vPTQGf5okc839RfrCjrRu-f69Rdz8-XLFyT-9o-_vSKm6v7x5cvWii6-2iDQmVLYWtdaq6eK9ibHdK_rsp4VAdKTHA61CHVDIMxo1x4teEDajCBscQNmaiYielqAqV7Mb8mYQYgmgLzWV0-7MSJECLO6qtriFNDau0tNe4SKaJZX3-_HzLrb1N71JjH95Kx2kSsyXeuKnZnZI0UpVHaLShV9fdr0GXUTbc4cPwsJRB_EtUakqpt8-hOXkWJLbsjZGEYFbb1aS1VZubPrmsn6fqt5d6m6TC1Dfn83uvJR2FRrTb_f5CCSs2kOiFYnYDqjMqbIzIFRygsdMXS2MtV07Ejqy1VlxV3VhBQrPLPdqagRNxcZAY7Q1wAFKyJqwTMigStdaR7HB_UZB9MwLVluoQapYayXSiqITpaO1s7jzBwlHJmVFRLc3ezHr1_P91NVM2rhPDCae2WOkPevpkYILHnMyjBxT-7NY1xXk_Q63RHXzrd0y86GVJYytNMjNTrGB-z0qIF0PoWJavdRKPDZyN8o-9zqhgNwNQVTCU29o8L2LluXyJhH7fRYnYM4KbjJCo98vlVlZlTIf1OEDSnsXa7o6qxvI0jNYyYZAH52nVBqF9yb2MMRde9qRHQThCjaxeauqnpwTmiVeXYFIyLykH13iJJK0zA9CUQLcmrG_rKIVA95MiICOPM9akdVWdmH0VKjYmKgOLar2Y0USjXUmq5cXvvkYy1QO5sNY_NPVK1mzO7OPR9sUp8Lv_Q0wAkolFJnEZ2x5YwWIYzFZX5hHTEqCP9Uos9xC-6dfYzLAr7KVCHKJg_5OcaU64zEvaYJZLP9ToO5cSz7OtkYQaz4y9_-lXMfYwvKw8NzbzgUYm6A9UjWvu57577vF-upuWuq1hXSMrsJWJXiAyw5zzyLOwDwXfX9_tM9ult52M38NBi0MhGobg2_48797NxqcPP6fsymdbLSV_C2NsUat3LhpnZXV0_bWtPVnX2q8OQfT4uY_tbz1lM2_f0_9HT9D8KV5e6jHq_mIwbmTTm5UPnTI9K7uM8SLkcULN8c2lg1uaL2WeZz_W2mAqPpqas-Waxj0epMuMKtKmHWtcnsNhUYJjeOwa2AQ6PTmZnq2SoaETOUYbe5m7lUu9lkwTyz6Ktj8ZS54TmhPWPH4VpXVvrllAd3bg-ntTuzhuU8Q3Vd99XdsQCbZ2-zqFNLcnpPJ2emCSBSRYSF2X5ylGqJopsmlrO_6ssrK9YrYJw67J1qqJqsNmCpaIiaecS6VsC40rL16kpTgYwp9vOIzP11Qb1nYtm1YqCjGuHUFnBAOKPSfd9XZl73xZdW2PX9_nmtu7tJMjaHcn-tELqccxRYYYHLRKrSGMI2F7Gayd3XtdhqZ4VPjitaqrL2Q2J4T4lBVE3FREXxzg1RqE3X3u-IWz-FIc7CD2uc1jiRw9gxNRgLkXEtqOZukQn383dGWMDMeQFomet-cfVJM44qPHxm2FntGTgIxOaDWOyDnOzEP6FygrDoIaB6pFvNppo7ceoqKfTqHriZqTEhxI088xfuIyf6KzLO_xdzdfcrlMkGk--95URd-Qg9EpWeRjPRQ0qFTg0Etb_dIusZCkt7HFY1Gj6dRHm4B9lhnbnfrUZdqqgPAnzjiSE7DSEzWSWiEW7mUEj1zMTlHlDAL_cVI0VgCpNC3XOgsrDMlF0g5WO0u2oaPNNAenerdG-2_EXwvPd1R1dx6NMlFq5kO3VBVLsAZG5zb5H3s33RS5DaozqTZ4jDqzlBeCSBflJtNpyrjcDtM9HTzuavwXSDthPoVLmRWZxgP5gIfxH16GlzF7ERoc_-zLGobQKgLJTbZHlY8ggI1H6kp9mCjDXTFq5hB8UjEFu__cdfb78Mutalqmb2fpdMQ6kuEr9CptcRPlwQPYESYHLue0HUVH3Ffd89LWYyHR7KHIzJlPz64y8e4hGAUrsLKE0z5NzLiKuuMDOMCZvzo6IYd3P3iHBnw4lb1g_uQ8bcn0OJbabgijWSYkxDBTZV5FpCffQUDd1dpjx8ukelsg__h_dZEVPf_CccYGONMuEVVFtSZcPpDL84Mw1zUuQB9bg6e6bjdpUZLRg20Rcqo8pUTO-NFfV-bJB_fovJ_vmTDgrJ7P2IjkwJVA3dxdCrEVvM1yp0gO4yc46x6CjQU-tqKod0JHcxUKefYO4HFMtRs-SItJpBFC3q7hbGiSBObVZFVdwPmGME5nCYBc9x5t497k72tKjmTp7MRMWcw1dWK73ysfsimnCFX697vzfLIdW1FpHqkdkeBmj3GOD3Ghm7F73G4dd-fz_fz-F25nTW9FQlx4g7qytHD4iiuphT552KnDUR7R4maIboqoh9DJV8v1EVcrLOYpa5gVApNpfPEBokvagcFb34dXG42_QVHNhmqYECDW4uFAi7SxqiToFJNyzMFIqpNDNRFfMR8VhuGNXhWb9L1c7Uzxgh9H4_UIF9pqGt7qu7DH5yiCdizZUL-qCumioIVQ23T65DhJPjGQGGvV7hh9FkvbI7B7ACLWr0zaE_n8NRUZL9rHVEhTJiWjvNwBKPuk9zfyBmUNJNGOui4lJloF1yqPEGmuP5C89_BdU-FhHRTwz9rOv1k6shD6a7sSzf28IMTqqh6vFsIozXPzNTHaNdxL25XzJUZqwF7a6OdYmaVmG5iv32L_-KiFZZ95oZmSFCjZ4lDuf88un2iNoPzBSamTJjiv2dDnJBkbUrWyHPs0Uh3QaNa6nyiajdBTEz5H7UUdW9E2tlVXfGilCbkZ01ud2guN7fZdgRseeUQiZr-WIeBUZXnUis0sTp1HNqiZFz-lfVzkeAsW-mtKBj8fu_Ha0DPsXpGv5BP6c6AmibZY7h5m566pPUoRKDakKWgFWnShkik1YzOR0mlTMxPb0ydxxKuw7M8nnMbDJVTt-Awz1Ae4a5dpHJXUwOqMwJVxksLkkRHDtprJhssnq7OELhhmtKys25ze8a7YmL6BsXUakRCESXxWSZBam1c1ZJijAZMUCq-ZQtOp-rzWzvrs9vjzuCi10xQmOhanGcGbxvOKwqjcbZlhWrK2dvUymp6_pqqk-XmfEn5DP45b6GWHcduIWpQnvk63W1jDknNG0O_S-UVZH9EhFuAphADGqOzL3uW3qu5VmPOcJ8mY93qcD1KwKmRFZ0dnAxCkC0amuomKrKBZsn4_bOCrYmQy3AK9nsupZJt0A_hQRaqclekGVLwWDeGRN9ff3I_dzrlbOZbOkqqIX5VB0esopFrHhxbMacRtV4nGoR3Ejxp7KR62kF3R9-lOnaFlGZzEPHus_owq2rJ4t7WsAkW6q6x7Co56ShDB7E-6miq5QzTG4P4aSpMBPp5ln0WPbxDJwEfFuEfXJEcM9W98vMahdU2brRE5MUopGpSW5tUS0ppSRYx4a17Loivp98rcX6b3Xp9FTtTLjN0AILU4u4eiTWMjNpvf030UfHiFp3j6wd15ruCDtgADNSuqvHluuMuwE23W4h2sSWdY8qamo_ydn4SL-fR5xZYJFpOPgZufkQCtK1rhtASbeIja7XpSI9KZUqWnubRdaOdVVtUQ13QLWKzyfqdg0mOjMFRe-kdKGHndHD967MtRZ7vZVFaMz5YhYXMvK8t7OoxXQBZKoPCye8kwxNh9l-HqqjiXs_lt8ZhZlbZ8pJNhpPw_SOMczGCv6M3L_8Kl2x1tT8-tuv__3_8a9acoffd4xOdX9_P9XtTqC_VY2MLFNVeZ5HhTCYNoswm86vX355sty9dOLyMPqgtHeFm6re96U6V6yaWWY1TWOulvqBb1ASLaLD9qLImI6KmJ0dBwEGBnue_Oy4qmT4lR8RF3ZtkPX4Wjk5XaOStenuUhmDkcs4VcuiMj-zrOruLh4vdLIAuBkEmRvO36yCAbCsihViNl3MaZHjLjMHJityaC0z6iqmB5WdLbAxiAg4peMn6Q6DVKlMP3-2thoaUk9OVT9PVYpKZo5Od-V-avdoybSJTLdinqdUeWrX8yaUMehUtiruJaKUKImdpizgBxrP2ZySJz6tBicb2RQusO5y81Zt-grNGPmo7lj3x4IO6TGmj9QExj-2RvQU-3W0jfp1dQ9LJuoUsJ5GobmZuhrc_Y-ff3oE1FIaZlcslenp-35RgQyL7spdZMVnlWlLq3TXTneM9N4pOpkJt3x_85Q40pghh15VZNDdZi6n20ooiEIts9SV0GcVZJUKjvNbdHr0LLqNUYjmiScbCqlxd79ukQO6UbPe28yfvY-kJVz6sIFHNOhmVuVgdKoVxsySGU4hSbW6laNy0IIjgk8tuweMwNspzJLwox-D3rQMBApVsFfGAh2DWh9r7ueO3KWGFpmPZA1H3SAw0xEqk1VBuTMzPDz0C_lAbAJOAcYvCnF5tTfFTco_f7Yuk-6z6JuDsVIjo3bMnQVl_exUGQk9FYI5_hv6WhXi7mRRsNwLUQUTfZhRFfX4yty80bGBexbLRBKzbaRCdi33TXKSIDiourB8UkfgPlnQUUGDl6px2Ndf_7r8q8eoZfawylnrtZ_NMHb3UKx73ZcBsVY-CdWumqrROW_SKli8n-_wj7FCmiQfN6M3zWydFlmXwt7PI9IK-_75pxiqine8mgL3kiLMydcHqzQwYcm7ihFBPW1VHylAp8ro1aW3ssrdamqqEES1Q0srW3Usfv8POgpGZ6qVnL8wlWEGw_ijEEJ-cDB5zDCSfiradVI8vEqQg0ZCDvm1imghgTik-xBLR9mDpJe7upiIoSDB9PN7XE1Xdc15IwmhKDwAK8J_VG2ZZD-pCQvogduTBZ71CUoX7REPN42plKrFasgpxbMSxOeLSDWg1VU16spxlsFMrHaHqRpYHn0_2w2xgtbhWIvuHsJeqpPBpL1TTXa3WxAAGbFEJ2IlS1eGey0eO9zV3KvzWmum1_JdzdnPtRYO7pFPiOGn4ctVLKuBuK57Zzaj4WLZta54nv3jXj1i8Gc_r-vl18V0r7S87mvvva5LFbHWe7_v11d3Y6AjMCDQna-vm0xAF7Fwcd1M9YmiO5Zxag6F6OzvFBVbnECMVlVLT1vcJc0RRCzjeZe5IOWnzwnFDICsHJhAD58c5D9khBOIbLFEe8WVPWKe51h2gl2iRi_3uu7W5gcnMubLoObe025-8o5u-bS5TY9Z5E6OUjz8-X6OVeDw0VIN1Zy6sFw_NcIaOsOj1CTmTuGfB9oz_LKcJ9q0hw8kd65rTadfqJlWnZZYly04x0rszc3gHNl1V_XM6_71ye8ZrWnOgubY8kREskYg2aMql3GUDpm5LGLd022nbj-Z23xEWqXNxMxr_oR5VZvC1SBz_fol2eFWWaenNWKG7o5YjGdyYujhmVlVK0KmI_zJhLBclSxu8Ql7CpcE91aJ4L5WrLVzX_e9nyRGbWYWYSmVIyI1Zjcgndsj8tmxFufBtfcRvpnV86gMrwpuJtIEHohOSZMtfTIe4eHRoyM1PVNbuzNLRbsLKvvJiKjquKKnmp1mD9bWBTYgVg-VaSugUpOMN5i56syIr9VVConw3PUJPapUW4SJQkxl1v3ijPB13_vP_frx46-__XXd9vsvv3wenHie97qdkAOYzowZjORL0WqJ5cuN6QidjuvqquvrotZg2aKkqape1-VkiV4BF36lSNMW-69SL5apiKmK2VqXgTsqcxF381hsatGLmNXQuVaoSW0OvmR368iloaLvZ5uv53uv9fX9vLUnM9luz11Tvfebg4zRGej7_VB3KCrSrYKeZhimslrKDJVl4ToqRu83b0BCqmK-n945mUQiqkpVLl5LtEuUnWMxUgyULbjOEp3-838qnDNV-_q1fv4pPQq838-0dLbU1iks23sjTstJgbFWVcmiVnigsDhry-JkbvglUrNnn4VSmOdOVRszNjU9wty7G7F62telzvEb2eSAOae6K-5nvy2Cm4EDtveYyhOlmDNYNXdy4OGnGNW8MLvDrJpOMVMFBFJtHr5A6s_M3OvVlfJ5gHhEVgNwD4Nk9lqXcsNWCTd3ZNbem_ansKt6S0nuJi1GZPbeKqKVplI838wou09QIVe5ynFwfMNLuDLyz37DkP6lnO6BiL5RHfNgXqiyPZieFzOYm7TMNGBdqQKlGZUTcdfZQ84NHQgGu_ymCmNUFCUtqtP01yrIvDGAd3AAVRWLO5BTxzC3g2PJmYMwPjd_gdq6uLNh31dOk1imNo7FD9VFYCiIgethdmOkBfbRE-opu-twHjQ9RmYObQYGMeudx2OgH8uvqvo_aegnhH9EDdPS5xXDOReZjrwvT7VfS_pMnZkLOFCAYu-WVxed6hWLs2dmWqsn_NIurpxEzSyYMFczFXZwdT5reU6jp8eUqgfpruO0FaI_rarh0VIRi88x3ore9W3iCq2SX3_72_rxhWBBBkpYBWRk3FZWhfuoxgoi0KTHwt7fP3t0VN77ibgyNy9E1Rkez_dDTbMqRiozFWiaCsOmyyP2s32tquTGBo7qOjPBbJ7Aq7avqM7us7eZrq6GovMc_HYeDJhAmwhU1enKZ4u2QTpTRIrycb9Ug1MSg5r__h8W4CKME4nKBLsGzbsd5dh9go2iMD-8iRl1SNF_edoSJxswfa4FH93SiMxgP-SNdHfBzkrh00ThEUeGxFzi_EVMAOO0qRVeRQm2TxeGSYoHgKrXTvLaPUJMW2Td1xylyMz0gYHqGb6YYKQtgsAsMZ0qM69Kvy49Ey2H6YjuXb6CkiAieHsmfI2kX6uqqtrDpueT0SsYsvtT7Tc1HY6Sw4EzjqpMhTo8q91NlIlwMfj3nz_jup-dl4dTz0Mb2OjrusyR2ToDWGVDUblXxK6JZXtnD2y5qjh0zJ_M5Raqlb3CFbI8ugsOg5uFGWRmqq_X3Vm4vHrC3XRWOLfJfl3TNSO5C8tLGjTJA897w8XcW0ZSpkoxBlPg-8_0FcJ9jqiaVyfLPdw11vRMC6Z2Q_VI8_SgJc8nOCIKYRJDWkdphmI9Fx7TFdcSTqgUU9MzZqtl1GAe2RlxxRVqOq3mTsk5EyJqxl5BuD_fT4QPRqpZ2CKyVqZrbyEHESoWpO26OZ-CRaSVTMCriBMRQLuJpiY0DXCjEZUFL47W1BRmz96xvrjeVkI2SFqY3rmn2jwAaxWjnQA12vxp8rE3PYgYFrIWFi5gtKVmD6GTLc_PPZL8Urp5ZgongtzSEtt92ORYvgyi5p1MI8PDn0wPk57gQ5YznuOK5qkBZi5SxLIcl3M1dRkEh7OY08IcSJk7VKtrv1N1PPxaq0f2e8dancmKcO00U9YtyZp0j5nurP1-uxuLTLLzUGNtTMlvQBcdXu1xiYq57zxVme4W6P5-iwwIXVHtLhWllY_LcYaJlTlHPq96RkZhO_NkigY95esl3VOq0gABBVq5I5aKmgfsuDVGPF4_FOrLobazPMLX-uX33-9fXr___bdXrH77j798TdX757MrD1zvMxeLiJl-6vtHvMx8TKtKTFeEqMYVMrOuu7MiwiAwM8Xr676uS3rMzFdU9aTs5z2irXNdXzjdHOPQelLc4QEIRCTcnr1XhLtXN8JPF5p6KbiMFB1n3UqcX0-hPoM7GZuslFNk1OnPAIensW4Zf9f38zwOmGpmqrDxP7YCbH85uksUxfMrjSE8E01xE9fS0mXERSnAE9i0FOPRll3PUyLTU4fJ2L3_-EawdLs-byud3M_3t4cf209uqWQ4sHsEA7PpUeNFRSiTYmG26hAzAV1hAq0sejo5luZiWWYsghVkuJt7J400_uxNJoGZYfk5Sx1pBZnv7RGmiKMQ4SCyr-sl56Ctw6NQLDPnatQijspIyD2HhHksmbFwJjChkEG3SIuFVW1eFUSJC_MZ6ad9HZQFiUBCNuuZV5b2iGi35CT36tOjkKlk9UuypdPVZ2qO6RatrIxAqsD9l7aMiqDqlE11hJPK0jE3HXHnhafNje5RixCZFZBsqRF3_oxY-YKH0sOoYmoMyuuIQ3swM25B0k5pj3Eb0rVbWfBQVTOKKf4Z3GII7xCJq9RcWC7nf8rRjoJHfz4izNfOR4F3l8PVMIzg13ZDZZ434KfORMUBm_jnDVDN6ZPOVNYI7VHDvSon0N3n3DUyGudKQOuwmgKYXWKqAyG1RZRKaWIYOPUntocIURh_Gw8qVAfsVs6hAXFYMTifwBGJAFoi6i5-NKOGgQdRJarStbHik5OTGXQPPKoSbsN9FG1iAjPMGbiouQlOFObgyWfEQU25-aWithym1y-_rnXHfYGsE0XtimtN9VrX3s_IrFhupqMt4q4AanqIVMq-1upK_gkzixVeQra6kkAz0RkIyebd1bvi69rvncWzeLx_PiN9v15J1kFxS4CqEkN1V46bkvOr0pWlpEmKxVI3PbZZGZtV-S0yaspqbmVZxJSodO-HpubpsvjLvzF-IzpdGy0WPtUfXcMRRBAQSI_paVQz00C9y4kKsmWftFEoRmcEMpn8eomom5uMiwm_DwS35fEmcIV08p3uQn2jCB-a-s_JnpK7XBH2mWiA2nOZNtfOMovOVkF11S5aaXlJGUF1S253G0g9bR5VrQyKPXV_3fv99rir0-MSaVWNdXduViCqmVqbG19Pbekh2ZMPYYWES2XXTGaHr5H2WDMJaPiqfPq7VaW1zaMzdcbDIDKi4aYyl7lf6-f7fd-Xyhgg0grxMF8-rZN7XRegCLtfy5eF6fPkdTuR22EeV7g0pt29RQ3qBnfjwdNMa1pGwkJkwiUclb2Wt1Sow1x23s568V2sgpmJyLVedHDCfIgYAhbsP__IMIU1WqlenZl1R-eWnq450H6YnO3W4c1JTZhxhC2wGc2d9rmVzoyZi6R8VHTuISNzsvIwM-IjlG7gTh1FuAiRzzIzETEz5qsyr-vqTCEDzO3cOLgkUpgjn6qd9Bqehu40zRokFUhLy0iP6sBwrjEMN6qpWuX2CM4RhSgDaNjV0keFoaPmxYgipLNhzo79tMa1zE1xKNH5fszhtkZVpFQwRO_mTDYGuVNm6imi_YGQzr1byPBVHR2zYJLCHMkjBbhIFXOYWWfDIRZVE04JkU2VX67mPSUy-493q7jFJDVmEGWqS8lpq2koDMgpdbQyPKLd01M6qGoVrf0cfDj4FhHeiisrlrsbk-Iwr6pwm6qR3s82U4P1NDwo1BMdmEyPq_Tk1GSnm-Mo7tXMT73JdET8vjMzrvW8n7huUMEHfb7_sFjqTEzKmMl5TXNKPEdFJ1wktYo0NwkrslLN1JTkClqESRA1wGMRLt09X_cXfwSdDR6UVoy0he-domprrbX8Xm72un-8vuL3f_x2_3KF6x__-WfEyYN4YFruWCVzxT0qOhUIgwtMTIyXOYy6ujkwzLUKUW1nq2YRXtXXdQEaTC0S9N7pZjLiHuYIw1r-GYWaml6XW7hxL8_Cg1nuzUw8wzYM3mSVNseY8_3z4UtkdCo_QK35hH5N-0kYhDRIjE67qozmLvPopAFD0NMcmJ3nOrrSzQhwm2ootEq7ZtdUyYwfKSzFDtLvFGjEvfeDblMTtOTItGTNs2Ej1b23drISSlkPWcoKy9pzQDoDQ1arSb5_MgV7mq_VHjHcQX-4hyIK9cxSd_XPpt0wnQcjCwPUzMn0Zrti5OCjzPglQjNL66uloODeO9x3FktJospSk8NHppNk90BETzudNsOeEYfJaivezyZZCwKYZbWd78J4OCeRBJt2k9VrRLIAB2jD35C9H8aDeSrSKhyqfSpMuqcla09vYmqGG9JsjjwUQuCmyClWUO12oBH6MYoOg5GnraFsxNK92HJ4NWb8KHpkppWlWGPeh9p3E9iM1LPZbFQ7GdXMNgu4ZZUGYITIy1qv2hui_DDNrKtVNNbi8e2Ig8w5Ce5uN-rmVIMRe4iIrVXVovAIC8uquO6sjDASdWpKWJvpQnhPk6TMwSs-B3_1mGm3a6ZExAzKAm7zEP4p7ArpmSQbkyKvzS6pGr9lByQlSkCETnb3mPEaSpZRj1S95bw50XM8wVyOHfLMiapCptWph4SpyTAAPAa0SrbIjKt2E_gpxwxam50KLnCe7w2HR4hwyEVFiU8n2RoK5QuLRsXpVi7QdaDaxSE60zGczbeI_Pa3f4m4oOgaj1B6uxgH2Fl789p8rxjV5_0TqhbGe70JARezn-rs7MOZGOnOdBgUm2-6aWL7YfrJudTZX2UR6ip7DCjpenjCBJeQw6IO2SKci0_6AvfYHBl3q9mdz7ufVNkqyW2OHjap0F53qtN8GVXa-u3f5RiDm0JCV5WWFuZrRFsM1lkqYm44QZ9m_pzUkSYMqtkNVlADphiuPUk0Y3-AxKGBSrEEDFDwTDOzcU4sg84yv9kWzUxqtBXySajJ5wqh3TXDqv_IzGip-1QSPMLuDv1yRVG2mna58v1DzZvJNCxqJpaj0s33-xse7-e7RkpG0VJUAxW5jtMzSPqDM_MQymZE0Z2kqM6Ih5nKft7X_ePJt06rwlcYdDmfFJxi8oyCP_54m_s7t8JGkbugtiuv180vaac2u55SzT0m8DwpgEegVUX383YYI2huUBHiI4pBJtXXa0EMlxIGt8wrt5jEbQbXKZfRaV8-3YBnpUBEJp_85X7t53E3xVTm9fJ60hXTvW5yMwE1dTgThy29CwExTOfLoo92RJYt7dbW6bLQS4i1kjFdy0UkLKSahmne7DtLRUfaF8VDQs4jo5NNPcrA15Ipd1BkCgNvYqKanZ-xlI5aZSp9fi0WJiOZSdZCj8C0d0GkKyuT7h18UjYwA5APtY7HJqvVXI3SqDstzg69YnTOrngGI6ePZbw9wuN69tvg4gpTE5jo-3uLcc0rPV2SAFZcldsVIs3A1UxxVsuDjkypaAiG71GdqaHVCSMRyxwKSH3ifGpqYJbAfBGqGe4yqmJu1r27dbLvry8_KwKJK8iHcbPKNPe2MYS07MyIGM6lDFCpqvA7a8PgQGtj0FIqMpWsxTzP424zncVdJkSbhZDa-4QdRURk-UU7jMh4-NAuctKmFldIl4iNzoqbcdT9lBhAlRtURNZaZhBBZU6LrzXVOkZeXu43LNa6OQGZanPur6UpdKvu6bXW1CiEr8bDlWj1O6raYLFuZm7hZuYWXplZsn7cti6sGAYLzK91m8eK5SuuiB-__nq5_fh6_fb7b-EQFa15vZaqVotAV1yArAgx5Oyv68eQT4IxESM5e8ZgWhrslpvPzH52TzPDpgaEKwQUnIMKnnFTEziMXk13d-WSXGKZQcNMxwTW3WEwta4RlefP7xbJnaUzPVj27FwwNbzfjy8TkaoebmD2lhbpzr15NCQo1Q0jkpWy5SyKoOdLdPRDPT0nUmg-MuEx1WZgEdZUpUtIJydPmacawNz6SZ5WpIsjeHPc_sq9zdnvb6hWbjPRrrM3Nq8qVeROVan-dL0dJZuYFxNIj9Q_uW7oavdV2acnx4eHQ_SkpbnwDL-4rDfzSoE5J8jmITT19GFeaA0iqkZPZqGPXSdCavjLRMw8FbbcGc6Q0iskEYSHG1RRmWqQEYOrypSs-2oe4okCN5OnuZJUd3q8gqSdcIi6R1fxaRlhNMfvvespqM7UzHRPfqeatZTSP1LdOmaWXQab3F2lA1qZe0qGRS-BjIlg0LW5O-qzTDeS0ThtJcZkhFOqpqMXBkZ7-XnQgcW1wHAHOcIJoKhND8xERMyU7QgxwN1VTU5LUqA1YKnzzIyY3lGLMHNxA_cy0yKHXWEnEi9YvLqchBIxpsRVw2Km1czoHGzletY8uEZWoDv5L60ALAh3lDOKlRapTtHpvSklFFYpyDs5PuARDuxFi3YFTkAULHF1dnXriNnKLnUcXghAvIGZqRuETpYDMxWRqYQZTKpGr3UcHNMH2aSH7Pd5XwuAhhwtMQF_qn6_dm7FuLn5NVUerph-tt-re9yvQ1uBiUjXwBAR9DJ1ldL2Mz068yToGwFgLlyc0lL3UWd8_fJbXHdVgQlRaETA8bzfOh3X8rAfP37L2r6u8HDXOvIJKSomOWIWrZ01teI1IhA1c8pS_VrTLTUY0e569oz2zh7VFnjMjF-fUmTVdGplPU_1Ewuzm8rLnqnOiGtUK8vgvR9aL558Kh-pMmjvx9ynlSVbrlj9-hLpmXa_80mFesD8t3_vGQuXLurfAAh0eK0UE5nJUjZQZUAKgRAINNMyih6VGTOfaQON5j08snc7TLpVbWqLiEy7R-XDPohID0Rgolr79O1U6IJtuBFvpzJT2_RcpAiQgoOpXW58Schqkd5ljq5sEaifRrIdAqQM0ZDCUkpD0e2-euY8ihWdrTguJ4FkJW3ebvQg2qe30GPoHjdnzIOTzmeXyggmfNXepCSPCOc0082aS3YCUIgJumUftSQL7Pre7_C4bq_MWNf7ne7Rs22g2u_v_2F8loR3NcWi-c4V9lSZxbqc9_ZRNLSnqwZu5LjNCE2QbAgxaiItEPt-drgd-DnAsaU5zFx7LFwnr8t2Jiyq0kbOHQ9qMEWYgh1H95VVCl1riWmNeixTCcMY2OYxHaCvFX8-f6pAzsNTjTkF_iYoS7hWT8LUnCjRxqeEbsD0hHs1GRmYGXfNXXJee6hukgS62VMowCqZwGuDzow69nuzeaKiO1O6PVwYHeTrqBuBKsYJuC9VCMycbz4evqlUNNPpzky-CPjYmpNeIRTL-XCckcq2tc5OU-V6fcHcubLpnm6xgVtm86qjqpUZvmbII8tl_O0aVTWaN1SzBzUG5GR3m4c0McBAmJj2qLSpGzxG-bFnZdoVHh7uYm1YZnatNdXrFc07AMncOAV9LoK7UkVIJp2DLJ9PxK_UYYwUTtOVRFofPR9MASm4hxyVmZbKYrhX5zgyr-s-WtAWd-O86MDx3FW19jaPVulqi-gpOowpvjAD5mBb8XGBV-UVX8M--roZ2adaZkRnGg6pHkFPkzWsECmBDPMPHIV9JGJjFi0KtVhfez9-rViLq55YHvdlERDBJwFME-LrL79AplV__PrLL7_8QMu___s_lkNGVPq-YkbNY1e9vm5XOrCH5F8zojV0qk2sOnvawkfEl_fUuq69E-447Zda91XVnJDNVFX9-TM11MKXhYWZuajcL3ceB03cTLVDz0-KR2cQRRGC6bhCPtQOASh6F5WsojpKZF5xV_eTaaftIydZCnFH7mQ6ThggDa1dgPaUGUQqd7H8QAwgD2P66cyRs3FsTTyITQrbMdCBTjNoQ5hFi0wXmYkqIs_7Icm3-1DiRCgYMZ77AD67UqjTmuLkh-V-RkpgSlXWkAzGJxjj_qqq-uymB5Y-GarlhdZUZ0xR3IPMDUQow9TdVJGooqpZdeT2RWUQwaM1G8783wqnbTqz3cSA2W0RqlI9HktUKE5hwSrc3dziIvd77ww3C2CZKhkYE34ti-qmY2at6_t5XysMHA5YVhpcejorv_P0MIxrNKlK9vylJ3OfB3LSmIvOmt4nrj2fb5-CwEsmVT9ceVWjDc2GufZm5V56ZPQAz80Xf7UkB27Sk_NwM9eMt7upx0ydZ5r7iGZm3Gt4Kpizy5MadYM03CsTqmaLLg2FyTSUZIUGG9j6X51gHnnr6bgu9lavtc5GaCQ8YOBhHt20ac4_mdGUmRhfE2JmEK9uDXAgBRg7x3Cv5_2he6O7lGFOc8a5AecvNgLDxAKzhHOw9HCYO8xh2O_H3JXdtmqPIFsAYtLnJjndcGfFvLMFZ5ciaj0FBjcM0wIiJd05G4XFjEDERp06ZLXDzG2BQ7rNsd9_8jUrp3HX5v7sTbYa9xpyHhZMXRnMWsdOB0Y9oqvssk6ywjgWh5rl9_uv__EfEPXlXeMwcpPe3xtuXGnwOh3hom3QrrnXK2s_z1ZAuqt7v3fPhK2Wydx8Fn2_v2G4fe1nz9lcae-CmaCnZb3i_X44mChakWS-__jmrUphU9X5MGW6nw0DIeyAdktp8TU3cJ7kdEZqwzS3qEGlO__Z6tCe5Aze45Ku3tuuv_4HY_o8yzeDDSOQsQ88CHDyPeHXTKmidgkUMx-cchlMsqgel1OcJm0AUyVE9RnOSb7LHI5gaAlmky1TcPAfxUYPb9idxdjHKQ_M9Ii5m-pIAUZ-6kd2rVxwoKdnciiJFFFMDXfi3d0zomOx4B_UmYoYJEeBnVUcDslZYTvMdE5eeUF0CNFz6N67Oo_JFuqLPnBojbuji8G-88at4TYw3HX6eWoIM1kxOk-WufAmRl15ZRsiMwNmF_b7oeRg-WrxO75yRLq_fx5a81qXohEOiz__84-1zD2ger_WrvTLecnuGXUYpienJMJFitNEmLqDRe8eXSsuMwGgyCxVdXcxG8MIRHWZ5_cOu967LFyktQc6Hg7YrjzoeRliqkVtIKXcYkpN9UzARC1sgVtUMwszFW3Zu2356Ci8Ky1MOWjnwlSdAFYV9bXUFe5Q6hhRU6o2IpmjOhHeFAgxbNozmVI13foZw3d2TXuE6IhKGDuQMtVk9ukUYeGZzaqNyFQXRyBZm2X4nsGxwIo5LII6CPloX6h2dvMeSXZdYKxRQlTYZ2Cdd0akxa26GQkSnefZgKhB6MmqEhISp7nxHyUFGqMDc2pW3H1UItauJ9YSonVpJOKIlyL77Liu1-tH7oywYbpxUNPrtsF0jS1TUyjpR1oyy9yB6laBAW7mqjBI9bnjC0Qm32nhJZWZJpBioTlHde-Ek-4lojCVOEMsaqraPuRpaqc46-zstWKaVUGhpw9AliDcw3kmrBmFTvWR4KjNiLk7PPdOwvJodDB_9oa7wUVHEVU1oiJeUqYhkvyS8uVDMMe5TjeZ7go3JgIpBbNwN1dA3RTi5vCrp8Ncob7C1Nnnt5m11hXX77__5V9---VrXX_97dcVLsa7RBzb5b3s8CU8wihMXb6qEtCWqcqv1y9KvbXinft-vZ79wLwpXyX1eQTw_fMR1v3D1_J42fLQlmUmKrHCRqHqih4xqGJevhT6fp4rQlS6W0wDQUCQKKq7WfmA5t6ApbQQdA19ald2yyDW9NZRFRs51ogjtDCMaO6tDKA2hTA9J8kpvJdPT_cYrJOTqDnFVNHMhjGPYMOupsLCh5Ow8N4EQ5PQjZqWwyMhXEWmxS5XU4uL-xz28IQUlV3uih6dYiiWY8V_yhnoGJQW05ijw4GM9tRQO-JGlWllGWfPgSMBWUtZpFH5wBmxrlfVZuWDZcfDrwBEoIL9PHHfBHDH8oOwm64sW845HXwd9Q40M-O6p0fUajpIYBN5nkegCo11AYfvqWbrviXFzGaICBJVlJ6sf7h1Z1cbUJVNNBX0KLhFOrNr9vthPeH53qpSuyo3zJVVzhkLrW7egs5Fbc7_KcYCCUfxWpt0DGIxx9fipzc0053Igk6JhxNcJtluSxRdow4K10ZEYYgQmevrElFKZ-kQgEV2njG5SGkrSRIWRJGoGYftfi2QyQiwywHote5W7h3N3KSP1ZR4Eg4pTnzJV1W5OeWV3WNOJrWxQ6wK82jO1MEI1shIq5IgzCiyfFYZ_B1hYk4BVRvpA_jkaYkXjRkzoywwbPFll7k9lupMF91o_NhJYYKCkTIhipi9eX7zhqlykcqD5Be437wX_RPeOnVUuHxRDtCEQo4SsCYqo4O1SDNo_oyY6HKXj2SY7ueaIomza0R12BCwmGppQazOPgVBOx8mzFT9l9_-FmtlN8Su-47LFYDDw2ukZe7Xa7pjuapmlaju_X7em2Diyqonpbv4qjukWunDDfPRViOrqfXMk3DgJd3THZdPp0p___HnTJqD0OHcbxGtbEBzb3XwyYdjMdf93u4xM92pI5Np3PiImmOI_tcBWAnDsUcPXbTpJma__kMUPQIMRNRQkhDlcHTm9Fm6a5SbtsOckmpw8spaLegJmh5R7tc64RBl9nG4v4DwR8bT9aexqcNrIms3LCzTpMJJvIKBH3KQnI918g6PlVBUepTEN9WucXMV5aZAiKuCnqYOFAK4V7NdIDDfuyIuYlCm0iDO8_oI-3ZaBUPVQIcXLcLUIqJGlwe_hTIyVWxXNXs4cIsAIK1kyfGrl1kel0DXutHy3pucsL1355RMdYmatOz3dlj3R_GhTCDN87x7-uefP82samvI95_fM1hm2fV1LQdEZ7l9_3y_Xq9QvTxkxuHu5jMuwUUPzN0sbFFaCfiKiPD9PLT_jswyu5czMHYiKyc0glH9-svXdOGsX7WqbXksz73DPNwaozLGhpCpimblWs4xiZm5m0DggBk7voDa5TtbVNzAWzsLhNzYtExEdKWZM5fpRqxTV6XH1RAZNYMh8r1ZuXr_fGA6Vb0pUunKqSoIyEqGojOpl4RMdXXtbukqagdGm48sFkHNoG7v93f4qtqqouMz6C5bi-5xkeFerbglYEFCQXn9Whd_DjqDsBM7z1l3sO3NDELAWDefmfB43m-F76rJ4i23tCHWM6QG5JRx2yY1crqXOmpmNX2tu6emlRWqOTpGxFqm9svX66JQFiaOiMVVL8wROiWAsTmQlTAWsMbXAdq627RUdURMjavsbDqYRebn86frUlgL_wQOg19eVTA7qONpRlvPm4yOItbI7FxHTcnkpXWuiJHpLDX4ChOnGcjMBBjlEIEjU1D7IiJdpSYKx4iEf__8ua41TSNd_Pnnz4HArHMDyPf37NIpzp-qqaRRs5DCNIkX1i1qRja26IRfjPsy524ecJmu_XNfV6xr3a_b3b_u65e_fH19ff3bf_uX__f_5_85b_lv__1fX3fkZAlDXEqjAgOkbiGQaskqN1S3BUa1ZiJMFcu8Vc3cVGF23cFHNe2nOoCjs8gsbkGE_bLW97vdcL-uy3QUBllrMc6rGHfMaKiXzLWWqCxzC3e1rq5uGXFfVSVq-RSJZ7nTFKpMHfCUUGiZTjPwHYYj-APRiF2F81oBzESxnzzhS2qfyBcxI1pEj-mKB_gzq6-WEcwMt3br9YI7sUaSBVeucBE-faYjMgM9GzYN7xFYyFF_COZcNmnNoTXW1N61zWA9k6WqVcJuOj7elpw2tzu-shLmaphuqHNmTHZW15iHqsNvkVnX68kNRVexSFB70xja1ecLQfOOua1Q6HXfA6nngZvUP28cgvCZietm_LB1WIU_VlbzBt21GG4urwA1aixnmH19_Xg_qco-oGMpgHwSHqIjDQvk89SB8Nh-NlSbNVvzfPLoGHbCpCehzpC-COsco2BeqMkM0W4zdD80bDLYw1KzEAXjTIGyFqFnkjHTOofjRIA9AHM1oydemgLvBjibg5KxfeJGxkODuXOaQH6iynSNmpmv2vu6X33apQo1NZuZFXd3MyAlMjBmt8wimFfiK94jzCyz-JsPWBcfP1wkcPVxxL-iPFRhqsgekB6F9UjPFGPrqtnnHiDVBmetnF07hrsHqjRMMDAhAjdIT82nqcxPe3BssA2LftIMMKssKEAlkHJl3TDT8KYGCnZ4J6RQdKsaToRMDysPRiCe0EWtMMfHXws135WgEDgwXe6rkobxT4HY1tCccxAIamYt0zPcOBGNy28_HY8KkbCZwQpO_qt6FGD5UOXHb7-5u1JYaWZGb-6IalZBBaP0qR95iPR0u4m7tcrzvNWEw7OqthXP85hHV611Z9WMPN9PxK3SMmrBbKasFTmlokXo9U6zMJwXDXpG-tll4XCFRz2PGEQlqz08d0ZcJfRhozKVN9KDGJVWrWo5Gz-fmqmGB9-JlVXZtn7_N-JjBWquJIFIjWqzzQ26R9yqk6uHkQEfFD09KfLZzBBtpjZKc0eTbVvZMPQUsVs6zf6HGBgaE_6KgifjhtnwsnfuBiM1Yk47kvR4xLngdveo-TqcWWF5SEXaVD87ZBGF2SI7YESBGMXp_nBAATWmv10zk5mlE18egTqroG6fa7qgdsHBdrab79omxsQnLEqlulLRImqRlaP6PLtm1rpYGDUP6Ozszn352jzg68BjpsNXddXur9erJgmS-P7eap21v9_vy-LJnJZ12RX36_r6v_7HH18_gszfGbnjFun9PCvWQF10WOlXdvtbumEWznk6RCW7uKmMFWwxXL5UjZJXUVWd61qqQLXbOPz9JMJg6qYtE2Gu6o4uOWlLOpBEScKAqDPRQ0_k2ebC9Sg5GZSHaJipDCzM4bH2zrVWdhHx6ctr2ldo5VoXx6IMRqrxkWXP3tNibjbjItNbfAAxValSO0luBdO85Qsj_LHbzEy3LxPho0poETr1pIeKa74ClDSnsNWdnHDwOO1xPT-_Aez9SJMHt3HuYGiZxrlHcZws2qquUIPGWqpun3dGd4uIi4p2d4VTLKp7b8HIqHJESqBqE6lBTFgxunN5CGJ_f_ta0zI5Gmz0fypPERTHrGsxTcdNiF_hkPzOcK9uE8MMTNGyeLiPOIfvGRnYMnOLyxQyor5c5XzblkNmntw_Xl_VTfzAyBjCDGaGk7dVOlP9tPRAhhrrhiNatT0CiuVKpJIp8TviagiHGlSvWCOza5uHzAA-lEQC131zBvx-P0aqDwEQ5h4xXcZIcCeco32drslHdXTaTZ28bb4UQZSeZ2e4m0HDTfH19aP4IjTQfSZG1BzmaAE8zN18rfW3v_3tvvwf__j7dX39t__lX3__5cff__6bucay7CI_j129fPZaK1bMjAItJS0m4oaqrhk1k2oYjkt52s0BBKKm6V35XLHkU6yfwnhYyXy9lowGaAPjyYhu5cML41JL0YCDcxwZtnrMwJxkl4xOmO1nmw4rkiehJDMlXWMGbTm0RlE3Q9jeWVk_3z9VBV29s4ltd59ph7UIdXojYhYj3d27KNrQFaz6CGIRWcbjpKpHBKVfP9871iUz3SOjfl9ku7l7vr8hku9UOG3fcd-EzJg5SMkjI4WhWOnMdwMzjaYJhNdM5rKN6K2SUfduyU6498hIQ2E8KuGMwI418MAJvKrjunoqfI1QAUkou7p7d8e6R8T4aSg8IjNjrao-u_ehLgrqJqKi7b5GxSN4AQYADxHtLl_OgXHu8lijra0KDfeuEXMB5auqZmdU76Y94a4s8TnIDmI8loQlVVRut5NV69wQqex8viuzZ3raRkSnMxUyLFl1HWWvHqY6rbdirsI7BoScFxEmuoT1G7czNxVht0FGzEzN1fC8E9fqal8-nNECBM9JN9zjvrjZ66nKopdDswzqHt0DGCKg0IhRhDvznyZwt6yunXEt5YbHvHapg1N8U3A7PTPXfXV2rJhpADDnk5NpN8bMFApVPhK7_-vnTjYXfyV4uOaLm6RGNRvOCTw4_rcVGIFQa47us8EgiY6FbD2NemU6hsYp46xWRM16hkVSviT5b8GlWjfpTjxzHUUB0aFsZn4Aj_x22FTH9cWlBECgn1SVm3msqpSBEbRm1k1CCw6lAxARIj2UGdRRxMlMzREvqgCV5W6G0IPJ5PtuAKjHzEA13H79-7-suCxWZ0G1u27e7lqkWwiN7XaPqa69K0t9AbLf21bMzH6nOuCuAulyt-fJK64m9nzazMlv_BifGNHtT1pPRnKmuzZMj8VSppLNb_5dBRYYsuB4vh9z_34_M9JTVcXByky5XaLTKi0pA3BU0a2Qzz5UOkfdwmH-27-qiJsJJXksDp9w_ilWVxVHLYBhBjIyqao5qaqGKNqz5OSxRlq6QFezffCajumDGONCr6cBK3K89HiLxIwnRRHpTEybgbNJhsDIIS0OgRhEloGA2SD9bJP4WODXaEZnmht_4ro5STpqDsWomoUc5AtOM71aR7SlqzpV_bg8hi1411Hht_p7__QInvxKRmEG312q8DBAEP7--V4rYMj3Zh7uJHRhfQBhOJiIEbM1IpexiKs7C7qe_Xas9_sB1n7eYqcLbWPfz7u6bHlWMrk_rSI52o7rE6A_NevKNtOSGUWeYYkVb_OUskF3ynVdpGmvcNKLySj88-dDTUQEKQqDmXXF-71f91dETGc4xPF63c9T9x0cGp1fKmj2VIuRXahi7hC5wnM_4Yuhm4_H1NRtyJqATicUFKDJgfaMmYe5ijooAoOqxXrtTFO9bKH5gigDpKXqfO2__3x7OC2lEIF7d-som6cCGVHyFrrLhGcaUpALhwQ5ZthV5s6XFkylRGa0WnjjCkZ1tKWPkarZD9diU95Eq2WgKghXYTjSh0p5slUcncnEVD3pBh01RPfmzU1wBKiwePbTo1Ptxvjj6mFJBFXld9STfq2W5uvE3Wbket1mnt3XtaTnel12RWff17Wfb4cHxFyvtUT5K6O-4qyYpX_8uMmxJZ_YKbrHoXzVoY5pD8ZazTvLeTE2NSAzOao7JG9FjcBgHm4sRPN_nGhUwKc7HAYwvb2uq_vztIVy8NbVo-NhUx2vO59t4foZJ3MBvuJSMOczbFfvzFg-7KnDCTsxg3QJWqsh8-RDVZyoNr9gQPdjwSWAw5f5qmbOO6obyyBGe3xVW7iaQeXHrz_C8fd__P2__bd_-9tff_vl6_pf_9f_-Ntfvpaqw_bez3s_7-fYIOAts2JBQc49hxiqWrn3O3sQa6lK7jepFzUjote6Bbr3u7pVSM9TUf1-vw1Gemzl_FhrRjvr676n63q9Bm1mUHFTN4D2QPhMhZtMVyY1FNXNuZWbN9D7e8yqM6empHZ5OLE_EZFZ5th7ewTpDaHqCHLs6vnm6zb3hnnW5nFkdMJ8RupJ_efvGHEMbK_xBDOdlPecpj_3BG5mxLJ1NQtvzG_MoLo4hxOR2mmO4W853CKmRgCp5HaL2X7jnkr4UM3uXL5aewSnC66ombUWY2vmqzvXtaZKWKHrUciunh5f13RbeJHo7m5uiDUHEETgCaaVe3I3g-P7_Xa3mom4qme62Gd1JsJFe8Yvn2yW192DgaKgW1uVYMfruodBCnMVXVfs5wn37uFEXN1Vh5N2HvZ8xWaFI9zce8Svg0W-r9effz6-DO7uPtXXvaqyVZ_9KMjYNR4AsuvyH70fBYtJ2oTBcL5-FLqcSc85dIrKCNxIHneKOLjxMfDzN_ezMrZjROYZOj5_fWaMHGecghcPs6oY6H4_jMaQJqSmuWukR4ldCjUexG0m-csF1RpVU3P3uFpKxMKXhzPK1dUrbplmlOBoGdgxo7Z4hCxMKuq4JnP3pGJcRWQc3jMKcbWa4_CitLiTeqvgtHuOzPhoAuT4cHW6FaZuVD6Tx6vngSBzlHAd5sRbkYM2osLpv4E_jq6E2alRi_KtzCHUiMBjursSwLIvoivNjZkNBadDKi0K_oqR-NA2gJvIEGZFmW6rSsOvxSY3zFVIrTAVrHXPMWrTh3BC759Th860KHI_RiBMjzKiKQLT1y-_rvtrZMzBn0VNh68BZwuz7osRo-u6uksx3W3QzByZiNVd3VNP3VcEomZGxuPgB_nt70zuqPh5xb1GCmZdKdX9pI5UTeUDlaoW2JkGcMqTrZ-PF4rRVlKe0PUkIHCb3K0ztXlnVjHze3I7RoFW5qth8Knq7Jmx-OUfvAkJxMyo56aeRgVwldMHFhWR3DIM180nd0fy7JCsBOiJhTFNC5UazCefh0tkaOpkW00MgKmSLKZq1kl-5EyXMaitMjipF8ZH2C3rnCN6UBUcZC-BcKImBlEi4JKRL4bYiHN392GQMQ_LpepT0XhKTTtLFZ3lLpTpwM-lrZltJQRHVRT3eulAR6tazUhMDnNTdUNm9si67m6C_8cjnuf5gMals0tF3ffz5j17P8_e-_vn-_7xlTsr90hZmKggrHpfZj-_n7huSItMrBgInBE62e8dHs97x1r3chiHlKie67qmy1VFrUstoAE1DXPJtlgtvTxc3bRVcIq2jStcdKZ63ZeZAtjVbjHZEaaiEUHAcGUGbK1Vz0D1Cms0ZSu2TmxcVLlmETehrkYBc-UTnpEfg4VzJZKZEaZgGQG-Qmau-wX3yRYaPZepu9mqzqw8dfVp4vmGv2_cxyX1ZOGGD5GLSN-uaQPEFIERcZVK5q_qyNRraO1sHcpTzLxqUy9FyxLDNlDUUIOt1WmwXQUHkXUUYyusq93IgR4zqj1dVWvGY5mhspkAloOu4Z1FJLO6qKPqnCNqVUHAFQ7TqveeOZR9qZ2-jI-jk4NrYcIjrosPjLjCAhHBO1juVBmP2Hvc3VfU1OVhAnfvLBg8vLLI5CHlLZZVb8CgQ4G2L5dpAGOS0iXjl0uXmXM2FO4OExX340MgsPaKNSoi6nGNyrGcyJBP4mE6WnMqRnAcsxI-Rj9GdosVYYLPYMBaC-GjoxG508LPqFLQUub2ZNJZWVWk-OfzhkVnSRaJ0gIbFazVOryuwE1Gh5CPgxPQiDCDX0tFOtugcAfMzFTEVU31X_7l77_9_pdrXb_95dfXr79g0s3HZ2T--OP9_bz_7z8ehbWCS_-eqSSEln_Iee9d1RDbVTB2lMJgpmYAEQVVLTKv-8VRopnBDJD9lPQg8PW6lnlVXdfSaXN_700x84K74tm5Iq61jAXfGgU-kyFbcdob_QlscX6bu1ksyV3q_yUo3bMdTMaLUo1sCIn3fpNoOTNThEQjM8lmPJByBhFFdKamp4U7ipZZ4aVanVDwH27GqxxPuKTGlRIGPWpuMK3pno7LaUXgtNBer1Gd7IE9WUIlkEw3QWVSI0_np0d-Amsl4u6cbWEtYZhENffuEhhLa5xnt7mRL2xAUzG-lq0Ft6l2DyG8BQJRNcywjjLnurycpeSeMseJlKhW16kNmEmLw0QEcIvgzF5PRVtFYRGi6OosmmtNWgDtUViYe6zQKYIsyYg0BVN_MuLXtb8fAFnb3as6ezM9OCSXNVll9fN5uj5oevZbZ3paJlV7P4_CJTf5HB8bA1UqUBFT70zpOW7d6eo-O1J8ou6Kzq1zosdwg18KqepDkhdxItXMRH2OkEeFGfcZhez3pqurdquKWvCqKXUSvCNmEQrtZyNWF2WRFAWu6WlpxlpkSM7kqcDYwYM5yb8whEd3O2JmELafjFhnLQeVOXbYD0JRYEaoPoOXc7RGEhZsbHYVDpIENWJmTp1wtvKvw6obanJuTPZfgTe1A3cfrW51E2j3KOxzW4weBsPPPoRHOOHXROTcw_W8qeGAW3bq9JSYAay8CAQCqJvXU-pa7EKMUeJGtgfCqVcyccCrhmBo_jkpmBeGfWREhAV7Yg-YjGP4q2fUYJ8Eh4xy6uxu-X6-fvvbWq-qijAKxRQYnXp2T0VYZl0RQwtNdWdW1n2vGcmnFVq7zaGjZj49Anm-H3e3ZblzqtXYKBpRZQOHorqahmC-t6Nhpt0yDRWFfz91PgnofifVhzJiGoJTeOsZ6TFzGsimZVqhgjCFdrVM6sw0yJiS3gJQTcDrpcVf_jGiAqme4RWBXfE8niBe8Hq6J92CjrcZKDuAcJEhfZDRIuJNVI-iD4z7kIzHLn8V3GRa4QNkkXOg1U2MRivZvabdA4wpK2JCsbZy9oKZhhumDFbsediIMb336e1pE_HpbiS4Q6_OwUcgDThhgnOuxzxDtMq0jqpNjevBSHHhZqpwm1TAukc1ej9XrKo2VknUZaSrgGgRc5-WrsIBcZKh29xyWMTI5JO1y1bINNxH-vLYM_lUyYxhP9tgTbikqKj_5fVrVqHlx3p9Z37_fNjC6Ud0XKWvH1G7dEzt9HzMYLDllrm_7h8tBagJXFfvujzcnLu3a_mFz9fG-axXN1V1iLgxOILBLLfg-6NrfS1Fu9m9Yj8VYSvied4ea95FBfkda1pcbYVhxGAWfD7q61pm4Iz_uoItMb-ug0EQWREy4uaqsq41os5ggp7hX9cIxMyr64oL0OyKiD2lQGbyDqbuwtG8qADZc61QxbhrRH-IB1PNNIcI_7Ga1VIlfDpIT4-Z5t7EdXM73N1k5MJFBEeld7Y1nCbJqOX08phut2AI1tx5n7xeXyNjscg3FKLmZO77rqQ6Vyt7RketukpLzTQVwgFBSHU4BjrQdd-9K8IiVmCZuZiwvXT_-HFdS1Ut7OuX14mCWhjcbWXW61oidV_Xda3X1_V1f7n7fbsvN9Prvm6_SgsKg67lU7Vgz_tt11Upa13dHddi6Jb1LFYntGV5VBHSb52palXl7suXqISvqmYteYCaruePiHWHc2d3tJcq9FFQX60iU8LEiC3XT8eokplAxLL7uqvIyXap4j3n8xHZfjI8ums_1VnEE1VlV4tZVVYXBGRuGFzFZgr8bxJTjxHFigAPlnAzHkeYsyHYgGD2kf7x4-u3v_31v_-v_5HP849_-bu5_PnzMejT_b____7nTL_3_v5zt0xl8xDDL8j7eTIrq7s7q7Pr4Auluzt3dbe5ddeKqypjxTr1jDIzmdJlz85p3pxtvS56779e11nBWajJ1JgCXQKEOzkwKqJN0hHOyUAx1Q6vEZ4_DKiRrlKXrhFo8WvAqtQM70vuRD6Yezzvd3fD-PM0czC8UVm-0AfIo_Qw1k628GfE-Joh5VAEcLpc2R6QEUZcB8p6kHQfNJW0qYZFZYq2ZLuoTGNUw-eZdf3I2jgAFTGDmGbPmEC0pRGYbOkGbI5CVsHRpls95bEqN6Pb7ka7iCEqd0Tk-yFlnH3uI7QSDXc3m5EVbhF-kgCMprLZGzPl5lwqSg3MpLJ79vdDNFzcq6f9iuqOcG7OzUNU9h__p18vgYKxKLXM7RE609PrWrtKzeAKo_BuRJTPRtpspmV63K1neO4c1iVHqtp4oZ42Xvszn-dRHW1Rl5qpboNkpYr0JHoU2p3Ss3xl91SaK1eyB_Ato6oGm57je52DOISHTJOaAqiHqTQVIvMJZZlbp6zrdS6HPeKoemytczqfA5Ri6g8y7jYzHq5m5gazqXFO4mAM2JD89np97Z0nz6dmAeXLDBjpiMWDpULv-9oks9cYrxZ-wEbnv-XcE0C2tS_vUx2UqvYj0nIZcQuckKTXk8bag3tXwYERXoxFlOpeFjy6xT2ULxX-QP9ZBmaM_-B2mKZQ-Bm8iUnvFrCFijAfaYXRuiNKORg6U_VwFtnPJL337Oq6iIra-83tTPjdlYARpuxxaMIMM6m6tR5aWhAzZWTNuLsa8v3Mpxs81eZe2W5On4Z8ptGEH_SIMFpKABHELxfz1_0LYGbeVXF57d1VRNXF131d97Winnq-v7kx-fnzrcpeSrx__jQLihpIx54Z6QYv1c-WFmL0dax14lpKHrCNqPV-myu_ETx8tuiTRSN49a4qwO26qkpFL4unNjnjFJJ0ptYo0SbSDtZL7p7U0WPQgnYmcwq533I0cmrr7_8-p-XD5cz5wEjPhZsamv9ohArXdzWic96zhzVGXNox1OkYyZ0iI1rSUJscgfBCzCmprR9T2-zAmQ2morNTIWDZAaJi0lMltFtRUyccg5Z0tmCgPiqMM1byKZAwlxF3R43Dqpq8uZ5t8KmBiZKLUtU1qiqK_H5o3FZgaqDt7t25AhAlP4apyWJk4VMq7xqEd2vzgSUiZh_-ANlE6O7wGOj7vX2tGfF1752gza0bIq7-rhJR15DdHwOxK8QUcPz8fnqke2pyOkW11Z9KSoirR1xN9bri_fONcDO3OcZUOyaU_vr6-vnz-_qK7tGW2vvr6zVTOiA9XKbcwy32m1tL4h5g8GViIx5LeqrgbiO1YikgXQBMEHHV1PV1ZRXCuwQDdzW3nFFH7ebvd0uLnPXlshA-liNU5XXfE1CzbkG3C3rGEd0V5s-zI1Y1Q2hGy565OZ1K7AMRTSAjKoTmmjOXuMLNYLffqa2waemSZmbGWAeyKbEj4R1R3c9DcBLfRgwNk1Qt0Jlx9-ZG07RVG6IQN9Pz7tRTxYTMmWCNQswJm1WYw90jcooud3eHIV7uoDRuBG7usJlsUdEV8CDrVsTEDjKPowExtbj3-1up_eA1e9pXjI5HtAhTHSrm6x4Vqble97pCTddaftn9-nL3dV3usJhYq2U4FOR5syqvuKcHcBE-362KG9Ln65cfvXOZPzvVJQxdoiMmNjuhNtWEVJrpWtdUq1CxlNd1uZmYqtuIXOvLBSJzrxe_72oYIQJPVZQ2K1Hx5VTsVFU-293CDKRDwWwF00VdqSadydObdLd0rEU2BW0ymUS2QSGVe2RETuKC904147qcheD1enX2FcFLjnkIxN1UtLJ6Bob98zHilkb_t__X__b19cvr9fr3_-Xfnu-fe-f7e5fO989HVf7H__Gf__nnHoyIJpfb0Gc_z9488lZPddewr67V7QaDjcg6blGxMI6_icB0O1PJ_RQ1vzKy1sVDqqvGitExDpurVeGw7mGz5uiu1BQTsXqmZnhqgUh3u6EZpKkU1efZAKpGoeGXzrjDzEe0qgzmBrWoLmm-wI7QF35lPYKPc14grQZ2E62yuQfjRFahCGNeLqthx8HKTb1QX62aWZnZtenA6GoFFwIf9IXIVIqgVQzGQRqY7x-dGQ2bSjetbFWBa3WPirIxbs6GGPNlpnA3rVLo_t7HqbecQBCKe414RE5fEUTqKYK1-LAre57vb5jjCM7bw2cYiwDcM4thcdILziqVgekeuDFezgeUiqpFV5q_dMbiqtwspMKgQHioG926mR1r6WhX3z_uZF7r2fSxjGgsBmrOT6D2JpUj93aHts5IVw30eR7pgiiVKVUj3cJReZepm32p9kxNd_XmM3O6c1pwanxdBzOohyl0QEoUR8q02WK5paqcY6mRoxhlWCtspn15y6gDQMSlPeZ43vtDVzzYTU78mCQh45UDSrqubBngYjC4SDfH-Ra1-3AsuGMHzCN30QnMrwybmrQlsnM-OrFW1W5Ovkk1BQRKYujU6ReOSPjV7DF3KyGVxcUCzlkOqmqdBYqxpO2fOV43dn4UDNlj-At88szO1yULmebLTLVFBaRak_Iq3cPgx-ipDtO9VcWwmvTA0D1ccPFKw2MR3BFR02auw8dknh4Ca9ktPYJwqt6Y_4YZT6Hc5nWNu9NVT4Ne94S5QkYm1moV6TKgq9f1YnwJZoNRdVWinGl_slhfv_32Ox3Zqnh-vte1-Ga35X_57TetVjvkItIypLqe_f7jZ77fqjqtsbyzLJaofn8_bnD3mioy6Llh8kkSeEWle7LVZmayulmYRJsZ_6pBOgt-Aeque79FpXb3bIFkFgRSIj1TCRvlom1EyPxprapDEyHRrBucLhA2ryKZhl_-gTC6e_mxErXJ_rTMCXjxYjynLzYCVRP6HYTSChZzeoReQ9WqVviuxD9Nh2d-M-aLlmQz01EVH4EMV8dM0JzSiBmmKSgs-oCku7KZ3XSP6mSPhUYb5dqRIQeOLASi1s14Eouv0JlWPpGUZXIBKtMcZpqZK6yz3GPvd0TkSHWXQM0zd2V1y55S8FunoxKI7FbXHkFY7bZYwxu3jqrV3myctgpi5futZmLau3U4F0RlZUs4bIpw_a8VVS1m7v7nnz9HJpb33gJk90CfKhn9cf1ymlLV6-VdrZe5-eKOWAyQCAhAfQ7U994K7xl3TG4ds9C1VHvCgqO6dblYS81kh2G6aqRV9_fj4Qi911WZqPq6AwZ3Xgn6Xtf3H--__Pi18hEZqMTy5M-4Jy53NxGC6sQMr_teFsyriIj5xcHi-_22cEhzcC7Q6wqYGMzc1GB6hvRwHTlx8MyK5VllcA97ng1h-5zuDyGdUMVTGiYUqxiUqw7AapdBw6FK3OI8Wfwa6EyYy0xXnUTjCTVa1cHXMspKs9L0mb6I9ox2i5l20o_Bv_8E4H3FrorrNZUQMahbwJw1r19-_XFIcE0Sm4grwq5wGXKxplXq2REmwmC6AMIFrpn7oqq2YRFrsS_xet2-rup93dd9XzBEONRc9cfrCzMWcV2-LEzsvuPyCGCZzUx3r1gItrtHOHNwx8xIqdlMvq5XZq0rnnd6uBt6GoJrLQ9raVvu7qMQHZwIEBiBYPBZevzA5KicVIFU1Sim2xSLm2KzEXULX8vdq5KtLz2k7YE7fRlwzExmNQ_6ah6uJu93Aso1xcyIaVWttXLXtGgf281Iadc5YkrrQFugRjASbZSkTCukW1TQ3ZljDojYWgxExR0e17_-419_--vvrf1__c8_nufZe2fpU_Kf__kzq6tmP3uEgGJ8f3_v72JorVp-Po-pfX8_UOVI-jLf1TKzriB9V2Z8uUO6Sw_iWR1gP-kVdzhsZK1lKgYnvmOaLWUoFIHRcbPK-rpff7y_3URh9VTcURxwQGUks6jndrX33iIDc2Y5ZiYrD4KjZ2TCEWbTnGI1jAwJNbf-FAd5f-BjTRTasndRtAlFJp954m6VxdqXdPUuZlBZjunPCnFUpsrM5tmTOSqdJTOHu3JUYTrVumLvhMd0rXVBdXrcI7N-vb6-3982A3IPprvKADl51Q94UTE9UFKmDQ4Dqqa7PVZnHWSFcDqjHg6T6op1C1TgREfX-QMwDSC-Yr8fC4fHda2uVrb4Z2yd0rCvpTa8FQv068cvquIR5i5QmFfuqke7c5dfK5-97rurdu4I8m4kYlV1eMBpJxp6TMy9uxlPPoYrA4B8v6FiGs_z3K9rejy8u6Zlvx8G7Pf3tnAG-UYKQyYsB4K191taYFHnsGJqizW56ZwhUrz1yKx1KlVRPWI-OidaUiWqCj_3sX9SCs047hiOlikIGrjCzHLvFW6n-ThsaEBxjI-w7uL82uHMjk9Pzfh155Ox1n5Kh4-y2NMKBz9taFfbFafkbeYeVSWw_vgxOMi41mt4xG8uyubgymQMymt2Z8O9pVXGDGznJlegwFSzAD2qZibSxry0HXXMvVZmErTsZ5B6CI1G6gwLLbvBJnE3IUeTTA1iSpe_RgmegkzBo57N6SqbnDPDlssnhSKw6Co99VymjPjbbfzWjKjH4u6cMCsGNGRE-qz9UhTu3RPhgIFl8c_HpTJhkfU2D2DVNAeWCJduNzsTbYvKBLEnbgBm6nq9fvntd4GYw3TWup_3t4d3zy-__iI5sVbnHhXm18Tk_TO5rdpPrde1n7q_7vfzthUjwyxcl_75xx_hPtK9q3c1GXedilBIVkUEc3pd5aL5fJuvFkKfZK3VkvRjVBEdysIG1TcT7l0pdIkIAWbcD6rMnOZ9lUBOlZtgSYFqjPRUWvz-b9yH6oHZnwpdq041CRJwGxqlmH8EZ-HkNMswWaFnncSbQNWY2xhFOpgc1TFz9pwYFBI1NnoZ-u4smVMrgJmoMt8_Mjrq7tQ6flyepAX7SNtn2curZ28uGYZLfy4oGVRVODmsMJjdorIzEdZVNAFIFeGhPW1h7Co93y0hJWXhu9OAtW6oGB9FrU37WpN7oFVc8pvo7CdnRg7MQB0LkKxq6AqvP9-sawDyx88_4WtmPOx5noG-M39-f-ulJZWVCzY1mYWPMqmmMxvdqvL9x3_CISIeCJFs6ghlpK7r6ulYa7pXLDc3CtEgBuRpU-PrdRdr44qqXm6j8vUj_vwjQeSh6dnAzNzXYjRmbGBwKEyWGUTR8KMLjcMBqvFYrW3rWnZTp2oOc9tZvhYgEK3OcGeKMGzB-eUMujim5yjtQxSoEVV1NYF0H13DGFeZxgs3yVz7ndToEENRu_wKhI7KGHJ_A67TDodZVrGLktMwy2dnZlWNYbgBF6FIoSvVXbrd15BB9sEMAK4jpjL7nO-7lKqwOXqHNOD4HBUD-5jRe923RXRuU4gh7ptp1NfXLSP3ukw1iIwHBFYtgErJ9bqyC6oBheio-HV1jQclFmCiQGEWtq6lZmut-8fLDQ5eitwDy0xGaaBbHtcVa63LLKD3y5e7qQ1dgO7spI6IB0TlyQy_KnOypySf7Ws9-dgVYQi3ad7_OY-fnWksfbvC4_v74aWOOBR3inXlY3kcWyEiHi4mgIWZZtscGgPMPILScTG9X7eI_Pr7X-rJgx_Z4-EEUlAgkzthdAmJiErJ958_LWzyrOABWEC6JWum5Um23RSisBFrqFuYEk0DgRo8n4rrYtYJBsF0kSp6MAVuRhzyb3_9_S-__uWXX-_K_b__f__PP7-_RX1X_ucfP7O6ZBzI6hnp6uf7fWZ7Ix6xq2Vk78cjDJApQv9F9ccKca2ecDC_piPnJR4WWGxrtPbzftPH4a7cXouoqQuGk2Nyb4UEYZPqWu7P99M54mqmTgCXHbTD95Nbs5XTaP_eW5U5BRG1ys139szhrJs7Z_wH6CGjoruSqiAR4cZpDjBKBfL-482Yr_TQ0TEEzdOgOVSxndCtr2umu3JEujLCe28CSzrLl8nMaJuZDDOEsFgw8-XP9-OkdsBGpatHJHtzTT5Vl981TbC_wsR86KyAPs-mhpMFFPYRKVqpvc_0VeWgnAScrwHRVWrO70hPn7But12-7pVVvtwsZmYMmcnFoV8hZuu6DCqQzPZwhdFoy_cpz2E9Ip3hnu9nRkZlvb5kjuXWAZwyLpnBYm7drTLff36zgp_5yOjIXPfFWPN-NmljxDl7RE3DbT9bVbsaqvz0yNVMevoyqbyFYddWHXXr2lI5NU9uoahy-pz5mwPs5vb1UAKJH4oY5jvPkX00vNiQ50LDnFEQMzoAMTMewQxhRAipQR6qTsMwRQHwULcWMdp7oOaucOZI-TiKFdKlY92NCFMjt40-b87bZ-SKUJldbRGiGit0xs1lplpGh5xQRiKv--bwNavPL_8IBOe-aFY1qhjViGDBgW3GIXx8VCg-Atg76C7F8S-DmN0udu4JJiJI6sNJhvDAJsq0CmDVZaQAGY6WGzjwXBFeaCnVM_fM0rNAYwl_GM215ZzeEjhynh5qZ5avITLaAzO6ITmvNncyp2dULURUTSizY83P3Gc6IlR0tLvFzada4WoYFcIkRgXHSWEDMxUA6_X6un9kFpkxqsr3y1p-rzWq05PPowYFnmc_uXft9bozn3gtc6eIhpWDnuY8faRV2qCVTRthT68ImYG5h0_L-3vn3hzeiYyvi2DrP_f_TUnnsANQGyomWlUwz_fbPixUUsmTsRxejKR6pxp6xt0UZwAjNfTuTtVMSgtUDD_-znsqV97cJZHBoyJQmeIUbWbUbfFfEoflVHKEJwQ8ySE1MFA2YzCpBthBEgKHs0ZstcwZj3axOYrjt9YuznXwmTII8EGNmvFxydp-7zcXfJAxQOeYAaBqbpWlsMbMiMenfv7PB8dMdbq7zND5IzLoPvMIUZvFdq6FmaoJesTCunq6ATVOnlrPW78UEe63eRgwIrkzruuwunRULKXqeQRe1aFihuq9n0e0YS4it0dTnBYXgdjP-yFqRkVHRwWV-dtffvQuf4WOarcH1hVqcMFAfvvtlz0NxukE0I7lWdmiWfV-nr2zdMTY5gGgtqI7Rf15RnrsggL7Pc-TZsqJKYuOZtyiDWCqcq81MlKSU1D1cIEsM94KDlZyhXsIhNx7cwFkBWgHkRl0r8u6T0shPGCT7wdu0hLhLRP8GU1zPcp471fc3_unQbOrtUVncszhHqaae_NvPMBXGQvXxf24WSyRYXiDFTuYWDjcdyatgham7Jg3DQAtomfieeLp3NxpHY0lecWq0xCIKcuaMDZriNA-jb4zsHSnqBIKvxb8yr0tvLLj6-V3mKgL7vv-ul-v13VF0Lfi4bqMZSxVQ5hUh4o2Mywf_q269iDg4YxmXq_L2Dtei2uuybpe1_VabBVd93XdbmZuuu5lMxF-L4RbcG6s1iSyMSVKDysw2jPdWQ69Vmj4fp513_QcZRVOi3E8goFAV7SMK77f7_sKzhoA_3Bcxt2n0t0HMtlQE2Cy7_ulqnG5mnmYubn7uq-9N39LHWbsVwAjyrvB8qsmK7veKdMm8DC490zwrXxZ13SX-kHOTc_sns7eP-mgYeZRVcWsNoF6qgzjhqnh-vHFyS8tNc-TvvzQ3Cgbh3osv3zv5y-__TXfz59_vv_n__yjVWsqq56nsktGd3VOV83397fCnr1FtKYzS0SqU81y7_u6ujpWvN8bau62n8JYc8tqKiEnj8FSuNTej1uwZBb8YavyUVlT2W3AjfVUhvsVYYa9O65VWVNSmKqREqdmezebFQ7ZVVVj6sWFZvewgHwoDcOlGEtQmaluPVk77_jqkZI8sraT8bDK4qOnpfP7z-vH13Tq0Uc23wX1PJ0tMlOlB6_ObB5hfnPaA9NiWtXq6nFBRNXqaVN1vWu2Qte6pxUWMJ1uqFW3wlk4zNycdJRMdYuM2-pDuD6RMP1c84oDTEN1x1rVNd2ihgNmUxoESWfsKXLrmb-eHo-lDK6FiSK_k7VRFTG_3t__x-vrd-V6Fzqtt4f5qqrrx4voobjWdLvBw7P7XKRhmzA6qRG4O1_f9RQlvj__3OHWWaqa31ugtR_eCurZBwQPhVlPV0_vMoi4G3nphud761HGyHR1t1abM7TJg8U4VHoyW6HaIg2pkiyIiQmPdDPyT9e1QimWGqCy4fYh8UMFU-W2CC48v1_u54cuOKkAg4pSUcoFhcJG1T3GZBR8mJt7Z9laahDDQeCfcQ2Zny5Qd48wN8unIsIc5jFVJPibR7dEXNVpztY0qtvXMoWIas993Z0pBjhE2J8E3IxNX5UW0eAhXghCI4CV566I2Dtf18VPtKvOJ67DS6PMKIWJAETdXWTUtGsuXz1N-vGpUvDI1XIwRKoy7A0PJcbDgqIecarqh7OuOlMwyAFMDDv31QyGHPV18yuQxTu_fuTIKiLdBve1BBPunEB1n22tKrpl-cVkiscqvoizq0gvFA6fRfWOH0X9-UzEzYIW_0Azsp8xo-8mxOCcN9X-7a__YMSbZ5ip9BU__v9M_dmSJEmSbAki0sIiqmbuEbnV7e7Zl___qgGYhoa-c6syM9xUhWmZBxKLmcfM2NzNVUWYiRDP-Xw6DaZVpQIx3dFXVmSQjGt3t7iJwo9z5GtKnaWWHhrXnkAjuiggW0x31PF4TnQ-YptTBRFBZWcTMqSpaRqoWcaevxkVZJl5IEVZd1bWuhKzj5vbe9eMm4tQ1awkKLoqC93swtyoQXUVlK7f_-P2pkyOQm4IekWIGNFUCqQrRBR3uvhO2aCLKCFRJQIU1HSyYXKjH0nVLnbduPcu2PGojrp1aC3mXZtsdKhqd05Cl5U9IoGJN3RndVLAMpdGo6AiyiHa30T2GulPd1WKTRee1bfoILKGKmW2YoZMkbOrn78BYMa-7a_S2U0YUGMnvS8PA1xp1LhWzau60OZu6js2VZpFX3Mj-y6k6-mP6ovzva6OfRG9X--hiyqpJu-vLz8eO3ZlRl3HOkpAM9ak2BeAdaz9fkEEohEwgZnfS6LJFAr88AZ9mTQkIQpZojaMC7prsdmsxrR8l1KGytVlxsgs4DDNrOXH-71NdWoQplpdqhDaCO8MNNG1XJRiTvLztL33XAZVTMwy96EPY5vM8FGNMg-CZWqgUGy5ubjb648_mjjW0YS61PBYyZGQLF1V5aaiWvI9zyh0JIHRqU8cOefgWDVQbVt-vcLPI_MyauesUm-X4SR5eQtEU8WoqOzYMcTF2Js9QA_s9xZqs4YlIkpmCyeR3CoCQbFVtRUmynuEUzd16Lu1rMtFLeM6Hw9fto6TwqgC6jwP80OqH4c_Tj_P00V__vzoTAhRzW5xt3Ucyz9_fvz6ry9T7Y24vVoqEFt32LyEso4mzuMs1vF4its6l5AGHOex1qodH58fbqqkm6LweLhpHz7tbyVwuI1oFjf4OaVx03Olu5A7VJWCJEg9TldQCREYJbvErUdVAqK4zETootVk1_Rm6psfYKIRMbhxpaBFbELtNIEOTRLiRrcl96tT97WPdYz_9VsOLyp0t6yowjyg5vss911nnHEpwmZ9A8tbfcW-CuXLGyJqMd4cJ-ZRyTJzKM0XhVVlZnMQzIyh70eUuZKohCyfoVSBvtbvv__4-PHb58f5v_2v_7sdK6r-85-_cjJe2Z_ruVH_9c9_1_0S53KfKWxnZrUfHq-3Hytz__j5W8U-Hu7KrlbXlr7T4ZTrGsMOVKSlq2utVZmELLfH8vcONyUl9yakokW5Eee5HJZdO2KtNdEzKJ7HMcUqijZqPrc07CgVm7PA1dmZJOoWCM8BOjt7RJUz_msUClE1gySQVQWwczR8t_k3I-dsN7CsHdk9AR42ChN4ywYE3XacXb3WWZnLjbfzsZBo0NzUtGZRVaVExs6OxsjaytcxZNTB1E1rIq5rHYdQRnaJuxohg98d_6q6zvBeIEPTr5wNpTagE3i45aWcXER2j4tNBvb_LZYaD4EuQ7NwKypGqzWFPfOHTk6iIOZixnFoFnakQFR1YMaj_hCqmYvw-nr7eb7-_eWnzyk2riTYiIr3qJS153cNO_T1x9es9mtf6gbS1NzXvkLwJ7OzqsXWMSs4W1aZOogGMiI6MmrfDDRCssixNNr79TaVjERPMgc5O9PBUw4HqUffN2eJHv6bmg7ancD98zItUE1noz_UGjUb3rfZSqGK-u2LURGduhRaKRpRukzmUSIuwld8mbuvNQGekfXOp1RUKabmJMVGki1dNeJJNRexzGudj6o2V19rR3ajKuY-kZ0j1a0oMwMo6iKGhvjt1RoR_IRz3LWmuTuli4i5mex9qSonODTFNeB2bnR_9wSKSoF196Q8AAGgygksjhLRzG9Hjzqat2VCJDPuGzS6OV7q-5cnvJfjd-y6Bg42EZw7FDRWma6CyHR9bokKJoOtMsCM4V2q9jy2fBhFUPNCmxtlljBsEtW-fIJuVVT3qg6WuRPTaC5RM1st8HXMZVKMVAV1EmIEfv7l78sUkC4c5-qs8_GM6_rx2ycKlRNr1dzVgq-vlyuuP14ZmwCif3z8yL0Bki0qeWVlorOB6_WmMnYIuZ4fg8T4Ltq2KhEJYN_MYukKZKIBmXRDs6FLatgZEQILdnebKFsLeYdSK50L3USxBw2Fu31R6AhkElDRrqQYqLMJV_v5d1R3DatkKBWjQYeIdMZEfUZxBdybjBHzDoBpcOzzNp3nwOxt5g97FA491C2hUMfqJjpe6WZVV5AtOZ_tbzNC7pm33eN-HztYDzeTJFtBbRbGMqa33mL-_XSv6rXWJJPUbX5Lw5eY4stE_8dj15kNVoYtm9_17HbBgiB20wbJiioR0RZ0oVXVFqWHEtpo1dXdsYsmo5UUHdOt7J0tQPWMf01lZ1AH0RWszMyCtbC15_Qwzr_cMVy8ZUdm7evSh3ezqrrSVEZ0_PHxEIGyKbJ8uYqDy3SZV_dxPDO3NuMr3deuMCFp8ZVumlG1G_dNjSJmpphCJ9OpFcGqOSOjYL4KObw8QX376kfNClRT6b7AOo6jK1QElcudJCcbiTt3r41lCoqvlTubfTyeapqV0qjotVynZtclomZ31Y0zdxcI4GpmHlFxXXk1yayMfU3YA0DJ9H5w_fpyc-lmDbceTdA8u47j6Chxgp0RFInYNpOwnr6pVmdFmGtPtb27K20Ovw0RdiOr1f3asdSri4qpyZmd6PrmpmBYimqDmDA166iMVtdqnI_HsaQTPz6fbv7zt5-__eXz58dhBX94dj8ex0BUn-exZKivCtdWRoSbzce1q_w0mFXjPB8deX48s_rz52dHncfx-fF4PtY63Zab8fF8qGI9Hqj8sc6uNri7PZ4-24buarQYxrBqZlEVsSHK2d0JqmG0qcwdaiRrcAENCl1FRdakUFlCecU1Meup_tdsiquGuDVe9emlCLnWSjQBpS7Xw92PIzLXOkbTpi77vSGY6IcIpKeyf_eF3RydtwUEUFUMUCYy3mPw08HjoIvLqkfwZFeE-Lxf5T2ORlECamswHuf5MDPoVLNSXYfMiGo9DNT50ILICDdfh__n__ivv_3jb69d__XPf1Lt9XrHFdeVy1d2_-e__vNxuKs9zsNNlvveuXdCZEYtahpXrGOxarZSkFu1LqbdoLGrI9NFxnFR2etcGaWu7g7AzdQ1skb5IhQa1XQS8GNrfl9vo8yfflfvCtzmlFZTH5rZTFyFCs1AA75ESygOEJkRxYa6ReVgTLKGE1KVIwVEg91dKBVkVFVTuPceKrSrx_tSMwr2tUdqGtnmqgMrbNK9ewZjk7tLpUUFu2UwPldwLKhZHTVITQI0s2UZacfz_fXlx0J0Z4kbcMcSItvPlZnSTaGZ3sHVBpWqiw2zoyr-BBzRFoW8Z6Fy-0a6SI1IXQbC1qouUTsez5mzEjbsmtl7C5n70uVUNCgKETG3w41iWWGqO3bzzrktX90Ve_x9EXvP4z2rzbyyxW5ttvoBQSH3H7_y61VRPW8W865SdZIdka_3PN_Wccb7uqsRhLtl5vAdj9OVWryJ-XPSycj3661qV0ZmsxtR3VV3o-py06oUk8yahf9dBL_5Z23K7kl4yjTyb0Z6C9Cqpk0RFdMC-97RzZddBGOpvLOX2ZNbk8kDjJjczLtaVExn0kExG0-Irwehaz0oEz2gH2dWqYr5YsvyR1c2eBwPAut8zkGTXfI9VT-OR-zIHX4eolLzpoiRvEyggsON6TE1jTDe_QawE2LWYASyWgZieEvFde5ptxDpRlBB3LJv08sQIGyaADevkX-CdknJbrWj7wDrtN6JkRIM4hPCWSD8SbXfMfeNcf8KZMq7czyKyDlPKjWzMbdfNUjnlPeHb3nfFX26DeJKsUZ9PJ91T4h65vqdLWYUGYurqFSUkoLRLE4kdESW6Gz1pQRI9xUR5mu_Lz-OmY6rOcdtrKTI8-PHGnqEe3V29t5XVy93UQWb1a46YbPrfQGI9zUjvPP58KVqfkXUFRHb3ABcry2EmFaOTyOr4nw-9851HGNEGR_olNkqsyJ691x41TTfGxgONQaaQrKrMtPUKhLgrmsu5o1JtGR1io7iFBlpag2wQw3oprI4LZfZSKfaz3_c5Gb5vuB980kmeXMDnmaLpDqU6wEvZuaNGgAHR30HFm_E0UBBXyI64MKRL8yTlA1UCmXnHqzvsL5EHBxVDQffNoKk2nGv4IpmXnnTgCF540RU0DM0FFBilw_hpzm0QQhA6ZrxZU21X-5WeavA9A40o7u6Cz3co9ulWaBKfWN37cYUrb3f95Xn9HpHx9XN-WaBPHQ1hts9nkUg02SsqM8balDNiA6ouwCRAXpcW9WqELGFWll-WGbOVdnN9tdugtCfn7-pIrLV7VzeN65UKkM4se9bq5ZXvv59-aHX9X74-b6idp8PhVYDVyZH20sIYNJDnzlPi_elEAh92f0Ebvj0jDLJnu9mVh1uSkbGWkvUqlEdD1-ITGYm1lJTMc7RCMMhzb1PX-wWo5qPAFJQQrKKpPEmClOoYIOZIZQhFpsZhoEbMWEzEaqa-THZNVcfu0K-3oKuHZXZLaJ0s2xEpdlE6zSqq9NEq3Zmxw416052VaSYfFtl2AlR6vwJjqRjRs1jAhZxG2pyixma1Vk5A3KdQaovK7Ab7stU3--3HU41N1XChb_99pt1ff54_Pbj-P23DyMfxyO6djVVj-dJ0WW2lo8CNtFVpaMIMaWLuvWMO45znfZ8rMdjPT4ebnYcvtaxXIeCambzwba11OxxLALHcYhyHXYLF4VqusyuzMik6jxeaTKPLWlC8Dgf84JWtQKgLJRMOrBBwsVmUT6umuw6_Ryj2Z1Pva7Mil97mBhSgAoFx1qT6hLKeGHHTWW2Mnd1xk6auZuYXq8tpn6u8QSJyMycM6I7AZr4WgsyRpG8XtcyQ_ZgK1XsnkZEULDj6oZSZu5o7oiaPIObRZe5zX7jO_qcqhLZbBznOc0-Gac36Cq-lC3_l__r_-3v_9Pfr-o_vt7va1fG3XVGi8pS__Hj8_2Kzx9nV197F7oFVa2ULojwONyoZrLUrx0t_Pp6iWp1mB95FYXGOx_ty8zMRNxUqa_3Ps71jtyZFJ0CzGh0lrveStTeO093VO8dNAK8nYwynW2bA9-huneOVkxVTURnVlR1vbYZfVnO45LSu7MzMmaKPzWM6Gow3rublZHZEVkRt15jLpHacybIKKCpPiudCST44XdWD6PJSSGva4-0cQ5IUTHxDwo5AkQVEkg04H6i289VEX96r5qiqndBGVM6BUWm7uh6Fqa3SrV1XW_eaAKBKVXzunqC9abSrXKble80s3nsAMr8bFRGrPMhKrbO2XyKUiDH8xxTmJ_HTPnMfe9d91gW63h0tbgKBKITwRrHCO6pXewbhVTq1nuTiAr1df37X6wUZGZM_c-Wi-Aa_Mjr6kJnonlXKSrVtbLFtDMoImbuR092PItgZ1Ym72wIqlOEqBmBa4Nf7y-hVFdk39lp_UZ7ds9cuSMFPQiFBjJKRUfCddfy-zZMldzCsptzo2bmd6-Fc64yNecQsdUHieHuQBFaaNWF78SRmKIhYiNekG9XOaZQKK5uakYWVEWsOkVtZ4goupAjKdMqRKWOVU2HqTsldcpYLdQ4aAqdyRanskzK63WNRAIzIebdeOys4zgzYuzIQtk7qHOPZY8I9ratJt1GJC_KzNLbZyziWlVAQTVqi_G-vDdGmjYfcxEWqmua-sS0jYd3WRi9xtQ4QchcN25ko05aFUrI7eIjRXWRg6trNessW0vdRy_RhZraEL7LfBBQQXFTCGk6jSphR3ZDaGJ-3IRJTnz_QXRW6_L5hEPm5cT6k0wqSul1HD9-_zlL4q5xVDQpbjyPw1yzcr93DVxPcP3aeyyQkSQfH-cYITP2caz7gw6iypZRBngIAQHurPM8Z-SHxvV1zam7o1hVO8wphr23iN6MI9fYG7MUwBBQMVb4RGIOICLZRdMBftjYIQSigmxWIm8VblaVzkicQCup_tt_m0Rmd0PA7w0Oa17VbN54hAZQqHGF9CTVKUbWeDRw92u7CWYVukVExRHB-Tt6ClFzC2gAVVtVMP_9Co4yidZZQtDnvw1k6YD8GyLoCKqA3Z1sKNDFbhU5RKp3jbd-RI_ToUTV6O5v2r-MxR2mN7CNQF7X5KYbRZm1i3RTxcbLnVE6J-QeBCSrax49y47cu3epaY6Hr4IUaaIy-r38_O6xdWZQNQXZM6S8dJ26jqzM955xmrpn7OPx6GrFbSFoSne72nW9Va260fl-fyUxKLdpB1alq-_rGgnQznDzeQxCmiYotsOsaXTV6xVrree5lqO6D5Ov6z0_ehd9fb1Jbam1DCXdffjqiufhjRJpd61oG_4JbKZ0AjFJV1niSiqposvNzSty2oWN_Hiu7jwPv8fnt_V6GuvzhpOuOvSI2jPM27Efa837fUaGAsmqIY6PCURNI-t6vwnGFah6__FFVeV0o1tETKjmGCYJmTuW6xAqcsdjrR2Rry1EZ-eV7FZVzKuoSihUmc0-hlngCtHIUjUzjeoht1K0ALMFptgi5FzHRnPA0sXz8WTXdb2P44zotQ53PZb85W9__evvPz4-ns9la_fnz4-__vajUfY4qLRjHefx8fHc1xaZCCIS5efKdxBq7nYe3Vi-jschwOn-8Xh8fH4sM1M9z7XUnufDVZQ4T3dVVxXKMjn9gEJJXYq7Nw8TY_c0Cc30hjHL9PW1G6qqapEZ-jK4unYXlfsKowpZ2ZMJ2VXVdayTwrW8u2ZdJjb_iLirH4eozq2DMhhGNbUd28nDDF1mtiszty43Mz8PNT3tyCwXtSX7tcc9SUoRHVkVEBMR_zjN7Lq2uHY1USKSneg2P8xHL5rYA8S8k48iOp--83zu3Os4Y1-2VkYON0bQnemqcaW6-XFUFar265pTpLuau4n8P_6f__d__Md_--d__vGf_-OffhzX12tWuEq16QKq7IjH85jgzh9_XMfhDdoydtvk5pYP53Eu4RXxfD4AZEEpmPepCETU9FjeVcdpbtZZay0VKTRFYNJ166HMlJQuqhhYalK7qBS3X680N043t9DSj8-DgtevN9E3HVeaIp25KFnc-TrOowbURsm5EisaLaJxbeUMCxJExaiB20S7EjUWDoEwqzqyCu-vLTIk7jEfTTKzKyEi2TVnzptFnykqqtpVqmp6v1wnvKxkoXuQ6apirmpizvmaq9A1suY3dpxHZohIV_kNaRF07R1qutYpyq_XH-t8Ksv8gW409_t9HMa7Djgnv8G43tGObvh5nOfHhG_X4wm0H4cIzR1LCTHzu8lG6Uw1V1M0ozP2dR7n8mPwr3Npub6-sspNgFbXbukaQELbDA3RmZWRlVlRtd8VOwNQFYfwPt_tHZQJWN5U-cEBomDnkZFmFplCXY8nqnz59X6Za2aoUl333uRw_LsjQSj1MI-6ZonqOrEiUQV2LrXsELap39sVodxQV7hNzMaqxor1DYoR1p3qUzTMXciqPo8zdwpha92yRbmvGP44b8PW3bNVYk7GnoCoCGW61APDpYjoqu7jWOSt9-ouP1Zl0qwqfR3dtSN1rZ5AeUOX3wK_bsxoH2DVY61qgMi9u3oSZW7r_brWsapyHQfR7jaRBOqNc23Vu3WJcUCFHceOAMXUWiQjfa1ZS0XEeZxVDbl3nmN-yMTIK0lWjQOBaNp6ZuzBR7p7RKCgqt-WMaWwM1mcTBs5jNwStYq6xcIiEVvd5wSnak1yciVdE6aVGaZ0iSpVamdGK3E8zsocAfyaENdyqpgqGq1UVWQNphNqwy57Pj4TiW4_jq6aer2bZwS6R1QqYt051VJ1nwDAx88f3YhIcxOTyKzcKvK3v_9tLGwqisbren39eg996P16deb8xNZ5qKmqxhUtN6PWXCPzxsNkVU5gXQ8_qsrcSYm89vUys4oQjgG7I3Luz5kblLiC3SYS7xiMj1IKvbNoIrCMi0a2ZVVXYI6XJlXAvW0Bu3EzEuerpJzbVEP1x9_v4jyaIzKtsXxBiL4BtMMvIAZdO4u3-s4B447T3uFmAl06pXVSvsm9Lbcljl3oHhzbwBpG_KtDrRGdm_rQ0zCMfJGMpDvkxtdM9JFq3c1sMVEFpCBCdaFmRd9czBYKOud3wGqOxOru6EmTorbfF0DYQGeN9Gl_CoVERrCLFCmIQtSbPatwArHzjnWbZlegMcy6LJq0JELPdWZdsUsANd97Q9miNJgdINVX1WYXOm2ZibKa4lUxPvsRJZqZ2FAvRe6-mNb3Nk3dM94mOtkPU6_c3fjnH78CY_UyoL9-vd0e747T_drx-hXNfr9fAPYVX9dl6o9jXV_5x3_t5-dHVdg6VEq63BQMVZs_3WV2PxzJ5SYNUYrQD8Ukc1qEiMylvkjeNFKaiTgBqWyKXXsPcCMrr9ftop79l5BVaW47AtXRpeLf-ztl90AUrvfF1qyiMSPuHaLMXl7tWKg81rH3ntaamWXk9JsBiKL2jivI6sr3603trpLhJ6MomrsgcPWunj-UJr6x6NMfgC_vKBW9dT0iYzlBpYgKtKe3YPwz_DMrxfU4ke0fD2H7cRyuf__7P37-eH4c_vD193_87bmWqjyeazj1ETUT4tpxqL--rvms9x4IKYRWGUt95OnHevz88fE4Hj9-fv7-43OpPU4_1VBhZj8-HlWhVESevkwVDBWDEFVrubp2jH1Lo7aJJ6qbLRBtgUaF0QBhlZkYlpkR8HvlDSAHkW7ut0cZXZ00u11vojVXene0mOvy1WgV8zE43H196UwTJYFiSwulu1XNdHLPfV27hpIDimnsVIr7-vr3G1UQRvXxOERk8IIZb7LHMCUqIhpX7r3njhkR3zlaUKRqmGiT-8BgKOd1Ul21N9DDadFlAKuru_frTRNCiYZQXJ-fv_31__A_m_F__H_-SfC__vmfLFzxzl0irOu939vMbamK5bV3Jcl1uAB7py873IZdS-k5YWMEL1N2FY29W-d-1Y9jnecalWHX6HdBIrL2-6pC7lT3jBgguijPY42tlnXLJJR6HM4KP5wgjc_nqU22FFg99TzqWrc1k50NtMp9zkYDN8GQHJyutMa-UNldkz8RKrozA5zsNyOzG4cdnQWWmmXeIQT5DjsLtYHeewBxFPTE07Mn1VpVnZWVVOkoDDY4p0osFB5rmVrWrCJ1YmN3uEREqDsuM--sipxR8OyjzIVKMQNxHg80hv0EFdQw72ajI3M_UrllnhNBUV8idlfBJiNPGkUp51poNkUIUwUxN0gA51pZ1d1qRtHYs9PQ-25DiUwKKfY4no0S0et6UbT2nt-x-kEWojqTnSJSFChd1ciKEtPuvV-XmX6ztdFVsvx4nFmZWZFJjL9b3Vdnqdh1vRs4jmPvgLBq6nuoLqcoUbkR7OqK7gF8D7wJLDDvP_37sD55FxTZbQDUIAN-wex6CagJVW59VeHu_1JvcQCJLFursigqywEVtcgQVTOZi4YvH4uzjHEWtOOAiPui0sypSsDPNR0g89Xs4zhH7l7VczrpKVaCcX-b7P3atkxNp2lau9wsKtythtHsE16giCx3yv016eETAJyPCnldKWp7b11e3RyxY-ZobrLua0B1iTi63FZXLfMBw4MTcCpdOl-QGUoMfnlykoWSe89X035Gd1fqsTKCnHHvPT_t4fnY-g7czoZPKOaqeXcw6r45VOpYprtlAK1uuUNsAPUCoHYeHx9X1DzNRE3UUDSzbox73sQB2NxLhrx3S7-Fc9CfYszw6E0j8jyPzIoIVVX36lQ1An4clU0VM0UTCm24-_Pp99Ip91SPZpW03zvHztQUt_N8TBW9WXas6hpV6JxrJ8Y3MAmh2tKKgmhEdKavIyMwUsLuib5VpBmrsiLA0tuk9mfzXgrduDNs0_9suQ2bd2qubnSy2ZLBUM4vfaam0RSvSAXUPv-G769YR34rqOe9qHeyGcBN0wSnB5w1-fyqGmoU7_4Bxss4k_75tsywHA2ZWmWXCoRSGXfmXzlv5W5mp6j2pMhp3xJA7VFwDAed5Biq1QYoKd0EMrNmTigDO59FBogCce-Lh1MLdrNGMrrfE5KZBoSAEOa1VbVyYzQZIrNnvIWIVTdVoFtVqDKCAgJ9pboSlZnT6EeXCiuCZAt8rdgvVcv50bUAWGbvf_8h84ePRvRMp673y851zT-LRtRauH79QveOyOjz8TmvkEab6H69bPnIv4HuqPM4q6GKimIx3lcBYrpM__Xf_1NUAR4Pf_3x-u238_XvC6J62Hp47RLh5--rGSher7cfPinBhlTCzG5MBLcQkFux3tnCVqPIQI7ZWi5WVc0uQIxaUNVvIQmywpeL6OTp17nIQRFLd1f3Otbr2riZAoouYe-9C0Ma7r1jil1dHVcA-K6Fz3NYopLfJwExs2UkIZad1T2qQnRTdF_vqbXEe8uAUyYdeXee53vQrnYbVUiyDxuBFIixn2CedzPkGPLAfK1EVXXyynPuFaAfjxNZfnj15Pby73_9_T_-9vtff_t5iP79Hz8fy8_TKhLN9_v1em8IbA4mRFSY6PvaZuv1fh-qI20REyXE-PjxONb67fcff_n959_-9nMZj3O5ych3z8eR1z7OR2YcxyGow81dTncKDzcVFdJFQLzzGg8UiGSioJDqEApNSLiK3sUhisq7QgSHntkldwDjfqmY3ApANPZOkktF3Tohqt2ZkcvdVU3obtJUk__6ep1ux-ljnq_qqXLsCJUx71jjljSBNF0z4RvLo5gMF-b5-cFqc0el3qoTgFA1oXKZu8SOuVpMYVxE0W0qzRLVMUe4r2m_dVbHRsNMIMzd4kYIkPG-KHNP0H1dpt7Ej__Tf_zXf__j19dXsf_X_9f_W8B__evf-6p1OpBz2yn0eZ6fv318_fHmvapsNtXdBEvtWHZzDJGg5DDpJy_DPh7Hr1_74zy66jAzke52NzXPHeoesQdfLEoI9_sS1d7tPmcvTKW-mZHI24_ey7yjIIrGw5fDEqkq7FrHoWrXe5PYcd3w7y5VnnLuCqA77i9md8VOsucZG5HdMKIrGhUjtVMhaSYZKaiqGp4dv8shwtGeoomqNhNRq8yOGmXs1DBaQMDda6cMPDRzpEbUmz631AeV2E3wVjXNOFOGB1WC7ymyzEZCQJOqNrXudDXl_SEBC81JBrovX7IjuwhlNxKw5fMyO4_HlK9ev97rXANIPc_DzYcYZjqWI6pbzaonBuZ4L_Rn3qmm7_f72nvHnuTPzhY146DwfO9ARndRBM0Wi_cvBZHp63x_vefBONu4Qebvr9ekqlCsiluFQlG13JVR61zuKiKRNWTM87Hc7Lpi1pLMUtX5Ks1NK7sTuE8CJhlbXGbfMhUgERG16iKKuOHjkyNPoimZJWpgZ_asUHpANlCAZt43KMCyC13iOuhMqIh7g5MpHx5tjrDcvZqq4maDjfN1sGG-blFS1Rr3Ypa5H8fRKF-P7DKz7jbV3FXox-MZGRM9qCgzFSX75qve9HqVnVPxVXS5KtjZnRGuOkVnyPePe7T1amy4KgS21kjQEdAJSOr8qEpuqysEk1wZBzd6RK2N6SFAhM1vWzCQbWtFFr8NA7dFOFJNh8afmTJsJZaSTZkhC6mdNRN6ilS3qc2XYnaPE3ma1aBS2CNJFIpCeEfgmuaqvkTuJfBUPpoQNz1WZp7nI3Z85xnRUxxSp4rbGtaQnYuKBvb1HnGVqnXXOo7MEmMlxC2jzD0rqDNWJkGo2MPf_35_PB6-DKLx9X6sY84O17Vzb6NW1_W-SFaXuU-enuDeYcvv4wSRV9zdDDVbHrt8LXGlYF_RkTvirmwJI_YcPOYe4PpZdSEaArHBNBVAszVfnHtFRxlV34gmKhoqiaaggUG10rQx6q_und_9FqJb11_-m4wsY7hp1cJvee08XWS2Nvdfxffl9u7aTryU1dlqCgqKoOZ88zm0g-EF_f8eHUNtRqXo7YemqtqjkHYcKKicQyvqbvWzxviQScqNeCMnyDUDfoq04HafCHPXtFkaLbeZRYaoen9uRGqYwEI_5uaqaoIsCrG3mWVuVXNft-t4XGMy_HZmdWUd66jIbovMY6l0slhZ2K2ni0hHo5IiulbGTvT1etvy_XVN53XeLdfrmk-MrY-oCwO3U_Fl--tyP-O6juNkE31Pj_YOXys7dm0a17lU5TzPw72AP35dz9PENDOTU_jv8zyuK4_zEGHsWOdxPs6dWbv33iC7mVdVhoi89lahe0E1dpzHuXc8jxuLu8yQSZWoeNjjsIfdmjeqqREjg5pA22EnAdjMtoQJE7qoKiJzmZq7DipkSESjZVCloBJCGeBsRBF9j9tvZFO6eew96twRCn6jKdlVyFad_DciM5FqRw5IBwDw3lFVI84AEFUqqMy8LlF2prpWzfeZ3aXmPUnLQjZ25BCjbxnm96G-yW6oL0AyB8WolTV4iGGfmRlEx2CvtlRFdCXFTB-P9Y9__OW__eUvjP37b58_P5-PxykqXViH_fr12pEwU9XlbuJfv97va89be--kUoWtUiWVUHNb-vnzx__8f_zrz4_zcRzHsaJi0JVrWWWt40AWIWD5Wo2aWGHmda7Vw5To6sJY6abZojQ03Oiio4rEKDjs1nUVmqD0DZc2EdrtpTZdEwaYWcPod05d5GgbYW7Ll6sdSopc-72O1eRzLTebFFbkVlV3j-ifnx86FsNp8Js37sTReOjcV1eJsZViikSjhHZdr6i8XmF-ENg7QeawjjImCoLKWe8qtSrXsUZnparma0aaApgohBkpAl1O1Hx41IzKzATa1Pa1lx_v__rX-_V6vd7v15evdV1bVNfjkMkLZQoNgsfvnxklSl-eV_hyNauMv_7-8S3LQVRlIKKGnNh3Ct8r8uOHuZqZkkg2pnDWlYkdu5ORoLCLkWmqQj2ea5lO4S93TteQRpnVb7Qonx_n3rkOc5W8AkBWm1tXminQh2gWUD0nH6q8sQtl4kAhk_d3tobPnZmEoAYngyUfWbvuVhY42QYwr2QX61a_dw97O6uQqEl4jh1sJriUcVdSqDti9sDx3lNVI6lkVRHy_PihoraWus2hTSmIeRJrxP5eHW_zFRFCsbXuMS0w2W1bR7N3bhpVvLupNq-52LNJM1u6rxiLXDf98IHQvL-uj58fQKka1d3dXP08Xq88n-6mEzsc-bEIGrDjnBbsjjA_VKQqate-2pb5x2HqFSXKHVmd0bsiKm9_MZmxrxGlNZomgHTuvK6cWxYhvmpfyDLz2Bf5LRaUQWKEHaai2fC11uEmUpgh6EzPMKzWyhqyyERZIqLnuYw_Q_pSGfMUuSeiVYSgk5CMVvc92mS5n-5GUVc1q6xx1mE6oWNvMB1ylK0jqtWE92RksuW-9z6fz5sROaIEd1OJXWp2PE43o8gM1FR1HQcJGT0whezj_GC3iU7irAd8iW6UUrpK5F4bDgXL3LooOg0RaW2qQWBmozsA1MzGyTxx9DnGDHTrrkTL2Fc5cgPhZL4VmHKjxhW-jqoUalW66vQ8VW0mU0DR_S4zDFFbbm-XLo8JQci98BE1EUhzAEfj7XJdVdXk5PjJRo1bd3LpMospzFuhwLkxN82XAOY2hNedIW63dFBFxlVrSkLV5mTI212rN-HdrUG6jutH7-ucf99iStVb1Ey70t2HaCpq2YgI9ZkmS3WKSGZQ9PnxOS-U5V6VxzKD-9KMAuTrj19itnNn9et9ia_XvmYRDfDx_KyurrLHUjFWz7zs-rpmBRWROSEX4-Px7Mzddb0vNVIFVcPX2VeMLlYoPYbojsmxU1dnzll2Vwi1crIxNyp_mAqNPvwA-7pKTLpK7giPoFER7NsiUVG6nKDaj3_c53j9_gOO0OWJOYCDN-FnmBmYDB8mU6v33JzZNOYOqjU7R0x9w55wXy2-0ULjDxax6iDRNw1OsgMtbBHaIIaKLUsx4yFVEHDtAa7PDEPmG6MkI6pByuwEdHoIfyaXMoqinS0CUiIGxq33WjiChcqJTlDNQOuh6YruKwZf3aSYVmYXq1pdR_qVDF1aO0wUoolQhYjFdfnS7t4RxIr9Rre51r7WWtOnUNPELLBanXu_u_JbsEBp-jqmPkMRFadJNyvr4-fHpFHHlJBRIB_-eL-vfV2Pwyt3RrbJjkL23qlqw8l7_7E723zJIa9f78HgK6Hs5daVfloHGd3N2a0DoEp2xLXRLVIZoaaHe2EmTWUqosque-JdMNFzLSOjU1QFNFeAhy3UTd8U8nCPKHa5ac-4oqViYMGYlcsQSDEt-URmd2XuHPlsZcyDb1rUcUV3iVKUcdusJy4MIcy1ouTP7ZIoUZXjbWe-N4HKaW8URkDY8y2liEZCBctXsVVtXgeF6h2EzmxTzDFsKCArcc8phlt79znGWmDHAswfS0xsreo2yrnsf_5f_vH333_-9ePz99-fYyaBAib__Z-_fv37az19gqSPdZx-_PH--vXHez3W-_UCMHj3JuEQk8PsPM__-I-__ziPw4-fH4_hq4hhAiSiamaZZaa2dGTAxXZX14VqULNvj4wJCSzzarjo4Qe6qwNUVQcrMhWWdf8m_6xZDtIqsqtq2ZmdS4-e0QBwuLG6ukw02WisiXFgTpDM2xnbvlyE6trsinQziuoawTuuvTm84qqBEKppVaqv6_0GlNUsKm3GT3tM1d3mhgpIL1-mzB2daWa1LxKVRZGBwKpb7G22juUTAhST3DGzhkqqrXtXVs3hh0EKLZSqcjVfR0bqsni9URk74h37irWsM87HkZ1X7GUzIbWPH8_am4AvzSomzvN4HEdEiNj1fvuy6kLkzJ8oHM3ccRyzheoMGY0AQfT7vRt4v1-qBpS5pEzvwgRi1KUj0Uaiq3ssck4xtTl7moncRNgWk3a-I4AmrdhmJo0uVra7xrDjqllET8xSCSpVVHdeKp4VJHMXKdeu5FYREaksQmPvmcUMfv6Wc90UeBCILBnr-30Nv4G7Lcguc2ukqLC7c4bIM-0a-ynlOKf3WVPDVK2EiMKkqtdxDP56iCjVLWqdudRmp9fogRpApDLMfHb5vhZqLtJ1Ph5KbdHM8LVImNiQr-MKMXMzVRtoqR-HyPi8-ziXkCNIgUhVxxXqOnEIoO4mpXllVJYve3w-laJqsUOV13t3cdf-45-_Ho_fKt41FM6ZIlU2GFUmhHRFEi0Ckc731XsDiGsPQKmyzp8fGQEUISLaBT_MfFWmmehYeE3vSHlnZO4IoI7j3PuqZu0tCnQnmtTC7ORrRt2DRgUgbFWtWenfEQerHreH2Q1xA0n63AGUIj2uQDRMlKLmI9sSyngKCI56xd0AiptMW87M19GkrjX9FnOz84CMfVYoIu6-XFR5H82gbtfOAiqzMjOTYqI2qyMU9JSKVNqYjLsopKl21xjKzXR-QzNcnL7sIPJwkwulAVGvLj-c3X3_2zk9h6ZUQd0GMCWmWTm_63WecW0xqwm03Yn__rZe3jrKSfyLW46Qa74CkWySbOmuplpkUnQGpiLW0mpHTwiWU5HwnMKyGmZW637LPc2adLdkt-j8n3Yc8v2Nnmx6C9HwdUzj3I_lyyeMfT4_1BTVNvxW9ljKoMLZBdk8M-Tj8XHty74ZjwMJHugnRYSsbqp2p5mZ-Hp8VOZxrufj4_XH-8fvn8_Pk9pff1zLOSURgoGkyHW91XTvPSdi8zVD7gFlRtR5-DwVJwlvS2nChrlTxNxrxz2nSPDbb50ZY8ut2ih0FbI6ICLIqqi7SlGtVDYzm6ogr2tTpIVVELOoGsP0qPGm0Z4ZY8udbqWaqBmy1H_8YybztBmC1uQqwWSLqNwiDdMatJybEBTr6PsfnCoWMCUYGcCTjHpi7n2TuhlmhMw3OyPUj8bwwwdV06N60rlcU6dgoKAIuxImyGqwqpb7nxOC8dnRdAQWsyEVtTFP3cC1-1c0i9Qe-TbRYh5ZEz3rbqhOUj5jkyUiQKpP3XN-PDV1WxHkjhaIaUZ1lZpWISIpdBNCE2ALu5vdHO5QSjepkSFmc3wsILMiK65ftTcrx8dxmC3R7I6r6Oyua79b5Hg4SFd9vwOgq5NSmUtclIk9MsdPX1l2fb2hnGfNvmKZNYsmJuTe-_UeZ-2Px8frjy9fUqjjXNeVy2fDDj_8uvbc5MmWruXO7uf5iAhXpcgV292GMi1gZ7m7makaqsy1UAZlNwVuXCajezalKSNDzXrCk_McoQxCRET7XmtyZ6hiQqjzanGz2eBH5cyxiBbQ735PEwJ2do7WFNXouemNpebOIczKlcDXry9dh5B-emYd5zGvOVXprumezENmWAUzrhLVHsOLTkQPvLk11hWqZsvmn0pBRq11iipYdiwVETNZ5oedz5ONx-NYy_7-3_76t99__nyeZuruaxkJNv7rX1-v11Xk8kNg57GiKqpb6Yde74hMupja5-dvf_zrOpfp4ufH-dffPz_Ph6GXyr72-VhI5i6gzG3HCGzqYR8hCdDUBGOdhgll3i7Q4TqrqskCsYxUojnJPadNdx6c24Xs2ADRujv0e1MyVa7pBw_hREVRLQYzSaaQJnQpRAulUNRRWtl96VWq2KhkVFWAGe2ocbKw-9oqIirX63p8PLJTTOT7Tjlp7HpfRo3Xe466yQJVaQXm9R5zM0lEixqBilD1Ao7zqWYKDtWiI-mGYdKZ3zaZqszMuHi7BdHVpkZh5fRoeax1a1lkLMJgtwnMrHebyo_P405dV--IqjyO4_w8D_PeacrX-zrOoyLHodfdax1AV6S5KmBqr_e13GNfAnTxfcXzeL6uN8jOmv_8w44rQ9Bu5ry_GstXdZtYVcl0sghhGxjR1Xkebsvee8KStd_X12sPSDiqjtNbcO09jcnc4WR3jBSGSFIW_OrAd-xmvmhzShPROdeCUFOhRJcsa95JDwC5w8wHCNPdBuw9qge24pYENVG91hHvS1X36xJhRzW0G27mh6suNGJfej52pi1VM1Eit6hlZdZQnnRsfqo61blbCdCtZqI2CxkTYQ84XkkxP9TURABGZBPx3qPe4ZSmTAntrsyedq9yzNwqpsttuaGhxqqEwFznqF2F4ZAuP-KKRlX2-x2fn8-mZCXIa18zB433l6KvP_6JjsrivIn2JW5zF8n3pRR_rLx2d6EmSlyiosImqltU_VixU9WH72em6zwr83g-VaS61T12FJC1hyA-FYIJk-SOAWjMTA2QSfZ2tojWHAbM0NWJHeFriS6OerMK80ObvL-K29FARIq7ilEN0w80rZzgy0R_Z4aHOfFWTlxaMEeFpqrdB251gn64LacKRGytjlKTYckPK0dUbPmxfECZphRAVdRsX5eIXnk9z48huAtu9P6QhTppPq33-313rNXVWeXHURmV0dUC2GE3Uwfly0saDVtux8poFZlBPdC2LPfWgSh1FzAEzNF1zW1YVMy9RxALmMtc5jtLdbxdCpEumOrQeKf0oWJzshpFwrCPlx07ojoo0mj3Y_xmwjEUlaqSOvkcuef3Y8rD1aVmcx25M5O8fz6E0vSeP6jJhIpMVI0QVYkoUwpoNp7Orqts-VorIkwtImYVvfflauOpqEwxn3pyV5utmjeU-oSTVVSJ6Pjt95_P54NEF6TqxipB3vG-ds1DcL8v3CRbruepqmstVclMP21gIWjWfRDS21ejlpFquo7z_ceXzeLOBmnHzOpMUa2KmUkO-LiySIqLqHeX3GplqEl2Ea2uqOleoqpKMOD4rkJcNAFrGGlRb7mJt1aZ6FL9_Dvu4vJN3rxly6wZP0CkKkn9U6SIscmJQVmYOfYM46f5gclTjhFOVMaagYH4kpl1p_W-1wrs78gSiUpOJtRubsW8VquKvJ11ypbBIhXEFDKSl5yLh1Ix-nHR6TMQ1CnoiACCysEpTbKnMsUUnUMrLwDMzhB0RjQ6924UBcikSOUkPkpMsqqr1Q0NUau9aRpXUO8N13C3ZXjPQmZhCgsFF53tD29TRo5PyrqEkgI0dmRVVnXV9nOJMN-XtFxfV3SaaHeZsCLF3JZG7shSWEbsrn2luDwPr4SgRbBE__XvlynPj_OKmGLc17_fr9drnXa9ryy0CZTSZON42JVbJ_azjGhQYocoGmVqlAbazbNykoj38Up5YyWXFmqsWm5G6YxSdxGMzz2y1Gxn-LGyEiq500SdFPQVVwlNBezIXGY9YM1Joex8nMdVAbUddYjmDALJLiDTbFXX1XG9r86SqcM0VCUjVR33bBLLV3aar8gQ0cqkyevabi5oVSMpA6roeahzBGEd0JFHZqtodc310nSI0rMsWj3cWlM1n6jneZ5dtU43UzQ-zmftdJX1cBP57beff_398-fnQwVrmRvjyiuu93ur647-7edPJQp1fcW-MskdYzXyvDabIkJrUQH095_P__jH78vs5-dDAZvWSgeIqs6oXaVC8yN7V6XdoU8QmDNHRs2BZ6qvDYrVaT6xQNDApIgYRKSAqBzUiIhV94AXunuepxPbMNOM9OVr2WiLsnGnVMl-b1NfvmCtS3f3Wu5m3V2VXdzXdZxrWNdANiSipFuqMmJ0Fte1H89zgrwq57420BTNbzfNEqXK-719rV3JnjtnXdde5k0UYMeZlb7M3NX9bnG4ZdUc6-XQ63rTlol1RnbtfY2J3XVllJvlzZnxytbl5g7Kcay4Nkg7FqUxGXPwfH68A35Yi-zI6TE-Hw8Ax_lwVVPXuRGdx9frJeT7emczch-HZ6aJESN06nWe7-tSsWwg0UR2QkRFd5Ud_n6FnzZ80mMZusUVN_2So68iee3s4usqPxxdpx8DfiCkWRUZOec3_Xq9ZnCrFFH9eu8h7fTVIJtNt-4S8tVX5hZ18r6e63AclTWSk1u7TB2C_myDu7saA_MS5kRVKZQZyZOKHTkFytjb3FBNlby2mna1uReqE7oOisGdYr4cLLYYuPwxvvHHx8frus7zMJGR0JOsSgGhmj1HQ8_Mb2dOT4W6qqjq6yBh64jYa3kxZYQMMsmYUlP309aCwHxN0U5Uzc3WGgOXUMRkR4hJ7DCdULmstaqqojiyh-jIfP78vF5vcy21X1_v43zs6x3XFa-NHdMQ0ZlGQSC8rrjrpzS47V_vwX5UQgARZqMbttaObWp2rG7UhOMbZl6TxBKhwt1rmtnMLtjdytPYea4V1zXbWF-LIrtyBHFKU5Wu0ol2TBxUaGbaWpl_nhBmYTgLqB0t7i062VyMB5MQV1GtShVxPwBMd4JK_cbgTLBnkMHMVhNfp7ktt7VcVdZxDGrfDxelUNWc7AGdke3qoxhHVzeQTXC63iZ67UvVGrhR7lk9xxJVccnRWqmgmwURrQqzVREm8j0R0NtV774nzK02_YGeCNRMWbtE5a5ostby7KbaeDaPtbIGVCq8qTvjzBOAx_rozpnTikmha2AV9Opkz41DpkMgaDf_E_IbGYSIqalxNJfq5j7JLvXZaMmEv81MVM1cacUa8YKp1eg4QXFr0NZCo4qkVIyXdgKkYubrWLH3RPfWcXZlZoNcjzO7pthAZRcmflLdmbUeZ-xQtcoQMwoquyfeThGz9x-_TJefC1EE_s__h__l_e_X42NVxNhJRu2yI94ZKpLDEcmaHDtaZjRQndJynGtBdtZ-X6p6nsfXry9yKCGYSvT1flEESAiv97uycm62UrF3T2IgqzOBHt37ACezev4UZ17ds63sArWySGvcWiSyM2Iej6iakm0lRH2UXGC7iR5_-Z_4545JblwmUMK7dkx8V4RBNNUUwNz5Moomf7IRAWZekDWiaABD5p2rvvnZbAh0rawecR0mImCz6idQooKsW-ohALUyukuVwuJo7e5QKZtAtmIw9zUpzK4e2jeAik3RBqqAYdkKOGkiIc3QaTJUNa0s9aMrJg0m7kTfvfjsvFJEcoe4iXLcbZz4HcBBhZiMkqO7Z3MxbKTqNHOhqglbb3pIhqigrarFqWBn7a-Xucp4ee6vuKkLTTtyZuLoctfKQvXeRWqjutrdd-7l5ipVVQ1VL9bViak6AJn147dnAu-dneUurnIsz2hTHB-rqVfUfge6ivVY9uv9NrEph4gbyWMtzqWNZIPala0t73e4WXaex3kbTlRILFdmG6WqAPExAk4SXHCLM1UwgNFuX36HydFVpChQBH1O4cJuRqWoZHeyVb2zXKW6VfSWkKvUZA7U62ohZMi2irkccw5AGSpmKomomn57Ttce1bZ8dAQ15ZBv7WRli9hkzoTMXaJGE6Ddve7oKky9u2wdw72eV_mEXkkhyv2ww9RNKYe70paouJwP__mXH3__6--rSbSJmGpV_fojWgiR8zh-_8uzs6r7db1_fV17769roykKo_zw51U5FR2lfDxOpfz4fLiKqu5Kc_nXr6uJQr3fl5rO0lBdl3t3_Vgf0XteTlP4mXwIQDG6a1WZcoZQY-A-3BuIa0O0uuY1O9B6E0Vhv-NeylStdTRb3Y0zBGV1qw7cEyoUF6E2WlzUtNECdmyhCqeRLwLI_CXRQFGkY2cFSBt6KWlqJozKrz_-rWss9z0rjkIHKtmyvKPmVDWV-nWekDZzkNfe6-MkWcLZKQ-3vkcyT3k8P7tKxO4nGCmuAlYmSZq0tK11C9uXk-OPQE_NgBrAcSyS7ubrVNPPn891Wryzsk7Vrl5Pf56nqSwVCnfuFlbm_JKWuag8z8fr6-W2Jk7fwl_X3hGDxIndbTBlBMw1Ig4_WbDDO9KXi2HMaKLqqu-9v8MAFVUku1tN1FjVlaEiX-84bf16_frX641WURXrvfOPf77YvHY2oBR0V8VAzVtZg6vjvfCbifnMG6NypnSzXp5b6N57jlMVs03mzMBno7Qj-O07GTLT0EVQEDFRoABh7hTlpI_Gj3r8ePpSWWtQFwoY2kylpVi2bE7WA5bpqjmRDBUoIwGq2UhlQVal-yKo5l05viFbLqo7QsyyQ6CxL6VmBEB1V5so3kDQ09RsuaoOrFpdlWJuMzKLzGO5qU6ldvCambHMJ2CgZhlvNX39-hJlvt_76wvVNCJSRDMuVFckCDO7dZ8jRUNXRO4NFsHZ_pEFs1aMRvoe2bo3RE38WKNhmsmxu2aUm7x_vSBUSFWuQ3fGrVL2Y8zIXQGd8fOwQKZJ0SB73mfVE1Axk5wWiGpGUozZ83-Akt3VJXYbf5sYjvsEv4Fetnpg5ibSAy-gmU-JfO4hPoMAoZmria2jAVH1tY7D5W5bgyLu8jgeUSWQqhTaBMxqFCRdaiszqsp8mQg61HUIAST1MFFRExMRZTdVxA6fTxG6fTmBuZz0nPmydLmYTTLHVFVHFTCfutl15DSMp5WUt6wVJNW80REp1JF1iuk0bucUN_GqKiw_KcqGihQbXb7W-MCy6W6mmlmN0u9Hblcp2F3mTtGZjIo5KK4eEWIOjDnaVKSAQh_rvHeAIiYu5mKqPn1LmC3qfLs50ELQ3L07G2zi8fmZmSDEVO__LqrR5HGe17VHMqrUylTXrBBQbYJOIipT2s5qEanISd9Rbbn-5e9_d-1D9fX1K94bVIq8r73OM2L_8cdLKQ1cX5sqHTm3_Y8fn5WFTBP7968v6t2pABg5pCVmhi6vrthZZGRmd1Qd63jv11TX5udZWdWJ4S-pUgUNPVbV-BiAxuAodvY0YopoEIWOt6DzejeaPd7cW2TFO4Wfc2A107jeIwJrfkcgpO9B-8RmCAoNXSiMuRf4prtUy0jB8N0ibwhNoTdXcWjZnP2X1si9yc4SSl5bpiVYnXFVlQCmVpkid0m5svsmxzSJ3EHqBFIrs_4UCwNVqarjppmwT_85pp1_FVtU5rEy5JYqVAKVE4vCrbwBB4Al2p0gI1LNqqHLMLWzqq4cAnF1o6hmVbsqVbSyu9vcMpqDLgIhjF0q7CqKVe9x2GSEql1jcnaiuyW6G-2lyGy3U91yZzfE7d7tgcf5OUs9c89KqKLyPFbudLP7u905o9z6Pqy_I0z9jz_-eH6cZsIsNH9-HDvzOEzM91UN-GE_no9ff7xcbXKvdmcKJaKWW-0a8peLJtPU31dKlZ9eHWZalTa_9TuHLZ3lZnQxU1NxMRrNTFowCp8s_c5ITIJXhSNKm7xOdUfe9tbqGi7yGCjYgm5213Co0N0oNMmmVrzVYWLdXeiJrlXXTSYmhKyoQulAXwUVZerVY8--G1enfUA6ImPn8_zICt58tNTlIJFZ2ZUxAh2dXtckDxsillXH-UCluneHmZM0Ww262lr28fk4Huvruo5zff788Y-__L6qJkwSBfHBtdn5fDz8qGuLyK-vr1-vt6j-61__ntpNVTY6yKrs6uNYZvrjY53nWs-F2KJS3VVpy3997dtv0DI8eP3WTLrZjjjM1LUyJ7EzvUYTI9jcygWVQE1fsLL6G0M55AD2N0yiwYYvnybjRCdAHOKqmlUf66BCRWvn-fBBL923he6INBURGB0F9zUPnfq2iWUXaL2vzvleK7J3pqu627V3REekiMCkItaxgNh7OtuOqsloRb5VDw6fTi0ilrst7yza9I1NRIy3yOxw9-Wocj-6QiAVqXaw_4yZSaKoqyvVrdEUGwccW6oLgiqoL5Awez6fts6Pz4_P56HNnz8_3eX5cV5Xdutf__qDCZLXvmRZZeV1mVvuHHJhZpqpzDpXpAlUHcvfrx05b2700EZGxy6yhOs4dR7j83Qda11OPyrN1JVrrfGqLPcdO7JF2Wg1_eevP77eNWPv69rvGG0kO7MKqF6u6IrKup0ZmrXN_N63JOo7X9cYvCrnYTsR8MyYdRtVClnCrh47IzkXuVKRro7Y82pEo6u_v6A9colvdwi-BYyt6m4ro7q74sKumeuzFUqlzX2B1Wom3d9U68lk6_wPAOtYNeofcjwYx-PMrMmDURRZIlh2VOSP9eOKlwpFdc4lFFWRqnR3ET3OCRPqWIvO42zAjwOVj3Wa6nvvx-M0VYK_fn25T_RyTrRHXHH9up6__f1f__1_6_eePIKKZieNUj0a7UnPzhOtd97a8Pflpr2DrFFzDRxC1JBFQAhZS20d57PRqjfDZAqlh3tnH8cBldgpbNYsG-X9utx1IIxLXUTiCnevysoEcmLoGJBj9fyBKmXvVLFCVYaaT8dMqFUtpmoqk-hTncf1hAKnFkx0S4_VYWoxkxWcm83z45Okr0VxfyxgrjnUpWu5iS53szXxvXWsKSGMTXyuT7aOjL10ff16iZKUKeYZRCCHn4WqwrJz8CfdAxwEgFmbu6qqV_VaS00j0g7vGbL6Ur_PqSOcUQoa61iECETdoibfLhBBU5dPYJuis69VMTFRUWn4OrKqQHUzs8w41qM6Sdo6anigOohtJW2UovdVXIQ6WxDP6031ugWXpeJAj7priFrHscjZukBHpCCoCVGLd4afLn9-aCi4IXkqKsdxFrqq3Ly7lGKqfqwG3f3whUyhuisBZI9rwpffQL7bZDwYU-mogQk37q7ppEKqq6rRrSrd0GVE_fjx8TweH59Psf4f__zX4T5jr3_9cX2exxWpZFYdz3XtXRnXa7d07RRfKjQzE67D2PL-uh7PCYwxcw9gsHM3kJFm3oO4iTjErn0JW8Ad4eaZ0d0dSUpl0zQTswkJlKgQ4rTX-z0lqtgxENB8_WHo2hegsV-iNzgT7GnIDFNxom6ZVZm6fv7H95EIHalmmOSreo-3q3MWgtQZNoAi_O5VIu5mXsfsi0e_PZnXwg2cblTRFUJ0yy1xmMb4YGlVZ5SuwO33HXeUVYRPB5BNYQHiOqXgRiG7KruTQlSLaaFFbIYV-0oVYd8pONzZD-2-sx_dJQCzRK2yhFTqvgKgyFFDBf0O96lKjgebAxftrsnAAFXz9RB1YsqP_R3V0qq621psVY95manwLthClyWVZs1SuERATIwUnRvGACUzk6q5S93f-xJTGkcuM-3bjHych6jS5euPL6HsXV2t4Onr6-sFcEc-P08299cF0Wj-er3O53rvaM7aER253_v5OA-311XPj8fe29RMJBOU-02v3y_pzBI0Ra6M5_lZEa5a3Yfa8gEEtLkN8XOtFRXK-5E00Ld5DLAhNtw9QNjd-wozFTPp9mU3NXUmU3MEpU6baKivKvrJnynX8B_n9tL5NtqFEnAtx5zGp6aiGrGzKvaW4WeTnT0g9bF-qkgLKFqoYgluWAFYrDngCarBHlAGTG52-MBYC1k1qRI_j8mCk1Sz207QdZwPVXz--Fxr2WHu6_k4tPA__e2353Mp7zNzXgWhrdUNAeLaZvJ17fd17Z3vyMgCOyvdj6j8-orjMAjWOn7-_sPdKgsJE17vqOrX3o0qsDZbmmyz-wTjomCNcuJeX4IVDeThLsNng4vorqyojqpKUduRMJ3vh2DwfDe8ApBmDX5hrlW5y00xsc_hoSbMvVliZipLVdA_9CgVdpo4q6SZFfvK6j4OJyvemyK9d10lpKrQAUUn11q9g6LZMbTv3Pl4PPfXS3TYHc1u06H4o5rL5DjP7hx55b0sHsJdwXUBtV-XCtc6WDX1pr13ZlYXG1lbVHI0IFm2VgM0Ifp4PNay5V4ZypGMci2BNJcenx_KWq7LjMBf__ZXElIkuNb67bcfdYWrFLgj2dh7i673dZ3nY9f1cM9qzPnbWF1R7W69b6uh2nx06bqI3tHZpa7dvc7RhbbCs6oamZmV61i5C6pXZmSLCtjL_fV-f_gRWfv9bkhmZaeMB1JwxYWsH49jV3w-H_sKd-7qjkanGNDjmBhwSgHFW6qFwe_PqL1qrrFl6k1GXqT2zgEZzQEvxiHXPRC9kTmQnANZ854jDkQSKJ2gudDczdfrCj_PtZZSVRxuQm9yHUtcROV5eA4EHUQ2nCRnz3OH-mj3t7ox3F8qVSmmU4USYUeYau3dXe_3rx2JbjZkolBi7h5ZAD4-n5Wp6rFznYeZTreVnOB4m2o1TRTsvWMdK4fMIXK9dxPxfkVcv_77_07T-5iRqe4VVejz_Iy9c0h6429Cm6D2JV3qJsKMBGDLB5wN4GaEgOP2Pj4-e1SkM6wVMZNKrmV6rK6iaHfraM5VIlMF719vNYvKqI1ZOXbGGDOpvcNc0TW0vTFa9pDFUXOkEJ1DTUK1WCqWSBMDZAJXE7WfsLG7mZ95E3JGyzlFajU3MWu2rrXW0lEMUZba-TggKmK-lvuSQfd8A77MV1ahy32BOqKhK7YoBdjXXFFQO0bvwC6KRKb7wSHaAzN-9rWqofO8Ik1hYhk3IkXIWW48Hg-SajrGVVUbMBZZwwUiG6Jz7s9dDUzTciI3uO1odzdeTIWKnv23Gu2mtJNQRpWMKHPi93eEAfLtzqNYVau7qE0XBpFMVDQJWYbJ_emwg2TEU2aeUWpu6iJUXQ2aH6T4cZCl5hM4N3eg1D2yfK2qVjNTL5T7oaYZeZxndY0_B9TcobZEpSrNbPqlppZxmTtVtGEmWUVVW3afxTFeRCP1-vWypVL423_8Rsr5WNdXNG0ZM-YcCzN9vV5xZWb_8a-vfe1WgK1uZFfV-Vxuer0v86M6h4VYjSgsNzU_fEWEqoNzuEdl9m4VS2xtuOprB3SyNkOyubsj5jZVn04oBXkfTYeHaeotnRlCiFkVEDWagsxstIiR6FvRADHrTMpAV3_7bzTtG_8_aaFu4a4cx8K48XLiBKIi3RHfg9NWt7r_0oTgrxnIiSrHp5uppmBX5OyC0NVRQlKk7ixkz8c3dqlr1c1Pzx3fkevht-vd6e4e5REUqBTXafk056OMzCzATBHDCMcdN7r5RVoVM56kkuCAh9GFnvgQmnv2yRg_clfX5MHYVaqWaDWfds5o0ipvO9Bwm4Ybk91dba5dIxntblT1smN2FRkBgLrGUj2NnKzuW57NpnSCqjvC1hrRs5jmFXHVsEbMFeRyd_OujsieBoKKiqCKwuz0pUMCjyvV5PGhpmx0ZZvo63V9fp6RWVXuWlGVgJT7jck5zpWdlWlqqJQZg4GDQ414Px5LALfh_GIt1fEkgGupgAZpJCGmcsW19zXbc1KocJUazuxgtIjD5EFPFoG4LlNT1Vl0Ai3z68rprpTrSK7rlZepqml-4z4orrrIZkIg6m6-qBJdTYhyrdXoijad0hHn6L98ufkQo8QFo5YCojazKdIKUVY2q011R6x1kNzZ_MY5dE1Ndfa2s9ZTEevu58eHLc8qdzWT81zH4xCVn58Pdvz195_LzB4e18at5eYI6XfE43H8-339-z__RbOoqurqMLGZ2e_3fn6sdZiQz48PNz0eR-cG-H6_Bjf0fscok1vA2bX2JHlhom5KgIVd48OCLlGhN3vMx2SD-woVRWWV7CxblpnXjtxVFaPOKCCvmjDdvRPEEH3ZgtI2sSWSkaYK4_e0VW8DNzoqBnM9c21R0sTd2VKdpNSV6FIRGEoEgNtyV6JtebMEOgYodTttddWwn6dhPOZyMzXVZcccO-6MWdR5zhRQljsqsmEUpWZ1C9W9WBFR2csHLl6mnpXAXDLD1Lr7OB5SOB9PZJ3n0VW2vBFmBtDtXNMMKP78y8fjeO7X63k-zdVdPz6ekSki6hYZpjoPHAyygWCDpuN-qmo2K9FTC-tWsRbuK0Vl1s2FPJZToSoqVmxSKnLOK-9r57c4C4CYNDquRJVggnM8fV07dnZULrNXvM0toquyc9zyVWhtKbKjC8gYVF8rZe6G79p947jQo6-vdAoaJl6C5ixUC5Du7KhCgyAk8lq2psukgnludpfovbMaTZVw2D81o-JEzRIGVSIyxEaVOxaShCjNlOiMXOoQLXS8U00huLJvDpIbccNPbHJmnORSm1kX_HiI0o4zru1muTNiQ7gjReU4jsfx_PXra4aXqtpdSl3LZyamrrPb-fh4Xu-tJgTeO_VGndzezaqkiph2wc1iX_v13q93q5hZg5DeV7prRwKsikLNtrA7cT9LvYlqIFGR416Yb-ts87OGVuxmll1m6zhPXWaqWf35-Ihr29Lh1avpn3ezKzI64ko2juU7NlVe75eqd2R1ztlx0tTCruoBVuZs9dg9wx1KR8yCiML-Rj4Yb8RwoWRo9OeRme4m1MoYzMBgfiadRVURzPVPRT4-ntIwNzNbphDa4TPbPs5FkQnV6IhfVNgD9yxfR1VlbTVFIXbIoKuB7HC1rFxr9XRaAFSjxto2pMF7vpLdctNaJuSvXTUBelUfj-VMTkdHCKKyjrXUtLuWWTfUxEW-L6JNGrpn7w1h5f0sqio_zsz0tYbtLqYz0lQ36DcrpyliVOkGs2VyS7NLIgRqblTLiHUcAqo7qJ3l5yGEqg13Uc1rly83NxLonB7w43xUJcUG2iPqEJznQ0Xv7DkGMSUUpUlm3TgjVUirrqyS5R15nCc6D_eqrixbXlEuJnp_j-pKkAUdtehyH9TmeGoabab7_V7r0NNdfK2zI86PFWPUrI7oJr6-vsbtcF2XPxzC2iOpaCWnjbOO1RUUdRcAcKFwchlfX78qa8c2826IyY63u1dHvPdaDmiyBydNdEZUszIAqK37GtaUHi97UK2n5p5BaMQWkdw5nfF7Qn8n-BtVmT3H3awWUwK5L_Xf_2P2mF1FDJHq_w-7Wt2F6crP5JVZQtwodKKn2c0WGxSjDHW7O3nH-AaWQJkScDcKqj5KZ3AMFgJiBp0gZQLEc6xWzRhSLKrb_VsIysHWNgEkRGdYDgAqJqrkABoBlojt2DeNdJzkvINMSna2fSfMolrt7ArU1Ay8d07usbpsOTp16AqiVSk6INGUWSo20aGzQ28Ua-D-yKYK2aRk160wdclOGXfC3jNoqQx__miKieY74hpzGdAY8aGpjkmZFDOTmh9qq6i7d5cs39f2-_JN6do5V2RT0lxgWrtnXUMV5U3nPEwL_Xw4ktKQxPEwm4aWiIhWdXb8eD7GNDQ9tMrsQqNUucyVXV2Pj7O6zrVaRQWqamoKuE4RSe-Du0xWTou9XMie8W1EHG6V6aqJGXIM3llui2eDgDYmOEzeVTOlvPPtrj0evLzZz32D6DlheppAMf11oQ6Umd067AMISV8WO01sWhwi7Gw0dO5y1JEJZOSUzNCAYi2PHcJ2n6Xzba6-O09yp5TX46yK5_Mzse1Y6sLqtdbn8-P9un78-DhNH3r8-DiXG3a93zGX0NuAQYnsKzsz12NB5bpi5oSuQuD162VKJGzRXJdxuUk1KnvXdO_GiZZRoAzPo4puMjl4U4CIKLEWM9qaFpDRxqERV3R3RFBnxNhU65LOgKKyRSWyzrWosiN8etyFrPp-xEPk_okMa3igPhGcHcus9yu7K0292CJWc00nJ4FaqJ05liQA752l3NMPybi_LOTExgidjGzEdtM5NIuQlLkp2ayxbQUTlMHF0O5mlFCrAsJ7dWBWFDtW1o7XHmoHsidpZrZkbBXEOpZQj-PwQwlZaw0_U87VKDsOET_Oc7l-PB_nc_38-VPApXqeqzvrOwxDkazKiM5ednxbk8XMKuvj-biuiB3RqW7dNb4nISNmH8bl4uYNqg4OfIK8o1WR631V997bVFX1NBWz_a7DtbPf71STKUhkxLGsO7sxaeKS1tbe1ZGj23SRnHXzUjHo0ohSqZliRpWbJbpbqDqJYJCxYw7x1dhVEEyuiaqZgaquBJjRmDJ4xRwbAehSdkdEV5tZo6vaD4-4TBU3G6AKqCoT6a7c281oQqq6-bGOH4eOkdC9O9W0WJlprkTDVN1FVJROqcpquI1JCKoiKp1QVaosn35_uTuB7LLHkRXg-LUT5DrXfl_n85mx13H6sUxdVAEc51mDhRlNVXdmcm7lVV1F6s0boXaViuXeeb3XOvaO6soM84XO2ttd9_ttQOy9ry1Ck4_Kq7tBJKom_aczRZuPyB2UmpSIyKrKYonq8_lbdrnZ4_nx9fUWRRdMpXJcbM7pwpoRvV979ro7t6qO6xKRnTFBaop0YYRGPYPnO1hf6JpNBStHClxdYmvsIuo-Jm8oVE3VGpTjNjerTIlZWaSaUZb7FFSP89OdvlzUfZ3rWKpW0br8OI_mrPytUW6L4KxqB4ZbUbe2_JYpSFxxA7yqTZWqe8exVlRll88beZneQjlWFFSJfDyeM0lcx4x48XyeVcWimvD2JDQqj2N1Y_Ci8yYD-tDHzGy6KS4jx13mKKDKzAZ5NuSxewLlXrn9OObKIWo0FdVjrW4ASlDFXD27RFTViDa1GkiXievKKtXB_Eqjj-MjKsRcTdHD8BNz_7Ptba4RacvnFCEqYiquU7BUIruaNDeqZrf7MW0etVXVd7xCOCApP5a7kuxsURntJoRrnX2Dd5SQGTc3cn6w1FHfzTTvTh1VVqFEFxWPj4_96_r4_FxmlW3LG5Npkq6q7rjiimjBe1_X6y1Qsmrn9AnX4zR3tmaVLc3IdaxGSxPVr_fX8_m8risbzZQSsF-va54YldXV72vf1KZhjk9MYvI4AM2uvcepDBRtZW6yK6JNolOH0yisDD1GSNDsW6sxF_kxtNx1qR54yY9_VJWYfmucMRI43MgdQLWqSQ6f9Q7BqA0-5Xt-34PgvFXvvIWpIia3RHN6whMiparV-HhVblHARM3uSGjebrLsaXhwyLIyCZVZV1lVi7Sq5c0JJpRjoAB4e3k7Ex15TcRkaM23qYMYd10TVVFVsyjs2lRvFEHJoM3OaDoJhW7UfPKoHPcxKmpUcygKWBHuqwQQG8BWUzPK1WLnzLyr0bcRulikyRzxqdaVMqlKVT3Wzd9cMhVeoQGkahfNTYyd1dW61nByrtjdqCy3I99Xo9fjjNhGF2FT9k5_mAtv-Xr3b59nRI5J9LfjRzfM5DhnNC9VbUKqZKWJHuronnqrQDNDQYGoyjq0I87jRJWJttzjfyHm7RhRwwdElihIyUo1QTUKXXAXncHVYA3Zy1d0CXmcZ1eZWN-fAKhJVvvS-VhPshcAm4efkF5uKtadNo06kdyJuUyyelqYUURF5DS259lKmZHDw5RFqCALlaVqmamUiC2TaDJTlbnW1ywi1prIFtmEottdwbZlBaipuoMw98xYxwnA3VzUVI_Tz-M8j_XQ9Y__5S8mktc-Tp-OvVLOw0W4r03VX7--9s4a27xKVz2fz8r6-HiQXK7dUgmgFfo4l1hXFAkxzeycnhgl444bSvUyOimN2JfpwduhiIwk0tzQiCwqG3V361lt871LaZjxeiWV7DJZVdUokgJTlRb4MgpucoAwKwUSFUXWLk7Qq2jLUO1QVYiouuR0FdjdnMm2maCm338Xe6a6akoSlW2mLS1ulVE7l_s0SlWp1MjNwghrCs1mdQmliURf74sN0qpq5PNUyby7_90dPZfvdGHtXLaU0p06HFQ0IQ0c6zAZ1usi4OtQm6P8yOdt2vKP56epLrMfP388n-d5rsP9_mqgj8OrqyOEd8q50EMcVlomREVUIlLItY6dOajvQp7r0VVmQuDnev7xvvoOslPAHkulyd637aQqI6tGrJ412rKsQbT18kOVH-cREdEdnQIF2pTo_uHnpXm99vOxxG5oT3X5kkXdUd9m0hw7782ZaAiZmayh7LTrYyNVBYWKmMNWRAx0BF1UUZEdMe5T1ekFMfYlN1e6yG-U3ljGVGYP01XrcezXxWqaREVm61poCEwafqzsGl5Hf2tQZS4zvJEYchfM-vx4ikkXETHhouFiqymu6zjOmqgn2OxuZMCXdecs5VX18fmZEYNAIfB4PESo5uhWdwJ6WGXFjjnDoOt8PrKqqoRAI6OaujMqqytBlEDUsroiVLWF739_KVlZVeWmeSUlgD8vFUCXyFTguruL34TuLjO738DKTphKk8_nU1QbUJeMkO7skuU3vUfXPIrjirU8MpqMGq6LXdcW4H6jmZLatRFB4_Dsx-c1hf3Re_IWCmmKTKSFKgASbKGZzZySflfgpoUPndy6jkMQ3cfjAbHEHs7qOhaFpy9zC5QfPthic6NSyHWcFSEUVJp67G1mUT1aXLUxmnUVuvI8DjZ3xVreTXXNXSLqqlXtyzEBm-UiBMRU1E1VY29VpVrsraZunl3LVw4QR8zUIX0eRpWMZLWq7dojCELlXIinwuaqA1OdFmd3LfOMFGqDfhws2jko7hFdqwrXsSL743kiCwJ3p6qYUoSQdRxgD4eDIr4OU0UXVCouO1YO4GgWWW68O9hY61ARdZ0ltS0TlYia4ouvNVbCx_Ojot6vrXrk3rJ8ilKi0sS0Rjvr1jKS7qsL6kZVolX19XqJ6PFcGXGeZ6Ey7mtkcVjVOB8PgFOqpFh2NCWrRor6ONzcnh_n9-G3Y9e-Mjuv965KXZZZYEcEOC3L0mNJF8Senx_duXd1yFoq1K5-_frSUYJTCqzK64_Xx-Mw98xay8YOqaM1UxlwTjcgWtFz_GUDIpGhYtMDrsb72oMCu67kWGcihZIZHTUOzq6urHEAT-BPpjsx3H2UHn_5nylsEcyqfupTYOUGR-ys0rh1vtkkBwwq5pN15vdck8R361GmVitmUwtsTGV73fm8AelSUIWaWP38gtg3rJMcBzq_pfb_X6b-Zse2I8nSBGUtEVHdx-69JD08IiOzUDWpSaMfpNGP0O8_60kDlRkkzc5W-emBbHMU4Ag4AnSS1-ycvVVF1vo-SEOfMhBQVS1iuktK9V-aLo6pQL73hkJ0ppnWmVfFc-gc-UvPvQU11WBVE_T05OZEg0ZTj-SYjKXSVCHfWlPzPDk422fRViMrs3i0O1GCrgShtrpi-5VVA1NtBRTIJmB4eJHmLoqWCa1Q0HVSRCDttlNyjriAsEsh9_vWZXq5OiqqTw191mjgsMlhy5XsLlRVFqiQVMiMXyloQw59rNEoUTFb5tKVZqtL2GKqgl5uJNy1Mp3MTEDUdF8Lmej-8fPj_jzX8uvDWTCd-7ZsN3WM-La7u4tule2qqnRqE52lNg7d3stkpnTS45OedRFFDN939-pR3oJybavumZoss8g0N7awRdFmqqYN2a-tQ1NQLnuheqlSoeZSNRbhtVZ363apIjFabzzdrdrucc6gJ920RCJy7ZVZvl3NpyMo6IlsPjYCxQiDlVSoql57mzshvpeSa_uvXy9XX6oCvF77P_-Pf2xdCvrlFX19XEpCkFHXy0_G-z6i_Hp_rWs5-fJ1318fHy_X58o6nqbXz_XjxzaD0tA9j12pruoB46o85eflDsN9IqXNfXga2dktmTm-HjXSECeqpBtdgjFwSc92JyLMDKKZtxKmli0UZqe6Kgkp0GdmpipZE_0WgmpLpE2GDlI0LTThJVVoU5fqbauznKCR_dRABWxUSW815Kic2tSps1XryKxsYY_FZsZjETUpi7hDphsmIhQFo6OzB7gx4GBVTmHJrzUPJDMnkJ_vipxDuSgnYj68mvmQoJ9RqPmiyo-fP9z8-nnlSSWkMf3aZQbpnz9_Oq2yPn68ZHjKVUreX18EpaaNwGrcJ6iPIZvKiry_7lPZLZ3V0grGCYDFclfgsV23iJnNDbZF1KwrSYxc-dxVeEgsLTWhuJbGYmdBij5eji6RyIqIwhx_WqHRXVn7WhkxDZ2K0oaR__Vf746gaWXhaeWBSgqiApJz9ZoPec_da-jU2dLlIKBV_UBopU1WIUGiNbNc-YgmezZLmnGPbaSl17Uj091mrCYpbKOr0mZO1VWvH7-6Y62r4vi1myLVr2svcxEaFd26fDZXZqZO33tWGOeca19zsScxwqkfr5_dtfa-71ukfV-VSR0KkFFpdEBohJlf24xoZMb18SFDNDMdDpp0-XLq4BoVfPTDwseQJ90REZL3uc8wcbvqJCh7r3rfLaWUPGfISkO8kJbr-hXnoEcm0nj0BM-eQQQTC-zOyYSosgWq1PVjuWXlObe5DYm_svxxJIiaDQFFUFjMfCB-WTkUaXGyAZUZpLFlGjUV-fitqqRaFQM8gmmTqvb0fJRCqBtGHOuLkGt9UHGy1FSMUJqvEQKpue6t7lC4u6_FIRct__nzV3ZDNbvcFGqdtdzc7EGOggA_P7-uvTrTOSADbPf7657eeWVltVC70mnfe_tZvYuZnQhbKtQ8sa5rhCqiGhHXtSFNVVfPKh3xmzmU64HkT1ec1UJwLydEzWQmQ_zW10FRFXNsI7lNRluMNnOoQe11veiaJ_210WI-m2lmlbmaW0s_ZWJ9yKFQ62pfbmqZR83OfabS9i-wqv0rvQPiOdmXNioO3Kgqql2pYN1n7TVlSaWCmrOyq97rEhWomdKuXZXnnSLlbl1hpuosEdsv98EEeffEhdSMUeVrqfHRHgtmQcZmZn5FrLUqQ1U_v25bpmsPMHqt1dX_9h__YW6V5eYiY8uozMxTdfKcep9zv9-T6pTsoY3HCck094psyH5dpsi7qkIUzwvOTahR1RHuRunsSYVAzSIPQCk0RM27283z3NOsa8j1-oiTMrzlGaDHcVI6bcKfXXnfwyPL-4wfuDM7-2lIgpxKcWPuLUKiS-3Xv7d0hXAevYOt-Xb9fDcHvlXd1Dmtixq653Pf30GjjJzk4MMAAVuga1WN_nEGwcPCfFpTc4WYqBcE1ahugplJas9kqEo4X-FxL0yE4NnnQqQzZ3vveg2Xr6sHIjRH9RpgrVvlGQbonH-UnN_wgLRkbmndzWdpAiIiv-NrpVTpotREmbrbfMe5IS3Qin5iUUVz7R48rJr6rNZmIyY9qwYxdr-DY5nrghPu3VUNaVDQmZlFynWtrD7nQDWztl-dAUIU6jYN2noH9cnOVxW6UoRUd8_ME5F3rY8FAzIxj3Lj3uv-ijlFK7FfTmKbQSoibO2x89JpsxSp3ub3120z5CYeE-QyQn77-RPs1zJoq6oCP66rWcvMSBf7bvzD3aBQcqmhW6DdsteEstjT2BjME56tZ0n5bE4yh9NMxfLlpnGfa6-JBvN5DAHAcoP0kCLX63Kz5Q4RE5CIz8_LPd5fQi0pM5Xu1-uDnXOxVuXyrU6QXaWqs5KuyqocVpaZt4i5Cui--FAnde6ESohS1fZ-UTkdaCVfHx8EAF17au6-1vr48XpdL0r68n_88euH7WstEF0y1I6nkktW1rmTapFxfVxOGsSMe69fr0u6Z_nr29UUxLbFGYqNmICAIeY0CcySqlq6yuw6dYx09-zq0vM-NdoRHa7kw9OlGiBmCiIyDJrREDldUFnUd2eV1HP9eRDe1Q1RQburQlQeerdClq9GZ6TkFOfFzCPa7JkNSLe7CWJYqvlA0VAYr590xBTrBydiZhP2i5OjW4qe_TSmq2OuCmvC3Gy7u3V1ZVLt3KnS5z5VRU7Fjdde1ZLjnB4GTpb6tqVqDl2f99vd59lU0ssXFHSDqbnTuT-uvbeZKQdXy05cH6_rWuvj-vnr4-fPn-527TWWjBheojSAFFGz-447a07_y3XY-WPIEuBfJ4HIMkVDruXvk8tWZWX2Wi46AGSXlr29pVRtJtv3HVk1K3Wqfr2_fry2GkQhopUpE4dVvM9536eiIU8xEUpplKQpuxqm2TnQNkwmU_pjr1Mxr5KIVNXzvgsCIEe4xpbvVFhnPh8YkqrnHMVzMZjoGiBCiZwv_aTw0J1Dfhs2XGdDp9avZsrqh8FrDzM0uyZDMpKKbR4V117vr0M-YfvOjnepoxXAuI_b3KSxr0vI7vLXykiatYDVvjdmRQhW5c-fPwl9f72f5X62muadam7me18j5hxz4vVxjTBRzRot1XniG8D6_IYBCLQk__78G_T3Oe-vr9fHjhPm-vXn22bDUuV7ZxWqsiq-Zj3ydGRnEBcVHe-uACljJ-1HzzM_SZt9hdrsRgfb0gQJ24tqUQ2D7UuyFKzqvN967fN-l4CK-_NuICOzEip1kqKVgm9ISD4Uk6KuFqipqk1rDkBL12MEbY4RqAHqXj5-MXnqcnA3cMRr251C0BdSzJcu97UFcn38Iufz4Kqyr8vdq9rXkHNLqRk1c2ujgTq11_scW6sys_tkw6wFEWmqZ-D0IhFhboSstbJC0GrWzX19tIi6mXl1mptSs5Jmgtprxwk3R_dY3n6tn5_nDQKKRqupukaFuk02fmxfT8fSdeqF0jAzdasGjcv2qRjIin1H1Gx5V_z282dJm5qbz8x2XxdIc7v2KzMfG0OrQPa1p7RgviPDlp-4YT4nv4F2dUHNaNpUmgrRJZSeE8t8GNX9_vOeylxl2fbuXtcrK6GmSnPSDdIj0u5uG7cbFehlS6jSuH78rCo2zAzK6RHgIRVpSgqx3IS449PoZsZlJd3Z27yyqPC9MkLNqDrZ9et6_fbHH3_-X__T1truqnrO2_Y658TXWa91y8nKyMr7EKwKVb-nXGGsCP_xMh-KhkDh26tq7zn-MColO-7s7hPjYpCSik6A530Edb_veZ59fb6HiWyuHa1qdBuBUpxAoyPQkvepb96J-Z4wjnRXJTF-LEMlqYBUtPpVUp2ptuY1quv3_5zfH-bJMBXkTCGe0FtVt2TdAs8KmqFnXf4kdgaI_VBniY7EM01Dy5T-8PyCjKBiDtiCO47QKp9GYM98QESkzFdVqq3IwegK1atK3fnMLkSk1aylhhgv1Ooz6r65P0yiSRo0g0hlchy5J58hSh4YGkIoIJlNs5YarmhnDQdOKp7xb7SoQnUuUMNXjTizl6e0K6tS0NIVp8ZGLNXSfSqbPdPZzFYKpQkVsLJGipWRY_WrqMF9dpXv6-QxWxNZdtOKW4FzJ927-j5H3Zb-qKi47ydnBe7XMjOwQZqyOyPKlGOltdmXvMOWrm1VXcjtKzOnweXLKPKypYS7ZUrccb3Wg9poiS4pkSkRokn-9rG6yky7RJ9XSF3LO0upWf1ApEVmRW5UkVblOWeaR1nSU11Whfbl62QOYmUt75FJ8akEfNNnxc2VPqdcHYwlZEp05HcQn0qlgCdOV327WnMGCcNhXtvP-z3Hd1LdrSnT6Nh-ZR4IoFajzn2fQf4Lde-rotytc_xfPCdIitL2BpDn3Vkgr32Ze0SutWCUbol2M4K_fv_VGa-PKzP_7eevnz-u7V7gOC7U1MnMVkNWn8xhYy31ylxuHx8vqa4qFa7tITWciL0ss9blc12nAM06LVM1Gu6qSHd-xwDo6hlV3dVP1hPQjCBZXW7ewyNGU1pKBJRqNypRJS1CsIfp0g_Cz9SgoEBBp7obgY6adIepCaTRD29bYKbosjULnkddhGf6ywZO9HJvqciewkD30_S_s2d4h8e30WbME3NIhbTPpEuV1OiCsuohFlxrnQgqXdXNIpqqMF4fP-Ays4BxvEslZGhRJoBQ5w-IqOF4_Pbz96zjZtWyfBH88cePn78-pMSXmvLay5ftvUFdr_X7H79DZOqnnSXo6q7oOAkwSuLEXO99WVVHdWTOli3OmXH-ed_VYvTJCYnAba6znNgXmidzToqVWTlP4_6ff_5pqgTvOFPl2u4qlJb7ZPZTbhhHXscEc2HKQUZVikhVBcGSPlWEPf1aICPRKM3ZTkxdZ0Knc7TFdEDJkh5_LUROlSgnYykCUa2e5_08AqSy1J_eYmQ38LG3dE6XB4SbZ8Qy77mHAgI9eQRWbHXtmoeOgD2mOg4WEFZRSlGQStsKh5nXmZcIzFSNcULdZhjkaz9SNOWk-2jce7t7xKmsuXpTnjzzfm1T02Vf99faW1Wp5m7L18wXbLkIRdqNbi6F_fEyNUireWTg-cnU_X7__fenGCW7o2WaIvcttHncRQbEMMC0mbKA6iboymNqeAKz8wZs0y2QM4HVJxmbNOe8T0GCHWXLpVhdGZ33raZVYu5igCoIX0aUmWemqwES7_jXq62lON_QGvoCs2scoa0t2TCrTC4btjBmn6xQ8yHWi4BPS9ZUOaa2EuxrKUFzXWrue6_vc7Cb61pLqbbdzIXta9NNnpuECunq6BbB5-cnTSNyvuYZQdUhVJ04n19fs5NpIKujzl67qwExW1nRIVNGyAxShWJKhQ0y2tdabtKIyOu6pKYXJ0ZLlJpl1cdrz6B0xi27i3kAAQAASURBVNKmBohS5-sI4fAS1F3QbsZv8joFQD9jOgEKs_vNrLVe2fXxunpSiK57Fln_uj6pEgqYu5v5M7gl87HEbKGOyObJhlEhsq9dVQ324-4TEbi7usXXbWvnOft1GQcZj0aZ7_s-67q6uiJ9-b5WnlBjt1SEuomwMjjtDtKWo3PZmjaX2aJpndjXK-KIPHIx4xNM_rE_7gyFVj4z3GHij9MjMtWMAjX__Y_fhfLj54_ta0aphETUiTKzOHeVgPr1X2-g430vt6jOakE_bh-6G829Iq6PV2Ut9zjn_vvey_OuqimF9kgzYOLLRDojjcgTuryk3Sa6T9Qw9J8K_pxCScmM4coI0dlxJ4wdRWeeEJQMs4vC6jpRnfOkFXTWIJVRFajS_c__MeB0cparNUB8PIerErBL4C6ds_cifX4386UaLUtXzdNlPG099QBQ1dDzZ4bUKAeuqPF0qsgwJaWzMlse6RtmVXruAyi6jBx-rXQaKNlU_XZdyOghqN7Szw7BbFQGM9ok2RVU6PMThBBTRcL8Z-gNypGPyIRH58oFSk32qVWRPWs-1rPAEFIGxAn2aMK6W9BreUZABFLqnpVKqzj2LE8Gc9SqbW4hTTVU-lLJ7GrfTunL9v2-bV2f__UX8sy6Q1L-VZSHK9GZUXGfO92BLlu777j2ReP78723s6bjTzUn8eN1kcz37Zcvd19aFFdrtiulOiOnR5V5MpKmqtzLhg2u5N7L1KSa3a7aXZ25zH79fJmau6qzKij4sT6eTr-hqzpLSWmqylo-dt6iuCkpT3x74GhTWEGL9L5cOQ3UBmjLZqmy1JXla9GwzLXZmaPhJjVObldT2hoeKe7P995z9TASOq8The8Lo-d0224jvFF1qcoKAlVhqqBGxoAonjXoXj1vdLOZF2bVfR8afTnVzkm3x4kI0Zbe12XbTfn-vFtEyf3xKukfv36wZK3ljn_-849fH685uNU5f75vigzXqKrQYq5quNZO6Y_XVteuFogtf11-MiMC0mYksZbPFbelHq8SRc3OHWvvyWXPn0sIlIgyMuM9J2aZGMbw96oH4mknqqJBzZLKIFuhox2jomSyRv6yD0CcPuima-2Uisg7zlouysI0--fmiyE1r8sFz4Z0ciIUOAnS6aQK-uV7VKaTSRVpcwUV5No2Pr6shqm5SZWqp9RahqzX-iit-76vtUep424QudxjhFPVph7Z61qlVVl7vaShxk1mZNyHZN35L-74ABZUua69Xps0GH59vFL6tTdFfvv917WdzZ8_XlSstYH-8esngR-_fny8ru2qpLmhC4qsJO1-x3Jr6eo2MwrGDY5RgGZJd0ZCtE67E06gza1OqimU1-uKyIlnVuYzYFclcHJC1jj3-bhekWIUM-9mZ1-mNMno-07fRhGh-NKuVsq6zGjdtZ3SyDgoMbHu9mWzOZFnXi-VCcrnX5_UITU_V_gZ20UFRcxs6DpTUstMdUe1DneXj1G-hfNZqorx5obUgIZHmb5UT5xHwpA5iimhQuU5ipkSXdndZbbP-8DRSjPdyyu7T6rTVO-vLzq5ITnNInfV9-f747Wfo7CqL-_ufW2ZRlmlgr7suhbmNFb93DHQpKjSNkXU3ah6Mn77_Q907ddFValClaDdNLLQPRFFkB8fP9_3Pft5kkptkft9qiLukO77681GdVdG3mddDrQpqyruI5JSMmc-gAP4GHw2skx9FoLS3XVTR6hs4Lj2HFChTbRAqH7tHsMohCLujknJNgRlr90n91r5TqNKQ6rP-53vh61XLEE10YWqVAVaukvdKwKFqpqb1ZTfL_9VmUO7xmC-wdl-j5x71kTregngaymmSECC157_56UOX66qbk4n3SeZvdaubqmmap7Ya93zEGhR94rjtjoLDYqY6jlh5l2ltiZlMb08tCx1p7aARgp8r7lgDxu6ToL82FdUull2f_hHSvM7lTW5g-U2OMC9tmQqoEYF3HRasBVpyuw2eHd9uN0nbJbyw1NBk9hrpRSo0vBlvq0BI9a1r7XUsPYV1a_rxXP7dgBrLb9c0L4WVV7XlioF3L1kWHnsDH8toz3vA0xVQ9ByfXw8oCQqlRBEhpnr9u55f8XjA768qqr6el2dRXJdl7m9__zbbH3-_enL9sfr_ffXj99-dHdl-fLqnvVmCmy7zkW0kqqY6lJLl5jptj2loCfEK0JlV8d9SmYHhgYya_kl6LXW68fPqU_sa7G7u0EZXO_9vml27pvGRmae8w7pfhRsJdJtSiWWr47a16qIYcqvpYC-lt-Z9lp3HFvWgikEQvT-uuPEUoVKZnUCaoObnHn4nP7nme-2BJ3Trcp--rAqi3NFSYhUjuxLUV33oc08lD2ZBIp0qxqkKK38-R_zu-lKPPfgZ3Qkk5SXGenpk_0hupJqczJIaRltKooUQaEhXZO-7RpNXQ92bDYGWYdmIkURjlN9xt5VczHE_LaeLs_3HH_0QtVPcGH2FYqZunEYWwAAVa-Ts-Z-_AiVXfMCma1izeIcEEibzuoBatbfHxTpfw2S5zE30YlBxJCm6JIUxZwtGFWiEEFWV-WDqZpb8hSaRVCzs4ttS9CniuacuBE58NrOpG2R1kJniSIyIK1rFi89zvBrXfNjzAlFjWXQPc890WRzm2CW-WzI1rnfvszNpQKC7FjLfu6ruzNym-e5FXrf97UWVe_319rLL9uvtZaeO-ZLvveVlaKoKqlUU0r_eF1qWMsvt66ikXBIbzc-kTGP98lsKtzV3Nc2Duohes4J42h8tJopFOmuPDmNkekrz0dQGyS82VVs2b6lmVlx3nu5otWXUJb7MhdpmmXlaNW7JzNASKtaZS_fAgG4tjs1u_deUEJRVQqSVkRUyUPSbXND5bquqGO-1PT142N84z2Zb9owrESEMk6TeUaoKs10mbc0VUaDtfZaa70-1vv9_v3n9Z___g8W1CDdUE7kg_o4DxvSOV5eUR3ABkTmW1xURmadY0a0cDzLaDdQkJE9tg1C3aXEVKNCzT7z78sWhXeciHTTitTl1IFyPDAs0T5xAFHXyQm76aKh8b_Of7mtHujk1B_YTp3a71zQ0FBTX6s7176qpUQUUFf0o09YbiJSw0vhIJjmL2SiJg_cUmANCILUrOGGQYkB6m6_TuZDyMbzbThf93V5U-bEMHEUpU2hOe4YWBHBiKTT3e736W4dgDTGqcPBHPlyxSy8OU-8fV2-HGoiWGvRVgFutszM1dc28npd7kvN9n7FqR-vl6sLsF2XWT0YYBFBRKqu-z7mDjAyTyfBE5OQbH24k0LVfTkAhY_04CkAGkpylBmTnavsFixcKXHfcb020YB1VWQnOyMIfmyvqtF9KX1oX6QCo_YUG3yQjPCyVU1lLDsyJnXJrJKW-jr3a-_OVtrjh5B-rV3SGTFvIs6fBcw621dGkVaRmHRSU6rV0KiZYVOn_iORWS0vf4kUH_08WyQyQC7bNFY8_szm7Jq70GbWLaKwBdNFtbyjK3XSIUvNlpqTam0qWZGJgmHvF4RZTeV1XRkxkXmpHH7_ZGXnoIPJpuVRX75tLRfBx_Vqeehmr4-fVCHN3McUSbSqXderuiZ1vV_b1IE2J6YUCXTX_f6Mys__-vu-3yJSEcMEfP996DYcFEC66-t_fZoBVV1VJRm9rjUIrDwpguoodrMpogJtBqrYRs-qeXfLtHYU-roaZTQh447lBtWqMrNqoWDqOYQAmpXvr_c7jyqynuvbL7u-7mjpzOzqilKoqHTVGG7dbDwkUtLdbT1-kpbmshbYMjNz3zOxtLUmtSINI9UUNND23pfvGi8dZO0NwswUNsYhG9nfXvdJAYX8et-21x1nRi1dJS2qDmWXSCdt5HQ5QyhSCJ2kQ2VVl7mfPFWyfEeGu4s8rFiF33m-e81akuBzuJqw-B2x1n6_Q4nKQVEJYfP6M7MT2U-7V-8Tqly2Uh8FtppB9X6_X-v1KO-murZ2V3emrqWQj-sHIW7eUovaoJujVZ2mZmoAW7CvLSKqEEAndvvdCxXpSTGqGUpmagGiv_cFnUWR6_W6T_oa3imFUF1RoeaT5Z7Z3Kxu1bRLsuL68YPkmK2rilRzlWpVa4qtraS7mupr75MJowjXsufjXuVrt0DB7lK1yopuoU4tvAaTDKpaxD1pkY_ffuT7_bGuiphsAskcaDUYcUD9_PvL1O7zVj7feLnblxJacWYnVtmv1_74-YoT-1r-2mt5VHL559f7er0gyPusaxlmSd57b2FPcqO7lMhz0NIhWVmQff2ojNEsz1cGE743RR0R-b5Bl9I6z1AKIDkM_apsChU9TIUnLymUVv_9PwfcOZdLwVTsTaShNkA2JaQHG9jAzGVFzRsCZWdy6rwDD5KWlsdDmZOHmre4VqeqtkhJogqQjjDfLSlZ5t_mPsXIqzGbWaCAalC1K2eROhEZAaVBkXlCjUC-sh4BsKC6HsWcsjO6JaukmgObKJCaY7eqh5Q0JzwhKmP23SRklAXGgVhwALrSqtWVzyaCmhkgaIxz1FeeXMsqo4TdYu4Z53FSKlrQXSCyvisWgqZHta0NNhXdzyTbpumskhkiyDg0j06qZd5q1lnS6Wa2LDulhEp3pUh3q0pXZ4Sh13LzsfA22T-vV3bJib18GV_bl1tHvj5eXbnW5WrnDlOaze2s1WblFRyc13Z0720RuWhmaqZV4TqxeA7UIuJMSudlM4OiKs_7VrNxiUfkhMVnykRDRfpawpKZBGHoMo0W8-F-ytqLBNREYu01u6OprI2Rwc0a3dLLzcxVoU4Hf_dXMS8Q1Zerm6mqGk11XOKZSRHjcKJKFHXCVSuTVTowClLV197jfgeqs1QpUnkHAVUF0Y29nabXx0d3reuV523UFnF3mn38-Nl5Pn5-GPDv__7Hz-u1lwn63DEc1hEk1AlbnjloWqjadNxJPmSSxv1-j9EtM90dREUvg4osuphOUlZBomcj2hO7nJ0d7GRu96FpdXf0GSdiN6rFVLPxL9_q3PCfoJRtg36dm6rLTVBDqRshGwmilU8AW9Uizl6Lj_fvWVi7ap-SluW-1U1tYkYyvD9BQ_4-bwWk2cIJTZobVSiokxP3Mjc1Q0tF9SwQB0smRrNCd3RDTC0zBIjMOIkCiezR4iG_4cJTf1jL4j6ff77XTxfh9A6Vvn8sMbivvXxfSyEfP1897lpYT6-gan34_rhIrGsv33Rbbh97rW00grzfN4GMlJEeQuMcX56nBR0YmbFCMcrec4Iy8O8xiERWPal3VRK-19OJERm6JaGn8n1_TVW67xyqrw_d9Z1zemIXBH--D41LSZW_Pu-PtaprKhzPWIaPF5UimW3K7FJFVNUg11ou83kcj9JpuVYkZXigmienXZOVVcXmyTB69iHx8GQr6oztfhzVq4b-K7VsU7rebyNGyaakyNxVKFIdCWk10Kyq3FejImvUuZVlM40wmyG9GubzxG-SdGXIiUrc5-3rGTtXl5q3lG2XrnMO5TlfVuZ-vQTialJ1f73XXlk5ZsaP67X8iojXj5eqjhf918dHRsf7TH7S3egKwJTua77F7lotqmza_fXZgr8-__7rf_19fx6IZNS0bM_7BoWucc72Fefcn1--Hx0HlHFC13QECuiKAr9ZQAC6taFqTd5dplB1CNRA0-x2dYVCjWYk1LQbyicFJ8BediJbRM1Bya46x1yHg1QpeSq7SzozzEcHh2V27tOY77g00YJqIdWvDchau9E0jyrbl4LmDoHvNcbGdW0pWdul21_L1Xw5yL02x--xnfOMX-amBQrazHMq7S1UytiyB0gIImMir5w9hnRktvBkKBnnKBlVVUM4ZURSSbeMbBESqpR5umaomqD82hmTUZHIPF85iTsQXXWi19qVoa7vr-gnICHd8v-N_98LF0QKkqeghPS4-U4-rCoIqBTSx9Ktqop5Pb2uVxFfX7dvr64fv_02DwYzQ8OdQM-5fF-u1LVmqC1qHKJ_xpHuEtHxdVbTXDIkc8ZJeP68k9F9XHxdU5qf0J-QVONlLgJVzKTD9VuvOW53wMxECZE__vjj77___vnrR3bvawN87XW5ZZZ_O8JIlRZTixNUTAR3ba9KCL_ObU51QiTfR90K019AZqJFVX1vdr1eL2O7a5fM6rkFpzKzAN6fbzM9JzJLvv26CqGyzhmCSKF_-8cvN7tP5rnnUCHdEJz7vJYr8fn3TapAqHa_b3Zd1ysiMEcL06_Pt-9LWmlYtkMyT5AmMugw6RNm7Oru6Kw7sqoo0pTMIKUyZ7H_ENMhFQVBDy-OWi1quyt1_f6f6vr43lznFvsc5DtnL0Y0BKQ-AdxqXTsrRXVqdhig54MWz0ezIoPBVnmKXMg4pA2gbYgfAPNE1-RyUtGS00IaODlRZaqDVBzku5lOqVcopE5ysbsg3UR1DWSwuuAcBqoapivTI4GrGvGEgJUJHQLIg0kaKdnAEBRsqUqZ8d4ZCOBzJJi1RWcVICWlxpGedra6daeaTbc4skWniw0ForvIzCatqnytc4ewaezmw8h4Ulls9MhBqFoipiqdEJwTJEpKBEYbPpxt_0Yc8ZukS1NtdmWP2M19Ebj2doVTz3krSROzhWpz-ujDutzdlF0pIuv7KHlOttRw3JUw1Z8fF4_srW7sLHclWN2-XJ0DgI9zC-GX3g23GfpJVZrrVn-KZ8Tosobykd_V9ae4Jj3OPY5ABbDl6jaIdHPWc-_D85rM9GUGVMcCu0pBSKs9Mi6qv_MemI-pZ_fJ1MVuUVs9Rk9CiYzYr4-MW1qQNcMMPNNPvK7LzRswX-ccVY0IFay1H4GBwswj799-_yPifr0-zvutOnxSW3tf195776VrrV8_Pv6P__0_tpg7utqcAL--Yn4Cvpaq6ITnRKoGj1DSUo0Bo2PUlZ2DtSXlWuqKIeaY-jiczTUjnyZPIzspolBxXaYzZVfXRrr4axlUq0uUn-8D8K5z3_nuOpG-Flpa2rdWg6PbQCu1qpe6GaXLZ4AUtZwv2w8sH61KV4-Tbgbpa-nWiUKOy9WyKqWUSuG3rNc5U32SppPCzJMKmKmbtTCiVFWQEzYXsgeQJ9XKJwIy-rDhj3VPvneweA3JSphm1tq7u1FSGS3y8fODpmsvW7r3ssXrskiQurbVyeu6Zlpm2yVibVM3XZp3rbUMnAGnSH98XCXZwuiZUktO_2cmtdlmQzOvWfKAjyVv0JYk0b32RpcvzZTsmpMAieWGb2hudXflfTK6IFA3tHA681Qzfp145jZGkNWZo3IPoYkAT4b7xLhY485BG2S3qwJFMDrM9Nz1kJb5jfiskm4-RgV5AALQ-ayezIOx3uScWu73bUsn7SJkVbn5vEekmZUtUhHf0OdRdbMhVS1Sw0WY9kx3q5GNBwJOGZwayRkGj809M699XftVLVAXga6lyu5UVV1rue-189TjSyJ92bDj8pxRuWWkr0WlSLkvKvKEEPvagzK79gLkfd7Xx0tVARFttz3_DstUFVPRus_5_bcf83cjZvrSH6_XiWjp09WV73O-_vqLWtIdd4LiaiXD9yppqaqWnn-fjoqJDBDDnRTwfr-ps0wTtKhaVY7cpzAEW0GL0QF0y9p7cFLzc6soKnWZPGBZUtFdUJr5wKKqBr_ZBM47xhoknQL4cqmeWoWKcNk57W6QFqqofWcdrVvEde3N5SK8ri0i7ssvMzWq7tdebu6rs_brgkyS3_y6UprqNtR5VSlRmm-vf0k-TwOox-eJvtPdzx3jJezG-5wZdp-ItZZAcmqspnGSa1XX9NDXvswsuyfLMHWXAXMNpgdK_VeRu5uAPzjINfbltRe6pPq-bxi7ei-vSsn6IT-RNePfEoj0-TpruwjOuVWVwAyD4sT1ukxN1SJ6RmCnS919m2RxGd3ctEuWLzp__rhaHg2ZGc0N0j9fv3qQGKRUua_BpqnQ1YYIX9VmGpEj1GnIdq8oo44NY2iwLaLLJFsge12DCyM43vrOWGuPm8aXd1VVL18N8bXMrat__vhZJ_a14-RPf0V2y5yL-GTMzg3V--stGNNIjO7KzPW53s_YtrtbfY12yUyhMNOfv_00wmimRuC69vmKlvbtFdWR5z4URGeeqsjuqoh97Yw4FZGhau-_v9brBYVAWPj6668qgFC3qs4zWmp11f_1P__Mbl0GQZXY0jglpG-HtEKr0azR3Qwu8huWKRDmSRi0NTPmCzYa3-qaEbyaVh0j8tTw87-j_ux-hIkirf7bf6tqAWUgH1Hkw-KkNCGVNTeGnqpUF58cBVpZVdJQ-hzaQMzkBbDqlJFUT9P_nMeTMloFEYAVbzVKRrdI5QwjQYwhmILhIUQNK1Tnfzi6uCzpxAz_5wp4V0Jo9OcfEfW462pUwFI9eEGrClL7cdcLhN2lsKoWDkCqKMiMWSs_TImpltl4JVPHRWBamY0hyxLw8ZXLv-Ak0uoqXcA4NX6c55AuBCpSTTOiZdankwx7jlHDWifZmao6X-aslkJW0kFRzDUUNt6IzB7SMCBZfe1VURHZkUt1qSrhkxtBx0nfVnX0uWIoIF9_n739YToJqtLI17WzUgF3nQWcQgj5P__5T5H-44_Xbz-v-33MkZKmigYG7RJRUkpiBkUl6DKQqkC7WkaDnJtbZs1cZJiwAE9EVGTG8DtapKue_neVqVZ3i0QEn8LAQHTL3TNPS0tzgstjD5kPlaoXCmylz3lxLVvLBG1qjV7XRorpYtdlHueIMO_38hURNKVZRdu1qFbddM2aE0mttRWao_vu8LUAvD5-dMWPn78ibqVGnR8fr_lDvl4vU_z2x6-Pj_Xv__zn79cl3SXtpvOdbyAyzcxtRoOP89rMJt1IkeqqaSOIRh4apWuiThPsgWpOIHUGSpBrr5wBAU0xQDaKoE_PPaqjRWStBeDrnJwue3dlGjcGs6Hcj3nXAMzlYbuDEPTaa0DcWel7tfS6nNBpz5CSWU8NlKIm2_yOoGMs9AW540xY-dmkjJELD0a7peaS3y3Qp7A4iSAaOmbvzBM1z76qHsPteZ-slJqV59Bm5rSqKTVXDri3PEAqFdp20TGN1-vjqk4NvD7Wx_Jq-jY3vWx9vF40qCrdThzn8FHpZuq6TJd7vO-9t4J5QlVjPFbKuI8AajMRbzq7EZlnStldJj6P3KycnKI_cWTME2DWMlSrhKEJqa7IjERV-lo1T0uBZI26fK-V0V8ndE8nBxV5sjJgYHaKoBvZmaN0aEYljaJdE1KnoNktDakJXAoH8uM-3REZCj5VT4QU1GZIhM-ve-b686O-T3SlgGMjya5vIW1D5GQ0EXFmPgdjNyRTVVW1p4zBfsDqfCKlZuZuPePqR6j32H-1YaZzyK0OVl-vH5kxSFwBdGlMZoNlpuLMbF8-hmkCmQVCIaSutary-57Geba7--gpu9tMB5imqttct8Udr-vV3RHnt58ftoyGGVpvteqhzbaIuLK7s6pVPt8ns_7686_uPl9R8-qEdMVoqiJzzgRneKwTj3sO4qwuc-2SzOPunZMHmOkGh-Ji-nz4ISpNXcvHDqggjeac-ntLV9u2mUE-Cvehw4BSogRETs46qGeHXzVUQBk9ohIKve9DNajQFNTuNndk0zG9hRZR9WvvwWjNzIWqahMScUxO0vyg1muraUaq-lj_5vVgagp2SlV3t1Fdrav__vN_0vx8nR8fP05ETOSajOqE5ByS1GQumVUz4xfyfQ5GVoARlSA7zcadoyePrz2XIupAx8vAlNlkY1gLWWVklXRJZubJyalPSVqqRfC-_zL3iHq_YwLuFSKFr_dbFff7vtZVIuha7uvyrz_fbqrLqo4IerEjX_phrgJxXw7-fL1slMnS5hzSWleqKqDfjhrPLgKul1JFymbCS2S1milBt8l6ZImagbzWjmz00LDYz89PzW1YlmPyATidv7l8jsBBRHytOOf146fq2GKpT9lafK-B4RYehsS5b10OICvUrSYWptZVbt6Zy3ZGTJAK0l0CskU6W5fnfdPsH__849z3Mvv164eC5vTl55R0GRhZdE7uKzNaOk8KkJkNfL3fZibdjzi0tFuua9ncXkZDbjYR4jx3d6rrifRrVcasmZfvPLHdM9IUVDnvY8pzci5OohRFRko13O73beSpJBgZ9S97B7DMznmT1gMbpUbFGH6rEqb9zOdb_Y__BFHT-JEeavXjCRC0NFRnwEibJyK6RFWLUifNPiD5MGueSdrw_iZXU3MZkk6SlQPwEFArYpztXSk6FqbBCxLKnuxS10OXe4hX1SUTmq_BgM5srB-mKAWmrAh11W_S2dOvMetvOdPjFenJs7SQ4xXvrkZ39fxxOuqZayiIZwmCahsBbQmAlJrQZw0-4nt1WBE9MsXhK2WSKj1anHuUtIpm9Vrr_vz0ZaYqhNHqJNXilDqfnJba5DVdPSV1zZga1e14vN2g9alTWWhVgoIqM3bnWlfG2W7z1FDKz5-Xm1KxfV2Xje8J1dfli_RFQb6uNR2ywdZW5jKrO4ZcMebgBfKF5frjtTNibXvfNwWQnverO1ukus7J7h4mDFPWVqWY02HZnZ1mGhnA4A50cofSPST2Zfqc1VogkhVKgtpSlAkmJpXSoqC0mFKqlbrdOuWdsXz1qA3BeQETsnUZTaR1Au4da-2ONlPvNrXz91tNYxIY0gpUx-vH664woy59vZbamnkwRKpqtq4ZOfb0tbYZqSrdr-saxJ7SVAYkoq72eq3Ofv348duvj__9f_s3bzFXiFCY0fMZ_nzfEFF0Z0OkpFVIkczqHuOfgBInIe2-u9KomdNmiyeNIu0-HkZVKqqyq6qo4qrdOBGqGK0YCOi0HeoxHSvyJEq6cXLgKrlVT4aautlEit3NFDY1AMg2p9S-XLp-_HidiGmNE2LGaz_JP1OrE5w6DSA9YLtWswGKKa3R0uXqI94AZ7bwLWJWfmwP6aqKSiVnIBKdkdHZGZWZBN9f785SX4DUiaj8HgiVmoHiZro1osY4Qanxq4uUlHScCebaXhWpvqJqLV_Ki5MdV3cThaRUpG-TsV53G5WQ188f-mBeZHKAs4-2wdKdFCIFY00el7FSpXrpbqnuMsLUSZkoAs26e5n24_foZVQio3xZtTyN7ThqnhL3-ygN0Ihj9FMhkEoxV6lSzgSil1GIRlfled-zG-7x_jq7BNUT7Jj6VWROd2vw2a_r6shuack5gkZHd7tpVxfk_fUW5dA5GjjnVj5ba5ItIwaTCeqcvNeyrnK1YVYPxHme5DOZkhadvvOwWswgGDDXPO3nHcGWzmgRU5pqZEl3V0sXtV5rSdfLr4jIrGXrROzXVSjf5qpKUpWmZjKpaKq6obuWLXXDjHKFA8hzm-Os7Uneq0o9adi1bGrfyxYpTvpaoGx3NzOldHOSesBa9v6Kd7z_-uvz86-_K_v-_ARQEZlVURSZF64rO4vAfW5bduJ0S7eoiAojQoiImDO4DBf8X9cEEupUVLe6KaFKkAW5ro9xXNCU20se0VZOeLhhyjzj9gKnN_4gm1iVhDZSaaO9767OiT73zBJmACgitnZlT8YIoC9Xares60dE-naz1YCrSoivNZ4v8zXZ8bv7Wh_DDBiYP6ENiYisbEHkMdPMGM1qnqpAZ1D1Pjd1ve_3fUJQJ9OuXR1qLpVd_b7vabuIaqHmQV0V63qNG_t9Tj26wCI1u_beJEFm5bWuiFuEERVxR6U0pOpJrgKfn19oQMX3wjS7KOcc2-uvvz4b0ojuUpMT0X3nCTP61vsdH3ufc9xXd_mykmY31UVwPm9X63yDfS13mCp_frxAM4Aq9YhruNfe21VNjezOCkLnNS1SZuaw2QY3h-b98PipOsn6LlF3oUzYbIY1wz6WbPc1LuqnI_f8X5sv4LouyRL0r5-_Mo5Sfdnr4zUTSlsmLed9N-T68dHSrsyoeTSrrvt-QwQCwwN6E_DUMfU5EGccwN7v9xPAM117A2p7TQzs918_VK0hOWHk6qykqTQ-3zcNGSGZQlK_8zICNc8IVasu20t9Eb2Xn3PTrKMiQ6n335_nxNfXm25N6SpUkegou3y8IjC_zwEA04hQ10WKCJbGSULcPTMKeaqm9SETSKgibLDdJaiq7ALnYCI0ij3-R4JoIUT99_82E0CpfCDL8yuEdBaoQ3Q0M0Dm4j5n8GnsSb7nsSGzXMiE4pvrLGNRJtiPf6o7H3WndM1YnWYiUpGgYIoaIqMEkSxQI26Y1R2-1iiHBYDUc0Gp5LeiCD3WpVEcFBVTL8V4gdHST7X0MdlQelh-wByHOBcoTN4mZ9wYdwzlVxqEuMh0xSCQlpLszmW7qx4qAgeYp3lSTSUST0cCdGaFmrY0S9S9ulS9paVSRCXDjM1pJXNkAv3cdloE70hpuE3wt6TFoBlo9nKKYK2PxbVpUvM4q6FgEjC-aNivEYuUm7pRWfOhWMrO_P21e_rKAEWuvQgZUwOkCKGKuUr0bx_LjVm9l23XpapP1AsA__j945yqDAHPnaNXI7GWmoEQfqda3-c9mxC7rLtV0dUQXDZazYE4lbunFEqIJpgiEFZWd533n2beLWYmSMVUunmtDSqAay1ShirT3SBhaMBFIkI5SAAZJqmZnRPq69xv3-vUoa-qEhEjM-u1f4Mjo659KdVsURWVkv1-fw5cjBMh41P7FenrWq-1qePSgTmHNvw__vf_Fu_zz3_7w9F__Pz5j48PE5gT0qNW6a7M_Ouvr7VGtChUNcgTBREpjOAc7_dRw5wUuyrOUYOrmWl2kVAjqSU1Dqas9EkDp4yJsMcxm7XNW9LdHn4qdFH__jpRh9CIEkhU9vSHSDbW5Shxd0iq-oDqP14u3dfyjNzLK_J1LSPddKCTIjLOBELMNKdjUGk0U8zz24YowBL0nelUEZ3D-kwrFBymDKaKg_n2RUV_3e_M6mxQutvUQvq8bxL31zvzQFlZHLp5tbpmZJzoks7OaOk2mqhUVkWpP3FV-1i-zJeb6V6bPrY7q4hqAXE-j29XQo2uZqoScv3Ya2-CavaAzURIxJ092gRpV7-jFq35PD9PFWr64jdkVovAoJ0AVaWyKnsQgCKvfYFogZhXHU2JTJESyrQIMppgZw9eurtgrC50zdUqO7OqpdXXmfHnEBUa3W1OqEj0cgV6-eoWM42qy2ykYFTrir0sMlskqgya1UPQku99rCrztEipdFaZkoJFIxv2L5cLKmsM1jKi2iF5kGosyVn6dxXQywYubBD48rVc0Kq63Oeu_v76HMl5qWZIS1_bJxB1Tp6IUzlflREC_Pbzx_u-3b2rTedLMrTBXHvlOeNQy0yqZsuor7ti701ll6hR1dYyd9truel8s8w0IoxcbsbJGbkANO61l2ucEGhLm9o75O_Pt0C-4nz99WWu9_uO970-dnWX4Hrtqa_kaXWfo0-JdJa6lfRgxaUKbtk12L8BC4IoIrNMNaWTWO4KisggzlpA26ZOo62l2--v9967Kimc-Zcvg4Cu5rw_w7b9C53RlSDPfdR16s-TPiShKq14R9FVTalMwLiE4mtnlC-vGvioisTr1y-hgqpDWls-P2RzM-Vea6jfQ6FRBUUmN7-edwQHhntnlEi1fP79lefQeGfcJ7jXfZ9nq4yhpZ2Z9zVmrMeIVmNVZU4jrpZfn1_vEf5ND9LI6iZNIEt3dc1r6evz03zf7zMnOR1eeQuk77tobIAKKSiURlHNTGlElrpFSkbF-4bY5_uwIdXvSKpV1df9tdeOc_bHriwUhhJYQ8Ed4blQ1aGyrm2gGxFpbtVZ3e5GYl9bskcbIwJog5hv63l_ce_KUtU7jppVV2XOgGR2yQBcFURlzeGDZgK8fryqJE7aVjQEsvam6zlBpW-niLqS-vefX7__2x9qCorvVSn6mL9URETFVDs7TuDZzOC-Q1Sk2m0N2l2VJwNgo8cTf5-3-cqKtddYhqpq7Y-o8_GxSL3f9-t6qdHXroz3-4B9fx01q4w___oSdGS4WZw4cbpkrnlDR1Rds2fb185IKPy1pcTXOvdBNsiWNnfJkrYTkSc___qf9G1qAGgWcYQE-7wPFSPLbOmUFpE4BaIqfL_ucxtNujqTVVDtzm-b1owjKZkUASVLZJo5IuzHsaH7j__eEPRDwn4GISQEU2GUyZ-2TNK_ZHyBjSpk4CEyC7_FEDXxhOmJz35nbiHfnRCClTlno5aeD5CAwmaPRbgzc1CME9MkGkRnQkpaq2roLlVpvipSCIGNmADKiOAAzgT_t6k_88T8G2FCPhNW7uZYM4mluyEd0SiIzqJAbHIF7O5siRqkaUIJNFV7wCoD7ga_fQIy-5Ken5iyq7NyNmVQZpYITgTVJMOmHDw3FqWuLVJ9KisyUtWk60gLyl27S04DPF9v6TFmUdFGVn5lZzFt7aqUWYT5HLr79XopYdvi9Me1fuyrs-OcvVbHudYulEBUtatVdSk-Pl558h___DBwL1NBZP7-Y13LlObKzFLFtYwkDR_XroY6s5LdUyTKd5nrvryiPpY3SmFSYxdtVTZGzEwK9EkN5nyvJrRXUqpWz0xUSOupdmaqrQGyN8RtCcp9CSSn1Y02svt7ndWtgCQ6M6IG9zv8qJxdq-Q4DmksyVKcKFFRsrrMtJBqdDeCvi-aumpHVpWbjax0KM76fcpV2HW9Ks91fZw4qjTV5f7Pf_7xsffeq-r88evnf_z77y9zV1bmYzRrIXnueH1ccXrQK4J2atZE9pqCKslKU2uRMfh2lSj1icBgFpeCNpvA7khEMRJRXwZh11gC5qMv3WLU6QN93e_POFFpuqNivvKJNjVSTDFVp_1juQ1E2kSnb0TVhyc2aZqlntLUJ1lXIu_7NrOOFGp1EXzmuNIG-oMBk-1LCeMs98RVo4LAHTFQH1crCCY5VzXEtxqZCeV-3yRb5L7DFB1zVGNXzZpLiCl7dVee5zIB5WzS6nRKQcHGvj6g4zRUV9vLhXP5JAZP4dZR68eWLltubrpcgR-_vVzJ0kn6zVlWpKUm9swuyZasPDkEYXaVmEiLkREB0n2f-4bqfQ7IbqkuFTpXVHaLgvOWFKAizn2fajXMtufl1_u-332Wu0zngdOsyKn27LVofN9HSqLrnuhXtkIc1LlA5pCCtavwcMA7xi0HAiMJ6Z5E2XddipCJQkUGjGfs7BNVn0NE9YyHHBaVOvEC8MRxc6Oeamm0FARn1Jjj-uzBcwkIU8_qauxrDZeSo9Sdhn6VmnGKA8KZIanSYerwtY0w1fd93Kwh17XnBssubfaJ67VZgDwTVleXLijXfk2LdF8bXWwS4qaqT8XRp87RImi3NWOvifVde7f0_nhlRkNNbZh4jRa16oYyMzLirz__-vvvr8-_v-7PEydaIMDaKzOBJ20PZaPNPbIhbap5B4TVktkgRaq6TbTzDGW3Jp_lG2iz_WRuBKYG261ia6kSEDWrSirdV55Qd6lS4XBI1rXPHTXOMnnGjf8K6cnD_GVK9re0qEumbQXjiCamRbquBZsZ7dwSpLNmg2t7QxBRulxdK85EC4YbM6NoJbuk7-RCNf78OgLJrO2vr_NZ2VV93_eZNV9GRIhqolQZGfoEGmSQIkbNk0LT5UNgVKO5irCqJ3YrY59tebgjZo94LnvKx9V13zeVGad6lHFNZWe5-TmR1Xtf76-jxFOfUESWAu_3m8aqiohz3yL4--tTfXXH_AxDqqLe97mu9fUOv1ZlVU-6RtUszxFir3X92CSXLZX--fEC29Urk0ZzdbUWuT5-kD0Wrr_fb1_X-4TRFO3ryjy-rbpcfeiMPUWgnhGugjTfggl8yHeI49FQCuHLFITpYF6kWrJ9OUlfW019WWR9fLwy0rbPIMxmlXHfph4R7iYl7_tWcz4xYBrt_fk1i9AW-fq698eqyB4oNjg36msEZBR3H8fwsErM9bWvpS55m9s59VjXMofgKURGVba62vZpyD44XbI6uiSj_MPdVhX6Tl8u6FHTCRAn9vL7nCpRZXy9qR53DOab1Ou1830AvH58VAztBpk9B0w1dqapZg4STdDd2TOAaJGKJmV0v_yWovbou6E9D9sxekqp__7foOxSWHfJVPuH5TNnZcHo6HUKwI9vDc0eFL4I9f-WqZrNe6OTQFagSjCtagG0q0RqjAYQNiHfQjvKHP---wHy1GfQ0tmVMTeIluei07OH63zeglkDXQYojXmvV0hV0z2rKnJOey2dOd6f4gQrpeksSOZjzpNv0958mSsTwiHMAK1AlWTPVUBsiHVP3Uqo2o2BI6F6TBMDtJo9ccTTVKtOdEJM-V0kByuHTv01Gwp_JjHdwzFpZNRMsKbVFAMSbrlePzLvkolFI7P2z58CubYNdKWySHntdeJs51KD1Gt5RBhhS1Xm9MWuU12dtdWk6-PyXx9bW5bClzf6998-3Hwvf32svSmNZTRlnt6uoqg7Z_M-iBhb_vFzv_--3dWWmS8zEnAfqBSU6DklfHNpVDVOzHQKeHIp8oAb8e2pbFWdzQT08czX5GXlET5AZECuNRkPjtuuO7IxYldEdnev7W6mpi_zlpZMyRrjsgnqxAxs1nZ73uhGci0758zCZKoL2f2xXyfOa_t94nXt_drnvt3m5REv99e1f328fv18_fz4sZa39n_82x8_fmzKmM2lIrOlHg8wBaKuJ9NIM5paST_zHCArK6WyIcyMku5OBQ3aVdtWoVRaqWgYx3P2LY4mVfndEEKLlAxrU9yYIildWRmh9JqxcEtJVdZyq8g58K_tri7Vay24mCq63WzuEmOzGSRui8zfZX4Pa3lXuVlOsGqgd9JAz2SoWwbSZard7fqdIn12U3S3wQFVy-fXV0TOkr3kOx40MPiUc8JcI44vA-fePKdgvd_v1_UCERGqHGj6fB8gKMpzJKXZ0q4qabYss4_XpcrrMip8OUEFhTJ__IasvQS6FK6m6nYNDlLmnFQ5n2pGFmYHL9R5qPYTe6vuysKjcRUzPxFrefW_KAxC9NoONCFOZD9kym5WSEmj2d2b11251RoEJTKqqns-V-ruXXVOSTWdSmZUVm_Vyursrz6zb4rI7BbKZdep-7zf7mvitct9jk2Zqaac_Kpq8-FKgXrOaQV73OgiNXfvEkFk_t1h36bxz_fX67qqZOLjXT0LKDxN-MHb9DDB8xQVJaWCKcQPZRzKzor7rc_3lEOMcJukKCBiam5magLo9upca533-7quitrb97X2tZX0rVAYVFVp3K_VPWmButy7S_uRFyhJw-vj6qqfP39W5VqPy6m6gN7bK8p9N5r8ppi7EfJ1HxDV1YLIind8fX51x-mMqKjA_EZFzucXOJ44HRtytwE9wMpukfFlUKRruZ_77khwDiQUio3iV552KkEl1cz21RBbPuzVsb3O9m7ww7bW8MdInui9dz0yQQVQ2UoKG_SW2HtPYXo-8xSo2YR8iAl1Ggl1VzW2zKaohUqau7QgezbIe-18HwfuP2_d634fW_44jKv6TpDGlZ1xomVOPaHw-37XqRNp6JP19XWyqiIEGnEaHB7ADK2zi2ZSUpkP2kYEOkkpCJhZpEa3KdxWxHG3rJTqFh00ua_VmZU9F3gAGQWi4uSpyKgsoWbPXyCNwZq0Ke9zbHllvj_Pj-vKrnPixBnMRmXOOe6uhEhk-db7hC27P9_m6-vzq05R6cqKNOPH61XR1_Kl4qof17rfZ29tQXWZuWTuvaXbt3dNR0vGatzdl68uMfNzx8OXBnxdDaGou4-v2mx1Jydc3T38mLXWILDR87dlVdGtuwD4XiKoyH1dlanmP17Xem13v08Qhq7KWXxCUmyvku-u6CjeVZ_G-UQjIO5rrf3115_X6-P-ytfHpQKRolpEDLhWyKzsLFVtQOIsXz9ey20NK6jJc9_61BSfbQwBlcfIFvHduX-OrOiu8067Nqkv6v337a-rpTIqzq1kVicKbu-_PzuTRjoz7vGm530-fv7oiZ-egOFfE-0Z3M-8zNQrawLPJZPNgXzHlqpzcHDTcYU9au3qeSFOQq91_f6f1SLyQMHnGTEg7eEu5hyp5xgCVWJ6Zt2ALUBm_1IiqCYhlfNe7c7nPY6nvtzyHOBQpTZ9miHYNVW7ZrvQs12SLsqTVIoM0uoMHL66qqFzsZZvB3E9hKMJxfd37kjUNOKoGWR8XiMVmIsHnsaSYBCi88qpyIkzPTecTlUZrdiUkiEi5OljutGdmXhcqi3dj3N2fihkxoEy3nNhPTSSju8P7iyvq0ts1vo0Z8dtvuLkUHGkM0_oUtrsuEZryRPvwb7muUWkkfB1pGmcBdzallHbVtc8mlOJa604aSY_Xz-iSx1r00zjxMf1ijrb_dp-XetyN9Ld_vH7R9znui4AvvTHzyXZ7PLLsnpv_fXjJdWudGdLmurMyM1sBlRdORrYAR2omU9qebwBwHQ5h_nj5iAIsW8jH5QVOU1iqZZG5pDO-YRGZXSe6Mm7iWSXQKvkxOnqkhKdd32BHISIme49EgCY21Qwzbyk4n2bac53o1gZSqtTHx8f8u0RceV2HwvyE7uDmKnQIu5Cufu-lrtPCsidIk0VN6X0f__Pf_vnH78Nv8ck_uPffl-iVWe7ScvwQwnmY18PAEa4GWpWzA8fs6qkBMrInLc-HqP2qJclKsHBRElk2eM6nrrEN7s9SsGCfPsgSQJuMy3IbHXPqL1eIvlSu1v-8fHjVLibUAx4_fxQHbh-A-wspWWWT953po5zf5Cm23cbeZTnBJumm_4cCFtUufae_o9OGJqK-VYJqrqJCX-ICMwbMZGGiLS1TwV9iRSVqovzD3oyD_rn3_d89c10Xx5SqjY_sXMOoLPvNjOg3u-7Baq6ltk0jwHfy6BrO6Vct5JmNpD6E0fdxCCNrWqkiH5ci0I1F2kb4kL1xB5VvbKgUNXImjfNrCEisqX5PEeFYFTFMKGrQZoNJiun-klAsozr833u-wxvUaTQ3NDI---8QbhbnJIHlpDz6lhqALqRmU-PqzGTaGEpNAkFl1tUCC07IDh1KsO4xk6AZ43W1enwBqoSis11Oju7OgUlTRo7H3h0dclzLO6BC5uyuyNynC-ZSWVETl27qggMZsbUK3PwbqaaHfOdRY81DxlZVTI66m6jFrRNfu7XM4auOe31Ow6W0YmUOnki1jIS7ovea-_hMVXWWl5VAJYbITTNLJvFb4na7HeGAKadtfYyEqZsGfd2ZTUBivtrBNVx3mMTJzmv6q-ojr6Wf359fv71Z2TkqcyKkxU5xE_3nZXLrcnItGVUkISBRFblaTf9rsO1UISoroH7VTWMNVcVGtxL0vcWQOmkgerrsmsLMBOQnpOipPvKSOlnUj9lmCnvZrQa1BSEmkmmmdc5VM16HDnSBehDgJBHwek2cSw0RKkTl9W1KsvXZe4VNaq-Kbz65YPo7bwp_Pq61U3V4BZ14v2lhr_--pqKXZVU1f2-78wmYmA0-QDTMmOEWXUSmdKdUXXutZaRlXVdbubvd81mCsrozjlsPA9T1HwLICKwvYQ01Vm_uC1QPj_fD5m-ysTMtNlCRhyC7_umDSGQ7hbVc66trlmRvc_d2Z2JCBbG7jRPh8on6EKwKiKzI4nGtvNO28as6-UNccg2u9xt6V7e3Xb5ucOMIj1lajUVICIzkgLJrhIxocL6WYZjvr1z3Bkf-IyvpKXKlnX1vKPXflUVldfHa25P40BCE99jnft--3ZfKzPG6PLx-lFdKsgTUjVWZt974iqZJWBnVpRSCxKZDbhvqXrf4dPDIYwmaDONe4j42t2mq7Lsuh5MpXTcUSde1-v18ZOotb277_d75qJUVdW__vwk6RPrP3HO8WsLUTlO2KNqagqR_XFR4Mb9sSlQVYzxUhEiVHt__t3Vce5q2F51jpqq9r5emWfe7M8A31RaJLtT1CzihmqeW3p2V23XAqFLM5KGrpTqh7uq2sJz3r5e8jwZdTDxIqL73_77ZH0eQ3M29UkMD-6ynlQ9hwlQ1U_of_ii4Ih5BAKa1M1ncTZfaQy7U4CeYap8925rFrgyfQs00C2Kwd1I5BjIWsaIOZP4rvnvRGaisqr6YW6JqkKqI-Yr0JUkJtpE964CyQnSi-gUdvMZHX03UbozIa2qXUVaSQ_Tvf4l_pXOc8tDplCKSOWjLaMq-bwvBVVVEKoKS0H3VXnP6qXZ5L_2CYgsrvnR2CQMKagqNehkFtkGXXxMMbNsoWI25EordEtTps2s39knryxzI8TcB-60OBAHdhOaqrK-C7em9MWMdB2-l6iaQ16v5dqv17UvXUtNqMTL_Nq2TS-317UkUkdbUKVq7mogBe7aLe_31yB8Xpd3i1PU5ynVtKF7Q2ZdTi6zfojhgJSZiogPz2tyIVIlJTlc2oqskOT3NRJAVHa1cg6v2dGC7sEqCDpljNxDjiKZWb4cUtKY8dXn121qJdmARGeFqbaILXXXqrrWBkXNTHkyG6jM9_2uLHmY_fV6var7Y7-uj-uvP_9c12K3-SwN65__-OPf__GbCirbnR_79Y-fP9cyXwtVWa2mkxqdArG5KeVaG9PzI0CJLJTQtB907rMgmXBtCVL6nGPu1Pl4lLqSopy2n0BgxMXdknwYKQJpE5Aa1SLoaCqrE0rpb_B8S7P5fLjMfSOrq6fZjJKBB0-QabVmixpIhcDd0A9gnySmnSFi1Jw2ImSvhYkg1vSFIIJEl-BkTv0ms92tJuVZmVmVOSODjnRflfX08rul8ffn51qmj7HLhfJam8TwPJQUPk0hUbQ0aWMO8bVt8ostBNbaQu2qtVeczx-_fl17PdxJkYi6rg2lmqnqNkXX9VpEL3OhNFqpQkYVmoVeWCWzsJesksYk0EJ64p8Or-6YcZ_AlTpj1DHimQ_wedoaSt6RBJYtkQ7pFCzqOaeEkY8fJys7c9x7M7LILDiDlV_pwN9fb4HQtCoJvt9vkpf7fc7siBSgtFQadYzMkadFZYKT0JT8OvdSO5mUOtkidZ9soGrmJohz5NGCMGoYyDKaWzcfDIP09GjnITy8INqo4lJOhJqeSIpIduZBY61X1rvfwDhfhiBmo3G006GwOQTTp54d5p5dar5sq5GtaswsV12XdaGrzM2mOFVthr0dIAXv-3T3x-uHcGinva9tzv1aeeLHjw8FHtcXkZVff38NaprqWfHz4-O__vqv9-fbXF_XNVDFkhb0_Y6K-PPr67_--uSyO_PckVEzLP_6_Ir3qQxQbLpkTYIFmFmekhZXSNfobqTlfb_NHA2SNUYaQFoIVXWptn2p2SOFctWB98HMbTy6US3Ata-T1eDark8Wwaa1ZdNvmd71KM_6CYWreWVX5b9sP9U1SF_zmfe3kpS2tSa_MKl6Uh-m-ehXiVFkgJY5ErsEpCpnorzdI-J-39OGjCMCOV-f3fjr82_1dU6IWp4EW81OvJVq8Pr7fn28viXONU8pmUOimYiqPSTu--RMfCpz7Z0SENI4zcOWNpv3e0ZVZGZlnEOwRuLa3RFqej_Jth6twawxRjUV3RRGxPiI3vdXDFUjTqNBnXJ9dq9rdWdE-V4ReaLuzwMSIp9f98_fPlB9XduNSn291uvjmvKVm88xqsbgqYoZAwlM19fXuyl3HIkWIKulYe7VQQKmwmfAOhQVM__ux1tmX9clFDWVbt-rBqi6NKoHfTZYKhJmhqe3z7V3RbxerxEAZ1Wc6EhQo6pFhrzXJ8E-kaOYOXlmuh0ZQ-qTGuKZnLjn223u_X2gra51raycntvn12fmWdeyra-93ay6lllml9TX1xuNk2eNLnZyh3P9zuiqvTTet7pnxgRir48PEqo2bpBOCJrOpkTk_b4zQiobpK2q8L0yqk5f-5p_zy7kHaZ27ndm2LJuIYe_NOkcoSC6hxbF2dNGSpegadYlgEpD1xpe9rxy1TwjKa3rt_8sQaZgtnqK7KwoVQqkMlVtmNNAQzkP0ikrtDQmAqXjfgtOwIUU9DOKH-bSTHRH1AaZnmxnQXVKQlOfrVNqMxeX6m42VB8SHyGsB_zf3dk0U-qj_q2srIFDQOTEgdiDMlJGpAwP9NHRTAJhcPvzg6NkoZqjjqPKE2dVYXX1_LWzv9ARFIwzRVCdWclxCEzChC2jtB9bp4wJGN2NQRqLRCSoNAAiJiD6FEDRlpYQye4ZL93ndtuD17i_3jN1QAOku59MUa1MOBE52xhTc11Ptqri9fqoiCGK7bUKvbbvrZ3lqmZwNUK0cTJ98lpSanQziCz3ddn1cgeIXobtKi2UNldXNeK6FsYz3aDiuhaEPgDjLlWcOwkO_mgpr2tDxFWlxKjT8BPK3v4YbaWlawaSCh3Qcg_q8rkSq8xLjDAzQQuEtPu8CVYkcjpaUtUmhCC7JEuVVa2q59zXtaYKUg849jHOdgunvzKnYbKz9muqeqyutRQYFrKsvfbSr_fZrjBtQtWUUGDvNfjDfflarm4G7tf6ce0_fv38-eP18eNDKFD-83_8c8OXTY6ggWezQUC-O7sk5wJcVYO0-Rdo-ZnyDit-UiEUkOd9S02KryNyoNHz0V_PI0AMjAxy4ppac1j6Bk3u5VmFbqW-v97XXiRvKYDj94aqCj7WQrcKTalT3QYFTUNLZ4aazVcfEHQPD36WFZUtCoi4cr4lIlP7fgpVEz40AmBm1iT1IT3VesIg0v2-3zrziBI1mkKFhBgew9--rq6sKvg8SdnV49XiN3mG1Gyp7rUuTOu_YMprTofbZjVB417uxt9-_-PHdak--1faMM1FKMvHpNhrLxF2Px1bCqtwIjkDkqiShsB1RSU4lyMU0I_yPT_rphvm5VzPjvsh2YNZ-RSpTTOigIho6aqomblLCyQyoHSlzL9J5sf1qm4lshoqpBb6_gqlNo66pwikx742Pxzpese4Y7urnPyhr9A-OepX2WoCZldUGeBq8vQL5H3nix8pmREt0o2MWNvf50hLi2T1nTEgxe-URcc9bI0H3fAcNFKescFEf2QCljx1BkKZdbv5qfd0TWgGqvkl6Mpyo5kZNUtGEHFdu0XMXBod2VW6_NcfHy2yzCevEqdoFOU04maGTVJKbA1rspe7lCzfClnLofC1pbpbvl9PkBZfG8iWNl9SJajOzsq4O6RHvirG9-cXKdGdwP7Y9_v91__6BPS-7-p8QB0dKDlxN9kCtaEMkAqJUjRSQHLbIDkpQqpTnraf-5P2see_XO6kkio0Ux3dEpVuZqpQnkiqjWWUAwUCaRS0LR2ABYwtQqOq5gm6ZQapd2Vk6KAnZskp7JanLgWYGqjzfTE3QCvT1McDWJVROekUJdW9q_JE3mcgQjP7gygFEYfKv_78W4kqOfdbKOOA65DZx8b96e5__s8vv_b_4__5f_7nv__x7__9nx_X1rXWa01bQp22V56obCpg01R5GmZGVWXlkZ4HWhOICPfV1ZkhFKl6f35FhLrnOeta55z7fUjx5e_81v_Vv64ctdxPVHep64RY8wSMcad0n5MQPee2tbNyyhZxuiGuFpHoaqnM8LVF8DGKCVdt_vy1P_YmsdcWkeWs7Kwy06z69cdPCBW8s9731zknKu47R_I1rOeSloL7ms8OzbvSaNLP9u9aH_f9JlRQSh2TAEXWvgDsaysV8rT5f_z4MDXfS7r__K-_Xz9_xnnPFmWbN_S__utvW3759Y6ja1WVtMT9Xu4YFlPm31-frnOcQj_nVfQ3ThSQ-47KMLOh8QyUSUTur7faksGHR338-vX159-___bz9bogs8nOQvte5haTF6t4HtQtUGac8UXbWmrWUdUplZn9eu3ffvu5Nr_e731ZZ4J6Kmdm0RBRrus1L6qP1-v99VUR77__bmpE-FpDR1z7Ul8Zuf31-dcnW847pmIzui81jROT9de1Kk6HCJ_YnjwmU60uVYsTswtUpdrv_yFCdVVFR46OVlUrBx1I6cdJKeO1GEwOtbKGCPT0fPDgKDETmqnCkPK0MTB0_2nTVw5jXqaZPLGfyc10V3XBrCGjghqhxhzcu7ueJID07EcEXYEHfvfQkOURPoja05Wk2uy7B8UFfgfNqZE9ZePuhpSQJS3ZQq2qLoq0TlUuizAZ0b3UzBsww1WzAY2PACerzXzgp0Mfn8tVfd8B1mtFJnpseNqVUEWdrI6SUlFYVmaGmZ377a_rZOi2kp6croic-92jzDopUZOYnLt7nyR1KmgGq4qPHz8bafZcXaQb1oBUpFFcbdE_z__1b3_8Pq1NI7v6568fIknyYy10xdeNyh8_Xh-vNSeVvbVFrmvNkkcp03kY85-q3ne4WXMc1zTz7TrAeDNd-2F0jC1vmQtglPtOJaJKwIgarHK1TH7d3QSoqLnRGRYE-eSBm60ns8Y20bOZfBrbOR8zkZYyo8J6cmk9X0a4-UzBu4Lg-0SjVWmua20K5lHiam7wy6epkin6sGwJ8qlwdbstNf14vR4qRfdaW1V-__3nHx-vn79-E7ZQXe3Ha69HUYcGqurOlJEeqMznqiod1tU2mV3BIAgnCMHJIA04dkJ6wjE3cVBtPVYAnApClu3KmAe4_GvAppp5fCmk43yZrQc9Hk3F68frft_VQuF2exjtLXvbOfe6XNfIROVfKGGRwWji0Y5WbbMGBl1OCMH57Su1pKXFzUR6qT-udZGunAhMZA2iK1Enhv3W_WB7hUqHFVpAUypVqthzvGpTrQyFBQSQuXv_WK-SgsCMExPJalJMTTJkLuszJWhRs-xWU6LnE77W_vnzY5GuBmV1-nM3FhN0lD3HJpot0YecTaF0qfuA9QnWJAi7smXAWQAiwsSGb0tVg-HJaIvZoychMTfSf425p1icGfMXlHRWTThx5M0uPpa3GWsYdF5xcHZEpXRUZohqROewyybYNqQEUKpbEZOKpn7lOV01916RiT8naoY48d37m4td9BelhXYykLNhfkToVRWDipIehOJg7FSt0e9zWrqGhz3gPeDrvBuimE8aqiIjlDZioIF-A11UFKjSlRNWcTB72mh4nDbd6_rIzO1XZRBE9_Zrlm809kkdmitIhdMEta6lqiK13KSENm2rmW81Fc-peSnJijT1uM_aJlJdqMawgNgwN4idem6D1f2-837fXTlmL4TU6c4YvUXcB-iIGFvIQAnNzWjLPWteEb18N6XQ5HqyzvDK9gG7mQngvueVeV0LAiz74b9yUV1tHMmPMtZFRF1F4EvX5eyxyJl0To6gutGgCNSANl3nfdZecd_Ll9k6EaZqpnOvNLh02bMw5sfrx8mYdsr842ikrqiY5pu65-OKnSOFVHWc9GVSXdknQghRPScqKk509_0OGuh-__U58764DziMAP1__3_-X__4-O1_--__qSpJ-fzr8_PzLaQqqmTtRWhl-nLpzKwuqDt17lJSLZOLdve198-Pj3OH-bo_31kFkTjx9fnuRomczxuqWXVOUhUty_bnfapKyMga5VHnFOP7jjLTc584B0RHkohTPlczveK8194ZRcM5sS5TRd5nbJfNCaSpK6vkv_3jj-7-9bouuNqcojAXmZMJ_P-Z-rNf27btvA9rXyt6H3OutXZxKt6CFM1ChCgqkkOEkJJYQiAnBowAAZwgQGAECFy8xshD9JIA-Vfi_yN5C2LEgA3BsSnBEiVesSZvcc4u1ppzjN6KPLSxDvNycXHO3vusvdacY_be2vf9fjyHjSZ7qkTE_eWmKkcECDj3t7TN6dUSEtZXwH8xiQKFjGDmdB_b6PJj2z3jrJnj4eExK0wtY6mIqY1pa3lmjmnz8eHl-bl5nU-PD6K6fEU7gsq96P5y2Jj77eXMjRP3KFxZx5jIYrG1jnl5WOugqj4ir2MBpdP2232MkSubF9PdFV9tGcpMGmYeayg_Pj0wsPajV7lVcI91uCi3LANC2Sty7ZNscUMsRDOWzQsofvyjH_d-g7KIwUUAsckrHEkiUkkpc5iRii_vPMhx7KYKFKOzhYaIqMhKOe31IaBsCHh0qB_pS-c8np9FTjCDqSShT9eZgepupACiylUk2_sf9DaqY9Agyoh-ovaphbi_9JMa1mTNXu119AfQNiqDeiJHTNT4ksqSZoP25w1JMVGmNhS_iKmEm94jRdWo3fOPb8xoH2mYKaOjrvVKJa8oVPMO8_VAn8wc7k2EqDi_3Mwzj0kEWgejKpIIrCMrVBmEkz6eJaJR0Z2BPs4odamCwIwqQVcrWklmEdnGU2ZF41kiCgRKZWmwCYF7yO0n-EwQxT0qhbSGjFoVTkX8_VlSho6gEpNYzmdOMX0tNS3k2bcGFALQWktUKSrCoSwsrDzGFClV7YV7VipDlJtxoFwPJuHxeL0k59Rtu1h4btPcU0Ws6wSV14uZ6LaNMWybQ0WFcdnGnLrNGcu3aSo8TJlYVUXq-nhhAhH6FjVMRSAiHWQfpgSosgifQfAqFeZzbYMOeUIYfIIgQbAh7iGGM1iWRaCVqyhNFYmMSCKSgnBkaOdeq_bdCdEzrGYK8ZkzzlxRJzuMiEJVM916P85sU2WIskR4bwUuYxoRm1IUJQ212_1OBVauCAFHxhxmw5oBqjoylrKwYBsybLtcxtdfvdtEh_H9vj8-XLZhCvSJrbun1t8LEQZMRUm6axSZnbtbsc5rN1WnZrv0XB5dnyDjQof62svOfW4yMJ0oQ2y2rZVqQpVE4vsxdIQvU2MZ51UpS01E0f02OQ0-OcbgygGhSDbtX2Y2RKDDqpIhqGImMWTQMFVIj2cYfLXZej4wo5JBkaSiVKQiEKzDZ3Nyjc2E21wxNaJ8DwZzETPFSlbOJLDcafUgkStRVVl9TlXhpCwB9TeCuaoUKoIViep3pQaVmYoIBQnIbIAxLtM9qEnMKCahLDPd5lTlTcxIbCpJsr6Ct1upCzYTInhFUQiLL1eR7GnvWXmlqBKohx8eyro8GJQR_QLv8cokA3G4n5Z2FFiLEicTk5rIToAA-76GyL2l1BFgjpZ4REbks-9JdPhS1qxcnu16UgUAympMWm8_MiIXiXUeodZqnQ9eHfBUGZTnXZur7eoCBBWhAEESC-O-e1_hMutIimj-F5lyMfqjqAtinek3jIYyR3p4ZUQHrETU3RsS1mnDKdafu1NHZii0UIjsZsuQqapZqad-S0VgzJUuOpYvU-HzJ8unvb5SxFS5-TMmTEBGL_3Apw4GlaWqYM4sG2f8S_jVgg0SkUZGbjbTI_0EHPemvpTabHXs9-tmqnq_77LNqrpeFUQGfn6596hm3e--577f1znk62NBZUSuJjum2kYZZsogD9-uF2KYGVWgg_jGWaUQcJppEIo5k1SUlXWo6kUAGUNsLgWYp5koUxYE23ah8o4dADW27bgfY1iBQLCOgHCtvTX3qKoxBqhET6kEs_SbsZVPzFoRkQGUMNqEB6kT967CgNpUUfdFwqIS4aKWqMvcKlKYq3uFFQxayz0y3UUEAFX4WlHRmClR82OJMhPKj2Jaof_43_97f-_v_BYduF4fPj9_VJUP334ElUd9_Ph53_Pw2C6X7TKyThdox-VMWkECynzz_q0INbvJ9_Vy34mq0-o93djvq8qhGocXpQ4rov1YiMyqLndVRhxOOAUWc5iqVFGED5N9PwCmCFMj6oXt92EnZkZUWkNXRaiyEQ0QNtbKGJsOU5vj8WrD1EQ7y9WF-Na8JLiqhEuZBXJ43Pc9K4_bOjybbNtd-WIwoKLCUhmmW8C7ctm198pC-zrGYNHK7MFTm2pUtagiYi1_9-VbBTxizJkeYlZFqGThuem7t28IHFUisu-7d-ONWbjDubwfB4tktpCNe3X_8nKD6vPnT2zNWUahdGztL0cxVYhwROgYVZXJ1d8ydGWFRfBwvbx7-8ZM41iier_f13Hcb4dH3NZBIr5cIBEB4pZLqI1qDL-7bGo2WHh7eny4zgy_XicFlcBMw72ipszDnaJQbqZg_vjxWYd12MRYVMbydew7Q56fX8AIotvtBtW-WFakTcvDRagybGhllgeBwpPQ9smtTp0XC4vqNeMgP-coVCX29BWYGNIZpYygSCa8nnlBVRA6T8yiRFCRQmWjOyHlDoUSiAJc6D_8TLW1oEcyo8DLlzILc2u-QMSs4UkiReXlndGBSBJ1mKdH_5RJ_DryZwl3buSkoKvN1GUullgOEcrsxW7HOLS7oQ3ZoGrYKTOoOjuO1g6IGqM8V5vnuphwlhZABQ6v099OSQK0baCLf30Q67syiMFxJnTVvZi5GwwQySiGZKR2XIG5qFCpjKQy0yJSSOyrgWsQzobeM5toVbIKFyqyGX5VWcuLEB6yXdZawlDVOS0zbQyAqXmpcbDItilFDp2grCgG5dkYrTfbhaqQCcbTw6QsYUYFE0zlsull2pyzTTgM2uasTBv68HCpSGWWllsNbfA2M50b6SJVtTEgvG02xFiY153Fzt4SM2XObYpw7C9zzAaDZpWpEBoSwRVpplSoLBFGVwb17KBHJQgntJmRWYjsyq6qqlp6Nni5Th8obTpAHWMJ-f5wxagqZVZVrZJiFoUSc1-dGExsAoIOK0pKEqY2hma4jclEl3kBY85JkdPstYGtc9gX7x7fvX0wsAg93_frNqcZiMRARSZSVOd0v05kZ4-EmvN-Yn_q--7zidlsJ6OqsaiZlGd6FZVHDVUzEwVYY5UNA6CEBkL32bF6t8bEat5HOpHInKYmCiKm2i6DPMbUAi7ThgoR6yYPF5tTL5cLqhRCVaK8ta2iJLPD-qT6qhVoNllGF_E70KXKrGBwZfJpPS9pKwc0IkHdbIQK97Y93Mc22lZu1hVopSoRbaBQQ44gfITn2dPh_iKm2cocChs9p5U5L0WZnpGpEGJkkQ7r21OPM0SFjUW5lj88Pjy9uzCYztVqw87aASpsjGIoE4qgyCQW98gI1pGUky9RWVUCDSK0VqbIZCRVgqJCRCI8CIkghpkQqpeiLeDNKGZJ977l3Y9j6PR0Yo4TVVY2Z29R2CSJmNjMum4bTCBS1Yw6DmcWZKZTZK6jd0dABBMnkrgHZkfj0MNDWdo_0GzZiDLly7DBRmKUFc0JJTo8UXRERINZ62x-ZZGCM1J65StSlJFLlI_jULPKGDZ72s0EZTZB05CEuLJaUXys1dX2jGRVKEfkWkGVwqDKBgyAabA4cF-7ihWqqxckjWpkImzb1uHpQomItzSh7WhAny-HWUWYCRMJYGZtz-2mbM8sTFQIlDmHVQaqxLplQhG1lt9fXrbtQoQMQGTtC8LkeX9Ze2aiKoKZG0ax1hJlXx7ZNy1S7fQXnclRgNpj3yB80NyMkgDYNo99zWFUVUH9-hRmHmpmRDy2q5rJtjHDxmCR1vltc5qqt3PdY3u4EkJgJ0-jqSQdSqQyvbCwMqto9GVDJKpZHRDhomxLt5nFWuigrCiBRc3GXJ5jzp4sDjUqErHumNKJ7eBwF9XOcEdVhDPgHgCIy6Z1oGDtnig__MwphTcgyKYE0R7jf_0f_c_f4d3zc9llVPi-9g8fPz7f7-Hx8vk25tgmb5eNqtbyrGzdRBHaVScQ3_3d-7cUMeasqszyffUh-TjctuHuL8-3dSwwbre7DNmPmPNyu90qas4REV5pY6yjCb8S3y84iD0WijJKWCJ97ccR2YH749iXt5Ojisg9H99cieh-3zOqiMQMUIBY2MbGSpc5Lpc5p2ymInV56FUO9fK0jdG-kohN5xF-O_ZKOu47GwlzRkkHmEXEtGeOEAHrse4RnkGVaSrEfLibjsr44t2bFvaJDTMRZlV-eNyO-07ginzz9k1EzG0ex-HuLJjb5eXl01ff_IDBnd9mdKYE-34A2D_fqVBMYGUgPLm4D4q9oe3ZQ7g3IKylHG09b2_63DbPODwPD8IZz84MNdvmI5BPj09qGh6VVSjWcd_3PqhEFp3izc66lQhTK4a8zJT7ACgqIk8PFzNVE2FrXQALYgURIYMYaz-2yzxRbkwKLsK6rYxUkfmwrWMZizCbCVUQw9c-zNKDiLsxF8eqpKZuZIaASMSdOjUtgrOQU_BwUKqMyp5hl8jTlz2oO4n5OAtBRIBKL4sri9B93CRUD6zBVG37-r7r0zv9TBA1sKktAYSzuaBikicE8Hv4Dknn--lk52QRcUahxb3V7skWPXK2zFzQXd7XtihVpqgRUTkBBSJUMcu6L6hVeiujRaTC-z2TK1X4VIVxiWilV6epTzhJVUVV3zGoDxJVAeKozFMOWvWaMKYqVi0UhJMIwhDJzPaW95Y2UaJKkXJ2MdDOHSII6_IUtqwgT9aREVQBcBSFU1vS4_BhWuGVSYKSRFRmqIrMkUwMFhXOErCOIdtWVO1driwmGqNnNYsZQ0ZEOcVlG-H1cJky2Mwy8vPteZuKyCqfZsPmNo2Z5za2bZjJHCZMQmJqqiJgqlJty5WZad-fOlrKhIigqmE2hzB4qIpuSnKOgQlqaqaUpTo73NFdau6ASn-HubdS6E-4_sgDqIoEVM1jZhbmk8SYxUPOsqn2ZxZ1oR_Ry8mm7ZeyJiVYEuVdCwUoU9H9JAwbVEhPVu6P2zE3AtfJaOF1HNpFCdQYIzNUpPsSKqLMKni8zutmP_zxl2-3DVGJWu5fvH-6jJEU_QXTK039TKV3pR7I04vcRXxW7kEX9aWryT3tMmtSF4hs09vzTiAVAUgNaBMqqIrYhLRD1ZRZ7iXCXplVapKoFgP1nVe5gzpMRZeLXbY5zWyM7WKXaZRFVCqqrf-sk-sqIsyQrjAI-kWrJlynnYAA7RILs1DrLPD91982cRZhIVEeNqLKs4ZIUY1pR-RZzimKTGapKlUmAldDJqmaRUeSnWWXzmH3E49UtCMbLfppqOawwSAWPFyv-74LC1VNM2ZWxuWyGbMRPz09sGpGrXUSms20i9giHCv6gdcH5CBEOwGJIotIjlh3uhmNlTspR1VHY_1VfyWkka6sEBBlK1N6-RUrqR90xK8Di8rTuMJJlJUq2pph9xhm-_IVLpAhFhWVlECs6Kl1VspQEQITcUWwjNaQncS7IBxrH7plZCNAM-K0yQog6kQZ9Tg2Vfq__-f_-W_9nb8tkEo63M-BC05H-HIHQ0TakZIRJxYQ5z_wrMo6dQZAZqowgc9-MRMJfAWhIiIqqXocE81zy-paY2Qu60oG0dUeisOzQ6KlYmBSU4awYC1vjkNV3u_72o8OKhDh-X7UIhFp6ZJQmZmZZGEwm1lSAmzcKVPKir569ulDTSOciqB67Gs0ZMydGdu2VdWc03NttgU5oaU7dA-fwyqTmCOpKIZZZoiIsESkDMmiCojKyetmFhuqymCz0Y4VVTs8GSwmrQPXzgwJm2l7i23OaaOIZJqpcCaYRU0AZs6T3NpYuyLmhzlbQaLDqsqGUSWbeS7lBnakqJFAxbJvepGnXqheO1dRapZFyagiViaKMWZGqAgILJKF05uZBUYv96K5VpUQiQYGtlyIsjK7ne_uAESNetrIpysxM4SRpr_1O7_-S0_v4-4Pj5Myv_vu8_N9_-7nH0TtWIdMAzTwWmpTieXuZcLEUJKnx4df_s0fvP_y3ct3n57ePX58_nzcj88fPogJWLLI3U3GvnYmHttspD8z2uTaYWA1WccKT_cF9LkoRcdxHCrIynCfY2blOksy5RHMUhnjclnHMac1H83MmqxEVWNaRYiJTWMqIe5qypx2vQwFbyI2hinPzZjZd4qozKp0JngWC1XWft_v9zu4mGVFdUyrmRwiwlUyRlTdXl4iDvJaHkRMLKxiepbrWHRuGzGPbcY6GJi2UadWK8YYIMw53WNs29oPgMFEwm8eHyrx3afPqiM8MnI_lpgc950Zx_1oo9a04RFq7B5V5CsIFFFVtB97p8L6CNHPCeIC-FhH91rv973fqq-1Vln7PkzMZI5xvVyqMqru91sWrcOja-vhCvbl-1o2ZNjMLKLsS_W8TDWlTGX2476NOXXu952FpOj-vDOQh7eXN6OuD9tlzueXly7OHrdbNehteRX5Om4vu5lFdoHEiSSol_ZUXdM1OYlVlajWhBExWE4GprIyhKjCHcJQzgoRZZRcvv5RVvXYrw2sYJRniVQlMxdzVB_COp2Bk8shPaHr8xQ3mg1UzFyV4PNURK8Z_55V9wrulf3XEpv-xOTK6BouUZ67hT4Edo5HQHQ-Uttf3rW7rhJwkwEAVjBRc4rTFyt6b9d_4VxHj4IadVx1lj-bTBSRcuJ96tQUFcDZ942mzrFwpJMIVQpa0EDNKKDO0xWd-jDiytJeyRWBR-_7--bDr_wZOnmMLJCiVOb0nGYRrmrEWUc03YOqx6g905I-9dQ9Ms61qYhkF6eIbWxz22DMHcn1g5mHzS4dirEN-7T_3GBfPD4GagjrUGSaaSzfTDjyehlfvHtYyxn1g19-T40REB2zXcIQ5m3b1ASgTjQyoM3TFmk6hLAMUxEdymOoCWtbxk7vo1D1Mr1xGi2WEFYB0dE1qOz7WCusuxAOVpznUaKpSs2QA4lwN-h6cSTMWQTi9DzCVccrSoTEMIdVZZ3FgCS0VqmmaUYW15jGJMxCSja0j9fpYeOkY3R8gpIqY8wBkLTWgchE5rYx8PBwVakxdA4Zg99eH9-_exqiLXh48_RoOs4wTzf_u9sockJqwWBexy5ir9ECYobivDIPlcxUiAzZVNHBuAhhlkJUHe5DVESZSEBANTW4iPKAqZ4lASYWoY7wVmkjdb1TeKSm3dt62DZjHqrDxAxTFURzbNYWmcaB9LZXtMeScq6OT_L-eSondKG5S7ooMtUqEiaqEhHw2SdsZ5CyaINEGNxWh6w2XApRX7eaCE9VHY10P4y1-IyZZ-YZZyYC1cO4sLQ9Ce0xzUyKGtOQ1esUIjYVVWGGqtiUp8dHZnp6etiuFwjSoyhFutF-elIassQqQG8XQyDHOtqxQg3tAie5lWkai_Xirvc8KJ7ntCHA0gmuJKootX7Jl4i0EIDbi0fNRivq62J1ifz1TcOns5MZXADoWKvrQJklRKOZAZ1cZySdukPG-U2uxppFgXGWquuExlPWqsyiFGbCVP2Tf_Wn_-qf_QHreHr3TsdGIE8fc66IYy0iZKSJkLAf0RJA9zgT2WBipkgWURYqruyh2-kiZciKjCQV5Okq1uruBFGhho6irEwm6j8D0EyoimcMsWFGTEwQsBAyTyzltC0yqsjMWuNN4UckG4-hrKzN0ja1aWBe-Z3JJbMYiNWmIYnwaSbMKDqfD6CIOPqLLlTVZXvYjzsINuc6fBsWkQNFzMtTWAs8VIKifdsexKgIzwIx9vtRwJzTzlFPFcAqY7vMeUEmE0RgY845wKQmOrW5XmKDkLoZtRoZPObctqsMuczRMD1liClYsuJymYWT13QiEKIAjRWqmu5ju2Ssy9y8QZ8eImCThrcy1TCl0_8AbbFjULJQs_ahAM85QdFNDpaW3HNE9ofaqXKpNNlaBySimV5ZvrxRDVmhc7TWHaI93fCIZGQUKMEVR1bSw7u318vj7_7u35o0x5Cv323L49PLx29_8d3LirUfbQVNYFx7XuvMTGDPg6G58Bt_81e--fqL9Xx_vM4D-Nlf_GzfY3mx8sr6_PklMqsSVGajnzzXhweoLr9HJNvwtagqKEVs7cc6FnmKaVc5m0vWA5DwFQEREGV6ZlDrjNoP_-bN03Hf-4JzvVwKWUEAqykhc6WoqCkTZ6w375_q8IuNNw-ThadoBg0zqgqPbUgSB2WiMvI4VkQtDyrydvh5EirdWWWInPhp0HHb5USklAx5ZbuBgW3btjFVhAWejeXJMRu8FnOOy2axFoHGHAUsX3O73F-ef_iDHyqDUMdthwBUrHLdHj5_fkFVVHgEUVGQ2lgr-vpHgPtKz3DPqsjIiKJiwXEsVSXQcSxQzW273XYmSWQeKaJdIg3Pqhoqnz7c7Drn0COiku63vSKl35JZIoj7waqnoLokKcU0jmw9aM_E7TIaTff26doRR1TtHgwqgahUkYqq6rHclz9sjy-3e6Rn1tiux7G329t9mfKZ6gH5inRUFlAQZNfnok-x1ViE5X3KlcrzxhjhVSSsRVFIJskIZYg9fXWiMFDfS5bq-5M1ZXme4UYA3S3s6FglCBBuKD1lCTFlVCQB-cpkbPSYiKLZ0NVD8_Ps3jlXOt1C2VyFdsT3ZJ07oU8kaEQjQIwsMAm4PNEM9i4YtkYgvT90PQOVldnwIjoZnCVnWZiL8oSNMpJSmAQSKyHdYaKKAGtfctAv8l5XNAU1X2ErfH7cdtCNBEwQVhCqeat15pmYiCr6CLKOQ8y60l5HsnDjO_u3E_fJss6sM1VBirLDyo3cZioKoIII7j6ub3wtFa6o6-VKoJNKGWE2kdU4P6LqjX8EX3S4JHkckW8u49iP4wgTMhVUbZehzLFiDrte9DKHMc-pm-qc27bNOQYDPfsXYVEMEzmHxmCwDR08mIuS5lQRZbC2pVtYzXqDjEbp0xkxZWMCV1ZjHCKKCW02IqnTCPbql2DI2RokmCqdjFpqnCtVTdUMYuZtTFZi5goSkSDSKf1HZBW_9srQi6xzSa5cEGUTi8qKmkPGbNQNtXwERLGWewA0TFGFrOtlzt4GKkPQ_YfLHNfL_PLt23dvHqYoA3MMURPWyhzGdF48uXp7Vl3YjsrunlK0Z5ig2nmlEuOpCnAJAXL-RcCQk_ZIkMjqb7MwWi3Wey9jNcA6C4oqQkUxVcvCiAhHMjM4pUMmzHNYHK4qhFLTMdhMsoKZh0hlmelUll7CAGJCOO9pZjDRNib20J2IGp3PLQZvMVHHnLqrHdnj7fDQEyKcvbEVG3UGBREe7SNkcJc3mgmmMoJyz11lZIGWCzUNKhnad0bRBphwRn-IgIuGDu3yRmX_V2yMuW3MMoZx6-LAlafIczYfnaqXSn1NPZn6Z6JeMqMDKtWYfzgKKHh5cZ6LHZGM6k1EolhnoaKSpXeQrwVYgjCzyPITB8eKqN6rlkKz8vCDSYS0CWlqBkJWDB2rPIu4CELpBcGRISIKpkyvzMgmR5Z3VytsmLtz9fIz-ie_wsMzY0GYTYgkImzI_X7_Vz_509_87d9Kkv1OFJRHgAp59BaFCZGFBFW5e2WpqeeCiCr7ihPURv0HMxWiDfPZ-ctz49oRfFHuormo4dz3t4-yqX9pOtskKwxmjkxRLSIV7iOvRxKViSg03IlKlOc0YklKIZ5mtHtmjcuwIR1eMr5ylSg3JVpMhg1iRhGIgkpb7JjunkLIonAXluWx3Ft5Rl1Y8WopchWSz4GYCJtYUgOH2VRgcppPTPKIKRJEy7NvOhQQKlNZ99220cvsMWZkzO3SqP3uyl_tsrK4eMwprMEsQ8eYJ9w3S_tDVbQKGQmWzj7FyrGNRrOKSLf9xrAs7-EXs0QV2BjU2nJIb5S6dx5MzML5WiY8MtQGU_XYLh2sPMboz2hRqSRmrSaMdNYoYs5LZlRRr73CXUdTcamI1u6iRtCipSCqRRVyefh3_-E_vI7Lm68fpm1fvX3zcr-_edgervbnP_35H__pX33Yl0eIUHkUWSaZWnlu25DTsF6X63a5bL_-qz-8bPPYj08vLy8vx-HlkWoNZLPLw9hvNzUB8_XhkZgzEsJVudwpK9Zuw5hqHUu2y3F_UQabRMZxP9RMTNzDNo1jR9L9vpNQujNzZTZHcXvYPBIEAq0V_TQWEIusWCftgXgOHRcTVb_Fm7ePRHG5bNfL0DbxMo7GAQMkfF9rzC3C06NAi6rvxiR6di3vi6fVSY8RUd7vezEt6pYfmamoFgWRQMhUTK2EKumEQTF6TphVl7kxE7O06qtLVjLki6_eCzMR3w4XNaa674uYPdax9q4EP14emBFRnmvOzdcRVOlZQIS3dcrd1-Fr7eNyUZZ8ZQgqi0cm8n7f1TQWQcRMPJbZONbaI2UKFdzpdttZdK2QwSxS1CkayqhX4AzGGBGd46ehAwIQJ4oLBrzc740DEpMiKqG1R2Nj1BSR5ZHhTCLKz5_vDERQZOkmFOgzmxAqs4L6lIsiAEm5PAh07DsxQYjBanpat9q3S-THLjIigpWjGzIkfDYiUuzNV2B5fX--tqFOFCARVeuIMqKH3B6Fth5VnjX4RnmzVLyCCIHM8yiT5yKgiflOPcum7A_yHgTSGSGtNgxTFjETONEpo55iV6MnKYLAmdVw0dPVBcrwVpe9lo2o0Snof4WuQqN5o9X5JVWKYGYBF6Q8-DVP0h_SOMWCSSTpDtGqYrH-rxOIxYqiKqsovT9X-poA7loCierwcAKLalUICzUVS5SqVAygMS7hB7O456lbb3pHFoGUqYCVaWNQFascy0UtqXpvo2ascuz3x4fHijWvjwza5gYDRExHhReoyWvtYxfgYY6kQpxuhKyKiBVLREztaduYIcJvHi4fn5-fHq_CePN0wYp5mdsYKiYqyhij07Moqu2yEbRHte3BbPq-qKgZQ0S0KXMt9y4qEkYDi5i7aFReYKEioFj4LCkB0QgVBgERiUZXgCCcWcys3O0x2oaBYQwRFhAzj2FESUFVKcpm0vrunor2cYqYtqFnQ1-IGQI0_8qGAmTCjbgBIMxqQklreVboMKp8vLyLvKvwtm3CGHOYiCojfRvjsunT9fLluzcP182GML0ubnC-Q4Q5G59LVdn_mqtIz7sI82toqZdsHVWvvk73Heg13qKi3A8CcDsKzU5vi3TYRrmSRE9B0DDxPtAd2XcrkTa1k6kKY84JxnYZzMwMMxNB-Or9CINaLxCRGWmD-wzBLc88xZZCdT57pJ9RRABMTyFDF_89g06NMzHRGcthNHS1TVtZWVXu7mulV_9SFWVBUBJBhaugzAwwGwuEIHSWc0SZFUUpxrlKRU8FhNBZW4-CMDGyartMrjJToK6P2zBjhrES5TARUzNBkSTYjJiEuU48QXXaAXXmFlamgD1bQV2DtuC1V1MuoKKxXIQDRUwsbZjOMWas8-pORMRJWcoSFQxk9o_3xOl0G6-qvWaoiu5gxlpDtJKqaHlL9ChWdD1zhZ8_JiCoUGjtNlhUUEXHiqIcYpkZ7qKSVauiqOz1xrlWgMGRb9_ov_nJX37x9Zd_4_d--9PHeP_N23fvrizIwvJID4JVFZSjsojE9H5fIhL9mQNUP_eZmat9NE1qY_BJGqQzs0qgMxvO3B73RAnLkAGROFxUi9J0ZhwghqDQmBSppOWZWREea2WlMIaOqGRmB7brQ3iMofvLPoapydjGFFPlfmkZg7IgJGJF3Ju0YkB4LVeVoNz3w7QRKryqPHJsl6hYyz3r5WXvMA9Ugsr3OHF2Se0sVybmDq7SOlZGXK5bFqlYfwLLkLGNbc7O4FXQfHxQZpsKcOVi0bVcGCwwHQSSqSpqQ1REmHQOgJbvZqrKWSdCkUUIqExVBnGhVAXCRSXKqFK1Dh8OG1xoSodYL2EpM_rpne69mIuKDjdSkaoFgoWrTisYm5iJitnokmX3D7XjeR12c1-NpWJt3QpO8VyUgCDqx33MrdJJgBWFZUT_4f_uf_OP_v7vvX-8kODlvifjOq_3_cXv--Uyfvrt8x_92U9tGptul0FJb9-_ffv--vHTC6OgsskoMAyA_IN_8G_n8x6RJSwi3373-dsPH20as-zHftyPaXzcdwazDSYSoSZ6rMO5Sofdn2-dqSbmte65PDxYdblT0bZt-31nsKn6iljZAF-GQCj2JcK-8n7sOgaYby-3MbUbLFk0VKmjnqA551Bl8BCb21SF3_ZtG2_ePIJomvUbx33p0LW8axVrrfuxs0gLpIvAqgwI8dyGCptZVVJXjzJsWBDZNBXpzxpmy4jtsqmKDd3GXOvY5tj3Y7vO_eUgEKrGGLGWsIxpt_3-8PjYn6Q__uGPPTwrWHktzyL3Nef1ZX9ZvnzVuFzW7vf74VX9qeERvvyc0WYym3uAea0joqiqo42dWqwkHePwlQURjUoduvZglTjCgypDVZPzFz_97s2b6zrW2BrvyDpw3706RhgJlQKi7SVUY5sE8jhMdZuzqOaYauqRT4-PvlzHqKIxTCFjjogOvFTjTPa12mdDqKwk1Ny247izyvIVyx-vb-77zsyqvJZ3kaey8fcUK5gl3EWIm9PdhtCW76BiVSPJgKyWUFHKeP9LnbEhaSufUSarnrYVSDaV67UD3vPV5BYhc-PregD_avak1zoBn3F_cGfM-q0PcOtyq6GeFazWJzw6k9fUgxOGcXt3e5HWqlcUE4ER1EjQ138twkX9ydH8QdWNzkOvULXzyE46ae8z2ktahZ7pCNcrjbQLzkVJWW2lAbeCzDIiC71baYHlGUlnrUoR43NmmSp9XC1hTqLmERE4z7JFgqiYRDXjgMhrg1iyQsTcHSKNp29LA1G5-3JXs7UvHhblY9sqAoxhprpBaT-WbSPK-7es51uneFvqrgIRoHKbl9uxi7JHsvKb-ebl_nK59PWGrhd5eHgQFYC2bXRA52J2ebhet4uNwe1pBJ2VWTlx0iynjahpuwwoS79wWKWRXQQBnQOezOxKZ1-cmm7bY9TXOkbR-XMqnK8wQiWAAqlZ0evWpMdvwgwIREUjU1gJYIGOrnafB2uFtJdAz70Stm0ehyurV1xsCuVgQRvKqIio2WkCEWWRLiOWUwBKVWajaAmzmgqfFEgV1PI5x8NlXOd4fLq-e3qQwhjKZ9OQTpBHX4lBzZebw7KitaAiHK2RZwBkdsoxWljRqE3p7TyRijYYofpjXCDAOtxEQcWifeLXzuFLM5ekoi_GnFnEdBkjqkikWkCOE0nUOlXhdkXy9TqnGM6fvvZdxVqTCQZYOtPfAmMmBnuENkmTmZV7Ydxos6JUk1zeqoKMBNNlzMgaNjoL5I30BXJ5Uh376nEAWBMJ1kBmJDOIIpsEBvb2Q6lEJZsp5L72y-XBIyro2O9JlV6sPMRUsZkScHiIiJl2bGZuQ0BiBkKETxv9tVelsYpIX2yEiUCeBbBX8DlDRRU6q1694AO8VjVSsrAyshJ9nWNBoSJNJal6Vtf4l9avMZCUpqNeX5bfw-BEOCnlhCmgkE6ZSFMVQlYmkou9v0XZk11SaHEySJhv96UmIhDRlbUiuiOens0l6jenr8gMQKMyonr7ERnH7fjxN-__4i8_3hg_-dd_8f_8f_y3_-V__d_9F__VP__9n3z7584Pv_R0oVHRG4isokgQQ8EinCsY4pHCraBFU5Kyvkcugk3Ck4jCY86LV7BoZPbWC-fTgVcsZj03S5CVLiysGqj0KhRlZpYNPZYPFQbWnllIpKqiQ_zIYQbB9eGhV-LCpx2FO7V6UpH6idPjCKoEgYRRK1SNlSNWZvWzNEFg8nQ_ssWOlURyClyVpSLmMCo6do-s_iDK6Giu90hi5aLKFauqTAYxjTm6fd7KEDCIEgwddj4bjYc2w1SPWNt26SUVtNmFXZvnXuAL2PfUKd3HVbP-Oka7uriLlR0YZjkTz5YeUMa54-0EuFRVOelgEY0kSvLKwxcZTLasUhY17fhw50MIp7Od0ZJg9ojRiqXmzFAX2jgzq6WPU0HY92U2oojomMKZt8fB_5d_8p-93663-_FXHz58eP7kVT0NpXRhkcv89rvPrNi2y7v3b79-__6rL95vlxFZDI6i--f7Ht7UyH3fH66XN3Nz0B_9yU8_fHj5_Pl5Xja7zuvD5Xje1_0W7jZU2HzFdrns6_AVHz8_A1LhK93XOnZnNRGJ_U4FMRbTOS9MdOw7q1yuW6SnJ4NauEKEyFwrVSFmvuLEv1WYjqi633ebo_HoItyn_6FWlZE-pmjf07jePT0BpB0QyCzg2A8ROQnvoDFGHG6qDWUGIyJjBSknigiiqir9gcUiUrruaxvMgIxhw-bYmmU3LxuDmtouImOYMK-1hg0RDg9mUVNm9vBEPlwfHq_z8-eXrNJpvrzZDy8vL8QdQ9MGnmaHIjNEtGWCarrf73NYZibRcew9o1_HUt3cDwDHfXd3Nk3yz593GbrunlwAua8kWvcXQvFUIt7UKvN2Px4er0m4Xq5jaK0MLxXpsMN5ziYWE4YUlQhPHedpRjRXcmXEcXl4OlZQ5joOU_v06RaxIv04fE5T0ywi0fCMfUE4PHow2Dt7Xxm1COgqsKhmlfsaY3R6roFLaFbyK5sB0uq91XfyxvdVeUT2nVrs7TdVBOUOq3SLrjvXGdXhjM65vE5nTkYKmJtscIb2zg-coKJGU0Oazdf2r2IBMqtee1rUsxPtL0o6C9Sd4qpX1Mfs8xF3XBXUosEC8uwlkbB0qqgx_H3wqOyekPdANNbRrgfqMhHLK9qHSPW8d7xydaiImDIjq-Q0pqKNAeVJjKjuPJwRjZ5nCHcrgO01sNh3Uyqo2Mog6gNngSnW4nY7F_vKqlDlanNqp6KYMx1VKIrq-pBWJYvU8jEsK2xoUTGb7_vcrOUGukl4zstQgMJJsD_vqnIuVbpgcSzpID7Sva1HVYSb34Ww7_vjw8N-HO_ePD4-jMoSpus2h_Gbhy0jH988qoiYCUjOkTu3z63aRUtgnLP_vhOeYbIkomTBK3M322rcpBcQ0E3fnjxly1-ritqeSMLMsCHna4SKmJOSiuSsETPOtRB3lhdMNrW5qwxOd1TZkI7nNp2IqpSlyodoRbHwMFGTy8Omzd8cOoaCap4eT_S1oRusXn1iL1M2UapC1sPDwzDemu2TNVRU-eE6rtv25mF7fLwO7Wk1hEhMe6KvzK-TfjkNd9x5KpzrlA7Tcyfv2oqcvUtpG1GvAJKKlen7m21VVq2IiBqDUbWNVpVzEXVDW1VUuaKYkEjW1uFpKxq6NLt8jaGATDubk9ftElGbGevZLdZG7PArRun8fhGA2Sz0V9-niVEl48Qv9hsXzL6cXkfR3XURFdV-PFTXRVZ6eOzHCk9mzZ6XVIcNKiOFIMJU6Ltfi_hEJDt3TJzdNDlP28UiY6iZXsdQhokIawo8YtsmzmkBN8GoIzjDlCtNlQgiqqrdze2g4RFnhNE9CRxEHkks7ZOic2PYR8HZJMREMb_WvgWgsv5bN8W4VenZYW8MMc8SpmjdKp8PxqYlrIpNdVVd2G6RSSUQIekGYVCooe_QDC40vSd0bETlR0jXCuWML1dlNwy6H0BMBYqi5Uf_424tHB4F9qQvnx6_ftQ___Pv7gq17cOHz28fVTM-_fzDd3_27T__b_74__Pf_fd_-PHbH_7aG9Vts0153G4vTGgNQvH38rdkxopYfla1KE_Z7arsByyBoqiDWM1aqSAwCdAixUar9SGCu72m2ph_NRvDsoocmWkySFDClcSQbQw0MCLKzKgo3FV67kUCjghvZwTTivBIVqkWfbSajVpQyJUEli4yMWmhhYM1h_V6KpDHOjrm6rHUxnG_sTArcd-9esWdacbhMW0rIeISlX5GhUdUsmgn_olSlbKyGBlFzBXJ6A0Y8gy9clKRSlSJAIWKMFNmiRWdvGflTIgp5_ke7aI1SAoJ8DbmEYeoEXL3BcGJKgNNs-VV4IoU5azyBmOAI9cYikJWoB9rIgCZ6XXbMktMTzqWKHWhQQT9dqvqZW9_LrNKZZpqZFIRBCJc4UyRlL6__N_-yf8J9-O-H571F99--Pbjy3HsqmNOGzb-9M9_-nCdH767EfiyXQTy5rpJUXiEh24WK-_LP337C5nm4ZX1b_-d36FVfLF93_fKuc2xjeeXHYRt8oe_-k42XUfNy8Yix1okfByRx8LyyLztR1UVBYscL8-dmuLeP1N_HpJHNg4oM1oFT0UQvb889-l8P44iZISq-r7U5DTAU6rKsK0iRERFKhOo2O86BqTmxRj0cL0wk_sadh4K-0rfHZVzhioMARNDeT8iK20zG1bcnAYiVHh45DAzJhuiap6ZBM_YLoOFQYmsOYwJKoOqrttlP3YIJ-Ww0TNCHbMyVMd2GT96_8X92D99_jzmXIdDZC0n0LH8er1E5b4vfp24ZnmdfpjICJvWVeksenm5RcS6H8RKVMfa1ex-38G4vyxtjNI9Ht9c7p9vGREeHhV7ghAR98N9VWaWUhFi5dPjhZIoa-1LFZQ5zZLgkcQlw-YwNWGi9Hq8XH2ttWoM7Wt2MN1vuw6dU4_92K6bL5-TlUt1omioLK-1L5hQ1ZiPx7EzYQ5lEff1-eNnMGU46ywmM133o4k1IlJBpzBTLc74ZC9DOthz5vuZKYnS3cyAKnext9-w4Rw9M9IXiCECkOjI9D7RNVaCCt2-bU82NbOcUZUJbg0NQOkO4cyu9BZlckGoez8N3Dg_6-i0CbYHiiu7PctonhCCWasAadRH68ZPQGi7Q07XAxEJKkIYFXS2ME52GIEtMztq0iniImRRZklH9BjoYUOXFppO9upV9ojzNc_VIuzXKTQosyUXTU7iIqdk1Uh0sLjxmujIeHF5dCiHKFnYI3SMzgkQJFYIwBQtZj8bkygWyfQiCl9zTN8Xj0HdEq4UY9GeR9GKYFUUS0FUfTmak6nMvVfxMBEWmWPc9x3M1XX1tdy9h8HM8ngZufYkYqIhEn609O_tu8cx7HK9VHplqOL8VlBRT8Ug3Yroi8xfn-0aCXTystBtEI9oPo-dYgKh0w9XRMjws-Z6Jr24Q2K97yFCLO8PP4BMtQjCp49Z-ziO9r4RE5n0ap1UWBnTrNcIKgqmy2ZJ1cklMzZVFG3blNmCSkalCVOWic7NlCU85jZWJDN1eJoBUbmMCyiul-tmsyg5Y0yZKu_fPkitH3z9xRApQv_6Xrx11uX1os2Es8DATEQUUVmp5-3o9HX0_LJ5pv0M7_Znw_2IqOVN1sd6lmMdItjMKlvezWfVPcmaBiA9P6VVOZUpSEFFJYRNtfP8YKCKiabqHINBNixB1pirOtGEInRlbWttZamxMRNlLw36jlBn6YJwMj156nkt165wiJjyZY7w7KFDJ8R8Hb0SjCgwebiKdrtGBNooRirONgMis5oRh0ZvdLeVWV_jfczai-CGX122C2WxiJePKRykysk0VYyZQGNoA6na_qHGqlJnPLMINLAd5Qwiz2JqcJma5fkYRGUqmVdGee-eqmKKbWR5jgBOq1cjaeW8RJ1T0cpc6H1pUfOWM6rKVNGPDeKiEmanBErZ-lkFxr4ONUOSR6DTcum9B83IIkQDk6o8875W1zNav4XCWoep-XIIhVe2KIyIRNqqlY6K45e-mf_iD__y437c-EEuj_vzTgaMR5Ehax8ln3_--Z_-03_93_z-H_z-n_3lD379m7_5zReiGkH7ukG1GdDv376pLPdKVDtnVKQqj30BXFx-d-1VGAMVoppRvaXy1eRMrDxMLZGZmb5MLA63MdyTVVCSVUCJ2lHRA2c5C_ElYCr48spKCj39EefKsdVmMpSo3BMsAjIdUcGsUdUV467s9-jHzDYIIMsPAnsci1otS8PMmNNzu46-z0OYogEW5Hso-DhaVde9-n51kBBHLFVjNrORlCj0Q2Czx-ZE7y_L5qjD2TQLmWlmDegrBkUhohcGqBaLcgIylEWiyHpvoGiOI1WxsQiGzapgYbOZqIiwYU3cF5GklGFNWBdGAc59ESpjMbELbUFnbpCKVAcLillt9JC5l702RzTpK7LHbZFnbo2AOLzlNnwOnSTSmUOEpuL_-k_-M1mZFa7x0w_ffXx5OW47mf3Gr_745999K1mfn_evvnkb1Y8RmUPN9PPz86fPL2yy35cnCet2fTuHjGE__e6nf_s3f2Mdx57-8XY7lu-3PTPWvj5-_Cxq2zbG5SIqqtxrVZhEOk6oW26Xcft8Y6J1fxlj7M-Hbvb2_ds2OrX387gdOmx_uYEojvDKZk3GCgIyQ1SSUoCKxawZznYa6EQts2yM6zaore_MNnSbp9KOsh4vU1WYqMn9vbClpOULwpUZ7mrK4MzSdqqDhg1ph07VnIbzU13EYJuNMZenu8852gA15xb7MXX0o76qQ7wniRjMSdVVMdHTpf31F-_g9d3Hz1StwamoIKrINLF5GR4O1H6sLALwcH1a6zCVNqZXpjD2-_Fyv7uv_lw4bveiaDvE8uXHMab2Amnd3YZkpPuhKqd6LUNGYyhoP3b3glfzOCqTVbbLYAaCxnVscx6RHRuaNrpMvI4ASAAx8bWKKYF19_Slohc1mdvtOB4frmDOQEXB5H6_dwCyt5a3-3M1OsCTp65jjW0SkqHH_WCWtTsKwhKVaiY2li-bpptmlnCvExlFOkZm-UpWAVVmimiuaLq26NNXTdtst0vvMatorQMEPY_SVZG9-qXKPtFlJReY2ygJEq5KFFWkmBEVCzICkSIGNCb0XCIXKMLPuHL1i4PjtcNcRdLbbbxGm78vHncLjApE2qrLTDrbyuclB-j8QD9ugkU8ss3kaIgF8553VVXhXu1lRnmxcrXCi5XZwle7Mli112pFVejf0s9h7klnJ68Z1DI_gpwb__x-0lfMViBRZRZi8mMxYKpdqwedtuPKE8p4eLCgRzUV2ccAsZF-yDYizx7D2AxE4dWF6QKpDoqam2VWMys9jgiHCIHut-dhKiwy2GxQF4iPECVlVKaYqlmtQ4W3ydeHy_1-e__mjTBfL9vD45Oyyhm7yrPHDcrsxbP0kZ_Olh41x5VB1GPYRsL1-qZ1L9JFA66k7sHxK-S1RfHaPA5hoJpEuV22MXQbAwAhO3JNSSKSlUxg4XYIvP75aHdDz6NZxcySAJSpijKrRp3eaMoSER3c6oOpaqKdNBaVdiBklAqz2VpLIb68913bMGVh1PV6KVSvrMx4mj5cLtfHy_unt9dtnuXhExf8isM9LUSIjB7JZBZAr7epsw7B6ORrIalLvRCtSNZX_RBDlFWZqLZt2BAmXAavFmIXToQ2kJ4qrZ4LFc7IoQogmtuXJf2O7sBeJ5uJuGqoCFhYjAUFFeVT19ddhQY5nV6k158AZR92e6MH8kxlHiYA2mAtLKhiEIG2OarIVJW7z3Z2-DOqQNpWXGZmDtSZ--yS_VkkeZ0SoKNV2ZRu6-kDi2dQpGkHb6jpW-V5vQ5QbZfNjN0Jkc1VpxIbclHrOroIZ5UoRLg_ORjSEi5i7b6St68-OryC7NxJxWAl4r1WVilrY-kadRUIvLIyi6prDCiKSlMtKgGfVENiY1WYp-uZEJK-D-DMo3yPku3SBPsr-JmyeoGz_EyKjTkg8AxqRlDTacJ7oEtZvaNP9-06-wTaKMDIpEJErdbCm4hqHv7NV29-8q__5Hnfj93-vf_kf_rP_suf_OV3u17t7Q-_ZNanObdmo8Va99sf_LOf_Bf_1b_8_T__sy-_eXp6eNsopf0ec-p9X0V0-GrPd2VRR00rwaxmGV1oJxV1j-zc-enhBRWWJyD7Ecd-z5UdUGZBw4baI_F9YrWKhnGB1Ww_vJcSzBjWwwVhwIYUlXvYbFcVqCgzp2nXjsew6q_1FSf3vbSeqI5cTllJqtIoS49zqy0MAtYKtZkVlWVTs04qdVIkEYTGGHEmYs_YbedfV3jEXlFC8MgkXuXHsQg0r4ORrBqRpwOS0Ore7CcnMcKHWVtOq8jP0USfB_rZ3ihvJqAiTKw7-wIGS0UM2yLWkMYwCAsaNeaRzNJJznM4kUkJJ6dOqgE6lJiLMLYNlCrSzOgCfK3Gh2UVM7VAd_kp_zm5CAWxnmJykgtFZP5P_sHv_eCLr0D0i08f__yn33774fn2sm_v3jx9-fjp08s6fKh9_Utfvny-gUnnvB_HNsax--fnl5bNCaQIEbUfNyCeP338H__9332AvNxXUPzs5x9v9_vt-cai8_Fy3F7iqHdfvvniyy-IsK8ljOXVrJBIv78cIrLf7uVLVda-WMDzwizt_d1v7fRtQCTnWqpalBAugvsxrpOKxPT-fBfROTZwvzGTIERQG5lJTCY8TDJ9bNsYUODhYTNRZjGROfRxTtB5SPDwBl5kZGQBGHOwaPtx7UxzacRBRCo8VM6RJdFlTgIt9zlmP9tF5c3DpYq0ycWmZuLuLHJ72dlOegFliurt5TYv06ZNtZeXlx__8Jv9iI-fPs059mP1IGjtS8DKetzuXfpntWMdx-6xlg3NcIi8PN9szB7CFCUVr_u-jhVN78nEGa2kSlrHSqpa7hnEnB7riPnw6MfeKmZiZBQL4r7GZQToFz__5JWd_GDIdt1U5DhSFM8vN19rG1v7N6tqXGZ4rghqGRUrA9uYH777tAg6VdSO-y4qBToO95W6jYy83Z2FIyMyEHWEe0U6sSAjM5qOtWyamTITBCuWFMQkMlR07QtV5VFRQBU3eP8s7p4PjXC1mZlUJZcvf9hrNSpiVYokpqRigvbZG01VqebrtwWx87it2WKRpiBIndmcyqATbFvStsgzZlN9W6huo3aWpqhdlSJ64oEIdLrGujeAjtdnRp_1weedrwMjxERC3JS4CCZkFakQF7fACB3VqqaAZ8aQC3d1gZnCufqoBWE5K87uLEoZ3NaDaiva90RCJWZQ4ASVnCGNLAJrp_bELok4s0Ki7quBJ8QclAUGmHypSKNQM5NVO10FgZn23WvIVpknnfS0jndUqbJKIMRYkcKcR5iIEJVnUkpPRJkKqcN0jEh_eHgcpmAWlfBFleEB4bXSVD3DdNiQquDKd-8eQc1Er83s8elxDB1qWYuouurUYsyTN3jqGf46r1z014PYRsQ26KYva83X1_PO2Ve83gGAztl2m6RIzghMFUGHjTn7slFAiwopUQCbiXBFijAxiNH0JmYpoKpUNapAoKKMZBFTPWNtICaghI3brxbuhG70wYYN0Z42NiDoJJR72-vKbKLSlLc5maGq6Hux4Isv3r95c53Tnh42YelaMJ-QS1KVpg-JgIlMRViqq7oivbzrb5o0rahbL91NByiJVRRS1ag-QdU02TYzBhHMbPmac97vq15Nluk1TCiLi0QgwueZnUiUzxgxYbtsxKQ9-8_qnwKbqooNaxNL521YG-0jPU3gs3iD17wWBE106V9Q1hiWvkWAhSUzREDf_6REBEgg87RdFlUXcTyLQTz4dM1T9ShLGh8OrqJhw1EMnFCdpNf9CXcdqO9XgNZ5pK1hdrkMMcuTPFCBzIKKGuMytkCOOYipfdJUYOIeTJKiEpGZmSsiKsFS1C7zlGrzSRH4oBWUgGyYx3JWWZV6KkGIWSjSM8F04RFIBok0spiyEm1_wPedAa6qbuzhDNblUPUIBhdRhFPkebJs0FJB2TwCfKJaPYsJ3CuoJLPh5Wc0CxBChy5EGdS45zjtdNCThNaST3B6DqYff_X0L_75Twr24UV-9Ju_-rd_59e-_p1f--mn289--tP5_mk-PcjD9fGbrx5_5Ztte7NV0e15_-7jH_3LP_uX_-KPF83_8D_4B-H5-ecf1uH3211YDj9D2KJWQFWutcCUUusIomoc0X3fWbgv8415U7bD7xkLweH7OkJ0JFFG9QWGWYmhIgJOIvfILKcIX40S7iQhm0UGs5ggs_syONH7wkenKaLGNiJi0xHRoMti4vIEkap0mykij4jIpaIAm3QLRJAQQqN7RDiDKokFynIsDyIbWsxV5CcIpGFeDNXYj4pDxE5plOe4bMJkw7rF2wdoqDJbhpe7ENoNQtnrOwjPAJWATEDSGdw4QqS5IpVZItZRvcZ0RRUTzud8f_ZTDWNRgXBmgORUeVargU52Xf9FmwDOqiZS564pTa0qVe28WU1jltv9zgwTaVEQg5ix3w9WBZGo9X2_QIzaRGTM_-Q__t_ePr58uh_fPb_c9uN2FI3pEceex3GYyuPTIyVtl7Hfo4hUdW768nz79PmuKoAeu2fwsY6I2_5yp_S__7t_twj35d99eP7uF9_d98ViSfj8-UYFJL979y6XP755--13HzLjfjtM7Nj3wx1MHssj0pMpdc5wjG0qODO60Ubgdew2Z7i7e-uDwiMrq0jMRIQi5xxE2Rvy7lgVSETXcVc1yhzDTKWi1HhM68PJHPr--vTp8_NUmdNQYqYgHO5iGlEFjpY1nCt7ivBmCXs4wC1ynnO2DcbdxxRhWSc2AuHLzABYh2uzhHmYZdScdhy7MDwqPExn-Jqmc9tQBM5N5uXh8nzsqxyiUXGZ83q57HuIsTKvfYlpAvuxxGauXRlVASCj1Fp6ZWstIvh-pIcMRQFMa_kcM2INtbXfK-O47yB83ydsOFtGZOT9fqc-pya5UzEOX_eX_dOnF0iJontxK-h2u39-efnLn_5iP_Yv3r9h1jgWC3usY79_fH4xtUj3CGSCxcbIzOv14muJqKhlLjnh2QgvSOOx6358ho2KCj_Akp5q3ACipzdvGuevqrfbPsYg0EmfU4twKpah37t0RMVXpK_XlHWbLSwpmEr06auGKPSbB0BGUCZ3ZZVR8YloniO4SKbs-EFX-nqmC4B4CCFjcdbJamhkRd860BttgDkzpNPSfQ6r6p17tc_lHIJxRZ1E99eCI6GLtmfjgKB0RoPBPCocLQSoaDgjESHBJCIjs0SYpT2RTBlzjOVLz-xCtY2bGGc2HSWdqO3PeZbKpEx9BSO0Iq6ygeVoBUkfVsDErH2oLypGe4S79By99hBmyuhFXGZFASoZYbYloqqUrLPQ7sdpHEuCSEUqbB3OQ4dYp2P3uA8Zakavr-kGui5folZJYjNjdeV5TK2M_eUGJXcfl0FJphpRKnx52u732zT56os3ZmIkTLUNu8zL9TIF8vLyUr6yyMYQkYY997TnnPnQ-QM6KS9noqdP9o1sJaB_E2WWEPcOpaNl_Q0573aMeh1h9vx7ztmjXQGa0-nx-hI8ATl0ggL7xBd5HotPauipL0RVs9qFRYybkNdbs4hIKsq0YWtfvfmXM52PHuYxo3ACrBgkAioS4aeHx0gfc6KIMrfN3r99vG5yvVxQ-fBwHWK9rMbpvmmYOjEwtC8Y_Q2ss21wmhHOVkm7kHvhcP5tX6MsqhhTLttkyDSjiN5D3e53FStQRkZmRqpqZSmTEIvAMxON85t9OZMe-0GIy07tMzfDW4YUiAUqCi7m3isW6OxFqEqfs1Wl13Gt71HubDkppM0hZ9KhRaZMXOcJHmf4tGeFXYPrhR6_Rn3OTV0vjS6iaipqNow62YBXGFJVZZlodmeTCJWXaUFlphHJgKoWigo2zIZWEQvvh1PVNqdNY-5RSPBoYYd0xPZEnTJnkrHewhto7Bl86rVP5tiKoIQwC6tnMmz5IgpTyQxTzUgUuLWpDBXJKnA01Ll3aV3jyVP_VQfdFNMY1c2mtiyBWBvjqFFVXMzSVOUOTUQ3artIxsSUzXCiyJYSpi_iPKm-wr2-629oZonofhxElVEocnJUHwtomDW0bQq-eX_9o3_zJ99-fr6P8fTFN3YnUfn6x19_jvunT8ex57tf_ppFhz1cvnx_vBzH7mMwyQgxyPijD7df_vrt-x--L6kPn-7H7sQyponw_Ti668-gtbyD_ZV5uIOIIJUVGaqWFacpIrxWeSywyDaWHxebRDRVVKCqyhCROfR2rOswiOzH6kWSmraWjJhUcA5rcOIGImPqVqDYaQyzacXY42CAkMwQaD8fGCzg5viLSKc8ixhndpeJaNvGyjgimHG_HwJ0Pp6ifZQFoorKzIo8lneDLtocQtl03VZP2Lb5sahq7QdBdKAS_Frox_nuQ8cviJKbelR-5rmY-yJ-irOLhLk8CaxDmpFBXGbKJtRmLqfuqaTXpuaZwnZEKmrT4RlNx26IQ1MUZSgRgVhFVkacfTAqDxGrKu2dMouv4O_HQoIGtN2fX-Y2k0pUMzw8COeKXy66HfQ3fu1XP73s2GSPYz_8-bZEMS5WVcdtn3NMs4vNN--vPWpRkbWv293nUBC93Hceth_35ALRiv3f-Yf_zky6L_98HH_xFz-LdcjYvPOFHhXx8LR98-UTJZFUpH_68ImKHh6vx-HHvotwRBz7ke6NHJnXoWOY6v1-A-ry8Ljfbg9Pj77786ePj28e_Yg5J1WqSnhQQVTcA4T9OBqAl2evM_rzsmpNVRZQ1fX62OHyYQNZJrJqKdX9uA8FmMcwNvSfnFlo7WYPAooIJdb1eskqqmwxn7JsY4jIiqY89QarFCLMmWVTG-ahplRkpsJ822_dpdS53X2ZDXBdtss0u17mV2_ebHOw1O1Ya2UVwsNMl0dkLqqPH-6EetlvahZJcewZlRXhS22s5VlFjH3fYezLw50SWXR52tZyZWazrMoKv_t8vHRvLCOvD1cC3e-rEyuVga5cKBPquB3zMm-fXzIOgJ5vx20_vvvZR6d09b_6i1_8xV_-fD_WihVRc5sELveM9P14fNrSc06rxNwGhM0GK477bkMzK5c_XK5UMed4-fzCHRlKgmgm1u2QyVS8jqXDkLXvB5g3YbW51iKwe4xh1Xpe1uWO9iOzUNbYRiYt94wQlVhBvcqERgaDiFLs7dc9i2RGeLb8xV637gAXGbr7RXWGFjghoKSO-QKnASsrOEtOZoH09OykiDRqs4_TEMqT74mWaDEjipgYdep_e0ROEJGm8KKSunYsKnQOS6LuKONz84vmnvTLl8FMQlnUVJXK19k0o7j6PKUd6q-GJVGcDbyMZs8VRKjOjFNDJwmoChYrFEOKKVfwWUROMYuqaulYBXWAJys8WYQUp_u3D6OVLXlqFGL_LiL2_VAdJdj3_fUQyK_LiWLRzEYCV6SPMXc_LvNClaq6PJLIprJJIfu8KCx57FwkqixVqP3l5fHxYptlgBNTeJgyk4lFrIe5CWFTUuD924fw4827JzWJY9lUAaiwVhTRGKPJ1sKsIvXXC4AT7doJ3RP3Suf_dvHgBP2Au8L42mKkpOpowmvqmfqYBWbi10Hoqw2kiHpu1_vlYUYg1RZCVcNbetDUgNde0mVWRrtFT2wtC1C9_a7OBUZFpG9zYxUUEcMz-icnBE9vzYV7FpWamOocE0VzGxBkhJpsY2xzNjxw2y4KEpztCJxQEXyf9imGipy7tuzEDaJTZC3iZaazAIfTmpbnDaTB0g_XycVDFULCilOOy0T0cl_MzXqDDWEi4RKRqLTRzk59bchzUHomM0URmFSticc6rbI4Twfd3JSK9ATUUFLpeSEkYe6_QqttAeJe9xMlZZeWBScPuOkoeJ0UEnWdt0cySdU-EI6s9Ej0g4i7rdOVaVEtcCH1NEC_yoPaB0HUBVsTgWpyDR1EZaIQVJWZPVxtQBpR6O42lEUZ0BaYeJSA6rzG8qu9r6pQBKY8r74gOkcsFUmZLHwmJImCaFU0IFGIiSTS-0l9wkmZ-wO1XSDV4Jez49HnJhKVfosIWSNQmsdiZ4mwn9joXiyYYw8Qd6kvV7BKVRKQqGHKxVXl4SLcTQAVmaxgWpknBLBfRaIEiowjdoV4ZmapiFNABUCiCqAokfriev2jn_zx87F4znl5fP_VO9rE9-NXf_yDH_7GD-4vt5__4U9vz8_h-6dvPz_--P0Xv_7LX7z_6t0Pvn589-7d15fnjx__3__0D_V6Qcb-fFzfXmxOD__egxCRGS6qDNzvdyJissNXxFLRiooIIhLW5Pp8u0FkRaUCBAjZnMIkgAnnigKNYUm07oew7vfDhE2UGn0PBoQTEXER86zlfqIsneacfoQONrEqqkxjo6yKEowVax3Fxqpn8-2-whRMbDSK8nZPomJjIxyVR9Ld917ZZYSpLQ8-9bcVWabing2HqKT7y87caRm2y7Cp6bChrWUDFUy9QngUAQLtmBEzCGpDpB-1dT5TKhPkK9mUSVDwzHUc28MQQvd3VUCRAErIbHrk6S3JgEgFGgeBbhiDsgi9-WC0o665Qfpa5z3X8yZRlcvbCsfMwnKsQ82O9PPv6Hm4o_u-WSSMakYsKxU3nlRozvHmMv_ub__m-3dv_vjP_-qIY909l3sgKykpPA_38nz_xZMSv9z3Pvv2oaXQZIzSOYjlF99-9_b901r-8fn-e3_3b95vRwFpuH2-g3nfQ00MtV5e7HJ5--Ya6A19vrwc-_NLFi9frSbx_cgqvztzMUt4Xa6P-37YxfpDzba5dmfC4XdTI5btMo_7_fUBqK2rEoGYUWV0NRHdmO_GNmXEm7fvsw6P2q5TTSvqcrHemXz6_HLZxvV6VcjD9Rrux-4MHibLwyOjyg-PSq8kPj_Lly8FR5KxFNFQySpiNlM9O2c4dldlM9VmgBO1nm8Oe3jYMum298WYI1Nty_Trdkk_tmn_1g-_maKfnm_HyiLKjKqaolW1lh9Z9wgRrggVu-0HM8dazOCK68OVhYuQVBXR5bBYGUFrHaoG5n2_CbGYpkdVqqqorWNXEZvD5iCitVYcR5sWxtwqMyKEdb2sdoq_fLzNN5d1X_v9_vLx46cPn__yT37--eXl43c3EsrI2-fbu_dfMldEqoqpxr4oiZm3OZTVk15uB5DbdUT4EEGBlUHsGWR6fzkYmUGUmZHEtHYvFgiJaOf9_Fj3uCelqYGhqu7RGN_MoAQlKFsZyffbMebmvhicTb7q9EAho3IFEcl493Vk8cm0aWdNIV-9Ytw14raOtYAp6aT0dJWTsokXPciv-B4Aeqp2ieh7PXCrEbtOS3UiNSqFhV7PjiKDetPMXElJfJIhT00KgIZkUIFBAwKGZKUIowpAeYm2dje5Ax4iHUBS0VczOM6QEnFGUl9kBESV3mrQ6uvQawQKjfvMxklAI5MFQqTSTEbpdSSr4dwSdKK3LxXaI2cqrkigKhzMvvLkhEIyXKDt0FMZ67iDT7Rpe3kYBOVEIUmYirlEwpvnSlTkFSIDrzJdIsiw11Z_Iakq1QRFNrUx0umHH07g23HY6D-VFHmdNocOlcfrCPeHy3x4uNg21UBZkTmmjjGa1dOplW4cUbvSunJ8hs66gtmOZOpXBJgr--5Vrwn4PLfqr7_xFMYxOvtUeb7qpP1NLNSUG3pFx2SxSku5uzaYlJQkzMaWlZnJKoUCMeupHDBTjwDOgihRTRmm2gwoFR2q3USewzqDlhEsPNWisipt6JxTgMscLQfOcDO1Ids0E377eDWRx4dNReikphL_9briRGxSUURmVvfxq6jr6QQU6mSgg6lIFQ-bqnCLzxriNQejMRgNzqeKIo-M6II9C0tVemVlqUBEHWlqfXDnc99y3kmYSE-_tDIzo5TFBNIDfqECSbNy27WN0_yFE4rFvSE5VxQMfq3dd4hyKHeMpPXV3gCu1wdFVQhrejKECB4tDuphp1Bj80-vMBXBM3rJoK_KrXydUoPZq5hbi1aCamD8YDE1sKiZqp5Af9WIGK-xJBJE5jSFGkuro_R78XnTwVrdtUdL58UziamjtJXpkcLqlSJCxdoP_eYQgKLXhlUE6sKovg6MkcUKgUbWnosLHaSmPtwXkNw45L6_RotXOraufUtpfH5rwqTSFRZRWXSq-6hMNg9XlcEqoiBIP7jEPGLKpVOVbNYRpshkMOUZ44xMgUUGKR_ugFRWxvq1X_7qT_74j7_7eHtJHJhf_MqXsQKZo_ih6Dd-_Uc_-rVvPv7iF1X-9O7KB9--ffmVX_7yT_7wz949Pf3qj3_1c-5_9i_-5R__4U9_49_65eWHmdkY5dGKxShkRKMtb_ueRR55HIsq-02UVLnonFP4wcSisseB7BDrWVOyOUuYCZc5kJx-DLXMlJMWgCSijqYAzPDMbYyXfYFxmdfn222YFeDunT4bJhRpyq_VOGQlmx77IsqGqoRQnGEwpJNuMpQV5_XgODyT9uX7fkD0druJWVRmRG93V6SIcFHPHUqoa5jZe_JuTxVFRr8eAaEkdG2P5Xwo0nk_ziZd6CxG9sOFhaWda9VlAxvW3TwwXbctPER4rWAezexwj8xk1iJkL4LCWawd3ke4wISrj4ztDW0ywRkJBUiYsh8FyEwqzOslIxhdoKfwaBd2LznEOA5Hyz5QRA4kCL773_qd3_zH_4t_9Hu_9Vvvvvzy8_Mtgfttf3m-i_I25-2-iKCm95fjq6_eXoZe5iV9mVlFhp8c23WEDhWxY_m7L96s2z3W-of_6H94gRERFN_99EMkffz8ksCx1svnzyjIGG_fP93u0Y-a2-0eK9jkfr-D2Ia8fH7psVIvB22qDRXWzChPmzP2I_sIfywWI5AMWbedGXOO6PtJUysI0bHXLlBlqg5RFpFjdx2qYxSjs1vbNpioOZv9wjbVy_XS7KD7cYjIWg6SKPIIiKzMIhIWz1zLgxJgFpGhHU5WVemz8jASfP70PDZNgjBv2_YwFKxNgkLkmLYO3-YIyrWWe6iqEBr68Evvv3ia277WX338IKxzXvZ957ani6rJ8_OKCAHKM4NYOMLLE8jt8vDm6e12mSSWvrr8s46j9-isXCsbma8mVQShWC5U6753BFp0mtnhfr8dl4drMzYy05er6klrC2-HI0Pclx--9v3Y9yNWrahIDD3uuyDnkO16IdCYW_bQhGWYmUo2pFJI9UQ27_vRmOP-lI11wOTMeYK5UBFjmK_VVrfyMhFi3NeiLFFZy1FExGstZmZhM65KFWGlCFeTOI7XFAWxsO8LzOHOzJQ1Bou9-YZbilQprBWBSBZNyk6YtdrmJJbHKUw9Wf9UBUoUj1EZLH2Myvg-r9CdNaLTMB8phAJ7OOvoQ3USESc6skScEWAGa4HQM9oC8Rm64FeIj0eyaJukCqCkBAl364o7_ARiFokkaoEXhBrFzdpoAmJEBlN2AioqO0LcZco-95vI6TgT7vYbMWd4YwhYAWIqys4rZPT_faVRS0aRclWoSBOUqteUIkSAoBpk60vMqm1rVVHRZ9PjOEQ0q43IxcnHijZbJSGJdChljLEBQWdMECh0lzw8BATBujuJJNcwJZBob7Pr_nwXEVIOSnB6Zh_Cfu2br8fUD7_4LpDKdN02Gyd03I8lyu_ePLy8-JyCIgYLK_HZ9O-JRZOU6Mz913mJqurW6_kC6ZBtvkaGmIkoOrlxBr16OHIWZbtMTcytX-i4mPuKqKpg4GIjmy8a1UynplJmN0YYVSVq9dpRflU7d6CWeu9UFMwkwoPVeumpyip14kZKTc-fcBIrqxgT3n_xhovG0HXf-yvYhjxct2n29DCnGhgRBSJRpVe7RQu32hbZBZrGoOb3LN4TPMpzyAQUeLrMIazCpjCVw71vPKZtns6oZKYs7F3S7L8Wo9HRVRSZwtKDwDMa1z4OOIhEmDvfd9LnT2KPsRAoQWKWQQIQlajC0ODuqDhL-MAKZ3Tyqkfa56rrLD8DnQtqckBfEAoVUdWR4uwAtDZRV1Q6eZF59nDaoyGgjMxe3xGKEFV9wzERZv4eTdVbow5xiShea4nNw2W007QqE2BllZZmqJpKZU0djcojooi-7ktEssiK8EwTRVVma8bRdaCsMNOkinN83_x03u87RBvU775UJbLAcMoTTUrobcRKF6iwnOtToAclBsnK4hKxqCii6vQ4KDpW0UfYNhh26Ker9T0ybQkuwTMaBrrKmaUoqIcRmcJtjT7pOt1DZ-XMBMQzOjkf4SqSTB3bMJZp8qMvn37yb_7k5y8eOlwefvd_8KMPn-4PNt4_TcusjPdfbl--e_-H__rPHt--vX98Uafcjr_3t776r_9f__14mu_ebe9k_J__j_-r_-_v_8HD5bIyqvr-Xp7hHshTA7Y8Iqnf7qqaidbenyd94UISUTPdm9iAoj4l6zD3iPDGPveLMKgpd8T92K801VhBXOndWyJ-FQSufUEBQKcOVhFi4liRgkxe4ZEJpqi63TyJoigyX_ajmTZNsRA1IvIVxXSsxQRfB4us_SBgxTrDlVIZ1BnltVahVpSpiQixUJXaQEFZi2l5HIezWVW2OrhPpRnZn9uP-m7RMcyKKGIRUWQQIT1ZSE2Hjg66EmhOi8hI6AALxEz4xLLt-25mKkyFXgWKcRCtFSAKBCDuzgQqOiI8og8DQSQ2bvs9qIoA0eO494FVWSq8H8-m6pHLu0brJ-OZpABwCkMZw_TL91_9H_7j_-WX0H_8P_sfaRLAkXn3aJvh5_vx_qv3XuUrTaUEF9P3757ePz5R1n0_ui-SkZ9e7isqwitzrQVQrIOhteK3fvNvxO6fPr1o8fPt_t23n0r08BVZK7zxsm_ePu73F86MCBaA5H6_ZaQf7rujSTIriIkJMmdj65gFRGrD_QC4K62iIqq5VveertvbKA8PBi6X6_JVlMhEUUMgiopZqAAhKkQmVVBkVD49Xk2FWYJyuT8-PWxzGrMOOyWnVRHklRD09-E0OkcUUSVFpJoquK9_16dr513NrK08rMbCxSBAGUM5qSKjp73yKqNkYYGOcelMgA4l-N_48Q8o42ff_mJFqiihlDkjULVdtttx7PsqULpH5b7fWSQiRHk-bl-8fwfG_TjOmplxRvjyYTOOpSpZXQOjy-O29oO4r4rkazWRxaaOMTwi1gpf3FoJlCine49We7vVxMp1P_xYqsJCuRZnRERUiHIch694_9U3x32P-7E9XnzF_eXgydt1LncGsTAVplm45_LzqARpn8z95VmmvXy6-_1O6BCNgxFdTPKMXCx8mdv-_BLHXqflisC6bVZJt-c7MctEFWUUwAhah7OcxsSer7EKkiDtQ3z6qrEZkCQKKiI5fVXc9uaWqEEysjloQZQiEYSuQiZJ76qTUElCycTc_EF-pX2fSqIzisOSmXymQr7HSOKkbZ4GqBPs0zW7SgeIMnv7KipEAUaetBlKegViN5OT0UuC4pPs2XKqPPkYDKa1QpTBUu6s5ykQYGT1mYG6iZxBJEQlotTgeYHxzCr0Dj2DRHCGBDove14ZW4La1lki8sNZ7ezzglviBEISR6SIruMwla7UhR8mSpWAhHdXi5mVzr-XZFFFmFquUB4E8uNEMAFAcVb2CQZCRLmZIcuPVGNKWveDwQYlrnaObI-XyjJG0PLj-OLdm3cP2wp_8_h4v93HZfhazaRLhjA_XS_H8jmHqFQU_f8l9oHXEE-d1mQ61_dxCufPrVGPw9Cq5-8Dx69FAeD0n5974Txpi-d3mrKOtZIoi4SYVWOtVuR2msiGRdZrtxrWNYkGTDR5toheV0e9u-w7jBB6TQCq7LMbMRr8LSQiY6gA17lR5cNlk6q5TQZ5RFuStzm3Ta-XOYYxcBqBmToD1kSiaJIFqoo8KzOJOTPpZGaTKinjYdNtqAEXU1DyyZOnDNqdokobZ9QR_vAq8qAgZJLH2YA9r0PgpIoqZhEmpmris5zoDkH1iQLE6MJT7weSUoSzqDPE51yZshvEoJN121bmrnf3zb1eY0tyskR6bN-5ACaGgD0CbRKls16prBHRV47Mahjo6yDgnJr0gq1AmUWseTIgUln5e28g956yhGHnVAIKFpUCTC0ylAHFuZnpsJ8wCFm1Is9vaN9We1tyWgSLgKbkV0Q34AHOKDmXnygiOwNvQsDyKCo2rqxpVqhueYJKFPUa6MqqQHklZZ9X293i_Q1p_WkiQVjlVPDDG1shytxty6xoVEM_0quIEBmEUpHudXSsX00a_uvuvVur17ff8iXngqIfipmemZWUDVyoyhN_TN2JJ66K9L_5K9_84U_-5Nv7Xtv1O51f_faPXr59sQ1fXObTdSOijPrygnicP_143y5qvP7sDz78rX_37z5d9ff_23_zO7_29ZeXy5__7JNtEwhf2T_9YiQoVvTl9Xa_o8QjO4EwTUw0KyvgVWDsR_SGMRMVRYzqyDzVWmtVpUf7HUDEZsfaI_N-vxWjw_YmRlVzjIrSOfqnU-BI8uNgNaqcl608BBVZYI5IUjmo1r7SfR2-iMQgwulZ5QRODwIx4fQ3F-73PSs9ax3uHrGihKPofqyoWvdVJXF4vxTCj0roMCYJ94p4VQrWft-P9PBUGxEeq1Cl0OUOgTBUFMVHvQjYMyOCfIlws3dFQdGzu4wsfp18KcgUvkLNiJkiqOhYxxwGotdadC__-GU_CnSRy4oIz35ue2SCMnOKVeWxkqTr42eGHKrtwODiFb4y59x8rTgcTCjifqREMicrr_3YNnzx9vqf_u__g9_-9V95-cWnx6c3UXV79mf3j7f7p5dbV7aPnZwqktzXdW4fvn355qu3Fx1AHfvx-iqmYHq-HRHRJ79Pz5-HjeUuYj_-8Tcby5_-6V--f_MGVPdcH7579kpRWbtTJgtUx8CIWBFJzOtY28MWmccKgGwba0VPc21OkxlR23ZtqWJDRhi43_f2mWRSuLOwKBcofAFkwyiTWY5j9-VMqIjjCKgsj7lt-7GoCgpWjuWt6QTVZpONlaAqw2asGHPj3rcQr4h97fuxIJoVWSWGoyE2RNWdAJY5rKgeHjcGGq1TkTrnvq_MEpF-GqLQv6C3k9uctokAzy_HaWHpsV06M4bxj77-GpE_-9l3b989rKCKHMxVdTX7_PmWwOeXOwlu7ve15uXqsSJzzvmjr75izf04Xj4_349V4GNfXdCacxR1K4KYKb3ELNYytQxK8lwBkczYtgdRvd9vjASq5ZI9slzhwyzWyoiqsjFB1LuIpGRIuPcbgVipUpgLeX_-PMZYEU2zWe6XuZUHkZbncu9vTmYWyCOL4ct1GFOuyFjLzIo8_39M_duvbVt2n4e1ax9jznXbe5_7qRurimRRvEvRhaYUy7YcGTIQO4nhBwVw7vaDAgQBDMMBAhgIkiBv-QvykCc_BAGCPCQBAkMBrBi2YskSKVEUSYmXYhWr6tz23mutOecYvbdLHlqfmyZRAEkcnnP2WnOO0Xtrv9_3eVhkZIWBKSM8DAjMIYelp0cExun5jS6HprRdNhVhljEMPJnEalux76Ls5hGeETGcm0DMgiVh8vryw6yN0kxrYBbMnZAgp44bCVDcK6ODV9rmjDMT0jzEE6ZbKUonV6W-W5UZjmIzBvBM6QJVqp7To3iH1YwCpioHXVvMiBnEgARRAjOqt3t2dyIBrAnXDHyjCNThQtTNhMXNCl5WQQikqScrpOPsj9aJYU4ZISNQNNJ59o8KyRIZ14dWGgJmUmCubQ0IIILENC_bYv5p4H1SFCOJ2wIWrC0IkAmyaA7ByuX80dZKj-ejS2thg5BLtoBV0gBC5kAAqTFkciYiNl0jg4kAHCMEizGTB6UxggBguEQe1qO5SyMmwgBp4sMrhUOiVHCZER7-4v4m3F--uD_eHvbLUOHRdzM_3rQKYa5L62aqotrqB1R4vms5tj4PAYgRoyAz6XMblVXOn3NFvCLwawSOzDzn_TOvwnCtxkJmgYETEiI9PDKHuTZpoghQQ7-M4rUiIUyGKAAi1tS2Qv8ZcwYcCRGBmQHZmq5LE0KZzPopei76SoQxCwEcb48KoKIIIcTrYeFKEru3xoeH5eaw3h9WRjoclqXpNMAlZM68CtZpJiA83NPcZpMZGZkDoswD9-vaGgukCBNRunEd2BMzcTOvGgMTFvYLEzIJEhE5pLIoNLNNAJlRsj6IKEuICCGU7IsoCRkja9Fec1LgWrMTIAAjMEsNX5EgPAmSEt1KbY8JSUBRYT0gjxniIuR5jASAqOw-MWlpPousVTe0uhp7RiGeYNaQ4jr7TmGp3YJ5ILF50cCiLhXhpYYLJqpjMAR4KXID6rGWSCwIPAvnBIwQytRIaqLxjiBahWYgYhKAYJJ5qU0MAEauWHM9AB2SABuKsIR7vREFuPeBKFHtf8IEbCwFUkCgiExIqcswgqqOMVTYi2SAQAEsXIBwRBKkSKgy8VyyRbAK1RU2pwldWwtIUs5IKBd7N0JmFjeTRT1NRTECEgggwpg00xsLEmZkZBQkBIXdnZDGsDKf1IQlMy0NA3jebQYSQWQf_Ve-88k__-fff3M64-3xVl7gyR0CKT86rg-Md8o2_HI-D9Efvj69OhwfYBDDP_xPf_fn_uLP_plf_PT586dXH71_Oj-lj727Ng13JjK3MerUajTxl-QRlKlNzALAkcDdESLqVhqYkcMq-gSW6RmllvMxhElUGreMCMj9YrIuSOxR7FeIgIBc14aIlo7M4ZYQCUFJRHB3e5fWD9o80wEcQRpTwr6PfVhEoMoYyYCcOIaDsHuoyrYZVCqS0MKOyyJI520fPgAo3DApCpFhgZgZMYYVV5RYLRMJFuG6OUOmirhZRiQBEaBDRCABQSYDtWkTdDckBoRKTu-9qzaYwd4ygzY3Z9UxAjCYMAKAkpIYiSKraxIJSKiikLWJw_RIghEOEcNsH1sh2MbezYNUInIMJ4aFWjev7WLxf8Oj6ZJpsVsv_hIkM4eZmWWU2TQhEwJYCDNF_Njkf_Hv_ffTDDIiTFcR1RG-Wd8vY-zjct7fvHlGBgi8XLbbw-3IePXe_QcPd-7j0HTbLSAQaTfvmX1YgI9tuI-7uxth3foAh1cvb3H4i_v71gSAzqMn5Mvb907PZ7NRivR1aYCVHyNdJCwijUiR0Mz28_nyfIqwpJovcDVxIkP4QBBY8O8A4jIrOzOLUt_3Gle6OxJBIjGbD7dRRsVMZOaEYBHzARmYoLKaj-j7uqzr0ognBbGpEGXtwurXWJwCAFCVMcw9EnDsPsyUiAT7xV48PCw3KyEcbtYMeHp7QiBWAkRPfPt02vpImDPjY2ujjwDM0mYT-cTWQmIKs5kD0BgdEh4eHt67u93Ol57x8sMXItK3y4cfPnjP41G_-uqSFfcUQpLWxH1HluWmff2D92K3bdsvl51IAOH8dEYmG5ZANoa0xcMjAywQ6Xi39H24GSsXjxxwYhxwnk8xzBORGcONmcZlAKUIj76Hh6oCoQ8LC2HyYeDhZqhITCSc5hDRz_1y2c36zd0NJKxrW1rzzPCQJozITKP3hEzCMBehfulCsC4Lk2z7juAAXLX5jDonch2SGKjvl8wYeydBImztGN7301m1mVlEqjbrPbheKA4O4K5CZi5E5gYEohKR-9YBkuXug4xk5enHqjOltAIBUQVnRSfC_8p4rw7e1fUECGjmzAzpiAAxjxw5nZ7zTY6USBzD8J1vOBIyCpJTc1AkqlILRE6m_JX6k2YknAFEfO0eACAwzNk7lB4ynWa-H5gVACiRpoi0Rvt1EioOKc_SXUXCC8UviMxhJrqExwSZO2QAM2dMPBHNVAlU7yeGswoRA3MME9EgqLN7RA3hK2yJs6uXmRHViqg0TB2jALN49jEK3l_jW_YAIkHJ3XuUXs6cr39FuLFwnbxYtNqN4YFI0RNgLiUK781MGebDIL2pOBlRZQgnvUlEMPzVi4cMx2RCOp1Ob99eKgxWKvBiJamqqCDMOE0FKQCwRNRENRctneXcCkypEWH49KkRcSVeYuZ-qnCeFVyrImdpRCKifrdCaBGn8xORRIA2qUB2_X8HBAlDxrJo1kep4LZENQ-dIsx6l1VsKNMjDoeVCLu5qgJmU6l9VASkRw2Gb44HZmqq4IkE62FVZtUyxRIBKsvNunjg4bCs64JA9aEFwApXumU47BY-JSn1U8AoCwAEI6yNjk0IkQBZuX66xbmnKgkAJgSrhFfOIarwWpcjBAwHjww3moWK-StiJiGsCXFtOZkr40kEwCQeCRFllgHMGlUmRjFJAyA8ykLAtcpjzgqYVJn76uGLTI8i_5drPCIQMT2vXdUKDM4hM-KVI-VpkBgZgOgzDhbCLCJYAwZAEh5h5QpJTwhIy6qLdwur1V1A1bDKs1EQg5zPMayOfniw1PmeZ6WRKqcn84VYiHig9ChoGAtFADbGSAiMGnwx14rAwgzBMwg4rkT_qGJ3JCHtY2cVZo4IpVmRqGSUeSwiXLupeutX84GlqFqRqaz7MM9AovBQlYjAiUfLRCSmaxARiOqzVx0lrsBhhjGRj9G0VW-HhROTqUSJkIDABAmM3N1bU49IiGFOIpCQRLvtC7dCOSfNJa4gIsYv_NSHv_Wbv3va7Hj7jeMnd9_7le-8_eHrF_frz33nk_cejvRiFaHHx8fb-9tVpH_5-rwNy3jath__4evv_8GffP3nPjqdLztDTcsulx0ADDwyzaxuesPdIVGRr2pxFgnARFwAE-hszsBCGADmJqLVoGgs9QtGAjNHhKUtVQNb1zVqa1X5eCywhSOrhe2j-8hSuGRy-Rmx5kWMiehIBIyeB2pP-4WFZ7AeSZkzYndjEQBG4pGemcTUhzdd9r1H4mXvOfehjOGZxECAjNT2sROV_g-QKwKO9XXzCCnSuVAS9p6SzXIAJQJHeCILMDImIQAXgMEBvBuRRCSJJBEyCWt6gNBl7yKa4ZlAyszMKJDQVk6kfTcQVNV9H0FAzMCymydCjAgLRN62EUFRUBUHFonwhrTvGRjXlz3Wy5NJAHLsY46DmDDBhtWdBAKBws3qHDuGP7xsl0v_9__Wv_P2J0-Y4Nl3i_PWt9PIyA8e2tvL7maWoMKJsu9jOa5Pb59WlcPhcH9YHp_Pb5_e1NiRiS7DhsfT6UyYfd_Xw3p3d9PNEamt7YMPXq4MN7dHG7tZ3N0ezvv4oz_-flvW8_lcbh-UYqXJ2If1nkB936vClpiX5wsJa-Mww5hQdhEB5GGbNh5mhc2OiJIaz8QasZmJMCBF5no89n3r2y6s5g5Qxmsw83U9ACaES61zEhDBPLGxj6GLalPrLsrrumZ6mPV9RGLxBaMUSwRI5OYA4B4kvCzL3e2h7JmqGggTGGoxRuihnU_7GFbmKcwEzHBgJh9RxqFCEhOjcnnoYN_34-2RCTHjG5--fz5dPHNZVgSwLV69d3M-XTxADsveLTKHBQSshIX4fHV_-9H9zVMf236xeiJ5iTVy9C4sEJGentn7oARi7jYggUUCEj3Tk1QhclkObo7oVLtrSEjPHsfDTaTFFMiENh19cGtEaGaV98QIXBiIE6kta3oWo9J9P97dYdD9wx0RRbrZQEaiepNGjZR9OEkZ_6Rb72McDqtKg8wiYm3d-gigop0EJJoNG06Q0iTGHg4-0sMgfPQtE2oZVatxYRiX4aPv2xZe2UaYozoDKLscAev9-0iEQDO5Ped0gTRZ7IhUutL6qtRxum4XGeleLpJ5ZKv_BiQAQgbwGugqXMmdMPXydSGA2jcAQenQAN-VtDiz1GNlYJk2Y0aa6CBAqE5zKSdKQZ7JglCyJKpRlocZAhBPoxkyeZ0HAaQ2AImEmAjdAghZJDMxMgnTjWqMXUHkCprINU9ZM8SJVqUCfZaNlpkzHEmLRpSTM4TMnEGAXDzMsECEUvQA1_XKq3aNkUgM7pWwqBtrhBeMBRE5gYkUYKl3G2JCiazr-YHhJk0hozUhTAQqk5API05GIWJE8PTWVhuuWodjbKsuTcxTRNdFlxt98_b0-Lzd3t4w8_lpv7k9bpezKK5ra0vLfZAwVMYdJxNmnt8DAnBC2MsDcRW25cTUFtRl0njgGkDIaye1cqgzEw-JVD5pTIiwKJEVl64XqGL0XmIFgiZabY6ITAAfhmUNq7Opef24rCR3TEtbIYGYDocDZGiTRNq7FYbVI1h4WXQRLv4gUKoyIxGRME0avVQMitfD0kR6Ny7iP1EkBtTndAoxmIsjGfXhmcxPJGG8PWipDyZtxmdr4h1kKQKIODyYkFmIkEWmpamWsFWVT4oMKssCo5IAADNBVftLHiVCAK0WxhVVrzt-1G6IAFJqDoEIMwI0by2Z0xCEABHJ11_fTB1NNUTWg68kr9W7mLVspCLW10xxIS6zH0I5Cef3tCp_kFH0wmHhmUySAFaFjzlz0kAvCOY7mJ1DVPUkI5BQhI8oZhaOQDCB5UjmU6TlHoBcdMsq0ghxbbSwXLn10Y0c4FLOoymIwIjA4iLNMUgCYmRAZWzKkFrVUnhna5eEQICwAkJCZqy0jrSAFGCvLwjVciOJKDGI664ipQGOCBYioYLrEgIDE6J5lFmWmSp16cPW9ZCZTXXAiAxi8jJnVb4Fqk-FguiZswpQPmYRN1uFh4ciAYEkEcpuPYvWBei-_8K3P_6df_xPP__i7ZdfvWnvffB7_-U_-8Hv_-g3fvOf_8Zv_t5_8fs_-L0_fvyTN89vn_dLLH_42z9owA-fPNx8oCJwfnp6fBpfvbmc9vH-_cPpiy_NbD2udaffLl2Wtu-DmcfwDKiUYKT7bokQlszUh1exnhDCUxqXeCghw6KpeHh4IGCaRaTbcMhVV3czz8hwH03VR3hGa-1K_uVIg0gWqa5TZCBj380ZWlvDLD0gc_M5tmaZbTQAiEpXJDDxPjowUIJUpi4CEZ5OFxRkbsMNWDLro5iBngUoC2eeGGVZRAAsMwmG9aZrAadtVDwSvJ6KJMXT0PkIkowAzzRQokjgIqMx9TGU5fo8SMLJohUVUUUM6y6qu7tZRGaMGPsgleGOgt1G73sauBk2NneCTI-tD1aqwYOZYwYBuntkIJF1B4B0z0hR2fYdagKVhSMPZKakiJjc5vRlUd9PQPAf_S__p-O8hXXAJNXT0-XxdDL3zey5j8fHnoBf-_T9x6cOlpe-Xbbt1cuHDz54cb8egPKy7Y-n8-3t8Xza-whLMCK3fewXCvgrv_bLi-r3f_iju_vj-fny8uXdYdF6afzoj__oq7dPRGyZ3bq5-24ibPV8Roh0h_AS0mEIS53brBsTQqQPB8jlcARKUo3wtjYb1rv1YUQoKghZDxEza8vqERlBiDOiQ0hE1j3Stc3XBBABkrszMWvb-p6eKBTufd9uj7e1-Doe19H7uq5x3RnqrLQFABwPR_MotngStKXd3d-F283xWCutL96emCkw9q0T8X7ZT-fdzIkgAW5uVqicTIGkCTJyNztvOzMnpHtkpA0TYshgkW9-_H4fBog3N4dMXI98c1wz-fl8TmaPGAEe4dahlEyEX__4A_M8PZ9H72P4tu1eitjM7bTDXNCCtNb3jWbk1Gs4OLaeCeGOiNUC3fcNIIZbupOK7Xt66tLcRtlv-t7r-b7cHCPDhmVmmtcLJyJJFRNEZd8GNm2LItHL9z9YmyakKrmNaw0ya-fctAEBMQ8zRgLI_bzB1ERxHzG815a15hURDgwOo1DAMP2HMYYRo0ozcwjL8HBQlTDzMXjhcdkAI8x6N1aONBaCjHCrhi-3-w8AAWLWg6QSMnBtbFbWtQ5fGYiQzO7BKrPFKMXugJoBJ2AlCK63gQBCCMfi_EyEX53_bU7p67BIcKVizn9o-XdLOVrBcZztXoTETIRIqidaFsccrqJRSCKLvcjDM-uaUcbhAikWqRCAWBQggCndScrxUHPADHMEDHdWBiI34yZunUnqEcXMU_VIiEk504wwVZSEyYyec7WSOG_IrH10lPI-1ashga8nICbIrMEqU9Z4C0USQQUDotYu6bmIwijdT8lOEYmFWFQB5wRdhDEpx2DlSApIVsLSNyK0VVV1G-Y-cJIooA8jxOEmqpAWkPfSvnjeGAE81tvj0iTchaCtDRIa83pc64pTg4or_7847HWsn5KpKrle58RFSIT_muC5_udEwsjJ2Z_DYXh3uQQisOHXCwMxzbcsUZ3mPcKZmRGWthQrcEoJyjRWXrDM9Jp0B11hTaJMCMuyCEJViJjBfJaQa114czysqjTXcliAfF2kMu2EoCqEcDgeWAQARaQetR6QCeHTUgR4jUrN_FzlkaTw9a1cYXFNdDAJXTWamZVxCkeAaKrVnSAiJYxM93DI4gjVY73-IVE_ZERiWJmBuH6uolzXhjLxUlBC0gQUAdTgsBZseXUbQTJTDYzqgoqFaLma8uqPWHe8ogBP4enV3AFXfTQARUaBVhPSwhHyHTw0MusfUUvreWWNgPrZRNooeF_BArBWj44JkJqamOEGRJHJykWwYZKIKFV6EkImCwMxULhPhpSPyphhBopyZBLj_AUnKEoi7bEptXxXD6ijU_1MoKiaQMhV5U7E0rsm0hRfAJi5NiFGz0gE5KyFISHvYZEhwAkESN2HcPU5JxXQRpSRnpGYpDYIbgmYXH-2Eik6IIJHejWpIFmYkQOcgPpwAQoP0gkNumLeMmHqrgATeP7iMjMJHIAJOcndGdljsEqJpQHAbPzKT3_6T3_rd3_w48_7JZ4uewQcDnh_c4TLhieLU3_7xePbPzn_-A8-e3loz6-fvv-Hr_0C7W5ZST__4WeA-PT66bf_q9_ej_rhw90XP_wJoYhI5qSI1bOh_i8ZgVTG3ASEWoyUY8TN62uPgJAhrJEIUyc9O0kJaFASF6oGSQ57uLsd3dy9LaqogNj7vizH9CCAyrUvKmP4enN0Gwng409R_ZaJAdc77vW5R9jD65SQmE99NJJMCHMgGsMSMoPcBjGFj-opjXD0BCQWtEwEMk9CFlXwQMDn3RszC9owQvI0Lz1yzPqNhWc6Cs5AAAFdrfVzFOJQ51QCGObuXs6OmCgH5MNi-_ARq8jTaWuLJhbUEgJgWPiI_dIxcezGImOE59TsqbCS2MiAGMOqrQSAY5hqK9YFzdEJ5hzl8NyCQNTAYQxHtERfjsvLh9v3Pn3_P_h3_s3-fGbkkAyiu7ubt4-X1mTrY7fch-_dAunL1-ftsvXRhWQ3e_Xi7tMX90_P2-s3X2VmHwMwkURXtYjh3i_nMcaf_4Wf__DuXoX-4CefPz8-jTE--vB9MHcb4KCybn20dWXh4XY59eW47LtF2PHmgNWCi6Qk8AjPfXRdFBOHDbAoggqWgbK1qlQN6zeHw-m8EVWgjiCTmbl4u5mqTYSLcA2ATOzXLGhYSGMzZ9GimbKUccUZAczDIiDH3h9ePhCiUmlnsoky8tLWhPCIfd9vb29E6PbmyMxVllNt2-XycHdfwpDnyyWxdg6yLOu2bVvvvfuIgoukapvYQ-JEFCILQESDaCzDfVgM8wpBWER6fu2jl5fLlkiNad86ATeiRWnbx6Vf3Gm4dx-R2G0nIgj42nuv3r55HN4h8XTa2nLoZiL09PgsjW2MiHBHYSoE_kSSR2pTM4_wMUYN0Tx9XQ_De1tWJrLeM8yG6yLee0KaDZi_spJpUFhAmI9eDkFadN_fLusdAPAio_f6Ur_34YfClJlKaFa4gUDAZWnlm3J3ZDH3wt4U3Qiypok0dj-0xsLhMWxUvZOQ3EyUq9wDE6fRhBkFM32M7j6arkj59PbEjRSpXy6EIE36toFnxvB9EBJg9vPGy8sPgbg2TpAZXoHUyJLRxPSGlAegnpjAVKQWRCTkhKyadxV2ZVkq2eKj5CzzP5kQlpX6SwgSmdmrslYEQFGRYmqfkBBJgxDSqNpBEcUQrNkn8ZVCVHYchJq1A3HRulU4zArlDA5ISMKTjE4ARGaOxBF-5Y9nurMQAsQwUa7-IBIlEDBiHdESktC9LMfFKinue7WHOau6V2fZORusIDqlAzPrspazwN2RkYipigdFTCcM9yhZqZSQLabJGHmeHRMhQoQtfBSbCQIAt70X_t_2oUWBaIRC7s7tkODCpAhMBIGykihjQET48Bd3L_a0w3FhBkLOcE54ebN88frJM83D3Zd1fbg7mhsAPby4XWqzqLWspIwgpJoaZwTUvJdqW1KEW5qH7yLcQ1FB65YAXi3YSS-pgdlcEsyhRKFw3QExACNjmAEEAAkLEYS7WyKjMq9tSUgkAUp3r60RERXKMDNiyqTmhYQAmJm5RtrECCoyRi3dp_z6cGhHlSnDKJQNIHNljFCUWUiEj8cFy5xVXddAD6C58IJa_WPRpoAicnq-5s2bkPDmZsV0RhIEFhSW-jlU2GbeGQi4BJ_z45Xv9mc-sfTvyPFAVLibLH1VJHDtjwI4gRBqg61chKKK3wMiedZZn2r8_M7sW0TW67_vdKpdc4FQI2eq_cvEwgITyRzqz-uBkE5FeG00yj4L5J7IlcVHvKZUEckgAjAizCwS3ZK1mVtdisMK5xrdRmGNCCgSIYC5uIyhUsE_nMKyRE9glmHpZrO8gkj1HUEIzMbCXHHbREQloUk9kWpcpEMxSZIwHSHBbDAJAkaGcCtUBsbsQiSGiiCkstZUBa4cqnBnlPBARnNbRTMTIRsp5jStIiAEERFEMKLSajkmtlKqDYpMZBYA5fNCBBAVH16rnmlbT_Cwxs0giorEyBnZSJDQIde1VX4sICkRMgi1ur8EXN-ChPITaSK4OyKB4C_9zCd__-__1pu3zyFkzsSt8x3cHA4v79ajrg-Hvl_azfLi0_e22G5fPdx98hIoc2W-fwDGx9dvmUBWGc_O6_Ev_iu_di9xfjq11g7HxkmIKdpseDssEdDdEWJZxM2nkBySGCmimNHKkpVtRHCL3sfaFotAIWAUpsioD2p6ijJgiOrWR1PtfbiPS9-btolUrqsgQDJiJArH1QxcHUcPSMljW4cNL2Na5UQBY-8kCEmNaJU2vCdAYOw2ImC_DELxfhFkQNx7X6RBKRIZ0AABEn0RsatJBzEJc_Rcltb3EQDnPsrZHGBINaEDAmBWs3r0JSKNCC4hIE9wO3CZ5rm6doCUpRdjcjcmDgxkIJLTpRcUtmjrKm3sIyFAZUTKIpnpkR6R7pQMkO5Wz5PMDLecqIVs0txHOg03ACIhiDD3be_CLbKWXQbkpy---J_8D_57f-Ov_qU_-82vufd1WYByhDvy5bw7-d79h5_95Hg4nocl4rAYowNVypHWdRWGp9P2-evXzHR7e_Nwd2fmbVmQ9asvXhNBH3Y591_9le_5ZcOM3_vDP4nw5bBIxov723BP9yR69eLleTt_-OF7j88XM1_XlZmHx7KIB0iTMYwSlAi5VDSwjd0DALJvvShjQEzXMj4Tq-r5ciFIN5vPWwwEwKx8wRyBlTb-sl0I6zUakdlUc_pRALImnmijr8djRGBxzwB0XVZVVYp9aFO3YCUHE5XDYbl_uM-M1tany2V4jnAU3rattQUAltZY8M3b0zasu3Nro-_ny9ksuqU2JSFhHG63x-O-DyIS4fPeiTgyxnBmffv8iEmnfSORMZIgmvLd3ZEJVKgJNdbT6dyWdrnsx7vj49NpGxuAbPvIDFRW4U8_-ehIdD5ddoNuYQEjIjPc_bR1TmzaxugTKYiEjCqFm5-hKu9DWIl5xNBl4ckBJ8jYtw0zIUJaizBldcgYjkgRcbi98zAuOX0gMMihZSDjKqKJkMg1-E0bhHB7vBHl0_OTNrXNez9XOeT27tbcPWNMYqEnwrKu1gcCXLbdu3HT7gOIAtLcGpMX6wSDqkuYGJmLrgjhYwAhJMSwdLf9MjyQMSHHtvXzBaCO9ZV56YjoYxCDNmK5fQ8QELkCT3UMSICejgTFw84IBFJZIHFWXROozh_hNR0sSmYgzdd5tYhrEIJQgtgJhi8rZ0SlwzOChIuSMVuzKmXdMg-iOrHAPHUxhwcyAUaF6Ou5DQjpAcxJUy2MkVXfLPlZiQpjGGtzdyJOQGjzZ8nMiAEziu811M_wohIRkoUDIiFDsoUTEyJGDTKRPb2iERNqn0nCmS6idfaCTOGWYcTFVhqk4u7SWrjXKQ2QrgEAjAgiCswq088Yluo-ei12My0CSltbcEFhKjqhNmGExogEHpCEWdqnGMKUYwBmOy511MBIBNwuF25i0JlYeDZofRg4juGiAkA197q9XV8-HD77yeMnHz4sy9oOR8yoUS7NJARVrD4dHGGe4LH-JHTlMaZDZZyoToEWXvGMIoQUmjASIsMjoOiynlOSVUGg-knNZJpAxWHNkJGEmigxV3ysTJYF0KjlhNu4zt0TmYmxNWnK6cmIy9Ko5vCR6cbKhKBNYvjSZGmtSvJMZUCau_JSyCkLCTELTZAM1kE8pgcTK8c_wpG4_O_17VBhICIgLEdRpDItjYuLOQVhlewqLtb1MVBd-8qmXP8SIJ60x7yqrKtzTIlMdeVGjGw4Uz3SZB7o5ncQClhPhPMG5k7VWb8mfJBw9gSqUxYzfy7zpUYEk8Eq0x9JwlLqrMrVv0ubZ5SGmR3nU2GGxQhLyAeZmGQWxOwRYbVTQYd0iDKpZbzLD-K8mxFlgmMAAyMXebZ6MiqUlspaecXI8OuwlpGZMRBxpo0wMzycZB6aG8C4RpsEOdKVALNEhZWZhDpb1nQjs6ornhEqDdDrB1aEYyJys4MsHsWdl1qTMlEyuYdUFR5hQelhwhRYeKHEtAh08CTYrWPRwxLDymJDCagEMQdYXGZarJwA6z66MHtmqVYQwMOlwkvuTBTuShyQUIPqBIfCVyQTW3RE2q2LSCXSy-C0bc-_9N2v_cZv_tMfv358fHtCWtwjFzDA7tF0ef2Tx2ptnJ5Or1-fE_D5zWVV6U9vf_c3_-jzH_7opqEw7aft5uEwov_m_--f_tQvfOu7P_XR7c1ql1hlWZZ2XG9ub27auigty_Fo7sAIWPI5ndnywGHzkm9WaIPAwKIgTW28p7BUuC56MFGMQWvzyNILlteZpdCXUKifku30_R3YZIrB16Mg1T-UhDgYejdR3nYnQOvemlZFPzyBgEX33gs0AhSBkeFCRCye0FQ9y5qHlS3Vpp4BCOthtREsHJaZCExMct42YSwSJEQQi0UKcSn4woOYhMQggDAwIYPnime--uplWvu3ZSnBarCSmUMAIgbwsAgILyinCCTUe2YYAIAnEIANY-YMKwu1cCvIQd1aKyNQ1ClisvSZDzRX0SzEm7AKuxniCADo-7_-V3_9Z77zU0fOw6GZo2NufTvv43zaMqmP-OrtZb27sw7Pb7flZq2Po9VXxh0AF20O6T5evXg4ruvSmizqCc-nbbhhwLD9xYub73zy4dPbyz52JxjDWlPbxt3d7brqdt4AaYyeSa-fTvd3d-ftMtz3bizcWDxiWRpmug0M2PZdpY29e3gm7PtWrzBkxKaECEDunoBjG8XYAg9mEZF97xEuKnXYQEjmQnubqqYbIALl2K3KixkxucatufV3-zskVm3hI83aomvTZVmeTxfR5j6Y-HhzuDkeiGgb4-3j0_PpHEjb3jMpIhwyI0Q1A0_7NiJFycNj2OPr0_F48IxMWNd1mCXQcGuteeR23g1xH6O7M_KbpydtMicdAQXovLu5_eFXn9_f3K_rsvUhB3p-3oiBkj2iHZfHx3MCDHNEQkrKfP_hviGfo799OlkAEvdRA3L3YZmRAX3YsJGZTaVGcEXfNjc3Z1GzwSLdeluWRLZtF5FM75e93siFfzUbIq3KWqLiZsTiY2RCpCNKRLAIZBDX1cJ0bdE9ISPs4cVDUzUHSNBGhPR82Vpb3J1F9r2bWQl2im03-vAxzKPe6SRKhJjRhzHTvm-E6DGVqemBCYI09gGZvOi-7zV1m3zqvQNk-ogxgKCfR021-rYlhLS173u6sd69gqzxftKM62TW0WleKAWzcu013qg9aiAyUZv8jemlyOnmgXSLmQGuqitSIQ7LvHtt_GEdv8rNBQGAJdWaNmOqXVbMVUEmRDixhoUQzbwyTbflLGu6158Tr7nzd5YxBCIpvQAzCWKG-7STeRATeAJkUXXLIJU537XMzFmU0UDm5Hcw6BlarAHrPNKUIoAYAAg5zGccZvZ-QFX3bU_WZBLEmsGnV6GxVD6S4VgpUgCILC6viFjxEBMI4aDiHjVWYZaMZKKEqPcxVd2ZSMvlNn_qjEVSgVyaImFmtra4AxMoIESI8nE9rKqY0Ba2YaI8zBn5uMq29Vcvb9rSdGndvW-Xt8_npbVFlJCRypRMERmR3aJ64wQV1qeiQ9ZtyT2L43Hl_qMXJgjJK5Q4s_KAVy1wFrggMzKrilqvk9nhhSSA43ogJOFyfqWoQHGeAM2seNKV2GAVRmBmrQO4iAqXDY-qgA4IECLq5sdjU2IRpvm5ggIFFV6jPFjEJE0as_kM-JjXpZojojquOHm4IEhCxMiIZEWKLAImUyOB3IVZsPyws_tS_0J1XqlhJxXyPIKIGJkIIrPq-2X_KdnW_HTOrR0SoRBDvTBUco75oWD_BfBFqmbULNxUNGvWEGqufw1lQTkzymj2juM00-rXaNdUaFz9DeWPgJoyViIGi08aEZSYUME9qBG-Z1aSJ2KKsyo8d-0XBANm0egQWZiuPNq6fxLRUiXsQCJQEgSKTHM3T0-wcEIq-UtFGAvoQZjCRESZaBEsxMg9gkvzhGQQlBTTxuUTUAslN0GHkILjATCQxWBhD1eWPgZhkdA40qM2ZogJIICRYTZItC4Ge3ggO3i1ZPqoGyABUZATMzNXAwcwUSgCDm3ZrXNhXZl235d6V0nJ1pMQPWHi2hCyBD2VDyDwsIUPlsbE-xjFbAkCL6h8yZwREJKRKjeEk2Dg3_vWh__wN_7J56-fLhc73tz2yyW56UHffrFh0u29lnblvQ8e7g-67_3Fkfbz-eHF_S_-2s9--1e-fo6OX70dtnvEenMLnH_4e5_9-Kn_-V_5zsv1KLcPN7e3kXgrTbTBqje3d-urm9v3XlBbj7ermaNVQ9ZF6_SbQuwjhCkjuIkIEmJE1AM5zHn6JQKFi3eUARnOxFXWKnNLPRrKIqSs001XkocEJhq7I2KGL0sb4UnAie4J6EwUkazi6QTZh0UWUylYpe-WiZUX8qCK6CDkPoayZFQeLNCnGry2eYgZEene-86CEBiZCMgow0fhXyBcWD3tnTSzGmtlmAeA-r5Vdk9rYQQYEwk4V7vzTe65W6-vMkwleT2SEasLVIOTKjVZQIBFLxpgBqBwZf_qvbk0jYitD67akgVMZwt7JhMgJ-zj5W375nsf_I__5r_xz37n99eDsJAKf_XmLTO_eXs5XfbzZZy3sUd48m5mmRHZmloftsfT29O6rp7BlPu2PdzeEOHt4Xjed1l473a2rsLPTydz__nvfvv2sHz--VckcN4tIKzvT6-f3nv1oqGQCKkQwGZx3vppu5DIPsYww8xlacIKkUwkyJf9jEABkJi9m9kQURKt10SYS2vIso-9tWZm4YOQgImJ2toycu9GjBUzLpIhINowJMgoXToSIiMgCCGEmWpxjTnT3Uy1ZQUNCPfzRbUdjgcbth4OEH1Z28263j7cMNLp-XLedtuNmIml98GC2z4Q4r1X92vj5_O2nTsKHm8PT29PjRUBWKhbchNWVJb0HDYicriFxT4clTLRzCw8gVFodCPh4m545FdfPf6Zb39y1PV02k6PZx_hmIsQIp2eT4F03jaLcE9VBoBvffI-In35-AitEbD1ocrbtgeDDwd3c0sMEQxPRh5WFapKh6Knhw0uCVlmW1aAhDACMLOIAAJBUuXMqAJiHfEjk0hFmypbH4QYVjeBZGJRKbwvCvkwH2a9t0UOx5sIQ6r5CFf86LAskekZBNiWRYH20ccwG9VJyuWwuHkAIBAjVyf4HXXTI0t8A5BIFBBe6DwPMAdKNyPM6Pt2frYcVTpPGzlG2bdn814YIbg9fIAEmVFW6Rk6BxTWzNIuEU0xmSckENfMHiEhrVywM34DUAzdNCcmKPtSGIpEWr35KwLBJJPbj9fwbLljiSOTSa4oWZqUnnx3biTElKuTa-ZucwJnIkKkAQCWWLRsMLoEzARIJhTAem4NAJBASlZAAAEZTlwgwUQiH17R4_mOhJqtZl2ZCDBsIErNgHP27ap_hvWfCBelhGChTMxEFHazZIlIqZNQYXAIhaSu0QkhrDW7y6guSmpbR4xIFOb0RCKPuXlwq2QQJgQiplCWc1sUEHK4EFXWWQjXtWXG2hYkZGnpY2nMOvFuTLy0liMeHu72rbeVPLLG3hm5LtxWXppE5MLy9s1jt9GUVVXrI1H5sUy365y3oK9V7YBMCGbJxBlvL_bsvPbh9EBlQT5nGWA6u65ysOJ_zOoF1NipVkDJKkAyE-QACFfW0zttdV5fj0LEvKgGZIQjVeuUZdolIRLGMFWuv4M0ERUWQbj-ohMnk0dqWo7MBEgqUqlpmhs7pBJtTfPXhCUUfXwKphkmGx_LCozCdLM05bn6vf6Mys5VinYCiGJjYgKjIBUOf0bVyyhVgxbGmWGqEI4I1xeWZAYZmJmYK51FBJUonwsFwMgqts77QwURMrOCgzO_hUUrA2HOTK59XuZc3pUGrv5t6y6ckHH14l2r27tbODJwQtmdss67WcVuj0Ao5e01DR-LaF3vpX7OEHUC94gIYCIkYNagTA8EEEpmAoBAHN3mZglZWGpbLTQvW5VVKurxjFsCpgMyRaYgWLxDWkFghpc9vUBJ9UVID2dkyyAGgjbNdjC3RkxoAB5p3aWeq7ObjW7IKOZGSgHg6WUeTEB3E-LwRKbIaKLmKUSNeMalMhkpoaKaIEzm3nQJN2L2ME-AdEZU5CSIHkAkzEqCyMPMS2aLLdPOY1PWwByQ4SnEQOU2kblFQ8hIyyCqdkH_5e9--vf_wW--_uLRnC8OdHjpoXyrSsuytPX28Pzm8bAu5mN5uL177_6Dn__0p7_9Yd97Epwu-M1vfOvlJ-8t4Y9fPTeVsPS4nL768o9-9JO_8ld_9tX773_91c0v_-zHf-47H_1L3_34_uHmW4f86fdu_7U_-zP_5i_-7K_90vcO98d_9Nu_RyQqzIhmbsPrDDr60LaMrReGoOgXkFUhQQtnnvbT-qNFEVIImKUeKFO3PHzRxiLXIStwSTRUPHK7jMOq0d0z-2VETveMmyuLZ2SkjyjoXKQTIjoCwDATZiIeaQggxBGuTepVxjyNEEDs7itz33sYhDkGjHDK8n64jyy_GNYrT8QziNjzv9bWmZBUuH4jK9NLuxkyM-s-rJIPZhEV22Hatr2p2hiV7XMb7u6RQKGkURmEmARPVbH0RDR3VsmshR7WywuTWMVGCFFEeB_L4eDhrIwEGZ5gIiwMT2--_D_8r__nX331hiFfvrrfnvemtB6WfbMff_WIACnSzUnk6fls0yaY2nSMcX9_fPHyNoYt63o6b-etAzg1OdwvY-SbN0-XvWfA0_PZ3Zd1YZFVFwc3i8--eHs6naS1bd-_-Pzt-x99MNxO5-3p-WKZ7rG0djptiDh6p8AoZYqwNDWLN-endbnpboXXrI9ZuBNJdcduDsd6KbmbmwtTjIGsNL2QZKNXFh-5ApfiMSpU7GH7sIBkFoT03qng0QB5nadp0wAQ5eiDlVl4N-tmQRxpwkRB3_j047dfPJpHYI6EBGhLQ6LdbFn0tBkQrcsyMl6_eXb3AHi4uXn79vzJRy9Vl20fu1t4JHN47GZ92PG4FprMEvoY-wj3GN2WVZu2MTwJwnMb-826mtsvfPcbY-yQ-HzaP_zW7Y9--BQAh-OaAMMGSzufN49oTRDza--_h5ZvzhcD2vexb_2Gb87j3Lc-j44Afeu2D1YBxMQMcyJiEnMTbRHBLBGBSaiSHhFu-76ua5rVGjzdIjwAWCUyLRMi26FhuYEjGbU6KuFxWG9sWFV1w9xtFIdn2y7goasO60_PlyphR4b5PA6otr53Ity2XZgKM5ORY4x68mhbML1eTMra--42rHxd6Zho5XuB4phH_beNYFnscklw2zsCpPk4X4TRuhHjsi7hVhM61vv3AYKEa9-OcwyZ7p44qZ6IRVCRnOwzfCefQwCzXsewIryX4YyrNFHIHzdEgAxkQmRGmQ7UuXbkygQwayEFIRCq95Ro5nXHqEQzXfPPiDzcysladG0WJm4QTlBJrBqtsnsys3mytpq4ISYRW5neLIhwyqUoARwhKKPwsNM8OCfNYJaeySI8R8il30uYaFlg4XfOY2BC5poIUmJGolS80iEJ6-2UQIyoy7jskJBYUVQqSAh62RWAWYTI-kDWyWcCQJaBGebCSAlVASZCqxgaJGWUmrcQpySUmU2koSTAGBsLY7mkiZB5bS0xlUWZkiDT11WURZXDRmTe3x9tDCEJDxUlhLdvn8cY77-6uzm00Y2uB1aPGDbFYEc6zBN9ATpreB_1lAbG-pike6UVeR4o4V2tGyslORP8PuvCjHVjxIyc6ClGIlRueD1Z49W2mwDl-CpyCABo03VpFNBEhQuBylJ680XqX3ZpmgAPcgBGFW5z313gqcltBOKcF2ASxsNhWUWVaF0bAAUCEkckARITYLLMzA7NcdksN6dPOhYzRua6yKFN_UHxsmtdNnlbhbu9uq4ICGbXdqr1KvdNSEzzIFsNn3eONdKq7UN9IevrhZCERNeIOBEjJpeeB-tviLVPKGMG8aT0UNFX63s7c_sw54JXanBEIoBHBEJVeL3AXUAxeYYzyhQFDCEKzJXFIiBKT5mIWkCtyAAMRox3UK3ZnyiGD0amIM11c_ksIwGAgcKzHIR7GKOW_jsBAbPJQhSEXBS8xKhFZQVIK_IUlEpUU9hEWFCvVBmYm0yqB1rUubLBkpwRaehMwFcIGmTFMOhKwSrabCBSvZMUODCBMSy55MgZVYyetzuEVmSABC84PTECuXsTApgWaAYBhHBDIPMhqrWIQvdJ0pG554kILKNnRMmQI73x4mkVGwPI8qbXkz_CpsCbUVgRk1GY46c-ffEP_uE_Oe1-eHho3_ulIy8t7Obh8PKTj-2yNzKE8dVnP_nsszevXz8_vrn83t__Z49fPn3-o9ewjdPT0x_96I2sevcr33q53Lz90Q-p_JK2bV89_-2_80__ye__5HGlsd7Sor__5umHA77-6u5Xf_pr98fVDH_jT96893D87rd-6ne-_8OEINR0r3FBQC7HhcJXaRVXZOJCAzGSZWgTZfQYTJQZcFXSsmhmVK2CCkSBXPjqelw3kb2PpbWo_j0AKgire5TxOR2AiwISypKRFbUilD4GBgUEQCgvkXVtZYtEBgYkFDOrgOEIj6QAF0ZRAQQbzsqeARCNpPuozUCkI4KQVvdmkdXSmLmKz7VFaNK0gBaBgCmiBUpGom5969ZUItPRCCnNSXF4MoB7lXiSiCuLWG_VTAjwBGzStr2rcIGW0xKq1VNP9QCsYZhwYmCS-VjWpffBLGkAQB6hDEyxn87_4b__7x4AYZgLfu8bR0Qangj5x1-8ed6SG_3487eo2rtbQjGRlyZjs7uH4wcvH45ru9jezU-XHSKXg3725QkgEbL7CM_T5YKIBAwZ97e3L-8ffvzZl5dtk6Ys8vz4_MlHH6_HgwjsW29tAeUAPD2fQgiB3rx9I9IOS-vDjkuLSBvlJkiADOsZue_D-iCRvneo1RPLhCXX4Wkfcb6IaCIzEzCFmS6NMjOgm7VlGfve2iEyIiMJkCUipPIjEAQEiLqwD2NlXZbLaV_vbghBlhYjMlNacx8Qdj49f_LJe9_42qdtkaovnodfLj0ykFiaMJNFesT9zeHmoBB53nZVVpUa9CxNwqG7JYJbJGa4D3NA7MO2bQ9Mc-t1M3EfmxGjR2hrSnzZRqGHYVx-4ed-yrYgws9PZyI4PY2x9yBoy2oZY--PT8_1iSWir3_wUlme-h6IHnk578MuTWi4C3KAj92YCYDCXFWZBCKICRCK9s3MXgeYileBg7sN03X1fSdCj0xzZK16ejFoSRQSDnd3l_M5MixGhBX3hpmAMbOo7zVdMQJws4R4-fKViCale5hZW0RqhwD09vHxeLNWD3K48XRfUoSzUJoz4Xpc3WIMswiP4T5fHo2JiNzH6D3dM2OYM3PagEw7n4icENBCRKNfMAEZgZJE0pyE3R3TWe9e1cquQH71sS2fz3TeMIIHNwU3Fg0zYsXyarmDOxFCOkGEGWSSMkRCOCHHtZ6LRV6maT1FpCQIh4oo1LJes02PLgjyrPWVzK7mjHWGzgIWkUwSI1UTlyDqEUQziE-EyMitdGPCWoyLgo96BqsUeAgBiMW8xEGGCESFjZtgVEIu-AQIsijGVTmWUbJaKCtMQsbky5Koz50AU7XHkTInxhQDEJypZbgjW7ioMNV0c64zALK0qAnAhBGuqkQUGaIMxY7wTkQHVo9Z-yRGrzpxVnyaAqCtmpmkAozhwQvXT9m2EczLonsfL-_u9m14uLDIonvfkVCREZMA3aG1Bay3pSFS79bdzv1SZ5fhpesCbczMNtwTfBiLIBDwHL1XpCTfuV6vTURmgpocx1QxF_4_ISunUaPnmGK_yYmqpR5d2Tj10aoIzZVuD4hYTKuqh16xlbUJ4aZNRerszkQJwICsKEIRUNFbJgmCmu4VbJEIKychwpW6rlgIBWjTtTXhEoMwM2YB9SGREaikWlnhopJ1EVNGAqGqAAMQsrIyNoRFqGIyJOV-mvXZumZXMiHnDwqnvqpu61gt6tm8qUV_LaUYkaW-iZWJqtk9cME4EQFTuGynHOkVs5t_WWLtA9_FkKpwgFT19FLVzf3hbDbM720dixFqAQkFpIIAyCSzEm5TBABQZmCisCQCBACC1_UJ6DIhUoAYBXchrH5zcQDm5YhIoFQ7AIkcmRE-a9xEQJgA3cLcBZu5C7NDUlEzM5BprlAqQUXIVMoIrMXjiFkdLliCp1VMqZzEeBXYVa22ZHxVR4sMpJbhGcmkjgGEC8k2RvE6IdIpkcttjIriGF4kn8Bi_BFxErkbMZVGLTLqGAYEgJSQiUFAtWVpTZDIhpNIYlLB2yKZOBETMQAmuguRiSzql14hodqUJiJQgiQXxrfuRL3vgnyt5kwLHpKE9W99_Oo3__E_u7if3nbSu1wOrx7uvvriMyK4e3mz9TM0efH--x988qGPS_RzU7hs54dPHp4vZ0y9uYmv_uSPX__GH59__JlfLkEwLJfDAxIiRTw__eiPP_t7f_yDPzz73_jGN7_z4XsvHl4ejusPXr_5D_5P__f_19_5u_-X_88_-Fd-_c_-2q9-7x__7h9CBirXUzqJ0qIdVhtGTKX1SaAKPV4f9vM7N82QmeWIyIC5AIcIqCtSEmJtMdO9tbbeLH332g8g63BHgql7r65LArKU1qvI15ngmZ4R9S1GaKLdPMFlUZpVHMSyHNSQAMrbzSMCGYdZQJgBAhmgeWhyJgBTIAlR1ucEg6oIB4CQwno1jM7HqwhnJACPPlQXM1tbG2NU_tR2U5bRDQiRJNJ5Frai1m61mzCP1tbp7iVKc2WJWvIRLbx4JJMWQBmJe-8IFOmYU4XLwt4tOZVJmIef__pf_5d_5XvfWhJU5fWbx8fz-f7uZu_2-s3p9Wm89-md90DS7bI9btvN7c3r16e2oC4NAShybQ0gnp4v22YPL24OBzldtvdf3o_dCNkztm5IkgHbtgnrsLicT5h02bcmbdj-6oP37m-PH37y4RefvQ7E58tZmwLIedsjfN_NvB9ubp6ez4EsKjYGCWVGmGemD7trx9PlUuwHFnGfwXGW1kdvbXl6-xzhgIEJTlBpzcgES1Qebne3d2ZDRDBDhZkFEnsfBMBMGelQo5BpUCWkyrUSQ1NlJPNAJGZOC6AQoH_5r_6aACUECRnQ67dPqjqGZTgRHA8LIR-P66raN2fhYYZAx5vD83nr5m1dnp9Pl_Nm4dKUiPbTCYl67xFBTKfTxROG-b4PFiZEJlImBDKz3V3AlsNy35Zvf_PDp9PFI794fX593jJz27tFHNYDCumiP_jJ5yQ8zB8ebt-7PYDl1sfT1vdtDx82hjsgJSEMc6CKBCQk2vBF1WxMMp0ZCfsw90SCjMjwHOY-iMiGsfAYpitbd1mUGMcwZslMVS1ou3sM657ufdS7rwCHkNj3rZTD3j0KKuouwpUeHMO__vHHp7dnFDmdzmYmWu21LMa_WzDLRKu5C0mW2LaxDY9hCIEAZlaerkV074OFRRQYY7geWt-3cH-XDshMgog-kAAyzY2YSRVK_pPJ-vB-zRgRKTOYKcuodf1zQeIs_BUhmNXNa7Rf5L0CXldEJ6-ZBagA38R7zKMCZiKAl6eJW00NixhGiEBBRAGY6AiYOdstEAEQRA0wrlFwnIxBqCAEZwKzEqJHB244dcKY7-pp1_-ViLIm6ziHykQFgKtGI4BnYXcBEbVGm07CkUnAkJgE5meWlWd-B5C5zruz8spco3dALFB9hdcRKQByBEYUWzspATkyWJCSw0cZi5CyIDjMmpAsCkRuXpAoN19aM3diSE9DV9ZEHGFZe5IEyhBZak4d7sVE2vYuzJBRFe0mWvU3YUoAEY0wiDyube-jlhhuposA4LhczEKaEGAi3T3cnp_382UjQQLwfT80WZRFJBNJGKEO53WwA2A0j4T5dfEIAroS7QvnPWfdSIg0-eX1gZx57sJrzDLIBMjWfeEKgaxu-mSATGphZl5viVWiAkhhUiQVrf8LCary_EiX9hk5IaVwSMxMJMJMNPs6Bb2RCVgRYURaF1WRZVkIkDJIWIVVKIcDgiDcrPxwc7g7LDeND4ssSsOnr4CREVEFOFEotj4OKisTy4TPzN5BpZoikd45OygnvTHK2f0OcHi9zgfgjEjVsH9SL7NAtXWmn3PBuk7PIBeUTyRn3RWhPkjXWvO7X91k9legmBDLbF9Ff4csf02dpSa3PRORpq0CASgJ-Xrxy2Kr12-OgCyiptVRmIEEBkwzx0DkiPSIEqvnxNoECllEAphn5KwnZQYiA3EZea-bQCLEACfliBQiuCqTi7PsZRS2WFnHrKNTFNoYcQyfzmDiSJg5B8jqeYcbADFJQPm5ISEV65E3P6sZ4OkBU6wyuUuAw6p6l0gQEEiUdXwkQpYEB-KCuNcoKBMyckLQECGSEK_5LgJMYMokyBDiMYyrHI_kkaIa4SzNM8yDrsyoYQOquMWcGcWWpRoIYUaEihKUxACgLNdImEw5vvPp-3_wB98fkW9eP_t6SI_-XmO5ffujz9rt8f79OwdJ59vD8ad_-rsffPDy4-Pdjz47Pf7k8fzF-fknX15-8qW_cbY9T92TTl-9QV0svI_OTRPjZtHl7UWZ_5u_9j1ejl9t5__N__n_-n_8j_-T8fb08tMP86s3f_s_-Xt_8V_61b_8ne_-3d_4PeKM1OFGiKSc6CrkFipar61lXdyciLTpMKvTuqhaGKGEZwCyUAUER3dEQibGejhoXaiW9UCcl92IUqlI20mEbpaEaZmejFQEQHMnZocgxvTK1xUH0FGoNjz1yzKzeuCYuUjzCMbEwIwAQu9mw6tGxYxR4yFmy2BVIBhulSMGyEKSWTgB1dWOEHzuviEDiHmka9lXMtxSRAyMhTlyTQxIo2DU8ODyfAMme98Hsnjm7g4YiGg2MIFZ7DoHJ8SUavw7N3IzAEBheNd9ivqEMwlS2LJKuv2v_sP_2Z__6Z_y88YIp8t-2s7vvbhlAEJNlM0iiZ9Owywtsw8TZCRcRFYSBTyuenNYnx5Pbx_PkfDppy8XbY3btm0q3IdFIrJsezfzRVWZn5-e7g4Hc9v2vvURQO-__4HFKOxznfifz6dErgvDbNKPCMgPPnll5w3czetUB8OHED2dT-ZuEevtwd2ywGlERLTtOwAkObhhhGWKqhB6uEeySu_9cLwJH0g0xoCcX9hwL2b8ZNuJvFO3L9rasvYxREVkAQBF3t0PtwsvrEII_m_9G3-dzC7nnRiH41dvHm9uDktb0YOJPv7ovaLdVwXsvO9cP9h1Dfe9-76Nvg_AHLudLzsRfPsbn97cHB8ejo-nHuEFkd_3wSyXbacMISEqfVbue9_Hvoh8_uOv_rW_8Zf5Ms5bB8HH8-7hAGAj3rx5XJZ2WA4OgICnvq_Kq8hHrx4I8bgun33-FRM9P51i2GnfKGmYAfG-7W1pw4yYWlMWYqR9H_UnF-YaRYqwj96WtV8uRDT2bTkePQ0jZWkIpMdGqlRwaHPSSfzY946QJERYo4EgJFkaQBCR28iaiSNFRkacn55JGjV19-18YeLHx8flsCAxYT69OS1ri0gSBgAr_P10QrNq670DYmCGGQB7GCGne0Ts2841Uce0YW3V_XyGjLH1GlC7BWSkDSbEzEATafs2lsNNuiUkuLHefzCHfJgw9elAVy678AGuZLtSOMUcGUrBI-uNXj6dhAwPYs5qAs2BCiBroFOCsLoZSCVsObIEbPhuABCVjaoucjmGEPiqEEgEnNM4AK83dZ14A2YwmVEUErhuKYjIxCxmhjUXKTYRX0uLFbyGJMawIIQCUEL6HM1mIBJG_aWF08J0Fz2COwvXrHG4sQpAlpW2cvBYZWpBRPQEFknMDJCmyJQBoEyUJWCl6qmEzTx0KaW4eIPoEXX6R65XMgGgFzFANKDidk4sCVFm2aU1G0NaS_ey9NX8eBWO8KYKmU24gmhp2VqDDE-PkSTa-ygws1vuu1fYHYUss1g1xclmhNZEKNeFH-6Pp-eNVCKCRKjQM3nl9c-jYbpn_XCqMQlFqo4pevOIiYe5Olk9SjtVcjG8DlXnTaHyM-6lpn83Jp9lEYiYY21EZi7RQQkUmygSZwTOfzeuEZ2qEqEq1z-xsuFVwy0UDxETU6GlqnVa6JvDoS3lB8is9OHEFTG2RY5Lu2mqSEzCRA0RAc496g-jhDcLvVz0QDMKcndQZXI3KQAlxLRex9WijBX7AQRwD2WOmbCfO5Ca2pZZgohwdoZnPx4BhbhsGFWLwLpjXP3N-aeZ_ZnEokmrLFbg1CrM38P0dmHiFYR1jenXFKI6FTVCTUhLp_kLLT_zDFvX9Yag5HHgAA5Z5QOLtKlfCkz0gmUVFtG8kvdesSIPBPTq5mPVeWpTVZaSnO1PooC5YYNIBqpitGdoKzBcASJBhSxiFJgLKv4BkYGISjzVy4QR03JnRQdDJERPx6zHWgrg8CmAC8xiNZh7XW5qSbr1oSqeyVPChhaT2VJrx7CkWaop6hfZGMolCgUSno5zQutjUfWE4vkwojI7Rm1X0wAAWJAnlMayUGZV7TKrEHnl4IkkAR1CSSM9IQKAkdGBSRwcRWYRCzmsf_PV_e_8zu-fz9tPfvxGmMLg_MX-8P4H3c4_-cMfw7ocDsvNqoloGUjabpdv_Zlv3THevljXV-9la-OyrccDHZYkxlUwghmS8HIZBMvTm6dkfv3Dp__0t37_P_5__p3_2__j7-Sb7RahG_joIG1p9J__7f_8L_yLv_pX_oVf_X__f__LQ2uRoUIQsG-9lCzmQRWUyigT6lwS1icKiRATozpwNZaBhAl2uz6auAlg-p5L0_PjuS2SgVhkXiQWslG2cwAkc-d6_IrURyUMSGR6tsOX1rbeEZORVCTSlZuFCYsnIOMYg4g8HRm3S2cmFnAHJix9EyFlRJuaWBAiJUZIDBQWh2RiRs4IynozOta45JrgSaAIsO6AGOkInO5YpXzgPRzBGRAgLMITGrUCC8SIurdrW4ftjMjAwDhxSpjDPIp9bl204ZSOm0w_IIUHsCuhLLSQ_-__d39LTwP7IEDSRLAmoiIPd8u6rH_y-eOIQNbzZSup-b4PADw0-eanH90d9MDMjb96PJ8vm64a7o159Lw7rKfNGHIMp9a2fd-HszKTnJ4vH3_0wWXfIKngwsfbG4DYnjsAWe9VHfSEYYaAe-_bud893L968XB7s97frC9Xfft47j2QyNwt3c0vp1OEt6WRSh0zinIOjEUeV27Wd1EBLARTjt1VpYiCYX443rgZA5g5IQ-3NMeEZVn6GNoWcIMEKpPcofW-UwAKI_Hx5uARSew-lqX1fvkf_nf-2w8HGd3XA4-0zz5_W-0wXYQxlyZvT9vo3qTmcXDaemPe93FzOPThFimInnG4XZ-fzz_zrY8-ePWee6wH-aMfflEvhNFduCUhJ4VZU7X9kkwREZNfScx0fyt_6c98J7ol8QB883gqku-6NlL2yMC8XVu_7Oetv3i4PT2eP3p593Tpd0vr7s-Pz4L8_HxhQWJmEuJ0m1CJjEBuU74kRATpWfHVCEfCPqxcULZfVNT2XVrTZTne3OqyXJ43JSLhvvW6CkFCRFjvXCB59_QUlRofINK-bWFBmNEtIbk1HwYIp8fHfd8x4XDQijuPbbu_u01ERDbrlXzOTNVWZI4E6L2LNnMzs7QrDtFixo8hI1yofAVQy2GkTCu_VoQHclq3HIMIPRyQzYOXJrqYj7EPQmC5f79C1nNtnQAYE-YTNXjKdCPl-jTGNbxfUz2UyR50j9L0VKigEmmQM7BRUYTC49XTBCfAp8wXSUBInFgSomnCI5KSICLM_1SMGaJafKGq81-DYTa5EsETS3eSVKpUZALE8EHXSnUFdsoNHA5AQEyZjsJgRhOhAvVtZKIpMavoLoDU5c9jQmyQIrNg2FUiqQYwMXuFguozl8GtJSYQCzeIWtprRkHQouZDxPW3QXBHBKREIGpcXYW2tExzd2auUWbYYGZhVVUE8hHregBOt8SibSIsy6Hvm4hmBDOty2IQqi0xEYEV1mXxdEhAwaQEDwtPSwA07wkwLLTpq5cPl31nwNFHYW-WZZHGL9-7T0ARak1VGIkhUbhUUxhZdP_yUyExzSwHYzFYK6eSkVg1ypl0r8NfWTzgKp_CK4KGMmccDK-d67gahxHJosybM2VJBDQtY1SJQL12XifBB-YtBd8FypmURWQ66oCQGBGAmUSnzJWVVHVRXQ-N3KqrDzkzTuaOLMqkSMyUgMTX0gJlz7nDWpjujs0jmbitfGwKCVy5hYyM5Cmypjpwz8b3JJ4XjbeSyZWbgpinGixW_zyTIzapyeIMUc1U0ETz1K0J8BolAsLwYLqKuKnuM_OPONsZBDDhqhAxL59l0quDe6126oIHNA1oc9Y9f43zn1ut-qrQBmRW0yUBPIoaGYmYdYF0TEpGz_RxJYDNE3Milt8DI0JQaqGkuFgazwp1wVEBgCt8QEQrLsQY4Thb7BNUbpFMBEUvzKSyCiARcF2VkgqAyjShVcXmoaqx40yJTDOeZxJzmVCAMNxFdEY7Ej1MWTJgN1NWy0ioBGoQEng9NwtMzImJGJxYVEqkuaspJkj9-mQWtuceJzIA2cyYprgZ66kacK0rJRGqMALNvCyi8gKzZYAGQYgiigkWg5FK6lkmjqy1nm3f_fT93_39P-j7RQ6H9uL956e9vVh9bB98-vL-0w---vzL5fZwOBzuX74afRfCx8vz02lv79-uDw_y8j3WRj2353306N1lUTmsgIjaZF3Wj-_v33_Rjgdgf379qNYXwZ4AiyJHj6gENpD_7b_9G3_xL_25f_3P_dzf-bv_YD0cBpK7tyY0I6LEyotqkfUSkBkJySOIeeHlgNzrREzYSIFgjERJrngQoWoF6GM9NshICF2auyMRo9QsHKCsZEZcwyBCYCYgpMBIRI886Fr67QRgFQxAZPeh0jy8aatMWh-mKplOwnXYgwQBGp7lfkFkrFovI6HW4owgiWdyLyLRkbn6_2zZa1oHCNaz6RLgnGERPlyEA8AzRAkik9XShBCBFpJRXB9KtyGC4ZGejdl9YmQTUkkSvEYsBzp4mKBWjA-RvI_K0I7uxEJcRYsAyufPvvrf_kd_y9-eV5bT83Pf-uPp6cXDgZMI4u7mxjGe9rENO1_2kVeRC8JR9Oe-8zUZdnNczqezI5wve-9u7je3hxg2LE7ni4OTkIogkW093LSJjXF3dwz342Ed3pGElddDOz2elpvj5Xm7XLZL7yMiMskDCc-vn97_4NVh1ZublYg-_8nrp30j4UDqvffekdn2oU2X1nykqrh7DG_LkjEdjUwCWQJLB8tlOSREmV0ygKYwFDOi7701TYQIM8vEXLQBoY0uLMLqmcrkFqQkKr13adLWG3dLiOOxQb_8u3_z37o7ar_sQPnm-fz2zfNp6wUb-fa3PlLi59OlHPLdxu3xZliYdUy7WddF-Nz37k4Me-bXP3r1-LR99PJuJL5--_jZZ296t0oRA85Y73Y5a122Kc7njUQjLAkXAJT8H_3Nf_XxR4_7SLrVH3z2xbb3se_bvt_etH1kH2P0_esfvk8jTltH9Pvbm1e3x8vzxpyn8_Z4Ouuy7Jceng7w8HA0DyaqKkKmszAC9OGiMrY9CEhIRJAxMzBq20dEaH3TZUXGm5cvx7B9u7SlefjoFu56WKvjMvqghHSHqKdGIGu4aVP3MaX1cR16zcOzY6aP_vbtczsu3cbrz7-4PF0Ox-OoPVGknUbFcnL4YWnubmaQaaO7-9qaRW5VE80gLuJcuGcTrqMSq9rYRcSGgQeJgjkJmw0pJAoJFH2nzJtFLkRiuXtvfiWLuFkLwUm4r-cXIHFOuhgXMA5rXgo5ISGVfAUnIiCCnNQwyGACcAdIMC9TKDEDVQ2y_jZZpyr3QTg5HgTEzICRVtyMBOS8ct_DnYSncg85M6C0O-YsUoGCyiUUvyM8ZmwDCcqXWeekckKFVz-h7LAF76hkNkQQ1USnSgEAVBv_JERiziiwRpBqFgtQNSoQFUCiyOgW2g6FXCCatQcCcE-UBhS1cU4zgCjGCEBKxQYqQEOzrpCIYU6IBKqTuZYiOvH4HgjEzEps3bBOAJVLFixCS0QcDmtiWB_aBALDU7Ta8zTMImI_7YSJwJ4hImMMQGhl0UNXbefLZVlUWZiJFQ_rYeUWw29uj2YmqqIKMeFJc5RfsNfp4p0j4gpuaHnmEKtpXYyzBBCh-FP4D05y0zzNE1yhHHWeLJHHdP5leHgpva72uriWhinncgAW0cDSqtcxOfHK2gJGVRHhqvkLExDWPY2RqGx2IpnelmVhaY0pgAkzjEkQK2BSi14mQBaGAh8BKFNYBlYQzCz87rCosMxyLWNVnCtoXAs3JCgbQB0lC98PCFeOKiJNOG8V0Es5NmsGE_dXOOS6-9I1exUJRJjlRS82ynUUWmzQ-RdjTjdfXt0aiNPte6WIVMXQgeo3yHNhUyHyWkiUrg8toq7fns6EnlmSgSkam4F4GOYcbIHFCS9Cbx32EQUSLUoIDTWD8YBaJs3EE1ECEqBHBAUmIWDlFggxkaCiEURIGNB5ahjIuheuoYoE1WgXFMAEjMYU6UX19XQmSs9Ir9QfEVEWMrVUCclXYOq0ecSMLzKxeaFgcJgLsfvARKgLXml8MRCwsZo5Mjhm-Q_dIcKFSAuAG1Cp60nSKi1VRrkLItLTCjGBmSLi7qoaFVb0iATRMrUxi0DidUrCSmwZkWHmggw5WU85Cc_RVJAwMEUVIhH5fuVvfvjy97__wy8_-_Ibv_Szf_LHTy-__vDq_YcAe3zbMfwbf-bbX_7wB_vj_sUXn3_x-Zfb-fxwaLmdxEFVxbYD54tXh49_7gNQ0hfN3ZdliZr-ELsl9LGfjanp2oA4R0A1HCrYOwYhEC96WP6z_-Lvfe-XvvPrf_Z7f_cf_e5CB8AQwGE2x0bEhZp6h27LdG06F5OYVQFhwPqNi5Z9qd5v2KQhkVtg4TRnGr6-_RkJexgiJrgyQ6QQpdfHr2yGAAiimNHr8ZeEGRUYCyasN1lGEJFFQM3Ur_-FADaMiIMgIDJSkoYPFOzuqlWtqjIHIJKDCxMRuDszJIRHIpJHEgKzFKrfexlbCAQ8AwHKO5uckMlBkEFMI4u5jATl6KjqWXqGCpvbrF1WCrf03ICRLqI-TLRihGRmy7pmRGJ6eAkc_8V_-69__e7-vdt7Zu7pX75-zUJhmRaMdFzb82kfDufe3zxtx_XwfHq23pXomx-8OhK89-JOlZKoRzyfemIO643k7sUtKb19-yzcmLkPG7YDwuP5_OrDlwIkjO_f3T3vl-zue7Dq_W1jXi06AF72bXiC4OV8YaSHl7eqy6efvHp6-zzGeH779OarRyPch7fDIQA8nAjHbgTEojkMGYc5Rlaj93BYet_THQEyc79c5mKQGBK0LcMHM3uJY81EOC2QaO9dmtSz2tNVFZDS43h_N8YQ4TBPwLa0PoxYqCEhCMRf-_W_-OnL-8PaHs_PI2Jt8vTcn8_nuxfHY1tbk88-f9vND4flsnWEuPRxf3N8--bRwm9ub859B8zIXNcDMn7wcPf-q3tp3G384Q--KPG2PYOfAAEAAElEQVTR5dLr8X659N5H33uVXro73bTttBNQQmDi9vr1r_zMT7tnW-h82n78xePefdt2RNi6j4SI8Ii7u5ubu_XHX731xMPhcLxpxBhu77988fa8PV92Yu1uke9Y0wgI22WvMZgNq3m5qroZoSAC81I_dutdRMa-8douj6cPPv3G5XRab277-dl9XE5bIjC3RCCWnADWKIorVBYXk4WFpSoxMYaHR87lDV6ndUWoP7993vu4bGeAoHXp-760BYZx0310RORFtbFH7KMLYu9e5KwEeD49tcaZMXoJK9MsWMgmpSsyYuwdIMKtdunmAyrUgoztBhBEVdoCiL4Pbezdub38sGDwte6twiCUT6j-gEAJiYLzTYNYwqlKEggyYKYnZNK0i8_kT_q7amYiQFIRhQGQAhEIC4VWFeCiVUMkqxKwXE1PdZzIBBapOEPJCW0EMUEA5HUWHg71r4oEJGbBonP8TFknxrqYEUGBjIoQD5AEaG6EVD1UUim1U6Wpa1CbBCAclcagUsnajPiQsEiRBP0dcR-BhIEImAEizQFxjGCWBPKE5bACU8BM9bk5IYQFEWPE5JLMNhAERh-DUFBItIE7EDBzArpZRVFF1aYGAYFRRd8ZGEjZPVi0QiARrsLogAyqzEwCGG5I1QwLQvJ0bYuntdbKyNCWZdt2ZlnX1UYA4Rj28oP7pdHCeH93uD1qDPCA1hZtwpW6oDmWxlkbmR8PZspAiCjglsc8zdNVjlXaByHi6rExIVHZD-ekP2fYnZCm6qEYSgnXyglkxLWUSddwCmUEc3m4EjEjsyBtzIRELELCkKkqAITMCMRIpa1pBV0nFqHjoT3cHnUWBGquTkR85d3Pkeo7120tKmDOrFGY10VulyYIDAA5SX8z-1UFuwi-Tus9kuf6bV5XMjGmC6AoLvkujYPXXUFekX88R_ZVxr_-mKstnVfoEtbFmf7033YGEq9kpZkTmEuJKxfouuG7lhDqh-_hFW-PTHfHGp1WegSAMRkmYjyqdUO8hwXNc08hsAIBgAAj3ZEYkzKgX-3dnpElSao_AMFcrQN4QAl3JYmRGcttmpXNS4iyeyMAVyMIERLMQ5QDIgEjMSMgKvGJURslzPDJpiVizJrd5uYuxIwQlPPGFgmJTsBIgWDhlIgZAOSBHkYVfYZApIrQK_IWg2d5NBQ1PIcNYa3xAgAExNzeYAZVCA0VNMAxIDxKVcGMVL_dRBISlLqimHVprfQCdcEk5kpkWUQGeOU3S9gMiQS1VC_3hSIaZPcxY4VRtx0Ks2qsK9l3v_7Rf_WPfvuLz5_-hf_WX_r93_rJi7vjYb1ddaWxff6Y4P7NX_zmy-UGxuXTj15mjz943H_-k48aU3vaL19tdtn_8LM3EX68P6ZTZFKAD08kG8YI4Y40tQytSZgRgyd6GANihDInUifS5ea3fuePv_btr__K1z763d__gfJi7lhrT2HIFKIxYsrXGBl52ET3OMz6UKVFh1fZGglImN2ttigsLMXpjQIch0orNVORA5gCLSugM2cWAECYhOBAOZfGyHNpFhFK8_EVmI11hOe1DoeTpMOYUR66zBTUEZ4QTRWAk-vSXiMrJCbHcvxiJiRjzs1EaaZrv-RE4BGR0JSHZRMOTyIK9AMvNmJlDnAk6mEsAg6c4B5MhZnyGqMAAasoQERaOBIrFG2XMkMaU62vSH0YJjJzWUsFkRP6Zz_49_7mf_fy-Lz3fYcAc2VNACU-HNaHu5uqkJ73_tmbE3EbPjDg4Xj4-e9-7cOHG3e7vT1s5k_Pj2-e9ufTOQnC_Xi4iUwEtjBGcOuN2sL08ddfRQ-wcXp7RsC9b6O7RWYyEavwcA_Ey7Dnp_N6d-jdn9-eP_nk_W988HB7t_z4sy-3HuYugrzqGMMNzudTO7T9ee99N3dV3reNVaww1BgRAZnbdgFgGzuLVFwhZyI6zZObuCeVegiSdb7ridHqFnFY3bxpk0UxYrk9BiQzergFHA4rFpNUiIVvF_1v_PLP_fqv_oLH8PTP3l6Whd3wzfMjCm2X8TPf_kSRf_STL7npw_2decRwNyfI1tr9zZER3eL1m6e728P9_Q0z3R2PIvp8On_x1dPz6QyIffjeOxL0S91p0cZIcLd43i5tuRNhSCOBhfkXf_47H93dfP_HXwbzF2-ens7bZcS2XxZdkigiug0CP6q8fP-FI7Qmn7w6vv_i7vR4Pp3Ot3fL02nsZki8bV0V17UlTT0CIry6fbhsuy4iTfoYzAoBPjppS8SYpVskTI8Q5fX2bl0PvLR9P9veCZJkZuLDzLZeFLwww4mzSmauG6ybE9PYepRwPmcYnkQRqdpc4MEEl-dTIvS-v_3q-f7rXzu_-XL4YMomi1kshyUig_L50oVlmLWmY-91RmElRhoWurZqJGY6EXnfK1xNQhlePzqUahkAIrKK9SGLItIERVhQIcL57v3wRFKA674eMXFCe-rsUug9BCCVtFGYvHCHwEwrqg9CTAkwUhFEies-gMwcU7acWYU2xLRkFSgVCwBB5Ru4xhWVSJ70SIj6LYBHeqEtoVT0lMkqPpyYM2NmImoeKVxA-kKUQMzlBvKUEBMLJLg51sscp5izKixXZQHOAjOhR7zDerJw2cEKhUYiaUHEkdNXDGn1T0lEYglzKkFpUyRSkTJhBeQYF8VDbXwq5INYiWCOGWH3yEBWFmIGsAgfTJx1J0lQVYsIt_If1btmHnWRkFCXBhCqggTCxMzKjDP4CSIMCLYPIUmA0d3BWaX2UCxaf6NuhogsJQvCm9ubPrb7-_v9sn304vb-eHh4uGtN1_W42353e6TkmvjX75Cux868phRqsF2jRJ5emsIXFdCm-JVExAIMc2yac7v27sxHNc3NKk8TcRSsJ6PW0DXLJib3yJxnuGL2m1u1aRHRrF7QPIP-CcKSkQRUqZept0XkxszYmA_HRVmYuIA8CFmIniLQVkmDmIqbWULs0u3UEyHLPoEklVsjjJnUKEwklLyzmq8TqDnXE0CEUfdtvAJG6lJU08WCXV4bMiWiLhbWdP3O30hF5t5ddLN-oJOKXg_RfHcloxltgsKGzoMFRMXtcJJe629fSZhMIMqrw6DSQekxJ6RwvQrOO1sGwuRjZTqAexKQB0BiSTZyegnBMwPAMcdwZkQUQoqsyH8wSiXGWIFqko6BkMUJmwYVwHIFMHJEiBAQBIYwl3-aRJIQMLGwceZEBbKCKLhPYkTFjaIy1iyFGTAErnUpehBgnxYLCE_ChMpwFxc1M5KYGCJnFTPSItNmiZsTy_SqRX0Nh-JqFbqHYI_ByAi0h2UCRUHfra53XohQSgFOSIaJZpoBTs-EFJZyzjBLZApxxTaHRWVNR3cm9uHMSMyREZGKXAByStDWAJKYs_i2sf_cNz_-e7_x22-ez9_5hV-A0_gLf_Yb3_zwo_c_-uBbH3_4y9_72sNLefrhZ18-PX_w0XvZ2i__6nf-wk-9v1Lc3bb3X7QXr44Prw7f_PS9j1883NwIErz58cmjr3cHsBRlSk9LRcDIfhlg0d2hxvNuFaUhANLmSEnaWvv-9__k1__SLwDk68c3Qgphh2WNiN4NCZibZVAVbQmL0qjSLJ2AMpJVCrcFgEtbE9LDW9OpmkGoeC4Soju3pd4ggGBmyLXxZqG2-aBy3AAqLQjJiEKcDvVMMA8gFJapUMkyYGRPr_exlwwD0apEW40gIhEyy2Q0N6ES29QevVwlFJARycJRizti4rXa3kQUnlDSXGX3WFjNQwgA2cPNHT0JIXxu1xzqfhwIGIQHbgmeiW6GJNW6F2JwxwDMQCFACkgijbDatyQCYSKhpZOIhavy3WH563_tL3_88ubYtA87XbYXd7dbt4RU0cOxvXffPECETrv3CMsYwxem73zj44_vjvtlczDHuJztD__4SxBuTSNwuV1f3BzM4fHp7Xq4yTG-9vF7v_pz3_rkxV0DenV_fHr7HIhvn5-JWVvrI5Kpm49uw_287Zfhy7penk9m-6cfvvz6x--dTuPLL9_u5vu2E2GAbJceAdUZjQgfA4nSkxBF2TxYaLuc1mVlIYcwCx-7ajM3ALhZX_RxrpxqdR5FNSP2y9a0pWfEKDQIJCyHBgTrumzbZV2Psduy6OGubecNAKhRa-ruLLAc19vj8jPf-eTf_mt_-bRdPDNXwSRze75sT6fTelx--ltfu21t7_HF68fADIK7m5tI58zjzfKLP_vt0_Pz4XAc2_bBey9X1n3bbo432eTzH3_x-RePSeAZ4XDu-3qzjN2FqWkDyLHvASSsz-fzIogQbknoSPGv_vlfEZTb-8P3v_-T07Y74mkfQKAqzLz33o4N03Xk_cMLCn9Y-HLup3M_nc_f-Pr7CJxIb58e-4gob0RGRTCIAUj6ZYtIEdW2mJuPcbg9updcCcDdi7wk1C_9_Y8_Ph5vHGDfLmFme8cEFLZttFUvb9-SMAoyktd0KqLW41fgOIZ7uk8SDCISqXBNMdPdhlU3L4qOntndbD-9_uIrC7tcRjusx8O6thUAVyIB3saeGQTkhaNgTmQRJiLvxkzMnBn7ZVQhzmqCk1bnJCLSQAbCQu0AkAiTAOI4n1SVmRCc9eGDOnvXRCsjACkrn1GfRK7-M9Tbr6L8FaWt5faMXQOKLIgJ4VhA-Iw60HtGJV-RSqp8yPQ_ZfiVEbtUQQSIHAGAZGaiDZmCKpxNAAlBLAw13EoEQhjOTO6eCcyS4awVX3aq9JMwhkOxjiNJWtkMCr6BZRyk4hJgZpJqybUK3UOis2CqLT2IEaMil8Is6UBMCMCiSDPLjjOMnQQgItY7E1eQXVQjgwhJBBPrgIhzvK0qChlM6FbG0zrhAzJDoRJHQKZIS4iMUF09MzzSY11X6xNAxlXYqDonkg_jRZQVA7RpI4lMC2CGpipUTGEBClSOQg3GgOQEZIAYHgmCVPbBsfe2yNpEiNEHmC2r3i7t449fHZfFR9w_3CIQTzpnTehhFuyuBtkZw8YkJEapncNs7iJcU-FwjZMCICrxfFfVlr34ntOvlcIMOBfo1-E3ZoJ5XPP0V3IQACMlYphZ-DYMmRCQi_4pNUHG67kbCFGZMLOaJCx0d3OLVIMVpmm0zim6r8MmoGeUdg6zkJ3wrtucmdxm-yUjZuT-ikSiOYZ_Z597J_9CnQIvnArAnD-kfHdNz8nmqTsJYDVbEuqaNIvWSe9AP_P6g1Djbpz7gXe_hLkJnHnA-gOVbupPG8JVlgSiBPT6dURiZvVtchpVE3HG1AHRwitM5NU0sKg7A8K8AEMgBBBgIDDQxPkkHJhHxpQ3IQkyMVpYiX8zgZkYNTGBQEEJsXY7DtM5AInvPmx5baQEJMy8FZTGqEp-Uy8BpMKZyEQlaCxQADElBBIIcc-ou-015UaQGUiKZJkNqb7KiRiZTDq8Z0IkjugYRCgeQRCOBRfGxGChd5GtZCou8Q0vDpARBCDIkUiAQZmYykyJlqEiiNlYhntdPAnIxoi6OyJkgP__mfqzXsuy7L4XG92ca-29TxN9ZN9UVRarIYtFimRRpIqkTEukr32lCzcXbmDDNgzhAoYfDBh-9Afwuz-DYfjFMAwYNgzDfpCsS-qKoiiKrapYVZmVWZkZEafZzVpzjsYPY-4o5VNVZkbGiXP23mvOMf7_30-NSkmPOCExUkBK5jEPo4wUFmbGJKl6IMpyxbCUNNdSCxIjREsjIREGzrB-5Y3H_-Yv_-rTT1_-1h9-78WPXzU2IEazi10RbQ9222fXl9985403LjePr7axGHQncAHo7gCk6VUNsGO73myeP9nt96e2rOgxSwmAOheITpwWdudSPALBBZGY5webWngSjsBp3hybIvGf_s0nv_XLf-_Flz-9Px2AJgt7vSdU99TREGEp1MZG3QR5TPxH7x6EeYx0GIUEEdV0KjU_BgCCqGT7XYjNHJkExRAMAAMLcyUhwGAKdCaGCDOQNGsQRmpM4ryrdo-IqdYUvas7JogMwWL47Ey1yHxqa04HgSg1x2Epa0BhNvQinKMpNRciAnRrSGiewL0RrgsPM28ezBjuyKxuG5nUjLF08EIVsiPjIUimjgAgOAoPKV4BR5KuISyQ_lQRgwBHFiRiV3NHdS_CAIwCxACmF1N974N3_hf_oz_cIW23-LPbg5oByamtzFiYVbUEdY_V4otXBxdem-myPnq4_fpbT0HtJ5989uTJxbraFy_v7nsHJgNsHtvt5OoecTyehKwIffdr74b1_XHp6od1bU3vrO9vl6vLbalytz_lttPBllMzABTR08HUV7Vf_sZ7h-YvXt5tNoWE16Utq9V5OhwXV3Oz7WazHBY34FIitLAQMTP13gUk3IuU0-FUagnXBHaZGVVCxHVZEaFOs5uXaXJVZmSivizWtZSSFmthMfdSChOVWliklKmvOu12MTDNwiyCfjFvwPr_9J_8o74s-2M_6Lqu7XQ4rt1MHdiur66--tbTSeTjn30hwmvvUitCTJXefPb4wW6G8KfPn7y4vQ-kqZbjcd2flt1ue3d_-uLLl8RSSrk_LEFYL7YYcTouYzImTEhBhKjztrZTKwHrsoLHcur_5D_53osv9uraDe9PCxTpFk5Yp8ldr652l5fzG48ePn3wgATvXtyYOzCuJw1kJbp5cfvs6cX-vu3v749rV1VBMW2EOO0qMa-n03a37doQyC2saZmqqSatTq2z4OZyG-pP334XTANRe-tttdbGOZ6wltoOR2LRCC7VXKdpE-ZS0ptpSQjwM8YEA9yNWZjQuiUjGDHMNXfkSIAe2o0Jl_0xHxa9n5r2p4-f1lJNlTHaaqe2JFuzqyJBEWYm7Vqlhrur1bmoRTfnyuruCGrKhIVKwsdBO7OoOjByqYSSU0UizBBrBLJcPhss7VxPsYwXEI_sTZpBMPK4HQTglqcBjJ9r78UywwEDtp0R7wHVFsnEFUCMol4edAAzipjTkzQYmTuyZK4gNesYHu7eFXHs7MNCSjWzrHRCxFmHnaakrB8Mx7B3xYhMSSBT_ngA0cxTDppPyBG-JnTtCVzLNUJuhyHPlAhhkXDPvAaylBghHxoPfY_h9_AAcFeXeUqcPomkbyy1TaXO2ld0QAAuEh5Bnn1wFHGI19GXHK2OUxySu6MQl0m1hQcSTJtNmBaWCJAqrrm9AgjY1JlKimaAkEwV0J3ywxdqKZltLUV6tyR1uRoSDbRjjtadAmHaTWbOiFVKZZ6FpOA00TTR06uLB5cXiCRUmIe3CzHrFYBwPjQNlSxiAI8TE2CaaAlh2C6HfxoHYpLOIfPBTxThZMad_wo__38_-ywROW3ChFhE3EPV8sQrQgDg2VknBgDtBg7ImD3dxNaqWS6LEuhOGMhUChepIkRIzJDKtkgozKi1DnxuHnkTcjdyvcNIBuOsgJhkn4HUREIIYR4LK4DzTeYsUY4YkY6h4YOM7blZnB1YDsHDC_bal3f-TnL6LoYP5PzdOxcpfMjFc8uC59sXDXRSBoNonB4DSMABxn4xJQHZkxkXNyBKZ2KCd_GMBcJcihENkA5QGnQHYiUPkaupgYMBINoZY5rAgMyBR4BiGCgHBnjhjAumwDjPsWERLToiMhCRGDgguoWHCyHmr2BgTKJJZJiJAMEhzIlHz9ndR26NPaXB9Bog5hiAHl6hBHneSbI9lSN_jUBEJ8dAjUgws5nbOcKWzQxGMA-DDsgdPK-qSPhaXgaY8H3mJKdxugUwbSpSpLtWkqw3sFC-ALqZMHOyCOL8ojiv5EbbavgOAgAtjEWCwN3NDDBYxMLcHYnMjHi8j3tXYSQmG1p5JsbmxlSIENrxm19554__7V9-8eruN3_zNz__6afTxVSnabMpNRtyjKmgZRHyIPQpANHzImLuBFEEAZwIhZBBNpfX-9NpPS6ADuGlSAC23lkEh3sRuKCvBsFXz7a7Wg3ACTZzneYJ6swEP_7Zl3_wu3_vP_zwh8DIIEhYBM1S00FcxC2ygwTuwhIR01SzF8ciPJr4OKQ5JGZ9M200NJn62VFo3hDZ3SK8MFUsSgbuxGzRAImEmxkhmRuLgED2Zd1diANsYsqgGjFmSzi5W2lPL8yWmPO8qxOZ9yqldxVhIVZXcyNhgqiIloyLIIgoPMyPCOTq7k7Cmmk6hImKhndTrlhZzD0ICLirAkGLTkjBYWH5PsezFzlGr4a1KYCLCAQwUIRGnjTYKT98TAnR3SiL0sJujuRlw8fe_9f_2__ZH373W1uCCFjM_vwv_sPFg0vtkZlVYXiwqROTAdzul33TaZqOy4LavvO193bMX3zx5fXjS5Hyyc_uPvnyDqWcmpYigeHuN_tDfozWwt__1W8TwIuXd4pwWu1-f3Lk3W5bStnfnwRquo00K4UiDnF3c5t_5LrbOMrh9uhuQaiti9TW7XQ46XgB8X5_XJeOSLVMYQbm293cVs3qWq3V1R1BtRNzb32aN9Etoe-qXYSpyFjKufW1u4cwIVLXNq6tQsS82WzMI8IvHzygwoiU6rW-6qm3y-tdLcWi_2_-i__JlvhwPPFU7vaH5bggU1_72rtG_-7XvlqCAuPP_-YTKWhIj55eh8fldnexqcfbw5PHj4WpbuRiu715eXd7WOfN5EDr0o7LoqpXDy762stU3np0-fFPXhamfCLzeaB5WpYIAo9uFu6lkHr_9te_qquGxOK2WlMMIvKIeSNzoU0V9njn0fVurod2fHF7d2oKTADw4HJ-crl78bObtbf3v_L8hz_6vKtR4VKg1tK7FmbtABR1qsRFTRECwgXBzJjYohfmTZ3feuudOk3IuK7NHQ_7vavnfd7yMnw8CWF6aqXI8bBi5smZAvz1OLIvKsJhPcwCKNxIGFKDl5U8pLrdeLeBwUDMXABA9Lau93vC-PBrX4PA47oAQNeubsvSwh0d9NREWNWSB4AMQEjCDgYQoUqC4SFcQH1GaNq1m0VEOAQglziTmk17qTXM86DO8uAZZWQYCQJSeJmHlORJZ-4ViSzPhedpved8lDmSepkZh5R_Dag3huUzPogxdaEZc3ALYglEgoQSMABylchDYT5Cc1nPCSNDkTqi2oyp3sUcvyKqmbnXunHrRcTVgSBFwJCUD0ZXG_wNFhiMj_EsV7e0Q4cmF0ncLM_aWQUOP4-OMwprwUjABB65N1cPZDYLjyi1IBJ4gHcWdgeeiqtJrapKIlwowaPqSpQYSSTC8dLBKFPFwpjxZ0REMtfXh0tmYWLMagISF4IAVwOCjGxKKZ5YR4ZaN-odiaRMESZMTIFBJEiDEG4JZW-q4WbD04sA4PnSGvEqoLlQYQioRMxAEZt50nZ6_PjhdlPffv58O01znYoQnnsLGWofS5EAJEhH8hioEZ5xGrkswgxO5DkeANwCYuRYh_gWh1N2pFAyy5vtbSAf5-wxaIdzbgcR3QIISiIvIkwt5yg8IJ-YYTntOpLsSMSSfExiZECqImibaT7nfTXLx4MeNJZ-iZcaBID8O69Pz6NgS6P7HKmoxXGLeB13y8pyHnbHMXygSAhHeSC7ff8RLpXQkk_JA9_jECMtdEYCEZ6v5YDmkSX8Mz-Jsx0xSPMEP6f40mthd0KZIALt_H9ziI7MiHHe7WA4WWYDUv48vjc4nB05PEyVg7--EY6LiL7-7AjO078wG6Ys3ImwCqtrZTEP8CxIsLqmZzAXpqO9g8AogKD5aolxo81XiCd93GMqGX1M1COOVm7A67SUg1cSADfzQHALh3CCIMp1vIKm0peA3MMxBNkdAgOzYG2Q5cgkQ2c3WsMnKt2UAQm4RROSKeaOSmdETY5XmMndsrHs4SLSElPGWZEHdeNscJ87LoUYMBy8UjHwiOihGBhEXRuSqCpzIQaDuD9pnepoZ3hgImfHddrCx11OmG1cTTHXBYKCxJgmLSKk5OKT2PKVt9_4V3_y51--ePErv_LLG5aXh_1mmrfzzMlGyjWdGyGU_2gdaJ5OLEBC7xo5OjBAge2uPH34SKbpdLvvx1MCnwihMAkxqvE0bTbTG-8_e_bs-lImkekf_MEv_sO__937n3xOoThvFuC2HL94dfv973zjBz_8KZeq6pIZfRZH0K5bkXw9sogwA7K6EYGIpKE5LZzELEyOLlzUspCHzFiJA6FIyfv4ppSuRkQeCQ9GIlGPgCCW4SRnIkK3cASHCHAKcg8ENgtGDhpX0xgPIXR3D88ekpoSEHowEScvOF-bpfSuzCHMBsDCgHlYSZLV2BqWUsy91ikQBNDQI2AqxVoQZ5mH1DoyIUGVCubJhctOUQ4yXi9AY_T9wcHTlpLOwcGcJQy3eZo1LACLiFkAAQsWlnVZ_vf_u__Vtx4-vIioiKvr2izKhkxaU4I4rsv11W7DLIzqdneyk_q6dhb86nvP33x0GdpuDqfNbt7v26c3R0Vc1k5MHrGsa76dmaRg_N6vf2Niv9-fPj_sSSQcuOLd_tRaP6192s6HdXFzrqW1tczzurbeWlcTluW01loqwbKsZuFuh9O6NDWzvnYSab0bovYVkYLCtYcHErnnvdodE_nT1Q2ZE2G82W4g0MPNPcwACCzcvE5Tb-uZ3hFmXkq13qVOSFB2m3Bra3_j7ee9dZlKaOtrb8tKzJIfWxDvvfnk-7_60f728PHLGygahkTl7vYWMEJ4O03f_up7THFa2-rWHebN_PDRg9vb_W4ju1KvL3ce8eL27vZon3z25X5dFdw9HELNXsPWL3Y7sPjxJ58TYIBnJVNVp808UqEQFkGMjB4RsMYvf_SVpa_7ZTktqwPY4gFwsd1d7WYyraofvPX0opbe7UeffyFlOi7N1cPhYjOXwvenfn_qn744FKZSqpur-8Pd5f3tgujTXFszJJynubWeH8LzPB1PS5mZRa4ePBADqKWZ3d_ez5e7u1cvC2Ffu1u01hLG2ddGzKpW5hkspqnm7hiZTbUvHRkRg0vRdUXKuL9IraaNWKx1LsSEqs6ZovPwAcsGV-uunMpboK99-5un21siXJe2P52MUNUoQABLEQCotYY7AVo3Er68ujgeTzlnAg8A0q6AqNakcO-aD2wWKVPVpqUIlwLgeF53ExCF-WuOfl57EQP8LMmNAeEEQC4ljzq5kUdIWLdlrIEiwNxVCQmRrTkg5Bwa03pojsNzjVJKRBCV7LcCkQWYh3UfjUPGCEOMMAcNAAjrxDhsBUwR6EnhVEVB4qLWAbG1lQSZBD08Ah0YxdW5MKRCxc6BojyhUBAjF4lQFnFzXzslOZvSsJO-VSaEMeogAiTvxpTwMmBG8M6EUshMB1SCi5uziPWGlK-hCZEdKA07ef0wdVXwCKlCEIzc146GyCzzjCREgsnhjiilJM-NmfOnaOYQUWYB91IZIMxUmAGcSVxbqdVdAaHU2nuvZRPo0awARbe5zBgDzSMiIyIi5GrMWJjmeQLmqU5gHs3cA0iauiN0a_O08W51mlG4Thvi5DKlDHfUYgEou6oR6AmYSMsmnMUTWcwFOHdEIy92IpxhfWIez64zFsmHNQmYyNKNnmP7MwzAPWdwAMgewMJ5r0RCEpZSUmBuauAhzMiCSMQlyWupjmLOZ5yL8HYzbTeXSeW3vMZD1vZoaBaynReYz3ocFJjEmoKbRTomfPQSMF67e2F48HDM44dPFsAjTNVjTPzzhUfnewWNFu9I0iGAW7ZWnDJLcxYlZNgAxtbP86h-ntmHm-UvZyaIYPg5DxSGZiwyBpHMzvGHygYBgKmZRXhgjD5Cao8xJaYEyQPJiXmSkTizMhhnDG9mc8DIAjDVQdndcMD0rzKyAJoZo3TthEEYRdjcAckAHMIQuwcSZ3FIiLJtDODCPw8rZnOUGapIuBE4EXr4eIEIBQ-GgaoRUDqG84ti4HAIQxvzlZigolN-vUkiMnfEEGJmMnMhsvAKggEwStKIBupj3afohBTmKx0FkSIEiILAgREBQuoEzgbgGB6Rry9HQCZiqiwUmLRKDyfEbgqOCKRhwuQYAT5uQSiELkIR2rVDhf_kv_EbX3v7Xa8YHuS0ruAW7q7dtEWiCAAy0AbnCxrmF6PWIWB8BpZChEiwu7hA5G49QCcsF7vL_dLcPW1XgUCJlstlI2phiPTUUoxaeY6HCLiQTEwU0Nss_aN3H_zW97715vvvXFw-ZKylFmC6eHjx9rvPv_HrH334wTsPtxfbqcpUHz7c_fmffPqENv_FP_3dD3Zlg21XSynzFz999Wd_8elvffeXNXop4oClShEW4nmuzCA5qRqPJ9xM8wjEAsGoS2WTl1w9LeY5YghzDAqkrIhgoLoXLoCxZRbAnBaVUnKNl5UwdjS1UqceXoiFJcJZWK1VgQkD1aoTOaEzAwghURAgqqN5TeaUEGCEKQNNPAsLI81VGLipixRmdI9ShIA2dZOrjFJrgJNgaw2R8u4d6I4hG9YIFOmeBhgeNwZCRNrxtrBUKgJYuHhzQDAA8wAMC8uWIQr4SABGKYLgVVjN8ruT4DULK4Dh9u7j6w8fbGprpGG9FcKI2G43WDkApAgG1ULEDIHu2NzVDBEKwIdPL6OtRImAgpuTmtp2rpvdTILr6VCZSQREDPtH7z2X1ZbjGgjiFF2XZT0dVym8mefD4dhOLQB6b7evbuq0ub25RRqzDHOTqR7vDxjsHkQhCQ-EOJ4aFSZGjTBTMwiD6KHdqYpFQP6YkiGeBbzA7bQVKb3b4X4fAK6pjad5Mwc4hq3LnpmZJQJqKXWeTBuz9Laa-e7igkVqETAvzGjQ1zbNU52EYQyJ-vH2n_13_uvQzCAeXM2H22NELIc9EgNiLfSVd99iD2sOgI8ut4-vL7791Q9--pNPC9Hjq6ur7a63tbVeSr19deMOJIVQPGJd2-G0ZJ3p9vZ2u6nNdVlbLcJFurmCW7iqE4ZquJprhwBmAeJf_82vyoyZHiPHyzo9fn79-NHFcntfGXSx66vLh1e749IAARoux6XK1M1fvNo3t7_9yZcvDqeX9wsjgcPlbr6-mkqRg7Yy4TyV091-LpWBtZ2mzSQcMrNRbHdzP_X33nn7arutDy4__fSz1pY6TYeb-3fe-cC0r6tiJSzinp1tt24spU7bUueIs60xwrpyQfAId11XZtGuMk1mPdfUp9NCIm6h3SkA1NzUw8HB1K2bWeS4lOcCvaX4DwCk1FomDJiSSGY5lmANN_DNg22Z6lSntmqRAum_VFQ1nhgYsBSmWkotLBlFMe11rpiZQGREkGmSOhOTsFAEuQUKu3YaJs9ASLRKEIupG_hI92KwiKtRVhAHSxXBgyi1wIbuXCXM8l6RZxfPaI671BpulJ4RROS06oAhIEXhYt0g28BVwBTP1GT3wFIAkInCw0GSfZ6YIWb2viJx71qmAufIJlgQSR4r89EOgK4-Wo4aRIQeKKJryzS29gbMQSGVwyCPFGEuktEFQwQWQUSzxogYFBZUh60HkNwVkHiaQ63Uat0DBDxjGBCB4OSqXArXcuZjBjFl6RDHpAdkrkxCPrlqdLNmJISA0ZWmkpNbNyULA7QwzKuRG5EgUFD03nKYbWok5AThwEQeIFOBAA_XpqXWbpaOMPMcTMB2KurWm6IEMqhBrQXRQjuo1GlD4RghEJuSibgYxoNzsQPCX4-AMyQzKD6BSBRuI4PO2Q9_fRkYHioWNssw-ODTZ1rcNPmP2SeHnFoj0Iip5YCcMNyY0AOAsKDkvwNA5g4UGfhI0k2ClxL1agHEREHIUQpNtZJBAQbCjCGWGLuj86jf8Vwkt3PvnHPaOeaDiI5A4OYsJUwHe31ErsFSczBicRgQeT_M3X-MSjoSD8R-bvYI2cnIwXHkDxI8f2YlUXbBE8w1uKEIOrBImFVpILQIBqRUcOTeBslxBNYpSUkQTBgQxOzmjqPlO8bk7gDU3REQGDgoIgiQOdwjJQXdAzAYRUOz44aIxALuKUICsAmrYyCQBxqGMBqYMPdmAATuyQqQIr0HYNjYGjt4MDOQ20BbKho7JrYVKSijRMwcHiwEydkgdI0cyEcWjIDAUIiSc19FzD3jEoSEgYpOgQLYHSKwu4_wPBITvA5Gp-wkQ-ZqxpTZIMt9kKkWIsUwNyZZtROFgwPKuKJ5D6GpllBTcHPlwhFQUVQ1L2FdLYcpRJh_llwBja0sOAIBUTcLB0JZTQlEhC3tjeTITJv5N77xvj98U_kbN-vt__n_968292Jrs1ZQNNdSambqnDtZoiAijmIUblKZgwNDRFpXZAaAeZrMYT20WK0jeSBSZPjbrIM7FwZ3QtR8ryTLwJ0DI8adJwMDDsBhhCBFzDsSTxN_5zvvpq1yf2xJX4A02l1Wbd3cwC1WeyA0iciu_M__83_6f_i__b9fKjTjReYffvazB4-3v_jVD__tX_yV1ElNhxiLGJABTRgR2SRCnSBEinYTIREBguiRImQRCfBscCIQA2g4igQ4GuS7i4mD3CEKUgeHCAYURgtUSASHWA6ZKPvuTkTdnaeiXZGEueTUP0GjKedEyvkcJf_ewsITc2wQUJhbIveGpgNPfa00foBrtHkq4dFWBQkORgYmCiJzFa6GGhoATsHZA3EwLtJ6gwAEOsWK4YBjf1k2EuZJWgiErexOyxJ1rO9Uu4Uxcm6rMRtlPTpbQGzqDKjY8D_77_8hHFYAWu1oYUezw-rmIJUnqCzwbHs1SRWkVXVVNw8plcCeX122U7u7Ozx8dIkQ--O6mj98dr0_rFNEUy_zFIiC4Sxz4a-9-eRwf1x67-aT4OG4gCM67u8Odbud5gkJ7dhmngPaspyqVFNH5MOhXz2d16Vf7Darrq112c4KYOqrdq4JVWUAJMDKrK6llB4pksOuxiQWLsStKwQVETOFiO1mbsuxloSXBxH23kud1sNRmMy8LaeLy-vejg4kU8088GZ7cXi1r5vK5xORmV1st_vDHgNkkoIugh99_R0EeXWzD4Z1UXBopxWZRCqRT7U8v750O-9ykedKP_jxTwjw4fX2yfXu1ec3QLTZbT7-wcdLsxbQVd366bQA0s3-OBd2X549eXzcH2_v7olp9Xax25gGFmpLa61pa-5mbm4e0YGh1t2H3_iGmdwtB7Q-Fb6-uvQivffL9wqAP__a28UCexThm-PiZhHYzGutQe3YfFnVLdT9xcs7Juinw8Wjy054OJ5okvvTOm8u2nJA4FIr9s67CZg_-_TVm0-vLt96djqd6ma73O03c0WP4-0dFPnkkx-jCLERs506C7V1ASbz2F5eAAEwWOsBgGCcoHPmMAVgAMslobrV7cwM3mkqREK6KCEAQ18XrsW7EiGgWbjpbZme2XJKkbOD9uZTiaToeg9XDwtECQAHwxACssTnYGjv7biUKmHmhAVlmjev1leA3MNFSl-1FLFumTJwcwB0AjQUmcxXdWO5fu4GyIxgqZgNB5YhG8vnSQz-x_CrxcD8-TmbzYNxCGiWwP48XLtwDpWTmAEZXRrobgfkc_aIJaEkmRXgIgN64R7RkMXNUSgsMnk91LKI4U6egZVwtXQbRHrCzIAoAEKNJOXmEYAoPMbMBDzKqQ6QjKCR-aH0ep6TwYORQhThwGwGwgWJPZyFR2ZXyMPx9bAEsmDBAZnMZiSURNPnpSeQWBhxEN8sDygUgKbOzI5Qigy2C9EwgwAOulFKG3gYgCZhZlq7iRS3EOEiNTDcgEXC-lRKeNRSTLWWGuCAVEvxMDedpipCHp4I0XyhgGdmFIowMhKEMEOYMM5FpsJT4YvNdLWdd9vNo8vtXAtinoNShHVOsIwUWXYkYGjSxth7vBgSKeMe46UFSMwZ3TkDaBBiiOvjjFVBBMJU10GadFLue46kBw3lwoCfAJKnNYOwlIQloptjhjc0PEFMAyFlRXiuUxkwIiLO6T4kMmao7uA1d-qsTT0HdyhbrSOfj68DNemoyzM5AIy0OQ1fwtmcgPlCojMlN_P2r4FDCOgjXwcja5Ld4NeFXXQ8x_JGXMjPEN8YwrpMdY_68aDXpttj8MMT0DkaCCkNwPFGIWazyCJ2riRsUIzodWGDRkqZIJDHD5I8uz_jQ8A5c0UQAGiggDnfVESgiMiJOkCEo1CMvMjIjAUGk1RMr2aEOSMgudD5nm-R5pT0nSECQW5qfNgNENEH_hICw6MwuxucJ_XuoNnLzQRFhpciLOzc5QgkNjdOrxyEcKI_uKXOIFATPI9h4R7ADhHUh3k37WOU9H2PQAYkdMLzb4EIKJgacYwIRhCSkQgBMPOUAGSnWVjUlEeRl90NMseYQipwINIwQkTmiuXtZ8_uLf79z3700aPrX3rnfb-WP_vrH_VTF5F5u-FsIArmokndJe0TkR9WIKUCokUkXyzU3rq-eHSx-ef__I9e3tx89zd_kwH3p8PE5cHFZV7pAYCE3ZF5MNZyRmThjBQZPnWrpbifD7n5UjRgAFeoiJMwBk21EGIQbzYiyLsiPBUiAIbT0b_24dsPt7tNpffff_MHH78IZgvgOn3-s5dvfvjeJuDzV7e7eQNAtYqbBqA7OKQRvCYQLDxkEvx54X0wpNKehhCFyhlgTPlehPBaKhISgak7oEFQKsMxF9eIjILsWYoJBPMsYwiVpjbwG8SIuKgSZ36SglDd3INFWh9JV8fgIph8YcgkCSCGSAn0WqojCBFgUEn_xSjtSClmVriEq3DelRmBWFhEJOd9nFT6gAAp4t7xbCtXVYDcXSURHSAA1JAZGd1DuJhb0sTdA7JJQkSVMZvUROBOXH7jN37lo6tLBszR5c1-ublbLSI_vxhhlnK5mcwcAI_q-7URUWH85fffIodPXtwo2fNnTz_-7OblzRER3ZGF1jWT9cHCE_nv_fJHE-LamjEclnY4NO2W_FdHut3fCTIL99Z6NxTiUphwqvP-eLjYbuepAqM21W7M2NXqXE_dT8eTlGI9XzoeamAWgOEegVJErVG-PNwiopshOCHn7Dg_1XtrnD8IKb2rh0_bzfFwZBHLUhanwSYJzozIFw-uIuJ0d5RNXU7HeZ7cjYVpoJ8UwP_Z_-B_WBGgUCC9eHVvpki8qqlbmWQj_OHTxyLS3b988dIR7o_HtnQRfHJ9KR7zJHU73d7sf_r5qyXcA47rsp0rEu2PR-3BQvv7_eOHDxz4cDouS0upqhCuvTvE6XCyiN56orSSi6Hdfu3bX2fQgH59NRMHQRyXpQgLIYYzwuPrDTMdev_hp58fD-qQ3kxsXVl4f1rXZms3C9PmqooG08XGLbpjVxPBkd0m7Np3F7vdbkOlXF5c1Drfnxau5Xg4tLWDuwMejyeLPMMjM0EzJrLWpQiLpBHUe6cIEiSStiy58EzikydQDjIJz2HjkT8AHtaTcZEB-zw2YwDjlgDcFIGw8l_86Z8_ffawlroGmIcHng5NhJhgbY4iSDHPk67tsF8IEBFqnTycmVjYI1Q7A3ZVJ49moBaBJJUZqTKRtL4QiTCpq2lHAC7Xz4FzvDV83wABHgQ-5pREjjmkT9dSmsPHAB2R3DwhgwNZMvLHkZDB1-lhhMjOJYpEGrqS_skcbghsvRNRmCbWkPMjyQfxBehs2QV0M2LOEz_AOYyI4-QNiMgCkERYAOC03BOTuQFxpEIFEYJ8WMYQmV0VkBLpmhmOccFJnTASkaT8OaWj-dVjPrSQWbIOEcRMACwli8jIFOrECWXh5E4gErqDBRIBkZoTkkf6N3OOCwhEDMTsEeZOQtNmGiRTdTAGCClC-RwlzldbUAhXDHeIoKhS8mGQiQ2ZqqnNm61w8rM591yeeZkgFjJ1NZ83E4B3U2DsvU1TyYrtdrfZVrnYlHefP9pt6oPLqXl_8-njKhVzoYDntDm8BndGcscH9ShPt_kBicN1AOczdC4Pkhwd8Nob9hqfTcScA_LE29HQCSeEcdSl8Zx9Hy6wyFwlmIVnkGsM7IOQNRwdUJCFXT08UHBivtzMVThFUQBh7pRk1VwvjKBOwPllnikZG-jJDAQNO8Hov48E0PDf5ReW_WWkcWXyc78Z87KRbZy8LxHyYHFCDG3ZGTXko0wMHoDkkUUeSHzhWaWWreCBwIrzF4ZDh5h8Lxi6ayKAoDjf2EfXIrHf6AHhkMXm_OlY_s9ItxdnptDcKXW-nkuS8-cBkKd2GijcB5qJ0v070tEZoj9znwIZzR2IzQwTzMvggQ6u5Jhv5PMGyQACiREZg1H8XD3P-6SbOZBHBI7C60C-EuNoznulKQ_8jp5oRQeLFLABqLpiGEF4JBkzPy7UszOcs9wADo689WJuh4hIzTnVDalYCsMAVyhM4YHI5y45MlMBUXPMMcOwrWRCC4gYEDhL8oQkAuGSQj0exfJzGQd91Eo4IFrXNIubBnvUq-1nh-P_9c9-ePjp_uH1bqb5rSeP3v_qW8-eXh5X-_h-vdgwEMxTDebNVAuPXaWGzVOlypGV6sIsgoDPd_XRPP3RH__Jlzf3v_Lbv1qB2nJEh8vdLi9uZ3EfxlkUD9ljD0AmQA6EqcyujgxUACNveCiBhQclywyy5MVM7kEOBYAQuBAV4cIi1I-n3WbbjgtD3IEeTmrg7iEsf_3Xf_MHf_Ab95_frs2IxV0RiCCkcBEKh1KEzkk7Ekr8RHI5pwyjMAKEsLhbAHDl3MVgABGraabs0paAAwdMObkAgiwNE2ORYm6FijtUKebGiDBGLhGQUg9wB2BubogkhTWUGQmicI0IDEpUHTGxECAUKWZK2QkOY2IRyUUHMrgZCQGhY66PWK0nQJaLBELivZlYW6fC-UZGwDAICxucGUaAqVYzAwQRAou8aQ_lGaOFM_IgQOfnDBNGSC3ZD5p45srTlXz3nbdqlVNvxPTFzf7YwgKYQJA2lTaChZkI9if98tVeIwDoJy9ffuXhxfG0vPP2s__Xf_nX81S72_ZiUwovrZlD7949ub7xcJavPL0-ntZm6uGHxV6-OtJEaqARp9Pp-sGVdYMAZl5a8whVncpEiE11kkKSQDPXbsS0mKqDuuXjxS3cgrL7hGSmDgl6AjcDJiE07dqtCBFBYWna1R0A3R083FS4pG8xR1dnGjPOmwtXBY15u0k9gVTxCBEmxlAr87wuS50ny02wNSJR9__8v_k7cTpxoX1bb--O24utq-1PJwgL8K-9-fzBdlqbHns7ru3l7W1XB_AnD692UwWzaZ6Wtvzkpy9uDots54Bwi6cPH7y6P768uSUiN7-4vHj29OHLmzs1V-3IgurrurTWu_tyWvOh79oscmDkwvCPfuubd1_uzWk7b26_uAuyabNBi3kzufZHD6532wkQbxa73a_TtjKLKpzaygjLSUNAIzzQQrmwNutdiWiz3S1LE6RSZTtt3J0ILnfb64fX62m9vn7gbqdlKRQ3r26t97qdWzcqIkXWU4sIEjzdH-bdhWtY75lArvPUWiMmCLPura2DpeMOQFSklhLhItV731xc9HWxtm4uLlS7d82048DTc66FNdyZMEAhoEwFrBfGH__dxx9-_avqAY6991Io3KmQuxk4EdR5WpdTQNQirbVlaZu5ZLPTulnSC9xNwZYuAhFAUw0EZgl15joazJR63mC5eJoz0iHE9ICcbWJAOosIgyhoIMqJIdQAIP1WmEsvHOHsfOjkASVPOe6O2Ukb2Atyx7AopQpJoh4i071M7kalWpgw4zlnnARPIAzPniNSLTD2BxwJ20m_iYeIdHVhiUzmqI_IbG5aRQIMIVupQKNgR4ZhmtX_KKVY75zz_vwBZwqDkJkxn2BjYMqW0zUAQFZzphIECMHEbia1oLB2xfCBthfp2rlOCCGFiDjrXyRCRQgYmVhy5o6v8TbMREXA3ONcOEWSKjB0sUgiFCFJS6iTaSOiBFCmVDh9dblimepMBCxETA6WJEoS7s2YcZ7qaW1MyMjNGiJOteTHt0dMm0rggP7wYvPgweXVtj559hDUnz99mBqB0fdMCVL83C81KqvnhUvOciDnl4mFgoxZDXxNJNkdwCyhLq46RExpYBghnPMdI69hHmABls9kzM9iCASP3PIACiNiWKThGhjzrE40Fl91kvvedlO5nDbCkrLps1chP23jbCEbPjiIHKXnziwHCsknxXGtQQgbBh8YRdjB7E8h7hCFBQBhRNrxBj8nJa9p_-XM7J97s9nVx2RPjVdoGjwAPfC8yBqH4rwXjS8h_uMI0xnJnwmkrOsNKS8MeOhYSngEjz8GJcYHaVTqPUbxHwJG1jVQBilpSIngbFQdju68OoyvJEfwowqcggdzt1xkEGaZ0t3wvEuiACR0Gy9v9Qwo8WhG--gwYOJyiNyD8u6CYBHC1awnPT_GjyaI2FWRadUVmdXU1AvVbgpIGmZuDpa3KcZMCjkAWoTGeN5DGsTy-5fVt3NDnTFXUvl6pxZqNm77QYDhTMyAhRgzSxVAjAYGnLLv4TPDxH0O5Q0ScrjOZQ70My0gIBNKTAhg4UJETANolLNYRzf8y59-_gsfvPUQ6atPnixI_4-__Onf3uyvdtM7bz799tff-e1vf_D80aNfe-fd3ZsPf_jjLxyizhtmWo_rtJ05MyoQBgGpz9N4UuVyqv_8j_7VFy9u_973fn0WcbT9enp6_cgDGJxYEmRFOTxCGC9mwBhd2HHH5QBwpNfN9JSvMTMTMkEKdzQKC5GBn2OBBEL05Onu-tGD5XR49eIVzPT9X_3mfr-44dLVYi2Mf_wnf_5rv_ztTz75GVLqkqAWtu5IxCTZpIqx08YibMlMKoxI5i4ixOTujJSLzRRMegxgkxTOslMatTIESYWCQpJLTAiEGpEBtoBopppUIsQYmpRICh_gAO6xjDZU-nPCIuEKgCG1qPtZVY5IQIWytcZEzOymwumBZgpa1o4RLAgCwGTqlaSrpSqxq-Xg0C2Qyc3yo2bgtgBcLZe5pVZQQ0ZLR6ADi6CQmSKJtS7C7hYYU50jO5DZoZICaFNhuii__dFX5gkz2ni7aAtEgM1UrPVacVPo_m5PRFjkxf0hPwh_6cN3rnfbu8Px8kF9-GDz-WdfQpnW5h6oZqd1PbUGCIGxHO__8a99F83X1u9PR1U7nBoK9KxPAUy15ueGuzs4UulmHsHApfLSl6lIJenacoDbeg9gc9NujBSesKYMD4PUYuFNO0JMZVrWVkS0m6lmUjostzWY04fKZTktQOEWjj4WI0TWVSYyjZKi-ORSMJlqAJBIESrMpZZ5N6_HzpWtdwvwbk7w9vuPvv-L31qXdr8cP_38FZF098Jyv5wmZnd9_8nTyqWBv_jyy8OyEEvXPk18td3sZrm62Hzy8aefv7i_Pa0aqBYQOE_1dFpubg9YuTetUmqdisjNzWFd27L2qdTTcgqPspnb2pGJhEGtLS0QDJwK67r2Xt57580IK0R1ghc3-0dX21IpDIRwO08aro6v7k4tNJDDYemaz3BHXBY97NfWOhGDUNf0eMphf5jnmckdHQyEwLs-e_bwerdrLbwde8SLm7uA0GZlqofjKmVj2vppNVViKrtNkh770pBI3QN53l0sxzXXqBDODMLY15WZPJSZwtOZjW4uU22nhcYdObRpuEY4IFvvGZHoZqBOiL1reCCzrwoRMtcf_s3fvv3e-8uqak6AZoaC4RgUjKzd3ZWYPd0CAUjYTsvptKo5ILlZ6jpzS5f1HmKWIjlsyc8i6-bmwszT4zcTnZlnk0xkpNzxTOLJ1ciALMI5pIED6DFMW-MmMKZ8GYQI5NSpA4rkQSPP9MhDToRI4_dkzLJgRMKMFDKfQDgO7onpBDTrEBxnJ6mbIQMJp8cAAERKiqFS9ZrNKkwlbTghe3dJGGR4RPTeiVCY3YwJQ3vqyrNvRVzSBpVwRx7N0Gx-4uBHM5l1qTXCpBTiigycUqosDXtw_iWzEyCN82i2KlvvxJTGb0Kayry2nv6pjP-kwQAgRATRA8kBpFBoeAAxa9NaapL73D3hEswoKIBxOV_lABmYplq8Kwvn6gDzG8OIAcyYIX5imko1V2YyDykkmdyAqHWKvjy5frid6NnD68fXFxOXt99-PrMwUQ6S40z-JMDX52CIrIuAnXcu8fODMKpbRA6_IyI0VSoBwINRnd_ItGqMfm94M9OMTQRoQLdQSx4vacSyqkGoeQQYxrr62s3M8wkdTurh4UguwpfzdDnVUgUDHl5td5upkHC-JxxoJOKyuopxVuYBhCaxiDBNsXm8HTcEPEfNchk1kFxwlgq5Zxx_gHR5HF9i1KATv5Oty9wW0BgbU7w-4J6DLXn7zrffKG4OjUE2vMeu4AziBcjOK5yjDfl7IXicky40vHn5Pc83JmUHY9zzIQdfRBTg49-MwTDK8M-IgeWGh0b9A4ASm5ggIYOAQDUDRIV0cFI6HSL7l5kKCSBANyAEIrQMREUIMzrmRogZATzfOEkTS8K7hTNx0HAUZK-3AHVwGiUmbK6FS6hSYbAg5u4aHkLStJdScpgeMfxFHBgADpEt0FxmCRFGxoWsIIZ7CwPC_O3IY4mGwZhdKA5Inxd6OKo5S0nYv2FMVCKihxEHBDJyzxRl5L42MUfo4Ak_ZSAzR-GhPojzusLHxaxKUXUG9hjiFGEOsJf3y29--8P33niipX7w5qNf_-qT337_8VtvXX758tgcr-e63i93x8Of_LuPp1pJ5HQ8FpY6VZYCRBfX8-lwqlsJ4jJPBf1C48HV5b_44399OLTf-L3vVZ7V8MX93dvPnnggM1ik_HFIqPNBU0tJwR2TRECYRlB4mK9CwowKXgorBgUGBwEOvi0GYiQCf0BqTQkQ5s3XvvV-e3n34bvv_oe_-Mlf_93Hrz798nB_2M513s3b7SWu8E_-0a_dv9p_eXMcTFhilgIeKFiqAKGHlyqAwUzMJV_SIrmaywUREmIRGgOzsCIiI9yX1zMKihznszARoeViLq1u4RGMbKbEZBBFJDlUKZJP31_vVoTdnIXRPcwIpOcuzmy0mDLfxqm_NClIwJEXlQgGautaN9UzB4ipCGTksTPMnhIyCLO5oYMU8RzkCHnObgO1dyklBjkABbH1jsTMlL1nIABCH4k4J8qnAiCgBUk2weX1jS6YyyTlrz5_8dsfvbOpHE5f3u8bUDOfigjG5VYePdhJQGGRygaoAb33WvjdZw-L6Zf3y_39st2U48KnpnWqbW3NlETu7o8i6A5V_DtffdvWfnu498Cu7gjmeFobEDGRmffW03nfulmAkJyOh-1mpoK3N8d5U9eWZ0SGc2slHAhRhHIzHBGJnN7Uzdq7CEKAcAlXCJDCmm2lQRsAYI4Y04QxXszNkMU8b1wXJAaM52-_BW7Xjx-pmnfX7iQ8lXI8HS8uLlQdObbXWzNA9N67lFKET8fjd77zjW88f-PutNwd7tVB3d3s1A3RN7VOU33z-rqpvri7d8RuTkSt92mq3_jqO4VwfzweF5PN_OXL-xBCobb0cN8flhYKWNxjO03atHn37uvaCLG1rn3sVM3yFeThwYgGDgTugWY__fFn3_3-t3Dp4FYrVeblTt_9yuPj7bIRwsDj0vanruBr08NhIaZHDy_ujycm1tZUTbtpb635_UlZsJSSRlFbu4g8fHx1e2hPn1zN8zxN9e7YluPhwfXF_u54XNZl7W1pMldzbOsJI5bTioj1YguIiXHx1i0sCC6uH4Z1AAMEa414cm2uRsTCBSBULR1E4TbtNt49j2tSipla8wAnIjclEUQw9whL5jwCmLrkVJ0QHTbztCpOF1fhZj2TE7gmfqpW97YcT-6xrisX5lLCtJRS5rourW4mYbQwVUdGkmKeiXoCkhjS8bRNY9JEuVw_x-EECghnEoexvsyp9zn1GMOEmQNdwlExhEAWHBgNyTABJKUuR_jjD4xA6SLBGHhLcA9TBeEwY2GzzlIGdSjcPePFgCzdfMwzAYGEpQCTqZYyA5qZQyAXyVO_ECGRulGRcAgEEQbizCBFAHFu1J2LRAAJDTB1ODFFjlTHqEyyURoRqpaT3iE78XNJAsnzjQvBwmbG-ftGEHMWsYgAKMIIaGz_U720nbfmyrUAgmSdwMHDuVLhurYuaTplNA8WsZ5yNA6PCKq1CAt4cCkBBkhmVraTdROWWmqSWBx0njepUgNPOO4I3LfTykI5Y0dkEo6w9DGxMCKxiGunABImRNU2F6yFnj-5euf5w-ePrq8vdrt5yrzSWPzgOG7m_ScnzTl6jNfZlbNCLyItD47IPq4Er0-coP46AQwAkEqwlJSnFVqzJWmh5k3dPLqZmamFeWjOcwJNR2CHMmQC0DUjUhDdnj7YVikBMG8Kc54k-TzSAyImwPNoFSn3-B7hoQNYg2ae_PkR0ghPg0Sa9YjJLJgpi-d-fkUN50NmoHHEkvJUk8Gp86keUz-EeCaLDs8zIHK4jT0xAQIOyD-ObBVRxrIiZ_bDxZbBuDTP5381T_YZRz7TSM8LFxwJhKGp5kyMAaDHMBmcCaYIA2aEw94GABGZCPJwdQckBrIID0OkgUiOM8QSOP_7-TR9jRpFQHN3C8oSP0Z6qSAFLDRyY2odkQwG8dgNiBkCiCkQw1HNMChjgubnQM1onUJFcAJCCiSDXOiTuuaK0j3rmkP72F3zHu65pwNgTlcDBGE4urmBu0OhgmnrG6620FzAA0YgmA2GaS5KYrxChQgFHXxiQURHZxF0zwBSLtJ2PCsE_by4IhZOiG4Dh8qEguQRiBzgjOjhub6NfJMDCsRvfffr7z3affJqvdjQk1kezHFV-LqUJ1c7Cv0C7fNPX63aW-DFbj523e2mtek81ypy8_Luw6-_sa6628yb63nLIIf16ZPH__Kf__Fhf_qdP_hdDAaKL168fPb48evNGWR5OV_tCIgko48Sau5hhTn3hY0BFcEhENARCDdE3YMB3J1yg-SAnFKaoCRJFL4_9P1PXv7Xfv3bdzd3h2V592tv_srX3__2B8-fXUxvP3_y-7_47mf74__l__lHtK4Pnj5Qb0my7mZcqLf0nWHaPKSWRNMBYK1T4uBYuJshEktuodHBpjpFeGFxd5FibkCgLSc7OInkGxsBNADQiwgoshAIhWaZH6uImQeAqlG6tDDyPtCb5WPOzadZHJSZPeP-bkkgjQACECASDMC5zMjBRFzltZObc6WQN3bMH4QIAQdoJMePJi65gdZmCFgY-6mxlLYsxDIwwsKOkD5pj3DL0KsTi4dVmfLpycSZESIk7X2qNZtFPWyq02aeri7rP_7eNy9323D90Y8-3V5dtObC6KFX8wTdCKAUXpt2j81utz8etlN5__HFae1IBIyffHKzGCjGvJlOSyOC436RKhAQoO8-vXrz-kpbO6zrvKn7_XJaFR0MAw0O-3sLB8O1LVOdZJI6V8a8d0nTCFepbKaR-t6IMAtzt8jHhTB1V4igLP0jNu1u4QEWqqpSxLuNTSpRXzvkKweiHxtiWDcA4iqmhgKEJJWs-8OnTxBhnrc5NBMRR5rnmQm1-9WDHSENCRVTmPfWkQgFT8vxt3_rlz94_mhZ1k9f3lxsp6V3EV7WtZQipWxrudpt7g7Hw-mELOr-4OFDNXvzycOKxIintWng3WG9O_WT9q6hZm3th9OKRGvrbs6Id3d7gDjcn2SS_c2xJEswIs_9GLAuCmm_ReIiEFGQgPDu5uUvfOUDRt_frgK8vajlWf3i48NuW1aNm7vDcdHj2niSL1_cAeOLV4dayv6wtuZMUggCySmObQ2LygyE3qzOZbfdfvDOY121TAWZkfiLL15strMIq5kBWDZVEIKxddXezlRGR4hCotp1XbhKmWbhIsLWW354rafFVcOz1yOeTJPkBanJtGl9AaLwQACDszcyV-vmzDJS7hpJ-0hiTXSnWinQKe5evHj3W18_3OzrXBBHumC-nE37_u4wTcXMXC3TZcKMEMSyHJpDEBIn1xsgurGwubOIqbJIRJh5aKCHiJgpl-tnZnm8SJxnFoQAEVAjQj17PCN5AoSSZ46xxSPJ2a0kAV3PIqOfG7_wXB-OAHBtzDVMA4CFggkRpUgCFMdm35yL5KgP83nGDHkHIESgwMw9Jq90ZMoz54FEHk5S1B2Qw5GIPcIM3A0MUMQtEBAY1_XEItEVzwPqnOmkTopI8vSGhANflSdAlkRBpfIwEIfyEDncWSTPEyQiiILERN6VmSKiTDMgkAgClFLbukxl1t6ROMIzqe-R9zEswuiu6oEUiMTIQpjnDSSMQUAqpQIGEatmedzqtGHOwtYo2kopOXKeNrsq3JZeptKWtdTivSMLIbCwqTJRrSXcrGtgEGIR3pSSCy1hevhg92C3-fbX3_nae2_u5u081dd4_jynRtJgspmR9yWPBDWendHD9kCjZDF-RhkSGx1UooDAbGMAukdXy_NTRro9gpBY0qrMCMBEwii5fGdiJCks51l6Ts0Hltsh99lB9sb1ReWSwZpwy8AXE2VuJxCIKVVQ7vnQS-gLqFke8fPGMsaR-VMjynD5gEKN98qQZ8frK7R7BBCxD1z_SOXne23sy2igePI7RQHINATAeUsYCbxRCYDXDfSUlA2xAIxfkxKrce8aBewAGJ5gAiBKGYP5EKVmtC_hSvAfa7BgWACTu_-6Aw14Br2fGw9-RoUFIABqBBAGUo4EIsIw1IHPME1I0P7ocEeW-rM83c0FCSEqkbqhYAYhHB05QxLIQB75WQCMRMjjhO4hJEho6Llmca5IweM65QQYhB4elJfXQETHYCIK6a4drHDFiEQkBSOaI-BoMYQXEXdXM-2W1_nRSvdAICS2MDhjlZk4o2o-vvUACLMw8Yhgjj_PcDlhkojHCwwCkRSMGZDYI4jF3WN8ZkI6PrKyHYPsH4N_nC1CYYAotZjj93_1Fz77bP9_-qt_83mXH724_5df3thJtmWaA29O7cvD-n_84z99wNu7_YGmScpUOGYRV79-vmu3Wid5793nfuiXdSoA0vTyavMv_8t_fX9z9zt_-HtuOG3Lpy8-f-vRMwTIOnucL5dMUEkgEMIQwsIlvYcIlL1xADlfepnJ8sXGudEk8Cgp9CAEcDcPCzcL03o4_bP_7DdPa7_b33_lq29MEGvAZpI3L7YM8GhTv_XuG7_3i1-7fXX_Hz7-It2CjJRZP0QQ4jBnovMbhwkhuQSIiA4kQswQIenn5jT7RNh5nh7OxBhWahEYNXt1oypJOGAgU4fE4-KQ9XFu4TAkHXyptnQTTKg058iBChq4sIRFBAWm0i4ybi_Mkpb6wse-TGWyMCEKyR0zBlNwfsCmIslzv2euFmgWAXl9TWgDQECoShHQQCR3YEHOqgMAAZopsWRzrxRxBJHqrvH66QwgLAPbgEGBIATMhZlB_8f_vd__2tMnG2Z1q1OJINWYC11up6uJz67MYu5q1pbT5WX95jvPUOOzF3fHHiz13bevP79Zp5kJaG3dEkrqXoS992989P6W2SKkUmFq3ZZVy3aypsuykhCzeKBHFBEAWrp2td61lNpVN9tpqmJqOai3CAY2NSAss8DwE4WZOYaNsSCaaqqM3FwKi4i5ZcUukWaZUgYMjnCLvAS7qzAE4PXjhw8eP6yTUCmH42G3uwiI6WKnqlyYRHKdEu7zdmthRGe6O0CgHfbH3__d33wwydL6zf5-s90gCgoS0HZTN8LPH15XESrls5_dCOJh1QcXu1rl-YOrvjR3_eyLV3_78c_uFy2XpfV-PJ3MvJ3WBCSaemXp1i4utnUW7d56F2EgWJeGzOYudWqtOcRxOSAh1jEF9Igyy3rsH7z7ztXuElzfevvp9eWEx5CpLE3v7o_zdtM99oeFS13djqeVEO7uTofDIjV534FcIHAufLGtgk6BbvDhV56998HT414Ph64WVcrh9q7WcvvyDhi3m4uXL-9z2rIuJnU-nk69NWb23ogLUzXrEB5dAYDLNM8bZPSu4Qn5cyQmYsuHDXPrnZMCTohgCaThwsvhNO1mV0UI7ZpnB-LS10aFEBAorEep1aybAxYaY_fAB48f2qoe3jR28wQepUo7LUxATK7ApQR4kSKFwm1dewBYeJhJZV07A1pvgSSlSBEzIObcwKIbeKgaQHB58FZ-9kA4IgNEwTkgCAIASEYWAD3JzeMuE0BIKFy9GxNTycKroTBA8Ag8BEJ-pGaQBzCApCA4CRORqSKzW2cuGTjIsz4yMrGrI0-BiCXdZOSOIiUgSAiJci2RyzgizCw-Eg_HAWZVOVjSXu5MlAeUcKcqbooJAAUfpiqEgdmGDJ5ylvcBOTwYqRCrhocJn3nsLOFOSEUEgaY6Z4bwnLdmd0uMT4RznZIKOj5UPaRIgYKF3f01wSadnUnNQyQsTMKIZN0JiRHCg9K3FYligN4tAKXK-OhHdHWSQgF1mhx8FJCZmGiSUqaptSac8BZcdRWipJ1fXV4SRikCQEzIIsg41cqExFErP360u0T62gdvPnvwsIgwkxu8Ztfg4EUCEsbrwTYOudG5bxxJgMktxOtfnCaJ87YJLBWVudWPkXYZJYjsRHpkOTsPPDkLNDsLqHK_npHpCEojakQwD0Qjh3a92lxQRLZrc55HyEM2kMnedBWdlxkwaP-JD8oTGiaogSwS35szdT6D-86Gr3xQDPlxhEGehbLkmvcKhDxM43k4PaL7r1cpCKkFcDiHOwDonBHKX5ZZrBHTzzj4Gcf7Gu5P534ZIIaNs32MEkLyr8iH0DaJTYMIlBElh6DRqyEfDYnhKj4XmoF83GPNTd0w82CINirfucxZCQdciAgdzSEsPALDk8uZzUvwtEPkBjKGnFs9BAkCVlUBztE_EphpEjMCAtARKfEIFANZBJjR_GwnRQ9A4CAMNwzwwNChVwYI87EfJBjMgMQ8k5OO2_gQ7GJgIObgCwG7-dC6QQhyiz5jzVskBaA6BaOD07nRjjAhGxgjB8IWa6ARUJxVykzIJO6GTAAhzEyMGLk4JSEmdggzTQGwQbhHxiMZi5kTUF4BEl4pgnORz-8WrvWXnr_1jSeX7z7evX8x_9m6_9p2M1NZ1Bn9B5-9EF_qdqemm6kKB7pb0-_8yvs75ksGXfTJtpapbgjbzWmzu_iXf_RfHU-n3_6Df9D2vRS5_fLm-YNHWWlyAOahUoxI_FswQiEKRrNgxlxlBBghBIeDITAMvfd4H3p4LQwYsxSgkJQfFa5VvvHNZ9959nhR_euf_PTfv9r_f_70P_yLv_jxv_n3H__rv_rR__2HPzp2v3p4cXffcXPxO9_7pT_-8ceo5unmRgC3sxWbiWA11UgkjEy1SuEqXErp2hkpuyUs5GeFhxBpTgeFpTBGoOebMRcUAgGEEBhJo6ucTO2hnxvgBMOAkMoWno1eIMxt8vAD-sCM5Uc68wC0EiPR2aAiKIFVmBiZUMMi8p4DAejgEUM1TYIeMcG0QA-NqUwIYWZCJROWuepwHdejMtd1WYkwN-qlTh5OkTgsT06BmTILEoUpS8kFCwmP2YRqEDuCEJ8ON__Lf_q7W6phZGaGcFw7IhSmWQAD1I0QkHhpjYX2-9O7jy6nqWLwn336xYPLzeL4xZeHw2F5-Gi7HK1pNwBblUUAo2t_-_HDy01xVQIWZoPooMfDSdWPS2PkpXcDL1zcsPUGgXe3p93FBgBE5OJyCsflsCJ6EBJj5lAdYrvZRiQnF1UDCVvX_Nx3NVODcFNlKcmNADUCirznQBCCm0khAgqwzOw9eePxxfZiu93UaTKM4-GAENMkujYk3G4297f3m3kuRda27nY77Vo28-HmkKhBVS2leO__7X_0feqdGC-2u7u721ImgAjD7cX0aLt5sNvc7df706k1PfSmqnf7-yeXV3OReZ4CcW16f3cEmQDpeOr3h9PxsGJQa2otAtA8bm72Dx5e3d4c-9py-RwQQqKmwtib5oG5gxMCRiFCMOurY2Gq06effS4RT59ePNrtruc5AFql03FZVdXguDQqtbupW97rj_sjQExSEt9k1utmupjr7e0JiRTto3ee_MLzR4B86LqsKxdeDmvvpobb7WQR93d7h0AiU-VJiOBwvwpRaK91kmnuywKE62EhcCSWacbKy_HECMhg7ubuZsis3TK9jCMLAmCmvWembtpsMDyzbpZLAOtg0NWQBRPf5oGIXJAR3Iyl5mQ0IL746WfTdtOWtrvYMhBBhHtrKyG2pSNTxGCpM0vmnLt2XVdCPB0XzDE9oltIkcilZRG3HI45EnUzEeDy4DlQUDYAx1HBISJrznkazfQIviYRp3GQCNyI2QMsU1BhQxqTh6nMqp73vDnWSjuIE3oE1woeJBMBEIutxlUgwE0CkWsxz0JMuAEx5UQ4ENEJgsKNkMJMhNOXTrkNGVGJ190x024pY5WMIOWMH8PUWNg1lWnDUBuW4U3OcxcxWyK0f95jJYjA4JwMIRCTaG_IyEIWRph-WSBhEE5jMdViXUsVJARzlknNINDRYsBFxnGLCJk5nSDmVmpxNRKqpRCMkra75dC9TOJhxIwUzBwWZZoypkGAtU7dtIiUUsKNkSKcSzFwJnRVMAOkqVRGYCIRBPIiZZIpFJABAnLGhszCcLXbXmzpvceP3nv72dV2i5AY0ixpU8AZQRfg2aG2YXVCTF77meOZT7EA95xRZg8leySEo2ACEWgRbmAeZpZ3htwEeA668zqa4JVR-SWPSNkUUv6joKQWuiFgin4MFZHnuT683hUmYcqX7HgbBIhwAKLldHxcXM7T9niN_cmhACIICbgzU8pTifncs0Udb6VUar5utsCYr-HrN97YPAxBcozCASCM76oDIhlEZP5sWMHAuw-LGGL6uDJpltih8Bh4snws-aAVnY1pcZ7QRTYucJSMs-oDHug_ZzQhBGq2WkfEa_S7YVzVRs1YgAN__pMtnMy7HALA6wpwwOAOZfcXkS1eFyjGv5CXZc6NEASMlSAFoUNyh3JsjDxgxcFIBRkQ9bW-AACQHD0oCzWOWRIHDwDm4hAEZAAAUBAdwAaEJafzIVTMvaAAZnwuNV2cbKuhF2TKl3YEDQNJ1lUDAqCpBTugAwE4uAISohCzICALgRMI5B0lSTmW5kgIoZIlE3UXxjArUglB1aoUz_wvRKptI6mMkf51BIAwCnDOvQzlp7cgQVYYf_jxi-dPn8VmblTNZQsgjrKqkEzCu6n81rfe_JOPb8C8L2233YLphukrbz1-NO_A4-Xd_eVcV9WHDzYcevf5SxL-43_zp_vb-9_-vX8Q6oTw4u7l1faSmZCgEA5MgpsQAQSPoi-FBxMyITMLoJBcxbWRjZ0cQUpQcPAbnJAI0QGE6GIzz8KbSaLHX_3g9i9_ev9vfvjFD14eb5YeiJs6URUiqED7Q_93P_z0J58f_r__6t9Hxf_u977z-PrR3372wl3Z0A1aMykslW2mrzx_8t_67i-83N-9OpzubvfTNAmjsAhREoTBxvItFzDgIIVpMDw5445qLsyFxXx8gFiApgYHkZEqFgI0t6YrU030LxMEBQW5mghVZjMzDUQsqRImYGYzL8QsZG6l1BQYcS1pg2YSVctsetKzwoOYmBgsCpGQQEBYOHuOwgiht8iqDRK4OxKQABCra51kkM8CmdERSCggGNkRmPMawkgUFtlXMbVSS7hxkfN8AaQUDpRCz6-X__R3fydW9DCiOPTWuiFE4Xh4UVqzsDAPYurNjr6-_9YT1gjHu31TM6llbWo9A6EOQEvv4PnhAEg0z9SOp0dXO-8eEPO2GLo1Py7tcOzTPPWuImWqdSp0Oq1IaBZSeLPbZLS3t762tdYKBGHAQIxcprqZqqRpEBAJTS0_aTdcWlvDPZmPXEqqhQcfWQ0QSUqmO4uwd3v7o_e3F_Om1rfffxsdLZyn2rtq73paGRnDtheXmVsc0GJG71GEkBI4noVGm6Zp3s6zwN__9W_x2rnIXGlt2lvLff7Xv_GuNMfwFez27rC2bq7mYbBORBPz2rpTAeIvb-8PS78_nm7v9sfTwsyAkE9gM-uqLAiMx-MeA9bWtLX0nYMBqK-9AyMyhAGsxlK6dZTAsMLspsT8g7_5-Dd__Rcf7KZ5mrjgzXE9nhbrcTie1H3tSkLtpL31fmrW3dyb2lRr4bi42I5QgKoSXTye_8F3vnJ_1w_HZYE4nVYO0taD-ObuMF9ujofTqpozpabKRH01JMxLnbBQQF-XZLIjIQRKqYiYyaW2nKBwMKl2LoULYTgyDSiOam7hMGBzcbkc9yySYVk382YiiMhB4G45A3I1UyUcIBsIDCbvDSLQ9Obu7vrBdb3YnA77iDidluV06O5rWyHDD0J1Fl1by-pcmPeez1_VFQgsWctCGT8Bd2A0M1cfzPfCLFfPRjcujycIAX5mZA88R6Zi8rwbFORGCKCWEEkAR-ZwoySlDcAOn39tEOFQSBIiozshBiU_ZCDcI8KlFIIgQpJcgRMTRx5zC3MEkrhHrkExAlwJMWckxLlXHSSWDMKyFEh0EKGIIIapYQb9LXIezYzIaBo5Xs4YCyC4WST6urexgh6kdR4AojxfOhAXj-DKhJSLRxQqLJmtSEZDqr6QwLqiI0-zmhGRSNXWSxUPc7PwAEcI9K5M-epB9yAeu46eExuW7DvWUsE8-5TgUEpBTLvWOJVyzc9j0e6lcJ2myLgg1-P9ARGYS_YaSDshTlNV1YvtNtyEKULHn5mIiC4uNpcX86Pd9qOvvP3m00eFyB0yNhOeFZJIM2KiXxJalBF_QNDXnH9Ei5zrJxp4pFnMPBByzWYBDmEQqq_3BEhMDlkpyYMbJcrTYSBFEyBpBh5598g-Mk4Tm4UQkSQNwxm5ED-82myYc5I3eJo58k9W1mv17cBsQoockmqa0SUkSMwdYfrXCIksD7oBrfVsp4TnNH8cavM_RykpGx3gpGgihI3OTYzaQzq5xzk7da95ysu7wRmrSsSBQLls8yx3Q8o6PFMyAzCb4Zw4y4BxzOTyuzyswwM2msQAeL1cSJhmRCJrB_s7ZYgRAJFQ_zPIKRc5KQfMCPf4R0mCylsUImr40AsQ0kj056sI1XyQhbIigRjgnJ2d3LogmykD5hVpGAwAfID8wwlcAwHVw_DMlQLECCEMAsyiTG43HQUZHMwDEbq75Ahh0KZ8ZKwJu553BCk0JAbwKmLdkbF3T7caOChYkqYKMQRkg1VNhVndkKl7B4qIqFIYUYgdnFG6dyGBiFkqIJpbREhJqRETiblOcw2zBJjSyGrEubQCGDARFaIgAnBmCYpVu2BJM5og1Yld2ze_8c7-rj-YLzai7Ihd7-4Xh1Dmh4VOWj98_Ma_-MEPXnT-4NHm3acP3n786PpyE9ZWD4g4LWudSgih2ixsBP_2z_7iuD_8zh_8XjQFgqWfZp5rZUyo-aiRRCEmIk87DTgzCmLKwSJckE3WiCgp6EUQovM-DUSyzAbowVx7N-1-7HhU57kCeFDkUEa7urmpQ2AQXF9twtx7gxKffPLlv_yLv1uj__Z33v3mh28_2G2ev_3k29969-9946sfffD2m9urHvzXX7y8O0XlEo6ntX3-xZd398ftditFana6RveAAaAUBM-itwPkwI-ksCOqaSmc3eJaCiFULuhBicONYMIq1cOZwdSF2D0EYqolix8OIExjWjB68jDVSjiq1ZWImZkLIq7LqUgFCKnSe5-KWJrsk44dWJBq2g8zkZe-P2QPc3dm3AJ1MxssgQBANOAgALTBWA8iCgcGdDeeJKmbAOhmXDhJFszFwwbLDxEAaqnhjgQS_kvvv_-9X_q2RGynUiqfmi2tQURFYpbTugKhOzAVdd1N5fn1FgCn7fS3n3yx2cytx9J9WTQQCFldU54KgTLJqr2yfPzFzTe_9rwtrWnvTSnoZn8k4jLVcNjVaZ6Kdj8tenc8beaNWwDAtC1uAO7H_ZEQ3Z2LDFOn-WazIQTXgc0YLOuxSnU1tTAUco263SBiWwwBrKdTG9Q9IDCMwHdXlxe7ab7YFpJ5UxilmTZ1RPB1MbV5u23HBoxchUROy6pq2-3m6vJiczn31m--vCnztJ7a7uICMLp1Ydovx7_3ra_Z0td1KXO9vz8JwjzN1xPPlXfb-ld_8-NuvUdot1rLsh4_eOvtcIBp-tmLl5989uUC2Nz2p2X1tizrkDmAdVdHOiwnAuqLWlu5sqmam3lgoLqVwqsqIlg3DCwCjt7biZGYydyZkgEt__gffv1q2grSsrTW-36_YkFTBIT9sS_LqRReV3WI02ntq_ewaaJSihIy0fFwrIQO_vu__gviclz74v202npqyRpX04uHly--eLWe1jrVZe3zPLk6eIQkv1XrVM2trQtzCUreBnKd58sLU8Wwfrf3DBYk04UInXpvkshqN18tDzMeEG6I0NY27bbWu7slPbKrIYlDEJOP5LnRUGC9no8DmEmZUOJ4e797_MCBDje3m81OI1_b5uHk4QrzZtZuCAFmjqDm6t76SkTraS1TbWsvtSBiKVMGKLQ1AC91UjVm4PnJW69Hsm4OyCPewKNWCCmWHuN_h3yMIxCRZdePItwhbfOQTUEAT-k3Bnqy8IFGfCg9FpCSkQgSDCDXzkWQwMxZxCMxw2iWnxrBXMyBmL33lI0XIXcfRl515lTYGsT4nvrArqCpImFmssEdc52aaoFM3KeQteug6uVKngWJiAoS92ZcK0o5wx8DArgUIg7KfTqm4iC__oCo0y4isFCYjzRMxOhnIAKnRspqLRmdhACCQAvCgPDCyIIpzckcBgsliD7CIhwTWEHkqkVknF4xO8RTkmTcwNzqXJGwFiEkt2CW5XTMFFoPS3hRzoi58Lypu7ki4ul0rFO1iN123m4nYpoLb-fpg3efPXt4cbXZEgadOx44jFR5SkwkPwxs_3lDlrGpvInmgihX7Vl5BUJgDA_3MIuIyHconXU8EWBn9gzE4GBGQNcIg3CIIEvzUmSQJlUIwUSKUEXWbt7z45q6tUNb3n50BT0IKc5HQ2HOHHyeUsbUG87p9NFZgLOeC8DTL2t5mIVRV3UPUPMUYOfFNCsQA-xKzJR_BwGCGd2cE_R57g2k4TuzUxliH6H815SlvDb5Gf8zusKDP5QO19egVTOH1w1-xIgQptdfUozBPIVH9p8Hqo8pIbtBZLn0SJy3oyfBOru6gMkJGYmhHD8j5sVvaMtgGJozsuQ-vi0JJBi-B8A8LGd_JDu1PLiyOFQSxACeBMn0LCSsHRIoBDBTzfUXYDAgEZmP3UHlAp70cYJA92AWh4gwA4is9OV4EzERPThG5pifimk6J8bXteW05kU4chqWk1AExORhGVQnolWN6QzIRSBgB-CCETaVikARY7wdBBjoZkKMTAmQMQgPz1z42LkQnEn_uTxCCHSEItzNslQj-dk44nVhFsIiLIgBPMYiALDZzR988DardfG1H1-G3Tft4QfsX3L7uxfrzc39jfovPbv6lbevnz64upoECXrvDVEhvnxx29X2-2VddFdHjvVP_uyvDsfld3__-7Yu4Hi0FRvsdnMgptXRMArxORYXzOjulIAGAEJkxoLQXBHIwgN0_CMeHyqUPzIkAAwKJFCHU7NucIqmDlLlZBo9TL0gonsRMI--elhAQCFBtELUHX_wyYu_-LvPf_L5q89e3v_sxf3f_uhn_-6vfvzJi5vF7bQ2dDMPmUqtZXd5SRj727vjfinzdO5mU4w7JyFhEQYMNcNC2dkNAPNczAZTde21TOrq4ITQIYLAMQigm-VGJAjKoHxhji66qhQyC6QS4cRUiExVihjGJDUFdkzctW3qjB6AuLYu-WAC4kIFCRC7GwIULCuYuqs5Mpm5pZWN0dyISDGNInTO4CXKm4GCUSCAz2smKSUxehjhbqWUEQEAMNNEkWSrx7txoeSDC8mH3_jgN7761cwKd-03x4MZIMLFpq5t6d2ISw6JNPpuW8UDHFb1HmAQy2Ldw9FLoQhUNc8ljGCEcSlzodP-8OByt91URtTlfp6qqhvSouYBKLyuK3icLH-SICiObgbadV0bWFi6dgTJEcOLFA8ngtZV8tNbKAy6dSFU02maESnblVylr1bnGdxNeyaLw0GI3fXi6gLMd7srd3I3NQWhtbVaBDzCrMyzlCosx-Oy2cxBYK3vdpurq0sC0LD9zeHy0QNCn6SwZL2HAOLPfvjD__T7v0bmhKBurTUgfOvZo0sRZl7VNTB3nrWWpZ3efv58W0QdP_nZFwfth-N6XPRwapfXG8FiGghBQNr0dFwdjZCnIrYsJNKtb3a7delgYN6FRL1zLYgYZoWwawMQtBDGtFbtLrdlmt54_qC35evvvyEB-9MiQjf3XV1FqnmUWbiydV-0H1rvR_cwiFhbCxZddGl6WpfdZoPsv_jum_t9359ObTWz6M2zPKZmALg_HtCDZDxqwVxNPV_fEYUTsMF1Uy8utvc391TLNE-llnY6tdOpzrXW-XQ6iUh0JWQEc_f1dCp1CrfEUgYECbs7Ri6VsbeeM7lczHp4dC21hHY3xbMPFIDy2kAAyOzhHGCnTlP13k177ysLs5CrW--9n6ZaSeh0OAI4ulpXdbt59UXawRwCEQqj6wC6AICZAQQLaet1FoTgcv3GOTENwJxhptzfxdB8ymvweSCDO3NN7w8P6BgM6fgIp9JoPDG7OUnNVmiiXFhSH5Q5Ggh34hLuhDVPyeNbB2kWQ2ZmRu_nfEgYuDlEqCMHRAIQPMfD4UaQWAZHQgDWboheqrhZ-lSISXtP9Hs-xpnYMcKMJLuflI1AADRLDDtOm8m6OjggRo5FmXOM5RHMIlXcgkQAAAxyWYZEPaskRCwEBG5KtZiFMI82FZYg0LXRMO9SN4WAwEhcYn4zibknunUqaaWSUlQ1g2h5GsuBUKlVe6vThAHzZsqISK0lzImIRTwszIgF0CGICkWSQ4VqrQS4206cpFHBIlxrmacqTI8uLy5304fvPXm02W1nGfXrs4GSUh6BmeemlOCk0yYAmFCIhtOYMvMU2Xj1XH6dMaAjYYOvPbjgua5BNPNEMA284ShLAqXBOF6nhyBFiIRQN9XMGdgMJpGADtC3l_P1NH_w8IGQuCkQeUQWvlOqhZQe2jCz8QVFot_ywAfhkG7m1xGYQcQZtYe8EkNGe8PDUzuQtr3RvAPm14gtIERJ9FbeJLPQxaPpkdPuEZ6K0Yr1kdIJwHBz90AcYBtPf27iaMaXhDYseXmDyugNmPvIJaUeAej8aRDJYXzd4ohR9o1hDBhFesyJ11ASeFLwkxiWemZK2enZgTAqEYxsEZ4tlwCEKISWVzbHCPcxYUy-6mvjGIz8c0ok0qKQWy3Ipj67q-QVNKIg9W6p9RNiDwsPTtgAICJnDC1G9i88LAgtJ_6uhck8kBkj60kEBAzi6q_rKMkY9dELyIdAmDkCjgVpoHarU8mad-AYIBDJBKRkCQUseYHAs-cLAZHMnIUSE1lKSXtrolcpS96IGMlbO3uDAF2NEYWFkAzBU5FAzCwIYK5C4hEyM2eplWXaxF_-7NWXx_blan_5o9v9zfGTV4d17cf73lZ9sd9_9up-H4trvz2cTu6v9u3U9LDv-9ujA0zzZGHe-kfvPl7vmwP-6z_58-P-8Fv_8HsFwTFiVdO4vt5FBFF2-yGL-5ke1O4inJfJRHz2UEIulT2wEAoJEQmS5NkUMBNNJFnYKgHkQFJYMJh4dzkLTe5WC0y1bKrwJEwkRFOVTeGhNPPAQmpuphDBBfMI5RFFktYf56KHITgzloK1lHm7MbYXr-6Oa2x3c6rrswWe1WuCpNE6ZSmOQIgJaSMlwJhK732q1cILs4KPJaMAs3g3oaKDBsqtraXWZVmKsHugoEMUqQgmTCUjnTnSIgwgC61VwqyW4gQi-fzHxIAAgJ6Xox2tu6EnBXt0a8CSBszdQ7szgmBRVwggIGTu_vNYfyBYNxFBIi4Ew5g5VJDmISI5VrNMSiBxEfdgQgQQwl_43kfffeMNUFWzpl1d06wniK1ZScO0O0SsZo8u58u5vnr5yrHcHtuq7oBNjQnX1olJilztZvMgQlt6j0CPeVPu7k_PHl3PJLt5t5iZxerKUszUItb8XQF6N2Y2AzdHxNXU3ZNbau4YyETTpm4201gyR0S4emYn3c3dnBC3ZTYM0NhspsK0nBZk4HzpIqCQR3ApTFQKPXh4KcKMcDocuNT7u33Z7DAMkKQIMJ-HuAUQtKuUEu61lmnaWCgA9Ka7i926rIAwVclN-IT2-__gO8Xwxd3dppa1-xtPrwvipoq53--PJ1VFJIAvv_zyrWdP3n58fXdc__aHnx7X9dT7cbEW_vnPXmBATbXWLCL04UfPN3V68OBqQlZVQFiXhUXAgEvt6ymCAIy5uDtAuJ3FPGDZ7Xd19xACMqTQCPvuL3woqbC12O42yKwRp7VR4OnUpeL-2Ho3IuzNRmqk0FxZqkjBwsjGH33ljRf3J--9THI6rc18aQqEAnx_vw-I3nW73amamZLQuqzrcb243JS5alOGEBHyuL_bYzgV2e42TNAOR1dlKaoNWDA8NB_udDoeSxFMY2vkQ5WTXJfQPCCmcEkTSJzpLQBEyLl1T7q0GU9zdDVrSa1IAqeDn_Z3x8OxL0cRyTLqelwB4sVPf7DdPbHw5XRc9nfa3PMbfVynUqnw_u6wnTdjYkWY6GftnVN3FZ7FCi5XzzELnuDABBaIjpaHehx_jJQ1AiMgEeUTOmgkGkYFE7MZLBkkSh9eTqmJ5Qz3TEUAgod7IDOJZDScCTEwArjIOHYAmToXGbNBIkh2vwXXQsCoHcK9a_52CIDEOdhDhCKzW0-IjJuBB4Zl1ZhS55XgIGRVzbh_LiUAjYSHmSZrvgQYwVLC0sEJxCNzCZSracAIKhzghEKFGQU8ShELRwiRCuEAxFy8NZlqREzT7G4Orm0tpSChAZoFMYlI3hpt1TxI6dq51oQEExMihCoxiwgSancRYhlhWiDKfmAVsQgmKsLChTm7WYAOZlqKSA4VIzZlrrWa9WniuUgRLpyphvLoaiMMc5HHDy8Y4NmjK1zXeVNEGGWswM3dMTKE4J5jpBR7xesTr53_pQyJZKDZs3-ZV8Th5GIkJE5gyZk2lWf73DNEwtdosFJ8mJ6ydDu47ICFRQSFgQADFMFKMTL66P13rspuW2dEMXUpHBHWTQoXLknJyKCNZbk82_BM4Xiew1P2Q3PZQecVwbDzJP4sszBDHpAEoMjLw-su89nDFYhYWMJwcF5opI5yFTDS-wGD6DQC-zHcvgn0ybKpByIlIz9f3WbhSICkbsm-zRZyon4IEYjMbHyhQAGOjOeQxbgM4HmKH8PFNPCI6dg8Q2fyfZc5JsxtqEUmBSIcw71gydsUpvEYARPSz2iRsXp0DclFRB6LmRw9O5QZocofmSfSlc6TAgCi_AQBIOwenIVp88Lilu928BGYOgu8JMvoEEhuljdIwOBgAwuCcREIY2TXGFDfONNP8_ZFlPbWrGNqc-RMhHsylBCROfG-gYgTi417TPI7IZg8e1PkectyNSJ5PUtJDBQCCLOpMUogTCweYRZ0RuJbRGY9hbkgO7iU6q4IKCQB0XXUgXKJoe5gGCzXW_qTP_qbItuD8sNan12Xh9fw9sM67ZAoJHmR2C4ua258bvYLEm3mqQo9fDodj_1-Xa4vturw5uOdnvzY-5_96d-8urn5_j_8-xjeuwZgP7XLi13yc_N0lXF_s0i1H2DaCRkiAizXF6lNK0Md4ykMyQuzey9SBsQKSCKCqTVdDTwQTuqntYIT8EQC4IUkzC_LtPHJUQVw6BEdIqWqBEWE8-3pQYKllgygAgURlXMFITy4UKmby6sLCk9sHNF5gWTBRL1phlIjwCCqTEOox1kfCyQWDERgFA0XImbuEREhBBEhJc0BMNWyntp2s9UsGDEQcZgJMiddg0FyzWj2eoqRmRQuxayXIhCh7kUKAanbxIIBFgbIqfVGYIRBMmZmyIYaugC6GwgxswjDGCkgD7cPlSIIwUSmhsjMNQCKcCCmIaVIBXAmNA2pnFKU3FLudvPf_vsf_aPv_wq7HU7L3elgHh6ex6O8QxELQKjbVPjZo4tYtRvNu-nFTesBgajuDFFKqXNBj1UdAVdTR8j--26zCVOAmGqtAlwoCE-H7uHgFBDL0jSwEIJD9-FJdHBzX1sXYQBwN0KQSeZ5MvPetQiDupAkXut4XFiYCyXoJsmSria8WdeFULq2HGuJEA6vhAfEowcPt_M00pumXMp6OjlQU91dX0HAPPHl1YVIaa2hp3Cqz7V07drCPbRppvgFo7I4MSJo73_427_GXWWqr25uLq923pbLeUPCL29vT607sEc_nhYO-Pp7735-e__p5y9e3Nxvr3ZI7Exq_uDhDh16N2_qESTl_8_Unz3btm3nnVBrX2u9jzHnXGvt4lT3nFtJurqSroqUXKiw0nURYBtDgnEkkBhnBJF_QBJEwAsPvPDAOxEQBC8ET-QDBGRhyEwTadlpS1ZKQsJKySqubn1PuYu11pxjjN4KHtqY-1pPN0L77GKuOefovbXv-_22hTI5KT19W8fjw9k2a9JqT-8-ptaYGNLSgyMoSAU2jCJZcfve08YiAgoL88fzYw7_63_h53iNNsvxOC_rYEXN-6Sq6hbhYUbLulXw8p2nN8vwwzQvY_TW5Cg__KV33jrdHnt_vQ0hXkZmE5LUru62-mjQzcfUNIkOfeKkx4dL69Kajs3CaayjKZL4cr6IyHw4cdL5_rEW3Las0tQjMoKYukgdD5DJIDOTPoVt1e6qyOs0n8K31iYfm0D2QR7X_phjHcyc4ejgFGkaZoAyc5aghhHmAo7LQqB1WUiUmcflfrl_pSLruumpP376SfpWs4xluXAkM7s7x6Aqom3GiuW8sLRt3ShKVsRuY2yL9CefiyAWZO42UexFVGQU5ZALqFOCIc49Z1zBjPKBX1t712dyJXGjmgBxNYhltSIgqA3AriEicP0-IAaqYR3uIqJdzMqhWrx4inBRcMF_wL49QgUsyaCyoggXD4F87KkbkR2zygSVa8ZgtwzvMo-rGomYcvftMHOJM6OY0JHBVEL4RM2DiWIYMzXRSmSjaXhCGoEY4m5EqdqvDVBpbWIhYohqIYaCUnsDtLc5ybXaA-HM9bVMxclvh04ZlRoXlshkEdXGxOGu2m2MelHRpLLAqrrvTcCt9X2yTpzm5GzuCqmSeG8HSgPjcJh8jNubI7vf3R5tWFe5vZk16cnd8enTm6e3x5vjdJiUcwBNRDIq8vNGKXsNa--xtusA--qUTaoXcY-_iEBQEXimH9B4SJkVUqd_RU37WAUqUAUnl5JWwCqASHjuC3hQmROythHAxH5o_COf__zTw9NnpzsO2X-ACUExfiqTpXXiLuqoxyqiFDXPJihiJypSUojw7ioICuLwpCtiMcNbNRZzN2FxlZMjIVyIqgIaClAz-aKio5r2O6eR3gSf6mFJ-ytZb9uS9NUv-gHTp6I4-31g5wnsHYy6OBFx8BXbXyd4ymra5zWztf-xe4I_icnd3tiAM7L4WkFRXrD9M0NMQSggEqHgVxU42vGvzE6j9g94M8Iv7hDBkyyJneT6g4sklnQfokocJePOZMH-m1dUofRHRBTpCtkTaJQCtbB6X_rOOeTak6lIUDAQTCrivAe7QGxGDCbfn3AQZuYts_xF9ToW7KJOXilX3UfsJrgmzSM4SxYRIHgkAMGuwPO0QhuraqZPMvmuCZfIOLRCp0sJnsKjvLZhlZrbN0xZFkUiihRIY9YEgYMCKukpIsyypRG5Sv0_qavWFhUiQcSCpnTxODH-v3_wh3_qZ3_4g-dPnj2ZQTIWV6cxOLc0JxLekmPjdF6HnZo8OR4hREHnh7GazVNrBxx7mydsS75exm_81u-eH-7_wt_4c7lluB9bf3x8vLu72-0EygxEkgIi-kY3U8sZAQmDkBXBxO6JyEAmUcPuvFDRvegGBvvlcTlv2yDaIrPxDDqiIrtClAjyq1p7zbFzrfZbPPfWrgRaEu2KVoN_iHBeRXpX1hghkPuOqTcc5qlCYjVZo0oDMXrTJDpKHxm9tbGZCKSu4J6lQWuFbgSisLjEQN1F9xiqouxRrAK3AbBlVGNACKcmtU5J90knitDWwRAwtGrIYsObNDMHS7wZrQGgXCOCQqkT5Tk-U9x4ePkZ3AOKEQaSjARJa3NEdEiU_Qzsw6ROBkl7nhBQqRtCmDkUNYtQkoLmiIqZVU-MOI3pcDg-0vbk7fe__NY0NpsPet5GOVKCUsDCpE21CVhbkydzS4vVnLXfr-Y1m0hW8KTqFuvwAjhPU9OaJZFs63acJ2ny_MlJmcxsW21Ehvvb79wA_PphWYd7EATDkhlmTpnn8-Ok3UZEeGvqYxwOJxCJcIyhgBR1kGUdiygTIVYv1Edib-WMbZmnOcl9WIHU-mHOjD7JYZ7Hks_eumsqXSUzLMItCNFUl9VOx5mviXOz8fD6nkQAmk9H7Zoey-U8n2ZRvHz5mBR9bst6HsmHuSeN0yzvP32Cru7ZgLfeejJP0-N5fVw2meb7hwcKenI6fvmL77988fqjTx9GOMAO2daNiL_09Paz83p-vIzwcA8Pbf1w7Jfzdv_6cV1tPS_kcby7ZebNBiVHOETTE0kEzE3dYz7NKrh5djNNR6l1UMRYNxZVFWL8N__qn1lfr-hIz23Yum7rsDFGE1kv27Ksx-N0uQzLXN2Oc982I8jDstYjP5M-ePvZe09unfLV_UKcyzqIsGw2T7pcNh9e85ckLqz3eVlUhLXNenCKdXnsvQd4Xbd1WU93d8x5uSxQsXXF_uWfMk22bSoytfb4-AjmgjeycLilOQRC0NbSoyb-Va8120QkM7X1sCFAmrHUPFEpCaqV9NTeyggt0Ermq7akGJft8M6Ty4tXtjz6ZUGT5fExbGyXs41h25pZwOj0Ycl0OZ-ZUudmj-P0_PZyfxYFZZqNonSu58eGVBaVssHud5RyJ9VgqR66kU5gJN4YZKgCskQI86K27_NMYncCEiJMwcNE4OnMEkylT8uUkqKlOc8otLAtmzSJNEx9s6X3g4cjG3FEWm6utQlIZLpqC_OMhMwcaWOV-UBEranX7UulIlUZUVMrtFZTkYLGoE2Zw4fX_azuKNpauAkhmZMZIleqbxLBhksXQCKCFUEgiz5322Kwi6IAo6oSaaxTRGSGaHN3Bk_9NmNsdqmkTJpHFZ2ppqex0ZDWCjNIw1JAQqqTqNhwJlo3ly5a7xqi3uZ1XcBEgvAxHQ9pBuYYkcQ6SQntk2nSeb0sx5tjl7YsKzOokWZbzeZpZhZLo4ymgOD25gmSRAXKz57fPLs9pfnh5nA4TqepPbs7NtByXt5--z1lVbQa3nuOOkCXG2s_mu5VtYzClOzy3NzfP2BiqTeNUELFhbMg2KX4oRRVVS6QUGQSyCzKW1wqzWoSR33ZgveCeZKIpHayIR6I-PznvxgpcJBQZFZBsjzWYRlUh1pBDcM4mbPzITgjohbQdUnmCIqkKgFH7iza4mB4MGWGE8GreY7k3WUV9dDP2FMsex2F4o0fY__Lyz6Pz6vzK0sxFvup-foJrMhgXjmdu-Q2dlEt9sUiMVHUGXn3JXugCYMokpPTjFVI9r-CR15ZMdVuKBAnArKXk_41aBFYPF2w1zYgnKCIUIZ5Un3_MyKdqdCfXh7ounusOYSEy0vCkREikpyWriIj6ooVDHUPcL2KHJFgbtIsBkPcvNq74ckCj2iQoGQWC69Jv0CMKEHuDhEP5sa-BAiSqOJH7SadUgX1KiqDpYcNRvE16tAvnFXxMEGjYCRbeoR3lImCKcu3VdUYYeYGzgyv0oXnaqGCppXE5jU3YdHkNUxY1hgWIcRz75FBbTdOiyKCNnNRzajzffl9sa3DeRcv3ky3y7hI7z6sbikqzTIUSim-E50YICHOxLJctgVo8dmHLz54_jT7vF1yxpgOtJxXVR1IUu4kbwluGk1MHT2Jly2IYEIyK6Qz6Hy5PD_dHgCekA-WCMoQpsu6am8H7Wc70_7KVNOehOFF1qp11R5RY2U1DyFsNkShguRU4oyB5Ho-kVBdyYRpUuHhAhxvTo-RupmFjzVFyZgJ6UaNq4JdXyTmwcEQAhQRFFQnA4kstfM-0E-m3iU8LTPctWsTsYCniaCq8BHZmmpP8mRIRq7bpsIURMDg6F3Sok9qbl2VI6IeKskg6l1HkBKnZYRxQXQ4Klo3Ypt0Nrd0ZyFzApOimiy8hqsqUU7z7OtgqTgliKOuVBnZFOk-t76FNyglB2VsUcRSMk3yJJroOYVv6W7eRZlg7JgkthAWihx2bqIeQyA-DID2iZltGyJCFGmhfYoYvTc2EukEWXNlhnOQwNMU0mQPiqYQU2y5vfzmZ6e2KjAJv1wuw00g9U0RnEwpyZy5Dj80JWALv3ty-MNvfSY6pSVFtiaxrqv76iGQ0pGNUmcTKL2rLsslmD-5v3-u_XBsq_mzu0Pk4bP7i0Dn02GNy7Cg5Kbinkq8pB37oRyOZpF7_jY4EynHw9FtgBiQyzDt07ouTKy9KciDPMO2QUGquq6rTq17GytZBls0MFl-_ofeeXi9FCVw2LAkC9rMWu8Mvru7Xc_rkyc3U58e7-9b02fvPE_Ccrkc5qk3vDxfIh1EhHZze5iaynSwMSZmyaTLw4-99wE566w3h4NTjssWmo-LDY_7zz4zyy--_fTmdPzOZ6---f1PUoWJnp5uPn58TQkBfePFy4fXj-fL0g99RLbWWmvLebt_dQ_Fw-tXDLFkv6yUOU_9_HCZp2bDb-5uLpfxxS-_J7BvfOuT-di5iSrfv7zEJce6WnoETXeHy_39uqwyN9LaUm698Y3O_np7yGW5rA1gZ_Pos_RNBOyUJEjny7o-bTc-bGx2ezhoV2w-H3Vs1ud-ub-oyOV-6Qc1F1pBhHXbTsd-uVw8ggRjWSNCehdtw0NUt8363JfLI4vsCLWIYHIznadd-OK-MVR1Wy4sIpBxuVRDKYsI7iECD2cogd0tnCONGT62jAwObhpeJAkOcNgGRQkCkziBpAA4gkdYnzQkz5-8jnXjsMyIYenmywVM22WV07xcHgiiqpxplyEU22UhIRt5eXxcLpdgp3qWTq0S_RmBMKu1LO0s2mQQhMmcq4nJBJFyFkXsI899JBLGLCk7JEBFKQIghZKnEFS14qc19dxbn-kF45OmnChWjEydhKQhbbSpe2wA3DcQi4cKIYJzE44YsZl5kbeqJ9DFfewEjEKpi4yRCU6QZVUYMxmRXJqo8BEeSSCuAx-IOIZVMMLNhq1j2zKT3Ckiw0QlBnlEEjzYd9YekUoIBVNQVn2VktJGjMEe5ekEhDhsOFJam5vsq2ZQdhUh4uTGwskRGUzoLRFBtK6-nLdwp8x5nolZVHubKOE2INDeKb1N81gXNLE0Joqw4uAIwB5UIyizV69fbWNzd6ZGYG0KhZtnxnE6gHOaGjKIqB06PA-qd8f56WF669lty5yUDpOebqZnbz0FtDDPRWlUKakAqaCriDBF7BdG2QVuABRQAVMKkwrmJl21K1QESSIMQVf0JtqlqRaXs-5iKlDRaapQKAnRPGFuOE56bHI7y6nj5tiPh2nqs6Gv7gS5OR5JO2WSUQaFUToi9mtIJA9z94zgTK4Ie8E0fUf2Z0RkmecqPnKduyujuB-VadF9r4VSX_je96yUMWfWbB91dKudUyTFzpjfQZ91yq4uAZjf0AFot3jJFdBJe_OhQsrVVS7HEpFnGKV5UenI_Sqqoiruh5eXLTzBUcLkZPcg4uJ7elhUQ4OwozyJd2Qms2dVjKqlsvf699I52GuWXrMDlNAhORIslMKQTAxLIeW9SrNTEApWlEHu5VS2TogMSRREgYhFeKctEZMnBzI4KbTtGNQ9i89BzMJoQIk7meHJlKlQG8FEStSvcz5JYSCZQiiKYUVJdSehrGBAye1BLZNU2rDaZBKYmjAomWkztwivlghnF1CmEAk3hCKJQfM8V60_yAXqSU2QyDfR8y6tS69A9l66KNRu9WIBlWpxp2UGuXThJp6h2pbt3FWUuc9CYAGHpyQmkUooBdXsusoVeZgbEF96dnz13e_f3bRuObWYuyroeJrnWU-qT0RvGh8l75oeW2cjMmbPRtHBynkUdM4vPLu763o76YuXry1xv17IjJLmm4MlHY6HLQGkgloTZvKM4VZEAB9VUK7QHydFKZ9bUxCwF2egEDD3Jk0hzMgAUVcJykj63_2f_g_Ly1f2-KARt9qe3PSpKZgDtGlyU4iSSCSJNGYRIDkpc9KmiiYAWFvFYFwEImjUwil2L4xSwEcouFU8yb2LdHBjkqhoazTBYWrV8-QgSoYxs3JQk14IazQFZxNK4gjxnZunO2WLSLUdBLO2o8wsWdqKZIgos4QlmKUzJhnhs07n5aUoBCycHawsCG6EBlKwKt5oRQAMs9aEmBLByskpkHBjqAq6aoMwB0jghCQRSuSkKpQZKdDWurLWwlH3pTqLaIaJ6jDzIKOgJC3yVBATQZWEbFhd8zJYiCn1h37qrb_8tS-EpROPzZjINrPhblZfNGCnHDbGdrHYHMxu8fT2lGGapA3psVletpWr5phJlL1JPZODIjL7NH35C3fHPr0-X5hyUuVI22Lu89jipk-nw9xaA3RSacLcMEYkQGDPUBViSiNhjs0l-dClqTrHFhYZIjzNExSttUgmVklmJlUmsAiEIK1VVGLqbXlYn7_91vls6EjKdVt00nXdzIaoMOQ431Li5nhqwFguUlhVxu3NjQiU5OWnrzNcIK21083hdHtabASSp4aetr0-nu6evXN3cX98PJubZhKLRZLyp5-8_PDjz959ero5Tq8fHj_-6EUknY4zgCqczqeeQet5iy1uTqepz_M0HQ4H2_zFZ688fVmWsZj2eTp27TzGti4LM02t_dRP_tiP_Mg780EfX77--MP7080hWWzLy-KiWC_n88OlQVRluT8DsMz_-uufGPmrx8tHLx-GhW3WG98cm2WI5HSQ9XHLEX3C1HQdq3lERodsm7Hg4X4R4hhh23j75hSDPL01iLlIaEiDRgRnpqdbgHRukwj3uSWl1SCMdxqkqPow7FZTl0K6N6XkPvVadNsY2ibtzdYNYKhQrfQjYmxjHcODSNCarYNVWZkiSuRaWZLKyBeCgijDbS9KgHb0C0W4l1d7bDU1iEyjzDY1omgTbAztrc1TFi4v0m1kRlEtmMPdzRZbVoptefVqWx5sbGbm7qJM4aoNZd-peiAExETuorLzA2t1rsoZLBLDWMrWmmiSe_0lmZEelHWxD2F2C1LeOSSCNJc3JUKGbd6bkleVYG-wZQm_RiDBRBYuuo_jw5yGkwSJ5F4IZN-Sy5tZhzuWhEbk2Dadu4eDxa1G7eQRbiGaIqKM6iBsy6oKHw4RSq8OMLgi-FRpqAgnEUbsdMI9GsEEpJQ6FRSUYTIfqgmLTFENc3YHK4O2bYUKiD0MSEpBZm8tM81TtXFGay1gtuY8H8kWMmekNs0gYvailICHjWqXMqom2Ma29Plg68IqHjb1SZq2PttYjqcTRcyn6fG8EPM0qY3NfSNBZoZ7U0kLUmPwaZ5irPNB50lm1tOkXejtt55n-s07t-MyJqaj6JOnT4QZ4PRUrSJ40jXSVa5mCOc1NlYluNwR-ymCBFNyLbpQpffi91xNX-7BYNTRtihSdewWDpcIClA4OWUDK1EknLA62AhNNda7mznQ_vlv__Yv__hXIwkJJ2dCpNMVm-8RLCRQZgjtaG3KuvEaFaypFkfBJFQEzl1TmruwrI74AMwp3IJ3PEw55DJTiAOS-_QgmNiKD5OZxAqQJxO5VxCO_7UadFRIgby6eQZGUTR5N8peeTm1_Ntb2VUKf1Pc5aB8U5_YFcOMCKJM7PIWTpZrOr-au1TF6PKQVdmn1heV206ikrtXty9orzF6XpVhROn132VVlYMyPJhIiME89vK-ho0kshEipJCyjFlmZgNvkSEFI8qsRbZnYW8LSUQKsev3V31hRRCDtxiTdgLBgkGztAyj9ETN8jk8QJiglh57KTorrSUEz6vcIChBwcEgZfKQzCBGF5zHRpwzzQM23FhAERB2z2Rs5E3AieFulMoSZIQEMpET-vDo0jYfEAknQXbWwstSeK1aBCWalaRopJnRIMMjOWrr2Eg9SJqGu05TRjFJWZQ8SRtTUFRcVYRB27olGKoqHBYs_PT5DcwLWK0N4Ji1eQZd9VVJ3nqbWBd32-mvMbZ0SvLsyqB8NpMalHE8TR9-_JDjcnPqvcGZadA0iZu1pttw89id2YXPpxR9s2LKpkqZq5nvJIZa6GpmKbo59oggIEAkSUoSZPp7f-u_MSPkcBpUE5voXY8C45giiWmsRozDNFEmtwTJngxDcMrIZOH0Kq9XDM6B0N6I4bYxdq99IZW0AnsRRR9w99aFCOaRnqWEmEERyTM4ZAxTQWYMQkEdfDNpSpQ0QhUU1KUNyjm5QWJzCFFSjswt534cfkl2IfaESHULUhSWPvenJeoJNw8HhLm-KjUlfDiiqvp7UhLQYcasI4Zo821tUw9yJAMtfQiUI0HiV2AHVchRpJ4-Is09IlIgUq4AJhaO8Exmha0bGjKTVbVmD0wjRpsnSvfh0hsU28Pj3_93_sa6sAYF-eZj2Jh09gzKMCft0hXns1WpGkI95ZP7Swaty7o6EUAMVQWJp29uHCyiMaqElaJ8mg-NvHu6-bqN7718nFXd_fXrx_n2Ztn88XzZtvoWqGaai2A-6BjBAjKuGmSldFqHgGMYcQrEEcwpjCqjuTtrMzdBUf2y6MyqamMUwVsUn__S56Yuac4k27re3Nyu5ws3oY1tjN4mjw3IJnI5r723eZ4u65JJY9uEeRsbM4Lk7tkNM7bzlk4ikj6IVvbxF_7Cn_s7P_3jn71-vY4g43eeHm2zzcOTfAzjiG39wrtvf_27n3z3w082y-k4f_UL7_7Bdz601Z_ynWVe1mWzTSYQ07ZZP8ycua6LDbusi2q7e-upWRAJsUtTKL_91t3n3n___v7-sxf367Im8nJ_Yci4SkLXx7X3rirbGBBcLqN1Jfh3v__66fu3RPRwGQQ5NGXgyc38yWcPTlXCTgUvww-HtrkLsJnfnE7rGE21qSwczJGg40HnSe4Xb5mP60ZgD5tkohNdLuvKvC1rn6aWujxs8_FwySWzWpMRma2rbcO3kFMPdxvm5tIBUYGSk6pUS34bSzD1wwTUM7ik2lTInUiqv_bU1T2o1LkkkdFa32xrvadt0lpBNQChuhh4gJm2DA5qysXTo6SgHCP3HR_cBwsLOMxFxIdpE9sGBbIXuCAogzdW5fPLF0nk68gY8-3TsZxtNUh2FfWykzZmN6JdIgNVN0NVeJiHl_WKw3wv2xGnO9W8pkLfwpShJFRRiFpwMnGBHJkLt0LY_aWgEn8IIysmsgPuVMNcpSqdEZYQMTMwuCPNQWTbQOuREUldmttgplhXA1i7SIOqjyGtRUSbetgWQeEhXdO2Wr9WQ1GbUgYEQREWXZp7evG2d6cP7f4UIm7III_oqkV24y3QhIJYlJWEk1nq2OXrAmm2uM5gKNdoUpEjU5WZbDCRQTWZ62FWkTF0HTYmOY1cmcOGM7N2EHgHz5cXh8jMoBpeVJAswLOq2rDpeDPGoqqqzce6rVtdsi6Xs_aJlEU4hss-k04g59bW8_nuZuZMJM2TzlN7cnt69vS0PK5PjsfD896b3JwO15EtX98wwlzYR79SZq43AWbfGf31C3YkYSW3c6dQV7GEdgweMwVJ0wp9FG5xN37t18Td1lyuAyIOaCQQPM0ckYL87MOHd28OS_C_8cWvPDk-J0cEQ1pmMsmeWc9oQFBn4YLAUDkNkpgCrEWPTeeg2P2ykQSOCIhWG0_2zVLuLPwSE0XhiOqtI1UJop25uU_isevksvyaeNMOTmLmEJLKGkdIjdJjv2vUFXR_TakK6rS3BuKq-iIUCN8zrxH3HZuUdfBFeCaIIjiYubqVYM4EZTAB4u6q6kW8QRmIr8YS2iu_GXVCrAT1fplPusoT9m-B2Ms2RW8gZspy10dQhFUoqKkwU138Crl_plVqCo4Sa5WbqMRmRViqnVvxhCOTBPuCJDI61MPBIIFbCEug4ohEAJXR2B3Xq0vVN0GUO3eUUTMBlGpKohi7YE8SYAlPJg6YpIXxXuuGu4lKYXGDUpKYaWr11tdtODcol_iAmGNq3SktApA0p-QgY-Ua0nvUdyC4GPiZEG4sRrXpIItgZjOf-hSUrJCkYKJgpig9LRHbcAEL0S4DyQwKVfns_PpwnG40ZwFrbIXKJ2dL0UzhzNjMFbL4oKSpnndnsBALyBMc58fNHvgwCXseAA4XHwfxW9b7zENrwoSIJiK7ai8VYhFmodrMDILwoOSizrMwosJBXJLH5BRmNHhkKoc7g6P-oZmMeP7eF3N9nN962ldxhJCFGZhnpoQE0TR1o-QrQ0qRATarzF_sHYAav7WqDWjsWC1vorGDrREWUUBqCucMdwVkaiNTmVUlBTvlXYWiitreu3CND8C77kVZuXva3NIzHSys4TZp33y0uZnFGPec86QtYgMjS30HagwLgyoTO3l4pqinBZN2KchVHcVrwS3CShykkZSW7qMpthHK6sOYJXMfWLhvDGzbAAlxaJNILzN9JAEAEqRWMwAmEVrNhDUyD3lc80KZwsxdMyMjLYd2ZQttzcM8vE0tbGNmDh_b9hPvf1Gdt7Et68IRysJMAtRC8OYwTa2t3Ru5KFYnWk2JZcKzJ6fX520EJcPT1hG9AZiHDxujS-ckCFPmXUcnaU6LGTpeP25-5Kk15xYeYxsQJA-AzXy5bMfjPMwnae7le-Zh3rQpsD5eTs_uuuq6ugrMjTyknBsC9twot3Vh4qbNu5obCwWjd2znaE2Od6fY4tnTp76tfBAPchN3d-IxPJK09zG2jJbgdbs0UQ-bderRIunxfI6kdVuD4und3XlZIBRukczuktJX-1__-_8A2V4_Pj5eNgN30cfzhYgH4fXj_fJwuT0cvvblD4bHN775_Uv4PB-Oh6khb-bp2y8-teRhsVyGSBseYBQb5f7yODzI5eZ0iICP8HUjURtG6WHysz_5k7_7B__KE-Ybmtw_nOe5h2ea3d49ffHJR8M3VN4WvCxLk8YU22oXyuHZhJ8-u_n9f_mtL3_pHRWNzHef3754PG-bQ1iZwzyIJ4W59y7uxunMIsrPn9_6yAg7XwiKaWqvzxeApWkpsHnJsLHYMkmzMaYmY2phzkk2TJjR21iHojkPmRSNzUZsA5SiEu6QtG3zSBVG0rYN6c19cBcAEUZMrU_mK5jcjJpwEFrPsQoTdx3rsm8VRCo7BwFnhA0KSorW5ggr3VY672dtSoZSc84UQRHtiYiGU-ulhhUR2zaGMDiGAUIRxBIjiLN0FdrFzS_nh364jbQMWhZTAF4cxir7VnY3s84KtSdtzJQOUuOkDPLMupERZVF3Yi8IkjID5k4MomCqSG6xn1uGEyiDWPV6nKD9LLnrFFJAWvgXShVxH1XljPDCcicFkBQjPaH1uNWCSIKSwghIZ20tI81M1DmziPMZgyKTjNvkw0SQ6RRROh_p6mnMqnvsO6U18N4zRGu2We-TB6c5mlI9sEo0yj-QvEaNBwgerr0RBGgQJjdVDggBRKltb1x6hiBUpHBZzMLCm10YRJ4iEhx79Roo5Qxn-rA2NS-tkZPMzczTU-Ym4tv6MB1uMqtG2ZiRfkGDaA8qPnEepkONTbE7RwOg0zRFjNM83d4e7uZpFplF3_383TT3rgqmOnxTUFIClXStA_rVPwq4Ze58GBZmIX3jkK4-NMr1W1Tp5AJbiu5-kKhMe3KdkLm8tvv_sScD6UHEQSFnZ0429xjn-zF-9qs_huT3bt6iDPV48kGzS4hxsmdWiRJMXiT7SB8e82mS5AyigrfWasUsClZz7Z8L7cLj8sCl7TLi3Eu6EEkP5wLzl9Mj61TOHo6r5reux0LseRVyRXitTMpHlZSZxllxNvOqumUB0n-A5qRUwOuoUeQjQmSGe0nBytFR7zFOpsJ07Mdu3nkm6SCJTOIANycvHZ6bVf9nH4hmRtGcijaae8u76OD1V2KnIPJIUTgnJwmxRw6rIV39brLZABU6PYXZc6-LUezrnkKHiNeyAhGpzDaCAIqEwClQEhne4ffpyQyWZKYsaABlJilg-zAiwz2JPKJByWmke0ZXuFsEMWVkNukjLNNDmIjMozHqUBoV-U_YZoU8czASLLAYkza33NyTvLWW6aUgSPemGGM0FotkZm0MIqlr5L4YIWYceotKFRIVKY9ixx8wai25r1coiYUlCy1HJEIZqlNGNG3DNp1024JBAgVFvdULAlpAXWlqY6Sndpya3p5uPT2dTrOIo97xjTSRngmgSqggXld7XJd5btOhIcXdPQdHvHUzzQ3m27alEn_26lPx8fDy9WIrqDcWEB0OE5c7O7K2UqpStfhahu0Yr4yxh-R5RDRIgyRi3WxSDU8WNjckKKLIxwDceJ4P__l_8V_89f_O33IPEM3JG5rnyKy6WjbtkWnsGWGZV-U2EZGzAJFMaQGGiJgbc0qrD0mBmMp6IixJRmMbyRmeaHBiELrCNwtmEDWIE0P4aievY3cwV1GWNxsH7e6eZMrIiKT0cCFQuKqOcEeIngS8rVs2FiCMOMnICwm1b13NW2-UKYyu3c2SODhVOTNW864dyUyWnpHRVNwL7okdOWT1UDQW7jyNsbapIbCNQAfKmr1TzxipxMh0DgZkmPU-xXDKvPhrBlik7vkAN2Cku2XXRukNsnoBKiQjQ8Qjtfd82GJ3SbqK1jeOCItqV8kIz-gHHWcbm88N28M2Nn727DCGxzJGpgq707p50aW7oCEzchZZwp7fdAp-3LaXrx5DYCM_vTy2uYfEmpZEFjHW2uDlYdbgoIwY0aBElByiQpRgPHv7ybE3Imb0y7LFsKZgq1w2Z5JCUwpq5k0lxuCUeW59anl3evXysfWWZJfH-ydP7u4f7wk4HCcw2xZjMekyNvNInW8ktowgpTFGuPcm9w-XjGhNX3z2eDr0IOYQbni8rKfbA1Gjcf4H_4O_fejt5YuH8-X86vzw_O6OLB8uqzTNcDi9_7l3lJghv_U7f3ReL1vmPLXj1O_P9ni_bhZvvf38G9_-sGwbsRkxkvjx8jAshxuqCekxLNxdhfrUueOv_aVf_NVf_a1MXn1dh41tPd7c2hibDYAfHl6cz8vUu7apUqGKVo-YZTUbK_D0k89eKejZO3f3y_bsdqJhyDjNzUZ4Opi3tIdlPXBb1vQI29YxzC5-avLw6eu7J6fTYXpcbXlcVKGTTHIIMwrKztNRz2t7dge3qAdlSeJVeTubNB0RYxu2jWSaD9M4r27OXJyMOjZwpLs5C1eeBZQJHmOrmWBmmju0ha2qShEk8gYWK5hE6knjiJSuJUXaiTRCWZI9IJYtweWNRWOW5psRpZsLGlFCkNxKfuTmrHXcZ7fRpzk4CZnuLBONAdC6XNp8JJa0i_kY6wIVbRph0p68V9xB2iW4DOEcto_x0zO8wgT7DJFJcaV_lCigmKWczBx2dSQxg9mdkgMV4wQl7-6ezCwhXI1wGBpue75ZQBEZBFHfRvmiMnzvASa5JYNpeBFSqOgMUQIvTvf9kKdaDDa2jSKqO1kOtqpiVNKLQKwSFkANhovsXssLAUPQKJMKNbHX-uPYjk45zKEa4QQFFOAwZ2nBqU3r65IF0qXAC0XxaFPPTBFlhvSWHNBWnohaI7FwhjFzRqQHK_femDC1qTiONYVSETfzkahgPSdnqmpk7MqVJOKY5jkjEju_pk6QU5_Gstycbua5-7YBfHtzcB-nwwwkOd2cprffeXIzybvP757cHk_HuamKqkIysUOffnCoJ77WTq9Q-31ZvleBKaVy1eVZK7VbJDExJPdW-T7nv5IuOSl3oVRyEsc1I7dD6jmTZbCObC-X1SQC08_-8I_AhJIpmGLnXrKDMlKJR5oFGoNrIjkCNMZoOiFLHFEurbwu_QvrXq01ak3BUFEUxYzKJ5tELEASuTkl_6CAuyscCG8YOlePbO1H9kN08fIr01N3oXzz2u425R27X9uJ5CtqqTgTu2iNd0ooEyF3SxjvtNB9Jk87rBNXCGdR-Zl2MnAZd9_sEAq2cyULMbGyeKZTSRgIRFEXpCtWqBY1mTV45lpEAhwE24VZPxCNEXNRQiJ3p1kGRSF99zdCDvYmwtW4qJeHiMBClBEAaIcVI6KSQqVB8Lo2c9Skn5KQlEHZoAzKmo5mpSJqYJrOqcwt1anc1pVm5J1iHsksxRFiYsvSLNSpIPdXkXe3Gjvt8sS6qmH_e1Ps0ZHMq0GvCkiZXD8V1BTWveb6XixYuX6ymCpvGhmZMVyhkSHaWJggEaGqFbIp2IDIbhMhEAi1U9s7OUIqeWr8Uz_0-f_4H_6nv_hLv_jWk92BWtRzqTKssEBUtFJm6zbCQyDT3EDJGQK6vWnCJMJQXbb43__D_8_jNz-8v3_8zd__w1_-i79cs67Lurz17JlHQBgC8gLoFs8HVWIGeHOXvZJfShxUTQZlmQYHOdBQtXkmFYVKOM0qv_dbv_WVH_1Rz6DMrnIztcgg0PAhAIEkyWM3sik0MwEC1C0EDKIuNdaqxwFNrWWQMIWniiRzBkbQa_M__Oa3v_PRJ7_zR9_9_kdnRn62uDaWBm06RkDr7kol0czdgJcMCUpijQimKM96WSGkwm9JqrKOrU0tq0IUgaa1eQMhMy0jkYCUGo-Tm-juwWAUexSCCihWbNXDq8NUS-0y7ZCHcyqUKJh5DFOA3FSbJ4VbUxll6qjVZO4EoeEmIvWtoVN3G6pt952w7Ji96ieJbmG9N-ZUliyaq6fOSkmixGS__LNfe2uaMyzJFxs-vJ5n5g6h09RnaT7Gi1f3UN2WMU_KjNcPiw9OSovczLhewIxSzwN5PM2T4oPnt3fT1BVn88fVz8t6Oh1E5X69nM_jfrXNcjXfhuEq57LI9ACLuRU4b390R6jK8TDNqkjaNrMKQQkyyd21t-GmUnmGAFPvjZhvb0_T3B7vH46Hqc1atvPDPDMnVM6PZ5W2b7qCIoKu-tTj4eAxtPfWNC0P85GQ5_uLNLUch8PRk1rLYa4zUZBqPH9--z_6K7_8-HChtK9_7_sCeXp3M_VpXbf7y-P94wOSlHF3c_jmx59-78NPWdUSP_L5949zI-LXj-fLsGWzYX4ZGwUn8bYNZh1mtnmbpUOWYR5-WVf3NYO3zf7an__5jz76-MOPXkljPejl4grexiCPaW4e9urlY-u9Hw-P9_ecsa4bUd4cbz2DPP_Wf-svHZy__f2PXPJi-Xr1cHt6d8sM25xBm_u6Dvf0CNk7FUyUrWPq6LMcID_8wx-cH9bWp8fHCzMF6xhjrAZtY8TYjJFIBKW04m1iHWNbrDUZ2yDoelmmqdu6zYejm41tUAYURNwPh8iMsFpium0QySSPKstlWcmJKMYQ0YiU-ZAcy2WTK0C7HsFmVqmYKpG5m4rs7VN3SmJBRDKEBBGM3kq1LYL0ZCWmNDdpPUGJSo1yuhVVnwXFqkkKYSYLaHuzpbd14fQ9zpOp0rSQwcnCzBmWGSQV8HYW3Z_vzE6hKjGM6i28_4OyeH4pnMRFzNyf57S_dhEGcIRn7KFjSCuRJ5hSEOGkwkEAx3BSEPHwjSpat0feg6JwjVnnoOKTupN7aJ_JrSzNzJxji8yI5OL9VRzIHSpBQRFt6hnWJ6nRTjJl1UDLbkZZnL7ijQakPpkQVW3DNidnpt4mEudUYmHhTNb5hjhEelaCnCW9sIPs5pA2PAguKpkJAmWKKiW5sygA-GZmpXeZlnVxN4CDfHcEMQ5d12WNbUWfhJv0IM7YPIVZ0Ka-bZaioiDKJp08Isi2rU992zYwWmvkNh9m85HDpTcVJuLbm1PvCsbcMDWhbdXTcZ7bYZ7LylykGWbOQv7Xo6tCJjsslTioOi5VVKznTFJ6BHFtfwrdRzuuvlL0RJW-pUy_Qi3ryFQxgB3CQxQRZpZE2sSDt9VVfIrlC2994el8wqilEurPsUxJ_ezVx-14PE3H4SsliSoFZ4b2iXwcb2bNrMIuUwA19Ddt6uHC6jFAmI4TRYqwmUM4q9eWb4R2lP6GsSdhlfnf_VpF4MGORaI3Z3pJSqYIkrJwEAeRsND1QFxNX68ifr0YFHUIrq8UjwqyEFEgOesitgdwuMQ9w73OxztAFMhwFUQQuD5SlXhmEo7YNWrptN-9d_IoJ6VllJ7Ea3mwuwPYaP9HlZeh9gAsdVHZEf5CYKYRVQGkooWuYXVAEUimG9Uqco94EfNE3JksK_mtFfInD88gZndXqYRVCjN5VKOaRSycSeqYXUbeENbgiGiQR_OWxISiYXJkFLExgiUbibs3sHsymBjBrgX-5ay2CFESSBQxAiXEodjBf8TcqNri9UwXwCNAIJRNkzxSRZ3rL8mR2RgGyeQttt6aRtoYDERmU5QU2SK0KTOnsQLonERz6ypq4SI6tq0JW7Ctox977Y5KmkHgGC6K1kCRbtFI0PjzT5-y0Xwzf-Pb3_nxH3pnXS_BoarKsvNVKNCVPMbFSbhP_ZOH5XTksa4RyWak9M6xP1x897SAf_vX_uhLufp5-eiPvqEdx-mOlu3ZfFPdMEjPdG7VtuEYu3iusSRFE-iu8shWPkHhSCJPUkZS02nbTJQzm1KMcKQQSIkel9EOxz_-8KMnT-5er-NdJCDHjgUIH-syWusNwkgtLyMjM81jVmZiI5qU11Go4iRhdteyqoA9iSlf4fyf_c637l_mF-_aX_rZH5uAWdWSty1OE__m7338_K63G20MAMRRKo00R0pGOlV3PKpvQKV9iBBGApKkjcJp6gcfQ1lGurRm2xACwGbWumjqZo7Wx1ibQnnf7LEgM5BC6U0lkOF7XLA3HZTbZlNrYywQ9oRLIBKgcNp8awKOZPDiG1QZAopMjWQhpsgamdUnrr5OiCh9TId52wyqM0-braqtUqkKdvJGYAsCX3ibZHYfrbe0uvVz79M__c3f-9pf-_llKQu5uBIJe1UttySSTD7dzB-9fGQwR26b5_Cnt8eH8yaih4k2N4shrMdJiSjdIvKI-ODz7_iyPYyxbMbBbZL50B8vy-Hm4I7L-WLE1lx6i-QxXCe1CDZSwTDvvRUCIpIv98t8ase5kUc2SuZtW0SaE0ukCFpoepymvqyjNAhMrIKndzfQtq5ba1OXXs1wkyGiNdhpqknuXhsPkJH2TktQBrRNyIxworvT7ePDWY7S5gYlhRLltl1GjOn2BkT-ONjlL__Sz-YYPIYgT6fjzdzX4bYNQ75-9fj6_vWf_6U_G8vqjj_6o--64nCaf_KD95qFJF3CXt2ftbfzZUui43zchrFFeeFtuMW4m5---PiFEJsnZbTWMvzf-JmfeHn_-nsffZq1o7okKMysybRsl8PUL54yNyI4bzrJNiwZxHEZa3KI6Jb50Wf3Mt38zte_3VUp8n6a3n16F0EiomzP747feDiLkLCEJywEIn1qBz2cFEwq-N63PgqZnp_o_XeefeeTF25LlbggTCPCnTmTc1iocIMwGUS0a2fKpNW8Tw2ZbZoiQ6Yu20osheyzMbQ1WxeBhg-UtxHZ0bbLOcIImhFJJNMhfOvH2cPNvKlCkgjEzio5Qli5omlRhJpO5EQJUXPXJsKNsEQER6qCvNZvIGK0KgpzPxwojIjWxbWDMqoRyqXfrctF-URroBokvfnjoqpMFG7EbJuJ3r1LmZDOVNHEmtEWmhA15K5jaFUcSJBVKKIKgCaDouqExESsKvsQuGDHNQJTKTXsblZKgmhWmyyuC9agnRavYKHw4KR0L1sOqyQlRDw8bR94MklkAvUFtZP4ay-QGao93SkTolySjOu-JTYTqVFxAVRAnGhKoMwMTxHlGsLFFVailblG9Z85QwRMrGUWckeTICdGGYhEkFGlaqEUKEuN6oXCfDpMO6MsqNKl7hRjtKknRQU60qNPcyonc2vN3UU0PGxbu4rZME4zF1FRYaFac0yHGQIm9NanaYJibIP2WZewKrmDYebz4dB62YdpmrpCTjfHphDh29vj1OT2MD9_-8ncJ4gw7VZi3mnXXG3FHUW5T3wLSwm6_o8yVV2TLckkVE6k_ZhaR6ki9teUtN586eblo9zbiUzuEUkeZJGRuQVtgxn8zZef_qkf_-qNdjZkMKJOZ3vS14z00KfTgR3EzI1BoAwwQMJCUFBwUq34UfNa4kDJp3bvGxQAqRvVqDKvxoEajYuW3GM3LRCoEkBezZZ9UL8nchjs-2R-v3bH3nPGtdRQ4jPsMR3exVlJpaqonjDtdQt-szahElfHdRdTs_z6dBSLsyQmFRqqgFCVkoMp9-3H3sHYJ9jMHlaE-9o5ZGW3KJ2ohvpE8Ks1YIeRUt2wkogi6hNEFb-pBWDtQ4JCrkzb_SaYQLUsd_YaC-0JO6_qM78pHe3bOFzd5bz7p0nqdUMpsTTTVWHkIlKx-y1C6puJ2Siq3sBMILGKO-9N8B21VH95FeGkGkzmG_ezRw1NqsNgZq0hIltrGVEYuaIplC6weFlBMTXlQqXuVzlk3dg4pRIaEE4O4pFeN4smUtNo8ugqOyQHODTNyCYioHmaiNI9inJLRMOGQChDRESgO-S13mUBiZ_50uea9H_8T3-tnW5-4ee_Zg-LIRoJJymTMEPgqy_DhAFlizxMaCIQRPgIm1sqVCLRRJP_j__B__382Ut6_WjrpQl_6Zf-zBfffe_Jk9vf--Ovf-GDt4d5US6ZaXgwk6iASEQI2bXn_ukhLpkUpVuKoC7JXlqTygwiPaL13lSYMQG_9hu_8Uu__Aun-Wae5AgR0GZB4Ju5g1ube3AeeispH_ZHZH1ZgiQdFM6q4KS-ewbpOvjA64hf_8OPv_2Ny-dOT_6dX_rC554_7SpJYpbnyxCVddjzZ8cnTw6_960Pc8iT2xlXuFV5HRnMLIx67tZ6WQLEIBEJD23YFdjuO5Abe6-0NYnYkQBBJMru1lsDc5gppOYwbVJiRsl23lSnWCjTwpnY3ZlgkU7ZVRlqlsTUVJOoaQsmqwuQB1AHCU5PkEQ4mlDh2sAQxbWTtm8bS33lVg7sri2F3UMnTWGvZwEQg_bfOdHm9uv_8g__7b_5y7Su5oGyxMoOJGiKQ5MuLSLPYzOiJnyaj-tl1YZhsWzb5vHeu0-qvC1MyGhNvvjeW7NqF1bg1eVx3fyyeXiOEdsw2-IyPBKpfFksg0nY05k4g92MCYQAQ7pu69q0z3NT8DRNEdEazK14lJzk9e5lLth1Ndyhcns6dFVKUm2ZziigAoYNCGv1O1XM3NzDI3YENbZtq6spg9o0gUiY26SUsa3DM6bDBLRI37aNMzeP49N3tsf7qcm2Xv7UD38-maZjr9x_mDfBsvgnr18cb-b333rWZPr9b3_nMiy1_5mf-bH11cPpML94_frhsj6cl2fPn7Pi4XKpNbuIDE-Al-Hbso1lI8ngsPAYJk1effTiT__sT37rOx-9un9Ax8P9tq3bui61AbY1GGzDwZLhwzMIZvGwnbtOSHazsdiPf-3Hx8OZOYn94eH82euzStsy37s9LOaXy7qZJ2hZx2Vbm2AMPx3bfNRTn-nstsRbbz9dYn18fVaW1gDGi8slI_Qwr5d1xNg8VislSyPCzUEj8rIuDAkPd5pup7FZ3didPEYgiGJfIkPUbRMRCo9IN8uI9IR2TvPhUmOa3Sifqtq1ZVhS-jAij4R7TIdj7fKYkpJk6slB4IrvQxUqMQYKOscQRnpkcFnjeC-CtjTvTZkYqtjTc8kCrmdZpginW3ow1WewxWZJGebM7GbamoDk-PyDsi1mJrsniKo7KJK84420tb0hxeBMVPvLfWeVF4iQkZ4QrXrW1QkbBVHJDKjugel6yJfcNfeygKrWSeuK44iwrG_mOjomo4LgdUXZxVGgivSUXN7ckcXtGfvKg8kjRVpZDgHNYEoWkar3MRNnotD14dVtTECbNhEikqasWsvT1rtTulvdojKuZlhiUaVMbiieHWVKE2awICh6a02vWpRKu-_rdXH3Ya5aPiz2Ycwk3IabaB2891hTU0hDIIkYwh6UxK23ZJqnm0l7nTMq0DAf5taUM0XUzKVxySbqHNBUj8dDUmhrUAhwOhyasgKHw9xAXfHWs9vTYbo5HhTXLE_uSrcs03Xu5dJM8ohKSkTuxtO6CDAjKSL27ZC7X5usvO9eMr10scSZ9EaunoG61O23u2CPdI_KaxJ422Ji-uyTD3_5Z77WaYKDgojJ3kiwCrPP0NYQxSuFahGIkAw3I0lOTk-SiqIX0crrKF8MOYg0EaRUDB-clG7XDFzpP6vSWUerKAwNcZTNbcf2X4n_e104-PqH7SawOtTmDt2pBsX1NhXEO2CJ6sa8G7hKvsN5fSsyCxFXqjzDiaTuCdUWLedevQFz39KVkbbGBLzHUmr5ULscKilm1kgAkBEevCuoKqEUnGX2uX7qqU4M-xLiSgGiSL_eCevXl_P86kpj4lQIJXvsyFUiasWSKu0ShbISkafJ9WNv5ns0hoi4GrHY9cvETtGgIyKIIlII-worqaOP9Lo8JWWDehZ7gEGUQZYhOxzgTTOYS5hcnQs3z3JXXfegAJubNuWMpnX2S4AVKHYykjNzVGCR9q_9CotFpkd2nc2MmT1cZHc1N5FK8IHAmb1rFwlKEmqKgiy33ql8xsJBoU1A4A4QhLk1reoNQK23NC-n4bZtP_bB23D9lf_yV--X7W_8xV98fP3oRErYJ-V795jmrpEhkPOaKphEmDE8g8fdzakzQ7hP84eb_y__L__43_t3_873vvfi9Yffn4_t619f3v3C55bl8Q_-f3_YhA_zEVTKDWGwCoSSmdMpkQAhGbF7SKqeVM8YBoHRIJXkYaD4wmWYSUdn_PNf-7U__8u_sAaDpbI0ICKWxSwpW5eIfLi_QFkhu7crKZgQxKoxsv7JTLxfD5DqsSV99OLVb3z_oVH7Cz_37hfePq4uReKhIKJsTWrWUafAH_3g-YfffXhyc-AIAYYFtOwdgMA2K55vJZyCnInTA8KFmxBRM5tVrp9WtCbrcpkOUy3ZMoODkATiLs08WwMz9fpcRXZViphULENZKTw8RIVqSYs3COEkygBJDaJqDnlFFChKuyGFXlDZ7ewpaIIOTWISDg8ItMB5qAqOFreKFcyawpzEyZ6RTk2ZQFBQCYIEnJi6fPW99-4fHlRQtxGnpMhpamFxmNUzPDwizfP2dGCibThzJoSSz8PvThN8F4u8c3czlw3TfN22l4_nYRSZnpkjg3LZIoMs0yP3c2q1FoHIrHhnJh9v5tPUiUBh87E15gYZ2xYeKprMUqtpMIOQpE17VzB5EiXPN3N5JJmTmJZ1094yc13W8ihnZmvTcFOV-TBR8vBBkDZPNqwie_N89LHeHk8RoSIQ3N-f-9R10jDP1SJjnufYVlVuoj_7U1_5ytvPzWLZ1mRR7duyJsuyXl7dP3z5Cx_czofP7s9_8t0Pt6Tj6XBoc2xr7z0hn3x2L13PyzIdD5fLePvZ01cPZ_IcEduwx_NFklR40sZKti20rYdp-tmf-ylze71cPrt_iOHDnDKGRQazcpcugmHZe1vXgdaXy-rbRdFBPGxrKoz4yo9-SSLOPnSezstYLbZh3_ruJ6_X7Z0ntyNyM1-3jZndqDVAKEWY6XSagbw9TOn-ve_fr8v2_e-_ON4e0OTQ-6ev7pXgHm4xzAnRoeYB5VZwRRGzPEyyRlTiH8RjGaLNNsux1YOPBdBOkmkOwN2KdsGVF3Sr7yjRPtyVYzqewDzGyiT1SC0MOiWJViSARKDTzIAwqvpJdYrdRZacGa0ag0zEqVMvNWHpf0RbzaCI0t0AyczWe01Y66hcQywUsjhSeyuJQQUFOJkB6U8_t6cNKFhYhGvNnR4iLc0Eku77gJ05KRkyKsYUsQ8sZVeoVrZp30jWHC581wVmlrmz5nDlqN0_P9V-i7B6KVvLDBFQOJhEQIlkBpMCnERGrAgqoadyBLQXQLdQd4VGkkouxhtoutR3cEQQh6CiPqVwZyZiZcJOKUp32akeyCIZJTHDhvPOpAzpncrNCmlNfXibZorofa7gikytaJvTNLnH1JtHFGFaUCtCdTNRZGRappOquHnvbQcfmUNYmzAgLE21FAgVJUcvF28wuyD7NFUkd56mdG-tF4txOs5M6L0TmNy1GP6teXpEzIe5MSv4eDw8eXJDNp7c3Nwcp-dPT7enuSnMBop1VyVaoiQOd7rS5TMzCGUw8_rhZnqMIsoUeM4rZSJwivD0zPAcHjtusuCNtYSKndpfb5KgNM9hbpHmOdyDcvgu1_rqD33pqLN76VmoYhpRmKpr0B77gJn2MH9ypVoEBEoLH9smBUmssSgXwSaYaf9MhtS9NevAvMus6n1NTPDMKtLXtjQjuQS9vJ_O68Upukn9rxq919SX96r0G-h_ZfE5fiDl_UGNoPruvHuPC5tatRXUKYOJIoNZfM8a7Umr-gzy_ndmIrb9MA8u-dk-fAzaw-4gZt_5NsxFC2BWZqtb3b47SfdgYvPIAhsHlad5__YkYmbPYCoUVGZmhfoU8GJCMbYYe8ydSusGipSiEjNlJBOZD2FRkppqiEAFlNREgsncgRIwV6iHnR5BnYCs-khQUkYmAMsxafPIJrXmIQj2VhH2M74IiGA-SkfhpXDagcxeJ8XIYGaIluqkKXqtXOpHW5cGro1lCgMUqsLEYPEIYslKYmSIInx0bUXTiggIt94yyT1quHM4THUfBrg3oeAubeoaniKgsPpBK6N3XVZrAlXpXYgoLKkC_aq-B_jGT3_5AyT_k__yt773yaf__f_uX7eHc5-mLpocYHLypBQW7WgsDJ4aRIkAURjnUfXu0Eh57n2a5v_z__Uf_d2f_4n3Pn_69HH-w1__Dc7tr_7b_-3Tsv3m7_7X_97_-O_-R__Pf_xTP_cTeSV-FgLALBhVBZLMEOIGDI_EnmMXMABRSWaUYSMoQQIhcP24RvCp9X_-L371F3_h5-u_RCYo6qu2qQ7Psu5MXS-2vdyWuU9NG7f9lkDgWZX2z0fN2Wlx-sTGb3_88MlZ_-qPvfPDn2stK2rKV_JflXM43D1CKDLjvNrts1m1wmUpymbBjAhPyq66CwKZIlMY4VEfsAnwyCAXlaroWH3PZ7Z5GqsJJMhFRLUuniyttAlSj2CITooS3mSG9L6ZQUgqhpreeJ9Va21CI7ME8-FCFUxgcMruuCGIANlFOKwmYpSsImGVj8-p9xLaiwgLvHrCSbIbUiHMxUPkoD37gJZOTMyACNrU_8V_9bt_-s_-8Pt3b53H0oSJSAgAMs03T6EJQlBLWpdx--QokdpxOkxJGsHL5ZJmx0m6ti---_bx0G1svWsyrcPOq7sHiQ53zpBJHh7XoEyS4U5MrLARTZSonKjctCEzI4XpMGkXMffD6bBsluSsmE_d1kGRUSzCoN5kan0bgxlm1qc2HSdbV1wFmDYMLGOsIkJEh8M8hgVlmKlMSizSCbRcLtqmCGdiGz71rkBXAdBbY4EKPAPCw0brqk0zEoKu3Ob2d_7qL90Kc8bwINAwR--vz48WpNpubg5z79_63mfndXNzUTk0PR2my7p9_ZvfPd4dbcRnL14_f_okGQ-vH87LVnyKZJwfHnsXVYyxWDDG9o2vf_x3_62_Obbt5cPjebUY4RTbuto2krl3rMs297Ysi3vcPL3x8G2sAsTmSkgmHyMjmfzh1f2Pf-0rn3zymoiXZVwez9TVJr5_9fB4WZ_d3dXFdRvj5jBv5hERkVOf3n56DKA1fVzMKObjdLbtw49frSPefef53Xy8f3hMc2ds2wIRi3D3ZGoic29uXlnOdGcPu6xgJuXMiOEQdg9uit4jjJJyxOl4u6xL6bcF1YOLqqcls4eptlodbusq1TdKQnKYaWth5u6ta1hpdaBNW5u2bTucbihcdsIkq0hSuKeoBu1VN9TXhUq1CSPSxoCIjSFtrkJbZVrNR5OukMwso3xGAMqRaSba6jwAAhJE6XX0HZYESWKIpruqIgkitZ0it4qDcVdiktoQJsXIKMCIx542BidnljVh73fyzhoTAZFAwoMB3oUsFOks4h7uI8L30UzyrpatDmswE0E5zOsMHW4MjnXhTN88PMOCCemZuYeoalBptkSyVbWRm0WSNBIE2JlHZCQ8kfviBQxl4TFsjPSIQvu1uavKFS_lFGCBZyZhPsycAZF1bKTlqwegyagy33C7FvkkiaTpNgZHaAHvIsBZlgdwhTAZImnJJALR3j2ztQ4GgUW0roDTce59CuYkbjq1NotoU2UhcJDwtm5okpIq6L2BSIDeW2s6zROIumqfJm2yDtPeodx6C-LH-_NyGefHbblsTrD9krI7oYa5uZu5Z5q5W9hO7KuSrmSER7qlW6aTe6zbGMNHpUQoLWJ4eHoQW4QNHx7DczOP5M3DRtgWFARGE2lNW9c-aVeeZpnBT4836cK1rKuXoyZx-9XkzRWlRnX7_aU2BAxYRCK5SQjvJBzAa1ZETAIVyN6BI69PUqZnelGikjzCwgjE9fwECb9JStF-zd7PFJkeRACkQYSR15BeRHgEgYPSI43IIixrZL6X5ne3MmXl-Pd8UNIbbcA1gcRJoFJ1gJj3risTMrOAYBEZGRmhkD3JW1dlyog9r8VA_WWq-TqiTr_EXMkfImBUZvCq8ACYrr7hkelvAK5JVpkWTqV4k5ZCskful7wSzias-vqe5CagXaoVkbXwYrU9WeRQ9oz6QnF3EAlaEvmVWkgUSqfIiDApihwFRNuVMTzcUU6DrFN9qjAzu0eDgsHEdRDlnWcMBRoERCUBUWIVhYBK5rLXvLJOh2DuqgKepX5jMtoY3FmQHByt9crDZDAxk6WojDIZZTIAgm8GorlpV0yHRhRzl9bReo-I3rsoFDy1Rj4A7E1WECFubvR00083rZoA09Q5dpJYn9o8d47wyM50c3O4v3_Zm06HqQsJcp5EJFQgYMthm1u6gA-9ddbwTPP7VxcOrGcHHS-D_uXvffM039x-4d11mz735a9slsviMi4__ad_4vH7Lz7-8MXf_nt_5Z_9818bbodDV-amENE-ta4KKCgbIA3BOU2iQiBCopwUTKlMKKwqrgl7gJkgUEXtARxqsd_HLZzAThmyh3DMaSRN_fD2k6fJ_Ccff_yN73x0sZBJWbGSk8hGFESbxzbGb33n43_yB69-6Nndn_vKk0nZvQUahIWIMyjSoshtKYqmqGENRIXZI50yOYS5C2QPO9UaQESlt9ZYQSTEIuqZRqGi4UwcKcFCvUkTTO2QHlPBZ5KbKAdzCjFdlqGqmRGRvU9oxOQUCaIgrLY1ESYtmWET7YBQdkhNYbrcYN-9S0nED9qVwR5MpNrCjUkivPcDRFigkyQHGnprk3aABamqKsLKwsycENKG1jRG7F9_TApIgEObNCggJFxjBnry-Xf-Z__b_-B7Pm6mG9scbg107BLGDPr404eX63pex6R692TelvU8xrKNh8c1MlTpOM13Nydp-u7bT5kpxtgX9JkJnie1TPckitfLOBw1GJHp6e45LMZmNXbJsMiw4cu6sWC7rJu5NBxvp7m3UrG9fliQPC4bExfsrqlKk7snt9Lw5PbGw-feOsQfNxEtF3shCsKHebTW-jRv66pNw1NVlstlc79sZzDmefJtEUZkKNPy-jWZ98OU4M3c3Bk09Q5hFd0uFpE389QoyWNZtrdvZuU6MqZHDPNtbBAcTqfT6dTa_PHrh8cxNvf5dLhcluM8rdvy2avXL-4fp9Nxjy0QyPjjT190UW3NM5dlm6Y-9-nm2CH4X_3P_3af5__Fv__3t_VVplsmFNNBYwytqzORM7XjRMrBSUKPjw_T3CLJR3RFZxkP98C-EP7DP_xOijSWr3_7--f7S1KcL5cXny0vXt6_un_8_a9_43xegfZ4touvz54cGZhVLOLFedze3r5-XF--ek2Ul9XDQYKH8_lf_MbvPo7x9PaWmxKTqLa9bO1zk-EmQpPqLDq2lTOnSafDVKxuZtZJ2tT6YYokUWm9qyp3OW8XEYS7U5ZAhpkKmU0gTmbGWLflspZHJWoBQSQqBVG0LWxbmSLdtmUZ29jWM0TWseh0YIL02WKQNJ0O0MaAogFtmo5MLBByYhVAiFmgIGrSyIyqOSZQkRxhtroNBvvYwBy-Z69ZlJlVOkVKe_a-yM5lqaWqUxkJKCNqSFCe9L2VWFkXC2FcU6xgEqgSpYhEOLB_ZRfMiMDkyVp_TJHX_vWqH0F7nT_ql1MkKlBBSUxu1YtPJvIdxpyUNbAUBgu0ogeVkaJ0CKUXiiVjbNmUiVgnANKEOKtzRbUs2VkMRJyc-3y0gB6cBJFr5ppYEB4CVqmzTbTeMhzaiEVVLXMM06lBoNor6N5Y5mkCaFhdGRmiHpFQ20yJidw2J9lNs7s5RPdrgzat1KuKMJOK2DDmCLNk7q1pZdCJVHSaekSySNc21nE4TFPvDO7TxJkUKUTH4wFa7WtM2jj9MPU-aW_SgQmYu54O83GeQHk6zR7Ze9OmvrlIMe-pyr-R-4F7L37nfpzNJM8kojIjk4CJLTyZwva2axJfw8rwsMzrNIXIMyOSpHClqBxwzb8jyZMbwMD7z55rO5Ahcgd4X6FEewlg7xjsI5h_DVlEufdpkZVMA6PgGZHkGUHpnpAqd1eQhmrZXX1USHU-EZQRXv9R3Qki3lw99lpsJKHuwJDr9qAwNlRBz92pQPs1o95_eU3T1LuxclOV1K_tSEYCO3e_MvD15zpFdYt3Ik8tvApDEDuxdFd75b7ucI83DB8wPPxKZsrk6-qiXsviVNYnJorBUxK3HdlZNo9qSUSGYu8f1-idAxQUlACcsiL7weThNQgonM5efyZCKeEomaW8rU00w3dlM0A1gSnh2e5FI0XzKBAHgzipmKFEQCLJo7LYSmq0_1Z7sum627nWAJilgC2oJm24C7OZNUWQl_StsVKGCAuDwQqJa8S83iFZ-7MgYumqdcvySOaU6xwZDO3ikcVRbU1BLE0Q1FSbcDkOWtPWVIpIKlBg1sZMw80jwKQqp2NPymWzp6djY1aWm9MsqkQxzV261EaqI5j8x774OTb_J7_xe7__7a__T__Bf297WIIjLHi30dWPQsHpnhwRnjZChX_r0xff_-ZHUPnRL3_h4cXLP_7uq_ffveNsfGxrttPp-Cv_t_-YTu2rP_0LP_PTXwHTw_397c2Td95_71f_xa-fpsPbb79TTVLee-i5X4mTba-ikQrKzamsRQatyCcR1RYlI1trnOlOQvzbv_3bv_jnfjHCmXkSMJGwRIKSr5m9-j3gBEF7dnu6Od18_OL1b3_8UTpPranwZvSpjd_95qffeUGfe_bsz3z16fuH4EQygaQwX5IF4WVmaiKV73KzPeWeAqLc_XhCkdAdI6Gq9c4somiE8046gKfX01P2ugiTp-5RnNGkOTkxNRFmmtCYcmpd2s7j0qYUedCW5MWgg7CQIHf-Xu7pxZ1IAFUmEDu4-nJtdxSQM2c9KC29tSYNb5hVHrH3A5k1CcK9S72wTeBenzMWSK2me9NMZ0ZE7iX5soDsi2SpGSAz3zx_8h_-R7_yp3_pJ5_Ph3BPswyq36eBg5nMmCXcz5fLk7sje17WbURYODclos409ZouxGePn7nDgwEamefNxxYeuVroJNuIyLR4Q2YgM49MqA733L_SU1XM7eZwIM6p9eF-3rYnp7kJfFhTtbAKMUJk6lJ1kss26rvI3Otr3DzN3CNYuE-90qAAwtzKZt1mqow0kZkv60bh4X64ORHHPB-T83hzBPPl8ayMLSy3tMV0wpPb221bbWzP33uXNP7K134E5sm8uXs6Q8ypELPH-fj4eHlxvzyODSKq8u5bz-aGh_Py4uHy7O5mOs0ff_QygePp-OF3PoLyfJjCySLGMCZC5zHiO9_-5Ke_8qPvv_u51S8vXi2r-7LZeV1tjG3ZzucxHQ9OvKyX3mfyK70bHCRJIzxmnYIkBRWfmA6HSPvjP_nOT_ypL79-OL96_Xj77PknL-8nyjD6kZ947_vf__R7H96___m3WlNfrfdp3QYkWlMkkHj9-v7mNDFjbN4qwQVh8Kefvnz27Nk8t8tyoaTVLN20CXFua8xzB0g7RjoRM2QN34ZNxwMBdaZhwjRNdcyJyAgfyyYQ9_Thua_Wa7dMe2VK2LfBGaIgRQ4D4O64er6FMz3SiRjpluE7jD5zvVzm25ttWSBK1z7ujpPuraZKlAkWUbVtq_5NWqrWli1jWO9TUeWIQeEQGeboGpnSJN12WCdnusn87H1KioKrJ3NyUy1-OcubXiQzOAsqTshMoSiVJssVMJlexw3Rip4L7S7l_cRyxaVf64KZIOZIFoQ7iVRhl0XAiTdnoCzuDzMntEW4ijIlA8TYbx-Vio5EYyAhcDcRRAQnskktk4sCRJ7VSmit7ZHs4QCkQviC-otit-6kFIWeC12XYAlzQJmRTkFOhGIpembuoKRsUyuecVdVVateVIZU0EMhXW3b9swmWFvTJgzW1iIcKqqSRCQ09zncmrZw10lEOC2U2Sm1TcI0t96aQhXg1juaTIc5M9rcp95EufVe3zi9iQKUIarTPAslZZzm6XiYxrIc5n7oLYc9eXK6Pc2nud3dHVuvHQ810XrWyr5UypqzXrPwdcaumTGzSES6BcBJdbraTXgKrlIpVzxaBdfjFzNH7Fh9ljohsWXth4h2RyMZkYWb09Pp0NqczjVHpisff6-Z7uDLPT9zTbzv10_erblFr2Xd8yqVkd0r6Sq9ouRR5XEuKE6GZTJxtYHDcs-0UYJ2P1cNKffszV7Er7c_UI_iPddcmSIqaD_elOeLMFqP2qxGwTWvv0PT64qTROVeQzmXizj-5s5TneLcVxKEErGVNye4xoZcKgJUEyCZvaJStP-IS4O1J64i4rpGiZ3-tPeMPcJzRwPQnnrcL0I7uRREnrstjBGU--2RMyJFJChq-RAFSC24qhsYwuLVnwBluMgefCp2LrjyBll9hBKmJQVSqhu1v868u9LqBMmswwcRq0yWLkBjIeEs5GgxVYg844oZdYVQkoVDNPbOM0YEiYMA1tiPaOoZwLXoLJJEYaaqdSVlyN58YIokK-PLTlBQYlJIbwKCbXZ7c3D3Y2_1Bu5NuyqDM7LXoYOImJ0cgtabCkTlMLUuOHXtulO-plmn3lUlPMwDEQrSzA_euYPnr__LP_idf_Wv_t3_yd-7fPZ68P5F35rOvQFs4RzZm-ZOqOVtxK_97re-dtS_9Kd-Yry6_w9_9ff_4s9_9dvf-_jRzpPcHA5HYfrP_5N_pIf-V__-3_vS209Od8_-3__on3_1qz_i5l_60ue_8Sd__OKTl5_74HNv3soCFRUvhxRza0hK89C-O0PMEkIp-514RwdIDZgojG9u5l_9p__VL_3iL2zrJk33hN6O6KPw-lIXC1dVpgwOCiLhu5vTB3c3B8Fv_dGHf_zdj3_3-59wyo988O5XPrh5_4Z9GBLJLLwf4utjsyOMd1UDVcNqf1zvLYW96gWG195OiCiB1BLBhanAKUWEmToaojZvTvuXzS7eUMjFNkFLd62pWboIN2g5DuQHt98URUQ2dCtuQCQLJSGdVGucILuum5w4FWVkToC6qoV3afUdKq0pc4QLi3kcpjmrFi_SgCLub2M_moDhGTI1RNYBIIlaMYAhEK6pU5qrNpcEiXTNPSopSeN0d_xPf-V3_tIv_dzd1ECcQa3J3JWArkrgrogRlPT0yY0Stm2MzHV4Rp5tzczbriK8ruPhYWutv35YHofdP9pwj8gIMnPbMjwpaTMHS3h93RETe0Rv3SzKi1iFiw6gRCYiAB-nTkljM-1S1OYEVIRAXWTzJE4VbJtHWO0ObVhNxo6HA0V65Y6Ymoq5m5s0YW3b2JKxXBaw2nruvZtb6005fRkWRuxu2ebOkOVy6VNrk5wfz8OCIoxsfPqtv_nLfwbB7rGOoQ0elHuqk2LY68dzQl49PAblYZ7eeXpLTH_yne-3piQyt_7hpy_dhohs63Z7d_RhgDhRmEOoC24meQ68885br88Pn718fFxWAmz1y3I-Py6Xy8aTEuXcpvOy3Uzzui3pcTjMw2K-mcZlbcweFRbwCkmsyxpOY91--zf-1bKOjz_--NXLy7NnJ1E6X9Zv_MlHYHp8vP_wk9c_9MF79fGb5-l733v57MlJKcF0OKhnDItdM66NgeNx4qRXr14Q4cnx1snHOkTINzvcHDjz7tBs2yxoDG-TiGB4iCoT-TKSEsloIoJtOIPNRwzXrtu2SNcwU90ZgBGEhgrim3mYt65jM1Ut_0xVTUhkjG3PhWbUM6zmquBrTCEiwmLEDrpgrrwrFQwHbPscmTJSeg_3TBPRLEJ37G5EogBa8XrAnOGQRkThTm6R5JkCkunZ-1F1WKkHelHLUyCAXMf78iZbUTz8cGcghaoqSRmgnTld4JtChgBaKKDK5mIfFHNGqHYiktbr4wfsw07KKJV9REDFcyejiEgdsavwZ5GkknXJoYRocETlmOtSss8iCAwqihGlm6O1upYwI2Kw6NWwy5EJkeT0SBExdxWNcL4GR8JdhEU0GSItiSK5TVO4M1PCBcJZWwiODG2Ngdh5SqZNk7g-XaoqWjBsGpupNiJKEjcrNy-qorHr4CmDtDUAYUFEs2oye3prfe6zmQOYesuIJ8_vIlwYDagFQpe2rtvNzREevWk_TAJ2t9vb2ySapynTFZjnjrBnbz3Jsd4eD4epH5r2qdmwPk2qWk-jOrJV9bEEybEb3YgiWXg_2EUVQqqwghraSjH-gruqsHBN0fJqwmUCswhDuEvz8BJ3RbpVBoQpMkdkZKjK3A7H-UBeMdz9AvCGIHrtd9JOjtkVBcQVqwFdK6tF5KkNUvC1rJPXFDu9-X2SRCg5AykCSvIqNe_LD6qsdmFyMqMIIPUSVRMuea_tRFbNvnhZpT-rDnTW5EEFkYQ3Ul26EuN3V3B97dRQu1RGdWHedcF1_Y8d9JME7CxSuToBinHJnIzYa8h1ZUgWxI4F3e9Knm9-wLwXfz2ZJPdFjVoYExfFPjz3GxGxR1YRmoudGRnJ5Qgwiyz-EMqMts-B33QW9s5QaVMpVDiZw01rYwP1rC4BiBEeKkjOopGae4kRIhMqyeQZHtEghGRmTwrKyBASohRhr7hIbArlQjUDkfvBsZgJifSIKh8Tc4Ipsp7iTbVB9nQWpSj2-Q242O0qmhnVXOakiFBg2CAGIKJMkQIOChUBRVOeRJ8eb06T3N1MzPtsqWn9Y4WSI-hwaFyFWIWIgLOpcuSTJ7OAOqsqbo_T1NvUVYDj1DyCM5syMp8_Ob37_Gk3_1d_9P1f_c3f_rv_1t9GmjZIpCi6SnIemtQmFUAQb0xBYuS-PP7FX_hxHfK_-X_9s__hn_-phP7-N77TDndTl9bboet_8v_4h73pL_6bf_nL75xOp_nVdn4yT6o9w957_4uPfv76H__J09tnpycHDnLyzFCCCNdiqt5DpWpk5orPXIs5bBEslBkjd2FcF_4Xv_LP_s2__Oc8g7uQOxXQFmQeVSX-wVCNIUBGhCfqpVX94rtPvvTB0x9_99kXnx9uJ2iSZ2qCVaqrVs8iKIGLV5VEQUYQqWtMk27p7N4gybD0-tCooD6VxXfK8Fpe7QWRoMxUSQuvtVN9uEQ1w5vqOtbD4RhpWgR0ICMYGRTDnCEcWfZcUZRbbsnNc-0ysRRFgFQk00sJ57zXbMxMQFKIi6bu3ltDIZeBVl9QxMLUphZpDQBQTIzWlSmbdoAaoKIGKvZlDe4ySMAszJmdyucgXu3JgHQlZFpWUFESEByfHn_l1353RfvS59-au9o2qmndu5inuXk4IJuNqcs8HxtjeC7r2iZ-5-7mAASRjXAmT_KIzWwZAZUxcpjbcCiYeVgEU5mVmNK8bEU0bOtdW5Mwn5pG-uHQVXksm6C8ceiC1sRqu80oii1l9mkiovNlADAbBboY7lEMcUCgvTWnyNq4RoKxpxyZRGHuHsZM0rTGasfjLEiPKEhAa3pe1uQ0GwBJ724Rbo1jG-tf_Jmf-Ykf_rytdn-5XNbL5sO2NBuXdbu9OW7DGfKwrK3p5fH8_MmTQ2_Lat_7-NP5MK2rm_tmeVnX2uuebg7EbNtw5nVbeu_ruj5_evtnf-5rEP70xcsgbGYezuBQevVwjh3_QCIdSE9LCoFu2xblD7LgnSQZHl6YEM8wy0QD0h6XMfzx_vzxh_fPfvrdx09exNke1nWeJt9svtXGYObw9b1nt69eX27nCRBp7dXrcw0F0JARBHSV4eHhj-fzq9ev33n6_Pa2jbFR0mmanrx1UnAGoSmI18uauRfYdm9s1AqAnTiQ5oMz2EJE13XtbY43_sjIoKipNoPGtqkK19OhN7dBTOajvsJjGESq4Unkbg4VorThyfDNIEBZKZtsy1LF2vCR5FOfl8siCs6dMl0p2_Da4AWBaJ81mw1jvqaZFYCiiUfEGE1b7IJ5kf7sfRYQIyOgwoygALijUzgxWUVHmqIkJpVPFa0cRbozJ2QvIBILc9Z1BECxVyuPV1C8OsWAkCUJiyhuOstevWQIoRr5ck1QCycJpLxLqgpBQgjMTeriTsSinTiVmcKgwlwO76I5O5fIzbPUNiwKAQTDrK76ES69RQTVjJpZVdOjMr7gdDMuyVGSebA21mIOofUWFk0aDQdEChISLr0T87CtdpdlmhfV3meAIfDNWLH_CWAv4ZQqKFUkOCr2I-DeRJSbVEKKklN7h-ixK4Nba_OhC2ieegZN04SgBprmSVVEoSpTl0m1ibBHExXl4-nYFbdPbsB5c5iE8zj3CZgEz25Pp4NOrcfwm7vTNE3Xnwlf1zi0-1_r8kbX42ekAJx7Gq5KpZHEWeXPfeDHUjpgCt8Zi6WwoeSqfSaFctGxkTXtoxCAkoKzUtg0lqe3Tym4_G07GPNqqKM3R_9_XVn2g9H5m5P_nripC4OwRP2Mk6CM-hWZO0ofZG5J5GaU4XViLic07fij0kmUEENFd8HX7hmgpAgPRu06KJhLkfbmer0Dcd4gNZOZCvO1M0bqM1T_CAFX7vw6KtiFI7nLsuqHwAUyC6rlQ30KqoKfUTjf2G_Me4XjWqJNT6-6BGv9AzMpMkU1IupvdYUV7jboekUFb7Jhu2Qwrq911jqoBA9AAUbfrJXqvSVJlGzlY-IkLoRINKiNnbRbAzqSK0ZWrg_UzP3DjuSiipV8EUVHqvfJ3iEuWpBTtCYRLgBEiKhB6Yosq0N5cYSgYmNA4OkZ2VQyUkWYOYgyTSG7rSxJd0wCE5EoKvtQybdaz-r_n6s_jbUtTe_7sGd637XW3vsM99x769bQ1VVd1dXVM9VqNklRlERJpESFgS1btpQBDpwYQWBACTIIARzAcD4IDhIggRHEgYHIATLYgSxFJGjRjh2LAG2TFIcmTbLZHLrZY41ddadzzt57rfd9hnx41r5N51uj-_S995yz99rv-zz__-9XSqJz84OEEKUIuBWWqZSrexfjWMi9FBHijrDZjIwIbonAGWqJiFI5pV0iKEzt2LaDkMDZOPSlbza1FiaIzVimsU4VD8cFAIShLf3F-3eqEDf_va-98-Wv_PZf-It_4c5ZiXByZKFpKuqurgnGcsdmBsFc65d__-0f_MRL9y7O_-Nf_f0f_dMfuxh4Xo6_9vVvAJYHl1timqbp53_m_0MYf_Gv_9U7m1qETHUcKiOHGzJfnJ3vzs4fPnn0vfc_uHfvLjMn4S0ghAlR8mlZWCyhUIy5UM0xGWXelhOChGDYD_Nv_Mqv_5k_90PHQzdAJsy2HwRlMyd5o8hEhKdKTYjk-y8TT6eiXWZRCSgQaf19ugUyEEKBggGCpNZLNtIdmJGJAw0pIVfG6wQZI6CiIGGgp98Mg1o2y1d1iCOSoyMRIXlkK5rDzSHcbCyjmkop4U4rw6oIMRBWFkBPvFcSkSgAI5gLhoB4hBeqpjkCA0ECDmEOR2EqXPJjkooABBExEDFWoazzYUChkqy3HBMIs5mJFAIiAndHpiqSzRs4fQQQcRHOxC8aEBsCBAMyMgsjlcj3MsrAKcnjICSq27N3r_3L3_vgCw_uVinTVNs8I4GrNgcpPBbWblgEhSyACwW4MD64PPMeAdEjujoK74-tqQFiU2uLuYcIuYcUbnne8vxNIxEW4cRjJK8cERlBCHbTOI6Sj5vj0rqpeggjEauZQwiREANgkbKYImDX7ubCRa2ziEUUpiKs5pZsMRYEzBySUzAyAlq3wkUtx0p-_97dO1cX6HB252w5NKl8--Rgrk-vb9JE7-pNnYW4lEpYMP7WT_34ljkgzWjpMsZSydSGItf7gwM8ud2fbScMu395Pog01aXbUTtTYWJH7K0hADOdnW1Ave1n4VIrE-H5bvdjf-Yz26F89WvfJeYgmJcWRod5Jhpvbg8YgVk3wQADs44e1rRWGYbKjvefv1LTMo0inDWarE0iAwgmtRmFvDcp5el3Hh2u98feD_Px5vYw3h2__Ydvz_Pyh1_7bh1ke7Epte52w2ZTh7KmkavI3DSX7cvS3K3WYuEs9PCDh7vz3XQ-RYRQ2W1qgpIhID2AGQ-0xZdDR-beLcLcos2zWxCStcW7DWuxHsPM1dxdF0uoWJFqvSGC08rTi9AcMeblEM2rlPDOxK4NuqIwE3lYgCN6fixGWJZdcf1ciAhQNcAgYnfTpRGX_DEjofeeMQlkyb4cc0kVEiGB-4raH9i6hnsCR1iEEbmeP5-f8EnyBPMMQ0MoCaWsi1FOeBVkyoV4x4CU2oRqFkfcnfJhAQAZcKScfECilHJfTcjuQLwqViBFlZHezFP2mRiSgeiwhrO7JkY3AEBoHc56nBIOICRgjhYYKdjC0IwOOhGjMEI60hDCTR2QuAh4EAElhtPWQ5okwp84GwH5DVHa2hyZKQgsLCHSSXpPpDQhexgiMQsKBziyMKAQ1NOxPpncCJBkIVjRLQRMGc4kcDMHAmKxMGYBJGRiIqHEWhDWAgHTOA61AsZQhAi2262ZbbYjEzFikRIBm920GSozjdMoiEMp01hLpbGOQr7d7DDsYrtFiEGoCk5D2W3K2VndTsPdq13hoQjnX5uW3PS3womysxLifZ1m4YpqD8-Z82m6DwjEaOCBobkzX8_sAUirtRZCcnRKIFQoojAXoYI8VBZMXAsagoEtYUTDvYvzrNrRCW0TawV9Pfd_H5K_dgOedYTXeXNm0jBRVtl_Ta5O5DR3xWp6eF6Tw7y7ZQZj_XYBwcNcMeOsRFnvzwYIrkuE_FtSqcfmgcyJrbT8Sa1czTUPhIRugXRKP53uMKtq1wN4jdpAABLFWjY4MfKBLHs8p59BrP6w9QaPp4RQYDzzDqesLYH9ASdYPIQnxCmPHgEZqSfKVz7GSkw6XV1wvYKsaNdVGIQJdwqGlFtZOBPpaaJrlu5cdIRC4hEOSQpataXrAyGyU8iqCoz5IyPG1XSAZBnHBvSAsOCEpnkQojtmScki0EGYZ11y9qtmOR4WLu5OJJqTE3cCgOSZnGwFfLI6RGTZF5Cg0BBhKYTOWiohuK4B6zWguC5IISe4UmqYC3G6xsogkZsHRO8-DnI11bNCl2ebsyIOYGbDIKWQthbgpRai8BSIQi6joohMQwmzWpiFN1UK426q21ILE1mkc9jNhlpM9cGds0F4Avr6t9_9p7_1W6-_9vpnP_2ydk12akDOXNefRAB2i0Nr3_z6ez_4xv0XL-78R7_0leF8ePn-pXqo2R99470_-4OfQ0OWOm43P_v_-jkP__Gf_ok7tR5ub64urn7397763P3nmi4MXBCkytnZxeZ8-ta3v9Nbv3t1twgx5mQBBDgTJni6L66oWnAhFJIAt0j4bJiCEP7iL_7ST_zVP6-GxkAehdiDfH3JJpeSMr1jEUzrm38FSgcghEhKf0nBMy1mBivqK50npgKWECDMS0sKKcIJUIjTnx1rzC8zSpjmEqKCiN0twgm5khCJmgpTJOgbcFUOhwuhQxCuRCMurKYs2XljwCAk7Z2y782JxUPhNKvTmutzCwxmQsJCeaxNQ_Qa26TchRJAxEUdHDwVy7nOQyJikDSXMweEqnFm8ggrS4QKM7NAYHdjQgsT4rWGCEBEi3bnfCSCgifhnvMeIiUXm6HKhMIVMYLhfLP54Y_d--Jr97d1YCJg6mqqli6kpTUkvNkfWURE3KL1_vzdy4IFkdWttT43rbUsZg7QDeZFPXHBCKfX88nbmrgRIliraghhRBTmRLEZx8LcljaMFRCQxDyEONxrZesGwJzow9VeqmaRRLvWW6CopdiA0jWZxgC18HBTFebDotNQ57bUOixtZpbd2XDnzuVU6v76dhCxuQ0DD0j7Q7s9HgGgq4kUrhSIaioIw1CnbflrP_IDpNFDEVHDusV-aRFORKXwcdEOPs8dODZDfXDn4sNHT2-OsyPsl35clkV90R4ArbepDtNuBLNw2GzHbR0A4qMv3j-r8v77jx7f3ILgMvekswTSk0dPj_OsvQdEIM7HI3GZDzdDqYQ0DuPzr74Y3UJ1GicWEKZhLCDUm06lTtuRiEjYAky9A4UQcBMhdzNzIkSQ1vWddz9U8kePnr7z4e2X_tQbsWiROh_bMIibUmFz3GzqIGklBDNDEWKSQZ48erKZNs89d7nZjuE-1qLdwE1VtXUz39_MWcnyMBIKgFAz0-jKXCN6a0Yi7opAgL6u4wnRFTzUFBEKiSYfI_N2TASBWN0t3IUQAsyU1nU3FxY3yw_TPOB11TCTUsy8DNV7y3upq3EpyddwUyLUbmXcapsBXLN8iYzgQhJh1o2IMG_szOAU6N47EYIjSwVXWclcmMh2CFAkJlzB1Wng1DBJaFlkDNfRYX2SOMgwuncgYBQ3xSLhTsSRxiWRMCOmlbSLqG7ImNRqMM-lLxF5dGb2bgEUCijotp5NKAC4hAcXdAc3IEYi7scGQiwMZq52GlUm88iIKU1ynrjCNSEeWIQsCpF1Td5Wby3ZO9aVVmb2mkfPAHROUbMxSVDclmRYBhuVCuaC2JeeUCd3JA8A4EEgLCwKTwGKwKdkgolUIkEJNAAKUydgJioi4V1KMfdhM4WuWx7m4qrAWIQR3RCCJNyRS4YpkbFUGYY6DqLd8qrT82llvp0GqVKG4qrDON48ud6MAgS7Te0twq0O5WwsUxGKONtOz13twmme2zRMBBgZx3nW4lhDr2sKyCPMNUfO67DW1-BW8n6YMFI5FRiEZq6qjAgBzJSJNZZkscaqiCTLF0Z2TgmRa2yFDXDjDjTuwc7KBEkbjtMJOZ4deP__u78pLlvPEf_1A8W6VAFAt2e5oHWiDw6ODoqUTuv1BG75-ndkQYgwCsr_NfFRAQFOJ8NxypHDIbldicZS84xvQ3jYGp0PCE4MvXq-HzNA4-50CtZkMAdXJuI69nfPPz7Z8-jrBsA9if6rrSFWnUNERtRgXdLkSQpWROe6NsjKtWGAn-S9GR1O8q25pc00AahuEaC55yHixPsgI6AzoGMQhQN6DmpWypATkqoiQkFWd4dApPQNg4fkbgQYELsrBlr6Bt1KSkUQIoJ9dXJkdxwdgYJwDQ1mwikcpVCGtwlx1YFzyTybMEUAA4UbM2n0XHQARq4dgakgBuKSZTgERnFSi8h9rUtfA2yISUmi1TjnSBxhtZaAwMLuYeYkHG5Jes2rZ2qTBxmITBguz6fzqW6GASiWo48Ar9y_09087LJKGeT6ZimjfPBoL6UupoiMQsRYCEsZ27EPhF314nxHAUPhrirCFrgZQJs6xtkgeeQEojoMGPD2B9cggsQAwhkddliamkOEzM32DfYz_uBnXzoru__kV3_34vnLV164RPOIotEOvdeKOkO0TmrQXUbVY5unXpk4gsyns8lcj_ORecOEGlakvPnGGzfXT_74G9-qtTz_wgMmjN6TE1BqQcBuqmaSEniNIMrp0sjYNZoq9GLs4ORIx6VhLYiADhFBDBDoqaEAyHYAOwc6WyCguzf3UcQcyIORkFwyO5eqDkSPkNViuUq1DIORWBgjDKMw-xpay1USm7sgr0lUQrCaFX6AyJrboS_MXLl0XYCIUhfNZKqpEwLABjpScXDKAj2sx_KIBNNJRAiTWk5QDFia9zLWaJ3IOcTAVV0kD6A-lGHW7hiAJsIeEOpESAIdQYhRyAHCBbq5G2Ex1wT1osBQq2knLhGqoCK1mzJAINRCgYExEkR3cw9CXHRBAiZxagg8-WaOIxODhXXjCshUkRq7sDhqRWRdvvgC_80vfcI7IEIzvdjVQBOhw0GzuGTkoXb96GZ3cabuCLw0G8d1smMBpUhb-jKrRWhWBMkpsKvJINYtINy8MIWnWDyXrQgQg5Sl9c1USsHzs43O3pfZtathb50JQ3sCCfNJUlkOxzbJJFLm3sNdChtA8nOExj7PEdC1I4lHMEt4i3UhHptxUNWhiOoCAHUs4zBMm_Hpo5upFqKYmx4OPQB4ogETCqyquhy6A20utwWg1vrk5hGjudtQSmDEvLax9od5GAeSYdjacnvz3N1ziBgBB-FxN90-aSRVqBni_nhUV0KUiONh5of46ivP78fbs4vz73zzvf60X725ub45vv_ho-PSeajHpZdanCAw1el8jJhbJ5Rpd3a4eVIGQfK7V3c-9uqLZTu8sz8uS1O33Tg0NRnlAnbf6vOubG-v92NlYyCsMwSYcgx6o1TAHHkoaPDkgyckPJztFuvbzRR9-foffevTr7-6P7ZuwYHg9Pjx4cXX7nnz2-t2XBpRaDgGGcB-Vgp66zvvQTx_db6jUh9--PRwOPIoHmAYZoqE6_nbs51EvXsBtlDTGZGGqVpfvCsXBAdMYAZErUNf5vXEUmS166EDsKoV5FKkzftAbKqICExuChDhio75ZOk2Ew_ghIgK2tviAWTk6shA4Rph2gnBtYMUJpmtFetURNsRZfBw6wsDdl1QRIpk3pRLUbUiQC48VHTnIq0tBC6rDIMLoCMw8eBmwAAUHr56vhByBO6h1jpRIIGl05HQwxwp1FgATnBP7y3PbSnLzLMLMYIHp9cUOzO5ZdYArXcWsm50AqdAZEsy3B0zWw8IjuBOgt49KGSsiKS9AZEAurmDAwZy8Yg172iGTJZMpggISvm8efTWmJGJHCO0uyMLWVejSqlF7B0gWDjRJTkWsWj5bxQ0VXWPYbszVRHmWiKChEGIENw6OpQyqLfMWZo5IcesNBYEkyrewyy1QYBM1hYpIky1FJ3nKgWyUoHBVUotK2wQsYgIMjMO4xTum2kqhONQL7fbJ9c3dZDF-jAUD5jGoZz8Xxx1Ph4fPLjKvQZRDNsJVKXwxdlUB-EOd8537ejhnqlQEgZAInAHMyP33KFnel_T5UQMOfQ9FQJWUwGBWZh5IAxIHRwdJQvfifTRQAb3sOZEIMTJ0-_mTCBMQIAG68e5IyFVCmEcUSZObAyc9Ex5sD9ZcE-NxVMr4Nki4BmkZ_0qB3BX4iSgQYAFgroxSVLlmXhtuzIZnmwYyABJt8cwWyvC4K6r-g4BeJ0bEyMYYpyWAs-YVe7BJ0SphxFi7gfXMvP69ZAWwARnnLI1Ho7x_StBIGL46qaLrLuuP5wVx5UTMAtnAncQogjQ1VW8NvU1gleqZ9KbSM3ysB4ObsGCFs6AyTIhgHBixFQO2Xq0XqUJ5oEA3X09QIQLYlNfIUJ51SJCTPbRagmB7CdhssQCiRYzWiHlKzXHcxuw_r5y7YMRXoibGwOtbxIEYVHIaBHm2j2Nm0zEEc0jeUzIK5jf1IAZQJMnhEDoWou4GToUwpNbbb0qERNSZPool77ZcQ8CwBCR1f-8GvQcEUrh8KyLoLalDCV3rnmxK5XZ7P75NA3jUIuZ8hmXsQhhUxi4pOZ8knro7XwzHrrWIvmnM_LAVJg2kzCGndBOrXUpTEjksSORq81x6eQeplSqASJRHerbH3zoFHl4ZUYHcHVzRyneAFSnoXz0-Z0a_9yvffX5e3c-8tJ9m29aDxSUgn7b2qytdTBo-9ll3m5Hr_70eM0GCNc_9KM__DP_6Od_6qd_shQuha0HhqHhYsfzO3d2ZxdPb27-4I--ef_e5XPP3Q3reowOkZo2EWqtZx5MzfJSZ-CAOAz1do6R0ZCz6AwMiXnDjukqFCJ1IyRwZKEAXxQ4iIkKAyFFFj-ZKpEHoDuShPbCJdAoBCEs8qXlTEgABatDB3iGQvA08GWEdFVIE5CjugkPHubRK4lbIMUw1BTDEUtlWcwyOEpMuXsE04GkADcMCOAskAcykbuRkAN09TRYzL1PtbZlEZGlN48QX01VTBzmQ2FCVtfK3KCzCKwxWTe3wpxDBYMQ4t46M5RkoRAjYZan3TzxHoTcoxcZFYIYzIE6GBKhVxJk6GYALCGttQrUAM2UiRlRZ5WpoBG6sDhnSJeAHKCUm5tH_9xPfNEXBSVAEIS5qfdYWhcGqRVcgGB7udvP9vT2dhgnYqxFAvy4zAZ-OB6AZRw252f0-HofFsREuSkDbGoQYHmr1dx3IBBE9-421uLuIlhLqYTeghCGaVBV1xAkzRYXExOyiPYGeTSh6L2xQMa6GBGIIcLckNk8SqmpSpqPxzVpmNxm99QtE8GWpZQqItePb13Na4HAQCwVr_eHMgxcJcK8EboRByMyuM6LMp6XUgidaQY9zsdubWkN3TNYezge79_ZDizf-vZ3X3vtpeJoan1u-7kdZ7WgQJAisQQyToP4sd2_d_HRe1dvtQWbHvfLxz9-VQd--vSwP8zTdmw91BSUrve9mXfzAENwZiJij44OwvgDn3n9U6--8nR__PCDx1IwgPuhAwN6zMfl8s75-eZCW97KFKAOm4oO282EUugSudD-uo8TLjczOAHgMh_Hs-0h2kfuXG6G3cXVnUdvvQURzHT_wR015hn2B1_m7uatN6nVT0F5ROIaoW0gWDw2Ux028uR6L9sB3NrNzAS9KxJyILg21cwKFOG5zUQSwt4WAuhtJkKWMhHN-9twWue4DsQMwqCuTbmSsPiydGxSpTVFRm2dmJ0IDNIaQSxEjKaRUgKKMAUKydJwRKRHgji6Q2Gqw3xs4EGCtiyIIVJ762Uc5uPMQ_XepRQNDQ9mBrNw19aRgKVqb-YuY4GOlHBOVwcktQhwZiZCkuIJ7MisMIaBhStJZH9JhNeGYqbokMATMc-glpUrIl6x6xBM6L1jBCWeIbW-lLi9dAArMSZJEQmQs6EXgJzpBRIWIiZEc5ZkJCCL8DB4IBahKlRL2se0RUCoK1VBROsaiMhCwkjhYQ5GhZLbEK4EQEJMIIUxHIgNjIjQEXKiTSTCjKiJpkeMiEJMEX0-qvZu3VSDwJOWl1NgDV0WYtEIqBRCzkCbyoIBhqmJTnVuXnuKOIKGI0PJXCYCBDKVUqt2LbWWWsdhLMyMpLMxIjNb12kzbrbb5v3qzq4U2o6je5RadtvtbigFiCKk8NnFToQ247gZ6t3dbiIS9G0p3nRgubqz222nzXZzcbnbjFMCW2DNj6x9VHMwczNPcS9m2RTWzuVJ9AyxQlrWTMiiFg7q1l0VwbLbTOAQOZQPQI1wT843rvrbWFEeSb2lAHRUB0rIXkSAn-wK-YCF9ay3TrvhGYTq-96yNcqS5-Mkmq5qzowbq_kp3pG_F4zEQBFExkOZEIKZCwkH1jKIDIJSssy-Tv3W8XpmkQhX3ASchj9rhj5R2BCceZGIE16fkAiAMBB8hRNnuokQ042ApzWLr8F9AEbHlRcaKyLzGXUg0kSYGgEihABGZMIhEcWEhQkJOJFNvhoT0CFW1hGqmyCFr1NVSLZgwltXAkHeqCLQkr6Tv4Kjzx7g5gQMAYwlf7uEwIGeNqLIhjCMLGn-BECPEFyLEASpjEopebarARiBMN3RmpQkQMS0cLqBIRI6nga6yMjCnMucWgQhmGngGhjIlMbuysLEHuFgmd1f6aiB4Z4lJiGqRZgowQe81r0BLBBAiEUkIACDhCRDdJ6v9GQXBAHWYYI4NTowqtBuWz_x0vPPnZ9NhQtjKSwIw8BEUQsSo5rP6oYGhYcqEJGNlELIEAggAmOplYuUZwIzt_DWNU1eWy67Qe6fb1lKGcqsfZjGSvL4ux_Sdrg5XrfWzKIwoLgTHRc6dhp323sXm7cezj_3y3_00Vfuvf7y1e3Dh202j-huYVYQxzIUxCIEDSoV7fDo_Vse6Lpf29LF24svP3j3rW_73G7387QZ6yBhAOR9PoYu9-6cffrNV93nL__m777_vYfD2bQZCkF4WFhUKbVUACwswoKZkw2P8GFiEaRCFJ4hSfNYNHNlMeRuHVEIiiC5VYAJURAKBQGmgmBIu1Z4qVSYyb1IzfgvWN4cgQhSWIwIBmaRyUHMhg1HjDIyEkKaeiWnEsJkvjgaEgoVFgqijDuRIzg0U3dfucGEAc4s-RGYbx8LEKGkynbrXEvGgWrhggAItQiHF5F86AkTIJqZlIIIWMjciRAFCaVKXfsPoFyxCBUiCmQsWYICoKaRCf7CjIAcFO5DqUMphZgQGMTCmYm4AAYKQXgVMnRkXB2gQJWqY2cAYu7RyLEOJSKYinUDg77MRQYIYA4L-xv_zT_fGlmPHn325bbd9t4BrBQSDjDTrhhwfWiBMNRqrsJYmVUNAcahXF6cQ9ChLRHOlU98CMrJSFn14YiRnz4uhYpILTLVAQEXb5vNJJUAQpu6x_nZNI2jGwRCql6EcvcClRncza1kIRBJiqyYVCFG1K4oKMxuHh5hUYcxwlMYr669z3cuzwsDqhKCMIT23ntoPxz2t_PcDYHKZhpYcDPQdhze-NRHr-6cP3d1MWHY_jAAQNiDu-ciHOBt6UvX1nsuYYQFInrXp49ub66ffPTF50YWDDjMXSEQsVtX6-bRe5dCRfhsGjfj-OlPfPTRw0d3zy_eeef9Fz9y4cyPH15f3x4CmZFb68dFA9nJu_ZlWUJ9qOMwbR09WMcqxfgTr7_u5svt4eVX713spvPtcHGxJcTd2eZjr7y0v9mfbzdX9y_Pr852F2fpL9lO23DUOUeDRYbKVENhGEsdBN3afLvZ7T71-Teff-ne_um1dQdvrds40bQdDsdZ22LWmWkzbsKhcPGuFRAw2lA-_ubLbu4eSIkB5-XYwCPvHmbmpoRQso41Sgh212naEpCo29LCHT36sa0V0DIEISBJKbVIjvzcQmqFcABDRg8DXCXjtdZECHoi8iFM-xrMI-rew0OIwcMzKIFgrYObaQvX3rthlIIQhqrgAAagWoeCrrWUBAe2NiMEF85PcJ4GLIJSgpG5BmI4kBSxBC8yUrgIgKdcYDSbpQh0BQkW8kTo5PfmDvis9QtAGK0RS2gSfgyDItBXlLpkFjBcs2kA2pFZ_cT3WWPWJ2d2ngVXwkiCX4xTeLhCySHcEbgIm3mYhbkwuwUyRzhIQYxCBihmAUEkpSIBBhJ694AgIKbS2oyFgxiJrasMkqxDHmogtNaLVCoE4CQc5qsGFgGZI1AdGdADnaKMhQDdNKyXzYaZAqibDiQk1OYGjKGdRCBxchy1lt4sAnJTAeFEUqUCIjCYeRE2NUYSJqnSjodpGr33cZq6Zg4Vt-cXZq0wM3Pv7WK3gahCMGw3hiFmCARmpbAUCIhKyIR1KmBeSC4mmTkOt_38rAQAgZciYLFqXMxECrghc6g-S4ungPZE1AzmtaWaK521gBtrmCeyWorgqYgEwNT9rkdDyzR5IvuS3X6Kmigkug-RmYqsdJgkhDAgMjoEC4WvxM9nLdRTGuiUAkov63ql-L4X-JThA7NwM17BpkEAHAni5YzcUZI8V9StSU73GMGBRHrvSJg9VEBCclr7x-vp22NN04XZuh-JlXizToYj8j7tQevrPOkc6xcn-2odMgNA1mkSlpV92qwSYNYhICEokIlbQrRwYbKAMAQEIQgHkbxvhwPkmQkhGNGyA83cTd2dUE4z-wCH7vZMJ6xm6TokWC8FeTnxiDUheWoeDDhEZMPBAkBjjhNACYAjSNVR1mukuhMRIXXTVd8cZu7MnFu4CCekvLmFOQImIAufEbvWFgGlFEEYPRwZT_TSYIKkuCIjBmgoF9amngZWVz-ZQASRhZbeLclaEBFeuARYmg3zzhvJWidC8cyBCFNwNnTZugKSSDHLuJWVoSRrCAKJggnLKGOR1x_cvxymguGYfYbQ_GYcAUCzbxJhPQpxhzjfDAph6pDrzyzrExGSEBQhRlwWdQtJiBAQhU04AMfSTYrMsVxenjEGW4iVx4-fvnBvMuu94eGIxw5TicuLzcOb-de-_vDt9w8_9gPP70Teeec9C7x7745pc3ea6kFbhDIjuIfZZjMahHVR01t88uq9T7rBX_xLP_KP_sHPf-Kf__z19x4-fnKz3W2kyuMnjyrL2W7b9vthrB958ODu1dX3nj7-ld_8yv07F5_4-Ouherzdd1cEGoQNXZcOtO5zwlx7HzfoOT-y8DBO2qyDQliAhxKBo6PnTxMjWezh-SxFRrcI9ZyXJ8UKIUql1rswAoGt2fnVXZ2N8qVrEUYBCEYAg4Q_Ijt5BFAAkevKrjXI-S1HRCQ7joMJAtb3qZRioa7hrMywusYNSMjMa2E_UeHi2ZSDCNwYCQi1Nw5Z3wKAZaAwBcBKAmAk4qbEZt0KsXcVYlNkIMIgoQDybughSDRVdSVgNSMEqWIQZia0urpLDgqDzI2c3J0rBVBfugiHeZgxFoNoqsCo6oQhRB7Gwu5LmSTcGTIOFwRovX3-5Ze5u1lwAYgoUlr33pwFEXDaCdrQ1AldDUshRrrYjIzEQuABBkVkHOv1_gBAsi6aI8xEGAKWpgBIFAGsYRHOsVYVWSjcR6zuToZNNdy3Zbq9afPSgKBD3Jmmp4fDtCvL7ObAjEhwiPmOb7NXRQSV2Rxb7-7OJNbM3RJ8w5KJWReKyvjJT70xUhwO9pRxf5wVCBD70gkQCNvcx50Ice4fqMJ2HH_k02_Ipj4-v-htefe9R4fuVSCYX3lwL2xtn6p2Jho2tTd3JnPYH9vS56vzbeVSmd67ufne4-uOGIFcilvosgBBa_ojf_rTb3377TtXl4V4GIYy4eZiI4M8fHijaoeDIrMZQsRuu-29h8X-9iCCfQb3TlILC2DUDXz-s5-5OtsU34R1aHH3avfw4U1HvH18HKazt97-ni1trJu5te0wNVYqqD3mebZZqcpIrKb3LjbL0uJ8c5yP42azHG625eK_81M_agt4sya4f3pLEDSxNgiLBCsHBBI21W5OEGqwvdy-_-H-S5_5RN_rUGtfZgA_HBY31MVTzU5DCbNlbhgwjAMXUTMeykDo2d3pS6113h9lYKFirVMpWKvuDywF0LOEFt6JKOO_i-owDNZVxhKtd_WSZB-S8G7WiQCBYO0y5qeYZfMtn_7ruYYA1ILClYhKNmatA7AzU1OgCFNLLSAyEaN1i5VvHuioalwFqcy6r6VOYzVtueODPEATCAkFgvliHgEEIkQsUhFTYFqQROpALL5yXcjNkeQEGwJEoDVoyXayCZl2M4-MNYtAYFhSLoVo3XhmxzctPOEnyHcpjATm4YHElqQlEbdYwwcRSCjZ0AWKQO1dUyPlnndf6y0yq5HuJI8wxwgR5tQbI6IUR3AEZNbWspjptk4-w0PNgDAIiaWrZjQdiKkyZZTQHEREBnLAAF16KiMRgBhrGZmKcGEARrRZ3dG61klESFiGYaLAQiQEaZ9FxDpWZpmGkdy300YASynoLoinR7aPw5h5CRbufWGEJP9cjuM4DFWkSs5cmUGS5MNAUynCbB6bTX3u3rkADIVM1WxJK2R-skC4WXhiy1a4DZxwPjn6DQcHigAPNXfvuXyBZ-h7XH9BEQHRPV9Y-Zte86wBvs7vMYSZOX8hMpRahJMVs8xtbtrMFvfu3s2PyxG8xynH_183gQECAEGsDeRTKfi0GFitT_QsIROMQEHga9ld3ZAJHQgQwTHP4d4ZAYlCg5Ex0MDdXapgsg-C12bqms2HBORr2Hp7WevJyLwCU_MqgEQOZIGnlcSpQeHrgX_dHKyU-wi3Z4KVU9Ajt3CrYGz9rvH0pbD-H9cAUzYATh1pPwWlOCLMcnDvYIxYWQzcgSw_ST0j0SnwdWK0iDym58De8lzs6IF06v6uFGQMACdGXzEJOTylwDRloVm4QVgoOBKk-Whl5wMWFgB0NIGa_pNcTQkRITZzSLgjrtFB5DWlBo62mmhiXZhYZEQwTm2RpHCIMCKY67O-b-LMu5kUFiYL__5bIFcBq3gCI2woUni9fiJh3iU44YGJJUNK-lghAYwqJARCxGHXrb_2wuUPvPTcc9upkGfCxbR7zymHWTgAaFMzIwwi9N4Gpu1QLoY6Mu9qORvr5W7IfQ5SzqtXgaOpavebw3J7aN7D3UEj3NWsNb1ztgsEijYCPH_13CRUBJuCBdw_H148G3_nj97_-V9_-zC3H_-hB2fY333_0VFRBZ_c3qiZATjS0vV4XJDA1WstKJMHDy9_5Pj4ySvbj5cyDgLvfvPtj33soz__H__C6594ndB6X5jg3t2r891O52O43d7czvPMzC_cu_fDP_SZj75w9ze-_F995613hosdl9LbEh6VyzCWwjgNshmlFhb0kWUoo5oNBMIcEN5VBAZhRChMnCQGwgSOEUVhFKRKXIkLS2XJtSoYhkdhCUYkkJJATELgbsbCSYvOy3MpJS3RuahL1A0BJoh5oIqOjCXJfYUEI3flAYiOICfovjCFahJ4SynoyEBu4eClCCKIrFgiAWbBUhDMIbCZMgukopuokgwsTIg5pk-Bl1lBCoDZzTzGOhCQEGOgMDMxE-uJQTGUmusFQu7N8gXsGIzIvMpGWKSIhAcjuzliiEgYJpDXVQkDkCzUwVKELYUDqFl3hLYoS1WLRL8lbREcoXsCozSsWWhAuKtpTkmDqJbRHVtXNwuMCGhLRwzOiVH4vMyH_TyNhaQghFswEjqstUbCvK0ho7kL0VBGR2xhQOi5u2AKc0v5ucHSliJEIvm4mE2BabOuYqGZBsLV5uJZcpILNdUAI8DMIxPlSpWkFGRIWsC9q7Mvferjg_m3333obvfuXdy_e6cW5FNMgWuZzraMYhZIUIYyFforX_z03e0Q3R4-PdwclYZx3E7Dbrq83JSSe04oIkMZAtHMDf1yO5mpEGyG8eLsXLt6uDM178k73kzTZho4cDttdptx_-SpmZ2f7b773gdtf7i5WWoVB7zZz09v9uoWxL7CHKm3Nh8XEjKHbpqFG-YoXEjGn_rLX-Cll4LDILe3N21pUqSpsch8uG7zvCx9bkdXvz0ej8dFZ9emQliIrC2bs8kWa0cNQwtkCO-dZfMv_c2fnHCAbr3N-9tbxwhkU__w4WFZ2rIsYY4rcQTGWqObN4MCX_r8R4srOvTopRIgoSASD3nIAM7u_mazLUORQUqpOXpmkW5LqViHgZjqZuxLrAogcwABAABJREFUpPgSAGSowzC6GRN5b9FamBMiBohwIQYzJDBdRHILjNo6MLIIrIgIPwmAHNDDPOEcq3HWzXsjHogYzSk8VF3zE0xVu2knguwwuCkyBYSrcy0IYd1omABAqiAguA_jCBatKXhQ1lw9nAo_o_h1cCQyc2QJh_DIGVtTDS7mEUj5wUsrIgBPxm9PZGYy1wk5z4iEz0iNgCgAKIJoBqYI6GtnMLXtGESBniOcUGAuzMIkZgog-U9kIuthapnAdjMiYi4UyCwUYM0A2S2BzSDIrgbBGITMJBSQH1u44n2ybEzkZiySg2cUDHNBAncWUutFCiKLVAiQgkhpG6XADDpz6paIS6llqAUYDMzDEfJYZGiGANNuQwTCQoBChIhgKkLaFiEE08JMiFWYhRy9FiaEUoZFPYCEeRhKYZBChFEG8QjtOZEE91CLm6UL4FRZmAyBpWaWiEiWpks3jJCChYiZp2mUgO1UCOHQG4kdb_Zt6cvSAMN81dZC5HSRCJ-9YsMtXC0zFQRAORZJ0HQOsJNzdJLI0mnPLZhfhIVImNISkKhMpry5JvYuY99kga176zabXrd-PS9tzbz_CfTn94H1q-UR4U8ygNbA0SmZA-HBgIKcbFN3p6D8IIh1weSJjYdwIEJgRqIquedftVy2rq9YCNfWfy4dHGg1epk7xOqPCk4aSarB8lkBFhgOZnHaFYe6Qx6Ns8FOsIow8vqE8QwwlCG8zNoh0hrFSU3larNCW__Kld8EgLqCkIJWZmpiQRAQ1l8wRNY_Is0ISMS0yslsJW0DOBFZBBOttlUISskcIHKivJJj7R7YPJE7qSiOgFB1TCjS6gPBiHBwolMyHhgZzUOAKESt5VKFGAlyf-K0LlM9ufuQOSVHSfrwKjRYEWU5dci7EPHabB9E8lZVOGEMwkAALsKMLMAEIMQkxEIOjiLq4AG1FEIUIgxgQMkxyaqsxfRbEwsLA4FjsIC7cvFxpFfvXv6lH3zjxz712j_7g5_66PnFptS8JfZYZx7dYdVLB_Y8kuQoEVBScQ8gjGebst3INBIjdvdwo4Sxelh6DzyaeWuWdyKKIAxBwoA2zyIlzBF9W2QoBYAj2NGvLmot9T_8ze88fnr8qR-796OfGuzRkz_89vWNYhnrQLUgAZCbHnu89PzdWbX3Po3jsK0EbIR3y3jn4sGDq4tKGILb3ea5u3c-ev_-P_xPf-mFV-9XlqXPgEC18FBm08VczUMjmvus0zh84TOfGKX-k__81931_nP3CPX25jqNEAUpLNDjfBpJCvJ5d3cKDB1FtpvJuq-2dTMMIAcOYlgf_ESEDFgIhBwhhILREIiJmQHQdV0VBoIwU-DIAyGMWBipMBWkisSO6CCIQkAAlQQiDGOJFqGEQRi1DOgEQYU5uwdMhCCANkjm8oDWiYOAOQMTYJVqCpFpnMAwBM_7BPdZh0FEogiDG0OGW0FBMQCIhTgsE5oIREHce9-wCMusixRkhFIrghdBYso4nJQEUzgTMtF2GieSoQin1IJAahWpqcUpRXp0KbIauEWI5cRjIBR0grw0CFd_ZlkBQAJzlUwWBBBBSU2ew7UHAAqDECSDKXs3xKwQG4ZjU9MeEEWKuSNFn5u7GWhrbRwLF3brbT5y4TBjdGYgQFXLdlXO16QkgTGjBqRu4LioAWBrioSb7XR5sY1ubiZMwAwRS9dl1kPTXD8WQmGuIk54PO49HNFrKRHhbhQ-FBZmEVII9YaEIvjC1e7jLz7vzr_3h--c10oIbVmY4_LirA48VWERZCRhEAYJIq61_MjnPnm1m57ezMf9XsSDw5I62qM1620mJGEaC4cbI6lZlbJoTxYfIoWpmY21QEQdKlCiBfHqYnd3O4zon3vjo9s6Ytd3v_12LJ2qLMfFOnzw8KmZlVqaLo8fPr29nee21FKGaQAIYaYitmpoQNWFS-_6td_71naSsfLZZiy1Hg7zzeG2CIuUm-s9AFOtd16-Ag7TZt24shBbkGKUoT55fDNsh3lp2pq3ZZgK6PIv_62fKF77UXvviOZph0DdbKf94aC2zEtT65uxDFLHceBC00Zef_35T714f-weTYlinnvv1lQRZO6dGAFis9siUDgIYOHSjrMgnm-myoyQ_lMAx1Iqiwyb0d1ZROeOwGWow7SBSHJdWqHCwympM3lE6THW53N0FGEQFOthlYkLBNRBzJylpnmXmNws1WYO6H0GSHC2hauZMtfsefelZcxVZwvPSiYRS5ipGhf2UCq8wlmECWDcDgBeUInTfRuRSpTCDBAiJbmTAEClRoRU4VJqHZkZCQ0sAY7uBg5up8MGYVBSlTUiXDslRKYrI1POZkIRIny1uocbuK_aVPeVkRQI6uwhRG4KjEBpFcmXcgoBkIWsNWIKV21d-xJMQATMPAhXwTzHA5gHkUiRlM6CB1h4j1VVikSFIAIdmAgMGREMGTkHfsQpX6jNetLZihQMzNuLgRMIITO6sAAB14IsGo6DgEhALH0O9-W4kHAOfhESvkFSapqii8g4bRC5lsqEtRRBAkfA4sJ1M0ih3XZKEGEpRYgqECNy4XEaRIgHIWYZhJjcMSnygIFAx-VobkARAOmeDI-uGuBcuYxyttvMRw2NNrcnH9weF52XvnSbl5astFLS_eTmvga_CSEbIQG0HsbSb5oBryCCwkSB5o5AQlyZUxO7LhIwWOTZQmkl4aT_zCMAm3qkpYtzMQYW0Hq0RlJ3S2-nQ-x6EfBT9P9PZoGykgt4St1gcnRindEDeMQKzqe1dUu0MjizwkqRPgoyCwTi1Ze3xo7CndZTZggCIVpm7_MBEGv_LIP7SZFZs_3htHKIgAACgShnjWtBNjwCnDgH3s8aDWAR5pEz_BUnoZlPCnOwyDQK55AciQIjJ9emdpriewRoeAJD1_JBHvsRIkLVkRDACKDkbzez9ys5db0xmGfiA8xgtQQw5c81SyKaCa211IERaIGZT03OFjP3MAVnooAggqSmd02uKZpbAJTMHoTnMkly6GeRMtFEkCbBLQUghcQhwiK9FIyUSg0iAsq3BiBARcoJhakREQs7uIYhBlNQIAGGh5llzToV5ilxEiYhzhsuI2vY-iDMrWvA6ZwHGAA9EgpHEuPIZ4V_8gufffPlB4PFdpSCRhjEHm7dOkS4-9LTUrJ2KWK1QOT9UAmgVilCCMCc1AcyACIgILfQZmo-L76YBtFx6cNQB0nVGCKQMA5CwzScT-zdNyOhGRIrkgHVsbz7zu3P_sIfvPDc5vNfvHr88PYP_vjp1z640UKbTZ0q78ZhrDXfWPNe3b3IUMZKhEIREr3Pu_u8GatAeNj-9njcH272-89-_KP__n_0S7__e18_v8BNKQCOE59dnTe3w3z0MO9LIeTQw37Zz4dXX7zzL_zID_iTp7_yX_z6dtq88fFXNoS3Hz6ONosqLM2OjXT8whc-9bVvvD0NVRyWY9fWp1KHUjZj2YzTUAoRCAMU5AoyCKAJ6pb1vNqO25ZsO8hUUMiS1zYwSTZGENQ88_bgoGgEiAaFKNxKSQkb5hVR3YhQXYVkrcwye1gOOJgIOT00OApDBGeUMB_LBIhYWJCy4WCVmQAwPHP1IiSMQcFSIHdzAEgwJB83ucpI4JG-iITOh4dGCHNu13M-4wQGjRgUDBkKFSFGB2YuggwsXAiCCOoacwNmAQ90xwAKsNanMhKgCAM6UGjXMDB3c2MQQAwGysFW-nyCav7xBugZ8wQA0HB3w1L-k1_4ZeFAV0yJUC6yOBxDgG-6d9MAIiZXxcCctph2bQrEpsAEjHA2DOBRhThoLIUQSmGISBoqExKuXOZwKMyFBSi9iiEk2p0RpXKdKiFThBBNZYCUYCJw4PpxhjQOxQPGMhBQX9RV01gTGAYZzMtpABPCQPSR-3dKxIcP33_5hXE30YBRInZDDW3zYU-EpRACaYRUISEuNIB_5N7ZvPRAh8KFqCAyMVpzc-v997_xDgsToa0Ch5BaWmvalBmXeQY1ADzbbvdH1d7d0SIIYhqkHW7sOH_-9ZfHiG99510u5cNH191cRM4vzh8-enw4LselBxKxjNPYW5_GlFIVB-hLB6DU2EIqpq1vJnzywcOb_eH2cFhaO87zbre5uZ0Z4XZ_Cyxc-OzqbH489wbbzVYKo4YDPHnSxrNaR2pzS5W7qzJjD3zujRfLtIGI_XyYpmEcJka8unN-uLVxw-l9ExF3Ox5bEqpTFviR-5feAQE5Yjm2sdTLs2k71iowbmS7Kyg8sshQhXgzbcG1BLp6GmM2wwaI3KK7NnPAoJTPmoaHLYuZekSZpssHL5GUQCnDxLWmp88D02Cu_hBQKAVoBnm4DOsQ2QBaTbkRkbhYdMdkASMChGo3d3SArhDu1llWIj56IHgpidVxJuGSvj6MiFDIBA1GVASMWI7z_tg_-8N_WcwcRUA4TcWEREDhQSuyDPo8Sy1oAMhA5q4ISJHhQgAI5O8D1h0izDiAiqSDWE0JvNQCAKYRnAJNR6SuzhnwsJWZmKPwrCeGu3AJ74CQ5-P0-IiUsNW3ksBIBJRSA8gymJC10CD0KEyx1illPu6ljpBmtVDgAEsKTI6RM6xCROTNPULyQeum7igMBFRQjfI3hMxhHaUQkjaTKmv2mZyJreswDBreey8iHZQJSBhQ1FRkCIqsIQG4ditDQQLHCF5j30xSxxHIqzqgUTAGlqGYG5d0i9JYJy7c1fusLDQMg3a3QqrBgVKguTJUDxgKt-YAUFbb8Upx7Wo2FG_GLER4cbGbNmW5XY7qiF2syATRbLMJdh3QGZiQUqz2J5L2KzETCcPS45BK5pzfRsZefC0M5-47V3oBGSHj5IRGHlwtfba-HuYg8rmMnrNqApLanfcGBHaZJuln0Htcz8jPjudIcMLAZrEX_iQcaO16YgJnThKA3HNjAARSELIHBBgRELMl6AeRKLJCQ0Rr5SArl_EsWoM55l7rC_mTglwZnLgwYXACy-flBTCP0QgRyJi55dRLIyRTKxcSp2vN6Ts_aQ0AkZKulcYsS2a9R-JOTyZsyN9HAs4RQhDUIyVliCiCao6Bgahm2UQwd0RAJnMjJLMTb9VXym7vDozJzmpmjBgRZlkHxzgZf7PC7YnWBSeMsPWCk32G1Qec2WjCTOLlJjLcC7O6MhMm7rkDoHcIcyskbg68-pgcTodnCAKwtAowIQPnytJs9XEirDxWyJGBEVDuT1bJQbY-EF3zaLX-yLM_bWpEnEMgJGCk3owpmBmyAlKQMbq7FGakL73-Sl8aESCEenLJzM0AydQ8wCxk9akRoMOaOPq-fyPWDRxGOANjZAI5WAoAmnZ3QA81B0QH2G4GEfEIa6pmhZMO3pgIJGrlyhiG6dM06L_x62-996T95b_8mvX4w6--A851qHd2Mk4iXAqsd6quioUHB-2BBIUIFoW0nUHc3aLf4mHZY8NS6O6drVR_9ME7_5e_89f_3s_8Z--988Hz9y4x-OOvv_zo6eFws0yDdPdpqOm3Ygmk6dGhF64vffIzL_3wF_7Pf_8XPnNx76_88Ct3zy6_d_OUEFAqKKnTZz_30q_-zre--KnnrfKdaWiNwgKt9maOOKtNUsBsgkAC18033jn-xh-9_8fv314_eXTvTru28qkXtn_-i2989P6Vmx5ab84RJqnoK-wegrR05xwlFAQDJDIP4sTqYDgGOgE6c75kmYu5gkOCjj21gohBEWFC0ntjkaT5EkEqht2SNBOkjiItPAW9vRmN6LZaaljRcobGqN2ZmQIJ-diXgUrAKvauld2DHByMpbCTujOVRfsk0q07Q0QvRSBCrQNiEdTw1jWQuimV9PyggzNTqCHQWOrcGnG2DsjdZRTrRiro4aa0QoQZMtLnSmVQ6-tHffLtUJbehTgloF_7-nvXP613tbgqObqT907oQ60APB971g-JuS0mhY4dSs3iIhf3ufVFVUTOzzZzV22tDEwI1bmbWvesA7sBOqi7A9YU-XnPmzYVYUn1iVvEMI5ghsLNfBynR60LQlNlrEyYXuEsFpHQsnRh7h7tuCBTGaR3p_VXgwZhXV-4PEPHp_tZhrIZcJwqaBx6tx5joe1mur09GgohccRYi7LXij_x-c8OhIvpOJWK8fRhtLlP03BzsCJcGTTRpAjkdHm2PbT-4aOnS_fusbQ-jvX29nh556yZf_fd78lYpdTbmz0HWtdpGO59ZByJvODtsmxppCrqepyPHsRSWmuOPndv6kMdEEPVmMvhcCRkLrwcFhR0gKXPCVe9uLPFQgb6kfsvfvnLv-MAt4fDiy9cffDhtbmP0xQGd7a729ub8910fVzmW2VBLPji8xsDP-wXQFxmdTUMm6bx2NpFvbscF0RBCgarY0nO8sWd2F_PakGlUETE2K1zqaYzAXzkwfMDl-uYqcC9B9tHH95qD2wUjkB4Po3XNwcGupkPQrjdbc1UJBfm4W5cWH0pwjiEmea008CQgIF5EoAYxuFwvT8e5nY81mla5gMSXty507sRsOmyzMe-tPCllOre0NmbOrF7uIEUAYzWOgEFGiK2puN223uDcOvBRUwNiIgkvIeDmxm1fOCYKlFSChmLhBsKuyoLAjASQxgS1VJDAZGBmsed__vP_O8-MVVZP7oQALEtDQZGJmI2M6pnfnxEAOCGRL0fl9ZSNc8AQGRqWWpRtVyphxqX9b8iqd0MhMNQta_6EIRwJ-Y0CyGTh6FgrraRELKfTUBM0Vtw8QQ351SyaxAWYXBQcI_gwgRAgBq-Ggwqohriml6nIkkfl2HjYVQ4LIglPALDAUUKgGVI146GVRyDAqjgupqQ1FdLKsaA0InMOwtDOLGUiVe6s4gjWldApCLCjCHAVKmk9jVTI-FJcYeuGu5SCyE6kroV5ioFwkriuwy5FAgjgMLsDu4AYJvNNtemJMwFtCnkuYOwu7FIWB57UAGbRrPGQGqhgda0ZKiKmNHnRTe1mJkMEzOg5og6IqBMtauKiKGhOVgNDHt2poIowmZBCJgeVoBgJBKDAGQ1yxx8IkGTrL_KoiLM11Gxr9oGByJbD8K0YusR11Kx5yCFHD3DRoHAjrOqmhKWk3kKEMAz1f4MmJkD61NrIYcx6z2BVhRbhIdjCgwpyMECjAqjJX4yv5YiDGGd2SNAFg4RwS2AIwL6MzsY5o0HCHAFhCP597fjdEr3kHvSNgIRVX3lWgKaeeVcqhgGR6xx7hXV70FEthaFIk5_y9rLPgmBVzBhZKeW8yzrCTsHUre0hWe-n1bCKRBhhp-YWN0hXCjNYtjz4qCWp-W8cwSB-8qyoZOGrae1NI-rp9sREUc4EZomBxTUgxkIyMEwAtfOHlShOIF9HHxg9ggJ6qaEktZeRjJ0N1B0IqR8XwcQQQSZW3aCHYKBPJwRAijAwwKAAnGQEuCmzlVUDREj83wWEOjgIvnMNQD0piQSDsTsDujr8yy3W8Tktq6XACi6CQlhtuI970zI6IILtJ98402hQm4aNmuPOAGt3CKMMB1nWYVSJyrIhuCrFO2kV1vpVVE4T5SAAG4B5O5ojg7ACMiAQKa63W6y7GgZvxLWiLZfMLDIiIWIo9QCELP6b_zON44y_JWf_sTT7zz9_a9_97l7FxfjBjlARN0EsQibdgcEghp0XJYNU4WCoREG5iRsGKLHudmh9Ithe7GZdG5Pb2-_887--Xsv_-1__p_9xV_6rZcf3ANBhOPFGZ3v7h2VZKigodqkxFihExwIf-tXf_c__83fuXzx6iOX9z79-Zf-j__gH3389U8-ePOVZYGqfdhdHUv_-q89-ZWf_aNf-iff8bv1tS--hvvFuHzhk_fEb6-mzcdeffWffuWPf-uXv7oEvPuB2rbeu9r8jS-9-Nd-8LmL3StHJGZ5et2--84H__if_PLFi8_9Mz_2hdibEKEDZ3qPQD1fEonTpVXhgkSQZALq4MRIRL07AQJj1y5cgNwhBuQe4dqZS0AwckCUUnI_YJFPmAhCIc7anHDiZbLQQsRuFs3aUGvGgSTYwRw8OcZqBuBDKWgsHM0tNdsYWIooWISDIzGpaRVCgkIFA5mwq0VEqQUczJSRhlrdgygUvRYxs4hAZMaUWCMzp5RAWDRMzQDQIIgpwgUAgDUc0ZCFSNS1iKh6hGs4S1Hzwul_ZIDwYfxf_N1_-G__G3_jzKMrIOEw1I3UQ1MhUErTCArRQlYKV5dxGGKx7po0zbEOwNibbka-vmHkaE2vLuuj62iLBqKpI5IQB3Gq2dmJkLspQLgEQIxDAQM0AAhGdANBPi4LCTGQhxUhNS9FmKX1Vko1n4kJEItbRxKmZs5ABgkK9nGQl1-8_9pzdw63x4uraZmPy_62Xx9kHF94_u5-tg0G1YVInl7vP3h0s91tl_1hHKvObSe43HTZlOV4fP-tx09vFyCKtux2kwcMjHJ1cVx6IQbovTU3K1XMeuv64c3hwZ3txZ0di1i0zdnm2DzAD4tOjLeHeP658_vnZ760blCl7lvnWp6_f3W4PiytDdMwus0OSzdAOc6LhZ1vd8d5RqIARyYnnBcdp0EiBKk9PUz3Lz77iTfGQd566-2Lu5fc_PowD3Ukvr28c3F2vhOguTVGUmhFyrTpzTVDurroUAQNdFkiQoTVvCAu-2tt2kAZIy-RgGTmwnicFxFo5m4GQMiyPx6242CuV-e7ZoAIwnjG00O7DYyGjhThzkgQUQsvLTx8HOvTm2Ob-zBwVwswZGAqfnMgxDLUZV6ImCu145zhW0IxCETg7Nu0ZovpvF9uDsCpHYTnXnxh2O6--QdfETQWhqMhc6m1ubFAt87MGJ7IHIgIoj7PgQhMBORZSwtwUwiECGYMVS7FwGXgPjcWjtS6JOACUNUABDJ6Qzxtt0szHOtf-1v_7X_lL_zIY4u3v_c4D8d58DYpxb0BJWGNrD_FcCLxrmnSG6QAIYRRoDsA0ErFkRq2ggjQHBHzrbUObhFAON_g3hWBXY25AphrT3YkBIQbAudgK5ATZpaWQiJR7URcBslCKhC6BTA5AIskBDBzD-GORO5qXZm5LyrjiIzsAAhMZGFMZAiUGR7P4BS4Rx0Hd8WUB6ln7oGwJPChYFF0AgRiSJkrgIUxFsPEM0cgUCklJXMAwzjNhyNAcM2yIgIAF7amMg2pSouAykNDr0RJCYyAzVSr1GVpbsqV0YGYu9s0jckZZKIs1wKAc2QFE5kzrOEevasCXm7q_tglGy8ivdk4MTl59z3oMHBJIWun46FtJqERxrHOxxkI5v0i09CXLljqbuN5VkVycMEVAoMA5uCRhgT3UAzylZOUMnvINqRnnBxPlmAHAzeERHRDhHskTzYQw_J17pnEcSD1QHZCMF1BtB6w9B5_0vcVJ1fuqe37bC0FkfGeU5Vh1QJ4nGbmp8ovmXpgEHI6sDDCAIhWfAhius8s7xS06tAiYfbhJ1EXrj2pOBWiLU4iL4c0Va3_jhUq70h0ilMhInB-OxbI61Da3MM1sGRsP0_kQe7mye1Mq1FEZDfXzJEoTZAptjX0rD130EjY6LNES9rQ_GQeT9w4BAAwkXveqSLfX2lQfSYkSBjPemPjlF2snsAcbOMKOF0TS2boQMjBa6QJw4wYs0cT6EJFXYXB1peE4PojYsxnTrgAd1ViCnBGjMSkAkFeOfNXFSlwoyQkQTClkDkCCRxAQzFSKg5M6yUqFxMEaOEAaG6Jt6JCEZ7XCy6EhGGOTJydY8BSaGWXnfJv5kHSWeRsmg7zsZENVP7c6x8bkTNWR4QpGehqqqrg6Igr3yYtbOie9rDk8Z7k0DlHTj0zPtNEBBC4hXu4G-DKjCW07TgIQQSqKSCgsKaqqfuOynYzbWphogqToXz5K19_8f7Fc5ebp996dP3k8Lk3XypEx-aEtFgUqQWJkBTAu0KAcBkJfuaPf-Ev_fiPoncWmRUogBeDm_b0-smHj9597uql_fZcpmEz8f_3d373Bz_3xtP9_KM_9lknRLVaZRgwKGaLD28PX__WN776la__8n_x28dH81tvP91eXpxPtAF51-M7D-7_8m9-9fpGfvEXf2O__fbRp4XsqtTS_FKe0liPc7N34ys_-wcFrXD9vZ_97Xmg3SsvPP_Se8_t5MXPvX5-b_NjCH_muctmgUU08AjULRRApvGNj7_6xsdf_cb3Pvi1r7__hZfvAVK4AsLA0lwhD9OIImjmCMglRVirIJaBItxVBdAd3Wwso5kTUQsF5AAbpBpGRUZEN7IIsvAAZkpFfQ4lECkiHFG9I5ITpCiag0ZhMAdAQDJXJPJwArbupXAy_gzcIgqTqQegCKmp9uDKdRD1Lizh7uEFiZhMfazFyBHD3LlUd2sR-a8R4q7u4YOU3E8KcldDikzMdmsOlO89DDQMYg41JKQApox0QTC4pUwFXV0IMYKY1QKDDAIV7nzk-b_zd_-D_-3f-WmhM8ZA4vAYua5PqlIdgok8LIKnsRBhEAmSexTmZk6O87GXAS7PN--9f4MefYmBqddiHuikroEU4ROVg5uapee0chYnokeftnUYSjSVQaB3c1P1knf6jCaaZxCciFtrlSUYFcyZSxEzRTAHzLCdQDx3_-ojl-cRMY6FRfe6LL2Pm-00TXPT5di7tQ0X2wxt7uMoBA7Ix-XmB974GCKOEy8Yjz94yoXqxGZrV87Ctcc0bX79q1_7s5__bCmKgGGRNxBkMQcLrMy3--Xp7cEj5tbHOl2dnfXeDPT5y50uOtX6-OETALcgJn58exyJDsuS2183M0MAcA1HMrfefdY-DlO_va3E55uJqrTZizgIf-7NN_c3t7vxSkqRgOPt9eX52X5ezjdbKBXCBWm_9Hlppcq8zMzMYCh83B_c0HqrQ3FlRnJ3CwSAb3_r_R_6U29GV7NogcOW5mXeH463x1ZqLcJzn7nUMF-WhQq3ri89_1w7tuvD4epiROTbpRXh3nxeOrgxIzODQ-sGgGbhqHWqHz6-GbHWimrmi0mlcbNZ-oKIa5Re3YGAAjXKtrq1DAvo3LmWYdyotsjJdIR3f_-tty3s5Vc_9eid7y7zAWoVN7PsGOU73VlEj02GyYnJTYS7Ap4-1xyDCb11dCcRDyPmxP6oOwshkqkRCwhioFvnWsMjQutmR4xO8vzds7_7d_-X967u_eNf_q_-3r_3Dz749juCEMjoTfPbCQT3QBGIRpGIQEuCPmgUql1nd7QwwEAOErIwcgfhMKVTgMfTI47UVZGISKwvlhVgQkJe6RkOTBgJFmSKDKgAwkrhQRJj4PBOiJ7ELsITi70gEmBo81orgIEGBqBweJARloIQNLBHMIqjZ5aXpag1KhOIShnAOmE4IQhpN6mypj7QiRGJNYxZEKBHH2XIYHGSybGWMAfGCNAAlBQYYG9dhqHN3TU8pyPNxk1xdRIkJBYJDCamggi02CxlIGJv6lLGYTANnHiSsS3d0RDRI4AQmQHiOOuwLWKO7ABwmNswjUvrACgbXlSZiUm6QdfuEd2BCpl6g2WEQhgIONYaCJuNHG46jjRrlwVYUJi359Ph2Dyc0IehjOMGgJnX_TRqpBUWmBGCMLN2AUgYBTwQo3cDfGZfBl8p-AaeC5Ds20RJUxugYVD6eVcuLYGfJuYOhg7oQuKBUtjNA7VKcRMNJzoN-__ETeD72oIck-YbaT3Iw8qFxjR8mSMU4JVDKnm6zfNTJM8H1sTFSsNkpLUbsCZrHBEAbG3mZtyFOM-L6Hoi7SD4-gcGADCrOaylzCwfrMaAFHtmjdrdgSnPcwFMp80GE5l5rFjMVU0VhG6BlowftPVHv5YHEMHM46RNCwti9lUxvAbS0DlWy4LTKuMCgJCMOhAGkVlAuBBToKIhZgKIu3UhzlhRMrgSDKrdgdDBBYtmbAqZYeXEYgTlwytPE0TuioTqEeEUBFlqA7Y4mdGCCRGQsyYAvt68FDzciTCpi2k_ZWSAUHMkLEwK5GEIafldyesezoSj11td0t4KQuTEzJ6ehZM_zBEClQnIibms_ReM7oZ5UfQABBB06FSR0P7cGy-XMriFhRViQUS31TKNWASbr0GucPRwcmQhV3cEdVu_ET8pLNa3UrIjeK1EWXRzFs4RRF6WzN3B3WPajJXJLVrXZp1ZIpdXhORWatkOpZl_73sPBfy3f_G3D5tyPt3d79U1Li52NoeSuwOQccougkydSaDgsmiV0IYXj-42PYxYexl4Gp8-fqR9_nCx83G8_8rr5-dn5xe7qNPycPqJP_vTVIcj9puDfvn3_-Actv-Pv_9_uv7efPvkeig7JpaxEBJ4ncbtq6_u8HIayAJnnWNuc9F79XL88P19ade7i1JvPti--jHYL0e8eO1f_6v73_36Jx9M77zzncvLe5Wq7ypc7p58-RuT7JsyLNNmnL64u1wqmjqEu9O6d3RA8O49AF597s7H8LRuEwTHrh1XVban2g8zX-oOadBjNIBT5I_Ac_5F5ppFkBq8YrYDAWFL5eia1Rh3RAQ1GKTkr4aEXS0gLLxySU0ACGCwe4SqFNZmMhB40oeDs9URIIidDAkiSM1FyBEsHAjqWNzdVIHJ1RkZYU3HgeRwPbPIEeDArNYrlXAzDykEay0INPd-DK7goWSUV2UsxVVFVgoTIrXegRGFlt5EGIKcAQOI2RTDlJDK2jyGJAourQ_3n_9f_Tu__qU_9fxf_1NvjEhEpODJAwY3YVqWDoB96SHsGu6ZczYPVNORWbs9etjPzjfnZxVue3iYQViIsGpHwq6GSOomAI4YTIURAgZhVWVhhLDwzba4-TjKzfXxhCmkrp6h03GohKjuuErZghGbtyIYLLr4j3z2lYePr7_y9XfLUD_50tVOuJn2sOO-EfIw7spQiWjRUIhDMwBToGGsm2nS1ip4qD84v7jZL5uhNtVhW548nZGECTajzPvZbcUD_NJv_P4Pf-rNiCgyzM20qzCC0IM7u2mcHLB17dodYpympTUG7O7M0BadWMDj5uYISMDkBKYGY73dHzqQGRBLBiKGWltrS5vnZZnnjsTevM2dC28L3wTfHPu_9rf_5hnV-XjDZCJwfLzvrTePt99-ePe5q8PhOE7TBx8-OhzmMoyPHl8nbpuACg-P2y16yIhIVoAtotbqFoBlYLq-bZPpOI4g9PDRUw9aehumOs8NFixcFu19UUAowCzQlqMLteVYy7kweLi7QqgtzshMeL3fU0EJXvbLmNicWXdTTZlmhE9TBSCJaEpEUbhQwdt2YBHCaM0cfGmtdy0UiN7asZTCwr0bYel9JoA6DMtx__Y3_7DU4f7H3nz7a1_hUgpL75Z0eDfDiGE7ZTEV1KBUN0cIsEbCboa8Si1cOzCbGyGfMB1hqpC6VgdH4FrdnURQCMcSIA8ePP8__h_99540_Z_8K__zYHz0wdOdJNA818kR1jvVQkJ9mctQoCkm4p0wOyVc0BpaWH5yRoCrJdkXKdaBVcZ1HPK2zzlQ1M6UgiIHwvB0CTvjijAnQuuNZOpqtRbwFdYYDiLkFgFQhmoeTKRqtRTwCAoIqNMgQm0xEkEA18hjGjJFVy4rF5lyNilFW6dSwA2RPEJYPDQsiJEEwdcxZwAmVIeQzBSQmEWtMxMSDnWr0ChgGkZNs6gIuIuw9V7K6GaMaH1BFuSglJFSwkMTeJJ_GnjXKBIKUEBqCXBgl1qJsRAilObYZhNCD1gA0QyE5rkXESrFeq9jVXdGyvVo6y6lHo9Ld7j2mZg0TAwgovB0ODTeMlg8vmkvXpxf3yoAzM2HgRTi-vF8dW8XEdvN5rgcK_A4jqUIETOjWzpbU06L69EIkwqzOovzHEsBjOSEZikJCEQMDaDv498TY_8sdE4IAM5A6XVK6A0zOZGDFSoGMCI6hlZcggmxq0NWfRwc_8QuAE_OXzz9R7SAnFOfZMCAHh4IHgpA7uqxwvsDFCPC0awLCSZALr-LHLTSeoFwiLxomK4en8RTunt-zEfibBEiAGnd72BqEgJOp3k8CYmTIboCLU87DIxISSesElyIjOQHPTOhZd57zf4gwPojJYqwLCxAhJkRsQcGWHgQk1onZD85NgjX-ToCUqCpc7bQCd2ciTyTVhgQaK6eJNEMdoUJZalR1IwRHSAcCIOZHYKCNWwtpbtBoNn3i7-euS9ANyeh9X5CBJDkTQIKCnTLmjh7uLojia3tEihEYJH6ZkZUWNOGFm6mSBwQlEc0BMQTrCkg8SABcPQeCIDByBRIzOFGAcEnnXQEMhSL1x5cDSFc6HtP5v2iFk6MqlmEC2KxUBQYB_qRl1_HQDKrRbq6EIdDkJuZg3NwOhNqKalsVXUz6xbu4Gu8C0ydiCLwWe0pEBwh3ABW6kLSpCgAIUioRQgLegyEQunKQDedpHZ015x4aV-WqMyMh8P8vsE7t8d_-rWv__f_xZ-8OWpBQTYAUHBiWhYlZndHKowgLGY6ctlcbaY6PoSnBfTf_Xf__uPl6IaoIExK8G_-T_-NQ112m-GdRzf9fd5sJwG7ue3nZ3E4LMNWHLgygALiZnd2xVwKJCJmCmTnol7m23HvTam6D44v_cXPvviXfvi5X_qdD_7h__XpF1-CT_7A9mu__kvvPx0_9le_9Pitr9x_4ezNi83f_PN_5p3W_stf_c577xy_8Z_9YXz4wSe--MKbP_axv_d_-53__ee_GIVIMYjSsACrFSS7UZIJSFdPyB0QQvjJ3doFJADCPCcRQKTmTGn0DkZCxq6a99Q43U8ZKdyBAyGICCEaGQKQhROEEKxSPUCiIFT3iCgkCsZYHNXcGCkSogWkCjJIpnDNQjDBdu4UcwCYiRQ3FGIFU-8jVzOjYoGY6cGsHDNSUseZydRSdMEi5DFbG6WqKVV0RTcTEgBAdjJQDwA0bwNPCzQ0ZCLVxiGBiuaE2MJLqTmdYOHeLLvS67ueMd8L2i0IIKCWYupSippNu_rHf_z4f_bVf_xv_av_Ijw-VCQsSAED4x77w8PhatgG5qPUcoPXHNaCFeO0G57c7OdFCWmc-OnNsaQpwLEOAhoGLRwcjAgV_GRphL7SF7zWkRCZ2LuHxzQOh-PMxB21VElKspnB6WEbboTUlmOlEt7djz_2mY9_9N7le2V8_OHTNz_z0mWtS9Olzb2pOxKUOhIjABV3U4txc7a0Jbr3w347cDm_uH369JOvvGLhHz5-emd31sI347TfW93IIHKzLMduXa0QgwZuxndvbx5stixCgu997-lmNyJQKeNYCwMf59tEFF_fXGPgoS3hxgzIsrSWX7XZDfv9vKnDk0dPt8_du7w4--57j8Ji2gzt6dHV9l3b0p8sT4UrcRBRszYM3Nq8hOHx8K_9S3_twThat8dLv1nmm5v5MCuReFs--7nXrp8eCODp9eH6dhmGclyO02aYDz0hGGXiWtgsCKCrUyTMoqi1RGs8ub7FafRDq4UAcT_PQNzVMDAI9vtrGYYVJoixHJbnX_uoHRcRefLk8YPnrlqL3vpyXIZxKEOF43yN1FoXQELo1t2cAMEjWbHLoe3OdsfDLIXGWpd5Xnp35mwPBnp4BwNX4yLQu5t378iFEIjRvY_TcLw5AoZwFYLWjm_90Vdfef2Tb33zDy2QiHiobTkScbZoqJZK5bjviIDEkR8UaACgauSBRNaNKMw9z-fmzgHEAgEsRbUzIxRi8ADqqncuzqWU_-H_4L_1qU8__7f_1X_T9tczS2GFuUlEeFtHFOHdFDCYhcDdNIgCh8EWHwZx1QXReCWdW2sohCTr0cuBEIOpewAk_AtNVYSyjuhuRIQiAAFFwoyYACCXaOHOdUKQmr3mFMQGqoKBATERuwWLRHgpJcXAa-8hUWckS1vGcZBInjrr3LjUrFEDIYuYOiFCESSCUtCDkSMcML8QHJAKEYaZCXPOeM0CiJkFEQAzqcCLL8Lc1agEESKnyDfcXcqQUityEBEHBg9iAgtiZmYCECRrTUQQgwSBBGD1k3ERB_QA7-EDDRWXfZhDqFERVzjOy8jELO5wc73fbDYRYOrAQOm-RGzaumnrjlwqV9fWlr7bDuh-MZ4d52MQOfrTxaA4haurGVJYJXz8-HazHVBcZ6sUyGs4BDJh4WAe4KmxIyAwNUYMCI1gRCQIS3ZeQIQwIUJWakgEADKlEJAJPA5EKaxqlTkT7yuX8dT9JQQhFmKxCNWuXc43F8abOtx488x8rMhKOA3qn_WTYYXaJ6AAs4KwsnuAHQKSoo0nRChBEi3dTLOPCwbIqTROAU-EAfFKl0_Y6FquhUAHIGCixGol2cfDPTDtgyukKNazPRMmOMbcU_6wwk8zxZ_s1DWrhKdAjhOiQcb0czkAQQinkrOddAGUZ_lA8JTsUgb-XLNA6kwUEbzajsk9LKwSK1iSyz0cidUMAbsZMqnb6k1e_0kYAM3awEUtAD1hO2kbSNYGYqJk816ehJwIDGJyz7ZurFYGiHXsiZAElQjwNIhEaD401p9yEFHrLYu5EZCdBALsbrAqyrOwjshMgN2jgSOCerBk5CzvAontD7X0Wp_WVuZrY9kJYSUekR0-98orL15ujodFhOemi6orECIjERMxmKmw1MF_-OOvF3PrHZnMHAyAAhk0Ua8RigqQVagQQg7mQosjrssAy-s1JnMXwSKEKCABrGvDJXdcHuCWF_MT8HZtsWPv3RE8ECirEShJVi647IOJzM015nb7R2-99flPvvTB42OtYwhDrUHEZgFxfh4MbgMp2aOH8_7m9tsfvv3o-ua9D773zlsPP_zDby7L_M2H10IQIgjUlqY38w3dBNjtBZxBxbtWZNZ5Ob-sInXDhHUAGAJg2g5hWOuWYCi87PfmfGfBi-ni4pVP33_prLx4DzZXA_H24oXt8uR2wM2P_-DZy18afu7_8HO_-gvf9qOX0T78yq_cPJpwuv9vaf3IA2bq7339w8tz-uxrV4fb5a3vfK_9gv2v__rnCzMLWHg4uBogJD-LicjB3KhQBKLkgMMFkJjMPYIRMNDRUzICwTk0R8v9jrkwmmPkcSaAUv6J0NSnYWrWiCRL2635UIiHaOpBaKoEBAjqxsiBhKmdAe5uPYwCT3oYBAQWcncpks8ddwvCIMAcFUgxCCAIRCYaY3IKtwhDJgz1JJ6xIEaUxBCb5WMyECxaqpHiFIhDcgkCDAfQbqc6c0xlu_QGzIt2DqpAYQ5Es3UCZiSlcLcUYqDEGlQo5GHueXSOQiWfPEDsFBbGiKpt7_ECX_5v_p3_9E9_4bX_xpsfCTMiqpXpYOcogOBdyyhmVliApbCaOSF0NUKste4PbbsbxZEraVcR7G6FqpJVJCO0yDdlUCAKmQUTMlc06-rTwOHm4Yd5LsPAym6pqoRwXHTZjCMS1qFootW6SykRTsSG_PqDy7kBFfjIx-5V5Hnp3fR4WNbLPPPluHv_9vr60WMSWtTQdVm0tZ5YKbP-hc-_-dxu-s67j4ZCm2mwfeewu5e7udvxuDx8dDsMXIrs93tEHoT-7f_3f_iv_8v_3VLKxWb32kcfHFs_NMMwXdqhRc5el6VDCpEiSqndZlPt87IZh7OLs_3heOtgrS8z1Fp22_Hy8sxuDou2XS0BAWN5EnA8HDdnAsi318fdbnu7PxDBNNZz1vt3rhjisL_1trSw69ujBgLR9mxLgUv44Thr2PnZ5vbmend29vj6GgI-9tqLc9PvfPv9cRyPh6Oa7w83Z9tzNz8e9o5IgUPlb3733eljL3Mpx2Vx5h5gZgyEAGp-tjszcA3StrjFtNsMQznOC6mr4KGZdhuGsU5TLdwh2AJgMdMENNWB3cn2y1AYAFB42o6wkmkYyT2Ah7oc53EcUPB4O8sgK---zwmwHUSs9xACJO0pi4TwjkjHubHwbiPvvPXNV1777Dvf-ZqvU0phYvV8YQQhUbBacCl6UBRyABQOUyAOt-CIMC6ClDSOtbKMQeHOxAAI5nkgGMsUvd27f-_NN177D_6fP_fBO2_te4_aK6ITCSRVntBMASJUiTvG4KqlFDMD92FTMbIUDRkHQjdK8lcGFNaGYhI1JdDAwz2Y2M1B2JpyHcyMAhEppwcrM5Io1nkcIIG7a1LIU-YjHKlYDA_HUOVaMCAtUgiByBFu5rWIsIQbEFGCHik5pOSBTMXMpu2u7w8iYpbLCiJm6wHCCFGHuswdgajkRyh6AIsAurWZuES4u5damUYjJ4TNbgpXqYOZeUSptZuy5Ie9hwcQkwQCuYZMpZThdv-0bLaBjsSWV69STJ1rce1eVry8AwqRzmpIh6MDASEts_lyZGZHQQpzD4XejSUz-bQc27IdtKsqtd6ZuDczPzDTwOyuBPh0OWxK6aZNbTvYcrswwrCtsyu3MAze0NPr-ex8Aubj3Fl4GqlOFQPNPdRFKC232adkwgyxnQxha9dz_S_IIYdOCGapAw7hnABRdmUhvAglcouJALwwrzT3cPPQjiDG5sNYQPmF8ytv5AFycYq3M0D6qf9EDijDLgSe-rh18bCuIDzZDZgdlTT7prAAE_7kxEAhFg6nM1XOqsPXI_8p9-6xNk-diCMMaSV-mhkReMTJdgyI4InETLmwZ9wGIYIJPZsS2ZTPU22c1Mt5gs_dQqaMAIEw3JOoA54N2vXAn5_yFu4AnIvBhDTburxOVXFGrnitNAMycrBFgK_XHUyZRmAm4gA94dlErHaKpYAPXNxDEC04PIghPFiy-Y3uhlm9jtWtGxQnZignVTbJNoDIjB7BSG4qxAbr8gxXrwQGhKkTUzcX4f8fU38edOuW3_Vhv2mt59l7v8OZzz13nvr2qO5WS0KtETQQwBBiYjvYJDFRUhgHx1VxJXZBJbgIoRISKKcSxwRXcAKOC5PERWwiJCTEUFZaEgiJ7pZa6uH27TtPZ3yHvffzrPUb8sfv2efqVt26t874vns_e63f8P1-vu4hQEbhlr6eKCzqvSD3sHQAR4BBMHFusUvh5cnwAAhm1sQSk2MESDL8wsOImCIQUV2Fia1_4qknn71x7GpjlffPLnROWwUiIdZc9AARAcNYagEMh0xFYACuJXFDJKSZLO5ZdJlrRISpJcsjDtaWZSvikWcjImWaQYZCi_BhxwWC4BjE4I562Agzo5kHgUiJ1pIQDelv6MY8iJQIbDYxld35hU169amnrj99VZtDsbMLfbDbfuPVV19_8-4vffmr-sE7b7_99lCH0Y9WNZBCw4YyaCZKqI5cZ23W5ukianWytvvgQdmIhRVha7rvUtdHRpuhn_AQx6dHvF6xlOOTisJXrt04vX3zxok98dy106snxWAADY0KYEFBODcdKmyPjkwFttujfvH7_-hP_L3_28__0O994dVX33zvgw9-_7_5-6_X9Xe-9vb6yuYHvviKz7OrZ1-s4D5PggN6dEuZYQBDIOHvcIYU5uyeCRnQEMlNCTzhMbk6JCHImTwAUhKqAD2qFA1FBD4YixCx0NB0riK7th9qMcs-P8pAENDUiAXVhDmFXknHJjvo-xkb9soSDo6Gy6ePcsjCDoomSQoNAAMHYMKAKCjNOyCFBghERC3i6hBBGZor2aQD48FGxLlKIu0aCBVKQ8vnxREhwBwcIDcY5srIGIRICFFF0EkiDCD36UAMrpzpIgZp8bcIIEwYV0BIyeOPiJSA0mwjgGERQMSoZqXil_7Z1378lTsjFcLoquNQOlitxZBCQy2EkdK-3DqiqYWUerQZPpz2U5OxlLHb3tp6PU5m86wci0ZSmMYql5e2nZRIcpigvRVmMxck9QCHo9V66rqq9XLaJ1vV3FdlqIMkSbqrEqHllYABCIMMVMR3M4M_fevq1Kzt-m4_qwcj7uceoHfvXz48uzg6WheuEKhmpjq3frwZoNvzzz1zVerZ2f7uo8uuO-v65I2bp2W9nxtYmMiNkzortB7MdRwHnNud6ze_8-G9Z65cMeybcVWLSNF7D84AR0Sep2kYJAj6ZR9HeXgZm0F8pqm1o3E8O79sGsdHx4-m2RFGLqFeDG9du9JmBYi-369W9WJq3YyYWu_jgOPR2Oc0M5RHjx79j_47vx-NTRtRXL-2_tZ33jdzYl54eQ6oMbV5vT66e-_esBrmNlv37_3cK3c_fLA9nwrR3HtEWPBmc7rkXGdMloM5bS_nFlDc0NHJgdG6i7ChjUPZT70O4zRN6_XKPW7fON7vdmfnl7WKmr333t1xNY5US2GE0KbjOBKf1SoXl3uIYKL9fj_NrQ51vRp30zzNXdUwPWBEJNy6Si1hgcEAhkz73a4MpevsHogcGJTW03XhFVhruLBOLAeU037Pg7z-2m8-9_xLd99_r88zsBIzKLgpcalCc4CbSxkd9hLg6oSEQEn4oQRiInlAmp4BcxzAqq1wAWYHkFIssIzjxdnFv_ZHfmCD_A__4a92BQYMF50n8BDMPXJm1haBMNAODu4QAmEBiIYGhDQMpg0BeteMzmKSCGPClAxwjkvJ0TElN4QcgYgMA3t4-pQzh1RImAeLvrQvjIzLjDyQzIBQAjunKMesSFnmr2rI4mZEyEXMLKGE6ETMQZB4Ou2NCyOGm7MwCwGwqZahQjgWckSRCm4gEhEk5MhlQBTp2pAqhDJTAFJSVYUtMOkBKGEaLpTtkLlTIVqEAkgsAd1BCCBaMDII1qEgQO_zuFoDhLZGZaBaIJyFq1Qm9sA-Nalj793VTlYDMV9uJ0Nzo-4tAqlU5NLcaqYfCgShmQNQbz4MtWuoOTN2DRSKsFILmHUHhCiMczcRUXVhUvcMSu-7qTIJqiPy3Ffrup32i5Xbs_AgynQ0ZnejBE1mjossOfZAlA45NwOEnO8CgLvhUqSCJzAzU7pwsdCCLxL4QsvM6RDXZREuJM5Y1VDKo4uzT7zw8T65cDWAQUYAh7aQEvEx3TNz3XBx5AJiqvbdHDnr3WQRobsnfmK5kXJhoBGhuVMTSHZ2wCE0KoHzbhmE4KmYyWBZDF0WiIiJyEh6VzwW1oYn5i8e7yjwgO4m8AxwcVu-icVEC2C-9CCH7Qan1hwiiD5qIiCIUDVfPspgawjPxwOW3cICMcKEYnq2cZESkTylkVChUzADehghZVQYE6ilRz-yE4AkkhJ5hAi5uRCap6EuCJAYKNCcAiDA0yivoQQUAehgafeGQAanSEYWRFAgcVFXpgKRXnNPLCgGCGAu0d3DM2GNONWGCBTuFBRBhMAE4OTgao7kjGjhgoRItrBNF4hZN0cLoqQwhVkvdQgHFnYMCiKKFZXnnrwOBmHu5BC-Wss-0NXUfGlmMJiojvLkteMUdkDCGQEBgtEdos1qnhsy0GZBoRpLqxrYuwozIDKyhQoxcABAkdJUCdJzTIFu5on1b2px2AekFlmELYIJwEKYwDPZAACDD2e0Y0gZGyK0PodTj__k__rXvvGdt2XFb7zxVj93MqqFKIzQLZyg3xHhwPDL2thgMMM9zKux4MntSsaTn0irt6796J_8V__6n_hfvPCDX_iRP_pTr3_p10-unJw9ePDOa-_cePLm0Y3TGx97Lvbz9_6eT-LU1sOGzBA9Jg8182BCYhIjDyOsUSkMGSjC1uOA4GMFG0JBrg24If7T_-t_iVb0u-l7_syf-j9e_trXvvCjv-vjP_oJCJzP9qpKlbujWpQqhAMR-YKGMvDcV4K7L4nUGUxuwYiLS5vZgd0D0xbvmT0eGJ7kJQFWcAI0JHVH5AAI9BwMIKFCK4Wt-7pWiChlSGcYwuJKMsz9cB57AUCqRoDEhE4BsJLRzQixawQDs4QbUjAJIoJGZu8IkztYmtoDHKwwY4RTovXAwkkQKEMJMdQLcXcPikBY0bDXGRF7UyHpZjOpYwSQJSuBUBA1HIFSH0VQzFtaWgjICWa3QAgEgWrW8aCdJEbXnvkuskwoGGbNjzsJDlEOJ3VlRrWeeSga4T2OVqs__zd_5i_-8X_RHTDQVVcitch4utqezwjgqolqIuJxGO4_vNSIo5PN0dH67HxfjtfjyPsJ3LSK9O4YSpWt-YvP3Dghe3S5euPhDoTnZqreCAOgm1_u50IY4aEWTBYmwpvN-OjRxCxUGQm8WQbzLd5oKh5G4U_euqkaRUB6eI_oZmHzPEupquoA3TQQNsdrR9xPPTJXkng9DLWUp5648eTVo_PL3jXOL7fDWM72uyt9XjOMg5xeuf6Nb70lWC-mvUdU4QhsCKsy_sKX_tkf_4M_sSoCrpeXlw8enXOpgDTPjRDn1q9fOx0q72c7Xhfm2IzjZhgFYb9zNdVd3Do6fve9d_mo6n7azdPeHAnFoxJZ1yrSmxJxb6F93lzb7OcYVzXHPFeuHUGbe9jc--XZJRLt940Y6rB2RlWfdvPR0fHFxcWV06N5P53df_g9n3nl4Yf31nX94Xze55mIwtkTveBapLi3MChDIYK2m_bbCerAEIIDoEkZDEBkcPMi1FrLURMSVubtdvrw0fkrLz-138_n988MidZ4MtR9c7e4d-9eLbV3KyxjlYvtxXpcafehFhZEwHE1trlliqVUyuSXTBp215TwUkEqHAjIROGEpG7j0ao3rUOZwtw6o7h2Juq9c5Vxta40fee1b9x68hlt_ezD97trqVWE99O0u2ilCo1Da71IYQ9nD3NmBkZXY-E0tAIIIqmryIjEHoHEjkBhCJIXoDPfvnHjx370-37rt1_94NGHGi2YELjU0i5nWeaLGVzanIVdNWtXN-RKFurBROLaCKjP01DEvCdqJsU_AbGL7YqOzJ0Xi25QACBGOuAhTCMckKA3lSKmjtghpyfIJEWCHTQnj8xIDERVWyckjwXXjYyRyQMBruHeMyQBpQKiuRMREOjcWEpre2GRgg4pMEc3QKFwJJZEUjJBTmeT41irqIcHCGP0SKUKYpAUD0IIFnYIxpCBIQAZF2suMSARC_mid-cqoFA2Eu64bDQAeWHPExfHAFCURQMN6LWM824GUxZ29a7GxCg1ms-9kSBhbZMVKYzkasTMxKo-SGnqAdy7lyFKHaa5cS2zWil0cbE9PTky7YjSzanS3DUCrHlgQ3CMGFgIikSZbDLoigXMKxGQK3afdlywFGKooc4ELQwBU9sN5unrznEwUqShVCPhsECpWqEFlpJbAoDwvKw4cfVpj4BDf5DdMgqxA0lEOSnbi_bMnee1AUM1J6aFIeOgHAIERhC2aNQzlwwwIhRxqUADjVHcl6ksoC9BXY_ZoJQ-oQ6E5kpLBGdqjBw_4ooudEvX_Az8Tv0_IGV55YTL1j6tDpHhYJBs_gTL51AbPT9N6eIAAkrT5fIFZt5wAOS0zdyJGBHCDBZGPaSfEQgZAZGWOuB3pPwGICJ7OGX7knrZ9MoGAoKaZmy2uiNKFqypI1CEXJgIkSMQkIdHdk1LCkjqmCDCc9nChG7gCkCxbD8gg7Qg7XyZGIMoviC2MJOBM1E7464c0b0TLgKuFAkl_8gcHoN6gNDMmICQIZVFsaROYGBPqCdDhANwZqVFKC-B1Cm-IgkPAs1zhqDUIZWd5oac8eX2sdtPcnBYF6GmHsi72YqwIxRmQyRHwJCxDgSnq9HNhQkohy4Lp6p3MzcKNAONsIAM5fFuQQQQTOwBagZIKJzBe0TkGEhJnKT0TeXGzXzhPgFAM8sk52wDAtmwkyUqCNMhEKEIZugy8tkH06OHl9OT67HtJ9F_9vf-8Qf3-_HRaIaVkGEunVuYOlU58qFuhqEe1Zu3T0_u3Ln28Rc--9RTTzxx_Bu__W49vdr384pgVdAU1jDOwav1tU8-cWP1ylObW08MQviTPI7y6OJiWK1GlqMdzntCbRCYFN9SCrgWKmGOwAy5gMmHOBeCiCgd1THMGup07eSkb7Vd8JPPndy-cvTUx593rzYhCJEbAoa6kEQ4dofkTqFhBDNZN-bMnmY4ZEKJkIZHpKUqPXeQLHsBaIiMYGYVJV98DwWHTIzr7gWJELoHRmQMXAMLNWJyiHAHdoIIAo4lyZoAm6qF59Y746jQ3d3y82nuoTaUiohGHpaIDXA1KCSVTY2ZI9I2wIkOiUj7f4ZyLFULAAiyQ8iAFpgxrpnZ0G0GAvAQZlcvLArOyAEZ1rVMTJLKogkFhqbRmQQD3ULVhKmjMREBCAoANFWATMVjtWBmBOQqpprQTA9vqpW4CE2qCGhCRFyEzbzUQowUdOv46vmRXd_XQBkD9n0frW3NZF2gee8dDUSYiQLLZr3aTvM8zUebtSuo-Vjl6GiYZlUD14bMHP7K8zch8LzB1ONoXXYtUsfASCxMTMEAiJWKqiGzqSNyBKc6MfWkAEBOQI6ERqxzY0JkquAESKNIi_3cGENNpZb9PGvGCMqwnXaq0c0SqzasR1ATipunR1c2q9fe-vDkylFyrQPxcmqqTYYjYdrv9rLii4udWo-I1h2wE8JOrZTh537p1_7QD3--lHLzyum-24Pz8_Vmzcj3Hz5MtPa6DpVjv2sQNtaivVnEyZWT97_9-unVa9NuO1D51He91M6n7b3dSEz7ODpe3blz8u1X7-7m3bAiGVfz1KzDow8v61j3NpWBz863D-49uH3j6q0rR1_56htcVwBwerIiFjV4eLnbzk0Kz20-3mx2bf_g3qPPfPKly932xRee_sVf_e157iEYAMzeXd05mlUuQeKm2kzJGOAbr7350kvPn6xGcyOA1vT4eBg25fLRrjUNkYDAoDZPx8fH__zXf-P29SsXF1tmLoxhjWXTkVtvrnq03szehpNNm3qb91dPjh89ulgPYxnkcrtHRBaiRsyy3e1KMLgToCPst5PUUoZVv9yigcUshW3uAUYoRAWcEUynVpm7Oxe2yahIhegeFw8v6lhKqffefXcY6p3nX7n31qvmprNGYBnEu6o2RArkIFU1Qjygx9E9YZxB7CwllJIbSJn8lb4WLLRaMw8s_t2f_8Tx9fHv_r--hIzd3boSdXfQZsLMczeGYJGsnEqtERAgTBKuSBwWCOqmYMGMsqBZElkCjABOIx4jwlCqajcHIiTGBccHHKaZLGymZSzhziVLQzQgXKaegRRuGQ5EEYCIpQ7WGzESS-K3iMhVs6TxFBIjdw-ughGmJljqMKhpWY3WVEhcDRxBCIhQGDQCIgGadRjCXdWgZA4zQ0QHB0BBQaQWaSVceI8ibAAaUZgxgIBQUlw4ZD5YznVqXZsrDBgGKZHJZADVXkgwqTRNsTKRWDfeDIBODKvNUQAIcK1sGlRBM4QJGREZGCnabi-8MAvmqW2O15PqvG-lFkRoMxu5aSQuwoPqevC0hiICwMXFvN4AJRyx2yBcIOZdjxEGGHqAmgXNBdw9Qhyw-jQDwFhos0kfBBNg7-YeJMAsaQgWCU-DqmfNCrE4QZUAuylzWRgpC7onltAlCEwXmifzEyFC3ZEIC1NTId4Mw5pPRhJw8QPXJgmcyos6IluPxwTQNJIgxZLwwjnh8wNfM2vH4CX8DoFyJR7MHOBZQiNAzlyXEh_RTeHwczmmW9K9YjGVLlXWoXzmDGgJf4zoT9E2IHiW-R64COEzOG0ZBKbo-AA1yqfGHDDtnuGBzL44fx8HoaU6DgOcCdWWcOXshSCW8Mu0EBCTuQWgJVGe8JC_TOhJFkEPB4KIIKYFn5rxXcEBCadyRlpCFiKS8sosYU6IgejJWsbIYj3fqfw6UBZyLgS2ZECn9DkcgS2cAy0CCQ_ZagCOqUNMWGE4RnZUhBBhYABJFQNawEbRYxYaspxycBZEBHMIIgwPDyY21cgcsMSpYuYVcGLKEBGYh8JPPnGVewsEINIIJ16Iht1LLZoefAJX3QzDGkGQzA08gBmW8GECUAAMJA1zRCc0T3c9HIBMy2wl0y8AidBo-UFYQKCJBQtwD7UuIrjkA6B6EAJTIBOEV8KEdQG4YnhEYSowlNkrj__2v_XnL-rx937_p3dBA61vf-6JT3z6iz_1R37y_dcenl5fUaGrt052euYd512v4ERkXedtu5itFD4a1yD4td9--3Pff8v2DY95N--gxa0nrwzr03DFed5cPTm9esXdKiMTbU6iVDk9WgsIVVzm2RnBjVByugMEAOYR5mmgyoRvByejIS0ysv7pX_rWv_wvfD6QzOsAcHrj-OqNa7QWYo5wgigMagFghbPPxTDDpV9FKeLuiGHhhRhRILynCiuCMq9jSbdgsJhhsVgVEgQAJM5oawxgwoghuJkFBcOSqGnuA9dObYnHEA61jBpP1xBjdFMmEqJuVoh0OSLYQUkkMx24crMujAwUBMIY7lz5AEMnCLAkwwIE0IpKD1NVoszqTps-FiQLF8Jc6EVA04Q7kia7DJewa4AQAHfjfCMSRoiB5hEuTMHg6rUM09SIRL0NhT0ADQ2MEQYoW52BkJyS0FWGGu4Q0VojIq6SI8pMbXGwWorOyo6BwMJByZpDC7Ay_NW_-gv_3r_-BwVCzSFw6mZT3z3cDQOfrgeMvA0APdbj4BA2qZuPlaemGWjDDTooAXTtz9y8OiLu3ae57Xov4wDTTEgRHYC1d3AODSplWBVUB4BaBICmqQNE5iAJUKmlm5ovO15mooIE_szTt8FMrXeLqfcOwcjHm3G1Wknh1vS19x7UYQgym5uaM4UIgfBTN05ffPLGG289iEAd6v5in6j2i4tLB0bEufXebd7ND3eXq3F9vp2YWa0FUDd3i9cuPnx4trt19WRv8eSt64Du2oc6rFbDug6lkBgKx_WjlYEjwsl69fVvvfXCc3Lz1vXLy_3pasPE88X28ny_3-6PTo8Q4erJ0dTb1Wtr3JV-trPm817VdKi1tVkQ3G21xs36Sh3Gi8vp9MrNfWt93tXVIIIP7m-1NUHZznt3d9VVGX7Pj_3gg3v3To7Xv_qVb57tJ2KeL5pTIHPF2t1vXr263U-Zc9NUCRFYmum2t9WqDrX2WWsVLGRzB8IgNLWhCLiPhS_Pzz_1iZfn_Q6R7t69vz5eO9DFfn7nw4cCQORmEITv3H04DPWFV55-8zsfcCk3r568c_fig_cfjqsytwYGHjYMAhG7sy0zolAZaldHdBEB8ja3Moyh3tXN1R2ttUimFgnkR28o4R5EUgjHig6gXYjafnf_vbeOT64cX3_iw3fe2G0vXS2V1do7MelOyzhAgKFiMIgRY5j7wvpbKEBgAEwEHBLIBaCcXrs9FDwe65_84_-67uxL_-iX520DdMyJI5KMI5fjG7AUMrAkTQYQi-oeuYTn3xEYlkBtVA0KcMdUKYlQCqoXlS4jUpGyeFGzD6AgITcHB-Y8-DDynGdGQJKSB1ne38wlBz-A5JpDfUyrHDEDkkcUETeXWlPmkdweYs7ahxBJOGKp8stQWZiImDncaylEVMuIJIhQiyBy2rPSFUXCiDjw4lgVplqLqROWiGwGBMKHccXCADDUKkTZGzAzBoSZCBMn34ZLFSY0d2YyU2EGdxL2jg6xHqs3G8YVcKBI9j_etY4DEnx494KY06HYWqMl1pSQAlmCKBC6ZjRyUJHFXYik6jKUDG2JUPAgYHVrvV85OdrPjYWQqJsTAQubx9wnzEkVw8DUuzrQvjdk2c97UDeLiNBuRKLeMcA9BilqIUxp3VhCrdKr9hgjmeVzLGbdpXZnIkLP4_-gss9iWtMwSxQegxTDOL-cTk6vQkdwDoCFZpnVPgaYQgQLIgZQIERuJIAACXzJ38x0XwRwIk_MNi75c3Ag8xgimOfSGw-0q2Wrg0mRgGCiNLSmcQUfi49wUbSm8snBwXMQBxEAHoQMS2kaSwedv_ij6OLlR5Z2DQ9iqWwoljygLGHSXcDZcSzULID059myGwk1J2ILONgMPNX_j1Xm_ji8GcIiaTPBxIGYil9YJPvhHoe6OtKkQIAAFBjgmFm_yabHQxLCISCZNC9tJEvWqUeYM6EFpFfpsJHIRinpQin9DMfl-z7ktqGaMdX85ZkUgcsrEISLszf_JIsgEoBgFAQgYgL0SPET5LAcKcCWHQUJIYJ3ZWLPUCdmZiw1njhaP3m69u4o0a1Ns57vZ2IyVykFKddIHt6vbVbPXj8VJkBTy6aAAFEYPWKBjgN6gCH4shaBADDL7hQshVFL7xe5-2CiZgYBKX8iwsx5SA3Gob3EoMXnHq5CKIjEpGRBXoCKFJbhS7_wW3_hP_gPfvqnf-aDNx79rf_wzzz18nN__2d-eTXi089_7Ad-1-e_-_MvWPfW9ez88sMP7n_zG29_85333nj7_t0PL157-9G3795_0GIcx0DTeWKmV984e_75Gx--fe_qEfVdR8KV1F_4u__g5Zeefv75l-9--OGTz9-2XR9XFTyaamFhZDAXwUwIBEiabQI2IjBw2awCcv4HlsMFHImQ6OJMv_vzT-QqRIZCrf2Dn_3lq9eOXnruKTAF8I-wXfmRZwEIypE_ZTsAhAQe2T9mH5vNJObiLxwXaCciEDCGBRImOy_ZYwHBSBAUDkKYArBChQ6o4YEQiAGCiM3zSgoSDoYICOvMBI7mWLG4W44BhBgQ1V0ACzIAMDMYBUaukQkiAygEc5gTxBS50HZQdHQnIaRIH10mjhQqzeaRSnezCAQoVBK1ko2luQORByClmZ4jQogdHClcnRndPJzNkvsBzOQOjIQR4E7MIty7MbKCg8MoQhiE-UcRECIiBaJjEXEMQiKiMEgauLkXInDHjM0mFpRS5NqTt77-7dc3g9RxEKSuTVZsTR197rYaRy4EmUgYEHEIykQ0NWImRLdQMwCYXF-5c8PVt9Nk5mqhij3C1GyZcqKaqZuZCQsRa3dGVHP1rs25UJLawoIkg2IgPMNJkUVefu4OtQ4Cl_Pc1JALAY4CYxnOdu3B2dYQ59ZZigNO02RmbT-vVqsXbl69mGO7nWAQYn7_g0ez2dSUGYnp1o1rbZo9YGDOj7q5W86YM20OBEf59huvf_7jH2PC3XZbh0JESFSKdO0EgYCCDBHq_WisU9d1kXnuXKSWobVWCFfD8OKzTxTm99-_Xwp37W3f79_bBvh4VAJo3_uD-xcszIT7_YxMLPHJ5-88cXRlENmsx93cnLF1e3C5m3a9gxmEau9uL7_0bGGet5fjavXOew8fnp2NlQNJWFQ1AsOcKWbVaZ4JkYXNvA4pouM2tRvXbxLCKEMhEmIwmOfmFuCg7r13d3_nw7ufffml1TisR5nOtp_5-DM3rh99-OG5CNehBMZ6taq1quuVo8377zzo7quj9Xsfnl2cbUuls4fn6B4Ru31rXXtrrVvK6Twso6tCm6v37uidmVUVCFprREjLzt9FaiL_zXTJHI0AMyb2cC4E5vP-ctf2169fv_nUs7uLi0DoXfN2Y8GDrBrdHYEV3dRIhszW5CIL2ZwxAIPFEXF1vN6srl09_R__t__gyy-98Jvf_M7f__lf8B5YcN41APCuQiEJrkg6I5ohkTkYOsnam5JAhFlXrBzuyOwQy7IZkEppFoUBiUDdmXJagwhCB8SZUARgMIUdyIypN4haChMFgLtTROGCBs4Awq5GTMTFwSAc1KFIUBJYHJkMgYeaRCTUQDIUBlzq78K1WUvTJLGIlAhl4t1-jyLAXIGCcoQYgYRCKyZkCfC2b6XWoDHMzfZEnnE96WslJiSUUsAd4jC7JemuqyqCoF1T1YQW-ZVYplxZALM1K4UJqKtSRZBIVDMJdtXwwEJchRHbvO_TvLNYbYbWHZFbnwdGz_k0RcoFeu9ZcJk5MHszFoZ0YyC2SVcrdldEL1K6eWDUUufZVTM91lbjgFwI2bUZRjNn4qK0nRshkmvv3VuIwHAykEW73D1x_cp2v_eIigZMgPNQJZXymZdEiGEBAWDBBwm5LYNJNjMSsnBVI07xP-XeOUeoWfw5ROp0977bDKtrR9fE2Akfp_rmwJQyUoLDtUeklBcAFIAgbPHN4EEjDxhg5qmcSWObu8YiJ1rSoBLqD4iQUZ1Zb0fKW90XNFDeqBjhkT1MunZhmXp7bn0iFsk1ATinwDxHwQuyyBe-D-b_J_VmwdCkTZeWej1F_3nP5vI5a2k85EDhkquQiV2LrAiQLNFAkAsHB4cE9ZgZIC1KEkx4PbtlGo_l-2JhSxVPyf8lhzRqk4cDJrSQNSyJQCkxMlNkyo1JeCbIIQL3cGJ2VUIIJg-oKBZutAQ1MFE3H0i6WxZpROTLFgZzd-EBhGxhEJbbpEPOGxWgxRSAIUwfeabtEGeAYRiprcjlwtKlZPRXboYwUMhAEaOUUhjHUQDsxTs3QZ2ZUCI0hHk1DvPsTrEe5cpqwEAR3u7ma8djhr910wDSDiDAlBYLT5y8ZaPuEeaHpQ1IShMBgdzBK5Klr90jALsZIzkEAubGIH0hS4MAFEuUnSOR5ptOqdGkYgZgdy_3f_rf-Ytf_c1v0rj7S_-Hv_jJT754hY9LqfTGe-Oxw86e-_QTv_Gr37x96_raYah1vH4kxE9cO-UBDRHCuhoJj8PQOmDYPM8X2z1s-qOL89WV0EIXj86H9ebe_Ajn7W9__cu__dXfOnnyiS_88PfPuEcALlQdC2W6OiGB21L9J3MpFpMMpaLNzfFwHaSkHoACIioeXy_jwI8eTesN92lCJkDX1t95853bt24BpN2FMnYbkdOJlH0iBwJKhEF4OtXMHA6ZHkQMgOa9EKs50FI-ezcWjjCAEtRdVaQAAKgFODMFRIkaEF37IMXDDHEfWrE6GgshAzkSkHkwoGNgYVTEcKBQaMiAjgWl60zMg9cwVbM6iLmDoFquotEMUQIcp-hMjAAMbBHpykv_k5oPRZYRALgg9eilDBZAwhAI7pe6LVTJU6AZkHZ_YndHIPWQymZOnoQBmtQYhdxy-QfgFAjuRACGjkhBZsqVLVyCQrh7Y2ECdu0AYV1rGQ1MBCuKgiGEMAaBgRUpAwl4MAawkPAy2Sc6u9zvCf_2r7x6sX_7z_33_9iplHHDH-wf7brySOfzfAVLohk9gjE0fDWMyG4BDx6dD-MoldlAkFdUsXA0jXApDHsLMEYCxGFVe1dkAgVGbr138zoWC_cIKdyUms6gSEhUBMEt5YYZlhKOwcBQvM3uzZq6z-6CXodCEWe7i6n5rPMwrjTQ1DBgMxQMM49n71x759FOhGeCd969N4x1p9rDuDCh3L9_du_K2UDiEChy7XRzMfX93HAoM0BvO6IyW2-TI_q79-_fuXoy1LIZ5d6DB6thXN25-v5bD3aXW1MdV-ujsZYBTk6O33v_wSuffPrbr75bS51BZ8JhqOeXO9PYrIcb106Q5J0PHzDxjRtH98-n3cXMQ4Xg9fG43V6uxmG12sx9L8QXNqc8FUOHoxrbnRNgwGza1IigVLp283ZvNu2m09PNbu4X-4lgvH77e9565_9XS-laASnUmxmij-NgaqaWOvEePRymuUGoKeEgrXspOLkDAwZbn1FYTcPcut19-ODK6UlvfuPOzbfef7jddzOfzdztxReeOnt42bqPsk5ZlkB5_7373R0YQmncrFSdwq9ePULh9955sFmPu-0WLCDCW1froC7DIG5JDCtjjd4tWBKA0QIYI5AQ3Y1wkbK7zhDYp0aIq-O1YWtz593lOw_vXX3iyTvPPYub1Wtf-efYAklAkRkCo6kKc9mczPsLrwgWxIIoguBFTAGAmUSIaBCudOv06H_2P_xXPvfy8_v99m__3Z9r885gBA0Lx4BwcwUeTm87QHj6kQiRejgzES1wi8hJbQaqBmCmXkVWuOCOEIBuSJAyRC5yKEo8Naw5uYMwQkq_HlFZFgUBwBXcCgFDSCnu4QDETMzaOyFKFWJEwoiQUiEpXcTCYuaAWGoBBGLWpoAgXHCRB4FUsdZL5SV5ScRjwQtigFRGTpAbMaVwEWupzASAzbuZllKoCBCgh4gMpeY0skjBiEEGLgyEQeRdh7JR7QmIA6YMKsg8mYM3y5mlt1bGQd2BKX2iZahAGOB97lyqmx2fXGEEC1AHBwpkFooIbc5MUofso5gIMITEI4CAhF01s9UAgYtkgJDmwohoap0XqiOICBECBBN06-5GTKFaqKRtdpo6ETEjIAKSOiDQ3LoDTr0ToALtp07oNS0zRMIUEUicxVxmQ-e8n5kJiRAzeDUjHQIhj90FIJQ6mURvL7sdB4trp9cIJYApJJ_eWPj4jhAYBmiO3V3NGoAhGXBqoA0z6TqDugg8VMHU1MIO0nxnznguR841VFLVF_xPTiiXKi3nhSl_96RHH3gtGTHmgY8TiQ-GgVgCc_Ex-T8jY3JAmYsEd8sh9GOl0GMMDC5EUDyQTDOkxPNLXJzEaaYAIGJfOpYIAFdwyE4AMTx8gYQ6Lkh_OASBwMHRE4vmnvI_sOxAIFN4l6wAX3CZGaKNHxkhYLEnAhLIsvZZsDa-xJwDHUIYMMIBM6AAwwGXhidSuLQsN7LXckAEoOXr9vCkB2UrRgiOLlQ8U304W2AiALWe4WJcxM1yEolAUjjfNUwkXjqIMn4OtQ7w1M2Tz734xO2jzdWT1RUZrh0XVAgCy1wSwnEsQynXTlZHRcYitVABGIp4Oq9TYBSekb0ZKBZLrhj60gIecJ5LkX_IV8ZkuQBhYAaMZYeKYSn6T8sTYngusx0oc2Bi6SwgiLBWZi13H9z7q3_j7_21_9P_42f-61_77u_67J__83_if_rf-pfvvPgiX7vyxnfe-sXfeu0v_af_2fa1dwX51rM3vvZPv_E2wfd--sUcnRBQcmnm2dSAuQZydPDuYQqA0-yogcfHAPLB-_d_-81v_NOvvPvlX_7nD-69MV92Ip_u7__AH_4DaYUKW4DIq7EiAiMJMYAjIXPiqfI5z9Mg8pMmQktcVj4khcGhcu1dRcTQ-74T0C_98q9_5nMv_-a756dXx5P1KgPdETlPoHBAooj8vCN99NkMBHRaVoCUfFtGIc51OSEUJgdnBI7AXBlBFBIIGEICnGWxMZh1KQyLUSexCSDEEI6Aggj5hhMypxyODdLCYQZh3USKhiGjezBiUrMAFqN_znIhnCV3bRicaXCAGPkKknAeCYy5k0rdTQqEcEETAwZihIkwLaedQyiIuAblCZYzRc1owKhYJugV8lPjTujLXtcAwSlmV5GyMEwRzLoAm7tBZl4TAHTVoRYiJHIiSF4AITFjYJRSwHOZDMKyUEMMhDnFRwBwuqI_8Qd-_ESEEdyduQzDau7aTV1NmCpzBAnz2XYSJkSptfSu4bpardOqdLoZTjZH4d499rtmvny7lqdfJB_CGJaMSSJEAGKappmQDUB7q0PNWy95aarerQ_DiKRV-Nmrx7v9vJ33GrHdd5FCgBeXczefWw-gpl2YmUiEjlfl7NHu1o2T8_Pp0aN9x7jYT91hu5vnrnPvwkVNx2HYt87EAdBbiyAA38-aITTeLZC0d4Zg4VffeuezLz87lNFNb125ghaX5zuwWK1XQIyM46oOMgTCyWbcbWfTUG3zNMs4tKnX1fDkteNSmQd6dLGz5OAKkxAgXO5mZgIPV-dCvXVEQupff_X1P_hD36O7Zqq963BytL3sfW7MfHRUM6n92pXjy_PLcF2vjx4-PP_gg3tyVC8evokC290kQuePHq6P1nVT1dS6W29miWwA7yG1BMaDR-cnJ5vKnNrSNrcAUDMi7L0jExOWgnfvPrx545SE9lPravPczi_2ZaifeOXFPjcz7R5IeLGb79-_2E5Twkz6vpuZE7AQBg3jaA5cmAQiqHeVUpGpTVPOBDGBmSTWFd2IiSKIOfM2c-GcCkS3DN50RBBhotieXbbJn_jBz0tIOz-bLh8-_OCdhxeXn_rM56_cvn324AEseuAUvCC4AaBA3v3pmcV6dHT65K2XPv6ZT3z2Yzeu375ycvXFZ578y3_h333-ztXt9vKv_M3_z5f-ya9M-3k3dRb07kTISAQuVCVHaUCZmONJiM6AS7dUTpCFMpaunUDziWcuHl55uY9zdkgs2jtxCXeSghGEbKDgnhG-RBTCKYmFACBqvVWRgISZIxcpXIEizIZVBQc35VLMgSXV8wwRRMgQWNkMDJGLIOBqXVlYVZPNJiIAUMaalkomrLxCmtWsjCvCCLfwoCIJhZ-nXqoAIQsbGDkNq41p42Qc1UKIvTUZqnZFFEYikgxMTaf0fn-emgJ3dFOz4Mrp8xIWBEdn86DKwGRZlyCUsWjvRdDDSy2JgSdGlhXYTntTdS41AlV9GGozg65EWGVs07QeV9qsNxuPqqszcI7SEKnt52GsEbFr8-lqPbU5MxrVrNTinvZUcyJCICH3IKCIcHBXl1pm6yuqs3pB9KYQ-4Fpt53mtj89OZl7G6uY477rmohh2e7mvt5SJ-ZBjG6RguwlwjYyTyGzsrKIXQQeEMBMAMEQY0Ht-PTTT1hjNyYUM0-JDEaezTlfCEJEIbdE5Qcu74KZm5tlV0yAPZpGLJE_KbixAAILTzxi79PBDyyppEcgQs4hs1n-BUnlh1TL5DexoH0w8t_AJV06a9THInUKjMRK5AQdMAFegEDEGVgQvlB18dDlAFJaJiJSILN8g8vwEZe85YUdCge3aRxgrQfYqcXST3hgpAcQD70NoWtWo8hIiuG5MEAMCCJGJPDU6atwVdBsHTgQIixseSEACMUxuT0d0vsOCYUFdyNm4LB0CHguRDGWbWmm2yJw1r6UEnAgCAumZRvjGCnhyVYsAM2iEKFDj05E5laANcLDAwyRM9HVTDNBjDibr2BEqhiOj2O0PLwIUsjzV49efPImIfGKOzgQgWPGorfmYRaIzDxwkDsSmamFBwIhuYGZpfaTCBMljojEnGUtEECikSD1JuiesMVUPoE72CEVbiDp5p6LfmJOYAMGEyMEMKlqDjVUg4QhXMMKo6u9-rVv_aX_6D-9fZ3_1J_8U9f--I-xjJta3j2b_1f_1d97-clnn3_x9pd_4yv_yX_-D58K53kPhL_0d_7x6Z1n_8nP_cpnnrn1XS99jFjXwwrNw3AUCUImIkLwaADmuJvmYRzv7_3mpX79m29cjf2v_eIv_u4f-MPf_tbbJ8PR-Xxx85lPf-4Hf-zVb37jhRdfmdqEwIXJwFvXwuwY6sFImD6rfMQJCZEIFz4UoCY5Lj91mBh2QOrkQIV775BhlU3bo4svPv_Mr371tS9-5rkbV26gWcrkIIAFu3UidM7YXQtKsC6kticIuDB6dD-04AFIQEAW4BZCGFn6MhGxm7tboxAUVQPGOdqmrHpXFjFvjhiuhVm1pQTVolMSkcETk62ROmTgIHBnqd1UuHhYkHJSdwIhqSZEc1f3qCQeSiQGQQGGRoBugYIgHMkHi7SRADFhpOo3mMghGEnNEKGUEu4KkQQkcHGLhWuO4KZggIgCqKATKDGtrGxxIuaADPk2BDLrpQwgiBDdOgu3ZujYQSmLeQBCd8ZKlQMdwyM2dZytC3Ja-9CJAomAISM781QiGBLsGyIBZOdnH149GW0KRrdu3ZRQ1kf1uMqHHzw873bl-MjCa6GrV9c6OwNMvV-7unl0vovM1AO8utmgGqSYk5k8yF3Dh0IaaGYRnlMBgoiuM0StBQKl8G7XELzWamqZDJxEL0Soha1PBPqFjz-r3S7b3IGQ8fhobWoAMKmqdgSsHEwyma6KTN2LlBs3r1xMjVFA4OxyD8QacL7b11JFpKkhoCNe7OaHHz68feva0WZN4QBcV-PFo62FQ6C7rWsxM23NUd88O3_h-ESEz3fbpr672CkAsNSh1MKb9Wq3nee5N7f7D87MDBJFuNsD0IOHD18TuXo0nl3sdtvJIWZtAQRAQni8Gh48uhxL6YWHYbxol0ghMt57550iffbuBGZx9uCBzjMg1CrqXkdcrYd5PwPRycnJfr-f53m1XiNxDLi_OK-CBHL9xo2TmyfY4zv3zzFwXK9UtSKbqZTS2gyBbTedne-OpBTG5XYyW43Fwx3cwls3UwXX3_it15BwfbQ5Wq2n8K5wo1ayVonubvcG2Huo-ZVb188vLhD48uyCIAbh_YNHd1569spqvZ_s3bt3S61dYxjDAadpX8qKaHbtjiq4IuoYER5t7szceyulktTV6Xh-9yECcC19PxUCqVUna90AcRhW128_46Tnv_1au9wCs8-N6gD7-Wtf_mcYw_f--A9--M4Hb3_zVY8QQHBgBgBGhsQVlyoN6q3nn_lbf-XPjrQGRSS7_2h7uiKhiz_3v_m_f-nVb_l2hw5YZZVhoBgsBbtCBNdrdxABOLNIQwoRJeExIkBNU9G9GPk9EMHDMhUpZabhnqv5gAApQUGMDhHhLNVMEYmAai0ZKpTRlQgoUjyMpQAGMXsQkIhwIXFTRjYzJkE6iA2QuRQiQdfUtZdhlWPnZdocBAdOdm4zMMdiCCISABGdmKlIBIgwp-yHQEpBpGEopdRUdhUpHgbhtTCnxwKi1EJFPGJYVQDjIsy8UFQQ235mRgQyC7MgJNck9OfWo-ZI1nSZQYowRTAzLTtmkEpcpNaadYMTTtM8N4VELwcSkpnLUEDA1dGDhM3NgRhpJaWK5Nir8KhhTKxqZazuDpaDQ3YzIu6qYUaEq2GFHogQpojEwkw8gCADFWRitehuGp5ek8Q4iEgyMEnQIcxsGCrAAviHTJPFj7iVzAuNJqVsBEipLWeizJkWgUNJTUK8SDLi5PiYLSEsFIDgtmwQIIggxbeBhktMfADZAsFjVmtAQYQR6GDqZn5Qvx9ajqT4ezggmM908PbSouhPZbofxtKHn8RlEI7L-Dk9rYvGLR9-JFr0PkARzoSPlxuL3eEgkV-ECVmcL8Zj4CRvwBJNjMtPJOw_ExIWt6BnyE6u3QCz1lY7QI4wYfypDnBEUnfI5Dq3QEhCDASmVDkF6YThSSqM5WQ4yKkTVpiAUTzsPeIQYbbM49PAo9EB6WAzQExJo2cywHKiUAY-AErhg1sECNEcOHWJaRFYXiFYBGB5hABAkPny2uaCJKtkInJaIpuWh4owNwKUqQvCkLELnGFqDhhUcBzo5pXVZ568deNkwwiMyDmdbZrp1JnwCo-d1-nd9TB3M2UmAmJCosyWzo6AiJdVWPp0OZlQuUNZetHHrpClkcqfzazWHE4vfxtCAAizWSBgBqARJ7qegIIxGLFN9lf-z3_97Xc__DN_5t_4yR_9sZMrGwe5mPUb9z_4G__l3_utd9q_-1O_79bV0yevXv3JL3xm_bmjX_v5r5QNasDx6eaP_Vv_4j_-6V_-Pf_Cj8W89_AixACVUYhqIfdekJhpXIkQOvjtq6cm8NxTt27evP6DP_GT6xs3f_HnfrH69OJ3fdef-wt_7sXPvPgLf-fvfu5z3-PhRFBrSb0dEYgQEkGGcC2PfX4-YGAyOHzLmWUtREhBQRGtm6nlhnEYxYIY4hf-wZd-zw999-nVo6efvfHqa29vt9P1W9eRENzSw5q7wHR_RH6IIYSKagaPIBMhHtp7hFiwExxhRfhxTvhivQDIHaaDD1w0vHJxjVLyRqPcsgJ4IdYwoaLLFmdJQx8o5XmOjgsLGAKFwaIQKwQCyOGRUnWgpIfhKEUPs_O0kLAQEXZb9PqRJSmAHSLPEwR02C8hAjKKqVUhz3S8MMRq4YQJMQvJNA5MQWtEkJk16oCoedpqZGciSJV5MbJgcp-JmHRxDTkcqAhEtCq52IDg9CwkNJwTmjRURgQWrkMhRhGsQzU3YGIBKfQn_8CP5wQeIPLC6r3t99PxpuwmdfC5uwycbzQXbmqFaZ7nUtg0drt56u3K0cCB0zwHxD5t35AwLiASx8xVo-iKwIFupiKSHolwF06rXrKJMVnkHuFurc8vP3H7-rpu53bRWlcX5oGLevTWptbrMAy1DrV88skniHE1DFLqbj89PNutVqORTK0z1732AFAEt1ADQwiirt0sZveLy8vtrpUqgXBysmqTdu2EnBaaad_cjUXeeO_-s3eOj1b26HLfI4TEABDjwaPdUErvSuCFqRQZh8EgdlNbH632-4ZCj87PA3CzGqapm9rqaGjdw2OaGwJqQp8KycDhOoxjhNZK-8vL_8aPfqHvexRq7vfuPQrAuTVEUXMhSQtcUyPE88udmrtZj-hz41KGWphxIC5Sd9vG6N2UWZCg9XxWyVRJUCpdXJ7fuH6t1qI9KQjACIjc1VpTKlJFAun8YjupWuDFbn-5ax_72LO3jjZz6xeX0-tvv8Xjuhk094vzy0Com9rnvloPaxlu3761Hmt43H14rrPu97vd5eRqAcDMrl0qC2Pv6qoBEG7aOgmGewAwRu7oal3NbSbwMKVaPTNIxkrroRwdX95_uHv4yHvjyqpqhkhch8G1sfvZvXss6-df_NiVm89Mu_O57SIwAsf1KohOrp5ubl6r66M_-VN_7JPP3hoIAB0kfuZXvvy__w__s7_-N_-_v_H1t8_vPtLZtme7NrcyVvTeJ2MEograuV65gxm9G4EIgsnQQCRxM-LcorscEO9IWabIAjdESqNtYGCpqo2IvHcSztuRhJO1B-iEjEAUyunOIRYpGa0XAYgsZXAzYiZiy8rVFJBYKguPZZ0OKZEijCRD6jVLHTCQJQMNI8eZEFFrBSIhYqGUVwNS3r8QKGkGIypDRcx0w-UeDldG8XAERgwWcQgmTikEl-La6zCYqhA7BIkg4GKj0mAmVRek4HANIYIIwuhqRMicryKFmVAhTJQouhkL0xIjAEUEEKftpH0pMdUdmUjYlzW_C7KHWSzckFkVhNrUSdjREdAW3mVY9yqlhYqkiwApkJGEirtaRKViC1kWHWCyOQ13U2tMDESt9whQVUI0syLV0r4oxJWHoRJGrZUwo3-X4KrsFhYsT0Qa-dLZmWIWWpJ0M0Y1TeNLDR4YaP3kaMNcCEoqRhY9COV9GQiO4ETAC1U75em4gCOz6kK28KCEQlLuDzBACHmR9ACnbzISurdkGizo0oW1eEjS-p35t0utkOwMT4FK6heWMgYPqQeHAm_xA6cOgTiWrzUnmrSgjR5HGQekeCltwknYSWDPYy9B4jEz-idhH2lHSGSiL_blFMRhWn1SqJOrcHfPxYvnZoWyycGujVBSWAQQA4hDehQOWWvx0RYGicw87chZyDHlLJ9x0WktBAEETCE2E4TDknO8GMAxApgZ6XE5n1OIxeRQaEEULJiiBZizgFotlIAXNzBGztSz8Uh94NJxWXjS9hdFEzx789jczAARjtZlXeoXnru1rjXMCZzIl8hSiHEQIkgToXZzd4gwD-akkwItg9qDjTdTXVmIqDDjYaqy6AkCDMCzZyKifOYXxwk6LG8NAaZuCJlt0WVgBEQYMSADAHLBTGdePOZE0_7il7_y5X_pD__kpz_7yVILIEfQdrZvf_2Ndz-4-OLnP_Ov_PBnpcpe25NXT3_lG29re_Lbv_HbqxrTNH_qC7_3_N0P_7t_4l_7L_7Gf_7p7_v-2O_CNSMjBxEzw9zpdVe1y4s9Mt17dHm527fuw-a4VHbafP3XviKwu_HUc9_9o9-3vb974mPP784uNqsVE3m4uSeyFgGFiRFoSQVZlGSUYoxD4OMBDktIkJNUIpJS6koQyQOo1NW6_oOf_a9vv_jcjes3AOX6jasQ8e6b7242m_V65QDJlyPmRdoakQHuB04bLphaW3JEMlQ3bz1G9vCkBaTzsxCniYqSg01hGBKLeR8BCy6WdUKCBAqBO1gpkqZ2CNQANyNgQrLEAAtyJsvnlgpgwShEgCCllxOXTRcu0IH0BCMG5cjCPCTt1RiD1LSY97aUsACQvnZcDqggSg80axgLClCAC6KHkWAAee5LiAINgR3SKxAQziIIQUAGoNqTXRsB7lZLSQpEKSLLN5TxKLQcWQRVRIgKCwlXJkLAgKGUVAKGexVh4bEQF47AsuIfevnp4s6FIlxVHSzDh6sQMrHINBtxeXQ5X27ny9nMY70qvZmZN4_uIIQ3rpwUwNa8DKi5cV3S_AgBtGtYEGJhyX8C7GgzWg8SBMDWe6QeBrD1jkiGXoWq4I2rxx9_5vZ23-89OusRZlCFPCAj-dKyVplO1ut970PhZr7bz0RcSp27bfeTFJ48AGHu2jW3-SSIAN7nFgsHLBwMw7cX-7PLpqZJTAHwImwQQVCHampvvP3ga99591t3733r3UfXT6_UOuy325OT1WpT9heXbbYgNDcmVIdmylykigzCAYjR9n29WW_nNqt5ismQXJWR512ro4jIej30ua3HWpF450eVbl-_FgFz07PL7Tx3R8BgRF4PpTWd9lMRKlIMfLef63p9dLzWaW6t37h-slkf7ffb9Xh0dn6xWq3meTJ1DwfHZhbhUkrKdxmiTfNm3HDh3tqqFnePgJYVEsU89-1u2k29CKvbdLH__h_55BVePTi7ON_tpm5chqZ-7_659rjcbdvc9hdzgB-fHA9Sdpc7D9_u-_27j7iSd-tuRNimzkVa74dRYWjrNjeAMFcEYhaRIczdVErtrZVxnC4usDCRyDjU9bqOJTx2798jckziIqCpC6Kb9651XAEHMMzbi_fe-c52e3nn5RduPP28UZ2nGfvcNCLo9NqVH_78Z37sd33PBx-e_a2_84vb2-Of_d_9rV_9la-89cbb292-9_2825bCoR4B3n293ug8uXmECQMPV-8QI3KNcBYhyvqUHX25lE0pRcEQVPJ-kYymR0CRJQE4kJYoVVNEDHWiBQxAzA4uXIAD3LmUiECWg4OeCJlFWIiIuPA074mrDIN7L7UeCgJmARYODCkMRFxEqrhFqSUQ3SwQ-tRKKXkQQEAZ1-lhMA8uXErJAnCshYkGKQ5RiCzLL0yMl2SOMQSpWd7yyAwRtQ5ZewYxAEktedhHhCto6x7Wukf4yCUW8x6kKC3MSq0OGRaLCao3c6lVtSMTiCAjEKsFIGxONrvdvGQShWdeclfN0EdzU_VN3Uy9o0cdyjKREkLGuaswW89WkxHRVBGx986Ewmy60BeRgRjUdCgFMDQUhQuRuhHQUKSpuVsG_WYtSIAihRDUTLUHMyIWxiLCQoUp1aqUZSjAov2M_IU5G144mHEomNMvTwvEhook9YKGSkRSaEg9NyIFaNa9EQaoi0B_GXx3WrQk-eDmaQUAYeY5eEOkdDQkYcRsmfXFQlT038GPQXrc70bkbzuI0oOWVOzl-iVaplyLwDdzgT8a72PW_UKY2nECyBE-fDSPw8NwcamEIg5R2YdB87IbyIC0HGMurgDAAF7SaFHtoAA4ACUjew7gWEidCIgWjp6DWFqiBsDdAAjNnJETAbS4klP5QAiLXjnokJG5yJ6YPBYVByIBoGRNk2svwoCw5A1le6AmRJAyMMIAX5joCxIE3ZanjpblTjBSRBhkJm4EgIYHRoWaPmUB9gXgePiTMZgx1SPClKIqzoOJsBR65s6p7bQiXrm2LgVv3dw8dXo6iiCQQ_5hmGS9uq4AqO6u7h4GuDQgSEjk5o_162bgZksqAiy84HDzCDXXcIsIiG45PQRCjOWXIy6j1mVg_dj1kUuvtEkQUjbqTBDuS90MkNJrJvzON98ajst3vfyirEZAqKVGKb37m2-_-fbdy89-7lPr46NB1hL6_sPt6dVrv_XmO_TZ51796Z9fr1dXrl75V__sv_3ic09B69_zAz_0C__w51759Ofm3RkglCKpC0GAbhZqKLRZjbt53myOLlurQoj4ztvvTSbnH7x99sE7UI6-9we-LwzWq81bb7z15O2b6lpE3NRcF68VZHbL0jqaBTIs7XQqreiwzX0MvEUMREaI9EJEaPM26c_-7D-69dTTTz93A50K8NHR5vSJ4zfefPfifH_l2klJU3im4wGgI2H0TJYiNAPCRUCFhAmrSQsyIIA7CS5rNQQLWPKqIZPsg0gej49gsdQsid3Z83Dih4LCAZfkTovwEWugK1mKAM0yOwUjg8YQEknMLKkbWuxFuGzRceEAZuJf4hTIIYTYwwnQAcyTTF1zksHJoCMKCEYkIrfkyy6B4sTo5uhoGGo-UGlmjKzuTGxhQSRB6I5E7o5EgaRqQlnCE1iQUDflQiKcOabpu8h3eeAxMNx1rCOEDUXyNa-lYngpXGthBmGUIhCOADKwERWIL774BFgkTnCv877pg4uLcRjGSojMhFLKtnnrEMgG8PBiy5LcVnBkIGbh080KwwgNiJC5N1tmOuYUwYBCTIhCyEKmnYiGoQIAErSugTgMQ0TOj5ZQFggb0T7z9B3zuJjmXWuTejdTdYvoamYQrldPjp443lhrhXi77-_ef9QNmnqzGEW6BgLO7lPrs-qkZmj7_YUDhunAvBrKPDU1125z1-ZOiGoAbsN6XJ-uu9o0td4Mg84v523z_ezTrCfHq_fuPbxz_UrrceP60b2751wYAS63-94dRQ4p416HcZ6m1Tj0SRGg1kLMGjG3RggX252qm-npyQogwmJ_fnl6fNKn_fVrVz738Rc-9annNrXup_7w_hkPQsJ1LMF4fDQi-OV23-YWFCxiaqvN6nizfvudD1RdSrl989rc2n5ul9vterXqvUuRQJh6V1WRwszeVdXGsbrlxxiOjjZIWNLXjmHdzMzUTMO1E7JqH9frscgXPvaCst072_Vuc49H57uu0dymaU_EXS08Tq9eOT5ZXV7uLnbbK9eP3_vgURlxv7feestUWUJA7K2FJfhKl5LDDAOYxcOsW2L7Sx0uLy7cOjFxKfV0jYG63Z2_90AvLst64CpcigNzYS6MxERCzDKMbdZxfRTeI7S3_fl77z548PC5j7_w0mc-tVqPV2_ePD5ef_z5p_8n_85PvXb__r__l__a17_53pnvv_krv7m9uLi8OC_sod3Nwo1JPHpvHrBkZ4U2cOPNjafclt3dsvaCsHCfW0YPE-YO3aWUsADHfBYhgtARACiocCLhEYCQCXMHTgjIZVhcmA5EogBKBEWIyc2IqBTxACLhIgFoqjJWwtRtIiJTYK2FMHNYEZB5rEylDoOwELMIZaEmRLUOEEBMgFRrTfB2kZIUMEIqUsG9MtMBlEEsgGSmIuwOph1JIhzCmUp6x9C91iHJ64godaDC8zwxS5-7Ns3VsTuQYJ7PROSR4868vDnFGMiYwayFhRa-BFBJCTIBEguXUnTqZVj87yRi3SJsXI0fuTYBgdP1hQjyGJGRdSkRdbUySC7KI7xyvgqkC-2GUsBRqWxnE3ZGvjQd68BIYe4ezMRIpk6M3ZyJipRwsO5mhlUGqfPcWBhMV2MdmKrUcCul5DqFM2gH8s7DyEi5IgcGNjLJch8KhgMtRkZY8sMYwGmoBSLV5p5fdbYStNgNnJahck6NGdJqm3Fsi1Mu6djIAKEpaFlsx5ZhWGkEBSA4DGRTgJpGWz6Yag9lSgb00BIHk3dvKnACkfwAt08pc3YF-SpEZOGISZ9a7MPJ2k3DLSH8jkjjHDfmpC8xQYcmCg-T-KDHWqKFVwqJSfXD8mKJCUkdXzYa9tj1D0ncD1dc5vHwOEDZzCnjQRYF0sI_QkImAgB3wMOeAQAYMgaUFJaNQ5p3DZaoNcoE5ThIr5Km6gGQzwZy4kcCOHNViRalTB4giHM4I-ohTSGTAFIMkCVXmlDSppH9M6EsIc-RysCkHsWwlit1PCrl-tHARVdV7xydHpUihJN2D1gNBYm4SD5QDGjqquaH2IW0baQuPBu-LHLyxSFCIU7zDxOBgyadClOTlrlKOVpGP4TIPQ4DSKbxYvWCcOQ0xgJhYEjSFB2XETiQEO3303sffPDSC3c2m1MH9kAuHMpvv_PBL_2Tf37z-s1PfPzloaIEq_Z51958_9EPfPHTv_rOmw-4fOerv3VMrOE_-Yd_sp9tZ9Wx1Ir85V__Z5_4xOd1v2WkUtJMBU1tZA4M16hH683J0S_-068-feuOYcz7edrNupvf_OZXSxm_7_f_CLReyC-3Z6erNScj3WPJkgushb2bSIImF7RiPh7LWgQBCTOgbUl7RGJBClC3DJlzxbpa_dKXfvnpz7x46-gUgwgUHAepV65f40Lfef1NABiPNnSwWRMCkeSnMHBJy8DHW-BUmwmFH5C9jzEZCJmhkm9TRDByJmCklP3xMDnCGRkQhCQ-CstDJDKzHAN4hnkvbiDg9PpGBD4Oq8HHLh_3YGRPwwN4JXF3zqgR5iziEzOV8kXmTN3NUQsH5LYKggKRmLKjCCk0YNHs8BMgl_tQAJS8vMgjAaBGXDCgN01ee2Zp966MlAHgmTocDlKKqhFBxnrmsywEw1DDTYQrFwxkJnMrUmotyfErIh7OhMK0Ggo4CJAIjSv-0U88c4UrejRt6mYB6jFNUYVboKomAO7Bo0t33JultvByu792tNruGjM7RhU6HmuuS7bbfRkYHVLx6OaSN_UBwps-aiIW5ojwQPUUMBJEqAcLA5i7n675u198tqtdTvPDaXqwnTAAgTJOFADQ7WS9Ol2t2jQh06Xq6-89aB7DathebB9eXgYGKKi7zh0Aeu-t7ebWT1bjj__Ip2HyabfvXcEAAnq3QJJSvJm5r1drjZh7m5vtLvZ1Vbb7yQDPd_udahnHfTcEfPr2zWtHw7zv7nH_0YUUKFzO54lKKVyEqEpJU9Tlbo-AzWxYlywtprn3pqXIZj2WdRXBaVKAOD7a7Le7cShHm-H3_e7PPro_6TzfeuJmMz3eDFJrrdUsrp5sLi52Zl0KiVRkllJd7YN7DzKjaVyNhXi_21_u9shcuMy9M7IjSimIPK5quEc4EGRoZmv90cOzAKxldIT9NM_7pqbdvKvNTYWlWR_q8Po77_7eH__BFcG9-9t9V1XfTfvdpC0UmNTi_sMLbcZDOdlsHt4_v3v3rKnO4NuLvQFMTZ2RAuepsXCYdXNVrYUiYp4aEgBAmGMYuHddCHUyFAAPtXAn5Onssl3sAnw83URhqiUA2m4GQR44DMwyeArDDMC0z-ZaVmsEIACBOHv4EB3KcPzsJ18y2vzP_40_iiP9L__9_-j-vQ_OLs4_fOuD_fZi2l2GNSGwbuEG3QEs3EyNhbQbF2ZwaJ3r1TvI7BYkyMTmHWwpRZiCEN0DMIQLOBRaB0G3u8zHjCQ8dJ0DyANIxGPR6gMQsWgYABaStBIikcjoZslCsVmlDLyACTj3koQCABw0VC4sIIiEVQqLJCuOiOo4IC4ViKvWOqSFIDWE0ZWLEDMLD3UMzKlupAbdzJEZCE09EENIdSngpBR3R-IASsMdAqhqohURABjM3cPGYehzFyIisrmPY4VwKsDI4dkSe4C7OQoSi3sXkq5TRi-5hRRJOD2TuHZh4VKAaBzXGO49SpU6VmIENzeow-BGQhwYkd5AB2bWptGtlBJhyChCvkSFAhOZmqqmQm6oxV2J0BPxEI7glbipB_og5XFgFkXMvaODIPeuQ5EADMSz_dlYRifM-MxMG9i1HefW2YNQx2EUJuQEVS8YbAzIJCnIrU_2Kbkm5wWbfxiEZxAtJegFATuomW3GSsxLh4ORJPpFIY8O4b6s7WOZ5dMiol4Kfw9bCmN8LKnJsCd1J4DUHEXqj5EyRTxjvQjRws0MF40H-UeVWnhmiiFA5p0dhPwYGTG7CFuW9mNJKE7fc9AyJwygJdHpoJXKC5_woIYnIvdYyDhp3AaEw4BwAYNCBIIuM_YDGzRXBx4LuuewS4AUAmWZ5bmeCCAKDyQOAF8wN7n0cEExcyZOAm9QEKBDQKQCEFLFE76wj4IAGT7y6QLyAbz-2PWNhkHp3iZcOorHKyNI2CVwKu4BIFgQI5bFY5qu8zuBBWP6WDrvB_RSukvcU3Gz8KfUjJkS-rJZyenx6spYN0dyMgxXVseFGR0NoEEfpFCGowCEa74mEb5k_S39EETKg5ZoiyX9IP8vdzLZ_xKSBVj6mdUh1W4AsGxsciOWgLZFiJCW7iUCIrtHggRCEy1uACRAZiFS7Wf3720GuXXreji4RTAPAxnAP__ql9_49mu_7w_9xNO3bkXExcPL1vrc2_3popn9wMef-Ft_-5e_57mn-ezy3dff6a6377zA3prq-x9-8Nyzz23Ptq--9s1nnn2h78-REdxVdbufZ-tDHcZxkJHOL7bfeuvDZ5956tHZ-bzdFtn4NL_61a8E2hd-94-wd3Q_Oj759S9_-flnnzPvlO06pABIBmZbkLKZWQa-IMIQwvPJoAy6R0BiHigCwoyYPcBA2z6Q6J9-6ZfvXLn28idf7vudmhWR3joRjmO9ef365XT5znt3iWRzMsrSIzpgACF4UOKUlqA6BnMEDIM8spIAs3SOuZuASIpU6twcvCAzp5kEmcjditTMN3cwIjLVxZ0SyyA_kCKiMiGEZPDfMl4Epkz7TahaJvd5CiY5v-sIX0YhS5RKPiDhwUtuwLJjDAhhWYxOEcAhyCnrdYgMpjSAROMxs2EydfPASYKZg2dGCWKwLUBV7O6F2A570Tx0HQGRCYHABxEmLpLRbVgqM6MQBQEjMuE4CAAwSxVGBK68GLsQqshQSc2Oj1dlqFeuHZ83_snvekq6ISGG7aZdi1yNMgS2uddagPjuvUdz6-6Wq14AbKpSkIDO9jt1n6fp1smJmzNhRBAAM1uAKSBLBGh6EnhxYQ3DICLmlv1MfhoT_xLmAUZER0P97DO3CUHN925nl7OpEhGLqPb0JRYuzz5xbbvbc-HJ_fX3z7rmJgsiy-g-O0A3NYDuGuDDMPz3ft_3PHflyrzzphqBIBwIarZar66cHN-4egJEXMjAH5xd7Lb7ad-RvKvu5za1PtQKSjRSD65Dgf7oues3gEgomk2z2TCMKNxbp0A3zwvdMQBpmjsJAxBlvsncqbCkIUrRHWQouShT19OTY2HYlOGo1qeeun726PLR2ZZJNkfrkYpqXF5erIbR3dVDpFYpyTdruuS5UOC-94uzCzUlkN1uP_emqheXO4Co42Bq3jsSWvdCxVXT37W_2DlGPR7OH237dtfMw8K8N_PeGyEgxqdefOaTT9_p-7h3fsEbenD_8uJiP8997l24nl9sgbAOQ6217eeLi0tg7M0vzvZmhoxz67hgum0Uaa1vd3thMvN00YcDuJk5E-k8k5SEiQyrVZubzZ2IdJoJoozi7to0LJP3DEwBEXrKnHPfNVib81JA4ZySabcyDMyym-aT09UP_9B3_en_wX_z-GjzV_4v_-9f-7XfRO0SblML69YagVvrSwHUDdBCzSMyRAwXSbbzcPXJPHeQ0N2YJadYDBBuC_BHShz0uO5OdEJQENBjIhkQGZAggmuhICmChTNRMxDy2AqLYHJXqsJCaFGYEC0UiBmRgFMzsqzTiImQAZiFyzBwKQ4oIsLV1cdxLLV613HceBiReAAXMbVkFxJzHQZzT1MvS8ldKhFHJOiESHJBIbgUdu7mSOxm5jpPO2QhTPRYIAJL8bCuHqopIpj3EwuTSCCqKwp3dUIgRxFhxjZ3g0iXU6ljlcLLhAvqUBOKIiQpSxApl5c7kVKHgRDLUJmLdUWibhpRUp3aVDFvBaDIYjhvQz0w4RkjQiMIaZTSTbmwtj6UMs8zEplqSkAIkSjzIyFU1Q5keQdCSKVvMiXNvXD1ADd3gDZ3JOpdLbD1xkJHR0fHmzUBCaEwE-USHTNBcpmnM4Fn3P2SwgOBJLLgDnNDHODe0_CXC-mUOogcxL7hAEaYqhUkRAfPWxbBMZ_D3LTkuZWqcEIk5EAW9gTtHybrBEHIC-7moMGPJbLsQGJZHKyHZK7Dlp-JwlOOshRz4U6J7V_4cQiA6ZJfdO6EuIBxcBEJfCT9iSVtDHGhTyxw_4PUJ2VJH0nkMcKJyHwhTOa7nxj8ZQa-dFsJ-fMAUPdEJxGhW2TQQYqAMn37QOXhHNBGivcXXwaaGxEy1UBPxRE4ui3ql7T4Mtcwz0LYAQ4eZQAMJ3TzxdmLi9AoMAuUVOknkQsTL5zj9cfkJV_8xOBgkM8_EcOShmhuhyAyyvHsoVmjgwvDS87ss1SiuH2yCdPNaiVSlwKbwlytt5JgHfDeu5pFkHmoLX6FnPKmOzrAk5oinEV9PnwpbHMLD4fZvKlZANOh_UQgAtODKYBgyS_ILxkAKarIYhkhgAAplLYNRM5maxRiiv3l9M4H7z_11K2j9ap7IBHX4mAf3r37K__k14Y6fvZ7vnszrADj4rLfP79oEUb1H_76N37kh7_HmO6fb08362986zv33n5X3T_5he-VgiGgXU3nZ158-c2339zvLu488YzOeyZBEg_Y9d6j11qKDFdunLz76ls3bt-UbPrN57Pzr3_tN6Tyy5_9_GaoCLhar9944_XbN28NkidJOMTeVSsWRDmwvPLDl7jKdBOVlJUwZGQNMZgtT0W4LRHpLLdunfzsf_lz52eX3_3F7zvfnzftJ0djnxQZNBwQTjYnV6-c7uf9d15_iwqNm9VAhIGOkTy33C3kR4aYcq6Ei7UDMhOv4ADgdFD6M3L284wU2RWI5K1--MSgEC1je-KwtD8tIST5qXFzJEhXlMHv2AwEIIIQgblaQCAj6-HjSZGWd2NiIQw3YU4FQnrcUxQKaaYPT_tA-pwWG5qZBTBDkjqREQksnJBSzEBI4S5Ch5gTTCxA9roJHUYmUwMNrrJ4tQ9HKxJyqZKc5QAmBgIRllQTpSiIGAESr1RKISARKiKEqNY4vIxlNfIf-eIrn75zetvbWpaUMhEUIdXQCHf8neGJ106Pb1w7vv_gchxGFs7P18MHZ0_fvvLe3bNSRSNuXFlD7pmZprkFGiCZmSsQ4QJlJiQEYhLhnO5c7mcRMQvzxJZEWtWI46Vb11ZCRHjZ9d6ji3zB5tY3x8cOth7KejVcGWsJV4BHrb33cLttCsshTCfHR6qdqQB4HYrrLAKfeuX573_xzu58vvfg8nKe9lPbrMdxtVpvxlJ5PVYi6BZq9ujsfGqTe0z7PRdOgcr2cgaizbDB_T5GvDSbL6dHDy6--NlXigAQHq_Huw9245opMHlQA5MQi9Brb9-7ef3EA8sgQHB6vBlrUe1N29Wj9Xa2y91MAMQ8DsxYtbVp2urUHj189PJzd1R1NQ67qdWxuMd6RLUog3zw4AEB9t6euHH99HR48HDn7h2sz7afJu2x2-0vL3atN_OYpjkA96qlllprb3tC7t3crIiEqyO01hBi2s-788tucPbw8mI3rY7K-cOzswfn54-2tBoA5nFcff7zn3zvOx_sup9fXszm9-4_QmEgVjONmHa9EBNHn-auvbtPU0_fowG2pozculIgWqZeQQ52LelsbjKO0-UFmpeUfweQEBL3aR9qxAjuSEiF3Ty6E4X3RojeegQmU7XtmyMSUwAwC7FkDPdQBjJbD6WOBYJXIz379DM_9Yd_4urx8a9_9Rv_8X_xX11enrmqh-k0qak1ZUBTRaEqNO8mEgZK-Z9hMg_NCYNXt54hYfTD4ZslsiuBR4CrUam5pswaPQAQtAgJGjCrWmqaCYmlICAhh6UujszQgAiABYkpuYMQkGZXN5OhuikKQ2AZhiRCAGIpQyxWRhQqcODPFBGpgulIPoSHBpjUobUOiG6BxEhEBMSyaPrNUn4hwm5OxIAoXHo3CCgsambgrtanVuqqT3MWpAHGRH3uSDyWVdr8Icy6auuBEQA8lJQ2mkezPkgpMniYGaRtiyHTljgnrOA2DtXU3CwZje4xjKMHEuMwjkSLHdDUSIgAm4eqFuHz7Z6LcJVltKMGRI6RHseAKLX01mgoZo4YatpdmZmIem-r9WBdESnIRQoQaTckKkJM3EKJkDgjbkmIgxCEiNDVIe_j5KUEmrqIYEH3CMfV0Ukh7nMreXwTHeCiIQu9EUthXMbMlHjug5IJFjGMZ41LmfiZzG93a33ajMMyXvXOxInUBQIAR4qUBy-m86Xx_Iits9RXSEvM8NKSYT5saT9YVEMJzIbUpWf3kEGzAI_jx_DxbuFQoOKC7klbYU6iM_hqyQnOvf9HsbgHYs5jCywuZV-GXSy8HFwWJcsPLBofOESIxaIqOuwaEB-zNij_nPxdbvFYnZK2gXwpaNnQWErIF8gMBCMeKDu4ZKV5isqQEBjQI4QOwKMA4oWxk4YfgETpB-GiCMhRt3c76LiX_ICDGzxXEil3Ti1EAKF5pKiAkCKw4GBoCfPNktiX2IXDW58W0eUVfizHWgwXsAAMEMIAUQoNaxpLrJlOx5oGnJxyKoSrFWECAoimqkvIWeJx0yi0eEsWHdeiMgsicvd0nsjSEqK5q5t7Qj8dkP0QhZxnWi49FmM_xYL8yuwzPuQAIDAFBbiBAzo6E5SBdbY3XvsQizx1-3opw2xea6VSHlycf-f1N-9-cO-lF1949oXnC3Dbz5fnu9fe-YA39ejk2je-9donnn_66Sdu_-w_-ief_dhLv_mbr0v3V1_9dhB84Yd-JHy-erxhkXnasfATt5948-3XPfjatWtz2-fWKRvMh48e1bDTW6c35Oj45rXddrZ51yadL_Zf_9rXxlW89MlPXrt2VZiF5Pjo6tdf-_bzzzyZ7xwzs0C3YCAh5BS8EXqEWUB4YcrZElgwcUEcKDDAKGZT6yqIVbguEc_xsz_9C4Osv__Hv38-33fvYDCuxojo3QQ5m97NanXrzq0HF4_eeus9D7xy9WhgTkStUEGGUM_BNzqggGVSG-VYDCpn7FWeM-zhaWWJLASJ1SzDKBGCmCFH9RgRzsABBodkwYWi5cDMttSwC6KA8XEKD_rCTkFidHTwRXGU68ciRRfIbKJlnRgjSeN53cBCVV3MPwsfIAx14AJZfC_Su4XwFmrCdMjj4K62EI7ND8k_ye8FJNrbjpFESm9aBglENc0VghTRbiupxMAQkjiQiFoKOZRCwChERTjcpBQEBDdKcjAk3SBa7z_w0lPX1kfmdLbbhyUtJDm-QcKqC8BAmJraZjWsa-ndqPDsRsz7aRaWy918-8bJc0_ePD-7pCKIsBmqdmPCsZaxDpsiU4_IrIHD2ZrHLgNBgKox09QbE3sEE-1bFyRk8N3lS09d8-4u8fYH9wLJM_sJAxBOTzbu_cZmHCsz8dluevfRriuAAwGsV2Mpol0topu7qkMbwP_Q9392Q_zwYnf33tn9RzsaKwu3pmq6v9gVkXCfZlf3eU58n7SubiFVZNx4Vxqim867_bBaBdPl-QQRGi6kT12_YrMJypXNar_bb72Tx3o9pnTh0dnu-tWNB5bKrWny4qap1cK1DETi5kWEmebuZl6JHKBpK0Qf3n3wqY8977OeHK9BaDtPZ_fOpNCqyKpUR0C27a4Ptexnn2e93O3c_GK_v7jYXmz3Omsg1HFoXVlYaj06PhrKsFyIiBG42--JwM3cw8wwCwyRs4cXU9Np7rtZd3PTPqu1_W4_tW677ff_rs-zDG-_9yEymvnZ-dYDRMp2v7-83GNQ7zpvZwMEpnlu1nsAdnUSaGamNk8zI4KDhc-tg0dCxhEwzM0VzCO8zzMSRVYr5kjkqqXW1npOVyGCFrrgcpRiTrG6IZMMZShFu2VyB3osGncuMg6r1dGt68fP3bj1v_33_s1rJyfb_fxn_vJ__OCDe5cXe6CI1jhCe-NaGMKsR2AgHcJKHSNEyNQS4sEQPF5_GjmlHzk69TCnpUJBTAWwMCJq3rNJWhI2N8S0LHCOaLIo5FqWeR8BSJZauctnQQYA0OBaIMBsllq5FkIqVZaFA2Idh25tszl1s6EURMlx8VhHLiXMHbH12VS5EBIJMyMicZvaMJahVKRFSVnqurd96zMR9aapAwBEEYGl0MFpv99tLy28z21YjUswaoDNjZgw6bMiHppGRgTwRAhLaZNmshWhRPhqtZ73kwxFXTO3VVgCkaWYa7oJmDnrB49IlUBdj0tWhEVEoDAQaDcWYqbL7Z6kTG2GCCklC0hVRyYRQqaVjHPvbi5DEUlRJvTeCxMCDaUWIvCl6nUD80DmQmXuLQtkT28qESHMqpvVajYN8FwQT_MUgNM0kcjcOwC5qxQ2gzmvCgCKQKb1alwPwkilFErv10EPm2FkkdZVSgJkrgCW6zC1HjnAzhmSuwFg4eLgrelqPYQbS1nib9PMl6_pgsPwLPjC_KNiORUzh-tMliQchOVrWarg7BTcY4nbyQkuorvlsow4lfax8HdSCZK_BR4Xw5BmggVmT8npwYXfmLP0RRYECywmUg6ezdIhrBiX_uJxu3AISID0AGQ5m1oBjseRwsHEcRjWfZQ4lu5hAM11OSzZQEuqcQ6es3diosDsvpZlhB_itAiROMBzIAqEZamJF7WGh6d-j1JlhUGCEOSepB9AIkgFDrEtXFGwyFCHKNnBLsqIhd2ZI5OU9BhqeBSqiVnIrO0la51QmHyBG4G7HfzltMBS3VK7XaS4K2MA-XEdKuLxOFw72RCi4KGr80AEBghbhgw5sM32KBu1XGrRQbKGyzoIP6KyZCY7LV1jrmI8YPGYL1ZpLEyFKJvOeEyYXQwSmUcbRJ4i6Uz4tU7MyExc6Nvf-fDh-fmLz984OdpwkWDkgq21r7_22pvffuv4-PjlV16-duUYzHqb2zzPPWaE5194-puvvr0eNzdvXXnz9XcuBW88cfXrX33ji9_73T__M_8Aev-hn_h9ZNPR6YYDZahnjx6tV_XWzevffv1bHPHkE3fMupuJlLlb3_d_9Btf-fVff_X_-aWvfvKV2_3-FhDmnTLG1778GyR4fPX0lVdeIeRCvBrHb7_1-nNPPVOIFdyQSESbGphikEMQ9q4GIQyFeWFfLhHOaO4G0NU0oCDWUoYKDj7NrU047_Xv__zPV8cv_oGf2J-fH63qo7P9yclKSgWAItLmloZad79ydHLj2o1p2r327e-UoR4dHzGEOVoYIxGX_AjjIdo-KJgXPq-5l1IAPaU1DubuJJy53ywHmVpEXkMewbnwAmdEd7DlIqADiStImIEcQ6Pzoad0s4wdcwfHIGILF2JVQwIgqFyXUE5gDQXEgVbmhpguagYIrhLmzOjgQBkAhRklMeDYyQnBzJkgQ0EwgEmAIN2Abo4LgjjfAhChiCAEYUbIDC_yCMbS1WftpRQkyqqgCnqmKBIAepWCqXcqhIiFBQiZIJCqMBI5eFk-RcBFVmsZgH70s6-wcYStVgKMFCEiCNHNW7fssoSouwPT0bqC-dSUBeamDu6G09yGyrdPVpXwaBzuPjzfz3pysuFAdQ_3bjGZiZCGxyGzEQ9SYybq2gnR1M2j9y5SYFlfGIQ-f-fm6Wow9fN5frSbVHHu3d0dYjXUvp_WwteP1oi4N31wOe_2TR3MXbttVkNr2syEed7PSHH79Pj3fPZT06zv3T07300Pt1MIDsLauzCaOwLs5_7g4eVubr2bI7gDA0y7qRRxoK5TESLE6WLuYJf7XtZ1vtha7xb21lv3vuvzz58M68vp0gOefv6GRGWWeZ6927Aar52eTE0vL3e1lmmetevldn-0WQ9F9tP04OzczFVtP80WOGtr2qVWRxcuyH7j6pXVUMN86np8snr99Q--8_6Dm1eOmsdYizsIBBJD2Dy1s4ttV5vU4kC4C8Sjo6OpdZZSSgHiNjcWMYf_P1N_Gqxblt51Ys-01t7vcKY735tjZc1KlaQqlWZ1CRUSIKmRwHQ3bmgMdjdu3MbYQQPRniLa7ugIOxxguqEj3HaHjQ0iIKCNGhAg0ZKQBKJEUaWpVHNlVlYON-98z3nfdw9rPYM_rH2uXB_qQ2XWyZPnnnfvtZ7n___9SpkJGkrGTAMZU8pqxUzRAwnGcWTBolCL2jynnEwVvebcfffHv23_ZK8Y435CIVXQYmpVLXSuLMlZZ7UIqKWUw0SAHqAeAEHMpVZkZAQzOwwDIkhCnWtc8vkiIqq5agOet3hS1dq6qR4YYc1GEm4IZAEgRNyAIeBqEcGSkMjUkMVUMxGCM0NY0PqIr996-WMf_vf_-L_9Z_7Aj25P1zr7z37213_mZ_6ZVw8KMIO5ZgKvBshmSuBuQUncS1sYVjPuEl32lQGCV1eeD4Sg9gAIr5U4IbMvL6mWjcZwdw9qVivm1qIkFgy8XJ0jkqSUPYI5AaKWKm1r26aOxBEKvrDYUrcyB2FhEuRmHoyURIi1au661utlJjVnwPa4MQ8grDrP0xjudS5mBhF1rkk6iqBWOXAHDzVVr7XMQugNb2zu5qv1qsyzAwHAVMrh4rG7IuJqu3F1h3B3M01916IVuetqqa3eZehmlvPKTUWQE1vVLvfcgtqILGit_wEoBFp16f6280o4AaYsBm4aXdfVAoklENwsJYllvylJcuPXdF03TiOEuQeTpJxqLW1JJExmlrgvXgAgCTOABYYbJ4aIpfDoEBBdShqhYFlEq65SP6um1Kqa1IbnHUn12Ob1YZ7AwBHcwyGGcehyrlqqhrmtuu0wDk7ecjgekXOSxGuEPmESobSc3pAYvOH1lnMltJk4LlZcBGz56mdn7qB2Xwg1w2a3wTAMUJVE7a0GS6p-4b0ghINRO3hdknl8SfE3LfmSwFmstEvOfoFFQlirBF4CNpe_vjh42w0BFw7Ps7n-AqikhakJl0x8jOYg80tu_uXaDC7_i54Riuh3KP8NinoJ9WvLhWdIQYBFZd0Co0S0ZJzalP5Sa9YOju0eYebM_OyLADQvKkQEA7XUeevVLMpVwIBILaxD6BDCTJdHXbjkD_mzpM5l4L_9NSKxWPiM7cdxuZIJRAIii6UUoeGE5LDUPBCxOa3UAwkAwwHkkrRvAUFNAuX4O9IyiCYYvtyQxOJ1aPRlXlryBNJ47S1NzVCjUkYEZ-brJ9sbJ5ubp8cEGK7RmPDWFInLBxZbjMe8Ke3aof8STR9wqYK-vJFiI4TiZZPUzN1CG6cXlsTast6CIIT1Rhhb3qDNPAOBWoSPqQk3gRGqOQEtWqqMBFie1G-8ef_O2erlOzfa7Zb7bq7zW_cef-krX_car37zB25dvUYAqj7sR3cdJ52qXrt-9f7bj9-4-_C9L15H5HmsX79_XwQl-Ns-9upP_eRPbfv8x_74Xyj1nZwTBRLGarW-e_ed0ytnz9288-XXv7bf7d73nvd5VHRfb1Z9SneuXT8-2qxi_Ol__Ksvv3LHWXAtROvf_rXPWswPnuonf-QHTQ0ZBeHo7OyrX_rKyy-8oO7mag5Acdz3LUyWWQAjMbXraOtqNxN5NSOiAASKtor2aszoHkg0D77apn_40z9jtf7wj__e3cOnKNz1fUDsdNr0K8AQ5qK6WAEcmOJ4vb5x59a9-_ffePOd483JattlxAj38PbWasVQYghrv2PUvo67MzMsIX1qDmMkRKawaDCHS78zEMByiIcAosAQJIBofB5CZJaWBnQ3RuEgi_BwQjbwZiU396CgIFziLu0-YNHsFoCCiYkUahYxaKo75GWOR9iK1UhtLtCeWIrWdgGEaI0KgNTagqpem-uDIgAsgpnbyESYqMm_F6NJM_MtLDRJTE7SMCNEHef26SaCVn5Ttcyy7CExKKB9spjZ3Szafau1ICCL3Lp6_MLZqUCoVl-u2dDljAFqXkvFZVccEZGEVpuMFUxNehbh_Tgj8qy1y_T80UbdQfjxk4vR5rH48brPgqbesBjmytQwZVzViRt3LkzNMTBANZAWO3wr8SChMLx47UTNAeF8NzT2XtP_MRMjVC1Xt5tO-FDrW_cvDmOdq1u4h187PXl8sQeA4mFadJpfeeHGtz5_a5jqm-8-mlQPk-3HedWnaZqG_Xh6ZXO86nbDvNuP0zQjAnJyt3BHtKLKieaxZublQFxsLsUJda4QgUIUIGv6xr0Hr77vpe26FyA07ETAnYk221XOyVWZWSPUNKeMhG4gjFk4d9lMa7WUZa4GEMyi4RBhFpzS5mg1zfPLz9-ch9L33TSXd-8_dZglMzidbFbH61XXJTfNqd9P89OLwQgOU52LWkCpXtXdveu7nHJghAYTW7jWOhyG1qVJfQYEYgyPaSwM3KhQqUsOQUyBxgm8ltz369P-3lsPf-CT3_3o_hPOlHKn1adSAOMwKCdi5vPhAIAQOM9FVd1iHqs6NvlxLfUwDq0FV0pxUy3apBDqZtY0OYZEXrUdpImZmLxWJsZAJiQGsOawQXUjwXbZDtVSahCnrhMWhbCGDELw5OOw7zZXft-f-In_7Z_9D_7Dn_jkj33s1fffOJuR_9__9Bd-fRx-8m__7P7eo1rVrdZhZHICRxKtyrQUQcGtDQ0lcZ2NG5iTyMyEUdqAbjnMBFLuFkcLE5MTgFVv5D5AASZwZxI3xQAHY0rL4YeYkdwNHIoWD-PUWdGOUtUqOZkZIkgnUc1Msc6pS6GGwloqJSFiV2Ch1UoswECZsE5TCAOR1spddq9hPh72BEiMlPJ02EfXoWTRQsJaCopEOCOE6eF8vz4-Nq1alFMSJqtepgJE0zBxplrGUA9wXG_dPCCm3ZBy8sAyl27dzcNM4CmzqiZKNilLUi2SOKqiSBYs05j7FSK5BQZ0WaapEiAA9V3XEp9tIeAeue90rpQzSQWEriMPBefUrdQ1SQYCU0OgnMjc5zot2quACHDVsIjwBrcilLEOzJxzKvNMPYIHAtmk3HceZh5ZMrgPtQZBWJQonfSHMoiQN2ISYWB4jdkKAJ0fdkRBBO42qqvXTd-Xqu5OLGFxGHZZuE7a9WKNcVaratodrEuSemTTsEjCy0HTPJDAYXlQEEZAyhT2rE6GgOgeHrrcEZZzuAdyOKJ6xdiwQMvkszd55eIPBmRcMq_RsNyIQRAGSxj8ktcREQgetIyQW8LHHd082pm-5XQa29aXBUVD2TTM0zICvsQ3LVXZZj6IWLYJ3lhASzRlOdy1zE9D7sOzTP-zAE4708ai0iFshUsIdHdfairPQPCLGKphPFr2BgMjkJndIjASU7gToLq3fDkTazgTRQAxRgAD2uWWoWFn3IMJAUKIrGE0WzWIyL0N-y_FwuBwiThyCAJv6aAWiDfXloFiwmeZKtUICCZq3etGWSIAA1KzlnxrNoSEPFdtPwAO1DBB1LClZ03obkLkABDGxBBobZ_RWn3MFk4BZtZQieomlIhNEDjz-25fuX58JB6JsBaHFi6HVre2yx8xEaNWdYcFhxqBbQXqAQCJecHXB6g5XEYs2llqQcoACi_rlLbigDZVNcs5kYOap0TtruO2JMGEBcnR3SysSbEZ3R2ZxmF69Ogca3npxav9qisK3CUOuP_k0Ve_-nU3-eAHXrmyXQOAFo-AqEUSATBMfnq8LtU__ZXXvv3D79urld3hyX64eLIbjjeg1ndhHJTh5JU9fgOG_cjEKNxLeun5F7_--tc_8IGXPvHd3_kvfuVT__3P_dNPfOL7Tcd5f5Au9dxfS3T80Q995Fs_6ANFkvNhuHJydXPt9vD4zYt773Q5zYdBTXLP106Odpu1oyVuSyFCpJygw-SViKCXpG5GbO5DLX0npQWjEIMi3K2WLAIQLI5oVcfUbY42gWAZ1xe7p6vs21UykQ55tHK6OS11nsd65ajvc1drSUnM1AoEAZO856WXtZY37747fOPwnpdf2mzXUktVD0BmAaSiFRk6SW34Go1axgAalxswDFqo-swYNYiBhANaUBkRURgopIZbBHKgByGlVosPF2Jzl4bGDmRAJwq3tkD1dh0CQIBWKUFCDq7sRWvCPsCoTfUBqxsCm0cWRG-lwogARjJwQgqCcMiYzJ0ZnCMCWMgD1J2ZKZwIV5D3OmOzoSMAOCF0yOGhbkRUtPa8QtBSaxIBh0ApdY7mSQRCwgp10aW5rfvOInoRBEjCqiZMrkvjRYia3qNoWaUOAihCXXEsTVmQKYcVIXT0RopoUC-_lMc3LMG9-4-3koiozL7OfOXk-OHj3apPfUZ1BUpg8d6Xb73-zgOs88U4XD06cjRVZYTEMo_DPFYLYkQQRjWNUDeRNIcFAzomEQB0XIYdZ-ttw8lhWkip1cPNgKkTIXcJPtuux1mHqUzVQxIB-VBPt0cPzs8ZqYarVVN73_PX33fr6lj04ZPD6D4VSylv1vN-d7h688rVW1zH-ub9h_Pc9v9cDQ4XF8xi4f2qQ0pqAX30uUP1hxfn6p5W3TyMc4UIW3eraljGeXrt8PO_8mu_-7u_lTwCaHYdp9kAL4bd9ZMNJYGYVa2qqunu4iJ1eZo9E7Yzt4V30q9WMVfViG1aaVg1K2ZQ8eT65je--sa3vPz8aOXeg6ef_u2vR_LTa1devLaRLO5-dLx-8_6TScfWayGiCM39ysYxIlbrzEzCMo6lleCGYSxaVI2RmIBXudZKADl34zj3qx7CbaqSmVmgTFHn6tZlqmMR7mywsNg9OX-0O_SrpERy1MfFYb3qSVK37XcX--JR52l_2EMNJ59txk681vBApVLrJnfuikSqzkxWi87WyjQsxETzaIBIIh6WmGq1BvwVFp3nQDZrgz7QuUCQTUpdy39KXmd3rhERziwolpAmtI7lz_wf_9d_8OOvrvptYIlx_O8_9St_4xd_ffeE7t17dOvF7eOv3x0OA4V7VObwuVbmtFonm0I1OiFsAkovZpRTSujmsLzB0NR4df1FRCTeEFQAoHZkElILQmEEZLHqzLL4dRYqWnBK7s4pAQAJI0sASuocgRgl57DaSGMsgiKAoHNtyEOvhYjb_13nKdzdIne9gXtAkuzgtSqqE8k0KRFQ4nmcc9eFax1mEY6gOo5IEOHCEhgkwolY2MzDFAxKNYBAYq0KgXWuKWdOZFaJqNRZ51kSSs7jYco5hYZ0GcKSEPCSH3e_DE8se9FWrbZwUAMHpMSE6ITtncFEQGAQq25dVYXAl60xAEJKqfEluZWM1Uho4cumrF6ZBcARqKGWFQAMmFk9mLOFqVZiEuYIL2Yi5BbIFOBVNQBy6mo4ERQrSCwiahoQLESIqsYk1Wo7kgS2B7S726pf7cuchVXdAwgl3B3A1XrJjjhrYWK1ulr1AdB1WV0zSU9i4anLHmEekvlitx_sopdVOxmzSNVaa116mQhuFhaA7AtoogVyFlRlXGYt2gxZssCCtIw6DcCEvjA7AwHCYNEPtx0iLG7eS1FrRADDgvprBia-hPQ3sdVSyIMIaJ8QuvwK7eR3uenDyyIBXH4QlqLzZXoFl-LvJb9_6Q1fVoTbzHj5AkTPgIOXk3-C3-F54iUPnhf2OQTFpRwVLwExC88kEHHJPrXtRvuPXxqULq3M4Q0U2BQBvkB1CJBACJgWaR8tIMMlYb8MXxEvNxLQPMcQwQQA7HHJEMRg5OXfpm3SAYhEzZrv7RkdvxFVln8xxrYLagF-cxcBCHRqm-FGRkVoh6HWZ1gEcg11QtZuAhB8WfRnoliEykDIIC4B_Uo-9tLta_0qo3BQQxoREZEQNahzGABGUIADuTU_xXLdCnTwaCxIX_4sgIU9GgfCL2k_LfnUhrPtRknICwiJMBLz8XGOCokIGa16u_08a1EIIThoI-MierjOttuNF093nOLq1ZP1ugOWvpOLef7iV77x9hsPX3rpzvtfeW7T92FW1MxdmFOSnBMjAcVmtf3Ub7zxofffkZTdnRAePX34_I1rZ9v-6mb1ws1r_-3f-1ng9Op3f-f0-HEIrXLOLAKAqEfHZ2-_-RaCv_qhD-72-wdPHl-7fT1ljuqmlSAQ5fH9p-6w2q6_9o13b2xOf_4Ln0vTMI_7f-uP_JHHd--v16uEgR5I8sYX33jhlZt1tjocjnKyaQK1JuQAc8QQYmJiXCybHYsAChC4BZgwqSsjurka1WEM47Q5-kc__fOZy__4j__B8wcXXe7RkaTp52ikeHMeztLvsF04pVrVqwlCErpydHz1-rW377799t37ZydXV5uOLwN-nTAChUVbDwhi8xW0W_Ri_GuPHcdwEGkl4Vi0GI7WvOAN47pwumjpzLRx8UI8ak0eY2I1g2Uc0Ug1GAHqhryEBVsVRbh5uELdgiEQmDHChSTc3INIHBp3ddkWtvJPOLTNExG38SU45o49nJFVFw7ppciFmhCHWCxCAJv6qrX6kbFaJQxGQsZmeGtXZWJKRMyIrWjxDMCKwMQeEAgi0v5RbZmbkjSYqVAw8w99z0eTeaNsA6FZZSaC9gfSZhDU3qSbLnVZ1GIqtesSWGjAdsWlxOZISomT7dpUBSFcjrZrt2quQOK-gOCQg4lzl1S9X-erR7IfHVsng2kq-szHYm7EjGAA9p6b1zInAz-MswcAibr3q-5k0zNTTnz76omZPzo_7IYyVDdgSUmYxmkm5mkqGubg3_mB97x07fQb7z4yoAe7CYVRZLffDeNU1E6ONp3kJ08uLnZ74OQRY6mOFBiuGkBmulr1WtU1kKCoV9MyKwqoIRNbqQRELEjp5MrJvXefnB3J-X6eNEatFqqq5xf7d-7vgZ2ExxrTVHfDCBFJkjAfbfpS1cPUXFVbmjF1ycMRaJhmVY-gadJf-uXffu7mqQI93U0Xw5D7_Oa9Jx_7jo905sIcFleun7EkCMSUZq27wzyVcnx0VLSle8DU3LzWMh0mFk5Z2sMTsN1RwU3rZCxirtqo9I4OWsssQd_xvd905eTo0VuPesT16fbs5tUPvu896FHMzs-HWup2u9bZtEaZaidpmIdhnqaqq74rZlNYOEJEKcXc22cNzJFAkOdxKrW0PJvNNUtyVSGECKvVG-xLpMwFlxNBABFQLKFo95bNa2maxcqNUV0xAokSICAc5-5v_eRf_t5v-xABf-Er3_h__eQ_-Tv_4Of_2S994bUvvzM-fUzT0_3DR2UYwNS12DyllBBJg7CBgAmsxYqIkdAsiKCJC4nZzUgAAvjoxotBRGCAwW25mRMgEAsTcYvS0uKzR5bW1k8kLagLC_CfHJCTLM83hHALu6QCsDhEKdateyQkERICc2KuU1ne6gBqSokl5cCYyhzmeZWAIKC6qqsiwjSOwNganG7mpSKEqXtY6vrwSLlTq6uus2q1Vk5k5kgMEa4K4WFGTOomiadx0lLrVAHJQ8MMiQHAap1rdQVkrLWypFJqBM7zHLFEAD08kIIJGVPXESMQB0bi1OB0AKhQG1bSI0jE3QgpAIgYmdS9rfkbGjrcIVw4uTo3SHWS3WGGANV2SAa3hUKeuSW5qaqmJH3XT3VOwohgGsBg4SmLOaTUIkOILSAO2GppxMCJABa5DFJQsEY7-WOpCkAWGogQ5oCIucWhI4yFMTB3vF71qtbnNM7TXJSFAcLdwWE4VC3sEGjWxJ_hxoxmoGZWrd3KpL3OCLiFQZuPFsAjkrC3xhqAA0hiBkprDkcWAo-WHGuV4gZLR2qWtIho0_LlpA3L-DUWavhl4rqh_RvzsgV-_FLDu5z8_LKzu9xJLv1lTM8O7UvG5pIOSkhAC-Xn2bcAi3ysDb55uRfEJeRykUHwcuK_dEpd8jrxmX54uSsQRYS5tvBhQ4ZeQkQXfKRfdpR_p3y8pJApFr3ocutqg7TEHB7YfiEXlDhc1pvbSQUWLk5AtDQggEd40wwTWTgG2SUljxAtAAnNwVrNYFmENEmSAy9lmwBfxMotauxgUDgEkK1x3htxnyDcl18YX7K6yEjM4c5MSw160aLicv8hRCBHz0ArgY--cqcHYMoU0bzAAb6ENALUQ92ZSRrGC6BWuxScIYRRYNfllEXNl5pAQGtG-nK0o6aHW37Z2r1o8TO0zjNgQN8ltOamgHlW1Qjkdvkk9JTEDJyoJazLrMP5YX8Yp1L6fnVycnR0su6FJ7fXX3_3i7_95vHZ5tVXXzw92pCDqc9Vm4KAWu9CfVYDkC987cHVm0dHfTcN8_F65WX-8hvf-OCLz696OWY6Sunv_5NPgZXtek31yRjpaHO0Xa06FhEihK7r592I4M_dufPGm_cuzg9NjdKndWbsAF__xtubo405Pnr87q3bN-vr7zx6cK_uxx_94z86PBxr-LVrVxXihVs3f-ZTn_m297-CCN2qx4iUc-6EGFm4fQBKgHpUM0QyB0I2IBcGJAEwNQYGoerhwYA85y2t8af_9t_PpD_4Q79702-JKQIBvM9iTgnxakpe3Rxco5H4BaHPyVWtWjte3Di7dvV0-_bdt-6-_e7Z1as5d81bgUiJYHHTNCmkcGMTEbZCDlEgMSKRewMtNPcwNa9vU5O02CE-Y_siAjoBmjVqAAGiQVBD8AEAQANVcwtOLh_GYMJAsIhnSzamZG6C0i6mS8K-2WKYCKC55IUFCTtiWPyLCAFuwUzUgLqGgMEU1jzvnJorhZA0vNFvIEDBEYiQGLGYEYuHKzkiOYJgADaCKjBLo7QFBBOSMEYQY04pCFISdxUSxAUl3Oi9RIGSDjF_20u3MzhiFLX22GnWPFigwEHCVU0ELXyeVRLPsyl6J2kqDoRVDYmb2YYiELloQcYrp3kYjBC1qhYFxFXfjUORlFgkZ5kqVHVomj_EUmq7eZk6QDATM5wdr7dd0lJU9WIY5-rzrH23Pt32-3E66jbdqnOzJ_tpqiarbMHjVKobOs7gjCHCs83f9aH3dAGP9-PTqSjhbigksj8MHlDdCHm76co4PXqyN-aiehgnQ2w4x67doBByTm4xDxMmqqVisIfWqWqAVxPCvu_nOlQwlpWF6km_xu7Bw0cXF9ODh7unw6HNii6GAkRCvBsmYckpDdMkhOcXF-u-l8zEUosi0zTOiGjqDmFm7QM71ZLYnu6nG9v159-6N6o-uNhB9Xce3PvIKy9AIK3k4eO9rFb3Hj8ps2uEG05V1VzVIqwUdY8IA2cAT1nqPEeoJKlqN29d356cmVl4mKmrj2PpckcMocqdHD9__f3Xn79-dv25V55bnxyxyGa7zXmDDqnLh3Gc9sM0lafnF5z46unxNE_H282j87EUdfQgmqZKEGGGFq2j761erwoQpVYwX4SG6hHOSWop0MY92Eyl7eRgrk4sauZq4dEmjwEkLCgYEV4cmcIckVlIGNwCEf_mX_svX7h14-79i__mr__Dv_Xf_pPXX3vtyZOH58PTediJFzd1dHL3WprhEpnVzdQkcbiTtEFYtM04YBsuRstxuGrzs_L62ottwM0YbkGSwoMoLUVIdwgDYAdgyW0ISIA99YCAmdUidwmJQ0eR3BjGtPBVmDiFe8rZIZAZocE0G_KZA5CEutybKZhRL67WCZuDu_ZdDgQt6hZutSE3Wp0uzCCAcVmzkrC6gztLcg83n8dBZwXy1NYUTIm7aZ4WYTrTcJiZ0jgMaMpMAIGMoZ76fNjtIJYdrhCVUlnEogI4epgHMlGiIKqmxJQlBWDfr-cyE_Om35S5pC67eZasalUj5QTgLCQpB12KlQjbVogSBwBTCnORZBDrVV_m6JDUDMMDsVRtVeeqlRC61PlSopM6VxIiIlMLB0ns7mFBzFYrBboGMzf8gqsyEjC4RuDimcdAD-u7XE0JwcIksc4FkELBzZ3QA8zUw908cRZZMHCJkJDGUiMsKDixhATFpGoA0zAzIyDVxfUDZg4Y6s6Igqyq4QaIXU5hCyizjb-BsBlp2qOehQRZw3QeuMthQRQIBAtbqtF0WnZ_qeY2ES0Ltz5WE8HGEtWIBpHyVnmHZxqmpQTgS7odEQQRwNpKIi7n1gtzdTmtt2k8IjgCYNgyxcdoUKNWA22OrIU3_ixy0-4wy5pg8bq1wV_DCtEyuPeICGRqx0yzWEZ3EJdIkOXQjoAO-ExS0H7hfTnTEwMFhl_2a5sXSYigpYMgwlveb4H0PNMfwbIQaVNGWurOSyCKL3-PFg3Coha9xJB7m24Stfl9W54wkgU8K9GatUQ_RYu8ACgsyi1CBncHz8Iei_etxWpQ2lj9EsxPy12aW5J4AQ0Fs1OgMdw6OsoiYAAeTgAW0hQEEQZew4kwEXIgBVYLdYvLXkgS6vteiMNglftltwBL9bg9ReOS_tmiSosHgdAdLBwBmaBPsuoSESPGYS4RFIndwd1YkIRNIbwpEOnx0935091Yi6sen26uXz--dtIXh7vvnH_-i3fD4yPf_NKN66cd4TwaEbWEiogk5sBA08NQ3PTuk-n5s_7l564kpNW6v3myfvBg_9a9dz78wp1O0spdZPOPf_5Tb7_1xg9-4jsd0tfvfe3a5lpYdGuu8-ilBvkLd250q5yJXnz-9um6P99fHG_JXKnjLiVzWa03IvT4Sbl59YMPOd79_Gepr_cePXjfN7-6Pbmy3w9Hq02d4c6Nq8liyHBy9bgKw5Ym4VJ9Ut0Ph4OZeoUoYNZ1HAZQYSr1wcX-0d2HX3vj8dvvnn_qy2994-1zS-kp2Ov7x_sdxBP79X_2c0b6kz_zr3_8hz45WRnHKTyEm1yLEqeUk1oMkxG6RmSSagoOzT8W5m4qnZyenJyeHv3WF750OL-4cuWGrJjDLYIAWRgwKDDQIoIRLBABhLHV6pGQoXnBWpMXsa3hEasqNezwcpV_Jvi6_AwiOMYSEQZ0AGRs9KHGjWBmAOMm5_HWzgFvDytc0knLQ4CBCJExEwQsy7os7OiwDBHaJxOAWn4es4i7JsYIVPfmN1AzanQFBARKnJrVvG1ImRnRAbn9nE2NhRGha9wSQgAQJDVvMK7EgtCYzpiYm3M3MXtEsUrLFwSHyELdKn_PR95_NXFCDnarlYWJ22PII4CFIyJlrnWZSZuDcGqsGHWr1kxx0KwRk-p6ladxJAZEKKPPxQCAM7sHtOUQkgd0SYCo2bIMwqpVczflxG5WXVkY3BLB7bOjTrJaLWZT1WlWSikA3n5yfvvKyaHUaZwDQCSbQ_Fwc0Oaal0epRHzOL588_rVTV_Nnk7Vkfb7Sc2nuaz6dL4bpnlGhLPNdneYL4ZDSnmudhhmYQoDQKtF3VzVMICIxnkyh_EwswDTdqozBAihGyB5mJsZecyTDefT9qhPghfnhwZVKw1Dwjgc5vOLoZh5wDAPjboT7g0b5Q5d35v50WZlHuNQqpkFVbdAdLdqqOKvvX1vmHUoxQOGYX_9xdNXX3jOHeaqyHTvnfv7w7w_lD4nMzUzM0-SyzgZwTBNiKBmnMRcw7XO9ex0c_vOjQg4v__k9NZZnWq4j-MUGClLgEfo-eOLH__9PzgPSoxqMNlcLdz8-PSs1HnVdXUsxPT48TkSemBK4oGH_TzPk4bXokQUDuGeUseO7QIQDfwFARBaDdxMLdwREBxMtQEnrBQG8DDiBZ1NxOANfm0EWOYqkgCpkRLNI3cr1ZpTggiImilPNv_RP_xjP_gD33P3wfSX_-pf__mf-8V53InYbnewUpsR3E3RHBEDDN0oSYsLIwQGhlrqUpu6gi-LxJaSsGoIDktE2SUQW_OsAYERSISCWFXbYydJH1bbqN98IXwFaZPsdF0XAISY-pOGgvFJiaF16hychNWVJUOtWtS7QCJhsmLERJzmeWYRTKBFCWmcRu76qF5Rw8O0IDgGYBYIS6nXMgECkzgAExuiu6363k2tlHzcafVxGLtVD4GzKolwSm2egQHIZOGIPgy7BqO20JbtlURlP0giq2qGnNAhOFOdx4blaTDECC9zRRH3AKCc0qSmpillV5-1UGovHFEzYl4JI0CQWKP-26zk67Rq20y1CANmlsRmqKEsuYZLplk9IU-mU62py-bmgdJJGSv2WCwSARNbE7m6IrNInueRiSQLAwYwBIiwsKhWBEMmU2BwyZIYGwfNMVLKc60OwYEQME5zv-7VXdDdQxRnmIWIGTKThxMJEJfJjzbJMYTFwA-TdSuAmPelgMfRujPXbhLOmQLmYkjA7VStDuQGBkDqgaDThEKU-tR-b0pxV68aLRaLQOAeoJK7tD4iIKCg4GYXfjbK91Z7hZZvWfIhWtUX0M9y2naLhRUaAbQEqCCWxAssk9lmMFvI2Uvc_xlvHtoXaTM9uEzaQCt8N6Ruiye5LcYuXHxZ7VzoEe14e5lyetblDVg6Apenc2ilBriEHiG2h1G7pSyNBYUIUPcG2yWgYGR3RKjmS8HH_BIEHpe2OMQm2AYgYFwoRhCwJAVb2ZkIA4IBAkBxsaE5IEZzHCuHqDd5aSsOAjhcUjnRwiDAHZYP8pKloUYeLz6h06LKdlerjOzQ1gLLPcvDmvOqmhGiqhLJwszRAKKlR4ut3wGIZBpE0NwQLB5OzHSUoutW0u4dEeiNEhVhEejuxkKEhObuYEQK1rjE5hEIGtgxRmAmMlM0I0RrLCcMirBl9QneOhIBSKDW9NVAiMQkAH3XEUQNn6bi2MxrBgAp4WJOowiAMk6Pz3dlrgrBIjfvnJ5uVxhx_-Hw1dfv7gd4_3tvHW16QoRGfkEPQPWFZDiDlrme7w_FIhjv6Xg1rdardZ0vHj296DrMvb_6ynNZQAMmIZDp1oef-_U3vohXb73v1tF3bj-c8orCJ43OtACenG6v37jy5jt3D7uB1r1O4_13H915-f3liaZVnz2ev3ZFiYbqb9396hufe_jVr3x2Koe8yp__2U9N5_H-D79vf_4UXSSlX_6Vf33r7Pqk09XTszcfPE0Og9ZxN256GmbTUoc5jnq5GCZkTAxuESkdnaw2p30EZNYeBW-evfsl-sZb7-x3F-PF9M7rb149Iwencv65dz737S9_tAxKmQMjqmWihOAAHRFm6hO3M1ZiKqYdyFQtJSGMqOrgfU7f8dFvvXj86Etf_XyH8L4PfXi1pfEwgXticXC41H4TGBIGPkuHtk8BMFHbNIIHA1p4ZvFo-2BQcyYgQl-kLogQguRhGJFZqpmImBpSsC9J3iUZiEEsYcAMEORgNZwJCfmyFxQtaBDhkMjVGtbYPYRpVmuVSUNHAabkXpdkIzVAiCXOaroATEATpskcwAGdgZyUSYotqz-IEEzhus69LnF4RKFa66pbe1jj-i9P1RZBDDQ3RkyUq1cC6RItDs0m-mCCiOfPNlIbd9EksYN78QZCgACtzkR11sbQhCAPKKYA0He5Fs2MY605iUPkRCcnfQJ-ehiYEqpNcxEkdy-je61Y6m4PpyebMI_FP972_7lfdfNcTq4e12rWyTxVc4fAs-26EzKdzZuOIDhJSnQ4zB968dawL08vhiyERNXmJxf76uAtSkQw1tlLvXn97OZmc-No-_jRwGu5-_A8iQylgBMwHoZyMQzTXPtVvigzCLOkcZjb405Ve-weDVOpvu5yn7OwuDshEYDWWiUMPXjhvDFCGM7TlPLatCbk8ck8XFTcZBRxRGOsxUpolyT3eSxTv-qrFyZeSmLCc6lHx1vw2B-mddcdxmGVWK4c7cbRp5qCHWAscX4xwIW34Vq3xt3TQ1T8_T_wAzBq1_Hbb77FQh7uDlOZcYXb4-2kNs47Da9W3YmI5lLBHcm7nGe127duMcXThztTn6fy9S98jbgDIuxTxgwJxcCCP_ET3z8-Hfe7gdOGXbFC13d1LupqU3lan6h6qXW12c7TvF331RQRq1vOOVdXdp0LmrMkiFDwOg5tvBZuiDRPc7i6GYRLTmXWlJK5AYSruToSeLUQ6zZrGw0g3JUYEcWrppTcW5U8WMTMmn3L3RMzEaW-P0nwh37kB22e_7t_-E8_-_lfC57HYZqnqCU8vL27RahOFVSbMxuQIMyXXl5QYq3tCOstjAAQJOyKzL7ghryGh7AIEFYNAsZEYMaC86Sck0dgcEAQcwSoKacEZkgND95A6iFdD2EErGYMwFlA1WvFLG2iC4FhyozCWcMQyao1923TI7sFCqeuQ0T14sPILBHmpiQEFil3AV5rJDBkcEOAQBY17fpVKbObg5OGz5NCAIlYC0IEgIUF1Fq7Prs3R_QcGF6qsDiiqknq5mkiFBFxrSzc_A4wOyeps_Z9NldvIlbAlCXAJAmEj2VGlraVlC5prcIpGEKtHfkSIzA7YlTnzKh5HKfIHogijOiYuN3dVdteFX1BLLi6Fw8QAogya7delTKTUAltjtcmGWyOdzV3qs0QnICAGrY_cCHKwTRr32Wj2kIkqgYBQjKbiqMjlrlyy4cSzlopkVXPzLWU3GUhUtMKLoKHsWzWyOjqxMiBlDip-TxBsTGLJIiasheiK1TZ9KKsuoQQ5GRg4QBAEC5dV7QyUi3eJ8HqKffAaAAWTtzGtywMzGgR7MYpESIQLqXLNgWjWKg7BK7u7TzdfBENwIWBTGEtEu8RsJQ92znTvTkFG2THLQCbsiBabIMW7S42mfRlVic8Itr_4q2IsED62-s_Fkbn5d9sgU0Y1Eb3l_eKuBSDLW3lZ9h_B2QCDwKo4RHgGG6XACGP9oRiXEw97WrhAYCOy568dfuDgryZcZdQyiLd9XAGfNYsgAgidmiOzMu4kbeyyOI_XiJriw8LAJiDKjgTWpB7W60sgRhEsGYUo1byjjZGcQdkqKoJUzCYNU0ZtBSWQwgjOVnY8m20ZzCzuxHJ5bdLicn-_2oPuNw_FrmBewA3xRKjpBdeuhmugEJAiOForbfc_IbtcoK-xLXbobyZ0dplo1jlidZ91naMI2IIBwJA6YPUcHlGPIPQhlsAPhNcNDyXgIc1HmxLUVUX4dYDDwXHMIyqdbSa1x10sCK8cf1qL3y4mL_x1pP9oDeunHzLh4_JY6xRa01JnMIBS_FZ1dUdakR94-HTLXVd1z1-eH4tcD4MX_z6N-YC4-SrNQGsrp_eWa1TyslY3n24W52evri9-jf-6_9H6elmyu-cP-S8WSNMT3ZGRJPevHHj-u1rc0_f9p3f8taX392v7Oztb_mbf_1vETw6f_ToyZOdaESQwbwRHne7WipTRx29_lu_8ql_9DO0zuuj1SrT0_Oyv_vW5mhbdT7ebjdH-Szxtku1Pxotjq9eWa03OpYX3nvHrV47OuuFwI3Dq4V0HXZpHPSdN-4_f-OoO8q_9anPfubTn8thhyf3d6Ucxvp_-nN_6a_8jb984_ToYhzAA7zk3DPDfjf0Xco9u7tQSCfEBCWKali4OzMSUU4M6gzjzRtnt27fGMfymc99_sm-_sDHv21zmupuMoIAAQYDSyGBrhaCYEQMVNuajKLtiMwAlm48EIA6BACnZUtGCI7Qai2q3jBT7tEYxIDgLejjIYzWuihIAN5YUxGVgDpOHp5INLTdPVqajlAcIrPUaDM_Q6BW2CXiiHACNU3CatYAE8gtpaMEEQwAQYGmtZNky602ENlcmdAB3SwRWXgLcgLUtvF08MQCbol5tpmBhHjhj4TnLteinHjSOQDQl0WBR0SECJHkk65nc63uYACWMyfA2QCsZRic2oCBiJlrVSIiD3AMM3Pv-nxxGE3Nifqcu8xsZB5IbAEWOGkwOQCLIHS51BoIqtb0wG6OCF1OQGwAnUioXj3a9JnffvuxulGSK6fH4V6t1DAA3GzXw1wp4MrpEVk8fLJrz_EusYZXLSRZq65EAkmHYd3nm9utVn2429fq4zTth3G1Wu1207rvJHfDfhyLAsDhMONVmevoHsgStaopcXoy7M0hMxHQilgdVKOaAlLqUzWzMIxgxFKqVyVDSatapyQbo7hy6zhnVgOvLqtUqkV1BqjoqC5JqlbhjOAWKsw5SZnrMI3Hx0dzraXOTy_Ga2dHneDqZMswXRCp-6DD8y9cefvNx2dn_TTV1Sp97atv_oHf-4N5glDwhJjzW_cejJPPasT49P5Ff7Rh4E2X33zrgSSpVvqcvUthut2uweL09GTd9_fvPaqlQESpUxmm9dW1qSNEt1qpVcwwjvHhOy9ePNh3PU-H4ezoZHMUTlC7_tGDJ33iGli9dn0fcz05Pbq4GB1hqmU8TLnPSVIWDwuvxilNw1DcStHVam1ezR3DWjbBzQwsjIG5em2QPQfj1N70SEBWLNyj1gW1zhREbp76pLMFoZsBYqh2m02pMwYYp-Pnb33fD3zvJOuvvHH_Vz77WR1rqJtqhCFcvikNiNAxCAmJPZwvC_HYAIBdBvcW3nM3DACSWowbS7PBIbJ4uDRihiQJBFPFAA_sVt1CB4doWWhmIaLwEOIW-3eM5ZTgTkicUjQr4lwRkXLvBO7ASSKUFho2ETEBUtc1dpK6I1KSlhW2Bt3jZp62QBYzY06tthim0As6AwemhAF5tZ4Pg-SspUBYuI_DjkSIqValRAhETK6FiRpSCpeAMnGiWgpw4tSp1pyzmcZUJZEtNnf08KhK6Ka151zdDYyJsDap2-KGAnMhnud5of5ncTBJgoClaAVgAOFkutBuu3U2U2CpZjn3pgWQicWhIBAQajWSGMYiwtWaeDj6Lpkqk7ja4oNqnBTwMAtCIfZqnBgSm5mJARM2Fgq2MiGVqikRB7opEGJAgjSDmdagaPHLCGqwvHa-K7P2XZ7mmVa59RH349jnNIxTn5ONhguTp2buyqRaZ1ixhuU6Ha9XWqrsQxhrKULkoU4IEaUWBJpicjOoZG54vI4Sqx4YmTebCB3nouZdl4dhBKJ116_7LhzRwzEA0d3h8ogGDhGKzNAcVO01dDn7RyKrbf39jGGJHsGELZlu3s6aEWrErOYtWs8ttANwqTALWP558ey83ib08WyzH826HcvYi1q6jtuxuWE9vOljFxFBOyAsX-5yQR-NAwvQPibo4QTU_lCiZWUQ0LGqIzTNnjeJDiE6AgFaLAye9ovauON42RGGVgkS9NqCaQDIgSGYzLT9yzQ8qYE1pXGjkZhaIxsSkoXXFuJfYkfLbbOBc4AJGdAwwt0DmaO1diPCPRGZOwbDZRqtof1bMaqGtqtMCx42m0kTtS5QUgT1VmQkJtSAVqkxB0JQWmBmWougDDDrPHO_BsMmYGjpo4gwM8cICyYXSQvUGQAJTdtdsT1acZxrOAYoBErmTLj8cnj0KRWymErzG2C750XDx0IE-KREmHsCjFrrDKHmfRJLAAEW5IDAQIiu8-T2dB7Oz4dVpvfevoLj_NV3z-89Gjar7oWXzk5XYhqDeimVhSevADwYFMf9bq5mqqXUusl5dbydhqlL6erV41WWyTSiqMBvX-zf-NxX_t4_-MnDeLh_MeKFS_EU41q68aF1q_4tDJeY_YmmXlBWHWgn_aZ_8-LBr_3yVz_1C585n_Y377z0W7_yufl8joiTk_y-l19JKZ3ff7i7OK9aE1-nrq6Pz1KH3_3D3_W-93_gjdfePr1yev_x7j0vvmeax-Ptus9d361qVGTE8GKasIVf2FCRWJaWDKVuHRYxV-lWTx4-gnn1yp3blXQa42Pf9dGPfdf3vbl__Of_5P_-D_-pP_nxDz0_DtN_-uf_0v_lP__TKGs1BGA1mLWstmvzQAgLQsCxKKGXYutNt7vYr3On5iuhWmbpe2J2cwI72ax-5Hu_s-7Hn_mX__zz__pXf_zf_ve21662zri7OQIgiQAiRrUG7CJBdwvAFqcEAK9OCE1wERHt1Qtg1ZybjxgpC6t7w0gWrYnJMYwXH6B7m6ZZG3-YLSI8oKWv62F8ualMzNUNsS2gqM0LkqRoG0YEBe2QJ7MWkQ0IxiBBc2RmBDc3iCZmidRJMcMljUeqhZHUPYkoBjZWOvKkE7M0lkNCZuKqJUsipEQcAaYunbTnNhO4G_Ly3CxRJWUsKpkjIqy8cvMlAU4dD8V2--GY1n1KRFy1CpqIIIKZhwcLRo1m2umEzRAChlmJ6Gi7drUrp9uUmQDqXGdjR5xdLdoVPjoRiGDq9odxLmXbdaauZm7eqhGuSu7CuOoyI16_esYJLBAt9uNYrKy2q2lXtJSc6Oz4WOf6eDdMbutOOIkCdpK63F2cH7YnG3V9-HDXb_NH3nfn_oNhHOb-qJ_ULvYzEjebwaT1Kq0fjqMGaDW3uPvoglyHqfTrVYa86lZTKUVr457PteScKdyilmrC1q-Ta9qPY8tclTqbK8pqHIe-zwAw7MvVW2KZYq4pYBimTdftytwnhiBUhwXDZ-Da8OVHIlWdKR-G-fxigKB50jfeeHjl-hFJMMl2uz6_2KtiIH7Hx9__mc98WXVW0tNXbvzEj33__HiHBPvD7htv3NtNw6S4O8x5uyoXuyPedium6G_evJISP366d4TDNHGSo9XGwfu-L0W1TOq-u9jrXKHLpWrOffZq48xsmz5_68e-yav1OZtb0dlCs2TjmMbKzNNUhNDCfdJiWgc_DONhmHYX-_6oG2sFwFLUEbnvdhc7InY3zljKgIhmdrQ-1fJE3UGIguei_SozyjTXAJcsZfAwa4QbAks5GZNrhQZktGBJGJQ7bJ_zLuWI4qBCvDk5e-l9L_xb_-6PfPUL35BVfvzwrbGMyBxATIgViExN2-syIrcyvqmDObFHdUyM7gigqi3Zg4m9mLAEOFTDlFqNJpzcDNwlPHBBB6IwSspalJmEsTY1FRIzhgKxIEEnHbKP0ygiDbJOJEnIGt4EEVMOVGKO8AQEhG5opXR90uqhlaU3tZzzXCo2ZkJYuLWKIRMHOAm7R3hFADDwhibspUxlc7Sdag0L6Tq3utpuVJWlSXfcAWyeg9HNwYiI-tNNS9sXdcmZIEotWpVFKIOrc0pdSvM8pyYjBGjdUoDQqkISQPNQo7ssFNoCS2HkIByHp-vNtapFUjuDgTsAcZJQd0rk4QTILI2PhkygjkyBIZKAApiJcykagVbUJZm6mRMFAAmJh8-zi3DOuWhNKWmpCDSPc9ev5nk0s5So61Lj9rsvyTlw6Lt-0BLqnJjaO0DNAiSn3XjoU3ehByaqpujt_uUESMKN429hyKSuFV0DEvNUtXHpIaIcppPjIzUrU0XEWHvB2dV8nDZ9KmZBPk9GAQkwAkCiMR-qujsgqwN5dSAKgIv9sOqEhY7Xa-bE2HX96jDsET0nPlmvmRM4tVkptPKmP2td4jNmP_pCiQkMq96SKEumBcBUG94Gwlsq_bInjK0MDYHhzkQYsSA-8FIwe0n2DnUkXE52sHwD0VwTER5KmACRsC06Y_HIeiBTc8C240U7gEKL6CwmlFZPoKYBhUBvO4hG9FnsA4AITgCBAc4kjfizsGbboTSWvu0lkrx9Y0vEs-Hn258vWHBjrrcTK6KDtUSDO4K3Yz0hBSM3_IWIhDtSk5q1X3v1IATyxjVhaocCXYKjrawd0bYY4dhumHAZqWqG6cv-g3lzEjNAEIi3iH40cUSTgV4m7JcTFWhrFyBYuDD4cu9yi7AgElTDo7TigPDGZA2hyytiu5e1sakHECATqLbxvzYDmIcDRljCUHUmAINjykbe-pLFAxFySupuRYEwltkttDsmIXarVBxiHrR6XlFOyc2hDU8FiBk8Ls7ndx4_Pb8YFPz9t85uXztWtbsPnkb4Bz544_iIQKmMdXIMghGgx5irBuuofhjnCDPVVSdHJyu0KGxP7z89ID56bbpL8nd_-h9-_SuvrXaDTpFQybTP9IJId9rtzvcspzFNo5b54R7yuqhDLSTHL33Ty9_1vR_68pvDn_vTf1I36f_-V_4_Z8eym-X7PvnRa2cnm1WHDsPhMJf6W1_6-te_-I2nX_x0xJUf_kO_a31yBMhz5l_-2Z__0Ec-9tHv_b43vvHmyfF1Pj3Cp3hRAzKgUCgJyzwXli7a5hIQMZspJaGAjhMEzPOs1V-_--bnvvKbP_vpv_tX_-f_1Y2z_snjB2XEAcv5_Qe3n7_6yVdurTZ9tz7-0PPdf_oX_5__h__N_8wp-8R9x-NetwTQ5Yy6vd3jCg4AeijO104F3thvVk5fffsuQ7p7PsGTMpw_SZutmdcohPLk_tvXPvjy9Bv_-j_7q_-3eLx77wdf_R_9sT-0OTpGVvam-_WUeHn7ekAgYTgDAho4MfLid3Z1iNZScc4ciGgGhmBuBsEIbiqJKcIdhFNrRLa5RsdJXVtjtym9VVuYtv0Ok4ESQgldLLZEAC7E2nQaFkiBQG5G3DMEJTCwnjvV2ijK7V7BjATt08RWnRroO6CoLu5rZmuzPxL3ioQ9ZSQyD1pkIdHnvrg1HhcAMiOEswhicHAFdwdmNA9zclfhNmXg1Sq__NwZWw1UEeq7zgycMcKIQD0QXSgxo4P1KJZjUjV3DUNBVUVK7Wl95ew4IURdKE5E1J40krKDY2BRIyRh2q5Wc63VvVYLQg0jIDVz97HOt07POsLqlsgJMxCeXzydvW663GO2FOuT45x5d7Hf7cvDw7BdrZAxIOZxOjna3Dg7OdqsyTwIRaPL_eOn5e37T9c9z3ucp1LUzy8O3Wo9lXJysnnz_qPz_TSWEghgUetsamVWoJK5I5JABQABqIBTVT0MvSAlToxJEkcrgUiYY4AAAWeI2q07Ai7zmPr89MH5Q06nR52qoSJEZUxB4A0s5QAWUx3dlAhzSvupJGZKWMc6jRMSn13Znh_Ge0_3OcnxMeyfjCfbdbpz9uDh4Tc-_8ZzN6--8_a79TB99wdfns8PEjjF8LkvfH4oUB2e7A5VrVx47vOTJ49Tv33hpZv5wcXj86fXr53uD9NqvTo7OxkvDvvdRfEWzAx169ed951xaNFANas50f6i_N5P_hv3v36PHNM6Qxn7rh-nsu6PHlycA-Jqu3708El7lTXv-niYh2ksRTfHK3M3M-IUWAiSuackOs9ZsFZRrEJg1ec6WERKWasuCh0LYG7FGAIQRgvQ4nndeWgtlUUoZ50KZylzaXXhnJMQowSEq5nPePuFW9_xg9_33J3bv_Fbb376V776u37X99w_fxzVpO8uHj_hcMLQWZuWx1UhBkQMinYStWoAyrlrg01EIUJ3BSIE1FK4SyBkWhGjTR4BHAAEiBciJzc9G7AIEFudEQlaaRGJBMBNOAOZqq426zZdkK5DRzfLXTKIuSiJBGEj5UM4IwURph4DJFPHPZq34qAIAKmIhIK6RwATBYGpkyMClLm22hOiVPeEiTPWUoTJzVpeW5IA4VRKiyexGyM6AoiAR9dn1yo5sxApHYbD0ekRFGVBVRNJjsXMSYgl5SylFHcID5KGfmdiAjUggHY2JnL3WT13GSgiYL25EmFAKQhVa0oZiUiAkcAd2dqwWb12_ap1KakXCCDinFIxI5GIsPCck7fTAKJWRWbH0FodIudsrvMEnBggkuTanORWhZOqqSkpAUTOvY0WZixS3Gcr2JzkYcwpWl7f1M1zyua1auTcM7ObSRPdqwcig-hk5ppTr20RlmLUGQQwcChlQz0QllLHuW5WXQ13hHGaV0nKHBgqiR8-PZz0KXiVBQWAQgTAAoip6Sfnw-RA3vJks7lnM1v3PZE6OEfadCtkPl6RB6IhEXngs1N7wELoRyBf2KELar1RHZEw2gsYyMDcHJCXYEwYmCEvdt6G7mvbgFZgWRrSzc_V4F0EYQ4LI2f5q-gYDQvbwvIBzSQLy6E9aIkG4cLf9RaDWTABsITX3SJ4iSE1cioikC9_Gm2uh4ueYEk3tbAvNQ1Z-8xEgGm0miyTaFQOCICGMCeC8DZibT9Ab4eShSKK0XL7AeEe0g6uhBjkbgxo7V1-OR9fzEjQoEBslysPEdFaQcTML03J5IGAmomrOTK5OhGbWzvsxWVwqC1Y2Zkg1CPcMFEAtwJ3QxSxkFuEAzK4ATMERhNomTkBA7eCBSCJuXHHFeA7PvByasYIACAnCkSjS1GEMHoEM4G3ZhA4hBZrNXRYit8BBM1YBGAIcPDSTBaASERE5NWQKKekHoxkDt7yvNA-hT4e6molhFUyaUFEJiEDZ_LdNH3lzUf7p_vVtn_vC2c3r246xmnSh7sZGPtt726PH-lU6lTKeH64-3g3K5wf5qfndrJdB4YwbdfEYJT6r7y7c63_6jdfx93Dh-fTq68-P-7G66rvf_lFuH36_Z_4xBf-5ad_5h_95tXnb-P45DA8PH3xpQdf-lxw6a_e-EP_8X-iDx7eeeHGBz_wYgdY5_m1L37pfS_HpLu3X7v_iW__5pfe_8J__f_9v-rDD_WnV7ddqlNZXzmJcRqPjz_yIz_0lz7_1effc-vWC9dS4Ji2vtt9_Me-5y_-tZ_68__eH7xz7cbT8bACpFUH4QLQRQCS15oRErK7a3UiTkJuDA4RblyYqM_oFq--dPMYv_3HX_rwOO36Qwqgfei674-ubm6_72a9vr04H1-43n3y3_zRn_q7_-Qrdehce7PDubz5xa99-Z03zp_e_dSXXrt4p_SJp2k-2uRA7lcyHuLG6ebdhxMDDJK3gk4o0h-Att3pWpKk_slf-9LFzj7wnud0Nd0_h__8r_7U0e3u-7_no9__Te9fETYgiRIIcwCBuocnloAgoCAwd_NwcBYkp7CIAEEw94TUynqpUaeBIFCXMKAzgUEDVQCAi7C7N16Sh_c5GRgChQeidyLhTpQ8rI0PANHMBUkhgJyBAQCJFZQIPBjBHJ2YaYEUo4Z7BDE2hoQQqQXFsm1DDGqgsRQdpKJFEB1BiDEIyUutPYuFI3hmdmh-TO9YrJkBwyadJXcIwIGO4K6EASRg6k5Fq7CjQZiP0xwYbqbhzIjK7j5qWXXARESipn0nGtFkgugIzB6eUiIICIWCyDSqjodz7HotFr6wa1JK5qFRIFJKrM6l6Fxqt13VwZGBGkeWaZOTzpWZnEnrrAFzLSljylyGYdNtshCYPdpNk1oEDHN1j_U6qdrTd-5tt5v1pieA8_OBSVYr-cob72xW3cOn-9Xa3UEDUt9NtarF61-_a8z73UACBAwezKIWKBwWk02tqqEO5gaNfIfqJGWcIUjNgWKY6zBN6JCZmQXAkIUQqznn1OfOtR4Oh55ps-5SLxggwqXOeS2UYNhpqYWgtb1lndNcVZB2w4jBDjSO07qXi6lM4_zW2_vQebVebU-Obty5tl3NyOu79x7OHtuj_otfe5N-GPfjiBTHp7dwXd-5_ySI9uOh6yFMV13OiY5Pu905DTkN-3Ln1pma3zpef32YLeVVkkNREsnIHlx0KvtBbb5-46wkl8z_q__lHxufTHc2Gxeci203fXNIms7MICmN85SzkJNDEKVwnccBAqp71CAExjTs9zl1JPx0PLgGIuWcHUp1RaQ-d75oTR1R1IyIs-RaJp-cCMwLCQMIEvKK56eziAS0kJ9YhOQMADmnxESBOnus0pXbtz75g9_96gffj6vus7_-2sXdB3_mP_jh3_jFf_7P_9W_3u3OS4C5eYvjCVlxAkMHCgfhcIulrRdgGMHu1uZxzBtCs1oJL7EfSJKSToODRQOVIQqn1Dz1TOTmlMmdDAK7DNVJwBGskXCTIAAyCUoiBkYiRwaW5MoiUueZCElI55okaakiqVZdb9YtAG3mrcKQUp5rAQ9yqNNMGUnItKmjrGXxS50bw4eSmAen7BiqgCnArevXqqXfbBvsj0TKVJgJPaixzJmYiYHMAizWm1WZ527Va9XUJXPAqA4YwYBkDkwMwCgJI9AdWdCty8nVYokMO3K7NhDmBAClaMqSJM-1mkff9-EOgKo1SXYEgwUL6QopZw-XLFrNVEUSMztzeOTcT_PcYmRAVKqZuWsNRwpGCDe3qpISQPNNg7o6RCJxt3ZsS5LbV5jGsc_Z3S1cEltE41UhMgS4eUFEIK26zqsJZqKopZKIh89mKGQQ01RX3aqTNIYzoINEaCnKgqgABCIJAMukuzpJ4rEUTjzUmYXMPFNWjIN6IOJcKQtyCgCbi4cBkIFHgKqHRdUKSBHarbupunp55_79F-_clNxZia7rbDEOE4SbQdBiL0aA4EA390AwWALdC9ITigFTXPIx2_RrKdk6APkih1YjYYYgxmcRFIBLbrcpcV7UXI2R02b23k7M4LgYBSIwzK0JNGBxBSxcoctcbwvqN9pdg-r4M_AQLIiB5utsrMxAMAcmsgXzb8sFp90QcPET-zI8Jw-nBRUI6hFYASkQ2qm_HVODHFtpGH5H1du-H_dACiRyA2oHXqflsN92K0StDktA1s7sFsjUerQIFGGNmdxWK-0wbmaBYeEMaI285NF4SoTsGi0G3bI9DUxu1IrL3oi67iYMgESAbtY2Mw7BQCjYKC7tp9cg0w2f1G5t7LHeXtmuuy4RGZFLhBGHgwFAdQ3XAIjZ-i5hgLkColZvhMUIY8RgcoiotV2eG_CJ2w92ifk4xqIiIohomlNHgCAUB3CwlKETTD1FOINoQQDAxG4xKb7xjSf3Hu578W_9wJ3TbQfgddK3Jn3z_v7Nhxd9lpS4Sxs1KF4eHIbffP385R5evH304u2rp2cbImRyQqhe37y3-xdfOvzIq7ePjro_-IlXau7euD985ctvvv-l6-u8Oe0FiUi6D_6-_NuvzX_6f_J7AmHaz9vt-s__qf8kMt258_KH1ni4caRT-cy_-Mz7X3muWvz2O5__gY__ELBwSuv3PHd668qf-nf-7D_57M9-mF586_W3bt28Ga6__vkvvnDrhYePy_r6rWGoV0-udEfbojRsu-eH4cUf_tjjhw9Ob_hx37vVFaNWz0mwVnc3LZKFHCHAa60pygi1Qt50AFymylFhHlHgXjG9uv53_-Kf_aOf_As_99q_2qw2P_zNH7ni98srJKvVbxzTa5_6cv354dO_8EtYdl_8D_-8WrisKMVKhLuE4UcVTo_7Mrmv-zB37GPKV47TyZVr3_79t7lb3XnfS1un60f88ss3tDKKjLuCQsNYjk7Xmw2h-zw5zEIEf__nf-G_-cKXn7t183_wie_t1qjDpG6G2AsqiGttrfJFTuKLbQ4ggsGbpS8gAJj68Lk9qdqCskXdwqE1_wiwMVowQoRNLSCQqXGB1IyQ2xrQ3BFLQjY3jADgS2G5J04QgO4NOgwICTE0BCEAbIkwOjHDZcoxMakbMSFBAsa2aQxADgpU1LaXWxwuYGHeJeEGHGtPawAETCxAQIHuhhCcO0egViM2oETuMZuzQ4D23UqYkANEUi2IbB6MQEiGKomE2NXAnaShiCIzekhDpLRdfVvJbvpcx1LrbA7SbyXBPDkRElFc5pwBwVxJkYlqeEp5dxhPr5zcfefBet2Z2dl2JYTACAh1LtWjRhxvuuOjlZawVUKCi8P8xjsPSkQNtojiVdV247hZdcMwI7N5BCdDHqo-vnd-89rV-xcXT3ZDAbIA01CEi3Fm5EoMgAZmDkzQ5_Rkt4NAqxVytxvGlLsaBghFre9y16VSSpmLA-SUpmHcrHtwyEiBUOaau8SAEW6thY4IDF7x_DCUMt-8enp2dpwoYbsRFRunqKFI0I6FjLifJkYci08HPTk59oDdYTq7dmwaF8O4n0Yzr1yHd88fPdzfuH2k2ZFFvWrE62_cgzVM9yZKQEBXr1_bFSwsNaPPOh8qUw6wl168dvHufvPc6jDMRKjmF0Pp-pS742Eo4zhmYe7l0aNzN40Ir_XpgydC8L_49__E4dGAXm7eOB6qjWMZp6E4GPGkNcJBqf3yI-JYVavth8EsAoIFq1WrmIQBqO9kv58AGVAJMKzBIQTcCalaJSJEDFasYYjGoNVTs1zYomsEDwrilL1V4pmWuAhRzhxTcbPR8PZLt3_o3_zBm7evI8y_9qu__kuf_lzI6k_8_u_-zu963xe--MXXX3sTu9V8_hTQw71WyzmxGIQDODHXaihMwlbbKwnDKhCguUeYHgKW83o0IaA5CANJWOUuRy0RIe2okfsOwJEDiIHbUSPcjRkpZwUCiOqBKUGjGbQBG3KiBEAo7FrXR5txHE095-zmzIKAIgkQzIOTuM-SCANqVZGMZORmFTzAzaXLkqTMHuaYGVAIwaypVgIRMHNeJiSoaiwJPJC51FlErBpGhGM1ZUEWCQhMTB5lnkstzNSt-obB4oRWnUQQiJLUUqRL4VGKgnCS5BZdt6o6GwSL2DSScACklCCCIhrYFIDUK1JgYJ1VuoRETNym0gjkbXzIiEhCqOacUvV2bQc0J5FaZotwADYNoGqeui4RlVLBIede59EwAjzUJEmEQ2OhBEaEh7GQak25wzAiqbVCAEoax6Ffreda0R2qYddBODLWeYal8RoJGRyKaSdpYbRrpSxTLQhoWvcOnCgzE9Nc5pw6K9bxEWg7RdJUlAUTAUkCYIxQih47rfUwqyWMarFdbVepF24kUXOPwOKhHhbGEhE47A9Hq3WpZjW2693Na4zAZhpB2Hq7jfXZAIvmwAsYYyFAAkRA05ITkhMDthgGRoCbIUE7eBKTB7RZiEFkb8c1b63eBfgPEe6I3EB7BIGIzWa15H0AzNu6bDkFImJDD_kypOcWfVmm70zewAcNawpNrrmcsH0Bygc-e5EuwjQEiMUY1O66bWUBwIRq1u5BcFk8bZlzDOAlLuSXGoK2KAhEdA9idF_ka9EGegs_ANycicMcCUna9x9IUt0WrSCDaUAbGYD_jmogWuoK2nDQAxAIwyjAEZgIzC9zOU6NvQuRiByiujsBOjAnjdK-YquvIxJR0zyHY7CQCJt5tXAIQgLB0MWwJERB4RAERizok5HM-_PnV2d9bMjZwBfVGZKbuVurS7IkYQ5rSFYIIA9oqMV2rGeErs-JCR19saKgW0Q4IDBRIjC3cPdYQM4e7hrNMdKvadvjPBsRE19aIcFn0wfnw-v3HmOij3zg2pXTVcz1yW56--LJ1998uiuchG-dra4cr1YJA0DcKfCwTR-_c2t7lIMzupt6hKLqPNr9fX26G370IyfbVcacgFZlrEcpP9rb9262T_dDbI-EIcoswHwkiftxmr_67oNvefn2dKU7pW51_eq1O9vn5dZ0GD_z1Yd_6-f-0U987IdvHr93S95RXQneunrU9bA9TX_gO3_v8aovZTvuLrbXjj78zR-aJ5uHx-nGjUy7_-xv_uP_6Ed-aNVR10s-Orpx43j_dJwvpv56csZhN2TOveA8q1Xn3LvZMI0iqc8429xv850Xb9cHF7_xW1_64huvfeFLd3cbef2f_UqXNldTeo8_99N_5a9sbp4Yy9_79K_Ns-mu9Anf-KXPXDjnFFlHxIBZiLqyh4BUOXm3jdy9-OrzN55_9d_59m9-09768HM38_potUJCDgidK4ZbdWLAwLGCq0atuUOzenYiptN0kPbJUiwC-Id-z_dLlkOZ_84v_0LG_oe_42P9Kts8eyAgCnEQkeszH0WEJ-FGjTVu1GMHIovCl4oSEjLzCBdsvV5qZK_mOwEkM4sFXuDMolqBmnSOEUAa_cyb5JHDHR2tGfp8eVSFKV6Wt4Q5WrOWGtiLsMV5KdzcwgmxzREnGzP3cAkrYyRr5FsRrQUQLTwlMY9oZx53d0dsZsQ283BoMUB0RDR3C7cwYkYRLQUQw-HK7Wte1Ksha3sidylJl6dhrEVTTmiBgQ7O0SQJQGihCsv9igAdzLt1p6W6OSX0EhCw32tVD6KAILokOlsgkao64KpLbrAb5ydPz0_OjmsphLTZbqZZ1zkFhYHNRSez61eO0NEsFKCqvvv0YgygnOtYiPl4kw-7YbevD6f9XCcjPuPVu-_eq8UuDmWzXd17676rK9G9J-eSumEcJfdEMs41gjws5xWQf_TV57_6pfuTVeKMWSp66lIAdLkXUZ58ve5MFZGrlc26V1XJoqbuFu4NYlZUc04YUedqpkR5HCZBHvZzQbViR5sT7gLCyjxt1z2zWPWG0Ts7O7ZhnsZps14JExTcD7O65361G52Y8rZfZzw8Oex2h6iWE-_3h8ErhodGl_syj3UeDXB3mCxs3J1vV8n8dHbY6261WU2z6a4-eXe_OeorQrN_xDynDa0pdhf1MI5mnvqujFO3XT29_2Aepi6lbe5uP7-5dWV9UHjtG0-gzienZwi03WzuPT5X81ELAk27PSANVtb90TzPQFGKqXnKKSFGcbcI0NWmB4JWNpMuealEHHMIEwfWuQYYE5u5pAQeVtUtnBwdwII6aTT2JRdgIFnahC7nDqISUrG6Pdte-eYPfeKj37LqVo8e3f0Hf_sfvfuNd8_3QwV6_0du_w__yI8_GZ589etvPHk8zbqnDqDd7RnA3VWh4QFIFqJ2E3upLiNCZmRBqB4mnMpcgRiiJYnNtQQuWeIWyFs6vQFErfUaCIDS5TqOkpgRakCj3kpiSgldWwKXO0FEEWZJSGQV3awj9iRB6FFTSmaaUqc2n5ycPH3ydL3uiAjUc17NVUVSlIhM7sbIYBgCwkxEReecstWaUqqzdqvsgWjMOTV2sZsDICdpL1ySnFfJZ0OhWoOyOCAgc79hq6RBgqoaVZG4oc3zup_GOeVOS8m594Ba526zBnMWcTIEF05t3CtdsgDMYurUIpDeiDEIxNjajQiMAtEWBkTRNAVQagmINaW91VgkqmxmjmgWJ5v1UKo3WlNKbk7QqNOABB5h7lVdAJAdkbVoSik8VGOVWbUsrmd3LaWtLmpVERYIZvIwa_qkiHku266bhlESI2BVS8JTKQjIQJNVYRZmRPQaar5iJcQaXov1JGrOKaubI-7Lnls2xpRFitYgyolcC1KCWgK14xzmlsg8plLWHR-Guur7ZsGs1Uq1aKBcpLGMInKY5uPtRrU-OR-6Lp9ttwFOIBC0NFkvz9_YcuHPcJ1L0t2lsSkCAnBJ2RCpKfASmcdltr2wX5hAEKg1iQOWSfKli8vDwLHZoGlh-Yc7NFrHAmoKXHzA7RDuAURNucuIEY1oF0u0Fhu8iMINGyQUwSwaNDgWdD64G7aVRBvet3ALUXNsRvtBLF-vudK84X-qOzVEKAABaSggmzrJwkFtAaTGGG3_RLeFzNOGjgiQgJUgwolJzRjJLi0BQAFtmsm0iOEAqjkgmikRAmLzBgWAq4Et2eWWYNAWL240Ug9kqmhgYO5MGABqFZHcXBhdqFos6iTDnLi5wygoIPrE5h6A7s6JAKKY-rJICHLyMI7Ud9nn-bnjFc8WjsRtsOkR3sw1zLTU_YEtYpE-NnYTE7kLS7jlxGDAl7kvRzSPIIIAYqSU6mwBbgDuLdxBiIACqKXrZJV5nt0cHYEajBjj_uPxtftPfCwv3L7y3K2VzvbW24-_vD9cPEZGv3Zy8pGbxx27V3OgWnyuVQQpi2xzGJh3HXJ1l6iPar0YYa_pzrXjG3euQHAmMoNSbJ0FYbAI3pIO3K1WdZ48PKXu5dvXVp1_-etvv_ryjTvHx9f6I7DJkYZSyCdne-Xq1Q_97t8Nqm_99t0PvnjjK2-80_fgj4c55eeuH99_enH0fD4-Wd996y4KbNYbEXh-s_nRb3vltTffmIfp9sunWaG68zwzrG_d6T__-dcOb4-r9WaTE1qJwsnj2q2ji6f7z3_1a7VL_-pLX37n0Uj33_nqZ79y6-hWUVud9WG7KNNxRx-5fmaEDx_urVo-O7l4ct4HFa7btNrXSMFTVXRE6cf9bh7tY3_033jyFP-r__Ofw7mYo4JBnXeHguhF48P8fBANNs8jM6qHd8SITAmJIaoTEba8GQMEEXFgNFIcAiNZZnH0qZbM8oe__3vC4-c_85uD1x_6-MfzGr1oq9KnJAZN3AvaOuiL-BzBgZi0ViRqcxESMjMm0iB1bV2-aLyDxgyNgEUxHW2hRkzPhiPWbNMNL4AQ6LBYAiAgOsJi5g5CAhgBFN7eSeyLIJyEqZoTgiAFEwM6YDOprKhv__BYdoIA0faV3qfkEOLY1u9FJ0wrcBdurL9AQjfnRO5BDk4YjFDbwpAZuVowMyAwhBw8GowiaLvu22OjDvNhLF2iqoYBImjuEuzmQNCxaF5m5hFh7kRQ1PqUol3GqxVrrl6htswMF8YAQmKdVZj61HVM5_M8lXmT14B45fh4GoZE1K-7WiYIUHMzTUQppd2-7g6HKaIoDbNx7nqig427ubxx_8lcHcOK2eEwjAqPnk6IEY7cpYtx3u8nETSP3aR2mLvVqs6FhMLBTEUEybPk84eTVS-ljmVYr9fUOuXmDRt1tOmrWR1ryslc3dwV1Cp22TS0aLTES_g8TF2_IgIiATf0KFo325UZqsODJ09uXj3JLElyqbrJqePEjMxk6jm3-nUUrR4wDeM822EudoD9xVjCusRwsgXTKXw2nw5PkUCEOXfnF2Pq0q9-9vPf8vI3HYZpldPddx5OCHfvPinMqc-H3Xy8XX3k5eeOujx2qzqPq3U_DsUjsvBhms2s3_Q3bl1__Y23XY2QV6v1NE3b7fGjR_d_4sc--c5r966ebK9d2UxzdbOAut30u_EAY-lzqmqpS2qAKlacEEkwJZGMItIBXLi5e2JhSrUWVWWmMiojB4QQckqOAWzkpFVLMSHwCEmkWkgYjcMLIuuslLjOEzD1RysMQ0qHwz5L70SA3Q__vk--9OKt2eKdN1__rV_41YdPn_YsQXx69QRn_N_9T_9AfXj-H_-Fv3z_wTuSobhSEAtHKQTh1XNic1f1MBNpirp2FUcmVAcrlvtOtRASSY_kEEEiYYWFyjxxTkRsVdtpQohFqzfwJbHkLABU5yKSGQKs5C4XW5g2CGCq3XZFQBomnII55WymuV-pmsOMTgrOq34ex5STEAIm11gfbcs0JUkgnvPGYI8B2EMY5AiMwKBSat915uoQgMIMAMAibgrL-jCQ0S_R6sNhYKHV9sjKnFLn5Ka2Tr2Zq0bqed7vUCiAjrbHcDhQzmWsKfUObmbdZkMYJNw0sQk6ZkZGM0MWIOgl171TwoBCSm16q0WpT0jNnJrcXaQbh3G12ZobARE3CwoRo5kjSZnrOU1tLAwYRBwG4GDgF-NBJGm1Zt5VQFc97vtJa8sWK4TkSz9KmAi7WQQKQnUl4nks_Xa9n0aWSCnNpSDiNBdeCyLVUiOiIee0JTWAvEI7xA5FJeWqc98lFi7qtXrramL4oUx97rWWVd-ZWplrzp2jE5Chq1pisVoFEEG0hNvcpzxX6xKSxzRMXaJp1LzOXP3Jfjrq8lgVA1kopeRIRZUbhRbzbhiOt-thKgnBkO4_ukDwK8dXn43cG1HWzcADwgG9LaxbIMgBCTnCmiTYPJ7dE5aTNQUiJCKNIAIkZmJEEGpDfowFzdmAkG3zzkvxt8kzmqmWEJlcDT2AFxooQPumHJqmh0AWUuci7MQID0fiy-8YF-M9MjbqUtPrxhIXgEUltMz2G32_RV0Wb1lT87ozBnEj-SJAMC2Reg1vwB9mQkALY0Kj5aS_2M8ARKgRUcFarImqa8svkRshhhs4tsN3Irawtl1okYYAEKYICBJACNeGOWJsfychthd5C9M3Y_OiSWiYUXVb7G-AQjir9l1WUyJK0OCpLoINO4iIF2XacDZfRGxI1P5FM2YmAnRBqWGIvFqzW3z8m97LZtDuT2QIQEAlTEOFkYRDve96bJErRA2PZhVWRwa3mqWLapf4ouVXxQPMg4kQ2WpLXhhAcyE6swAq1Lo-6axCrYDILO2n4vcePPntu49QuvdcPbr13lu91y--9uDeoz05nPXde-50q23PTAmxjlAU1EyLpiTIPBc4TLbuScC1-mHWWvVglDt-73EGZHRwJPcADEqQif7WL339B159_ujoqGr0wqQ0U5jD0dn1alg5x1jv2oNpHHQe6N0HTx7sf-P-mx94_oV7u_ihj35LnZ58gvKLz1_Z12ncHST06Oh4eHRx753huZN5P84SCTWePn46hj16qreuX4kov_qLn_nv_v4vfue3fdP67Chf7HbnQ7fZ3H7-uc0Lp3_pv_g7CeWEN6997te-eP_u1aPTeTwcdT2guUInTGu8devW-3_P937h7__yMMzd5vTG7WvDbhxv9kfXv-WF-eHbn_uNbeY7r77njc9-6fy-Pv9jH73u6ev_6hdITnN-5ZWPvf_ajSsvvvfKj_3AN_3lv_R3dHd4ev_pjI2zRE6eU5aOwBWDEgMBSpA7JkJUJ0JSjABqz0IC1AAAqM7EbAAhHqYBWIpkAY7qDmCJ8fd837dCTD_76V8riN_3gQ-dnXa7nUYsJH9EDvBFV9ECeOFelVnUlInaO5aFw5dRnbmRcFg0fFBbBCZOjQ6Xwpv52iNM3dxFpIE0HKLDVWB1criUhalBOCAjEpoZ4KUFT2sQIBIJRng7W5sHBARFAi4cbiFIzTLhFBxovsiviRDcIcgNEmMEdLmHcBKKACQGxCxS0TzAIUSEAcpcAZGEFwsYiTt4eEYCwVqVA1CAAjDAwEBws-otHAyCvKgxgLtJShFQVYWQiGxWXIQs0ESt6m230d6_yzOVCSJITftVJ5CwC7RQ91nrMIx3rp6OFrXW81qPupzb5ADBwoZp7lYZgOdRH17sdsMUiYfZqoaT7dWLx2GqCsYZzZgQTk6OmNggELCGzVVNwzHmqXR91zMONXQuz9269u6Dp15rALjVK2ebHruU8zAXTInVyzxjRQcstfapC4-qVXLWpEEQgLWquxPxPM6unpgJMTCNZWQhAwcgrZUJMKWuZ3XdbDaJ-fzigig6SSfbFWEoeHN9AkCfc07spmW0J7t9UfWIsehq25-fD_tpGKbZPTzQHbtO5mFCQdcYSz3K2xq2Olr91M_84rf-Rx_uEzkn6emtr72DLMIyDQUAr1w726z6al7mWYCslHma52G6qHqxG6XP2_Xq3QePLRxZdJ5yl1brvlv3eJF2-2Fz6wpQbJIcrXO_6stjvZiHTDRDCEZap8FctSQSrVWEMMDcNpvVat0L0TjNpVQgUCuMyMwtHBYQFp67btZ5ngqYu81JEmo4BDMzETRQtc_dZutu0QkYrrabCEzN9MlxcnR89c61b_6u77y13lLn__LnfuH1r3xZxwJAm02yiuttXnXdlvOHP_LKa7_51dGHyIgluk6m_YwYWptJAIES2JxZIIJaklB9iQy4IxExmhcCJASDWbJYLR4W6sgtgAzI_z-m_jzmtiy9z8Peaa09nPMN97tj3Xurqrt6qO5mN5tsUpxHSRblmI5kSXYiQTFiRTAsQ4adwFEExDbgIMrgCVEiO44sKJBhIVJkSZFMijJFSxRFipPYbPbErq4eaq47fuM5Z--91jvkj3W-poFGN1DVVfcb917rfX-_5xGMSgjhyjc-8AlKiRKiIAIhIFECAHJv2iFTI07gnnPHgDmJ6ZY5cWJhISRkFkkWvikXHByIipAk5ZT7sW-F44a76XIHCON6DAg3F5Y2whTJe_oGQO66sizQEomuBBFhXd8HAqdERMwJiZAxd7mtJokAAkSoNV-zdMAiXWqlhS5nDJAkxBwOxImYAaIfOs7cWkPhvhpHSTnUJFHKiYXdQE05C0Tk3GHOWioxSZ-4tWqISdjUESn3fbjnPgcgdWJuyOIIribNohBOzBHBIq2AbRAIZEUzpyaac3dzG8Z-mWZOSVWJc2NKSkpWCiIhSRs2S5Krq926X1UIQShuCBHW4gmi7q0KtttNXZ_DzSNUlaT52ckArCpdc-tJ2NW8ia0QPTyJlIgkQkS1VqB9a4qQGQkBG3pZhN2DEpl5SkIAzNSlVK0OY7fOIsLqrWVKTAjedtOI157LqdquVA9jRkFkpHDshlxrORxX47AO4HBCoOuhFlzjNiGivUkbyf66m-uxV__-j6SXe-Cj-_XhGgj2hnr8VlK_Lcej-RsaL_N3eJ97q-ses9NOnxAAguxxPZXHa49vG6ztPcbXcP99ReFbn8H-34ywt241re81AbQlgPfhFtyj5dHDkfbBH3BHALO4_jSv9cMA1rr7sRcVN45_k2MEUTMTu1mTI39LaRyNMt4SOBDY8j9AbfKP-_kV-Z7y0Tq7YO7g0ZgkTc2sDVboGACOrh4NlnCtSgdABELfW88wtO03gJGA9rGI_QcE7hFCDEiJycMTMRPlJBHRgkTMLHt9cWBAEAEEoxwdjB-6fXMkwhCGFBHM4QgeUXRmCkYiIkZMzA3npN7WwWERZg7ugpSFuDWVcc9sguvmdGqRoXCz_XmpahUkhPBqjIwNVJ6YGTTq42eXr33z3VnjO705zwIAAQAASURBVD_y4sceHg1gzx9tXnt8Ppf-4d2bB0erWydj12VxFMB5Njeb3ICIO-YswuQU64Nu6CVMY67v7TadZJI46HoOAAOM6JghItSs6OnZ5uLp-Y_9yKe-8fXHx8M6syybBSyenm0ervOHPnz_A3cOoepvfO3Nd19_c7ed_-3_1R_Nie7du32wzieHWczfef_Zbq5lKQZwY4X_h1_8yks3bq4Ox-12Gm68sO7g__Z3_95xd0zcLbNzSl9_4wmOd-5-z8cvnp_-pf_v37x768Wjl1-6_8Hbf_O3vvCf_oWfeu0Lrz1_8-3Nu299_He99N7j91f9-PDFO9PpudtcNjswG44PhYbA1ere8Z0HD9W9Wx3OgBfPNyfrQ5wvsCwKyKv-hVde_tpvvfbv_z__LJfx27_npd_8R5_9yB_5o__zf_0Pf_xjdz74ys27925K8q9sH33q_stViTOR5C5lZhZE9gayhjCkaOTZkAgMpwAiNGtvVidAwGBERCehFjEHjO10kVNvXhqkGqyZON3RP_bC_Rfu3PnCN9_8W__wC9_1oReH9UHf4P2uiASA6s0aGIghwo3U3Gbe7dm1F3UAMrac_HUsBxEbRpOpvQjUAgkEJTAYkRn3TmpARwUMCIq49gMzEUAD7hMxul8_IaBBt771UIoIlrb44GreeAOtUGThLejoFkwUHtgwdxEirGbCom4iEuHCLW9PgNFwKRDYLJUR4OqtfQTAZkGEjpASn28vvvOV-xIgiSGslAoQzNx8zA7u5kBB3HTDEHjt7tp_okxMQugQZooRnXDZCxWbAxncNPbPTzjoBzAMN3fPnaSUNkt59_nZwWpFjAlh7DpE8PBqqurhxJKutsvz8ytnyakTYQ2_muZtqecXGwBMqbfAtksZUupTutrNucs1fNrOy1xEhBAuz7aQiAlFUtFyOPZXu9nN5mkehlHdd7Wcn23a91RLqerTtHh1Ye5y0upIKCxqVufS5oQGYBFRFgY0cwvLWZDJ1OpSmvGwz92yTImEGdfjuNltHXCppZqmnCK8SwlcV2MniEyUmJdaFbCqVw9ELoueXV2FgzpN240bHB32perT52cE1B8MklIT6kgWRv3d3__9ZstS7fT0nJiQeyPY7nb37t386MOHQ0oXV5t5mdW0qk9ztYAanhL3Qxemb3zj_W5gkoSItdY-5-Fw6Nk_8aEPvvLi3aGTTLLb7E4324urpVTfzUsAl1pbJBsC3c3UAd3Nhi53OQ0pXZxfpZSqW6n16momJnBjZFU1NwB2M0QMrwRg1b3WJMJIlCTcy1RTlxGprZ4MkACG1UGEInHuSKT7Q3_oX_jnfuIHv_7a6z_9N_76lz_7-bP3nyECdZ0BE2Cm_IM_-f3l2emf_NN_9OWb6__rf_LfvPXoacW4utqCI2NoqdEUoi3EGw4BYRaqSOIO1JKEEEB7xp20t5UZZnHTCGcRcCNmU5XEEKBaEYJPPvRpYEp5aPloToIsy1K7gd2BmYgZGUWEArrUIZikQSuIcOo6Zuz7ARnKbu77lQhT33tASpJyavV0Srw6WJWlSMqpSzklSiyMSRgikERrQWbOLF1CNAwADApKWcJcch8QyMIsEMApVbM8DN7qlKrtjQ2Aaeza9cPMObf-Qg8R3dCnLCQMQJIEGImQSVSNRRhJslgbrux9rYgEnMQjupwAuUaYR-46yZJE3CJ1iYTNnEVIWCQ1EkjKydQNLfd9o3QDkpkTSYuptBlwqdriCESAzEgUBn3KXo0QRFiLteNf7vqqCwCoGkYEQqnqEeaWOjEzQrB2SSCqav0wmhlRG2s3AH8FRPMQSWUpxBgIbvsMxDAMVbXBb5jIVAmpmgVhKZUYzayXTs3bk3yVequK-5cKeUTusxbjNuuF6BIyIARm6dTcBRyA2kwLsW0zdtNiHoag4ZQ4EDUscc4pl6WykDMe9N2N44M-9RAMQNeM_Ihm3GpqXABihthj8nHv62pCJ993SACC0ANwD8UDaemXiPZSaYUOh2-Fi_aIn0aJbuxPImwomEDgfc-2rdzJI8L3f7RjGDSJ776F2ibCAftQfPuT8X9kD2i8H4u9wnifPtoTgfZygEYo3Qt9ASNszyNFigggMmzB96bsbSCRtq9oJK99KbnpS4kpPNyj-YII9qstBGBuHjoHREdAFlNzQoJIjL_z4bXbDITtOwbYfn5a-IcRCXivvyXc_zP7LuC-77z_CiP6vjELCC3LGxE-dpkR0cERMtO-Kb2nsJIwBwHv-ejtH8ZEguQSFBBMhG6cBq32ygtHoiCYwg0giBuxSRGMhYkoESdmRFfzGmaq4dEAoIiYRDK3RJdi4nbeYG7fu2DBfbbS9sp1hhBu2QjgLDllYmTwMs9ffevdz7_5_jqnVx7efeHWgZueXU6nVztjOhrT0QGIWBahCAAgxqksm3nJXQc558SILCJMmHtBoMupXC7l__WlJy8fdatMx7lLgkykAX2f1XE3TaaugT3ynQ_dO1mvCIeT4wFdCcCZ3nl8-dFXX7zYlYtFT6-2fd9__Utfe-Odt_6d_-zfzYVZNytKRxmHDC995P7H79_jxOO4Pv_qk-32-dtUn5i8HvroxRtf-eWvvPfGe0EH_79f-Ll_8IUvffFz3_zFf_xrX_nKa29_9RvPHj0ap_kbX_vGP_r5X_2nX3lj841Hx3XzzutfI1-E-c3X3h_u3Hvy9tnF6eU8V93smChE-pur1frIyDYXy-qDd_xqTt2Q0-rw9toPIPW9i0tOEfTxj3_g2dXu-OjoiLvv_vir_-jnfvHOvXuf-cwr607WqzyQrwCx2K2DA07M6BHormFGgOCOLWdPkJMg7pF8LYLfdBwi3ApBiYSIETm8nTabE5xFyAKBE7MspTAJeaCBE0WJB-vDl47gje3VL_zyb7z5-PGb75z9vV_8zW_7-EP2PvXcGlQI4W7h2JI9jYLV2GBtTYex94buRxvUKmDU0oLhQUJMpBFI3xIUNkRoe1LtC_2EiExFVailelrth5AwGNHRwdtckwBbcR-bNYc42q85AjG1M0GEtideS_21UFCrFSVhxj2vN-VE0ChqkFhMrXnS3aOat74NM7qFZAGCaGMx9wj_xAfuCYADeCPhI5iBubHsm28BsOo7UyemvTmxfb7tzCLkxZqLPeWECO5gDUDs-6Iw817BSQSqWpYy9pkQjeTp5WY1rjfTlBmPV4NEqFZ120wLERU1QHp-flkBkPlqt4Pg7TJ1qdtu5zItHnG1W7iDlx7epLmeX2zDjYmmaVn3_dV2YYC7Nw8_8vDm_TuHd08ODnMas8xWa-Bm2l1d7UQyID57dnp6dil9XpZaiylgVUXAXsStjrlXhFqqqptrXYpkyV2ed4uWAgZLrSIsSRrvWKtBhIdlyZwYIpBh7Ac1C4xwCLPMvMxlvepdNeeUEtdil9vd5WbnRCV0My_LohEwTdPVdqfuu3nygJy7pZouioAMzkhd11NOAJj7PHD86Pd_N1RnkqVqne1qOw198qDv-uQHprMrN3_rvSfV7Oxs60yL-VLqfvwTtsy161JVS9zqWixMZHp8tCKEz3zbx03VzRThjUePOfXFYzeXpdQAsoBqerXbLq5F61zK0I8scHiwYiZVSylvp4KMtRi0L2Wjw4gwi7uVokkyWCWRokYsRBgWbQbKTCyC2JRylBKlnrXMhwcHd1564d_903_81mH_H_-5__vXvvRFMkBgzBSUHbnWxd0C4puvv_3-W6e_9_f90Ou_8bW_9rd-uh_y1W4LGojOzFrmfeMR2kunc6sYBkjOCADM_C2NEQkTXOeIAxyu0SOu-3u-SFN1Ewa4ScukmEc_DLosbQhxcDBaLZKjiTyrWs8slEwrC5MIJkoJvSx5vVItJDKsVlpLOAKYCCPhalxtpi0nZiJ3P7pxJJIiPAtvL7ep60FdkkxLkYRMpADzXK2EJAnD8KihkrNZoFBOnYZ2Y2_h3MYYpnA9vyBGQnB1M1dVsEDhvO6xEbaDALHrOsFa1QGoG0fAgKlxY9AJuiRaSsppKUWEI8wd-r4HdEECRtewWkUop9SMKstSOAvnBNZOaIiAnLKVRTBZVREGwtBgYUQCwog97ViYzcPcRKRVS4OQiSVLXWo39H2f5nmCAFNjJKuN44xWq0cgpdbQQoJM3VxnIRJO1W3a7XLO8zKLSE5iSwQAkURUcwMEtYC6dP3gVj1Cq4rkbdkmJAZRC4sqSUx1JSkswsPJEou7WlFlBSZG8ggt2q3zdjsPY48QdSlpHM09oHKQQ-05lzIDUSJ3xlIqE-aUpcuLKkzWYrBGPuSBEKopJ7LwpeqS02LNt9KkuOjeKCFI3N7gFZDcGqIdoRG4mZGZvdF69hibsPYq2x9gA66V2dAm9G3Gtx9_uQdJ6xQ7EYEFQAtRobtHOKAgtnv4XnfV_hbxHpvZUvsIeK2x3e8B2isbiHCP4W2vfNRraCgShTnRHveJezUYhMV-sg5OCIS85_4j7dH9gdHC_URq0c4NBNSSy7XZRPcfAFjDKjXVMaNDEOG-Hg0AEUJUG_9SDZubjxmihanYwpHR9wIAbBcGajNSCPNwoPACxMykpoDAImDWWtVEFLCPyWOEAHkEE5GQazMhEAIzoxCDGxNpVRHc1z8cmJCRGIETqIebESBCJGEzFSJAIkTp4YgyVIUgB4uw1kKMxmHE3CqTRARuBlhMmw4tEMydEqMGtb1QABAzEiIw7QeQwmhmZoAMSNQ-QFsUr2eeIeTFHp-fPz8935p_8O7NDz24B0RqNs1Ww4tFGgaECHVzBIWNza429L2bmerJwQqRcCrQrOvmi2rfdbupgtu4lD_zHfeHLl0Yq1tQQHjXID8Iw2oNFsvF7vbRqng3XU2OycHFJQTmNH9Nppuaz58-fvzkgmH80Pd9x8vf--xXf-O1v_DffeljWunu6qf--k9vL599_Uuf_fQP_ouvfPD2L__yFzbPnm52u09876cvfvmraTWE1vHv_cLVduNa3vzmG-t1NyhczGdd56vjHIy7C7ua6q2bN_FiO3_97fNS-k5WB6vdtLOLy1pZkB-8-tKzt98hGOZpTtJBiAWfX20gDV6gXG4O773w_NnF3Tsn2_NTdQ4SYD-8ud6enpbp6lOvvvTgzlHdxtFRr5w3Vxe5YrhJAIRvbfnwB1_-xc--9uPf86m5OickJDNDMxF0REIkZmu59sbGQTADokiJEZBYpqo1NALBoesaWCUQbTWMY9-nUXZLZStXu-m3ruZ3z86ffvGL733-3YTy8kfu_f5_6cdvT_bq7__wQun99x7__M_93L__H3xukw_-_H_4b4dGgEcrxIcRoXkgNg15gxYgADiimTElA2uGYeRwD6GmHN8_tzwMPRILAAY4GCAhI2moULs0gKkmoT3yK_ya-UttEI5A0m4agUQUGK62h5QhMrJfYxKaEAzDfT9nYSKo6nQ9O2u6jxZFpAhh4sSE6MbIaG5eY48HTWxufe6qWQBWcyLwwCT0dDs9WB-gK3Fqe7bS5lQWfScF3QGLmgWWqXZJ2pKDGKzUAJZE0FwLAarajoweUDwI9ntLVU9JAGBelmW243XOma-mEintqvdhq-Hg-bPHx5lTtzIAV3A1IMqSLnezEox9f3VVGHladlZNRNbjcHI4kvvHPnyfp5LMv7HYsl2uyqIWFXDNBEjrdR4Sq0VgfvL8_HIzzUVpTBfb3VI05Q5Enj87q4tyYnN38AI2zwsTZU4eVuZyFpsgcrVaSu4yQDBBXQoDoKSiE0kLCyUSmaa5KeQzijuYek5JkjhCEqqzySCmdbfMQrRbFjDo-m47F_CotXZd3i1LP9Dcd4tOU6lXu4Ull2WmAOk7C0XAy3mbmA2YAThhhBJ7Hsdnb78z7zYRDqAf_OCDG8dHLyEvu-W9p8-9WHU7Oz1ztEW1RmzPr4K42azKMiXphDlLGoeo1QRTt07TbjtdTlv0d957-t7p-fHA7z47U7P1cLBbVKsK4hImyHOp5J5FIqL9lM7z7s7926awTFsOmpeZ2Hdn2wgoqu4-q_Z9xmgrOwwN9yI5VfU09Nj4GQnRNaVuWZYhd9TixBKOhoi3bt_8t_7UHxv78fO__Y3_6i_8v8cxgwwEqFWbRVf3F38gMkb59u_5thdu3tks9MLDo6eX5uaEe7o_AaIAQBCBaRhoEABKmF6LJglZoEwkCcBVjVNCh30EKSeb59CgRKYOHpRzXQohEJKIsAU3SBASr8a-FG3QGkDSOmOSPucECOB56L0WSoQiOTPnfhx7C3APj5q71GYZHedwKGaI1PWZhepSJK-YCMMRYhh7BA8JUEMhCvRa09idxQ6Hzs2WUgGBMNusnFMSaQMIj0hDR0sV2hcmCdHVWQjA-67floqOeRggrNTa574fOp0t9wKAMgziUUrJKV1d7XLXCckMM-cE2Lyp3ne5LkVSwtSQfyhZdFchgjshkuqWJLsb911KosWkz4HUiaQuB2ISRmiLWHcjByfmUlUoEYXNahVRkALd2d0ZmuM9rrwSsLnPS-lFTA0wiHJjC0rqlmnq-gHDvFajEJGqmjkF7Atd5MQEtSwYgQDzdsckiLjbbbouAyATgnuWrlYFQGKaSwHCMIPEQM5B5lGrdUk8IhyqKhJx644ylggHRyYASCRhkCXbYpwISQhRqw1jtmpLrajBvdRSDbmYpT6L8G6amqdJzbqclqWkYUiYzX0p23aQHcI1y-HhCOZEyf1bm-km3IAII2bzfSWupXWitaO4DftR1YjAIcAbDSOCwqo7IlJj7EBEEKM3uVSD8NPe-7tPoOyHS7FvByPvwziEsZ_qw5680-bce-ku7MXAv7MIiP1n4I7txdnG0dd0I0Jodi1vhP823W_3mOYhxn1vFyDAndqYDaHNjDOzmQqwEoa2w64H7LM0wdjG2nDdWKDG9KGgtr7EQECzQG6aBcRwNwiAnAQAGjWwBaOiKUiIDTwiWn-3QUqZEBAIExJrGDk64_XjDCDthW2BwG31T5BZtFayEJFaQBIpGBEwC5cIiJRYmDHgd4xvEAjcfGmSBcwRgiL6IUd44jQO42aeH5z0ibgRQVDYwRjRWnc3kKitqryBejwCHE2dJAF6qCXhjgmCzBT3aws01fZjsV8pULQaggZYIOSE0JRi8eTxky8-efuV49svPrzb9RLh1d2rG0QNNXVEoyAArACMpBTi2I05SWYPHIcwRYA8JJTsGKVaEXQPEGeP50-n8d5JIZbALAKLWlXGMlLAqmfo3396-h_97M_83N__7O_93g8-k4P_7b_yL0Y5_JVf-vU_9xf_6uqgbB_737hBGv3JvaPt2W73H5-9-PD-nZduvP6zf_2LT69wnbh0Cf3bv-077h7w65_9opw-OpinGx0ub78tqzWJ1GV5_M13hyw6DLsl0JHUhHrAWt672CFw1IMu7548c6ejFx7y2YzZjx7czU8eL9vNONPZY33w6aEvN6dn2wMG3c7d8VEvwxIlZXzy6Ey_SusbN8L06vQZYMybkjpj9POrSbTWBT718VdfvHd3vpgPVkJdRC19n6bznQIgIKfu5uGNHQZSSJJ2n2bAIEQiUkJqdAHzMOQWCiQCUK3okTKth2697ndX0wsPTt589v5bp9O0zadX77-x3XXd-jd_7h-_eONwOl2mza4_YEJB2yzzjkT73E9X83_5n_zUYvPZk6erlQjjvZOj45snf-Jf_p_Vqx1ncQdkalTNcAh1bwywiERCCDXcIxLL_je0CZMdEFD3y4j9mD8jaYSZMnFgMAUgWXgYKjgSVq2EDBYtwpeRrxcNwULuhkBmxsjVNEtSV07s7Z5OCO4i5GoQoeEt10YOauDmgcTEbVYFDg6O4MyE7kMWCDAD2ItDoaEqMQDII5yR3PdDh7ZNd1Uk-blfee2P_XPfkZvpjIAZmRGBgsDNEUirV6uMJIRLLV3OktjdkbiWGgjNCOIQjOx71FpAhLq7VZKUOwl3ZjYTxODE86we0I3D0TBebKfTs-cv37uzLLEa0BWQMJE4YSCyMBKpR4Osd12n5rps7948_sDto9NHp13gleFn33g0VT8-OcBd9-zsEj12l7uOaewyqi9mb77zOPUdCtel7J5fFkUIcrfN-Sb3KbG0ayETRy0E0KfOI4oBsyx1ZmIPD_Aylf0oDIAAKHFZkJk1PEwRSBAXKyl3iKZaISin0VxTJ-TIjFZsNQ6ZeUhpt9mtut5NZehLUU6pLDov9WoGB9SwpZoznV9cMUDq-rnWupTcDZKlbGcwXWqO6kl8XK-2l09_4ge__2gcjWv1PCOCyMhcazk6GC4vl2enV_NsN04OL3bTs4unknLVEmDjOAbSXCsT3VgdnV6egmA1yyTeDXySDo5XPcPf_0e__gd_8gcLwMVmVqtX2zmnVVGr1fs-9eOKIYpuhHhzNYNqEKHGbrsJiI77-eoCIZBxnmchBIIuZXSAqLWoE0pm8FCLCGAWktBq4c5dtqpJUs7SqIGcOHX8o7_nu7__Ex8fEP_uP_hHv_BLn735ws0guji9hCbl8AgwQiMKJKGcIEyxOgiuD3Yxqu-iIHhJbqYW7oRkVZ2COVdTIApCCEg8mm1DLYCIOEypOXNUIRw4saQwQ6QQCESkCEBXIxYEdzUJQG-nx0QimZP0SbwUSrlOS79eGTbXUuNuCzO4BWdyh5wkAnJObhYUqh4EicgicrMdQDMFEo99SpwlLcu8THp0NCaCshh7XapjgLIw8MHBqixFmYPI1FJi4DCLiCChjGIB_ZAXdYpIkiLCzZ3YqyFTKSrM1LO5djk3vV-XU04pdSkQw0Lcu5zUbDzouDlN0cPRPXKXdJml71KXPDznzqBz92k3p5xVFZMQYBh5hKlKl7thQCyE5GrYZZFk4MQJ3ZiEiA1xqaWoebgAWjhlKarStEpZXNXAUYgMTB2EcpfnZZ60dn233S64VDcjpKKzJK5ahVIL0AOEVp9gJuQgnKdCbcLcoiAOgDTt5nEcJXd75bN765l6hNs-3ooeGFCLAqCICHOxigBNC0DMpdg4DkvdMRM7FvOwJSUJBHBTs7HPgCQZul4Ykogk9l2ZUFBKSPu5Y7bAzVxVPREti_WrrqihiKM9v7pgBmGqqsQMDstS6qQp5WgjJwIgCtBrl-s-uO_mIOgWjAhukiTc2oK-0S_C95n2VsltTrs2p9oHWdpgGtGRfM90b6Yw2Ef7EWHfsG1mXWxRfQ9AIgvfh_X3tYO9UyxwXzxolwIHQARvY36PlhpssXmIveILAK9ZR_gtQzHsz_loZsS8v2XsU0zY3s7ggOBIrA4E4Uz7P5Bg3y9o9rEW-kVqXotGwcMIvt5ZtE0JIRa1FjhqeTxGdN3nfYnQA4TIWrUOgPcXDG_xuXBkJndPCMhUfZ-b50Tt-K7VgJCFOMAAAqLvUluSpFF0MRaO8MTMmbUWYm4P6HAwd7dIid2DEBmBCBiwy7JKfPNwyMLmlJOUOgpiqLXWLiAAuJqrLuzctiWtGVlqCTAKVtUAMlVAIPeuSwJoEMhEDK1ZjeFAQRYBkZncrQmUw4EEAzg8zk-ff-Gbb37s3gs_9NFPmoe7l6kysQGAh7qZO9i-oq0R4BWZMvPQZUe2AGAyjSBKhFv1hERh0vVo1cB6p7A4X-ADmlM3EuF2t_uV33j9Z_7xr3zpq1_75un7Kzx6cOugl7g43b561L_1hdefnNf_x8Xl7nSze356J7kvjkfUHdzocsf9iSRYHTN1J9_1r_z4l_7-z28vDRaGqMhcn-925fFuM-3mgLkORHq-cOqtXwjTvZfuJyC7eTSdXfYn-fHnvwG-jDfu1KW__6E7b_321--8fAfL7tmj89NHT1_4sR-Z33ujFD159ZWnT8_WR8f8lefnX9rI3c5XvL5z05fNm1977aVbnwQkzN2dDx1dXp2hbxmjhuY09oc473aKQAyS01a3v-sjr25sezhyh8NI3SgyJCqhXiGqdYd5APjej3yABT2IG8LJoqiGiqObU5KuH_NSa1xNqj5mFpQ333v867_9W-8-e_rs9PJf-2P_6s0b3Z_41_7M8689-tC9O9bFekjrkxu3Htz4zk_cf-uNt3__v_UHTn_7yT_5O__99vwcS4LMy3Y5z7xawR_7X_7IKrrjG4d0kF774tc__p0fhSmuLndMZGEQ8K3oobsxkV2vJ5saMjErhu2B_UnD3EJEzCx8v1EMpqY3jQhq9_R95wmQkBkCUKumlMNd3UCjvc4b2B7biwDZw4hob-luKX8I82BCMGsYXyJ0BwxiYQho_zhRIxFxJCRCNxdAY6qqh6tVl9gduPXKCC1CiB0APBLSZKpqLcxIgBAEFomzWUiXf_bXfvvHP_3KOmc3a-0sd1-qpZzUYy4qBAYOjkQ017JODA45c0CoGQQm4UYasDZE8UhMKTOAmJpqpSDOvCw1QNETMCy7pV7Nm2lB4aoxHq19t5xvdqs-I0R7UtJhtqmM3VA9cvLMVObFyrKd6osnRxfnV_1qOF2mp5tysXNgFEo3buQSenGxJab1kIr58_OtPSmp7zY7Va1ugJjMlmWZOGXOpA3qF94JMSa1uH-yPt_N8zwbQVnqNC9ZhJkAghA8fF5q1SrIiZmFDVrHC6btnHPKubNah7Fncneb5qnvOp1q7nLHeTX0d24dJkGdtHoFhrkobBcQWkq1orX6YqbM01wNAJhz3wNCKTbPCwt6KCw1kW2urv7i__F_J8fd_-ev_PSj87Pf_0Pf88Pf-Z1Q3QjdAtxuHq6fXWzEkTg9fb4531WhtFSDQErdXMtuM6eUwOeUhSGI8Hx36Yibac6pm0sJj2EYmFmItvPlT__9X1gN3Y2jY3WYa3VcRFLunHMmg2maPHy7ncEDAN3j9PwMA9Zjf7m58HBhGgZRy1pqJgYS17KdrBu7Us2hdimpmYVr0dwlEqzznPs-EjIiRgwpD13_7d_1kd_9A9-NhF998-0_91_8N59--Q5x78yJgrsuSmmWj5TJPJAlDGp1DH_06EmX8bLMXR7TynwDaIGIUZWE9vkWbad1JGarBQJCp0YBIqGW2SUkJgfwCAsDAkDJHopMXhV5j-TFIGZwQ2m2W04poiJnIEwiRlimwkkAQViCtEu9AjBgaq8xpi6ljrhB_chBw4UoMIg4iYC7m7Pw0A_mFSK63FmtSWQ47iGCBI9W_dX51HdISeZZESBX27ilnHGag1K4AQZnIiGrnjohFN2ULFkEIUxLdSQ1I8xlLkzIWQIIsROhlHLiBIHD2Kl6yl2wld1EzBTYpzEoMLDPnTssWsOhzwfVKlAOrd3QA9HFxWZYr-btDgGLG9A-O0IkBC28mAjJmN3cwwPIwRGAImqguydiDNTWVlYwN3JAhlp01XfEvL3cpNTXsnRdnpeSug7MHMijASjV3NSNCNWtFtOkTMieAInZS61j309ll7Jo1bDS5d5ciUDVU8JiiwQAiZu6O4QxEwK4OQrVsqyGQT2plVIgEA2VCCPCzCMsCwdiBTMADqg2dZLVlZAbBl4AWZhoj24nInOrtSLQXDQ7BzNEzdJFOFHazvPBIEC0qwoUoMCzT1XHlLxDSokRpmnJaK2Wok2S27L1zIAQoXsLN7XWasvJAgC1tbWZCyKxAEbr_gIBtuKpeeM-wbfqxG1N0MwWDc4D-z4IBrYAvUO7EGCDju6pQthg0uC-jxa1VLpDA_QBYzRWdzjEvsXcAqz7okCg8z5CAwBkAW4hzG6-F_Q2a68DoDcMSDuFQ-DeGtDaQX69ddjrCByAPJq2MPY7DP_WbaKlwjAJe9utXAf0DUID3LzdUtQDwZNwyz15hO8XHUgQSKiNq7-XZlO4NdhFhDtgqJIQAyKAmgc2QkgoRGZG5tZwTok7Ji2OBKqVOAQxkME8IHLH6NSO2e7RCgANVhARBC7Eh6vhIFOCYCQk7JkjoksSbowUAaomTNQqSYQi3NLP4AruSEDCvgCihFlAiGDuMgQAB0GYmxVjYiJwtGZrYmZTB5R2nbag5Kyuv_LZf3JjvP_9n_wkEJsrgKsbAMylAnDRGgjFgkQkya5WX9xd1uItDy0pdd2AmS-vdt98--nmXH7z6urtR_XWfPPt1_7J42enX_z6l4dxef50-sQnPvAv_amf_K__4j-4KbvnZ4-Pj24LpRvrdc8vNkulMh3eGsZxfPz4WVV2TVeXu2oRkmOJ7mCN_YryaFYMomxKOZ4-_zO_YPP8_PTJzVsPqAcCXZ2MN-7dTBf9MAzscfnkna7rH_6-j56_cRU70zKHp_uf-eTzX_myF7vx8AUnj261jiGtVy988ING1t-9d9Pe3Tx_dvHbvzoc30tD6PPtya07EHbjk7fH48N3X3vywi0Swbpaf-z7bj37xpNgPLhzkNLQEWgp4DFX8KgJuEs9mprVq-307HPPn_-B1fOvvn07U512H37x6J1t5SRPn110Y58yrwkCYVXs_dPp9mqNETXCkTAPm3lOiMM6M1ts67LzX_yNX_-Zn_3ZCsvg3W67Q_Ab6yOC9Ku_9ts__Ps-82_-b_7E3_7P_9LLP_BDj778lb7LmwnffG8-euH-xebJb_39Lz9_7-0t9rvj2_-TH_vRT3z84fHBmkOLVqIUSCjp6tyebL7-wrOXoWrqMGxPxDL1vS8EkYhdLeCaBcBUTBEYIbQlUTEEONwE0RAdgZsiAJsEQzwMoZXKoO04W0ComTR8PzvYR_4a45-JG7YX990hYOTGHiVko3ZBAUAoZjl1gMpMoHuDFjkaQEopwMMgMQdzmWZJcniwnuZFuG8LMS3aZ-kgLrfqAJwQQRIBCZRSmXhXrRMkRjUPcLN4av7T__Rr_9MfeZXCvag2k2BAqQaOSbhVbxxDEqGRmoc5IyfJCGVZNBICQk4yLRoBjkAQWrzvWESGTlwjmKpal8UsElPqurnWpczDOLz88K5VBcZpp8wEYRZIjLoEMblWdBx6AYKnTy8vHX_o06-uESbVd59evHN62Y1D14sDbDY7Yiyzg1PqZF7q1Wba7JbtdrdeN78y1EWXql714OAQzLWUZ5cXfZ9X3ajF1KFjutjupmlxiKpWSslC6NWBTQOFx6EHdGJsL6uu76-uNqvVyEKHuddahUiFRTilYVlmZpmnnWVerccbRwehKjmVUg0893lIyap7Ci92sVkwou97Md_spmXREsHAzCnCBH0c-gjtO7SZrp5u_0__wZ8p1cfF__gf_wlyZyAzc_fLZS6LpT5fnF-dnu1mrQZYXKvHxcX55Tbdu3Nzmkopi0cUtWmZ-65b9V0p_vT0vJhxks35-XoYAxyWiSg4J0ecqlebz67eH_peJG-XWatrqURU1bfTzgK3y2zg87Rbr1abq-X2yVF1Y-J7t45PtxtbxDvflIqIuszLUsfDUU0JomuvNoB1PyysEC6caGyoEu-zDHn40Mt3__nf80MnR6tHT9_703_2v3rxzvDiODx9tpnDxKMuSuzOIR2juxerapzZydlCESgir_v10JGw9KNpRCmBBJLco50AUNhMKfcBllLWeefgzKmqgnOEg5uGoAgAR3EicldUAGZECg6S7FrA41s3akm5c2BV74dOGAFwWUq36sVDgtvPZhLRWgWZEXJKGgFE5EGMeejneU4iOgcn6nImEGSqRUudhy4jRZd7EXa3cRy8FkGiJAgOBqtVx0mCuO8iAHeXV-H9tJTVamWL-1JzEgNPQ7JiwEgghPng5urqdGtqwElrTUmsWjcMwASOGN6PPTIieCCknBILcRCDtfJvlyhAiybOVWvXiTtqGCR2s0Q5PPphLZKIKCUpuylBzPupcKPZQOJsbgDBnFwdiXOfa7Xc47xYFtKwsngEdFlEqC66eFmnFECCEoC5l2W3dJ3k1TDt5n7otRQMNHeWTIjztGNiDDC1JNJ84JbMXJmSmwlTBKqFmgJEWZau68pS3LXUGgGpk7qYVeUhadUgRoKwWMwAXLoEZiJ52lVmRGHwUK0USIhZMiAJQtlW7vK-sELktcVDoNFaGTB1uU4195K7ZB4mMe-WPicEVDXzIDSRNBeLIPcyDrmZLUpVQjJTRuhSmkpJnpkjixzkbn18jJDc2jjdw_Yr71bCaydfQla3_Xj-WqS7H-27RVAgEoI3fn8EOBBjmHGi1iW-vj_s4dz7DAuSRRt3OX7rWkBgze5j-45tk1HsJ3HtqtF8y-3lHuCB1qI-DYPdSKSIAHvZZ7jvB_hAjcGEQObeOscNV4F7rD5F82hHEKE1pmaD0rhju3UAurWhT_syNEMnQCASejQGvQc26AeYWfOCtUKyAziEWdtVgAMgU9MPt_8w7SVljTeiFvswReK9oJkSABgGBBIBokQghxMDEVUNFgaPbp2tSXfCO2EhYuFOpFoDpTqAp5RMAwDDInVkdQ9Ob-GlCCfGCCfCxJjQCYWEVQ1CQTRqcErMggBmitiqz4SETC3MvzeANhSSK1rDs7ZEcwShe7CbqRtCSMrNr6jq3IaRYY30Lx27IBZ_8s5b73_9zU-_8upwdGjqCyBHLItRBznrMAontom9758-3Zqnrju8ujr_wlvvfOm955_7yvOj0NffeO3mWnrCd99_9t7z87FLB12qu6uuD3RPTKnLL96i7uDGYT9-x49-2z_8a_8YHj2_FK1b7k7W43B4pleQ0u5ye-tkffvu4eO3n4DH8dHJ8a3hzssP33vjfZ2Z3IiyuxOL5K4j3OG0zDhbhrDhxpreN-kPP_Dpjzx58x0QOH22GY6Oe-5Wh4en77-dZz37_JmTR0ouw3xaN5_95no17uok3frZm88-9L0fuXr_aXm-PT5cnz7fxRQvfeJjb335S7vdbnl-fvO7vnvz1ltcKch3EWdfffyhz7w8bTc2GQgD8MHhzd3phaB0kg7v3bs8PV2KaalJhAJ09jxkX7wb-urTX_4v__zDlz7w49_-7W-eXv7QH_iDf-lv_b3V3VXp-2fT5Vd_9fVXH7zy_Ls-9su6-Zt_8j98-Xd_5tXvfPUnf_jbfvtXfjvBjeHe0Zuf_-xP_e2fkSS3T45u3LoVQJ949aO3bh49eufsvbfe2S0avL5594VH33j3L_-nr9MRPTk7qv_0a7ps7PQ5DYfD-vDn_-rf-eh3fuT09G3p4C_8-X_n8dtny1Kk68FUIQwFmd3CoJ4-P3vh_nezBbSGLEG4MQJljqbwCHDXzC0XDsGg7iQE6g1JqGTt4dCyiszUesKEaB4ONqRuVkffgxKc9n7CJg1sCC8CaiiwNtdAQCZS04a04sS41w2ZZFGtLMmvZeAssu_YACBhqcYEwJgQ3I0YhIkgXrx__O4jzJJUdRz6Uk3rIpmFGICmaiTsrqYRYhGRWSKBg409q7VfQfQgCI9IpYu__Qtf-t3f8cqBZMoAJBimZoCIHl1O7WOzqg6QgRwiPDBCOFWshDGmpuIOYhJo0C6LwC6LEM2ui7WcIUlKHqiuu91CrjfGPEied0VVAWNbFSP6JLXqtNSEaIhalxvHBwQk9-_du3Hg6s-vlnefPjlbbC4x1-1SQxJ6YCm23U1d31GS528_5yyJSYTnZSZJXjQcFqvqcUioELnvZCNuvCwLpZWaeS3b7dYR-8PVtJ0xyL2x7IIyuYOImFYMEuZhzJvz3WoY-txvd9uu7zmlqhUQZzXpkFNnuhDJvJQuZ6318PBgWSpF9H0nmTCIEk1Fd_PiQEihHsuioY7Eu7OLnAdO6EUDA91DfTwcx9urDz68ffewW7aTRmUAszBECNiqbUoxhXln2-ouPE_zrLCb5qKhTFeXV1fbpdRaLSIgzNzNIqZSq6qi7-Z5wL7rc9W6Wo_TdmdqVRITIMt23l1cbnKXRPrD9eoDL7_w5tffDvVm13M1rBFhwzgi48G6R0Ytxiznu7I9K1OZDWN1OJZiZtEd5mWeh3EwrtNmIhISgkAJ0LAuZ6ogIscr-dS3f_j7vuPTqz6__db7f_mv_dL77zx98YX1UvXkeHjnnWciRH0PXqIqRtTiKRESEBMJgwEALmU-Pnm4bKcgGcaDjV4wIaZUigqjY2Cr69SKiFBKMDkiIrk6QdCefEUaHmpEAgjErKVKSloNmUEAAK0srehjCE3HKQEUxGlIxIgROeUZFQCIBQFRLZiQQBJprYhiAZJTw4r142imXT9ut9t8OHgx4eRAjpD6jhODB0lHAqvDA7cG0k6JKEnOWSC0qgYSdTKmfHG6IcKxz4BYHbs18Xpg4HleGGFcZ86pVk-Jx1UPRlWrus_TEsRhllOeph0iMzMxjuNx-Nz1nTBrqbnrVCsxj6vRA0DdPZalSE7TPA2rkatU1eYoSV0yC-cgJnQc1iud5wwWaoghzaqKljNr46BnaTT0Wp1J1GqfSasRMRCqeyLOOS_LouAoVOcSiH3uJ1s80KoC4LSbEjMi6lIdLDFDxDIth8dHpSx1qV3XNTEUhAtyBFZTBEycmqtFHdzc1Iyoy7lUZWtQxTaPBghwszF1s9aite-cidwjZS5LSdJ71C7lUEUgi5ZuBMoMbm6Qu1SXmigFOkSAAiAuVpMwihiRmocWrewApWhKhISgYRgSvfu83dW-47Ws6lI9aUNPhEI0lxqyeWVO5sFdX83zmHwxwhTWSBj7UI65t0Fecz62V5SFMdI-z4YNYxtNU9Mi_4hxXXuDFozzgL2fq7XVAgB8z96kNkdHs5aq2d8u2p4gbC8ZaPpbQmoOLb7OFO1dsxHQOoPtRuBg2KBE-wCSBzcpkMW-5HrdFGgAzLaW2P_lffUBApz2m4prXqhf64Ib3RoCzLw9FqIRSfdNgmj-S0bYk7u_tdVAaj8lDoCI1hDf7ghQHWR_Xv7Wf6NZQLgwGYIHCJJa06MBwT5z495WEHuhcpdaOxYDnIS4BidhkTBnJHNnjL4XiJhKjQBJaOrcgEpEek0bQkBKBPuiIXpA7hIEuBu7O1gQtRy_uwKSWWXcG30RgPa80lbhsALmZoAUgd7igAE5cRJq2YtG791_31FI2DyAYykFMaL4UpY3Xn_7i689-u7v_dQHvveHn5yeD0odwZefPSdc_9T_8Fuvvf7aa2-_sTkvWC8PU-LVMPT9UtFZx44YKYXvrjbndemypBsvHzx4cXh69coLd_ujo1rLcjZo2RYvu-KrYYw-0XiAu_nLv_lk3in3nVfqD1O_PrzYLovFdtHE_PDDH37ra6_xsJJ-2Hld3z643J6XjY3rAwYzK882u1744O6hWDjQcHBMazJduoP1g09938X5wkM2DGQZD4-4J89ZyY9feXX37rOTF48uzieVtMoDHpdEoQ6Hd4-Pg207Pf3G117-1Kemy02Xx5U5rfsn7zy5_cor73_t9TpNj77yxYOTG1lcumHZbvGEnz-66PvMXfJADyNOt1940WxhyZvNRR5W5vP2clH2zDwO_VJU-mFkRtAnT07nzdd_6ud_6YWDm7du3eFJ__S_8e-9-dX3AfDhgzu_-YVv9L_0i_Ds2YuvnCxvvPlrX_zKr_-Vv03OQ0oy9LmD-7fvRC02ldPHp6sbN59d1LOLJ8tUNxXcvBK9-ejxC_dult1ZLMMnPvnBqc7VxoPv-MTq_gsAfPLW8z7Bm69_5Xd95qPPz0qtyGlwMwpADAFAV3QUpncuL7_zIw9hrsTsVSFaLA8Bwj2E0T3MQVGbMgwQCREMzVyY0AmRruNCiLy3kiMTICSSYlBVGZmv9ZGAEEgehkEKfn3rDSFygAy8QBCgahWRVlhyc2QiQEqJAoDZI8JMmBu0swkKXD2YchKzPVrEtSbOR8cHWOPRo20EOIU6JGHEEBEkamtAFLZSmImQ6t63YZ3w4uih4KCB5paYqpsYzhsX8n_y-ffGA_r2B_cP1jxXv5q2x30PAew0rIcyl2BSte2y9JK8zVEAhj6nJJvNHDWQQYjC3dxrVZSMxKpWllIapCglQChlQfRxkA8f3Z93pevo7GIRRkl5t12ODgdCLIsGoWMk4pvHhzduHn7ta-984MUXdrsrcD7fTWk8uDGinl4E4FQnlh49drviHvOiz88eySDr1epyswuYgcgdJOVS69B3jAAQZVHp8_pgvDjfOCEnjojdNOeuawQGIYQmo9IABWEchyGshhlCaK2uCRiFOgAnITPNSbpu3F1tMGBZ5pwyINU6n5wclbL0LBdnp13HfdeZkTg4RDVVM5A0XU3CpOrb3WzhWmzou0BIRMhEEn3utxdXK1zu3brzv_jDP1F2BhzzsmRPgTAvWqxc7pbtUnJKVm1adDNNZ2eX53Mt4LvdXK1s54qwdF1ftBZFQh-HIYKAaVnMg8b1uN1NgijIV5tNlzozXaJklt20iGTO3VQUyjQtJXFHOW-miYlNXdWISCIz41zqOPTDwWjn6urTNHkYMS9LtaVgSuPBKsJz4nm7MFHKOdyHsa_zQg5jN67XQ5_zpz_96ic_-sHjjn7xt770N__OP84SCni6WU7uref3t8_PKjG7qc4ThYFDXTQIFnVQlTx4mIOxi0h-9cMfee3rb55v5sV2Z--_C6HqwUMGc0LQUhgZMYDcapU8NFKf5E6XhRKFVZSE4MgBYQDsHpw4wkhS289r-B5nAg1ihggoLAlJck5N26EWQrRsFgIKcenE3I0QgDjllDtz5ZTAoe97VTs8PLraXvXjaKGSCPb4buLEbsaJc5e9GpjnnMs8D-uRI5gEycfUbaZIfbeodznnIQH0bgYpKRMYZKJEsl4PWpeDo7WD1-IUeLQ-6HC-vNqZOQNVc5QMZp2IqTFQ3w8iLtQJJWLijlyrCHuEa_SrfrOdiZE5AYUFRSAQeQQQA-5dSh7Rjt2LLiGJiGk7E3HUGiK1qAyJmIgImcNbFQohKBE1VapWhwDm1qYNC9stMfRj33Wl6jJXDy-1dpLcvZjPSxnGlS8TttGuByDu5gmZWg1gqaWd-gK8VMUuA5irBoKHuTsSEoFVhWinx70KCwHVjIWYeTGDgHUekHCe52EYSpkld6qa87AsNQmrGlUECPO9bJcstDoiI7FHEDMQNDNtWSwMkNmLCWKUuh57s-pOLOxhGWS7XOW0Px8W06oWpeEvInNCRNcAREmpVFsfdRude-x22zKkDBAUSEwNAOrQ9AXtdtKOvXvTru8n2XH9Py39H212brgXBuyvBIERhoCA5OR7FCW2BkF8q8DbAPn7tsC3Wr97Y1j72oKD72f-0SoACIj7_hxEtEE7NjcwX5Mz23iucfDJoeXK4lrP1Yb_9K0AT8NM-d7Ie_0nkTR_J4bRPg0EDuBmTNRsCLg_2iN4Wym09BL5_t8JHtG8mGru0fLBDoRh3lRoxVw6QXMPwwhBNmxLBQoIQVL3QEiJa1UIYAASqurtK4OCCdEBJIl5JCQFj2IpIQu7RRK2WiOAhQmAmAfixhvfX1CIiCMFEGM0hF8gODBzM19cTvWgT4hEDa2I7GiC7K4MjODEHBjuC-JexhyhjNC-1QjcYjz7yw1AFqbABiSEAGIKQElUpxoAYVgB3npy_s8-_1VNwze-_N7NO_3lxcXnf-Zngw5_8wvPprjMfXQw3z3my2e7g_sndztYr5SijyRe7ft-1-_9_Bd_0YHmYlXppQ9_4iu_9ZtzreN4sPD4-pfe3p4tucM7H77_6PGjbT1zNRkGVNoFHt06MU79SX_zO26_-8_mWXjA7tXv-vgb33wD-67Os6xEVvn59ukOagZc5cO62R3cOn7vrSeHLx96QBTDygcHLMMgBweggROkDmadNfd5ta5oRyzLPHer9RzOw-iO6YABNR0dz-8-On_3nNdrr7SbJkazoGIw3j-Z3j99-dteef-N9548vliPnVPceOEWCM8Qkun2iw-fvPMOaiVAQAPX1GVxQl2sRllsfXz4-NHzcTjoc4q5Llq71AEGAUbo5cV2ODpKmdwWr3F-frm52F6dnZ_xxQ3qSjmfDw6Gwz4fHhw9v0KnPK6H1bjZ7HxYbR4_f_CB--Nh2p4-B4Ph8LBUvVzqzZuHZ--9gWnknRvH8bgej4SG-cHx7Rv37k_T6fbS-lV_72Ov9gNunmxGOpoMu3VfNr672jA4jeSg726eu8a16SRaKB-vV2foFJurPuNiTQTeDADkBtY6IrAn-apaprxnD0c4gCSOaHE7k8QNPoABCCHECKDFgIMAeu53NhOw435bhwCIjASmQEBKFRohHmCBFksEJjH1tqLHcAYxdCax8Fpnptw0w1aUhZDC3TEhNce5sLslxDz0N2-MrlECq5a-y6U4EAhTQaymBJy7vJRSqpNwmevY5yS0LIqBbtEJzzUQgBiCKByu4d4IlGfT5bHPD8ro_eb88sbBmCSxyDLPdjmpuTAKExEEARJVs0zkxedQTqnUSki1Frc9exU8IrxaILGgj0NHTFqtVNMm9FAC5KvNQszFtGwnZEKEhidRVQ8QlhvHh77oR196-Pjd98bjoyur3arX2cpmVotlWUqtue9Pr3ZXF1vJggRD1zv4druNcAQoVbvcuTdqKhPFslQSjqI5pYPjcZlLreaqLXoc7tvNlLm9WxFT4o7YAYmAabedE-PBqpuWSYS6JAgxYFdKMXdUY-GyLBzsEcU099kCmHC17p8-fZ7T4O5CscxqWhZzxGRaPGA3LSFQtBIiZsKFCZzA12Me-u4gdenk7k_-7k9Lweenm1C7mDe5k97DjBYLDbu8nILC1R1t0ZIzw5AvHl-GwGrVf-PNZ5ttGXoBFDUIt2E1WjXEOJ9mgJjqMuSu67o-y9X5RoDn7ZL6zOgqts4S1VfjqnMotUzb7en52dF6BMSpVPMIbFM5YEkUsdksTLvDsdtNpe86ArTN3Hc599mBpqWWailRN3RayjiObsbhlDEfHP34j37XJ-7fpdS5lnffeu-_-O__h2lb0GEyDnLpcJkXiJiXxcsCQRDoZgBAEoZMER7otsR1quf4YP0TP_YD7z0_o5QfvfEuQsvPmiQhbk4bFEGtDgSUxGqV3KmZg5NQg_BCBCKbVQyjRBZB3PCAjoimFZm91EAHTBAuOVlRUXXuGRnMQAMAsWyX1Gb8RMEgImNKV1fbvpOcxClFuCQGgG4YdssiecBwUmTEZSp5NRyMq0mroqaU3azvhkQ5ACR3krMgdJTcqyPkPqfcSUL1SNLxQFUrI5bFunUeU_ZSc59Va85CsmcOpz5nTsMwXF3tFrVaFCCWac7dKsIlCREV1X41JGaMmGphSqbOwgpW5tpEnuCWOAFELbWNhInADbQoAuiiOWVmECdABq957NHDhcIjy2BumDDnztwCwC3CYZqmlKRW6_rsoQw4LaXrO04Z5gkYWooRArHFi9WVKADDnRhVSyPGk5BpiDAjzcvMEFUXRwwHN5trQWCvBmCB4V5TTm7Vq2m19WpV1fqcXR0hLHzRRUTctVTvus7MCgEqEnOppe_6WjQgqhVGnudZRDyMCICpuoowO4CHh4OwO7kriBBCENQwojRtd8KsDMyyW8rQMRE1hEWtlXMu7n0nhrGUalbNIBFR8GZZuiwdZ40Ic2QIw-pw-uyJPnwA0l8jOh3DwwwgkOl3vF-_c25rCt5AwuvDeLRXYWOZNuPW_qDH4oBIKcLDA_a5-QjAZpJvhH7YHyjR2-_xHoMP3rBLjUzKezkZBMQeV4SBgUxhThAWEB6thHDNA3Xa80ibcjgIMcDNHfZ9Z_xWoL9tANybvZj22wGMaJhRwCZ1bt8cImyOYwRU2IMvPKKhR9tXK7UxvO9vNPvCA-41Ba5GzKqVmTA4ALSqZU54DdVoDUMmcEMLJ2_jPXNvnh9wMPV22eDG_UIQZqG91SABYcaAfSDKwgSJhLJwsXBwJAgPhOYwhrBoECU137cPITzATXMSCFC18513zCeHXZ94mSsJtOulm6bM4d5KltjSlACMBOgEyIiMtBQlaqlpjDAI12ZBSWzV1G13ufvb_90_fPPZ41rj_FLPnl-99Y03uO-QZbPdrsZedTo-OLhxfHCvVO7S0fE9fXbxhS8-utr4rTnmipD7Ok0wq4zDL_3i3-WhK_MyHAyY-avf-K1AGA7Wl1cL7C6Wq8tl3qbj26d6efrsWZkqp0TYV7WTo5PuZPXu15-98IE7dm7nZ9vVyQq2WGnOQ29HeX76VLyWhXXsvMRw50ZBWejwI5-8v2yn8-Tl3FHY7erwYOWpY8vFax4GNYfLKXU5rQbcXh0cd2NeTVkRHcB51vHohd10Pt66mY6PLBMjj6OQIbN58XI6TW89Ho7WF8-ups3uoB8O1ysT7Po07-Yb4-HF7jlRPr5z99nb31zOr-TmnTR2u8vLedokzkfj-nLzPA764_X49NHjzTk9vP_SvLlyBOQur8bBjQCmZXN4fPub33zj7v2HGpvc8_rosOtXd1_-yLvffH11ePPtd9496eDD3_6Jdz7_zXF9cLqdK-axZziuMN64cfNmvnHr4umz_tbRjYODoK4bkty4Y7Xsir_03R85wHz-_umNmwepo7psbj_84K1i86ZiYL3y1eGN2y8-_NwvfT71KTHUOs0LnHQ3xsObOg8sxORVKyMFOBJFdUcklHmpd28d1WX_i-seTPskY5uvtGpKQHQsbW-WKFWo-2YSkIdLoqadQKBAEE7t74pwO8prKBFahLkJJtw_sPenaHdNJMUt9hFKTEKqHu6E4BBEFIjaRgxhBNCn3ltdFyAxAXG4Cre3VRAzt9WoxcnhWgAX12cXF9HkPimD6W67Q5ax74ha8A5Nbamllzxt5tQnV3fCLBxukhOaL7Wm1BdbmMURIGBRN4hxSO-fLkfrsRLmnDAJhLetBiGqGjCFel6lpepSqxwOUaLvCElwhqKm5s1BQhiZqRTb7UpKzCxalrKAq9ZaNUJyZiTVxQIDyYMiDKsV9cRCCZdpunF0eHJ8hOa56379K1-9f_PEw5dql1fL1WbaVfOIap679OTZeXXv131jTgXgsp3LYnOp6g4BakWLjWO_TnJVdJqmrukINBDY1cw0PNIwlGUXQdNUeBxTSlAVWXJKZSpuGobmQGDTdtlZPVyvAJyEGaDvu2Ups3kK6rsOHTIjJq6lDidD4uTmw9ABU3gomrsHUrdK86JLsaUsaVihG4C7aWYmXNCQEV-5f-9Hvue7DzoO82WZlKhWnZZdgd4rrsa0LfVqmtWhYrz_7hkwGbKDHRyPm7mWWuoSV1MBRmZYljrNZykPTLIsC5pdzaVfDfM8l0WtGqEMXQ6OMlctRa2yJEDrhhWh69WMWZKIcrfbToI05J4QVEuZCwBI311uNm1YVup0tRWWxMw5ifWJOB0erzfT3DNrn3gtl4-3qzUDhFB37-GtH_7ezzw87C-38-e-_Noc8Ru_9sWLyzMGVpEF3OaCmSGw7BTAo1qZtRsSGoQbc9aq7oVYiEQIKUMsYAz_-r_5J3_1N35rYX7hwd3pakd5b8aI0qZoFtf4u1AjRlevy7x_MngFCCa2UlM_uqubS0ZgCVdXBRHiVEtJw-BqlNmqYaCVBcBFA0G9YHgAkda5NLdO8-WV3dLlPLuO6zHUiIiIpsW6JABoAeYYqv3QaSARrg6H6rZUBQhJ0rLSkqV4FWhyn0h9Rx4saV6mo_VBdUNmK9r3qSohSJJstY5Dj1Vl7FOX3FWEh3U_X83DwThNiwDlTsKRa60p5mm3Wq_djYQJEAgpNx4WGoEBdUIE5PspL4VZ4mQOdQkMDo1rCjICenMV2rIgckAQiy-FSTBHLQWQIyyJoAOxXM8dPQiSUJlLWABh84IubVHrUZZ5GFbzMrlZy3cQSS21VuUkQUjMdZmFRVJWreZBzFpNcsdM-3EFIxFwJ8tcMucu8W5q4HzDgkzYSSo4hysGaFVE7rq83W2FcZmWYdVHWAsyI-1dBIxcSunTMGsxtbETEGl31EBU1dz3USsgE3ANX1QPurGEh4GCmwEzVLe6aJeBASWMEMsCObFHnayuhqGGipNV70hqrRCQhJdSufNeusmiNUKbpnEuevfWYS_DsO6wejSFrkeAE0E7jjdhBe4FvoFttBbhroG0P5_vMy_tcozNGO0tDgt7eD0B7BvR-0k_WZuImwcGAVmj47fJeni7A7QHeYQjkVtQezETuu21O01y6ftJfUD7GQGI8D3LM8KBop2OrwM8zUsACGF-vXrYrxj2HeMAYrQ9txugFbUb1R8pMBjZ9tmgSELeigXQKHuA4RQNxO9tTd5uTdp6yREBwMJqxkzXSSdwgO00d8RDFhKyiExYPQDB9sYhAMAg0HAAAnDGRueJCBDAhuN2DEKwQAJgIfdgZHMT4gYLN3dC1KLR-tpE1IoQ1ywmBjJ1CNBmDgZSdUKsEV40On965nZjHCQxeMP6syRoKyABCHRwjODE4WHqRMQsgJBRllr7LpViDuzA4JWZIgAJU-7efOOtC-0_8fDDH_vgnX59sFofqvrN-7eCPCOWUggprgVn7KCcwNxQlzT_kT_6HxFh3c0oGYK7LFOpXsAWKhKUaixBblawbKOXfLpdsO9X94_q2S6Wyp0M68Nx7Lph9-FPv_Ls2dmD-yef_s5XfuVnf321Trcf3Prab7wFLMQ0n-9MvdTh1W__yPFNXh2PW4eXPvzCyeOre0erf_Jot751NPZl-2xz8oEXvvGV9-596BYxHawOd-Xy6OZ6d3keHYeFO1xd1vWBrm8efPONt-8MHaS0HrDjVZnLjZcebp8-PXzx1lIq5R4FY57vvXz3rTfeupPTg1dvz7vLzdMnH3nl3tWMviurlLEiaprqdHznxubp42m3efljH9WqBzduUNf5ZsMIR0d3nr3__IWXX-7T6ptfe_2rX_nqhz78we32spOsU3X18Nhels1qd-vO7e3luXRdIVo2C2yms6ePctc_f37ep9X2yfnD7_rIuzi-8p2fvPrl1zzqzTsny3gzhI5ODg8OhtsPjs_eP18d3UTuxnW3Xh-mZL_whaffBqtVolMgYkcHLomKq8Fj-Gcfkh_iVCvYs6uLg8P1iy-dvP_W2VApON06Pnme8WgURCeCLAkJ2sGfEhoQQZydb05ObmAjJABCOBFeUwT2HB1qiR3fI8WKFYUQRGpoMgByDAYkQKDqxojVjZHa6EMo2X47BoyMBO6KRI7RXFet099qPO35BoQpcVs111qRmBOHmTBZQ5S35SiRmTkBoyNzeBCGU9w47I_67uJqIUZd6s7MAPoxuQOzIMe0W1ZjN_Y9-T5xkFMC3C1aTC0Q5qlgYnOYQIUEzAih42TuGKSuFMBCrqaIm7l-_c3nH7yfDvtUFYXjarsw4fogJ9BScMziAVfbHQaq4-XZ5d1bJ33iaVnajMD2JvnmUaFZtaiCIGuTl0EgIGNHGZi3cwEkCDDTQAwGAlL3vhcgPDgc1-sBLIjl0XuPPvTgTifdu88vnzw5LxEgYmVp-MZagXLiqr3IMqsRhCkheSghhsUwdu5u7NM07XaspkhgVYmklGVc9VcRVgsi63YTEMiYE6kWq5hFiKnMc-qEgLfTwuKEWM3ArJaJaOSUcoIKpLstEoPkuszj2DEFCd08On7hxkGYW_gwjMsyRSInIGbKyZaiSwWP1PWqBmiGDjD5QkNK_-q__HuqehKi0LIYhIFIeGy35dmufseH7xb1x0-unp5tIlNFfH62PStF3ZZZweLsYvf09Eo95kW3u13qBJE482aevJTEVopbMSSUYoIpk6lWFt9dbJfFsLiFV3UkS1muLjd9l3NKm-2ERONqeP7snBKba-76LueyaECM1E9cyGDazaA7H3ugElWvLnfUp_XYXe3mO3fvXT59JHlVYlkSvPTw1o9__-86Xo81li997Z2_-t_-WjlfgLvf95M_Ms2mkpbiu6tZlymQoRhUQ0Kwpexqyhju6sEiDePRvDlFlfsOHHfzggwf-dCLf-W__qt_6I_8wd3FNndpmnZaVBK5VSQMNUSwhgdAMFVqRxkATh2GuymgIaFbbS3BcMcI5BTupmoenJMuMyAQcRAigxdNDHz7276XhAkRwzWUmJC4mJobiYgIAA6rAQIBULVyyl3fmblICohpu-S-cw8PJGFOCQCqaS3aDT0zdZ1odUc0gHk33zg6aLvR1KWDw7WrDeNobtYcQMxm2HcpSeLA44ODYeyODlaroesTH65XJ0crKDauBjBgSW262FxOCBGEw8Ho1YjJA5LIwTgoxH5sahEMfdctpRJSsxK21WrqUth1VsSjT8kg-q5zc2ZhJHUf-tHdqzk3zXJ4lzstKsKcpExLNw5lKkmSQUiSZiUxc0CWlMNBzTgJeIiIeWRJSykpiVZrJ8DEolUZAQPU3bUVSTVztlIdIXOCAAJqaZ9E2cMxkDD2XPnwCBARt1BVJiEic0UgIHDXNkBNQqUoAANBmHOSyWo7tqauc3cIMLOI9qGqm9UwSIwQU12YqL3DMLMuVRDRqgiHu7CAe5iOXc-EZtp3nbuP0qtalzO2MywiMXDiWgARGICYAIkThHo3jCH4A5_5eHJE7LDt0ykA2jO5jcabSCu8LcSbcRZbogP2gkrCcBdmQmogebgW4jZ6P-4zUo2t33Lx1-xPaBGX6wj-HvGzR3Puw_eN3bEvFuxFtdcEoPbz2NrygYTuQUTY0KQeHtiA8dFUYu2U60FMexkxkoe3v9diMNeNg0CA9vPePh0kRMSmVmhvuH3OoH3MTNfW4aY43fP-v3VHsn0RAuE6td9OKQDXcuU9P8e7PiMEIF8TVBGBYp8wQiSM1n8mZKKA4MQNt8qIiRkJchaEa4UoUZNzpcRJqIV_Yl9BRmhmEmyEQUqJr78LTV-BSBTuiamJApCp8d0rAAWMHTNg-54xM-K-2ot7w9q11TiAWTCACFNbF7aFCba_7h7u7mrl5p31d3_ylYcvP7zxwp182CvC6flFP_SIeTctjlwdl6pmsFSr7ku1yepuV_Lhjb_-D36-FOUs3kkg3jg4mLc6VZ-WeZAVd6lMuyGTBa2PDvON8fnji3Q0ro7Xz99-DAh5WHWHRwfr9ODBnbsP73zuc-9_6kN3YzYgqgiY6MnTq49_4mWrOs_ztMThgwcPXrm3HoZbRzdPPvzi7RvH05PLhw9Onp3uLpaQJFe7enxyvJnKCx-4s0AM624pVTq5eHp-54Xb07wcHI07tWG1vnlrePreRb8ep81CCdEtd7K-e-utr71---ZNorTZVCastpQafc7ovt3OEFK3V7uz3Y1bN4vaKMPs06o_1O0CbJGGs-fnh8fDajisAU8vJ-qyu985PtjO8-bs7Matg1U-eP_tdx68-IBZHj152vfduBo8fDdtcyd9N8yXz1cHJx548c5rvfTz-QJDOjubb988MQjM-XxjN-_fWo2CWG_cPJiutrbAg4fHMpfD9fq333j0gZdPiEggDtbd0OFNVOno7o0xAHOXkfz56aXkNGAWv00MnOliG1Hm-WruBv7mszfehycru3nrSC5PH1vAD_7Ad5WpIrZZEJIABKgbUnzz_fcf3L3jNQIcf0fJF4jobgDeurwBQAxCqf2iExEKNoB9kxUCAAVNtogIXfeASeTa9hnN-Mskzann0ey9hNDUwkjXVSPc_3a03zBnIpIm1iCtxtiEJ47QsL_qEUer8cZ6PD4Y5rlkkdXYuVNVRUFqmjAmRwyz9vxg4b7LarbUenmx45wXXfqcd_OyqBEzEBEhoFu1UhQRVduGAx1chImJhSzasxKI4RvfvHhW6Z1p9_40vfl48_mvPwmrY5ZxHJChFtNpJsYsHJXGVVdmVfBnZxfaEA0tBYIwVYMIVWtCxZQQ3c0jSQKkaakG0OYLFuCIJKS1Dl0-Wo2bza7rsxAS8TwvRbXrB1N7dLa9mibpumU2JzRk9brZLvOiTLgsVU3NfNqV3W4mTqXq4fEKAabd4hEeXksBRACsWnPObl5r1aKO3kva6-HdidE9IqDrsru208XmakqdlHmxaoiEFsgkKRFguFkQEoA7kvUiH_nwiy-c3Hhw_8HJ0VinHXpQ1213O_SQrrvabiXlZSnzbqlTISEiRNBSNHyyiP_1n_iDP_BtHw1Vm2v4EkVrsatFlwK__da7uc8fvHtLALY7Pd1Ml3M5n8vTZ9vnl9PlZtqWOhc1j7JUs4autgqau77U6uFWKiGeDDemsnGLAN9ut4igqup6MAyBeHV1aeqE4WEIJEzzbqoWTJ3kfHm1Y4Sc5OnT8912t16PSFJNScjArRY3Q2w__4HIASA5OaEwHx8eCEGnejCk27fu_Bt__Cdfffjgc19_82_91M__8q98_ktfeXu3mbdzMa1zqcXq6fOzq4sJwbIgyZ4x6FatGDNhILRbSkC4eyC4e0AiRAyssKv6n_9f_vdffv2tn_-FX_jRH_qh55ePvvr5r0YACKAZqLEQELobpYSxh_8iAZK4GRFDqFnjmWArBoQbIbkbXJuNwLx5LCX3Vko0YnlYhPOtj3-fBfbdME1TWBALsgCw7ZWeyCJLrTllYAx3lExIqR-QebeZ-7F3sC73yzwhJSQKwLks42pIiTGCmXLXlaos4uEpSUq56xKgs0iLNau3USMm5tR3pnXs-q6XoctDJ6sxdznduXW06vOdO4fuOIydJAkLMIdAJlwfD6ohSViok5yy1Kpdzn3XlWpZpFZnFl0wd1KqRoRpaIMfXLt8rBoQVTMHB5bWFWQC4bRozczUBpBuJBwAnCSn5IEiwokhvM0jwfeqGbXYD32ZAUMk1VoJG1m_NgwTenQp11L7LGUpANjnrG0DJxKhWkyYVXWPYDdj5lpLtJMgeCJOKZVlIWLOydVb_lRNm5OpdR8jHAJNNUmutTBLa_myiJqmrjNVcFAzoMaNFvUIi74f3M00yKk9g9r8m0VKNQoyrYHIJBBELIzi7py4miFAEsmSzL3LjIiSyNWauECa343wOnqDwunkeBS2T7744MYwUAg2cDcGoAVa0_oC7gVXfu2Zj8bnAUQmBGDiaPotBsBo8i7aEyn3RRUk2vtx_fpesO_YXR_i24K7vXcR92Af2CM42__1OlK_vxI0z--eBop7PGez9bUOb5vOt6dPqy_T9a0iWh7gOrbTzu_a9hRx_XkiEBABhEOLNLZSr3lLy2BEtFvA9QdBgMDY5g6_c3tpnzcgtq-EtVL_tbcYELyphZv-iqjRk4pqYiECcGRq5WZqny8g0P6TwtZybvsKBGy3PUZE3su0wtvZJIgZARJTIg6ggFA1RIBAxz3bFAmQqGXQ0KEFdfb3CuaWnaCI28erISWtFTGWYsVs7LMgglvblrRLYxuvErY8V_uvZngAAgBkN_MWI-RmCQgzcwhz1AgiUDMmDrPxePz1z_3K0fowpT7QTR1b9gPacQ4jIqqP6-6__adfKrNVZOPMudtczt24nuLNOv_acOcz5uDhxGI-Yr9aaoWUju6dpJ53V3M-WfEgvM7DyWEhOd35w9sH9x_cQaG33zu9utpQllc-cv_urZN3333__GJTgu7eP3755upWpvXRwetf_sbt4_HkcDw-Wn3lnUeeurKUg-Pjvktnzy5u3ztxkYUqakWFiycXDx--MF1ujo4P5goQcev44Pn5ebcai-uNk4M-cet97M7PD8bcUXCPXZ8OHhzqpiBRLTaMIr3Mm407HD84AXMsbuAYUGfHnlLXjcfrt77w5odf_eh2mo-O-rfeerQ-OtBpuXXnhlefdpN0Q16P3_zqV1999SPb3SUhEVEvibJcPD9fr49ySrW4jLkqh9c89v2d43C4eeegfUOJ4sWHL3CfLqbtcHTIKZ3m7ubNG1r06Mbh1x9v79w-WdSWapi4BJ0pcR4d0OqCELnj08uJx46YahRJnLp0Oe2IPAC4k7XcWMEBg6667vTJo4vdxY_92Pfpbt6HyDwabw1RmOiNJ8_v3zwxhaAgCG6_ktB6_N72h7BP8TZAwL68xNB-bQMgCNEtEEJY3D2JuBkiq1mfkpm3p0H7UW-szxaSbLrrvaO3nbARG_0T97MzYGJ3S8IRwRRETBSqighI8cq927ePD26s-o54u-g0Vw9nTm4e7kX3NLGLy_nkaOXVvHrXZUlsBvNcatXUZTX3El2XnFCrOjgiaVWhZAbISEjm3hQn3-IUuTsGNhqCB6LAUu3p--fzrl5e7pKAIXzlG49v3R4TQe5Sn6hLPGJeHY5IoLNCohb_wdjzMWtRYoZAEp7LEh4i5MU4SQRsd-oA2MQfgAZg4cLYCz-8fQOJLq-2ZZ7NY70aNpspmLIIBFzMS4nQavNSp1qr1avL3W4qLaFk4ESELOebKyQggkQMHu6-LMVcl6VKygEokgBdiyKRuy9zaY_CWg0bXi3QqvWrzktVCwBwM9eSciq1mFd3G8dxt5uObh5Y9fDoh3Gadt2QCPDVD79y-_BIIw76HF4DaLG43O7cPKV0dbUZxzEA5rl4eO7zvNSWSKjT1UsPbv-pP_wvJKPtZr7YbqOWy2nZ1rpodMOKQj_48PbNgyElAqeL3Xxp-uxid7adLzbLvCwWsZ0npFwWvbjauoV0qaiVUtsbxcxrUUCoWlXLPC-tDqmmEFSWmsdx2u0op1rUqgIxETHzPM-qvqgCo6lXs7KrBiFZSrk2r2gtpZirho05vffsseS-VHVARO76YTg5wDrDdv7h7_vUP_9jn7n_8N7f_bl_-jd-7he_9pU3t1fTYrgUA6ZlWxBnSPzit3_gq7_19dRJTjm8qHlVR-E6Vy8qzG4mkpmR0M2UmEjAzDg8MW2X6Sd-349_-pMf_bP_3v_5xRdvferbXv3sP_vce2-8Py9LuGGTHEXrYLYJobXAG0YQU-vlA0C4t1w0hINQGDBnd93PHBtuxN3NAJBEXEsAIDgi8dGHvnueNBBM1dRIpMyVBEMdArqOKWB7ddWPK4AQkdQNtVRArNWIMQBcAVmIONwDcVmKRbTNu6oJJxa-mkur3vR9t14NWqpZiHBKqYFW2qTTAMN97McuSc65Exm7LMzHR6t7d48Ojw7RwTSSMCEhMjJFBGUpi5Jws5KBBxHnLmGAcPKIlKQdTCiTIwATIbuFY5tcEgkzNWdCMndMBAZJxKtCoMH-a5caEw1QWJDI1CQlBHA3RKIkEIEBQZG7vKivepnn4hBIJIjgUEPNPNABqJqpFmhxZPCqFoBF1Tlgb4ENRDBzFlZTksQk4WGxr89KknDXqpSZ9n1SgHZywmBC4tTQhSCMjHtJa7OnVQeK1bBS1ZSTVrMIof1UWEQC0FyFGTw0XBABoE8JLNyDGKtplkyATBKGRAKIpkUYhZr_mARBkpSiJBRqjOgQVn1_-EMmBA4QJmZmiA4ld_jxD7z08t3bjHxdKY_mwYZrVy41Dn2b17deCLRXWkADOTIh7pmhbaDvLVqDyNKIFuCmCG3Gj4h7xtB-lh8Q2Jby2O7ce_2uBXM7GZM3gRddH6kjGCn2ap39BiAQvbEn92RJ9H1gBwCvx3YA7aerHZ3xulu8J_8QwT6bhESwN3UhEO7Pvg0gKLLfgERA81vBdRCoOb_g-m5DvEemtvZxBLk7tWJx-yy4OQn2Z_V2N0Ak83CL3CVBYqL9VWffw4A9lQih_SI15WcTKBOhMFObrn9rpQLR1qGJiWn_RVZzEtoLGv7_TP1psG5Zmt-FPdNaa-93ONMd897MysrKquqqbnVXNzRSgwRICAGykMEGW8YGPGACA4H5gJg9RUAECjA4HBiHMQQmCIexTGBswAQIIbAQMkgWYGi1qtXqrimHyjud6X3fvfdaz-APa58s7oeMe2-ee8573rP3Xs_w___-sTYw5k4P0FVhMntIRO5pykwYa5DyIHi-SejRms4WADgKCRIEIXXpdXQVMBGtVKboORCMBLTmNPTaoyc4RN-9AhAYdsSrm2FnhSJ9_asf_4k_8f-7vb9_9vy5d-yU95S1cHBBm-bl7tj-5T_-n-rRp6luz88E2VvjxGYXx_uzR8-_Nh1uS2aCMbBcvtxSyuZ8_vTCZlCn8erpcpqfvHz8-INnR4uf-85Xd-NYvR0b3x7unn_4FCD9_M99px5Pv_Knv2_MT58-3gJ9-PI5uR9nuz9MaUzPL7ZJhkM12BR0QqD9dvv27c3V47O7w3Gb9kKB1W7v754_Oo9aL853iknBxjFzlpw2mdCbZ4JBEhK8-eIWws_Oz1Hy9eHGjropWZK4qgiKyHQ36el0-fxSFU7Hen61wwS7y72FbXa7i81-rjfnjy40KJUi2yIO55eXabfb7XetahAJsRDlITHI4XA4v7giBK1OCeq8IGEpQ86j1na4u84pn73_dEy8320yYhIxi_OLPZLMGmdn21xSzL4p-TAv43YzbuLtaX50eV5Dp_6wDcsb2RY0a29Py-XF7qRmWTTjHDFhPNpvbu4Ok8GjJ5fz8bhNZN6weUl4f33zxbvrv_qv-u0xVwBMveEGBAckNPMwv9jucPWzY5h_iRYg5ABgZiJe4zrCA0BYGLCF9U_VbavQS_kAADRfp5iMGOaJCB5K_odNJ1pYXjmeYRBEDD3DnHpgnxHxg2sJuN9yENzHVUzTUne74RvvvwdqiKBNrw_zm_ujSO58MAjXakT04r0rUyfE3dnIGXebjVrc3E8oHA-3WG1Vm811yTkn5NoqAi1NA8Ao-mNAULq4sqREBNqsI4rBXA0CwYPMGhFOc2uAs2EDjkQ_-uz2u99_9fZ6evH8sRmRoC51t99GYKttsxtbAzPvi9ohpyRi7iISESKcU9JZkWCpbhFO6AYGdJqX6srMCP7h8ycZeVpqc1P3TRm3m-H2cFRt-_1WRO7menecPag2NbPZalM1jYg4nOZxMyDA8TSpRa22P9tFgEi6vblH5qpVcjZzIlZrj3ZntTVAcO-yK3c3ZHCAHh8X6N3upaoBEGYBWOcKwHWamSkIcs65DOpOCLgKLOGb3_jwcszXh8P9cb682lHmubW5ti-FUmXIQxksYmk21SaUl2pgTXUR8r_tr_uvCcibt9f3794ZhJq_vb4vOX_80VfB6sVmJHfCuL-dro_tbpqPzSrgtDQg6qVPq-FmdV5MVS3mufKQXB0MwmGQpGr1NKtXQk4i8zyZg5tP0wwRbWmB2NS8n0AEatZqBSQWMXNrOs0VmFxVawswAJ6m43azcY9QXarVphA0pJERrcVmt5UxTVM7G7bf-Mb7v--v_KXn7z37o3_6e_-H_9u_870_96P5MJt6EHNBU2118Wbhdnczf_Ctj3_jl38t3EJNBlHtPb1FUyGCaABAgcx4OpzGYQjziCCMjNICLva7v_fv_jv-nt__P6un4-7Zo9_5O37pX_9__rt1ntxU1XqiURcud70xaCPoESJdBrHa_ggx3BApvM8KDNCxE0SI0CPCSXrhEm2ZiYg4I4Gb8f5r3-lcXlXtjmNtMJTSWlVzZFZVGcYIZ6LjqZ1vz9RbW2rJRdWaah5KBJrWMm4tIsLHzdiaZkmnuZZNOc0VAAkIWcYkFxd7U3X3lJOp7XfbWg0CLcDUk3BJkodEQsKJwsfCjy73-3F4_uhqI3Q4HBGYhgyAy7ysaahrXDFh-FAGCxBhIh5yDgczz3loZkjcB_8i5BFdFRgA7l3hHUlyBIT1YxwDMbBPR5yF1d0iElNKwiIsbNGvQ1JzenBHMbOZzdqXHlBVITAiZBimeYYAYXIPIGAGa2t15h5M5KHa_OGQoH65kKwQQzc315RTV0qAe5c_9QaxV0tIZG5DGa01jRhycXCiFZ8iksxUUmf4IHpAImtKRBDOSMjUnaC7zWaui9CKn1ohmBFMDIzMrM0ogJjMVXLqI89mnkQCIqXUt85FRgNDo5RpSMNxOibGPmuJcG1NEuchIcBYytXF8P6TJx9_8BwcQIMBA4K4i12iM3D6pNsBAPyhFgQi7ucYET-0QGuaV39_v4w2e-C9OK2DMuxzfoT-vTjCqpOBB1VP_2K4Og56L4nrcdnLfXxI_31AyXQYd789VxomPOiHugE3AAh93SvgmtkTD07dWMN-VzB-lzk5IMJq512_tBNTdPDOl2Ux-ENK8opIom5l6e6Eh0Fj9LXGal-OADS1lWvU5_cA1t8lpB6WjEzumlOS6G8prRaHCIjVCL32Xn0ZwthfcCeuIoF0zlEA9WWAQ2IS6vIe6MX9mplM688nAoSZAN0MGYm6Mgr7zmVFjqKB2SZnIhAkZgJGtJDE3JsUAlirfXeLCOx9ynpd_0QcgT3mgzuHJAzWt6xvOAC62KybL4E07OUHL24O959-9sXz954zdA9KuKu5N9dpXobN8Af_3f_Yq6Wc6vFYUk6ZnSCwPHrvg_ECx4JqMZ5tNk92qZQfv36zH7ZS8qkuQHR_N73_jedf_caLAeTK-ed_5tn9D68R_Haa6_18dnmecvn6y_Oz3fnt4fjTv_mn3jvfffuj97f74eT4p__Mbzy-GjejvHdx9vrtXRqGu5Mims91O-bvffLZi-ePN5Jo9NywzXpze78dL6HNY6aZxdA3w3i4uy-7TUbAoMhJMiHDs_ee_vAHn7_41gdujiRnQxZ1YQT2MJcsu_PtdHd3c1zOnz9Ng3QhaBmGV_d3uzJKwjbNP_je509evtfqstlvrVUGyoTH4ymJkNluvzmebufb-698-xtv3749Hefzi0tAc1c33Z6ft-bDdtvv9nG3Pzs7O7y7v7p8DG51qjd3x8fPH5ecSvJxHC5Levl49KW9fLQTsEeb_Unn987ORoL5OJ2d7drczjdythtSGZp6TqnWZtW2m-2p1ji2zSDHwwKB23ETywG8Dnl7fz8TKbR6fXv9e37PX9wOJ2bq7WNPJgyMaV6GcUgo7mDgQn1BAeFBtGYSQgAhCCEhdfuLaQAEEgP06x8cUYjUavfnIEB0DHwEd2cB9sO-PwchInpafL9PhVjNugq5mWEEMzsGYqzet44gA-eUADQT7obxGy-ezItOU83C93N7d3tU82EcxiRu1odZ52c7hmgWnW-xG0ZheP32HoU4yTJXXdEL6wSHkEqRdT1OqK6MDAGZCQEBY24mzH164d5T2yEQmJAAw9c0ECAg5DBXVQAOgMNiv_7j-7wZz0YYEt3eTZvteHc4zdUcQt2GksYhM7FbgBkgNrXezvcxRFPX8BqBzIepTbYg4rJMzx5fXAyDWVzf3SJTEKkqAd4dZ3cdcz6dJmee1C1C1Q3h3e3J3cIpArS5MM1zOx5qSTLuBm0mwsdlAgZVc4tSCgYSA4mYmTsAASO5NUdSNSJW61Y1cDVk9M6xBmdmBEDGOs9IEEAWkceNWSMS1ZZyZqFvfe3lVc53N6e7-8Nmm91hWarVNi1Lr-ZFUhnyMjcmqlWRwcFdqyG8-_zTf_Dv-JtSpGjLzf0tJjzUSpLOtuPHH32wARPhVuustjT_0Rc391oXw8V8mtvd_bQ0VwBQn4-11jofp2CozeqsCKBmZjYvrbYKbknk_nDENaanX7edaNNph-jhqgFIc611VohoVfM4doNf3gwOsCwzAqhpuFESCCDEpSkzKHgp0m_S4_HYFdjPLy7-5t_7F33nqy8-f3v43_1L_-af_jPfm-5nE26LimCtWhc1CLQWXkPVCL7xUx99_7u_TozRrDqoBjHZsoAqI4lwSkPTprWWnFWVEQMqAnu001z_9__sP_UH_9V_7bv_2S9Tpo-_-Y1vffvb_9a__odbVW2NKLoIARGJ0axBAIYzi4d7z-8jhEBmCTOEtcTudWuod2-b1UZCqyIoMMyZgRBcFYnClc-__gu1OQY6hjYtYwEACJtO8ziUtlROCZHM3N2HUg7Hu2EYiLiL7G9Pp5xyyrLMRkSAtCwNmRJLH8932pSpyZDrsqRBzrbbpdVmJizz4mWQZlpVTTVlcQ9i2m4HQhyybEoas2yHcnV5th2yAIKgBXKSUmSZa5hjQASRYJ11M2ZEDOYumPYwoo7xDmJ0is5U6lTUQGLhIVMgpiTVWq8VujobVr0WchLAdUFpbkCQytCXrUK5NctZUimALiLuRsxEIJICnFZz0VrYEYq2OqYCwVaVkJo2EoqwCE95COv-TkQRN-fEEKFNSRg68HHNbxLEAI9eDyFhBPZ5BgBISuHWq5rgIEDzJsymZubESMSIBOZaGyKYuqQCYKEmOZs16alMCOCYkFS73ChcHYXMnEUcrGt4zM0hxmGcdRmHMdzDkRMxkxABOzhQIBEFNBlknlouEu7ClHPKiYsgs-w28NEHz7_5lReCRIFM7BARPSnTV-J-jwPAVYqDiB1z0SWzPRMnoiMkH5qGFbf5QMBEdPdAjMC-ykBaU7MiAtdFQxewRI-NeaBvw4OjeN3Id5xoL7y9S_OhD87R-wesMnxcsTOxxpQFASAFBji4ea96DYC7SAYfAKO9cn2wIVhYX2r0ti_Mo4ecQJ8T4APuv1OSuiLf1_6wV68RP6EmBTpGXxy5wZqT3L-fh--iSxHcgpgeMhT8Yjeir2BUYn6AEq32xL6j7NmfPTCDVt1tMHcE6gO5FSAnTn3C4WucwtrZIPaNASLxmvjbuaVdD4Ue0R93QGjmIhzmy1zLkN2DBMacurZqNRggOoKvuUgdqLoWSdKlGvQlILa__uhoXZKEQBBh4YDYXAHC3QAAKVpzYLq4OkuU5vnY1y-MENhDw2zS9npq_9Z_8svk5G0BgGGzJSETknFIoxC5BaNkzqOU8Vh1KBebMg5Xm7q0QChj-uhrL_eax0gwe5ltupsD_dPPDrshlw2fleHrL59lxsNds4gPn1xukL_7q5-9eXd7d_3uxfOrX_vuJ7_1z_-paVrm6q--uHFrV8OGhd68effRRy-OtweqWpjI_fbN9e58f3_76ux8NztmohdnZ9dvbnb78-04gptIxtD9fhDz29evrvYXREII9X4pGYiFEOfTYsaYcTm2gHj08Uuu7YvPXl89umiuj_cX8zwBMZfxzWeff_DVJxFEzVUN3DYDAqK1tt0OmQidwAwD0maz1Abgu-2uqrIQBIlIvyJ1OY057c_O7q-vz853jBwQx_v5bL8RcOJ0U-vIeQN4Otnl5RYYo8UPPnn3aLt9dL7zaSkp390cxySXeYMIyQkgomqoj7mk2gZ2RjzcHvMmn-32qgbBbsSJlsNhm8oXX_zov_5X_xU-VaIHUSJEZzN-_urmYrvtGyYiUtMA73c34LqIM3_QjyEiUFNNRKtQrj_DmLoiKIjsQWnXeWIQPYSvB_4FIyJS5mQdZeben5hd94yI4S7EBGtSh5unTB5astQ2P3l89Y33niZAgdjutndTNQt1d4bEXBWQWV0DnBlFpOQ05GThU9XNOJyOy9l-09zup4UTn6YaAcBoYQRMBMSUejLXuprF8DA1wj526XtUFkKDIKTW1D04YVfrOnjP7eiktZwzreOZVdMAGEefljfXH37lhRsxo0HcHSZXm5ZWckpM6gHuQNDULWCpigGJiJHUfDZ1lMWh9pmZ6W5TvvL4MhwO93cypKUaArZmZRwCfLcZs8gg-dPX7yjL0qwj9SysqQFSzomJ3HzR2pmqgIDCp8MRiNfHEyAADCUhsJlprcf7GSXMvDU3NwsPU_LonUBKQgFmJpJcLZVUq4b5vNRcUgR0iVdKFO6hSgBlyB995blIevv2br-T09wkpXmep9O0LG1pevHofCyjWhMpx7pAeKtq6IhBAr_zd__mbz170Q7zcbqdTZng8eXZsydXT8_33qqqvbu--_z6dnKYmtUWeRxuDtNhmg-nWj2qqqmBoyBUbcw8VwWC1O0XAQBR64KITWtTzTkt84KCK0yO2dzqYiIp1AIDgcqG0QG8IQSLBEZJ2VvbbTdh4WolJ3M301IKebi7qYNhW9ybLnMl9_OLQUB-9usf__f_2r9sO8i_-G_8sX_5P_iP5tOkQnfHKaKejscevUfI1k46T4lFihDL5eXuB7_-wz4YJQYIhbqERhh0zX1rqtY3byHESG6uKXCa9e_7h37_D7__3f_rv_SveZss9Ns_89N3d6c_-8vfbYshA6gRoHnFCAxfWQARyOy2TqqI2bThqphbeScsDKYAASwYgSSM7G4sCTBcDSG6m9BNAZ03H3ynNc1jcfeO4gnEzhPISZBQtW2256rNMeZ53ux25i5cmCW675CEGLQpiyy1BgQyJy61qXtM01zKUBXyUE7zfHm2O9tt7-5OuRT3KDkD0u3Ncdhu3L1HipYyuPrFfiuMwjiWNG6GRHZ5tifkXIoHMnNYVG2UMyBahKQkiQSJMjEyM1prIuLggUDM4V5K0mrC6ObIXOuSEQXIESV3vKCDdzkilZT6RBOJXK22utvvAqwj5CUz9XGEEDGHY7hJEiQyMyKCwKaWUwoLd085WzMIh7CmLjkxgbWGhNoaEgOxhwv2KeVqrexRAF3n19S6PCMC8pBNW3iwZAdU1TKMhAgdyC9cq242w1KbNgPu4200M8BgJreQVNSMmMCDha12kGjPlPUkTIymhoSDZHVnYQwnYgvr62lTTyRdFd2xAeHdPcksSP0SRTR19yCKTZHWDLsTtXnPjB4SvfjKxUUerjbb3_TND58_uiLs9Ez2sJ5Ou55z_TfdS_OlemadfH-ZU7UWxH2WZR7dlNJZOhHQy7ov59aBKyXXe_juquxfy-Uu5ehdBK65Xw5E4F8KWfABVf3AIV2NfS7M1l8nwk_w8iuLFDtKsxuO4cGu-1Dermf-g6kPCMnWlGB62HfgKmDBtS8h5OjW4lXGTw9W6dXK3CGD1kuPvkRe-eMYgb1m-VLEb6b9MzBTdzgAoBswBwIMick8AJgRPNQiAAEJHloQwgdLNa1dU-J1Us-0DtEjIjH3_KPehLDQWqxAdG2jqwMCA1LfdvcMr5_ovoiRAKCjQgGJhZopI6iGCJ8NQswMIEJrAESXO3SuaziRrFaN7hqnB95q90WuxmxaGwX7Um3WLzYCx4hAJ0AYhzGQpmk6npZhSFV9mptDRMj5_vzf_vf_hNYabpCilJKyQGDilApjeDvVANxcbPM2L4u2Fo_Odpshv331rtb58bOrl08e3709SZtfXGxJfED4_uubu0UfX24e7YarnLeJv_e9H3_-6rWUIkzXt9Of-bOf_8x33r882233--98-8ON4A9--Ortu7khAbREvDsff_jJpx9_8GJAMpsH4LDAbG-O91998TQIFsC95MthgCBX3QwUbkG03RRfZgg-Hg6SpQxDyXJ_cz8WZmKPGMayO9vW04kx3r26vnh0dbHffvDyxfFwZGQAXKbGJceCTtMyL2V7WXbipjhAGUcKFBSbp6v9fn91-eqHn33tO986HebD6bDf7FI4MGhzVd1t9lbNltZOJ6_66P33bm_fbFK-PN8CorY5ZX5-eSYjtFqfXuzAKudyqjqWwuH37663mTaZz9kzwoD4Rz__3i89f3a5G19u5XGhpoYgmzF9fvvF9fX9hqCCT8fp0eOzptWZMYkR-jwJ8fXtmz__t_xCebgFwCM8CFgYv3h3-96TK7Ue9essiB7rEb7qeYKJEMEtCFldaeWY9RHAGg3Y0b1dsAe8PgItrJt8kYBW5jcQUp-XENMaIwxITH3NSLQO5rD36-DMQRG7XfmpZ08vhiFCBWAOur65XzTUo2R6_2LbjO5Ps0Jst4MQb8c8JB6GAYF-8PmbRKKmLLRJ6e27eyCcppZyMtO-JAd3hGAWNbduL2QCgM47z0XMY65qEY4gzFVb36mCW99ymBoguQYgNVUm7mcZM_FDWKN6hPtv-eZHm2Ebgaelmas9rMnHoejiqm4Ri8Xd0o6LQTgTIWILa-YK0AInrR2lAxAvHz3aj7lH6zATBIYHCaXEwjy3drHbqRkJffH2dlpqU6euLyCaq-ck5t7UgoAl1aV6QK0VEKbTQh6UJMCn00xC6K7N3Kzs8nyszhAQ6oqAbdYe3NmnioFg7rlkCCBmUzdzQE-S0DnlolZddal1s92q1q999Su7sRynaRi41kaE1-_up2rHw0QiYSTCbkZEczUzdVVXb16Z8Obm9N_-S37rfD9_9sXranW3KY8fXzzZ7RmgLUs4vLo_fvr5u5MFShmG0QED6f4wzXM9TYsHLktDgGlaNpvCjB1Uj2G9-VHVfpWbNgA4niZBIsbjcVqfzczW1BEoc1OlxOtp6wZOrSnlAg7QDBGDkIEZZLzcffD0-csPP7zapedXly-fP_r4w6dlny6v9oXxxVe_0ubT_Zv2-_47v_e3_PTHv_767f_xX_n3X796e7xbHHw6zPP9EtpSQdfGLPM0tWXuXXTKeZr1q1_78Fd_5VcBQpi0l9TVuqJcdZ1pdUZnW6ogBHgRnk_tt_7O3_5zv_jNf_x_-b9lJPNJgv7C3_2X_uE_9Efvbu5abTkJQFhtnMgtiNGts_3cYeVuWNWua0Uz7BO0Tj33Pq0KREThgHA3ZLLWELoX0tdBZwRRCAFIyW2qXCSPMh2nze78NB2JkjqAeWuuFmpGjm5xPJ1yzqrH7WanZl1DvBzb3BqxNFNXS-MwtyUiWquSOQiHIVn4WErX6mj4aWmbIbPQMrcG4QHDbnN_d5QsgOQU1bSQ7Hb7kkgSj-MGLAhxWXQ3ZlnawHJ3f8wF85DUw9AjYpmWnDJEc6PNMPQEEHPnRJSyasuSJDiwEvNuDO_-NFUiTsRdjK0WIqzqFOgB7uEQZRyqVubkrojRI2GH7XaZZ3MrJU1Ti-625pVcmYQWbQjOhLUtBEzEZm4eZAYRyJwJu-u4WznNzN0CkFkwFMyRWNh7GhsSE4DVxbWFBzKSYAKOuT_lXN1EuKdDNzNmBIsubV6WJimFubnnsqnagDEsQN0hOKW2NBIEDEEioNqUECHgYEsS4gDV4ExmxgI9ACt6iDoxMUc4RDhGz1B2M0pZQwMis1TT2RkJHCIchjG5e3J_frn5ha-_p0c6342ZhBndOp5TexeEvuZ8rUVyN7WtvBoI74BNWn9KHQqEqO496NX7GnF1Gjsj9Rk0MIb1QyPcApHcMSKAwN2Z0cMj6CHWDl09VvlK98t2FKjjqqLBCCPiXhsyYefb4DrcwPBAWkH7_eaEAIvAoAhHJlhZ_oHd9MPYq-Domb5Agehh5ACJXZUAg_AhUwwcnKBPtREA1JwQoEcRhwKA-U_2CqsciZCB-0JDfS1B6CdgnC4dDOzpdoBEQYiAXEiIHQhbUyRiN0RaIRu4ankBoLkjUEAkZu8SNe_81nUb8JDSAA4OBKrmAIHOiD3WtxsJwqyPGdYGrbuy_UF7R4AIrgEIjuSA50OZqs2zmvluzOHgta9ygnrB4d4XMtQ1dB4ODg5f2jIREEkgrGvMgNACu98JDS3W1xAdjxRuiw7DJm22m3G4fnd7N82X-60ZOOrS2t2rqRie5sZE0AwWH0qa5xPkBmbTcRZEzpJRtLoqbLfl7LxA-MjUKj39yuPnj86Ob25fPDs7H3LT-dPX18jmaC9fnOnd6enVHkIXgEONi2F7f1hurg9SamaozJJkN8ogfHWxm-OwubrQZfn0e-9G1f1mAEQXHNLGPI6n4y7vAk6PNuPb-7tqAdt01IkphkGI8Hy3WwDHgZijWSDR9c3N_uLxdDg8fXZe0A3j5ebsN37jk2mum90I7o9eXN189sUA71s9bsay223m07y92N0tS74YHseLTz_93uX7H2TIlPZfnN610_XLx0-bzVLK9fXtR9_84OLJ1Q---2dffPzTt_fXx_vb91-812J8ncvrz1-3cGPfnu3afLj_4g0P2Qd7Nd9dpSesYAyHWoFkJDGYQ3WTy0hpAdTltN9uXr68NKV5ns8wHu3Ss135lZsRwa7v7l7Xu1IuHo_5s5t3Hzw6P3vv_d1Xh4Xs5jh99sN3j59sdL79lV_7_CsfvHSLkob71-82Y74_zbshowMjIAMGmLo3J5TevzMxBrhrF55aBBE6hDCrGUYgYrMeha4aAQwICE5hhkwYqBGMBL7SQj2AiZnIVZHZIViYkSKieairYOrIOIcuLg8hxPVSd8CIsCTs1j569Pjle-dffHEzblEtZJuW2xmB1XReppJ3r--n67tlSFyGwZvfH06bsh2Hwdzf3J9SorLJy9Kmw-m9JxeS-HSqXTSXU15aDYfWVIQBw8HnZSbgJH1rSykLEoWuK_Q2V-rfghqAEhAI17oI5-YWYGA-5Gzc12yGmMyVGJkcAd67vHjy7IKaE8PpfjotC0kqKT263JqCoiNicz9MbTGflkbQwhWGYWDu7GM1TTkzqINcXew2Y26LEqMIqntdFo0YhyIRc6tWF4gmidB9Os3IbG6AYO6mwYynuSFhVdUA88XCYtFSxqrLmIVEiDnvNuMwTtO8tKn1zUWwIcRiHcPm5iwURELgriHkDqZmroS4LIs1CwxkBnRzS5DBI4DD6nSaBKIIzXeHaoqSpmYKrm7uDsyENOlyfa2PL84Ph2VeFAhaqykRGcFS_7a__q86H4bX16_LjoehPD6_2G12S5tv7o9COM12fXdSZiZRM1XFcDUHj9O8EGJoh1TCsCmJ4ei2mGKiMKhtEZFAZ2akJELhFmYQQAZnm81cGwv15jUxhVlOBSFMDY3MSVWZVtbzVKf91X633z599oxdj_X45vrd8ZMf6P1x1sicxqFcXJ0_enSBNL5-8_bpe1_5O_8Hv3RU-xf_rf_wzau38zw1c9dZq0PD977y3rtPf7Dc1c2-zNMc6kwUZi3cTq7uv_7r3x_Pii7uZoDhFqFVkhgyAKhHR8oHGAsFKTt74Ld-_uf-R3_77_3b_3v_gKSkNA2y0Qqx3bz79C1ESCJTBVVJAmCzKaAQpwiNgHBnZjddsZdMaMbC6g0QmKQP7DgozPr8D4i0VSJCRkcIDSZZg-0tqJkhumQJ11XljIHRSbSUU3ZzbQsGumpiCvd5XgJxaVXdbu8OPTttnqsDMmfOuS21VV2WhZHCyKoz5_CVNuiAzXye9d3t5IhL0wiwQK2-250RJPVQj-benx0oCYCGIWOEmU2nquq5pE1JX3n-aJvSALzbDOix2xRmgYDMGYP2ZSi5lJRSSWBeSgLXXUmlCDEQRy4plQKJiclay0UiIBdR1yREjCysGgGRcmaiROLuANCzgUSk1vni7CICVbWMxWIVjeA6EEUCTCk1cw3gkgOglMFBw7UPGbuSKnX5uCtxz0A1U9XWTC0JIyCxIIY3hQgpHB6SpGezqnoHdXVheYfOBjgnMgvqDs4AEiaIlFKzcDcH6z9tAwRmMwvGvow2C2CJACH0sKrqhmY-lKzaACPAa23h1sU_4YAeZkq8uj-7XaFpbWpupqZAoB1Dg0CMi7fhYixZ9qXoScYyZGEM9-YEYKD9q6zt6gM737sSyCPcA8O8LwfQ1aI7MN0AwNy76Cuw3zLm3gWrsFoA-nyuS7vjAev5XwEBdW-FxwPuZ8VYx4qxwQACN--VfQf2ENEDBRQ9eoDvwz_u-vsux-8egBUL1GE22AN4-74ACc066Wi1IaypARFECAzQUV9fokgBAMDMtH_X3jugIKLVqIdfWqHdu17uoTGy1UsRwgyxfjvrMoMDGQA9KHowISMARbNGhEIkhCmLSND6PgJzH-k90NUACQmBIIAAEzNE36AgExLAkKSv2h7GpvjlWwHRFVNB3bIb2CPM--UNHokIVvM1hMMayI3kAW-neTvSNqEAno6LiDhhV69FNxBzNwGjuwlDB4OYu7uFeffAICJ1CRsA9UajrxG6RIOYhflhF6DuAFYSjSIXF2fHwzIty5AFwzaS_tR3_7RAeG27Tc65l4ABAMK4TIqAaRi2203Pe4lmu90mhL_49A002JxtHm3TDuE8RcYIq3d3869-crNgOt9tG2B4SEqffHHz_dfvQqgt06vXN1bn5c301ZdPr_bDNtFuLK8-f0WE6qjHend32m_TsixXT88o4XY7pCGdwFzo6ftPbt7enA0ZGjzZDUlg0TruxpKTJKoxZ4pQHTdDzvKNb35o8wTWdmNJASUxNr07HK4eX8zzTEgl81Ayum1HZmFihoR5TDJmMkOzMeN2X27e3RDYfovvP76AlM8vtu5xak2FfvzZ6_e_8r4utdW7q7PL-9YqwfHufiA6v9zWCBykEQ4Xl5T4_nR_Pl5lTwTgsTy6uGADV3PQ4SyBrKFbw5DTKGZRzd7Ww-vp-Id-8Bufvn39ydv7vbaK86_96LMjpTdp_nw65ZHnAY6naZR4tN-JhTIu745yip_96MVnP3x3f7Ky26U85FR-9Od-XVJKLD1H3tRYYKntbFd6cK-bR3iWBITEQIAQkZjXgCrqdnlRU-lu3UAGeTD-dg0jIBIxCEHq_hbAQsS8em1tjT9EQhDJptqdAMRk4Szo0Ol-3oVwhHG2ST_70YdXV2c__uK2uvcR29tXp6m2GdwjqocwAuCQUyDe3RwifLcfBeH67nR3aqemSOnV2zsiSCWBmZsRCxMws1MYgoE3cABUU_fAgCRcm5rafjd6NV-sm5cRSAaptTGhgwVwMz2dZgSZ5xpulFiSOAQaznNTNAv1ADVzlZLy7_hNX4sl5qndHw_VGifOzJkzAROCUxxbu5_qrNY0AuG0LM2MkswRbw_Ht6dTSfTBNhMSBrTqdanNjShOp_toDgFJcFuymTXX-8Pp3bv7493ExM-fXBIAEqxUE4zEDO7aHAKoA-E8AOhwPLlZKoWY52k-3B8BPTjmxRCoQ4tS6qIptmqlDEjgHoTCLIQkIj29uIMsO2k6AI_z3EyP010gzqejUGIiTmS1ASAzTdPxONV3b48TwGnRaWnLaZ4O9fx8r6HXd7csgIh9_j9P9x89v_z2-49tXqrPOcWj892Y0nKa2tTOdyMx3U-1tVDDeao-18P90Vq9uz3OSyVASSJCwiIQowgF7caBERIhADEnaxaOjEjgBCDCnBgZmpsRypAoCRBJTiWni_Ozn_no_SePry7O9pfn-epsQOvaQwgAlnxxub-8Op_a_Mnnrz774evr6_uqhsNw9eLq6qtPx6cXMdKc4m6-_cVvf_tv-m_-ru99fv1__9f_2Oefvbo71WpWCuvcXDWovXv92d3NJ0TRpkoegoma9RPWIUqmWutm2IA5RoA5I6ZxsAA3i_CcEguDK5E7RDgFIMrmH_rH_id_z9_6j1AID1hA3HHYn-WIHA4BjAFuRMTEgZRSP2gczIW4A1mJkJjCA5G9a4MJw4N6QGZ0qlh_4HTX4RqlhEiwHqeBCCzM-w9_oamCWcql1QUhMJBLhmhEIJzCkAnVdCw71UXStheV0N2u1cqYm5qHhXkq4h5CYu6ttX5kbrZ7NzXTlNJ2s8lFDoepSx2Gks0cmUQSAJipJJEkRZiFhGA7jOOQc6FN4m0aA0ABj6dZRIQx55RIApyYzEGIMViEISLQU5YuTrbwJGkzyOq0JAwByUndkSCnzEgoSIxVfRySWoxZpsUCg3MiIIAwdydE6A4CrK2VXDxA1wRfLyUxUueOm2rKqf8MMid1r9q6nWtNRAJEBgxUcw8PcxFu3jFPqzKh45-QiYRrbQSIiEMe1NRMJedwY5Gu5woPKTkiOnKn24Nq1Y4S6gl_WRJ1w1AAuLsFZ2GW9XFlzpk5iJEdvanlnM2iX3AeLlkQkQhROGy1UmBKTCBZIJxJvBkjIcVYSk9aKDk5RE5SsmShUBPCnBKFn23L46cXV7vzkrEkRECgbpTXLmXvM2kiMugEhxVf7b5mLnXne1fXGwQSebh3fcuqFO-RAQ49MQdwleEABIRZ9MnySutfVfKr-ejL8h0BY1UOOT1AfgKia09Wd-hDcq9HwNo8PBD81-J_DRYOiC5TXnV7tHZM3dVLiEzkENShoYgPWlmACPRVr9MDqgTJVwcurqTwHtyFwEABYWYG2KIRsD-8p11NRAgI0exBfL_-8iQC4fiTvos6MYg4rNqzi90uCXRLLmERak61ajcfMQICMGDPOCNcUw3iYW3SXQpM3A3BiGgWGh17BV_qqbr8plNEVxwRgAit3wGtFgsm-pJXxExrtLH6IDIWKTnthtJjj-QBqwXxX_E9BzTtfulwXZVgKy52hcpGV_yHAzKFr_lN_rBr7VZoVSuJCCUcEGO7KYfbY5F0XBoL_3_-0-_-4N0rU1DDaoFSzp6fffHFW2ZcliCCi4sLnes4prl5rf745fnt8f7mxxMxfOev_NbXhuGsbNvt4dE2OeiPb-7fHY4_8_NPppv5zaevnlztbbbb-_vvf3Fdxny4nV88O__4o0cCsR2zVn35_PGTIb97e4ub4eT19jB5gBBCQFWHLCOn7eb8bpnQ4enVxe3t7ctnT7747N17j6_KOHzx6vXz956_--LddiyZKGVhEbOWRTbb7Y8-efX06SNB8EUVgtCrGnGaTkfONObx9voAQF_9mW_evTmGugkroEYDw0SUdsPpMB-O9eOvPi1Cs_q4y-3utDvbzLUBsXDcvn73iz__9V_7cz8atqOjT1P98MWzd_cnilA0NggHZLSmFiYDnu5ev3jvq8xQW337yeuvf_iV8Wx7f3skrZfb8fmTK8x0e_suSd4UAaAnj54MZXi8345nZ598_82e8_Ozyz_-G2_5xgDx7vqajYznNGShFkEJ6Owi3d9Pj_YjoCdmdc0cbbq_uz_85l_4mQ7hZoQghvB3t8ehlETSL34GJFyjynHNBAskCvNA7LZOJvR-kXkH41G_ZQAgMzGTWZMk3im9hBpGhB020PtvCycWtx7xu2oCtWmXCCIBETnEKCwOH714Upgc6e396fxsiAjXqAGRZVKTwtvtOJYhHNWjNY3w_XZXF12WWjVkV1qLaV4gsLkR49lu29TuDkcgrObI0nooJgATjqUscxuGwd1TkpwlPGpVNe9sU1XLqUAAM3VdCKr3LSgSMOeuEAx3RiIqpk2EVrUUI9Pb73z0NVts0TbVU2CISElSiOfW7g-nqeriUC2qe4sgQgLbbwYhDsKmvi15P-YfvzvNS8U1aA02QxaKu9s5qGc70MXF5s3be21tNxZySCKH1sz5VJdmHgGq7gA5i1XVcDUFRAGKCK1LKUlyUm05FzfTqnVprRkgqjaR1Jp68x4doxZJWM2tVTNvrRIz9HyWFebKXY7KRARcaw3AwEhDwbBA2l-cnz-5bK0e59qa3d2dnAIdW613d6dhSESSBkHAVMZlqZ0KEapjxN_zd_w-mPR0moDbbr_ZpuIWZloS1-av3x0O6s3h_ngEIpE8DJki7o8VmIkEnJelqioDL8eTg1OQlKS1EeLFbpxOyoSq1k_nZV4Qyd2HYQSilHIE7oZycXb-6Opiv9s1D3RQbMdmeRjKZii7cna2FZBxt_ng_ffKgJ_-8E2d5_k09-0ZESMwYMdYwOHm9nf_Fb_rL_rZb_8__o0_8qd-5Tde3d0q-t2bG2v1eHcCaMJoVSFDpk2Y6zyZGqATITClYQCDcMvj5nDzVmddlrbGSiJFj_pGCQdaHf4qDrmM7vbP_Av_6N_1P_yH6-HeN2hzmLbTspT9uZ4Orz5751bDnRwQXFURAwMxgABM27qy7q2-Wh_7QgCx9MN6hVB2lLAZEAEhMYdbl7x2NYK3xpwBMdQIKbznwiZBN0LQ2jACkVvV03Rg6c2lNZs5yTQdiVNvUhNLALRFW9UwVLPWzCOcqO88l1aRONyQmagnjluda_NQt5yzW591kpo2baoWAENi6aARTu5dosfjOHYquIYB8839aa46DuN-Ozy62I9JhpLOz_fjmDc5g8OQBjMowkw4DIMUwT6GkoSOHDimMpaUmTk8EWRJAZhL4pzzkGdtnMkDAZ0TUxZMCMy9jyOmcRzU1Nw7oDAo7u-PGlFVWYRLMlUMBLfaai4lsbi5qnFKbh4B1EWTmQO8adOI1lo4pZQiHBw669Oqh0NKiZI0U9WWUiaSfpO01kRSxFqg9N1umIebaWMBQbSmNtdu_Khq4e7ggJSEu3xNhFhwGItVQwQMqqeaJanqOGRGBAcSXpYKuGZaRRiEq6mHOTgLMQkgBnWyNS3azAMd3YyCwqBryXa7TRBw1_UbhOTmmjlq7RgJR_RuZIew6CaoaBH2gLjp0HSMhzre1yl8uIe6N3VTM-hzflS1cDdA9a4iWiGT_cnJD3JY8-5TXqX8iPjgQMBupOs8egz8EmeBhNaBFCte8ieV-Kq_7zsBX-mi3QrbS20PBXd378uMzqHqXFCDvuoLjzALjzB44JMGWHSObPQ9hvaKtbNEo_9tX3pADWvdKwcBkJqFATaP1o9KBvMICwYgXqOGkXpUAhCBCOUso_Cz_ebZfvf8bPtsv_vo2eOLnNH7YjEcYgG4nxfOxR-G_v3FMEPqWrQAwEBa8wEQgXqOwJebGLdej_Z-4MG27cyE3P_YW4Fwj64p6jKmHmEAqys7-moOEEm4hoNDJhFiDCKgviroRH_s9uhYVy6uDkBIHS6LZm7eAmzNXl4TmR20Nw-ATNiBoRDEQIScUL2HClMiHnI5vzynzHfzEoT_6Q9-BA2BZDHnlNKQ372-42BQioZPnl2ReUJoNU6T7853MMP0buJirdqHsZ3u_dXb23fTfB3-K59f_3t_7osf3rdf_eXrN2-u0zg8_ejqez_44r33L59fnf3cL_7UflueP9q9e_Xmt_-23_SV956ebyTmQxF__-WT67d3Z-OYWVqtmRO5P3_6OATOd9uxVZt1zNuSBvV4e5rn5ostOQkTq9nZ-eZsn9rUNkxs9ebdQQhKopz49eubZW7jLh2OddzuiTOCP3_vxetXR0d-8uwpGrz60Y-3ex5HOt7f7naEDcZcIJw4Hj95VhK-fvWaKe1328P13WZThDmR2NI24-Xp1A7T9Bf94rc__dEn--0AEHN4Tuzop3d3GWM_8jDS_uWF1elqe4Y-cqHW2sCbs6vtfJpj1u1QTlP1VrXVen8_Jgr0zZBu3t09utx-_OwZkmw35asfX-0fbx-___h3fPNpKvbu1Ts9LdMyN5X_-E9-_hs_ent9d5ja6a4ugunxi8dFhvPzwRdjppLLD379-zLknhEJHgyYmG4Od-fjBonXxDwI90DrNvRwAAuPfois_w7MQDX6JblS5hADIaUeHAwipV_sDmCmEQiRwhERm-maaRjeWUEIQIDeseIAwhhqtU2uut-PX335rGdd1doe7YeLXWYpAFS1SkpDzoT07Hw3II5DAYebmyPl3MxSImIR4SGwLg2IFU09pqW9vTtKkrPzXVe01nmW9Z9HSvl-mtOQlzojoZl1LFhzQ-r6VmfhpdVmuqiCQzNdag2EWWczpXAGUPPFWgsnsO24cXULcwgD_z2_9DvdGJA4Sc4DAk_TMs3LYV6uD9Os3tSPc52rqbuFqbWlqbBoNXB_dLZNQK_ulmnRQJo17qb643d30zQH4NXjc0DMIu7eNIBiu81EPC0qJV1d7tF9N5QXl_uz7cYdIELNc-JSUi5lWdTDamuUEiCmIinnZZlbrWpmASLSFkWkZa6QBRNp1XmuEGiGrTVEIkZiVFXT1pqZu6ot89TU3V1bc2siROwYYM06SXZpC-V0e1gAaTGdXSWnpTZwioggfvreeU7p9u447gsTL6pAgjl-5jd99Xi9_PiLN9_79NfUgYPcoTUFiGpxd2oNCJkk8bAdgTEVzpuUSpaUMKAIpwddAJMNmed5Pi1TeIzDUEqeFjs_2ySRlHK4hXpiHjILU2I6P9v_9McffOXlk298-B6Eq8X9vCxuKVHJQ0hqGimlQkOdGjM9f_8pEX7v118fbxYmHoZh2A1pU7a7LRP73Bjyo93we3_bb_5tP_dT_94f_08-e319fZym2eu0YLi1ydp0vJ9aXWrTUOlzx5SkE-Rq0050B8Rwf_f67TiOgIGClKkbTcyCuZOLAMOFCS2Yuc7zP_fP_pN_4O_7p5b7uwUNAk7VHDnn7c_-0i9cX5_mtrj1lbYDASGiOTTtmU7EbO5A60RuLTzMiLFHevUpITFFRCAhC1I_3ZA4dV5WmAMAS-5UT0CgtlRJqd-ow3bXpilczRoiSGbTVutEDKamaqbW6mJ1UWvuVqullJJkDx9KCnVza0urp5mJIkByIiQ3C7MwDYDddnOc5tY0EKdTY0pt9izZWkD0vQYuVdVcmIWgeZ-ZAhEHYlOd54bCuQx39_NpmkvJ57vNy6ePtkMes5xf7PfnmzIOaWAemRMlEUYQEXMHwqHkUiQzQ2iRNOQkiVOizZCHIecirakQ9ngvRKyLEhMCUDADAqG6GgESA2Eq0molosx5GLYI4Oam6mbm4eaEvPLO3JOwuTdVEV5qdTXv-xoLSQkRt-MmPMLCLNTUesEE4KqrESG8thoeamaqPResVTWzZakAQMRZUpgSgLZGwLUqMEtKQmhuwuwBtbVcBnMHNbWFCA2xo4LVzdnKmIiwZHFVIhIBIUzSrSRgbmnIJMLMpiYkyzwHxGGZRBJnYeYkMg5FhMMIAZjJ1ROzgSYiwtgOQ87ZzA6n--YBTHNrFr0q7sx-XzO2VnVGqJuZRoSZ9hn8Q7-7Rt71OdoDmnPFXq4hMhARUd3NQN3UPQB9pTP18tq9MxzXWhMiMHzu7ypCn6WFx2qN7fP9bkUgpIcI3vBVmLSm-K6GgV784rprWd0Afcjs0a3egWAPn9Xc3Tq4sw-hAiDMo7P6YvUfd7J9dLMtIXSiX-f8NDUEMkKL6DZd6B8JqF0ChugI2r0KvMLBgSMJXG03Hz65_ODy4tF-RwBMKARZmDEC0dG1KzwRb-4WM7yvy_1Up9o0XFJ_2Hf_tDOhdKmCAxAFddkOpJ5c4CHMnVgeAZ3eyYhC9JMVEGFYdNSHuTFRlocICXAmlM5d7Ms0hwYwNZci7ubqD6ZuYhESwQiRTihaVVsBYNYXZhhISNTbMgAQFiRcmyPsYQLRwxmQ191E58ZOSwsMAOvaopRTyfLobJ_HDPdLdahoaWQZBMDRIgCIaRjITJemmqQiUsGyTzfv3g7JQee_-C_78JNf-43pbvr0-noSujnNngV0-ZmPz1Kenr93eXY5UG0__Y33_vxvPf3WR48Pn3-xz_Bowy-ePB6F9tv09u3bD18-vb0_EcJ4dvb6i1t2242p3p-8tU0Z59vIgYu2Hx1ulRu5Ph7PAHD_eMOluNpuv8XQy7OSIY7zcrbnQfij9x4J0jJNjx-fpwwXF5s85sePd2SaEd1MbXnydKt1KUPhRD_-4efzrA2xGcjJPtjmDy7PtrlYs0UbO372_VecM2oIQW2Lg20zD8yH--thU379B5_nkn_x577x-sdvEXSpSylls9mcPdoOm3HDwABj2j5-fJlTvH3zA2FhRt6U16ebk7W02-3LgBJ5W87Ox6Hwbhw2Q9qd7YZBcuGz83G32wkzB96fGhVfhC-vLp-9eP785Yv9-X4znv_8z7wQ53HcBMnd9fzu7sAmsQC2lBl9OhJSW5bNPgEAcTefBwT1k9zd1kS8ridEREQR4ljbzG6ZD_oyqnxFQQjJystp1vdNDuHks2oz702vu6u3iKhqiYUQgMAA-v_uljPEB-qPWYST089_66vffH65K6QWp6Vqa0nScfZWVfsrUEP3jQwJpUipzWtr24vdy0fbRSPndFi0uV0fZkrEiZjT0hohX7-7d4hl8Vy66gbd_HiYt8OICNtNYQgIaLURoqqb2jgWEmJkMxhSZgLA0NbclBFTFgBkZhZ2cEQQYuZkrak2a0EkGEEBi9azTcLWmGIoiVmGnPebjZAc59rUA6g5mFpELLWGKhO8fPpoLCUlTkS1tevTcpxmYxqGjIS12d39iXKeqxPSOA5JJDRubo8YuNvsMGi3202tTfMMQkQEzIG4GXNO0ublcJpBdczpYj9sNmW3Hfdnm5x5Ps6tNVVbWkN0Qp_mBZk6qLoe5_l00lASrFo1Wp9QQIRwSimD6TAODz407CrJvlSeTzUAVRshefPWlnEsDB6hCDiMIxAvs_YBU0m5DIM1n09LXerd9R0LZyFh2ex2_43f9ZemgKePL588e_9yv2EUM9MwDb9fllPVRSNQ3CBJKjkJMVTvmlIp3DAuRrLAIDhaQ-YkpaqjAwVk5kRYW8uJS5IsuaSEEWFwtjt7-vhJzuXtqS7Nv__mmkRub2_n-2OEzeoOdL7d5oEQY6mLk_B2cNRPP3s7LUvechfJEhU3qE3dHIPN6m7Y_DV_-W_7N_6dP_Irf-Y33s7L0pbp7u7w7p4IEdJSG0DM0-zgWuvpdDrcHhfAYFkWdaShnC9Lra2ZehYatzttboZgbGpanYFYsggSgNeGgCmN5xdX__z_5X_z9_1D_-iPfviJgZOzB-UhcRkD5ad-4Rvf_-6n2AfUWQAIgB928wiIlJO5sQgGhAbn0ilAfZJFlBAwLPpUtPsMv8RYaFVzAwCWhNhjBGyF5yJQypI3o6vqslhruYzu6s2XpSIwc2nV6rSklJjYgQjRzRYzIzxMx-o-q5HIUo1L1uYeWBsUHpiwNWcmAmy69GTyJIzESOJGLDJskiSuteacy2ZAFmRCpgjYlx2itOZBkLOszQ1ikmSGKEy5vHp3N2tF5s1Yvvr8alvyIJyIN7uSRQQZAPOYRJIQJZHtZhAhSZxy6rM8ZHZAyqnPGRNyKakMqSROwsyYM1szIpoW7YITLvwQ14pmEUgd4d8hmzklAmAiizgbByHmROgx5NwnMpIYkZlRCIUl3HJKqiZA7tHB9CUJM4VFXRY36-UkCouwu63JBRYU6G4B_X6LprYsc07FPBxCRCiMmKJpikAFqwYAiampmlWSzpPGWhtEIAEn6lWwWRiEMQMTuG7LKqUoORNgTsm9H0hRmLqOPpHs8piQsWGm1Ikz5k5AAVCb9lWJzh0ZxDml3WZ88_nNm7vl9WGam4X3Knuld3ZLbpd-_0Qkvkp0EADc1MwsrH80uDOhf6mZCethrBZgbu7WegoX9WgxNDW3dfzfAXy2sne-zIwNwLIqd2DlGnU9Ln2Z97vu3MEiVnxTr-v75rhL3HtzEeDQXbA9a-zLrF56gPOvcOsOJgJEs-iWjAA0j4f-odsGelxoz8MycF-TwIA6oJYQLczNiZC7UxbR3B0CGZ2CGAhRErtbFr7c5BcX-5e7zeNh2BSp6tV00WphBh4et6d5WvS4tMPSTs2rg5vvxnS5EzDNHEQw13Za7FC9lJRTFmImQusQWOxBBMyUuLO1CIgCgon6sis8-iCw7zG6O6DLkHq0cc-g7lApJEQiJlJbeU5f0oAmjfupiqwYItMlIoh6cndeMV8IYQb-4Pfo6yPrF4l7WHjflXWpBq3v_NobxAMrlhhIkkD0YKa-u3G31u3p26HcnI7YkFk8wBRozNUaZpQs6np7OysCJjktC0t69-m7qPHsbFdx_P_-iTff_cHt63a6vrk9vT1sHD7Yb372g-fjMCYawdrT8_FiKFfn2-ONf_Ibr8QsMyxL22BkRJ2mi03ZDmxVd2VYFt2Pw34zXGxG2sjpNAfLvS1GLJn3YxqFm9Xzi22RtBlKIcxo-5wk_Jz4yWbfcnxxdwpTD8cw1Hj-6Opwc9emCZ1KLgD4_PnZxZj32w1U325H1caM5i1lRMCXj58c708A8snp5hZPReRst7l4dNbQbg9HIHh6dkZh0dq4K0-u9ufj9vHlJUG-fnc4P9s_utxqqylzKbzbjZu8mWp78vjZWDb3h1odANKrL05JsLW22-8VYoY5mj3e7c6HfYDf3y8ceLbZhtf5MGVBr82Xei5tm-Dxxf4wHbd5MzbfjbwtPDJQrY_OSkG0RQe307u76XBYYnl993Yosbh5C8MUqRChBa8XSUSY11bHnBFQkBDAzZgwsawBed0E1FdPHT5gjkQaDgjqhiwa1j-Shbt-xxSaGjmAO_RkqACH0NAkfUmJq93Hw0yZCcE7IdObDSw_91Nf_c3f_nAEOBz003e3LXSzyeOYzbQtpuGLqXqEuak-vty35rXpUiumlHP-4npZlnZzWuZmx9nuptpbehYKZMpyqv7pF7fH02xm5_vNtgyJ8MWTSxFOWbRZVWeWVHKHiwD24HEA8MQA6InzOqzok5IgQRYkRomApt5MmRi4c6L1J3K8pgQ1whddTtOhtgUgkqRZwwilsHW5I1HT1pbl0X7zeLvZCkWzAGyAP3530kDOZT8OrbnOCkRUytubw_2pdVwH9gkCx3475pJCeLL69uYIDLd3x1b17u7UaivCRVJJ6fJyd3G-w_BhyFb1fDtSwDhuOLEwJSFwaIvNi7oDJiKh-bSYaSIhoGiODMu8CDozEUbXmfQjDADqslht1hpQN6J6GiUCwNFbc_dWVTWub44eqO61-ibluVYgdsSUS_eiOThnvnl7E4yUibFBxPFwYIIy8OPLCwd299bUEQO4Ne8YvbZUQg71RILhT67OuqIrkFXj3WwlUSLCgNmNiAoL9tFPUwJgQUzMRZARiIBof7E7u9hBEnBt81JbHYeiZswyDPl0e9SlgXk0dcOpNspkbsf76XhYMHC73zKHu2FGs-r9gQVobIfbw9_7P_4b_tCf_C9-5buf3E5tnn2UkhiGwhhqpvftjpCSJMkpXCF82AyqDgQgIikfjjfu0JZazY43pzKOkiSXIkJadW3FOqoLKQgWjfc--vo_-k_-A__0P_7Pvf78rQoSJ-AcgKlkKml7efnxxdlupIRADBCQE4cbYiA4UHjTDhz31laIoRoiuSlEuHUjOBGhW4QbIBNyOIIHytpCrHPV3h5AAK1IQgpC01Y2JSJcobVKLAiRkmithJyTaF0IoS4zMYdDW5pwmqZFw93aNE211i687kKflGPxJYiHzUgsHo6AQkLErend4YTMSIwsPbzr_jhL4m5wWsOTEi3eAvzBxwDu6GZTrUo4q8_NmvlxaW9uJ9UoJY-lPNmPuyENKYlTZt6WLJiieUoCCCmJIIkIC_dVWspScmKhnHIny_c0ZSYBEiEmIAaWJEnSMKTMlIQHGSJwv9kQkxBqa6ahWmnNMO2zzAQQCogiGXltyMxKIqvW1zun03FMuU0t-oaoLeAGZtUakGAARQhThCVmrUohPQlArREhhBUZrTp4V0hLmIN7bbWq9gLF1N2AACKMuYfJuzls8thmDTPs41_CsQy2KAVHYKAToxDpXEkEWBwDIQigVU2SSVUcOyaMAhjANBxWt61kMrd1KKvWXJmz5JwSspBZIICTf_B0hxjjUIRgaXGYLahn3z48BoixE1keWDr-pRbE3cwQ-3EL5m5mXQzC4B0ZI53ciRSB2pcKGAhg3hnBDrC6AjqQU9WxG1oD-lA-AtzdA_qmxqBriPphE0wP-WgPA_01riywl4gEQA8pxNgp-es0GsFXEHhAYJcedW9ueA8l8wBf2wAAjP5-UjxwQiF60m6s2WHgEWru5s08HNyiT4Y6hgg9fA09oAivWgFRhCyihL28PH__Yvd4LIVZoBJ3Ur7Pyzxr66-6mjHgUlut7bi0zs0-3wz7kgXx-cX2fDdshwTek7bszdvjot5Z_fCQCtwFvd0LR_6TN6_3XUBB2JcAkDqWzx3XwOBOT_KephywBheYu7kTIzMRBBMycVelfXp9PFXzHolAos21aQcjBKL285MeULAQsIrBoGuuvPeJuMoniDrmNAijBy8i9VYwgLqW0pZlUbPueyHkuU5m-qMffjEyumm4tUU583SYhqFsxrG2msdSNpvLp1eBMc-Vl4lsvtjI3em434y7R8NP__TzRwP9lp__8Lf9eR_9pg8fP9vJMuPH33p_t5GzQa7Ot4nwbOAEkNCGhFe7vC_lo5dPLnbbEo7NyZQQjfyzH732NiWM-XC6KOnlB88S4-l62u5KGnI--X4zuOkATO5aG7m3ZSlpuD8szbSUXKBkFmYaMzfzWpfz8wudl03BpjrNy1Jtqjrudqfp-OLls9pmySmN42bMd29vJCUAwJx_cPN2U9JI-Xg4FErsPGT57EefMpK1GIahZG6hu_32aj8OQzlM8-dvbsLp_ecvlsP0409_fLHb7MYtEx8Oy-08hetG2mINZAxWD1PzptPFdv_2zdvtbiBO03E5TkAMKFC1DSIp4-PzzeHunjHcbWmaNwOG7zZSChn6ZBWZtOo2p7RPUCQP8uzpfpnnMqbv_doPt7uhUEsjRs4ynEnO_-V__l0gZyJiEaaqLaXk3vm8wUzmYKH9yjc3t0DEjAwQfcdkYEE9FQPNlFd7O0EEI7t7hHIQEUZgaNekIcMaym0eak4EvOKRKQgd3KIBxbakP--n3r9MiASUQqk197NN7rz7Zq5g81KlyDgWcLvabdDbUpegmKouy1JrO50qEMzVmQWYPUBbtGpV7fxyPJyWYGpdbqd2mOfFdByHpTZJPE_Ne4A3IiOmlPpUQ9WWU-35Xg7ouK6-Tb02rWjNlQgBbZ39mKMHmDOhhUeAUAjBNz9-zxSatlmXuS3mWtVuTxMwmiu65UQ54Ui8K_mj58_aVFVhXlwRj2pvbk4a3tzN7fZwPM3zsdZT1VLGqTkRqsW8tCQcgAych9IUarVqBoJVzRmqeVU19ePppKYAQUgKBuit1pTlNJ9ExMNLKSLZzYZcKIu16nPV46RtOdttdW6O2KwFRjTbDfsIah6YEgh6eB66ji4BYCnS678ybAh5LIM1rU1rXcb9jiXJkJvFYl7dkciJlrk5RhoyMZym6dW769MylyFvtuN0d8dhg1Z98-psGMx0aY2457W7IYxJqtpprubdswdNK3GYVmECM3BLQkxQGOuyIHhKPOZMTBaWk5ScBFGItzlvUr7Y7RJSKZkJzy_3ZciS6HS6b3NtrT5_vK_L0moFiul0ksTmZq1aa03teDgtUzvdT0SemdQdDLR1Sblipo5gykPaXYx_y1__V0qa_9__wX9xb7Wia70_3r6FaG2e7k8HBb_YPSEhsxCkNs9uCIzDdoiA4XxUt6pKMkopQXE4LiybfuI3BRZpVQkhdWq_AVD-h__-v-0f-5__d__h3_8HvvvLf5Z2yYOrgwPnzZCZKZe_9m_8a_5f__Z_FCRqttRqixqAQ3CSACRmQELkIGDucTzOzBAeFtQnhtDj3ZGpH4vW19QPBBBfzWxhXYbrjsSZekoPIhKQNuMkkggAXVvPF1A1RQ_q49VApFZnFAbmOs9MfZjdQedo2ohwXhqQNANHREGI6Ol-4RYr3bybJAwiBOF0XDywVu1uzWHcSEqtKSODh851u8klpcRUEkfgUq01q02n2eammJMGXd-dptrGoey3QyEccz672JScE7MkHDhxxJiTLpUAzRwJc5IkKadEzCUJmAlJEpIkmzHnnBghs7BwIJqqamcqUclCwomTm5F3vD4RgxmoOQl3thYSIvHiqqrB6BhNzQLMEQByzq4KyM1NEjsECTe1kjbEqbWeOAxMhEDmzoCSRHXqN7mrIWBtbbGlDCmsdflCmCIAUZi2MMfuNOVwsEV9bh7rDtEgImeGgCTCTG3RHrTITMIsTJkCWstJGGKQZOY555SShkM4CRMLAKBgIKgHEyOiMHYXBwk3U2RHAmJQWwYiAWpLy2Op3gjoxzcTgj99tN-Nm1rb8TRNVR1gNfG6QU-6ggDoSWc98wZWAA72VSl0TQ0xBYD3vDp3CHBfuUN9euwBfWFgnaexbsk68yiso3XMev3ffXjeN3DYF_QrAAgflgPhX3JoHgy-3dALP4HFr9Kfh4is9TN0ED2uaqe-hw0EX430tpakCAbhgRHRWf4OYPHQZHZOqa9Y1a5I95U_Hp3uv2Izwy2AuqKeQM0p5PnV-fOz3YePzl5cPRolgZMHNQPj4bDMTe14mtVizJlIWjP1QEYk5pQEMTOebVJ41GZVHQw2JNuUXj66GLggioUfl_nuVDVAmCRxmNMaqBZrlCnGuusgAEZhIiaGDhGNIpKyJOFElISJUAhX2kOAdxdgvxJ8VUUJIoJnRmEYEt0vS5dAEHcrX7ibuUa4hvW4ulgpPw_5EuYeYd5vawlAEiLivqLp-4WVtGTWGwgAJOSUslr0OoxJEpMHmsef-_4XjmBmKaU8ZBJc7qYsHM1VLQ95e1am--P929M4YMQ0irz_cy_ezjFcpZ_62RdPHp3t8_ByHB9ty9OzYblrz59u0sCnaTLy_SaB6m4YT8fl2XuX41ieP96PBa52W2_LJ59_9tNf_8ppapuS_8P__HtOujnbZM5jzlprpnBrn31x3GTeD-nDZ5fbcVStZ-fjdsNvb-4kybgZkdpWPIm0ao_PhnnqYO-Wk1ydn7Ebkr-6PRrSMObNmNz87njabTecIGVurYarpDTfH3XR6TTNp6nsy_3hVABHKdNy2u5kux2mtsgeFexumYcyMPA0na7e2232ZTeWH33--dTqZjucX-1fv3ln4EL89NHV1cUwTUdmKGM53t8DxNP3H7-7fZNSvr272Z5t770e56Vqvbjc4QZOp-NQ8tnZJmVMBOebURLngdNuk7OM27JgE8opce4iE-EmMBRORNtRMtOjq_1-kMvzwavtL4bzTc5CacwgknP-o3_0j0GKbkkhxPvbw8V-3x8I_S9XtR-QWXgAJQoDM09ICOQe0A9_6As96KEd2kPo1FaW7toxu4eprVCpPnxAdIjoXL0VPxDrpMNMf_ZbH0XQ0pQApmOlZl977yoReXNVdIjTrIs6OYT6y_cehcbS1CKuD9M81yDilFo_rZqph1kQQSC0pqDms0egJA4LYFJz07YdMnoA8eluUtV5qW7W1OrSjW9RTZdWpXQJUDAiejATAnoYIS1LIwJ1qFVr0-ZKRGY65IQEERpkkLG6_oXf-TaacyJ1m2rV8GWpTJSQz_N4Po4XQ05E81Kbxac_vv7x9en6OL09La_uTsfFTlXV4tX1zWleNKK5V1V3r81fvb17d3_vBHNrrcVhWiiJqt_enj5_e3NzOBLL4WC1NveVPLLdb8chbcqw24-n21nVprnV2tT78lndzcDUIOeUJPdFs9YIBQ_dbnemTsxeFRGmeo_SlVluDpJTykLC5k4dIWiuWud5ykm02RrUjtia1mavPn_95osvEOD27j7cJeXLy4syFElUzWpdWpiIDEVyEvDlcH_701__-v2ETWdAJ0BBAjADEKKqcXc4JSF1Iwz3BuhCZOYXu2Gb8vl2s92O3hQwwiIsskhJkoUDVNBbXRLT-X7YjulsHLTO3mw3jvvdOPKwnPR4qvPcWsRmN7y5PZ0OFYg8jIhqVbOo1ZZqVtswlAjPhXfnW4U4zcvpNGsz6Dve5taMKJVUrnb7X_z463_yP_nBTV3qbMtpmk_TUmeLUPcy7tNY3M0AQmiZWwSUcQCh03Gqc7t7fautIvp8PIQZkYggsTkAmKu2PMjmfJuHgsC1LX_JX_zn_RP_yN-_LPV_-vv_mcNhPiFdvDg_TTWIgFyCrJod_Lf_1g__1B_7VQvTcErsGO5q5qoGIk4EjKa1j51iTQ1yJOIk3kMtH2iJPeomAIEAaI28hECSgkzggSIBgSIQqwKWOsHUVBFAW03D0P1F7orE1rTrb0kSuOc8AMJ8PDFzGNRTw44J9HB1DAqAWhckMLNQS0itLSSCKB4oxNrUIVJKIiREplFb22w387zU1gKCiEtKjMiCzaswgGuWhLDO7SziNLVpXqpFVZhqOzb95Mc3XUJxdbYviceSc8mS81AyFabEDrHZFEocjJKFEyYm9wCEUrIIsVDJmbsiGTCXbEHMiZN08pMImTsxuTdmmJf5fLuFCBZKOTkGJUoigEgiqjqkZGYoqNqYOZes0enpNcJzGQJg1gkZoSs1I2abnYJW76QDAbNExGwNcEW1CBMJJU6IfeRuAKGuACY998EiccIARvJAMCh5tADHVaZia6gWIbNReFgZc0SoGiIyy7yogzihmkGEtUZETX2qVRIDRtWKCVMSCqxmnLNkccTFlbIoxNyqkRsBJY4AQHYMACtFwHRImRXr6bTNQ23TUPD5k1FW5-wDoadb2iPM--6kmypCI9zW_EhcU3G7Ej4cum_3S2wOdqGOe0A4ArqhP4hnbJ3k94MZVkR-rGB4NQUAZNJu0Q3w8PCuFYc-vO9iHiLqX6VL8PtvIsId3Ax74R4Pv9zWXIPVe_BlQnB3JK_czIg1AXit9mH1EluAWgeEgKo7gmNvUSgC1Az6-0ekaycD0HtOJAuNCNN2MZZvPLvaApEBrjJDcAx165uP3VCGMXXFF3ho7dbZ8ABk9PAxcQaGRWtTiBjLymBjh9q0uUNPswdS99NU7061mZGsy5We5ax9_NmZuR6MQBgJfJN5LGnMuZM4za02DQhm5MQ9BjvWWOq-MsSUOAJF2MP72jTndHW5K8LN-nHp5tod2J0AmzABcwACRfRsCnB8WNLAGtDaTSAPHFX_0n285qu5KwT0zSEyzcviPQQ6wlqH59of-eVfMQ_OKdyZGAM1kAQDY7MZwIwMfdGrJ9tMPIz77f785nppczsT_MqjPAz43vOzs_NUsphy8_L88fn9Zzdfefbo_SdXj3fnm5QJ_N3buzIOm00Zt8PZUFSrNf_xm-sP33_cHQxvT7e5UFN79e713du3X395KRCnQ_3aexeibTvIftz0JM7TNEW4kRvUaBpVz_cDBd7ZhKySE6z5ZYAQ6u0rH35we39iFFv07u4w1aVBM_XpeBploLDLJ4_maZ5PJ22L2lKGfLo_7bejWhO3LedtKj5pOHzyo9fj2dnVxeXlNl1u8lSnH7--cYrNppDW2_tTC7h68gQJ3RQ0tM4Fsc73ACaMPk_oen55eXc4CvPl2W4v2-J4WI4ktNtuXh9mZ6qm0zwtdQaP3VBe39x6s01iNNvIkDTUbJPSeS6lDC6kYQCeMEWFZVmEOLFc7He7i5GCRmGBEKaUMmL65V_-1bQdkQKImOC-LbTmcPfLhpLIGjGO0HkGQRAYDdwBrFk4PDheehpG1_qEgdtqQOnZgr6GFYILoEWYmalD3-cCBvTUbegeHEIqKFf7wRY9zjUQTqfWAN9dHxcF9ZiWpS02lvHRxW6f84sn52cZU05L0_t5WZpyERA61ipZjtNcu0rI3DTUfBzSmOVwnIswQeSU5qYiXFJqTZelLqfZEJBIhMpQckos4j2yFNb9qKOXgU11qUtzNQBAdAeRtCYXeVAEAzIxA5g5mmWmDJSBd2UjYepe3edqHtg0PNxBeypLc3xzN3_y9m62uD6euohganaa22nWqoaAQPj0av_0yVbdVAORVO10nI7LdH93NI-z870DnO23TQ0Abk_T-flGAW-P883hmFO2UATw6mfb4WvvP04ZdK4u6O5MtBrDApbTonNbjksvmRJhSgMgpCJh0NwtWkoMFsEoKGaGitE03LUZI5mahS21Ooa7EYt1koqb93EvATJHxJCwHk5vPn9zOk7geDpOdakd5WzoLqCIuZSUGEFC9bf_Bd_5zlee_Yn_7Nf-wD_wNw88jKVUU2tVza01kTTNLYt4kC0LBggSOhThD18--ejF4904GOJmm5Glp69uxxHNSi4FZZfydpBE-PjRPkv52Z_7-Dd9_f2r3fnjyz2D16nW0AhbpqUujYS1-TK3MgoyMXHKWYhc61JrX6N36SxxevLxkx9_eg0RzVRY0IGRISIhPLrc_9Jv-eZf8FMfH03_8J_6M7bMzKHazC2YWng111aXpXZhVZ0XD5OUTauZulm31CKG1sYJAAANyqbMp4lzkgRXl3tGDoPIw4sPnv2v_sA_-Df8nt_5f_6D_-o__y_8KzzkJWqb2vFdBWd3FIZ6rMsUf_f_-u_8Z_7pP3ixZxDGzMjcnwDY-XLu_SXlNLh6p7t4uDVFFDMPACLxZkBMnDplnLvpjgHCoLUAA2ur8icMicK0O01X8sV0nIdxCAtJWU2DSMPdVDIz4na3R0BrdRw282Eqw5Y5EXOQY4KmikHNtGyHZZ6JkQkFWWstuQBFKUNTHYYBwtVMDepiEEjIU10UAgBSTkGh7lZNW3MFQm7NBSWJIHMZsxsg4mI-14aCS3hzn9VPix-b05jeHU5lUx49OtttypC45CSZkTAYpGTODIS0DhEJAHJKZs5MDo7CncJGzMSMgrkkJ-eCnCgPxV0JiFiYuJRSUoJAdS85h0VrOow7dmqtIXHXLHe9kLszy2okRNA651JOpymPpYcYzdOSxuIRkthUUQ0fUmJVPQhJuGkLgtYaSwpis_XTaW0sEgSdRxQOANxHzdBzJYmQsU_FKUAY62mGCBIJhLBoi_YRdtUl3LWqR-SS-p5azdSDElt4a60HLiZJxBTum7LnlEouqq23MZKTg3EiQsiSTRUCpQgTVG3IgiIgZM1QgAPC2jYVVNXJqruktVw26xurjrTG3g11LGcn7QCgeTSzjmc17RxU8NUsiuamriv1JVb-PhIoBEQPEOBANLDAtZ3op2XX2RNQhIcb9QzZjtftpWEPqe1WPQLrxX7Xv3UGTtf4IwLyAz0IAsFUPTqFe7U4mDvCGj-MhLYGdEFv6qwbbh_ahV6Gdthf302sOKIO_wQXhvAQJkTo_zXr_gkKMBEG168_f_z0bMsAvRcUwebWtIUpMxXhMQ2JWJsRswhH8Kp3YkZcR45YZEgciGbezB1Q1W-X6d3h9OpuOkyq6q7BiEMRC69hh2448-CITRFfW7YggJL5bFt2hc9KHpIQ2FLnU7NZ7Ti12rBa1OZLbdqUCZP0NQCmDkGDcPfEtLJZO97Yo5jvs2RCU9OqAMhEa7_R9a59mhpQEguhSKcQMSMxM6eEGETeFzV907damdf1DaymBkTzECLtZIYIAmBhQhJOP_ziVWvU1PMmd_NwKUMoEMXp9n4s-XR_QHFELIUx_IMPHj19un3_cfoLPn4M120H0UX899eH42QidJ6Wq10xrck95lMmzIllSANzBq7H5dF-SyQ12kHvTqcTqB0mffv6bpuHs91-Pp0-eP8Rkpj6Upfm_m456NJ8mZLAOKTNftiNw4hem5WcCxOi5y0eT6csrLW66nY4G8eiYY5w_uziZjp4KECMm5KJh1wMdRiyWgWNelwosew2n3_2eRrKsixF6O3tXaB9MR-l4DDy1aMnmyywmHBeTn44VAwQoOM0hZnkhAk__-EnKfDx5RULf_8HPzb3q7MLtGAEW3QcCyHkRJth8_bm3VA2YfDhV97nlG6OM0pKTMlAQ5elFsln4zYTMW7cIBMlwMRSJJ1txmlahizJdJ-49KUOQBY_G9PSIgtenO8yQZ18OlVrFq6cAsU3mz1hnI6TRTeLhwQJMvgDtQMcrZvLCRiopxxGIHYms_Vs1xUmiBEA1BHvnX2LEV38AmDeGwIg5lg9RxyBEOirj8qR0R2s62-TDCmf7k8EUQG8WskJ3JMkD0KipbVpqWfbzdVuV4a8Tfzq7exutToCMaa2OChY9dvbw2ky95V_wATDkJ5fbN5cz2NJLCQsuYgGlJSRGIGaWn_WEcKmDBGhbs01GOe5EkISZmJEUvOmahDCRETEcrTXiViEgdDRkcHDAxQFk7gIEgKHPrva_uU_97EeTqd5WlplQU6Cjq2ZEGXB2fzNzfTZm3s1cOecskOkkojoNLd5qcfjNC_LWNKQyjLFsmizliSd5jrrMtX58uoRBNRm86y1tSR8mJdmOlcjlsPpxCLalu12-Klvvfj4K0-fXO5v76a72-n-NC2nGhGYOr0P1DUxg4POc0rYzBWBBFlEmCVLnU0ViAmZtDZO6OZq3q-Q7VjasjDikHOnIddmFpFS0mZLa24WBtbczObDrBqq6hBvr99RYkkJIeppqae5TRUD1ZQRx82utmmby6z1b_xdv-1_8bf-3hIUzQwxwpfa6rykLO7RJdSAkYckmcpQAPF8X17uN978VGudZlPbb4sQbYaSBTdDGnN68f75ixePfdH3n56_fLL_-lffu785ndQTx7jNRDTutrU1FmnVd7tNyWWamkeoQXgAUl2qqddFObFr6yQcTtmyvPvBtS2Lt-a1EjgCMgEzppJ3Jd1-cf_68xvZyaS11Xa8n-vcepbWMlXqjMgA1wYQbVoCkBnBIBEL8TLNqykFqXvzJBGwf_HFmycvnhOi15nQL67O_5a_62_46_5bv_vf_Jf_7T_wf_pX3x2tId7f3M33p6ZWT5WSU0QwN627y43c1T_5R_7L6XjUadZT9UWlJFdnETfrkTvYp8HMEYCILOxutLr9EdxEJCKIqAsJkMkDhMfObCcErw0QA8CqMcrqGHYPDwEIKQkQzZs7CXGDqMvCONoySxrAvNUWBBwEhNpaEDKAL64OiVK4ezUcIW_GeZ4DoiHmInVZzs_3ulQD5EJIknJemnalCQAsy7JnWdqJE2UUyayq_3-i_uzX1i29z8PeboyvmXOubrenq1PNYVWRLLLIEkWRtElEimU6ESxEiAzFMIQgSC5yESBAoP8gN0YuAiRAYCQ3NmAgiRLJkmVZkSIpkWzFaiySEs0qVhWrO3WafXa7mjnn14zxNrkYcx3erXNq7VX7rDXX_MZ439_veXLinFkSdx1v8gBIKSVGgIiiVj0cQA3nVTFgHIZSqySZZnPy8OuH52cPzrZzKWuSqVQGPO_GQy1eAxGZySqoOyB6eD8kNTdgJ-iHVEwloLpzisYk9gpDx3VVIIYIM81df7i9S106-Z7cmDmAolbBKNUCyMMtAhNGALKYaQT1uXPz1v3shm5dK7GYFyBwtZR4nS2LAJ7i6pKzm7PkiBkDEidXZ0INN3cWJiJHbxrYJMmq5WHQulgFSdlKBTJigVBmFmIPE6AudxSopboIi7hrzr2bQj3piIXEbCURYESkcOecw0wIhVgx1lqaif5ox8TS3j6CEzJ6dREBCwpIiCEUjmGWUupzB0zUdVzXrpMEdLYdO5DLyzExafEnDzaM1AwOJ2ZOO3ifAuKt5N5m3tggLQBgFn5P8b-nQoaaR0STAxMABrduCRJxNDUfuimczvGnDhoBQDR5Lbhpi3pDU3SZARIiuZ_Kps04dv8lTyAPg5a-OQWV2q9rnAwCHkTtXzY4UaPHtNp3qxhT3OeG8OT3ipMFGUjQ4hQJaLoCQoT7VcOJHNJgR6d7UwMZIRA1TGlZ6_uPHzEAIru7mwO3obYxc4sYAYSbqtlaKnCjELhjACEzLcs6jD1KPhsHXYqbWiAn5ohZ9VBMgJu_jwMCrBOp6h4IHtXrXP1s3JhhWdXdiRnDKShTEkIgimKBtJ8WBy5mHhCIzBgWFsaItUYbpzIhC61rJSEIUDVhbiXpcED0nrATCghGylnitNMEQmyGYyIg4baEDwu5L9URBSKBh7vVlrqiPzYiN9dCo4F6862HM0pb5bQUGRKph0UwJx676xe3HCmCmtp6nqsg6VIoaNye6Rpnj65Q9TAdiLDO9WpIP_neC1tskzsKf3w-hqmX0LD9tD_cTk8vz77_2UszywS7zBD04vrmsK6AANUG8s1G7m6mn3786b_1K78OSOD8k49e_OwH79_t69X57unDy3BE8v1UjPi9L42NstWdD-u0qBqgJho2297c17DtMNzc3ASohehibJGT3O3vHKJLTIFYddN1usyDpDxsjocpokrXueFutxVcLYDOH-w_fWPLmuKYshCJrWW8SL_w9L1PPny1e_yw2xod93V_N-Z33twsbxR2ux1KPi4zUxk2w24Ybl7cAWjOm3ffe_v69q5YoWrbs_HTj68vLjsEH_o8dMOjs6vPXj7nDL5Cxzk7T4e7Wi7JIzEACBGPkicNIuPUZcUEbgAOzrVcjduX19ePx67fdGcOiIxFhizV_WzoPrq-4W68enjeDXkYX3MHm8h1u70xFcHc9wD8vW__6Jd__uthSER3df5Cl5tYEcLAoUazfyM4uJmQEGA0LHMLDnI4RgqxMELUMApq931CigiiqBYIFGTtba0CurbjfiCi0P0X5JPpkDAk4MmTR4jc7-Rt6I7TVJYVcko5m8br2zsgf_LoMoG9er2_ON8cqh5rqRrIDGFrWXfj7m6Z3YxILDwoMneu1okw0n72p4_OIIAYp2WJgLcf7hom5fZuSb0wy2E_pS67a7ipOiQCb9JxyCLzuuo0d8Ikgk7uLRJp2_QAA9wcDBCQOCIsfBlS93C7-cWf_eDBxVm4d2F3d_tlsqK16yglQcBbm7bDAMZvJr07ztf7JUmWLA5m6q9ubh89uHRAC1-LjZsuAXWS3KLUMozd4bjWasxkAEctF5cbMq9e-0Hc8_Xt0SOky_NxXkoQy_XdfuzzdjMeXk191xXA_VSwE10VITyoVNtdbG7eHAgaerXkrsdAybysZV0rMnnVcDvbdPNSQCNcc87LsnJOZkZIUcq6LpwzMLs7CVVTTlJKYcJhyMtSujwg1OYIQsY2M6rzGhrHs4W2YeoaMG7GeZndCgljkru7Y2Zc1_Unf_jj-Ztfu9htwXGCiZ3co1YbcmJKzVlh5kLcbzMTluqPzvqzvu-Zb6b52cu7RW2qcXuYIMLM1mo5p81mrF4vLzZCj863I7iUulaL1y9e9eM4VUViFhzHYTnOm-0gY3r17NoiKEtKbLOXZUWhdSnNDEwiuq59P5rZ1dCXxYlIq3YibHG-Ha8ebB88OL-4PHv_6gxFfvr9a8C4vb2r7izcJ9rPJSXC8ETM6h7OgW5ualq1Ff3AnAAJIywAwtQySzWnjhJTO6n0w-Y4lz_3P_7zX3xy9ubD5_-H__N_efX-9k_-D375P_s__u2zq1G1WEC10KqUGIXRc5mOf-V__z__j_7D_-vF5Vmti7slkVrVl1WECUUIzWpLDCAbnOxD0GJA4UFMVg25RYWJwonRqocpoqsv4dacl9DkIwzh3joD1GK4YYKEYV7VA3CdFxmGAGaWnNO6rOA19x0nCfdi6kallHDDgJRlmpe0zWAw9l1da952KAwe5pFTdzwcCXFRI-IAEKauS4hcVq1DHcehVFYtqct0kvqwk2WhPqckTA5j1213_a7nsWMwX1WnpRSLaalujsxlLQBUqodqDAyzXZxBhGXCTZ9WUzIvVYVYhfh0YovMXMgjcJQ0qUZUCam1ZpJKah5emjDVW43aTZuKa9ON4fXsbHd3OEREVUNiSa6GZa2dIDF7g-ogsFM7zAagWeQOmQgB3VEITXUYh-O-5pQpEIG6LnkEmoM7cxcIwOi-CqNVcFMBsFJFODRUKzVuilqXh2U9Sk7hVYhbgp6Z6lpTbi-VQAyRZGoMzl1v1cC9E5lmNdVWeSVg14BkRGCrBmHKwiReq3SpFjV3IOpyZ1bVnDJBRE4JzBxciJmgE9Z1ZUnV6m4Yl3XtRJiAMYacWBXdxk3e5LQ768_PBvJIiaVrCvtTECf-OCMDJ9vqybkEJ1UtokOrkVKc9MAOeMrytCCMeyBhAOipUI-uFQlbwa4pMNq1uP2v0by_hG7GxOGtttJW8dTO3q0P0Pbw3sJFGPdplBPg0xH8HiTkp8pzBIF7i_-CN7Y3narthM0hxvfGAIQTnxQaWvREnmk3CgDkk_qXhSLCIhCoscLcwcwbNbxRSdWcEmbgy4uzgdgVAsHC1Y0BALxPgsQe4VpJyAJWMwMSRAZQRggDgHmetttNFiEAXVU1AinCEeC46rO7w6bvp2rMdL8mwR5jCmQEp6Z2oKWu25yKhgCZW9d1fUphBoFC8KrUUrwYWrP2IhIjujtiC_4Rs5pVdSbqE459p-GqFuhFvUGEATGIqpCBuYK5SU4nSzBSYDAjEbi6Fw-wcHDwgMYhsrgnO6UkrqaqJ_4nkWkrXDsBWXMeBASStZsHBiFWVW62UYBGNNXVJPUUMHb9PM0pERJorYCUhnx2frFM82bMMnCd61e-9LTraD_dvvNwe34-lP2E5Og-HZfzy_F4N3mso7A7XW23Q051OqZhM26Gu09evfX04e3rNw_ffRABu93u-bM3v_Gtb3ooJygW6s59fnN7e3V2vhnGV9fXu4vN65fX2-EizN1jM8p0mCPR8W6ee8md3E3HsdsoBmVGJl_Wfuh9DkdnAUbabIZ6Mz2-3D3bbg-Hu83DxwDACYUH0_rg8vzF9W2X2TTKXEMRh-H5s-PDqwvOwll1pr0qd3mepgebgR5evbp-XRxZKJCMYuz6pSxlWbuUt-PuFpYf_tGzL3753ffefe8Pv_uPH18-WsIAvO-6ab_wSu-__-6rV68fXl390Q9_MozDPO1VZwD_5NPPfvGL76p7D1xrpbA0bHrpqy8K-nA7zMWIGAwi1rcuhj843r61fbtjO7oNfb47xN16HD3nLGd9F0ZDx8O2Hzc9uK4eeZPKdcmpH7szAvwX_-xf_Ilf_PnQCoIJGKPh0hrz61SYY2CDYGYGrC3uI-QWSEhBaup0kg6eQmvh5uigxIR-WoViEAG3kHVzKBJFeBT3CBdO5mYATAgcVuvZpjM1yd06zx5BSYDEPMzNzd59-mhMaZmXnGipdrMv-2KhHhpqphCv9jfHuQzbUasZIDpAbtuzUw_Q3bouq2qXEjF5IBPd7ScSXkoVck7iAFpKBAjjUoobCCIAGQYTYU5FNdaKwoxhYIDOLKXUIaXwWKtWDpnn3_rVX_zZr3zRVy1hVkotemv15vZuMw4sWFQJhIA2XU9Ch9neHGYzJxJHWKf5wYOtGW67oRNZV10tAmAthkwWjsz1qBrBSJMWDFAs7z16IIhqsT_MLGgac9W2zt1PayDVWrsuM-LIoCwI_Or6bipWKqqCjL2tBUuU49qR1FKQCYhqURauxZKwJpunue_GpVQiZGG3yJJLKZ30ap44Byh3rGFW1mEcpuM8dv1xns1Nw5iGWlbm5KUmSeuyIBMRVFdJEh4G8Prl6-N-6LsMZusK42YDJAChTr4ukOh4_eYrX3_3fDNwQBD13VDrmlk8hyrWxcbNcJgP5sY5adFA7AjOhgE8ruf62d3-9WEZtwNaKWZaihkM2-7B5dl61Om4oqRNN5w_3L5-tlfVupaAePnmJvd9oAP42IlrLqvNi6UujX23vzmupYAHd2la1wAva-kbXYbIdTkWX6blq7_01SdvPbi6HLciF10667uD6Q8_ev6T3_3evyrFofvf_pX_6fPPDgGuRtVXXVYSmaaFUy7zrBCKVGoFgn7oyroKD2pmABjeDWOZyvbhg-vXLy0MGWopiFTqfHdjbz159Mu_-SuHZ8_--j_8u2ukx198-s0_-3N_4__01zZj72jrag7YDQmF0WzYbJb98fLJYz7Md9evaa0oWC0wZXYnUAE0ULiPD4ZHC6s7AGiklJ3dTbHB8aGxv-EUqENHgEB2WxnRSiFmTL1HIPMpUU2tK-gSp7mni4gk9HAGQXMKrnVhJhCcl5lTsnrK7LIIESzzhEScaCllsRkYkXCtJQCIUZKo6bgZ1cOiDQGhqiMyEGy247oqkjBQWaubI2EiNqupGdsQEpEgMMBmyLuxB4NaLRAJqRYV5giY9_O81lk1kFxwWfWw1B999CJv-sePHpJFz5xyAqHcSSeJkaZ1aYKmNmaetZ4o42ZNEJySoAORtHx46hjDa2AN55Sy5HWpFp46hkbnVUVKTdwAzAYgOSExEZt7YmEgIUldYnAmrlYDvbVqalVJuUU-icDMJWdrE11yQGdCjJO3NayB1wmRG9cckLouuTpGuAY6zGV1UAAnItWasgAYMbddrZsys586OSEiZjr0OSD63BMJJZGOiAmDRJgiwBwRkImFJQkESBK1mnInzAmSqbWTKVN7UEVGzCwiREFejRw5YswiEGjmq1JQ1_HDq82QZTOkzEJEbZ3Rlrsn8pv56UXqJ4V1AHggALlF8TUcAdhOZ2aMZvsFACSPluo-KaIAw-CE08PGczyd2sMbOhdP0Fz3aD4_OPXeGzKo0X0aYD8IUP2Ul0dqR_DGxfeIUxeBGq0_HCHaCh-BPnfahoafzJhwv-cwPKV776874c39eb_8bxUDcAA3b4vL-xA8-x-bdAOBGusUEd2BGTGcAjb5NPiPMCREdEQUyq1k4m4th1CKNqGMO5pa46SC-e5sl4galKtWZSFh7rrkgYv6xXYEpkBTbejRCIt9CXUrZu6hHvNc1qUicy31bl02XU7Nih1hbtfHpREq_F7u5e5mvqppczZE4523dkTMp64d9lmEBJmcG6wJ3GG5K9OqKXEwaSm1FDth1IFYKKjpzzAIiTDQPBog9dTaJjwt8YgAwaxpEwABwsDvubDtOmdNJxaQRdTsHuyKxHx7c9v-tkhkbe0QJIHMnIdus910mzxse0KqU-FR3npyNU813M8enkUEM-zvplJ0mStIup7X3z--pl2nVlwqRu1SrkXvlvmZ3kUUcL062xz3MyEQRhaYjus0GZBMy3Kx3ZR5Hfs-3J5_9jLn4fzs4u7mFRQLhzPZpBCP6FKHAO8-efrybh8ExctmGOejjdJZtVpK6lqj2kqpfRJy26TeLKQbVjUQ-eT5q9Sl_Tz1fV7reqyzDKk_62opS5mJUQj7Lq-1lDLnnCwMOJZ5Xer64Yc_BaQXz98wEAtdbDdjFiG8eHA-Xox5kIY7vzrfEXimzCmD5N3FlhhIIVH64nvvpRBgqaW-ub3tx75Mer1M6gGU2KmGX2w7QswdD4M8vDi72d-lzJShE5Td-fVchAKRDqYWQV3cHOZSy2GdNepclozMhg8ut_vpuK6FzAosgKXfjczbn_74Rc4UEfPqPIg3kQWgA6gaYCCShjZ2TXFFimBvLKxG8GSiU9U9ws2b35cCwgAMi1tzjhtEcS21qLpFGNgJTdDEde7ClJiFSADP-nw15oTktRyO82FeJXfmDURkVw82Z2NHRNfTQsxL1aPWquYUa6lIwoxabTMOWi2nzs3bvvJs7AI8TA_zIkS1FDhVoAHcpnkhEQeQnICIEE111SiG1VGARSQwHD0A-m5oS0uMcLW6KBhkkVCnxn8mFyEu62__xp_85pe_6Ks2PnSFMIK1qgNbVaha22GRKSc-zvXF9Z2aKcBSSqk1CEu12_16dj6O_bgU1Rpl0du7Q1ENjGleprXMS50WXUoptZSi3_jqB-Thrkmwqv7wkxcerojzoh6oVbskP_nwZtMPPfOwkdv5eHOYqikiQRLhzjxIyFokO3QutZpZe3cBMwgO6FPnqiJSrarqanVeFjMzLRhmXjGQOYeau6-1NkdETplZwgNM61zXeVYwN5NOUJiSBGHRlselAL-72S9lQaZqsKw1J-m6ZGallGVdaMiPnz5eF63VmbBjZEIPWKs3rttxXqa1sFAmutiM55v-4myLDM9vjx_f3D5_sw-hl2_u5tUdIZhlEBZepro_HAjczaLW6-eHm5u7ZSkQ5IjjZlDVUuo8rdNUHcLc-sx5SGWdxyGTASJBEGpAQNdJWAUzZn4V8W_82q9-61d_4Xh79_EPf_z7__R3_t9_5x__1b_2D_7jv_r3_m__z3_4r3_nu2_u5uA876e84x_99FN1XEsFRK2e-6GVBYPYEiMBOAhg1cKCkgSFgMIjdFVH1GVNLOiGAFZqRTw7v_qNX_v1X_rVX_wHf_3v_Z2_-fd3Ty9evFx-6z_4zb_7H__tIfWQUS2AmIXbLp4cfLXjtPz7_6u__J_8X_6zUHWE3CUmDrO2sStqVQG5Q2RvFmlTEiZAEnKoLQxsbhGK4USZWsoZgpBCayP9gyRMCZCsFvITSjxaobfBUQgpzHLX1aWqBgCaGRH3_XByc1ugu7unxIIUbm6FEbiNIRQye5SqyxIBDSBvVQmg1eEbJFW1mlmEq7bzmUvmABWhZnFPud_fHZilFE1dTzlX02Ho-k0O874fmJMC3uxnC1gMa0DxcGEDX6sd1tkwSkDXDdzlj569Aoi3nz7Y9rLZdEmYWzBdJA8CDIm4zykRcTOXuvuJMyOA1HeZEfquz5LdwxCGTUckgHBYD5h4Xqe-H0SEmThzaCEiQjnuZ6telhLoVQtRU1GFMLtprcqMSCcvWEuK5JwQycxbY9VqzV3WAEC2AFWXnFWDc0YhdShuASf5KwGqRmBUK5zFwlKiUgoiq3rXjWEWrYoKkXIiRJHUcJ4i0mD2bsHIDiAZiUKSrEsRYTcjYQ1QNY-oRaN1QN0Q0aIiU7gmkbIu7cUN6CmzkydhVxvHniAG4T5LqCVmDOs6GjoSYEYccspdEiGI1lOjaIe_Vmb4Y-xPBKCqnwq_EQDAIPfy3YAAaydqQgcIC4OIAHNoArpTQTgCkdyCgBkIT2iXdp5Db51bbMuHaI6wAG8J-2jmY3AgaP0LPz2eT97dU4QGoUVE2jOw5fubUSxajpwYA5pdCk7Q0LbkEATk-woqIWBgtJvz558YQYSMyETUAul4etQnIYAID_p8YRAW0JYMTghD7tpnszARM0pOfZZOWFqgqGVdag2NE-fIVAHjfBiGJJuhFwe3mKa5Vm0DdXRCADVbzZWwaiBgnPzGoBFLNdVY1KqZBQTzUvTN7d7AB06A5BZqrhFzsWpBTCR8urRRk5kanHq5aB4W4O6BAYxIsJpOq07FIrxnHlgyMxIwBhPcLj4VZebUZ0mEGKHaRGvRGFttY3C6S9_LlhGJyB0-X7m0Q1jRk6U8INSi9T1aY5uJWkxLRKZ1ibi_t6p9_0cfSVOIMR_2EyPW9ehoyMAB4Ea1jGPPXDFcb5Z3hq7bpE70C48vhpTPz7a1aN-RJDnbDJbTucjQdw-vdkL07uOHLFkRXuxvM8DDy93PfOGtVSNJ-t6PfvDLX39_nlYW_hd_8N2c6enjJy9evh5yzn0_dL0zI8DhcNy_toHJtQyJuq4jpFIqMm_68W4-WoBCRHjfd5uzgREurnbTYaprSbk_HCYUevXizfnmvNR6_fplY4FD8gjU6tv-TLp-X8qi69h1ibmozUtd1rLMa3Ohu_u0Lod5Orscyzztb_f9WQ-2RFUm6HMihpyFCJ88vazrMh2Okqjv-XB3k_vUJUksEdjl_nicRHgYhodPLn7y_e93icNqYu6p3r64CwAtZTYtbnMoRAgxIF2e715NBz6xXbEEPcpJDYeczxnGzON2-6LOmSURXwwjaIpSO6RHZ9tpXsaeienJOPq6bM43F0-erHVeDpNwmudp6DpoNm4MRGgt8MasZzoVeVUDnMz8hA-H5pmmJgNv7SM9aTEI7vWHakEop9I_AgRasZYRbzcFwHBwYX36aPcrX__yN7_6AblxwmqGCF0_WICZtWrO06sHVvGwP5yPvZOsix32S0o49HkzdDmxm5_tNkULEJlrl_moOgiXqZIjAFS3ZV0B0ANIeFqXw1I0mosslrmoubqvpQhzRPGwTgQ8tMK8rMJca-lzPtEvIDBMCFEwwoE8sHLiLvnX3__C17_89rwUrWW_LMu83F7f3t7s3Sx1ea5lLmupNXVSlrKf691SW8d3WYxZkACFilU1D6Q3y_FuWQ_zXANu76ZS9G6_LHOxCCJaytKgc0PqeiAMWEqlJHd366PLM3Nc57JWO11PEn_zZ59kwdu76acfv7nez0Ss6hqGEKYliKdpNXAnNaSqBRIY4LSsprAcSpzA36LVGhhiXYpDAHMwGoIVdwukFJQA6e7NjRbDYETIiAmEkSWzCC-HxcPghLQ2c2uvEC-mBt0mH47LtC7HaT_PS9Railk1AETk84vLB-e7vhvHPkN7ryOcl1JULQIBzGzcDuM4bvuBCVR1Xsvz2-VHL26evZluZ3t9c1jNZy0BnjtBhIfnZ_O8WLWu7xG97_N8nFr-spgispl1OYskScKJITBlIQjhNI4bBBvGvuv7dVpzlyNCLarbNK1f-tbXfv2bX_uD3__X3_m97z7_8Pl0c5hLXdc1MithjRRDt3u4uXrvoUJ10x_-9JW5glApRXLCiJR7Uw-RGmCtZc4UxjZH3mSrUYquqxoYECzzHiJK1FKLUf713_o3f-EXv_Kd3_-9v_Gf_j8-_vDZ5btPbm7gS1__4h9959tlWrhHSV1K_bIaIokgg0uKuUxMui31xSfPoVZUXw6lTTpZGIkli-vkXpAIAYmpyWqCMAjdgoitTSZbp7EuHm0-zo0xGKYkKQKIxZsTlQCRMRwBiVOcnvpBJGxmJOyqnMitMpOpEolq7VOuy9oaA9RkQ41GCCcZeSeDcCKSlFNbSeSUPFxEiGmaj4hIwDUUGYC11lJLBbcsCRmJkDMx4Wa36ZPsxhHCE8D5bnO2Gzj8crslwJMcllABuZfJvQLOqqtHqM9q06wRcLvWAjAX14BMsMkyJhqG1OfccUopbdOQJDFxVEAktVBrvNXQcI1KRAbOnRSvQC5ESOThfSegysQMxCjrtLT9zEW3C-QuJ3fvx9QlsQiR1OUODVydcqpWkwgRoXCfcjMzdClHOApLTswEEJxImEVSTgnBU05AyMIoZBERJMLgZkWTiJliIuQgxqKVkniAAAtJmDNLqYUkN6BQSvmEMWXglMwqYNRqas6Jwr2uFagdnoDYiaHPmU6YK-xyRqGUM6OgAwNqcQRyRCTqN0NdKzGiOTkgIDP1HWeJsc8iuBn6bkhCkBMPifuczrbD2HebPpOfUBeNvc7NKXaafoG3libBCXOHAeFIDQMKEWFhxNiOi0SNu9_MrCdtlyMCYWOJnhAafFpXIwQ1LgxSVYUINXMD91CLaidJc6NFNgiktx6rBwQQfo7pO43tTwSh-zsEIVjbG8RJy0UQ6G2diNGiRBAttH9_xzhNoD_vQDfFWtB987ldBuCUO_KIz3V_iNTSTdacA8gA6FEBwswJ1Ep11wZJavF1wKY7CCQEwqJ-rNUiHNBciWA7jOBBjq7ASMuizAIQDfDlZuB-PBbzmI9rVSuNAEvcrj5mUdwtYFGNiFVVA4pBCDvh7X7er-W4luOyTkuZFwPgiEgkLaEkjcsLbOGnJGuYh1e1om4ORd3Ri_lcdC5W3AIiMXjYdpSBoCzWXCzUAln3-NZANAgPJ0YRYnQhbPKB0_WIyQGKVT8tnU6q4oaNagUNjWh_H3PzBnokUrN25293yX_-u3_ASRSacw2YMHFCYnMzhIcXO7CoZZ32S5fl6bsPHenVy-vL7cWGUy3rWgqEX1zszndbPKxRUh43Gl7XKoBnZzsMutidP3nw4KsPn0RAN3Yff_rysOgPPn3-lQ_e3t8epznkany13-_nKdi7cbCwm-Pd3e0eIDzWYoegZknGi003Enz_7nnVIOINJAsFDxEBoCENm814NmQid7UNuYiHle3YERoDvnz9WkQSpwfj1fPnN0upx3mS1J-Nm3JciLnLOWPKQxr7PqXMjB0RM22H7XFaLHzX9dux379589bTy2m622QUjJSo2uphdV0ePjg3ncu8vPuFd19f3zx950EEbndbYrq-eTNst8zw4uWrp4-vbu-Ow7YjpC7nTZ-FIKJebja21kAoHo6Rc6qlgBgy7MtiilNZhy6dyfj8cEtAHWcAHKDfTMBoRjZuO4iitg6diGASAInAePtiO3QJxHYXl3nc_H__4T_jLhNyXQHuAVLogC1wKISIfoqbESJ6tMUWtWRZa5UQMWFzmTaoAwG22gnQCXRmaIDA7R2UiBsgUNUA23mv_swX3vqZRw-2KWUKM68NMBTROrcAwQIX2w2o2boGABPpqktVIsipc8MIOBwnyRklNkOvpQoDRby93YB5ShKIChERq5oGKMDhOGm1UrRWv7ndV9Xc58BYS0XktSzMQtyQ_kgJu6FTdTVf1tqaP4TYlJdWlIha23_scMvwZ37957zaNE3QESdY18nVmIKFASOPHYlcXJwNuQvOr26OR4v9vFazpZSlrnOpd_tpntUCjtPyen-c11rC11q7sVeHdamURdXnqQC18YNuemEMtRCSlLEfOmIZhk5SVtdw70b5-s-8dbnbdZJz16Ok2_3y_MU1kkB1dIuIUmvOsq61VN8fDlpVlxJV0QAQmNnMmmpGCLwqEQ5DziKl1mpRzaRLgbA24Vd4JgTX4_4uzFw9CQZ68zxttluwIACrGu5tikUExAQIhoAE0zx7xHI4GmgScrNuHCSlivHi-kaE2xvgUsrhOFXVdhdt2YHdZpMIM7MXhcD9vD6_PhyKzkU9YFr0WHQ1s0AgfPzwwqrOtV482Fm1BxdnImTm7uCODZsuKR2nSVgQW5ABpAXJzMg9SUeJTSuwc8KUuRtSx_kv_aV_55N__aPv_e4frsd5nY4ENRwh5OLRk8fvv_Pg0YNHT7eP3zpHhLvrO7lIavTD5y-CydERqOs6DAgwYnRddVnXZaVEtfhwtuGcrKgkTpSQQJIIhRAFI1j-1V_5tb_w5__tn_zBt__uX_sbH__ow7Vat5Xjsn700fMH7z_653_znw67ESQZEriNYyJyYbK1IDCB_cw3fulf_M53KQshEgWGE7owBrO5RwDT2K5uwExEwETchpQRGEHhiJwyEbk5uCNwOCBlAGpiaKIMREAsKd-vrE95inAjpFO5shata5E-kaC7mWmtmrZjVSfJ63JIOYEbs8zrynmoa4OwqptJ5rUuagqEGqrmoQYE7qDmZpokYSAxuEZZFJnUTUNblrqs1WqVJEDBLA6RO2GIfkibjrd9vtxtH5wNp71DqUWjqs_zCnbafS6LWkKAmKe1mKXEN_vZCZ89e5kynW_GAWBM0ncpddwlAYAhZZDADAFx8L007EdKS6lAVGuVLqk6MBGGu67HCo5lmSXLdJyDCNz7PgMGGO7XSUQCoh9TqygyUvs2cpecQCRxktRJBDIQEyUBq9b1HRC6moi0H5g5ACITc5LEKdQBwVRPtmBJiEiJIiKnzCLrogDkEQZY1VNKyNymvIBOLCQICMJZraacPHxdSt8PhELCJOTqWRgiRAjUwUMEhVnVWDoM6IS7nOtaUyCjgrsgWbXN0CNaZhEmBhyHjsK7IQFHgDFHx4Tm4LYdsqBngj4RhneZd5t-HPJu6PucGRteP_AeetdG9e1ei4iBn49iw60tAAzC2tg8AvwUmfKTfdOdEAnoNDN3iFMRFpjJ3A2i3Qvaaa6xuTGacqABHakJ806B_Hv7cBM_e1NZnW4kp2VBu5AABDMFBFHTFDRhQCPL4X2voY2a2_Hduc3uWsgLm64vokkCEBHQ4pR7CowgNPPTnSOAkOEkGiYPbL48QmTm9tU8DIXR6WqzOT_bsVCxuqxHc0VySa2KHPfEQNkfFwJkEXcjgN3QE1JVa2G_WY2FSiNoYDg4Iqxmq2lTlzV6ubo7hJnXdokJtPDMAkQQQELqUKtXcxRZ1lLVtInAMJZ1qbWuVjw8oWAgOhBhImHmcDBvA63WTQ6zQBQ4wc_dzdUB3DNTEhqYz3cdYTSc0knPerqnGdMJ6dPgjMxNt8TUdptIGCgihBRx0jy3FwYSnWYn7qefW1vYRCMAhXlLVSMO-V_-4fe6PKhhv92aellWYg5wZLl6eP765U2_2UyHIyAK09NH54jJTbcdCcFmM3R9Oj8b3JyEpmV5tU5PrnZC6WLoz8aRnOoac_Wb_XSxHR_uLpZSt5vtze31Bmh_XKe1fHr9ej0u290uABnx4nw7r-V8c26AxbRPozKuaku1uaz7ebnYXv7eszcdsSD-ws9-5c2ba3Ra1xKlvHl1MybumPbXk2K9vd2D0avbu4oeBBcPzj1MSyGA3XkHDKXqm-u9ae1yd7bdlen49MkVgz3_6bP93R2n8FpMC5tD0YGFwZ6-_daQMFEMXX_7-tWyTgjOiEDWMV2dX87TkQkE4YMvvX-8m--OU9d3popMmfvXr994qJba5eHm5Q0QTHMZh7GWwsJWoIRiomevr98cD8dlWbVEWZlxEPzk1ctw1-oMVWJ9cXc9dgxWEwMzFC8OfH07Kwqh3N7VstjYDeeXGwTuum4q3vVJSDa7s67b_KN_8ruRUgBVM2R0wMZlBARidLOTKKY9kgHAWwZRAcHB1evJQ4gILX8Q6AHVWgS0vXGBqqubeY3Apuu2aG-H4KaBMBK_s924xolW4bo_HJelBMCu690tdfLg8vx8OxbVYJDEBvHZq9t5Xfs-952sZV2WFRw6Shh8OXS7bb-f1xrhCKX6qiqMLDLkLuV-Xep0XOfVgtgigvz84kxYwM2KJRYG76QzDSIq1VXbuzAGobbfMwgCEMEkjB4MnjIxQR665TD99__NXwejw34eh67PfDgsy6LIGEhuznjCTOy246p4PZe71fa3EwhX06A4zMub68PhuAQgs7y-Pa5LLUUBgJjN3SIU8LgWC9TQUqqpr6Wc9R0TG3jONN1qXdf93fEwryJIBGF-vhmnmyUhDmN6vZ9uD1Mb50zzTAmnpR5LnVclFk4ylzWlxJxsBWEBCrdWN0I3wGaSdBPEnKTBSJhZRABD3YSFAEO9epRlqarzNJdaJWUgCEZKYmBOoWacyIqGg6nmvuuGLABYFavaXI_X8_H29vWLNzc315Jx1UXJlOInn_5hBWuSBw9zgDb4b052IhLzXmSeJkW4XtZn18vr_eLI0TKjRFpqWSuY9V3KwUvx7dAzwbvvPgSzu5sjAiHxupTpOJn7qlY91lrCoay1S0mLkeOmH-q6rvOyHmarmlhM1ath8J_87_2Jv_e3_-v1MGvxsMZky_24_dJXP_hTv_Gt3_z5r0sQBU6vj_PdtBwPuOJ6mJZ1Ph4XNXXTdVnAgtTISwvi9X0G5Ha_Xo4TuKsaghKTFY2I_d3-8fnjv_A_-nc__ekP_9Zf_y8-_P5PhvEK86jGRLK_q5sH569ffoQBQZS7ZKXqWoRPDbGcO_eKAd_61W_97u_8jhU3VTVTbcItgPDGPSRG5gSuiKhFhTDsc7MPeHVqXDEgZkoijAQQ7iUQTR0Cw6vfxykQsY00uVEETVuKBJCIkFiSFUcSQJKO3c3cSHIgrFWRE0vStQZEgHVdDjUgMjckZIIkrFrAT-n_TNyiadLnpSyARCkRIYLrqmqWu9ygJ8OmOxznfujMLBEPksYE24EebPi84y88uXz_yQO0uq7zYrqCFzMXciTEaNato9VSbJ5r9ViK3hxnC1w1VsBX-6Ub-7ceXz06G3uRTd91KZEwBNrqiTEQc4wAYA5AuNmMql6qhQEjrkshTsg8dJIB-9RnTsOmQ_RhM05zSV3HnZgphNe1OcKh4RE2m4GRXc1NwevAgu1n4dalnDhFhaqakkBETkLMjMQNJ59TIBarKWciiICUhJMUU8ldXRUYw4ERwS2njADE1IAvqhUR1CozgoeZBUYts2rLZIYHrmVJRGDRiKjmLqlJRXjoOlPrUgqMk1XALKpyEo_AaMD1yJ1YqRKEoRBuXpAgsVg1yZI2mTI3m9vY94wwjF2oiYdEbAdOALs-jUNKxMwcn0ddw4Huk_bmHuHtB4Otb9kkwdj0u21ff5LdAkKQ--eZ-tYZiJaoPwVyEM2UEDEaI6gBP9vxD--v1QhI1c2wqQNAT8IdiACLpj1vQf0GjWmsn5NPrF05iBrxlcz8dCkBbL-BJzA_Y0C0cXQ9ybnpBMWMQMZWGWg4VEEgBHDQgMAgITgBsaP9XreRNiHca-MAgpgw0BGA3R_uNhe7DYWb-lqW3OWqenOzn5Z51Wp4Tw4k2G5GRk4EHcn57gwBy1puD0cjMte2ExDBlLixCKrZ7TwbgqrfL-gIADWa0yLUzcIatVzNIrBUt_BS6nFaW5wgCNV9quYAVaOouRoBRoC5awsEIGg1DxCiJkpqIw8EKrW2ixkCmWFbFc1T6Zj64XSzDqJ7YcBJmIARBNA2OPe6A8PWI_fQquHetnKnFx9hnNJNBmFIGODYkgqnnnb7CLU6Epp7INRqXLtayBGO66Qe_TC4u1djpJhMRDzUQyXT2dnw1mZ7nA8MunmwLWs9HA4evt2Nr1-8UfOPr6eHl8M5y09--DFD9MSSO-r4ze2-z31YJKKXbw6b4ezT6xe_-Wu_opZu9vtnz24-ffHi6vHDuSzDsNmebYR4ceUuT1avy_TOblNqGYduVZVBbpb55x70Hz5_aeE--8efvuzG7O5E8fRqp2udl_rulx5ZdUrUdbQdh-k4rdN-7NPl-e7u-rrvOgp68OgsCYPoUmYPY8Sxz6aVkGqpcy1Wgr05rte-o01OydvnrHUpETEM6XZ_wPBBpGtsizr3OZVSTO14d3d-tfvss-cOsdmM62ESSSJpnRYP22533UUfhKr6-uZVWdfvf-e7a7V5nlLAE5E3b24enJ85ybTMh3l5tL2Y7o4QMR0PjHB5sVujcMeJhTCypA11fSdjn_oxo-Anug8wdqDKSlaWGSNYiBDHzZA4H-bDpEfKw3nft-AaEQZRI_8CorsDITE2-JiFEwK3Mg8EEkgQOJg5YNs2RoRjoPoJO9zMgUCITA7W-r-q1loEjYf1rZ_7oGokggp-e5jnVfuuc0APuF2WWj0xJ4hSqpkBQWJR837TnZ3vEOH25mDqi1VkQAJTvZtXrfrWo7OL7ZCJcuJwWGoNAA2vtcRpG4nLWjysT3144Gk-Y21XtpY1Z0EH9cgiGOCqLX0dAaqKbrtxBABIdHGx3Um8_ehsyPHND9774pMtqStoCL58sy9aFUA9qnpV1VqnaXJ1qHFzN5WI1I8oiUm63BHyUqtGGNDdsVQLzqlqeESptlYrCpjSXHStvj8sRWMttdRS1YYhL8dpmha19iaAgTAd55v9hMzj0G2G8cHF-bbvBpFpWs7Ot5uzTcqJIbqOU8II32zHqg0uR1rCVgUHrYZCzJi4aShjLmsgAtFayjwvaqqmEUZITIwBqkoIpeiQs3tYWYmptdJahsfMAdwtAElSQsQA6_qOHJdpLms93BxqqYRIZuSYQWDV6W5algkdesHf-tXftlIdYq0VoLU1kRDDcVlLFgLAtZQKMEXcLmVf6uqOzMWiVjdVAFjmOcwSYF3r9c211hXDw7xWO7_aDZsBiZC4343AuD8cmzS6QQ6L1vauOx-OXe4D3AEtKiKZ29Xjh__Gb37zv_q7_w0AkRhDoAAmMUxf_sYH77_71rNPPvu7__if3e738zQty7osk3r59Z_92Ref3WRhSjl30m6eU109AhTc3ExdHcKCoNbSj3mdCgREaJ85dUQu_85f_Pe-9HNf_n_953_1s08_tYD-fBsoFiAcIALuOckPfuc7ItnMluPi7s7txk5AUEshJAW8evpoXuZSCqX2kIGTBskimqjVza0iE7aljVUKEErUvmvETSwT99YjpBP2AxGB-SQGbKcEIuSGqjsJSbDZa4UBgGpVxKDEGM5AQpmEdV1zZnAVobouSCBdclUwQ4CUxeqKHugAxA6nOLZpBcBuHImJCNXUa8X2PPdIXXZwdyPERlKPCAVvUttEsNnA2-fp1772pd_-U7_8G9_42llKyX1WP1R_fbcelrg96rLYuuo6lbKoK7JBNTc1QJiW4gpTLXdLPXp88uJGup5zvhjH822fWRCCiTlTZhRjwAiGCGQGVEBgd3PwcKi1bsfOTDvJjGLmCCRZWrxeMBOJrhoejMzUnj4swojQqAVdn1suqA2T-9TlLjniXFcHkEHcNNyRsJhJSogw9p2blbWIMDJHKDauPaKpNQWsJDZX04r3AZQ-dwQYq5IgJ9FmyXIwU0ImB-KEgOuy5D4TRV2VRVhknksQraqOoa7haEWvdmcQsel6dxeHoe-CTllUU2cAkXAwSmRFETCnVNTbzH13tluPa4YU1Vl4HHISJKG6li4lJBgyk_vZkLd9yomRW871flYe6HZ6JTXoDhJ5e-BFINx7VwGgIRchELmdm1ujxT249W0xAKLRcsLakAlaCfmelN_ALe1Q38a6DaAZpzMftsn8idEP2Pq-QNSsew1kD-7NO9YG9nRfDcZwwwgGapGh5pSC-9ldS-rjqbFMJ68UQQBwa_tSIKIwBQAHIoJg-ytDCyvjyQEURIxEZkGE7u1K4B6BBMLy5OpqO3ahFgHEsNlsF9X9cVGiJfx2mp-9efPZzetpWae1ursICck4dqp-XMrdcQIAJ56mdVnqYV7aX7UJzoCJg06T9PDPR-yqGginqSegAy4aZhHQ9gPgzBpwmKtWaxpdIlyqRgDiCdPqcJI4LKVWDyUw83Bszl4QNAI1cwezaIopg0AMonjn4QgWaG71JEElQW5-j-ZjThyA5m6q1SqE30ueG3KqnfCbsBWJGe5foQ6o1qg50Mr5TdKMgYhA3MIYZqrq8ez5y6oV1MZdPy9rzqShICQdckLqaHu2KVpSTrvdBizqUkmgI_7Se482fb7cbZ9eXrDTo6dPl1L_9fc_W19fn296jNjmvO0HMweiFy9f17Kc7YbaWgoUn758cXY2Xh_nMgyv5_mdt9_lsXP3tx8_KmV2K59-9tnQ57Dolnp-cX47L5Naf7Wjrlu9fGH7oEzHwzRfnW_v7m4-ef4KUr6tvneDTiJ82S_uKpKneQ5dz3fDOPaJIswPd3vz6tVH6cZetl0aOYFa4pPhOXVIPdS1uNY-dcvhjZWyrsfuglMShHp1tq1Wx53kJCvosO0zc6iPfbp6cCHCpapiLMv8y3_yZz_97JkQjkPejBkZhqGTRKUWch-74fbN3eXF-fRmsrqYr89e_vRf_Xff_fEPPozcW4B6cbVxM5Yawfzi-uX1_qCcXr6567qUlR0gZR5SzkkuhjyQbPoudbjp06bPxDDX8rNffDDVSkTjrhty6ja8G-Xxo8eI9N1vf6jERNTkcS2s15r6EEZMbuGAp5UnAjQ4HwITNyhYC_1wg2ohAmEQNoFHc4ERslkQcOsRgUdjh1vblAF0jmEhDFF1yHK1G3djf3WxqwbHwzQv06bvmOTmZlq13tzuX1_ftvTkYZmrxmGpxT3nLJJqKYSQcsYA1BAiIvIWSfKoamYG4UAonQBGn9OmHzA8VN387rg4AiUGZCBcS51KyVnWurppoNZaukx_4ue-8Gd_7ed-41tf_eKj3a9_4wt_7ltf-uKDy_NxuNgO7z959Fu_-DM-m67adXl_3FsxcGgMr1KLu3lYn7t333nn4nw3rbrWWs20GCK6OQLUIBCeSj2udlz1sK7zWpHFNKpBUd1Py6w6VzWiwzQDcXVT9e0wBMR2SDe3dx7Qj93V5a5LPGQeerl8cAbVlnkGREF88uiiFg21vkuBsMzFi_XEZNbnTkRyzsyELJxQzepSKbiYzksF4nmpEEjMgUHCkmQzDqWquyOiSGrPoG7MSy1IxCkth7kR4Yi57UbdvD2wDCL1AhGl2Ga7cfVSC48J-y7teu6JerydbgyKWUEgHocX8_z-W5eIEOHrUqN5rAFFkqSUOyHCda1OdDvPL1_eHaa6VkVCNTUMdXWL1rY4P9sy4o8_-XSap83Q77YbXdZaK2DTj4oJ303L7WEmlrHvLaLr8m67HfseCe7uDoF0dzwQgoNxl2qty-Jf--rX_9Hf_92h35pbll6Gvt9uWNKD97Y1Dv_8n__uj77_47UWFGJiS4iS5qK_9as__4d_9BGCh1YvSgBBZBaMGViqe2uruoNWczNDr2XNY65Fayl1pt_-y3_h__f3_uHf_y_-fmBPeXTICAmThEPkDpjTkJhsneYAp7Y2KWtL51uoWqhWC-CcHj86K8c1MQFyNXWialGrAROxNNZ4RGCj0ZzA4G61tpVzNBm2W6sjWjv1NYktMrXnWRvv3z_Y3EqYQtMIRIAHYUIkyp0gYTkckBMylXU2KwEtDtAzcu76uiqRiGRXhyAMSpIEACP6YYxAAuiYhZObqQcCldVSyl5Daw0NQUKPTKnveggEh7GTxOl8GMGsk9QNlLT--T_96z__wRfFnQIOx-NPb_bPb-fXh3IsfnMoh3U1qOtSpqUY4DwtNRwdqvla6lrq8_3NWmOpfn17vJ2XP_rRx8xpGLoB4-mTLSN0nSTCnFPqiAyHLht4W_-32WrHvK4rE3MwBjMDELBQNe1Tx8zCfFwnTtT4gQawmgYjIKpFUa-qLNKImTnnGjp70XYcCifmqawOzkzMEBZuFkSNuU5MCBEO3o7vyNYAyOGIEaYAhEyBIZQSkFtrA4MweXWzSJxctZbSJRHGWmuAtWOKqbbqq6kF4LgdwjyzgBkjAhogHtdlHHs0y1mkE4jocxq63BG2EvhmHLwCBKROUhICG1Oy5p1VPz_bZMQh54jY9D0J9TnXtQhjStAz9Zk3IyfiqNFK6MgYQNEiNy2gBs2bQ-F_rOg6ia7vTb0tzS3ABEjUctkBiNoy7g5u4HYf327BbcR2XHZ3pFM-iLGhgYAgmvSgRVncooX0Pz_w4b2O9zSDh1OgHACC2tStmThO_xKwBXjuJ8QIbqej4z0BCKKthSAQ2wIC4j6m0qJQAagnZFGzvIGdjtrWfr_NmounsWYgAJCaI8AfbsaemQJO0oMwd6ulsnC7ARIzk4Tz7X7ZT8ub23lZLQKmudweDjfHYwVQj2VeHULd1lL2h-W4FA1c1ddqpfpSFQAb9gqFECBLDkOPQKbmYvYAR3RAZHKPdVFHKGpTtXWttagHAKEROKBFlKrt0GNm7Xih1QLQEBggY_J6crkFgkV0JAQQqmo-rQGCucskfDp2tW_36Xvt7TLo4UjQ2Extk4MUCH7q7QO0VbaZAaEkFAJGYqDwIGhGMTL1iLZnc0SM8OZ5dUCz-s_-4IfQmK2KdTFQR7Vwl5wOr6fLBzutZmYUsa7HbYJEtt_fbLt00W_KvPaEwpBS0uJfevutX_-FdwdK86rmRRK-fXHGiIey7o-3HePF-fl-mnrO18v-59_-cpnqi9v9K60v9tMXvvxOnZbzbtgkmfbzdCifvbx-6-Ej0fWtR2fvP7pa746y1jefvX7z6s1nb_bvPH4wng3TdDgcp6n4p6_flM4J7Ha_iDAKD5vurYcPPv7k0zAAxFrX3AsybLdjGpm0EHNd54QIarqu2y73Wc7Pzuf9OnRbMYG6gtUsvNtcPHp4KYS5ek7AiLuuSwTH_fTWkyflUNd1SUxPHl71fQehQ5_OzjqrS5fy-bAdcxr6POb09tWDzbgpU5nn8oX3nkiC86G7fv788uHlt37l5-Y3qx71_ffe_81f-Op26D_7-Nn1y7tvf-eHDFDVljp30j3ePb5ZDkS0FN1tt5t-mLS42rbvupwOETO6IgzQbbvh7qYwuleVSuK0ml7m_mLY9IE9wuZ8u9ls_8U__d2zi37cDBYOEU0XzhGEAN6eNQgB7dFDSO5ubgioZq2V1F6X5n4_QQ-ABgWK0zuDOyJqGLa-cEALMTYSb2IatqnrpFid5mU6rksxRlIzFkpdypKGs41aAzPkPnWb7dmr1wcNd4dFtW1GS7WUKCceknitQkAebGBVtSpEELGbm1mtLpyWuZJj2xKqmQeUUpEiU2rvf62bJQhW14gg8kz0b_3Jr_6ZX_ra-5c7qPjxs9fPXr1-cTP_0bPb1_tj14-c89fffezBtWiwWei6NlB3IGG4mcdSiyR6-vBBmde7Yz2sZVp0WepS636e9us0zYW4oVN5LuV2mtfZiFHNgKiUojUOx-XNm8P-bp1LxZTUHZFzTl2XwmNa1lKdGJPIdhiZoPk4M9E2pzovdSlz1XHTj0m06nyciLCqpSzMDu7Luq6lcuqAWD2MGn4gmt18yJnAE2NDblgNAApCVRtS1lJqLYjAzFoqBAbTWhUg-nGkACvFq1JiZ8SUOCVmsVVTNwgzANwd9nnoECixJOI-dahuqwkh-go6jaKK-r_4H_6ZXZ8InBBTpnDngHFIFxfbiNhsBmGWJGvR41pDyAE9yAwcyRGKuRNUtfOrzdl5X9fy8PL8i28_7TN5qdtNB0Sl1P1-nosaaED0XedWETAcalVGrmGmFgFqdbvdqPnVO4-zZKT0tW989ff_u2-rA2QgBo2oEUBkGNOr5ad_8Ozu-k4pOHeGUBkld-dXGxf-0lcf__DFG0NcjzVKBQgMtVrcqmohYq2l1BIYqdGaHSqotBQ3b_6Dv_IX_9Z_8te0LFcPxwg0N_O6LAsyO1EexpT7i6uzVz_9qWAGdg11iNQxE1uYhyO4dGldlzSO63wE9X7cuKN0OTNgWFCo1sDGqfAWe2bOTIKE6NZmj2bhCObajhxN9tVaeQEAeMoGuSkSY7hpDVXmhAZgBi117RFeI1xUlRihNQxIIgwhwM3bPEy4FYxYxNbiqil36hFWiZCAlnnuxoQBpZTUZQ8qa4nwxJITr4Ik6KsCRwS5QRIOCxFa5oqMdHIixqr6q9_4MpxsO-knn3703Wc3nDsgmKZ13G2mZf305d1u1x3ntVYLERI8TIv3zkQRsRnTze3CsGhVYpCue3Y7fxlqZrrYbT98_gYJ3NwCghgFu8ym7hjqbkGcQIzqaoYGKsPQLWSMkXJaV8U4cY2ISK0y5ICa-lSWEoRoZlWZKHWpFrdi4ZBG8cjzPGGAqjOnNaoI5ZxUG5U1AbibWlMcBUWgmvddMuWyln7o1Y51rYAYtUbumcWqaWiYB2ENl2AzZ6JqKsKIzKkdlD1hRyLRBlFWmXtGxMTIiEHgTokQQJjagVuYwYMcOCV1l8QIkJOEmxMwc4QTpm5wJlavbpYok7AgIXFgCItaHfqciLEpnLwOQ4ehF-dngjD2fc65G7K0rIwTCjXK5329EiEAidxOp24_7Wng_th_0oJFgEZtneC2d6YTmP8et92onRitA3CiNp4go9G8em5GcCrktaYBWmCDbYSf9mUYpyk-nCrwcCrtnaq_4OAA3Fo19yCf-49Pglq3wHuijcc9A7TtNDwC26E94rQNbA_y9k2Ikw6B0MyZ2m2-Haa9MW2hLfqw1UzIPd46v-iZG_QGKVryr5YWQCAIrJMattZAU58BZ6wEb-6OS1UW8rY59maJVkREJo1Y1CKQkuz3B2uZLXdiwoYdRWiW7yZoIIRanBDCHYTDwokg3DQkS_Eg9cxk0RYqrTAdIlzDzAP8lP1CQHe3UGE5rXeQwDHwdBlr6271yET7yaV3AuBEGO1mBBGmEeCG1NoPeK9UC2x1ECKkk5u1GScYwtTDFCIAqV3CiajVyQlJhExPCyyPQIRSVRv2neiffvs7nDMlWbFIhiSATqnrc0fpUWbC4-20u-rUDZ2eXOy2ib7zw2fvvn15_cmzy23fJbp99WZ3tpMk__rHH4ZFAiGG4-H4_pOrF7e3u93ZvBw_-MJbjChMx2nqx_6PPvv4T3_w1dujHu7mmuTh2e69tx_83r_83tuPL4bEASgdvnV1DlZ6gMlDwV7eHn_uy--_Ps5E0FOUuwkpXd8eL87P4vWtPX70yY8-e_rg8ng8slvXcZ_z9aubx08e3d0ej9fHh08f3e0PEfHk7SevXr15fX19-fjR5nw87g9pI2guGOfD9qDl6dX5Mi-QmXMu6xq7bRKZjjMgVauJJCww87TCWzkNm-7ifFjm9fxyBIFYdBwG6uT2dp6nQgiMeHVx_ubN9dXZtriGV3DHwI8_ef7k0eXlo609x9vr_cPzjQhMS9nymdLU9Stn3vb9Rx89W0q5vLyqoQ-uHuw24_d__KPhi1_2qvHOo_Pt8ONnzz548CDQxXXsxKGSA6olgbeGXSBrLGjwhacPv_3sWXHIQoxVuHv77Scf_tH2s4-fYSeqQaiNuREBen_zb6aMAPdotZ9oI76IAAIPx3v9tztYGBJbeKvENPU1Ejp4OJ52odEc4QaADu2XTEspYFAVXy6vL_N5lzGhL8cVAatpP_YD4Zt1JZHjvALIzc0tCIOkuqzQcN6AlFiYMfAwL2aOSMUt1FY3QkAmJC7zqgZDn9ey9l0iQq22rIUTIxNC9Cy1KAqqVWYWwbJ46lKf6IN33nr78oIdAuCV-Wevrw1g3F28ePWm63K3y2t1rwXLig45iSBCKWM3TNVIyIsRcUSVRNs8jEl7migtAAEAAElEQVRupzrd7Wv4UnyuqhHVYZ6WTT9A4KIKEIJcazWwWhSisS0AENTDqnKfalUGLuYGoWDd2NtUUCh3aSmLSJcGo0AtpUvD0PWHm7unV7t50em48qZPiYqtSO1dCxMhS-46d4R51VomoECGQDQNDFy1hvvItGoQMnAQhaTkZmAt3oFDPx6Ox2HoVItIXqap6zMzEQkjthfRuiy576RLEajVMrOkVOaVmBJhWZaz4TynhIrbi2G6vWWAt96__Hf__T-VPvKvffDlnLq61MttIg1HclDzqqEBVFerGn0vHVGpHoiHaS3VTVjNJPGkSy2xLCsw1qrMcjwsutk8fvwQi76-vV3mev50JIaqauGYeD7MHkhBtcwBrLUyQk4yTSsQIwtns9XXpZ5fXh5eXhOyJKZVDy9v-q1EqCEJwZBzNdvsujKboW3ONgq4OdvWdSlldY39pLLE7dHvVOdqnKkoVq19x4BgaI7IhNwPZT8hopoKIjJghbubu7LGb__lP_2f_of_d8zZwrzAcVqY1A26MTkCMjfWmxXVeoJbzrUyE7cdYHhVA8S-Y8x5e7k77CfXYm66WhInIgxqgG9hMUAARyRXvQ_1hbuTiHoAARG7aZs1IqCHt2BAWDhxuLZ8v9USHkwMHGgNQYpeNYiQwd0Jgvou6WoYYVpTZryPXgypc2szgIUELCom4kQQlnKSlAOcWKzY2F3Ox9nMzF215q5zdQhnh8TZzYpp7nog0HADIOGU2QICCZGq6rjZAEJ1swrLsv7e93744e18BHizn_fzsp-WFy9ur2-nZS13t1M1L2bzsi5FI6yoFqvLYmtR91qWcn04Voh99aP6v_zuhwC42222_TB2iYAQAgXDQDphIRBkkW7IoRgalKUUr1GnMgs1mAxJEsmphuW-q1WRycMajZGJ-i53OTMyACRiaVNXiFIqIiVkIaqq7giIqpZTBodS61pqUe27oRZ1C3WVxBG-rGZuRW1dCgKERZd6RrJSkIhRqhtnDghADDQiAAISRAwW9moe2ubXIqLrbK6BYG6S-jaFTh0jUpkLJXGgQCaCzJglVdN-O3Zd6iWZxTCMLCIopwzKKdceQKgRKxgkCQQWJAbTam17RtjwiCIc4f1mcOTtZrvdbXbnWzxl4jEgTC0c7iu8EKehTjuQQYQTYpuKY0PhR5zcZm1-ezqIYzSfDiAhVle8Z7W3jjC3xVg7m7fQzomWTwDIhMgIARQYgE0IdpIHw0k9FogBzidxGER4NQ8AVz95wtq5vd0KCPye1hPmCBREnwM92y0lCNsHHkDYKj2NeHna_rs5IjASnA6dDSgO4SDC7g1RhSdoqdtcfRjy4_Ptu5uh4_b31kZQQbzHp7LcQ5YCg1oJ8XOq0lpWkOBE6o6BJxwnnGoM5hBIar5flrubowV5kz-4Y1tLtKiPoyRKQowQ7oxASJIk3FkkvCEMmqbel1Xn4gjEyAghTBZQzcJBNdpbSnO0eVOdI5i7Gph5NQ0EdavQtpsOQgXiMNfX--XmWNZq0e4kbQvQglAIp541YCsAtCseBhMlAEJCZog4bQPa-qbBTRvAN-6vaRjQllin6FAgEaq6B3nExz991cYighLAwBycKPHhbu27YV2j2wplylsmoMeXZ-3CZV62m5QIiOR6f3Ocpjd3hx98_ObusL9b75bp8PDqQhhvb6-v9zcfffri4mLcdZ1jfevq4vs__eG33nlrGMbvffzRq2X65OPb7XZ8e3Bxx3BCvb67mYpGIsgmxHeHA3W-f3P9ZtnfHKfPXr1Goj5z0TqM_bosf_bP_srdxx9FLXfTcdFaHPaHuWMCgHVeu7GTsXvz5vrs_Gy33exvXn_5_fdu90cRL8d5t926ukIIY4kS6C427PjswS5ct7tNuHNQ36cCtVodetnthrHLv_iVt8ahPxzmx5cP6lpQMAF2XQcel-NYj6VPCKYRIEk--uSnF0Ne65oSXj6-2B_urnZjQvnSW19iV44y7rZDv0Ur_-Dv_53v_cH3bubJqqnX9999alrWMn_y00-fv7pea7x99WCZD19869Fnz17Wu_Xlxy_3h7VqkHBGPE7z2XlnUbtOHl9sXuzvPEKZetBBYz_fMfPV-RVSdEN68NZjJ3392esuMQG5A7hTK_-cDH3gHowMEK2bAhGtiA4B3sr0bQBBrQ7kdJo_IOF9s93B3BoRHJCaiAQQIwwArx6cNW6eJH68eTDkXBY9rAqMIoxEgnF7N4kwCwNSNUUWZ55X9ZN_HUutjFSqTaUioGRRCCI0jpyFE1n4zc0-ANzj9jCTYBtIBgEmNgh1ZxICdAj0SDmLQCbyurDZL3_1i19-8lASE1AQvH55s18qkLx5cweBiHzcl3Wxu_3hd7_9R8Jc3ZZqh2ldTUs1MydhEAiw7TiebzfLqq9v7l4cDsdi1OUWyaxrzTkX1S5lRrLqWYiRcko5ZT69qUZK2aqllNwBgKZpKbVWteMyT9NctM5LMQiSNB0OnSQktKiX52MnqAE3y-rhr2-OEE6E4zAQ0TwXZvDwVrRInJhoHPrtuIHmNmYK8HAF831dglvE1Nqyv713LUVruIHnxFYNgUxVOFkt_TAQs1nVapwkdz0iSqA4ZKRhyInYrdXSXDohxK7Ljx_svv6ltx9fPXznC0-_ePnw4jX90te__Hg3nAs82mUIq1XVdFpmTjx0HUY0g_og4gDuvj9MBtEUZh5BEBkQPBJT36Wh661WRhnOtuimppshdzm3Yf84DixJupRy0lK0FFNflpWAEMkDUhJCmOcFgB3QzN9cXy9rWUu5eLhd51VSAgsA4pwopWU2YtY51MwAgTnC67yCBzF3zEnkW1_58vNnN6p-kjBytgXWWSVlBHIztdBi49BjAAO618vzHYtgjP-b_93_7B_91f_P5urB2cNzlgRZSALNEdEDXD0M67oi0vWnnxGgmWkpQnxi7bNQQCJMIo7gau9_5UuH64mFUxIIC8QlgkQyM2IwtqI1IVDr9gAhipweYmrtmSXMJx0QERJZmwEKBQQItjM8EYiQqSKAVY84nZZYmJhbToE3730j9T1AuCkhUTi6VoUTIS8MHNDbeQitqqQORFoUuJPkCMTWDRvVmlIKM2RIqXP3oRuIW9cpkuDQjfOikpiIErN0CQi6lJPw1fmWGb755Xcf7HaLrd_75OW-xvXtEYTXtS5rhUTHuby53bOIqZdixKSmELGsmkWm2TY9qwMGmnsSWVelxO76cOj7nIlpP83VommOarEAMWtP9kB3RlzMBCmJaITVaIHLqmFuucvrXFgYmcpSWha_tEk-omq415bMaNNrCBDmWioit1QDC7fYt9UaALVWaLwZ8BbgFmazCni6z0WYmzK2FacxYLhB4_8jaFXm1LYE4WYOkpIjJU7CpOCuIZzVPPejkIQbeHQpu7dbIzABELQqSVtGCxM2KRciiwRYyikQusRMyMw1LGVGRFUTlvAgSm3WnrkdsH1gkoCUyWsRopw4Mw05dcznu-2Y09BlaXKcCABor-P7E9R91f1UzA3ith_A-085jfY_n_JHQMNj38fpIQIYCVr4u7Hu2lqhhXwg4H50Dx5A2BAx7Wu3i8bpH_x-KHzCAbWMPjWyZ0BQu3-0pQR-Pqg-kX4aHZ6amq_xPO6jfEx4UgV_njpHiCbBYQQCb63BAEI0cGpt5cYP8jYP-vwUb8K87ROSf_nxRS-SkODkFrMWG2XBpmljxgBwA8K2t43w0zbCA8yMAJiIuSFEvWUKTv89iGZhp_8wrBEOWIuSnHpIjNxUyu2n4eZJqCq28E37Tqr6aZJBFA6SxAHCQwibDsKsVaqxMYaloaTat79NQQCAoP0ptwgPYDKPhuZxdwBg4mlaq6pDsLBwy3_hvWYZW2EXW2caEQGYhJjbVSqgWQDg9IuCqNXCg04vj4DPrW6fL61ayouwmgEhU749zn_zv_wnhMx9pkHqUjOCA222w3osT99-uFZ79OjKbLXqv_DFd3Yi1cO5SoK3Hz9w1c1m2G42bnF7OF6e9xyw7bvHj662w9mz588k90Dwza--885bj_qUo9a1uB2XL335C6r-33znu-eb84HzL33ra4dXN-BKIl2WwvDmcHc19i-fv3q4u1ic3vnC409-8Ozmpl4_f_36-cvX1_vztx_uj8sMBrn78Q8-ev8r7x2Oh7OLS69lOuyTpI8_fL4cl8XK8fZgWq8uz7RUKFWQh02uy3z95vr8fDsOGTA0PBNtxz4lBgdI7CzQdWhOEF0nw5D20-HybNMlAUXoaF1XVd-N_bgZXry8McPNdsyIi1Yi3_bjdDgQYery2Wb34Scf7c7OCWieimQJjZcvX3_tg_efPHrw7e_8II09j2fPX7yebm933eaXf-sbP_7DD1GQCN_9wnu1lMuznaEu61TLens3hWsaZDNuCuJnN6_Ozs_G3U7QO4DL7WZdyuOr7bKsVxdnv_-Tj37u_XcPxyUlPD_r727ncRh7yfNhNjPq-PWbN-Vm_sa3vr7eTZJSe3NpzF6AYKSGk2oP99OaEFrqF82dTrnB0_Wegdst9PNXoIURUEMEcKsnMZ3sMACm-tX3nhJwROSEFChERFhLVfOpFHTous7UILwWnZdyWJfqUKqahVZtUePNOK5VVX1aylp0Ke2856vF02FzO69rVXNITBAwDF1OCQPMQj1qKSTCQrXUCHAIICOIcTNebsZ51t_-E18Rb4Revl6m568PNzeTdLlP0nWp64d5mQIQwed13vWbD957VFRFaF7WpdZSKhBaRF1rEJ6d7xDo7jjv1_lQbFVfVndw0zr2vboXdQCMwLXWtZp5tBFUezoTAjKsxZoVnATXWvGUL9X3H1_1QkRQqhFDOHTdsJS6qD1-9CAgnr-6PTvbWAAyfvjJy-ev96nPddXNpteq4WARzEKC5sBBpmpqAZBxUF3DoxRXAzcnYffQtQ5DX01bFIMBw0yrN3ErRDA4EANAGoayzIm5ViPi1LEQgbskafdNSQ0qgQhEEJnoV375g7ffv9wIP7i6GDZj38t7Dx8lRHfPzEQY4FUrAyQRYQ4gVRNhNzePRW1aC4osRd1gbWcb92HoEaHMJXeSc1qKfum9y-nVnoTC8Ww7bjqZ5zUlLtUoZF7LtNTVApnUGymbEQPC17VgYGODlGVdSg33zTgieO7y7fXd2fnGA53QigpzzlTmmje5Df6IyUw9FCI4ARH9r_8nf_H3fviTn3z02XGu66xE1HXDPB2IGd2aAt7Di1bOqQ3phBhZfvt_-Zf-8__ob22HMZ9tzOo0FfA63x2l67jvWRgJq8c49MKy3N0iBpNYnBJ94KBrFQxTi3BJ7Gt550vvP9xd_f7v_A4hq2lEoEjrb1hVlhSnVQC3cScxWy1NC8uMbaGAiMRk6tycTsJuDkim1ixPIhzVkKT9qTYpaFEGEiGgtugmIILTQadtzBE5p8ymNfeZkNqvgQgDYbcZVWtOuZaCyMhiRcuqgNyGc7nPWhSJ3OwwHfIwuGm4LcvKlLosXg3CS6ltxot8wu8dS93tzlfVH372xjqeik-LXt9Mh2WdSt0f1-NcifJSXDXWpdZaazEBdoBlrUlgLmoWxayqFrXZy6K2Knz7o2dBtBn7oe_ykCQLOghTJhhYOKSstUHxU0oWQCljAAmIcEQwoTAt65qHZGqEmIRaPGMYhvOzzboUIEfhE7cyIMBSJwjIibXBd5iWeTazZV0rQlBLbECf-1oqI2GY1RUBTYu5mrupuTkjuhoEFNMmeSDJhCyUCXgYBi0l5xECzHVd1uBwIgfAnByUECFcWBgIA9ayELefKJAwQTBxq4-nnBt218KZydwQSQhNba2OgiKUmNdlaQdud81DQldm7IRSQyZ6hFvumAGIqOsTYCShhLAZ-0Qx9JwTfu5cak-1U5Elopm9T3H7xq5Si4DwIOS2BotTyIYi2hEfT_7dFoPF-4psA-m4AwSf5DrU2P-f28ROb6bgiHAvZ0PEaL8cSBAeDavXjovYzs3uEHhv_jptJwKwlYYDW7v4dCvw0xMcA9DvMadtbncP_YdGm2mXluYsY2EHaIKzds047RW80T_J3F08yLadfOHx5dVmfLLdulmmVoQFQK-gCuphbtp8K3OprSDY9Mrm3soHxCRCKUnfdYzcFpHNjkyIkuR02GVgBPDThqfFidqNAAPMvWWBAJDxdAERPoFUw0-B3TbXaO5rM8cIZjL0zTZtBj4FrBoNCbEdi6JVf_E0qKsaJ-4oRLOiCAoLQ4RFrKUe5jVYKvBxjf2iczH11sAURGpdAGu7gVPeCk43K0mBAQiq5k2CbA4AiTkxw4maxg7gHu5GTBSIhPB5RwSgBgDE9z78SLWkjhFwPa6dJBRhIC_GlC3w8ePLeT6AgWpRqOMo0zpRoicPzrucHjx-kIXRkZJ8djtVgJLwajs-Ot8MIx9V33_v0ePL8emjXZ3KyxevtZSbm7uvffBOHuQ7P_h4mtOw3Xzp_YvNunz88Yu3Hj8wL_NSX316Pe2nGuuXvvD0_OH2i48362FKWH_-G2__6p_62Q8-eF-K9lVefvyGp_LZH_340e7s5YvX_ZCz2eH6Br1mjqdXO0yccuo3gxDtb_fjMNTVEJHCH1ydb7e9rs4A714-yeoQGqoCIBKEIBK4LmBqS-kSZaK3zy9hDQ7wMNQYu67PYkupXi8udpiICR1iSMk81ApC3N7cClOAPTw7-_GPfhAYXc51XuZlnef17m4fAI-fXHz46fPru_344LIidJm-_vUv_tq3fvar7z8dUvqd3_lvV53Ujv_en_vT3_qZr553WddjmdfDcfr42SeSIVj-1fd-nDsWlqdPriDqixfXrw5H7sZjLe9fXB6mmTMyyiDp-ZtlXZZd7kLLpsvb8zMK_NFPftpv88lhZx7oDEAYTBgQSOARGODWqAdsbgFQTRHBEVoJqPnJAcPNEE_vbu4Wht6KUUHtPeoUKXQH4i53_eW5ICCCe3RJWm6NU5IkzbDhZiyMwYdpdkQILKUCYC0KCIicqa_mjYEbAbW5fQCqBgM-nw5IkZg44bJUue9WecRaa4SxiFev1Yu5hQVVZnj36vzP_MrXfuadR3_mlz4oEUCQmVYvL6_vDuvCI3NiC5DUO0XXpTwQsp4PZ7_9G7-ki5Va17pWcCRiEgKwUkW4z71b7Kf19e1-UZjnejgutdbjcV7MFjVHLK6r1mWprXyFTaSKKMJZuO-TCHVjPqzrvJayVgB0M7PYbs8Qxaoh8LLUaS7jdliXMo79w8uzw93xuF-GLMe17Oe5eiwG-1LNiRMjRMoSENuUN8IJkQIsVM1SEkk06yEIpeukF0kkIhguzDn3VishNh4IugNBt-lyljBosvWAQI6yzCyCTEM_ClPf9USQxu7scocI4yYNXe43GyFm8vMxb5k2Kfelf_Dk0fl2VJ1ffvqKoBIqgZsXsxpu5IGAWhUDAVu_XCOcmaraUnVeVlVzdMYgAEoohIk5Itz0arshwo9--uroVgA2Z2MtqxVTi3nR_X56fXtX1Ko6EuQ-U_OoVNO1llnd3ZoaKEl3Npyd7TZDG1Lbj3_wYxl5arXoqizAQnVuS4t7b2NRDUeETDQIf-O99_No_9Xv_eHdtAJCTm1u7o_ffwoQQZxECIAAcpcAIgln5DLpn_rmn_i9v_WP-6HPF5uz9zevnl0DllrWzfmOu0yEwajqXc4p5-P1a04JkVRrw1-QoIdZ1AjnxBEoxMtx_7v_9T8JrxdPzw8310QAdjqTBAEy1loIyQ2qVQ-rrkDEktys6tpmhC1WFNaqwOHWJrmB4Ek4qjEQ-T2chKBJwzyCmMEhVAGg6Xx4-4VvpNS1r5i7BOFqxsyIpyuZe6SUI4KImNg9ui63UWk_9KU2YCVrLYQ07nZV1zx06ACEXR4itAUMUDjlxMKCkFPicJHU2gfnZ9s30_pbv_gBGHzn48-mRe-Opbrd3c2BuC4VSNbVzH2eKjE5xWFZznabw1rLotylNnRUNaa0roqILAThfeq06nuPzhIxBr3aH61FFapjQBaYrcTns2cASryus6uHegAhIhMTgwNgIOfkbrlL7p67rhbrUgYK9EiNMSIMEe073nWduxOQh5t5G123aEgbWbt5gCYi06qqReOsO19MI8wjQs09OAsiWJg5uAdJAgRwizDEICZVo0SmlnPCgHAlZjUTRit1yLlRKpHa6DNyyqEmqdNmYAgQRCYJgiFlZF5agRg5wlPfEYGba_V-6JKkWuqm7_HUOvMsqROpZWWRvu_QPTFdXGxNTRCyMFTvBc8uxj7zbuhEoOu6lFKT04Ujnh6H93DPEy8_Pk_7NEpOO_M15ie2zRpCALScEDNGAAK24M0Jlg8YEO2c3k7hHhFuTHSP5If7r3-aq5yWBdE0zferhjZ5xs-BQKePTzx_AELyRu9tX80xoGXY2-j8JAmGgIb3aP8fhKeQT5v2_fHMjwCsfdrpjzXIDAASE7RiNFiEP7k8v-pHc28j7VMCiaCU4hEWKEwRLoxMVD08wtobgfr9dSWIiJhO9jRCD6tqGhZwgj7DvYc4vH1b8JS5BzR3YGJqE_HWonBgYIKTOhoQ2qdFCzNEI52HnH5C4OHhvXDHCR2Pc21S4pPSFOP0wemc7k1FefpHIgtQ0_aDPhFRiRopfbvdEoaDg_3_ifqzmN2y9L4Pe4a11t77Hb_xzKdOzdXVXdXV3eyBZHMSqYmxpEi2YsuBESOGEeQiucqFkSCXuQkMBEjubBkJBCcXjm3IdmJSpiQ6EkmRbHc3h56ra57OfL7hHfbeaz1DLtb-ynVVVTg43_R--13ref7_308jUxV6GUwAxfozN_W6Z0WsKbqqH7YqZgJ3nV50hBjwSv9cb2Q44dcq-98BydA3-yGEQBD_0e_8d48-fdrMZsVARCIlQmwXMyDvZu3RyXqxmj999KxNhEW-cPc0EudSPvrk0-duXL95_TCoJaLdmKWUbChF9xluLtvF0fLJ0x0avnBzedS2i8X80f2zLjSIYZ-HO68eP_pw9_MPn37pldPEcPdwPmx2GKNxfP_Dx9durD_69LPrB-vrN6412LjHH773wfe_9-NPPvzou3_8lz_47vff_sFPLh49-uDtDzaPnn30wQff-OYbP_2z7_3oBx98-7d-4Z2ff3jt-DRwfHZx-fLzL6rT2fZCrLRptttsd9vt8mBdckmx5RiaNl1sdofrVUe82Q9n_cOj5WEKU9l6zjH3hRmywnq1NPXD1cJVA0LqUiklchj2-_V6QQDXTk8-fPBJg5xiiIn2-92sbZm4mIlo5Nh26d13P7h595bImPOY2rjf7W_dPAHHRZs--uyTxXwVXC6fPLx79-av_uJXlzGdHB_GxPt-u931Q4H16Wkwv3X9Rvb88OFZiOQKN05vhNAxInbx4slm0SZAPDpcfvrw8Xqx3G33N46P3v_g09s3jsecD1bN-cV5aBsv5fTGwdOnm_XR4uGDs4vt2be-9VbpMzHTVXi_bhdrLnEiTyAggJoyhyLCxKJmXrdkbmZq5jAhgOqWCRGQqRQhRCZEZHOr2SEiAgQGIvCDRYMEo2QdxrZpUoiASBSIGSn0_X7epaL27HxDRIaoDlmsiIZJyG1V9a1mgMBM6oaTeQQNDAwRsUgJTWAiQhpzKVlhuuSgA5SiKZB6RpOvf_HlO-sjA28IQiRVhAB90c8ePO1HcaDVYl6KBOJh6EOIDLK93Pz2b37za7dP0VxFBLWONpkDIK7ms9Skro2MLKKPnpztcylKm6EA4XY3qLuIgWMIbA5DzkU1j8UBtSgSUUBVo4pQQapuQSsKDiLCIRKiaXnp7vVEEGMYczb35XKBiG0TU9PEJork_SDPnl1SZAN88OSy3mEq5GkULWbk2DRJHYZcLvd7JtIigFhyFrUi6m4cWKUwc1FBJCSQolerTStFEdAm-byD-bjfxdTmPHRNy8Rt4hC7-SyxwW99-41xO86aWIZSeQ9oenC4WC_a1fzw1ZfvlDwcHaxThLbhW-uj524d1_V_KQUJpYioAkIM1LVpyFakpBQ5RmTOps8udhzCrs-5qDP2-5GcRHKTODaRmK34kMc8ljHrfsiHB7PE7KrFTNR2w-AA-75UPXzFCeSSHbxkGbIEwlx_ck7t-sBzJsLttr9-7_RnP3n38PhgPwhHMikmbgDBa_VVY2zMBF1qHmA5m919_u5ffevNZPhn73y66UsVYFNR5jSbJXXLeShDBqLUxvlsPZa9jBLb7m_9g793sT17_OCzcZQsw6P3n5oWrHkYhdlqtd9sqxg7NIGY-ssdIziCGpC7ioYYyzjWk0g1ZHvOTOXpo8cn1-997dtf-8vv_pAjxRgNwYogulYsLJK6AAIBu4O7VjSFmdWHSdWbhhANFNyJ0SWDAZgTkZlxqJ9CYeJ66uTAdewJhEg8DbAQeP3iV-t7p6kAOnF0nDAFhKGepqoRlsDNvf7uMZGJOQHxxIaPISDAvFvUJ5SbB_YQCMGZ2QEciFOMKYEomjVNSk0MgbsA80VztOq-8sLNYS-fXZ5vs277PAzF3EwNY9wPuSJ7zetgzsWnM1YxU5EYqPoznI2Q6m8NA6dFm0JMRMerZQi4H_KuH_djdkdFL2rFwNBzFkIiwMmQUFve4CbIkYGpiFYxWIwRkUopzBU0T6COhAQIXpuyLkWAIKUkKqqWRdS1Da2IODgTIyIjkeM4jEixnlyK6i7vw1TuBCYgpGlRGFMpGSMyBajRjKu9sTuYAwcOSGBeRdJaxEwihxha5Kl4YKWEEECBAwamwMFV6kQITDlENWHCEENkNjNKQdS0SCCWIo5gqoAQ6gbAnYlAHd1SCgBOiIkgISFhCtQypkjzFOddWi6agJwY2ialEEMIWN8SEQDJwKsMrJ5iiXDCq09ncPp8sl_LchUQVPEZAJ9naWquaUrOVJwO1cw3XAVTpggtTed4v4oDVS_spOKqc32f6J84ofcdYVocYJ3yTwl-8HqCnAL6ldgxfTqVJTqJq7Ta-erxFZHMDcMk9qmm35rGqS9erV1kRKLJO0ZIjlxxqOa2ns2O5p0XrUfQusEwNU5YiuSsRFS9coEJaqSNqIgjok4Me2emyGzuqsoBwaGoiIohgnsMcXIgaB0CQuRQW8yIAIyExICRMGfrIiOiitw-naGxm9ffD6vQfabKaaXpxUujWkAOgRBx0YYQMDKLeS4FkJDAZKIZVigrmAHglesAKRD_j_mrqmnnquFzhBCCuxK5FUnMgZERJ8TW1c-jVgsqLe2KxGymYqbTRdDAcTK60fSxfAokAQBACOEKBmXAZA67YejamQv9w__sv2YL3LXDOHZdx8iu0nSduDRde_vGNR0HK4XIX7p3emu9HPoy9ntBuH58fP1gnjC4eexSj_l7P__0K6_caEVPD1cEvLksWe2N50-QaLctJWtIkYjcpCG6_2Bb9uMrry5d6MGnDyHN0ny-3fXrVbeYxZ_88OPljaP33v_4O3_2s_c-_vCll55788sv_-q3v_FLv_jWiy88d3LzxqJdfv1brxXzv_Vv_WvvffjuYXf4yuvPDSos4darz3_vD7_3_It3P_zkk-Ojw7Ztt5uNael3AzrudjsH4xiaJs66lkkDIkTqAi9nyy62XdMSh2G3awLHyLkUbYzMOmowAQHGGJBBa2AMcdz3B-vFMIz1Et3F2DKjYwpsaOcX58wQgJomPH38pG0b4oAGq9Vsd7E_3_e3r9-k4OeX27Hku3dvvf_zD-7de-6Xf_EtKNowL2fNtZPTeTO7PN82Df70Rz-_defgxVeeu3b79MnHT8owGrsbeL83gcR-fDjvUrPr9xzCuNvHEClBzuXm9cN-GNu2aUIzjmUscv30cLfrQ-R-GM-ePHv-zt35fO7--Y0VEHl6dFNFetSFV9UTWk01qjshWb19AtY-Lk7GD0SCGtzj2mMyQCSvcTQypIBMBN73w62TpWUNQMSBA5YigAjk5rjte47cNOH8Yn9wsFBDLUIcx1GdSKRULp7pdOUOiVPgKoVKxPthjBwdgTw6w6yN4OhuOReObG4VU1LMOZBr0ZK__tqL1-dzE-3a0DTBRSrj6NGTy7OL3t0iRweQLBQIDQClIf-r3_zqrO5n3ZChaNn3ud-PTjRfzk0FEUsRESsu-yIKPJhu9-NmP-SiNbcsZmYuio5WV7RXhpaKUPTKuM-iMaRhGJkAHTkEMSOEJoUvvHAz1VqW6ijadtEdFrNGxXb9-Ph8s1rOHp5tQ0jZdNtLbMJQxnmTmMN2P262YwgYU8xFPeBYhAGzlLoIxpq_AM9jRsBqRQTEGMNmu6leQlWPKahmRODA9SkW287Nutig5cTx5Gjxq7_xxsnRQaO6Wi1ee-HOer1uUnPjzvHZXr78xedvXDv4hTdf_tLLdxtENQ0kq-XCA71299aqSXXWU5mHWoehSE2MYj6IpEghRQcYxpLd9kMWh34suzGXYn3O04CYmbF2WoHUDLyID33fzmbo3rWRALfDkIuq4abPo4oamNg4ltSEIiIi5s4UkDGmJjUMUhhJ8_j40e72tfV2m6s128yJuQ2cRTflLFFX2XnmBdHBsSF-6dUX37h352hx-J13Pvrkk4djgV3fj7s-ELlNd90Y4qyboaJpGcaxWR984-tf_aWvvvHDH_3oe3_ylxSt3-fQxrwfI-mw7UNqVNUJQxtDIHJCgFyyi9UjAAMhO5pzRJXCjCHyuC0YQfvx1r3nxMa2XR_O4js_ehcQgTmlWRmGFLkUdaw-05ptUEB0NUS2aolTYyZTd1MAJ2S7ko4CQl1Qo_uUi3ZHd1c1AIyhmusdAKkWABwBeHbvy5o1NYlDJYxqiMnNEaHrOhVFgJIlRDYxd20Wq1xK23X1LZOIQohapOlmpRSOFGMCAANrQkSAmFo1pcgI3jTJwauhNqbGwRfLbrGYrQ661-5cv36wfHq2-_jifDtI3-f9vq9npqEXNRhzEbVhzKLmiMNQZl0aSpnMBsRV9QPiiMCAHIIzukPTNkO_e-70GBGKlLGUoWgxH7NwCNlM1TyiWRUEoZtiYnUfpMy7zkTA7QrECzGEENAB-z7HGBA8pTiOY_0trUWWYkLAgCRaipVq_C1S0ZIMCKomRTmEkjMyB47DOBIFV0WDOo4AR1XtUhqyhMhMQUXcfNY0Q86haUS1iewGTFw1MSaOOJ2qasVRTSkEd49NZOY64EYkDoxEHImIIiPGQASROTAHIlUJTTQAIiJAN00xoBs5gCjFEELNlAMgNCkEZnRvkAht3iVmwFFnTYwEq-WiaXixSIuuWS5ns1nLxMzkZl6p2NNZvXohrubsU_xjQurU4TFNgflp6O4wnbPt86kw1rExXsWy6_TeaXJgeK0KO05IoNr11cnlW5P6NFnHrL5PXLVm6geg2oTxaVfAVN9-699XST5Tph5RYfo_XvmegDWBx1fOgenznLTAV8sNRJ_CqbWgPPWf68ettmREiJEPZl1EujrU1vQShMiuVqc3RKSikYmRHICYpuS8OTLV0EBENAVV5UBEXPWigERMbk5IjmRuNZRMjJNQefqAcLJsA2AbeRa4a8Llflx2SZQiwryJEIKaiQgzuyoHWLVNJFQzdAsAXcNgzowxADgasxQxADUjACY088A8qY8dsPaoqpkZwIoS4RUFyarTOHAAxEAYAzH6YpYIPZCHwNWGWF8nU7waJgRT7QpPH6gS0qr3y2xa31XDNjG6IjFXMNOVtbleEUV0zCWl7sGjZ__dv_hOG1qPJO7uFojarjHS0KT1Yt41CRH6_aabxZuH81mT0P3h-bk2_PrdO4lxuUjPznaXuT8-WP_knWdvvXG3ZIlt0zT0r358_sWXbqXgu-3ASMXs8mJXch53Q9nbJ0_Ob1xfdbPZk2f7ZraYLztkePpsO6j8q-__fHm4-oWvf-F0efzKSze_-Orzh6vFwcEytTOi9KR46tZf-8obYda8_KUvfvrxR5ja__Zf_vGz-08vtudPPrn_jW99PSJ89t57D8-e3b__EIDu3b1nopebrbo1qQWmoiUFfvTo6bCXdp6YmECbtmlSHDXnYVzM23GUZRN69Iv9MGvCajYPTIzYpZBN1rP5ICUPY-o4Yco6xsjnl5dNijHgvOu2m77r4ny1-uiTB9eOjwENCJ49vXju1Xsfv_PZ8mC5G3diFjl85bV7T84u-lxevHvvsw_eeeHl22998cWOoesCIc667sb142Y5e-Ot59_5s3cKyHP37hx0zRdevGPFP_r00dOzZ6fHx0J-_uTy-uFs3PcnJ4fby22KMFvPpOT1erk5P1-vFpKl7dox534ckIKLIcFiNvvs_mfD2ebNr365DLkmFUMknRgKVteGULkECFVubVplHlNzpr5ICRCQXG0yi7vTJKCY9GB0lVAEZAMHg8jMAX_23nvL2J7cPh72AxI5hc12a4b7fR9jvHV9ef50X60-SKEfShETAGI2rRQDdAS7SjPHQCZ2MGvNMZsFJjNUkzqmqNC2kEIxCRQUDMDVzEEjp0borZfusEMpCi5DFhnLmPvi8OR820tZdF0dYXAgJEDXwPJXvvZlNjWRGmS8HMc-52JmAO0s9vvS96Xv-8vNHolHUVHsc-mcPz3fjkXFDICL6ZilCt1FlJANwB1Na_6xale9iAxDdneOlEcBBHFTscAU2W8eL2dMasoh7vcDIJlO0yEt-umjMwEfshrQ-WUviP0oT5_ulqs5uW33Y9NEDGGz6UFt0GLqxWovDN21rlPNfHptgDdt0mJuoGq10VdzBEUlhEhIaEaBK6kTVGbL2Ruv3_31X3izS93RavHA9r_2ldcOl_OD5ezk9PDgcN4h_ubXnrt3fHTjeNlw2I3Dvj9vw8zMiurLt641yGaqqkSYQkBEQiBiIhJRZkqzZNnAvS_igPusQLjfFzFXN0TKuag6h2DmzBwIUxOZMC2aJvJut1_PFw3TWMpmN6r75W7PMQ1jroIjEXWHLGo1ymHSxMbMEUiK9LudgqUu5HE_7IybAO6KRo5SBBAJQ2ySSi6lD4Hr4uzm6enXvvbmH__hd3_jW1_-9NHZx_cfjUApYJcig2dVJO8WnboUGZtZ8-abX_zqL371tZfv_OTtn37vuz-4vNhSIHcfRrdcSj-ajjFEAAVATjEtF9L3LrJaL8e-l3EkgHpIw8pyAtOsgICMCG7DngP3w255dPIL3_7Nd3_6g4unT4uU6vsjcDd1UCI00dpd0yL1LFiJ2j41ONlMCSdeuFkN_cKE-ENgZjdPMZop1EguMrgjgVvt-SWrFQVwPnrlq9Vj6u4xBhPjEEoWSuQA3WxecjaAkEJMjMCOrqYIENuu3-9jEy3ntp0DGBGJatstSsmRQwihQu1n8-W-7wGxm82cOEQE89jGQe3k9LDt0nIRv_Xa3Wjh0TCe9-NmN47iYxlFjWvh2L0fs4KnxONQiNHFASvCEmKkPJZ2llQEARGCg3OF-BCq5IbpeD2bN2nepMdPz8e65gcS1TZREdBSgFzVwTybcYxqXoo0KeFUDMWcMxCu29koGkMay8gc8pibtqm3LFWLTRRVJoxE6maiXWqGfnC1ooU4uRuaDzlXIoSj55Irezz3PQdGxKIlUDBzc1CXmJoxl6ZJJlqnQTUQJqYIwBxjCGamoBjI3JBqQxzMDJlrMNTMuq4rOYcQ3KxpG0QqRWKMIYUiJaaoVmIMEQkI3AGZtJQaXSekACylEGPkoKrVUBmZ5ymqKilG5JCgIU_E8xTmHc2bZrFIKcTofHg871JMMaLXA1QlsEwjVHOoh7nP09QOdQ5T4fYTJc_cmWk6UU_FW-cam6lUIAAXnTYzU-6mYnxqF91xIsDUpqqpKSMDkE-Ex-rd8c_fUuHzz1Anuv9k9PJpsXBVBb3iexrAdF2pi_76h3FikhIp2FRcxisRGFyBZK48fdUfYNN-Ytr3OTjULi8oKp4cdiDuDE4IJgCV5IRZNRclohQjuRLV5Ao4IgU2qwNuSCnUSI-IxRCAUNXzdEl112oZdCnmaIEZ0NDBTBNDYrpxMFs2qQncNhgDucH5fmTCeRMDceRQwJkQkNWdCdpI11ZLQFhFKgCIDOCuPoqiY8NYVPf7Mo4j1IOR17ozm2nkgEiA9SEITBQDM1IghqmwjoxMAOhk7ojeEKaIXaSOKRHOuwbMkaiSiaZ4NV4hfq6Yi_WdrEblzEFrttqMic1MRGpfhpnhStmAUxkYHNHU-5LbbvbHf_HTP__ROynNxbUur5qmEcmG1HTxxsl6OW-DC4KC2ev3brD7vEkffHT_-GT12r3ru4tdN08jQB7GDz5-dP14cXr7pDUQwZDCB59c_OpXrudsajkEGkYVG0JLw9A_K2V-MF_OWzVUQHG_uOx__NMHcca371x77s6t27euPTvbXTy9HNGzlcPDg6ZtAJkCM_ty3gamf_yPfxfM3vvR20fPLd7-Vz9br4Pt9puz3W_-W3_nuFm-_qUv_NI3fzEP9tFHHxvI6cHhr_3Ktx8-fDro6CKLWfroo08O18cPN4--_92fzJfpxtHJtFoxA4c2RAVSxxSa3bNdImK0puVcSh2LGBgBJqL9ds-Mh4tVyWXWxmE_Hq8X5Na2rbvv-3G-nOcxd21DIX1y__HJ4coRn15cNsvZ4_tPDtbLs-1u3w-brPNVfPjhp0fHqzdffTFRIIJAbOCzWXN0vGoAjw5nP_zxp1_64l1GTEyH6-W11eGf_vH3vUtZtAvoRUPgNGtibLJqGaRtmqdPnl07OWkD7bb9fNYZ44OHFwdH8wZwFGmX608--ezRkyd_7bd-ue_z50HG-pia5hRV-mLoAEykVVhRhYY01VMC85Uz0NlxcgnXFaIZAiCQTapGqsX2QIhEXRO-8dbLNPrR0eJP_4d318uGA4uoiCJwTLTf5SzuaH0WZhyK1AYsVHAZAhE5QIwEAIfrWUDMRYaiWbQ-aiu4rUsJEVTdTCGCK41FVJVD0NrvZ_z66y-1wdoUm1nIQ2kbMnNukjLfP9vHJqhrGxsD4EQIBq6__vU3gmO_7xE9teFis63R2M1uaAIjYD-M292oACHG4nK5Gfa5KOHFNm9yr-YiVtRNNVAsqgruSDnnugFgZjBQUSLIomY2jCouZiBWaXaWx6xmbcuv3rlJqkVs1w9p1mSx9XI-7LI7iKgibMdytulTE3ZD4Y43Ozk_3y3msxg4ixRVYjZ3NAhIRQozm2jpRyI0AFUtpVSMxOf-JgRHoDLm2ER0dlPNhYnrlAJrEY00hHB8Mv93_v6vz0N3uOya6F9_8fZq3gWw2awZ-5FA715frVfLLqamiRXas5zPHaFLzenh_NbpCotzwGEY1WrVsE42vPZKMSCI9X3Z5zwMtstlGOXsYldUAbEUGUqNrnmKwc3Ifd6286ZtW84lo6kpHMzagK4AApbV-qwGKAjVns4cVNQDgWJ_2Tti6lIeRxnLOI6O2G_HL_3aq2Q47kVUIgcKlHOpPh2iWFSICRHYkSleP73527_9y7_7u__Si_2d3_r6H33_J0_O9lKcwFzU3IG5_hqmrn3h1VfvPP_C2eX5d_7kz3_2ox9vzrYVRTJuRgM3UDLBIlNmgUHNY0xkPlxuXIHnUXZ7NAWHGNiCgxkFAlUiLkUcEJFCIEQPmLY5_9W__zf-5Pf_YLfdOyIymAihq6kWRcCKZWeKoAIOYEoh1pgAkoE5MSGRiWLlvlMFVaObM9el0UQrgc9tplxj01ViKlALeWY8u_sGOHMMbkqBAckMORACqGLXzfe7PiSsgpGQQo0lq-tstsilNCma6GzeIYCKhhSImRA1F0QgYnWYzedqFkJoUnK3FAKiB6IUwmIxbyNda9Ort0_HbA92-6eX_XYo5xeXDpSLjfuBiPd9FlVRZ6JhyEhQL_iEWERFipqpGjK6WyklpjjkkQACg5g2MXz68OyVWycxILo_PjtXD1lVFAmmtHVfxNVDxCJOUJ_CzMSAKKZcm4gOWRSBxIqZiWRAqlzKOp7hGEQkEJPhKKWM4kR1jlhFV4AArkhopm5GGHLJ4NBUia8AMITALspM7l7EiLjuetQEEKVITMlxgh2ZWtskNS2iVKNWTmAWUwIkNUkxBgpWpG1SdY1xCEzYtS2imVnbdKA6m7UiMmtbBDR1FSViqNwbAQqVPlSNs55mjYOHwADYzjoVaxukgCliCiFFnrfUBl506eB4OUvhYDGbz5oUU2DmcHU0dydCt4lqQ1SnMlgjQDDNZfFz5_Hk6CW60llPh976TbV6ftYaE5lm7TZNx6e3U5yeatX5BWDAHNVr8bQmQVzNka4iQDU75FNw7vPVRE24VXyfmRFU_VjN8dRO81Vxt7IhYcrvuhkS11rFVeoJ_AooWS8CV9JQqM9grXkbBFBbz9N61iy6NI8xJITaWwUHNaSJQaruah5DaJn6kgMicyWqGjPXT4sDg0MWAwBiYsIsNXtzdfciqslfIjJVAGe3k_XycNEtu9gQgzkiMwdEFoUhexY9XrVNiiFwLna560WhFEfwFGk9b-qHfnS-08BjMTMXw0DRwHOx4jCKELGCm4OKOkJgYiTAmp1AZiYkutIhT2qV-kXVCwMjocUI646XbThet8mhbZgRGXn6GU0coJqrqIeYepafwkFTImsiIUK1TU81CXRHIK5rFzTzelyrF5bNds8Y2_niH_7n_9XlxdC1LTDt-sEJKWDTpZQCqt68frCadR9_-nC9SutVezrnsR8PDlfvfvbgYNXNY3N8ON_lrKZtE58825yeHJS-LAPlwWNKnz7sv_bm6fayJ8-mkHdDaJqA-PDpNnbzx9sdYJOJP3u2yc7P3b5298714_VB07SEvBvywaJzQ2M8OFgtVnOstVSEhiJD-PSjz_7pP_mnb33xtaPTo4_ef7I537j6eHExO2r_5e_883_z3_n74-V2EP87f_ev98O43_Tjfj_68Itf_3aR7SsvvdwwPH36-GfvffBv_-2__uLdWz_98Tvn_ebirH_pzt3IoaiMowKRgkHxJtByudqXEUIAQmdIMWrRRNw28VLG49V6u-tvrFbbYejm3Xaz6VIkxhRJVFOK_WYfmyaF9OjsacDYde3Z-dDNusvzs8VyMfbbGNOTzbZr0tnZ0xsn6c0vfCEiGkAInHNuI89SsqJHy9nJSXtyuLKsYDbv0mzZfPLZZ6Fpn15ulrN5czA_O-9ni8VyPbdiolpUTV3NVotZQDRkGWx-sHj6-GK5ai8v-6Pl4vHZxeNnj37lW98UUfA6KAVEyqqT_4vrgwKJSEwnvbhXAYi7eYj8Oc_ADWoypGZyTI2YCNkMONTRhiGjgwF42_Kdk-VR0zWz9snD88WqwxRiiv1YzBSxvgMgEe77UtSQed-PCmjmYnalXsdBcgwUkAhJ1blhczA3V2SmEGN9PhdRYgQEyVrdf0UKEJlKjMlcX3nuWgDiAClwLtmAMDDH-NmTPRJyDCnFEHjMSgw5j1-4c-uo7TSX3TgY2X4cQmLNOubcdXGe0tPz_b7PQjhky6XENhrCZtP3o22GwcRyrTk5IJIB5GJaYcCOolYBfepuBgrASJPicygIUIqa-1gGpgrQt3kMXRMj4X4_7PYlF22a9OTJhQPt-iHN2v1QzjeDmmf33WhPL7ZMzAHnMTn4UHQ39mMufT9QAEQe-3LYpP0oEDGriTohN0yqSoiRo6gwsYpSYGZ2NVFjInB39dgEMykqMYQ2wbd_-a0b3cF60cbGu5bmTUOOYIUSMdOiiav1bDFrwVFLkSxMhByYOUTGUk5WS0KIkUQLOIiBm-aixTSrmSkz55IvtoMjZfNittuXTZ-ZGQFNvKghIUdyFVWNgZgAxdpEDcD5Wb-ep_m8NTNHEncxKHW1ZJ61gFmgUMyGXRYtdY683e6q8oga7Hd7RqTsQy8eAIh2eShjNrPYxOkxboVi0OwEvjpY_-JXv_wv_sX_cPlsc3Tc_U9_8xu_999_72IoqmCapZSinrU0bTvmcu3u3XHcf_8P_2x3-az02RQQaRglRARGlVGKmDohtbNZHkdA5JC4iWW_l1xSStrnZjEbN5dAbIAm4m5aFK7Qc8RgRbht3BzUrOneevP1H_3wx6YwDjmkqKMgIyEAuZuGel1EIMDAsdbrCVmlIEAM0aeCKiAGJFZTdAByploQBdE6JgATdSQXA0IrXiPH4GDuIQYi5KPXvqEGhGCAHNkV3IE5OLgpxlnCOqtWJ6J2tlC7UhOFgA4cuOQSm9S1XREhIgxIyIigpt1iUSO5AE7E3bw10cQcmFJDJwfr9by7fevgjTvX5yk-udw_2u6ePO37PJqbFEPHfT82s6bPpQaRq-PMGMAQESgRIOZhDE1SVXKGijdhH_rStIGY2On02pFnfeHmUaTQNPHx2eXolutQtYqRARGxnhpr8VfVXF1cAWDf53rQrDd0rsCs1FRXG07xYlT1kKJmjcwKIKUwo5qXnMEhEo25HHfzISshSBZGctOYgomq18C0GgKBE1BILKa10khYL7dYx8AhJK3rv2pqIEOK7hDCFPwKkZFYVEMIiATmKQYFa0KcaIrIi67VnGMKRMAIkalrOhPhQGYeAmK9Tbq1TRMJ3TyLEMJ6vR5LDiGpSowJK2I_cDtvAuCsi4sQbz-3ouLXThdHq66NzXzetk2qmWmvp2OsBdOrHHYd6hPWBDw6fg67xKvRePV9wZWMCf7HISwAABOZOX6-LKgcUK_xypojx4rFxM8NXIjqtRNsjFj3afXaM5kKEH1ayU8V7krhqPeJ-qsUiKa-8lTpQ65uYYer5vHnm4ia8AGs6ZqKsSG-um9clQv86tJjtRJAgCBabhytjmbzJiauf6j6gOrmQQ3AiRmQAKGoBa6bOkMEZiQiclBVQERHILKKAEUkRFUQB3UnIpHp7mLuHFlUiLANdP3gIDIgWBHLIluzpibNHPoxX-zHo4NZE0PJth3KbizMSQBM1UCP5l0iGopc7oZdEXdQra3FWnBydZdiOetV1qc-0uudyrCGgurPjLBae3JV9VZC8fR9EyRsEJPDjaPZDLFryNXw844wYS1BT9_sSe1sn3MYP3-dXP1rtaxRHbuaVVSVT4Dnepuk6k90dzzfbFeLtTn8P_6z3yWIdSeAUPe_zGAp8fHh4vm710VEZX_3zsnhrDmateTw-OLybHN553h1vFzOE-5L1rG898Hjw8PltZMDGGx9MNe-H3Rz4zA0bXdxeVHUzAhDGNUvnu3eG_ZbC8Hj3RvXZ8A3Tg9unBwAUhub3ZAXbdptcxM5xTiAPx4u7t64RgYE6GIJmRxzKT9_94OTk-a__If_9d_59_7B7_-T3284ojkUGfvx1nPXi-Pf-mu__dmDj4-OD9945flv_cKXv_GVt37vd3_v9bdeK_3wzsef3Lp-fb08efbkyZ_88Ad3bt955bkXNmM5Ws7-Xz_4zhcOT2LbqI5ulKW4a2gad0_dfBzGGHge2-1ue7Ccb_d9itilbrffN0wUsUmxqjoXi0UMYRhySDGPo6ggUtO1o8rTJ2evfuGlD977mFkJ4fHDpzeuXdsP5XIzxJZN9Vu_-pXnT280IcZIKcTUhsgcmIY8MNHqcBEpBIfAEdDR9cadGz99_76axyauD9c2yNmTbUxhOZ-ZaWibRPzg_sWrr9w2w-BoaF3XDOPQj-N8Pc9ZUoiPHz9cd7PrN07r6J8J1CDEULeIVVyiOv0iZrUqOKxpwPqe4gBFzUFjYAC8AlN5vX-7uanSFX6AAEktRpSsv_TGiyoK5qEN3bzZXg5jX4axzGddLqUfR6JgCFIjvqUgh1KKGTqgitQK1rxtZpFUTB040mazdySdHr0AAGqmqkUyc8CrMUt9FhkAOxD6ah6fu35A5sU0l3K5k11WIipu5_uBmeuCFjEQGiU2Gb_52osu0ueeE43DMOvSOIy5aBZFxMvNcL7ZCdBuGLfbvRmJEzIFipt9PwxZnfqhIHE_ZlFjZnXToghe1yyllKJSchGzUrQCUsyMkcStUssqjc4RdRwJ4O61YwdVscv9CEyBAscEiGMuaRaz6nYzbPshF9-Pcn4-AMJmszs-Xs_aRs0UEMFcdCyi4qOqMoxQJ3o2DpkApIg7jOOAgerLYyw5JCaCIRdnyEMG8LZty9AjRjMLATvC3_qlXzhdL7o2MEOW0nBS0SEPhCHGUCEQbRddtexzatKEYyMKSIv57ORgiY6INo7jZtsDUhObosZMTeI2Bjcr4vssFLkf8li0L2IGhli_W6OamMaYarg3hUBq14-Xp8ez-ao7aEJsoqkQh2xa8alqvu-HUqRkVZvY2-ru6vNVO-xH02Kiu22_WMwt23LZnVw7Ont0ntrls8sLZtCikYOquykzO3iMETicnl77jW9_84c_-dnF-Vma23PXTn71m1_9L37nTxU5u5tbiEzzgMyBEATy0H_4s_dTciI207wfnbTKetzdcm2FKiGaqIECMzgw0-5y28xaVJGSx_3eCUScUwQXdCxZOQZkUxHiyMwGHgMNw3D7lZeeu339T__geyEGdUVwQo8cp86NGiNpUSQgdC0jB1IxjoGIRHINSgCRqkCVDWHdZbGbMQWoVEOmQFxzWYBGIdQ0Nei0QKokYpKSY4vAThGRKMQmxkBMzNzMYumHlAJR4BiJaBx2IQWOE7U0NIyB61hizGNsEjcRAR09xcghlpxDDFLyYrZwx2qJahIbOnFcHCxG6a8tZ_duHAGl-08enp9dqqmMwh5qnn4Y83bb1126ZnUFd9xvhiy5ZJFsYICEUoqJMbJKbdAjuI-jZgXj8HiTOdInZ2dmHiLfu3ezi9gQIJEqVNJjAO5CdMOYGnFjohBDSq2KpIZMnBlrUsKBAsVxGFNIRAwOOpYuRYKpogHkjhrClDdJMTARxuREexmIEMyaNpoW5iBFkNndIyMxaTEwMPOSNaYGicy9jQ2YtalFZCJ2V3RMITIHRCjZVa0mVkIIFIIYKFhoQp1rOgMym1vTtJFSCEFdDbRpk6qiOROqGiHM5zNRcTJHMAJDBw6ikhJzCBgQwFE8YJBSmCiGmGIISKiIAqAwi-HwcLHqZk2gg9UscVx0sZs1KTWEwFyJGPg5yYcYkQkYgQjM3YGJgADdsZquAapjgBDqLQiuONl1to6AZqCiFRlpNevmrmKVbcVTmMeZqU7x64Td1QhJ1AhrdATrUH9qIV9VDugqp0tMk5yzriPqX1WBotOOAtSvTrYw4RvwqtAAdbUHkykCHRlD5XEiwfRrrNMyotppxQzdDKxxWLUdWl1AQIoMABRIVMGm9xcHCBwIqYns4PWrMAARqftid3A1cCOHecORKRDjdNw2QFQzJECu6rHqmsBF29xYrglA-mxq6rgr1oXggApABIrkDuJ-fjk-vOj3osBsjClw1_HJwSwG3Ga52IyboagiOkn1SLsVK2JW1MQ1JC6qIl5Ur_I5bu6iRsSGXlRFzRzMERGYiRMBUZEM4Ex4tEhfeP7opRvrjri6s5EDEhuiunklNX3Og3IQ1Vr38AkEhA5QfUpX0oF64azLGTQDEe3zIKJSawP1vCOuZsMwhBgvLi419zEwB1Qt5B7NZ_O2aZtZak5PDrOaFjlez4jh-snaAJqu6ft-tZzPjw8_vv_kYjd2oTlaH-8u5GCxmLed5GHsJYs8erBbN1GGvGhbFRrUPjrb_uCzZx_08NXnX__qvefeevX5JkJaNCmlYg5qjj6bNRCx6WgxTx7o_v3HLx-eeq_j-RaGMiNGwhDjd7_7ly8-d-eXv_b1wLDf7dVoNwx9vwV0GeXGzXu_90__cFvGX_7Gm6EfO_Iu-OPHH_97__7_4p_8t7_7pTffPFrMPvn0o9Wy-eY33sA-_5f_xX81Zrl97-bR8en_9pf_6snRyQcPPvvTn7zjbrO4kGJWBjQNhF3k5Xye89hENpXIsOpmy5TarkFmNTxYLVKIXZPMvIB0TVg0TZPo9PTAfZBxf3ywDkCPHj184aXb58-eBg67zTkFS4nbaJFDjOnG_HaKDTMHYnNnYgoRQ2iaJqbEGBA4hHi4mp8eHB4crl-6c_pv_71vvv76S7uz_cWTZ-181szDz3_6_iASY2IMDeF6Ce9_8NHx4TwmvnUwD-ireeJIi242DOPx9ZNuNvuD7_xJjA2gE9m0C1StrziT6bY7_a4R-9VCoA4_qiksEjKxTT0jZKz-TBRRAwshADoTUCBOFDu8HIZfe-vVfp-bJu7GbIAPHl6OxYAppCCAqWmz-j5nI2q62LZpFM1FcxHR7J7X6_m8jYeLjgk2vVzs81Bksx8dQMS0qCOqQVEdxuwOqUnqVhtQaMZInjUwUcRhuz89WJ0_u8xStvt-u8-zRSSyIrbbjGxAoAzKBAAQmFKEL7_4HLuCgrpGssW8IwcRefDs7GA9D0CX-94RRlEAMqLL_e5isytiCpbahkIU0RQYjQCg5Lzb9eMgWTQPIiLoTkCmgIauFgjdvAwlZxE1rmp3cAIuoqJuyA-ePBuHwsApNalJ22F8eLERFwFTgE8-O9tvxqZNbds6oQgQ06gyiD04u0T3vs-7zX4cxAhLlt2Y0aHvBypU-kFkJDOqZFiw2MT9fnRDcC9ZtOgwFjMF87aL5KjgFEg1E1qbwp2bx_OATcQmUhtCl9pSRncNMbqp5UIArrLf9uM4LpYtEQXi6imaIAsGjCBFAHC7H0VtN2QAVAHGCECBAyAU1THLfsgla6kzY6ReJGtd1LOKT75NLU3D3SwOGaM3p6v54ayNxAY261LdvUuR3GdTuBKGUmIOSF3T5F1OXUxdowEwwOZsK-p3Xnt-uylAtN88Xc-b_bYPDMSoUgCBkIjjOJQ7N67_lW9_9ZOPP91teo6EauuTwzEbtGBuTZuIkJnydvSiwzAieNM18-W8Wyy2l0MZjSPZKEQBzaEUBJfci6NY5c6ZDpkJc59DYBMBr4YPredeyYNmBS0hALrUQichmJobmBokfv727U_efqdJQXJBh1IUiWTMzBwjE7pLaVJQsQpGN9UqRXAA4lAXAq7CIaoYGLgYBXZw5GA180BcR5AhJWSqfgCfxquIgFTXCOYUQgLkg-URgZcxiwoRg3mIravN244IxQS5ngrQ1MGsJmcYgxZt562UEptWVVzU3SKyuxMCM8VIGBG7GJsQG267EBnnTTtfLNZHi9OD2ZdvX0OHzWZ7sc_b_SBFxmHc7bcYccyZiVTUzXXIgbhIIcQmJlADdBcXkYYCO-mYiw1Nk3b9SI6EKGPZ7nYQ8dEnD5-ebX_09idKCAg3D5frpmP3FJzQA0IK2CZmw6o5iiEaeGgYVVWctBJPWEY1BNHsADE2WnKl6lvltTCpiKrEGABQHRRdwQGBOYg6B-hLjhxF3JUdUKQAkEoxUzEwByZsmkiIBkiOruZmfe7VTKuiyCVbmTdt7keYEh6ObowMYlaMIqY21tRpTJEiVTsjIWXJQAAEMbIAGGFsEzFwDCGGUbMScOQYA0biFFXNQFIThlKcgZGa2Aw5E3rbNITooAhIAbtZR-6HB2tCOlzMg9Ot6yddahazpm0bRkBXImBywqn5BlKP0TUKX8OPQIhgjlMaEv7HuTvhFfNnogBNVd7aBvhcJQaOBGpKCFwbMY41gFXTHVgP5zXccTWzr8d0r57X2kBlqsgXnnp40zpiSvMYeJ2DmdVVQpV3KjghVY3I1VqJ_SoiUoH_9VCLXD-1CesxxfSn1BHqtP-rRwEn8-unJ6Be00huqibmlnOeysRVmQymWibEPYAZXUUAmSb2iNd8kbsrUGBEsApbqp9a5VO5o5oju7oz0vFqCeDoNpruSxlySQSLJhLixX58eNGLY9M1fa-jaEoxi6m7u4qUVdugeRa7HEqhSXXUD9kdHKzBiFa_YmQgNWQKhk5IWStthwzQCLOqqdX9iamrqSkgMBg6AQRittuH8-dWi8YxVplZjATI02bH3azOJ-v6CAnBrVLSRcEqFqnuHYjqoISZmJAZeSKvsVf-lXq9LhaZ7g9IOOZh3s3B_Yc_f19GRbZSChO2bROCgxcGOFkvDzheT00K1jLdWHULRqIw65qmYcjaNeHlF29cP1mw-4efPHrp5etvvHZtPN8s5x2AzJfd4WrRpMQO59v83tOzP3j7_tHRya-8_so3X3uumxFHNrUQIiHXHnoTGwZqUgCDJsDYl2ePz2-dHDQxWC6q1qUIjFpsKOWPf_x26sJPPn3Uu3z0yZMzke0-O_Cg6gmzbf69_9U_-I__k390eHSybNPT8_Pz83NROz5ZXL9x_PFH7371K18uu11q09e_8dYPv_vj8dnTf_gf_UeJ5ttS3r3_6WfnT__Or__K116898Mffec7_-r_94d_-p1RsA4eAmLp-65tUkyR4mI2V_NhHFukfb8PDWQZ5_Nmv9_mvD-atbEJJQ_RqGFuYkTzLoVu0Zw_u2g4HqzWJjZrZz_4sx-_8PpzrjRebqHY490OHRgohJAiJebIzEBdatsmNjECOhDGGJGZKRXH-aBPP3uwffT0aNaN-41bhgg__8nPjQjUusXq9vVbl5ejDnm9aERLQDg5XXFRLeO8CazWpfn983MOQkSBWet0_0oKXgcKtaWDPIEbkEivNodi6hOUbtIUimpt3E5_2t1cFA3ITk_nL984-MrLd__Gl19MVFD1_HLLjPtd36Z4emN96-a6Ye77ssuZQyCk3W4nopLL6cHBrInX1oub6_nRbGYq_VjO9sNuLGO9mYv0-ywGUjmUBupaVFKMQGD1PFdGNxdTdSFyNGmYDxezW9eOV7NFKfL02fZ8c9mGwERZZJAxBOyapk0NO4qMbQpB9ObhCtTdM6M3TRz3_WbX90UXXeNEg9p-VDEQ0z6XXLyY78bxYttnNUMgqrhSIoCEEQzMxFXAp__MQyFFLw4OkqXytdU854LoWbVky0VHGZApl2HI5XJXHjzb7UcvUkIXt7k8PtteDLLNxYjmi4VCZEwcQslu5ll9fbTMZu----knZ-fz-dwJN8NwsdtvhjEPIzCpqGoh48QxptAPWZ3UQI18Uh1607CWHDGqohmYUExtf7kBZCaOAYb9vot0eu14PWvA8OJyl8dc1JCAAWdtkyIFBnTrIsUQgIkZa1aklAzgOedRVNTqiCqktBvlfD9k96JaGc8G7kiOMKoZQL4qtzkAAcnn79FurgXRJUuXEoo14MOwP9vttvtxUDG187Pt-fnlsB_FCsUgqrt-KCKRGwVLAZghBpjFtDxYnt48vvf6C6vjg_XB7Nmnj86356Pobp9LkcPVsu8LmEWmLjUBOaX519768t_69td__vbH739wP3tmoovL_cFi-fDBRTtrQorjMCDAsN_noc_7HYgMuQjUmyQCuYGhQ2oadwuIoAquTWgigrsoCFQORuCYGM3IrO93YlpKccIUyGV0E0RgcMtiouhuXpetCg67fnzhlbvf-_5Pht2gRUITwVwkW51NERNQNW5O7UFmr2EE96r-rbl_ooCAzOTgFCNTICDTyoFhDoToRYuSAwEFNnCniUyuVv8UojvP7nwJOaoUNyilxCbFJuRRkMHAQwxu6kAgRgE5RG4SgaNBCNFynrUdAI6SYwhuCu6paZgDI0mR2WxWt-8JvWsbUI2E6_XC3I5PDq-fLp5v2nvXj0ThweXm47Pd080wZNnuemDqB3E3YlQzEXP3EGMRHcrYhDhKLiqJo4qpqIOHEHb7EmICJFSrbmQXU7HETDEdHK3ff_uju9cPmXnVzp6VASlmlZJr7RBNfRR1r5BgUBFzC0RISEzubuCMoFAJiQ4TKhxFNYTo4DXuaSUbwihFxdAcDUQ1MJtIycIc3bWYAqOU0jVtKQWgilGdEEWEOdQ5RKXdc2BzKCXPZou6qAWCEKmMEqp_gCimYKYBkTEQYwhRcm6a5GoxxHnTmUkkamOjbkTetK27tiESQQgphpAiggrX8zRRCMxIed-HGNqU3A3BHHE273LJjBiICTwEbFJEt9ksJcbDw8VzN9dH89npybqNsWnSRMH26fhF6LW9S1xX3fVIPel3uRbkam6HiOkKxDmd_LGe9LECH-FzJvx0pvcala0Srrp_qZ6BKflDBjXNg7W4VmNENBXv6vEep8hdpQ-ZM7Ff6Xu8Il9ximMh0RQqcieqaIgrdCWQ17uKKxICOU6K4WpAg6v_gKuFQcWG1jNohUtOVFA0O16t6Cr1BAjE7OaiSoToSOhEyBzqBbGOtysCCbF-XRP-q_ZaCclcVDQXcZwa2LXlPB2yJ7OarmZdNEfEQUqp_E7Ag0W7y_7wyWXN8wBCyRpC5IbUYBwzusuQj47m7r7r8_kuC8AwmKipaTXGKbihgaGBV7daRYe5GjogQEQCBAWvTysELGIYSFUBgPkqGuaK7IfJby7nKTJfIWQrH7aCwRDqcqeO-auW7PM710RDu4o1IDLytCiYdHVM6FblO1dNks_L4YhqdrHd5yxdmivQf_Jf_OcX531aLDe7sW0igYUYGqbVvLt3ekTFVWXs98uuvXNtze5AYTHr3n___np58PK9G1zMRv304fmNGwfMrMWXs1kuY4ohJnaDffZ__t0PoV08f-vGmy_cZo6OtMtak36ENL3IkQITIQYichKzkst-l5XxxnJOHC72-1lkaJo-ixb5v_-_f-ff_pu_8uhJf_3u9d_7R__1L_39v_7j7_9l3m674AFwf77_P_zv_8OmCc_dvvHOOz9587XXDe2nb79779ZNCvH1N774f_oP_-O_8Vd-uQgUUUJ_-wc_z5eXi9Xij_74-9_89V_WfX95cfng0VMt_uJLXzw9PLj_wfvvvPPx2z95583XXlusVg2TiUSkFBnZZ10qo8YQOITtZjtvY0yhwfDk8mIx69o2ppYRvBRJMQaOoUlDLgfr9Qcff3R8uArz9vGDJ8OQD45vdCk8fHi_ieGjjz75G7_-dRmlSK4lSjCYcFLmbn5-0btBm1IKTUph2bUHi-a5g6P7gbXj-x8_RpKDo0MOVMZMgZCBEFbrxc8ffni6XHZtl_vCkQjpydOLk5ODMozr5cF7H3z45uuvN03jWqtftV4YKlbLTMHdABTgc11GYKyL0CJGMMGFXQ182nnWCR0AuCsgoOtrd26-fu_aUTcH9aZJ5jyKYsTzy_1-P1Cbtrv80YcPBCDE0DRJRIdxjEAnh-t51ylYL_b0Yv9sO-yz7ceCGEtRBwKnnKVuzxRqbypU0jEBBCZTJwIO9XfEiLAfhhQSgQfCk5PDeYiztlX09z_8dL2ac0hMIedSSrl-7YCZnp1ttUrNgrbqz10_LnkcxiFLP-vSdjdudgMzc4gEYbvJCmqEWbAUyUXarslFEShnaZt2GPOTyy0AZFNDULNxGIFAzQYt2UTUigkRZNMQ4jhmplAkxxArgHUoWUahOg0xR8QQ6Ozi4u7NUy8yDmV0Ot_tSrH5YrHbDaMUM93uhqJ-OYxisBnydhy9SGCvRuH5fL7thxiqA5pHk3EoXlQFGF1dnbCXEmNEB6wczECV2aCu9SGV8zkYpzYFQrOcoFkfHPy7_5u_eziiA6pbX0YgYMRFSl3TOnoZs6q2qeGKk3Ywh6KWczE1RAqRhzHPmkQBrQIhkIsUcG9TrEM3ABhKEYMsBoZF1ACkiIgpuLqLqJs6Yn1Ln7fNtdODWWqG3OdhZA4h8LXr6-1uvNhunWhU7XtBZEPY9ruma4cxK5q5j-PQ7zO47XY5cPRR5m0zX8wRcMx9L0qBzy43s6ZLTSgqbYghhZbCV978wlt3b3z84Mlf_PRdipSH7K6X282__w_-9sWD7b_80U9FQM0un565mbkisiP1Yy5jCU0cRU3ESiEEBSi5Pu8n3xoRmBg6qgrBRETVPNTWBIfgooRQwySWJdTpEWINpKtkDpHdUxMz4m__7b_2z37vX6BJDNEBbbL8uqtzCK7F1ICZQjAVcKj5DiIy1wkbPD0WlACmpiQTMWmtN8dUWWRahCjwBP8wokA18BwiOhCTmVI7i4QmkpFxsV6pOhK1i7YUSSmIymJ9EBA5hpiSu3MIFSMamB1RTZhDmxoCr0ENpBCYQoqpSY7AIdhQ0CFFbps472aJ6MbJ4XJGtw7nX3vt-YDh2WX_cL8dDcQgF0H0YRgFvOQCBqZeclZVVwU3UyMGM0firMaE5g7EWSRGVhEExYAOZmTqkksuCBdSLiDQst3ZCObLWXPn4IhVI3EMxIEInYN3KTKio8WWUkzgVAe3kUlF25RU3erBq3JaUhQXcJNSYoju3nUtqEWOKaTERKqJyMVcnQLFGAEE3GLbOICBO1iIsSq9mNhEkTlrYWSTgkTIgZBrLLS4ExMxqgmHlJpIxOiAFEJsAgcOARyaENm9axOhB6YYOFsOsUmpJcIYYtO0VnIbAqqCKLoiSBlz4oQOqMbmltVVmhRNVV2aEBmZACUXqvR-LW1iJkDXFGm-SF2KMYR5160Plm2bmtQyBXQIzFdgg6s8P9WZltEUR8Qrp-80nQeaQivgykzITgR1Bl_zKldAjSqtn2rA9cP45AGrcaE6Efeaeq-TM0Q3t6kdAKhqTGGiQIJjnVRfWZ-uTtQ-LQ3qKB3sCh9jKqbTyN-vlvpkNt1UENHJJyKvO4IzOaHRhBsin_oAhmC1zQ_mZuDgTETEIfGke_DKAqfITWLmum0AUxVGrgBNMTOzqiYoObtZDIxEDqDgCB4Dx0BpqhBhDfKKKlX-pUy6OmZOgddd4kDimk2RcDXruqbZDfrBg7MefD5PqYmzlOazxk2GvoylhBSIabWeu9g4yL7IqOaE5gaEFEP9MqKzKwxWqf9s6FbR00gVuKpmtRNQvVvqXk3VHNid1LwCKggxOt25cz3EACrmbprdSk0PmXnVrU6xoSnWjza9JD6XQ-DnHugKLqs_sirccXVE4CsGEE5aJzA3YHenp5ebGGPbdkM_fPjuw6Zb0DKGJlYO7GLW7vbj4eFqdtB166YfL9s2HB0fmdHZ022bEorlUV750q0GlUrZ7PZHhzME0P3Qdi0RdV1rAp89uHz7wYab1W_80ht3rh9z0xQldwIOTQiBMCARo2i14XlV6zlgKQURl3H-ww-f3Tw5gMBPLndN0xbgnN13-enjzVsvPXfRj0XK4fEpXD85Xh2kQC2FSIxgYbn4_bf_uN-ef-NbX7t4dPmT936-mi1fuHPrybOL-w8ePnly_m_83d_6D_7P_9e_-Vu_-Id_9Kebp2efffzZrs_bs8vx6fnPfvrOxeXF2aPPfuHLXzh78uTtd99J66O7X3rjV37z129dW3_w0Y__u3_y-z_46Q_NGAiIjADGrBybsUgMnEJUBcs-iKya5tn5ObOrYUxxGHMbqUsBVdeLFrS89soLFxeXy_lsdbTs5uGnP_wBL4IbBYd-e5nNizuEoAB9FnWQCQqLQHx6vExt2o_js8vNxWY3ZhPqbty99b_7O7_xv_z1b72ynr37k_d_9Gd_2T87W7Rd3u89lwoJPonri23fj-NiFmcx3r11st_08y45-PJgvpjPv_tnf9E1sUkhBWZEYmRCpEnFV5tLPvmdHA2qNltEiJEi10flVHmqbBgHIkZ0YoyMi9iezDvJGiIRmKhtx6wIY6-5iDqOQxn2Q7uYm5qM4-7iMjLeOD28d-1oEcPT8-1HD56ebXeKrIClCCOZaV2HmmqdCBAyOMYUGNzdc8luUETUtGLf63FJRFNK5kU1u4zP31gdztOw3202-9S0lyMoYmS6PL-4tl42BGvmReQ2wGKWIsMbL92xUiQPzTwFjMNexJwjE6GJIHpxiykNBShyMWemoR9jjLWt1292kmU1XxhYHktRbZqwXq9SDMSQZZScwW3o81CsXEnd1WqjGtFgHAqIE6OoZCkOIO6isC_62XYjHEMKz7bbEKIBPnt22e_Kts-IcLSeb_f788vNs812e7nJQ19KySKb_bgZR1E9XK7yWIb9kGIqvciYHcG01K0jITKRSEHyGELJJRiNm-LFXAzByDiEVeVzCiA5BjOZ4WIrBWEY8sVmjxAW3exouTxczJoYKtB4MWuX84aJtKiaIZGZZREDAPRcysPHZ0_OLvtRbJr6-XLWoXuMZObbXT-W0oQw7AeRkovUd81YSREikahrmlnX1qSzGxydrts2utvldpMSt02zXi9lUFVThWKYixbVAmoAy-UKjXrrz55cPnl6JiaGuB_G2TzO21g99gC068fTk-uq3rbtydHhvt_1_b5pm9XR4s2vvPHtX_rK8zcPt7vdX_7k3RAA0Ktzw1M362LWMXWJmoCINIGxMRcVtJhqwNPzbsTYYkxOjBQNDCLWBIeDm1qM0V3RndlNi_S9TV4OdJUQORAxM5oHRlVRqWN8RoAQIrkiSD9sb75ws_c2ArURXQqZxBhF3Bw4pFKKIVJkU3VXBGQKFWICAEyBOdRfSyJycSMGMOZQA8PA5ACuWlHZMUbLWUup1RHXgkheMX-glWtHOZuL1NaJqzBh32dAnHezQATqUkpIAeuGNETNdUuQHM0QHKnaxcWcYlC1nHNWFTdMqKCOyomymbuFxCfXDtOMr107Smh3D1ZtG_siP7__4NNHF9vtoObbzTBklSKBoO9HCqHyZyqZgJBdvYhUHa-5gLsZiOpYJIVUyqhF-rHkolO8Hr1YyVkf33_8cN__4Z-_sy1ZA7148-S5o0VyCUTEJGKpiWqOYIGDKQAZR-TIZh45ABHHQIFjjCVnJM-l3kgQEHMpfT8iYz8Onpp-6FMKyGRMWSU0cZSMwIA4FlEzE0EkYh7HXOfa5hBCCIHdvYjGGJDIdcKzcqivVAiBU-RaAydGCpi6RlQoMsdQS8qlZGZCRCuW2s6spBQdzEiJqb6qK10mNKHysNy0HjtjSkhAgF0IUDRFZiYTdPcutYlDigkBmLxpk4kkCmDeREbw-SIxlzZS5EpQYEIKMdJUnoWrIArW-i8A1SxNnX5zzbxUjE7dQwBW4F0dudYJxlVT8-rvwum-UDVeE4GnzuXNwaeBcD3s1qW6KkwAyMmXQIZTxRwBzKUuHNTgKg7u9d-tkrcr8Ymm8AziFA2iq5wSBAJydDBUDNa53zpYXl8sbh8sbi0Xx21smNkVqviontcJAmETqA0cqyVuEh_grO2qOG4qp4KaFTOPITASE3JMFdyEjszEgQOjm3ZNbJvWDE21HkZjiFwdiYYAwKmm4WtISonRQRktJComJ-tlBeLD5y4yRA7kTIfr2bX17CClw5RKzkPOu7GMlZbA05A-Z93shpylyt6QoI7RzVQdsklxC8CVyDvFpAwVJx1NrhtU8yr7M6iGNTQxIEeabAAxhkQBCtTGCDkECoEiAxNyFbxPsM6KWZzucXU5RLWCPqX-6xW1_qztcyNAJXg5ERIHwkDA6i5W4eJUvDw7O1s2cyT88x__XNUZ2UfVksvYV6DT9ZODw5MDZYcAj549OzxeHB8vsrgjO-Ennz59_Di3IfTbEbu4229XswTmy0UXAhW1x2dnP3l0fnTj9i986QtptsDQZDVTA2JkNDeqK2JwMw9MPLVYABHMRMkJ8PsfPPz1t-4eNPHivD_omiayKeY8_KPf_87h8fLk-o1dP4TYzmftwe3nVk26dnBatXbcRJHSrJcPHjzYPH38t__1v_1n3_3hu598ltJivVz_5fd_cnF-1qX5L7723B_9xU92l3K-3Wtxdy9ZAOWDn719cP30ctSn5-ccyMf9h5-8i4CZ9at_5ZsvvvbFf-23f-2lu89974ff_91__t__P_-_f-AQMTRtE9q2AcD5fK4IeRzZ9XC96jjsdntUjUzHB0sraloWbeg4jPuhiWEWkwzD7bs3cy5n9x9ZLicnR30eNrvLxxfD_Wdn7zx6ev9s8-hi9_Ozy4u-XI55FDcn5NSGZBgocRNjURvFQozctonp3_x7v_V_-T_-r_-Df__fKWP3R3_04_ufbppuVQRWbYsMFUYeErPj9rJ_841bzx4_aQO3bWqX3Z__9GepZeJYeztxQkZU4tnkhycCJGdCJMhSHDxWyxDUK77V_B8gUEADVytIyIG7iL_0lRcj0-ZiN_R9IGLC5bJB12eXl-Zg6JvNlkIwB1HZ58FVnjs9XKYUI7_z0aP3Hz2lkJCSAwYirl02tdodE1UxHaVS7AxUR1UxCxyqBjSmWERUFBDbEAnJTIFIcvnKq_cOu3R-fjFK2eaxmy9G9xh4P-amSQezaOqiNm85ga5aurZsIyGotcsWPNcsHgWKkcFQ3fo8UoAKjjNxqmlJw2E_OlIBG90UIEZqm7ZtU0CIyA2HpmmbpkEiI8i5hBC0FDSUIuBYRMCD18eLGTKKWFbd5p2Illz6LLssf_aDdzb7cd-LDXD-bIvA7bxxQivw-MnGUGfz2e5yZ55TQzKUFMkNxqIX2_2nD58g0Wo-c6S-7ytPrMhgaEVNxaVIxZ2LgbqHFPOYm5Zr-l9HAxMmCpHVzSVjQGzDCbeqKOJ9zjHEVTtbxGbeNGLU74dxKIGZgajOygiKVBHv6ICqlrOKgQX-4PHZzz98lFXNPcYIprOmKYNULs3jp_eL6HzZgTuRMVMiWi2aro0MHhAjUuUgElPkkEfVgts-t6lpUujaGBxUDNVjihTIwIkn1Y-JYmAUQtQqY1ofzG_cvT6btZeXOw5cXM83G3Ed9_3JyRpc2Ww5a1-4eetv_uov_sbX3ryznJtKHsqf_vBnhbSojjmLGiTuEs4YLvd7dCpFgbmZd4acXdVVBlVhLeLoTULQEc0CsbukmMYhA7EaiCoT1-yoiNfW_tiPRGBZXAwpIJKZSpF6rhApGLBIrt4eYq4sdTS7e_ceAEZTAjRTcifCEAIQGVhggvqzmlABk-vbVD9POtSRgQFQZDcDYnBgZCZ2MQJQKYBU1QohBRkzOYoUopCHgWIwNeKgRcCAT7_wLUMytdgkUQ2BQwyO5Cpt26kpBI4pMjJzAPC2aSVL0zR1HU6EFU6V1VITXSWE2HaduYaQkKmddylFAF_O5u2suXlj-fKd69cPZ43qF-9eQ4ePnl3cv9w93gy73ahA_W50LaltJFt9EsUQx3EUNwIEAhWb7D_mdb1lBuZopkRAIRQVRIip64dh1nb9fiTkamcYenHkDz48f-2F2ynAejZ_en42upUCNbrNDbqSqbh7k-JYVKTU3ZYzKqCDBSQRaSgZups7KBG7KgY2tSyFQlDROjosWmKIhE3WTJHQ0VzcLXAwRFchImI2r6OvHFN0MWAwl5RaB6s3DKt6SKuXE40pAEDiIFmIAzKpWggECLFJyNR2cyZAxhAoMDNWFxIgaJUrxRRTxMo4J6YU4zDktguuGpDNvU1NFgkYeJp7GwcijgyAKNUSkpjAfNY28xiaEI4OFssZ37t5EqpHmsivDlvgjvy53MvrCOxzEv50pr8yXyIikRNU8C7Wki7RxOB0BGSGevQHdDOfup0w3TIq7BL5KmYzDfSn6f_nBFKY-jLgFq-k1-iOwFaBQ8RwBY6sVGwgqu8T9TKASGoTk3uil04jZwQ0Y3AZbx6sD7pZYAyEolIp803DITI4ae2SijRN6CguuyawNzFewSUBybvA85C8cn4IHITcpE63AUIIFWxazMeSDdxU2SGGlJpY4_tACGCgOHE0AcRNtCBzUTdRhwpXBWYG9Dzsbh0dkTmCi2oWzVkrf5BD6PtcCNmxFBmy9SpZfJS665xijE1icx9KIQ45q7jVWb6oAkAI0Srb06ZvHVFdmQIhRAjFSr1siBkhIle6IBCig9dRi4MhYkx8PG9mKUQA4moKJpvCOrXw7e7mZlCv0xO_HAycAImJp8UDElBFqVZIVfVOTxXuz5sqVAFQZBM3DB9fbstYrh0dg-P_7T_9L_shpyZxCDqU9XrOkZfz-asvvdBvtm---MJPP_iw6_ilF24cLLu-zxRw0cXPHj66ca1dt93-ckCCZt7O5itiIiBT_M5PHrzwwp1bp9cxxCqIc3cpmQPXNwsGUpUaoptQ0dWxQQCECjZnOisayI-WzbbXJ5v9tdN1zjpuLn_w9gdffO5as17-7O33Xn7hecZ07fbRxw-evPKFF999_6Onn9xnZnPjGG7eufPFF26R2K2bd9r57F_-yXdevnenHwpGLuN4fO3oB3_-F__8d35_u5Vv_9pbf_BP_yS0GJkX6_V8sX7p1Zcvnj576cV77Hzr-jULeO_Fl_7J7_zRm2-8khItujaQv3Tj9LXnn7-9bt_57LMf_vkPfvjOezdu3pjN5mTGhA62mM3MQdCpwDCOiN60MTAW1UXTAtBmu5nPmiZ1m83u4OTkyYP7YL4927zwhS-dPfzU3HqLq24262bAqW1CG6MbjH3uBfail7sMgQNQFgSFMXsuutnsd_v9WDS7iTkF-tYbL_zrf_Ur-33-3s_eHXOfmmDZEDQREtFqMev7cdGmB_cfHB8eA7o5PXx4_1e-9RUXRMBSDMGn8j2AoROxg-uVvRARInNoGgdgQkRU1atAoFNN7Pmk2e6adLJanqxmucioZdYGMYuMqnq5GRwpNYmcYtuJFUTnQOvV7Lnr12cNl6IfPHxyuR9S15qRydQgMgOK7O7V-15EkdEJRZQRRNWdALFIQWcmhqmXVhDBCczUwcDs1ZduXl_M-_Py6eUuWx6zmNOsjesmEMDhQTdmMasPQ0qBV23K-4vT5Som7vM-xcjMOcsgQuBAyIF2Y00iuqltLrZZnciHoSBjCIiKkmXfjymlijs38-qw5zAp3sU8jxKYmFCyVFhC4GAqAFDMCxgiDrlEIBGvd7AarshDVscwS_tchmzDkGPT1sLxsye79XIxiO1Lzo5lGEnV3WdNJ2Y5D_0w5FwWXRuati8jA44qAKQmMaVKbgFAcAKAojkkBqCsSuDo6CZIDBP_DQMYI20ut__g3_ifrGNLFLvERNgwt5EBKY_ZyEPkJvC8a8F8zDrkYuCLpu3FAV2LAWERVfPdmHd93vflfDsgc9-Psy6ZWmBiJrMwSgFkBx9y_T74YtGqw6g2qpq7iKADMQaENlCKkZlSIJOSUhT1vs-DqiPv-lKKiPqs67b7fujzvh8BfDmfd4s5x6CuKfKw6_OghDQONWpEJedhHNoQX3zu7jff-uK9e3eHYdhdbFKXnjzdXmzOfvDjD8FB3YSg7WLo4te_9OJXXrrzL_70R4_3w-WuFxHpxyGXfihtaByhYUL3PA6z2fE47NGdkOv5gSroT_Rqrw-qQuiqZmboCqZgZm7MyExojjx1eWs_MTTJVCsZ3CsL2PTlt95SbX_2J38yDpmp2jaxXvOkCDG7m6hOQ05TdycmB1e1EEPF5wGCmVBI6G4qaoLMyAFcAYyYXZUAiNBL4cBTIKKC9AgmOWwIBMarl74iCmaOzLGNZk4x1HS2qnAIgMCEzEFUgDjEKc7BIYA5BGLEpm37Ic_atmRpmwSMMSYGizESYZMiMbYNh4Cvv_LczUV782D12r3bEfCzx5cfPrt4ui1nm3yx6fu-11JMiqlTZDMsWZrIZj5oIUrg4FjzEaCiIuroHGKRMXAYhoGYvd7AkFIMuYypafoxx0Bo4OqpbefL-P57f_LqnS8SWjfrtuOuuKmik5sgmHIMXhwBY4gK3hdBN3LUul7PYuhFhYnJUURdnJCIUF0QSMYcYyTAnAuAgwJMTFFHdFdNIfa5NDGaTYLH2sHgGKRI27QljzVRxYERoKoAmMjdA4WaW6121zYlNaUa_HdNbXKzrp1LybO2lZzBvU0tRTKRmBo1rwP5GJMDzNtF0YyOSEiADFVloKlr1E1VQwoV8dY2SYrM1y2YhkBAHiK1KaYYjlbz05vLLtBqFk9Xi9ODVR1u1WN9BcZNIZr6NjaBda7G8HX3XWeY0_Fr8mNORLzPB_hQs68TAggnYijUMMwk6gJ3qIsTn7D9UDNCSETuVql5dpXq8Sn7XQvE-PnfUD3KVzSgyVeMCPXxUA-KXgE14Fg_senWEMwUmSLoncPDgFwHSwIqqiLFAZjZnETd1UPgWZdmTUrMJsrE6iCiUgUHZMuY2pAQoRYJaqpJfSquOEIxdwBmIvKGQ5OaGIK7AjgR1jtGlQSBYxXbursD9UMxU2Ke7kXgZHaw6uap6xoGQ0MQVRGvVLTIDArP9mNCywJtl7b9-HQYCYLWpjWSlFJFJCI2jAUIxFwMtFamDYDQKncHHcChzrArz8zMQBKmKsQ2txiIiMycAEIgcjRwBKyAJw5M4Otl0xHVN_UaMZvK4jVXZpNneroe1k5W5TCaEwARuxpB7YDg9HCbTHETttamvNDnNYJJ01AM3_3swxvHJ_PZYnfZ_6f_-L-JqcPAu4td00aOjAS3715DkOdOTh4_fTAUXXXd3dNTQBjGskOYc_js0_sv3Ttld0Q4WC0SNxzS2Wb_o4fbo4Plq8_fRAqltlwcDVzBRi0UIiFoUabAdCWPxikeStXsJsLID55tPv7s0fWTpQOdX-4NcbZqf_KjD37-0bNf_uXX33908cKd6z9_78GXvvTibqer49Xj8_7GycmjB48-fPs9RmPCUfLrv_jNL772ym63v35yyqn59P7Hd-_eAQqPHz_m0KwOlj96_5Pf_2d_dHJwcP7o8v6n92MKhFhU7r7-2nf_5XcPD1d3rl0vki-2m0_Pz1-9e2dm-5un1yJBwzyWXsUd4eBodevk2kv37r5w-_b7H378wbvvP3p2-eorL-5HJbemS26UGEfJB6vFKKpFLocBHFbLOcXw0fsf3Ln34m67FZfQNE8e358vVh9_-OD2Cy_vtmcffnD_1dde-fGTJ8HwcigeebGec4xqygxtTKGJ3IZEjIDzWYwxnKy6FGLbtO4u4EUlqzrjnWvrv_0bb0K2ELpnlxempWtSjfWkEMBksZq9895nBwfr2Wr-4cf381ZfuHebzKplVdUMnIgNLDCjYfXZ1Vc7M0fmLkQ1N1FC9Lqfr0UjECICQvRy59bJgqipWW3ylFjFc5Ex17kCIWAx7fsRA4lIBHzt3t112277MavshgKxNfeLyx2Rbza72IQivlx0YJ4NikjlotUnY92dqRoxmVmTIgKp2ZgzEdfBCJgTgpb8-u1bbdM6CTWeewmAXYy3TpaJiciYeBhz28YmcOLQpmY_Dk2cHa8Xpch-v0fyoc-GtNsPxS0QMQRD2g_lbLtzBHUfxkzEEMNFHhj5aDlnQnXJYx5zyVLU3NyKmhtWDp4ZIFiFSphDSAyTy5G8YlrUShGs_vgqmEHOQ2EmUXj8-GKP-ujJBYVgFdKNwOyObOC77W40H0H6XU8Muci--GJx0O_7QCyaz59eIlHXpCKquXBi91rlYlCjWg8Hy1mYyaymEQEYDSCGCmdzdAsEs3axuPvC__xvfavxmGKMkRExiwYEnkZoaCWvZ_NxkHnX7Ipsdr0TIwcRJSAHIIei1nDo1cRhLD6aGePFtnezto1NDG7IMYDDMIy5aCVyuIEpNG1ypBozM9PKvogBh7EsFw0TxEC7XR9TzKpnF_tiPhZzhyGXcSzq8PTZDmgyr6eYUoxjLuv1atiPfV9iihxo249tm8zBNI-X_Ze_9IXjo4PdZnhwef7DH7_XpHBxfvniy3dTTO9__AADmXl271aLRRv-3d_89qLpPnhy9nSU7X7ot31g2Fzs6hti7jNhLctWyHmps0pTVytQGaCuYGrqITS5ZHAjInOv_Hd3qxDoGvJVlQr4qkXDahqzolyVHS4ll7d-9ZceP3zy4Q__0tVig-DAIYIDMqpPowD3qRVpKkwMDubqakhUPbNQtTcTxsnBDUOQPHIIVoQQsUKBEF0MjSgwBAKtDxrSyrIEcDM-fO0bSJGYJI_cRDRARC8WQmhiopCIEQ3Wy4NcMhB1XUeA6r5arMehJ0AgjKlDtxApMHN9H3VAtLZpaliFCZl8tVicHq-Pu_TCzeuRYdOXH7z3yZP92Bfbj2UsWUvJRVQwF3EAVcsqqGBuRVXqfQtQiobEuVhlyYuZmRIAEIbQ1OJsdZ4uF4vsIzq4moyZAhlhIHru9gunq9m86-aztvTjbj9apc8jarUwAUCo1XsndCJCpjyW1KScMxKNOTMFM3GHMmZ3aFJycVBz0Tqed-Jhv5twkERlGJvU5aEHcEAKhIg89mNoIgOAIzGbapXBEiMRV1RZrSBHDqpGIdSTTT0RL-bLLNKk1MTkBuROgQEsMlFkAuBA4NaECAbEUAUwMTZqOaborkQYU0SHxFSBNhiQKAADUP1OOhJ2XYsMKZA7eBFGXMxmKUAyv3k6f_H28dGiuX26unl8wPXQTIDTWYRoSrN4fV_Cq3-m1qkDc8VGUe1uuhoSVn0vXt0fEBFxmpx9fiavYXy4omTQ9CevrMCOAFB_Ya60rzV6VMP39eF_9fnUBrCbGVxdt6aH72T1qv-_9pmvrtRX5rKrYyehm1WY0bX5oo2BGIvJmMtQCjkDopqrYilmlQEClmJomOHKUSBqROCAIXI_9qt2lqj-Ptd8ChSVohX8j2riakSWOAQOgRmczdWk1BhGERv6LMUQGRxKhYhNDgkwA2Ke7mpq145XDYf6tWN1sxsUUTfTrOvlohSFSEBQBB3xbJdbpkFdRaWYgodA7t4EHvqsZupIxKJW33tjCBVqUkGaClMDu14XHZ3w6vvgSAzoQLVaREiTYa1KzYgQGb0NoUVtYiRQ16s0mVkFmddUjF_d0Kx-VVeDNAQkBLNqDa8vM3DTz5dSVVPv4MRYccM1AwZgWkHDxR48e3rn9JQofPcHb__-H3-Hu7aYuJTFaj30_fHR4XIxPzpYrdfNRx9-dvPu8bXVajGfM3MpxbebGZbt-ebO3evjrhBC18w-uP_0bGf3btx64eZxk5I4qBhc0aXc3Q1FNIaAgLFuCgBElYgcDNxTDA4kapLL5SDvf_bZF168CUDPzvaPnl0erZaffPxEXF96_vqTs0uXdPP6waMnl8_du47I7by5OOuvL5b3P3343s_eDujgJm5f_dVfuXft5jAMue-Xq0Wbmt_7oz_88itfoECvvXwve_7R2z_7zj_7s2t3Tt1lu71w0bqy4ZQ4ECEy2HJ9kAf7nT_9wWs3r6WYVk1adXG27J49e7yaH1zuN4tu0c6a2KRZ1z13--ZytdxcPHv3vfefnG9Orp1GJjdzhDYlN2PgxDEFWrXz88vNrG3GXJ6dPbt9-8Zms-GQnj05A7P-YiwE7SzOw_hXv_FlfDY83Y459z99eAFF9mPe7ntX24zjmHU3ZAYAohjJiNSsLi6b1KaYutTGFKTo42f7J8-2MYS3f_rJs2cX12-ftDFKHohD4qgFZm337OxpjO3yaPX-Bx9_8MmT3_q1r0suUiOHjETEAYmpSezuahYouDszT1xlrdB_zFkZyRyYyF3qQ4uImpBevXu6nHUXF-c5S2piCmG77d3RCMW8H0XMTV3dTSU0Yda1N1fLXHQY5XIYBfDycmsAppYC3Tw4EkMg6Puy3Q_qSpwATFWB0cFLkdpOdgCqWhamKjCjgIGCmruKI8wW6eVbN_IwztogwS-f7ZsYn7t5sG5jFl0uu_ufPXGT2axzhyKqIk1sjw8XXWB3LVLAAZGN7Xw7NDGcrBbbfR7GrI4KkEVdvKhvilw76O7cOOko3FjPzZ0ohiYgkZjnnM0gpjgOxRyGfkQmyWJio0iTUhEhYtFiWjEUgA7mPuaRiNyRiafnvpqIGsDu8Xa7Hfclt02cNbNxnzHAvG1mXVey9GO-3O9xFs8u9lYgaxn2ewxgAsNuMAYOZKIpdWMulkuMTb_rpw6Iu5vXhxJw7cCpO-Q8MEVzV4UQE1huizM2v_jqvde_cC85OPjF-eBox7PZums41oOhHS66qjHZjXk_FEHa78Z9Lo4eKBQpAp4VeilFLYs6YTYbBslZzi9381nbhsSMY19SiiHGoUjTJor87HyXmhQCF3ExFQHVYmCRuTqOnCwQtikBGjqq-7YfBtEhy1i0Po1LKRWIt1x2-172w7jZ7tqu6fu878cAvN33KbIjVi1a085-5ZtvrBfdg88efe97f_HRu59strvHD568-_P73_qtb9y7e_Dnf_FRNWql1KyWc91s_2e_9rXLwf4_f_jn9x88rV1tVwuJQXzYnSM1iBSbsLs4Q0Z3LDkDQoih5DyWHhBFJgCdqiCjmzETeOVhFSKu_Mepkq-CCFJylX0DsUkmItVSx5d5HL_1m7_-0fufnT34BNTqza5CxIlYRfjK1gtIkQMCmBunZK5UgRSEbo7ggYMWJSLXGvRDd0NCMIG6AZ6OPO5VQUg0iaz-_0z9V7BtR5rfiX0mM9dae-_jr7_wtgBUFcp3d7VlG7K7h0PRiEZDRQwpyvGB0oyooEKjedCTQgpJowiFNEO-aUSNxJkmJVqRFLubbFfdVV1VLIuCKZgCcC-uP-dst1ZmfkYPuQ-aEQgEgMC9Z99ztsn8vv__90OkGFv2F9H55IUviliKgTimnsu2UAwhhWYjbw3IECITEQEyz4fBzAxbSbHZy5ibLFC0GzoC4BAosjlCwGGYqZbZ0O_tLw4O5jeuHr94_cphl6rDMo8fnK4fnG0ngeVyrbnWWkWtqFYwDsF2EVZMIUxFHDxRYER1FzP9-EVLECkQeanqYCEFVHfEOlWT2sW-TJmJay4hUHt_TMOwPD1_9ualwOny4f6D06Wz5lIVUEUChzErIJlDnxjdpZohiZqJBAqOQERVhJHMxQGBYt7mg72hasNiBSvqaERYTQMGcjBqfC5Qc0KSqXapdwJv7jBVJkJ0lxpCUGs5BB26DplrkZAiMgF50wESQohRpIQUpUo_dIgQ2lYBbIi9aZ3NhmnMqeuC-2K2EK0hhWbcSik4eJcCNriNOQEghSo1UgC3PnZSJEYmwsiNa24htpqQdZEi--Givzmfv_L89ZvHB1eODuZdaiJqICCmXaWWPvbv4s5miWi2m97vAhZ4Mb-_GOQDeOvJObaC7AUJqx31EXciK0RE2sX3cQcFhYu2ASF5qxe01yOR-U4KBQDgaLtgUBNt4oVymHwXHLL28AEBWmYFAABV2y0fG39_97haH8g9ECH5PHVHs75WUZNqVmvzj5M5AHDL0e4uSAAxEFNo50sDZ0Kn3eof3Y4O9tjbldrVVEzdkWJEIi25TzykFENwVTNxJDUtKo60rVoVxKA6FPPsvtzmZakpMBDlKoCAyKVWBmTC_fmsZ9Za0TFrLVXEHQjNPTAd7c0dQB03uVb1Kq4OVcwQqrTvkCOCGTQ5EQdCpCIGjo0VGIgIIYUAAOrGF9qjyNwOuIwIgAzcFju73xPIqcXx3dzaAtIBKAAHNJCx0NWjntuPAhHcmS8aIw0GBa0i0lDKFyawpv_apficuf100bGFLNtpuz2Adh9BB6ed-aFdlf3dO7eOFvt7iwVw-N_-539HRWI_y2PhyMQ8zLsr1y9rmS5fufTBB3e2q-3lk8Mnrl82pUen5zZNV4-G_cWij4lS_-DO6h-8_fZzjz_1-LXHr14-RAIxB-AL4p4314EJOLhojTEZaCAOH9ujWkOG0A0MDAgt8cPTs6N5PxW9d-f8rTvnz9w4AdeiJRnu7S9SCJusT1w__uj-6vHHrrAhsp0_WO4xP3zw4LXvfDcS1FIC4Sc_85kXn3psO25u3_ro1U--vDxdbcfV1WtXh6F78Oj-45eO3nzj_le__e2nH7t5er5yra5uJoAIwywu9tbrR88_9_LRlZN7j-58_pMvfPOb371-csKzsDhcPLp_5oKx62dpFrOt1tu9rj8920zjZr6YPXXjxmOXrkoev_b1795bbl-5eQ0xonNMiQBiZA4hVxm6lKv0e4vbHz1woOOT42kaq_vpw-UwhKlMfT-__d79v_Af_5VF6C4fz565sf_Zxy53gJdODq4fLojYRAzqdjutixSVe6tNVVMmoqhEohoQQgwpdPOuOzk46rv-aH__hRcfv_H41R98762Xv_ji6mzd9YljJKNStB_ivXsPn37i5rSt79299WOvvuqtoRECmKfAgMCMJgCGKQYi6FIyACZUdVFpazRmREKp4mju5C57s-4Ln3r2qYPB1Nbr9arUrgt9iqWomoXAU9XGPiigJlZEiMGlfvLpp0yBE56vttTxapM327IpNXSxS-H-6UrcTK1oY6PRNNUmD6lmpgrmZkaGiE5MCt5AyxTYxE3M0VSFA3ddvH5y0BEC-6XDxXopV68d9CmRw2a7rW7bcUp9n0s5P1uGFIauc9Wj_Rkz5ZqJ0ANL8fW2aLXUR1WcttkAkEjcHYgIj48Xn33u-hOL-RB5W6b7j5bFLA3RzEMIR10631RHqFWQY621FgFCrSqipUrDIpSc3aFIdXUFB7BAJATgGGNQUL_YXpsBxaBuRmYGp-fnTz9xFZzBKQWuImqAA0-TblZbdHDR1IUQuCoQk7nVYmCViYA8MuVq4NalDoBKrhi4YQAjc1UPGMHUtAYKCpJScnNwQRAchvuPzv_yr_zk_uKwjArI6HrpYDFwYmIDY8K-C8h4erYuDvfPNsUtV3fEUUqtgsi5SBYvDlWqiYmaVAVkNT_fbClQFlXzYehCIHcICC22m3OdsoQUE_FyMzLGqU4IjoAhsKjEGKoIqM5TFyNH5PVmMoCx2naqWfx8vR23uhpHAMxVxNAAHj48jYG1SOjTlHOVIo1abVaknBztffkLr4zT-O1vvPH-rfvbTcGIVbO7IEmg7oP3V-DjfJjFRZrPeqfyxz_zmceuXfl7v_GH6-16Ncp2s-27VHKNMeVcgVOcJUZjNQpRa2m4iWksgaNYUTFE8t2235ox1s1iiA2rQNBmL9BuwmUsMYU2KJJmfkNyVTBTVWZGIrX69CufeHi22dy7zYZmWpWBSfTi1I4YmUWMEQNFdXVw9Aiubtbmv7sVNjdha0RwU0FA5tBQY6AG5hxiO72DmyMaNECiIyAEdrXIhOB88NSrGEPkoCazfuYOjs4xmnnqkrm5W2AKKamjq-7NBjNFoFJrYDK1hk3tUldrjUOnbsjU90OapWk7zRZ7qDL03TCPB4vhpSev3VjMAvPbH9z54YNHH52O62qr5cgJkXyc8ma0Kp5iYsem6wOiEEIWQTcTGWKngKoaY6wlD6k3g1zGLnV5KmIWMO5kx6azvi9FGEJPCSNpFQdgolIVoX7zzW--9NizKfCVk2PJedJiAFo9BHTCRlCpVeLuQGkciYgBqAmfzNzRkUOV6qYUKYsQNen9xMRaqjpUESBkdy3FiZhCKSXGBOgILZQCCVlEqkqfZl6VAlIIagqAIUYO0dQokLvXKl3fh8CBCNyJmdsqCBHcupSkCiDt9SdqguRI5G7qhgwhBjDQWoiQkcA8MKsJGIE7oFkrdQA21Ak5unskZuYUOQSmgCkkdJ_1oU_hytHsU89cPz6cL4aeAzKjqJoaEHEgd0fbbY9bkMPdkXfJmXaJwp1vcZf_gd1x21vw7GNKSyMlXPA9tY2EP_Y67dJBZq1HdZHiu-gHNyWWV3BuwoYL_MvuseEfJYx2L2e9-LoN3_9HeaXdduGiVMAXdI5WxTFHIgdx1yv7i7YqwOiqIuqOhK2WgG0j5SEguM-HwEgMYGbuBnRRP22mKveD-UAN_WeuDhhIVNkBTPdmAzoRkoGLKjbA9lTEcRRV9dq8aEhGVNUbcWKqNk21miOyGjgYErDZ4f6cgRBxs1mp41QFEVOXEDxETkS1-PlUtlMRsWpugEVqFRcxNQMCjrRD6TtGZjV1x5ZoCswIHtABiRxDjIbIwLAzPO-2M4SQmLXd-wgYd2zc3Xi-pXNcETkxvXBtsUjdPHBADAQBqT2Jds3mRvx0AGpshIsr6E7Tho5gQAY7GbDZTpLQHDftI98cdqGpnXKuxcawqZPfev_dl556DmM4e7T6e__on_f9QVqk7WoC9dlifrB30EW-fvVKALt372Hk8PJLN_eH2f0HZwFsNvDl4wOO8Xwj4Pgvv3XrP_1zvzCLsxijuBmgN3EzoLsrGBraznHtuWoXOabIrahr1gaWSGToRMBipyW_8e7tGYeHD5Yf3nr0-OM3nrl2FBHvPDh78_27n_vcCznrchzN8PqVo_dvP7p57ciq5Frv3TmL6GfL87d-8DqpuErqwhNPP_Pyi8-zw9e__9qXXnnpfLk-2F988wdvXDs5-Dv_j__vfJ5q3Lv78Hy2v7c63VgtLuIu1bJyl8HB7N7d-889_1K16sCHR3sfffDwP_-vf-PG9eupT7_2rd_45NXnatFqeu_0jJhX52txqwKnZ0tgPjo-eub6jffff-fWZrlar_a67vLJUVU19b5L7XXRD93Z-QqIzjbb9fL05tWbwHT7_Vsi1s0GSGEa89d_99uvvvzstsh5kRTj_nxexEMIMdD-3uxwPr96aW9_3veJExCiPXq4uv3R_dPVWqoGho8Z_NUspJhLYaQuhlD8v_mHv3_5ZLY_W7TRGTp0KTx48Gg2zDjE99774PLh5eOTvfZe5GJAEAO3wwUoMGFgNvdA7O4lF2ZSRwJyIDNtYu8QbEj8c5_9BJWsYrnUfuDlanuwN2fiWgUAi4g22qOJGoi7W3WzxXx-MPTTeiyiZ5txs82rzWTMVZVTt9psaxVAEvBcxcwb8h8vhmwAiAbgyAnBQc3d0dSYW6YSkTwiOUAARMCnrp-ACYJtNzIbwuXjRRZDRwy4zWLqfdcxoZrNh66WGolODuZjznkSCADgedRtroAYIqvCVKWaF1B3D4EChy88fT0CPVqPH61W69W02mREZGAzWNf6cLlJMWTRmkWqqCgzhS5MpTaVyzAkqWrm0Gw64FK1wbvaGN7NQMCEtBYOKCKIrmY0Y8QwMEGkk8uXGXQRaT1NgDCNEyCO25w4ueRprNN25BTKODGTVwEpZ6crJKy1zmbDVCXnwkyRKYvWXE2l565oQTQ1q7kGDiKOHXEkBCUl1_A_-J_-h89ePqrA5KaoB4vZrE-REMFC4MbsFtV1kY3oMlcMYb0u23FabiZT4C4YeKk2TVVUHaiYcAhMyM2jkgIT51LGkkNIzNym2ufn45iLuFMK6r5cTlVEzMCcmYfUq1kIwURiiOA66zogVpMiulptxTyrrdarqm6u4hS6NNXiBoGx6_vWT91uRidNgbUqCV85OfnVn_vC7_32N7772g81UtYaYugH4hCIMMXu2Scf64_7gKGfdYwCajzBX_tTP_XO7fV767M337uzzXW7mZioioi226wBYJmmEJiB3FRVwAFax2Qn3NULpaeLVHSXqkDu5qoVXMEV0JhDY5CrCQE1tm9IyUWxnYVSArBAAdG6g71LhyfvvfUDa8WtLrXcqau6KwABk6q4GpAbuqm0PTW1DhAiADY-ZJPbuCmgEXqkaO7EvKNatFpRCDtXTYwu1pjsxAEMaqkNcY_MaO2hV41djDHABc-LELsuuYNKDQzMlHOhwCHGQDSkNPRDIxNTgGHoHBwZA7OUkjgRkdccYsw5P_X0U5f2-ptHe32XxP3eanW-ymPW1fnaXM9PN-YwFjN3Dig1Nwa8A5jDNJWWlhOHs2ksJqIqWhFpnCZGBKRSa98nAN2OGyIutYYubPJYpFTNueY2OZ1q3WzLOJaxQoCriq4eZl361DOP_-TLL-0FOjhoSSbkGCBwQzZOeQvmPUdGTD2pKhH0fWIilzqf9a1zB0jqIlaRsYKGxO7KA4-1DilRCFKFIiOxqrR6R0tVYgzN2W1QQwqEbN5qu61IAF0fmYiYYmQyD0TM1BYzgL6zOocAiP3QmflGzmLPZh5TokCODhTGXJAp9YOamRkTM7OLR8aWBQEyCsgdAwJTALYuxhB56KOJoDmrs9V5wqELQ-JZDIv91EKobmCOHKMjmqoUdbUdcmq3g6LW6GXiFpc3twvfF7YS6C6E_-9eBC6I-ADYoJxEoY1pAZAIArVAoxM3tEvz8e6WBo2yj-4EkT5GCTWCfFN9wcfxnV1UHJqhaAcCdVU33V00kFB3e41_J8UEQIxNHOtuSDTjPjQIDVPNIuUCSuqATq0I2_7cgfGC5tkat2KNKQotDMBDHwMSgpdas2Y1I-B5P_QpzfrBFMBBANabvK22KjJmNWIxl51k3IsVMZFaapVJd2idbF7ENqU2p2PJJaW44_C7NuYuIoYQ8phFjAy3xdYiRaWojZOI6DSVhkB13EVm95yrkTkooIgDADE4KjGZu6FPCkXE3BAsIEXGQBADEwIzAiMCVddWtkFHVVW3BuPxJqyX9pO1wGZO-313vOgSExHZTqjQDAHYsE2tgGHghjs7W6NMtWsA4K74YbDrb6u7mqgZwAVpCC7E0rsQETqCG9x_dPdkccAIBPzbX_saiZO5bSQSdikkx2h66fAgMn_w7q1tLi98-umj2d79e6dmxggH89mlw735Yv_DEi_fuPYf_wc_P0ESZGnfTgfkFnBzBGBEUKdd1o3FnZCCWUv8i7Z1qCG7AZyX_M17Dz64vbp0dHL9ykla7L_yqecOFqnrwvsfPHjzdPXTX3hZxjL03fHBEQJEijNOA6eOmcBmQ0zcm3PfzykmMVOV1HWGKIDD_ozc-nl_MMx-dO9uoO6Vz7_4wosvaAjPvPxSv39ptRVOcbXdrNcrkTJOy2dfeOkTL716--zB49cv5U3erjaLvUV2eeXG8Ob3vs3If_nzfyLOhrQ33F1t9q9dHqUeX7782GNPuVHOev_uI6u4Bv3CJz_lZ7mM8uFq-3vfeevDu8uP7p-ePtr2XVfUAPBob7Carx3t7e3tv_f2D5957Ppj1y_VcbMYho7pcNGf3b17cm3vfLl8cDaVSVR9ERIaSHEVUwMS9GoDxcuH-5cP9p9__Nqrrzz19BNXgPmtDx-8-e5Hb390_2yTK5hInXUdEkZKn_jEs_-Tv_Jng4bXvv92N0-5lK4jMDg4Orj34Ufzrhe0b3zn9T5GEwsIKVLHHIAdkQFiAmZ0cHJwUVPrU2xaUCRHcAAlRkQlkJ985cVxGocuKdGqyP3TcTbMZ7OuVGklMSKKzIx4AVxGIxyLPP3kzVrdGHMtjn5-vi4KZ2dLM9ssNyXLbDYjZlFDAjExh4buVYcuxhCjEbaqMCBCIGJkpjK1vLSbOTByIAx-9uhcRMbt2g37IcxmQ1WPSFOeShZGGuYzAOy7eHx8VGoR1WHop7HWUlOHITEg71SOhDnLZhwt4CpPZSy55Oj29Ml-AnzwcP0wjzLCdixO5O5mmiINMVTxFkAb5l0364Z5b-Z1W624iRFQnkRUVdVsN7SiGPIktSg7etWA1KduSHExnzEgcxi3UtWnTa1TXa3Hj370kXhd5elrr7__8HT78NHZvbunm9V26JJoNeP5fJ4WfS05dN12mzEEg9jP57mW7Xaccokcw-5htyKXC7giALfCoXMDfzJoMatGZo-dXJtdvvxjn3k-pXA0T4uuP96b9RwDEQAxUaP5jaWcrsdHm7rKUgwenm3WOWe1qjCJrTbTepRtKVmrI1YRRHIHdRhLZWJTB8SplG0Zz7erTZXTdd4UrUhifrqcAPzB-ahuYykihoCMYarFDZerUZGKynrKsqMxgzk5YXV4eLqsjlUKOA9dAkfNomZFdLPeYuDtctXPO81qYy3T9gufe_7nf_ql__c__t2Hq1ECn49lM07bcbvORQC8m_37f-6XP__Z5z547_adj-7duXvv_N65lPIX_tTP0Cx-58M7Z8sx9H21OlsM6BCpTdBVpspsyFBzSbzD8GuRAFjHycUCts2qh8bhkiaWMnBV1zYFUhHiqCrMvJt47iB74CLYhp6KDqGZvIn4h9_93uPPXl-uSnE3ZEAwM2JuB6Smf0YCQ6vaEojkqi2QQ4iiQkxE7FpbRCekoEXBTU0wsLYIc2OquwA4EFOMu7yMmxtoNUDgGNS9dQCImYnczJApEBNxCNzUrIAcKCBQ7COYlyrz2Z5orbmGQNoCJTvUIs_mszwVDiFxa5BD6sKsH_rAi1l47NLeS49dBad37z58OE73l-N6rMvlxh1yycy8XE2qpu5lqsPQlSZWUCXmls8utYYYSsld6qVWMwkhqam7mVriOI5bihwpGXidKhFjoPPtJnSxHQNrkdTFUmoWz1pKgIh89nCdZmEY0vM3rj1ajYnBVFNKIkaEtda-H5BAnUwVgQyhqeHclCmYWJFSqnDggJxrwcDjdhtDUgdTsxbuQALClta1pqBCMnfd5ayoloqIIhJT50iuGkMAQgeIgWupqYtWFIBSZDdQcyRkZkYyt2GYa1ViZGJ161LchWpc-zRD9GqVAuNukEoxtkNX8JY-IjRgCpRCwDZLSBxCcIcYCMyJIHXcR571cb5IJ0f7-zFcv3oQzDH4LvUP3oDv4NTAFq0U0nZPbSgLrb_cqNZ-MV7CncCrAUpboxR21wbYaWTtgm7oCNRkXBcyMG8R7QvUjzs2Bseuf4DghkTtl-xcTgiEYG4IdIEcbRGSHTXNd25hZEREbNDoi7TSx-qo5vdtiwVHBGQ4WfRsZmZjKVWsxWQdgJDcnBqXKUCXOIbd9oZiEBEDn6qa7yoNTNSn0FFU1Srbru8ChRQiGLa0jJgQ4VSqOShAKdIaq-Bg4GqqpvtDArFIWA2sMYtad4jIG_XePaVwcrAIjsC-HbOYpxTdTERDpINZp8U3YmfLrSAU2b0LOgJQg35yqQLkazEEz6Yt1p9VCFEEqrbWNKl5rVVMApJYUxsiE0l712qG6IblbskWgkgB0BsJdtfMI3SD64ezBTOax9A2dDtl0kXSrEF8qEkV_p2AmbcsZeBGVHA12_UykdR3UNe2DWjxn1b5aHssV28kKDO_de_Wk9ce5xAB6X_zf_zbRNwthlIE3Gd7i_nQX71x9fLJwfmj0824Pbp08MVXn9mebVzEyK8cHx0ezGpBsfDcjUshJAfWBgR3bPdza0UURXMnYCRwB237JpQUEzOZN59Pw376Otc7q9Pz8-na4f7j1_YO9xehQzVaDDhEfni-fjSWz79wnUPoUgpMY56W6-nxa8cf3j-_ejIg2HI1Llfjyd7-j-4_fPetd22qUjKhPvnM8y-89Lx7fv_Rg0898fim6D7zv_nmt3_uC68-XI9oMBpvz5bzbnZpfvmj996o27XVGrp47bkXHnvy-pWTGz_84esHV2bXj28ut-sU-eBgMU1y_9HZC889mfqZZvnWOz_8V7_3td_43X_zL37n97773W__zld-Lwst5ovf-N3f_PZb96blo--__a4hf3j7ARPeuXffQqg596lbj-N6Wx-dnR-fXN6WyoEk6-Hh8fvvf_j444_fv3_v4cNT7ruh662W4ys3nrp-7Qevff8P7j3SKntD6kMYutCEGMhIuEv0emtDOZraXp-uXNrrZwMlfvv23bt3T--dnYtZiAEQEYhjePLmDQW__eFtN0mpd8IU8ezhg6ODvfc-uLdcLX_8S58gYEQMROBobhiowZuqWYisagDW3mQCBWwBNQR3DYx9zz_9yvPoMk3lVOp2zASoaF2IbX-FSJspYwwdx81UXS10bG5qdvPkcJHS-XKTrZ6vcurjlP18tY4pumMpNcWUOASivRjXU21vEA3CG2IQdzE1MEaIzBRIzbXU3e6Udq9cNwe3gOHKlb3HDveH1Gerw25yBdO4raLmYES11FKlaHEHQoqJ9xaJEQB9yhUVl-fbqYqAu2PNhWNq4HoGjyE89-S1eWQ1e__eqag6oAAY4JgrMXOgUnZ45cCRIqfjTsYqpWZTUyPa_XxVlZwUbNZ1U63t46QWQXCO3A8DOIjpYlgAIxEZeq25SqnjqKrjVIngaJgjgbqoaBx6DpSLFNHF3sKtqiA5bsu2G_rtdktMkTjnKpoRebvaphSrGCCWqq7WMM-NBtthcvVq4g4UQkB3Ra7dm--__uMvvjqgz7tu3FbuEMxTR2RCZNtal-tt0YJdPJ9km-tqNaqZuSu4IFZ1IqpFRW29GZs-SMT6vq9VqlQObG6Nc21VYwzuPo1ZDIxsrNaEM3fvLw1M1B3Q3Dpma1dH2BH83H1vNiMCd3h4vs7m620WM61qal0XgGzaFoqkZq6euhgDT-MYASLyNNU_8xd_aav5n_6zr1JSJTfR9XJdxgqAN2_e_MLnP_9jLz1zenb6X_293_zo9hIDlml64flnx9P687_42b__j77y2g8_LCqrzVaLEEA3DGcPzwGpmMxmSauDu6oCOBAUrY0QZ6DeaLCqVivtyr4OasSkuXIXGxcckRBcRJDQCFTV3biVx8GgfYQzA9pO7uZ-dvvOl__kT7_1b7-Xc46hB0etQkSuigBqHjoGdRVlDsSkImiOHFTVwZrsGsDIjJnBHInhouxGFAhJS-YQAHx3eHLXKtx1pmIqSEwh1CohRVflkxe_6E6mZqqxT0QUQgJwKbZ3fCBVEClFJiKV5hfwFCMScSBRpUC11tR1IXAe6_7hviOwAyJ2kYauA4S9_b1E1vfw4y-9sN_3pdbvvvkB9PHhWT47W-bayr0w5QqAuRQIVIowoanXWlsxFEGLCOwCTQ7mfUqilnMd-s4B1ZUQuQu5ZHdAMBHlFKUKM5epMrWKBXIgN1OtgdODR-v0dP_RDz9850e3r964DByeuXzl0uH-tN0CSKlGIbTxEiJNU0ldFHWMZGX3Q3KRYUhjUfQ2oZQYYsmFE-dNXsznpVZkrGPtUwfuiLy78zXiVBO1ekuFIjOoGBM1q54TYuP9tRObSeg6cYspqBnHiIgdRyKIKYnU-XxmVTgwsKpYSqklnfvAajbr-zLlPvXuu-osIXIACqzoqQtAF2F7s0TRwPf3Z-oWmNAdVPtZFwLHGBZ7w5WjxdWj-f4sIQAHdvMQAsAumPRxqbIFQhCp1Sfb20GDAMMuxQ8XMWv_o05uaxK0_CXudK1N69uO5u5GOzR-i-7vzF0fFwku2satrmZ44f3iNsH1j5sHcIEeBWs1edwtA1RbssKZ2MF21w13ZvoYD2pmDA1n024piCaHQ0eI5qLatOkeAiHRjjgBAGZMwBfKWgUrUlQN220ayZsOOSBl6yOjQez7QMy4-1Oom5m266KZ7woqZk7tJuYEdtDHeYoDIzEH5rHh39rc2wGImICIkP1kf8FAYJCnUUyZeTEfpqLkGEIwwtUmb0oxp6pe1QDQzFPiba5G0EBDDYCqBojQ4KJEiMSl1NBQBmC7PiuCVHUmtZaM2pHW3NzVAwd1jdTQar57LiASAre6FRgjVqv7Afq4YxghtXfDnbQbEYB2Of72NGlY2N1dtK2iiHdPzQZi29XNITCpauP9AO5WNEjkasTB0dzs_vlDTv3h_IBT9_DR2X_5f_-1-eGRhVg1p37Qmm8-8diVK5dX5-e3bt934p_93Is61lJgttdzl65ePnhw7_zKY48hx3bLbIE-dW2IFwRvEhlERvD2cdJgSQouIl2MZuDqTu4Ao8mds9VqaYcH8xsH82HoEgctngtsprw366rQa2998JlPPStF0LFLEdWq-P3V-rlrJ-_ffnh01AHIg836bLm5Mj_6_ge379x6lKd1zmNAPbl5_Wd_-suB8XyTn7h8fLbNB0z_r9_4_T_7Cz-xHKdplRezxemd--tH55b99O77pYz9LOwdLO5P00svvSKTfuFLn_97f_fX_syf-dOuddrmS5cvHx4dfucHb33xc6_qlDnC6nz6yu9-bY7A2wIeSPW0Tr_8iz_3xONP_PJnP3P7ow9ffu6Z0ezmpat__5_8i7u3H6zuP1yL9peO85jfff-j44P909Pzfja__-BB7MLZ2dnVK9fv3b-32Uy5ooPnTQ59-P0__Nav_NJPP33l0tNHx1_54Rt3HizT0CNjR2QGIopOLferaqrq5oweCAMTEZ3szQ7ms-NL-8h0f3l--97pg_P1fN4DICMcHx8tDg_v3L13__6j44M9NSiiIaXlJj88XWKMTz72uINHhkikLV7IQITmAHqhfjcnojaabvodBKh5-tInnucLA9eNg71cahWLzOCYAlfVIpU5mGNtbJkA4GAiT1-_sh_TWHXM2yKiiqHvt2MBQjVgBDFDwlLrdqpjlapK2LzpHtrLy1BcATzG1N51DYyAVJQDMTMyiJmCJyZHv3Syd7yYdTHsNrSqUgVDGHMmDrXKlEuuueu7IcQ0j3m5Ptqbm-B6s-67Luei4KVIPxvakMIBBVxFOcWA-MTx3nYrGv3e6ZYYt1N15HGsFGCaBDmsx5EIUgqJuZQ6nWcwH7OsNjkwmZmoiNoF7VA5YC6iKlVKK1YiQUgMbqWWosXMipVxO90_W7GRmABzqeX-3Yer1fnBleP1cuuMjx4u1SFrCQGW69V2LCl1Q0zbTXZTJlbV2CUEz0VEKgBWqbN5v92WGEmqqIGpIIdxzDGgghKSEzhTrerdXArGuv2zv_QzeyF2ke_ce9DNB91O3YxcbV3r-WoDoEa8LXK2mVbrqYggwnrMVbWKpxDIrVQtpgCgohQopWTutVQASDES0tB1iyEc7vUDh1qLOW3GsVSrZrnao_MNOhhS6nizLeYWYxADIlIHKwWZq9r1o0N1C4zbUseprNejKohrdROzzboogplO2xJDaAmcUmW9HvcOZ3_8L_3MD37_nd___e8PfTjblCpgqil2P_Mzn_3SJ5--fLz__tvvffs7r7373j2jsH-8N9ubD_N-6OTP_OxPXbk-_4f_7OtuNYuWaXLzkkVrZo7r7YbBIkUAk2qiZlKJo6jlks0crKk5EIhVqzfMuBsTWzN-EHtV991smiLpVGJKJhXMqEUbDIDJfXdeNzEz7fuExETp6qWbt370biBGQkRXE0RkZhHDgNQQPc383TBDjduHQIFdJYbk7RPqQtUMYKJGfIGLVHUzAiQOqtI-7ZrkyMDBjGJUkRiYL730Y8gREdAt9txkmvt7B3WqxLueZpMnD_28VHGE1HVIpG5IJKIcY-AQAN0QInLktpsA8pQiM58c7x3sd89cu_LJZ5_Qaj9458PbZyvn3qLdf7AsORPRejkaGnVp2mRRcTfmYKAqpmpuxk65VopxGrdd6AISmJdcBYWIzUxqgXbsdXXzWTdTk5prP8xU1NAAqAsLRGWIIQajxp-EW-88XIsUth---9FU7GB_sd-Hx29cWS_XFRzJTRHNuj6oKJkXAww7IMsicVEvqg1RjuCl1FnfT1NxbSW-IGho3urbzMQcRI2IrBYmihREKkc2s77rSy4cggP0caFewSEwlCLz_T0CEGmnXu-7vvU7UoxeNXWB2hQ8EKCrqFajjsC9j4OIEmFgUpVu6MwtpURIIQQHT6lr7UYmptaucghEfWBims06QupiiMyRabFIQ0wd4snR_NJ-d_l4vw-xiwGgNSPBrY2isKU-CJyQWyCHmKBRjRuAExyQCJEoNOHWbrjvoNasUxeqiUZ-NADEJg6jXUJo99y_EHpdUH0-XgoA-sXYfhf9BjcEN9iJOGG3uGAiFWuw_wvv2O4LM7Y7ttFF7MccoBnHCBj54zKygxHg0HV7KbjKKFNMCbyx3iQF5qYRgMZrbEEVLFWqqTuourg5ACGbgZig6tHhPoe427A1iD26aVUTIqxVtQry7mGLiaMG8IM-dg0XZVjUxqJbUSQ2IDUDbw46BPfA0GHYXwxkICoQsPE812M1V-aAjOttXa2nrFBEm0K-YbOLSAxhqgqIVZVwZ4gmpNiOy8S1CBHv_rCEoY3rFaoDAQbabXPM2zf_ohXT_gXAHNzwwtZKu9COIyOCyJWj_S6E3bpkd-vzHfCpdWKhLcAaV80uKP6AiKatUoiI6OpIbI0OhKi7EvAFshYB3JEafhjczZ1u37t18_INpkhE__p3vvoH3_j28dXjImZVUt8dnFw-OVm42kc_-rCC_OKXXz3oEyHvn8z2Dg7yduxTePz6TWlPweqEO8QwgBExEwFAe6qbm4O1Sx0yk9kuSLfzJIEAPjo9e_vBo-P57PJen5iIYgippexKrZGRAv3BH_7gE88_OZ_H9fmm6ztGc4Ot2Ef5_OUrJ3cePZrt9Xt9-PBsWXM-3Dt8-9bd9354u67Ptqt119Ezn3juj_3UT9Sa3_vo9NLhLCEdduFf_5s__JVf-PL5avv62-_cvHzljdfe2GzWV46P37_1Ts7TbBgU9eD4ytHRCUH5yU9_5ruvfadHuHTtiXE8nw17h0d7P_rww2vXTwJ1i4NhufX59cfG1WZ5bzxZLDhIPYdf-rO_sl5vc5Ws4fjyfojDyf7et7_7hlR-7Ce-8K2vfP39N976xje-eXZ69sab733nrTc_-fKLD-48cDAMpEaOnBaLWx-8l_rFdrsC9Drmp59_dj7bSz184vrTHPCND249WOX9o1liYiAHDyFUdcR2Jp5AQVwTBzVQUQJ281k_O5zPjw7nZ-vV-x99dPfBIwPr5_PFbHbtsasq9uDBgzsPHh4dHLhrtfD-B7dPp-VnPvlyaHBAMACIXevJOHn7dHZkJoCmb--6VKV2iQnx-tHBtZN5znW5nSiguWy20oSYxA11gNttaVRTETcTVX_2icuH80VE36ymba3VXAyWyw0ErsWJKVeJIZmJAwYODl7VmLiIgO96-exYawVDRupCUlVVaQ2bhmA2beg0AgAKCFo_-cqz88ARAcjZtbUIxlzEoIieLlcxhtl8FhBrrVrK8cneEMJ2vRVTTiFnKWZEXFXOTpeAYbPdpr7LWYnw-tVjMqpVVmN5cHa-zVWMjDCXEpkMfLOdxqmAUzVT8FqkvbSmXEXqDtmGaO4xBkAPTLWooXKKjcqACDJmxMBDAOftOudxm9dTzhLRGRzQSi2EHIIvz7bjtvTdbO9gAUh5u6lFN5vRHYrDcrkqXmapy0VjIESoUsGMmV3UayHE5XIdAhGxmPEOTSauZmJIpObFHUIEw5D25v3wt_4Xf-mJw6OuC46YQuoDdcHnqdtMeV3GLmLf9-uxbKueryZ1F_HAnFIqYlWtfYoE5rFICjhbDJF53gcH3I4jB0p9x4wNL8FIpmoOYhpC2I4TIi03kzQxI0MfaMq6W9Ei7TTkBGo-dDFrncWIDEXs9v0zdR-zrNeZCNfrsYlXTJXB83asWfou1E359E-98PmXb_7rf_yd119_L87jwcH-tRsnf-5P_-xzN05Orh5_cPfe17_13nsf3D1bbnM1D4EHHmbdo3v3h26A9eZX_-RP3P7g_N---f5UpeQybScH0JzNfX2-5ciBU92Mi0Vfq2jNDlbzZOCIqDUToeRi5iUXUHPbFcFNxV1Dim4SkNQUAekivECApRYOgULYdRAdsW8GTydAMHV0JJvEnvn0y29_79uIydQRQc2YiRkdFKQNF2nXQnFFoECoVQCdMJABuDhaCxZgCBctOQsU3JwpmlsLRBNHc1WpSIzEVoXbJSEmN0N3PnnxiybQdaEZL2MIDqgiFKgx-5iIiM08EMS-GzdTSL26dX1fpMQUTSXGxCkgI4b28YUipev7LqYUOSA_fvXox195bn_oTpfj6x98uM2WzU8frYvqetyCUy1VAZlJTdUsMNUigbmKILqbNyV6k4DEkFSrO8aYqqoUTSmZVQfvQlL3SSo6ELKQI0ZwZSIDNyvt2x1CMHDRXddudVoOLi0M8mq1vnP34SeeeYIRbl46ev6Jmz947V0n06auMiAAGriIlmKAodRaa1VwVwd1tTY4hBhTqTnG5Kp9CqUW5ADmWjV1syIVwQlQxWbDrFRBQlNLHNQEzJkCBeTAKTWqLxFxCh2DcSAiLqXuDweERuhMiICBqaqLWuo6EA8xEIdaJMVou3lGgNZ-alPVQMwoYkTATCbWdSHGICrDrGuEDXAYUhq6EBAZse_CfK8PBPMYOsZLe4tLx_vNZAHWjFq4ixL5Lu7TlgxE5K7t0II7WPvHVidoQe1WFN5N7lv7FnE33LePD_cXyXvfXd7aOb3Vfxvjv4WILqq9BB_nhHxXqSTaRcR3sbXWLXZnItuRhaBFs9q-KDCZ_1GjANrZcPcFyN3oIuPUtjqzFDskMiPmQNSlGJgJkUMwbTeS9rddosUAAGjXKXcHwirg5EgwcJwPAyg0OKa3dBOCmhGRqInobqAuSpEN7PLBvMfARGruRKttPh-LOkZOjtR8k8AErioKaoy-SF2MQVWRwAw2G9lmFTUENsDNWNajbIs4k6ibec7ZEXL1LNosu9CuNMxmYKZijZtm7s4c2nkaCZk4ERLQENmBI2Iibjkwhd1P313buN8Jmg-FGjNq1_9u4B5Fwn7oh45m3DQVtEttuDm62Y7247ojOUCj9rjtdEstR-TWLh66a5nsgpON-2Y7LCxceEcaJBDNbbVZxa5fdAsKoWj9P_yf_wt1Jw6ny818b57mewfHB0dHB7c-eKhmf_FP_-Rh34Hi_vEhhnT3zvmN6ydXLx2XHdhYEazN-omwlUnoAmfl4GqGxDtJlKOqV1GKIRJW87PN-NHdh4L4wrWTvS66aQwxdqkBU3PVMU9SbbnOqvDc01dy9U0ui1nHRAxQqj88O3vx5sm9h8uU0rwPD_L6fKqXj45_8MGdB7fvBahZpE8eUvjVX_ll0HK0t3__0cMOA2D8wRvvfv6zn1St03Zz49IVKXm-6J589sXf_-rvr1ZLJxCU27cf_Kn_7n_79q2Pnnn8iVc-88rXv_6HP_9TP_XhnTt9SoGDynZ9unz6qaeBsBidb6e7H9zLq41vN13XpeuXf-qnfuzhg9NrN65eOzhcjuuhi8u1razeurO89-G9X_zFn33r-6-Vyf_G__x_dDjMbt_66Pd-53dPV-OrX_r8w7v31-vtZhyJ-PXX357N-nG9FFXq4jf_8Ntf_pnPknEiu3pyfPVo_-75g3d-9HBxMBvSTFqc1BuJSxCBI2-m3O6Su526e9wpMOHwcH9vsR_2---9--Ht2_fWkxzuz65dPXr8sRvnZ6fnp2drKd384I3vv335ZMEQHn_sOqGnQJEQVERaw7zhbpECBsJZH5kpBBq6NOv75cPVy89cMkNR62e83WxMMYsyU63SxThOtZikmKZcur6vOfdD94mnrrWreCl2f7niGClGAHPg8_MNxwDIKjJNU4h8sD9UgfWYAZADWhvTuLm7ilSx0AUwR5cpF0JKKeqO1UvM7M2bg0YBnz0-euLyntWqVtx0zAWZzbwauNPZ2arvY4yx1U1NNQae99HNRVVd1SxGih074NnZ2gymkmPqmcnRI-NRP2NicUGiKZdRtJZKwSPH9VRW6yyitaq5UWAkNFU1r2J5nAhB1KsIIV7oILF1kkTNwVOI01gwMPWxitUi5jhup2paWjvLTEQJowO6aRc6NS1luvfRvW3Ox0f7XT_vAp-ejVMtTIiE41TcPXTkZoAYKTCSmMYYTM0BjcFURQ2Ju9CjqIoioJqYGjJB7GrNKfTz4WAC-R_-d36BsgXvIpGTxx6YQcSW46pPiTiFSOfb8XyTp-Z4EkOC_RSbKF7FFDx13D4rKRADmAIybtZbZkrEgXF_NkRCNHR3czVkJDhdZjE_32REaqLW0_UkohwZmANRVTEzpPa5ZF30k8MDNHi02pRJEGi1GrWIieYxn5-PII7ApQqqfuEXP3ey6Bdd_8Hb52-9fvfy9eMnXrj53_vTX-iiny_Hb3zrB3_wjXfe-9Hdh_fWUtVjNGQHVFUTq-498snR_Od_7rNPXD3817_3-v3N6uHDlWhdn62AqJaMFHIuKobgGELJEwcWE0DXqZI7tyW21BBZ1EBrYgJVaHLrWhHMxTiwm7gBIATmljo1U0RQc4zRTdwBd-ZONAerE_dDQCDGUuzqk0_deustxwABCdFU2-iqpZ8JUUpBQmIuuRITYe9uxGwqHJJrOzGqt1aCK4Xg2j5CgqO18xHswjOIxPgxLcWMQ6eise_NlMC8GyITxxj6rmtZk9h3MYXtdtP1A2ITB6A4lqKzeS-SmclEIgbJxd1jTKWURlgHAFWdz_dcrZq6e4zhxqWTRd-VUleSjRLFWEotUyag1M2BGGPMua63GZlV1IByqVrFTUVUXE_XawWsRRFwM66daDVNZfe6sQAABiJS24pDRMmrWa5FtTKEWtqyx0R0NY7rcRS1MlZR365GgfrWD-8_OLf9a5c84N___33l1r1NLsbuP_vlz3Wp6_vgpjHQYtHv96kPgckVctfxbhbCKFKZKJdaDdQNOZhJdWEC4uCAiu6BikxdbPtkphDGOoWOY2AObGAppRgjEpgqqBJiSp2KosOUx2E2R4dAHGIoNsbIoG4GGFEcUheZUWUa-giGnRMoAhhH7vrEzOwQQwjIaD7EQYsMfd9G932f3AwZYuLElFJIkS4dLYZA-32_WPR7QxyY92I67LvLl_YuH82PDxegRswhMDCBNz8ugkPkgERMxBzAd7WABqUys3Y7bqKwxtJvg1UA-yPCPjY4LoB7cyBelDsb7bDpMBuEy5pVaqcDM0AEJgIkcCcEd2fcfVoTYnvdKoBpW8sYfSz6bXN8RNtBUQHRwI2RiHYmrdYA3h36zS9Kyw1LBIw4zGchRAqxHd-8agNq5KLmrrbTUBmCqhZRbarBZqqCYNaOGGBmQ5dAdy8oM0U3R1cTR1Bzrda61yqOaHl1fjj0QTBQyNUm89Nx2tYaYirFxrE0bDAjolsKfLTXDZEjh-V2e7bcbMcMIEVlKzqKVjUD3JaSazVQAc-5FlUx4MBmvps3KIC0ASIBuKi6oVrjAjVpMiHBReDLc1UHq2Rd9MgArERg7rRjQTEwAQOAiygReyPfowPhzuLj7oaOqGjdkFpDpmWv2jF650xFRqeW4Lrgu5o7uBkCmbmImJk0pYIhIAZqaR9HRNlhnj7uqF-EkEDRYLnc7M8OShVAfuft2_cePBpmB1WdjCHMU0xXr15an2_Wq-lXf-XH9kI3S_HGk1ceni0fPjq7cXXvqWuXGl6aCJrownXXXsC2pTA3sx3DipERA7fLuzlh6hIDrDbTa7duP9qublw9eObmcdcxOIeUKBKiIkNVK7W6095s8Y3X3nvxpceK-JTL0d4MwVMgJu46WgQKHGIKy5y9Y8LkvKEhzHumgfjSYUWdz7rT0zUlruqE4e7D0xRDcf3ip5_90e17s264f-fBoktPPfP4pcP54eWjsNhHHnLxLBRT_8SNqyezRcmrxy5fC5F-72tfOd47enj6oI_hycdufvMbr-8d7VOgGOlwPpT1BlAFaLst1w5nWu38fCV1uyznXZf29hf37tx55ZOfCjFVk_U6b0sep2IhbcF_9d_7927cfOKlF579L_6zv62e5v3R7Vu3MVDXxYe3Prpy_XqZyue--Om9Pv2Xf_f_E7s5BB_H1cE8_exnX3r-uWsffnjnW6-_kVUUABFyLu7EIUq1vuvUYcplnHKuxd1zzaYaAqt4CHGg7pPPPff8s0-ut6s_-MPXfvO3vn26Ka---vmnn3t-L-199O67s-jM-LXf_-refB4ACAMCDF3oKCSkWepiIGZkgr6PzMAMfcTLh8Mi4QtPHhugia63mRxj6Ks4IlW3vcXg4CFyCKkNknKZUh-vHx9qgdNHKwD04Cl1opqncbku1V3NRKuIcAiLvXmK3ZS1FgntXgjGhIGBQ5uB4DAM1bSLLOZ933FkMQlEoY_YTC-OiWx_Tj_zyWc_-_wNLDUi1FqXm20RocBAodGNkKgbBncb-l7NN9PYd7ENdWbzIcWYiMpUp3XJU5ktZmnoiMN22o6bLYFdO1kQSdUq7svtGEI3DH3swzQWIEYkYIRAGLGo5aIOLlVdtUy5vaepWltUM8Ms9hxCSBHd2T1vxuXZspZapeYs62lUlzxtTLOpAJBBUIdRdaojuJDjVLKa57GKyYN7D771ne-_8c67AnZ86UAhdIw9cFBwr9N2zFNRFTMppma-XG2cUNxUjdoRJReRUaECNviTNmh1GbeSJXpYn58f2Bll7SgZgKKCW2ROMSH44eFsPqRa6-ly42BqUktFInVn4rNcxDwkTkNg5imbA3EMUmQ-9CWXSDzr-z4EMD-YDRGRkZlbTRHmQ2dI3dBNpjFyKapSx1yktNsUaNUqgsBuligkooDABfoUxYFCZOapltmsu3Tt-KnnH_upn_z0L__xz375J1989vnLNx7bu_nU5W_--td_-zf_bQr6pc8_9yu_8NmTK8M3v_Xm__J_92v_4F--9vo7997_4FGdSh5LVYHAgF5rMfBxuUQyN-xTN9-fX798jALbHuPe0C1meSqzvmuAiVoqcXBX1VLLqK5QwUUkFwAUKaJiauSuIia1-aSxAfHNsLUiwEzEkRTc0cVETauJqVJgdHcVVRO3kCIDBsJAzN28pSRqKZ_63KeX778rAq4KiKZOSAiE4LE1wqtQ4EbgjJHdTHR0Bvf2ZCk7SERoyQsjIHRwV6llJ0dCNxczMakt6xxi3PksDVwrmJtWdwhIhqClSAgYu6RjZvI65b39hVapZTJwZAaz5uBxQFdlZGZwCrUURyg1hxhMNIUAhJyiiAyzJKocutV6_fjJUYpJpLz53m1GMvTT0zNxUPdxPYWUDBkDqygzM_O4nQAtl9zFOGYBQkCUUkIkE5iqDB2YuUoBB1VbrjexC1pkmvKQYoxptdwsDvciBqml6wckmpqXlwMjj9uJCXuMOmngIJLBYT2F775--5Vnr8umOnuuPqRwaX_x4gs333v_0ZK2p6fnefJhGPb6zqrkYsUUI4NYFxBCqGZdH1Vrl1KKYbutHHi5yanvyjjFwKrOjCXXvuumPHYxTiV3XXJ1YkAipuBq4paYwcHNOVHfJwYwQJGSUl9qDiFYtdgHMXNCA3bSLqUIpla0SbzJZvOotSJFKRrYmSKoMbKDI1nqAoNRYCIE8TiERT9kyQzQz4bFvCPzjmno6dLJwfLREsCP97tIFNkP9_sYnBmR1LSNr6A1aYkJTOHjs9NOo-vEBAjeaurYnPb474Twyc3bLHmX-29nMLwo-sLuP8KFxxHRiaChP93RYWfWMgdXb8ETcGAgb5x_orYMaQ-0VQ64VfXBrUVvzbxNid1VjVvgx40aYrJRcsHBHRkJ0NRaX9kRCLyKkou0GjQyM4Fh1aoNk9m2Fr7zGLQ3l4aaaesIQNRqzORg0bwfOjQGdHQjRnevpaipmXIMMYUQeJwKmgHCpYMFE4tjLtP5WNWhqiFFAzJAVzVVAAhMB3sDuAVRQZoAisBmPZrbXunMcSzaCBxTEVVFYsmVHKupEdZ2rbddJkrQIhERiaiai1r75rqjqhGhiiBDC_kjEBCouYqnyIigYhCcAqi0kA6YGzn5LurfbJjq1JocSERuBoGkag14uhxn-zMCNHOkBnFqUS9yg12sHlFdkRCd3FvfV9smQW23ibJGom6XR2zRtfYsQ1V1bLed6O6qtik5zfuPuUa_9QdfQYqBu6Ijc8CAJ1ePQ8Xx0fi_-h__qRTdXaX6O-_cO9vIJ1648eTVg82YNSuHXfyjgeGZuAmSVc0cWhGZdouq3RSTCTHwuMofPVwz6ZOXTg4XXVDX6kAcE7XvIAJWkaqqCvNZ95tf__7Pf-klhPjgwfls0ROhtXEeIhmSRgo8j8PdMfepO5ztj6vLV48vzwfWitv1ZAWmnElPQx-nrapImYobTi7PPfXEP_it3_3Lv_Jz9x6dpTlf48P1-tHlw-6Jm1fOProtRQJRv989_NGHl4_3Z8gPPrzz-GM3v_Jbv_1X_-p___79D_sUHr9242C_mx8Np2ePvNY5J0blltMislwNlBg-_PDWi489_r03fvj0M09QiEBkgG74nQ9_EEO_XJ9_dO_uybWrb7zz_gufevmxJ659_uzR7_3ub42r8mf__J9-7c3XIvFqmu7duq-Tru_nvfni9O6j_-c_-5d_8Zd_poskOsUcXrx5Zbxy5Wvf_e5333jz5pUbVy4d9CFUs6rGFNrbi4Mroop6RwAgUtkJHZkhQXATdbx8-TIRfHDno6989fuXLx088-zNvWuXD69eO3t4fvOJ67_95ld_8MbbT1w9CWQUiBAwSIcE5C4ErofHe3USVR26LlcFcw60ONjbjJXEuiEQQepitgrgLqFjquZAUIvE1G_HFSnNU78_G5bn671ZD2jr5RbUxLW1p8bNRCGIeIosLghh6NN2GsG173mcFHwHUQiRXcEJSymIts0ldLHBStRATUNAIADSmIzNfuVLn_FxaqwRYBXTcSyzxaDqADCf9dtcZ_MhEIYQEb1KXSzmXdd1xOrVVVKIxO0cz2frbZ_S0PeLoVc0E1OFcVtPi2Dk7WbKWQOHo9kMFCmE800GtyHF5umOhMQM6iKiYlZrGsLybGNuIkqMFLpRq4MhYgq8yVP7VOKL3bir1MKXeXE3qk1TRCK2itRDcq1QCoYk4rkoIrJDAKq5SH30_fPTxdHRwbxXw9nxnLhbL5eR1ZAsW2FX00DU8q-RSSZTqwSALqVqQ6kCcaSA5EjK5FVxLHrr1t3_6G_9JVoDOoIWAFUtah2qxw6VudYKXEsp5-uNGRDxlEuMRAi7jyDxGNnFK3hCqFWuXjrY63sAzLWkiJG5T10fY8cI6FpFTcF9LFqr5yxMQazu2lschj4atiq77R8cr1fLFJOTb8f60tM3TxYzMAe148VgasMscAwHh7N75-X733nv7mobsDMzAhlXZ9N6-nN_6Zet1r_7a1-Z9ahepsmReifYbqcxayTgmBCwD8m0nC-3qY_93iBihPV0zH_95__4w3ubJ44O2HV7PlYzCGSO47YAhinXaZsJipHVXOIwDBwlGyAEAqktc2WRQ9HiJuggpZorIYE7th29GranvRswurYsMGoV4tASuURkVVQLOyMRO6qag0IMVvAzr3zyv_mv_mtveslaASkEVhGgICrgDkxWK3Fo83QHBSckBgdHa6KqlmhtxAsIbCbEbKbEWLNSiI5GCGCGriqKFICIQrBSAQHcVDFGom7ozRyJTCHnChce1yo1xBg4yKQABgrm1tLGDl5FtM3ZUgwxTLnUXFNMeVsYAxIXFa1SpYooB5RSGOn2nYe3T-9H9j5SFRWXmGLfJzCdtlt3cFFQaF4xRsxjIQhmpqUwURUDJammaqXWAC5ZgchMxQ0QI5OKVTVXi5GtqpYiZmMtABgjl7oLB0g1EROHxmRURSNYn6-A8M1379ZAD8-X88V8tR2XZ2fv_PDDXDY5F3R3dnFzxZ7jfmJS3N_rAoOq9imBYeCgqiIOSBwCAgB7DNyFyI7oRoipSyI1xkQMMfGQIiJ0IRAhpwiMkZmJ3b3ruzrm1EUDS11wAEALMTJiN4sO0KWO3NWKVDHUGBgVnbxSJWYwQmYki4GZW8DAKXCM7KoMaAboxoQxhsSxSO1C6FLqY-xjXHTp2qXDK_tzzPWxK8f7PNy4dPzYlcOrh3v7Q1qebVTFrZVhdpbSnXmOCQCYuCUXdpUAc5Fdur8pbxsFi3Yz9B2qpckBWu77Y2fTztKoLXvTmEKwS4b4roSL0GR1uxfFzhSs_rESGJq5ZnfShl2vYKcda1kga5N-dzfYycVaUMh2Hdcd62j3IefeZrSALZlNfcAI3u4ggI7kYiIqDk4X9b52-m-6aWt6V0NxbEEnZxSywH5wuG_VUNVdKICjuwtg-xVAyE4gKogOqDH04AGAl5vxfKpTlaIGDmrtxY-OyIGIIHKIblR9W2xUy8XHKmPRMcs6y_lUC-BUfZ2rORjQVOqYGy-7Eee1esMmtJYyq0OttQVWAnFgTsSEMPRxCFHVXFzMHCmraSNeAaharuKOql6qEiG4o0NARAYiZCYgSA3qAWiqkRHV2-UtBA4A66kiu6l-3P-m9lTDluP13XOpeQDQLwJljtSQoKbmqu1OBtKukbjDuLk3AuPuDqqmDmaOy_XZ3mIfHFNMeTt-5ff-MA39ZjxnwkKaAh32_ORR95_8R3_-cJYis5i_9sMPqsOXPv_CleO9aSpuEFIwE3RgJHJgYjXbfd1mRNi9fAIiOBi5o9sk9s7btz94tHrs0vyxGyfXjmZoO9MFERBqwwmUKrlqruZIv_tv3_ziZ54fAc_PVqNWDk1b3WRzzu49EQkEo5xrj_0AMeXQAw4eUzDTPGMKnIpWRlxttuJ-cnB4fHi4t7-4dHTw4Z37lGIuMuV8evqIxPN43g8pdimkdPnKDUb97jdfu3Hz6vdf_87J0cGzzz73ow_vRKKTw8M79-_udYvF3vzNf_v9aavvvfMjdip59EAZYEK88_A0hu7Jy0flfJPHcX9vxkAVTUW7yMyYH2zjvOPE3_zBOxLDy888cefWvTsf3f0Tv_onF4vZ8sHDOx9--NwzL169cvmZ557ent_bnD16563v373_0dWblz_6t9_8F7_5lTEDcXLwaTsy2k_-2KeffvrJH777zle_9s0tGCC6UlGbxKpBI6hMZtuxTEWmUsdSN1OuomZKhITgCNXs-pUrL33u6dksvfH6O_funYfF8Es_-RP_6h_--uUr-7_7u7-VYowRu64j5D7Ehq06Ohzmiz469JH25wM0LFF7l5Y2qHNT9dYNQULiPoZNdSmlWVZynVLfIUGXgpszB2ZerrZSVdwc0IiKVCBoSblcJkTsYjBVNzTcDUYuvIaAimYwlWJoTKRgpm7updQ81RbUNNCO9drh7OdffZHL1BGZKzLWIujQpZjHnHM1gPUmpxSx1fMDrtebksUcusBVxMVKUQM0AuxSRVSkbc7nq_VWZCo2iYr72TafbsbT5bTclrP19sFq_WC1mqQW0ZKruE1atpspQgIiF19vRqTggBzZskVGRkwxomPXxRhYVEWtqGlDT4C7mmdxVapec3lQV6q1AuQy9sTuHglJKPJMqjIGbgcRkVwyYgQDdVufLe_cunP3zoP333lvqps077puHiC4NroObjcjEI2bydQYEAFNtFZ3ZBPP21xKASJTKLl0pAlgb8AvP3f5C198nsAdnRmZaOhSakMNhG0u5-utaKkuFHCcCiB0826-NyNCCujmUqtOtS2dAwEx789n7hAjI8CsT7OhO1gMUIvV6qKubqKApGrrcVL1cTs1Z011oMBGqNVMjTlO23WuU2B77vrln__CS09dPYmBx1w3m-1qnZfrrVJab-13vvbuV7_25nIsTEzR53tYrWTQT_74F7777Xf_yT_7KppupRoFZDQ0QxdwNcFAdRKtslmvUMO8T1qLaK1VRbSbd7_-O9_7_W--Fru-MzfXKWdDMkJB30zbUiqC9ujsFiOXaTyd7ntwUxEwRCAyVC15BFFwV1BAJ0J0wVoSE7SgAzoRG3rkhLibOFIgcGkUfgQIjJaruaqAibRLnZTacewWYdoWJGxdQNAW5pUqtd0IYacDMuLoDQpihhwMKMYBoXHhdoMhN0Ewb4_eVGthRnS3WuEi3ozkauJNduloosiMiCZOIl7FOcasuRs6V2upR0BUU04hdiEwd31nDg6UuiGkuJ0yYCilMDJyqCIhRCTasfoIAXAqRUWcmRi__e476nbj8jFWffjodL7oRLWIrLaZGieScDvlSeo45bqtYC6lOPhm3BK6iLl5LhnAFRwZcy0xpEZaRUCRUkZRc2SotbQwgYgCcUAwUXQnhxhZq5oZsueSzzfLXLWaFjU1dODzByseZqPYu7cfho7vnW-6xD_3xc_kqSzmaTabG8KkBRirAYdggOgUiMdRqklIBK5D3wUGdOtSIsAQ0jSVWZ-IsU8dGHSpybWIgMlpCH0M3KUUOZBDYAxMMbEjzVLXdSkALmYzcA8phpR2jgInxBiJFv1AgAfzAxC3Umf9wMQqJu6xC84eUhDVEAKxzfue0ZkoRiLCPvJ8GBgwMhB6lyhG7iL3EWeJLu3314-GS_P-xvH-k9eOPv3KY9dO9q6fHD5-_fLebH58vA8ItapqaybsEvii3iy2zU3dKIoXx6mdOs-86ZBbsHuXdgDaHdrbXJaQmBmAGLgVbS7gQjtx184PZW1W2hAu1gB2fwQY3Z0AcZffRTAHbLUJuDjMY7vb73jzF78Sd0Xhdgk33_WAgYhJtP2zMyOQExEwutssJjB3V3N191qtSvtk4RZtMlN3U_M2j_cLgCmBtRcqgIfIFLp5itxyliZm2a2WWtSUiEKMIppzXY95O00hxsDRYlqN03qqVUHEzXYD9FmknRVP6v5slgIb8Gasp2MRRRFVR3NQxCqqplVExJACBt9OdSyexapZFctFVIGdmltXHdRM3UNIKtqoBW2j0X5S0vI0DBh26oZWXCKkLOIE5i7ViLkVsFqBuN3o0EHNjADReSc1h_YV3aCPFAKK2L3zDSBSC_8oqCs2dgq2L6YA7mbqpurqYO3t2tzBxRwd3N3UzEAVGhJc1MxcTVWtQaXaasoEqsruJoXgEd_50e1bHz4ARXcfyeOw-HO__It_5b_1y3_ij_2Y1mmZ9YMHq2-8dWe4cu1Tn3w2klk1VRR1U2MKrUGBbYHd0muATMSIDAQIDkroCLYeywcPzj746OHx0f4nHjvZXww9kQtEZGQmJHIEI1dXB-RgCCWXt9__8Aufeq6MnhwP9obIOIQQkTtiRAyI4ooBTYwJyzShVq_THpdZleAsuez1AyfEQAK-VTsfRaTuL_ZixwbEKbx39r4aK9rD5fnp2fposchn677r07zHEMY8gZuqoNioxWwcIL7w6nOr9ene3tHd27dT8mefe2zK05OPX09GJ3v7kWM_mx9fveHE4kDe3f7w_eefe2a7Xk_jNnV8sJglIGfu9va3m3jz-vOBYFPV1dZn55__1Cs-Tt_-7jf-g7_211589bnf-p3f_8HrPzjZOxm6-dHlY0Ydz8-223rn9p1nv_QFifB_-7V__vad7ejJHcbtqKt8bX_xMz_26nOfeOKrX_vG-3fuGaG3yJ9jrQAGpmSGpVpWnUp1sjHn9WbMpbh6QAhMiFRGi31_cHJ8vj7_yu99r3_s2s98-ctn95fLzcO12Gqd2xtcg4j3obNqi5AIMAGReeMMqtnBont493y5XoEauuVcpaipgblIHbdbcVivNwg7-hkH8l0O0nMt43Z0aPFKm0oxhbYxcwcgEK3raaoqxBgDuzjv8MZaVLPUWktAHDgSB0RCcqnVA3Ydmyl63ovwU5989nNPPTHvSIpms2J6tr5fqoo6hthouipWVUopgUBrFTVDSDGY2qPz9XozVYTi_uB8c7rOD9f54WrcVj3blPWoDx6uz8_L-VaK-zrraqpn60kJIfJW69l2PFtvz1dbR-hS7EMXQjJXqbIqYwOY7s1mABQDmiERxMQHh3uLEJgjeJvguIqaqYgYQFFHwNSnZjsZx6pqlPpVFncquTi7IzhhoAhOoQsUgzsxBhFHD0SMRJpHzdvNcnl2erbKGw_a9TRtJy1CjOCKDFJLW_Ujc-i6JhsRUzRHcjYk0Q4odmE9wv_6P_0rsCVzIgMEC2iMUGtRr7VUKVVNKSTmiECzWc-IiblOdTNWdOLAVWsVVbPZLMwWsy5yBNhu64xxPnRDikOfQqKYupakdnPmSEQ1Syl1qnm7maYxAwA6qbpWRYSQIqPEgDePjn7p0y8-dflkvx-mbTnfTsupPJqm-2dLCOHR6erW3UfbsfSLAbrkQNXl_Gy7WY2Xj6_90i8-__aP7iqhBy-TuTg4kIOMxcQYuWbpE4FOdRy34_l22gKiqKspMIX57PuvvfvwwSMzk0dbbwlbUc3Fi0BVtwIN76yuRZixbLdsztiE0FZqkVpdpYMW_XdVacvUBnBvI041q1rAoXqVZlkFUhEzCxwMDMCZZ81DiSAGRuAEuFquXv70F15_-70imZiQGUOsYohgqkiuUsEdGIkDups6h4DESMFFm-ijmQaI2AGpEQ3NGnKmhWbN3V3ibKailIKr7AQAqkhMsZHyMIQAZqSmITITgkVTad0OJDSzWk3MgTxP2VFrnhqPqIwFycxq4jBNRUU4gNYiUnKe0MxKbXXerusfLVeU0o_un9dawPXpm9fH7VSzDAnLVKZpFPNxKv0sNaHaJFOITYkAAFatAgVwBdOOueTKzFZMat3kSdwRMOcM5kULErKTO1apJgpqJedSawKuRWqpUitTzKVIFa0iWtfrdXWgjss0MoIBPHxw_mg5PpxKluqA__QP3qxoP__5z2-Xq45q57CI6eDoANC7GBaLLgWKKXYdAxMSmHtkdtcQA4KbGe5Qh7ijnURCghC4j5HQA2N1iSm0QAgnmvezyBw5pD4QUQyRQ5imbeqTqHAIITCBEalrNXRr0HovgYKYc-DIfDDMVLXvEhibOIRdEFDNWvQ-T9IPPYAgKgWuFYYYGQJRVDUGnM26w_3Z8X5_8_rxYzcOFgPvLdKQODAiOhHHlNApcmAMrn-UmL4wu7ohWJOdIYDtkJwX3woHcNGdk5cutlm8I7j4zrELAAjWMv9tku_AO9nGxUUAd7QsxF1FD3f_78W4Hb1RINzMzRFA1S6AQ25moua71gFAi14AMjI2-vuukO873YWDicfA3mYBiFaEXBaBbhwsFl0EVTerUotoK1031BqAA6M34Ue76qi3Yi9cdAnITbxOebw8693A0QxUVMHdVM2A-05NTbWKjlOuIsiBKQDgdjOdnq-rqIgBgog4uJmebiZTZcL5Ym6iDr6c8kYFmcZcShYRK2YmkKtIri7GiCXX7ajVTNyUUNybXMwBkYMhtmqDXQjdiIM1dmp7GhNEJkSPxOAYHNl2bQBzZ0J3QiPVtsPxBNEc2nsrEwQiAozE5mra6DtQTZv3LhCK6uMn_eW9fqqwdVBpVBXgdnzGXaisRbOYiBwMwR3EXFSrewuZ6AU_Fl13N7_G1kEAQnXb_eiZHVzBcy4Hiz0CRmIp8jtff62YmUsW01P_3_8nf_2Xv_zCfMCpTGePNj-8devde2dHV44__dz1GVEkRjMijJGZiIliiCmG9rrhQCGwm0GrnxK2bU_W-o33Pvjmrbtd4qcfv_L4lX0ibxQgbpILIEMComKoFAxw7fbejx7-8PbyiWdumOPlg9nh3jyCbbYTBZ5MRCs6ROZaPatAShPUVV5lClufNl6LbFOAdbbAIVIIIeWtfPjo9P7Z8uhw_3j_wBBnKS72h89ffsUATyWrwYerR7Mu5nGCgUMKSLjZbGaz7sM7t_ZnB0cnx4CeEn_hpZff-eBWCnH_YD6OqxuXr7713rt3P_rgaG9Wx0cuiuiL_U_GqOM4DUiSBne7fPVqF3i9WvfBGdClblenU16fPrrfxUSbZXR-tD5XmW5ev3b18OTOe2_9-f_wr-4vZsv797_3va9Pm-XhyQl1s6vXrkJVF3_njXeefP7Fm08-_o__yW9-7ZtvnmdjorwZy3YEs2sHJ1_4_KfOHtz73g9eP1utiqgTAJM4VHd1yGrgmEXWm5KLTkWK1LFOWWpKISbuAndD6ofu2pUrP_3jL9_96N6nf-KLf-Nv_o0P3jv_z_5PfyfFYXW-0lz2ZsO87xdDCEzmoFUhYBHZbsYq0ndxUyTrNG2ns9VmtZ1UoUuRCaec-0SL2QAOHKKYMGItYrKD9FSpppJSEnfR6gZmrbPYXrPePgfXq_U4FjFlDoEJFFIXQrMTqjMxEORaSi6A6OIOpOJgjjId9fBzrz5_3BF5rSpFa7VC6Hv9gVSbsqq5mIGDqGy2Y65SxVQ1ccQGma8KAMX8fJPXpWxF7p2vbt17dO_R-u6j9e2H5_dWm3WVR5vN2XJ7597qdL3ZVt9UOd_oZipFbLUu56sxZx3HOhVV2y15Symn22WtYqqTadelftYfXtq_dONSl7ohReJdq8urmXrkQEgcgrT7iYJAazYpE6pWVeUQVVRVRW2U9l6r7gAYsggSTmVNAVS1lMwUYop9PzdVl6qbOm6mqZbW8T882XfDoR-qVAwOrrizjTghcRfNodZqXhHEXRG6n_7SC8AHbsGtima1CuSRKDBwhAYrZA6OoO5qgA7zoU-A27GUKuiEjn3oUwiRcCBK4EeLAQ1KHh0hBl7M-qPFvptnmaobEhBjK6gVrVNp6QesDc7W8BUIhs6RTOurzz_16rOPccKp5B-8--G7t-6up2m5yUUwzObrTT5dbieFrL6eiipkmWyqq_VKIT719M2__X_95-NYVpMiYooMAIzAxFaKlkpAKaWqJcQ0Zs1SkAlAaqll0sX1_Uf37i23mzfee0_drjx-vDrbEGhomklQ1wJSFOqkGQGATOvEIbgKAQZEJDTX5v7MOlHcIeLQvD1pvWFCsH0PMEYiAFdjRAcLzISERGiualU2FAMA1KLEAV3cfZgf_Nxf-Ok_-K1viGII4GKuEiOBeYoRzEOIIhWAZDcorO7o5m5GAFrFHHaiVatASDGaqrtyaAUiMq1_1FdzU3dKqQkLQkuVA4CpmbgKM1BDzqfY97PUCHq1ipTqbgYGYFKVwu7m4VIRrB9mWss0ZnfoYmREqFZy80NAzdUVQJ2ADAAQq9Ojs-2Hdx5OFR6_ceVwb-_84aMb1y8D8LQdx3GsouNqYgZEUDVTj8DtKlxFahWkhi-EKpUcOARk2Gw3hKRWzc0Zxc3NS60KKqJZ6n4MqDDlahfAyCIy1YwIalBKJWStNi23wQNTBAoKKKXUWlerdQ28dziDoF_95msW8N__Y7-ATAf7AxLk5WqILanI7qELHUESIEghxg4QQ-zUvJsPMUUmABF14URAnGLQqpGZCELA2WxQlxA59DF1kQzRreviTkfOECPN-67rOlTtYsrjuNfNyCF1iWI7D1GXohq0-2GplSlEDkM_SC7zoUPyABgCOwJEB3YgYGZRmc8WbmRaU4-JKYXADH2f4hBzLrNZnPepD8TNUyulWVKLGACEwF2MTBwC4cXp3Hcd3xYzM2ukmlaIb1VPB6TdSdp9dwBrzBZo0f82wTVl3CU5dn1S2ikDvFHRW3CooT5hx3Og3e-9-wvcG-uVmkPAWsFgd7vYjbrcGYBakQDR3C8qxY2Au8s1tdbv7g9G4GbEaGQD87Xjw8t7i70USUWrFPXNVKaqarDNbYbibVXVagYtS-Puuw6zKpID-qUr-5f2F0-dHD11uB8cTRRAHARADazkggxlPdVquaioNTAVmKpI1TzV0qxajf8YGIFIHMS86QhE7Wxbz8e8HmUsmosoQPWmHzZAKGJjlVFkM5aitplyqea2Q9M0paOZNruBgWtLZDmK2C5tr-boPSV0rNUI0EDNXNXA0Hc3JkK3Cy4ntWB99trwy7uehTkREGCCwEwRG1oMGznbzEDg3v1NcuuZHpwus2RzoQCm1g43ZqaujWwGRIjMCLvbAVG7qDRGlSEYkjUln6qoiRq0_caFkWvn0HGfypRCJHdHnTarf_Xbvz5jXmbZC8P_5T_96688dpxL3aymH3344K1374jipz7x1KtPXY2qVU2rARI0UwY2ZBS2ZXFgcgdXDxQa7dQYpqof3Vu9-cH5pW7vJ55_7LlrR4vEIhpDCIFiaDgrV3dDF2JnzVI-uPvwe9_7QNF-4uWbvdPxvBuGlDpal5rmM1bXIiBKSMj0kW-IUKr2qbu7nbY5VyXu9h_kaoyrUShGK-Vovh9U3v7RvXEqv_6t1964f084bavsX7305KdeePejOx9uymY73nr0cC0Qhnk3zMQcUphy7bv5w4enKeHx0eHZ-enxlUufeuXlr3_v9XGzun7l6nrcyDi9-MzTX_vaHywW877rxlqNfLP-TuzTVCbo6eq14ymPy_F8mHfbaTxdLdWdUkgBdVqCugFMUikhMBwcLA735p3r8Wzxozd-8IUf-3yI3XK5OXtwb94PVXz_8vFTzz2Z16fL0we__U__-ZUrhz_25U995_Uf_No_-vXTbe5mg6jWMkmpHeCnP_ny009d_-G7P_rowf3JFBkvMGHkAGqWi4hbNeXEJi4O5jBd-KtrFXctUjHScLjv5qvV6m_9rb85V_zNP_jq4f6xujOim5soOaKrgK6W2wenaycchojE7__oXpfikFJi7voUhziOdbXezrtojuJWzRA8hFhq7VJX1XKZpinfPz07X20oMUemwKoCLQnjQISq2t4sGxDT1d0spRiHQEgOCG6RdgUxIDYXYgwBHdytIlmA6Zc-99IiQikKAGMubRsbmaeihrg4mHcx9EMvDuNUzZ0Yc83e7IGqXd8dHMynWs6248Pz9elq3NR6tp5O19Oj5fbB-Xq5zZPYcizLbTnflNW2nK_Lw7P12aacj9vzdX34aFxNVRwFXNC221xVikhVQeLDtO9m4KC1RAYGn8eODA4O5-a-rWWbt4EwBGaiNHRqxikVUURrIE4E58AhBlc3a0R5oy6qOkZUAzGNMWopjfFfcwVHcDO1mqcY2VWYY-ySUzXJuFsD1-WjVQrRVE6OjkDMCQVUyqSTqIqLE6OJojlFzhXnXf9Lv_jH3_zwbuYgpOY1EDMFR4fgbbTCTExIzLUYGMwXfc5ls80hhJBC1SpVkCAljkiX9_esyP6sG8tEkaoYIc5iHDcrnXIimvddF0IMKXKsWccpc6TcnMUEnLjWKlqAQN1mPf_0Z165sTd0Kbz-7u0337t159FyMmcOjQl_dro8X02QuknrqFWQJskiXkCLxr_5P_tT3_r2244sBKoK5jHy8cHMHfo-AoGruVsdp1x0KqWbR1GtuaAjI5mW9e1Hpegkk3k5W42PP3519CIOm7GsKyw31QiBvEpe5626qahX1yJqLl6R0FRcpfHk6mTeNvRi7sYIROi1knsMiQwYCRRQICKTXcRLAUvNwI09VV0NwAgBtDJRqdNnP_fJ7aPzOq4BTMWc3NFblhjctVZ3CyGq6w4zaNpy_w4qmpGp7YgdzBp8V5RjaFaF5gzhGEwqhwCAITC4a8nEEQDMdEdZjAHctIqq8vGLXzTbxWS71JspM6loSn3zoYbItYqIBQ59SiqOzGiGDhyQA5dSYwjIGEJg9sC8i4M49IsBGUz96qW9QH58eMCAJ1dPDuYHP7p1e7meqnipplJ3hwRzLaVWaTxjMwV3R2MiBMqlmAPF4AB1m0MgUAsQAFCkutU8Tvt7B6Jac-YYshkhWRVyTwhZFAwMbIi91IIIruZizKDN-dlsVaIuslxtn3_6mRT57sOHU5F3P_hATX_mx79w5eTge6-_2wUbt3VsTGjxLlJwHosSuasQgJnFGEylITJTYneIIag6gacQEGE-G2qRGAIA9F1XtbrqLEV3CKkDckZCBjNPISFiZHaTfhjMJMUoUh1gPgyqgkQNXJ0S006JC2o2mw1Z8tANINZg0QA-dJ2bEzohucPQpVwkxqhQT-Z71Y0BQuA-0H7f7XcUCAMhEzIRojcsCSCqSKt1NkA-tJYn-g5ojf-ub_dCF3lh6QJqWeTGZW9Y_N3_DdiWXB-rJX0HwfeP68LNBvf_Z-pPgy3LzvM88BvWWnvvM9whbw6VQ02oAajCQAwEQBACAQKcJIqkFBpNS7Lcckd3RKtlt8Oy3Va07W5Fuzvk6JZFqVvyINsKazApiYNEiqJJACQIggBBzMUCqgqoKbMqx5t3Oufsvdb6hv6xTqIdlf-qMvPce0-dvdb3ve_zIBNvMz4tYtSgnK0G2jqnrYHwwNrbUDHtv4StVmwrAQM3Im7c97ZMb-mV_78-9gE9GhAJDAKWWi_t7e7EqLWSZwMq0kbmLu6EaOpuUM0elBnQzLf7ke23gpAAg8tkD53fDx4YGbyZEwCZgXwrYJMKEIBJxAmp-tagZSKzrmekkuuqSAsmVTV148i1qppXc2p7UoFNqYpQxURabh4NwRGZGswbxE3MkMEdpBW53UQ8iyBRC2kBknlzXBAxM6IBuhsiMJObQwRvjVXC9qlkDfLUuHu07WcbtB8JNSiqijATALptfQ5E0IrTD77x2-seBwD3iLScJTCb9dHYTT0wIZBtrbhtp9Ky_r51xjW25vaHuW2SNOCStTVAe9_S9i9CQjNqvC41XK3PAvM8zQhBMXz-K1_9xV_-dTK6eO7C3_x__kdXH7mopkfH47e-_frJOO7tL9_6yKX92RAtuAM7UUAEUN_66Zi3b-YmCW-JAgcTsJXWG28eHY9j38Url_YvHixTx1lQnWIMIQC75aJFKzOH5Ah-Nk6__cXvvPz6nXFdnnji8qPXDvJUDk-n_UXPAVMfbh8eDbGbD12FOqRU3LvEcCbLWcc9OeIBhb2DHVlNyH2E-Qvfev2FF15GBPVTVdMyUd-_751vPb87dAaqshfjbBjGsxoDvPzqzXe85eEvfefbl88_dHS6-daNW7du3jKHk5Ozq1cuVLd3PPt033evvv7aYmf3YL7_3Df_4Oj46J3verbUzfUbd3YWO-I5aLh29fJnPve77TGSOjw6Ov4Tf-In16tV33VIFlOa782pG1zjt156g91X69P93X2r9dzBuWfe8vD9O0f7i9lDD51__sWXH752-eR0Wq03lx975Euf-wIiXX748t3bRxcffWQgWiyG4Hh2fG-xMzz-1OPPvvUtXaRPf_K3X3r1xjNve6KKqtQYCAFmfXf16iU0e-2VN3bn827Wg7sSuJMjOaE6KBgZUCACRAJRD4Raq4isxiLiCjh0kQlE3UA_8qMf-lc_90v7Dx08ceVqqRnUjLFkaZ9b61Jns5RiAvO8KbN518Vg5mdTWfQpIU4KQ8-BaDnvi2jrtSMQIqmUvksAsLOcN1e9mRpgVrVtnZ7BPQTuuq6KmjtzrCJ9imLe_kHmnAsBISMyEQcHdzNqvhhTBGLIf_wHvz8BMKCCna5vxxBTiKK2GctURdyWs1mpQohiVqtOOc-GGQKCyRB5NnR752ZEdPvuiTkAx_V6OjreiHpt8gsiZ66lHp9MbZiyGYuYF_GzOoGRmGU1VRC1KmYGoi5ViAgM1IEDuSgxtcu_O1ZVZgKiOuUqJlW7lBw8V6VIGGjKU58SAQVmMbEqSMHdTJVjyHlqjGB3QBdo4WyEZl8CM3RwqeYuqqnvKJKpEKKZNR_jMg1jreBmKoGpZqXIcZi1p6CU4t64fewg4IpuUititxPC_-bPfeI3fvHX-6AXD5bcHpfRGR1Iq6hWAzRHqg0-KG7qRJyLcORaa7tgphDO7y8evnwBTHd3ZkwuYgYQmIYuoamUGgOjAwFxCKWomp6ejZtSRvWpgm5Rfs3aXlKMoPpTH3v_1b3l6Sa_fvPuKzdvQQizxTwGOlmPR2cbtTIVOx2LoucKk6oT5lzcrRuGD3_wXb_zm1-_d_9sdMi5VKmuPk3CgaZSIvImVxFlAiLfrAsFlFpj4FIKoZvYuYcOzlYrDiEw9hzf_77vuf_mnRfv3B0Fap4cZFptvI6RyM2RaGtUd0epYJJzCZG9apspbuXe7mjWAIwg2vjmbhYoqGlgRvAtwk8buw2IyNQ4dujE5FLad8kZEc2cu3_rr_ylf_bf_eLp0QpVmBHNkVnMUgwgBqjeppuABM39DmZCMTZUutQa-5mbqipuS2IMZkjOzNY4H41z-GCb7aZb9Io7ADCndih1VWxVuphCFq9S3SzLBASubg6lVkByZHN1QDCIXdyMYz9fmImIolfrAgAAA4ZQxhxJEbCUHDskZHfIm8whCNtiZ_fbr95-4pGr836YOcQLs_TSUOpREYcA42mOiaapzrsZRz0-W9uDvHQkNoN1nmZdB4hiimNpj3YVqV4OFrvrsXAXRQuYjXlEwhDjtJn6rguBXTWXwnEGZIy0mTIDGzgoKmiKoYKi1tj1Jobc7NBUVW4cr5Yu9-6fpb47m-SNO_eOTvMPft-7_spP__i__swXZDxaLAbjeHj72MFT8BRIQcXRReezbjNODtYq832XrGpk5gG11kaqUZWuj23CWEX62SBSVa3ro4HtpMVq3KhZiGQuMXItwiEwszv0sZMW942RTNCx76hNhJtBOCKDVKlCRgDGzLEPZqJ10sCp60RKJDIEA-QYi9cQ-8NSOsaYEjGH1FWtU6b5rG8xazMDQ2IHRDAIHLZg2cZ-AXxgXkJiUvMQqIVRzZ1Q23mwKXAa4we3ty7y7cm4QeG36P6tRoBJHzgyAcnUCJB5i6lux8IH5id7cKrbvsKtyhe2twDz5sBqVC9AhECkatu1mBm4AwE1mxW1lSx-1xqzNXGZEgGaX9iZdwiiplIzkIMqgJgjWAs72fb0CVvBZ4vstc-dJg5rOwGGg-WcfWsJbn87MgAhEZuY1smxB2RRqKKOXhXdDMgDIQdW8VWtTsAhICK7AZCaq1hb5ImTgxepDlDF29DUVIFc3B2guru5iDGRuIJBYCymEamIxkhW3VQA2ZBUpc07mIMUVUYK2LTopSoB1KyMQJFVFAilaYJAA3FzyIMCEyJwI-w3z6EBiTgFCA-CjMhNBqx1-90nJG8ze0Rai22kLrvYRXZHDA1FYaYOCNtlzgOhnIkR4VaY3hLQuIXtt-CX6bb8wVvslLePTSJwCCJqyKerw6sXrzKzgirYr_7Gb2uN84fO_YO__X_hOZ-t893bh9945Y35PD1-7eqFvXkfQ3vPELKjIRF5u5psfQ5Fm5eVDd1RRfxsXe6frTHES-d2d3b7WcSinovmUY0wRigR6rqsx5KQlnvD5sxeuH74-RdvdpvxbVfPXXniyvlzSwTfbEqK8bErczcv6qSsGa48NJhWULhfpgRhKuXLR9e__Y3XU1wk06pT_eJXnj--M91aP_zQQ8sUdnaKTVhX4_yhoS673_vkb3_6t3_jqctPFqqqdXnw0DOPPXr50kMwow999FnrxIvO-8DK67AZ9i6iHPudWzvLvXW5--L11x-_duXxxx-7f_vu7iNh5rS_d-DOy_kyg-8udt-8y3cODx9_25MQqFYFLBqkD6GCoOpi6PtF31n65kvf2T934fjsUEkrCw90mE9Exjv37xbQSQ36BOhPvuXa7sHiSeyObx9fvnRluTx3_-4dguHS1Uubo7M7JyutI0YyDl__xqvPfs8HprK5dvHcwce-_407N__z_-q__bf_2B997G3XyrTxQgGwEvRdfOtbH5lyefXG_f2DC6XULiYwJ4huuBk3OER3q2IxpcPj44fO7QcKzD4b-Gwc69moXUccT8ezc7hz_97Rv_Pv_7v__B_-kzdfe-OP_cQfWZ0euVPqUnFRMYxRAGopXYiUQp5GxRBj6qiG4EUdyAEwAICZZAsRJ0C1CgpAqKrF7Oj0bDYbEAgiJgMBJBKApr_FECIAcGAt7U5O6yn3qWssckYaUlTzUsVEgRzQQ2AMVMaciI3qchFm7HVSczUvs9lel1IexbYYNUCj9XrTNnFFlZG3IwfCMknaW3Yh5FXFwLOhz-6rTV4XbVHVqooG6yIXdub3inZ9LFXHUpFcc3X1CdwCkilCaKmBEHgq4oh1qkwYIrvTLEQfhnYwyrkQByBUc3JpOIMhcJGCxCGi1trGRYwcAmUpJqrmXiuntpczCthYSgf7s7v3TgHM27awyPbwx6xSmYK7oqNlMwMkY-SGITgrE5ObgRtUyf18burgFcwYqQtxLBJYOXZSgDi4C3Eoml--efz5NSjY1asXQUioBkITVhdMplY3JcfIk3qpshmrmpuaEaWY1uPUxV4sc-Jzi_7q_l6MQQKq1vUkm80o5vN-QeiqHkJooJecCygD4boWT5Aw3b-_oSatAHcQd2CKRab9vdnC7WST_-DbryMjUgKKYy6bs_XZVE42I5Dv7O-Zgbi21p9Vl1K1ykc_8v4XvvnK4dHaQ9icZAiIiMxAEatKVbk31ZbYaXfTbtHJtGEKNQsTq5oU3WzWgOCooZt1srl6cXFyPaxOVtOZmGqdVpLHvqOcJSbGAqIV1HUqkcyRDVRFmFAfbMtNKhM6ojswuUeQBr9AEK-N-i8iRAxSEUCrALGDRQ6IIFoN0aBGim6GpFr18tVrdw8PT45Oaq0UCF1cgRC5YT3AgKOocGATCbE3rd6kNYDbIw4FyRMxcUwm1U2JWdQxsKpSCCZK4I31wjHUXNtUldCdqVah6MRcS2n-bq0laMO3m6UUasldPyCQm1Spw2yYxs18Oas5u_u4GodhmDZT6mPbYANg2waAWzvaxC6UqThLTMDkTXUTQnjhOzeunJs__-rrT108f_nCwe0bN27dvpNFN7mEPoYuuBkHyHnVcc80dRg302qbKK9iboCsWsyqI7nZkPqp1CmvT8aRA4tqGXOXwjROXepMNTKbGVtkDlWlmpYpB45MlKWkGIFQcglMmg3E0bHvB9HSyCzqWPIEs3h4Nu2FuLu3v96sD1e3fvWz-Qff88xPfOT7v3P95j_77NfOX5mv530tU9f1c9dNEWaKEZB8mHXrdXbTvk8iSqbmvOi6tSgGShxE685yvt7kNpZmIjE0I4gI1ce66WcdGpiZaE59b-6m4CYIlCUvljunp2dFSuRg6qRiYMNilqcpclTTEKjvQp4sEKUhSZ1SDFU7MKilKGoXZpNL1kIBU5i5edE6zGcVak-hSh4znWXYdYYW1jYARFBkcndCpBbnYQbwB8d0YnNDcwT05lJ68AvaDh3bkqDVH9ss_wHkk9AB2hgYARV8-2cgEqK6b0_SuL0btF_N-tXO62bm7kjYrhJt-N_qpNvuAaOag22P2-reeENt0o8tT4Tb5UDb5bYjogO6GbaxrQMgzgOr6yRFTA2ImW3b2_PtNAAJQR8oqdC2XwqaGVNoVlkgQIXZToeqTlBEUAtwjIHBUcFdFSARYjEQbZ0JdpOmuwIAcy8qU62ckqozQtel9TiZ2qTCSOZYRBp8x9tSpfmMEQFZtLZXqdqM283a4BW0tY8d0ABSjC1aHDh6u0i1Sxi3rHyTFTghMKGpNwwAM2tzcIMTcitaJw5SpJHtfUtldaIALa3jpC7EwQ3EtVZ88BGG27eKo4gRIhG-cTg-fMApsZlL1UCBCVW8lXeZ0NqaYfsOI0IKhAroKtsoEYJ-t6Lu7goGhojgHkPccpncHayYGYYupOqIgc-Oj5_74nN7-xf_-T_9W1Gmo8Ozl9-4df312-cun3v60Wt7KVKIVh3ZHXRLt33QZUFC0UbsdGMA1yJ6vBpfORofWvQPX9ifdzFFBMKVQMllMxYxFEOxupnqyzI9FNNO33_9xcOXbh4eBPpT733s8rnepN5f2b179z790r33PXn58rkli45T4RjvT_e-cevWF79zvbovO57N0sMXdw-6bnWkH_rw9-L98dmnz3_601_-8Mffxw7jGdw70i9_5Xe_vBIn3PCwqXS6mv763_0vnrlybhzzTj8rLDTp4Wq16Jf3TzY3JzTLIZEYItt48_7hyXG9f5QyHXz0p9ef_P8end354MV3v_zyi9O6Pv30Y8-848l_9VtfevjatWtveeju2frcpQt-PWZZmXoXQx0NVLLkmrNscL1aac4vfvmlUOmxZ5-kblhvpr1hyFVXaiHLPM2HUs7P9_afffLa5Stf-_rz_-AXfq3YOp9M-f76wvnz6A4QvvHVLy_2d6sPu_vzUnemciZ5eu87n_n93_udtzz86PkLB_1s_p5n3_ahj3zwK5_76n_6H_3sJ77v7X_oe985i_PzO4vlcg_Ahq5Ok11_9bXYL-J8Tqqhj8wY-6TiQ5_AxEXP7-6dHK_3duYhEBsuYs9JiYIaXNjbJQdRn1ZHf-Yv_umXvvLcpz_12Y9_7PumzWZTanXtughozFiqTmNJXer6zsQAfLnowJkAuoCBo-RKkfohjdNE7u6obnksfYq5ljFp4BpjUMIUoJuKESsbArj6Jk9EgZvjsGogZGJER2RmLEVCCCa5S2Gq1VXbmtQVQgrkpmoffO_7a9GW4icm0G2-0dXzVKxtZc1c1BEikboNXQwMY67nD3aGLiQmixGIhkU_nY7uqOaGoM5FBaqp2v3VpA7IzE4YVExPNnk5DMFhWk99DLlmJuTARq4AVitzqFXUtUopSSIjEVrRMU9DP4CBQwN_obmLVgOsORNA4rSZRjTIOmlIVdXRKbBU0eJEbA6Rg4ID4Dpb6ILVik4mNXTJVdixUQcQDNVMapr3lk3NU0JVNxMkNtNu6MpUchGpp_NhnnNpx25OITpqNaml4SaRIxGFoMNi9x_81__so2-7Muz0kj1yRyhArqLtSdl3PZCj1VocycFMzWKMKrXrk5nN-n5nli7N5z2huTFBzTUGXMwSc0DA4G6M2rofgcEh1zqpnqzXmDoPqe9lzBKwqUmAQPsQFfHH3__us1G-_errdw6P-90FIovbZpNLaQBWO97U09X9p59-5P7RGemYY9iUvLdYPHzlcrbpxW_fIE79sqN1BsCuSyYljzWPFYghCKiBSS3GQ-fgMaRprBxciqY-pD5K1ZBiFVmXKXT0zXu317C-cGG5Xt1fr0dwD4EMoYgBk2mNEUoRBmioxuSgtTigEyCiSA0MjW5OAc0UAYABzNzAqseuqzk7OFGwbe2QDBwMDIBUiUOtIzg5uWt1JXD74T__J3_zlz895ol6A4Vx0sRMSGaVRMnBpJpraGZXbU97NfHIXZuTGUikHs2a3UjMEjG2ULE7QUukq7tCc6nEYKUYNrodBCItmUIIMVnOgQMghTZDTSGiA1PMo3TzAd1JVUpmCjLlraUSQFXcjamHYGAmuXSpV9QYAyqYWeRQSaARCwOKSOiTg5Vcsi1fuXv02JWLFMJs6FUVrKaI05j7mE7XoxswwGZzhujVpq5LJycrTqkpOqfNGRITsUl1g6ym7qGL42aczxYETRVM07jpYiLHxmEZNbes-PpsvVzMplJCSI5QctmbL4TEwasoc6hSYeMxEBOlYVbLtD47vXLuCg18sp7McPfcweqNm5tp_S9_84t_9o985N1PPXr50oVf_8YLuNHTiU5ONwA4pBAD65THVR52lrMeq2QECBzUWN1HkdClLBIImfr1pgx9lyc3oADsjWNpzpGqimcZOh5CXAuMY-6HVHJOIQBAqVpLTjG0njmTU-KxyJQnZAJ0joyqLXQB6EgWUyAATFHcmFyrrWulEBhB1cWl60MMrDJFimzW9QsDmxpU36FhyIkQHgTG3IwZG9cHCRloa8hFIiQ3c3UKW8n9Nt2t2xgG_q8G9779A60F_LcxIAcibIgnh7ZDoMbbfZBYc2zqAN-qxtot47vFX2rn-zbWp6apdBOjQL6d_oLpNgSyDWa03sAD7ywSqmoDf27_9YPT5BACEtVxlGqGTByqqIkhIxKaWDMEAAIygqOYNcAeoBNig84xI5LtDHM3NfUmUqcQkdBRrSgzAUAIsXH3m0_tAWwVDDy1GbN7jLHJ0Qwgj9JO7UzBEayqAao6gHNgtS0Vx4nRVETBnGMwaN9pZKAHkKJGYYVgiZGqVkLUKoQtDEYEAAyl2f9UAamBUTmgPUhLBcaWpiQCcICAMWLQsI3iGAI6EW_dzEAP9FvbqwohtDuFmPH2fw4jJDEPjAJ04_76eI0PXz7HxGIuoohN1GCuRIGRvYWwtOFIgAiBiBHAgdQM1B4E0tjQzIHRHaCoErVllIHDejzZmS28XXUr_sOf-5WHLp37u__VfzLE-sILN27dPL5zunnLk1ff8ujlIABNFIqKQAHB0QFA1FqvyYCA0VwmldVUVmeZzPcP5h97ageZQMHE1tlXgmPOCK4VkCG4LQe8OOCzaQERtcrV5fwHnln0QY7P4IWXT26cTEdeh9T99IeeiX08mcrtOycv3j8scZjO6k-97-lsEK2GWYeo6Czj9Oz-wTPLnRtht1f8_cObP6AhO_VDWNa8mA0kvLwwv3_rdt91y519XlXG4ej4aP_h8zKdnV-cm5QCU621I0eki7M9S3F3tkPKi_lcbFrDuH75c-cunM9aOaZzDz10ejzePFtxmv_4H_7o67duPfrk5X6xVLRL5y8eH67ELA1UNmWTCwQX8bPOD_b2Dg-PHt6_hLS0I7n22KNfGX8fVoeHt-_WcfPG4VHXhSd2rn3pa1_49S98_WMfesdbH3v0p__sx5Y7s3P7C3DKUzX3--PYhT5yd_3W7Yd2dlb3N-yFz188vnP9HMVZRFfviaNiuXN2em_8c9__gde9_I2_9yvvevrRJ9_y-J2XXnn58OTSpeXbrl0pLm9_uLv9yo3Z7rCkndFpERMH2OS6M-vX0xQQuxSgXacRaq2hT20QwUjVBMC9aj5ZvfXZt90_Xf_n_-Vf_c_-6v9rOjtLiMHhbLOZzwY26LtORJnY0Ekk9F0EyFlTR7VIVQOHrsep8FinPva1ahscANDJ6XE_nEcHMV3lWkSlqgOYeYyhgtVcgCgQZ5CGM3ZCCqS5uDmRmwAGiDHWUgicKIi5IzJxmvU7gVgBCTDilCdw6BKdBc2r2hqHjf6FkfoYS9XNODFTSmHcTLMUutCRCyJmqWyWp4KIyCSlCJhKm0RQLhWYzVHNCdAdYwq1VFTOtU5TUaSuDzZKp8GacTy4oZsZMqpVLcghIJIKmlHOWVXn8x6RkLlq22-gm6mpAwQOjjjWrFUQnYmhqUjMd3f37t47RAdi7FPM48QcpGYzRBdg1OYEVTeyEOM4ThRTm2yNU3Y3Qnb3-XxRypRzCTFyF9abDSB6FVOiRGYaYkAkzVkRI7M4OMFsgE5X9bBPobNa3asjGhpFUDFCFhNHr7maSZdCzSOhT9MUu66MY6BAgLt9msfEQO5achYVM591HQU2NSAiVyNkYlcrVYF5Wo2IJNWRvOMgEcQElBUspt6h7nPYjNMbN49uHZ3y0F977KHXXr61Xo-rsVRzBlru7EAYMeCdu8fDEJCTwebw8OxHP_7hN268-c3PvMLE6_VETQijOK43gTGmOE0jAkGRYsYhIVdyqKVSjN3Qlbxplzkz49QhIqiZZA_hZ_7m__x__g_-cv38N4gphZDHKThqrYE8qBu5FDEEbCEcFTCLKeRV7mezcdogIIdoNXubSAGZg5YKCMTgYlWaHKjRDpt91FWNOQCiqiEzAVKMNedIaOrm8OTDO7945xZaxUBFJcRUS25RVWByEMbIGsCcnYmigSFQCKy5BmJMg23O0J0pqCtxALdaC1MggCqGEUNKNU-E6I6mxsSOCGBMZO5A6OqIBKxA1CaqQWohZnUdurlpdjB1bVVC5phSr1ViwHG9WiwGajknUTAC0yoVZpaQ8zgxx3EzplkyEJ8kzHked4_H40CMxCXnW3fvL5Y8W-wA8PG6Lg52Xz2Zxiwqks2AQNTyatWlrqqoIgbiiGMtQ5-wuirEgcbNugsBgXLV1PfTekQA1Koqpq5oSLRerxazhaOVcQJOxEZEolpyAQKVCmZGdDpNXQyuAqpSasnT7t4l9QyuY532d5cIITiuT8ex1JNNuXN0cvHypeP794ee_8df-vSf_MT3nl_u-fHJm6dHM2DTKrmEIbmUiMkTQRUi2N_bX52c1VpDIKgKjFWlG1JgrlVCDCVXU1BXE-XACDZ0acpVq2FUhChkMTAgikrfDVYrAjCgu7WsXq01dMGdUvT2rgbzGDuKjm4MCI5ZS5-SqYlaM7K5G7C5i3NCEqbo4HWSft41etRmvT539SKQr6ovIrs7mCETIlZRYtpS-cGQ0FU5BARroXx3QERHVHME20LY0VuLpW0SiFudtwVAGnlle7RtEf8m9LUHCutGsobtcHmLFt1iPJ0AEZAMminWEKnR05vLd2vfaqigbQAEG360Tfrxu2Niw7YGbk1deiAOQG_dX3cHJgwplipoFVMCAVETBQBs5S2gph4jc3C1yMTEZtvwqLkhkiO4KzunlLYhQjS0rf4WsK17wN2d0NEVHAhge4hFRGCjyMkdRdW8FUwdDA11yjXFzglqUSBCbfYyEDFr53UMppUweLssubsbM7mimDVFjZo22YKpYsB-1oF7KSbSRtnWpvehyTdA-0hqiI6i0kV292KCTBgxOTu4qba6SEwk6mAGiUQNHdC16R3cXNUxalvvGjqCBeYH2x43ACYPjlUNHSr6Rvn64WZ36PYGRncCaH8XIJobGTSn2__6fUYNM-boik7siGYtig8A0MitITAjtibJesyqur_Yaz2SN27dffEPbv3t_-ZvpBm_8tXvvPDy7TDr3_vOx65dOY-K1a3F3oCaUYlEtlsGdUN31bo-m45WExMsF_2laweBCJlcnMxEpNZ6t0ACPL_bm3spEpgQHNkZOwczcQWYDG--qveORjWjiO964tLeThcSlIriNh9Cd2m_zsOT-zPkNLmz4r2Tskc6H1JWc6Sfe_PFv3R1ZkIc-7fvX-s6Wp_mEHUWbTnEWjOkBcU0uQ-L-Ze_9s3HL15YLOZnm5OpTKcGXP3o9DRY-MoXv_6HPvF9N-rp94pQHxl1gN07J9ePbt_97M__wmJ_8f0fedfuud2XXnphZ2d3GdNNlqevPvTZu_dCn4aUBOuVhx85vH8U5sOy7ytX7qKgGOMLn_niu99-FQf9d__O3_vDV5_5gR__4TfvvHL14Ud_-A9ftHmaAdy6fe-pJ5-EaC9_57U__-M_krMfHuHx4XR2DM8_f0skX3_1tfnexc987gvvfsczb3vmmX4x_-t_-2eeefjdjjVPztOZno7PvPudi0sHlw72mKHbu3TjJEeoB4R_5U__UE_yS7_4W3v7i3__z3x8Z2_3W6_f_tSXf_v3v_qbi4PHf_l_-czjj189d_XiH_vYR37kPU8fHWoC7HaWohr6UMZx3Mi1i-em0CYZFJjNLcQul7FLGEEZ_Mq5g__wr_6X__iXPvuTP_w9hs4MezszMwemIsAEbtpzoK6bz7hOmgKPeeo5IUDOmqs6ep-6tsdLHIpKe97v73b37m4Q4HS1jl2fUgiEQwh3TzYJmSIWkSq1NfcaFrZO1QEANMQUGh4NAIkiETBJroSEBMQyi6w5UwpgNSSG4pvJ8ySNwYOOgKAmXUwxUINXH59scs7c0tMmHKDkPI6l5Joir4_XMXAlqlNuiYgYUjU_W0-YuBZFpMDMVUWlFkFiR4ngZ6crCGweGQIH3IwZmdDBRRFITFOXply6oVNTIl5vivhIgYkZydxsKtPecmcsJSRen47MDKrDrAezPOUYoqlUt9V6xZG0CgCO4yb2qeYxDH2j9yM4BNZS4pC0VsLATKVMiGToHCKIqmnAsF6vWlmT41YmmKep7wJBUtUyla5DAAtdcm-eTwUg5A7y9Oi1AxNHdiYQyYmCOopal6KB11q3AD615Xy-Wm2QSaapC2mcpsQxMK9r6ajtDNABqysEJoIuxeUi3bu3GRJPVXMRVa9SiAMoItI4ZiiG6CmmwoZu0X1vZ_Hux65t1tP99WllSH28c-v47tHJ2ViEwJEJ2Utxh2mVEacxz9rq-51PPX37lddfvXFvVbOCpGDTaqxFzbVbdNNqvRgW47jRkrdPIoeYIro7WM2ljzNBcFSt4OBxPqu5qnhEHKcJZDPdOcvHa2jLf0cds7IRRhVFFHIzc5OCjoYMbpIroAMAAwH6VEqKUa1qMYrsIoDUhDMtaW1iHFhFOLJvBYxOYKVaSNGbehKAQgCpBjDfO7hx4-Z0dOrgTImosjkF0tblAzL1mKJb8SpmEENSbEwwwmY9KhMSqhSOnVTB0GIY1J5ZIbK7tfS_meG2_gghBJfaDm-O6GpgAQGIUU0IIcyXs3GTTbWWqe86hypmQEjMUi1FNHMO3nVdGUuMkWMoJXddX6uEyCenJ7uLObqr1ZDiZj22O1OZ8shnXZ9cxLnELrr78fHpvEsAUBWlQkwRxuIiU67VAAMqoVnTDVmKMwMYS2n4lU0y2AABAABJREFUS0IGxBC4iM5SRFW1AkRmlrVGjrlM3MVAJKVMVQwUCMRKFztVYcZcSkpJTJHJzESkj92YN32M7ha7tFofLXYWVsp8uQNmTBzSvJSsamd37i535uv1WZotwa1S-Se_-rt_6U9-_N_88Y_9zD_9XyatsXI3sJJjgDJVJCA3HQUGmc3S-kxDCDEQAo4OkYOpmWicJQVTsdhRKQqKjtBTx8G6lIrkUkqiHhgCoIi723zej2PpYigiZhooEEfiYGZ9n6RIDMHVCDEEqpP2fSemuRpGQgImCyE4egQsm5xmvVQdhoTu4K1WAkw8baZhNnQeN3k8PtnMzu_EGKjJUgDUER5oSlvEwtFVtR39v1u8bJdjesAGbe9NajaNdo5lVlcEN3DfyljbEwcAwbWdyr01BFpvoO3b8EF2u60G2oIa0QGBHIHQ0UGx_aAJ0VqApEXxmzgMtrKb7eZ6axlGIHDbBpMQ2tEYzZRamqX1AcyJiQGxmyf3XKo3uxegWTu3b7vIjsZI4GjNl9YYN61lbI4dd9SBY_MUgLlzoEjQtDzkiIxsqlLFqlhz9CC2QKo3gaWZFREzcwR1Q4dcteu6FgcqhGYgpo6u7gTQmJoGXrUVM9AdTYyARNzccPtqt1VpDmgOIJpSVHKRSkRVhJHBjRilVEAyQwohAqg5AXehzfK3haQQAJ2c2zYO3YAJzYDQEdqyFc3MERmBGmulLa9andshMBtY2--AbcNazs6BizmL3D7MdDCfB4wBiBicmrVdHVWU2lrB3F23JKltE3s7t7OW9XJw2kbH2lXRFGJHxydHF88dUGDJujjY_dmf_W__6__P_2FD8Klf_9LpyfT0s48-9dS1YGiqos5I7oZqYF5dXNuAx9VMVI6OV1JtltLDF_e6jlt0TasFZHMvbjdW46vT9K5h0S9Tj6gOXWIiUHVDLOpno946LrdvTz3b_pwfv7roOkxDZCcpkidQpKq6GevX7p9-6LHzEuIAODBRktffmC5fPDeN6zFbn-ACnLt0bm8VajdL8705Ip-uzsKs77v5YjF3kADI6IRJbZ2Rzl06f-_0tguYKYXuzuG3P_X5z7_7qe_99Cs__1H5IN8_2axWB8udy3sHh8e3gshDO8tLDz_80OX95597jlyXe7s7i93Dw-Pb11-71Pc3794KBZ--ds3ONgs6IAGuebw_3Xrl7mIeeffcpWu7k2QIYdD4T_6z_-t0Wo4305uv3cnBzl3YP55W907PXrxx_bkbr1w4d55Nv_zNO7vz4f7dU2TrF0tiVOF-_9LOxd13vfMd9-6tn3nfW7_2ua_66pyl4BoX86jqp1TPP_nw17_1zRfv3H3i6cdpuhd24oXl_p2b937rN7_y6V_7zA__1A984gc_-Pd-4VO_-9nnRTZPX95N3PXrkz_z3vfJVG7d0L__d_7lz5RTTLZYLj70zJPvfeLpZ558_KHz5w7l5MXrN6-d32sx8WkqXRcoIpoho6h6mYj48Li89S27v_OVF9793refrFfLYRDTLnKXgOOCzaYyVTEpEJjGPM372VjEQWNIuWjkNGFW9y2rQRsilt-8u4lI4zQOQz9WTRzQ-P7pSECU3DZai3RdFDFTC0zgBiYcOcV-mkrfxXWuDEoYnFBEAEBNU6Qy5ppHd9FS1YwjVHMRVdcYCet2-TmbRUbuU6AQktLqdGSECs4hqmoFr1XGXA5P1mmYD30vDmmeUkr3T1e12MnxWVx0qUurnDFQnTTnElMoBXlI69U6IkTm2dAfjusUGcjAiYHdgEOc8hoZN5sRAFJMk4iqBI5AoAZlrG0JCsAGxIQmXmtpYZ6-6xihiKCDaiWOJtKQZQBAMUjNWjKFhAKBTETcTWsFZMklxs6kMkV3iF0suVguFAI7I6CaBmLmAAKBgTnERcqbjWJl4mHW11JixC0hW6wAj5Omvju598Z8-ECX1LIyurOpWa2FGRvYtxRRq5FpubOQKsv53unJWlIYq6YAsxQBYJ2LMHR9CkbYd7MwIDgamdnqtHZdPDobS5axiCLmKkURiEwtMB7ms2HYIUZSNKng_q4n3iZVX7xx-2S9Ye4nrKuj1eHxeqWWixgQh0guZD5uxt1z-44enN7_7nd_-evPHd89Xm3q2TqH5FJVpUBgVJD1SIabzVnfpdVGwITIXYRTLFJUxJGnMopWBCRGc8jjBISgAImBaZr0pVdf2NnbvX10a3t3TYBE0yb3zLVUTozggdmrqDTFLWqpNRan7fWViM2dG_INcfvIDWhihG6O3EgOTVGPHgO5aUrJzIjIib0KcGNIxPMPP_Lc574BXhF9OjkNCRhB3dzV2zEFDKw99xQAqkxtI2duSKCuFIJNOVBQNwpkauBNqoPe1KINk-hu5oxOiC6GiAZgIkQBEUNkq7WfLaZSgQAcQqlCIUgpjpBVkAjUUpdKGUMMYgXAI0erboGMgNUCYMmZuJE6NYMDc8tnpz5tNusYCdGLSN_3kidi6xKGFPV0Ne87n-Tw-OxoNY1jKSUjuJhFjutxFPcuMFYEhzIVc-i6WKcqIoAWvVPTaVNCiKbb5LWrTGPGgSlQg4arVrXKFNRra1UzcZHarAkxxKlkJLRaNUmMoUpVEAyMIZZxZLNSNufme8__wbeeeuzq_u7u4ck64KRV33jt7qWrly5d2pumjQT9uU9_-U9_4v1_4cc-_jf_4c_PZ2FEHqfcdf3GS5codh0PnlLqFyGLAkCtsjMMTlinadszB0Oiru-KGlSHoAHDenVCXVDVgMHMpQoZG3jAYGBMHbMhmlelyMSUAplpF-Jms44pMrNUIdectYk_OIQEwUAJcej7XDOHgB7cCJQCoo5lPuuLyHzoN5vNud15NduL8dbRYWSyUi-eWyQnJEYkwNAUT6JGABz4ATkdAdBbDAhaGgUBAJlMbQvmZzZzZnBt8mndwvxb8sfdHZjRGkt0GxcCYnSAhuUywO8Gx5nbNHc71NcHtwtTbe5ebMInd-Ctz8u9hfNBzZhQrDGLtkyDVhttSSBrdVJ68P93O48CmDkFXJ-edDsDAs5TIsBcqzFrNSdsOf122mfkZkjm5nMyo2bTcQMErcLznsAaJkJr5tghgLm6GSC5upsSk-baKGPtftUqCi2zU0Uoko8KIMxBRLdIH9U-9ps6iVRAUnVthebWcjZj5hbWp3Y5AwdANYvMLbzAbT2izgzohs5lrKYeAymSChAbOzsRE3ax7wNV8cSNs2mugKHd18DVY-Qq0hg7Ik6IIXAbkzuabhcuoOABW9JLGQkIE7TTsztsNyu-xbYaKYkbBWpBxzcOV0MMDx8sydTMDL3DUIo4opvyFvcEZNCmX62NuyWWORg2OASaewjMjGLqaOYBMVIkd-lj_0_-0c__xB__sVfvrT73yS86Dx_6vrcfXNhl8byRkAK6FK3oYGK6tRubix6frtarTIQ7O8PVx_bQgJFyVa3igA28NlWRSoPFH7wwN6Rivp5EXZkbtV0N4d5R2Ww0RXr7w8PefiBMuSo5WaGTVWbELkUgJEPD-oFHzg9MLg4MZlCL_P768Il8rirszDolPdjDZeohwpBSXKQUqXPrmRL7hb39vu8uPnTx3p3bIjUi0eoWQ1-nUk1fv3599uTO_t6l973zgxf3L3z_xR_uA_7wxz9-qZ-F0K9kGs9Ox_VaAOLp6u79Q04npZBpvXrl2rh_-vkv_v6rr71-52waS3U6-zv_8Df-6Ed-4OHHrtqc__Jf-z_mVHHsz8q43J3dfPnO__wrX9yd4Ss37949fuP8hYcv7ew-_83XH71ycHR6NOu6-XxxdLhendx64uHLhzcOx3M7H_3oR3_nc1_IzvNukBkJwmpTlstzN6-f_dw_-Fez3ZDHk_W0unfrTj4-sfU4ePjkpz4VIr384s0_-OrzXZyP91d6doyx29vdv3esX_rySz_3y_-iXzzygR_8nnfsXezY3zwr15569NLBHmreibTs2Mhh0ntnm1inX3_1O792-7WDtPMjT7ytn89MMQaa9d0sJo4YZqkbutVqUzZluZirGDvvXTo3DHD7aPOzv_LzTxw8cu_my6--eP2kbs5W8N4Pfvyv_Z_-uB2eMFqRmqsUkRhTitF029zpUsy1BGZxt61QhUx0U7KBdUwxxsA4TZWJxBydIrGlyO6pDwB-9eq-id984wgClWptnx47NiVQM3d1R2jLTJoZEroT1Fq7PqpDLqMDhcBIJHVCgpQiB5apagjr402Y8XLRcySzolprtWZUbCD-ccpITODuUIoGThPosDNfna2p65jjZjVJVSQsRUzMzAi9ilXz2PGMYp4qkw993z5txrLpUjg5XXMM62lCCg2-VkpB8MCoWYsKBgKDFOI6TwBOgUVBRfthNo4rCpEBpdQMRVRyKa0qUadN6geVCU1NpDXzOERzM1VTK2UiYtMSU5_HMYZUqkR0R1RVRgJFdQmEdVIODEAhxpIV3BiZkE0ru4WAk05PXnrkB37o_f_y1z51Vvw93_NkMq9EKhlDlFpjpBCCmRIAIEbmEKIU6bs0n6fdfrYa89Hp2qWAVq_KCFXdc2Fijhw4ggkxikIgVIOAqDFEgDJVNVxPExJPuYYQ5rMlEg0hRsxpZ_ax9zx7782j51-5Hoa4e26h1TerzeHxajVlBXLDMZd-wMBUpCxmizzl2XznD73j2S_-wfOvvnY7xODBuw4NrJ_167UFxmkcVZU5umkXYgyhlAncXRxDNdVSjSIpZEarpYJHcDcioOBuLurElx-68NZnn_rU57-W18XIwDO4l1IArJpiZAPHlms2pYQty8CRJUvoYq3CAKq1iYO8WXqYGNDNQkhEzIHAgRTaWL1lignZauUUtRo27LkpR65Znnj26T_4vS8DOrfpFIbGeHIiLYINA41obdhJ7uZAYGZMbNIm-hA4uoo4cAwUSIszgpliCIHJ0aUqh9hmsuiGFMWk5SfcFYyAyd1yHZ2RgAgsgEOpkro4jtNsMaATumupHKjW0qK8U85dTFMRcwAOQG2GQQzgDNO0GYalu5pUBwoxglt1Q1fSTIEgYIw0LLq3PfuOgfA4y9k0zvdmcO-QicapIOGUc4g8rcQ7q0UDOjuriYoSQkpdnqY6lkAcBp7yhjGqlC4NgkTBqxQEKlLmi2GVc6l1MevVFMBzrhfmS3XPWkiNwPqQxppjjONm3XWBiWuuMICrKBhDPLl_fO3ixTduvwlErlzUKXZVs0t36_U7ly7P5sv57TfHN8Y7_80v_sa_81M__O_9-R__Wz_7K4kgEwfivo8tdBQhithZyfPdxfrkdOhTW8_N9-ars7NEqRbhFFVKFxJ2bm6EgBBBfBi61k8tVdzdwGOXarGT1VnXJa11mKWpVFcLDVGP1nddLpLruByGKdfUd6oFtwIs0Kl2fWREDlxzRWgoRpVqs1mnIqZ6Op51MU2lHBwsS63FbGcxxD5MUx5CB0AAqCbtdGtuCA-y-O5E1BIWrSAMiNY8WObtBA_ebLuALUwH3gg_2BSoW5IubCPb_gAVZO0UjoDuBlviLnjL5jiANcNTI_mbETIAgjpim8UqAJoBMZptpQHmCI7uRoCKYOpEgNvo6hYz2u4l20TT9kXjNt7qsLO_S6CuPk4ZCAxdRKzJDMwMnJgcsF3QkbZtBCJqB10wR0JC6vuEDoCKqhwDkbuaqovUBxcFMDUksqr43e5Eq66KonsuVV05sJmLmrSxCwFhmGoFcwqBHK3BLhUQSW17MSJE3cp2ERm1GhmJ63fBp-6oKuYUGQ3AwTliu0sjgoh0XewdKDC4uSBpDSE4Aocwtr2OOSEQuKq2D4zWIiDmmiWEQOjE6A4GaK6B2d0bi0zdGUG3RuHGlwIDb-DRJnJ28EYIVQVg3Ii8eby6uOyJqBYJ0YioWksAgZvFSNXBRMABiXh7-vfWaVBAdwtIyChutVbmMI25i4EA5mn2P_3cr7zzHY_O9hcvffP1S4899uhjl87tLCIEdwg9o6uYVREgVNNJpFTLeUOIQwiPPXLQxwCEDFgVtAEDcRsxU_UUEkdf7i7cXITcJXZEQKXoevKzyQKF-aI_d4EDQyKsSuu1mGFknErmALN5R-gIdGfc3Dg9ffe5S8ghEoF7Q1l___65eew5VESKCFfmOxQoxqCRdmZhiLg7i7tD4hDP7STSev7i_t7e_ure6mhz9NIbb_oi_PI_--IQ-2-_-bvvePxdMfh7n33bNK0-8cH3UM5zdamje2EMDuXg4kO5rHOK7_uhD_36v_7FO2dvbkJc55Mwm__pP_GTp4dHDz-z6ju8uP_o4tr-9VV-Y3M3f_PGCa11ZbfuHI2nBXsIyBD06Ci9cfvO3mL5tre_4-Kl84IYUr8a5c7h0Yfe--6bX_qWSL4zbXi-e3h89Euf-mQ9W095XA6zm9fvIYTd5Wx-fnZ4fNv3p3o3y6QvfvXFziSfnjpZBrr_tRd3usFEa7U6bPoY3_6R9w07F69_6_V3f_DS9__Qhz4oHw-zGUMNO3spjLygCMmDFeA32WS1zonyVE7KMZ-cXL62_-yw8-V8-xee--Qtqkdv2u7J-I1X_-lbLvxAeMtj7915xOViWuqb3_r01176zt1jG0Ik3OzM4vG9AoR95Cceu_zItWsXhgsXLj_yPU88ylUNXMDFHdHnfeeOXYrron0Xsqi29zNikx61RWMVK6KuUtQWs34ca8uQIYiLAQITGPiyD8thpqP2KSyWw2YqWiWGUKWih2GR8lhzztsPQ3K1Mt-ZEfkkpUhOStW8oRK0ej_wrB9iZCe2nBdD52aMgOJ9F8UkMYp7CwEyh6GfDaPmKtVM1dZTOTs7Je5SDKuxLpeLuydns_msDQGY4nwWlw-Fk9NyfOpH4ynEaC3lL8JAwQnBYmAzMfc-dWd5NHScJjebDT0CmzkYpBiQScQVZDkM47RxAFXrYswWSs3qqFI5xJCCyYiMpUzMEdykaozK1B5GZiIYgqiGGKV9883IjLsIKioZDasII6auY8SGRtmM9_r-IHXR3ByNuo41MzOCobvWCuQB_O__3__q5YtXOvY_-4nvg7MzLTn0vYgC4XqzbhOdwOzqoQuxEFJnbkPfdxynMfchLueDi80XKec6G7rj9WiqBhQDeFarspx3BIQRrMh6vQkxjlIby89RFcREqVV9ul5Mqk1n94__2I9-2LOsx_w973zqRKaXXn3j7p3Tk7Px-HRyYg8kKiFwzkUjObgx3js8_OD733n_3uGrr96KDiVL34dq1QnztEkhWilejVIAVxMr4xSYEbDlQpu3ncDItUWP0UMjhZtUQ0l9D4x5Kn_-P_6LdgynhxskkzJBFlNjhOZzrNUWw2yTV4F5shKBVQVUXaEbwjROqY_OYFIa91NVY2BHr6qBIKWuWt0GHwik5IY0UdWYQlsnt1fUysGlasmyf-7AVWs1EAGEmgt1sY02QxfdjYwBCRAxRK3ZUQNEdQQKQIYUCBmgUGAzJCBH3x6MGvGd0arBAy-qiRChP5hstsls2-gbuOfMoXNXVwvWhq5IjOimMSV0i5HBXasiOSPnXIeeoWLJEw6ICsSYc95d7uf1STMYM5G4N1NPTF2dqjiqlX7ZRcaUhr6LH_vedzV841gUjGLXlaMzDlsU45JS5VzONuBW1PogLhaBEDFvESSG5qwsKpyCo49jhhBNCrUvEl3c-37IkjfjOqXOTLTIKlUzBwep6qphSOCkpSIzQFDLKQYt1cBDH4FJpjLmnHpz10fOn3_z_nHa2ZnOTtmyZfzWV1999PGr589fSCTraf3Ln_y9P_KD7_8LP_XD_8Mv_mqVQOxDiCVPxLzcC_durbmPw4znfZrWk5J1s16KRu5ANbRJY9eJVHWJqZdaiDFSNBVkNnNCMtf5bKZmTNRs1JyiijCSmu50_UaqVY0pTUUcYCO56xIHLNmZSVRjiCauIpOhkyFzCkxIpsJEmiXOIoCrqiCa4dHJZn-5lJJjjkxg5xyZTd2qtBIqIIQ2QnZFBAroTb1qDa2zHdO6t7oMACE0EI-DOZCawpb-39oprYzbsEBNBdDYF1v-IwABKSqCt1Wsu5sBEwOTK7U77oNkfxMSkJr7A2gZNaYn-HblgO6ODQdB4NtjYHudDo6t-QxgoGDWKuYtJIROgWSziV1SdQSvFWtRA_xua7mpUgAQCMwdZFtxxe3V6IGVjNBMA6C5mSt4qxCwNpIloJu3_Ce0myFRc9k3CWPsE7gHQgDWqoHZwZFRq5uBiIl5FWtdt0js4Oqth-Bgru5giky0tX4aMRmoGRCTmxuQuzITIgbmsdQQuEglRAcwlb3FzNQCsqlyJDTnlBriTs05ojlCW3oQmUNAF1Pe_naNMaorIcQQvBqAU4gOLUVMvkWvtiSSO4C6YoN6M4J6g2qqG4s7gpoTEjKq4-GmHiyGwJarEG3xQurte7I1WLoDu5sJAhMhB3RyqK4IoO5iwJhiYA73Ttd7u4uh7__xL_6rD3zoWR76l57_DnbLh67tLYcw6wKKVy2tUz7WshlLlnK6zh2HxTBcu3QxPVAihPZxrY7oYmAggdmdzB1jAISAZABVJYuJ-e3T8c46n4BeXcwOIg-zGCMxuQrUIkenU-zCsIhaZcExpYDkCDhO41ffuPOj73o0K1opFqgtNTDR7Wl8KhgKmDr1HbnHGCJK5LCEPTHLWgCqYOgWyWNIqT-6fT9inM8Xh4dTOT6hIH7_-PBk_9abb5yg7M_qbBGPj08ee_rRr_7Odx5_-NJ4_3AewtGte-_8_o8rr9Dx9GT8yU98hJbDlRo2p1aPV_ePbt-6d_dTn_lCjExpeO3le18r357Nds_Nh9rTfN7tXzyQ_IbnqGU6PJlubO7duXX_yiMXfvXnfqEKUMe3bx2e25ntnd__7Cd_68Ybd6L773_z5X65mI5PYd7tXdrv-p2nP_bhc1fvnN46-uYXfi--ERj4_hu363rs9_dtnaVOKEw7uxevXZnPdp_56CdYzm6d3q95Orp5TOcv3Kv1yvufvLR_riRcdnNedCcn9Wuf_fz9u_ePDsdFhLNp3GwyZMl5cgWfzmou-ztL4xhJHePlg53VlAfG8tj-pbO3Ht5-NV4_-m34g6qkZcTz_U__1A995rlb_8n_9sd_-t_4a3_rf_q_VYVHHrtm1VndA1fR2XxgxOOT-0C0WpcQCInNYNYHU61TAUStSsR9jJDodDNWkS4GQhQ3DgEZgWmcMnFwR5XqABwb01kvX9rbibGq1eKFve-6YpasRQuo1ro5nQgwhVixMlpgrlm-7yPvwjIx4WIYRGyIaQR1MDMIRLOeVWF1NgJjj-QE7l5rBaBNrTEwIJyejgd7i_VYEHw-6_KJIKiqg3mX-s2UQ4qRWbQuZ72qDJHUgoDVatcu71o-5XNRSFdnteRCxC61C5ARd4ZhUlXCcT12swErotgoU0DWZDHGzSTVtBYxNSJSlT6Qqmh1Va0K7oABPSsYlFqIqI-9FnETteyOqYvrzXpnsZimycSBEDmqVARkjuBuYkAIhorGHAEsMIC7aKWmNDRI3T64aWsfi2LzErsyEzOwIYMewLC3u1TZSLt4DB06ZJWzsYTQBjpKHmN0JwT2VopbLvuOUsnV1TFBIJzNkgVIIZzmIqqAUMcpzHtDSMQECGamWppxFUBUxYASefaO-7HmbkjZKqLN--Rafurj30_VX3vjjga6mc8Ob65UKCNNxpiGXLLlWlRjl0yNI0eiXMaL3fwDT1396__vf-wBMTJWKbn2Q0d9OLp7DCIBLAUcVyUNERBVqpsRYpGCFLJUA0uBdKzGziEQR7cC5hCcmLVmgcAMV_Z2b7953DZMus5oasUwoBmom4iOZRMiixskqiQUwAUcSaSGLtZc09DVbCFGB40pNgFpTAHdpdQwxLyZMALAdoPurk2spKAtjstE4EZEwERZuy5VFQ4EFDULGYBIm3t2IWXJBqZuTKRmLV-MBjFGM2nTUxUN3SDThpAAHB05JNfqJkiEwNvFryhhQFBXd68UB3QydCRwdQAHc2I21RCDiYSmjSKkEImRTk5OF8sdUwei2WK-Wo_zWe9YSq1AxClKKcMwtIltrhOHUEoJYIxEgXMugaGbzVWtG_rj1fr8lUueJ1cdoE_OZCAuFODseBNDmPdprDlnFdHJEMTGWjglABvz1MW-lBHJiAiIainzoRcRYi51ihRVraEUyzR13cyq1LGk1KFDnXLkjihAkGkaQwjkAKYcwjitKAZEKuOYYgBXZFYVCgwG4uWP_MjHvvq158TxuedeePbpR77y8qtlrHG5q3kdBzk9Wr_ut_fP755b9s--8-2__7nf_0f_4td_4ic--hd-9Id-54UXvv6t14ZEWgkYMNKFSztVbbPeEJJ33WbKC_SqMF_26-MJAEqWYZ601NinPOU-RJGKAUIINUvTE5ZxCjHoNDEBtNKAW5_6AtlUT-umRd87opSCEoqYipErM7hbg9G2jVRMnGvDGyK5AYKBzbqhVkXAGDtkVBVROxvXsxA3Yw6MR2fj7nzGqhzRqgGgI1SzGAOAGxg5W2uy-pbovy2wAsKDdHWzRG2zPejQRvqwxe3jdu7eBBAO390IADi6Spvet_euIWGzk4kJ0dakBNSawdvNwBb-79tiQJu7Nwtru5ZsWwCITugG4EAEW8uVNnXZNrPf7JctHEKMeZKDvZ4QiwoHcrAmy6nigIgEjGjqIWwvpYDgqhzYtC0uyJsPdvt6W23HWsulLfUbJJWZzdBAA7O6xRhyrlsoKWKITMYxsRZtPm8UdVE1dPAiiswcqMEuq0gr5zW9N7feAaETurqBi2pAaHP-BgNtQgMzSTGMm6nrOwCfdSmrxsBWqWMEZMMWykcKBOZEJM3Bux1JcttNPzCztZuec7uqAdZagRkJTDUit03oFnFKHiiIWSACd-LQsFGEqGiOrg6M2IpQ3N5DBmORcTIEW0RmbiVxyLlur5Le6MVbJViTBACRiLW9KzODOzGqqYOL2zDrZrH7_S__wd75_eO1PP_VF7rl4h0PzXdSUkp3jnIxD6xe6ziWPI4cwu6sP7i46PrEyClEFTPRmKKbIbR3sjE4pYiEjR2FZsUcKxxOeV3kZCqKPMPwlmV3ftGN4hVI1TbjmonBHB13ZnF_t1-tNyJl6HsQMQpe5fOvvfyjjz-tlSMAUVRVM9cxn-TxikcULmMm6muBe-s7Buaak4b9BR_eW926fX8e504lxP7gwoXvPP9SGua7y72QrOSzr7_yBoSdupMfsp1bClXg9cO7T17b_6XPfunt737Xpnaf_a2XKuCtW0dA3SsvvsCJwLSbz69Px9_89t_fTNOF5dKp05wF8PylCzdfv3nx0f1ZkmG264C37t8GoxUEuHLwna89r1aleJ3WWEQUdb3_nn_7B7_xy1-kPgbNT7z__af3z_rF_hPz8_3BvhdZLnfGs1OLYefKtTsvf-feyfrFLzy32Zz0_RASaS3zgWva7RYL1Ek26crbn16ev4pg5vrtr_8exgRLhmW6s-TFgKchjHm89fK3T1cn12_cmMtcV-tZonPzMFuweLywuw9EOJVZ7FebjLB67evf2d3pOcHu5YeuPHytHq8-_PFP_Pc_8zP3vnjv_G4_6y9efeTRf-OPfeLxRy_u7cwxzNXKH_1Rmu13P_LxH92_dKkPoWwqYDAGkSIq5SynwIGJSDhgDMyUCLwUzdmaG2g75FM8G9ddSuQoKowcYhARCiilLpbzXEWm3PQjsyFmt_O7exfms7N1qS6hjwC4PpuqSNeFaaqAkKU6WAopUljO5qdnIwflSrjK5hAibyUwiQio5fOIwARamzNSNPNAITBBCKeno6IFiONUj09WWUoK0RxEDRhr1VyrA_QpiboDxoBatGn4cq7MOGa9enHv5MivXTh_497R_mxexhPFIA7LvZ2zoxWAHNkmDYkIu27I62nou3E9ETNTEAWRiUKo6wmYtMpmrH3Xr8fMIYiUmIJWU7XAxByyZAD3amaZCRwZEaYpV9e-G3LV2CUgUhHV2sVQciUEZuaE4F6rZJV5Py-ldH0SEWCUKjFFU2WEGFikMrV0botcOrCFSJji02975uDcfg2eN7KI3ZQrMZSyGbOuc4VNtSqEWNSLWYxhb76Qaotlz9Q5AQUnA0AIzYSiKmr376-agDylKKKBIPZdrUZEuSogMpM7hsBZiisAIgeazWe5VA6ErpLzpcU8Aa7G6f7R6UR-9Np0cro-PF4djjV2A0UKEMTdJimqxgAACYEYfvITH379xp2pFIQ4jjUXS5GkZM-q5urWOTKGrg-15hDiNOUQIXB02XA0rRUAGIESi6OqRGZ1MENsDyIFtwoMNFpgHJbx6M7KAN0gBIiJ11MFwBBItTqwgRGQVgNVAgjcAqke-gjk1Lzx0kIbHkIgIimZiVUqBTBT3DLGDYjdQNW8Ufpa9B5RRSlETHR8ePfCuf2To3sqTRZETIFMXTUGM-Iq2iIKIURVAQevNfS9ukNAFQUEr0pEUibwwbdmS28HJSsS0uBYAal9o4jIVIyFCL314slAPUSWUgmDVEH0INPEqSvTFAIjEBPVWkOKecopRXSvdTIzNY0hyrpAQFFtz3WtNXRdHadYbZOnYTZDFxURNSY2tZ5Jp7VNNQe4-swjDDiqphQO9nbeOJxmfZdDrKLE5uLrKbu7k4fIpZRxysRURSkQIQQOWspmkzE0VIYYKVCA6uBKIeQ69t2gLe6iFiKbVXfchsHBpQq7M0Vqn5uRQ4oy5Zg4cIAA1YppUGCfhWm9hpS--vU_eOaRxy4sZ6_fvid5U7T21BPauDpbjaty5Xx-yd79gXe-9sqNv_vf_8s_9ac-cfX8I3tvTc-_cWNajScnm2nSczvD7nyhWYpbSD6kubmKyWaymGItuZp3xkRbHUSuEiIbeMKIiRoNZz6bT5sp9d16tULEEGMRLFojxyqqbvNufv_0tIsJEXWqZl4DRsJ5N9vkSVWIiZg5hiJKIarKZrOZz3onzDn3Q9-yL8bOFNCsFCFkqyVGHlQzWBHtAcHBHJDAv5vS92bpAGIkJHMDcCIEQ9tyYlrZcnsaNzAw4MAPsDtbND42ZbCh24MptYNt_Vy09TY5qCgRtiqMuijANBVUpcAOGBCIWMUcHQnNtq5XM28sUVd0dCY01YbNsQfEIW94HHDf5kvQ1QHJTAgZkcCRUFt6vuuiZumbx03aH0IPdMGOgMDQBitbOTGgiiIjIplZ48IzEzFbLpi4KXkbBgcAVDVwau4wdFYTIiqlEpFZc1rBrEunR6vUM5G7uom6uTqGgCIQQqhijKjqQCDoARERE4axVEfX76ak0E08cDA3ZnZTNWciEw2J3QgMZrPOvRUGOABEIkxYxZm3KylwENXIDACtp2vaWhNODZ9qrrSVKjQpWkN1MrMjunsgrqU6eAwREds1T0QdQEAHStUVWxjMvOOozRYKqA-uimqKTOxgamfrMiEc7M7crGYBxDb6AnFmQmxYUmMnACDeVpMVQNXaosodHAnBd4fF57_0lVcP34R1WB2OP_DOxy4-tI8EtXiZJlKYMW0ETk83iyE88vDF9Tov5l0MgUJoPWRijIEbcVVdKXApElM09wbxPR7zC9ePrh-OCXEecH_Z7XRpsZgtUshmHtERIsKA1EfqmNygC1wN6mgnJ3UY4lQdiZn9zv3VUzuX0u5Sq4kbMkGFau6RpaS9c_tiPq5X-xdSzeWRgnWaPNia_Jm3PvYf_M3_7gNPPUJdfuHbz7304rc_-mOfeP3e4cGVy09_3zve-9Z3f-O5L__qb_z2Z7_2lSGA4fDy_bN7r97bWyymk-PT-yf_6f_jbx-d3p-O81hyQkKrq_t3h8WC-346Petns3wyLYZFTAcXLj4mfHZ0__bDzzx9dP_-Fz75-Ygmmtd3D_thPl_MCuLtF14g9Dh05w4O-uVbDcsw373z2qtf_Wef3azr4Z27vcpXfvnTqUvijoDdYnf_4Qvj0boAjGcrffPGfD58_V9_-uDiuX5_OHvjFjKm-TlBnw3L9a07CW351GP7T1zpMWRxLHp0NsVaCaCzxYUNvPo7z-NsDl691iIw20C3pPOPPrXz1AVcpnc8_Mybz7_59Nuf-NyvfnIz3rl47erm3uly_-FwEp74wXfbzdvv-PB7PvnPf_HOKzdfvv7KwWOP_uW_8Cce3b8aBnQyQsSUTtxBR0LX6oPED__RD8z6udZCQA5KDhHZQVKIiC4qbWFUgpLAfEiAKAbDLCpAA1COucQYWvByiF2RggpEXtfTYrGczjYh8pDCNJXF0C_nw4by_nLIYocnq2Ee-x7HKgJWapXiVdTd5_MBHVSdmMZxOrcYaq0f-bHvXa5PpGhMCc1wFhCdCKuWwMHdzfFsM6UUTM0QjZBCiDHGJNwuW-qxS-MoYac_Xa1iCEPqAof1ZnX10u6dk03vpmA21j4wcpxyYQQD2FsOPQMSilNHcWc-K9XvHh6PU214uDFnCphSaFmRSMGKmfk4bgBx6IdAbADEoWwmROq7vuQ8m_e5FAWQWgOzVXVgIGBiIHDTLSSAwdViisSkJu5k4qL2INVNIbAWcwpg2QGYQwJAgq7rvGrfdWIWmME8pFjPNjgLWNEDBMJEDgZMoEzz_Z0LD137q__WD927vTk63Bxr7ct6XI0hYCQUJTFX8TxlNL1wsL-ZJJr1YxnmPTOT-1Tr5uRs6IepiCZo_uMqFgJxCFU0F4XEiKAGQG4iWRQRSxWFLdjDqkgVREIgjmS5CNSHlsMPfehd94_Lt1--UUBXG3UOQNGZuw7VxIxzsZ3dhbk7OhCilEU3_-C7vmdxsPgff_bXMEVMPVXZHWYySYoRI0Hw9TqXKkgMLhzYwQIhAaoUDpSI11PpY1BremRVrWiOEUuZYhh8KkwYiNTq3nJ2qx4TQDfrpnFDDAzRJEfGKYu7tbIKFkFTYnZDNFQxTkTMVhWQwMjNiVhEm9TSyUupfR9cvQ00rQpxAEYzBQIzDTGKKBMCmre0goIFvH_3zuNPPf7iCy-aOxEjIVIkAyIQNyZUQDA1AwgAxCoVwVFEEZACsLk7c9BaKSRDY06qAsTIAGAArppbyJg5mIiZUoi4HWJCrZVpexqjEMENzBAwcGSOcb0esSclBfAqhWN0t5rHvu_HzTibzac8dTGlFKuZGcQQKVKudRZjChHJTZSQkCIT1VyZENFAdFqXlJACXzy_u97kF1--9b53PHbxYN9fuiVFU4ip85P1RsFDIBCVUZ3UAboUS8lN9cyUqlYnQMIA1kDfpdZh6EULIioYMVdR1RJjTKkTq0VqHzpgNleVSswIpFq7EMwhIDtYywCjOQQKjAA664cXv_ItUR1CLNOmSH3n02-5fvO2AxJCLjWE5D3ms7xerxnhs58_-Qs_-QOQp5__pd862O0-8p73vX1Iw87NN2_eW4sQ4clmfPapy8-9dJMxmNXUd32FqpljcE_TelWmYNUIPBKZKSKaKITQ9Wk1FpUaZt28G85Wa2QOiLWoOTpIl0Ifwlhy4bwYujzlWZ_QUzGbck6MuRZzCTG0YjgYEGILQPddL6IxBEPYlKmppx0AqKYYYopSC4aoY8592JQGd0FEJG4TaHLazu6BqHm5mhKYmLYU6MY__-4pX7etS2hZ-y1lHrfBmNYRaHQbRFdteiYzBzLfovut2SrEFQFErWyD9-RVzTxFjoZMbTeHAG5uBGStooDW2LeNdYwOuoVLWmDeHt7BibYmbSJUeOBm2LppkQjOzTqt268sF9nC_g2ZSN2acarpZrfsIjMiMgN0UNcWXDf3UoXAiaObE0Vs9QHctia0VqYI1r4SJEBFbDV3NOi7tF6NMRAApEizLt45zlXdDZC3mwqvkJCNXWAL4HH3ApXDFqKKRFKVEDmQGRBxrUJM3K4siJEI-3Y69jHrMDATYGwrEXDEDEoOCN5Y_eoaArs5EUV2cUNDAXV0hO17G5AJg6qpmyMGbBVgBcQQAyIQMjhw2B7r2UHdigoSQsPGMooKEKJjUxoHRgcH8oSMjhwYyBXxaFOo3Vdd23YKzFqErGM2RzHnQFUB1ACdCAlJq5AhIRNaP1t89TNf-PRvf_0__Pf--K2706ULexwJHc0hBdsduL2TlDDsz4srGgw7qcXeLHtMUWupUpjJCc2dYiw1I3IpBujjOL14_c2bG3nfIw9_7C1XYiREqADVzMQqwBJJXPsERAjmBAkBxAEJrQIyX752qYgh8bgeA4f9HdjfW85igAGIHQiz-3qdN0XWBKd360knn7z-2rvvjK-X6V984cZnv_HZr443Zjq95dELN-_Yr52-eHj_67tDoipf-c5r0-2T19988xvPX__XO7-93hzm07NyfNot5tDh6bfvdW4urqv1Ym_5-o03XSWl3oVHtb2Dy6vTIy9jrRUp7l54XOrd69dv7a_Lt55_7eTsXs_63NefO-j3dpf9dDZ1aba4NieyR558vPRzO767unP7-quvQzes8x0xS2k00fHu_fPnLmxCZCbPU92chfncCaGcvPnCIafBDTZ3j6YsAwVmPL5xorKRcRVQaRfUEi6sj-pT3r88bO6ejusy5nJ245ubnCDa-avX7uPp-UevXOS9XGtKy253VqXke30u-Mi733r_1bMrYX7zm988unn_i_deN5ie-vC7KMTp1nG-c_qeD79jvP7m255-7Hf--b_8gQ-9873_-z83zOcMqZuHmNpnYgAHA3TwjlhdOZGL7-8ux5zBhAndVPW7hGNDR1OTKurGijv9cLoZU0zMvNlIDGmTxyJVzEPsci7goOAiNaY0AD3ytseh5jINKYVvvXZnZ9HPF4NUWXS9PAjqpBRVYRyruSJjx8QBYuBaQR1LGRsmaFNlGLrP_OZXf_L73uYs4IbOTBDYCOq85xB7Ubt3fNK8IoiYTcyRIgsYE5ubuk1iWbSanx3dn3eDMGmWneVsb7mYB9rfWWxKFVGtWlRH9eP1NJ_6vb2-Ts6MwFRKWY-rsUjqMaaEpa43GwImsFhRaq1qgTz2ESAR02rMsefNNHUhUkAw7_qEjidna0Iex8IpgIo7yFQis5cK7afEJJO6SJv3dimOY079UGtx3boVYwgKUEuLACG4OGOgUErhkFSVORgCMIG7IZpKCkSRzKq4xFCWs2G-d-4v_e_-6DkY-n6QcVPO6rdfvX82KaQ4lhzRAVyy7u7MA1KuWqaxSkX36e7JThfqetzfXyQOgcMo5f7RSouEHsokOmYCICYgTt2wnqZICAAqhiFK2z1WBYIiquZjnrKDmok5InAM0ySOFmKY1ps_9K7vVYN1KTzrrNDZ3WMLnBIer8fZYpYnJVCKlKecMDh7ZFjM0g-97-2LYf7VF14ZSwEKZcyMUUYZ-hhjEoJyKiZmus3yVnMwVRGp7l5ArTqiaZnECImxablUa4ydqZBbyRKH1ISLqvn8_lDyBOaoBoCqFiMH8RjZBEKKdTMhGEJrADNw4wGyqxFTQBZAEwsxiGobZaooOxKhixCCa2srYvPptaRAuwC0vI25O9gwHwj4937ni3_mL_5FCkBEqmBuKiVyENmGfx2QACCgi2IgUAQEAQEHU0Mkd9ua6RXcDInA2kDWyR0QpGjo0MARwVpdkVDVmCMFdCdwc3PECIxQjZldagDzPOWYgmiJhoiYc-GYGMEEwdHVasmRaRqn2HXTtKlWyD2lRIQNCyilqqi7l1oIgRldLMW02J2LlX7YPbm_3k3DztDfuXtY8pVAgVxrmarWGGAYEuY6rSdySF2oprHrNtM6tNajNUEbmRRDAOpqkS7OlMo0rmIIoeskF1FNCYmo1hL7blqNgb1WRKYQIqDXks0xUHCMVhQiiysBAXCtmTAxkTN_3_c8-7uf_z0z5Dgx-OHhvcuPPgwOzMwU12cT9oiZhz6Mqw0jdhw--bmvPvvWp37yhw7-0b_4zO986ctPPX41cJcWi7LZhBTrOr959_ixy_sv37iXhjgV4eAELCKu2nedV50PabUaU4wOPMRQxPNYgMjBU4zr9bS4MKeQXbWWGlPSWoa-20ybGBNTEKkpcAuuG6A7dH0CcFEhiiXn1CUAq-JG1OamJdts1qtKImbiWmuIRBTpAXIEzGOAVuE8WW3WJfdD37y25m7mgVBNFSFyaHigLcVfDYmQiBi9Zf7NW1mp4YAAGi0S3ZyYAcm1ybe2AEZvrEpEBCSG5pZ_QNZBVTcEc61iogiAWYSYAR31gSuAyQGQkIxMHQDMzcG3XZG2XvAHclzfonvMvcUzoN05mtUM0OC7VExA9VkfUVQcVETEi7kHdjNy1wZBcmAkQlJTNScGQGjuKXeg7ZAcgUihnY0RHICxKWeaSzgQY_urzQDR1AKhOpBBYAIzZuyIN7U60cm6iqshGLiJMZNUBTMhp4BsRIBFqpurQ98WQcgAEJi7nq24qmfRQASEqs6R-1lgxZwrdwTm81k0M1cDtBRTNQP1WjWlpM2D4O4IYsoplCzmhsSixuBMXE0BvKdeVB8seBwJxW3LT3AngBAigJWqSEgIIo4Ibkih3biQCMAMkVSMiAAgPmgwefsoBDd3RlJrbxMPjA4QQwMpkajiNnEMBIDb39XgrWymW5ec12GxuHX95i98_ht_4z_-c_dXevWhPSSPSIIWAduucruHEFJQcyL3UiswEVKtlqWUqlJq1eqKaR5xKhTRgDri-1M5PJ4-9Oxb9w92jdgcqjqpDWwDYwtuSVWgwBRaT30aK5ixaykehgCJ52H2xp3VVOC126df-czn7mg9Xt0Z-tnLr74x6_mNe_dKcQQ0qeOZPPr4lZTmptOXgJXScsAX7j3XSeBO3rh3PHY59BeWe6uze_dsLTLXfp4OHnkoH483X34ldmk6m6JSPpvkbOy7MGYJh6cxKI41j1PZnMV-RrHHmKbNCkXK6bFgN-wuj-7eCFjO7t7srO4MOx59sb_Hw-7iqYd3MOX1en12evPrz7OWF7_6zSzcd4qR5xceid2Ogw77M4C4fPzh6998tXvf957n58Y6bu4cES6dCIdhM5WdRy-rFpnqIvb9fK7ThCK0nCXaj05Hr920-ydx_3y5NybuprK-9_XXdq89OU3VyrT7yLuu7iwt2Onp2cn104eupVeff_nqk4_CKOPx0cnhmhzLpLe-9vJYyu1b69M749WHDs5d2L184fKr374-TX58-_Cp73n69HjldSzro4ML53_sR3_MzEDcAzATORMAETs5OgMyi7gKJR5zXg7JFc5O18vlTETB3dw4RlE3M6nKRORYSy3BKKZNlWjeD12p6u7EkUBracJAFUeOePFgMaNYpjEyUaD1NHXLbp5CAqgGgCKCxXQYOlE7PR03WRQ0xcgds3gteSy5mjNTFxKHqCKQa2Rb1zIQAbB4Vdt-tO4u58dntboaYEwxq6NjCIQum7MKCOKeq4HDaspkUE2PT9cPP_XQVG2x7N68d6Tur01jSJ25m7paZcTFzpzTcsgxhJgIztarshrPxhJCHFdjmbC6cWJ3GE9GdovzedHaDTPZjF1PDlCFlrvLcTO6CMYQODWjSJ5yN0_TZgoUtVZEgCKISACGFJENLecKbWAMvNlMRCGEaCLgTkxlnDhEM-RA7uEBTI2mae0JDTwGMwMzRWJX7frkosSpqiJg6KGc5Z_40Q_8uT_88XHTO0sI4XST12fl9ulpKSCRdJ21lGmq4JD6yLWveZQiKfG6qlY5182Oc-kCRQ5EOI15Xcoq13nfVYRNrbXWPOXFcqGORbTreyagJiQxKFUDQi3VAULgDC5WgFCqNk1uVUUyNCfw97z1qYC0PsvPv_LaWZXbR6cSQ5ZpZzZHdzKbd904FTaYdRQIrly68I7L-zLmvKlfeO5rr7xx73gSDoEYtNR-Z953PTCuT1azlFLAurY6qZjFPmhxxk5LlqyqImjItB0gops062UDVbO7cSR3rcUp8De__cqF4fLlSwfHL9wI5CrmriYobWqFAc3NhJgcrcUokMBlzbPBXFXNalVQRBBzM9s-TdxCQJkm3r4SNFcCenB4adU7ZSQzrTVzjEAx_f94-rNY2ZY0vw_7hohYQ2bu3NOZ7ly37q25uqqb7IHdzSZNtkmIJCzSFg0SFmDAsN8Nw08E5BcbEAwB1ptsmJZtULJly5JJDSRNkyZFtuxWkz1XV9dwa7rTuWfcU2autSLiG_wQeaoeLurpnLNzZ66M-L7___dbraKU25vd3c3u8vz8yaefEUMwVEK3wjEoAKNSDLVIoOAoeCSSmKoxUuxTLdXBENmBgRzVrBbuOivZFLALLhIimUqMyUyR0KscA7KEAKTtRuvuohg7IANyJAjuqKophnmeuhjNPXUR0NCP1lFmSrHLZY7MABhiMqtuOnA_L7cqGjg6qFSb54kTI1FdlvXYIzhTINTAeP7W5eXZptb6-Xcf_n_--W_-8p__tT4FROtWw91-QsOuTzUXVLPK5uB4FEuhAQU0tUhMIVaxYsocq2RicoREx50LUQBzUMi1cuo4RKmVIqFjzWVYr1yUHGtRt9yPadovXRdLEQAIAQHEBOdc7-bJAQSlqg4n4wcff_zojdfvnZ8-u90tczYsUCMwchdyXeYpw2jzvP_BD59-6Y0Hf-vf-It_5x_9V588_iyLm-QuRWK8_9p9KNIN6weP4GaaE1FdPI3x-nZHAIyMPWof4ACtDpqrxBCRo5qlyCqqZlnMwUvJTLzMc-w6B-AQS6kYQi05EMeuOyzTMIzVJHCoOa_GtasoMCGVpYQUxc3NYghMOO0P6_Wmeqm5hhSAkAKVkrsQRWsXQq06DLFWu7vVok3r7q5WRUIIZseQvhIwB2urplfQ_xatOT4RiVu-Ho8G1ldBbJdmEXZ_NaD2xs8hA1UFIDAAYlJtR0ZsUP8iVUXUiTge5kUBrAqiQwrm6gGDOUd2c2QGVWJvWl6kYx7IERuQqNE0m4EMqcmMj6gfVWVCIKbj54GblArcEIwYRRADgoBbAxR5QPDmSkZsOwQObNbUVEbcnAhk7uSo7nnJIfYmlZjA3PUVA8kdiI87knZCbVbgyBq4T_Hudj-sUjEtRZTAkBgZAzFpXjKmUKogYbvGEIC4BScI0IJGXUTmoIa5SlnqauikqABWdRQLRImoGdQYoDnG1RypMZiwGYLcveMEYolTNXEAUT9CfBAbuCcwm6uZB45VigXlQKbiCKoaOSIABlAHBmTkBnUaU6oqkdiwNmBuK5KAOzK2VVXrLiOBOWL77YLrMULmVt0BBbAZpt3MihFTIA6M6NAaV6ZmP0XRmrl5U2Y6-Olq-6_-0T8ZTu_9u__T_-GkdLYyf1VHJidzNgNf1IkHBKeojb8U3JhTn9wxpIq6RPBb9qunh9ub6__w__X__MZ7v3y5Pn3_G-99-atfP51vfu-Pn_746sOHl_fKzdXTp5_ezPby-vbl9cvnL1_Ou9ucZzWoYgv4fJirWq01V91s1zknweFz710OAfJdWZ0M893LaX-oRThyP46AMae-j9s-kqt3q3SIO04nJc9qliG--bl7jz_5KF9N13PpItmLvMwlxRu7vj0975yo4vWzDx5361W36gtYXg71sIyriOQRTfISxCm4FeAe4mrQebKPP5L776Sg3iExAyctc56Dw4vbQ9Gp3vlVdx8jQ-pA89XdB7tciIcRx4E3J5b3Z288nF7e9l1S8_2s0I-xZxySgS9LGe-dPv9X3zp5a6vLRonGk_X-ejdenpfDtL87jGdnhCVRSvcv88vnsCzznZy8dWaTXHzz_TLl3dNrVounK1gOZb9fv3PeT2WZbD2eHeZZD9P24iJh2pzwN3_t6-uz7ZMfPj5_-_7V05cP3nvtj_7oR9t7q3QT9PntV7_-zjCMKTCs-frbN--8_4Dy5uG7px__8cuHbz7IXu7dPxUFL8oAKaZmwkYDNgcG01JVv_3i8dWLw8-9_7kY0ourQ4xd10dFN2-bU3L1auamITARRgcEzNXYwMwrgZUqok5epRIEZPRiROBgI4ezPqlQqSWkxMTV4sWatPqSdZqXYehKVQQCAkQypBCQiQkIjTg4SOw7GMAUyN1Vi4OLyjDEf_Jbv_-XfumbaOTu6MaU1uuT2nyj1S8utrul1OLFapXp6vrqtfv3RV3Nlmrier27IWQyONlsT1ZdvZ6vdhNHevHiTt0tT8ihVpmmxRH7WTkSOtey78fOzaecY4xZpB-GZTclDvv9IXapMYaXvAAiciHG3X5i5qVo6nvvbBLJpapB7AKItHVzCp2hgrkWxch5XtTYHCgQETKRB0J1dwgxIPF0uF2tN80XGbsOwQAlcEhMVbyaq-h4cmKsMGlV-IU_8_XLcfvg7def_-DjZy9e3O32P_nR1b1HZ2_87Bv-8uaNB2_99b_4y7XAduheTtMhy7Or6XqaXlxnBScO6Cql5qWCUSmOvpyvCRIGgrv9HAn38xzIIzEYECOGcHt1nWIoxRXkZncwU1PU_ULE7hAZtXhgIHNKPOWa56XvYhWtSw7EKcai1sU45xIDl3kh5C7R4cXVl955IxFOsi95Oswm4kYSOTx59iIB96Fbr7vL18_feXBGZoickW9302__4EdPbxdwn5fiChDdwKvSeYhSVL1arQi2Dv0Uzb2gedt_MkEjQFBkLdqPXa5FRVJiDpCLujsVNAUApMAiJSDHrv-3_zd_-9_7d_7t915_-JNPn4n2Je_6lFSzuhgQJ66SmQNGMEXkwIhmmtZbBGvJAkZAQFV1kxiDqIAamCOQekUFZMyHJfbBzSmSSkE0YjYTE8XYRp_qLtM0b1Zj6ubf-o1_9Gv_rT_3H_-d_4CIzczRpDUDj7BxoxTUlDioFEQEDIwK3sCEGGNnYsQsWrB1b0pFAOqSmzAH8ZYAAsRACB6g0T4QAJiPeHNyE6PkTlhKjYRBaqWYVDTFPs_l5PLs-vqmI0Qi5iAqFKiY5Fqq6apLRJznA3X9Lu-7PuUlp27w4-nPaxXsujiMDtbAQ_OcHw2b1TgMfUDRi8vzf_Ybz3-p6r3V-vHT58U05-KmqhaQaykhkFQDYTNzApHiiF3qCAmcBYUDaCldSotUBA9EVSsgSCmb9XqZMwdQk5RiFgHAwJ1YEakAbugxBDVHpBCimbQTVsk1UR9DeHTv4uXVi7kokt0dpgevPfjw409vvrx__-23n__-Hw5Dtz8UkUrsUIwBaqlAQWDhrvvP_ulv_U_-2l_4G__an3-5P3z84ePf-MNvHfI8jkMny5RLRn_06HKYyssXN9ZFN12LL8vk5gAkc41dEpFSCodghISEbojJvIxjNx32qtIPQ57m9gYKgVzRSBswxsFLzYG5tTW0SuCwzDMHHMfOzbsuVjMOZEi51BRD6Dux0t40YEAhlDnHwKrWcEAcU0AyxBR4t1vOYghEYnrM6CN7c-c2tol4SOxubZDfCr5I7R9n9Aq6fpxnmx0BLw4mxwKAmyGgtfMyACA0XqUaIDIym6ihq1QDFEdRE5myt8QoEAJYSRw4kLuxkQOCHT0bZmZghGQObgbE0GhCjRHU2qlN-YugaohILdp0_McQmDlax6CliNRi4WjmcjC1Viht5mDC48-CHACtuT3oyEDy4zbBzR1u9_N4lojpaEJoCCJE0EYnOvL5zS3GTtRiDCPzNGdjrO4oGhOnwLuDOmDbmAJzSpyLmXm7GVgz0TIwUqN5BiImUIWInlIP4OMQrZBOlRjbHQUI76ZlPSY-tnuPh99219FqDU90TPi3-w9z63kgABG1MSMhiRu4c2gUVG0vBDObecdcTI2azFlbAkxVAmE2RQdxAwAM5G7EjOiiBoSE2ChYgIAMBHR0PBMeBc-O1ewoH4NXd7LjhgcQQLVFcqGFc0CdGcEMAw_Iv_vb39aL1775M1-6UYiOEhIgugmieyDoUIH-6INP_uB3v_sPfvgP_9Zf_lt3-VbuDi_2C3fMXfju9z74B7_37Uer8cZ1LauuQ4_h7PxnfvvDq5j2_-Uff_Di6v9cnt-WhTQi9Xrz5FlAOL130aWzmIbdwbX247jCYKuhf_-NezfPb_I8ffz9j07XqVuvHEOXxu2YlqV614c3zsZdevG733f3DqlgQO5fPp9JKRKUfR5WKYzpcHe3u5sQAfvwg-88JkIAG9y6GJ8-eRL7TedCA2EgUL55fMiHslzfGWB_uZG7OQum4RRAgS3fTqEjK1kwnb315f31J48e3ZuePjh79z1eD2HWDz_47nh-frFenT96c7gcBadn3_942U-rmLoliyl14dlHHz948720PrndH97-3DvTtHP3_uTCVDeXq8HidJvXrz-4-_TT_uxE5oWYiCnf6pzzeO_B4fbm_NFrQNR3cXLYPX8-nmwpJc3LeHYSdMt3Sz3U1WsP6_4wbnqterjeFwNgQrf5cNvFs37UmGwoUoJfXp4c-lDFV6tx2u3OHpyVXDaXZ1bx82-_6W7b85OhjwRsFSrY1We3goIdb--dQ20UjcNwvv69b3_3b_xNKtVSTMfIX_EYUfPy5PZwM5fN2H_-7M0vv8aHaSak7dkphWju0yKo5upDHwHJ3bq-A_MqgkBOBOBiqKpobou7e6nS9UlNQuoAg9UaYnzt3okazMvByGg2c67ijlhF9_PcdekwZXUQdVIUtVqFCBGImWotaqAAkVmMXCoTRY5L3lGgpPVPfvOrAIQErmDoeVqAgoL3Y3zxZD_f7YuigIP7kvO42lzdHWJIAK4OyzKT0c995fNe7bDU5zfzzW6uoLna3bQAghHnOou4iUxT7qaZYmzOR7rdIYGopwAFbVrmfujqfmYCmZfAwVRLKYSEpqdnZ8jGZM5xPx3aN0ie55JlO2yr-lEQ3kQrTm6VI4fIBGii7hhjMHWInUGVXMc4ius4njAisiMjExEy993Xf-Yr0_Pr_nK9X_LuZn-Y7k5W8bXtu3_6l35-6KICliVffPHNz799_3DIX3nvOvbr62cv_8qv_9qjs3udUUpxn-WHnzzPqsXh6m5eGqysLlZ1mQtxADIpDrupVooAT6c517qAF3UmfePBG-6uatXEnXOR3e6ATFW0qgbirJ5SlKK0UIw4pASBlixmpgBLNTXtYkKiIsXdiClwUMJuiFCNiX72l78RXKd9-e53vnNysn1--3KMw1yXQHQ6DN98752HJ6ucRURvd4cPnt3--NPnLKYAQKEUM3dE6ntwiOdn6z3PoaN5vxiBAVSpHB0ZOBBIWA57VXUUhAQQZM5MXvMEgdhAl4qMRESEbkJoYFWrAqKB5lxIQWR-49FDhD-oqmnsU8e5KFeMkfd3-_W6x4GqFHR1NCKQqhyDHe1F5ubM3FY9WoQ6LqUERycDMWN0qa3q3eDm4K7VjpoIsW7srAghlqJa6p3cuNqLTz_Jqm-_8blPHv8whE60YgjNGQoEgYKaFDDCAODMLGKmGphV1V3NvIpEIk6DLpOaDMN6OeyPyeHA7SakBsSkYi2qDWZlXjBGZHapRNQkYi0V5iZ88aWfp64jaBNGaAcRjnzYTSkN6lBrpcTukHMmTshupseRJ3IpmSI3lycTiFngwISqAgrZ6unZeZGyiuHrn3sjAO6h_svf_9711e37X3n3W9_7UVGjQF6k-VdrtaYFMnckcAZRdXNCVNGYoppKrX3XqxoSiahUCSkhUlUBVeJgpq4eQkCAUvUVddHAvYpGDqVWjmxqIVCtAogpJSAH5GEzPv7oGTGI1JL93qMHOi9E_IXPv_Wtb38XGcSkukpxB1pxKuDCtsyIkRn18afPPvfaw-3J-P4bl3_q61_5-S99cR2HkyFenAxf-8I7h2XWo62ZVJww7OYDB0YjJlbVtIqqzXKCnBIgllI5BHAPMVLgmrOpIUKVakAxBiRCBEYitxCiOzARAahJlyIwOoBU7WPMtThiiAEQOEQRYaJm5iImZGamUtpc_Ri2HvrekRhhGNOQYkeBCU0kxGBtGttyCQgEhEgODerf0Oz8arQOzHxMZrgj4RHDczzsElJL2HiLu8FxzdfMcg0nSoQErTRqZuhiMOdaxYpDrZoFmiuXCFTU0FMMxKySQwgt7I5HtUBTHmNrGDcmBh1XbkeoPDRe0LGj3Kid4AaI5mB51s3YI4CJUkAzh2NGyJHIXxXz2wPK3fCntuJXwt_2l7YrUCAexg4dzKz11wGIEJgDtQotgKi4u4l3fZdicsUiOXaMQAjU90EEGxlaqnZDIkJ3nGdpr6Goqbf7DjX4PzAyACJ7ixWJJCJVraoUQosb9SlV05iCtt80UrOl2E__P4KKK7g5KLqbmR9jsc3k3aCWgKCmzb8A7UrT5vXtqE4EduxpkEOTBjARExdzM2-2oDakRAAkFLOmj2A83toCMyIF4gZH8nb6B9SjEwnAjZjdoAnUqOV_HJARm1w6EBCWUlPqIsTUpz_-yWe__Cs_c__hBSb2rpsivriT772Y_uij9A9_57v_yT_6g3__b_-D__vf--ff-tb3vvUHP_jhv7rLr5_-3u9_-9Pd_PGz65u7w70vnr-sSXZlUgDhZd7lRV88uevW29n87m66evbcF1lttuPZ6df-7K9efXKzf1ljv37rja9_7otfNcSrqwmI-nGzzGCedjt58bisuu35vXu1GvAm4DCsBhXaFyyEt_v98w8ey119-4vvD_3m9N698fJBtxqnq8ly6fsuhPDJTz4sGVbrk_2TD6DbrLcjuSL6uDndPjx98kQu7p1sOsaAqRvTejy5v71-8rTrFOLw4E9-dbqdTu5fbB48iOdrXg9pHNPYT3e3abuSpWDXTwdZ9hnM5-dPbq-eHnb74aS7e369zNOzH3767MOn84sbQty_fOFiUphDf3eX58O8Olul_qSWuj7dLuoUk1TNO1lfnoXYL3dTf7rOUzl7dP_2-RW6q1p_uqrzNPSrHune5ZtWC6FT4LunP16d3a9zRQyJqR_W02FPFoaQQhfj2N09v12frmR35zWf3D_rVpdelkDhtTfvAWpI6bOnN5s0Pnxw__lnL5Z8OLs4M_e-T6FLZZY3332we3Hdedf1PQZ__uR6ub1bR_zwu9coi-YDG5r57ur6r_xrfw5UmgyRkYT8u88-_d7d3Rsn24uz7Tj0AiSiDsQRS5EYg6mCOSF0Kak5IhKSQVMDtsAiApOJAngAXK-HoY8cKHF7hkEIiMRnm1UfU6nVHFrxpFTPuYrjvJS-79TczLshgdmcs6gyU4iBAxGAVBN3kdbFbHA1mea7k1X_a19_762LsxQDMdW6vLzbL3PGjruxryqHWudiU9VaVRHUIRdZRJ1wLlK03O33l2frn3_vHQC-uZv3S7mblqnUIr7bz8VsNaTru7mozlly1aWWImaOUy7zsohZKdUdVFvcQkqpTHS7P4CDiLQaa8OWpL5jJAQ0sRRoXvK4GVVkmhZ0TyHlRVIKyFCKmFRGBldEOoKQQ6jLFJiRIHLIom1-RIicgqkNfeAYv_K1L3zhvXfI_PziPPX9yWp18ejy0eX2L_zqz_3c-5_fJNQqDOCiBECRVkN3fnZy_-HJN77y_luPHvQpAqFi-Z0ffHQ7y1x0t0heigGq1LyUumR1EHM1VdMQUEx3u-XuMC8112ohxVzr5996fRNTFZ1yUXFvtnjypVQKuBSdF5mLOnmp4mbQHvXgIoKGahpCAEAxVbMiagBIqGLEnBKPfXr3wf0-YT-mu739wUcfrk82X__S2195_cGj7eZ07EDhRzfXv_u9n_z4yd0Pn95--vRumQ05GHKuPh_mowpd8MFrFzVL4HDYT0B42M81F6mqVUXURGutDsrs4AbmITCiOGhtYyT3ru-sVHM3A3AndFBSq4hkYhRDSF1_ujpd3fujD76rVVXM1dyRGGXOQ59iDDXXNPQ1L1aNIzNyM9sAgFcJnOqSj0gQd2C0qgRuakwBY5CcsTk-Ec3dzTiwi2GMYM7EqGaAptKyWf1qJeYf_vhHf-rXfv073_od4kDo7etQ1J3peMrN1bhZjACZG7iEAEMXpZSYkqoxoXtrFVpKCQFeleucmGuVVhl0NzCjENQstK23te9GCP2oJSMCmvHpF37BHYa0mud9SklNu5TKkgHJ0RoMOPWDVsVWLHBq36bNb8oxLTn34zgfZk5BqgxD76rN20REi1RCjoG_-OajcRzmQ_6db3_n6eNnP_vVL__kk2f7mtVAirSJcHN0OnoiLiKtABADa1U34EClFqmlG5I7hkB5WYAgcECGPC0pdcdLvbVKBTS7h1sNMYEZc3A3Ne-HiA7uGgMjU85LjNEcP__O648_fepMUmrfd1fPXkCgZ8-uvvTee0vOL6-v1WlZSkhJmS_iA6AqUjHytK9PXtzQ0P_R979_dTttt5tx6Ps-vPbw9K03H7379mvnq9X90-3Hj68dXNVVPBDGLoADgbe5Y1EBpxgCMUtVDsRMdSnIBI4xBCREZETsKbhDDMHARZSPHxc3t7xkdxuGgWOsteacoSkwEKpqi0cbWB-TqwEjInAIrQGJQFWtHxKitya-ujPR0MeeaTsmZmJAZibidqJF9BgDQgtOtwMzMBFAa1V5s-equoOJtkydl1JFtVY5SnYR0LGBIl_VhtuB31qJnaG5frXVeat6Li7galTUirq6q5iLEQYOzF1kwsDBzbmJspGOiB0D5GMAvR3H6biRoNYIhleCAjhybxCQHCwQmdvZZk1uCEfaqKlba-S0fBMiAgTGVnpuw2YHdDsGmODVJYGRiMlEu44Tt6l7swYgEuHxwmFIYO5EiEhDSoB4mLKYpRS4WauYpyz7edGqwzi4uhs-e7nru2gGosr4U6WXByYzI0BTDxwMDNAj46oPPbMqVnMiNvB2BwTDhuzEpsxlbP2FKkpAHMjbIOEIfD2mqQKxA0RidXO3yJ2jd5Qc4YhGRnB45U0AjxSQQdUAMSDnKtZ0coHN9PjGPLZDvOWBWlEcEQ3QtOFKDQhal-NY8zBAQBUN7WBDrcJNhkqR1axj3G661dCDwjK7E9uw-d__p3_vP_n7__g_-jv_4O_-1_-_f-ff_dv_h__L3_1f_3v_wf_xP_7P_4t_-Bv_7F_85u_83m8_-fgnpVe-LeOWnz7-7Pr6Ooxp_-zq6dPP9pNbiC9FvvXH0yc_fP7i9qlSt5-XvK_7J5-tV_Hu9jaksNQZzT78_m-F1OMQPv7xT_bPr3SZzi9WS56wo_1-ev7kOTEx87zfyXI9766dbfNoNdf56uoO10O37nmMh2lCgqtPPytPX1rOl--_tlqfOPk8Cw8Rarn96Onpxcnp_RNlPUx6eu98vNhePaPtgwuoQgy06dKwWvoArpvznsGdOzOqRbs07m_nzeU9hWHcnIBjGkYgwsCqJtVUQIox2MWjh-l0uHt2vX14Jlm3906lclpvh9V6WK37ccQMm_UqxcDMh6tdGsc3vvblCnh2_16-vsqyDCf30tAfdvtuc6KmHCj07ICO3m03aVhVraFjcEDy1WZds5hhn3i6ukOQcdXfvbiKXR_GrdUSQ5ynHGOa89KtV91m2GxPS0Yet4erZxEqG2Qp06z3vvylQDieDA42Hebt6Xo5HLoe1qtI5BziYZrVMSVa5gJAPZkr5KmELsUES8mP3nm02t6_evzpdrty0NgFDH31uRu68_EkxKCOFfSTp7f3V2dvnZ5RjOquqm7A5OCYYnh-dXt5diJVYqTGH25RBCJSs1qKg8cYIxOCB4IuRsbjiLqUAughxHleYkhd4ogQHIiZAzUk8VIrhJCX0nXJwKtYGkIpImKEiEhN_eFmJUtbQnrDObjmWtHkz37jq196cOpS3OxQZJ6Xm31ZxG8nWcSvbg7zUq92y1xVESGwiKkDqAJhXsTZp_3y5__UVy_7UYFvD_lmnrPanOuU8zTV3ZyL2mERccuiU5ZmgAKgWkqpRUSlqgOpGhKLtMwdzbnMy5IPMxIaAiABkYv5MaLqWqWZAJdcur6TXIAwMTsYItRcXUGkqggxqwkj9ylRRERWMXcUA3PnjkENyfvAqxi_8bXPf_Fznxv78eknL1Zjv-r7YezI7N66_9obj9482wT3MldTK1XKUl75Fkmrvv3o_oPTkz5yqbKbyrNpfjGXm_1cRNWAAiI4iJtBdVd1Yj6UWkUj8e1h2i-5VAeEbkhFxMS-_qU3ofpcSpuLhRjMSc1u99NcpBqKeilqAAGpQesYj6SjdtCiQA5YSp2XAsxSBYDMDNyIcNV169g__uQlM21O1u-_9-jBuKFSr_f7P_jk8QefXT3fTy-u691i4j5NJZeKCKIqYrWKihDQeLLuUr9KBICHw4wItUpZMoIyY661ZOn7fl5mV2UCFxNVSgRmLq4mAKAKHBjcQggiQm3cReDqFAgBQozm9Xd_-9t_82_-1e_94Pv7XRbR9bCqdYEqNdcQWdVEVEo1PRr0zJw4uIouCx2_PpTR2-CYA5voMQDcpoJiroaBtFpIydRQBBiRWWsFMDBvsBMiylk3l5flsLdSpnL4-jd_6Yff-VYXe3EEQIoMxO7ahWQA4IbgxKFRBBsTnZCOREEiF29kqhCCmyKgirQxJXFsbUciQAckMqkAgIFdFBBd5Zh6RgIzNOOzL_5JA6h1jl1c5rnpQvq-X5aFmRkDImrVELiWYiJ91zMH0cwUwDxwMjAEH4dRakkxqUhIXcvUhj5WlWFc9Sl-9OTTn_vq-6WUf_6bvw8BXlzd_szPfvV7P_rIOTgABxax1Kf9YQZEMXU1dHc1AlIwIOSApuIACCRqwGSqZgYKGAIeIfGipiGl9pKpu5nH1CEiBTYVQA-RtVrkAAgEYAAxtRNmWD04uXpyo2CMIKWayTiuTOvF6fadt9749gc_CMRq1izNYnkICJH2h2oIzuPVNJ_eP_3gw0--9Z0f7XO9vlte3u2ur2_upmkYuu16XMX-xWF_cjHWpZYlA0ABJUBVxRYUVQcDJFZzChzAVdXUVTX1UZci7gY-pA6Q3KWaMhG4mzoxqUi7FB6n70iMpK6iugprp-PdKGAbTmNVaYballA_nonBXQHMQh_MbUgBHDqIZ9shRQqEQMfzWMNZIjfC5CsELoEbGJAjSFUHMEdVrVXUQM1qtSJWxKqaHL8vGNqJufkBWmjb3dzVjJDUQdREVBGWrKIgpuIupks1EVdrY2JyBAwEauhAYARgZkQkVRC5reug3Q_dWybnODkGOILh8UjyxZ-ebsGZCNgPUznb9K_6BMhM5tCuOUTsR3oQMqE3VNUroy63OH4j_BBSO9EDxhQiY4rs3jARgIw_pegTIsdgqhQoUUAmV11yOcal3N1wyXp1Mw1Dak3saa77KacYARrMyNSMENzAGWOL6ICnHkMgE2X2iHw2dgjogKJVW3QI3NRCpPZ7ZSJw4ICqbmbM1DYegFhV8RVBiUNotx1iBgREJ-RX0H0zt6Pkob3LwAnB0REhUgCEGIgIYgyi2n4xxzeVe2BuGS17RVCVVr0iYGYFAwciIqLmnWgbGERgbv1gC0yMoOaIbmoEnk5X_7d__x__L_6X_9t_-s9-4x__xu_9V3__9-6uH5_AgLPunuzL9Rwm6Wo4w-H1_vTh9kzj6h75Rb99fz1--K1PvvPdz4rc7e92ty_unj778XJzs5sOt4fr3Sz73dXtiyccfZa5TFOPPK6GaTfHs5MXnz4Hov2nnwy0zvslna1ubndln88fbEM3HGYJl9tnT57c3ezX27HM8_OPv1flBsO6v9zevtx9-MEnJc_bNx5igdmLzfnFx48HLWV_s9qePfjK23e7UiTcvtjf-6X3Pv2X35Mql289AKX9fHDncbuZ5jJd7V976wFTMvfUr3Yv9oGpFjPQftgGGpcsoeuKVhQ9ff1cOYzrEYjnQ16frgLHOYsSoROn5JFVUj-exhQrqRkLRYyp69Iy5269pTQMp2fd_c1SJA4JmAwYKHbjhkPYPjx7-fix1ry5dwkONZdxsy5zBmJzM6duHIgpjf3h5nYcuunu0G9PqOu0lrjqiagiUuBxPVZV7kIcRwwhpBgSdasu58wxIAfuw3ja6Xxb55kx1GUHtbz7s1-Xab8ste_CsO7KYTaF588PZ9vT1AUR2Z5vnzx-frJdd92gVQN514dpztv7K1PdHZbTe-fzzdRt0mefPj6_PCNwCmF7Ov4Xf_effenXfuaHn_zB6embaHEcUuzjsSp_5MdAcyQi-FIKAjIBtcWWGhCkrn3Be4xM6IQQA4LpdtW7mROLwGFe1BxDKOYhBDSf9tP5dkVEAJIIAUAUFFHd9ZW-vX00clE4ytStkcpUrYgEZtVWE55KXn71G-9_5fVLU9tP5Xpa7rLsp3I3y1S9KoTYmVlVU4elNpaWZ6nmvjvswaDvhptp7ofVX_rm59H4kO0u15tDzuZZbClyt5-mJYtIrVJF5qnUJkpXLqKm7uaErG6Bk7gsSxV1dVUzVZuWKXBw9FoLYQwxEWCKnYjkUolwHPpStRQzwnyYAByJVGqIQWsNkSQLEbb8BnM4BjIrIIOrmhiShRQYkVjX_fr1i_u_-ud--fLkZNOn-XA4vVyfbrdzzSr5_sn4hdfuPdwObZgz5TLN2dpZEADIN-vVV99747TvUgg1y8cvrm5L_eTJfl7qYSmAsAnru_ngJrvdXAzUHdRr6yohVqlVfL-fmbBfDXMuIsbID08vcpWru7ulyn6axUDMalWOSQ2Xqkwk4rWqiCuYmjlYCqGVPBuFXKqKGjE6gBuKKSIgYzf0IHK5PXnwaNsnntSubnY_fvbit3_82UdPdnf7ipwgdFMWQs5FlqUCsGhlICADlfXFiRmcbMdV12m127vDtGQFy_Mi0gZNpOIpUJVcsgDgiD0hF8tatI9DFWFiVQnMpupmIURtUrNldgcnJWREBoS61FXf_dr_4M9-_7e--_zmBgj3uzsEMC3MyMyAoA2JUUqIDG5SxUDbcR_AncFqZXQMwd0b9w3B3Z2JVMVN0d0VqIumisc0MbkbErgoc5MVsQMicxr7spso2NWTT77w1a8V1dv9bQrJwIj5uAB0Q0cgsGpMTMwqFRmxgQuJj2ZYAmKwKmbKsdNaKJDV2r5TgRAJKZBWaSGClsRuBlJXdTdENFWOjA6BU9T2s6vFyIg05xyGLoSkatWWQNynQVRSGmotblClmKPWOnTJQBlZRCOTG7jZNC3AHbMw0rTkbuiLSCn1w8dXtmjCgOu-Znv25Okv_plfeHh2ejsvBWh_mIDRE3ZdlLwgIxiBmVShIaCjFKmIHDu1HDiUksU0dEnyomJsSnRcobbK9xD77ABeHZzIS16YQ9d3y3TAil2fRIUQDDwkEpE-pe3F6Qf_6js09AANCyvo9Ozl1eXF2W_9wR_89_71v3xxsrk73G1Wq90ya50F4PpAp_dOQ64U6XraDbD67T_46MG99cu5jre7H-vhs299OC0zKvB2-7_6H_3V9966_OH1y6cvrlfr5Eu3E_C9IzgRcaSyW2KMbuZgMZCUwilxSGq1j70umUOkWsVhAXMzbgdBPEYkJEtIHZjFwBC41IoIISYTNfepHoDQ3dyMQ0R3c2didAd0QlyWshpXiNXdKQA5lUVSCuoIBuSeSxkYoE_MRIiuzojtIIvUZt5A6KYg2ibtKNqO9CbVGhIHkRxQ1ZwAzMVcVUyhSxEdwEBNG2__FT-UpQggAbLjcaheVURE1HI1MaiObl7BOoziCgKm5CIeqO8jAYEBh9BuRICNH0Cu3sKO7X3bxtwOxsjAx3uBqyG35rMy-qOTEc3Aj8Mnb_myhgpGp7agb70CMAc7xvcDN8gXgtOxIW3U6LSl0nhitf3tBKgNL9BO1IisRcgxhYSODr6fl-IOah2FrutKqYcpn56MWU3FilcxRSYkOkwlBObAkUiKKkDHXGsNgBg5mKGWdccIfjL0BB4ZVwNB6F9cTyrOzFUdqiJhJGoFABFjJgxsJmjHNgg3NQGSHneaDujQXuGjQ81dBSkgkInCEeCDgVnBAnFgcrTwU8iDArkjkgE1QURDtVL46QuObTFKRMBg6kxsYO1qwcQO3pJC7h6xbWBMrdmNKTKZeyL2yX_9L_-ZH3_3xz_65LO_-3_6t77_vY9ef-9RLYqxm3bLD373O-9946vnD9eMHswIPKZIoLlI1kr_8yDmGJgCqYUqMr-8efn86q_9z_4t2C9lZ-sxcNqq8Pp8m1_epq5_-fz2fDN0XSBdZJqtqnlXRerNfrNOCrh_uX_t5z73ye9_32qNarrfyX45W1864zCulue35a5cbtZTrhzx7vYmrU8f__jDN--d2TzVGNyRh1HyLjisVv3Tf_F707TrVkO2hR27GJUDpoTzfhg9rn3_ZDffHQb3IjXkeHLZy-Rpm6yov8hhuxKb1YRST8EBPEQe16NR2D25DasQYqABbp8uSEgj9X2wGjhubHBUB3MMOPSrWitTCGOqi2zu36v7fRjnOufUhRQoz8bDZlyflP3d7dPPhs35uOqs6snFxTLvfFHxUuc5rFYhhtVqG6ymGKe7u_7kdHt-uXv-lIeIyMsifUfr1SqbHPZLPwz92erl40-Hk01aDdO862JyHnY3dxh7QFyd3J9un2mefXEu1J_0Ip6qULHzzWZ3vZ_L7q2zSzUbhv7d91_b305n54M5HUrejCcHqVutKYVgul6RHUI_XPzOt_6bb1x--e7pcwA7vFjWffe933v2hXcecSATR0RXwNaUa-E2xKqAABVtyvn0ZAMIaiZqMXAp0iYtjDCmwBTGPko1DWim7QLmjlmUI9faWvmWGE-3Kzc7LDlG8ggm1g399fM7A3fEEDjXquqWXVRbfBHAQgita9Onzk0R1KR0gf7SL39zOeTrm8NUyiLajNpdiiJF3BkhVwGAKgYEoS39smO1zdkg-9wNA6Ij0c-9-6gYT4f80fMX1HV3hwyBCRAIA4XraTf0K0TJZTEmMVimwhxETLVS21sigwuAiankhQGQyAhS35WsXT-K6DQvbc6ChszErrtcy1ydyYBqrqZOiHmaiUNMSaUtVyF2XesEtGEwk1cTcAqhIxBHI8LUx8148m_-j3-9PIGru-njpzflZn748NwDllJArI_-9XcfnY9DkVJVD1NxQCZWdzJPfSfqX3jjQSIzx_0yPXl5eHy1xxBDl1wMAHLV_d2zaV7EKlIwdUJqR16tLlqJaFoKExPFq5c7IqSAp-v19X6SaVmtolaZc7nbLyl1oQu5CBK5eVERMzcoqgkJIdzdzX2IEDC4IThHUjNzF3UkwoCx5WCZEuLN_nC6Toy8LPNv__Efv5x9f5DHT284phAInboeS5WWU6-mjETIooqGQMGyrFbdEEIAvJ7qfp5LEfWKAIBWVF3QVA281GJmhHAoewdHwOKCZW7HOneIIdZlAQJ1o0CqQh2BeYqD6DH1GlIfx_jRf_OjL3_pnR89fjof7txNRAk5RJz2mRhB9QjLVuDIqmWzWs-HfVFJIbV6CBJYyW7uisyo2oLM5gh2bJQBYTCvCGgIDhpDZ-YK4sRWBShqrWmIy-3ekSSXLvb_9B_-_V__K__9l48_MdVmIGVmMGNmQUGDGFlE2JljkrwQODGDGwC5qKfQ4kzgLnk-2jCZEMlUDQlNjVKTeLYQjau5G4V0jGebI6AjAhifvv_z5h5DcBMTiamTaiGwg7WbFiETh8BcqgB41_WGgMRuCgBuqgAq2rLcQGQoLVNuZv1mgPaRVZe6_Ok_8dUhhO9-_MPdXmJkr_Lo4aNPnzxxC0yg1ZYp94lrlrJUjFyqpBhEFdRSikAEbrUqEjGSH5ln2g7NrY-YQhCVWp0im3uplY8HKlfDkPiobkY0t5bUMlUAF_VHr79x_eKFIYOZlIpIjh44dF3aH-b33nr7jcvLDz76qOMu1wLmomJOVbUf-lrF1JghBKIU3agsNl8d9lM18_HsFGp5a7U6v3eKVT599jJnETEnCgEQvFSF2Mjn3oXAFM1NCRG8S0GrqkjTyhJRqdXUhi6ZVDePgcdVN01Ll5KqNpq7OdSqAB6YqfVZ1Vo_spkBmYCJiYCIDDEwV5eeQ4zJ3VIXATGAx5QIbXuxGgNtxzD0MTK7Obe-OSETM-ExuIPuDiKq5g2yrm5EQVSrqJoKwJKrqNWqak7IRVVUiQkBObKbMR9NvWradAFtIA7gCmgACjgtuYhVaR4ArO1u8SpJX4qGwOZQspkDMhGjN5hui-g7OPhPewVNCOxt9XbsHUCTbSEddwEc8LQfusjN3WTgRMdVyBFOBMeQPbX1mzcRAeCRGHb8rwOYGsXgrkggouebAZHQ4VhwaBYyoq7riQmRUwxtFl5LUQdEiCmMXZJS5qlWQmOcpjLl2sheai5mhhAZQpPGHtcRllIgh76j-w9OR4DtKo2BA7gj5da_US9mHAIgmEsgJMKmXwFzIEeASMxILWvDxHY02nvbMyAAOQCiVmsCLAI0N0SkgOZAdPSlIWMz-LZLUSBuu9fGVWi4t7YXQWpwPj8GsxyIWmEaGcC8_drBwdoKSM2BWvQfOTABtF8COBC9Qvm4M9L5Wf9X_vU_9et_6Vc__fhF7FdXufzks6vvf3Z9t5__r9__j15fvZcomOG85Kq6lDotuijUatW0VhGVmrUsWURD6k7vP9rf3n37Wz9Yj8MwxDrreH4_YLr-4eNhO9ztNDJ7191-_Hw8TUO_Gs63t8-e9-sB08ndywk91Nt9vVv6VZ-oO320kSUXyctt5hTL3R3FACGutxdlyThVqr4ZVifn67vrO1HcXF5GIEQqKghw9-xFGjZEIY4dOFOXXjy96sde9jlnIezdrRsSIm4u1xRpc3papxqAhnENZEg8vbwph3Jx-SAfJiQKIQBAGKNL7Ya1mUYkBAcGojimE0STogR8trmYlwOatTQbI3XUW5XL-6dsqmJaq03LenuB6DFw6ofrF5-BybA-jSkOm42qACEj5LkicjrtOXCZF1NNKVlVBojMzF6nalrWJytSVLeTkws2Q8IucUrj8yfP07gau353szt_7fUXT56F4FaK1hpApOYY-weffyTFwP18tfXq65OBx_jxJy_ub8dVtzrMuR9XkvNr98_v7g4UeUgBq69WAxuWuaxPVlI9he7qyfzO2w-rwv727nSzzcv07p_6xdfWfR-jGyKhkbU5bnt6wJFr5QC41LoZh1oEEVUN2lwW7KSPZ6u-DxQIrYqZp5TuFtnlgsQK3JSjfd9XLQhGyKsuFNWcJSVWdxXN6ovW1lecczU1IC61BqJ2COhSaqNDMUUADFjz_k985XNfeeP1eS5XV7ef3ezVXQARqbXyzKBWrSZtgiStmmbtSW73zzYPT_uUxmkpISYVfXB2EpHnWndzvjss-2lZllqqLEt2wzimeckMVNzFvIhVFRHNJQNTkVq0WnUAFpUWBAfzlGIuggLE2GSXh7zEyIG5QcnNUVWQGMhVMpGHSM22blVdreuTg4cYl2lh8sSpH7tx06tZXioAUiJi5BT7k9WXfubLf_lXfwkPtFQpZuM4Prh_xswK7k5s5ee_9t5r21FE7vZTrlrMapWQYuq7vguvP7r3-sXJKnEt_vRuenK9_-TF_u4gahb6dHO9Y-Y8LfMytbW5I1oFV6-1qlleFlVTAy16enk6HQ7VFNQR6eTs5N7pZimqKoepHpbiiCIGhqpugC3-pA4IWN0csFTpum6uVUUBUcRUlZhagyvEyMwtXw8EzLSi-NZrF9_9wWe_9cFPnl_llwcxiGKqhm04m_qUcyXSw5RFhBM3yoIjmmmf-s1mDIHmsly93KsIkS9LlWrH8Ki5qoYEtaiUQoi1ZGv8OHc87rJVq6W-KyUDIVQFcAAnAwrcuqvcsZurYuzpxTL_ife_-p0PfjBNs4kgglTnQI7oqO1MDITHKLXZsQOgFiM3P1CtElrTuKqZI5FpBUJXJCZCUDVicjCi496oRaAN0UU4JVMjpm4cay6yLAjeajYvXzz9xV_-sx_84HuBGNwosB9r6Q5IQO4O7pZicDNib9UU7pKZUGwwDSU6Rq4ZAYFUBQFjDLW2Si00mU-LISCAiyIxgBGzE5kqgfHmc99UtZQiJXYzVcVEQAREgQOYMpGacUyAYLUYYEgR0CUXMeWUAJsHwZCDuddSwHHo-93NYXtx1nLETByG9M6De_fPzx8_f3F1m-PQ__APf_D1b_7M0yfPpulgRpYLM3nVZvghxNTFvJQQo6q4O3HQWk1lLjX1HTbeuambkjsySzUK5OaIDoQQKDCDKHFgYiQykVZ7ZSSpEkIw14gs6l__5je_90d_RDE5qasjeq2VOUjVkKICXF3f_PzPf-2HP_rQVQF4v5-6vg-EtcrQbTCSm-VSYuq69XD7cj8wXr-8ERVFmquenq0-e_ryl77-ZWb64cePqeuvr_fUEVo7e1IpJcSYS1XweckItixL3_e5LIhsJhx5v5u79WgqHAIihBC61IlIA8g0dk2ppc25Qwxu4KrMbOrIEEJgZjMFIAokYn3XEXAAUhE1C0SByFGbAjFFDojroVulMHC4f7aKidrRv53AYgwEEF7hdJBAzapaVRf3alDFDFHN5yVX8Vy0ihdtfVesanL8iHvAlmRqaXkQURVT89ZXE9WqWkWUaF5qVq0CWZv9FlSBiRiowY0NYT_PIu6IwISIkY-i4db0BQBwdHA3b5ei9r9Wr2npdGhX54Y2Nbu33fgxdGKtkBeIwNHNFH_6B7aNvnnrK-sRiERH---rb3sGw6Ov4LXLcyYOiOboKswEDg4UUyAiPebBEAGklkVM1MVt3SUCBKIi5pH3hyytBWFuCmLKzAgemFStmZgJAQOh-8OL9YP12KMzeKCj9EzdsygxSdWQQi4VCANzjNyiUS0Y9Upr5otWcwQ6Pu8QEBzBnZCau63NJMANiZrTwbz5z6n9ewCa3ANTiOZGzaeFgI7irVNhMXBo4m7wtgJuFwzmo6uSiMDNzJkCEFi7KCKoKTcbw6u0FYATNLTWcRvv5ITIgZdFutSvtv16SH_8ydNxu_2F9-493G7_wjf-NIJdPrgseQEzaTD_WlWkWdCIiJ3bzULBzAwZhMN__v_-zXEYwcBztVx2Tz8jKVOp9z5_L12s-xQOhylXGLcnwOn62fTgnUfp_n2dlBHGYbU6WY_jGgP1F6MBc4xdl_r1sH92c_L6g9XpKfeBCYtIWo1dv0IXQM-zPXz7NQTMRT7-_k8261GtAkMFDX0ahjFnffrZ1XpIQK5gm9PT7YMLnQ-nJ2dvfu7e1fPbLN4hMIXubGDm5W5m17K7fvjO53Z3O0dzD12f-i5JNgNTAWqEyCJmTm5j36mCSE4BEY6ZsZJLP46rzaBF0CFERkapBZn71RhTp7V0w7A77CUfhr7vVlsA4q6bpz2YBYpuOg69lLxajVBrKbksC3Mgco7JpCYKteQ0rBqilzmCU-i7rg-mlucDAyKCaA1My-6uG4f9yxcxoGm9e_nki7_0K4ebuyx6ue77lLLWbNatUpVyebomIERkUJ2l42jVXWtiHofOTF9__cHV1ctuGFw8RFFESt10dXuyXl_dvnjj_Ozy4SZxT8iq0j5orQmDQEQo1h5CcLXfn23W3i7riAho6menq9UQEqM1MKI5M4nCIYs6mJGIIjEzVammlmK8vDwZIucsoeWhQ2DiuznXIuqei6YUm0PTAQ2gFIkhuHvbPBA3Dpe899YbD9ZrNxNVi0gh9EP307aamgECMzFS4ziYu7muVum91-9frldzqVP2mgUizXWZpvzmvdPr_bxbylzr9d18yHWpOueSRXa1OFgVm5cixIcl1_aEdRBVAxtCL4KB2V2BUMRLEWISVSN0U0NYd_1chUMEwGW_xMTmnoaOiIjcRDULqNZFzfTuZpf6uDpZM7G6AaFKCRyRwzCuDKCISC1djF0fKXL1fO_hxX_3l37B1YuUSn53Mw8RULy4hRS7AO--fe_9BxciupS6FMmi-_3ibbfg9vD-2Unkzbo7LPLh0-uXu-VQ7bDknBdVX2bxgHd3h93tNWNX1Go1U1NVE1ezkmXOFYGpgy4EXWTOpcy1H1IVO9lsFfEwzeCYVQ5LXZbiiES0FFEDJKpitcpc6lSqaGUkrSpVaylAJFWbwcbdkQOCARhHTokTx6--8_o7r12WWZ4elie7_c2sSHyYlmm_GFgTpwMGzWXKUmslQgwI5oDsBP2qZ8ZAWGu9202HXFW1ZhGTZrxhRBWpi2DkeV4cHUSIG7HbAJQRTZtiyJEcwQMndzMVQJK6uAEiQWAkBCAOLDL7tPzlv_TnfvM3f2epCyG1b2UOoO61VHcVOWZ3G8wHEaRWLZURqX3PQxtuKTmaA6Wg7TPcgNQAaCDtGxpelQZbaLV1rAlVauwGAGTkZX_o-iBiDjjv784f3bs4u_f02ROkIKJgSoHVBCO6N6lwqlqZg2mjbCgzA4CLgLuJetv2YzuStUmrMLXqJjATtFwDOBG6GAd2ay8aUujQKrnzxZd-gVNwc0KnEGJIVZGIACiFJDWrWBrHXCsziYpWbVZDcENuQXAjinXJRNzS4dO8BCaOCdBUFBwSx5TY6Obn3_9KFfvBp8_nfTEwzdPn33_3hz_6mAK7ihMuOUtr7wLGENVMXc1cisQuMEGbg4YQWykzl-LuKSVz93Zwc28pbkdiZncz0S51iCg5pxis5VePr4uU3PihOzNT87Hv81IIQUVDiAa8Ol2T292L6d33X3vt3oNv_fH3hxgNwMiL2LDqrq-uuz4BIhnkLN35Nl_vJU-hT-iUVQypG7vDYf_zX3l3TPHDT18spVrgqlqyxEgA3hApKtqq50yYUmzfFyrahsfDZjXv55hCrQIAHDvV2vcdOB6maRgHM3MARydiyTXGwIxu3gy1KUREZA4cuIsNraMqGkIL63kkNlfyI4anj7HrwoN7q3WKZ6txPQQGZ2ZqkX8AbLxkbHkZUNOcNYtVwGpY1UpVNaiqSxFVk9bXVGvHWlFr5zly71IkxMboVzVV0Hbcbl1gB1U1hCq21KqOoqCAauqOSAToVU3Uq6qaA0Lrv6sBNt-zO7fSaSv6wrEl08ItiIDHJvKx3eBuzIyIzLjpx0AMRFVUzY4JdW96YBC1tqxsZE93tzZsAWwNYzUHdGZqNWAE4Eg9x8v1KrXicLtOHZ-kYFWZQpt7Ix_dZMssBqDmAXnsgjnMc11E3EAdcxVp-2s1JFQVbcJsc-ZQzSJhx_Davc3pMLQfD5FEQQ2ruQMEDqowL9WsPVKAKbRdRDudI7IhNqxwpNjwCGaucDzSoyMxmTszIxO6Bw6qGgM7OrbQP0AIwR3QvMkojtAkas1nO94iTAJxpBCoNVOIOWAz9VJ7VzgxtPw0UWsz0087F0jAAUO73ai3ok_rNRYVc-cAgSkgMjMDMhoiQwwX2_FyDNjEZOABE7i52Yvb25v93tBSSoGRCYkJCdRVGmMpICKr8__uD3_7-Xc_jGlw5GE9AjjFwCfb83cevvmlL-ACNKSzNx4dbsvm5IRjuHh4-tqX37n38LI_GSHE7YPT9f2zgA6IRSFutlYyB4pdny7P1hdn3A21ZAqIsZUaYLvpKfD9t1_vVyvs-mlaHrz7ps9z10cjWJ1stqcngWne7fYv7oZNTwzU8WZ72nfpyff_8HR9cjoO3__-pw---NbpJtw_WYtILTbflZPtyePnVxevXXZDur3Z9esEhuO4mXd3xt6lRAIcKJdiTIHDGxeXUy0KzkipCxXEHA0pcYhdZ2qxi0Qo6kvJYhUopHGUWkMMq5PN_vpFWeZxeyoKgNDgxF0gX2rO5WR1guBdP-S8mGkgTl1f5txvNnk5UOwwMqcIDiKmLswRiTjwYT-Bu6uLeLfa5t0Owcm1zhMTWfXP_eJXloP2fdyOY0oDAGw2w_U8393li7PTvguyLKFPdzf7d147z0t1BK1GIYDqZt3d3d6M3cgW5tslWyUOXkqXaL-7jaCf-_z7fWpPXXJ0MGuIMDg-GQzcYwh5KduT9XED6YAOxLQZY88MQLXqNGUHAuIpS9uImjk4VClmZqpIyOirLtXFq0ig9nkMU5YpV0A0xxAZAHMRO5YQPBADNIg3ikggDAHOV-OXHt3P1VylmHEfXEwUStZjlLHdq9vdH8ARVQRR33_9YSK6vpumOSOyEe2zLIvspmU3y900VbBxjJ892825VMDDUpZqt3d7c6xijlBUzHCaFwKuqrEL7lBq4aOcDwxAVNrXt7WMApjYEdYiojGGfuwDh5ASgQcOWo_9YSnVwQLHbhjKsozDKqSIrWULxETnl-fgQGZMFFNCZECjFDnQv_nf-QvJwF2ubm6fP7_RpSStixhTFMkD-c-9944VXarc7OelaikaI4_DQOgPzs8ebNcmtlR5frc8frmvTFPW5TAvS1F3BL2ZDlfXd86ROJRaxQwcWt25Wi0qxKRaQXG9GnOttSgjpLFzg75Pec5zzodcl6VaOwAAZTFAWpZazZdapT033ZiDirt6LgUJxAz4-N0HeJxvpS6ddulPfOGdNy_vbwJXhZtcPry5e347zdVyqTWLg6l6RY0pcccienWzjzEB0jRNzLFIISZTIPDEuD_k_aGoCSCWWpBBpabIZZmbfStEqiIholepLbwkaqKpH2qpjg5oeGwJemu1GhiH4OZNDYyMzcsW-uiY__pf_Sv_9W_8yykvy1zhuEcwBZBcEbyqMjoxAWhZirmZCrUCn0Gt2dRCCC6Kx2A9tvMYorc8hYkgUa1LiL2bSlUKTG01HUPJS4ypne9FWuKItHpc9RHxk49-8gv_7T_zww8-sCpAgRFVqsHRRo-AUktInZYlxgTujgpVOHaq-ipx0U6w6u4colo9thCxRWQdEY-IdHcEIGZvhqZW8kdHN958_ufcwcyHfsjzEhPnWoDYxELiqlWqEmNzo4KbSR2GlZkQ0TLNsYuITEiBwd1i7KrWgNAYhibKzOBORMxIFH_5Z782OH3ro48OGSYpLx4_-cKXvnj12Wft7FOzcIptnImBmoy6ionWBhs39YZndxNVYQ7uKqZdSGqurq233n7RsRu0VhNpqWQiNlPmpjhoawY1sdc-93bNh_1hMXVVQQRTFxVHZyLq4n43MwMTv3jx8ld-7Wd_8sOPc8kKNOVGLQUTmQ8zMRFyrVry_OZ7r12_uO5PtrVYKYsBe6Dtqvva599Z9929s7NPnr0QoDkXBIzMrrqUOuccYwA7HnkAKS-ZUzBTQiomKXRqim1fxsFMRb3mkvq-ShXRrk-1mIOLKDEFJAYkCgig4GOKptYavKuhAzUiVLHm2mCiFENLW3Qhdh13kU-GeLZOY9dtxjR0gRt2tKEzj-00CIFUzd0NIVdfTA2pFgV3NTMz0UaiR1UTczF3RFFvjAtCX41dZHYFdWs3OGmhP3UHBw61Vnk13hYFNchFmmjA1IBQzNRcVQGwqbgAgzmKKoCnRF3gGNjNiQgJjl9gbTfvQIh-rLo6vnIAtwD70IWO2V2JwOBIJXJHNwdCNSdCJIzURIM_rS60PjBoO_W3vQIQoAF4x3hxsolIBE1WKw7mqsd9RYzeqhEmSG711WAwsKkOKQQidVmqGYfD1DK9rqbt1CT1OKNodbcQIrgRQNRy_3wTiB0855yrELUHaFKppr6IKLiAI1IVdYT2cWIiRFKHtiGMMeYiRABA1rgEiAQNCQXenpUI7eNGiKZGdAS5gqO6MSNRIAdQB0ImZGx_eAMUHGf1RwcDNSashQbpbqkqa01sOE6ECLFJ1toQoF20zKk9m9xDDA2q2rYMRBgQ240zIgUicyQHcu-4rRzAxYHg9GRYM6_X43o1zMWe3-6XkrPqolrUBMCRiliWarUuov_h_-Of7D654RAxRgzUn6xXDy42j-5fPLhfb5f16alDOD0_255tTh6dB0zd2VmK6z50YAGYOKVaIQ7duN1i6m0WkYKRqOu60zVgDCkx91JL6DqkoJqZ07C-2Nx78PLFy8OhDEOvVc2KEVAcHrzxxvl2Pe2zLgVBQreOY_LsF_cfktbl5m5cn3SX25u7Q7ce7w_Dtl9NU0Ui0Br6AEiceu5T1bLMte9TFzsDxRTIXBdZn49zkVyLiV2-fjEtU-goxLjM87gZay3A4EQnFwNBnKZlfTpW02mapC4p9mIeYmDklOK8P5R5JoZxtXW3cbNGAAJHRlPLIifb1W63H1brab_XUoeuUzU1b-8eETk9v9BczAWZY-p2d3dps7E6swma1pJrnseT0zLvujTmu90w9lYF0njx-sN6mFdj33VJqcaRx_Uw73e11svVuO5DNl1QHmzGPkTJubjFLpjqyXroQqdW07iSXOdctpfnZdltNtvD7vbly_2v_OqfjC0f2Eo-YEzBtYm-uG3RiOh2P12cblp7CB1VrSFquxgMfFqyuItZLrJkXcRE2nPSXwnOkQjPTjZdpLvbu3GVpqlUMQOYc6XAx-4Uei6q6mKuZsTUnnGtHkqREdVUf-5Ln1PRWmYgm0qd9jlny4tYI7iBm7cRIaoagAFBAP_q597omfZz_uzpNSVaqt1Ny7KIAtRczOxuNy9FX97ku2WuYrnInHNelhiDGiylijsCVTE1kyKOuNmuAoXDNKOjSDX3GKNa08BrrZpLAYCqJiIGThyrCKfQ8A51qYw-9Mka9QGPqvZAEUy7rmNmCmTqHGi1GpiCu7qaA_R9V3QJFKqUv_HX_uK9mG5vDvs8PX12FxL1fV-qemigRnn3zdc3Xci1XO-n_ZIRqBmH6rLcuzi9vxnQfTeX_WG5qc1H5dOU3YEZz09XfeD9Pk9VcrGciwnUxjlGrmWpxQAQCEx1XI1AvDvMDtavx5zz2PcxdtP-UETcKaurawzB1OZcmsBRRO6mpYjs89JCkUUU0Q_z3M5mLaIJxE11wjGp6Nfff3fFMXHIok-ubn_w2fOr63kvZTflUqTpPikwKA6rzosf5oUiiptVNURrQzKOYBY5OMFSyn43meq8n92BWoB7NtUyLQsCqhTJyoSgKlqZkNyQuNlXrC3V0biLpoIAyJRSr6reGvRtcQwwnKw48jjhv_HX_8J_9p_-k6yliEmp7magbg5oViUwB-a8y9ShasVADuAqzRXqgQCAmWqVJsEMgU2MQ6Qjic7VHImZInPL-DoRohkGdqDEQ__wot7dNbBKCIhgQNTuIQHp6c31l9__-icffYxuSNSGZeDmKkABm1u41X-BUCtS4wUZExGS6aso0rHX6Ob26nIO5IAAakZEiE5ELUgNZhRYqyIBIlBIoZ0X3YxTbNQ8AI2Ral4AmBPnaU6R0TzGHpmm_R6RVDWthppLnhZmNkNTdPPIgTC4GCOEEKSUZc7zXIfTs8lgN-eTdWL3QrmAZYbvfvC9b_zyz2hdwCu2I5WJgzpgmUur9TkxpeDudmwVGgLkKoaG4Eg-19yYg3ZkkaOKllIBIaZkrt4eXOBmyiHVMntVUaEuMtcnn71EB0UDgCqibsjsDkRkVdDV1MNAVy-v8yy_-HNfY4bIGAMR0VIyJkZyNAOzjsHnkg_L5nzY724hgJNV11zAuvFbH__YkC4u1v2Q0K0bOlHJVTAE7sMwdAjHQ5SrNx6oiqoiIplAKZk5lCqIWIuoiLtxDPM0g1OV1nIEJlJ3MzMHMWckJiIgsQaf8MDs6hwYECggBuAQYghI5OCBKTA-fDCuel4l6pDXfUgpOLOji-hxQXNckLmIAToiivhSpIrlubjrnEtZNC8y7cXVnMDcazU3rEVFrR3iGznCDAxd1ap7lZbLJ24bLFUxr2JGr4Lo5szobViBzkBqXkzcQc3JmZHETNUMLFeppbZkvONPkRdIhMwc2njbITJFosAcuH1kgJACB3KoeWmN4YAtYIaA5IRq1k69CKgOhORI8AojCm0l2F4rBAdXFwMF0TEkFzFRqbVa1SptdWOqDbdftOQ2I3FfchEFU3eDrospsaiCg4HN04RECuDWpqYABE4O7u2nIPAO28rGTk_PAjKIuDmapEDcAotaDGhfaq4GSCkwIfSRA0BkikjuoNa2HQ2-pg4t09Tm-sBMROQA2ZQQmcgBxDS7qSo0wqC3qxc2YD8ThoAcyAyseZ4BgNzRgQmImpPFzEXN3ZG4GeICUWjvZ0JAb-ckt0ZoRmbi9rwED4yBIUYKjAEd3ImACRNTH8KQYmDqY4iBmIDRzWQppaFmgQAjmFYwr-aBuOf48Pz0i289enR5GTje7fPjl7uPXu6ud4saRA7iYCF88OEn3A3UD7maegrDyWp9jkaym7YXp92QtpuxG-PdpC-e7bFPm_NVP8TNqt9u-s3JZnVy0m-60MfhwWlRwUDLUnO2OAyn28vhZD3nxbimVWduqevAsVuPXcebdepS0MNtH3gVYVx1y7wMw9DFcLOfh2Hsx_708iwMfH5xenZ5hgmXaZoDaPV8NR9uDwwynIyx7-MwdEAnw7gZxz4GjkjuBWw8GbPJrDn1qevisO5pQHEbLjb9qnN3URBVRxhWQ9_HUsp2u727LiH0dzelySmnaQ4xrM5PI0WXvN6MVYpHUMTL119DounuMKxGK2K1IAUcet50PHaY6HZ3GLZrI-nHwRIVEO5CraXrBzANMd5dXQ3DChzLkmMIrr7c7iN1lhUVooNPc51m4l60xhQAgyM8_t53Lx-db9er0-0mBnx4clKnvA50sd1c3eRidnZ6crYaTeB6rtzR-b11DEToQx9D4H7ssGelPJ5EUC_7eeiHeTmM25M87c8ut0ezn2jrOSooMRKRgQJ4UTtMs1ittYoqOLYmEDDf7ctcZclCBMwkDRKJUK1QQKBX03jEEIODz0vJ1WKMDkaBq9ntfslVS1WtUKq0305xbelnM1-WUkTFFBhLyQ58cbLRUrEKgDM1kJpKFWxYE-I2R3V3EcFXU8bPP7rfOeal7vZL7JMSv9gdZtGsejgsnHoFMsRq_vTFy3kpS5FpydVQEKp4rermNdsylxA5MHKkgCCzmNnQd-KqZlPOUy0AWESrWVU3sGoSCd3dRV1LaGkHJgDvIrpqLbIau0DYpT52g1cE9DQMt7src0BOgWg9rtLYi9ZcKjCHLs1lSSllW954cP7mOMhSdvN-Wcr2bDMM436ZC-JSq6iY2v2TtVbPVWuVIpJVUky11vPz0_NxkOyPn10vtRbA65v9zc3u7nZftVaT3ZRdoSiu1uNq7NGUAFRF1KtYFalVXQ3Meu5ONlsOZOaAxszTbooxmfP-dl_Nlrnsp2nJeZnyfiq3-2k35Ze3u928mENkQoBVGghYxUV0zlXNqmoFn0udc7nbz_tlFscQ6d3X7l-OHUL49OXdpzfXz3aHx89us5mLl7kY2Sw5q02lrtZDo0rGGNAA1MUEDZAY28gZAND2t1PJ4qZSC7JJLcuc81I8mYNpWSISO7BbhwEM0ACskd3AW14jIDIQkZbSsBwAgKjEmEs1JmgoCMRpOqzPTt7_ymub9XB2uYVISACIda7u2NodSNhg5dihiYC5lcoYzMDcS6luTkBalSgYIhC5udTiIhgAjwFYR2xwP8N2YHepIqkfzx48gM6mz56ZuDnEVSem3tY6YgiMhM8__eydd18jajPaBtl2RLamAQUANAxUVZCDIVUz0dpqfuZGgU3UoTGzEcFTTC5mokezqtuxWHekMiKFdkQAJmRiUCdTA8TUd0VrCJzzwhTyIYfm-gMwEQ6stQYONecqVawEolqqG7qpeWlmLK1VSkVHU5c2pTAgYFLsun5_t9_vlx8_eZrF_vSf-MZJN6Y0uPt3_vC7P_uNdy9OVubyi7_y5dV2IGQCZ4cYuM6l_YEGVMwCsZu10T0RmkGgFBzRIXUduLsoYXS3NI5SSwpdKRUAVKXmKRC7AbiAARBWgYdvvfGDP_rhZrWupUK1MmUpGdzLUhEIiMAUXPOU8zRnWf7uP_zHr73-4OLeqZnVXAMxJhYRUZmXZbe_qWVi048_-HB1_pCRpSyIwZyULKj8zh98uC8Z1EYi05qXY6TYqyWMapZzGbre3KyNIFs2AsHVhhihAXlaQgfN3JgpLzlEZiIkdzMCVrXAmEIMjComJsyhiyGF2IXQxUBgfQoMGLAdeYNqTQkjOqp1MaQuIsftav3wYjuEEIECtL_QidHBTV29jcBNzVS8iImBuqt6EZ2WUqssIlVaj4dMvO2earVaqrlV1eqyWo9GJGpL1aJasy5LrqIiCogN4ti6SqWKKYqKiULVSGgirl61sENHsR27AVHcXFvUCId1P4x9M0KYmbWMvtrxVN5IQ5GQSI8XaOQ2gHYncAIMIbYOUl7qMT3U6gDHeA6YQlFXa0-7V3g_d3RjJDBonitBI8LtZjOOfWD2hqekdkI_rhVSH9SkiKrDbr8c9tkQc5X2B3aRyY2JcrXDbkEKJSsCcGRmRIKq2i4gBEROSDTXTIhdn8YxSG5jc3XEY9fafFmWORdz5hjVvePOzdCPYNTACO5FJKsagKiKOSCKtedZEzAbMRBjx5GO9GigQJHIiZrMwcyO1t4j4MhbgTEiMoUW8iEM1gZLAA5QbCHCwATg3HajDDGAw_H-FkJ0sNjCPI5uYMeINYAhIgaiPkIfaQzYBUwBU-SOiR0DUiDiSMTHH8Hd-sTHXjLSkGKppZSiJu5GxAEwOvUxPDg9ef_1yy-_-eCL984enJ6omarMpWCATeloXGHX9Zv1ycUW1FgFcmWmYb1igLNVd7FabWP83BvnD1-_2PRdinS-CmPHkWm52cks4zjK7rCJbHlmDt24KuIJ1XPuUxpCt1qN25NTdLu4vOhj2m5X880tAJ5ePGxtEsAkEDhgvtv1ibs-qYJ6ePjwjddef9B1XTfw3e0yDlvvIp6Pq3Uf-03OXmodhuDusRu5i-OQUkzDahwYvRYCcMRq6mCxCx1zGnpWDKFDQjQHB1csVYaT9eb0hMfuzXfuU_CLe6eIdLHdbNZDx7TdniCQVXdV9vaOxnE86YaNW3nxw--PfZSsDnB7My1V4ibVXE2sCXH7scdSZF6QKMZUlvnsweumqqrDegAAyYUQhmEgqAzopppnspoI5t0OKYbQx3FTlkwhyjT3na24m28nybV3eDCccPXXLy5oCI9f7KZludysH2xWiA4hpr47X60h4_nZGsBPT_rXH130wdabYejCto8MMO-Xs-3ZuE6Si1U3R3ULRIExULNxWxVVN0SbSg1EQFSKVlFxAEJ1M_SnL253-6UKiljqkiMqSpe6PsU2WgiB0WFpAxXXeclivsxSqhyKVNNmxlCVyAyOy1LBsarlokWs1eeRsdn6qqhLRhCxOddapGqb7jA0eqD70aVYqyIjsBvZZkjnJ10WPeS6uFMMUpxjur07AMNca61S3cSMOZgTGOSlKmARWYpqVRCQ2iY03rLpqtalVHLerjZLzqbCIQLy4TCJ1RhC06MGDPOhqFuVupRcRNTETZf9UvZLm5yVXNWdOTgCJeo2XcO0EwYpWUvuh56JZCplLkcwOFLj348p_vW_9uslSy6Sui52CRCXUs1sqTXXCgwXp2sEudsfDlNW82E1xK5bcl5vV_cu1qnDxy-vDvOigFfXOxExx2p6vj0ropuTvpqLadsGlaWKKgLVuXqRknOj57VaqjpU9yrFBESVI6duBPK5FnQUUVOpSz6La626LLWUuj_M-93h7jCbNey7qSuQA7UcrEv1w24uVadpnqYpzwUIDrv57ftnBnA9Lx9d3V0V9RC3Z6fLIedFyHE5lP1cs6kjKAI4AnHqExGFLr7SxVeTWuZpnqZpzlnrvBQ1k2qyVHc1qCJZi6gYIFrNVisj5GUCVBO1KlJq46A3bD81JQ-41toGwXkpSJz6wGAhcEiJmWIY8m7607_2y-X2bnuxUdWlZAXjCOgaejYTU0WEWjMxGhgBMKJJbW03YtCltiO9uTXpqeNx-eziBqhioeuQCdwYHMmZAyi9_qWfJcaXn35iSwUwYOhSUBE8dvEgRiZ3Eam383DSWzF3q1IBQXJVESAE08DBpYmLTLwaE0VCAEInIkTydvzQ6uCSCyG7KjVCY61gbg5M7dusaTbNzdsw7JjhBuDTz_9sGgetoiLmkFIKMXgVJmJmIEKEkrMjAmDsUpUKpl03EPG8zEO_riUfdQZwdG1aS-CkaCIcYojJVZdFUuQQ4EtvPtyM62__5CdL0byfUUWy_Plf-YW33v38D77_k88-flFKFnW3klKnZhjQxFXUTLsulmlxRFXvuq7MOaTQhX4pQtS-nrCduo56NiYmqiKMwBTbHq0tYVTs7S-_8-PvfNB1nQGYAgYi9AZyGU5GyZXa-Y4YHRix5ppSvPfw_qOL0-__6GMDNMduNZSlBsJlKSkFVQ0pqOrN0-dv__xXX_z4h4GDzPrGw6_dvHx8erb5__72D778zuVXvvT2Bz_4tGk2aq1avQ02s0jbs5ZaAzO4u4GqRWarSswOYFLQ2RFX_abUkmKHTbNX1cH7EJdawbHngICcIgKESO3dGxm7wKIaOQRGbY0QJBFthq-WwRnWfUcpEY6J10PsO4rhGG_jlu-gFqRiB3eFqhUAl1xzU4sXLWLiTsANWO9oopqrGGDbI7e-zHYzdhyqeK4lF80Kqg5NPcEMDmIm4o4gBtoOkQaBKDAnCilySMFdcxVt4Rxsj3ePzETAzGfDwIQEbG6NINOE12DNBebe4ivwqgsMiI6N0xeYCDA0yKm7qIAfATitvdcsOse7QIueePtsNZQQGxgiqBkGQPNV6jd913p-8ErpB-BEjEQcgwnkqXCkKg5I5mjuQFhNVCUyStWsOue6mNfSehEaApmaqLeWRfPFQVtPqBMjm23XA7c-Y60AGDhOuc6lVgFxLAIGSoxVBBBU2-MFW6i6TdwZyB26js2PRmOgV46zNgVqKuVmVABnRAZqR2pzY2I81kcQyJ2QjxQla8I1p59eD0jdIycADNTgTWDgAdHNiFrZC49wKEBwPALOCAmQGANBHygRuEJECsGHyO0W0SVOgSMCGDDisWfsTkxgLcEE6ICR5iWPQ8fH9Y0hOroTAVjL0bVFkcUuRoQu9rPC3_sv_0Xqu7ReIeGQYkxDvxm6IcQhRqSI0ANOS-ZGhHXcrHrd7zvTQ5Elz8PIJ9sxMVnW5Xa3FDGAMETuwhi7JS9uGpkZggEA-npYlbw8enj54upazDghM4hjXK-eXu1eu3_W9-P17W696q5vrmeTuE7u-OnHL7YXpy8_efLwwUnltLu6U5B7b947Xw0nq06s9l3yGGq2acn9yXo-zDXPjCGuOjAzM3DsQ3SzFFMVVVci6MfBTVbrdYwRzDZnWzRw8BjTMmcK6fr6BVMY12tTqXM2rZFjf7Z58vJHZ2evuZbt5el0eztP5fL116eSBaTveIhxSN3rD-7f3dyM48qkqpQuBRfou5RSRDUrhZDcrIisN2t3v3l5M6x6RKrTwUTRqpXCfVKMisjRA0VdtF8PWjPT-Ojti2U3bc5XAtB16faunKy71x6dXb24G1fDg9WYYpjn0g9pID4_G3Z5STHlLJsugZoWwcCHu4OjDON4uLnpEqL7bj-99fYbwREDM4AZUgBV_yn8h4lKEXHdrtdtlNiKNCJmCFVczKclpxRCpESRiSNRKVKkqruIYtNsMzjCauilChM60iLijm2BRkxVpBo4IHNbtGHLI6mbWtPwgVi-GMLFdsPMgSgyHealKLSlmLgC4SFPgVPjhzJ6jPi5exdgkMVmVXcoxZACI16crD-7vpFc_HgRoeubXexTyVJVVdoawdYhzEWmOQu4qMcU5qXEEAJTWYqhRqLdlEUb6c2lCBOpQhVpg4NaChKJWs7S8IxaKwcSEVWlFGoRM5dqsUsGGFIwlcCchoQQVmMfAyLgyfnWmaSKg4dIs-Q_-ZWvPTw7lVKRkRIdDssiGkPoA6LD629cPH9-9wtf-bwKiOlScjWLHMVtHPt7JxtynOZ6fff_5-nPYnXr1vw-6GnGGHPOt1nNbr_-9KfOOeWqSjW2j6mS7dguY4MNUUxEJBMCQihALrhB4gYhIYFAEAkJBEgEEBJWFBEiiALCMTGJcGK73FS5qlxVp05Tp_va3a213mbOOcbTcTHezxffzf721l5r611zjvE8___vd9pvB2L-7OVhNQtEJ5gyAwZzrk1FzHsyNqOYZ2ImDAw345SHYeJEqgYEZrCca0Iihs12o1Vb7Z98Dcem4hFzq8tSASKV5G6iodqAegHUEqdue7gkWYERoYUSoaqRIyf41le-9OxqKw4_-Oz-sNRlNQNcahXzT16_8Yg8lgBqTSCilNKLV-Y2L83DzEzV3LyurQu23FTMrbV1XkTNXVXdWjOzFKBmaz1lTgEWEWItPNQaMpqJE6hoyqnTALtwPjMz87ouuaQIx4tuhsR93G6nQmk-_pf_8l-Q4L_7D_7xZy8f1lqjyZhTU7MwFQENJKCEKuoBYc6U1QSZ0B172Bch1C7WHSQzwwBO3IMkiAiYoO8nENxxHPe3X3j_0x98py31ItDp4_ngYVdsqR6BEEAcYnlItcWjJ08-_vGHAe5VAQ0xwJ25e5lSJ2B3J2pKg6syMQZgd9qaAXM_9AJhInS3fqdPQ8EIJDRR_Lz9gAguSl2kEJ_XdyNC1qatZWY3UXW1CIh5XcwjxMPQwwGwiSAlDMSItS4OyEThDcDVNAK0SV8yAgMlWs4LJgbGyOQMRMma_u4__U7K_PhmSClxIiyZt5vf_q0_eOdL7__RH_3whz_50MKCMZqZYhXBzNp0HKeBiKo2WakU5i7LcyAQdQlP7NpaT7A1EegEd3dpfYxOIsZIYa7mfYW0vbo6vHhTcmpivXULHeHuxJRcIzwsFIApwCzW6vtHN-dVPn314q23nkWAiorpui6EYADM7NWl6rKsJZHP64e__b23vvaV5eGA1j788LcO87K6PX22_92ffHRq-vUvPN-NuB0LEqchlzK4IgOKGxGFuol2UgpnXluFhGItzBGThmiV03JIidxbZ32OJSGgIeSSEGB1rW69TqDuEV5VKCUkLrmIW8655JSJO5yu7xWGMVPqY1dNHW4LgYBu_T3Q50AdgtlRWqHhAOSAANiqqbiaW0ATq9o0xMLN3SwCMCxaU4sQ9wAMhSp2WNa5uhCv4ueqi0gQOkSE91ZrP6MHRn8W94M5gBXGkmDKZcrM6OZqZpiw550cnBDqWteTHOf1sOrrY-skCo0wwkAERFPXz8FzvVbWy3kRrk37yP8Sa0fuBdoA0AAk7OyduJjXusETzNwsMDD6b4UAciIYCK7GseOHJNRcgFDdWqeZ9hBPIHFPyGNfujSxVlWamTn3J1-iQGRm_2cm4x5bBOjVkWafT_78cu_PpZRSCDu8lT1wblXBDWHFUA8gN3WzcAzzsLgM-wCRmBJydgAPIjS1S3rYAbrYCKD_MXAYGBNRb0P0tBgFmHvplzBEwkBwDKCIDu3O-bIBYcR0WX1CotT3MxZk0cNbaBYR_W4PzMjpEoHsDWpETMwBgAh5SISYmTclIQAYRsQ0pN2QClOYE0Dm3jDuQjMk-Gd85wB3CnCH7oxEcKRuNHDwjtPtg2vPTJ0alzN-_0c_TpRMpNW1DEPa7nk_7B7veRqImCkxERQahnJ9M4oLJ0LCq0e72ldnQJQKBrQ17t-coiSJEIfarJTSACpGGSdzj3CtbUiJ0B_dXnld8lAEwBLhOAz7LYZ_7QvPh7Egwn6zDSQD2F3vr2_2t89uF3aCeP-Lb7_17PGz7TbcT7OU65vqMQxD5pw4UgBg5MLbcbi92qkaED9_-vYwDNfba0iBiYabaf_k-vFbz7a3V8NuczydtCnncV3Xvjaapml_tVvmebebmi67q6vVrLNrNlc34DDuNwD49Op9Js_DeP34uUYC8uP8ME2bq_31OOysxXJ3evPRi-txOr9-vZ22m3GjGmBtt9lZc0JQkXEaEEFqQ8yt1mHMrTZZasnTOJSwoIQpUUk4ppQolWnEMlRp7vBP_t4_2b93NV1Ph_s5OPKU3nv_mhBvp2E_DXNtn5yXaRzee3qDzSLB68O6Gcq6VjeBBGNJQ-LrcXj3i09_9OMP08S7mx0aoMlv_IPfJOoFuuBEpTBYAMRqGhDMyczr2jJl9-4VRxH5Z6N7B1zVF7H7Y63NzdUjWmvNpFmX8kE3fIWFiKloScm9JzQvTpI-a_XAXmB0C8LLkrJaa-ZNulXFI-Dtt5-EOhMTUQDlNHQ5kgN0N3lJU6ehg7u5odmQ0C2kNRWpq6i7eBPTh7nevZmb2Km107wczsup1mUWSETMtakbuNrL02k1cQ4xlfDDaQWgta6v7-7D7cOffJzysBnHwIiIVld1q6IAkYhaFVHlnJoqBHSyS6uChKKq5pRSEEViixjGQl0tqUoArbbWdBwLUSSiITOoFcChlJRo2mwf3zz69q_8nC_CzGp-fJjXKq7emmbKT65unk8QHkx-npdqRomlOQG5w83VnolrVVF_fLNVx912SGMhxJw5AZxOC1J-fXd-eXf4-MXrV3cPol7KMIwjJEQmCCzThOFEXkXFFSnqshICMpEzBq1rQ8KUSn8HRUSISVshYqltbapAgQFIKtLlbtKkty2sS9_dpenx0OZFRbxpBPJXvvAMgO4fzj998eo419N5OS9Vwh2ipJLKAMgQSMQidj43Yjqd5uW8LMuyLk1F2tqWuVZpotIrZ8vpXNeKiIAmIgE-tyVj0lbDI_MYbkjYpAZCbSuXvM4L5YQeObOZgEdKjBE94mIiOVG4EUCIebNCmAgGhiHXv_4v_Lmb6_y_-zf_7Zef3qkKeISFuBMzBeYAxnCzjgE0lQBTkyAwUUQ0NSIg5iDE8FIYMDhzbxoSIOdMTMyOZkFoCs_e-dJ4s33xw-8hEvfDpPtQOMAj1JuIOGViTr0mWFsFkPvTYhjEOeXO3GboiVQA0wYIxIWR0AAsiFKXwrqbuWJK4d4jJBSd_pf6XMrNHHq9MTwM-lQMAJkcAgmppOi6Bi4MEDkRuCeiuizEQIkpcTOh1M1iANbA3NpSckmcZG0EQEjLsk7DTlRDW56KuiNyTjkihiGbmqwNLy_osBaqYcgc-Mvf-HKi_OjZW4qlrvDqfHe4X-YmzoUpj7sJE851rcsSCG2eMSyNaZ01HFS9S5tSyu7mJm6uooQUgYioqhhBRL27mZiRsGn1cMCgnJezqur96wczIGIARHQk5JQwgjn3k0qVVrUiJ0Jw91QyZMppA5QD0cEIHJowo3QcA4GImXitlreb9XBcH9YnX3zqpaqtHvHJ61NN_tvf-Wmt-o1vfmniQmClpFqbqm-nQkgYoGZlLP55YRvAMdPaxCHcdCyJiZChO8YjQNTgcvhE7-STzqVHBHQ15ZQco-QsauNQmNEhJIKYc84pF0RImYk5jzkPY98_cObMlDNfAkYQ4JddcK_fdbtIH3b3fi0R1SZ-WTjBal5Fq_tqsZhJgJhBps5IRuLV_WFelyZHsYfDujQVs6W17iNsFgFhahgxJh645FyASN3X8Fnbm-PJxFOi66tpkzMSYICqSpiaqkWY8zQIoWJU99Xjbta7czsurbbuJggEcrNQ93ALEOnzixDxwJ4oCehFPubO6INLP7H3xd1cHRz7T304MaZMiAYQAU6JAuOqjI-urhHCutahNVUFAkC0MDfpbAMDdwK1vvTo03VwuJiY-nfVNyF9WBgAzH33wB5AAYSYEPFzomqXDvexXy_rmpmrqBkTVvPQ0H73JbQIBgJkAEJC81A3JCJyAHALukzcAQmIgDESX4I0zJQTyuWWCP1FFQhB_QCBhAgUhBFo48AJnTG498ovjd8ADGQCgpQudwUNF8BLO5wQID6vDF8Y0nHBqwJcVAHAROiREhMiIZbMnHpPAXuFfRyYmZj7EzJM-1Q7MC4a5j55KemyVOxmC-SA3jgwM3dEd3dw4_CMkMl__zvfDWhgRmbbzcaljVykCloMZWACct-Pw7u35XRal-OaIsj9KuWUeF3qOABK3ecUIte7YbPN1iyXnEpOkMRsM25rn7EgDVMicNX1nSePgfDNy9ePrrYJQVV31_vDw_HZ86fmsNmUt57cXl_vgGO3HW6mcUp8c7WZz6dhoGU2S6WFi7WrbQG383k1NRNzbSUjhxXE3X7QteWE6_E-BYrM25KX5VzKqKqENozD5mo3Xg1lyNOOh-24qnJCDgSPJ88en9cllWxhw1CASZvtb_YKeppnBxh2-8ObJRz1PH_9Wz-bh3T49NPe_UolR6Y0jsBUMpeU1nkeh-H5s-dlnF6_fLXZ78RA3FWjf5Lqcri5vWJCNxu3U8pRxrK73Z8eTrIquxaAzbQl9f3tFUUwIbXz69czUtlN6fluN3jcTNP1dojmH7x1U8b88vX9tB2nTbndT2MadpuUJhq2iTOdTisl2EwJpL37waN93p4fZHN7o1LHNHhdy4YxIjGKSKhZBJiPnFsTDGAmjxBtEQHIKZM5lMIBIOK9EqPEi_snd-eDmHWGKGAmDjMLi_CAMIDW5P54Pq7rKn48rqHeI_vEFJ2poN5qW0Vraxbq7iru5uKmAaouFrkQIYYHApaSidNQMmDfT-YA5MSBCBZARABvXd9iICYEDnevavf3p_vTvK7y6vgwTtkDq6gYrq0BkoisVauoQyzLKrW5hzR1NcJkaswcrtKkSjuvdbfZfPrpp5thpLisTVvTKrK2tYkEAhGJuSvU1hBwPRzNxF0dfBhKINS1drBAdzFOhTMxAKTE4zBuduNYsqoudZ3nc7Vm5MOQoMDjqy1qE7Pq9c35tKxN1FSMEw9D3u2GNw_y4rQel7pWcbcAMoCqRsBN7XBemugwJQKsVZfVSklUktSm4nk7zKsc5_k0z5RyBFqTWCVh74dAKqXOVc1P53URMcTzXOtazbSTpObTCclUdZlPbthaCwcOkqqiikh1Fa1mGgG0rrWu61KruCESuGtTEe1NwcJ9g40t2ts3U1Rxw5--enOua7VYxN-8PrijiA3TICo96uqERng4z_d3p3lZams9ULvMM3KomzRlovU8m6pBmFuoMnDi5OIjMphkzmGOYW4WFswcEYwcpsOYwR0h2nkBjcTkpuHOBBGeEnYWpburCJUpSs5Dvn_95snjx3_229_-f_2t3_gnv_d7i6yEFObMoK2GeoCGVoIwEa9GmPuBG2qlXkjreSAgN0dm6I3Kpq4e0OM0gUBoBuHBMJTt1__En_rwx390_9HH1BP2OXXzQGdgUsLQCApwhMRdd-nWz8qDBao7JrrAsglNhTn1F5upRhAShrSICEDMBRK3pgCEiJRSuBGCdSoKIFIXBrOJceLwXptUt_D-snTEIGTycL756q-YWd8ijdNovVmBaK7ugB6Js4qG235_LVV4GNpyRsJhGgGwNckla6spccoZ-j-du_fTFCIBcy59eQMRzdtf_tN_fPDU1P7x935ymOf7wwnQ_vAPP3z83lsff_pmmDacE6XMQ7YIUWNEFYHEFmghBFFSUhVO5ZKvUEXObkLEnJKrQEAZptYkMIgzQLRaU049QYbhecgQ1kSQyEPRHBDzOJoopqQXADsyJ7EAilIyMqo6Ffrnvv7HdG2_870fqFptQkxmULajhbvKBbhOmBMRxHI8bm-ez_M5IbnGMtel1ie3N59-8vD-80dPnjz-8OPPMCVV72YYs1ijiwioC1Zy5i7B5pwSsroGOtOgbszUy-nmTpk6f5ITEiMjuxkzh_k0jibSa5qUMhNdtloJ3S3n3MsiQ85mUUpOFIVpM6Ztopv9lBLlxB2jGQjY7ySIESFqfsG0EBE00dMqp6Wpo7ojU7_B2AU1gBbQIlpTTOwOgOBqi2gzaE27H4AQ2IkTm1pTtwhzPzd1CANQiyrmDMe5LqsAkqo3beIIDP0_gEDv1m4cS6KB1lnWVU-t9aR-cwckF-tInOjarx5g7l6rDpok_Lxxj-6g7kSULvB7jIBAjD568c89CF1a4h4YiZg4mipTPNrtt0O59Pp73twdETgRODhaR4GqxaK1v0fdwS-hduy9BQzfDoNpnNe1b_MvBwCE8F7GAEAMd0AK8DKkKpYZ3X03lSkzURBHq21dmwGszatb8yDE_pRgZhFDQGD28L5fcDcIMIdA7N9ndNQwQsebpJwYkZmkCSXq0GV1ZyLmRIC9HZ0LPbra7Dlf76YUsRsyImamkuhy6PAI7IApT0ge7gaEEAGd2I2f3wQAsXsbHPpegvquFflCasuZt0PBcIJAAgJgoiFRYio9SQkIAIm7r5jg8x2OWncJIKU0r0spydQvfYh-z4jorYYL_LQnHs090f_8__J_Pz8oM5ftwMPEkbbbMaNPQ87MMsvbz2-nBB9-cl9P624_lDwy4rljCtUfXh9SYgw6Hs-B8fDZXVVNJelyevTk0VCG0-mQEjNCKkm1lZIzw9Pb_aeffAaO63q-3W_3-ytISKbXj6-maUxkCbOgnY7nt997vpnGm-stEu6u9jxk3m4flnZ3fyD0L33pi_VwyoAYsR5OrQFlqm0dtnsIN48xpzRMx7t7NJi2hR0GglA8Hs9JwcUPr-7mNwfkHKLrQ1NRa7qel_XNAZF0qfNxvn1y4x4p577DaSLTfu9uw0CbaVrO50hpfji6LVe31yAUCAFpWauRqgMldEMC0ghTVVHOjJRrXXJOTQwAcirTbnO8vx-GTIDMSarlcSxTWed2tduie8llXU6BvB7PhTG0WYuvfv2Ly6kWk5v9hpg0IkWGAc_H2tZ1fzNdjcN2kw3otErJpSReHuYM8OTJGIaZU53bfF4MgQnIlQmqrL_yy3-cIAiBA4PM7BIQ5L5PBJjX1T1226k_GpBZmgT0o616gAc6dMeLabPwni1AAFiqIgEQXQ-Tc7RzpZTMwgIs3N1zzqrKzKo9VYTRq59ujGweIvOQpv7JlnX52heeFe8hShD31rSKGaJ5mBshnpfKlyahh-lbj2_YINDvzufTase5GqCJrs3O6t4RBQBmuLSGQECQM8_LejicmAgTuYeYdXkkBNRl6c0qM-89I3doIuLepx_bcXA1RBrLaKIQ1kdRJooASJCBI0Kacup9Ss-AjL7bbrabyWbbXu0HpqePH09j_pVf-Pp8mPfTsNluOPVOH4E1Bvlzf_KXSt-KJnSP87k5eJ4KMT3bJVgtUJdZPnh2dVrWKqoOYl4yjzl5wHyet0MK97bIw7I0i3UVdVCPYRjE9HReOx2uNjFzNWNETokTc04lpfOyIpE69Edrkwbm-5udeyCAull1M01DEhHMbCrSWmJWNYdgJgBPTG4egSnxdZmqWZWGSO4honGpkiP2Slb4n__2L-2HoYl-_8WLu2qrgKqurUXCJqYA89KWWh3wvK6qxojSWk7pvKxBdD4vomKiZiGqZsaE7j6fF_eIMEBobXVVr80Q1I0gCKAb3jInqauJmlpOxcNNLaWEHsjoYoHOnExal8EygQOkkvOYNpvh5mqYX7351_8b_8pnH734P__b_-75ODcHMV3mxmCEIGa9CQHgfaYXAdqUGBH7EYykG0gRHAGA0pDw8yZbYsQLRbAHXYF5-87Xf-a7_-g_KSl7BJcE2v25QMiAFO5pLCbKjNo0CDyMiTvnftpfHe8fOj-BMKQpgpl7DxqhB3GS1voXhkgq2mmk_fSBgNCPi8REaOYXmrYHUlccAIK7KeehZ5wZgHKWtSFjWCQ3dSBbaxqKB1AiJJCmhCAqQGPKjEgQIaqUOcyR2dyW81rGoUzjUmspxdTLkAAsIsDBRBMngi7hk8SoFkPeNNOHVfaZHl3vTndvHCm8NYOPf_rZV3_xZ7gwMiQqTEaWhsnquroEM3e-UEDxVoNSAJitROzmOafwoJx7OINzUWnLPKchS5OGrRQqJasZhk2b_XI6Dlt2C1mVJoLeMQwMiyY25FSGsbYaZiWXccjSqnEARBnSw3F-5-n1d773492uLPOaSzKNgMgKBIGFtXkHFDaQMCCC-1cvyMrS6pidU-KcBOEwz2tb37ra3m7G8_1ps51WVZ3XaVtOsgYBIzOiqrTacuaBUhOZNpOZmINzV710oDsys5sSMQK4ODICeiqFifo5mHLuNlg3FcWraXvSCIdWpaQBIkZO_VilrQIzIKJDyZkLEfwzzS12-KWaQyfDeBTmZuZaS5nEveu11SyQWmtmzowBtM7CKQdCE0MHV2CCDilb-zXMvBt0uZQ6iy-a0EvKa3OAEHFzCAKHoIKLSKvKiK0ZUEAYsyNRySUixEEtcsKcUiDPp1XEQsLCiBImB3dGNAxGTATDkBCpn_z7DZkiPufpQu7fdFgHEFtYnziHR2f-QEB8vh4BcCRPAdv9NjORetsERWRm70BQBiKKJh2hPZRxmSs6QMKAWNYl5WwQCOGXL4cgnDMT-XYqGqAQS1VgUglmEhHwIE7MVAhEPefcqjiCWRQmIArxJlWUkFK4qVowqVo1B4Ax5yoGAO6dkUVrEwpmxgiMbmJAAMJufVF37NQfggRIRG6GQEgxDrmzAnNi8gtT1SEQIhM-uZoeDUNklzAQTADXU4ZAi0BCNTaNAAzCjilMcEGnB3hi9kAPY0QA6Nmhy8oGoceHnAgRKDECeHhTyb3z0IRLIggIRGIM7xEIJiLG0GDCAOrGt4vhvVPuHLDTYLvUGS411_j8s9ETmsgYxIjpww_vhxij5BpYPLYTU0hKo5gPU7qaOKc4r_L6cNoOJeVhlaZpPJyWurZNyku1tKXz3SnA66yvziszidhb776HAMvxAdQsYn997Wagqkm_8s6XyXmZ53EcrqbrUsY8DR9_-NHT60dYfXc1nj5-gIkCGMx3Je-mCcJ309BEyzS9eXnKm620db0_ZaSbmz2bzucGo2dmT1BrY4L9dkpEc1uahbuv7XT_3Ret2XY3jJvpdFrymKfNnhlw02t46eqLt92vuad4_eKVg5vVxPijP_zB21_6ktQ6jGleq6nlXJZ6Bk7NPI1jU7t9_vzFh6dXH3_49IMvA3MqiI5kCRBSGsUblwytiazDOBwPD9O42d9c3b98_c4X3j8eTirVpOyurl58-OLpu8_4gpGFVoNykoB1nVerw2ZjKmW7aXevwuzD7_729b_0a4dXjvtNGTKAw5jPsl4N-elXn726W37wg0_f-xNf9-b7qayLAEGAreNYbX39-ny12wkYtvXt95_9we__5NGXnkO-Ob14OfDw-7_1uz_3c9_sq6QwKCmsOafkwU0MAOdlvbraeoR1jAAa9bxjD9gFTMwS6ObAOKuNGGDBzJS4TNjt6Ys2EQmmZRFAGMYSghGuIh3ZdiEXd4YBwXHRbQYkSmmnHuKeOHa7Kbyz2ElNnNkRxEE8wkFEKGDMudOKKCEi7rdTO9Vzq-eqZ8GjtEQZMK1axzQej_eACZCWtoaHo-mqWko1zZkBoC3Ve2EvINC7U9xEU0Ikkip9JGyqCFHXFgEVpTUJorWuY86taVNlwnB3YiISMyBw9VbrsJ307ML161_84i9-45u3T_bHl3evTvPd_fmTj188fnLz2aevHVuj_MHT229880vY4vf-8LuV6Ol2-4UnV4eHE7C9fHnvkA0BIqax3FyVr73z5A-_--Knnx0e34ynKk1kHMfaJCOLu52XB5OP716_v9-9-_ixi9amr053zAjDNI7T3eHUxFPKVc8AxJTUFALmednsr5q0cRpPxznltK6NUwKG2iQxTePmkvJ2cOu0am5rK2WsdXX3XJiQS-Lm9vnhO_rdD3B4KUf3QITIlomQEZkDPSystWm3e_v59dU0OtCi7dXDPDc4nxtAJAg767q0XhOtqqEeauHRwkN71Arr0qQ2Dmii5kCU5rrebuk0VyJ088Q0n1cgUJOU0lLXzbTVtpq7mwAmW6ubA3pigjAGVPUgTymFOxEgpG5w6kOluoohPX33WSL41__6X__xJ9_5z_wrf-3JO-_-D__H_0ujaOEhTdQYOoBHzXwcCg6gtfbLcKAhh_WIfKh7lGF0N20tJBIlMAJAE89DIg9kdqkQBgqb26dPv_j-T7_7e5vdddely1q5DC5KjGFBOWQW3k-ujnyxUnZjZx7GnEnUKHOdJUWkTIkZQZFQa-MhmxqSUeYIQw9m5IxuypzAHcw5J7fo9PBOrcQLa1zdHANSKZ3xZaaYGNUAMMy6MJcQycM553E3rfNZzNwcgzgxQnTqtrZKiRx8bWdkYk7E-RLyBXZxIDovi5kwoYlIa4hYSgZTAAMHoKJuhCSiDHw6rcCEgdNA2-00JO6Oj_V-YaR5XV7fHe5Ox9XEFdERiVzdq0AYQXBKCNAR4wwUZqZKQBFe11Xdu-uTmUwVCRICXijsHRconAgR1IxTMrUIQM7EHBHEHA4ekDi7Wo-4cB7cgwgCME1jKv5HH38WYtZv4hAYYNYyEQWFgyMSUZhLbW5-vjtvn1ylISMTIr95sE8Oi035N__gR8dV_vy3f-FmMw1j8YhA5EibPBbkWNdwG5gQyC3cnZCWVss4InTGOfVHQY8-9txHTgkBEmDJmXoQJ1zB81A8IhdGCCRarebC4B4YxJE76sUNI5i55LTdbDbjUHICvQile1BaHcTdEQxRAhaVRU0MAnmpTZszJyJkRghDIvHoO2gzF22qJs3NoYkG4Co6N3EHA2jqTTUQa9VV2935fF7lXHVRW8xW1cNpeTiu82p11XVRCVdADTAADTA1RqrLuhnT49vt00fbJzfbzZBU2nmW86oC4EEGYBZDKdrMLRYRMTePKqbmTa2qWmBVNXeLcL_cPcARMBAhlbTbjAMnBnRz_1yzC4GdcgOIZSwDEQMCBbmAC8JFXIMEiD3WhQhs4gCwuDOiShDgNLCKm12AOX3obGYq2lG-5oKAvQbr5ikTdu609RZBAHrONDD3DwBEJAptypxUxNzUIgiaCBNjv84h9h2GejQNpkyAHIjhGaEgoQWGc2JkyjkzARHmxCkTdxJy7lS0YIT-KmfAzAkCCCOXNEI8zpwAPHxtjZgkQtXt8ivSdxwA7m5EwAwpU0ZkpE4WYqII6hNRwhiIICAnunyjgBHRGZ4IAA7uYGGBME5j37cERv-ZRaJSunGx55Qu6KduIFS3AACMJoKIgdFfueIubuphAd0H5xHuIOJqJoukyHkcuGR1HHYjgq-1Lud1nSszFUKd6-Hh_JAal_Tq9f35cB4Kp4RaRUV2u7HN82aahqmcltUJh_3IqQwlpcTzud1cXd1cX5nU0DoO-cn1zfU0uC2U2Nwz834zZiRtens9scUGy3azSUxtWau262lo67rOYsvqrYL68XSeCl_dXqWS3n77rTrX092agX3FkTMGGcWqa0rMiQFRpYXK5nr37lc_ePzkumw3eTvsH9_ubx5TybvbJ0TZ1I1JIFaRapWHUvbb3fV12V7vnzz62s__7PH13XvvPaOIt99928BaW4btUFKC8Jx5M47T7hqhtNOqohAACoVTQhqG4b39DTmt59O4nZgYQG-vr-paCdIwDufTcbvdpSET8TAMT99-LK15xDBNlLObQYJw2Wyn-f6BBgLkMu0hmNLYjng6-KZMh_PadGUVcrm93ZSU0ODJNm8L_eAnLziVqeS3nu63Qxly_tbXnwypgOFuHBLhOA6PHm1uH20yj9J0s79Rs9_63d9LhbGH6MLX1hRcwQzcwwxAw4mShXsEAJREphYR0jwAiVHC-sNZLXrDKoiDSANKypuSQa213rWNlMksopqZu4GHJyKKYI5aq7u4BwYORBSdJte7UshIeRqYGYmlF1nWdprrqtJTiEjkPY5In2sPEQG8qn384u64iiMipcXk1BpkUtJpGMLEzBydSyZEYIRe7wJQt5SzeY_URajN89ohjAAJmIOgG06aNCQah8HNAkLdpVWMaK15uLmqCVAgoZk1s3Vdowenm4osv_rHv_Uv_vqvfuG9W2hts0m7_bi_Hr_8xbeHwuH2ja9-8c_98s997Yvvnu_uMdqv_fI3_sVf_6Vv_9yXXfW0tmnMORUKR_TtNNZaH2338-pf_drz25urp4-u10WvNhsiwoB5rav6sbbTamMa1qCGlKfx-tG1AwzjdhrHeV7XKgY0LxUgaY9wORCQKxzvD7LK6XCOQMaUUx6nsp6XIef9fj8Mpa7VVJ0cGdQ7rTVBCBMNmTPlDloonIZh2E2blBIilZS6HcdMEyO4myhFcnU3kFbZw8FYbTsQRnz65v7Vp4d5ac1krutsdn849VNmqOeUUmICdHNTVWlrrdqsNe21wW4CR9dYRcMdzFS91rY2BNDaSSfOiVUrEblbgHcFj4dB9EkbqioguoeaMQElpBQISoWOx0Math98_We--Qu_cL3brfcP_86__-89y9MXv_BFE8WrTQs2QHcA1ZyCCUCV3V00TIkQwAnJLcKDOFEiAkopUURPvJVhyCURgquVkhkZIMAqgoPkr_zar_NY_vA3f2vcbcUIADvY4iIEyEm78LTwxRZqxpyICQPrqj_7J3-1YD4d7_ePHlHOgCkACYkphVqvgWPXAgKAQ2fTQ0A4uDtGMCOGMyd3F20dKohIAYHMn7vyJIjc_WJVM43L2QOYGRCo5KEuawQM2620VV1bW8dhQkjhwWXoPkXKZKYQ0NqSMge4tJWw40AiZQ6P5XxOJdVFPCwgeMjqZujaztQDThjTmD_69BMumZDyQNT9sRHTtrz85NPdmNUiArvXDs1Mmohi4jIMKoIBzRwKp5xaVTUHSk68SgPElFm1V_SwSeOcEDEQ3Cx1mQKE9cMVJ0cIvBSoIaIuGr3Wae4eqkYpqxhAgFmEAQAmfO_xo4x-8GW1qOqtaR8Jt1UJCBBqVOjPSUBOxMycUM_ncTd0bHLYuqp_en9-PWtbmpp982sfTBn345AImYgB1Q1zAcMpD4CAifq7gYFcPTGFBifsrHepRolVBRyJsadZCDAnLkNGR7eLms7dOSU16fUcRETktUnKnMfMiXIhIsqJpymXRNOYeksSejC6T48CAPk8y7qKGTTVKrY2b-pVlBA2OV-NeT_l2216vB_HVLYlP7ra9bMeYBhEZ4OezutStYm7kTlGAFM6H9q8iAkc5_bmtBxmeXE3vzws92s7iZ6rHGepLZhSa9pbCkPJnEuVNg45yMG8QKxr1bWZmfTOkCMCZszhnhEuxSFxCei3iN6juPioHDzAzBOzqbtar4SbqTt0-j8TMiMBmpvDRQHsoaoV3CBgabWpdMaQuV2aNv1iAQAIHk4BFlaQCRMSAdFa3bELQKJbifuyfxpKr2LX5mXIndQJAAWZMakKRoQ6E4E5EfRja_dwAQYy1yYAiEDm5n1pmMnU1cLV1YyQCMk9Pg-6K4hixCZjxvicndRT-1QIMxH2raiHqRF4uDMz80V2coHxJxoGev78JlHy8LWt0dHElBSg9kuJe1VViOpWW-v9CG3aJaVDSgkYAZghMQMABZhb-XyMwb0ng53gFIjAjESBHu6OGcZp9EB36PIZM2uqnFJvsffQY4_0AMbnOmH08ESIAEwEcenD9-twz0BEkBMYWAB-58OPBuacUgROucBc0bWKAsZuO5wf7gDADIdxeHfYvXjxene9MUNCffHZ4c2bN_fH5XRqh7nOZkGcy8DMZdreXu-vr_eppGFXmIADTBoxbaa8Hcq0SZ-9vN-O2_e-9K4HMqf5eADzkvNYuK7nVpfMKNJywqvdbjPkYYBEsN2UR7fX2zS4GCINu01dKib8Xv27hPj49noJc4-UiB1L5qUd26puNm63rVnivLu6QjV2QoDtNLJRQmJ2lCiIaILdRw663e_U5ObRdYKETZ8_e_rw4s22DOMw3t7e1HNLqVAhZgJgd88l3Tx5yiO38zFxHlK62mwpsQMc63y13zvA6eFhs786n5cAKkMBijwNy2kx7ajvSoSb7dbdT6eZcnG37c0-5hbqxDhM27tXp7QZOVEqJeXETH__P_hPn7-7n12GsVzdXD9_fHM9lev9lBMgwttffHo41CAGi_047jfDZqBzo91-rKCfvT6UIRdKY86EA2_yNG2245TzcPfpi2GfTUPNmZkCu_K8yiXfOA6juTFlZHZw1eiFvZy4P_BV3AKkL9cA1qZzrU0VAa1KWwU8tuMARBHhDv3sqwaBGEAWsIq2qplZxVUVkIackVnM1MLDARTQ1noOcHMhQuRLpIopubmq9rWoqRIBEBCDgZm5g7Wm1kxFUsFa5Vzr6bzMi1w5Q8DaWsmMCESZOJVcSko5pd5wQyTiy1fOzCpChKKKAESp1aaiTCRNS06csDXtskFXdwsTLZwhYrPZhBkDAETJGYkAdNXlrUe7_-yf-uMbpp6vGG82u8e760c7GGxeTh988fk7zx6lbHVdE9Ms7Sef3v_B9z_58Yev7g4rF14lPnj3Wc55u9lGRIjsM6OBO46cXAQBLACcUilpnBbVGtDERJ3LMEtD5tOy7jabYRpcdTnXRBwRZiFi_bUEBPeHc2ti5ufzqhbrUt1syNlVhzFPwwgA5_Nc12YRbm7SOpAbMVStlJRTrq0GQxCkIfemhprnRPurKQ8FEXPK4SatR9qbuqlZADqjhf3qL_8CGFWxH338ad6Vw2Gpos3ieF7n2u4OJ1FLmXWR5EhIai7NALDNdVmWWudWl7W2pekqYm5lSPNxRndCiDDC7rqxvu23JgEgreX-GRMBZEQGcKnVWsOOyMPITHVZwy0xlmEk4dvn7wzT9uOffvaTf_o79599-PLDDz_8o-__5NNXLx6OH716dT6LOFFKrdUL3kNNVQHcXcLUTVVUpTFBYiQPJsIANGAsYYGuFMEp9dQnMWI4kLdVEDdf_ou_-v3f-I_uX7wYy2hBThDUXTfsbgDo6oAOroHgapgQKNFlPgp5u31zf1_bsh232gQ5uCQzD0BAigggcHPOhZijI8ABW1055_6V9AaziAZ25la_kYeqAHSZmHEpro6IyMnM-t3ETCMMAN0NEWiZl5woEXWx65C5j7scIpCqLAbAKaNhwghTsKA0QBAhnI-HNBSIi5JQxZCpFO7NAY-wZjJXVVF3d9_f3H7jG1_b7LfQ8fOJzqfTqt5Mq-q6ru-891zVEGI3bcl9sxnffv9dYGjmARfUFAJGCwQOxJI5wrR_UBCIIFTJLRwYGT3CzVo18yoVkANcpSFBuDGRq1k4I2EgZ4ywlPOl5BhO4YRIDhgBFiUNAfGn_rmfX2vYWdzT9GjTmrIFuw2clnnlxNuy0ZOoak65x9RctZ7PUGMoG1cJlfl4Os7r68Px7__2d0ztG-8-X1--SWiJCFSnkjMX9wAGdEsEIsaZgSARRfgwboApp2E7TswpUWKgRCkANnkoJeeSiLh3gktJiQjdU_e4IIZ4jzSoB6XEqQQhcz_UEoIxRSbITKk7krjDKEG1m5ZxnqWpacC8tggCIOqZ_pTW2pp4qyrih1nPix7ndneY51anbdmMBBFNJBNKcyQKoH6P8ghCrk2qqwJW97n5WexcdW46r1bVz2tbmpxaWxapVXIezF2hSyfUHU-1mvjxuD6c1wCcTQ_nulZRtbXKKm2R-cl2c57XJtY0KsBcpTVvzUTdulK-2x3V3UGsp91DXd0tJRyH5OFg1pPlvXoK4eZdyQn7zWY7TGGGZsOQmTDxpWJgpubWKWg9UN7CCLCk1AdxBNTEVd0C3Nz9ggskZmZCh5wz5xQRhAQMmbmvBYgwMyEEeSBEn233ATUB5GEAJMLkgRGQmPsx1szj87Djpb1ElBiBIw-Yh3S1nd5_thtyLjmnxOkCQ1UIJ4gRcUjJ1TMhhIMHIpoZwedFZAIK48CB8zQWYgKA1kP-iB4GjIHUxNxAtbtvOvAnek4zerTILH3u7mXqBRTsJ_ILp5W72jwQguGyDCmEJSVGavOlOSuqHtFzcSK2ivZrnrsDdLYVMhJhCkDTAABxs3ABsJ71v8itwXthuUPeggL0b_3__kkhdnNXH4dydbMbp-2TJ080VFp9__13pu1EA5vqzfXVze2jJ7c3H7z_iJEGpHe_-DYgvvv1d2-upse7omtjhOtHu4ggjOvNBhweP3okVShimgZyRdMvvfMWmJsHpYwOTOn1mzdv7l6__fTGWvOq4PL05oowTFZpWjgmTi8_eZ0AHl9PX3nregplkO1Qximz69W4-bW3_3MpESQqOU37rWk8LFXVTVPe5s1mU-e62ZTj8agieSoRniCGzTAONBacdrul1WEYqDt81JaHszePamT-eD9xwJBwt9-4Rc4JLVDrlCjEpS5Tpj0zmFw_fb4udr5_MxW62k5DKuxu9fwwHyKslJIyl2GctpPomnMJtTFP03Zo6zyVrCYBaBHjZkqZ1zoP-03ZTNurHRAEpKvnT2KRXHjYDLTf9ZHVj37_u8_fvR5r_d03D3lKz3ZTSflmP-y3g7vuy0Cj_-Ef_SjQU-LbzbgfRsaYrsZNnojoeF7ykBnpy9949_DZYRjGw7w8efp2a1WORwQgRggiZHOIoIQgDmERGglL76GklDXQI8TMutAcECJMe9sIhsS90h7u7p4yEuJ2O_UgKDOJOnxuCMZ-XYdAoEUVOVJOSKhiF-RdeISrKoJpW3748dncTEwcqpioq4Oau4ZqgAMCMKWu3ATHu6OJalW92u9yToABji7aqphYnesnD4dWRQ1UQ6sc63w6nz979aZ7iAmhTyW0h6cJwR0wWmvISEA55S4DX89rx5yVnA2chtwVMQSYANGMgNtakcDATSWVxByMHKL_lf_mvxzK5-OyLudQyaY3lK6m9MHTmz__Z37xg7duh0TzqS61nlc7nvTlm-P9m_XF4Xi3nF-f9bOH9bO787TJrbXzef3g3ecJCdw_-vELabWu1lybeethGEY3--GHH929uTud5px4LOPD8dzEm9nhtLw6rMN2sM-RBaayrO3Nq8PD_VlN1E3V8pA5AYKrNGvi6iUPObOphgMSJ2JbW6KUEBMzAlzfXGVOQHB1tUk5b6ap45g1dBxLGXJEQAQx5YJgbmZLa3fzsafjFLRqnJmuNrmJrrV9Np-OzZfWltbUtX8lKtaquHjOWU12Y0ELcBNTYlZRFXE0BaOEzIwQCYA8EiVsSgFNGgYQREqMgJwo0Cnx55aMREjeRKsSIYSrGGdWUAALSnnaIYzvfevr2urhs0_vfvpDPL08fvri4-__mF2-9bWv_fpf-HMf3d39X__m_-fh7pCG3NsImNAxJAxTUjWm5F3n44oQYBoq6OGiSOBu0paAcA2g3soFZmIIB1nP8tYXvvLut778g7_zn7oHMrba6lIxAhANAEtGJkJKVDhReKSUvLXocHMXaQKYNre3siyuJsfju-9_0F1b0NlOKaVhtCoaEtihGIzM4YaI7r33zsTcdUUOEMQIfcDdew0XSLtKo5QutcCOsGYOcyKihOEAAISMgNBqvd1eeXMMSCnVZU2JXQXMpNUw6wyQVhdmkLpAIjfBMHBLiYH5YgWPcHQNDw8mBoJcOMwCgRK_ef1m2k37q6ulWXN954NnogtFuLs2f_HRy2ePHy_rumoz5PtTvbubKeVpmgBDw4chExCaugshhnf3KRBoSCWLCAS0Jq3koqYmrRM8Uk7WzEOQuP-6ibl5LgWBQsNNiXtF2DCltqyuDl2choHoZSxhhoGPr_YvXx9cvYm1s2JAULg7aRhgWy0A8kAQIa1uh8kiAMmB19NSGNPIzFTP7fDmcDzW11U_efNGw_7r_6W_mBPd3O7G_UBuuyGnjJhABkTqhto0TRNnTpTgoowOMUuF88ABnhITY1WZSkHs3QACDCJMzBOnBFhyYqacEgEwMYAjAFIwUSCYGSMW5mngMcFmTATQh9W9-W4RVb2KLybdzTFMEwIFcVMXxKYWiVrEKjYvqgqBBAzmsayq6g-LndRVgVIqzNVxDViqnldpzYC4aViARjSxuenx3O7P89qsmjeFpXptUDUUoxmclkXda7VFdGm2NpMadRZRrQarqDpQSY5RW6vS1qrnpb06ncWxmR9XOS-6qi9NxbyJNtEqNlet6tWtmlUVdQgHDEhjypldHQMx0TTmkjhRJCZO1IWyJeexDA7oEaUwRKSckdg7Xxax93gUsL9i16bW63Vm7lHNm1qfwAegu0M3hLlzYqQUGCVhmPcffyCsag7eryGJ2d2JQD3wczImAvQAzAWj7E5MBqFi4Zf2K2cG6jTPzjHyAHh0s9uNeVni89n4hbLfl5JMySyaSHeo9RwRIlp4YmZG5hiHPJS8LXyzKdaAKClGSejuphHqtWqVvpuhADADCzeAAPRAc7-IjRGaS7hgRLgjXJCOAZ4QCJ0ghkQp4ZQJKBDCzVe1PPA4lH7_QnAmuliFKSFS9AgDAgC0JqZm2rlwF4tzShRBiNSND5eOJoB5XKJ3_St2J-D_929-B5DVlBFTYURKZQgOQh5LYcBV5NPXD0uTlNLN1ZaD19V_8N0XhETOz54_Pb1-uN5e3b04LkdZFwUu6_H81uPr893RxT75-LPNZkxEhXmc8uPr6xTwcDoflgpML1_cNRHO-Xh_fPz4kUWkKf3oBz9QjJLSuqzTdWFK45BMjTFi9np3zISH0-FwOJSpzMuRGRv4m6MAwGaz3W3HAGNIu82QGG0xDxh3kxukVHhMVU2kz7ENGCgxYoJC61rHzTQN42a_ubm9Bm-7q93pdD7M8t47z86H8zgOnKktK0Rqi5wPxzLlPOT747m1Zbedbh7t97fXZgFqy2FJBNv97nZ_O5_WAACNnMZUytXt48Obh_3-GjzIjYIQKBMjgEjjlMwMiVQcDJEYck5lUsFHbz8fd2V5c0Yu2_2VB5dSVOyHP_nsZ3_263iuom2ubZtLq3UzlHEoA8MXnj5-fLN_czhgeMq8LePIw27YjONgqonSMOUc_Gi7efxoxIjNzX7YjXnY_Id_8-85epiraUpEQKoqqskjMbbWaqvRob2miHSDW-8QiMtNIChjF3JL7wR7uIeZZiKPQAsmzpkppcAI6JAeACbzqOKiuhkGotTv6SYt-nTMbF2PP_OlZ3_5l7_167_0s__VP_3N-fVhBZzFq4M6irqpIUIuTNzDnGbmSIAcbz-Zzmsl5s1mfPr4ajtkAgOEUpAQGBETIvTLhVh41daaEKIsAg4pp0BQE0ZyNVfNKXXBxnJeTMzcgLjWWsZiYoc39zkVN9cmEChqtVWRpmCBZuGq5h3ZLtbH8tN-84zHdV44425Ku03BtZ3vDrtcbq6uSlBYvHxz_ujTl9ViFl_VZtE3p-XDl4dPXh4auoTNtX32Zj7OjYe8VhGPWeR-rpvdxCWVkjOzaKurnOaVE66E14-2T26vwv3-4XTWOK7tXFUjdlcDEnqVOi9MMG2GWptYlIIlJc4pmPdXU-KEzMOYibFMg4is5yqrdIWTizHn1tZgXtY6bTZaZRzyNIyXMlNYJhzHPA4Dhvd_2_AgMEbKJZdxzHka89BqM_BxGK9vd4-2wy5DOP7j7_5wPrfjYV6W1hY5vT5q86WTm8yWtUqTZn48L72YXef1_v5oFpyzioEAaFhrBUnqikhtrUQ9_EJq2vfLTJA4abUgBAqzgACpjdJFB6NNMALdKRAcHn_l2eNnjznhd_6Tf2S6oqutJ1vPgBYQf-JX_8x_97_1L__P_if_xj_9vT_85KNX81qPbw49qWZVwrr0MgJARfDSIsNO_TCASBQAqk45u3uEE7OFaW3hgWYaEhV-6a_8lbvXb376T78TDmpBTAggy8pDCQMPj-7TcQcIoizNAnr1LjiVXsZpqzx-_uTTH_0QI17_9Kfj87cQsGrNeQOBTd2ROGc0CNXo8hAunLij7TkVi8tAKgC89fd_hwE7pdwDPwAIxBYXeSv2-SBRdz2FOWUOQL7-2i9qU0SCRIDh5mpexo37JdMCgGMaAi4EvM20lybESdeZUgaHMu7VBFT7CKLnTJjITT0QiUsZwg3Mpmn82heek-BynvfjNqfhN3_79_s-HTGRyZ_8s7_43T_40f39fDjX68dXbVnCNaXiZnVZO8Gob-CZ2dw6acTVIIxTZk4IENAVPZCIiJPUVkqJiIjgnBCIAaNzTiDqWodhcIpwSik1VWYGFQzIpRfygcIBrBO7f-3bP_d73_vwYZ4VWGtNBCqmAMEJCUvOTVpnhmpzHsjBzY2Y1QwZXBkioKOaCCjn06F-8NbTIfOr1_eL1nG7cTVmTIXRQcVKTtw9F4YEllPKhSOMOQEGRiRiBoxwCkCEaRoDgIlTYoTglGprPDAhp04CciDCcRwZIcy3uw0jTuPoZtOYE-HVVK63w0CYCHPmLs-KAFH36Hl9RcRcUknZ3ZvIvLbVrFmYx9p6dQItyLsYWGxpLRzOS-uM-bq2lHFpuqzVItwMEMDCNMyiNW3mGtB59ohEiRBSR0EHgJpDb8VFiFmXV1xKzG7isbZmEU0CkdGjmdnnjd1pGJpKIJqHVOmnQCTwrkkMFO_pIHUAEwcIQswll8L9mCwqiMRETGju0hTQc6LdOGyHIREBRlcYUBBhQqQAzDmHg6qKOqRk5mLOjOAxDNktmqt7BKA6uEXvDIc7MSLGZsjdh2WmahYAjKgB3fzVzcOISJmZEByDLpdAYnbvCVMfElOiusoqFr1600_7AQRoHkiYGD3s7evNnhENzsvqCEikHkiEhISYEjERM_a12yVsEM49pBiRiYchmSpHbEbYDTlzWt3UFAmbhAXIJXyAHiBhHY3So_jeSUuXMVn05DB0pwIihBPTBQEa0ece-bIsRrfIRImwMD65HjMRd-5SdBoxx0XiHNwdLYiM5JeGN_QWAnNC5vvDYbfbeHQxAFys9tj74Z-ry8CRmSj_H__d_2CTRygx7sf9zWM7LZRzlfr46c2U03YY1rqaW8oM5pnT8XRSU3FxMCSchlLntYxlET22BimY8Wosj672iUjMA3Q_jbvNeJ6P0uTrX_3iOPDvfe9HmLhMhYDPay0DTyV9-UsfmNR1Pn35S19Y1-qQX96_fu_L71zlbUKctsPp7nRzs3vxyeHT4yHdjPev5ydPx7efPpe6VlnN18xlmzabqXz26ugR77339MXrQ0SgE0IehmzNS2Zrhol1kc12c646Q2QArTJO437a9MVX5iKtpWk4zUfMAEDjZrq_u99uduqm6vP5NO52m_316XhiwudfeO94_1CbqfrpdMdA4zhpuLgMOU8pn-c5D4lSsghGzhnWZd1sJhEj7vMc5UQpDWY6jGNb1zIOgV6GiRh1WcqYo9WUB_U23IzsuB4OlNEAXx3XP_Erv9g-_ezDue6GPA4DEnJAyRkBp23BxJ98-ubx9a6UPJWcE48jg3tKdDiszLC73tZjvd5Pn_zk0zwNQHB8ePPhDz_-k3_ml0CBUwoAC2PEhKmD-Y6Hc57KZppMvFnViJXUw8W0mTGReyeCOBIAoXt0WUUhElVTz5zVnAcWjUtSswtKEyNCWCBjuEeQIYgqEmGiBOGif-xr7339nSfNFNzETBzFbV3VPYLI-iIRvGcA-9G_B01rW95__DgsmLB7pnb7jVSZttNpEfBwiFU6eBCivwUzg0dJtM4tmKwXOc1VdSyTIagZQnDOidBCmJOpceKOsijDoKoAAOqEqK1hZnXT2lLKCBgeyFjnOkyDuwDjW28_-vbPfROqb7aZMppoBZqup81-i05rlbv706v7gxFNm3FROa9N3Zelrk0Op7MrmNsyr03MIBBxXduQ-bNXh4d17Vil3fXmPNe7u4emTgFqbk2_-a0Pbnebrz2_fvOwHM_LuakCOOLhWF--eiVuQKQA42YCojCfxkEdgXC7LaZ-WlZgdEAkaKKiFTGJeULKxADoapCIM11dXZlKYkKijj1koq5jzGUUkQiotQWAmLpFTskvkUdLiXLKlxw0xbd_5ovvX19D0G9894fn5kt1WSXUAUKb18UtzANFxM0eDucAcNVWRaQhgvfTajd3ugVQaw0Q5vNCzGq1i-O1t6g8IjzCkXt0JYhATFNK7hYaEZ5KRoRWl4gI4Hd_5u0_-kd_NCRCina4yyV7bWvDBca_9Nf-hT_963_q3_hf_G_Xqn_hr_7q3_mPf-e41NBGbtGk46JNNMxzTuCITB4gVQiJcxYxQDdpcOF9B7iLKHNCBEJ3V2nx1T_7q7_7t_82uCFjGjOohznGBRPuYOhGRMi5SU08OPjlZ7YLaszCFRAd8qN337_78Y8YHMMP9y9vHj29f_1mGorX6uRmhuApsan3sb67IQCG9YwyJEIgE-khZIRgzp242OM9CMApqwgS9hr9ZXBGDGHE7Ko99UoIkEshxLpU4iyi7rDWVU2DyNwjbG1rThyAIra0hVMCh5QHxJB1cW05MXFykVArw3g-HoGJUsIEKaWmQoUwgWs9z8vzdx7_H_69_--hLl_90hdQPQVEkEIcT1VneOfJTbiPmby2hH3gGpmZGByAh6G_gGtr0GFLKWhIDmhuEUaXNLYihKkSIhG2umAEAaIqqoSbi2FAqI-J3ZS8C7JC1gbolJNaNZWvfvntb_78l7_8lS9c7TZvvX17NYxlKOd1FfP1vHRgCF9KHrHU6mGl5KWaO3Km9WHhSGGorWmzWCOaMKFrA1UnPNS2In7n-z9tFn_p2z93Ow6wNkqUcimUHt3up6EwcWikxE8ejWYwllRSHnNJCRPTMBQimrZbIsbCXHJzI2Ii3k5lSrmUPEzJozNCPZUcCL1FWhLvNlNJ3Ds3Q06lpN12msbSsenMZG6dPb82Ew8PpMAx53EYmFjEm9hpkeZQDdThcGrLYuJhgOreRBzBEZam0lUzboyRCZdFznM_qIOpmUVrJt0u7mAeqtYTWKvq2kzRLNyBDMAcmioSrVVFPQKQIBhbRBUX9wCqa12WdVnOq4g7qJhpqOK8CgCd5qbqgjCLLLU1MUBwJIsQsyaq7qvY0tpprcfzycLC4zjLaW7mARge4eCFaTvl3TTscx5z4gAIMFV3Q2JmooQA3rsnjp2Qz-CRkHJOl-axmCOYhqg5QJ9AE_QSMFzsfioBQUyFeSgFEdERxHvmFZkM3C8TcQQAcPcIA7fLjRM1Qt20GUQ_Z9NQEkAwgHVdKEWQEcOjaRw4AdOshjmnktQ951RFOiQ4ETFhbwCRIwAkRCI29y443o1pk9PVNAQGGa5qc52XdSUi10BisXAA4Iv5FwITls5iCoBw7-REAu894HC08EBkxMIJARghMaXU963EiJk5E26GnJmGxAjoEmhBSAkpMRIhpf7M8y4rdnAjXFT00u64mBxE1cPNQd07jzDcAOxzXKzHJWbhEBhOnx3nq82QEBMmVSCyq0fXZUyb3ViInj555BqbsRA6uCHBo6vNou7kpSTEGDKtp4f99a5Km6vq2vZlGN1vNpOJiDuhjYkgNCXCsOfPrvebAYJKIoAuP845J0LcDGU7jqXwq9d3EL7b7ThRPS2P027MedyMY6LNpuw222GT7tvhlsb9ljfjlpCud1evjnerV1TfDLme1u2mAHNONCDEqhCOoNvNcLUbt0POWMADECiz6TpG3F7tEwGZD4QZsABlgt31Vmp98vgJIpzb2vuJzcUVAOJqv2nHU07w-NHj82l-eP0KiZjh6bNHKQ1vXr2ZdpshU87JzTeb4UvvvENALjIk3O8n8HDz0vdxOVm4aZRxu7Z1Mw1h7epqlzMlYq11f31lauBmq9w-eQRAy8nS9bi93kaweXz84cc55Oe-8sHNbvpITw_reZsyOA9DHoBGTgPj22_fvHy45wRIuBl4AExMV1djZhw3-dWnb6YSbHb9aGqrDDk_ub6ROrfz0RzcTcXdet0RgQgQy5AGLiqmIRlTQcrGZIAB7tCb0GGRkCA6BsBUrQvjzWKzKbmQNq2zuKiKmbqJ00WgCNS9ASnhZbXoCAhmyPHkevqZZ49Px9nECDEPKRVeRVZVdRAxt4hAMffoekPpXSdVvR3GJ1eFKR5Ox9PpVIij6S6XqPrkakLA5obkBoCMhlHrqu7rXA_3R0p5mdu6Nm3qHkQ0tyUxEWNTTYREHMGm_wy7FWUYa63dr1qwC1EBeraAuAeZeCzuWIbBNcwhIb7zzjvhmEtemyBEM-DECGxiyzy_fpgX99lDne8fltOpirpbEHPeDnNTVTmdlmam5g4wN7s_zf_49390P1cxW1XNoSA8nNbtdrrabcuYE9HPf-UL15gfTdNHL5a74_m4rmawzFXERWXaTmksHoAAba0D02YsnPJ-Oz17dlNyAaBxHIchp5ICUZu4AYAzxH67wZ7eppjGsaRiIuNQciEVCbdQYyIzRUDrhzwIqQ5OibnWKtqAghIQIXXfG3kehu02_bEvf4DEb-a2ildxROSCatrWZmGUYm3tdF6baBPLnGSt2A_1RG1tpm7SnYndyrzykJs2ZgCAbmoKcALo9Vbv73NH7jjzwJwH6BMrhDKM67k5UJqmZk6l_PAffm-z5WW5M6lG6eHNsTn98_-1_8K_9N_5L37yw-__b_6n_6sf_fhl3pdf_dbXGAJdmULW1iusKo0Q-l8KGGG9YUIAyNEJqEgACTCaoAeYM3G4IYQ0CaX3__Qvff_v_8OpDESoDawRADMGhiCYS6U-qPMIi5RSZ_UgQHiky2RdwxwCdje744uPEpEaQOLTi1e760eJubaap7Hz9nrfDJmiJzyJAZBTdjO3AGCAKEMJD2CIAA0LBmByhM-B5oKMAOBm2LF9vWAEZGHAZBGIQETUarskzgkpJ8pdLRqcGRFTSgHuGJgZE5hUCEuJpQr0JHFrhAyAmKitq5uVqUA_lDl5lw84pDwuC_7VX__Vrz6_-ebXnv_Hf_838jB--YPn8_Hc0wm8Kfd35-vNLjMi0TqvJnW5P4XZZjPtt7twB4Og3EQA0cwKYij0OZzKqiJOff7u2APUYgzgTXIu0ppbP1-6uboHM3Y9iJq1RQmIOYW7iFIeIJXf_-5Hv_0739dSfulb3_yLf-bbj4fJFvnk0zfexJeVAhBQxIzDCXJOKp6xlJwcDJAwkdQ2DAXCdtthbee8yWpm1dzVWq11vTsePzueX9_P4v4LH7y3G3A_JAa_2gzZ4fFutx-H6-1mLCmAr3bbCCvo05if3m5yIgpPJTnauNkkzkzsakgIFIA0bAoxjqUkjMQEAcipbMow5gDjlHJidB8SM0LJqXBKwNvtlBLnkt0hHJqKmjXRZqbu6k7I5tEsVtWzSItYzdalnRcJwmBs7s1Um6qFdHVdIHIftiZCAmJRI-RVLRN323UgiHprFoAeYIG1D_aJAbA1U_GlrqBoGuEoKkBExOaGwKuoQFRXNZCm4QwRvb7tCJgwCBLRWtvatAxDdUVMSLmpN3UxBwwAkGprsypexSxQAFfl82qHWWfxw6qrWhOFwHGc-sOrpNxHy-7moYkg9SBC7xS7RYSqrmsT7x1fF7fNlBIwAHX7mHsQk1lcjF3dcYUBGK4OTGGm3bnd9b54wYUyUSmFmFMiQPAIB0OCznnryrZ-iyBGd1-bYT9eB3RyUE7MRJkhBbz9aP_4agPmqlEZnFDEzVxFCNDU-h8ivNxUJIwguhkY4xKQl0BKlIi2m7E2ravPq7p7rdLaWqWJqwKog_YkH5K69ZY2E3QwGFGkPmbH_gRjCoDw_pV3_BZBr2IDgCeIlIgIUiIkmEqiQAJIuQM_ITOBWR_8q5p6qF90xAHYg7kd-RwAqta9dxFBn1-rzCzAEYAImJCQAh0Dfvt73wOHVDgPecjDOFwFATIUSokILMrIh7uDihDTbrN5czo9vt6IaFMVtTKWzfV-Oc06NwrDcDSTWq-mkRMtdT0eTtsxX--2dZnHwl989330ePX6fjnLN7_0jXAkhERYSnn0-IbIl3n9xte-tN9uA0BEyzjcPrqmhER0Ps8I3qQuUp9u9qWkNsvpcBpyKmQfPHo2n-Tq8RYRr7f70HBrBA4WS13VDClNYyaiCNrup2nYBZNU3Y-745tT4owBdV2aiErr-SBA2O4mlZZTQuKlLdvtlgmHTb69vQZTrWum4mJPH18hBKqMQ0LEPE55ogENiRMlCVlbg4TbzXRzfUWcRev140fDiG5r3uRxt72-frSZhoK-GwYC2G43Y07zm4cpp90wutj140cm1mrVtg6coEk0GPc36mnYbueXdx-3xab9FXK9t5fz8WFdUwJCv77ejDlvx-F6Gkzaw-kAFMOYh5JvttPAfHMz-tL2mwzhFvbWW29tc3CCMo37q6v_6D_8h8DoEMyciD1AXJHRzc2UCaC7NtRDXEwigIAyEgCqqJqpaZhTwOW6m1BFp2kAIDXnwt0QiA7QZ_YA0lSaQ2INUzcRVVVOOWV0AHL99s_9zLlJIgCMZVnWVeZ5bXJpZ_WlGTPmvvKDYOKUsFB84_3nX3vvuUocz8unD8fPHk7mahaBIGLzue2vypffv8mpMEIqebMdS0kpXEWAUlMZMoN4SuRu1mQciqoQYR5KhHlozhTmhBQRmVK3k6M7QXDKEZA5a3NXU7CuzTER1cpEwAGAZJfApIW-Oc7m2JWOpnY6nk9rnZflXJUSi8rhtM6LHh_mtfrhXFURclJEHkozkMDjeZ2XOjdtiEuzVfy0SBV78WYOgGkzNXYDSJzfeXa1BbIqH7-4O82rAy1rrc2PawUmEVdVN1PRh_vjw5uzaoRD2Ux1FYU4nFcwd5Foqq0x4pjHMNvtpqqrmarbuJnCI6VcShYTaYoIgegBIsLE41gAojVppnnLizQRQaLwUDOtTc0zUmZMBvtd3hPdloRAH755NVdbVmvmfaZDzBNgr2WJCzi02qTVxLyKiIUFEHfOiyOAtubNGMlaC4tw11YhAgE5AKAr542QXAMizM31IrjVcCegnMSsTEzobj5MBTFUZkTDwGaRh5s__6_99X_1v_-vff_v_f7f-ht_80c_-ZFH3Nxu_kf_g__e7_7uD5bjrLU1UUpkEFql6yjRxM2krgBgvcmGYdqI4rJz7xorDMJggg7XJCIcyuG7PwVV80i5EHmYRHRNaQABRVBKHQuXOLlepN0Q0MGMRMBICKQalIe7l28c2SzUDNUf7l6MY2nLmSmN4xa7WpWoz_EIDMCtb1WYAQNUELAf8lQFEACDSnLXLtRMlFwdANzN3ZBTECL3TmqEBabCROBBADHut6JqAnWtnAoitLqGRUocEarNzSCgq3a1Val9TM4RwJlUWuYSiOHGKSEGI0JETjkur0sYyrjfbn_lF7_y7Gr70aef_fB7H_3Ob39nPq3_-b_0lza7fH273-wGQvyD3_vuk_0tEaz17CrigYnvXz-IxXZ_lVN2UAwvw2jaEFBqddWSCiFR4tYqEzKRNnMEjzBXZgTEppUyBaHF5TVflxX6xBfC3Cnj0hoRXnRQ5tq0ns_1tPzOb_7e3_77v_X__Ft_B6ZhmLZ1aSI9CQ7EVCijQqAQUDg0WZkAALsilpi1tWEYVBSQ1nkdpykS5MSnh7NIO1W9F_2d730HBb_2lefPb682GRPG7dVuux1vbvc315vHb19xyUyx3ZdcMmZS9TIMbz97tJ02Y8mEHGaZ6MluIKDCRIBqyqmMJYN6ySUnYk7glplySQFGRIRAzFUrUeSUSuLNlDmQ-ogqoImrY63mAObR1NXgvFo1WKqJQ1MARG1WxefWmhhCQJBrp6swAor6NObDvCbOrlqYIwKA1Y0Zj0tVD3Hoo2kxF7dAREaLqE3cHAPdQ9SkeavSD2bNAplEFYDmde03jXB0c0RWdQjss-0IgEBzqCLmUdXW2nIem2ptqgBzbbXZUnUVa-ZNtYm36vMiajirHdd2Ejm7Wrg0VXViMGsBwDkRMueEHWitDkAUXTJ7ETWYufWjfaCpm1sn6VVtXT7bXe59A37p6fdqfQQglZJ6ft88pCnnlHLqy7-cE6dk6l0kHkCiBgiICG5qlrAXZyO6TiG8pE6u52VtHNgNvjnzdsjvProqAGjgSIuIVTFRMXf1Cwy_A3f7nDzC3UVc3ZqImIdDt1Svi0AQMpga5BQE0nET4eLUVD1czS3ALMRM-tUGzKFBX3qEQ5BDeIC5AwYCdKvYRXvvToGEkRGY8KK9jmAEImBGJGRGC2eAzZCncZxKSsR9yI8d-9sRaYEBEHbpSFifa6gRdwFb31F0P1h0bQ50ehAEBhLh3_qNf4gQqiGrXl1fr-d7FRm2G6_1yaMb6MQJ15zT9X4L4FMZmKmJmNrTpzcJkQuHmTwcC0QeiKZ8u9-VxDnx8Xj35GYciHIOkWU3jlNhUXn15vV2N_z0sz9S09bW_XZaT6cnj262mwkRZK2F05jLYT4ZwZO3nhDw6Xy63m-vr64x4aev3-z320x5SEw8UMTdw_zk-na3vWqrLst52BUz6S7Ram282p3O67QvhRncuyMuJWIIaTVBTBlU2ma7q60p2GlZoGBG8qUNTLe3-xAH1SfXj3LKGLQZN5g5UuKpPLw55IwW_urV_XRzs66amZ8-eabqb97cJ-ZxGubzmgc-nc77690qlZlzyZwIKc2zTNN1bUoExLQ0QQjiVHLKhd79wtun-4dxu2WCst3M8zwMQ1uX_c3tMBXkGLe7VMZhnIYy_Tt_499vW99vNz__9PHH9y_nkOaNKDHnPA4F6GY7PX1yjUFrU48oOQH4Zii7aTovsttO6MDEmzFtNqOc2831nnP-8Ec_Seyi0ROGABgOc23hLqu4ubkRYRAGgDRlgA6zBgxkhH6OhVA3UQEkTmkcJgBUdQ1cqrRm5tE7AB05SoTubmYA7ECYiIlVGwBMGb70zjutNRFV8Cqtiqxr02aFmIktQPsgEpyx__UualfT8M7tzT5RBL46rJ_enWsD4PTR61MzRaTdMNzuN1saDq9bweAEJuKAZcymPpQhCGdt51bRQ6oSUx7K8XAEpCaNAJ3idJ7N3MGZkBM3UxFhprUuZrZq5VKIsJQUbkxDXWt3P3sgEDgGjMzb3d_5e7-7qp3XZbspx8NiGusq81JPi7y5X525rVbP0odNc23meDzM62zrSUK5NXTBpcl5WZYqVXURPTdp7tV9kTa3took5sh8eLMsp3k_5oTAubye52paxk0eCiZ2iCbt7uH0k4_uXr4-zs1e358Op-po61rzkKyuTKzLer3LENoWOR7O4UFMSLGZNqFRVzHXaSptnRNjYUyJIMACTD0RKgTnxLmIexOzJjlBZi6FAJAQe_E7l7zZToGw2W0fP73SVf_qn_k1VxTRn754iRBm5p-Hft19VXM1MVF1UWEiAgwA4kwExOmij-VUmwQSoJuYR7fJIqWccjEzFYFwTEGMkMk5LNTVtCoShAV4mFhYxOfMWUo5p5wyovPcVuL0z_-Vv_SX_9t_9ZPf_96_9b_-G59-8rJsN08-eHe73z0u-fnj_H_7f_zdVMDNidk90AAJGcFFkNBMO4ui6-r7K9ZUoZvVVM3VzYG5x5JFxCTG3e3h9T0guaOZ9vpNEARe6BnhHu6QkkWoCjERkkMwYbi6aRf3caaUUoS7SKAxERJz4nWeOecyDfPhfrt9GykHkagwpw6gIyTi5HCBqqsqIXkX26RMKbkaWGPi8E7WYs6MCDnnjh8BQHdwIuxiTgviBIAUSAaAiYhDqgJBykNOJdwz55xy4hRuJjKUsVcJmNHEUndaNQkKC80lI7CHa9NwRA93yEPmFNthzCk9ffvRv_rX_oKK_-jDl0-e3OKW_vf_5v9pt9t_5YsfhGkqaSz4k59-9PTdx0w-lmFVq62qh5of7h_Oy3m73ycuSFTXtfPIe8oKIhCTaRCCaQuPlAgg_HMqakC4mZtK0zyMQeCueUjgwTlBGICbKrqvTSI8MAzUOw0tPCEAxvG0_PgHHxHg8ycbwOCcVIQAKGEe2MQCO3Mf3ZzAwaykDO7uEGaQkBk0tEYtOUutYTIflvvj8bPXDytNP3p11yr8yZ__2W---_Z2N40jvvP09mYzPH96e7vZPrnebjebMef9bnO7397ebNExUb7abYZUttsp55QSq8ZuMxLhNCTM7BiZaJxGBHQHJrjZTmiWOSFzSrTdTMOQx2FICCURBuTE4c6czMMCgLgZrOJNvZk39dW0mS2LiEQ39d49zHOzpmEeTXUWIYhEpdct6tqaikmo-nld7YLNx-bmiRxQzNaqImLh5gYE5iCimTARo0OY80XuC44mJuidX-nz2qqquEVmNTcDJEKgpmLQxVxAHi6GCCIianNtrcm8tsPpVEWr6VxFzB1RzatoUxP1prau9bSs94fzaVnvD_Obh_PpvM5LbaZAESbmIbWCOwCYi_eBRg_pAl5WeBDW6T8ISBiBxD1-UwonBHR3EVUL8-DPCzHQZctIEQDeIzscSCYKyGq2KZk558SXsDzCxUbQ0VVEpj1zm7CDXB2YEhG1qikTAqbOb0JIAbfb8uV39m_fbEaODOBhq9aH48qA4RgRm2kIt4jgAI0gQnF3d-wn8QgFDwQnaKYBwejrsj7cnVdR9UBCdWjiKnFqDRHde-4ILkRUCAgQMTXvDmkgVDcL0D76CyC6DPAcA7DvNwgC1K2DgbozOLz_f6SumSSMCAsnRAQqJeeSse9mIQiIU_Zw7OYlBPcwNwRnZlX3iyTBL38jcXR-EXSvQDhASfwP_uCHAFkj8pjCjXNS13aet1eT1ppTUjNwSxjg4E2t1vPxdDov2tpuM0qVFHw4zWdRSJgogeqT_z9PfxpzW5be92HPtNbe-wzvdMeaq7q72AO72ZxkkZRkU6YkajAlRrIlm5YcJUESB0E-BPkQOFASJEAcBwhgx4YBS3EiRbYBR5ZiIpZki6RJa6AokYxENkWym82u6u4a7_SO55y911rPkA_rFPtDo9G491a9733P3ms9z___-51urS7LYQdhCHZ6MqJ60_rG6y9LuJbl8sUNC-1vDwSw1FkYz063p5vVvDtY2MXFWS1FazHAYRgA0Fo93OwcQFsTwtUo6816TJJzYuHW9PRk1Vp5fH-t0DoOUnKKUAyYD6W0mge0amqqYfMyMzMCbDZrA5OUT05O94cSREKIiKVVFtawMSchxPCXXro_DrLs7tbTcLLdPn_xDM2H1Xq_P3BiYKSc0yqbFSEYh_To1ZeI6ebmhjmlwAf377mFogo7M5WyJOHVekVALA5etsNA7hHetG7PNll4mefV5sTCNmeb_f56vd0MY77_8uOqtdUao3BCXRS3eXWx2c9LlvTe176liJSSEv-u176jzmWxvkX0RJSzpJRO1mtGuHz2QgHU_N7JdsrD2cnm3tkGGPKQMiOaPnzpDLzee3yx2a5rKR988z3JKcKB2B1UnUUMQ_uxNTCADKCZMbN6J-MbBvSlfM4jEBJATun-5gj9LHMFhP1SSq2BoB7uQQxxfCh5F6xCQDOHIDXnAGuN3F5_eGKmrZbWbFplSaNpBFBz0OZN3cyxoyTCAWIzDm8-Oj8ZUkKsHs9v7vZLqeqGuJvrs9v97Tzvy9JCIVxdm6o2q3MtpZVl4UqI5BgppfU4LkvdWwnwJIyIUx7IYyU5IWWSzTQxxpBSmJFHn8syk5kRY2ut1abhQJGzRJipA0BYTONKUtqs1vc227dfe7TlQJ0T8pATEh7mwzLPu0O5m8te692-Xl3f7A7L4dBXxnB3u_Nwp2ihQLjUendYloNe3u6aWql6u59vbu9e3N4eSrndL8tSd_PCIs-e3Wmz_aGcbQeP2Gl5erl3ohpxtytqpADavMxtGAiQr3eHfV1A8DAXoIAIV6-lUjdEO0bAOIwcwIjr9TSNyd2JOAK1KQK7o_lxsNtK60FQIWImInBXAAM8CpOEZRAZh5ECRhEJXA_80uPzR4-3P_g9n_3Xf_SHTqYciE_ubq4PSwtiYknCwjnnIDmozrVYbW2eS7PFVMNrbWENAVpdgEmtlXlBokPZB-ERf2IIAOZW23J0y_b3EII1jY6ODEiZgXMfbxMgC6XExInA16tE5l6B0ub7ftfv-bE__2evb6__1l_6G-9-9d3hdDuerjhjs3b68OGf-DM_frL2D56-v2_etLWlgIObhxpx6rJR7NNyhHADxI7nxq6IIofO2gcIsz5-J6JANF4QAIcE5K7WTbzuHaLSUTFOCMwSbu5GRKoqzOpqTSPC3Ey1C0SJGSL6O677tFFdq7o6EF6_-OYwrNABkDsfR1sjSQgAyIZkGiIc4ESMzGoe4CLJmhNnAoDwqjOxeKCbI0G49-NBTxT0EJSb9l1HWGtIpK1O44BAbSlElBItu4MQukWSVGsT7vEtbk1Tyt2QmYbsblotp0SEiOSq4zTVUkxLYuYswlQPy-_5_GesKlv8lb_-U3M5IKQPn1x-871v_fE_-KMAdnF6sjk_wwQNHCPQNGUmIWaG0DBddjOKDENm4U6mB0ZTN_PaakqZJatFqy2nTEEEREzNWt_wMwIjB4KZ9mIHqDJzuAsJhg8itWrKOcK7ywiRSZhpYCIHWG9PQvzFR5df_NSbQjiMCQBbVRdSx6p2WJZANNdEYuo9uDkmAfO2uDdHZysx7w4AgYCkZq0S4O1uef_ZzTvPL-9azQxf-uxbf-L3fPkLb7322Tdeeenhvc-88uqj09OLs816k9fr8ezkJA9ps950XGlK6fRsxYCrYWJETJKzTMOAzOTBSMiYhHPiYUxC0kzHcYAAQRqyhCkzJyYhEYAhsRBGuIUuVfdNr5e6L7Zf2qF0qDnPTeellmaHWmqzu7tZAZaIpVltvlQ7zGVXdF_nRctiVV1b9Ro1wDXUzZwQMcrSuqfG3IiglBqO89zMO0QZdnNVNyTEiKoayGpqNdSgqR3Z-31zrqHVCKlvBtyVkAgjD5KGBISIYOGAaBEeUdTMralq0wjsTsPaifgd6gmgHnPTpdqulNt5vlnKzX7eHepuafu5ArEB1bIQEyK2Wkt3iQVgv-FwF0hZf4t3ZWMEYg_dECFCrbAdc0JCQnPtGipEgHDqRC1wSdzzQGYOwsydjAylNW0VMJgIIbj_tnALQwQEEJEjzQYcIlLuN2cVZhFJScw8MY4jP3ywebCaooR71FYWtbm2edGqVrrsimhBW5q5R2lW3dR8qY0Q-vz7OCYn7EHH6qHgaj4X02a12uFg6iFJ3IGC-9mCmFStx-gRCQiYjk8pDQX3gPDw47TJe6fBu5UYEQmpryEoCAEYqcf5iLAPPksxR-pporm0WqupH0M9hgQgRJzIVInQwjuSEQmrtYCORHIW6joFIDxOuSD6oCUAzZ2QJZPc1iTJAab1Nhx1mderFZOfTGPi1Ky8ePGCBE9PT1-8uEpCq2lkTs8-ujy9OJuGiZBrVQXAxAxkZckULDgN04tnTz_98sOo-vje6dnZyGRDokS4lAIIZxfb05NNRJsSZ-aV0MmY19OQERg8ZzGzm9vrRACHit4e3j8h0yEzAES11XqSVRK2zJgyBUewjcx1mQ31dj_ndZ51QfSUnAFSSkubO2R9XE-73X69GYdhfPHi2iLyOOwP-1AnZknUTGdtxGTuq3E6W63RfRQionmZD8tudboeBrn38Mwilnlph7reTGkcnHjYbtTUrU73NosuEYCA0yD7sgxplAghzlPKQ06En_mO17PI_vYwrkYk2G7W0zRdX96665CHshxSztvTs7Aoc0HGYZWBiVNerl6M41StzVe3aTUhQpoYov3Nn_sZWo3mfv9k-3i7kRQR_b0e69VASc4261XO5_c3dzc3EECCmXm7GcecWvW0yv2ovd2uI7G5XTw6X21WP_vf_SMgtmO8F6ch1UMJj9oBKBjmChGY6CgEdl_KohHVFgBQaxjQLMzsctfUNFiV7Pput9QaREEdz0WImIU4UR8SdFsTdDY2BTEubffFT72p6rVWRBRmswhwZGJhQKpmqqramilRnE35dD2djkM56Fc__KC53eyXogFCalGqlWr7pbz74eXTq12JWDDuSqtN3T3nJMIM2NoigGNKCDGk8eLszJrm1MH_rK7EYGHhHg7rh9vWuhkKU0onJ-t7Fxer9TisxoBAsHAFiFLMEcNtGKRPYgNaRHjYp9566dd-_Z3_5f_gT5NBTlKqHUprLYr6oeh8qJyHw7IYxlzK7jAvi97ulmZgFtrscCil1FJ1rm2uNQCr2rzUw7Lsl7JUvb49NLfD0g6Husz1dnfY12IILw7Lze18fXsgIQ_cHypJau616VLsMFeirBpzqYi0zBWAhpSzJMrUWh2mXOeShpwSIdu4zkScWSQxIOWUHKOTxcCdhLNMZo4AAZRX43oaOQl4HO6WUhVZUFCmgZhQJI0yrOWll05-7I98-dMvPf5X_8jv_SPf-6XvfO3x-XrCwI93-298fKkqBmQOUFWAEMDMHYIAGSEwWq1NbSm1zE1LBfcI1NaA-89td9kRILiqIKQkCGAaqk1y1mbh4WbCJMgMwWBMaGY5DQKf-DQBRBiBdK6G8fprr__Yn_9Xpk3-W_-P__Sf_twvTtP29PF9Hsc2V69FD-X84dk_9wOf_dM_8b95_8NLtSaJ0czDCAEJDEwhkKgLJRCJSMyOa3YzN1WU7N4HWu4AIISIwBgYEOT9aAGk7gDB0tUwpGrHNVmtSMws3rQjeKyZpCEigBDBWdBKi4BWlyNxAgCJXXW-2XHndQq4tW6Z75sKYXZrbtqbCsySk4Qfe9SMLMx-DD8AeOtA_N5R67Dgvu9AAGIODCIgFCIAD_Dg7ae-PJ6caK06lyHxZr1xC4gwLciSJM-HnbuP41SXZRyHUhY3G8exqXpAykM97FhSStmPAA1GcCICcCIMiM20Wg_Tn_rR33e-XR3a_LM__fOe-Hq3C7df-KVf-ZHf_0P3xpNfe-e3fVkC6OH51hzf--ADpoROrdUkDOZE4UsBCObUWnUHNyPhgHBzFnFzFgxzjHB3Tql7QSUnq42C0rgqh3nImZBMG1iwMKVx2R-YUS3yNLZDIUJtTkwBBkCALuNA06jNtts8pOFz3_Gp3_zGN5al1aLWHBIDOjtQIDMthzKuJkYuS0UKFEo8aNOUBBDGnF1tkJWjIUrTmNbZmnIi9Vrn-eXzcxZ2j9U4np5s3np078F29ZkHL716fs-aYsSQKVNOidx9GHI_AjOGMBBTq0qZCB0RRxEOlMRpyBHBRG5NEiFQGiTCc0rM3BVXmWm1SiJMAG5hahVicS8tSq0AaBrNQSgdam3NHEJbVDM33NUCDp2tCgiC3BMdzSyQJCUUbk0RpVTNxMTU3U8NojYDh3CfhhHBKZGZQfdSIieWLIIArc_b1YWJmDo4Rd2JyNUJkJDUNfpImzMSNm1ISIKMjBS7uwMTadM8jOpKiCKpcy2ZYcgJzJhIzS1iqc0Ca7O-PW-ukhIS9RnMOKRpyNAaSzZzJoyIUisgCB9Z3xDu7s2sNTOA1gdUfUTvABGEmESAoMwLJ1GDT4o_kViIESM4ibkxwjgIBgWAh4E7s3RTwdGoFaBqPZLSSTqIbOqA0FMxCIDg48D9T4YAIgpAR2Cm85OVVWUEAIiAqrFUrQZAWEvrJc_DvnbJcXyy82QARAImwH6f7YOFCAhhIgJDdA5XQCaD_q-JTc0cLSIMIwL4-BfXUz1A6G7hYereM6PE1EFAAYQoTP3LFCEI706AgEAEQXHsNm0ID0TwCGJwxPBADGZCBI0w9yTMzNCXdke2Dx6xQoAekVAgoHiVbleHiDiyq7uembnDRR1ZLm_n__zv_L1hWDWLaUjMnAcesgjivdMTtK7wbv0AAQAASURBVJiXQx6GnHi9WaP6NA77w_7J5RVnFqCTk81yKO-9_-GwSkzo2hLi2595YxJuVg7zYTVJRnzl5YuPnzy7f-_s3vZkWQ6LqboTUqt1nDJEe-21-6_cuzjfbJblMM8LYZTa0jQ9ub4Wipcf3l9l6j4mrXHYHSJiyits9PEHH6XV-PJrD-0wR43EsNzZIKl5lKWUQ33rtYd3L3Y3BwOA9Wp1cbK63u2iKRKLYFDald1mu8VEGFyLqraT01NVCzWEuHd6rhrkloYcHnW3D9fru11mWk9rVb_b7QnxZDPmNNzu7pAhEUFrOY-7u_3d9fVmNa7H1TiN-2XRpuZ678H9y6urRMwAq5PNiydXru21RxfVoWqrh-Xiwdl-t3v8-P7uejetplBdDcPhsDs9v6ithtnu8gYd8yBZyKpS4lYX1xoQzz--_cN_5IcGs_UwDDlLRE6pNQv0nBgBIwAFxikfdjOin6xWRMgEknCemwgDUBjknM7PtpdPrh69_NIH735wqOWzv_cLuOCQjtQKTmwR8253enYS1u15YeGO0GqX1PWRYp_oRzMjBmG25ujYzIUSBNER1xFIGG4QkYdEwNGfNxZmhkDae-9gX_qOT99bZzBDBA13NesYb8T9fmGRi4tNRkKiIfHJmMFjqarhgTBSIkHz2B3mq5vDbl8MsCw1Ag6lAsm82FJ0vy894qwOvWmzLIWYmEk11KyZTcOAAKaGFBS2nlarMQ85be-d1tvZwUlQUk6THA5VhPM0ypitGgGZmUjqrebEJMQE5GBEaGgPL05--Ae-5_d_z5dONhMiGsHd3WIQnNJh0WrmLHNtsyr06o97OLi6ugoRMJfWIEJVrScqCWttappESHiYhnDPKaUkWVLzmJuSyGrMh93h9GR7czs_u77bzQuSMPH17V2ters_IEopVZslkVoaIdx7cHYyjc102dW8GgjN1AMJINT84t6WUTbj4O7ugRGGTiwMkLMwMgFVrYBgEVlEUmIibZZGyYmnMUMACGUWJwByVPvDP_Al3ttn33rNPTL4Zj188NHzr7__sSLd7vTZi9tlaaUsYxqrtl5H0aVquBA1s5yoLtXCXT1lwYBaK2C4KrKYKTkkJuzE-ghgBA-rzc1CG0SYWkrJA8CtG10Ti1t0SGGgijBYJWQmCB1-5F_6sU99_uX_9q__V-985dcj-cnFacgYONZlZ20BIIz4s__Gn_i__V_-70u1q5sDCbuqV_UIydwtVd5cCAGCmeDYfTvGO6PT7XpUmDAwCFlYMDAQTh8_1KafHNYNwsCsLz-ZGVSRkBDCIKi_lchMUbAXSiGAJLvqcYUVAcjeCkaEGRAgAXOS1WrZ74g5LFxVctLWhKQbM0FVOs7fQfJkdQkMBBASr6X7LzMnd2WScAfCjoJEc4Ku1yASQYDegw0LYmJCPvn097KI1iKDWLMggog8rfY3twAxrDetLqb9C0ZicXMk9NZSnpo5M5VlliTEpKaB4KZIyMOoZZnWG2L6nu_77jdfPv-ON17W5v_-f_bXSmuX-0I8TNupLeXjj5_8wT_--37ta7_5tV97dxzGxPylz3_hV77yG5xJOHV8Yc80uxsiEzELNXc3zTlheKj1NQ4SmzZiCnMEjB57CiPkUCemo8cWqVnrbPt-P5Kcy6GmnACcMlo4OoSHJPZAGbIaCAsDffTRx9_15e-8fHH94uq6L0chgJhDlUm81c1q3N_NaTWGtmoWGIyMCB3QHoiY0FyZCRDzlOZ9kZyXpQXzvNTVNK6nYRgnMzuUKuB5kGmks23-9KsPPvvw0dW-GNgwDpSOAkVz0GaSkpnRyClJL4lPqf-kYxqyuSVOwuRhiDgNEwAyUUoSbswslJIwAABReBS1QC7Fq6lqNMNm0dzR6aAaEIHoGBqxO5RqBkEWDh1JFWgBh7kwsbsLMXciPWBOREiJ5XiiSmzhkhMRivQSOql3REtoM2HC4zAMev31-NHt_yEMAIIgogjwAI2WOCFD9F5kgFDifpMnYsaqitgNsdC3jYTk7qthOOIwAYHAHZuFuQEiEfXuIzG7BhBMg6xSYmRmcg9mbmqqigBM7LUBhpkHUeuwDuudHu5u7j5CULVpzIGuGp3yAL2LwijdoRIRDn0ZmlI_enpEGAARdpC3muFRW-cBnSmCvR8Pvbfaj6oAADAlCXdhRCFDaFWRMOWcCRkYJZrZoejdvMxVFQIcROSwKDF0JUoERRgRqyoxAnZyKPXwZEceqTsBttoXwGRx_CQGODGahYMDkB7LGWgdBtetWgAYfblJgNSTOf1LIiRmjKMzACFcmI9KXiIMMvidIxBSrz-H55TaUh2BAo-20SO85wgU7T9H_cEP4O4QgAbGyAFxs7vrAmYCEGTCPg06fpMhoF-H_uGv_PrP_9pvpnFNmVfTOGZZT2tBePDg3kYSOjJzs8osCCjMrbX9obz_7FpSOllNkvMHH77QWu-d39vvd7e75d7Z9pUH50zx8dOneZCc6eUHF2fnp1_76jdef-Xhxenm5vmNATj4fj-fnp3mMZVS3nj53tk4XJyuf_Mb33x0se3J8tn16fXNo0cPV5KxagBEaBhe7W9O1pM6PlwN7z15nhK_9tIrQ-hGhInTmEptDeKw1Mvd9YOTi9vr29v9QRBX0_j6w4tnL26GnMZhKLWkcZx385gHBJ7nfRqy1jZNI5id3d-ux_XNzW3K6WK9Lq018LkWJvncay_f3lYiTplSXofa_fvnyzyP40rVVtM4UKqlAqFrZZLHDx-0Wtab4fmy36TVdjNgxDRN4zRoLRf3713d3FS19XabkhCGLnVMYxoYjhwauthuzPRwmE9O19q0ak15vHxyff-tVxjdoyFSO1QEgKB0un18cW-apimnnAQ8BmYicFU1IwhEMjNG2M-HYZBRsrsRQKk-JOlFnf3-cPLwbN7Np9Nq2e9ub-9Y4eXXXvMjSh-LaRjs97vVesOJiVCbRjcoezeLBwSGH2tCTv22iwCgrQIAIAABIbl195ejQxIWJg_QqtAxx0hNPaIJM1n97GsPwqKaalhZKiCsxikAGXG9yhdno6gdFl92exHZrtPlbhGm1bQ2x6Z1tR7A_f0X14dmrW8qAwARhIGQmee5tto4k1k4RiC6uTZDBIdgouaNgCnCwazO0zScnZx-x6dfWw_D-XZKGA7eqpZaJSXzyENyM1NnJFBPwrVZqIJQL1p5hFvL45gSlLn-T__Nf_W-DGPOSFFbO8zVmA6lHhYrapDTvJTdXMtSENEAmHC_r4JQFwUIRW8RpuoBpl5LBcRSKjEhITgKIwKBR06SKSlCqRWz6GIvnt-9-uj86eXts6sbQ25qVzf71rw1BWJt1syBwDCISVhOTtbMOO-XMF2vRiYmEkNDgJxECC_OTk_XU2lqqieb9VJMkkii9TB2TnRbahoTEqymQYiAMAzGxJ31p83NPCchhvU6_9iPfK8U_vRbLz96cLLsDje6_MNf_Nq7H187Dtvz1Vzr1fX-9u6gbo6gzWozwGihS63NVANHkX2pDlBb68v2Wmtvm2pT8_BSs4h3dVwXhVUD8HBjYQBnEXPtuXlXJyYS0daAAgikw-_QQ-Pk9N5P_A9__J2v_dbP_u2fc_c0jcPmBAhL08Pu5nC7A1Vzfftzn_30yxe_8Pd_-WauQeDqiA4BR1tUOBFij5b0A0oAUoB7l366GQMHgNUKRBCYOKUha6sR_PJnPv30g4-pv5HN-PjTFgEIxH2CRMQREP36DcBC1gf8QtaU8wChfUAGRICM6Aj93zOQyBSH85WX1sOw0Jfb4Snn2lrna0vKiFBUuxusJ5E8VHIKs0CKCEIGAObRvZv-HIkQAOkTOD51pw1wyn05wOdvf58hdpx2q5U4L7UAxbEuok1yCjc3NW0yDoipLftAht78IFJt4QDEaRpKKczkgGnM3H3IwV_6rs--9ej0c2-9sRrhP__JnzlYGJMFHA4zMb__jSdvf_bt7__c53_1V34z83B9dfeZz7zKQB9--CEYmoPXlnJCAG-mrQy5b2pATUG1ux4CkHMKD62FmQC5VpWcww2JIvp3uZNQCQjNzVv_Bc6SvWlvXk_TatktY0pq5v27CkwpEQED-KIpc07yXV_4jq_91jsE3RkU1hw9ylxJIlrkaZjnwgKJqDaXgcK6CxuAgQKrGiVBoB6wZcmHUjrl8NmLu-3JejOkgeV2P_-NX_mN99778De--c0IONluZTW99fAe5fHbHz0j8mmYes22X_fZHFpv7gOEMwKRBEBXnzJGzkOphUg0FBESs7bGzBbmDkAhWZp2CGY0jWbuGoYYAR7ujrX3bAGrKgjNpVYLR-r62qZOiUszj74dUyRG7Go6xDBhDjWATmIPyYwey25ebcZa1Xqswo4deqAOxrB-LTHzPolhZiJqTQHJ3DpH0tx7DzQl0aId0BhmhCBItWnH8EOQqgKgm42SIQDD-xYJAdzDIqqqu1tQbRoASOgeRGxq1pwQT9bDejUKERIBYgBUVUAIx5wTIncufxC2pkdIcKe-dYMBQHS7tKoDaDh-0tpLSeAI42cHCNOUBCOIAN0RoVSFQEmi5n589GB32QZAj62buZoTwrG1SwjgQ5aOFCWICLDawXZhTVdD7oWn2swMndGBe4lQzUTY3RDwSOQDGDhZJ-EwGSBESKJxSGBuBqrOx6cMRlgXoGYkU1U1A3QLNQdChzDoHoKgIEH28OO68nhhhMQM0FOx-AnwsnMOgonC4fhZ7oIugCAgxNaUe4ixFBBa5-TuvbQMveID0avGAMdrUkcv9b-m1qqQMNHtfrfZrDE8Uaet9lJmv6wdNyJjnv7D_-SvPbueeRhZkmQ52W5GYTc7P92uxsFDa2semlJejysRWkxf3O2Lep7y_XtnpertfkFGbdUjzi5Oz0_Xrz6852Yfv3h-erZ98_H9h6enV7v93eHmS194G5rdvzjdVQ0IzsOy7IecU-KTibYp5YF-_avvnZysm9bmeLXbPb_evfLa4_vrzWsPTx88OCWM5y-eXd7tP_XW63f7cqh37z-5UvQHD862Q0K3YVjt5kOprVhA0OWLF688erTb7Wr1nGW9WhHFYSn7umw263leps2qLkseOYlEhKvf3N48eHQPictcEOnq-kAJT9ZDljwf5qUFEFprIqnWul2vnj1_3rSNeUjDMOR89exqWiUiQGJiKXMphzKuppwziTy7vj3fbh9cbHd3e8BYTWuMQKHb693V5dXLr77aDvPp6WZ3c3d6uh6Eh3E6LHMSLrUlkWVe8jgA-LLUuuxPtmPd3V08fuBNl7u57HdpQEnpyUd3p9_7-bg5JMrbzMwUbhFIgCmJuc9L264mdWPm3X5_fnqSkLudpizl5HyrZtVVNU7P1ldPX2y26w8_-ujm-up7fvf32GLDMKpHqW0pvizzenvSz0YQwMRhhgHICIDuFgRE6Bh5GKQPRSKmKQNEZnGL0jTC3Q0JhiF1eyMgNPfoSB0PQENmsPKdn3p9k5kQDfzmZofMFJwktcXv3VtvRvFiZYnn17cGIISXtxUZ3aFqu9vtr6_uiJlluLo99GUFABVVP24wgwnN-7CyB60xhMyNAN0MKQWAkACaamGCAPuRf_5775-s1dtuX8w9pYRCixsR16J1bqW0MDjs9kToGjKwG6gFo9S5DjkjgptJxsPu7n_-Ez_--sVmd7tHciRcSnPEubTbQ7m63TWIw6wa0XFpFIAsKXEXvxCDqrt7dRUmt2hqahYezKKtdSgTEAmLuackhDIvpWkbV9O8LKfnq1XOd_t5V9tuLmYQ4GZmgfNcjuZAMJSE4A_vn1PgvCzzvBCCZO7F0LDAcBE-Pz3JJNOUVT0QSlu68TOJEAYFkNB6PZrZkIeceUycchbEIYkgCVK4IcXp-qTN-3_xBz77xYePXnl0tl6NX_mtb__Sb33r0Gy31_VmQKLt6fD02e7Z5Y15T8tjZzVba5wThB-FO0HNzMJba0mkNUXwnpcwDzxusiLCiYkIm7aIAAKr5hhm4BFDSrW2HoU1dWHpJXgRBnVMTJy__wd_8Hv_hS__1z_5U1_79W-cPNyOq01Z9hR4OCzlsEO3gWIgaq3-r__3_4t_53_3Hyzuap4H0dkQI9zNAhFTSq4NIsLMtHV8W4Rjb_GGJ2ZwBHBEZsngQczNChE__MxnX3z0bTu0VisSMJKbRQSJeAQdl-0GFMzZwzG8C2IQCQJSTqZHTiURQQQApbQNr8dpEzMTe2AeJy-tqQWAJHZtSExEQhh-XO93KKCHIhJCCIuqIRN0lpIbMUeYo34yIkVEdHVkcvUj4QYhzLEPZcN5_eZ3zYd9zkO4EwURtWpCYT1LY5qGqbVKiOafTL-6ebTPVLuRJBEEiCQihtCcsteGxKF6en7y_MWTf-2P_nDC9Jf_q59695vvlYbhAa31c_t6s_7Hv_BLf-RH_4XTV8_vStsfbCSXPDjh1d0VdjtgmNaiZoHYanFETAzWAogjEFEN3E0SI5C7S8puLsQAQQAaDgBJkrs6AlPq-OohS2tGBCJi6h3bKCJWXZgcPHEmBhkHQCegIaVI_Ov_7Ks_9od_xGp58uJKNVxYi6Uxq6pBNA8KRA50QoYhJW0OFO42rlfhllICIm_OhCfDuLhF-JCYSMgxDWk_z-ebPGWeVuN3XGyb610r7z558ZvvfPDBk6v7988fXWw__fL9j57dIASCj9Okzfp5L4k0U8m9r0GOIUkQ-20OiRGRKLBqDQtCJGKAYOHeVe2YmqUpBHmABtTWSjXrfTIADTMNCGzmwlLMNbypqloQmwcAWAAGmWr35LkDQjRtFOjotSohILM2D0JJdLJeDYlb1QAyUwIKA4pIKSFjK004IxAYWBd5QKi7hi9FIYIYI8AshIiFW6mcuB_xhHv-1UU4oH_5aO6OkVgCMSI0TJgCo1X1gKJRq7cu4Igw6yF7wKMqDHLiPPDFdh3N6NhGCbWj70aGFL8TIuw0qf4yhkAiNQPEQOysDiRsTdXMEBIzMyfh8Oh-gJQSMUqiTNLXXx7gHV9jUdW7e9w7r_4TSM1xmx1OhCIE3vXDmJjAXZh6tl3NJYmbb1ZDThLmzXVe2t1cLAAQExEzI_fLG5sHAnY7etPmEOrdVgwEwEwUpOoexkTIfaYOnTiBjF0AAYClmgi5gfsxpqOm3J9K_fhNFHG8LPcAITh4rzR-kr8BBOJ-F6Bm1rUHPaEf1isFhB5hfrLKJyO1FqU0_KSwFUH2SXzIey2r_57ecQowbWMeEeD2sBvSQARChHAstwLEkU0aFsjTevNv_8W_Mo1nnEaDANf7JxdqzbQ-fnzPw58_v77bH7Ynp9M41drMQQN2-1kR2eB8dVIpnl9dZsnoQULDgN_51hsJ-fnNi3k-PDhbv3H_HjMsqofd3Rc-9RqYn29Pnt3sAOny-vr0ZO3g25PVySj3Tk-D8Xa_m4bBg4oHr1fPn13-oT_wg1HrOKQylw8_eIoi5-uT6WT7jfc_fHJz2Bc7PV-t1tsHZ5u7u1tEvJkPF-fnu30ZV-tvvvf--fbs8uqGOCUachpFmnA-lJJFotcMI724vBrGUUim1fqDdz4-v382jImRzX19ttZSA4gpupj-2c3VmPN6vbpbFog4OTm7vLwM8HGYmODkbGiHhUGI6XA4jJzSRqzW09NzYRwz3u6WVtt2O7WmQVEPZb0ezx-cv3j6fBpWQnC4uT57cO_y2YvWyiuPXg6Cu9vbvrIfN6unH19uz05FaHd9gOpW21z89PFpHKodCoULQzrZfONXvvG1dz78ypN3fuujD7_8qbc0eMjQ3MJCWJgwCY8ppSSlNkEZciaHYcy1VB6StoZIQEjIu7v9ajV89PT53W73xe98GzE5hFmgkGnc3e5Wq1VK4h6A2Ky5GQE5RBBARHFNJIKUEoY6BLjbmBMje3ggVjcA6PwxoM4MIW3NPZhJDdSVAwzaKsMXX3_FzIrW27tdM--nyZOz9ZByxnB1JH7_6aULS8794BERrTUDAPCn1wcAv52XPGRHqBpuoGYAZOZuTkAeAGEA2Jp2DGIWIUAUtnDipFaE2by-_ak3vvuLX-iqvl21UosT1eql9clPSErLUtWi1VqXZq7C4hacKKL7OYwTuRsxjCP8z37iX3n1_rnOpXrkUXpLuanOxQ6llqqlVI8wdXc3h7IUTuIRtZl6eAARL3UJAGtq5kzSpwfd_OH2CY80-qwtLq-uGdABqrqZTdOwzqk2e7E77Gdl4qZmgId57huapgUDW9P7D84GTHVprooIQx66w6hV9bCUaLvdDiltTybuoWUPrbUsjYTXm3FIg5uLEFD04Mc4DGaRk6D3-UggAVFM0_Dg_vaNe6s__H3fOY3DIOmf_Opv_6Nfe3c9re6_drHfNyG0FucPp_c_uLq9KwqRx_GwFA-DcFAHsymtalnCHDD6eT3MAZDCzT2aBaJDoPf9liJSqcWxvwkjwInQwyMi5VwPMxG2VhGJEEQwABCDmByDefxjP_Evg-g_-Ft_V2ucv3zv_PHp9dMXrS673ay19hwqki9luTi_-L3f_z0_-9P_QIOsVhb2vluwEMIwBXMQwv6G9t7uik9eJRTuiBze5ZJETOGAQmH40he-dHt7dXhx3b0BTCwpuVk4MBFLMrWjSaEpEQURtIYI6BD4yaoYQHLW2gA5vMdcO6weO7EEAix8GEc11VolDQS9eG9ESZKYNQ8XThDe0X_o1iO3JBRqnIZwjQgUPHozPHrPFFP3vkUPg7gpMTGxm_f3JkG45BUDW61qZlo3U4ZqzOJhYe6mfXnibseTP2cE5EA0JyAMco-OeXZTcCCiCGOhvBoevvTSNE3DyK21n_m7v-jIjgQe4GDqrblxtMNcd7uP33v67OOrj25efOWr7_zqV37jlTdee_jgYSC4zqiBLaD740TKMm-3G4EUTSElZA40SlxaA2JOUuYDY6hWEgoEcLBeB0EG936TA49aljGP9WA9K90540jESRwh5bGZhgI7tmJ5M0AmN3v8yoO_-wu_-APf991JgJjcggWOlBUNR3VwVAJwa45IObM3TyJeSjIEp4wiWYLg1lvClEMAYRjSrra9-V3Vr7zzwWVZ5lIhybA-OTm_tz29VzQ-unz2d_7hL_7ir34NmX__933XephYGDBIOKeEiSTLdjUNQkOwNziyoiIAMMKbmamRUJIUhAbmYAahBqqOQa3ZvpTqzYJuy3woRQGtwyW6LTWoeRRVcyuqah6BnaFTVZkYHaM_WxGbGYtYc2TfTNO0HWvTYUqShDE4AwpKSkQU3ncUwCGIAObgYE21OaV0qEtTA4IxZwQsavuqFthZT-HoAT15j-bEnJCaeQIyt1a73RXNzTyIQYSGnFWVIDRsaVrB56otsDQzM4twQLNAwJQSEjNJv3IgY61aF93PpdTWmmlzVYPO7mEMd3UvqlXNAwgpur4YMDxyksRMiObOSZr3FT-E9jE4tGZIvTtF5CFImYUg3EIVrNNwws2OgD8McPNenWXqrEAHiCzSY_qEKIJZmJA6zh-xS8DoWB0RCnMkah3fg-Du1vRQym5Z3KGoLq25x5GzoR4RZqFdllzV1OpS1VTBVmOnCx8JCZ0_FAGL2uLezERI1SO8847cPQMzsqmrHbGacFwZBeGRZojHQtEx6BwendJVtRFRBDYIJ3QIgui6ky5Cl4GbESCknInZoUciEQFVrS8EwgHA5ahKDQR0AAL4ZNTfySuASOHQbwjh0fNH4zBWQOExD2MecJXz6fZUEjLhvfv3KSV0X0xX62k1Sj0sAgzgtzd3d7synZ2ebbet6dUH11nyvBwkMWHcPzk5mQbE-OijZzmlV156eDqNly9u5v1-FJoyHPb7prPpsru52Uw5M0Hoowf3z0_PA-jF9W5MmZgpfGRZ7naqFZfDiGi1PXn-HDK_dP5gvV7vb2_LTaHAIadhmG5vXnjzJMO-VOFsbgFEQrsWnMjMdKleC6uZBhFux7HMyzQOY84Evj1ZIwYSWFlefe1hmwsjW2sW4NXLbv_Bex8NOZOk9bh65cE9dF_meRo4ZfGwISUKZ4JaSyt2N--Z7VRWkzBmdLPrm2vGQHQxzgQGtl-W03sngti3-fVuGabxxZOPN9Mow1RaXZ-tEeH67vJ8tdpOa22tadsMebMZ3Nr5_dNpnYP80Uv3L5_f1IPSMJCwllbvlu3jC1zJ3Yvnd9--efebL_5Pf_Vv_8X_5udvimsklFy1CYO2EtZMnbN87cOPmBwSEcS9i229259drMecEuJqGrbrFafh1U-_FYi_9Iv_NI3CjERkBtU0MDhlNXd3JBRiZgEAC--2pnUeiTBMsWHn4YqIuvXIX9Gm3puJBF1UF7GUiswB2AG6LBwYqv493_nF3bIs89K0qhsEuDtJyjkHmHlAoLbGKQ_DOJdWqy-thfvNfm6tefDjeyd5GChgmZemxsT9KEzcK6od-KuqhhSb1ZiI2AEMIIJJRITZA6K25fH988996tVJYi4lMqOpCCJQrzQe9vv5sNTWhvWQRAhhvVmFwbIsHmbmMg7DlCkJgE7rTBj_5p__kw_PthHQVNfr1KrVRV1hPrTDfi5Lac1KU1MbhmFaj8z44OHZxelwPqaMRIGu3iOHdV-0mZmXOveHgEjHqDtELId5WUqttdRyt9uZ2W63d_NW6gcfPnXGfWu3c6FMzSwwNLohoVVQc0fA1XqUwAgstTgGBNdaA6KZKagkyjmTOwV064mboVnOPI6yyXnIktAyE7tnwix8froaM683gxCOmSdJY5Ypy3Y13d-uX7-__cyj-ykEjL75_rN3nj7ZbNPe9YNvPZvn_c3dnQja3na3u65EDO80WUwiaRBiLjoTgkfUVh0isXizMafudFE3t3asgmEQERJK4n7oVjOzcEQWAQ-vRVLqlnomBsQAy4MQgFd6-aW3_ux__19__9d_7e_97Z8tUWmTA-KDr793e3l5eflkrjMwhpuDZUxDpn_rL_yv_t1_7_-lq7VDEHPbLxgOAd5z8CIOjg59KNcpEd20KTyGRwQahCGpAyXqLDsHmNanuxcfLs-fgysPxABhFv478FAPVzqOVklScvVEiZEpergUEBw9vGl4oLCD9VADgkcfh7S58y3MfDksxAw9c6Y1HEKdCaI_hQm1FUQMB5YEAYCoahDUPUHMQixhgCxuyEScGRHBHfqtB4kJu9ALECmCmZGR3MCaYRJ3Dbda1YE5D2YWQX1NEgApT4giOQEgELZWw9SsqZlkcfNWtTVFxFIrEZqDusqYb-br7_jcG9pEOHHi0giOaidGor7YN-RhGD588mQ53OVixYtZ-bVf-if37z94-wtfMDULQ0ZKmHIiJAi4eXZ17-VXAriW6oDM3Eod81CXCkSOAYyBUEphZmZiwtZat6u2UpCQBU29tnkYyWvrPuruTEKCPjkOJEyylIUsUpY6z1a1WXzzG-_OZfcD3_-lcaBxEMkDEqxWIzMnzOZwstq4GRICJMTEzFawFjWPjBxggGZNfdHoAc9qCpUJWvUnL-5eHMrf_7VfcUSm8bXz87O8Op2Gabuepo2Mq6dX1z_7D37Vov2BH_j826--JAGnJ0Mek6QMiSBiM6zzkJlAiFxN3U5zRuJufV5a7aOpVq1_yPtmJxABuJQWzoc2R8Dc6lKbmjf3Zu6Ac1EUbm4e0Mxrs1oakzRVRkYAa25VzQwgukaEMwplRIagzWo9pTSNiREHkQzI5hRQypIlWXhQ1NIMwY76WjQMhVAw75Z1CGHJwuEBzTIJ9aEskh3hmxAIwsSEhgSM5oGBDChMSWS7Xg3Cwkkd3PqkBD36IRz6XENNoys0QB1MwZu2poaExKhWW1swwWE-HMrStHtduuzPmnlTs4jazPrgCLCP6BEZAM0cEfozMaLjicC8Yzaha42lfzggItD7R71_WJDD0dzNj5y-_kRhYiTqFabuVRREgGAI6WUXc6FgJoMgESEigmHMObOZ12Ya0eNJwgQYzLAeMgJEIBF1M666BfxOa7ZbRaH1AQWGtSjH5qIDQTgEBwC5desp9_9NhA7WoDVXBetJGhYRZEKy6th9W-HmgQHCDBEMbE0Zj1f0CADHatV6fzHczU1De9-RpZlb1VBwRTIy7V6vMDM3czhi0ZA_CfX3yBwCQBzsgIBIUJtG50IhBjgLd6YqE3FHlJF8_P6HDoyGiXKWIUuiCFd9-PDcF31-eXuYyzAKBgjh7f6uNN0fliGx7OaUZXd3CK3bzCkLJBpGefXheRKMsPWUVlkenG6daLGGbA_ub1NOiPjB86unz17sl4OGNWuZeSLIKanZvJTd7u7uMO9VlezjZy92-8OYJ7OWANZpevPx43FIL27v_umvvDOXYhWJk1Z779vP5zrPde-h0zAkzn2us8kDoO-X3WF_Q-TzfDcOOZDmZWGS2ur6ZJM3KefUrc6bzbhejbd3t2nAPCRUHQZZjesW7dvvf5yYg4MAgVCEMpPVwoHTeiQCJkiCiWMz5XlelKskHKchj_nsbHt7dyvhWWy7yaucdnczmiPExcVFOSzn55sH52dEyEKb7SrcV9OaRa6ubvOUxnUKQkc4zMtqXLs6I6032zQOt7fz-f2TyyfXvB555A57fe8Xv7a9OEWOndWrF8v5Kw-evfftf_ev_K2_99WvXx4OhgjhTl5aSylPlCTH7VIhgIRySicn6_n2sBqyQNhcxjFb-KuvvjSu1l_76tcjFitNesKWezUREJGJtDXsfXggRhaETwIVgVkUnAKJex0Qzd0C3CITY-Angj5qqr3TKEJHx0ggCE9DanURYmfc7Ys1F2FCXG-msEjCiMBCwziKiLkTkUKUojeHslv0ULWaIfE4DMM09hlqKUszrR1xSEBEqkYAOTNAMEM1JaFDWczDWkssoZozfeaNl373l7-I5nc3OwQUCIAgZPOGAE1bay0PORSEeRgHQFb1cRg9UEszj_7oHVeJhxwRf-xHf3iwscMSeo9qYF6vp6WU3TzPnT4cThh5TFloJfl8ux6JUQkljevMmTjLXIu6A1PTjqrojOKwPvZQU219XHh9fXtzc0dMd3VeSlG3u_3Bqi617Xd1NWYhrrV5gzov4S5ZipY0DGZtQEGgZk2EEqYhJaEUgWrauWeJcLUaTBXRvGdZE005bzbTtMrswYir9TCtBnREwPXJKiGNWYQhiUiiaUjTNFycb-9fjBdj-vJn3wLEQ2m_9BvfqE44jGXR65v9PC_PLvcu9OHT21JrgEtK87zHMCZwM0ZBkVKbegBFIH4Sx6XWaiA4BBK4WqgSUwQgoqSk5lkyHl9Ypou6BnJvCgL0lTKYZAGFzun5wR_6_j_23_uRv_M3f-o3v_KNcT1GGva7u2cfPJ2v7sicI4_jgBjgPqQx2Lbj6s3XHjy7vgvgWptHhFdECvUk3F9GHhEEvRMQBO5AzEBkWnqcDgOYqZu5A0JE1uuz5bDfPbuMWs0tEEE-CQ4hYzh27hIRxFFfFmBhBXpQwLyPspjZ0UwrUgLHcICu52kKQCjjsZVKgEC6VEnSnWXkSgC6LD2oisRIxIDdAgqd7k0EbkQUEUSMJJwSBDIhhKMFMTsAkrNQdKcYsbsCOBCqGgBSQBBRnZeURgqMsMNyZwzE1Hfu7pZyVquUoLbCnFuraUiOgAxu1pWBeUhhKgTTuAqAxElLU40Xl9cvP3psrf71n_mpVV4BCSDpUpG4h3HDoxme319__d2PW60Gvrs97PbL-mT7W7_-m8vu7vu___eOqy0A6nJgcKzLxHzv5GKZ9-NqcyxzByCCqqZBwpR64Cs-sX4FgLmDByOAo_txFQDgqr8jxcawcKu1BQoxI2hEtx1DKbq7upkPS1U_25wO4-bn_sE__r7v_VJCEHBAVIsAkCGDa4TuYodJ1N2imTsQYQp1a6BFi1twpCNdKhQzqEG9abXWpdbS2vPrw9Pn8M9--6Oru8NA-IXHj87TNF_eIsQ4Dmm9gZH_wS__5kdPb7_41mt_8Pu-BDVWFGOWUZKMQ2CkJKthHBATUSKeowGEqQPGMAzqxsSYjpj5VhsgFtNqxzGsBZRmAKTdi8xkAUttGlFKrU2XuZqCddudR5LUL4qBIDmhAyEkTh6ec-JMwFBK7bcMU0dhs_BmHO7mzDJNeRwn9wjgCFB0jUAmtYAINavaWq--ejBiZqbj0bZ3OKOZNjNV1xYGUfuAlyAQ5larKTggYmkaAZy4K-gJKVHuWO6laXO3cHOv2gCJiJuaRj-nQuf1E3NTL9XVwx16NC4lmqaBmRCgB6s6XbTLDQKAhHsdmKXbqqO3fiNIu6fX3MAiQPpW0aI1c1O3ztQKCA8L7dUl9f5z35-lPT3f69EAIIzEIIhZWBAyEyMSczgwMUIkgSnngcWaW8SiCixDzsJMAFOWRAweap664pGo13yRewyf3CO6oosxJ9FiAa7N1LwpNHUDRwgP70Xfbj5yh2aGhAOlBJw5-Se0_s4kFj46t8Aho_Rk1XHVf5T2AgUEuJoKSHh0cA-hBHoAdDecRRjiXBzIr8pehDdZhsQSIAwC7O7F3CGQj4tY75tTjwnHo049HAARGbH76rtx4Xdg0gEI_5-f-fsiIZkDgyHQm5lvT7YIAQIRcbqZhLCW2syFudVGxKW2kVOrcVfq_u5AARyI4fdPxjcuNgPBs2cfJ2mff_MRqbbQpy-umi5evRYdR7693TfXe_fPrq5vx3E1SBpYVO3dDz4KwvN752axPt0iMiOnDXN4s5YyZyFAeP_pk3ff_6i5rTYrzgJe9VCihaQJY2CReVlaKOcUatRiGgcAyCk1tWGaGPn26ur8bE0cY5bL28txNaRE02pSU29tHAdkvLs-MNJmNXG0k-1qgmE5zKWVxJJyOsJoEdljSHS63hDzMi8ZWADHlPNEy-GO0UbCdU7b7Wq_23lYVJhExlHGAcu8dGTZMA5tWR48uDfP8_OrO2S5ODkNM69NBJ8-fS4iFxen893hdnczTelku2HkRy-_lFfTUpZJWNijWrq3KYatlYRK-x0PSdUU9av_5J9hGvbz4ed__lf_wl_6L3_qK1_7-HYHQIGI4TmnR5t7X_ntDwA68oHX47DdTmB6sh5Wg4xDyomHMb_8yuPD7vDi6QsiIYQxp_DKiYQ6NdoBMNATBWCgQ1NDRPAwd2-OAM28Q_5aVXfsGcUIR0QIQIJemw8MDW_q3WJn_Xe5Z6Sl1Fo1pURJkGlIw8gM6lWrmmvAopaTdEdkRACzBYzToA6l6lKqQ8zL4kGmHhDmsbTa3COIgI6IdI9xyNMo280wTHm1GschjUMKr5vVyG5f-NybjLrf7xatOcXzp7eteTPLOfXI8sX9i5QSIrSlBQEyGUYLFaYABsBhWgEjS7jF22--9uW330xEGg3IAUJbkEhVWxYzDyYGhFrKIHK2mc6GAc3DYra2YDy5uZtrCyQkzENq6ubBOachcRYDN7CylKWUTi4mpMPdniW1Wpe51qaPXnrYbcpn56e9ta3F6qxEWMvCSB0AMKVJtQahWqMIEV6tR0mUcuqpLQhi6bYlsdogvBzK7ua2n6pRaBokMZLHNA2r9bDdjPfub--drDLQ2cl0Oo0bSZuRz0-n881wth1furf53Esv_a7PvzVlub7Zf-PDJzCkRjIftJmVUltEHnPzdnW9P8y1GczLstRiAVWtqC-mcy1382Jhtaqrt1Jba71XVlo1tFJbH59oUUJE0zrP5OG1YEeqIxMFmJalBPR-DwkTUTAEYDCmH_nRP_T6Z1_763_1_3357GOeuFatd_tlt1g7aJgD5WGNjjkPq9WYBFnbX_g__G-__tvv5jFJmoAEwggzQK8XAhEhEhL2S3AfHiH3LAN0VA4lZiaW1OOdgCHTYNaQHCOIIg_Jm0sehVN4SB44CSM6QJcsIAQyIqMBBHNICpZOBmq15mFyNSDobED8HZI3BgIQiYcBmNY5ErewI0EEiYQBsbYm4-jhrurehNFaY-nmNYYgRk4k_Qs0U4Q-ouqZdvwdlClAhAMRckoA_b8BAfn0U19GopSEOdwNAgIDETGQCdFDTSUNKaXWapfaurWwCLUhj6XqOB5v7wDOkt10XA21R-sImusf_YO_75X7m3__L_814TxXZwSAEBHwYKJpGtqs__Kf-v1_7a__FHwC41MNtbpebQ-Huxc3lyen9z77nV-6OL-4vXlWmw5JRAiJ9ze3ksWaAmEzc7WcBwwgomY-SEYIMOixp6raDzO9Mc2AvY0OQUJoZv01H4CmzixhDp8E2AjC9RAg43pF0-r6-mq-u7v38MHn33jzN77-jjmwSKkK_TalCxjyMNZSCQgJXD3QKZO6CqcwT2mwaIupUHYHzsLiZEjM3Ykz5gxuiP747HSY-MHZWk09tDTvwxYU-OijF2NKjx6evP3Kq3fzYlFTnppqYmLqyyhAB2QOj54TdXUiBkA3ZyQR7gd3QDCII5EljoCXjndgFgfXpoGgahFQa5OUzL2XWtQcAdPAqla9U18iAgEgJSZkAKylMsEwsFuPUMKxnuaAzEQCnJalLksZxkFdAUHdBRNCtKboIMyAIImRegaDza25W2_TQBARC3s4UCBAUTX1cPAIBCfBAFwOJRy1V9rNEIFRmrWA4xcDgD29YhGMPU3LZh2-SSlRIp4yr4ZMgG7BwuEwDLKaBi0mSZpqAPSwzXGN0R_dfPR79edAj5f0uz9CH_wHOgrzNA6IFIARBp9QdPrIBBEDQdvxYIweCL0FEeGfcHAAwXs_CTIzBDCjmRMACZkaAiThnIQAzX1eZkNCJIjo6eEsaIG1KQJiABFG4DHj1HsefZyQ2NyZiSISSzP3CAtg4m4-puhDEiTkZkZxPKJ8EtkPAkgk3cPSE5GEGIHChEgBlgj7cTuiQ4QckZr3wjyZByKpKyP1ihciuQcAkKB6VPdlaWnITV2IshACdzAiYBB3OSb0c36XMQOgel2lERBe3N2uVhNjZBEiEpbjgpup1x6GafN__I__Msco44oGYiRJeNeWN15-KSVZSnv-7Or0dL1Zj3Wuao5C7374TKueXJxroHFc390Z2Hocq9X1yfhoM77--IG6_tOvfl0ovvTZT-3n5ep2mcvu0f3T-6eb7WazX_SbHz8PZCcYx2mY0jYPkhIgmvu98zNyhODmoWHf_PDpyw_Pv_TWW4Nwa7qfDx_dXf3j_987FtQCQ6O0pRwWYYrQVZLVOK6miZlrs7YsEPHhk8tXXr3_7SdPxjxYqIC9-vKDxXUYhIVXKRvgKOwBaUjuRshqVrQy8GY7DoliaetpPL84vb66mtYTYWymyZsahAhBWF4JEly_uE3CQ5bNZnV9ebs5W0kWCWJhRE-SIgO737t39uT51fn9jSQ29-1m4wCr7bTJ0lQVrJR27-xiGCQzbk622tRLy0kAgxMQymG_nN8_abt92k7Wit4eWrXVevr4_auHLz9e5qtyt-hSx-00rrbmvsqCAa1akhSowvjxk8tf-u0PH56drgZOkhBJhOr-4BTTkNFBhEeRw1LdW85ZzV88u1qtN8O4fe9b716_uPzu7_uew74A02FZlrmcnp5GBHPX4bkjWIS6uUdPjBxhWJ1b7q6mQ8pzW3LKGGAaPYUozA7o7v0S4L0BHN47sq769uuPe2KotQZISeTkZCVAtVpoy5MA4jzXpdbbw1LNww2QEKkbOZfSimpr6hHjOPbDnFpjSWYO0FNETgTjmM42G2EEo1ZdRkH3CCTGzWp6eO_8bL2ed_Nhme_2S12qEpp6sSY5qfo0DUHgFq1pAPS3zzIvJCzUvw-OzIB-dnZ6bzP-yR_5gdwBhpmWZYaA1XpyhsvnNy2Ou_yIuH9xerbeDCIt_PJud7csTfHqZj8fChNZRKed9JhOIo7OzQrzAFM1VQ_vjaw4vuRCRLabTR7Gy-fXh93y-qsPd0s7HAonOcwFzNXdtAmLgwunI-oN4MHZ2VwqEQJB0xYEqkbEeZUSyzDkfo9wj9bTthjavDUvruOURTAhroc85XGY8pBlSDIknjJlkTdfezxm_vybj7_0xsuvXWwZ8d13P_rqxy-m9eb59b5U6_eWpTQn3O3m-xeb291ymGeQtCy1ag2EcECiqjqXAhYE1F-2lOSw3w3jtCwHSemTmluAAwl0cGoakpvV1jqkjrFj1oyJUxZtShEgCG4ErkY__qf-eBrxZ__230X39WZ19tLm7unN7m7flkNdKgB28CALAjOradM_-6f_zPpi_eF7H33r2f7y6RWhiTWW1JohCiCbt_4uZkQSCfdjMZZJm0qWVhp11S4zhEO4Gq7PLva3t0gIFuHOJMwCTHWekTm6RwsBAN2QRbr8wD045aN-W7Vz8MMhDaNpBXeWoZcAu1qh-5aG8aS1igwQkFJ2N2I68oVMgbh3N_lYQ-x6Jwn3oyO4GTD076p5w6BP5lTgAMgMAUJMGBBITN6FmpIjXBJjBLkauCVGC-RhCgIGSMjhkGUFyHmYWi2cMqGISJ3nNEychm5cypnNFDACvSxqrbmHVh3GTMJ5GNYnp4NMNAyzh0JKY2ailJI3RWEw11pefePx9dVOXSNIhkyIDG6L7vd3pZiwzMvtr_7qL10uh83F4x__E__aa6-8cXV55W6tKQS7OkYIk5piN5wBhoOas0OYMbCbM3G4iQwdFm4RiKmnxYAQHFvTTl4gRg8TkSFlBkQzRp6m095qevrRk5ubm-vD_j_9z36SVtPje6eZgQAYgYeBibd5CgsI50QkTAg5CQQx5cSp1cbCTfeJxrWMTGDQkINlaO61tGUuHrG09vH17qPrw6984_3Ly8Nc9Mvf8dZLF_eGxHVpELHUNkP9ytd_-5f_6ddC6Hs-8-bDe_cQ23rMTOwB5iFDkkEyYkBkljwICUc_5xEyixtoRE_vtGaE6NAbXZhYAFCYGAmcavPaLCJUHRBrx98SUQRTD-6HsCRmpOBuoyEUSoCuTdXdA02N-2zbrWPj-oEYyVtdEGG1Gjx0NY6MnIgglIGIuS_OKImBWzMCMNMA_IQbEyzcew7goC20GSFF58VAJw_hMi9AJEKEx4m4htsx8RWA5AG1KRh6d6gBV1U3ZyAE7osI5hhy4v7FZ7EIyYJErTkK3-0OVbW5e2Bzb-4djBZmtXdsjhWyfpDu-RNAJjr-iQiI2tNCAsxoDmZHGS4QeMQnl9KjszYg7EgW8p7MIURhFIz1OgsjhiGEMDIDIyShcZDEEuokABH9QliL1uZVFSLUwVSZCInMzR0ISQi5H9vNIwyQmmkSJqSibbFCBB3A2loFdwk0Dzev5rVVDA8EQCMyxlA1rUFBAEYQgogAram5IUN0FwmAH8OWx71MBDQ16C1DAGby0IGlz0QZuafzAaEVdbXWbD_7za7uqt0c6qEZEUxj2kzDehoxIh0vYqFqCBAADq5esP8h2piA-8oGwI5uskBkCCQRAF-eLQnlcJjRnIlW61MyOj3dAsTtvExTTgO3oo7ACLWVNpdAV63DgIeyq7XmUWocUoK3PvPw5fvnY8aiy4OX1m89vHh0snWDBrreDK88foyQbImnL25lHDAlDH7z8cufe-VVbQ0UvvGt99frTavmSBh-OMwAJIlPN2dIAEC3c3vnvfff_fYNpIw5hYE3i0NJQnnIqzxc7u4kDY4QQOEqlG5v7iq0eXeAQ93v9oJgiIy8msbmbq4g_srJttzMq5wye2IsumzO1zarWiHCAGgeB6tK84NHJ2C22-9E4Ox0ff_sTDAeXpxH80Hy2cl6NQxh4WGvvvGyLyqAq3E4HycBEqGRR2SAIR4-OmuHcrrerHIm8Nfv34fmrbRxlT79mbcIm4BlQ0YmThFQwYnEI1IazdzcL59fklDbL2cX988f3hvHvM7p8cPT3dXlyaNXHdGJPnrvIxrzerOZNptxWgsxpZA8cCR3xmb_35_95f_wJ3_uarFFzYC3J-v9rpSmy2H20JTpdLsJBSvLmPHRw4vbq2fnFycn9-69_-Qj8YqBYAER-3npfRhVV_cgsAhjQOYWhkwKbuAe4McBkxKzhRMxAubcGy7UG0GdiMWCHtbRhxDOAFlkNU6HZa6tEmMxR-bVdhQI9_BQIKxLW-ayn5fbux0JqTbrHz5wAERmEQmAogpApbZhHIkppdynqKVULbV_SIhICJhEmwKF1hYYMtI05JQSM6YA1da0eRgkDicjE0l9Syks0VDNREQ4IdKQ08nplolFEhIQEyNMOa_G_Pt-8LvdiQBVdT4ctPUlrd5d7ZbaAHG1GoXxZD2djMOQ0lLb9d3-bj-3ZuZOHsRYljLvDq1pLUbEDKSluisgAJBWVQtkQSJVr6UB4DIvCDSO42o1LocDAGy26ynz_tDFYUoAtTVTS8LWVIs6aKfCmftdmT2wtkYsZqHulJgEVuMwiIT3dCiV0gL5MFfvw1kCBKhF3UOYBGFM9Oh0fboaN6t0_2Skgf65L77x3W--9MNfevs7H9_bZGbA6-vd5VI__far3_z46u5u2R3K4TCXUhVC3cb1WEoogBMvc-2Wc0JxNW-qpX3yxgEEAmK3Nubcaq2lhgcoYFA4BVqSkVhCmCRpBAgFggCAmlqQZOasaszsZD2JroX_xJ_5iatl_9N_82eur5_GxC-ePfvWP_vWsw-f3-3vgliRHZiHIU1jynI6DeM4fu7zb__4H_s9_9G_91d_9Z-984M__EPkjgEkqS-sAxEZUCQAWDj6OSCwz_ncHYiAmEUoEJnNzAMoi6TcUWYETMTE3Lu8jNivpkhiDkQdk0EeTiIIRESgjaAn8cDdAcExWpuRyJqZVckjsQBSzhkMiLnanIeR_Di3SizugMRulvPAIoBEREkm8FDA5oAMQGBNiZDHBAjBYOFIIilBOKfBnQLBXdHBwyMomB0ImaJv0gMDJQAJrCHAPC8938-UhQYBIsSqi5vVuiDRvN8hY_-tnwyWoZQSEEjUY8s58yem7iokFHByunn9jfvh7fbjZzmG2txVtVQJcLdwH8c8L_VP_aE_9OLj6yRiXVriXeiEphjEVVtercZ1mnc3Vevf_umffufb77_1-S-QcEA7nvPcvajg8ehmTYm5WRhEuNW69IO4qqkWPHJQzLyxJGveqkpiIq6lOGAEMDGGIUFrDQHCjUmYCDG8zG2ph33LQ_qtb37je7_8pZxJCIhQW9OIQMp58GoM3EoDZBRKQ3IPCkGizNkims6rcR2G6zy00mqrMiWPCu5317tl0d2se7Ony3Jb5pETAX7-zdc_-_orJ-crx_CAvFrHlL_25Nmv_MZvNYIvf_qN3_3ZtzdTPt3kYeQ8CDOjSB4SMRNjj21AGIRJYjVVjKa21BoGYeiOVS16jzcMIFS9mgIAJwmCpkcGbmvmFqqGxMPAJKTuHUpwZOIiInFpGtAbB2jmEQyIkhIBHce6Qp2lywyJofuVwH09pAj0gBruHoFxzJ0ojFPOWZKICB9LONE_FKDV3EObOaCHd7JnB2CZeQBqUyJmJHdIwkzS1xyIFOaAfWAN5hYIyCBEZmZunSEDFtM4sVBRBY7NkDrbixk9uoYKqF9F4Hi2J0LvEBw_loe0WWvWJ9bwCboee72_l08j4EgG7dN8dPMAaOpq0azTOIIQianbC9QcEYWJmVJmEWJmRmIhROw-pq6IJ-rF687VhEBSQPfokGBHVMfaOjrQ3Y1FAI9gYu8FuQghEcIxJSFGADBUDa2hNbSpRzAEB5v170FUA7eo2gLAECpERJCghbmHepgZoCdhIc493XhMOLFbACEzuUNvSbobBvQlAwQ2s-7B8XDATzApiNH_0gmKWTHbh10dDgc9IGpKNEp6sD09G8eJJUVI1wcQIkCCjEBHyUcAIfT_nxAIUIg73o4lv_PhMwAQmVKSab1ixlIPDx9eCJG6v__hs812PNusbm4Py6Fs1-PTpzdaW7nbj4QCcffhzcDQ1ADh7ddfWrX22qPTEePyxYuXzrcnm1UxO8y7-VDCcDuttuuVe1iQm-dxBKGr3e7J1XUzV7D3P_j4dDsedktbyn6e3WE3z1rqF15_fS5xs9Svf_ODpzdtt68kMqwmGjky7OwmpbGWRsK73b6YqxoSLssCZrt53o6yHBbS3SipadPQqk2Xcv_8lIm01UWX8_PVdjOeTNPJeswM1OpLL50l5lYdEU62Y0rAAZtxau2QCQGiWRPRTaa2323y2A7zahgQHQUyE3tdT2m7ykg2bOhku3pwdvrw_jrLsNy1BxdnK5Epc2ZODu7LyZjWmVeURwZb2vXVZYShe63L9mzbFnXXKQ8UttlOw3ZclrKaTmq11ZRoJWkSZJq2a60xMm7PTzFxW0rb35FZmVsDH8ZU71x4XK02zU2DjZIV_3f-0t-4Nvv4Zt9I_vF7H1orlLDNxRqMg4xjCkBvSgTraSp3N29_9jtmo7__8788bofWjMKsNYeuwgCMGBAxoNcWGbgWdQvrQj5CREgp9W2VqTNB1QaIwyBJiPhosA5ASdKN2TkJCyEDBR6WttTaQ3rEnINTGpwM0M1U1bQ2YAwmgBBhZNSwqqW0BgGG1ByWFkvnEUsiRGYixmnM05A323EQWY2DIAqk3f4wZhnHlAVzThQ-5MSMbW6GeP_-6TgMRdvdfjE311D1cRw8os4FIqCaEIyJ1qtBOK3WK8lca-vwdczYzXqbtMqSJIMkCPfNeuyQkn1pQeC9-Gh-upoIsLkd5vL88q5Vsxb7_bwsyzKXYDZVUwvEMBMhYYLoMIAQJmEmIUL0cCBq2sCBmM_OTtD5cCjDIJvt-vndjOBIuMyzjMxJWBCIgMJcQ8PVIryaXe8ORNELRatpqtUS53FcrVEgCACaW6mNkNwxJTY1QgqLEUgQw6K0tluWVrWW-Y1H2x_53s_-81_81J_8gS--ef8sQ3BEUbje11_46m_9xgdXT0t84-MXzy53u9r2pS7NmuNSXJUAuTmoWmtmYRgACNosWpT9jBEpJQA31yBA8DZX4tSWklMGM0JgAkYHR21LznR2_6SVOqbUXS2UGYWGYSDhqo0gUBA00K0e2k_8-T_77Mm3_9F_-w-b1xZx9fTZ7u7mMO9RfBin1ozGaXpwMYzTsBqTQ13K3e3dn_sf_bl_43_8bx20_vIv_JPXXn3Yt4iqR7azaqg7ABxhNwEEQIxIXTyH4R3rzJ80ygB69ENSAHPm4GM7wNUAJQJQcjVFIkx9YAUAhgBuTjJERASwcIAjgzWNLmkKoB7LD5eUIABJAikIHajW9gneDrXUsECUQCDq0hsnpjYvIkjM0Dv7ruCOREDkABYIlI6yT0AFCGIZB0oMAZQImdUAiD2gh9zcFJkBQHLikze_qObuwXkgoFYXawWYe9i3tkUkRfgwrNzDTV0t55GIQhUJJWVmioiUhvAgRG06TCNzYvCze6cHr3_0B373-5eXv_7r71YFrbP0mHISM5tynuvy43_0h__rn_7vXtzeqiIEtlI9gokDmAjHzXi4O9x7-Oj2arceZX9zR2gfvPfO57_8fe99851-JBkkOxiGY09PJQmA0loS_iS9kPr8zjFYUiexAACLmCqz5JyX5UCJRYQQologBhgSWjNAT8MUYZKSLpVIOIlMw_vvvf_l7_2u3Yvr_bIEZTVFxDBF7sAA6-ltZOlMkTB3M0AHQA3QaEEQREIJQBnEDbxp98iaej4d2O3mbv_wdKMGxJAlf_jiurSlGaiDgzjBUuo73_ro4b2L8810sTp58vyaCQDYIBhBhLNw90h5NWayYymetGmfnhKTA4hIR88tzZC5q1prMwQKC0BSPQaguwIx-imbSK3DGgMCe4SIuD8rLQzUgrAHVYlJAECIReg4wHdoXV9g2hkyZkc1bEQwE2AQUiJGBySc1gME1qY5s0XvgEQAWnjf4bKQVuuHag5EwpTIA7r6mxOrqflxgdsdOj391eUmiCDChOQQRNB_JUSIpO12HDJBc6EurY0klJmZ0d37ovYY1HEg4iOQq6NwurnMjyEaJrbArhMKhDBDBPcgwjGlnqBqrfWWMBL1ybt3-697p4n1f1BE_w5BuDPRasrdU5Vz4r7qEe74fCFMOSVhBEJCNStVHcEMLEDNgVgtWmulmgd4hFqYRynVkdSMsFM-AbEbBiI8utSLkAIoILoWxEGJBAHUjPtrlICYmvUkEGIc-Z5D7onGoC5ToOh7WojoYMS-0Ot1SO4OieP1CALCHBBBe9SBAJBqhIV3jyMcrwoRDkvVulgWykhByMiByIzE3OcOaoFMpc6bcR0BH10-Oz85HUSEJI5_icAkRIIIJPIf_Rc_-dvvPjk537KklDjT4BRvv_Y6MKophp-erjsBjBB3Zfng42fmuBryw3v3atNnV8-HaWCAVx-dTG6vPTi_t10NI3392x-8_PBiNaxba_u5Prl8kUQ-89pL5khJFqGruwNyMq3gChbX-wM6HA7t4vx0Xuqy1F2pRXVu9fr69vU3XvnW-x-_-62Prnd3S41hmgIhDeN-t3OFRJOjA3YrDT24f6bNEYFYvNm3P_z4runJZl0OjVMyQw145dGjqnW7XiHC_jAbASCcrSY109JO1xMhXDw8vb2-G1f5_nZicw5ksfvb9X5ehEiYy1Iv7m_AdN7NJyerLLSaxlorEWxXIzlsp9VcZgTihNNqOhwOUxprqeMgFMQYq02upnfzfr0ahyFNwwCIOck8l48-unnpzfsESINMmxHNKMO97dqDmllrQQDAcXZ6sr-5Obt3ftjPz59f5dVq3Kyef_uj9dnZ1fNn5Lp7cXfx5qvLbmEhZgDQCrBdDQC0FEXhZV4y4s_97K-uz88e3T-933yappTEVJdS711sI6QtBQUWbczUmo_r6aOPn33jG-_-gX_xhy6vapi99-H7b7z-mnq4a9_BOoQ7avPAIOaAwIjEom5qHWsGRJQyc2JEqFVJsBcZmcjcMks_WQJESqS1nq2mk804lwYBu6W4w8XpOjMJQSm1WoNAIiCU0kzdSjUi1ICH62Fu0ZoaIUBXmQIQcyYzlZSIqVYzN8lJmFVtyAMALK2YWxqk1SaAy76uxnHKnIRrKashEct-qTLm44BWo6qT8GEupTVMadHWH0F5HMpS0RXVGQLV1ushZT7fjlbb93zhjdUggL3wicxcijrh5c3e3KfVOKa03Uyl1OfXu7tizy9vP0HYhWTuryVtmhMPwnNtx5FNhDWfDwURWtU4IhAQHESYCMvcHr1yf8iplMU9UGjeF2ZBt1qam5lHVN9uN49fuV8OSkS1lDwMR1B1hJmebE7qUrKIqVPf4yIxxVKqW2BAUztKZAKrmlkAwsCChKo6yJizhPnv-663J0kJGNzfe36LA394e_uVd5-8--T24xutEJf7w25fnl_dLHM1c41Aon2pIjKOwyT59u52P1fkZO7uXrSVVhKnqmZdM-HH920exx45jTDAfjPBjknlTDkNQEmLpoQYsRRVM-FESbg_wyWYkBGJxz_3P_mJr33961_99a9G1NurQx4TYESDu-vDtN0OMuaU8jCM43i2Jbg5uIU5_z__k__z__Xf_ouHefYodZ7nauzp7vYaIvQTImfvyrs6RBBhyoNZEPRurhBzhCM4BgJzuAEGCksemylakAgAUEpM5EjSP4aCBCGcVBWZO1MCib1vzaunnMyDhM2MmZkQ3MINCEMd0UlS9LcmRKD3-3q4M2ESqarjarLawK3rR_uvUAvqrFviREJEiIGAnQBOlIiIicKt21dJEjoERHMnRGAmJmIOYESkJEz5aFXavPElYBmmscxzngYC1FY5D1WViChQiPv3VIbU_RCEwpIhcN7P42plrZr5tFrVeeEkyCRZwoEIwu1Tn379i6-__l_-Nz-3u52bgdb6O6lbzjxmCGv_0o98_3_8X_xkKO2rq5mrMiEnbOZASK7b83NmONzs51rKQaeBw5ab6-cvv_X5jz96XzhFOJqqKQliIEmCMGYMB8mDae2gGAxHRGstDSsAdfOUUi849lNRWUrixELaZ8AIKQ1qyihAKDmbR2hzdyTxgPVmFa5feuutb334pDTjxPVQEKNWQ5F-_mORkP6zqHzkEzAJe4AIddLuan0Kqizd1hTEiAApp2eXd5Kyze357e7R43MJpEQvv3Tx7refBti8aFVd5TGIqraPn36MhK89fvT43vnV9S1Ar04ReGj13tGBrqhgGlJyQjBAwg6pdEdAZ0QHbA4e4QF2PLsHBLBQBHYb1Jhy16e6R0qDamNkgxBGAAoM5qTuSahDQjseDI4WPWdG8nB1SYQUDtjvPCIJINzNMdyAGDvYzjz6a19EAiIncbeqvuLUPBgJMKTz9Rmh27eCWj1mVNRCzYjo_8_Uf8Zst6X3fdjV1tp73-Wpbz995pw5UynOsA1JsWokiqTVIqcpSowEsBBYSIHiIICSGIH8IXCJY8cJ4liQhBhBpEBWiSJLFCU5Ekmxir1ML6e_7al32XuvdZV8WPeh8uUAM8A574v7ee6917qu___3Q8TDJN7dW2TcDl9CRm5s-iTS5WyuRM2HFebeSRKhZeZB0tl6geFJiIVyYmauFg5R1Rtoot0BDgbu1tJFJEQRaiJjdwMgEnRXpMPFINqpHynMRdjb7Bk5EALR3c0a0SDMIH7_hoTATBHeZvx9aiJFT8IpJ8IAOLyumLjrctsymGkbYVSNolbVDQAIzaDWCg4WzS8GwFjNwyEQoP2f4c2eLsilWmvyE1OQNLBRBEZ4DRckQmzDDBGx8BayUTtEt5jbzQR6lgY_YUQm1HZBxYBoM4vwiLbuIWSHgzu5jWGQ0NwRIAiaXKI5BdrAvhkJ6BDZBCPcz46gaG2nD8wAhEkEAs3dzDBiNaww4oPr52dH6z5nopaHIjjsegEDU8p_6T_7v7N3eehz6omdnIj4lRcfEtLXvvL1o_V63acA8Yhi9fnji3lfHODhi3drhd2uAtLpenG67O-suxfOz-6drphx3O2mWu6fHp8er999fPnghXtfe_fJi_fOX3pw98njy7HWverNdgfIblCmqRsWoOFu985Pu6Gb58kdrjZ7Ndvt6_X1zb2HD775zXeTxDQpSZ4nXS6GOk3IVOeSc2aSYppS8vDbzfbk6Agpwiwleefxszrq3Qcn42Y0RGckhvWyG_rcrFX9YlCzWuvxernqh2p1YEEk9zpVJ4aOKCU6Plpurnfr5dAPSa2mIfcJFykL4mrImXmZu5vbWxZcDF2YnZ6tdJr7RZ8zzlXvH5_t67RedKrGASkzcZydrICQhZaD9EkoCJjqPHepw8FyIFMK805oscrPnl4Pqy4Rd724TaX45mb34IXTHCFMhmYaOQ-IZrsJBMs01f3oXu--9ABJNnVUiE6Gp9uJEIkEJCK8KIxTQYAPHl_8-jfevvexV-8In56dmNVa6zyVe6f3q1vROYS1ugwpoexux7e--fUXHz4cVqfj7uZyd_3g7gNrYwhCtZBE1YMCLKLhaCWzu3MbqzTrRwARLXNnpn2Xa6kH_WCrIX_YMkyZT4-HpXS9UK1W3G6nyQMhYhgELcwc0es8E2LjjgdCRFQzDzdVDVKIAJq1uAEBaURirqqJGTy4TXt-35DnIIkx7OLqdr3sJCdEBLflajhbL8Zputzs99N0tdnfOzvej1XVJadpssbeGefqpmqg7mE4jjMxTfMMWhtp9Phk-Yc__7mPvPboeLlc9tx16dNvvkwGSGHFalUHMMer23GepuPTo4S8Gvp5Lle7_e1-3k662c4WgYFqRoJzqQgwDNkj9vuyvd1GGECgByOQUIRr_X2LKK2O1kSw34zn9-4ycx1L6nK4zcU7ob6TwKhV59lOT08f3D1fdX2zf4XqrBYetTQAq02lVNVuOYzbCYmTtAkGmet-rkX1Q7lzBDUlmbdYnQcBeEtGSY7vePn-w7unghDIX_vGe9-6un2-Kc-309VmvrjeXN1u93PZTfPt9bif1SLUHQOR077UJLAc-vVqeXlx7YBzrbVaKbof58Z8VnMRcS1mRsyCZGbAUaZq1pJBoLWS8Lzf52HIlIGhbOcIbY9wZCRESRm8gKNbYcR5tD_5Z__0W1__ype_9DXVenZ-rJNO01jGSYYFS8LG3gzPRFrGcnGj05xz_sv_xf_xf_5v_jvzZJHs5tmVA91ebVZ3znebzTyPAtwOft5YPR5ILWgMQeiuiIHIlKRMc6P-OwIgA0B4SN9HEIG7OqfU-BWmSkgkrLOySErDPO27LtdS3JyTBMDBgYOhqtiAm4BhzRAaOS_cCgs7UJnnxXqN7vNcoP3RrdUmzSnGxBJNKBbhXptullO2cAzInNUqApDkhuWwducJj4icBzVvHX5VTUna2QMBiSXam5STDJ1phDmfvv7tDq06gExk1YDaEU0OGqcwSdnU1svjcR4pEVhrSRozRRgSuUPf92EWYR6R-q6WmnLHxD_0B7_9zbsv_K2f-7mys2LmAVorCxfXoUuM9Ee-8IOv3Dn_r__JL3SL5eQ1iiNFkgRIprFYrnej3T25gwn2F1dzhf12j2wBsN9uzh-9qPut1unQ8QVikmgKpAA0NUQnDw8EcrCEAuHqkCVFmEjSWpvAGQMjXIQBkJGZaJ4rJ3aLIAg1zokOT_0p950hIgkhXF9cftu3ffL9p0-3c1UHrUpuyAjhLTXdJs1mjsRDP1ippdrZ8ck0lQNWkEjE24fc9ckBwqK4CifOlITCzCwu9uM7F7cseLUbX7p_9vhiR8xWramgGk323SfPEOPRndOjxeLJ5SUwV1WCJqJDFkansVQmbHl3Em6ROCRkhCC0AI2GRgQHbAgjBmpZFWsEGtOck1YnIrOIA7SzwViAGd0DGcisxXZaLi4gRFiIhLFfdF1Kq9PF2dHSiteiQpBF1keLxarve3EIEa7V3QzNk5AwMUJKLesPahYA1RwJwZyIAxGCQ72d_wG9S32AMbODA5GHuXnG3Bi6AdFYnADR5Q4RgQKbLgyYEMZxZmZuxz5EQrh_76RL-WghXRIi6lKrJLdbm7cVBzbCfTt4IraRTmPbN3NWsws3mxUzuzsEhh_G3hEtmwNuJszm4RFMVKqpN9vOAZCK6L_vvyKinKUXJnPk1jmWFv89tBWyeHOgAJlpM6FM1fZzmYpZgAd6WKsGFjNqHz6DqtUmyGmltyBzQ8BmmQEkwFaiiQ-1zU4A4aRWek4e4R5JxMKlfTqBRNy-YtAAPgzmLq2REAEfxjS95RwOR3o8yHxbFgvbXIMPix2AQ4MCKCCar4uZzAIIPiQJhUEgkCFUcEhZa8xqAGjhc5t6EURArbuj5WmEvff88f2zOyKSiAMCEYiZRcKcpLu-2f2Vv_XTy7TuV3maSssln985y4n34_7mavP6x1-ephoGDnF1efPuN953kVr9_Hg5TfNU5zCr-9v7d84enC9Nx_sn65TwcnP18Hi9GAZGuri6vd7NOfGnP_7R_e24HIantzdf_-b7xcKBdrvN6fp03O3KVBzh1Rfvbbbj7W5f1apazunyegNuaPDsg2cktNnNw3J5ejqcLJfTfr8fy1xKDVWCCChlIqLbm83p8XFKGSgQ-RvvvtP3_dHRcnuzmwGYoOxns_rw3j2NQ8BLslxeb06PVhQwTdOw6BJRKXWe634_nayGo9XgXjOLhh2vBhbcbvfLrgMtJ0cDqBOTeRUiTjyOk5CcniwcQpDmWnKS8Oi75GoS6CVKmU_Pjtz8-GhZx2m1zH1QR5hI9vuZWDab8XZz8-L9u4NIGefTo-5qe7252Z8crYVo2a_G3da9qo4vvfTi9nq8c-_09vLm-unNydEgOe-2-3653Dy7htBa7eGrLyXEJ9e2yOn8-JgEkKCYrlaL3CdTEAKG6IbVW-98sB7kjZfuoVqtNYTVfMiJmIvqftxFACMS4Ve_-c133nrnh3_oB28vry8ur-_fe4BMbg7mRZvE_HDDPyR6Iswt8PC0gAB01FoVIiKEuc-pTjXa8yFsMWR0J4yz86V4CLJB5JxKUdeoqiy07FOfO1MDdHAqak5ATCmxqq2XnVsUjbkUBUiZaonwUDMETEh1KqbuQFVVcmqyvqqHbDozbLfTejX0khZ9Wq-Hvku1VADulul4tdhtp-vtLrEoxjiWol7cEWAc5_04EZKZNSpJmw0RQd3X7_7Ct33yjRcQ-JX7Jy_cO314dpz6_uHZuk7FHFLPEOQA1byoq9uq71bDMM_1drt_98m1k1xv9vtxDgA1Q6R5LpxSJ8nNtOpumso8pySuSkAWhkj73dh1uR-ymiJR7rKqHp-uCYAYAoIkQxxYkcerhZWahBaro0cPz4dO5qm0-LQF1Orh3l76SESBVqa-77abnSRpYlUC3k2TuTsSQFhDYlioemYuVTFlIiSExNgN3Z2j4fu-_eMSBBHvPL18VubJYbMrVze7690YFOZQzeZZ51pVLRy0hmRuI79epO_6CNiPowLWaqXWqrWVSjBQ1cjR1MxcKCP5frdNOc9zBfIGYm4nHZaUUna1ab8rc9MauJsjs7qBKzOWaRpyt8zLH_vJH_u93_ztf_lLv5p62G_LuCsn9x8uz1IBkISvfeZVCrGpAHiUfVLV7Xx-duf_-lf_o__d__Y_uL7dyWl_ezXut_vEUHZlqtp-OyFCiNzAwM2MEZJItPoCcQv35tw1b-7h9YnEkkGrA0FKVs1NJSUza37uMCNmN9NSiFnnkZhCFaLpNyg8GsECmyS4Vj6kZY2aCRUNSVRNckLHMu4XR-eE4AFMAGYkolol5da0AySdZ8lEnD2cAfrj4zJN4MAiavXALGnEencSEUS3hg1vwlABaNabtk9vIYLfp3Iws-Q-k5vmxaKRATBlIAIS9yhzAWRAYGZTRcJaxr5faNHAIJEIkNxFOAESRS0z50TEQBzhkhMJ7Ofp9UcvLpedjTOKUEqS8yGNkJKZb-f55Qd3x1LWy9XuZi_BBCDCSGBakbzohAi7cV73w-04Vt30fXgpxCQoX_v1X375o2-UUmYtzOxBajZNRR3dwhyFyUvbDKqrmqsfstzaIuxJUngQAWDrXLq7MWKEMyN4y1wpCrvq9vamcR_rrAIkTHUsi-XSNR7ev5cyE0HOiYgZwGaTRCKECJKYATAswEiIGGctw9CxSCASxX6716JBVCdl4pSzO6l5nXS3L5f7uQo_v9zO1b74zQ8eP765vJk2u5kQhBAFS639sFBH7vuvvPXuV9955_z85Ds__bGjRX_vZJ37jEy5T4nTos8nq0VOSRIvhrxaZCBikbYaAGq0B9Cwao7AgVCqTaaG4B5q1jSKiNy0bO6uZoTRd3j_xbMHZ8cfuXP-2oO7p31mCDM1d2Awc_WoVquXAOtERJIr7GfbFX22H2-L7urMQkvmk2Hxwvn5us-JIwsLc5czAhJJM0O1e5W7GVhoBISDV7NqxT2sWJt_tebsVIqqazWzyDm38Yy5l2qIkIQTyTRNERAW6C4sAKDVur5jJELkoOYV0VIXPSXioU-rxZBzDiQ3Q3SI4BaIbygMj2jCP6DDTaCx_xujBqkZJYWwS6kpb91D1czc_ACqt_D9OKn5WNQcWsK3sXKgcYvauzGaBJobrOCwyokYp7llqdSasMuK-lzVLIr5NOlU1AKAUN1rrbWoajPvAjgg8zTbXD4c1wNitCIxeli7VUdYIiRC8xhrAUDVCAQiyNIpurp7hFm7fKlHKLiDW7h7oEO4uwYTm4WaqXttyLbf9yhG89W1LRS4GQSEGkZUMyAAhAYgqmoORoQN59lgoHBoZSESCXFLWoPTVHRyrRGVQgEOBCwPFGaUVo9IhIRtacotkkRAAMhISOlXv_jlWqPrUs45Z2GhTHR0eoQEzy8u1uvVvN1jABLsp_H6-W2_zugqCYzo6GytWt3KsOjXx31edl3XnZwvJMVuO6bMQvz02YUsht_66vudkM8zEb717MnzZ7er9aJOc5mmxGymAZCHfPfeSRBd327QYrMdUz_sZx13Zb1c3-5ucyfvfHD9wiuPFgtJmaeyn0bNOfWLgUnAzUsloNBYLvub2ytVZWZMst_u97f7cZyAmBCZJSNd78cQturS52G5EJCT44WHGyIg1Ko32y0gLlbLlPBm3E-q5iidbMdaa10N3enRaj_OQNwPXbVaS9ns9py54QG5k8vrTRZeLFPXyWrouo5AHcxzkqN1Pwx53o9otsjSJd5cXfdd7HfTfrc7OVkcrfoHd0-7YTFjSEabxmL25kdfY05z0UDOXXfn7CwNvLudvvbVd1964Q5W7YdhcZQevvJCmev67CjnvDpepyz755dmobO-dG8IjFL2hNLl5WK5nifVGo9efhCcXLrrzbjZzX_zn_567buQbjMVCgCom80WLY765WpYBXgWfuHB3U99-s2r_Wbc7nfbedKCxLU2XTYxoVk0GE1zUxKEe8zzfPB3tgwBhCHup9GqNfFp7vtwJfAAVLOuz0OXfbIuJ2LUWsa5JOah74GoBmzGUgNynwPYIaRLqlam2WpNzO1BlTmBAzugwtHQpUTC1GVJTJwoIKopEM5TIZJhyJfbabHIIoQAp8fD_funQ-ZEmIlWi359tFqv8tFiMIXc5cPCM0CtfSsDAoQTS5qnuY61zipZUj8AAyAtVh1sK4-4BMxCi4TLLC-cr3SutZ3_AprVZLcvAbFcLJKkWupmN27GkrturBoB0gl3eHqymsvcpUxA7chYitWiKXfzOCFJNSWmUmZofUqkCBz6XgKWqRcQiEiU26aShLWMEbHoh7HG6Xr92sOzHM7ucym7_b55bKZpMjTJKXXderk4Xq9Ojo6ePH46FyXGaoFCs1fzMI1S61iLQ3s-K3uA6ZCSMBJjKVVQwuoL56cZgINuxvmdq83l3i435XIzTZPWonPVSbV6jEXnou5mVhGViRxMiCIiEc9TbZuBQIwAIUaLDmWupfkQAry9epr1GSA4IQpREiRIIgAtGJ3dDSKYiSSpKoATQeIAjDJP4LEY-h_-1_7QL_38z_32r_-WCNaxJIHJ9rfXz-oE53fuL_qji3duVmfHqjMRCJf5Zvfmpz791_7Kv_c__jf_wuXNpS-6Us05S8oQAWBHd5deZ8kIgIYQ6OEtmASm9bBfR2BicHePlnZGIoQgBK8Fhd0sd7ndFtocGJqrMyDcAJGJCMBUXY1S59bGVYEIddq3rsHh24norgiASQIaxFsbVC_1PUja3l4EReo6jOAPLxsBbrWGq4iACInoNEtKrqFzSTmZezVFJGQ2tyQSANCO-cyUyFs-lrkxMyinpoLlnAAoCeeUJHfgGBHEwkcf_QOqRoxhTkjIDOFt25277O5gsTw-Hnc7EsmLBYKrOhF1i3633Q5Db7V2uTeINPSmtV8P1ze7IeeU2cH-5B_-_h7zv_iV34C83E0TmPaSDhLjMCb6yR_47p_-F7_SDfTsg62VXYTrfKvTiFYRqapSkq7LL71y9v5bV5DxgGsq5qEC_PTZBx_77Pd88K2vi0gEEGPuugAjDK2Wh07nQgTEwkTuLqkzM4igJNWKpAzRvMsuOVmEVSVJSMiJI5w5hTsgQngpxtzS1pD7fp7mTrJjvPLCS1_82ldOTh7cXt941arWmoIQNnT9vCskHAAYxEjmoWEevlotp7lyTm1HQMxCUq0QE3DzOGOpZholTI4GrVqmYoHzXBdD_szHXz5aLkoxJnDCNKSh701NOvngyXMieOn8jIMvrm4jcS0KhO6Rc0rMmXi7n4W5qBKhmgICkpgdNhVW3T0UTYg9AplaZRMD3L01KwihCa2ykFB6dG-9yujBm2ncl-n4aNmvF17NTRmkUXc7kXG2B0crEUbCor6fFCgNfeYkXepdzR3ee_wUmBddd3y8wggSWuQkiZOkYpYTodpunIRYVQERmpgwoKoCRju1Y9NtY6hai7swcSBOc8lZvCmfWcJDTTlRi9AkkdYxbdEUIgR08EiCXUrCeGe9ZIywyF2KCCHs-pQQP9TExkHfRdgmeEjUJkOHXjA0SioQUxYJB3U3C2skb6CAwICUGCLMnIi8jcMPJ1QgpnbmbwKRtrPohIc-i1C7ZrR8q4cTYwQ1e8A0ld83CM6lOgKzFDULNIdSawsvHdQH7qUqITgAEWs4InuYu7X0PxGFhZmre1UzjAgwiJxSywOEgrq3ZEC7GWmTBlCe68ztDmchTEKkeuAfI0FLWzsAMx0kXQgA0T645k5mAiRqkS0PQCQHhyBzpwBiAI9oHSkza8IHQjdv5i8kZII-84J5motWPaCPGzOOZNktEOKDy6cPzu4IEyEFBhGJpOa2B0r_h7_y_3jy7PZ4tUYhdO-GoZe8XA5dJ9fXu5dffhCmZbblon_29LnOxVx325K69atvPKpVn7x_Kbk7O17fPztC0KNl9_prd_b7abcdT06Ptrt9ULedZvb5eL0ep1q07ibdq41jCaRhsXTVo0Vfiz568fzs7tmv_8oX-2UecucIo0MM_cXji475dh6R0usffy1pWQ951edpqlebnQFABCOqOjGQe6nFDPbXt0eLzs33ZX5-eZmYFuvF_ma32e-GRb-9uckdnxyfINPzq23uuEsS4eSgxUuZ1kdH4C69iNA0ztJJknR-vNzuxtPjJSF2KQNjVQOHLDz0PYsAed93BgAAtfrLLz2sU0mCi2ExTyMjMeJUptVy2M9TouiSSE6SkyAI0unJys2X64WaRq05p_cePyPm9bBcngzjdpbEy5671I37eXG-KnVOIXWezeqwWILI3bOTy-3N13_v65_8zs9sbjfgWHQcN_tE9uCFh2lYupvuZtUa7KuzY5aUiHabcT9uZdndjLtxN-lUd9fbHdLrL74CdfzG810fulwtn1_e5kyS8tXtZi67vlt40Ne-9o3N1fb1N19__Oz5-b17CA4Bc7EAUDcWdgAnq-6t7544uRsSm1lACDEiluIG1qWEktx00fdudrTuj447rBaOKaeUxMxUIxg1wtyBhQEWfQKAJJyE57kSAUVjiLG7zxpzKYjk7oSNHYd9lhbknrTWqgDoEcKSkhABBtw5Xp6sh2Xm7Wa_XKQ7pyuvBhiSxTwaAHGeKjEQS61aq3KWcayNnuwOplbVItBNiQg5IQUipw5jpy89OFt1crbuhYEQWzjHw909p-QasyoJbsay6BMAMsJuLFe3WwOcLbZFZ7Vqce_06Hq7g0D1yJ1gQHW9utloqe2ZOpeScpp2E4vUUgV5nMa790-XfV-17rYTMi36ziMwIPcdo4Hx5z77xlnPy2EgDzXPOT2_3m1229R3-6mUWvJigMBwI4S-z8K87PLNbu6ypD57EBGbVojD6lJEECE8rFQKrLWmLO1JlYQJHA2-8PnPrFhq1d_66tvPyrQZdSq6205mZmYa0LT03iwpzAiOQNXNI8yqh56frG5vN1PR3VRNq3nMtQJirTpOxSwYWaNwykBhdarFuy5b0banRcRaa0qZCLQW8wNKTkjahJsZtRZhDPOPvvqR7_q-z_6Lf_LPLi-vkbWj7KHbcWTptMxl1HGzqWOd97v9fl6t-6Pjk9td-rf_4v_0277t1T_3P_lfg6TubH31ZBuEXtW1CkE4rs5Px80ewsy0tSsAAcLpALgOFLJaKSUvikiBB21oy88ccjvNwWmuWiIA3Jk5XMu8T7lzMwszU2IAaxudaODplrFBcHUzMxahFqwQVndOGVQRgISROZCEU6hpmcACRUgEIlwrijQRKTMTIzXPlxkKBVLKvZbCKTd9fTu5tVl8hGOjVQB6RBZpPR0gbHcfzh1ENCASpY44Y3Co8tnHvqNUE0E3B8Qk0gKzHCDMKeWplG4YItysivTMqHWOYEkUB1IeA6MGMCETUepToszcdWne7_7MH__DS-7-q1_9lcBhs90BQJhxFoM4OloI0Xd85o2f-Z2vvPLiC3_2v_nHo-8h-MVXPjL0tLm9GKeScqJhMQzD6f0HT7712MB0P7cjlBUDAQybynjv0YuXz58uh6MwDaDGSa0aXRLHAADXaEXsJGzuSMQpualb20U065MABCX5sF7phBQBSNiuUygQ7gDY9R1IU8_CydHwuU-9-Su__ruAuFyv9vudubNIrbWqkWBibjZRh-j7PsyDIxC16GK52u_3h-UvADGggc2VWdSdCNWVOJBBZ5ckbSF8fLx0szPhk_Xw5qMHF8-vkW0_ahAPXYcRXTdcPn9-fufsxXt3yG3SshwWqgaEhqEWQJRELBoOHR-l41ubI1q9DE1NSDa7MQIjoiU11DQsAKJqocTESIicuNS6XPbLxZKZd_viGDebrSSOoCR8NCxup7EalDIvl3K6Gu6ulqtOpuqbqsXCAsaqTK0UrpzIHY9WCzMbp7njhAmTiJkFIhNUBQAYZ2Wips4CgmaU40NK6ADMTpLnWiDA25WVOXEf0CqoLRWOzXzXaDtE5B4iGIjmHh7MpGYAIFmIKBwS4XrVdwCLZdcMtQFgZsUs3IGRkVpzFfBD0n87Lh5qwBAA3BC-rbEAUOPA8YT2yCdsuJ6m7QAgbSVhb_8EDwuABriCCBYSokXuGFvGKezQykXEIGy5GmiwHXXvpZ9NVTUQCNKkBnA4xyNhbZEYd3VXbXbjAAA7OMu8eGMbYQ1DZnczd2oPwSAiEOCi5uoi0nSmLaOFRAc7IiISFNdEhETI2MCFwmRuSKRt2t-khxYIbO5CDId9QAgfjAIBaFWZGvLssMejwNa5aG4EYmQiBlL0JkojYuZYnvYrlu2kxSEzEaGQAKGGiY_L4SgwHl88fnB-T0SagwIDiAUBALI7_KX_-P_SpZP1ybLrUykqHS8WiztnJ996_N6il8WQwwKyPH1-9fidS6tlu1XoFi998v5xN1xe3dxe356cDh975dEyYyex6tLp2Wq3GcdpvzpZjWrjVPe1AmVXfOHR2dfffrzdTQa-m-a-z33uIayW8fx0fXZy_Pitp0frxfn5WhXGuazvn37ja2_bODLTdrIXH96rc2HTo5MVAb3_7IoShZnX0qfeAgysbEsSRgLuU5lmDd1t91brdjMOi0USubq8XC4XdZqWy-XFs-c5y9nJUWglolrqXCpinJ0eP7u6JJYy137oUs7Pn96klHKWxMhJWlRrNeQuSWKq89QPnZu26_HR8Xq7m7pM0zgvhpyEwCxn3ux3q6PBTMOhX6axzO415a7rcqgi4mrdaXXJZBFVbXXczRaXl9d375x2SbpFT4FnywUxjNtx3NXj42Wgl6IW9uzi6t7pnbluFhkg6Mn7H6wenG03u-V6dfn0GRE8e3L58KMflczSZTcvs7p5EkGLxXG_H_fTOKtGn3JmnPfjV7_8_iaPn3_99RfuPvyddx-fnZwMi34z3dZaj1drLVVrPT49_dI33rl4_Pwjn_j443ffefjoRXO00IBo8ya3MAtMVFokqOFoHANo1plZzLxRw1HAAcw1J1kNeSm0XucjEC2wPEpdl8qst7ebaPWaAFVNJC2XuNvu-r7rc0ICCuhEmJiZa3tZmFdrVSgPJEZkICbMmYKxVA0PEUYKNyUACz1Z5uOjvhM-OV1lRp0t3Lqc1MJUt-N0cbOZitYakWW3q7U4EN5sJvRA4apWS23yUw1zwGoVENH97Hz5oz_0bVRqRJyuB4xYLrppLFf7cSpVJGVhVZ_GohYtnlb2dV9sM85Trdyl5883Rd3BAbDWOo2FECUxOGmtpdh2O36ICnRVAwRVT0nmqZjVxXp1vFrNcxn3UxCmLP3Q76apy3K06F58ePbGC3cJYzf6fj9vSukX3Vhtv51S5nnSUPf2Y3VHCCbq-g7db_ZzLTVnJqJStOpsavNuckCrxkymdrARq4kg50SEpVYh7Pv84sOjT778IAHOau9tbjdz3Y9eNcxss9t5wH4uIgKAat6AiS3tXdWrVhZSjeOj5c31bTVF5Gku7qEO1UDDVC3MU6LWxwyPaT8LSb_oTRXlwK9EEiKYdiOEMTOwhBuAI5N75QhHN9XXP_bxF9986af_9k-7uwnMe9_ezjnhfHkZqWPg8PCopU5omnJaHfX_1r_xZ378J77nL_-f__Of-umfMZM5UHKe9opu4dqGQogiXT-OezeNYm5KDBjuEYQtIYzA1ADiYcGM7mBVc9e5tqRZc-BwWykwRrSsbQQwhRMzhitAgIFg6-AGIYAbJoZWecUABFejcPoQTxlIyAnCoZ0qgZCYc3ZzgkAMLQUpL1arIKzqDM4pRy3ISVVTt2j7BFNvqXUUClUBYEKtztLi-2xzWQwrd0tEbtYkuyTS5vihB3WAqlULQBDBLjOvP_rtKNLlrhnv-2EZEToXNyNkTqlpYlnY5tKYIohUi-a-O4AKkTS8HxaoikymmvrUTpPI-D_6039Ut9Mv_e5XRsNxu3OtQtlch8XgZXr_nav_9p_9sf_Tf_b3rp-8-1P_9J-_9Y2vvv_kvbfef3s_24_-yE-cnJx98PiDbkFMfSd0-fyqX_X7zU64WRPDVBlhv7ldHd0FoP14JamzqoisWoWIGAjQrbpHl1K7W3PKDVhjWiVxRykQzSoGJk61zAggIh_mL11Y1Kqk1HVdeLQ7kgcgRxnLJz76slD8zle-VU3v3b1nU93PY_OhtA8HgJvCYZpql7tZq6TU7M0O0C6LkrKVAgEpda1_u-iXjk74oWKjiZmYmFBVh0V_erpe90MSeO3-netxUnBCYrM-90hmHl_7xjuvPLp7__T4-eX1zbwVYTM3j9JycokFqJhV1S0WQbSW7_FQP2gHm02CWoyihlcjaW3yxBAAsV4vc5eP18skOE0VAFUt50xAHB4BU5mPj4-OFsPdOyfrfui7DpE1YKM-mqu6ms-lOISIpC4Nw-AG86xIHGZMhA6S0mEm3ERaRMXVI7b7Kh23dBsQ1lK7xNgaAtAuDGThCC0dDojRxLpVHTHbgVIJzMTMbu7hiGzmksQPtikERBSC8MQyZDrpu16YCESkiXEb0AAJESm8RVuQmPAQ_oE293eLiGitWPdwDweY56reztYQeKjrNOImtfUkNMm0I6LjIQ_8oUEMKQIRE0s_dGCekrREkLo3qmWXMyDVWswDgdTCANQiItzAPNSsIUQBgBNScES4wxwaDuCoRQ8G3IAIYIzMqYIxizZ4dVMsKqgZIR7CY4QO4QimxnywbXkYI7u7gS1y12YY1tQkABoBBATk4RbuGoxMbQB5iFZhQNu_ReuVhwcxqXnjcrafZvuBw0HkG4Ro0SChbY3nrtj16d46TVMIEWQEAEGCwEAHhI77LB1gPLt6_uDOXWq93whuM4IIlvT48dVf-X_-vfXJeb_MpdbFai3CfZfPzo-fXtx85OVH874kBFn0v_iLX8ldVFUj5mX_8iuP9rdznerqvIeIj73y0Gw8XS36XlZZbm-2pdShy2U_vf3e1cNXHrzzrWdnpyuMePL0ZrebDbFPqR_YppIAzk5WLzw4_cZX30fExaKvaLtNBaQPvvosdnXaVuL-_NF6kNSxrJcDSKTAi5uRE1ig1spIoVCm2YERLRF7tTKNzz54DwO11rvnxwbadwN6lZTmaX7ptYfJwLSkJHePjiczyUnDh2F9u92crY6r1dzludRWZ9SqXZfRY6qWJLmqSHKPYjWlFObDsAg3ABineXnSj5vJa-m7jsy7xEmksZyPFsvtOGcmYXK3nHDRd1mSlurmGPD84hqJF10_1nq7r4B252ipNQQxE2y3Ewh1fWak3W5crI9ut7cYMJVpMQwYeHxyenVxtd-PZ6f3pv3eAaf9WMfZir7w5uu7sVA3IPLu-poE7w13d2WXumQm3WKxv9wy08OHpzk0ij55fxt9_qv_n3_ixL_y61986cXzvu-ZcLvZLPoeGDCl1fH6d7_-DXY4OjldrJeSJAIRoVTDg_jv90FXIUhuULxCREq5_W57eDiAR51Niy6Hvkvp9HTRIapG33WSMAm5GQKq2yF4DgQBCVEh9re7hhpo5AURpkR2gFW2yaipKkKklJg5wBGAhRFwnkuDrTOza0FABjg_WQ9d5x45ExPWUpOkWpQQpmLjriCxBu5L4UXe7uYDq9HBPFxjP9ZaLQjUDQKmeSamIfHxyfJssXzl0b1MdLwaukRlLiREJPuxONjJ-ogQwqPMFgEp8W4q6j6bX15tOYkGlupjLaaGDe7raBE1FCKqwlwqMZVprlUbleLQCUOYp7nr0r2Hd73q9nLTLQYGIMIgmufx7r2Tj73y4iCcksxz3ZcyzyVlMcBa6m67twgnRKFpmsdpBqIG2hemudSb7bbNj109Iqb9GO7MXdGyHDqoquFagwLAnRitvZUjcur6gV44X3zs4QMyfPvZ9TuX19ejbveqquGRUuNwpACcS1V1rdpYlepetUJAytx3ed0PV1fXATBXVbPqDgC9yDy3yxiYWT8M0EZthixsWnLXTbVA07aHTfMc7ikJsXQpqQYxEjobmKlN9XPf-V2o5Xd__Xcd7OTeet4XQjSKOplx10tHSEBIYRSADn3X_d_-w__l_-vv_8zf-Zt_7-rydjtXINRSVRuewpm46zvVCgH9-shA6zh5rQcDqoerMwMTtpwwHITZzsRAh0W9uwGCtL-rGTG3ZC1CUECzPpt5W0GDOzbPBUCYE5MXR0Ih8arAFGZyQB1is_pACwCZYqNTgKN04O5aPZwloRvUOk77vFpwymEhjAjQxGmNq8giaIbCXg0AwdRNCVEadAWY0IHoQyGbEzGgE3OY52HhpkhExKlLEWAOKUsrlPPy1c9w13mtTJS6br-blquVlpKSmAVSUw4zAYaZ9KnOZbk-KdPUDb3WCkSUxK1dxExEPKLrsoctl4tZ65_80e9NCj_9xd--udJZNULZQSQR1nGsxenHvvDdP_OPfoG01LEaKCgNXS7T_Du_8RsI9t_58__GP_w7P310cvzyyy9eP9_sdWyQUMSAMGJKkjnJzfXTR698ZLu5NnBGQYKW1mpLnRawRkLXChEHuUP7iUYkSt6qEkQZ2bH9WoSkFOFqwMJVTVhajgjBUu72446Ja_XPffun3n_v6dVua7X0eTEsu5vbjXukLPNUU0rM1He9AzZrMznWou7W5QHCmYmBXT0Akghw1FJy7uZpGlJyd2YBZkAIteYVFuYsIhC9yKPTo5Tw7unJ0-fXLT5t1Vfr9Y9_z-dKxM3V5Uv377547_68HWUgBJrd5rkS4ThViFCtbvHkZtcR9zml3Ad4C_Ysu6GUGSCwzV7DiSjMz89PRaRLaTkMiWAxDBDBgE1Dj4gRGBYBMM5lnCtnnlXbJqVClLDRYKsu1EyuLW5DiWU1dBBQ1MZ9KXpYdqtqNYXw25t96lPuZLcvgFK09lkIgtytmCSSlNwMHIiQhD2c4ODebX5are1gjJKylspCh0B5eO4GC4vwpvbA8JxTC9sgHI74Itgxnq0Xq2WHCMJ8yKU4NLnXof-L2L627dtIRO1cHwd2R5iHBXiEa3gAUrQ0PyECkrshEwHSgRkK1az9N93D4-DGakQjaHo54aZLi9CIlugQRMwihFSqznNVB_Ow9s-DzQ2KWa2mEQGQstTiwlwcxlKaWtTNkSkC2wzeAyKUgDzQXN0cIpjZD8N9aKuDlLlRnSAiHyrVEC0MhIBE4SEiFO3RCAHQrhHtAN66iEICGI0FxHSgOhBiYGROdrAXQTQxZwP2EzbWqkE7T0ZLDgUAAyRh8EDE1GUCr1PknICdAwBBCIkYCfSQsk0EeLW5vHd-lwDoUEdoehBHyn_97__DX_6NL57duZ-X3TB0Zdbjo-XR0fFYRx3rvburejtWi52P737rWU6plOooR6v-uBMz3G5u-qUgxIOzJaienfV3T9fhvtvtJHEpdSy6Pl6b0fOLzdnZ2ZPnl-Ygndy_d5RTunh6fb7s16v-ZL0sJTzo5GwoxSzCTK8uN1OZOGyzsVc-eQ5Bw9AtF3lfKkh88b1nd9YLNS_Vue18HKtbqSo5W7V52j_-4Ft5WBPT7XYvi8XNdnz89NnZvTs6joxcyogsk1qEcgAmmeaCEFD0eLGYpnneT4DCSAkoszBCytJJQqT9OOaun1WPFsvr2-3p0TogdtvdsOjHWVNwLQbhk9puHFd9h4zh3ji7p-sFEuzHMSDu3zvf3O4RHAD6vm-gWwTMOTuGW7zy8otvvff-9vp2uVx3vexub1fHy7FMmVODmZQyHh-f3NzeINLl9fXDB_dJ7fj09Ktf_VoAMRGaLu6d7J_fuOmds059cPFwk4z7-baqro-XNcBmD4w-8XR5tdvOd07uQy-3N2N3Z1mvb37nt377eL34ype-Sv3w8isPGHkey1yqdL2qvvXWex88e_bqyy_1wxIkz6bYrD0Q6u3rr81R3uDlY9WUBMKFJByQyRqFy7wbBEPvrI4XHQuzKi4GHJIQQhlL36fW-3OviyH1HeVFnqe6XvXEpLWmJDlxwwpjYNdJLyxCpToL9kNPjIDtKe8A2HWCgO1f6ZJ0veRE69WiT6lVNdrzKYg9UNUn1d1U3QMxAULbU82T7vdlmmsDLZhGu9IDo6q1Y_R6tRCC11994f7R8cnRatnl1ZAJYZpmdxrH0i9zFlnmDACluoVV9aKwmetmLJv9OM4aRDnJXKK4mVsnyczVTMOm3RSBs9Zu6MbdHgPcgRlzzpgYEcZpIqKjo1WXU500MZ-cns7jyIwe9Xx98v3f9Znt7a2Ze0Ax285Fzcs0ueH2ducegbBY9OOkt5udOwAgESVK81R244iEImmeCgtXs7lWFg6M5nEf91OpnrNkDgJwRqNGgaYs0i3SF777Myvu3OPr7z-9Mb24nasZAlnRTsQca5halLnM85yEtLm33IpWCjDweydnq2X3_tNnZhAABDjPauYIPKuqNyCEpZwDrFZDhDDHCHNUt2m3z5zbmCvn3B6VasaJwyuplTIvF4vv-YPff_H0vQ_eeQzg_WpVJnvz8599-6vf9IDFerk4Ptpubp04mMGdEQPsP_4P_-Kf-_P_3rP3n6nPu6logEAQNgo2ILg7LRfDuN2HqaTOmebtXigQwgOIgBlxrtCcuIgeAe4UYKbADAGcks2lqZ0ByMMCpa2Q3QMjUk7uGlWJwlRBCDwAsA3UDieEAEziYQgIZtKsacKHuCo1ADqihfSDe5hFXq3AHMK9quQcoISoajllANR5DsSDABwAHJKkxt0ws36x1DI3kWtDjQinouoQxCnAuA3FRNq4NNyRWVWZBQEoJxY2tTwMocbnn_ruMpaGWmxKDyZBCgtXNYiIcErJtSIiuJsjIbpbThk5mXnfLcxqAKaUAzwAcy8MkFPOOX3vZz-ZJJ0tV7_ztXe82rSfRO2FV07HubiWfLz6jk9_9B_9g38-pG6ay7Dsq4GHLVK_Xiyef_D-L_3sL_yl__3_6r_62z-jNjMjC-13OzeXlFyVmR3Q3ATh8snjl179xPXFcwQ0nTOLmyIgJYEIm0fMiZBasjA8Uu4BwGoxC0rSYDpMbODuwcLCjEjmnjoBDwDwsCQZw9RNRAhprOW_9ZM_-M9_9tdLnc1tv9nevXu_lDLV0nxB4U4kQMjEVgoQIROgQ2twBjJzLcU9PCx3XZhzEnQHAPVA5-pz5kyIOhVEaKzJPvG42z9-crlaDMeLhTC_fH5n10D0BBrx9rOnH310V6ur6elyuH_n9MnTG4OKzISJBFlIGFdDH4GrofcIQEjCQtIgmdXMzVQtcdcgQMvFcHy8cgoS8VB388CGpHbwTHkqU7Wo1YMDhYdFR8wJCANrtUAYJx3HUsx1dqSYqweyu1m1rktWdJ79yc0tCQVRMLVa3PFqGI66oe_DzWswcVEjAsQwBULIXfZmyQ1Ax_ZzDAOI-H29EzIBsQYQcxNbAaJwwgBikgOnHkSIgVIWDCeELG2l4DlxJn7hxeN1lzMfVFDgoLUVOuAwCKemkGoHUWqx9YgPoUDNA1EVAFwdACxaiBQb88MPRVQgpMTJISJC3dU0oj2koK0RAgA9kFAYe6EANLOqWmuD9nhzkKm5QziieVT1sLDwaHDQQDU3iLkoNYCAw1R0dgVEJq5q3gD8CK3W11D4QNiopRDREocMYofbAGAQArpaYiYh8NZQosCoaoTo7gTtP-CA7fMJU_cAUwNon1tggEJw-1MBEKDxmgKRDjVIOFQCMET4Q20aHFyoBMLcPnQzT8wAQMQBLghCeNRlQpin2g3EQashN8RQNV1IZhFhuN5cP7hzr123CLBdXRCYc_4L_-6_X43P7p-pWWJZLRdEOKyW6uXR3btV67LPV5v9F7_6HhMZWwAu-vTRF-8Ap6kqCQHM58fr-6erUm9ffXi3zzz59PWvv5c7OVr1Q06r9fLrb32w39f1cvXB7San7rWXju8M3btvX9w9P0lMZg4elzcjgDvDOPq4rdv9fH29dXfMXIq9-MaZWwoLM6xg-1GfPLnebPeB7Kr77dzmaQF4c7NJguZm4xxBBLHbbAKwzvPtxdW42X_w9rv7zSa0Pn7nA4N0dfW8znOXhyh2cXmz3ex24wQsq6P1uJ8FyQJLKUkEkG42t9KAlTlHotGszJUAdtO4IKkAd06W6piTbLcTtMxYgGHkXtJiAIhxNxLL_Xt3AswdyrxfLfrtdhr6vusECKdSui6VeXbz_mi4fH4xLJbvPX728ksvXV_dPrhzHFFPjpfjdoSAvltYrQBgiHWqm5ubCB0W63ncf_TNj37xd7_65sde2dxs-tXyyTvvT2V675vvvvHZ75zHqWgwxrydkIATU_BcFSFMQxA2zzZ7cFgfsRDC9ubJM618-fj6h_7Yf--Xf-Hnv_L27affeB2skCRAXA2r1XL9ra-_BSgvvPgSEKEHMVq4uqmbAHptopTwQGJKmVs60Q9fAWy707ZAPLu7fuHeqgPMmfLA7X0dBiwUZom5y5IzPVj3GK0E70xhbgDYi3Qigi2qoM0_OBWVLuUs7Y-cx5mah_bDehIhJYZAn6dZmFeLftHlwOiyhMc4zshiFuM0j0WLR3VQtyBkkpvbvTqqmVaVlEu1QFR1AAwA0yABdBemj710_yMv3Fv0ScJb16DOdT8WYprGKsyr9SITmUcpSsLVYzPNRX27HzUCs2z3cxDe3O7UwgCBYT-XUt0pwMHMkVDNp7GYGyL1XQeIRKw655xTkuOTY6bkHlmEEs7jBBRHR8vPffKNMk3Pr25y36nZ7e3eATabTSlqEbWW6lEsaqm7_bQvtUH-hcW01DrXqsIylypZ3HyaCzOHeSmaUi6lWHjzsQBgTh2SVNUgyG0I2Ml3vfHSAiUQ3t3cXE--H9Us5v1Y1IpZNavuu_04lwpAYynU8iFCZZ7DfHV0dHq02uymq-tbILDqDKClFvUK3hCf1MTIAEgA4SKdu6ZE5jbNRZjDFABrNSJkIEIBijAlwDrNL7_84qe_4zO_8fO_cHt1YVbnosenJ-by-J13y37moecuEVDqe0IY-o4dpnH83_w7__Y_-Ec_-7Xf_XIkC8JqhSBAAyO8DQfVkJmFvMzzOM6zru_eu_7gccpCBNDI2x4sZB6ccwv84wHLHRGOLO6GAMLsTbbDQMiUuJYZAljYzYgFwgjC1ajrGnGRmJ3aDZcBQ1VJUkN_MLO2aRZzQJgZcyIkJPJoLHJSs6YLIs6u2qg8SWja71LuJaWqFkyqyhiE6K6N_mGqzEhwgH4ikQNyN0RYEEIAYRBn8-Ak_bDQUog4dd3hLUaibtL1LAzqiZmPP_YdWhwJGvyrTRo4pTIXyQxuxBxExOSqQY2Hgd3Qj-OUuh5aOMGdGTEROPwrlh_E3Yd3w-3Vhw9fvHf-Uz_7q44YHFHs9Hh5fbUBjPOT80eP7v7KL_6mdO0vjVbNjaqG5A5IhOgXfu23_sL_7H_xa7_8a1VdTa1q13fMxGFWiyM1SywL77fXJ3fu73c3mRJTW7EpcWIKIGkTQVVrA9M4aCG8BW8ivFYNCBGpUyEStyqSVI0IACgP3bSfhBEZESN3HSbMSN_37Z_--d_8beD2W0F9nxaLxe122yRwB3Ab4HLo2u4ipRTgXU6qCoQ5cwQwYdHq7iyiagRo4dIltwqK7IStviPUEGwOrtVXi8U4l-OjxSrnwFj2_di4sxYKvFiu1MuTx9d9TutF_8rdO9tSRNgCi9o4l2kuqiaJw0LN9lMBRyHsFp1gzFVbKmax6nNiJlovuiaMNaspZwxgBkRoW8K5lHYsS11LxxAT5SwCvJnKZF6qzqpqMc71fLV8frv3OJBgck77XdnN01hKn7OkTIRzta7vXdW1ZqZ117OIE0yqpdbwIOJ2ggSAlHIghkWj1joEYDhifDimR0IzAARicA8SRgBmqbW0PDlGG_aTCOYuDTkRIYAHeMqSOulzPl0tFpJzYjc_xHUDAOhfTaAJ_EDMBEIMwBa7QjhIyMMdkLwd670dUMG8pQXhw4CPC0uYIbKaV2tlOyeiiEBm1dquNcTYLGaH-H6Et7M1tLowe_jYIHSIFtEMzQZuGuqh6u4hid0NCR1hrgoQFOLuwAgtFwNBgNUUKZDIzR2iqrXWlHswUYQ5mLAgAjFwW6e2VwageoRHnzoPFzpAVc3NHd1B9VBp8ghAMtW2kCtRMDgADdDcRTgIVBUB0DGiNb25QZ7b7AowMACZmo0OuS3qD-sSD5PESNh3KXWpwyDCVeZFTgGIDkFQal12uUH_b7Y35yd3mpejwVvRQtLw9Nnlf_7X_966X67PjruuD6hd3y8Ww2x1ICKg4_Vg7l_92rvjZpdQ2g_04d2TIWfOPQqP-4uU4PT06M5RF1VfffF83E831-PN1e3rH3mQmYHzNNrf_bnf-uwbb0y77WknLxznBeYvff3SLN74yLks0272m13Z7yckqtVDfT_W58-v16tunFzdu9Wywy5q7RfDbrNPi355Z9EnQVPwGHfTvN-o-lRVJz85XXot8zQmggzYLTJE7DZ7dLh48kzH0TWWPUGZ9tvdxeNnJ3fvlu12t5-6xfKDJ096Tm42a6keOhUgvtjc3NzuzWspNae03ezNg1nKqBGxvd0OmRIKQrzz_HoYunFfDPz8aEUsJ4sOM11tNrX6tJ-SoFWb5-Ku62FY9B0HdosOAWrVxGxVU5JxnHLuWDrw6JIAwtXtzdXl1RuvvDBNe0v4wbvPHtw5Xaz7J88vj4-Orq9vT87Pp-1-u92l3FmN5WIJELvd-OTJpaR-vL3tOtlcPgevZw_uAAAjDL3cu3vy9rvP-yFzl_q-3-42lBgpI8F-rGbBxOV2e3rn2MaxZ_vGV37nf_jf_YlvfOnLV-N4_-G9qt6n4fZ2e-_OyVtvv1fq_PKrryGSW3ute7tlg0OEBUJ1b4mFTNL0doTQ8hIBqKYimYTvLbu7R0sJFyFAFCRJDNFoItTlNNYizIjIIuh-tuoWSY5Xi3XXIWArjNZaLYxFEpJHZBYiHCd185b8IWZkMtMwT0KOQcSJqO-zELete0oS7lfbsZQyz1Ut5uoOOJVa1XeTbfbzdpzc0VSD0QPmeVYzIKjVAsBqlcSrnr7tzVdfe3gH3BddWi96RIfwqZQmLQOA1WoZFlojTANDLWbzSb24b7aTqlUNDy-1qsY4z2a-3c7q2qqrmZK6z1NNWcqkRCGSiUiEb643kpNELFfHKUl4mFrf591uF6YvvXTvkx95jRCfPbti4S7ncTfWqgB-dbVRs-Nhdb3bI4SHO8RmN7XnfRZWVVWFACFRrWo-DIt5nrwZc0giQlJSszLX1AlhJGEWNlQErHPtU845nZ0P3_X6yym4mn7j8eX1qNux7Df7QAzEYof6uEbMWgNQ1ZKIeUxzCXfEkCQP755c3-z2N5uh7-aqCDirV4vSjLPIpibEKWUkisB2Gylz9SC3IAhTJULmVgVOgVHHkSOszJ_9_Lc_eOXRv_zF3yj7EcJ1JOH0hT_6I7_7a7-239wEEDF1y44CUJL5zCi7_e2f_VM__qM_8In_4N_9q2mBDhHI1vCpEATWgtlqwJnRETFCNVxTP1CY6cyIH66Ao4l-EclaVVatndrDA5nAPTwQCYm0DeMREMDdqV0gWtzHvQk1LZwOMdOGmWhHBMeIJAkgatUmL2rwIGKKAGZu40FXI6JARCDpOzX1sNQGzXMhIjA382E1AJJp7VI63LsckYmE3RU8RJJaQKAkdsAm7ghABOyGARBYRKsn4ZbiI0IkASDpB0SoitL1EbRcD3z8-udqc34RIyKzTEWHk-N5nBDJw1i63HVlP-WhZyA167qBmMIMwUSSQ7h5IKYsWTqrOgxdGOzG8kN_9Lv-xT_65R_53s-s-uGnfv6XjfJU3a1OtZhaf5Sp-t1HD3_zd75mHoERCFVLCynWUgGDh-5ms33zzY-99_itUCBAtZmA24i0Vm1EElODcNd5eXSMhqVMxEmtEAFEtBQ9p-RmAeDmIqKlkohrbY5WaKyPZl1JHB45d27RThWAhIgs2GpPbtb1w6zlM5_6xNl6-NI33iUWrQpqVubj8zuuXuqMQLXUFu1OQuBgbtzmW0JCLbjFwEgAoQ6E_WJABzPlJGGemuAGCcOTdBFRvYA7MTdoFIB98PTi1UcPCICErq5vn95s3SEALi4uSWC2ePL08mp7u1yvTrvuS-9-ME372YyIHLFUJUAMFIIGSYyIWkwjWFi1jnvthjTkNh_FJtcwCEYkhjAsZuZWqxORO6AwETk4SwIIUxvr7AFqAMxD6nfTWNw2-zK7VQ1HLLMJI5hvywwBRLmWWooDsdXiETWwGKSuXya53O7HuU6TmVuLlSAEAbQqKsCBLIeIJGKOIkKEZsYfSqlaOafFOZgQ3M9O1qY1AeUsQ-Kul088PJYuDTkJRE4p3Lssd1bL01W_7iU8AIEIq4a5H8S0hNBS5BHmAYF2GPxjs4FHhJl7m-YAGbQEy8ERrO7miogBkZIwchOWzbUgkVkLVTXTjvdDFqTmDmPmD3cLh6H8XBQQ_VDkbbygSCjFXMPNwqxFa5AI3Fu6Joip1qoaiAc_eeP9M_HBG0wf9r0AA4AIkRABCNHNEFmIGDALVz1URxp6LaCxjAIxHLzl_s1bSyg8WlLqsApwAKKDhE6IhZK1KX9TJvsB3eABhBSIEAYA5mCN23vQMkQcnvdBRILYfGpExEKLLp-u-_vrgREWLaHSQiZ4oJKuuo6AAOBmtzk_Pvlw44yAGF4pd3_j7_70r_zel--c3tmV7Wp5GhQnR-vcZw-7c36yTN1U5t1-fPu9x6ZzaC3Vz87PEOj-nbMKfr25osBpnF95eOd8NRx3cn5n6arPLm_PT1fnp-vb67FUfHYxndBqWKRlRySo6k8288T15Oj4g2c311c7Q9jOo4Vtd2METPup1tlNx6lKJ8NqOHthhehRzK16nW8vLt790jcvH789Xt0-ffzOu998-2zZ_egf_PZPffyTH33h5N233r1zTK8_OHvy5S_uy6bvgYWOjk4u3v0gD8vzl17e316Nt7fbq-uyncnH7e3lzdMLrfN-u5nm6fLyEhEli1DYrG46TdM0brN0z54-Pzo71TITeC_dXMvt5Q2CMWFxsLCHq4WqYy3muJZ0PY6Xm23KknIe99vMfHF1e_fuHUdIjOvlslSXrhtnPVovAbAUaxDMrutmrde3m6uLm6EbnCKKjdO47AdmfnjvvIzzbpxOTpaLo9V-syXieS79YrHf77a3mzxkK-aIELHfbRAtikuX5mme95sY59c--wfG_RhO6_Xq5O7x7bMtOXSdgOLmdhvgxB16mM3rk-HotO8Xy4sPNreXt8z8e9_46un5nS_-1tefjuPoeNz3WQiI7hyfXOk45HXuu8b6Ygz1MDX3EGYSJiRCastGIPgQWoBEUN3bSnmR8_07q6PETSgpiA0S3aBkwgweiz53iRnJNYiAMISZWNTN3XJiR1BTIlwuBlNPkjxi3M9q7giI1L5EHrEbZwgoRZkZBHOXu8RWrZF5iLmom8V2N233475ahdiP1YGqezWdyyHIXasG0FxmEZ5G84BSKxAiASJ89nMffeHkCD1WSfperFb6ENiw3Y-Lvss5MQJ41GrTNHvAVGoF3471ZrPfT9PtdjQzDPCAohYQpdQgZCL3MA1VdTN37Pu0ud13QxYRN92N4-pokXNiYrAQEWuzeAit8527J598_dUsvJ_1-c2mS2no0n43jvN0fbPbbucQ2pm6hzuYxTxbaSEhAIQQFo-osxJRQPS506rzPDMka1lSAFMtc6FEiG1ykWZVd6yqkoQAJcnQ8R949UEK3tXxm48vN9W30zzP1cKrR1GvxdQMiKtZ0aJmAKihHq5qBJEkD31_eXmz3-0ZASU5xDgV86YlPnAmuJV8Edw93MKMiFRruKoWkuRaw4JSLqV0XRpSv73ZfO47_0AN_dWf_60Am_cTANy7_-jVV-796q_-0vWzTSullH0pY42I4nXgxIBDP_yFP__f_0_-07_--PL5dpyBUC20FsAQQJEmpGfupNSSF70XBXMHc9V-WM7jjpjC3FWxUfcIiaU9v7WqELdqrnSdVWVEYg731szsuj7UmtCLMCKwqsZBfAPMEqYEgUEkdDhburk7Smpbh4DGimaMIELTmTm17xsGNEO3m-cha6k6V0Yipgij1lasWsNYErhH0xy1gCwRkyCCCANzABATARAJEfNhYogEiMicM3q4GTKxSAQFAjAHhAwDsKRhgYSExMdvfI6ShBoxJRYkVg9JCcGgpZqclkdnZdr3Xa9m41SIcX20evH1j_TLo7wcyr6s7p_2w7A-W6d7i-PjVRYk4NXR8vnTCy3TH_rB75PArz9-XDlXKz2n_bQD5tuby83N-ANf-KGf-a9_btEPnCimfXz4mqdEjNgfLTIPf_pP_8RP_e2f2u83atoN3bgf28dsbmaOAQjBAl3ONxeXj17-5O31M8Qw065L7sbMzWxl7qqGgCIEjRce7YGPLA2qHURsqtQIMM0cXCoxewvDzVPfL5iIBedav_PbP11N33rrg-1U57kIoTCzdIvVME4joQhTGACjmy-GoRFO3GKuyokigkRKKULYdXk_VYjoBDl3WjXlFO4iaTduhTggcs6GzkJVPQ3dctGVUY-OltfXmxfunjLT0TC8e3nDicOdgMaxfuEzn_zqB09r2OXV5s6Ds_Uw3F7vlmeraT87-KxVmAOAMwETE0FESuQATNxzWq0HQiYkUz8MftqN2TEROwSymLsiEJC7A4EAdpLb3GMzzhjU_LB97vZlHqeyH0sD7GiEWTCEhyMTBhWH82Gxry5CqhYec3HKHJwiYC7lxUfnzy5vkcE8eknW1izhkhJGAAWEJ47jZXf_dPXy6fpTj-5plOvNFom9eWOZPFyEs6TFkI4Wi_24v3N6lDvOwuv1cOf0uOvyQLLqexFYr1Zdl4YuPzhdrXJKRJyo1GrmCNGmYg4OTEikDbpLEBBtna1qAGARah4t83OIvKNHEHIEArXrFREReCTktkuxUCZWNUCMtlOASMwELIcZBrvHoY2khoRErHZAF5tHVSOCabYK5uBVm87eGv_uwNeMaOPtxneuVZnFzZiJm4PXo_lHD4VfigBiaOMRh0BkiPAwR8ZqKs1M3M7qGMAYFozYTMARYE7uYRF8AIAiRLR1Ewm2t3_rkxh4eGCEN4gyQmAIi4UjUyAYhH_YiXYAs0BsRBMEAmFBQvOIAxHVgfxk0d9Z9ETUp2aABwJE4lB3gKq66DoAYKHNbnN6chreOlWNRyqpW_7Ff_8_mY26ruM-9cMSKY5Ojghh3pc7904ECRG_9KVvTbsppc4dh-PF8mh1uuyPVoMJvvP-k_D6wqM758v13eVimXMJ396O2910fn46YA5kC_zqV99_8aXjRHEz2y7sye30_pMrYdmO2xC6ud3koSvm5jjX-fZ6894HH1xc3mzHeTuXccaLze6tr1xtnz1__MF7--srC33z44_--I9-_o_90I98-iOvf_7z33b__NG_9ef-9c9-_GOfefnRp954-bveePNP_pEf_KHv_a4_8cd__E__5E-uuqOf-GM__sPf993_8B_-k4evv7q9HD_zA194_MVfA4Ak2cvcrVYf_-R3Pr98X5L8yB_5sXe_-fb9Fx88fv_9t77xts8Via6eXoTBxfvP-q6vZbfbbL72rffKfnt9ffPs8uL58yvKIpw22ylSV6eCnCh1m92IGjdTLVXdfL1Ya9F-sdyPo2pcXG0vrreLISEGmQPgYhiIAVkWKe3mse9zEg6GaaxD7gNp1vn6dntyeooQ3TDUWtz92dOL1WIZAEg07vYsjMSbze3J2enFs-cnJ3c87MmTK0wsCZKk_fVt2c6vfs-nqTIn3mzK0fJ4WA7feP-dcZoly9HRMtyDcbvdd73sb-c3Xnt49fT66Gh18eR2v7lRpJ3zw4fn0-bq-eXVz_3y7z144f7bH1wvj1abOj19fPno4cNWuqvVgrD1o5rIIksKMyahRBAhzI6u1VuQzzEk8fnR6qW7RwI4DB0zgFpL60AgCRMiCzJJO8Opm9Y2vsB5NlPPklpjHrGBhbmdS2rEzc1WIYI4EbuHJFFt1l4Eh7YlAKQsaZ6tTDMQA1FR249VITzIAYJoPxYDKFOdi6sGArC0A42oeilFiEwLd2meJyY-7vPHX3i47IdeJKdob7QImObZrPH0wKsRUnUbx1k9LGC3L_tSbvfz9XZ0hGqmHtOskqUU16JAWKs3SNs8FxGcpwJI_dDVqos-h0XKmQCIuEWeWIjaMjE8XAXjU29-nBH387zdTrvdxERdouub7c1-vtnsA7A2Bwmgm4dBqVbUEEG1Dl1nZvNUmss51Ji41lYIcyYyrdLuJ2bCmDrR4jmnYiaM5tEiqCnxqy-effKFewx8eXXxreeXG8Ptdmyss1Jt3E-1FECcizInM9NaWKg2zLOZKcxVVyeLp8-vzWrf99Ut9d04l7buMG9CXBFhVdOxIEStlZk8YJ5mbweq9jT2tsGNRTdsNzcvvfjolVdOf-af_Hqf8PXXXrp4cvXg1Yd37x__ws_94rwrFmDqQBAeCo4Iq0XXJcJZ_9p_-u8-uR0vfffLv_LbkjglstKAm-DFMEJrCDEh11pERKtFOBCGWh6WFmpNYxLAiZtGnpD9X63pG-yQIYCIEaPZKQ_-T8TwIDiIOxERXFkITKHN8lt5F9HD2rFcmFQVkR2sNepNKwARsKQEAQDI0jWTQKgBizsgpdY7hTCMoDZnTLm20BFg7oda5kblCkLHw-UhGl-EwU3RQ1LScERkjMSsaohMwq6a-76Wikj9aqHVWbIBpJSIOXdd6jtJwievfy5Yyn7MiRFCrfmgoJPkTTguTExAjsL5ZOVVl0fH1Wy728_7HQqaap3rNE3PPrjYvXs9zbbbl3E_l3l-frEv-3J0d_3xhw_vP7j3S1_8VhCC2X67IaJSplLjD_3ED_7cP_3FJAjmaDMhhzt0gpyCU632-iffjBpf_s3f2O0mJVwen-o8u1Z1HY6O5_0Y2rjGYEVTzlfXz47vPBx314kl_GD4SZJakJgJTWs7aUnudS7IjZ8KnFJ86LAwb7sFBERikpTqXCVROCAhuAIhcPrhH_mO__ff-f-SEOcGw_Yyz2717O7dqDqXCZHrbAhOSUQo0HPfhfvR8SrnHAHjdrdartU_1Ed7GEV4JOZ5KsBYozBzOIAEC4WjIFVHJpyrmoYR1joj88lqxUT9cqgAteo8FeB4-_qiqJq5A1xdXb_-6gsnR6fA9ODOHfPIJGYK6Ig4z9pwBczchI5VvcsiXSqlLpddYFQzYlINYTZ3ECL6sG5LWE0F2TyqmaqN8xQAQbSbRkaZtc5WNWDIfbWKQGVWJCjzZAacskaEhycIdFcb1Q3CwAOxaFX1_X7ebseBeDtOQkJ44O4fRvuMifjoaPnRF-8vlv2QMwsp-flieOnhg8vb22qKEEIUYD3xYuhOl72W6d75yenp4tX7y_VisRqGxZAEIDOr6WroupyOjhbnd08erTsOdDURzlmWi06rY5g3U5WqA3jrxnrLJcHBLXuwCvgB6wHNRnWYBrUVQetgAAABAaJVi6YTbrRQJG0rRcIuZwgIDFUFQPBg5hYxcnd3-BCscdCKxYEuRO6g5gBoBubBwu0CFh4oiAF6sA00P683o3OpioSEWM0auSiRtNeHNdNZ01u0TSU1OWwEoCMAQIepWYoIyMIjyLU2IwcKGfjhdzsaxKD1ryg8mKV5CcLb7yQEYDVnJAtPzO6u4R7WIEx-KCQ4McWh-t3a69QAssSYE5-thhdOjhJgEna3CEgkAcjCyGzubtZ3mYI48c3t5vT45ACDAoQAxrS93f9Hf_m_HNYrJ8vdohu6Yb1a9MP25ub-wzsnx-vLy5tFN_zmr34xHIK9y4s79-_up-kTH3vA7le3VxdXt7PW7_j0K0ecHp0dAaqDP765IoBHd8-uLzbzVG53E2S6mndjJ1_81rPdxa7NlIjCatFxKtVvn12999a7ur05Hhaf_cRr3_npN__Yj3z-U2-89tnPv7kQ37_zwQ9_9qU_9Sd-4Cf-0Pf_2I9973d_9hMfffRofbS6c-_0l__Zb3_i46-dnx8Pix5BGuLx6fXlapUXfWYC6eCtt997-eFDq_ibX_oy5nUpukrzxftPpmlar89Mx0D-3I_9yG__6m951e_5_OeHrvvqV7_5Pd_9vbbdvPX2t1569fWb2-36-PjLv_u7PRJY_egnPvXxj7x2fn7OHTHH1999uuy6b25vyixf-fKX3_rg6TsXzzcET5-83-dhWCzAUbrlftof9Wud6_HxCQAkScF6sZ9urzZ7LRhYx_Fit79zfASEZSq1NNoGXV3eBHvf9wg-7fbDatkPvVeFgCF3RyfH7773_r0H5yJS57I-O3rywTNKqda6WCxurq-HoSPmt7_-_uJ4lRe57Pbjdn_z-Nni-IwQ5s1eJK1Plh999GIdJ2ZGoC4JhJsWhmoE0lEdfThJt5e7YriZynY_fud3fOKHP_eZX_uNL077-ntf_jI6Xm63iz7v9vPDe2fTbAGo4SzsiGBu7pK4JQ05sUcQUJkLEgeAJGpuo_N7q9fvrNbCWVI3MAS4elHNwobRpeThwkwUADjPBRDDwQIIuYVLi2qdCzIJ4sl61VQf5n55czurFo2p1LZNJEL1aEEdRm5nqlJtKlqrBkBVJ6FxruNUWYRZzHGqNmvUquNUD3a-QBKKAGSsRffT1HYWDghhOfHHP_bSw9Njce8zCmGXcymKDJKk73LXCSHklGat86zVTANUvaih0OXNvphVa0FHcwiNmKYZADEhILW_v6sLs2pIx4xMhO1O0lDuKUuZqpvnLiMhZ7ZaA_SNj33k3un65na32e41TEdfHXVmfjOWy-2-mLcXk4YjSXjMZS4W6u4YzCnndoMyYY4IYnYM95hLFRZV7fqhyeA8YuiTu_dDjwDTXLohebirCSMhf__3fvxOygRUa_nWs5sJ-OZ6jxZANE11GmdgQsBJq7XbHgUEqFqpioBNflxUd7sRkVInrqEA-7HMtXCjIzefTtuTRCVokXSvtSIGmLb_ie7u6AZnx8t5t0PK3_vdr_-zn_old61Qnzx-7pDe_J7P_Mo__xc6KnZs7YSBAcCGnDuKfWWmP_U_-PG_8Tf-8X_xt_7RXrdP3nlO3EB4Tu1FiyBB6soEQdFC-EhkZWbhKEXdUk61lHaLcw9isWIhxDmFOUlbHDd9PTfBBZIEEkK4ehxOROBqFg6HYRKDKSIJS7tgBBMSNtr1QViBwZJNtenDPjQDAIKHARBhK6pBBBJQ5K7HiKgzIXJOABBagRmZzSqTuNWuy-0emLuFzkopIYSbESduGwZmrZVSNveuW3gt0nUASJxMve-7Qw1ZEqcsmXNKgMAsXdeRiKlLu3p2i16tinSSkkYwYpnKarW-uHhOCV0LBpZSc2KmbLVOuz0ADIu0ub7uhq6WYtUWi2V3MmxvJiLqhjzP4_p0ddzz7_zuF__1z3_3q3dPVwPtdmW735h7maZwSRn32_H4ZF3HYmWG2ShRVWcBziwI497-wKc__hs__9thKlBzt9zeXC5Pzh6__U4ahvnqOucEYjrXbugMCXOC_W61Wt3ekEaIQ07dPI-TF06dOyAxJYFAYnLTbtFP477BLVWNUD4k3qBajUJp6AgRwVPmBr32cEK3gD7nu4vk5NNUx1IFjQCYea7z9eXF-ni9nXZWLGXihGOpi6ErxYB9sV66-WrZuwUuBo8KgFrrctHvxhGcIZSJPAwgIZAWzdLXyQhLzgmFuLHbjYr4ZqqJh3cvrjPLi3fvLHLOSJlkZxaI220lRklZERXw6289fvHs6Pbx88J2lJYP7y82-5N3ry52ZZ8ylWIAZGHEXKdCTB6oxZHQHMwwgkqxVv9Sr14iM1cLCqygWZIT1VrMQpBYRIu61T53DFTcvURKCd0EGFiGnmetBrjfzQrETFatQrg7E5lHJkLB2UK1ekYOKPvy8P7x9unjYRg8UBJXCwhHwZPlcO_0OBMBeLWYqEL1HIJMaON3fvI1APiXv_etaZ72u3J6t3v95XMfy93VCWdCpt0-1h0HJwrnPhOEdLnOJSfOkrDa1qEn7Bad1SIkBLjIKbArqrqfCRsBACtSuJsHITaKPhGZxYdcPwRAdeXGDW69N4KA4MZ6AoqANj7y5s-FoObi9WBJLZwTDqWaZBISD7dq0AriBOYBAS3kE4izWnvglVpI2BSI0AHjkL0Bj-AgR3ALJAIIb7_tEaaWmJClGQYYydDCjQGVULxhjwINALFJSj0CapBIg9YVr3EggEYAFtWeGTzcwatKIxVgmAa3fjOzq2OgoQWAuzKhWtD_nwFAkNUMgYSauSi4XRwAgMjM3KLvcvuw253WyJNwx3RnkaPWkGRmRMzEEdEqwoBASMLkZkRs5ggQB0UDNjYcJfib__gfB2LXLyBFYAhTJsFMtZTz0yOrtevkl3_j9zjF6b3V-8-uzx8O988W8bxAgmlX3_7W49x1hagQLns2mL_13mNhUteHJ8Pzdx6n5ar09tVvXVpRHNa3z691u12eHO12Nz5WSOlk6I_u3PmR73jzwemJhnmEagRiMAnRyfHa3b5S7At_5HP3791frlbqXnfVNFiEGS-fXz2J6fjO-vp2RkKGADR0zIkxQsAqGAbcf_E-JZUputOTmzld3O7Z5qJBhozEgtc3m65bfv8X_uDf__s_s-z7rh8--tor22nzxqe-Mw_D4yfv3Dl9YX3anR4d73fb9fEycb9Y9OSQurQY-sz5eHm0uN5--2sP_sHXv_x7X_7S0f2zL_3Kb3XrYfvJ8Z13Hx8fHS3Xx4h14xff9_p3fvPdpx_76Gvqttv5wLibJjaxGlfb8uBk8fbb7y1W3bpfPL24kSwqdHb_bD_O29vdan20G-e33n8vpXy2Wtxc3zICu75w__642e725ezk6OLmZrVcXVxderVF39eqXZdWy-Hlj9zf3O5Xd09P7j68vb7c3dxcPP6gWy-P1-vFqht3o6X08NHDi5tLnc0czu-c3dzu3RUqAomC7T26F063bxWpltF_5md_6Y2Pv_GFP_j9f-2__Fv90H3z7a9j5D_y3_iR99-7fO-Dp0dHp6GhYY5kpgLExGWuzCTC5la1JuIuy77MzKwa_TJBpFOlRZKuk8QYAW7WiLoQ0DwcmcUgyqzzh5Pp3GUyA0dHR4gusSzy0HeuYQ5MYq4BoEDc59vLXQWYq66WQ7Wo6jVsKkaOEKgQ41yHIam6IRHH7aZM8wyBtRQDB-G5VMk8zXObebS4oKohBmXhzOXGOC_qNKbEOTNnfOH-nV4kSRBEnWdh6jppzNCwFsIkrbabLSzMQtUtoFSttaUj2-SF1QoT73cjIasrlQ_xYy0ZjICEfZ-FKIDDDCKSSO66eS6qMxG7OyJpndFttV4_vHNvKvPz55fHy94Blmu53exzHooiIRN6rWZqwIexCgAjBKH3_WBzDXPTIORW9muEftUCELUoC8bvbzWRkKkW7YKL1wiqatWcAc3ADearWzo6RoLcdU60v9kDmgdBOBI6Yri3Hpog2lyRMBLV2hT1GA5F6_OLGwbExOFk1majJgjhgQFZWKsyY2OCYE7uXrQAI2MUM0KvZUaQ5dHy_MHJ7vnN84vdT_xrP_SNd59s1BzAZqPw9f2jn__pf7a73HMvqAQsaDUQDkHOCC36_P2rko6_8Y13ebp5_OXdYki1Fg9gQiByM4Ao3jbMUOeZuAs087Hre9PKgqE1rVaz7EENkDAQgSRLrS6JzIKJHF2ErRZwDyZAVK2Uc6N4I3h7NaB0Nm4QCAKIMJi1GrEBCndgJVCQhLWUA04Q0MmBGYmJOarRgUmOqe_UounGOOcIcKA6jf1yBR4easWG49PtPIJqykNqhdsAZ5Gc6gwElIYOCVyboCyISHLWqtL3jXSuqihdEIdHHhbuahCp76q6R3SLwV0JRaN2yxVhrJe9LXo-e_M7gsS0RilqRjlFVfAoqu3s5MWAQEgA3GpAWBnHLos7iDCCOAIB7J7vZcjg0p2cEIVWo9TlnGzc_5mf_MMP752525e_-cHTm8tpsx9LCYjEIomOV8df_8rXyuxmhSii1UGKce5KnXc344_9iR_4-3_3Z22-lSR1nNFhOFmtT06vnz5OSITcL4eccvz_ePrTWN2y9L4Pe4a11t77nc5055p7qO6unpvdZLObbJESRUoULcmSHTkSjShBBEeQkcEJAiFIEASy4HywbDiOkcSRkgiWFMMDIlumIHOS2BTZInsge67q6qq-Vbfqzmd6p73XWs-QD-uUbqG-3cKte8579l7ref7_388diDiySTl__PC5lz7w9NFDDkG1tvCiszOxiJiLiHDsimiMnWlTjmBInUjRUrBFlh2YCVXAMYbgZoRQao0xpo4R6cOvfNRtunv38X5fXSaoVlUxBOaQy3h8cj0QFZGGR0wxDClxhEZTDoHMPQwpTyXESEB5zEgcQsjjyEwp9t6KrIBEbKghhcQdIjtbiMnBWmqrXw3b9V7K9M6D89s3r0Xu7j98XDQ7kBNmNVMw8FpNVPI-37p967nrJz_80f3vb9ei2qV0Y7U6CsNFKajKBKYeUqiqiZmZAzdEjAG5ijWiUamCGBo4TMzMAJnMm1JKTFvzklSt75IUrVWIYgWrVUwhm4gp9zGPxdUpsJo1fo6YGpKoAJKJYUBwCDFINalFRJ9e7j77iVfuP3qQmBrSph-6D75453A-7wLlIkVtKtXEXTUgFing6K4W8blnrr300o0Yw4t3jhMSAfSJq6uKVbWi2gUGhxi577sQsOtDDBTMxRTUYuKUQgwxJGZEFStIQNylIOpIWFWt2nsVPjR_Lzny3lQe3Zu3QBXsPdi3wdX5HoHMTLXxP8EbhQHQVZEpEDWybztni2prZXBAUzMAdc-ihGwGVRtnqE39r6rG2CCk5sQUgKtUQmBiVVUDda8iKXJzJ5pZi8K7m4rGEEstPUdTQyIXICZAQ0VxQ0ZTAwcTb5QDR8SrCKwCIiAqOPFVLwII0Jvry1pPsX2eAZyQmBnRm1E4MFkLVzKaWHN5MbP41d-r1qsFsb9HT2ds1Gwjpob4RILDg_6k71Z9asDP1uJA8FbBb2BwNauqhBA5GvrlxcXR4eHV-B-8vY__6t_4913i8sbq8mK9OlgeHRzFEMdpd-Pk5Oj4QHO-3I3vvH1fyatNh8cHy9Vy1tPJcnnn1tH9s4v7714sj2aho-duHDxzvCg1Pzq9iAEOlz138fHF7slFPnuwf_z0cn6wmMZy9vRst9UZhxXBL_z05_-1X_jpV15-6SMv3op9Zwa1qik6MiI5kTu4yr2Hj1-__-DHP_2x-WxGQOSYiNkJ3EnpB-88PDlevnDn5PziIsW-I44IgfnB0yeH8341zHKZGPFyu5vPO1G7--j0_sXWCYLX3eUFtmGXS3X6I3_y5-69_U6f7NOf_NQ4ZYpc3A6Olig-Wyy--4ff_vEvfHav-uTew6nUj372k3ncDF1XvSZmijxfLk53m4PlwcMnZw_vPRhi99FPfvCNP_jOjVvXSfTdN36Ew_zBu-_cml_7mV_4_D_99d-79_bd73z_u7OD5ffu3ru43N-5ffNyN3U9L2dpc3ZJhEO_iF2HiPv9NGpx84vLy9R18-VyfX6GCIfLZbMPdqmfdYM7ssM-T7WauZ-fb8xtPpvPuqGUYqpMdLHeTrtd7A8vz05BpuXt1f7J5XwxPHrwgCHExIExALorp1DFU9fHECkAYji4drTTwtnybhcpRMKc9Yuf-vj24vIbb7y-HasaMRNzGNd7rbI6PBBRJAYgNdVqLayIjGZei5o5BkZCQg9IjPT8ndVHrs1vnixjYC17oivrhlUlZndvn1sAax0hZnaE9pkHgOUs5apuhkQhRFFzQKKgbtv9VNTGIqVqFpVqTGgGIXXS7JlIVS1L3U2FAWLf5VLVQYqAc661ik9ZJqnbXa4mrbdjDYtn6tWJqIqEGIuImdVSgSCAdamPET_14fdF1dksBqIQGAhBYZ9Li_LnYvupnK73Y665alWfxmoApao6ZPFSpNoVYhgApn0mIi-qasXcwesogbkRLFbLQaulFNycMahajFRK2W-3_TBwZHcF8xj5o594OTqN2101D8S5lMvtfjtOk0Gxut_lLIqBRPxKW2NeshiCI7ZoiojkXEquMYQWF6nV3C20LSdh38VStX3DOLYQo9ZSInOtolWHLqUh6Vg-9YmXrs-WMZCCv3OxfXqRRbVmVTWplqeqRQ2k1JaVViYQVVB0M3IQUWScinAMASkEChzGsSCCG6hZCB265VwA_MoGDQ4qWoup1HHyolrKfDY_un5tv1lfPD6_vNwtVvMXXrr-td_73lRL6BEBpbqI6m6Pga7i1lW8-Uj7FAiCUQj0l__tv_jt3__O3R--Ceztw2CiLgKIISVVcRU3bxR_VUEiM9PiHLlxtc0qkBMll8pEoAbmTAGZma4sMEShFbrAqSVHWlGwDX2arktFG_u81dPMWoqtWXqUgMGU0NvErkVeHdFchvmyjLn9WRwitoscsZkBBW-6MaLABI7EUUyQABADEcagWdLQIwCn6AbYYjgOiu7S9ESN_UMhJRWlkNoyP3Iy126Yq1ZDjH0H7o4YOHCMiMR9xzFWkZPbN6poTH2tRsh88IHP1KLM2LjZiBhTwojjWGIIBGAmbZCJQGHorUrouykLx4BEiBBnSczTYn5wstzvCzISgIANgQLrT3_05b_4Z37-weMnDx9ePvv-W1_75veRIDefbkwB6cWXP_T1r3wd0AEVEa6EqolcjRn3Y_1jf-qnfv2f_E4_S-ZICMx88fj8zsdfzpfbadzHviu7CcCPr90edyMHCkCymxaruavnmpmuelEla2NCtht2oOY8MgQgAkA0NSQgRlOlwCrSvhpmytjQkaqqjbGi6B__1Ce__gd_uL7YWRUEc8PQJwqBu4Qm_TBPfZhqAcIQQtf1jEgU3ezo8HAaJ1VLw0AA9b3nrhmERoYimMZxMV-IGFEAV0B2U45MgXQyjhRCiBRKzkPXSa6BGQgfr89evHNzOe--_8N306wvBrWog41TAUJwUgDRcu1o9dyta0-fXu5rvtzthZBTuDFfnMz7zZTT0CEBEHWRd7tJXWoVR2ox9FLFKZibEQCRippro16SOxi2s1_NQsxDSmOtZlDVPaDUVieDFiaRqg2LlIsQh1bmUHU1a3JcVy9WAak0PSRCFZn1_buPHv_Sz_zY6fmljbZc9O97_s48JjW83I1VJIuJATggUlFFoqlUJ0QnM0fD48NFjEQBz8a63uf1KAVc1aqogTNAn6KpJOIhxhjJ3BJBn8JslkChuonqo_P1m08u7z_dUur6lEIMNdfdOHLipgfHq7AhtBiPmTfAf3U3h8a-UNErmJdaDGwNF4ru1og2V_JbImxq3BiiqMXAbYpgZmom6o5o5tpCew4KjVYMaNBYBs397o7uoG7NkehoBEiAamBu2Gog7e6CwMR41a5mYnRUJkYEBWhNPm73dQB0BEQgUDFEMneMWE0jBTEl5GrKRK18bIBihg6GjugBiQgCNxcZIFNgbL5td8P3qhHudkX5JwKiUrWJG1UtNMwrkrsRv9cLJ8cAjBhTjIHY6fbh7LDvmJiJHB0dETEwIXhbZIC7gZZau65r9cfzzfrk6KjhFcAdQ__t19_8v_3nv3q0OFheW-zGfHB02AeOXTp9-PBTn_wooEGF3_vqNw-PD_alisPz73v-4GDx5Mn5Rz74_Ga3e_BgrVJi6j7ywRePOoRxvPfo8kfvPH7x1g0gHjNfbJSOZu8-ODs_3z58tCmj3j4-_it_8Rd_5guf_PRHP3RwNBfVhkwlR3BH5FbIQURCEPftVL7y1W_-8Z_9iVnqCYOpgVuE9jLDnPVffO27P__Tn4Eq7zw8v33zemRAtEB49vTixrXVctFN0xSIzHGxHMYxrxZHv_G1V71q3u42Tx7NFgurBVkr-k984QvzFM9O1z_9-Z84PX0cu262mp0_fvrSCy9cv3Hja1_-6h_5o3_k-uHBm2--ud_tPv3Fn-RgoLVLYeiDVWME2cjNa9cudrvvffN7WsvZ48egBrH_2Kc-9Zu__tt_4o__zAvv--A3X3_946-80sd47-13HUQK_-yX_sj3v_mHr37_hz969-Fk9N3vvLlaHjx59PhivReTfa4nR8fb862blSmfPX16drldLpYX5-thNswXyyp1GIbduDdT5jjmMpvP8zRxTM0pO417ZBp3uxgCBVpfXOTddrbq88X63_yrf_lDL33gdr9whN1Yf_jmI0p0cnjsKMQxMInWyNSldP7k3IfZfOhnHT350ZOUutmt5eWjx3fvv_uxz3zs4Tt3RTh03W4nJ8erD738_sahMOYUU1EFMMaWH2xrNSCCZv1xUyKkoNeOF88ezFd9z4TE2HUpRVZRDtHcA5IDhkC1qNqVOpCZwRCRCB0M3BGRY4rNhFiqGOBuzJfrbakq4KLy1qOnpZSQYujD5Waq7lnV4SoUp2YqGmLMVatomxRt9mPsuiwu5nDFKYoNyDvMZiFw38V-SByQU9jtRzdTx1pz18-qVkAH9ldefKZH6iJfcb7MN7vdWETV91kud2Uz5bOLURHdQcyrWFWrou3_JBepomqmqrtpbNnEGGK75ItKUelSMjdG6rrUdn3t7U4xmtq4n0IIap5icrM0RCC6eXJdxsw9P3h65oz7SS7WO8O02e4BeBxHVVVRcETmUmutWc3BXd2QSMHGMTtgjMEBWnH5ahPCQUQ4BASopdYq3bxDRiIcpyly0CIxJmYCc3G4fv1QxvGjL9yOSCL6zvnubCzjVHabUd32Y2kTZDU3FXQ0NXWv1aCCiapKydURq1vfRVBHxirebInQFPXmUrPIlXNKSi4177ZbcxlSvHZ8fHR8PBzNi-r9dx6oErqJyO07N2KHb_3oXUZ20DwVQ0RXUFe7wvE5GBIhB0oYtLVfwy_-4hd-45_-_jTtkUwEmqmT8b2SnCn-y0M5hVoFEYADmHBo_BJjJi3azZe1TK3HiIGR2InAjdwpRnNv1icg4hjNtL1YXO0K9XBlkFFUN1NyZw6lVgQMgWupyE0rioiO3NJEhMwI3GqBLUdLIRiAiSEzMre7Oai3ZgkFVpV-vijjSByklpACp67B61WcY2hmYmvUUQAOIQy9qXXD4G4GzoldtZvNzLShOlLXV1Mzna1WNZeun1URjjHNhtglAJovFxiSB6q1EnNQ1a4frOYiFhLXXLtuMLdZn9yUOSFLAyrlUjEGxIAhqGVmCn0qu9xxBKhdii64mHemlrUGhp7pl37m8_-zP_NTd-8_-o_-3n-z3u3_j3_933r2xo3vv_5DyRUQtrtxQNrreLhcjLs9ICkqapMdGTKpIxIQxz51ArVUCQxQpevC_e98b3F05KpVckgkJZ89fUdEkZObOYe33_rRredezA8nNBcgNaUQTLXvOpkKoYuWQElVgUjLhMFjF8y0EW1TDK2hL2ZuKlo5RjRLMbgJeFeqzZezt956OIRkZuBWBSL2Ig5TTYke3bv38ic_vpjKZruvpoRWDaRUIDw_e5pimkqVcYoxBuaSZVcm5lDEkChiZ6BjmboY3SxyVy1TSuNYekJKWIuieeyZQtzvpqGLTzfjcpb2j_bvPDq9eXxwdLC43Bdkai4nU6_VdtO46MKb7z568ea1g7770ic_9I3X3t7UaSxTimFflIFu3jrerKeLy43kGufdzRuHFxc701pqZUZR6PpOxNxxXO9DDPN5B8YAiA5MqFdDa1dwFVvnXXXIuSBTItjuJ47UxURuzKzuOQuaIsFUcopBTRG5nXFCT-qeMOVxanf92DEw78p0PJt95Vtvfu7ll998-8Hx8bJLtM15uxulqlurRdY2MjfVoESB8mZczjGKq3goImbr7fTgfD0WGUI8PlodLobgutnu-uNFyVOIkRJWMyl1HHMMIaZY5KoaNWa7e1Em4TyV-vjiguP7n70WYn98LZ09XQ9Dk-aAqyGRgQKSEyC4ODiAtn-v3AAADhTYG9ke27nfpY333RGAm1fQvUpNIag2cGibTKC9N-WSqt5MYYTA5NbCrEQAYkqIiKQGAIYA1kL8ISg4ojd8hzlog5EDqLqoOaKaqVvogoOJgYAJAUUea-lCAAIGtIboDwSGJhohMCdwi8xiQBTUrN00kICRRBUZAhIy1lKRArYbOBhSoIDMqNX06uhCDNC058hkApHZ3aQKEV3N_duAM5J4TRiI7MWbx_PAfd_lXLh1tQDQXU2J0dqkx4CI2vNNzUHbdvXKNUDYbgeArbSN-Df-zt_vOMYhmcBi1g_9rFQZCPvVjBNvd7vL7bje7frjeVF98cXnDhbLRZ-6m8fLBI-fTuvd5uT2jbPT0wXlIFwTZdZb1w-rk44OC3r9zQfb7yKDvv-F27_0cz8zGwKCqalMVdVaKMq1ha1A3ZDZVAkRjapCAX36dHd4cLJIPQjsq7jkGEMVowBE9Afffe2P_8znrdpUbLfLCE0LQaY-5VpqbZaiWuv6csNDOFuvD08OhximOg3zAY6ParUyldiDmUOXtruxS9SCAWbl2u3nHt27d_3GkZt1C14_vq_drKLut1vTilWi0zN3bh7Mh29_-_W-S3aos34uY553zD5pCUXk4PCw1LI8Wv7w3Uc_-bnP3z46uDjbqupzd57_wY9eV4cpj4ero7tvfpsMzt555_D2za987fIzP_mpN77_xqc-_Yl7Tx9dXO6Wq9V-vYnDrJuvfvD6D8X8YLmcilys7984Onnn0YM7129u9vuap_VmV88vl8vVOldQuVyfv_jcS6_94PXVanF-frZcHYxHq-35Rolw3v3-P__av_Gv_tL49OlPfv4VmsXNbv-rv_U7P3j1213ia88-m8dytJjtx8lEjk5WIfKT8831-XDnfTfefe3t9e4JOr752mOYp2vH13T_-JWPvfLszZu_-63XSAyzvb5-vDw5uo6IxlqVBiLkpvYsVQMiMgTmYBBj_PSnb9yK3XbnAZvUhWpRUHMHDgCOzYbhBi21T2YYWN2yFG-iB0NRMMTIAQH2pTogmtRSp1xjjCTuznduHNcikxhznOo4rvcIHjlwioxATqvl4nK9jSlVdwDXohhwmzMgmmsesxMr2tFqcbEewYwBEUlMzTEAJWYRM6mIJKUikJhHU0JgBFGLAV18s89nmzzMh6mIuE2Nog96eTYiQoqRHWII41S2YwFGNSu1UuAUk6hVkJozkIcQeo6b3ZYSiqm7IcA4jothMHdiLFNB11wV2rHNwVzRDdUoUM1jdPeMIaRc_PxiRylNYybC3XrtgDGFvCup75Csqk77PJ8vsmQEqg2yzCRVQQwjqrXmrBOy1Jq6lLrgZjHFkBisRTeruccUJjVHZU4ipYNOHc42I0RERUIq46QioQuOWHMuqiVbSGquORdGcgOMKFoZQuPOOaOZlay8oJonZqjiKYXmc2z-nP2-UuBac5sv3bx-7cbB0TtnTy42Fw8vz3YXFVUdoB-iV1EVKWV1sPz-t16vWRyNCNyMO3Z1DyEyiYgDOHGgwEwxMIoW8__RX_3lf_D__ZWpFCULAIFRHMXdgK0qByCOtWSTBhiERNyq3MSMesXIYECpUx7XIXVSirgkjrVkSp0iIkAKqZV6y5SRY-OCV9FIXKoAGTT5rTsAcmQsDSFjIbCqgVsIjT7gbsbIVZVDrFIDXyGATA0IEbjkGvrUjkNMBATkZOQOaI2n4Y3_n0TGGAcR6xfLcb2ljqgqujF3ohq6DlS5C27uakwhxn6c9ohMxCEmKQVDEKldiCEOPaIjV_HZYoHIq4ODmOL5erxx51jFu773XDEwVAG3wMSqtU-dmiA5E7lao6hqlVwKh15AAT0mdhERXMS-hETuZSwUWKuExBixWnVUoBRIdpf7__Vf_gt_8lOv_PNv_PC__Y3f3u2nss_fee3tz376E99_9QcD8ThO6IqEX_3tr86uz3LJHFinCYEDR0OzFsgNst5sh1lXJ4kxqlaKYVjM8nYXFvrsCx94594b43rT97GW4uB51G7oIFKAtD4772b9tJ8cMYYE7Ruodej6sU4t6tgsokBEiCqViTnGcayBYxUFBzfFgLWUGDsntiIxMbIeHt8aLzeLLo57iYGIAxGgqjsaQZkQI18-OTs6OtqPuU8dmk2aOXEpUrW229h-t-9mMxVdzmeqdcy1C9FVXNVcp2kkQCJWlxCiZOEYpNZkwVkxRanqBYchtX0jhWCE33n1zeVnX7l982T79n01BEJTYwrqHogEgEP61g_vfeHDLw0xfOqF27_13deq2NN8upwvrGKCcHywmvexmD0-vRCtq2E2m_luGktVtRoIJ1EObAy55qipcTYBWzDRRdUAGbiKVfWsmmIYp0KEqQs5FwJiZFcHJGTQqiFQCAHIuzi42JStqhQRNahlCkxExESmHlMAN0F2x9ffefDiswfnF2MtqICiUNVMtWQp2gBLjIhTrsMQA9JmPw0JpixDl5ydE147WkxZibiYPT6_RM_PHC1TjDHGbkijeR0rOAzDzFRLcUUTsO0u33-83RWpHCbRvLONbK8dzTqCyOGlW9efXO4Q1UExMJibOpFfZXwATb15CRDYHRQcGrcVydWBroa1zbpl5kyo7iDKgXKt6haYcq6IePWaZ1S1hjlC53Y7UFEkbwwc1IYcVSCPgdlJ1RBbk9tVjBndwQ3ENCBVMWISFQAPxNWEuZHpWvOYAjggBW63EhczJpIqyATgzEROKs3s4x694U-JqI2uEYnYGYEomDqHoKqIhO7g2GyghCxuSFxVA6EBxBikCiNwIGiLu6ZeIEBkNzc31Zoi3jkcbh2sUuCmUpyl4HgVHXJTQNPqgQOAu7oiEQMCMLOBBWqmGEOwnBUIXR3AgePucv3a119dhVlIRO4dx0AEDFnyhz_4IURypK9__VsvPn9rM5XVcv7C87eOl7OH7zz6wEu3xlF-ePd-HWteFNmMPbkT_ejdsxvXTvAQyjx-48s_2I3yyQ8-_6d-_ktdokZL0lqbwa0PoHa1E2nWZbz6BYRAgbS6mjvDk_XFKx97PxhPWaTWkIiZRCwavf3wNKT-sO9L1e2uAEiigK7k4AjzoTclBEohjlpVHcx30-769WfBTLNtN-NssZDzC9XMwhQRwA4WSwg4Y2a3LGUR-GJ9cXl6Cu43bx7-k1_9pz_7x__YnefueN5dPH14PJ_duHE4C3EJs5vXjlbHi-3lTqzWKkTkgmCeuljLztxHk8dPzn_rt3716Nry8uzcpDjZwcGs7PY9-XKxUMBp3MRZquttnC9_-8tfPZr3v_ab_xySe5Xrx9e3Wj_ysQ-DTS89-77T7Zk7nD452-43ZZJp2vYhzBfL7Tq_8MxzD548fvL4_M5z18fd_u6b946O14fXD548fLpYHe7KGPqZh-3y-Mb66dPf_bXf-h_-hV8c5p35NIgtV8Nf-pNfEtO_99_9szxtA4dEYVS5fedayXa5Wb__cFVLSUfXHi0fmpEXj1C-8mu_87EPvvIr__hrpwVh_Nr7Xnq-VD-6cQ1FHp5ttFc08ysrBpgYITCDugZARIiJlkM_7JPOuxuHHYK6G4NnQK-i6CYSIoNbJAZEAiAzMdvv9lfKjKYTTKEWy1n2UzFEQuxn4XK9r1mmWrgWcJj33bwbPIGt95cXOwcfSw0cQsCcK7sRMRqqY3AQNVVXURcABDWQUoh5mqbFYrEvGgKlSOpQq45j4YAxhlCYgobIIiom4E4Ih8tDUbMU85RnQxrHXLIFZjPvkM8vdxebPTCZY22SsmmfmBxQtKbU7UsOSF2MRbVqCUghxTJNU5WIOPQdwnw_jqHnosWcupSIWWohpJRiFXGts3lXc0UkJ9znikzj-vLp0eGt49XDR5fEvN3vixmJKhoZiao7BO44MIKWqdYxA8B2u4-Jq1UMoV3cXYwCg7mYxJACIhOnGChwYi5aTS0k5kCNxDPMe0U38IBcRWKMInW3n66dHDOAqtUi2_VWRffb0RFUTUVNdZrATKtWa35GNzUEEjNHJDdFJqlCYEVVpwJAwFdTKZmKu6uC5v1qtYwhDEfpyTvnb715r62aRQXUkRyIREBNQEQUAP30ybkDmbi1vIWBiKF5ZEwpySQcUiBnJBebaj6-feO5w36_y_vNumz2xhRjQkCrToFVKzf-GzAm0lzJW2SERAojIZqUVlk0CqT7aX58UqeJU3Lz1MXJDZHaehyJFBHa_DpPyC0JaghGbVevAkBEqKboBkCNI9d2xETNi2chsJlxjO7W97Mybd0pIatISAnJKJKLMxEgmRkjUgxt1d6ce6ow7Xah731UCixTdYBu1o3bcVjOyN3A2qKXY2e1DMu5lGLqedr1fSelBg6OIcWuqkIiQDQrIUUx6BdD3e1j4NlibgCHx2EYhpptGjNyBNHQCsRS1WqDjKJUBdcWNW4dWRNzFzbQsWL7criXcQophtQZQkgBgSU7EROjifc9BEn_6b_7v_zJT3z4__pf_tr__b_-tXunp-fbmtH_4a_86rUXry-GLjoQhJqtVJVpPDm8RoROaETAgUJC7upUwRDJX3vtzZNb183dkNTZmpGHeMplu9-FmIhJxWVUBsIqkiuCgdt-fSkVDRDATSoTk5tWNSJwdRHVoiqIBI6m6qJEpFJjJKkZGgilVi-KhKoqVdVMqqr57Wduf_f73zd1RnQnKQIApdSiFZAc0JAePHinW85ms1mutVaVxmdBpNitL3dEKNXKVHIt2-2WYmSEohkQ1W3o54kDeMtjOzqEyGhOSqpGKdVSkNBUS1aMQIGmsXr1Yv6dH7x5cnR08-QoxRhC4BSQiIkBqVZTh4fn69NSRWA-ix978ZmBMGDIYx1rrlpUlSgcdWk5m9VJ13WvbsPQHxzODw6XIYWuT8zAhPus05T3-0mrNAp9lUpA6BYT1YZqqjbmgs55EnQIzKImYn4lG3bFRs1pfns3t55jStFcFSxxLEVEBYmq1CoCIUxVn5xtN9v8zqPdfldqrbvtCOZoOIlKq-ywTK4CaI7jKGOu0yTrcW_gY877XdHqhDwMcTnvPnjn8GPvu_bjH37xpTvXhpiquQC88-Ty7v3T-2frtx5enO_Kuxfrp2fby_N8up3efLy5HOt6N-4mEXEL9Hi942GmzpdVh3maHcy6vgvkaoqNaGnNy-nN6dPG_QDQZrygBt6gYGAGan6VyQOXNvolVEBQr6K7fQYic2zJsUYWEFEAbvtNqUqE7iDi7qjQ_MLIQKWIuTERO5koXykuCMgNgDGYAwKICBMBoJnFENFBq7RFQQjIxERXDM5GyjMEZKRGKQbwtuVVCCG4aiIGwMZ9w5aWc0uBHQwBvLY0UGO0UooxILWFNTIxNac6XqkeDExc1RDI_UrFZqgYEN0QsUt053gewNtugKkVEK7O9A7qWii0vzM4IDG8N_JxROTmN0By9yLNNIEINNX6te-9XkbthlRKnna7o-NjVR2nPMTh6HCFpg8fPN3vt3kacxlPVvMXrq3Gy_XBYtF14fHlpmz3q3l3-e755z7zEqUwZTg8XPaL8L2vfu__9_e-_MlXPvTX_-e__K_96Z9fzAKA11y1GDiiAyOo6XtcCm9cspZaMmudT62uwI6KZSzD0G32E4KFGAipVnOibbYf3L33iY-9lKVsxzKWPBaZSmnpQzOoKrlkRwAFAnbHasoxTHWc9vvEkRxKFlUzdyJmh_12F5hQbNxvE9H6_Cm4xxQYMIbuQx_98A8fP4wBvvTjX0CA73zru8tZ9-jhA3Lfjpt5CmePz6aq2USZFNCIDbmaPX38ZFitKtaTk76z9JmPfNyrXDu8vhjC4nAxdU7G7p5OVpBmNdc8TvPF7IOfe-XJ4wePnz6tu8nM7z94kC_W__y__7Xv_OG3ZD-S43q7AYCe4-X6LOcyjTLuSwicZQpEi3l_9vgsEt-8c_zmG29cO7keZ8PT01MkDjH28_nu_OLw-NjF_sXvfmMcYZvzpHC53xR3NfhzP__FP_8LX_zAS9esXsh-v3nytCc47GeoggYhde_7-CuL29f6wwMx-I3_-surW_G4k9MH72KX_vC1-wrEQ5e64eho1vAASNQA9SFgk8oDYRqCqCzm3QfvLBmxI6KAXceBGdAZAJlSCO4wNelkCIZgiI7kjjEm5KjquThSKNU2-2nMJRcxsxDi-WbcTrIXK-65-MUui4OD56rIXLVOucQQVX2spVnXkWi7Hx0hm5dSp6mUUkVst58UPPaDO4QQTKSM2VWrmonVIg5eVcdcmnyx67qGbkREEw9hUAzbXUGK6-14vt3PDoblavb47PLukyfn612uYkhjdUB2QweotRYRR6omDqhuDAgApRQzReahm5m18IsYaDfrAICQhyGFEE2lTyml0MUQA6cuuViTNLl73yc0N6knyyU59fOOEipS7HuptVbZ7Sd1R4RaC4BF5hhgM40YqB-imrm6iWLjrLkHbsYc7hpsVC0QM_qURxEVqe6o1VWUCaJjmWpKnXOgwA7OIWJM2f3pZheZI4dhlmII4G61TlXa-6WLwVVNXNQMPaRI6C1VquAcyNEXy1S1SX8dEcBwu5tEzd2rKZD385kRnZ1t337t_umTS0p9CEGtApiAeeoQUK60KzhbDA8fPq4tbUoAaBwCmLiKq2l1MLLq5i5SHcVdIaa_-df_p3__H_zKzY-_7-zywsmkmqqDWuwDoUYmE40xuhmaB0JXZQYmZXR3hUaCd3ciAjZV8Rrj4GYUoyowMxKF1BFhiAGAHCgQBg4m1vKfRNQqB36lkwQENHSpQsRIFAhaQa_Ff4DIwVXNDcCaIYMA287OKMQrWwdgDCnG6Eh9P3PkNAxA0ZypJV8dCKDrU9d3SGgGy-OjQAExxNRRYI6BQkizuRm6EcUOAK-UoGrdfF4kc-LAHDgqIBIPixmYc0oUkscQu2RIIabZMAQmdMvj3lRD3xNRYyGPSORqSLzd7gzR3RDJEGutgND1EczAPfVBc0EytUb7KsDkol4FgBZ9urmY_e3_879Dqf8P_vY__ur3Hl3uyvnaduuxCrz1w3t12nzqEx8PAx4tDyiSVB_Pd9euH5O5mnII7la05LwTLZKnPsHvfeXrH_jkR8xxWMzn88VidZQnker9bMi79WK1rFrdNPWoUhHRRWM3EEVOMU8bJkCCnKdas7mLaZXi5rFLNRfiILVSoLaUYWDigIguZuol19jPzd3VqzTIOzrCer2Zreb3HzyoWQ3c3UqtzR6XUlelEAIwicPmcnd0fBC7iEzzxdzMYhfBLYTg5k1li24iGijEGLWqo8fA7goIKqWxCgCYAAgDOUSO027rquN-FzvOWaZNISdVr9WV-WKXZ5EXITFxCiEyuZuZ9sRVfJqkmv3BD36URczgxRvXPv6-5yMBIeaaq8l2mp5ebB5c7GNIB8vlfOj3edpup90uRwoMNO9TCuHacvninZsxxODYdYkZFaxRrzSLFxVx7ogjNFJMR9y4suBu5OI-1cnROUQkDBTUzBwYOETuQgRgM8ylkGMe85QnQBQ1Fd2PkxNe7ve7fQbGba6GqAbbPO2riJiYopOUOo5jqRWYxLAYTll3k5SKVWE_ljzW7VaWEbTU_WV58GD9-OlurHa2La_-8PHDx2sBzmK7Io_Xu91YKvrpdv_Og4sUARhU28tEq_hmzIDETJu93n-8ffBks9nJYrm8cXgw72alGhMBYiPpO4E38r25mTuCI2lzAbu2vXC1KwNWG_QaYjVTcFUrJqICLejv1vicZqZ29dzHVp9qcR-1Zi4DpKqKAFf53ybUIXBzVSUkRmB2ImhJeqaGMm75-5aaByIwMGCoUkNkJzB0cVOVyESAXiUiWQBBzZ6309YMJ5Fm7kRAFUFUcNDG4CekgO5AjM2ILrUiQEDsYnDT1AUiDEgAHiIBeGCP3B62BgzmDs4AQJHcIXk0A0cwq25i_1K8oKYibmAQ2qmeAiO3iwC4uZqpWRVFJCAARC9KjAZezM6227_1__q7ByfL2XLIuzyfzRMHUC1Zjw5XXQqnZxdvv_nW9ZMjM5jx8PGPfpAVtht54YXrDx9cXDy5vHZw-OTB-uUPHD938_pA_c7l299_9x__w9977s7z_8m_-7_4pT_6-cNE7lMpIlncWgYJmtuuVlUxJGSiGIO9h3kFc7VmdgM3ePD46XO3b0BRc_eANec8mqjXqq--9sbHP_TBLg2iOI2joEmCFGObqlpbtoia-24ai9lY5WK_32z2Oe8BTWs1NRVtI2Q3NFVAi5FPFt39t-4fzpcdBwZYLlIMQK7vv_Ns9Ho4G8AqB14_fLxYrdIsudf1bl1GmfbT0Y2T_b5g7Iurmg6zWeyHsqu7zeXLH3zl-_funbz_pSenj7_1vW9V3V07vKHmI01jGWexP7p2MlsuumEBhPtHF7MsVmRxdLC8dSfNFtD1qrjdT-enp__9r_9azvL73_iDb7_6epdWZRIHOt1u3336yND3Y3V0InStlxfnmuvtG9feeeut46MD7sL52cW43cyXSxA8OX5mtTr4R__VP3nt7tvf_uHD9b4-Od3lSaexJExHXffFD3_gj_3kJz_9sed9qo_eebTsFzevHR0crmZd6DjOuH_mxRf62cB9ePPVBx_--CcIyCe7sbCACkClWMddxIAMgbiB6ktVNWloXkIA9dUQV4tuiMxBpeY85WmcxrFOUomIkQCdGVOMu5ynXDa5TlWkWQ8QiCkGVKvb7TjmaoTV8GI7Xu6n9W6aqkxS3NkZHXA7lv1Ui-pmN5qYqcYYi2itPk6TATmgODhgKbVWLyIQ2Vy3U65SVcSIjKnJUHOWmqUVnTgQMat43pcQiJljSl3X9UMTMIIiZTNzeffh2ZOL3enphjuez4f1fi8g84MlpzDmaT-W9W7cjmWb1RCk1qZXdDU3I3drPx7qIfFsNqQ-qZmLMXJTugZmAgUAMwGAEImRIjEjFZU85YaJL3V68dlnrx0cdikRgrcwN2O_mDdWspkikqpMYzYHoLBYDA6AgQ0bBBrMTETcQF2nWrouzBdDiLGKE9K0z1rVXIf53M1qLfvdZIa7_cRAzC1ricWUUig1q9jZ00eOgOwIrqYtYVm0NH97FhEVB1dTMy9jJsRSq6GIStXiBMPQi4A6lly1yJSzqGw3-9xCh86pT7vNVqSoW-zZ0cWs-ZVdgdwRNYADWCmFCJ68-7Q5E9QMiKGhNsEALA7JEcwysQOBVRnH7cuvvP___V_86t131yFCn5IBGTV_sltVE2d3QBQpGKICttdkA0i4g6pUEQx0dQUhxBDKLmNi4qjvtXebrNPahhmxyV6RKARs7P_WuGvAB1NFbDtzMkLiCABADN529eDutdbmwkRHIgghaG2aYTJ1UcOQ1LwppNoHYColDh1FRsLQcUgBEDkyhmiAcejAgEJQBQhhebBw9yI5dn2I0RzSMIvzHgj75dwAFBGYW0zXHblPmIIiUIhSpRvm_WxGEbthCKmLMcaUnCCktNlsY9cJQhUhA1C1EBO1Gwygtm8VBQYKTG0pZlWlFhUhRI7MiHkc3dkhSCmBAgInxuvXbvyH__u_EhP-f_6rX3vn9Hz0vZSsUgFtt5nCkP7j_-g_-_DHX7l2cgTBKQYDj0CzvmvHIyQPAQGsSFWwvN8H4oev3o2zIYYAsRtWq9AP1cGYpu1G9nstMsxmKtnMQb35ok0qcWy93dR14B4DQ-vuEjq6O6hqq_yie4zJ0dVkynupmWN0cCISLU0nrCYA7thQK9jNFjGgiEAIYmZmMQZGcHAyQ4NqUKsg4Tv37lenxKyuJuJFycHNsihRIA4q1UXNPU8jIc76TsVCDOqgVQwUDBFcdZpqEdBJp6lMFIOTV5Ep5yq1GeIB0Yn2k-Zcf_-7bx4fHEaCmvOUKxBUk52WEMDczODxZm1V33jnaa3ywvXjz33og9Ggj1yKtEi1mVbTojVyXAwzAJdqm-2mOReZWMxEZbkYhoNZYKyq4yRZtdTKzFUl5yIiRNDixVkrAU61iGkTkBGwmVWpqp5LVdFpzJfbnYNzpFnXoSmiu3sIwZs12d3N8lQUPDtUNAdT0SnXzW6s5gzEFLWaVC_ViogA7kvNakUFEIrKLu-rWXbmGG4eLnL1p5fj4-10OcnZWB9cjhZDWwDtpYoChMBMWez8cj9VGw4X0HGe1J0MUMyzwcWunO7GneNOyoQ4VXv3dPvqu-u7l1OcxRvXVqt5j2LcAv61geicELWJKrwF_FrDCdABzMHBDbJmAm9iXWl3AkdrXGdseB-DRplwmFyyK2DbWpKpu3p7TpnplXJY3RCbIaOouak3sDeCq4XAeGWvdwSITICetUTiEIiZGsqj73pwIActiuLoaKKt8SxoYlbVEDAwtzGbVDVrDGPkhpEVL0WKVWDHSK2SC-ScGvoC0ZEAtRpTAFBCALT5PM1SDIjg2nfJrd2gwRG7GJaz2c2TAzZigCtYkjkFCiG0P7etA8z-JQQVoJkbqdWNyAGZgxqMUz6-edCWU7ud_Oo__9rdu6eTVEdD4m5IFGi9u3zmuRur49V2v9mO-fTx-TSW-bB4__N3VkNfRJ67cyQ5b9frR48e51J_7Cde-vynX0mz7vXX3v7Hv_K9n_nUJ_7m_-6v_cW_8EupS2CqAiQEauKFIzSdhllznV3lud3dxMFcVZmoAYvcgQAJ6NGj85u3rtWpNt8zGLYu-VtvvjvMFrduXteposNmM6poH2ejSFZVBxGvqpvdqGbFTcCJYbcrkbmMFVMfugVA7IdZil1ICR27EKfLnEu-t998783vHR4sIkIex8NuEUAv1xcHs6PuYJFzLkXu3Lqx3Y6HB0dd3_3w7befnD0tlrknk_zNb3zv3sMHABhDv1jdOVqddAcnZv5jn_5M3Y7k5f3Pv3j37r37jx6cbh-98v4PycX44Omj5fHB--68xMzto_zkyaPd5WUM3b037sdld_3Zm57H67cObp8c77Y5V7177-3_w1_7a1LKH37rm2cX56enF0-fXhwenlSji-1GnTj0tdRZ30steT_Oh9l-uzuYL-bLGYdgtR6cLI2kW86t2PJT7__W17_ztW--9tbjizfvPsqq9-49eu21t_bbEfflJz_54V_8uS988kPPTKePd09PQQqxH8zCajkfp80Ln_vEcDT79V_5593i8Od-_me30_raret3777NKWmegrmCh8SA0FMaWumTuKr2MQbitK1HXb8MiUhToHmKXQqLeTebD6vlbOjCwWI-77vlrCNCROpidPcqmqsAAgcGB1Gfik5VMLESTVYd8XK3349lN-YqOta6pOAG2-203hV08CsEUShVkDgXybWKuSGIWWDWUqxKoBiB0fBotTgcZimErgtkOE21ihbVqpaL7nMZc81FiqqDl7GYGqcQQ1C1GEJKXC2Pu_1-KrHrzs4uL9f7cacUaTmfq6ODy1gdoLTcglsxHydRQ1UQ0f1YkNDMu9Rbe903p5G7A7TXHAKXUqRIjJGJKAQgn3KdaiklV1VQQBCtdSr59nO3_syf-GkKcr7ZXFxuppwZCRzGUtMsMXOkqFYBnNEb-z0OPQcseSrTqCJmWnNBQo6NQMBdF4GoVoHou_1WpNYqIUQgMNVxnFIXKLITxj6ZVK-GiEwcmDoKPekw9IAO7gQ8ZXEzQu5SBw5MTKoghuAuykyqTQBPIEaIhFyKAIKC5zy5w24as2RHN1AVE1GpZX2-zWM2qGWqRLEtphp5IQaEImU3gbOpc2AOBKrgqFWIGBxcaqlaKnBI5pBLiTEgUddHAGAM_8qf_uJX_tnXx-niK__wy2wagAi52dmLiCauZCGymSFT8z86kba6EkPbVDOH9gQHDjH17ACqHKIDqjljCBRNW9scvAlkA2ut7iBV3qvUeVsMB44EQE3rCWAETlS0SpuCuRNCy5cyEjPVKQMRx6CiV34xDsih-fQUEIlil0JKYBBiVPWQuhRTk0HNj45bbIRT4BQAjUPa7sZutjg4uBFjjCmEPuYyAhJ1iWPsZwuOiUOMXUizARiH5QKQOHTzg9VidQCgi9VBPwyzWe_ms_lwud66wzTuF8uZucYUQ-yo_UqxAwREJiIiqEWswfY4qEgtElISBwLy2goXELsAmiOBuVIM3aJHov_TX_vzxfgf_cbX7t57CjGUzSRFtHqZspvmrHWfR9l-4XM_nmbxaDlPfUCvOoojuYCKNxKRiLTYS82VAd763htp1lHoifn6jRsEHFParrf7nE8fvnv99i2i4AScusBoLm5K5LHvalURqWLgpKpSxUwBHJsj3SxPY4itCszt8-PmJU_cnHAqVotUIWYtAu6cmCL0XX_66KG7l1y6lBwBgVSNkapoLdqnKOol22azWc3AwdvEN8WEYCmGqez3eSS7wiOKmqoZuDsYwjiOsyERk4upm6NPRTiEqlMModaqolcGLEB3m_bZwJHQTVRtm-Xbr92dHXR52qaAVVWvWE6uRdCdiFfDfF2n711c_vD-0_U2Hy2Hn_70BxLHPiQxZaJqUms1QXcoqozcdZ1omyVYrdXB0TFPhc3R0RXQLBASBiQcqwCBK4IihZCLFFEHROZca1G53I-NvQ6ApWRREREEC4FyLgjQJx661ELJZnBViEWqaqlPxNSMlVK8VBMtDu6qaIzCBNSiIg2PA8BVZF_KKFLFCuD127PFwLNEu1xON-V81AJYmbZFLrfTfqzd0C8P-vmsK6LvPr14-_H6wen20fluv6uW30OBmSGQmmMgRXpyOc5dtEodR1c7urY46GnGMBbZTJIVDw8Wq1nvKkRo4t5MVObeWJ_ubWTthi37Fxg75mWcMzE0PugVR4fU3cBFtKqpNnJoowA5MgmYYWsUI0Ir12IrUqM5uJMDmDOSVCNCN0N3JiRCFVN1R2wWFBU39YQcKDSkWvvN4EKISBgTh9ACQVDdBKGqmQg35Zl5kw4ERnCPiZCwqBYpzNR3ITCbQRORtqoAMDphe_E6OJKbCgKA-bV5P4_h2ZPZIoZ5n1wVEYgBQBNz7Hg28DCLyNxWFXh1XXF4TxOGYIwMBEXKlQ9TqltLiF5VygCAHC5328PlTFx1qr__re_9s3_x7Vc-cuI7sOqrw5UD7PPeFK8fHgeki4vLr3_9O4z06c9-XCpeu3ZEZrU6c3jw8PG33njz2u0bhwN-7nOfefj6w3_wX_728Wr59_-9_8nPfOHji47VtBZEIGSigEgYKREwUyRkuKpMsKgQXJlkGIACIZE5NvQKIFxcblLfRSYRV9GSaxEVtx_88N6T091HPvJ-NKztcB-DuF8_OjQD5qAOU65oVEUBaczZTGfz4f7DhwfLVa3T6mAGxGbuRmIaYnAwRBSaCuD7Dq_df3jhZrdPrj94eP_66iRQfPTgQQB6-dbzl-enq_kBc9csp-7gRRarZd_N-m5xdnYK4FC0S32cdcYZ0YvVWerI5SPve-n117-7mA8KAtmePD2_fnTr-PDg_oOHhyfHR_OFCxKgA4rA5Xpn5quZ_uj3vjan-Qc-_MEnjy5v_9i_-twzt6-fLMf1-e9999V_6y__m3_2l37uMz_2OUzp6dnpN7753f20DRzXu93Ty6f9fDnMhsVy7oBPnz4-uXbCTCrSDTNRqOLnZ5dH169xh__wP_3PPvtTnzzd75gCdQEQ79w-7ufdOObT8_O33rp3slr81Od__KWX7ixX_Z1rRyfL2dFqcf3aYeqSG7782U_O-nj7-cM3fvDWL_7ZP7O4efzu44vUMwDFEFo1KoZobgKgxBSo73tOIYTwgY8-94HnrzsicFDzWoWQGWlIcRHT0HXN3mqO4z7vc9llraK1GBEQYYx85RBEAiRzFLNqkNUvdvsqnovlLGbwYJd3Oe9ymUo-u9iKQiPKi2gj-U9FxlpFNQZezTogRsSTk-VsMfR916ck5mI2thmVahYrYmKQS61V2zmyqgKhi9dqDNR0TC6-vtydPrkci252E6WwWMx3NedSyqg3T06OlwvdixUPGFzNxYiYmzSKiZCqmKGpu4iie3tViNT50BMHU_PGlREpReaLmWgzkqEDlCpi6oHMzKCGrotMP_VjH_mzX_zM2w8enF3sLqe8mWrO0t7YeZe9QisQO4Cqh5CmqUz7HZY69N0Q2UQdNMYIiGQQmGPgwJGZaxVzdQVRAQRXQIM8TlPOZjabzdpFbuhnGKOAAigzxcSBS1R_9vbzAIiIIVhidkRCmM_mFEjlajSuohSpVFH0aaoAQAhaldDd4da1w6aJVFcH3I82jRWQ1bTmqiKmDcqHoh4oSTEmJwATd0SxYgRi1dSsWimiYoGQiQg8BiYCcGeEEIObVq1IxGCusN1vP_ITn_39b72WOsSEXoUcQTQQtSslE1opyFEcpCq6M0Ui5hgciCiQIxpwDKKGIbR7V-BEMaFYP5s3zZZVYYDAJOpmDfdmKhaYTMXbDh4bNbsggJs6EhKHEJ2g5syBERq0utk5AcHNwc3MDRCx9eSYHAmQ3FDVmRmZU0pmMCyWiBC6rnGs0zAD5G6Ydd2MiRarVeySOzhCN-tDx4vDVYicYuiGDtzJPQVOBKQqubRcQEwhpZ6QKEYkXxwsu6HjwIywWB5ayQergxjC0eFSq4KII5qalDosDlLXcwyEqozVbaQQKAY1ucqNEWAISMwhXgVPgU1Nyhi5S9xFCEzBHRzpzsvPhj789GdeijH85__oq1_--qtj0Wm701JMzcXcLRKiuSn8sy__3s0Xn_nEhz-Upx2Z5XE6OFzERaI2Iycwk0jERBDdzJH87R98p-aRXNNsMY4TUbBakVC1MsHTe28vDo-NopgIkSq4g9bKyN2s11piQJFCHBAcTLVkAE_drPFVtJQGdTJVMG07IMQAjiF0jITA1JLA0D638NyLzzy8_yA5BSYVISSOSIEM0dTMXauAiroy-vdefaP9OO33Y-wSBMKYFv0CAcBUqyDHdnGtKhBDHxJiKKV2KTpALRnUu0AyjQRQFYCCF9FcVdzAVTVPYoZqjiEAeeziweGcFT750otFSkBg9yENgchMDdVI0xA5dbdWB2up37v7TtPXfu4jHzCxWeKDw0UTIQuquRFi7IOL9F0CcGLe1MkdUmQCq6K5VASMzK4WI0oVVQBAZlI3rdKlqObbaQRg4tgkNY3UjnSlynJHqa7lCsQkVboYCbnVXt0IxMskrbOt5sihW3RZbd73MXRmJg5iki2jgWQTlVqFKYhUQna35Xy-XM4PD-YXp7kUPd9P2d0CU6Qqfn65G8e6m_LZ6eXp000p_vjp-vHldiqyHsddkcuxvHuxfni5mYqot9w-GeE4yVTq3bcf_eG9R-fr_Wq1PD5cxNBR7KnrVNERS9Wnu6kQHh8dXGFnQFtpquXwEIgU3ZEROYU-RgRiDoQeiBipi4GQ3NENFZwcm6q6AW2pub2ai0FdRItIVa0qLXeE3tCoyMzE2O5UxOStERUCoIeE7cvbIjCEANCYDCylIICoEDExtS2NgakZMalrQ7ShAAGB4VWkFD0yMYKbMqFUr6W6Q4wRmrzLHN1FKiERAAEGoJJrF7DrYmAmcECMCRdDXM37PnVimBInxkUfjxfzVR9nMYAouXfgEQmZMQZkRm5Nqha8VdPqrU9jnmJsVrY24wHwFv7vY7zCLhrHvqtVVOAffeXbf_SX_-hXf_Pu8mDe96FPya3ux8tbd27OZl0t-d13n8h-fO7F22bTtZPDm9cPIoKJ3X39h1nt5Refx84-8YmP_ugb3_jWO-f_z7_xb__yn_9TqZuzkzubE6IUK23lQxQcHNDVrdoVdNjNUwzQ8rveqp7ICMyAgA0Q-927b33y4x--OFsHov1-BEJFfO2Nu-rwuZ_8BJmp2m6srW8zlZpSnMo0laxWa5XUDRy6omBORZ0QN-tpGBaBw9G1IwohRCy5lFKYyQ1S160vL6e89xA48Thu3vfcS8lhOZv1kR3LbBafe_76a69-N9vuC1_44sXpRZlqCtFC2O_L4-3TSWuowWV_6-ZJx2x5evDuwzxlCrY8OLg4P3v2-rUX3_-8jhtmPprNH613IuX44CDvx8VyNY9pPkuzrutCnM9CudwOfey6fj9VTiFCd-e522_94X97eOsGEfWxe-PV7_ze731tmC0-9ME7f-nf-DOHx0d5XH_lK797fn5qqoHD6enT-Wo56-eBiZxOHz1cLBcufnl-jmiuXksZx7zdjve_9cbU337r0cPfevPN33_9nceX-bL6rZtHy8PFyfWjH907_-offuvXf-crt599phv6u2_fndZ7F52Hbka9jQW5-8Hb91YH1x89mWTaL_o5mF6_sbp2MD-eDyl0gYkAI4XVcrZY9BwiMXZ9tzoYPvDsgQnMu_7wYN73qUuBGOG9Ln5VK2bVfb3Lo5g6jaWAO0eKgV2tZlG1fugaYAAJMZGojEWIoxEysiOJ1N005qJF1RCmIllyVaXARbWKzLrQMaEquco-7ybph-7mnWMiVFFFn6rsStlOZcraHiW1VlHd7kYIrGBSLeeqBqIuajFQLcXNOMaG_X3r3sNcZb0fSy5I2Mfu6Gg2bqbTh0_qVNabbTZB0SbsU1U0TIG1CgAhszuKWuQgooRAhH3fV5W-S7GLJkbgtZYYuKo2XXutUnN189B3bb4GCACaQvrgrRuPLy6fPN0-Xm-228mqTFPJuTQfGZibWlZtAANAQNft-baMedqOk7hVKaXsdlsCQzImKLU6gJpPuWg1Uwkcpr1SiHkqNSsgpiGZQ80SQrzYXiLCYj6LZNF1yfXlO0e__Ce_GAHRUYvuHj_tg0dEFyf2ed91MQJy7PtuPjQbhBkGZmbkEIjgKkcZghbpUmr5JXSpUsecJRdEJ2ZVjSlYMSl5uz0LjLlkUcEYiMARxlK1CAIwoktBcBVFQGZyUwXQqk7UoqqMDA5kJlm04pd-4YNf-81vZTHXbGoihoAgFR0YOUBj-RsixK6hxtRbhrXR6dsDUQTdm2HGEauJAioQAHBIrmroIuIUAAwJAIzYimRrECEEQ28svhACgbqp1oqRzCwSgzkqBWq03Aqm3A7GasBXph9ATP3QbgOOTgEoEIWQ-o67LvV9nkakIG6YUpx1xKTo1RQD1CrdMKfInOIwXyK1PJflMZecy1QoJANycRMHAGZWqX3fhRAbdjF1Q1VfrpZd6gLRYrXo-jjMZ4Qw65aqfrBadH1HDiYWu_l-t6MQZkNPedwjYs4lhJi6jjEEjpEjGVL7h7hWQ-4AkIMTYpVJZeRA01TTvCdkEDo-OPjxH__i3Sf77z0-NQ9iZTjqpklMVdxT6gyIw6w_XH3t97_7-MnF8y_cet_7XlaxSbTvFgfLQ2bKUy6q1RRDoMAySa2CGOouh264eHB_WC0oRQ4ArYph3s9W5LTbXBwcHDkCIHAXkdFVyKHZFogCAqlWQmAwMjVRk0JM6GauYM5MiCAiKoLgNZdW2xFVc2kwXTcRkZLl2snx0yeX01TUq7u6uqmVagTYch3UVN5VYoq7iyzqQ0pECOTTTlwcEA10V_amYCZIpDUHjuykqozg5swcgFRqVXUKGJKrmSuAhRQAHByl1iYqLSW304yqSzFA_NG7b73wzPWAuFx0HIOrBKCu60wdDGSbTxbD0Tw-ON9utH7njXfQcejjz_74yy_eugHFFvM5hRBSmkRBQQ1DIHAA4L3XvaGCZxM1ULdsMpVaTQFATIu5ghHh1FbPRmC4H0tVL7lKFXRwM3Rw8WabIiYEICIxLTl3RFOVnCdmzzWXRgY167qrG5erq6GaVXEnbwMtJ9rVMtY8anUwAC4qzj5pVbDD1UE_9ExYsqz303Zf1ENVqOKl2r5WcxynUs0F-HI_ukrfp2kcCdEcq_vebCNa3Jp1UtwUsZiNVfdT6ZezR-c77Psf3j9_48nlVGXBKFn7QGq2maaL9XR6OY4KB8vV0WrRjuDvpVFcmyELkAgSUVvwmOl7AxhAxIYiAPAA_B451NvsXEybZ8TUzQwJASC0TRdcwcQ5kAOAARgExsbQBEQHZ0CroNKSM-ZkBlDVCQlbMRTZEayBcd-zFCOQi7kZE3MgcpdaVbR5LNsT2cDEFBnRLRD2fWJEboUBBTUzVyIg8hAoJpz2-yEFKXnRcZ-467hjP1j2z50sl7N0uIwEntCuHfTLeTqchVVKy1l_MO9OlsPRomc0a2uzq-0mIaKYmgIAqSi6MwcgMhEDN8TaKuxNlyY6TVJE-tkwKU4F_86v_dbPfeljs12eHXQpxTTvNtOmqEvxO8_cAtT1xf71b_7g1u3r15955u03N5_7sZeR4tsPHj94ehpm_bPPPnt8tHj64PTJ2ZMvfemn_ub_6i8igLuKgSOrOkNlhxRCYxFFphSjA5peJZQc0F216UjVAYADq4IqVgFRhRDevHv_T3zpp548fNh1aZ-lApSqb_7o3XGCT3_qQ4mhijhBCpxrpRj3-7qcz_uuR6JSdayVQ6gG6-304PHpmDMFQvOhm4-b8ej4qCoK-NPz083usohOparqZr2Ps0Ggu3nt2jsP789mg2nx4NzFgJgS94RHJ8-N6-3x8uTg2sFrb75Rpnx4dNDNF-dnFxfbLQ8p9v2NoxuiapgIaTvmanHS3Xq_n8_61WKOUObLxTMv3HHLRQtzsMgXm8usZbac7VX2pUylrC8uQFnEkGlzfu7gm912frh4--13jm88WxymAu__sef-9t_9B2dPdzOC_-1f-eWXX7yVEN66d-9ycz4b5kcHJ2fnl13Xc-RuiDnXy_PLF158brvZ7y73IjXFsJ_GYT47f3j2-td_49bseL63abP51a9892y9-_qr7_YxTgKx49fe-NHZ6cWv_tbvLo5vHB4czZfzzXq9PntKhHVzWXb7o-X8_OLJF37igwfL4XOf-cxsNpvWU4yRU0zoA0UC7DtCw4hMgAerBQEuQkqO8xRTwoSQOERmckMANV1P-enl9vHF5nJfioEy78dpO-ZJxNwAIFe5YuoipxSruiiMuzpmVfcinkutYFl9V2xfRNyKea1aHQSgLZTAVdymsTY8PCJ186HWEpG8eohcqxTRol6y7cZaJhWBnKsYjqXup7LdFcJARGDkBnmqjlhFS1YzIAAMXKqdn-8n0THrepfX2_z0dP_W26frcbwYx_tPLzZT3o7jxWbbJielSKPXq0EWAcAUQ62lZeMYCBSoPenMJOfZrCOkGEIXO1XASOa62Y5lqq1jamZNBISEv_TzP7Uf7c17Z6e7vN2qTkbMTA4GdS_upq4tbsiEUqXUWsUcQEzHsQA6xtilaKbmjsS5SqlSa82lllxbhUDNuyG6CyCoKqhF7qTULgUOEAitCqsuu-Ewhs-9_OKf-8KPLzglJyCKfXd441mZPDLOZ4PsaorUxxgDm2ikRIxu7mAhhloUnNy5SjGzfhb3YwFCEa_VtKpXaZEvB1XVUqQR-bs-7vYTBlRDMTdREBdRAAA0IlK3Ws3Aq7SzObiju3OLXzZpjaiBqdq43y6OFt_4rdfH3U5qRjMCR25pTK6iqesjY0QnVQYEdURqj0EnoEBSxN05BARkRCaSFtlsWhqimkvoElJAJlEzqcRU9rm9KLWWWgvHdMWuEmEkBzd1ZnR3qeqIrQnR1jtgrbIYTYHjQIFbeQQp1LECM1IAYiBqeh9EdMBhsSqii9WqG4ZGrVueHAFSPxu6WT_MhqNr13a7ber62EVCH2bzblhSCIA2W8xin5rwhSO7WTcMMYUQY-CwODpS8-VqNe5PF_PVfr8fhp4DpW6opgcnJxi4Wla3_XYrVdf7p90wGAg5ouNUlGaLwcSkqkhtTZIitaqKmDQGoVsMVLWkPqIDUQADqRZTCgGxCottTi90rLPV8OVvfPf0nfsXD59Ylgd3nwKDXqmdwJTNcL8vXUhn5xevv_72T_-xL33pSz9JTN_69rfJ0cwosrlWEQFHAsRW5Pdps0cjrnX94MFitQohqjMqptTlPEIIVqXutoerm7mKquecHUBl0lK01Z8QTNTUCJkgNCEfAohqq3q4ORiomZoAgXslZkAH1xZlaCI6jjEF9ugpdWYq1bS6mTiQGAiAmki1fR6ZHRFdVUq5eHI2Wyz6LpH7bJ7EhCIbACCVaSIxK5kgeK1SM6GrVAKc9rnrhsDYyp9uMsQhUDDRKhLizFzQvZQsqvtddsQmOSfikEIIEd1vHR1Nuz0BiEqpVU0YEdCkaER68HS9H8uFwMnta7_y299-cP_8fJ1vHi5Afdrupu1YxxwBKVJkBISuC_MuHPPwwmzW5CtVxdkRqVTNOedaVbComYOr55yLuoIiQexCqRkYEKyKKrihAXotjSAEhFRbj8r9chy1xZ8AQoyNiSgmVh0Mx_0kVaVMm_Vo4FOpuUpWRaREwR1djYhiCNWgqM1Tf3x4uJoNkutYZTvm_VQt0D5LyRUA1XycdBJ1vKLRHR8uHQGQjo6PxCWk5MjirE67se5ERMwAjRpUD5BoO-V9ofU2O0Jg3mlVsGmquyxdShRi7DsgfnR28fBiUxWuHx-nmFxFXUutCEYEzBCJAJ0I29aeYwBANXWHGFsQH5He2zW5MyMiipirmV89QAHIHcDQ9L18kZmpIIKamZkzNiZFqxErGhOBg6h0kRG46aaqiaGpq7qIuKoCuFQxMxc3kbYbdXBzU1dmCoQhcCCKTICQTfoQRQwQvCGbG5XEXVTcMFJwUTRHsABwOJ8FphSTigfweR-Ol_3tg-Vq6BJSaLGYGBFp2acuhX4e5x0fLNI8ha79keBmV9pIB3fTJvFF4hRCCgmRQBUQzczRQggAToRVFAPlKbvTOMl5GR_tzm8vwuc-8-F__Ou_v1gehq4XBgbAEG9cv9UFRtPXvvcDcP2Jz7z86O3TH_uxD-_3slmPGGIIfOPWLc35-z84_d_8j_8H__qf-Llnj0-kVivuzghgUIAkdYxq7kBApipXbHBvhkhAMjUi5hBElQAVTNSIHdBbw-Nis4-JN7tNCzTvpUrVH717f5frH_sjnyZQUCMKqsIM2_3ODAE9T9lURQTcFSCFeHqx2Y3TZpclax_SspvFGW3Xax33Y9lIIkuBuzklTkMPaOvNDiocrI4PFrPT9TaG2cFiNU0SPXX9ihi2--nVt9_IJRdzjnjv7rvDMJ_3CwRM88U3v_NdivSH3_72bHmwE5uyFCUX7FOXR9ufXsz6rufUdzM2HCcYYpy0zqHvEgefO-gwW8UumdliNmwu124eCKhKYJ51847TrFt0KZ2fn0mxx_ceffXLr84Xs3_v3_87f_DNV-89ePIX_ty_fnLzBlY9f_j07XtvI9Pxasl9WK6Ws8XgZio1l-lgNuwu99P6su9nhLQ8mK-Ol1_-b77yE3_iF45ndP3wOHX6_TfvPj29-K2vv_bwyeVqvvrwhz607GcHi-7d---erjf_4mvfODl5xj2S1FmKj955-_N_8mdigA98-KVZl9659_bHXnnxN3_1t7qA86FbzdLRwTCfpaGPQ8cBMXU8X3XLId06WgZkEHE1bhdztVo9V91POk61ihNge3CWqZrjVUYRXc2GWUd0JUVFgPmQQH3cFnHIVdf76XSzvxinXam1qhu6wzCbqcE4VjRyMXKOIV0_OWBE9nCwWlEMaUhqNl_2ALjflX2VnNXEitRaZMxlzFNRNYHEsRTNOW-3oyqWImVf8ii79TjWAgSmhg7TWGuuReqUJ0d-8GTdz_rj43lVK2LFaTvVlGIpklWkmhlkUwUTBAhs6GZGRDFGUR2GjgIxYWLuYnCzYTb0ixkSGkDXJyJ0hTZYdbOSi6tXVQQjpJOTQ_a6nabLMhYTqXmqBYBLsRhJpEoWqeJqbDBN2VRVpZbChFrV3BrBpv2wNgaEgTuY5KnWamYcWA1L1ZS6XOtUMyA4Us2lFompd3WZpg6N0G7cWH7s5eff__wzKQU2VFNwE5cwhNB1WnAaJzAp-8yBuhQBXFWQmIhdXLQ4AwcI5OAEagDUjvuiDuCynwhQdgUBmYO7gsq03VeZzNzcp93e3UWq1MrYwvBmalIVmdrxlxmJmBCrtM-SR0YAV9EYwKyiQxnzZ770ie9_8_siBV1dJTTHmYqaVtEqBSmCti2xEbRSnDuA-pX1BYBbu1fViCiFgABAhCFylxAQDKm55MHd1aViO8q7dkRoLlOOkR2873qrFTmIa3PBEHHgdDV5qxUBDcHMUCQENh1DZECkEAkBgJoBwN1jihzY1YAgdJ1KWR4u24hptloy8RCHEMkd5sOitc-H2awWSaHjEOcHq2oiavPDo2k_WhUt4tDMzewEToSI_Wyo0xiHFCIdLG8s5rP5rJ_Pu2HoVoeLLnWpD7PV7PJyXWvlxMSwmN_kITl4Nxtc_fj4kEqpFCj2Me-zmXapb2i5ENDcraoDKFhKHQIiMkXGACrWz2bgkQiJ7Ozs_F_5-Z-hIn_wzVf3l2vDysHzVIobBIxDUjduLJosILhYHq0vtr_35a_81C_8_PPP3Kiy208TIKfUASAgmIhMGQ1AhQAwUq0ZIz29_3ZAunb9pEhuVTgpIqUCUs5Tni6Or90CsBi4na1jjFqllJFTCIwcqBYxv6q4IoUQGIlMCwcKITg4qnH7MZUSYipZiaOINVisA1y7fuOtt-67iiNS4HalFZMQueQM5pFRi5mYO1YjA0YOu92-6wcn6tJgRQJxip05dENfTaSSo4WYRM0MgLhUUWvgDc1TBgMtrqZNJS3iU9mnmEAUDGutMYVpu7Mm_VaTIq_dfacP4TPvf7FP_ZTHXEpVUTEk5i5Qosi0Isyq-21-82x9-9lrP3r8-AdvPjjblc9_9qXFMFvO-5TYAU2l74MzF7MiGhjJ8CB2iRM6l2wNmhVSMIasFQlSZHMLjIhKgczBFUJM41Tc0QGreOOTVLEqLioGIOZFVRyKmKlqFqkaCVII5NaQiA5epZpbmUrO1kiJIYTgYKrzRQ8EzpCrmtqd6wdHq-7G4YLRi-TdftpPNVdHiqaN3OxVZL-f2mhd3EvVMUue6rQ3F0-Buq5X9FHUGjqh2m5ft5OI2XZfxlLVBJhXXfroSzdvLodry6Hk8vTx-vUnF90Q9llPL6ZaoBv6VlPDgGebzTjV60cHLz57J0U-9vLLAAEAAElEQVQOjIE4BOhiaMBQudJt_ktyN7YkCwMFZEK82uATihghtttfO9u7maETk7hGZrX22nGm1IqhomoKtXgtRshdIAAEQnVn4qwO7sxNBeOACISNM0NOoXkbEU219Qfc0AFLVQrshA5Y1ZuE00xTiEYeCDly15NWJYcyWpFGAfIUKQRKgZazbtYHBosBU8cxIjN2ke5cO1wMQ_vpQNNAMB8CARLDvMNlF5ZDnKfQpcQhOACigRs6tI3x1dYEIMSAFMyBWmmMW6-46dob-QGJGEPYbMYHT05fOF6d33_0Y5_4-OGcf_j6E4faH3QySlFF4tvPXE9M3_rDH77xg4ef_uJPfOdbb37gA3dSjOvtLswSAG53p08ePbzWz_7Wv_OXbp0cdZGqCCJaIHNBVgIndCP9D_4ff3caq4CBu4iJCJjzlfgYKbAZ1lwB3eiqzAAOql7VLtbbUurhMHv05GzWd9upbPP4-MnTspc__Qs_ER1MgCgQmppUs9Ql8TpLibAh5hIyqhui1-oNFhFTmC-Wy_lwcbE5vHGTipBLQuxTSiEispu6KKkv--XsIFy_-cyT8zV03PU9BMfEABA5Pn_7zmqYO7lTEZXvvPqDNJuL-2IxPz46fvkDL3_ilQ_funXnk5_9RI-ROM7ngSNM-0tkqoDDfAFTGWazRDzVcdqXkAJ1fvrwLK5I2Y6OrsUQOg4AqO4ikysawubyEgyZ-0W3tEpoYQjdnTu3njw--1M_-8XDwf_Jf_ebv_O733zn3qO__Mu__NIzt7ebfHlxudlvhtmMgJ-7-cxzN-6sFvOAkLebD7z4_DPP3iDAx4_eWZ-vp0nf_4kPIu_-i__k_9IPJ99660cddqebKcT-yflumuqTp-dabT6fHxwdlHHT9d1iNfzO7_7O7WdvqtRZP7t5887b333jJ3_ys5snj45m_apPxwdHTx89unltuZx1HUPPfP1kZWp9n5CsC1yrHR_NUyJ3g4it8WMiu1y3U91l2WcVA0NS9TLlFJEZtRX5ATEwGIhIEXXznGupZkjFPbtXgyKei0ymeykCPkktJkJUi2yrpC5yCg64y_nGyeHhcnb9aHX75rG6jfu8n6aUoqqp-5hlvy_qpqq1qriIy2Y7rrflbLu-2O1bb0GsTjlnrVVETQChZT6rCKiDIwLXanffOr3cTsV9M5UHZ7vUdUc3jqpISmHeMQGpqZm2oicQFzE1q24IHpgQoe8TMUujtruFEFKT1lXpurBYzKb9qKbcRhVlUlA1bVp0Jy95WvBs2su-FFHdbnZTrh7A1MwsT2Waas6jGfShy6W4AYaGx7DGGSNmqdLwjVUrEueapXEuEUsRqVUBcsmIWFSquoFDQ7Expi6J5JKngOAuiPbis7eeuXndi--3I7E5WDWRnMFsPsQQKU85T1OtCg4xcYrJEJg5Mg19VPNSJIsBkYi4aeoiIYhoIkRvyqpQ1LXWkqWKlWa2UjKxAKC1tqCXmaqgVAmAxAz43rrFnJDQwdWJGMFQDR0NII-TmxMgR44pDinmSRksEMtUmIkRAxOhM6qImCvHiIhSiokQXt0CkFr2EVVqW5s7sVbl2AGiuwORA4gbkl_pUpjJAQwJicHB3FpOibApoLFVqVwpRJVWCEaVTO2_QAYkRkZiBEhMdQIwBAVXp5A4Bam1m804JqSYQhhm3eroKMYOEPtuSF1KXUxdMnOKREjzxXKadl1KIQaVsjg8qCUP_Xza7eazGRPKuF2sBillWHRdCsyUhs4NumHWz_phmNeiJ8fHqe_nyzkFZA59182HeWQ6PFjtLnds1MVA4BwicXT11CVw6LqQtzm5EoUgYuhGDlUK94MrMJKrkXtgil3vyKoFEaqJmLi6k-f9OMwCkfd93yVeXD_89lv3SynTlLGL-3ESV0Z3wFJr7DuISOyEOu33-8vT597_woP79_7jv_Uf8Kwz48PjkzJOCIjVyR0dwI0AHCAQA-K4XXerhdbp8snDELvF4QK7mQIgGCKpquRpfX4Gpin0Ut0dRFXynhi1OAEyRW_MGVSHK9-wm6NVnSY0Rw7oSEiuFmO0qinNzJS76NgSkzTM5i8-e2f9-JwwIruIMGO7Y7s5MbqT-9UaASOLSUg0btdPT89nB4uUUuy4C2xSRUoIZO5DmIlKsUIQ1d3BmRgZwKHUAoAhxVrr0MUqMpUMCOQmoqWIuptWVxs3W6JQahU1AwuRN7uaqxOAgzITYSilumMpVcyWXdqPZSIQsbHmxw8uTzf7MKSz_fijdx9_-_VHH3__s9dWB8RhMetm_UBOgbnjQOSEBu7KFgLNZ10XCRmIQQDKZEA4C2k_jpNK513PHZiKCQVgoi5GyaJZYggI0cBFFQFEfKrV0ShQdW0UHGQEt0bY7bqOORAEFWkEl9CH7TiqehYRUUeKFKXqwcFssZqvjmYHq1nHYd4N-1qmLBeXoyKaAzE1ER8SDanbbPfctj2IAkpMppZzPr_YbPZ5KhpjcIPdZrfZ5ywqDoRMqmjOroE4UXzpxZu3T1YpEndshEMX57PubCcPN3L_cv90s98Ueevds5g6ddzt6q7W4v7kYr3N9c71Y0pR0au6gzOTN7Cn6nu5RgcGbRBrN3V1M5W2omvC44YPamMO-5cyQwMXUCYS1RDDVErzBjCxqRACM7VXqJkVkVxE3Kqo2v-fqP8M1i1L7_uwJ6y19t5vOunm0DlMd8_05B5gBjOgAJAIBANIShBIkzQpWrRMW7JNW65ylctVsqv8QRJZllwuq1QSixQtlSxCNDMJEIEEiDA5dU_n23375nvim_beaz3BH9YZ-vO9deuc-56z91rP8___flCkpq58LELM1XHo4Fm1IkQNwGsihZERiWvlGH4YYVdCTCECwJiFOZjBuDWrPDwEJHR3B1O31PL-3jQQ1fcHmnVt6rqwO2uvHexN2xSJialtQmwoJU6BXSUgAnoeh8jYRCI3MD3PIGHFtQEgIpBpZZsBEtVGsLo71EKXu6nBufMXnM3wvbsfvPDc1aFfr85OLx7MaCNnj49ibOKk7fuxS5Pd3Z1u3nz04d233nrn-ZcvB8HLN28uFjvrbU8pLDdny5OTabv3V_7sn_zypz-ObiDISEwsKmAiVtTMCRKTLuHv_87XRi3mio52TiR0NTM7D1PV_1qC4OqAwMTFz_tojw6Pr108ePTwcdulVT8MOd979GAxn375Rz-huRTRogroUsQd1uttFllttpNJs-17sHNU15AlNmHbZ440m8_ALY-Cqvdv3797-wGJUT-gFDYZV8sUQuAA2UDK3s4iD_ni3s62SBPa1bBZPz4pGSgGTo2A7ezvTiezPueLi4v3P7rXNA0hbXOZdFOeTJbj-uLly0H7Sxcv7k47HAxFy2pz6eLVvUlz6_YtMI-L2V43OVseB4PHDx4-89S1h0dH167PtWz2Lu-FjjMOp2cn_ZAX-5cyx82QDx8dYdDV2emHH9yaTuLp6TERhRSuXLjwT3_jq5f2D5576vpXPvPqb_z6r_2jf_QrhfmP_tIfOzk-Grb97Qf37zy4986dD2_dv-chDGMu6h_cvVMsT3bniGDSD-N4NuY0WXzvW6_zfN5a-OqDd8XD3cfHXZo-Pl5CCJtxXOchlxJSFBv2F4vt0L_x3e9eubA724mNee7zo2WedtMim9ls4jK-9OIzh4ePJyHOZpOu6yLSYmeiojGGSZMaYHbd6Zr5okttNHRDL-aj6aBmZo6QUiKEGELXtQbEgQDREbpZC44hkqmPYylmWaQf9GS9zQZOrI7DKGZGnrxo3uacMyI-ffPK9Sv7B9PpbD5JTctNunp5X0yXy-2Dx6fH683h4UlR32zGIrY82xYRDMgImm27HQYpkzArxRxctWQZzVRMakZoKDmXks36nFVVRIeSz3eThDnnlmN_Toew9ZDPtpv37j5--PCEOYYY751sPBGH4IZq0sZUZU3qWIZcI5GztoMiaIYAZlp9OuaaYowUY-TJvGuatuvaYRyLqCOs10MxNTUmblNIqXnh408dPjx-9OgUzNabfhRxRmAEwL7oVkZEGIbxaHUGCKJWxjxmycXq_rHu8SgSMHSpdRXJZRyLmgKjajFGNQkxmJV-swV0FVEVd23ahtDKWEQEap6E4sPTzdmwPVkd_-DN799_8AAIxOThyWk_DOM4EAkRAHPWstn245ARQVTqY9YA1RQRisrQb1VUipydrFQV1EWUEBUroroIatGaUxpUTURkFFCNTK6SUjBRMyEAN4o4AYOAXIEKtXjtDmqKapyiuZladSeGwBxCM5mcHI5DLwBgoiagZg4akKQURGDmIuKBIJADAbNKDjFWZyvUF14IQICERIBIbkZEYMAOpRSDSm93MzPXrOKBHFRV3NysgEsVRJqpozCTATEFRggELiVwrPyWUoYQIiFr0fq5Nm0SVU7siFIyoFf2LIZGTc2BKCBzZb4SEyEyhxjTZD5FgtBGDri7t-tmViS0zWw-5RiRoWkmUspkMUuzKcU0mS20FGQGAAURN0BwQCPfO9hpmgYdp5PpfD5NTaNqXRPbFNoQFvM5uJAJApihe2hSkO3gBv2YD27utKkJDnWsPy22QuB-2MQulZKLFGbKWWozWAsCOsUQQjQ34mCqTQoBcXdnp98clf7sH_zON2U9hDaIqZs1MYBbKRLrhCYXZkqBci6L2fyrX_va5uxkvRq2bXSjL_3sz77-7e9gdYsiq2aO7OTgmGV0cmZSA-Rw59Z7T7_6ae66nFfOhELgxoiO0E6a9fHjbr47DFt3TSmqKlhhNKuckxBE1U1NNYQEbk5oaiGmkjNyMHcEcXEgAHcEQ2QvFkNTck-h2b9weTVskNHVUpqYbkEdgWKIFGDdLyN15uKOiFTTyLnkaZsQNFE5Wq0xhtQ0BDqsCgKoAwO2TZPHceQNIZSSmRncOSICugCYiXlhAkRmNDUi0iyxCaPWcjM44na7brvW1NgoZ-iadj3kLnEkbAIPbAwRCNyt9EViVrUdboSlDD4OW-Dm4iIY0fFy48dLK3r5YOfyhb1b9x6uhwEJBxUx4MBOKCpm2EVMGBAacW06Xq_WTWLNWqI1IZ3lHmkIwBxaLSM4qFqWUj1DViQSjmKVCFCpTGAemjSMYyAqpdT4IACaGxMXUzciwNhEURVhZBFyULMxYxXDFouR9yadBVyvBwLaDmO_FQMzQDQ0kSKKThwcEHOkJoYQg5uBmgHPm7DOpVcz4GGQHY6IOOvaVepHdQc00RAQgfIwbsWeP9ifRg6jClhZF3bsmhgm3WpbwMf7j8-Q4NL-IhflwCfrTUC4cW337sNTBV9nw75I0asX9lfLVS7CgU3MkX9oeUJVK6KBsHpJihgTiQpXhr_hOd_bWd2RgGq85nzdDEUlBmZmUeVAhtqmmEs1g4G7iYKZdl0qMqBjP-YY4zjmEIObBEcRyOTqUBcJdd5G5LXqZAqBXNSCk7sHJlVhRIrxXGNcmc3uYpoSJyRzw0gE4KqBmMAmqQnEbccmhiEh4LRL7jZNbcMBrR6BTbKomRkwU0wRCbUIcwAzEwwEHCtOGOC8Wo2uVgHoXI_-pojoroSIiMZV22JuAsgOEGN89903bl68uts2b75_66lnnzSi23ceytkqXdvP_bbzMJkvnrh6cPfdB9_8vR_sXth76bnn18O2XewAYnZfHp7ZqP-Lv_hvzdA8j4boTsgE5ERQ2aZGRIhVS8TedlL-xv_7H_4Hf_mXPI8M1Y6GFTNXRAEdmUCxGktEjBCQYNzk4_Xy0t4-R9psx27V91mXy5OLi73XXn1B1MZiAMRETGgOoBCJqiyiaUN1C4p6yaUfBIEQsYkRzVTKdr0qWs6Wvbt1TYrRS_HAsRTr2rluBgU_OTqcpKjD2HYTH8atbhxsGPutDbO2ySbJw7jZhBDUtFssjr799qSB-3dXsQs7i8XE8hvf_v7Hnr8JJPOLi8cP75grB3twd-WjfuqTP7JcPnzyiZvvvvPel77y44dnj5578UVB_K3vvnPh4oUHw9nDs-V0z1_97CfG1TOTyUKKAcEn4id35_PN2dKhfPK1l0pGivzsZuy3mQFXp1tD6Xb3vvXOnUP7B--9_naKdHS0_Ze_9XtPPHPze9_59tlZ_9pXfnS93KTJ9N6d24TcH58g86jqDov9C75ny-OzfjvsX72Z84d_67_8v__hP_5vv_O7H2zny1nXvXX7gxvXrjxeri_u7-Y8RqSu6S7s7hKRs7395gfz2fzJ5176-Auf_bu__N_-yi__vT_xR_7Qo7t3wPBgf9rNn3j_w9svPPN8K0Pb0naQ1oI37o4xRACfNd1k2jRM9Qo9ivbr0SITIROp6ViyG1CAUoxUVX5YKjpfXqM6ELGYZLFcshoWMcBKVodA0UwkqwTtMP7IJ54X8TLkTENs43I5zGatiw85j3k0xs12RPQh55SCuRHzdhiLgQFQRCy0WQ0lnhJRzjmLiBRVCzFWSS0CFZHAUU2zIgFVkI64ooGoE0g_DEcnZ6lpvAgjIGAp2jRUVBy8DCWGIKBglkJQUTFtp03O2k66SZPaaQK0Uqy3MmSZzSY1sJ4CQcMOcHpyttjpQgxlHCvEL0Yskh05tAEoehnmLcls2si4OuvdVFS8h2zFRAcRFSVQMFV1V3YzYAQ3QAcir6R8YldPnCgwgBd1BBu3I0d1ACml6xqqU3oEkMKBXI2bgIjbfmyaUI0vzXzB7ndu3z99SF_65Memi9353k4p4kgf3P1Qw8LI1AyDowEKjjlHpGKmog5aadqG6GAqUnJxExU9Olyqm5vnnK0oxaR5mE6mZ2fL2c7U1NCAk5cyqgqRl6xELGMmhqJD1YKIbbWIklIM4GJen6jo7qXoJDWq5m5oYAiMHNs4PN6GyDFiHrRumwHMFTAyAbiasbioEzowJayneCjStA0AuirROdPd1ZHYzciJYyxlIKLAtN0Mk_kEADiGsi1uzkTO4FZCCpqLg6uYo4UYzLCIEhO4sLuZcNOVMhKhGQKT5kwpmWRAKrnEbqJSDBBMmYOYcUqAniJL1tnerrmnthHp2_lksdg1tDHn2WLn9Oi45DJfLPr11symO3OiuF4vN5vN_oUD5jAMfdO2gB6w4RCMxv5ExTW1XRvDfHc6DhsEXMxnATmPw85sIkVTahlaRGi7iYw5de32bD0OxYCAYBRfbt-fpyfbmKIKEzM284P9gG6ANI5LoArjBnNFIisaAhk4YGxbNNHUpLHvOThy4BgRvekmNmyOTo__nb_y54fVWVxtRjcjlH5MiJ7FA3AIGCMz5b4AhXXfh4DXrh-88zfeURnEkRUJcTMu9_Z3tusNhziWvk0JycaxBGYnCiEiEZgC4LDtN-vVhf39j5YrYq7BDxMHwDJkQBw2yyY2ZdyOpk2a9nnNCF6KuoYUI3N9pxIgEngxACySE0cHJUZXRSCvxkvzlNhcUkghTcGhbdt33n4bnEvOCR3F1AEsc4iIsWsWOQ-EXO-IYy5tbFLT9Nse2Rd7i8OHq82ml5BSO0PYqipyXGuJCBzIVEEd3EouFAMAlVJiCEUzxwRe0e-IkUouTWw0l9S1o44NRhXJAE61ScardY9T_v6tDz_73DOvvPDcd958P5Gm2XS13iA4IZ314wh-6cLO_G7cBC1moP3dE9ts-jZScXi47A_Xw83LBy_cuNy16aMHh-XRsUcd-0zElDhXtbFhcEJwB5t1XZ_VI2zH3IRmGjCX0QKoKiNrznWFti25C8lECkuKcTsM5GiIbUiAmMfMhGORyu90AHF18BDCsC1xkpAYkJDc1Ip4EZ2ksFlnipBFOMadlJbbvM3CCCIjAKpDxaQOQ0EHChAYpm0bAhcpjJzHQgiirgRHyzW4q0qgYLm4aGyiI13Yma3UVqseRBAopbQa7KUnLha09ajbPAbz_Z3OKRyfbgexbt5cv7h779EyMD0-Xc67CQXuN0NvtjuW1KRtr4P75nA9bQkQd5vuKK-2Qzaw4EjVAiWVcY92XhUGRHTUqq-qE38Bq5YuN6x1YVFDBCQSMwZyAwOvyAJGGLOo-ejSUGBmMwUmKdmsjvODFDN3KSXE4A4EYCrnmg7m6rOuA_W6ghjrOB3dDVQVEYsZETlALsUNzQ2rfAvJ3UWNEYGxorenk7aJUc2biJNZIKBhk8mBKTRMAVC8rkKckMw9pUAYmAwQEawKP5ggMlerYt3eOjvW5QkgAFVb2jn83zGLcQghIAOJORKbOTqsVpuMvHsw16w26u6V2aj-n_yXfx_EqKXtZgyhvXrjytG9x_ffv3Pt5oWbTz5hMcx40UYe-_7WB7f_2M9-5YsvPh1crCic99qdyL0oxKAqjggGRLVPZSFiE8MPvv-DEGPf9-oVqctm4GgARiFIKaqAEcGREB0wb8dR7O6DR1_61CfPjjcFJAU6Xp5c2Nv9xPNPuZuKF7HA_kNDiQ1i4q7qMYUmRHcNGDhoaJPhxq00gRxcpcjo6zxkzXv7O4f3HkLXOKEFtsRilqEYoRsMm00zTQV0xDFbJo4Pjo4P79x96oWPuUrxspHNejl64BDD3rX94f5hGWEcRgJfxc24Xu9e3jfpwPT5F5_bHh3iJHDiH__5p4ftg0hz1-03v_31be6L8um9O753Ia_OsJ34qH_rv_47m6OlZ5vE8ODDWwCAnilORpGiwkbEmJeDAe9e2B2KzqezvYsHOY-PHi13Lswcbf2d0xS6cRgWXTeUMW_Kzt6lUu69_u3vT-dzy7p_4eKwWTLBZr2imIpIVp_P51efeOLs8YN-e9LOm_64nD0--8rnP3vn8OHFabf3xI033n738u5u0_ATly-FJoHDer2JbfqxL7x28cqFH7z-wenm8e23v7N_afc733rz3_93_vKjj27NJk3DsLsz75qnv_613__S5z9rZpPF_GS91qGYSwX7zSZRtyPOJqZ5LJmAKEQObOqqGgK0HNyoVDKP-iilgiLGXlLkfihiLmIKuO1zSE1qQ-5tsx36XrauIqObDSYT5M9_8llX2WyH1aY_Ot3wZiTkpmXJueZbmEPh0m_HhNB0SYspWR7LqG6OUsQcpg0XFy1ZRE0FzMbtOLLOZ50WIQSsQbashSw10YpbsCK5qGTzObZqcLraXJlMCGy77iNy349ZIMUktX6qSAC14QPqiKZFwLyJYTbpskg7aXU7MFNWpRBGGQkg58LsimDFTk7Odi_s1gdFCCGP1HBjbmzgnhOGzfGmzxK7Ka4GAm4aKqNs1tvQNqYS3ItCyRICqxRCIAhg7ubqygDZrGkQ3Z1UTcU0AubiMUY15ZhUC51bYcBqWlEdOWguIzqSjmOZdG0z7fqsg_SxxzH4O_cffPnVl4BCCmGdZTLZWw9udW0LDoiiWbRATFmKqQJhLgUZRRQY0YEdnVGzHT06rHIUcHOA7WaN4MwynyUbRzRjZDBwAyR3cBFp2sCMLqbBiIJbqbByqwBrMxUjIlVxdEZC95pjVZHUTGMKkgcrMpl2pgpEkSiPxdXBQcWI2cU4sIq6qagTEXGQPIYQ3bWS_N2MY9AibtXOglLryYAiGRCZ3UFKzvU-YCauhQBEgFoqBk4WicBZyuDsHINJQVdzA2KxfJ41AgMV5EZLYQ5qEokRnQNjSFpyBXlTbE0VgrWTJjSx3_QAMJlN28mEuxiZUjdhoul0ypHmswUYckBEKLlQCJPpPJexbZrlmNvJpOQ-xma9PG2atl3Mtps-dR2CgVkIPF_sMlET4nK13Nudj6PMp9OBSjtNLpDFAygzISEQMFHHYdzeDCmpSzeZxLaxsZw-ehgcHAAdlZGZaehHTgGJUhvRVd1IR-ZUg_XeJlUNTBQTuBSXtonr1XKP-Kvv3yUzxlh0IAI2EvTAtOxlllopQoxgguapTdthGyKKkKs6IYCvDpeznflmvZSiASCXTA1xYlNzkTpNRCQnZw533337Uz_yxY_ev-WSc1ZHN3KOrENhwGG1nh9cMCEIXEqfYkARYsy9AlIIkdzNvZTSxgmiORg6AIaaXABkDmwmxMFU_vVfn7STyfxisd7d89inNpY8AEW1nFJSL0yI4ikER2cKwzi005lqoZjcrDjOZvOTs8103o5ZHVdV0kPgZto07baM6gaE4CSmDQZRQSZGyk65FE6h2opMPMbkqhzYZXTEXEoFIGkxsJERnYwhfO_d919-6vretHMTUB36QdVcdSiyUvvW-_devHrlxsXLb350hxF6ERiwAKbUDJtxc7qeTdpbDw7p-qV517785JVXn775tTffvienjiCqAVHdMOKYJRc1A1BoU_Ri2sSxSGQib_KYA6MXbVMYhhJSaGNQVSTq-8xNYAzOik5jX7pJIypazEgDUQDeboeUQmB2hhTZtBAEc3PF7AXUlmdbbRtiEBFk3t_vVivdbrcxBjPK4m7mBNO23Y5j18Q8Fssy2Z2aqRlkMxEbTc3gbNWnlpoUpZiqgVqIjQVejZkcwcJs0oykzbRJjIiw6MLpcpu6ht0NrIk8jNZ1sLuYPF6tVP3krH_iysFQ9OHp8uHZ0gX2F5PtyfLe_bNL-wvgIENWAkE6XW0mYTaftuvtOJaSEo2DnY_EzAnQ6iiEoCFScEcsdaIv9UDpFXZhhKoG6AQs6ugAgKLCTjEwAjCRAZrmSdMUESZ0AzUXsDJKtX0NYoysLi6W3c1Ac05NYwbmhUIABwQnjl4b8zUgByRZiAnAYwjZlAjBiNBSCGJGyCZKHFyAHM4XozEyBQffbsf5bkLjEGkya9BhPmnYGRGZDUAdAB1CCirq7DEGM8PI4E5YZTiVkwmIcF4oxHNxY9W7ADiCq7opEFPNsDqZugZkRQ8p3rv17rX9C0RUiu7vLgyD6_jr_-z3bj51MD3Y-_DDx6--ctM2Z3fevzvG8NJLT8TYpm42bFZHy5Mruwf_0V_5s5MGXbKIODABAjkjEoIjowEjgXs1wKsYqETE6Pz4_l0iRgerwlevfxUBuORCRBxc1LGGlsRS037tja_-6Gc-l5rmgzfe3dnZvX34KDh--pXndBR3DExIiKheXGufRCUgFXAGSDFIqUxsd3AVSW3qx2xgD4-PduadKo2GUsZecmz3MaErc0yTnWnJWb0ooJEVgkcnj7ZO2zyuZFxvll_9we2Pf2GrHB6vy9UXPvbGRx9JnJRh8-yzn7n62d_59Te--s2vv7WY7T-8_-H2_v3Ll29IExbz2cNbZ6v1I9u49fLR22-AWuAgKs2Et6th0tE2R6X3LSORs0E768wcOJ5uBlLcbFfUICedzvd2Jw1gmC8WH77zwXMvPf_hex_s7O--8PyrmPj1b3xjZ2fugF3TbDfjOGwPLu_udN0777x1eHxycnR04dJlCgAmoPLg3t3d-c58MgfEzWaYdq2IHx2eLvbLpSvXH927-8KPfuYbv_2vfuWf_9O_8D__S9fRTlbZyvrK1Wsf3b3_5u3HLzy_nUba3Z3OZ4uTk82dj466abp4Yf_WG29cOLjRUR_J_-4_-3s__zNf-sZXv__MzZvr1bC_d_Dg3oOjs8Nnbt40h67Z8bD70Uf359MwDv3erO1SGsZhtR1TYCEMkSOH7BIxGLq5ZzEzL-bBzBzQnejcg9EPBQMW97E4hFgAmWjT926uCIY-ltGLENmPf_ZlLvDweE1kKytrkeA-bdpxyCLmpqV2VdQgkJqTY58LRjaAkrMiihkgUIzjasSatAMyUwQ01XE9ICFGJ0QmTDFtyhiA1C0YGzihI8nQ5xgY0FerzXTWAIdRlZiGvrSTkBKJm4m4AyUubmoF3Jl4OusWs1lk6ter1LXTSSeGZTUAgIlQ4BC4GneYcRjLarluUhOIHaWddtvNhh1CQuDux7_0cejNwU0lMU1m88PDY1GBGIaxmBoHQjMAVHUdJcbgrgB1mW3q6kTqpllcTcHW_TZRY26oVH1HjChaKZRWRuVAY5-bBpjDer1mohADhaTZ-u0qkGXynUv7qmKaxz7HDoF8NpndWR1TQFUXAyAas4japu_dVVTAzRzHISNhrtYhFUYo4xaHJsYkOUcOknsHBTNHZogC49iPiQJHToFKgTpxIy5M7AQlG7gSY6X0gSsRmxszIKK7o0pgllLUDJiBAoagqquz1c6lvfXxsmYxiwinUHJx5pxL18Rx7FGEEMGdwN3d3YjZTUU8hOSupm6qtdRbtZHg6ODuxQSRI5jJmIkQVFPgnBXdAjeCUtcCIsXNCIFiVLEQiEMoWZEDUs12lxCDEyNHU49NK0MfYpJi5C4O5M4paS5ETJFcXHO5cPkSRZSSY5Oq7wHMQtuYmJtevnpxu91KyfP5ZLPZpqYZx_Xe3u56vT24tLc8PAtIRBhDkpLbptuu1_ODA-JokonjOPY7-_uxSfPFnBHiMnLkxWSyPNss5vMmBErUtvHk-LTOmgCJOYrKwcXFcr2cdJ2UHFPkhuZ7U7748msiLkWYOUZCA1EAREYCIimFA6XQICMAAJOKcEgAriJMnJqUy_Cn_uhP_u7Xvr9Z9n3OZooABM7I5p5iipMWyhhiMFM0e-aFJyLFN998nxDr7ySgnz46uXj96ma1NrWihRCBgooxIRoGjuqSJq3kzEDgdvHJqzYO2_XKxVUkMDISIIJ7YES08wCWFEYyU-b4Qy8SAVYXqLt7TI2ZuKqhETMAukoI0aQ2gSimZui3bTeTUZ5_6RNvvvX6fLF39vgsNTGPJYRYVbVFnIgpRMmlCU2tLzRdB24AyIEo0pUrlw6PjhiDm9drXBZlInMPgZBIRGKIXpn8SCk14zg6grqJamqqaMRiaEbJYKbuqWn7YQwBi9R-MHTtxEDJ0VWY8creYm93sVr1R8en2UDdwHkYCgW8fe_o4Wb1qeefWx2drvMwiIqHfqzYJMhZauV3KLI8XSZmb8Lzly4-9cTlcdOXYSSEUixSqLX8GJDA1ZwQmIODJ0YmR0euqQy0wNxvembGgA6QIrtqojCIIDgnAj3vOFJKCCClhEAxcikamQFDldo2sQkhqPuka5gYCRh5zJqaVLI9erja2-ly8VKyOoiqoY-5XGgPlv0aEfb3FhV-stwOxbDPpek6EUuJrUhV249qRCiiqQnuFggUfLVWDpAY1P10vZWsgRE5guOsjVJkzIUAVv2IiIeny-NVf3K2Ou2HgGHaRuKwGUpEo5A2RUqW2DIT92MOIWzGcWfarNebSoc0B3Ov8GZVrbGWc2gokqMDglfAJwAziSgx2TnXx6tI6LzIW4kMSGBA9TFJVESawBVzS_UlVFMxboBYNHdtIvQQwnYogTEFVrdIXP9-9ekiACBIkUAM5yBN4IAqEkJwO8dxAEHkUCGb9ctvQqxM--mkZUYdS5cCIUGt1pPNuqZNDSCYQT2nqoi5ec32nJd_vEKPYghI6OYhsNb5_zniH8AAEWvI_7wy6Chm50VmqvhZrLea9abvVefzLiE_OjyJKaTJ4vW37_3qb319cfGSgMyayXQxff_dW5sQ965eeebGjWGU7bg-XC7_wz_3J199-uYkopeCDoDsYOKKXks4ldoj4CBg_Xroulijg4PY483Z--9_-Cd__mdKzlYDxkRjLk6oZjX37wBI5wVxU33_9q3rl68eLHbGXO49Pj3eHiWIX_j8x8kr1hgA3KxUF7K5I6IxiVhWRaSL-wvtx9m0EwVT2456dT5_4717Lz1_4_W33tvZmSVuFAyJ7z8-a-YXb733vhQo0m9OTiJCMSlqs4OdT3_uteP7t7vp7v333v3CT37pB7_3Hdsc78yn7926ffv9d3_3619__7tvf_Tgw6__y996_3vfP3xw_3vf-P7qo4fre3f649O8HU9PTofTw3vvfjT2p2U15n5diagRQy55ONtoBhmzFTp5dKqDbYdxZzZvpvMQQ99vP_mVnz55-LDvB9kObRMxxr35zmc_95Pb_uTVz3zu8OSME2_Otoh244nnHj56D8DZYe_y5ZPjh2N_hnHWdt2jR4929na96KXLl95759Yzr77Ur1d97i1LnwtE5JTMwZEohhRjyWMetvsXLjy8d-_ZZ55eHh994-vf-sznP6-aj1fr1TgsUrczoQe37w55NNOzs_Xp2WrIw6Yfm8ki99vDw4c3nr7Zb1dv_uDWn_pTP89Itx892plNZrPpE09f-_rvfffTn3xpklIVbnQTtmH7wtPX2QwAx1Iq1layIGJKPGYDcHEUdatzmFqMRXK3FJgJsygBITM6FcXNdlSElunwbCDGoaialzLmYZi1s0sHB49PNsNo6zJsVrkfRkcuozhDyeII7pYV61aWOCDVyh6quTmIQS65qGYpIqXkomamCgpaimcFhyEXDmzkxQsSlbFkyabKTOZmYOhAABRYi5jadGdXy5jzgEwq1m8LBpxPJwiQUnICd0UiJMfIly8fNCmalNQkN8-i5ogIpc-uqqrmmgKv130WadpYsqloEymkaKjOoGPe21v81E98KhYfM_ai41hEbdsPY5HtOKpkV5eSZVQxN1d3UjImCMQOVvONXok0AOQuIoFD1gIEJm6mxARWb2gK5poLoKspVxuaOaAhYDedTHamue-3qw2DOZKoHB0ffvFzn2RgIKDUEKd3Hz0-2wzLZT8WNfG8HYLDkDOEenj2QCR9qbtklQwEWkpMTS7addNhu2XCklVda1RGVR3cKzgRzVQ5JJFSv7VKhUYiMIsUzBy0Uv2cmXIvsQlq6gbVKGnqHDkPOtvfkTxulptrz18HwOMHjxFBTaFuNpHq2pMdzMRMK5rpHG8HFpi0aB2gVAaoi5kqIQWOuRQiREQ1Dxzc1U0Jo4uch2KhEkIZHIgZTAngXOqlVtVSsWl1FERHq-nuJEXqpJaZ1d3RaqwOmZADICIhEFJqQoztdD7bWWyW63Y-7ybddNKh4f7lPQ7UxKgik2m3Xm8QKERcLBY5l1KkmzSb9ZhCGIbMAGUYQ4olF0QqZhQ5cIiJQ0rT2Tyl1E2axWK2Wa2nk-l0Z0qEO4sZkzcxPTo6JYrL9TIQOeA4ZnXr85gmXUyhjENIMaXYtG2iwPOnPw0UOPAw5JCCqoSGHd0FpjvTYcwUgoo0betEteHHMWrO7aRFlwA2nXZf_uLn_9U3v7PZlmHMFFjGDKJAzAmBIoCRG7qB6zAML7_y0v2HR2MerbiZ1q12WfcXn3n69PHDohY5aNbYdVIKmRARMpqPgHT9xrX18VEILApNN3v86CEFjkxugIAhtppzTClvhradSJF6dydkFUEOUoQAQ0gOXlMh1V5R9RK1zmgi6IgBKz8kTadDvw0R226WdewmjZsimhQhVUJKTQsA7tXgWiV7rqoUOKSIjuAWI3fzdtI2w7jNxUoRJnf3EJqhDBCx3-QYo2ohgEApywjqiBBCUlVCYMahHwEQQxAtzEiAYsIhhsAlDzGm-j1CcKZGJccYCXG1PXrp6Wd25tPX3_8oxHS63ppDM4njIGnS3rv_eH86u3Z97_b9h4okQA5echFzCABEQ9EiOKLdOzq6_WD55JX5pJs8eWXv2tW99-487FLkyA5AgQgxxAiIuS4ZA2t9BJKJeEiUs5lr6poiFmJEIhFz1yYScnB3UCRCEwkxqggIMKGZEXOIoYi4WkiVYgf1vyUwJ-Y-j4Ak5uCw2ow7i5ZjKEVzVd-Bb4ds6lvtUyQENoeT1fas32Liot6EBOCMhASM2IQoYqNqiByI-6GoaJ8FQ7BgQ5-HMfdF1A0CAIKqgdlOkziQmvVShiEfn2xTm2Ztd7buN2N2gEebTT8KEWzVmeg0Z3eHbGMubYjOQc12Zx0hnq57ABczA1cxQATEIoqExQyo4m2ckIo5YN28EhOpGTogIRKJCiGYGyLV1AgjESMQAAABKnhgzKXCfdDNAwZRA8BiBQlDIBUfRWsDx8zwnEcE54xAAA4EXuWb4O4GYG7oHgKbWVFDhBBYilR1euQI6Mwsom0bq-u6Xk32dqYAGENoYmialFIDhkRIhO5WgTgA6IbgTlQFB-hmMUREgBpgqvR_JndQ0XqZUa32alMzVa3XAyJGQmK0sXBI9bZw59Gj-XynaUJ0Lq7Tpmvn8__oP_mbq_XIXReayC0cna3OBrl28_qlSxf7YdsX--kf-dy_-8f-YGPZoJhCtXk5ortwYFePxEhUyRPqbg5t265WGxFV8Cx25vkbv__NnenimeeeFlEnd6sfpLsTgBs4WB2jWhnLvcNHqvL0zScHEQP-5htvT2Z7r33yxQgMDhQiBShjcQACQMTAQUDNYVukmLch7e5MUTU1TT-OgrY62Szm7e9__c2PvXD9vTffu7y_T02bc8GUvvvd9-YHl26_94GVoiXLuDYpHJgC7V-_aar_8vd_5dGtB4cnR9_47d959523jg9P3r9968GDBw8_vFN0lOUKiPqjk-mkHTbbJsTVekOA29WSDHWQhmIepOk6dYeQpODelRvDsJ7uzp949tn9g4tXnnjy5Y9_8sf_wr9567tv_hv_7v9kXK4uPvX8577y5SZ1n_sDX77zzrvLs7My5Ol8enS4VLI4QaQwqhydnu3s7B0-evzg_kPk0DRtUQWzMOmIo3qYL6ZiauTo1Be5fOnKg3v3A5sDO1POZbG3Jw5Fx9ikmmcLKRDY-mxVht6RVqvt9ZeeXi1P33797R957TOnx8csSIkJMMSw2JkNqzUCBKL1uh_7QWTsZjMcT8JkeuPmlccPHt07uv-Tf-CndFxtN2sGvXRxb__i_u__7tc__9pnmhRd7dqFvSu7U0aaNB0AhBBqVoQZHMEcR9HinrMWNTErYgYQOKoZn1PCxJHFnIh78dXQn20GBDrux7FIVhNRU3dVdJgt5llsM5RRRcXrINlVvViMKQSMxEORPIoWMXOvTCoAUy_VuKRiCMMwBA7DMBBRdZVrUa8pEwQDY2YxF6tNVClawAwR1QS8FvCoPl0dzGRkJjc309Sk1DZlyIFj10RFWJ1uYgqgnpq4WCymTSTHGAnd1WFUWa76oc_D0CNyLqUuM7OKFAcAySWk4O5DP0xni_nerGsnn_70q7YSpnTc94q2Xg8QaFgOzJAlD0ORnAOl2q81VQCU4pGwXr5NBByYaluH3FWyptjkLI6gquGHG7oQk9WasuoP8QjIzGpCFABgsTvLmzKMY20rmaurTCfpZ7_yZSnyrdffuHrlIgCsxrza9pv1MAxZq35HXFSLqWQVUVADBlRVEVcDgLpyDDExYik5ACuYI4AZAxC6qZWcHZxDVBWtm0R3hsrjB3dBA3ANAI7wQ_CCERMzj2OWOoFwEFEkDBwDI5RBx_LUiy91k3a9XI99b6qIhHaecjUphBhCKEWIyQFqdznFqKVApaQgiSlC_S_GShwCqrMpEimB2K2AuZoSMYG7i9ZbGaK6AZJqqR8CEImU2MQy5JSim54vMSriIkRTASYXbed7pe9jDODgbtw0roZAsetS27nbfGe3nTWBcXd_ZzqbTmcz5jCfTysZFgF39haxCcxMhPNuvh02HAIRTheLw0fHO3s7pqrmnKKbi0kz7dyMEGNKxDidTAF0d2dx9cJeydJNmuligo5dakyFAk_ns-XyjGMiDtt-k9rOzJzIS2l3dhFVhryzv9s2cT6f8uzpT3FkcDOxpm1KX5jRDJgjIKpVfip0bVekAJiqprZVL8whBk9d-tIXP_7y09d-57e-LwBFrOQixWJkDIwhlFGbxWTY9G5FpHSTdnm2vfnMk3fvPRiHofbywIzR250FAm5XS3Bo2nYch0BsktVcTFWkjEqX5-Ojk2J5u9zOdg-2m5WV4gCWxypfcBU1YaYiOTQNIKgKmCHXUp27GofgBloKAlRuILgTsxWjyiqtwFNE1XMxp0h5_pVXP3z_bTeYzhbbfuvAnjWEoOLMwVQwhBBCkZxSIybEbPUEU7ucFD72wjO3P7pfj5ohRECcpDYgQzYkR9JIqR8yJQQFYgwcimRECiFY1sgBkUfJk0k3jsJMKsaBE8Y6laEmuJqrq4mbAyEHymLPXb_Whti7Pl5upFjW4gBDnx2AWd97_6OPv_yxUsrxticK5q5Zcx7FDVMohuqwXvXqYcT-d998dDBr0TGF9uPXrl7dvxCQslmkmptSAA6RY2QE1KIV3YXgBFWWhybGSGoA7hTAEaQe2gDBLQRGrj-Njg5jKTFGA3N3rk4TrtVPM_BSFNCHMXepQ6TVpk8J2jYq0nrTK57XZxUwBIqJXH3SToAcCMUsxIDIgHV9CSESI1X-7qRts4qYj6UAgJwfO6Hfju429KMZuLoZEAJKySIWCZF30kJVigqFkEWJcDqdXrkwX2-Gschqsx3UxuypDTPEdZFRTQxmXdiMqiopwjRwzlKLs1Xu-8PHEJEDnhtGGADAnevzztHrcRHRAPT8JAzgAFDhoYaEgB7O9Rc45kzI9f4QIldLjpsTopNzDCDuYMTn_7KZqwkhEUIRdcfIDJXgxAzgjKDuwGh-vl5gosrVMbfAXMeESHUf67Xwhm6RyN2aFGMbJrMJR4xITQx4fgJwNQNwDlxHPnWFx4TuTsyBqSLnKmj4nC70Q5MPEKi41dXED7W_hI7IDsBV347nF4az1XYwm3TtLIXj01XTtqFtxr7_6__5L6dJN93ZKQTTdnJ8eHZ598LsYCdL_9mnn_lf_uk_cXPRug9mBk7gLlYIEOgc7U9EKtXLhnW0VpmVZ2dnzXQ-jmW97qnX3_jNf_Xo-Oxnf_YnSs6B2ByKSHXD4bknIDiYKSw363ePTj753ItOwYyO18vX337_F37uy54lhcAcvII-zFy0OiLcax0CV_3g6lcu7Gspl3Z3V2NebYcHq9VGZT6ZfOPWOx975sm7hyfdpF0Vy1my43qzIeCH9-6vT7dStv1mGULbLbpxO16-enWxN53iTl73m82wPj29dOlqaXH_yZuvffLV3RvXr928sYX4k3_q3-pJ7987_pm_9AvPffxzn_78x09Pzm6-8PEv_MRPvfDqp_7on_tfzW9c2ECybkrdrAh2V_e3y35-cPBzf_YX92a7N158tul2Ht15sM12cOXg3oPH1598ggL367O9WXpw52G_XrXcfvLjP3Pr3R_EKb3w6svLVY8x5mxZJLv2Z9-7fO3lUYbl-nT3wgFGPDk---DDf3Hx2suR4PT0ZH5xf3u6RISd3dl8Pre-Xy5XOuTtaqtmDTd5k_NmtGyr0zNXiExEvj3bUjPbLLc3n356PDt5_c03L166uZWxBZ_MIxPeufcwRiqDEmBo4qRpi2i_Hbpm2qTpzWeevfb8tTe--t0Xnnvl0s5eiohAB_PFc09d26w3681weXcvJjaxJsY8CpDXzxFrqpGoaB1vexYlJEdwR3DcbocQqWkSV7wvEAbeDoVCPOvH9TDGFMxx2_cqvu6zO9UNW6RQTV6bfuyHMval0scjEQQa-jEyH682eZRhHAFAiuQshKSmm2EchtHAAakynEtRM0PHinMAQq3YfjhnbjmCqeZSUgwA5ur1plw18uaQc0EiFR1LmU5nIWAKUQ3Gkts2RmYwY6b5zuSJa5eWp9vpdMKEqb4pAlbeVBE9XW1LHoko55La2MSo7tu-d7fUNMScc-YQJI8EdPnK7tMXdvenEzM7PD7bjOMw5iHn7XpbTLSYjOri4ziqyvliU81EakhCRdV8zEUU7Hx1WeqzK6Xo4OjAxKXPjgBo6GaqJlb5igCeYjQVU4spVpWUiDCxqhUrHOJkNm1T-NKnXinFf--b33r6yRtNascxHz4-BGqWq83R6aZIKVrs_OSkVgpRGDcDIJZcHBwQTU3ME3PTTM7OlqKGSLkMYy5NSjJmg6p8BEcDMyce84AE_9q6q2ZFBNyN0MCkKDPnsaQmmIO64A8dlxwDOsQmbVfbJpCqXHnm6be--yZbGVYDUKU1IAdGJJeCRMwskgkxhMbNwI3_NX4agSiICDIg8jn7Gh0ZtUi9A5goEkAphK6auWnAANERkTmUUjgFFXFzcaPYWB4JvbIxmMhVgbD-sxwDUqhzYm4CEZVcUopmGNoWAMCNAxPRZD6fzab92M8Wi-vXbgQOk_msnbSEGEIEt_nOYhwGDhHcu8nk9OxszHJw5WIeSi7GDVVnPUVWc0CSksGBOAbGSTdFxJTC7v7ehcV8yBnMUhNDSIE5RW676Xo7EHEuJWfhxG7eb8Zu2jIQBiZwcNvZWbQxkHvLzPvPfwZrLJURwGIKDkAhymhd16IDE2nW0IT6WZoqI2CkyNQ2YRjk3_ulX4hE3_rB2ydnW1EZi1T7TlV5oYfJfLpZb9A0BG5ns8M7jz__4z_69vd_AGZSspuZgboN6-3Oxctnx6eqakVMNMRgJiKO5E0KY1_SosknG2dKgYe8bZq25NFFQpMcUFU4BJHiSKHOC93cFAAjsxQBJLCqCkdAUPPzH3ADigxQ2edgVhd57gCcEJGk6HRn9vjBQySeTRfbIbsDuBUx4hCamPsBOWjl-YsiU4hsSFqknTSIrqqfe-3V9974cHd_jhykjKUooDWm026y7sdcnUTMoOcTk5BijW8yBwICM1M9P7swAUIgrsMDAjIEMEQGRpZSHKCIUEoBiRBvXjqIIZ5sxkFKEdManyvixhFtlPHTzz_z-MFjA1AFEcljwcCbbRn6koBVxUHVYDrlrdg7dw_fv_3wvdW9Z69eu7y3ePXG5YPdedfEBw9PLux0MYYmMhExcZGMTFY3ZmrM5BiIKcS2zk7caKxEVlVTJ2KrdEjVaoQIRDXAUEUtHAM4qhnVG7oaOsU2xogE0MQEwDlncxDRsYgZIHOiyBSm05YQEGE7DkMpTAgAJWtWyUVGkWE7MkckXm3WZhAY95oEHEZ1AByH7KrsERAAIWB0J8lKjBwZAVT9eHW2Lnk5DBS47k-6GAaxLD6dNjHEGLA778zhbNKdrAdAPxtK0wURdYdFlyZNs9z2NfCDgd0csbKLUcWByOqcpr5v1Op7pj7b3OqPLdajP1N9XCKAxxhKkRjZtUoKQc0AwEUDs5rnouddLrHUUmSuoTlTJwQFCyG4uoNHZner9aEK18tFHQkcyKpSz8kZHIjAwZsQiJiJ3SuaHJmQmWIIbRtT4MDUphbVmKibNG2IhIT1UgI1wg5EjHjuLvZ6qUAiqIJGo3qhcKxd5POIH4BqnVQ51JsMWKheSsQYyQ2IU4VGf_DR_elssjObA-HR4-MLewsP8evffvuf_8a30s4UOu8mk9LnzWC7872f-Oxr_-Ev_sKnnrxaysZZQQmh1q2diYkJa5K_3sMIGevKwoxqc5rf_OADBj6YT1LbUtP-43_wq5jsj_38Txfx-ooF8PpSMzFwVHIpPoq9-f4HX_n0x00YE2Ls_r9_99f-0p_5Wc-YUkQm0wKIYA5iDXMgJmBA7_uxm3QPD08HG69c2l-v-7ZrnWM_bAjwIjM0yIM0O-1-1236HGN7ujybzxbHJ2d9Pz68-3iz7EUGNHGT-YWLw_Jk7-DybD5__933Xn31cx_eunPl0rWf-zO_-NqnvvDyy89f3n_i4uWLh8f9_aNHP_HTP92v-tXZ6id-6sut8Msvf-wbv_fNz3_pS4vp5Gy7efToo-9--82P7t5TzTUzNt3ZccgHN688__Tzw9inpj1-dNSk9uDq9XfevbW3WMz2diepe3z06OLu_rtvvqvqHDvas7OTk_3Ll68-e_3w8eF02pweLyfz5p033rBtEyaz0Da29naSHHmy2Dk55st78_ne7I1v31rMp6uj9e07t6btTFU_-SM_dvGpm--_9dZsOr129fLla5cnTXr5k6_AhF3FVVdn69wPk9kETFIMx_eO0nSS83Dv7oO_-Ee_OI7mxv_ml1774PFJ7teTyXyUHJA__OijmLridnpy8sHbtzbHR7vtPDTdP_g7__Bn_uBPBdbtZthN6Ww9XLt8-Xe--p0nbl5tAztYXm-L6nYcDGndD2oAhKPYMMig5gJEZBWGYcrEXdfmorO2ycWZ0BxDiKfrYVskiwcMQLRcbh0xm6nCkDMh50FDjNtlD0CiIqZ5GHMuFIKYO0AWKVKy2lhKvc_nMVNKhppHIcQQkrqZWi4iVmf34OBiQsTugEDExJERoertEKAMUgdADsZIoYYDEUUkRgZ1oHpoo535zAwcPDFPp5NxGAFt0jXtZHq63KYYxMTF6rNFijIHURcpmzGLKDONRWJqHLBIGYfsNeaREoENZUwpbpeb6zeuTAZf9xtq4-PD03HMWX07yNlpLwClFFMBh81mawDs5IDnslHwsQgwaykVCumuOWckcrNKR0B3NWNHFQV3MOMYpBSgWglEd5MsQERIJo6IIYYQAxJKKQpGxKHhRYc__rnPbPrx29_7AUe8cf3anOiDO3ceHy6PV-vT1SaPA4BZdk5sbkQEroGoyAjVwAjkrttN3zSdIWzXWyRvmjgMo6sGbrJkV0NkLVqPjnWRKjWKWe9vroRu7gZag_opxTyObdOYO5iBGgGqWiAiCg6I4g6l3-TnP__J----W7YbdecmSlZCdK-yZjU1JAqBh34MVQ1g525hgqpGtcBUbc3EBABuCmaBg5uDG3FEMKiSZkSvhTc3N7c6iUIGMHCoSwwECCmqKAcC1ZjaOoExP7dpMHNtd4ArMYMZhaiqQHyeI428u7s_25trGfcPLrbTJjKnGJomIuE4DCHQfDFr23Z5tuQYFjuzMZdA3KXYzSb1KwOzJsZ51zlCHnLiMOm61KSSZb6zYMbJtJvNJtPppIxD28T9vV2KQdUmTSqSxT33Y53_WtEUyMyhfnlIIYYmxaZJbdfEwOjOsyc-4Qqpa90KExFgLpmIYgx18gfgOZdJNylgMXBgpsBMiMVuPHGdEP_4z31xuxxu3b5_dLY9W2-dUFTbFBQACZGjBcib3kWqe4IYeJJabI-OjpgCEZaSQ9PKsN2_fC33WymZKQCDjCMHVlN3q_OzyMnFp5f226bpV6vF3gWqBlInN6hWcDdTFVXhQCHEOozAOszkKi7ykJKqGhgSV-1z3QMgkamCU6V2q0oIkZj3Lh2AaNac-76dTovq2A8GHhCdommZ7uzkYUghmAoREREQqShTYCJA7ybNF7_wsW9_882i0I-ZCANjkexOxmgIgSkylT5zLUsQQg12OBq4m5giMp5rHNGZSIvGFM2tiV3RkmIkZBMIMbhpTMldXYd-2L767NMphLdvP9wMfSletIhZoKiigWi1Onvi-s2D6c4Hj0_GUbZ5QETCBOI-KKJWxr84ivFmkNV22Ix5s_FHm_7NRw8X853Zort4MHvlicsHu_vX5rsZZNoFAA8xaU0w1OcdOAXKVkQKGiBxTbKGxIjQcBK3JhARmjmih8AcyF0RsG0SKAB6jGSOWsTdY0zujsGbNlVxH7Gvl5lCcEQ1B4YmMiPWkbOJDEW2Q3GHvs9FdVAF4pLLejXWkck4FoCw3m4NaVDoh1yZm-PYpxCM0cyJGNCCg4ONpl3XIeCQc5bS9zmluOlLP2YCWvd935fYRGCKnMChJXy42vZDfnS6Yfe2CQZe69-qNgzDYtbO5zFnQ0Yirs-oUjfL4BUOxAB2vsxEAEcmMyNANasH5xiCuJMDEasZBQqEgQOBSQ3JBwJHQAuJRDSLpsSA0EYu5kTojkMW8DrURwNvY8hF3Y0CImIMwcDrnwKiVxuc1zkBurujOyozM6OIcMAajSAmcItEqQlISEiBHEzZnQhmTUIDIEcCK_WND4hUQzAO4GYhxfMqbb0IIZyf9-sOHSrHAc5_q8HR8dwPXxvB7rGpyjCkEMDgwfGRuV7YnZXNaEhm3rYxq_xf_59_-3STYXdqEncX7cmj9ScvXf8__Plf_NLnXgAZNCJ7AHNDM1DxwoSB2A0UDMwBEX7YWxA1A6_RDY7hH_-T3_ov_qu_-fLzL9J0Bo3_f_6bv7de5ZsvPHtwsC-SA7KqMgVzVAMBRYMi_v7t-9evX17MdkYv-weL3_qdb924sf_Uk09ShRuqAmqg6O6IGAMjcoW3ZpVm2o1D7ihc2Fs0gboQxm0OyH_77__z3_7WN_7O3_vNK5fnb795S2z82rfeuPPRrU89-_yv_9bv3Xzy2oP7j_M237vzMEIp22Jm05RkyAeXrkfGqweXr1-7-O57t_f25mfLs0995hN70_D1779-48LlOx_84PDO6c__1Offf-f9u5vjL7726urx6mACb995-LmPf1y0HJ2crMX6Id-7_3g2m0SOFBt1lX584dXn5qlFLzuL2enRcjKZbD0_uPdo58qFFBpEGYbNYmd-5_ZdMjOE6c705PHp7GCxf_Hmw0ePIjXvv3s7heZsubr54nM3X3rxws606drLF6_uHOymgO-89d5ib37l4qXV8ckTz7-QEj_7_HO7872sI3lJzIdnZ6Hjd9-_c-etdzjgvfc_OLp76KJlHPcOdhhJct6slvPpJCa-8eSV7cNTHYff-cGd117-WC_923ePEH22uxDwSZqMucwW84Bpf2__-vUbFy7tRbBVL3_-3_4T3_ja7xrSzRvX3XCjuT87o9Q9_9yVf_w__N1nPvXCeqvMmBHKUFbb0ZCzuLoNxUQMELMKMdZTCjPXPLOpDSXXhSEgDVlWm6EXccNBdCwlhiBqIgaOOQsiABMyIlEpYx4KMeQisWmKmqOPOZthVbQaQjm_lLN6Hei7K5pYUROXeWhX28GKBiKtVwGHYRx-WMNDVzUR4lBd3MxQiohIN2nVHAGpmsjBVIW7NGxHphDaTkqRkhnZwbQMbP7Sc8-u15vl6bJpYik5cTAtTUwqbmhNin2RYjCWghQQmSIiwlh0m4e2aUMMoEroRJ6aplf_yuc-MW62SrTe5k0_iFoR32y2Trbdju4wjtkpIACo5HEsRao2gSOpuau4GoLV8JQTxBgreB4JVHUcshOqKXqtJykwUm1uFAVwDOzuIURwR4YxF6JYSnETBXeVEPgTzz374hPXP_zw7ru3P_rat9748mc_3QRA9dsPHx1vtkNRBHLzrAKm4EgIoxR3E9EiGEMAcDcDh7ahPGSRAtWOZJqHEdDMpLalkZSJsLZuAcBdXREx1B1CziEEYpJSzAyDuRhHFiki4moVzIznFz93KwiaXZ98-ubtt9-NTEWM0F0Uwevhhyq9wYFrT0I1hEa0uHkIQVXqzxFzAyZW0_zuiMjIcJ5_E3dDZiL2HyarAkdzNTjPgmB9P40lRq5b9JiiVFejOcWA9SMARMDAQUuhGANTbJOMhZgREVIw9W424xC66eTS1Uub9XJ3f-_g4sFk0sUU5rNp0wU0KGPZPdjNY4a6D2xbLVLtrA7cb4d2Mhn7PPQjMoamXa1XDlAJMYPI_sX9Mo4McLC_s7-_ywwEsLczYUSmKFnclQMjoIqIuqNzoC41q1WfB8VEMRAHnnRtDAHULMukjbx4-lWqbQk1DCHGiEiugIAiCoiiGphC4jKUEBGdOTCnhODbbQ-Bf_yLn24w3jo8_fDDe9wEV2CwNnApmhKrWh6HvB2arkWH1DSG_oPvvvnqj33-3gcfGBg5mSi4OShRRJRtP5hXJaa1XWMVPq5g7ojOTcqbbb_eMvP69GT_ypXl6owoxthIyegQYrBS6iHSVUPT1IMdRHa1ECOAExEgOQI5ububhSZVs3CIQYZMIdSTTUhtv91evnHj8f0H1cijWqaL_fVqlZoICrGJIh4CM5FKBTC6ubfzqbrFFGOgYdQmxUsXLp4tT0WAEN00cMwi3XQy5sxAknPTtmomxThEESmjdk2jYgBu7qVOPRVDCiUr87l4Sd0NNISoZrnkENgBiVlF3CyFIKCfe-mFSYrfeveDbT-UYoagxYtqzQwo6IPD40998mO3jh6uzpa5mJipC6qgKwYGI0AixCY2omXT98VRznHHeLLtP7p_1E4np9vx2sX5bNo8c_3ClQv7Ny_tf_6py59-7uZnX3jy4Mr84d27L7385C_9wc_-2CdeSjO8c_dhE5OTNynmoojcMgGgi1nxEAmIAOrlD1MIjLWiJObGHBDBSkHyrknrk-286yrGcXnWc0BAEvVV7ndm00ihHjDFbZtLMVOrLm008UAhaylZuWEz1FKLaL4dh6YN7pVJBCWbA4CCA9YbmYrHyBzYIpITOg5jQaJJm9aroZt1IYQsYg6xa_ptNnFqKBKV7EYACItZNPFhLAgQIxsomkzatBdbHXFUAzc1Q6wnHHBAB1P3iJQIHOjcxuV4fuO3c-W5ulGNmNbHaGD-4QIQwR2ACFTMXLFm-g0IKQZEQFUzAyQSVymFmABhO-SIjERqCu6JoxoYorlJ7Q0AnOuzVWPg2lIwt8BUJRUEJGJ8LrgkBAhM6I6IWiwQNW0Eswv7syaE-vh2A_U6DSRAJERmAjdmJj-3QyAhEf1ru5i7q6mKmnstBZh7igGZA9ZBDTFiSITgKh45AoGrv_nBnYO93dmkG_synXUupW3bO_c--u__zm-PsXni6Sfu3T25efPy524--7__939pfycZsym6sThAcIDzbFI8f984OtbBExHWN1Adm1n9mgCmi71_9qu_9s9_9fcfr6c3P_bi7_zOb65Wq1_9je_-wp_8SQbkCuxDFrdRVcVPTre_-_oHX3j55mK6t8kaOKzO-l__p7_3Z__cz8hQmAOYink_agyBGZsmREaK1MTggdbr_oP7D7dgmNKtD-99dPfeu48Or-zt_u3f_I1_7xd-_hPPvfgjL7_4B3_ySyeH65_5Q195_qkbr376VQO6cf3K4dHZW299RJP24cPjpoFxk4G9iWHM4_6FS9eu3Tzrl_fu3G2n0y__xI-fHp987JnnE-vh2eZgZ-fkePXPH7z7J1577f4H91c9f_4zz5-dHD-xv3_70eNXX3zuZHU2DLru_Qdvvrd7cQdZQfM49ESiffnJn_zi5d3ZNDTItnq8BPYfvPHem99_-7Uf_XTpl44eGJ64cuHWu-8vT7eGNt1p79-5P9tfgOGNq5cuXbrw6MN7r37iEy7y1I0nSx4e3fmorMds9uT-bki0v3fx8pPXzk6H_fnuwZVL77z55qNHj9969z3Q-Oj48OjRkoliO7l8-dLOYmcsoyp2s3a-2F1vRsm5XSyGXAYREz18vMxbuXTtsgHkOw9gZ_7M09fH1enHnnxy1sZpO43JTjdnZ-vVtAuMuixnt-7eeny6vPnsjUL0B3_u07_2m9955XMv497OqNvp4vJ8flnVv7cZnv30J-7duTe_dHXaTSaxoyaeLdfgwIFK1spWNHU1jUgUGAHNcRgzAEgF8oqo-8lytdwO1DVjX0St7UIpJuLFFIAEtLo31a2IllJyyW7QDyMwpcjbPleCpCsA8XbIbkDEClaPa-hoqg4gamO2UUopEojd3FWy6DD0WPPaDvU3tJ4mq2w8hlC0EAVTB3MVM1UmcIDSGwUOITio5KFtJ5EYScnh-uUrP_LZj-9N0lDGs_WZiBXVpm03m-1k2jn4ph_EIauv-xEBUwwi7uZF1URiEwOzmSH6MA6piamNL7_8dFREIO5weTZkKf12RDMn3G621JCMkouK5BCDq2YpSk5EamruImJmauIExbQ-EF0VAVUFahy4mqXUieqjoj57Y4Xxn_eX6nPM1dVANbSNm-YhC1g76WKwj9288tyTN776re8-OFqvtsvrl_eeuHxpMZm-efve2elJVh_6rGA5jwAuBjHGXIqCaXEpil7yqE2b8pi7STNsR0B3MSDarFcxMLqpZKJA9Wwsjshiel6rrTAYQARH8BCCialaYCqlMCCnmPuh0pdj4KKCIYiYibuJWUmL-eWLFx7cvitZ1IEQ64oBEAgBEV2EkAORmZgoh-hgUBkV4ERuZoBWESwBSVURnAlcCnIFVHh9J5jreQIUUd3NDc2ZWIogI0J1lpmbInMFCrnXfQNi7WQAABHUEnCR1HVlHGPbqDilRMzT2bSo7h_sX3_y-tnx8Y3r12aL2bRLk7axkiMxM4TzuCpxEzWPjAGZxHS6mK23_cGlS5uz05xzSHGxvzg8PMql7OwsYgylWExpZ28-bZsmxYOD_Z1ZO2z63b1FpKpyp1wKunOKp8vtetVzE81d3I-Pl5PJZDJrgWA-m6no_v5uSjyZtl0TmCCkpivnpk9S0Uycc0khBvZioGox8jCU7nxKGd0VCM0EEPIwLGbdf_Ff__L_-n_6p3_yi5_72u9_O7VdvxkmKciY2ZzVtmO2CGnWMVgWGbfFDToKWKybzPOwUSvEJKIBYH14uHP1YgyrbOAGqYsqwkiCDiDILFnSYicP29gkGTI6DENPxMN2xZzIUcax6Rom0jJSjOZY_RfqRk4C5khupZTCTQciRUrXtWNRV-UQLLsbAoObY2REACptN4kxIBMgueZhtb5081kAKKJdSkCMJEVyExIAiIxYq-LqAZgQzY0YOfp7t-5evngxTbofvHFbpYiPgankrYkTeYyhDGNMkRgAlUodGJQaJKDIMOQiGQDZIkdGwnNcfdOYuaoAeC45BEQnDi24u9I4FErp0fHxM1cu7c8nj46Xkt3YCYNoKW5a3NWLrlzL9eneMSzVesmWXbsQGLiMQwgpEBtq0jGrYgiGmB2Plv18MXfIEfWbb39wdrh962D_Sy8_MY_datv__uvvdySbbY_tdHD58T_wY0e37_2j33rrx77wyh965WOfuXrzr_03_6Tr0gjUxKiqyIiuFAAMyICoAh6dEAMGAm8TqaFkBRdwiDFY0Qx5sdOKCDEOoxh6apoxFwC8tJgnZA-02Y5MPuaihsRY4Zh9n4m8H_IoGhpmA6uTqiwh8nwyQYWxHx0QEdV1LDlMJ8A29sIIyDyqMEdwAPZRioOruaK3ixbQ-0HdzBx8LBVErWc9OOztz7uQXPzxySqcy2lR1d1scBjNV6oh2EHXKIbV1vNQzh9AYAZ0dX86Z3twlkvRei5Wt8CUc04cAP__eQCEukRCBHc1rOdyR1WNgQmgWoHPWwauOSszO0KKbOheIKV2lIyAs65FB3VnYiSqDjEkHLc5xuDgprWEAJxCRfcYKTHPQrMRKaKJYkAMAdANEZoUGACJEjFHr2H_xWwSgGujzlQ5YC3n1AAPx5pux2pHQECqfWj16uzg-htq4IguioTgtXoCVeBu5khA_MMfqoBOBGr3j8-AoZs0JhIiiZoYLAv8D7_ye3ePTy8_eSPDUDL8qS_-2GuvPtNEVo1eDIAMsriQG7iT1x0-mJuDEwE5IIFXw1ZlWIATsJgQ-bUnL1y_uP_h7cN__D_-d__k139lt4Htpl8sum9-452v_OhLq7NtO02GttmO620-G4bj0_4PfP65lNrT5SZ1cTpt_rP__H_8S3_xj-gAARFJC0KKEGOj7kPWstmc5pHURvUUIgW4ceXi-7fvH-wePPPqtS7o6nTwMsYeexecpRktvPSP7p22EFbrsSNNDOv1apYac-kooGdwDCmggxSKGLSMs7Z9WApkHYp7yd0kSb-aLNqzfml5PwDehDl2nKbN7sS2x8OF6SRg2Nvfk2G8d_jwB-_ePd2W-cF8s1wN6-X-vJu1zbg6y6M-eenJ7ebICobA62H15g9ufXT_6N_40o9-_7vf8dXw9CvP_8U__MfevHd_ajTEEGPcHq59KNtHm_cO3_vF_-3_7r__5f8WQD94591b733w4KMPB-Gr1_YvHuxMJ-nRo8P7Z4cJ22-_9ZaLhLa9icO1Z24UxGtNdNWOmmQ-5nEzji6w2o7T2WLSdeDoXi5fuTxddNnLYn8eAcXGOGnLSPfe-2j3lRvLB_e_9S9-82u_9Zunjw-nk2jZCZ0AxSwxidn5Wccxb_u3f-P3JrOuFFP03_on_0hEBkQBv7QzGR6dQWz_1v_lP4YAR8ebC9f2beepX_ubf63rpm4qYrXoj-4cagiUTQDAtkMpIoyYYqwRQSKO3ACUs7MteR1IgyMAAygxoY8gJi3Hs02v6FmVmXPN93Oprbg81GiaIYBkRcJAsRQlsJFt3ky3PpBBJcw4ISAMeWAKWQoQhRTIccgDcwSkIhndHUsVdRQDJwjV0K42ikynU3c1gNCwA7iW2sozK2nS7jbd577wcshWZFjn3DTp0qWLh49Pi7iLxRjHvu8mkyYkcHA1yBpSRMIYLedR1AEJxLhjFAU3y7mbdY2Ha9MFEh-tN6xojACo5shehowhlr6MpQCTiwNYbNsu8NDnvF27umqxokT4Q1Ufo0PCIKIOFmJSkXMsQwiSe-bAMeZ-IIKSUU1ElGPMuVR3HgK5SmyafjuEgE6Iphxwu179-GufIYHvff97Jc29ia-_9fYXX3mpS_iFF196-60PYRykiLqhYhYRQERvKG1LD-jMdSupKjmmgMgipeuarGOWwiE4OqhjCGrGSJZlFO2aFsEdnTnU-bmIVKZOKQJmjABgKQQZy1gGIKg3VZHCgUvJyNFNXUvO481nXhj77IhmGLooY44c3ESLxUimQuYA9QvHmiIzVWZGR3UAJEBDoFI_DgBkdFVzBKYshUL0PAZC5FBGJT73wYcUYFRAVy0hRFMDM2B0QAps4LFth80qBHZ3wAgu1W3salhhzERacmrbkjW2iTkUVVO9dPXCjetX3cve7uLg4u6km4bAkZya2I9l6MvVq_ta7LQf-22ezWcly_HJWTef5qFMuta11IDuzu7-arOezCczXKyWZ7PZZGfaIodhu91d7EU2Bt-sNovF5NKFXclyttwW0flsMg7D0PdEvtib9EOeziabTT_bmQSgInnSJillOm0TowjOZt246aEI7zz9qTRpZSgcmGIkAGQUAcDKSdU0bbRIO0miFmKITShFayNip5skcjfcmc3bxexr33n9bLl1BzUvosBExGqgbrGJZSghkBmAY5PCnbu3X_nkq4_u3D8_fkAx9RDDZDJbr9cGHoBr61HGkWKwUvvI1X5qmjWlCGjb9fLC1evLo2NmahjVvYhERhGHWm1gdlNwaKrFzTTGqOrEAAhQi4_VF1pblYSqGlIqY8EQzP3K9euxSw_vPXQkk4LE3XTe91sDwEr0thoVQ2Q2d2QvpSBBDAEMUxMRYLaYPH54MhQ9WW6ffeW55elxNNrf2dn2GcmHzYDoDsSAFGMZxtoS3vYbIxCDpm1zzpx4GCUwq0kt5hMEMWUKIqXOMxzBDR2AidEdA8cmXtxbPHFw4fHZ6ta9x0gI7O6Yc6lxEQHg4Ej44hNXf_DeXXGHch6qblKT3dVcFBwgEGQ1QApMhBAIXWU7DNtxKOKzaZgkurQbpymZyTfe-WDVbwen49VwtrX3bj84HuTOo_WdR8dq49Ub1z_78rP_4luvR2cxiQQqSjGWIpWdZqXEGGqkgxgBIaZQhRuGyinWmmtMgYmrK1FUQ-QalekmKWAwhfUwqIOIqXjJrmYla-CQNYvqNksIZEX7TfFz_JoB4GLaNhjGoqpWZTOKZgq14kZMTgjIiARSPVsORmYkWv1UuM0lBgbAPAoCOiAxtm3oh0LA00jTkIrBaGNANiMke_mZC31v0wYjY5cYxAxQVdDQCXenfGnWRPSzdVnlUod2hDWYqCEGcENEIK_YezNDwBiDqqYUEFzEHLzKRxTczAMFO2_GcwWGUIilroMrv8EtxuAO5xJmRnQSM2YuxcCNiIkR4HyAhEQiGii4QeRkCFp7GokCoul5rCu18RxS7t403Kawvzebt22IfM6wBDc1BECm-otZ85dEVBNBUKdneM5GreBPK6UWe8_rwgiB2X_o9UZ0YIiBARHEiCMQqMOdu_f2FpP5bJY3m5ASMI6DPNiu_x__1d8DiLPUfvb6M__x_-ZPP__kpaYl0WjFrBIX0Q2M4dxwRuh4Tr1DJERDIgzn6X-vFCA0cIehH9W8u3Lt_ccfNBudz_iv_tW_9Ou_8rt7F-ef-fkfe3w3b6FMr-59-9u3crYy4oXd2Ree2utCeLzJDsBt-uv_2X_3ua-89PTTT8s4vnP3wXsny0ePzh48Pru_XIFZ04TLu4srO9Mru7PLO7NL00nTTFxwXWRvd0eBQeRoO7bt5N7x4xefeyoYbWSYxub2w6NXXnn6G996Pau8e_vDf_irv__Mk9ffu3sfUnxw9z4z9Os-xbAdxoDooX3plRcOl8eAMCLvX5xz8OWmf-npa-_eufPk9UsPh7Nbp49_6kde2_Sb7x2efepjT20225vXLr1_-6NPfeGLX__Wd-7cf7C3v2_g02kHWk6OjprUPPvxl08eH7322jnlsG3m_-q33z48PPrr_9Ff-zt__-_vdNNXXn4RDL76ja_evvWBuKzXZx89PNqs1gPiaruZdt3dRx8-fnw8m01DE69cufbsi88988KzF55-Yn9v1xr-4P5HR1td9asLVy9fvLB35eq1NEmz-YVJ2-3MdvN6mE66bSnLs02321nJ8ws7aT7pNavZ2cmpdnb6-PHjj27f_s533n3jzfvv3_7g29-_--bbNm7GR4-HoYz9IMMQFdpJ28YUUxNSbKeRAJu2aUPDgds2uJQmYCwILjaqDgVVuuyN2njag-Sz9Tjdn85xeuP6M3_mF__48RvvvvDCjb2D3bEYApZBEIFD8FpbZHL3UmTZDyr1aQAOWNSr-6mYr_JgBowIDiJW3NRcHAjx9HQ161p1H4fR1HKx2ovr-zHFRoqIaCmS-zwWMTMDC4HGXABMDSlS1mqTLUggRc4ZvGbVrXnuKvzX1SMzAKTAKiV1LQCoqqtgXY8RuFmKSdUq5d1UiLBtw2zavPYjrzy1t-duovLw4cnhySqEgIGb2WS73YIZh9BNW3PPWbNYFhWRXAQpiCgROYIjUC01iRCjDvqxF5--cflyIFtvtmfDVg3N3MxErR9LP2ZoUFzKIGCOYFJURSInMhVVNCdHM0O1c4ejAaKLkmQBdMBzGMMw5q5r1Qyp6mzZ0EHB3cysprZUlAKP49i1DRIxU60ZMKOqLCbtH_kDXy7r9a_9q9_1ZsItdJF_7JOf8FHF5NmXn_n6996RsYhaYAbAkpXcUbDkggigFXGOUomLYCoixbCWyVRM1MyASLK2XSdlyGUVw2Qc-hADGJScTRXM63ePga0o1iEQgLmKKGBNn5mKUQgYWMQiAUlGguvXnjg8urc6XUVmYq6Jf1dDpCqYJI6VTc8hiCqnKEWIKNZCMLi5hxjdFNDBgZjUTN2QQwUlxxDNXN2adiI5t7ETEfrhQtrNY9O4V7SdU4h1RQMOkRnraS6wq3BdSRCGlEwEI7vThSvX-_WKY1LT2DacwsH-has3Lt967_ZTTzx56dIFImwDTttkqmraTjrJpWTNAqJKgYb1Fplj4BBiHgYiCpHJabPZXr1-eejzdrW6cOly32-bSUeEO7tz1fzkjRsGemFvJxFNusZEpSiiovsw5nHQH7ouKY_jzmKhuQDYZNISUDft9hdzBzSX48en3STGmEIdEIYmAOKka4ZtBkRBQYpZSprOwMUc1L2-SrU41VX81jSaevd_-j__B3_t__b_-quv_eVZ2yyX22xmqrFJJ8vNrDEiYseawKXIVs32GHRz8uTTT_zga9_OQBWSk22knK2U6XR6fHIcKLqoMxaxpg3uQE0ANRmzlDFwLOOAgC7GqQN1VRNHDqxZHQkJVI0Z0IQBtYgnIGQ1NYAQsIwZufqnlTmKFK_UvRCYmAhjCtP5RBydoBSJMSrUJIZypKZp-m3PMTAn021gBiJ3AHJw77omj7lJXc4ltlHEIifhcnq6whC__rvfDWh5HE-2OTVhNp82ix0oufTZVMmcKKoJADSxNXdgkzK0qREtqYkOFojLMHTdxEQIkcCIgokHDuYeU3QDAqLolAIGvHP8iMNLMcSuS6PBWMSLxBgrVD7E4DB-63uv_9hrryJIYsJJYypjr0Y9UAC3ADAOIypzSkDqCrWWmrWkwAKYVUPb7Cf66lsfffmTk2lqP__Kk9_74K5ikn419H1Irbk_97Hrj-8-_M3vvHd_3X_-Y8__hZ_7yt_4p7_dcRizhhBALcQQApoqAeVzUhO7W8nAgRGBI0QOMZKLqUNkWizmq-UyBGb3MpbUpAiEYqKyGcTQAfm8hoCuZgQwDL2ZSXF2jEi9KiYycnAnsWKw2hIxYhMAoRBCseBsaoPmqm9rms7ABYRU133uZpGJ3S1CGIcSmAPyOIqDd12LSKb6-Gh7sDdlwnsPzmbTJjUxNbQI01JGFY1h8uHD5SzEXGwxSXksALBejY7qTjvT7qAFB9z0pc9jzlB7cwoG4IGZACpQExEjkTkyooO7WUACcAJqYiiqxCiixGwgjs6AGEMpgoTEtekUxjETkZg0MSCSeJWKETtCxdfVthYiI6mZZmvbgEAOmLOmSEjYBMxjTiECGYiElECBGdHcxxI5iEqIkQNOmmbWTBjcRVMbtKhnAyZza4gMfpirU6-AZzUBRABXUUJEJFUFJORATK6GAWsyipFqU0BKadrIkSpFzowgkGZ7eHTYl_LU_kXZbrnpgA0x3H3nw3_0g9eHZb50-Zn_9P_4P3vm2gWlou5eGEoxNQwOARFCAKsxVSSmyip1czd2hgjkoG7uruZmBmbKPuYyAojCJ55_fu-XfnFqs1__7d-9fefBzs5kebb8J7_8z372p38uH8nZyZ1Z7Hbmk9lkcjBrj62sNkNoG93kN9568_qzT37h45_-F__sa9efuvzUtcXH9qbTdhLUzMyA64VI1LObqxXRnLUft5uxTCMC2YRxEzhFzWChoeV2cJOsYqDLk_XW5Ond_fUm_-Gf-kLqJvOdmSiheUht06Q07UY5i23bb3No8ej0bO_g4GxYCfF0Mnnr9r0vfP4T5E033TVNzzQXuvnurJs1aw--e3p8O2nSPjz46MNx9f_j6U-jNdnO-z7sGfZQVe90ph7vfC-mi5EABIAgSIoQLJMiRYmaB0eUIjmy4uUsxbIieykrtuU4XsmSrShLYyzZURxRIikqMi2KFGeCIglQBEEQ08W9wB177j59pneoqr2fIR_qIP2hP5wPZ_V6-5yqvZ_n___9xquz5SLObD2en5_MjC22THz_1ltXrx9c2Zt95auvZPQ7O3v-XVc-9OGnf_vlX_7-7_3E0ZUjGfsHtx7S4jlFXL2nC6kN871-3C5W89IP4HJxcnr86NFy79p2fVEExer2fH3j6GC72V2cDk8-_exNBAVwdRlluz0fT84uTk-Hi01oG3QYBh23uxQIUcehR7YqQJP0h4OjGxBHYkiLNrirUjeOErvZ7nwnCDGEFBqLOm6KmADFZt4wwenDk_f-O99y5wtfbQ5X24vzcOXatbe9-0__-39qteh0rAXGf_Fjv3AUdbvb_uAP_uHXXzv9xEfeO0A9uLI_9tXF_uif_KM__D_843d_5AO7-8eDCzIC-jBWQqKIw1jdoKoy8HkZcpNT5AkN4ICiFlMYHg4hhhTJDR2wVt2Oo6mJmLofby8iR-JAACaiiC7GIYxTPF8EzMHBATiEcRjXNhDidAbqx3HK_AFiHUrKuQxDGUZgiszT_aSKMEAVMzUOQavQZbuHyljQwKpWvDRJUUIjC8xMONQaAyPaKHJwsMgjVjOqvlmvN-tNyKnfDoPa3vW91XbBzPvLToay7aWyjiZAiAHH7aiATFxKma7uqc0mgxk88fS157_t2u58bNvm7OT0YujPNmM3MyTqa_XIdWdiboOZwcQJFHUpBRHHfltrNXdkqmWYys0uzk1wMzVwNG7IagUFQjSRyFzLyACMqGKARszqiu5SZAL3OqGLBY5ilgA9IiABGENkw2__1g-Z-EuvvqHEKbSD1oP9fTfnGG0ob3_XtZQAvADQqIJADEAIQiWmAAjF1cQDspgB2rDtXUHNMfgUh0kpjrsRTSIHHUdwj9hpHYjAq4pN5UnUKtlCVcUJTGuuUilEMLNaJ1Kn4zfxdFVdANBK31f0J5-88Y1f-AqJK0xYiIn36gSGGCEGcAWckBMIgdUsRDZV1Qo4cZHd1S5LVuhkyEQyEV1gwmFz4NCPA2IFwrH0xFzHGmKUcUAmkRpiLEMFQpm62qJOADGaCAFqrRgimATiyUWPTOjIsdkOfWxbQAgUU4xN0167eXPWdTduXnnymauLthk2u_15N1vEB3dHJprNW6R0tt7uLVM_jMNmG5tmd77OOZValovl2Wbd5qaUOp_Ndts-cJzNF0O_Wa5WRDyKNE2T5p2TNzntr1p09Krknti7pjtbb1Nud2Utpeac1erefHa2Ps8xlgqmsFgux2HMOY2jUExxj1OMjCHkptmebdIiS6kDcZObfuwjo5YS2kZK6VaNDOpmIbCpeUSKREpNS_cenv83_9kf-gt_4b_Y77ovf-O17_q93_ZD__CnOFDOsVRBB1Qbq1IOUjU2SV1FnRw4UOT88M69m88_9earb8YU6lgYyVW3J2ft_h441lojAUxNYkA3cJkEZWgTZcicYuCGTh_eb1ezsR9V1C81XzodHLWIAMUUnaRqRSatBWtlDsxcpaTUuEqMqUp1N5gml02WKkQ8my9SO3vzrTdns8bAIydlAdfder3cm0sVA4nYADEQqUiIARUdHUM26EsZHVhFpu6-OZdxh4aqtR8kzZqxjE4wPj7vx_rsMzfbnE5OzgVUwYhJh0oAOUWIcRx2ixwDNts6jHUIzUzFCvYcgxmEAIbexliqJkIUBUQ3dSMpEpYNORCzSCUCq96kMJhEx1FUARgghLAeSwqRDVRqX9yDE7kUB6oIUWEbQ6zqZaghkrois4l1OQ7iTI7k2o9fP99gHf_Z7V_9o9_3be-4eePieHhQxqHrTi6OQR2QcTcaslu4e-_kN_qvvO_F5_5X3_ud__znPruc591YkCnG4ABlrIGAwJEjgMfIRjb5bcZeF11oOJjB8miOBGM_zGetgtWC80VnDjJoVVeFqu4EibAfCzqqChBv-9JEjJwH3QXiKhpSQGQ1VZOUEzHthoEphMgxEJhVk6FUA2xSypxTonGopg6ZzQ0bXm9K02ZEFBOKZOJalGPIIZhA0ZGJD_YXm20_6_JsmTcXwxLibCouYRxBG8ZhK7O9fLwZMGICALPZPIYY54GnPsRmqCdDNSMHB0ZXd3NHdWC9bN_a5fEcnAkDR1Wd4vPqCuoI5nI5L48UTGQ6s6ZICgCK6EagjAgIMQQmcnMXTSm4QaDLo7aaEnjkEIl6qTEGVUL36saRHN1Uq6GRT9-NQoiI7V5kw0AkZioS2sAOXYxHq3mODKrEwdwQEUOsWglBVNHBCHzi0SGJChJMhB8zM0JzA0JDBQMGCjnU0QEMGDHgZI5PTbi0g1XxQBDYHDZn53Ucn7hyaErM7IwEvC3y3_6jn_mOT734X_2l_-B7vusjCjrq6BpBzdWRKUXCCOoTu8p9-uTMIEzUU2NEBEFAnpblhARkWgHw-PgEgWJsmf3lr3wZU1wd7l3Y7sHnv_ap3_Pv_vD_9GOv_9ZX3_ln_vjY19Vqzo5EwE0sojuxvOyw6hdfee2lB4___O_7nU2Tft_v-SgSiIqOOlghY0NgghQIwd1tQtVWwI3Kw-2wXM1LCKQ6VDUpbrFFcqeWiEKDyEezdPfR8TMHixTsfe98-vbte_dPt3vzxVsPjvM8mzknxoCl1NlyVoYtQRsph9R1OC4pvXj1yd_43CsPXn9w-_ajs2fOhtMRq9-9dUdG89Ccnd3rL9b_-tc_f-f2va-9eevqarbuOgnyjnc8_eb9zNU-dPMDsW1my-75J67ffvCwzV0z664-Of_43qwacEhGUKteXKyLQynDuj8_1zKcnV_cfn272fU6nJ-dlrNedx4itemNfjg5P9-RyugC_xZlEHKCBjbnZ7WOTUpaBRytqhMFg6ydqSHwcpGtCsYWKw1WFl1DRJyDjTaMttw7cEon91-PIaS22T46z4vZ5vwcgZt2-dzv-zNw93OPb9_5wIffk4Bns7mz337lG-__3hvbs82DWye_4yMfmJ_Ln_zzf7B1XjaMtTa5vbY64hz_47_8x0ebl82uXR2OUe88eMBNFOGAdu_k4Xd8z6d-7Te_8I7nXogCfSkhECO5T2NQNDfE4KBNCGo-WUTcsYqraYzpyetXHzw-6UepWmJuQgqhapEC5rlJQxlq8WlpSSHudrvADO61mtM0vQf9Zg47xEAxRGZOvD3pU2bky_eymJEKMYUQxlJBDQjMXdXc3BA4spQCjFVqiElrNVVQDUxSBDNNvDJMiooOEGIgRkQF02euP6nVnJ0YKmBo25zCer3rh-qPzpeLZdvm0o-lWNNmNbcQ1o_P-75SjLtd3-bGwbeb3axraq0R-R3vfQ4VNueaEvcyFoT1rifHnGLEsN0NpWoZFBxcPRCLje4opap4CKAuY9VJbO-EUoQAzF360uSFSz8BTCbbl4qlGKcZqLkjMACIKLiaYUACBncvo-S2ocRQZQI8oINNlmOmAMO3veddoPZvfuOz8_nCI9StLWb7k94lxfSLn_6NLpM7cKRxEHRLKUoZBTyHrFoYedQa2IkxxjDsNlNi0QRUCyFoVWY0VVCxyxM8AHjmIOCmigAuCmql1sDBLnVa5n5poGOAiKDgdRgxJKuVYx77nhtysphmj7cXNo7siMS1CkZmcCVwNUADN2fCEKoqT0xrNZ9s7-jTDN_MVY2IxrFwoERkBohgqiEkEy1lDCkRsZsioF-ySwEZQwplLAikUJGIOLoMaD4Nq00FCR3QzWJKogbMCDh5mcRsvlyOZQRCR9w_PAL2brHYP1qdr8-uHB0u5rNVN192qQ67AHm5v4h9re5ahQMTAKiPaiHFdp7AockZHEuVJnvTdpO-xkxySu5h1jaO5AUODvbrbtvluN91iYO7K2FdDw4-1ioKu9IzTVYJRSKdDDCRkFPiYFJWy5lUCZHLWHKTVKrUGkwldw2hW0RkKqaqHlKiyOaCSGWspkacZvO9_uKMmMipmc_X5-u_94__0x_5-78wm8295f_xf_qX_4__-3_4o__op0CwqJnZommYtXGlmI1w7EeOjMzuVlU55Z__Vz__p__DP3vvjds-8SKxhqYZxpIQYo5lN2JIAJ5yg-App3EsMUf0qfhHkwqX4PJHgi8NPOzmSJNVgiCST1-ecIXMSGCmMUZzAEeRwshmEmIq4xjaJFKa2MKlf9f7Rw9RysVpH2JGYDUn9_XF-mp7bdpXjmPfzGd17HNutEqKUUyAIBCFEFTMzRx0s95SCEBkUsAJETfnu27WjrthvuzA7c5rt594-saVG9cfPThmAnMkpsBsaFjVpfY0tnGZg4mWqoWRFCxz6MuoFQSoCYmQ3AxziBQQ3FRziq7ScESG9XqrYuMoKO6G0_h2goQ7sGMoox4cLDb3j8FBRgUFQ1AB0Nq0ud_tmnbmqBSzmnmp4m4iIUCTGqvyqFQSywTg8Kuff-mT3_bB9z7_5PD6W2_tjpGhiIip3jlGp1KqA6zPjzG3z16_8ie-55Of_dLX37x3nAK4U6ljxwFRDWMxf_L5qyRYtsPgIOPYLtouJ3eYz1ozCRByiuJKBk1KdaxGCOyjahXDAKo6iIooTNgYt8isVYEHAlYwFcPqyMIhIGF1t0HAXGzsB4-UiAFjaHPabcYUGyvFmF00xaAqgEGrpiYNtYTAITK4b8cSkNDZVay6kxlALR5TONts57M8n7XbYQfWzmYBOGrxk-3FfNGernfzJp1f9MF5PZRnbxx4tXUVd0CA7U7kMs2CrkZTGBIIAQCdkd0VHVSUCAlRVSbVraiau6jGyR1gIKqBpwatE4E5MAISiQk6ENIUMq4mbpJT0knQiZdPRqkKRFU1JBb1mAiJTG0cStdmALdihISBwHTe5TrWtuFFl6VYR1TUBncmnLX5sG0SO7rYdGgVVzEHSFNfH8jRp_bzVK29NHqYTn7cWkTBYwxhmhWYuxpHciMEACBDhzjJgR0hACMSq7lWPb642NubWXWmZOwmFpn-7t__p9_6sRf_gx_8I1BIWcwJlREFgzt4mEikDDLaMNaxjhyDu1Wpjmqm41DORZdkOysIHHNMoYmuWx03570OCmCPhkdnj89fuLJ4x7PPCKYvfPprjx_d_T_-rf_Lj_6__9n68fZxuTjau_LwbHfn5OKObT509PQ8csocHNb9drGa_-Xv-ShTSIBOMCmEmMzUWb06RmYFUwNxB0IErF45pkfn589dvaq7spp3kX07SIjdrZNbaJGQ1f3rb926c3p-PA4fe_G9jx493NuH5288c-vub3z4ne96-eWfPsjt45PTq_urHGK8KtV00ebmoHnw8N623169fvPKzUPufJf8rZPTj7_7uQf3j99549pH3_d2HfDK0ZX__Z9-z52Hb774_PP379_9no99cGjaKwf7FfzhxWZzurmyf-X48elBl19-41X14dU3FmcPjh_cebzbnB2fnicou2EbOXZNJ6W429CXnKMDlqG6K07FIXIA1GrzxaK6JAyz2Tw0XRXZbc-Xq8N21j4-XVN1kxy45ZjaRW73lsUktXsxh4tHZ8NWrjx1bZC-v3e8Orze10eRhWZNGYY8by2XHBLkgBQO5-8c-m2epys3bnCi9eu3A1O1Rt783N5Bu56tFnm_XWRANIKrL7zj-gff_vP_3__lxrufu3_78bd-4tvb0KWYQ2rIHMAI5GCjg84ChPls1rldPDpjscwBdYKqg0V88vrN127dtrE8_9Qzm3E9FR1NHAEnxo6YI5E5AaHY1HUBLwyIbYoxpFJq349j1ZQzmKKDuckow24kDrudxhzBgIhKKe4UAmiVKcM2YewJAhEyOKL3u4ECmjs7m-vU9CWDYSiX3XczE48xOlW_5K94TAkITabyjjGgIzk7t9ndVDzGCGYUcgooouTYLbqjpssIm80mprDZ2VCrqELB7TCmnFbdYlfGk-22yRkBCIwR2CzgZSg2IPX9NqYu56y1UojL_XnpSxSEht357PHF4LLZDBzTTF1lSEj3zk8Yo1QzxDpWRlbtJ-78ejM4QRVzNy-VmUNwHSuQO5LYiJMOhNymuCIhgHMAMwVHESFEjlykugHFwIZmFgjAbNyOBJhi66IcyEAb5wR289rRYRu1jmdjn5sVIp3dP333U08BIla5-_j4l37usxejWS2BiQD63a5JGQjHTe-N5RAVHcCqqonZrKuiAZy-eUIuRZoQxyoitc2dmvf90ORkIk6T3NdAnRAm65arEJK6YiDZDZDaKVctYkDEMaoZAKlqTORS0eHqzetvvPINQjZTNOEQ3JxSqEMBdUVkJrVLfYuDu0tKnYi4mYiGGM0KE5oKUYi5qbWMtVy6exFNigMhokhxAwxTtXc6CNJYKiNQDAhgJj5dXNwZUUU5Jwc1gRApRnb05dWj3cWFqacQu_293M2P799rmkUVye1MwDimqzdudF3T9_6B9789erBaDlaz2gR12237g6t7295u3344W8xCYCCkEClyqqmM0uU8VskpxhDJrG3y3Xv3Z9281rFtmjY3xeRgttfvNi3xvGmX807HQjFEgqEfHWmz3uUuj-ZSJU4QauCh3yH4BDVquwyMTUyI9OjkbLmc9_1mMZ_PlimYAudYxpFjnLTPIZCph0CAOA7SdLO0l8ENrMausTJQDvcf3fk__yc_-D_-9f_l9Vv3967vqwFaL8WfvHp0695DMYTIl2sa9Ags7NyQi00L8hhJxRZtbAMe7h-cbM5SbDCaqkHA7emWkVOKUowYOJCUARlDJC0Smkv1BiEikJQxJJ3tL8_7R0SEbkQIZuCYYx5GmxoDMQR1B_fAEc201pgaj1FrUdcQAxNxDGMpOUSpJaRcq4jr5uI0MMuoGFy0EhGo7C7W8MQTQA6IJjbsdm7KxAQ4FUl9moSYIWMVB5BxGGezmU1tTAoYPSCaiQPtdoUAUpMe3X-4Ojq8efP67bt3UN0ISxk9MLnGmMs4xjC4VWZyRwqpSqmjTLdzNOuHvmkyADuigxMCh5DbbCDP3bheqt26_0ikpBj6YeSQdkPJuRFRRgiBD44OHp5uVnurfLG7OD5DZFFLMQ7jOnCq45iaTq0igBZEZ3ePEUspIsFs2N-f17FCoOLezPPX7z568Xi93zU3Dw8ersc0k9PTs4tx7Issu7YX3lYlp9duPdoM8tF3P_v93_l-GOUrbz6oVR48fNQynp2vIYX50f6uFgS8cv1ov0uv3ntcwPpRQWyLIlUdxhwo50wATFQA3KFW6UtFQyeTYkisZkU1MJWxNCEC0rguIZJUbXNTVHNMDt6PJSYQ1eBExKLVax8xs4VlbOOcpY5OuKuFiFzFxJUEGU0dEVXUzcvE4w9YhgGbhMSmLuCJQj_08zYDYDVJXdiWwiXszQMmrA6nm22XEgIGihFtf9XtNn2IMMvUJn68rcWdmaTahF9wgKrGCDYBN8jRbWKeRsaqzpcULyYCr8aXoGUghBQIiNW0x80cFjYBjkEJA6K1mYc6hkDgbhRFhAhCiIqGCCZARFWFiDhiKESIauYOoEZApZSco6mZOydU0eg4bwKoz5omuBJTkzk2oeGYc7RqEGkK9BBiYDIHAmCKE7dhwnzidIxHYIYqbm4iZggqnuOlyTlMkftLvhe6ubsHYGKeDAVEwQis1JOT86Zt2tx6RA4sQ0kcf-gXf_Wv_MU_kZsFiwtJKYguVVVNN8O47cepYQymY1ED4hRYrNaKWphhb94e7rfPBIjuFIAdHUnRENygw2sHagHNBtOWybi5f_L4J__1L3_i29_7Iz90-84b2-_-3b_rlz77S3_tP_lvfuRf_JOMx0fzxccaCZioiav5rJjhnfr8t7zohTmykpO6grm6A05OZUQQqQ7o5iLT1ssyx3mAF29eeXLvwJjawE746N7ZcGjXaVhw7pLbqGONTy-v1CTdLNs6lE35zNd--6kbTzw63X7jjQerDHfP-u7KamjCJz7xe5pZlyLv7V35K__ZXzrf7J67enUYdouY_ux3ffcbjx48iumV21_60u37YWeLCHG1twjx1TfulYvtruzONhf7HMc6oHpKMcVoUrfrdSDllEFIWRmjyEjF5sQxxvl8j0PkwNDkoR-amJlxd7HJbccUECCEMF_OgVCqqGkL1s3nYliB18ePhMLxg0cCdPOFt61uXL135xYCx5SlL4_ORqia56c-DOvH67ycP35wL7QJO15vH_Kei69HsLhImDC1CwBKswxm25OT1cFsePT4Yr1DBiaPe52hutrtN47f_TveLbuLtSQk4G7eV6Qh7NfcPXtjrPjix997--7xk0_drFXcfLVIX_3yKx_77g_3OyU3BuMmaMBbdx688Pzz0-6omgGiGV29fu2rL72y_drL73rx2Yt1j4STEXJ6GY3FQiBRHHqZwFxujkjDbqwKOUVTTSEMtZpZTqkf6jgqqDHxRN-yihwCAKSYhrEE9N0woAM4ARszq3qKAYhVXEQNnQCHfnR3muDCDlMtbiLwXuLbicRUSwFkCmEa5AEocXCrBk6TBsywjiVERrTYcAiBVMjhxpXD9z73HBPFxKNUN9uu-4nkW1VXTbMt_d1b9xbLRQg8jmX9eJvablAJHBEQbGKSQq0jEqDDsB7S4WETyOu4XauJYmBT6Mc6b7rdUBh9V2uTm6GvCu5upeg8h-FczFTNCBkR1YuDG5ObBUAOYTtsMeWqBdWJyIp6CE4WKZr5JcwYXUulpglEjmQAYABmcAmpFGaIIQCYUwhdghEQjEX-N3_w-4pULbY529KqrVDamN72zHUQN9Zf-I3PUdMM640ZsoOJxszr9a5rU0wspSTiSxs5WddlK7WOI3BwB-DoZpcTHjB17WtxMGZCDKallhEIyQlcwRHQxzK6ewwB0ME8Nsmk-gSAm7DsDlpLivNaS8pJd8N2s7124-qXv_oSKDCzX5qhgQQm-ufEbwyBFQBjmCzwqoJIHNjVwBGIUQyIEUi0UgxSNOesMnAgNTdXQAwhKngdCsegqswRmCJRHfrJAAnIqpXQOTCowmR_cg8pwVQBcS5DyV2bzcah7M62gTM6UCDMTWhTiAHNb9y4hm7X946u5NYQwzxF8ja1t--fNF2DTpuL9XLROYDUygSLeVtKadqGqSz35nfuPjpcrYZaZ13b7_orh1f6Ybe_v6euVSsQBsImxv15t5p3OXB1poC7bc-ARrxcLWuVGMIwjjknrdKPfdu1UaO6zrq2yWnXl5CpH8a9ZVtlyDFbqcwxhMn8hYhEZZB2kXc7YQ6i5oh51qg7mjbtfOhP592qtBFF_vnf-6_-u7_1rx4-Ojl8-tr6fMdo-_vNr_7al77_e77r7_wPP5xSu-l3VoSDA7rTZMQD4mCoTGpmrpqa9K9_4iefe-Edp184JcSJRaYiy7306OSMmSasGBkShzoWno7YRCEEFyNiRPdIFydnFPbNPJCbmpkRobqpKgGZliqacjuB090cTAFJpE6lJEQuwxiaDgFTzlZLSp0bzPf3j-_cC4GxGocw6b3EJXGYYiGAZK6EjKAhsIMScQpp2-8cPDZJRWJqUpu35_0w1OVe7LcDBRrLmJcNICLRRb85SHOvXs1DDGen50RpNl9uLs4xEAq6eTFrU0ohyFgw8gR5MFYGqnVMbVOr5JxUYeIfRgweyAmJqZ01e_Pw7NNX-74fzEp1J3O3KlLMvAwAYEKx8ruff-71V-984-U3m9WsafJ2O8SctUgXsgMVAq9DmxsAMFEgUAOsBoAONlZT9dGEKSDyiNi7_fRnv_gHP_XRSea1mrVQSkH_2smjgzIEikUhEm2r3Tle__qXX3vf257MMT3_wjV2f_Ft14LqFONrYqwBZZBffelrrz9ej2OBGNw8NYHAkaJKrWay7XPT5gRBwzAUdGo4VazEwUWGXQ-BYwplHB10q8qG--3Bznom3gx9Sk1fq4i4mwl61UpGRpE5piRFHP2ctpGRm6Qi44XknCQ7JIKqYNO121ULMSORk08462IWiN2hDKWdBXBEBUZaj2PXppxjqeXuyTDvckqpY6p1PNvtKHTXr-5vznfocJhmAL4ddLerTCSEiOjmyEgOTIzmDIhEAB5CcLgk4hOiiSJOrGSYbDtVFRjBgZkd3NA6nCEBmjMTOqs5AIrW3IZaBRTAHZDdjCKZmgEUlcCcOAKQmsG0TXM08NwkdY2JI9K0c8spIuqsixw4ArQBATk6msmsSQQMCECkZoRAU5t6ImAQq5k5VNGpRWSiPE1uZEJBXPpPuyYwM7gFjm7uE_z_0n8CKQQHcHWOYSoYyyinj093_Xjt-jU1y01SNdTy81_8wp_57k95YBCYmsjDsBv77WaoJkYc5k3OOalVJOdAIZI7uDpzEyeHtaK6XpLlwCrgRNSY9icAQAGRKFso4zDIugE-Pl__0T_6Az_-4z_1L3_4__kn_vSf-JlP_2wpZ3ffeH0-X7ZN6OYzNAiRjh89fPl8_cHrN3NCAh77klJwhOmiHpEdjAEiJSRFSiI1IKm7BTNmNl3M5x4ACCiAar16tasx3bzxwrYUgZ4yzQ5nzz3_1N0H95suP3n9mQjy5AsvDNvdi--dvfjRb2GW44cnw6hIuR_rcr48Pj2__dYtCvHx6eNXXnr1t77w2a9-_Z70w_7-geCA64EhDO5D8NV1-U__-p_63_2Fv_32dz3_bz_zhbkzgLQxYBuQQzdfjOsdbUYirzvFHJo4D11Yn6yvve3Jsht1HMf-tB_HMIJxUIi7i3F1de_6Rz5w77XjFz7ynkevv1Y2263aye37ABAYTCFtfdJVaEgGWhWvv-ddAvzw-Iwwq9vpvZNydtod7seOxrNHMeW9q_sXpxK7zKEt66Ftcox-fL_TML_2weeH-w_O762PnjmSXX_nc7_dPXF1__Aq7qcXv-P5kP3Xf_Jn63Z39dlnnnnPC8e379k43nr99gvveTrvdQ_uP37jtTuDn88P5rt7w9HNKw_un5Rtv1d7k7GNzXZdf-iHf_pv_q3_fH26SW2o1bEIL9L9u1uZ9H9gYhKYRUwBn3vmma9__bW37jw8OjzYlUKATDSMUi4DJZrNiihOAG1TB3TCUouJAmHbtrrZuvuwHYZ-cDNRsapixQwRyVQ4hGG3Q0etBdyraE5pMrUaoCMy0zDWcTAH8YCEwdVMFAGL1onm6Q6j11nTShUAmPw2iMiBZSLSE4LZ1KmnwC5uZioiwuwYHfb2ltqXp5--9sz1K2gWMPTqpZQYYts14k5ER0eHovLma_faJuyvFolDRUupmwhvu6GIGiEXqTB1JJ1Cou3ZpooQM8Qw9GM7ywp2froxoL7viaCKVLUJGYKOVnW0_mLdQwR31AJMILuBDD2gqTpCRXTwZrZQM9UKBuA2TWFwAujjJaiYU6IQXL2CqQooVCdmslopBFR1RnPg6iP0zS4RWI7hL__7f-LGE1fv3L21mM2bmMtm9_FPfuS3f-O3Yg7WG4rd340Xgw1iMSQXyyEOY23bYCJTWXmsxQFDYDMIMZZxRIRapYrOVskVh-0YiMV81JoDo7uKIRcxAWQEJzARDblxFXLVoo5KgbTUEAIRlUtRg7iIR44pIyATMJgEX127HmL0sbpPa2fmQKroTFCRJsiPQuBgWMD__3gfYmYZhfibvjQ3QDOHEOM47IhIRZhJixATogNFMaUQGALCZA3VSR_J08J00gMDITEx-IScJnBHZFQFDowKMeTN-iI3iTg03eL87CRwlCqL1b7qKKAH3f7B3nwcdjeuHc1X8-i63mxni3ae-NFZM49sFGZdVvN-rAREVNGgigHjbLE4O72IgdQN3Zhp72B5erZuZ52YxhhjaoZxWM3bFGCReZ6ZyXUUF0KdrNLIgNuxqsrecj7xOULOSI4F6qCzriulzppmGphFinXUdhZzim3mAAb711fnx1uDCgDEIbYkg87a1WY8r0PJq2VAA9KubRglEf7Vv_q__Uc_8umvvfHW_Gh2fjLutqVN9dzKP_nRn_7bf_OvaIc-Fg7MKRgIpTiWmrqZVDG3EIIZ1EHYABDvvHbr-__g933xN78ErJSiWwWIfe1jjGUcOEZ0UpUUMzKC-xQvwxCl7iY7NTKkFFLCrYlzIsbLaAC6qlIM5KjlknM8NXhUDNHJg4KZGRMykVslhG9STUjVYtOmiAjqBiFld3PUCVUL6Jv1Weqi7tzUXIEbNjUiMpeco6iqa-RoZnUcQ5vHKqKOhOxE7FAtcHDVFhNWN9XUtYSEjJvzxzefeOL85BTAmaeAEjg6p2TqYsYhuLqpBuZSZLHinWjiWFTM1FwbjkioppxnXZdu7C1nIX7lrfvqII5EBBzKKMTUD2NOWWUMhLdv3fnUd337p3_13z51uNfmvKtjkSlNw2I-1kop1WGkEN0MUKfAVdHKxOZ-fHzKETkkU_MSUmwfbfoRZTWfIenF2Wa3sw6WHRyXfiuUAgdKsSoR0TfeenS2G5p5c7Q8aGc5tlS2Qwtw83C-T0QhrvbS93_sg7fX5z_8C19uqlStOAhHnur541ibHIZxUAgqrgDm0ATCSnXKjUSuRVvO6rVtZsXcqwyyDczVnWIqtYQmaXVUoIijSOCs6AjQb4fQxjbgph96Cim7jtK2iVxLReQpVe8aEM3HwUaruU3goFqZHAGHqg1zUelrmSSCiXi_m_dVShmYaN2PCDBGv75anQM5-qDeF6FALBDQll0epVCPTKSmDm7ubIgIjGgIo9ZEgQnBMTIDuqkhTtM3nWQo5g4AMTCyE7BUoUgEQAGZGCZAIWIRmxAWXpQAkTEQihtxcLMYuEjNMUxWAmJS067NgGCmgUkniSUBOrZtrqIxhYa5iSHHQJeeAo0pITZ-mSliBGPCyKFWcdWJ_HOJLlUlBGYy_aZpzEwdEYCYJ7pAYAB1ThkRgcBNDRzcDIiRiAgdnFzFDBwRTk7Ot2NZzLuUoygg4W_-1lev3jz8XR_60LZq6Ucx2O22UsuD04uj_cPNenv96mGMHDiYC5GHgIiupYooGGmwnWogSiGoGXpVN-ZwGVlFE1fVut2Np9v-9sOTOpQlhevP3ljG7iPf8r72YKnmd954a31ebj715J3HJ__Rf_zXfvSH_75udw1S2wQBX1258hO_9vJ74rzm6wQac3LAioCmCgGJ1CFwUqkNt4lh1gQEU5Wt1PWoxSk380o-jIUocM5huTg93s73n37w8ORs2N69f3K-7hft44f37-uXH2526wfHd20rx48f5TncenACRo-PH5vZuN6E5AkbyiFBoADgdnDj2vrsPIx1dbgXmzb0IAHBvZsvS93dvbv7hS-ccO2efNsHXvrCa9v16XarTZvJuT8f1AKIdfv7nDqezdYn_ds-_r6A_W__wq8_OnnsajqO_U5hezfvvy3EnBeLvbfty1BuvXH8zLe8MJbd2dl6d3z_4PqTV9_-XIwMVh_dPW1Ws7Kru00_21-unn3q7he_4W17fue-ibUZAZX6vmvAdg_HHpu9_WHoh82FCSFSv-6Fwrd89ycf37v7zIea3VnfLZp842h82xhbenj3_of_vd935crRfLXQi1plfHjnbvAAWM_unac8b9vua1_4ipf64__g84vDVXOwb8PmlAWw3RVbtc3ptr95tIwhdCkz8v0Hj9eb7atv3c-Oy7RgBBXdX81mB7PtZgB3M1WrDl7FwdGqP_nsUy9__Ru9-NWjg-1uZHVTG0XUARxK3S2bCIiXKg_AqlJHQUQt5uhdm0aV3diPVRxBVTkyWBhGiYG32z7kBER1KEoAyIoVEYPDWEqMGcQUlafzO-g4GHglpsiBAM3cHcWUmWtvkGHqJIhqkxoVM1NVFRFAcPBALARahQKrSYq5zTxbLPZme-_7wLvGR5vVfkfIDnbR70YZRRQMY5NATVSZiJD7sR7uLxEQCEWriIoIMqwvtnmWxLxCFRM3zLPWyZtZOry2ryoxZ932yG6Dj4M3OVRVZjw7GzgiBCS3BDRKqUVKKUwM6lZErE7CP2bUUThFFTEzRHZTMLg8ifpkzHLMYKoKTpFVhSO5QUhR65RzdzPliEBmxTgmBHPELsaGdX_W_tX_6E89c_Pgzt3Tz_zbz__hP_L7__Jf_HO__LmXUtB7t042_dgJqpl4KeYGICIpcgQfFUzVVC5FmBUpJjOXsUrNzMEdah05JB3KJItVUURhAi9CHEAMkgK4lCHEKKbAaCaEpELMAd11GE1NzJ2IA0stERGIDJA5gDoTj_2Qc_ORb_22QTcco7syNybGjEVNAZgDAIiJI7irqIFZzDNTN6scc0hp7HtEIQIKWVQAgMFCuNQdEgVi50Ai6lopRncHcHCkQGamY2m7mU52GQSVOsnWTRUcKbCqumNMDYSRODjgIAWJmqbZ7TZD2bSz1oyabt4eHtx_89ZsHt_znrcvZ-n2_Tfe9tF3tl3qNxfgFpEfPO4zswP1uzGEsF1vc26ryem90-VytVzN15u-DDWlsJrPzjebtp07gokuF4uLzXnOrbnlHN0kxrBo4mq1zDlILWZedj3HyAHGoQxmY5UQIodQdn3T5LGUqTyziuyiTUoO-Mbdu09ePVpf7EJgd5jvd5lCAMZ-Z2ZWpTaztNv1KSdjGcoQm5yBu_35-v4xR1b1HOjJF99zdlY-86XXrj97cHqyxUiRvZ03KdBqf2Y7e-HG02_cut0PIwJhCC6mJiZ9iIgUvar1hUN0xdS2y5X89hdffuGFZ199_RvcNLIZmXC77ud7i3EoYArEyAEJGUmkOChynAb3ABMlMJgaOAOxuTMSsTl4TEmKhtTAhM-1YmrEIXCsJAgASMwEGgAnRB9wDAG5SFGpHHPpB47JRZHdVZt2VmRUNMBA5CLKKU2h6kA06cHFrGkaKTW2jdfi4BxYRTkyxWBmpioA7GhVEBiDBScFH7wE6qpKNKhQd0O_t1isN9vU5PPtlkNgxsBRoOSQN9vtbDabMGsAKKZAIK45ZvHKzGLKsUkh7h0uY5BPvO-d7Pjym7eLwKhiKoECAZWxphCkjoRU6_j11zf_zveTmmy2W1cLEKqqTQjzAG0MXrU3TQiMDOZN2xQtdRQPiGKKDhxcxUup1kydp6-9-uBdN6_MQ3wwnlaRc6mZoqm59KJsngr41XaxE_nGGw-vXD06XdfNIA607Tfn6-2sjXk2e_7woMv8fR9822G3-p7vfM9P_fpLyRxEWEFUUo6xbQP4gHrlYP7o4TYGG8TGsVZ1Ce6Mg5tH2JaSEo-1AqGqnI-labJyAFMi1qIm6FZ1WxeLxTjUWRtrFeqiGwxFmVJk11LHoVokpmAh2ji2LRPESDBrc3vQQsy73cU4DttxDF3SKsiMyDmygJUiEHiWeN6kBZFTvhj71WKGxFXqcX8RIACoC52dbve6JIZN21ZVcO5SFlUgMjMOlyJJJCSHAJHQ0ZEmHZgbTth7mCQrbg4hhiqG7kyBEBGCqQUiRxBTRibCasqRaMpeqouZOgTmQDx5alIkU4TIpdbEXFUZSd0CUi_W5WAmBMTEIbCJpMCEGDMvZx05EgGaUQiIACDEiQgQDNzRaXIJ27Q6AEACU504sKYG5lPsycwD0SXrE2hi7yABEQKQTTwJNGaekp-OrmpTY0fchs3w4HhzdDRfLTsf9d6Dk68_vv-eZ57M3ey8WC27UafJH-U2PT27EijeOOg4BlF1sEQR3MAnyyflSFUF0SjwoKXvh8DsCGQ0mtS-OqBMzCI0c56FWdCzxWL-2197-a2T0xt7i9vfuLt-_DA2qRr-1M__wh_7M3_sr__Xf-ei9i-99o33PPmcgscmyiBV_U9-78fPjvWNu8dFxve849mcWiRnh2H0x-Nw96G_8tZvia8-__K_4PUzr99-9asPXgGHLMRG_ShPXV0Ms-ZTH__osOm_-tVXdSynj9cWFPvhDOSo24vL-eb4pJbd0c0bUBgZzx6tY5Szrx5DSt28AxEoulzM28z9xfiBb_toeXi-vP7Cb_3Kz9-9_ajpml1vIwxoFWyXIsWcqU3z_WV_99Ev_thPX2x3P_czP758br--UdgJQBW9PWisKmiVkMWr13XR_qXf_DXdbBxIqzMHni32lhHz0zZKaDLPun4s1YhD0-s4bgansLxx3RA8Z0jBNbR73hx0w_h4tre3OroynJztP3UEZMPD08WNo-vPHt352ht5nqWw78a0t7c4uLFqwlCGZj7j1UzXkhazN199o0vNdtO38-7-_UcM1M5nwXnEdO-VW-18uV0_vPXG3WH9-OL-A0ZomIbdRRMtx_jie98_lm0iPl-vh5NNsc3q4OnTxw-61awvRVBXe4eApoBI-GM_9Uv7V69s-y2GbrfdzboWkXe9PPv2J87X47yN7jDpzwWBDKZI4TNPPP3Ka6-GECPmWksKCYDcRMSMYMfIiGrOYAomRdW91IoEYgrmMae4q5FlqBUD99sBCJyIiXKOakZAzNPKCqUyE_S1UA7VKkIUsFKLgGidhGCKTgam1RAgBUJEAwuRx1LcDQBSSCI1cvAp60LAHAhwGAoTACHhNEMwM7px_fq1w4PGarvXANlkFAbGzVkfmJpFB-q7UgxRat2N42q_a9om57QdxvPtzh1zzrtS5_MWkGQcE8VS-qbJCWkch2bWlb7GQEMdQ4rjaINInsWxt9rLWERMhq3mBrzUqeU_agWmCT8WyXs1vdR98DQtRkCcZKxFzI0CMwAR4MQvNkdnAHVzACCOtRQSdQCOAdzBXEtNOUMgdMwp5BSaGNuAf_aP_0Bs2r_1j_7Zz__yZ9OsvXU2_sV_7wc-9O53_92_83dVbbMZunkXNARNbcebzYjBHKmWcVqpTPVcJur7ISGpjIzootvdlpGV2FUppSk-h0Qml9NlcgV2GSs6ptzUMnKMpupu6hWDo3gIZEbKU03EDYBDqrUGAFOPiasMITDFoDHtz9uf_aXPBsLRnVAxYMxplMFcVWsKDZuVUisVRDACg8qBbGKLmsUcXKsj6eWgytWnO58gm4lxCNOrytFpEqsBqgiFiRyBZsrMYDDVlx2cYdrXg6lhCM6oUIFRTFNuQs6mVgG4yXm-X0p_9NQT5WKnQ__EMzfIcT6bDevN-973zhaoJQptunkwHwcTVQ4EMUKRwDSfd2UUr3rjylUgWBzNh2FsGlZVkeruR1cOHtx71DbterNuUjOW0nXdYtbmiG3ga1f3uyapGBNEAsupiFZwQS9iGCZ6rCHwbrfrupmIFBnbpgVzqbVWffbGzd2w6boMgRkIRodIIeU4bnYcyD2083Z73qcuuCoQtF0nxbxY2-YmUp4tHPDPfe9Hf-Rf_ebzb79moPcfbQFtsWiahrq2pRT_7j_-sT_03Z_4G__9jyznnYkT-8XJNgWSUSCGEJEpl7G36sSxFhOKv_Izv_J9f-j3vHnrNXPsms5ERi1FKkYex9p2qY4FQoixURMVLSIpIDJbNQhoakRQdkNuWilCwEhQS-FAbqIyhpiLu7lOdCAgphCsFncDB4pchiGlRt1SmJlWx2l7IAFAxRgZ3KRUXrBVd8TJTjqu10dPP3t-fsGpQREMQUUBoIyladtt34c2a6milkLCQIg4DiUElmqBmYjUHYoTUwU19DKOCDaKMMG9-8cH-ytH3Y5lNmu3m01VsghN0zBC0-ZSS9e17qZjX4qK26iVAhJbiEnBmzYFBOLxQ-9690HXPDzbPlhvFACB6zAaTVYLULOxSA6hVwmMqn2bZyqKTDnH0dQAVNFEQuAKak6lCpEyEhZXheKRqjATchSB3dAfNJHYmUOb8-e__tqHnnvqaNm-cVvrOKhP6HRCzA6622gD9vhkh2oE4Xy9u07NxfEGQbfD2EQG8d1meyvB7s3-3v2z7_vo0zeuHPz57_zgy8f9V778Shl6oGBqRY3QQkxXj_Y3F6rDzl2MwAxAGSpyVC0WmQSUKLoJEsemdXNGrMU4BUcAUIYgZkrazlMt1ZCKGQOmTEPfa1-QA4CZa2BG7Seg77WbB1455BgipQQN5Wa12I5ldH10euFQdwqoyu6ApA69DMO2dDldyQ1guxtrKeN0ZeXEYt42wRkMAMmKyMTJRscyVEqISODOgWCKWjoQoxsagprlQAY88TEdoY2pmKKYuwcACowO7k5IxCCGqpojOwC4kSMDIRgiIGEkSsyIWIsAIqVQRQJTKTWlBG6k7qAxkimkyG6aYpisVzGyucUAibHNSdTamBANMExLf2Y2NSZ0BFMLgWxaT30T-DMRNJFpKjgCOqIjeqDJ6YtTsniihBHiZAdwx0AARGgOCObG1ZHIAaqZKTw-X998aj9RGHf2a19-9cbNgw-990UtbgjEgaO1iamM8zarSBfbfhgM8fj0MZrvrVajT0XAGpkRIcWEZmaCyGVK4XMIyByRcwyr6NKXfjsUCTFgCKD69NV36Vg__K63PTrdlL6__tSzmVJMqwSbb_zm1xd_5g_tr_a2df33_-4P_cP_9r9iam7dOqVg89V-N9-_sd_8sR_8Sz_9xpfn3j157eDew1OgMg4QRANT281zDBV9kV9LAa-N6o4HN66U3mxGhMFOyuuvPXh053g5bzcYxu0jinHWzK_FtLp6QwUk6vrB6TrtPvHJj9669eAdb3_-M7_y2aGnp555an71yRD5pV_-N6W3Mvr63F766qvr-6f0ta_q-RZi9HE83J93165vHj4c1xQxpti64djvDo7aW197NVEcH3s9H80szXKe7Z09Ok6zVutaSklsNhhpkyO6WL8dF4cH6AAphZS7vf2hHyrXvFhRcC0675oc2C4khjYgdk3erne2wUpIiouDo3TQnD-8aOcdJ_BNnR3uHd8_bQ8P949u4CwvD65iy2Koylefupa62cmDB94bUpuVjy9Oc04nJycHzz3tEGo_dG2W4mnejpstOXiFB6_fKrv-zVfuPPmOK23XlIsNcGiW_OUvv9KlvLdcAsW3f-uH33jt1nPvff-D1772xstfedu7P7hdP7J-fOHqvo1jSE0RSine_sa9v_63_w8vfeE1vXq4PLpaamUnIFgt977x6q0PvvMFMCdkN5ngh1XVAYDwqWeeefXWW0d7R_t7y6FUQNBqTOimQ19iDEAOwAZu6EgTwlcSI4WExIsuK4JttO8rMIpIFZesjAQExcVUBFnEUmqK6lglhwgGEnBcb5wIAGqRGHhCcnGI4kbudkkELq7uAV2NQzTRydutOk0iCBHKWHz63SWSukttO6y33_rtH7h6dORVh3Xfrma7iz6mUIuUMhJxbpoylsQhhygIg1VRuXn1WsPMBLVUAwiRS9Wui0S07QckSxy7ruOIUobFrNvbW7mYE4xjIYeAVKrttgITQrdUMVfRvh9Timdn5-gWENW4yEjMHFzKzgHAycUiRylCQC5ubEDOwOqGgKY-9ZouQf4mxFiKcq0cWWsJjCYlpqbqLueUIlPEj37sg2-8fmu12js6bL79wx94_4tP_synf-s3f_O3wZTMa3_BBlf3u5s3b3SL8zdu3b72nncw8rXV4dcfXyj4MBRmqu6TVLiquTmhceA6DKKFiIdxBLDJMGmA4zCEFNen54eHR65GBO4wjgOHYIDMBKaBg0mJIY5jAXZQpcCj1Cme4aLASESlSggBCF2sqkxdaEB_4R0vDmpTCUFFQYeQUhknMpmIipIwRaQiYyEO7qa14uR0l8qBZSyMBEhmNcSgYuCQcjNRo0WcKZpXCsFErQoBARLFZFpjIC1WSwWaVJV-KRcjcCJ3wEAChsimfumsKNKsErhBoBxmZbftFquyXsfQEIEH2lsubtw8GDZn--2si7FL4WxdoE0X28EQkGlzsc0pq5u7djmpSUxZzdeP-1mbxfTiYru_vwdE5-dnMYWhDkgYmqjo1w4OTi7OVqvl3sFi2TQJoUl0dtFfDOdt2ivVJggEOMzaZqxahhIjMeZa6-Hh_uPHp02Xa9HSb7v5fBgGACZEJFyu2gjUzQNfefHjuWlSk9YXfe7S5C1a7q3G3djNZ6beJLIiATzmGPOsu7K4e_t0dbVbX_TtYj7v5stl3NtLuW0d6K1X7vzpH_w9P_2v_w0GdgWpaiIxJTV18zbPpAoimxsS1bJDRxB_70fff_7g4nx9YQYggohTIlBVQmJ0MFGO2czAlTiYFA4BKHCI7u5uZuDuquoIAVlFkCYsGlBMpjYV8GNI5h5ynvh9QDQVwx0dAc01NZ2rmEkVSTlKLaLVAWOMVSU3zTgMjAEctMrhU0-cHZ84Oji6GwIEQlFLuXGciJPoSASORLvNdrW3GsfRRHLq1M3duqaT0UIM5IjqhgZmgFiLXL22X4Za1dUcwZoYEbGIxBhrVQ6hiiARRzawGAMi1FpiCEgEgF1ObROeunLwyfe9QwV_-td_68HjTdUp3Yim0rWzs_VmErKIVAISgrN1386aWkUqXH_i8PzxFgFUqim6g5pdHrMQCQEIkVBqDRmJuKqCWxBgxKJqCDHzw3snn_jIOzZnm9feur8Z63oUQagiEMBsWuoogqGjm0mRGt1Uh74AehUbip6td3Ws5Hax3t4d8by341K6wM88efi2566-47kn3vHME1cPj97x9PVktL_X3b53oup-mSwFdu9rLbVGJGKXqrVWQurHguDTiBiZpWoOUVQJjRBAMIQw7UnBlQECWESOKTbtROg3UFBzjmG-nM1zwxTqMI6uUm10K-K5Sd2qmS26cRxdZFc0MqecUmAwJA5ojhxs0jKQd20z9lXdcwrgyorg6mb9UFOOZxfD_jzN5hlNfbq8TsF7QEQMhEA0_b_EQGrAOKl-ydARkR0dgQMSADObGQK4e4iEjhMvwg1SYHdnxJwCIk5GDEJOgbomThwFN4spInicnAHu5pBSgEvVDTBxIM6Bq9pykSNSChQ5UpjcvA4ITGQ-cX3czKcB4STWm77j9IeZEcmn4BBYDPFSAOxA020BcDLHmztOi4tv_u3oyOBuSOiI1cGJ33r0WAIuFovPfvHrr52M1w7yfNWMQxmLjSpMfLHdqKirkTuppRxyDIYaQmqaSAQKRpEnI33MWcyJozGHmDJHZppKyBdv3v9z_93f_Af_9H--dVEW3f7Vo0PkLlGzWDQKQd0ZAyAbpnR4eLJbf_ozn79647rL9tGj82tPPHHr3l3dDDc-_O4Vdz_zcz-56xb_p7_zD3_s07_-Ez_3i6_dfjMM5Z3vee6d737bdrObzZfXrj755LPPXbv5VFocHDz17Om9M3Dcne1K76fH2zpAGepQDQOOg8Vm8bWvvLF-dMacYg67ix1EkgLdwf7J8fHm4QMEq4h3bt-7-_r9x6fHj2_fJ5NxHE9uv35y783UdrnLm9NNM0s6KtViY81Nk9pZSCm03VjGsukJCTi0bTtuduQ0bvuzOyfdakFOrpK6DkLSorFtvSrVSv02pI6QSi8Ymr2jK6CIIVRxz23ev6YKWnW2t4fiCKj374b5PITU7M1dRMcCEFyQUwox5b2FOw29BKJIuHl8nlPTrPZsrPvXV7v11olCbjzF2bWDEGKezWoZVS2EhC6PH9xb7l1JIawWzWZXQkznF9tuNTs5Pk051lE3m_VqGb0K5bZbNFLGcdvTlF0fh6MnXrh38nhvbxFnzabfLY8OatkypnFzxqS78_Vq7-DazWvzduHAxGBKD9548-Of-hhReuVrX3vhbc-DmLuryjy3d-_dPVyuMJKKFDEHr6IqJipgQIxdnr32xpvtrDP1fhzdcer-mqMhmDhTAIAqLubT3JQJU2AzlzIlf2gcC3McayUHdODABi6iAFZMzZ2RzYpWySlMYi9AJ0SRUsbaNI1IBUA1dbHAQWo1Q3ejyzKSTTYAdACACQhHRIRgbkSE5IQM4Mt59453vvDsU9fbkE4fHi-WnYrGEKqomyIRxyC15JTFQA0uLja7sdx88upe227XuyoKgWu1XR3dgSiqKiBOI63FwWy5XBKl_dWyjcHAh7GaepOzmQ4mE0be3WMM_W4wNQKsVUspk5hlHAYnADNkKKLo3nIwMUOgwKbi4N98LnrkeJlVkEJM6gaM7uCqOD2tfTrAOZib19SmiJhCunnz2ccn529__rlVpLPT3ac-9rGf-Mmf-dEf_Z8Hk1ErIY5l_N7v_t3jbnt0ZX623Xjff-DFd4LZq_cevXV8AcxlHGtVIzAzxGlUbmrKyE5Wx4EDlzIych1HQCB3UEQCNwFzU3FEMHDTiaNCRKpTR85iym5A6CqamlZMFIEREdEQQghSFZEBVcRi25RhRLIY0rVr1x49eHh6fCpaA4IXmVBySMlNQcRgQjYpuIWY0BRUAzGCqSoyg6mbxZhVKk7_bKRJ9GgTFoOYmbUqMwEiEk-UNp-IpgROly9Nnpwt1TAgxdb8cjFDhEyYug7MmUNok1ZljjHEwNS2HZrtXTnaO9xfLOc3rh7evLrXRH_n2282GCN406Sz0w2lUBTPz9cUeHopqZqq1CJNm8HBRBfLbhyGtu0AsGlS17WIcb3ZzeZdTm3TZHUBs4OD-ROHq1UOu80uRhJxkxgipRwenw-73RCZJjoTObrr3v4yEKlaCJRzuDjfFqlIHkPq-yGmYGp7ywWI5UD84qd-YOhHc2tmTYhkRUMTckgcWKqCQ8yMyE2TKKblcvbmm49T6H73d76rVFepJ-vttWULxcXgYG_Oju_9wLs-86tfMDIOWUFdHRmrKIXIyLlNohWZwAQcELztmuOzBzduXr9378TQ0SA0qRThgOAM7miemm7oNyFGUYspuen0iRKzu4koIQbmUkac4r5hQkSRuiM4IZlN84ng6sRsbmaWUxap4EZEIUYnQoRuNpdhnMopKbe77YAc3CHGDG4ptSaChG6W58th2LoZiJgrKObEpg5oIQU1n2hb5OAAYMYxsruIioohmAOQE4PUwoFLrftpvhlKE6JKDZEDp_Wub1LKU5SNcErOhSapCQeuQ02BYm7Gccw596VvcnJHjhQpLGb0Oz_87pv7-689OP-tV14_X_djsbGOKu7m7TxX0SJC4D5VuoDOzrdPPnnj7PR0HMd-WxazeZ4tNtsLIxVFQGemMhR3QAQgMnBiGocSKNRBA2IMbFLVXMWLOQf4xPvfvdtsv_Hmg3a_PV9XDMSOIooE6AEAatUQg7mJwWY9xBRFNQYWVQJzKcUsLuabi5IzXVxsb987PRv7s3UVD6lrcsay7fe79uYTR08d7r386gMjVUQBr2pEpGoErg5VYGqZu9YQo5mP6oSI4CGEyDhBekNOk5oxBgbwpo0EsFrMF4vF0cFByhETq8Kkk2ti3O_moAQOlzKuAICAYIFD7TUSL-czrbWvI3IA8FVI2-q7vsREg9S2aXQcIURzIWZyTUiEuN-lfqgqWF2q6LzNxGiisyYTujk4oJpd8s0Ap4kgMV3eDIjMJwAHhktENwCRqk9vXCJ0dSSMkztZbTq85hSIMAUG9xgDE8VAiTkSkZOoccQcY2AOBIt5cvcYpmYVIiAQ5JxS4iYFRmjblAO3ORHC5PKd3B4OgI5EDI7TFoOIVRTw8lk5UeYAEMBDYFVlhBjCJGYnYp-YX-ZICIhuRowml68sQAQCU1UHA1CE9WZ8697D84enT6yu3Ll3cjDrnr2-aHNoU44c1L0fSxmFAkWHpmvRMIZmKEYhChMBEbMTaokWO62-6ceubQJQnjWEGXz6CEI_-ldfufef_3_-CW_627fPzm89-Bv_r5_40vbi8dnxX_6L_8Xf-Hv__L_8B__sx378F3_0X_zkL3_hc_-3v__D__3f--Gf-bnfaJt2vtw_O338pd946dt_4JOf-_Uv1gy_8Zmv_egv_sa_-c3Xfu2zXzi9e3by9du3bt2DJuflXkjLo6c__PD1VxaL5dVn3h_aPJTdtNbsDruTO3ek1phbsLrYm7mCoGFMxfzouZsvf-4r872WUjx99Ojw-rW3Xr3VrhbStfX0fDg5pYAhohAExPZgpdshdDGQG3iczcApH-wXrdtemr1FX6TZW1HXhi4poScexjIOBXOu6txkaGa0XAlC2JubAHeNhsDLTmA63-t2U5p5kw6vKCAvlty2Am3cWy6uXOn7gXJbDQAZAJvlAohcYXa4Wj71VEg8jMZN5IAAaBQgRchp7Dfre_dCu2hmXXUh4mvvekYNl1cX7Ag57LZ9bJvQZht9sVywsQOI-m5XY2aKaRhkt94-8fYn16cXVSx1eSwWQwAnVFWgYTe6425dgYI7le3WzEBMtar7zeee40ghx5QaGUYC11IdkDiePXpQZBj78syLLzZNQ4xNop_8mZ__3j_w7-61rSOcPH682zy-fv2mqoIZGriVLiYKAQzN1dEmnnlVV_XA0RGWq9Vrd27v7-8XkVKrI6m5mJkruCMTM2z6YqBVDJmI0N2l2rDrgQAAqvkwDFV9spqr-dQGdnUFGMYSONRSQNVtmlPZxMy1ojB5wg1UayBmIBNFYnBT1am7TzSlgxQJGAEQEC9_zQERCDnw0Pcx5_2jw7c_-2zk4FVWe4uqMFapKttdH2KcgKiMHFIoRbdllKq5aWaJoPo4FgoBMz8-3eyGkpokRbSqm3KYHm-kYpPqExzHsahpjsxIZl7VxiLMXKQMQ5FapYiqm7mY7jY7SkFEtSoiShHTScdCou7oxDR96ipKgQiQCaQqADJzoDCqofnkMJdS-JtQclFB8kBcR9h_37tgN16cnZa-3-xOz87P_tQf_AMa-Z_-4x81t76YqiCM5_3me7_rd_3QT3_6lz7z-ePdxkQ--dEPQwVb5K-cnK0fn9VBqtQyiKNNmEBEHMqOFBBBSkUCgImuwzYNE0OotYBbCMHBpNacGykDqHFkV-UYLgczrhQiEdVaQwgTj4ER1S-17MyMRGYi3yxuTe-Gw-tXfvvXf7Prsqo7MqAhgKvHlKe3gLmhm4v6BFma0G1urh5SAuRaBkJ2RAoETgBGHADIY3tpmrjErYK7M0dR45gQp7fOtLJiBwsxljIRO1DNMURHYOIYEyOEEKWUlNupm7E6OCx1NPWQMsZ446knU5OeunG1Wnn7E1ebkPba9sbh3mLehID9rr_Y9QahVKvuMbKKLhZt06a-H8mx69qma0VFpAIAIlUpTdsEisM4dl3DTNNWrZ11Vsu1K_vLmHIKXZe2_WCmKcftbuwHKVO31SzFMIh0s5xCdPdAwd1SiGCQIi_35mO1JjeYwtn5ejWfLecdTW34frOOOdZaVPTw6tGpnaE7BpZtH3OaX5u7-zK31veck7NdvbJfRnr51YdPLGmR91dNd-fW3Sev7y0PluvzsW3bf_UTv_z0C0-89voDc2PExf5qe7Fuu67vd0W9Wx3gjiLxYIM7cIgG4fitR9_2uz_5xS-9DMYm4GQpBvPqKhBJTNkkxCTjSMTuHjiqChAgeMqNO6h6bDOPI3EwnfC6UUYBhilsgEYcwM2mhgoQI4gbxJhMxNU4U-0LZrY8qVHjuOvbRU45qRRjJmaRMaUUY661IONmve5m7e58xxSRzN2KVAoRgaRUjqHW0RUczNyIaX16Pp_PVMUNAjelFAdNlFIT-s3oZKf9BZiJuqo9fnSyunIttY3UghxSSmMtAfUyUqgSU4JoCGy15pRMJSAjkIIu2zYwzLr0wlM3pfpvvfqN0_VuqCKmiDRImTWd9o4Qio9EBMFFJVHwYm9-_cHVGwcnDx8Qwt179_eu7j9x_cbde_eKFvHpmMiu1TBKcEQGsxwjAMcGCBiNjBQQFQ3VocLtB2eLtqMUPCZgBAE3I_MKPjEKKdF2HCkYOCl4P4yB0MQZyaAGZnNaby5q7-vN9tFgIfLyaLmuMjw4_sZbDx9u-htHyxvzviH49t_xjk9-64s_8Wu_RVMTFTnmAIGlwHYnFKFujI3FAMlCiOiC4FItMAqRG6SQQxPHvubAzIgemyY1q5RDQLCz85PF4d5-nh8e7G03u_OzNYOrSAAuZidyfNAe4OiG7gQj9gTcn--6xezKlcNutXf88GQYx4dqHOPespn0MeNQY8gw1rWOgXze5jKM2CZkFACOABwc-XSsYRbLtm56bTIezLvHFzsBmuAG7IAYwJWcEcDUjZwQcLIA4Ddh-gAAyIghsBtQJCcPEVXQDQB9qsuCA5DnHNBRzHNO5GCmBApoTlFNcxOnjM2iy8hsBqVqDTRU6dqM7imxmTSRE3MgdHNXU9dA5ICXyR_36TLp1QmMiVSmgT0gIiKBAQCaaozsZgBIYXolOCAYGDI5KSgAwmTlQoPL_YE4IZTBHHG33t59vD5YNssnrt-7OJ_PZmneqBoRVGcwb1JsUrRxOFjMRrc4y6_cOhnOd2-dX3z1pS8K7b_0lW_sTo93ps-_7frFUL720uuE9mh9trdqDcNB3hs259D3jBGX8cr-3iDyHZ_86OnFF37n7_2uOz_8r9763Kuvvf5GvnKjG4Z3IohIUXvzjcf7s-XR0TVUoNicnG2uPP3s6199a9OXw_3l2bAeZZC1xVkbuubKlcOLx6dVB0fWsdz--qtn998c17vT4wcPLo4JI6c4rG1-ZQ-t7k7Xs1Uj46DVH9w-TnsZOZXdZhRan61vPnOACo_u3HMtpQwZQzuPu90ZypiyxSYXx3E9trM5mOfFYtxtkUNwcgm7oba5Ofro--Z3zpsm9X3drkuet7W6eAwW0a2dL4HBdKjGoc3pYOHR9TxhKLLpB2G2rmmRCbkRCIGbXKoot8NQYtvOjxYxd-reXbm6vVjnEHNsm8X89te-fvDktXbWqQZ1i5jyDGLbjZv1bO9AItWhH9fD6saz4bkYORhaEAHyR3cfB4qUmmJnOc4WN_dRAsVcZbs7v0AMOXfO8Gj3lWf2vsVFEVXr-Oj4doiNq1DgbpYRrV1mB-3PxtSwaqUWgAQM4yxfnDzoODu5Gx7euIpnj0uV05PzJoAKbNdbIghNOji8-tY3XtlAH7u23_V5f5W4-8LnX_rz_-s_vF3vSpF3vu9dn_nFX3732z_kNgbC4vVwb_bbX375ox97fxGrZuY-VlV3AFd0M1Gzpgl7y9XXX3_16OC6qw5D7dpkAFWFDdVglrOom1ut2iSuooA0ltrNGkNSKPNl1_eDqZop5eimUkXGwoHRgYncRKuYG4oJKRCgY98LmANClVrHYm5gGIgosEhxRANwV2KcnkAyQcSI3dEdU0wilZmd3N1TCIvl8uqNo_XF-cHihkZHon69FbNaajtvgJCARMWBtpthO1YDEAQvY5NXZVsW8247lof3Th18PmuGUnJuDNQVVYwQ1utt0-XcZDMbau13OyIOiGSoBOqGhv12A2DjbsAQYtbdunJOgJCa7KrkoJOZygEJtWqPCuguwASXuEMAdBIpsc1O1apDcHUIBG6mE5o-RXdkBAMIMakUB-OUNi-_iRHKMOQQxjFcv3rwzDNHf-2v_e0eYacANJWc_PrhldmsefkrX-VuRTSaFjRgouPjkysH7W3VWmstJaW43RRkRycEypjQjJABgT0oIoPVsRi6aUViQhJVJQE3RFSVCVnKGAwMFEDM1dRBTYiNiczNinCO7h5iNN25O04CdqfJaUAOMaQ6jvsHR4t5HsvonK0qAblURJIyYCA3clMO0VSR0U2BWERyZANVLUg55aylALhWoZR8dIMKxAToAdnYzcADICKzk4Ghq6m7mQdCc4dI5BSYIScVdXfOCQlRoZu3u-0uMQEYIZvUZjYzhdXe_vr8pF2sOMQ2N4eHyyoF6nhjb7U_69oc21mI3zy170ZdLBa9gMjQ5pRyUN12TexH3w6ymmUA91qaENd9aShgCmaaOVXVoR_mixmQp9i6mwz9wcFif9Esm1xLrV4BsFYHVkM0gECs7MyERIcHhw_vH1-7tgKFahaIA3Pf70zMI2PAXR0J8GB_mZo47IaDqwtX4qc-9EmRmruk4k0TSqnz5QIIXZQjrw4Od6f9vE0E2O90uZoF9OeeuFl2u1WzIkdjPzrau3FlxSqcAzs8fHBq4syoWhnQRuEYFKDUGlOOManXOhY0FTU1dQdCevu733F2_-Riu3F1BHUFDFQGiURmiuAcoqoyAzqltq3jAMhujGjEONE2yC5J2KaaUmOuSJflmxSSqKhIyq2Z0xR8cycicBCVGAIgqvnkFQWzWg0QiIObulpghqlMjtERAAwpMkIt42UfF1nBkFFKzbOmiJp5pKnCHByUKRqY1uIA7hqYaxUwDynKKNzkKnUsMoXPzH2xOjg7O865KbUYalXHwIy4bObOWKUSI009Y7OUEyKlnJgm6oO9-5mb73n-mbt3H3_ua1-_2EpxO7_YOMLQlxRjzrGaSa0B0Q1rEQSqUttZZPJv-R0feOv1O6o-jmO_7Q9uHA1Dr-CuEDk4QhnFObhbiOjuKhWItCq4q8lYFQhDiPNZA2V4-srerZPTk4t-LKZFKE6jWSNK04wXJs6FGRNwQK3mVafJXlUjxPlsBhW6eWYAMDg731ycbs7Wm22_VVUIvFN_9dZDK_Xd73rq_unpg7M-InIKItqP4oS1CIEDAoeABjFydA_EROAZL4_I4GbijiGnqzcOGaCbd4tZjimK-zj0HGgcyqJrEvK8a2KMSNNjEwh8r12qWopBirj7djcAwmRJB_Bl1-wtunEc1cGKEGA_DilEkZEA2iYdzGZOINVCBBPoizo7U-pSWEVWwLP1eNHXXuowmjMdLvPV5bJl0tGQABHULIUQiHyStBDgpD9BAHckcgNADSH45QOR3JUI3TAEJEZwiHFKXmoOIQbiQG0TYwquxoHQgZGaHK_sdxEphbBouy6FWZOg1Bg4BG5zZIS2iZFw1qVIjEg2wbnMmBgR3Sd3hSG6TycMgGmcb2aImFMEwOlOgkyg6sgwAYYAp_IWTIFoY3dAJ3c3B0cD1NBEd3Hzvkoza6vjwXLOzJzQMEJLGAAbGEms09My_PxLL7965-xf_uxnf_xXvvp__ac_9y9--rO_8kuf-9xXv_LyF7_ymX_z5YsH94bt5l3vevr-q7d__-_-vdeeede9lz7_7PPPndy5_8Kzz-Wqy3nDLsvDvfVmmzmD2PnDi1e-eHsQgNX-5t7DqrzfLK3o-z_4sbtvvlkGIUQXdKfucI-bRkSteDufbR7fO7yy3-T2-O6jJ5-52W_6fr27ODm__-btcb25uNhYkZCjDj2Wne6OdVfAMlPoFk3LMcf46LW3vJTFMlOkcYDIiMTtvIEUu8Mr15--efrwkRXZv3KwOFp0XefiIYT-4YBk4-MLB8z7c6mOCDIUL4Vi5vksHO6HFHys3XyWLayuXCHma-9-G6o8-5F3nt87jjkww-SedAzdYhVTs9hfPH7l9tETV23QG088SxkCp27ePfn0M8wcmnZ3umu62Xy5XK46N6u9pnaeQz463AsxrE824DTfX0Sixaob-37vcN9NEbFNuLy6v9v129P1bNbEdiFDYea27SJlIuBIw8VucbiCsZZx2Jyc99seFJZHBxPMDV3KZuiWcwwsoy7j1RzicLZd7e15HXXQ2d6BqdVRU2wDxdKP0otWBzVTYwrol-46EN-_uj-en0Ox7_z9f-DkwcPdertazF3VFKTW7XbDISz29vpxd3p6_p2f-o7d-e5wf3F6cn7__puf-Pjv2GyKgxLjUMrrb7z67HPPoaq5L-fdl15-_anrV2Vi25kik6mBu1UTM5EKDiGEi-12s93lJrt6TpEIcfp6v-2tajUniCkxooqBewzIFABB3YdxHPqxjCOnIGZ1rIAoJgCgbqBehtFdgdDd1NQMTN1UgaiKmFRzMdXQpCnUx4HcANzDtKBB0iqEiOTuICKIxMyAICrIEFPjhE2Io5Rnr9-YzRKG0G92gDaFxomCiSWOkUNf62YoY5HNOJjL09ePSBHIh1rOtuMg0nadAQ39yISqAghmNgwlJXZ1tFBVailOaGZt19Ti3TycXAz9MIl9DYmHfmRmFS1jrVUMnNBNFBzUFMQDgLupmrnGwAgoaqYaUwTXlNJkKp_iyeho5nC5l54G4o4ORKw2JY_QnDiiC2AM7axhjP35-e__ge_42V_69b4WcHOpedbkrvuv_8u_1rXxZ3_p0yk3i3na68K3f-BbQgi_8sWXXnvjThnK2I9lKJdQNHN0UxFTM1UHM3NDqKUCE7kT4zgMpsqBSxlSTCYqojEkqTKlMgmQQ1Sp7hZidFF0t6oxJWY2FXBzUQAQlcDBVKe3T2ByMyIzdyZD8m1vjuiqMbGLTHP7KVsM7gh4mQpV4BAJzUzQzA2Iw9Q0iDFotcDBVNyBiV08psZVwSHlDjm6KQCGEJAQmVyNyBFAzYkYp5gWIjObODJDNWCKTAZYqoWUOcZaxsXeqt9uY45S9YMf__aIhZAY6dmnj_b2Fu__wAsP7z4-XDVHewtyR_DYNO6oiKVUZLq5vxpGXbXd-XqzWDQxhH47LhYNgV1sNm3bIWJKjaLXWudNk1MMnKpo1-bAfv1gf79tA0Gp0uRQq6QQRjVnBoBhFAo01ArmieHK0SKHkFJy91rqersNHMyxVKEQQB0QctvWvs7nrdUKBiGlKGIA2M0bML9yeHSxXecmN3sLVIhgewddIKNZ03S4mrWbYQzRQxdXe-H1N09S5C7HedfM9uaf_uVf-cBHPzqfzd68dR8ZVqvF4mBx_42HzbK7e--87YCQTMXMiYPqGCKru4iEgF_64suLq4t4caZoLu5YMKTYqJYxpQzmgYPF4CrmxoGJgpkiu1ZRRDcDs6HUdt55NQOvKoBIjD6xUJg4RHCoOnII7maiDhpScjN0G8cBOcaYxqEnZhPJOZWxz80cTGMMk2BZagmxJUJ1qpvtjXe9bXP6MqamlgoglEItY-RUR0F0U1FiBLVRgCm1iGZlGCjmGIJpjUxuqlIdwVVdLYYAKgqAZKZ1vpiDakrZXGOKZ-dny_liRAWEnLvdbg0xgoMBjWPJTUZCkQIeTHXRzhz5cy-9st4MCmRIyFxFUuaxHwamSdpiDoGDkkzPo-35xfrs5JPf8a1qJXf8-PGameShHuwdnFxstuO6IFQxZByHbUotmMXA5k7kTjaYALobuXrZFcxht1vnWZrnKENlRjQjpcTNRPJV94ZjXw0QHQphkEEDhSJVESlyyrzdjpv1eQp5HAoQliJQZKfuDo4wP1gN642fbjLAp7_0xvLK3h_5nR__0V_61W_cO_c6uvqMYBhrS2RepBgwhoyB_n9E_WmsrVl634c901rvtPc-wz13rrGru3oiKXZzpiiSLZG0JkpRJFlC7HwIIljRFwNBgHwI4CRwgsRIHMeJYyRCAiMGItkxEjuiLQmyHGokxSbZ3SS7ySZ7KPZQ8733THvvd1jrGfLhPa18q6qLOnXqnL33u9bz_P-_HxEF1IAmwaIekTIfxrI9aZsmC2CZlv5kWMZSHOtUMKIsSkgOcXU5tn3bNJybvFRdSg2PzEkAE8q8VEoJwkz9eBzbNp-enF0frsG9a9vHTx_Mk95c75dl6XLOjF6RkDMjAZ6n3bN6M1cfWkoi--MEDbr5vV273Fot6oAGoGJ6XfaTvXQh2yE_2bYpMzOWYjbVsiyLkJs7hRB5RGggIdDKBZV1A5-ETI0JhUUjAIIJmWnF2nZNE-6pYYQQBIEwQjNvm0R0d8_sMgILEawnevLhdpo2uUlNHseZIoahJadVNk203gFwJW5R-pcCeQAMQAbEcFtHVYhkEUIciBDh5oQCK9nTISIAHRHDApjNFVerKIBFBECtSlPVZcZINzfj88vj17_93osPpufX-6989be_8tWv9UO--vCKpLudsG3BUu3yziAY8ezsdJiX2qZ9Hl7c1h_7c3_0rW__wxdHbbvhi1_-9gvVf_8__o9azBZ6_Nq3H9x_-p2vvZcYrj8YAyC3MHT9UqvOpe2yY7jAl3_t1xLnascX743Lsnz5d3-dEg_SBiJLvnw2kQYV7dq225EkOXv68A9-68uf_dxP__6Xv_ri_Wc4edfw9de--5Gf-RFE2N1_cPXOO4J8_vL59QcvhpefUkh3flHnuZYFJm93_OiVR-PFLnXbqxvY7DavvJzruKcmz2ov_cAn63zsh5N8enY4lO12y-RCzebx_UO9GgZqto1p3j65oP5WUm6ZzXSp8_XlIcGYmIfTLTHur2_S9p5FrUfb3XvQct6enUOoOXLXuGSoloh9qW3Ku4vzhNT1_VwPnPLulDnld771nccfe2Uj-Xhzq0tp-5aazfZCan2Rc9pf7YFQAM4f3KfMSy1I3A0n07SoOhEd9_NYSjcuZdau68tUBUtquuN0A40xY3W7eff63sMHEcqSmA3MHrzy6Pnbz-f9uBzn4aTnlI_zldq5uDMGhsNSQS1KCXevcLw5NO1ADOFRwyEQhYecxxvTqhHBBA4hiH3btU2XOBWb9lffZQcvc0MyRzmOx5waN9uP-65r7z15-b13n731u19_5SOvNY383V_5_J__b_-58bgwIAodDvuPfuSjv_WFL95c77dtRqLb0Z--9GhanAWIqTiaqXmYhWQGBAheakWEe2dnf_jtd5jT0A5rKJ2INGJI3VQqE81jPT3rXKupEhEIuquZh1nOKSfp26F6wQCAsHkBACe3Wq1qSqRKHgGMUCJAiSk1eR5ngLBamcmQaqlCwJyXpXg4o1Qvkliretx5CYjWu3uYq4MTU9t2xBLgIs3zd747fOYHwBwgFrNlWigLEt85v6qO87KfZmpaIwUELeZVFXyqy-247MelAo63-0AiprooYSylakDKTEAQqzkPVzN8KVargfn1VZkPx2o-jgsxARCgT3OxWH2xsTZpMUAQZ3MKgDCGUAN3V9Qs2cwAwM0AIRCA0YshBTqpqTTZvAqg1zUBSxU85ZU8vxLCEZlMl5T6eToazH_xr_4FQr69vMWcHBcyJPN7p8PFyfBf_NLfXQ62PUltI4_Pzx3QTDPn6w_3dVkggkhqrbEqIxGkEbPi6LWaqQmie7VFEUlLzZnBwq0igLkiRNMwhq_qZisLNY1rBcQIgjUFBExNnqcp54aI6jIHECAIs7A4kZmyEK6aYQ2SUMPjYd-0w1xrEBdXREocCoaYXCsAqisShgYRgFcMYM7mCyNiOCEBMyMjKiIgy_pNAuK6xECEsszt0FtBCEfCWq3ZDF4sJVnGhQWtVpGESFEVGyGGlHIpnlJ2N2Ro2vUCQyl3ANB0zfXliycvPTrcvv_qG0_H68NLT-8_Od9k7mipLz8-vzhvCIGJiKkUC8TxOEsmQLyd5pNddzuPiNDlhMTCnISmenz04MHxOCdhR7RqIsIYiVP1EEYEaHIampwjMjO2aZ7LNFeAaPqmHHWca0AAwnY7ZMnTON7vumlcitaTbatVTzbboupuSLxMBYlSTu623XWENB6nriPZ3jtFvC1WzXx3cjGPU9NmME0p5U3_zbfef-31R-qWAl7_-Ovsy_TdD8syZ6NpKZuh2Wz71Lbnu2F_s__Rz3526Fo9qe-9z065VG9Z-t0wT8vJWXd9XcFAq9ZpSVm476fjlDhj9gAt03L-0n2id0AAQEzVvRITCMEdO8WJqNYIhOlwzH0_7fceDkDEiMSEDmYIjGzoEGCAUeea26HqDLVGBOJd-1eIJKdSagQgorSNlgpRm7Y3U3VjoghLnLVMTTvUZQKC1HSH_Q2sjXgDU6tLlbYp89LmXIsyibupWmpB5ypCy7QYgnS5LqVts6qxpHAgyqoHcKhViZGYXFW1roZ1bhkC53lZ-3bnJ2e34yUD9n23TEtttXptWxmG_ub2IEmyZKsRGZalCItZACg3ySDeubouFnOxaZzRIMIMQJiPx6nfDiKkVa0uKzRGiNTCIK5pGSfDhqVvx-vjrmuevbg6OT8DisPxkHJD4MjsFIFYlmqAPpeUxImq10BlT5is1vrO-4cIfHJx_rvfeubqDkAACC5eZ7NAmGvFYGYqFlosp7z2qEr1hBjoRFqOddF6vj0d966hURw9RCIQNcwNsXoShER_959-Mbv_lT_xE9_51jv_5a__7pHqUq3vZHfv5Or9q9yorqlM9HlRITxczxcXG2I5TPPTly4Io01UxpoQWaVMexZucpqXWdXda9M2jlrN9Oi5TV2Xh7b98PKFWdRFSaAW4-wptUCiRWvCw_GaAtz85vrQdX1O2DXJVTd9e3sYuyzj3T2zgJWG5aCzAxZ3EVIPgfjmO1NOmBmXpd4_Obkt86RqVrVsIksNuL1dEkNUIyFpm4d9ToiOfHM8XN0cc5PMAj0AMQBo1QZHBAIza_UV1xBIgMFCzEkYOAmsmwQPAxchThTmWdJaOqfMAb6WH9SM2U9PBlUQkYqQW-lSjoClqruzIKGsGQAkCHciAvdYp_531UVHX-OkjoEBvi6HVvDe3TYjwkzXLnqsf8rMEJBYvZTL8f29_vJv_AG4_X__6394nMe5LONxZorioebsYLrgQlmM9bD14jcxj4eb6e2zR-eHcTx-OKA0cnYCrJg3__j_8yupb195-eXNtvn61791crrR5RB6IICgsID-tLV5VoM5oC71cCyACTyGCGeoi27vDZfvXiHSvMz9rp2PM5kv03jx9FVEaURbkhDb315VSy3ktt1--5tvX7z8RHJLTfPoo4_f-dbz13_qhwOgGbZAuLl_YfOSdpuTLu8v908_-cpxP2HTnZ7sLt-6GU63V_vl7CNPlwWevHSaueEyLmPdnO-2TfZawBOIWPju3j3abY4vnkfbQrvpdyX3FHMnOaU-X_RPpuOURebjsU1yEqFaKIIkLYfFKebbywpw-Xx_tumuP7gdtifHmytp2oDIIuYGEZQYGUbVB33jHreXN_2mn6djSyKNcJZSKzUJdDnsx9YBrOzOd_1JBwgRFTjXpbZda-PRiM8ebS8_fH85HLb3zrpdp5NaLf1uU-YlkECgjnpycQ99PfTw7uH5OE5d33DbHd957_TivM6qi4ZqItZFCTm1OysmDa5XUXUDwkVrYBCFuR4PN2cPHoyHcXu6NfMo1dCxFXHTWmxNPKdU9XjYH5GFs_z2v_iNl1_9GIVPx_3Qb6Z5QsSm7a_3z47tycn9k_Mn57_5hX_xxic-Idi-eOe9J-e7cDOAqJGJ6ry8_rGPfv4Ln_9jP_bHUsJq-vTxk69-42vf_-YbpehKwXJVJwenaupm-8NRiHObHj64f3l92zRdURderdmwqJbqAIu7T8e5zWIWiGEKbh4Qy7hgkt1m03ZeayGJ28vjWJYABEY_WikGKx2HolZ1U05cFgVENVsNm-Dujl5KsCCFmSEComs1IDB1JkRYOXxIQnUpiBIIw2aT-k5Vz7ZDmH76-7-_EYygscxjrWreBTHCshQRLhqHuVQPm5a-SW7lfNe5Gya-uhqXatNSUtfWWQMAgUKhriNmoMRkDmvFv4DVulDmvsmAIczPrl4wsplpWAIMU606ziXMy1JEJBCsahaCCDP3ICRyDyBPiVW9mgmxunoAY6pLTX1LiADoYOuKNjzcAwCYpSwlt7kWFSFzVzdhCQMAmaepaYSIP_uZ7_vP_tZ_lYS0OLEAT5zy__p_8T-Z9pf_-d_5e69_9JMF7OLhK2--_tTMieP5zeV2NyhE09ZSalRcZiWKsmhKEgCqgXecwwUZ3Zx47Sm7W7CQry1Gc9fIORMRmAGC1kqysnHWNzdYBLghYiklNa0DgHkwEYBZJWQWmo6LZEmJQatVeO0TH33_298KdmZx1XBgIgInCy2FcwLVdTAf4Qi8lsos7C5zAYiIQKi1cuJaiqRkK51QyN2ZCZx1PeohcBItKjlrXSiREnKb3Cw1jZkBAjHdGeIDpMlNNyzzRISc8iqxvv_k6fXNs_lwbDb9OC3bcXzjldcOuxud9vdOd9u-HYSqEAHxeqUjMqsrJuT8pD-O1mZxj6jet03TJmAm8HleckqbTbe-PG5uj12TC6pV7dpGl7lhZo5dP_Rt0wjPZc45VfXcNmHhhtXc3CTJ-tycx_2Di3uuHhE58ThVIgwEcKpea3jqGjQnWBc-rODAqFol6iwZBZumbSmhuXZtOtneI8LDNL355kullIt7F8f59vL9F-fn_dA390-3XZu---33PvnGS7fzPO-Ptwi7Tc_MBLiMy-PHF88ur5dSm9wO3RLuuWnU9fbFbW4bVVnTN90whDoJ1sqH2xEN2XHdL4ZBMFYriYTR5qm0MjgiMglyKaUZdiRzmKYmR_iylGHYEM9eptz3rr7eqpkwwpCxuksSDAOA74lUGbG4aZi2_abOlyRoVklEawUi85CEZORWPNzKnPqBmNQqS8PCgXr5_Fk_9GUpWkuWHBFMWMa5ZkEEDCfClJplPKa2JyLXxSzcDctk6oEujXg1SbRMCzCvXqaVRnDcHwI7h_jw8r3Npl_mhQjbRo7HPSK4Q9-3m6GfphlyIKED5CRWDRxTTu8_uyqqQ9e8ezV6VICgiMR5rmrggYAITLisjvTwjDSXIojVdf7mM1XbT4dmk_vdMI4TsuxvrzebLXK6fP_DtkmMpMtSwZuUPDCJeAFooKVmiQKCqrbZbl66eKjFhmGTB9ECgKCliiQCrHUZrTAJW5RS1bQSkhM4rB2ApS7d0I7HqlpN_fLtS9okc6TVdgxQl9DbEdNcAC31ECph_-WvfnXYbD710uO_cXL6n3zhK2-9-6LJZMuyHfrtw5YhTjr58Prw_Gp2sJMLAAdKzBk5zBHGYrlJKITomzZTYkx09cJQmALLUskjURFJy-1he7YRSvdPz_e3R6BAACA3qOhSQinFNC1WVQSqR5uFycNgu-kbktv5EODIonXcTzMnaXNmhBS0lIoetegwcCxaIHJur27HJHiriyM5VPKAFJKIwg-HoozgWMsyFTuZlRh3my7l5iMvnb773vvEuJaGhYgYAUG_15BGJorgFR8VQUyMlAXWRNw61TD1lBgQgyELJWEUDLMwQCJAIMKm6zQiXMOsadPQtWsJGYWWqWCARzBxgAHiWl0CAL7719cTNSEQBQgTEQP4HfFoLawRAZoVAyZc0VUEEbAfy2_9xu_8B_-Xv_32O3-oQcRcjwlCuG0eP9xi1ZbZ6vHm3ctqkVLS2R-8vN2k7Wd-7I1Oulcuhj_49oc_-XN_7Euf_51xHk-ePPh__9I_GradBmMuLME5v_PsfartLLVTVIN5cU4shovOidPw-Il-8LwjiqVGtB6IEdW1PxnmF4cyzW3HYRFB0rJQrsdy8err1_P48JOv5qk41HGaybwucz9sP_6DP_DhW2_t9ze7dqsUt5fT-cMLdC8KWiaiIWq0w8YWIMjbe-fzVEjatM2ExkOXu3y4nmzTbS_ODDxl77oWIArAi3euH7-cPICE-2FDOWmZWSTaTgL6JqNw7sHVc-4JaRCxqjBLalqtWmpFTrkbEP3m6krHm_PXX5bne0JwJEAHjMPNzTAMt9fPtic7V82tgMODB2fzcWradnu-C_D7r7129cEHXuYPv_32K5_62NVzQmzDyI7XiJiHrS616ZoyzYsvkhuz2nZdlnxzefPwtZc__O677tENeT-hqveNjB982J7uuEkN4XKc2jbVgHkqbSdpaLBJUMu9BxelzAn6tmXwWOZ5O5xFtZQFw9HDijJzyr3WSC2Nt7dBJh6qNfdZqy7TxClDqAMBEksqVpk5ECPBEjMVmZciDIer23gjSUJIMs3HYbuZ5iJNomkjXWfVd5vTFx8-D-Dq1ry4TQnnuSaR2dzMMKATZoLLy2fDcIoZxXGplYNrVFAnQANH5BrmHqqeUzJTBGzazES342FeUte2200XWi18Px6rWiPMRKHm4UV9Bel6eG6zWkhCTtxkBkI8lU7tcDyoR9duCAXU3AyRmTnnYTzO0LogGwkg1xX-j0jESOjqd2WesCSyvs1rXbIkFo6VzyYsKY3TVM3seGzafim1HKYf-FMf48UOx-X65jguFSG4KgYgs6rNRUv1camYaGizK9w73aHBVPT51XHYdpTzcT-GsFVlAjUtVR2jzajh47xQUCIUx6KmCNwLI1V3pARg81TKXNKWMZwRCaCqEigTLWpmbhBqVudCBIio5nc91GKAZivt1G1NOpgpIhGiVg33pm1dQ62u2RVmDnPJQhCl6MnF6TxXnSdKwoBDv9FleuPRyX_27AXD0mGTAprze__2__zfXPa3_85_8P9oT07-yl_-6b_z939jPM6PX3m0UpG_-633mqG1SzV1AKckNs8RQVmWeTGrRAEBWZqyLMARFkBgVSURIoQZfW8TG2aBjkjFliTsHoFktUYEha_hag8PdWJ2VEQHRBJeDtOw7RmxmnFmIjAzV339U2_81j_5B4Cs1VLfhdpSZgRADBAEDVfFCI9IIsGEFuBm4SiitRIFwh2mx81xhUeJuFYmJm7VF5LGtaxwpUAOd0hMRNJwnVUhwpHXyLg07sqN3B0FmYTlOO67fjMeDtK3ANBwXuoxdV1_koTg_um9B_fP94eb0037sU-9kkKvrw5NptNtK0iS2IoJcRJmipNNh06hcx7aw34CBEIbut0HHz4_OdnVpd47PT3M027o9uMiwompSY30_c2xaK2IEeYnu3tdJleNiP1h8gjOaVxmdVumqo5gy7bvcm4Kl03XaNUPPnzx-NHDRUckBOJGCJmZ4LDMqo6i_W4D5rt73bL3BCBCuDnf3tweG0nP3n92fu8sNfm4P3Z99_j8QnK-2l_fXF_vzobtNrdN053x5c2-G_nNjz5dlul82-euu7q-zXkgyADwQz_0sV__9T94442n77zzYjzuu669vT0IRJ8yn-8O18d2GObj6B4R1qTMDbnVk103728tCjOZgeSkUdcqZ4Qjo2pJTXY1RKDE0-GmHYb59hARAB7EU5lSm6xaXWYA9AgGCl-HHOBIqwyVkJipLrXNrREjOhKbVWlardMy3jabE2Yqy5JSclMAWl2i6l6mPYvUeXbO4RUIluO4OXkEcYkk7h7VgSjQYyXhEImI6SIsXrVv-turmyBi5lrGWLmMFkWtS8N8nJjQq2PTRJ2BiYhyylcfPt-cnBwOB0IOiMSEECJcj8eWGQjaprm9ud2dnZrrsiC4065zh6-_9a2l_tjTe_d_960PgLm6VfdEWN0jDIKPhxEIc5N1WQLCwA2CAe9d3HvrO295lK7vtLqbtU0mIpR8e3t9enYvPzy_2t-6OYSXZUVWo5BUrxKSIzZDv9fS9en66vY042L6yoPzjlhBnakC1Fo5SfY0L2rotEIEAsLRLIggKIihHi2LJs6Hm0kEiUiPDhRJhDUcSJIDVF3AKR_nw3bb6QK3df5__vJv_twPvP5Tf-SNv_7zP3T54ub9q_lL331fTa_HQki3Ewi3Z-cyzssqCnSE1Cat5sW6tnFVBNKqSBJIN1dTNzSSoZQ6TdUjrm5ut8PALIfbsR_6pmuXpRr4PJfUtdM8o9eVj1msBroxW1kwAiJ2XSsIaUgg_eXV8ThOTZubtp-OM5MLQd80khKulzSgcSnCEBCSRK3q4siEjE3TXJy0ElCKVVWk1OSUsZG8VLVt01WLm2k-Lvrg4iyEP_jgOQuBoVsQAa3gWUBGdMQwd7dmnSgAzCW6PjUJwYORSIAIzQAJkWilYJkZ49pyWCEPQQAiGA4pZwBguGt4MKGZ0zpmZQ4AWj1lK7EBgRCAyKpnQWFZvz4QRDis86kIVUUmJAYA9wCkWgqxtCA_-aM_8iOf_cx0PX7prff__i__9n_47_61_RxiGoGJkLLQUv_JF771z77wlX_jr_9xqhwIxISBCOiqRFRVf_7nf0pYlqp_-nM_-zf-p_8eNoIKkpHcbFn0edG5jjrX_TGA-2ZT7IDqk-H5K7vTk2V_2Btj06ez185efPvSDQAZWA6jX9w7ffGd97cXGwxgSB5wfL6_eHz_-Nazm6s_HOQ1K940S9OeIzc17aTv_vl_8Q-efuT1P_jy759dJEZ4cXXY3Tsfzk4Ot0vb9af3z-Z5Oexvl2PJIFm4HTqro0n1qsRls83gDgRalZJEimFonr9_CVbmYz07Owl3zjIdDhhB4F2fbM6HacLgZtOkVua5StOaBqYWwnJuyswWHEFNm05PT272MB60H05u3vvg4uRRILgOxaAuswjWMm-3O2GYx7oscz8M03FKXaqLH26PFHB272KpevXOh10ML273ItTlbGb1OG8enc9LTHPphnazyXPRZdLMedP343hAlOlmgujbYbvAsc5l2PW1mpfaNDlpVFcMTAjN0JW51FmJmNp2f3UduKc7PZDM07jZ7gIgKICAEmMQJJA2q9Vuu7Mo-8Nt2w_LsYoIMk5zoZRUKyaO8LooYGseqJS7E6xzmFLm43R0WC98PNeaITjLdtN9550PH-d8en6CXq4-fFaxfO3r3_noH_20GUfUouCliGRGrIs9efzyF774xZ_62T9hc3EHYb6-vQnJIlAWgwhfx9ABTMgkVt2LL2MBAHcsUGOJJJBFwnyQtPc4TgsjY4cAsWLdAIEzIToiuDoSsbCpCxIl9NxOWty8bRpMUOapqjEnJmnarmotpXDmVQFmEMjfO-wyBQKEkXRhBrAeMVNEEK0hbMpJpnHebDZdTpQSMwHGo1efwKS1RjGbpoIYRFKW0g-DUZQC-2NZ-ZkUeBiX09PNurc5jKVtk6rP0zIM_bQUSqnWxdxYkDyEpbpHgLmZOgWknMZ5ySkTicYEgBDoYCw8HeZN2xcryzwjhlUHq8CiVpjQI4jddSULgRkIcYHq5sSkc0WmFboJBTAQwhkBU6q1EIQggbqCJ04R4V4dQVLSYgzgJFXj4596Y56vP_rJN9__4IWzp6HP5h9_8-N__V_973x4-96_83_4jy1J223-0a98rY7ze2-_N43Vc72al-eXz4f0cJwm10KMXpV41erqOqYxNwRogCsihQOTu1oEBYQHo6eUzAwiAsKqIqMQoyO4C6GZkXAEsHCsdCAPAPTF0DkwwNdZEgIiA5kqiocHs_zwpz_-S1_9-uQiCUIFAxMlK8UTqrpHsAdzBlewCoBBwJTMKyGKJLNiVhnJw4U5XM3vrgEAaL4wk2qJ8JRzXeru8cX4wTNmNtWUk-QUYO6B4JzEA1LOEcEsAaFVc9Nth-00Hnfn56pFmubs_sXV5SXllPuhjGPq0-a06xO_9vSeLXOb05P790DQVdtNDncAL2UxsyxiAUmSNjmqEeL56WZZ1IpenO4W1YYoJRqkPdzOpcxdmxyAcM34-WZojsdxNwxDQ2AKhEJUqjmE18Ip1QU8lvOz7bIUZgIru-1QS1mKnd87VVd3Q6b3L28e3DtBcLSoiwtRliSM7nH1bN8gHaaJf-Bn__z-en9x_1zrkpvm3sVpgGdJ6IEURRUxnjx4NLTcpKaW-eH9C2E43fZIce9sIymNN_vN0C_zyMTjNHdtMo3Npsltq2qcEMIdUTL3u15NOWHbtSlJbnJOAuEO9OM_9APf_fbb01yZ2NVqUWCGIJ3ntu99dTczma8lj1SLpraxqrIqgRhLVWFGdyI2U0TklftjBhgEIUQAUZeFRdZJpy4FwBFpnW0gOAQgrkZhJGAkVNW1d4gEupS82dlSiKlte_AI94snj_aXV45AiEDsroxRS8ld52FETBEOwYmHTX97OKyQYKQgpLoUZrzrqEdAuCCbzgF3OKs2t8fDTZKETGYFYC3n1CxMSEy0PgQcHIEhnAgoCFABcdHpx3_w-7Lh57_x9XCeFwVwrUrIFsYsKUkpJRwQ7lTw4YoZX3r04OWnj955drkYHPcjMZs5MqvWzHJzfXP__v1nl1cWCoGpaRHQzUUw82acJg-IoF13Pk77pu-7NoVNrz96ZDeH6_3eHMtq6CDaYqumEO4M7BxA4UYIQlyKMt-NBiCB1hrmYZa6TIC-zEESYSvuaZorzB5W2p6XxatZMF5N0xe_-k3Pqe263cn2Y08efvTx2eN7Z7fHpSyacjZ1dxg2nakxQJmrRUiArGBhhNQKMYzT0uSUkoASIKBAhAtiLVWalLpuXpbcZErEq-Nm3TJFEFM4MqEVRwAKQKRErKoJgBI0bRtLnWqJgKbhcEUIcxDilBgEIYIQFP30dHN7dcxtSiKqLiwW-urHLvxG66L7afHArkkAcJxrTmQWXStlsbKURpJ6MNC2b8NiroUSmt4N4daBylqtZgxkYuGASEmEVilYBARSIBIFMCMjAUCYmZq5O8Ja23L39WW8gvlpNfh61Kpr5HetIRARIa6vurX4RUhIwAA5p5SY1n5wOGKo1RUfChB3eA1EWgHVYYDhVsysuFd3avOTV87euNd_5Stfs8Dtyam6qsJ8HD3S3_t7f_sv__k_S0BqqIuFIRiae9SoVRHQ3G_2BwR45vFL_80_z92WWaxWAAoPDwBBtKWWMh-ndtdoMUT0kgAnsqIayBCS-q6r8-JAvBtARHphxmdvPXvw0VfGm9vcZ0nStDkSgdnZxdPvfOfF6ZPTef9-256mPo-3V1dXz599-4Pv_9yPvfONt4azs_ZkK72UfR3u7dxgc3aSU25Oejdz825oQnE9Y91cXZ2en-xv9maUV7b9WBLb4dmh65gthr5F4vn2tk6TuluJ1AjMFTjq4t12cK0k6OAoSbIQ43JcEoOWhTg5MDEKaARyxzbVruWmaQ4vbptM2CRXDdPQSH07j9o1ST0ocClTv-1Noc7HrmvQrXq4Q9d2JFjHySaDOkvOnJrMlJo2MY03tznfaePM6-m9U7NwiHbTjdNIzIC4zOrzEo4pZ_QgoTVD1rRpvjk0JyfLNPqinJvw4sUAKTe53Zwth6PkLJl9XS4RHca57dsIDozb2_3ZyUmoLVPdXZzXGk3fWdgyLtisrjxgEs6JgLIgKmUQP-4DvZayOz9nypCikZZTkiw6zqenJ6o2DF3b5Zur2_f-8K3vvvPOT3_uswJJwW2xCioEHgBgfdu-8-47yzzthl1mGJr2n33pd15_6QE4RcQ4zURsFqpmbqpmCOMyAaAFHA7HIGJEIV65-w5YizmERazyFgBGZIhAAnWHwJQ455SYvWodl1LVQwHI3HE9HYqg8Hps8ohSKueESIjIbWPmIgJuEFHVmQUghFG1IgEi1aXkLGpGgMRk5klk6DuRVMxSzgFwtts8ON0dxmW2NceBHm4GkiQcbo9TNWNCJEyc5rKc9q1qlGqHsSyq1TEQq6o5IMa8lLZp2i5lTkhoAMs4u1kxJUFk7rfd6WYgoP3-oEGHaalVtaqZjeOIEMfDBBi1FkI0qIwMEDoVQdGleEQirmoAviwFaN1q-qoVksRaKzp4OEQwEyKv7Q0W8XBiAAB3YMGu7fttv3u4K_P00pNH73_r7T53v_jTP3zv7PzHPvPpH_rMp_-Vz_30z332j3znvXf_rX_n_6wZVNqr59eHaRJyG_VP_9yPDjk7-q_-5h_s53pzeZta1rBSFMwZwB2WaWYiN7P1k9pNzb6nLTFmoQALQyIkXsnKiCvcH5hEtYowBLirmzKSmRHSmsxZMxemSuHr-coRw8FDGdFV7z19cnV9-fyDF4AIYYwkWdQUV03NHbouOPH6Yrsz-aARokfk3IYZInJuw4yJiNE8JGdch1ABXdsHAqyKGwcR8Tu0KKaUTSsjubtIxtW-YMA5Dfcu3CoEv_qx191snue269Ss357UZTo5PVe11HAv_PDh-aOLewng3tnm4mQzdLlNlIRy0wpi34pOU5IciEuta981iYDFrCU1Sc1DdbvtrFrKuZTatU0AWDXOKSKatncHRGtTiwSbhs6GTohFZKk2rooPj2qr6IgCA8LqUje74fykT7mZF01ZlmpMxKtMOsk818M4pSwR-ODeyf528mIAlBtuNg3_wOf-TLfpmqYpWp--_Pj5h5dZsqvutr26qpprvbg4FcbDcTw92d4_2d3eXN_bbaZpOemaYegA4N133n94cZpYLq9umyad7DbCXOe5mAKLmbo5InVdBwA5N6F6cnoK7hHaNHk61ievPv7ud74brm0zhMFKkmJ3A18bS8yIjGYe7k3fm5qju2O49_2mLAXBIxwCmZPFqoKGsLommtffR045zBhBTVl4DQOZWdN2piun0AmZUjKtgE6SImzlBTGRViemQGDC0MjdUOpiDqnhMi-IlHKvuhAiBiAJ3q0drNTSdJ1DuGkAuplw0nlqm8ZKseq5yW4KSFYLuEc4EqxPi1qLqotITrkuS5gSEAG4ahA5QLgJooYlTiToVsui1cEDPvHKq-cn_e987VtTNUByd62emMw1HIPWRk0qywSAQY4eHvSnfupH_-E_-nx7sj0cRwsFB4AQwKXY6_eeXB6uX1y-ePm1147HMdyFJDEh0XEqi88sspRFPWafnVHaoWi9fPeDT3_09fN7m3cvb8xMctKqxW0JNVrbm-j2PUqCWZuzgRNhLZZzqovWucDK8p9tVcYuFuCsVUNAwxGxzIfw7AjImQjd4_Y4f_P951_4xoe___7zq1Efnm_uDf3HX77_yunmnavrw1wjvBYDV8FwDQTpEyYEIkCiYnY8Tg5QbNnfXtdaETEnbKVx83ZoOUKIJbdWVQi6Ji_zUjGQk6upaiAAkaRMSZjlpN9OqkupSjDuS865a1s1NSS_Q-gkh0gQWqsw1UXbLPNc-17WLGZgmK8Wdn_t7CSAa6gDqcY0681xVgtEblgIWRjONl0gXt-OL_bH966vn1xcnO6GUqtVJ0YmZkG8S9MDIDCxuxMhE6wOG3c3D0QkEiIQXq3p6O6Od78xAiwrqmMNgngQkDATY1hYrJlXYiFcX3QId5UpWReV2HUNAAgTMyOiw0r2hwhEwgh0QI_vZYcQzDUgPDyQ11LBGhMC9NN7508_-uSrX_vW-29_8OTJk6D4ztXNP_mNL5xR85kf-RQEBrgHMPMqrzTTiCBCXqdeju89v_1Hn_8toIZyPhxnpgSJqE3zfgTTCDxc6-biZKma-01dyu6iL7OHNMtUI0CGxgkUHJkBsBbDWqbDcvJ0V8qYhr4_OfE-e0DTZG7S2x--uNjScPrIzLnrCPHi0f3n73zn5ddfuvzgqpK03dYd9_s9E3fDjojJUY-6Odsdbg8pEROnLKixa4amSXMZ29ONuwlg2xBoBZLNbrtMBsS61KSLWpxenB7Hse97AE996x4kQeFJhJsGiRJiqOukTcYyz9K2VbXLDVq1atxKNwzLWAjp5HwT7ofLfb8boMbQ5_70xGbt-86qMUtVxwDJWecSVVPfIMm4H6sqSVumiSLaBg_jLXcnkpvqlli6bX88Tt22J-b1tMEiAJgTozTldt_seje3ZU5NQuK1oxkUsVQwRRGdZ2Je9zy1VK8LsZuBp8RZgpwlcSdatdv2h_3EWVik6ZpxPzU5N30X4AbRbYYklJKYqTpkTm2T7LAwE4JH1TBn9OV4zSKbe6eQ-OWPflySLUuRlNeIDjHf3h5ntUbyZji7urn91te-86M_-kND3zRDNy4LA2IQMyYSreX-Ky99461vvvmJT5rOIukPvvPuK48v9lNRN4NY1EotQFiLrtOjudi8lJzTsigJatGubdeIOSBWDUBc3SB3wToEFgrC9UQuOQGSqtaqGqqmzDkEa61ay9onILxL_JVSVsY_IsCa_omAiDIXc2dmD29y0loJ0R1W5HF4IKBDNG0jKRGn1DbmKjlpWG7Sxenp6fn2-dWtqjKLVpWc3L3psy56OE7hjoSEgozLsvRtNoCiOhedax3nUs0AkBDrshzGabcdwqlr0lz0cHsUYWQy99x2ZrodeiGpZgZ-fX17OIzLvJSipbq7kkaY6TrZMFsDntUUI-h7M68wNwVAt6pMWGulO0k5uGktykncdB2KWLW7D5870J9HRBI6P9_NtxNGNM1Q5lGX6aTb_MX_1i_8wCc_ejJsPnhxveubgvRL_-if_u3_6h9Oas-uShhcHQ5tg_fPNtntT__Cj3NBNf29777_9gc3tzeH8ChFzaIs9c6jGEgAphqmwrReBAhJkB19jSRpOATcLXhrlZQdDNbqRripBiETewREsIhpRaRaKwAiA4Cjm7lTEvBQrSlxVFPzz_2pn_rir35BzVlWlSU4IgSYKgYSYrgicwQQcwQAY3ULX7HjK0PCAQFpxW45EbsHBAY5IocDJ0Hi6kbEKSctJXfdMhXOgohmARj99tTduWk4ZU4JJdmyUE5NbmotAb7ZnY6HfTdswO3Ro4e54TIXLf7G66_GvDy4f3pxtu0TXZxtbalNYhKWRsAcA9q2jcBSNSVGwlpKTsnUEKlpc9dmEQYPiDALlqSuy7S0TVOqppyGtiUmK-YQzHj_7HTocikaCFWLqXdNnpcKIod5TizLNA_9cLU_nO0227Y7LgsRRQAhXt8eNajMpdRwc6Nouw4cdEWUEzx4sJnGwgb8s3_pXyOm8EiUxulwcr4ry5KEdie7rm-1VF90sfkjr310f3v98MH5Sd8x03bTp5RzTklkWsrD-_civGlks-nMdOiaeZpPNpu52nF_EBYttWnatm-W40KIXZuhFjN19ZwSUJxf7K6f3UDEPC25lcN-JOGUpIwLCBKhTiV1XV1KuMGqoQVcxhERLJRIwhzcHJwZndBMiWF9urNkKyUCA2PlmKWc61IktVbn8ABCSUlLYQFAYmGrBSi4aSlgNX8BuEhyBxLxWu8kGoS61O3J2Xw8BkCEIoKr1lokJXNFZnQ38O3uZDzuy2JrzE61SG7KVEkYONyUGCPCv8fECozEqdts9jfXSKtDSa0qBUREl7sIIyISWpZFUk5CjMKJvQYnSV3nZSavH3_55Q-urt57dqvrZw8CM4aHFQ0ECKAVcqGambq-ncal4_jwdtyPo-R2HpdpLBBwOJTcNi_GW612c3NQd10qMU_7KSiIk4NVd6tOTMd6I9xp-FKr16qm33rr2ac_9cZ5v3nvg-cBUWtlxHFZzAEQ6lJ59VitHjdK4IYQtdbFFQkJPWo1UMwsjFUVGIGd0CHcDQDQNTGBk6HkCNCyzHOdF6hqCHR5XL701jv_5Ktv_cpbL5pN98Mfe-Vjjy5-_73nGSLMzIAldZtkYYepzlUdwsNdQbVWtXBw96UUdzRHd7ra165PDk7uFK6LAwSnPE3F1edpwQCLNeEYCAiAGoWEPIKIwXFeFJhS01o1c3VzdUeMJouIlMUSEydCAzXLOSVOpRSO6Nr04Gx3MnR1KZwlN4wIwBiIRKTu5gGIQ9s2glONlJqm5dPtbpwtzM9P-oAopa4t3MQchEDBiIRBsTodY52jrBqXdfS-QgA9VoATBCB4mEc1jUBbP9PXgX4ErpZygPB1ZQ9E0OUmMadG7uy-brlJCYmIVkgo0t1Axy0AwiEA0Hyd_6_03lgDfu7m-i8pq4SB7iCQnMgNnjx-cP_iYjwef_9b733_608-8frTNz_-6f_d__U__ekf_2ypldwJCDwYV-ooMKGHghun_PbV9T_-1d_WisF8OO5BeNidEMDx-U3bJDeszqf3ztUNwIXl-v0Xuyf346Q5HhYz04rDaSu5kSSpZah1vL7MOU_jlNs-DxsgDBIQcYsHT59Ol-9uNluklIch5qlth77ffvCdbyQSbrpS9ekrT220h689vnn-vD85SUzdZnA1hBjrzDmpB5Ms8-IGbdtcP3_R9Vsk0lITJBReRoewEta2HRJL0-73B2YBjwjzaklWO3vY0SSJNI1EtCIAoIuCl3BHzpwoc2q69mAFJOd-yDkZOBNL00lKy1TrOEcEoSAioOckpgUAkSlzggBOCVn6s_tNx13b5k0z7femtSGRzZkhD0OPyObWdr3GAiRnp0_MRjBou3a8vtVwSrz-ELhpA9yrc-4AgRwgDCFSbgMVmXUuzAnCWbrji-t2k0yj2WyReH9z02-3bdvPc-23fTiae-4aZhGROpXcD9P-psx1ONmZOafU5ubmZt6dDVANzdzMq87zolVTaurxqtt00qXvfuvt63ff_dy_8ifRfZpLvx1YiBHPT8-uXlwlEe54vr0q8_Tzf-bPMBowL3O5O5m7h1nTpCSyvz1ata7tkOno07ZttEJ1DQ9EVPdaVd3MQ83MQ6sFxdB3ZanuykJNSrVUx7CIYuoWSaQu1SLUHRBZRDWICBO6W9V6WIpwdoSiuvJGrdZAVL1zbi5LVTdmXqaCGIhkZrWqm7MwIgpyrUoMCLB-ILjduflMXZj73eZ4mIahr9UQUIjM4_RkW-fKScqkJIgAx8PMTO6w3fb7w9QPXUpCSPdO-uNU3NzR94dxLjWIi-raoMD1mAuQMp-f76BarTYvi0EgcUC0fTeO08lu2PQdAI7TdDiOh8MhKDxWumkFdS1FEru7A2g1ZkQM9ZgnI8EAB0SIiHBiXCGnfocQJQgHDFNbzYxuxpQCnZnBDehOo8kJ-rZpUYCYKMbjXsAJ6Xy3_akf_8Hn--P_-N_-3__GV7_62psv_c2_-bf-xee_jJJr-O2H1xraCBPn1z_6Wjb9uT_2IzraBx88_8LvfevqOCrEMi1EpBZuUacS4arOAm7KAF4NeCWsOQrGConGuDvKAyLgCvx3wHVTFKFIiEncLdTWFBAixtoAAgwE14rEZiStuFYiAK0Rsbt3L2N9_91npRoTMmBEoAgQUDiYr1hUX_0Wq7OAaNXV0_eunhBrzQFQ2N25bcIDkYQFgQIhZQkkJDQ3AGcR6jqCtWLGzLKaHIkoiB2g69qUxAFSboiBhU7O7qVMnFIiSgTn9-7dXh1e-_hrFw-GJsujB2cfeen-0KWTTXMydLUqExBRFgYPRE7CQBSBpdSUSIgwoprlxClJeKwgIyZqskSEA5gFEQVgOCRi99BakZlYzk8GjiCknPP1flzUUuJt2-zHOs4zEVs4It6_OLt30i-LHsYCgvNS3Kzru6rWdkmLHccSzNW0TEutZdN3QDjN6urjUvkn_-y_KolS5izRD8N4GDVs07a11CePHiPHNB_u339wfX35Iz_4qasX101KfZ_7rs1Cp7uOkUpZwq1rmnkpm65x8xVEKgI5p1oMMXLOqooRQ98JAwYuyzJsByuaG865mcZlOk6EvD_sPcwjalEmzJKmaUEK4QwIJGJVrS7D5qTMhYXcqhXrtjsPV6sIUeeS2sG8WlVmcndGBkI1ZQI3R0BiCXd3Y-K19AJE68m4lpKbNuVc5wKAKTdEXEohYmZCQG4aLWUly-am9aoODqvuGyHUiIJEtKokMbMACINhu50OB16PaLou2qiWihg6Fmo4wJkSODIC8h0rvd9tp3EECAx0MwIgJPBQr8RpriU34obSpGWZtfhm2yVO853-0K3On3nzY0PffOX337LgWowRI-5u0nf2WKAAMzMibxr5G__6X_rHv_bbruXqdiq1SGrmaXGM1HBZKqBPU9nuduM4bnab8TghY9XIGTGCgyWRBwgkRrBiQBC24uDo2dW7n_30x3d9dz1Pbu4Rq4TczINj7XebOyJrxKZpzTwQNUIrCEbA2klNBCicTRWBGHAFzLsFITB7AETAxW6ry4xAxqEGs6oM-XB1i-7u5d0P91_-w_duonzuj7yJRC-u9-EQrq3wVMzRDf0u7x6BRLUsYM6ciFmLsWDX8WbbBpEpzHXiTFGt7zpO2LXJ3O4cVgQO7hZNSpmImFNK1Zwihpy5wXGcMmBwqCkANjmBuRukRiSxVU2ZyCKJQETfZa3rm6g_vzeoeq21mB4P5TiXcVYgBli5-oyIx7k-vyn7_VzcwIEztZnM1Cps-ubsZFgWDQiIlUO3holptQfwWucjAghcP3wRwz2AzNzcHcDMHWJlPyDcqbuYERCYEAJ8_RkiijARdE1GBATk9WYAkXIiosS0XhREkIgR1uMNhjsh-R0qdI2o0lrZYEYIDEAk8u-5vxApPDAQA9QNwCTxNudxKQgQBD_yI5_-3_z7__cf-sEfbJqW-Y5aTYHM7ODhNpcSwC8ub3_517_iLNKk26vbLrf3Hz067I82lZSFg88enEuieb9o9YdvPnz4kft1tOPiH7x_vd3lx6_fr9My3tyqARPo4cA5Tcdj2_eNtO3JFhzCvM0pHOs4jpfHs0fnh2kOQBJqUsfI3_3G79--ePaRT3_fXEYPODk7P71__8W7707748nJCTISo9YytJ2ZImPOyUzJwl2Xm33TbYIQqjc5cWC7EUNMTSakTdd7rXWeujYbkBftmgQhpuqqm2ET5hUgM0dEBNTJEJUyGkbCJIk4p8M4d13bbTtSD3cPSjmha9Nl1wDE3LVt187TEqpNzqsTahgaEgEC9yjTnJuGVpX4NKP5vc2mBqobIzUphxsnyZzm40RRiAiFmi5HhFmNwLZtCaBUJXcwZc5tI-GOQqlpynFxVbc1ieepFURAxtBainZtk7uGG16K7ja7JFRL7dqePNqmDTPTOFxd5bZjkeWwz6kBYk5tblJY-FLqXFwN21RDEbzW4stky3R7ffnmD__YS08efPsrX82SX_34pzmWy_3eq8sqCff48IPLYbu5d__8d3_rC48fPHjy6AkLW3VCz3dvOyIij7h48ODXfuULP_aD3384jmL47OqGCFZymgfaqtWOFZvr6sYsupSubU-H9vpmMre2bwmAife3I3jUap1kRPHwxGzmq8QEAMPCzeexZOY25f04u0dCqlURSM3cjYUBqZpptTW_V4ohrotbD8DwGurEhBzztBDTqjQGpLIsTAJAXT-UpaamzV0zjlPXDciohqf3d9fPDk2barUmJ3AChjY3TcO1KhERswAT47jUaS6lVhGaxiU1eZ5ms7AAoDXV7Vlk6Dp2FMHjcV4P4qUoEZtZ0zR926Ys0zKPx3HdXx72I6CQqtcyH68sGKoHuIMjQVQ1jXBjAgTXqmWVeq6fRKtYItzibgES7uvoc7XQEiGJ2BoOUV-HJ4L84NFLQ9dUj0Xnhw8fbPtU5vl_-N_7q5Piv_vv_c2vfeUP_vwv_snX723-8T_5YtNvrq73h-vbubjWUj36YZMb9lJ__md_WBwh8J_9xm8f5uU4FXA0s3GcV1o2IwCoVV17WOFxF7pxA0QNjVi7XGt4lZHJrCJxatKylJzF6x17be16wJ07DLWYSAowQqmmBM5JIhzMRSI81MvPfO6PfuHXvqiODIDu69dxhZRTmIMHC0MEIDIzBuH6LEFaTz4sCddYBRMirp4jBBdukAI8ct9hgAf03cbNUtsCrCVgEGZBquaImJsG3PqTnrI0TctZTC03rVnp-y1iPHj46PrFC8k8DO2Dh_evnn_44MH96fr64aP7WeSTH3vZITJy38jJ0AGG29ymXOeKRDmLMDUipWpAJMG-yR44TUtqxC2EMcIJKMKJQM0dcXWQByEAZs6H_X5oO1VPmU-GgRGY8XCc5lKGvgNActpPi5kicZPT6W7j83TS98eptA23OU0lXCMAWNJxLlfX027TisjhdmybLMzAdHtzTCmHAgvyj_7CL6aU5sN8_6V7pRatloQ2w4CEnBAJd9uhjqNO5eSkr6W88vKjZVnKcRr6tmGCCMZg5NykWqxrUk5Srdy_OB2PcxK-ud03Se7fPytLzYmXpWxPB2I47MecZdj0APzw0dmLD6601vBA4ekwt202M3Nr2xbA3RQCgCg8CEGLgggSA4KXGSMCA3OHEHVZcJU9BaxacoyqtVLKTHfKqXAnpghwdRYGM06tqua2B3MCiIDU9gixDpbUKiFbLRGOLMhSl3m9_a8no3meUt_ZvAgzBFo1dAfO5qta1Tanp7oUX-OYqoBETNzmMs8EgBjr4QohEDAwwgvn5KokpGZlWcA9S7pzJ2vltVXuzsQEqFpLKREmufHExKxVE_E03vzEZ37gdOi--JWvGqzNHKqlIGJERDUilAxgnjgaSWLwxsdeevbi6vKwv70ZDWmejkhQSiEhEbFq4VCtlGIIPE-TqRKTaSBSAGaR9bgJASziaO6hps5--bw48cdefXx9szctzCmq5yYDkC1mvnbFLMIByACYoc4LuOlUBHGpi2q4-y7laooI4dpQBqLjvqQ2rzB6SYkiGxQmOCyKCctUq9Xbq8M8T1W9qFsYEhxv5y_-_ts_-MmPPLwYrq4PnQASLnN1XUNegOZVjRMkyVaVBckhJSERkkTMq4s6YXatbdOERVFNSThJBCbGoqoaKQkHBMS8HAk5sWRBAodiKYlA5NyoGTOvAdwkKIl1qkygSw1wwMhJzi52xDDsui4n95iPy6xa1ShhBAahA5gBJiJGUz8utVQNIBTcDO3tfkkJ9uMiIodxRpK2lblqRJg7IqTEtCb0AZiQWP7ljihWHBCSr7J1WrXCaB4QiIQA5BCEyAgI0ae8poPW8Y0Qp5TAnUUIkBnw7g9xBWfZ-oUA4u5lGqrqEbpSNmJtFMS6e1gfD2qusCr7bF3rE5ODE6F5UAACWQRQrG56rY4EP_yZT3_pt77yO7_7Bx957dVGVreAAUIEOphVF4Tf-O0_-K2vf3eZzQM4rEkcYNPtIbeMFGB0dv9iPIwRpTvrE2bhLNw9-uyTfvHze9uhl42ks9PNJz71eht-_cH1y6-_XEb76A9_5ObD627obp592O82DJFY9lfXWsv504taCmISMA8XSm2X3vnG13_op3_2W9_4lhE8evpa8VK93l7uzx4_BLUy165rdVZB2Wy2CFjKpHNt2uby3d8_ffCScJqOU9c13batNULteBiHoXM3rVW1IHHViAidxpQySVpZ2qlJqt4MPQou4yKY3Iq7R2BiIsC26TCckpDGsN1QhJYqCG4mOQOAqjJJaoWRnKFpMlFqh64spcltYAgRcfSbjYIF0vnDR1cfPKMkkJNkaXKzcskcwBCEAdz7eiWzBQABAABJREFUvp-mRUtNOc3HxR3bLt9e3jRNW8tUD2PumpQS8YqnjCTCCTkTcR4P-93Jttaa2vb62bOcpYxLf7Z1o_3tse140w_7_TExu1Vabz534FrC3Hi1WufzJ4-0aHGvy4LoZZ6JoUaFLPM4CTEsRYi9jIfbm-__iR--_eD57371dx89ftQOm23b3F7fCgE12dTY1MBOTzaH6Xi4vfypn_jRw_EYwe6aSZiQ1miaGSFKl77wO1_-2BtvlHnej3NKLJzmaakGS_2e68ZWs2LMy3LWN0RsSFl4Xgo6pCTVfJzm9Z1-WBYSAQgC8ED3WEpNIrWaWxznmkS06lK1lKruqrqSUsCjqqvq-ma54-IzuBl4ALjVgkQk5OZ1LpwFA0SSmXk4IjEis6Qmi8judDcf5ybnpsucUjA2OU_T3GRxjb5J1VASJsGMcjxOScQV1dTUr69v1WMaKzIF0jjNEKRmZppz66EQkYQbkcRcLUqpnHL4Smk0JgaH3S4v1ZZxjsB5nqfZikUthcDLUsyBCYVYzVYWGYVr1dXYtU7117PE2rLAlfoXEOFZmrs0a6lICARmzpylkVBHDARCAkbM0nO_Kcuocz0ejz6Px2P5-c_9zPd__6t_6z_9-3_4rXeW8fZ_9G_9m_-r_9n_saTm5vIQYMt6Ls-5GG5PulLUS_mzf_wn0TA1_A_-4T8vzIdprloI0XWNAAWQ4xpwBDKrcWc4dRE089S2WjWlpLVArABVWvMIKSerzhTgAcwppbUe4Grr-N8BEd1rrINESQKIwhzqzB5u7Xbz6OWn3_rmd-5wsKpEhMwRxCIEEBZrqgcQEgsSWVUmioAwQ4iUJNyJhBDrom03WK14hwOKAG_6zTLPyJSYw8PNMFHKDA4sTUSlppEuEUsEUm66fnvc33pAGED4ZnfWduniwcW9-xf96UAWn_2h75uXKROen26226ZNedM0fd9s2_alx2d9kr5JSbhJKTwQSBIRY17P-AEs1LbNOJUAcgRXz02zKo1X5GuXG3UIt3Eqa7tGmM2UCYXZ1DZ9J-sFKNzcJeW51L5tb6fZPKTJxCIIu6EdUibh23FB9FpNA9V90Wqu1cLAgO4ORojYpHwcF07IyONUXI1_9i_8lXboura9_OB6t-0Ro2ma2_3-3sV5VA9zK_XexfnpvZN33373I6-95rZ40dOTzdmmm6baZ1a3oW9zk9omhZt7TOMsIpLl3v1NlqaVlBlVrekzC_dNSolTI2Uum-0OwAV5mud-6FQ9t_l4c5sa0armEYGckqm6h7SNaeEktc4emJqWiesyEzoGWQCnrMtCGKYmKUEYgIcqAErq7ui9Eb4iioUDVv8sIIsDgBsiQCgCxtp0vNviyZqBI4JaoxkG04IryUSrNJ27YRgiEJFZhBkzIxGAqQcF3bv34OryRUAQo9m6EGQMKLWCuRC7KiDGnVjS3CDcV0ESM6pplhxmhBQRd-uyCGJUNwA0ULdAxHBsmz5cPTwhEugPfOyVi9OT3_n6N4-LLQq1lgBAgjAnZgSAiKah49XhL_zVP_exV176nd_6vcvb4_Or27HOyFxnFSSRPB2Lm4oIi3hAKZUTQ-AyLyjo7m3bqXupZhGMtELQGNAAOGfCvDsdbj64evrKvfPz7Zd-920kI8mqse26WquHWxiwuCoiAFJ4mOqaH2VCLTUiMAwcLSgQ3IPWWpuA3bWJnYTCS0CwUDHjQKsKAREGbrY-yRitRtvlk017fXn7Y594_Sc_88p703G6Oc61BjIzNl3nQMvsjJyIkHkuFRAMgJghgknobhqhzBQBOaVYXVWBfdNkpAWBkmQkESYR82gzN40IMUGox-GgKd3t8lRjriU1Eu7g0G-6ppOqWtGaJnVdV8a67fssTIa1qoGbGxO7UxCGh3q4-lJq4lSqE0BKiZjA4eYw3b-_ub0pFcLv5u9ByMPQE3i4NVkgAlbgDq6TSlz_1iGIKAIDUNWB0CwC8C4ETLR2fIXvumOyYoLW6yYjE2VhYiQkWlH-gBGATEBIQOZRS2UWIkEMFlYNM696Zx4NgHAPd1i9AxF3QrEADFhtAIhrLsjDAhHibhXk6-Ns_QeCqVj9xJsf-ehHX_3mt9_-tS_8zic_8aawEGj1IMAAaFPzH_4nf2cqVoFU6-muW8YChIycOJurV8r96fMX70uTTk5P3awsKsHn2_vjB1c3z19kxLKUH_9j339vaLumf_z4pYap2wxV4_L5gYW2u9Oua82ds1w_v0XkB0_Pp-NiS713cRHuXded3bv31pd_6_6jl26ur_q-v3j0xE0BAZIfbvabflCt_aYry-RWm9zkJBFR5qlr2uvnx7OLC0nCjWgFD06dhHmz6ZClzoWJpmmCxBVA2tbLnCQRMzfiqrguypnDHAmXaQpwDQ-A3KRw3AztUrQfOrdgQula9-j7Pre5agFkgvCAYejUFISAuW2atstEGCvXDxyRS619vxGCaTqMNyOESx4s1KvuToYArFopESO5GrhzypgYyFPK434UQW5zKYUQ5_0hdy2yuBAIarWcBWg9m2gpC1FKksxXooOGeuq3hqS4tG3H3JIAhN3pqJJIk3UplLIDBJFOY9r0pZq0hAIYqKWkjOZWl9KkJszqYeScoh5rgSevvdwNw-Xli-cffnB5eXv68H5iVkRkT0lk6JI7c5a2_c4fvveX__VfXKalliUztcIYIECZxd1Nven7d995r-27x_fuX15fnu-GCJrMJWV1L7WYejWbi5nGh6O9fJbHoyKTrsHF8K7fjPOsbo6h1YuWNjcA4OBLLUXVMO4KOuGqhgLTsszTshSNgLpUSSkCSymlViHWUoTZITzAa3Wz6TCaGQSu4xs3ReK6LCISFmYqScLdDXLbtE3LIuuHPBE3uQmHJMnMCKHrexFqm6ZoEaGGpapW80Acl2WpOi6lVDNAhAoEak4iaxGChEtZWNjVkpCwoMjhMAJirRURIgDc12_G1MzM1RuR25tDMJV5XvNU8zJ7sZRT1QoBVjXCgxyQYv2lNI3WBRCJ1poUmDpCrP0sXBma4B6u4ZKEgHPbAoSprtJPRECRnLMLlvE47g_z8cAMHPgLf-yPfvn3vvNP_8WvL-Vwstv94i_-8f_87_xK23E7pJvrfUCoO4uIEAQAy27Tfupjr5-1LaD83tvfvT3UqVqZazg4OKGvW5pwM7W4O24HwEp4cCSxqpIEAiCQWdZid2CEBTMHrucZXkkPiBCwCo9bM9WqOSdECjdGighCCrWUECGq249_7md_49e_YIGhiuCMELG66QOBPSzckSDCifDuPCYI_9L7CACEtaokBgiz6NrBrECYiLh5EAFg03fH8ShNTpLCjSi1XesQppqZAZEltW3HKbtFTpJTym3qurbpm9PTk5z54YMHSfL1i2dPnz66ubqyeX76-OLDD54jSrdtPv2JN7DW158-aRLklLq2KXMxA_XStxkB3a3vmrKoRRhALVGrClPKwkxN4jbLdJzvHnqIjdBxqutdaKW5ANJxntu2BaCUiBFzpohYZo0At8Ak4OgYTc5lnlOSnlOTmw9uroeudQ8CmediEOuPbypWqlZdT7iitRQ1FKrmXZPXVRD_wl_515JwLdoPedh21UM4NSlttl0S8lqGpnn89KnV-eG9e_M8ffM7337lpSfzfsw57TZtANSiVutm07kGQFxd3zy4d07EhAhI4CCZCKgdGgeIcAY47o9t30oWryqE-9s9MnXdZp7Ly68-BHerVhcDxLW3TrSKS1w4W62SCMyJJcyBsCwjISNz-Mo3DHCQpoky-3qgViXhCCdERvaV00IEa3gNABAInRGIk9VCggiISOAaxEQkxKrKGMjsbsxCGBHOTLHOTE3dXXIX4aAuIrUuyCkAht0GKOZpXmWoKyKLhQgCCf1u_-WShZBgbT6vgTJmrdb1wzQfEYHXoB2hm1a1QDLTJHmZF0kSEBQYrgBwN_YM7Pt0_6T_yJPH33r_vWeXx6JQVRkICKw4grtamZYk_Ec---l_8Pf-aerk8maay9T12-fPr4kFLBAJwkSyagCCAxgEMupihJAyj4eZE6kZOK6BGclr1AqWWtdToS-K4SzwhS99_Sd_9JOnWd7_YK_mUzE1ExFELqUyITJ7NYigzL5WHxZFQGTyqkRcAZL0DjCWK5FcTU0r3K0NI8wwsFb_HuxlzcuCqwbSUSFlVDcCROHDtDDE_jC98fDhJx89enp--rW33-8SQRAggkNOxOROgISUk0cw07pfcgBVBbeU08Ozk_1xMTcLI2YAWNWYTddSwMkwMHOb5HzYdJKI8HS7SULEnIWEYDe0QXeJ4jW0JlkiIqe8rpWZ87yMjUiXMhIngqIrJRNrtTseDyASB-La6RDi9flkpgkZGFlhX-uxWBAGgFsU1WWuZ3231Lv4bBJaT9cYa5rnrq27nrZhTePAKvQMInJYBe649obDXZgTMxJDoCTOeLdSWN9lccfTgbV3RIhmrqbCDIToLsylWrEZkf_l-R0B7v6KcK0BMzP8_7XAYAYOJsLr8wK-999zd19Vf-TIIshf_fpbj-7fd4-H9y8-8vprv_Xlr37-N770qe97EzRUSyhzzv-n_9d_DdxFkum4DEM7z4pBD57ev31xDIBpUmiwLn7_8en2ZJskt1nalLuBX7z93vakefT44YPHFw-enL3_wc0Hl-OrLz8gQKN4771nVkq_25r7ZjuM87LfH5AwzPqTXlIzbE-Wadz0nUMQpj_82u9dv__hj_zJn7j98MUrH_loYJTq03G8uXp-cXKRhxwGIKyl7jZDP_SgVWtJOV1PVw_OH3LbGBhVkIZSkxDR3Ye2QUNgP9zuk2TZbJloPh6IuRtOAx0jkEGLkqSu70JItQZWIqxL6YamHny7GWrRYeiYBYglJV_BJuYkkrq8HI8pNQjQNA2RLPOE4E2XmSQCWIiFCDFJGsfDZjswEQGW6SCp8WWWJO5OWSTnaT82bTY3j-iGbn9z2JxtbanhhkC57aa5cGIv1ZbSnOwC6ThNm75LDdeptNsGiAgFwvq-n27H7f3zZ995hxMSN9TkVrJVbfpU5uLuLowUTOJmiXieF0wN5zTtr2zRzdmuFCNEVwNTWwoSi6QyzZKyG4QpRU25ffXjb9oYP_MLP3f_0cVvfv5L3_72H_ZDRxGAXFUlUd_kNstH3nzlg2-__aXf_vJPfPazt4cjILEGMCNEMa3qSViBNs3w-d_87Z_8xGvVeS6HIH52ddNtmqoGiKUshF5cU6LzbVIkrdWqq6_78CilEOE0LcdxKWudl4iC1KyqEvN4OKYsREhJtNS61P3xQCx1fZpEaITaun6LCFczIGi5N1tKqeEOhAErfgntzpKF60Bg9bUzYwCnlHenp0kkdx01AgCSEkZIYmasqokTMm7aps25qmUSQAzGeS7HudYwxTgeylI0IEoxrdFu22WqVlSrQuBstW_bw2E82fZBVE3HaV6miUjGskzz0nSt1aJq8zx7wPE4KkYAH272YWG1zlo4pbbJVpVT0qWS6fqB5xFgseZfwsKB0B18JV4CEQUYIWRJrgbhqpZSCgBCEhJAdq8ErmpN33LO42F0s2UuZjb0fUrpL_6FP_fmx177-tvfeP78g-OxfuoHv-_NN5_8yq99EYn2h4OacmL0ANPE5I4oabdrX3n88JUHFwTw7Hb_3bef3x5Hq-4BWiquE_u1qOAWGECACLhOURCrGhETYcS66zAkJCIkCvOU2IoF4ErkRIKmaWotHqsULAgIgcENHD2AhJAotDKih-du8_FPvfH13_sGgQg5B4I5MrkHEwPTejALCFdfR0br0zYCPHxFThtEyinUSSgCgFbwNKMkTgIQJEIshIS4emOj32yQMBQQsekHBJS2NfWUU9d1wCAiIvLo6cMmM7k9eHRx_-yECELr-W7rWt588yMnu-GNN14pczk7PX1wr80oXSunJ5vMTESmTgjb3bCW4oZNRwCqERQpJ1VjJAfILISYmMtSwS03SZgIxd3GZcWEMAFABAMyMzELE1Fk4cRYanUFNUspA9I0FzMFDDd97eUHGXAq9eZQRHhclgCQdYcScSwKQPNSImCeF0Y4jiMi9UOqbuYqQstU-U_91f_u48f361KZsVbd7Ia6lLbJZa6qUUphoqvLF4fb8dXXnzw4O5nH4_nJtt8M33r_y0_vv4TgXZtNo21TLYoIbZuT5FLLZuh9MV5fgEDLMjdty7j-T9IylqXUYdtffni13W2AeJlLGJw_vHdzuZ-nY-rbMlViRKCIWEsPObUQNSJq0bYf5mlCISawaiQpVPvN7ri_BaSh78u8AMEqtnAzJHLHlPqICuHM2byKJK0rWpgigFnupqMeXb_Vug7mWaSBsIBYZ40pZXd3VSRy99z17upuOXcRZqZEDGGU2N0fPn763ttvd20P6-seIdwJEIlNFSA8lIncMSJIxLSuOhVAYJbctbUsFHiW-iUAGQOASXA9V5mjEFhEgUAnYWoSsdSlBFC3ay62-ZOvvt6k5ne--u0SjuABq5LdPCKnlDu52A1vf_cDCnzltSff_MbbS4QWU63gABHMrIuGu0hazZFmxpzcPCOpGmcpS8EggLVPyWUs3LTLohBVgMIMSMJMNTadZJRPPn58PR9ux-mwlGJWzZsmUTBgaCmpabxWcAu3QKhLYWE3CwJHLBGCuGKQEhEjuzkjuQIACAsGmYdDxSCdHcISBQAYeYBlYVgcBcwh1L3W4_F4e7t_85XHp3369KsvB_PNYSQkVWtyCgcLwCAw94DEGd09PDdJtapFJlmqmatkKVrmUiGwugFCLaVNicyIXCTMamBU82lekLlrBMBrNUdsUlpqzUKAKMKlliZn4vWXDE_unUxF3W3Ytmt-Q9L6Nof1sZ0zB4SuA2oWZLJwVffq1T2AzWJR12rA6B4kmJJEADHWstw_362VTcTV3L4mf9bnAAoTIgeulQZYw6K-EnlWzw0jWOU1BynCzIiroBsAKcLXAO4a4gHE1SADdw3puxM-BTCRR5gWRlm5uKv5cc0drSd59whwWul1iOsw666JeHcdQACyuz4Z4lo5cwTGRPH1t99_9ckDVVcPIX3y6NEbr7_8q__8N588vL_ZZC3mbfMf_dI_6LoTYJz2h5ybakGUhgdnzz-4JMHjcW56Obs422228zQNTXc4Tmf3zw-Hgy71_NHZo5cenZ9try-vuySvPN4Unb_9_rPvvvtMl5kFqc_h0PV9LXp7dSOM9x4_2N_ckLRNkqevvPrs_feYmRievf-2HvcvPXn56mZudr1w07Sy6LS_fH46bPNmM8112PVf_e7vvXTxONzDq6suVWWTkzQgKZhqmfttFx7mxiktx6XbtrWU4_75cHLOwgCoZYrA3AhnKKWoampzahphcQiWpPO8FvwBsR-GsiznZ2dLKSgMAKlJZhXc-k1ftDJSmRZwP71_Tsg5iyTWUru2K8syDB03bGaIsoKM19LG7mz34sPndy8exq4fapiDIaKBb3ZDmYqZSs7LuDRDL0TTzSwp2Vz77VDHGZklMxLmlKG4mxPDzaH2Q4tB81TAbVVfQUSZxtAYTrZuFhgEMAzdPE_EIg17jSwJwks1t0i9HK6u6_F49uCizkoYx5uxzQIMkTAlAeSlVE4pSpGwuujP_Pmf_O4fvLPZ8Msfefnxk4ebpvvNf_aP33vru2UuuU_1MA2nJy8-uL23GxqmF99---LxS08f3mtSTqlFdHeinheDb7__AoE1_CM__qn_5f_2__ZzP_NZ4fbDD1-Iwxe-9LWKtr-e5vG4P0w3-_22T1gBPZqmFaEIE2Fzn4tW9VJLNQNaCe7at4O5HY_zYjWl5OpM2c3KUlQVAMdxIpayVGRxg6qllFKK5pw1FIM8rC7VVMPDgZgSWl0zMGHOkszUIZBIqxJTAG1Pd2GYcsdr2hAhwhkpN7nUWs3BLQKZqe_alFMisrBxLLfjtKgh0f52LHPFRLVaBM6HKbfNOJVlLLT2PRmXql3uRHhZ6rzUWHvM4TWszQ0QMeHt1aHfdNN4DIhxng-H5TgeGyEIr9USU0OpFi21YgSCekAQgQcR16prK5USu5mrubsjEEF4EJOt21JGQjAzya2WwpwAqmOsNJEgLseZhdHX0Rh3u6bN9Nf-2l--vT7881_51Q9fXO5vD__G_-Cv_fIv_zfvvnc5HqflcHRTW5bETSsp3BGhaYeupbq__bHPfJbAzk5OPv-lLx-mpVZ3xLoUB4-qcFdRAFUnJAKW1bFkxixhZmaSZGXMMbNrEDGsMQEENSMMwlADJgYIq0bMuM5nhNCNWNTsDh1Bq1zefuKn_8QXv_SFohhVEYGYAGFtn0vOVRWZiQkiMGI1POj3vgcAwBWZKMzMROxmzBQIkpLfLazvCpObzVmgr_wIklxVm9zlprFwd282G1XNTQaPtu-Y-PErTxhACMHhlZeePnl0T1J-98NnLz988OLFhx_72Edcy-rGfPjg_Gyby2j3dtvtpuP1l3t3G3ZEEJRA0HJoUrtCqKr6PKskXm9ay7Rv2m591hXVnBKL3BwmlmQBU1mtbSicAJEA1ZSZmiRlLowcgPA9xmVR1Vo3m_7J_fO6lJzy5X7cdKmaSk6Leph5hEY8uxkTcSCq-7wsgQgAbdsA0vF6TsS1GkTwX_rv__XLZ9ep4d1ugIgmcxgmAmLJjCnLg_tnfduenZ7dXF2mlHJKYdown2wuGsKUckqUhMNgKVpLIQRmDoCchDDaNtdqbdeZ-u3VVZuTFh2Gdhzntm2Gk56QqmnTJ9PIqVnKbGbLXJC5zPNKFkNmcEckXUo3bOZxBPAAl9RoreAuRCIUrpREiOt8dNXctHWZwxwxJAmRhHuEIbgDCDURBvC9ygmLmxILClstQWRWpOnKMkfA2oM3M2CspVBq16b8ikkHAE6NlsWsptQFoNYFEQCjaTfuakVNDQBKqWCWhMzc3VLTrq8kTgIR1ZySoBNBkFBEqNZ-s9OySh6UhICIkNcjYKipGiMiI0IwoBNIP4StBUdqhrTL8SOf_NSL69vf_vq3Uzcs84LmHmY1Hr909uG7V9cf3u4PI1Dc3oyPXvv_8fSnsbpt630n9HRjjDnn26xmt6e_jW_ra_vacWwndoLtOHHs2Ca9q0hIKSVCkBCBUIJvSAiQ-EJFCCSIVJCIVAWRClWFSEiRSk-cPo775vq2pz-7Xc37vrMZ42n4MNfx-XB0tM_S3nut9b5rjvE8___v9_CbX30XGW9vDkRBgGauah5gtvaf1nPX3b5vZW6DrymmSshIFGa5y7U1psi509m7vbj6-pZxsK--9_wP_PD3T6fl6eHmtESrrVYDDCBIkppahIYHBvhq6lYkiFDMpXMyXn27iOgBBsLi7c4TLokAcS2r6dLc1dG8BSCv59ESbNWWenRDX6MndXEI6fttn77x3tM0dF964-HFZvvB0yte5zse4Y4OAEGJEIHMEdECwmGz60oWUwuPpS7MKSjqUnMuZp5TZkBzmJemDlVba6qqiKgWS11TpNE0xnn5-M3vSdhDCQgDW1NO4gkTwelUBfH26pSKAAIieGAW0VXs6aDmpQgALa2KSFNdlVkKsWo_kRgIUaPrOMBbtXFazBFI-0TVHR3cXYhZ-O78Tsh09_Dw3x78B4DD3RAIIiJSznKX6AwEYKY1SUR39nZcK-fuBkjgsfIDV25vECJCFllvO-EQEOtKdP3Au9gb4ipYWHcOGh4BQLguu9zjrjt8ByRcoRHgHoEYEYQslL727OknXnkICkwQhgFOgq---cbLm5f_9J_-i7c--bqV_Df-5s-loWsKVm2z2xIAp5z23fOPXjAzhPZDd3Hv3jxPGLgp3eX9e6dpOh7HV996-Pj1R_f2u4_efffR5WVGxWq3t-O__FdfvXd_q1UR083VdH5-ZuHvfPNb9197XBc9Oz8bj6fL84s-5_F4VKspC0Tsu_z-O--Nh6tHb33mxc3NvfMH07hIlkHw7a-898Xv_OKyqGSar5eLe-csXRbYDt18mtRg2AzcJ2Le7rbQ6OJy0ybNvQQAkQgzoPAwTKc2DJ25gdBmGBiQiLx56tM8tX6_WWoNVyGGZv2wGfbnrhEIyzKfXZxpbcwCiA4Y5sPQqWNgoDs5dKVDRPAQwZK6WrXrOzfrt71p1Hlh4aqaUlINsLh5-hICGTDntFTd3z_TxTCAgN2sGzaOmBIRMCXxat0ghJBTdgswSGhl6DnlxORqyFC6ThInImAmBFPbnl9cPXvRnZ216cSBQZjPz9usOi_dblfHmZJ0WaLhdtOP04RI6xF2d767efK8323ysHWzoWSr1Zvv9htdIgDcjBDHm-t6POoyu-EH33pPMn71N775tW9962tf-dqu27_5qVduPvjwo2--_cHXv_7s6Uevv_novW89eeUTrwPH3_0bf2du0-3x9Hf_8V8el8snt1e_9Y2vf_D-86vrZ3p9evLipozz4d1vfe8XPn1r84uPnrx6_95-kIteBtJNz2dbeZDSpz7zxoM3LkF9s93vdt00TkS0Cny11XXph4DLaV79R8iAgMfTpKH7_W4l5rXWRJKFO6KqAaJpQwuzEFov-6i1MXKtDe6QEiQiVhXcl0VXYssdpI4ozFkkJU6p3H98IakQgQgTBCGIyHZTrFlEAELfdfM8bXeb3X5zV4gDPkxzIMyLjacJEJjT0nSN2iJjq7WZjXUuJRNRTkVVO5F5HH3dWxLO89R1fcopsczHaZnmoDD1eVIgCIdxmdxcmNbtUwIOVXdr5sQIAeakHqlLEGt7zlIq6gYa6IFMtVkSMndhdkQgCHcMdAAPZ6J1lEHIOVMqnTZziMQc4Q6x3Q6PH97_w3_8J7cof-_v_5tf-He_Mo3Hq6vxL_5H_8H_7i_91cKiEaY1dNUpkqkScxqGuS1D6Ydt-aHf-V1gVrrhn_3Lf3MY9bg0RIqAVpXQiMis8jrS8XA1xEAI8zB34DX5AxgoCO7OxCKpLcv61HBVZlkxySTiHrAS24jcDGTN6yshUWI3TYjAeO_eo09-4fO__qu_HCHgFhAehgym7mpJyoo8JMpua8OY101-SslVRVIEEKwxJHTzbjPMp5kEkTiIiIURCCWIQASFPSyXHsJK7jyChYkSCXXDOQnkkrqhe3DvfulKYnjt9Ve9Tt_9HZ_fDLKR_PVvvv07vvMLx6ur1199WAplpsPVtSTenG3u3ztLCI_un22HghHboXgzj5AsOUvOydR2w46QCKmZgYOsC4mIJEk4FREzc0AIyDkToAECQlMnZKQVHE_hjkhtZYITuZkI1cWsKScOXN3HFGqdyDLbMrfrcT7bFgK5uj55GAWcTnMNckZVRUYiEuE1Rs5IVTVCyXmaZnQXjHb__u766nR5thlPswSeX25c_f62-9aTGzCbl1pyQrFBNgDY9d22zwROAVLSdJq6LgFSgG82RfIA5q1aKbnW1uZlt9tsh-zIm0L3P_OJ51c3JZUadv_e-c3NUafGifXWDs9vy9BXrbfPr589uXn1zYdoOt2OVRcu1OUyHZ0ZnA3MU0pLWJ3bcLbBNpNkX-Zwz_12vD1uzvZ4uKlLTbknToDm5q4mJSM5C7UK5tG8AgRxMl_AI3ViWlUXScUDBMINlulU-r5VtdBcRFsjBE5JlyXlTIgeDh5hEVC7fnu6vc65MKMDBYR73Ls4e_7kA1fKKZUyqB-W45jShgmrBa9yU0NXB6DSlfE4bbY9hNexylAC_Pbly24obYHq1SrC4qVPjGhLc_OIcCJttkt74jotzZcGAG4uEqqacx8cshraXVtbOCAyv_K5--__1lNw2D_az-MELNMyXb56Ns3WnXNVQ7XSbRB9aTMgdaWvy2JNEYTQWtUul0aRJMAhEQqIGSRIp3rqc68cZGGzpiI6NUQiFMKgwA3BdsA2NR89F56PQGjW3IDUarcZptNhbkvXD0JYl5oYl0WVYh6XwIAAQg9mIFR3QcOkAIjuFGQW4b4TPgWHA4ihYDVsGpmNMzCniqlaxLRAgmBpLu-_HN8_Hn7519_uv_7ua4_Pf-zLX_yjP_Y9f_Of_DwZNgxsjh61QagFes7SmhJhlhwOLayqAkCtjmgp5Ui4TEsq5TSNu80mIiRL06pqgqjqEZETDH0_t8XVAFFKIsBlUUBszcxRyYRobo0w5iPvumw-usdm18_z0iObG2AycgFzg9RzLNUhpvGIzDEjcSiQGy5N-0SGRAAJoSoeDsqIfUfOzKVfmm1E-syH60PXCQsSrXhN8HD3tewVYR-f_FfNbwBiMNHaihMmulP_Rrgz0YrvWeHEiBEWHweCwDzM7A6jB8Esa-BnlQyoggO6uwU43l00CBARzA2RPNADVk5FBMY6OURQ83X64AFIsBoMAMIjBHFRu7_fqTshuhveeQoYsT14_PCHfvzH_9pf-5v3PvdWGrSOqqZCGObMudtv5-tpOmpXSHIauqFsunGaAD11MnT5vQ-f1Lm99dqjIffaxoGxzWNfslqbWttn3G_76VjnFixEOS9t2V6cm_snvu1Tbi5doZS2265p5XR2eHFdun6zv9_m0_EFPHh0Mb_99lSvd8NurLWVLQzPJECA2qLn52dLbTcvnt-_3JhpKrKTTEm6lNocoNaXZNUk0f78_OmHL0snYAwWXd9PN3NmZpSlzetlbJ5r15c8DNN8GxBJWLru5unzcE9QMnB_Nrzz9m9dPn51rvPlowc3Vy_XutexqQO2Wt0aMgXFi5fPzy_vlVJarWkQNt5uN8erg1cTJiY202HTqbk1y4VBKKJu97vqMB7mfGhJGITWEHZOQky3V1f3Hz-eT2POCYCON7d5s63HeRlPBBXXDVSRjsvxWCU5cwZzZsxdcfXrl8-359tASKmrxyMdbvHiLAtIX06H6zyUubXes2RZlnG737x4fhVBuuj-8ix36frJR48-edYVifCbl_N22IDBJpdZSaelma6KWYyoGo_feKit3b549uTp0650dVmefvTE3DAcVPV4_NV__W9bg2dPPzoebjHH0w_f-_V_94tV8-37P7doLewWcXs8zLUFyLDZlCH9x__nv2ZwevLhFWHcuREaDUMRhu1ue_tf1B___T_1mS9_niGsRt93L5_eEGPEWgIPA0CAQJynBeC4OzsD8L4rp2VeljUSUJPw0jRLmmtbQ3RMstLwmcAshpxOMd1FAs2S5ForukvHVj0zCSNE1Hm-f-_VpU3TsoRFlvzotVdFUmQyN2-LB0hOiEQi0-1kqikzEZSSICIstBkLLfMSABrRVOfa6lxTzktthOLW1jabRoRFayqpVG1N9dAOw7BRs1xkOs0kJRw6kUW1qi_j0m06EKrqsUz7s7OwcNO5Wt93rq1FMAKSMwWv8VpwAQj3JKxuYKvDnJDcwVc0TWuNCdVUAwiAAXW1H0QQcYRHxDwdpOSzi2FIgpLALOdOSH_3D3zfi_fePy_Dhx9ev__kwyw4Tvrw8YP3rp7rdBqdtRoBKoRwAgMh8XUiSXBq-s63nhzmZU-h2t54tJ_Blal55C4pWlvMWkVkJrRWIVZuEamFE65_PW0mjGG6uh7MHXSRTtQ8syATEhIxBpk5S4pYBU0RHrC0NbCw3o5WK8vhMP7EH_mxX_7NX5TS12Vd01KYJ2HIsJivuWtDijCEIOK6LERIhOtPcw_jQq7UtKXchUUE5JICsNUmOZtql3MzIy4RSsAI4uY5960tKNndd9uzcTk4zJKZCS4vzwn1weX-4b2Ly3v7w8DM8Kk3P6lNie2V-9vjTV-n6eJid7bbnW2H3X4XrvfO9ieSUniZaulFGI3XTz08aBqXvNqRiYCQk7dxkZQAwhzCvJS8zvAZKffF1FgoHM3u4BaEZBhm1twRnJgAUd3c3S2YADP3fTksTZibac655DJPbWm6H7pxMgckQoQglK7QQevAPLG3iHlcOMtpmjYdppymQ2UmNTcPysL_nT__3zd1Rri9Hc_ONghcSur7_OL2lIiHoZwOx9J1ZnZxdiZM8zTvzzZgXpi7TiCgZCHhFy9vur4ABDG5ekorCRAF0WPNBXGAQUDK-fZwlJxZ-HQa56lO41yG7vmTZ8s8l76fT8vhdDSMQHQPnRczK313urlFQuC1n26BkXMiwGWeEGxNp7jfTQbBG4CFr_XnWGrDFSeBKws2YnUirGATD0IBAK0t910gmmqSZB6pDGv03NUkp2WcJQuYsxBJIkRf3w8QbraeZzhncEchABrOzo43tyIpwhHQTIUI3M1cI1gEIxDATFEQ_K6bAIGY8hroR_euG5ZpDMQVaJ2ThDsQuDdiCdPAQHAmAEZJCSgQcbPZ5D7_2O_-rjcvLsbD-PNffXtWPB5vjjfH7cXu6tnV8foAgkTeagun2XxzNnz00RUhzKdTuDe3YbuzpVVtvmYrwIk5tMl6Zg8k8EVV186Tg4U5gLoirCdUWqarwOwKEQ6EInkY0u__Xd8VU_t3v_G1cWzLosAgmSFATZFDgB0J1sEJ3I3eA4EIwZVkhTA4EiCBGwCSqq3BJDV1iGqNAcGVmAyaByKbh3LqLFqY3tXiOZp5oGjYtz64WkylpOvrqTV9eP_8rXv3fuEb77rjvCwBa1wqpSSurWkQEFP0HbemS12Ly6DNxtoi7ronidnUiYCQcpbEJQhKLszi4AypWgsLQrQWhEhC2oyYx0Vz4tKltbGNhMLS3Da7Xt0xUFhyzqqtJIFmrz2-fLjrz4Zh6NLlfjsv1d2b-VQNkNUqBBkCE3YigWHNUNBh5QwjId7cjOe7ftuLmxNiBBARMBIgEUasv3BHtHP3j_XYFB6MIEJZ0FewQgCsPaSP_1nrcfFxqGct68LHmX4KyEncgZk9rLm3tfAKYO7rH4mA6uYBQIBEamtb7K4AHBHmdw0F9zBbiwa4zo0cIBxIpJof23S5269xJL77rdeEgCXGN9_8xF_5T__G6VabskkICmSpVff3L-fDVDq2OlO0i4cPLy8u5jb3KW-33c3NIRi_7TOvffL1xxHx_nvvvvr44WbTaej1cfn1b3x4ef-sNX_24npaWrfd5S4jxji37XZzee9CUvrWN99-7bVXp_G2lG5eFhEGgrPt_pu_9ito9eziYqk-LeNrb7wxbPsP3v1QEpzmm4t7j9fn8nQ6bYfuzUcPUu6vr1-en13GVJNIBEQ4Oqo1baGqImRLYwiAMLdSSpf6qvOw7QlQEkczIEbB0vWJWJjn4-ym7mat9ZvBLEq30bn1fSecAYAI59ORmUpOaq0vnSSqtXbDgIApoS3LUvWNz7_uyxIRbWmSONzdvOmSUgGw3GUimQ6n0veYUkrJ6_TwweVxrCKUSOrckKHbbm9fXl1e3lt5i5RonGrqsqBPhxEkdduBiFXDvalpLtLAV9qgu_XboY6VU9dqracDJ0Ts02bTTtPQb9x9mubN-abPG53m7fl2mpbtfqdq1pb5cLQ2b3bnoOFrW75W8GZ3diJbphnDdT5S-MsnL2qzd37jV589fTEfx-n6MB1PWiuYm4EpEst4mDLLzctrsqin-fpwffX82eH65ctnL49XV6fjrMt89fJgqvn-4x_6fb-7FLl4cP7Ndz7og1559bXv_P7vefWTnz3eHOrxhhAOI_Rnr_zkv_fjNjbJHIhkuL_cbvuOiU_Hk7aglLRpmAvzOC_MAAYaRgBqlijNSw2Iuda5NoPQ1hBx7dzO2tYcgpmtADok0GaAZK6mDsRNbbMZENDU7j98cHZv_-i1-8N203f9_Yf3uyRZumYK1gRJspSu9KUvOQljNxQHWK8PQ9-VnNQ0AqbTDEzj0qZ5CQ8ktGgAEOaqrbXGwuoBYcLU9Vnd5qWGmiTmxCteDBxKFlefaj3NDSHcTN1X3WTVFangYU4Jb66PXCQI6lyRGOBjwIJ5TmLuECF3MnM01zWG7o4Qjoics7uhQbhRyg7hZiUX5DCvAfSJL3-mGF5cntEm37x88eKjp2BW23E-zD_4Q9_7m996952vfWOZx-N487lv__bjy-mb33q7I7n49Gvzs2dAslKJiCAYzCzca60M6HX8wifezJvutdcefe3rv7ntCyF3XefWTB2Jws1a48SAkBgD3D04JQhkphWxIEwRcNdki0DCMAACDEIKUxPJa1FgdR0wkzVnBgBmZE7stjAQZv7Md3zn4zfOv_qVr06HVrpss66RUnMjYFNAZm8tEFNKAL5eTt2DhYDRbYVtuGogC6dEiGbKwuG2_uTJ_cCEQSQieRg8XIgpSdefrZsiDM-bjJQc0-OH9wWjE3xwcbnp0_d8x2fbOPdd_sQbr7iZqe53W7NIIpdneyLc9LkveSiy6Uqonu36wrJoTSxr6IOY18pBRBBGyYmZI0LVI8BMCSCnxEymDQl1WYAwS1qWliSNtQXiUpsHrqB0ETS7O2at-_AivC4ESlc8vKoBxGbb39tvOOD59SGVHEjMPDdtYV1K1iL36bToerWwcGLc7GSpwQCOYOFA4QGmlnLmP_Ef_rlpXLqunJ1tSxZC2G3KfFqYxc3OzwYPuD2MAW6m52d7YQT1LqfLswGISkrV9Pr6eLHfHA7H8LAIZppPMwGmIsOmm8fZLQggSdrs9qb14uKiedxeH07jjJmubo5PPnyWUj8vMyahPrna8TjP47I-oZe5EoKpoqCbJ-IAUFWvmssmAtwaeKSS61IRQZggIFSRec0xuGouCZC01pSzq7uq5MzE5r6GaIhojSNba6XrINzCAgyRcs5WGyBwFjAXIW-KSIBCKyUTKcBEZJ4rpwQAhJ66nkXm8YiIYY5EEQYRJKnVmhIJc2vN446jTEzrK4qIXBUj3Bw8cleQpLaZYSVPwto9MHUmAgKICPCUE0DkXCy87zepwy7LH_3h793k7u0PP_y5X_7aAnEc56j26dcfvfP-U3cSxiTJ3OZlPr-_f_HR1TjPXquZmmuEp1y6oR-nEQII1DWseSoJYp3OBhMaWA0DJjVjkcN07EqmQG-NySh1pkYkwS4i5n62Kz_47Z-dx-kXvv7OsTYLbxam6yiF6qJIUUoXpitUR3JRdwjYp0HBwQADMglAEEpgSC51qQa-cl1Vm-S0zG2FM9DaIV2nHgG4VqQNLnJXURuEMAPCKol0RGC5OY4-z1_8ttf3u-HZzW3m7O4RwcgrCXHTd5KFkdczaSCux167yzmR23ovA_cgElUjJCG05oDs0cAhwJBJ114sAhK1qlLW3rEioDshgIh4hKnmlIJQzZh49eGe78rrb3TkUue2qF3fnpr7Wc6brrCkaVnUwtTUA4ExEBABwtYbMiAgZiYLL4MsU7Pwsz7nlAIAPFgQicBXIxgiABF6AAY4BCMC_XbCB1bGD1gQEwGuR3a6aw87Eq3hYKDfLvSuP_DXz5vW_wi8A3UBBgGouvvaECAEDAhzXUP_EegR6nfqmNW4HOs62xEQPeDumHb3dkEithqq7Wy7JwyENRUZgLQ-47yZkf2__tY_uJ7FA_v9tjYlJiLe7ban4zGLtGXZnZ3vLy_WG8bZ2RYIa1044pOfeO1yv3nnvQ-6wvfPNjkzWPzKb77TgN_8tjdvXp6ux_p0Hh89erjf9IAxT1MhevzocV0qJmPT7XYH7lfXB87d6XBaqj57--vu7fbq9vGnPmWI55eP5rndu7hnGh--882Le4-bY63TZr_DaPOsr736xtvfemcYdurOQpjzWpKQQpSQmZAwpeQOUzuBE65kJg4MDAeE4NTN88I5MWDKmQhPN1eMuBynbrvZbjZAbLqcX5wty3KxP6ttOdtvjqexy5KEU0pIAYF9V6ZlfOWVVwBp6DtBAXWMMA8kGIZOPXJJq-N5v9-F2eXZxe3LF5vt1tRy6ubx4Gb7y4tap1orAqaumLecu6tnL1_75Gsvnr1wCkBcTst2t1-mgxumvtOmZ-dn6E4rSs0gleKtgoWFBcN0HDebM50mD6vTfH557uYakHJSUzPYdN29_e72eESWqapZS8zdZnO8el7HaXN-SQKpZK2LtuYN9pcXukymCgg6jgwGpqerF8yU-56CuOTd2U7Khne7_euvcukSpte__KbPvj3fJ2uCNi1TPYz3H7zxP_zf_MU_9NM_8QM_8oNf_r7vvf_qJ37kJ3__D_2eH9rt97t-__onP80hP_FHfvKL3_mdD9940yB1l4_eePPRl_5bP_i9f-iHf-gHvzyPMwBaeJiTEBOKSOpyRCADl9yqZVrfL7gKLgPwNI4e0UyJYJ5mYkTEVYcLiKYaq1tXV_Yi17qYupkDoGoDQmJmkX7o5uPU74b9-dm9Bw-y9FVhs9_sdpvNpgcRYyydLMtShD2g7zcEWBIRoHsAA0QQccqZJXn4tCzuPtdlnCviGrPJANhajfC2NPc7hnGdp5KSiEzTUmsTonmaS5drtdZUkCnA1G7GqbaaSm5Lc8A2z8DUmpp62B0XqNUGAMLszSHYF1uzHETYddnNVvBZJKpVI8LdWLKDEQEymsIqPbyjHRCaNWLytuRh2JxfHD58efP86sWHHz19_0kDsLBhk6Zp_g__zL-_2Wz-9n_9j188f3aaR2v243_wD_z6r_7ai2dPWsTxyYva1NfTOmG4V5uYSqw6XMS3333ye373d52dnw1Fvv-7vqONNxROGa1Wc68W7tgcGO5S-gC4cslTLroCtgklsZoCpxVrSixEFO5ZOnd3d0nF3cCM1ueAh5Qc7mAOEMwEpg6xVPv9P_n7_s7_-78J5_E477ZndZlJ2Jp6ABPD2gcIv1ukQLg5ACA4rF9S4rViVFJRM9PGIsyCsF4WEBANiJMIU-mG1pQTdykzsocOeSNC-_3F8XDT952b5ZyZ-P75_ktf-PTldvP5T7-eGF65vycIbW236ZlQhIhwv-mz8Ge_7TXy4IgHl-d9J2ebHpGfvvxwv90JydLa6qDsh6K1JqYhl3Wd3cwQV2gqR7g7MIIwr_Oq9YWNiGNVRFzUGNdTBX8Muot1jM4QfS5r1tccCKAtBhSbvgeDZWllN6i6exjA0iw8NIyIavOxtfG0IEJXOAKPhyXMJIkD8Dq_QyklhxsNm3xxuemKLPOCiK5eWPb7XgiYYJrq7nxzef_s1YcPO-bxcGTEvk-rSjoRLUsFh8uLLTL1fc8pIxAC5lSIWYCsWjd0XZ-HvvRdAbeh66wtYkqBCHHz8iYRP37jkVp1jdNxef7eSzWwpjlTWxYzJ4iUOJcE1kK1Li08GCzATSuCrSY5ayYprxACYkEhlgTISIJEYQAWIimaSsos7K4EyCzodx4TCEdXV9O6JEkMGB5Nl9YWTuxqFAgRWpUQI5p5tTBJZKbu0VrNXdJxjPBlqiml6TSqhy7NTSOMhVtrCuGIbV6sVkQ0V0Bab4phpq0FwHobWf2op-NBugQBZkaApcuIjohAICVHhFVlTpCQhVY7t-uSkN96fHGx7VqLp_Pc7YZZIxC7i_27z19OqkG0vTg7TSNgOpzm11959MFHTzfbvrmjiDZDxNuXL4RLlhRggYQIvFoPARgCq43jiSmHwbwsHjAt85C7ehrrMgMEREIFRjEIcz-Nk7q-vDkgRCGZl0aE2lRdLWxZloAgxPFmUm24BicB1OvKJTvaKWUyNzNbagUH1YoQYQ0ZEpJZM1UOsLm5q4K7my-VAhOSV02C7rpMjSjGqIgpEAN8Xlp1PU5z9Xh2fXhxWv75V977p7_xrc--9rjDwDYSsERkEQBgJCAQwpRTEkmJhQAUzKNWFZRmGgChCowoOM8Tsozj3FSHbQYyjyBGIXEAJAGkAAoIFNKmIqtzLswbEU7zHAbztMzTMp0Wbb5UbXXp-g4cbw8wN709na6ubyZtZv5b7z29up0Cot_0CdEx3CAAhJiDze7MI8igqgxQZ719PhNia_H28zkAkzDLb9-I0SwQ1rN7CN8FNVcgBkTA-pshEiAJw6qEvAv9rPl8MDOAlQ-JqzLs44-5cwzHnaEjNEJbDY_1ZL-e_iOoRWiEA6pBbd7cDVb_UZiHBZhHM48gu_MUY2Cs_9chLEKEq65AWF3HNhGgYQEfXygQ3OAbh4MjY86BxsK16ma7racprbItj4vH93bbIXd525e-S89fXgPCFz731nlfXr64DrfHl_cRyavd3Cyb3fbRoweLx8vDFEyvv_ra0uqwKbVqM9_tt6fpWJflYnf-_MnTYeglSS4JmDBBc3312z7T3I5X16lkXab3nrxfW0Nc8whw9eyJQs1n58u4JCnqfmoLCa-GZEo0nQ59JoRY9ToAWHJhYPQARSIkxnDz6l3KmQkAcpeJKHOyqonIDfdnD7pu6IaSmLWpA3hAVZUsCI6Ix9vbktN0OE3HKUyzZAporc3HUU0xiHPan-_EQ5DALBHVpWI4MZ5v-yGz16Ut7XiaCOV4c8OhKcHQ9afDgQKGbtNteg_LwpJybfPZ_Yu3v_mtNz7zZjA76HDWz_OUh03ZdqWUkvNyGruykSwE0XepjqfSbSinZTx2klJJEcGld2uhtS2jpAJBueSeUzuOWicgzpLNFFz7rmhrEGiO8-mUJIOjqjsARgCZTRMAIwqtkylTrTMgRTdM3sX24auf_64v_r6f_eSXv_PVb__281c_8doXvlTOLsHvP_ng2Gp9-fzF1dXtj_yJP_5n_-f_05_8M39iPs4vT-PTq9u3nxzerl-ZK93cXgfAda37h9tf_-oHuXSnsb3z7rObZfyV21-9-Nzntpev7cq9iFxyJzmZATIiengQBRM8fnh-cbaFuqQ7_2PknOCOmutINE7zOI_NjZKsn9pq-1pW5WXEmnVlIbXmECxspixIRG7u4GWXHb072-Zhuz0_d4TnL9_fbQu2SChuzkS5iBvkklD4bL_NWVhI76YFKMRCsoYGTds6SV0borXqtFRkbl7neQKPOlWAQPAAB7NETIzTvCAiebRaEcE15nkpSVb851Srmpra8eZGw10rQ1hty7josixLBQJVZYZQq-OUslA4gFtt6h6IHuQKiTmAQiOVlFLCQNWGFggUhkhhZtYMiVLpIjynZOh5s-u3Z-NhdG2B1sgpIWCUPgHSeb9_-Pjsl37pN29fPpnqjAgR9O3f9emvfeVdDIzaABqj20rSQIKgJAMDMmCotfBK-L_-P_2nCNGXIaf0h37sR3_2p3_sR7_zM7_3Bz__-sPtWZ83276UknJKSZiJGCQxEVkorlXaAPdIpUAYhKvpHbnBzLwBcavNXN0CPJBofbWvaQpOwsQABiQ16Cf_2E__3D_5Fwgx3t4Q2-lwJYmZOWXBiFXiSYSIDOtwq1nOaUUyysr0SRKmTELCzJRzijDTZhEpZwQnIs4SCBGYs7hrx2nY9EQAbk6GQkudUukI6fze2W5gBnvjtQdtOX3-U6_vBr5_3m0z2TS9_uBSECj8bLfZlQ5c33rtvk5zJ_D44b3M0CfJjN7axfY-BYqgSBqnOUJdHQlF2NqKlXUkslWCBCHMJaEw1WlJiRGRCJioastCqoaIDlCbBvpsihREyMSAKCmpNURk4dIlde-znA3DPndTbad5Jo7WWhC6B95B4QEJx6V6OCesqm6BAOM0u_t0mlQV0AjBvAHGeJhJgAQZEHfbLie6vNyPSz3eHu-dDZeXezeVoDfvX8ynQyLSWpMgeOjSzMI9dptyGEfy0GYIkIQ2wxARw6Ybhq50udYaHsJCRNY0Cw1d3nRlOp5U526z2Z6dOUCbzD2Gs-22T4Smy-JuGABm6JYTH6-vtTXOGTmQvEs5IkI1XMHdIWAtnzGtuEBishYBwYThJolixTy7rhx8hECHZoaE62vdTJk557LONbXVVLqVN76adfFOYkRrJA48dJ6ZkocTAcDdwD6VDAFuGu6MqS0NwFNOWuuKaXRtkoUJtFWI1UYMZgoBksoKUwuP1YoqTDbXkkrJXUCM8-RNu7IhABYxCyJev7ZtbBG4LHVt0Np0-uSDe9AwC3313fcT5wDjiN3ZcHN1IGBAj2ZW3bRKyggiSF4bOoAbMdiyoMfV8w-2faltWbTZSgH1EKTVWeMOy3yCUEYA1USs8wIITau7q1e1OaABuFdX8_FUP_jwRolSJgBakY2E5BoQNE3LMk455-PtOC8GRMTU5trmGRxUwQKlJAM3CAhoVcNjmWcKcFMi1KUhEIaDeYCqOoKAU9PmFNO8aFgLmGs7zq2ZZ1oVvWyLtaptVveYapsD_92vfP1rz1787A__4LAp2x5S6YyCGZu5NUf39ajapTTkwggWkZJk5kTkaiQyTzUgBdOyjKXP5lCrdTkzkbunRGjRtFZrwLHWpIVEZ2MkjwiLZWwYHOGzmcNKHgBzFeKMwsLTYV5qM0LIufS5qWZJS22H26kE7Xc9I-RMXSImUvWlKiGoWVUFXK2QDgH9pmuqgOoECFRylpVxC_Dbd4GVZ0cISEAULCBCklZCA7k5YkDESgVdc0Qrqigi3N1WMf3HpgEhJhIhRiD3ULdam5kFsQMqoDms-2j1ZuZrs11X9if4Ku-EVSzgHhgGsP5i89DwtWHWzNzX-Cggg6_NZkBGJmRGgXW5EBSItSnWJIxCSA7hMGz7_VnPiNvtULWFpc1mY6ockRmFkQE2fbk8G_qUvvqNb1xe7Ap6IhqrvfP-03vb_XkpxxdjzrICMDilUthcu1w4Fw1HjH4znE5zrYAsKKQagILEHkkwEeOHX_uqDOJWN9t-mcfLh-fDfnf14hmEuC395YZLMcOlzgKkVkuRJJzEs-CwSWHGiG4OqrG0LNIVCYqUUs4pZ2aizAmAPCyVNNcRkeusJNnN7tg5rsTi1nKfwZUBD-MhJSGWZZl3--2i0Q-ltipZXnvj1X4zXD173g8FiGpr1-PcDcP-fH9ze3h2dQur6ypc1bjrdxc7jdqg1bYE5nGctpcXlPPzJ0-sta7ru2G4vrrpknSlc6sIePPk6t75OaOMxzH3XZsaWhxvblgECBebEZmEGImQ6nwE0mG3W8apAIQtF48viYQErt_7oBsKUtR5SaUDt-l4mpdlM2yFZJ2xCRMLSk5mFaERkSROqRuXaZnVwiSxNwMF4YQswun-57-we_zKo09_-s0vffbhJx7D8f351HLenD-4v79_-fTlUSR2u2E83m62XZCc73cYybkshuM0n8axTacXX5nbPDazubXx9vT8g6tXzvu8Se988GS25pP_sS__gfN-KAIUjQAlpczUd5kYhLDklJBTUEfp0eX5xXboO1EzD2hNndA46rLkXIahR5S6NFVNpax6rGYGROuy3dy0mTZf6XBNq2RpTRGxqQMIQvIgRu77shym26vTvXuPCXC7H9R1rTUJBWIMXbfZbFhEawOi42mqZktrEGFqRGStjadpmSYhDI3CHSN2KetUKagrnX0sPgsHU8dARFhqnZdlnudxmpr57nynru4ea9Rs1qXWeZwDPAjXJ7KF11oD3E2JoblKJ-tUek21ttbMFJjKkOOOMRySuNt2uS-JU6g7BAZoC0lpricGJkRORCxWmyBDEKF02zNQJ7e2LHVZwiGcfbEHj1-9f-_yk59-fdjIL_3qLx1PBzWr2rzCw8dnhxeH2lzVtYZqJKCEyGaAaB6mDdzcvFU_qV0d9C_9X_-z54fRUZY6PXpw-YPf_zv-9M_8wT_9Mz_6yoPzTSk5CwITiSoQMOPdlo-JkkhmERKISCkRAjFhBLMQs4cxEzK6NUZHBlNdN7qIsX651gqrYrz56c8dD6cnH340T8s8z8Fkagi4jo1WIkT4-nwLX2tkImvwQUTWPUN4hIXV5upECERACATCAuEsBYUxADm5Y21OwVxKrW4WSJASS-Z-txFZg0n-6PU3Htw_e_zGxe_53i8-vr8T8Pk43h6On37rcWJ8cLF79PDi_tnwysPzx_fPM8ByHLf9IASdJDMDh9aWoS8BoOYQNmy6xAKIJIyIlNkjGAHCc0mE0eUkzAxMAZxTBAhzrW2pOtcWEFWNWJDIAWoz9wBAt1XRgPNcI4D5bo1dmwUiI18fxpubYyoZWty_t8WEc1WzCOAIXCAsgoglJZGEnMa5ouB6HwaDdmrjcTa1cZo5E6XMJacuSxbx5pmJEB4-uEzMfZZH9-7pXF--uNrsyn6_uX95dnN9m1k2266UjBEvr2_v77ZmnpNEwOk0Qui6ZV59QpNWYY6AuuiqEz9N04urW2Ap-_3cqmkklkAfhuF4fQvhm03nrfWbjVpLSbQ5IKacXM0DWm240rVYAMytckrCKczcjAkZ0ZsiMiUBNzfLaeOLIYbpQpwcHIkBeD3Tg_vKyWbmpqp-N96YtTkCMSVm_ng5hREB1NSBOMAQI6whsqqxpFgTghEITgDH62vO3HfZ3UPBPeZlzCXrrOirYSkQwGqNADdrrUUYmM3TmJKYmgUGElAcD7cpZUJE9HmZl3lGRBEONwtbVNPQhxAQM6MQ9qUI-E__3u8No8Pt4Wtfff_UaoQeD9MnHl_WaoSchi0GIEKz-dXXHj199kHperOgcApKxGttfTkcEHnf78ItIuqyLHU6zeOstYEGKEGAhk6Lu623trBwb9M8ncZDSv14aIAOaKotIroiHzy_4dJtdh0xpizE6B7iGIspxFQnZnT3ea5qiuDWrM6z1jZPrVVDYgdvsALCZM2ABJKpS2K3RggsFG6UwdG1traYTk2ttdYi2l2W1I2aRjOGCAQNq9qataXavMxH9X_687_xbJn_2O_5vpQyQ9Olhq4qAE5MfU7kuCxq6l1fupKZUENpfcOBs-AyHzHC1FutEb40naaFmZKk8TT3OWeSPud15oLoyL4rBT8OJhmYiJhFSoJE2lqEd7mcne3GOo3jfHs7naZmLtV9nOrhNB_H5TAu1ze31zeHNrfL3XZfMoYTuLkCOTOaO7gT0diaICLGYZ4e3e-z0PNnNwEYa_g-DBg-zu3Y-vxjpJKkSFoxUGB255P7uMKCqypmjZC6e3ysHluH_Q7CiZFwpbxFKLiBN9VVNBCI1cIDPEC1xYquxrU_vFKnIOwu-I8rF2jdCwcCU6xibcAANI-10NbcAWBpLaX0MTw0IgzuOuWA4KD6rXc-YuNSEoJn4URUOOnYEnFJJBIPX7_su9z3ueTc5641v3ex_-Jn3xqIj8fj5X774HxTOqm1PntxjSk5hak1Fw882-671G37LqcCyK-_9qBPKeaGZra08wdD2AzVupwky8XZbt8Pn_z0p606Mn349W-89alvOzx_Se6b3XZ3b4fIag2zIEqft7WpBNTplHvedH3qOwcCLrOGJCpDEmHg4JL6bY8InoRLp2Gc2BSBkJhm1dEsb3PJpfRJRFxnFgaM0_iimlPiuqplLCD8dDxpU0pSht4RSXiVVwDR85fXnLi1Ni3z6XiaW211efrR03me-_328nyfc0LknHN4XL98fnt7KykhixThIgFJvT147ZVWq9tiS2VC4Xx9fX12vt_sNucXZzdXN8JcSpe73ObTsBlsmdl8qbPhKqEjb7XVsWSE8MQZDCxMOHWSCDlvNtoWDZ2OU5HsVZd5HnbD9bNrdz8cDqXrONG4nJCFWM4uHoDb7YuXjJwlcRLVUK0QEeosnDrKm4FzBmHkUKebFycWWU71dtLcDRfn-9KnaZzm2FTTzcX24uxyf__BsNl893d_4eL87Ox8e7g5PH36ojW7ub6-PD__5le_-a_-9b_59V_61f_fP_vF0_UzsxjHSonbtLz6-oMAYERTMK0oELVpU21aF1NzdGOkLjEJYvj5bnt2vi05MYJrDQedFgwACCZkgFB1szovQOS2AgW9qa_Hly5nJMBAZsolr5AZ9yhdIgYIBw_JgpTSpr98eF76QkK3h3EcF4jwaofr0SxYEkA0cw2fjsf5NN8eRnNQC3Mbtl2ET7WeDss8tbnW22lCCDTdDv14HOdxqdVUVesyzaOBNl2QqI7Lcpq0NhZBpqEvSFRK8nAH16YGkRMLU6ttWWqYLtO8zLOHNjUSCvNlrhER4VxkXuYGHkQOAUEsaVkqidQa4YBMtjbWmIBQMkNEzoO6ASMSrUgdd6WMTFJKunr2rM2LtbamFpE4U4altuP8H_ypP_5rv_ib3_zKNyz47N52GAp3PSDnkvrNFgTNDQERHU3NamAAxNKqqWmz47ic5uXq9vqf_Ntv_tWf--f_q7_-X7774dXSoEtFlH_k-77386-_ud_2uetJWHLquowE6u5qDByA7iuRPBCRScwswM0ckAPDLQKCkGgtWTUlZsoFA11NRIQwMJiplP5L3__d_-wf_SOhgLBciN29eazeJElqhgwkFBCcmWiFPbghhns4uIO7E9E6pkXGQKq1AgoGujmSBAQw5a5PzKlkR-yGgZAliUhC4lS6IArE1BVJabvdmrXHrzz83Le9sdlkas1b2w7ls2-9Ngz92bbfb0oC6wjvnQ0Xu26_6V575UHJPHRJBDdD7-ApyUrtQ4TjtAiCh7tpklRrW7OsDlCr3qFLMdBsXiYN58ThDhGtKhDmnBFpxWA4rII2YCL_-HaEgIA0zc0MimQBGroCEGNtx_F0__5-t-28-ovnp9urkwcs2kwVEetiSBQEc22KcDtPx9oCaWpKJY_jtDRFopWXuN32JMTDpvR9Wf_dat10Xc6p71IniSBKoXuXZ5sy7IfO3d56_ZXNrnQlrano-5fnpcspCSH2vXRdrksNt5QTErZmJZX1ckIi2vTlzfE0LhZEOR9vj4R8c3sYx3kZl2Va3L225uYsspzGVn0el1Zba80RKSIRAyDyioL0ItlX1jCSMJsZqK6AztUmTRBqoTpJVyDQ1RA8HKwZrX0X9YhgTgBrYI_aGj5hMnetFhFZMgC6aSrdvMyrJrgty_pmqcuyEhMZQTK5qqkTMyXx8HmaEZGZIGzoyjI1U0sJtS2mtnrFw91CiZGI2jyWdcIBq2bEltoCcDyM_WZDnBApJVGvyzxDOAkygocHGhGbVgdgCYv5wcWwKTxre3k8TQqnZkgxN-u2G3UsJTHJ4XTsOmlzfPH1T7_3rQ8BYzxOLcAiWlMNnJfGqX_-9Mmw7dHcteWUwd3dW23eGgPW2ralgzCti1sN8tpaYEYH1zgeb4WxnVprxkwBULr8c__uF9Nm--ZrD_qSU0mBZG6YgXs61clFmhoGaTVrVmf11tZqh2n1VevQLEwLY1smIQYMCpPMWietGo4rzdpbWHggoFnf56bamhKi1wUdTRWDQclahINQRyBgBOgRWK3dTvXXfuObQfgzP_g9WWLXJxRmBmKczce5NbRJG-as1RNQlkxJMJMRHt1BGFgQRIoEkYcjxrwsWo0hzjdb0zYk6STdL0PChAahPmsdSmYiTkiJ1FsEuDonZuGL_bDJUufxeDvfTsusEMzTUsexCmOzSAU1THKuqq22ZVwYIxO2ZcFVArEOKjyqthVoYaqoeLM0AgiSNUNvdlf-9NXvHWHW3M3NIYCImSQRZUlChBHrgMdtTeCAQ5ibu4evANFAxDvJcKyLgo-TOGs6Eu9ELuQuRO7hFshyhwxarQGAhMhMXUmbki9324vtblvKUHKiuyoBIgXAXe1jVYkRIkRismhBbuHAtOLt1skSEDQzi_hPfu4fF2ER5pS0VrQYBkkFwxZ0BKPPftunUqyUjGbox6ubT732OBkcTvPNdHzrtUc319eEaJi-9c6Hb731mrVonF_c3EytRcAndo8TDAKM7r8tOes49Yke3HvwlV_99fsPz-s4r7IRZtr1g7tAOIe9eP_te_fuj_Mpp6wTfMd3f2_fy_u__hv7zdnNkyf7PuetIIokWbQRUxLoO5GEXc4EOM-Tu3MWR3WOUnLXl1ySZOk3uSTkwpSoKwmRUxIkpExS5LRMIqVsduBurkwRa-81JU6SsiBC6VIZOsl8v-8RqCsZPEru6nS6ffkSENysy7I7O2u1bYY-rd8tiDbX-48fpZLCAkDP7525W0p4frkDNYS498q9cZqXeS5ZLu9d9v32cHuDSN3Qp5KePnlahiFlDsKQUFdPaGCYMXdpmaftbr9MzRYDBEmYCpdNX92wsNb5_JXX1lr54flH3aYLBym5Vt0-2H_00YfIaNb2u2GZF8NYlplTgZRuXz6DIApAiq7rc5fG4zHccknhgMzhSFk-_Mq79z75Vt73m_12s99ywbQdxqW-fHI13dTv-YFPp76o2Ur8YI0Plpo3ad-X8_Nz13Z9fX1axs2Dyw9unt9evf_0yYtvf-v-17_-9puf_uS33n66LeW1Vy77UjiVisCFazNrdgcatsbpboIQoBbW1Jio79N-052fbRGhSLo42w99KZkw3M3DVdXqorWpu6NQeABh02bmax8AADgl80BkhwBiAAxHIlnmRRITQYRttmXbd4SEgInpbN8F-PE0O4R5jNN8OM7Xt6fT1KZFa9NwmMbFPBAFAibV4zhywtqWZanzNJ2O42Ea67JY-DjPbsrEuhLDphoetbW7PZ-HTtM299OpupqqV_VqbaoVhKy10FiWNh2neZmnaZmnqY4NCGxpbV5sqSlxTisT00sSZhQiD0OCwMhD6XeDexPhQEC-o4gL85piREImJk7uZqqKZA79ZmMYqhXBHIBEQJISsODtR1d_9Cd-1G5f_vW_-l_Nc9Omh5fHCExbiWqlo9wlQkYgYNRqpqE1tLWqiizNW1gLaz6309jmOv7CP_rXdnXzl_7a3_nf_uW_jlBBESL-_J_-w_fPz_ebDUtCYhEBIg8CxhDCxJyyhgOCO6Ak5LTWK1wbkjhEhNOKbWBEJg_3pQJzeDCzQwDL7fH05R_90X_7z_4FAoUDqIcHqBGZtkVbpcxBEAAB6r4ufJCF7vgOTCREQhGOyBAQEVpbksSSQG3YbNxRUnILUCiS3T0QwoOTnE7jaZyocLfbHA-nzfZsTShd3H-Q-9JUL4f--tkxI5-fb4cu37_YSOJCOAwZwpjibNPVcdoPQ0pspjmRNU2JCKJV7bpMjCXLsrShCEAMRQRBp6Xvu5UmcZwmTuTmnTD4qkkQBApdn2cw1qU1r83NnQkcVrQ6miqE0-o3Y5rroqbIGBjjNC1qAFC6DiFERKd5BYlO05i6BERVfaptrnqa6lRrOAaAqrlCx9yJdF1XlyWlBAKz1YBQs7P9QGBgzbuSS5KSZbvpSy9tmrW1_bbvCj-8d3Ga591-nXCi15qBb29P81wlSwCYOzOnxMtSN5sixIwcbvNcm5mkdDrV0-1koUvTrsvN_Obm-OLlzeasl8zQbJlHQTb3vi_Xz641fL_fhBto67rcdbnOi7WGwuBuanW1jwQGOhC0VjmVACJBiGBCEhZZjw7OCc1sTTsgEjPjSuhlkVIcAyJU66o2gggikJTDsaQMruDg4QgBiNN0KEMXYYnFw5BIhL2pNWXhOldwcFVkqPMEAO4NYo0du4WbeU6sy8zE6C6SWq0RRsK2VATAO72Sh-syT4DESGgK1nweb15eRTiEL-NotYL7OE2qCkBd14d5m-aUi7VFNArAz_7ED9c5iuAvffPrKLktdTpNGenleEuIVf1wPEzLoq2mLO9efysVRoNW63pVrW5qLVxbXWxenr3__m67bcsyz7NZm6fRYY39mM3LNM8IZNrm5UQOEWjz7K6MpE2RSFUhSM1ba8zyz3_-N1vo7_rCt6E2N6gtAnCpAcDDdqhaZ13Yjazp0tQdHMwBQzAQ3QEil0Ia0ZQQwz2xRKwtrAQaWicKisUYPdSsVULS2gRpFTKYhZsRcAQ01wAMhL4IMw6bjokkM3DysK9-8OS9Z1dn2_Rn_-APnifZsXdFMMLdiAPCGTCi5SzR3MOJhYVzyvu-BwMKBHIGJkBTs2YMrE3VQqMBYlvq0uqtL6kwMQI4IJg5ADCyNU0pAQUzWau7vmfCZjY3a-RzteNSj9NcXc3p5jQ3NXcCIAdYanVCgtBWN30Z-tQlFkSMKECAmCVLJwEIiGZ-eLlE4hC6nZsD-MeHdF67vrHmf4iYBBk8CADWFvwdeH_t4mIEmK_y1pU6SKt7dF0PAICZq4fenSoAEVb6QTO_6--qMgITMYI5rAhzNV9FEsywGXKfs4d7eFfSWV_2XelEMt19R-5wpPjbBmFaNY0rhjQwYhWGA5iHWwQSEH7jNz-KoFTycpoAAJiJU50bCbfW5tqiHRPhvu_QLefcbfqHj8_O9sOL6-ev3bvIBPvN5jiOHzx5Wrrh5ctn8zxb2LvvfrQdSsrw_tV7vYB7a6c6dN2yzKUk5hCi_XCx3w3qy6NXHs3Toc89C6YMm_0QYRD6G__0X7352YdP3nnncjPc2285AACX5Wa6fv7KG6-qBXd92ksEZBGblZ1KEKnXuYHBfrMbuq5pTUPJXdeWis0EaRpnIkyS3TkBJcA-5ZU_p9Y0QIQBLCfpSiZzDNx3mYGiWcp5WVozg6DTOGvzd568rPOESP22F-REyWorlIRQUg6I1PWn0zGXvCavWrXT4fbR_YeCGEZn5xeZE0TU2sqwqdNsAankcB-PR9U6lJJQpvE0T_PZ5WUq3fXVy67bDNttndvu8tzNtJo4bPtht93VNu3PNhqGwDrXe-d7Aq5Wc5_dXJtu7z3S-WR1mo43_WaXy2aZda6m6Leno4ejw8Vmm1NCIu4ImafpQOJgzilTKmDQltrvNgERFmUzoBAgbgrvt52IHcZx2GySpGVa5nlEoYvXzvJmOy1A292p-WlZYsd_6__yX_yXf_tvvbg-jvVQhu7RK6989kufe_Do8Y_8-I_-5B_8kz_-B37v537HF7_2W-9y19--OD3-xKub3XkuferKLhcGH4TxrmgfzGvLfY2yqLupaWvKhPtNf_9i_-orD15_4_Hl2ebbXn_1cn92b7_rS3IHSpyzuKn5aiZiwkgisaYrtZmZuyGtpTnHjJAw5cTCzJJSDodlmkVStysI4M3WuGZVbwDL0lozdZ9qVdVq9TBOVa2ZmYOqE-NSvamrrjAiNffaGiWZpmVpc10WB18ngGbqFoBo3lSbO1hr2haW1JU0Ho8iEq7jOJ6OU23t9ura3Kf5lHktjmmE5ZR0aV5bnRZGskWJOTzCIAy8LoJh7iIMEH3fEZNDEImuZEsHizWhkAGcEb2u_pkgIYtIJREkAGjjLClHBIsACwI-OD_rJP3Q93zhB77nO37h539z0jFQtS7Hl7c3t8elTcvUTuPN86fPx3FUreFOxHCXT54TSlNzIpEs6DbPbZ5vbubbxl_96GD7_QjtL_wv_4_MrC3uXQ4X55uUBIjdgDglka5IElE14DvSHDOSUKtTSolJEou2miSzCHqs0doIXJM_AcHrBTAsiWjze6--yTS-fP-9QPJokoQimECEoxoQL6c59b2Bp1QAkSUjMQZkYm8NAQPI1D1crXFKQk7h4MEIRBzAnFnVpRQhruMoRCLc9Xk420lJw24LgG5QhhKh3VCEGNGZ4OGje_uzbSaJpmEmSBQ8lEQQmWjbd4_vX4Zb32eA0GrTNJsqCwMCEQggI25zTok3fd5vuk3XhSoDdiWvazRAYCK4A1AAYCx1FiER7lNGSk29y30guHuoNdWzXQGkkgUBEcnQI0AhGIUAF9PaNHW5lJRzKkmm1oY-DX0XjkvVbredJx2niZNEsHtwFiSuU0VgJo6IaazjXOelHSdFIbdIROFOAVgb__n_6H8ihFY1JYGAZVk2fQ8ABHQap1KyEJzthkLsaqYxlKQAJfEqB0rCKed1Ry-SMydzIMIVyC3MSJREgkCbv3h-VPCy7Y6Lvff-s6XG049eSC-S5HiaPnj3mYVLV8CjVrWI8fYUBCS8jgq9ueRuVZELkWtFdxRemgvTquBdvVzhQJLMmqkhEqwjciQkdPD1F1nSiibkJGHu4SLiAWFOgMJpVd4ScyCEu7kF0DqcQ4RWK3MKjDs9kVk_bLQtgWSuq0UVEOo4p2EDDq21FfO5Ng3u0hCu3lrOZeUqttrW6QER11YZfc0nuzsygVvJeR5nInBrSFS63OpSSgHECDUHjOiGst-n-7vysz_zw616Xeb__B_-q5uTHqcRDM43HWW-uZoCUSgKxzguP_S93_8rv_YrJXen4wEgtLVht5vWP0iNMWhVMgE5RKtLSkwYrh4RnfQNNdzXfvOdGlkyYlgzQK5akQ1F6nhEFreIALP4zFuvvXJ_-wu_-bVpqkZEvAKfsBCpWe6yj1qAxraYOQrNc3NtvEJkHBBXmqqusSwP4yTzaUZCcAsgD0-JViELEYUqb1IwCAoTI3FKgkxV29riSgmFKWeh1VDbWq0WCMDx7odP33z0cNh03_GJ11OXn7-8IeRFFRFTTtrMzYJQI6o7IpFDISqIhZOZZZaN0IY4mAyCBYnWMQoFOlIgUiCEg4blnD2MhKyqu0mW8CCCInJ_uy2Zx6k29eOit0sFj9qCA8ztfDvMtUqABWxympshoamlkue5iiRESMy5I0EsOSHBUHImNreuZG3RDRkDq3oA9pmZcOXuuYH7HWyHgIlolUHeYUEjEFdt-yrhWjE9q5jBIVbyEAThekNwD2SMCAcgXn8HWPNwhETMzMjEwnTH810Lx7iGvJARuy5lZACMcA9XNYtgoj4nRGyqsH48Bq1_BEGf8lD6lzc3KadeRHidB6xqAfCAoNRq_X_87X80YL-_tz_NSgmIZXPWR20li2rrN-n-bqNqKefTPC9t-fbPfCKWprW61t2m6LIMw-bp1e1X3_3oy9_52ZurqWyHb777UcaUhLj0LLTfbpHi5Yubs3vbVrUvpdXWdYmBSPI3v_mtR5_65IvnL5LIeDjYsjx5_z1fTmBAjNvXXn10_2F13aR-Nh1Vn7x8Jk6vvPnmeFyQaakNatv0fQBxEmLqh765CbPWhiylz3VUxJjnOvR9Fu66Eh63h9Nm6AnDVgEz-GbT12lOnZAHB50Oh74ful3_9Pl7udu6mWTpugEI86Z3NypZqwqRpHw6TnVe0EJbXU5HRHR3xzjeHjCxO3mzbujXzVydvU4LMgLgfJzreBse3GfJab_ZaFjKDOjE6XQ7ne22kng6jXWpHnZ-edFabcuUc0cQGP749Vd0mlNKjDzkNM4zC2lTAM-pLNPcbYaqanXZ7vbj6bQ52483NwEr5PQyXIlhOk3gxiQA2KUUag6uS1sBccvpMOz2xAl5nYlHG2cpHXEgBXhonUOViWToHj5-7frqqs0jCQd6Hoac2RT6oUifPnrvWcqo2orF7_7ZP7mN5u4ikJg1YtjtHjx-5frq8Or9B1cvDv_2F36tK_svfPe3CTEJl25ARgRnIsJIa2sIInyNalCXirkC4EoWIeZ5WgJQ5M6z23UdEQFhKUJE81wDkRgjAAIkUR4yBCDxXNVdgbCpkYi7u-F6Q8xJwB1w3aVbGjqYl_uvPq6jVlNzpQS3h_l0mlcOm7kVLlO1IedpqnVurWkuqbkNfYeI03GCcHd3AHVAiNa0NV1hwm42jjMTYQAxxfrJIYCDtcaZ12oAEepa_vGYlxaI8zi6u5oF0nQYIXxZ2hq-BXNYfePgALCSD8ZpgvB1hchJUslq3nd9qy2XDIi1NkKop5kZV50WR6w0BPcACGTyIBY2tfOHF8fjjU1NitSAsune-vSrfji8eXH_T_3sz5zmw3_2n_9XL65fLhHVwciT4NLaj_zAD_yd_89_bQZmlVkYyTwAkEU8oOTVLQDCpZkjExKvYoLmdLy-tWrL1dOf-vEf5qCS87PD7dsfXdlKWWh1vUmYWuo7d1NtwmK1rgM1ZnFVAAcUDyNmXC9CzCzk6u5-14UUCXQ0Wxr85H_3v_0P_p9_l4kCHNwtIiKyFEaJcEnrsCiQSc2IOAIgghHXCZGbSkpmyjm1uYkwuAcgEsfaJ0tZTYmFWAAh90Ukc5Lm0ZXSd5uI6IcByVMutS1J0tB37m2QcnbWfc-Xv1gA3nrlbCg5F16xLqGWshAiB5Wc1td_1SpCCBjutWp4iIi2yiwIuD8_s9pCjUWIKWVevyDzUgFg9eARsZu7eSnFHTRiXBZgMsBpXlb0UWvBLEttzQyI8e6SA4gQHln45jhe7DYI1Hf9VFutNeckJObeAFrE9c2JJBng8TA6giO0qg7hHhY6ztXN3RUJ1qy1miKy1QYQb7x-7-Hlnv_8X_wf0x2KFRBiu920Wlcqa99361l2Gpe-L2o69CVlAUKGcIhQZ-KVK6RmSdg9VK1q09ZWxgcyuDsjjeOCQlNrp8nGZW5Le_7s6snTF0BkwE60OSt50794_ymxLMtSl5a7tEYI1OxOMRruEEzk5ggRqsAMHhEuOYepu5WczT3u8v2BsF7LMKWkS6Wypn0cAXCdT6--ImZXxbSST1hbXRcKIkm1AhHnguZMFOpASEgBLpLdDOHj1Jowhq-QYSRILFEViBwcEazW0nXa5nBPKYeZ1yXnHIGAICxrtGZFIyKGVyUilqR1AQh3o1IIwVuVlNvSNpsHCEYQEcA5gRkLDV06H-R_9Of-NLlOkwLCz_3a118eljpPJXfzUV_c3kawm7Z5ygQg8uFH7-Uu16rmHupNIQ2ljlO4WXUkbNoCXFtjYAbSuUlOruoAzZDATW39-2trgbCOssEN0B1XFghCYjBPXWduhPCbX3n7M5_95Hd-6vVf-8rbXdc5oDZNQjlRXaovWpdKBMjktLqewpuGOiJikYgIUyRe-ZucZa1rO4CZEhNxZkLXuwMhEKwvyDUkbmG9FAeszTkDESeRPnemJkSUwMxWv-zSmml996Nnl-fbod_u-nL_8vIrT58VFGLCwL7kCBDhnFMEUIS7RasITglYUNWQyBGYaTV_gEMn2cGJyFZmDeBKZiYgVeulq1qFEBEo4Hy3HfqsrodxUQB3wCQi6BbCvL5HKCAwMBDAq9uaoQei1qx0kpACIBOmTEjobrU11RbhKwAuzAjBDVZIaJ_TnfP8jv2Psb7vIoRpvQ5A-KrnAgBmXtXEdxgz-JjveScGCwhKzMS8juDVHQgx0D18vTMguAUiJGJCCkBtZutzYnVBIKbMwkjVVk0YgoGHB5gBCXogBKhbeCAROho4RBRJiaiU_OJwSH0eUs5MsTKtENdrrRP_xlff-Qf_7Ff6vJGcZlVgQpSh6xIQhF8dxu0274c-9_mjm-vUZzT4_FuPCtLNixcP7--T4Nl2O7b5nQ-vuv3QdeVwPe4eXf76r7xdGMquWPgyTRdnmzqf6mzbfZEkqA7gRLjfbXbbM3I7HG6FsEPyNgFokfzy2VMwRcSn73z4-ue-_WvvffD44asgrFDf_-Y7WuPy8UVKfWs1D7mOC4T32w3lNaLA6jTPY8oiQ1nmuStdKfTBi6v92R6RSTian46n7fn2cDo5wO5se7yZttvOVGvzlEqScjzcdDmn3N-MttkPskmcSm26Pd_3G6nVDjencCiJW2t520_jUZdGuCI5IO-21uz8wUXqck6ZRVqzcMiJwVWSeMDxNLvB6eqF1kZS-v3Z-X4b3rz6og0dIrzWCgDDZutNl1qJ6Xx_Ya2Be2Z-8dHzVpe-ZHN0j4evvzKdTl7rsO2nY91uN7nrqrdE3JZqGPvzs2ValmWq8xQR24uHEAGEyzyLUGJZpiXctsPGI-hjsd10e-Uam_N7qq5u2mqdxyQJEwGQm-uyLMcR0G-uxje_9LlNKYer02a7W5a52-6Apeu7ZZ4RpM2qywTqtrTv_fd-4gLKfn-WGLfb3eZ8l8tQmw59poB_-HP_5P7DRz_5U7-_9HkZ53vnZ93QdYLMzBAMyEjM6B5ZxMwBojVVM0RuruuplNY6PzMziQgxMeEdspcpd2ltzaspmCNx15c61RbuZv3Qg9kq1ViHbIgkwsRMwqZu1lLuzPXR41eKMLCb-u3taI7zVLs-TadZTS1oVkNwcz8dR3BvtTU1gBi6TkSmeSk5VQ1VPZ5GEk7CVtVUGdg97k6KwR-vGVfrj670RAx0a_M4I1MgqEetrU2VEYXx-cubnFLTJTGaGZCFw7p6t6Uhkpu7WcA6Q0AiYsFAsvBhO5hb1_fuK666fvzot3X-FeBNNSyAkRmZEjKSBwHqUsNaa3pzffzi933hwdmZT8unHzz4H_z3_v3zy-F__3_4K---9_5s2J9tUyqppP12e3F-8eUvfuHv_zd_b7M7W6oSohDDetIIROQsW9UFAM0dgDGTsGQWN0NwVV9sgeXwZ372jySWcPyF3_itpy_HwzS3adbaEIJFYsV7a0PmVpecElCYOjLDmpYGICEMSF2uS0XmRGIegJElhSsJppTN4Xf-1I__y3_yL3QaiTERRQDw6m-E1S_m7pwkwol4HRJZMwhfNbhhtk6K1ou3g6-jUFPjJFLyii0jJMrCIuGAiVNXAjznzVLnlNnUu23HgQHBKQvTm6-_sszL44eXofaJV88eXmy2SWh96a4RNaHWVIRFZKkLBjbTeVlSSkIizARYciqJRTK40-qQRyLmNY9KgIxk7imJe6h6TpxTQohYWSvuGqHhhmxmAWjmOeUAR6JlMYNoZoTrTxgAB3VLxOG-G7rEqbV6nJtkvn9vV-cWgONix6VW92ahasxMzBHeqnvEMjd3D8J50ZwZAE2hqUnJrS5d5uTx6VceyVryJ6KUOGdJJbWlJhFz3e8HSRwRhHDv3q61OpTiptpaW5qHM8EwFIwIMxFeWmVCQJiXxdRLLqY2zcv1y0M1m1rlLCkzAh5vTi-f3RjCdr959NoDBl5O43Sc-n64enbVbzddX7ou55JSYgLY7rY5ZyIWoQhdR4GcugjnnMhNGAgB3ImFEVtrYAquCBCxqrzXMBZKTqYaCB5uVT8uFiIguClxQkBTV1dMYqHA1FqVlDEwWgt3WxonpgAmiQiri4iIcEAs07hOEYjljleyNAAH0_XLyElMmzusnW0iltw1dXMLDwJcR6qt1nW8euc4UhPJEKHqOi9IQMxWa8rpdPNhzrIuIBhXTSC76w_9nt9V-uGv_I2_sxk6YzzNGhDg-Lu-74ttqWZel1rrRAiH0_zFL35-Ph7nqWlddmc7B9hfXlprCKGtImNr7WNqOoYpgBNjnUcHb9qYaqyWoLoAgmSBUNe6RqTcDEMIQgJjNkRcpllrNbPo-C__3_7vu7Pdz_z07ysdbbLknJZqS_Ne-pQ4kk3k3oBDwGK9BCBHmPpSETwwKhomMnBttkIjCb0UDjNwzSyEQgBMIEKuSg7MGBjabFomCEtEsdLh1JoqC5XMU20K5ugYxg6qcX2Y_t6_-a1vPnv50fH4-qX82R_80hc_8YiYkjAFbboylGzVCVEtKDFmDuBaCUKCoIFBhE1LgUSNgsJA1QwMkmSiNQkMTOTWOHH1RYQAYejy2X4jjNr0VGvzaBaQZJ6Xjvqqbk3BwB2muhAEkDvA0tQhgD0gkMgbLmrjOI3z1JbWCQ9FtkW8eZgS4rzUwJiqeeJAWLS9vDlagBP6nfIdEXktyazzrYBYZ_y0PigRBfEO_bk23NYlWKx3BRBhwNWKwAFAjBSxeknWljACilBmhIB1A5Azp8SAIYTrSYORupxLX1KiLERECOTuzKtJIMIsEQ69bDdl2JRNydsubzoRJApyc0G6E5J9XEK4Iy-b_fzXvmoRkoSFCSnCN9teEm2GrpRiJ72_3QJB13U301Iy_47PvzUICwGyZYawULCb43R9dTOkDqpfnO9_5ed_zeuyGYZd6trx9OjehS7Lex8-eeWNy_DIRVLhJIhAgd7q6cGjBxng3d94b3s2eKP_79__1zdT3e3vRVhYE6vYz9OzD3_xV38pZXjy4c33__APmtWXz54jEQIt41y6VErJWZKIVhXmUiQgGLmN9eL-vTDIlLal6zrRWslcEg77bK2u4TdrujvriKDvC6HnTK1NwtJ13WYz3L_cmHmrwESbTT_eHJaj7vf7Td9tN52bsaR6miO8DB0yA1Mauuk0AtLp5jheH7Utfc5JuB-KuZfNEAQggggshAgiCLoQ6Wm8vdjdu__gMYFgEs5IiHVum6HbbDfnF2fTOJ8Oh7OLc04CLLnrTrfHzW6b-2TePnrvo1defYjCx-O0v9w0byidNS9dHob-8OIYAV2fLh-9slpcbp594Kahuj-_QIBaKzGaLmAKFqHelW6z2ZZcYhklE2CwSCoZkOuyRFCrSrkgi6QEbtjqw4cPGOnswYW79bk7HW77rnN0ocSCrbVUhroYDfwP_5O_vt-Uoe92Z7vNrh-GjOBn2yEs_s2__QWJ7k_9kZ949az71i9_Y-hLFskRiaQnLkiFhe5u3dHcTK2Zt9C1sI0BK4WTGTG8NV17PXVeTqex1gkAhLDPpcsy7Do05yzn5-eZ5eLyYtMVRvSqiCzM2gwA12v2Gnxo6sSc-15y3vT95eVZKJwOU2umpsfbo2pdppqplzxMU62tTuN8uD216tM4BXittbaWmJdaGWWp4RamJkxtmud5UTcIPI2T38EJwDBM27JURHZ3FF4zhZhIW5um0zzPAVyrhRoRAsY0L6VL4BoedVFvDg5rClGtIgCBp4zMzEx93xMCulnVRJgk26KpdGsE9e6gD5CFIVByArO6aJJEmSTz0rSFBjpQ5EJM9PDy3o_-4Z_68nd86eF2K04__VM_9qf-zM_KJv_P_hf_8Tfefm9WDE-ZM68iokVtqbcvnqe-nE6nvu-1uVZdZrNAR_PwakcA0qroFtp8Ma3NLSSRqi7LnDifffLx6TgfT5O1-vzJU_OpLqcIl07mpuGuS6SQkjomJGZVBWBOiRlTYiaRJEwUHlk6kcREri58Byl3BKvNgT79Xb9TAMaXV4kTk0i-BID19r8q11wbpzQdJ2Fp80LE7oYMSBgRwhyIQAxIBJhYVhQmoeSSrTlouDmYS84YmHMvXQKgcGBOnGiz3Vy9uKIkh-trB8h9X_o-IpY29X0Zp_F7vufzH3zrqoDlxEIc6oS8ZkRlVbmZAYCHm1mfc0mZmEQYYpUWS2LJJSdmQWKglffPSOs431ZtAlKWJCxrrC1LUjMQrubNYKkawHqHewlEMkNfGbvm7oEIBAgQibm2OvQZkXJK01Jzlm3f66KSuLrOZsGrmxNrVSSapzpPTcPVrIWamWsQQ1saf6x-A9euz8zyxuuPc8JhYP5zf-EvuBohEiGtcjiEZtGLRPjpOOfEKae2NBbOJd_ens7Od8sym1rfFXfPJa906qatNlPzVLJH3F3WwyNQzQ1xmZZpmcexpq5U9ZvjqQz9e-99lEpmkdvbm8PNpG6lZG3WpsVMJeXD4ZBKTiyh6u4ioq2teNpwXZP0gMi5mK2EfXQ3xN9WiIa1FhCBAevPLwx0Q6b1GxZu4I4AkhOuAP5wZgGAVqsjJElulkXMjAncDEUAwFtDJMlZW0uSzDSxEK7yVw5VSRII3iz1_TIuKZcwgwCigLsEYRCBeZgZ3s1QjQgRHJG8NWZWU0CCcEIHD2FBAE5pjWWkUtZSJgptuk4Kf-mLn_nzf_JnvvaNtx-d7x49evji-vof_atfbc2WFr_rS2_-_K--TYwW1uXkS_2RH_6df-9v_4Pd5Zm7j9NYSler78634-kQqsLSqkI4i3j4UmeSrrVKRHGHcFGrCkiAqw5v5cSE1lhXae7urQECEUkSaw0QXGOp1TBy2jw9LN_51lsbwWfPbwJMm4uwhkNwVJt1AgkGCoA2NyTWqoHRdx24E62QeOty524iQiytGQMzYEToukysKkwrQcyq55LdHCMQggtjUCklkXS5gKmrIUIQuZsglyR9Sdj3n_rMaz_yPZ8fpP2LX37nqx---I2PnteG3_nZT3Aq277v-9Qnbu6X97bzaWYEUrSwLBJqJXNicgNiYsScad-VcV7W1VPuBACLCNOq0AIKNDBtuh2GTddl4dtpbmq1ea1qFvM45pIPp5Ok1ekDvHIALMwt5xwAzDTPLUmCgKVVVaP_P1N_Gmzblp7lgV83xpxzrbXb0997bp99q2yllJSSEJKQBBIYDFWmcZUhgDBYmMIUESbKjgCHiYoKogIcrio7omzKpjABxlWSCaAowKhQKpFQppSdlN3N7ubtTr-btdacY4yvqR9jX-zfd-9zzj1n7TnH-L73fR5EEQRAayYszDSmVM2EAZGzyK4sx6Ps55qY1WLKDBaB4OYAdOXbiiAEdwO4-gwTIBMBUlxN-gMJOm6zx1WhB9iIIkCbNXcPzzkhYFj0px4gCyMjdjYC8ZWwrJOhzT1CB-EpJyImCJEEEdq0muckyCRIbg5MYRgQ45iYuIcBemVZhM4ud8OQk8iQuIvIuljP3FjyX_lbf6_tI_EoIz65nFOmzWpFQFq1attu56fuXru83Kdh2pfdacJbqywQDx7ePzoY16spkdSmX_zmGycnm_e-521f_8p3JqZFoQWWUpJQqAmhMz08f_L8M7eIcDNMU-pRw2YQ24vd9RvHR0eHl_fvfePzX3zjO68cgI6Hk9Va5z24EqdH332Nm9--fXL76TvoPp0evPnGvfFgM0wrglhNIzSVxO4RzCmxLlWYBanTPNndG7irqh0dbrypiGwvdqenx2nkZZ4hCMCt6Xo1TtPYEUlJ8v783CEOj0_ned_mtlkNEGZLHTdTGnjZzQhIDCSUE3XBQ0qDVgPy1eHx-mgSligLMQeE5KSqIhgErTbXCAcwNTNhmi8unn327n633L51p857tdJ55K6-315OY7q82B0cHYrQwbR5cO-MmbMkR9_v92EGREDi4V712uEGc6ql1FIQoUtbWVKEr1bjfrtdHWystjLvW53BbH1yYuZI2GoForrMgqhdeRXk5hahZV_383R0iJyYed7tzRUCxpNNuVwiQpcZVCOc1F_6gfc_fvXxMGUtdZ73JDRtNhJoYZspbd94om1OSbztzx9c_uTv-6n9-eX6cMXCoTEO49nDs6_81lcON4e_9_f8CGpxg1deffPmjePU3RmuAg4IaB5AZk7IDOCBhNiKAhMl7nocIoIINTc1IgDvWVkXya2VlFOEExF6rA9Wh5tNIsIAICr72fSKUcgkzSwnkZSa1mlct1Y5CafctAHjrds3MvNcmzOWZvO8q2VW9Xmp5rAsS1lKhE_j6G61tt6PQwxATOPgFrVUCNjP-6oGATmnZbc4RM9XlNqqqkFobeba1LrK092BAElarWrqc9mcHFvTWmqYu1kn2COAafPaEMGbMiMCai0YYOqOGIQsIiJLmQkZkwyraRgyE0EgELZaTb2VJcK0NotAoT5RQO5VQY4wRGaAIQ1tXlarfP7g0fve_vyG8ff-7Cff9fwzP_TBD77vuVuP3rz_J__c_2HRpSJNR8MwjvvLnbmBeSvtcHNw_Wh9dLz5-jdfA2wAghCUpGtVJEtTJQREKLoAcR5HCEAWTqTuqspsz90--IlPfP86T_fefLBZHf3TX_5lwOFyuzP1IOw9HAAHdwrgCEKKt2Y2hP0pbMiEV-kjd3MmRkbALiCTaye3nnn72-_ff_3Vb70iHlGKmTVdEkOfrhKydyFm4mGcQhsTMSESmZmbS0p92aBuiGCqPSbQT-RIIik3aynlcCdhcwCGNCQmYuHa6jBtApyJ05AlJSec1qujayeb1aC1fs9HPnS4Ss88e-tdz9w4OVxnEldDwjTmXphz95xTuKupmqaUa63CkpN4KDMyZQgQFiLsK3JVFSJgam59OAtICIj9JI1RmzFzeF-229zUEYBkKc3CSlGR7O4X-5mQLcAC-41azd01Z3HV29ePI3y_1ICYpkTMpr5b2r762cU-kGo1iyDgZg0RDaCqmVkge_PWrNUyroZWbV8KIaoBuD3__O2DPLTdwgj8J_7sz9FVMy6YeDuXacx5zITYmuWczawuS8pZzRkwjWkaRN3zkAkgpRQAXRsMHZKJUEqJAMDozI4wN4vVenr46OJiu0vjNJeyVD17clmWcrGbjw6PL7b7Rw_Pbtx5ytqyPbtspUjmsi_MZKattJyHWoo2RwDrZBcCM0X3INBiLKJaGMgRtC7jMDpALUVy7pnCZiYph1nPugEQi1ydZYnCDICI2bQRJ3grG6zqQh0RBO4GnfEZPa9MTQ0DWAQwdCnI7N512YqI4K2_bAACISBMEMytezfCnJmjH0U9BBnRr34Ld2bC3ugi0lK7nWTIueznbvxtrQW4jKPVOh0eImhGVGt_6d_7I_-X__offuWbr_ybP_XJh_cePXpy8SuffznCDPi9Tx1_8euvB2LTBksJQMi43281QOuiPclodnL9dN6X7cUl50G1hff8dkQAM4U5ojNzR3ahB-HVZzfnQZsGWN8ph-tb_0zhjpgliLQpAVA_8UmGaI8ff-N3_8gnXnrpqZe_c58Jt9aQqR9rscFuLkTcCQ9EgRCEGIEiKdw6C9VqY06mCh6I0EpVVWIy894AEcIebukR_6oNnBBcOIfjOA6IAKgOCoCIsB5Ta-4IR6ermzcP3v3irQPM3_zKq68_2W2XOs-1FluKvXHv8Yt3r3_f-55-3zN3Xrh9_Xy7B21B0D8iSwtCS5k4s4UrhIUzcSisEmMn51Fo85GTanO3vgJCivVq3Ax5yDkClta0uTqqmpqbGxG3pofraSke7oQUDuqxVAOioirEQZAlMbObM6KZElFV3YyDgjdV4SSCOaWyGA-82xcO8LfsvN0JP2bqPjhEUDUH8Agze8vyiwAgwm7uAfYWrJMQmYW7-Z3Je0gX0Cx6LhSDAsDdEXt2gShQhAH6G4O8p3cJRViIklDOSVCYeuqpS6CRkFJKTD3L0Mv6KImJqdfpvZukU2IiRN7tLyUNg1BiVgPAqwYPkGDgf_63_tEAeXWwSmMu22VY5dXRRqvmlB6dnXnYO977drX26Oz8ye7y7U_fvna0zkO-uLgUBkIap_z644tH293JtaOzh-fTwfT66w_eeHQOOUUXYB8fcpKHlxdieHR0ZEVzRPJwNhTuwqxpszo6nI6u39xty9kbD6-_cOvlz345iMgaIapVdHjtW9995esvf-YXP_WDP_ETKxm3-z0m4cDNejXk4fL8fNqM2mKYkquNeRKC0NjXkseBCceUxlFeefXxya2T3eVM1KOU7eTGtScPzjsBnJAODtb7_Xx2ue8uF4JwhM3qqLXFLcgtIg4PD9xjNa1Y2KINA5eq4daKHRyu1eu4XrlWDArHgMjjBIlbbbUpB4IqIBLGkMZayjgNSSjMd2e7nNOi9ezsbDWtI2KzOb48P9scHW532wBPMprBybVTbS0P-fGTJ5JovR6HPO4uzsdpQsKyLNZUazs5OXLBy8u5Fc3jaK7EWYSRYj9raTWxuMVyccbC2urq6KSVOq7WSync664AeT1CgEM0893ZhdW9u-b1ERMu844JARxRmBHBQy0sDm4c2VKOjk9dY1EbxqnVUmu7fu0EAK22JEiA--2y3hxjubx4sP39f_5n3vz6g-PN1GY_HKbHDx9-8Uvfffr2tU9-7wcHjsvtbr0Zv_r1777wzE1ESoytVSToBvXmkRNJEmZEwlJKynleSuKEhEm4J-3O99uEHN73BWTuriYkTa2WkoY8TlNOSShJllLK9vJS1aJPrSLU1NSnaahVVZUEegSFmJAYHZ555qlabVuLe-wudstSA3ieFyJurZVWUuKUGIDAo9QrMyYxAWBtCojb7d6xmwd8Wg1CuC_FIFpRiEBmxzD3VmoSCg9C75YyZjJVDw0IJFkfbFS1zhXCA7zORRKHmZm6mlcjYQCzqghoakgEBO6ehwEMyjzncQBmlgxAQJQmCYKy3dZSECBNqXPwhYiQ9vs554RCrRZmZKQAIBHx5bmnrn30XW__g__rH_uRT3yIMD1-8vCv_rX_69_6H_7-L33mi5yTAbfSllmXRYd15sSo7kU_9pGPfurTn3nt_tmP_8QPfOHXvzLmbGEI4KaAXeFNrt5DjCJZBvSm48Gqlda9om3ef_D9L_3QBz60L-Xv_sLf_-j3ffA3fuMrj3ZnagCukge11qoGRJ8HaWvhwZKEuVZlRAcnSq1W4SQ5aSlJuJbWYRXTdPjs-146u__olW-8TMAnd649vn8_j4Obh3sEMDM4dbybaksppT6hIyIWNSMEYkYPJgbuuuVwc0AgSYhhCiyMKZkCeKymVRDkcR0OhJRSNjdikZw9bLVe7ba71WoN6BSRmAhjM2bheOm5p1eEd042h9ModLWfBncIIAxOrNorvIzIIsQsEE4E4SbMKQ3YR54RQGTh3iwQTF21QztCO80U0dRyytpUhEmwVt2X1jyWqlU1gExVhBGxmTWL2pSI3QAAmjth5JTc9HizQQCRDB7AwID7bTXmR_tlXiogldJKaYG0m-eL_QKBCtZKn4RyLQoQREiCy9zmVgeRnIch07PXT7LgtZOp7vf8c3_hPyBGVU_CpbT1ajS3sEBkMxOh9WZyA0nEiLWpuTJzWGxWAzi69ZO3pl7VJXYPNQ-E0trR4frycp_TYGZuUZtLTrt9fXK-nTarR4_PCGXcjPfvPzB1M1vK7uBw01qr-2XarCK8aWXh_rlUXbAHucMBEIlcW5Js4W-tj7EsdZhG0woQzGKuHQndVUSEFBHM4uYeniR3wBkxWWtuRsQeodrHlCFDRnNEIKayzGkctSkyILKFExETmnaFNZD0xEtPGCAy9lQ6SyIi8EZAiBydYtlD2-BMKdwIPDwIOdz6EUpb9ydcfUG4AVAn6RIDEltTGcYIbl6GIYEDEP2b_8bPPLq4_MVP_cpTT61feObu7evH3_zW65_76nd4wiBKIz1-si21pIRa29PP3v3a53-LObVoYU7d-Wc6z_Otp55-87XXZRgwggklQhDBg6Fn2iKn0czcNRwijFIC72-VULcIyDyplUAg4TBFgqpKQwqL7vQwYEioTbWMTPLineurMX3tO6-1oiypLQ0xQnVkJkAcUM1NHQHdwgC4C-GBACDl3LQZBAt1xItkcVci6WX8nNgBRBKii4iZEkEaGDBkyGoNAYChlDYNAwsSCQUeDPlkk1rBh29ePHhwti3lfL-r1ZWCSDjBMMj2fL_f1heevpMjnjo53m_nN88vD9YTII0EjN5aJUMmRscslDIOIzVzxiuiQs4iLAHOGMLSvK6mUVJCwGZ6WZd5aRrgDsSgZswCEeYaGExi7sHoCGodZYRqDoDracXE3mwahmpKwrU1JqqmKSUzb1VVHQlW63FfWoRZM0QaptHdOwp6mlLXeEV3aQZY7_UCIKF5N369FaNDDgg3y2kgpADyft6HXi8KNycmZomANOQkHOhmjkTESHwV_ewZ3H48Bwx-623X-wjM1NsIPa599StDdGnolRQMEBDVvGeLiYiZiPns4ny1nhJzv74SIRKHO7KcnW__zv_4z4dxlYaMgt40JQmLg8NDEtzvZ-M4OjnYXmyNiR3e_-671zari_PzIXHKtF6t5lp_5YvfIKZbN47n2ZaqtbSvfutBTCmtB60-TSMkbqU-_8LdWpUgDlYjgbPwZW2hvsl8cXH5-nefjKvx1jtf_OIv_fqb52fV07Mv3d4_Pqt1Jss__u_-sfe8_3uff_d7v_Qbn5umevvZl1579f766PDN175948adnMR28_HhygPHlcjAtigCGMY4Do6-mHnzouZRHLzjUEZJN05PH19cHJ6sIKCpDcMwL3MakmQp2txj2e-Xeb759O3d7mLZl9U0ysBWCpEYQF4l0nCNZa7jkNardVzBJL3Nc3jcunONmM2VAQ6OD8eBOfBwPeRR5t3SvAHyNI0OQQTLbje3ZbXZpDFvphVmKWV3dHx8eX52cu1kf7lE6DiOTT0PaRzTappqM20NkB6-9loa8niwGVarJAxN83oFjubKiG1Z5rl0d607BIMQmxkl2Z6fdYTt-vgmQhCSuWtTwm6OcmJ297IUAi_L1mo5vv1UmG2ON_N2Dvc0yLQ-dFWranNdtluIeu_eg9M7d8xtHAc3vX_vya1b1yAIXC8v5jwMy3Y_Xz5aEe4uLn_s3_jRN15-vF6vFWEu57_869_5oe9717tevLsSdPWyL6vV8Pjhw9OTY1frLRwzQyaCtyYHplUDGEtrET3P4B1c4REBtNP5IE-dVbnUWpsChLsTccrjlYaD2N2qqjUrtYTHOE5mPWeMzExMFEHMu8vLYb1pqkkyINy6fYMsdvt5KV73u_CwCG1tyAO4lzKLJE4pT4O7koiqEiMimbae161zqbUYBDARURJyiHGaLs8uIYIgwt093BU8sI-krZ_4WWshxgg0s-Nbx1ZMq5ZSSVBIIADVay1aFcyIQ5cagG7hbsAETMzkFtM0lFrNjFgCQTJraxAgOVtpWtuYEwi1uZkpp4Tu5i5EHeUOAeCeiMyW9UQfeOc7_8Qf-dkf-r6Pi-T_6V98-s_95f_zv_pXv7rbasiI47AoNjUkJIjD65tpGKFVq00R_52f_uTf_8e_GIGvvf7qwWq82BYkYJboIzBTCKDEbiaJtAvU1DrpJBDyMGitf-F_98ee2hydP7541_vf8fP_-J9_8od-5LNf-FJdigFis3AIDBE28D7cCfAe40QEfmuuJ1kigphVnZOYqXscnJ4Cwqtf-7a7EsL5-fl7PvTBN155w8zcIMD7Lgr64QmBqQ99DIisqpmhsDVFDGY2d0RkRmuNGFmSqfFb5pdAQISUBkcaV8fuNqScpuwRaRgEySySiAyJSSiQhU6OT8chM9jN06ODYXj_25_fjHz9cJxE-q_amhJCU3Xv4zARFkls5uExDrnzIQIi9c9o4nB3CG0tALS_Z4gkCxDs54bEZtZKc4i-iyMRxNjPtfbTv0Uahqqu5q3ptBovd3OzMEALQERkgggCaKVcPz0-Od1wYFO_3O_dYhiTBsxmF9tS1c1iWVpOqZle7pYsYhgirBrM0NzUTE3L3CSn2gwhRkn7i4u3ve3pg5SFHcGwGf_JP_tn-6Z-yByATBiBwzC4G_wvkrur1QAB4ziY6ZCzNXUL5g6HidYUARyASdwtjykQm5k3RyCttppWjrEstbTGKT96dBkA1X17udWI3eWcx2HIsr3ch1ltNWU5P7tYHazb0sw9ArQVJAqP1tTdh5xLKSKkVfOQzexqoN71Q2FaGxG7a08CCefOMgNAJnJXInRVGSZrRojg2sc9EU4EIgLqzOxmCOEB1KFGCO4ukkyDiU1b7-nWWjgN7pbT2OqCLKoqKUeAtZbHUVsDCCDq8WJ1SzlfAQiZEKOL4gBCzYgI3BEZKFmrnAdTFUlWawASYh4Gc--_smklpEhx-6nbP_kD7_sv_8Yv3L19enC0-qV__i9_2498Yr3azFYsj3U37-b9ajr89nffPDxZTeO6tmW_vSSWVisTE2D3ZpaL7a3n7z65dx8BGBCaQqcmAWpVSrKUEoiU0M07HtjCItDBHSGsuYJjHwNwxJXLqWnjbgsENLUwoCE39-lgff_ewxfuXvvIu166e_vGy6-_2RnBtZZq4YHM2Fprb6FkDEySdAUsAhJTLZVYtGkHVLbaEFCS1KXgVTAdmcndcsqSu5IDCZ0pI4iH5TEhRWYuteacBTGveEj5ycO9mXrUbVkeXy5dLAUA6XRd56aqcysPH28t8O6da2Oi525eGxPOVnLivJqI2EyHMbt6yiKSwgKBzZQIOXFT724EiMiSzJwC8pDzkC53MyKYYdMQFvUo1T1Cm5JSrUEo5oEIS9NSDQysWQSYQsoyCBEQEUb4kFIAJBYiIKSmioCUqDexBuY8JlUQoX6bZUJJGcCnVe5HfyCEQA9HfEu6RkRMBBRxZXOOcL66ZQECOSLAv7YCQHQcKFJ4MF2ZhTF6_eaqGGDezLRHi5muIlFqCgDCIoR9RQEIrVkzM4heRmQiSdw9yXEVPSIIUA_EAAAGZuF7T54cbdYi0vcbCFeQKCf6lS989VO_-rkpb4aDVS0zKAxDymlAkHE1vvLKa8fHx88-d_fb3_w2C946WX_8nc8-eXJx9ugcw67fOIyAexfzo7Pd3advj8wF5WJeXn3l_nNvu0tZAGA15mkzlVrE-UMffPHR2XYcKBMH6eW-JsCPfOxtQbTbbl96-sa4Go8mevM7r__UT3_s9q3r0_H6ze-80moz9M3mYDxenxysv-93_MTR8fStb37DcXNyunnjwaPrJydl2Q8dloQMCF6LmUNCIZqmKRGjMAC622v3n-jiDoEGbZmF_PD45OzsYjocd5czuA2rlMdpt9Q05iFxmD8-O3v6zl2zaqok6eToTgvdHKzCAywy043T9VxaZgJ35LwFnSRrqUtZNkfHyCjChHK5X04PD9x8zLmpLbXklBInR1BTVdvPs1obD4-RGL0BEaUBsKU0UsR0PG13CzHtLuc0jKAGwCyMEOpNCLeXl5vNdQ9zr25-_uTsztO3ptW4n2czf_7dLz558_7Tzz3l7ueXF9ABXAAY0eZLQraw1cGRNx9WkzVLU67LYsVaOItoKRBR91vXdu3us1YcCQwgwlpVV5RRoilCm8_OEnsE3377i1ZbMxtTvpzncZqY07geH75xZhplN-_OnqyT7OfdR3_4o_vHLRIu85PP_9prP_PTH75xuA4zrRWIAnRKw6OLs6PNIXOHfMKUMxgKkYgQ0TDkWhoy1dJqrWau7m4ukogo3DMKEEdEKUttpqqqysLuIDnZUgN9t9ububnvd_tWCyBZU404WK1UDboKqjbVllJeahuGBAR1t33u7jPVbTvva63CXJal1hpMEWHa-rYhAhILOJkZI4R7q6pmKQ9mVmtNklQVibJQ6kCBamUpZkYUqmrmiOBVhYAl1VYDWevVVS08hHhKuTZXbcRRiyIxYkSnALlps5Skr0Go06Mc3AMItSlgmNmwWrWm4MGJy1I3q5EStdKY5X8x3gsmgIBal_60jWjCFKCUcAP6u37qk__uH_y907R-_dGDf_8__I8-82tfTRFIA5LU2mo1TCmsld2eWSQn0NZ2-ye79u_9qX_7r_xn_zWFK-qybXk8OHv8OA3igEnI1YigNSfCcOjnE2SQnN3MTVebFbKP6_SjH_nAsQzjlA5uHH7z5Ve-89qrn_yB7_3V3_jivN9Hkr69R2I386a934WAnemETMho6iLcD6iE4aEAtDo5QorLBxcpEYmYKgc-_87nv_udNxCCEcIBGNyvbm1JJMzzaiilegQTMrF36oUHEgWT1po4AfS3DA3Tqi7aj-WUs6mJMCYxbyLMYGkchs2kFhAuCJwzMY7TgIwpSY_qjyJPPX3jZLU-3uSjMR9OecxZm0JHQCCGRzNDxDHnZqq15ZwgIByZUJsxc0q5U5E9wDxUnYj6pyUCkHB7sRBLLY1YnKFqDcRw0IBS2tJaEJemknOzaNoiAoGmcbhcWlCoWrfqdPmaMKHxjeN1W6oC3nv0hISFc2mNEj8837lD83CMIEwE81yr2pBlLi0huVOrtSnutlXIUXiYUmsGGAF-9_bt64fT5fmT3b6sRPKQ-I__3M-5OgJqVy53Zg64O4RjrTWJXOH-PMJ9GkdrSoRJ-ocf5qUSgIhE0FIKELeq4ziYujkgASE3CHMn4KJXSZOylFoaSnJ3Ztld7udlQQQCkJy3Z5ckEoARoE3HcaxLFWFCxgA36-BhLXM_VJs2MI-wfuCzVhDjaiZSGhKBW0QPeHTMI3mriMgspgroEBFm6P1gGRBBzFaLWQPqzMnuEnjLaIoU4ZSytgIAaRjKvEPGcGNJHnr1PeCArLrIMJU6OxB0PaoaEXQFWB5WbtbaAoTdydfRLu4uDGbhoCIC1rFcQSIYSCKAIVfYRMFMP_YTP_ntr3_tW99-_drt4y9_9gtvvnnxzN1bd28_PaynX_r0byDJfilHx9e--uWXb10_eXK5219uW9HACINolRw9FCy8RW06rIa6X6j72YGKOUOf2HqAIRE5qmuEJxnBDQFK1TRkcEdEM08pM7rWFgxAkJghQFLuOiiHtt_vXIM5LW3_a5__BhB_4p3Pf_Fr32y11mbLvgUjhApSq9XCu9FmYGZJdVmIuRVFJhbqZ0TTJkQkDAi11GGcmFDSgOCJBBAhMA3DvGh_XApmJsyJqSfjc5IshChJ0jgUVaHo0Roz9DACoEDX0HnRsuyWuiwVGO8_evxrn3_5g-9-aUp8_Wh9O6_evLgIC2BZ5TwOEoEYkBIJIGMwYk7JXZkwJwEzAmDBccyJuee71NwB7Yp9ZeAEjIjOEEAAiGAQVwsZWFoTARIigSzJmqmqAxBRmRv2OCfH1Z7VwMCFeTUN2owzzYupGjIQePfaBEDf9oY5s5iZuYnIlXi3T0c6rqy3fgkJUYQgus_cm6m7hYdZVwgjIfQOnySGCA-oTbnvDxDULFQD0T3AAxnwigUBXRvsfbLUx1QBgZ3wT0TISBEhjE0NOBAJAFTN4gpL1P-n7j1-fPP6MWLnrAER9v9OQ_6rf_PvnT-Z8zRtVis3dYuDo4PVemq1jaOcn20Pjk4wQQIP82fu3Hjm5pE3D4jVmIGwmX_pG_fOZ7114-jV1x6uB-GUvvqt18uu3Hn27pOHF7dPTtV0Gsac8nTt8NHDs82UViQBuD87Z7D79x984_U37pyeiMF-v_vqb319--QSjlLi8c61m5_7V19EcI6488ILN-7cGddrgLo-uv7FL37-5PTa7evX58tzmdYYdTOtch4oUWs1j6lV35cyTkOpJRKq90ZHlP3FwfHm-vGUiRjx_OwyD4fzsttfFGE0VXAHpPOLy8xM7vN-WebdnWee8tpKqU5EgwyMUdvQo0Ucu6W5u4LlKSUWdEiZhGg3z-GR8iDCjDDlFKGbITUPYsoDMxCoIdLZkycyplprK_Pq-DBUp2HFBJuDqc6VCXdLOTk9dgyrNiQm8GW_5yS1lFbrtJrCoLTtNG5sqYhkWoXkycMnecrEqSzt_P6j0HjztXun1667lVUerWnbb4F42V4yRi3L6viUmdMwdGSH1obgUQ0zkTChWCumFZHXR8etNAu0MJt3KUka0zIv5racbYm07NrzH3_PfFb6CKmqHmxWSXJdqgJyglCf9-dTzhH69a9--8Pvf-98efnpX_ny7_iZj14_OIKIebev2tY5jePg6tvtDoE5sTCFmTAl6h9-MlUitHCzaKq11QgQkSElRGS8SmRHOBFut0uXYTuipBQBWmu4CTEFIqI1RQTJg1lEF2kQ9ct8cyUWcOeUgiKzuNoLb3v7iLhf2m5ewECbIqM7LNud5GG_nxlwmgY3Y6LWtKfJA8LcVA2RWquhOg6TaQ0H9BjHgRG3-4WYtUPqAJsaMYX1el0TzvN-TxSEbNqA8OBo4-FdH-NFE7GFE-K825NwaxUZwCHc0IOTeH-iAQB4GpI2zePYg0MkjBHINOTsgdZsWk-mZqpuQURlX5CBiF0LB2YiybKZ0u_93Z_86R_6gd_923-whf_f_8bf_tv_wz88f7zEkANJHawZEJnF-vSY3FptSL5eT8v5xeVu99GPfewrX_jco8dnAWS1mPm8n3MSRHJ3MAA3CCQRRmEk7iU9cAB2N86Da00it28f__DHProZhuPN2gNefOmF__Hn_9kHP_aRH_r4h_7pL38aq6F4wsQQ0QIxkAMAe80SuszdAR0ICBADjIhRCFHMff_oEjDAYlyNgtxKu_3iC_ffuG_aBEmYARGZQlU4ebfBMEGEtopIxAkirLUr3HOE5GzWWAQCEYUkEVMEIhOlTCxAzCI8rgCDc0biaXWwzHtvbZgmTkk4tXkWwpPjQ93P69X0wjO3PvSup8n5-uH67p3jKSUwJ6acxdx3y6OcNhGRRDS81tqn-A5krkjIRDknQHJzTtTM3CIQm3lKuVRtqq25I0F4iLg7AOz3bamtuQdQtS6q5UBqZq2qOZSmechBtJiaw1wrISFTnyYT0dM3r_vcTg_X98_3QnRwvHnjzScOcLEtF8siKSEAM-VBVNtc-s9Og-g_3laKllpSYuxlfQBCD0dBeub2aUZGx-unm9VKQJX_9P_-zyGiMDJzKyoiTa1VRQJOnHO6PN8l4YhOoXIRcQ8EYhFtGgE5ZyZuV_xEeby7LzFUVQSeyxJBhriblwCQjO6-3c7F9PL8QpLMczGLy91-XuqyzNduXD8_uxBJxMwk0-Fq2RdiIGLrVilTZnb31kyQgCDAESEAiFCE6zynlM0UISCAJXsoErs1d3c1zFlrwx4Bi37IFkTUUkQEAlg4kFQtpeyqiGi1ERMzIaCrmhoAoSQ374Bed2BJROLawvrPD2krIklNcx67XRgIzByIe1SGAImTmSJyIISQlpaH0V1NTdJg2tW50VvFAI6MrTQSGvKgrUlOYZDHzJmB0_d-3_v-xt_4BRHaDLzb7iPRl1_-5vd99AOHB9MXfvMbS_OLeckp7S52J8fri7PLvvxChrDoAm5gAqA0iNW62qy3FxfuQGEgHAjginhV1SylTdPKQxXCVROSmXPOru3qORWADNxvkwqqVfIQFhF9ltwYCQHBsZbFwCnl-w8eHRyOf_h3_rZPfebXU07bqgYW4F6Nc0KAeSk5ZQyecKXUOjyGCBlZrSEBEmNgZlF3FkaHnJKDh4cIYyAgEpOHMmJE5HGQ1DeVNIxDWapMQ_dWafM-v0ZDEge2iJBIwhQAqs0talNmJmLAmFv55V__rVvXjk6PjsaJrh9uzmpJY3r-2ZvrlH70XS-9487tcZX2dXY3TMREKafNwapvOYecA3DICRDUbF4aIhLibq7m2syXVonwRIZdNSbRcE6k4JJoXwoBuJkACTMjIiMiq5qZceLdbmcWRJB71Q9hHAYCRFeL2JeWEkdHO7MQADO5xyhcalNzpGCiQOzF-wBHwKtYEEEn_RD1Ii72fFAz65RP8wjEt87hQZ3T5ACAc1sSSwBFWI_iABEi9WB-9DURBgAmzmYteg8REQPCeyEZwT1JgogrEjlcWSYCQg0CwMCHJETCTG8-fnT7-jVzYKKmyowYgJSD-a__P35-wAFSHobRo-0vy9HpoStyklrLq6--8dJ73_nqt1-ZcgLXd7z07P5ir21prR0erOYSL7_28M1H-3EzHU0yCT94cv6F3_rOradv0mp4895DN79188itCdC1myfLUr3NED7mBAbnT-bVyL_xre3v-P73XTs9qFUl0xe_9PWP_fAHD67fIhyw1Mt7j7f7C2S82JV3fPRDpJUdm-m16ze-8fVvvPNt72y11LmMY3rzwZOTgxUnWUpr1hxw2gz7bR1EhiEFY90WbY0YSRGq1xaXy5LGxEPCgP12jxDLskCwpLQ-WJV51xSSpP3lI5ENmF9eXAIFqiWRvBqQvba6m5tMpLU5hBUY18w5RYn1mL01iEhJEPtTD-d5ASQkMHXoWQsLyWk6PnRtzLzsLpaL_eH10_4mXUp97qnb1XRp1VoIp_1-N0zjdrdbH2xyyn37BI4pp4vHTwh5tR4igoQ5ZWsueZj3y-HpUbgTRhqHh2-8wYQstD452p_vSbjutwRABO6-OjxJIsM4laVMvfHcos5KSTAcAuq8L_vl8Po1RK5uBFTmwiDDalgu9hBqZYFQIVxfu0GcmvlqGrYXexHK4xhI6hqqrXlZ5iGwte3Fk-0n_sTP_PX_8u_-vp_-gbvXbmHEvqla3Zb52tFxF2YPU5qXDr4TEb7YL8OUUQjCkai555wuL3fu3rRbuAkRmTv2HQJAzba7vffHYt-ecGpLMff-fESm_VyvgNSMARhIrdS-tzPrxwNMOQEQMzIBKDzzzO3muquLqSL4slssQsNJxJpVVSYikVJaM-WUelusqZWlEKNHaClI3GpFZm0tTyMPuartLudhTICh7h6hrj3NuyylR4E7p0VrlZQAaRhHB2i1YU-uAs3zwpnrUnJOViqEh6mrBqB1r1l_PHn0PpG7uWNEJCEIH_IwjKO7j6uVmurc-guOCEiQerrR1BGuXdv84T_0-z_84XcfEHzswx94tMSf_4t_9Te_-kr1KA2QxE2JRbX2h2R3nKjWJBlbm-eSxtVH3vOOX_rUryKN1ipzCsDwwEASCgAPk8SEuLTKkhDNzYJJVTEJEhFRqAvhZhr-yB_4PYEBi01DRrKD0-n_9t_-nbOG__Ef_KOvPnr42uuv1bKoogwpENx7b9W8z4IRRSQQPQwBtDgJW7XV4cZKa7X1yA1SvyHDsDkoWmupjEhEKQ0RzkyuhkhhJuMIAYHu6tyDzoEEcSV4RzILRg5zSamqjuuNm7NkVwemYRiR2QMAYFqt0zCU_a7jIqfVgUNM48SMTdudOzcD49rp4XPPPH398GA9Dcvynbs376YASfKvT34ikzAhkQW0VoaU0jD0ImaHmSTmzrp1iKLqHq25hXfPDSeuquZYmwLQXBSZd_sSgKUZiqjHrlQkMoftvFSL2iyP-exsv5mGpWgzK033pTKzByTpE0w-WQ_MsrO2r6oQ291-czDN1R5f7jab1cXFbhiHWuf9btnO1dyExQHmRS1iWUoAzEVzSu7mEW0ph5uNWj0c5Jlb16fVmDKlBMt-T-78x3_uzyBTX4ICQM8kNPOUGBABMeWUk_SsbUfFpyH1e5upSUrm5uHEFBGl6sBTj5K1GuoKzA6x3-3NPMwDabtbEGOcprpUNyjLkqdxu51Pbhxenu32-yWxqOpqs9Laaq3DMFVtvV5Ya2OhCAg3SUm9QoCpEqJpM1fJqS5LyslqdTXg_s8ZyP3pF8iMAEhidQEMQuruhjCDsB6X7GTC6LRXggDvtw5CJBazBoDI4uEpJWs1eshSVbizDTFxNlUkACItZVpvlv0skkw1el-8tQAKjDAlEUCyWvnqbErWkyHW6YgEPZt1hVQJCABCEgaI_rtwSj_-23_qcPBf--XPXHvu5oN79y6eXPA0TuP62adv3r51-9vf-s5Oa1HLQqfHJ48fn1Wk1hpSAIJXZ0fkoJzNg4V0N9948bknDx6gxyCphbWq5FdyWDclgjAnJnc3a0Rk7gyIEWaaRFxr50EyJjcFAgBwMwsDcnACDG8KAXNRJUZJkYevfuONvFn9O7_9-__JZ77kARfbORG7q2QOiITkRR3csBKRYVyRmMNZKABbLciUh9FN3SwIkLnbzZubDAk6qejKFOPIRJndvaoRggNYU0mstXa3Rdl5oB77xpHNW3TECIq6GYGaZZKlNLWopjHQl797_41HF2-_-3Se8vXDQyM439fHT3b_4mufvwg-vXX0wRefffHu3cu57OaZmMYhE9BqytMoxOJhZWl91C0Da3UjrAYBfUbAHoFMhkY9lgNYmw79ud_zuwi1qWMQobY-VdfObWCgpjaOQyJxN3TYHK4S0ZCSNxvGrOZAV6E-IjA3M2eUZiaJwYyZO7UNsevVrtTVhCFIBOiB7t6_kQhVvSeVA8E9mMmvmlKgqojU3-jd59VVAOFXhq7w6A1dYu57hr52SyK9zwMIBJC6pgCg53_6WjYAPLCo9dn8mFMEZqEHTx7fuX5NzRGAEEnEmooMD87P_l__6NMcPJ2utFaESMLrzbTbzZuDlRB89_V7t25dL_P58WZ1_eT0Qy8-9_j83FTTwEnk0bZ-45WHj_f12vHq5mFar9cJ6dU3z5HA3IjTzWvHkkAkjykfHK62u_29hxc3TjaCEMXmZY4D_tC7bh1M6fK85Gm8rLvXvv368888PeT89OFmv7-s5q9849siqIt-8JMfKbslr7MQUKQH9-89fesWy_Do8cOT46Oze_dunpyi8MV-l1Pa7pZRCJFKrRBQ9uVQhnm_7PdtGmW_VJUEQq1o5qErLBIPknnICZFAGyj3cmRZ9tM4rVfT-XKZWBAip4EgWlnm7bJUhfCytDYXN7Ol1bltd_uy33frKxG7e9kubS5EYNqIomlo-LTJzKk0RQCt5mq788e6tIPjU3M4PTo9e-Mhhh6cHI2rVStlvdoMq6SlpURLKymlZu3g4CjM0ziU2izi8PgIEFuY5LxZrwJhmCZrc8orZBrToLVsz85355d5yoSJIMysbHcs4urDamPhKCwsdd6ncdDSkKPvNkPNyowR0_EpEI9DctNYNMK6Ki8g2m5P6CI8HByOm8OUMhmY1rRKScbE8ujJZe_HuFX2KK3V3f7pW287fnT5wY-9dz2OS7Enu3O1yoynR4foWK1Nw2a3zAebTZIU4YeHG4fYTINwhohSa2ttu12q1mAORA93s3DsGaF-1J1LJUE1jyBmNjPt5JZhQoSltWbugdrUkQPJTUU4wLtinIQ9upnGOJEbvOOD73LV3W5uEUQcTQExLC4uL8ZxaqrhgYyq2lptS4noXIC-sEc3x44MATBtvSk3TqOplVrKfmEC96hV85CW_cL9SyHMzLVBWLh1fBMiEGEpzc0jesVPu45CTd3aFdwIA5k9HImRgCV1TGAgEAGREEGH5QPg6uCQEIbVarfbmToKgylAPx-7WXXz8Pa9H__QH_59v_Mf_qN__Iv_4l_-9A9_5Om7d_7T__y_-_pXv5kmVsVWtXNvtLVuIAlEAOIkVuqQQpeyvbQ__5f_6F_5T_6L49OTWhdm7IVRVwhwAAxzQGDKHs6cEYNInLBLmyE6RdPdvRX9nve952d--4f_q7_9j05P1zeOTsjs-p3r3_num7_2hS_-_774a9_33vd89Ic-8OyH3vH4jftvvv4Ge0zTGNYIYBgSRHhzJAqL8JDECBSEzJzGoewXQCBh0yacSBKE37h7d9Fle34eGkQA4czJzRCBmN2MhAOpx4R7EDoARbKWwiKAKClBwBViPyU3l5QDLA3TenNQdvtxNam5SCZGJHEIqzqtVkBkZoA-rIcPfeQDX_3q15572_Pf_z3vvzg_Oz4-PD1ePXP9qUl60Qz7-8bcAdzMWUQ9miohu_eDFixz6bECRvSAplZKaWoaIVm0eSAQiar1lUwAqEdt1tSbRQtwj3HIVU3Nd_vigTkPxVSyJGZCNAtEOLucASHncbefc5Km9akb1xJzANx_eFlcrVpOSQMfn2-ZpTQjZq2FEPsCLYC32yUPqVQDiH2rnASBWmtLrdNqrNYIwEzf_uIzh-P0zVfuHYzcTPe7GSL4j_-Zn0MA0wCirpkQkSFLq8YEapGFS2sQUUudVmO_EplDRKQs6uba_Q5gAW7gEQDk4IqWOJlbTqlpiFDOQy3L8fEBMD1-cm6B1e38fH-2nSGcmed5nsbBTQFhdzY7QRpSmWfJqS3NIgDA9Cqmo6a9UAgRIhwA2hqzuHufCCJjm2dJ2cxTGsJaeKCkiN7yNm-VmVWBmIjQlnrlQUQgYVdLIu1qE5rBwy36Y6eTiBCw02q91ZzHcJfEtVRkAvCcV7Ut1MfhAF0NaM2YkSIIMJDCGouYKiGI5GbmZkPKYdofcczMRA4E4WCW8hBunBkDEQGYwowY53n5kR__4S9-7gtv3nv0wx9_91e-_B0hPLx-Mq1X3_rGKz_wvR9919uf_5Vf-8LhwdHlbn76qRuvvfmouTJzXQoSugUTuRYkYUKtak0RGBnqUiACkMAtdWMfUrNmEb0z0PMevZIV4L3mD6BCORCt-SDZXd3NIhDZtKEhehCTVUcCdyWUrm3jxJf37t96-sbPfv_Hfv6Xf-UgDU4BFqU2c0hM4e7mgaRVhzQiAhHUZoi4Gk-aFg7yiGEcqqpqIBEgO0RrDYjAo1fYE4trSBYEULNO-KqqU55aU23WCb5LuwBI1dtSVcOdAgHHoAohCIxAicHCAzwIiHlKVtvXvvndmycnRwfjnXHYnW3PtgtCOt_Or90__62XX_n6vYcffu-7Xrr7VFvKw8fnEaEW5s5MpgYACHS5lJFHi27ewQjoPurwKxd7a05E2lSIycnCm3seRvMOBWHEjsU3EqKBAsPCpnFQDw0DgJykqJ4crMOdUy6q_hYaHxlTSohX6xWiMPNBiDO35gg95oOERAjgkZIAIBJbBGC4d5POFWvEvB_fr_q5PS8UgW5OBERgpqYKCH1BhNT9F_6WXP3q5h5X5wUKd0S4kooRuXszD-rfGNqcmIJYmxmCaVuNOQyZ6f7jx7euX1dzRvRwYgx1J_4nn_rVz_7Wtw6G4fT69VqKkOc8rFYjI6lZrXtCSkSX52c3Tk6ODw824-Fi-9XA42qYF3vz4fZsronio---kx12-_LaxfLkvKzWOUhSkuefvjFkOTzcYLMx00yO2l589rqGL60eHafbBwerTOOQNnlYin7m81-b5-Udb3vq5e_ee_DkQbmcv-9HPvErv_jLBBHW3vuxj6IWyYmJTX29Wf_mV7704nNvOz-_JATVhYPyakLG5jo4oQFJRrdLa4HkxQCitcBEOcl6nXIG8hhXyc3VbNrkzdGw7JecUqu1zU_SuFmWOu_PhzxOR1NT9drW00rnmpgSMzhAuEg0bxRR98qI--2SEtUy7y92IMicw5qXRuQAMO8qCUOYqSJgr5NpaQDOBG0uVnfHN0_LUh6fP7p1-_rl493R3VuqyohuOuZhNY3hodZr6tBqXU8rBzePst8dHGyau3l4YEJVs2FILFJ2u4AY1ikaWfMybx---tpwsE4Dg9P24nw1jV3jKGlI4-Bac-blYp8mTpIuLxZkCnOrJby66frolIQ5UaiXuUAAkQAAOYSamZ2fbe-8423hkYRTlldfu3fz9g01mDbDbjfnaXCzy4ePNkcHlDhl_sj3f_DmtWsE6GruMWYkokEksSCLmZ-fX57eOGmt9YPCIGQaiIFEAWBqwzBUNwAutXmn_YQFOFiomZqzJPPuViViAoCmmnKGCPCoaq2phxOzmXv1wDC1QGhmoV3YBNZabcpCtdmt6ze9aUA40LzbQ3QbO6nakIfaGiGaarv6-0EWRvC61O7alcxuDsCtVkaycFPPY65La8uShMMswuddcTMznXJS1QiwVt0d3ZGk9SgvQEpDmZdwhYAIxwBi9mhtXyPAVfvlAYK69ZN6djRlIITOqgJ0bQSIjOAwHR4gQGsNkfKYIhyQ3Kw3CcMagX78kx9_3wff9pf_o7_25d_6xgc_8PY_9Ad-39e_-a3_5r__xxy0OVwXQ23NzMKbuSPhsrRA3JwetqUiVF9qre1n_8Dv-n__nf9PjhAmxLCmEcgsSIiCXg0l-qqWEN0UIsCVOIM1BgwNZPGIYRoI0vH1k3_yT395W9rX33hjM-Q7168ngBff_tIvfe7LD588-PUvfenXP_OVb371lfd96J3_1v_mJy8eXbz-rddknRkTIHkzJE7CEeFueRiQaL-bUx6CWK1yklaVcyJi6O8nSge3ji_uP5K3CIZIFNFf_KDaRHJKyUwJiRkDwQMBTRKHEyaGXtdDJM6GOIwjMUFAGnLOmRN3XHQaEqeEhLrU1Xo1DKta9utppaUmHpq197zvXaQ2ricJu3Xr-OnrJ4KxGjKD95K0u6fMHaIfEc0sZ9FmSXgpM0vybpRUTzkx4lJr06DEZlCbBkBv35kjIlY1QKotipoDFPUIaA5LU40o6q15UUOG3dySSLNwgNYUmNSiS_oSo7pZs5vHBwEQgNt5F4DzXNOYSLg061s7ItTaAPH0YLUv4RFI5KrMpGbNQt2ZmBifPDlfrUdTI8SDo9W77t652M1jpoNJRAQt6rzwn_oL_4GqkbA212ZI0kwhIklCov2uMFMH6rFQeDRVjyDkarpblu7K3u6XKw4IS60tGPohVc3PL7fuMAzJ3cJsXI1lWTygWTy8__j49EgGzoluPHXt3qsPjk4OW6nmcXLnWp1nScKS5n3ZHG1qrRAhibUpCkIAJokIcLfSkOmtIo9mGZoqS3JtwsKcOr0ckcDVIlASIrwV0AcRUW2cM7j29RAyd4NdR6NGTz5eEYT4Cp-ccu-4W22AAQGSkjXlhGYWrkmGAHe7wok4OLMQIIRrKZITAUEEMYVqxFWDBxEjgoAigrBrCdgwwtzNiTqLU4gpwlIeEJwBkPMP_-D3_8I_-AfE8MbDJ-ePz5Bw32wcUxicHhzdODl-7f6jR2fn6pQYG_D5-TmGo0BY62bnbqMKMxA0K_NuGYeplmIQ5obuZE5AwqJqlKTUIiydxC_M4KYWeVy5NUIM8DAFpmbO0qvPEKaSGAgTZCAFEF8UwQG9thYkghSM3_7Wazeeu_uTH3z7P_31L4rCohrFe88vAJG6K-oKXAsAQgQOiF3YQUSkbpTF1K9AtIyJiJCQMHEKC5EUCDklYoYINRORUhoLmnpiCfBQD0xnVgcYiMO4hUmWtGuFApBk4KmVBgSOVMwIBALVrbm__N037m-3zz_39EbkK_ceFvXSAsAJaL_fvXbv3qPLy7e9-NzBjdNvvXkfWvMehGUJ80AYUkqp27VgX4q7BYEwR3CrwdINu4GAYxaLQMBWFQgImcI5JaL-BcGJqLcGHDgiD3k9DQhA7jlJF1Ymwf3-Cnxh7l1w2FSRGBA48eotjTsiI_7PPRiEEBEE7OUtj3DvPTTzPivFPm_DCDDtUJKu5w5EQEAG1PDe08Xockbo1PGukukIn9474B6fQwCisECiZhbw1tL2qhYAiFdtnfCQJIxkGpLozYf9AmBI4erM3MwkDf-n_-a_00qJJWeyFu66GlfEICLTNLzyne9sptVSay3lpefvTnmc295rO9gMY0oPL3bffvXhbru9eWt982itVRXx__uZL5_evNG3Hc_cOt0McnGx20x5lbK5E8qyr9dOD19780me0jRO0zi0XUkyqEfR9rVXvnvz-OSpZ5_6xte_49mhwNve-eLn_9Vn5-0lMQ3DcOP2bQBE9CHnQaZ_-Wu_-uEPfM-825maG7x2783nnn1JQ0MwmCJTXg8p4ygyiAwo8zyna4OwSCJGcQ2wIMTMLAlFkAkatdXR6G4H62MRQZJwJaDT2ye1tgAfk0zrYbXOklIeJQTUNI-jNWUAZsgZh1WiNFyePcnrUUSgi-mYECEPEo6ZyVvYvi6tlWWxhoSsYRDgtezOt9fv3q37ZdnuZM1vfud-Eh5yWvYFhKu6ZElETBTg0zB406q-zGV_sWViGUcLu3zwOg8Zwd0ChBGi7fYR7BzTapMl1VbrZaXM4WBaA3wcRw9jovVmPeTETG7aQkO4m22YCNDbstiyHD99i0Isoi4tXLOIVgVxBt6fnbnXtl3uvv-9Xq01TZJra0cHhwGYpmxm6o4RZ_ceDWuudb8s5ZM_-qMwL-M0hqljSyiHB-uDcdXJdaEwa8ksEYDodS6IkBMC4Xau-7k4YGm6W0qxOi-lNauqCLAeh8yCzKU2t9jX2nP8XY3HktAdHT28qWl3dwAGgIWToEMsS6mlspCpEVIguBkSENLNp25sz3dVq1YtSwk3VVdzRFBrptrmxVQRI-URemQAiVPiRL2RGdCZeF3LSYhIKVnPZ5dq5q1ZuHqYFiWWjgBo2qAZ9_1-eJglEa0VRNyMCVNK4Fpq86bEAuEcSIkBsPuSkVCY-ji2xwo4UWinThMzQy-tJmnN7a3XBAoYuHtLKPN--d4f-yHx9t__zb93cX5299nT__jP_yln_k__s__qtTfPEFILKLWpmquCh6kCdKl0zzoaQ5TdbCYvfc97v_rZz1HKbZ6ROCIinLP0iYpHCKUIIBEIBwhC8KtGWM_REDK15oTJPXa77eMHj3vN7rtv3P_Ae981ICaRgxsn3_jmG2zZI5Z9-dJnv_Yrn_7SjWtH7_r-l17-jW8jcBoTI3kfsJqHBUo2c848TlNzA9A-p5c8RBhRitB5t7_14ouPXnudCAk5ADw8pfGKS8TYmmYZW6sQ0a8NEe4e3HUMgIF4JWAWcsBhnMyMgJAIENOQeRiWfRkOpjrXYZpas3Faa6tmToLjamJiVVXzeb9_cPbkHc88jQE3DlcHIxOCN0PAnu5g6rAIUFPvSTJElrQslRnVTYTVYsyDRTQPg3AHNQfC3ntD4isCJKEHlabFzT3MnETUtLn3wAcELq2t1wf7pTmCtpiXAkhLaTyOu90eEUWSq45DPlitCXAB313uPXBpfuPaejvrblcu9vNqPS6lEvGY867UpTRJqVT1wKpqER7o3dONsZ_nzeZgu90KUk7y3M0b5xe7zeGq1Lbb7cYx3Tw-pFIsgLSjrBIDRjhoC0BQ82k1NPX9XEiYUYhZUoIgwDCNaRizJCJaDWMAuvmyLELkitGgqddWx2lspuHhQUvVs7MdSd5spnWS5154qtVatzrKuDze3bhxCuZ5kHHKZ28-4ZzCgwg3R-t5u885dRxVGnMnA7p6R8rkIXmznBIRWoumKom7cdoj3BpguHu4AhGGWZkhLDDMHdzcGhOHNrpaJAVBr6xwV2K4e6ute1JMW9_5UARioPswDhDuWrupGzF1pk8te0ZGJK3KhITcSkES6j_1HoQAiGaOwhERFkS9EOMBwGkwd3drzdxNzQLCXBFMVd1U1VqpGMFMDlHL8vjho7vvfvb8wTYPDIhRTFs0iH_6Lz7d3H_v7_qRdZ7u3rm5v7TN6mTMEyK4OkZE24dVA6-19IeJ5MFbQyYAc3CC4P732VvIhOamGMXs6gcjLCjCrba5pyndQ61PdMNU3SNcu4DGtRFjW1RVu_owArxUb-3i7PLR2f47D578ws__sweN_uy_9TtD8Hg90SiBEYyLBkpuFoSs1dwdiZElJwkIUzPvKuzCKMOQRUSbJhBtQYhuVpYZE3qoCEWEVvUIb95KJYAyLwerrK4RQJIiYMNitNRWobGD1VYgYmmupkoNiaKLUpwwfEwJgYuaYnzrO29sL3d5NT5769rBwYQcpq5hwzB4wPnl8i9__ctnDy9_9CMfePc7nrMIJLDQrnoJggiL5uOQD6dVIC7Na-1zbqyl1mXrbgDeSnFzBHO3ViqCA_brVwQ4kY2CT906eunm6el6OhrHo5zabjZzpOjuv3nfEgsl6WN7hHCPZS7atFv8Sm0s2DN4BAAeffYfgQEEgWrhBlUtAlpzswhAc1c1M4UAVetsT-8UV9XWTFUNYDGr3ewS1Blc_fu7P5iIw117nP9KE9AlNSQi0F-kHUPkbh195u59LXhlAYsIR0a_UhLDVcOAGSmYMkTcf-MSQxaPBlDULEJE0KEuLWe5__BxWcp-3p0cnFDQahxefeW1KctmlDcfnr1xf1ccIez73n03IRVIX3r1McGUhwTuN6f1yZigKntshlR22_WQ9tuz001OydcT3tyMJ4fraT3cun19tcrMPAzD_vH5jc0wyEAII22uXT8u-7Pbzzy3GlaI_trL32QRgSpEo_B6oNU4qc7Hp6eY4vDktEYFmwlYPWawcT2RcLBcVJWgxDYwHK6m1cBD4nGS1Yo3m-HGtc3F4zMxZ4KbN44kSBDX4xCtHE1psxLRFvOl7_eObdf2SAAQSADsA8VG8pjSesPrw7Q6GiJoTGsCkiFdv32aoh2MeRiFM-a1uFAep_XRioEyZaaRHBILS8iAXWOdh8GXxZYa7ha2PduvDjYPXnlNdSdCpRRTIwdkDIjN5nBbqqwyEojwsEpqCkDTtJ5OT-fLyjLsyuIIlNL66ESSUHMmP7p5enL9Fq8Hb6GthYVWCJJw2z68Z1rDlYimgzUFoydiZhFH3Ny4xWloWh999_WmS48L5JTbfiYErIEBDIiBEo2joZurMQs4lv2CRFGCAgS4LrY63pRtIYO2lIt0WRGrGZhLn_loSDARL81B4Ox8x8LbfT27nI34fNsePJ4fPto9Pr988PjiycXlXNtqM877goAUOKS8zMv5xe5yrvvSPLAPo2tpPVez1FaXohrhvjSdl65A9lqbmbuaFvXmXQjelmZqtTbXIGFmcWtvvvkIEpeq7oEQ27LtRDmIvrp2EiaEsNBaIrzNs1rT1kKvrvoQ0WfC4dANUGYWbtFzPAFlvyD2jbSjB5jiW50iSVznRkBEhMRuEaZMFNrcNJBqK2GOFEtZgsiaXSkIA8LD0SWzJB7GiQhbraqaJLsHsoyrtanuLndMkBjbPBNiXUo045Sd4AM_-KHDfPgP_u7_BLM9dXr6geefef4dz376c195-bXHgUMwW7VlXoCwE3VJpLOJIzTMwNRqBUk_9Lt-7Of_278dzE7mxO7W_Qbo0Md_HtH_DwPMmkKAmTMhEKhpa9qxyT2HTAS73XI-l8Xqmw8vHu-2n_rcrzVHNP3hD733xTs33_au5-888-zb3_2eZ154ZjXmb33ttc_9i29-_Ec_0Vo8-7YXl1I3q1UW5IRInnJmwZxHJF72M3M2YEkZw5FFrSGRG4C5VYt_Hcolarp0tD4EkpB7TSlFQBAhIndnS_CQN4iScuKrVhgQS1PNwwCIwzBAxH478zjKIOERhAAgOXmYoY9T9ohlKeN6ZKH1mC28bOfDGwfM8Nqb9yKAgvKYRRgccqIwt9bfC9C0JeFAarXmUYAwLBwIkwBGIDpAEOznRd27aWJpup0XVV2aquHcaoNAZCAmln2pc7PmoADqWNSLxflSDXHWeHhx8fhif-_x2b5qM0s5e1yBNw4PDxAwEjx5dBbMzLyahnnvl5czYBysp2nIB2O-dm1zuJLt-ZKQy1I98GKei8dSFAK8NVVDRAsxcE7JIbZP9m88fHKwYmu63S2HB6vValhNmf_tP_2n3V0N3OPKxBwACMu-cJJaW8ppaY2RHEDNkHC7XWpTFlmattaAxMAjAj1ad8gxuYeqBcI05o7qdzWPyDlZwMV2e7DeNNVhmAi9mykl56W21eFGq-UxpSRqNuS07JfwGKfh8mwHjBDgauDhpoAU2rqCLcwhIKLXDhmvEoUO7iyp1UYsRBTeiMQtUh7CGoTT1Qc0MBwRXA0BmMVMI_rw0t7KK4Zbt5Ne0c3VgoXDGsBVUdLDrRUhiojEU2377ne-yjFDpJzLvLvSKBEBYq0LC3u4SApvAOgROY2qS4SnIQMgdQaqOwCkPF3hR4nAzcyefv75O7dvfP43vvC-j33g5c99Pa9GRiEOd1v2Cw359NrJrRunn_5XX3h49tg43X_8AMIddb_bc-I-5tGqzKhqzOhE88U5pxzoEGFLySm7anMIQGI2UwQEAwgTEXBQq0TExKZVUupLDECgCCJ2Dwfw5swc5gHKkpal0Mhhju7eHEKbW60KYQ3w_puPn3n-xQ--8MyvfvXlgXHZ15xT3VcE5f5mIyQhNVMDEiQWoB5JB9cA6Gj4zmICIgD0viQAAmJCiiSsbhAhDEwoxI1AYIOofTA18hqsEWAEVLfMg4UR0TCkqsqBMmazDsmgPFzhmWvzWhpAvPyt-x98-wu60998-ZUW3WeKGASAzR0IL_fb1954cuP4-J0v3q0Wl7tZAsA8C2eWachC6ITDkFP_hINnocRJhHOiq2KIe7hLZiEUZHPNnEhoEIokH3zh6cOUDoaRhZ1BiDS8A4jCYxqGam4WS-1_QEeAxOwWCBgQSJTQjibuyFfAK4BGADBzD9QChl79jfeRYag7AgL1_Bu6R5-7QDcJ9NaNd4wPhwMghPceelj_GuqoozDrDfj-BT04it67xeAeoebYlwDRxfIQ0WvtV96PK28B04PHj-_cuKFmhG_dBoLuPTz_hX_26yTSrK2vHZpGynJ8fIqt5mkFJOdn5yxytr34wLvfmUdB1MRw49qhQvvuw7Pdvr7y6v0f_cQ7DhAR0t1nj_75p791dJA544HAU9eOplHmpazGvB4SqJXaXr93_v53vbTb77f3Ll-4e5OJTk6OrZacmDnZij735a-9_6WX1tdOv_GNb9998an92cVqM92589SXPvM5pJjn5Qd_9scfv_b6weFhEkKBcZJXXn3z6VtPzWYRXNrFmofVamNaq8dqzAOTOGCtiEDutdo4Za8GbgfDKAFW6_HxlAHMlZCnzENOAycBGFJCApZ8sb1sl9vD42uSxNzWwzBKJkqJaDUkIheMDDStV7qrqzyCV5AY1yM7znVZD2thCiZvuh6H0DpJGhJNmzxMiYBY2CGEaBrZA3ZPzgPtxlNPUwQlcA-vtl7lB2-eNWs5S1saETBy9TArWTIQT0PKWc4ePm51OTg5WfZ1PSbiQI952a-maRiyu-aULTq6OiJ4Lvu0maw0CHVtoQYIaVrV3TxuDpkoDUOacimNhLyZAy2lSk7l8rLt6uapmxDs4YEKWoUZI5KQteLWCG26dmtIgySx8HFIy9I2m00tpbXGSUiwXuzavN9sVvP-EvDozs1ThhiEIMLDATEgEkGxSIKv33t8eHJwORdgbM1Kaaq6aHNAFGy17raFmOa5lFKn1Wq_nwNArV0dIwFLKQA0lwWwCyVBVatVIK5Vzaxqg4DFlIRVFQNrq9rU3ABCe9GNKNTDvXdY85CJaLvdEzKwYCACzmUxiIgwa96MgQCCmYJIzYgxS9LWhiSq1mo1s9YUeiFXHYldq6lprSyAGFYbhPcMYoSHh5lqq4DhEN6Me0zUo1f1GLDUGggOikCScrglwqbORMMwqOqQR2RytzRkYmpVx2FgAclDVxtqq33iq4aBrq2lMSOgezz3jmffdvvoF__e3zs4HM-2F-95z9v_k__wz6nH__Gv_z8fPtkxISHWeQmwMCMAcAPHFgY9b-3KRNYap9VuWbjtPASvzCsgKYU7c5c0CwECo0N0OjkhAGCS1LRdlayI4V9POgKJoNSmFs3UQ1uz5599cSLMQ_6e97zjU7_8-ZOj1dHBiZXitWlVa7Gdlxfe8fRnP__1mwfT4bVNJvzg-9_-eHex2-4SMYm01g4PNhphrdusIiLaoikn1-aB3iogSBrCzSzcvWvY3czd0XFcbVqr4C45mXrfXQSFu5MwCrEIAHJKgRiAnASJiTANYyuViFNODIQQ3ednauuDAzOdVpuUGJnmpUqiiSHJoPv96cnhjZM1Q2QRRO4m1i56AkSSTiqJUOv7vXEcPMAtkDCxBECp1QCKeTgERAfTE2GSpO7ANF8Z7rGYl2ZVralrBJOQyH6pLKl5tGbzXDTcEdX8Yl96DAHCPXyQfONo1VovWMv9Bxd3n75xcbm0puqwOlyfHG62Z5cHB-um8fhiZ-QaUQ0s3AnarK0pBGZOpRonyCKtFlWdhiSkz9w8XY_Dw7OLZS5jTpeXu9vXTvh_-2f-fTXvQfCmxshFvScC3Y2vAORVUrKIWlXNOacIbGZuztLtj-AWKAwAl7uZhcyCEIJwtytJqG_lmzoTWtjhMHU4X3NvHrv9HEyc2TxqqdPB5O5udnB4sLuctWNDmw7rsZZKRFqqQ3gn_BNp0WDqGiDA3phlrY2Fr2YL7h1TaFoRKSzyuNKrmwOYKjEDidXWnUGq1pm4HkGEnS_ZS0vE_dxhYc4iV_ohU6QoZWHJGH3NoBHe80Le1w9h6BbIEQ4UGK7aWAYPF5HQBgAp5WYa2K8dBgTamsgUYf2sT9jVGIhIwWjhIqQQz73tbZvV8LUvf33M-ezRRU99tFYBEEmGafXoydmH3_vB26frX__iVxxgu10YkaZUanEz4ezVCSMBAkAQeqsk1PZLHoZainAncnWgIpEHIYNalkQB8j-jWTyzEHErdRgns0bhRBwI6pZEmhoBQP8R6myKnSMHM3eNthXlxG1xI53Lcv-Ne-961_Pf__53fuY3v5JZ0maoS-193xBuGj0jFWYs3INa4BDuSAQQlFIPjyIisUQYc-o1L4BAR2dUBwRgSm6h3o-cs7daqgNQWA03DzIMQAh1Zu4rSUKQJMllv1RgCMdhTBAhzKaahYhSmedPfM-LK4yX33gIguCAhOEeTKVqQLfkxpPzi8eXu_e8-Mw7n38mB1wuM3gE4pCGaZiaeas1DxMgWUQzlSyAkJIMeegZeuQgZmKSxIu2nOnW9c3Tx9OdzXpMsl9aI19KK9oMWUjginuHxNStwLW1MGOR9Tq3Zh7q4BwIhOvVkAR7lDACPRyIOn43HDzA3ZDJHOzqkA6A0OcF0eXBV2rIfgPqXKC3Jn8e4fHWjxt0k2L_s3X5IhEjACKZmXkgUxC49Xz1VdkAI-BKFgYRiEDhQUQWQIAGkTh5wKPHT27duN5a61mycEWWf_Tpz37pa9-VIStgZrRmKdHxjet1N0-bzeNHD7cX58yg5m978YXL_ZYSHq03JPjaK_fPL8quLEcH48ff_cz2sjSnf_Zb33l4_-y5l556_ODi2Zsn0zBOY3793oOXXnzq_Ozs-OhICb_2yuvvev72drsfEU9PN1kkXFGbmIX5o0cX3_zWvXe988XZ_XzZ3bp5o9luKX6ar33ml3_FoVCz7_-p377f7fKUBGm1Go6Pj37pV7_44Q99z_byYj_XzWb1m1_66sc-9IH95W5Y0ZAnQmLAanU2WK-mNx6c375z6mqSfTOuiWA7t81qhQ5AkIeciPIgw8RmrVYdpmGvrVgzK0eb49WYdGkUsBnzwTS4BgcyoC5NhIeR6y7E2V3X05AZE_H5_cfHhwcAForDJG0uk4wpUWIWJhxovcrbywUJ85D3u4VYgGHebhPk8WDUpQ3rgROtV-s0ZXePaOFQFhOhWzcPtNaIEJbuTFyWZVn268PjlKTud5BomCgQvKk3HYZERK0WB-AkhLjsWkRQprLftf2chpFE2lIw82qzDovVZhUe_YWSV-seIte6gCtYywdrsJwSWmmEJInaYh215NrC63xZrj_3bGsWiN58WA3LskhO43rYXe6Zs7da9-egFgL3v_vmJ370o-IxcQIIDUMkIADHZqGqr997kCQ1a_NSrMVSylLNMeZStFnR2ppp09paLdU9atN6BdiFZZk55dYaArjZvF8kJ28NiLRZ016aiP2-BcSyVIvAIDefl9azdsQUVy5V0KLuPo3Ddjef3rhZW21VMVCrCrO5G3gtigTRvJXWHxvA2LQxJzAY09AlQkBkagQQ4Zyk1CZZTBsgle0WGbR51za5hYKrm5tjuKm5tXBwV8m53yIcABGFOcxrrYzASNM0YkRp2oHELEIEwLhaTyISPZjeOrLGRVhS5iym1mplYQhwcIzw6GBMunbn9JXf-NbD7772_u_90De_8rVm9pf-0l-c8vDX_ou_-a3XXp93rR8VylwIQhJpsw7HC1eRhBjaLAki4tHx8Xz2pMwLOrh5n0gGQqtq6D0Y1ZsLTZVTCnd3RySRHGF4tUIhBHIHCOIkoQ4ebm5Ls4Dq8MbDs49-4N0p8Phg-J53vLhajx__8Aea-YsvPPvH_uTv_8RH3_eH_lc_8eM_9OEf_NB7f8_v-tHf8ckf_t6PffxD7_3Az_7YT77w9hc_8_nPkSSgZC4olMbh4nwrLF0cwEmsKrLUeccpmWpOOVSZyZpnGRwiTIkECAkBiLGPUhEBQBIzMxAxiQeyiIh4UxnHgHD1CCBhEWjVTXVzfIQeLLw6WKNw0yp5QMRhGjF8lYchyztefOZye_ns7RuG9W1P30TvGGrQZgGeUzL3pTQidIfVOPSjWimtN9-qmZkBMIbPtTa1ALcIId4vlYiAuedaS7XazAHUY78U624B4tKaJKmqLUADzi72l9td81hqq82ABAgk87xf-g0kkwwi9x--zuMkJPNiR0er1sIhHJyQNqtx3i-rzSBML3_z3mo17KsH03Ze9vOyn5fe60EIDXUzBG5hWhqg7y_Li89cX5a67Ovp4WapZcw8slBprg4O6IyBtJiqWm1eqs01drUFAEuaF12WquZNfSmtmQexA83V3MEc1PFyt7RmkqRUW0qtYRiYU1YNa9Y8OHEtusxaVJlxNY6rlHaXuySpzPOQ8-FmLUADMllMeWilpZzvPHVzGiYiGdYrBGylpDEjwjiNEU4YlKlDXRzAA1gYIoaUEPr1vREzE1mpeRzDLcC1zUSIIFYbIYYbRLBkB2xNKbG5AQNRX0oaIYWbtoaUACk8umeA0Lucy82JEUyhacIJgcFjWbYWekVfNo0IEdZWCdnNsN8_AgiYECGgtiXlITwoQJsy5zTkuuwZqSPbLMw8OvALIiKCRar69Vs37j15sN6s82oEN28WGESiwQ5YTb_9ndceP3709M1boA3NkoiZk-GAWRDLvHe1DEAY3NNN4VEU0EiEiYmptWbmfSrbTMEVI8KbhzdTodxRv6UWhCDmuiwEoKqhTWthonBDNERnZlcNDYrA5OioHoRM1ciNdK51t7_cL0u5d3b29__Jp7YBf_FP_dHVyYDzfr0SCUjBYjgQ5UGgaUoEtREYiyNCLRXRgchUgcktUko5UwB5qDAkzEQYiNMwEoKHYkIXCgIttdYCyO6u3hwBhVsEMgyShJKgJEnhxsThvrhiQkAcMptGrYGCxECMgBiJOOzg8GC1zpLyNE0RXrRaU2bqk2pVuyxlu9RPffYLn_2tbxycnrztHS8MRxlcGVot88m42uQpEYwDH6_G9Ti6VUZw9YO8IgttWqvfuHl0ev3wzrXDDzx_5-Mv3Lm9WWXJzfViXijhOifi2M91u9s3U0IcUhZhrU2rbucFkZEEEffb6uFd22Rh0ZFbBkLs5p0DikCAFABBYeEO0Jq1pm89CswszMI9WuuLNHSECNKrPk2oe_RaCKBBNNNm3tybWhAGQE88A6BDOGJpquZm3sxrs6rNzUyj_9QbYL9-IPVLSpcPIwERU3gAYFPrFAFi7JcKQCZOf_9T_5IkhZiQUzgjbjYHbV4kp9Bm4OhQbcnjcLBKc5k3w5QGPj-7vNxuzfTsyeWP_7aPvPrdh6eHh6v1-OjNy2kzqcB6lGtHB8NAiHB0tFqP6eTocC7lwaMHhxtBbw_feHjnmdMsKSOvSBJeZZzO52UcNs_cOr58snv-9tP1yeXp4fXtxX7MwkzhhFl-87NfoIgs4gjCPKZ1tbh2nDerKcCuHV_b7y7HpEnkeBgJ4DDTCuKI8gHxJHhykK6t0lqSKAngjesHJydTXvH6OI8jH2wygy-X-5Pj9XpIt24erhIM4CfX147S6nJzvVqnJEQ3D6cp0eE6bQ5ktebTa9O44mktB8d5tZFhpFJrDjo6WR-fHgDYycH68GichnSwHiDawLxsq1mUuWn46dE6MxDowcGAA61unKwONpHi5u3jg4MJwjHIm06URxkGSTkza4Tq_e8-WA1Zi8_7pTYtzdenx4a8u7wAgLQ5njUcZcwDeCxL8QjOPK4nTkQUFnVzukEiDBzWG5ZkdSZgRPL9fHnvzYsH984eP8lDXm8O1-vNtJpSymOeOE8eRImffPcVGYOIc57cw8xkQPcIYIhw9fnsETARswfMS6nNZEgBtmznnJO2xpwYxYGGaZq3y-p0ZWok3EMFu219497F2W4_l2W3X0bJjOxqZakOHoDDeujNCgf35jlLR3Eh4jIXtRrgqmremNBKs9ba0rxF9yeaham5RWvGSP9_pv402LYtTcvDvmY0c8611u5Od8_tb-bNPrOyGqiiqqAQKrBDtDK2LMJCEOAgAtlYtiwhIWQbCIUVNCKw9UN2CUwoJFnuZAvRCiSqIAtcHaWisjKryczKvDdvf885u1trzTnHGF_jH2PfCv86v063915zjvF97_s85IQItVZ31drMZa0rBzJ0QBRz7MOn0pwh5GEtNW2ygzJzGiISxCECATNNaYghBPBAlIbYz1hNpL8SKVJpa8rsbqYCaqbCFEQ05L7rh7IswB3JVsXEVFwamtVaPqIiSHecAYCKuKqbW6vgJq00qcxsajFGcxcVDuyAHIgDq-k4bsTdkQiRgFUNARScQwB0EwOztM2iYmDM1DU41szE1pvbGOH7f_hz8ZTG84sf_L7v_nWf_9h_8Tf-1hsffLiqxhi0CSMyKKJZVXUv0qUH3EP8iVBrk7lMpydXlzdITIxuvh4PzESIQM5IDlC0UhyQyMCbSEfAqfZUMCJgAEQCjgEAYuSOhQVXbOKtXn94-c6bH7z7wQc__dVfPi719rqdnJ88f_8C2vxbfv0XfvMPfHdQe_ml525vDm-98-zyMG-2w1_8kf_oT_75P_tv_oU__fv-nT_5hS9-9tUXHpuTh-DE9x49RqOT042CERMQigqQ1eUYQgTREFITQSQ04BAcIISYcnYzN1MzCmSIIcXIAYEjD4wxcnQ1dEJAV08hgEoIFFOIOaQcRD3klPKgWomhlqom5xenKWc0H6e82w7TZpNivLh_b3txMo0bIwhMJggGzAEBmIiRa2mIGCITcSeAhcDMvN1MHCI4BA7MpC6qkEJgYlNPMSJzijFERgNzKKp9iQFOQJxSAmLEsNaKAMfjogYGWM1V1RCrwn5ej0UO68pE86EcDkuV1qpcXGzd8fz8udZsPqzjNhyW2nWOh8PRTD98djtuN03hZj9DCKXq1c2hrNWauwISO8BS1gY2bcchD0hAiOMmlVq-8PlX3B1cz84mBwO0i3u77Tbz_-Rf-WNmXmtzJHWvRXs5RQGIuDYTc2naCzgx5F4SullWc3S3KhaIFKE1ETMkLlXWtTqSGYqbqYmIOtYmaqCdvW9OyMtSOQYnVFDmoM2macxDnsbhcFhOzybiICpjjlWdU7p9ds3Mw2bcX90M0yBVxmHS1ly1F6T7ZNdEkanLqwGBieu6UsBOngJzcFfvqlHsVSE355SbNA6sotgbdu7kToRI3DPJXU2KCITQXTkcBjPjgGjeug6QWUzcBTmYCHEwEU4DaHM1DgOCAbibE3OPNAOAmyIRUqAQe8iJObgpdHUuopkg35HTevMB0BEgxrA_rj_4m3_jh--_d-_i3jtvvyOliqiLOUGcRnA-efHl-eb68umTL37hU1eHq7fff-YclmUNQJGDgfQEGKiJSFNB8I7pDSFJEw4kTQ08hVRrdaJaGwUCMDXlGKvUfoVtpSRic1CXmLKrAJgh9aS-gaWQ6lrAOl8vuQmQO4RIwVwis4OrCFHkOM6HNW7y9e31299-_-zi9H_0237o8oP3_9C_9Nvvbc6e_8TL3_zVb3IiN3MiQqLAKeZ1rs6QYjT3OERtxoQpRSZMgUJXyyGkmPpaJg-jaV_UYIrBVImoFnWDPA796BtzCqFf-ToJDQP3djaaQ0hRRGJgVTE1ETdTcidkd0fAe2f5-fsXP_9LbwiTKChAWSoC9ufjbhprEcc-oiXz9v6Tq3nVX_fZVx7dOzvcHps7sIlrU4iRW23k3kTdZBrSbpu3mV5--dFmzJsY7m-nkRgQV7eqvl9LFXVgM9gwVsP-_mYwUEghmIOKqXlV_WjGZGCWmbabrNIForAb8hDZujYSCPr52tAd1B0ITa2n69XcvNcHQcUNuu0X_aMNQP_V1YC5OyDVXbwRRbsT8EFHfCKCqvzaJ_Guh4_oan152NkvDohA5m6m3fEOjuBu2JVkfetAhNRUr25unnv4oLUGCKBOIRep__F_-Q8zppCCO0eG28v5pY-9KHMZOcec33nrXUYQok9_6hMjQSI6P9mq1m-__V4zrNo-8dqDR1s-zcP1Qd748NnV9fLg5QetyQuPLgbCnNOhrCebAU3JcNrufukb33zu4vRss4HanChRAC2BfBwSUrid64f7GRp_7vVHP_dLb77-8iOp7WQ7vfHGW2e76Ze_8tUmYug3N1ef_twnIuGQU8JwMm6--d47n_zEy7X6fHPYTcP18jRRTnlacamGG6LTnBNicx-Yquij0y2LuVtK8WTIJjqNwy4GABhiYOLtLp1vYgh0fXXzcLcBkDrr7Ty7tHsnJ9MYbtZjHgITjkNqteVA3izEwAaomHMUt0p4MiQtpUkF4hRTiMGkPnhwxgg5h802MmhMHJB0rZuTITAHBGvW5rktdT0cHr3yuOxnZBxTsqrD2UQBGGDKCXv9HGl_O2_Pt_2Z30qBFNfDkcynk425MhsB787OaqnaXN3rWsft5q5JScxMzKyiJs2kuUhrHnIA9HWV3YOLWiUNIyHmOD19cl1apRRjHqxWV3NtxAMzEeNyexyG0RGlNASzVkCrq-4eXoQwMZq7kxuhYohtWdM09Jw8qJgYTQNI_d7f9r3ydDnZTapQpR5vVow4xAQIbnR5c5WHgTlwZHQYQmS2MSMgttq0i7XUllJUHBy0qpsisimYQqftOZGaqmqIXJr0UaWo9Xt7VTFxMyekpRR3NGkcOITYRAlRpLkqABJmYEWDk4tzN1FVcwNkc1UVqU2kmgo49AY_RQLCJhJjdAFAYI4qrTVB9JRzZ4bFlFwEgVor4BZCUBETAxVGIiQ1IyQiVBF08o-4BHAXoDFvAoHubPGIzFGqEKOohJCktDymabMhJqRQ1mNKWWoNMXT-PQcGR0B3U1CIKVEIqtYV5A5WluPt7f7Dd975F_93f_Arf_Nnnn_h4Z_5N_9nb7_x1l_9z__m9VIOS2n9q6li0pgIAY0MUUGVezmi9auLatPzF5-7eueDkIMUBSYKwdQQWVoLITKzqIA7p0FVQP1uHAPWf_4B3NUdGAiJkGMsayNKgP1ii4jgxMDxUOSHf_C7pxhyTG-99_bf-dEf_-mf--rf-8c_-ku_8t4_-adf_cqb3_rSP_jZv_03fvxLP_kz337jCcXQVhy0_Ld_-0f_xP_2X_9b__WXxu02j5Mj1LWgqyMSYKsthMCBrGnMSZoiYUiplkpMYtrZRIAQArtDr1MCMfS-dyAFV_MwJGeKMTm4u8eczYACaxfKIhNzHsftyWRigTiPCQxE6rib8pBjjIebm4uzk-122o7hbNzcP9-8-Pj-S8892IbICHcwOnAAb6ZdaXUXK_Uurrc-uW9qayn9zaEGgUn6yoW4uacUATAwi_pcCnJPFsFaGwXqwUJAGIehqStAqXY4zs2siZU7UqV2r27KeS3F3RCIiYfESDCN4-3-yBScsYpc3h4B4epmGXe5NoiR3vvwhglvj4uirYscjou5BY6I0ETGnMmBMYqIisRIpvrS_bNyLNOQehKXCbebgfsLWMHEQVRLkWbuhFVtbbrWaq7rWkS8qnFOx7KU0vroVEWL3Ek05rmKw36uRUzMKUdFN3QVPx7LcWnX-8WQarOlNlNYlybmISczDxymccopnW4mlXZ6Mm22w8NHF9M4jcOQYi7NO_g-5WSOaj5sJgJqTVUrMndueFedgAISOhiQd1KYuTETODZpHAekSPGunuTuIcQeSpbWqAcTAwEiIAXuiRiQJj1JjEStipgjBmJ0sCbLR14kCDF1Wq9KMwSHDkoXcDdZwZ3QVRfoLy2HDk1hTnb346BSi0kzM1FtUrq02E0APIaAbnAnsIjMzMQxMJBPOc3H-erZh2T69K0P1MTBtSfGkS3y-99-S4C_9itvXN_Mv_n7v19q254McUghcmScQgJxUOEUrJtmCbVHusHAlIkQHQDWumAk8RYSNinNVAEqmLo1rYoQI3fZUxMVaRSiqKlJYEIVb2KuKUYTAVOtCwFJMfVq0Ji4mqADNJNa1vm4lvrBu0-Oc3n_6vbv_NhP_dzX3_4Xfs_v_cpXvv0d3_l6Jv7id3_n5mTDIeUpGyARC0AY0hiSqZm5ViXwDoyttS2tMXuOwUSLV3Wrra6tAqOollKKtJijNg0xAJJIczUA0mYBCQy0mYnNy7KWKmomtpYmrcVA3WkPbiHSWhdDbmrEfH6WL2_2IYSPvXgeRK22GDim2P9ZKnp1OMQxKoBUXUorqzngvBz_3o9_9d0P9g-ef_R9X_zk_dOzccwn26y19BCWioQUYgrHw1IEW4GTaWpNDsflUNeiYk6uim63h3VZ1nlZjm6dzjakoOrutpbatzr99QEAoq3zGcxhXoWIAHwchhhJ1dDvqrVwp95z7xDHJqIq4lVUzZpYa9rU1E3N7lCMCI6gaqKmBs3dDFS9NCm1moUqqgbN_O6l6dDUgNgcxFzNAVEdRJq6qUMVawqO2GVDve_r6iraTPVOa-fuXpv0q01T456aY0JHJHTwr37zbURWQHOPgUKIeRyYaC1VIyi0q6eXCnY9t-24vdrvL3ZnInLYH955co0EZ9vh-YszNs_TGAP-ytfeMfK04XK0lx48yCFOKW1ifuXF5--dnqWUzJsF-thLLwHzxz7zamt2cpq20zDkgZGIaW5iQLuTzer24dPrMQ2ReKTw2quPzcvF82dGw7quy-Xtx774stTG6IEI0b77Mx_7mS9_dcjD3KpLeenR45__5jc32yFr2uaQpyTkeZPPthsgK76GHKfTHNCdxTI2kMw5ccpjijkI1HGM87yQ04P750Vk3I7juCmHOu_nAFjWht7r93gyRUIIkUKG87MJA5yeZnCPjCIlBNhN-bn7D57dPp1OBiYM0Z-8-_T-o52hTpnzFFOinDEEAGnuMuSUA21jZMDW6mAwbadlWZpUoXo4HkNkZpAmaQrjRcrbeHZvc_X-lVpzs8RJ52bqrbb59gjEkYZ1P7usw9kUp8BMjmYmKUcXAwdmyjkOKaY0gIHpyi6RGCnEcZiPRwbfX159-P4HtR0f3L_Y7CZHB7Rxd6KKTdrh8ink6A7DdqxrIQ55l4hJnfvM-IM33naH1bSUZohONE455qQqlHk4ndxRAQ43R0f42i98w6EHUMlVKs4fXO7dqFUta0MjSuwIPUClKnWRy8vl6tnt4bCWKkXEySNFURNRAxf11lqr9Xg43t7ui-iylqWW_bqWplWtiRfVZjrXdVlrlzc4ooEykUpzB23qjqaqJmIGRA7Q2ixV6rweb5a1SAwJAAI5AbQiyHd7PgNrrXYxOILnmNCAe83I1dSGnN3R3YmcCVykVFnWmUOQZqJqbq59q4JmCm5m0lpBAgUFBmRvbW1NDLsqh9zdxLU1BKplNRNwHHIy1PF0E1L0QOYmrahYq027FgAhcBDTUhZVdUSKBK5oFhgTYgQciR4_d55RHz7_4Bv_zVcuLu79qT_-r16X9qf-wn-4l1ZWSTmkCDEimIA5GKqZiYH1BCoSAJKrSLctPX3vg2Ez3pESxEy9H2wQSVrzTlM2NRG84xEaMTJiB-2bOwTshXgHV1VgLLp2H7yqIcaiejOvl89uP7y9iYEI_RMvvvz06sAhhnB-vb_95V954_rycHV1y6M_uby5rdWIGiDF6fZw-e13376YhogMhsT8-IWHtaibikgeIgUkIlM39RADIaF7GgZ1DzECOMcoVTgE5kCIIUUi5BSA2Mw5BCAwwDvmErMjKxGnbEAh5hhzR_yhmkhDcNPei4BhGKy2lx8_JvAhZmvtB3_DZ-W27gJNKUmViQOCI4D3S2OISJSHDOAiTWtzhNoaBQ4xoAMDEWAMSdSa6lxXZMophhBMLTAhojSromoaQypVimozk6ZraSLKRMxxrXKYy5PLm5vDAYnVzQDHPK5FatNm3gCrqrgbsjjcHNdGrNYchJhVdZ7L5fWhgUMMYnZ1dfjg6eXb7z69ndfTswkoElBtou6A2FobQyDEujZwFG0gVg5zW9uje-f3H-5SCMOQetv-wb3TFBgRqKzSxBywihdRMZgXMYEmVsWbOiKLmTkdjsu8tmb97esxprmaO8zF1X1ZGyI11bWKCDRFBy4iBgBMKce-TDCgCgY5FBHvzXYxFyOEGDintJsmE79__yLmNO62ZxfnpjaNOWVGJlMjIEJSldOTTStCBBQxpQGMQuAUmRC1SuSISAgEgCFGBKcQpK7IBMj9aE7c_zAGhNB75Rx6IojBTZr37iIoIqho_3Sh3YkIvHtoHcysXxW1CWF0dwJw1S7R4MBWGyIAglZxMXCKaXBXqaImSEzYSeqgbY05MwdwEtGUkgE2aYgUQgaElLOpArKrm9pud356evL4xYc3Ty4vn12ZWGmtz1YBEUxRqtVVxBe1b3zrjYcPHp5MA1Y9OT0BMCm6HcdhYGcwVXAHBWJW695JNJUe6EQEBzIxb4bAZv3SmrSsKaWmjZANSAHBmVOorQAQUQQDphiQ0QFEySEwopuJIEOIBiru2lq1AsDMKaA7gaMJqpe5rVKXsn7pSz_9jbe-_fFPfPzf-DN_6ad_4qcvnz0lxWEcYwivP_cSRyYwRARmSlERS7OU8unmJFJw8nWppXqkKeVRu8gjUFuL9B9_QFkbCKgomBIYACl4aQ0RzckBHb1oiyGI6lpaNQnMrYo08YjY5RhmKYw9ib4uRQ0ORdRtSmk3DTGgmwCAETpHjmGKqS4lGATABOwO87yI6DDQu0-v3nty_QtvfCgAD88vznLKEZvV43LIQ2CHUuvmJG132b0i2HYayU3d5rkcDiuIY4NxyLVJbfbkyawG69q0SWcw91CNE_U-U2nSoRRMrAZjiq0KAqkIIZl3Ml6v8JJZd3uZmYO5K6i6iqtZv9iK3nVz3aGJqrmYqRp4XxeQdVyIw91vUGhyFyZ0AFUw79tCVPPatEhT96ZgDndCUDcxh4-UwGbQC8Gqpmoi2uUBnSikbiINO4TKzVx7_PTvfukfuXhkmDZjX-EQM4DuTob9vFztb0MkdP_Oz7werK6lYIDlUG4PhSM99-ILL90_3bCFYXLEH__y1yluLG6twOvPnYTWEHQpy5hIa0kAY8zTmK6PMqUMEPfHZTvFdVmZusCAl1Wv1zbv5-1mcAqR2-5k--DirLa6i5NJ_C2_8Z8Rx89-_jPq-KtfvWTjInVZjoH8s688_9Z7H-aJn394su6Pn_jY60-e3mBbduMmuYtUijzGqC7TkA9zIXRfSx7jcDLNx_lsmxJ6ZozuAZkAtbYHpyetLrs4SJHbq9sXHp1tItY6n2zzyRCNZBoyobnLdpvcJBBjtWxBVT57_3QkmmKajwd0fbgZYnOsss3xPGwenG7X6wVVWzfKuW_GkAdAtM0YmzZgHVLKeWTGD99_sjvZbrfbpp6JoCkWIaecAgqwIIg62P3H59fPVlWhRAiIBIGxrsVUdtMUOByu5pO8ASSRxcVlbQQwjgmsaVnLcWlNx3GYTrcGKGpuFuKg6svtLKKb7TTf7D947_3tyOO4SSGAad5s8zCmPLb9db2-dfOYUxgSMYOFnlTS5m46P_0gbUN0OLu_U9PAfNgf02acl2qKWpTTAMwmbgB_6__-Y-Ek7A-lacG11qv1Y8_dI_dhzCkSEC7zEhkJiBGZw2YccuaYOI8pJD4u9fJ6FgIICNxhXSSqZMENjvMCwK02N6hSSi2IvqyrG6gqEYs1RDezWmspKrWZuYi4gbTq5tas8wGAsUhxcwh0u79i5p6uTsQDh-12cvc05l66AlIHBSYHGDabkKIj9F4pR1KpiL6W0kQRMRAyk4OpVGLQ1txdVcys1KXWZtbnPGYqJtJBeYCIaARmbkRkaqAGKnWetakhhhjMFBSHceivtFaqqxOyiQJQlebujr7Oq7mJCocAQLVq09p1L12Q4qgvfOZjn_zs67_v9_zw_-IP_Iu38_Jn_9z_6el-Xko7Hko9iK7iUr21GFBa6bgRIhRZAFDdpPejDZDw-OxapbmqoxNjfyzWVh1M1U2V-0zKpG9EzaypWH_eurfWF6jWDZhEDGBoxh_ht1WFHNT9-rD_y__p31mbWtPNNDy-vzm2eb_f74-zMzx7ent7nC1GJx7HXFfQqo48bnd_5Uf-kx_4vu-zZQWQ28vl9vKWGF2UmUOIpo4YYk6dI8eIoI4AIUXiAA4xhDSMda3jkBHImzIHphjHMeaMxBxCZOwNumnaco4UY8i5252HaWpryzkRoxVN-TREXudFTG-vr9Dh8vrZbjde3D99cP_k6XtXX_ziqy--em-TkVVBBR2IMcRIRNypg2q1KnEIMQUmIFjWouo9ND7G3KmSCGDmtWnf5485TENKiWOKfandC65iJtLU1cGnKZ9spxjjUhsRqWMRP66lrtrMj3VtpgbQXdJVXKqVKpTjovVb77xXLbjS-e4kjYOaiwMTxRTWph8-u0UOSxU3XdaGjE29iarocT-X0q6PCyFSgOZ62B-B8Ox0GwhfuH_27W9efuxjz4VA56eb--fT_fubECCnSOJeipYqXXBgAqXZW3LlBmom6kvR7k5DZA7pWKSJH5Z6u6wqtix1KVUdALmZ1wZVoVTV5oe5tKZq1tSP87qudS5VQIgZnfa3yzy341o4BiRC5WWtKl7WutlOAJyHYbfbRQ5MHiOX_RyImRDMiMkcapGUIpqzkbSG6K4GhIREzLVVsDtoiYgBYAzcAYLQP3nqJgYYPjrmrj1Vr31ACu4ugC7SCO8kQ2ZGhB0l6oZmSiauVTpjEhDApB2JkACsNXND-uiYAz153PXMZuBIjGjgSghIIKVSl2qp9VyDmmgVZDLzKtXciaKoUArS1h5o3t8ebi739x-f7G_Xd955R0yZwaSVZZYmnGN_VJTlOOymf_JPf_7y8uZf-ud_93rY03EFc4poxLtxm2IyxMABDF2EkEVUTTkkBDQ1BEBwdGeiSEyOWppZTXE0aUNMpk3dmquzgzoiqgmBkWpbF3dgJO0_YwogLq14awSEdzhmNO6t3oRdz22m0pq04-18LOtclh_7if_u3We3v_d3_-7Hz78UHFOKjEaG79582MdhAQAc7z24Pw7TbrMxt1LWPGyHlELgdS0HOTg7B2IKkYDImTAENneKpGSUWE0MfciJkXfjAOq1roZGju4uqiYm_e4KDohVva0aQgw5cQzIhIhNDRyXYyUOTRwovPrSg3unm5MhBycCGodBDQzJFBAZzbgfqglLqSq0lrLWclzKB5c3X3vzPYx8sjv1jL3dVVZBJcK0SaM7LqWZaRqTqSuqabuajws0dAwpHtZ6W5bbwzzmQZu2Km4g7lW1qCo6ATMQI4GBmYYQVlGKUVRFzJqKKKD3jJ-YWZ_AuKGDNlPtXwsABzNv0lkjrObd7SJVXHo25671awYqKqJgqB_tsh3cEdUhQnJHBFTVuw4xoKhDiMVMDVTMBGpVNVPrNxdQN7U7DQAj9pESMSt4d5IQsasSEhkBBVf4yS__cmRW9zpXN0W3k01utS2HZRzz----iyCl1Fdeenxc5ovz8-PN4Xp_I1K_8D1fKLfXQcvLj-8NiF9_5wOgsTG-9InzWJYXz7ehW8wcHj282F_tTaWt5dnT_bDbPDyZpJWBKccAArI2NGfG2qqUJnXNDO8_eW8kMFdtyzvffu_d95_dHJelACgtzdci_-jv_jdEev3sxlxDTEPKfruatnvnZ7f7NVO4vxnfefe93TT6Mo8pNZHWypbCGIfHpydkthm4HhuIMeH15XVmnDhOgIkQVLc5elkTmMwFRB5e7HA5nG03nOje2bDdDrH6FDkgLMu8G_IUos0ruybzk5AudT8OEWvTVofIMYTdJteypsgGigou7fRkg6ZjYGjqTXOkxw926-F6l3Gbgss8beMwDu-9-WbO6TxHFBkSj2ibHMk8xZATWa0uLQC4t1deOh8iI_ow5Wm3c4AUgQlWqbuzbR7z5ZNnUx5DCMMQjlc3oH62Pd2OU8yxQ3iRPOTJkAF0vj24UwgBwbS1uSzbk6nNy5vvvGPoQ0yRgkib7p_Xosh4ePqExzBsp35AUzBzS8OYtyeASecayCMP6Hh7u7jrNDAxxIBoDdCGe9u4GQ0x8-Drqilc3R5b02Ozr8o1R05DCACBcBhCXSshl24IQd-EDE4BOXIEwGk3xhTU7N7JiRvg3cSY9utxXVdpRbUBgtay4bHOFSq59wC9lbU2sb5wU3FCIidy0mZM3OP7IYUYOOVcShuGkWIIzLWUw_FwPMzusKzFAxp63kxEIaWcx5EoxDi4QooJ3ZghDSOABmKtrTM8EKnvvY_rKtrujCKtIZCZMSOiA7F3xpC7q4LDnVwWAM2hqdVG7qCtZ1CB0MGJ2c1rq2mYUsygLlXq0lO76B0d2jTEGFME1zRE6wARdwTHQExEbkwWqOWBv_ip1_70H_0Df-5__i_jtb757pt_7H_1v_nGO-9er9pUAVyqpMxoJirVPAQGdHRz9xRHabWfRJDQVQEdwDGymvqdsghVjTjaXbC5t4-1NfGedGJKMfXBNhJwQHc1VXczM2nVVUG1pyH6TTGwW2mX10fx9t7lVdfi_N7_4e9KOd9__HwMcTzfHlvBAVXVFdBU1tXMa2mi_s2v_uoP_ZZfP7FHopy7cgADs4ubCmhvXnlANDUTnYbxrl0KQMx1WZmQY2pNQowUGMw7WrrHXwERKOaQQ8qrNg6hSROQkBISIcJ4ulFxdxymUW2lkKbdbtrt7j9-dHHvXpM65uH3_A_-2U---uJ3fuKFIXBoTaTtNnmaIqKrqjTpIDtm7DthB1hKEYXIXEtTFXDfbTfqNuY4pCTqOYXWmqmHyD2pHkMEMydqamJA3O00zkyMxBya-LzUtciqZgZNdC1V3QNyWepSKsccx7RKPR6PENAcr66P-8O8Lro_rtLFUhSWqo60Fv32W89Kk7nKoazF7OT0_OZmFZUqVos4eI6pqiBjp17X0kIMh8PB3EPk5x-d37-_28_tbBiHHE63Q9kXr3Z1dUPiLu5iXouKeFMVs1PdNnNxq62J21xVBVvtRSJbltXcRCzEUAGXWh1wLQ2QVmlqVkVLk2Vth7k0x-O8NgOkUGpD4MjcmoYYDZFCbM2YQ5rStBlPdpsQgpsPOeWcCcVJDej2ZsHAAXEYh1p7CA_VDIkdkVLqCTMRJWa7k5CCqmmT_m1zdQcCAKSEfPd1AiaVhkRA6Ajq6qYcg4Mj3mELkVBd3ZUju6qW0ksA3W5tqkho5u6m4J0pBGAA0EP8nXNMgXtyo_O9-inIrZuarNWGSCFFU0GiVtYQk4pTr7E6cAyA1EpFRFOX1gzIEBydEz96_n491DLXXnABM1cjQnZsRa01k-a1bafNYvYrv_L1F19-9HA3ThMy9mmO5mkT0rgWcwzaXMTAIMZMpuvhiAHNnGNCQjF1t1orh5xyqmW1VjvMixCJqLnUtgYMSEGbhpi6LVZVzBWR6lI6xAYZRVqkAdxV1EzcvK2rgyIThh7oZjdE4Lro7bG-_-E1uAYVQH_1lZe_74vf8YmXX5yGXGVtLlWEU8jDeDzOMQUiIwJnWpZl2myHOMSUW21oGEJ0M1Eoa0WMH11vqK6NQmyARfRY15wDAuaYVSVRMNQpj53kw4BSpTNhcwwGUOYVVBkUVMENCSj4clzHNBwO65tvvX_aY4imKSC4eWuBvC4rIZZ6FDMI6IBmEGIy9ya-31cRPRyXyP72u89a01cvHr76-PHp9vTh_Yt7ZzswvT0cSq2tVhOLAj3-ZWhqIA1U9TSGwIGYjmuprU1jKk3Ue7cWMbAhNVcgMPRiUkWRvDYFZnFzMwUH8MD9AugAWEWqahUVNzERV4GGhNJXZoQKLiqiXkX7D726NdVuhTRAtbs4prp3cr-aqbqYqsOixcHFXAlVrd2tabDU1vcP5t5UHKG51dbMHal7w-DOO4zgcvdXEBGgaxMzV9NOHSWi69uDl4BABnByttsN43w45hxRYTkukeN6uxCET77-cW52eTwEhOtlrqLf9xu_qz65fEDt468-J1qf3My_9K1rpbC9GM85PNhMOcZ5Xcq63rvYPjwZHlycOkG1drnOFMIYyKQd6l4dYg6BsJS2PxzffXK1OxnXecmg8-36qU--woB5GJ5_4T6QjkPenA8PnttdPr1a1_WtX33r5U-_atLiGG6OhynET33-tafPLk19XhZwvTi_ePPqKXoNMXFyI41j2uRYRcYxMUMc48V5ToRD4mnK6hInHqY8RUiRAG2uJQCprY8e3IsI7vjya8-HnN98egjD-MrL91NIOfGzm8P1ckCCzckQE-WBiixLU47sIOM4FtHqNgwDke_GdDKl7S6dX2zn_d6Oy8h4MkUU2aTcloVrYVAG2ew2p-e7YbepKhF9zClnrODDdlhre_Dg1MBTCoFwiBHMc2RCrEsd85CCR4TApLXUeV6XZS31eDxutpuy7Deb7bKum5P09L0PL29v45g4D6XV02mropuzbcoZ0TmySR2GKaahVc153JxuKXhb17o_5GFKw8CBh-202205cptv2v64LLNYrWUddyPnDCGENDkhkr_55a8BWdHKY6gCiLGsLeWE7uTMKaVpg8ghxGkTfvRv_4Oj6-VxQYo_9NKne2ipA-TMkTjg3cqaGO227CNjCiEQDDGw4zjkgHh9fRMYmFFVpEpphQJy4Plw61qrSqlLaWW_3B6XpZk2VVHpJRyVpqaH25u1FnEjxlpXaaJNeoFNtW2mgZG0mSui4_H2uBzX2pqDHffHjwKDnobIgfNmkzfj7nS32WxCYHNG9JhyTDENAwDFlImICNfjQoE4QIhkqsSkJioGCGpaTXtV181AgTvdW3qrywHAFVzEmmppKqJunCMm0lqZeLOZYuYiba0F3LRamQshhhCI0Ju4mIpxf78SiEiT2hXyKdqQwsPT83_33_rD_9rv-93nIb57vf83_tJf-Hf-4o9cLfWwtHIobRUHczSTO3i_kwGxm1lr3PWM_FHsktjB8a6-bYhEBK4NzHqyn7jb2BwAmKlLNkWad9YCuKpp8xCDdQiyGhKoCoNFRmvF3MgBHZBZ3dcqgvAPf-YfGQACPn9x7-XnHrmupxf3KcQ6C1Oy2hjR1U3uZthIfHKyefDwbAhBpIjbcVkAIOSQMoIpInV8E5Cbaje9piEbgoJRQApBmoR49-p3NWaCXt1kikRDzmAmYGJeVfM4jOPg6iptmHKHzmFCyiRuhAhuIXCta0SuMm-nccz0y__0q9_9-Y_vxvTp5-_vcn7pwfn9022goKIhUPfJQz9EiY5D7LwoEeHARlBVSqsAHpnLWtCtNV1rW9ZatbmZq6NzORZw60sqIEwpBuYh5zGne2enQ0gEeLw9AADGzjyyEAZAfP_Z06XKNG6Iue5rDnEz5piima-1hGFwVM4oRcT8uCxqzszmLu4KYIiHuV4flv18PDYB4uO8GoCIzsuqCsu8MLMTilk1GabxcFxatQ9vVmOqpRyWFgTGlEBpt5vmeebf-fv_iHbgNoGbFzF3bKaBwrwuZiDu2qVOdwIeEjUmdkAVE1UFWNbihIfj7ECtKRG7Qw-3tX6rNTcEUJ-GHALNpQFAFWmiQK6Iu-24rJJjEAAEWmuVJh-8-3RtTcCBcN7P_aDcatudn2gVd63HuZUmruAeU0AEcQh5tFYBnWMy0TSkWgoQmTVC1n7EVwX0OwoVsWtFIEBUdY7RRN0s5UFVEQwcVZVjgp4aAkAiFek5oMAZ0K0KB-40IWJWEQwB0d00pKitu5YFiZG5a_AMjAnBEYncwVS6wNXMQx7MGrgSUspDKRUJERGZwY1S5BDdNIXEIbzy8dcC2ze_-vVaGwYgdEYOgbTAcDHqIqbGhIQ0jOGHfsP3HQ_Xn3n9cz_xkz89bafDzW0rVR3iMNRaHQBBAhIgmhSCXiJCaeoISJFcAcz7qNidwbuhlpilaUzRDUiNiE2lc3LcvYkgMzIj9ASXM0VtCkzqFSkAAIbYr1LEyBRKq5wY3DosTAwEaTMOmzz94Pd-_se-9LNvvPXmm-8_AQqvfuLlMZ-I4LqsYALotZQYSJqlFOf9gjFCZ_8ThBgcnL03A9RFkSSkrCIxBkA002GIKYZAMSC5S8hJwe6KG-YUWFVTzu79enNnvWDinjoHDnUtRJRjAKRPfPrlhLQ0Oc5lSLG05onUuS2VHIAcAwbk2sTRTA0JiQlAA6KRLUsFwKUUYqqtlmZG_vDe2b3dsNtmd3Rp05CGGM0gYxZwBl6lIpIZcuJVAcD690vMx2Hoadqu1sI-HwMIkQAgBibGELtBzxiBzMaAjHg3v3ewjph2dHCiXmmHjiqznhFyIAqd8-luiGzmiMSE_Z6HgIFCleaAflfZA-9Q9ruKMbqaEar2vgG6g5kjobuLmDkQkfQ-MEEgBnADsI_Kwv23IFMtLQQOSNfHo1i7ONkRdisH_fjP_cJP__zXmZMZnG82qk1b2Wy3QDjmQUGeffDElvriC4-L6dmY17ZWlfN7289_9vE3vv7er__c85vdcFjrl778jlGqaK-8-ujw_pOXHz3EQKWuy7o8ON91r4gTvnd5Uzx8ez5-90vnb77x9u7iZDtu2FxMZG3HtRb0b19f13m5d3by7Q_e-Z4vfgYcGOH09PQb33zrZLMFsA_f_fCD997ZnWzY_LO_6fvr04O47Xan2zhsNuPX33znxUf39svtmPLu_PSdt95Pp8Nud3KyyaVpq83D3eEjRTJ0jnnYZVOdD8t2yhwI2WIARpvG4eb2yAlPd-M4poZ2vF1v1vV6uTXze_fvkdk05NcfnG_z9uZw5IiOcCwrM1IOFRAC11rEGzTNIQyZzeRid3qyHY_z7KCqamYhMBJOOczzPG7itJne-eaH9-9txm00otJ0mfcvPnow5hwiXc-zE6ylPTw7VaQ0AKcAautS8ziYex5CW0t3Wl89uQJ0GkYgZsYxJ1M9PT27enaZp42KhpyW4zLuNmvX6B2PaZikVgc83h44RQqZQjJrhJCGxGEg9LouVsVBkAO613lBgOXmmtDA-eTxI3Ro68JERFFbk9rKfg9gy7w-_NSrrYKaeasn5xtKQZrcXn2YxskB67zW4yEQVW_vv3H5fT_8Q6HVi4vTaRwCE6IjoIks69rcd9tNq-JurlhUmGiudV5qj-aXpYB6CFhKQ0JzqCI5pQ5hQQBOYRyG_XEmoqrCIYi0WgXhjgfRqsDdKA1brUBkbirS-Y1qEjmAgaqpGYcAhNbE3CmCVmm12kc45iHGcdr2ykiIzCEgMxLcETjUpMkdWVXUzUK4e_K7Oor05xWH4G5E2C_67OBmXeBqqioWiPsNgAO5GiBwSl1n2zt-MeVptwHAMq-mimQE1Kt6IQY1IyIk-KiY4MwUYyB3EgeXTMgY_-yf-1_-vt_0fQOl5ebwf_4v_vr_9a_97Q_euzoWq9XAlBhULQ8jiDChmBBRWRrHQAjdf6xm0mam1Of6XQ-cpkmkoTsYOkKpFfp_1ayVFtPQiXGBowMQk7vFGFUV0ZlCJ4QSd5hRl4MhOoiruCME5P6k5xTy-clw78GD584uzk-2APTi88996933edqotrYWUrVqHfDPxJiiWiNkM__13_MdN_ubp7eHda5SW4hRRM08Dtn9ziBlApyjI2EgYuosf7pjOZM7BA6AxKF37wOGgIg5JZXqHIA5RI5hQCYECBQZCcHHcbMuZbOZwCGEBOZDykBwutkOQ9jf7F94_GjK6ZWH54_Od8-db7djzpG306Dq4xBArWN8EKHUhgBOYAq1CjOGEGJOtTVmDjGIQ5UaUlQDQ_g1r-QmR0BEglIaB3KgJqaORQSBTDXnnJlr1av9oYo09aU0QGi164k1Drkv0G6v9s7AFAwNDJf5GInQbb66-fhrLyDSYX9cRTDE29uDIkUO1YSQn17dSG0IXFo77Oe1tlKlqRpYihERGNnMKIZaKyDGEKYhm8iH7z393Gc-Jmt98YVTRmTCkGiz3VAzq03mVdaqxy42M5Nmt8e5iBWDZRUHF7RjKccqYmDd82xeRLoElDiJespJVQxAuzAI3QyqKDjUKuoW87C09uzZvoostVWDUqUsUte63y-iuizV1arq5ZPr-ThPuw0H1mbluHBEYjCrwzRoa4DgptNuzEMacxqGkTmAAyLVZUYmcFepYYhlXTnfVfgdwcDU7c4YgAaAbtJNQ3znO0UicO_KW7pj3Hd8OfidQsIVEWPKYGpa3Q1DAOgwsc4hwL65Q0RUQCJ348AIDiIIeIcb61JpQg6BKWhtAAgAphJCICIzNWkpJzNVMdUGiMzBwQlwHOOzJ08_9YVP_Vd_80fVtKmiAyGpaAis6O1YMHaVcbu5vP7u7_mel1974etf_8bX3vjVH_gN33l9-eT8dBciBmYA4BDAlZhba0TgCK1Vv_vcdvliYwpWXYpwYDVvBmZuJqYaUja1gOQGJkJEtQmG5O6IKLWAqJo5ggKyU0qZiNAdVHrah3HGxD4AAQAASURBVDggQquq4GCoVcEgxkhECBgDVZHD7bw5nR4_PnPUeTm8_f57_-j_--UPrm_P7-8-_cmPv_La661ISKyqKq2saxqjmazrUaogUJ9IhXEAQGAPmetc67oSg4AAgau7QaCAhALSzNa6gjlS58uYakOiZV2AuMjapzxgAIBmJg5rWWNOJi7Vqth0P3_t8vqb7zx5cjU_Ot_uYkwAJ9vNNCVErWJrEUQcY2IgUwVDc0gxK5MqYsTmrhAcScANVZpdX-_ffXr74fV-Lesi-uTm-OxQF5En5RDIY4AIkYmRQQzUnYGog6XB9sf9mPNuHFKICHC3J-kbGjBEdKRecnYwYuDANARnLEX-_5gJoKLurnJnrlYF9TvMAgKC3GGCepQNERGRgAyBkEWt1Npn-d1q0avFDOiGANx1AqqmpmL-0V-MalbVmrk4qKAbdvqyIap6aXq3zNTua3RR48CIZA5Vmpk6AoABMUT-f_-Dvxs5MlOKMYyptgaIznT15ApDePLhk4h-9vAsn03FKhgcD-t2O37hE4-P777_sQcbiCFy-tmvvHt7veqxvP7iQ1CJISGxquUYXnx0fxqilEZAgVMRb1o-uTuNNIbNoEWyw3aYcowj8-X17Ukeg9np6WbajJ988aWzi3NSH4Y8nGyevHHz1lsffOkf_tQ3fuXrjMrkkPCv_Ln_KG6HVk1c1O3B6W45zJuJ7l1snj598vKD87wLv_D1b50MWWq9P8ZtSvemIQCcbGIEvDjfXGxjUL84He-f7nJMh3leIu9LfXa5V9PTk90YkmuDAEzAmXabTVB-8t4lBbx6crmu66-8_-R23U-Ry7JMY3ZnA9of1zFkch_H6EBnp6doHhUOa8UQn93cqnhA3g4jaJvn47LOBNSayaLr3B6_eM5It0_3db_uLsZhmr76S78ahkGrbnLeTdM0xqv9MSiwhSnHPIb797ZaCohkDBRxu5uIfDwZPXBrlYAIozZxs7YeHz-6D1r3h1nADOy4lsA4bbY4JMhBVKbdScrRwFopdZ2n3QlYs7m1dQ0pIzomL7c3ZFFEzCHuNmk7GuJ8dTl_-JRMhhzX5Vhao5TjlEMOQFT3t8pNzc5Ot229PFwetrhlos10EWJcjjOliCEIkFrYng4__3M_HxgjcUBKgRGptupkMaX97RERRK01QSZCFAN3D4GaaAx3OM5mSoFFjJByCq0pIaVxUoCqdjsvwzg2FRUty4rIrTYANBPCoNYDfKTaiLAsi6oaeM-kE4Cb5ZTcPATyPkVANPDbq3le1rKuZV6lNlhb5MAAu82UmFCtMxZrFTAw0VYLIVIIZSkIEEJABL1DDCFgPy1SF_9wJ2UiOoCbWxV0cHRiB7AOY-hyGBXrHCFvQszDZsrT5A7H_dGspcgOVEp1u7tUIPVnWgfAAwQAdzILIeSRBwz_-z_zR__TP_-_filtPcV_7z_8z_7An_jzX_qJLz97ti8rWjVQq2uR2sB0PRwIsK4VkREgRjCtUqvbnfuTYaDusFbtMaO6zr1M6OAADO4ITo5E5G49r9zl6oETmiEQKsaQvKlJ6-nXtq7oILV2CAOYhxBcJcTgoiQ6JB4Siec_-Ht_6z_-uV80b-x-f7f5_Mc_nlCee_5FbX7TDrjZMCfmGIcEjo7kKcUh19r-yB_4H29TSITjlNEtxmhIhoTMHCIicYwcs7oDoKjmYQpMIQQKkVNgJgxhGCcKoQ9gAUDNKaY4jEiYx0wppZQYwpAyoMUhIYcmZZiSVun2tGE7hjGlMccUbw7H1z7-mlh77tHZ_ng9kEFTcgsUAkFAd_EQSESJyRFiJEpdIsrDMMSYwGFda39hHUtZS13WVms7rKu7pxhS5L4CcnQR5dgzS52TKcux3u6PhiBrQ8RiupQ6nUxAxAAphNbaOKQ0jmigauuyIkBrUrUcDuXq5raZN_Xr_eH-g_sB2cCK2rKWwzwXhevDfFvW_XGFyN2eg0TH43o4rIQgKuoAGOe5OIYisjapayViVa8Gq8h-XTHym-9-QIGc0Nw58LwvZS1khK1jZ5q2qtARLm4KkEIspTWz41zKKlV8f5jnYz3OdX8s81rV6bjUudSmYgqRUu_MN7N5rfvDutRqDiFECjTG5KbHqkU0wLaquoEZ1CZucFxKilkBDGxZ1jik2rysrTVDBzBioJjHmDIArHORtQzjZI55GKwWBqtrcTQQ6daMzik3lTAMZW2OHgITYEC0JhQyI0kTDomQtamroru7SilABO5SK7iZKPUUvNQuTurmCHMHDECkWsEUXQFQW7M7Q4ebSKd8ujsxmViImRABvNWVQmCK1hqguRkz90uDtgrgUgpzQiBkMgDqqyZGq4ZAUgUBya0c59Pdyb1NnJ_eOkAIjqhQFQgUcHOayzxLaYAy5ejuz19srJaYttc3N4fjzec__tLh-FSP11b3SXU7TowUKVJI1gx781XB1RBRS7WewwhMkftSmDkEMzZvIoCuTQHJ-q2JydHNxBEBqY9hQsyOIGazzBQZgLQ5IuSYrd15smKM0Hd13Q3G1Dthrq2U-cnxMlB8_rkX8nBiFdANrXz47ltvvvHG17_5javbm9c_9_rFw0eQMhGFkLTW2HvhTUwaAyBRDjRsxmmctDQg0KXJvBKQgcUUOATveT4nVGil1dZQURWYIwLWtZBTK7UsrZUGQAAemJiZAZmDuMKdlyz-4i9--OVffLM5z-6Pnj977fH9-yfbpPV0GjbTlAL3A3PTZq6AXKtIs1bdBQSsqHYbXWmwrKbORLCWsszlONcCtJitZtfL_vIwX83L0-NyeVhi4hijq1dZD8tS3QAppBgCI3JfOJ-cjI8fnW02ExEioqMxErh60zHniJQAAmJg1FWlGhGrGgAggIsxETmpoRncbfucHMgN0VC1IgIhevdWmiFCc1Mzg87sBjUFIjGF7oE0a6IBg3cjmEH3fNUmpi5qTdtdk5hQOwcEugPYS-cZ3fEHuyUUgLAjQ7sJTqQFDoQERkB8uNnvPySChAS73eZwOJpZjEPM8d6De9tpuHz3g3m_fPyTHytLYfVSF7OGAGfkLLSdBqL0i28__dUnt3GIp_fyhPbsrct7Z7scKTA8eXq5HaM3H1OKgdf5iIFA9ZWz3dOr_Xvv3dw_vXh2fST041xmbWMaOdKz28MwRRxCTHGc8mab8xijIkN77vGLb735rSkDIB6u96Dqpb7y2iNkbvNyUDs92YLrlMKLD-9f3Vwz80sXL9wsh7ruxxQ3ObnJARsEqyLEqOox0CZCAtlNeTPA_un1Q4D7Y_ji689fXc_baZNSRKK1tjff-VAcAWDkHHO6_4jYsZYia7uZ56ZyfXs4HpdIqNVKba0sJzknSsX02fFI47A7OSlrvbm62mzjg8cnbtjWsjs9OTs7iU4mdjIOF7uTi93J2XgKAg8uLnLg8-3pbnMCDBb03r2LyLw_rNM4AUFAGEKwZgGRAwXG3RiRLBCAtO04kAG7cVmDrAE1mM1Pr548uXLm3bS5uDhZD8dxzLfPrupa3X2z2RDjdH7iIeSTkxCZ2IlYauGcj_vrHKMhYkp1ntGhLs82u52pIXA-fSAi7uXw7ANOKaYpx8Gb1VYNIJ-cA4eQwrtf_hZyXEs5PXsOkRddXI0AGkAYh3w2bU42jnq83R-W-Rd-5ufUSeoaAiFCX9t1ICKSiTsxhMCigg7H24M7LOvaaj3O80f4Cg9IRKSqiJByiGNUazElMmDCUus0jmaKiFpKjNFUWpXaVoqsqq4GRq20HBOZsYOWtdYyTVOpXQ3mYIAEtUotAgpDDOtNGaeNmWqVzYOTYTNGDtKEiTgEVy23-xQoRtLa6lxaaWUpFJOYU2AOiTj0Tn9IubuxXNx6PsnNwcVM3bqHsHeP1JQ5dSi-uwVCBGBCIpZakdjRxORw2FOkPrXpip5OTTVHjGxm3WHPHAiMEYaEr7_y6l_9S__2559_wXn45htv_iv_9l_8ha_-yn5ZlrWuawMAaUpIpITuVkpPCrRS3cEAGBntDvYN1OM8pnUNFAiZOkmkCXZIOqC5MiCau1RQJ2JTpR5nNHUpnankYK4aUuzRSQQNMbi1gNCDQECEBokTmDGjOViVeamf-uyL_9q_9yM_94tf-S-_9I_FbIrhB77jk_e3W1vWF19-_t7Zi82Axpy2W8w5jCOlPGxP8m779__G33ju_n2pVmt1cxVwkUjcl2EdTYscnHDImZmZgrQaQgoUxCykjCG4A4dEgEiBcohDzMPQaQ7MgYnNzcDGYXCHnAYiBHcDGIYhTwNyIEQOfHb_zFV3u-3HXn1-yPz8w_tff_NbLz262MTACIk5MASk7ZjpI-2kqwI4BVrnOi91aa0PeUtpbr7bTq0JOKnbyemmVJVmrdrtYXF0AqxiQwzVoLmXpuodyojMBMxDzillabK_PQKwWbdPoZuN06DmLqZmoD7gwOTluByORzG_o8KDPvf8w0985sX9XG5vV0En4lJF3NT19ubgEC6vDiFGIDguC0VW85ASMnGMpZU0Rjcjx-VY5rUAgqGlHInC9WGfc76eb2LiZV_APQQS1SdPLqksog4KLuZNvDarYqLuiLdzqWqiZu4drScGqzRkrGri0BNUTnR7mJvZ7Tx7X58Z3M61dgaZuojupk1ptjYRqdXgcv-sFDkc17U2QVACCmFeVjOY59pvBTykInL54RNwBkQHfvLOe6a0vzkyc0wJXMq8rHVBDof9vD05i3EwcGRyAOQQYiQMAJTGaO7MwQFCGpAoBTaDGINaRXJKwYnMpJOeetmYmHoo39RCCD0Lbaadmo8A0taeNya-CzwQM7ijOzN3YLm6tdZcDZGk1X58-ghP7pwimJmoG3Bgu1s79EBz31SAqsV4iu4EgOFuCu3SUoxA-LFPfuLb33onMHa-Sam1SEPiulZTY8DSCiICUdP5-YcPn94e_-6PfekLX_jsg_tn33zz3X_rX_7Dv_O3_85MLrSUektEDo6uHSisAo5g6GEcLCDF8GumVwA3VTR1Jkcqq4oIQkevKjBJqSknM4shBA5ofevWmewkaj1UhkxmWGQNmd20OwXNTdSIiQNbL3K51lLc_Opwm1IACCfb02mzQWcO0Z3Ww6wOTz788Gtf-drl5dX9e6cnZ2e77Wa7ORExxAABN5uRCZhwf3tEpJzSsNsgETOkHMuxjpsBASIjBw6cADwHBjACVK0IINqsh06s_9dZ1Xo3o66FEEOMkcMi5gDiPu3S7dNrACgI0tZlmZ8_3wTzk-3m_GT74Oz0_m4gLK02RHdARzRCNSsiHaYWMPS2G6IxBVdbiziiMSyr7K-PABg4UkiCUA2UqDreHCqR7bYTIRvaXYvfHYlijiKCSCJai5wM9GA7vnC-uz8NETEyVjBwI4cU2BcbQswhgDmYIkHVBkTEDN3lg6Dud1nfTt4kLCYKrq7SkYGmSNjERFVa5xJq79aLChA0E3MQdXVvWs3UwVU9UjJ18M76dLlDJ0Ot4uC1VXOrqmIgBlUNmJoqIHUmeM84dZuYiFURNe9_hoj_zJd_2Z2YYx5SM2_S6lpSjtEwD_l2vilVHPH89KyudVlnJBxi-l2_5XuXpZjIvCwn59uf_PLbEw_jmJ__2AsfPL282AQ2qbXmHBjx_sUpia3LwohLFVN6690nMZBCkIjGvtmMxNRAf-7tr52dnySKi-om5ynne-fn3kzK6q1FpoI4bYI6L8eFgXNIkcP5ZvzRH_-5SPmwLK3U7TRs8ljL-vjBg7LO6_H48iuPQ2nvvf80xFzqqlJHjuDqYCfbYRp4inhxumODdb_kAJvtsNtyysNxXR_eO2OE3W48PTm5ubp99OD-1f5mPq4hDk38J3786yUgEHG4A-butpvWBAE50b3dNjLWZd6N-STlQKR1DZHVjInm21LKwpG2uy0IKtDLr714uts4o4PnTLsYkKnWmhhsf_zMiy-AydWTqzGHB6e73XbiCNPAQ3QwM-nOSwdXhDtti9Q2DfzC4_MAMKRcl7UulVOaLs6Oe7l6cmPm0zBcnF6043qSx-Q8UdS5RYxslAMRsnu_xOs6z7W1eV1LmdEp5pEixRzW42J1HbcjMqZpM-zOkVFK2V9eE2BMuZQljoFTiHlkjpT46p03QyQwVOBF6u31IQ8YhuRNUkCsPow7FGfDVlpkfPfZk2roqKJqTV3NzEIK7iZFAEncm2qTlodRzIC4Nmlr66BtVWgdVmBmVRixrdWarutaREyklqbNEMDqioAgSkQhcqkVrF85DMCQsOdzEIBCtKZlWZmDqqUUHXDerwDGsS8GfNqNIjVNE0WKGNHR0EA0pkA9VxqQAMtczYwDq0pgBm0pspuZKTqoaSBMOXdCgIFjYOtjcrpzEiNSa63vKlpz0UoEpg0cVO3usYcITK00VT9e3w5D1qLoyIERWZq4edPWVMtagEhNQ0rEGMZht02ff-2lP_uv_-Gz3fb9p_t_9U_9H_7kX_iPv_3h5dGAMJj0YHYgDg4wbAciQCYzkXXlQGDSOvJRhTAYdE6a9htBV5L3WGMXDjD3RYcDmGu76_i6mXcGC7upmnGM4B1_4KqG5O5q7g5kjqbeU8fM1I9jIlXARZUiYsMf-3v_5P03nrz_5Prnv_H2V7_5prmfn0zf9alXHpxtT05PdifbYdzwMGIMxIyBOAZvqm6np5Mz3VxdTb2Rw6gNUuAQQAVLEQrB0cnRHTkESgEBtckwTgAMjsRsBh_dzCxybGKcEwVGgu20CTG6WIpJtG53W4jEMedpGvIYAGOgccxxSNDqs_fe30zDvM7bPPzzP_DruNbf_J1f-PRrL-UhtbZqvydC15BKE0mZicgVWtGY0maTS5N5rVWEQiDCUhUAVa02aeqLSIzBwXOKJh6HyMw3h7VKLaKte2_cORCGwMylSsz0URvNW5GRQoCwLiVTyDmrtWUt4nZoB8KYUraGrVQmZ-Yc0wvn9-Vo4l5NliohZys6pKlUa-ZAVKVJbaZYmxjasBnWtRFFkZaG7EQxJSfebDfDkNw8ctBWS1lB4bisT2-u752f5pQNYS2VCB6cn9JaWy1Siixr35GbA_ya7tfMVbwImkFtCgAi1poCkQJV1cDszXPKx3kRheNS1B2INlPKOQHxWgWJxV1dl2U1wyrNAFu7w906BlFfSyutVqlEQdRDjMfbPbjvzu87Wt5mDvzcqy_XskybIW8HcTXDNOazi3MzHaa8rvv9_pbIOWIn2QN0TSD0hJyC19bU3NDWuqYxt1pcRcW8T-rNVCoAmAj0-DsxIUjHpiASs4uAG6Azc4-j_dqGTqUhRwQwu3Ob9xA8kHt3cRCpKQAQgram5ojkhMQssjoRcY-pUatVzCjGO_DZckmB3ZQAwdTdGL21UrR-4Xu_80s_9bM5EAK4VldEYm1t3Jy00oCQEVFkWdcvfvHT97bpP_nP_zoinI7pt33v9_1zv-UH_92_8pf_yU_99Hd8-jP_vR_4QaZq5cAIOcRgJOrmCohhTFXaMq_MzAGxaSA2kxiIAjsCEg3T5OYYOARmJEZENKsVEEVUXQ1dVZCdQgDVnDrMFAGBYlTpl_yurWkEkHNCBGYmDhy4sxGYOQWeEofo-2VWdEdShP4trstitaqs683tt7_-5uXl9c3xQGMYN2Oa4na7lVIzB7ir7RsQDNO0nba9ghoAqYmtEgORmevKAY0cidxRzJkwh8QYiouRASFTcDc1RURDv3OFowcmCsEDxkTX16uoK6INYV89j9PD8-2YOZCkoPc2m1cuLkYGUJWqTaSXVtWtNQMnbqTNtPUJldVarfVGkIYIxChVq9QhpJRSDKEsomrHuV3v69ralIZgpCrzsqyigFSbmGIRMXeRdrtfj0s51jUGOD8ZHpyNz52f7ue51ZXAHj4-294bxSyloO7zUg1orrpWwYA5IxECQg-dkqGJggMxAd65LvqSt-d8ADCEYOourgDNlIhMe4wY-qG_NwF6OWdtRdSb9jOeiXm7I4KDau8BGyCauaqLWq0i6k1d3QDdzbH7Psx7yTiEaAZirm7_1T_4SeLAEQJHa-IOIn7x8J47meEHTy7H7e65j716sxy0rjmSNfne7_r0V37-K6cnp8u6Fvf_13_900T5sF---LmPv_WNt6Zhc7IZ79_fpYDruuYxzMscczKHwzLPopYQXE3ty994Q8XdYbPJHEnNXz17LnIQtyHjyb3T9bhuhuilMbOs1dRijnGgV199_tVPfoeKlLmWw7y09b_70pfzGf_Km9-8uj1cl_X1jz9flrpJ6WOv3Hvj7Xc2PD66OP2VN94KaIR4cbED8nunUwp8koIrPX_vXisyMQ5TevBw8-Tw4e5sExMN4_j06nJtx1aP83xzcrpry3p_uzkZA6DNy_Htt59OcapqUeFi2p5v83LbHt4_2-4mdau1lGU9OduFGHQt6LpWI8bTIZkLM3KIc6lPnl0u7Qjg73_w7MPbm5D4oK2A3Mi63YytVQHdr_MN6JDGt954Sx02wxDAr2-P71xe3ZYVk6ccEhO4RKIYMA64yXR6sckj521WxtnpdhFRWWo1xAePTtbjcZnL8biolFrK7WF_2N8yhUhcjvsYMIW83eykFlWp66JgTgjB55urAEhOTHlZ5nGaLi8vPUAeMseYpl2pYG6IdvnsQyfenZ3I0lpzSplTVnPqjfrm0nTdr2aCEqAZiA8xBoR8MsnaAEkqOvM_-NGf1QjXNwcA4Bg4sKilFIMBoiOCIhiCOFQRRCJgd_AAQ84GSp3WBUKM5m7qYObgyGBuVRQRDse9iahardUZTdTN0UlqZWTGUKtAD9wTzVWaGqCraKul1VJrabWOwzAfVic0hKbawASpqUwnEzECYxWBxIjOMYqZI5dlbdosYBNxRFFFZDBHh45xJQCmaE2QyAlSTiFl5kAUQkgAXRsIBh5CdHdiMLAORsVAbmY9yoBQDou0shz2IgrEQNiZ-mbmqnVtv4ZBQ7XEmEcKY7z_8OKHfutv-hN_5Pc18L_-oz_1p_-Dv_ru5dVNcYsRhGoRE9VqtS5IFONY1pUoSlEAqFJjmtw9p6y1Arm5ILhV6fUqAAdCFeUQidms37XQ3PsjlZnVFB1CjN5NWMRI7KJgfTwnIca-x6h1pZiQsEk1EDfhxGICiH19RMwxBo4Bkx4P15dPL_ciH1xe_3_-25985-oqYPjCx14b0C92GwIKhKYeYgxDjinEnEz1fHvylV996_33LoeBppxbkZDiuBsgsZKHHDhSa80B8pBSTiKCgBRDHLKqTlMGQkSKOYpZCHHYbNU0pOhmnEIcJmeSquNmwxxDHo7LnMcRyDGQeAs5O_H57oUh5ZzHk932_Gw35jiO6ee__fbzrz7_-iuPc4rWNMQEYIEocCAiQnBz6exvpg6zVvGUYhGtTRCdQ5zXJeccMgHAcVnMzBHHMaNjiIEAHYCZWm3mNs_lZr9WMSIQM1HlLhUOgQKXWjtoVJoOeQT3TNQaxiEBU6kySxETJmR0AjD3Vz73MTC5uZk_-PB6P5frfXn_6aVHevL0GSgYIpC7AXM47JcmcvlsL-DisMwLOqsAAM6l1NbEaj9qxhBizCGG1z_xcWTc8M5diWGtgomGaZg2iQys1NajzCo2z1KaOkIzE3N1WEXXpjdLKU1UYK1WmpbWylpE_Divpclcm4C3u3GMrUWIWMQBMKW4n9d1qfOx1z3dAc2huK21NtNSqoqa2VraUnVeSlVdWwOmUpqaqWo7VgJC9zgkqQ0d0WE-HIdhfPbB0929e27GFJ977rnazBSHacMcOnWnlhXMc4wd-EhgDKBiLoSOCIaEOcTu5O0FQUI0t1ZWuguuRK-CHfYPDtq8Ve3Nd3AztNY4BBXE3p0xl97CBAwhgPZZinUxsKh17XgITEja1FUAsdWKFEIa3CwPU1trCJmICV3rSohMRMSARgHcqpMmyjFHre24rMuyeJdoAFkzMCFCqRVMXLWs67_wO_77X_vW25dPnx6W9n_8kf_s5Hz3G7__uz7z4gvLOv_sL__S_-Ov_bXv-twXP__F76hWmjYDDFCnMde61rW98MJzn__cJ8_OzzY5iDeptVcmSPtkFdQFmUW9VU1DLrUwRTMLIbgDIHt_HktfmTACMoWUkyqqW8gZ3FQVAIiorC2EYAqUBwA3dQMjZhzStJ2aGrCv69pak9qYSV2tG3yBW3NzAxBrVaXdXt2YtFpqzgkDH9falSUuRoakOo5pPB0sEOcAgMgBEZe1mpg5NHRngAAIqKJNBAlOhsncCPon36XZcV7MsWprJmDIQAbgiiHHuIuGWtTV_cOnVyHwpx4_cGnr4aituejJbnru0dnJLnHw7nUiMkB3wiZSW1OxkBIjq1MTCCMP3bRiaO7M6OYqNRqAGiCpA2YuYq24i445RQ4dYwvefcZAzEup_Vs3l2VZ66G0ea2rQGZ77nT3_MMLDqOqyaIpBGYa87DZTtOYqugienmzzOI5xU0e-hbTu0Aa-wq-C2k6ghB7jt_cEZ2InMCdVKGTBfomARyYyAFUtJoVqXZXC8au80P4yEKg1nfr5thEtIOAelO8uzfVTUHVTS0wO5ATzFZDjuJKHG5vlmfPDg4YEuYpKii5pTEHDGkYOebl2VGWdv_F8-VmjolCoHWeCeXhxW7f6rHoe-8dbm78cFO-83s-025vdZXdLm13Q86BE7_11jsvP35gajHA6W6nRl97-8lgdn_aOMLXnr6bphgR8sA5D83bUmC3zdXBRccUpik-enhOBK0dGb1YffHV-8u8_22_6Qf_p3_095-djOoVnVIM5cnt_VcePjx7sNmFZzfH-w_PAkOt5Xu-4wvvP_lwiPjZj792u79qaw0p50RjZDQ7ieFYyskmCdI48W43ubbk_h0vf5zVzrZ52nBml1bnY0kpgiynu7yJ4FZ5E6ZdzoMbVDB9-GB7ejadnoyvvnrvZJp2m-nx44tH9843m_F4nJnt0YMLIKRE43Y4PZkO8xI4LmsLjPcfnscUppylyjgMrclmnFwZANAx5RCYivPh5sjMZV1d2nFeotnD7e7hNFxd76-vDylijLGzlq-uj6g6pmC1aTNOcRxG13rxYOdWwR0BhmEaN1m0uoihxjHNx0PR9uzyybDNqrberog67PIwZiZxbSlmr2LmDYASM8Fme1Kqg0sO1I7zfJzHzeb03r3t6Yk2vX3yYVsPdTmaNU7hDogchzRkAHv6jW940KI1nwUwtdrQPQRaj6ssjs2n05OcU8BI43S4vH7zvWcKWFVraegQORIShVBKdXcCEjUjUAB1pUwYsardzrNUW0sV1c7b1Y9IOp2lgQqm1rHX6NRE5mWptRn2cj-heSIG081mC0QKiCG5KQDWpre3-1prVwHWdZVWTs62bS6M4OyqZmYAGMIgisfjGphRnZxcDR1Um2rj0IUrREyuqq315XgnAhNQHCIGUDPiQCEwB44xpSS1MTESUUAxUzFwdDU0BMN-Ju5HvX51CYFNxNYVDMq8tNLWeV3n1awCoTGoKYJzIAiUt-F8l3_nb_2Bf_-P_8Hf_xu__5feu_lDf_zf_5v_6Kfe_OBGIKgKKxFzAJG1xIhgpdV1Od64EbinIZqoltrWoyugw5CziVmthMiBEO7-bX2YKE0ckEJsawN3MINeiwLsXFP_CBMCwB0honVBQkQyVe7sCnUQRyAicnNG_MhvC2YeuuveEZDdRJZSqx2Wsl_kVtpf_mt_71jW04vdr_vCJ7cjP7p3uhtzZAIHZiRiUMghEfP7717ls_zc_YvSKoG7CEWWRckYVRGA-m1BjCJRjBiYQ3QATpGIkTgNOcRAjDlnU4vDwMzMrE1CYIohpNCvqsyQhgwiKQ6JKBBxREa6uXmLQEUKE51O4-HmNjHcO9lFtNpkCCnnmGMgx8hMffQL3UDspqbuYlZrM4AQw27KImLmtbYQ42GZh5QdaF5qD2GpGXLX4GiOvM05pWwACl5VFX1uWps29dvruVZppgA4bKd5LfMqxHcNnrm0HBnUYwjELK315TYi1abrvMLVUkQaKCJuT8aQaCny7befVG1zLfNSl6UCoitxSPNcKdDhcDgcFjdfDscQcH97MHcgH_LYhVFrqWspovrk6ZW4_vovvkJqrjCOmZCWpVzdrKSOCqAOzayqAsFS6lplXbU0aaJNW9VWpVW1oq4IpXlrBsC1taJm7rVKrVpac6RWTVSf3RyqahHpKiXp20S3ELI6GnlO-XSzQ4WA4ThXDMGIyirHuiqIuh3mgkPAAESwPdkBWCt1HKc0RDB082kzARIh1nVFBNE2z_PuZONuqAbmaHcNXhNlmsz6PBLBe-u_cgzgzkStX0FMOHQSgAOAmd75xYGYKPBgtRElThl7ZZYQkO4kJ4AxkqtQbwN36Kdqh5Qh3H2WEBE7A1GcOLo59gduXy-AqRYzdZfArE3cu6Ia3Tv2rKJJApgv10998Tuef-GF6-vD4WYGh44yVTVH5xjXeYkhElFHtpzfv0cOf-lH_p_LcQGrh2dP7Xh8dHHy5gdXt8d68fDBuDv_-z_697_5xtf-ud_x2-8_vl9lCZGlGIfw-KUXv_OLX3ju8ePXXnn1N__wb_1dv-u3O4rV0qSIGAGqCQcGgBhCQCDEYRx7gNvuVFNu7hS4o1cpkJgSs5nFHA2g1soxqhgyYsRhzFIqM9b54AZAwDGGzMM0vvbxV9alXF_vt5vRAYH5eDMjp7WKITiquclaAwZXRdMA2NbVmz978qyKIGEtpWlZ13VpNeXBHGLaxJhKaQaIAVHR3KsrMIqauquDMhqKqACgIcSUgMmpd7o85VRrBe8xOQFEZg4ptoYiQClBxGb2bL939jSE3cDbky0hqZZaa0R6cH766N7ZmGIi0KaMWOqKBsBO7ESkAOjOgdzJkGJIQBwTBcZpSGCqTWqpAIZIUsXdj6Xs19J_xgChNVPRpRpzKE3M_bi2-SgGrAalNnE4zvXqUBfRY2vqsp_X0uS2yLPb9ahKidZq1e6MfoeDHNfWat1t8unZdpiGDnQCNER0AgjUSwPmaqpdEKbmPSgI7v2z0K_N6gaIosohmrgb3SHI3MX7g1tF7zQdYj0ShwDkCkR363Uz7E_VXkvo9QYVccQOy1O1qvrNd987LtXRMIZ1LuTe1vVst0UMgKbrnGMY88gF9_ORYySCF5675012J1sw__Evf-NmWRqqYnv4YPvL33rnpefvxxC3u-28igo8fu7hdhrQvKz1sByPyyFs8lvz4ez8xAIHwUdnFzFEQsgpstFmGocUj4fjLo4IpGLbFEksUxymkR0-9YnXHj649-prL7Eef-i3_jAaiDZOvD2neLTJ0_VhuZyP7DCO-enl5bTb1nU5Hm5ef_U1NvzFX_zVEMI4DmUph6Xszra3tZ6k6dnV5RgpxnBxsclpiAQillyltcPxAG772_3h-nY3JLTmUlV1TINWLfO6uZgYfXE9O9k9fHj_s596IYHL8fbhLu42w5QCSNttNwo-5mjH47o_Dindzvvd6bCdRnKXUnfT9nDcc0BiIMT5uI8RQ_Kis3hjonspggliGIdsaPcvzmOm-XB09YvNFtxTzo8enuy2J-cnu899xyuumBhPdxtQjZHuX5xucxxSDpxMTeZ5WQ_D6TBNQ2Bc9i1yPL84m59du8r-9hZMO0aTkNO4IYwuEiJHp0xh2c9Xzy43m11ZlpOzk-NxfvDo3slmQ2CBEAymswfAQaXKOqss2mpOIQ0RgUo1czbTp9_-JsUQxrHMYTlK3E1xmxF8yDlN1GodznYhBCR78tY7DfSnfuLnDkVqFQdsYktdj2slQnEFcCYaU8gxDCkgUUw5xMgpNG3WLaeqdSk9V13K2po2bWUtS5kBodbVEBQAEAMTOJRSuseDEFUkpqxWEHxZlmU-IqK6ILhbY5X55lrWkmJYl-IGIQRpFdWliDXNQ0K01morlYBEFBzQkVyliotDNVmriXZZFYCXpXRQdkqBmExExUOKMUUCl1rd7_xf6tZZZOAQY-joxq7d9B5BiRHckUlVUk5gHigQoVZRVVUhwrK01uzufK0C1s5O4nd94fU_-cf-wB_6Hf_sJp3_xf_bX_t3_4P_y7PjzZvPrm7ndWm1ltK0pc108tzz44MLxcBp0K7lIq-1YQgcQmBSq4hYS6WQmEIPBIODqhNHQDQ3DKTuyOxqeYhgGkOWWj-KrxR3AVAAk1bABVSJ0ETvmMfe47jAHU6IRE4hBKlCxN7vRW7g4FVUPe4yInGIHsJy1Hc_uPrVd9999_1nP_2L31DRT732cjQ_maYhDjkN6ATmrVVzbyatijT91W9_e3t--snXX-vmVhOnwCYWQ0bEccgqSiEMnIgDhqDmKWd3z0OKyA642e0cCZnHaeoAqJBCSNEQYhohhvT_I-rPfjXL0vw87B3WWnv4hjPFnPNQlVnz1FN1N0k3RXYT3USTEilahOjpwneG_B_4woB9wwsBvBAMGLYhSLQgWqZESK2uJtnssbrmuTKrsrJyzsiYzvgNe--11jv4Yp-i7wKBCOCcOPHtvdb7_n7P07WzFiwghaYNKSHiYrlsus7QuGnavj-8cdz0zW4cj1bLtom7YfPo0aWWYiZuc4PVzbVUAXckkDrTJYHIHZw5TlNumAlwteyIsEjdD2NI0dxDpJhCimHM9eJqtxuGKlpMzZUZlouGiBwRGLP4MFVxdfMi4uZ5kqlmqWUqpUhFxFyliG7HcTPuiThPhZHpuhxqRBoQuhQE5fRssxlKBdtscp7q5dVuue7c3dD7ZUeEPJP0iki1PGamUEVyyU0bTS2GMBXZ5ryXydSrKCJf7bZquhuGxaK_ebBOMXTLdtzury63-81okWgqtYpNRUUti1axajaUam7unnNlTmCzH9R1tmi6AVARqWoIKOYxJKAwZQGASXU_SWoadUBkc3QAZXT0EOJ-PxGhuFfRfS5FdDvuFXGoKuYYeDeUaZRpKqlNWqqMmTCIq5o3fT_u92ZQyxjbJO5lyoBQxgmItNRpGksuAFhqAQCKwdzmVWKWDQZ2B5VipjOFkwhFVGqha6wAzM8FJI4hErHVOvd4AcmsIqOboCsAuKipERIAgrtpnVUjRDTnFDkQgItWB53POmYOiMQINl83dM73IXgtGR2YGOYmkKqZAJHbfDcgqdnMvWB_7zlQOThcvP6d711tLt1ApDKqqjhA1WpiZrXt-3G_YyJGzWZ_9-_9_p98-3XVOpZCMXHLF7s9Q2zacOvWjWG0pl2sj-7kIX_lD__wE5_63Gd-9fPbXDjSM_fu_c0vf6lM5f79919_8_t_9K__9R70b_-dv7Va9jJWjpzaNiB5FTR31RhTyXWeQ3MIUmsTIziEmEyVkN3ACVIb1bztlkgYY4hNqlVCCISMQJFC0zTEZCbE6OZAHGNKCK_eeQpVi2gVS11yBiIGsy42kcimiQ1CDOgeIpviOBR3RgQTKVlE6_HJLQCIkU11nCaIhIxd2y5WSVRj4qoaQ6yTgBEhaREEzDkDEMU0jdN8lQOgWisDmELOdd7nliruiIiM0DUR6LrK3DAhhJzVXQTguadvlVwczMBrKSruBos23j5cnqy6PjGYoDtFAgADEK1iaigMqEXJgQhKyS7aEfQhdF2bUlg1TUI8jqFp0pyB3w35WqbjwIGMSEWHUkPkqYo5GXKuKg7mNJVq7nMFwgwxUDUZpjIVEUdVrKOPozIGVQekXCVrnUSyeBVrY7q16pdNgzbP3q7f1aIC5oQzPxeB0AwcnTmoqQOY2GxVrCLqNNXiCA4gqq5etcIMKnC_rhkgFJkzyjZzRUUrAPr84UIydXf8RZ5xTpahmDGxiFenP_n29yL4ousYUGtOgCmF1XKhuajo2dmlam2WsYBwE_YyIsjdO8cx4ZPL85--89GYvSLHGD_x6lMffvCQAVar7uRwud-NZHT_yZPjg3Wb0tHRwWKx6BcrbprA8anlQc-LtFgw0Dr2iSI4iOTGacGxabv9fmLirkmQixaspZjXyJgo3Dg4mKYcWo4Af_3Xf91MVfTi_KJU_bP_4d8eHCzdSh73DH50uFa1gOngsBunYcHhuafuvPbzt7o2SbZl21SxYSyPtxdFMrqmxG2fzIojP_vM7WXqmr4T0Zm7BWDL1WI_7Pfb7VTy80_ftrJxVKluyz50dPN4veh7dmINd-7cOOlD3A8N2O3jw9WqHXPebvalVEyh79tXn3v69PG5VDC1FNjNV4dd1zTrZT_u9zFQZB72u_ntSICrvmf0ZJ7YY0hf_fNvQrQUmNhiigpaitx___RiW2IIXdNMu2m9DNvzzbDdM0WbJAZMkcbNVbfouOFcR0AYr0ps2pDaxapLTIuuP7pxAkq1TIn5an8VIgMAp2ZmhewuLtv2us4ERB_df3BwcpSaVsS3mz0TM4b95YUhxKalOHuL6PLhw4AoWUSVU1yfHBIRYLBpNB1AMCXkhs4enJZhiswzk36x6CmwG7qqVemPF-998ODxdjNVn3tTkRjQIWDOeYbjmpqLjTmTkeTSNW3fdG2Mbdculh0RhiaYyjRkADKTNrXVijmUUoB5pnVLqS6qUkRrzZkRRaqIqkrgBtwRwbV2TWtFrVYQL1OuuYC71GKqbjNPDKZhAjJAHHaTFpymjExZMgWq1aSUmitRAEJgdDUEVJGZwJNiCGGWTFHkAERM2Hdd4ECAASAQmwoR_GIlDhxYTYnYYUbmI-AvhneOs6un5skdqvocpx-nAm5a60xWdTUHocg3Tta_8cVP_Wf_63_4yu3bY7F_9l_-dz_88c_Or7Zj9rIbkSAPQ4y4Ob8Yxu12HNUAiGsFqzq_AcFcpkKIwKSibkKBS62GgOyARteuHiUGB5cqDjZri4DIwQn4eoeKgEQGZqpADIimM4ybHMBdZ9A2Itm1lkGQEJkRmQIREoeAcJ3BBAQwL5dZxRQ9Nmzu4LTfFWD-k699ZzttT46Xh-s-Rl8fLlfrvlm2SphrBqYqpuaLg_VffeMHX_uL733iEy8vFsHRHCAuGg7RGFUhi2FKEGKMMXCMkdu-CSmYOXFo2qjFVIRjqKJKjoGapgFFJqYYchkjBxNlJnfhGAgcXbquk1LUvOuarksmFQGXh6vnnrvTd-3Vxf7Jo_On7xxmKWgC7oDX2plaBRDRMcQIRIhQq0xVHLyKjmNWdeYISKIWYwzMwzjNU1dTj4Hbpln0LTIi4nasYt4QLdo0NzdFdSy1mhe3Inq-3SvYbMoK4JHIVMnn8DCLqLsRk4ICGkfgxG3b5b00TXN5NVS07bitIkWqOjRtmkrValJsEfsy5sBUanbyUnK_XOyH2TPmjjjsx9j2TOTq01BMLcaw220XiyWHoGKaa_DAbTh_8oQRCYEi6Sik5mI-TXUswsRZ6jAVNxDzWqSa78apVi1S3a3WomI63wPcVLyYKdgoxVzNfRzLNGUAqCIKUM0BkYkuL7bEoYiGGEKIkYOa7cc9EimS-vwy92mcln2zSMEdN5cjc0MxitqTh2cYwrDbAUBkysNIHJgDMi7W6zkX6LM6yEC1mpqIMDWq4I6RAwJZrkRuLnOF0UTdPUQOkcE8pEDMCAjm7uAGzAyIrg5E13cfUwjBiYjRTJjIzWKK88JNpSARISPgjEoER6RwbUOZtd_mOIuFyVWyAaS2qaWk2AA4IlBgJp7Z4aY1xOjqgOgGQMhtnJ7cz6Vkz1jgg_c-nIark4OFu4ORAbepAyYglJJj02jJpu5A6-Pmz__sm-pYZLLiqV9898dvkOOi6xV8rFM1RYoh9W3gP_m3f9Ry9xu_9VuXQ37pkx__2je-99_-N__922_-_OHbH-13m6_-mz__yr_-81c--6XVYiG5SJVaJCAnoq5vEIFCRKIYw1xXMCKOUUUQZ46BabUZXZXHQiGpOTIBIQCoiGYxc0JnDhQC4MxIJa8yjcMLt29eXu2GMU-5OLmKdIseBANSBJpJ9CJihOBgVkNAqdncYmwicy1wfnaKzpIrmUgp034MgZhw0S29GjM7ABj0faulMkKTIrg2gd1dpMaYwM3VkbEJjYgyUZ2KVDVVsUqEVvHmjSM3tVLhmr2ONet-0D__7jtXoyzatgk0KyNSSm7CiFIrE7aRD1b9Qd-1gTpCdA-EhJgQuxDayF2kNpCLNk0UgV2WXCUyxhQooHudrKQIMC_3A-xzCcwxJFUbhlxFpyLbfclik1ZRFcNcVBXBuZpNVWpRRspTccEqjkyBw24_PTrbqUOMnNrIkZeHbQyJQ9wOEzjkUnelDLUaARKquJuBmZkDkoLhdQfOAAGcitSZ9KfzTWiGZZmaY54HEODqFjiYOyHPqR4xE_PrH7VDnTEDCnOQcH7V-YwYQvj3emJRazm5I0AchvqD195IKTRtKMPEiCo1hBACI3rTcskbbvDOMzdqUTO_eXT8_IvPmVYOjWF864MnFENIka08f7T88L3HNw4Pmja1DDGG0PLjh2frVXu1HYY8cUtdxxe1BLF7y9QzXHx0uor-_M0jNM0lv3__yWa7KS6bab8fdmnZMMPh0aKWSa0OeQZC2fFy8dMfvZ7HXehi38S2j0VzGfOwu_z6V39468UbXeJl6gihCXzz-FCn8Yuf-Nhb77wDqr_xq7_08PQxqTqFw2UP7qXa-cWwzyM2tBuG3TCs1l0Bc7OpyoMHT5Sh65rVojeFPJbA6ebxyTP37myvnrQGB_1y3E8_f-2tqah5gIAUyE1LlebgZK7LXe52U62pCZ_4-Iunjy7RPHZBEQ_6DpAWfbdYtqZ2eX7eNXx5eXl8sBrGMSUKzGXKDHZj3RysSbWuVm3TBkKITlenZ13XjtvBwShwSrFbdO6wHydHuLi4CsDHx0fLZc8B0bRpQ9twTFzr1DRdt1iVcU9spYzVahNbxyjq64NFt2ratnOEGEi89n2zPjpyxNQkcHPErm2l5iY4IYzTmGI8OFhO2900jusbBzYfA60cnNyYsgIBiOVxF0NE9xgDIrTLNWFCxgdvvE0cde7GALhBSo1WC5FVBR1iE52hVMvmovjjn7wxc-fMoagAeMQwlgJAczrO3JqW5hEriKLacr1suhaJDEnUq2hKicxcNdfahg5UoRpUsarjuEfEalZzpmubXgF0DmygpRYFICYGrHVyEwAo0-Q2s7vUTBF9mgY3w1nlwSSl7jb784tzjhSYtpe7qgpkgNfvQkAqWTg1HAgQxRwjEdH8fRIiMEopDgTmoqBIHNikICCHNDt6mQMoIBK4g7mrVxEKTMwwg1_MAkVT01pDBK35mhPlAOAEM6HeEKhr46c_8fL__h_-_p314c8_2v6f__P_x7d_-tPLqYpUnyYXlaGg0TgM3aLNUyl5jKkVLQYGEZmDFTFwCqGKmTmHoLVa1dnA5Yh2ParQWitxdHBmDBSk1NA0NWdHmGRHgQFgXoq56jzDCDw_8gCQOIS5JwXuREgUTJSQay4ck87sDkCkedLoWgVDJAaR7KBAoO7AVF1DCEixuv3Ft1-_2OW_9pu_dvPGyfGNo9S1B6v1crlaLFZuHptIHKep3r61Jqavf_Pbn_30Zz1PgUmqcWRCXKwXRNzEKEUy2HysmlNYIcYpFw-hX3WxiU0KsU2MDIbmvl6vAKAJIXLjiG3XgGrf9E0MaK5ZUgqL9UK9Nk3bNGm1WjNCoPDofNMsGiG_dfO479vNZhyr1KrgOlfQUgohspmDzagKz9UYYCY-UwhIME01lzpMZcg5cRDxq6thN-T9NAJ430RCImSperUbOMQmRa6w7NpVmyRLnup2OyriWOp-nJioic3cYlVVcCdiMzSAloOWakXQnRUXfceAd27ffO75p1arVS0i5ldX424s26zF3TgQp0Ekxnh6ecExTkUm96FUimHcZ0CvU55Z2yImdSCCxCi5TqXkcer7NuesCiE1BZ1ZLs_OxDU2_OHDs0Xf3HjqkL_0d_9xVSXkWo0Qx1pnyhKomWGpIiLqLqqzOdkA1JwRzdwMplIQycQUoJZq6MQBwMapAIEjqBkBqQOaiYHb_JvAAEVBHd2xFKlVAGcMCqiDqMUUhmEch5xrjomlVkeahoGZp6m4W0zJ3Mo0pKZBBFc1N2I01VksHZvoWtqmFRVHMrVAaGYqFtrOvaI7YZi_NER0MWK8zi8imCoAAgeRSjEAgBsQx9kxjODIjPOn0w1nKsq154vQjZCR2VXAzXy-TjAxEQCYE7O5EzGYIqGrcIgiGmIz2_58zjFyNFVgdFNqGssCWsCDEbXLBZBJsRsnT737zs-6ZskBAycFVREM0czQlUKKqfv8Z196_Sc_BzNzBafY8DDs_8avfNHJf_iTtxWolCJSwRwUU4zvvffujRu3XvzYS9_45lc_ePPtyDMciNzQoDLie_c_fP7jL45DKSXHhhbrlZihwzRV4FBqjTESoSNrLSEEQDYVBMLAKpWYncjdZj2wKWjVEANFEhGODLOe2SE0DcdktTBa24Xf-PIv_dGffvvsYjuWst_s0JhY5-nw_Dg3B1MIgVzEr_k5FGKcX6tqbi7ogEyqDshgplXbmAzQRNy15ArzxqBKjJHcyZFjcADiwAiRYzVhCjC_ZAAcHAmI2dRC4jYGd81VXOY9ExqCu6UQQsNd9HuHh_2yOd_uHYnQCVGRkKC6mjohdpFTCEwO6EV92caUQggoZk0gBefAAjrnzxARzGIzU9RIzRISIlVXJ3SiLobEYS6mq4OYgGOTmixq6nNhNyZS9Soi6mA-5kKI4uBAAGhuaoBNQICIiICo2qawDiyKArAfJyKax1mzpGJGr7mDuhIy_MKBPRsur_EXAOZWVQOxurnjTPee85eIdK32dNQZbIfo6nOuj0IU1XnBAgBEMNvu3GdHKhh404S5ODWJnF6crxfLJsSfv_vhX379ewf9KqQgaqC5SY2hnhwf7IYxtvHNn7wT2dyx6xuEcrzqbq4aJgLE19_44Oxi_NSXPvv4_oOXnrtDzOdn-xdefrpKZfAHD04P19Fq-diLd8-v9q512g2b7fbH7z85aPjqap9SfOf08cXl5pe_8Mr28jKP1SC3zFUNnZ5sLsT03s3DqDbspzZhG1PTRBFfxtVX_vyvPvepl9yV3H_0459cXuyYQkoYmH7vn_wHjx_tV306O73sG48cS9YXX3n2K3_ync9--mN3bh9_9Wvfunl848btG4p-ebUJbEuGtuvOLjfrRd8vO8-Sh7Fvekd6eHGxWLTTWKYxh7n61qSAwYnyJLdv3Hnzgw-oCY8enX_i4x-7c7w6e3BWc2liSE185_7Dkqe2a2MKs35Uc724vFwddMvFum-b890VBlx17SJFJooEN06OpJTdtD0-uVHztGxj14dpyCayy_nw8OByt6OGd_u8vnl4c7VcHi7aPj54cnn36Vu5TgwwTOPh0SGaOfh-v8WAl1eb9cHKzYqWYZpKtdh0VYVjIKZpKou2W62XtRZmCk0oQ3GEpuFcsrJJsUANgI_7kRgNdNxOt59_Pu93TLxYrUxK17aLRXNxcVGKdU1omnbcD_vdLvWLNrXD5jI1seTirkghl8xMUgREib1O29svfbyO0i66nCcO4KJVFGa9vRshDpc7B1wcHWKDjx-fv_z5TwYAMK3qTgxIm93-cLVUA6mKiEXcqzgAgROTVnEAUTNziMQhMLNWBcKx1F803VyqEMyvXCx5pJhUNcYktTapNbMqUk1VZL6rVBFmzjm3TaN5Ig4l53lGI7nEJgCwSW3aWEtlwjJNMaYUA4egVbSoO6pUhOsFXgg8D1OkSggBCTkQAExDcbMZCY0E6l6qIKrVig6mArNh1ZUozGxhJwJypKCihAxggEAhlFyYg1VzdA48c0g5xF_w-Lzt27YJn3jluf_sf_WPjpf9vpb_0z_9vz88u9gOstuMbYdlyIQuVTjguN-H2KDptBtUp26xGoc9Icxf6jzRZwQ3kFoAPcQE7ugQQrRaEJCQZ20iIWqtga67CiGlWrKrEyIAMrGbItJ1NMCJrusZ7IiArmIUkpkxB_frdMFsQXQkd3ci8GtgG8BMLmQAQgfJigk4EAEP2zFwGHf7X__sp7DKOw8fL9brq_2-irlL2y8ckSCAOkd-__6Hq-MDNa3jdPveU4_PziLH2ERUQwxOM5OXLXtoG7NKxKGJWiU2DSGmlEwkpVZU265jBFVvms5BA1BVDSkExqbrSymcQkwphdD0kYBmVsec314sFyp50abElNr49O2Tg75hxJODBYilJri6Xr8EkJkRXc2qmJo54FwTLFIBQUyHaWqaiMC5aEicRQJz2yQkyrlW05hiDJRFInlCVKT9NG6Hgm0sYhgZZ_iYGWGoLm6g7gAwlZK6trqpm5urm4EHwpOjxZ2Tg8VilYgihyzV3DfbHSKo436f59v-bjtW8WE_AXrJmotCACm1ljLuJzWrpR7dPGTE_X7vDlWNiEUqIAXiPJWp6nq5HKeRTfeTPXXrqNYi4l2MWmW63BMym7moIvpYSmAG4HGXVdUcRK2IVjNzVPNIoVQBwCmX3ZDFFRHNwZlEVd0C0HazFzUA2u_yOEz7zTSIlFqKqSEKuFTJpZ5vhyqyG_dTHYsUA1WxKrYbx23O1TXnnLqWAvaLlRl1q44Z9_uca0ltbFLK01jzRMC7zRaRgKhZLEMMTdMwBSKupZii1OqmWoVDJOTAoUnJbUJzdHRQADNxpEgx2pzhsRlGQEhEhByTq7vZdTmHaJ4JAXiILQLNkQYgn2tMgOSAqkKIgEQc5mrTXEcHR7U5gwiIyKEhACIGNwAQKQ40-8FUxKTGRVenwm1EdwNBcPGqZqUKEXz44bsZ9NkXPgZg5NHNQSGk5CYUI4K56ud-6Qvf-vZPigFwNMT-cIHoP_zhzwT9869-suGw6DsgREJCbrqWkCLz69_51sP33791ci-0DcemFuMmqFutQDFEsZ-__tNucXByfDe265KzVzdHCoho6_VBKRUBiSCEMB_0mLnUMl_bzFVrySUT0bz6QEAHqKUwhzqVefyLyAiIZClQm9LxatU14Xx7vi_FHRdtq7XO_84UYlWbmxbEtMSWMATiND_6VShyNeWAIab9mKsazPIYU3Df5gmYYkpNahy8TAXR1cW0AgIGMBNwKKXs86hujlhqoRiQyWeni0NMcdk3y9T0bVJRlbKfslplRgZqAyraPtdvv_bu2w8eH686NJnKdDWaIbtCE2MDIU9iVVU1MC0WzXrV3T1ZLpexaxgB2kAAXkvl4KsUE0EK5Grnm2l3Nbo5AwXiwCEEIgNX3-dSpaK6Kji6kWcRBR_GjMgz7gochqmKuTsWkbHmYrIvVYGnLIpQzRRR1aZatrUUt6ZLqnA1WTEHhxBiMdgO86MMZxxnoGDX6kcAhAABFeeo_swkkSroGJnF1BEV523bdVFHxeZg3i-AUTNkja7rXKJMAZGvSeBIAHQtEqbZQwjoiODz59zUCcEd_-oHP4hMMSYXdS1NEwnt-GhNYKRlc_a4W0CuuVmEQE613jxqGYARb91ZP3m0iYkfPX7w9M2Dk8Plw8fny6Pu9p31sm8u9_vjgwPi-OwzT5nRqm9SYHO-yvX1s0eFYJzKtkzjVG0p07hTyKtjzLlwiCL18aPHV6dXd2-tZbOXok3kg4ODEFC1ArmbAGXAdHm5Herwj_7hP2ya6OZHh-sG6eoxr5qDm7eO14kWbRcCNW3L3OXdRmopQ375pWe-9p0fHK_7POSnbtwash4fH7QxNjFl0f04QtUiXsEutvs81c3lmCimJjIHNFifLEObaqlPzs5PLy7HzbQ6XFd1zspZs5kFHtQ-_OjJRw_PgVM1mDlRGGisNTXp4mJ7tdl--PChqr_14UellohkUt-9PD-72rz88r02NpsnD2WatpvdatGslou-a24sl6tIJ8tlF1N_tBjG4eHjjxbJVz0fHTRPHj-JjPs8dClenD7KZVyvF4t2IVXXh8v33n0vRlg0adEvOXBA6Ls2tung6PDk5EC05nHiEAAdzChyLnl1dLBYLCLGXKfYMTMtluupSAgdMu1PT4k4pbhcL0htGIaqdnJ85LlePrlIbb_oV8uu256dtTdutMtlnqqrqGTRrEXmgRSmJI4qJNOmX3VuNmzHMtXEvFouy5CZkGPkvg8MKVLd7pqmy1X-5b_6d6WSuIsDBp6qGs7AK6iqpdQqZSyiJrlUUhj2peSqajGGFBpEMjBsOCTu2rYWMZ-FeqpqBAHVU9O5KJrFEJoYRcvc5HcVEVEVJ4yBtQgBmRqH5KYpRjRPGEAlD4OaliomsyWG2yZFDqUoADAzsJtL23XmFmIEJlHhht09xCSlgoGKmxsxAAAyiYqCI0IT2K7j1hpSE5uERECkKiEFDBGJCMnMMJCoOIX5EMaJASwkNnXi4KLMlMdsJsBECClyE-n_-L_7j48Pl7tB_y__-f_zwdnji_2gWB103GW3go6pTVIKB867bR32oLLbbLbn5xHZ1adxokjmqlLNLDAzkdcsZWAEcLXrlIQ6KF7PbZCIpBZEE6tz0JoREMFNpRaiMHNKwAw5zKgFMSVO7sgxgBtxNLOZv2noHKMBcUrqFlIEcphNje5m4mAuFR1iAt1krLkMY62CEbbDVryu-ja6j1eXiZgQmthE4KOjo37ddofr5z__ytnjLYfu6nx_fnl157mnA3hqENQxhTJlhoAYmhBTHx1krgekFAzQ1AAwErpYqRMgOJgSNG2qeQpMhNyE2ATulz2itX1DyETe9k2fUmRmsPWiT4FT5KPVqm1aQFyvVhE5j_LwyaaqiEiIZOoxJZrZcwiqoq5MFAIHJiJs2pQim8N2N4na5ZBFYD_mIrVU7bsWkVJkphlwBzOer2kImcJsJ6YwiuSqiIAE2_00lZpVJqnXezlzRzAnAjBRqcKBOQAzcaCmaUNoGGkYy1SrO2TRccpmpqZAnmutRSAgMzkABXb00DWl1CpmYMjQtjGl2DYtRu5Xi9iktk0nh6vIhFViSkUNqoO7ZFH1P__OWw_3U-DYtun4ZNUmWqwS5Vql6jDloq5uu2FSq4pQDPZjNgQkFDFVB_UhT6KaS1EAZJ414Oqecy2lqsIwVVWfchU3IjBXinNVNkxDNbMisp_ybhiJMQR2wN0o69SpWhWtoEoETuCA6DWPiLTbbALh_nI37PYHx6uUYko87Pem1i0Ww25YHx7ud3skDCnVUiXXNoQQo0nt172oaq0xkmlRVxGNqWXgQKSmVtTNKLBIcQJDVHBkAo5zggeACDGkBMAxNlKNaQ4LeZ2KuCg4cXADMwcOsxfAwc1BVGYcKDNrzm4KSIbg82fcVFWZmSjOP1VCdHMEZ2ImCiFYVVBDpJiSTMUczAMQg3nJpVQdd9OTs9Nnn30JAmafxNxNyB0Nyjgu1odlkH7Rf_f1n4w5iwo4bK92ITTjpG5-sl51bf-ZT75aRiWHef5tBtO-cte-_eZPVaXpF4baHR4CUkCIIWo1M2mIry4eTbJ94RMv7Mf94a2Dp156NnYLRShlaro2q6q7qLgjMSGRuatI4IhAIYQYgoqE0IB7TGEGAbk7Es_2MRfTXKBa16aDw-6XP_eFj87P96NkgVwFmbs27adqHJAoNlRrBgJk2NeJA4M7UABwKVDGTMjI6AixTZLNqwNY6hpHr9WmKTOhIZl76pOaRAy1iAlKUZH5ngtINJYRFeYOQGwaIuLA7aJ11SakrmlVrbiJuIlVs_0wNmYuPo26HbJx9-0fv1dy_tKnn9Msiz4Uc4poWSNi10RuqZgAgorFGJoYybAJfNS3q75ZtJEYpAiCpxjNzMCP1l2TQp2yiYpqUY2BDlZd4ACM28knVTOD4i1QF5txLNV0LFKrunsRFefqEEIIlBx4n-tusv2YMXCeJBcbR8lFS_YqNqkN2a4G2RatSgTk5rXqbARVFXUvUs1tdozNp_HqZuBqTtfrMmRmc71WBfOcPXD-xetxDvNUNVUX1bkSMO8EEHlWiREiuNE1ZRQJ-Rd_F0MICDgr5cS0SGmoAYXvvPbjGNvUROKkIteSveBV88nR8smDs4AU-rZU3e-3Jwddy7TbD4vDxR_9-Y9i19y8e3N3ubtx80Tc9rWkFGrO5rbo27t3jp5_5qZW7fv25GhxvFpSaPvj44_dvRESPNleVler--fWN1BhzDVBTCG2kXe7LRLnWrdXU2i61IVJJnRfdAs03-_2yH7z-AYREWNM4aUXn-dAUxnHccxS_-f_5r_vD3snWDShbVLfdUh-eXrxe3_3N7_5gx8yxt_-7d863-z3u1yV9-M-Oi2W69P9roqL-G4nnrrF4XJyF_dCNOzL6dnm8nJs23475vtvPXl8_1Eexmfv3SWkp27eKrsC-4m7xf2Hm5_dP33n4cWHD7cX-3Lnzt0333n_tdd-dna23Q9Vqz-5uLr_4ZPdbn_65LxHfu7OvbNHlxdPri42V8u-fbo_ePjR4zd--s5ytVitFoH98cNHV2ebo8P-7slxF8Jx1zx1s79ztDxouueeeSpgY2q3jw7u3jji5KNjqR4bvn3jRh3LuNuFyHOU_eln7o27kQ2Wq34ax0DUh5hSMocq6khFqoNkKe2iC5HWh6vTh2dHRwdN1zSpuTy7BPTFqmeOeRwZZXd5mgi2l5tchUOz2wxTVWM-uHkIho8_eNA0qV8eodP2yaPu6CbHhMDj5ZbEUOvmYqtITbdolwfcxDe__6PUNgB-8-nb4zCpWMAE1wMyMzMjnHY7xhhCE7g9-_Cjq-1uElDzmisAbK_2pVY1ZaL9NIEjEooaIOZam5YdIYaADujOiCbCjqCQiLsmIQIChJAoEpgDAuG8urZx3COTAeVSRCzEGANrUS1ayxxmwTp_yP0aGzrV0QHGccrjLkQuUqbdAAFFbZwmCiC5IGEeqwPWnN3BRQMGVVPxyA0ChBjn-zsiMhGA1VKYydQ4MqIRMsXgTATISCGkmmvqO3AMMSISEs3hW44stTBzbBIAGjjHRIjuDoQOwJEMgBOnPlSZPvepV1epZYp_-M3v_uSdd_ZDyfsybMZaCpigWRknTOhALoJmTMhMkaOJEALO8AG3EIKDqVqdCiISR8lqtUZOog7IWoupgrmUCsA-V1ORTKXUkZDAwIogQmA2natPrubmSiHOB3lXIQ7gKGbMbIAOc02Dq9QQorkCEjogEoUASPOGAUxrKTplUGq7ZFkieSTZXu22F8MPf_Kus__NL38RtHYN51KQASIt-q7v2vVB7xVD6LabbbPoumX_l__u3_3-3_8HZRjSIiBC04WmCYAATDYfggVCiFCBI3MKPksT2qbpFm3b1SqrxQE4tYsOgDhgkyg66VBDCGD-4jP3IkVyurraNX3bNHHK--Wqb1M6vzxbL7qIpOYpBSAsUhZNWxQoBnVQMA4zjFxFBImQAAFSCCkEJtpsh1rrTJHuUjLXEGnK88Rfb9w4qFXBMZdStBI5iKTAtYg7llKIuUlhHEZAKkUdsKiOYz272Ik5MplqzrJa9UUhT9lUIxMqmOtquWaMw1hKnjKUR2ePxylPuTrSbqr7qU6lmuF2P7VtJyZN12x2oyHO2t9SKwVS93Ga2hQCs5k1XbNYdMT45OJymspUhBRiYCac9mO_7FeHJ88-c_hnX_sBxahiAMApDvuJkEgBHHA_TKI2g7SHqYy5VFOpWmbqvykzqbkp5Frlep0BCGiqDlBFmUnBHa1UQUTCFKnJk05lKibGOIwFZ7FESFKhFgBFLfro8nK7Hba7XRGZShmHPOwnAyq51lo5IAekmXEFGABVbblatSloKe2qL7W2i84qlKnMu879MOQxH9y8udvtYxO71aqOMg-aHb3WCRzUIYQAjMgRAwcidDQxIEKO4GDmInXO6qg7BVKtaFZLptggYEjBrCJRSMkciZkZ1czcKURkBDMCNIfZhUtIWosjckjzeNvNZ1YpBzazECOIuarPrHpzZgKCtm9U1c0CMxAQkgECzflUf-mVX37ttR9_-gtfNpHZgXLNQxEhopjCU8_d3W8zgJlWK7XmMpW6XHZXm6EJ7Gxv_vQnXaJpN87QJ5VaVcdhCBwfvv_OycmNELtSsrmDK7pILaauCLEJ4vjad1__nb_3984eP7n_9gdFJGCYtdvg4IgGrlrnWichmJpWmf-faZ4IXPII7oSIQG5epABC6lqTCqAq0kZy93_yn_yDX_vU8__v_89XmIBB5wsUMi3jogy1agan2LdaVdUKVDVFIqkFCIDMYdZQGSMGx8BooqZWirork7prlcIEq9XKTDl1WhXNaynX4c0sahYhaFUP7m45i4kwIgEOu30IIUutouNUpl0puZjpNEzbYbwYy2Ysm920HcrpbrhS_6__4Luq4e_85iug3pDXWhTMmWJiNkIKql5Uwd3c4BdlfUaMbVgvV5hIDNvIbduGgI4OwA6ESE3TzBwEMwgce4iGuq-5SMm5lqJg1qbW1EWqVBmHCYhylanakEXBANCdFHWSOo4lV90NeapzfR6mrLnILufL_W6c8n4a97nUaiZGgZp0bc8AvObxq7uZmpmYAAIiMgY3J6RZqA0EajZ7jtRMVE3V1GaQFCIAzcYIuB5JXttzTKvonAJymG_gju5g4I7zAx9xjgWCw1ziPD8935zuAwcBK-Ow7ts2RXO79czdq4t90WpuqtL1jaH2Kdy6cfzk_Cq2Kbg9fHSRVVX1sE-B8fGTS2a8c-9GnvLD09Np2iaUHuHhw62VcnGxOd9cXl5cjfv9J5-_DWN-fn2EzLudHhyti0wHy0Qx1lxKVY6dlmKi62WzHTdfe_jjNjXIfLjsI8XVYhEW_NzTt59cna-X63GaiH2-VZXqu2l486fvPvepe--88X7g1DQHjBQJ81hf_eSnPnr4Ub-gk-OjWvG__hd_tOx7JgaiaRz3l7u-W11cbZ88vviL13721qPL7_34p-cPH9bLPO0LKkdK7z14QhAvnpw2XgF9bsd2q3UDMSLeP3_0_v7sow8-ePTR2Q9_-rPXfvb2D197bcgyjONHDx8-eHx2cbUZt_nW3cO8rxfnm2-99e4e9WjdXu12u1LOx0ljPDk-VsNxzEdHh7Fp-pPFOw8var1elz--2Gwvtwqyz9uHjx48uNq99tqHg-LNOzeO-_Uvv3LvuE_vv_sgi64OjhBZRedO_-5yc-fOXTONkW7eORL1UqY-pcShj6nmvFosapa-a1SqVkPz9cF62A6LfpFiAJcQiJvYNIxgxA0jOZCrISMkbrpA4OYACCFiHYfL87Mi49HJcd3tmFK3XJkKB9I8NKs-NIxWHeYwLPo4NoctUiwiorYd9t4BMtQhC7gzxb6FGfCbpV-uVOWr3_iWAjngsB-l1iaFYZ_BUQyIYxUrVefA29wZm4HujESEQNiEJLmaeqm5iP77PZsJqigAgSiYuWrisDy80faLGBtGNAVTIAQiJAQkBPQYY-wbdTMCiFRL9pmMPMmMQ0lNN22mxCxDmbaDqrmKqg67_ZinUorNgV8Hd8h1frTMWH9TtSoy6zvMlJlNRdWxiRUgNp3PFAeT2HYqpnOu19QRY9MQIQDFtnVDdUBmEVMXJFBVdzJzKYVjo1ICMCn__b__O8vugBv7V__TV7Z5dk8amsWIZRxVfX811dHMrYyTjNUrtv0huZO7VkV3NxunAji3sgUYHd0BArtIznXAud1M82sRiFlq8RmcrpWQ3MDMiJwQGEmqEEe7zpe6Sp1ni7PYJMQW8frX6AAcOAQiJEfJlYmliM8nHGAz45DAQUSJ2Wdx2ExYVkfiqn7n2acePXpiRQ-X_e2T1adefv7W0QGoiuRpHI4OV-blaNnGtnNuqvFmO9y6d--_-__-i7_-v_jd_flm0aYQQpkqBz5aLQmBCBwsBQT0EKKpgXkRoRgQhImY2ECarhnGMaSYpaau40DANM-ATi-vQhO4pX65ANeDw6N-sTw8XlGgWmrXNCKyXHX3bh6XUva7YSy1FqMUHUClglkpVUQVvFZRub491VynPK0W_cF6wYFr1eWqb7oE4KlN05SZOe-nhjhPY62y7vuu603qimjddeIoAH0XYogxcGjZEIpozqZI4na1GwChCY05lLHkkkMIU6mlln7RdakJ7OM0DkPejlMbUmq6XCo6xtQCci31YntVTSiGoUzmJCCHRwfbzX6zGwGQI68PDhbLHhUocJ4GBFr1HROS-X7YZa2GlvOEYMu-1yJNE8-utqOQqjXdkohNDAC6Rcuf_u3_WEQBaX6t2hz0V_O56gjujnmqM0FPzWW-CUj16z_hojjPIarI3D4G9DaFUjI1DED77YQRTU3M5kVDrlOMwR1yyVVqFQmRVBUJiGCYphRDyZUjIWHe5WEcYmQiVJFas1TZXm05BHcNIapobKJVBbRhvxfVFBMgMFGzbIfNlpyQMaXoRDYjV2Y5mBsRmdgcnuMQVSQQq1QkZHdVAwo0U6bNaLbYyhz8NkAyQEJGQgAFNSQmnqEEBO4htWo2S1iugaIc3CyEOJcVkQkBEXEONZqKgxHiXBh2d2QqU059B2o0hxkMDQCJiQK4osDt556mIu-89dOXPvn5x_ffwhgBCd3aRGp1yPaZz37me9_4PjugWs2l1uoIB-vFX_vlLxwdHHz3jddPH1_kIo42J2NAFQJpEUZyp3Eam6YvZSSvBPNkwQkjM6uTm7Zd89YbP_m9f_BPfvrjHx2sV0VqSCkyO4BIRcIUoomEEK6TGW6IDiLzd8khwDzzigREXmvX9e6mIMzIKbjWp27fysPwpc-_8vTtO9_7wRuHRwdXu50YmHlo2UQd0NQZEcEcoUhlCsxsMKeiKscGwFPTSC7cBHEJMRBzYjYRIgIHImo4IICaI3hqgptBCCFxLSVGBoSEBATTWGJKbuJ1Hj8jI9Uq12trEZ2HNuqxSZMUNwA3TmF2whW3EOPDB5dPP33ncMEfProCBGcEADRAAA6s4FWUgEpVQkQCFZGquWpKKVHD6MV83I3VbLbJiME0VQQKKagoIEbVEKPIXNgBipiruDOgEhMYllwJUN0RSVXAAJ0RQA3V8foOTAzoamBmgJhSNNUpT_NClRnr_AmiayxdiOwA5AgOzOTu8z2GZt3x9Vr6Wk4MQOLORHOncB6JBQxqhoRmBo7o5OYGFojBkYhEFBEIAyIwEzMxESLhL2oEkSkEThzmvNYwlPunT566c_dPv_mdH__ojRsnNziFkseUIiEcLNZf_KUXNmP-4Ocf7vf7GEOMiRPfOj46WHdT0Tt3bv3x114j5HbRHnTtS_dOEPFsO2itn_z4Mz3x-W44aNKiaa42gwDcPFm8_-HjcTOuFi026QbFN996-PRzz268PHn_9Jc__cqNwy61JFU1FzDk2Ivr9-6_-yufelmq3Q7rhsLR4QEaOBICrvr-5-8_LFKfuXP38ZPHLTdf_dpf1SzupIhNaH_7__D3z9_4qE3x4GDtgu5CFBZ99z__q3_98nP37t25-41v_2hThy--dG8a6vmHDw-hJqbd5VUfko7SmX703kdTLpdnlyFGCmmzGY6PF48udlWzgt0_fXI1hc2kT853-914slp_-OH7QWG7m5KV7cWVSnZTYwaH3X4_1fqD778FYOvjVUI7vHNbcxn2IxYvUq82V-CEholguW5X68U07Mftfn1zJZMdda1IOV4eEGHTRGBuUvPsCy92XbApx5bH7cRObPLOR2ef_sSzk9jVxRUxEuP64HB7dTXtx8Pjo3E_tMu2jnnMtZSJkB28a1JKadm1282wXi6rCBj068V2s69SiXnZLgBoqjlPmSnUmsuUgVhrzWPJUrR4d7DgmPab8fDmiYlWVSVzAzVjZkphe35x-6mnh_0VQHUxdwRCcESmEJOUXIbx5NZJ6lbBbLnqzp9cxZhKnVLfTWN1NCs6DVt3axYHDMQB7r_59qc_9xkOgGaGuB8HV6SQVGw-3SA4IcsvSH0OAOYRPRcVN6jKzLWKmhpAraVtWjV1NCAvJQOxmaS-qcWsymq9nFENUgoiaxUvBkw6A-4M3eesDgMRmElVRwpNVNUQI1FYrPrUNjP02Q2a2IzjCKqzKNCqcGAwR_BcCjNWFWa2WYyL4GCoMBfr3FGKzCUfcDcxdecU81hiE4FRcp2bXTFGFcUZm4GQQjQTQARVRALEGQvAMRYpiRKQHx20_9v_5d9rOH73-z_40299d8yg7nNyuAwZ1F0dmUArIJZxTDGYeckjzpL4oo7oqogYIlutqgYArta0jakSEQLPrScEmCGeTOwiFBh8lorOIWEAB7wOOgIiMoCJEhM6AV1nWhCDgxOBA3CY4xLkVhGZGYmDmYYQ1OZ8Ac_C4Nh1c4w-hWTVHJFCIA4QoVv0L730_Mky3b1zctgthqm89d67JzduXO222-0eQAOBiN577u77b9-Pi9aqgzuFeOPk8OHj-y-98uqDBw-61McUzKDmmrq-qrorAtVqq_W6lrpY9yWXEKOKEeO1L5QwNYGQzQ0cYpuGMa_WXeBYpszMi65r26aWvF70t2_evLg8Ozo5TIQX26tn796Zpvzqyy88fnL63L0bNw4WjNi1ydUCodvs8kJGiDGWcZpDVyHwkGsVQyJAzDkj4apvh7G4yKJrF4uOmazKyckqhpBzVa0Hi37RJnQsjlf7aVQTo3GqBpiLTJM4-FQ1NcnNu5TaGETVQZaLdpbqLpb9_J4ad9kAKPEw1amMuWquijGYKjhxCo8vL_umm8VJxDzba1PTiKqU6mAxMTjFJozTUEpFMHfr25aQCQnBXdUd874AAxMSoYhVhyIyDNtnbt2SnIf9CGL8-d_7T-CahKUxBkSsVWKkWub6j4GDuRGiI4h7CAymCNeuCSRSm32cGmIKoVFTMw8cgKlINf__1x9ULabEgRZtM46TqCHgsJuIQIpE5jzl-eJMRCUXE0HE3WZw9zn0L2rE6IYhtQ5Wq0ut7XKx22y7rpFSUpNiSvPTcL_dLxeHVSYTNZHQBDVHN_oFFwsBQAzAENzFDcFnHIn7NVaXyd0pMDuoCAA4BnBFRkQ2V-YwKxKRENwQQaumtkdAtwrgyGFGkhk4xzAfkWhGlCEi4nwCRgRXadvWxMyUiTGwk8_FYmJyLaLqBgZ27TIER7cy1Y9_5hMX55fT1eXD-x98_st_7cH7PyMPgBo5FJfbd-51y-X9d99MgOCCbhg4NWG16k6fnP36L3_hv_2X_xMiXY5TrWrIwz7HNtL8TFdJXSxTDm1yMykZmc1MTBkJmChEYgIz4mBNvHr8uF12i9iCg6kEDjSPIsAJg0qhwDEmU531XrGJAIYcOAQkBkOtQiEiEEdQkZRiYExp8cwzN1_76cOzi9O__Tu_uXn4-O337k-CuVQHwogowobAOIfzzIA5MZKrp76Z0a5myhwk5-VyNY0jEAxTxoAU4zRMXbcwVFcHJHVniqqKjoHI1HOuHHmaSkiNA8L8AwdgA2JygEikogwhawWgXEqTuqlMgCDu4ESGDpjFkBlcapGpTID49oPTX3rhhRs9n-5HU6qiqY159om4IbEjqalVvb7JmDpSlToHqyrofIUEgKlUBCLCmktgRA5uXszcAIkNgJnzVJlYTcxc1NydkYpUYp7z8uBgYKLm5I6G7oG5ZEFEIkbmWkoTk4MPkvvU-jXmKwBgCKRqgI5MDOjuYC4yT6jQHMAthjBfv-c7kzmYGiDNoCx0n0sfOlMb5uYMkl7v3NnUEEhVQwhM18y_GJiu7w_ABAiemoTmkZgY1Tw16eHZhSEs--X_7Z__82BhcbBAIJe67LsQwr2bx4uQNhdbrXm_nxpOCHh4fLBcLU4WPROo6_3Hl-e74eTW4d3jZWTclHK5nZoUn75zbFbfeXL_mZPDLrZX201BW0R-vNs0XRTx4pD3-zffPb11fHS1GzaXw5e_9FL2Xd2rEu62l1pVU1OkPry6_KXPfHzY724dHXSxj-SB5jMlCPpH-6uHT85fff7ubnMF6pfD1fmjK1Fvupadf_03fqM8Gvb59Pbde4zeNi2gIePJnf7Hbz986amXDrr162--pbu8vrH40RvvRm6advn49HKqMIhOFc63AzGcTnZw42TKsh1HSOHian-x2U-7nXkshqu43tepThMFurq6coL92dluN2CFH73-l7dvvoSYLs_PS3G0sFylvMtQ6pPz84cfnT58ct41_ODBw83lPsaw7Pur7dYNTs_P33rvgTudXV1uryYjcva7d2-eX-5WXazqjy_O9opf_fYPdYJpP5HDy0898_DhkzzUhw-uTi9HFd1cXrUhnJ1ecIr9ojt9dLpcdYuuz8PezD56dKoCxweHooaGDibVplrbGBFxn8cZKJfHsaqNeVz1C0babDa1TEc3b12cnbsKgUuR2EQ3OHnm7rjZcORxv6cUuFtqrcNujKkZhx0gNynUMqWm312cI3iIjUNyLdwELUqMWqbL8_O7z79ac1GpKEIM6mbijsiR0Hl3doqR0-rQXdtF2j15tLu6evFjHzM1NTh9ctEsWjNUF3MvWQBxKkUR1GF2COapVLXYkhSXKm4KxNcJGoBaKwQywvXBCqpXKQZmboFC5HC12aoYRapiCDCfTedmKRESopmCgZk6qAMRzYQLhxhS06j63aduuAGn-Itwf527P1KEU4sApvOEcd5nk5mltgG32f6JwGoWkBFJXYkDEqKhinKMyCS1Nk0iBK1CyNfDAgQARyJVQYLribs5wnyiRgV3FeRAhIG8lPz7_-i3f-2Tr07D-M_-y3_-eDNQXI_bHboEAhArUwE3Uw8pSlUAc1GvBcFVlZgDkquAqamCGhACIIKBm9RKHFxrYNKqc1JnPn0wArq7KrrNN5P5yjLTFH1OdBECMs7POYeYGlOdx0NujswmAoAxRJj3JgYU2M2JSUQcPISmSp4vDUhOzIiICHOS3cxVLLSxX3SLJnzsxadu9ks0XS6b-_efbPZbNTQwLaLTVLb5V__Wr73x47djy6qGkRAwdt2jdz964ZWXHn1w31mX_UpEmq5JXTvVGuYTfkSAuROCIYRSS4oNBsLAgWMIseZKMQamEEJsopr1i34ccoxzpsuGcbdYLCPhWMaXXvjY22-9devW7WGzWS_7w0V_tbk6XPVtmw4Wbd81gQlcYwxgwIEdcB40UeAmBQMo1cRMwcSMA1fRQKgiphpD5DAL5ChEbgIicAi-bJsYAgDuprIZ63aoY7bLq4ECiag6TaMAEQApGCJ2KRKhqzhgbOLlJndda-61ShHJUzGch4yAgMNQynxHdQBCBETA5WKhKnkstda272stCD5NhZmriAFgCsy8vbiQUrfbzdHR0X6cqighEodhGIiZHcZpoogYg7gFCosuvP7z97_86ReaFH3u1YnprCpw82ks1wk_0VwEAER93rBVtSkXE6tVxWC29mSRKjI3XAxmyr6Az941MLOSVcWYOISATO5gaggg7qWYmapZaGgm5Y85A1GpFcwUdJpdi6DNInbLdrcfRX3cDNNYU9cDeJlKTMnMp2Ews6vNNqSEgKbGTO1isTpY7rYXTUyr4xuhTbWaG66PbtZaKTAiEjAgqoKacQquSkRAzkxEDK6MzMzggMzzUS8wM0diVlVwZJz3rWo6U06MArnbrPsTceTIMc2pfy2CFJgZI5nOF1SnmKpWNweimjMH5BhndrsrADrTzGV3cKQZfQzo5pEoECFAcxB1ygbeBfzh17_2q7_7u0M5B3IpgkgvvfrJ3dkFM2kpKgJIxLg-WniV7_3oZ6eX28---mJV7do2dl1qWo5UpgmkzrOSWhUxDNtdWvRKbqAhxi421wAXU2SuCiry3huvPf3is-_-7K3T88dlGqbdnh0CQdOkWoqBOrjmShQoBAB0A6sCAjVXB3Q3ZOSAbiZYKVAd_c5Td8_PC5A-vtyETn_4k5__wR_8m7_3H_4tCdYFbJuIaF4NiSmgiV2Xb8BmbzoE11ICU0oRgcyruuY8cYyBuUkBwfO4XyyX47AvU0UmkaqqCDUQzJtuN48xEOJy1WvJCCAqpiJaHcHE3VDFYmgc3czVdKr1artBQHEQ0ZKLoglaqSXnaZqkirvTREYxfOsnbx8cLg9WDbsh8VSkApQ6G8hwLBU5GGKtUqqoAwJKFRMXra6mpkSIaIgmWp0cYtgWGbIO1fZSs2jOYySqRRxxqpUCFjcRVTFAh8BZdcw1VwV2BR9zrZNqdiMaazXQXGU_jOpeHUS0irEFJFJ1MzDVkiVPxcFLsTyJiTGzIYQ4eyxmXwbPSxKYTXuAcyLIwRzNEMxB590jOLDPWTZ1AwZAUFUgNFBEvBaNAjKTXQMBOTAyMTEBGBGESAAIiO5-eXV1c33y_v3702ZipxTDVHIFg8Bmcu-5Ow8fnJbt_tGDq7ZfintK4cbBYhX4dLOpIb378LKoLZb980_fJMDULfa5qsndOzdiSqlJt_vlqu9Sgs043jpcbXc5AK9Wi0l0s9n94P37x0dLCr45v9xuxlVDZOlgvbRaj1erfr06OV43oTHFgxvHm2Ga70HutVQ7u7jcDvvLq_2rt2_rIPucE3XY8K__5pdFLI-jqpztNv_s__pfdPfWpRKbgzuBlZ3uLravvvJLf_zvvvGXX_ur28_e3Ofpxz-_f-vpG83JorbLMzVvV9uip5vhwwfn1C6upvJ43Fxspospn9y6efpoe3W53273u6qnp5eX57uHp4_LMG0uTs-ePLGpmCoumqZfPDw_e-mpL5WiiEmNV4dHxeo02Asfe6FaMU8Xm4GJrq42QLw7v9xtx7fe_2CX7cH55myzhza-9-jx1b48Pr-6PNu9_8HZD15_7_3H51997Wevv_H-OPk4luNF_-bPfr4f8tU4fnB2mk2w7Z5-7jZ5nYZd2wcMmJrm4ePzk8WKOGwur4bdJKIth-BQp-ndt9_NU77cbLfD1C4XjJ6nkdAJcBoGNYMYJishpu12C8xtt9Aq--2m7SIxisHqxo3YpDLszj96wIGlZgK0Cio5tV1adkWnbrEgCvvtKNXSslscHlTVcXO5OFppzZJHJFiu1qlrx_PzQBLIVXR5cjCO26DetW3btAEwEBGzo9c8mck0CLeL13_8-na_EScCb5sm7yuaq4KYYSQRMTOpVUTMFd1mGvq0FyInghBDSKxuPHuIGN3hueefffbFlz73xS987pOf-vyrn1hQq6UM466USfUXAVcA5AAIzPPmHOqkkUIIBOBm5ghM2KQAAGSQYlj2feSm7boYQ4yBAlWp7gYzt97BEIrrXOJnDhyb1KQ56mMiDhBSBEQKlKeMwFqFOABBu1gAIyCmEBnJxB0IGWdqviPOJl3VGXFGM3qamGopiMAAMUZXn28gkcNvfPFXpBSVcn65Hyfb513RKkVkqkjOER0cTGTKHIKbITMxOKg5OtgcWGFCRgOTxIyA5o6RMbC7qXqthjifFGSeiIoaAAS-VvPODAxVBWKfLcA-P-TAKZhZSE0pJcZoOkPSrq8JZo4U3Dw00d0ISVWJG-bo7gbKFEwFEMowOZK5IbM7mLjU6o6lipl2bXewWt-4fQhqKcSXXrzXEd46ODjqV_2iWXdtw0GH_dPP3DKzAIjqVarkcvflZ772F3_5O7__e8N2nHRYHq6nXFX1-OgoxEQxBAxllIQxeGQObdNBLqyOVREQUftFJyJd25qZinZNU8bp4HAdm5Sa0HZt06auiX3fBwgfvP_O0888dfr44Wc---mLs7NS1V36tgmOTHHYjMOY1cxN9ReWtPlMi47qAOZuwpFSitOQp3FaLnoEYmZCWq3ahmm17AOTlIKIXYjLtuuaNnDYiz_eThf7PBlkM468G8Y8SckFI8VATC5ZtpstMu73ozsgEVFo28SRNtshFx3G6gCuPu7KbjeJE8SQxaapTlXbthMFxjDV6kiUQhXZ7_eB2A2tiGtdLZfTkBFg2G1FpZaRmB89esIca86RKUQ29KmMlEJKrC5jyUCGwU9OjnrQoSgFrmIGyJ_87X9kCK5K4KWqI5tpqVKqzD4FZqpVzAzRiaPOp2RwABhzAUSF-fo-s20UCAAwMBqaGyCg2Uzpw8gBCUPAtgkUKMYwljzss7vVquIwTXnVddOQS85MKNWG_QCIeSqb3a5tY0ihVlEVkSLTZKbtonN0RJBSV-vjqWQtOQUqRatUFwmp2V5eIhIDIviw29y4e3PYDEgoIhiZiJBQRN0YyQlR1VOzqnVkRkdQmWWq8_8kY0aYVx7uDjpTQDkxmOu8Z2SudR6WX9NnOSUwdfMQo4o6Aocopcydf5xri24z_8tghv0SEs2S1PkiK2I2l2WAiBDQmQggfOqzH3_rRz8Zp6GqxEhvfP_1X_ut3xk2T2qtu8vhM7_yhT_5xtcYqhuJFnAQcxGtUxWtH3_5pU988uN__Jdfi03jRpOqq-mYmclnGqOoo3sVAGi6rg7ZVQMGVJtVa-poXomo7vOLn_7i_vwBEILNyX9FjkjIIUqpjCRSkYmIpVbm-fsDQgIiF6DEprOoLzGzmO025ybVXYZSS82cwoOHV6lPv_dbf-ObX_8RI1IMItXBMSChQ62ETgHRXUUaTlXqbEn0WQktEjiUkkMMgRh0pqVFZGAgd-UUVCWGiA4q1RkpMBKh-2z0QKaG0zQJImapoUlqAoTmjoxtjNM4IrMDqFlKiyIlBjbXtkuqQBjGUmPkqoAB1SFyvHlj_cLNo7fe_KBfthRZqhcTcwCCEEKKNOWS5_odEzM2Mc287KODtbnfOl7maqwubtfJGZ_FFHVG7rt7GxMAjmOOYW6eKDo4euBwzWBinKVjs6eXiIggXM_yEcPshXSmX1jQEMAhMoYYRETA5uM20PXrUMxs5gWrEaIhursjOcHsrAFHc3MwQnKFmfBDTu5z1AgRefbXExEg2IxGo-uwYozsDghGxEi_kHKjEc4kc4gpXH9ikX_4xk_u3r33L_7wKxePz9fdKq36ItK06XC1iEivfuK5r37t-4tb6_P9XrXWUler7tWXn37rrQ_2k9y5dfz-w3Ot-olPP3O36y5Pt8tF9-GT06tN_tJnnt9d7sT84uL86Xu3TOG1Dx7eu33j9OwyLVtFuv_wYr1eeHFIYVB5-MGF-Pj7v_Xp9x88fu723amKa3n7gyerg-UkdnV59cXPvPLGT9994emnOPC434IjJbza7eKq21f7l3_5p5--9zSVbAF6Pvr6X_7VPhdGtjq5pb_5-3_jL77xrccPt6vEP3nrve_96I3bt26Noyx5-u633vrEpz6WBd586z0v8s0_ffvxw9Nv_Pix7rYffnA15AxmV6Os1s1X_tU7v_Zrz_zT_-qPbz19fPfOwftvPDi72O7OL6atNH0b21TqBEPt1l3kUJ3abkHUEsd-2R8cr08O2na52l7uV6teRfb7fZNSLqLVhmFcLA6aJrbUiuFmP1iFYbPv2v7iybZM0nF8crFzs-VyeXZ-No6l71bb_X4c5XxzeXCwfvj49MH794dh_-TsyVDqw9PzJ2dnqvqxj9_bnm-r1FI1j-Vss-liIMZEIXHYl2yOV1cbh1lzW7jtLs4vmGnZtdVq3y3HaUoxMeJ-N5hpKXmxWJVp4hDOnzxeHd6oeSr73B2sri4uHPDg6GZqGlObpt3B0dGwn5yMYzDVlJo61RgZbAIDTs20uXAR1zE1q1JySsGkhiZOV5c3n7oXm4VKLWrDMBJAig0imhVOMddS80hNy6Fz1ybxcLnb7XYvvfKKlDJNZRz23aIrAtXNzE1ETVy95oqE9IuHoprO-UYg0mJzPaeKpEjdcvncnWfHXKc8gUmzarp-1awWZS_r9SIgp7Y1V1fjyOCgohzCDFhE0BQjYRJRcwfA2EStwiH1q-XR8UHbtKAw9_bLOCHh3NCYUV1EWEsFN2YGx1qKm5dcUzOjLXmWCLo7BMrTlJpkqswMRAZWcmUO4K7gpVYKqLUioOrcwrP5oYFmRKiq1zy6-aAdZp4mIPJimf7hf_Q7cLX9N__mK-89vjy9msSqZ7EsHAIxS61SBNnRMfStlCw5B44zhtRm2hWCq7orIZlKip2bqRghEQEYmhmH4CbI7GLI6GYcgqmiz4gEdLAQEvh1lIuITZ1jEK2uQhTmfzVVBUBODRKZKSIwBzdwADMLHAwMcebB2gxfsmt4qBNHNwvEjuhkhFilGuKtWzf6Rfrsy0_fWi0iJ1M5PjlGcyVJlJrYfOmv_8rnP_7MH_yrP25Sc3U1jMMQiJHCXOw8OFp97zs__tu_83fefO0NYo8hdN1yGkYObFXaEBARCWKIMbKWEpvW0CgGJiYMDIiOTYymmmKKM9wtMTIQEDN1qWXEadoFiuIVVJ997rn777978-SgiSzTdOtkdfP4QEthghSCVmECBIyJARHViRF9Xtf7PgsChMCm4O6uFgMRkSuEgH0TmZjMzrJ0TQQAplikiurFWPdFqoJFVpWxWK4VkYr5fCb1alWEEdd9G9qo5oo4lTqOxQOqW6l1qjWEQCGIqQKMkgGpFqm1-jVuSAOSmAZmFRMpJpZSs9_vxNSsMkcVcZGz03NVdcPFeuVmu-0VUwCzEJIZjOPYpsbU267d7ob1etk14WDRrtvupEvrRZfHfHp5yZ_7u__YAbumHYaBI01T5sB5qggkKodtM2RxmPmKqFUccIZv-HWpE-ZZOBKbAyCJCSA6Ui0KsxNEBHiGsUIpmSO7IyOJGjs4GTIxc8mViUy0VjHVJoTLi30IgIxaMjuCuoOM-6FfLGrJSB5CiCntdrtl34cY8rgXNWasou7WtsnUmBwRUgilZAYE12nKIQVzncE74K7uEJgJ29CozZtKRXCtEmI0s_ljprWAGRCbKSCEQKDGIdaqHIK7IwG4U4xShZgQjBDNPDKrGiI0MRqAmjEggIEYMfscoblOYqAhXBeewWNKtRQixMDkfg22Mp8xzsRQ9_XVV599_fs_BYbqjg6LPj386D2C_lO_-asP33rri1_-4ne_9l0OAc2YQ6AZ7Q1SPDZ8dnr267_563_wh38cmSfzqZSSy2yORSSpElO0IiHFMpXUtUxoKgTA8frLdp4BjYAEpw_efelTn3v_5z9PHEWLqTozBCLC-aEcYjDxbrnK40hEboYc1UHNUxOBoE4TOIDCLAK8fPykWy5KrlmUKR0fnkxavv_9n_zKFz79uVc_9sOfviGC1cVF1AyczMUKMiIqiJmaIkAIWEp1h18AqdDAtUjbNDO5mZhmjawbiAgF1loZ0RFNLDCrWWR2MCYWsxBYwYG8gsTrRarOxIF5JCOKgC7VVQXRIwcCdnXC6IgCm5Yio3OMhAxMj09Pf_lTL3zplWcvLzelyFhVzRgpYAR2qZbFHMzBU-QYg1Zp29g2jVltQ9Bqy0RtigBYxAE8Z40RXdwBxSSmdswjuTuhVgUCBgI0IzRVAzBXDsFsdhY4ugHabK5x0ZnQb46IZKJM7AqROTWMhGpeVK87ADGWWs2hlhoCESIgGICI-ayBQ5jf_QgkUsFRzYjI3R2dCOfzAQDMy18HB3QiNAd0TyGI6TU01i0wcQiAMN_iEQDcIlNgYsSmie5IkZ5cXe220-HB8X_x__rnnbcHNw4RcdKSQogBbhwd3759-PVvvt63zZPHV1YrRzq8ebw4Wr7x1oN7z93Ag3D16GK9XPzuX__l_eWmb6OTPzjfcgiffvF25LDZbRrzw6MjqfLGe2fP3Tv-6OHlye0bAHhxMSz65snpVXOwON_ux6urMkx__cufe3h63jehlhIjnW6nmzeOv_vDN1XL8y_c_eidj-7dOkqEfWya1MTYuuHFZlcL_I__w7efurn8p1_5r-Ss6RB_8sbP8zQRIoKGYL_2u7_eZf7Yq8_euXd3dXz41NO3EnLo2mdfeuXD--9ebfYvPPPi6z9762_8-q_evrP6xIvPLfrlP_gP_9bhur1x6-Qf_85vfPPH9__T3_1bq6P2y1_6_D_-7d_43KsvP3_3qc9__hN_7Ve-8NJzL1xsNoOFzTDdeeb599764Knby635d_7iW-__7M3nPvFqLtU8ff3r32uatMsltKs_-9N_e3zj5mp1NNWa2hZjF0I4ODq04k1MhHD24DGH0B8ePjm9TCkx49lmn5Z9xPDO_Y-OTo4u9vsPHpx5ldOzS6B4-ugyUTg-XI_b7ZinlJpSSt83w2568vAJUyxVlgeLKWetuWv50eOz_bBn5nGSOy8-f__9D4ZhnIYsoK4QAoHbdrsx4jzlEBuVWqZ8sFyD1TyVYb_t-oW7b883eRjWJydX56fmHmMwt3G7WR8fz3OEcdgfHxxKrrFhqSUP03LVy36j1QGB28SIUvaaS-x7My3DPjYNpyAlnz16fO_5Fx2YGZsm5DzKVJp-qaaz0nJ3eeqA7WINCKxgKmcPP_r0l76ooiJlEuEYgcnc6zQ1MWqVGQOspuoemlCLAuJq3c2H9CxiphgJEITCZz7-imlZ9Gmsg4qoGvaRU0xtPLl9Y314cHxy1DZpt91KFTOcxcEiYn7tICVgZHJCikwcuE1gcPvuLRcMTeqbNOz35CpuUqsaqApzSCHUWkWkaVpEcDVACIyzGZyIVAzBiXmapkDEIUieCJmYRYRDqFNp26ZKdXc3ZYozp9vnEcScOtZZnWXMjACBeCYIOyEAcGCKIXbd_-Y_-juxatMf_NFffMNTdNO8ywQwC8Xbti85MxOYxa6TUhmBHCgGB3RTmJPlTKKCCIDBqobYqCozalWMTIBaDQMwEgWa6dMcIgAiupuiA3EwMY6M4FrrnNucUyGIaFJT29ZSOBIAuCGH4KYcWFVS26oIEMyTWXAIHNH1F91DdlNAnp_egWKVDEiuGkPsu0Z0Qvff_w_-2rLpGJEIa83Pfey5g8Xi-advvvD07RuL5dNPHb737sPL3XaYRMFTbIiuA8x5lIP18snjx08_-8yjh49j26QYu2457ndEM_0cVI2JEUABHJ3baACo1C0aJ5h3Oalv3TQPuW2TIbT9IjICwsmNVS4FzNuGwb3vOis5JW6RSh0XbX90sFj1zbjPi0VDAc2sbXgePF0754hmGFStGpiv57IIROzm3aKLgWLktmkQkDmIKpNHoqrqZhX8KuvFPlfBopqrTlnPr7YpECBFDgpW3c1tLKVfdGwAgKOUqUrOlUJAh6mKmeUixFRE1b26qKIWmb-YcZhcNaUIAMMwMLEh7HdjKRWYtrvBXcaxbi63TdflYZJaVGx5cLzbbbWo1sohlVzSonGHWoydAzMGKCXfvHvMAJ969sann7t3cLDIwySgu8tL_uzv_aeGlsLsUTVENDVTKLUikICrq6kyExgCQBOaGNDUgGluDyNaCCxqIgo-x3odCQDARDkQI5o6AdSSu65NoYH5Ug4utaphKeqiEb1PPBWdptx3QV1DBJskprDf7F09NXGapuVibSbTfoypsVKBoGnbMg4coqgEZDFdL9f77divmn69LlOOgcfdEJirVQ6JYkTEWZ4XU-MIIfG0G8ggtqFUjSG4OqrM4TmmObCnMJtLEVQBESP15pVmwD-gqxOBmwFYDAnRQY2YOYSZVe8AZk7hGlBLAIRoDrFtr5UfgBjCLBKeM_RABGBuCDPagBCADB0RFl1CosP1QbuKD957UrUiugmoOsYotT569-20Wn3mS1_4_te_Rymyu7khX6ctmUKMvNlcffk3f-Ojd94dVBjDfqyl1JDmgJOBG6gRoIogGiAwBnB3BzMBInc0J46REN2k7seb9-6e3f-AiKvonJAjprkvVopyYhXnNrmrqYeYnHzmSTMFQJIisaFaRopBa2mbpFLBodSSEnOiJ_c_WqwWP_nZz3_llz6jVT68_1iRtCoaimrbpiqFgxOxqCICzuZ0ZHO8dnhNU-RUVebEOwWuWgOxISABggUO4M6MAcgAgCgEImJEAsKU4jCOxMQxgLlWIYRZE82RDMFAidGqMEKKUStw4EAYQkTkgMbYgrizEbKaT-OkasO-3jlaH_bde_efTKruFFND6KhWtJpZDNEAuhjyMC26NgY2NRffbwcAQEZkAuSmCZHJAdBw3FdzZeZxnCAgAixT2zRhteyXbacGCQnAyKCqNRQCkpcamCNxYLx9tACnNgUznd3WbUpzaS8gphAdHIn2YyaiGZ4rakzoLl0Kc9hU1BDJEWd1xryPULM56Tgf2ucjvwnML-45ZECETNcoUPPrq4NdoyucmJkJHZCAEQnnP-yBENwCUQgcY9RqXd9-67Wf3rlx52dvv_fVr357vWrWxwfb_W6xXLUhnaxXi76vVt_98ElIVMciY0W2F557xs3agAe3b4xPNo8fnL740tNPnfSnj8771WIzDrtpeu6ZWwfLzqqD6aLr1ovVPuvVsLt369iZMMWrx1cXj3c3jxfDZbUQH330ODbx-RduPvX8U7vLyyYmDkhoHz3eHJ-sfv7-k4PD5oUX7pU8vfL887vNVmqtqkVVCBziZju98-ZrN9dHv_fpX3r5qcMbT99ujvoff_d1dGu7BMKffOFlofjVr_zhv_nq9776tde-_rVvv_vme__6z37w4PTDG3ePHpxdfPLFl9qGz_ZXh-sbr3zihZdffi70zZ2bB899_NlM8r2fvvfJjz1z8uydD-5_-PHPvfq9H_309jO3h93w4OyxhOWjzfnR8YHI8OF777_71ocPzh6_8cO38tW5CNx55aVcBAyJ6LMvv_Kd737vwUePv_BLn_zqX_7o9u0b3_nuDx4-vvjw7Mq0fPj-e2HIlXQY99_43jeb2F9ebYYpX15cPXry6OTO02-__0Euulotr6b9NGlUTTE0TTMOudQJEaV413TM0Hf9ONa6m0BtsWjqMIjq44fnMzVK1KdhUvGc8zK17771br9aX2x2CCSiBLYgHvNAgRFgmKY2NoxITLv9fi7rl1zUQLUiwLDdh9gAeFFDM3Z0AuK2aZpSJW_3FMCB0L3r-5ondrIqddjn3eSEzNFMrGTJub_xfN1eGTER2zTV_ba_ebPrVu6Qs2w2WyZ0siwVIKSYyv7SFVLfz7pcBJ_222mYnnr-pWncT1Mt1ZyAORCCi3AM5l5LbfvULxYUKLVt07Sxadpu0a-X69WBOty4sT65devFp58OZMGBiIIDVCvV3dHUOJBUTU0TIq-XBymEaZhMNKVIFJAQCefcDSCoa0qBiYvC0a3DW7dvLrtF6hqxamboOC_imLkWoRmHACRmpgbqxKxVTQwZAex6xDBX9RyBIIU0120BqWlTrdXMrcoMLp2rUQQOgO5OxDoVjsFUACwyuaOKgltgApyBB8bIDtQfHJj5RR5fOFl__DMv_-k3vjuOFSiM2zE1kYCqV3czE7cqpXKTXFVVHR0Z3TGGeaFdwIFiMDVXNwQDd4AQosK8XKU5s2SqhAwGbuaM84Nunuwxsxky0bXHF93BQ-wISfJEiDH2BgYmCMghzt8guP_7mw-ogTkjqej8QGQOiKS1piagOwETYQgJiQCAmdA9MDl4l9JLz949WfarrksxhhiQ_P0PP1r33cPHZ--89f6f_cWPmoPu4Ufno0ip0vQdOEYkDFSLxDaVfX7u5WfPPzpLDe32ebVaoKq7AZMDpBQCR2Tq25bnM5BSCIyMgZDUD1ar_TgtumWbGJERMQQMIbj4wXolIqDaNi0D3L17YxrH_x9Pfxpr25ae52FfM8aYc65ut6c_t-9vtSxWsUhTJEVSJCXThkRaUqBEgdLYDqzEShzEkGFHBgI4P-z8SJwEgYLAUBDJTgTZgmCZkCwpEUWRZles_lbdpm5zzj397vdaa845xvia_Jj7CvfPAS5w9j57rzXXGN_3vs9zsLdz69Zhw3zrxkEEbENMiUMgYDIxAm9TJOQpEw6IzOgOTGQTXgo9BJ5uS6WUxDybdV6lSSlXqbUwUZOSqJ2eb7ZZzy9rrn5-2WNkA1z3OYYAE1DJvZs3DiAiTQOLrmXmvpQh14vLTeC06QdAEocxZ0Aa-oFDMLBhHBTwapBq1rRNSrFpopm1KQFPU3Pq-8FUT4_OiH3cjlJL7tcYEhKEGFIb85gvz853Fju5DmPOOzu7m7GEQN28TW2SkkGhSSkif_mrb9b1eLA3J0YmShT4tV_4M0yhH3o3U3U3d5rqleauVaxUIUQ3LSUjBTWZblWTRU9VEaioqgMCtDF0qSnq0yZuKv9xmKbFCAYcIjK52dHjp92iEzVmdxcVZcP1NlcVB1E1ycIcQyJXy2P1EPrNdr6c534cS04pNoHNfb3eprZt0vzy7HT_4IA4bE8v3GW-mpchb9fbxWq-vuhTSm23QwRFi2ZbrHbyMJiIufpVYb-bFmqEOK3JTBXckcjMKCRwmQi-gDCFgNyrmZo78HSmhxiiioAZIl6Nvc0hJHKf5MQOV69CN5taHxiiq8TUgFutQiEqqLmFEPTq9wGcIsLUtDaiq_NT6prNMNx5_s7R4-P1esPTtswVOGBIIoOT5spf_ekf-4Pf_ka3nJkI4jQCUSdyJAoxdq3W-qf_9C__7h98s2ln0jTrywsmFpEpaQ0AjMCEGNiqcgwUUErFiC7GbeMGGMhEzYyYHnz6yatf_MLJ06ez2WoytsYYQ4wU2N0QPTC5uKO5GRPTVXjDmRgZpgOgik53UQiNqWFgF5cyce7iYnfXJZvKL_3MV77z7Q-ETA0MzdXd6sSVrCqEJEXcp0yXAjgCBCQO7ACigohdOy9XzkufUoCMqCKcolaNKYmJuUVGn0bQpjFEAxe1yWZASOTTTMZrtRCSFkODJgYEMrMJoTPtUjhgrZUDTTkfAnLTScS13Wy_9MXri3bx4OHTOGs4JCAAg0hoCIQMwGjWRJ53TQgcmAE8SwXHKqIOSBEndoahAFyue2YkgJpNwBihi01qiSgwQEKbdTxreNG0MZI57czaWSBRN_BZG5s2cIjsGCYQE0x2PABzNQdwIHf1cSzE0zvG_Oqc7gaepiy-OwBMgyKAq7309GNhZoCpiE8ITgAhciQMxJM4wO3KbomIZjixDYinl4jxFUViEu4gARAgARATgQemSBxjQAAjeO-jBzduXvvrf-vv6OVw87nbHlikLBYrQjvY3Tk9XX_3h9-LXWcOJ0-PTeru_mq-WH7wwSdvvvby1196_ve__UMV-fpXX0tutdTUdR_df3x6sf1jX3-big_j6KWUqgc7y0-fnQYOIYX1-RCQySyaz-bN99_5cHF999NPzxzs7t2by3l3_OxRLdkRAvOjk3NAev_dD55_7tbh7vzp4we3bl6TUszQEPo8qPrZxWUufHJ8cnhr_zv3PunX-aN3n_zhd9_RcSibEYhEyw8-vP_eez-KN6__L_7ir__Cz_3En_rlP_azP_P1n_7a259_8_PP333tn__W79x47ubzz9_5z__rf_Drv_rHf-e9D7_40q3VYufJ6fFydzVqfXp8cv3m_vOHq3_-nR-9_fbt3_ydd1579frJydnpybFZGDZ9u9h99PDp5UV_-vTs6SdPx-1524Wa5fqXvjBcDM2s7Qd1hqNHp5vL7a_80i988zvf2zncPdy5_fEHH2mWL_3Uz_7oe--cnx89O1n3m-H06Thsz0-eHr_0uS88fvhAiz579uj69bsl13sf3e_X-eJ0e_z46Xazfvrp448fPVx0i_OLcwjYb9Y7q915TF3bBYohUKl1vd223D57dlTymMcyjqWbt0QcIh4_exYc0TxEGvo-xBDcQYHSnTycbbcjI68vL6rUmCKopRiHYcyieRzbJo1jLrXkYWhSW0qRKoGiulWpOOsSYbO3vP_Rvb39a3UcpVQIYdhuu_k8EJobujITM0vObhKgEIWi4iJexXXcnh_fefF1RNAIRdRFKTBx4sBWddwO03bVIBI4EeVhe_zoyRtf_fw4iLmYymw-V3eXyswcmZjbrmFkUoxNQgMDG3JW8xhCSmE572bdPKUGwZEo19qmgIAQwlgKMKqKqRETBZ53MzeNnJh50_eOhjwNnuOEt9YqoW0BoNtfkuO1a4eL2bLrOmBwwlqLiUrOQOju1Q3c6lB0En3TZARWdCRCQiOYCm_G06eCW0B2BFf7rN8LyDEPQ0w8RY-kqkk1N2Z0QKkF4Wp6DwCEhCGolhiju5uoI4VIqq6Eo7mNA3P-Cz__xwOFd-998vHDZ2Ou5h5S0mlrb1pLQQBiVDWKpCKAYKITfoeQAF3FY9MaODJNFCBiIo72WbLXzeizqWhs2gm06Oo0WXtlQghOTVCabp5wJRAFJHRVQJocz5MMkVMyqRwjuJlajK2KADgRcQgqBu5EQdU5RKTpvylX7JyCu3GIBoYhxFkTEbrF4u7-wWo2R_TpeCoq__C3vzWKAMXTi0vj2JeigBfrMSQGhxQDIilBDCzV6ljuvHT36OmzNEs5-50Xbh6fnocQQwgqysQmtuji1JQlh_msKZIjB3ZrUgoU3KVpuG2bWjXGwEQxxtksicnuYumgNw73x-32hbu3c8mR8GB3hSLL-QxdUgxuuly0Xq1NzBSmHfJ0A3UHJDd3UwXCzZAJuKqBWgqhbVtwa1ID4KrGTGiABGMpT8_67KgctmMpLmbeD1VMKQZmOLnsvTpBULOzi83d63tSrKgPosNYDYFj6Psxi4p7Ljbv2iErRwxNKFlDJFfPuYooEZtNKE6Z1kplLKriiJeX69Q0s8Uc1BE4te04joHDandVxpEoXJ5etF1ycBOfL-bi2rUzQtyO2UwP9nf7zeba4eqNWwd7bUpxul_K7mrOX_zV_74jmfne7lKyqNRapEzyLEZVYyJ3JyKgK6e0upmBOLgDIdZSAbCqEJETZhUgYGIzRWIVNQetGhM3bTeOGQCGoe_aLpdSqxKS2xWMaTtU0xpT0JpBvA51ux0cwMlUDBADOQfut0NquJSCITIRmI79BpENVFQBIDK721VYGYgDGXrJIwVmwq7rxn5r7gBuohxSraOKuFREMlcEdAdCcjcEQEK1Cj79o4xjdHfkMNVkzQw5TCJ6oKtwzjSW8EkCDg5EAVlyJUZmAiCf7lDmZsohuqnjlfyImKfDNMKUK3VicjU0wsgqhYgSc9e1fZVX33jle9_9YQyAyGZqYhMG1MS6nTmF7otffP3733inXcy9VkCMHM2ViD1GbIKan376-M_82p_6w9__loVwkXXYbMEgdUFLZcKa61Srn9oIfmVUCWJTxB9zrYSIaVKiVPIwX-6WccgykHMIkWP6jIJKVqurzVd7kjMBTLYvAnQ3A4gp1qptnKmOCAbIYdaY1mnKRAFVXZAUgWI4enT8xufffP25W-9-8IkZDqWAAEcGyTVnAQshTH85MZkaEQWKhKhqHJO7ivkU3Mp5mHbbE8TJ0Cf8_KSdwsnsB1BzocA0wRtM3I0d-jqoKXMwNycwFwQAQ3EloCJSQHha4gIQI6dg6ijGZIGDqAIgYuhmXR3l7sHetW7x3oMn6liuEBnOxKYCoF0T1bRrGxU18zxW56tojcDEujB3kypZoS8VmRxDVQPDiLS3MxMVRiQEIBAAZuJIi5S6eZq3zCHERIt5w0QJEQmayOiEAWNkrTrkMnXLmGm-nLlpCkHNJmcKAjIjoTcY-MrmBWauk-TBp5Q_uzt8FnJTU8SJEUEcIgJwIGICQCJSN0ScgnpTi9g_OzYwEQNEREZsIzNgmGCgACGGyBhDQAImWA_D-bZebvq__Xf__v5yd_f6zmY77O3uJ47dbDaWYTOU7_7wh3dfevHJg6dWdTZr0ixt-3yw333u5TsfHj8b-uHFV67fOlguu2azzrFrPvrk6brUN1-8vd0MF9sR0I7P-8M7B9_-_keHBysIYRiGFJKU0vcZWN-__zTuzC_7jYmu5u29e4-eS8P5xeX127sj27gup2ebp4-OXnz-Rq2jjv1qtXBI9y_PHz58cv_ew-9-8OE3vnfv8YOjmzf2Hjx4mAbiwOtcf-Jzn_vmH31X0FoOGHB3_-Df-9_-lT_xpc_FEOerJTIVkSa1m3HoZt3x8dGQx1fuvnSxOb1999W_861v_fLXPnfr4Nrx6SlFPjk7pVGJsVb9-__oj15_6fZHn3z69gt3TfX86Hy26IZ-HLb9mPPp0fH2cmhSsDJwjJzi3c-_XkehyOvTi4hw9PgRIdx8-7n77z2-eeduVUGzZxfDm1956_7775vIrRu3tGqptuhmF2eXt1_96qxLFydHi_m8Se3rbzx_7-P7td_s781DSKlbcJofPXl6cXp2_Omje-9-eP_egw8__nAzjEPuZ13DgXJfzLTkoe261MRNP6hILkXyKGOutT56-ASD56GaVRftL86LyTxpGTOomRYCvNz0pqbqkVjdSsllzEQIiHUcZBzb3VXpB1c1GUSrqs1X-_0wmlictUeP7j3_4mtilRBVVGpGYrM64R05JpOsOeehb1f7ExkAUdFdxnzzzvOOScxc_fHJg3a-DCFMPavtxRmAUoohJVVrmggq42bTl3Lt1nPj9tJz5cBheopeMQKImQGQQxTVnIuoIvgkDNLPEq6BA4CNpU7CxMkEZuBaat4WQGy6Fs0YPMUADIv5Apj67ZYcJJfpkRZCSCnMulaR5m0bQtxZLpomcUQwK7W6OiOGFN3U3Lfb3kWYUWTqTZlXQUIVIwBEp8Cq6ld8IaMYEMwdJmQZMFAgQKxSka5AojVXJDBRUwWmWss0eKMUwD1wEBXmIKVeXTKkEhExE2PbpMBsJ2d_6S_8Wu77DfLv_c53qum4repaswCBuSKR5DLVANJsJqXClbgQmcnEJsqyo09P46s5BxEyI7hV5ZQAgAgIQAyuVIjuTuiOBIbTaoJY1BABAJgRQphUKNPeFBFDjCYSYjDz6XNzootPkSBzBVVABiIKQWrFgERMiCbVP2MPgRkgYUCpwjE6AQR284uT9c_96k-un52nJooqhzhbzm_sH5wNY66yWCwuJshUbIahECGYBeaUUlVDIjDT6kgQ22673hLE2bybVBjMSMhEGFLAxOBs7kDYzhLHWIuEECgFR99uhtTG2KTYtSmym3ddauddAAjoIdD-ajFsR9M8axoC71JctM2Na6sApLUykhoQWtd26MAcHXxCTSB4LgIISIGQYohXA18mRmYANA8Ts5GICHM1dSgGlfBsyIogAFVVxXMRAxL1fqhWtFYZc213mt1u0Y952-fqVopm0e2Yq3uMuN1WMdz228tNLyYqkpp22PQI2A-5lOoIKuJm4FDVgBgJJoJOrrXvB1Gt5qVKrSOGUHMOIUzxAQBkZgcFonY2j_OWYyAgHeswDDElyUOX8Kc-98KNeSf9qKabdW-q283Ab_-JPysqk9avbeM4jlXc3GazJo-lVsXPrJyBCABrrUw8jVSZ2NQMgIlEJAXUIio2rfKZWEWJSNUIwQFrqQ5eqyxm7SjVCNzBpabAal5yAbLlvFHVnAWRpkLJ9nLbdU3NmZnyOG7O14vlHIgMPA85j33XdSoyWyxCiKYSIscUtZR2PqtS-k0_9FsCUPBu1m0ut6lpx5z5iiPodcwxJkDnwH7lGQWkaGCE4KrTfZoYEBwRTTVw0KuAMjlAiI2Z0lWGBAHBp-gLTecYJySafqNq7lN1VUOM5lMD082cYwL3EJO54SQtnFCIhByCqpnp9Kgw0K5tU9f2g7zyxkufvP9pCNM3rogYU9OmFpEOX7h5587NRdM9uPcQibxWQnQDDAzM5gAAWn25aO7sH37p7bfe_-TjJqbL803JhYnMVGr9THPgkckQzZxDMFcGQCY3bZqmDEJ0ddkJMR4fP37xpTfXFxfAwCFM9eWpm2GqPt10AorUKwwMABBUUUBQNSAxk882oeTmxFP3FMTMAdNq2W82KcQnD5989es_9un9--vt1gy1iptFJlB1c1EnACaa1qlAoGJXBQARcHcE0xoIOcRSCiE2IVWVahJiRCMyw6ndbk5MjrQZhsghcUSgWmqMgSH2uUzhFDAHAgLUqupQZCQM6NOljlQ0hEhVQ8AQESAogmmJMRFS08Q8Dm88dwNJH5yeAUIRLSLuWKrGAEyh5IJInEIttZYp34pmAIhFFAxdrBYRgywVHR29aGUmA0VQdWUgqzUkDEwOUEqZoreTZS9GDExNDIE5RKqqpdap7Dux9WSCiqIRETqo2GSbFNOYAhIW1YbjrGNXIEA1meL75qDq4GCm0zthulozM04JLSZ3m0K6CJ-9jwANUKei9rQRNwMAQo-BmSAEamIIYYJjESG7G6cQCGJKTIBMnzx8OFvs_r1_8o8f_ujh8y8838y6MY_zWTtv2na5UC_3Prl_bX93__rByZMjcOBIq73d_b2d3W5W1T59-Ex1_Omf-LzkMg59CM16yE-enXRN--Ybz223-eR8k9rgzu1s9v69hzev73Vd7IchEG7X69iEXv3scsiG4yD7q92yrT_4_g-0nW-KffhofOe794-Oz9ETmRAE4-GdHz345rc_scs69lvtqwx-69r-k_v3Z6uFVPjgw493Zru3bu0vl4uh2A--_X0iTKlpu_b8bHvnq1_UzeXtuzfJWcQccCzjdr1VR4qrdz587-7NO3sHK27jYt0_f7DKm_77H380b-Ll5eX22fr773wwb5rvfvP7s3m4dbC_Ws0O9hc_ev8TatqHnzwUrafPTs6OTtfn5-uzU8bQdckcD194qQw9oJ2fPyWHH330BxnTl1578-T42fXbh43XWRMfHZ187ae-8vTxAxx0b3dPTdcXPVPsa2l2l_PVjnnduXbwzrc-2Dk8ODo7efbkfG__cL537eHxM0JkxqZpX3rz7eXO4uYLtwlosVoO_fbs_PTZ48cPHz02rU-fPL1z67ltzofXb9g0vSp5GAoSb8ah35TtsDW37XoT27S5uNyM26ZJiD7mYgYYsEoWkVpFS40xEHopJcXoJtv1UMe8Onwhr48kjwgmdeiHy8ODQzN1My0nWrFrGjed4JOljKFJQN5fbgA9NXPwrFrzdr17_baMpeZC4KZyfPzs8KWXqkpAXMTZ2dPz2DTNLKJqjHF9eeYGnFpkBLUAmIeLi6dPXn7r7YCmIrFtwIyJAzMixhTIIYTk6KVUUbsi0Du2TeOuDKiuLiK1AEJiYg46oWBCu173HBgIigjolMpxBKCAO7uLEDnnEQNolaZtgaFdLOY7C47xxuHBancVG0JzNUCXOuZS6yQTQISqarWCOyEVrYwB3VPTTBU7V0OAKVAw0QJVANymrJEZ-EQhNVSVwOxqzCyibupuMGlzEKdjiZsjEOKVhQrcACdsGKkZEljgGGJ7sJhH-ZWf_-pPfPEtwvCdHz14-aff_ui9T_NmS4wyFgBwU1AzEzKvVUPblpwNnCiIKAAQMRJi4CLCITKhqkwf8dNulHlCIBqYT2bMCZMiIhTS9PFPiKpoTMSE5v8iuALuMSQHICJwI_CJP-5qqWkRUUSYyCc5BOGUHOIUDRzA3ZwRgXGiqaFjjMmB3JF4-mIITLFtY2BCWs34Bx88PLs4vXPn1no7Wi2L3UXD6fjswpFHsfPN1pnHcaxFAAEAFouFqHEgk9q0DYLFJjapHfOICm3b5lojxTgNPZlD4FlqcymBiGOTUtPNGxVdzRcGwIyRuem61LCUun9tD0Sl1IYghYbBdhYLYN9bLU3Ktf29ZZf2d5YE0IQQ4lVzrE0xpTT98Cfeegw8zWJDCGAAjGpuACISIwfitmliYJg6Fe5idnKxFfdNEW4bNb_YDApeDUqpCoTEQy55LIhQRBDsucO9orqpdRjLsK1FbTsMtWI1VYQxy3bTO5ia5ZxV3NxiiH2fS6kmltrUb3qaeFlV-mEwURGRWscxp665OL9oF6txu2GEZ0-eLnd3zVVEtBowxSaN42BmIbaL3R1EaNsI7Iwurgd7c876xddfWCRq26gqCuZu282WX_7ZP910rZZSq1Gg2La1VBUFQlULxA7qAByCgY9DDhhKqcwcOQCCqNZibdvkog0zh6gmk3lVpJr55NiKMQBYrYIIFMkYrWjgMIxjosBo1byMmre1yugOpVYMDqaBqGm7fzGeCCFSCLWUvB1iSmDazbqS85UxFDH3YxVlxH7bSy2rw31R7bouZ2EIAGhaRIqYTWEkAOMUYpy5qZQ6NTBMjNM0tzYO0d15cqoDIRIxwTSRBCJiAP8XaebJiuJXNUdmTnjFMg8TAXi63ANA6jqr1c3dnWKc1ivupmLNYm5inMKU-kFnc0NGd0fCyLja2VvNFpthBIq3bl2__-GnIaE7OWIMiUOoonmUX_ilX-i3w2Z9PuZ6eXlpk5AJAZAmvbHVyhhC0957_-O_8G_82R_8wbtqdRhKqYKTcsmMkaooMYmBuYKBijIShzi9QJkCE6opT--zgE0Iz54-Prh-d-zXgGGKkE3PSlBFAuap9w-1SuAYmqhSnTAEdlMEq2NFBk6MIbhOYVCiFGoWZDTRifEsY7195-6rzz334cefFDU3D5FUlJHdDMGQY5UK4ER41Y0Cd0Q1i5GDMzgi8oRthc-eoQysKiqlbebVipmYg7g7gkhVM1NzU0LMtRg6E0hRCkxEWgTcAInIGBkQzaFLEQkImZniFFfnMH3pGAMnMsQQ2cWfu32tTeFyO55vezWeolDTMEnNmTkQlVJLmQJ27kRTHY8Da_V5m4SgOmiFUjM4oZOrEHMTQgyBmfuskcAAwEjV3EitBmR1M3VkusLZqpKjmgI4TTwrIkLOpc675OCIGBibJiEAEYtDamjeNA2HQBAJjVzFiMjMYBpjTcYMhEkFQDixOMgc0NEVqoojmcOEuPPPZjfTuBHBicjBAhOhpxCbFBg8EKUUAzOaxcCBCdxiiMw8lHK2GQO3f_1v_D9ntLz-3A2TCgBNSI6oZCdH5-vL_rnnXyCE4ydP3UERbt6-3rRx1nXbfnh6dnywv3r1lbvsIMO4XCzvPzm63FTi-PxzN7b9uL0clruLBOnZycV6u40xuZWjx2ddFy-HPhd9eHxWBo0cA5SjTx7Nu2aZ4snpZVkPy2Z2fbetYx1zqbmen64fPjp64ebz2Pcvfu4F2RbJwk2XSzk-O3nnu0-Oj05Oz8bVYmax_7v_6LeHo8pJvaqZc_Rcoa63f_O3fvD1r36hmuwt5gbWpLSazx-fny2XOxcXTx8fP3311beooW998zubUl9_5YVHz4631p9fbnzUQfq-H27duv5jP_m5u3dvv3D3hlF58uhsvlwcH51gDOOoR0-O8rqszzdIgRtS12svvNB1TQrx0Sf3lsv969dfyJeXb33-rQ8-ev_mjesotc_5yenxj__4F1zVFvHa_iGnmBbdaufg-OjTZne1d-fG-ZN7d1548fjs8vr-7Nnjo9Vu--Tp0aNnT2689EbwrGX4-N6nN27fbdug1ZxCCs3zt2_LtsyWh2PJhij9cO-TT85OLs9On1ax28_d2l8sEKkN8ZVXXhnH_tqdW8PQD-ttzQMYoAM6DENPIQx5MLHZar65uEBTjrFUaZum5mwOuRRWGTYDwghgkjMxMpDnOpvvOpiVYsJaC3JEBPSpmqnDdgPgITbgqrVQTHW7Vql5OG8XSxPJ242Z5e2wd-s2cecqKYW8GVIbZ11XSnWgmkfT2qYmEJchuxqgDJfrGOO1m7cvzzYQkrmvc56l5AwNU67T1FxzLWrGTBfDuJjPTQ2RchnRAFWYwjhmdQsxciBX7fNYXUMMdrWfdiLiGFwUwZuubWNbjaTUyCF1LWFc7e3u7e3PZrO93WXg6GJVKoLDlOsVM7V-0xcxEQNkAlBBxgCqgVm1EkewK1MghTCt5ZEZaZqdTI4dZALmUEuNTSpjUTEgZ2YVdTBECMwA5uKI5KJgMH3WqE8oSDP1EBiQka1tWkC-dnv_pTfv_Pv_5r--wMge_t4_-J2v_dStfnvyzrc_DYHc0ExAdYrLgzuYp64xN5gEfZOxh5E5uGiIUao5EwJPiiRwaLuZlkKBp92Mm8WUTJRjBAA1wauh_FSBADBDQw6kIgRAbsTBiVTqFJgKTeN-ZR2FaUpqjgSRpwioAQJxAGK8yrUyhaBVYghMjIREzCGGyFM0QSYdqgHH-N13Pjw5OXt0vn377ddT4s3FOiAv97rHnzwtaO58uemnqaWLBA6G5IShmZk7E439sFgsL8833WK-3W6ZeWdvV3KZNcmdpBry1a8gMMYQYwh1HEqpIbAzEBMatE1C9ECh1rJadlolMsy6OO_ictmB1kXXtBGbmNpIq0XHCMtZp6XkPLRt0zUpTnBo16l-OM2vTR2JaNJkmU8IbHNbzGaBGczAdCLVGCAgxhSAaSh6vhmLqzoOuaghElXxfqziGkM0V2bcP9iRqtsxj8WHXMZRFNGIMGCRenRygYEZvVYdxtJ2jasRB0Tf9KOqcqBhKKlJ4K5VxZw4pkCMeLHecBORSQHFZLtZM0IzW-xd30eGpw8fNd3CgajhsR9SE1erpYlg1UBpWG-ff-u5tpYX7u6--fzN2_tLcFtve0RYLDpVPb284Dd_4dcNsZt36-22VjHzxXyOAfOYa6lTLEWmLv0UmvGrPxNTmXb_5m5AAVIIeTqzmLnbdCz2q-y0dk2r4CJWR08p1LHOUuo3RbPM5rOzizWAOEjbpH47NLNGqojUyFRLFRczGNb9YrWcZvySJQQCgprHUqVt0ua8n-3umNSL84vlcrFer_cP9s-fncZZI2PeOTwo44CEroIETdflsYam8SIWaPIszJfLYT2EEFQmhxeaAbgT05W3NyUwcXdXIGZ3iJFhwr5MIQczZAJ3BDSx2LYiMtEuOSRzxQmzCIyIFIKrhhC0akiRiFUlNK2rAACYwzQaMSNCDsFVEb2JsxdefunBp49uv_z8dl0Ob67uv3-PA0wHtBSjg6uIx_TinRt_9IffPjt6-vkvffX-p58CoauFlBwCoxGiAQYidYRa_sKv_eT6VJ-t13k7rHNRFVdjBwQoVp3IzN0tpeQTHCk1bg7m6FglpxiBkYhBQbOlFDlSljI18EMgNwOc1MtcsrSLrubRXQmZAFUNiVUkpDhZFdCJQwJHAjRdAyQMbG5EpLnEFEghRHr65MEv_vxPPbj_6OxiXQSrq5QK6LVWBFdTZJzgcaY6IWimoyhO8RpQd2-brtYaiIhYRCkQAZgiuYUQJyZlDKGUwkwmOmXNVa1qdQACAAJCMtHptEoBJIsjOvg01a5FQ4wqMiFuzMxMJ006Rw5O6N7E8OzZ0c2D5Z0bex8_OCJ0jskc4jTdvoK-sZvWqkhkCATkgOJei5h7EXEjYshVhyyGXnUi4gcmik1yscDURhLxolOpnVQtRK5VAaiUCgiOju6qyhQCUVVz8CqKSEBTkT2aW5cSmUXmFEIXwyzEjolgsv_qZFOe5nAGk0gbAVDViK_kyRMMG8Ej0RQDA3AkCBwmBSGAAToFcjC_smBCYIhI-6v5omlCCDwp6ZhiDBSmLBcRUQrh9Oyia3d_5xvf-N1_-vt7q72XP__6xdnFzmpl7k1qZqv543ufksMbX3z1wXsPyjiIyOHNg0UbGGx3f_98e3l-dv5Lv_ATc2ImA7OL9fjBp0-N6WBntbe3mzfD5mx7cbm5dfP6J0-fXZysd1eLWYMP7h83s3D0dHCQi5MhqooouhkCs8cmqNiQy3w5u-yLqebsL770PGOYL-aL1Wz0cX91cLQ-_t1vfON7v_v9B_Xy1S9-7cffeOUv_k9-_dPvffj5r3_xS19588WD_T_2Sz95ypuH737KjAbWb_JP_uzXzu9_-ls_-AiqHO4unh6dPzs7laxZS5fCcrb6gz_89td_7MeY_fjevb3Dg2u7h7a--MP37--06cMPHp4_ujy4dtAPQ7tcffd731104d0PP_jgg4fOKGhHpxfOzfnx2frZRUAEhqaLBr567nZwbJjN9P6HHx7srJ4cH7366t2H9x-udhaRuYg-PTv98a_82MX64uz4_PqtW3nsq3DOcnF2qpz2bl6vQ7l288bl-enu3nI79iePjhIHQX345OzW_kLWm7zedItdTnE7DHHRNW2DsYXQcozDKMvd3cMXbkjxN378jWEYVMvH739075P7F2enF5eXm83GGV_e7UKcH-7szueLvdUeIw6bjatuzrdmikrHjx_PV8u8HbbrHoCHvgczNECmJiWp_bDdBqJuvujX68SRWC9PTzilbnWYIm4uLxx1HLamSCmFECji5Xo9hcTNfez72MzQa-kHq4pN1DxO-_WT43u3Xn59CiSMQ3XRqTinqpIH3W6llDRrpNSmiW3TXp6enT45eu3H39quR05NiMnViMBEq5mamWMuI8jEmISGIyMFQFWTUhiRHQHZ3aZxHjiMVdXdRBEQabKSkJkjcmAWMeYARCk189ViZ38vYLh-58ZyZ9k2ab6YO_h03hKtgC7VarHpgRsSM5NWSU10Uweb6L2TgNTMKDK6izsxTUdnU53IlQYAADEmcJtgZRONA0ClVCdABCmChARsDm7TVB5NFVwREMGRAyNIEQqIzCk2OdflMv3JX_xj_-Nf_dXrOysspbj-w3_0B9_83e882cjThychEXOotV7xkWsFm5I2DIBVFLLGFCmQmUeOU-hfwSc5AgWeZEGBENzNDInBLIQwKdBNtYlJ1SCQVY2RzQGZ0K_i-m4aY3QHdQupBQA3meIYE84SzIkJpiPNFDFFkikxizQ1LRkxxuRmqe3yOMSYJohgig24gTuG6NN63wEJyWwsZffG6p_80z_6Ez__415Nt_3O3u7O4e5333l47eZBHgbJlQFLzq6SUnL3QGiggE6IXZekSDdrphhzCKy1qCkxQZwmcUiRptO21tLO2tliXkX29_ddJ-85trOuaVPfD20M7uJu86Z5-Y0XwzDu7XRSxibG3b02IOyuZgF5MUsAMOu6wByYaYLeTiA70WkMp3rVGJmmgEUEiRGwaxp0IAKRyoxmVsUMaWJaZvMisunLWKQUNaBxrKUKcRQTFdUqs1l7a3_--GxbqvYiAi7mapZLQfQx68nFhggT01iqIYiKFHXwYcwCqlVFFCMzIcAUS7b1-qJtGq31-Nl5aKMbpqbdXF6mGNtupqKBgwNtT0-nvNasbdZnm3bWNU1smri3WqUYGsavfOHN7bOLF-9ce-X5W6smPnn2BABnbbPe9ieX_bsfPeLP_6k_pw5ZhMmHcYhTYicGVR36YdLfmlpsGxetRTiwqJhJE2ZjzqbTfQnBHQgQab29aJuUIotCyUrE4EaRFHwshTmYq1dHREVxEWIerZqrqU5vp1qtbWIdKzoO23GUITaNioQ2XZ4cN22z3Wy7WcsAUgWRhj4v5ovQBddqqsv9HXIPkVWkVgGzdj5bn582XVfHYbm_m8exa9pahGkaGwfmUHNB9JCiXAm6cWJEuE7Y4qlHYoBTNxEQaRotT__DEYl5qjUiTvpSB3KfnCCfdSABCc1DTFfnOUA3c0dkAAAO0ao03dzczIQnIhAYR0I0Qg6he_Pttz_84IcHN28tDxZP753cff7mvR99GtvAHJA5oJs6OF-7c-uj998FoM3l9o2vfuXDd36IgdjZiU09TCc0QEGmGJouqsU3Xn31xddvf-tb72ITL07XgChSKBFPC53PDmDuhswcooNTYDDhGHI_tLP52I8cI6C7e7--fO7Vzx0_vB-YEPAqSYIUQpCizSxNoaZA7ORAQIRgzkRT9J0YkQMYEhNgUAAgmKCcJhpiKCJTcfiNV1999c7dD-59mg1GrSbCjCYiVdWVAjMSM5maSkUK5lPbwgVc1UyNAlap5oqO7i6iDm5SANF0arObg4WY6pCZSNWmwz06Tqd5cJ8-HsQspji1X9wdQwjEZmauMbK6RA6OnrqWKzIhOjIRAagIEZCHz3_u-fUmv_XKrfuPjjlwFQtEboAOHMgBpKiqGbraNNIgBECyGIKp7S0WBHZjb9XN520TdBgQDMFNPYWoqi6i6ipebTJlIpDjVCEQczNUBwUxCxSQYKq4TzmbwEyERcTNQyBmiCG4u5qGCEAgBIykOuUAydUNwMyRyKZg7Gf0H5voPwAOjgiGV6sANw9EADRF6dABiRymhp8jYptCYr9zeNCmwFeAJmKiyfOZmuCqGDCGUKSORSim_8P_9f8m27r_3O2d1fLJg6Pd3fnh7g4hrS9Pjp5eOIdXXnvuR--8b6bV9NYLd1KKs_nMkl-e94D4-su3uJaYGBD6wZ5c9LXoy6_cvdhsxu1wsV7ffP7w6enF0fFlcF_tziLbydP1cq87PdoONZ9vR2pYig05X1z2E1va3RarOTllKQFt1qUbz90U6R89-vST-8ff_u3v_eY3H_7CH__5f_UX_9jP_sJP_fxP_NTbr9yZ7R62Y_ngByeQZnfv7HazZrjIiVY__OZ3AazpOoLmf_of_uW78-58Wz969OjgYDVUj7NuAP7wo4_aNH_1uRf--e_8M63czGfXry1_47e_-dU3n3vw-LEX-vyt5-8fXT53cC3N2-_98N1bLzyf6_jCrUNx2gwFMQxjPT7dGvPF8dn69DTGoFIpUtFCs6ZrF5cnx6-89Frebn7s7bdPTk6uX79-cnzKGIZxfPD0ycOnJz_5ta9cnD358KMnL9-5-ezhg_Pz7dnZ6ZC3QLxzuDz-0Uc3nr_z9ON7-zdWZtZvtvu7y3E7Guje7gpkPHpycvH47MYLN7mLMTanp6exDe3e3LSs9hbjWEII89Xi4nR948ZtNHjzc69fHJ0AUnU5PVk_uvf43fc--OCHH9776KN-2B6fPCX2xaq7frAD4G0TdLshBlB1lRAIvdYypOkLMXMTulk3rNdSc-03zawZLy9NxUoxlfOnj0IbmYNpmc9neX2epSIaY0DE7eUlkQWOZlbHniZLrMA0NjJXZHKB3et3QpzVUqzU5WGnpZDTMIxEJKXXoqmbI6i6xRSj2-bsolnt7OweqOvkhUR0dxtLJZoYiExIOJVCiWuVUqqCmXlMMauYGwJPlR40MPcqQhRyKY48AbqkSoyspjGFyVJaq6aUYpuWq_kE_wHCPPTmWEsFVIRAjgZQq0xv4IBsZlUqxXBVDQIY-0yBVJQmHgCSiDUxllKnLXWI0RDcPYagJYeUSi7MpGLT4dLMrv7NppIrkpspuHEgM0UHjgmZAaZrDCEYEzZtDCGa-7_37_7bn3v1xeuHB7YpkeR0s_lvfvOfKePjx2fryy1FFHUAs1onxj4DIToiQYiqtQkBRAwIEAEMEasqEYtUMGu6mYqaVcSrWrOpuRmFyMQiBcBDjNMUClSImIlUdYJXMgdTnTq7IsohEoGVGlI0dwpJS5mMOgQIQDDtrilNuw4OgaZpijmHqOpAEJi0CsV4VTZ0LLVyiiGFEAMzI1rd9CK62Wx8zGOQ1154HtWceH_RXL-5--knD3b39i7P1wqg5lUUCJlwv2n7nIFpsisQ0FRTFlNH79oEgMBUagUGE-MQmpTUJMTIIVJgJjC3lBIyMlFIycGIKMWws7vqCBbzjkp5_eWbN1fzFNOs5dPL4aVbh8s2dSlMXewYCMEDo7lPKBE1Q6IwmXyIrvxrfpXCalJsU5po1eZaJMfpYOY0lkJI1ayN8WKbL9ejO-aquYghqXmudWKzAuBO251s-vNN3xftx8LclFrBoJRsYttczOp2mxVoyBkDQ_CphLPph9Q0qmAmDqgwAWUIAapY00QFuLxcj2PebIZu3o7rratz25S-xMhlLP3lOqaAIYSGIwc1e-XNl55--Phgb9mitYEPZvDyyzdefen2zqxDhEf9k-cPblATOSVehLvP3eRXf_7PiFGtIqU2KXJEE48pqaq61VJBNZdChKZGgAQB3PLkWWNwcAAUqYhYi02eZzBC5lwLOKbIVafoLjm45IruCK6uEDHnqtXykMEdEfvLbWBGgzY0OQ8cKHSRmOfdPOdeamFCM0_z7ujoLDB3XQMI7by9XK9Tk1TEzHKWsR9TjKmdjf3Qdh2YSRXJJQQe-16KhS55LYhOTCaqIpPZGz-jv1NgrUpMNj0fr0LuwBzNFKZisU9UwulOAOaGSKLKTJOn1N1ibNwUePLz0QQ8NnVkRkZXp8AiBSgiGDGbmruEpiVwVZ32BUjoZjE11-7c_eCHP4ixm-_uLpbdg0-eXb9z-PCTRyHxtF4kgDzk1bUbqvny6bPdw9316cXutVtnx8dEEJ2ZeeIk57p1bIgZAoL7--9-_Of_3K_sdu1_93vf2oqNpapWKEqAU9_I1IgwMgGg-WRRAXBQVQyEQO4aUhI1mGYwAU6ePXvtiz92cXocYhMCTzfFwMFdI7FPUCNEBENApAAAzIEYq1R3oBD8qgs98WCcHAIFdJ2M2dymGJrTk-Of-NqXHz55fHx2IVlMpBShwEYu6hPCNSCZOzGrTgC4q6UnODKT1UIhSq2MaD51sHzSriE7IfXbAYhVKgd2U2KWWhIFFWljK25g0MQAU9MZeerGMHMZpUlxEhSDW5MSmhKQOaSUkKiKwXR5JEgxzeet1Ly_2Dlfb67vro7OLoh4HEcMxEzjWEDBWKsqGAgCIlYVZFDzFELTpGIVAPtxRPAU-XBntbuYV5kefV6KmPkETGJGV5ywVFKvCscq4kzmoA4OXqowkzsEYlNDRkDY9j06oBkCA0EMgI5Ajs7uhGiMpGqBrjgWBhNLaiqRg09abAN3R0dzAwMCMnNHZ2YkcAA3m_JZkVkMGIBRG7I7-6vVYs7MVXEa6oBjSiGPZTbrYiA1VZMYw3Y7hjj7w-9-5-_8l7-xmq1e_cIbF-eb0PqQa9WiYvfvPwoYXv3yy5enFw8-flAtX7tzONtdbi83X_7iF46Pno2n52-9-eLtvd02cb8dzs42T8777Vibtlvu7jx59KyO-ZNHpzfv7r___hMZxjZERO3Xw9MnNRGdnm5Sw8O6BPC-L4BKCO28IQxdTDuHS1O9uDh7_PDZN7_3ybvfeu_e_Se42vnf_dV_68s__vlf-bkv3Lw1X-0t1U3JEeH_9613GNLOXH77Rx_-S2_dXdc6rteHh8_91j_9Z80sudp8lr7-8ttvfeH1S7lc7O_cuf2KVXl4dGxEi_kCAJj43icPvvXD937up36CvLzz8b3P_dRXH3_y-Oh8fO6FV5-ux0WIWYfffue7X_rS51586fq8a5az5ScPn3EI2RSa1I_jZrvtTy4MvEjdbjZKurxx68b1Q5V8uHtQh7qznD87OTnYW37wwSeXeqHqp49OifCLX_zcziKenZy-8dzd7dlZN5-fXVzUmimF67cOh8v1V95643vffHd_f4-V7j181kyPqe04a5rlTrezWubaL5fLrpnHGFLbShVyH0tGJHA8vL43bPomhXHYOvFqbw8CxDRT4N3d_a98_a315Tjf3UuzFhCWq_nYjxfHZ0dPj-sw9P2FV0ktb84vTSUmrtu8WM7XZxccSLScPjurpSg4IZZcgACQJv2flG3sWMbRRAlDv76YdsiBg4ukrm2YxnGoOXMT2q4ZNhtzJyZKwJTqWEIiAjx68uDwhbu1GgUv67Izv16G7OZai2lF9mHdxy4RRhNzqSLjyacfvfz5r-R-DG2cHv7uVE1MxdWlTqN0N3MxzUWKCCCAY87ZANVMVGutaj6OI2PIpRCQgAE4uLdNUtVu3jRtalNk5skO6WAqbipFFAkR3XRauGodCwIwTRM0JMRJWiQqRFizApOLuiHH4GYcWKpSIApsDhyuFEhIZOimGjmGQKIqJkWqoyNSFUVCE0mpNTNRYSaRCjZBwyYLGAKTT7MYcEMlYnJf7q6Wbfvv_pV__ed-4q3_y9_8B__kn_yTnWX3xmsvv_fhp__F3_vHs939x0-OgcDcNYvUjIxEYCLTerFUaZerOg4EGJGyFopNzWMIgUMwU05Ri7hDjGHq0QGjuxOju7rTNEwZhwyuzOEqHCnKMaoKE020E_xMiDidK6bczqRtYWYKoYw5pAYBOSWtlWJQkRibyVBKSKmZaRWKUzph0jCy1sociAMwAFiKER26-UqqMLq7BQ4udvvl6-uT9Vd-_EuLJuqQE3OMzWYznJydDaoXm76CVvAh18DsHgBMfdpp6Go-7_uhbZKAtU2a-BDdbK5VAnOKAf3KlZNiHPNYa5nNZujoKt28m14ViOC1cAqBsEth2cXnr-0fLuZdE7qmaRNd25ktZl3bJDUj8MAYmCZuh6qpGhJeYaAQpEou4ghEaKCEyASzpp28ljmvkSaeBoATBy5FVbWan27HPtdqZoClaq5ebZoIuqOXYVwtlrXqyfmmGhb1sYy11qI25Jy1ikMtVdWwiXkYHWwcMyG5kdQ6YawBsebiYCkF9CvJbhkyBz4_O4shiNW6HQPHnIu77V8_RANq-Ojh41mbAkdsGzQn8Ne_8PbTjz68e_Pazb3Z3YPVV7_86rXd7nC1YFdQr3Xcny1VzNTPzrfLVQsl81u__Oc3Q980ScS0qhfvS40N1bE4-LDtESZ34OSk4Km8DuZEE6zPrmot096Jg4l1s7bfjmpIAIEIA5kKMo5DTm0MHJjZTbe96FiAzLTMVk0ulRAIEACzjOBgCNv1ZjmfSx7yWBw0Nc00Kph1sW2iqCKGMtbEtL3c7B3c2A6bJsVZ1-Z-SG3jiCHQsNl28zmopq5j4tnOjtRCxHmbpx0CUQD0brYY-jFMMEImd4gpTR0m5gBmxOwAYFP73hGgqoWmdVN3ijFOFXNwSE0juSAS-hT-v5L7Elyl9KY1QR2l7eYiEgK6KsdAzJIrhwk9zzbN84ljmL342hufvPsuRa5advZ2mcL5yeXu9WsXRycYOCADuY4lztrd6_sPP_xR0y739lfb_lJVQ0h16CG0013ZbToPs4NOI2VZ93_pz_8Jy_TD996tgU8vNqYQ0NEUA6EZ0PTgtgnvOAXFObUALrUgQaCgUpkbN1epaOqKoZtblVKyiKIjpQSmaK5ugAA49XzBRM0txITgQNMJ0dvYqjtPMywkcCdHq4oIMQRxrePoYnUYv_61L-2u9n7w3ofuYFqRUUTdYXqruyoSiKhfXSWcERLytBEkwDhZaUohCil1eRiIUFW01gBkk90ZHUQRYHLMRQoqFmM0qeagplW1CbNcRkJEQlUD9xiCuxEiMaIhEbdt4wAcqG2iuhM6BEAA1akhY-fnl7f29xOFJ8-O3KgfcyDe2Z2PfQFzATFFIp482YGAmBbLbm8-F3MAL8PoCMjU51wqbEoOXbNcNASUxzJ5uQwBAopYmxIRzlIaawWbpLtQi0KY8JsYJhELoKMzE-G0WuahZENfzmdojkSA7gIIgNNGf1IEAjAC-PQWAAcnYkQIgadf8AQKm344hOTgDAgANnHbCBA9Rgqur9y9dbDquAy7izkgbqts-jzkut72pWpsQpjerQHNTKVwICSUKkDhP_6__2dPHjx97qU7O3sHjx4frXaWAXjM2dzOjs9z1i_8zMt_-FvfBrfF3nx-fXd70S_nyzDjs-NnZTv8xX_llx88elrGoVl0z47XueB6KLXW3b3F5fk2b4eH906fu7V8_PhyxpEA3WQYBUHGMuZ-2A6l5JESl2Jo1M5DYtcynJyff_iDe58ebf-ln_riv_Zrf-rP_vov_fyf-Olf-LmfeOHWdWEsHHZv7lxcXuzNOsQAQJfj5o8en7514-BCLs5Pzv_lX_p6CNGqtWn5-7_7O9P-0Gz43kf3_uVf-ZPuw7ffv_dxql-7-2KA0m-2XeqOnj1qZt0XvvzVf_Bf_8Yv_cpPAzff_fCTWwcHH96_t5qtdvcOPrr36Ys3bsQAv_kb33rpzRec6OjR6c5y8ejhsQBi4PVmNKD-rL94dFbqkAKK2Pxw5ZHv3HrO-ry7d-Pxww8QZd0PCWJkvzjb_PLP_DTYUGr-2he_nFJ99_0HX371te-_9_5q5_rJxUXut7EJOzvds4dHr7_8wnsffHD9cE9yYazHj48cmRRff_HFXIda6noz9EN--bnbojpf7QpNdltb7q-2Q79YzACgbVO_yTEGIPUqqQnbYRxyne-vDm9c69f54PrevFuudldtaFKa3XruhlY4uHa4PispBaxaN7kOg41l2FwyQ8MhcoiBtY6LnQPT3M6Xppbmc0AnJweqQ00hqBSrJQRMqdE85M225tG1dm3SqiqieQyxiV0rw6B5CLGhGNBA8wAIPhRaLdL8MCJdHh0NdUjzxAxgob-8dNC2CaWIisyXs-Fy6yZlzHdfehFTG1I0cwKTaeCOToiAzoxTlN7cEQjcyzDUoszBzIGxSCYiAo-pEZcpH8LMlquq11JiG2ZdG0J0AEIydGZygzJWN5MqNlVNzYhYTUqdsog6XXLQQNW2m7GKmoFICUjulscyqbjcPUw-RPcQAweahuwT6CzEBA7iVmvhGM281goTD0DVVJkQiWrJ4IBqLo4MobmauTi4iiIQxQigXWoQ-M7h6j_4X_7l119-6b33P_rP_9bfyeWSzH7xX_rqP_xnf_TB_U-Pn21yKT55x1WnKBE6uIOrmbuIdKvdcbOZ9r4hBDNJTap9DjGq-9XHH4WJB-RSA7PUysxWq6ogErCj24S6RvcpwzNtQgDc1InxCu1iRoiEwRw4tSbCzKJGqZ06h2ZOgac7j5lzjFfCFWRidnBkCrE1NeIAbkRMFEwlNa0ZIAKnCMSEzkhgFois5qZN283w8f0nL794J2IoueysljE2j4-PKKX1doMcAIjB3N1ZVnu7uc-BeKhlsbtDrmpuCvOucVMkbDCqVjBLKQ25LNq2TcncZ7N5atqUUkB28BAYCJvE4N4wHh7smtYuJg6-N2uXLa-WcyBs2xhTnFAQhEDoV8ZpRKZJNseqpnKlqEJ3ioGIJorFrIuBA5m7o7gTEVEwNxNnJlUzN0PYDnmo2mcb1bZDRSY3dwcxnexm80WH5mOu622GEHPOjtjnwpGGUoexKLqrb7YDcei6ZhwyEoK6lMpTBUJsvV6je-6LmXMMqWm368sYuZbSb7fExCGcPDthQg-B0DGGYbt1s4tnZ02CGKMBUtZS8qyBiPTaKy9Ehp_-2lsM9vjh0-2296ri1rQpBDaEron9Zn1xfP79H35EUiXFEJiQFAmLqAx6cbYuVYkoMIMjGnIIJoaAVUpVBcLJZuwCS1y5QR5F1aqoAdRap1vTMIy51jzm0KRSaxMjY2DmUs0cUuLI1MWUmmZ7XgJFQjI3Vc-5cKBIlGIQqf04LueLENJy90BUY2QwyLk0cd6PfWoDxdAuurPT49Sk9cV6GHIza0-PT8j15OlJM5uFlERk2A6ObFJVzNzb-XxxsN8tF6lrHXC7vlzuL6XWqeQAgEyRJooVk04RBIpIGNrInJCYmcANmYiRiCfpuiOaO4WATOqGhBRYpqgPISA54AQsCG0QHdomuTsR5mF0sxADmE6dIURq2xaQbr7x8o_e_T5QQFAXmWDskSEClSw4xXWQTW2-2OnPz5oYwWq_yWk-P3nw9OD5631fqEF3N3BAr1J9EhI7TaC3v_G3__Zyf7Vq2722nbfJtTrCWEUVjRmZKDbAQXINHIipiqplCpE5IkYT5di6FgTjwBhimqWnDz6KTZIi4BYCaq3VVNyQCIG0SinihJQI0LUMKuZO0xpUJTOC5ILkoJXMSq1ADgB1HLHUwBxiKNW--Z3v3L17bT6bhTYABydHsEAenKyouldzCqQm7lpKEYdeioEiY60y_Vo4hjwONfdNaEDdRQhcVSQXcteSCVBrme7C4zgiYT_mUdUJkUDEiuZJIpZLRXQzlyIqU9SeMV4FYHTS_g1DDB4Su2NvAkzEHJsUmjYnENYYI6Ac7i3feOmOZ3n1zuHh_sqqMaGJocNi1iyXs4DITpd9Hsbcj1Ucxlz7IRMRokaA7UV_cdFzxGEspVSIRMxufuWdUd724obINA6iFUVRM5QiYgCGuVpVybUqYhUxt6YJTZOM4LLfFteiVtwAXN0IQLOCAymqqCqIenGtoOpgatMBnwgcYFJwmPm0SwQECjyFCc3dXa7tL165c-3FW9dIc85jxubRxfjhw9Oj0-2ooI5OlHNGQFNt2qkD5xwDAIpqSIsPPn307W98d3-xu7hxa51rbNNYy9npMTqcXJw5eJrH-99_YlVnO7NcNYXmheeuXztYPvzgR1bAke9tnrkPgbDvK4V4drbOQx4HgzbWXLeb7fXbs2cn65Scl7GKnq2HszEfDcPj48ut1n4onBoHFO3LOJ4-Xj_75HLol3_21371P_lP_tf_6X_0l3_xp7-2s7uIISZKcbacrcKD45Mb-3vBeDmbA9N83nrAR2cZH31PvezMZ_3JkJo0a1uw6rq9friLhgCYh_Lo3seB1juN__rP_PiDb3zw3fvvvvraCz_x2kvz6Lvd8uGjx0-fns6Xs9_7775ZR__883ceP3wSkDfri95H8rE9bBepuzabnxxtdKDR6XK9nqDdHMNmfc5tBCQFwtiJM6eoNdeisx3-xrvfeHL2JCwXmyHvzFPb8rrWw5v7373_8YPT7bb6s4vjs4vzHzw4L6anx9uczwmCiK8v-rwuXuu8C7kM9x_c74d-NV9ULc4WZ-H-g0_2d6_fevEL8-Wqr2OuG275-OyoYB1rZedxm0NMTQyRUHJVte1lvjwbjk_Hpp1Pzo2mWRJ3t-_cuHH35nJvFWfd4vrh4d0b7Wp199Xnrj1_842vvHb9-ZsvffWt5956-cbdO7N5q6VqHi5Pj558en_cXtZ-zKfHaKA5z2bLJjZdu4jdfGfvYLHaMYWACRQI4_mTIxeLTOV8nc_X50_PiDFG7tpuXG-16vzgMLRp2A7jtm_29gEIgAj08fe-EanKuE1LQlQzBTAkaeadltEAYozb9XbTD6lrU9NyE3_vn_0mM-U85pod3K3mMbs7EDJRzdURa1WpolKlFKaAiEPJTJxLJQwhNgZUa-UQkXG2bJomTnLWtmva2LBzJAIxFdFqfdYsKm5jzgiu6rmvhFSluCEwj7WMpeRSx1xHqWoW28hh2hTAmAeGiISmKmowWRJS5BCYWCf6OzLHAERSq7oioJm7XjWyapXJqeOqtdQp5qFVkIkCAKJWJWKY5ngpOVtoIgb0Ji5n7b_6K7_4wguHF5fnf_0_-5tNRDX5_ne-GyFuLy9yVamlW3RWKgKouJsTTxoJR0Ti4GCSR07s6BhQVUVc1bpZq6WgOSMTgmnJeYghIVAgDkjgFkIgcJVKzkzRVaXKlBECwFpKiImQQmBw1KqIlGJCdXclJpGCMYopIoEZhyC1coha6rQhMEdRo5gAyR0dFMxUXFUJEdwQPAZGNA5BpCIzMOVh9CrorGKMjMTtrDs_3qz7-tHHTz8tfbeaHx2fai1dG1aLDrXMmxbVUsQUEkttYtev-73dhYGm1Pb9EJoUU0hNRHUTB4PilQAMIc1SSDxtzzjQBOUzkJDYXCd8dM6VKKTYFbWDa_uzeROJZ21AAJFCDMzcxBADSxH0CStC0wAq58ocXK_yxlWrisp0FxN1sxSYiQMxcigTW1PdVBPHpk0To5YAnx2dMcdullQrgDPTZBFAZDNAJ1RgCEKYASHQMA5FZKh1MD_fZDXgGM4ut0PJHEO--j5p2IxSBQCAaaxjrtlMch5DiuY2bId-6LNYVb9cb8as5-fry03vgMM4gNuYSynZHNbnF-085lwvLjd1mw3Nqjx-8mz_cP_l12597cfejrNo7hfD8OnTJ737qH58vC4CtaiMJQUOTVJ2KkNPhOa1ig4lKxsnMLUqliKRYxmKm0kuzEG9OpiZunktqkVE62k5nY65teRJlTIM40SuXawWpWY1H4eMGGqRmsvFZnu53XgItagjrjdbZMJInsdZ26A7J1suF1YqB05NM_SDG45lmLftxbMns9ksMCNCO-uKZHJAB3Ny1flqgW57-7tt18QQ26Zxt4Nru2nWDpdrB0xdA2jrs3Nwx8CGWIY89oOUPN0CaympnfkVERZKGVPTuRoCcSQVdbWpkikmwMiBpVTG4GIqQiGUWhzcVZHJ9TMduWNgNpVp5Uc8udQYfCL5AgKaaQhhKkHaFDMH55AU6LlXXn368SdADFhiTIHp5PjYFEXr-dn57t4yMDNxHXPbdanhi-OjQBEc-vXWitft6FkJWas4gCFWrTFGdAWtoFXGghx-83fer8A_-bUvD-frG4erENkQIaZS1R3dUF2l5BCTg4NbjGmiWXkgcDUTGXpCcjUkNmJFTDG03TJEdiAzQHRXIYIJ3MSR3VXRc6lIU7O2GAICqtdRirgJo6k4GjIiu4GIFAoUKLiBAivA7_7OH3EXXnvpBqsTYhVxwFKUGacidZXqQFKvXA2OVkQQQE2q5JyzG2gp7iIiw7AFZALSLP04GpOolrGOZQRiAB-3IxCOeaTIomKqagagtY6m1VQnsrWoAIG6ClrRKm46xWgYXLHPtVQHDLPUzmMkQnFbD-P5evj2t94HwMMbB6lpS5Z7D584hI-enHbzcOPa7nLe7u8vlqtZ0wREBqTNduyHbIjiMIqWIu4AinUUVWkIwLRW29lZOFIe8zCOtQhRIKSqldhVxR255UpOgcTUFKpKvdr0gBvkMU_dNSJbLrpVmgWiWiSPJWdxJ1EtqhBIRfxqneAOkCgwMhEZwdSlqVXdQW3SgBE4WFECVp0mL45oXYrX2gjiYna53V70YwUcshhSjKlUGXOOMRzs75Q-12rbzShmCghEeRRxLu7_n9_4b8d1vvniXcJwfno-m3W1VAxhLPXidFNNd3aX_TCkltqukQy39m5attoPl-e91vLqazeH04ucBw9w79Nnx2ebYSyL3RUwPfn42fpie9FnwPD0-LIInh5feoRhqGcn6zqMta8RQxfIVY8en5_cX8e4_Et__pf_2l_9N_79f-dfe-v1F5k64CakGWFDEJomRLR5XC1j27SEagFBsqjZnPWdxx_-uZ_85bYJt5-_E5q4u7uz6Xt3NRu-_rWvqFitNcbUcgs3lnnADvU__p__2nf--fsfPXjy3O1bb7_2ai19HTf9xcnLLz33z3_3956_eePLb795uLNs5stutTsOheczDtjtzr7082-GLqlgpPbR05MPnz0jkHYezvt1DJzamSEOwzhID-BFbNxsdncPX3_-5dXO9cuT4ydnFw_XF-8_-vT-xXqoOaW0KQUCAidMkcq2iFrwbeYK5IBNSipobp9-8vD2zevDUHKps1mTAipA7cIPP3rw-NnDZ5_8aLZsUe03_-i9NjQE7BXc6moxjyFE9r4WbsNif9YuE6V63F-kVeIVH14_nM2bUXLZ9gbetu1Yy4heEmjESra4fmAenn_x7mqxsz7Ps909DunmKy-88oXP71-7uVrtRwxlux3W6-352fmDh_3xcX9ysj05zpttHbd5eyl5wwESU7foQKVpQmCuJS_299wEXYbzy3GzpdDMF3Mwk1ypmzNTHcbx_CTM55KzB8bqlw8fkYWmXa3PNzVnMAaG-WJG3OYhM6fZoh3Wl0aQZh0aDCdn0KhUN_Xz8-0UMc25VlHz6ZxXwDyPpR96mYhm7mUsiNNoGd0hcggxiggCqjgQxTbFht2wm3UpBUYCQHC82PbONpRhu-mraaky9EOpOgxF1BFwFpoAEQE5oIHnWmWCZRMQUgSSXDf9OhDHFKQqGKrqxPpExqLihNVEXadFQe7HWou7l1LdLDC5qtTsIjGGq2SLAxKZw4Qdd1WrFZEdEAFTSCAFlVdt8-XPvfkLP_OTy9R95_vviOvyYNnNVt3OAQI8fHbWzGZh0bkIIYJ6agLF4BMPBNkMtAoHHvstITOQqLlPSSWT6qbirio1UCAiN8i5hylGQUHGSpTAwFXLOLpaIEKzSXYO4EgstUz2MgSnyOYu7hgiMbtPPi92BwoM6FMdmSITMSAhcoxxWscgMwCQATHHFCbhfeBAEKuYGQAxpcZV_wUaexhymjWOEZEcGYBKKarlm3_4joOtdncC0s5y_vyd21DrtcNFYp6lOOuabtZu1xsikKG23cxMkbCqcdsAGkSeCNHEgWOIMYiYGRhAs-ggBkdPDYNhEYkxAWBkTinO5x0HypdbqiWgvnD7sGuSVN30AzlYrVJKHocplSoG5mauUqsTmzsSEqCqggFzQJ7-2mnJRKCgakZQTauqqoWQphVZLeYAYjqbzzAiAE5COke_3OYimrW4-SiZA5rbWGWotZqJuxLh9E4BkqoBednOXAAdVevl5QbAQ-JSipltLi62w7jdbEwFiUotKprHARAIPQ9bAooxEuLpk2duWnMdhz6muD6_cMQ85JTmQ59NRWpe7Rw4Q4hUHYd1HYs-Pl5_8zs_uBz6bfYP7j2swFsVRWxnDQb6nR883L22vHN4SA6-28XNpqipO9RiVVUdzOT86AIJps66FHVzRIopxsgpRXNBZKlSitRctVZEqmXyTXBkRuR-HCixmdVSSx4R3EHHzdimUIZxuWiahhxpcz6SqJnXcWxSZAiLRRfaZrFoA-M8xf29xaxLWmpM8eLikjgYYO1HR-cYicJivkhNI1Vmqz0g1lIcIabpEUCLZuYCs3kXOMTY7B7soRk6pC5BIIrRgJh5tlwikIuoQFXhGNxRSyZiFa25Tq0bM1Gppia5gvq0uODAqkIcpmeHlhI5IFAI7O6MgUNECmYWY2IKCEDgMSVTxUiTWNHdNQsAippKBgIEf_XNt8-Pnpn55EhHg5SSjiMgN7N2fXFBU-o8chnrYn_v8uQkxOTuE9uhCYiJVUrTNhQjAxICuk8sSjAlBleDyOu-nPUXb7z1hknt2qYNEREDYUrBQRGMHWLqpFYwqKKqyhzKmANHAuYUHZCYVcTN0adimZ2fHe3euBa7Rt2b1EUKiBBSKCUzhanywoG0VFAFBK2VCJiimbvVGLAM4uYOCjBBna8a5wRYh34Ypc_aH6-__PIrqY1dF1NgBJtokhyJAIlIakZ0ckIFLYJqUzQFCESKa21ia2o1Z0Mf-o2DTovgPIyIDmAqZlXRDBHKmBmwjiM41ZpnoWEMaqI-eZrBzBCpihAH_4xRLepVxATMNBBIlbqtwzAaTLtLrFlKKZvt-O5HD1Nq9hZzZr95a1dBVPX8PKsoNwwMFKc6GbiBKSCGyGzu1V2ZxWDMRVQvtyWrDYOUsbjJctGmFDkEQOy3Q6nZwLUaEdeqJlDVZTLdA9Wiw1CrWDWbisemLqW6Iqp2TZhqD4GnJpCraTHpazX3LDWb9aJ1qmKpMdDE_L_i9YIzYYhhits6uqMxIRMi-sFOe2d3NRiut9vHJxeXY80Cqh4CU2Q3aQKsZk1DmEstqn2tRjBUFXADV3Bguv_pw9_6zd_d61Y3n7tdq_bDUEq9vFy384VV0zIS4DiOksWch368fmO5WZ9eW-2MY1XR_mJMHMdNVYGjZxel5loqBzp9choBz49OxtyrWEXFtuv7URGOT09yHmUsKXFIkMfx7HSLRX7xp7_wn_6f_spf-6v_vc994eV2Ff-FSj0S45T6RHd0MeUYxqGfBSjDIBmYI4cwb3Z_973N_q2FAu4sFmnZxCbtrJYUW3H__GtfQQJwa2czw_I3_o__hXrz-N5j7_F_8D_8pf_H3_lv_9-_9YcfPnq6vHar6Rpl-1d-9Zc2m83hIs7axcnR8d58r_fh8vzZ87s7jlCC3b1z-Pjp41kH7rlJuGBedAn70Y7XaVAuNTGyW-RoVWbAEbEj_P0_fPfhR-9IccyK60F7vbUzu7m_d23_4GC5U9WfnV4cn23Hsu1zHxzOtw8YoGtTmBB4y_bRs2eLxbydJWCG0FWL7lEv6rWd5tnH71fL7tYQpyzvvff-btd6P-7M59vTs50QDxYrrxY8JG4DN123s6RFuayNNU1qq_jZ0zO1SgAM0M0TiiUICXF3sQzm8xTYfG93LyC0keerbthujWC2s9jZX732Y59r2nb_zi0FaOdzHQfJvYybOmzG7XrcbsahXz--f37yZHP8LA8bs7q9vIgxnT15EkPaXGYCbLp2e34qWprUIvBsvmpms9TFWgZATM3MVQH94-__QbPk1HRxNstDjrMmNjMnaldLDM2w2Sz3roF6zRpjF2NEkJMP73FkU-HE5lqGcWr1SLVSasl1MwzjMBASKAAgMiPTWKpIyTkPw3aoRdRqKVp1fbmdkNKRwmo1J2YVEwdi7IcxcKjbMm7ECMRprHWa5ohqP-T1dnh2flFViFEdaing7lWYAM2JPQQOFBAR0aUIIgBYYK5jdjWpUnPRWgHcxV0UyYncVEEUr6SayIAwdcLATQRUA10p5TkEr5UIzMDdKTIgVFOgsJgt5hz-2r_9l24drE425_-vv_33-iKrvb22SXsHLQNs1ttc3EymBzigmykQOriIuCh_tuf3WmfLFaATEyMGN8iFkiGBiiAjAgaOHBhUODCYMQK4mWRiBndyI5rO-a5lnExfBM5TCfCzIaO6c4iOLrUSYckjhxSbZtJHEjFRNDXkQICIzCGAT-C1MPndpsA2MosjhAAxUIjA7IiMEZk5kgOojBy9P-8JIMyaK_9lCIuDXa7jso0vv3znm9_6rpu_cPfmoutm7Wx3uWBElRq7Ls1aJhCAFON8MQOE-WIGprPFciyyu1oAM5FRjACE4ItZS4TDUBiZHBEpNJEY21nDDE3kNjBbnXfp9o3V3s5iFsL13WUKjImnsscUoJeqPtmY4AoiAgB2Ne53IkeaICLualVUam3aNoY4vTaqSBUVqRD4YrNxNyKKkWOMDmzqASlvax2riQIQBhabXgk-5KLmucgwFCl1UsHlIpuhbC7X281mGMchF2TCidQkLrXgRBmP7GApBinVtDZtC9MF05SZh6FX0abrpvPZ4nCvbds0SylxQAoMs9kiEC1nC3JrIlkeUuA8XnKg-XwRUHZnDWp554_eCSm9_aW3-2o5-3s_-tF2rKXWs_Pt_UdHX3r58GC_836kWvToNF9uB3TQaqBmVQBESm6a6IhOYAQGblpVdOgHB6iqpZSJ4mEipRQxL7VSQACXKjFGB2kbLllVlYnKuiSK5NxdAYW0H4ZSLUXuArYprhZzbrqQYoj0-NHTGMJ2lMnDVXMGhNFqM1vMZ20IyMShjYAYmwQM47iZzZdt29VxMMmqNg45pGa1WJUxH58czXaapknjZhzGwTmsrt2YZuQmbipMJCrbzSUAtfPFbDZzQ2AwUoOpojSRZGSSQ4U0m8DDE1W25pGm4i_AdNEmDqqaUjcBcFQLAvg0-FSdkPOmhsQOpNXAgUOkSSDgHgIwkY15b__w5MnDzaafhq_moGoiksccAiNayT0g1VKkltm8UctashMZuKO7GXFwwxibsRRkENVJ5C6lWNWJUFqdFvt7iPhf_lf_jSLNl7O9g30PSA4cgmZxg89Wk8rMKjWGeKVFCOSiGBlDMIeaB07RqkGgMo6ouDlbr1aHJorsJY9MBA61lMAEapMjlgzQQUSmOF9LiZ2DMyOCagxIRAghcuMqSFfXdKSgZu51rOM__s3ffv21F28d7KEIGboDX4EQQFXQFG0CRbuLonqk4FJdjQxRzGo1FVBDMNTiKlbEpEIp7Kb9wIBWs4mwIzowkpklooiIhkMZYooTRKhWSYiMjOYpRK8Vq3t1N2jaVkpGAgc1x1IrkSESeTBDMFCF6m6Rn12sY6CD1c5iMTs9H3qtTRcv1puzTX_09GK9zeu-bnqpVcXtbLMRsM02O_C04i-iEBmQAL1aBRBVV4MqGjlEZjR3sCxS3JXIHKoIkE-uOwXIpaISg1czcBJ1FTXXEIPCtKRxJJq3zdTSHutYs4iAARR1BTBwdUOEapWB0dHUVU2nKrATXxF8EBkNjANyIEJsQ5w1jZH1tZxtR1Mds-3vLlPknXl7bX9548bewf5y1jKFYA4GoOBiVkXGImfn21qrefhb_9Xft37cvXYIAJfnl_OuK2NZzJYxpfXmHMwVdLlcXG7WTZPAsevmz56cpr3myemxgXMbifn8speKx08v0fnsaN1vxhQ4b4f16aZmUFBX7s_7vN1A1eGsb1pkkM3ZBofxtdv7_8H_6i_-h_-b_9Gv_smfjSHW6tMrMQIFmMpeBo7Ti98NyOneyenB7lyqv_P-x10KSAG35f_7-9_43__qj2WIm2HcFGkWbRmroz9_61apWdlTCFKlioxD_aNvfr9bpE8u-zLEedf8W__mn3vv3e_98OMfXQyXy-VSJa-34-5q_2__3d-4PFkvVwvE-uKNG3m7Yea5TqU5Oj69WO6twL2bzXe6tJqnw9X8uRu7c7Lh5KSLQITENF-trGrrvjleP7ec31jdxGqXRyeX63EooBKxCQZF3GIgYSoFrZRSmBue0y5iqCVvNtuji3MB2vTbl158vVYHMCy2WO4SBzdDpdjtbdZb5MjzDoGf3Hs2TzQHPnv4bLPexBjuXrsufdmdzcgMXCt6BUkxmOi8mx0crnI_bLZDrqOo7x0erA4WbUOLxczBiGBnf6dZtLEN12_tIfneweHe9UMHmS1nm7K56Ne333o9zefdwcFsb39x7Ua73F0d3Lz14st3X3r95osv7x7cavfuLnd20ClSiKlR1f78cnF44E1YXdvBEGo_MJoOQyIMaF5raFNIM3fMw-AMPGsdgFXe_73fb7sdckWzMgwxRATnEN3NCGrpm65TraI6W-xxE3_4R38UEwGhIw6jEMeJElhKMVcRVRGKoUrlGBnZwVOKqlWra1FEqkW2F1utygGRMJcam9TE2EwGAAZCdwOOAcxyEdFqSOdn22GsuVYOPM04h1wNjBIaet-PZgg4PcKVOfRjzq5x1nazztwBnRFxOqQqIHjNJTCrqFUBd5UKpg4uUpGQEMZhO1V-VarUKqUAuI5ZSkWc-MIBApUqIQUkcp-krphSapvw1_6d_9m1vdXx46d_9T_6P_djPr8spuiG6_MeAC5Oz5Gh7_Mw5izZAAFB9KrsOJ0sVdTUXEVrjk1SkVIlUEgxaFF3NjPpe3dTV0QyVTQDgDwMzJO0mAjR1E3BkSfCuIsS8wQN5JiAaMIiMQUDwBA4BDdJMagUICZmQARTCuhmbuJuahNQApBAtfgkL0BEAyIE9BCTI_JkWihVZRtjYOYQycxDjNQQRnT00MZm3rVtd3jz2jw1KcWcaw10dnoZgZ6_dfP46DhGQLCuSymGiBSRUiJQpSmQydGNXAQCFvCYIhNhgNmyQ-ad2Y47hMQcaDZv61AZePrEHMaRCRfLeRnqct7N2-b6_u61g30ZZbvNR2dnRgSIE2w-pcjIbj4VS9R9okukEAysqCDhFQI7RneLIdK0MUIax9yPV6O3UtUQ-1JtYseaBqYQwmaTx1JETJyyiIFzjCEFRgrELjaMue_HYlaJC0JRVZO2DRzQp9-MGjGCm0vNY85DzxRN1NVqlcRxMZ8j-GyxqsOoWrtlFxjNRbQ6gjJ--uEnqxsHzMEctJb5bBfMwCwQa67MDXMjRb16zc5NGGt1pnU_dKvVN9957_s_un82DL3q2eWw3vYy5g8fnmwGpdD94J3H4foBiet2GBpyMFWpUvNw2a_PNw5YzVQltk0pwomdUFRTk9wNTFOTtNam7QCIQjTV6TsrtZjDpADMVYtU4mCmzYzNPefiokU9RoRai5S-70PLw9CPZTSVXPLm4vxwf5X7YTmPVW2TS7tYDKPsHt6opb9xfb8OuWlibELTJARHJC1l2PYlj24qovvXDkIIhIhEAN7N22GQ2Xy3-_8T9Z_BlmVpeh72mbXW3vvYa_LedJWZ5U2bajs93dNmGuOAsQ2MBARGMCIlKCZIihBAE2SAIBiUIFEIkSFRECURAYgEAYgYUiABwhEzGJgezLSbdtVdpquyqrIq7c3rj9t7r_UZ_di3g3_yR0Zm5D15ztl77e973-eZ1FVTm0HpM0VeHZ1xYBBHglglQgL0TdupyXgycwUOyd00CwARU-SgJoCkuR_8ggPTcJhbMqMPHQB3JFApDhfjfHdnQgpo4A6OHC-I8ji4xAUDubi7U2BTRXBEj2k83t06PTkLdVJVjNER_Idxm7qptrZ223WHqaYQS5-3r14-eXgS6godQ4qKVKwQcxkkI8zuAEwDujJEBrdBDs-B1-vOHL_2jVe4wZ39rYf3HgaugJBTwESAqOqI5OQGZgADdEJUwNzNkFj6HFMEG7hQoFmJIhFXiU8PH8y39vo-DyHyAcilqm4WmAf_yQCLcVBTUS_kalZAdFjIltKbFEZSMRkS5-oiPZoDU1f8X_zuqxbDFz_1YSQghBCCA6goEpmZ5mwi5DjwnEgLuQI6mg3P5xdV5uG9NhItxDQAp_vcc0hd34toEWm7FhCL5a5kteHspuhgWi6m2-Tr3Dn40PlIVa2mVZ3MDFwBQHKRrMwUmCGgM2Y1LZqlqEtRp7opjgeHZ1XD67ZfLtfrVbdsS9sXR8xa2r70vSzWXUDIUoix7VpgXK1XSDgZNeZGAAYEQO26mGOWAgA55yLCzMPyI4sU9dV6U1S70pcswcFFDYwZEUCzt906qwYKROwAYjYkfEpWdCTGUV3NmpqQgUmsDMPtUmQ47ospUTDyTrqBeTsIAQjdRb2YFhvCwaA2mcSd7fF0NG5be3zcrtcFAENMTNT13e44japqNoT9HdV4te77LAqghqteNjmbugByPb5_cPLl3_rqKFXzve3VKrs5I7E7AS9PT_tNT4RVlQBgtVqDeqyrKlWrtn33rQfrVR7VjWdnCrEOFCCbHB-fb9qCCderzbpdr1XfP3wvUGyX64gwrpJBZy7H985ncfyHfumn_w__-3_1j_3Kl2Y7k06sy9plZyC8kPcMD1DOiJEv_D-MaK7bVXxyf_fxo-PpeDRqmqBw-_7hcl229_azmrcOoISQqnD_vbt33n33_v17QO31a3uIUDrbdHrw8Gzvia3H7z_49ld_--tf_lZ3_9Hnf-Tzhw8PN-v2-PHxbFyN5_Uf_pWf__I3v_ncjb1pM1M1EH_w4ODg8SOO3vYySaNld46L8_tvv3N8cHy26G6_df-V77w139oHAse22UocUErOuRfTruhktjO7sv_g8f22ywqkGI0qms8AU-u6cV3m_ODeg8f3HxTMq24h2t0_eC80pCBF11THuuLzdRvr2omPT86W3SrEIGBFxTAYjd-6865zffXqlXoU64runZzBKNGovnLjyu98_bXz0_Ot6ejw5DjEpmrGzbg52yybpsq9otGoTilCL3mxXD86PFDHqh4BW9Wk8bQOEUvfgslsXjPSZr3OOY_qSR0rV51PL0UlFt_e2kGw1Iya6bRtV6WIK1Sxnkzm0_nWeGus5qFKo_lWqurpfF410UsfnJpxM5nPFcARDPD09MSRulULTqmqqvk2AAKxGzSTOTN3i6PV0cFoMjtZnK033Xq92b9-q6lqZCo5l6xALKVbrzehqoirzWrFptrlAT8SIkux5XLddXm13pyeHvddW0oupRgKRWpzh4Bdl2Pk6XzU1FUiDEzk0Hc5xWSmMSaOcXiAV1PTPMBGEdncgVz6ntlArbSFgIqUkhVcpVftzQQQQC-6alTMiGOqqhQDOpReRVzFTNQdVRTATc1ETTy3uW87yf2QPdQiXoqKqGiWAgPSGMzAMLC7qoi7uRYmUimuFgKbCriCC8VQNc10Ev_EH_3Sy0_fKIp_6b_5e6eLhVJypoODw-X58uHZqgcQw6quSilgRiEO7nMmchEwpUDFxRHcII2a5elJ3UyBiGNAxkF9BOhxgGn2LdqwDUhmgAQUSaUgX-z6IFApBZnd4SJoIIXIEQmJzE3FCMFMbei2AiCimaBfbGsBqRQjChSiqlHgYUXOde0AnJI5GCBy4CqZKAJkKRyjAyJR1VSD-iqGFDjGpjEpgRisQDEHAA7TyXR1dvzTn_skWbxz__F33ry77teg-MFnn5xOmt3ZdHs61qIh4N7lbXMIIQA6mgZH0TKqYl1X0pbcd67CgUMI7u5iAB6YhhI5AdfjityqFJerVVPVKrpenj-xv7U_b7abUUOwPZmkpo4VR2Z0kGJMgZhNfUjcFMlZZNiCEKKZql7gGQfgBKEPyOsBPi128bYE5pTiYKpR9CzWd9kBRHWTy6LtVm0XUrywLCEOg49sFjkg07rPClBU1b3PGV0TAiuiQuDgZkNpmIhjHSaTsTtayRxIJLsZg0svJevpwSPiWPrepXjRatR0RYyMOWztzvvN2txEREVOHz_SLKXvzW3gFrphGldq3q2Wq9VSCfpcBs9x25YH949EdFPsfN1lxFDFB4fHVQrbu_N21b_6vbdIBYqWmGK36oNryZkC1-NKxIqUGGLu-npUUeIYkAC0KAICk5qJS1s2hlYkIxoiJawIsF1vulxGdU2OA2jQDaWTrEXVcsmEINlSiLntR3VSyaPp2NBTRYFoPB676XhULU8Ws53x7u4cTZsq5W4zmc_PzxaxCk2dwIABm_FYSl-PR0gOJjFVsWowhpzzaDRZLtbz_d28yQHDo4MHDpoo5HVPCFpkvnepruN4PuUqVqNJPZ744KdQ6UvLVQA3JsJBX2oXOB8tfQgRB8CZIyKqqKsSAgIQDnRCG6CThsCBwE20AA5kXnM3R0AEufDU8vCYTswG4q7Ww3Tn6vTK7ttvvMExAiDH4CocAgBwihB5sVxhVVFgsSwlc9OsVwsIUIrBoClGR0IVj6Mq94VTKMWHaIoDmA5_jEBEwbrlhigcn5y32T788gfWi1b7DBjUwJHdQc3NgTkiMjKrWZVqFxtAR4EZgdyNUkC_GJrYIMOLcbVaTS_tjOpRIFR1EQND9KGgBIgBADgyuCGDo_UmQhBSVDAicvQY01AhQKKUkqI7D2Zp79uBJCa995f3L29vTThgrKoQmBBdNCARMZD78H-v5gH60jNy0eLoYsVsGJG7iKgXBOi7TMjmLmbiRkyKaiAihZjUFNBUtes6QBOzFJKZEyETEaKDoZu7Fikp1ZL7EAIihZSoShzCcGXouuxFJWeRnLOpOCKfHJ9vuvabP3g7MT9146qaU-TiYuSr1YY45Db3fRbTg7NNCAmQwQk5kKNkKVmrFLuuDMVcJFqse05Bzeq6kqEKPXTcY9RcEAkQR1XtBiri7i7eacku2bXyWopu-t4IikORUkRKUQBzM7Ohy-sc2G3gZRtj1OEG74BAxa2oimpRdR5EAGgO6oNaEMh8XKXZqO6XRcyKZXGJiTmwmua-UID1sj1bZwNbd91ykxfLfHC8AiJHyqX0ORcRJzpdrruiktJf_q__226xCVU1mk2Wq5WBZSkp1YTUrtegJuqj2Vg0EzOgE_Pp6XlVxZOTI9S8Xi22dqq-695599HpKh-vN-eLjgOePl60OdM89iVfmV0eTaqa3PJ6sVgsHq4_-Oyzf-7f-9U__a__sQ9_8PlcqHdWCBQTIwUiFUV3czU1AEOEAawMgz2OHQGJq1XRjdqtW9eA0My-_fpbP_ETHy2Ah2ebxbp_-_2D-eWtg7PFsmuzkqpmWX32s5-tR01BHM8nCf0Ry9PPPHn55uVPfPDlr_7ON49PHs52dtCrZSePzxbf__4PVqe-LOWdw4er8_7g4NHmtMt58-UffP_2vcfvPjpuQ__u3aOD1bInWi5WV7dm_WbjBSzT-dkqVZUjAqM7dH0PzCL50eGjs8Vxt1mbysPHDx9uNifr0y53RkTGEfTSuGLTxXpT5nh0tphe3kbnqqbc5jrWz37q5WoyPjk7vbS_v3Vpp6qjSL7-5LXdm9ea7aZqqqtP7O3N95-4teulL-1Ki7zyu2_sv_j01mz61oODp569fm-zuLJ_1QHv3LtfTcbb8_nV2byJtFkvkXE0nU5n0_FoxKluV507TmeT-WwGbiaKyDGEnPuu31y6PO_7_mxxSCDb21MmmI5rQiPQ6aTev3x1vTypZ1uT6ahrV-badstqnCiiM3RaDO388HEaj5rJaECFaC51VcUm3njm2awQqgYxmuTUBEJUBA7YjEeac4hRc88pWG7f-ebX5tevXL561bV06_XRo8P9aze3J5OKSdr1D1F4stm09XTMIb3xtW9uzyZNTFXFbh2C574rJS_Olg40RHrH01FVJUetm-RgTVPXVRVCyF2PhFyRubrherVKgYp04p5L6Uvpu9K2Yg7OUHIpJoiNFGUa4JJapEOT0hdzQTJi2Cw3pS86nOjdcxYxHej-xIzkBkaM5upacrdRK0WLuTK5SY8MYkVcmWoEQHPNeQh7uAyYf0OAi7Wtm6lwCMN1zB3AMITo6kRYpRRS-PCHPvwTn_44VfXf-af__J_8zm8XZCMyhiIqqqfLVQuw0qxSYh0IiAClVwDyIoGIkQb-KXKkENScGZG5acaAKO6iKiWjOxgTRnYgt4CDd54ACA0Q0e2HkmO4UKIjsbpRioPwB8HRLYYBtGdE6K4x1aqKHN1B1QAhhIAIxGDgwOzujsAUTJ04AEc3ZwJmcoK6akKIaci9EMYU0NH9gmPrNphWnBDjAPYhSimN6no8bq7t7b5w61oif-W199Zt9zu_--2-bwPRh5--2a7OU6Qrl3dDjATQNIkZiXBrNh2Paxi8nwbbs1FATiEMkgcGTEibfh2rCs3RoGgRdQxobLP5DFybUZM3Mh3X8wS7s8gqkyaUnAGRMICDmA9HDkYydVFDIuYLkxYhKgCgDWsrBDRXMB8-fmaw3rRACI4OQIS571NiM237nN2LEwyzbzBF7NWzmagSQgqEqgOqjgOfbjpgNtXS59K2A9texA2xldKWnLUYGCIsNutetbgaas4ZAXIvogWCFenadkMxFsmcqscPD9abztRiDOjWtSt3rCYzBLRifduBAzC2bSdWihQbNNiBF3m9vb9z8viUOfSlV_fTxWI0Hi-X60tXr56vVrEeLdfd6-89yuaUYpslEy0XHV_-xE-aGzoYq6iJqpnXEbs2E0K33qhaSCkG7vpMSBwJmdaLzTDBHbZa7h5DzKUAmWhJMbjBKNVtl1MkEdu9tmW9YIBiWopyoBCrukEvOholMwyJQWG5bpmwTrFdd4EJmfNaqsSaOysi6q46m02ODs4QvOSCBLn0qaqlSAppPJoUkVSF9XLZpMrM66bqztej-US1Dym0m4yIqalyJ86Q-xJCqkZN7oqLpbp2dUCQkilU7iaiw7kKhs2aKMc0CLwoJXcD95AqH8CodmG6wsHDwgwIIVauhoFcLKRa3RBxQJ0hAiEOybPBZ-JQwIwwXX7-yX69Pnx0GOtqYKcbWCACcM2FEzsjp4kTtsslgKvIaHu6OjweNHIUopm7KxEj03Kdd6_tnZ8uY4zIYKI0eJqBkLkthVN0kyZWVPNnf-RjB49OXn3t9nLdhsDIIEXcdeg2EA02VhwMuKFKue85JgTiQKJGiMOV14FUIdaJYnIRRN7Z2VmuFgYGbqmqwBRQTdzp4ioEZj8MdwKAOZoZABKGAIAEOLBZDQAcHchUKAQc9qUBWi4ffea5xer8zt1HpYiIMkHuu0CUS3ELgMBIYlJKwcDD4U9MzZRDAnAkArUYk5siETGhg7lcCJtV0QGRTIwCgQ5jABx-4Bh4EDwBIiG7e4yRGVNdE2EzHqspuoVYmQkRO1mKydVKLn0pGDBwYHMiYByImfqR559CkXunq-V6k3sT997MHIs4BFq1najn4mqGIfQlM0GkIKUwkiGqgZqWLDFGdAL3gW1loK5DvhZFfnhxRBzMwQaQmMUVGUWVIYhqCAgGJQtzGB59hyK-FEVwc6tixIGdNUzJCPyH3XcfPjnI6gYAIbL5wCVzAKBA7m6KalaPq_VqgxSKWt2M3JQDM4c6xVQlNd20mQJ34l1XgKGo9aUoQs65F0lEXd_N51uvvPX2__s_-6t7W5PJfKvanZ4v1lKMEAGgXa26xRKJKMXJdLZYnE1HYxELIa6W64jx-OQ0EJcS9_fH58dno1FzdHyaO3Cw5apQwNUm17G2Is0klW7TLdc18x__E1_6_b_wxU987EVH64oWRDDkyAgw6OQInXjwYCIPlkDw4fuPgcyNA7_5_sO93dmlrW1iRjeg8He__M3Pf_wl0nRwtPq1b33j8vzS7Tvvhz5_8KVnpNdlp5j5-q1ru0_f_I3f-OdiJcWYzb3HjYZN3uzuzr742c-frdc3bj11eP_YiVMzW_d9Ren2e-98-Z985dpTTxwvFpz7KDwe1ePnrhydr1dH57d2oc_8zp13V93mzsHBl7_xyr277y1PHp6dLyqiIrI4X6ArMjWJkf3FD3w4b3pw6Nt1WZ5vbc93tmY3bz55Zb4VU7z__qGW0kmvm06TXZ9f5yqtVpsUJ8cHj1JV37xxa3N2dHqy_PznvvDWWz9g9MCcwhhdyvGh9Png4EQ2-eDRYb_qvBQomREO3np3Z2tnbzS-fuXa6uz44eHxzRu3mGnZtuQyqaqmafpus-o2VdVUkdu294AqzgyXdy-RaYyYYshdtzudckhEagIIeHx03KTxbD5erVa9FDNz1VQ1zFXX91lk0ky7ft3mDjFWVQKHvu_RLYWgpiCQmjFH7lYrRG1X7Xh-qWrqyWwOpqFKko0CA5F1QkimqqKIVjYtMYJC7ldnD9-79fwHZ5f2CbQ3bc8X41lDTueniypyEe3Wx00zioE27Ub68sInPrZcrAzRBAIDI5fcpzopeB1jTNVk3JQsKVa5z8xYxyoyq6qUrG6iBogGuFltTCA2yVUDookMAsvNpu9LJuZ125e-VS25y0MHtxR1dXVFJxNzhyKWu2xFL2YAiCrCSCoaA2UVETFzDrHvOyRUUy0K4CIFEIuKmLmbSXbzgcoIA3ES3M0HEnQpBRwHC5SahhgHiwsCUQBkDhwM8dLe7r_9q3-0Gs9__be-8n_9f_7lWNdKFRGLCoGR-9al5ld-4ef_zq9_-fHxQqR4FkQonfLQtXUlQKQgec1cIwBGcvfcd9t7lze5N_dUBVB1NANC4uEY6m6AREiIwyAaiNAMEDCEMKTGQwgqFlJULabGHAcxIri5ATE7sLkyEwCYKRGHEN0sECGgiKbRyKRDYuRh6sdIEAgDoqv6oP1hpiH374iMBMAxmjtGJgQOUYpyCC4SU80ppCqNm9FsbD_7qQ9fubTLAKfW3X5wvFy1t5641lR1YNz0nUNYtUXUTJVD7HNxIsTI5PWodgCKjG45l9G4GW6-bh5CKGKTWT00HErJ21uzTZubpjHJEXx_Z_aBp69uNyESL04Ws-2Ju-YsHDhxMEQtpa4i2ICCciRUG8D0xIADDxbAY4xuzox9JzGlEKjb5BA5iw1OhL7vGQGJZxWfr_NQLVRzcVgs2r6IR-5EV-vWdOCIoPQlNEFEASGXCw1N12d14MAAJGbAvGp7cynFIoecBUBNVYbjtTgz5rYgAUTKbeYYJGfp-3o0Eskm2rWbZtaAAwFtzpfVqHGibrUiQhOPoya3nTn2mzZUgYgMAIlG85mjzKaTq3uXVssWiY5Ozqqm-dhTN08Wq7fuPEiRppNpt24DBm318OB8Z1rzzc__fCmiZiVLLwJg4OZgSKgiViTFsFmsOcZSCgABYN-1gbkKsWtbRDQ3ckwxdF1X1JCQAMw0m8QYTESy1ZOoRbs2c2AyYwR1u3ptN7e9ucUQUAqBxYoNiAOmKuYs050ZM0kWQ-IYmvEo9x0SVFUMKbj7pK7rulbV3HUUcN125j6djtvVhmOoJ2MiKNkoYO7zZD4FB1N118nleV60TJI3bb9u3QFNihTpCwVmQleZ8rR4BgNkcnVE5Jjch7RaAAwI5g5I7BcQdQQgDGG4szMzGBBHQHCRwZIwnBYReVB1OGDAAARgSiGo0dVbLxrJ6eFpt9lwpNJ2IQYENC1cpYAsRYAxVnU9ma9WCzKNIQIjWvGuIMIgd0UCrqOLVM0kG-zsbp8dLcaThohy3zGCiQzCPOeIITB6Ckms_bmf-uI7dx68_tZtR6IQqlHdd9ndwCwMCgE3lcLEqk5MzKF0mZgwhEFObqZAxDEBEIdg3SY24fzgUAm3dy_3fWsm4O5maIhEXEVVYCIyMPOQgoGDQwgNAqhhqmsbqM8hwSBmB40xuliskyMC0XjULE_Pfvqznw4ub75524z7vkcgG-QrwOTGRAYKg84G0M2qNC59doDBpO7uDERE6qYGRBypchVEirFSFTejFGMMpuZuhNzE8WCdFC_jZt7lvkpJwVOq6xSJaFhShsClL0AE6IGjikQKwyY0cqiqWKUQiMw1BELkVPHWrLk0ayahefPoYL3JfVd6EUJGRCZiJkdYbzoRAcK-71WtL3lvMinmqgIUsomDDTlTKRKYHD0wuhiao1HJEhhTqhLjaNKAuUnpRYaTqrsDgBlUFYNDZCZGRFS3mILK8DjkIbAM2G-iKsXBE-TqRoZIBl6Kutjwng47Ahkm33EQ2EMuEhjVTPpc1XUx7XIG917UzJjQCVR9uWwdwAC7vvRFBxUzXQzsPIWqyyVxFKI_9x_-J5i7-c4uxthnIITNYj2ZjdtNV_r18CTTTEcBsR7VmjVGLp2ggWZZdt2ormfzhiNFpnbTbdbd-WKFSMtluz0bO5pK7tZrEnnu6u6__Md_5Wd_5guXplNE7PJAdAjs4GDkaGDgYCZEOBjDgVBUf6hZCACgrjGwK0guLz15XUU3y2xabr_3aHtSX72y2-eyWpdXvvrtTz5369Fy8-mPPLdoPS833_nWq6vHJ9Vk9P756sHdBw_vH8TA5vLgvUe_9-c-c3Z4sj48vnPn7ldf-ea3v3_7jddfX56etuv1yfv3Oykf-tgzb3__zZc_9oE3X3uYl3J0cvbOq9-5-9rtN7_x3fffP3j9lXdMSrdZl-Vme1R9_KVnPvjBFz_y0U_ceOLG1tZeV-yt195hDuCGYAr-gQ-__PjRQ0ZKFPujVT2f7-zsP7l_8_reFdBy__33J0x9JyrcTGC3uXLt6qXHdw4w8tH9w2ZUNzsf6k8PTo8ff_gjL9195z1XOTk9zav-8NH9xHh-eq6o-_vT0sknPvPy0f1Hnbr2OmrShz75obfffud0tXj43qNuuXr37nvbs_Fsdunw7HhcTziFVFWlaC-lrtNoNGo3natb7_N5PZ9WXnorVnJBl535zMlzn83t-PHRZrW-de06Mi8WCwMqRUeTpqrJcymlT1WzNWlWy5WazMdjDgEiMoXN-ZKJU536tsx35znnEDj3BZlGo1EYjRxx6-peNZ1pthRjqipH5hAoMJpVk1F7fsZVBBUEqGY7zGMFlTYDYrdcUSBiaM9XVZPKuljpd564ppvVyfHp1SeuGtdZ-8OzdUzB3ZpUtW3HMYB7VaVYpUBQJJesqUpVCEi0WrUwWGExGDihl75LCfOia-qaYwADdLQiTKF3FbW-7wCwlBKrGIByn8UspMAxiOTAIXeldH2IPJBtBlQ_mJeSI5EUyUVcDQxNC0dCAFeTLIFqNXXUIsIhQJ95SIq6B2YzRXQa1EPqHNjdVNVN3ISZtaghmikiEVlKiZB35_P_4E__qlfN_-U__X_8vd_49fUmKyfkkHsBdnJo6mbvxv4nX37pN_7ZNxbLXq24Wun6ENjN3JWYEcnNiKvhNqelR2dQEfTxdKfrVqA2ODEdwd1SiCBioKJCxIMy08UdjIYRbiBANDFmNv8hoZ_R3VOqSikAOHAh3Z0DD2ShgZ3KIQ4KTgQYBszEbCUPhLUY02AoYmYFQERkiiHZD0fgKUQVc4KQIscIAEzEkUOK7hgjp6qaj8c7W-Or4_iLP_mZiuvcl43ig6OzNnd3br__iZeRHR0OAAEAAElEQVQ_2NTp_oOHiz6neizuYMDEappiNCtVDAA-3KkJrK5rzZmJY-RSjIlDio7uzgQoRZsmVXUkcBOZjRtxvbK7vbc1ZvetrREzn50uJ-Nmaz7KvajoZFw3TW2iMUZEcHUfbGriA1HJBwjdgFMCENM6RRMnRkRerDc4yJYDMTGCF4c-FzBoOxX30bhZbnI2O111bbEsIiKiVqU4HlUusF5v-qIhxSF3xDF2bUlVTClkMSsmRUFKn0tVxz4LkpsNSQs105BwKG22y7W7lD7nrg8pqhQCym2vUnLb5y6rOSPnvo2p6tYb14yUFMnBq2ZUui7VqYhw4sn2rrjuX7u8Plt94Pmb7909GY3j4cmZmD1eLuqQAH370nYp3dZkyoidquR-2tR86cNfxBBzyWhmpcTApcvuUDrhRGBa-j6N6pwLBSamvusRofTFyG1ASjFFCkW0lMKMkTlWVSkKQO7KITpCE6P0ZTwZrVab6da877pm1JA6qXKkFJjQS58JUMRKUTev6rprOxWJEVPTANH52XlKabVYz2Yzs2ENiJJFSj_bmoUQxYAQS9_VqSqqUkpf2mqUpPRNMzp6eDLZmW9vbS3P21EIXS4c2JEMkYlDlcwEAUOsSpeRQDSHUA06ADVlDjYQx9xVLKZkJoP51QfrU0wDmoCZ3XXAmQ8JHzd1G9o5FqpqYIAAOBCbCTGA0c71a-Od2eH9e90mDxkJAAdHdQ2xyl2PCFXdqAgQInIab7WbVZWSbjquUr9aX7hViTAQmMeYSjFAj-MmVnGz6mJVA5iWHAjcLAypbrV6NgWzWT1dLs6-9Is_--jB4Ws_uG2OGAIwm6t0HSEGYgd3N2QCMyJkTmYCg7tlCPe7gTmFgO5IHAKZuIoQAqCdnRztX78FRH23AXJmRiYzd3OOCc3APVZ17vpBJg4OQAQiHMgVRY0Dm0HkSOox1aqFUmSOo1EzvTX74kc-9d47b__g7dttn40DMhhiyX2M7ObEKEUvQKUD8A6dQ5CSBwTYBTkIANB7ESQGMHPLpsREAJFDzhpTwkAmShwANMaECCIWq0g8sPWQkao6uRsxOQAzc4pd24cY8GIrDFUVmTnFmCJT4tLnGDjFGJmbgFXi05PFi8_e-MZbdxBpeEGajcGZ2N2qqh4g-mrKgc0h9yW7G1oxG0QcbmBFAJwwFJdpM-rangi5ijGxAzR1HFXMHM0sRDY3Zs65pJBgEGoymRRwFzMmdrQm1aKq5oQ8yKpjiMPbxYgAUEpxAABycNeL3yQcrG-ARDhM88wjRzWJTKNRvem6kELJCoxFJQSu6oTDBaG3nBWQc7Gh_62m4gaIJZuqMlNpe-QwnW__jf_f33vtm9_e37tEddOWoZmnmKWZjLq-y112ldTwZDRSs_l01vXZsrVtr2aWtVspBay3mj6jgW82-ezkLNTJVJ1t3ft609tq86mPv_wn_5U__PlP_chkOlKzbKhGCCxmIoI_tFwDOuHgdgR0RABRJ8SATIOmFMlNi1jpu_2deVfy8eHibL159fadp5-4WrL0RnG7-T__2t8-W_TX9y_fufO4U-_H8Ld-7X_45u989eHhoy__o6_dfuOtw3t3TXMVI6hwpG9889UHD06u7-1_57VXf_pzn_3v_-v_8ZOf-8zr3_r2waP7h2fnr33_vUf3Ds-W51_-x__k0XuPjk4fdKslxSY08dL-tV_6xZ-0bFdu7v_oj36qb1uDcO369a3Z9t7Ozttvv7tebo5WZ0ePDwkGq4Oo2dWr199-_Q1O1XRne7VYLXLuu_Xjh-9f2pm_d--913_wdmzi6enRdLw9Hs9n1XR7Z-vtN99t-7xp1zHSNNRdf-ruN27czKs21fFkcaYIIrkZVScnq8lkPN0er1f51gtXTu6fXb559flPvnhy_-xHfvqnJqPxO7ffvfHk1Xdfe2cymTw6eNzsbWWxrs87u_uPHh1cu3HjvffujyazkNJkOj09OppvNaMqjUajcV0Xs-PzRUKu68oFFqsNUVyuu826BYRLe_u92FnfC1NQ353MY0rnq7M-y_UbT-W87vq1mMaqASFFd8Juuaknkxixb7tiHppRTCFLdsAY09bWbt92dTMab2_lrqPEuROVwnXVdV1MNcdY1m0IsWu71enh1aefLlnbsjm--35skvY5xlByhwSxor7rS5bL1586OzlYnB7fev6F1WI5noxX61UdQjMZA-Bm3Y8nI1CMKZpYV4QDWZE6RkBKVTLXyAmROIXl-SrEFCIjBQqBkNwVEc2pK6VXXW3WTEQcixbmqGruQxPKHdEdxbTkMiylARGAUxUBXOWCMYgIgKCmmouXguAqaiKqKtojmpgRkrYdA7iagxMDqKrD4FRxVzcwVxymboRDhAH-J3kWBIS6riaT0Z__s3_y1lNX_vS_8x-9-87t3ElXIBAWu4hnsyMCvfTRD42VvvK7r67aXFysCDOqKiBkdzQfTIiDu9MHpyEgJ2oXp_vXrrbrVTGPMSGhmDKzZ6nr2hwczVQRA4KHGEyUGIkJHJkjDjnAIUaMoGqDt5aYSu6RCAnMh0cdB7NY11qEYxwOvBzYTMEtViNTJ3bi4AYpNQYEyCGkYeELAMwBiQwwxghEQztAzQZHZayrQBSbOlbVeDwiU4rlF378MzeuXK0wfP_efY9VSOndt--lhjS3zz1588re9u237xqiIwx9XHPPImZe16lYYQqSCxNRCKFiBWhG0RzqKhCxI9RNDaromBK7AkciJtWewT724k1wGE9inwuziyICEmCVEhGGFIemx2CTHMLJg4h28LQOOKYYAxENLtHAcUj_d1md0Byz5Ml03K1LCFSycAge8GyxceKsbm4CcHS2RsBeJaRUck4hJQqIcHq2UTQ167J1Jbt5VUcTy50VsaJFJYvJuu0Cx1IKuPaiosVUXE30okepIqTm7qGqpFhsaiQ2MQ4sfUbHkIJm6VXXi2VKKY0akxLrRnKpmyqmVEqfqihaYj3WYimGzdkaYmzX_fHZ4uGDe5s-b3J-_a139vd2r-5fAvOHR0eT2fjg5DwwzHYmvP-x39OvNwPoNEbKbV9UwZwjultetwY2tEykFBdT0UHXVXpBJhEdYB6DRBrAU1X1XVuNGiSQohSidFlUkZGBBwUpkjV1mNZp1FDg0HcdVTFWUYuoWV1VIdFm3YbAJfdNqLMKIokaoKWUOHIpueR2NJ30uQMiN1-3vZk0VWUik9mMGPvcc6iOD0-m29tt26aUVL3rh7x1jqmqJxOM4UJfagaAPjTmESRnDOR6weFCIg7RVcGdGIjZ3C-EvkxDqc_cgAbqFjqgqTEzEYspByZi9cGUEgeTbkjRXZGREdUZKSwOj8wVB7iQCrohIlCgFAlBxJmDq5q5u-08cf306IjdU4o5b1SVEQnZHJDZnWJdqxQ1ryYzQF-fnSMiuFiRwIDIbgoY-qxhOkLR4ASBfvYnf_z2W----sY7CuREIlnVTNWKEICacgrgXoogAnFwdARHZnUMHBBAigCCuxMxp6Bdy1UCYiKoAp88fjiezEaT7Zx7UwPTECsXD4EAjIhFhCIFBwMY6sEcggPCEKcgMjVHMxUHSnWt5upap3o-2b62e7ldrRXz46MTLz3GRnpR0aGJMjS1xS0SD37fgSHtZirKKQ7jA1CLVRr-PUJHAgAnZDBDgFAlUx3Vo2EhEFLiEMwshoSIgYO5EVCIXKcKgJCp7zMgEjGCg7m7BGI3qKp6EM6tVus-l5QCuE1HzaRq4qSejetR4is7u-er1ao3A1IHdIuR0ajrJcQA6GQornLhqlRXZcbVqhcdoqE4TENUVLQgOwdiCsgUUhhyqEwMgRw9RDQbKu_OxE4OgEUlxGCuMUQU8OFuSKTq5kpMxEA2lKuGTwUxBxEZ2t2mA__UiLiIIAUVwQE2A4AATDQZNTmLiKaQQgwny8WkaWIMqrDc9M445L5ykaG4rIYONqm3xHo3JR6yeJDGk8PHR__FX_0bAWh-eXe1yuoUIqE7Objb-flpRHSTZtzkIs14RpFMdHm2MjEiMhEkTNPReHcknXSrtm8zOqSqWizbzZI17n7pJz_8r_7RL33hR18eV1GG5rq5IQ6AL3eXIugOCIHZbBhEUYwBDcydGZlpcH1wJEQvogo-Gzebtn_9zsNY16-8-oPJfHzt2qW_83e_Mt7ZevXNe7GHX_rsy2HcKMLdO3f-x__yH2Jpte_GPPrS_-qX5uPp0cMHBji4LLLYqK4966tv_uCpp29d_9hT15998jf_8dc_-1M_FprZbGtWB_6lP_R7v_3V77nLL_7BX9q_fOPJj3zs-eeektzuXrsWJvXDuw_q6eSF55596_bt7Sv7Tz59uV0tL23tPj49mIxm63Zz550HiDBQHwjpwx_7xMnyNEZ-fHjWnS-LezOdGZS9_b31Jr9z-91nn3u2XbZVijeeuCor3b08e_z49Oh8UVQ5Ik9Ge7u7J6fn5yfnk6YpRRabTsQww-_9-Z96-OCBQWHFS5e2bty68fjuwzsPHrz35oOubL75jW_evHljVMUbt57ans_Pzs6lz69957vjZg5oUPx8va4SVykd3D2IVX1pf48R1svzrtiVS1uR4gcu33hwcsREdV0lYBM3lKppzk9Xaj4dT7a2LnWlOzk5jQQV0Nb23M3vn5968UuXd08PTzaKIcYYiWOQ3FPizfmqGTdcj_qu89zNtnbMHZFjlWKMTd2oCJLvXb3GMThwiCHEhHEAx1Wu5iYxsGt5_OjRaH4ZCcfzWem6vu3RjBA0F7_gaplbwUjnxydPP_88ethsNiGE2Xh0dHa6u7vV91IFokhNFUtfsmQG0qwppR-emVDcVLTk4maprrq2nc1mTMQBS86CgExd1w2zBuQkpcQqxip1XYuAKUZA5xSlFDUrXWamPmdgSikOUMssRbQgI4CXoqLKgdhNi6h7LsJEOBA_CbUImjLxcAo3KxijgVMgYgJ15jCYy9SEfLAMAgca5LhguQopNeHf_fP_1pPXrv37_95_9IPXXlV1RiRAAx-kp0SemBjo2o1ruNl8_527uZhYMTGK5I6AaEjIziEQs-ZCgaXIMOxAIijd8vh099qN5fm5mDGSi7kVRxApdTMuXT9UTaWUYTavUsCdmNUNAR0czMEtVCMTVSnE0d1DYhWtqhqAVDVe8D1hMAqrGbgj8cUinQANcZB-IYTAP7yzGQzVVY4hxsEx7ORIHENAdGAiColDXSd3TalJKaDL1tb4Q89c-aUvfhod3r979O__tX9wbb5z8_nrv_u171azybu37370gx-oGbPkZdtVo0ayEJG7p5rHTcUOkZiZ0bGqAwEWESKu61hEmhQUgBxNPMVoakPGQYvUVUrBN-erZ25cYcKAcHq8TE19AVYBQITIzEwIJLkAIjEWNR_k0AYyxEoJmBkBiaDv27qqTZ0QN7lQDA5u5kQcLmqCYOKOaMybom2Xza3tRR1Dqi4GQ0WIaX9vnrO2XY-Je1EnlGLn50tzrzi6w6YUJei6rAir1drVipaQWGyYgkpp-1QlK9Y0dbdZqRQrqu4YGADFjEMANDfTYqEKyNRuOkDsV0sEdvC-zfVsyoR1Mx7OcrntmYlSRPTRaNRvNk1Ku5d3X3vttU3XrbuumsxTCI8enWzvzKYxUYirdvPG-w9Oz1cHD48JQNQcXS0LgZt6YERXl5JXLQz3ThEX8VzMSmBG9MBMaC5CANZn6XtXFS2IaKbE3G-6vivIYbNcVaOURYhYAEOIaAJq_aJnjgqM5s0olZwbDheCN2amMB43sU6j0UjJm1TnrhvVCc1DCJtVy8hVqleLVYh1iBwC784m6BY45Czr5TqEijlWVdjemZ0eno_GIySsRk2I1EzH1XjkbpuzhWx6ZiaHlFJqaghYitQpjsYj0SG_aKDm6m6OTO4OyOo-2DvMQM2MAAIZoA3nMANApBgc0QbKtzkQcSAzcRNgguF9NkBk5BSY-_UqBOSUfODagqEKOWrRvm0VaaAFA7iCpXpUNmtXaHMuItYLilkWdySKMgi_xAiAEatUg0LiFEMyNQAwgJLNnIAwVZFUA0Rn2NvZ6nJXcoFSUiICIwTQwgghJWACpKG_TIHVXbQMrWYzRTdRGXaXgDDgkzmwqVkppRM1lmKxSufHj0-OH07mu9OtHUp1zpkiDqB5MzUwBLIQcxZDB_MB2Drs83xoTnAsnlXNAV2NHDar1dliddL1_-jLX_-ln_nJP_IHfzkhumZki4lDYETKRR2oZJeBwuYGiADGA34SwEyHX60A-qBhYBcIyFoyIpqDiTKRiqaQiMkGMhwAEqQqqaj7xXvVbdoQk-RCDOAGWckQ3EsvZk7M7uDow8DYzV19-_KUE7WaV6v1su-ViTjOpjMEms7GgQmc1dEQnWC1bvs-D6ZMKcXUCFjFpVcDFJU2905QxNy8adJ41PgwGmJmZu1LnUJIQdxFxFW1eHCs64qZgSEXEVVE6PvsBqbqSFbc1dkZgYDJANxYHUQNnFS163MpxRz6nIsYOIBjjMnMmYJKQaRiJqoYGADUYN3nrs1NU5u5ilUcGQkMRJwcRaGYb3rpiojqRW4N6HR9vslF3A1puWwdGYH_2n_5Nyv1_St7o61Z13ZVRChufQ6R1-cr63p04NRgJAWqm7pdtX2XVQsCjiY1jaKzjkbj7qir66SqJXdt25fsH3jh2f_4__Sr_9Vf-ON_-Gd_bL7ViKsqAsfIAYjdXHIxN1dzQHUTVQEbMk6O4ObASIxoHpgCERGpCprHEEajVNR-65U31n2vSi2GyWT0D__5K49Oz6dNeumpy7_4Uz8y3duajSdP3rxZh_SZL778xnff7zZ9NvrQk893Hq4-87z1GTSzG5j0_ebgwYOTuw_--d__x3_hT_8nz33wuT_5v_tjX_3Kazd-7HPPPPfkjacvf-Xr3__MT_8eCOP333s82dl7_RvffvTOu8d92dkdt-vN1adu1qmKdRxV1agai4Q2W196cKzYK2JCdxUA58AKxpGrUVX68sKLz0puRzWO6qilvHX7XTOJrLOtyXhSdW1Xp1E1qZvReD5t9i7vNaMawDeL41ZSu1hd2tuliI8PHgU0aTdbO7PbD--vj9fnj0-K2sN7D7_-5a9cf2p_a76VYhOIEwBXHAK-_tr395-4eu3G9cXJ43nyxb07y_tHN569xkW6Te43_aX9nVhX791534B3Ll8r0n_zle-tc7l9erq3e-nhyclivW5NR019frJJGC5du_T-3YP7R0el6565eevZp26dbc431mnpp5PJlen0-OzIMe3duG7e574NIVkno-m8W3VVXUuW3G7m2zt9W9bLZYhxe2eb0Q-PD5brpbkx0nq5unLt6tXrV5985tnt3b3JdHt2-epG3OrUdaYGoNYeP3p4-zsoKiqYUnYITYUxpbpOdWNIbtpuNltbu8Thd3_nnzaTFAJNxxMV5YK5L_OtaaiTqJ6vNr0XJlYwSlykuOPwjcpFSynSl6aqUwqX9vdDjKoqRUU89yVLBgQ1MQM1IUZpCyE6YuCQqkSB2tXGEMyEIysCJDaAi9m-XQCsL4KvrsSsqgYAFMwwVlFdzVxUIgQEB8CSCyAgo6uZKhGYWemyg4EVRtCSGckJiSBUwU1VVaWgI1U8qnh3ne68du_73_4uiASHmgnVEUGsMGM1GoUUwexnfs9nV6vO1RmBL4gwwFSZgJsR8jBO5yo6goMSMxBaFuQG3U8f3W9SSDGoWoqMjoCcFUopw9G29D0Rlb53BApsg-NTVc2QGRnVfEhyUkqqmZnNgAOrGqLHmHIuSISIMUZwJTAkBDCKwQnNFEFTasCRyXPXoTujow3lRaRA6uqOITG4u2ozmoARICEhRVyuV4EjR0ijeHn_0v5-_bGnrqcUgfC7b723m-A3_-m_aKqRi2zOV9XO6Df-xVdCSi9_8HkyawD39nbm0yZFYPNZUwemKnAkIsPIvD2uIoeK2XqFfJFdCoEBJESKFYVE5jIejfpuU9ejJ27sBbSAXvqyf32HHIk5ILlZnSpT3bRd13U4cOqKuvrgszM3M6dATESOIRAj1rGhoXblRkxFFYCGfiY6hkDmVNWJmbtWijs16WSxXnVlncUJgXBU18hchdR3EiKhY6TAxF2XN90mMJe-9CVXFMDxotDsxkxUEQRStQE-GAKFFFGKad_3XYghxUjEJmgZxZVjLH2u52MjjKPQnS1Wp4vcdVa6ajJ1K4QQYyA2AFidH4eqHm3NQh1G8y0tWk_G5lpPprffuVfcq5T6zWZ7e69pxoiwc3X39tv3luuuZDg8Ot_bnl_Zm2_tjshECRzMTYWkgGpuMwJYVgQDM8YAItp2AIbOue1FxFwRCZCYgNxcjYlDCKLiDv2mFLkg-HKKbd9zoJxls1mmBh0sVWH70oy1WCnT3RocJlV9drrocoeAUnLX9U3T5D4Tc5HMAVOKXddO59N20-3s7lLgmKoQU859xKpk7bJMp1ORPhIh4tn5iYicnizq8biuExEh09Ax0FLMcbVskQEQVKyaTQfbFwHGui5O5liPxsjBAUOVAAkZY5UUmQIPhDJOVaobAOKQnAgQEZFjAPAQEpg5gQ-EP-ZQVSZeNw04MDMREXFgBkRTc3QgyEUpNMzmpujAMcQQBl35wK8ppVcHDmm-u7c8O6lTjIHVxLOAygWniTRGMjOTAgRmQkCl7zgEKxnBCSiEqADAQ5-VXVWtqJRbLz5Tit57eFjVFQIyQkUhMQ_XTaCIREzMwygG0UWYAzIQAhEQOoUwoFdDCOiYc2EORBQSIpohiGisIjssjx617boaT-JkYogcCN1jTMwBAEKKxEzu6qogAO6qCjo0UAGUMJmrmnZtT4iAcPLocDwl0-4_-yt_6_add7_087-vIYqIbobuXswAxSREJMZQxYupteEAQtWcI1diBoEVJDAzgZnYsMpAVnUKwxo3lpKdgJBtSOG4DvL2qqnAEAhUtZjm3BITmoMZgalY4oqYXR3R2_W6b3MpZRhKcQybleZe-yK5yGLZPTw43t-Z9quMgZeLNRD0pm3ue7cqBGSTXIYtcEIGcQInoL5zpkhMYKjF0C6ckWaugxoRVHIXY5SioODqJgURTLWImBkT9V3HSEV0CK6k0ACgqnIAMBRVQnQxIFLRPos6FC0OgO4wNNyB1NwQBNTckVlVmJgZAiERmIiUUlWhSWFnexZTCCk6YlPX4Dgs6wCxXXeLVd8V7YuKOCCLaN_1qhkcxb1tlVIVm_G3X3n1B2_cpjqJwepoU6XE5CEYI6oLYGEkRxPw0sn21lT6DYIWzWrem2iBbpPHFRNmd12drsjxqZs3_o9_9t_4i3_-3_4z__r_8ubOvCIyY8IqUSKiMBjBtRDqUG5Q10F0ZgZmF9hTdkgxujoDhsCgTgBMwETgKKLtRt668_jN2_eeunrt-Pz0W1_-1qJvv_zVV-px5BTrGCTr9159O6hR2dB092___d_983_x37p8_ZZj-U__739xtHP5-99_nTiUvoAr5eytvfiFn_jEF38qzad1k_7z__D_9sKVZ5-6voVHB7uX5k899_xqub7xzFOW_f033957cvbCR29uXdp5YmdvNN2KMTWjJnIUXxuaWOnazfnhSd8t97a2GLyZjGLEEChUbOAmxUwns4k5Hh08mO9tVbE6Ozjq2340ahaL87Z0ue3COBUqK1k_fP_O4dE98bI4O1brcu5Ojg952grCqI7nZ2dPP_X0pb2dJsS8aduz1aWrV3avXV6LqZWnnn_myZdfHE2niq7K7aId7eyq0nxn-86ddyyGuLWzff25s5PT5ers1__bf3h-cvS13_xnj-7dPTk88LwO3WazWBDArau3rl--dnJyct6uimjAsFrnUvS0lK1LWwieiK5fu_T48fF333jjrbdvX55vjzGdnq_W4mnSXL5yeZzCwcM7t27eGsfq5PFR6TYEHpjG81m3XgF433cO2kzqrt2Y2unJ2bUbt0YpLM5PT8-O-5LX7erB_YeOdHx-dvna3s2nnrpx88lbL754-bkXxnt7BlhE6siwOZWyrGdb4-355WuXEQmduqzjre3JdEpMptq16yeefPro0UNWGTdNX3qOcbo1ijExhqGsaGalaBbrinGqspXVet1uNlpK6Xo3Z-aqmU3H0yEUXjU1BQ6JY6Aiom4cmRnclAhiFUrXpxAgYC5ZxcDBBEIY0PVsBkQUYwB3EQH3yCxZeikAUEp2prb0WXpkAxMmIsIUYu5bHkLT5FqKtB0ikoOV7KqmBUrJOUsRRAR3UwMncwBCAmQAMl8v188-_2KT5C_99f-OaqSUQhgQNxgICRlDiCkxAkW4tr8z2ZoBJaTAHFKVmBgZEC0axhDRiYHdwRQQghrCxU3FFSEvN2Aumw1duA0Y3YioSCZidEgcwDymCoHcEAk1lxijmzDFAfgPpqmqrQggDL4xKdkGTho6B3ZAB2AOoABqgdjEiZljcjVzcAqAARQuqMJEISbTC_JSTJUjhphcFZDEhKsIbswIgFWqBtDL1mg0n6VZhE999GUQe_21d37zG1_Pmh89Prhz-_6NJ24enq0M4Y033z9drZsQPv2BZyuQEUodsQ60NWkC2CiGrdlod6sZ11wzpzqN6yoyEvh8XPdd3zQ1uFVVyqWEFJhjqIKhN-ORIjz37BMGFAK3uaC5XJQrPMbQ9jmbMLG5cSRRpRAcnIjBgZBD4JJF3ZFw0JkRAtHFubQUbdsul1IkD0SmUsTMiB0RY-S2y1QR1akX4UjrdcuRm61xYEaAkpWQxCwEiAybVdtuOmTcZOkdFrlFMDQrRc4XaxHVIv1iqaUrXa9FRLTfrMRdsuacxRVj8MDjnSkShBBz23GV-n6oskCajKqmbuqKiaqmRiBTjTFWVYqB-rYjpjSr55f3Tk8fr1ab2Iyy2BM3b7j5gwePlsen5yenRw_vjpu6iFejJk6apbSCVgAW67aajI4eL3jvo5_PRaWo_1CCYKKcQt_2pgbgpW-BAGAQUJAPKgUmNzAVdCUEirGUYugxRlVDxlJKGoWhkxEiB2IEJ8TRdOYGWzvTEcXJKJW-R_F23ZuWelIDYNPU7aZLqd6slgiYYuAY1utVSqkUzTnPd3ZWq0UM7A6L02VVR2TcrNsQAyDlvp_v7DggcUKCpmmOj08uXbm02WykyOJs2TRpsViC5PHW3Io6EBKq6PBxQIdAHBJrGXRyzhxLKTFGCkmkhDqJ5BSTuQ-Qr6HVC8xIwERILOJVnJjloQQFDuaDtw9NjIg5xuHT6eacKskFeLBDAaAxBTMr1hImckeO6hYCMzGYErGq7l25sVyvAlAz3lsvjwOCqiGwAxoCERMTmDGTG0x3L60WC8JhF2FgSIRShgcWjHW1WpxHTqD6iR_95I2rO9_45veVfbPsiYAMHcxERAeyMLkZApDDQMa1IrFKJsIxqhoxuyOoAyAxIripMvNQsSVm5lCKjCdXiqwNpGSNgZvRlNw6LRwjIiIHckfEgQCBSLEaKWgpwikNDhQHdEcKBO4pDAH08MyzN_Ny8-LLT7_1-jvf-M5r_7P_-S90Wo7uP65HlSOVopwSAAwJ0B_GLokJiLn0UqVKVdGFmUuRetQ4IhIx89DYRiIHjylRZOYouaS6AgSugorGlBIncVNVZM5FiJgA-r4YgLohhS5vADGmmKWPIW26TYjDhZh4-FEcc8khkjNVAB99_tZ33r677ksuwgE3bQeEItaMKlMrKuDExEBIRG2bTRUDDxLos9zWkd08xihqQyUltwIOxCwqMQVVczVGNFMARAp9bquqdjBCLmKIQA7mQsTqGkLoNQckRgyDcB6HqgAQQi46DGOA3AEMBuAcEJFqIR6Ql2DDOh6xSikGMgcpCkOnnlwUkbAvWtSyShbotFw4N5gu3rpATFSyEFFuJQTOKn_p__WXK4K9J_ZSM1ks2tLlmMhEJYvkUoogUIgpMk3mMy3ibl2fwb1db2Z7Y5PeSQmYKHzomSf-pV_5A_-bP_JLP_Gpj83mowAuouZIQABhAHequ2pJkdSgqLa5qKOKA-Eg4XFHImDGod59EVB1JEBHkCwhkIIbsiDeOzj8wJM3H99__B_8hf_iJ3_2x27c3D5f9F_43EcDQC_6xp37j_vyws39drFCat58980_8As__ZkvfLKX_gffuv3My5_6zm__VmCLkVUyAALh-fnpMgct8v_5r_7sN7_xxu9-59v_yr_2v33zjVeff_H5ew8eUbRpiIvjk27dXX3umfZs_bWvfa-epOmkRqDNWe9m81l99-277aZ_5talbrO4tHvp-Ohx35Z79x8fHh2jW-l7UHXCH_v85772la9sjhfqcH6-bPt2PBk55CduPF1Kf3Jy8syzT3XdWs2evvFMNLi0vy2dLc6X_apnQnG7fOP6yd379SjNR01f8ulytTpfiUkp0K1O3WC52gQMRw-PL-1eKeN0-P7DiAEDf-gzH1kfnxc1K5hCfbZczPf2D-49itT86O_5PY_v3UmJc98tHp-8f-etRwcHDrpYnX37u9_hVN15992zw-Pjo7PZZLy9M--l9KU_OV_HVK8W3Ww2296aYsmvvHqnbqjbZABYd610Mp5MIqMUzVqeeenFo_vv11W1d-2JxeI8prherqs6AVDu2-l8x4oQoTgcHp3cuP7h3J0v23x6dl6nCh1OTk4FddMLBxYA5lhVVTWaElpete4ufem6zfbVq1CcEEIM25d2xlvbB48eVc1IXPqc-66rUzOZzd54840f-8LnVptWzFUNCWOM65wjk7jFlBQgheQIq0VbpdTnHsDUHdxS0yBZiBQ58LDrdgAiBS1F0cDkf-rduUOINAxdkUCzuHu36ZhAzVOsSikDEFnUDQwBUIUo9H1GAHdXEURQLS42CDUdQEQQGQBUypDn8YtjfTQwUeXBqU5Igc0NkBiJA6s5AqkZABDFYvSFz330xz798Tfuvv3mK29SCO7oqlKMYwgxMgWwEsEA9ff9-Oe-8d3vHxwtspqZgxsF3qxbEKlCUFOKwd3MzK0QEBK5CAVGNAJEp1invu8BXaXUo0np-pRYVRDRhyIDAhMDKBEDDjpmRkLJPYdKdVA0Aw7ZWSOOBAAqUjWjkstFWhUoxDTwlznQgPtzR4CB5GlxcDQBEeGQswdEYgbAajQS0aoKqooAyIQIdd0EiogA6CHSeDTZno6vXh7_kS_9_Lxq-iz_7Juvv3NwpBDX7erxg6OPfeFj3_nmq9P57PK13YOHpy_durW9M5rWzWp5tjUebdouRGhG4_DDWV5AoCpILxSCiDQpROZ84SIiNRmPGlM1V-bYSz8djZH9-tZWzbzuNq6ehtCBap0iEauVaTPiELouB-bAAwEQu1x6kQGWyIMU2lxViS7oa47YlZKlGFAuxd2aph6msJtNzzE4gbl3DudnGzVvO1mvOzErogGxburlarNou6Jq4r1YUV91xdCyuKJ0uagiBi4mxa3r-gCuOeeSVcUQKHBgyr0gOBP0OQMRhDBIclOKGNAwxHHwYo5sRYbdftVUQKSqqapcpHQ639vq1u3W3qX1-XK-vQ2Eq5OTZjpbrRbtut3e256N69VieXj_Qdv3Cj7duVSNxovFEhDXZ8vJZNr2bWSeBOrOVzx94VOcUskdAUjJsanBzVUunFYmOPCoKIhBjDURDvR3EUH64RRQPaQ4dEG6XBgJnFKKbV_qGAIN9m6c7owCBwZ84uqsqqhdbWIiQICB4jQ8dAMY-ahqNu3GzeaTLXMrnRBDVdWzra3Dhwf7-_uL5TkThjoQEYdIKcxGjZbu7GgJ7NWoWa9XyAFN9vd2j49Px5OJZB2PmsXZ2XQ8cuTV8eloZw4medMREQfMxZBgPN7K3VAYKAAeOAAM3ll0ROlz00xKzoAwfNS0iIMjExoMrSRHAO9piC0OBC-kIX_IxG7DF5aQEcyJ2MFCZAdwFXAc2ipkAcEUFGOtKoECE5oKMVGMVdWsVgskFulNO-lKCJECAxoic0wmwkyuomb7N59anJ9xjFaUIqbAAF4EQhUZUSTHkDjAul3_8u__ufl49LVvfG-8vbU4PUcm5go5CCgxmQORgYGKEJEDmCmHaKoGziGAo6sOOxBmGjzB1gsFQkIHpRTRnIhEu0GqEWLUrm3PzpvpVjPfW56dhIgqioju7oRgCkQwHL-R0IyRzBxMmcPAhA4hVFWTS398dLh3afvWU0_-7rdeqTh-9dvf_uQnf_TSdH5weDCeb52tVnUdtQwZnkJIIjrMD4YrBhAQEROJKqfEMTp67loOEQOqCAYKoaIfbmOLyHQ8YSIVMXRkFhNAGPTjRKjFYqoQQM2HqTgHGmriWYUAIBCANeNRXVXu7m5mCgHH1cgIPv-RF7aq8P6Dw1Z9vckOEFPcdDkEMvMYGQClCBKmlBwHeKqLgJmminandcla1wkBAkJRkaKpCu4gpkPdAgFNzU0DMwU207pphtuwuRMzgMXADmRgMbGDxkHd5grkkZmIYdhgMSEiig_WrcBhEEiragpsZoEREMZNU8fQjOu-lxgCMm7akkspYlmsqJeibZe7Xt1BHRBJzNyMiasUS5FsUqVo6gIGjojYTOf_3d_8mw_uH0y39j_4kZfuvXswmVbz2fjs-JSYRCVE3qy70biuRnUknF29dH662L-2v1quCAmcY90c5-pHP_6BP_VHf_lXfu4nPvujH9vbmWkppRgTDnSJoc0bEBF9aDgQkhsoQJs19zLUgmy4J8OAAoM6xeGZGQlj4KHq54CGqIgGsc_29jv3yKrvff_Nb7_-7s3Lux_6-Evq9r3v337q2uVxPXrv4eFbBye_8MWPcC7Hi-V3v_dwte5_5mc-Dh5eeu75Rwdn3_rWt24-c-Pg_iMmczUAKLnPRTYdvfDJDz08Ofs3_8y_8y9-49cPjx_-oV_4g3_77__9D7z44a99_atc4MM_8pFv__Y3H7z53qd__LPSPnjvaP3yS0834ypA7Pv1U09ff_D-ezvbV-bb08X52ZUnrj64f_iDt96N0-2jo5NuvRpeFKJNZrtbl2YMVT29fPLoQBybFM3K3pXLXSmn6-XefPv47Mxd4ni8ODpo5fzk8XpVus1mnXMfck5No7n_4Mc-fnr0YDwaXXv5hbu377VdN2oaJzKI852JdZISzua7hw_OVquVQUCQ5z78IUZ_78F7TWoms8lqvdaSx1vbROBc2uUmxhhD3JyeBfLRaLJZrU4Oj8u6o9F074mbrJzN33n3_Tvvvn94eHTv_uOANHi0R-M6W9ks108_fX08qeNkXG-NNJd132lnm26dUoWKfRHNsjw9Ra7MbLK_a-1GVK3PlFK_aWOVzIyInHjdnjWTOnBkB5WyXqwcfTRtjGA8Hc-3Zhxi1_VxXI925qmq82qjIib96b0Hs53dxXIzYHE3603djC80T32OSJt-U9UNihbDmzeeyaWcrFoGDSm5ATCZEjGFEEDdRFKKpfQpNWqKTlVTpcgcQgjEzLlkJBqKvLmXtusBEIHEBFzJSt9lCmhqKmJquS-OXtXJiroYIKgoEbopgG82Q39ASilIBATshnahSh0Al2Dg5H0pAEOiGw2UiEzUTA0KEIIP_VUiCi4C5kTBRAcYNDsQYwyhmUy6fvMv_6Ffvnnr6l_8z38tr89VL5TABiQAMQRADEyopVuv_6X_xe__a__ff1DUV5viLlJKbJq27V2VYuiyIlEI2PfdQLgmQENHInB3KRjYAGJVg4NlQRcCcJPAkQCIyMCHnQAjO1IpmZBirHLJRISDltENHDlFLTkEZk4m4gAOSIOKyAyHeiJe4IYAgGNEZhNhJFOjEE0EwGPVMCd34JAuOECREankEmKoOJppiClwQEJCRMfxeDyfjCLozf3tTz7_rBf7p1_5-it33jtdysnZwkHef_v-pz_96R-89rYQpaY-PzlXybduXBs3adI0fb9KSKr67NPXQAGk1FWaNmlaVxRiQGiaSsSms3FfJDBVFW96I7QqpRAiA6RYocruqL42b1IImzZfuTRXg6aJRdXUqsijqg6BRE1NAZwRYwh9zoBYRJBIXKuUTDQgA1MMHImBqOuygWOMfVeAGNyGBkAW7Yu2fXbEorDs-iLQbvp112fT88VazOfNrO02XZuL2en5Epm7IotNt-o6TaFX6duuL1Ky9LmHgFkEwUvfqSoYgoO4Df3AkourAhMGluIhRUfouqIAnFIR3720NXxZgKA_W2AIVFHOGuqmX61SGrWrdapjUa3r5vz0ZHV-ChRDHWMK8-l0ebo6OT59_oNPdst-1fXgtt70rcl8a2tnvn1-fLI1ny6Wy5Rqdzk_WTz71JUQq9T1PQckRBPw3DOCiIKjiRADhiQmwAAccu5TCnU1Uiui2lQRAiMhAYsU7U2DciB1SyH1fV_HeiftnMuCEFKK2lmofXc6im0WVU7cbVoAZ4SUQlFFpFzytJmenh7X9chVl-1aNY-mYy09czg8OJhvzZfLxbUrVx_cuzeej87P1okDA7YlI9L2lS1ROzk8HE3mRfP5Yj2Z7Axn8fF8Il2OsU6x5ibGmFykX3WxiiFValpPgpd-tTgBBEMkDg4qKgZAxA4-wKNMNVWViLgpEKS6KqIEBGhuziGaZHdgZACxosToqhB4WPcPQ-6BCkIcBkzQIK4jJAcPKeVuHavk0hYlk45jBGJkjO4GPh1PTAq6I5hIDw6YopqDg4ARhRSTijCyM3S5G0aww_iRiUU0BOYINow0Eclg6OwkgFFKzXi0yj3Xqc-ZR8GKGAdwiIHNcuc9M_ugJyBW1TRK7XLNQZEIgByQEHDwKhuEKsDF8ZdIVdSBgKCMRvPFugUQcAiRz88Oq3H3xM1nH9x_kykSYe7VyRHRQaW3UFWuxjERsuMFzXOwaxhTVtFSTo_O4Nr1ftWmKtx7_1Gq0z_4u__Dl375D7zQtq_fuf3xlz_61u03Qwil6xzRdcBZmos7DwdNR9CL-a6IllzVjUYxBADAwIBYSj-ZTUrOAsaR-tLPp1PW-PjxUUy1iAxWGiYmjkjet93Az2w3XdM0Bu401JlA3bTYqJmqabuR4QxNibZm26a6bDeXd7fvLtbHbWuhasb1-emybtK0rkoWR2s3edRUYKBmw04ZqxgimyECkWfMEJAAUB3QQNQCBxFwlziKWUpiKlrQHFMoiCQWOEqXq1FtRXt3LdqkJueMjG4GCsMtGRL3kptQJQRiJGIzG6dKxYTyEPQaVBimyoGKSRXDdFyhU0rBTF0hxdD3ebkSiAzqIr0hBOaqim0vgdmsqIKjJ-aQQowRHZm4YgZzCpSXUlccq7RYLr7zre_t7e8---GnD947cqC9y_ODg2Nj6kpPxKLajGu6oFVZu5SrT1we783q07WE8MJL-3_iFz5zY3efCC0GAsxSVKgepAxmNmwn1JCDkyOTqRIhOBih9YWGdK-YmcVAxKRmMQzlf3KxwKxqqgaMQJC1ZAh9lx88Pvzud39wY_9yD4vjRfd7f_4zv_6PvjVK0Rl3Zzu78_n5cv3e2_d--ec-Na7ia6-99_b9xRe--PxOo6s2J3HD8Ct_4ld-9U_8Gz_7-_-1-2--LtKbaiCCAKkZfer3feYDH3hhc3b8ynfe-pN_5s_9u3_qVyuqEfH7b3wdir1z584Xf_oL9bgm72aBn7r1tI-OAELt6k14-Pi83ZTE-u3vfO2Zp3-ubdvNMn_8oz_y4P3DOJ47kqoRGjHmbHtXLt-5e2fT56KnSnr6eEFYUhUpNOfLhwR05drVhyfHHPHh3Yczh5Qmk736aH0uRep6bJ6z5p290au_-62PfugFBX78g4fM4KLS9UU37hx1QE1IinXfbbyUSEhNdXRylNwd6dqtK-2q5Fb2Lm3TTv3uD97arDZg3Fo339oezZd9tzl8ePzch1548_uvphS65bLL_YP3H-xf3t2aXq7G-vDePaB09_37i9Plzs40hmq-Ozt4fHRwdHhycAgedy5trZfLpXTTVPerbvf6pSqNy8nx3vVr7eIEQDZnK0QCpybVebjgFWm7jonyZjOZbvVS2LHLHRE7YD1tVuvNe-8_mo_monF1vHRERW3PV4uj4ypiHI3r6fTs8SFCfvTaq_Mnru8_dc07ZxpvVhs1DmEUt7dB8tnZOQFzCu9-75XpZGcybSaRAgSRkiJmsXGTBN2LxiqtF-sYiUIs0scmaTFwGDadJmohmHruWwLAC5oniYFYKW6Yi2cpRXVhVR1dTYoSgqoN8R4zl64NFMC815z7UiV2VAA0LaYIiJEATQIHZTJVK4aDeMWdArkZYIkhmBYgRyA3xaJu6kQckYhcHQf6BuEwCkBGB_C6ygFvPnF5vntJBJanR6YEBOrgpmrkSMYBRJR0VFe742pU8fp81XHg4ORshloKIKi7umspzajqBipRYPYgpeMqaN-HmAp0oJlpgC1bSMFEUmIRVndyj6l2yI4oKjEmpsChmHnftamu-3Zj3oeUxAyQrJRQ1ZJziAlDBCnuHpAR3Wg4-lusE4oAoxYjsRBDSpWbuRuihxgAIec-NQyopghE5hlbrEZJM5piAeUUMARHQIIQ0uBOMxEN_rEPPjsejRLoSbc5Od4UNVVHDWkSTpfHzL7erE6O6ms7O0fr7u7jo1t7l67tTa_uTw-PzkR8U_rx7vgo-HK9nI6mvQHHtNggEmjRvs9NikUVDEYVp8Bd7kbNKJsExMmkeqM9eMEvoZStWVNKMfGKqnPxyTilFE2tqJ8t1pNRNfCZ_If0lmFOBGDmHgK7g5szkYkzQYhBVYsaEBWRqo5dlyNFAAL3GKuuKyeLdQ--7vL5eqOOXc5KkKW8_ejATGMMFLiq6uJuhKJKTNIJILYiRQzBbNNTn3wYwyABeJWYU3O62qhZnzOlMAg3VJXrVLQ4UdiqydHcMNrRyRmNQll3MYa0M21PW6qr7A5uYtiVHjCvzs_ryfTo8UMA0177s0UYVZvl6XRrtHVp69H7jx8-OqVRMsZiNt3fXp6ftssNiVfN9O79g_3L-w8fHCQKnruvnmx4_vyncluYAFRSlSRnSkyRJAsTVVUFDDHVpShzrKumqFJgQUshDlsnyUXNGBEIY4pqHmKIHMwcDYUN0au6jmDuvrc339sde_a6CdKLl4LERATsIYXSlxDC4mzBMSCSmVi-YBs2qT49Ob10-RKAu8rh0dHu9u7J4cnWfLsr7ShUJyfLalRX46Sikevjo5Oq4ulsvl4uwHxxsjw5O4uBmYAir5bLOKrdFBGrKpp6VSVElKKpqpBIslCKRMwhMIciMh6PJRc0G8C9Q6CakELVqBYryoGRedghOiIQIOKwKGBCvOAB4-BIr0aT3HdgRuA45NQZwU2zDCSZiy0BsYhzTAPhU7XEFCezrfVqjYaI6K7urjmHELNmjgkUMAACWlEEcNSdK0-slufDjgXRiElVJCun2lUGD1TdNG724gsv3bp-7e377z9-dKKAJWtICYmKacl9iERIBj5w9GNMRGxiNFQdzENVmSoCuJkWiaOJlqylQwdk4pDAHdBL7s1YkbV0AZw4qmlklHbTdutqNlsvzofFyMD6JdMYa5PCjAhoLkDEyCEGUyVmTkn6UsW4WCw-9KFnt-bjf_5bX1-tiqFTsVW_fPljnzx8dHz30emnfvKTN_e277z7ICIquDugGyMiuQOEgNIXDghAohZj7W5IsW27qqlF1QGZqGkaroI5SMmEMasBOcJAhFHXQT4-0B28qZKqOFGIAdAIGC7KBxBjJOJhWuxqKUVApEiRHNUmMXz62Wv_9Bu3T1dijiolBTo8WkxGdeKgogN4KsTgDoGjm6VUDfTPUrIhtbls2r5XhUDOCEBSdAh-yfDX1euQut44QlFPqcq5jzGo2eBNNwUwBcKB1l0FBvSqqhAscQJTZFRRR-fA2aSuQlNXIURACJFXfakTlSLjpmpiGjx0Yu6qWZSZDZwQB14bOvR9Hrp0Yj7kssSREQGRCEF12MnmridGFYixUoCY-K__lb8hXdm7cXVS13ffu_fSS88sNx0FeOlTL739nXcB0UrbTGpA5Xp65YUX_9e_8ou_-LlPv_zMrZ_93Kd-7-de_plPf2Q-m4YUsiJxcMMBB-Y4lHnV3RwM2EMkUx-a3xcQMMderIipmZgTDuANIOS6HnSkhEg2dNQQRUXU2wzvHB3-1lvv7sXqIy89t3tl5z_-y3_rV__Yl05Xp-_eO_vQS087YbvM-1d233r77sc--Ozupd17j47eufvoxpM3XvjEE7_5te996iPPMcaaoQ78-quv7V3befet90spzWhkqhwCxdFHft-PY9HtS9vzOi3XZ_Pdnb_yV3_t3_yTf-psefKhZ148e3wgopiq87PTG089V29P_tE_--0UwnhCkzR79Oj9l57_cN-t7j462t7ZXm82hNSbSdtzPfnB6z_QvgvIIkXdXvr4R4jxzR-8U_pNf56bKtYVE-jTzzxb3Jx9e7Z78PABWTg5b6ez7dYX7aJF4KPHh6mKi_Z8XI--8DM_mdfrk8cPxtPt7dnuW9__PkXkGEu77s77lz7-Y4ujB6Zy-cpexeHo0aGIVBWGpnnxqecw-PnhKTvGxHEUq6Zar9dFBYm7vucKi_jRvUNCXZweXr56uV-1BGF2Zfvg_gN3PDo62dqapCqy090770HRrZ3pdLbVbvoH794l8HaxAtD9S9NAcXVw4FJy3xNXWIWTg7NQ14ePj8AgpFGq43qxKK1CCLGu-tVKioaqMgghVchsWmKIuc8c667tPevezqyu46wO65OzzdnZ8b373emJbRbd-braGsfxyLxI15mV3K0X7x-WLIvjo83JQtbLft227SoFNis5d4FwtTq799Ybj-8_pFIuP3FplKrJdBaIwMxFVURUmQgA0UHEiJmAmlEdOSBACJxLRgcFVVVGHuKcKgoIoNqtOkNjRCkZYKACQtfl4XKd-1ykcOAUWSQ7oKqgmWdBH5yS5g6qYgAGYK5ohoCMzEQllwG0qcUQjSnmnAkRAVw9BAxMWsxUkcgRc-6YqzC07xzSaGQA-1cufewDz_zcFz5zvDr5b_76f5_NMbKqERLEsOnXzXzLwYMBoF2ZjX_iC5__jd_--rpXVZOuBQBxlSIcmEEJXKTEKuV1x-gihYaoplkpZQCpac4p1cAIiGYGyObuiIBsrhSSWlEtFNIFT1zKIMlxMHRIKeXcM3NIVe46JFAxTslU0AFsaFYBuCsYVwmRTJQJCckRBugwImrRkIKLMEc1S1WFiGAWq4jMzajp-2zoAMiMDk5Ew5Y71qmq0qxOkwhf-onPI_j33rrzlTfuLDtvi5fNJvdini9tX4pMx2drwNiLVlU6Xp2_d_vdJ29d7Xu9vDOLTdqdzvd3ti_N5hFhlOjytd2swmBVSK5qBiWX6e64XfVgxkTgFCKOmwrctmajl_b3t0fRgZixSix28dIjUZVSycVMY4rEiABNk0wcGIsoADKTmY-byh1SZHSIMaAjABhCcccUVQ2JBxQeIKpoIMqqIrZRHU_qx8drBKAUuqzFDJBX640adKVQDODQ9TkEbkWWm04Qui6baWl7LUKRQxVFhENYr9ZFSnGlxAoOiOoOgZwoNokiIqIhYs3VaNStOwpMVVQVrmtVgQGCHsgdgahvN0To4u6GhrMr-2cHh9Np3a9XIXKqQt70Svj_5-nPfz9Zs_s-7CzPUlWf5bv2frvvfu_cO3Nn43BmyCEpipRIji1QlGxZlBRLiRMksmQjcWQYRiAkdhYbAozEcGDHMG04QhInUkTLEiiKkmYoijuHHM4-d196X777Z6mqZznn5Idq5h_oRqPrU_U857zfr9dy7wBqf-f9x1dv3ZCap9B5AF7s7w25IFgqY01CAPM2dt69_PoLvHj1c77xpmXacJtCHosRl5KIMNcCiKoGRKaADMAw2U5rrTH47Xrrgx-H7Ji1GDI_TWiDKljTNmMekQhVXeNnTdxZzAISEigDqpJzgrbd5FSKqY5ZQuNc8N55lbrYWRogAM5ncUojmFjoYurrcm9nHHsf3MPHj0KI1aCZN5JT3iQIfrnsEGA2383jeHBwabPZ7F_aS8O4u1yK2Gqz3dnbl1wvVqsQg0lNfco1TVB8UQlNE9vOzHLKjojZAdD0G3POV9UQQqkl-jChYiZ47zT1jjGKCLGjaXYBTI4VgNyUkJjIa2QI7FkmdigiIEqpQEQIaBJjLFLRoRkDAnuH6EwFxKro4Y2bm80FGkguYqZVQ3SGpAaE4J2fdl5NDFIVGXf2Lo1jX9L0JjUVCMFLFR9Y1ZANgRVNwFari8984mPPPnPrt772jdg2Auidd84bUUqDlDVjmAohAMhEYDK9DadDPzunpuQcEuZxJM_IJKUA2kQxIyYAI-cnSrpnENEYm5qTiy2ilFJ8iGBmhCbVOUYwqVVNkVlEYIoeiRIzMxOhGbB3LoRZ0wx5-LEf-eK7H95-8PBhruB8NIfb1frGszdfffWVO-9_eP7gSNnPZt35xbmKEpJWwUmp7pwpEJGqGRh7L1WYGdGIuUoBIB_d5KSMoZVamUm0lpxNUEpl54wQzKQKKDrvEAjAHHt56oJEwwkGL8EFUXUuGGiM3ofIjhFwSCMI-Og-_cmXVfDBxXkRLLnkMaciFaqoCmKV2raBiVQVpsuHgWmNwSNDqgmISymIpKoTCMgxT2WUKaYyNf995Na3mzGBotTqmWqtk7HOUKUWA5hSbVOjg7xjh4gQnIveT7BLJvKETYhgRgDEED13wUfnZm1sQozM7DjXWmoFUwCbdPSMyI6jY8_OMTddJEQx6McECOB4Ym5PJ_AJjpFzIQdEnMcCSN77-x998P3vvDXfWX7mC598cOcxeedjzGm8_tozb3_zvUuHB9s-O8NcYXf38t_6D_76lz7xscaRoQxDuXywE9gBu1qM0cG0qTITEwUEUDQFm4JG0_qdJqS_mpiameVitUpRUYOpao5MUpNnIkNTEBFBQ7ACupJyfLF5996Tr735wepo_cXnnn_20pWTi-Hv_NJXfuaLP3j9mYOT44utwqvPXvaeHx-dBIf7O92VS5ceHZ3de3i2d7Cz17a7u_M3v3XnjY8_S2qRldHfevXZ77394ed-5Ie__-1vyzYpGjtij-Mwfvwzn7x8aXd1enTl8j4avv3Nby7354eHl1ebi6Ojh-OYf_wnf_y3fu23z0_OXn3t4w8fvVe3-uyzVxH9h7fv7l3dKTXdefDwjddfv1itrl25gpmePHi02Dl46803cz86JB9dYHfluRcsDRfHZzdv3tycP6y1dsGTpCu3bt67c-f2u--_-Owzx4_Pnn3uxtG9x1euXOI85L6P3PSbHpGWvvMNt2jbJ5tPfuFz3_3W92ZLP_ajgHgIomkc6s2Xbx4_uGdGbef6NK4vzh13VUYG-PyPfmH15AkiOgNkHMsYfCD2jx6exEVHVhV9nHVls4I6Bp4ZOU3CoVlePhzO14cHu2Wsq349FO2TbFfbvE2XLl_NJR8fPbaqMfrtZts2jSJfHJ3Vkthxt7OXqnWLZTtrthebsc-znWWzbBGl70d2QUHb5fxsM3SLNrRtN59vtyMFRKPNehODK-O4WV-o5Jzz9mLz6N7DtN3UMtYytNGNfdk52BXR1TqNQ9Jc0XDs-9D6st2uzk6Gi9PN6nS7OgUp47gZ15uSc8lpu94Mq4v-9Pzh22-99Vu__b0_-P1vf-ut84uL-Wwxmy8QzIc2BK4qjhkM2LudnQUTBe-m6UCuVauqwDBmQxpzCc6ZGKnQtPoXYcScSy1WanHBgakUATEQRcIp9o4IJtWqSKpSKtD_H6KAKkLsask1lSqiKqomUgkAidQKMZgaoVMTRzwNLJBYSjVEcgSoAExIMQSpY-w6U6zmmt2D_-jf_zd-9LWPuzj7d_43__FqtVYFcCRiYEbOFYXQNLWWJrBp_ck_9qXlbPd3vvfmZhAk3JxexLbJJamJd4Sm09AEwEKIOSVEmMLoRKgiIQasagAqxflGzUoVUCEmM0HnJly4mTCxmllVYJoSBggTv1LBlJ1XFfYRQMHEAJ2Lhgpgk4zFDLwPk-OWiWgC7YG56bzhGAFNkQARjJxTAXZuuukRIgDGtiFmNWGiqf9Gpux51rXkeDnvdpfxcuu_-LlPlGpf__777987O18Nq80258ERlTxwCC-9-sK9h8fkfam6Wo_Xnrv5wf0nF8Pwe99665mrl7rZjIjaxi26cGl___Lh3uHe_Ob-7PhsU0r1wSsgEYT5bLvaBiJy7B1duXpopUiRl56_LiV33hFM1kTMZSr7mfe-VjGDTT-EGLxzNdfoHTwVQYABllpiDIAgWXzwCBacA0RQqKpleqhVAbjW4oIzBc9cp8uZigAMYx5yRQFCL6Z9KtshTwL7PpdUK4H12wxgo9RtrmMqypjH5HiKEyNRVBUptdRiaLVo9C4XIe9KqU0b64R_NatV2bu4t0QHhlZKFZVqErpWqkgqoQs51zCPhiipsGOtxTnn29geLLanZ1aTbIfU5_0XnwfTftuXWveWe4EEQBvPTx7eL-OACs1sBk2TSpE0RO8d4t7BYrd1D773gYsxpLHUUkJLKgJgQGAq7FhMKDowU1THASeUkjlgKCJWq6nrZo2ohegNlRzWmp1vAEUnYpaoCw7M0DMHnu01HkULGhpl845LEVZaLNtas5mFEGqt42aMrVssZ5vtQJ6X7aJshyFvZ8vFOIyP7j7Z2V-OwxZUmhBffOmFYd37pj09PSPHXTPLBOfr1e7BYnVxMYv-yeNHewf76Gx3fz_l1Ox0gkZgZczLnZ2acrfcIb8F5DRuvSMCHPuh6TogDI2HiaVFKFoZScFEVcBiaKQUEOHgAWnI2TtUEVEl78sweOfR1IWY00jOlyQ-4IRIFxUCJmQCMlTRyi6QZwRNeUTni4jzodQKBKaI5EougZ2CWrXZ7u7w_vtd10Gtjt0Eg6taKbB3vo7ZxwAEYjr1EU9PTmIzq2N1xLWmWuqU-EKaPKXAzIDceb5_7-if_drv_mt_8Wc__sqz796-P2uiGIUmQuSy3QCRiTGFoQiATu9rQJOpl0lgWicPABH4GDQV8oTMiGIKAia1hNjKsGUkzRmiH1P1QZ33tQzsPORxXK-I2FEYJaEjqwIGooXJoxExqwro0z3aNBo2VQqQcxbTW89d--Vf-dWa1YCKCVYjj7_1a7_x5S__zA_9wKd-9_f_0MaCRADsPAGA1qchdgBij7lP7HDaRIlKEY5NF0yrihRl9gzYb4d2tkgpB4daFZCkZlWoUj3GUmsIsVbRIohq7Macnv5vA0R2RfIU1mekfrtpu0aqOU-pFBVhJkQ-O1_94GtX_-7f_wP1kKs5Ngy-jL1zXtTKMJoIIs7bKBWITGou1VSkC4zVom-2_YiAKaUmhqoK4CRXMJBafXCOueTkvC9JxWUDyzmH1psBGJcsMRIbOe8DuTEV73gYx9BFh4hmhFRq9o0PLqpWMFCFWiozDTkH55CxKppZzgqmMo0VAXKpnhnMiKjUGhidZ0c-5UwExA49s-NaylDKdsixiWZWi85al-vTzZqpmKEBM2nR_Lf_6_8u7O587lOvN43_4P7p87cO27b5S3_hZ082x3KB6-PTbb-Ruvyr__Zfeu3G1WEcxrGsNmOczWzQqSWmoiE4M0WykqfPhDrv2NFYBWzClysbkp9Ud1grwPQLc2wE7LjmTIQOwDkyDAo6SGFAAyPTTUnfu_3w0XnPzEHpE596_cVFN2_jJsP3vvnRl77wqf3ZjvPuw4_uf-yZWzWboZxfDJ964wVn-M6H98Bgb385b4OmSj1K7EqGoIoMTcQ3Xn_pv_sHX_3Cj_7Up7_w-a9_9detWgwoQ-7HOttZVskF6nq7McIf-9N_8s7du7Pdw0tXr-0-erA5751RN2-P793vdvdCN3907_TR8erKZVc0nW02i9livR3WYoBwcXGhgBR4sz3FMsYmBs_9sI6RL5JcbiOgDXWjKDduXkbCRx8cHT9Z7ewcHlxZhUWs_YpUUhqGXMZ08eB4fOXWAsmF4Drf3P3ozp_5s3_yl97-tUuXLsdgmvNyZ_fk9CLR4MD3F-cXJSMyOXUYyOd2seziXraL9fGpj-3pajvmPqBb7CyG0tcxv_Dqi--8_eHFxSoAkmY0b8YpA2j1nYgpoUAar1w5cIRtF9rZzsPj08Xuzs6VndPbpwcvvXD7W99Cga6d-cbN5wvw3HTL88dnTCHOdrrDK3PzoeX57g4UuPysrE7P5os9CjZb7o39MIzjYm9vsb8LSA_vPWTWy5cPeBab5fLiwUMUne3GMJ_VIhyZkY7vP6pl1KzO-7NtvfXSKxHNPB8SPH7w-Mr1K3e_-zaU4ez0pOu6vYPrp08etbEz5LaJHOcb3MwX89nu8oVPffri4YOa4PpzN4lqSWXoe8njB-9-Z_X7673DK5_64R_KYy25hiYaQgwOTaOPUstEVimlEHDONUQHpgbQp4QqDq0SOcdTe15NCRTM0jjahGoXRVA0NOZciyPwPmqpxCjIJVcXmRBwatRKxqegCDI1rRUMzDRwqKUAqj3FB4GagUMrRgw2DU4Ba6nE7JwzGRsX2LudZfdzf_nP_Uuffu3qXpd7PV6dvfnBhzN21DpE0KKGYCqzWUMmgR0VK1K--KUfvPvuw7OjtSoZKjsE0hCb7WZEN6nKDc3KULltHAfRXLXEGGtOCKy5wnTAF3UAZhpj0FrKOIauE1NGMqlP4RmEPsZas6oRGYBjx5ozh2aS_pacmHhab9SSgKa2nsQQUhkceEI01akJYWZgKLkSoYmyY5ACAM61RSo7L6KhaSUlJGUCyYmjjxStCjFbKSH66JjBQnS7i-bwcPmzf_zz0bte9HSbkGITBc7Xf5SG8I8fHn3phz7bb7cCKAVoZ_6d77yLIr_3rdvzzv-dr_zBx567fP1g_7nr12ZtExvIhbbbwbG_de3grY-eEGgtzhDLJjXRg0EVubS_Y2k8mM83nB7cf_jsjYOKtmhiLZJTUYIi4h1N3w4CcEwpZRGjydqjZggigsSIBGagWGotuTgimK6hBIwEqTCzD24cqxQZLM9iLKr9dixofa5PzlcKjADVrKaiUpvQHK9Oy5jabqaAhphFweD0-BxiqLUu5t1qmwDcUJMAlDGNucToipqLTdpWF0OqZjQlgl2uwDFYTlVNiIyxrtccvDL149B1rZSKiOy9jFXJh7Yp2zRuRkLwO5FMLMs4pM1qG7sZlBFrUc0f_MFvX37pk-Q0b4bbD48vXz4sY15tNyE056tN8HL_ozuXXn5JRdbrdUQ8uHbjzu3H-_Mu7iyc5Cqi7Mlq9X6Z0zmzZ4NSzcQ6NxdMNhVXAdm7nDIDMgDGoDD5HpQI83YITQuEptU3UU188CG6kpMPLgSCbfULw6Jj7duFN62rTTUxHxnUjLhUYTCtsli27Hiz3jgfaqnNrK3juLe3Owy9Y7r-zMHZ2frK1Utvfv_9Z67P1xfr5WLn6OyobePJk1Peb3KfreL5ycV6tXn22efHWlXKyaPT0DbNrEv9WHJ2zOwcE-SqJ09O21ksaZwtd4ft1jl2sVGRtp2tzk5JjRuXh9LOOyuZkGfLoEVqTSFGdUVVADG2HlTR-Zyz9z420URRjZEQ0EBDG0vOZNWFaEam6JxDR2oipU4nWmR2PtQiyKaiLsQ89kzB1Jp2ATICMoBKKT4EMPWOs1RUa9v2YrMhAwBwMZhCjNGKuBDMsGqN3KpmQQ9o7BnMwMz7ZhgleJ46jtVwtjv7R7_y1b2DnT_9Z3_2F37hb6-GOm_abGq9tfPZdqU55xgDuoJiaOgIVbVIRcfTtJQcTzVEQgIEQvLOpTF755n9kDbOOc8sqjbtgbwBVDNFoJozMTnEnDN7z97X6bxIWFQkF3JOtSIAO661MNN08GJ1kLJzoebcLsJ531MgZ6ST3Ne434yPj45PHjy-duPKxXp7fHQco0-1ljF3swigwzCSQhnBAM2U2ZUxuRBMLefkHM9m84vTCzOtOfvot5uV5FrQP_WTESJUqKhQHHMtlRyZCcBTDLCaWhHPPqVsqGBWsJg5QHLOl5x9CGkcHWJoGsX8xpVDzJki9mOtgkzTk2JgSsRGomr9MJrZsu36cXQupDQih_XZMJ_PmEZCBMa2CbVIBdQhVwcO0buQa3G-8SEQICKVLFpBzPphrNEFcKiKYI4JzcjBTozesAkcPXuaysGYRYZSnYF3jECTGUOrommf03LR5lGBtVZDs6pqCmDigyczQ1JVYkqS-zEt5i0xIYKpOceGNu8ariHlws6XsTTRAU41XHUBawEVQWeVwt_7u79SQ_vlP_nHisI3vvv4ys0bb3z2pcs7i0cPT8bt9spzt37_69-_fv363_xf_cVxnU9PzrNodLS713oDnXlVATVRZXIiBc1yrkQgpla0VCq5eBfUlBjVwKuWIgwTckQQbdpOgVlwLufiiK2qGBChBpIk64v-nXt3T9abtgtfev7m_rLrAm_VidS-t3_xzXePV_0rz1xqm5BTPjk6_ewbr2uRo_OTj79642Cx-Af_5DfmcfbGpz8W2X_7nTev7hwOfX35-YPTk7Pr-0sAIxQu9dKyS_3qtU9-4lu_-btlzAAkKGf3HuxdXj5676N5M3vy5OTWM7cenZ7_-m_8_isf-6SK-NC6zk6OT72POfazpjncuXL7o-OcOMwOdi9debTt9_afrdFhDMKu7Xa2m83JyenhrZ3QzspFn1XKUNoQzh7cf-YTLztf12frzSgXH96NjsjHwfzx6em6Lz6EC-dPzi6eXJx9fGdXLga1BztXruKHjy7Ot3F_7mY7Q5bz1fa9995bb3K70-_s7JSSG9-YEAV6dO9O0pL7AVGPnxwdnZx56KkRLJJsk0sfWz9u6iU_bxtBEoVhsegIZBySqM73Zqgc2xkB15IAoIiOm2E26wLHrfUsxEVCQAdNqXL__fe1CjBCNTAWBCYrBLODZbtYXL52U6MbNsPJgyfGft7MvIuhbbKMxx8cX75-FRxfvnr9YnWByIu9-Y2XnpdN7wkc-ovH568-_2wWeXJ63i6X0TdZITLcfO65KoMUOX5y9uq1A19Razo524rp_HDPyL3xo1_qmuZ3vvoVdvXxw7sHh5ef-9wPwbDtDg-HbRGtIYb3333v8fGjK9eva7WCNJ8t-rw9vLrb9_0ff-H1ittf-6e_Maw3AjBrWxFZLObjMAb2GSsT9ylXUWRXixC4koQmib1VraKIY6kxRFCB4IdRtWTnfRUB50oesEw-2kk-CwCkOYEaAAFkItNSGBSAtAoREygDiVYkryZgpmK5DswAxqUWhOqQpAigmVpNlQMgkzpgcJorOnDOVTNG_N_-B__OYjZ7-_2HdyF_NF78R_-n_2qvacVAVEwEDAkQDbyLUzwneH_26PH-cue7qzdns3hxvEUUJFez0oyb1peUHEEMsYqSN6nFeSe5Sq1ZBueDQNZJ_UNEhHkYXPQ6yagcpzQgOe-Z0KWcng7jJ6c9GqjapAYJYRyHtm3t6YrbMzszE6kxBKk2sYQdOy2labpc8iQSVjViIjD2oYw5upBFERHQvIvTP1fVmrbL45YDDMOwaFu1XFWJiJCQnCEnVa8660LbuBeeuaIJU0mlmAqMqZoZe8c-UM4pFwDX9ymELpDTlKHa3s2DN7_-3rOvPJO3Ve-fjsgY8PHdJ7u7O5_--Euz-axfr_a6ePXyztHpesvZE3HjNusNgl062D84XJw-Od27MdfHJSfxzjmiJEIGuaqLzMFNMua2DVaNmELww1jEZIqMbvvRe1_FPFHJ1ZEL0YtI45yaaRXiid3n1mMSwHFIPtDQj00IiFBUjFFNHblRdTsmEzrfbvfnszElYwsxbmslgmFbDnaWiiV07XoY1xdbmY5NoBRZ0EDEas0jFAR0EKI3RFAjQ3DE5AUs7rn1g94MKGBc-DTkoR_nz-ylOkqxtuu259t22bngakpWtVQN02I8CyDtXb-6Ono0rtbpfG21ZxSPgNXKMFSEcb2aNXGz3jgBzWNomjhr-vNz5-Tk3r0wm9Wxttd3t31_7ebVzdlq6EeSUpgIspZc-u2x8wGhDqvtVBpdj-dFCjrWqhNqysBqyTzBbhnNLOUiVcgHqUKqaGQVEBwYISM5L8VEtNvpmhBUtfHeRsmDVMIMkKsqGrCFGNabkRzFxgGY89w49t6PfSJmBPKOh2H0xDF2p8fHV64eppr3dhd37z5sZ4ss2uzs5jI2Lc2XMbbh2ZdeeHz8aP_yldV6vb-_pzk536UiwXOVujhYchtCG5YHhy427WKmJkhkZn7a3KmGEFxgRGhnbR5GIlZTBCTP7DyaoSEhTxwVAzQE572IsYtIZIYK2radCRgC-ymoo1N6eMxpKhciwHR3JXaI5J0DA6kKSN43aEroVCv7EHzLfuqwP105AQA5l9LIhIgMgiKmYGj0NOwBuFmtuuUCiUQUkJgQTNH7knP0johySeg5VclaufFf-fXf_2e_9rt__a_85ctdJLBAfoImuBh9F0GhWTRIT99hU5sNzFRrzhmRwcBKnZA206zXx6AmqOK4ETUlUgUwAMHIrvSJ2ZeUCMlEp0EsoAGZC2FqtHrnAYGRtVQwAATnnFZQswnPz56A5fmPvXB2tFWhUX0WAUCtVUTHXB4dHX147_FHdx_sXLu-v3sw72Zd4713oiaC0YXYxhA9OSB2OpW5kxBi8DSR-Jp5N5EZ0jCqqqrWyYghMkGdiFGk6B8Z3VUmzIWQgRRBA1UNzpVSVKTWOqbRTPt-K2qr1YqIDRVU5k332mc_8fWv3xexqmZmaUg5SRYZxppLMYGcJee82fZPTk-RzcyYCVF9Ezb9ltkTIAiqaBExFbWCoqaQ0lilbIdUTAGhllJURikC5jk4iJPGbiLIocG0HKVZbJvGECk4H1jMDKiAllKGsQ6pFNVarE-5CAxVhlGT1HGoqiBoalC1ilkpNdVaRSqIqCgoeUq5Dn2qCqmWMVdVBXIuuNiGnFLKmQAjcykiRQEBkEWNiKmU99_76PN_7AdiwPfffvTcs5e__GOfvXa4H1z4p__iN3_xl_7xV__xr_61f-tf_9__tb_YbzeTMHJ32aGpA2lYjk9OtEqtBdCGbZ_GPAyp5JxSlqoXfd-P2ZiLmU48buRxqHksY9KURQyJvJiKFDMpZUIvGphW042Ov_2Nt37pt7_-7e-_-dyVSz_7I5_5M1_89DOXd7Lg0UU5O-kvtvW9O4__yR-8_bHnr_bDsFlvx2F4eDYczMPJah1cPFwuj44uHj66-PQPvj6L8cN799fbbKxDGrvAD49OEQwRVLVmffWl5-49uH3z-Zd2Lu0oUCrVO4KclhXzqt_2w9UrV2_fu_PcMze5cefrs9CEF1560Xk4enL0U__yT45D_h_-7i--_sLHvcOvf_ftu_c_2m42rlQXQtPELVQNMNatMgqqkWubhpg9oilqLXfe-2je7vJsf1PZBT9rF2XUcRiP7n5083Bvbz5_950PyvnKhdjMl3XYzJvOobaRzy9OQxOsDcg2JKyMe5evbOpwdLFpdy7tLHYNwaHH0IV2_-Da80PWxc7B_vLg4x_79HqzdYWGwcbzVJXyCBfbnLXWPIIBjuo5sG-UvRiBJzFtYmCHjlypgo7Pzi46iFjLZrMuNq5XGyeBHJGHzUW_zUMaxlIFQPtVzhlA_eGzL_vlwdnFRoqp6Gx3BwmePHl0fn7edJ2N5eat66uTszwmKaXmenBwuL7YaNLLV6-G2Klq359_cO-huXD95suCuB56s3pytkq55kIZ3Wx_9-7tR0WzAl6-fLhYzp599uaNZ66DszGPn_6hH37hjc_sX72y6S--_iu_3MwiqLULdzqsxeqLz9_47rfef3T7gQ_RETaxcwGUwRxeDOfG4Yd-4kdSHhE0iypiGnNofTEdc74Yh1KlmFawUaSSqpTNtq9pVDPnooJVk3UaiMnQpgZnkeq8l1KAAJyZQc1Va5VSQFWkitQipVQxUclFRWtOoGYlA4LqJIocJ12e98QAyGRgzhEZSq0ueARkz2iA5mouYGBIFBlAfAy51r_1n_77r928-l_-X_8_f-s_-2_-d__n_-IX_su_v3A-JyNCqIZqnnDSQU7AURRFg729ZdM1v_Ybf8DeIWMttZQMTP1qZHbT229MqZSsWqVWgWqmbgLgqTAjEiOyqYmo1gKKhkjsANGR-6NkrHcugKmZptyzYzAQE0MFqdNVqT7V6pGqko9gBKo1Z3aemEzEsTckEZnSMchEPFm9zBEhgZrCpLUFQYeIMNkhp5asZwdqeRgM0AdvaOR4onWoSPBRSl2frlRq6nOIfj7rJlxnLTVlyakAu5xKNvXshn6IwddSbt95cLq-SAZJ6pPt-N7ds2-9_-g3vnN7S_60T29-eHcYx6Zt27aDWruunXXBEdQh7S66eddozQjQti2DMdl8FiMiqm4vBlWJ0eWxIAJ7TqWWOjUmbczFwBA5pTqpFaqqggkYOwZQQhQRAFObAKmmqqJCBsG5tg1t287ms00_ikIxq0BjFSAyMwAqoFnqIOrYlaSD1tV68F3jAqlURTCm2axZHC5PT85NLNcihglrAjHiykaOylC5jeqYltG3cTgrYhi7plRoDnbanYWq1pzVMFcbzntuZ8pcSxm3o6n5mW-bzszCrOUYSi4ylDKMj--8L1XqmGb7BwZaqw19llK3x_fHcQtEQxqFLC4W0LQXm22cLV1oYhPKMM66-a0XXz46Pnpw_4FIzmk4PtmQ2kQ48VZFtQz9OvUJJmo_gxmUarkIEDvv-9UgWaYkmZSa-tGxVwF2ntnJ9FyiEQOozLsgWQlZmIJrCSFPOm_PjEwcjCA2jpj6zWgKtZblTuuQa19NLDhHjmvKTRNMcXOxBoC2ieOQAaTpZp5puVz0Q7px63ITeDaLy2UMITh2UoWc265Wy-Xs-OGj5c4CHRUFKYP31HYtqctbcYgU3LhZlZyZqBRh59rZctJX5VKQ2fmoZm3bNG1jCCZSSgmxnSC7IbZG1M3nZgAISEzOI_LEemfPk_4wBG9qpkaOVCv7SS-IzEQIAFCrEFPN2YUISITAwUkp6BwSAwEQ1FKACQ02q-18Zylagdk5X4r42E5pb-enhxhSLjqRF2DqqpOp-uB8jCI65bxANTQNeeedR0BkADHCOGj-zne__au__dV_96_95Z1lnAfa318sF0sg79iDgqfgfVSFipBziU0zNYock9REzpBpQsQiEgCVpAiAYExuOhQTgnMsOYMiIBoDPz3iIxqy81IKEpkIIT4tVdpE5EcTIaTpdckIwXvVGgixyOvPv_Lw3lE3iyDmmaAUAtSsjNTnoeYx5fzB99_MJe1ePtjd258vFkUqOhJAVSVmEVMzdE6KsHc5lTQm9gGN8zgg-5qK976WAmBgqrX44EWLgRQRMbM_6msREQIQOZvkyWaSJeWsYESkIpKl5iJqKeVxTClnNfTBE8izV-fmAExUoRaRalqFjQuI2tSjM3RoCFV0GMpm3U_Z_JRH38SUi3NMZEDqPTpGUKsizBS8V8CqxQyrwpBLLeIAVVS0jsOYUhHVMRUxdY3LUoAxj7lIUdNUCiKIiEOO4IxQRNSkpDqWOnWqs0gaa6oiBmksE_HPAHKZiPxSRarCnGMVNsCiUlVTKmYgplmsVJFcVaXUuu03BaoyCpgBlFIBgMlcaP723_mlNz713I_-4Btf_8aDL33pjdc-9tzBbncy1P_H3_vlo0enn_v0Z_-P_-t_4xM39s76ba2oZt7zmAcwQ8Xbd47feXQe_JQLmNQ-VUSqmSGlXAnZwIILwbMhqtgwpJSrgOVai9Q8liIiqlUl1VpNnGMjPd0O33779h9-5871xexP_dAn_9RPfOG1F69G74_X-d0n6-8cb47WkkQN7Le-9_5f-Kk3rux1s_kMvW03fUcoTKCyM29843_j69_8_Oc-Pg_-Yr1-69HD55-5xKBouXPN-TqTY57KWlDf-NgrH925HZv5K6-9GkMkdBxC8O5rv_eN_YNDLdo4t5wtL85PXnv1uX4cAbSZNSWl483RMy_cmi_bt99789ZLz75wZefj1_eW5L7w8U_OiVrv9hrfubq3M_PB2mhXbxwAikbPDWWqxcb5otlZ8lirY3Nerj1zs4INNe3u7M52mizFg3Rd98KrrzZ7u_POKUul5D13s6U6Q8wNaxs7FyAwrrYne_PZfNE2s27g0UhyHbvAbeNOzx8udzsKcOPWdXToHGcYDfJ2Pezu7Tv2DLrerELjd3Z2nx4FvNtuNk0TCSLHYIjoyNiJaghNXm_JQWwCGNSSZk2jmqCU2bIdxnN2AZH8IoadJtW8mDcIpabRah63q5IzMe7s70T2O7tLUuvP18i0WC529_Z39_e2fd91balpMZ9FsvXZWTNrK-is65B57JOXfm-54x2C1b1Fsz477gh9HvYD37q6c3p88ujJE45AKa9OV2yKpmm7CYxXr1x_5Y1PXH3uZb_T_tY__dWo6o1-4KXndxfN1ZvX_9LP_ok0ZiwjMWBNsyYSgifWsbpRdZCuW8SmMzXP5BxLMQOsIDmVWmrejsN2rCqbtB1qrlZzymMqpJjHpFVUyrYf2DEyhHYOSLVkmHzXROgcxYBESCSmCiYTHJdQEYlJ1KRURjCAlDMwksNaKhqoKCGaiDzdoCqATcdfIDRVY8w5sWetUzHWGGgc-5dee-7l68__v__uL7315nevXZkRuMVuRCR2VKqpCqhIkon5MbVFAQ09LedN3qxdg2OfchpLzRxISo6OtWQmIgbNI6OaCjsHpoTGzulUSZqEMjw5foA8pX6DiLlUpoDsAFRzZfZkxuy9IxUzVRebWqtJNTByjIxPWahAUqsqoHPs2VQJiNkhktjkEFEkLvKUR6FqBiCi7JyI-RCk6rRIIWZyqGhmVUSTViAkx1OwColVtdQKxAjIzLmOTWBmMqwffXA7DalKJe_aLoboQgyIYGbvv313vtsZ4sXpWU7jyZPzD799u4u8XQ1Xr-5JTQ-fHL9z58Gdx-cr0Q8fHN07OhazNvhrB7s1Z6niCINzhDhbzIgIQNs2Si3nq23TtAK02mxDdCnXWqvzXFKpuSBTrrLpR6lWihgAMTAxIDrPKuocIliMfvKte-cNUFUMpn6JOeemPTMRpSIG0MRQRZ3nVT8QTQBGz55X2zV5Oj7bWLHdebeI8eYrhydPzlKfa6251L5KdUSAHN3ZZgWKpYyWlQgVpG08oPmWQYWR0roCU3epIdCyTdvHvVSFiNxSyqoss8sRgbdnvTiAljDkkwd31kfnwASAUopv_Pzyfpl4ElL7zakjyjKG3R2_v29M7d7cAezsLVIZXevYYSlJkJl9LtkFB8R1LLVWrWkY0rDdPnl8Rm1s5g3vv_ZFJMxjAlAyMRE1RWKRCkSOmBlVxTlnUl3wRKQGCMYxgqlU4QnigUhuYikCOGLHMcRSjSI10TNoiH5zsgmdNwRGqqIGxGCEGLsYvGe0fkhN40sRYjdxM2J0NSfPHkgRgL0301nXqIqKykSJAezXm9lsPgy9VHUhoMFmtY7BmaKAERI5Xu7vpJRj22oxYgAwBXSN884RTqc18E3DTKWWyQ7rYywpNSGKChASBUBkx1P_D5EMAczI-YlIRUSgMB3tRSoRE5FI9aFVAzBzzGYAyFPfFCfsJE0g4YhEKmKIYMDOs2NElJSQCYnNYLFcjtv1ZrW5fv3m2ekRMoGZ8w6YTI2ZuGEzBH5a1CUAdJ4Id_f2-s0GQEE0Bi85T3A39kGtMjkzqFUcUUpCbSBy67PCXfhzP_0T7731bpw3Y8p5zFoLE4EqqBCCikztXlCawP2m5rtZ6QsRANgE6Hqa_5A6lYDBbMpUgCESTpKUyQLDExQZDBTZBQTFydhVquEf_YEmpkYYDY2ZS07dbCG1bFP_cz_3p956890nxyeiClJBjCZXQ4W2a_t-7IctqOS8PXty3i0WO_u78-XhmJOVQoyMhIaO0TMxspoSEXpKOYfYAKBOgIvoABB0Yht50ErgRSoRSVUidMwELFUmVSUR5Vydo6yCzFPeyUzZTW0urFKlCjpyYMS0s1y88eqzv_f1t2a73SjgEGoqSFSBHWAWGbU6pmGowXkwyzlPH0hmjwilFnpawJs2PiylgIEYEmLr26qWciJHjngo2VRDCG0TxiF574iJmByTgiIxgJFhTblW1SqmlrIgIQKqqrdOtSJUERVQMVBVBhSFkjKYiZEUATACR4QMbGBjqYxYwZCwTGAiAlMqpQJSzrWK1JIBGIGarlGZsFjVMZsCMqrYex-8_96dD_-1f_Wnv_71D7_4pU_dvLp3sr34zX_-O__wl379hRdu_i_-p__qJ19_wchylioGwCY1DclUPSEhXZxdXNlpF4t5kUnaKDVXBQDEXFRUg3MhBLTJbQxVqqoamyKOuYhWcFS1llyqmbFuS7p_evKb335wMaTnrx--_uKNF64feO-zyNm2fnDv9Gzbn6zTjWU3b_28a8ac371_9MZrt0gJyZPp2x99dO3F67PYuuCWTXh0vn337vFP_PgnVPXr337vpWeuh8Cs1XsP4D965-7rr14hMNDSdPFwZ_7__fu__MM_9mOb8-N3v_fWtI8EEx9n129c2V12AKq1tiGsVpth1T__zHNq-ZWXXn_zu9_ZbocQd7abk49__OXDnSvff-ubpyfnjx_e_e533lrOdr_19W9dvnJlMdu5dOnq3nx_f3kpdPN3v_u97cVGUj_0uVn6O3eOfuDzn6W4ePf77_zIT_wQVXnu5Zd3GnfzpTduvfjC3fffu_nSa-fnKynl-Mn5zmIPCLjyK6-_8o3f-K22bU3xbL197bU3fu_3v_YnfuKn3nznnR9841OG9PjOO-NmXG3OcxpuPf_Shx988KUf-rwH98nPflZKfXz3DgP3m81PfvmnH969f7i_d-fe3eeuXRGtr7302nyxeOv770ZATZkAn3vpY3fe-v7hTsvACrWWPJu3p2erF198PqsdHx_t7OwO682ynQ1DP_NhzNh5njfx0o1nXnjpmZrLJ37gte0qHV69styf337v7unx6vDq5Q_ffbft5pvNZm-59C6M47DdJh88Orl_-3jRdnuH-3uHO7kvQyoUfBODoK1OVlpkm8cn9x6fnp98-PY7rlrejLdv3503TRa9dHhIFT-8816_SaUvREgmpRTJUmplona-s9zfuXr4zGp9_uZ3v3l8-_5m7D_5yU9enPSzhb917fJ6s1bNjfc1lxidStlu-651_TaVWmg6ggGoaTPzWYDAEJAJVXT6rPR9nk7MCFazdEyl5pyyYzeR8GtVcuTZWS026cTMgNAA1IwMCHFMmZgZqeRJPMlgWlNBRkOdgBhV5Ckwz3Byj6gomlapMGFJ0MgzmAJMJBKWaaYG0vjYb9N_9B_-zdbwP_m__ELV7GZxve4RqAoAaBkTTotyRnYMTOyCGAS06PnP_NzPLIP_xvfeHyoVrf3Fhgirmfeu5mKqWgURvWMpBYlV1KEXyUxYSyLmNBYOTNPIR5S8Y-ccT7zuie9v3oUqFQkNgJGKyuQknnYCyM4AtErwUVUQlJ5uFdRqIUfsfKnivFNVmLTuOJ1XUERc9IiINI3_GpioxYhN1-WU2XEIfsLyTdA8H1sERDDnHbNznq8cHHSzeDhrvvTZTxzuLmIIF_345jsPzoeMgcV0HLJzIY8jgLimY8_9dkRyyMCmUmvwYRhHF9BM7nz4aDGfqecq2s1aRHv2ymEqtWncnfunF9tegapYjB4Zdnba6FlUHWGfCxNNT9Csi4SoorXWtmkQgR2NqVQx9pRzJWYA84QheK0qTxfg6JjljzI_zrEjIiad6ChgBmRAVQXQjSkjYR5q7JpHj8-MsB-TGHTL9mI9pFzGqvNZ3J0t1tsREVfrLQAksSGXo_OLdSmpymY75Fqdc0RQq6FBYC4iiEwxICORdw2FeWx2Z6FriEiZKKJsU-mzbnusuWwGQ2w6f37_PCzbxcFCtwmrrc7PYjcb-35crbMo-1byOJt1Xbebh75dLHMZHPr2oD1_9ERTqVrand20WlmuzaKtUqefc-qHkkdAXl4-pIDr49M8XjBhRX3yYM27r38BCFUzE4JKzYpEHHwVYUIfHQA4F0zUN62aTmAbNZOxTBZrQgID9gyiUiXOOjCRYuyIHRogiBEhO2yj82SalSIaQkoljcUxLoOvZpLFzIjRB47Bi1QfmafVoGku0nTNdr3t2janMva5nXVt154en7lATdetzs99G5FZkuSUY4hmELu2bZtSC5Pbrtaz5dxExqEHhElmnFOJIYzDmIaxXSzStt85vJT67c7-Pjo2rT74nJIiEbvYxJwyMuMfuZDnzbyqSC0ueAQANSA2AAAIbdQqLoZaBZG9D6LKwU9tCkRkZlBlz6rK3k3rKued1mn6CCFEAzADF5yUEruYx9E7X0qaz3eq1FJz4wJUBWYzQTA1NCKVCTeDMUQTJQ-GQI5KLmQgJQuAITBFBROtQI4dlZw9MQABu3a-U6S__eHd1z7x8hc-96lS0ma9zkXWq96YSl8CoZQKzAAOzdgxmJFjqUY8wS2NESc0EGg1E2QEQZqIbMxAqGITjWuK9YuIijo3eXPApBKSqJkhM8HklPUOAMxAn_acCpFTqM65frj48pf_xFf_xe-PpaQ-qdRpqhJiS4Bt14DYerNFRa3VuA7bzfnxOXqaL5eHewcidb3ahDZUJanVxyYVMTBGMgStBQjNUKuamfchTyCLWmddW2vFp6YvY54CS1hqdZ4niETwsZZihqbgHDpimT4zUk2UnVcTYhaVovrCs9dfuLz3-MlpRT9WUdXtmNQwi5FDM1v12-A8IU89g2oGhGpQSmHvpsEYMyKSmnnvpCr5oKgENAFnvaOU80SlHVMOzrkGHXKuSgDsHAACo2Nfc5nyQKUIoDK7iXCPiFWhSipaRTRnJfKp1mpqikWEkExZTNCRmpVJAYFogM67SfYzyYnNwAhrqYBYp5UZmqiqqAG0bcxFkCzn1MVm6nWM4_hP_8mv_pX_0b98fj6-9Nw1ms_-0S_-ym989bfHvv4f_sN_-4d-4A2TPI6lCiCSIrDDXHL0HJjMAAEeXJw_e_3QswNE0YlJaABUc3GOQnDOkUOM3iPatEknolJNxUSBPGWVCpZIH52t3v3g0d0HG-f8p1-48vrL1y4v24b9xain5-NHF_2Th1sgaGPYn8UmehllKLLZ9OtxvHllvyatSgDwy1_5_Z_60R8cS91ZtEOxP_zenR__0qeaNqxP--9_cPuTH3spjZkcC6ACHR0fvfLSLamVUWLsvHe_-Rtfu_X8a4jj-99_P48JCb2nO7cf_fiXv3R29OTy4S6xc2AeeRzSqy_cunbl8uNHjw8OD_d2dj7zg5__5V_6R8Px5satW7_z1rdev_rctYNnTh8f7ywX6-3GIbz94e3N_ccnT067rrt__86Te4-P7z2MDeecTdNYxr3lzpP7d20Yymb1vW9-78ndj-49vP_47kd3b39AeZy1vqzr8YM7VMd5O2cpMw57i-unjx9IzYH8ydHjH_j0Dz1-dHTtxj6utdn187Dbb88efHRvPmvYe0jbnUU7rC5W5-dvfue7jx88MIT5vMHQnj68_fjk9J33PhjXW5C6Pr946613jo8ez7w_Pjsmg9U41v7cN_5Eem2COMAYjXmEsrF87fDq0dnj1vtZN3v5tRdPj47Q4Sc-_WkK8NGdB_uHV8XoxrM3xVCRlLyWul73B4fL2ITZYh59DOzbeSzjmKsmFc8MwM--cIOwrNabBw8fD2WgSBdnK6vWdXE2a_b39jfjsH_5agzoShYoR48eMNHB7u7Z8dnp-Trn8XD_8qxrnpyc3nr2OqInD1nLRx_cJnabVT-OtVa59ewLF6uV6fDk3u2v_8G3Lx20xm7edjHSZtOD4sk4NM6L4oQ6MbBNP7IjQywpD31SQFXLpYKBqIxjLmZgitO-utZJUDWm3hiYeTv0oNB2vpSiVUHVeVeLCBojGJghChgzBw5VKgIQARAoABHUWsGDmk6E0OCbKoWn6ZGIKhoawoTSZqk1xihqT3VaCMwMAKpQTYOP4F3L9Nf-zb9w_OHjP_zW13xsm-VidTqiWc5FJddSiWy6NqBj9F5UffTzWcdW_pWf_ema8-9-483NWHOpmkZFLRkAzAcuqRCj1IoAzrucChHVXLx30xaWEDh4yZWZzMAxqKgZsmMkMlUiRNBSCzlXSyV6mghgRlVjAkRy6A0UwbTU0EQwMIDgAyFOLuGnyDvPKgIA7B2oVYEQg_OhlAoCzWxRaqEJSooTF0OD96aCTI7ROTeut03bllpi0yCII-dC6ObtvGm2m_NPfublj7_6om4HH5vj89Xth5vVWKpqyWXoByauOZXUX3_mOZFyfnaRx-w9p7E4htlyPm7GmnMpBasR05VL88sHy5xyHcfFvGmcA7T1diwK_Zjappkt25SKGZ5frJFwNuvYOUSbddEz16qTB5qcQwAkAqR-GJlZzFzwNSVDiNEzsDAMY26aoKXG6EVtwlBGHwBUanXemSEBiQkQjmncjrkfcmyaJoT1ZuObdqjJzMZtCT5upWyGshpHRGzQCyo4KooPn5w2bSiligh6NIUhZzOrtVyZzU82Gx-dIJZSCXwp42J_PgyjbxpAhEBSpaCgj6tV6i7Pm45zn6wAqFfQZh7AoCQxtLxNnqPl4mdN08aqCgZMwGQKWmoWKRNDe3u-XjxzaKsV1FKGcX7pihkAKAE2sxkxUuDtau0Qm85LElA3rLZNQ-f3nrCLEavTIsWUDEvJCIZkITioNRBZUYowObRdaPI4xtks5wwEJGAIBGhVUrb5clFTCjGOMkItLkTwiMTMrpTkZi2UmvpCXmZtW6rUpAaUii7bgIbbLCXn-aJxmcZcai3Lzjc-VJPz9Xj5cE9q8i6KFu9c1Trfm_novfd3bn907dazJY-MvFguxpLmTbOtYy02X843qyH147AdZruLWnJwro5jLbp_5dp2fTHvuuOzi4P9-dnJebvsHO1IrbFpjh89ns3naUzzRbfOpZYS266mJFmS5ThrSi7ko5QcumbIY4htymPjF6OsDK2aOe-QXCmpmc3Gvvc-TOpvZqdqAKiTLhdBhdDIt00Zk_O-SnG-dcGkVjMzAkZXScTUFNi1w-qMOseADx_fvnL92fu3P6xQAlEWJaIQmnEcY9OklFRh4o4hO7W6Pj8_uHJ1u7pA5x34arWKxc5DrSYkAlpqcAEBJI-c-eLoiXMqs_if_uf_r7_5N_7nn_3Yx-5-9OCeHRHxdBpz3uNYTKqBEhAjFVHHjh2QgoARO5MC7BSAfaSEaCiqoEBApobOheBKzoDo2k6k-BAlJ0BFeFo7D91sHLamCsxW9OnOhZzUBIwmuZvPyzgyk3Pu-q1nQsPNLKzGBMyoSIbkSVWRUBDMe_b-aV6zqA8UAqyPn_SuAUfXrt6Is_2LizPUwXFTa2na6JkNsGO33fah9SklpIlgU5iwSibgWidrHDuicUxWVKhOunNGEhCVCsTThB7AJKsLLKJSqqoCQLEeHJmIEJpo0_pxSGWoNOdImHIlRwbmEMXAs1v6xmol4qrVkIHRDHPK83mnKpoFI5sCExNJzsV5NykJ0UxMmIloyo-wqnRtBLC8FSRr2wgARJPEAnNOPjgEEKjIAOhTLm3XpFzaNrJSRS1SPTIQpZq8a3JOGJyZGDBA9eRLnYwL6ghBgByaIoLlKkRsIAhIAMF7NQX7o_4gERBZlXEsxCaqbWwVIDAcHOz8wn_z1Z_7-S_P_E7yq37V_7f_-f89p_g3_t1__fLBDUYZhqGIdk0AVRMxNZGKABP81BARpcDTe5ppRQNVMCFAjT6wN-eoiT5XLTVN5RlTlemUQqyq_bbUnN97cNSLAIUXb12bx8bPYgAsVcZShjwen21LLuz9tStdYFdVCaCmKqC5yPlmfOXFa6UaMBCCwzDf6aqpbxtA_oPvv__CzauXdrp-M56Nqe3ahiEQqQJ77gXWRif9ZuZii-1QzIPdeubGP__Kr_zgZz7-8U-__nv_4mulpK7xDiBgLAMQey-2kr6bLx49-M7Z-jzM2sePjy9WF2MaTzd1ebD85jvvfOlHvvTJl1996cWPXbp--fKtaxXSy2-88f57bz1_80VJYxsjEb3w0suvvPzG6dlJG2YnqyfRszfd4fDunbv7n_nilauXnr_xQgzN-qPv7T_z6suf-NRH995pWrx85aXvffN393eu3rl_9_7xg93LyziHW2-8-uDBnZaWewu8WB_dvLn_5ne-P_fhYLl_cXLy4z_4o595_VM872LTrc5PnA-P79zb2V2UVA4vXQbw82XrIj0-e9wJIsMyzIfcp-14UXSbts9dvxFnM-dxLHXMGRmVeLsZes4euY0Ocx5W2_VF_y_95I9vss5CkyXfunaVd3aGqlcODs9nt_1B82i9-vDDD1_5xAvnq4vjR-_euHl1b8dXGUPcjRDOj47VoPP28P6Ddqfbbvu0OYfA9--8D4o__MOf--bX_vDJ0Xm3t0xjJiYAms3bz37-00ff_-ixvN-fb06Pj5658cznfvhzx3ceVxzG4WK3w816a8Deu4ZIoX905zx6ArDnn7k-219ILmCQan3y-O61Z66vLh6Fji8ePvrdr3xl2Gb0jjztX7_8-sc-tq5A-aBtW0e-6pAHlToOq-qbiLW25DRt0phjjEakoiwKhuicApR-DLFJOUHqPbmSMyk0zCnVNBQTYaJaiyFT4Aa8lMJMNauLXkULCBoYqgKamYqYIoeQxxENEdUhSU2ohuTMKuIUJEIgBGAQncKKhFSqMiEw1qLkmJgpOAatVT_1-dc80t_5h_8wgxUAWaecEwBbriq1psIxkGNgyKoOTGppoDMRIrt57do3vvWdbrH78OyxGhAzAQgaEkiuro156Mk7M5VSXfAqxUDJN2aAKiLC5hBBqpoqB0-StCSOsagBce5HHxjUHLuaRqnG3rOZ5EKOSx6JeFL2ogEQqQo5V1NSJ-gcklNVZGR2jM6xVqkqigR-mpsgOM8mqCZgamY-tpbyBKN2rpM6EHItiSOFrlWp7J2poDEYAljXOKT86qvP_c9-5sv3Tx7v784886YUarFKHsah5LGOo1AhIgLcbPq2DYRQ1RQwtqGkvF5tkVmN6pA9c97kD996WJPNZ3Hv2sG9xycHLy_LmC9d2h0QzDkg8mY7805KFWaH7nyzart5QA7BkSkoOO-IkRDI0ADSmIP3fSrzeZtyboNjIELKKVWEWRcnD71UQwR2joDMEAzZeTNQVTVQ0aYLpTQCtR_rer3ZmS9CbC8uzs2AmNmDlmpZl4uuqCWpwBCDH1KqtcSOLi7WwYUY2yEPKhqCr4ardX9iqZ23uVRu2BOyGqCXlOe7s35IKQOb7T976dGHd3O_8VHXJ-vZYfA7c9uq9n3e9tvaY4ykrOZxOSt9pRBXj0-W1w5D2wznWyVpFrPS9w5MNuniaLtz6VpgOn3vQWy6sh2JZHt6Pl8un3v2lbe--_aVZ26tz06BoJvPxtPzkcam2_GBgqNhu3WdW188Odzbd1KrgXFDOSmDghGBM1JRCE0EgBCarLnWguRqqWbo2Jd-E5xXER9icAxafPBVKhiKmpXivGemkkZCqqtts7P0DmuVVGuMzgCziKkiYIhu1Y_LdpZzYecbBGji-nyz3JlZqpcv72w3o0M0TYvlDAiYCAHbWdtv1s-_-NLq_Lybd-v11kwcUedoZDi4tH9ydL68tLO96JV42A7NrMu1X7Rz9lJSH0L75OhkZ3dv0iV4CrFtVufnvmlC20ipJVXa8WoYYpNLne8dDNsNsDNT9ORcSGillLaN45DZ-VL7GEKq2XNAQJU6TRR9E2uWlMVFRGYfwrDZMLNk4eDIkwGqmvGkDiEzRWaaKABVCDB2bU6jgKEXNyOTGubdMPSmOFvM02bjQvOUMk_EPoCqAwKPKlrVwCC0sYypnS9F7rFHJGSOY5-kFEIyICQGVURkz8G81IqExSArhWD_2X_7__yP_72__qd-_Ivv3763s-hOV2tDN4w5LrtyviJEIASzGMM4JmIiwOkNI1WQUAERBFCnezyCeXZVBBBEDR2DWhpGFx0YALGiIyYkymOqNfkQcs4KSo4ACVSRaVrOAHDOiR27wNy6V1599cH9oylVI2BoZmqERqRWrI5FjTg4EkM0AgOlWrFtlymvQd3de7d3Dy4td5dtPBzX25OTM-d9GpOhEbFvfS0jKACTVkEfpnar8zSO_bQKMO-Rn56bOXgDKCK1VgYWMkCotTh2xGiGAFZr1ao-xjGViKFU4UBi1M7nLrif-onP_Ob33jm9WBGzQwagfsiqigaEzgd_vh6cd2Of2yY4DxjDOCQj8-THIYXgGdURFgCtJlrcNHQnlFLMESKqmPchD4k6jt4NQ2au3kdAEzCPOF3tTA0heIcgwuxTPzZtTGNmYsfU-IBItdRqsBnW7Nx22DrnPYuRoaLmikyIQuBEa6Bg03GaSFXVzDEaYMqTT9c5olQrIeQhOe9BK7MrJWetSDBr-Cu_-rU__XN_Yr5oHp6f_8o__vXzs9UXP_8Df-HnvzyOsOmHVGpkNsNSKgOqCgIqTN0tAiNDM8P53C-6roqIIE3tQs_oHIqQ8zXXQQSBq4ohVlNF0mq16JDSyXrz-PiooG_c4vkXD5fRk2NiX6uurW5z6oeyOR0v7cR5bNtIqiClmhp4ZgQFWiz849OzeddhNlMomp8cnz975VLbBNim3_r2hy3zK9d2aTW4oquL1aXF3IpFoKISADUNtw72NgXufHj7My_dnDtfWF555fnv_NKv8mc_fnD5sJ3FfJEBHZqcnI2j0L0Hpxen2_W4Pdy78vgBfeP7dx798292Xhd7l-89ebS1drl3afXwvfbZ3d2TK3ePnpyPSU0fPbnfXq9rl87KqmxXZYWXt2dTRoGQwDmTfP5gwyVRbBtyx08-vH9x_9zS-9__zo53H37wva-9_72rz1xhoidj3TqBUPIyXtp58WBnsS4XL7780iuvvLhN8vK4Xp8ceaZ-s36yGOT73xzW5eLyWUYb7pdmFtbrTdrmNrT3Ht8RFXnn28Gcd81Z6h3CyXpFWY2tjNvz9Hgxu0qVCdWMmalIrX2Bjrtutq0DGDmAEDxA6DwMg3VdpyG28xiCe_-Duzv7h8lUNms2973f_IP5ckfy8If_7Hfanfn53ScXdx-89Pprt9-__dGbHwVHzqF3_ui-5CRpHdGHIV2sz09DDBzCr_y9f-Cd940bz0_yMHbdzAd8_O6Db4ve_OTzb3_1t2sqy-ifPLx378MPdpdzF2m72jx4LzsfARGAROzhO98HxOBZpRI7N2vTMIhq2qx9nJHhmCV2vmG3s7sMbi21surm9oOv3z1KVcEZM9cKPrJz0XvXzpo8ZhXxMbKz86Nj75xzTkwdeZw17WL32stveNeUMRFzkSI5-eBT38dZQBR2nLMxw5hr27JWJTb2zkSJUasAwFT1r0XJgQ-N6ohIDOS811oA0FGodfTIpVRyjsC0ilasUkP0k_5PKyGpjzH1KQY2QnJcq1U1HzxX-J_8-T-vpdx-8PDK9Rvff_seY82lsEM0s6rRB0T2wVcV730uiclJyRngk594dv_Szne__Q5zVO9q6s0QJo1RETCrYwZCKUpghJCH0UUPqCVnZodGkipC9c7VUl0IVjMhGllOA4WGjFzwT1--aUA0MKi5Ou-ACImQWFRFKjFLFWYEEWU0sFKKRwIiRlK1mpNjx86L1ac2HUA0RXZiZCYg1RGritQ6Gd5UVDR576sWH31J2YVgk7FHCgKBY890OIsvPn_9z335J3_v3beffHT_yo3Fy7eev_Xi9e-8f4zknZNcLppuPmy3E-zj-OxsHxdFKjdx6AdSbbtmEvLuHew9uH1XAD3F1UX_4UePL13eW8wWWssnpzS5WEByDKWIenYAm2FER_NZ3I4mwxAXnVVhx4pqKs55JExDIZwcpjilxaoKoGeHZhCCA6kABmLeB1VFAEJ0jtTUIREzAooJoYphybmoilm36FYX2_U4MmIX43oYt7kulsvtOkWOgIa2Ye8-eHzyzI1DGqv1ed7MTvO2X228D-xo2Kb5_uJ0uGgX3fnp5vKVw_PVipApMorF2Wzot_uHc2ojjSmN48kH9-dXZ-cqIGRl2D4ePfH86iytKD0adQu6zWFvVnPCCiWVpokBt-O2J-_DXqRE2-PNzq1DHGodsqwuTt_7aHG4i-DyOMRZV0ou2wu-fOnhxZlaufPWd2fdYpvKcv-6DEPN4_m9x7vPXBJTEaBSw7ItHl1oQhUhBe-cabEqKfW-6Uw110Lmkg7OudliOabUdbO-72vKzWymqVBwwBi8NzBiYsZ2NptsbUy82Wy72QyluhhqSS4EBpSiQx3j7txMulmTJp8O4Fhz8Iig3bzr19vFvAPTGGOp2jaupLIzm682m8O9gyePjpquHceMwGoyXyxKSd18tr5Y-eCTISCtN323s1ydb5uuNSqzNuacd3b2-n7DztUiTLTY2VmtL2ITY2xi8KcnZ02MSNi03Wa9CrNms926GEtKPjbjOCrSfN5tzi6Y0HlGjMX5XIufNTUVM1REdn4sNTYtaI1No6rEnjwGdmIKzFWqDwFEzAMgkmdGUlUGUFXvvZkRB1BAInS-lsqMzjkR1GTOtUWT1RI8Hz-6e-nqM0f9mAEQ4WnSUZWDs4KKqKbeR0PUKmjab1fz-azmDBTMJLCZijpEB1oSOwKlMiYkZMTUD9S0IEBqncLx0UU3n83i_NyXWs0RCSFoQWLVilMenpz3kksGHckHZK7JEJQREcnIq4FZFiV0TIBWjX1Ifc-EatWpV62mJpY9B1VhwpyzC8GFWEtSVcTp70EmD8SErLUCMxnNdxbPHF4mxMO9_ZOjfr57ffXwjicSqZoKE6fNGPYXPPqq2RCZGNFApd-sXXBEzKgPP3rPxbkLeOPG8zd2D1Ianzx85LGKpVrMVBAp8DS8zy4EyYJYDYCcR6mAZqJiSswqRghIhmggWilPNRkxMX2KhzAiDCRWfWAzzTl3zcxF-vWvvfXczqUrXf78x1_5ypOvIYiIpVJRNEafUppQRbN5Y0V8jEwIAjL17cSGktombrf9bNYaoHNO2WoWA6q1egrOuVoLKOda0CB6n8fskJxzecxmEGIYU04qgZ0ot01XcpKibfS1CiBUESKY1FjOOTCgEKDWKhWqBe9LETQmBsUKBLWqm2BuilIFAUQsMBJNdwxQAyaaFCrCKFWVCYkJiYOboIGMGrv53_8f_umP_MwP15Z_9au_81vf-PC5m5f-xr_1F-fiztbD6rSfLWcoMuRsWEF8JJooW0AmIjo10b0nsHHdu8aPq-QnKRKSmLJDRUYC9gT29GZecjFQRLj96OytO4_vnG4Xs_aTz1199sZlIsqoxUgVtqvzfkgjqAOeNXF2adY2EYbM5FI_AMjTuh4YKjaOTi76a1e1VCulVs2_-Jvf-Kt_-seo2sMnFxfD6oufe90MUq5PLtYbLJfaLpcizrLYWGQj0OzsX6zzptjFOrGG7RZe_8Tr_9V__YvbcWiaGQBMEQLH9Nu_9hs3bj6TNC_c7NHjs6Pjfn5IX_udb166fnVneXj_yelsvlu1zOY7EPAX_pP_grhZD9udmaupkPJF_ZpmKWQNMiDVcfQ-qCVG9cGBWaqmWcQgECMRImy3W1V7wqWdzWaLy6fHb4GIuXespkFEU60qUkrdpP0bh1IK-9gPfTBUB7otFuiDkpnte4AlZ1VTtaaZj6lYlTKOJqJj8otA5KHxs7YzMAUARUm52MK2KRAtlrPQBNcQVdjf7x7euX96-sTAkP1mHHMVHz2CqVBsmmrYLmZ5HF0Imycn6_WaTVFyO5-vHz8mAB_duN7ExpWkdz-8LWkgMsKI7C9OL5xDH0Labg17MpnP52UYhrNz8gAh4og1laKSVqsuOlf04VvfO3rnrYpGWq1q8IxWhotzQ0BAZ4A5oYGisVDVykAlIQOoqyn1JlN3NEBKqtoFDsgl2-nDJ81ioSkjGVQxyl7AiByRY1JJIKlkSitDADLLzqc81iGPoI4cMRkzbGj7eHP9hddM0fmAjFpAiqW-N4OcK3nu-957V1PxSDVlUFBFAAMErTW0IeWScmpj0CGZmdRKRGgmT4OdolUxolp12BBrrRVMyTkVmU69YOKQmF2pRYpxcOgcG6Kh92YG3vlq-dnLV_tVf3x8EXeXp4_P9myOgEBUVQyAmXOpFNgMTLRtOisFar5y_Xrtt0tuLl_a__DsQTub9eNQrPdMwJBzCjGyZy1VVb1zZuDDZEpVMDIARHKORYrVCT5jZqCmplYlBxdVhb3XomSAUgkg597PZlUyIoMqEhOASCVCYgKcrI7mQ6xVDMx5BypEpJN6tRRCQrMYdsZxpWYuuloFCWsVdIxmQEigoIjEuZTGBwJAIN80IiWERnMhjNy5RRP_zb_657_7-9_86c9-4tvvfPQHX_vW66_fePv9Jy_efOGj9-6v1pvzi7Mhp2EY61gIybQokIiE0Ei1EJ0LXsZRS24ad3HR92fr4F0ZMi_RRqdg25Qfnp56XFysh71F2NtZ3j067pxbaw3Ope1Yc3bkzrfr_Z1F3gxWimtjLsUMmuBzKoAEBNH5IQuZdMGXnBvnGs9dCMSktapqdF7VEKFqbXwwUWRXsnCkaeuLaIBQSlFzJes25WSmDKdnF_vLnUAhunC6Gtf9kSPPPo6rs515t-0HkHK8WQlBqbK7szw53RKzmkrRbDLm2s3nm82m69phM8xns_V6aDqftdZhaJazs_N-vt-0oQORajI8GYJzY601QwxcctqsJczanVdunL9_UjclrTZu1koqYT4HBnR7vulEsyatafSzsDk6jzG6neVMVPqx5pGdk2I5D03X5G1_-vBht7Oc7-48-eCD5ct7WMv25DGoMvKYy8ntoySFmNNF4diKuInKokBMhDUbEgKY1GpAPnhjnpxsadg2cZbTyI5RwUCAwEykmjhHTICICgTo2BlTGsc468zUBQcIajhV8EWUHTof-rHKUNQZVKyiWhA6RMZGIPiAAIYqoo6pphS8SzV3sbs4O18sZ4BkptxENaOALvD58fnu3s752QUgeibnWkIoTFYMtHIMc9-dnlzsHh7m0jvnN31PaHv7u4i0PluPKR0cHPR9z-z6zWZv7yDnvF1vdg4WmwsQUe-8bnMp2QiQHVGoqEzg2m7cjmjoY5vSSMzsDAE4RIfofFP6gVE5UFVhHzSXGEMaBu9DrQWUBKzr5v127X00UyQyqYqGQGrCPqgYOge5Ev0RQ4C5iGLNRMYx1lob50yp5IzEuUjo2lyLlOLMQAGdAy6bi1UTm6HvsVGoigqiZqnGplVLDAweEb1kQURPZERWcUy27dNvff1bP_1jX5wdzPTsJHgWKVCqArZNGLYVwJBdKdl7jyXZhHkGJSSrYgbMTgmYSSqjmhZFJkSTkpmREFRUpJBjMAUDk-o8ViV2XFKZzdoJv-WDUzCRCkjMZADoqRYZx7w9v9i9fO13f-f3bz73wjsf3q3bMxec5ILOVxFkUxUQQgDNxSGYiFZxDsEUwOWhNstlbGrOfdXw0YcfXr1-rYnx5s1n-mF78vihoZZSCNCkIKC6YDnFGExVaiVKTWilZiQyASY0xNh1OQ2ET-2MBtPsWUC45AJqquJjIGJTAZ50brWMeHlJa9l85b__9l_8-R_7wmc_kfvxK9_4njoqRao4MHWMKZVqU8PYAB2hJVEARDYzKLl47wCg1uqQwDnJFcEm2L5WQCBgNQHRqmLO-5RzO-sQNSVRGdtZgyLrfogYIA8heK3QVyNURzSOtYnOAlRRKZUdeecAXU8JzUQUiaRUM-e8GSAhIlKuFQSyUOPYOVZVU_OB1bBIVaKSSwjBFMBPSGzMJXtwtWrRcvXKpW_94Xtv_OTnHz46_fq_-G5S-F_-ez-_Q1H68cGq7Mxa18Y0JgNLORfJ2hg6BmLPQMizlsmA0Qly8BSymKkCiIkUcdGZVBGQqlXAIaYypCL9StZl_N337qlkZ_5zz175Y89d0yZUdlqykFMAtaKiDWHTNUgizHlbWh_rxbao9FUNwXmKRIiYhlSNZ1VPTjci0I85pyxW3OmmacLd0_Vvvn_0M5989faDtbrxxNKji7O93R2k9tjUe9_4lmJwSzjr-zoWK-7tD5984sXGedxdzlORx0fHu93y2Rduvvv9j2oVYnjy6Ojg2Vvf_857Af35xfqlF19W9JcuXTs6GrarD5vl7Pxse_u9Bzeff7Zuy8DjfHffQUWL8w4PLh8u1unhRx8Q8O7upaEOoW1FMvTWtsFRA17KetPMu5TLYt6OqXhuZjuXTo8eaQGEZm95vTt0j-585OYHJ3fuO4-7z9yseVNLbZczGU1QS9Erl_bWZ8fPPPdCf3E2rNL58Sk5aHxbaBzG7f7B7ny588qrr99__MAMumXbX2xMqhrOl8tac85qxDv7l8e0ev_NtySXENvz9UbP8xufe-UPv_YW-xMoANw0TfQuRD-OmzFGD0gKBKqM5o0q-pozVUItVgtHX1IK3vkm1rRRIfIUHNRUoNbYNc6zj13qx71bB3k9yHpgdqo0bLbsQ7cbZzM_rNZgBIzEbtzWAkaEmLVCYU9apUolDNE3ZgIAoqoKBqAGU2YGs4kIIosB5OoDE5IZGZIqGuTGxzrWcdS4s3DOVcOSCnkkou0wUKFKWLOBVSRj78i3gBAcXDq8vnfj1uzwcLG761hNaXWx9rvNo9vHiigqqKRZADClTVzM6liJeMLqSxUFbaIf-4ECYzVjNQAQYyBQ9c5LFVABQMnJx2hgVYqZMjEyqogVy5xg6gMBlGkfJ0hAbOqcEylERghFTQCI2KAaIHkeSlqgYsT__hf_CXs9eXwegpNcOXBVETMkp_a0b-u8K2KgCiLM_Mwzh9uHj1bD9rWPv_o7bz4YtltTq1LNTA3VsIzFRY9QY4N1yERoqoBGCGBUhtTM26RitaAo-VhrBiItlbxzoFZGYie1qqojmugR5FCGkWNQVeRJkGlg6p1POaFUH6IBiFYiJMCqFn2jakmT1MLOiagpDOOGiATMxuRjkJLMDFWIg5oSEDcu9YPj4HzYbtYUg2satWIiRgqRP_Gx5_74H_v8P_57X213Iszc73z12wx6ut6mWsVqrnJ6clFrLjXnlJwHzWhTjtlR0zQmtpjPx6EfxxwZsqx9060265JzlYK9D010wdWUx6zo4_2jJ3uLZ32Axbx7eLol55LUWsv-pf1asphqqV3nYxNVLJVx3nadxySYi8Q2xCbkOjLzkJISXjs4gCyeCRCMyDsniFp10oKZKRiImhGMOTcxoEwlYDRFxamD4cqYKDglt03ZgQX2y3l7thlSrp2LJSmA-davH5yPSuTAL-NHj08NqJShbTszQYWcSnBuPm_J-5pzt9u182a93vrIs52lOuqQV9u-1KJE_cXgohuzdMsoVk0BKtcCsk6DCs6b5lo7nA7I0LhQNms3W5CPNde4mPf9wDF6lNyLGYvLtW2QqPRbMZGa2IWxH13gsjrrrt9YPXgYF_PH9x_sXr0hrtYtm-R2z6-P7lFsZazdYu5McbOZiPs-D6OaofeSc4hBDCYEjYkRgSMmxXHYNrM5EKgKuVClWK3MACqhjRONdXWxjvOW0Ng7kOpcsFKrWTvr0AEoAAGQrTdbqSolHSx3hmE8WCy2eXRIjDgOxTOiwzTWdubyKNyEoU9E1s1aRCDPsQmPH2yFRlGIXYsEy535OAxdF3Oph_sHpxerzbpfLmZDn0JsxlKGMiwPd0vunXc5D6gwW7Sb7dB07Xw5U9Wzk7PZziI6D0j9sBUD18RUJbRtGbP3wQDbGBFo7EdT8SH0m40jCo0DtVkTwASJNKmadU0cx9HqSI3niiVX5zyx14A1l9B2KjV6LwCAXGpm76xWJs45N11rCCpmhLWk2WKeU1GTnJN3zocgKQVylev52fF8uTw7PimAKNUHV8EInKFNzhFwJEWhFiQa1_2lF184OznBSTZLwMRZjQ3ReWAyJjMDA1BEIufBsOZUMunvff3bf_xHvohFTa0WQRUfWHJx0RmCn9RdXSMizjdg1RRM1cVgoiLlKXEJ1RGKmJGG0EzpHVSqUjyzqng3q5YkFQOg4KaqFTMCAzm2auYdViHkOlkpEJyLJqMnjuQv7-_WmquUJrq-V0Al78mxjmKi5szQmNA7RoBasqjVsZBnD6BWy3DhmwbZc3Tbk9PTh_eYXa56cO3azuUr56cn7FRrVTEXPKkikFQBAkKXU47drIqRGoqJ5ykzgkQ5Z88eRVWEvUcDwAmZhEBoBkxUVDRXbthzqIa3Hz06XHzhr_z8D__f_u4_w-Bff-7Gj3_ps--8d-_7Hz5gK2rA5ERHDiQJa87MKA4dghLmXBmZiAg4l9TETnIGqdG5Uqv3noisiJr6wOwwhmCq45i6WTOmkYkJLY01Ro_AbdPmlAuZ5YnXJDaZgJmKGRuIKTkq05XM046blyqoUKsIAqqJIiIpKioQspJOXI9S1LmnwBAENMMqRuzHXIGAKjrntFScFiVa9xe7j-_e-87v_s6zRzd_75sf_I__6r-ybNo5xVwMgWPULJlgyhQhMHW-QbOT8XjBl3gRTIWqsmNzykocw-7BoUwWC0MgmyrOhYEJc6njWmZtc-nQ7t86-N433_mzX_jEalP7JBS5eDdUIEIdzCAVyezMSg3Biybst2G-dOypjGPWEFzed36oCbYf3dt-8rUrp0N9cN6X-fzuejuorIbRUzyrQwne-_Htt2_v2fjhvQdr1aMh8Tgc3bl3VOD9rrtQ3a7OtkNvhjuxFUjjatyervd3d79269LP_-kvd3139erhxcnF_nznynMvvPvObckmUp_cf9S8eed8c_H_4-k_Y25Ls_w-bIUn7L1PevONdW_VrdTVVZ272d2c1BPJ4ZBjUhKpsWlDhugPJmwDMmHANixaMGzDthwE0KQ9ggBDBEhT5IgSTU8iNYk9qafDTFf3dHWoePN733jec85Oz_Ostfzh1Pjj-XKAE7D3s9f6_3-_O3fvlWdnx4-evvfO_fnuAmtcd7nLw8Fi7_pzB9N5nO3vlz410xuzg-uXJ-9Jh_3xqSOf0Wlxw_yI0lV_cTGd7T579l7J41CuAmOYzRIg-skmpWkzb9ersun7zWClNzf54MF75b0suXv-E3eHklaPj9fL1TCOue3n-4tNm9QosGuaZr5oHnz_gY-WN-P5ydnNl--5GJE913VY7KyznoD0akPbnpwvL44v28tl0ziVVKQYOQBm7yznnLReTNo2s0Pn8TvfersKBD6IFtfUBpxSMaGwMyEfiHjYdIAwbIrCWIaCQfu89JM6ZRlW3bSZgKOSR-YwdqMSARB6quK8v9pkJ7hJQLA5XvumJqfsvZXsJ4yAqRiMilVDTI6aZnEgm27ol4gIKkyM3hVJbEDEZgTBucUUNmNFzlIGpqRKjqrJLJ8vwUpoJpqyqTKz7Vf5pDNTx8BIXEqcBsyY2pZr56gqhke3br348c_0YxcndawqZ1JP5qvLjUypPTn93lf_8M6Xfng4G2k-a4taNgAdMFjm3RvX-74rkj2CpmJoTTPXLKggJVsxYpaUi1hVT5wrpiaSzZCdI0clCWz7vLmgGpMbNSGgqSICAEgWH-pcejQws-2oSEE5eNViYCJCgKkkYpRsyABIIgoOnGcdrfLRBfi3vvjRoOk3f_fLk73Zs0eXGCEn4eCLFFNLap7Ie69qkBUdWikEVLS89pFX_9V33n73vSc1M2J2hKnvHBqoIBiRSQEHxkxlyAAACN65YgWZADL7kHMGDr5iGUezbXWB2Mcy9uQdojKSEYpCzmPlYyk5-EqLOHYiBmrM3sgMzKR4dllGFXHOFzUmBDBEHFNyLiBAlhKcI2aRzOxEhdgRkeQMauwdEHGsoOSshdEDkalJST4QkqJJ5avYVOzwF_7az5--8-5__f_-lwcH-__-3_z5b_zxN773vXcdh0cXx6_eeSkX27T9pmvruhbT2NRlGES0nlQlF1VMQyaC9dWaGeomLi8ud_Z30zDWdaj3Zu1yJWRFJcQmjZt21a6WV49g_caLz-WkdR0Wc-0JxnXCwAzF12HoBg_miGVI7LgMhRtIYkgUnLMim36M86C53JrvsEHtWNUQdMi6XToRYC7GzhBRAQmMPUtfNv1QVZEYRZUQvXeq2o45EyDTet2VomM_HMxnTFjEFMB5v1yvStE4c5uSbzx3-ME7D11TnW96YRhz9pVfbjZ786n3vvRFG6pDBci-4jwqB79_tNe2g69C149jSZWvyDlzGmdxczVYl9pV65tqGEe_H6vo1882ksAxpa7UTZ1XGx1TQBqXq_pwBxHH8wsssjw-cRXFWMu4Nk-DlFgF52F8ej-GXfI8tGVcta7yz959a-fgtit-dXHeD0NJKcx2Nk9bR-AjSbGmbqRdlkFzzi6lgt6MiUyhFAIrpbCPAMDMtt3coYoZOQ-gaUghVmU7YGYSlZzJpbLNZ8_mFTCpaUnCtUMCInIhcCA1G3txHIn90IupxCpcrTfexYu2raIfSw4uOo-enUGJ0YF8WAeczmtQZUdA1K02PuxO5jURra4245CIsKlrQOi6IYTQj3ls-2lTqwAYmSEgLyZzAQXnHLvgHaJpFu986rNKquvq4NqBqWkRHwIyfFjQRCJn3rGKOuJhSOR5sbvTdyMJVJOmSGb2YzeOUmJTtZu2bqZ93wMQEYsqohkhOsrFUDMihhjMTDNssTHsg1mxot5VgMoIAgZEWwSbj3UZM4UQUgTbbgmtFGNvzoVxvTm8fvf87MIIQ1WLZStADggBP4wwbPVtxsiAKpJj9EUkuChFS87BR0mJvdMt7q0U1eLZA0DuC4pO5rtMtmw3xlqkEFEIbuwyAiiiFDUAMUXHkgswqgoimikps_fj0JEjEUHHUpQdqSkZi2QglFKcc6hEyIYy9pvQTDULEIgUNEDnpGhKyXnGiCpiJs5FUClq5hwrzBY7OQ03bt7-l7_8K5LK-dnF3uHe8moDaIvJbJO6EKJJHvrBVcWIiqr3DpUJDAlNQFL2qJIMHYR6ZmqhbkSLlgHRnt3_QA1mh4dIuL5aGhKbsPcqICaeg5YcqjC0LUeWJFX0khOiBwMkEgNWJaYt9iL6mHIq44COcy7ElHMmIvVGhCkNVR1QsfG1BY7Bt-PqvafhW-998GNf-OzP3L395a98kzxphuh9LiqiHAIZrtLQcAOaY4haCoEBgYiUPKJzQxqZmByzcyknJCDYpkAJEETFeTY1IMomhBorP7RjrKrgmapYTDWnpp7kPPpYmRViBLOxZEekps65LSoHwBxhyQJGppowU0YRBQJPDGSBnXNctDj2Q0rMnPtCSKoFkYCAAEQUHZZSBGwWI6CNY_u97z_-5V_7xv_6P_rv_9q__oO_-z__W2NS8iCDbTOgytS3_aSKxEgK3rtcBIC_Pbz5Q4ufTYNWTD46UbBRRXMBbZqqAHRSCChv2b5jsSHNvKPk3s79f_m13z8eq__RK698en-uVlEcJ1UQhTGrFS3kimlgrn0THcKM2s1Q1CaBhsu-dYPgZDX2f_r2u_cfnrgxvPqJu__ff_zrd-7cnt288d7xcsJy-eDpv7BRIJTLy0fvP9k72v_Ff_X1r3_j_XlHZpby2K37aEaWgjcOyGiMUJl6X3GVx_UVqcTi6sWMSjlZnt-7-Zwj_84P3n7hxVfRMTrfLzchQh47X_lFnJ88-cDF5uzkwlPzwot3js-eEvPetYO9_d2H33yYj2X5qD84CA--8ybNo6_i0V7TVO708XGFpRgv3_omTQmNHz75IEpnGj0HU1yeDc3e0aT2D7_3ncVsL2WYzhoQzAVr4rFbxaB9Gu6_9_1x1e5d3123Xd2Epo4cWc_bvdtHLOjZRPLFycX-jb3Lk0uuK_KuvbpKfS-On14uj27dPP7g0em7D0qW2NSgsNidy7gJlSdXZyAfK-8Y1Ioq-HD-bLm7N4cECgoOm4P9s4dPa8elKzqsK8_DOrl64utZXMyoClcfnEPGGx-5hUBnj479dLFZnU6uz1HS0A0k7Kd-_8bLJ_cfuiZQqHLX8x5hUlA1zWMqiomiA-JiICAqwE2EyGkcCEkV-6vNbOJLDv2q90yx8ZalJLXA5JjIYcO5yzqIBVMkVCjJtM_cXoaqmu0cCkC32QDi0Cd53IJYsUJiVeNCVRVzaewRUEb67L_1s7OqzgLNdLqIhwKWS-r6pGJ-MWWGb733-LXP_RBnVy18ziV6l1JBgKapDYwIfawU0VQNNHhnyaoqdtaqailSYVAV7yHrgARaFPBDj5JaMS0lFUAEUCJQkG0wBQjR0AyRUCQjADCYGgZGyQ6IweWtVlOBAlkxM_PBi4ghKBA7rqpIFTU7_lZV_eWf_8vnz5bLVXtj76jYFZiiORAlRcdIBFs6dQi-HQfvgqrmIX_hL_7wP_2lX-8vL9LY785mqKoiPgTNhdBtug7NiFwZxaSwczkXAlZQdl6yABMTCuC2h2tIqesoOARmZnBeJSuQUDFE78MwpEzFO7dd7BA6sYyMZoaIpqqlkPMAKCJEznufx5HJ-xD6YWCyrVehpOwCIxMQgamIILFjHkvethRK6qpYiSkaOnbsOA-dixHQrGRXVR__3EfcUH7j135tfdXNdhZ_7a__lbc-eO-_-uUvJ2OwXDjcefGGCN4_PWPvsAAHvyXop2HcnoimTYVg26X9ZDZbXZxOFpOhH2bznfXVeDDdLbj2jo1w03YIOozdauPLfGc7EWqCX9ogbULNjqgJrAAU_XzWEKEWLbnE4IuoKRqI85zHcrQ_n9QBa1RRxw4UtrMoU9nOAcGQGLdCg60DauxTVu2HtOn7JkRVI1PHnACcQ3O0WqYy5q1c8qLtvPe7s8m6TwLSp9FHl8d8_PRqMq-rSX21adlz7pNJoVixw7YbXIiTnXp1udlbhNWmX-zWVIWL5WZ_b6eehMvlKnq6Wp5Xk3kzm44ihSxMq9152KxaMW0W9bDqzp5cEtLe83v9-VJ6V8ZSLSbrp11OIqqpr8H5YlBXs51bVPouX7UKFObTQESgw2Ygv3_w8vNnDx5W83nxLOOQ16tUbyB4X1dXz57sPnfTssa6MhmkAE0ZA9hVQYJSsvPRiYFICSECIqIDAC0iqiFWQy_NnLo81tVUVEy1quqUR2ZXL5q-7arKD10_9BDriRqImkiKTUMoQ9ercz6GSYhJShpSDE6llKyK1sR6tVwt9qZFEjEPeQwcRrPZvMYuq-GYsnfMRMw89N1kOlHTOvoYdjRr8L4bhtl0try8dLHOJS12ZyoKBJt1V1W1odXzuqBG4rLuUyrodTZdLJeXBuDJcXQsOgxjXU27rp3OZqurDYA1s0ZVM3JOY9M0_WaD7ILjvs_OsYvBOc45IRIBKQAzVQ06x6JltrvIqWwJ_M18NoyjZamaekyjla1umsy0imEjsq2mMyGBNwcKBZkRuR_TZNpgPwIxARNiLpk80Z8ZWolZ_mwQO6RutrNI_ZC24nowMOjbMcyaiglE0XmVhAaucuvVcjKdbLpsaM6hFBZVck5KYRcFEdn5ylsuPjgxA-B-dVEvdswZEMS6UjM1c8FZFmIPDAGqNAwGEqqqSOboy5BccDIKO6LApgKA7DxgQUR2pqKiBsi2pXziFs0LHHzJaRvsAyDyDp0jLcxkouRDCD61Haoys3NezKCoGHziYx__6R_-7D_5F7-Ssq6v-jsffQlKAYBNt8qiaoKMokLevFLxXgwQ0REY8qiDC2HLHOu7gTmgIyTIg7jgVLIjVJD2_DTEON-7JuM4tCuzUYq5GE2FHbGhqFgyAygqzCSltG3LIQbvrAiTLymj45ySgSCTobFzgGAIW8o9KkopvppVld-pwuZi2ZViFFZ969n_7lf-eHd_52e_9LlvvfXegydnkRKT1yIIqmgTXyEZq0taUNCsZChElEpyAMgoIo6JGAN5z47UAHHshjD1vq5zSsQEhgBYkpnLVVWnUkSRg2NEE8zjGGLMObHjImqqwXvJxXsuWaL3gFhEAY0CabHOUnBes5hqUSBPBCiqWixn8a4QKKAicSmJAMghIRYxI5BkIUjjXdbNd755_7s_OP7Exw__o__4b1qRn_yLn23mk9N3T-czn1QZYegHIgA1RCMz51wdHBAOm_aLk5-qEdQheRpUTFybCjvfgHznybu3XtqNG3MRIsSzs8vf-_pbv_3mN37w7Fx6_uRLd39s__DjTXBcjdNpSiJKqoUZZlMILo6OT07WH9x_8Oz0HAEQqnCwB_vu__p_-Zc_8amXz_LZOw_OFuSqoykdzLUbnv7JOzSfvf_kRD54NqpVARn0T77yXTWsSiGQ5SkfP3oWh-Sqqq4boTCb1c4ghLC4e9RJeaHZfe_0knJvXYpIe7NFkvTwg25-fZ80D206vzivKr_ajNV0Yk_08Pq1rm2ZzHJ68fnbj56dlBhfeeUNQ3j6_tPdWfXs9GFs6pTGy_NT07C_s9j5zEfeeetNjvGjn3790fHZ1WYD2XVdd_vujbpavP_w9NUf-viT48fds_nynQfSdwB9MQUXp5Fi7t94_aO7R7cv10sI-Oy9p7LGNCQXcLPZ9IP1T85uHO6qMyvjS5_99Ntff_PTP_3jP_ijr2Pllg9OW4B-OYZQtRctKdWVX52edsvNfNHUs0bNzw4P1s_OJruzft0hQ5wEGhOHKo0jI3E9dTEYwpZ-Vh3tixFVnhpidEMpPeZ4tKOq9XQOnU691wJ9McdcEPsC9cHuZFpdrroYw869O_35en59P-cCxDdeefHJ_Qea_bodJgeHYoKhGhSLlIPb150H71nG7EPoNn2z3-xeOzz-k3euv3Rrc76RfjMhbldrTILo9XDfVzXNWmnHoslygSFJcvn8Msz3YU2as59NHPr6uYP-cg19yikbcjzao4lbP7xQw7hoJGcm54KvanA9Wh5TN9LcOXLVQZWn0K37MvJ0Mev7zNEjWB2i56gmKLJaLxfTJh7MOCMKqgiqRe8MQFWMkIigaN70LkAVqjSOBgSS2bEOBQgyJGJkdKIll4KIBupcyHlEZLMSoitFyXlJCQFNDMHMlJhlS6pH2yIvzUylMLHlYpwNjZi3F0VTEDNfObKCzilCVYU-jXvTnb_1t__dl-KuudCnoRR2oRmyeh9QwURlzOzYim5v0KkIsVMpDjmzR8OrixWDMueAukX-O3YJt-zjMA4dM7JzhowILvg0jnVVqQl6zsNokYGIyeXUASgHJkLJWZjIsYxJLYOy89FUqqYu4wjeo5qpjWmbExNih-SsZENGZmIyNe_DmAfnfSnFx4qIVBSIJKeqagBo65kEJFMhYmT2IZopghURMQJAUI1xkkvHHhEsuggA9z5yb_N0-eCdtzddu7d_46__ws8TrH7lX355uerrvWbip-2YP_fp1yjhyemaybWbddEMoJvVum8TYkw5D30nk4mZFSlSxhjrdrV0MagqEKSxa6rGyBB5zIlZh6v-0599fTL35EiTxeDGrkPErd93MttJud_drXLORIye-mF03hOwFA3RAVg9icwY1QqCEiEZMmlRQEYiNZOkhmJg5AhACYEZ01gErKiuu6HyYQu1KyU7xyK2vFoNIqVoETGA08ura_u7o2pT-ctN7zxHHy7XfR7HoeeEth5HtKACjN472t_ZvTg-byYzKbJYNADUTGIzqQX1-s39cei8p_m86VLe3TtICTZdKwpx3liEPKpVro5Nd7We7-97R-snV8PxWS5aei25xL15PZ2OxxdVtPHsdOQKCYX62c5Euy6EOI4jjCN7J6PsP3_n_J0Pnj24P1lMV6eXVdXktmPA9eXJ3r0X2JF3IXdFUUNdl9WYhy4S5FZECxOamctFy5h9XeVxcIGUSVMhHxA1lVzVHhTKWMTnUrIpkMs-euf82Hdb7C8RAuI49PWkLjkBhbEfguMYqqqKXTdcXi4n87nz26oALDf9rG7MazOvRY0dERMQGGqIFQpUVdgqM4AUGfs-VSGWlJi9iYUqFhEOXgCGTTvfmRJRMdis-_l8tuladjydNSXr5XJ9--a145PTpg4uRDE4PX62rQH0_ThvmqfHJ7GumDi4ELwLTciDbGWHnp2vq74b2YcqhL7v5otJPyQiHsbczKY5Z2DSHpzjsagaiiIbhRiI2XvOqZAZVyFnIXKhIjTIY4oxJNE4aco4oAIiqmlowtiPjtk7VADvuDCBYSmys7uzurr0PsoW0IyAjqUUIgS01XI1nTVlGJHRQIoiekYqUAojcAh9n8CUidlR6bqjW3eXy_veO0Qy0FExECChwtaYZ4yeyESggPpgoGhg0RE6BAAphkSSjZgkF4fMjpwjLQJSnAFwwACaR-e33U0CAhMwESCSUtg5YlAVxK39BQlNxIhJRUKoFROwQ6Qx5UAeAYipJGFnUlJs6tS3zA49owAhjH360R_7wj_8L_6Z9FmcJ7A8lBiqMQ1k4FAKABL7mqQbkQGZNOUIbJa3wnbJ6pzTos6Hse2nO415VzB5R6lAKmZm7HLpi6gtdnddFcZu7YMRIgFoMd8EKaOqAHJOWZkcVaUbmNkhZjRHXKgAGBKgUk7CNRKCFGWH5DkXASmePLOr6xgbvzyhxaLZ9CnlMooQUN8N__K3f_dv_MxPPnd48pU3v6ubBJIAAZxT0zHl2gUrEj0BeDUhpBEyMTghFznnbCLEuBWcEdp8Pk0lqVpVVVtq9TgkcCgAKY-IDMCSpKlCNhQQAnDoHVLWnEspUAL5bftPxHhrwlAA04BUe_9hGaAoEmQRKOaaSSkjEYgJO9-PyXlTUEespXhyuWhwUIdYeXj03ae_9Bt_8r_9n_7cx16-e_fG_rOLFBm4WqyvBg6KZM5jMeVA2mlEAoUYo_fYrrOKhHqx7s4Dymy2EyaOa3y23LjOP3u4lj797_6Pv_T0Lzz4xW9-67DPNvOH80nY3fm5z__wv3_ncGFGTcM7c-ghteuT4-P318NXvvW4e5aevvu1p6f3c6-gHoo2LI4MAa56_X_-v_7H_-KXv_PadX73O28VID-Occ-vH16VR605P_bJA2pG9g6VVKGUUcj5WFnfK8Duiy_1Fxddmw5v7E13quXajYMFLdOFs8BTR8cK1e0DqADGsqccUl6fXHzmh3d0H0MdLy_PrdzZu37wzttvBx8C-cV0joYlZx_c4w8eZtTL9VpsnNcNVfmq3UwnYRjb_Z0FBf746y9r3_nJzunxzu7Bzq1bt-eLmUtjWrcPH3z7zgs_9OzZyQsvHeWLM3l6eXBweAkP69kkpS5yVcy85MX-3v133r44ORXzR88fOI_z3SZnmS8mZeKeP7p94-6tt7_-J8Q2u3d7c37snIsuhCaen5-4in3g5994TvKIxsv7F9V-tV6vr905cqHKis-9fHD-8P7Zo7Oju4c59fPDPUtwtTwjTaUgKl__yO3L-0-CBwq-aOlXy3o-H8bex1pyMqKSNDoSMe8h7u1DHoZVL6MsDg5n-_uyUz_9zrt53dbzaSpSAVfzBgDSplsPsBnLc59-fdrMTh4d7x0eLW7u-J3Fd__w2yq2mEz6rg_zZuiGcUjVtVtkUM6Hg6NDbcv-7kGazquKbnz-9Se_9y0Tsq7jWUPMzdzWZ5dWsLo2r4mZr43tiJZptsd1VboyPOnVUXfR-ZlZqfuTyw5y6cvujWuiioA--upomjdpWF1VOxOAML-9d_69xyVjM92Z7FRnT9bT_Un0gQ0nTc3ezi9WJScf6Pt_9NU7L72mvSqBofvQBoPkHBtDt-5iDGRSRx5TGnkoKqYogiVnFymwT7kgMhAomIKhqXOsmpiopEy8lZQU9tEI0zCEaZ3GgV2wUsCMnAMpWzUkoSFTHnpHLLlIMYrbEhoSeslJpQADO1YrbhK5Kz_5k1_4wvOv5qyXJxebkERh98ZR-ePvV3WV-uQd-hhKGpB5y9gjQi2lbqKmsnvj4K0_eUsE6mmtuWBRw0KIhmpM2aSAoWdQhD-zfQICO2eIJoBI5EmkOPPmYAvT3EZnRdV5JyU771NOJY3MHokRjJkkFfJsDKqKDkS2DwsOmdTMRIlYtGyFkqpKjkyNafucpLGqRUoVpoBWisSqLrmYCHqPaCFWUjKoSUmhqqxsixauaPGoYdJcv33j4Xfvi7aSCmL9M3_5pw4W8P_4-_-8LWY-HO7uomvK0EXHWPDkfCPjaGhXy5UBoGd2ICmrFnT8zrtvE0GR0m6G3d1Zu7kahhxrcMG3q3Wo4mJnZ725YheX58f3nn_p5Onpfrw5juKdI4GmCWXMIQQFWm-uDnbmTBRi2LQDIsYqoJkLbhwG56hIiZ6bEMHQSo5xm4AQADAp7NhEtz-LFgEz571jKgpFVcDY0aj68OnTW9eve2AizrlUkWSVY6javqSs7NlVYZAtoB2jd0MpTRMfnlxOJ1XWHCLFWdWu-4ocG9BAPPPXbh4p22bdZdH6cFK7kEQwIoI4T4AoClLKYjFLIKnI8rItadvwETYeuz6wXz1d1oEPnzt49sHTLNbsLrqrTbvsnSOovKQRss0OfRoLMrUXSxuLD-yMS0qeED32m2U1q7vlktZ9qKquXbmq8gwppfFq7UN0VexHmU2rUVuceEwkw-gnhFVMfeu2kG9gb6auimCZCcH7XJIPUaS4ENLQ-yqklGJdMZKpypj7IlXVpKFbXa1dcKhK7LQoIDBpakfzPlROMTomRBJJnn1KBYPFUEnWzKOPLlZVHgdwlFMK0TvWwIiG45jq2hfVMQ3ROxFNvTqHWy0XEeZBAnMmJtDGuz6rAg5D5zzPJo2SeqWdndm6bX0M2RKaiJSj6_tDGonIOy8m852p9xHBqhDWbTufzeJudX5xUkapZjEGB0RD17t5zRpySrGpgnOG0HV91dRFS4gx5VTPJiVL5aLmksbEzklRMyMiTR-6mXIpVT3JOTOzIo-SKEbO4oNPw-iJM-B2o7hVBHofUiroMOXMMZiKEBBRrJrUJ_YeoLAH7fvFC3fXlysXvWYQLmMakNmxzymBZiJISXF7LSsySJ5MK4Dtqke9Q9MCTN47SyOoUVAkNjMURKRQBXa-aTwoMgcjDM1Es5AqEeRhqOpJUiA0K0nNCLSuJ5thNJRSsK5n6-UpexdjM6bBOScqZkYAhAiARUoIESEbUckSQxgzFMkqQg6JlB2XMdfzWbtau-iVoF5MsxRi712Y1rN_5y_9zG_96r92xuf9ZtpAwfL4_fvz3Z3l8sK5gMVsGNWpc5z7brG30603RCholXMC4AhUUhVp7AXIBGXsUzVppC7MFJ0n1mxIoo6Q0nh1-sxPmvn-wXp5lXMGUAQex1bEvHMGoqJGpJB8IEkZmQko5ZEdA4EVMzEkBjVD9U2NagCmqsDsPRPgC7eumdrvfPO7WVWJjEiyAeOqGxezya99-Rs_9pmPfub1177yjW_toB8ViygABWIm5UhgQEQNBQZDxrYdmmlTQH3w26pd2crJALKTiG4ohbgQErNz3shhJDf0g0PMkkOIqWRTE4DV0DOCM-8chhARzMiu-n4SKk9YJCNQToPzoZg4gyJWUNmzFUE0JMqpBwAwC97DNp-2nQ4iWLFUxtpX7Ohrv_MVAfvkG2_83b_7V8sA2FQXfRlGamZVKaMVa2rvozYOA9G1G4e_-J_-o9_4N986L62bH-zPb_0Hf_N_eHDN_rNf_D9_96n_uZ_49D_9F796tlxC1832bkzI1a4_Pdns322-vD7-mz_-iWkTnn_5taaaff-9k9_5o99-7x-fP1u9mdYTzQpJJ4uagergwMSBFNMdF3AWKTa1mqSSctndmU3X7nffTiVWzlXipWT0gbpNsqxqyVQie64qZK-qAuhC8IGXZ2Py6drd6578rY8ulu_hk_eXSHF1ZcXBKtqD5e9_Eb9UOSqMHMhCkCKuDoNAim5sp81icvn0Ihys9w5vrDbdx1579ff-my9P6hC9O9w_CqEaB5EsT-4_fOnTH71ab5qKGfRoPn33welBNf_jdx_eOrjtA735p29OxvjyzXvr5Xo5XH3qR3_kwbtvvXP_6Qv7O7uzm3XICKWqwny-sz-bPbr_uJ7Wpe0AWMCaRb05O9lcXu7v7gvopJlcni5v3rmRqvDB196qr-223frq-NHF6ZP24mr3YOed7373uXsvvPDy3RBMhpGEDvd3TaFhP4A--tP3QJ1c9tUk7i4m08XerRdeOrvanLzz4KWPvLB3ff_YPc0im8ur0qV6VtfXdntDcQUDhNoPm4EY16erIQGF-NzeHjV1PZtOD3buf-f7z794c32xTEM_OrcUufX8rZ_-2Z-gBv-bX_79vZ09WFgBaKr6_Omz1z79erU7IcB2PVycndezGfjQ7B2uh3H1wdnYP9VMpDa23bSpr04u-j4b--euT33j8_rq8uQ8p7SG85dee-W9H7zd_-ADGtOkmW1WvWspI1W7s8kuw65qUhUTZJpXZCiimszVNUpG56oGfbM_XrWO0TKGqunXvXOO0aNY_7SzNLLDPreby6THjTCrAAQ_nS6-fv4dP_Ht1dmtW8-t11elyJOT5Udev_Pwj9-twnTnYGd5OXDtmISZcmkdxZSFmGNgUMklEWGs45gUCVUysQdCK1jAQh1Z0VQ0qWMHZsTRaByHHLxHQiJwEMQUkCh4K0LkUkrRRxHNw-AcI_qceucdIkpRFwjJURFGQPgwHQ-EZsYcipS6bqbRf-6zX_r5L_1Q7ez_8H_6xfcunu3NHPvq2rVD70nMuApI5swQ_DgKECCCmhmAZjNgI2iHXM0nqmsGrKsKRosxCgIWSSUDJAQEsJILERI5hIJopWTvg6TRk1dVBNUy-irmTkSFvWNPJQ0-VlaKdwFgy59X56M4tazIDqQAohqw8ypmDERO1ZAcmqBlycXXMZdcUgYF9qyiPsY8DmAkJW13XLad8xcoqRBSSQmZiHkrdFYYY4VlpMZPD24cHOztPn305Oz0yWyvVnSvf_L1N16-8ff-_j8bpfjdmb_MKYvkcTKv1xfr9TJVzq9S6bp18KEbutSPTCySUsqSxMdgouNmrILvNp1jB2SiualD3yZSGPoOjMBkMtnr1m11-7Afuu8-ePDJF190zh_sz2gznl9eVSGS83VwXZ_MTMXQGRmpFiR0zrVdHyPNpiF4hiIAJrmIqSc2g6qK_ZjVrNgWJ7H1VSIQmgIQiWZg571LIv04uFAxo0OqvSOmUU3N2KELDkzPLlfXr--rFhhMi55ebXwd10NCcm2XCTxDlmK5pOB8QwFR1qk_vHl08ug4jcOdOzcfnS6ntb9a95VndjihqGpbqeVst0akLBbVsKTpbv3o6WpR-TCvl2frSVU1R4vVs6vuYg0Is51Jf77BqipdS6Xo1SpM91QNSNsyKBRPBmZg0Cwm_dVVHgcmkpwcs2NnllPKqDacnabFIjZzJGVfYT9Wsx3OYjmPy67Z3Q1Ml6cXDpkccykJixFDScWMEGlbmyAjA5RUtgNdIHTE09lss2k1Z1X1lQNTMDGlJCXGKqfsgydiUwKxGCMyjWOhgPUkbAV4bCoKnFRnzhxfXa3vPHeYNkPaCDUEgEw0pFRU6roquTBT3dRAOLRDM52Mw1AHv7pahejbri8lNXWFFUkO666dNPXVch1DJTr64EyVq6iqB_P5OA5o6Ouw6Qcrspgvzs-XB0d7q4t1VVUM3Ke-rid1jbmk6LwYIGDXjjv7O8vzpYmKgant7O4WyRVXbd9Np1PvwupqbQC5KDs3n09X641n770rKaU0IBECgsNQVypG3jkwLQUAXQhF1QUf1YC4H8fJZOY9Xy3XhASMRQqRExUiJqKixQWGIpJNi4EyOSTPYmJmqOaYhKgf-tlkMozjmHsfgmVhYgp-eX4xO9xbXVw679FUxhyqIFklq3MeiIpoYK8kDhiIRMQMclEjWOzM1EySEFPuEjEa05hajizFUDQG3_YDUu_rKg0joRRJoYpjylkEkJ33qKXkArhVtJrnAKa8jZFUcei7OJmUXgGNCEspoZ6VPCpoaKqx79kFAd4_utYN6yJ2-5UXf-sbX1terLtxVAEiV3K6uljdODo0RgHwIaLKoLL1LYhBM51cXC7rWA-avWPneSyUBCh6LeKjVwXNisxZLVS15QygOWdXOyIyKWzYrq6mi92rsxNyZEAGAFbQHBATm-aCQuQcRwSybbc7AKvKh5oHNOe8iJIoOgazEBw4BuJ-vXn56Lqmcpl7ERuGEYGIgZhMiWNjOv7eV7_6w5_59E_82Kd-9yvf9gXaMSUzNCtiPvo0iEczE2RGwWZSdW0_qZuhJOdDykP0lZZCiONQ3ISJaegH7z0yuMCSlJCaqhpTquogxYphKSWEmEt2wY3DCDGyw-AIBCahKaW0kkIVTCUVVlA0GPIoSMxsoGDGxIyU8xh9LCZFSkqCTGUcVEFC0SzOMwQISD_3Mz8W5rFCzIZuAns7exkMxm69WX3_O49u7B78ym_87pPjJ-16Qz3Wc1peXFTcTTLwcmjh2X_yv_87g44Xy8sY6__87_9RjOHF6RzCFI_03_s7f4uSLVeXJz-4fPzowe999e3Lk-Hk4S83e9Ehtv1V7XhGN6rDCRGaIUU_bgZTtVEohqhg7D_7N_6Dy3e_evb4eydP1ps1TvdnL3z2xaf3T0POi4_928--_I8INfgqjYOwI5HmYNr1IwfCrEhAjnJbyPEK6s-_PJvtVF0aLz5Yd73u3JxyxdP93ftPLmNxn7_5l6Ckdt1hcK6uQEuseGd3_3bTPBtbJL82_OSPfPq3fvVf3dg7SGYfff11YmzqgAAq42w6Gfo1Kjx9-OiNz3_aO7-8PD04uA0Abd_fvrG4Wm1QxrPj9nOvf2J9flHN443nrl91m-nB7sc-9ennXxke_-DN82Xfb_TJ49ViP7kQUidVdFteq_cMpu3p8NN_8xcCd-ya3__t3zy5uLRC166_9s2v_c5kt376-Mk0Ns10Uk-bj7722ns_eH_n8PD6rVemDZ0_Pj09Pr35wnME9uTd969We5_4iU9ffPBk0_aI9bPHq499-nMH-7uXq2V7evrjP_vn48SL-oOjg177Z289pBeeizuLdSoINLt7VOUyCc0rX_ro7TvXsyVTePtP3zm88_xb3_rO7RdeipRPvN_dncZmvj65_As_9UXyJJuyLvnbv_nt4XKYLqbk41Xf63IFCODo0Xcf7OzvXHvu-nyxODk5HlcrNJgtpoDudDg9ONhZXa0FdBQVxP0bu5ePni0fPzh7-HBbRQiNXx8__X5qRTBOYs7V9PDIJn0W25vPrAxcxWHTc4NslrJtLjbzvYOqCmZFUMcN793aoWmdUplOps6TpaxFvQfNhaqQN8kHFmV26KZNN5wg43Q2H7u2ms_jzu5r917PQ-eRv_0HX9u7fXA5jh977dXYeA7uxgvPGQZfiRESAiGwr1WAwBhIAMeUvPMqRRXQNPeDY1IphkaMZRRjK6ZoFqJTFWASSarGjpAAPsQYSREjhwGCseaUCFEko5ljD2CmyRFtEUA-OBFhBmbTYsqGyIBAngRMRdh552mvjn_jp39Y1f6X_-F_8uDZ2VCGkzUy4bNHTxwHJkqlEJoQkPOsaKYqRp4cODVD8mUzEoKi-ro-769emtxhRlQuMiKF-WLWtwMbmRk5KjmXbIiggJoVSAFRRE0FpECIRcRVlfRDHpMPEdBJyURsSVzwRcTFqmzfgrnk7H0sUgiRmRFESyFyhpJzIu-AwEBFVFTR4VbcAlumLzFs3clx2rbrynlDQI9S0nbU49gLFjMpqXXOiSiY7B3t37l7-3vf-Pby8pyQJbujGzd__r_94__p__2XLrsxzBsYSzG4eLap5vHHv_SGY_rO2_e3gOYxJTRL4wi29YwJM0XPl5drBB-CBxU15BCGVQs1tqsNMxfJHipJXRUmVDc-cOrTpu3fuz--8eJLpoZilefGO-coVF5MxyQqxUUvRberDykqKkbgwHmgkgozKxZPtEVcjGPJOYnamEZABGZRkSwIEIwdcimFmQGsH4sUu9x0bs6MhuzQbDGZnPd5Molth2ikihTwYr32wAhGRF3bOefBIKfimbs-IXHXt0yGNs4WbnXW-RgvL1aTWROjR4fEsFr2ALLatM2smR5OlJq-ZESHI1bB5_XgABofrk7XEe3ichPIZgc7665Dxp3bh93JZlgPw-mIjuqjg65vRVbQp5LOq729nI28y11nCIRU11V_uZntHHR40Q4XkHMCDE2j3uVlruo6b_r5YpKTOoZxsybPeUgYakjZE-V244NHEAdIxOTZg1ntQw8DMZVSRItkG7E1BOecjgmRDITYj31HZKrbXRUAYU7iKnYEaWhLBppEz967YCKAaGSxrosULuqdE1VRrZwjRmk7QphOqvXlelb5-aQC0VC5MZnzcRJo6EYQjrWHbRaOyUCYOacUQxCVvd3Z8nIzjH3DTQh-hk3Jua7C_v7e06dPfYypmOZUx2a9XgNRn8Z63jQWSpaS0-HRbtt2LrihH8mRE-76NJlXnPwwpulikpKMabRcJpNqGBJ7vrWYXVyuHQUAq6sK1KTkalKlMdXTieSUJSNzHnPVRFFo3LSUDKKpH51jX8cYXduTsgNv45CIuB_HZj67Ol_WVSylsOemqcchIVPOpY5VGjoDEJXoq75rHREwE4EUyX3eRgmlqPce2Bgob1-bOOdAlb0zA0O0kmOoYzW0bQ-IsaoMVCSLMAOhIQhkzD541eKYraQ8jr13jt31wx0iEslbrLRIIUeajdENJTNoFWIoRUViPTURVS15DNVErM3jQDGkkmKoTURFRQr6sLWdT6ppTqstPxKYYoxDp2CGRICGiGVMFKKLUUpxkdt2Gar5zsH0r_zoR__BL_7XGQQIXKS-7xBQ1ca-nc7m7Wrt2RO4GKOoar9REyBupk0ZEhMWU2LPvpgaua1IXYjJULz3fd8nQAgM2fy0EjUD4BCJgNhtzk8n9dTYhr6wRzCUXKjyYMQMZICIaRhjVSETAAooM8GWiElOrSCRmjhiBERiDt4HV1X-4y_eDMCrVZuVxiETQIihzwWRzpfrPIwTj__it772l7702b_w-U8_Pln-yTvvcx5HIQUlIvaKZMSQVURAxUJwWZKh9X23hf2DmjEC4jAMDGxmaUzbhgYzb29-cz_pUuLgh3EUUxtHYu7bwTssIn0eo-fgPBQhwxGsNtdKIedEiqmFGIdUAMyRqSMpBYm8ZxUhRCnadQMhAdrd29cmBJOmme-6_nL84P47X3304Cqly_PLcbU5v7p69vDpZt3pgGbFfJwG3EqnycAwbJaKKWU0MxKmPAx5HHvR2XznR_7qX61vf-z4zd8t_frps4er5fAP_ld_X62sLi7DdNoIbizPort9uzk4mo_J1B3uHlw_efJUrCAhBnSh2ozilRE5ToMVnD5__fjkN84fn_idnYNXb-9cDDSWdIvT2dmQyvHX_0nWoWC9e33mqYEuD8vWFeHWUjc6NZ1PF7PpD3_qhTKsu9VAjRw_XoeqWhw0r91dXJ5dnZ61crG-O52E283xg2e37uy2V6JZKISMaMUWJV1dFcGMk_joyXL_8uzOvetjFnDu8GDXOf7-995mx4vFdP_g4PjZExJtqnr-3N3bKanZZnPVjX1oJjnZev0s1hPWTs3UeLMaFKBddd_4-pvznWbctJPZHlSBCIMHHct4ld_9wZt3n3vVOT8aSspI4Of17__6P79986jtxzwMHvnps-M__sPfRNXV5dX86LpZPj0_-cKLX1wcTs8vppuh_dYf_JuC9iM_8-MiUjV-4hfH4bHp8K3f-aP9g6PL1ftR9WB_2q4v77_9g-Pz5Xq1efe9Dw4Odhd7-4vF9Pzx8Ww6yyBj2-fRTh48ud7l5164c_v6tZ3ZFFJ_-_Aw1pOL0_Ox61Z9evbwPkq6eHb-PmHKduvOzcfvPbp75_b3f_D2H339nfmkDiFYyhm8r5o4Xezc2Ds7Pj68eW3crC9Pz49u33xx-tLJ0yf7h0dnx8dPzy588MPQMisiUqDp_r7lUs9m4-nZ1IECJMllVWYHt3w9ydl29vZsLyTJrmmqpiZlqiMGn-VUcq4mE07a7B6U0qdUXJhgxdjgeq3N4sDlzNN6OFnVs-ny-KJ2nkKUksSDiFXzXZ41KaV4EG3M5D1IESYXwr2Xn5eiBvb65z-zWa9K1uHqYjxr82jN3k6_GkSUjGIMBpDSSAioAKqasnNOdOvtQAOMTZRUkBAVARFJAU20EGAghwiquhVvIQAxK4hoYefGkhw6JDDd9n-UHIGpqrJ3TAxmqSgDALEMiRyrCIdQpIBlYk5j8rEBR752bd__uU-_dv3Wzv_tH_zS2frSOGuGcUjtOrfdUEBAwHlCU0ASkCxgBKZQO7fNxLqJy0NSJgYMzbSZHxXA289fv7x_5V0euiGvN579OIyMYABIBADOeSmCDgGUkYS95szMLviuG6DyxIRApkpISszsCkkeR0MSESSS7aGfHBGysmTxvpJSELa1YCpFgFkBDTQwFxMCAEBCMigIgEhFCiKaJB8dIBgQmAKhD_XQbTxWCGimaAaAjO76K3dfunvn4QdPTk-PHUNsZtPZwf_g7_yN__wf_NLyfO12Z4zYbbokJfigYG_cexFEv_Gn72TJF5dXJoKeYhUZbdyMpobEi4PD-48e1DGgYnB8tdpMFjNilpJdCKVIqMLYbgCMEERy1Uy6vg-BfeTL1WYayHs_brpQeSZCIyUnshlzrh1JURVFsRAAgIihqaMDAjAFVcBpNV33A3z4bcAwJPIOmRUwOpfHgcmVIuiIvU9jWl6tzAcAE8XzyxUT7SwmZuaAypizqGYZJSVRQlqve0JmYmbnXEWB5rPJctmWZIjgIrtEWmTTpv0bs7QefHTAmjZpseMa0TyUImm-P22asOoyJ-MJ2RKlaJ-GZDBZTNtNpwDTvWnJ2Ubtxn4-CfvT-cnjMweFa55VjbaJmIerpVssurZHK6jWry6sanyMVLT0PVW0Pj3xIV4-fRxnjXNOSwaEcRzJkZLlnBH1_P0PZtefL2Pq-vXR8y-su2cyZhtSDJQVUi51rHj2yme3p0xGImAwBTTcuicIcYuzIXYuaC7eRwBl9i44VWPHJWckYOcQYZtjI0eOWUVdcDllMzREYgJVz46ZGYGZ68ojITNWlSOg6aS6tbcTHCrIZtnHartVZCuChAA4tP2QMiFtZagyGgLGujKQxd58GJKKMtLOwU43DIv5fLPZTCaTLIWdAzUV8d7NJrGqmvVyGUJVVXF1ufIhTmcTMEMkZoqx4sDDMAKRAjESAMSqcuwQbTKdDkNyRORc3w_OeSYyg6apjAwBEK1yXkSnswY9b9ZtDHFIaTqpkJ33jpkJwDknaoSACOyJiABwiw92zFmE2ZFtVQBmAOwZUEsqTFSKVrPFuL6K04mJAiM7b6BmysgIqEWzbFcXZCrMfqst8Ry2sbmuvbx-4_ZyuUI07ZI5lALOMQAwsSkZUC5SVdXYt3XVVDFypC998VPPTi7f-sEHxQi2upOsAIqIoQmgoKJk4L0rIqBKRIwAxFoyIHnvVBSBP-SMEhlCjFGkMHsAQCJVMVMAF-rKtrhM50BLnE5LKr4KqhqqoCDzuhbUN1594w-_9o2uzSLFtFgxxg9d8qqlqmJKI5pV3m1jVT46NqIYc8q8BV6KAQNtodRF2TERlmyAyMEDGKh5diqCZMzkiBgpjQmdR4CUUzWdpZQ843aSBcAIikBEsDUfb5eV45hDCGZbX5ozUBMtBuzZzEJ0xE5JXVUz6U9-_pPvvP_0B4-fJdlGwjAnSQrcuLHPOZWUjB28_cFjw_H1e7c--dLzD07PQUSBiwI7VgBDlCy2tW0Df0icQDCRLeUDEAhRDUQMGYHARFXEO0eMYyqImEvJuRiaFPHkSymAJmrFtKHaTBFJVRUREAbNWsqQRkEZUhLVyjMigVnJOYYYPcfgGs87dTyYTm7uzu5cb2jTVe3y4aOH_9k_-If_9B__03_0D__R7_3Wv_nmH775_Te_8_S9h6dPTtqLFSiwAJhEQI-oSdhgaAdpu4uzZb_uVNQ5Bs9MLk4mu8_fnR3eaIf-4Tvvf_83_9X9999uV6uxG7rVJVjvVMIk7M8XKQ-Vr_dv3K4XM8AwdN1Q9Gy5GgYVpHbZl9Ugo4Gic5FAsVE-cPPP3_NJZy7MbxzNdqt2ubJnaxK5atP97z_klGQUrHxZ53HZjevOAZrPcVZ_-tP3blyr791oXrwZihYp6TwNB4tpMZgsZjduz7Rtzy_S1VX681_6RL-5CAwyxm7V1gdV7lLOlh3lbr2LnIYMWbDozb3p6cMnR4d7eVhN63nl6t_7g99HtaOja5o7ADx-8ig45wLV7OfT-tnJk8V8Pg7txXK5qCdvvf_-R-7dMbGdnV0TddXUucmzJw9a4MA4bdzMxVWv-7vz84tLZptPJ84HR3aZ-2G1JgKOYVyPn_ziD7_00ouf--znH92_b0AiAOTqWK3bdQgNqpjDl--98PTkdF7tfPbPff69P30rVkE1f_GHfvLk8XusoW7i6dOnztNm1c8Xu2Maoo9vf-cdcjxeXd64fqRqq_UaydrN5sYL1x9_8Pi7b31_MpsOfTq4thciv_zii8_fvDGrwsmTZ6fn54cH-w-eHT89Odmsusf3T4ZuvHo6NHM_CeAn1bgekg5PH5-bKgLv7e0sdhevffS167dvTCf1jaO9ceh8pKFry5Aul0vN6d6rry5Pnx3tHnJVOe_6zWbvYCePSUXqSQMeQhUsF3RxzDY7ujW9dkOrwNXU19Nbzz0_nc88uzzmpq4R1Xke-87HQMzOV81kwoHCpOGqCsFZ1oBh9-bCeW5XPQHNjnZzl5pJTT7e-uTzm8tNrKIJxdg087qaNmQk_RhJh9War-0z1Hns23XnqxoRtiVIVD579vjGc7edi6I2DsmHbS8PFJEJTdXEXPBFyhZyMw6DiQEBEvHW0sVMCLnPPnjaMuDUkIgQnfemBqDBu64fFY2JraiZJS2I5ryXkkjVDIyMfSglsQ-gRmbeOy1le9AkRMmZvffeIQKgEVKI4Rd-7i8eLSb_xa_8677rUzIxcIwMuHPt2unJaYgBAURERZAZ0AyAiP3EpS4zUx4zkwMiAEeOPv7avbt7-2dt-_13j9t-gCIqwgym8meoIiFi2xZvS2Zk3G5CVLfkBueDmaChmZgqu6AqHxIUTQWU2ZkaO1_SyEhbjochGciHESEx5z0SsQ8qggBmRI5LLipGyMhUsrgQ2bbsaCSmsj3YgIEaOyYiBCMmkVzVFZAS84vP33vy4NHJ8bOSEwLO9vd-4d_7y7_8z37t8uQKq-ro2v7FWauizlMziSHgX_-5L3GBr_3p94ekq7ZLY0ljDs7nPqkZSC6KN2_fPj175pARqXJ1kmxayCGimggzbUmvTVWTIwSIwU_rij1Op7Vn2plNo_ObvlNDBPIhlDFvhsERI5CimohzPGmaIjKbVruzCQoigX0obN-uUhgAxpKHIkA89CmLAkHOmQmtGAAggqKdr7tRpIg452Z7VdsXdiEBEaFv4qrtk4ghDkMW1b39xcnFqojE4Ildu-4puG7ochEgzOMQQtCxpLHMps31w2ullP2dvWePztr1GKZuUdcX664UjdG52g9DRsN6EqchhBB87RXUM11dtYCE3g05e8_tZnAO9hY7m6t2ujfRXMZunEwr6WS4asPcixgRmhmSd01MmxZEOIQQYhpGkIJMZGgiJSsSGiqZWi4kxkT1fMfUGZgHAfmzMASzqsVYNzU5cuSqKJJMS5eSj57JAZiqiWbJhQy8D5ozmqahYx_YQUlFizoEYgYrpch0Oi1FTZS2qX_2UsTHamtdlZwjezbQogWKJ-dD7PvWhQqJTXU2mStCVbmSqG4IROrKj1YEzHuaxAhoNWHXJ0amuCVcak4p1nG13DR15Zw3sfVqvTUTe_ZlGCZ10_Y9V9FUxyxjEe_cbDFj9qXI0bWDetJcnF96FzJLrOJ6082n0-AdKA5pSEOJkyg5N83UeQbD6aSSVMZhWOwttpJRBEvDiOBMc11P8tg38yaPmYkWuwswFYOkQORMy3QyH7qllFRPJ-3V1Wwx69p26FPdNKbmQ1Sxuq5SKrPpLA0D5MQQxs3Wkg2OaExZQaqdHTQLzVRM-q6fzRcnV09CrFRLNlU0IkQyE5SS0JCIUhmJUEFzO0xmk-BAxIzRDNkRE46SnUfNsKXyZ831dAdMQvSh4jTKNEbnOSgqA4KVIiBiAJKAiB1xkcS-9j6UsbDnotkFr4CSsqsCqjkiBeNQgShI0VyCjzlndeSr2npDNgS1ot77lLKpGoCkFJtKiwTniECzrpYbQXz-3ot_8pWvFYKto5egmCmyq2Kd2nbv8Nr68tIMxFBVzKCuakMyQGJEJY-MYIAMDI4oWyYiAPMO1MxKccQZhAkqX4_DoAxQhS0wDj4UDJKoMaIqoiGSERsio4EpiigyqUqS4oMjRiYvqgoKiBwdFEM0x8zIgtL4uo706u1b_dD_wffeBu_RIHd9ViGmTa_midCQEBAHRQR799nqT9_78hc--dq__VOf37Td733rreNll3vZtOK8SimqpmCIjthMQceM6IqJIbJDUUUzZkpj8d4ZaHSulGJZTaktvfce0YgYBHLO3rtSFMwKlpVceXaMVUKxkhBQEINzIfjV5SrUQVTHPpMjH9lzEB27ZF_9td_63re_t1c7MDo-65ZXS8BA0wq1qOQ9n3fIs9PemHFajEFDljKbT4a0WVw7nFw7Os_2iXv3-nFZz_d0yV42zbXD3HW_9cu_UgcY-_HG9X2DtHj11XFYoWhz4_b6cpMc9Jerpp6XTvuE00UcEvFkjnW1cqW77CvD9Unyu42y1U1T1RQOFlxBydLnXtSlpUSk_li_8vd-Z7LTLGbmcCJAe9fnxfPuG6-e_OG3Kh-dB2VXx9lkEthD1-tnPnILxjGQZS_tYMPyjGf7pdJ3T4fP3rvejxsf637EbiiyKeTc3Y9cf_vN7z59cvXc84d7i0Dq-rY7aOpNhotN2t2ZVQ7QYEhJBjncnQ1El-fnN6_tnS-X-9PF_v7e8eNHf-6zn7lI6539XR9jv9l4hO9977s_9RM_-sF7T-Y7Rxjo_snxnYPnIMm4GaZNE9xkHm3dZ1LapNQ-Od472uNVB47L0AsQu4ggjG5_vn_87CxmYuRSim84TiePHz3SvDl5-ng6m4Rgq4vVZj3Op3MZhV2VhmWRsnN0bTUMf_rm2zEEdHjvlbv3338w3DifV5OHH7z9wstvhHhf8ziZTtv2ypMPVVPF1bBa1fX88nwDPpK5bjXs7Acd5fjR41c_ci_G2XOf_-h3fuO3b73w_ODL-08fP3fj-mJv_-rs_PT4ePn4NLJPfaom072jWUEitq4D6sZZ5d575-kwKqADI6DZvdfulHY9bsZFqJ-8--7NmzfOz87u3Hn-8uIcvTs7fXb87NknP_6ps_OzyWRujmQcurb1wVmXUtf5WAkyLnavHjyaHOx2I1iN1XxPy-iYV8uL6XyapJjk_nKZVPeu7znwxnx2tty_PSkpV_PpZmjTMA5Du7PY3dlZjEMC85iJPXSn66qpStu6xrdPNov57jiOuWt39nfHPhd0JZsjwtyb5dLlIQuYzuom5QEwdG0CslQkZds5OByHbGbeO1QbhoSI2wS5mBCwiTKQKkjKgZySIXMaRkdcVY1IKmKhCiUV752aKMCwaX1dAQo7ApGi4iKnXCqHRCaGlhUQFMVUDciR5SSZR2A0E0IsWThGLMKEW2EQ-QC2jcgXQo7RN5Nq_9q1d94-6VMCV1GV3ZCpZE9-urvwxGDofQApyEE0bQ_cfhrHTYtoKqIlY4xDPzRTHyJ999vf-YlPfOz1F5__1d_-FhNmMDLc5nhzGQk-bC8gAAEogJTE6IkZnCtpzDlN62nOAE66tnOO0YQQwcyIkB0VKSlXk9nY97FuQAQRixQFJPKI6BhznwxNVBgRt7oxUAZWQgMwLex8KWpgosqOzAyNAEQBmF1KgwgwkuRMyt77PBZk_5HXPnp5tT47fjbKCM7V1eTf_e_-t_7ZP_5VopIcm0II1w1P2AkgN5UPDEihW63M3KZtVQBMWbWMY8qjjAaAkouRtMuW5hjqONpgkgxdNZ2ktpvUYUgJY5BcnHN1JAIzE_bMHGe7O30ewFHKpa6q3PZilrOM4xiDZ2ZJwuQKCQWnIOzYbQ8mZsFzSWKaVIRwC0fRIsrsU1FDAgQkErWsggqRo4GNOZPnknJOhZxD5uOr9uSy3WT4-IvXmwzTKp6crybTGQdVVSk2q-rN0LdD70NwkcZcCHB9tfY-pC5X0zCbTYnz_Q-Oyw3vguva7pVXn1st-5OTzZ0Xj3bn07PlpkA5OFpIIVTkjATgkIdNu38wPbnsJtNqtLJp2zAJ0o3TSVSj5bINVVxf9FPvEsvFk6eLveu5z2pJOTvHuNlYd1VS6wMbeBk6YI-OhnUvCE09g6H3gVWhtKOPHljVAKWI9GGyU6lfn13uv3BDT5ImA6ee6-7yMmN2kk00M7Bp1pwLYZLs6-Cjl_UAoJayVl5MAABF2EO3udrZPVi2SzCPjkouuagfRkL2VUQkZJZSRAiImdCUHTMhCijjtv2pjggJUSwwecQKso5AIXoHmzaHQOt2MMK6qoauJxq9IyBwDOho7FNd-ySCbJ7dbFqLGDtMovPp4mp5CSrTWXV1mQgA0KbzyWbVOoYmRGTIaYxVKF0PgGg0n89E1Ac3jMN03gz9UAU_pGE-nY11lqL1fJH6DpEpUIAq27BTLYBoHEcAaJpKRAnZVCa171CLWqyilTKOGYhiFRhQpDhfSUnkHQGi6Xx3J_dD8B6B652qvWh9cCYAKOi5H_vAhIXANFYRJDMzonpHkpJ3LsaqX13FugFkVWXvi6gPLpUMomDUjcNk0qQ8gsF2cGtFyTMCqZqPLrUDMI8px-ANzBQNyAdzhMmAyRmqIkhRMBbJ0WGsw7ptwRCYkAmMNKuI-ui1jGCUh-zrYKoI2-dwICbnCEy8Q0QyMxN1Pm7n_cE3RREJpQhunQWSQ5wOY-EQ0NQBG6IV8U0lw8AWyAkiTBb7Dy5OkAykOCDQXFSQCZQAWUTLWMKk7lZtjDEY5yHnXGLdGJJHLCJGQEi6XZg6byYmFmIYNZkZmPkQRLSMmZ13wRmSFUUmBYvBp8HUspXiogcTSeqcV1H2AVlNDIABldiZlO2ym4nIQNBMjZUUkZiRqWgJk1kMBm33s1_45Olln01UlAhjDP3VJjauqahf9kQQay_F2Ddd26tIEf3Gd9_-0--_-1d__Is_8YWPO8V__q_-iAnGomKmOTsAM3EaehmQAA1BDVi3ZGskUC2ICGqKIMVMFVCJEA0IUMTAzEzZk5mQGXJAsLEMZiqyiU2lVhhsHFOCvDsPzbRZtX0MjAjaKzMQchkVAF967VP37r3OlVm_vvX8ixfn_b27h9NF8FhpgqvV6d_7D__j6vDG_-J_8z-5PEmH1xezplIAxNKn0QjXy03OJYtQiIasRQ_3Zu997_HRR67_1q_-61AFnuDm_Ufxuec_-J2vACQOjZka1os6zupZv1pjrbMqeooQcTOOe_tHxWRWNxhs_5W9-a3D8eESC-R13nRjerZarfPQ9s5Pp_t1vfB3vvBJ_N1v7Dy3d-e5W-1ys9iZnJxeXiq89eXv98dX86oypSHix146urM_m1f-6qKNtZstqnc_eDg4_-XHl5-5cePm_PDR8fLHX7u1oWG3mV7lFWuZBuojeKNa8dnj9cEsNGV86YX5u_cvdjFedp2NuloNJkc3Xn6utBejdlxk3yTvLr7xx29-4hOvPXz3wfLy_COvfuQbX_3abD69XDKz7O4dXJ6vUIbNpi0oV5t1E91VkXs3rmGEvSY-PDv_1Mv7NRBNDy7X73Pk_mqzqKc79YTGFh197PWPD6vzSagm83B-ddZerp-8_w4f3vKx5qjcVMP5Zdu1H__Yj_76_-dXX3j-5hjMGELlM_FkcWAAiCTZAoV5M79z99ZiUpUCO7u7Tx8fb_qzup50qQwwAlE9qbNS1czGtt-5cdB3bd93gWlv7-bpyRMK8fLpaU45je21m0dEcHzy9MGvP_HsH7_z_tHdG3t3XigGFxcX61X7tT98c0QYVbM0i9u3Fi8f1Tsnm_Pzul48ee9B80ItSatA0-m0njQ_9HOfuv_N9y4fnz736l1VmwxTZkPQ4yeP9g6PkkhT1Vnym9_442s3b-3tAptz-4vzU-u7zXTejIOyUS6lmc2viOXiPDZTEsICMqSkFnfDMGQwnS5mIpaWG2Y3mZGgHt5cDOv17t7Oermc39gH1dkkpt6cC-QhTDgNlYLiqAbaCcBVmlyfT_d3NsM6ZfW7TZLO1TGfqQdwjk2EPdaRdxazMiYmSn2e1HFM3bvvvX_33h2HWAgBtZTkg9-KCBkp5WQKxASgdahW7QaJUAsAFhFiqkLIJRdAMXXsPDkwFDNVjVXcTsT7bqjqoCqM7FAkq6qqgfesUsSUnYcsquoYwVHqBgV05Iiw5IQMgFBKJh-JHLs_m3oTicpY8tHB5O2nJ9vOaBoyjIPlYqirk6UPTs2GoSeEkhIySBEX_BaczURmhggi6ohi9A5cLoJo01DVjXeds435wIA8amJHOYlzrACBueQRt-tTddtPwaaqNrTr0DRjO8S6GtoWENkFKcJI5AJQMYUi4qMrKYcQtrlW3vqSnVMtFEhSZh9KSuz9sBkY3XZzAduLMhB5k5LRuayFiRyzZxu6xJPKVxFA2TkREMlEDr2vQrh29-hrv_vVnBObOod_-2__O__0n_zaZrUOTUWM5PHho7dEehWsagoxHu4Eb2XV91lkyKZGQy8xQMmSinpmNVQF8s4MAG2zugq1A7OccyjJOXd-fjHf3UUEZDLTdrXZ3ZlPJ_VsPpUxbS7X1Dg1Q4UYfchSRBXVAByQ827sR0fOALVowlIRzSe1IzYQNUUCBCp5jKGWUvqxzwZGZACjZEklSQHTMZXIThGsWN-nXMRVfLleh2n13pOrk8vNpAlN1Zycb0KgUWQ-nxQ02_KChrQ3bzKX1TC2vQTXVDT2_Rhqx569uWKAiEcHe5f92lwJdeg2w-58Eq-Hdx73T4-vmr3JjOD48cnQ5dnubOr9tIpk5enVxhNfXaW6irlIXmU059lVO3z--MwUXHDAhJlpZ2JXS-bY9yvjAlwZjFoEkHTsQIuPTdZCSDknV0dXBZOS-5XkgttlkGNJCQ189DKWq-Pzo49eL5seHV0dn4emhqEAqhk67xwUnr3yKQBQKSZCjpgBEVXEikoRRCDnmDnljKgKQIzsg4ACAJBVkyjZtmwcU5xMJiolDRKiYx-2ywvHjjybZFVl58yEgera5yw3d6ZDzp5pNqum00nt3XK1UdWmijlLESXSGDwg5D4PaYxVLGMmx2aWyraaXDwxM6sqmCEjEplqVUdTRYI61l3XE7uUUgheisQQh248unGtW2_qGErK1aQiAgQK5LeLSO-9IRSRnYMFENVVjFXlY-i7wUSjD4ZKW75k8ACITD762aRKOXsf8jBEH6sqkue6joyICLGKuJW_embnWJQd1U1UwFiFnBURHbMZjmOOkwYRAQ2JkVmLfhhIAmMXpei0magokKFz1WTSDx2qOe9kzCF6VTEzFxwZAKCoAiA757xzDhTZMQxdUSBi3k6AAJEZ2JCQkhR2nIpUMRAyYPmLP_o5NPyT778_ZstSEE2lqArz1rKNproNx5spEjGxmRISIYMpIiESOGJ227QVmG43q8jERESOHYEqGClaaKYqJmkMMYAqABC57fqUCYjcK5_6-IP7J7nf2PZqm4Q9GyIRKxh57Nd9vdgtw2DmQlOXlAhxTKmezUDF1IgRt0hlJHaEaga4jccgoOiWzhwMMpFTVVDh4BBBDckFNWFPoMDs0EhE-ENDITjHZiBF0MDFCplgK5xSjU1gYDHxjj1TU1XReV_XYQI37lz7K1_8zO5O8-33nz48PWfvHbuUhhDD5aqPjROFsc9EllICBMtbzAAUMSV8_8nycj3ePtj_sY--_M33HxTRIWWGbeUAFRSBtIiibQU2CgqAKWePbB_iTEVByGFOBRGJiRCK6pbznUrOZoBUTBi9mCQRJAADUFA1B-g8p6QhEnk0NUJzjggsjQM7jrXf3d_dO9yd7e428_1HT88evfV10vZo78ZkPunzeP3Fuzv3bh_deOX5l-623VoJlsvVanl1uWyHofR9EqWNWKwn4kI1qeuqYrXZdPb1P_z2xz73-rd-_zvVrEYXN8M6RKIQ59cW8PJd7se4Q2k1evaz3R0q7qodfdWYaN-P65P18uRq8-gsnfUffP3ND9567-Lhk9JtbNSDG7df-tyr7vq1T3z2-Y98_I3ZYl5WV_XEK9Ddm0c39vecMRmV5eYLP_HJa9P4mVePXrp3_SN3Dp67MX_28OlqtQyB2fJ7bz-4WufZfPqJW4f7M79pezeM-7NJE-s26dlZ6yM13skoyMpl8_LzO7Pp9Orq7GLd18386dmzj9ya7y7iz3zqlW---c7p1dlkWsW6GfvhCx991ZO99d13XvvYvX69XtTNiy_d-4M_-KM33ni97fr1Zn1-frW8uPSBssprH33l4ZNHb7zx-iqPUMah67pV3_XDZ7746cvlGXF8__4P6skUox-G4fbde0N3_t133j06OES0i80q-HD_4YMX7tzdvfPiwY3rxw8flGTb-IgBfuIznyvd-Wc__7nA1be--W1XTQRA0RazgzKsh77_cz_xY6vLyy6NqR8en54HklDXO7ODi4unagQE7eXasTMM9bRaXV7dvHPn_ORZzjmncbZ7zRA2q8vguZ7P23X7xmc_d3F2AcC5bAktenjrlubuybtPDBAFJzs7jx4-zFkGabHvlvcfkmQjujhdvfyx5-tZs1qNe9euO2_-YHL2wTki3bx7gz0j0Hq1vH7tZu42Rtj2bfCOkfvNxtWh6_vLs_PpfBHrKlbOFFcXq2bezHYXaRjJAxD267UW3bt9G4i69RC22BHEruuQWBGZaetzCiEQUnu5aibRTav11eAMmWxI3ZiknsehH5nj2dmFqIXIzXxmuXjPZqIO2k0P3o1JTCA6bM_PZpVbrVYHr75y74VXWcackoiqmkh-fP9B8Pzia69ILkMSz95KJqJSTAGkiII5ZiliBglNQUsWCq4UQQDHTlQAIElRMR-D5SJFgUhKBqbttpYQEc07X1ImAxUBgCwFELZ3SRGRXKq6LlmIWXPG7QEfQVQJvYFt51lIgIREpCbEzMHv7c3-xl_4C48fPPmT730_mytjgtQjmJr5-axrWylKjqyULYIPHSGgiEDJqooM5BjQBe-rpqmcA-l__qd-xFH4za9-sxvSmIuoqKoiGCgTmRYmkpQREUxNhUIEQAOQoWcm2IrMtzhrxK3Kl5DBAMG2jh0VJSYwQESRbH_We3bOi5pIMYTgY07ZhSiStnRsJDIwyUKOkIiQt4loINyeAUCFmU2VicAECYHEkUPyn_mRL7z11W9I6ZOkUvi_89_7hd_87d97fP-JnwRTRsdIPpehu-pjCI4sVOFwwn_uU5_4429-7_HFZpNsGAYwkZwFANy2-wFjX268cOvRBw-CZ8nFOXLeOWbPTg2niymiGgABAZFz3Ewbg3Lt6DA6mFdONd25dmhFyVHOYgCgamYIoGaEVMTAzDH5wE3gaQwgtv3mVaUkYeeZnZgVhC7lpKIAYy79ODIzO2JiyxarIKCrtutLEnCpJGLXlaym1XwypNKtu4vlZtI0l6tN3w3T3XlO2Qj6MgJgznq2XCMqmaunzdiXlNOkmlxerNHTZFoj2GSxMAdVVblIUPNib9qNaSxeaNg7mI49LK7t7M7qWYxNTd2QnGMrypGcdyVrBiWkdrVp6mZ5tj7aq8ekXZ8IcLrbjCctpJzGzsUKQcu6D1XMXa9qzkUylZwJSdlM1Qdfus55l1NCNDMlv9XbIztXVbVxQKTYNKnrfRPVhFCtJDT1TE4FVAqYEsL__98mJStiKSMjgUcBQ0JiyrkQuZw-zJ9ptu5qZAJCFs0M1PedD7FqPHnOY_aTSU4jEZoWVXVExKRGsXLjOAbnr_pEDpGxG-TWvu-6TFvmCTIzKgABqgIzkqeI3kQWO7NhGJOWxlVY1IgAsYph0xYfopbinQvODV2_t5hftW3qhnlTCei02tm0g3d-Om2QXBn72bQhshB96tNk3pgqKJReqqbSoohEiDZkEatiZMe95qoJYV51my4NJVYeBRAgRl-KqKIoLnbmm3U7nU9Sn3KBqqmYWEaZLeZt2-0f7K7bde7z0KdJEwyUkfIo1QRDdDkVYrZcmkkEtGLmvO_afotjKznlNCpyYHLebfpViMEQALlIsaI-BtVCrGlUdOTIl5zJAA2ZqR8G5kbMHNJms7lxff_ibOVjkKwqaqJF1TIs6lkuWURFt8ERMGJXuZOz5cFsJ3of6yhF8ighxG5ISKSq0TGqNxAFMEN2bKrOB8kSG29sZUzOORDlGLIWZofBxMxEquCLSCnFRwfC6FnV0Mx7Rg0G2_GzTyXVddBciMNmvb73wp1nZ98SMSMSLejQERUpwGRoIVbjeiRVHzwAaSlWFBjYOSnFR5_GEYmkCDNn-dCAoKaEzqAgE1hRMRcYChsCeTRlUd3SpRAMiUAUEJAAzIgJVKJj-fDhwbEWZi-pIINzThlKLqVoFSOwqUntG2R0td89bKZM_7O_9lPvPjz_4-8--ODkbLUakcadxbRfD7NFM2HtlyMwC8g4iIoCJM-ABdi5gthnFevkOJXV1c__9A-9-uJzX33ze2yAYAJYkrjAxEjGKatnN5YxhmCAAABAUgo4n6QwokhyzGPODddjFjHbMvmIcCgF2ROiSAIz79nMUkqEAABqFtDVPg7d6AIhgxVVAvDEWBlaySqamAgduaq699ILd1566aJb_uo33r6zHzg1n92ZvvGxj3yj_QFVFQBxcCW37PXF2891mrv1msluWVU8F3CD9FAUITSVuzGf7r1y9xN__gfn6_PzByfNwV7f5mvP32hXV6vf-SoVW2rJkqwbxshjK7GpNmduncLt53Znu83O4Y2bz99upnywvzusxmldLc_auoqKfPb04fDeV5fplXSRlPM49Hdeuvbw7Q-u7YST46VTuzF1eFQdf_fN9uzyaO_edFI_ffLMUqgrN9mde-axL5Pdvet703ox789Pnr5_cev560fPX1ufXE6B8jiUNKBQvLc3m_gHD57dOZjNo7v2kZu__ptPS8H1xbi3dwScqV196zvLz744fda5fHmhkxk59-zyIuVh0oTz8yWQCI53b99crfP3vvfd_WuH00l1--ad4_v3pQylH-vZhAwvNquuXe8v5kPJH_vIK-8cnzTN5M3H3zq6Jof7C6rp8NbNBw_eCYi8syePj2_vHT16-P7uzmw2mQ1pHA1q5zcwghqTlKFEz92Qc8oK_OCDd8oAdVVLzrkUUS1lCE3Il_re978TnK9qL327v5jeuXNvtjtdXl70T8z5WIZkqpuh3Vytb80OPQWO5L0bRoHEt19-473v_f6Q-jidpG6zt7f74L2HlY9Fes-RHdYzJ-MI1tx94baKtf3lk_eWHfhutZkf7e3sRkfmg-dQvXTrTif58mKdgdb9anmxen5nGma1o2AKzDyfN2T24N13r928nY4fQ8Xdapjt1kf17SdPn_jgx005Pbt0aNfv3HXel5JK0X61bubTzbo18hjYM7ZtNz-6cWPnqHRLyyoF4mKSxsxgiFhNJypackEO9bwah-y5me7U_dklOqqni4Yptdk7UM1NHRSsCbH8_3j6j2fbtuy8ExtmmmW2Of6c6-993qYFEkgACRqAKBSLDLAoUSKlUKMaUrf-AkWorQg1paZ6akiKkKIiVBQpsgAWWXAJIJEvX-bz9vp7_LZrrTnnGEONdcHbOJ17TsQxe685xze-7_el1FSupL5tGylDU0XJCYnQBCgQe1ENIdg2xzqkHoZNIqZqp1m-uFpdLX7027-mfT-kYmZowo6HXADQMUlSzYXrQAgpF5NiamaQ-wGQVQoRESIAIFiMvqTMAM77oeucYzFjJjMwMMnqHTlHkgXUDIF4LHEHx46YFKGkgR0zjgTColp8jJqFyIgjKZiaqpliQWHnZMzJkapJ7dFzkNwZAgABgxl26w4ZA7iSMpoFHwQkl1JVLUiWgsBISMWUGFzwm83a2-TF5dAlmTRxt_HnV1Y3VTdAUSFw0qWAbDC6IoARtSg5l9PgqxpEwUeDgmBFChGqWlXVqd-WYYhVYwa5ZE3JxwhmCpZLcqFF45yTc07VhlRibNW0pEFcIXaqSs6DKjOpGpEjj1qEHBsAe0ckgKAGIAWJTWQsIcilcCAkpyCz3emThw-3q7UxAPh_8a_-6dnZoy8_-jZOa1QWsVIGF0SdKmouuaqrfjP83h_-l6UrpxfXm82QckJTZ1AIFcySmhkTxEirxaZuYk7CYAQ0ImGGvp_u7JqpqDWTXcmd88FIYx3qyudhe7y303im0IoUKS_TksOQiDCnXEVfVAwhBLftMiLmfmin-0xOrWyHvomemGLFIpKLDCWNQrWpAoBjquuGCJq2hawcMGfZDoOohipsBpGCarTZdKH2m5T6bohER3v18W57OJ88vFycLdcCZbVJNQdDmk6qTT8MOSeRUMWDw_nTF4WIQuWGbji_uATE8uz89mu3PMJmM7BEwcxoSr2pucg3X91pplG3wg43KftgD5--mEx3bAMh-mYSr1-sfIySbHJYpePZ82drdDBtq82ybyaz5tZB2azyZbGud1VMfmvIvmnykNJ2Q4gmFtqQRdVQUzYFyZm9k5QRAY0VjYPXTSfSTzx1SZGwmk-G9YrIQY1lK46p3_Y8f-vXS8oIiGQIZkWlFESzohwYtZioaOE44jhDiJEYoQgRIxoZSi5Apmo-eCkZiMbmC-c8s4XoJUmMEdFidMRkok0VCWG1Xe_OJwZ2NK1LEUQGtDq6rk_Ezsy8p1gHT7zdbINzVVMRsoHVTVADB1hEVTSGUFT2d2el5O22r-tKTSZtk0sZUoqVL6LNpB2F7pQLB9zZm4YYypAJ0TmO3ksuzCwqdVuF6Nw4bL7MaPq6ikhkjIEDqoYQY4zeO0JqYqjrMC4ld3cmue-DD1JKbKt21iJicNiE2lRCXQkIA8XoY3TM5EN0wU3mDSEojIYQvnEw33ZbKRbqGF00GLu3chWimhZVDsTI0ceUhiEXH5zzcb1cAQKYIXExY0YCYMdmwOzMkDEAqImYSMry-luvPfzmiSGoGjMAIjM659CcWaHoDbBqqn7bs3PVNNze23317q0_-9lH600nKWvOjtkx5ZTJkajE6Ee-PBKZoZp6HwQUiYCdIwBDdE4Jnfeqxt6r2VilRQAvO5-dzzmZFmImcgiKziEzmmoBQ_OOvI9hUv_23__NX37wpUAqZoroHTExOsqq4Kid7A6bZSlDM9nJKRFzFZyqGlgMQUrm6FSVmXHsAgMNdaQxNu1CMXXOmQh5ElFVrdpJGhIBmsq43HDOg2Q0GznNI9qIEVANxrNSbLR1qgh5jqFWUIcMaMTgQ_BVcJ5Ojvd--N03f-_VV63y__FvPn10tehEl9ernNPQpXrSnJ9e-SooYJ-yc0iAKpKzmKkzyKUAIaDbbgYVzUrZ0m__8P2_-asPnfOpGBCpGSJm0ZfrZ0NGUgFTEC2GNl7yiZCB_jN8ySGnUkoWZC5SVA0BSymOvBmAKRFJsXH54wMjYE4p5ey8G9OE5IgZVZQQ0MAxj_1xaDCWASlYW9c3To5ne_OrzfUvPvoaFR-8c-9qtf7LDz75qw8_X11e_cmf_Oznf_s3_-YvPvjjP_3wv_uPP_vZt4-__vLFh18--eTJ6eJsW642i_VVFfnkeD67c-v59fXibOUIVk-fXj89r5uaWUNb3_zuK7v3b954563XfvCdt3_rB9_5yfff_9F3vvej99_64XsHt29OZrMqThar4fLi-snjp8R0fv1Ju3Pz-bNHy_UWaD94R2CTg3mxcHA0Xy23P3j_ldJlNDhdr_vBvn306M69WxuuwFdV3T599GhvNo11NXT9R58_uXNv77X7tx598-31df_6u7dn-w2ibVLvAz18fOYYc8kx1mWTN32qo6tnk223fuXujccPz_qh69er5y-Wv_fj722HdTWdLFZXwURNmsjnz17Md3YCwdnV-d58igq786N_-9__B8b0vV__wXp9XQb55suvxLQMee_g4Nuvvqmm9RePHr1z754h_Ob3f_DVN1-_8uY7X3z0cazbWE2kZITps-ePb96_te3Wjz_68v6bD0Tyo6fPKLir88vjW_Ori-tQ0ePPHzIBMRbLyvz2269dvXgx9P1m1QPa_be-X3TYrBbMrgpuvbpuJtNcJGBYrjvv-Hvvvn_Rbb787MtXHrz69k_e--ivP9xsVtP5ZGf_YPdw5_LF1bu_8f1f_vTnoa3uvfValtXZixeSy3R39_TLRz_8h3_vyRffsnO-2l2vr0KMHHn_8KSdz72zF9fn2QU7mU3uvyqbq_2TQy0lKRzdu71dLm_dOn746VcZ8fJynbMsLq_r_X0P2FS-26xd9J6hbSeTtn76_OF893hxvUIXNGUfuWpalKJZ-27LPpyfXhzdut227fXpZVVVKtk5MLXr56fIFOZ7YXdPu1VkryrqcLvd1u0kazKFkstsb65garK-XgJarAIUc8yAsHp-5mIEk7quu23f9z0M2ZdSt42oDauBvPOVJyMuKqmgESMPy2tGk6Fvd_dv3rmj67UYVpHN7Pm3z-6-emvSNCmJIpRccuqRWUZIgAKqosLoL0ciIzJTMyNEQEUELYWIpYiKqCkRahEtxVIBRlNjJClKhASACCXnEaKTS2Fi5xyoEbPkQoBiagaIDKoIZKLomRCtGPtgKgZEDoGZnRNTIJrszlzFf_iT33p8cfbpw0fLdWdgqDoy9Zv5XHJJQ0ZAFUVAVSH2ueRciosVEiACOa_FkMaddwg1_-QHbx_vHX322adni4WY3ww556ylOETSQoACSoxowER5GICQnUcDAJCSVVVF2QVTI2QwQ4SiAog2UkxwzDRDyQImztclZyQUKYCILwNsAKLEDAjMTvIQQiWiLzcjZo4dIokWRCYCQhr_FjiyHNiJJO-8cwzm3v_h-88eflNy1j7_6Cc_2blR_bv_93_AyiuQ834YCqqKlW6zrapKVCv2uR_-2T_5XZfpZ7_87MWi22z6fr1Ry0BgyiUnKwoKhqrkkURyMTVGbmeztF6HKhAiE0lRJXExEhgTTNqmju54b-dg0Yz3AQABAABJREFUPvFs924eoZj33PU9Oy5iPnD0DEBg0HUDR4-g3vH-zrStvImq5aqKIxuVGNTAs8uiRYqYNU1dRPpcVFQVhiE5dsGzFAFHWUWcW3UdBd9tOyFZrLab7QDBE9LVcv3mrb3rLi2W266UMdadBYjBOUbkkvO26wyNvDO27XYbqpi7IfdpfrC72awcYWhirGq1_OLZeQHZOZjuHu36EHMeZrOmiGIgRC1ITVMzO_Z-temaWTWbtNtlvzOfZtC6qbLperGZ7UUpMHQqAKGNebmyIVfzSnoRkTEqg4hS0ritp8iaMxGaqeXCTARkRZgAkTQlYpS-60qOs8OSBudIuoENq71JWfVp26EZT179PiCpKUUEUwAT0ZfdXkisAdlEzFe15BLqdlhtEICcUzNQG5U_HwIhl6KhbWnMwCAQsag0TVOKBO8AEAAchaauYnQGsDPb1Vw8YpLMBM5xZGJiMTFQAiCiSdt0QwrOjzuHIoqABgACIuKY67oKnpsYhqFs-24-awmRmaomguh8ukugPlQ55aYK7NFH9j50m-7OrZPF1XJn3moBIHPBVc4BESPOmomYhMCi4IPznqdt02235IJKHlZrMzNQVGnqGlTQoG5jrLyVsjuflZR39maIhAJENKsjSPbRR-eCd_OdSemHyaQBgOCiSDnZ29tuhqatRRWBhjw2q4OLgQP3QzJRZkeESKimplxKbqc7fdfjWAmCuF2tXXBoRkR5KM6PHeMkKoRGRFmEiXNJ0XHO-uC1-4--fuSiGwPDCEQIbFRRyKDoUdQMkD21zURtuHO8_94br_35z35VEGUoZpq6gUcFGbHPyoyAYICKGKtQihKTFCXnABXEkNAIFYGYRYWYDXA8gMiFIsXFSMSlFPYOFGJbI2LRQkjsvRZBdtF7BUHvv__dd79-9O16uSkpmxVUYOfIjaUk6FRMVVJqd_eGlNiziCHimHVyjkS1mLkReckMjtCAcET3IDE7csgMpszeTMDABVIwM4vOq5mqjp-pBsRITGaGREgGxKbgw8jeIWRi50wLOycq5NGHoKjtwf7BtPqX_9Xv_MabD754tvh__o8_X2yHi6tN1w2boQPCnNK4hb-82GDwMbjN9ZYcqIGCElgT_DYlVSqSXfAeqIA8e_ri9VfvvP_2_V99-lWIsSCYjMRmLKkYgGRFNCIAFDMYUmbnCFCKECExl2IlFze-x-3vei5NVQQZRQSE2DEgiCqTZ4DxpzRQUTMz74MYjIZOycoOwZEJGIABOO_EEMDIk4oAAQDO5rvNbLZdb3_5N7_8_o9_MI_0zjt333z97m_-xjvvffeVv_-jd373h_f-6W--_htv3_7euzff_87x99_Zu3N___YrB1XT7u3uXyxWy9XwZLk8_eKrGJw68u30-O6tyd7-zVt3b9w4yeYhbQ4ObrR1PWzTeluePn1xeX5Jrlmu1k9fPL-4OvOa29je_-FbuvKxqa2qry4VKfjp5EXpJ74OHiaNO9nduX1j5-Hnj1wMj682G8llHpp62rTt7nxCJTu2qoqI8Pz50_ffu_ujNx_89C9-YcB3H9wMwadu8EiO_NVi_eJ6NW1C1-c7rxyUTRecTqK_Xmx_960HXz-5TLIdpU0menJx9dr3H8hy_fbNoydnF6--dnteudXVtYBcLZaL1fq9dx5o0f1p8xc__QAo_-DHP94sr0Tgo198TAgEvtqdSR623fb999-b1PV6s_Ea__W_-59eeXD388--OT7cO3_xou_7Ju589OHPT06OAvHV8_O2rtdXCyC7de_BX__Zn00mVRVnWvTF42eeMQ2JHCHBO---2a3W-3u7KafDGzc_-ODDi9V1yUPb1sN2DZKb2SQN0rTx-YvnabNddd3X3z4kk8OD_T_513-8ulo_eP2eA9psNwiskAOHbrvWkkspy4uLg-PDPhXR3HcdeN6s1vuvPHj68EvHXkvJZsc3bxzfOGLCNGQ0ySu9-OLL4XpdpNcsvqo3204FXnnnVQXeDmsQ0tzNdxtijJU_vnksuY9VdX15fbK_55u6FNkOfdPOh2EgyFrw4Oig26aDk72h9GUQF8NqsT7cO9g5qp8-ehZiBVKcmaH0641sNn5iaN7HQETT6cTASslNWyMyu1jXzVASM072ZxffPJ_MdkQlpVw1dbU_AbXtZmh25jkVYtost1rARU-1BzA1c96BFu9CzsNyuCIXPLvu6kpLompy7913zr7-WDVUlbs-v4YixzePJRs5R4iIMgyZ0REQ2JgLKt45ATAwICgqmsVEAUikqEqRIkUdESGqiAAAmokxYe6TqwIimingGMh0w5CY2cDIe1XVLGCmYuycmQKaqSGSlDRKRiICRACIiKqCjgHMhciOkNkHTx5V8x_-vd-Bgh8_fN7buF1ADp5dUIUsWZJwcI5QwcBx36cYPSGaFANCAxoVFMIhpdmkAQfzxt5__U01e3x53g0CMWyuN0CQ04Bi7N1YXEhI43ikImDgfJCSgEklV01TijC7lzC6cc4xJTMmllKImF0wKyJGRDDGKcHADMCQWHIGMSRGYlNRKciEyEAsJY-sNkMcyYoixczIO4SRloTjJEAERfHd3_r1X_7V3x4fHQ6aPFX_-H_2-__3_-t_R0QZQQ3ZOSlZrCAgMHJVWS6hjin1_-pf_GPt6T_9_MPz6z5rNiuSpeuLgMB4UIISoRqrFsl55BnGqi2SxYzIV3WlasgEarGuct8FxuOTnZODnd1JSwL7-zPLJiYcnIiVIo55pGP0OYUQTGU-m6DK7nzCL11hBQHAsKiIaEoChGImZqLaunh6vSIA8l4BVM0zbjcdERuqmq62fSra57LadIokiIYsRAbiK_fl08XNk92ny9V0GrpcDDlJYe8ZeZCy7gZwxN6vF2tfNX3fz_ZmuRQ1SyKzvXk3DLFpuaLFYtsN-eBo1lTVfLfthz5r2WzykFI_DPPZ3NSa6NGTi-gMc5Iu5xDjZrGmguvFOgaezJpvvzxtZ1MdSqgiqmCm7mJBRMhuhE5ZLuQJTCWnsQsMEZFAVRyzpux8YOfGCi8rgojk0IB8Oy85xdjs3bu3efFC-j5vMjBMJjXX978ruRigmXLwqubYE4KJGqjmHsnAeReiATKjSdFiwKCigEaeCIGcA-JQB0QyEcfO-WBsVVWHynvvmcmNLi2iuopE2EyaknPwzEzIFL3TLG1bMQIiBnZE6IlK0aYJTE5UgqdYVaNtwzOJQRWrotpWVddnHzk679nF4KRA9GxIm-0WEEcdGokJDBGjr5qqzn0_m7cEOGmjqdV1vVpviYwd9UM_nc-IMKVCjMH71A8-hrqJIFqxy0UMMcRQ16Gt6yIlxtBt-0k7AVUXXFuH0dYyn8_RZG9nBxw4doBUxcozIVjbNo5wPms3my0xAxOatJN2vVhNd6apT0QjBTkOXY9GuSQfAhPZWLyiqWqaodtCwXoyy31PCFYEmIHITBGRiEEMGRSMvR_DW6ML6-btG08fPqEQJIkRpiG74NQkkxkDOidg5NCx845mO5O03f72D7_3wa8-74YyJClFTA1BEdRA2RGYhiqKATMZGDs_Zms8MwGOkH0wrJuGiBQhhEDEZsLOiQIHR8g-RDMw1JcPHcLgg4yWdMeOyaQwhx_89q-dHOx_-fmT3Zs3VosVqTGO4AU2QCuFA3oO624TmxYAx3J1VUFEFWjn06EbDO1lrosIwIjIE6lIFvXsihQiAlUkLKkgoUNfSlZTYhqbVlxwWgoQjB0Cqipo8BLmYG4E7OHLJZKJjT5QFwKC1M0cK3j9zq0fv_GgsP7xL7_--smT1WbrmDfdNvV56DoD6FZ9CKFPnZRiBp6wDAOwgaqJIDEAFC19L8yIAfs-1XX16aeP3vvOOwd1_flXDwGwpExEKmpghIAkAJaykHMqxo5MzMa-ejEkBHipYI1a2ihNjQqaqgqYc54AixQ1LZK9d32ffPBqomKIICPeGkCyApgajsPtS6yeCgCRjTxxRAUTQyZ2XNcN1fbhT__6lbe_t7i-UuMktNrmIeP5Ykiluuhdoeb5hV2dSdrqejE4ZABpw-zjX3x68sbrX_3yM-_o-N6tW2--8_Wnnw6b9M2Tp9XhoVGLWRy7nrGKLSLlAkixCq703cXps2lVT5sZu0i9QB7MpCgqKVfop7TTTip2s0mMFd27eRCZ9meT08urg9sHp1cr6fLN-3emTdsSps0atMzqupPkY_XKK_d__uHn5qq9g722jdOq8QZ1FSDLs_OrwGym676bVXUAzHlYXG_efec-ETx7cT6fV3cOdn3gbrtdrMuzizSbza-vVtGF54-fL1frg4Nd56pnT88Xy9Uf_Be_ffHsYtLETZ--efr4ve--t75aEvInH32BBOwoWzk-PsIY7t64uV5cDP1w99bd__Snf_7222-cPn96cnLUZ3ny1SPW_tmz53WD56cXV8_O3v7uu_fefPWv_uaDOtrpk7PpvDk5vusbvzi98ME579q6SX1RVQA6uX3zr3_20fHNW19_80SGtfeeTLo-hQaJ_GbbSRnOTy9v3zqpmrr20bO_eH7hHPpY9Tmvu2G52VxdLGLtnz17fu_u7Z2D3WGb2qZ5-91fJ9Qn3z45ODncrrftZHbx7El3ufbkYlV1uRzdOD463Ksr321WO7vzh198aVLYc2zqdrJzfPP2er3wddiZz85Prye7h6cPXxzu7EnpJ_U0pf7mrduSMzHs7B18_fDbyaza3Ttcb7bdZjNvdxfLhYitl-u7r7y6vFp5cv0wEGrutlpwPt3xjX_-9AUxoaFkzeuVk1IG8dPd7bbfme8AmWfflTLdmZAygJEDHys1cVypFUTm4GaH-9eLdTup87YPBGXIPgQD0D5pXpKLIoRA3TAQMXsfmkAQTFhViUJeXHhW5Xh0cmubc9W0qe-en50dnxzWkyrnEoKXIUtKxcar5rjhB0AFJiAwE8dUijCPz8zi3AhJEdXiCFWFgxMVJC5DD4Dkx6gumGkVK1FhxyUXYtKRjQxmUphdljzWjIgZgI1cRzF15A0RkdCxd1RKQSIOgZnGpyghUXC3j3Z_64ff-_Lrh189uejyIAq56wGUiExBRRRBiyGCIalBHSowBVNyHkHJORUVVUPyzAxIAv_yX_1RWfcc_Iuz8_OrJfogJZUiqEoICKYKWQoxqijgqIegqqFnU1NTFYxNXfrEzKJKRMReSjEzJCNiUyVkFUFUlcJEKmIA3ntVBfaoMpqInA9mZpKJWA2Jx8J4MAMOARGJyExLlrptJSUXQyl5ZEm309nNOze__Pgzy8NsPj-5deuP_uU_--P_z79ZLzebLNODWd8XQi45kRkSIpMBE2FglzfLf_ZHv7-63Pzlzz9dDsUAunWXcgECFCw5O3amWjTlPtdNI1JMwbErObe7O-vrhQth6LdV02gpVd2aians7-0Yyuv3bt2-ddhEbqIXMRFDAxEhQmZ0BEx-u-2r6AHMM-40dWSS8fMQvPdjT46aMmJRNTMVAMRNn7YpV8Gj892QVATRqlj3Q9dv07aUs7NFAVr1AxCZpz5LXySnUkxLMTHc9MkFj4BJJeWSs-zutCVpnwsg1pOaEZVoux28d6koUgwTX3IZSgJmHwKggXPHJztHh9MYXUFZbjrv3TDkTTc0bQ3K223f94OInT67LFrYBV_5bkj9tktDmsza04urelKFJmzWXdXU28027jSmCArDehtmk9JvrRQAtbFwIwsTASogMTlC0H5AVefd-JI0LQCAgKJAiPMHty2rGmDp--tlycPe_duQu26z5cmr3zNCRFMzTeKck5wRMfVbUChSzJRcACAk1CKOPXsCECyCBipAnpGQvQNAdkyI3nnHOG1nBgpqzr1E_qjkWEUyC7ECANUyaWoyy2KVr5zHknIp4h0zwDD0dVOnoQTnxAQBiNDUfBXNFADRkalGH9ixilQhSFEzq5uqih4AovdmGquASOy46_qqikgomqezlhEJZW_STJpYEPs-scOqCt6HEGNJfR29mu3sTogoBF_FoKoOCKzEqqrqGIJHACZj5x1zjO74YEdRoovr5bqtq9l81g_d7nwqUjSX2XzqmAOT5NTWVR2jZm0mlY8eAOsqNJPKSmEmyXk6ndRtrWrDmCARDVUchiGESkENyRS8d6qiiKJ5HNARwEaKMYGYSireuyJlbIgaGwOci13fHxzun794oWoABlrYI6gZWTFx7MirFuUQoAAY7e7P-vXm937nR19_-_hqvc1JlUSLmgkBjXOCqHrnzICZyLGCOu-AKOVc1a2NCXLPUsT5qGaM7B2PGyeKIThXsiAAIQGCiY76BgG54KWUEDwSOWYRu3Xj9oNbB8_Prp89esbMOgxgIIzIzA7NgDIwYc4jJZqD90Bginuzg-1221ZRwbSIyQitBSI2gNbXyQQQxyi9mbF3TARIUmRSt6MxlZBHzcoREvOYCYsxAAAARBcNxHtvZsE750PR4mNEAu89MoVpZOdCFdXy__5_80_-6qPTv_jlN48vL58_X1oRk2JJTdVAtUAeimsYMuSUQI3QUNWKOiYtwKhiCIS5H8AgC5WkTdMy44vnL37_7_8aEp5dL4oIeZ-GbOP3SmgjotRs7IgAINFRvYOR__2yNs5AVYsVNSAAMzUDITNVTygIhJy1GFhgNwzFzNizCqgZgzcpzCQKo8_YEyuZJzQY53G2IkTomEyNAEyUGabTHXTh2y8-uffam-vrS2a_3m76nLf9oCY-eCJdr4ZJqIvYs7MVFFqu-9a7L785P7q19-Ff_2Jvf1ep9pMqOschPnjj9eD56HDmMOwfHP3szz7YOZru7VfObJ3zZhAu6Knd39shh-tF38ZQ-pK77XZQ7B2iMfkqRI9Whu7e7aNb-zuRsHRl23WrZN98_fjujcObdw-3L05rYoZysLu3Wq0-_ebbt9949ezi2odqOmkNtPEepTs4mEOBben--4efvzk76LOI2o3jXUeci873mu31-uGT051Zy2IewdWVDzUQodnl5dW9d-7eO7n59dePptOaQxXqatvn1bp78-3bV0_O6qq-de_OT3_-85sHR2bmUF88v-jWW--9Gjx47bXT8xez-a7HeHp--Vs__r2ff_CzabNzeb7Y2PrF-fnTR484QrfddOtkko9vHF0vrr765efL8xeLqyvW4n346MNfXjx5sd4sUio5py4VF8O2S-vSP3r48HIYKPrQxDtvvLZ3dDyZz_f2Du_dfWXy4Ph4eqgycAy-Dk-vL55enG1tGErivXmxgUKY7kzv3Lnx2q-_d_fGwdHtGzs7s_nu7nxvHqrq6uJcit65c_fmrVvPvnmkKki4ePHtZH5gOQ05v_7emyrl1snN0qery8Vq06HxMBRyjqjlYJvFipGmO_O0Tdvlul_3ebud7ew0bYzO-m5z6-a9zXphWk4ODhcXCyRs59Ou78R0td5MdmY555zK3t4kxFpEhu26CG-Wy8O92eHOQajC2eW5CzUUHdZLVEWkMGmj567r27pGR-CgX6Wd-WSvrrMgsy9DEiub61Ue0nQ-AyD2rEOWpKHyPsQ85KoNHgBEFMhXkYIveSsl-apar9Z7J8fQQFoPGDmtlpr7qm1O7t4xNRd4u-rXp1cP3r4rAygqOWbQ7XYrYLkUA0DiUhSQsgiYkQEqlCJMMGbARl4Ajye4iqmamohYLiM6QkWIEca9XynsXD8MPvg8DMRO1UpOY0SYnbNSRpAxII29NwZICEQkquw8EatqKZmYkRwxKRAQTfZ3WPJ__Qd_2LL_659_YpFXF1fd9RoQGD063K4GFxgBCEENEAwRzCRnQSQmZ6aEAAZk5Jkt5f3Dg__1v_gvHj45ne3MD9vq408_k6Ek0W7TI9gwDERE3ksqVgQItBgQqBo6D6ZIyI41FUAiIkDUUkxFSnbO4TgVgamCdwFMDVBFvA9aCjkaewNMjYhAZexhGwVQVSN2o7tj5OkRs6oxMxKCQmhrSQnAODoV8Rzm-4fffvXNzv5OHrqU-6FLb7x6_4__7Z9uU0bkXAp7J1okZVQzESJnjr13TdM4V_75P_2D1eX2L3_xyboXUXVIQz8wwXJ72Tbz0bwBIMMmx2nTd1sXvCdnCrFpmahPW3bezOZ7-ykNRra7M5OS33vl3iu3b8zr6JB9YDPtU1K1MuQYnGgGNB9CKYJg81m7vzcLiN77XLKaOiZEJkRVGA3Gi02nYmpWRIpa9I6ZhyQpl6wybAd2BADs_Xo7-Biuu-1kPt1uh21JRUULIEJVBee4ndfkwRNt-q6dVGqYQRVwvUl9yo6gGHTbhMgC0neDZa2mfHCyE2fN1fV2ulvv3dmvmrC720bvT6K7zumq74euzGetESxXm_Wqd5Xfnber643nECfhetEVUQZomgpMX5xfI0L0YXG1nTR1aGO36aa7s5x7ScVVQYftdG9e-t6kAIB33kRNhZiIHdpLhgsagEgZ8ksASUrOjZgBLylX8zmzX10u69o30aeSN1dX7XwKkri69x2qHIiaipmMN8giJTTRCMcaF0Su6rmUbKLsghZh9iZoBqGpyIiApMjefKdPAyCLmo9RVIBwPtkRkzwk55wCm0IzaeqqGYYBAYjAeRejY4dkhsxQ1DsO0c3mk_GyNeShqaPzTIjjnoiAStG2jsxECNHTOEw755gpBBYzNVEpdahFivfu73omjD0fH-5tNtvANKS0O50gkxiKaROiqTISgDlC77yIOM85y_5OO2x7RlKTcczKRZhxNmlANVYxePbekXOTKogIGRIBIddNNanCpK7ZkXd0dLJXUq6Cb9t4687-vG2b1pehpH5w5Mz08HB3eXmdh0KOjm4eLa9XoQomWrKYGTnsh4G9BxXnQ-qTobF3zKS5IBiQB0YD9Z7HJaxi9rHSYs75nHswQOdiFZtZs7peqap3rMVQIeXiKu_YIYIHEsG6bQAhRvZELuCPf_je-ur64fPr9VByKSDqq5iGBArsxhIZGLV2JsfeiYxQZyRG9D5LFlNDAgJTjTGOg7wiFBECIFNC5BCLiPfOO8pDJueQCQHYOykCRCH6t1977WqxeO-99z_99BO2nIaSRMzQuVBKZrQYgmPebjtiIsPZzs7QpyIl9duxcaxqq5wKmlbeA6GoEIGaMjsRQTRGYuLgQ8kF0ABURFx0qoYqlQ8AYEiOiInK35lnpBQEDN6Nze1EDghdDOjZzKKLakqeJ5PJAOUf_70fnxxM_2__-s-eXy_WkleXS1AtfTHTKrrtuifEXFSGPFry8pDHUjwiRsNA1Pc9hloBguOcByBkoqKpSNmsVm3d_uZ33vrw40-jIyM2MRAzEDQwVXI04r-IHeKY6CJmNsIiMkIv2LGZjm8cVCDCiqOqSVY1ATQEArCiykSR_ZAE0MSUmc0kBG_00llUiggAIgbPIipDMjJCFNMRJJWzMDEggMp8f2cQvTo7O77zyvL6oqobAofExO5q2TmgaTUBNmZfTesq2vOza1L9__7Vn373vd_41a9-CVKuz5bb7frGg9tDkYOTvSF3s_2p9oPjsr87_fiDD9vJvL9eXS-WPgZQ9sRxEi-vOjZ3dDLrVquCOuQerGBOqLKzs0MGnsrJwbx1KFLWp8vtkB49PTuYt8G5eQjDsqtiuHf7ztPT06fnl3fu3NyZTXb3532Xzq8v9venB_PWszfEoUuLq-0hVp78uh9U8WB3LwRPjlrnGN1yse76DoE6w21fprNmOptePj_3gdbbQnXjIT97_oSV4qRB48XVtfd-p65dUx8f3_rX__bfD8Pm_t3bDvXZ8_OLy5VI12_lO7_17od__cn-4d7h8dGmW8_m9S8--OTs6upoZ3p1dhFcnHD19VfP9vcPZ_O9m3duV1XEgi6GyWyvnU33Dk_Yt4dH-4d37rz-1mv3vvP-rbdevfvm6zce3NndnxEzcWim7ZA11u12tR222_PT54vF6uGTb55-9OVXX391fnq5PLt48fDJ8tlFWW_LcrO-uN6cXW0Wq9XV6urs8vr88vTzh1998dXpw9NH33z77NHDpw8fPX9--uz50yIypP7Oq6_Vk-ri9Hm_WTXT3ZQzeUrbdOfe7YOjk6FbgaGoXV0urs6v6-kMo7t69ny76bWQZum3q-nO3JTPnp9vlqvjm7ul2Pd_44eXz66aCU6rHTVZLBbT2V4nw2q7qauYS28A1xfL0NZ918MIiKwrBS6SHOnpi7PZzv4kxi4VM0h9slxyKjIMk-lkSLkUu-r73d2DZjYD0eXlyhgWi2swS32nUmJsutW6nUzYhaZpWXHoE5A574diY52OaAFAMXJV7bw3xHbWmkK33fh5XJwtQqzyZm15qHd3b925X7L4yj368ulb790nIDNLQ_EeycAM88hvKBp8ABiFAUBEKYWJVJUABQwIVS3nAQwCB7UiagzILzkwoYg473jEr5VShTYNW3REBoRmhADoiMdrropWMSBiHrJjNLXRzZKGwXtGxCxAjoCYHTvv2DkkBCRfxS6LlvwPf-27Nw_2_-qjT5brbn25MBFmVAUCxw4JofRZAcRIEUIMImPbrkERJixDct6ZFjQxgMn-_g9_fO___H_5H-7d3D3YncycO726TEnHbC8gggGPgAPVl78iZlVlR469FHUumBUEE5GxBQwB1NQ5ds6nbiCPZjbehWyk6-dETKBmIqNhCgnMFBDZeSYeD0nHjhBNwQzI8UhZZc9WCiD5EAjRDAzBOd7dP3zyzTezSSUyaNH1erm7t_fxp58NqS9ZIbBlJRcs932fwMw7NvIUAwJE8nXj_t6v_-D509NPv31yvepFVdXykEQLsWNgIiclG8HQldnObhoG9s5UpSh5JHai2uc--DD-2YhgNmtv3zp-_dU7U08H7RQIVGS5WCORqZlpCI4QGX1JBRGaOjLA3mxSRBAAQJxjHDkVBmMjai4vncNAGKMTA1W7Xq6LgSLGym2Wm_39OYAhYiqwGjryfrHqUJGZygAE5GofIw9mMfhUEqBk06ziGFORbihdX9KQfOU324HYF9VqJ_TrQcRC206mLUXaDLnvZDqfqoPJtEoijkUBnGNkULNUMte8vt4s133TeKKw2mwjeSKSwS4Wi_l8QuaIuOu3jtgAjNizJwMCC46kaMliue-vNrt7O-ur1RiwJEJNBUzRRFJm59BGGVdMlNgBIJl656yomhJZvy1-MmEzx9x1HRKhAQL3iw1PX_1uMQhVAyag4jzlXJiRkRAZimAphqBmbgymgAXPQIhEHH1JKVRVyrmqKiJGohBjrJsQvPeOkE2zi77vh3ZSmVoVAwE4Ysew7dZVFcgzMw45RedBS1P7-bQOPg5dquuoZuPVat7WOUseEo63S0eaxRGamhZoWy9FPDMYqMHxzjzr36WZAZs6MhEyVtEVsekYiHEYg5s1NTLnUkCxHwYzExH2FH1AsrZtVJQRh2GoYjDTpq4MsG0aZkxDIaS2iWjAhN5xUzWqqQx5OmuapkKiQFTXAc0QkBjJdDqbWCkx-JsHO0ezydX5Yjqv1aBIqdqmmcT1opvvzeaz-dCV1XJVN42pAHDKBZmlaKzqUkRTIuesaCk6me7326WqAqCIcBXy0Dtix850VIlR1IghhhhiQMau30oRAyhDQiR2CMRaNKBPQwrBhVClUvptIeDDWzc86f1bN3dC-NU3TwRJwaxYyknG52PRGLyijcuZEMPfcSTJVM2waaeipmimwATRBynCwQMhGNq4oQAqquzY-1BSISIDQALnw0uYJarznJLde-OVP_n3f7azv7dzsPvk6SPnvSEwUfAvm4at2GzWpiGxc6oQK4dMpSSHyMy5lHY2KSk5JDAgxCLZCBSgClVRGbV8NDPQKjYK45MaPQVExfEgCcFMCcCK-OAVdRzFCUCTkCMfAljhES3qOcaoObsQHRF7bmbtf_Nf_cP_w__p_yUiq22SlHIZQEFFclZDLFKQjBDzkJBYVQEVVYkAQA3MDJxzOfVkij4oFFMjwqEbkFgNnjx88vo7r75z79bjR6dvvfng-nqjoNvNwN6P4W8yGvHbquO3jsScciFAJlQRgDFDQilldojIAiaqI0UUcexIxqFPCOg5AL7sxgME07HxWgENUMfi4WIKZgjmmUbimxgQYs5jHJ9UwRFJ7vZ2D85PTzeLy_39w_VqXccajMiMGK-uOzEzQ0aIsQItk-lkPpv82Z_-8jvf-86nX3zqmbynG3dvEVPq03w-AXMu1pFd0bJ_cFRPZt8-fvHKndvr9dk2Q2xDRQ4YV31qgptV7IPbdJkxGOTKheOj_ewskk5V3rh7wqQlD30_iHOfPzrbbRtG8o6tlJvHJ0_PX5ydX1RN_f5br1dVvL5aLq-Wk4Zfv38kqRu2Q1XHWTU5Xa-KuEnbbLOqcUX85OHjUujwYPfRw2ebfjvbm1dNtVyup001qb3IcHx8b7Hanl12N4_2Ufvl5fP9_UME2K7SduiePz97_ZWbyNzWk__h3_8HHdL7P3i3Wy8ur69fPL4E7ZfX6f3feucv_sNPX3nrwd7B_s8__NXd-7f-_M_-Znawc__uK0_PXxSBd9559_GTR7tH-6---sZkZ_LGu2-2hztHt_YPjo5mN6bcTusJnJ0tVPovv3l09vTF46---uaTz7_87IvHD588efTt8ydPrs7Prp6_eP744ebq7PL0Sd5shm5lORsCIzGB966qKgWpKs9ggOYr5wiDc1YKoRJjFYKheOc1pTIUBDMFcqMf2ZarVbfZkPFktpv7jpsIogd3H-zuTALhZt0R-SePTn1VuYpB1VXt8Su3V4uLOky2q9XObKdLCgTXV1fHx4cJw3YYvvOdtz_68KNmp7l5cHh6cZGkj75yzuWut2KHx0er7QqAGdkYvIWhDJP5TPu-gBDSarma7R5QrK6vLid13a23_WYVap-HcuO976L000kjaqgWnKPgXizOqlARwO78QGTos4CkohZjE4kMUYtQcLkU50PbxKuzSwUrJcXJNIGWYQCCKlaTaXv-8JRj7BbrwD5fLyxtQ1PtHN8KNV2eXrTEdx8cbboiIN4RAWAZbSUwqtEpS2DOJTNTSQMZEjIimpkAiBRFUFVP5NmLgSFoLlYEkZHQtDDxyNcnxzkPxIyGjp0Z5lwQkBBMChIVEUQCEDA1Ey1qhMhccnaOkCM6UhVHjISI4KsaEZWY4ihX4_tvPLh74-j_92d_e3p2KTmjGQfquzLZmaSSS59G2Y49I6Hk4tkLmOpA5AGMAIkICcmhKnRd_vAXD2_cmH71xdfv3b1z48GNL798nFU0xO22HyQDEpiAoIIWUzREdmNuDQ3IcR6GsTRmRBQRjVBkU1FmciGkfoBRBGNnYCMbmojJOVMBA2KnIFYUEBRoRGKPcGwmX1SQ0Yr64IuM2wBD4nHkADMfPSFv16v9w6N7b76-ePF8u90C0fd__KOHn3-VCwgqshezqvJpm1TVO08I6Lwhohl7eu21k--9-frHn3_75cMXV-sO0LbrFSGomRkQUgih5IwIKlpPKgLKkh2xAzIwMfBVYGYADFVEAAp8crA_nzZv3b95Mp_XtRdJOZWUB-99KUqEuZSqiQBIgCGEKrid3SmYliJDGkoWMHWO85ARyZjFtOQ8uoCQqGRlZgNdbvoQXEpllGvRDBAePfm2rprLvs9ZkyqYDaW_TokCsmNiAg-eIWdRpDwUVRMzSSWE2HeD984UEFhUGW296AisoEwPJvO2XW9TNa32DiYqslgP1YyX_VYACoiaIJgnZ6nEKsR28uJ6cfp8M9uflGLR-1wU0J5ebUpKoWmaaZ2H4mIkzzEEA9U-r6_XIpgHaVqftl13sfJV3feDqCmQaHFMWlRLRiRDTClzDJYLmmkpCMCIKsLkEIEZgR03lQwZAdvZJKekIijDzrzi9sH7WbKBAIpqUdEQ4gieVS1ohkSiSuyRyeAlZZ-d93WsqjrEiAhVU49sYBFBIh8DqjrnQvAqhZHEoA6-ZKur4IJTLdH74D0aoCqZich-OzXTOvpJVbngJtEPQ1pvtsW0DmHbp7qJVROa1iPAYtVXgUNw0Qd2GAOnJMzIjurgixUwnTQNAjBgn7KIzNoGAerKxRiQzDtGgMgMQOOQOUYUEShLmc4mjGYGzjtADJ5jDMjAhKpWrADgzs7ERJsm-uBNbDZtGNG0RB9yysE7Ipq0dRU4RhejL9vUTlvHuNNWd28d7TVNS86IkkqIYewDXlwsY_QIPJlNLy6umHmzWcdYj49OdpiGhGAUeLwis3OGKLIdcTTI__khC1qKWgEk530ekndeSvax6rv1m-98b3l-ViR7rpIIInjnoSABoCPHzI6VkD0BgKurlHLrqKr53fv3P_nq4bovORdQ4-isFFMlBlATtfHaTMzOuf9cTwaIRmODAaOYFB0HAEAGBEdsUtSMiImJnaexktcglxKrQD5IGgCBFM2s2d398uOP6zo--vZR1daHO3tnZ-cOR2AFgAojSoEYuO9SKck5h4pu0kgupjBmxMcZ2lSKGQcEA-_DeDIi4lhp7r1TwyLiQihpMAByBIhSMgfHjgHUoTNTAzBVH4OpgapzbjweDNARhRgcESLWVcUMddUoyr_4_d-dV_Wff_RJSgnQyjBoLqLK5FIuIpAlO0TNaioG6qpKJBcRNEs5G5KQgYIDTVKyGscwbHsfvaQsqiX3iv7xs7Pf_M579w4PP_zkq9_9Rz85aGaIRtFfXy0YWRg0CzsPhEAgIgZG3o15PkROJRFxLiXGgIDOOVHJUpwbUdU4DJkdMlHJoiSEhITICIAMaFI8OwEbC8iYiNBedgKWl9mAikNRMYMsaioMBAQqKqk_uXXrs8-_aupJ3cY-DZUPQKhFg8chD6mki8V23gQkBuMQ4q8-_uytt988vbowhSaEWyc3u82qFNw_nPcptZPoMi-Wl1Rs0tSnzx6C92zhcjvsTtsJsxAi0d5euzuvuj4lZTE7W17eOj7pus00RrDh7o39W4fzq-XSka-q5uJ6AaaEmIYCJEeHB0B2dbno-vT226_MZ7MvPvl8Mtu5vry6c2N2tD9fLTsfQp_Lo4urZ6dXt48PLheLvpTrxebG_VsfP310cveG9bIzrW_fvJGX29Vmvb-_l7cb8rzt-9V2RdGX3GcZgq-Ob-516-18PtvdOXz0-HHbuF_7_nfTUEDob_76Z-v16ke_-_3l-cLV7deffeu8qbhbt-af_uqbm3ePved5W833pt_IcrY7u3ty1B40e3s7zy_Or1ebYa2T-4cf_PSnn3728ccf_urDv_ibT375yWd_8_HZ8yff_OKL9fJ6e70sqy1pkX5wxAzk1KBAEyqCceEXQqhCqBXM1JwPzjliNjBFyjkjQUr9mCZVs5xExDh458MYoyypjMAZNPOVFxEwLIPOZ5Ptulu8OGUCsczkAQDVHrz7Jop4psVieXp-uXO4u1gtjm-cTPf3Xzx_fOPeHQLbLC5S2rz6xmvXy9VqdSFDPn71du1rRPG1O7p54_Mvvw0hzNs25bTu1tNmAgqM2KdhujubtM3l2XW_XPvgq2nVdevp3q5lKMM2b7rkinNNE8Nmtayn8_VyYaVDBSgy29kHLE3TTmJYLbfT-WRnf--brx87GM7Ozw5vHkvKm8UqxKqdzhQUVOs29F3SLHVdg4Lz3G03BgZq9Wy6Xa5LP9TTmsBcFVIZ2Ey6Pq9XJAMg3X7tbRfg2y-evP_rr_ebnCTLiPNHKFn6IRmDqPW9AIOZmqrmZAIEMEh23sNLIgIhkkgZp4KCZkUYENRelgcaAoASiKqZsnM5D4CUcwJmU0AAT07FAKGIOu_NgBDJMQAiAjOD2t999CFWqR-qOqgaM7H36JyPIVY12_APfvhrt472_s2f_nR5vUVSBBI176OPXkpBIGfRoAAqMr6sohUBAMcMYxSQQUTNDNAkD1fLq-WQj48Pv_jq4W987739w4OvHj6ezneX600Wk1wcUSnFQMkzGkhKiOgcmxmoGYCZIQEij3K-qTITscs5-1jpyxgrvLRXgqkK0ViWmgCAQ22IqsaO8SVMgSRldlhKJs9jisD7YGjOkXNeTYmICMW0quq6Cavl5uYr92yzWJxdiMOjV14Pls7OLnI2YjRglcLEhgYChJhU6sm0aPHMwYXf-8PfvjHf-cUXD5-cXnViUgqW4r0X0zIMjliLjrEBNANQdAERu9UmVpXznIbsYshpQMDp3t7QbQO7ZhIqk9_4zmvekaqG4IopkQOEIgIqh0e7jEjI275vqmAIjIaA275TMCIIIYwB6DFTN6RSRLOULLZNOZfsmLNCVXvy3jvqtmk-nzA5UJASzKkRXm1TtqJIjsNq6M0hqNXRmxk77tJgonUVgmPPjMxgSMzOc3AhZwO1y4tVksLepTIcHO3UVbzcJAwYG08xJMu-cih6sVoHxwjo2alaHav1Zkshsg99HjbrbahbFxwxoKODvWnKtlxvJvNmvdosrtYHe5PLF4u2qd0kSs425NQPoQ2ayrAe_NSpgchLPi5FBlUtwo6d8yUXGqfQ8e4x1gOZiiiBAiL60B7sxqrtFis3ii6GMgzd1TWHO2_ZeBQrgNhI8nLejQZBIpJcyAcDK6IcPZiRw5KFXSBHzEREYgYAVRV9FYsIEgIAM9J4aSUAxVA5YnbBj_8bHRNY9M7QUsrBsUJp6hCdn7fRAPou90PCwGOuIEQfHXpyMcbNZtibV0ysak1dg8Fs3njvomfvnWVBtNoHZESD2MRJU40KsnccvCtZmroy0LauTCTGsFpuEFlEVJU9OedSNzh2TV2PMcfg_NCndtIwQgyeiAipir5tqn7bt5MWTEDNO49m0zaG4INnJtydt6bgCGfTxlBMS9vE3XnbBEeKk7qqJiEXaSYNB0do00nNxC7ELz_-qmqqNKRmNhMQA0OE7XLbTifDdgAzKwYAzCRqkpP3AcCG1BOHIiX4EbZAKDAaLpnHclck4vlsdnh4_O3jbwgcoiCAJ29kgpqzkUHwAb0rIoRcigTvHfMHv_jV_-J__gcPHz0-v1opUC4y7ueKqmQITVAoRKNUD-zGHA-IKZN7iZoVQBhtI4rEJQ3MzseABogEauS8qjnvDBBUx1fPuExIKcXKi9hrr94-e7ZEUR_s4uKyjs0rDx6cnp-OKFtQICRTrOvY50REzjk0rKdNTnmEVKiKc945RMSiCoAgGmMNRKbWxArGaYScmQK99MaImJg1dS0mknUMwqoqezYiA3TIhqBi3jOAuSqYqQ_OAJz35Nk5dsHXs2bauv_mj37vky-effjwUb8VY8vd4IhKVgBSM3b0d31-QUQUDEUdk5qpCCBlUAISKUZOiqmo92QICDCe9GgAHsS08u6te8fnq-s_-Y9__vlX36767XS-8_5b964Wy9wVcGSiPng0YDfyNMQMRErOwkiA4JgRkNGbCIAiIIwaFRB7ZyaqYAQvAwYAYKP2xmO1EAM4YERGtcoFA6scK4zF4gBmZQScMThkNSMcUxauX68evP7WLz744OTkhvchl962mZgNwDlWttV6nbPUVS0lFytDHprpxBJ2qfeDvvrKa8-ePCbnd3Zm_TZVFZdBPMKk9kf7O92me_Ti7NXX3n787LRq6-AJGKOP80ks234oNpgGhvN8ff_4Vtd3FRuQvPvqg1nbKJXV-aUZdl0ZEiKgqbaTNtbh7PTy40-_eOvt1-_fu_H08YtbJwdXy8s7h_Oq9ttlJ2aH-0ddGj7-6vHTs8Xtm0fX626rJaUy35_MJtWE_Pv37l9cnPdXKyFjb4vVsmQBwLpqd9rJ0cnxsyenQxoO93Y5dw-_eXxyfKMivri-3qw273_n7dVqBaCnp6cvTs9P9mdErm3iJ59-ozmnUubzyYsXy1g3-yf7W5ac-gcndyoOr986-ODDz5vp5HjvUL1dnS_PHp_Ws7C87GMIMQYCdNGPsPNmZ24ZOMaci-FYVwiT_eNS8ljPjM5JUSlSUn4JO2Eq41xaRLUAWxkSqiHCuL9WUxeiFHVNnTd90QxFzNRMiXEMVpYsP_wvf-fm8d3Tp4_Tuk-pA1HLGGNwjJt--_Z7b_jAg4w9khsxeP78RRUdIfXbzc2j46ePvskMxeLBye269lenV_ce3N0ur_cO9s7Ork7u3EAdnjw_ReRJ24rok6fPD_Z2nfNgQgrDkGIdxzFmdbmom0kEUBFHtem2X60xuEnd9ikLUOk2DOiYYlstX5wtrlenz14c7O8TgpRBk9bTSd8Ps93d54-fn9y8FeqQN_3-4TF7J6Kz3ZmahRDWq66ZVbnkfrv1yNtl1-7OvHN1UwEiGG9T7jc9EhMw5KH0K-J47w9-69u_-mDim5OTg26bjAp7kr5E5wxIwRTIFIhZzAyt9rGoemZTUBUkkqJACGZoQAQEI-szZO1LKkSohCPqFwDZU8nFB68ijDyeMiZCYEwMIi5E0cI-9NuOmUvO3jkgZGIRYedHOdzQcSAkRO8UwEUmdsAcq9q3wUH5V__kH06b9t_8p5_mJH3qFSjEoIpMlCQXSQo6cggVQcUAFUCZqKQc26ZkBTA0UzEiQlMpuE25-DqSHu_VDx7cc2KXq-V23W36lFIWUQYsWQ1Jh8xEoqLFyAdVMQVEK6nQGFYmZ1oQsOQUm2nfbWjcj6gQufGdggiShUMwUynFuRoIbXwviLkYS8nsGIlUjZ0DGIV_BRqPQgYzVTUzdk5F-vV6Nt-ZzNoX3zze9h2G8L133_vw5x-O_nAf_FjknLrBBWeG3vuuX8RqB5iaKhDoH_2jf1B59-XDZw-fXy82G0JApNwnMVFRyRLaCArESI5LEh8qszHQDGAATKEKWrLzHkSdd23rFMvbt4_evH9r6IcxQg6I220_aZuiQmBVjIRus93UVYzel5R8DNuuryvvHA9DZgIbQTceUy5dX5wjUXDep1IMFEeZyXDWtl3K3TA0kxoLGikxbHLeqapnyy07WvXJRW-KPST1rubgiUVBTJjJULOUPhcmGjvdRECRtl2vIopqY_hY4P6Do6LQu1LVbr0ZyPlcNIuxd4pZs1axcmBqJAa5F0Ccz50jX5BC9JbFEcTglssNekfO56GvQ-y2yTneLDbbbfLs69oRMQAvLxbzo93cb7bXPRODqY9RxwAAOcmDFXWhlpLBgJ3TnMzI0ECUAkneso9gRj5wqFQsVgHAsuiw2jKSx8LNg3cNyTkyyaZCBGVISI68Wy6XddPYeJeoIqFz3oGhKdRtM-qtzjE43m5SM22lSKiqcWwYH14-eGbnvHfM41zhPUMRK1o1gR1NZhMpuY6hDh6Jbt_ad8SjJrQdkuDLVFDuhkA0bVtR7TZdFVwIXES9c3UdYvBn59f7O1NVjUwvW6gcVXWMjvfnbRYV0apywblAzAhMQISeyREr8svkTpEQXAze0JqqEinOOUKuYiRCx4xgIcSUs4HNm2roM5jVdT303XRSOeeDI--wDGUyq0Gt9a6ufFuHbpNmTZjPWgZ0jkn19vHetKog57r2QLxYbGJwjDiZtJeXV6vNumoqF8J6swl1Vc_qIiqpmMnYjGiEjtmhqQgiqRZlKGbMrCJjekhEDcERlVS8DyVlIsTg5zs733796PjmTTVbLy8JnGYxIiNFcmgaiIoKeg-IZsDM3nET6qOD6R_8zq9__dmjq35IAiLqggczBrCAkopzTsTGZQqT88GnlBFsHL1KyVWsSs6OmACQAMCIeATMGAAghBhKkRAiERuoc4zkQAtzcB6RkSFCsH4zEMnsYGJqV2fn-0cHzldd38UQc1-cY8cIjD5wn3Lb1mkos_ms64YiOadCBI7IOacK5CjnFL3LWUKIhmqiTB7RSslEDGbErDKa9Khk8dGhmanFGEYMs5kpKDvm2JgUF5i9AzNEIueAoGqrMpSqaaq6Orq59_rdW6_dOfqTzx4-fvZ86CU4yn0PWCpXlawqZeyKV1RiRqDUd2ZKyICgooSIZqVIiNHMvGOVImLexZKEgweV0Tnap_zi-eXtB3fvnpx89vlXk7ZZrvuLi8WnXz576537625tnSEjGhIgqBYtRST1A5FjopeNzqoGAqgM5LwvJZupqJJ3DlFE0flSSmBWNQJGAyZnJr30DA4BTTMBqdpLwi87ZqcmBJZLYcejdSrnAgYFNPUJyAyo9Ou7r77yP_3pX8wm0zo2ZtlMhyEhOzKaz-r1YqUAjEjs9ud7Xz7-5q27r__qk09KKbd29s4Wl-zCdFINfarZl5J3duZdv1GEGzdvf_7V11ers7v37z2_Wszmk6ppqrk_nE21yBLE-yBd2vF-0kz7fhuZRLsfvnF3eb1I3WZa16LGiKeXq-Bin_rdnZ3Vpvvoiy_u3Dp68Mrd9WIZQtxsNl98-dXB_vRwPr2-XqtYCOF6tfn0k0ev3b9Zt82Xnz5OmkKkdl5XSu_ef_Xq8gVins-ndWU3jmeSdH_WvvfW6zuHO4---ca7OvoAasvrxRuvHD56cX20O6uaNme5XF7evndb1htiJGy--eorhHxycpOBPvrFJ2KSSjLQ46NJETs8iOvnPWF57fX3Jo5evHjx1TdPbh_vny2Xblovz9di1lRxvdi2kykbdl0mFxEZEGIVt5stgJYsgD6rUVUJSOkTACA5VbOhd-zNZOwFl6I6foGIlkIGgZGJQESyyCCeWSXDmGzZbgNTCE6zkAkB-sBtW61Xw6v37j9_-vDbz7-oYyypeGYAAEmr1VKy3rh9sthunnz7DERX16uSyyuvvPr86aOKXO6HtvEhhu16FWc7IIkRl5er-aw15FnbbLvtan11487dru82m1UpRcSmk-nF5VU1mRJS00wNDQEk5ZIlhHj68MXJ7aMqNpthE6fzYdsPfea2BTUx1KLddqNF2_n81hvfLSUB4NmLFyc3jpm9mCGSoR9SOto_JOdyypvF4uTkyAwFQU1n08l2ubGUybE69FytXpxXbXCND6HOfeI6mAmQlpS71cAUKJd-fQ3s7rz74MnffvL6914fRWtFY8DgmBGLjF0xoKDj8TGkQsaiQsRIzgAisZnlXPwYP07FAAxNTEaYn5oxOiTy3qVUvGcTIEQTBS3EZEXBbBSeRdXIgGk8qghBVVQUGJFGqD0jIyKJGjmnauPz07nIwTnnm0k9n9T_x__2f3eyt7u42v7J__RTZVYrko28G5_S7FwqxWDslgEwUNXoQ8ni2amB815UPHszYyIQZecJAJFS34Gzr79--I9_7x88uHdTswylO18Nm02HYPyysxZUhfDvLusv-x8ZANGMx6lDi4_BRERH-pAraaDxa9QEzLkAaqbK3gMi2NhFQwbgnAcwRaAYkLgMCQBCjAYwIuDYO1EBIzUBJCDKuavqOGyGN7737uWL081imU1Obt-qJ_H8xZmCY4QR7sAIBuCdT7k45xw3iEjBk8lquflf_vM_3Cw2v_ry2_NV1w15BHAGF7ebjYgYQPDOEIFGNpzGqkpdH6Kjl34xlCw-BO8DMzHZ7s7ezZtHb79xb-a89y5pidEPKSGiqCACEbVVNfRpREMCWlu3pWQ1YOaRdFRVQcSKiIjlLICYzURtyCWlnFJSsyoEROy6YaRzRublcqMquZTBytWQBilggAH6IUGgto01BWamQOZREUVLHjJ4XA-FwGLtDFGLLZedc1SKOO-MjXxVNW7_YCebTXbrnLLzXhDQgYIC2tR7UGS1OsQkYiDO--Wm65Oqwe2b8_VqwGLRUTekdT9crhbOVzkVH0LapsXl8tbt24uzq-7sup5U_VAQmBm36xVHX-20w9WKwZwjFTXVMUNCo0UNCBFUCzKpCPJoS66dq0AKEaVtH3d2uJmkfgBQQMCieegs9RxvvWmIJqBFAAyRiD2z6_ttM2kll1g1quJ9ZUy-aUyNnIuORYG9VxVCV7WBCKq66oe0f7A_DLlpW2Z0BgYAZJN2oiXVbeM9e-IYAiOplFB5VEA1JtydTBGBAcnxNg9gSM7lVBSBiaoq1pUDRO98DN77Uf6PVeVLKk2spBQmdMyEUFW-bUNbVcHH5WLjTOsmqBgjjWgZE-iHVFeRiQtYHjI5QkRAqKugWeo6MDEClCIA1tRR1WLwhMAOPVFwzlTruqpr58mJ2cHelJHaOigAIuzstHXlI_PupNqZ1WQQPO3uTZ3jyru9aT0JITgHgCO40zmfh-yauFkNi8Wymk4ArWlazZKGIfel6zoAzClzCCVlQJUkLkQAMERFQ2bJZUzhMIGN7esIZkDEYDK2i08P9mUYzp8-fO-7P_r6q89ddGhMpICMaATofCgCzvs0DMzOVwGIDGhvbzr069_43tsffvYwi4KnLDruBFMu7FiLBu9NjRynPsem1iyOvWQdzWMIRI7BDIwNRg0GEUc49Ag7oPGc4TFrxYRoCAhiPnoi2j_ZX1yuxiDsMIipzabV42-_-cFv_-jps-dmWMXgHRoiojkXpRTnWA18DGpQ8mBFtOQQAhOOtB0pykwi4kLIqTCRD15E1EzNmFhFPJPJaDoEh45oPLFYTVFtND6aQjuNYjo-4EKMxDRIjnVVh6pqm-nuZKfyP3jr7u---UoTm__HX_zt4vnl9WLjPeWxdNeMDEwt5YEciYjqWMtDfZdCrMxUAXLJ7NEDW1FDBTQ1LEnII4KBZBvrdYBMDCN_9tnnr96__c5br3_15Nls0qasRdPF1VqGLAxDGhBRUWPgVGS0gBHSeDqbAbLrukFx1GOMiES05OKYCNEATcU5rzq2DbAUNQPPwYzYYbFkyH1JPnhDU1MAYOcUDBAEwCEWkZdtFA7RjBgDswIBuJKGB2-8-bOf_2xnfz4uNwOzqIpkFKyqar3eIAiQ3djf--N_96c_-cmPP_zoo0njnj17vDubJdV6Wm-3W-fJk5_U9Wq5Yib0KIhn356-997f7_S6CVx7VxMfN00q6arrTdSzcS5FwLtce5i4_Pb9k_OLa5LUTOuSFTx--MnjnVklBA1VXz97jibvfecNSyJabt46_vnf_uL-_ZPd6c7Q97mU-XS22QzfPDldrzY3bpwouMvFOXvXLVbLTXdjp86Lqxu3DgEkDdvY8M40nF8s0TF7evLsuRRImiI5KVi2-erq6h_-_m9iltMXl0eH-4-fP__si8f3T-YAYjn8_Je_6Lfb7__w12zYPD5_trpYS8ky8Lt3f-fh06-3w2adrA3xlds3-i4hFOyHV28eDF3mmr_-9OGd1-8e3Lz79PGz3aP9VHJBSL0287ZkVQQCHPNgyM4Fxw4wD44pSykm4Bx7h0jEDATAI3PQANAjBc_eYS4dqtWzObvq6O6datIe3br5nd_9TRnK_TdfPbx9a3p4fOPeg_tvvHv31Td3b93eObjz1nfe_fbrL0Hj1eWlFShqZmiOhyGjQ1_HajKbtu3teydNdNPJxBF5pqK2Wq7mO-2zF5fRu1nT1qHu-vV0vvvFZ99O9mdMULcVgJaU15vV_v4RCRhCtrzaruc7e5eXVzdv3VheX-_u7Jd-XVehQCax47t3fvXhZzs703Yy7derwGEoqQzLWE1TLlZSGgZ2OgzrpHh483Y7ac8uT188u0CjuqnGziMkdIhDys1s-uyrbyfT2bYv6C2n3PclbTrvYLPcdIM4BwQKKquL7c7RUbe8TuutFiWPOoyUN5TtKm-XZtY2M9l2R_dvpm0uZoxGYGSgqmLWpUEQRDTlDGDOkcPRy4JiagBltOgBEKCKjpgEJhZTNCCgEKK99KOjqHl2-FKoBjR7ufATtdFHZKrjonA0AY5OdjDnnKj54LVIiJWC-RjAoMvDdDZT1VHei472p7P_7T__wzfv3CyqXz4__cWvPj87v85ZDUBScc5rFiAsSYhwBLiNMLeRFmVmo4BdckGi0e4bXBhN0gpISEm0FJlM_L2bN95867W__KsPzq-XfZ8AEbQgYcnC7NOQiQm1aBYDIO_Hg3U0S6kiAKgqjcig8XgTcc4pYnnZA2DEo-fHqygxEztARgJCAAXybCgIOKbgfKgUwVTIjdctFDUkBo9M3G_Sez_5zuL0en1xmcpgBr_2k9_--V99aEoGoi9LDNCK4Uh7GCNayBzciH6-vr78l__8D85Orz_8_KvL9ZBKkaKSCxOlvkc2ZgcGauN1E0pWseI9oULOiTkgWqiq4Fi1-BCqGF3k-U77_uv3d9oGSU8vrjfbvu-T987KuBNUQhLTpq7Pr5_vTHYRodhYTAeO3dh_SoQ5KQAVFQVYbwdg7Lp-vKppkaqKAlBK6bP0KRWBNCRkY6Q-5dW2Q0VgQwRfx8VyaNsYnDdAcihja5Fj7xwg1t4xcE7iHZdiXdeJYs6SFcMklGyzuo7RF4cqvaJuFwkqDK3vewsuGOG9velmm8lBW1ddKZtuwOAVzLO_OF_mJMhEjosAErEPw5DZuevF1cHeQe6HYtLMIoisr9fgPHqq6mZYd6uLzcHdg9WLMwYKVatFEQmdQzF6WVDtkRDU2HsTZSRURVTnIyIhInvui_i2bSft8vwMibTk8abF8fabIAZgpoKgiKDjPxEyIsSSEyKLaqzroevBbLTap1SQQUUVIYaQs7kQnA_9tm_bBqREFwAhpbHiQZtJA2YgIlIm0wlIDt4XfRlZaOoaaERAqoB227JadkKWsvngHZNnjs45ciE6xxgrr6KOiQ3FzNkY2YedWc1mfZebNnp0CrAdkg_snQveRx-JoO8zILRtxYiGMPSZnWMgZlIRBnPsxm4vBAzOOUYRYUdtHQkJRwgAYfDOEREgO6rrioDQtK6ryjtm5xx7AzaatM2sjke7MxVAhE233Zk0e-2E1LQUX3kDCNETU8m6uFpTYDNcLdZE7Jlyl6q6yqmY6tBnJCRCFbWiSqAiLnokIwWVAgI5Zx-DqgIaEpWc4GViyTEaOu9D7LedR3v4zZdvvPWd508esXMGBoZFzTn27BTR-3HjiC6EXCQ2dd3EzeXZP_oHP_7g558VKwJ-yHl0vKhZHhIiEo42cEBgk6Ii8PIUMBqHLyAiBkYicp4BDYMzBXbupbbC6ENABABFpSKFnSMiJkpZ928eLa_XMbDm4gOLWO5THeOjJ6fvfP-7282WEUvJDhkYREoIQaU470Ws3Z32XUdqnhERXfAcohkqqIIRs75sPDEwCyEWyd4xATjnmBwzqSg6h44MzAS5cgCgDIhExA4RAdE7VCN2jpmIQlUxkiHUbX24O__R995vAlwt8527N_7Hn385bPohZ0cgRYppASAcywNwvGErAhBJEcecUiJPQOQ45JQIx9YeVCmACFBUDRBLEVMVtXGGERBD-Pkvvrn_yr1b8_nibL3OCYkYFZBzP6ShIFoWETUgBwBkSKDjuFhetgegFBEr3rGIkfdEIEnYewMj5CIZgFIqqmWMfxi-bIcgoiEVGmNVxKWUwF5NS5H_XJYpJkyO2SEiAqlBASWjVIqJpWF7486dX_78gzs3boGhWnGO2bmiEmqeTRrP5Jy_c7z707_8xY9__GvffPv1ar25vLzYme8v1tud_UnXpbquCaHxrhRZrLe3bp18-fCR915x2zpyqh4QVSO4Pg1dTp6pCr4KtVLem9Zo_fffezBt47cPH0_mbden56er8-X2y69PTw5npuAJHz17dv_u8YPbN68vr-d7s8P5tEhiAAZr2vb07MXu_i5g_Mtf_OrBG_dn03az6p-ePmcmMz06OvaWZjF6x9vtpuRMICnLzmy6N5vmpAQwn9dguFxtmerTq0tHeWc-v15c6qDVpPnbX3za9-m3f-3di8vF0f7J337wQbde_OS3fzJslyTy-eePkbUUW8u2W2-HnO_euylKJzdObh3vff3oq9pVk8nkzz_62YT2P_34C1dVFp1HFTGOHqtoCkg6DCVEL2gINJYzSlErYiWnrhBhNZtYLikXzQmZzUyZDNg57xFVMqJydME1r__W70-mYcg5tA7AhSp-9cnX84Nd7-v1ZlDDAna1uFpePj8_fXFx_vzi-kzN1HT_6HD_6GDv8LjZ24mzaTNr5_u7zrnLs7OPP_rlZ7_8-KtPv_zys68Wl5cff_rFJIbLy8Xr33uLkFXMed_W9eXVau_GoUqnJYfg9w_m0_kUpGy226LJ-0pUYz1hT-fnV7PZtNsOO7vz9WoxbRsTubxcudpfX1zcuHW4Xiyns8nQ98iEhpvFsp7siBTvwnq1lpKbybQ6ONykNJ9Mbr_2IJfh4vHXZUh7-_fExDvftBNhBubULbttH9p2frBzfbFsJrVaMbB13rSz2ThpS78d_RjRh-3q0lcOimVVdgxqlku_vEACifHGazdYY8klRj9euTTDeAEdpIgYmDJxKgKAxMRIgDReBQDG-y6OoS0kBjPnfCmKzIQgWQwRiYqqmo52XzETAWaGUXJCLFoAMYSooDIWCqoRoqgGcobGzABA5JBQDBwRO-ecJyKuuNltmrb-rV__zn_7v_onN48OTy-vn19ffXH6vFNYLLuh7130BEDMimNL0ZguLsicxwcXMQCNTzMmNoCSC_0d-0FNjRAd5axJAFEvz5d_7wff7bfpZ7_41en51bYb0pABEMiQcByg6O98awZIzptoKVlBAdFMDZSYJQ2OPTlXchmhNMTBDHAUigAQiGPQnMAEidE5KQKgZuZCRCQwUMnsw8twBREiAQKqEbFzTExWioqlHkxs6BcGcHz79s3D2WeffhNCYI-SFQCcIwAhcESIzKDEzo1LAWYs6epf_td_9PTZxa---vbiapuHhAZIZqCAVEoRtbpuDdQ7DwBIiADOBVAFNCm5nczLkGKcmJS6aUxyFejkaO-7rz9YrwcDWay3i-X6xsnhcrGZzts6htX1JkRvpjmVtpl45r7v-5RCjGBgCGYag0dEUchZxpcHIHZDSkWHktlhHsw5FtPtMKRciFyX03bYomdj66X0JQfvSjFDUtPpblMKFC1gmktJpSB7AEpZkBhNiACVtl3vQwy1V7Fu27vgEHC9SQd7Ewx-0XftLMQYgg_dqu_6cr3sY1sZ6FrKQRP_9LOnIYAAIfOy67Nk712X9Xq1yqZ1Hbdj5lgtqyloXVV9lquzS8Dx5SSpG6oYRAqg1SGmbRLEfrllHCG8KiIMKGVMHWd2DtDykEOIUjKoEpjJSG5Fcr6UIuCa2X7pN7FqpBQVBc2swtO3vieimosLBGpaBBHZOSRmJhjnV0-IqAqxrkKMy-ulIaiAiw4RJKEPAQxyKsw0m83MAA1V1Tk20Og9IezNJyPIVrU0VWCmIsURIyIHHnKu6rhYbkrRbd8H75oY-5wdub7fOub93ZmV4oPXXCrvc8pNE71jRJjvNAbmPflATfRSymTeBO-lWMkZxlslcROdARCjGYbgcZy3y8vVHiAy06jxm5r3zESenaiUkqsqjrUZTNQ2oYp-SGnW1GrqvWfH02mFYAzkGWPwVe0JjJH3583OpG58YMam9k0dHNFOW09CJARRyyoX1-uhz-cXC_KulNy2zXKzIUfMvF1viGi2Nzk_Wwzd0MwqUQO14H3qExCUorlXF7gUQcCRBkXIImLFgAAUTJWZVQ0I0rbs3DxYnV8HXzPgxfnpa2-8-fz0uQ8RnWdUSWJiiKQI3oUxSiUKMTRV9Lvz-Ls__N77r937q0--6LOhI8syCrpiQoZo8NJAzy9rVEY2Ef2dBEhM5IirUEohNUBUgzFCFaIXACJ0ntWAEWE8IcyImT0Rx-m8GYatiiEyOUIGR8zkah8Pbh2CmlkBBZFCREPOO7O5KYQYVDTEWlMuQyJQEVFi4JelXURUxwBgo5FJFZpJlfIgRUIIgKxmk8qhGw39ziGDWahizmkEN3giDk4N9vZ2teTKO0Agz3XTGJr3LjD8gx_-_4n6j2bLsiy_E1tq733OlU-6e7gID61TVKWuSgCVVQU0RBeBbtB6QGMbrc1oxhkH_AL8FpxwwGFzQGOTTaJBaKAhCpVZKSIzIjPCQ7t7uH7y3nvE3nutxcHxJOfu_q49f--cvdf6_3-_b25t-Kf__Ke_u_PwRz_5w_d_9cnTJyfuYLV6Lois5uROANXU0Aml1IoTQc8cEWqpiRnckKGaIToi-YSdyDZ5K92MIpkqApgaGJhiasOde4_eefuNENL3vvPNXLovHzzdbHbIPoHHshYk4RjHIROR1-qAs6YptVr1AC4cy1h80tAxIyAJuXkKAuiqblpZgIlqrYgIBFOoIIVo4FDdASWwsLg7kZgrAE7N8aKTcBisqqoDwvMIMoAZqFPNw5VbL_7H__SXt25dNwBAR0MKguboSIiuGIL84oNPv_HeGw8eP3706Cvox77rjl85cnBGYgkC4mC7y3pyfg7iN64dnp1d1KxWfP9oLzDVOlxZr866bQFjQkSLDpj0aL3qdpc__oN3DfyrL-9dv3bcb8da7Oyi68puNm_7Xb8bdoT15tXjeZPOt5fvvv7KJ59_cfb09Ohof285v_PJx--99Wap-h9__ltnufXijVlqHOzi0dNdVi--2_V7rTCSjkOSkBph9vlsdrhYgvOTpydDqcziQhdPz_auHlIZYuLLi8160TBSE3E36K_v3Hvx1j6Ct-3iw8-_fPLs8Xf_4DunT581wX_9m89SknEoImhWQet8b2_bj2-_-TKaf_7pVw3a_sHRar5m9k8__WR1tB-QSS2yzJdtrnb19o3-8qKZtU1i0xqFteRhOyz2F2DOUYhlfXxcuhGc0rxBBCR1d0NiEVQFK25aakXE_RtXP_vpX50_fSIE27PN5enZs0dPh67fnm3vff7l5uz84tnTk8dfnz19eHZyvut2ueu7zXZzdnn-7OTsyZOnDx-dPH109vjR9vzZ5tmz3fnldnM5drvadzrkvNsNuz53_W6zOXvydOjGJ3cfaDZ17Xc9Ap0_OW2X7dWrV9t5mrNkHUMTUHg2b3ebLSONfadqs_l8dbg6Oz9dref7e_tCjgRNiLPFbLftJk4xBzm7PHvx5s2Tp6ccuWrtNtv1_r7mEdVK7t1scbDyPDZtO2vi4bVrJ2dPct8Nm8tmOV8vlhdPznjWkngtBVWvXbt-udnOZqnm0R2YuDs_Xyz26lg4hN35BgjapuEYun5Xtru9vTUh1GnUnXvd7dzy6vjGizdfIgT1igSglZGFBQgQOBdLHMpYhES1kk_7f5zgQH3uAgcWQvdaqjvCtPcrmYSsmLAAAjGTBKsZ0NEcCaaDrTCDo4gYgIFHiZM2HVwRjAj1uQNYgcXcicJzVDRySCIhoKCHcOvF_RfWB__H__1_9-O3Xjo9H_7ZX_3q__o__MuPv_x6eXQ9D-PF-WbMqsPATLmqmQ9jT4RlzCGEcRwlRUSvOQMAAbFICHGyI_mkIWNBBrPJhoJAImm5tzePUt55482PP_7oIufTzbaU4uYlF6IAYGg2UR-e55_BScj8-aQ_NTOtGQiFpQwlti24grtV5RBULcTgVVlEHRGZmKZ_imMEc2TyaijMSBwb1coiiMjMYz_GpiXCksvkBZLUmhZpA3Gowyb3O2R56-1v_uqXv0KOU47fYPq8NgEwmBmAbMrWA8YQwjzM5s3f_8lPfv6bO_cfP912IwvnPiPxth9TkFIrMYdp-UBSi01meWRkJld395SaadPSLmabzS41CRGOD_euHx_vdrvlcn52scvjCIh9P7TzSKrzxWLXXyYWcA-RUyNDX810gkvkUtEBCbSaurFwKZrV1HUcS0hSVWOQ2ERAdIQ61qYNVR2RzvudsJBTHjMTrecNCVDghELIoysSFCvqReJzC44QqnnTxFI0tgGF-iG38xCbCEEuLoexWjFvF2FXy1iygzXI8720v2532259vDq7vBgNO3cl2l-ke2ebqYWCLDVndR9di9u21GEsEkNfCpCDoTCa2ZizSDx9fPrCi4do8Oz-s7QIMabNJu8dL3dnW2SsZcRcTcERvBpGmkyvOnQEBAhlyCLivydQaVUQee7sDgJB2tUqNfPaDatX9quNZdNb13G49ZaqTTkLLxbbBsAMHAkpsLl5AUR0Ig4JSGoZTa1pogOa-iwcto2UcWAOsW0AQUJ0gM1m086akIRZmFEdZvNETO5WDFITHa1JTT8MKQVHxEB1GIOE88sti8TYbPohhFB0aGLKo87aMGskSSCAJgkArvaSK7gamBGRu5pZG6MIM2Jg2XW9o1etqWmCcGDwatU8RAYHFuq7UZj9eXrPiHyemhSkqs7bplQzrSnGJkkQmmoMQSRGQkcyQrAQJCVZz1PN1YqmFGqt4L5YzlyrMK0WMTHNUwQ3MItMUYQdEjMixCb2QxlrIebUJAQyg81l38zapm3cfX9vjeCAuOuylXp4_fDi5HIKq6gZOoA6MQSkaqoIAQkcJ0YvEhKxqcnvU5XEZAaLw71hs1FwCWHc7ijivFlshwEdzYGJYmzcFQnY2cxQKITEkVfLRZugMXvnrVf_3c9-mRWASftRiGup4ODoEmItddojcRRANABkpmmIj2RuiCg8B5oUhgAIhMxT3Idwii2lttVaWIQDE4IwSwzNvKljHketZiwUYpi8khKZhYvBarHcnF_knIkBEJDFHFKI7lpKni0XU30qtQkQzaCZpcCsVcEBhRGR-TngRtWAPDWJA9nkBjYLTVTVGCIhOmIzE1AyVQJkFgMjEgBPKSE9B0a1s1lKcf9g9Xe_-52T82fvf_DpsNt23fjdH731m998eXK-GbqtIHAFpAmM5-s4z1VdDRnB0VyF2cDJjZAaDlV10knW6kjPp3oMCA5MwcwAUdWsmrARUS4FhJezGcRmN5affvjFf_dffOeFK1c--PI-DK6oNVugQBxgWryo8nNSsAiQqiKhMIgEy9WnIZajgctzjSUBoBsAAFFwhMBMRO5ATGSI07FgSgggsJDVauaEaOAhRJrawwBuisyAoGpuXkxL1ZjEDFDLrddu_6d__5c3b94EdUK1YoSEAOZO4EA0bLsY4_njk2dPHpRdX2teLfcUTZq9IEwITRBwunL9hQ8_-Pj1N1-xWp-dns_aZnUwK-OYIhcvfclVsVgpeVzEgAyH89k47r718s2zbbfZduvl4vJi04328f27s3be51EgfPX43mu3bq3mi6J5PV_0XceIAfHa8cGzJ8-uXLnCwg78268eN_PZSzeOz8-3tZQPPv5ytb-HDrMor9862F_M4izOUnp6dhpi3Nuf7_rdtu8eXT555YXbIYRhHDjget1enGy63XZ3uds_ml3Z36_qr7761i9__f5slhaL2d560c7nn9z59Gh_vVovGOTOJ1_GyGNfYwg519X-vrmvmrR3eCCW0eDTu49uv_7y53fvDbW8_s13H3198tZrrz558KB0XQUYevv663tXrx4M5xfkat1gVsecpZHYyvnTizRvkPDy_HzoBxRAIGEEmLLZLbhhyYgmMbpTu9jrLi6qwny1f3zrRjcWcGkWM0SsgxI3TC5BAN2cAgo5gqPVKhw4BCg61dbRUYQZhJDcAKqCOhpJEEQKTTQ1EopEYLXmAdTGMa_XS0BaNLNdP165cgXJrh5fG0s5PT3hQEfrgyePHgUK283GwQ9W-9_71nc-_d0HuQzXjq7UWrUoII792Kam74Zay-5iC4x7672QGIE352f7630MApq70xNEvHx2tnf12tjtTNjQF8uDbhjHfjtud8WRJQDYWGoTl5q70MTFwcEsydj1-_szd7OhzpomMls1tcqM_WbbHszbmDYnF7kfrr18u98O4y57ztZfeu5vvvPOerGodeIFq5kBMHNAgmqGZKgeRIp6YHkeC2FMoTGtTWzNnIndDWCa4AAgWK4OzhPzn6VYYeJaMhSbx5V6MUdQQzIArKoxtLVUAndwmijOxYgYmCeHFsUIVblhjjIFiFAEg6S2Pdiffe-9N_4P_83_QlK6-_D8v_8n__y3H35S1Dk1u52fPH7cdV23HdpFMgetlYJUq24qRFhrjNFKERRCYArCoZRMQQAIfEolEQa0aWY_EaslhDY2KTx9ePYnP_nho4dPPvvqwbYfiwKoIZFZRZvMiDpN8pnFtCIJImoeCUGIwXzSpU1DNw7Bq_JE7UGetiDTl0NiIjat4BRSk3OhICzs5k6sXn0ijDogP4_yArpXF2YDJYKqNbaLsEh1ty21Hhzur9d79-99xdJMYdpcKhFoVUBIIapbdacYwYGEiSim-OJLN7_zjfd-9Zs7j0_ON9tB6_Oa1vPyMQIiRWGvtdQiTQB0K9XUQtMQYh1LWs7cvKoeXrlSS2mSzBdtzuMbL99aLNqzi00_jjnnIefXv_U6DHnetAAwb1simtLAIqEbBp-STkiAHkQQaXMx4UYKICFjqTmlplZNqR3GPGvjBLTd7npDN4DAeNkNgUBYFACBsnkSBmICzKYVgdHcdDQTAlIITURjdKimPMmbADlKk4KChTbszvqsYBWW-62Ctm3MXZm3LAEYKBJ5Q4BhKKWAdzUbQjEr7oRsSARkJBncA4zVLnKeL2djl0mkG8dp-giMwtSdb_vdOD9erg8WIk0dehjLxdn58nCpvZqrjUPNNcySmSEJEKA7GoB5SNHKc_yUa0V0ImEJboZCCtgs181spkNhgP6iL5u-dL3XzM2L74QUa60kxIHM1cw4NoDTQMCFmZhKLpISKJgrExKTaeEgVbNZDikCeGwiIk8g8FnblGxNG80wa01JCIhEJMiuG4Qlj4WZUAjMzMmqNyF2OT9vhjIbGKBm1XnbrFdtI2Ee06zhJoapP1pLnTWJEWMQU13MG2Kaz1pXZ2LVotVSkKZpVEubgtUykbvQQc3NrEkCOLFNEdxjYASoxWKMxCRBhMVNmYQQXeusTaguRG0TGT2lwEigNp81MYpMDzmCFGItebZoAmCDmohTk5iZkWMKQQQRYoyAMOH_Q4pINI7ZAdCsbSIAaDVEX7btycn5kDOzSJQ8ZlXNtRathAKAAIqIJZdJkT2bL2rV6uqT2dUVHVUrx4TuCgZOy8PVsOmQAgdmCbuLy9ly7sh5HKYPCVOEnFACO4DESEKxSbGJ7Hb-8Oy9b79xdHD4_kdfeoUQYyPCDHnCfJgBQc2VEYkopDBl-2MQBpCUiEBNHUqIMo3emUgCxzgFHBmfcwMFiWq1-WI-lZDGUdtZcpChG9uGmchVsToLH-6vSBgMX7hx_ODugyZwCgEmWwV4SrGWmqs1zRxRAbxWbZvGzRGIiWg6Ozu6uQQGN4lRxGaLWR3qcj53x5iCRFats9lsqkZMXpLURnUlIonRwJlwvVqCVSJCtNSk1Mh6Mfv7P_7j_-k__Ocvv3r67HJjjpfnl3_43Td__svPt-OgqgGJ3WoegcQQVI0JykTlBAdErQrggFhLBUZ3Y2Jzd3A0x6mn75ZrNq8kNPXGRBiqqQPHGFO7udylgD_5_nsnD-_9zz__6OoL1_7OH3yza4Ynjy-cAgJIihLEdboNY61mYEigbkNV1Yn3EIpVB1M1jnGCQPRDZuYQAiKr1igBYJIFOAEiASEa2LRBZxKtysLVTUSAqQxlCv_kPALSkAsS4qQ6N5hUo6ZAIGD12isv_fLnP339tdfGbgBCQirmFVyHOqoK0F_99q-vrQ-fPXvIyMvlqhvzfL2OIUkituLuxlzMLs933_vBGz_76w_B4IVXb6DjOOT1alZdi5mplVrWi3bRhu7y4nhvzlDfe_32_dNnKTBzMMfLPne5nJxvgHhX8q67uHHt2vWrV7_6-t7Na9fPLi7ufvXg9VdvMvh2s2lmc0P89Sd381i_8e7rCP7w4cnR1f0H95-u95fDtjct69UcmwDuYz-uV6tF047j-PT0Ytamo_W-Vbzz5a8Z1yJ8_97DP_r2dz_89G6bQsMiqCTS8OJnv3w_Bj7Y229SiGn-2999fPfzu3_8x3_z2ZPTjz__0oqNQzbzWjzOl8ujva_vn737vW8-2JydnZzvXTl4-OT8e-98-_1ffbS6uoeBkB21AtC1V27tLjfvffebp_e-HoeOzTmFUrRW4xDGvlvurYahi230UUkQHUMb3NWQqqpqhVpTYmYBoPXVYyvFGSWG5XplZt_64R-dPDr95ne---pr37n_8KuQGhEpbrli286Xx98KzchJ5vtH3cUuLpfozsJQK4AySbU6TTrMKjNx5FqqOeY-m_pE9gXAbug4xWEoL_3BN4a-R8Gh6w9Wc1QYx365WLSLxeXlhZW82ltxkr7vSqmMeHJ-9qNv_Mndrz9-9PhZNV_t7VvJy_VM1Te7jgj2r1y5OD1r5zMSLmPlmTy5__Xe3mFcxIuzU2EJTGPfEUO3G5Z7B4Rw9do1Fun6QQIvFvOqujnZNrP29Osvr926vr3cTLvrRuLQ9_PZ8uHdR6ujg1oLE_abjRvHGImwaWebri9dzbWOueaLk7q9iMFrsau3bhmTo2vOiCBMrkaIw3QtACKC6mpu7i7CiJJrjsyTqUNVJ6qXg09yQ3c3cwP35_U_M6tgToRGtRadjH5q5gBEom7CBABVDcCFJqsXVjWaYKA-jc9hstQzM0fZv371YH-2gPC__W_-UZyv_-1_-uv_8d_85YOvT7AJXa9xufzBH77-8Yd3hm5bQR0xj1maZvKKimMdsjDXqk2bcq3MrKUCAjLVYiFFtefVZx0V0c1VWEQIWOKsIRYY6_e-_dbNK4f_07_8dxTCULVWMLOxn1QJGRDd1N3AzH2KBwcwc6tuHtqkpbjb1JZ0N2YGcDOXFBDJtDAyMgMgEBDiZK4100m-VGsNTXJE0zLNdJmljCNJIJ6MYI7gyESI7WIBpQ6b7Tjmb_zoB1_e-WjMxlFckYURzLVY1amrG2IchxxS1Krz-SIKS-S_-2d_erha_eaDj5-cXhphf9nHGC1XluimWhUJypjx-SRnAgvCtL5AxDhLXdfF2BjAVD-USHv7e7uLi9svXg2xufPF3SaFrsvjWI7WK606dMNivkgieahtkxDc3MeiaiYkIQbTikim4G7tLI2jFs8iVA3Ndcx1GIYUuIx10cwudzsDM4diGhv2OvGcQYQiEzIum1S0omAFH8FvhfkIwEBqaOpZtRFmplbEjCJ4KcXNNmdb4mAA6739y76TGPcPZyMbgJeqoQkGxO5NEz59dI4sm7GoeQohEZnV881OEdQ8hlQqDDnPmmiECNiXumhiLnk-b548u6yKIYqOZdbG3aZPcTmbNdvTi8Mr6812tzvdLObL6tDO08lXj-apcavuXksFZlCzcXzOVSzKQZAIwNAcnbhJpWRAnh_si0RpZv3lrpk3cRZLzlbGgM7p5lv2vBfiMF05AZ8LAs2R2VVRRIsKi4K6GjgiQAyp1mLFKAiySGwkEBKIiKpJlDCFM6KUMSN4Udtfrcc8xhACAxqBeV_KYt7stnU2D45UUUk4qyEhuM1i6LvctnG5nLUsx0fLQBijMFJgFGJU48BuVZhSjFHIzdsUCVxrSU1kFldtUgyMbRNzMWbyyegn0wERHRjA2yYwUXg-5qeUJkc3TtYIB49BhDBMwkGEEFiEA-FqNs-lBAlBuIzZTAORASxX88S0aGJg0VyQkJgCMzhN9RdVy-NITCKhjgUBrt9cnV8M69W8H3MIITaRHXK1rhuQeLfdqpqEUEqp6qZuahOQmURCCoQIbrVotRJiLKXIhLViQrfpA0CFtJxNMgFwmDRPm4vzw6MrecgOMHmlJaUx19gEnAhwKDFFBH_n9RevXDv6n__Dz378w-_94tcfq7uZ9l2fJFEMpupFRaI5MBNN32pEcK9FnQEZAwdzRYAYGJ0m8r6rtbOZuwNgbAQQGYkIQgxalZkkBiRuZslNQ6QgYmpMAgAoNJTqCLtR33r31oOvHk1p1NgmV2MHiezuRJ5SSBIAEZiHPApiiMHcm7YldASYpoZuLsJarWmaWnRSVCKCqYpIahIgpJSAIKZWhAk9xpjHnFIExyQhhaCmEoLEuHew_sN33_mPP_35MOZCAGDLWTx9dvHS9Rc--_RBV2upZSq_EiRVddXpKaquzy1aakzoblYKM-RahEOuoyOQmZuDg7ojGrirAdAkT2cyN1MDUjc3Y8TLy-0bt28f7x_88pMvzk93H92790fvvHPl6Pqm2HYcEYzc0JSsEjg4pBDUzBQA0aelLFngMLEdNRcAM0QRnmb57o5OiGYGtRqCo5M9FxVOHWIgQSAUpqoqwkM_BpHqOuEkzb2iirO7l2rmiEJImEJwU1Dwmo9euP7r93_-5kuv9dtekpiDO3rVwLIIq3_5H_7lH33vjx4-eeAccrX1em9_fz80jdfRkLiZUWrOLrerI3nl-LAf-qePLo-ODwiNEBqkEPnidEcAw3azmjfrebp49uy112-fn50e7K--uPfItRb1MZfLapthqBglhL3lYhbCN99959GTBxMz9_zs_KXrN9Ft0aSSC4a47eqziz626cbRwdANXr2Zpft3HwZKnguCivC47Q4P9hR8t9ucbzZo9Xh_b39_WUrZ7rprBy-s23h8dbG_3xbtHz7b3DvbfeO71-sIo5EiPDw7UStXDvcJPSrc_er-0ydP33j79WfnF3c_-7LUUscMCNOLe328HPrNpx988NnvPn3__TsPHj_-_KPPnz56cvPmjZvXrz9-8ujBV3djjMNY1lcPH9x7cnS4evbw4bxNJY9jcQV08JACGHSbbr1_MO76cSwhNnksoZFSrGph4OFik-aNu1mxalpyRubZau2AT89O9q9cXe3v7TbnPIPL_vH56Sk1MedS8lDLYFjH_nEuQ6m1lorCE-G6jNlNAclMSQQQmChIMLPndlUgYkYEEuYg5t7Ol8OQq5or3Pn4y8UyxZj291eW6-VmmxbNUGqT4m7Xu8H2cnt0dKAF-m4nAT-_92kKUWslxHsPHq4W8zxqbFvTPA6DaUkhWc7zJmktY9dvTs6a-Wx3sVtdOXx872sGPnrx6mI263Y7EkaK3fb8heu3m3k6ffq47LaroxdK1XnDErBmb_aXi7153nSL9SI1qe-3ErnPQ2iiNCF3Obaplmzu-8dHY7epNbd7e5uzp-xeNlumShivv_l6HnOudd3Ma6kVTNETpazmgNVsClkCTllNRZjgPBUZxzymlKaxLiIwkrtNULCcMwsTGpNMyZ4Jc08i0zxdAldzNw9RajFEKlqJxBwny4oDRBEEZ_QQAjgScUpBMEiM6_3VDOP_5h__nZdeu_l_-e__ya8-urPb9UMpHNGd9473E-YvPrm_2eyceczVwQgIBEqfcVpVTB-GsK9mqNNykZlrVRRBRgPXohKZOCA7Ta5RIU-pmbWrefvqrSvXjg__6he_GRXOLkerBgAAarUQEyBOdecJUKtqxORmhKTVWIKZETgiCIu5AyAjTiZh4oCICICEHIJgUM2TA9h84nqzmQETTCMeVZEA6IhTkCmAGxIiopmxpBSD15zH3WL_4MUXjj_-7R0Os9CIZhWiEELNOq0mtFoQQaIgkVliGwPzaPaP_uLPKOuvP_j4YtcroI5FeNr6soG5gyGAK7OoVYniBlpqDEIO1TQ1swmtGlMDqCEECUxMR8f7168cCeD5-ZkRd8OwnM_GnAUEzGNgrzpvQ4zi7mpQzKajIwsDkgQ2NTUrauba9eNQyq4fidjQVS1JBHcMAOBWbeq_aVERjgLTPZYZxlxcNAgRkRk5wgYrM2AIghQgcKAAYOqE8ql_tkfr9XKuVvfWS3cy4vO-b680MeGuK92onCil0F-MvduNK2uvGhI7ApAMVdsgquruTYq77MAYmGsxJ3rW7SrhmGstxiyl1AKAiH2uREQIYz9C4HY1bwIfzRfPvj6Ny7R5esaA41jbg7Y_uwwoZo4xIBEhoCqpA8IE8QsxVHMkmEaaaiW0iTggwdCPy-NDEgqz1G37cdelyGzG4eabWgwAJUYEoOeiOyahaV7uhmBOIrUWdxcJ4L7cW5tVRwiBkYglHO7tOwALTzD1-XxGzKDOUXIupVQ1mND1E_FdmEKImz472qKVUuowFjXMrsKk6kK8Wra5VEKcJTlczVBrw8LC7jr0hRiiCCIQQdsmNfNqJOJea6lEFGKoWRlx8iMAQp-zkKg5M5mZE5lDrZUAmCmKTBGFEELJZarzhyAEiIizNjAzogsTIoAZOrTNtF8SQkQEic-BpykFcmuZF_NZiOLgwjhNu8HA0REhCLPg0FeJbGpNEnPqdkVEHCC1Ygro9uTpSUpJmuSmJycXQCAh1FoBjBiIqFR1R0EOIZpWYiJGmxgdBtNXBQnPHYRMjmZq4IS_bwlzSEPXNYvGFGKMVSshcxMIwR04BiYQBmE-3l8_Pj29ODlf7e2tl8u797_WWp25HwuKiFDJBQE4MNHEsoUgNO2XAYmYWmkcHRCs1CBBohAjiJhbEJ7eJ4FlsZzVakQwWy3NjImYZX1llUdLUcaxcIrADAAcUGT6H4Arh0dPHp0gKBJpqQAQoqAjoAMIIgB4TA2Sg7swzlLMo6rXZj5z0zRLiKCqsxRDjCExE5hpnOKbQSRQjBEJ1WsKsVpFoBh5MZ8DgjCFFDngoo3FLLXNUPOLN29fXp58_fVpdTR3KxndxyG_8dqt-08vch1LzgiOgKVWBCAkM2VAAwByNwQ3UHOAEKWU6jQxNqDUKQBD7oZINmm8kLU4ursjIrkrIBACE0A11PzyS7evXDn45YeftbNwubm4c_dRRX7x6uEP33vrvduvbPrd5eVF7YfqhgYxpRQTCWt9jnNlkgDogDlnEUQCM2cWYDJ3ZkLw53tjdESfaFTuU41Bo4RSa5IIAJFlKgsBGCAbOrhPIFFmJocUp6e7IXg1YyYzR-DIsD46_sXP__rll17cdTsn7schVwM0dtmcP7l-_cbYbYbRLjcbJnnx9Vc2Y1bXpmkqYEVTd8r63qs306x9-vjspTdf3HU7chRyRrI8eC2reUK0eSM151dv3wAtYz-08_bs6QmjlOLUzLqunJ9tDvdXUOtytmhC_OnPfvX9b33z9OzyyZMn-_urfrcDAmpSUfv5rz7thvyNb70zj8svvvg0hDAO-cuPv27bmISs6Ctvv_7ud968PD1PLCEFqrZYzFJKpThLmKVY2a3axfl2HLXX9KPvv1c3l6cn48tvvlLzuM3VxM8eP9vfXx_szZoYiOSLew_H3TBYefDFl1mzF2cm4XDt26-Uy9PN6TmQJQl5c3l4sHewWGwud6--fOOnv_7la7ffOt2cvf7SS79-_-NrN270XbHa527X7XKgppRaS52QDsiUUhy73f7BXt9nAHRECsFKjfNWu93yaD8PAyCKRAzoCHsH6z7XKLOi_off_cPzs3Ov5b033_7it584GBLaWHM_REZCbJfzWTujlAh4ff1Kf3pmVq0WN0VwEiYEIHLBaV0GNE2dazVAkrRcpNnyyo3rmCQQr_bXl5fnR4t2t9uFEOIs5FKV9MHpWZB0sdnN2na76wOHMpQ3vv8q9Hjy9CREtlpT04xdx0h56Obz-bOT89euX3Ok3bZjxq4fzQzcSUjNz548aRczB3DQWrXfDLVqTFG15LHnEC8unoYQZvP108cPyzguD-Yphb7mWnSx2qvDtqo7-fJgsd0OGHCXcwgzVUVGRp-tFt12WOytah6fPXgWkljR2u2w9uw2jPnGG697NgjT3Z3M3QhqqUSoXicUA_Nzk4m6IaO7q5uDB06GFgjUYZoxMMl0B0BkM7OqJAKO7hpDUtMJ32cO5m7FJAiosZChB-FJdFVUiYmCE1IQNgQBqgghhjSfcUztPKyS_L2f_OCH33jz__R__r__5s7no_vY626bSz92w_j22689PTs9OTlVrSjuWsFRq80XS6t5Ut-Ao5nGGBHRVImoFEtxrp7BjFicgBzdHJlQxNVAC8dYHY9fuXXzxuqlw72rBwce5eO7D4ehOHgpJWdlQVdDmER1xd20mqToVhEnxzCB-3N6BqI7SIhaK4uYGwJKjKYVfMIHUYituwJMpguuqsxkVXEKlCJBVUJ-bhtjmkB55gYETMyhQdDdZqe1vv7mm198_pkZgNqk7iKiqqqutWqIDIAsZFPhOyYAn7ftWMb_5h_-nX6z-6u__vCiz3ksRFRLMaBcchPD0A0SyKqa1hCD1hoDEzM4CYuaSpSY2lIGIg7CRTVKbGdpuVoM_eBAu93w5Mmzq1evprY9PT1brJZNYFfTMi5mzUTCGcZS3BC55IJADhN2CFS1Vi-lQOAxF3MYxsJERBgimXrRGoQ4hqLK5NX12t7SnutFUBjaFKoqOTJJrxkQnkM_hMlBKGSrIfBYK6Hv-REYGjo4jGPeaYUUdqXIPHSXgwFQ4ibFRQjIyEDbkudzicVOzi89iqELE1MotXRFO51exQgExayaU5Auq6qNY26b1HWDE5hpyXVv3Q69qikANUQzoNwNR8fHl-cXiMoSnCUPHZm5uzJJiK6aQmQ1INKuR3BAQBHQ8vwnh6mO5cr33tRd3Zz3N954dXt2OfY9moFa3e6iIDcvfYMk2FRhd3czUAA3LQZEwmylSiAtNbRNCAkBTdVNm9l8GIvEFCQQoLPPmnnXDxM0ygukGIjJVJ1c0G0swDBrIoqUqk2MalahnPY5YMyj5qIcZBwLKMbADEDuBwfttf112Y0H-00CJKZZm1gkCQZmQUICq7Wd_V4YhhhIRLjWSdIBhBBFhIlZmAUBVa1NQR0cQNUQIDARU5z-EBGhB2EwkPB8j8FEjDiZAZoUJ_XPrE3u2sQUhYUIJ1FAkFxyYmlTiCRNikziAEQ4XUucHN2FCYFqtbGqMIbATFxHFZZaamSezxoi2pzv3IEiP316Ug2lCf1urKUaQogRJy5jsZgiEZSctfp8tcxjJkJAFKLAbDjxXRHQhblqZWBVJUYGcgeWyfoN4J5SAkCbTLxEyBRj0w9D2zTDML7x9ssfvH-HhH_21x_8V3_x5-__8je7fhyqDUNFJnCfNalMFLaA4OBmSMyIjJiaJuecYiQhYAwiprVpmonpyUTMLIHni3kudbGau3sTY1VlkSZFQpRZAoRAaAilepd1NpPne1Siw_2984ttFAJ3IEhBimrbJBAkDKvV0twATJgiUq01SgCD2KQYIhAQch3LbB6j8BT6ZKLD48PdZdfOU2oSEiHjYpkAUXOR50gjBoSmbZHIAQkJ3NvZHLEyh8PDoxcO93975wsFgnX0UgOBiMznzfH1o8vtMOaSh4wIlrNNsS3hooUQ1FVVkYAAzIGYEBAcrFQAb7lVAC1l8tu7mvtzix-CMvNEaSQkAEQwy4VJCKFofe_dt373-f086OHhHtSay_Dw4cP3P7xzlvPV6we3X7712muvv_HKy1euHl89Pvz8ky-1TmFQJEJXRXBkAHNyMPcQo7mZm5bnG7MQg5q5Q9MkmxrMDkQUkAPRJIKLMdRSENHUap264o5IiCBAeazEjDh5x7UWY2T_PYxrLMoAi_XeZ59-8sK1m93YG-BlHoQ4xjTmYRZglpb92D97-HQY7W_84Juff_Uopbicr1W1mqsV0P5vf-fdz794eN51x1ePNmebWZK9xSJFChzs-ed0NF_N2r3V-pNPvjrdXsyb5dhvr109Lr3FNt2792To8-3bN0_PTt96-aX3f_ubo-P1xfnF6cXp8ZUrDDafNZtuoMAPnjy73A7chFdefOHr-_dSCEM3VKhffvJotooxhVwVUhjPL2OS3dD1_aDk0xQgNa3EeLHZpaZB08cn50Lx0W731RcPNifnz04ur17fs1xvrGfSpl_89YcvvnB07fg453Lj-tWPPvv48YOndZuhFFeVppkfLfvLS-_yjVeuB26uXL3xzW9_-4c__tEf_-S7n925f-XGC4vjmaqOmrfj8OobL335xcPjF_Y_-fAz0-xFGcXVci4hRBaKTQQ3HUctzoGsuiK4o8RQa_Fq7CjC7azZnG2q1tlqtduMb33nD7745NP5YlZLfu211x7c__Ib775zcXpyeXGx2-4O9o_HboMARBxic3zjhd3FZSkqIuP55ebJU1dNszSlWJg5NAnRkUVzJQzgVqtxmF3_9rtYRhYsNXf9Btwp4I0XX4xNato1eL1y8_qT-_dzLcuj_ciipSz29oAQiy3mbUhhe9oB6ND3qgUQd_1wcGW_dN04jtvNNjCfnF-wiAiPw8jBoFpRna_2x6HL_VCGIvNZ2RUHmHpEpWgIDRERkRattRJ6aJqTJ0_39taLvfVuGJAdDF567aUmhc1Fn0uVFI1oe7FdzGdjn1m4aq21zFbrs2dPKTZgWoYuSGAC3V6C564bXv3O97QaMLK71coMWtQdY4g-GQAICT2mBO7u7hXcQURiCKqqNsEzyMwlBmJ2B1dtY3x-0iBxUK8-gT4REVBDjFqVEFlEqxkgAruTKyATIAI6cXTVEAISJYlNM6O2FYlvffNVGsZ_-OM_-JPvffu__yf_-oMv7u3GvioUtVozmA3F_-bf-ta__hc_ra5mWIY82dwVQIQZyc0BQYtKIHUgJFOzUonIYPpUAdQcDBBZJKtOblqOjA6msDef3zie_8m331s1KbXtv_jP7-eqtZqZ1apIRgDmjjJ9MffpAag2TWuIyM0Rp-ELOFBIkYgdEMCReOL3T1cFNSeeOAc6PfpKqcIMCI7ALKZFJslwiK4GCAYQm1nOU-QylpoBsJRxtVou1osH9-6ndg5mk-JNggCja_X_n3oMgGMoQ6EQEH0-my2a-Gd__L37Xz6989XdXaljP2IpFLg6EnNkRrUgBIAlVwo8a-fdRdfO0ljGohUITVXCsta-aWaqVUJo23YYh-Pj_b31arfrzy7PDw_2a83nZ5fMfP_rh-0sLedhb76IQUpVU-tyKVWJMJcyBVyJcHO-m5At277nwBQEHMdxFOGmjejICMMwhihMgESRSc0BPXBA8Om0hoiMWKyKkLsLoakxsqo5gGolJjUVIeLgULNrHvJ8taiEjtKPI6oPmxGFIEQMULUYQpqFWQy77QAAAFYGfeI1cXBDJkCdtLmy7cZSbdZGIhzHuiu5KznXerntDtcLrRCZ0d3cx6yApGZgupynhH7l8Phye7l3tLe92AC4zIP2xUuttVAbHNH6GkRM1QGtTN40apYr7TtAMHfQkuYzM47zmVdLTVKtOuhsFmwcPedxt-Vw451pemdgQGi5MjizqCMLuVVEBnNHSKFhYSKyWhwghFbdZ4u5ArAICZdaOYQQmQBDFHctpRqgDpmBkUENxn5sZgs1RYc85lwcrACBuzoDgMfA7qZaAyEJ3riyP-zGF68fJuHFMqBPyTYQZiEUwRRYhGuujOAGgViYzKafIQaAad_ESA4IgFoNyIVRkMxxLJWZCSGmyAhByE1F2AFVlRAIIU2KL8L4e_lfEGYkAEsiIXIplQBqLczi4IHIDQP6cta2MU7ky2lPqma1lMkt6-5AzJG0VoTnzHUDc7dxyEgYU9hu-4Pj9XzVPHp0UUoGQTVr2qaOJaDMlvPucjMJa7uuY5HJvwgI5urViJiFAWgiFVg1IECndrHKQ88sJOJmkhotBu4SgrkSsYSQS2GRWgqlFAIx82KeXj5a3398NnR1nsLBtaPrB0d3vrrPIaYk1XTsNKZISIBQi8Yo5gjgEmTaJVGYur5YSk1NCjFMVRpET6mZvu0xCglpqU0T3Z1iMLMYOKWQh9qmxrUGxnY-I_SYBBHJrZq--tJLxjQOfS6KhIAQQ1TVGAM4Tk9xcIshMQETBEmzedPnsWmjgzGxCAXhMo6xiUTkBikGiez-vBTlDiEEBCqqtdTpNzY2DQK2zYwCoQMRd0PHDhX8hSvHH3_8Walu6pRHB2BGdju4epRSKuAB8eRsQ27P9XlgiFBzIebfQ-UAwQmRiMX0uT-NsGpBUCAoVTnwJAIxdwcjDlPcy7NOyGUSIoCA6O4PTp_8jT_-4Scff7G52Fw8O7u47K-_-MLF2dm22w19_-zk9Kuvn3x679766HC-XCwPl7tNj4STEsHUwNyRTQEQRIIbAJKhW7VZk6pWDlEY_fegPJwW5tO8CsHdEHEqLxBhyROpys3UJ_aRGjiysIIJ0tRtkSAGXuqo1QDRjchQgoTV8t6Xn928fWvcdUhS6pBiCoi_--jDN19988mzZ9t-aGezoxeONue7d9973dQ2mw2Sbfrdt29fubG3-uLrB88ud66mqo3Q4Xqlpl5UXQPRbJbuP_z1m7dfn0n64JPPP7v78OVbL0TG2PCwLdLM7nz61WIxW61nF2cXZPDBnc--_813T88v0S2mcHS49-zZs_2Do_PN5Z3P7u0d7V09XDZNuP_l_ReuHV1sdk-ePKujQcAQIhii2t5y7g57h2smWLWhCWE-DxLjRTeM2e5uTi4fXvaGy9hst0N3uXn55Zsv3b529_MvjlcLmrXNov23_-xnWYdvvf3mo9Pz2zdvvPHmO3cePby6XLz0-u0nT06HcfRawWzMY9eVg-tXX__Ot4PZbLHIqq-_-fKLL73QXeQbt185Wh-Ow-7Zk2fn5xcH1649ffhk1kRmKapOpHVEkHb_KO92TRIiXK5Xh3vL7XYER0kRGIUDaGa282dnewd7s_Vy6Eq72B-Hfnu--eP_4h_c-dUvVuslFkN2IH_69HEZq4K1bXr8-OnolVJDMW0ud2MukpK0DZJ5KRwDCU_kBjVL8zZXjdLceuety6ePAeX6N95aLBanDx_sNt3ldvfqm2-_8c33brz40tG1GyBxu7l8_Ohrd9-cnaJafzmePT5NcTb0_W43mKqOlcHGbMergyaEGJvLi62E2O167ctYRiJU9ybF7W5Ti5H7fL7UWpjZwXUczJwDjmPWYRSZ1VLrOHATKYWitd1b5VJDDMv5YrfrDq5eHUvZnF8w8t7xurvoicP2cishzJZz5pCHEpgffvXAAYmxeh3HXHOdL_e73aW7Wh2nvD5xyJszdK3VX_3Ge1oqJSZDrMUNatVp2D9PS0VFcCEGhxjTdJYlIWRS9xWvs_dohsQ4tTLNJ15eLYoEjmhuqkaBrRYELKo0KYPBaDK6oE9YQ2J0AnJHZmJmImJKJO6QiY9uHL781htXbx4sGf7sm2__-d_4_kdfPfw3P_vgYhjHoThL7ofAgMxG9MbLtz7-5HMAYomIXnLFIKaG5kIMyLlO_StEJEAvpTghIVg1BwDHEIJqLVlDCk7TLf85dH61P19gvRrkxz_8zkzi6Pbv_vMvN5teq6G7ViulJ0B0clVisVyQSCQCAAlZrsQTJ9xJxLQCEBJOK31zJyRinkKbIUYDB3fioLUiTdZ7sDI9_P__PO3pujgF7mudbM1Wa0ViiWyadxeb199-96uvviRHIKjjlHpCAGBicvJqk51ZYqQgWnVKYcyW7Us3D3_0rW_ef3Ly8ad3N7tsWieDZVELzczLgKDmHjkpGAFrHdu2Hfs-NC0gAKDVGpto5ojOgR3gcG-_1Hp05aDr-34YXrh6HIKMOe_t7T16-uTm9esN86JNe_O5Vqtmana-7VCkG_N81lZ97rM3x4ntUVQdiJmRn39fUiN1KEgwm7fmCo6lVgkBzJsYp2tWlMjEzDxRCHc1l1qH57dgiE0wMAmckrDEaX8D1dum4cj9dgiRc8211jLWXZ-Ls5JRI-CAAKoWA2bV07F_fLY7Plzd73o2NzNGCuBj0ZTCqJbNH5_vVrNUDFHAigECqedii8C5FiLMubKwmZdsDla7gQVVa80GoFltHEc1qLlqHpBJnSGCj0UYzbyUQg512CEFikwAteiErDQEp7A8vFL7fHDzes3FVAG8P9uEiF4rh9vvOcFUytdhFEB6XggAdOcUfGIxMFupKFFVgVlicneOwZFq0aZtqlYiAYbQJK1OBLPZzAzaGBBhGAoa5r6PUXLNKcUURESQJAR2M2TJtUxe3ii8d7A3XzQrDu--fu3G3jKQC4ErLOYJldDdq6YoSXhKzrl720RwRPBca4xChHVCIDHFGIQICXMtU8WRScAnRT05QuBJ5AFN5MBhEoUwMyNO0_PAvwcsIhEjMyEhM0UiqHU5bwzAzM2dJDBBm-Ji3gZEIWQmB6tViWDMhYgBEJGA2MGsugRBB2be7fpSDJGW64XWCgAxpgx2cdH1VftxzGMpY0bgsZvU0DDmYuiG6O7TjZ9CKCUDkIOFIFUr8rSCIPSpAuHAVKsZIEuYcDfgYFonV9ekfpPAHIKEGGKMkWrRm9evPTw_7S7HoRgm_uzzz378t378yW_vuHpxNFVwj0RuLsQhigMyETzHZAZkmKcGkKrWtm1Ua0htyflg_3jb7UKgGHnRNrVUYWmaOG8bR6jVmbgJFFhytXkTNefZalGLxjYFJAabN5Ji897NF37zyb22CRTQ3IUwSiSmGAMjlpIlCJiF8HwfVGsNjQRiM0Vgd79687D0hYgOru7lfvCiuY4hRFUVDu62Xq0YcbcbWLhUnS1nU_ZmAqJPvI08jqmVxDKM-W_--Nu__d1XTStRJnHSlH3Hf_DnP2xp9utff9qPoyQadj0hCqeJ1j3xrBkJ3HUsKOAG04wfiVW11gJEgdjM1cEcEFGYXdXdzR2ZJ4DD9N2eLB9Wi8QQMPzge9_enm_ufX2_9Fsg2110cZ42F10ey_bsnBzKMJ48Ofnk06-QZ30tfZ9zzk0MTAxoJKRkQgJgBOjuzCLMVjWGaLUy0iQoAHBTdyRwCCJAULSgY60aQjDTENJYRmKeOKfmoG4IrqClVkBUU3MoNZtZkGjg9HtcEAAKc4yz-199tX903F_uBLGqHy3X__Kf_4s_-ZO_9flXX1W3OlZz29_b07Q4Pz25uLxcr1e5Dj9576U584effdkVR5HVMs1T0tz3_W4YxlzHEHCWole5dXSUh_Gjz7-slA_Wi7blhrnf1Wzw9ZOT1Xwx9P1yPqt1PLs8raUMeRhLPjrcP99sUtte9N3d-4_vPzt_89Vb8xQvNxtB4cSS-Ff_-cMrhzfdIbUcJCJrpGa72ZSxdpvh_c8enJyeP91ucj88uDi_ON9ggePDxbWj_eMr6-Ws4Qbns9YDfn362a1rr1igpml-d-fOj779brNsZyEeXjtmaXYXo6nfe_Cw9vXi_JwRQkAm4UYW8-Xm7Oyv_vq3h1f2X7z9Alb9_NPPxpyt5Pd_8_7bL73l4L_8q1-88tbrj75-2DIfX716uduZm-YCAIgKWgV9HMcf_eRP7j96trk8RycgNLRaKgM2sf27__gffvCLX4YUFotZ0TpdJ2G722wvEHS32b76xpunZ0_d8OL8YjFfd_3oThLnYTHfbrrZahZjzEMJKQybnRVdrpbjMNZSQ0rgrqqpWSxffOPTv_xPi72Dt__xf_n4g1-fXnZ7B0c__sf_8JU33nz04O7R8fGDr7766MNf3_vss9xvojTlcusIq2YxXJ5rqbvLy7wbnt5_dPn0PKV2detq5DDm4ogAuL-3349dIqpZGejZ6ZkEGbo-htSmeHp2dtltWMIk1d5st6Y-DD0SoPswdiEEiaHrdrGZF9W0WDJj13dM1DSz7faybeeCvru8WC7WL924jZG7zZZTrGaAwAihSYvFYrO5PL5xbbPZoVuTZLc7m69WyLK9uEjzVIdsJfuws3EEg3f-9I-1qzi1pQnMFJnR0RCcHBlnqSlVEWjKyTA9n1sXd4oACECIIuAgTFO2h4RJ0AlEJpgvhyRT6I8CAyITAQA56XO4Dtv0GkAidI6SAnEMEhMftX_2p3_25__gu3_0ziuL_b2SFv-7v_-jH7792od3n_2P__o_dlQ7nWyn4FZJSAmPrhyr6aMHzwCx5DJdBUvJs_nCqhGjVp24RW7m6oYABIaObiKsaizUxMZViYCZ3YwYm5hcSxQ6XLdXrxz8rR995-1XXnKiD7_47Ke_-t3Fpld3K0rECEAATALgPm0ADNQVmQnoeRTN4fcgf8eJyuKOLA6GDhymA5WlkMxNzSUltzppT2s1JnStxBhSW_MwxTKIADEAKRoQo9UcmlktJQqZjXG2mM_T2cmZcODA7sYgACAhqKrbc5JPzTXFpKoSZMpoMtO733z73Tde_uzuk68fPRtKrqpkbuZDdURgctVa1RS81hxiyGNFNJJoE73bkZlqre18Puw6YalVgZ0QU5CuGw73Vk-fnTBT0yQSSCGM_eZgvdpfLdaLmVYr1TBwVhuKbocRiBAhiJjBkIuhA3pRNfOuH3LRpk1uvr-fSgbTyoEFOQQWJnQITIRo5tVtCmIBQmIujqoagjARMpaixFTUUgyGMI6VgUatxNSNYxNCFDbzrsuDalq0g7oHMsQQw9BlrS6B-rFGiVdjc9zONlqXbbzcZQM8mEdgAqSzrsuO1cxMBVgRqtowZGfXIV88PWvWM3Cote7Od-OQ46IZSxnOd3XIh0f7FNCqR4Fmbz7s8ubkcn7Y9tsO1HKpIqH0nQPWyTKhQAhEkVIs44Dg5MAMQOAUFgfr3WYzdONiuew2ndWxdqNrRRFOL76HLEEaqwPDhENxRIoxAaEbSkruxhImeRMgVnVgZhEHNPMUAhKbe2zbPJamacwsSMhjDjEY6tAX5unNjVWrE4cUAGjqMrYxGjmRGBgjqevBwTKP_bW9xdG6OZov9tsYkJarxh0CcxRBMCaMgbW6gbGwuzGJupu5VjMHInAAm_LHSMyECN1QhZiYJg9fVUUHIkLwIJxEYiA0n2AOCMBEgDBLSWtNEgDAVIW5bVMQaKOs54mJDbzrMiKgiJk2TUL3WRNAVSS4VVU3r-6Qi0oITJRrdTdkBjchmka3QBACh5TykMdSJAqAN7OmG8uz07NhLF0_hhS6y13bzvs-l7E3UyZy9OVshkhjn5smsYSaiyMgMjAUNQRkJEJ288loMgUsYhJXZWZTQ4SppNnMGgVjElWNqQGoEhgRX3n91u8--KSioMTQRi9-9cqVt169fefLu-rAUTRXMyX3Ys5MMQUSBMfUpKKVkYR5MZsX1yjSzBpwS7Edx-7qlQNTCMQ559VqrbU6wtH-EgFiFK26t7ecEkmC1i7asR9jSu6WmoSurrC3t9e8cLR5doFkWgwcplOmO4QUSy6EOJvFFJNWBbdrB3uOlHNhpsVyXosi4ryRiVm6u-wP9_ZCjCGEMgwsEoSJeehHiWG1mI9lXKyWtaqEYKapbco4SmAzbZtkpgAgktbr_ZPLjburIzpWN3Mk5ntfnx4f7d27_8CcrizX3XZDhEMugOxqzNTXajrxoMHdkdFMiYNqAQQmrlXDFPNCN3NwSCQKpqZAiAqAhO7gPjUi0ZWcHAFErhxdXa7TnU--6rvR3Guvt9-8ef_LJ1Z1N47D4IDMZIx0fnK-t1ox4zCOqjpr26lsNZGG0UGrIRMCiJBWC8I4ISp84iuzI5oZIYBTLoWZ3SoHUlUiqjUDcSnFAYS4lAKOiMAhmpmpIZA5ptAAgpppLTRhBafXsHsMIa5Xdz765ParL_XbS0SZz2cffvTRH3zz2198dbe6llFjCiG1HGPe7RqOq_W85stvv3I9Nekvf_mbxWqFLLNZ04RgJRPhkHsJMmubNjCqHh7ugfnvPv10LEqcFm1YNqkb6ycPH1fNjFLd1qvFb37z4Xq-XO6tCP3qlWNChhil4cePTi-77sbh-ujw0E3RwRCIPQ_-9Z2Hr__ojQL9Yr138uSZhKA0zpq2It68eviDN29d3V-nUo_X62Vo3nzpyowZ0Num3ebOat2M49XDPQjxysHNvho4j6DPHj-78-nnf_XT9__tf_zZ_-ef_pt_86_-7e9-_eF6b3H29PzRvUfNvGGA2KRSdb6cPXvydDt077x2-8G9r4-PD2pVienRo8er2eLDDz4hqd9875s__fnP33nvzbLdXjncv3L91qP792utdRyfs2LyCOalH3_yp39-cvb45PFZqeausW0cYcYhNs17r7z-2eefjV3fzBbL9eHTx89S05rnwHh5vpktlp_-7tO33n1vd7E7OjpsZ8vT0_Ox5uNr1w5uXDl9fBaE1CyISOTxfAvmKc1MB6tKxO1yWcfKs7Z_9rjdW7dtuvur38z2VofXrt5-672nX3z65a9_1Z-ePXz4oDu90H6MksDUcvn23_6Trz_-fOg79BJiOrs4Lf1u3G6DlKG7uH__cWli3-8oyoxD7fqmiYAQojx7-mw5mw_9LsVIyJtuy0xjzinEbdchcdd3KUaz2nXD9JYBMAxBSwZCCVHV3nv7rRB4LOMszSRENA2z-cX5NpcylmHoxwqqWoNMqeu43XVBQim9qXvVkkctBR1qsWY2c7fd-ZaZ8q6zMUMt7nr99ssS26IaI2OgPExv_KlN6mAUJDATqIJ5LS5IyBwkmjoACJEDI2DbzlwdiZ6rap0mkA4zMz8_3wOgFguhdbdp8oxE6DDJBBGBkCGRmr_43lt__o_-9jfefe_q8ZXN6emv3__k0zt3t49PXl7NX94_PBm6_-e_-E-PLy7Pu2KGw24s4-gGpkUBjw4Pnz49LV1HQpoLuqM5IgOgmzpAeQ4qpUlSLCzE5O5qCg4kAQiRHIlqrWCVJZhXYWL2IPT9H3z7b_zomy9cvbI3W17m_E__00-_-urJ5W6clFtoZjWjowM4ghVjRnN1IgAihEnVgoiO5A5MpKWE1Jg5TTjBEKYj6RRxJ5aqzsRuBojMASYTqyqSOIBILOPIMuF0AQisOhOqGpIQObjlsX_tzTfvfv55SC0jXV5sJUZ0dPQgUd2ExaoiAwpNXmYA5BBNDYneeuXWD771zp37Tz774sGQy1Q8yLmUWk3LVAChEAKiZkew6W8huDsIs9bCLEQcQiAiTqGU4q6LxeLwyvG46xFZ1bqua-dtN_bvvPvW7uz82tHhjWtXSinIUqoNpTrxbiiBBcAjS9f1DggAl9shtnK-G0tRdZ_PZlAMXAOHlDiGoFpjIASbymRq032JSi3EoK6TYLhqbSWQsSsJcoqhGuRSydGBhiEXtb4bnAiQd7s-xECEKFyqmlEzCySMjqpWEViCEyhYAe-rJWEzvRWlCc1WVUIYakUAIarF72-2EsJmN5RamLHPJSaIURDg6cll08yAHQP33eCO0EitqOpjqSkF3XVHB-vNrt9f718-O7nx8tH5k0vw6kJokObBC4RImhVU2RwAJAiyoCsZklUKgULcPz7Mu9EMidi9lm7wXM1qjMzN7XcB2UpBcgRwUK0VkZCERIhIa9WSEYGCIJCkFFJ0AyRSrRITJZE43TV8tmhdS0wRiVjI3aqaxOBjdkIOqWkaAmhjBMCT05PUtubVAOezMHa5TTJfRVaYBZZE11erl66uFjGwILgheCS0Ykwugk0UVTd_vlATpmkpKWE6hTz_tSGAKaJfq8Ug5uBmxFxynW6x5C5Mgcldg4gEKVUBYAoyRiKE56XhIBREQmAtJTAtZ00bEwAYADE5MRKFIETeRmlDSBIQAZEAPKSQxzqRw9yRhCc4Gv4eKWAAtdbJkqjVsmqtFcwlcN-X08utqm4vOhKuVWOgrh-QUCT0fQ-OOWcOPB33IrMxOjpNhkcD4GkzMZWTpk_KecjNfFbGLCEhubvB9IB055AAnUIEVCESYUnxG9eOv_j6GXKDjIQWE__m57_8m3_rj-7evbcbtZib1iQpBHGw8hx_JkAAjBxEGM2AeDIyWgyMwAgoQWJsEb1pYgzRtM7nbR7Kwf5awWPgJoU8jM081ZwXi9ls1syXC9XaphiTpBCvvnB1kZoHX91vmmjVRJiZlst5LiXE6GYxBRGqpbJEQmSiihpDnDB3CKRqhFOLhvKYEahC7fthb3-_lJGIJAkTOroIBxFHUtM4j9MSiQDBobrFJkoIszYC09UrR0POQ1VOkYQYtaiWam0Txs344tu3zi62u74bzUzVEYgoDwoM0yvNwAGdfJIS1AqOTOhkrtO-3k0dHCfW0pQAAnCHEMiKTXL6CZkCDuhOTCjobrvsxwfHdz67B45VzVTDrBnBN5c7ZiY2iVyLzVcLNBOR6zevhHmz3exqyfgcz0aBZVLONW1EhFmI_VjADIU1VxbWqs4gEpjYVFmev-eAacrdBoxVdYoKAPC0QGMkJq5mMCHJkAKzajFVYYyT09SQmQAdEIqpAM5mi88__t2NF26AOxN3ecjj7uJ8e3Z-BkxBpElt0YyAQdh9vHVt7_r-wbwJ__zf_-LgcD-khKgMuH12lmaRiYSkCRgR99frILQZy8PT8yjxheMrL97Y21utT8_7Z9suj9Bvyzf--M3TRxef37l37YVrAL7rdyQBRELbfvT-b88veiN_663Xvv7yq_V6vr-_1213uegnv777whtHTQhPHpyEgLvN1s0fXXRXDhrM9crhcvq_jSF8_fR0uVg8fnqKFBbz5WU3IFCT4jy2QLE6UMWf_vQ3j0-2_-qf_eXl6bkA3Lp982i5vnrl2ltvvRri7I1vvmFAztBvu3EYCL2qdsOQlvtPT7ebzfgP_ut_ePnsGTCgwdX9420_7O3tPX78KKXw-OQiBU6SXr39GtT82aefgaNN1mgR0AIMr7z3-u0Xb__yl7_t-k2gQMLLw0Ov1ep4_eDwjbfe_sUv_jrNZycnZ-v9VdW8vbhECYvlsrvYaXVHOD68Uq2k2fzp-Vk35DiftfPF6srebjcOu-1iuSqliEjebN2ranZTIpAQzCykxE3T73bzxX4_DntHLwxjfu29bz_7-t6ze3d3m3E2X-_t74W06i4v-l0PqLXy8duvnnx5v1ksmEMp41s_-OHTR0_Q1HI-f3rqQ39596vThw9P73_97MG9i7NnbWgIJHe71XrVMK2XSyQ8Oz1R1cVsJczDuJulWa1FApeSm6ZRM2IghzxmDgnR3TWElkLc9fnFG7eenZ2VquxQ3cYyrvb2Tx8_HsvoQGYwqsaYtB8n3K2E8Ojhw7Eb5uvlsN3Y2IEqmu-t1yHFzcUpCYBavuzQC0CdrfZX-wfCjOa1qhNGBp4g-ACL1XocBgLUkl0BBFECAJoXQWQi1UrMzAyuRg4GZgqMYy4iRBO90oGEnBDAowgwuGMuyiwTzUYCkiADShsDNH_vf_WPr6xXH_zVTz_6xQf3P_9ic3ruRJjWf_9vfOsn33_v_Y_v_8_vf_D5o7OTzvohE4IwdJudoROgOb_-zhtffPw5OeRcrdTIRCJE4LWWsRJJmjWmqmOesjdVNYQAiFadmbRYEjH3qQmNDsIehFMTD69d-2__0V_88M2Xf_NXP33zlTeq1v_3v_h3H37y5WCy2-y0qpuToam61skEjwhT1IgQiEhVYxKtKkHcHJkne5qDI087XHNwCalqdVNVYxGg3xNXJzUxoZsL47TsfX7jMsCJckUME2skBDOPQRxqaJpm3mzOL0garcWtMCCggyMw-SRaE7bn-2PKpc4Wi5qLOxHCW6-_8o03X_z07pNPPrs_5HEYMovshoxmTQoEU9ukErKZIgMiWjUO4o7uFlKjdXQAJExt07QpD0MtzsTzg1l3se26gVks16HkNoZWYiA8Ws0WMXRd18yafii7XHZ9ZqbLTSeBx5JDSF0_qjoLYqAh6zjtr8wRcJYiTV0KwSYGRCfwnGvVCgQxpVrLRGfKpru-r-6AXB2KGjP3qilyAUssYDDkMcWEiKkN6i6Ey9msqMWQRIAFY6JcNTVkAAZoZO5QVBEoa9mUgkRjlPPR1zPKjp89PG1S3Ixl3oaqUNGGrNttT2yg0G17RNHq4LY7v5i1gYBHdXcfxsEIFaq6D3299fILu4engWW2alYH682Qq1Js0rDpg4Tcl9XB8uLxRTsPnt21Qi1EyBKAuI6j5bFp2qHvzGF1dFRHUy1pNc8lk9vk8Vuu1swvvm05cxBC1bGyNCWPgKS1IhMg11qRJqmrc2xCE3PWENMk75gYt0iEjs28ndaIMaUgUoYBwLvNRpglMgEDOTpoUYmhmIbpIMhSqi7aZhjG-SzmrsTEy1kKaO_cuno4S-wWmJ7j4YmEueYaRJy45ppSdDNhtgoANv0KTWgzBGQRYnCzQKJqgalWjVFKqRIkmzIhEk1KYUKMQrWouTEzEcqk_3YXJmFCokBACCnKejZr5PndvKo5kLoLs5kS-N58HkhgivYjmkOtmkuVKLlXJHQiB69Wxj7nqlrNDICQiIt5HmtoQrOYaa0Avt2Nm822AOTqan7-7JRjU8ZacgmLBEi1FEdkwgn-YggArqpMrCUTYi6FWfA5FBttIpe5IziFkMc-pdbMhZklAJHXMc1mQ9c3TQOqVfVg_-Dh9rIMxVzR0Kui2iLwleO9a1ePP7v3gCWgo1VjJAUFopBECCfpIwcx1cjCQnuLmRlQoBhDSgnAmxhiEDOdzxogRPf5ao6IgTkFmRomV64fRSJGjDGCGhLsLWcIFGNomhYNh3GsWnPOsY0EZA5IMOkForAwS5QJThqCBJEy5sV6UUtuZzMza1KQFPKYmXn_aA3gTTMrPszmc6u6XM6GfkgxxiBMggJarQ2zMmZyjIFZmIRoIrJGQoBbV6_G1XK725Zcqtay243FYtOAGhPdvf_gre-8fu-Lh8IOiFZ8NtuvMJoaElqpggDu4NhKql5rqTi5tQAcnRBqrSKitRj8frDjk4PGJ8u9qSPqJI9kIQaMsal5HNW__b1v_Pa3dwDIyFSBLVSouWgMUYS9GqIgIAXud7tnTy-uXT2-fuVYLffdOL0AnjfVJFS1GJvJbu6IuRoLMoFIyGMlYiIXCarKBDBdQBG8qpbKQupa1cwNkapqI6loNdXJEqC1MhEBZa2Tc6NOL06wWqqIsKOjp1lbSj7fbI4OjmrfGdJf_-JnL1y9dv_-V8frA0Bc7q37vm_ns353cbCavXrjcD2Lpv7RF18ul_sisZbxcG-9ni_MbRx7QhSoUMvx3pJYhmKPHp9q9TbGb7z4wun5Vp3un57pTudtmi_infc_iRH3D5fL5awbhpSa9cHBZ598MQw2X7avvHJrOWsuLzYvv3Ird937v_pilmJ3Pvz4v_7-R391Z3-97LbbWYwN88nXD6rJ9YPV_sFiNAPH1d5ib3_Zb_v9w_04m7Hw5rLfDd1Xn9_Lyk8ene26_oNffvrpxw9e-eaVx3efXLt29ZU3X14cXHv9G-8dXj368LcP3v7GN-ar2aYbl1euPPz0MzdLkZDYnd74_o-i-NANn_zs13_wR39weX5-dnJxcHT07Oxkvpz_7pOfffb5gx__4MfbvmNiKP1vP_zN5MFwAIkptclKdoDX33pj_-D47tdf9ec7MAjzpo5jCKlp4_np-Q-__4d3Pvv4nbffWuwf3f3s82u3X9xtd0BCIc7Xy4vzy9ne_MnjJ2-9-637X3_dtrO-74ch37r50ny56HZdJMjdKDH12x3kEbwSTvdDEAkAWHIJ81mMcbe9WK73-9wdHR_devn6vQ9_l5hvv_TC3_tf_4Of_au_7Dfnpg4Mi_3l5sKuvnTj4vGz4uXk0WMd-_tf3d87PPjGn_5k6HeY0uVm4MCHV6_uzs_OTk-6bvf06aN79-6CoFX7-JNPXjg8qmNer9br5dLKOOaRhLa7XS61bWeb7dbdy5jHcZQgecx57A6vXuu2GydzI2K2mnc5n5w-i7EhR-JgZZzNFydPH0sUkOmEiqqVmSjKbteledOdna_398rQax0IsZayWCyqKYJdPjtt2lT7rgw9EZ_nfPvlN9wqASBAIAZ3JHIHFCEkQANXA3Q3dWOW6u5myIgMIJxzJcRqhuAhBkL6fbwQhRkRnRABpzmaED0_DyCST70lBHAW4hQWaf0X_-3_8t__k39279M7w6ZDhOXBkiWIyH_9d_7G99575f_1b_7zr-7cfbLrB8duV1QVvPa7XquamcSgWV965fbXn3zproiI4AgQJJRafYJc8AR7lKrFVAOT60QmJqvKQogOYADoqAxTSKc2It__Oz_aR_rgF-__-qNP_uIv_uK1t1767JP7v_jgt4-fTfWTPM0K3X0cTwiCI9rkMjdFxygLJ3e1EIJVFQkTwZOICMgBgJCRzF2LkQTk51KUEKK5uU1_0RRcJE0TQgAIsTEzQnQ3FkER1Upmv8cKESPstttbr77-6Ot7EqLEmMfspmGqbRAi8XMel6vQlABAM5q2_yElc_3eH7zx5ks3f_fpvS_uPTZUd8TAQzcQg6mxBAQoVogBzNUqIYUYgbyqp6atpUxKh2m2s1rvbbqunSUOsj3fLJYropCHHcrz1eU8ya1rR7euHJNrTOHuw2eXfe6GuhnzOKrB5KsLCkAIgGBuF5fdrs8cgwISQBRqYmBmZuzGs1k7Z5rSaFN_PRJ4P1ar1QyaJiIQMj03UiMWVSMo6JHCZCmdXKJmKiHAhAskz7WCaRRf82zM1lXV4o5uWiNHM-hy2ZZ-W8o6NinFcVR2MIKu1L74yHXImhUtUgV6-vQyBnemSU8xDONiMevzUGsGR6CAwnnMcZ667cCMCOwIZTe89ebVX__i47dfuf34wdNXbr_49OzcStldXqqZKq2Ol6XLwmzZbCxghREUwAIAkuaKrs18UUWGkufrvcVi7oFNK6rqkIU8X5xyuP0uhMCBzE0COyqaEgKKsIgD1KpBOI81tImIh65rmsbAwQ1FGImZYztzdWFyN2bROmHvOcXYNnMrlQnzmKu6owNLVQ1NAgACXS5miMQIq-WsacPx0frJw6evvHzz-CC9fX0_GE6MdlcVZkE0tSAsIoEZkME9CEUJiDApXUUEwIOIT25Sg5yrBJ6EhIjIjASsauCYZhOmEtx1PottCmM_IpGqRQ6A3gRhwtWsMVUEDwS11hh43iRhHMahKhjBbpcnajkzzZvYIKK6mYUoxATgtXoIQkwsgsxu1ndDqaruIYZxVGQCp6ymWh1xsr123WAAsUm7oWz7sTlYX55dxDTbdXmxv8i1gjoyTjFwU20Xc9UqoSklozsRpJAMMLUtT09kgufjU3REpwlsKsGmcMKEdPRpbMEhRgBtgiDjS7dvP3j4iInBjAAINMZAzOenJ3_v7_34p3_9IZNU8xCxYZ4i2ujIjCnJBHgnoraJWiwmQUIwSE0zzftJcN4kBGiayEIv3DzwArn082YWm9C0tF6t-22XYpwefBJZix7uLxU9SoqBL84vUKiWMbYzrWqu0_lg6PtZ2xKig4nIJLtnohQmbxekmNx91rZEluaNqUsMmstiuXSw-WyutbRNGvtx3jYO2DbNJLkSYrfaNiEPRbUCQ9-Py-UMwUnVDd9-_ZVffPDR3t58tx2JPAaJKTm7OSQRLNpd9i9eO-i2HQNWLQoZJ3qPgTDZWAkBhAqoozOyq5mWmJqSKxNNeD4imuJbWl2EJ-3ntFQycI7BzQAN3MG9agWzPOp3_-i7n396t-tzHgZUzTkv9_eGrjdVCWw6oa695NIPY3V7_PjJs_PttatXjvYO1st9LYURzaoQ1jKiMBKVXNDdQEkB3aec4HTPBAAiGnMmoiBSSpmEfMwCJEFEi7KAVSNyNSOkqjpd4qcpGDDFIDC9FczUprja5MlEdZutl18_eHDtyvGm6xtLd-5-dvPo6sNnTw-vXK0VFrO5ooxlPNhbLPfiWzeuhMCX2-6TLx9wTDEI1Ly3mrnZZnNexxG0LNugdThcz7PbvQdPHj073eY-MLxy-_rFZpPNvrz37PJ0t1imo8PFg7snRWtq064bzfDo-tXN5fnFyeX5ZuRGfvzDb97_6uGtq4cm8ukn95br2d4ra8jQHoSvfvtQoiGLW91uhj_9wfeHPLDzZ18_a-eLJyfnf_nv__r-6fmXD58-Prn81S8-vXv34Wa7ubzsu86GnQJpu5gpl_X1-Wpv_fnvHt1-882zTXf9pZe4icThwd0nb771cl-G9cHewd7Vj95_31wZyRGr2re--84sxt3Y719dvPHWe8_OT1bHR-bw4q0bJ2cX7771nTt3fn262R1fO3711Zfn83nuhxQbc3Jymc_Gvhf0mPid73wrhvTRb3-nudZcJHJ1CG3DZP3l5h_-V__F2enTzbZb7h0UG4MEt1qtxnaeayaWWoaYGkihH4eXX3nx08-_BPU3334HMPTbrmW5eHq62F9qP-S-D8__04mYwZwYc9Y4X5SSU0xqtZS6OlgvF_OTxw9WB-trN65_8bvPut3OESYw1ovvvbHZbG--fqvkOm8W119-abPdVfX9o8P-8rTUfPL0zD3s3bzd7y6n48VitQgpbTfllZdvf_7517kfvvryi7v373796P759uJ8c37t-FpKCyBqmzTutkGSmdZSU4qlGrgRU9ftbt58e7d9Cu5aapqtaqlmeXN2lkveXJyGeQtem5S0apNa9eqqe1f2tpsNuNdaZqtFd7kxVXQo_WjuInx-fn5w9dirtkfr_nyD6gJYxqHk_O4P_sBz5SAIMAzjbN1SYCFkoiQB1IDJDUbTeUpIjAjIgAhA7IDoxoRTaYcDO1OpGqKYTgBYBwAOESdcfQjIZOYCiMLETpMqSuKVg-vf_dM__Nf_t__H0O0kpRADE3AKQ4ff_-67f_K9t_6Hf_HzDz7-_Dzny76GSDX7sOsmMEAeCiGCVSDev3Z8fnriTqbFHASAohATCY85lzKyRHdHeE4akCDIDOaTX9bU3XXiJxo5YHrjnbdeuHXjs_c_-vKrh0i-f3D4d__8R_NA_-Y__OyDDz65HLSglVIAcRgLIgJIoGBVSWji4xNitUJMxKylEE2kMpm4Z1rz9INatAJPGjSc_szkx0HmWi2wmBsSAQIjuupU_UWimgv8HgYxcUIkxjxkFkI0Yz442N9tLplSiKJVy5BTSlP2IaRkbohmAJPuDYVqVRR292Y2wzrO2_BH3_vOF189_Oze4wpWHcKiuTi5YEJVlwDg4M-3B9OZD5o2DrkYeEixTihVQnAIIeXnwWPQcdRiTgKOKfLjJ88Ojw9v3Lp5-ujrn_zxH5LWvh8vu3zWjwWwSXEo5XI7pDbMZ-FyO1xuulJ0OW_N4evH58i02fUhptVqZjkvYmxSSIEY4iK1o1ZG4iAOkLtiSLXUqXXmCETSjbm4F3RiRCQHVMMh56pQXR2dANXostsBUWxCrXWiXbiBIxS15TxOHutxrBJCN-aDw0VSqgWQ0YEWTEUdAnMKIzgJV_WuGxU9k7tbzZa1ThLqJoRul9s2YnEd83bMFDlxqGOhaoQ0dIOQIJk5HKzjg_tnt27cuOzPjw-Pquq43eaxAtJs3oy7YbjsUNBzZTQEcGDigAaWc9PO-ty36_0hl9l8zcymWPqectF-0DFrGZluvP3cTAFgqqXPE60DaTpwVEIMMcUYCNmKEVLTNu18VrK2TUvESCiMsWmYSd2s1uWinfzh7eQCC6GWyjGZ5dhEVU0hlpyXyzbGUK2WnNFhsWqvHixPnp0dHexVLXvL-WvHe4LEhF6NmWPk56xdJhYGgAm7CQYIkHNpmghMWus06J1wYG5Q3abdXFFTMzAn4SRh1aScVbOmRoRo3kZCHIoSobkzIZjP2jRLMQRuQ1zMIxPlbLNWgkjfj1MBQKdfKnACEMJZlCZENyeGkjM8lx-wq6lOCJc61oJMjliKqvnEZM6lDGO53Gy7YTTAvs8hRGLIQ6lIZ7thtx3dDJ2KahkHJp6GwVbrlGVhllonCVpCBwoMho4YYzKrgaVWnbUrByOAWirHUEoNTXQzJpbAHAOHIJG1lHYxQ_QkYoT_X5r-o9m6JDvPBJdy9733UVd-OnRERkRGRkakZiIVBIEkKABQoVhVbGNVWbW1tfW4f0MPuic1rUlbD9qMA5p1GauoigooEAQIkUCqiAwdn1ZXHrX3dve1Vg_Oh39w7j1nC1_rfZ_nK1989eMHj9xMzYIwEBo7hpBIbt56fpq6RycnMUZGQPPppBtrBaiC0cFjDMKMCK51upi6atfFJgUDF8GmS4mF3KfTCaE3MbaSqpe9aZdS6DfrGBvXvLe_iESBgVjaLpRcmZmA18t17vu2CRLjOGQHnHQtEmotpi7CIjSfzLfDiEAxMAPGxDtqXNskAmjbVgTraKbezZoy5NSkbb-po7rpYn_uqiEIABLCfN7tNLEphVpUUsCdqDjXdtKBA7gSeFW8-eLVx48vuxgJUVVFFQGr0ziO4B5iHIex6yYJiAITUC7q4AjmsJsQAbgTsjpotR0BIRcVIgmxlswiO7IE73A7hIggRLarBhO52u6MZ3XXxXUgilEM6O13vvjg7qPtMAqBFnNzNyPwsYxWNIRACECo5n2fTZWZailPz84fPTm71NMXbt66cuX44OBo_2Bvtje_WC2RnIHNPYqompohibprLe5OO0QZYq0VEcCBANVMzQGNkIRJAscQxnFE5F1MlojUd0U7QARzJaTdnoyZCB3dWETdJAgjSupOHz2uLpHlcv3YNyvVGKdtEq6uEhqGMuv4-qz9ws3rJ5erzz67s-6HotC1sY0cgyAomFnOALVtxVwPDg_OLtcPn54_PDmNMcUWb17de_DoHFL42c8-6ybN0ZXDe58-vTi_OL6ytzjYO7-4PDo8RKP3fv5x10yee_7KX_vq65uL02kMQ9GPP7k7bxOCn9y7nITuyd1Hm-Wya5t-7Nfr9f7x4QY0TJo-D5PpdNsvq1FGzIWA4zjqbNa1XeTUOtPsYPH09OR8s356Mp48WXumz-9cvP7azdfffu7mrauTrkHiRw-fXq7XL7509aOffjY5bueU7ty_1y-XJMEFvYyCfP3G84trB3cePnx0__7zt17-8NO708Ve18iD06eTdrq48SIJ_qff-9Gv_NovXZ6vWKC6nl1cZMtVraw2kVGLvvG1t8nje--9l8diakYALBQEvQaH_-p3_86f_NlfpK4dqp2vLo-Or5eax6LC8bmvvn1-5343mbDgg4cPXn751fPL1fG1YxFCiiEGG0cbRqvmgnXIZLb7bUjTAJCruSNJSovpuBkm03kMDXqdT_cOrlzZnp-98NIrgXA6nS7PL_shuzsTX7l6dVuGg8PrebNdL1fzvYPl8kKrtU3sQgrtdDeiTlOqm20MwdEnkzlRuFyWF194gWNz__69jqVf991s7-D46OTB088-_vDu7TsEoNXLUGJs-_U6pTCsN6XU1La1aD-O_XY5WxyM23UxXV2eT_f2a9-HIFBq03WnDx8zMAcsVcehPzg4OH1wGpt0eHjESGWsqnl5sR7W26s3nludn7p7M2vKWLbrPoVASLUfLNfSr1HLuNl84d13EXHQjAghiFcwM2QsucaGRShnDYFLrSKhuHJkBC9ZHd2q7S4zdMKdC1MN3LxWJjaAWkqMAo4ku1QnsrCpkyAwOWhsQj-OL7_2xhe_9tK__1_-Y9d23HVtNym1MhqSXDk6-nt_49sf333ye3_4YxPIg9ZqJSsaFs21ZKsOBqltLReKgsCb1QrBSy1IFIhqLl3Xllw5NbVUdifEnDMSAXgt2k2nOY_gxgK-G7dHrKaHR1fe-dbbH__sFyf3H5VqzmG6P1ssZr_57a9p0Z-899FZrk-Wm6I2jllLBeYyDuyGbiJYBoVd0wDcDQzRzWLb1nEgIgfgkMCdAME9paYUjSFYLog73jXXUpCeIYPADXeZKvMgwd1UCyBRkGcLGQAktlrBQeLuCOxmZf_wcHl5qVUJxcwVtJQSmga0ajWJu0yXS4gIgIhgzswsbNU5EKk-Pb_4u3_r109PTt___P6mH3NxYtJxEMGiCojM7GA76_BOBU0kKJKHvJMXaKnugEjdpCOkcRi7riPA0KRxHJlZtRLBdN7VUo8W7avXrgzjSCH8H3_0p9xMz9bDdjMI86SNuZTltmxLIUA3mKXYj6Vt288fPWFhdW8j116vHM6ZiRhzHUXYwcGsVnPzpmkMvaq2MRg-eyQV9KHqCBhSUwCqeWRG5BjIkcysCbECUKB1HtF24yqu4G7YNM20Defn2_m0rWhDX7eu2dCKt21g96FaNbPEWfHeyXnbtsOYzV0CllwihzLkdtJUU0RANQAj5GEo7UTGrB3jdqjtZKJWQ4xMVMaeW9FRya3W8uT-JZE9OT958ebzDnXRdnnYnJxdEgRCDpGGTW5nqax6YmclSg2lgMgCJoEAKTTN_pXj5enq6PrxoONwsSWtOlRDoBhIIlOUOhQ3d1W0ArbLQ1d3I8ImTUrOuNspBXbAvh9KVUbqh77WYooKBAwQQUsmglorKAxD5hDVKogp-nK5FAmlz-Y74DcySlUloHHMSAhmIYSrR4e1lkYwBRqL7gDDIoIAbuAAxChCVhTdd638GESrpRjMnIFE2Kq6WkqRkYkwCgNCrZXJx7EAoTm6-1BViJBJs02bBp3KWGNkFm5ScNMmiRC6WuAQowhTFDk6mIhIyZpLTSGmEITZa2UmJmiTNJGJoKq6GSEgQVHNtXqgYtr3_bbvV30eSjVAFK7qamBuCmAM7bQjESQypG3fC3PTxFkbD6ddw8zuqmU-aby4CEYJpj6Zz_f3DgJHrTkGAnBEjzE2sUXy0EitI3NAgCSx6sBBQoySAhFKFImBhUlYJHCIjogkMcVnYkLA6XQ2gosRMkoTUIhCAAkQxLrwT__F733vO1-JgVPk4uCMxbXr2kXTgtXZpBWBybxJUWKKImSAktLhwaJr0vHhwSSFSZOY4OrBdNo089S616O92cHRom3j0fHBtaO9MihDbRqOIl5rIOradHQ0FfRJ2x1f2QtNY64HV48nbdN1cRJTlBhC6JpOzbOXyaTZHemPDmeBSIQXe1MCMvCDq7OuiZNJXBxMBWAxnaRAR3v7V67udykx4q0rR6lJ89m0SWkxa-bzDpHm-9N21oTI0khoZD6fNU2cT1NCabs0m7ePHz9FM3erwzBP3TAWLVUEJ02Tixt5M2kVoDisztdMcO3oqAlxbzEJLMzAKUjcKU4xiTAgAsUkgFDyQCxWq5vnMrJEA0VENd1dFQ67-geCupaK4EFw1xemICIwFF0czN3BEdWtlnHoB3ObdNOStapmtTGXqkqCqLC57M28327KsDm9c_GH__lP_uC__Je__ODnf_7Jx_Nrh29_6a2iVjTXqnXUWqq715qFAE0FyYvlMTvhbDIZh4II1VQ4MGBg2TWbAdDdYwywC91BKLmIM5E0ITqgVu-HMVctbkUt19qXmkut4IRQ1fYWs_nhwXp1waF59dYXf_aLz5577vokhcl0BhTVB2G5eXx89eB4XYyIn14sDxaz2WJCYM9fvdrFpDVryWNZYx0D0rXDwzKWMo4VXCus1-tk2C9zCvGTjz8Pgqv1htDXw2YybUJs7nz6sG26Mg6fffpZE2NctJMU61jns_3R4PxyO59OZovZsNau4Tsf3x8uh_1rB1nNCy6O9zDgOOShr9ucL09OHt2_ODtdxdRM9uaQUiUs7hQbCuKID588InHg6Q_--pfX6_E7v_6lX__ld7_-jbdeeeXl2WxGDkM_nlycG_HB8zdo0f7uD3_t5Tde_ru_-w-QkpO0k2kI4ac_-um3fvDtO48vv_zuuycbOL567e0vvEYBtkOZyfTuvTs__dmPNmP_7i-9Po4ll3zjuZvdfNZOGolt7esP_-GvTpvQLiYB0na9IiIgoSApJQcjcDVbTBoEe-0LL375zbdefv7FqwfHd-99-tY77-bVxq1efnoPiXMeLy_WYvjg7p3l2erGzRdW69W9O3fWq1XbprZtLy_X073ZsBmQGcxKVqRYq5FwSpGZrdYgMXbt8uIsNOHi9AQhxi6CIAUixnuf3lUoTtgK3br-6qKbXJ48bkNTvV6uz6QRDjiZzs_PL9vJ0WwxCYyntx_YoE4w35u3-5PJbB4it214eOd-kAhMbWx1u92fTt_54pd1BMZ06-qNGOPZydMf__Efnj58fPro8Ww2F2Rz2zs-iClut8t-s5rMF0JmNZ_e_zyK2JBTSuJ28_pNhMqIbRNTE58-fnr91vXaD5uz836zcXetdTqbVNOzk8ftbB-Zt6eXUOu42q6X2zxkNaSYStEKiEE2Z-PpgzPLOA6GynlQq_j0zgkWy9s6rAfb5pPH51B81-0NgEnSZNaGJsUYJfI4FnVnhiAsTIzkRgbAwm3bCrKDugITp5hYhIUpILHHJg1b_cb3f3V-0P2Hf_77s1kLbSKEzXpT3RSlFvut3_m-Wf2D3__pOpe-oJnpmLVWAxffyU3BwdGdd9seDTpmM0NC06qupmq5urnVkppk5kGCSDB1UCNi2zmwCAEJBUIjrvLFr31nftj8-A_-2K1iEygxuK5Wq9IPJFRGfXJyHvc6c86bPqEJAQEIEu9ako6hiYFFQiQSCiFKcEBE5BCJCNwZcVeVQSR3jML2zKCMeRhYwg6igOZh18sjIGSRpIgoUWKDuwkOMZHUZ4I5YRF9xmYFVTg6uNpve0A2LyFGdGAmZOIojkCIzIRmViuysDC6kwMhxshJAiCeny8xyN501qUQhBC0jCWweKlMWEoZxpFItFZ12JUxtBZGCRLQXEB2r4vmVqpV08mky8NoACXnlBo3BUAmsKKah-O9eS1VR_8vP_pgnfHew9PLy9Xj0_Nln2utl-ebhyfLs7P1WPXJ6WVFNEAlW8zmQ9Fh6HMpBwdTibyjSE6aFh0SoRClwCEENROWKEHV6JkNV1MUQinZny43Z5thna2IQOAQEwoD4lDUwdoQD6bTFAQNhKklnreN1doPeX_RDMMwa_lo0c0kzZJorWOvkRshUvV-k_M4BKCz82UXm_Vm6DimEH2s0RArhBjEgBFEyK2Q6WY5YoDlqDaMeb101FKzgfWbngTd3MbBiu0dz9fr8fR8vVr3E4lltX3u-ZsYGyQoQ6kVcKeREnaFqla9AJIRVbOYnsEz3G2xN991EHcZHGOO066Zz5iuf8Fhh_TONoyBmdEt5-oIwohirsSMAHksLEGaVtXULaWopim1EkKIMm7Grpv26w0xhhhEoubi6LGNpjCWkmIQodQ2pViQIIyMENtY3Wquxeq0m7DI8d5-KcN0MiW354_3J0Fod4EwVjVwZ0Im-iueMKnabg6KhOTIyIi4s1Hbbg0BkIKAOhBFRgVaLtchMhCXWggxBpm2UYis6mbbE5G5hyBRpGsjOe6Wb_Ssu2-l2HYzrrZ9SiEEESQObG4xSors2bu20WrP1ipIYy2b9ehMOwOxqhkQAuZqqo5EY90BgixnZaHUBHPs81hKJQStioHU7e7th6vVeiw-DmXHES3ZEbnuLNgipWZw1FJiSq6g1aez6TjWnfLXqqYmdU2XdaeeRhIiIneMbWO17ky9QTi2idSEhWMQQXKcTCem9eRiI4htEECouRKyNHxtf69rm1eeu_753QdjHljESzUDM2i7ECQ4OCNrtXbSpDahmUT2qmA2n06s5BuHB6YlNEHNDhez2AQgaGOw6t007c8nYLY3m2rVFGNKEdFTihIIkXO23XTDzGu1ELmbpFp0GIskcXAnm05n5t5O5wAKiIwQmNF9_2DBBEyiWW_cPMr9MInB1AhxF67J2_769YNnbYH5hNBLqegggSWIIKYkSKBmjNikEFgWuwgWh5qLRGlSJMCxliGPYy4UhQADUttFIkopjZtxPp9cf_nw_MlaTatpzZpSqKWgAwDsiuo7Ry447Fbbpg4IEkRr1WctMdrNF3Y_eTcHsN26zM1JWLUyB3AlIBae3ToMBo8en9SxuKlpJgllqKlrkbyMecezMFUwYxJiVnM1L6UGETNkJrWC6vdu379649qNK1c_v3snBoFn-jiwaoDgjkHiDhsxFjU0Fi657sCpOzafEILhDswH4ETobiGEHdDDAYppQAQ3Yi6lACECppgcd-5gG2tuYmPVXnrtxV-8_4ujK8eI8Gd__Mff_PY3EUPJY64GQE1K3X6adN1mWAeS5XpD0qQ2mTuzDMO2WN0Mm_VyxUb7V_fyZlz1PXD85PHT7WYMhO--8erTJ-fHx8d_9KcfTbtwcLyvVbXqYjHdrLfPv3Bju-lZ2nUZrl49ePDg4Rdff0ErP31ycX65Pro-s6rL7eXds_X-8bTo1sgdaL3ZZsNx0MvtePL0QiT0OU_nMwea78-6SbvYOyjDlt1Vh7v3H62Tv_X68996583f-pXvfecbX7lx8_DP_uTzX_7BuxSm9-882TuYWNGYmlUptz9_sF2O3_2Vd_7iF5-9_vqLkaQN7X_41_-x6gAIrhoZvv-db8wnzetvvjqddX_yZ3_8D3_tb_zFLz7eDusb169--skn_93v_t3_7__nn4V2Op1Or12_dmVvf7Ve7R8cGMC2Ly_cvPXw0YPtOHzzO99eX1xervrV5SpKQMF-HBc3njs_ufjH_9Xffu7mtdX68u6de82kaVMsqvfu3vnuX_-12x9_VDSnmNYXqxgkxjRs19PpoutCP45nj8_efOuN-7fvNbFZrTap4XGz1TETe8315suvXJ6vSCiF6EBxNtOsiyvXVydPmFligOCOkLrJfNZN5vOD61c_v3PPnSnI3uGLJ0_v9dX2Z_PL5YrYCQjUb7x45fGD075frlebcbO16vPFYjLdd8TDo2MDM_UrV47Ww4BYcl-ni2NgOdlo0073Dw-dfL64lsvQtF1s0_npUyTerC739g4kpNwPs8WijFm1MEnbTFioDCMHKWVcXl4WNahFJDr6M5Ef4Xbbz-Zz03x5eZlLQSJXRbSa87OV2jC6gdY6WUy3l2sDt5xBq2thwTSZX__yzTHp-nQjrO2sqb7eWHnlpcXtD--p6dGVxfUXrizasHx8CmX4yz_705__5_8U23R05cbuvUGiIOKu6pOzSdxt55CJQSHEMI61TYlTqFWZgIJ4rUS4Wm5-6x_99oc_-fn9zx9OZlPjCIBm6mgELE2cNfE3f-WvffDzBx_cv5fVyBmFzGrJhYnH7VDNgBB5F_ixMo6H165dnp4gExFBVdnpBWPjYBWolBIbGYfMhBzCOIzM6Aiye-cVJ4V2evj173_105_8-PzkElMgadxxJ6YPKVw9mP_KL311vdr-yz_8ywcPl9tSa997zggEu-4Vo5qLCLiJhF3ecsc22JXrHBSRWLioBWEkKLkgAouY7RDNThK0FsRdnqdRr8RsasJi4EDsaLtb_o43ugvu-g4l5C4S3BXcHJgaKsOou4wlJ7fqWUkYn4k_gYTUQR0oCCLs-E4sO68pRJJs5fvffyfU8Cfvf1gd-7GWPApLyXnncNBqO4KiqgEAVEVgAzdzBDS3FFKtlYXzUGh3QnTcFSNtt8IWYhHV0Wv57lffnc-my3Hz0cMnffHTi1XsGiRo25Ylnpyv1pttqZrHcX8xB_MxqyL1o_bj0KSEVg8W872uQ7fAKILq3rapH4qqGoKaE8Eu6lPHysT9mGNIhWkzlGKOzP2Yx1ok8FAqum9rfuZIJQaklNrdZLmN0VQZqB97luDVtUKSAAn6YgaO7lMRlV0YldoUurZZ92OaSu7rsOkPF1MEYbRcoAsUgNfbUivUYoEl5-LORBVKddM61DiJgdiL6VDZLSIOWRevHtp6NK39UN597UajAEh9i3mjzFRzsexpksp6a30mdmpCAZgsprrakiAxppSG7Hv7B6XU1XqlY44Nd_O9YbuVQNy8-JYbobrmLAJeah1HbrqqEJsGGVzBS0VGkmBe3ZGYUzMxq4AUYuugHGMTY9bBtYYgzFzGQYiGdZ-abiwZgctYmkmTaxWmWvN02jmikas5R0kiTdei2XK1bdtIZHtdWszaBlGI1H2nDzJzxx2qFGDHOQQDxKpmVVkEGcBx50BFxHGsu-iVIyHCeszCmAtUNTXfbnPbRkRifNaOUjd1H0tl4a6Jbs9gv5tx1Kos5EDVLGttm9jsFMiIpWZkMjBGnEw6NENCYAJzA9fqoYuqPo6lVN2OeQc3caCyoygSqVqpsO0LBu6Hml1zsVJtu-4RuVbotRrgWP3yfB3bZttnZkIhQGy65GCas4OTEAB2bQNgxIJMu_0JkYBDbBs148C7V0kkDpGJQxnzZNJpsaZLvtO6Ibj7M-4ryeH-_uWwUbUQBKyKExIXty4mCFFCyHV4-7VXP_r0XhQhFIjEUaKwCBPxfNYAECDs70-bEILsgqASiRbTSc25adMLN6644bRtc6mGPulaFmxCHIe8XY8psUhw0yDMRGDASGgogURkHHLTpnGoQHjlcN_dx1Ikplxy5OjobdN4rceHC6Fdw80nXTv0w5VrBwIwn0zQaptC5IDmtptDQ510EyJEwLZJxBhFmiZeP1qYQQpcxsxEs9kkb_PedErgxFKqpqaJQebzbjsMLElr3a63Mcami0OtzEHNWGjXu2gDj2NZtM3jk5UDllxLtdTsyBq-2wKFJpZcAJyJSym7c69pDdyo6bO9EQmg79a8-FeqLTBXNObgYMSsVQl3Sk6Qpnv5uZsff3R7KEXVYhet1CiyHTYSg3CqWsG05kIStMKOfWemhGAVwl9NvKZt1LHcuXP36OqV_W765OkjACq1gjsRq1V0_qs5HoYYSi1MHENEQnSopRBTtbo_nQw5A2IIgs_O86RuIQRwz2Mxsx15iUQAyQGq2s6SU82aEMA8pZSr33vwyGOYxfiLn__8-Oq-iDx8fL8a1ly6Ji0OZon5Fx_87OrRjQdPn2JIxLhcryKFnIe2m2z7XsCvX7-yvzcfxzKZTLZQP7z9oGQ19VvXj8c-n5-faslNN2lSXK_WITQ5j1qVmUvFR4-edml-drHc29vbLLdB0EHvPThJsfnk548wtCcn4_p0e3Lenz2oY7_sV7rut8fXrkbi-bTbWywCUuk3w3Y8fbp8dOfR_U8f5sC_-sNv_-Yvfefv_M0f_OpXvvTa889dvXJtsbcn3H706Z358ez69SvjkCez9mB_8fThCVL84ON79x497ibtu2-_8ge__-Pf_LVfurxYCeIHH3z89ORxlCBkOuI3f-O7uUeo9cbx8Sefffjxp7f3FldGHva6_Z--_6mT7l85DoF_6bvf__CD9xeTmQOEKNV92IzboYzjFsnffOut9WqDXXPv04eExAFLtWa279V-45e_ejQ_AijTtvvoww8P9vaqw6MnyyePntx46ZU7H38ym87MtdRBQshjLn3_rR_88p1PPiSgF198frVeW81D36NQGUY0QPJxW7_93_3OL_7op8IGrqFtDBwQGCxEXp1fAriW8uLrXzg7fXLt-tUUZLkZTi832yGbaaX87pe_9vGHH1y9cm27umQUMdsO5frB_sd3HyQJZKbDUCsAtiSc2nB8eGSOp-ene1f3Lp6c9tteWXrLDx99_sKN5yaJ7t77TGuZzueLxeLenc-vHB47wLgZhcW8bs7PwXEsue1meRgcrJaha9qUunEcppM9Yrw4OytlLFo2662qpqYZhzFKMMvgiIzr9QZcTc1qznlkkVLGnIvVqiUTA6cwLDfozuCqA5JltV_8-JP3fv_nZ7c_u_fexx-___FnH3y-Pbn8yZ__7PbHd548uP_Bzz740R_-l_d-8uO7D-5-_OEH68vLL3z9m---862xbhzICd0MAYF3dlsnIXcouQjvFJOeQsBdTJec6dnUi7n7-__97_z7f_7vx80YWsnF3Q2suv-VDUv43a-9_cXnrv7xzz87X28cXKvVcUTCUipL2EkGVK3mHAIjkVfbOz7IRWvOUA3ViZEkAYsThJhyyeiWYipjZUKttemaHSabAnOcvPX2uyD6wc8-qNk4BS0gsaleiSmlMN3fe-WLz33ltdfzaP_5_U-WmzzmreVqDobsiICQh2Ju4C474Rf4szsSARHVWonJtap5So3rrqOFuwykmhKLqZIIB9lVs3Zlu51IfTeyMVURcTXVQsTIBIRorqYoggRalYkRsZ1MludnALKrwRDL7oARJJRxBAAKEqKAQVGjZxRXDPGZvZGAQkwQ6vUrx9evXnvvkzuXy00tVnIREXWramjGRCVXJEhhWsoQRHi3m3EDwFo1psbB0B0DxdSUkkMIzJzzECdNN51ZzVhLEHKzr7z9-p37j__y5x9tDDaj9blMFzNX3ZtNn5xfPn1yscnj21964fRiC4gphbsPT--fn6naph9GK0zw_NXjhqXrUqm1lkxEIFRKBbcUqCoAE7gzozATYJOa0aoyFURjzlUdLKXUxsQOUSIimVo_ZiIaVHOtSGxqMYamCWAKgNU9pdh2TSnF0DDyZhzBfaVlkqTPujsIjrkCmRcXo7OL7bXr-6oAbut-KKBOtqlqjsSw7XsKUobSzqOC63qbR5sfzoE8IW3XfQw4LrfGkEuWNliG7Vl--c3rzQbaGC3G258_cnJCMjAm1Dy4KiEWLbGd2TC6WWDUWiik41vPMTMm0nGAqqlLajqu-sW8Y3n-TWIGM2IjrWBKUUhEYgMIVk2LESGjaCmpaXeFDwXYhfFLLU3ThRTUQXNmxLodndjQXZWTBOZ-3UtgYSYAAgpBdhgWjtFxJ6ngIFJyIeYYBc3U7OaVvcdPLtoobXo2VvwrKxcCojvsLiottZgBIDKVUhwcCa3aM9MFspmp6q6_slxnN0ThXRHHwBx90oUh225fBgC4q78Io7kCxijboZSi5o5MYy5VLbWpkZiEdgokJyhZtWrbNgEFkbRmJKzV3E0BilZyrOZj0YthRORcDZB2QMntdlxvizl0TcwVTH0oOxGSO6GjuPP5-dLcV8PgiO0kjlnbFEwNCICl9CUmSSkQYwhBs-3KzoQ4m0xKzqmNxMBELFJqmcymu3YHIoUUOcadDjm1iQMDoBCGGIiFBRHwtVdeuvvgESKJo6o5AkhclTzrum7STNq0XY7f-8Y7P33vo9RIG5uYmAFTFCaJUYiRzGJMptalyAKz2UQYUhu6JqbATduR-XzeRbYYAyG0IQSEGGOMMu0iIS5mk3HIgBBFhPHgcJJ73WGgarVaVEJQtcQw7brtkPOYY4zgKiIEiO4ll24SyXw6mQzbzf7-HoMTQNuESRubEIPAZN42KRRVBp4fTlKKgalrIqHPuiYJzmbNetMLQykVwZmoiSGEHWmDZtPWVafT1s1rcVWVgEEQ1WMTANjArNQkEgPXUl0dFM7PVk0biCC25AhelJmRCJ5tv3ZEfDQ3JHRA2HV8XYOEXVnJqsqOcKeGDO7GhGpKsDvCoZYaUnRVEU4hVLPX33j9w59_uDtFoxsohMAlFzUArBwD-i4RDyIoQloqEiGREO1MjVo959K0rZmfn5_v7R_sLfYvV2eMEEJ0cFV1dyQIIbk_i_MTUyRhoSTMIu5Yag1RdsmlPFYO4u5jyUmCu6Mjs5grIji6iCB4rqWJqdRKiERE4DEyAtRxLG5Pz8_3u-bhnaeLvZBElsttl6bby4s0aQ8O9vJ2c_VgP4R4fnaJhBz48ux8ltJkOsm531xcgPr-fJZCcMAnJ-ef3n50frmREMaxfuUrL7nio6dPUtPcvf10b95s1mMdh50CNUM4O9tM5tOh74lps-rTVLZ1fP-nn2vF1dkFsD59_BShPPns4fVbh-0-vfbuGy9--dWrV64_vvNZrnnd50cnp5erQafpO7_8jd_-4Xf_29_5ld_6O9_5jW-_89zRfkjEBIQ8qhHLNvvFdvjf_v2f_OCX3qnZs1VhSuRNojzmn773yeXl5uvfeLebNB88evL1115ZLVeBVGTysx__TBgWe9O-X9-5--A7v_rdaOMrt27cefjkL37-k3e_-KU7dx5KwDbRretXAjZ7s_3z09NhO7rnYdWLtJPJnEAvzs-2Z6ftYvbKm68P635Z8oOPPwN3da-m06NDHYazO_cA8Pf-8D_8xq9-38zufXpvfuXqT3_-fppOk4S9w8Xjx08We4fL83NCI0AWfvGV1376o58f3Dw6PTmfzGbL9aYfB2kaL-q1SIBhrN_69q99_tGHlnvPpRoQR4409v10b7G6XBGBD_ndH3wnbzbz6YSZ-6HPKo8fPE0xmtYX337n9kfvA-VxHFQVoRDI9ZeP7t9-QmgcpQxDyT7fXyBwtvzGSy86wNOzs-PD47LaiFCvfrC3d_nwfLoXmjRdXlycnV7uXznql2eTxWG_3Uwm05zr1Rs3Hj560i4Wl-frbjYDcJBdntvWyxUzNU2zXm9SbDjE1flFrZmYCUyQJUgICdT6cWhiRJY8Dk0TAcjdNssVh6h1dKuhiecnJzE0DrVr0rhe1Tyw2ezgSh62hwfd0fUr-2--AkO-fnOh4yAhvvL261_62td_-Pf-xlvf-kq_hee_8Nq73_nOV37p28fH17OO2c128zB3092Dg92sjiZETUrg4DvMQBAAIDJBBqpe4crVa9__za__y3_6vzMxREkc6sjMmgIVc4whpoSAP_zBN_dC_PDBo_Pz1TjkMWc3q0WNKasP25EDuxmAIZJVFYaSa7eYbFfrsHtpJlJEQ3e1JjWuZrUioYMbKDxzAZmIpGb-te-98-M__VFejY7ixAAAQuq6s_2goET51jffee3qDVf9jz_6WVGoNQ_rLQqpUs3qZKpZmMFcWEpVidHBwSFyVKscwg6ztxOjMcmOUuDViHF3oxYJWlRC9F2goGpqOrcdfumZlnSHEEUADkFrZSSJycwQkJDAnYTrmGPbWrUYhMBRGndzUzBMXSI3zYWIRaKCExMRMlBAphh2sxgwQyeFqkm--taX7t55dLbeFt1RJWotikwlFzKXGMDRIZubm8eQqqohCDEyai471mrNRoghBS11h3_oYqs1owMDIEHXNm-8fONf_bs_p4hn63x5uTWnbT9OJxO1enq-XW-3JJym7ccf3gXkGMPHd59MJw04bft-GMf9wz0E2wsymbaRA4IzoBetqg5YijmAqblBl2JABCFFcKehFIlhW5WCNJN2rLkfcynaJhEgRKxgTruqNPbDENu4GQZzkL_CQSIgALUNg3kbcauWizliJdyO9WzdI1IM0dTWQ967Omm67vN753uTUAGL1bPlNg91N5jTUoSl5oKmXjNGGocSzPrLTIEhQN-PcSplWxBQzWMgCJyij0_W33_3jbOTi5JLQRjWG1NHR3fQ7eCjxhSsVIkhtEE34-HNa3Uc2-nk5svP5748fHS2N2tBIUxEq1577aiqMz3_BqKJsFslAhvVDdwxxMjEZaw7Ty0BNJOJowMwEmNgcqxVm65T83ZXuywVtRKAugMiozD6Zr3uum67GZumiSH0w-gELHEsuWrNwxhSdLOmaxC9adJmswHHPA5NkCg07ZppG3cLODMNMSCQuxV1dSNmYFIAdXdAfTZxt2cybQBAIEJiyjVfrPpiUGoBRxHJVYdc1b2Y51rNSV0dIATJZrnUy35Eoc1Yh5KRkIQliKqOY1Z3Itz97t2UhAkhhMBATFhz3fn3HKAfaz-MWb0vxR13vjZ1uFz1EmNRHfosgWt1ZNruWiMGq81Qwap7zjbmjGB70-bp6erp5egAkuJ2M1it0nCIyWshwHEcpnvzflujBAUnIhZBIEcITSq1dE3ThADogQUdEKBp0mQ274exnXZWS0xJTWNKIpEJGbyZdsygBq-9-eqjp49TaoQ5tcGMoAlNivPFlISuHR4Mm_7q9b1-yOdnS0CkyFRNgCQyk5DQ4dGeMO1Gv20KtdTANJ9N-k2_vzdXrd28FeHDLvW5EFgUapI0SFpV1VMKVa1pZDpru9jkWmOKKBQCiVBsIhFNJk2b0unZeUySYjKESRvaNgISA8QmdF0kkpSkacK0bYNgk3g26UBLjHLz2h4gXJnOctXVapx0YZLi4XwWANoUZ01igjaFgFCydW1sm2gAUWQ-S7Np2m4GQgzCy-WGAIggBAaw3Oe2S1otRJ52nSt0XZh1yRmEeTZrYhNyP6Y2jTlTJFcnYhJ2NyRSVa-7G4dJCEhk6maGAAa-Ow2TAxCT8C6qhoCmGiQYOICLBCRwRHd1VVd11LZrv_HVt__8z39eSvbdLlfVcgEydx23g0igEIFZazVQBM6lArNX5chuxoI7hqAEEZbDK1du3_58__BgkWbnl2cGkKuCwQ4YrqYiBG5BAhGaPntC7kRl6sbEWtTUmGgcR0Qxd3AXIZaIRFotBEFmq2bqO88wILIbu3chHB7M5l03bkcJ6ZOPPjw83pcokrdNgj6LNLh-cqkoN5671QQKIezNFo-fPB3HAmbjdrh6fHhxccngWurhYn-WplpgyPl8uz05XY5VkejGl14aT5d3P3243vajurqioBr1_VDNq3A22IxDGWzoB6hF1WqveYTLs4u9_SPSYb3qxy1AwaObV7INZ48uzs829z96cPr4yWQy__Ibb_zNX_3B__W_-e2_--vf-c3vfP3VW9cOFnMShl1n30BAArKZA_GTs2WD8sc__fBo3iwW07Pl-uT04vhwz3I5P19vB7j75OTp6eXXv_rayXp7fTYzt365jmKvv_bav_mX_6qWIoy1lHEYf_ibv5Y3m0enFxK6T2_ffvD48-995Xv3H979zje__fjxg88--Ww-m_zZn__k-pUrQx7M4fziJIbuzt3PP_jz9ylI2zUvvP6yV398cXJ2_yk6tF2j4Itr15pAL928-b3vf_U__-c_qsN49eq1473F-dlyeny0vOw3w_q1L7356c8_TI0M2zydz1iIBB_cv_PiS29Ur5988ulkMv_kvY-fe-0lIRqWKzSvrkPRt7_7raePz3XcukNqm6Nrz5HAONZbX3jp7NEjNNXqb33tnUmMm6G_fuXaZrWupptlPyzXIQlYyOvTcayaLU1mOrpwePW1Vz567yOJsYsxBTo9O50s2iSEib_xpW9sxvXjJ0-nB4vHD-5f2zvarDZXr-ydPHiyd7i3P7-CRDWPx0dHq9V62rVN08z29o9eOFLwCq61pEm3fPwkdLFtmtQ012_egpoRvYkphJRrnk2mk8WMiKMQmOVxa1o3F8vUJt2h4RzFiNzRrOQsRJvlsp1OvKp5TRL6zTibTwSVEMf1Opd66923mzQNTQsy2Zwva78e-_XlZv9X_9FvTmfH1KQH955sVgO28ejKMcc0DGM1daRancDGsQqTMAvLLtRKzOCGSOYaYwTcVUNdEBVVM_3G3_6NfnPxJ3_4cwTkFK1o0YoItY5VtZhRCg4Oar_zw-_CoD_-9PZm1ZdqWlQQJMWsauSOQLstNTKi046kWfLB1WvL83NzQCAWNoeY4rAZMTKoEYJWc9XYpFpKFKxbe_ntt5pG3v_Rz5iwInAgHYqaAbOpcRA1jSLu-t133zie7H_62WcfPnh0draKQuPQl7ECuVflAMxUihp4lNbIwRzdtdouV2OqUVLJeYfzRmbfiVoY0VF2tk1hIHJCEgEzRCSSwGJqiEiBULiWGmNjpZLgzrZExAAuO44yAhIAAAmVsRCz1kqx2YmSfKe_VENwYXEkCmzmCEBmiG5uHCKHQEAxyHbYno8Xv_3Xf_3Tj-6crNajEgdCs81mRIaSMxMmCqpVhEupAI7IFNjMzJSQkSMhiYgwgYNw2I1F65A5MiGVWp9_-cY4DI00t1688tOf375Y95Nbz6_X54ETEIDIsO0fn63aNi3mk9t3HjGG1bbfDGM_lMkkna77JkR3B8d7d09efO56G0IgZ8QoYb1dIzAgPqNooCPQ7lvYyXcfrs4rcq7uEBxBrNZSRlUnJMB501BgJAqTWLKOpbZNW610bTTHNrVa62LaroZ-HDIFTCxDVgBWtSHXIWuadICUS40hMko1ze7np-vlpi_Mxo5IVupunFaKcdMMmwFzIQmlqmbbXp53XaPbbJFLNnQYx8xujGH5dDk7nOtWZ3vtvJQXrh5tLvs0W9x58DSXbOiIFs1tGHTTCyEIcJumx4f9xSoktmJHN45efOWF7WU_bFZ7s6Zf9xQCVJ9fOSjbwnzrdfAdsN6xKiFwEiuOImYOu1Tf7gltFQM5skRBEmAKsalaQ4pNk1aXK1M1LTsVKIvExHUsZbRdJUUiD6ohhum8TW3U6sNQQqQmyXyxgKrTyWxHeFgPm_3ptNbSNRGY1kPemzYsjAjEVKspwlgLIQCiuTtQqTWXGgP3pW6HwdDXm54DIyACVNUQQ3UHQt-JkxXcwABCCMVstRmHIavDZC8-frI-X29zrYi75B_sxB1IKMSqvuvDdE3ju0KMiHkFwMhiDixcq_a1AsKYtbpjDE6IxABQqgaJBo5Cq81gAOvtgMxGoIxZcax1ue2FAAlL9Wp17LWqSaR11iGrupexHO_NL9c9oph5HQszAotWC0lQkRDbJnbtFMgRIOx6FABmzoG7rjFzRGy7Sc5FokxiTG2jtbSTSa1ZQkCAmMTckYCQJrPZer3cxTNiClFC7FII0ohEp_m0mTTdMOrp45OrV6_048AszDjtGtXatDGmFAI7wKRriHHatY3wpG1SlOOjeRBkYQRvUqilWPXIkKI0kSddW9Vns8gU0T0Gado0bIcoYeyHw729MRcmAhJJMW97EY4hAAI7HMwnzKhVp02TmjRJUsYhCCeWwPTSjeOYuE2x324Ws7ZL8fJiFViqKrrPps1OEDZstnv703Gznc8nxPTiretNZFBl4baN5j6dNCXX-aQjZnNr2jSdNG6VkFITvBY1v3ZlMYzZqykAkDGgFk0S1Gy6NyMFiZwCqsKu1E6EMXFV3TWZDrqpmiEB-C4lj4GFCNV1txNzNyTWWiVG1YoE7mBqAE5AAKiuSLJ7Y3atbdvEtrty7YXPP_44l1pqcTerrrU6QC1FUsh9NqupaQh9zJmYRAitegV3iCLg4GZg0MZYtuXw6hU3PXvy6NqVaynE1XYdQwohMIKqxRCYSc2QyN3QPUTpx7GJjZqqVXAsuezmNyFEteruTduUYUwxImiIUko1M2aptRABEqEZByjL8WCRJimNY56leHa-vNheekoNYBjXe1cPHjzazGaTpydP02Ly4ks3sWwFaW8xvX37Tr8Z9g_nZlWYxlLI6uXZ5rnnDsdxnKZ2dD1Zrh49OVP1EJrDSbe52Hi2sdrQ52YxO1uN5-drDpJdz043y80251Ich_Vqsbd3eXY-Pzxeb7ZMsB1gXG7O-r2__w9_uQTr769TnLz-ykt_82_-4J_87m_-zg9_8Bu_8vWvfumV69f3RGB3Z3f3XSpRhAMGVxBhc-9LHko9X40Val4Pe7Npdb84u3j5hWuNkAA50r_-079Y9euj61fefOW5n7__ydfe-fLQ97OAhOFwf__f_dt_O4w9KCoi1vrD3_nrubdahoP948vN5ZOTs9Ckl1586bPPPnzh-Zc-uXP7xVsv_OyDj77y5S_2efjk4w9j0548fXT29DQGeuXN17Ju96_fyOt88ujp6BpS2rt6WEo_lPXxtWuLZI8f3n715rUvvvXq6en5dhj_yT_63X_2b37_5q1bJydP-uXq1osvfP7xJ1efu3n-8CJ0qVbtN_2bX3_zzuf3jo6PQgivvfJSamR5vq7r7Q7iawJvf-1r_Xp7ef4EASTIYn6UurBabm7cfGlcnVstFOX0bPn9X_nevdv3X3vhxuXjy81mMz04vDg5dfCTp49ffeW1e5_dGx2O9o_yWLpuevXqjduffj6RkMcybfaGfvvKS6_nbP2wljR978OflWG9uVgixtXq8sHpudf69PRCGB4-eToMy5NH54vF5BcffzrqeLneOuKw7k8enW7OV-20FQ7TxcHF5cnJ04v9_YP1xaWrnT998vjOHXQrpWy2Ww5hMpmwiBputoPmITax365S06rBdNIFdFDv15v5_h6B5ZprHlhCv1pLDEGICF2BJZQ8Aujy8eXLX_vS6f2z9fJ8c3qZpmm6d_iFL33xyvUjUwhdg4IOAMJIoeYKgBIlj4X-SuhNSLsHqFZlxKLKjLWquQdhClxrDoxaymyy91v__a_-m__ff1xdDCDsiFayAbrXWivF0Otq2u1T4CDijH_j-1_Xrf74408vlptqpmaoniSpmZnjbl7OSBRK3lERUXM-unljdbkC8DY2xGwKCDU0cewHFkYAQkcWZGOAPOob3_jyw09un59espABmEKIjBQca2iiak3dBMFZpO-3_-S3_2a0-M_-1b93ifcfnqgWAiy1gmmKolmDsLqxcC2ViN0NEUhQc92BE4mBdm0lQJEdad4RHBVjjLmWnb3dkZlDrYWYaikSxE2fVbd2oFCrIqGo7gCC6IbuDuCAHBjAm-lMbdd-3MF5QGIA85pHDmJmjriDJUuM5m5qTMiIoWlyP6YuWfH5fK5aH2-e_OO_-XeePD25_fhss9ogIYlsht5BwZSRIwcjBDAnyEOPgBISIboZMptqSGJWmXYkQmQhcJ3Mu-Xl0t2J2VS1Gqkb09nZagRdnVyYw2q9jTGen1xktaK-Wq0VIErox50aTDjycr1FxDwO-_P97LVJ4d7J2Ss3r7QxmppIQCBgrGqIAIRRhAO7Wgjcj8UMYmoRqI0JmaDkG02zCF1Fviy1ao0SI-E4jNVxVAUm1dIP2dCZg6uFQKt-QCAPMg4lSGKiVoSFh6FyTLnmXURtve0BqZmly4uVCFeyfqhN21WtJFhzHsGKOpBNOmSSvB6QmUhTICevqrFtUSCyjH2p29w0XPOIQA44mU5fefnwCFKimAmfXlxkKMunGwKyUrG4VmV0IHGOMTWl7yfTrl9tKHWvvPjc5cXy4vTy6o39XKyZpMX-nvaZEVhefENSa7W4GiJqVQAEJuDgroiC7uigtcauAyQzmO7vaymhjaoVULTUdtJqzRKIEIGcWIKw5rJzBDpBaiIDhti0TXLdHSegaxIBaK0phGEYNWfV2jRNiCREpv7Ol19db4updl3rVdsobmBIVRXQU0y5mjoMJQ9jGWuJbdP3uSK4IycZszpYFAlR8piRuK86lDqUQsyOrqot0zarEw6qQWgYvbi3Me4WIHksbg7o7jZpmxQEHB1sOmmDBHfIJZspEm-GIbAAoKoWUwAAwM0wKKI5KqAj5qK5VHOoBiIUWNbboVTNuQ6jddP06OllKXUoNRAH4fWm32Uqz572wNYXVceqtd8OaoCMHEhVo_Bsf7LT15Fj2yUtNbWpupFQaBJHEqIQgqqmGEJKudSUQjfpqtaubY2QCFOKCBZiEAng2qQEgCICjvPZZBz6FOLQjxKjdE11aKO0Qvuzdt4245C7Nj052XaTyExVlQiRsG1bCQRuTRPbJgr6pGlCpMW0TUkmXVOzei3zabPXtl6UiWNkFrJqs647u1wfzJomBUJsUhOfyXGeGR6YKYrsNjOoIEz9Zjvfm6EjoTcpggOCry63i70mEEP12aRJMaYQci2L2WTSJTJbzLoUwqRtrhzOwREQYxtSE0OMXdc0gfYW00kTukm7XK3bEGIMYMAIarA3nyHi7tVcAqvafNZtVxtmDkkCi5k5IDGllHLOTZd2QdkozMJd4HHI203fzjpE8J2JJbAWjSHtduJKyjEQkjvIM80hmCszAzoH8ao7fTAiIaGqCjGguxoxEZNpJWEU2l3ZY9Wmm-xdPb7z2edmjkymrkXBHdwAsdbKQSwXr6WbLsxt3I6MAAZk5joikTE4gJkjOJD3_eba9Zub5eXDJw9v3nqxDqV6ZmJzbWKsbllLHrTPedeDL1aYZbvpWaTkssNeG3hIoaqqKnOopcQYtVYkdrCQgpuHwMQ89v2kS0SI1d944_rhrNXqjmiocW-y3Wwf3n_wtS984er-NOv2k88fHx4fXp5fsHg3jwdN7KSdzdLnn97ZDHm6Nx36QsLDtgetAHD1-uF6tV2N24zl9qMTjMERG45sdcx105eiUBFX65wWs83TCzDQXM2pYXEzhNrFoOqXl-Vi2auEX_v17_3d3_nOb__2L__j3_6l17_0XLkcv_Zr3_kf_08__OY33752tNc0iRhJQN3NVWsxQHRgImZyByZ29R2_eDPkjx48_fDO6ZvPX9u1Te49fDLb2y95-8KNa5vVtozlcr3505_84mh_cXh0NI_x8fLi3bdfvXP70ayNTQhi9qMf_Xh5sXTAybyxUb_whdeaNNv2l5O2EZLHT862dfzKO38NIRe0Zb-at4vLzfrgYO_i7DwX9938gEDNNuN2Pp0tDvanbccJP_zwPrKMm1Wtlvvh3S-_0z-4-7d_-N1f_v53r-wvXnj1uYvl8scf_fTa81efPnl05fjgow8_eemN18uwzcMW1Q-vX9ucn7FQ005m8_2Ti0fbk9XR1cP7n34O6KUfAYGjVPDDm7eu7B-dPn2wXa1JaNRh7-B4GPtS14Jc-o25dvNZTDL061XOk7Y5PTs_uTi_OH-8vbwEx0ePH8bKisW1IlXVsR83F08fl-16HNdPzs9GKxbdfdjkbP3F_Qcn14_39rv9V194_vnnX_rSF9-89cZLr7z4wo0XX7x688be4cG1W9eGzbg_W3TTedvN3DyPuYlpMpuCOrKU7apNbRsjAAlLyQMjeynk3k662WJPx8GRHQMihJA2661XNUMtRbVuV8ux712zWVXVXGo3mQzrVRSJkYeh92qcsPTl7OH53rXF5vQySZgf3hq369img-tXZvuLu598_vLbr0-m01JGZsq1lmpMUZC6IBJkJ9x09VIqIQOYVRPmneyWdkQMIhYhdHQgJB3pK9_6Blj-0__0MyIEEYrUX24c3NwQkBiBQuSOKJAQEDVd-Pu_8q3V-ebTx0_OL7cV3AzlmeXDa6kAULUwMAAig-1wm67u1DWhbDMxIAED5nGkEGOKZRjaFPM4psm0jnWxOHjhSy999t4n41DSRGpfiZ8Zw0KIXTftN32KEVEBPYWIVf_BD79fc_13__lPj25cvbhcDf2Qi-aiO-gm77aygF4qJgFGJilaScTAOIjWupP17uTrho4c3AxM1TzGqDswIO92G4gM6Dtr2jPvIgKE0IAbgEtq8Rn2AZgICEkCuIK5GuwdHY39gADIDI4GGEQQAcyIWFI0rSjsRCjCKSBQJAFwQw8x1VyJESI2baSi_-CHP3x8cvLZg8dn5ysD7wdVK6bmWhHcAM0VgzwbuKITB3RnFqt1h_3gENx1zCMiI1Gp3k5Cvx0QUa0Eob4fmKmYXSxXDpiH0g8jEaYo55dLcwPC2KYnp-dmmGvpc-43w1j02tHx47MTYcrkboRkt64diNCibQkhCBFTdVcARFbz6lWehTUqERGHvpYuxm0_VPLH5-uToo_YvKWq9uT0kkGvzmeH3eTxxTKTS6Tq1oSASBf9NoRAxExcvC7XWwxxO-QkLYIxICde970jRubz840jhGkIwsNoQHi56gG0a6RkH8cylJqH4jUHknHQXHQYR1CbcKMKw7ZnhnFbUUjJKYR60ddh5CYhhb1F--DeyVEJv_T2a-zKCT--_bjUWnIB81oHZ6jDGARBBJvQHe6VdX98_XoQFImvvfbc8uyyWzRA0K_76f4UFYAcyMQdrVQ38AISgEVM1YC8VgIPTTCthpDmkzzW6cH-drkdNysOKfc5tg0yd11XSyahcRibIMRi4OaqWgMFALJKqk6uHVPN27353vl6m6JMp91mvXazfhjnk4mWUUJabTaTrqnVX7p-2F8Myz6flO3Vg0kMoVRQK6uhTJI4US7KIqUULboz4I7jON9vL863Oddeddo1y6EvqrO2SamFnJ8ttlyDgyEWg8vs26EiwOgVnOYdqgGxe9EYJYagqotJM2_DWPzycp3dpykRi5nnPFqtHJMQBgq1PAMS7URaMUleYxlHAgHiTR7HrBRk2A5msDdp0H0-mYxVnzw5Rw5nF_1YdXAFoECm4JMuff7w4ubV2dWbXR6VMdSyaRPTfDqWcR7b7TBiGwnADVlC26q7NW0qptRwAjathphSm3XThjCbdKVUALt57fjiYummTQzdrFtte2ayWgiQRFjCWIoTApGahShnJxfkGALdunXt7OxcAPdnTS1lsT9LJJptb9atV1sgyKUg06Rr-r7v2mYxm1yuVjFyyTk1aTqbQFVAaENStzYIlCxNc3GxobnFmNR8PpnsFBSANm9TG4MjAZmBMwcDsLLdW3SAdHm-iimZqZnVnNH88GABjGna9uOY8yjC1_cPDvfLMNY2hmkbJ5MGiayUSZO0ltim_b35tJNavFZzRhYMghRjO_Vhm1OIQqilMILVcry_75C7JpoaoKeuUbUuxjGPXQoEwIDb9Xp_fz70w46GEIMwg0gccplOuzzm-XS63W7AwYuhW9PKdkN1KG0TzdQzdG3Tc98vh_kkhYi5mhsIAADWUlMTtKqg1KyEguipa3xQkx33DAInK4WJpOGdZJ6ZHQDMQhO9VHe68dwLdx7dFpGca0rRyugIEgVdzVFLsWpMUoayvjhNiz1AK_0oFAAMKdWqAFLBSXUYFQHc_Ozpo-nB4fLu_fc-eP_tN750586nIJ44MVOgOJbCyat7qUok6K5VAWEcspmrKoIb07bPJBREVJXIEYGEhk0_WUwJTbpmGIbAIYQ0Dnk-bUTwYrX11EwnHWpdng8e-OVXnv_8409fuLb36P46Z83b1eHe_l1hIrx8evHBo8dfefft9z_6eL3t20lTxzput7NJQ8DbPKQgudTVdj2dTk7X66EvWn0xa7yvUWW5HSSG5fpiyDA7mthqKwj9tl8c78-btDof-03g1B6_fvwbf_tb33vxppYxbzajQZymyPhwOcgG3l_pD6ddn91LQcBSCgJABUADcwJEU8Kd4d4NwIsOufS5jmP59PHZ2Xr49hefq0pMnsdanduEaw8GlPtSAcf1ePLZg6PZrGGhVk4fPw3E03maTifkoJ6_8pW3bn9-1ytAiB7q__ov_-3_7f_yPyIuyOvx1aPZ3ry6_fmf_dn3vvONv3zvLw8Orm1wZMTf-73_dOvW1ZhSv11Pu-m0m59frAk5zeaPn5wcvnC4aCYhCJpvN5uhHyHK55988L0vvnzj2tUb144uLk5__P5PvvDqrT_405-Q-uFkntFvXL3ysz_5s7e--dX3_stfpjmf3Lt7_earD-9-8PmHH335O9_ZG49OLu4N2y2qNdNmkHUZcx1VAmQss0WKEoC55KIolxfnN158_qP3fnqwWACSVdtcrJab5ZMn591kTlcP928eb4CM4JUvvv5f_5__MfX9ul9tUaccNgSwWp-cXn7p3ZfOGXjtdVvTbH4Uw2UuF-vT08enN0vdVlytHt49f7Apw9CXPYjrvGpiWm3WKaSxlCbEbSm78SoT2DByCMNqvTjcT6HZFI8hnNWTG4evVIqnTx-y22p5MZ22D-_faefz515-4-Th3YMrN3Ku7aR54ZXXhs126Jeb1UatxiYRoVsE8NorAOrYzxf7q_PzdjZpHS9Olo5AXlOiYb0JQUoeHn3yfuomBaVU72ZttTwuB7iJCGi1gqlpEcEkQghqQERuUFV3pHkKJElKKSyMhg6wa8ppqYCW13l2sP_d3_jSf_zXfxlEJtMJMp-eriTgzksOiEjihCHGJjVgpkliI5aLEBXVojVEubzYglGtQGAdNzXaMGY1IwHwZx-FRRB8c3n55luvnz09YWyISARZpJaS2jY1yRy6xbzmevPVW5vz9Z2f3RZiSAiGEsNYxxBirUbsJZe2ibVkd0xdm9rw_GEDZGOt4KXD0AZeohtYbEhr2KyHGFmrBxZnLOMoMQE4I4EBUdh9QgNgSWam6sSh1iox2ejuJVcjYS2q1SRFVQ0S1Ao4aK0hxWqZJexG-AhoVkNMWouhg5mkWGoJTUOB1mfby9NTCansYChR6ji6R2JGCebYSleoODkAMLJmDRzARiDMWdMEiUli7MfxxddfTk1mhJPTy9VqHZu42fSILiy51CDiVcEVEEsuKUZjLrXUsuvXOYk8OxRppSBOioy1ZHMYc0SiYRjTJA1j3a76JqW7nz-kIONmRMQdwlEkqNPF2Wq6N99sxvVl78W6roWdu9Jwsx3dAZnVS6BwerH56lsvbzarDHteNQWuaoFZ3Xor7kaIWuuka1dDoUDVYOxzCbYch02vHGVUCxnNfLaYTFHR7fHl2bzt2mmqufSlTpqUi9ZqTNyXPAxlllKTGpjRehhTase6BfWIxGZQHEizQpyGvup2VeOc9ptwPpaXX9v_7KOLk9NN14axltkknZ5fpDblUrQ4tgi9WwUQxVqBkB2sZt-E0VT2ObQRVtvK2ixotd4sJPzwt95JG_KmqWXowC5raVpZb_OQPXGsah64Zm0WXPuRG9r0y9RFaOJLL956_71P9ibT5abX7Ldev_b-H33itXpkMatWTIgpUPWMzM6ITmAGyNUqCeqotVRkqbuKXjUXI2JHFBYh3IWvcj8EarRYM5laqeNYY0rIHgIzEQD02y0SLLe9hDiOpZvWkBqtNXBYr9cppX7YGth-kOvXD-eLriV_dHa5mHBxS20ai9ZS2yaouw61EAQHFiqqIUpkIcLNasxZs6sr9nlJ7kZVUoBSEfHW8fG9kxMBXg_jss8tc-y4EqlWBK5qq6FYrUy4N504EDN0bTL39bbWahh4L4gqjJsRCXKugXbtUgtBwI0R1X3MSoEu-uoERCH3WrVmVTMy82yQSylrn6Rm9xbUTpqL1VBrqYggVHOW6m5ipYDKep1DpFU_qgEaFnNm5EKq5gbgNJs3edQ-58OrB5fnl64-W3QOOA55khoF1FKaFNsoqgrm6oYCk65TL01stZb9-bTvB45RWSs4AkwXHbH0Q3bFadfUwfJQui6y8MHe_PJyE9oUAh0fHngpU-LptHnw8OLK_lRrXW76Kzf25k3oh6JaDg9mMUnJmkKwoSxm7ZBz14g7gNcrx3tWbRZbDLA_n6w3BRnQadoGM5sfTYbtJkROIQBQNdtsS0yRXIlxbzHb9sNikvqhhgmZWyklxtbAY0hWw3K1KUN_uDevBl51PusePzg7vjpP02a3iwkIxBI8hASYPLJgY0HCMA7kIXXd6dOztmsm05adSsmgmdBDommbcq3WZxGWTnLfE3mbgmrp2jQMQ4qSmvby4vLK4WIc61jKfDJh4X4c61DaGJg4cyEABt_fazd9aYTDohuGut1mUu8mzWSvOTtbN4rVTUuNXLOURtJpXptaoQyARZUcKUAxK7XEtkEjDThsxxAJ0W03Ta-KMYBDM-mY49fffvFf_Ov_VPrMyASQukmtvZu5gaE9w3EiCVPe9I7UtJ0LlDELO6IrukigOkoQ16paEYYHDx-9-MqrXdvkIf_0_Z-89cbbn3_2ESRx97zeECGiEOMzWJ7TkEchNiMWdocdO9bNXRnEETDGuB3GFAMFHvuhm7ZatYmxqnaTEFk050nXbp8M85txLIM7RgkKoKWS23MvXt1ePH18JkG0vzxLbbNZrcpBu9ibL5dnt-8_aLtAKS4vlg5-eX55eX55eDSdTlOuuWvk_oMH2TgIX56ezydpsxkvTtfVodKoBtO2aYjOz0-268w4xTT72__w-4fYfvGdF84fnZai1KTLYSQ1l66W0gKtV7kWi_Pu1hTnLdehiMCO-LfD6jm5qUWEnfcql-yEYwUhWl32zaxDCqFZfuWF5zK4kBvA_Scnr7x0VQfbP1hsN9sU0jj2dx8_fuPV54_3jvptvv3w4fGNw6L55OTk-nyW-9xrfumFV5ixaN1crMHgwacPrr10cPkXp9euHndl_O2_8-v_8__7nwoQel1dLI-vv3Tn4ad5vf0Hf-93_qf_x__re3_rNz_77M4XvzDPyrPp5M79B7defPliu1WvzGwUxmHLwHtHC4l4eX7x1Xe_YhWaJk0if_HVm7ny6zcP3vvs_OnTk9e-_ObnHz-IjnXdHxwfXp48RrdSeifq-21EmLd75XgpwLPFdLlc1j67OQkUhXfeen58CkdXryOFR_cfOeB2GK7sT0ouJIwiiThv-_f-4hcvvPLCvQePPr3zcH9v8f6Pf_b8S6_dee8X__P_83_abLfb5WrISlaIWBAlSFUQBiRyhTEXQoipKWV0QM3GCaDUlEKUMG9bbrAJrZdhGhorIw95c7kCI-0rOTm7FejHZeoSQVhfLNWhz3Uc8tPLz3QYHJzIALC_KB3C-d3HmydP094-l_rGW1-_8_h-LT2F2LZt206ePnm4O98zQdPO1usli4xj5ZS72WQchmY6CevlZrURsqZtbOxrKQ667bdhcQgOJJhLPbr5ctM1HGQc8-HBYjv0IYbYNujo6gJUat4xJg0wxmBupdYQwu5kQMAAUKvGEDfL_tW3Xgsd_Lt_8-dqHtpQ1d2UBEqfDSylMI6aEkOIMbXkBiTO3E272I8EvN6OVutsf3Z2cYlgu-xi9UqGgpgkOICps3RI2evo7nUYYwhNbKoV9QB1JOas1bRKEGD2Wr2ygfdDKVpTSjDkWtzAXQE6Tkw1lwoYmDgE3BH7gb7x3W_lbJ_du6fOH338wdWDvYcP7gcSBVHT0DQIECI4ABlEiOgYQxjNgWEcR2RCEgAsecTAzEAIz9AlIZKZkxOImwMCoosEAwtNO25XKMQiEbGWDAgxpFpzrSbCDhXAAUFLJWY3l9CkOKJBLQNLKP1AMTCxu5sDh1BrzTqk2I55YEICQNo1PGOFShHrWLmRNrX95WXN461XbhqWzWpLRKUMMfDYj6mJKFS2FQgqQGDUXKrtKgtBVQNL1apV3ZVjE1IahtHdixZGiTEszy-JgyGWsUIFCnx-tpzvz2optZiDtt0EidbDSISUxAHzmLskTSvFSlUjdwE9uzgnh9Xl-oXZTWS7frh_78HjK7M2BRIWQgRAUy25oIMQq9eSq0VLKQLxdrs18NiE48ZxZXU7Trr2dDuMA5mpj3oofFbySKSE2yEjy2rMhGQEhIRIErC6183QdAmw9P12Mmn3U7Na9x2HWRser9bd3qIGWp-sHfPJqlzvpmKwvigAtt5sYzufd83lart3OF9uelM1taAsxuhluVwbaGxSPl9rqaGdM4BeGhF6R2kq_cWqm7SOsNkgiRzPoD_bXjuYPF2uY2xlW4R7kjpZTElLIIoxTmZd3qy2m_W1l14ursvL5Qu3jsl42GwPDyeUwnTSqJsF5vjml3yszOKgDuYGtbq7EQkiVTUrtWlaIjHdgfUxtq0zWVVmsc3WmSkErYPmgq511HbSmhsiSIrI9Kz-QtQ0bVHdDDm0guBoaKZtG6eL6ThkaSIztsKu9eZsRiAfPTwBtIO9xfGsEyc1ADQQdkdk1qpDGctYpvNWMBDQar0VYeYw1OxqQPDSreNtX08vlo4wlCpMs5SmTfPgZDXtgjHnWotZVnOHPutoNp1EYDpbbsaiMbIQNjGBuUhgAIli6shY1Sqh7nJ5hEK7xg_kUivAWG21zduhUERCGrVSCptSLzf56eV2NG8m7XIYUxDNddKlbL4dRkLJauNQSvV20ph7TGjm_Xq8vOiHMlZwdVtebLtJQ0TI2MREQikEBiCE2XSahzEyxzaxQwicohBzE1IQFpEmpcliWnIhJgZo27SYTjbbITLHyBIDiaha4JjazlW1WBAmFBZPIY65pklDTCzUSjiYT1uRQOwoY5-nXTCD6WK-Xm26Ls0mDbgLcRPDfN6RadukJsh83nYtpSAxxjLWWdfFRG0TXb0NnIIIALgLIpo1iUsuqN62Kec67cKkbZrUlFxns5YDBaKclcw4UDdp-qFcO9xjxJTifNrlvjSNtEliiiHQlcN9rHWSKDCnNjDAbNoyUgiCCHnM4J4akRDLWBhh2jZxR8IOlIS361WToiG0k0ZzdfMYRYgpMhNtV5sQY0qhaRoHIHBTa1LYudQDSS75yv4eEQbmGCnFgO43bx4gUmoCKPhQJpMWmKIEJNSsi_lMTZsuhhjAAJkMn4WgmMDM0ySZGjNVrcS8u2aRAYl2myg358AKwIKu3s0mqnztpeff-8VnXaQxF2d0ENVKDA4IBOjoBrCz2CDpMCV7BsYAAQAASURBVBpojNFBGcnMJYWaRyJ2UzcVFhdSrSHypJtvxq0DXlycvPaFN-4-vMcSJRIwmTogEQIDaTVTIARGHIc8m7a1mpqZGpgiys74YQ5mZggkMo5D06TdnxRDXEyiOY457-3NutiUDONYKkI_DgJ8-_6jr77zytOHT1ary08-eZChB4hl8DZh207Hkvt-iIGz6XoY8jiGyFqHvUWT87Dt8-27j2fz-TCW9eU6TtrNMG42_bofFVwwLq4dbJ8-WT5YxdT94__hd373v_7hr_3y11vA1KWSK0BQCkGCFmtCJGRCGIuxCKQkQn_xwee_9M4bhMRWwKzUwiIVIJsZ2M7hcn-5Gsy2VYGpz3mxN22bMJS6Wa6PDmbkBEgc6CfvffLWm6-en63bNtRch3Fs2_TP_83v7-0ff-ELr31-frodNrcODt987eWn9-9fPzgWtX7M1w6v_S__278gQCDsus6s7l-9sn98DerQpvbeg3t37zxd53E7rl7-whdPT58mpnnbLvvl4ZWrH_z8J-ijIczn0_5iGYhvvPB8FGDAF1968cfvfy4p7F87QMC33v3qw8_ff-7Fm99658vDuApeQvS9Wcssr958_uMPP9mMIxLnYf3k7oOvfPt7m4uTzWadxxwbdqeLy4vD46P5ND15-JhFaq4UOBcz0AKwaJvvfveXf_wXP_vyL3_7w7_8OQeMqdtcLFPXVi3bzRbMCRkkNPvz-3cezCfdk_sPSXh1_w4glTzUXEgQnbumjZL2jw44CJHsXdnTXOcH-zGE6f7BdLE33Z8zC6coGJlD000pNUAi7XwYSmyikxiEqnF6fNDs7U0P9trZbP_Fq9xOb731SjtbVOP54dH05g2v_PavfnMymx49_8Li-o3D5597-ctfObr10s033nrxS-_G_bkLnz56cnZ6__TBQ81jFzqODQWaTJsgHES6-XSz2uRcah5z36_Ol0AIBl4tSCDzlKK7ay7jdovgFGRx81rsJkoeJb7-5bfOLvvKttqMIRAidt3s5vFiGEoUNPDq5gZqSkIA5q6CxIjgPu0mAC6EieW5548ODvZXq-3p_WV9trdyczQwNQOmTZ9nsxaIgohwcIQoAmAYBclmAX_r21__5Paj24-fXF6uq6kruBsG0VxEuFZFJnEAJAMlcDcjBwm42my7eTdsxxhCQFaAXEyEA8dqGlNUt835upm05pBaGcYcUnBwpgiA5LYZ-9S1xMRMHJiYWuYffPPLe6n9i3ufW-FPP737yivPPzo53Y49SgRCBAbCqpWIHHayWFSrEoiiuLsh1KJN2-6o_FZ8d3wyhRCjFqWd0BccCd09hKS2iwaTmj8zCRASk7mHlNTVzYhYq3IMOxDc7r_s8MxAICGZG-zi-MhNOzEzFnLDKAEAmIWEHQFgp1RMbs4x7DTsXROKlm996c1Xbj7_448-fXx6ebHsa1ZhKoOysGl1YC0gO7J-USY2NQBARmJRN5FQS5EYHJ6JDlQtpknVERHJITCrKQurYWgiOtSi6AAIhAJMiFBzqWPdaV22Q5bYVlMtKkKqygy75HDeDN_6yhtW8tsv3UwcBBmIxpyRYDOMKcZSqsTo6tPFTIgdrB9yatI2Z0IZiTY5u6MCLA46RKPNAExn29I2jQtp1aaRbdZ1vwWGWt0ZzWkRO0MExBCpAmy2Q4hNVQ-BgVBElss-tmmo6g45KyMVhDEP873u4eOzmutisaeOwr5ej1qUDQDUTUVgXI_gQhJgyKA11-yTBKrsjqWQgxZljmL2_XdfwnV9ujo5O1lL2zx6uuqO9kotZTNYsV1aCdBNUVI8OFhcPH3azbqjw72DecfquRQmDpNuuNiuLrYpxW46YXr-DTAkEQ_OKQIBERIyi-xE10wCYG4OIMSUum6z3sSuM1Um2GFehs1QyqhZ20lr5ubGzMwhhgDq236cTFtglCiGjkw65joWEtZiQCApSpO2y1UMoVQbM956-fB805-tVvsHcyA4aDoCvlj3DoaAvRoAAiAhuJOpO0I1a1Jk4TGPQWII5EDmcL7pS65p0q7XQy2m6qPZwbzZAVEcsda67LMEKQCAkBXGrAG5VpfAAREBTWHXpmXGbT9m9X7U9ZBd2MHAIQQ2cACo1TNirjDUOtRKSIkZmZd9__DpUrpmKLoe-nEoITabdf_kdHu57h34Yr1dj0M13Pa5H3JsEpEjYql1GDIHQsHJImn1JiVhVjUURvRSyjNkCjKTAFobIyGSQgg8bdtSqnklYhFBYtV6fOUwD5mZay7dpAN0YSQCFA4hIGGKQWslBAkUY8g5pyiTSSeyKxh5ipKYDvbnbioiQx0ddupBBrZEFILM99pIoYmxbdK0TbO2m3Zh1kq_HeddI8QCEGJkgkaEkS5WQ9dQE0RIUhCRUM3bLk27hogdsJtEBLCqEkMQYYQmBDXjEDhKDGHapjaGUguaS5AUZbHXzts2iuSxhBi7FBeT1CaZTBqtiohhZ3MTIgJGTG0KTGbetI2qdk2spkyUomw3fWoaNXPAoequObqzo5Sqfd-nFN1NRGIIRDCbdiKipcQYpl2rtUoUItgdAESklDKZdHmscVeSRWxSaJqohg61jYGZ2hABIHQhEFqxEGNIkQQFiQBCisxESKlNBrBrvStqTIkQd2tWFpSd-cHd3SeLxbAdu2YKroS2WQ-qIG1ENc2luLME22l6iZ2BGUNKato0E6u7YKgbGBGjq2ll5qrPHgzjWEOTCDyPQ6m63iyvX7319PGDWn3T9zlnVXcAV7NqpjpuRwXjyGM_kvAOj7hLxVQzQIgSkGgcRxExclc3NwBy9_Uw1FI2_TiMozRp3Wd3VANV78tY-uHKlQPvxzoOD56cbdYjp7S4ulifriaz2VDK-cn5tEl9qUO_cVUwu3rlgAgA6ORipRRrrXljl9stTZvPf3GPCCKlFFhzOb1zioP9D__3__Z3_tYPjo8Odr3_pmsCEVQQpF02GoGcsJRaahEmYdhuNrNp-9lnp---fmtYj4SWy0jkveN2KEOpm814udyu1G7tL9oYZyk2SRJx18SLi-16s510sWsiGiCRWrn3-PFLL9woeUxNFKKnT89me3sf3H3gyldvHQZpXnv9pf1m8uUvfuHu7dtXp3NhznmcdrN_-W__dzM02BXn5KPP7nzrG99yKsO2T8Rfevvtf_fv_mgcxv2D448--CxvlhfL1fs__vH-0V6_3A5ZZvODf_D3_sGVK_uLw_nR8fVae9_WV1957Q_--C9RcFhvtQ5dF3ToZ234b_7u3_ujP_vTWUxa88nl9g__4Gf_6__-B8fH1-_cvj-bHyyXm7GMq832-RdeOH_yeLserj333MXFac367te-XoZ-s9lcvXo1NGmodnG-DJ200-7q88-_-eZbP_rJzzHyw89vE2Gxapqvv_CSDYM5MLITUuLptYNA3KR26MerL92oVdHJhvLaN97enC1jSmAmIiElROQYLWtqG3calEs2dTAF9EQSTeH_z9OfxdqWZel52Ghms5q992nvuX3cJvqIrIjIiMyszKpiZXWslixSLIqUJcKgZIs2RBg2AdsQ_OIXP_vBhgEDNvxiyDIsWyZMixZJyahiU8ViMpvKrGyijxu3O_3Z7WrmnGMMP-xbfrtPB7j77LPWnGP8__cZMbAvCsbB1dVYymR3FyjEdree7Fy7_dI4bKWzLiluNrJ7eA0pjCUZMLkwPZiBYTudmaNRwDAsVus4nW5kHCUXgf3bd2azHefad371V5_89CfrxcXl8bPHH306pry4ON_fv3H-7FhVRCD3Q2xrEwETz24YehtlG4Fg5ywLiJShV3MPv_pBt-lC2zax_ua3Plit1mTi2AGCJ3YuZC3DZuzGlFRVwEyC92aKZGmQpo637tz2TMFhEXvr1VtjyvPlsOzH9WoTG7fpeilZAGJs0pAM0ZSISUf1VazbSMwxRkLynkMVmMyb_d43P_jy2ekXJ2fz-Yqdl63mU0BUzCxpkazBc84FCEspoLCtU_Xd-tbdu5dnp4RkYorqHIIYohKwaAFAAsYteRPJx2oYU920_aYLzplZVbfbS41kMcAQua39X_2Vb8Co__Lf_HC9HrhylxcXv_C1DzY5D12HKGkUQnWEqKCp-BCIQUom9kaE5NGUyb2I3SPaVrFJzoBwS81HsJJ9VUsqZoCeiRhNfVWZiinUdTuOaUsvFxPaqheY2HtDIMfeBzXzkQlRzcgHIAg-AgAxmhqRUxVkJscqAmbO-zJm9NFM1KyObRYJMTIhMTvnVOVv_8FvHFS7P_v80WfPz8ex5D6hFWQkNkdsqgrqnQctzgUEMFXaAlgIiVlKImZAdOy3lTAkNBAkNslgCgAuOGZfpKjkbdFMRIupix6BJBfnXLcamqbRMrq6ErQYomMXYrs7bdPQQ5aU0-uv3Htpf0eMbh_s1OyZySEDgAFUPihASonI6qZhZBnTcrnC4NebTgySWayc97xa9wPYkE2LknOTOhLimErORkhMHNh5F88Xq6ati2BRZQeNi6Ooi_jkclVXfjWk_bbpxuyIxpyzwIBSEFebUUydg9kkHG82w5DrqkJCQLJS2Lv1uqsCS1eQsIDokFWTGoKK5MEFb2IuIJpBUdKiQ_bsXHABJC2Xb12_eW3_EBE3JV90w3LecQzjZq3daAquDrlkF4IxeaJuudjd3X3j4b39SXu0t_O9H3zy8OGtVcnnTy-Y0Ig38zXbnZfRwMSQ2YqVQWJdgSFoYcC_wPQzsmPPHCIwkWOTAmqqwLHGUKfNkrbcXeKSRlHxzksWEWXPoYql5GbSppSAeBwTIEiR2NaMWHI21badiJa9ST2OKUScend8uWaHy9VwdHRw687k9HzZl3y2XI1ZxyR9yjllcm7VDWMpRI4d05bA04_Rs2PfhLjYDCfzdfB0cn65f7hXHDy_mHdJHJCp-eBTKt1YkhYDGstITIycxUysqn1R6fpU1Joq9OM45jwkOb1cj6rJwJA2YwqBVdXA1GxMZTWmUXHdDYIWnTvYmXnHntnMrcfSFy0KFIIZZhEGMilVjAIiapusQ8mqEqJXKZLE-zCOSUCRQLPlPrlIiCg5I3Iac90E73jbsWZPiOiRJ7uNY6qqiIR5TN5RFWsgqOrgALxzoGXbf4pV8ICI2NQBAb1zjimlXFWVoTExiDCyc54MfaDZ_rSMqXIheJ62rQ8c2ZtJTrK1WnpmyHKw36Yxa5bZ_tQRBqYYfPTOEwXvg2ciCAQOMfoYAzEzgkwmvmJHyApGzKIleAoxgELwXAWvolbMe2dqTCRb4RSTijFzFZ2mNJlUkSk6H72bNpXm4pnr4KZ1jJ6a6CfBg4h33nuK0VkRJiIwLTl4t11ZMHMaxqaui4hjipU3sTFnR0jknHdD1w9DCsEXsHYa-35EgBi8GCCYpMJIMQZCa5vaTFTMeyopx-DJAACCozoG59g7LkMOjrNKWwVCOtifuei79YYQg_dE-vDOHqITU2JCAO_Cdj_pYlAD7z0CAGypHQiGzMRMW84mIaMBEcbKuRhyHmc77WJ59csfvPvs5GLbAC5SGBERsohqQWQ1A1AiZCIgMNPU9aFyUgogqCgzAqBmAwIjcOxMzMWwvrqc7u0N6x6DH4dU11U9naxWVyEEk4wEaSiKaARgBuxyKSrC3pVShjFv53y-8qoKiKpqzMwkpogIps4zbt2dZpu-d84Tu75oM530eThbzLWUdU5tHR59_vHta0fdatNLXm1WsQovv_fgy88f3T06FBUgIcLFfNmtOlCsGy-5-Fgtl6OLdR7y0Oezs4thTMuLZV1XcbbTr65WV53D6j_8X_6dv_03fmsamwKUCpSiUDQwRd76IAwRkAjUTMU5K0XGIQ-rYXU-3njp4Ieff_HOu1-5vFw_3Vx8tOqGjTJz8CE6msSwvzu5Nolb2XlF5MxKTlnh8mrjmabTRosQgIFlkSdPzm9dP1ys1t4RgVV1-9Fnjz_6_PN33_8Gki023f2XjqZV9eYrtx8_etrGOka6uLisqvrPfvCj1WpNCIQkqt0w_PJvf_vxl08P91ogPjrcOV9dSi7Lyyvv6NWXX6t2d6H0i6vNr__lb__eb31rv63Pzh6v0jD043Rnd-yWbHT96M4P__zHOzt7qHLraO_RJ1_-_De-2o3jjz_60b_-7p8_Pjnemx2N6tnV73z1g_F8YcxPz55WdbNZ9-Ni8-rrD8-Oz5OU-cX5O1_9-uriZD6_-so7X_ny0eNQV6nbrK6WIjD0Y7szrV314OHLZ5eXadNdPn2mBdR0Z28PwB_evLlZXJVBAAERnUZ2cbNaVqG6vJgjhNT1aJyylL7sHB0tjq-A0BAliRKWQbt1b0DNdJdDVBFTbNv26K07m6seCWMz8VXk4NOoCpBLYcdl7DGgoaKDOAtZigPa3d_Z2d_bbNabfuXYO-8347qtZ4e3HywvzpgxtnFnOhWwnFK3WY9j7zy1OzvtbHZ1etbs7CLz9dv3Dm_dIIambTbL5d7RdLNaEWrVVLkfCNixpb4X1XoSmEhSNsTcZ08OrWTkl999ZznfOEdtM3n1we2L5Wq-XKlijI7Zq2pTN4v1BpBFFRnZkeTsiR3a6y_f39tvU5aSxTVh6MaffX7qvK-mzWa1BsJNl6QoEOeik-mk70fypGLsKg463Z-AUawq58J28s2BQnAzh7_y9a9-_6efniyvxkGGMYNREchbmVFW8gwIRdR7VwiSFkLeAnLyUG7eud2t10UKgJmZ89WwXUhuOZeq7BwxSimERISqOg4Dg7HD4L0pxjjJMooU7ygSlH787d_4xXG5frZYHJ9dbPnvSX1VV4eHh2o2DDmNg6oSIDORY83iYswp-xjQ1LlQcjbAUDVpzEQAqiFEM0FCIkAENEB2QEi8NUwCKFahKvqCmUEIxAiIzIy4LeCF7bSFmc1Mi6FtFe8oYkROS4kx5lwQsPZeDaQoe6eiCBZjJVqYiR3lVJxnNSP2rmkY1Hk3av71v_Tzh037J9__88eXi5SErGguTFRyISI1BTITRXZmyMQABoghhJIKMyPjlm-nRb33pRRRBYCqnhTN6FweErMjQi2CwGYGYsDYDYnIsXMIKCWH6EtJxDEXCaE2zSjGjkvJbFpV3jHN2vjKw9uW7cbBtA6eCA1QVZHAORKD5WrFZJOmIfMK2rb1llTd55LNxlwsCxMcXt_xZrf2ZjDmIsKeKaCSidl6TJO6FoW6cot-rKeRDbVIFb0jbNk1E3-66FIqQg6RxBQcdcOgguTcUHIqRYAE0CN5pm7IaRiHIaHjbkiIVsbMZGJGiJJE-kyMzKCpmBqMyQZBY-fZpcKjMvuxgGUbr_r33nnDKRzuT5-cnJ8t15tBfKzG9WpYras2xp1arQAQOx98VXR4cPf248dfvPvqy_fu3naaV-vu0ecn_TCEKophCMDxK-9JNrStegLYs0kxBShiBV5Y-7gSlWo6DZNWcsmleB9FpJm1aezKsAFUUAWDNHaWkveBiJFVTbIBe6qbSUkpqxFiGrOIAFouGmJwgfp-yClntRsv3ZxfrVr2nehqM-Zc2GNbhfVFf7Fahjquuxw8dznX0VdN5St7dtXH6Meik7oqUjbd-OhqGZiRqYAqYFuHEGJbNWay2gwnV6v1kF3lukF2JiGE0Hh33qXWITBVIazH7JAULacybaokaqZFzUQnbRyTZtNBYCxaTHPKoiUwB_bO82ooF-thzGXL82iiN9GmCt2Yhlw2Wcekl8t-sxlddE3lN11ZrYeiVgzXKWXArpStzsPAnGNTdZH7IXlyUpIZJFEfmIi3yEjvaBiLJ5ruTsgMANjATKez1ntumphSaaqKwJq61pyRiGHrBkZVNYPZ7kxSjsEF77xzznNTRWJkZEZwxKXk4B0jTiYtAnpHjASqB3ttW9UgcnZ6OZnUAOAdM2Md3M4stjFM6jp4N22ruopoWnmOnk3VOzw6aKQgmUZPZNZUTtXqOiJhGXOoXNtGFXWOSy5M5Bx63lLegJn8VlvmXFsHpC383hyYd1R5j4rsOTgGlSr4re2LGJnQMzNBE2MqpQpuGFPJJXhCBee9iaqYgm4VaGBq2wiKaEoFANi5lAoSlSyOeLsRLlmBUUUJwXvHSMF7v4VCIDGoiKoaA9RVVTkXnAOwvutyyUcHu2IQPSGaaNnbmfoQciqgUHmHgNEHyUYhRu833TipG0SToj54YjRABduZTErRUtQ52p71QYCIABCZDVTFEMy7QOydc9PpDNWOXn9tuFwsNgsq9hdZWy5beyU7zQUIHJGZSs5EW-wLkCMiRtzuS5CZwApSMBAQIIMsqqYAUEo21aur-cH-dS26XFwBOEkZCBVNihmCqEop6MhAARkBVbKCdpsewMZhYB_UTFUmk1ZFPLMBgloWVUVirwCgKkWOn558-tHjxflyZ68tyYjgez_57Jfefuv48jwXmZ9ctbP9W3dvPPrZ0902NrtVv-qHbths-sgBvbv70q31pkNGM0vDuF6szs7m_Xp9ePNo8fx5Gvrl8byi5j_-B__xX_ntXzyMk5wFkLY4PO_ZtLDCZhiZMYN5xlSKKaRhXPfjMJbeRIZ83qe7948-_uT4jVfvfvd7n7nD-qX9_VkT9po6OKwcx-gD4fayQ7B1LUEq2g1lyAVIQ_AmhQjBYLHZAGBbBzAkJMlSJJ9eXX3x-CQGvpovdqfVK3fv7MVw7aCeH8-96c7O5PTyhIEX8_mnn3wJwIaoaA7dvbff6JeJAw-rFcXZV77y9j_8r_7Z_Qcv6dhPdqf__E--w4aL5eo_-u_-rRs3r637bmf34Patm6vV8Ox03q36z558ce_VNz_67NFq3Y1jqutqSBm0-Lo-O5t3Y8rFPXt2stx0_-7f-IP_5l_90aZb_-ynH99_8HIqNl-uyNFsb1pP9zfzedf1WpIobtbrdz54_8OPPuo3Q4yNipYMQ5EQ43T_2lff__qnn3x09uzp_PSimrVm1rbTIaV2Eq6Oz0cxAAbrA0crsNl0XRLPIQ0jqIkJM5WUgAiKhElEEao8GmguHKp2Z7fZa4k8lILIhenk8fHVYhPbygdXpKiBY89V6DdDLuKDr5tm7_a-qV09vXR1U3L2vgKG5eX6eHU-mxwOOTtfTSb1sJpz9P2mRyJin1LZcgMlj97XMdZhOnvy2cenz5-0OztjSXu3bgdHu4dHp8dP-ouLy-PT9fPjbrXYnF4YpOBCt-kAEBSkiJqZYkkJTLQkc_7W_Qfzy1UdHfvq1YcvPXr8tG1qXzsQYEbP7mK-JGZmVpVStoZM_rl37u1W9WbIzHR2ulyvVlfz5c7BzpjHyU57enq1Fe_knFzkkkXRYoxb9VUuFmoOlQ_kRVRKYseenYFWdVMFd2M2--ob977_0efzxUqCGzeJvBuGQU2BwMCAKadcc9BUDKmIOkRkIkKDsl53zaQtKSMzOe-dBwMFdc4LiGNWEwAeh8zk1BRMSylbaZdzgRyzc8RgKkjoAJo2_OYvf-t7P_j-0a17H33xKI9jL-mbv_yNcdg8ffoMmb75zXcjhdOrhUNLORsAgKLZdtAiop49oDFyrKNHRgMOvqRcNxWqATiVbEQUnAGg2jbCwJ5zSkiooAxsYGDGTAjILjjvikrwwXI2A3KMCM45LbpFMYEZOnI-wJabaua8NzAfmAC3uhRyTsyc8-wcEgIBsyNmU2XiVNKvfuuDWYj__Ds_eLbo1-uBAyIYEaOj4EIWISYVJcdgoqCAYGZZiw-VqYxp9DECgJkig20pSKpAQEBiSt6pyDb-lEpx3gPYC4OqIZo2VVDDsR8BkX1QMB1y9BWoimYBS2ls6mq9Wl4_2D06mN3cb5vIqJBScszOO93KYJkMYVLXpDQOaSji61hKBgBBbWJw7AysqrwVnUUXhPImdTlPpu16M1STOql0qVR1AKQq-AIWkFisH1MSaauYsiLSuowAMIrUIYxJAazb9HXTRIZMDiSnrKPkses5xGwlpTL0IzvKqky0uuoAldhKymYGhKxWxpEbB6BYlMYcYjSkctGFnUqC87UPzo05ff3dVyshzWk1jJ8_OR-G4lxdxs38-KTd3RGD0NShDXU7sZzQFDUn01959-cO92fHx5eK_vj8YhiToa5XXTcIy9ErABBiBCR0gIKggmBoBgjOewRj5xFBFUJsfBVzTtsyHwUeVwNQga0ORDOacV35EMm5YUhGFOqq61MVYoxxcbWp61hMJSsChhDHVHLRrAXQACkNEionCpfL5WzWdjIauMNpW8pIwG0d5l3P7IRs0Y-gcHzeMWExkKLDmFabftkP0ybON2P0fixSNTUBZgURTWqKqESrftwMZSjjyWU3bWMweDhrPJOJDVtDL5Fj2NufkOHQj95xCK6dNMOYN-s-gXIIasU5QrTcp9lk2rb1ps_zVV9E6ro2MxA52tu1AqkUEQDEUfXJ6fJy0Y1Fx1E2myKqnn3OxRhSKaPqKOKdKwAKyEzsWLOsFhs1zVmAnJkykifSIj5y1YRYOTJ0iKAqpVSBCdA7PtrbXcyXsQqEgKAl5aIAprEJdQxmwATEBKI7uy0abI-ebVO1dRzHFL2XVBBJDYJ3jjFUkQFDdFUVu83y9tG1KnoVrevoHFV1laXM2prEJtHtTds6eB9c7oc2uDq4OnATfHTk2BVRJqsrD2aqVlQdO09U-RBCCJ5VjAgJwDvOuajaVstAhI4pBm-ISIgEnnl7UspFovd1FcnQEVfR5SIHey0Re0dWtIrsHVsxRkTi4FABnSMQQ6RQBUYmAjB07EoRQoohIFOIQRUAIfhgsF2KWqhCTmXMuZRSVTEGn7OkMXtPzFTHICJkON2ZOEeeeWenIXagoEXqKlRVDNGjWVNXjrGOYTqbBGYirsntN00yLWqIMNudjsNYNyG0rh-SlIxM7LzzTkX293Y3y44YQZUJmdCHyEyASEzoyBTBwDMBETkgYABzMV4-P3_za_c--ckjyULBSxJfRTO1IqBKZLj9LMzshXzY2DHqC7QfqPrAKgoIiCxiCAhm6Knv-npWEZAJBF-tFpd3bt_qx01WYe8QII8ZYVveKrD1kxUBJFMFVRF1zoGp865ICSHgC_ggG8CWfp2L1LFyzpVUHG9_Z7h7OLnz8HZw3nNYL8fF1WlsnI7w5bNHi8X65s7Rbru33iycrx7evf_hTz52jCEEMr1-fT94N2yGPGoZ5fz0cuxT3JtCHi8ePx_nHRf3d__ev_8H_85vNnWlakhkguScmuVUwKSIACgxOYcplzFLMlquNwUAkQABmYTg089PXrp_97PHz1975eGNWbjR-Ia4YRfItjRvNVARU_PEjtGIxOzZyeWkndVVyLl4zwygIoT4-PnJ9YNrIopIKkkFSPmf_Yt_eevOjdXV0Db1MKQ71_ZKt2oqn5Ybcbize1hGnU0Pbz54-P_8h_-vqqlTnxmgiDx_en7_L73xf__P_9GXnz3rS_6zTz62ceg343Tv4KJfeXSX5_Pg8dVX7k6rnYuL8xs3737y9MnzL58X07cfvvrhFx_dvffG8_nZ2GWEsrs7XV8tr12_6X29c3DYFXv0-GS-6Jer9Q_-_McblYv5-vEXz8jj3dv3vvjiM2F-9uWT19_8uavT5-p5tZo7xzGEh_dfW85XAsWTQ4FSLLTBxSBmr732uuR8cXW6XC58CJnMfGzaeme3ZefnyxU7yjl7psOX782vLiGgd4Si47AxgFg53SojRdp2lvNIzKNmIlrOP_PNISGPJW2Wa2BqpxNkC1XYu3HoKy9FZnu7d958vQzdICnGZrnoAJ2oa9qpYBmGMfU62Z3Fujk_n-8fHOYsk51pXQUfnKiQq_p-NPTG3C_7NPTeB_TUzTcuhM3V5eZitXO4h4jtdKIZ7964m4c-k7s4fjrbmYzZXFNNZpPg_TgO0QdynoNDxaQFHaZVYjaTxNN2enhjHLP3fHDtEFlLPzbBtXXriAggFdmkkYlMZDptcx539urre5P92WQo49Pji-Wqu7xaxcbP9idjnwFxteiGYfCekSgnCS6QYxGIMWqxWAdmdFsusiMgTONYxYqJY11XE9eS_v433tuZTD95-vT4fNEPOWc7rGjeZQSrajdkQRADBi2eopGJ5OiDDAUdo1lJZbI73azWQI6d16ygwtFtwRgpJceeo0OyklI9mwybzXbmZarEzMEb2NaMyESOibx_9d79f_rf_vG3Pvjq49PT-XpZNa0f6dd--a9_94f_-snJyff-7GMf3I0HRy89uHXt5m1nuUgZxw6NyJmAMW5hBkjs2DlRFRVAIKStcgFMSsrB1yUXZgqxEhXnnPdeijBRCBEATAFBGbaKc4Cte81Mi2wP8WYaYtRSDNS5sNWrs2PAF0cGFQVEI2IileLYEW3j3EDb_QU6BGAmJhpz_-_-3q_U5P7pv_q3i7GICoCAARjqi_RUZ2CmiobgOBel4IpkBOLgwNTHOA6D914Vtlc0AmMkNVFRF8JfOOAFyel2KUdMhkmzicYQhiGFELJmJhxLOdyfLRfrWLmSMzIZAJjUwd-8sX-ws3t8_Pgrr78MIlXlzUAV1MzExiJahI2btvXed2NWKJrKmIsL1iXpc5qvOmQnosvFppnUvvKO0YeQ-0QMfcl1W_Vd2iIlkbkYpCyjSrEcHLV1vVXNZhUKtN6Mk6ZVM0bk4E_nq6Ztji-XYrped8RcVc1q2VeOV5uRJNXNJKXkA6c06FDAcOwLomkuqlB6CZXXUXEsASFn5YoBABCLga88IgaHDdcPr81mDkbSx2eX682QUrLcb5ZdM2ttTDqWUNUhuLHrJtGHhr_y6v3X7t5ZrLpk9Nnj56uxB-T2aA8QXO053H3NeadZLCiqYlEVISMXHKiy96ZmWlysgMjXdRq7nMpsd6ZJDVVLYtSSshFqygpAjskRooW6rmJAoDpUY-q3X192vM14GED00Uglp5IEwLJIM2mms2nK-ea9a5vVhupweLS7M6mbKg55HAS6lDKaMAnaetkdX3XBeXZAiNFRMUtg4HgzJM-ciqZSVn1OItGH5xerUWUATEX7XIpYbGICPVuurjbpYLfdn9YzdsuxTAMToc8633SeYBBpY-UYQS2GOOSMgEnK2eV8r50c7Myid-NQyHFWIcYxl9m0PpxNGEHMVv24GtLPPj--WA9ZtCBk1aEfjdgYU5Ehb9W9OIoIYD_kqo7rzVBXPjBKLtHTOJZmp0aHnpmzjv1QN0FUfOWJODr2iKAWomNHdawQsaTctHVOKdQB1MgQtwLB4Jhgr56Ukpu6YqLKcVUHRGwnrebcxICAksR7CnUILnhH3ru6qlwgE3Ge61gH9kQYgqvbSrP64GZNXXu8NmsPd9trs8Yhz5qGQFRkWgVCdEjebSf54NkxA5rRtnXgmBGZiREYII3FecqphOC2bMEYnSnE2jtHaRx98AzovBuG5IgUjYi8oyYG78kxMSozIaLz7JicI7ddSpnG6Bzjliu9PSiLSBXctk_VD8kRGcF2AUrETCgAachb8Qoibwtb3vumdggM-ELRFZuaiYLzJYtjqmJcbdb7uzuSNATeEmxicN6R9z54DsFvdzHO-Rh9U9dWVMXE1FUO0CGhWUm9JJVQxTxkKLBYrYChqnzJtg1jhugFdGuR2T7rAcGH7WcN3jlEIkYil7Jw4CpUVuDa7sHjL59v9-ZiksfEIVoZAxKolVwMgdmLZAUwgC10QUVA1RS2VFYTRQIkNLCcMxkNowCaC17VSslo0m02t2_cvVouQBQBNSsjKCgiELnDul2NI6oqWNEiRXIWItZtMVCNmSrvwWzrf8hpROLgYyrZOW-Si2hfcjudzqYtM3vguw-PiPgnf_aRHtVf_OjDcexvXb-3v7N_NT8vqN0wv3h-8eCN62nMs_0KhUpRUClFvvz0y6pqxn61Ob-8Oj3TFN784Gv_o__F_-D60d4oAkgqikpZzQysKKkAGTKAY0EsqmPSQTUXGdNYM23W67NFd7ncHG_GltzBzs6Xx8dvPLxXcfEELGai2wmBIpiqIRCicyjZsumQZb7sdneaItKNY135LSUoOvyTH_zszdcepLF3jkEMmJsq_sP_zx_-3Ps_d3Jyfu1wluabV-5fv7E__fL5aST3v_0n_9_PP__shz_682UqF_36O3_4HWYEcrkMRDqsNz_7Fz-YXy1yLl98-tmf_9ufXZ5d9t1w9uzyZz_85M6dm91g0Y2r1fDwwUs_-vTDLx8_CUBd7g8ProU6rlaLm3fvPXl8vL66QqKD_enV1WK232zKcPvle-3O_nR32s2XzO7zR4_Gwf7Fv_ru7nR2cP2GGuzuTS_Ortar1Zi6Ow9vPXv-nMn54PtuUwV-8OpLjz9_IjpeO7y2WK_6bn3t1o0ypnc-ePfRsy9Wi6txGNvdWRmBQwg-9MPm5u3bdTU7OzulUsZVbvZmoWouj8_aihvvuqu181TFIGLeYxllSOPuwdHJ8cn-tWuri-Xs2gNCXzW1oQyL-bXrhxycCACEumnrSdP1fazr2vudl15bX11MD_aTlvUAe_t7IoLBi5b9GwcHh4dm2I1j0zYhVqX0u4fXpYwWnGIwzN6zMVxefhnjDiBIVlSd1H49XxYZuGoouMvV4mB_f1pXq81iVAGjvZvX9-_cSGNp6gaRh7G889d_oz89H8aMBnlIZeyR1DOVlCj69vCoattUxltH15bn8-mkCTGqGREa2tPjxf7erJQy9gMQxhjeuHdr1jbPj88eP7lY9SMFbJs6i9V1vV51hAQAJoJGRGwGsQqo2NS1I4iegdBH34TIaHWImqWuQl3V3tvhfnvvxt7vfvWtN-7d-OLJ5fc__HS-6Td9KUW6DJthAARRLJKROPUJwQQK-WBijoB9KHlwzJJk9_p-GosZIKgUJaRcsiFup8tAaAaIJLl4dIakSbbhvFg1fRq8C2AKamASYpjsTu_cvPO9P_vR1dXJb__eb_3zf_GvgeG1-w8qW4wtd5sSGTarzfnJ4ovPn6w3q00e3njltTfeeq0fh9X8UvOgpkgaYpQioaq5jkOfnfv_p-XNCJGIHROhmBK8cH55Dtt_mokPUdWQgXmbvyZC8OwJCRGAyF4gv9kAkJ2CESMhee9ySrCdABG4EIhZcyHHBuBjpVrQTHKumgYI3dbGED0y_rXf-MUA-J1PPju-2DjnxnWHZqbYSzYQx95MEUyKeuecYwRQke22YXtNMTBEiM6pqZqpafQBzJKkEGsjYyTnXMmFvWPHqsqeDUBAfQy2teqAmCkwFlUpWrc1Iqpq1w_tpKkcG8LebrtfNTev7QbnUk7M2wuPKJiqxiqaovcudf2877OUbsxdKufrJbEfsxYwU2OEtm3Ozq-Y3dCnuoqTKpgJqKZcYh1UQMwCe0Y3Yu5SCs5HH8RsEmMSDZ4uF90i945947wxq2rWXAB6LWO2PpcsaogowH7LNNG-6-ppu-lS24TlxYqdCSmDiYgWIUT0ACLQJ0DjJmQrkbl0iXeCmCo6Z_bKnVu3Z03t_Sbnp2erq_mqpLJeL_du7jgXHNN4tW73ZmB5fbnYv3b91kvXvvH2azsu_NnHHz56enp2tR5KpljVTVukjKuB-c6rIICjIAAWNRVmZwJISobsm5QSEbPzyH7c9IiMBqGpSiqljEREBnnMBsqEMXqTstXgIYEZViEgQtVUy-V62_hGcmICBEA2phEplDELGDgEdPs77bAZ-1VnAgr42q0DKzKOeSzS5QGZRjMOfrkeU8mx8ef9pksZPQ0GRQC9A4JhzD7Qoitni-UA9ux8cb5coY8IfLnqDa2ATeqYpMw3wzqNpeRU5GB3Mqn97Z32oA2NEZg13h_ttbf2ppMYaueic-wQAGdtPNptWx_22pqJc7EQHaDVVUSFGEPl2NQ2Y573_cnlIhEshjwU67PeOpquRkWEQZKKsaNNyrtVNaQsRH0pY5e2oUAwzEPKKV2f1RzCNqjdeLYiVRW2MjVGJCPe-kII2JEagmnT1N6T5AKGRAim5NgxV9OIYA69Y2raKvdD20ZPENg1TfDMTfTbgaur3FZn5pi8dybmPBNRDL5tYlPHto21D3lMVfCI0FYhENVEu5N6VlXMHEMIZN6zD1xXzgowE5iCWVGtgnNEPnpECMxEBAoIwOzUzAe3JfmYQRVcCI7MHKNzyMR-a8aCbXKSyRExVd5Hz6gguUybKqtKlhidFgNFQnPkxAwRiMBtK1CAhuYdOXLBuW3g3MC855wFidRsHHNKW8c4qpmI-ODzKOyIAMx40_fOEwAQQPRMSC-iQ6amVtdVYB8rV7mQU0YzcshEqtbWYbnu6-BC8LJNjBRRLfWkkqKoSoS-DnnMzvt-1aPY6fNLC4REl4tVcKHvc2xiGTMSOsdFM_I2amoGiEBmAGQq6qooKsxMnqqqds6J6sFBM7_apJQ4eBbLKqVkZAbVykcxVQIDcEwEqMJWtGpqKcUQzHD7Q6RkJRQwVFNVRHTRqRRHzH5bkXcqUmS8cfP25dVpDHWIgQgVtsFYLGDBuQJiqqrby4tJUSQCIiMEhCzS92Me05aFV1WViBDjcrMmZAX1Luw0NTGDFBnHoeDV6RLK8vN_82MjHft877UHk-mEQL54-gx0HDo9vDk7frS4dn132JRiejVfPvrw6f7-ZH5ytriY5z7Hau8_-V_9J--_9zamkrKRf_GuYqYMomRAkk2BwQgUVSGPJa823fOTq4v55mqxefT0-dnxfCx47-7BO7cOf_HtV4nh-dnFmw_veM0OgQiBQJGyCiAE4m2a3xExogt0crWeTaaEBIXESgyODZi9I_rw08cP7t5edRsgUhN1nJP-2Uef1HULzPPN6muvvnLv7vX7L1330X-xGv5P_5v_7Mf_9odfPH7-vX_zwz_9V38agg_BFREtGuvgnVfSKlRtM2Pipq3f_fn39pq2yGBjKmSgcnHyXIq8_c5XPn70xduvvyFGp2fPDvZ3N8Pi-bNnk-nhat2t5ktD2zvc3azXcRKS2NHtl3otHqhq6tdff-1P__QHQ8bf-Gu_89PvfL9uwtGNh1K6i6uFop0fX-zs7ty8c_ezjz7eO9yTomfHl2-9943F1eVqMSeipp2cnZ374I3x3a9_cHL2bDGfO3YPXnr76ury1p27q_Xl_OJi7LprRzfPnz72DEw6dsP1u7etH6zk1WLtI5On5WKNHoZuyJbRcS9Wt5Of-933Tj87D5UTK4mtGFw-vWh3ZouruRVup5Occ-oGEHRVSH2Pw8iGod0J3jksVWQzIXZYSh5K29allJJS8M5UJcts0pjYcrUMzDomMRi7wWHYyrurOkymk9j6qmmGsbDz3ldX48VOPVusllKSgTbTursc7rz986--cufRhz_dv3792ku3Pv3Ox29--2vrxWo1X8bAkjMgomkpJdTt3ku3JOnl1fkbrz6MwdVNXUfPwXGICNhOGtUcvQdQyWUS470b11Tk088eN22VirAP63XP7NAs50JEORdml1P2LhaVGPx0Vsc6jOOIzIRUily7drPrFuTQBeeDowCtx1_4ysvffuu1nbr53ieP__EPfra62oye1_M-JUGGkhN7x4AmNgxDdIGJzbbNfCMAMUUwlRKYi4jzTsXUgMEITcBKEQJ8oR9g1FLY-5THOgRRJEd9N1Z1g0zFBETrWCfJIVRdyV_72s_92Xd_enK6PLh-e9LST372bDppDybVTz58cnF6tlgOLrApuBcLR3x2fPbkyUkO_PDuS9cP7sx2Zpv1fNz0qlrVcUwFCQHAyov_ADsGRFD0npBI1WKssggwblGdRS04FjQVwW1Ohiin0buAW52oWh1rM3WBgKjkggbeBzOofDBEImZEABCxetIWydsBrq8qU2XEqmpAgTwzs2M-un7Alv-d3_xLWvBf__iT47NVSQPk7JgVDJlBC-TsQ0jD4Ji3oBAA8OxK1i0bpo51SqMJOHamklVEX5Sgtvw2BjRRM0QCNDAAQahCLCIlFxcYkFLKPsQs2nVDU9UGNJZhHMYQY6xckXE6nQLDg5fu7u81L9241m823nnvPCGkVBQBiMdS-jF1w7jadCH69VjUOWQbs3LwYgBI3rMQbdabyc5UQDab1KXczioUcOQc8WrdhRBLKSrGCAhCxZQNEK4WXagrQjWy0FCXS0laV9WYCyMWteOTuZ_Ey2UnBobE5LcfWUIxw6vz-cHBweKyq5ggZxQqmksvhIgqYGYMkIXMtBscOTUwlZSy36038y7UlQ3DS6-8dL0JAXEcy9l8tdp0irC4XO3u7HLwQDC7NlOAg2u7m8vVjZsH6MO33_0Kqf3pT344KK66gSuniJLFkjgy9m_8HICnokwIqpp1C7QlAzQUUHDMjtl7ZMpZto17M_G1s7GYFJMEoijmGKkIASkQEzN7A9CiSOzaBtRKSqKlmJhDAmRAK5I3Y90EF9AEcpGi0rb18mqxzbk75GuHO0NK7KBLOZdST6quHxfdkEWygTrnY7UZ86aURc5DksVm3NutMeDVZhzNruZrMVDEVRoBYbFJRS2rBs_DkItBP-YuDZ55SBkQJ1WsAlaVP9pv9yeNJ3IOo0MCkZzZwVZIqwLjmB1znwoSjX0GwrHoMCTnWdWult3ZcpOyulD3WRO4Vdc_X27mgwxq6DmNWQmtACCMOVvWy_VYBwds1_am683ggPKYENyoBpJLATPNqUyqaFvxK2CsHJgFzzGwKZoBqLV1RWTBM4IxIRlE5wCJHLfTEMgF4ioERmja0DaVI3AATRWZcToLVYh9N24Dc2xoYnX0IQQDC5X3gdu6RoPDoxbErCgBOIJJ5T3S7m6zO6kCO0BrascIpWS_jaSgeSbvGMGcY0QUEQNkMt42JuUFgV7V2DMAWk6OmZhRFZGLKCEGFxG3cGQAMEMUkRCCqXlAZgcIQMAIsXJQzHunaj4wgMKWN2_m2aspEomIqDkmU2SHsNUwGpjBkCSVEqJPY26qLZRas6hJqarAjFsYWx0CAqEaAogIO5IihBCCr4Lv-5ERqzoQoBQJwSNCdMF7rqKPznl2ABZD8M4hQF2Hkgt5p2ZlzMM41NN62AxNE8UKMK2HAmRqgAJFCztWxO1g3ohVCxIjkiMmYhkLOd4OIdCRATGToTWTlki__PzZ3ZcfnDw_AwOQwuTGnJFAwMixw227mhwhZmFmdIRgzF5KVgNg8j4UyYCITE7NM23Trew5DylUDTOhKaB2XedivHXj1sXFPFaRHKoBEQXnDEGKbC90oChZtWjwURG0FF8FdCxFcs5VCGLinQcxJEAxESmlIMC1vV0gLClBlhBd34-r9WpzdX755OnXP3jt7Hj14O2XLjarODucnz92hDsHkyK609bdpriKV4vNernM43x1cn55NtfEr_7cG7_2-7_TYoCsYgoOkUFJ2KOippxy0nXfPb8YPn42PH8qH_346qcfXj55dJ6LTvzsK689fOeVG998-5WvvfPg7Qd37xzNJk3dNNX8fPmTk6tpaCe-Z9jG85AUg2PPDs3IgAAAIInmUp4sNnUVYvDrriMC75i3OlPAnz07vn_jSNS8R0dciiWzn334ZbM_Wc83n37--d_7j_6Dy_PTGOP_7v_6j__P_8f_W2M2cU1dN47Mg6FjGZNzXMa03fL7UI1jHlJOXXr5za98_dd-6c_-zQ_e-upXf_DHfxKb9vz03HGa7s6-9a33v_vjT06ePo9tuLqa7812SpaUhqadXF5cdstV3VbD2M2vzttmMqId3DpSkmlbR6Jr1_afPjuNzp8fn508Pk4wXrt2XUuZTCaLq7NJ2zx5_PSle_f3jm5-9LNPm7pab4bdo9lyvamr0HV9XYc0dhTcxaJ76c2XV_NNLmXM6eL4-ZiLGkx32pPnZ5PpBLXknIb1xph8iM4TIxDq-eml8zzZma7Wa3a4Xo9i2u7snjx7dv_BfR_C8vISJ9OCbgysWfaPDttp3U7rzbILbWNYyLtUuuXF5cX51XqzHvpucXHZVjF6r2MmRUmljvHw5kHWYXm1CsyT2TT3m7MnzyezxpNziDKOVeVj9Jureds23ld1iHuHe_Oz8_nJo3qybyo-BCo6cTEymwH7AFYYae_woNL-i88-rdt6uju5dePBkIZJ0-QxS7dJm7GI7RwdVu1kWG9ibG6-8fqzz568_6u_sNPubG_O3rFjmtVxtdlIzjH6lLIj9I5QMXhW0cVmPZYMgYoZEgTvAa1ICc6lXFRtNpsUkbat6zpuF4-uClaEDGIIJsl7N6nrquJJG69Nd_-93_72W4cH2fQ_-6M_-ej44vx0vVrnPOaUS8kCaLINBphJVuecRzaRMSV2ZGaqULIQ4vbJn_I4291bLtaIiIbk0Yi0GIIRk6iF6NSUkcyUXRRR5wnBbRXuBERMYkIIzjsKYVbFZ18-SwCfP_3y7_zN3_jOH_-5ob726r0PP_tys1x3faboBClUUZPWMbRVtVotpM8nT5-cXJ6cri7f__q37r79yt6sJbDpdLpcjRwZDDw7QCBCFWWEuoppTAZAwYOZAToiMEXH5JxDZCY1IyIEDLHKWmLViuUt1oHJqSqzB0UAo-1iFI18VBEGBFXnPAAgbfmbzkAN2bSUlMg5AELCKgTHtL_f_NYvff3Jo-M__eEnV8Oopch6EUMcUzEzR1CG0rRNyRmkGGhwVR5TU8cxJ0IAQAQoUkDVe2emaqolM5EWUTMmCoREDICEiCKgpsWQtjQZVtO6ard6e3DOVAixbSdlHOuqTrmvq2Z32iYphHBwY__GXnswacw0xqiqWWQ9rOpYI_N60682XQZLontHe6t-LWp9PyhAUQ1VSFrWfedDRIfdsD64fpDGktGuLue7OzNTZfCFbJ0TmjHS2KdJrG4fTItpLooMomXrZUcXVPLFekPEk-iHJCnl86FXoqwoxCkXUZnUYT2kpgnDkKykEJxn1pTHfgQpxpAHqQKOm1SKAlBwTrW42pWhMPIWxOSJUMWp3by-u3l-8mtffZMK5JSOzxfnyxVVPo15f3ey2YzNtNq5vlP6YhnScr1_feeXv_keDqMqhtnexbJPat2QStJ6Olkt5pAyw503HKAkRShixQdvkk2ACZB9MUMkBLQsUoSdY0JE6NedFLGSY2y0ZEQ2LTgmcAzERi62TZEipbAPTGRmRcU7EpGiqmZVrDUrGXMgVERfNTuTPGQ06PtBDXIp4Nz1l3aNTEppJ6GuqzEJOEAHFLGto5gWA2HA6ExwPQwx-CxG6E4vNsNYZpO6qqvRYBCZr_ti6mufRRWwFM251G2DBkQsYkYwXy7Wm75kA0-IbGYGL1aFWTSJIVJGFMBVPxbVMasQNU0QAxfd8fF80fWpyGIzbESK8Xocz69WWeFh0zzrsgtunYaSddMPhtSnMtuZbvohm_oQ-lQenTyPXJ_PNzHQOI51cNf2axHxno2tSGbmaYxFLQY0MlRznh07YmLHbYzoWcdEZp65FG0aX7IAIbKLIUiS6J3zLkbnHVfeMWkTPeO2oYtNFad1LFmIoa4Cew6BEckx1nWMjQ_MlfMRkYzaJmopTFDXYXdaOYDpJExidATMiAge0BMTgmPyjnLOyFSKxOAdESBuYz9oGIJDQufIIRDzi7MOO0IK7JDI1IIjIjI1BEaEMY8AxISmqCJV9EyOCBGBCVS375Nt7nHrXicEYEdEzgwUTIogcS9d7So1QABDLEVMwXs2BFFgJmaXi4TggN2Yxu3KAYhzKVuIShUCMxWRrVYmOE-OycwxEVOMceiGGKOYAKoapJwAYRhyXQdmQgQiHHOKwTlCQ8ogRXUcM3lKQxk3aTMkVaAYzWC1HgEMATddz7glJTMCmikCmem2ASYlU2Awpe1G3JAdb8s8e3u7m_makXxV9f3GyNBegHWRrZiqQWDnPadSAABfAIVIzIL3QCCy7QYAE4uJFQ2IIOq9B0eI7BitDA5drKJIiXWzuFpOdyee2bTkJFtwESGBmQGBmhQl3II9kBBySuwoDymnwkzBOQRDo9nO1DHGWG26bhgH53lnMgkvWIE2Gl4u1k-fnV6crFdnTzDrzt29-fPF9Qf788vULU-XVwsCBHQqLqtKpU9_-vnp46f9cpHXQ0q5ouYf_K__J-9_473dWYyVDmk1z-OqwOWmf_r88umz8yfPzk6O58t5P_X4YLf--oOjv_ze9V987_q3f_72t99_6b2H11-7tbs_C23lYVsWBHMBLasP4WS-frRYfvDWQwcS2aEhEiEgIjhGAnQOpYgBFKBRVIwDEDk_33SOjYnIAIBW3Sggk7pmJDTthkHU_vEf_ksxvvf6w48-_rRpJq_fOnp-fjWO3aIrTx6dUaFqWlEgUV2vOgYspRDamEczJEJ1vt45uPngrWvXrz0_Pd7bbb98fKJaLi7mt-7eubq8EDQB_dVf_uXT8_PLzaYihiJf__rX7r10tLi8ErE0aDfvskpgOn76tPJ-KHL_4T2xMp22jNA27TD0FydXzrmLk1Mf_Pnpcd1Wi-VcCfeP9vt19-XTJy-_-_rF6UVSMTAMDgn3D3aXy00p5XJ-WTeTdb-5ef9WVdVn56eb-Ua0SNE4nUx2ZufPntVtNWmnKmVxdWUqPrg09O20TUOnhsQU63az2WxxGZO9w7Pn5-__wtcvHp__9b_-W3_yh9-HLKFp0CiGOq3L3ZdfKQO89pXXHn36LMTq8vLy7p2XF1fznXYydBtENMgAoKMMeaiaaSrp4P79kyfHy8tl9P789GQc-3EcxmFz7eh2N2wQYEzJh3pxeRmCH4ZRbVu2z5v15vxqk3IZxyGN6fBgv66bJ198Ws9mSc17N45l7_q1PqXVphdgYl5cXDV1PVhRkeNPvgxt3LtxdHj75vNHTxCAKNx57cHV6eV7777rox-HMQYGhL3ZtGIuqv2mD96jYRFBpK-8_fL5-dU4jt2QfBXHUfpu8FXUIuQYkfKYQ_QI6CqXc65i9Ig5FzVUEVUAAu8ceZvNZrWH2wd7f-XbX__V1-8xuT_6_o-_8-GXTy_61WB9N5aiKSdTdJ5UhZmILSUpOTMxIaoqsitZ3IunsaioZ_YhlCEd3rk5v5wTAYgK6laot3Wfby8kjGQAudi2O4uMORUXnRQxMMcupUxEQzfsHx0S-OPnZxDcuO7ffuvlr3_lrc9Ojrssz8-WCjokY3aML0IMoArkiiIAxKqq6pqJnnz-xcXz5yq6Xmxm1w5yzt7HUoQIVFVVmFkA2Tkf_NZ54jx7ZgAAQyJWMxecqXKIohZjVDNRAMLtzKsUcT6WIghIRATgCImdiLFzpgpq4AiZmRx7l1LxMYqqagneAaOPlYLFOiAgGNRt_I1f-OD0bPlnn3-5zrK8modQESCzy6U4NAMTyexYXrQQAQlLyc45taJi7BkRkuSSlXwwRPyLzx8YiJA5iEkuL24I3nkFc96DGDsa-gygqkAUcxkjO5MseUQA77hqYko9KcXAR9f2iskbd281zlWBVc15NjNWrqo4pjxf9-u-j1VUwABqJl-en41DqqoqFUiSmypskbJEDEpXi-X-0e5m3XkfN91QMxNoUskKIQYCNiZSG3MB5rP5mr11Xd6dTvuULOdQx_XQo5H3dRolRB5NxyKjGU5CyWIKSKCCUExEwEDMYuXn53N2tu6zAXuPgKokkpSskKL2GcFkyK5QSom2MHgl6DKIXn589ovfehdScd65Knzx7NyYSRFVqujbutnGnNvdab9cNlWz17rL51exrpV51aX5ukOHpQiDYckpJ3YvvcmM5BG8AbIM4pwDg1KK4Rbs7lGzpqyAsW3AgNnF6IfNhj3lsXsBRXEOCY08Oa8GagJAHGLJuZ5Mh9RrMQNr61oMQJEQfPCIZKpZM7EDNDD1zP3Qu7oWLdNp6wSKSFs3qS_Tttqb1CG6g70WC_Vd99Hiyhk0Vd13yTMr4ZilngTNtul7x3GTUpxUSQECm0ISTVkTSWS37EZy3A-5qIYYVWS17qdtG6OfzKrAXs2SQSrSlXK1GTdD7rNlgX7IT07natpOqsfPLvpxHAXV2WoxXKzWy81GDJXp-t7sdLXe9OVq1W368YvFqpAVoJwUARfrddf3XZEyJDBddf2Q8zAMk7YSKG0TV90ggoBWN56ZVa2pfE7S9yXUjhAQwczYcYgOkcyACcWUAQKzdw4AiWjSBh88Ox8q3rZsGaGJoW2id4ygO9PaOW5iiJUn5P3dlhGIiYgBwHvvmaN3sfLbIGJ0LiBW0c-aWtWip6apAlEdXfQ2ayo2Y0LbAqVtC2w0QAQw51izENGmjMEFJmemxFvKGalaYCdiYMpuO8ZGAlAxJPTOMZOJxRDMTEQAEQkV0EzZOUZGIkRTVRddyTmLMJMBeuSxSJ-2NBs0AyRkJjFzRIEC4BYajTkXtG0_1dBxEZFcihZTRE_egW4ZlgZjn4joxfYA0fPWnUEIVEpBszpUoqoA3jkBZeIipYqBiEIM6_Um-OCdU7UYg6oMQwYEdGxIi_laBQFQdftWs3FIyFxUyHkzCy6MKQXnpBRmKkW2dx8rUrKoqPOOmJFRBIgJAXMakByIgsF0Ntms1qH2RcWFauw2CKRqyESGhCimRYSZvHOiirTt9kARVRBfBURQMNNceW-AWtRAkTipcGBQIWMZRxeaXBI6UhUf_MXZpRYZhywGqc9mSiGWNKZ-BEIpaoYGpsWAMKWMRmqwxZv2_UhEyA7NUp_HPKQxt5O6aeq2jimNYhx8NSY5OTnv-l66lFM_XF4cXd85fT6_ff_22cUqpU1abTYX64MbBxvTZx9_vnzy_PLx47EbvPfK8c7Lr_z-3_v9px-effrF6U-fXD2_Wo1W7V07-tq9u1-7f_Obbz385vuv_dJ7L__CO_c_eOvuKy8dHRzt1Dt1Zs5AApCNwDlAMkQVQSQi8uyIiE3Bu8VQni_mr9284UpCQwPbft3QjInEtOj2QsQpwbxL4mjiPTJJyU0VAjsHmBUul5tlTpMQXfCaynocKnL_6nufhNC6Gp49Of7t3_ulx0-feYCffXn6ta-89cZbb0yv7b3789_42u_8inb5tfd_8Wff_56ZmKkPhIjETlXf__VfH3E4v1weXN9_9-d_5af_9k-Q0TkoMs7aWb8ZctHf-e2_3K3WxHRyenVycjzvVt_9wZ_mLrNv-jIuFuuqnkjquWDlGZEfvPIQjWbthEpGs-X54uNHj1vnxiER6va0UnIZSpJkPtQIslqvr9-5dXb8PHI1m01jvUOkJZeSx-XVytAOj_bv3n_l8MbNH_3pdzGPkspqMdx5-f7xkydWyo3rt9t2pmNKeTARUZGx3HvwoCR58PDls5MzVnMcKs87u_sBMW1W1-9ef_TxlxcXx30_HE4nYiql7O1NJ5Nm7BYXJ5dpvT68cdh18_n8Sspw88aRqyoDZO_9dLq_t7dYLJu27YbeEwXi1PeX56c6JlDaLFaSxYcouZchredLLGopg5bF2bwO3ntf1dXuwd7BwdErr76yd7C3t38Q2-Drer1ZnS6uKogbyMGFUko72-GKpzt77BwAuuB8bOujyXA-l34M0Xdj__o7b65OLrSMaMiO33jnzZ3prAoxuBCCRwAV63MSsDGNojZr3GKVqoquLufrTbdabYwpZUHaBtjBbV8oAHVV5ZTaJuaU93ZnLjgTq9tqsteWIVWhRtCm9m1V1RFfuXvz17_-c0eT5nw5_D_-8I-fXa7mvXY56dZ3mUtKyrT1YEMpws7nVJAAQKOvUk6ixoF1Cx03C86ZgZiCgW9rBdWkjp0PXgUiexRxwW-hmtFHQKDtQs3AhyBmAIqOtns2JAzOD0N_--5NysOT43MEmx1OP_3ej__Kb__693_wo_OrTT8mLQrsLBcoBgDsaWvtNgNDKsKxbmPdeBfMeHf_cHqw-_z5cVNNh6E3My05VJWaOb8NSSgS49YR7LbtobB9DrDjyK6oisj2kasIzAiI0buSMrIDVCZUMXJspsRO1bY7WEZCIlNQggJaT3dyHhHB1LxjQmDn1SSEaKrjmGoXUtr81W99_fRi_i9_-LEAjF1vZuyCKRC4YeiQiIh06xlGNSAzcTGM3cgMarqd6L1YrROiQUkJTKuqMdEXSCnnkUElI7qUU11HLTrkVNXBM6cxsUPnQ2AvXVc1dU4JmbWUqqpNhBmR7NfeeT9Zurk_2QnBOS4ixGQIAJCldJtRGQUh5cKEIURmlqIhRkAnat2YgVAVwTiLVa5qKt9tNoH5Yr5ExrpyjqEAXnX9WLKAqQIzdnkUw8m0EqAYokmexTaDqMjZ-SpBmdZ1FcKgJUvJJv2Qh404T5tlL2jRcxlSbHy_7POQnPN5HIlx2HTOBEE3Xdo5nJbV4BBN1Xm2kgmAHMYb7bjs3cxz7ZbPur03D--9cXhjOtvxFQKMOT8_vehWQzNpIocbNw-YKPVjSpLVqoq6589feeXOtz549-OPn19_-eD0_KqUMl-sh02umqZfrpaXC_b337RSrBhG2qopzIoVA-fQORcCKjJF5OgCGyjb1siB7B1toSkiW_EEMouakQt1xd47F4gRFCn6cUxaRMS6IamoSiqK3nkXgzGmNCKRewEuBEQqJrs7uyJ5Z2_qvKVxqF2g2lXs6hBBdDe42tcPr-2hofduVPUVZ7GxlJThYGfSS3lyedl3adnndSqCIGLn6y4Xm8_76WyaS-n7REQgVoUql1JVwaQsL1cVuzBxHz46fXy2uFoPx1ebejJRA2Sa1O70au1Q93am664cX81DVS83w5BgvukySNclruonJ-dPL9Zdl666zWrTr1PqrGySPnl2bgDX2tYUx1yKCIGmVNKYR5HZwXQx79u6WW_WXTeyJ8_Y97J3sOMFVoteROrKmViMHgFUpYqRgb2nGLwUMXmBinfMqFBXtRSZtRUaVcQmUlfOM4FqkTydRsfsCT37KrhA2DYRQUqSNoaiQi-8rWhmdR0QjJkiU1PHSRVi5dEgOKwiT5vY1q6JMXpGgpLFecdMZuCZ2TlAc0wquk0Sbik9iMSICFhFvzUhAoFDYiIwUBUA2MI3mVhVERCI2DnRgrQlXZLhVrqrTJhyIUJFRMQiAohm6IiziIJ57xURjFRVzVJRQnDst4mf7dPEzJxzAEAOAXHIoqocXS5S1NJQzBT5RYjfe-cdE7EWqatKwbab3JyKC76IOMdgWKRs80LsWEQJQUS9DwBqBsEHAOn6FGM0RSnCwQ1DLkVSkU0_7uzNujFt7YuikHPJRbxzYz-IqaqVoltRHSEOw0ho7BwRaSmI7MiXLDkV5wMSOu9TToAMiLloHsFFykOvok2stYh3rGZSCjMH5zwYgiE6M3UuEGEuJTiHCI7JiiKiIW6tNYioBmjmiJGBvRMtMTg0SKkIWNPUznG3WptqrEhVczfknJnJTIi8SHHEhtD1PSKSZwTr-8EThrquJs3h9f355ZyZiLBu6kBMWzMmWjWp1uvxi8-_NKIyJBUMzs5Ont2_t__pR8-PXrq-XI8DWne5COz69eb4w8-k38gwIEMIcba788HXv_orv_aN0o_f-Etf_f2_-mu_8803f_X9l7_52q2HRzuzaaAqiOqQ85h0FBgLKJABAxAaghkZgW1LLrbFHDlmJiCELYIQES_6tLqYv3z3BiEywbaBbWrsPOD2m6hqBuSQ8GTeHe3OEEnNhjG1TU2GRRUJn59fON_W0XvPJecCVDL85NNHvm4kj5eLxW_-ys9b6r7-zutXl8v7d6__-KeffPeHH7azuru8_Dc_-PG1h_e--MGfq_QxBDOy7QBV7fbd2-TrOw_ur1fzk8efnZ5cQO5fevf1j777473D68qQynDvwcO-DM3OrkP3kw9_3GL12RdfvH7_3stvvF5AHz05rqbNwWSaUkaS9Zgevv56KWlnZ8JSQhsXl5effPpsd-9wvVhPZrPJzu7f-Dt_7fvf-REHWK8268162tSL0_W_9zf_w4dvvfPpj37ifV2KRO8WF1ffePvn58sVo3WjjEN3ePPe-dMn68XCg6lqU8dhvWnbpmpCnDRQxTT2KWkaxxhjPalDDIfXD_b3D_qSzs4XvdimDHdvXz-8e_vo-s1f-vYvnJ-fvvzynenO7rd-4ZcevPz64cHBV7_2jSrwm--83ZPdeelObOqj69du3n8pVu31O7evX7_-8quv3793__D6wcHB4a27N2_fuXvzzp3Jbn3tcPf-Kw9u3L754JWHL716__W3X73_2oPZtG3r6sbt29fu3YhtZMKdvd3Z_mGGcRgSiZY-zc-ez08vcz_0yy7kEZx3xcLBTWTy0Tf7zTh2ZbnqVovV1fHy8kLG7vLkpD-52Myv9vZ2v_nf__3n3__04SuvxGl9dfK8lDz2y9Pjq_e-8XUtSVAYkZC9w8vlWotksFRMDNKY58s1EI5jYcfe-35MgADbP2pGUHPe5TG1bQsGk-kEzKCor7yLXopWvkp5iDXXTWQrD29e--1vvjOL_tHxxZ_89OPFahzMbTajqpVkmoqBpWEVfUA10WJAaqIGZmoZvHdmkMvoHQOSlOLZgQIhIjOAdF2uq6qMaUuLJ-SSRu-cGSITAXpkNVMALcV5hwaEgI7KmP_CKkDgCBBv3j6cIT49vqymIYbal_H60cHtG7f__NOPr107HMZijKYASEzOB1Iz9M4AOAQ0BCIwELC6bS5Pzh6-9QoUmi8v6lgDCAHolmymoDmT4xCqkkckYs9bhg8ibsWUKuZiQEQE0KTOBS2GgAy8jeaLQh0mimaIgCiqzjsgNFXvg6k1dSumZuicVxVCAsTovZk55qqpU8ocvCNygRunH7z15nR_54--_7PN0DFAzipFQ1WLKjjTIp6ZCU2UHSFRKS_OGEwvcryO3ZY4CmBMuM3_mJmPHs22_mAkAgFEBgAUM6IiGY189FqyGppaDFvtcWDmUDdEnHNyzNGHg929BGU2ia_evlV5ymkc0-Acm1rOOYkkLX1O_Zh9cP0wEnLfD21bFYVsaqhNXQ9DJucAEJkqz3kzAsDBdLYeUtcP3ZjbOEUi9DDkEurQpRxDMKS-G4dUdmd1ytqvNu2kBgVUnO5Ui9XAHKzkfiy-CufnF943XT-EEFggMt2t4zAWRKhDGFabtqkll1Ik970Ow6Stxr5QziRophxc7nofI6Rko4WjepxvdEAGqms6-Xy-F-vX7z9smQFg0_U_-uhx9O6rH9y7OlnNdqokcnp2cXhz_9nz49u3r924fviLH7zbVtUPP_xkTOXR56cipWRBJL_jdSwHO63ToqQGSpBAwYjY1MABMG1BF857SQkACIJkAbIQmmKiUNgQmaxkAgLvAMkFT0iEBAbjMFJ0wQWDkobBOWdi7F0uOJnMhFDAytiJFvB-0xUMfn93JiWNQw4O5_PLW3eub7plgmbquQO7OFvevDZtSbaHEQiURF0MO7Vvq_DjZyehCmksr96YPF4sWZWYzXM3Jgx-sxiSKDdxftnVMZx1q4Z4b_9geXV1tL93Pp97j5s-ub1YlWq6U3_8xfzR8fmto73lmIac8-n5wbRxiLGh4_XqjRv7vqIvPz3x0U93q6tnV10um66vmugn7RdfPjs4OjqdL9DxVT-8cv_w-z95erVZpULDpj--tPlmszOZhjqWTR6HRAyzaTi5WJ0dJ2ZXhr5b96kYA9GQYh2OTy5u7LRjESTGogoaCnskQkagotJwMFAmkGIICGjIXDfeEZHFNBYPjITTSeUcl1TY-1FtEkMCjREZyTF6QlFj70EteKqKZxYgzmMCbDa5n7SVj16GVAXnCFDEMzhkz66tgzOrAktWQtze_nSLS2ZjBDVUMzVgh6AQmNG27Fgggi0nGAyIHZGVXAjRMTOTmTliAABiUAHElJKAEZKKZtPt9hQEUhExYaAsIqqpGBOUUjQiM5qigI6jBM9EpGpSxJQcG26JmQBa1AxEFJlKzsWUkEazNBTPSIQCWIoRQWg5GIrIVvsYQ0g5IaGoklkzrVVU0cSsSDZABDeU7D1nkX7ovQuOHRGNY3FMwAAEsQoyJCq2WXSOSRxALmPWq_m6H0bnSBE3XQI0h7harW2bhmV0jCVlJpacnfdFkkhxITjHqRQwcJ7RoajkVMAsVLGMxUDyMDIVgmmI1aiDQnGEYhZjBAVRMRGm4JzlpIRbdDRG70mxiLrooAoOEBVkVAM1Ru8Yt44vJjRMOadU2AVEYMY0Dr6K6Mi29xYDgWKKDq0MZVtaTjqyiyE4x05USpYQ4jD0LkSVcnU2V7OieVLNPDsm0lIAmEyXl8svn54OMlTNtLD240r7btK0Rq6aQDKZtnW36o6fPD863K9HdiiMtFzlyaT-4Jvv_f2__-_vT2YQeNY2SVDXy5EdCAIGVQMgEzExMDAkRIMtGmkLRQUAQwVDBFPBrS0IgV6YicwYzGxMGtGv8hB9SGUUADRwzIjAiAq23VIGR2MRIbw0feDDMI4i6onQzAC9Cxn1-fLywUsvZ82u8CaNSezDRycqimLnpycv3brOm6EJzV5TTapq2tTPz-Z77ezG9f2rs4UV-NmPfvTBb_7qH_6X_2WowEytqKGxc0-_-PSt97718v2XTz_9eCijWy9PUy720e179_txIKQbd26a2fJq04_LaT25e__tm7eO1mNaZfjLv_BL__l_819P2urm0eF-HU-ffAmC0GGLca9tjsLuZHefvMu3htnBo6Pre8vNMNuJk9j-8Ht_7qv28upsWHRIvNZl5Zp_9F_9F7_2W395Mq3zsLk22RvXi73d_Vz7t957b6Fj691m2Eyxf_2N19oP3ro8ubr9yv3UbRDDvet7RP7J-YWHyO-9HyaT9fJCOP_JP_2jr77z7q2XXnr_594sOhyfnl2t1sM4jgrMzfzicrWe371-HZtmNeQ_f_LTmn0axkfPPw31ZJyfT9udq9UcQNlht1penZ7kjzZFlR323SBD3swXwIbgCISQGFFFyDkEp2ggpaTsYlCx4BxYkfwXeRUAVStSfPDeOUV0jlW0pHxKlPvRtTP8-CdaQEwlSYbkBJnNCQhj3UzF4yXTbrX_V_6Hf_2f_aM_am_d-N53f_Dee18f1__Se8vLYb149s__yT_5_T_4g2FYjcMokrOGum6KmAyllJyyjpR3DndkSMQkYmnMRERKYhJjIAImrusITdPWfhyTFQ3Bm-GWW78ZRkPQMk53Dqatr2P43W-931bxv_3jHx6vlmeb8arPRDimEYhyLkWSGsZm5pCKE81ZVIgZ0ADB17EoAFqsaisFGQMFAkPnDa2U5ELIg-zsTNcXc2UyM9NCnnJW0eJdXaw4VCNDAVEhya6uZZTgAtYvfCmmisSzvb2q3d1cnU9mgZmwFD-b_hf_73_6P_8f__d2_gWBgnPsEEcvzjnNYiaCQOTMITkiURedaCkbk1yquv7J93784K2vnpw8S0UQvUHe0io8czY1onHoQ2zHobOCIuDYvPdGACpMLuVcxTYNG3BISM6RqeWSmQiRDKXAyI4UQM10e2ciYPIixcgGGck5GZKWHFxE1K7vBdGx4xBzKiEEZGDgMoxvv__ux0--fOf993eb6uLyEgFNpBTBtEV2snOSUq7IgxmDMyQjQQAxIYPtzGwcelfVIIKGoGYGjlhVA_lOs3cEZMFznwo7Am-VD2ORwF4NPLuEzjtK4xBmbdydLVddvdsUKWkYQwwiCmD90EU-sixFSjIoqojbhyuagQKux9SPYkBpzLEKgEZMOUEax8LgfEDQJla5mDkjlcV6E9AR8fFqvrs3Ie_OF4sRShRsKJxpf7VcBxcQTEUmPq4tHZ-tamIf_KPjZ_eODrFAoFBVYd1tru3u1MxDGq9fO3h8PG9DRKIC6Ma0NGtCXA4DO6ei3WaYTmpZZkLKYtHvRFeoCKFTLDoWUyhjdkQikk6T46Apl5UWoPtfuzeeLR-dnt66d3u1Gg6Pdm9c21muS4xtSdatRmbvgveVa6pqs06_-7u_fHiws153d-8fPT1ddZsNosOSp9NqdbUZu7wZBwfes_PSZcSiBimb885U0LNlAbKS10WNnUMySTlUDUWGcYQEollzQTRjNTVfBRFxwbngswhHR-y02Px0zo7MRAHJIDifUp_S4Hb2YjuRTn2MBdc65svzK1-Hvut3wqwMQ8pDU09uHO6P3Xp_z-3M6mfHnQt1L8JoUkrrfR09oU-Sj472CN2lLc-6seuyc8iVG4uFprpcbmrPu40_76WodSlrZ_5g5_jy0iN-cXpKCuMmv3Lr2mu3r7shb1ZFFaXg5WqczKZn5wuxcnZ1eXN_t2r4oGkE-PnJOhm0dfz88eWi7xy5Pg2hraLn3ev789XKx6pY8QG_ODm9SuM623y1CQDT3clysTIgDqxsKFYMCuCqHxrzmFN2bCoiWEDEhUWfM1qsoguVSh6ytjUZqBgg4JgkOBzHDGBqGipfcqnrGtHM1HlXMeWMJasPhMQ556auCKBlZofbdF5V16qC7DxTrHxbV103XNttV302VSHMauyqMaWAbnJtmldpZ1L1Y66jI4OmChU5BiNEFxjQtAgKeCJyiGAAwEwq6qM3MYe2vbsogKpu2fBb5rGkzMF75wBAt1cCI90OOdQQQcCkiGdftktJMDNQU0IaShpyUQPnnaiqgWPWYuMoLnDps4ASczdICI4UxczM-jFVgU3R81YPQFuUDQBt4VwAamBDKnUIuQgSVZXPWb0jdqRqjGAA_GKkpPxCvAs5pyziHStAEXFEqsaAbdUUEUcsUuomGiCCEVLfDbO9nauLq7oOQ5ICwlmms4oIOyIpis4jQ-3iMKwJAIyYMY-jSo7OSZEspiIxVIu0gTGzZ1JSFWIAIUAMYSuLSHHWrlZDO2uHdSpDqeuYh1GK-Og0ieQSA0uGbDrksWobg54QS1bVQkzOgRrJIC56KIlpy01FRcgijBg8eeYiUiRz8AQv6BwlazvzA8E24UOeTBUQh74ndGUYXXSikMtAiEIKRb1zHKJkBLNh3btJU1cBzTSXECIHp55TyYtlN79aGtO9l145PntW163sl3KyXJcEGBBJBfq8SvPlQVO300l3cZ6HND3Y-Z2_8Vt__x_8bVvR5eX8bJnDLAqhJ3aEWnTLhCYEUwMAM_OOzOzF11oNtoG3bR9dDV8sQwgRTY0AAUjRttK9Ynk6ia0aEThkR0bbNRBCKYIIBlIHUkOycrWBVtSReeIh9yCFCgKCAHiCfqWR2awEshhcNZTNer7pktoye7x9_fDg8HBn2oybYbVeb1Y5DUO3Oj_-4tnZ-aKJVRsDhzA53GcEwmKiQFBEPv_ki5dfefVnP-neunP38y8_P5jtffDOw9ndN_8v__v_w8uvv7q5yjepzusUNSj0lcOXbu2_8dKD1WJ1Y9ZcbOzmzuFk9_DxfNPNu3Ol675OYYh5XK3yhnSJUtdtDM3v_ua3r906-OBbpR8tuKjSvfXeN_ykpYJTx7NpLar92Bnp__Q__Z8NlklhtVjEdpJSAuP12PvoF4uz3I2TECZxuqjlw88fO9bNsnu6PNzd3zv58pMvvjiO5E2pcTTmzeXZxffzDz_-6af_7B_942EYx6LPj0-aOjJBTsU7v1lvqAhNnBTIkmVIIKamUgo4DhzGzVBNKkIyNBmFGKUIeSQmyxnRHHt2LnWiNqARBTYtWpIaMDGYkoqKqIlnUssohSuvaiF4yOBDKFkJrKCVYQhNlQet93aYvGE13dvp-v7oxsF62a-ZgoW9WQtmn3z0SVSzBL_3n_5dVP-3_u7f7Df05OmjJ4-fHL3-6mcff7oziWbpOz_87s8-_vRv_Qf_nddfeShjv1p1_aYXgEldCZHkbNkpkm_q5WIRicmTA6yCz8U4uJKKGaJSW1fsAC32uRdFKVmUipgU4ehu37hBltNy-Qe__3sB3H_9h9_54vgqxTBmyiKsWMZibMg8iiKSFMWKDciI0CyGoOMoxiZGDk0spRKD7_q-ibGIkINtm2u7e8wpu9qXooxcksbamxc1VS1INKQUqoimTV13myFWKCKkSACGYGpIyEimMg1-zs439bDuETibj949e37yza-__69_8tFsMuGUctJhSORYUnbstSiokVIIFaghcGhIUiFjRl1cnh4eHZ6dXdZxoiUM3cABudpKgIHZD0PvQwQtjsDAkPlFl9IhGKcyGpCqmupWJWJGLnoZE7Ebc4mxMpWi4qoAao7ZALyv0jhklcBu-yIzKEw0aSeaR0YCUWbOJdfsDVVA3nz7rT_-53_0yqtvfPXd1z589Kiu2nFIRMAoRqYihM64kEMYIeccmobMl5xBMefctG0_jMTOVEwUHG7B2SpoKkULMqoaiOVcfHQGhZiSKjGaoYyp7zlUoe_6uomLi-WNuzeQ_Zh7Iq5iGPphenBwePPasy-ffHHy5N3XbpsUCEFG3WlqUwvkMsk4jKIGaHVTbbrOK4yi4zC2bbM3nXx2etpOLfqYU7m9c_Dx_ERgHAs67yXn3WY66FgFnu5NTpere4d7Ti0GXHbAAMEFJu77cb0ZObKLToq6EHoBMwveReLV_4-m_wq6bb3OM7ERvjDnXOmPO-99cgRwgAOCAARQgBhEkWxJ3ZRalEoW5WpJZUtl-aLbse1yyVUqu-yLdnW77Sq3q9sq210t2RIlk1BTYgQoUiACkXHiPmfn8OcVZ_jSGL5Yp-_X1Urz-8Z43-cJm5BHMYo33Ifi2FZTd-_xyuaSJDNjKH0CLTCMp-PVxXo82pdcFJSN3WwWxCpZYgjkDBgBAAIc2oHRAdoSO4mJnANj24teh3z3gzs_8_qzi_P1nuLObFZKZwSqirIIo-7NZtf2ry4enX3-069enU0suhTWq648fnJcSOqxh4KbNvSnG0Yab2-xGURy0aRUk8EiMRFybgfjvST1k5lX3CyWZMSNxqbyoetzSKhqDSMaZZVcyLicEhB_FKS2TrSUFC1bJFRR45uUY05F8kDWGvas2LWr0WS8XrSuqkUyIsYQnOX1fDHbm7ZtPjys3394lHM-brsr-9PjxcVuHBtLrFw7mxMk0Mza1DWzbYfMbKLkNoWjk_nrz9268-jooKrBmVbl4nTTKfRDOJxWQcr5fLk3Hs3PLoDK_nhcAD91a69rw8liczFfwbhu9iZdzKUfppN67PDu0-WL1y9VxNXueLMJfS6jaeUZV5tuCJFr6FI03eCaarVu25AV02bRYgWXr4zposu91JUd-nD0ZL6_P-37DgOzJYucQp5jhwhh6DVJQNrfuZ7TaUSUkJhwcbYipf1xUzsgoX6TJ3WlyKXkUW24bM2jpSRoJqyWpQAxNqOKFZgQjDGmeG-1ALPjrcJJlZXqUYWIIELmI_qnNYwKlTVKIJaLElk75NwQxGiMIStQjbxnUsvekHfWExncZtWBHG-JYwhQiiCBKhCi5EzbyL4oIhB-xPhHx0SwLfshoDHbMkAmZpCCTCWKtVaksDGStxBPEhBQBEOkIgUM0zBkZHLKgng0n8_qSVbVVJIICCkWNkxoUik5lfHIdX02DKUUKWgtG4SyTVKiGqStT15xW4slkVJyiZgV0ZittAkEFBGNoZKLNaxbeAVtUWwYRYwzVKioxCE3dRVTHkLErVJ3u_xAUBDd2oCQRHW9WA8h-toWKCml0ahKqzaLVI0f-pRS3saZEJCsYc1FBUG2ULaCWtejYQiKWvtKpYBASUUJ-L_b4EMRJGQwgIhCKQQiiF1ndkajUdOu2y07FBVAhLesfuZSEhIxM5JIUiRSKUhgjCFU411I4kbWIQ7doAhsWURUla2tEfo2uJ1RUbHOqYbQx2o0isOACikVFXSO1JJk5YpLETaGiHNIOYlxZAiLpAKyWa-bnXE_tIcH-4hQGU9MReLFxXKz2cSiQym-aZ4ePxy6zTCES1dvmnH18Iff3bSDdXVpZXe6u7j3KFs4f3JS8_gv_s1f-Gu_8hcrT2dPuuUmjUYj8tRMJ8Z4jSHGRNvVFYkIihZkBiDJUES3w_-PkNhmS-MQRAQBUdh-L0spKliKIoMqqooANbU7oZ5YkBBQtv51TyarMGMRTiWlVIy1F-uLyqIqVp5PLuKktsaZFJMWdWO3SB1XQMk7R_vjvW6-ef_D7zTuBmsaE9zY2T87P3t0_8nI8qMuvTDExbI7O17_pb_1qf_0__Bfnh4fP__aizOYvfYTb77_ne8jghR11jpCLYauHrz11W8u5xfPPXtVx_XpcnGqH37ys5__8O3vkavXIVeN_Rff_-6bey8cLx9PJ6NWhqFkrvx6dfzszSv_o7_-50a7-8oCJZcAe_vNkIaK_dn8fLnRxaJLXYYM3YDNZLppL1K_Wi8W1qzqpgkpzqxdlcXZej6z43W7TF05ONw_Pj45PX66CfPcqWEskULfLi6W3mw7kFySJpCqqkFgVHsVTYTEvI6dDkVKqUcVZjw_PrrIAohgTFY0gHHZOwMqMH1mbzyr50fnLKw52CKjyejmtefO5k-4ssuzpQIboMnBTtcGEawb430V-oDMaO1kMqWqimG4-vz1x-_dnh7sHD141HZSeXYjf_mZG49u379-48qw7oytJjtV7kMzmqLjajSJcYhDcrXJMVnjSsnVbNxthunu3jBv958_eHLnyZAiV27cDpNro5l4Z2vf2G4TyNjnPvtZGpd3vvM9Od28vTp-TZ9d9d3VS4fT6egTn_oEskXIO5NJiPnxg3tf-Rf_7J_E8os_--U3Pv7Ggfcn52dDTCg0qkfe-SGF1Wa9O9uRnJBwS2a33rKxiARZK-adygXVk4uz2tWhJFXNSRJq3XgkbjcbS_K5j7844vjenaOzfljlYhhyyCyICN6blMumi7kAGhHUIUQiEsWct5UxQN2SsBQArWHVQqSEBASoUEpBJCA2CMvF2libSxJA65kIsCApZ5CanFpCIECWnH3tQNQ5i4gZisI2QZqZLTGNLPz46KnxVaVMpCllX5t_9P_853__f_wffPsHb1feK1Xr9WCbSpKUFNkykUAAUBVAV7scAv136BsCOX344I0vfO786GwIGyDjKqcERTNbzrkQ6dYmUTtfMAtCRkVmlQLIWrId-VQCWwIE720cspSSRMi6HCOy2eYAaSsaEMipsHNMTGxAS8nJei8xWF8PfU-1UQUkzqkQbHV4GLL-vb__l26_f1eM-_47t19_4blJVbUloWNDUEJyxoLlNERASSLIXCSnkokJlAxRLCWmwbpqaAdb8UfBK9UtpomdjSGjQWc4lSwIvqqTJI0psQIggTqLjMxExvssioRhCCKACl278XU93dmJJV5crEfjej5f1O6VGGOpKJWcS3bGZdEQ0u7-ePmgJ6TJmPveKEjJIkrEwMh7s6kASMGc06PN-eWd5t5xEiwRSzsM4O20HgdpNfdLGXqZMvKY3Q-WJ7cODyKKURDC2c7ozuPj5vJeL8JI61V70Ez6kPbHo3XfL9ftuB4JACOiYL_oG8Z2yIglgkdHZdVDAkAyRjFnyxYUrGHQQrx9w_AjdreKAvmqAREGBMyEIFIE0tC2XvG87XKMO9MRql7Z3wldilFG43HMqV2vfc13Pri9s1N95tXnDkdNu-kiqWgZ785sbB4_PdOKhrZjNJ55NK2MRMAKmuen8aKlrKWPqKKsbNi6SnIuQ-Bq4psRIhGQEhZVZkTCoU-ucqoF2StiVmF0akhEHAMUEAVFMUwpJgm9qCCaIgXFgGVBG0NwTXZ1NXTD9ifadZ0jsq4KJdkQ-mF44-XL7374tO3TnaPllYOJcdxuhvHEqeGk0RA19eiiW6szbMzBdPRosZyHdmdnvGjbF68fPHk693V9Ol_HVMomAcF6oDgk29RZxTEbNs_dvLY6m79z9-xgMn5yvrSjWhj7PjOiUXnmcPrw6dn16wdaJA8lxYzMxCoJHx4th5QTqoqS8WeL1eXDnWY6u3f_IaQSY9kbjx6eJQNmbzrxk_ro0VmZUAh9t-pcU09nEwTY2Z2tVytnOOWcckwqefNoOp4sFptZU7EzvjJdt2kc5ai1N_XYBtXU9ZXjIgWL9AVUYbunFUm-9qHtMSuC2so7gyporY2aKiQCtJaLgGVCAG9Qyha_CVuKqCESQ2GIlTMFQLMCcuWrYMJ20OmsaRpvAyGqM8gChogYiBBBkCiJbPknjKaIgqJhBlUmU4wgAAIYR7D9GxC1hkFVAIiItxK-vIUfgHUWFSSrgIh8NHUtqShAzImsE9SSi4AUwZREWSvrmTml0nUJiBCKZPTGaEHLNqTUhZgypCxMZA3FlISImVWyfnQNYGbeKl69s5KKAAQpKIgZkSCnBGpAAAwTEzOCAiKraMkioDklJGOYSYhrIyBDTM4aIMhFrDExpVKEmCQV9ZVkMdb0IYJASh9hNvuuL7nEmNWQijCjA9sNoZlVcV4UdZvKjSEpaF2PcorMkFLeHt9TLgKAwqJFSt6GVRQAwSAhO8ohsjHEnEMkRDYUU7TWpFKQcBtkZyQF4a0TjVGVURQQ2LAUNWyY1KDJKRdi4w0okHGp72MsdWOVuB75HHMRdRUaNnHova-rugp9wO0WBwkUjDVAqqJSMIZERlEwF2SLDFQkccVxGNS5JBkKGLZa-g_efySaHVs1thTo2o0CrFfrqObeg7tXd-udw72Tp08PdkfE5ezBkxBDWMOf-fN_7j_6j__WsOoZUttJY8Z7e-SIlRVCGtrASISKgLpN6QsgUs5CiIMUxo_4RUSoiKIgW1IYIm5BHIxICLLlYGwrtpQFSSiLuOMNEVpQJgOqoBJzRqQkoIgKW1Mp1aYZWYgxm8b0uZiESgEFg5L19oOjsy-0abMZKsZCWDn_te8vP3ltfLxp__ovfeHVl14ccvvai8_M9g8-yU0B-dkvff5He-_8f_7pP1PMb3zqEzuXdr75e1__zJ_-KfI_kvXgKy-STdPEHt7_N19_cv_xdHfcdt3xo7PTbxw9-7HXj-8ff-xLn_nhH3_v-RefXab-3_vsn9HaVU1tqcy7fvbc5cfHJ1__w2_0_fnv3rtTnYQU9ej4QTqPMAO2TckJlCCJ8bPRhFCkT0lzHk0n4NCoyans7o5zGrwjNNJ2hb1PKZK48f74-PGJt1UK0XpbN7WG6MBP64momLouKVmDRsRUXhWMdWDo5VtvvPP-95hHpSoGIalmySpQGweKTOOUuy5g4x17Tm08Oeu1SBrIsqYkiGW1Du_f_jAOiSpGY6yj-tJuL1TGI005F5VchqzVdHTzxRtYwFR2fnyR-_6ZN15__ODprU--mQ2RojPGs5t97kCQQynErKqYIjknoL2KGjZjQ9YIQEL0zSiK2NFosd5kSfnhxZAxUYnt4C2WlYJRV7nNoqtqn1MZUM7eeVxN9rh2-46X7VpTbs9XZneUCMSUNAywQYNw6dLh3_3bf7du-J_883_x1d_7t298-hM__Wf_bAr9ydHpfLNh76dN7ZxNQ1f5qkBxlkWKr6o-pJByZW2QshziarOqm6obhmbkU1LY1n6cRdKRGUEJf_rTr4Qc33py1KUiyEokKkykBH3Kogaw-MqlmFDQeJvDYK3JqeScjbUxpa1wHRGJWKEAUJFs0BaQbZlKRYgRQWez6dCfVr4qSYqUunKbvrdCCKgKKmKYcxEQzZLJ8Uc_6FzAEqIxxu7t7O6OR0Gyl1xyUtGBZET1dDZ59_aHn_zYq9-__aFRR85glkICbFNW40wYomfXd5vGO0cm5ICEOWY2xnp5-9vffObFV-98-B6RWGdSjDlmrCyxAUZRcWxGdrQuazYEAihCQMZwsQZVabtjVJSCQGgcl1KY0RhGIAF0xmZNyJxL9M4OqURKbKxmNWQ0q3FVLsVYAsjGmlwKoDIzKEQNs92dt77_4NGjB6994tXHj88Ody795Buvf_Xb33fGpKJApu-TbZxVyv2wXdTnkEsUroxmFVbjTRiya5C90SJaElkvjAZRSYlABaxzKQYyKKlQxYwlq9B2g6pCxueUm7oKWSXHyWzUdT0SWWeqqkItzpNk7NvV4f505OrRqG7bXkq6dDDr2gErBMACEPo8HY9OF6uzs44Rh1gQtSiulr2r7O5kcrZYtmFg5hxyMX40rRddvx6GqnF9iK7x9aRSzOC1azcHuweHbnR11mQsq03LbC1T7fGVm1eW6_7qpfFyOYRQskNKCkgpBWZSxtAHY3Q29XGZJ3t-3Xca02BTxcY6g5qSqOAWE1LYABQMfdjq21REM9hJLX1gZ_KQIOeyPOeaQYUMFiihGxKjnc7mmyGuU7U3mzrfD_0QQjXx0Ouqz7Who6PTP_XGaxRLhE3bdi_tV9_7cUYhttXewezo5Kyua4gh9V2Yg5lMxvWVqn06J8HUB8hiPeaQwfuUe8sOndt0G-uMq50GkVLiECbTKUAuiGgAI-WU2RhrjGoppeC2CkdFlVPMvqqNQo4ZnSk5Mfstvj1jmu5NV2eratQgs62cFG24DmGYVMYZd3yyaCbjH76vtjJx3ddTe7TYXLmx63eb1TwolKayuYjJAQz2pTw6uTDW7O5NestDP2DjUko7s-Z03b01n1_HyjhwYM5X7eHOpG17EHjl1s2r0_rhyfmNvZ3Qdd_68f0eyp4qG75YbfbGze5o9IPbRyHFS5e9Ep0sN7Vz_dCHqEMp8xjI4GQ0XW9aZ93h3h5k2fRhnXJTObKMxs7naybOKeVNv7M7Xrf9ZgAlSDF1qw37imVt2ORYgClmhZiTpuiSM1xC8nU1DHE89kUBVci4OCQtwXu32XSO0TqfU3LGhJgw5srX_dDPJmMp0jgLBSbTOoQIIpUhIpQkW5O2NZy6fhBTWYMKlbMiSgAE6phNXSVViwiojrmUVBk2TCKKqKjCiARaeYMCtAWZiCKxqBhDORY2ZvsF-UjKKEVFPnIjApQswChSXO0li0pBBFJWAUXd0jx1CzggIsOEQMQFFFJm5lQKEqWUECnJNnstyBy3pFFJqppVmUAFN5vgnBgiVEWmUniIAyEqljE7iVGsOsDtka6IGmYBYUBRLlBEoBnXbRuspVxEojhrUZWckazIlIuCQlJxhqigZmB227kUEFjLy1W0TEgMKtvbPyhKEcMMxlhnpAgoNLXvhxSH3HZBiXMRFSGiIuCsHVIGBmutgFhjMmc2pFT1ZjDsc4xu5GMbSi6oLCLGMaekknS7syAyTAoYh4RE1nhNWUshBs2gll3lSx-AcNvizSqucgIigorirO-HzjpHUkA5lGKNEZWxb7AkRsxFgB3kzIi29kXAoBlyMM4axtWiSyk2VbWJqd30k51RPWnKumcSUJAsYIQUCUFQlRS373wuKiZpAUVjHFke13UMySLN5-ddO6BRLWgqH6IM_UAWciz1aMRD0E3cSBdiXC0SVJPRtE8gv_gXf-FX_spfMGg2J4uIxjuDkNu-c84lsmkQETXMhMKoIIygrLRF9CATAAChI45SUCEWYQDjyGYBy1JUCTISakmiRQ2mDEApl1TA1MZ6EuJgDQANotvbpAERFkFQIWc9QwYArN3-kE0FMQaTMnRD5RqOfSQjmR-cLqc9vv_u481qFWK_e7inCF96-fm6uvrirZ3b758QfHCxOXrrne9-cPuBSmhMM_R4-fql5WpNwquLlSXr3Oj4ydObt1548N5bKWaJhVViSmfHi_Zi88qnXh8WG-vsrY89uzo9tg035rBqxnfv3_3xt7-nSBElbgboN1w33jiyxKBFMhszODKFdj3Gw1Gzv1NyCiFba7rO7M1maGF3f-omu_fe_7CIfulnPvOj79zu2oLIqYsahbzmsK1Rc7_qDFrswXuKkVNKs9luDNl4NtjEWNCOrEuOddgEySBF2xgA7O17bxURatgbb8Zu9fhCiMaz2eLo3Dvra7XW-RyJOMaynOdp7dJmsTlf71yasfUJUh-JvZ8dzsD6YiQNSV2zxYYx643P3sRuePLOyc7eXtvFvau7F8cX7WI922-GPjz7ykvHJ2fOV-uuhz5c2rFDJ2QKGr_ebKBIiP3B_l7JIqUYNG3feW8vlqtb167ML9bNuMl5k4Z09dLu7XcfmGbcp83l2b5jXF8sdy5fzRgPr19aHZ9iEbTy9P7jz_7CF1zVbJ_Oq_P1V87-9Zef-ZUyCZaKZTy8OlWRdQmpDDfGV_77f-OvF4Pn95_8n_-Tf_DMM6_-5X__Vy6F_v7dp-3QE5ukQJJTn4nzZFJjTppTCQEsL1ddu1kjoaAKYh8-quxPxx4IQakZV89dvT7E9PDp6nTZkXdRQgmJDQ9Dr8LgTAnCDkNfjMGiMrX2bD2gUyTMKXtXExMjqgIDCoExVrIQEqBa41MJxjCjSzmGLvhnGjwhUSDCoACi3tqS0pbXZpiLbEFzWFCJDRQtRcmQMZYt1rW_cWWvaSodpGiBbWUH8LzrxnX9G7_9tb__N__Gh3cfDGSq6IchOLCqmksmhd1JXVKpfKUKzllhlSGa2oVuqBqf2hhimDSjLvQKoIC-qlAALRmyKcaE0kmH3sQYHTtrHQrFITnnDVMxAloIoaSETAY5pLINzioUy94SobX9MGzpC3Y7slBAxZyjEjLXzprUF0BUQOO4H3qrSGSSms-_8frXvv6t6XhnNB2tVu37H7z3pz775je_88OMnD7KNhkEtEDOu5ALEzpjiwAb9d7nlIyxaoTAiCYkYLUqlCRb3yAWlbTtRrFzfbsyrsoyGOtTzoLgrUVQyQIE6B2nIkh9H5yxiJpiMMTEJDFvqT6M7EfNzmiEOYmAiNJWiyBYUlqW1PfBW7vsOmdcO4TppCbEHHPpu93ZyCqTEhtbcloOnfPOAKPBklM_xMmswQI1mz64x_Pzg-mEkC6Ndi5yakuWIVzd3xOF2stiFearyATGUCzCzJLyjcPDh6dzMmVb83BUSErohAyhmtTHSU1xCNZZy5BC3HTtqK437QY0s6WcEiE7Z0uRHDPVtp93no2EoDF5P24XnamdndRSYlbnxfZQnqxX3mDTVLM9P9qtNyFAm-qm2b80e3h0dOOFy43nzWodg_zx7dMsSVAyaVX76WTUrduwauvaTGZTs4mDPaspuZzWbI2UBEzgjBRB5lxUoihnEY2dAnNqQz2uU4q-dpRSCsU5y86VVLyrh1RKEedcinH7bSTknBIgKrHkTGxEsvN1KZl5DED1uGlGHrdUdVECI8QhCY_YNf58uSCD2oFtXBHAQLICN8MNMZOLijujuo-hGVdayuHeNLGEHMfeFDQxZWeNpKwCX7p1adXGfkghCBCtu346qlIpTxaL9WaNBZYpOqRedefSlBEReRhSqPJ5l3pABTo5WfqmWs03TW3X8_Xly7s7I79Ls8cnF8Oyc54VKaQ8T2k5RAVMQCJlGZIyDCmqqoboqjGmaNk3B03oB2IIXQcTk4pMvF2nZKyzoxGCxhiZGBkFyDg7Ho85Z2-tlsxEOeacUm1MF3KMMmsqMmwA-xCd9UXUOZtist54awyB8JZUoM6ZCGIdW-8kl3oyLqoMoAJaxFiOIZiqIgRiAhG2VnNBxBgRt7Zbxu053lakRaAII1pjtpc-QGTmPCQmLipbdaIWwS1XR4S2y10FImSiQgpFDJMobwfUiLhtD2_x-AAIiKUUIMqpKCEYKgWyoipUzi3bPqRExuS03RCA5uxGXooWoJSVpAhgF8PWBWSA-xRVAUUAZAmdN1grEYhkRVVmLqXodoqBZRgSbofxCiWqIQaikBIqGkXDpKBbfoUhoi3BjpREmDlmAZF2NXjrY86IEGIxBmQrvCEQAEXY9MOo8gUgxagg3ZBSLPXEZtWkULKEmJ13W00YYnr65NS7xllLhDHmUTVWACbshxhjIiYtqgoSt81pscZGiVsCHhI4V0nWNERALpKoADl23vV9sN7mLK5xmsWCMUy5IDhKkEFKbb2UvO0IOetVCgMNObJlECmKSlA5n3JBMgoZSOvat0Mwvq4nVdsHIDKVz31IuWBKtfdFCqqKSOhiVXtVaYehqS2Q0SS181nEWoNMSGSJhq5HUMx53bV-twl9z2zOFnMRshUZJBWZ7MwM-Xf_-FtXbsw2882nf-Gn5o-PTx4__c__i_8TKkhfln3X1E0MYb1cTyr2TAyaRIiIDSJSyWXIRUNWAOaMiEZZQJyzEcoGsBQoiMa7YcjYxZLBeGOZSCnmaEittd2unWZnxW73uzFC24WhCuOrN37t2z86P11ehPbBxTz3XUmBYjR98sClK9PD6d7uQRzg8IWr33rvRycXJTw82p_Ik9XKyI6F4Jgkpnfee-vpwwd9r7uXdlLIIpnxh2zqVOK3f_BHkDML4RC9m-QgJWYy1dBdNLt-un-J6mpnb3L33Ttvfvknbv_oOwRM28miCDFdvnHw-P0Pc0ayrjvNm4vVzqWrj5-8M542IH0zqrOCkVzvWLO3I1mcdcSGmIypksDulZ3xeGdyaXRx3hv0V28d5D4ZJ0CNsdW9uw_YsB35w2df9FTe_Nynu0F_9IOnrRgcp9X5csQcCz1z7QZb-uHvvfXpv_WT3Xef3r933-7u71wea7_ikQPmnT137_b8-deeWz25B6iXb-6_9OYnfv_X_uXhM1dKInGmHlddKd4743mNgA5h5tOaaaAXn795fPxo_4XnF09OJ_V4dLkH54ax1Jdnu1cvDzrc_eG9G595eSxJ29iGaGrv6nEOMfXD3qXJczevlYt83ubnrl-9cePw9Phi0Q3r06PVydPTe3df_MLH68lkb2dnHQeLPF9cXDmY3rp-aRU2OeTVMqGIZUtMpeSd_SlmGXkXQ1exKXGoDO7UXk0FwDdevTadur2dy__6t35XUIZCe5cOJIenH54Mt3TPuflydedH72xO129-4mU4D7mPxVQ7Bv_J1773648vXr_0xb568tr1T-XZrK7GlAqntDy7COysr68_c_N__h__w9s_fPt_8b_6B7_081_-5X_3l0-Xq8XitB1i2w47dd3HTMhgDcdcVd6iJiJ2RMxIyCDIwBVDAlDkrHXjPv3y1VpoNhrfN5vJZLwcBgQahgEA-1iyZEETYmhqazx2q9Ywtzn42vT9wM5Ilm26GAhKVsuUYiZmtkxEJeWSkvMWWVOIWwJpvwrWWpWtSFwVgZCQrai4qgoxWmOkJGN9kcxA5MwQBmtc1sLki4hV3KzbZjLq-1RitMp-4hGx2tmrU3j_zp2Pvfbit95631uuqE5dzCFaIlItBchYkSCgWIpHE7GAiq9q8tYjPX384NnnX7hz-11yhh2BgIJu_ZHWOciQVcgaox-tNXLK3rk4ZNeMAaOA5lI8GyJGAusYEHErS1boQ7bOWl_FbhDaJm9QRNBgUQXgnJKra6hcGKKvfM7FWiegw9A_8_zL33rvNvlmleKP37q7P5noej208eOvPP-jO_d8ZSCDdAkVXOVDL2ChFFBEMhhDsdZpLqBAZC17ESUtgAKQ2HEog3OsCRAoldTU06HvmblkNQzuI1cAbh1pgLperZrJOM07BcwlTkbTdrXeu7zXtm2KKUrZH08v5he3rl_JYJ6eHb_x4s0imFMqhkPeejuxKGYtVd0sl8u6blRJoXDlUhiWXTo82M3zBRgCgH5IaGR_Or5_ejZu7GQ8XsyXh5Nx7R3W5ngxz5lCLnu1X64HdJyVUpEwxND3arANcdf5IadHp2e3DveylEnlUHF-vh41dReisTAb1d2yq2sbYhYow0Yr72OIQLi_O54_me9cvd7UdRfXIKCCOWZMUoTYqKbChkARRCFLjsmPTLfcVLXPIruvHMy1PVq2z-7vPl1vbhnz7PXLg6gnPY_DbDqrRxYYD6e7uUhV20L65N0jQR9iEmNENbS9xMQVnV-c3Xj-WTNp3NnpKcfiD7zkqMWknMBYzRm0oOUYFphTtBWT8eOxJMkh5qS2ccZ74qwImgs7CrGzblQISkxcV0Mc_MiDAhJJySUXV1U5J2avRY0zCiUEFcQopfFm08YSdW9Wg20ywHq5QcmEeH6-4NraLKMD78AsVp2tmoOdatOmoS3DUHYn9bzvzooOIYccQ9sr2ay4X7u-i13UJ0N_rdS71aQb1lWNy2XnmdteOcazPj9uu0--8ryipR3j5022NJmO7t27qJpmVNdMeH_TegOv7u6AhdO2Wz5Y7UyreLFxV2oFd7C3m0uZTOvz06UCFsZigKtqFYIFICkhycXpcjRpGuuePD6at4OUtLez3-c89aN-s2mrUSrCKCFFW81AB0JwzjjrLGNJCqiopkhGAMNmS83JCQKoZ0haQi4EQASOXCkFpAwp7EwaxG0JERpvc84hiSgYi94Z0G2QA0GAFJmRiZDQjRrJ4ms7dMkSIsg2wiDbdA6osQaZcojGsBKyIhEa5lJkW4CEImyMqLAiG7NN9ysACBjLW3qPsbQ9A_NHjSxEQoMIiqBgmIuqKBAjAJWURVQIUipgCGn78pIVchFEquq6G2IGCDGO6zqp9n0sRNba4_Nl01gihEL9kInAghXAEjMxGKI0JPQWJFPjHHMqwgDbAkDRIkWqyqdSUhEBCbEoY1EhQlLQlEAZgIGgiDaWYswxZjSMqKpgrVHJALgluEjRyjtE2oKMQHU7bypFxDs2cLZcOV8Py3Y6Gw85933amu7JcIxDLlI2AoSHh3t9n0tWa20unUoOKaeUtlqWXHLK2bAlYhgGFd2sVq52WlCxGOdLyNZysJhyIWNUIIewhbilGCRpNalCiWGIxhECEqERIsSYI1lmImtsGwKwUSlbdElEZItDDGwMMKeYUDTmMKrHRQBEjWUbTU5CKMaSZtFSStZ6VPVDkCxsUBBCzE3t2XDXDZWzRAR5C8YUiYXZNY6Cwvp8tWpbXS8ts4o0kymCmkztau7rqr9YnB2frtv1ZRw__8pL9x88_tKf-XIVyoPj07OLcOXqZWrT6vzYTkbrCCnLpb3a-0ZAc8ySwBogUlB2jkg1Q9ZSwAMBFMrJohBOdkar5TA_H2LmpacP1v3p3aNxSxREoixP7qz7FGYvhIv3J_3u0fnbm_xEIbxz__TS3qWZxfWTBWUxKpGh5FRS9Barxs12ZmL9ux_knKNTVKSj0_PpeFrV_mmyobOeUxlCqaur1289enrnpVdef-W115OEP_iN32eP1bhK4mSQftM5BskqKdY7ZoipOw9P7z8g53ene8PQP3l8r_GjdrlBxNF0N7ZdLkO_2ZBxe9f2lxfzupoRiJnNHt17xJO9yc1LUPnxdAJ95hcaA1W_bnO3aeqqAPlRHUoaW2PqerXsR_vj3IfzRb9YrLEa4pO4t7s_Mm5nMt5slqdPH-5d3nPNzu60Prw8vvfhvc3p2e6BY1-nITaN272ye36ywNqBKE6aaTAXgLR7CfYuNRbOb7f-6m5cbUpffvmXv-jravzmrd3DfSzwo-__-BNffOPRg6cl5_X5-aRp6r2J9bZ06WBvmks-fji_eeN6bPvFycXYjU8_fPTMq68d33lojPO7k93rlzen89CFnf3ZjVduppCyaF35g1tX3MGuE775mZsmlsWH53mxXCuGoFTTfLGa7o4bA09_9E7tayztyXv3H374-FNf_KmGrRq8dvXSg7sPT_3Fo5OjF29dn4xHo1FtfJWHvp7U84v5xDfNqJ7s1TGF5Xxe1Ny9936zvzvZ33v6b08Wp8s3Xos3r12ah9a4yfff-4P9-tZ4OoOLk-O-Xz09Gxs-Ten06fHm7jqB1NU4S3rjxr_z6dc_xTVuhj0qRVIuNgKVVbs5n69n05lz3cOHT8m5amf3H_yDf3h-fPQf_v3_8FM_-fnP_6lP7dWTYZMsmGJwsVjllKx15GyISsRayBj2nlKfWYwpmFMpOdeNmyqYIcqQ3nt0frC_K-Uu5oIlay6xFGCKMSEk72xJoiLOmZQkxeKdo5wkAyJ4a3JOAMgOSyl17UUyW5tjIMNSQECsmsIQU2aG5XLtrEsx101NIQBiDNkwWmNjGIxzxExiXeXjJucszqJ1TlXJEIMCCZH88PaHApqlWOsIcDwaX_TD8cWSiP7b3_rq__p_-vfe-_B-1w_b5bkx1HeDscTstqznEIP3ruTyER4AbQyZVJ1x9z784MVXPnHn_XcME1pGxJRyIWmcyyU6YwUpi6SobG0o4ljYmiFt2LIkAaAkGbXUblZiyipkmIk1Z0EuqKhgrFFVAMiSnK1UMxEToBRJKQOicwZU2RICEMN4OtqdNscfPAU2WtLR03PN8uZrz_7Wb__-L_65n_vRO7cN2j4XRmImZRULlCFJcc6GmACxlOwql_qApFkSGC4pWWMFwRiLIg5NX6JxzMaG2DVNQ4hDCEBq2BqinBJZq6qlZIOsBZz3IhmIU4zWuVW7Vi3jpsnrnpnbTerbdtWuzi_mOV8V2Y5aSk5SEM4vlr5pNu3AZKz1sSTd8ow0Nc7lXCzRqHLzrstSfGUGyZW1B9Om7YNQbGq36LqRmTZi1eCj5cVhM63IQipdKY0xMUZAAMs7TXN2tlxIAETvPCkZMJuY68YvN93OzrhfD662OQbV_Oyzo3e_1VbCPQxcNQDcLYMHmu6McxqYmZCoNlybbr6xxpAKI8SYQKGkrKmwZVFSMn5a501n2Jy-f3_n5lVf1QO7-_dPbrwxujLbXcS-rzxT-tQbL3ftasSmtpRT8sYkCMSVM55MNIghpNwnY3RDCWp-8viBySHWja_2_KZbQRI2lGJBZbROVWIcNCbjKnKMRYbFBSmaumJj-_m6GtUiqrmklBSxqrxKtsaaykkRIk5DqOoRMVnng8lSoiGDBM14tG6HeHa-e-Xq0Kds4OKsZWbA1A9pPJqcbZaEpKIlb6CZaddTUDU49gwI84tyEkO17-dDHu_66aR5uhoGkfOu5cpsAE3O1ttV35dQ1n3yQoraSiZju74bTZqhDRXDkNLFYt1YfnJytm5Hq3U_9oyMR6Fb9Ln25CN8_8HRSuLre5O-TUfvnbc5qzOBTYlp3cWQSjMyfcgX89Wotgnxg_tH6o0gIBNbkxW6kCaHk1Ftnz5ciasbY86fnrVDC4bP1xskbDcbbSwnVKZucz7yVgVilmbPG-FUomVar5bTpkYypYioiiqCxqypBGvYxMRIVrWqK1Ax1vd9X1lyxuzujjQVEK2ts9ZIFmO3oWZihDSE0WSsWQDUGBIFYxgYiIEZcy5EaIxBpEoBCESFmQDRG7PVFakKsymlENFWxLg9npMSIkkuAEBEqvBRgkK3BlhUEUREopijFVJAIJSsxMjMJWeEj2y-SACAIsqG05bKoaKqIQukIsiSFRSB0NfVehgq5y7WgzFMTpra9V1wzqgAWxtSyiEbawsAACdRZkxaQLR0wRn2zoRcDGHJBciIQJFMxNZYyZkIYkrbm5K1FhFCytZxEIFcoqUkAogqoohIlFIGwmZUhSFVle1D0gLWonN2zPUmhiiScsy5rPsQQvZNE1IxnlebrhmNESOz5phiSL6yWQpZkgQlJaFyeFgdH_c5RiQK7cAVGzSSBBSJcFS7dtOBIIgob-3vJAp5SMxGslhnhYAAMSTn_BCG6c6OFokSWbSpKlUlUgDKUerGaVFWU1AEKYGyM0VlXI-HEIDRGZdLrps6x1w1NYAaAyHoEIMzhiyqwVIAUNfLNZKZNB6ZckipcJFiLItA2_XGGhF05L3PuRQTy-74wJHttR-6tjKuWy0UmMnuTw9M4wl0cXE6zFfO2YuuM6JnJ0_U0uHu3o1Xn73xzDM_9auff_LweDKbzO89Op_Lt7vzo3fOX4rx0nhy4A4ePLyz4Hz29Ytn9PrkYNJj3w_zZV-etvDs7jWkeJafxpCPu7O-xdkQSUKJ0_kTeWZWWC7atDm9WIIzoLC8WJu8KJlGY197VzXTX_hL8jtf--q826zagoDN2P3Epcs7t154-O6DGi1TGU3qws18PUAl45EtJR7cfO5zn_vSzkuXf_3_9evPvXgrDIuv_f4f78wmn_7kxz79yY-1qZSk5xcX85LzPK43Jy8_99wL169c9OsrL9wYLs7mi8GP3KRuojHtYukrX03G6qqmmd6aHo7G_uzofHl-mpGHYVgvNqO95vv_5g8vX7n5-M77UoSRlMvpwycx5Y66vcuXzx88qMlS5Q4uXXr41ofk3GhSD48GTfKpP__l9Phpce7uhw8k5aoy43EjapsKLboEabNczmbj-fnm4Lnrs-k0x-5ivVidrVIHzvNs5oeuqypTQqka9-z1ncX5RbW3t160TVPdL6tZqIzSZOS90P7ejqvEe60s7bxy-ZlXni-b7mBaWzIM5dLVQ6Pwm1_7etgMP_MXfvqfPv7XwfQ3r106PbsYA2PJaFEC7o5mb3zpM9_6V3_SrtprbxxaMuj16PHxF7_0pT_62u-GR-GX_4NffXTn3ZKkmRrhZyvnFicXBJxKlBAmk1l4e37t5u7Va5fz4d46DJ7ylStXFsuuj3L29KRbrC3qbHc3DhsY1t_7rd_g8e71Vz42m8yuX7mau-HNV1_qu4EKhPmKd_HJvYesyCBPVo-6xXI1X5rJdPf6bghl5_DKh0dPLoU49oZSWXbGTl5fPfp9i10tV57eP-rkoVuGq1cOplcvX3rhyjvfeWu9ChebdTNxhHLp2uHB0-N5Pp-NL12d7o1mE04lhHZc1R2vX3j5Wj2qVxfLG1cvpZAy8NHpEevwP_w7f9va8ltf-cr5av1L_94vUPaffP661DdX683yvEWFLqSpH89m1aPNeuRttQsqxI2pvA_L4dLuaHZpz-zsPLM__d1vvbNZvP-73_jx9YOdICAAsWg9qY3HnJJhCn3xvm5jMqQIUFIBJWOgZMpSXG3jEBUQBJRBAYyzORdkQi3OV6oCKoZZRRwzKKSYp5OJSMm5eG-YtvZ6QmDYql0QfGOHITdsEImtCcOqGe95a4y3P3r73mQ2BeSk2Xkfc8EiyIiJZ5PJxen8hStXTpZ3a6bMnCUj8aBCpThjQaWYQsxDziXnpvElJUKSBHZka4bH9-88--ILd9677YyTnI2x_dAHVAFFUesMWKclIiozxxAnzW5ILagyMyIb1JhLKq2taoiD5pR1K-IVKOisi7Ld7aoxFlQMGxExzCULgHhfSUk5FwXVogXo-rPX7z94hGJEc06pH1rE3drUMcQ_-f73f_7LP_Ubv_9HBok8ZtXQx6r2UZNYAGJn0XnXtS2ooiWUgqBaCrLJRYg8ChKAYWco-MqpbE3o6rwXUBUhsgIChtjZGAbn7NCFusmOqVCVUhiPR13bFQFEmo12hyG0fTeejDf98PjpmXF22fV7k5Gxlhgt2iQynU36lKWI8yZ0PVlylk-Xq_3p1Fi7WWzG1ky9jdFsMuRSPJluHRq2nQzjWV16DV2ONajR3abelNiVMLP1fuUlxN1mlIoO68Ewr7veGO5jvLQzPl21t88vntmbQabd2WSxWndDrEe-XfdXZ-NFl87vx5vXZxeLHgSGLhMDoMaUJ5Nqueqd863odNos5ytrWFMCwRwis8txIAYkRNCSArK1zmMZUEpZx9lO04DdAXuw65-ezT_-3O7I5wbIFVNlHIp2fZ5OmtwG9W4zX1-5fvD4rM0pG283fVEFa6EeT1arDTIbLEqM_aZ3O1ZCKatMCppEoQdnQTJbBk0wFFVUVGQbu95W4Ks6pZC3w1lmsqYASIlMBogJ1FsHiCpl6x4SldT3lthUVTt01vkCnLMqFgUqOUtKYUg8g4gZjBFEDclbzjG5UZ1KSiG3FPf2vGgmD5Fw76DWqHcenPy4PVtU9CyPD8ajtotMuhnaEbtq7J6_MY2rfHrW-pq5SNpISH3NPkG2lWkH8_pnXmyPlkjmYt3ZapIGXed2uteglDtHC6j4E9cuHz9aXN6pipRe4Nrh3tt3HjlvdqZT6TKhHp9voPGL2C3ai3mM-6NaYjTGGmsuztdDzsXS8rxfpeDYSgHr3artdqbTAooO131_eKk5f9ISyhZp6YgmsynkTKiGqfJOpCBqViXZ9iwKWgYREU0pCQAAjSprCuQUZqMmhrjo-v3JJJXYWFdyEQBQNJZFSu29AmqJZJzmggCI20wd8Vbcm8EwqhKKimbnvRAwoSojAAEUACTYSr0QwBAXENmCnBVVBBTJIBqzFZYZa1RUAaCUj1xgiCKipTCQIjICsSma2XApGQEE1FjKSRUxFdmSc2QLYS-YigwpW-MQactizKVIUWRuQ5RShiKQFYAvzXYXoQ8poxYRJaQcCir0ua-9z1mLqq-dIIStQxdRCIsokuRSSi7OYhLNW9yyNVrUsQkpZUACWG3CdjSSsooUZ23JAohbgzrIduGJORViKrlYMIq6CQNZggGSbLk6Oh01i9UaDBtyvQxdPyABoiVW5gKIOWdrbMppGCJbN1_klLI1PHTBOZtSUQlsmAqhIDKI2ZZ2ceTNetNXzhERW0NEZDANxRqXQ0CQoeuEQVGddVokxGIM1r5KOQJCZbmU4qxVBKeaRbs41L4qCqUkJiw5We8MGikFmEsItXdpAHVlK_ZBcGVQa9gyS5O2n7fGXI9qEcGiioXJ1F6ZjSpAGSbNJIQBcwKJ3dCG1K9Wm0fv_Ghnd3zy4GzvYGoNA3Hl3WsvPNdMq9_--q-_-cIXrzxz_aD249nY19OUh1WXj9dDc302CH7_7uM__LWvXDGoXfpx7ktGP-JRM02cpR1-kLNzPmbM2FkCVPvUVlm5jR0bZQfjynUe-_PW1ZXr7GYwQ1hhEUhlNmtSHEIadhpbgG1tTy8W4Wz1f_lP_zGs186xRN09PDx5sGnG-NP_gy8_fOsfcUVV1ezevMaTnZvVXsIhLdqu38S6_ua92-bDd2aX9y6GIUUa7Uw_9_NfqGm08NWQ-ovF-cny4o9-55sedH768JWPf3zTLe7fube86I5P4mIRPv7pW1_84iesrecX5_fvPALGVLRfL2e7e-vFGVjy4xGR9DG89Oqr997-0Wo-Ny8-n1LhupF-8M4sTs6n-3tgIHTttG7qyYwsL4_OXv_sa2G9ZuGLss6yd-_b742qgnW9jnnHcGXdjcOrEeVkfoHGQsRmf_eZ52b6Yf3Zjz9zfr48HYIYRl8Ork_fePX6vM229iXFTRv6ILaPKcrhzmj32UsoZefO6c54enqxtIfjs_n88MqV0x8vOeWX3nw1Dau6cujd_u7O0AXIEQF-_4--30Z98aXn4pBef_H5H9_-8Pji3I_qVPJsOt7b3zsc7e_vjV_-xMGP_vAHh5duIOJFtxpEC5TFxdHx02VMZVrzfsMFrERplyH6MrGVNUaKtYadms3QHT8Ua3G005RBZqNRbHvThw9-8MPHRyeQo3rTbvq9g2v9_dtoUJeLh9_94wdUPf_Sq_uXrjy69yDl1C5PT2_fAbtTz6aHNy5fvnHj8MYzabPBKT_8wYcQM2Y8ef_ewbg6-fHb52IIq4s793Qo1Dg7GqmUGekk9UFXq0WZL8_PH91tRvVv_1f_eGgHGHk2dli3zHZ1vnrhYy_2m80wRCxaN1UMcbNudw6bYehLkAwprNtSRDel2t_f2512bfeFn_vc0_fe-Uf_u__EVo6gqGLjbSzgmgoKfukv_RyCvvfOB6vTAVSuXX1FCYn0ytWrr7xwfbnovnr63Y-9dMtAeen5y3XNm055bE-PT5ddVqIhlj4kgGItpzQgkqqAKnqgosQIzKDYGCokCgLb6hcaidkxiyoq5ph8XfdDMEyIGIbBMBvGTbvxvhIdQJSZs4IWSClUVQWw3RVbNpBzLql4b73xXdveev55w8Y6VgQUBID5YrW3v1NKsWTROGL87a999b_3K3_5m-_fRQBRVQWDCEjKioBZCwKiQGU4OZdiLiLO24wl9tGgSJTTp0fXbz775OkDY0zJyRvHzMbaoQ-2qHNespYollCZQloTmVK0oBBTSskZF2LyjSFgIC1KzDVI1KLCBQxKQSQskgHAWIPARZSYUDGnzIYVEqERkKtXr50fn3btoAyWTFKIIecQp5f3-5y--_3v_52__Temf2TXMaWsWgoJyFBQtbIuq2YFBHXOyXazL4CELKSo1tlUYomFjIm5n0zH6_XajxsEROVYMoASoki0VbXsNqOqtsbEmOpxFUMYT8dxswHE5WrpqwpLYeOOL068dykn78xy04q1BihmaPsw8y6mUvkqFvE7o9XRIheNKTXjUdf1IaSDnWllXT-E6bTKJdY4wlxySN5bX1WrLhiwTVWVviAROxIQR1Rj9eDiaLJvvK2u-2Y9hJOz-aXZBL1fblqY-sY4DHC6aj1xGGKIEYyxoOOqevD46NUXb42xCauhUgZPccjoOa0HVnTed1kkJcNVCakaN6KsgJo09xFKceMq9VEFbOVz3yPKR1ggVTQYY2xs7VhPzs-dNfOu2x1NH54e_cRrz0vgmNILtw6RZDapLl_eZYQnj5abw9RiXpwvmukIH-d23qMIG86K5NzB4aG31uQUgRHOzwpOSgiSMhFpSYgKcZsN31I_VFDJ-iH2vpls02nI9NG-iUCloLMaCyCVkqWokLC3BJhFC1HuB980JYYsRWKxM6uYQxyQedMGSKWyXDVVSCKbTi3kkq1DyQWjhNJXY79aLWf1waNVG0O8djDL3XrVw-zZaTW4Q5m8uVs3jnowmjR6vJin0aWqzzAJGIOw4c0QyZvR7mh-tiaHs916cRyayn_4wdnN3ebh2enVazttn3ZmfGNvZ37anR0t0WAFPK3Msqp7kQ5LW-TBYt2nklHfPzr94ou3vn_7KIbQABwe-idn7cjZ23ePXn39xsMnF0-PL0IfydnNebdYtqOJUzL1rkvFYiEhjEOWIRLwchNCP0wmrjhMSWaXp91q7SpfOWcIcomMJoeIKsZZUUDLzJxAUFUJQimC2A6BjaWCueje4e67tx8xm5DKSzcPiBEUJGXLTIgEkCWDAhASo7NGBbZnf1LYikW2UZxtb19V2KAktYZEEUAJtoN-ZiJUUVDNxZBhtggoIiqqCkgoUrKolIxATChEiFCyeGuQMCclJkCQIgTIxkguRAjWSCqlQBER1aIS03ZjgKIwhFQUmU0sWTMU0QKSkw6xB4GkIgre2XUX2eFp6kEEGEPe_lNrKgkFYskITAhIJm17p6VIgYxUVU5Rt6xHQRxyVoWUMhgqoojUhqiqCdEjA1IZEqIqQT9EQ0YUs2QmiiV3XfLOGmsQVfJ2TwKk5IzNOYMCGWbkth0AQUVLzIDUdoEpZVXfeEUU0M26L4Jx1Ve1H02qs_NlVVcoUkR8Y7NA6pISppBLTsbwECKhsiMNYtnKGDWLgoJqisnaylkTYtyuHe2oKqBdN9Ter1YLY5yqWmb2bkgRQEVBhCyhiBCWUVOXXByjglhjimpMGQGYmbSUoiVm751KySVvyXC2wtwDqPJ2l6JYkECRiY3HUvI2fQ6MICKE624VurUzGLv5wf7B8zeujcd16F5rN-c3fvHPjhzGYfDTWWNGgnJ6dPYXP__Lwtaa-kFO-cMnV_Y7HYYTDffunLz56isfu3H1mV3_9eUF7rh1GIgoIYMYAPB-bP2sXcxzGmIf-tQRwWSys1l3uaSQCzL5qlqs-7ZdQilt109HBwuDo9qQ8sl8fbFcGwRivtAkyI3FSzdeaCO5FF_8qRfu375766Vnf-6v_jtPbp_cfPnGN777zWoyWm5iCLl7dMbTELp7sumMQLNrJE3Xp3NnTS8yP-tGdTVf69f-8DubPl71E3CQuwEl7jexHk_2D5-9cXk_bTZPHx1lLbOr-7iPT9frxxfnTnh5cYbGcGXDum3XPcD85PGpYTPe2amduUgXz1w_fP9Pgig-uX80u3p1_vQxIivZatQAat_2CMZ48ma2WJ32pTt9AotV_zN__k_f_-0_nu52EfjGlavHR-c7O-7KbIrOuip646Q0m0xNVd24uvPFn3z2W_H25UruPjleL1eta3a8OQL01k0ad7Jc70wn2SZbIUrebLp8IM8fHgxQbrx89fVXn7nzwZOP71-2NLT9ZjnE1WZY_t43_vTP_eQm5hcuX60bUxl2tln17dnF0lhvvB-Ww9Xrl9TAt3_Q70wmP_nFL_zWv_rtV1576cVLN-zEP707n4xG15-7YsiOw4RcHVPXjP1f-Wu_9F__N_-My7Kq6r7vKm_HtU9FVYu3bO2ICLVkrklyMtbGGIrm0XR3uV7fW1zcvvOwoiJAEDOQXpwesXUpJ2ughIgaP_juN-4S8Wxnun84ObzOai6_-dq08sd3Ht-_fXtnNBbN7XwOwDm3KL5fnaWzXFu2jTeuai_OULlhvz46EkSVUkLPCAZbUU6EJHEz3yACbVIxWBPN9qdU-uXjDz1Z6Dpg07ZZs3hrbXYWIZRc70zWqcx297r1YrpXnz1-Ogj8wb_8ag7tuKadnclmuQmS-3WnSCkEFfmtf_yblgQNQy65G-YP7glnEvwB6Ve9C6EAGzIuIzG7AiV0_Xg2xsJlY179U2_u33rG1nY0bVIoikgRwHHJCkREWFIxllS0gLDjFMWCU8wpJcdcUEEKG1bVGKMUQENScs6CTMCQijSGWDjEKJCLiPceFHLJlfVDDL7ysj3MEEopyHTj5iUmWLedATLEMWWDjCChDWAwixoGUzdnZ0-byh_uTbt5K8UhieQSZUBm66AExAIpJ2MNoZDn3PWEyITWMgOCgzDEtt1cvX7z6MkThC1Z2EjOZGjoeltV7JxqIaKyDGjBMGYU78x603tDSgiIKQTjvEbJpaTUESOxTTmRsVrK1sWLgClGYwyApBTJWMM-DL1zZqsU2JtMzi7OVQoSDl1HhhXw9GItgO2Q-lT--Vd--2d-6af_v__0N4xp0NhcehFx3g3dkBGs9X0I47redB0B2qbBmBGYGQoqGyMCxpo4xFSBEkuGYYiT6cyS9DHWtS-KRFTbWlDRsNuWfUVVwBirWkoRZhtDRCBATVmc9YhUch7tjPvTlTV21Xe7Yx8GSaVDoqNH50mKovZ9_MiqoQIFM-S98TiVstisr-wd7E-mIc9d3WyGQEQhhYnzx5sVk9l0oa6GPdvcPNh9b3kuACg0rRo6W03GJuw13Z3FxbqfAqopQ8irFPdnVdmU82VbN7UxOGr8uKv7kIxCKunwyvjuozNFECAASFkxZDKUA1o2qqgIyFwQSs6A4GqnVECFmRGVrVVOxnOKSTQDegQUTcMw3Jg1rHByvp5ctV_9jfd__vOfykA3Lu8RpuV647xh5FR0s-ku0uYsDIvTxSefu3k8Pn86zJ2j0dgXiWRcHxIw8fRzn48dsKm1D2hEtEhOxMhocIsmFaBtEgO4MLKvQNFYX0pfclEBRHTWlSyaxVY1WSuGShJBAGdTViJ11m9vlMxma7pXomo8KjlXY59DLFmQQUDJoIrmIRhnY1BTW8Oco8QYufIALEVyiOpxkfPNvf1GvAbjbT2bmpDh6aKrm2YV0gu3DmRTPKqzGlMphJCLU2xIR9ZoKJVhyVJCNqjLdYhFD67MjHM1gQzl6OFSGGaz8eUrk75VURiggHPHqw0zrNqhS-WV5y7XBT88XRlHLzw3u__k4myVoObnXrt-crby3rmpRWe6tpMi3lcosjqfD0MpEad7O-ORW12skMA7ziGNZuMhpMr70bSa1aMc83Q0GWKofNV3PTJ5IutcTFtMuEkxgaphirn0IRnDlWFABdFcymTHI_CQy3LTdlGauoYibNEZds5KEe9MElUt1myFXeAMowIobKWPxlBOQoSAsIULeO8BhAQA0ToDAMSopRChsXabOwQE0C1xXhRVUIdYhCBnGWLaLnUts7FGQUVUAIsWBHHOI4KUwmwBcVsbKCIll60hVVRVsaiKQFEVhFwkgwjoog3WGjSMQCHLbNZ0fVi1AyFl0RhzyBpy8q7q-tB2fSkFEIwzSIAEhBiHkEpRhe06hZhDzoIYcibQTd8LKBDFLG1IKWdVKAq5iKiWrEVFCQhwa_0dUmZDIaZUCiFvPe1JVUSMMSJSFLohiOgQMiKVHEuBxbpntoSw3nTTvXEYYihl0oyWq7UCbAHMiOC9TankLICkRQEViD8CfkohIpFkjJGy_RCdlJJBt1R71a3KyhFTiVEVU8yImEXR2KEbptOJqioIIkopbO22qgEMxpqcsnVWCUEViUoRYkvWimRG1q0CC1FhW05IoKAik-lUpRhVVNmdTKTkktLW4IsgrAqgJMUaNgTTnfGVSwd13dy6On3t-vXXXrn1yReus8j88T3HUtf1o5MPh1a---3vxj781m_-yz_4-m_evf3e17_2h7fffvuPvvGHP_7edz749vfe-ua33vmT7_7oO997-Na7x3fvvvMnP375zZfunjyd1n7IJgZBtkSGvU2ip3ePTp88zqEdVl3R3Occla9fvWUcWKNtG6DAcLGwMXqLzjcWK05pZE1dm269KkNvlAxYo7h_5bBq9t3-8_-z_-3_5K__yhe_-FOffua5m1_6xS_eePaZH7z97u_8_37nm7_5tfd_-AFBESjGWybSVHLf-67UtXFEkNNmNV-fna-XK9YQh3bsiHPa8YwwpCCItScu69Z464Beevbqen7-_tv37Yh3rl3pUnvj2iEPfez7aweXm7oBY-7dfgTIL336xvxovjhbvvnZL166Mlqdnk5mk-lo93Rxupn3l2_eaC_OibcPWvHNJCet6ooQ1uuL1aaF2AaU82X3_lsfvPqp154-Pn75Y2-cPnoUSKaz0Xy-HDU1Eg7L4f2HR0bN7nSmJV-_MX3nrSd7h5O7d8-aUVU39exSfelwFmMEREWe7EwQ6K1H872D2XnSWd2ktEyaP7jz6PXXbvy3f_SjL3_qY3FoYxev37oeNsuj49MXfuITGvK1_Vll7ND2hvD8fPPeB48vXb90-4O7s9mYGa_dvOLZvXf30fHxkz__S78wJjvyeDafT8f1M8_cuHv3_idefz2l3PXtlb191uQcxRQePjr65Cc-0VRcsBAiG9i9NEsxPT06ykmKlMnu1FnOisbWTKZP-b33Pvzxd39oCMgaQJUsCkCgWy2gCgJaRTLIUDLkob-Yd-cnpYvrh4_P792_ePQozs8WTx8sHj_UHONqyUQlx9L3zFgSSC5xPcgQ4SMnCfvpTlX7phqDwvqknezs1VUFmjUFNmbn4DJ5H9t2s1yhQM4JELWIQmHDRYSIch7SEEPKQ4h1NYoxLZZhddG3nY6mO7Uzk1k1LNtUkmjORQWRrU2CorZr25ik3-RqNI5J8pAsMDFa25iqXpwN49FEInpwla8qM3rhlTdef-MTr775k5_44udf_sRr9e4kF8miYYgAoILOGCDY-n-Z0FhGgVJKUSVGRDBMiFAKGMtDTAoKhILqjEVQLYKGJQsoAAMqMpFulRxMUrLkoqjOWgAgQmaTc7KGrXFt17_-yvOead11y00vqQBpGmJd1wiCzGAMMGehzXz10z_7hdPT07N5t-pCARHRqnKrLlTeK4FhDFKQyDlbhiQEKuCMsc6GvOVCF2ZerdejZjwdTderhWHMOREiACpgyYWdKyoMQKIZwFjHCISkCiknQ8Yy55INkZSCAGgYFZGIiAiREYmY4CN4sQIgorUOALYFPwF48eUXHj58GIesUKqm7vvBOcMIe4f701H11tu3FeD05OKFF1948uAoFYklSynbyT0yl5IBNOZCSIapiIgUIARQAUFmZ0w3hLpuRAsguHpcJG87zAjgvY8hsXNaSm29aDFsUTXlhAhsrKt8jskZm1JkJu88MpnKOmO7th2PxsYQpNymrjKm9h6ZEDAUXW46Z21WRUImGjdjRfHeWLSL9XoIsY_pYDLxzvQpna3XaFmLxhSttwDUDf2ocX1Oe5PaIFzbOXj3zoO9val1vm7MepNnhvogTVNf9F1duaZy6023t-tjwiB5f6dOUUdNtVh2McbJeNTFLCSIIFHUgW3qLZ8EC2DJKUWyjMRDH73ldrFBlRyGEjOIxnbDdcWO0qJF0u3jkdhu0Vg5pSsvPPvqlcuL44uzo4uYl2eb_sr-ZYa8P925-_gol3x8vn7-uWuLxQqsuZgv96bTylebdf_o-HxnZ7o-23jvch9LKs6SietoRs5UVHIV2jUbsx3WRkmMDICoHViPxIAAqiAiKjluQAAkkTOQJBGAcyCEyKXQengyG11V0ZQjoVHkru-aps5pAEHnTEyl9HHQth7XkgQNIYmi2obDOhhrwZIo1Pu1cbxZdtZYqqu-FF9xX9Lu7vS0XV0_3GtcZuSdqV0OuY960sW2C37KpdXnb1i6vPPgfHO6GRhpKLJdLL79dHOdq91Zk2NZnw3WQRKonSmiy9VAlvtYzs-Xztr9g2Zcw_HTFhTA0AZ1tV52YeiStDFMdkYbom_cfzKajFMI3719FiVnp9nat24_CatByBAWBEBvnHHri3XleDaajg4nzH5s8N33HpSQxzsNEpWYyJk0T4XNdDzrVpvJeBKHvmocoBTQ9abD2gpDiBkUs2RQjLlMZnUSAYUMerJqjaHacA6RLE_2xmnTN03ddn0H4eS025lWMIGGgAzFXDxbJGdAWRUUpMgW74AEWgQJrSMkREFjMQ0JLBIz8XYMTGwIEZERADQrGaNaBKBoCbmkIqISU0GkIpmIAEUGqSsfS7EqSFQEiAjVMJJIQUUA0m3yHxEBVVWJEEBgK07CkkvXD6qAxmXQLiREGFUuhKyIhnna1OvNEIIwsSITQR8jAReQxWqFCsYxKIlIY0zJKReZ1HY9BKciRCCiiKt1Z70J2ydITEQ8DEqmKBIip5L7MFRVJaIImjQ5MO16aBqLjFGRHGz6KCBMrABxGBpjE8CscqsullK8t6pQRJi57wZbu5C6kAtZISjemVnlextcM1ot1oZt0ey9zyUz8DCkpqn6EOtR3XWDsVyyEhNmBOIwBOecIfaVi7nkFBHRG3bODO0AhEicUm7GTVhndsY0rpTMiJLzeDKKcaiqSgcl0LKNS3o_hECgMSbrbZFittM4JSEpRUQiGxaFFJO1TlENUcrZW5NS3qrkUQszZ5QYNjn2BstsMgbxs_Fkbzq5dOWgL8EBVtbsqfn2Oz_o7jw8GvlLz7_-f_zf_O9TP5-OHChu2taPJ1_5yj_-yld__Lu__hvvvj00dlzAXjw6l5gu5qvp_pjAVeiee_7G6eMj1_g2h92arx3ukwbZ3X1692mMw8VK9_ZszzKbTv7cL_3ZverW17_-L9nnN3_q05duPrt-cvbySy-e3j_55tf_4N_81tf-zn_5n61-_L4der2s7Sbfmh78_Jde_n987Ydf-7U_3r229-yl2dXD6Q0_ffzkbLJrdndnFIsb1-f3f3hx3zA3oyt-Aav_-p_8dsrDpZuHJeUJp_nTJUhRBs0lh4wRxpcaZ6xSiEX6Ye1d3aASuiFKKGgIz89bh8a6eLR87-rOrWq3cd587ic-jURa8MXXLvHupZOTiy98_o35w4eNs0R0-uSBcKPe9UOc7Y2P7i9CFHLV8eJ0_f5dMPrww4f7h7cgQzN2jaNmMhliIVUlcNZXh5OcIkA21r3wzPW2LNqu9x6Nw-OH85PHy3eq7w7zQgjNK5cmO3XV2GevXT0_Pbs0H4-tWZwtn9m3_cnFrcOm9GF3p9q7vDvfhMq5p5vFzcP9qvK37915-YXr4_HIOd_W5myd7j9-8H7qDnd32nX76U89_-ith5956dqDs8k3vv7t6Z75xMdeOz8--fpv_v5f-Uu_mNql05E3ZMgYtrGP3dBD1B-__cFP_9RPzE8vXnvlOSpy9-L4m9_69t_7m7_67W_8m89--s27jx9NRtUz1y59cOf9K1cuI6khPj5dvvLqsx975fkf3rk7GblcjcajBoSWm0UZMhl7cPnSZDwDYsmJEV2tm7D5zg_f__Yff3vEFaQCQJpEE5BjJC7IvqlqtjF0Bat22XJlFBkgExSWQgZLUrK-9hU13gCjIdWyOl927YaN2_JWmIygmIYS1lSPR88d0nTq9nbtah0Wq1HlmtMVl749vmjXixQS2pI2HbAwgJABtgqopF3XJpXaVykWNDIa1UVx53Dn83_132-fHLWbed-n3eu7Jeno0uXv_5Nfj9KL0XXqp-Pp_q2Xf_4v_7t7eztu7KfNaDXvwOnJ_SfdspeQZAJf_b__v0PEv_Crf_XLf_bLB-NLL7549fTBycPTpZmO3r9_v1vHkOPpfEOGjudLEUhDQasEyqrGcQ4RjSm5GMMpgRIBZVKw7Po4oIqhOkliw2iImdiYEKIxlEsxzkDJZFAF2NvtdcUYawyUXKyxWsJ2fxtKJCQk0hSts1pS1djGjSvkZlb98PFdtiyCKnFLliRLOQkYYMaswk11OJ6M2DmLtTO5aAugpcymTU6ZEFXQEElWNAQIRAwKWopBY4gAiI1hQ42phj7E0F65_sx6caYi22GKMZS1iBQAQGJEKiJly4BGKpKss5oUkLTkwmCsTTlJEuO45LLt41niDFBQLJsYIlkGRAFhY0qKoEhoYwntEIgNoxuGaCwb5hB6z_r4wQNb2dCJa-o__PrXX_7Yi9_73tsVkzgrJcVSjCNHvl1trLMKoKhMiIZBMeXAhpCQnLXWGTaFmYnT0LmqQtCSs608aGFngBWy1NVo3S_ZMFmDhYpqGIIzbK3NMZWcxvt7KhnQ9puuPtgd2an1bjFf7YxGw8nFzYO9gnCx6Orat20XYw4pK8LeziylGENb1bVqykAgOplN65yPz-fXD3f2Rs0mDqKq1sREYUhslBgBYCVhE8OInWUwY_vB6fyzz-51j49uXJr--MH82uWd-2eLIrjswt6k2plWx2ft1WsH9x-eLzbJWjMM8WBvejJf-BHLkkLoVYBExqZeZQERJPDehEXOKU8PD_sQpMTl-YYQwHNOZBDIaCYqXeKJ5UmlUXLskUwqxVknsbOVe-HmYbfqbGUuVm3b5nbT2Qa7ZXK-vnntUrva3DrYPTtedLEcna9SCjevXs19P6p5d9KEtgcUBlCEq89dPjuem5iybUah7wQVKtI2GMM5ZcgChskaNo1mkSLKQIAgueRgm3EuGbf561KksGo2xgmpShzXV7EAOx_7MN0bs6XsXQ6bZjpan_WaMxIiAFnOkqGQAkkEEZE8ODYiYL3NQpAl92U0GRVCVdq7MQUyh6PJYrH65DOXr-xNG8Pzflik0mnuNyVkrMaeGC5fH39w2j03nV7enXQnqWLzyvXpuKb37q--8PLo-nRMgSaX_ffePdEYrEi3Ls4Za4gMLYdYDK8pl1VcbDArEmFdcexh3Qdythnbw8v7fTvMz9uEOqopFXj0ZL57sOOm1enFwlWUNKZ2LSihk2c_fXNx55xLqmztp6PKoqZw_9G5IU0GjDVd11dV1bcbZkBWJi7GMOIgwlmEKRUZ2o7YhlKQyRoTQ7KIIeQuR2AaV37TBgPahT4bywpn8xbQ9iVvcnKGN6tugHx0sV6s2xduXva0tdCBtYiKpSgAKUFFTICEkAWKFGYEJBWRLMTbLS0IgqiCFgJk5i2Wd3tyT6V0MfUxKWDK2RAZawnUVR4UcpaUgy0ZkKUooSVUsixZVUUUNEWylYqoYhZRLSKaS0YiazkLplSICICAOYqmlIcu9qrjCqBgKoJWh1yIiCx3Xdg5dHmAlEVViKliE0JUJSbNuQwhOkuGTEi5bhrNWRRKKWwwS8kDaJRSRJUVpABKKgSSYtnKXlU1iw4xWsdFIxKuNtEbSwYBpRRlZIGP2s0xlaKyKEWUvHUq0A7RWOqHLARDF7h2HnQYeoPE1jx8fBZSsXV2jvsQreG-T6JqLKNSPwRCVlE_dtsCd-wHRDCWKq4MICGmkq1lRlu2qh6BuvYpF0XaNshtVW97Dh8R7pGGri9Ek9nOerNh3tppgMEYLoggKiVFZ6tckrFOEAiFFbIIiBKRs1ZVvHUlZmOtSjHGAhRLxGhy6qeVGxnzygsvkpaJq16-tfN__b_9N1997_bIl_MOzu4dQYXNuJ7tjf_hf_5ffP8H737jm3_EuTfF5K7sHBw09WxxEX7tj59eO7j2sz_383_01d87OV1bhDje_9X_6O9yu-Fx5cd7CpJcefcrX3909_jFj-3_qz_6_udee_1PvvPB3rXrn_nMJ28-e80ATw52Fo-Ozs9W1kHxpz_5hU_42aR2HvtQV9X5yQlpbizkDK_G1eKahzRKyvYyO9Uf_tuHny3VJ__az67EInNVGVvgmaax3uzNxhYzluIkpwx3Hz7-3u317bePT9b9C69diUMZjej8nYdxk5V8kbJ3vWnnfcWEzIGQXFVEZqPnhsXGgel7d3g4RasxrXGnWqzj7CeekfdH1AUe266fj6dNLrmT8O4Hj4f06Is_81Pf_8YPX3z11uXD3cbX3WQ95LTUXE1Has1i0_mdyWrZLs5OV2frErvLr157-vQDpIqNqd14sns4nJ7kMGjMlnzt948375WSVbCZ7VycL1_6_Md_9N13qqpptf8Lf-tnf-2_-sqf-bk3_WhUEnddO542tee65luHo89__M0_ufPhqy_vrWPb9Zsfvt9-8fVrxyVdRk-NuTq6cbZZTrD52c-9vLs_ccZdOZw9_6lb8zsnMU-vXXmhGTv9xPj2u4-vP3Pd73rfts-9-NyjBx-8-NlPjL9dr1ft6elq59ouIE93Ruv1pohcubF_-mRx9ZUbH3z9u7_9r3_nS1_-4unR2fMfe_nhV5-6EX3929_-_Kc-_aPbb89Gs8qY_dlOiNmxuXppFtuSD3f3xiNzcO1kfnHvnduvfvylxdAClGkzGVJhjZUzgPlofvTuW--_9d0fkK1KUsk6YkOEGYCNxVSasWeG8_l6fHm3ICP6jL1xZnJpT-OgzCBFVEFKs7-7eLxgQSVVa86Ozl3txzuzZmwVZdgUM5mycTEVPxtZ5_avvZTnZ6PZJK3m4fjefLNCqif7lWsMJl8dTJu9Wb9ZWwMQQkokYK-_8nJ9MLk4PlUrn_vVny3Ls3tv3zm8fqm-enj6weOkm261eesPvl8fjD-8_Zih-pg_GO-NTj683y7XZWTd7Nrf-V_-_bwqaplGdRskEbT9hhKXIZEbmwm0Q3l6-4FOdt988yfAVE8uNu_--P7hpS9Xo_o7v_MHdjodCgwC3dAVQ0MMKgiiyKCiQ8qVc5KSsSalbIw1hlIs20GpihpPtpiUc8i9MVyK5KiEhCCOueRSsjhrCzEiUUWalcHmlKC2qERGuqH1xqqKJSoiKWfrK2CjRRBIBJ557kbXrQ9ml0fYFLsSsJARjJScrakaS9EQeFcjMe7-3r_55q2r-z9-cFJXuGoTIYZSDHAuxbJBg5VWg0Zi5MpKLIAqUBCs4Y-4dkMM470JKna9XiwW3rrZznSxXKlkpGyNUcYwlMpbo4gxAUJWITbW-5JCAnG2sgohSF1XolpEEcE6V3IR1cralDKRySWTsZKzraoUI2NiJjL21jPXT47O2JrQhm1mO0lBlBBkOh5_cPeRcy5GUC3Dutud7DrGrBRCUCwgnHNh5sq5ohTDUI1HCJRSUCI0TAAKsL2b9UNrrBUBYJYizCCijGSdG2LMkqVIlAEIcyneOVKDmiXlFIIfNUWlrl3bbnxd141jAmN9ThEQz07OcU9HjQ4x9q0ZTep-SMOQSlEh8VU9hCGGvNlsdndGjWuyDtbXF-fn48lYAKyxDQiCEmCMqTamK3laNwqwDmnsvTLNjG2L7PnxPA0jT5NRtVuPTsZd7AdnuTbQhfA4dK_dunX_-Cj1gS2dbroXLu3FBOu2E9WH9892Z9PI9N69B7PdcTWuL54sK-e6vlcobFmBx7PR8GQwoCIgoDkXyVktSVHvK1DUkNHaUoIgWG_YGpHsG2dlpOhXy_bK7s6HF0-ev3HIxp2v55vj1UvXb2qS3fEoF1quNjjzd370nsn6uU-_1i8Hg1Q7e3qxfO2NZ--8_Xh_b0oFDqcznnzsM6UocAnrnjKUPiMKIBIjgxAQimJdoTNsrRISGXK-lEyGRcChM9ZIyWStqz0aFgGDxlcWCKxzGqK1TkAQTQElw1lAAPykURBlzCkbZ6xlVRFmdq7ZnxKb51-50W06JIyiWXG8NxpNahW5cWWHAJ-9PAPRpLkH4FnVphIUsfaSYxhSg2aEOBSQIu8N7SVfGUBMejDyta-S8ibL4_MAgjsHzWQ6OrloH80Xm5QWfQwAbPno_KQZjTZ9iCJCmqUsVu1QclXZ1Mqtg4MQ5Xy-rsZNl2OXciyRmZerVejisIlSJEXdrIfa-dIWy2V9thhfmY6v767-_yz9SbCu2XWeia21dvN1f3f6c25_89682WcCmSAIgCBFqiiKEslSqXFVOWRFVLhshzR0hCeeeeSRBhUeVLjsiR1uIsplmyWVJZKiCqQgUiBAAIlskH3evH1z2r_7mt2stTz4c3oGJ-I0__72t9b7Ps_J-vjpxaodXFUhYwoBya1W3XhWLy6G8XhkRAyQ2fAZAYd1p8JIsF4HBeyH4AtvlQAJo2SFEAdvnbUmhsyZWYScjTGL0SuH26dnKxSNCds-bc_G62FIOdXeF96RqjHWGQNIzpmvLbwKaMwGUQmqxtoNxscYq4rOUhZZ9R1nRkMMmkED8_N5l0Qv2j6yxiQsIIgs7IxJzBJz20URFqXtnfr0vBeRdZcMYQwRAa13IopkkMiQEQVrDBAIA6uCCHNmhpSYFYbIQJgkr7vIikqYWDMLIHwNggYbY8oKG0aYsBIZNBAj9zHFlDdnWVaNKRMQgDGKBKRglCgqx8iBv47XhJQTS84SWWJk3qjJjOv7oBvdsYAIZhFjrAKIaGbJqinmEHPeBKJUrTUhAzOwZCBkBiBgBUKjoHEIknXVDUNMVVMacheLpbGUmFkkJ94kiFQQAVnF2w0BZdMTIlEhIFAgMtYaEQZFZplsT_OQrDPCIixlU6uCddY4g6JgMA6DIUqZyRnjjLBUvhDVHJNztLEiI6pBZFBXeCJSAMmCRKBCaDYBMTIGRK11qoEYOCdk3qknFvRoZ68Q_Mmf_oA0f_zzd__Vv_iX__6__5c_-OP_8V_8yR8t5menz-fDKnz_V7559_MHoqPRdLJ37cbTL7-6vDf9_It7lLhyaKgpjH3t1q1idrBdubomQPnNv_v33333vd_9-3_rx3_4_vnTe6auiqJ5crY6m3enz1f7B9s7371x7aUXX7t5--jS7kftp986ePnz0-MrjtKQ2vlw0s4nRSlxYM67OweH-3ssYhlLa1FUQO5_9Ojnf_GT__Qf_t7QpbYf6nHjJBslIS39WD1Np3tDu4TIhTVVWRS-mDSjbIouhoeL8z_--fs_-PMP-jVEjfV0PNsZLxeri8enOamEdPXOOCqgKSAhGQM1WWetdaBIzotyPR5Np7PZaFR6rpuyaerUxX20lAQxxRwuz5obR1fatnt8-vx03kZxr37zlS8_-ez69SvbWzNvDKgOIQi589MT6-Bg_2Dsy2__Z3-nffzw7Pi4qMp26BQ19mwrt16sq3F1Mb9AjaRIhRkfjs4fPgWrmqSum8D9arH-z__L_8mze4_6ixUhfeM7L51-efYPf-fX_ua3_6PF6mLXEsf-5Nlp3ZSvvnhza7_cHeNoZzayxO0wmo6qpja1TWwuT6fP7x9fvbY_9GF3e8yB7x6fzyblpVn96mvXL-3tbe3PLu2Mvvzq_uXLu6N6BFabZnzpaPf0-PQb3_3-Bx99HmL35msvXpwtrKGyLLoufPjBJ0ywOruI_bC_M73_4P7BwSEgXb1x_b133zMe3_nmm-1F-_T0eG9_vxmPPvn8wWRUGF-gMgE7AnSubKaf_vLut7_7FiCo8cfni_fvP_zXf_6Tv_jLn_34L9796GefLJ6eOCarpiiq0pVbh7voi-rKbuo59ZlATVnZoigmY1atJ0WOMQNNZnvVpPR1bUfjentLTFmNm4M7V9Oi96MRK1XN2HiXMu5844Vmf79dtViWYI1rSjcu0BruVuPdRmQApsXJaTGq969e92Pbna_ycr44WawGJuNUMJrx5bfe2v-NX_WC7__kl4n51itvSEyfffJgvHfp8iuvrOfpo7_4k9Dn2OOLb9x67c4L5_Oz3_kHv4vG-pH5D__dvwbknSvXf_-__C8KW_QRqanRGSZEq8Y7aJdJ4p-999c__NGHR1vbz58_2d7Z--bf_E6IpNaGZbx2ee9g0jw_n0-v7J-ctX3KWVUQVDSJKoKoSMrGGTKAqiLq0VpjjAFWEdCUU-F9zmKN4ZhAN9YnQ0i5S4pqrDFkUohfu3IRiYzkXNlCgVHVWgeELLKJpYKiIHw9c7RGQawhEdnemh4_O93bmpC1z0_mMaa6qkE0ZQaVqnJlWcduQMTKwJ2jw-tH2z_-6G4UQMT1ujeOQChz8s4hIAtvqHcOTcwMIKLEoMYAGCOSctaq8jHlnJItiHNKKY0n46Zphm6dhRlIQbNqTkkBQNkYF2IeNaPMCcBk5qaYCGTAjUXHCoB3zlqXcrTOO7cpEiAA0Ab9SRtrMs92dgPnrguZWQlAOKfgCu-d7WL8_nff_quffUjesZKgAoP1rhoXi4tF4UsEyCEBIiiKSuEci0rkoqk2RBJH5Iwj6zkl60pAFRbjvIJY65whRFRV5wswJJJ9UaaYvHdkfY7BW5dCLOtKRAxaIjSOUMA5m2JoRhPWTKoxxqouU057W7Pt6XQdgyv9xXKdmGOWmHNTN5sf31iSxN4757yKNnVTFG6Iw7QpiYwiRVUkQ4S2sG0farJZhVDbFI7GE4f-tO3Ohu7GbDuy1KWJTKerVbM_jW0mxczqDFlfXCzXFk2IXFVWUh7PRncfPkOwaKwFnO1Ml314dtbb0oUQADW1CQmMteNJ1bV9GvqcIudsnFHm3LagYLwFEePLxElDcKV345FkhZibxoZF9843vzky3hp876N707IcJAHQ82cX2zuT9aLd2to6X3bvfvixryePn55euzHdP9gy1jw_Oc-CrJpAlqc9AQ7LYFRN881f6_pcHe7KMNDQ0tcAEyVQpE3DmwTVWA-geYhAiM4SIedsnUUAFVZrwFpAIucADHpikcSwkZha54UoibiyCDGRNdY6NKBZJvtTdM7XhSucoqlmo8n2pB7V3Toya7ldc1nayo62qq3RaL7uXrh16cp2Mx436xg7iewxe3--iKuQi1HRhrRYD1XTQMg74_rG1ujx-eJS47Yb3yujc8kQWGKkeQ7G0vkQz4I8OO5a0t3L22ZamcKkzPN1t1gPO4ez6CmlPMR0tujEufNli9b1IRjjl-0QNK_7Yb4c5us1qDs7O2cAV7rYD23XWUe-tjlEg3TyrMOi3Htlb3m2XJy0xkOXkvVoLTInUUkpjLYbYqWN-8NZFnaGkuaBY9935ByAKELX9QjqfB26jpMMOQ8hbJRrquDLUkCNM5tKU2DthyFEXi07490gLCwCuOrCpKmdIQObBKEaY1CVAA1ZBESizdWPEEVUFUXFeceZU86AELJm0XZIbReDyKZCyqDWugzKLKqKiKNRtWqHzIxEo6ZJLMOQAktkWXVDygJoMgAQJtVVu_K-JDQCwpwUIKsgQk4qiIhonWURMqYfQsrQhchAitjH3PWDIRLFkDIShMxFaVKSHNk5N6SoDF0IKUvMSZASZ29LUeXM3ntAVNAsnEQiyxCTAqTIkYURWJU5pyxZIOUMYJiFJQkzWWRRVrXexZyITMw5smRmIpMTKwBaIwiquDkuFSRlKQobQkqZF6t-GJL1VgQVIHJmESAymyKNAidFMqqaszTjihPnlDOLCDtjASDmZIxVBOsdipKxaEwcYll7yOJKS6JISICExKLe-8zZFz7lbIwlFCQXYhTd6NCgcA5AcZNApE1tmq13LLzJm5KhDWwOCQHVOgeGlDOqri4We_tbxch89vDp_Pz5hx-__5Of_WSxOE--WAzD0Qsv3Hn1tZ2rN9781vfG44P_6r_6r777j_7uH_7J-99855W_8R__3Zd__ddeeuedoxs3rTM_-8m7L9y48eZ3f-Ptv_13vvX7v__Gr3__2lvf-PXf_Zs7u1NQXXf54f2vDq7srmN66z_5xtbtS2M3OX-28JX309pMCG1R9G5v5j67d_LmKy-8eHDzytWt5199tTvdmfd9PRqfPD1z6LcnO01RTKuyywlzGBWmKmxpUjPZu_x68-d_9O7f_Hu_9e_f_2Jv5xCs2aqasiqss6UvszEsydS2GY3IF4BovceafnT3kz_74U9_-dnT-Xk_rMPRtcvXbh7W28163VqBoixjGwE0JSnGE1c26HQNPJtOqsIXipU1vnKg0q-jSopxHWNIHNFSVVoyIAzGYDmqbl-7cbi77Sv7b_78x01T7167vD5flWW5NZse7O0sTs4u5otLly4_ePbs5Gw1rorbt27fePH6X_2rf2sLU9i6ruph3e3u7s_PlwywbsP2la2-7drVOsekCP1yvXNrb3U6Z06Tna31fKUg01kTlt2tW1fDMCwez1eLcLTbuHUd2rOdvWZ7q3rw7Oxk3aW0TkPYnox_8Jfvr5bpy-eLw8szsXZ7OjnamjSlv_Xq9dmkHjdVQWQQ9xuvMToJzaxpqvKiXTSuZIu3rl3Zquv33v88DuujS0chDGLo8ODoi88-eOnmTefskOLW1pQ1WuueHz9NrLEPhjCHrA4d2uVy9d1f-95f_vBHH3706d_9O7_3-MmT3b39umyuXNo7Ojy49-X9tm9_9a2Xd_ZmL954YTaa_ff_w5_cb8_-6__LH_7Jn_75T_76g0efPw7zZWlt4ayzrqxKYwidL8Y1ucrY7djKpTeuK1JoBzcqbWlsVZN1hBxWfVEUIjK_OFNFTlxP6uf3nxtDzrq0DvXOeOvWlfX5KguU4xEVFQp1p_PR4UQtqDO-8tW0FtSiqvdeOBpWXb9apRxBIXaSmbvzk5hhuczX3365mc4SFLsv3_ST8eIXHz77_HO3Pb5569bh9SvrGI6u7l25cfj0q8-fffyxstk9PNja3_7-7_3Go5Oz3a1LikDj8r1_---ePXi6-8IL__P_zT-1tooxo7cJeL64ePbs6enT86dfnDw7OVueLg-b3XfeuV2W_kf_-oevfPvbBiw6IOMMAnF-9fphMS1-8fFDtW4IvQgAAovEIaoIqpKznoyIJFYCNGgN4ZDiyNc5cU6SmJ13KWVCdNYKK6iqqiESAUInkskYADBEDjegG5uYlUAQvXeiqpkRKItsvL-erPcmhiSi1hqjevX2wen94_P18uj6lTCE0PfCGCUJKCcZ1ZWqokHNWjra3Z7dvHL4wecPuszgDBEOKVtnQJTzxnoJyioq6AwRcMrO28jR2WJYt8baIUTCjaaXEdARIeD8Ys6crly7tlr1CqqaEUFh07wkFTHO5pzKoooxkDGiTERIJCqEwCywsfRwUlXnrKiiKAKQ86SMAM4Z62zdjOYXi6IqQ0gqGQFVgQiIHBP-5q-88t6H91xZblp_RHjy7Nkbb73-6METIEpZCMEXDhHjENFbRFQkIuJNGJiQVQtTiMEQkvVWSJ1zKlL5IqXEws14tFHeRk5FUSpoUVREVDifYyyrOvY9SxrVk5QiqfqicpaILBp0rvTWCcrh9T3u88Hetvcuh7RcLM_nawHMIs5bBIkxqcikaUKIQxpmsxmIphh9Ya21o6I0QPN2XVRF2wdQ5ayiahGZmRPHKIfTsSj13TB27sbeztl8ngYmMus0JNFVSG1KBiDmfDCbna1bW_p-vQxJJ00JkoDh-GJ1sLcVuugA7z896TNvX5nMT1eAkFMGgLqpvfcX5_MYBonZWpskgSgBGABDKjm7UclJYDWgo2Jc6RBNCCqx9OXf-4e_cf7wAlk-uf_VqKwfPT2ezKZtDkcHW_vTrRTi8cn88fFZOaofPT6-tr-zPZ3E9fDg0dnVa3v37z611tT79exgfP50PtkZm_Gb3yvHjWaFrpM-qrB1BlRRFQGVjAIQGWUtXEUEnNg4h2iQUVlUSREFjDVmNKpZMMZMzqsCqwIComFlUzhg3hRW0hDLUdV1od7eKrarvt_AnaxpioPLs8P96vhsmFQjdBocuPEIDJK1a9GrN_f3Zs28Dwnps-UFbFqo5C5W_cFWlUjOznphnI2Kw0lVOXvepkVM-1v1wNglVtDsDTh4tOgWKZwsu6hC3iThQXPPjIBqbFF5JarGdRdzjNrnlEFXKSbO1aRar8L21phKe3w-N7VtV2sAYE22rnLm0dXt4wcnfdtTUfCgiLbvIiOUV6tx0zx9__n6eIlGU2Jjjah08144t-cX1dZIGSRzH4cYo7EOVNerLifOWXJiUJNC1KxoKHHOnNu261MMOSJSVGWWLFIXNgvGGAtfkjM5Z0AwhEPkwrkhJutd4V2W3PX9zqgGIhC1lmgDAjVEQAiEmzoNoCoaNIAAQBuGJgEwUhLNhF0XFEENhswhpcQac84qkbkdAhkTEztjXOGss5F5vuzaEK13yz6ow6DahjRkzgRI2EchgKEPQKKIq3bYVOpiyn3IiiCbOT_SugtJAQ32MVnv10PIOWfF-bplhaauAqe6cN66iS_bftgId7shGmussRnEkenjQIZUVFQUQBFzzCFyjCwKaE1MrIAxZgYYQuqGuIklCUsGGboITEMUJFLFnBOiEVaDSMYZQmERRWYREQIUBhZJLCHkkHJh7TokkA0aTfuUmqpoQ96MrKw1CNIPmyrypsaFoU-ld4bs0AcFKbzXDCEGa4mFCYgMImGKyRAW3omwISrLAkBDTL4sUkwijESIlBIDIxlEREUAAVc6Z4whU1alZFFVVxaqSohAGyuDkpK1RECq6gorLBuRpQh4aySn2PZffvp0Mpke7G9PjvYvX71x9catnb2Dy9ev7R9doarJxqyZ1qK99R_cvXvpcO-f_NO_3Wn5eL5-Ml8_fv7s4ZOnJ89PgyQ1-ODk-UWOJ6v1ycnp3S_vf_XF3adPn_zk_ff_zR__8GJ-PoT2_ruf_eYf_ObIN2fr7s4bL776ys1r-1tFgna5MqR5iJUvb107vHtybkEV5P_7hz98643bXYrXLu1OJ7Un4MKsbHE6P__Zz37-Zz_6D1_-9OFHHz_69LMvnt5_trxY_ON_8vfHJTWVjcO6X3Ttqkt9BgMlklEecg45R5Pu3X388_fe--s_-_GDz-9LzFcuX_rOt984-_L8yqWxr520MeehcCDr1C57TlYLbeqJ4QwZjDDHiFkLgm49aEo6UDPxo8YZy1UzQmMBlQRVoGp2EYZuff7d73wrxXwyv_jqwVnI-Xf_4O_84E_-7OYLV3Yms5zi0PYxyaWjyx988KlFONrff-XlWx_8_Oelq6rKTUejxLl0rlt38_P50Pdo8Gh_L_Yxdy2p2sJpTNPLN08fPiBLxXgcc9janqxP5rvbO1duXN2aTZKk2y_vXazy8dm9euRPTk-sLaxvhi6LpZdevPzw4fOzZ-ev3Dj0hU63t8naZb-GlHf3d8ZFAUSqXHprkLa2RtuzcbfuF30wRA9P5sLmrG1nO9uffPr5F3cfCsPTxdmjB09uXtp7442bf_VXv_jwl599_9e_u1ot56t-CEOf0_17z1KGmIQFy8oC65D08Gj_3ffe_-bb375_94vzbhGSOGP2ppNL-zvb06qqimuXDw9mO9Vk9myx-uf_p__HyZMHp189ayIXYsbV2PliPJs0k7FrJq6uisa5qkZrjS-KcjLdrq7fuWq7gGD7OHCMpStc05iWX3vrm6XHi7OlLwtfuhhyP0jZFAfXLxdFwcy2dNb75_ef1k0NhtiAKcqicDmyZvVNM7p0oImj6HoF25e3Q5_OHz_v-66cTExZx9CNp8X58dqNJ6_87htVUZ8fn00vbduxm39xH4W2rxzeeuO1q69eevb06Vfvf1aJfvRX78Vl3t8fX3vhxmRv7NTef3RKSdt2GM9GRPyTP_-rqy_f-c__t_9s_nx49ODp8XL-1cMnn3706aPPHuahLYy5fGU6Gpf19mg2mZRl-Wf_6gd33v7GN37lGwNrFimcu3x5N_XtpZ3tw4Pdz794EkViZjLILIACrJIyMoBAYVGzoAVOSVMmoqw55eSoFMgqaFE5s4iiQQVRBUlCRAAqnNGanAQBQXFzoCkhC_MGiK20GVWoiioDIip6Y0XFWReH4JyBIe8fbVVF_ej-Y-saVej6lYIBRGEmg7YoQAkN5Jirws-X82-98dovv7gnrliuWhVw1oQ-kkLIWZAIIUsmazmpBYugOSoQGkRniZMCgTUEzIAmJ5YsxlvjbOjCulvPdndVkihwksK5nFhYXeE0i-ZsndPNM9hQaQoGzTkjobGoorb0zNk5LxtYtvCm_EaEhKCMhzeuzs_mriy7vg9DBFBN7JwxzinCdHubCv_8dK6ioOysY2ajcHDp8mJxllJGRGvskLJxBlA5MpAR_XoULDkrYhbJktGQ9cYg5ZhQwTknnHxRCue6bkTUGOSUi7Kwm90MqCKKindus0i2BIhQ-CLGRM6oqDVknfcGyBijoko3L-_UpVuHdL5YNqMyZQgpllW5XreFc4awKGzMqSxKFmmaUoQ5JTRYez-uKwQ6ny-rpkwxSc5KAMb0MW2Nx0l53NQopu37xtpRWb735f3JaIKE54uVGhJjQsq29Ap4tlge7UxP5_PK-ydnq92t8XLdb29PFl03X4atWcWcnLen87Zp6m49cE4qICkVvmAQBc0596t1GAZhUYQcBmOMhgghiSBVBhStsanLzha5W6soOnvzpVvrp_NH6_nJs9PxtO76Ye_awUs3rxtrru8dLLru6dnFahjQ4PJs8fLr16f1tEDT1NXDe09zzvX2xGVz_OSsKvwwdKa683YxsrEPad1ZUGEGYCInWZGsAiFa58rMmTkrEaABFiJUBBVFa8kaJERAIYPOofcc0-ZaIarGOiTnGid9UiP19kgAbOHKaSMCIpqygCvMuDTkc-C5SNVMauU0DGKdKcqy9C-9sDWIMUPyU-8m5fm63xmVFdl24HXPdV2EPt19uHxy0d65ur3TlNjzqk3kzPaoFMWeJas4ZxLwV08WyWAxqRNAs1OAoVWMojhfrYvSZ8EI0gcVQlFJnC8Wq4wQghpPKUnXh2paLubtcrman89TyLsvHAxBurYfNcXJ_edptarGjagBZINKRKYma-zqeJFCZ0YVVs7vFpI4pYEsOGMQbVnWQ9uLMDloF_10XK_briqrIFFFsmQhXS2WDJI5q4iI5CxtH711vrDe2hxSjikJ55QRjaKK8mg8Xa_7dT-MxzVaG_porSFry9KXZSGGKueMI0LIIaFRg5YQAQABNvLajR1ARAAAUQExsQhAFElZBCCx5KxZdNUPqsiAMXM9sjFKGrIiZhbvDYs-PZkD0UXXO-vP1z1nJesGhrYdzhft-SoIqC_rEHPMuYsbsTDEpDHzxj6IxgBiCBkMxawsygJDiCkmAOi6AZ2LeWOZxMTaZ17GnIH7nM8WXVF4QCBFVYo5IWISdcZIlpQFUQGQjEsqIhASAxkRZZGchFWJbM4ZkYAwxswMggiAQooMOWsMiSwaBGYxALrZTyN2Q2iKMmYOKXchoUhknQ-B0ISYQUFUUsoJES2GlBARQFQgxORLrwrWurLwWQVlk0ACY6gcuZyEUI0hFUQBQHDeWLIbzbIz5JzjmFzhiMgTKpK1rqy9sBSFZWVyYK0jQ2bjfXB2aMNs3IiqAqQUUcAYAlFR9bZAAmMdATALAiCRiJrNvwoiWluMqsl20_ddBBy6tmtTmy5sUbMKq4BFIKwn9WhcHx3tG6Lnz05_9JcffPjhF9Vke71eWevJ2KIsRtMZWZcEQkih7duzdeiGoY2pHVB5VDbbu_s3XrrTxu5P__DP9-rZLz7-4M-_-iq3lPvw7Pzs7NmFN2Yymu5Mx6h5ZvxHd5_cOLz8o59-8uWDh-_94rP33__si8-e3nv09N69p198-sWXXz6wubRaAMtq1X5-9zEZmdQ7l37v7XvvPpzHtHdp38_GVHtx5vlyeXyxfHr87JOvvvz4049_-dMPHz94lIdA3jez3S7gS5f37358z1Y42TPDqr-4OF-etpd3xy_c2N7any3ai7qudnbKqS8uXdvdP5iOCjdy8OILO2Uztswv3dn9zitXF4u-no5j3hD-KIVBQJxmTmFvOrlycNjF4a9_8b6xLgK-_tqdz3_52f7ubL1cjkd1SonRMMjjR8fO6Usv3358_14MQwzd4fbO8fEzi_Ct739riPnzTz4dlT6mtHf58Pirh74iEDHeCQOWGNYDZFEqFHl3bxc437p-6-TidLZ7KVN3uLV19-7DXzz4nGL6iw8-WbdxfrKQpEBmOt259_Dh7VuXTONz4HLUGLX37z91rprMJkeT6XroQ9s58oK4VZQX6yFmObh8mZVdUcSBP_zkk5du3_74i69ef-2ld15_-f_zh39Mk-3f_OaLMUhRzH7xwYfXb96sirLtutHWLKH74ouv-qRonMRonCODi-VqPNpqRuOPP_rg9u3X3n3_vddevP2j999989bNyaROKfqqnIxHNfL_7p__1_-3__a_lTZYVwHgaDZVIOuqyc526IahH0KXXGmKsrTWkbOjqlZM2-OxRmmKIrOknEgkJal8dXj9qB43ALJ7eJiFna8n0-ntl144PzlplytjjTAPbZeGoR6P2mXnRmVI2TrbtS0zNKMm9lLWddt2aMx4a2QEusWq7_rJ3mx8dDTaney-uDvMA6s9eunIRrr77ufGAg789NP7pXXN_mx0sBe69uGnjx9_8uSt77yOFuvJ-MqdK9Oj3Z7wfAhSlEbU1YUAjQ_tL37409jrP_vf_6_7i_5Hf_aT50-_6M5OygL3ZrM7r9y8dOv6bHenrEvFishUpW37-NFHX_zt__T310PbdgmQytKV1lnvlufLF25dX6_WzxeLDBBCVlZImTIAAxkTga2xwpwSqzAh-MKyAouqIU7ROSJEUmLOoiAowuI8KQoSbrzxZBBok8a01hgBUQEyAAQiYpxVkSxclqWKbAiYikpIZEgli6q35eHe9NHjp_Pl_GBvv-u7fggClPtknBUCZ01mVpW69s8efvnbv_7dX7z_KXiflM_PVuQtszCzMaScvXVfl39BFRgNmMLkmDjlqq6i5JQiC9nSA-F6uVAEIuAsSJBj6odQllWMrKocBwsbqB4aRDI2pbR5nxER45y1BKrOORAQAQCoq5I5u8JzZuONL5wIAwMarGeT1XI9hFBOqhQiK1jnrC8FxHkHRDduXLn_4FFiJEJhLZsayXKOhqiui-VyUKQwhLIuc06WCAgys7GmKgtEEgVbOk5sCIQBFRTBGSOsZVEmEUNQlEU_9KBaFN45T6SEJsWe0JIlBQQQ571wVmFJPNveiRuDpDGoEFLc39maLxa1s6J4eW-6Wg9tzKtlb7zZGvvAGkPc7C6Uc12V1lvhVHnvjPHeAoBz1HfDeDSyCMthMGRENaRsrVn1gyOs6oJUCcE7c3axONqaxiFfrNvz5eLatYOyqM_Ol35cDVbPz9aGzGLowdnMGRWbysaYJlW16HrJTF7Louq64Muq7cLWrFkseiIVEeuMqKI1iLhYLJmzqpqCVBg4Q4oWEIU1CdR-8xFAyL4pNeWsiog3XnwBRJ-fL_b2d0tfjkajZ-cXf_A730-rdne6c7FYjiZbj06fCGO3Cr_7d78_P1kV1szXPQuMRpOgg0ZeXvSTrcYX3pRvvD16YWv5dGVSsoioyoKmLpgIXWG8AzKqDKoEQNYrKBrLKmSciLqyzpydK0BFkNA4AUGlTYwBwJjKMwuL-qperYItR-WobJf93vW98dZoWPZFabNFW5VFoaEPlvG3f-OFm5eax6dRqBrV9MKlWYypLu3tW7Nln58thnUbk_AqJlcUaoiJTpftF8-X1y7Prm5XXmjVBu_MqzuTkz4JmLVIQkwIT8479AaNCUnIyKzErx5eqDF-7KY7I7K2HPuUJKQ8aqxaWrdBEXKGg8NRlxPHrIhQ0MmTs_l8efWV_cn29Px4QUaGPrXHZ23bunJ0cH2HrClHtYJkBltTPw_Dsje1RW_A4HDWxzaqMgCCMVVdbB3W89MVGu26boiDSi6rOqdkvO-GQNb0IYTQDTEPQxBWa51mFhEQDpGHLvrSgzEhJl8QGco5j0YjYR5Cb41hAWttM66W89WoqYuiXq-HdojTUTnyhUECAGMtKiCi2QxaRMnQJmK-4UERGUVUEecoDDGmPKScUgYiAMyqSBRDzArLZWyHWFROVHPKSkYAQs5JpY8J0YYYrLOisFyH5ZAisyAu-zDeHj0_WXchZhUBiDFnUVYF1K4PzjlPJgPkLBtbXegzq25tj0_O14iUWRRBVFVkuQ6LNgohI3Tt4L1NwkMXIggLJ2bYeNGrRiWT9yHGfsjGkABunGLMgghdyF2KWZGZRTWKhJDQELMOfUIDsPl48CbZz8wcYlYQUUBjRAUQraEh5AwSUyLv-shBxZLJzGQoJ0aLbQilL4XBWacCCOB9QQiAGGPOwkVhiYDQ5JytNajAnAvnUszGWiSIKW5eDwpnhbP3piy9dWZrZ9KuA4CiMVvbo8wQYnTWqqqqDDk7Mt5aQ0AAhXPC7J3lzd8e1BiDAGgRCRURQIz11qCAkEEFsMYg4oYXiwjGGePsxitniRDs1_htVVAERBUg6zhlBYrL_oVrV__6z37U1HVTmczknPWOrLGejDHW-aIpakJT1kVdl0VTV00z29me7GwvV93RtRfS-vzpgwe__g9_V86GbT-y1q8XF3cXi9tbR2iw9q7yDhmOn6wGySenF-RCnK_GzXS8Pc6uV6OS-kldDovzUVVuHR4qp62tYr0Ixaz5-GcffvnZ559_9Pjx_fsffnb3F-89-uWD0_c_f3R23j47Pj87WbareOnatTYaW0CkZjTbfv2dWzev786Pz4u9kQb77MlF4f3ubPLdd16djkvMOu96zLFUunJ9d1zQtKhmpS1VL1_bf_2dq6-9eEUTxo1TmmR7b6_jjEjMHHOU1KukN199bVQXCvDBLz_d2d3evXHzi19-cuPS5XFVV76QnHZ294SMAC8uVq4ud3f2vvjqC0yp6wfI0Zd2b2ena_vFvO9XbVHXLHx07YrJQ9f1QxZEFHI5yWxvtly0zWyytXeIGkMIxaiKQ7Ic7n72rB6707Pl8_tfXju67rNZztdbh1tVU2dmTbFfd5ePtj-9-0ByXnUpM1dVNaqrwpiyQGPsagjOGE7SD91yiKtV14f81b1nP3z3Z3_54z_aKff3d7c__eDjuF4-fPzkxvUrr9y4Oige7ExK7z_67LNH9x6--cad0A5iaDFvnz0_68OgopbIIDTNiFWfPHp446WXhm797NkTRDrY33v-6MGbr77cR4gJH52c_8mf_rt__n_4b4Z2GFWjnb19EbS-UhGVsh9w5-qoPR_A5K1L4_G09IXz1r342vVHXz5w3t1-6TZZu7W1BaA9aLdqXeEmO7OmLvuuLQyxasA0X3dkCunTizfebPuzzJIVRuNJUp5uz9B7MRhZq6YR1bpuhpCNseWkhiS-KDlp6IP1SIVrmnEzbkBAhRZD3j6YGkMPf_klxjyaFf1yOZ3WVDrJfPb0PHUDWXv95WvoWMS4osyZQ-YUZbWMVTmajCaqeZ2XP_uzD1bPV3_wv_iD-x_e__zdDw3l2y_funr75sGlo-3tXVdUBkiiCmuKWUBU9E__5Z_8-m__5rSpF-texViSuvbOF65wse9ffeFqjPHR6UnMmjPnmDQxgAIoIIbEyMyyGd6DAEkWQy7noMzOF4k5Rq6rKnNiZu-9iFgi-RpQjMYYQN5AjVGVkHizBxAxSAoIkouyZBUQ3mSQrHMiIqxlVSBCu-6v37l8cbLQhImgD-HSwcHj5yek4AtvS9eH6J2NMVaFnxTVt159Y39affLlo2UIYGxMkUXRWCIVUWcoZ5pWxZDEWMyizlpmBlVE2kQl1RALI5Ao26IEEVQpmmK9HGxVWmPWi9VkMhFOwoCONg8yUUUyzllFMGREmRmMMwiotEHwYVmUYICZnbXC4pxjBSKjIkCewIQQUWi6XQ5t7PqQszpnjSGFPGR-8-UXP7_30DsHmQGUFCWzs7Q4OXv59TuPHzxBY7x1rAqK1pIhs3EOAJD3Bg2llKqq4pi9s6BSjSoQQURAMURIgNYggCsqkVwWXlgABJCsMarsXcGZi9IrJ-89sxKBq0oVJWNQpai9oqoIASP5y4fTs8UKjCjAejkkMUOIgCgsRFg63w_DtcP9nLV0tFquytIf7O7EGKqirIuSU1h2Q2YmglHTFN5Pq1IBuvVaWH1VqujD9dnVyXYn_ODs_ORs5atiPKk_u_vINE2fcjeki9XKeVcWRWMLQwgC6xAK6-rCXSz7rh2m40Yy5yG6yq2Wg6oAwbAOhnC97JpxySmGISqz5mQ2e64-WKAce-NdTqkY1zHk2PdFWZDxLFyWRT0q93f3G1-LZmKYjpoQw9nF8mh79tlnDy7tjvugHIYf__yjIcSYeXergpjHVXkxb0Nm0Sxozy9WxpF37mB7z2x_5zfOHreSWVKUlIx3YGxKEcrCTBsgym2wHjkmsyG_gioRKFhnrfUb65DEhKiqitaiNYjGN0WK4icl1U6CmsINq7YcjwCAM5NDZ-vFIvQizV5DZZVEOEYVxB6_f2trCvZXX9zJjpInX4H1_jQpVu7psrfej8e-8jAeFYOa5yeLDLLq-OrhrCIqMhPoPORy7D9erplopdoLR-WLPopFcjYqxyQxwfFF8GW5s78FSSaF64d4dr4-XfRDOyizigmJm1HFaWjP2uXziySwnPdbh6N-Gbf36qoszx8v27armqo7nfuRE_GXXrrCwwAsUVMY2JfOIK0u2nrkaFwmRocGVZmBrMas02s7k9sHF88X3lrnC8kBk3DmYchlXdjCxpD6tjPeokElRE_GmJy4KKucN38vtKXPORmiuvKxDazY1CUCcGZLVBZFWRRD6Ou6RILtumrXfVn5IfUl0cF0yonJgLFWRIwx8DUvXhUVccM1AxVVEADVTUpRNGZOImQpxGysHRJnVld4EAg5CRAS9UNAoGXXC6BzvqiKfkhtP0wmo5CYRfvEbUhtCF1MSalL2SKu2xhixsLZqlwu1oYQQFnVAq2HPKTYhciqicU756uSWbMqq6roxWJtC2-tCZGVc0xpuVhb53CzP0ZYrbsNPFkErPM5x8y6ocsNfbbGDikCIBkSYUQcQuoTi4oitUNMiQU0JhFQZwlQh8AxKwtba4acNzApAETYUN1IUR2ZyDmzEJqz8xVZG2IEBee9KqtCWTgU6ocgzICKAHVVIcBy0YIhUQwxqwBZAkJDWnqvoswynZQsQATO2cJ5sliXhSMAlWbU1CNXoBWRmJKzbmOKAVAwZKwxiECUYi6dzSk6ZxWQEFW4KqqcOefsvVMA5z0oxJycc1nYWrJoEYBVCXCDnzbWgAgiqaghp5ulN5IrnCOjohvEBykQAqoaQOWcRQfJb_3Gt__DH_-b197-BrMU3hBZ6xwgKqu1lhAdWGudqm6qfGRIkBTJe7u1Ozl9fDbevqZVevjp3VaBmnJ_b8sy1HU5Kpu6Mc64IUXwI66P_urf_lFYD4AZzGj14N75o-PF8_PT-w-HdmAN5xcXKQwyZiLfr-YXD56G5-dquF8PKCw-8arD3GtoUxRvta6LbpWfPRncpPrut165_crO4_tPf_qTT4QsAD26_-ToYOvS0fb-0d7I2dXjk639nQfHz8rJ5OD6gQg48gCxaQqq3d7Bngbt-2C997Wfjqddv173PRofIz8_OT159qgwNuTu22--fr5a3XvwUAEfPz3Z27tUOCyRbGkXy_n2bKYWP__qwarjh08ej5p6b3drOT__3tu_8uz5MYL-g9__-6fnz9r5MPRxPW85Je-Lq7cvLU4viHX78Gh5sTAGDEhmBdS-H0STsXTp0qVJU71wsDeu6MXLO0p2a2dstbp26fKtW1dffevOarGwhX_xhf3IoXKFJUopM8BoZ2e0Na6rylsoLE7GVYwx9L13xhoMOYuhpq5OF8vr149OHh3_wd_6vXE92r-0H3L85juvv_KNF1crXi7XR4f7Z08eSxI_qX7x3iffeOmmsV54aEaTk9On63Xo-sE5673PaSM6hPPz88vXrs5X6-Vy_fj586FL77zx6h_-j3_-f_1__4v3_vondz-7Z8A3kxmh3zp6aXVxqsqhi1S4rVtHgJkK9G68ukijquAhW3LdwDuHs2pSV5PKW9OuFoQWLT188KQwzpfl1t62s4aMXLl6fc0BhFfn587j6cWz2c4eFDa1UZkzqaDxVSMAjuzFyWnOGYDqqti7cRDauSQY-gBgJju7rqqmezu7l_YWJ6eFb0LCyawuiZ98eN8Sza6McsyiGjmHLnHgcTMrGk9lTTGFXru-E09tHAqHBVnvzfnDz-aL08ef389rXYf-9hsv7u1unT94Pt6eXHn5xXI89q6x5FVIRS2oqiABEVhLTx88XZ62f-N3f_38dN6GXBUliHq_2dbb5dn51mQ0HtUPnp91Q8wKHDISCmkGCJkdIRpUYQBEoBCzq0qDX-sj0SAq8ebMz7w5LBwZUAWgrwuyhIi0Wfyyyqio-5SIEFCsq5il8A4RRdg4i0AhZHKGCBUUQJ1zsc-5oNra5-dnAtCFdmtri5MMXW_IKohyJjTd0O3v7rTt8L03X6mcf_D8ZJXo4mJR1oUihS4gYGbOwikzeSc5q2rKApYsGWYGVOOcIRNDNIaKsswhWmszM1kPguRtTEkyAylktWDAUAzZeZuGoKJgARHIWuZsnQWAqig3--qYkzHGex_D4F2xmcKoUec8CwOC8ZRzQFEVMZ5YUZOSNZKjtQBoWOmlO9fvffmAyaSYOEVnnfVOUsh9d-vVlx_cf6hAOYmCqigR5szWEBmzmfQrs5IJIRhDROh8sbkyoBLRxm_gyBhObCylnJ1zAFAUhYAya1WVBqH2lXCsylHftUXhOAuRQTIiDKCeLHM2pM10ZACNNednq5RlMwLNIpNx3ccIrOSsIyy8R9CtybgsbGHJoEUEVVr13axpErO1Zoh5Mhmt150rbDcMe7uTk-NF01QCWni7ju2N6XTVpceLta-Ki_n8xZuXybiP7z8um6by3jofeu7awZdF6W2I8dL2bL7ui4mTrL7wi9X60s5WFzMoHp9dxARImroBQX1hAY0rTL_uc-wtgGQ2aGUYJDMJgiglEWb11nkLWbr1era_G1bryWR04-rV3b3d9eLk5Ml8PG3uPX16-fBgZ7yFFXSLWFl7Nm9_-ujLUVH33XDzhcORK5w1SOb-vafLtl-vhyjiR1UY-twPZvTOr82PPy_HWzIMKGyKIklGY2xZASMSkMG8bnHjTELNokTGem8qq6LGeRAGhI2TAlQ0JhCkgjQrEdmycta62rmmGvrBe4dOdi9vCVDKyY89INmmCAqsvLb6wsuHW1bbdftJyD1pMbOTUdWJFAUthphJnYfImpQ6hXadfGkdUGFNZWHkSAGzcjPyzxbddFQGpfmQJtNyGbIQMqCiztdhNWTb-KB6-Wjy_HRVl8XTi_Wz8_bJyXxrp1BLZKkPaVN4bVf90Adbu_Fe7Z0x3kBgXxtAPHk2H01H7WJZW4vkr9--7Did3D8JMQbhYlqEkEM_FOM6RUTn62nd9cGU5MZ-98bBZH9LAssqyBDOnp92qzaGnlC56613TTPqUlwtWzSYUjTWqKGckyi5wjEoEMacN9D8zMmQSTkrgXMFIWbgcdOMRs1isSqLYmt7cnp8UZXl_u4sxbzBRFoDl3e2IGUyqIBEqCAppZSZLCRmAc2SgYCVQUFAVRUQNxxMVt0E_VUls5CzOWvbxRDZWsssmVU3FLaY111vjA0xqYox9snzuamcIC67DhSZILCuV0NWySmOmrqLPK1dHJIII9B8GVzpEgui1qUPSYx1Oeflql-vejImhgyg87Yvne-yqLDzxlhSRQBcrfqi8KU13hcC0FS-KQtDxhD1fVDRISYhCCxoTEybASxKZlayzq66QVmAMIvkkFiBszhLKUv8OnkpLOKMdcYig0EzhICIKSZnXExZRMj7lHMWLQqPhlSAQ5zUJRINMfcpppy8teuuq6qSWcghGYqcrdlEJMVYcsYaxJxyPSoLb2PgSVOLCBmoyxKNscZ4a70z21uz_f3ZqGyYWVI2jpAINoZxQFEZVXUIYfO-AAbQOUIjhM6RNQ5QjCFFUBEiQoOqar0T1Y1wR0SdNeQAsiCRMSSiREhmg3lFZ61zlnM21hASEZIzpLixoRGC9R42e_mUbr_x-k_-7M9efPOtFAZl0I0iZwNaSgAo3ltEdN5aS6Ja1KUKo8LuwZ6GQU10sTy-_-Sf_c9-e1gOv_jq8aXLTbO7V47qftk-OT7rYPijf_mv7__431ZWCwgxrPuTp8LJaCwMaqXTgy3amigHtRg76dchDdEUdHK-XLd572jblnborAyxMHlYLF586crNq0e1we3t6ZvfPLj14k5erT94997iLJTjUdcOoRte-cbt2biqKrc1rfYOqp1ZE4d47_iiLMvZdjOejCxx6tKktteubI_ryilwzrPxWITJUFm4yrnpZIsYqtJNm3JUV1bDGy-_-uxi-elnny4WrVHz7d_6dneyjDFcunzoUTJzVG6X3dNnzx4-fLK3s328OA6r9dt_4xug6emz8_nFs6psmp3pz3_6S855tTgvvdu9fsQhXJy1l29cPXl60q7miKiE3tqdo6vL-cXNW7eqgn7w5U-_cf22kp4u14Xzo2YskAnx5Hj5wuWDv3j3o-3x9uJicbC1_dH7X1Z1iUIXfTg42CNr9w_3qqJq-zYKzhfr9x8-QnQo2iYT16uzRT-bjMvSjMaTg8tTEULyQ-R1v3r05eNhzc2oMRPeqZoc47WjvR998P69rx5_8-1vAkOIedX3YNxqvjAWAdFZ75wNfQTg89ML4-zZ6fne3m6_6n_4wx89_eqREy5doUK-rC4dvXA-vxAfcupBUx4G7wqOcWdnJyx6Sbx7eTqubFG6sionk3qxXI2asqn8zs64Lsvlej0Mw3y-bEalK4uydM4b5li44ujy9eNHD3Pi9WKlSP26U-ViWqFuNq1Ul76aNEMYnPGT_V3vfNM0pw-fDyGlLCG77f2ZK11VlNOt8fPHJ5PZ1G1XLL0ul08-vF862nlld3XvLPWcWKz3xiIaCcNyGEISDu2wXs1PzxYXF_Oi5Yvj9dn9B8effNZf9Iu7jzTR9TdvUzPequp23qHYO--8qqgGrGYl0Q3iGQ2iBULjPAnxX_3pv__9f_yPckzzRURDrjQq6o3zhS8KX1VVjnE2m8TMF8sekFQggoQsag0ROGNzypYsAeDGBCMMsskQGAJgkJwSERqDoY9EhkQBKUpCos0MypIBABEWBebkvPu6jJuzsWbjdCFj0xCbos6SQRSJUkpkbc6SU2jnq2k1WqzWxXgUU55frLe3t7vVauNbBFXrPBIY5b4Le5cPJluTB4-OTdM8fXpOis77oY_WACIJC6BaNAaVRYA0ixTGKWgXMhASkiJs0rnWGY7RWCtARWFIAEXIImdGss5bVBFQa4wlAgsbvpyk7MsyhaiGjDFkjOBmyo6WyDqbc3aFlxTRGgHVrMAACikpZxUUV5VDz6oMIr7wAGoJmum4IDm9aAvvEKGdr-vJGBGIMId4eOnw_PQiMntrN0Y5s3mrUdBNIBi0qisAMISEYAjJGFWtxuOUBu8LRXClQ4TCe85xNB7nnMrCI8DXZzhrUTgk4sygUo-blHjzguetKUvfdcPGaSOZjaGqLCazccpBCYc-EZEtTdtHTYlVcmZrLQEfbm1N6oZYQohF5YuyTsKc4nQ0yjFZQiCThFGhb_uQ8njSgEKfUlM3v3z--FePrhK4B6vFhYvt-frqlYM4tLuT0SfPT9X4boi7k1pzblfrsiwLEGt9mwYi07XJl3bohqppzufz3dHkou3bvm9GFYuuF3NjbU7ad3Gy1eTIIKox5Sh27FKMEqMrvXSxKCtFIbQcswqDkLNkDeY-7R0eAmBo15DFF_Thh19979tvXdnbf_b43oOni8tHe5Ot6RcPH75w89LZ4-Oto62jvS0ZQlXUp-dz610fki0tIqU-WeNM9cq3gKZYSlysiTTFCN4heVN4yVmyoCKlSMYYZwDIWu-MyZERDYiiIUBLxhfbhyKBB7ZkRQABUBCJRA1ZB0gZkAwUVQHG7l3aWS67jAjGjHZHao1k2Tua1SVvjcaLdfr4vHNbRSLJLBklCLQhnKwHi0bAnJytMpC1JjGJmHIT6zZYNgU6a0q_GjghtgmXQ2ymvs98Mu8YiQGW7dAGPjycdd0wqYvFsosti9PzVd8j7Ow0IpITZNH1fKhHrl-uhy4ObdzenaSgEAFVhzZYsk_vn0-36_X5qnDWl256acJRLo7Pq9nYj8cKnLqQM44PZj1Rsv7my4e7t7anW6N6qym3y-fHqzQk42zStHh-QQQqGT3ZjcQPiLxxpY8hMaeUc8gxCbfrNkcu68IYM_S9974ovSBUrkQAW_jxqOCUUXVnZ2YIHKh3JRodj8rKGouUYxiNJgBSlG5auEuzqaqKah8GRehCVAMiYAsjoiISY1oPgUWjSB-zs0YUFUEBQkwMag0xQwgZUGNkEFRLWdh4K6gxROucglRV6awFFRZZrrvpbOSdU4SuS0y66gZXFiGlLkhZV6C8jqqJFXhrNpkvW18USTQrGoNZtOuH5boDpJClC4EMGe8UwFjXdoN1ZlBednG9jjklJK2Ma7vEFrdGpTc-p1w4RMTaui4GRehCMuSicNoM2xWGIfcxWWsAtSDKgtbZISQRyDGrwdLbLKoAoioItbPe2aEP3jkB9t4yC8gmK4_WOgREQu98zDEMkVMqDKXMjLgMg7PGe6cCdVVdzJe-cJvHBmdOmcvChpALb5VVmRHo4HCaA5fWqIhHNGQREUkn46YsbFXYpiy98U1Vtm1HiCFnZwskHM3GcQiWiAgUhRjIkjWFClsEa6wxRkWqsshZWMRYKzERkiASgEUiRAUtiyqnREiZmdCIikEk9zWSylrLmdGAJZMko6KKOGMRBAAsmU2rm0AlMQtSaUeT7YuTZ9s7B8zsCo-4odQiEhgLoooWNx8OFjZkvLPOWlR0VbM8mzdO9y_P_of_3w__-se_fG17_Obl_X_9R3_pU7x378lXXzx69ui-7TqIIfaDISmslyRhGXmIqQvDaegXq_7JWVy0vFpzH_t5NOjjkP1k79KNy6MsV68cvvX267_9O2-98eKNt99-1Yk8fvQsVK4ZF-3xyV__6Ben50sBWg99Y_DOK3cu7e0dP3t6uDOaVP5wWpRgNjbHT76451xx43BSKu_U9d5eI3EgVQTlzP26A5RR2ZzNz9q2RYCY2QgOwwoVqsZdv3S1LFwWPrk4yxFQ4bvfeef48dOz06chh_b8YrVcxm748KNfjsp6a9xs706vHBxtVeZv_Ue_9R9__zc_enD3e9_89qd371rAX370GeQch75r21_99V_n1JdlaQtqLy6MAUNYGAdgr1y6o3n-_nsfv3bnzpVyuuzWb7_1zTTEru1nozq2_XK-_M4bd9rVcojrEOPdx89ef_Pa5a0dVt3Z2Zttzazoo8fPLi4uxqPqs4dzGKBd95jREBzOpkc7sxeu7qAtprWPCmenF6--dOnnP_9ChJeLxf50vDWrJec0hMuXD42QM8OLAAEAAElEQVSihghorl659Oc_--TwaH9WN76wtZv--Ke_mIzGq3VfloVk3d-frebzNMT5YtWHfmtrMj-f59B3q7UvK1cXIYqSYbSrbk3Ew2rdXcxzZAWcHOz28-V4PN6ejVO7rrydzKbnF8vtnalzZVHana1tY-xLl2555x88etwn6YdQlAVznk0mXddKys45Dj0Inh6f2KJoF2tOfR6kX7R5CBzVKLQXfdul0bjOos4UHFPfdgxmtn_Izl-_fWU6KiSl2Ww8rAZnDSB288XJLz5dnZ55b4qqmD8-BzKASAjWA2fuVsPAiNuzsqh2R83I2cJQ4T0wXrq2t3Ntkkz99OniV_7Jb08nV6-_80Ib-5DyO997oxnPvAdhSilvbC8Am6ueiJCAgsInH3z6wluv7u3trdZDH1NZFCAS8aL047IqvS_71dqh1oVt2xBFo6i1kGIGIFRBAM2inDZ4YwAERlSVjYE8ixKqqjcWeBOetJyZAHIW45ykbMhssqbFRiefQICtsQgIAGhMjNEZyjHD5vwU-bpxSl_zFBCgdC5jNmXJmTNoZo1t3DvYlxQFdGOfzynVVZW6AKDX9o_uPnkSQrC-Oj29YBEy6gljygIYU4asQOiQRBBEUBUVFIS8C0NABFUxhiRnZyyAZmbO2YBFIOPIAhGaJFkRqqYREc5iS8-iCGit2XQdFAAVhMUXHgzlzCmlzZGYs6ICEcTAAKScbUmgzCxgFFSQbNcH6wwzWzLWG-Z8uL8_b1chCiDEFDnnoixEhFNC4lEzYcl9FwW_5oVDSt4ZBARDZFGZ67LYhJ1U1ZcFAYiocYiKIcfNV4iIEzvviUhFJqNRShkNJU51VSqrqKaUjUURNda23boqqxzjaDRJEp2zZDevVuqsSayswoCZOaWEYGPKiZMnq4jWEqJc2t0pLNZVmVLy3m1PRuvVkIQ1cu0KAX12fkEGR1WlSkHEGiKioiy9d-thuLmzy8b94vj4YLRNyher1cR5KgsdFxdtBKX50I1GI1-54_n68tH0-GxOKqOqGGIeN8Xzs_ONf805K5YWq7UCZtmAARNZowSFsX3XpxBCuxZWjpvfOULOpjCaMsSMBv1olLt2uj1bPD8v63I8Gl29di0zfv7lZ3devFnV9cefffHWqy9WznTL9kefffny1b1hyPfuPrlx-9Kzp-cvvXLjyv409YxkHjw6cWU5X7Yk2A-h8nZU12byzvdiTKkLGqNBEM62qFhACEAULeXV0gKgtZzFV3VOCYlsWSKRKXxZN9ZZIJI4MLMtKjJGDUhm8J7GtYra0qXEduQ4y3oIBzcPnj2cZ6VyVrdddN6psSjmzVf33v_gop7VTzqWkS8rq6C-smzs82WPVSHORYJ7T06ns_HB3vhsnkD58GZ98qS_9-js4MruasjO2cjSs_QCEUTJoOKTszWjGViTqvG2HPmuTZrFED5bD3VdfPX4gsDUHnKXQ5u5F80CObfrfnXekTAybk1sNx_qcd2t-5yEahlNq9S2RsQgTg8m_SKfPZ-P9qd9TIIJERPD1VevUOnffufapa1x7YvTk-Wy47OLtW_q0WxWbdV-Ujx_eBbaFYECM2oO61TvzRgMeaeKbRhUJTDHPtnSiwJx9s64oiCjlgyAShZJuesGZ0xdFwaRUxIRHnKUPGlGxhAqFNYUFra3xlm48RZRL0-ns6YhQmONagJrlstWAJAIAcnRwKlLnFX7lI01XUzMnGISRAUFMlmk71NgZlUByFnJuyHnrMos1lpjrSrGlMuqDCFZY1KW0WzS93HdDst17yt3sVyjL04vVmosE160rSDujGtD3IckBkLkDBJCKlxhEBarNrEKUDuEoizQupizLTwnLrw3RIt1q-iXy3UYQtcNbZ-QgKymLKsQvEFrDStsNrDTpj4-WRSlj4lRSVRXfS8K1jlVjDHHPqklVY1ZYpaNAyFFDplDDEooqMwKgKwiqmTQeSMimbMxFhA2-4SU0qbyq0iRs6qCscYUXYyld3FITVF55wA3wDtFxKr0zMCizpmcZDaq2hBrbwvnYx_3dyaS2Rm01tS1r4vCGmiqoi7cpKnHdVUUru06zRkMGOvQGOdtu-qcJUfEnA1ZQHXW2sKRammJRTZ1POcIERWUyACzsY5FiLAgIjJZgVC8daIba7M450BFFJAIFC1uQkFQGKcEZAwBoKo1qEi6ET-LoAIZl3Ni0dFkjIRhWJb1SFWEVQEIABAkiyGrLLTZCRDq5k5grUI8uHz01Zd3J3sH27PdN9-69dWnv_zrD7-8e7H6B7__G_vbDZTw4hsv3bixd_POjeuv3_rG77xdXt4-ePEOmeK7_-h7zc64mU0vX708Pz31hVVVTgNCVhOnV7fpcDJ-4ZuF1b2rB5Tz09Xw9LPn62Vsz9uHj54_61Zfff7o_t1jTlJOprnwh4ezF29fuzRr2rOz6dj-1vdeF1Uj8dLB7uXpdJ752cnF3fuPdg92Jk01qusbV7a3agdoYp_AEnmqxqX35mKxjBwuX72sBr0xIeXz-akhuw7tt958LSt8cu-rbt53bfi9v_d7F6fPpuMpihboL1-5cXJ6emX36KMPvrhz_fqvfOf7J2fPTp6fPDs7DiF98PP33_vgw4_f-_nxyfnZ8xNhjaGrCmeNvvzSm6enF4uTZymE-dkFcx5Nxoo0DG1KS2V55fVXn54f37x1xxrw3u7tjpVzNW5efetWDlSMpgej6cX54uxi2Z_NzxbD7qWDmy_cvPfgq6IqjaEYeutoXFW__u07r7148NpLB9eOdhrrUXXgLJwen60carda7-zsjLemP_jjn40m5eHe_v7Olko-PV7cun1Z0_Dg8RMOeXt3Om3G9589efLo8bXrNyBrVRVf3rsfUiBDZtOgFG5GdY4pizrrlBSEVNgZa5y1RdF3AQjrWalW1-cXiopK0_1pThKHdra3ffr0eTEqMzNaulgsdg_2-r73vlgul9PZqCxKlSHmnFKajEbztitGFVgczSZVXXZDN6lH1qIrivmqNa4UNcJU155QvaHZ3ta6HZrZ-KVXX14sVmiMsqQwlE1z6fKlS1emB3u7lnDdpWZUa2MjyPJ8uXj6ZHj-jFCKsSdnl11S0WbchBSNpwzGT7duff_tV77zxltvvvz6KzdevHXtziu3D1-89UlL3_3NX3nnmy_9yf_rp9aM73zn9aPtoyuXDsfT5oOffP47v_WrhTrjbMpAZFjZGAOAxhhEMIAAYlDX6_7J_Uff_rXvxm5YxtQPw6gqiciaqvKFMWiIcj-Utb39wtWnT0960VU3xJRjSpySqBCACgBCTslYy8LOOmNo4OxckXMCRO9LThmJRISFFYWsSSJojIAikQBkVRQBREAAwpzEGENkWYSsyYnLqvoamAFgzOZbiSFjrQkpozGs6L1VQFVMmwqp07IuV12rSimEsigYwDujDL_5rdcenDydL_O6H8TAetUqkqoa5_s4AMgmYspZ6qLeiIctGSLKOVtDmnPpvbACECoWRZFyIm84saMNiQ4K52WDIgQiQ8yMAs57UUUig8YgIW0IEAYAM2drHRnUxNZ7FjaGADQxO-tTSikOYKwAGLJpiK7yrAAgzrkUAqKy6M071-_evc-KpCalpMqjpiYgAFWV0KfJ1ni1bIHA2AJAOLMvnDEuZkZUax2RQYPC7Jw11jjvBZQAqrJkYUOElpIIok5GoxyCCJLDuvBZiUW8c1XhhxTKukohjppm89BBRGudijjvitJzlrKsQghF4VSBWVghZUakbujIUuHdkHNdlikzgO5OR9vTEQnUVWEJWbjtBwH1huqiVJU-MhpqqspaO6RYVVXibG0BqJnj_mgUQd-_99RovP_guPT-nVdeWl50D1frRT8UZbXuhn7oPFnXWE25MDZ0yVgbc8wI3vrlfNVUVYrMoEM3ZESwPkuOKaG1aUij0Sjl0K5XxpgUIhkkVBSByKgWGSAnTuzHTqOyQtkU8_nyysFBPR6Nfbl8dnzt5lWlfPfevTvXro_q2iIfn128euMqGd8j3713f9w0pdK1_f2-T92qU0ORebFYF0UBiHu7s0ldmead77JK6lcGFbPkxOoQGsdJDAIIY8oGkZnJGOGsm5uhr4QZFInIFBaMUU6pz6YgRBI1aK2tKl86QhpWgxIWhUUiX1pvnDjTcVYQg9TUbmdck8K9p-21O7tSuWLkXAnksI1cz6qzdoDKRZF5F87bYXs62puV7ZKfzLvRpKgG-eTBPDnZa7wa9IVbDnHNElBP2nww9U-XXZs5WdsmvbJVGzJfPl5fu9xYcH3K5cx-eO-5d2ad9PBq3c7zrC5cbRNH5TQMYejWhcMsksSawqPR5fEqKcvIUsZh2ee11LvVas3NbonK7WrVrldgysu3jl781guFsxbtsteEkAkDQK-wtb-1XHYckvM6LLvVcohdR6p5CAi2mDVm5PpVS4iL5co2JgwDNaQCCsIhQ1Y0ZMkBalwNZe36VfClBVBNGZHWq_aFF26GoStKP6qb-WLx6gs3l8t5bVxhcFT6Lgy729PE6dJkXFiPAIhIziwXa1f6k_Nu1FTLVc_C8z4MWZb9EAXWKW0WfLzpwwJlkSwQmEPiIeYMwAAhsQAOMYlqSIIIKWdASilYpHXbWl9sOj0xiXUkoOLswCyCbT-s224Zwt7O1hDirPTr5WC9jUMCJRGGrCyaskymTRvTxaoXoC4kXxTDEICo60M7BOtMH-MQoioURVFVZRdiUdd9P6DCqmutNdZ5ssVysWKhENPQDYIUYmQWIhpiJEOcFEDIuJgzoE2cQ04qCoRhYFBNIqK6ufQW1jCrs1aEC-etJ29cGAKrTkaNACBt2hVSlC4zAEDb9jmzAuTMhshaI5xFxTrHKXvvVNVYyiKNN5HVeQpD8s4K87gunaXaO-vMqC7rukgpKcjuqC5dUXgPKt0Qcs7OUeUcWeu8I0QLUBWudIaMY1VCqOrSEOYkdV0gIJLNws6TsChQSsn7gpmJUFkUFDf1ASQBdrZQUCRSYHIODIKCsFiATaWEgUtXC7PxRESCaAtPgAbQObPhoFpnvbOx6-vxaDVvU982zUREnEVXOI7JW6OcC2eyKCFs5nksXJaeAIjk9it3Pv_lx1duvpRyuP3iqyNreTX_7N7D6c1rNRUPH9z98KN725OpEc9r2Kp3MIEzpiqb0XTH-qKaNddff7HZmmxd2dak3TKXo6Y9mefF6uyTj7unzw933fXXjn71jZs3r2xVhU0FjSY-eBc6LsuainqAans8vrY1tXGoiW-_cPjay5eOtqrJdDTEdnd7PNuZHNST7__qSx98_qie7Tw_mTOQsKi4woh1FqqiqgpQSMLeu6aqS09EPD3Yunf_waiqNOWL-cVrt2_cvffo9NGJLYubt66qDL9494vZeFQ248X6vGuHIcWhX73_7NFvf_9bNy7vlqPxbDK5dri745pHjx_jIE9P517c6flaxWagXni8Pb14fnpxcWY0O-OfPXs-2d6ZbG_nlAVZc-j7oV0upO---vjDh_e-eu_d954_Pz-9uDg8PDLV1p1bt37ww_9wPp9HkXd_-RlzCm1Yhnxxvvj4l18dHuwnkKt7O9s70_297a8ePiVbHp_3Q8xtSKNJNRnV_dBaY8dN8-6X96a-_OTDr8jqwdHuwfZUY0jDejJyf-Odl4Rpd3dre2dmELyjF15-8a_-3Y8fPn58-84dQthv6vc-vtuMR33XOYMGkHMcQiwql5mtd_1iTSLGW1e4MERC9YUHxLgcWFiV-_N5sz0dlj1nQcRqVIUYm8lEARkw5yxZ58vF3tYWIiwXq6x5b3vHWNPsjOcXqwwckzZlMZnWy4sFCIQwhL6dzzvOmcCSB0nim7Et6qFLfjKazmanz5-xCpJYX46mW4fXL_lR1a-y8d4WJTknyu3F_OyrR93J8xxaAGw7dbOxiuEY65FPSdulvfHazVe_-zcuX92bNXVV1QBq0WalKLDqhtdvHd7amv6f_4__cnI0_bW_-_bO4b73dnvaPH78KIb4xus3-3WnQAKYN3lFIlAwqIQmqyBHcO6n_-6vfvPv_a4OOWWdr7va-aKwG8JeURYGtPT1Yj6fTcvLh7ur5dDFOATOqiFFRALGFAVRCTcvaBqFN7CAzAkBgUBZDWnOmVWMtwAYQwIiZgYDnFlF0SEzIyiiAWBlQYMCXHivWWKMaNFZTwjKgsZw5k1KEwGtxS72iBRjCEMsC5dVwhCtsaELO3vbbdvllAvnjTFiYDwblcb87d_43scffnHexyEKAAxdcIUfhsEWzljfLdfee44pcXaVZc45x4yKhgya2HabmxKocghCoAQGTIoBAJw3ChhDcIVXAJXkC68KBgmJQBkEWMRZByJKgIicsyOXmZnZWs9ZjDUxJFFFRzll2JSsnAlD3pQlyrJAQ4CY-4Fwo2_RfogvvXTr4cOnBi2nTAggWHiPiMZaQhDG_aP989M5WMs5W_t19thWhYIA0GRUqYLzJQAXvghD8IWLITrvyRARkiFXFIDkvWNh57wrCjBYuiIzO-eUpSx9SNkQGWsJiMixsLXEMZvCqmhRFDkEIgOAhERkur5HY1LKOWcFKIwPHHe2dvuhJyI04K3dm44daOF9yrnvI6BpUxTVxjkARENdiF0ICgIGjTVB4ta4WXVtRb509SqlZ4v50LZHlw4-_erBS9eOSt_8_Mt7gaWsy8IbSoqq8_naWjctqjZE6-248ENiYBFhAugju9IDYkYNXRKEtl2HbqhHDZAYRRHuul43K5TAFhW6TiWRAWvN0A5u5EEpJS5mdVUWt2-_evL84sUXrw2rZTWu-3Xs-u6Fa1d3p6OL88XnT59fv3K57frX7rz8yRef7e_NJs3ocG-bo4TAq7ZfrHoFE1Ny1mqWoi5se75KmpHBWMttcGg4gYQkXZLaO2uFLKFoRuVEvuCYq1GtjixY54vQ9ylGZq5GTT0zITJaslsjBcTCtavOuFoK5wvDQwxZL791uT0fzs_Wrq6GkHOQYr8alfDuX5-_8_bBVl2frvrpoe8GBaLxpJwv20Wb3IyOlytrSmUFlm6dL5bJEQwVvfv5BQNcv7I3ZLbWP5t3XeaiscuBZ9v-uA1P57GaFCz5ym4ZU75_0t46nDg2wMF7un_crs-70ZFD0gdfrdKau8DkpJ23uhhyFhtpve4nBzNw0HEczgMhCitaiU9aVKQGksHuuN_artOQMoOh6u_9F7_xxV8_CPOYUDvkkHJTlamP90-X-7M6c9zeqqcj36_C3UePy9r3hsBC6A2NKiY6__J56XyglHJK8yiJU5sL8pLyaDrqVstqXClJYV3P0YNf5D4HzVlt7fu-q4ry7v17V69c7oeO1-tZVT49fXq0M_nuN2_Nj7tVuxLS-XpVOABXECFZzElUtGzqxHKwMyVjq7LMko2SrYuTZUskiroKuSEiVeescrDOqXDbx6qkPuIQIpAbUq5HJbJdrNfW2pCh8qWkVHgPzD3L0LWrdSjKajwtJXHqhu3xeBXOQ07t0FtrqsqHoTva2nbkyLvlulfW2MbprNmqqvPVwBnmi9ZtBJKqIHJyfFpWVUgpZmYAjdyuB1FAVF_5nGJK8dnzE-dJxOdInNe7B5TbQbKk3FZVNXDKkpVlsV5fOtgdYl4tWl8UFiH0azWWc0AyKeWmrnOOQOhKMwzJk0k5ezRdjJOmTjGO6zqF7G0Rc7beK2iSxEkUEIgs4rDqm8IvJTNCCkNR-PG4ziH1KZbOM4s3Rq0rCjd0QUEt4rKPOaWYbVG4nNWCTndGJSGn3Di3mZegaulHSBRjIjIhxDB0XRvq0Ug4E6jkXDqiwmQWROPGlXVGteyGEEOsm6rrh9IVuR8sIWeo6gqGAcEhg1oksiFk1Q0qm1Q1q3oDhGDJdJGJNgEfKKwjVEASBRDkHA2BMBKSKpKAoooKITlvZTOYYrbOdcvltZtXPn3_w629vaKwmXMeotuA3AQYlIz5mp5EWPk6pzyZjDnFdrE6unr0-P6nV65e6ym89r1vWnj9-OH9P_5v_u9X7tz4p__Lf9C1-oP_8NNvvv2NIecYWizG33j7lf_u__mDl24fXDk4atsVi-EpAvD2O7unD55KLM9PL_Yu75ydnJDB-_dPPvz8DM1P9w-3TJa2jw7N1VcPfuWbNxtbjsduMq6uH8wgxraPjbfqC-7zF6cnOfdO7cmzxfpi_exkffaD-dPjxZ6IV4DFmd-rZrWseiLvHUDsQxyGnHVne8siMKjxzpJZLLgxumwXN3YPW-EhDjnz-fn57sH-tB7_T_-zv4NqitkMzDdygPVqcfLgcTNqTGE65mo68U0xmY5czu-8eCTLwXhLwMV4KpSNs64pC6Znz04lyfPj0-Wy_dXf-r6gOT1vH3z1yeLs4vT5k-l0a71cQBQeYpYUU_p48eHupUsnJ_-2LMd_-x__J9ZZFX1y7_GsKhWlrMuLZyfDYrG1Va_a1flpfOPFW0KCinuziXCalM4QNt4bb0PI4GsP8tHdu0f1eGdrcvPVS2ePzi-6yJJGlb90dO3sdP7FvePJeHvksAvtOoT1_Gw0nlza23rw7Pj9Dz959dbN3YPtyzujs_lCQupjoKrYQAZZJKXkkhPJqBpyLKGp6rKdrznIZLYV--wEuUtVM5Ovc9ooUcy4BNAU0nR7d921OeeiqbrlxdlyeVDtgjFPTxeT0XK9Dnm13tmZ8cVyeX5-cbGabM1eefHO7Zdu12Q_f_Dla2--_eNffPDoi4cWsLqyi-ByiMWoGI3HfR_L2bSsy92d7cX5uh6NAVJkHm1XiTi2IQxh-fkXoprma2dYizJGc_TCzI-axbNnVVXauoLe_cH_6rsFgyo6t4WkA2RvHUtctn1Jxdakuby799c_-_j7v_XatZdvtd3QLqMzFgk-eveX3_ner4Y2CJAAKrD3BsQCgqiASpKkqET-5z_56Z03XqaEAprROELAbGxdIHlfOO8g5yRsDMbEZV0bBescYg8qBgEBGQDRWAthiGQtkOgQFTiJGmdQARgZcoyKSFkysoKK84ZRjXecclGUaQiSGJjRu5RjVTR96AyZlHI02Rj01vfdEDB6bwS-Bs44Z4bEYFAQvK2AFATB0SCMrMYZINKYHLimbtrVedNUiaM1lSXkLKNpPZ2Ovlq0RdWs1711rg-D82VY9b4ui6oQUeNNGrhrO--diA0ps4D1xlRFSJmHWDjjyjIkppTrshbOMcsQs3eOvBlCUFAB6kNE0LIoAUDBAiRAyJI5ceXqkHpEYt3M-zFn3rCtraUcuG6aiFFFAUCi4Mbrg8jMFqzE5L0XFUcEyKNx0y473NCZQFHUWWeNC6Erm1FKiUNyBjaTKVN4yRFUhUhFrLNUYGKRnIHIeuesGftGRGdb02EI8HVpmEDFEBZVKTkZciJMZENm5wwgGOeyaFV5QkJBUDUEhqgoCnUqqtY6AaiKKuVc1wUAsgCRy4kRXcpDVToFUdX5clGXzpCRlIchGiIDAKCF86BYe7_oelYWBFIoXeFc6lOKOXvvLBEpICrntNtMWJRVysqetTqejVF45H1G__Dp-d7VvbNni_2jSZsyai4LC6JRZVQXZxfLV68fXAwhxrgcwvdu3_jlk3NH6AoTluyMubxff7ZeA2Vu1ynVzpIrS5RFXZax7UXVuYKdyyErKJC60qVlT64g4zyVdkxNNR7fLC6eH4duaBrbdytrjYIQYELICR4dny4X3Y3bN2bVqLIkia335ViMg0HiKuYupJhTWfsY0smTY8spUklMkrpkDFlCzcJB_ahEEuGspJozCoKxKuDqSkQoZuYMhEAqOYJgCMGNpwZTHsBH7dcDOZ4ebQmD5JTbvtgdH9zYXZ32y_kai6IfumY8UlLJ_OTZ6ui1idTF6fEaa7ucR0aFGnPItvYV4bOLdhm4tqkeVZNJsVhwBLN1qYin_fOL9sbtHePN_CI3TrrIs7F9vBzaoEEghVxMSiDyiVGw42wcJdB1z8s2tppPFl2zO24Th66vCy8YctDhOFqJmgcEUgOudBzjsMrFju_PW4lQbFs-zRgzjcoYpTtb71yZLc_mMcP-rSvXrx7d_cmjelxCZVerfsg5A3FicHC028wXw42r00nhSfXTT56xYuJY781Wj89GB1uac7hYWG_NqMySiTIgIIlpEJaBCHIcfGlFgrCPhL6067ZTlqyMBhRgSAIQm7o8Xyz3DiZx3SfVITMZJNatab0_LU667my-fDwf3roObQhejHO06lNivlgM27NRH3PhKHTISGk9NKNq6OVkvWqKIip4gyWhMcQ5p6wpa-qzAAoYzdKHFFAL58fTcbvqB9GY-rry06a-6Ls2ZhFhhdD2g6TCmCHwAF1hqB5VtnCrtluv48FLhy7p6Xw1GVerFFddywJmSOdlKQiSuSjKKMwpx5DQmdlkPF8s1Zjtpnr_7sPxeBwSt-tuazY6O_n_E_Vfv7au2X0mNsIbvjDjinvtfHY4sepUnQqHrCoWQ5FFipRESVYwZTfckAB3A77qi772le8NWIABAw1YgINsoG25W2S72RKTWBRDkZWrTg47rr3yTF96wxi-mIfwP7Cw1pxrfnOk3_MsY4ys0ZZFO2Q3od3KaUiXz8-AXEx6_ebhct3EmEKSEEQQz9cdgspn8jMwxg1DGGImi4rcDj0hxZSZXY6QJJCzCNAMgyfy1qB-trMOkiwb_f_vK1EyKKoI9F1AorIqQ58Ms0QJIVVlOYSEKoOoIRz64JzLkoY2SUqF98MwjMpSUvaGUTKRZWNGpYs5i0pZWEZGVC59PwRVLaxzM9_3CQ0bxYNZuV6H2IXJqBq6IASlsUMI8_FoMirbLpA4slxhSYDtEDUnt4XCsqaoRETEW_iPtV4kgqKyenYhDb5wkhPDdnClIhEUnHFBOhQwlpQBFLYBA8MGKxviQMgiOeWMWdmgMdwuFw9ef_3dH__o4euf15gzIBHFmL13ornvo2FEBGusghqk9aadzSpVOrxx7Yd_9YOjl16CAbqQXVnPX3rlV_-Lu9_9d__Tv_rX_-1v_d1f-8o3vvzs9NRW1exgr1r11tB_8b_51h_8f3_mM5XFbLG5HI2rkIYMcPuLr2rSO-HexfHzw-L2i2en0_FoQtgNnXfmC2-_vDf3RouuT_vTqpqOqhKaxelf_fA9zDydTypfKsXjZyd9103n4-mo2js4OD472a1nq1U7G_mUeGdc7ozGHz06f_qCuiG6gkeFhazXru2-dONwcbV4cXHliwKFLp6cvvbyzY_f-_Dxe0_e_O0v5TavLtfT2XiV4ze-8oX_0__53x7t_w2TvbhcaEpNPxSukBgXi3W7uKynM7aWGQVBU7aGs2pV-mEYchAEyFmSZgBRpaFtYx5SzNtgX4iSU7a-aJt-PMM8pKyaQkTSup6-_qU3Pvrg08urK2_6f_N_-G-kh3pUDJu-6-L4cNqsFtcOdp599DjdPvov_9kvnzdFEq2N6VN01mnUNoeqcAiQh8gZU8bYDqNibNEUzs-K-mQ4bTfdrbtHhbOWEyFtNi0ClZVzDotRobyXwf3j_-x3fu_f_vdnjz7-YOjuPXz5xvXDs7PLSemZOMR4uWnLokibjgn7pims0xQlQuj7ohgxABkNqxWAsinb1BkmVIpDprKQmFmxCX1Z113fZxFDtut7Y2y7Gc5oIRILXw452sJO66nmy7uf36mm1cHe7vmjYz-dbT2lsdOL0-e5GUpiJIXLDZfVeDoaYupWXSKsnJ9MZ6q4M5uEIEkzoG5OLobUro4XcUioWTVhUe7evvn00fH-9dmkotXZeRxSOdrjsvrqtx-OjB-NnClMGGJKwRuzWFwtF82DO3fmo2pnMjld94WFB68_PGtjP3DaxPG-XV5etevlnXs3FpebPqk1ykiaBESIAFWVgAhQcUjp7PnxN771S7GPohj7waJYdimksi6tt0wIYEDBG395tTbO9Cm60hARJKGMSTNaMASWOJNXzRql4BI0J8kKYCwRGVVlQSRANFmkdL5tEhJuqxzQXBVFCIGMBQVQCjky25wiM6koGgsxW2MVxIADW7RdMI5A0FqbUjaWiQ0ikAlhiNY4Y6wBjEMggydnZ8Wo8taqMcPQuSGsG3EI1oMSqEAIWUWssTHENAzGWwm5MG4IKaW0LaApAwE6toQMCVDBGxtSFxKwQV9YSdKHiNZ40hCTglrjJEuW6OsydB0gMhmVtHUjdH1febvlv6UoW9sMKqSUBFVz7vseSIEg55w1AxoAyZIUUBOoZuPrGFNOCQ157-MwKMB8Pjo7vxQRkGDZIjAAeldLikpQjkebsAohOmcTaI6REbOIQSAAycpExMRo0JgUOyqcZhANrqgl5y2wCBVRtPR16jsgBFAisJYZKaVMCMyIqiLqSzOEgdFJFuO4HfrCewOokj-7AkW1zoSQQSKCGLT9MJS-SCla42IYCospq2UhQjZABHlIQw5E5BwroUJeDe1NswtJESlLbtu-qqy2goUUbA2SRx55t-ijAKqwOHp-dvGNtz7XtemyafyoYLVEPYdkcu5iqKYjy-7F2dWdW3tNGBZ9sNbEYBXoWTcgCiFb44am2xlPl0s16GKK2g-WLQgjISKFlECUsqShI2Mh6VYHTaIoikiqEvvWig2hdQJd2098ublaWuKj-f7ufPzJp4-R8N7Na9bw4vI8DenBy7fnvnr_o-ebZRO73lnz8oOjn37wnAnrUe2cdRVrjEz3Xo3tIDGRI8hZsyiRLV0MQULGrBizUaGtDpQNGoMKCoiEKoIItqqJSBOCKFhiS7ldF7Wf7Nc5Ywa6dvdW6EIU9KXfNEPEDISCSobZu8M7B--88_xzr9-4vOz2X56eXK3YKnrMImA5Ix0vNk1UQiaA-bg8XYS2z2CJUvr4yeW4LD53d7RaJwRuQvZH_mIznJ73xJAEFXlnVjgFBvUEF5uQU9od-_PLxo3Lk2ajCCFJ2wRfunXTIXHbhOnI5r6TTUQLQMBKEiQhNIuNBbClFUxDA2BNSGHYdL7yqY8xwI37N2_cu2kLHyH6snjnw-eLVizrZKcOXXrvydW1w9nMm8p56fPFsu1y2juYI6IfWTs12EfpovTBjAolwH7QGFOIOWccALMgUgrZ2UoA-y57XzAibo_84jAeTTILILO37br1zrfDcHjt-mq9mNRVE_p7N_YdO2_IkVGFB0dz7ywStTk2MV82nRgTJJ2s2snOuAlJmVg1DgmQB4Dvnx975JAlKQro2aJBNG2Izpk-iSKwNUPKTQhRoYtRNIuAqGQFzRATJInOcBfTtC6C5BCzANiCN90AREOIMWnSrKKlMWNvc8rtcrN3UD9_sWm6htgSIKiGFEF10wUh2nStr4qssGz7uiq7rrtYtZuu7_qwv7-jIWw2m5gDZpUo7ZBKtK8-vGHBLNsYck4izbqdzOvL83XXDxkhAzhrtiklJAwphxhzFGd9TMOsHq03rSqEmGMMk1FFbCyTguYMdeVICRFzwiTJGGuN2XR9uxlEYAgxZhmGrMwhJAJmRGtYFDRD0uyNizE6y9aabe4ti1gmJCSkYQiFL3JSUElhcIZL57yzCIoKTKSq3pquDzFGJqqqUhUL660zhTfVNqGVRLMw03g0ijEZY4lgPKlSn7MIO4OIRGgssQUQFBFVFARAHGL03gESM0kWBLRsRDOoytYfh8pACEqGMmRDHFM0RKV1QVJhrcBWHc-gypYRAYgIdLvMscYgUs4AkveOrn_0_ru3bt3t-1ZVvbOSEVDJsuTsCwsWHRAbs9UXk0FruJhVH7z78dHtmykmZiag2hWvvf2l8-PzH_z5j1997f58ftBfXZoAljn3IfW6d7i76lt25uPTbjqyN-_cHrqBESGl2d6EDO9c33Wj6vnxuea4uzc7Pb7YXF1KFm_9qHQvzi8-Ob5slm1OtDPbYTYCWSSvVmsCsZXPabh95_bR9Z3JtC7RPj_ffHJ8Cux8USQFw9ZClhQMIpHZ25-Px9Xl1VoUDPtmGARouW7bpqt3Rqvz9c_94tf_4D_8MRClnG4c7T98-ZXPf-7h7Xu3v_jmV7_5Sz__jW9-_e23v_z2z729M9_92rd_uQv55OzyV371127dvfXi-KQe-65tQxIEiEPf9W3TbLq-7ZreGYpdgJxRFUUQATICiLPeFzYFnezsxxAy5WbR3Lx_VyR3bb7_yudv3n_t2aMnKdCv_MavnR-_sMXo-uv3Zi9da69WXd_dvH-zCfL7P3r6pbe-EGMsfFGVXkQNwHq1PLu4bNqh8qX3Zly4-WhUl77yBTOFkGbT8bVre8aSsZadsYV3dTWaTLwvDTvri6IsN0380U8_PDk-ffT4sS3sD995_Ou_9o0P3vsIjBnP5iFGtppyYgJk7JreVTbHZD0bXypTs2xG0wl4H_vB17UvfLvpqkmd8iCaAckVRd9HWzgEzBLIOQAZz2ZAOgypGwIzjXamzXr99NHz50_Pu8v-8mRx8fzk_Xd-1q8XlxeLp8-ePX96UrnSl8V6vQ45IttqVDabAcHceP0hxtysm52dkfXWFdin4eTpSbtctleXw2oTulhWvtqp3HiCphDmo8P9owd7p58-WTf52r17_-iff21C5eF815eln1hK_bQoc9f9zc9-ZsF9_s6Nw3rsrDk7O_8Pf_yXD159KSvlhCmkcWHKiv_6r79v7fjlV-71fUqohKAxeWsUAUGTZgAiBGvNd_7wj3_xV7_lTJkVU07DMDjGwjhyrvResjhrhiGUpSPB8-b0zZfvfvr4ZBNSn9LW5BiSiAJuofAEqsJZrWVS3NrFVQU-84kAEeQsKQsRAkIWyZK3tlEFIQJFAEJrTByitQYRt08eRGAGRBPDwExbdGnKAqLMxJZzCp6NSBIRYlRGzwZUUxYAiIMW46ppWkRNCoiAijkMv_lLP7d-fvWz588AjCjKkKqy6PpWgVUyq3hjYv4MXuYNxzhABmdcTskZD5pRlJgICTUjISCJiAqQ5aEL1lgBNdZKEiQwRDHEoq5SjlmEDYECiJJhZMpZJKs1NsRARCBZBUMWVM5ZQXIWzCkSsaqwoRQTIQFjTomJt6RvQBjVYwXTblbeGiTSlC2TSqqqsut7NgYkE0LOKYs6IgRQ0aoqDAIi6Bb7Q-C8RVJmqoq67XpUcWWpkl1RWGYlcoUxloY-VGXpS68CqlA63_T9fDIZ-sEQg2ZmIxn1M4cxG2tAULN65wAhJilKN4RExDnGHDMCqmQ2VnMuqjLK4NiFFHanY6V05-jAIQ85qmRmDlm6HJlhVo4NURJddx1b9s46xJgyE06mNWV1zBl1UH12ejKfTxYXl2_evePYPFuvXyy7NmRmXqybnfns9GKxtz9fth2itiENYbBlSc70fSMZq6JcrJv5bHJ2vkxDNsZVzkVJbbMJXa9ASqSec47tcmMJSSH10ZQMFsNmYEAJmWonxlhjcwiQ88OHr5y_OB3a9atffLi8WlvA0vpX7t_48OPj0bj-9Pj03Z99cnFxefOl64e7uwd7O5fN6o3bR826hyglmccnl6B5G5XOMe_tzdm-_IbkRAyaRYbIBQtjAiViJNAcefuVQIzWZkVjvRKC5RgCGyuSUz-QMaBApd1mdtgVYgvemRc7tWMTNmvwZvpgL4a4uFiLQWAg6xShno9T0mpeVqOyrunJ2aJPsRj7PgtZq6DPL5pNyFwUq7Y_2K_Oz_qzy44tOyeLZZMSTablECQGCQrzXfPk8WqzGhIhOq5HBSAVhO0mjGoXJG-CjixVjnqUpxfL5dUqayYmTWpYDUlcbVByc7yApoccoCAlgJgBNK17GhrvTQ4ZBmDHUHkD6gkto_FczGdv_trraTPISP_6o5OuGdAWX_36vmU6Pe9P1_2XPnd9RGxQh02vqlFxPqlV4_Vdc_xk0V0OeQiSEhIoZB063QyURAVRhEE1CxpmZmQoapva5EuLQfq-N94by33ofVFnykM_eFcMXV-UfrFZF5U3zADy3uMXr14_BMbto1YNlaVd92nd9uski2E43XSnm66T_PRq-fHzyx8-efZs1TZRe5AXi-ZLd46gdEOfhzgowrrrQ8yrMBjmJuXC2gjQ5Wy9V4GQ8xCTZdrbGbfdkHO21qasKedF2_eaiHndDQKqCNa5lOVi2fZ9SJRzTDt1OS48ALy4XNbjMmYhwzElZk4xIdFoWq3aTjIggCJFkWR43bRni7Uztg2xqivNsl41hbdZpQlt5aucZX40Y2VvDE_cuulRNUXp-5CysqeYNHSD5OR8mXMKoW-bDpBUoRt6MgxIQjL0vbcmp2TIGQPWmBxjH2U6LbOAI4wxh5wVNcYUQwo5EaoiRdSMmJIMIYaU-5AygiqElESEjDGGjDGGUSUrCBGllIkAgACUEKzlnPONm9eq0m_x25oTqFjrtqMUQiicB0BrjbVGNFWVlxQJqA_DdFSRIQOwDS6LRMvcrBsmcNaDomb1pRXJSiQxE3LS7CyDKqFhJlAkEUUFAgZk3t7xM4Nq3rp-wBmjCinnv63yARlzFjYGCQ2xbrsfZoNGVAybrVUaBRWAgFDTfP_g8cfvXb_-Ute3zlg0xM6AkHN2yMkY6kJ01nhnCYDRANFkPF2fL8VA5StrwBorGVOSe6-9XJfuz__4L6dVdffugxRayvlqubp2uDed-ZKpHtuXXtqvi3J5sUAlyyb2aeiH3cODsxcXB7dvzHZmo7qwDJPK56CXV8Mnx8vRrH713q079w-uH44K5WvzyXRSDX1fWoPG3Lt1cPNo_-VX7o_rYrVYffeH7zZn7ccnp-tlj9YmAW9ZUvLWguF6VE6nVWmo74f1spEgl4v1pumaTXe1bLomPHn0pObywat3Hj39VBEvNv3f-41ffvz8aWFHz0-Oj46u5aSgMJnNNEZbT18sF8cnZ0U954LuPHjp9s3r9x_ef_nlVwDc_u58d__afHfvi9_-xcXxma-q-c5ODoCGiDlnAUFAU1SjsqrKUdU3AxmNUW7fuT872Dt59qTdNDfu3dqsV_X9Q_Ru98YBc4oxAwNZvnpxWY-q2w_vFXXVrzYO6ezitBvi0bX96WzKzHVZ7M4nu_PpwcGONQ7B5gBoDKHNQqPJCBnGkzGhcbbQTEAmDHB2sd6s9E_-5rv_3Z_-5f_-X_-b_-v_5ff-h9_9o59-__uLy2XfhfnOrvTmvQ8-uvXSSxcXZ816HfpoyIZ2YGZfjxBFMypSWVciiJ7bmAmIyccUCAHZOEbRPJpPV5dXkFM9GSvkoiqu1lfOOHKuGtcpR1_42awsXLl3MJ96_ujD48rgjVt7alMMQ4oBEA52douivvfK7Zv37vjCP392nLIQGuOKKBlDOnhws_R2Z2cHnawWm-NHx-dPXpw_Oo1DayQDqi98OamLatS36qpq53Dn2sHUSfjwRx8G8n_3n3zrC2-9ZpR_-N6zezf20RgrsuPKp8-f_j__-q9-6603H16_Vju0xpwtVn_wZ-987VtvG-MASQQMamkEVf7jH_ynb__Pfp2iqiIoWQaDJqNsB7uagQx7pMcffRoxvfzy6yklAJakkEMMSuyK2htrQ0yV90OMdV2ixr1xeWN39vT06mrdb4YwxM8Su5LTFoaWc1IFYAhdJMfOWZFcFUWMMWdRzUikqMwUc3aWLJrtJNgwI2xZ1JBFDLElk0WYLTJAVARgy_IZTAiMcwAY42AMMXIWUBFizgoac1ZlZu-MZow5WkM5Z2JAgKyiCIWzviogpW997c1JWfzZ3_zUl6UAiGRCccySMiJuyTxKACq6nXuBZsmyJXqCMjKI5JS2wk0VFQQgRKIYgnGMCFv7JrFNMRpAAUxZiJm2bFMmBtIsAKiSRTIwAJBqJkQ2lGMkUmSIMRliBRAR67zk7LwVBWbMMRtrc0pEgMw7O7N1swZRZoNAhhmJoor1HkFjTgRCCIX3Xddba0CUDbM186oKKbOhKFoWTlIqioqN-Sy862yOgQ0ToAIa4iw554zAvvQIgAjMlFKsCk-GUkxFZRG37Gl1zMrK1kpOhXXGsrVGCZ0zjGgIU0pbEAQDsAFiREeQclXVGhIiIkKy-d7BnkVQ0K3NZohytVlHiTvl2LJhw-uuO7s4n47roix2xqOY0mRS9JshSr5YbzLw87PzVU4ahrfv3Sd2Pzh-vhiyKV3KGmQYVxWBscx9G6ejqpq6OCQBiLEnxcLbmHNKuXR20_Vd0xd11cUBiGNKoe9Q0nrdmXGdM6QwMAOmbJhyDNsvS4NIClEyl7XmnGOsZ9Nr1w9rx88_-mS2Ox_avirtqw_uHs6qRdcbb842bWi7W4e7zy8uXn3p5qwaf-_77906qGtfWOahj8fniyYmJFKQoW0LEAMAOWQAYIdc2pgTIKqBHAKTITSSE1mbtj0jU0ZEZkAyZakgKshlpaBgIIdEZSFZAMFOXHe1RDNuly0E3Lm5uzxdLy82blpkySqqeegHKfKoWYeDm9evVu146k6uNtP9cZOyK9y6G9BgNCjAl4u1QVqupQmRSlptmsXF4EZ-NLEhhI68oKiH9540ISR2trCmKG3fBWvMekjXdsuzVb9oBmupdu7xqjlfNG0XJGse0uywSOtBAVIf86IHgvEMwkkwhiUDQsyDaBbEbNS0i96OaldSRpSYy9q23Sb1OJ7MXvvq62fvrhfDBte8yyaR_PwvX3v27urF6Wa2Pz46nFSo625Y92lWFYTIfei7dnXRPjtvRE3bDSPDGTT1CfOgbTB9ZodsjfM2tkMfIjhDxjIRA25hyd1mAM1sjXGWnGvaZjStIKPzaNhdXS2mhztB9XS9HpfF7qz8w5-8f3d_fnN_jsQXV5shyabr0LvTywWjveyaNks9qquiXF2-IOs6TX_x7DGC3SsKvzMJ6yH0YVy5zRACQBxSjAOTiQBXfbtooqvLFNu-z5thKK211qFAFyXFnphBwRkeQhBwPSpZvli1k7pAzGLAOLPYNBgkpygA58tlgdw36fj5ZYwSVEaTyYvzy0lREpECb9a9aFbAdbM2ZbFerNd9ICBfFr6Ls8moXa7ruiSUbEdtTInIVTw2vC3Qb9bjJ7AsvL1o1iVy13bOW2ISwhhlsVzO5hMjtFn1CtEytkPyqolQRFPMKfV1WQLIfFxtmpSBRSUhdH3MTlgBBPu-26b7RXHTD8Y49JxBhhhDjIBsCEMfEZAJPbGIhCyImCNCTsRkLQogMTvakniMNeT9eL3eFDtj5wwglEWZJBlGIiMiEjJotkyasqZUF15FTV1nzZIj5jwbVynlIYQHN3ZfXGzQYrupAbVpwrrrLbuYIiJBVtjKzsAwEpCQhZSyN3aQbIgTZG9NiAkElHJhbQ-wPY4aYnLWIoDi1haBiECWERVgO_oSBTZIzJYgpyTOWcOoQJISISuAQ5rs7D8__uTWrTubzQaBKClaC5AdetDsrcmSYwhlVbM1DAAB77356ifvflSVE4tERGqQRDeLzfWXH_id-U9__JNPHz399b__6yXF-Wb8sx98eOOwvPnS3tPj6FGrSb2zNz07vhCQvd39j979qLlsDvYPmsvl7f1rm8IX3lxdLa4um03X7O5VzWb93e_9bO_G3hsPjo4Od9v1ijW_-eBwZzxuY3aGi6I2vtx03aysDiaT58_WL9r20yeLPERfOgA03mSEpk8KGkTXKJX3IUMfuwTah47Y7l3bqXxZzsd3bty_uLo8Ob6Y7M9ffvUGGO5iv2iW3hfNsN6bzJ6enSWmv_6z79rR6GSz_u473_3WW7-43LSrq9X9u3dePHt8dO2wz_mTDx8dXNv3pY-tvvq5LwTJjz58_-py5UcuNP0QUuG89-V4dzKs2q4bqkkxqqqDw_HzR49uvHRrc3k-2ju4PD4tZzsn7zzzBk9On14hzCZjdqZt17P57PjpCRuez3YOdg5v3zr83js__eiDx__-9_5IC1uO6-Wy85bR0N5sVNdj9ubadDwqoKx2fvbRs3s3r7eqJxfn3eayWW1AlB0fv7jcGY_JcBpiWfpx56pCucIUxLliPHOXzerlN99aPH50sDP70aYBkJBS4ceuNCoydMPOzRvLk4vCMDGHtrGIw2qYHo2MQU1x03bT3ekgydoi9ene66-9_5OfiMQhpq7vEGnZthZzjGF-uLO_u5s0z-b-8ZPnh_ODr779xsX5xelFYzzPDw66YTO-MT-opsbYxG5xcrlerapRVU_rPKIcKDTp6acn3cmyv2xEFa2mLhhI7IFVqSqMcoxDN6SRG4EtH7x8be_BrbMnjy-fPI19-If_9DfuPrypfRyaHg28fvPaKrQTY-7NZ4-vNi_O-__tP_2H7aoLEhMXzy_X3_nhx7_wK1_y3m9WAwLmGFBFUT_45NPd-WRa1G0fElDWDJqZHICGHDErEDkGBP6L__TX__xf_mdxSJkwpJhSB6q28GXlyHDMcVwXMQ1EiipK8tbDB5tl24UBmUWAGBWIknpvUUGjFsYoQoyJagKgFJMxNiO60mE_SBRnXDO0gIiGYhJPZBgzoAJaovzZljWKZAuGAUQSqiBCzKhBrXVJNcTEIYEha922QEdAEUgooJAVVDEmzUKCOWXd8smaVTMelavNYLxNkkWys_D0YrljrSvKFDpVsgUNXXbWQMohDuQs9cZrSgxB5G_pKJBS9p_hE0CNQRFkQsTtCMU6l2Nw3mXJRFZVDABZI2qjCiiCiioZNmqsKOh2WClaFNW6XemQaCs_U1XJll0awlbLuD3dUoKcIlkWgKRCSZ2zMUdnLKCmCK4u-9Or7fWRgorqaDTpunYY2rKqMcYEmrLs7YwW644NV2XRDwGRNjmPx2WXElByhYuJjGNiDt3ACN5bdVZVkAgBGGl3d_dHP_zx9ZvXq6Ls-5YIEQGNTSETZWMYAcu6yFkpIwHGLpSTMjFZcDkPWbJ1TlWi5sLaIBnB9G07rmtRGVJioMLZMESL6JmjpFJEUZJA4e3VYk3ISNZ5n2My1uYkSSX0oa6r-WSa4tD3wSBJJ5IzIIcQBM3h7t4Hm7ODuk4qSfnF-RWptXW53JzvTGYx6KTyaAhyDjkMG5NzNilPyyJqulqt0PucpAtJQMCocpYAoFpWfn0GGdR5xj5BSiqSt_-OogBMDplIcxYVJgNDAFRSHc-nZ09Px6V9-NqDdr2eTEbOOGLz5GrZDMNop-66kELYdNgtFznGp8-ffutL92PQ0bTodTg7X924No1nmpXQUmoHtMT08FXYbpiSoCoaViIqWSOwMWZ7-uOtEiCDZs0x21GBxDkm450oaMzArMjFtATHqY1sbd9HINO3IYmqIT-teOys5xgzIRCqik4OZqsw7N3YV0NN36vjFoQLZy2FLqC1EfLVJqYM5LkoTdeFLkQCWp6tCjbXb01Xm67yThHDEELWJnTgOCOIQggyG1dI6BhXbdcM2RUmhZA0NxI3V5uhj5KBHMqQOKtGjcvWMiFlX2LekGGTm6Bdx4AShQ32ffL7Yzt2qGZYx3rmCwK1Dke7X_21rzhJ69AdXq-umh69G43qq5O4vOzu3tnvRFFx0YZlNxSGM-bKmU0TumZQgOmNYtU0EAK0A2WxBsKiM8SYAQhSG9MwBAFyBVpbWI7tkARFRUSZbB4CEqG1OSUgLn3Z971hjFEKa3ITYwgDw9ErRzJkb6wtXV26pFJVvulTFIysA8C7zy9Ngb4eDQpnV8vEtGXZQtTDW-Nro1E_DJkpqyxW63JSDapRQA0YY9dDUEOuKtZ92GzaTiIQOWbLJsbUx9ANIYkikTMMCOu2i6gRwHtvmUnp-fGlH9ddGIYh5Swv3ToYE1VssspqvTSuXHRNZg4hSEr1ZLRYt6V3kgWJ1dnnL86j5hCTAC3WG-P4w3c-ViIynCXHrCg55IiAs9oLGA2xiUFQLy9XvnYhBSQIObOx82qEhAronFUEUBRUNphiUgJkyikTgTc2pRyjmsKu1q0AEpCoSsrEzEw555hyPwQkUxTeORdCCiH3fepCElHDpLC1JhKAxj4o6KSuiFlBCAkIATBn2T4ZEBUJvPUpBEI0iN6xN47pMzoCqKCi5CyiomItW7aAahhFRJIaY7wxzOwtxyENYSi8q-uyLvx8UpWlaYdQlcYoDcMAiNbbFAMjr4fOe08AWURBiSwCiiRAIWIDJAJoEJFUFRETiCGDBIaYiImQkRHUuUI1M7NhUs3WsEpC4i1yBAA1q7GGkFSziM6m04vLqyy5GtWEzIiuLEDJW2OIDBlQYMPOsbUmZ2XDrvBtM8ShL3xFBNYwMRmmNMR6XO0c7i2vlj_90buH144KX-5dm2-adr0arl3fL6xpN-1oVMx3Z6Ef6ombz-vV5VLisFmsc-oOj_YL70bz8d37d_d3R-NR-fEHz7131pqrs_Vm09SFO7pz1IX8_OR8NpuVpTVEm6Zbd521peScLZ0v1-988KwqPYRsCZ0z-3uTIFqOfD0ezWaTUVkWvrDbApnIuXIy22Ew125fnyP-_p_-icG8t38wPZhvVuEkdXvVxHu3P5nOJ3N15sXxC-_9Rz_65ORq_dL-9WvXjnIefv3Xf2l3NqGc5rvTdz566mz5yv2bb7z-8rj0GvJkPg8pxpSQSCWnJDmvCS0DtuvWeeN9AYDr1Wb36ODDdz_4_Ne-2q_azWrjjP-Fb33zne__-Oadm7HvC1_N9vdzlDZ00-mOK836alVP69H-3qiYvPK5-zduHE19UYyriS9m42pYNxpSu1wsTi6ePHn60fvPfvr-B1nT89Pzp08ePX966tiXvtzd2WeqKj-Z7x8owuq8nU13Tp898YbBWEUuar9aNJjlpXu3Zzv7_-EP__J_8Y_-7nf_6vuOeRj6PEiOKcU8bPrRuKpmkzj009l0yMEZBgCyRkVXV1dlWQxtQ4DWV8urK8NIBh1aUzjnyrooCutvHO2bGEMzdE2fBW7sz5uhv7pcmMLVRT2pi51RNRuP9sYTWxpUGLp-fbU4PT3vkzRNtz5pN5crieHuwxvSt2XtysoCokgyohpUYtIUTAwjyF_54qto7VtfvHvz1u7p-x9_8N6HX_vG13_xl76xtz-N7UAAo9oX3v3udz64NtOvPrz5dLX56_ef_eavvHV51fUhItnT1eqnHz7_8pdfG5VuswndEKxliakomAn-_R_80bd_8-8YYxXJEDvL1joF8c6gAhAyw3Qy_f3f-5--8I2vVMUIFEOWNAyaEwgVla9Kn1VTzpUvckyoUFc2puHrb9w_OV9drtsh5RByihlAJUtW2drkDQMiiOq2viBCNoqGUFHidjqgDjnFbAzHlEvnYkpZRAEcU8pCziBiFrFstyC17TgBmRQEiTJkY1mzGG8lJSQCAWIkREZkQlRRAgU1jg3bGAdjTQqZkOpRnXMyzIAYuuBLG1UPpvPbNw8--vippIxshyEwkXHmb4kG4pkUVRWSClsmMhLEOZdSQqLaV30IkBVI2RgRVVHDhhRSzoiQc3bWEyKoqlLO0TCpQmnLfugQJUomBNFseBuBBQRlMjlGZCAkJiSDgEhKMYlzDlCZaXswXJaGDLF1qloWTsns7E-aZeMrR4xEbCxPxqMUc4iJPTvjAAFERvNpjAGAkI2IOGuRSLJYbxCZySChdVZzRgA2DKhlVW-RoGyM944Yzp-eH928nlN01rMzIUYULUoPKmVRiMio9KIZBbIIM4uCt2UMnfeWiBQBVQ-msyEMZVGlEEpfJM1VUeUcC-8K55HAWmtYq7KYT-r9esICSESIMWtGTKBZ4tQUnq0CXmxW7MysqjLCpBwNoU8pFd5v2bGXm81oPG6axcOdg7IYPV9tfvTkuIvZVf7iYrUzGvXDEGKaz0fLTQ8CQMCIsRu8t5OyarvBGK4L1w4pC1jibgjOcMm-H3pjbbNqVKWuqpQSIcbYW2sgBIwRVZBQs0oWU5cq4pzHLNfuXr82m5cF3rx17Qff_f7RtcPr1_aTpB_-9KOrxbocV08-fLZZbLbfpK-8fPfk6url69cvLtd1XZxdLg9vzocE66YbUmyb9ua1-V5VMd55FURzEhAkppwjArPh3GckVAFik2OQILEfiB04q6pCSMakmJAJEKiwflaGNjAZ9KRkxKItCzQoisWkihnKWdlcNTkFBlUF9sB1gd4XdRVjrnZGF1dLVGbH3pkgih5WXUwZRYActe2QhoQqkJKE_ODW7PjJ0hMDQt9GYzCGPmTJpMx26PPOTpViTkNOAjFpnyKmNKpps-xPny4lRcAMzA4AWvHOgc2yShWrtdgtEiFBToA6LBtXF1RzEFIxozsH_WWrTNV0XDiHWa7dvXH_jQeqetlsWoVVG19ctWVdssUM6XB_jEiGsWlb4zkPUfphtezOV-t1G3uUAeLikyXHgBKGxRp6aU8adGTHFZCKqhoi4wAJvXGjIjQt-yKkoRzX66YtaksG0SASkzGa83brN53Um7axxmRVZpyMyldvHGwWQ1UWfdKjWX21bsBwn7MCMNOtnbJJaTIbLbpusdwo85DiUVXzkDuBpgmTyeST042xlh2Tses-OKF1DCHmi6a_drTbxtwOYd0PSfKm663zbPlgd951gZxZha6NfU6oRGRQwCyHMNsZL7uBFa6a3hpbu2oVBgBUoAcv3Tx7sbq2N06iTdtnw64e9TEoqi9dE1MiBNLQxfVqkwkG0dWmWa7Xith3w2q5qEfVerMZQhj6GGL0lU8p70zG08l0XPiLxbqL8fxqM-TUrlo2PsYURELMy80mpW2qVr0xgJwl9ynOxqN2yFkgqyJSjimm6J1fLFdHB_uLdSNZytLFkGOMQ9humyGrIJNkDSEBQso5RBFVVRHRrNoPARTJISKRcaLZMoogIBATIsaYmDRlyTkb60QBUXLOlNLu7tgyqypkcc4AQRoib-FIgKWzuBV7AYqqxETMVV2IqmTxzlhnt5vn5-dXy1ULDkPEIaQQsyGKAjkLMYMIM4aUnHVRsiqwIY8uUwQgBUSE0rohJu8tKCDo1iPBgMSICFuNOCOnlJxjBJTtPSsRAEgS4m1ygEFFJQOIKwpERoDdw8Pnzx77qq6rwhgDiJV1aIgINWdjkQgla106YEMIDFDPR4uLS0AtypJAGdAVnomQ2Bhz6-X7i3b57g_fPT6_eu3Nl6f1eN116-V6XBQxwXK10pxHozoN7XQ2ns5GQFqPivHu5MN3PpzvTQ8PdwqIO1W9Mx1_9fOvEfHxyblySpJOLlY__uSxdSUZv1m3QxQlWzjuhwAokvNiE2m3_OAHj37hy2_ulU4RJtZdn_rPvf5KQr22N0cABxTDMISkqqNxbQxxVB5y7avFyeWPPnx_f3--XLdf-upXZ7v72jc_fufdP__LP__pOx-36_Vyud5s1rvTnWxpur87BL116-aPf_z-0Y2d_Z0JR5lOx-t1PNjbdWX1-KMP63r8v_s__ldvPPim9VzuTFdXV7YoUkwbXRg7M6xAKCKjyWy2t3t2flGN6ul8duv23VdfffPD9z7sU5qMR4x49uIU2fii6HOY7d9quk1KYIyOxkXt3YuTcwWZFNV0Nv4HX__mOnbXj65N5pOrVb9zsLuzt79soVk01joyvhhNbz14_ZWHr46q8vDomkZg75ZN6PvOFwatf_LpWR_XFvHitL39xluQo0Dy1g-bbnr3sPJjsupG7q033zi6c_Pw4PDL33yrLrwM6dWXX9o52G-X3d7h_umLS1t4ZtN3PTujglnSZGfWrFZAmnKSlDbrJm2Ws8Pr-7euD12PADvj-tNnz8ejarlurh3u7R_t1GytcyUZGlksjGHTNd1m0714_uLpx08vXlxcvri8uLhKgiEmNDbnwVgEghS16ZrNplteNaEfMuLB4ezhm_ffuH_r29_44iv3b3_-i2_evnN7Pp31MPzuf_8XO3uzf_Y7_-Durf2mbZvNxntHzKhwtRieHp_8zj_72g9_8vzf_cXH__TX3z59ehJDEF8cX1199Pjs537uLZtzH7VrgysYWZ0gE11cXD56dPz2134-xRwRk0RDyAACmkFFQRVLX1xerI-Pn37-rS-mnNUYkAykQx8d-LrwVWWFUEG9MTlmawgZZpbvHOy_--i4DWm5GTKBJgWBlBMBEmOIGQGEQDIgqDVGcqas22Y-xmjZpJwIgA2rKjJaw0yoSMSGiIE4iwBgFtnu-QBQdVvsIQooiqiiKrJRUQVJANurGFUFJt7GLImI0bFFla2dAAmyKBsiorS1cIlKkMv1-nTx6O994xf6GB4fnxrDSkqolosYVTWm2ANQRgUAYwwzExOoIpGxHIbI1mTJSJBjNo5BkdhASqV3MYsxnJMQsoBYaxBpSwJNWYEAiVQUELJkQt7mrYy1KSXjtyksAgBiImNgK10HTDlYZ0FVEYrSMigpkvUxxLLyzjnLJgwJEBHRGC4K5ywpQJYITAbIOIOgqGQsIqK1VBQOUAwxEpZliUR1XVg2kpNlVhXvHRJ56wjREDrrGBFUjPV7BzPZ6opDNNYSIZFaa0OMdV2nkFSUmAEhp1xUJbJCFmsMWaMA1nJKmRCHbvCFU82CaIzdGohBlQkRwRIVRXFtd7Jb145MlCCKbReSQBeDYTqc7aiIoLYhdMOwO5-tm04wrpt2PKoBFQgz0QcvjvfnOx-8ePb569cHoY_OLgaiQdAYXjbNnWs7bTfkLG0Xs-Rls-HCAUA_xOu7803TKkgQ9c7nmEm079t-SALcdz2oAnIKgQHDpi-KKkrK_YBD5iyUIPXZuEKjIGEYOsiw_dNu3r2zM52BSNus9w52y9KPSt-28a--97OvvvU6dsO77z-6XK7EGqU0Odq5s7N3_8bhj9_7aBCRNtajUZBcFFVW-cKbD_vFen4wY7j9MiARfybUYKZt6aMArixTTABChkXAFB6J2LicswCCqCZBZk3K1kIGUcwgpq6HmNzRXFbNECURUWm7LgiIDL3JELo-xuRGo8WqG-_NfV0OWWiCF0-X5bji0qUQipKXbbg673IE4YyaUicQwRAMq2G-Xw3N0DfR1Ia9iVFHI3r-eJHRBKOS2aGdj0zTpKpEQblYtuTYj2GQuLzqABUhC2RoBZkNmaqQ7tm5xtht-hgCIILJKYc8SDkbEUEfwJa2KF247GztfOUBNcdcjib33r4_xHR6tcGCmpBOLpobt-aFN3VhwaC3fL7YtClIpstFG4awuGo-Ob0CAFNgjH1_uoYwQJKtCF0tIiMXRgjQM3qDyJoz1wUSxyCaVTNM9neVMiaxkCGRrKGcVZapHo9D09ZVkWImYlsWjg17Hzb5ark5ONjB2heOU9ur4TakHnQzxHUIP326YGvO182qG3xdXiybRdd-vLg8vHkzAMtYX1ytl03bDsF6RjB9kjaEnGMTxBc-5KREIeWQ88VmnVJ2VWGMmRrTp7zsNjsH-103FOxC1DbENuWQ0tlikwWGLCeLTVX5QZUAM6rmFNquLMvTtt-Z1ou2b0NMjAkAFJ6cXO2O6kdPTpohLZsOBAKTL_zl-aoejc4vL5lMs2mddb4oHJskakeFZYIsR9cOUsxDVAXNICHFDCQqKYacNKumnCRLBmVila3YPA8xLDe9qA4hAiIS9U1DSNY6b4xzpg-JEK23xpBmBSQglKwxZTJGJRs2yERATTsgYRDxpe1jRkYViZIFRA2lnNtuSBmBQBGYKYZESIAwhFj4ErbRKzTW6dHu3DPx9sRI1GzTAsyMlFWqukAByTltI2OgWdUZZmZjCBCctYY5pLTuhpzyYtOuV0PMsOnjph3YsmHOmkU1hWCJMgAgAqAxJmtyVGRJQBhj8s4miUg25UwITEZVNWdjbM6ZmLYRIwTcApgR0THFlBlRFCwTMHjrYkjWWTaGrcHtWSyCZjk4uvH8k0f7h4coatmACBuLRgEIAVmBjBtCX5beGAugBsmUZnG58EXlvbfWEoPxZkvD0Sh37t4B0pPHpz_-wU-u3di_sX8gGlRhNquZ3NANVeksu67ty5E3hhG0WW0OjvaHTXPx7Gw2LSfTqWUCA7evH7z55ksv3di_PF9dXDbX9nZOz5ebTUwpPTs5_f57T55frYaURVI9LrqsL47Pnn56fu9LryFpUdnvPX3_R08bSKlZN926Wy0WEIUJy9q__fCVNoeL09Oj_b39gz3D_ON3f1gAj-bzpx89_dLXf35SuEk5vrO3S6erv_tbv_mdv_reW29-fjweK-PjZ1daF6vFJYE0y8sbRzc-fvddSHJyefXJ06v1YvU__u7vr1dXRVn8V__5f314dLi7v_-d7_xpNZpuFgvJyfm9y7PVaOpAISZBLuvJZLlYJoBxMX7t1deOn704fXFcTqrl1cV4Uk-msydPn40m44RcjEasZnl6sr-3v1msm6ZdN83Zp89s7Z2lx8vz0ch_8uTZ8YvTpDI4vGw3V8dnBGoL6oeo1vZNawuNEp4_PYESyPmnH78Yjat6VMUUT15czfaq8c4u2sJUxhp1bNcXl37k14vu5oN78_Hk_Gpx-9atuvBlVVVFubs7H4_qp8enA-jFs_Nbr928OLlMAhql73tE0qzOcNtsVGBkXTGZ9E1nnC2nu6qpX21QMYkqYFFO-qGbzPf6tl0t-uD4qlt-_P6nTz9-0l2sLx6fLK-W58en_WbtAPs-xb7XJGkYYIhx3XSLVe7abrXOsZ8e7f3mt9_-p9_-xm__yts_98VXvvbWq6_euXHn9o2MgL66f3T09OriP_7hn6-W_bf-zje-_vYXHMl6tRmGvA0CGWQQWoXhF96489_97p_96PGL__yffevFp8eKUNbTjx4_Wi3DV770BRmGbsiCbJmMwZySZTKo__5P_-xzb76xN58PMVrjskRGQgAE2X6u2GBVjf7f__bf_vJvfnt7z55TzlmGISTJrix8QcCYMrrPRgxirBlS_ytf-dysKN99_KxNMSr3Q5AkCECglpkVLLJBRkJSEswCCkSgiswhRDQsOQPAEHNdVH2MnjiE6KzbeuUFABCcc6pCBKBKhCJbZS4TIyExm5wTWwZAy0zGDDGwJSYkJgI0jDlDzFlFHTsiRIAQc86JEUIfjTVdH3xZSBZiPrh27fzx5cnl1Te_-fbZyfH5xcZ5JuViVIlmgGwU3bYuBoohe895EGJMIsjMhraRWWRiwyjA1sUwkEE0BoliSGyYDRNRipGsURAmBNjuR5gBtw0SE6uqgBpjUNEwbd1nxhpmEFE0RnM2dvvT0FmjiJjQGKpHtebkS89EzFRWJQKQZTKWFCzh1urIFhEImInYOeudK6xBAGMYAVjJW0Y23lvDVDrrjGGCwnsmdN46aw1hPapRxBgiQOP9fH-6WjRF4VC2oTA1hoq6IGRrrWG01iio9RYUSMBam3OsnC_LIolYNs6S8z5LIm9SSoAECETIgJaNguQkhslb57ydjP3BdKxZYsxJRESFsK6r9WZ9OJlKhpTzi8USGG9f2z9frHIUW1oSAAAkGrImQkY6bhYPDo9iwo8v11fDYNgC49PF4ouv3n386HQrwXC1NZWLMakoiFg2DGCYlk07AHYxlMyI0MWeDF9drMu6il0a2o2EgYiGMGBhYtvnprWGQRQda0iICoDGOQAlkLIqdu7e0D6WzrGB0pnJaNwNg68r0fjqw5d-9N4Hj568KOqRGxWz-eSLX39zPMhsMru4XO_OJ_Pp6Omnx-Pd_Ren5_XI33l4Ixyvvnz3Gpt7r0gSMrTtjwlgG_kFZgWxxJAFt5u7lNlbMtaPanQGiWzhyFkAKXYmKQSyJvShrOrcD3m1RmPEGUADmIpJoUr9skFSFfQ7ddcP9bSmSYnGgIGLFwsSnVyvxedhI13IbZ9FlC3VY2wuYmqTpYwiBvHafvHsw8V4VnNBoYv1dXP8wRlkxMJMKhdb2dkpUp9OzvvJmFabmJOEHDnI5qJXzCnE3AQgIEck2ZfQvLiEpkdU8sSklFUlSaeOmbKqiq-8IQRgBWCVOy8drlbd4as3733-5snjdUxRR-78ollctXfv7d7ft8tlPL3qielq0-es0YTNemgXPYB2616japvii271aNFfNRYBCSCgL2i4GmpL0_26veiMIemyiQJgslBRFVCZnBRZMaka_cV_8e1hY776j782350c3D4odiabyzUSKkA1GR_cuWFJrKpadFWJhtEQV85asz8tMwCOistN4wo7qCKJAG7CgIWPKS3XfdeFyyEUJCkM7Xr4yaNjiGGx3jQ5B5CY85ByXfn314v5uApJMwI7t2i7ELOry6g5xnRtPE8xgjHHV5d9TCEKkFEEZdj03QDQdmEIacgJAFQpqazX7fWbN9r1qqir5XLVpRQRLzatsOHS9l1atN3HT8_2dqbLdRezJE-rzdAsB08SVYXIOCKQdhiKctR0XV1VKQyM5JGvXzvYbAIZUFSj2LapHwZGYEVFSiQx5xRFNJdlkSWXzrotIlrBGATF9aYZut5Y0w1BmZIkEazLIqU4tGHkXdsHyTLEBKoigkCSMzAxc0qJDW02LRiy1g8hK2DOOWfZok4cGQToh4CIfdeHkA1TXZY5JWMNW9O2nWGKORmEw9nIsAkhEKOqxiCqioAgQITOmCGknNKoKmHrwlQd-aLtg4goUBdS0tT1McXExjhfZpWkmlMcYvLGqEgCTSkyYRQlZlEprZOUkUzKvbVGRdiRgnhbi6bCWRW1RAJgDSOANTanbIgB_nYzIODRAikAsiXYtuOqBIYYLKIAgoghRGZQ8cZJTDcf3P6bP__O7TsvMSZABFBHxllDBIaMSLbegFDh2aBBA-NxuVxuhqEbj0eGGIEIwBCxMaAQhjCq59ce3jj-5PkH739SjOx0sj_fnTkL43EVs67btq5qywZV5pPJbDbz1k_GsxhSUZbPnh1_8ujx0fWj8ag2JBqSKty-ceOlW0dXm-7H7x0D5dPLTTGudg92VCRGFeKPnp49eXr5g_c-ePHhydVicfz0OEYpBo5pszOu69oXpZ1ORtN65IvSF86xjf1Q1-OYYbqzs16H_8-_-x9vzvYuL1dXi2ZnMnbWleO6XSxu379_997Bqw_v_t7_8AeT0RiNXS03r7z-cKe0X3jlHqL--K_-6rf_3q_Zovh__e4fbLputj_90lde_tM_--Qf_IOfm-_ND_emlPTDR09Pnj5htrFtUPNsNpIYldFb76pR06wBcFxXL14c_-av_vp7H7z37MnzvYMDyRBjLquRqipjVY7arj3cu7G4vExxUBIVYs37hzuz2cQ4GkKaT6ePnzwbuqFt-_Hhftr0_eWqtOSsiznbwpjKdqv1atOR5FsPj97_0fsppFffekiQz1-cVY6rwhrjx5PJZFzkFM5Pz7y3MecY5OU33ygIz65WH_z0Z2-89sp4VDNxUbim607Oztvlphni66_cf_zoVFm3UFpUNaTGmOm4-hf_8n_16KMnbbeKIc3nu8NmMxpPZ9Px7Vdfrkb1dD5nzZenzy-Oj5vLC4uYrzY1WyHdGU3uPXzpq2-_eXy1-fJrD8v5rmPrvf-Fb3ztwf1bX__qF95-8-Gv_crP_a__xT_-R7_1S3__73zz7_3y27_whdcPd-beF1Ek9UnQrNfh-HxxsDub7s1-8M77_-Gv3v-Vb7_9zS-_dv1oT5NcXq6CABkihmJra0Kqx-Uq03_7R3_xX__Lf_L442NveL47_-733lluhp__8hf7pkkxb6dcMQchSCEW1gPQf_qj7_zGb_16PyQ0jpmtI1RyzDFmUWTGwheffvqkW7evv_5qGFKAnCWVbFJQZkuIo0mZAUQyAgABgVqLifLf-dLnJMG7z180fQxDGmKKMSMgI4HC9sQFSUXFGIwJRDFnJEJFzElAlIgVpA-ZDeWcAEERLVOS_FkCWAEUkREUt6jQJBkQs-j2DbXWbPuYFHNdFLKd_CdxxoGiCBTGZlE1vPUSG0MokEERlADYGCTom8FYUiRBgyhZzOrqqm-Wf_9Xv_bpxXHOSswC4As3ZAHEnBXYuKpUEWstGZaUjbUx57IoUEQVCIwxZI0NMSEzKBAgEpitWRHBeZ-3l1EKkgWJsiiiEsDWvJsBkCnEhATGsBIoqQpaYxFRRNjzFhyHTCpKiIZYVLeYBu89MYnqZDw2hlVk6KN3du9gxkj9prHGEWKW7OsCCTGDtW48LjQLGyqsJaLppM4iKFJ4DyK-KJxlX3gkNMbEmK3loi4kZMMGEbz3KEpIxBT6YRtuZuZ6VIqqYQohTctSASSpaK6rAhA059qXiMiGjMGqKkLMoIqAkjMRIQARjstKAWLs2Thn2Vi2Bq_v7UxKn2PypQMCBFx3HTMi6cFoIqKiOoRkjTXIQ44AEFPcGY2HmBmoyzkTsnLM-c5sNwv_9MVxk4fCF6V1x1erl2_tLzbdeOS6LpChrg_OWZU8GY8B8u6oAMKzZkPMqU-ccX9cvFg1Q5-cJUXDJDmkrm2ZebMZ7KiUFIxkVFXJW88rqIIqguQs1pmY8v0vvo5tHI18u1jcODpAoqqsykn1-NGz3en8o8cnl5eXZKwAOKan733y1c-9OqlGz0-OZ-N6fz5ph9Tl4eJ8LRpv1aP712Z7-1M2L72So5DBTEDAjFsal2VfESDHRBlFgZnZFWiLtknFfMTOpyH-rWiaYjO40TiEaIxFBBmSIVJFdJz7SM6itzEEzGFoO1MXyNj2LXhX7e81zeAMrpedZKxvFIuTBoB7zJJRJaHR9rzTIYGIBSA2FvTy2cIVJiHnLmsMq5NWQ1JjMqLzqEIWtVkPpqCeUgwpKwLGPASFFLshbwZgJCLpo7aR4xCWnQLyzi1ZLrQVAEFREEFQwGyMHdosSqPdKbF543MPnzx6Ue3sTHZ3lhedElBpLi7WZeGLkd-blc9OuyFCz9IMcbNq-zZuzof15QYFmKQPgZWzJiTRJL5gKhIL-zJ1ywYTAWhzEWSQbtW5wqu1PC7s0T6omlHRh8zO2bJ48OWH1-bz_esHYd1Pd2dDCtW0GBbr1dV6NBm5sW9OF86a2c3DjBmY-34IQx9F9vZmZV0m1VWIL5ZLV9pAaAr_fLFODB3IJkRJqkx92PiycHVxsW77rr1xa3a1atuYk0U0XO8UUpBTGhV22UVvTWYAb9p-qMZFHyMx9d0Q-tiKrIZ-3QyXixWRQcQMeNW0ZO2qGfrYTubzzbqVrBmgaQeVOJ9O1ov1eDbqsyjCAJKd3Ru5R2dXde2XKbSao0ATU_YGQIeu6ZqwahMYN54VYch9I4xqM4WmqaqiHo0mZWkIuiE2m5aIFsu1qYuhGUS17QMzZ9GzqwWRqgAQDTFIVgA1lhVgvW4UUQSqosgxFmW1xeAyEoqEIdaFb7p2q1lE1SyQsiAqExfexCE1oVeiJJC2g3kVBxhzTjnnrKim6bqYojN2C8aOMZXei6qvmEhTElVgZjJ8_fqOM6RJBVSzqiozJREm6ofEjDFute1OVEVBsiLR1iCDSFkUEGNMfR-6LiBSNyS0DIAxRcsck-Sct6iNnHLhrYhsTcZsCAFFBMGgghFUBdHk2G9HU2wYBCRnUalsiQwqao1VAGstKTARGyYmJIoxMwEBW2MIVVWJEQlBABE_GwgRphiv37r1_T__i5defkVzZDZMwGwQAUAVUeNnkyXnnGVOouPJ-OTFRVXXpfOEYK1DAhJwJWsUtkgAR6_cXF0uTk-unjw7ff_dj3Z35qPJdFwXMenl5coaevz80iASm9l8AoRVWZdlefP2LUf8-OnTZ09eAOlkPCZjEogv_Ww6fvsbr1yb7T759Nli0z17erxcbjbNMJ9Px5PJuu0XV83yaj2dzmPfZmBr4eGN63duX5-Oqt2daeEKkdw0TRzCs7PLmKQsqp2dg5zN9378k48-eOSKkSmrjz5998N3P_re9_7mP373B4uThfVVUdHVMv7s3Y9uXT98_Omz3_vjnzy8M9NB_uAP__jh3Tv_4B9-a1JWpxeLf_1___2jo52oiin9s9_5dml4PBk9ffzs-fHJzaOX_vyv_pIzxtB674qi0hy3pBJB8q7s-zCbzheLizt3brb95vFHT11p-q7fu3Z0fnbabDZseVSPReJmvSqrwpE5Otx9_uzZtaP98-X63p2jvelYBNeL5Wrdhm4AlfXJVWoHj1vSnwgCsJTOD30aLpcuh4vnZynB7rWZZzz-6JiLMjbD5enp7rW9GKQPqV-t92_fXC9XhqDv1nu7O6PReFS7Dz9-sre3SwjElFU362G5uOrb2LZd9qZtB1N6RpbYl1XNTE3bvf65Vx-8eufVh69t1uuL05Ou3Qz9kFNcL1cXz56uLk6OP_4w9svdvcPD_R3vi8LY17_5lds3r5cG7995Ocvw6uuv3tyZ37txfXm5ikO3Mym_-gtfvXa4c_1ob3d_px6XXRhCSlmUkCJZdnYQTEkQCK09X63u3z4YQvzuj97_4MXqN3_xjZeO9kRYUu7DAKDIZJHGVWG9Y0BjcDKf_eBHH_z8z7-eVh0YLnzxvR-9k4B_7iuf69t23XVsPTAYZsOABIYdA3z88Sdo6f7DB4tlA2QMgcg2VZYZmKyxqN66P_ij__j3_8lvry4XWUkVQxgQIW0h_SRVVcWYYEuMRVBQ7y2jvnX32vnF5sefPG1j7mJCw6DbMxMFQGAS1ZgSIjIZ2TqrNCNp6gMRqubPJhkEpLh9fgKRqjjnU4rMTIhIQEQAgMiiiZBBIX-GxNkmjynGmFWZCJlTTqDKIITbGbRue4kUY8rZEilCDglUkSCGZI3JojEKWo0hKfPQ9cr67PmLP_lPP_4v__nfI9TjpxfjsSU1Wxx_4U3OwghoKOXkTJGTICgxa4oMCABJREFK79LfspuR1LsyayailLOxLDmTMYiIBGyMcawKzllV6ZL62m8v-1HBEOWUCY23RvP2ZnsbcTCoIDl7X1gmULDOOmes2caKrDFmPC69c30zVHVprS2dicMASMQEKlvytDW2qsvCOUlhZz7OWRGgqApA9YbKwvnCMRCgGmMIZDIZ55RKZwvvnDFE6h2pitlKga0lUskaUhpPxqOyVAACzJLrwiuoMaxZnDWGGVFKZy3zer0ZT2pnjbMcQkKRrbiMmKw1pTOk25cSCcAaawmYdX9al5a7oR-Nyj6EpPnF2Xk1Ki-b9bXJVLMCYtRsjUFjF6s1W4wxTeoKEJl42a6BKCV5fnl1a7572XY_fXoWQafjURxiE7OzZr1qokpKqW87dj6Evlu3xjEj7lQVMTchtCF0y-6l_b2UwwB0cX5lEIZN750LQ-ja1lqTw0BACqgpxnbgwooKZEEAyJ_VosYyIj18_aX2bMUgR_t7d-9ce-_dT8vSaskfvffIY_HJ8RNQFeeKST0qy9XF5VtvvO6I1-vWOUvMTdfHRKumvVyvXr19a1baaVUz3LqvggoIhFwZGRIisvdJAyNAn6qdiVgTRX1ZZoBiWpGqAoYh5hSQuZqOFJEIcxZkjiECkaomVPSYVN3UZQtx1RlNxkBSNN4MfV8e7OCkbBetgjRNV4x8CppSzEopZ-l76CMlzHFARMzJWTQMmxerHKIZl2BMDEE1D-0ASdVAzFmUPWIeUtMEFOxikpxDF4ClX3TFBPqLBlIGVQWBJBByDAkTaM4SzlElYwZEFtKuRVAVLKpSApRVyWzn02nfxOdPN3c_fwsMD6lPiI8eXVQTY0tzUNHV2cYUbhVTcrheD5B1sWhBYsp6tIOLiyEPOYuYEiFlNWoQUYBj358MsUkAMWeNmpTAj6x4qvenbKyEbLJuoZciaovRN7_9lQIryXk2Lrpls7szyT3IADdvHfRdRABfmNDHOIRqXEtOAliPqvF0NJqMetEAOGgeRCLROsZx5VqEdQoBcdF0QCxExLZpO6nKddeVlk-eXe3O6pxiWTpnGNCFoH1MQdNl2w-QmjCUzhDxuuuaoffGkeDdarRSeHpxCYY2XacChXeasel6sCaFkJKeL9e2QCltCN1qsditRoeHu5KDL-1V3yxCEOJ1Si-u-rZP48lk2fc5CRvTDUPs4mLZNJsOidjSi-dnk1GFSC_dvfbSKzemvvBFuXswBWXH3Az9RXNl0MQU2z6pAoEow-W6XTc9IYgKMSNgVkWEUelQIIsW3sScV-vWe98PrQKKZDYGEVUBiVJKCtIOCRRDP2QFYLoK7cgV3rlm05GxF5crY4x1hi0PMaQcmyF4XzYxqkCIQxqCI85Zuj6wZcDkmJxzsQlIZC3ztgRX3h-XjqzCtsFABVSFbeKJCBRxm3hTJWcMbf3pgLJtV5i3GvnNpkPiKNj1oe1DiClGkawSxRiTIG95UyKIsu0yYPvRFpWtpt4ZtkwxCRJKysZZRMw5e2dBBYk-C-chIikxoiix2QrtUSlpcsYSIjOmHAyTYSuiqGicAdhKR7bli2GhyfXdH3z3L--98iqkAArGMCPFLMjIwEBgAJjIWcNIjOhqv7haFkXpvZecEbbNEPJnpwLAGac39rOamy_fKq389AfvLlbttWs39namZeEl6bWj_aZpT47PxqOpMVxUlpkkp-l8vre7d3D96NNHzz5--vx8sZztTMZ1VTEZgXFRvXT_7o3d_aoslsu2qMuTk8VPfvzeaG_cruXDn34ymYyqWfHKw8O6LvYORsYVZJ2AdMPASKPJuChG850dNxrFzCvp_tW_-m_e_9k7V-t2sTi9vLhYbpb3X3r5K1__-iv3bn3l61_56JOPf_lXf-HPvvMDsvbmrVuXV-tv_8bbdWHX6_XV5cWv_vIvXJtP0Jrn54vjJ5_OdkZgy9_5X_72wWjKAjlD6IbT8_W9-_f--E--E0KLyM4YAGViibmoR4JofZFCX42Mt84b12yWbdslUVENKY6n46bpjh5c77uu73vNaXe2_-DVz1-cPNk9nN-7f-vRR08Ucwa8XK0liyI_f_5cVYy3zlIWRSJ1ru-GIHC5WJ19-vzqcuW8HY3qkGX_xuHutb2zZ8_Gu3vLZnPVNPdefZCxfHF-Oav8ZDRtl0tjObRtt25vvHRLNA0hvvfO-688uJeSZM0ppmbdnTx7QYXfJj5FM6S01dizQW_Yen-0t__T9z_-whff_Ks__3NLrKD7-zuk_KWvf3l_d--1z70Ru-H-g5fvP3zp2ZPnbHh9ebW5XJ3F9o3Pv_7nf_H9n3_rLc3A1pwMqw8fPd45uHa1TtO93cloBKQWCJFFdBPCckiXTXe8aEqmSV2fX1389JOn12bTi8XmBz97fOvG_ut3r-_PRyq4utpkkJBzGwOoTMdVZV1ljQG01mIXnx4f75aj3flkyPiz9z8U4p9_67W-aRfrhown_mxQCgp5SN4YZvqDP_7D3_yt30bBoMl445loe9_3WeyHiqr-kz_948-_8YXC8qDaR7UGc4oADIjsSAHHYx-iOMcxZmOtc6Yo8Gg2vre_--RsuU5x2YamHQBRRPsYs-r2lj2LICjSNhfBAJBR0pCssSFE46wChCCqyoa2Z4OIlJOoZmesgCIAG5OyMLHmjMSMJiPkFJ1xOScBNc5r1jAMbKw1Nkke-p7JKGEIMamIigLmlCUncialhASEqFkkwzYXu72MyDFD1hwjAMSo9dj96Xd__Ju_9LWff-ved370wbyqooovTUyiApawGlchCDMpYgy5qEpAZQQiVBQgzALGMBIhkTU2pqEu6iTZGIsgbEwMgZlwe--_ndxsb7SZUBEUgZABjWVRMMzWO1DwtrTWgGTDTPRZ9spYQ8a4wo2qmhAQsSh8jDKqqxBjymKdY6IYQgiBmIzl8WSsIr7wzrElo5qrshTJO5NpZpUsZeEYyVry1njvmGBSVcTIAArqLYOCIRpXHhhRCFCNtZDVsQWR8aiM_TCpfeijxFQ6ttZmyZNprSCG0FjjnPHeL5aL3Z0dw8SAQ4g5Z-ussQSIhJRi8s6xs03fldYRYVXVCuF8ePGFlx5YwqZZj8bjy6t1VokqZVUxwl45hgyisOkH60zTDwIKhIoyKyvDbA2_WK8z4boLfewPJ7sXbXjWrVZN88q1_b_40Y9v3TxAMZerhXNGiMmaduiVoXAu9oHY3J5O-yFtcgopeTSeTR7kqhnOTs9ndT10KcdUVqUirc4vy1HFihkypCwxW-vi0Mc2Wu8g59T3iIwo7Wpz--UHy4vVjcO9u7cOTp6f5KQ3bx02Mfz0B-98-Qufb7rh7GqR2RCCLyvn4s50Oh9Nzi5WTTscHkzP130fdNk0ZWXv3bgOsd-bjbh48KoAahZEMlEJMccIxAwkqoA42h-HkFRUJRLzeD7vlpuois6W0zECT25PNenqbOE8S45gqWvaoq66LrJ1aBkSYmnysjOsQ8y29DFEW1biPRWUQ4xhUIPFrm2uWmNNStmA6qDTu76_2OigksEZizlLiLnvskGYe-mjphTbgDkjYyJhQ5B5NHYiOfUZq23shfIQVcSwhkWnQwAR6DMUhjhryCBBs0IbgBmVFUkHNJIgZc1Q3D2ARd81abq3MxpVNx9cf_cnj19_-y6VZujietV2MdZTB2Q3q0GM66Os-xxTWHd9v9ykEDhhjrHyenXRSc6IoCnnNkLMRU3YhPWTC10HkJxCQtCQFGvjiCf74_50oIiQKKz61A9ZExQFjsrf-J9_HVZaQ7683MxqXzlTWCdIZVWWlavmxWg6aVdt4cvQdyEkIOPGBWZ4fH55-_ZuFgxDerZY-6o43TTk7NUQu5TV-ecXy7bLVNqoOYdkiXd8dXpyabxLJneDjH0BgxzNp5F16ty8LoMoiJDik-N1YQAFgOh8uTRkWInYGuBVCp3mmLSN-XB3R2IMMTVdUkbIKkMy7DarTUqSInz-73yFLpqTi9XBfunGxfPTZSZdtvH8aoXetaKKlHLqQoasse9ikDiEq01TulIgaRAC66sqdkNZurL0QTTE7Av7_Nm5c4VxBpCuVmvJ4o3JAMQ0hFCXo2EIzOxLLymxIhkux_UwhKYfokAC6frOWptSkiT9phtNJpA1xphiLqxJkoAACLc39xNfMmFWUZWuD0VZMCISZ8nWmb6PXYwpytCFGEOMYpizSBeSAqSUGKj0npkQYTYpQ5DYx6Rpbz4eewOqWSXGxGzCkHUb4wFEAmc4xgwAW3hvBlAAY8gQqWpIuWm7JOqcX6y7mFNWUERAZcCURVIGpknpU0iIJDEDY85CZvtMAARAVSaKkpzxgqAZ0NFnMy0ARpNz2soDDROAqv7tsH57CIssko21245CFbwzkhUNkjEEgATWG0nbE1gCESIqXVGMqicff3D3pZfj0ImqsxYLiygqoFlSSgRonDdExMaXdnV5RcY4tsYQEBpmQDGWCBGJRKR0PvQDiNy4fnTjzr3jZ89-8sOflZXd35lryjHnUVGPpnWIw-L8siiKwjtnrTGUFUTk8OBgMh4xm2dPL_7me-8mjd46ASaCauT3dg-u3Tq8vrcjCpeffPhv_8N7M0ebi_WD114Ca54-u3jy4uzd4yfK7mrdzubz3YPd2c7UWc_Gdn2-XGyWy_X_4__23z7_5PnZSTMs19LldrPs2qFP4f6rdz731bf35pPPPbhnKPz73_-Lw8MD6zkn-eE7H5al75uw2Wx-69d_eWRd2wx__Bd_c75cHxzsP1t1v_mtr60uryZ1FWJ_cLC3vFicnS_r2fzDd98HlZySLwpbuE3TRU1hiLsHe5vVxjrem02d83276bt47_5LpxfnhzvzxdkFW9uuNppTXPcqMpkWP_zpj8ej2nt7__X7oes0paYLxhUp5mbdP3pxYq3JQUKKQ0hBsvHTLJmMrUZ1Oa6qnWmMIUXNpLPrB965q2VX-XLVNqen56997u5iEdy8ePHBOw9ff20V0vLy0jlcnGxe-eLnU47WuJPT82o6mlQjMigxrVfrbugRjRK6olSgdnMlUVNUYwvQbEhee_n1nVlliKrR5KMPP75x5145qj73pS9cv350eP1wb2_v7PTk-o1rN2_dPn723Bejwhf7-4eHs_nNg4Nnx8dvvP4QJaU4DGp1ywWry3sPbobVmgFzSptNF1M-vVy3fY9tvL0zuzYZXzTDv_nO3_zql14fz0ar5erLb79CSVxhi9JfnK8UQUGj6KQsDqYTb9ggEYAAFER9lpOL5uH9G0ngL3_w47KsXnv1Xh6GYcibGAtrjTGSEluTP5vz4dAPH33wyZfe_krXtUPKpfcg-bOWXJWZLJvVoj8-P3n5tVe60CkxE1HKhKhMQOS8haRVWcQgxrEQsDWEgipvv_agYPfes_OytpE0BwRV64yzVnlr-EJn6LOnCFEWAQFNYpglZfIuJzHMgJ8hO5lZsqiosczMOWVRVQBRIDKWDSGklIAQAZJmb73mLERZFVQM0vZmJqcEmAlYFZJmRkw5AyGIGMCcMjHnmJkQmESEiETVeZNiVARiDH0DyhlgUBhNJu99_GJ_Pv2dn__K93_20ai2CTkmZYNsOUexxmbNSGQtsTGSMyJvVxNIVJWlqBChKG57r4yyFb4CkTHGGCYEFSEkRBQFYy0AGGBjjIBYYkOUQiImYwwhZhFgZcPeWbaGkJHAF95Yo5qrcZVSRsaiLkXEejOdVFnFOA8qRNg1DVu7_a184ZNkAhrPa4NgkeraW2YF9IXxztWVL72NIVVVSQiEUBfOECEAgFRVSQSTqtpseoO2GteQdTwqt8sdBjKGvbeF8yFJUZjC-RRDWRSSs6gWzkhKvvCiOptMVXNZ-iEGRDKWBdVaK1kMky8sGc4pGUPeWwAkEOt5bEc3D3ZUxLEtqkJU2xBEBdkSwcR6VRXRPsW6Hi1WrTP2-Op8PqpHvmJEQnqyWKScm5SmhR_5-qcvnj1fLauquLd_8JMPnx_uzjNyn4MrfNt1paEnl4uxtcB8eLBvQabOqejji-UwhBhlbzxZrdvMJoSOmb0t2qYp6kJi7jedkuqQ_W4ZVwOAxq41zhhvUTQPwRRFTuIqZ72tJ_tVwYd7Mx362XQS-zSalouu__733vvKl946Xy1PTs9t6dHRdlY1Jn_vxi2LCpqXi-UPPn5-dPvai_NzIrx_48hCLMmwHt3bro00ias9JEHJQBaByTIklKTleBTarqiLftObuqJtFION9UUemtyHftWmbgCRKKiekQkRICsgmtIrq-aoIaiCHfmcMhMLGLc_7fthuGitsZAhQ4AgYdiq0IGZ-kWXNkmRrTGUpfDcni4kJbCWEkJMilQdVfF0wQLljstqJWVUaTcDKLDnDDm0GftITtMm6HqAJJAFDMOQoQuQInQJQgJESFmjcqXYBZtEURDJK4Z1f_jKzatlvP_a3R_8yY9298ZHtw7OTpsYAnnohsG6crVsxuMiC0aHFy-WqQ_tonFMVvLIssV-6EO3Ss5YV3FYd6TAlcVFiC9Wlk1KERnJ6hAyVHjt9br5aB0G3HtwVFRcjcuo0IVgRtbe2BsdzO7vHaEQGLh-VFFGY0yQLCHVhTEG25hm12abdd93TT2qmk3nKz8el4xmb6ea1fXz88UK1BamSQk8n643QZUL8-J82aecMmRQx_b5i8XRwbwuue3CAMrGUEFB1ZZ-fjT_-MXq7sFYFcbWFsTT0vnadG3ISmi42XSFZQYjqo2I9aYHXTW9qCCyqJIxURRQVXTT9giizN5aIDwaG4hSWDpfD3dvjS7b8GTdgrPZWTfyi6YZYgRQsFKXftPJrduHeRiGrt10LZApLV0_nNXO5BAePb-YTccXi03OsOn6DOItr5pgLIV-MEBNO-yP6l6yAsaUEAAAYkymsEhAQGxN34WicMtVS4jOF5JSUZbGOkCunYlDQKS6dIAw9BGQcxZnPWRwxIQoWYlREFPOSaQu_BZWYZ1tQ2jbDhGGkJw1xCSKSASgqKiSd-YTNpxDKkdFZa0ohBCv7U5JMeSYBXLaYj81JwEEyUKIIeR-iIDAbEJMqqKijCyiMUs7dN4VbI0SrDf9dqIESEPMmzaoqrW2j7FJMcl2q05CysTDEJhMzqlypcC2a2AQYAI0IAKMiIyWjIIU3uYsxEBotpxTJCBkUbDOKJAhZNi-EoCkhgwTKyogAwD9_3j6j2fbsmw_DxtmmrXWtsdff_OmrazMrCz7DIhnARAASTAoBkWRFEmpoQiprQhKPXXUUE8tqqMGGVRIjCBFSYEASZAMAcQjnqt6Va-8ycxKc_Pac-89Zru11jRjDDV2UecPOI1t1p5zjN_v-yqaqg9uj_IEZEQLjLPZsqR6_uyLe3dfB6uqCkBsZATIQuiMwFRCaIjMAcV5d_74eTOded5HjJQIa6lMnpCMAQ262eTl08vZYk5gh2dnYR5_-Ytffvb5l-998FWv5D0YOu_88uDger1er9ch-FrlYDlFBSILse1ms8ViOZ1MVrvx44dPf_mrz-PMNdHH6JvAbRvv37l1597933n3tc3lKqP_8LffmbbhzTfvnx4cvXHrpmtiQ7Qdtv16fXGx2aw2H__68UeffBmb-PGXz77-wYf_-r_-rz1-sv33_hf_5r333_jgg9ev16t_59_9d958542LV1evHZ0tjw9Uhn_-_V9--9vvC2vO2VW-dfd0s11vt-s_-J1vq9r1evsf_-f_xXw-e-3t16uDP_rG1z_95PO0XnnnptPu488frtbbB2-_9_0f_eUkhpwyhUDeVTEiTEmWh4fjsDu7fXI4PTi_eIGASnzzzq3njx_Ou3Awjf-7_82_-_5X33308DET3rl7781vfHtYXd64cbLZbMdh-MM__K3NVd9MJgnx6fOXRq7m7Ii7RWfAtVQzLLWI6vOHryyl2exA0ZDUUhrH_nc-_KAwTGN0aJ791avLr3_z9etn14ezxWc___TtD9-Z3Lr7xc9-SWSC1hwdzWJoY7Mahi8fP35w57X9N89qfXVxheh8041DikeT3WqN5JG5mbQOdLcbvv6tb5hUrXLz1u2f_exXronjbnz97Qf9Ok1nnUN-46tvX7y8fHD3tadPnqZSXAy73cYEbp0cff7549fv3ARVE2m4vbx8Ne2mBeC1W4d5t5t5JmTH6AhagpuHyxuHy1nbPL1Y_fSjz_-Xf-936lhDJMnYMlxvxqOj-fX1kKpMJg0hzSfNpI0R9wtA2-cfCvr_y3_zT__Oh1_1Ln7vpx89227-4Fvv65iroBKOJXcxMhEZIuOQhug8G_z0lz-dtZPbt--klH3w3iMBm8ieSxYchhj_7J_9d9_83d-1qmZepFYtlisokPNM6AKbadtGz87ECAgYnZln-trtGyL28PKqH_N6nRnMM4KoqoKp89wESmOJxIwOzUxNxACMgJCgpBqiNzHHrGZITA5JAYoYEBIyU6nVwMg7AIvkqooaiCog1qrBhVKLIZkByP7JJyZQtarIXqYrKgAAAIyMZgx7bAOhQVEBwFIqAoCCdx4AxCoaMDKpIRF6h957gsdPHh2dnP5rf-e3fvLRrwlAAKSaOgaFNAwuBFVldAASm1ilhjYaGDs2EwAEIMc4jxNBM4Dgg6miGTtGM0RUUPZORZCdITAiIDKilGKg864RA2KHZk3XoqoLjpkRAY3ANHiOMZhZ9P540aFzomBmgNTEGLsujYWIVQVKZc8hBnKOiFLaLedzAHDkCKANofXeOQoePbpJE7zjwDiddGayzwERoWcCEB-CY2xiAERmnE1bQPDOeef6bQqtQzbn2Ac_lNQ0PvrABDE4HxisnhwemNTYBGZazieo6pjHlIY-NTHsNQigGByzQ1UjYOcxem9inpkJHWPbuhvLRescAudc-zzmUqazWUqZDQ4nM1QrKqvtjr3Lot2k_eL507PlMjChmJg9Wa0tuF0_vH50kqr-4OEXCQDU3ZjPXl6tjTirDqkEz2IWnX_y8vrW4cG6T4suXO_Srelsm8qr9SqrrjbD0XJ2_nJlZuBws95WFQNOY99Nu-16HbzbvtxMFvO0GbBWVtWsLkZAsJqByDEBQ9u1p_duDFcv7pzeSmmcLxap1lzyX_3kl9v19tvvf_iLTz7fDltwtG9Io5XN1eY7H763WW9yrmMtDx8_nyxmV5fXJ8v5u2_ctzpEIG7f-WodBVSRGfZ-agUgJ6gQOcRIhiWJIoJDpFaJgZEYLScpxXnXdJPdpu-WE3GQxbDzzkcwM62uDUYoUrVUMlBQQJSqrmkkkEVgpLoT3ziiYlQ1oSr4WSNFTKrlDMhg4NjQBGWEsRg6BSRiycVFGL94DmrVzBRUFADyWLQqItSaJQkjYM4yJBwzZIEiEAHIwy6zFNsOYAANwZhBiAlwm209EIESeeKcSrs4XNy8MW_DZ7982E2b49MDdbRar4ppzhkYhzHP2iZ4GmR8-fyypoqoh_N49cWlZxTZg5ARqxxMSF8Ou2djO4uz47j98qJx7GfsnQPQuqsQ0Idp3lDvuvf_-N2z9-6Ai9hFz43X7OehX8vt2zdPl00XY9fBvGXJFqJnxgBMZJOmYR9i9I2j3WYHigAKgLPlQpiXx9PRIHaRI-0sXw9DcTRq5uCL5l4xVwNHrPbk-cVrt0_evnOcxrxYzGsuw3aHVTa1TietM4jsRGs2eJZ3W4OIcP94eTXUCtJNu7EmMj49nA1VBZVBL15t-loNCIGqgdRaTclZqUURkNAxHxy1pZgs2pajR9ll2A3ltTuHz9d5ROJJHMTUExKudzvnXcvUj_n8yfndkwMkklKn0-7oYBo4IECpcLSYP3_2QoyGXPqcpEgxn0pSg3G3IyBFSBWqyp4Osb5eu-CbNoQQHZHm6oPLpY6piCkTrdc7F52aVrHIOPT9MOTQhG7id9tETIagBlrFO557v80pp5JqrQqlZBXdjeloOduue_KkhheXuyaGNFYkMGRQdewBAc0c43zRgagDnM075yGXOp-2CCZZs1QDVAA02PfLRCTGxsQQEZmIcW8GqFWICZHYUSk1xmZIqZSK7JMJIg1DGlMSMTMgYqmioN6xiBBzlWqIahLYmwoRwT5KBIQEhkhMnhwQARoTMaLBftKPrKgq3rMjZwb0G4m8ikJwHvbhBDDPBKqBPJoBGpIZgvcOwJCdiHhiFz0ZIMHB6fGjLx6P4-rk8AzIeL9cZ6a941rM1Lq2ZUKH7J0fJA3rYTKbeEImMlPvHBFoFedJRb1jR1zGftK1yNTGycHpDR_4n_3JP-9ad_vugyaEaiaAy8VBiC6lstskRGHk2EQfvQGI2mwxcz6enh21gV69uv7ooy8__eLRdLrYu0p88PFgfjQ9-vHnn37nt7_--mt3ltN4fHJ8dnpyeHT02u1bt27dvHXz1mw2vd4Nbzy4d3R49ODB7Xcf3F2enB4fT28dHT94897r777zzvtfQb-4dXpg2FwPu1kTnzx_-eL84j_5T__x__zf-we_-uKRCl88vTg9Xbx4-XI5n3z4_ldFcT5xf_rdn5zMFur49Vs3vnLr9tXViwc3Tk-OD1WsjHVT8p3Tt3_08x-M1yskBLR22vVDb1I9eiDToh988G7uy_d_-KM333y978fPPvvk9__mH_4b__Y_-J_-G__qcjEJkf_gW7_7-Pzp9TBeX67Xr64BxmXbUkmHy0Xfj6nmkjUVcSEg0vVqF6cteZe3xQBSKjWXkJ5N0YlkbSdaBUr2gb76nQ_7pKjoKTRt8_DLZ9_63Q9evepPD2Yvzl8dnM5uHs6228vV5VUe6vG9u84HINfNZ5988ulX3noTFYjB-6ZSePT0eZxMEQGI--0mpbFrZ1JHERWR997_qmdfc_axu9xudrsRUF5_6x2zeuPWqXM0m8_7fvP6a3efPH-2Xq8nXXd263TRtF9568H5q_MQaDld9jU1jX_66jJ07vHL6w5dyWm2mEbnzAybdjaZCsDVqv_y5dVmrB-893pVMNPGT3ZDMofzaTuOqRadTWLk0AU_8T44ZjZUYGJU3WX9P_zD__abd2_fOZr98KMvvnxx_Xf_8Bvap1qxAtZSHJF3ztQc495l7hG7Nv6jf_Rf_vHf__tQddcPMUQCBQNmNAXvXAj-88--iNPJwfGxKqRUQnBsWnJh5wiICciYgJj5N31cVRGIpAL1vdu3fvbJk6th3PR1lHJ1tR1K6ZP0fQKgXHQYi5n1w0BIitBMGgNCRGP7zcDbQEBw3wcCc55BlZEMgYPTWr1jVRNR793eMFKkgkMAU6mOkIjymJhRVcx0XxUANa3FDGL0ORdHWEpBBELaLxCcCwQoWokNgMysmDYhihpWtmKM4JwXrc4HRMqlSNVfffzwb_zOezfb2WdPn1WjVNQQ2Wg_bIjsCNAQVc3FIFr30fg9G9k5InLGRI4YyUyDd2hoBtOuUTMxQ0QfnXeuCV5FHPG-G8HeASEYGIALzjtGIFD0ntnRviWBSLFt20nTxLYoWBURRcSSynTasKFI9RhqLSUXYkJC59iKWqrdvInOE-G8jdPo2uhEanBuEsOe0zZpIgIwMZg0Pky7pm28I0cGnqlromduY6w5Hcyny8Np3iVVmXZNcMyOUE0VDibNyWKupkzYRl5Mu5xGUohN3INEJRcDTGOeTFsEYkDv3P4trlVCCCjiPAGCZwcIjslAmPDNWzeYad-uE4Rc63QyKbkG5_a4aHKcpbrg2BMRpjoum24eoyMqZl-uN8mw3-1eWx7uinx8cb5NZTkJszgxtfmN5cX1RlVm7XRMKbK_GHan87modY4PuoaAq0gC61MlRBU1dNyEsU_9tlekPPZN7Iaxj12LqlpEpSCyodGQwFBBQuPLmExqbDrT7Ns4Ozq4c3y2mM1M5OjkcBhyCOEXnz68XO3-4He-_dnDp1fba-eCki6Wi0XTts5958MPxl3_arWGgJ--uHzj3s2Hj17eOj188_6N3G-nMTDceKBqzjs14K6FMQERN06F0QVLWUvBwG7WFhfjyTK0vLva-sb1m613jiatAhKIjDl0M6mZFRBARUHBCKsptU5TRjMtAkjOu9xnDo20Lq8Gigy11polg2wyNlFUGBFUpU-ARB5oLFBUL3eWqjrTxmsBTxyp6mqHPmgTTEBrValGBEXUgBg0iZmwqNaEg0BWQICCSAq5mgiogBiqohFUQQMcB2empjxrrJgAnd67v35x5c02l-s4nzx49_ZHv3gmpKnmfpvbrhFyk4nf9nnYFUkZVIKnYbVlRjWtQw5NRCk4ljrSMNA7f_Tg8DRsPr0yoQJSgUKMbhaGq6E7Pji5d_b-7775zrsPpiFcPVq3k_ly0SlZNwm__smrG1-5_dobJ3cOD8wqSEUVBdK-NMSTJrZNRHJiwADTrjV2aUgC0s6nldQYZ4s2sxNSY6DIPex5W5ZzIbBtFiHIYxKj-aT9w6_drYP7wcNnd24d27QlVentzu3Dd988mzYNI7XTTjuvjje74arUJsRJiOZQ1Ey0i67fjrnqNuVxux0GudztqkBJVcaRGNVUDFKt61qcogvROTf2aX2xOzmanM67RmGssJO6ErnMOYn0uQCRglaTbSrrbYJcWGUYZdE0OxHnXNM0ZK6JE0MpfQJHOaXlrFn3qV8PEpSj31ytAvoxpdg2CpCLpJTymHwT267zzoNo6jMblixi1oRmlDzuRhc8gm1X65JlGAZi5xuvZlIUCUuttWYiVNNSdJsrEwroWErKBYhKqkOfHWP0kR1DlV0amTmnwoTOuSY4E2DHomXada33Wir7sJ-a57F6xhjjb5pzQGCYc021Oh-kqnMO0FJRAE1jAQQkJke7MbVtU4p6cqISmzYXSaWaYfpNHCsF5wi5iR7QQhNzqWWPPTVTA-c8qBoaszOF4Hj_tWFm-A2VAxHR1BjJzIBwf15XA2QEAkRsKAgAIjp0oIKIBgaIJgpAgIoAMxcTCJMTBWSKYX_UAGasFZgJAe-8dv-TX3wcJtzGDhEYKARHimjoHLFzYz_OZxNCJNDZcn51eV3NppNAREpEpkyIjIT7NJMtj6ZPHn_axnnXBCZ2zs0Xi9P7d569ePWjH_z45OTk5u0bBFYledd0XRe7uNv2RWutImrTScdE3iOxzxW6xbJpZu20C2378NHzLx4-dZPI3pcioQvPn52_-_671xd9bLoCAsyNj84TOR5TdsSnR4ftpPNtVLUQ_NPz66Ol-8nl85vL4zGJF3u52rKqv3G07Jqj2dyzMVPD8sd_9O1nL1efffb0t9__6pjTo2fP3_vqW2_du28VP3v4xRePnjexGXP9G3_j2yfLeRs5xtDESJEnTffJrx_dv_3arx7-dHt5CWJE_I2vfuvhk4elVBcCEeVcj09PmRS5np3e7DfD0PeTSftbv_2t5WTyk198dLnd3Lt799HzL1-er0uVl-cv2ln75Nmr__3_9n_tDE9PDv_sz39uUuZHB7VI03aGMiYLIcpQgG23SdOZi7NlVgOOABQ9lnGYnZ7df_ON6_U6EKYhswuff_74699-Y3PZd214cXEhKS9n83Y6e_jZ56FxD788f-dr71etB0fHL18-f_zk8btvvyk5S9EsMvRJTQzBT8L15RUCWRbvvYA5B3fv3FxMp2bg2ma6WH76yadt8CLVAc4msWmaLjY5DbdPTq3KoyfPhBwT7nZDDHR6MvuT7__8d77-3mocQPG69Abt8_Pnv_Odb7w8f3p0MCXkSds0MV5crj56_HQspevaG6fLs-P5bt0fHh2cr66q1cPZZLXrq2AT2DlyiJ6RCciAmcdUDaFtJn_y1z995-TGN-6evtimf_69X_7Rv_BNp7VWFCQFq7WCaPQBEQzAakUDB7DeDF9--vCDDz4cakaHTYiEsJdSIWBkVMMffP-HX_v2N2utRQ3AtFQwXO12TWj3qXQ18MjIhEZVCiEbWgxoo37w1p0__dVngLAbNIOOeSTHUoUYDAxQ94A9QMo5VUMzQzDvGJFSUnIECM5xrRUMCAkIRDQGNsKqe9YUiokRgYFVCbFJuey5LlIEzAiIHNeSbc9BViNmh6RSawFCUhEzRQMzI-ZaqwGCgXdOq4AaADCHQXsiIiAlZVAi5zwrGKEjBq2Gou00_Of_zT_8X_3b_9qnnz8dhhHZgzMQBQQRYMJSqvMeAzEAe69FGMkHb2bOERJ678AUEFBtH_gH4uCCESCzinnnQQw9q5mROUdqhkTMLoYgpswMYKFpSik-OEBwziHu06Awm07IUUq5lhJjLEV9G5omlFRVqmittZKhmvomIgIzMIgp3Hn7dufIAcQm3DhcGmHXhSZ6BHBMwXnP5Mjatqm1EMK0axDNEQXvFstp14Sm8U0TzUBTjZ5mXZfHHJ2LPkwn8Wg2iZ6ZpIsuBh9DuL66nk27dtoyUztr16vBABRMAfaFCOcYFcx0NmnJOXIoxRBUVL0PmouohOgmk_Z4MSOA3TAmKWMtgEjOiUrLbh47MkRCYFxtNn1ORrgdd2cHBw4AzNZ9frTa7EohsJPp7Onq-rPLy1Hg7slxQ-56Paz7sbCVnFNKxGxGq-14NJvstiMR7Mb-5tFhVViP47AXTZu7uFrN5t2Y6nq17brJ5urqYHE4bLemXEsmUK0GoM4RluS8FzEEI8LS9465lDQ7POhm8c7ZrTT0KlrGZEbPL1988vDR8mDxR9_51vl6_fTJc-eYnNtudjdvne5Wmz_-9rc_-_zJomtdjP1me3Z8Mrk5fePs7GTWTRyiGLu7b5gB4_7iXdA5UQRmI8SAkDKDafA4naj3OSVVIyYgKJu-mU_8YXv1-ROoBcByHtCQgq8q5Knuto5ZTeq4QyQQAxFiRmJgwIZcy3XMrmPLCTVJyRDjfklAQQmqXAzggaxitmaGttpKLtaYJSUfTOp4uUbRGlGLIphTCBHqWLFRx4hsep19a_VygJygVEAFRQCBITsWTQWyQMlQFSoAqpURsxAzmEgxRTu4cWO72ty7d-PRl-d-1rjACrrpR2BJu56YyPF2Ny4O2t12GNa7SXTjdgsG0mfnKI9leTSr1xsqZtCgd2__wZ3Ljy6ef7ZxM4xvnQ4v12bKAWNo1r37-t_74O7J0SR2KYkR7LJOZ003adyswa679-FZ17RnB8vo6PqqD8F57x1xF1zLVM1GUfE0b3zjqYj5rpnOO3IuDWm7y8a0PFy87Hc--utUdlrV0a7UIgoAr4a03mVAZzXH2Ny_f6tupRabRDKt37l1dDhp3rx7YzrtPvry1TpbZYSZ7xXnVS0pq_vkk8ccHCJNQ9ycXwLirZPDq4sNIe2tLIK23mXHlPrEPgAAog5jKmNeNM1YQUyt2rDaLm8uBsGT4GbdZDWmHHANuhVRJLQy1Nz3A1SJzkejmopaGXayHfoqQEJt02Ss_W643u6GVPpadqoqmoaxFM27AURLSUYcQxjGUVVULZVyeHoAhEUtjaOaNG3MWZBJQTarXa0mpnnMgmBqe-6-JnHeIVjOVdREQc188KlUZNyTgyugj02Ranudi6kAIxMCFLHNridDAyDmrpkS1D1QedL6JniH5H3wROurq2nXBCYXvJGpWk1VFQDRDBRgb7esqiWJY6qqYlZV___D-jJKLqkobIeR2RPRZtMTOXbOhUDEhFBqZaLoQAxF1cyYWAH2nTw1M1BGqibk2RTMlAxD8CKiqJ1vxcQ5JOLgnJo55r2uRdUEKyIxkUcCMPaM-x9yVPIsKs47AWB2ZhY8I6IJ7lsQjsh5NlMCBK133nzth9_90dnZqUdSEe-8d0zsALUWJUcpjV3TMAAjNW348ovnh4eH-00_oRNQEyVkBCCAUvTk9p1f_fST09sniOa9M0AEXi6PT-_c-eVPf_SLn__i5PhsOVsgWKo5eD44PtBSRGUcxpwTAgTmpotdF9NYAL33Pk4mXdt4x5fPV-t--OFnz65fbLjh8yfn55ebv_j8sW-8D6HhiMQGZGL9dtztcnDBWb3e9JK0Ki2n4Z_84MvvvHEz1ToNpi5cri5u3j7zalaLB3h2-eLVJiHKuLOf_PyX773-IJdxPfT_0h_83nzS5DH9n_9v_4-jg-X9B68p2K2j45ODw1LKdDoZq4hCO2lOpwtReXn56Pt_8YNcNEw6al3JY0pJERicZ_f---_tduuTwxvr7VANXAgM7tbZoZT6k1_96v133-3a-OmnD3_5-ReLxfL48ODgoPutb31w687JopvPZt2bb9zpt30yZQxi6pnBJDDJWND0ejUeHc-SWPYevJvGGUo_7sq_-G_9fUb4-ScfvXbj7rPnr5DrJ7_-4p33XrNevXfPX7wctsObb9xdzmef__JnSN47d-vOvcCeQ8i5vHhy_p1vfkOzFC3ehd2w68cxhMYYh-0GCwYfJ9NpKWXWBnJ079a9pvHgXFL-1S8-kpLaGBDg7v17OY-Hi9nFbtWgU4VnL19cb7aIsIzt1Xbzzbc-_P5Hv_r6u29fbYach9XV7tXqhWfnyF47PQrMCGjOff7s6fnV9sHp4Y2To9PDRXCUUylFmnl7cdEfLuP5y5UHnnaNZ4zEe9fH_i9X88zTxcGf_fgXP_r8-e998HpR-_Tx83bevHbrmBSKmmM2EQVzjpzfMzG55OKYGfTPfvj9-3duH5_cSOPYtt0ezkuACubYGt9894c_vPfgtbZrzQDAg1YfggFW0RhdltJ1EwBsYlAwF10VcY4B1THdPjm9dTT_yaPnjt2YtAzjfkZvCiKQUmVmqWoABOSYaynMmHINjWd2aEBMzu_hPuSZkNjtGf2mpkZMzKygqqYqwTEgKQAiMKJWIcAqFYhMtWTxjqVWZFQzMjAjACRWJKylIrGPcf98MzB2jpERjYD28iw0chxUDUA4OFBgIgPy0ZkpARsycfjqg7du3rp5czp98vIqKVURAHCekMEUYmAXXYxBxZoYg_em2jUxF2VGx8x7qxeyd-T2-HUy3DvEHLEjx8y_QVGbIgZmQgzOGxMgMO15mEDsyGHXRoDf3GqaSUvs0UBK7ftxzxQCx8453sec9tFM0H3SCRABqeTxeLGcTbv5dHJzFiNw14SmcV0Tai3TGOfzybJtEbRpaNI0PrCPfHJ0WGvZa-ybJpopE5aiZnv0877rIE0bXeAktWsjmOwbYogMSNvdbjaZqOIwjE2M6-utAaihgQ2lLKZd6z0gMGLXRUVkwpwFEYzUs0cEQ0A0RJtM4q3DZT-OpZQCttn05riqImLj_Kxp9p8gcpRqzbUOJQEpK8xDRKNXw_is7y-HvnPuwcmpufDzx-fG_M7NGx7cZqyPXp6z95t1jwiEoQKo1NYHNsu5GMprxydjXy63u4qUxkzAqppKAkMVLbkSmaZxcXyyevXi4Phg9fKVDIPnACVprqVUCsyeRAQRYmwlj800Hp8dvv7a_Vpzy9i2bVbdgn3x6NnxrePff--Dn_7soxcXr4CRoye0morlfHhwfHH-oplEICdIKPLsyYtvvnt_2baRzTMy33697jV4jlAI2Ykqe69gWhTVPKA655czC0HKSAjsseYiWcSQkHUYODpEr0UA0AICOpOKuTjH6JhaT9XY0BDRkYlqqRRcGQSMKCtKQmAdFQT91Gtfzcw21TbJTz0gYlZvml5cs2cMjQwVW2YDWfckCq2zaqRm1WLkfNG3M5cHDAHquratlasezMAATKFUEAExJtTVAEXBOSRENSrZht4T7Z2FojZZzmLsqlFsuF9vTm-dNfPJs-eXym51dY2Ift6mrFjNIV6_2nqHNowhUM2FspVh8J64ZKyqhm9-426zoKvPttuL7cFb87wuadd3MyLvR8C_--998Pprt47aSa6Qi6qU7jhw49DhVT_IZX7jwUQTQYb5crobUojee5Jq-15jqfpyN_RsZRhVShHbE-Kz1Gbavrxe-2nwXYOBxWNR3ZZKDOebHhEqowhepO2i8Y92q1kIAPaN06Po2tU4dtMYPH_-4uKts0MmdmxnN5fgaL3bbfvRHA86Prsct9vd7VsHuzzGQKbmG9dbLams1n3Ttn2phC4bboZkILUIegCiyTTuhjxt2rYJ_aCN57LLivL4yUs4WsRZfLEZ7t85fjJsznNKCgYWGXKp6_WKEbsQHRM3sV_31aoP3rtwejTRqptt3-9S8N75UFV3u4ze97tkVktOTg2QqQ2lln7X15yIANlJFlQbh6SixriPLG2u1tttGschNI47HrcJTaVWRAzBe-998EUVECqqmSpgSdUMUirMmIuAQS1SawWEvbiSmbebPjiUYqvNYDn7JoToQTMCOHYENp9NgvfDMIpUF2i9_k3SrIoAk4imkg0w1aqIuWQEROZxzADmfTCDLKJqUkUBgFzKhYgroBqI2XY37iuGtUpsfNuEfshNE0Pj-6GWIkiAwCqCAIREiKpWRDx7RCNEBFSV4HytNfqQq0bHSLT3eIGhc0TIpUoT9_c9dESgRvuGsqEjNq2OXRV1js0YwDy5PbdEDZ1nNPCeAcBUvHdVNCBR1Rtffe3Hf_H9uw_uoSGCIoALjPt7FRgjAWjbRlPwiObs5eV6sVg6hyDmHHvvwIwQXHSO0DJ0i-mrZ88XiwNmYGRQIyYiPLt5b3q4_MUvf_H0yfPDk-OjxRyr7lGw0-mEvR_GsaqWXNOYO-e7pomBCKyIkPluOj05O3WeD5bNcjmdTbu__fu__dqdk3fv3KjFnp6f__LTR5-fX17tdkeHh7N51zjKZYxtc-vOydnBpOQyad1utbl161DGPAx9x83jp8-a-WRCcHV5eTBtv_vjn_yb_-Bf_fjTxw7p-ZPH92_cfLW-2o27r7_z5nK5aH34R__dn7z5-v3NpneNv3d25x_-4_8q9evDg6P57MATsgEq_fTP_vzkxlGp-dn5CwTvGp7xdDMMiNROWwRIMiynB0A4pMHUd5PQb4flYjaO26PJ5O7tOyL541-_eH5xvloN3_7gq32_O5pO3_3KW01wr56f5zFd9-Nkcfj0_KVjklr7vgdVT8SMIhpmjRELR2JML17UcVRufu9f-VsPP_niy-ePvvr6G19-8cSkvnpx_cE33llf7Sjgoy-ex-BObhxhKb_99b_1V9__fgxwcHLYTuaA9t7rrz978riWdPPsVjXp-93V5UpFJvO5iqCqpOo4SMnjMAYyIP7a---jSduGWvTpsydkNTYRVe4-uDVh17UeVNZXm8V0fr1eXbzahBiCcxng7tnNhy8fz-KEILgGWfnlxcVkOj1_eR66-U-fP1oVPZxMT48Pbh_Opl1H5BxTGlPwEYg80_nLa08QvJ9NGwaMnh2RY2QkMhKtPiBj_Cd_9eOHzy7-_X_xt9NYxmQ__-KLN-7dn7cTq5BF0VRUTcSzJwJU27t1iV2p9b__H_70b__x3wXEMafQRBBDNEAEw-B5HOsnH_3q_a-9n7IYEnnMJYmaVGlcjI0b-jSfzczAexJTAjKTpolggAhfee32MsRHFxcCbhyTaiH0Qz84dmLgHJlVQwM0doiGVWAP_VTBJnoicoTRs6oCkgsuV20ajwhMDpkdO0TaG2PArBbZq3O1CgCCiAGoglTx3o2lBkdqqmrsWFWBDMAAQVX3Efz9fwMEJDQ1cGSqphqcRwABAFDnOOXqiFzw1DKYEhETI1HbxnbazY8Pv_cXP_1bv_feJ18-FTNit88kgmoTgvcuIBuAQ4zeA4CBMJPz1LSBAiOAI-ccs3fAhI6ySnC8mE6HUqIPjskRO08IaGbTrsm1OHZEHKMnQOeYnQNCR8zknHeScmxbEXHI3tM-0hmasN-9zOczIKhFQnBMmLIA7_1fDsBAatuGqXd_9PsfzsGfnSwPZ5MY_K7vTw5mbdc0watqqbkNUVTYwaRtAQBMt_0YY8giiCiKKeVhzNfXO3Y0Zl3O27GoI2zbBlVrqYDEzgHRbrebtu2-m7GYdHnMWbRrI6NOu3h2OAUxMWHHBuAbL6I51T1USkXJuf29C8nEqvfuzvGRKEgRBUKmIZcYGoM68XHiHAAgE5Kt-q2PvqoBwdl8Gdkr4Mtt_2S3HUp5cHp8SM0n1xfP-75k-e2338hDffjyVTXrSw7OETA4HksO3knViffPNutliDcOFqL2-fnFJpWSKgFWsKuLtfOh7_vFYkaKq1cXRwfL7WqjUmJgGTPv6SEAYyomCtVoD_gD0JpM6ltfefu911__7NdfLJfTxWKZVT5-_nizXp0sDr794Cv_9Lt_VWp2wRWpTAFAffCB-d037z16dD6dTy8ur2JwP3z66d98-ysT7-swIjJVVQwe0MhARRSMPQOoqVHwznsxBVUwlJKAHRGlPikhhBAbJ8MOTHW_9DfTkonBpDaLiXeEWdrG426kLICVnVpVUHPsuuNgtTYRGIpVsV3vtCJmrQWKMlbShKKgWVaJwGy39gHTWMqYgczGZGmLprJvEUoFNQTNm95Hzn2FnMomQ8rjVQIQqAW2AwwDDAOWDKWUqx2qMhNkZQK2ZKM4Cui5iQ2ott4H4H7XHx0tPv7ex2E23_Rpl4qibFdX7MEY1leDQyLSkqtrCAm0qA0ZN0nHPOkmlKTuSt3Bm995Y3g5bD4bX75Yh-Mmb2vV0ROOV3x878bv_f3vXPya2zAVsoQaOndy88BGc4KlL-e_fnHvbvv5R1cXL_r2KI4i3aLh6NZjrUDbXAfJV2ncaiVC7trKvJbyyXq3SwW7wJPm6O7J0d0Tc3zZj2rW17rLWYkGFZjwdiyv9shrERCtOV8NyVcJTMddNwvxYrudTpsBcEDBadsXXa93aSiBfP9stb4sUNNsEfqUb9w-fu2tux7oK-_ev7-cT5CPZ_MimR2NUFwbq2hJuutTKbWoYSAXfIhOGJAAkEqp0blp53Wzefj86mVJPzy_-nK1Gw2S1JSKWRlTUZC-Sq_azOPkMEyOZhfb4e79-8VkTPVivRGAJLmIrPttKsm3fnW9JQJkqrVmUSEtQ7p-eVlTrkXUbHrYMtNus9ZS_ITjlAVKP_aKRo06xOtXm4hORRzz_mE7jiV2LQCx92MRMeS2MeYMYCrB-XEsaSwgiIA5WxEtWXIuu3HHhNs-5aIiFcjtoc6l1qpSS5nOusZT7hMCqNTzy6u7D45cQASoVVLKQ87sfakiZkWF2WdRARhKTVW2OQuY95G9M8PVKvVDyUhDlVwl17pab4dUdkPuUxpzvV4N6-2oBLnUXV-SVgMzBakVDAmZCAN7IgrkzBQMovPE7JmdB2QCkDY62cfwWU1VSAQB0IJ3oiV654BNlYHMgHhfUqjeMRl55sDeE3oiIGAix9h4ZkQzMDUDc0QAGoIzUkAMO_ngtz780fd_4Jx3tG8Kk_fsnPfsEFGKlpKDZyS4cXqYtruL68ualWjfEURCcv-jjodQF4uuFsu1WAEAcY48IxpUKaFp33n3_eXNm3_-l9_9H_78L7cpt77zSCraNe3ZjbMYgoJtdv2q352_eGUqk645O1ic3pgvFw1CbZswadpJ0_345dqaGLyfTps375_94bff-5_80bf-4NvvnE3id__8r_6L__pPf_jTT0CwFn30xYuX15sWC4bw4P6tbT8iYq3w6OlzJu6MInDeDbt1fvxsVaVG5p_99Jdvv_ZApABoSeNyOrt6tX30_OVsOnv-8vm27H71k1-1XXj66Nkbtx9009kvfvXRmAt5hGh_8t3vAqF3zb3X7gpb6vPFboME3XSSUo6tX6035HyMsR-HUoblYukCfPLpo6abKqKYbIc8WH7nnbeLiDtckodt30fyZMae8pguL69ODuer1XrXrwGNCRXUAEtR9Jxz3fNlCcBEQQQ9a5-22_XvvfXhsN7m0ksq8_msZhEFNFLDXIUiV6TPrx6H2USlfvTDn8Sm06JfPH0B3v03_98_ub5elTHXakX08ePH0bsQG0SSKlJTTskEb966fXF-FVq32falFJP01a99ZbPr-z5J1euLa0eOFW4eHv3ks88679q2Ozyc1VKv-3Gzvlyvd9_8ytv_-E_-YuIDO3fn_oO33nxrdXnRX27u37v5d957_w-_8uBo1kQkIlYw58kRTtqGGBit5JyG8eat4_mkCw4Z0RF4h8wEBmDSskuZ_vF3f_D663f-_X_w-6ucf_3lC2zcxXp7djQvuajp3iNrv4Hr656dtT9CSMnPL64nzZQD97ttiC3u_YAABsAExOGvfvRXH37n27mWUkQVJRcmrlqQiYgcBedCFQWDqmayV33AHp4jwLPGx9ZrBfKIREaURCiEbLhTFUMDQvBEHoyLGgUiJAdQaurHBEwY2AC8d96530QivXfIqkZo7JAcAgGaosFe72cqCCBWwTF5x4yGWk2dZyJ2xPsGADoqqoJAgY3Ae08gBLo_QwIAOgJQAwUGIHUhhsBNDGzYtd7FAJEMEdEpBj-JjtG3gZBXlxvk-OvLnReaNIFMyYTAGu9AKhGAxyb66bTzjprou67x3iPCfDp1RI7JOfAeg6flpCGDZdsxMgJFH5BYzRwhAzumGBpRdeg8eQBU21fqCB0575sYiUhy8cED6F4fnEsl54xQESFw1wQwVVG3bxF4Cp0npnbSxRCarjk4XC6Xszfeuaeb1MZ4dLpoO88Mi0nbBt-FUKumnKddw54BrQtd9HEYs2NP7HZj2WzH1TadX6xWu0TOLw4Xim7M9dmrNQD3Y819LkkVaNo2RFRKZWZCCCGcni0VTcims7akNG2bNnCqUgHIOQN00adSdruxT3kYR2Nw0XsmRhqHQdW6Sae5IkDOZagl11rUDCiXvNv2jXOGVsqoVvucdru-7WKRQsDoSA3MTBlD8MZ2PO0U7cXVajadtN41pmMuj16eu0Ce3azpJs5JKcxWa753tKgAB_PpwWwGAMmqee6HgYJLovPl3AdnuSDgOPTTSRN8WF1dNjFqFvTOiBSBiY2gmUXniajuL3m11qadhhgdec2jCty4dcJNSKBcoHHu_unNIefnFy-BrIgAqAsuTiebbb_d5R9_9OkvH__6h48eT6d-RHn_7q2DSYRawarWQgDAaL_RqjkmVWKn9BvVhhrsbcu1qiECSBnGZtrUofiAebNNqx0QI2IpxWqlUmyfnF7vpEgtZdzuLIuUbFVUlRitVkAaXiXMtayGmkodR0hVhmxFuFGTLJeprpOxqhmaMtbxxa4MxcCsVmKzy61tE1axInWbQVT61BCnl730IxpArdJnKElzBhEYMmiFCqDVcgYnkAqoghSEartEhX5ToM9VckIAJNjsRgNqmCeL6XTWmGnBPAxDrZkMpK-3bsbUj2i2HlJJIqWo1LTOWIXIahkYDdkfvXNzu07nj64Hy7e-dUrzcPHiYnUxmguvf-fB7Xu33M7OTifotC-lQo4Ry5gQaLMZMuKD908u-prAtIU4mQxjGotWtQL4dDde5PzxRf94k4rUNBQzXY111Hpy0OxMkxmATOetkHD0zbIdoV4PAwY3iBDA9mrsGqmlYK67sSDa5XacNh65s2Kt8IsXV4R0dzaFMk4cWpUXL64HKYtbBxdjTtGHxp2vNk-2OwM89E036s3D-XixlVwFcNC0HYaxFiMSrfP5FKNTsipCSLUKA5SsZahSJeVUVJWhFvj0o8fXeQuMq9XmdNHWWtFUWFeaU0mOHWoxp848Q1PQ-Y6fX72adO2Lqw3HuN72McR989DNuouXG0BMY-pXGym1T2m33Y11NGccAJiAadzJZtUb4TCmzcV2_XQ1bobtbhDQnGpS8R1dX6_Jo5h1iykAdbO2lGwGbQxMPsZQq5RSpdaxFDEtVjfD4GMwMB-wqB4FCp63m6GYGbk-JyL0gQFNVcdclMA3zkTzWLyjnPNs2pF5hwzgksg45jFJyrLaDoPKHtyUqla1zXYwwCLap1JExYzJ7WpB0lyqVRtLXe36vk-pKjsCR6OImtZSSrVxm_s-bTe9pOob5zwZATMBqikWUyQkdsR7T6UyIAKpIe2deWoK6n0I5Jwjzy4QAxgTEVCVSox7H2QMHgnYIQZGJHLokfaR3wqgagrGzI7IM0XvGFGlEiMYqCixN1VGWjbzNz_4yvf_6i-QvSFKFWfWRBe9d-zEbNePqVTH7NndfnBjdb0ywioiRVULEgCjM9IKjgir3Xrz3se_-jVFb4AA-99dNjWHxN4v5vN3v_HN7uDoT7_719_70c9X29TENiA2gMfLg-PDg-ObR9thGHPabIary-tSijdool_MusWsnS0mBwftycmUpGw3KSepOWsBx3E5mb775oN_-Y9_99_6V3__a--__o9__It_-qOPH16tNRXZDJPp5M27N0-OZ01w0eMPfvHF5rrP2-2w3SwP5lLt2dNXTx497SazL58_nXbNarsqUo_mC_aYc_5P_-t_vJh3i_nx6enNb733dmD89tfe-Q__s390cDB_8503Hz95tB3S5Hj-ZCz_1__oP3vy5Nk7734NSDbDbj1u-n7MOYtiLsjOD7mq-surzcX11c0793Mqq-0qNqFPvWcCoZrS7dO7HPzV1St0vk9j0wapZdI1PrhpNwmBFrNmvpg1TYjRE4Bnatsw6SIDOgWu1QOHJvo2Lk-m4-WlH_N8OnEBXrx4nmtezrpxOxrparc9ODpomsmLFyv2HiOd3TnzPo677aPHX_ZDLyA3792bHLTf-8EPlFxF2Yzb2WLOMZhoN-l8ExVBRRHd1WZbRPphRMeqSuyOT08ns_lus5kdTL747OFY81hT20wvt9vL1cXR4eGQByA1R-T41XjexsnFbrM4nOSKm931y5cvht2YyzBvp8vlIvrggRxDdL4JITAR7sHzpmaXm36x7EqujBBciMGhASjUYmZCPnz-avWnP_rZ3_ztD28vpleb7Y9-9aXrZpNp03EziQ73ohOC_cA4hEBIZpBrAQLnXTH7yx_8xYdfe19Mq1QfokpVk31poCF38erKO7c8WKoCeRaonnifNWTE4PwwDI5JTADEAIDATAFMzcyQEV5utjFwZQ9ibRuIyQGRIZpN2JWaRVXy6AEYgZkcIDtHznvHVaqCsKPQxtCEGJwHnjQewZjRe_aMdSxgoHshmmNGEBUTRTA0S6W64Ig5skM1Bwhs6ChE7zwjGBEgo2fWvUkKmNCY2QdPiCF4ItzXc3XfwvTeIfmwl4hjIPKIzcRP5-yZJ23XOq-ipdR2Gf76Rz_64Ouvg1gbHCM3wbXBzyYNIoS4p8FZbLx3RIDeu9lkCqrTtg2ePVMgj0QUQtf4afBt2wBaF52jvYbSGu-CY-8peB-i95H2L0vwzhEG51CFCRhRFFV1b2w0NN81OWdmZuJaa2iiKVoVx4BqHtk7ZkeAioiG0M0mjeM7RwfzJh7MWxaJjgIhecpZXpxf7vq-iTH4xhMeHx6EJr68XJliFuyHlFKKsSlVvQ_kfBYpqoBIjrquKzmZKnkmxhh8KXV1tZt1YT7tfOBZ68e-5iqhiVJksZxnsReXw6vLXlRX62HINY3l-rLP1cwgJRFFQByLpFpCiKY49OPx8VEa607Gi-ttrnXINddaalW1GLyaFNFcZbXZHh0c51G1GBsG9IAIRM9eXUg1qCpqiu4S5OpqdevwYJdKn8dZ16bdeOfG0Wp1DWab7brk7Igm0V2s1l0bmR0hpVSZIbah1JpS6oeeAJC0pL5mUMDY-e1m4723VJowYe_GXQ_MkoTNERiIqRp4B6ZGlDUTcj-WpnENeSl12Aybyxclj9FCrkrBUi0igkgOSVKZhHbipz_5xUe5jO_evKmJSlWIzfV6HPqha7rrl1fkAGDIUCshEpBltZwB1FQVFBxXMRXkSFaKjSMkYecRAFD3CTLyJnUkZ2gFEVBUtdZh5IkzECLTnPaOERtA-gyq0JiMyapgA5JGzNVqMVFAyM8TqqKOoBW0yjpZTrrekWakCpaZwQGyYvQIpgCCe2tarXnYAVajKiWDVKgVyawW2AxQR0ABKYAC2wypgFRLWVKGIqhaU49kSAy1Sj8yWt7lbjp948HdX__0V5Ojbrsbt-tNuh6lVGRQMyl1uxo1l5ySWZFxRMtas5kMu4SIeSfex-nJnBw8_-TJLg88j9vL7XCxC9ze-869u-_fZrM5gidJUp6eX1zudl2MptjEpip206aZN9t1-cWvn8X5rJ1NX7xcAXMR6z2OquR0lIqt9y29XG82Wtd9fedON2mDVRWtWO3Vy81mI0-e7jLpq9VmV1MC9Y3rQdB0vRrU4dbqJDZVKytPgjudzae13Al0Pawvxu1bi-nEUYsw9v2nD5_sBnn__p17cfKdu2d_dPdmg3bjxuz337v3zTtndxhy31epF6vdpy_Xs9MJd36-mNw4mrXRNzF451z06NF77wI3RF0XnQNyTIB5FERUw5RrzmWyPOCArvWPzq9KzbUWLeK9A0Gs7EO4e3w4jtXA0axdHB-Nw3i9HtrZpJgMeVytNoH9JpXHn5-L1X67G8dxu9npfvNcNO3yOOqQREFmiw6kKCkjSs1jvwWSISfPWGtF3leQvBlpRTMb1v3JyQGIImDKJZfK3kXn0lDJyJB826njy92u7ZreSgWpRarUR-v-xav15npYb7dDSa7xxE6A9mpcNArOlVEmkyY2MbZxupycr1Znp7NaRWquAOiolppTBSAx6JpYazVVJKhmQypZYLMbttu-lFJqWW9HARzGvN7tqqIxZTADTKZJte_zZuzJuz4NYntwQiHHwy6LIiEVFUJgBiQEUyLYu-5FBdG8J1X13hEToe1R3wLKzgOAqjl2gEronHfsCA2qChARsQGBoQDucR9qst-sEBMwVTNBI8eOkImi9wBqAD4AohpCrUVqPZ4tb9-_94tf_HWITSDeBwnYMTP6wOR4H_5zhrcOll3rnjw7Zx-DI0IHCiKGHptAaMhoDdjt-7e_-PIJgnfMgMiAXRvQjAwckwM8Ojr7ygfvc9t8769-_N3v_fV6mxl8AArsZ769dePG8fGBadn2_eXVq4urq81uFyM2gRetb4Ifh83l1bYvuegIIsOw3Y5DKTlpBWYVmHTT_9nvf-d337rjptM_-eRzBv_lw5ceaLMahn7MubaN2w7r5XxRGBBx5Px3_85vD7mu1v29Gycuhr0S4dsffFAKTNt21_cKfOPO8dWrl3_vj35_MWn_pX_xj2_b5Ht__tfnz5617ezTj778z_6j__LV-SvHfrte_-U_-9O_9Ud_L_WDlkoARsQOfXCe3NNHTxbLg7dff8sh_ehn37_14LXVerPdlpzFrKbd9uz0cNq1J8dHu83YTrssJUTeDT0jtl0oVlQqis66xjGDqlWpaUSFwIxqjki1as5mMCRpJ3EzrG8eHrYhkNmQ5OjgxDdx_fJ6MZ2FpnEeQggAYcjSNpM3v_K1WlLwQaWIqY4VDa3iz372C0LdbMflcnF1sXIATdOMfSZ0_6PYrq7W26GUT3792WY7GBAReyDnvBlS7HbbHRJtt6NY_q2vvvXZl09unJ6FENMwXm43x4fHD59dLufzSePWux7Vgscs1hdDF3gR8phsz4knVjQFNTVVM9WiAgjjON44nlvR4Mikggk7V8yALJD_ySdfPrpe_e3f_drSEZFerpIY3zye7_rd_KBLRYH2kXEspgomUpGQCQmAmIecN-N4_vzVgzffHvodueCYgQmQgIkZmf33_-q7H37r28OQVSD66NRIFABMzCEiWTuJWlVVDaCKVTMzdOxLqQaEaOcvL4rK1-4f-eD3Xc8xZceMBT1S9AFAY_RQIRiqaUJNWoNzNYPkksekCuzYB0egQACiiriHee7HBI4dCCKBIyYirea9Y8ZA3gcmJh8cOY7OM6EJ7BEFpNT4xpMj268yKE7iXjaghkTsHGuRLjYI7INHjwBAAERMiI7ZAznwnvfAXo7OtY0PnpvIIRCYvTjv20WXQCeeJ23TxmZf0l1MJh7JM0Tn2IDZheiD920IPjgzXR7MZ9MuNj56p2yTSRti8I45cNfG6F0TvHPOwIL3RMyORK2dRCRyQAzkyIFZ8M47ZwiTLiIgIZpZ28Q65j3ehxBmsykBOkcpZzIkIlBjo8aH6DwRLLvJrAv3ZpObXcemzjSPte9zP5ZhyOycD84TEWHNqYltv03PXrw0BCW8Wq1DaEJsVtvdWGS9G4rakOrQl1QEAFPKzvN8PjFVFck1q9Tjw44Aa6mKVMz6YQDizTaJ4XbIq924HsecSt_nIjaZdkPOu7EIGhC2044J8pDBwDs2qM4R-zCJXlV9Jee4ZL26WnVtZ2apFB99qWUxn5Rap103mXeXq3XTTkKMKeVSa6nCwaVhRBFv_HI7VLGumS66-Xo79qP0OTUxBHTzts0pHzTTjt1ZN-uaSKIsGj2TVqmVkWOIkZyVur3eMLvtaruYzfvVGgft-0zk0pgEJKP6tm26xmplZJNCigRMgJgzIpoKO3c4XVxcvSpSrjdjHscXz56RoPPu_Qf3V5erKkZ7opTZOOwOlodDP6777Zh02NX5wXw6C20M07ZZzCcOPSkfLg_IyKQaAGi1PYHfimoBMENAABNVlVpTkVI1CyhyE62WOiSpFURzn1XUvJOc0ZRcQ-Stio6V1HTTM5plQUPQygSaBbLJkIlZtuKqOhXLFXKBsRIZmGqfYTuCCJihiGwH2FYdBAQta-2rlWK5WBEQs2SWDAwsFcjFcrX1nvhZIGfoEwwDF-GCYOrZg2kwwSJsRqZ7lysmsbGYVTOwnG0cc0rjLj387Mucip9MXz6-Qk-rq2utYmnvTAXdahrSOORxzKCQVjUPRYqwB6gVqwEFHe3FR-cm5idO8khWUhV_OJkuDsIIEzIi6If-088eZzAfSaSs-_FqyEOpmzEP19vYxlt3Tl5dXBWRycF0FHv2avPifOsaut6ND3d9rdLNm8Oj-ayJ0y5-9jy_2pTH6_7ZbkgMO7SrYfv6u0eVDB3NZpNxKLshS5WxCHh8fjHmq9SraCAxxRDevXVAzo46_vL6xfEsnE18RBTE81U_lHp4OFvvkhur9_Ga0vWoH5ydLZPzVQHp5Xq7Tumzi8vf_fDB-bPN0XzyjQdHpS91l9MmEVpg7kLjnGOzUtRESi2qJXToPGLDZlyUZ7cOzWQUu1oNq1dXmI0Dl6rrbUXC2AVP7XYzDqkKu6vtOFsu-lSUVNhdbYdhFI5u0-9qEQqIaE3DIfB0Pt2sh2ollUQEsQkqMJtPrx5fDH0BNMWKDiG61VCKgTmrNY99Hft6dO-wPWihdRmsV3m1Wg21FFdTzf2Y-13uU1YAJfDe5VF2u3HWNp6c5DyOSUzmXVgPfS7ZNailbK63mut8HuPE5yq79XbatWkzLheTNngCI4KTWbx9sGSlmqSCplxz1VxFxMZUhrFerrdVoYputmOqmlTXu14BsmjJkqp6JGAqolVs3e8ccypqqDkVEEWmnLHjVqrBPu7juZTi436_iUyIhmAgtey1kZ49IQbvqyoY7jfa3nEI-3dVHTkEcLQ_vaMjR4SBAxn66DiwgjARgDGhd4xokWivKvPMHtkBOM8ipgq0J_kJkDkyyqmKCnngwKYiudy__1p7cPizn_-IY0QwEHEoTWDnCRVLKsCMoAj2_ttvpnG32q3r_zi_8IigYmghMBs5ohs3l9t-HGomA3KITFDB4d7OQ2jmGadNc3bj7O1vvk_N9C__-sc_-PlHm12OxN5swnw4mx8slweHC3C8ybvL9fbZq6vLq_Xl9WYYygnyrInzhjyBY2DHFcpWa8mlmgQHTERNM53P3j88-sbNe7-43CBbrWmz2h2dHWzG_JLS2eESgr-6XIG5__D__v-8c_P-kNI4jA8fPVFJBeXRl1--9dprY5ZPnj0sQ-26djE_HDapPZrshhED__bf_k7Thsl8yYHA8d_9e3_r7M7p3Xtn15e7sfQ__-mPbt643XbTEFqrhqK1FEPuczo4Pvqd3_8Oenh5_oKn3Wwx-9HHP7tx44SQ3nzt_ltv3Ds8bpYnk4pSUMGTgFQRx9y1TWQMnk4PZquLbRcaAawsFUiqYjUHpLWSUh2zivjgYzt5eP7y-OBABCJ5U5guO-fdrx5-eTQ_sJzffuOt6bQh1lJwzLWLzXK-8NE9-fjXseuAbLqYPXjjzVrH7373B66JABDbkIbeap3P5-wY0YGRGpZUfcCLzeZytWailEskunf7hlZ99PCJgL26Wp0_e6EAZ2c3rlbXD7_8dD6fTWfzV89eba93293Wgnzw7oN1vw4YZl18cPvG6w_Ojg6aH_7z7wEiMoOBiYGCqVWVqppNclUifPrysomBEBAMEHKtg2Qmsyx_8YtfHy0nv_fVezXnYZcud-mzl6_m01ZEXzy78s5JVcQ9eQ9537z3TESyt28gmOlPPv7lvZu3ZvN2HJPvuqRln75ixNBMfvjLX9y8fYPRFVFjZyaAVgmRcNZ1Mbiai3M-NmEPAvbemQKiKkAtNecRUKHK-YvLk9mi7drdZuc8VdVqQh4QlJCAWYwEFJQMAUmSWVVBr9WgWh36bS41l7pXxLCnUioAOMeGIGCilUgBzHcevQuBnXOOnY9sumekkhHGSXCBQ2Amim1TVWIIIXgm7GLrnEdjFwITOYdgujcoilhsnHPkmMkTGHaTifeOgZsuhIZ8DAA4myyIGAh85AIgYGYWmiaQ3T1cxBhjEzkQOCdE6IH3z47A5IjQmugRDcAIYf-uOUc-0GTaOEOHGBy3jUNCMY3RRe9jdIzMiDG6rgsUvHeuaaN3zJ6bLiKyjx6C83tTdxvNmIBLrmjgnbeiMTSePDH2u75rWx-8ghpBaDwTElFwPGv92XL24XtvNNER2FiKmuYq3vmD-Xz_WWqnDZksZ7PoeTemMUlsJwjofBhzPb-4HlKtKuRIVIoJeUZG1RpiCNFvNjtVbdtoYs65IjrmmotUsVeXu7Hoaj0ooBFdXe5qslJ0OmuRqOvi-mooSQ-Oui4G772qrLY74n1YzoWmBb9_QmuqdVdHdq6IiOput0OHbROjJ_ZsDKnk0IQhFSTapaGUQsRMfL7ZAJJ3Lmtx3o1K6z4Fz8FBVn1x-ere7dNhlDzmQWouuWud5nLQhFLh-HDatDGl9OxqZYxV9fpyJWhKmFIupu2sHcYMYP2wOz057Xd9O21rFh0BPe2F5S46BHAxokcrBar6GANzGQd2eblcEFkMUYs8_OIxAFaBRYdtG02riAAhO9_vduvN6uz2rWyWap9Uxl3y3bSv4-Z6nMyag8XcIcwmLZkaMJiZBgJHSEakFAjQwKmaOkd7zB-oQS5KNvTXLiIBMBHW3AanY7F1v08r6rBGTQzCaARQ-0zALjKLsQhWYc8YDUzJKduIaaCSSSsSgGTdjlYL9IlUoBawwqQ05v2TEU2p1MAAJZf16AhBFUHRBGqRlInIuQAlMxjVbLkgGxCQiKUESXQ7OBRZZYZqY4KqYIr4GzPhvpJEnoGDn83md0_KauMan9K2O42MiKU6ImBUKcCSS_IMIMYiJgWtkKmZsOOaKy8dzGAc-zwmMVSCfr1dv0zV_MkbN7xzoHJ286QfE3l_enaMyFDgetMfL5qU8sV6t9uO1eom1ctthda309BEXu9G8u7-m8uLi83zsbx5uHjtaMrizw6WXRMRTcj6Kk3ThRieXFznyDz3l-teTZPg9bb4JpjDaiq1EpMjdFxFa7_daq0dQ9LwsuA__PxJe9S8dXaE5J5ebV4N48W6ny6WF5vt9cXuMg2vXrz6_NNXb5wuQwVXpGn9q20qqVLg08Pp-eV6MQ0R3NOLcehzjIHQXDUCnE674-Nu0QVQALV-k3stySBMm6Ev0NLi9aOTN24Jh4T2eL2mdgoNjEMOCpiEyFTw4ObMLZvpIvbjduaddzg_XnDrdsOmWTZx6kPbttNmMo9doGHdSy4pS9M28_kUhXxwe9LWdDlZnC4ny0lsHaBmVSFE55c3jhm5FqbF5OjD2zd__62t9xvnu3fPwt0DdzLZlXHI5foqxVlHkZu529XMLVMg9oQeYuens5mRMhE7n0Uka1-TmCVR9h2gOTPvw6TxYNC0DTAsjg5unC1SP4pAKfVinQTUSEotw5ByLqICiCJQpUpVVVORVGo2W-_SOGQx2KWSVY2oZgXEfjcaYZJaq16vd6WUkmW7G1KqpBy8O796iWhoCHstDuOerc-I-54cMxICmAIiMUmtjsgRGaiZMXOq1bHfx48dAYARomN0RGomUJHMMSPgniAeHLJjMnJGDnwGC8hIjIAM1lII5loXnCqKImHTRERzfp8IIquGbM6zmUnNbz54PU4mH3_8k-i6wBycp33Rz6NY3UsPyBDE3nzj3hdPn6l5RPTMUA0UVSxrZU8MKAVee_PGR1987jwToCcKMZAjR-gJuugdGqsFoobczTs33_jqm9XBn37ve9_9yc_7sQCyJzedtMvF4vTo-Hh5Muu6oR9LTX3fb7bjw82mmcURKCvWqpbUG0_JOXJSbbcbc82mOmtb36Bu8v_7n_z5q5drQVzMJ23jb944-hfeevsbX3v_xsHioJk3YXpxcS1F-jER1r_zu38w9H0gbh0tj-cq9fs_-0UbY9d1q-1qOp-IAJILIX7wwVtf-8b7026CxJtNcrMuxPbRl08RsAz68vlL0xrRe8dsNm4HJC5WYxOmi8nr915796vvi-rHP_7Jg3feXF1dvtr0V9ebOOmW045UD5qmpJz6jIhWVRR228EA2yYuZ_OuDWJ65-ZhE2PkaGRAAIi475WDtV1kZjLJm3Hs--vrftP3zL6O1rXz1Wrz4tF5sRTa5mAx-fbXv1HTuNutytj319ccWuZoeYA8AGLux8OTWxAmH__il4uuO5gt8nYch4LeKSHH1gDVQMXKWLbb5Bp6_PxZESVnzPzm268jquXUzOcff_pwcTDf9OPQy_HNs7Ozs-uXV6enp_fvnh2eLPN6vFzvvvXNb_yTv_7JfNKg45PT46OjwzfffO385QUzEpoRogGqioKIXY5pzKVWRUYtEjyrWUUbq7D3MTaXr9bf_-jLd95-cHa8WG-Gfpu3uZxfrV68vJpNmprTkxfn0QURAQMVG2uuIkTI-JvYOOD-RqyPPv_yb_zBH5QxAZEP_jf3ckbnKWX98Re_ev_rX9_lbAYOgcA88n7K3_oQnW8n0VQdMwHVoo4RFdSMEYMPVo2Um_kMDYQA--SYENB7l6uQY3BcTZnZAiSUTKWh4NVHg6LG4NjYCqQhlZSIWNDGKqIKoqQEqojUhYYAPDEhGRAQk9sTUhEQpzFG50JwjhiIyDMSB--D903XGpgiuuiySIweUELgGFx0npB98F3XIBs77mIMzgWgNgazGoIPTThYToJzkyY2IRDWENx8OXORu2nsli0EpsibsRwdH3Rdszxom66NzrdtiI2_OetiE0qqsXE-7NlGdLBsAMERqgg5REQTDcGHQLNpDM41kdsmMPHh4jD4MGlDbGIIjjlMZy17t-fxex9ccCF6x85U2DslcI2fzrv9hs0xeU-z-cSz80y1Vh89EYHt2zcAIp6cI5w1_v6twzdunHWT6JB8E0eRXcrkHXoywpSyqEyn7Ww2RYTr9c4ADw6Pdrtxtytj1Vfb9VBKnwuxJ3bI1HivWtOY2tiCSpU6nXVdbFLOXaA-J-dg3edc62a1q2aASIFFZLcbKJCgBudC44ckkhUIQxucj2oGQH2S6aRrY-ymoUpFgOC46zozqlWQiTyhIyXwIRjApI0qSki1GBMXtc12104mxK71TRsCoOVaOThAaxXVQFgQ6ep61QXvCB-9ejFtJrsxe6bWx1LKZnf9u199887R0cX1dtiOb9w_oZQs5fVup6gc3bbvi4kK1FoEDT0YlIvVhTr2TZt2IzvStG260C2XSdQ8udm0qkEWAhjTAFiByMXZYrkE0XXRnLc1Z6gZEd6-e5YNr6_XzbTrFnNCllJunN5avbj0HNuJ38qui4gGT1-unnz-rPV-3xwxgiGNREgmqlVBjJ1TNatqo6F3mlRVDQHM8noLZKBGBOOznY4FDawURy6te2ZCVDJAE1QkUxdZrUItnhGKmIGU4oMnQmLQQUjNhmK56igwig3ZxgxSIWVIeY_8hYLQZ9v0kJKmjGogYElqn1DUOdKawdRqAamgClWsSt3uIBdLycYMm42lDLpfixpWsTFrEasVAM0UCTSrjBkA9uYRq0bkSlXXtOOrdR360_tH189WR8tJXm-gaB0zFAEDMEtpLGkkER2TjEmKqojmgsR5VCyujrrbDX7qVSqoKlBhf-srN8u2pKtdG9xuHNmzsGzHIaUy6TqB4Lw9erW7uOpD15AL635ULC5yO3FfPFlT7Py03V6Xdj75rbfOjhqW0SxXNaqG62KXo2oMq5yVoS91U-o66bovqzGbx8vrnRlsr_vtMEL06yKrvqSk4ypZRhJrs-Tzi89fXD2-unxjsVhMJi93eQDdVPPT6WYzNhQKmGvby347a_zNtrm9XBSgIrAzuX3jUFK5XPVoMmv47GB6cbGhiAlqEzg0jKnGJoBzxXRM2Uc6OGwYMGfxrZssArAdny0OlnPztMplcmMyRBBFCpRzacx3IS7vLne9Pn-y_fw6PTxf-bODT5-92gkcnBw3XadjnXVNlVT6XIaxDHnWRdQCIOvN2jG51rngXIzgeTqfpT7NDpexC2HWaGScRPKxX2-B_e2v3Ljz3uvtyTJVdUfd7J2zXaUaW2198ZFmDU0DtAFbl9AssDpsF505bBZtmLRJVZnXaRz6HRhcrDeRYxFFpFW_q2a7XMYsq-0ophidm7RhEq53Y1aDAEpYq5VqY9ZdKkOuxpiz5qLeBcdR1cxwz4_PWUQkq1RQA9qOBYAEoGtbF2JVI3YKWkVUNNfKzpHjKoIK2UxE0aEZmRkagQAzseMQo_GeXOSIGEARLDZxLCMzI5F3LhJ75xnRsQOAIopACGhgwRMxIGApNbJ3xB4JGVMRR8zMzhEzgbHtiRyMaqBgYtl5ALS9JI7J2O-NwiSmjtARKyB5RkCr5Z2vvj8q_Prhx-bY0Nh7h0SITRtERE0N0SGdzQ-OjhY_e_hlVTYAdi7XimRIoGiGQIhTam8cHTx-ce6dI8cIFr1HJDOsUrxj7zh6DoSd98vp7P7dO-_9ztcl-D_9wY---6NfbTepcWHueRH90WRy2E6Ol0tCJkbEepRVS7m_7G4vu9tHzf1b82UXHEEM3DY-BFeroFqtGnycHh2Olh-fb_6P_8l_vJxMht34fLU7Ppgsj-fPLs5vnJ2tdptbN49BhMn9f_7L_67pvEPsh50Mg1ecMH36-Rcpl1zKbre9d_8mIjbekXHrQ7_to6P5ZPLO2w9i45cHh7fuvPbO268DA6rkcailIPF2vd4HiGsF570O463D5b_xr_z9GNrVqy2MAlU_-_zJ1WbzZ3_6p7Le5VwnIRRkVpNUSoVJdFer7TiOKdU05Bhp3W8uLjbOkAgQCJAVTMEAzQyqmKBth4Fj6Nd9YotNWK375eLA1NWhLNpmt5FIrm1CE0Ma-vPzV4jkgn7nb_wLV1fXBvr08y_GlEVy08X7X3nrejc0oWGOSURBVUBKrqiiUquiIUUOLvRj__TJuW-b9W4oUEPTGNA4jq9erQXAt7Pr1SY2YT6fm_fb1aabdV9972svnr34G3_zt69XwwT86uVqMo1ZjFRmk-U4YmW78caBAJhBVS1qtchQ6oRdE2N0LsYQA5MaGoBq18Wc8_e-__MXm-GbX309AJy_Wl8O9TzLZxf9Tz557Ahb9or4008-fe3WzWqYVcv-BQRAIgUsajkXItJiD8-fN86fnZ6MQwlNK1qryt5EG3z4s7_4s7_7e387FzBDRchaci5EDvfkHWYEcM5575yjGJxzJNWaJqzyZl-WC4GIcOL8weHi8sWl8-Cj32P_PBESds674ABMqyHCLuciggaBPYkionMUQ0T2fZ-36x4YichUPaEnhN_oDsUxA9k-JYhgzu1LBI4IvXPMBGZNDCF6JIzRxzawZwBz3nnHbRPbLu7DQhQ8xWCOmkkMITrniJwacAzAHJrYNLGJITQhRi-KkzZ6T8t5Z7keTJtly16w886ba7s4nXePnqznXZx0kdRIpIvUNj56N4g0RCdHUwcwbWPb-f2xato189ksBkeAjrFtfGAIPpjZctY0jiLTrIuEadaFtg1MNmsaQnOEhNA4it4FJoccnTuYtF3bMICKOvZiSozkvfeOiJ1z7BAQDaxpIzEgE4K00c_m7dGN-c3To-ODxb2jg6Np64jIo0ApKZvt5z-wnLWmNpl0jfPBsSHUAgJQQUVhN6YxFzE05NOT41pKSYUEwKDfDofzybSNADCNrRTpx3GoshptPcqrVUm57IaSzYpoEStJU9ZqQITNJCwPJxUsxsieY-PZM5hmqQq6mETPzExplLZrALUJgQm64M2s8X5fVmtDqCUT4uFsamaE6Nwe9IKqez62OTA0ceyeDjsAA9C37pxplafXq4ac915QrrZbIi65vHbvRqoiwzjpwtyFWWz7WrZ9v1x004ZC9AfHMwHKucY2bndJFECVjYddRmYOjSn22910OR9S306b7dU2UvRNDG3bxqZu-j3uip2PsSEg9HTr1q0yZtb6xv3j621_3ffkvaC47lAJC6kjTrtei1hOpNqGVqt1bbfebk9PT5Pll-fnw7AbymBW1-t1nxIGT1IrOqL98F4Uf3MILggCZi54QkRUEAVViKwooNk5UBQ1Mag-NgiEClYKaDHJMhQtVbJWMVUwVUBFtbReo4mmAlUIDFQR0Eo1KWoCKuAUSqFard9YlT28X1I2ACEQM1DRoqBiOdVhlJxADWq1fgDJBtUkgxQQ1VJNBIghVRC1PGLJlhOgUQTbD05NrQJ7D0WIHbFByZgKiDrvHMDqi0djlmEEYnz1-Gq4XDMUZoLGAyKZglQMRoykxA4JKpSMCGXILnodyvb8ugyDsZaasSKGcPb60W7d520fohuTXq16JLu66F-ucwhRqkjNP_n8ejP0rgGeuJcv1yDYBn9zOfvs1y8o4PSomTW-YTic-HEsW4PrWsTjCHUl5VUec-ARxEW3GfVyLFkqeNikej3mdR4rgRr6GCdtI1K9p7Trmy6-6jdxNkuJzg4PzMcv66o9nQDQbqwiYt6vpf7qycsMsFh006775OGj5-t8dnpYSx2qtJ7HkjV4Y_vyejM7WLaTOQj2m506yuy2Ke1KLrW2cx-JthfbkmU7ZKnKLnpqvMPVq90IbnbvzJquEGSz4rA4HAv2mYA9GiITm8cVbK77zdhXy732H_3003Gs7Nz5s-frqxV5vny5AbMmMlWsQ3XE7Jz3rqZSdW97caXI4uAArDbNpCBOuumkaU9v3QgxDJm2o_3xv_zu6w9ubg3PNyWezfFwsRpNJ_F61w-Is3cPD98_mtyarsr6Og3Xpd9Zxs5vaoE2isOxps1u--Lldb8tR0cn3hGz16qAULQWk5QrOlTJkqqLbnI4Sbt0-WJzvRkE8Pq6r2kfu9WhT6lUER3GklRylU0ahjoqaKq1VO2HnIr0Q0pFAvtcSir1augFYMwVjfYpTFVAIOcIDZlpHLKI5JqjcwCgqt4hIQTPe0K2d8HMwJD21Ag1RmcADC74qPsyRa0CwIBmex3Y3kIMRoSBE5hzPjgHiOYwBM9Enjl4b1WdJ0EDUu9IQJ1zjskHB2ienWol5oqqIMEFAjIzJGhcQMKcqsp-VKAoKmP_wdc-fPXi1YtXLwg8g0UfTVEEHDsF8yEoGCJ85513g5THL57sDShtiCpkYmbWtQ0JoOnp8fL6xbWakBoyqgmZBu_YsYICKYI1waFpQPLkGvP3bt996_13leGf_fM__6f_7M_X2-zId8F1Teia5mixOJzMWN3k8Ojli833P336X332_L__bPPxF5us5tDXoYwXu7HPgICizChgPPVf_fCNN45mf-v1b_-3f_Lnqdr_63_4s1q0H9OTF1fbVH716LNvf_gVhTEo3jxbzNvpbtwN4_CNb3wtp7y6vpKkxsIUSq0fvveBqVTcKyx0148lZwRUqaUkFVyv1__B_-k_ODo8YLLUj2DV1LrJnH0zmI1m0IQXq_Mbh9N3vnL3_ms3geUvv_unZ7dee_70-a7v-6zf_NaHk27y-9_6xldu3F60MyYgwKOD5dnpodQ8jJunz56lWlerbZLimBw4-P_x9B9Pt6XZnR62zGu2Oebz1-dN76syq1CoBroBNJqNFtQNihRFKaihRvqDFJopQiOFBgwFFSSDTaOG2N1o2DJAZZZL725e893PnnO2ec1aS4MvqdkZnYgTsfc-a7_r93seQylCSM47JB3nyTGzj1Vltbc-Wu6PUkPbPbm8-OM_-sffnH4T2-beg5cTApNb9n3jXE-BqB6uViH4btUtFiuz-vSLr1fHB9vtxGAvv_Zy08W_-nd_p1UXXZzGiRluxkFkxwxNDAiYCixPDtuukZoWsVMzU3v97Vd9DF3Xj1cXu6vdOMxIQMzDZhcXDah--ptfPT19_t_8V__vf_vvf8pAb73xwvVuJ0WD51UMn391ujkf_-Fn31hRU1MzMmTH67Zp2siEBLa5HlaLLpsJ1Fr0i8-__eC3X7_91uuvv3RftFxdTRe79Phqenw2DnMFhof3bhUDBEpJDg_WYErkSipWtIpWFQMlpmpkhI7pg1_9-p33vmcqU577vmeHBESOnA9fffs0rJuDk4NUs5m1vvFA0XtR1apEZKgGqmZg1rTRMeON0oDdSX_AaI7QOQrOnT4_R0JPXKYCYFpvBMNWSt5JJgNAEBVCcmSqRemGNGbMaGQFFACk1pRSGYuJIHGpKmCApGDGGGLw5G8m_ei99zdGMvbeO8_EQMxtE9CgjZHZMTMANk3jmPqm9c6hQvQxhhhCqAoxNAjgPLPn2AUfIzeOvCPHrgkKEGIIje_6GEPo2w4A1nuLGFpVFxYNALBpSRWB51T2V50HWPSxi7FfNiGwdy56bgNHx8tF75lb5_YWrTPyhIGha3zfNctF58y6EBtPXXRYpI9NE9yya7oYGxeQqG1iG30bm0XbtG30wTXRx8azo6YJldA734SmiRFM2y6GLvrGhyYgc7fwIbIP7NiBgne-aZu91bKLvvP-3RdOfved-6_dP3h4vOwclarDnC4vtwpWi0qWnMvTsytyGJsbLwWrgjkap1yrziWj4-t5RHCr5XIYJudCVZnybKB37xyyd1lraOLp5eZyN2WkbDZVMYDtbhA1BdzuxrYJqioiorrseyU_TxaQpUBSUYNcChqKat8vb9plaARqZlan1PrIBlZqYCLClGW7m6pUTy4yXW-30TkpVc0IgQBKFWK32Q1SaxPb4EKuIgpZ9GDZvbZ_YLVuy_z4-urkoKtzEYWT_b3lsu-75uzibLmMyz7--N03nOfPHj9VM9_GVKSiNfv9ONVpKmLQdkFyAQVUrVVyElUJwW_OrxgcEt9wZa_Ot2jcde20G9quk5rRkYDGfukY1nvrW7eP85TyXF48vD1ux9OL8-X-ahyGH778mij5Js7DhKJM5HxEseP9e3vdOkle-MWDuy-KiCFMk3x59vV2MwCTOf7w118RIXjvTMSKeu9BDbVSLShmouRZS9FpxiwwFcjViphgnuT_bx4CUSBAJnRBBKxW51hyATR0AGpAILlqVSbUuXB0VgyKOFMsQipYDdUgVzjdkapNBYyZAIgAzatCERLDuWDOHirUQlVQlA3BzDlgURc8icGUGAARYC4wJarauB7T7FVBhVBZCg4ZVUEqejIwDkJoVlKdCggCQqk1Zx03GyJaHO9fPzv1gcpuwFycMhTgJE6Kpmyz2aBqYiqQi45Zk9wYNVwkapkIgqP5cvRtqGJmvkz16putiQHixXY6XHV5Lk8vh8DucL_fpXI95PPdrIgl69mz3eYywZwXjr744vlUbNG1HVpkQ8M6F0DaVRUkI7qeypPL8WrOZ9thmhKarle8d7h8drE9vRpnsJxlvkxQ4Oaxla7TeJW3z6ceaNqkvba7GjYnL-zFpv3UxtbxK93-uluKaXWUzIa53D5ePVivyNTP9dPz7e-_dq-MuQ9NKvMk0yi60fqzrx-fboex2Krtka2I9MtmLhmdG3PdTAVat9mNaZZhO-d5nqfStGFMyTEVgruvHhye9NT4BHZ2veHOba9ScMEEAhB7x8G7RTtilkAQEAhajt9_4_4P37zd8KQiYiZZ-70mJ1GEUjKo1lxUrIpy009jMrC5VGVE05SkIBJh2wXvfFFIpfs__J9-8Dv_6t0PH88_2-bF_VtHL57gqk9RcR-HeYjr6PuQZri8rLtcLbjaOuhjcjzUvNvN15sppXT25Gx7PTJpXLjzy0tG8-TIQIqkUqcxzcMsVS-eX87DWJOmq1lSkVpSSttpJkKxgmRzzqVWqRUApFQDzFKr1t04TzknkWKaRLNINiV2zy43xjTN81jr9TBdj-NumnbbMRedc2V0nqN3Dr_L9txgqNl7ZnKm4JxXUSJCoFqrY2yCdwjRe-cdM3jn1IojdszMiIQKwI4du-CcD4QO0TEjoiIgqZpzHINLJQOYc0RAgOACmwggIrJoDc6z6k3JjBidZ88eAT17U1KV4N0yNpGdmRG72HjvODA7z8BAai6XH_3Bjz_-7LPL7YbYMUMbPIMhgwHWUpGdqtZ5-P3fe-_58-vtNIqRmToH7Dw7KkVc431wrfP7L9z66OMvkInM_M2ZIwiTQ0BRM0MAYwZH4Bm8Weto3bQvvPDCWz9637r-f_z3f_1Xf__rq7EyO1AVgeBCt2hXy7U5eOvBnd89Pnh5HS_b_PPL7aPtXACOb-3fu3_Stp4DoZrmshmnB-1yYmuX3Z27d9umn55tbh-dNDFebcehyL_-7__t3aM7Ttzesi1jqTV1zWK7uf7-2--O4_j16bPo8OT24TDuYnQNhFzKso0MGFzI48BsIPXzr761KuMwLpar4_Xh22-9nkYxADFlxz56MGNuXBOBEFAvr66WBP_H_82_JBBM9VcfftD0_Zys6-LjzY4NP_zi88fnp9c5JdSzq3MDWS-bvYMlgV1fX3VNu2qCgYXgYxMc-ia2TI4qkMFzu2QfpBatAGqLpn_yzSPnw-mz871bx2en5_defIHasF72IYRpGnKdFGS3G9QKmo7b7f2XHt7w2D774JfBsZRyeLh3dHL09Tdfr27v1WJFlICIkIjYOyYkEC11tejOTqduuXj06Ck7F5iDdw8evBBimDab9cHeL3_5a-6a58-eNSEG7w-O9k6_fTpcb6HqO-__4K03XiioP3jjtY--fdISGcGyD13rAtVfffBrY9lMcwKbTYFYDMBQkZFxmHPXxlTlepw__uZZFvzx-6-R6PnF5tHp7ovT508vN5H90aLbW4Td2WbdRFPYzdNiHVVEBMZa5loUtI2RkKvBXIqiFZWreazb6fVXXi1SyXlBQ9FAHJCy2q9--ct_9vv_uOzmUgUIqyQRUQUCDOy1KBiE6L27IXCpd9x3jY8eyASAo79RhBgAMivi2---wkw-elN1DqtUNcNCWLTlGNmbCrKv1VQMCJhdFQGievMuT7hL81xLUZ1yqmBFxG6cA8WkVkfsmU3UOQeqBASoAMZMVeoNvtAxesfuZuVGAGDskRmIkJiJyDv27GL0bePbNpoZIztkz-TIdW3cXy0dYeM9msUQELBpw6Jt2uA80aJ3iy5GDtFFguoARCo7ZKZF47vg9xadB-p8IMSC6hx7IjBtvIvRL_um60MTfSAMfBP1geWyaxp3fHtNQG0Myy72Xeu9izE4T8u-jY3zjlrnWueh2rrv2LOZMGETPQN6x8FD5130zhF55MYHYvLeM3oDI6K2CU1069XCM4QmOqe_9_1X3rl_7_56_e5Ldz1RaBhQp1JKFWZWk6nkKkqATQiR2eGNxQHnml0Mw5RTlbHWkm21t86pSoWL642I5Vy72JjgZkxZ7PnlFpibvttsppSFmOZUi2oFEK2r9aKIimFRJWZjX2ptOu58s9vMfWAODlTMjNnVWprGIwMxcPRjmoIPAEpMjQ85lVqLiVapIopmPnjn-bBfmCCqjeNoCGOe55KSVCLea1uRaqqrttlfdi8tVsGazVR_8c2jPeZF13387elYy-Gqb4kg5zSX2wfL223XN931UHfbcbWMoBDQoosnC68F2s654IoghQBNVCZikpSXbTAzbzDsrhd7K9cE34UypmbROecBqWp1IaL3xAwpN2179fzq7p37m3Hnkfa69UsP7uwvlxfPL1DscH8_z7nOadF3jJxzEdGsNaXdraM7jx59dXJwq2kWV2N-en6RtR7HPUAy75Tx9bceECDKnMgxkqlk8o6cIxNGBJU87BARDJiNEdE5E4VaWc0hQhEpRUsmEJVkVtmK5FzLHJcHmpQdA4KpAoOaEROIqYp3aNXIAWlxRAjAzhEAKTAA5gLjzGZQKpbMJWMVKJUQHPs61ZYcEkMRVGFVFsEy8zxhSjCPqMk0IQmJQM0iG1TRomzoquhuhnpTMiFitlwliRQxQNcFQwFG6hpF6RatIk7z3PXLeTfUiy0GBy3LPPtcYDtTVpACpFAz5AQps6qJMWHdJaxEYLrb6W4GkqJSssbjZpdTv3ShgedXg6Fd7sbLqSgxBv7m-dVVmp-eXl5vdtSKMVxd7_plQO_Wi-7ieloslqLmzGqB59dpEpoKmLE6V61ejWUnWgCmKtnsbFfU0eV28jEI6tV2GjZjTUWssi_b6125moEY0ZY-tIaxW5Rz3bfmg08eP_vNk-O91YKppjLlUkTOr8fNUE72187Z0rn_8hef_NEbDwUkMqR5fvL8Yqf07Xb45ZePv3hy6Rdhf9VO48BAg2hkl6ttpmxIyjBLOt8NGayQtMt2NihUFWBMuXgj7_YcXD7dkkomubrYWUFmLJeTjtqtl7lKup6OFy2yGwZYhObF-w-c0W6zuTzdZFFHNFxfjNvRSK-nOc8FnBPSCiYESkoOEFBAu4PlLk1h2aV5ZMfPL-eZI3P4w__inQ8f5394nOeXlu-_8fClo8X37-45KNthN1-P5LF4VW8UNFkaZR5JJ5PqsT1sZ1OMLtXx-noH5JCNGzdcba-ur8_Pt5vNhh35GLuuj44WfSxpWizXse_6vYWUgqZgVnItqY5TcszbMaWiyKxqJasYTLmkWocpIXMq2QwEYDfNKphz2U0zAOx2I4dggGPJ41w2uyHVgkxVIZsYaYhsooTgHQNiFSWm2HCMN6065x26QAZKxGaqAjesHkQwU0VUkBtVJSJUFReDqCIROyZkcuA8RQ8OwHsyMDNz7ib9726YFYjmgvOOCSE4z0CMFMgRoXOu1MLMnllUmhBqVbiB8gBE51XVFByzgkIVFxhATAVF3__hj37zmw93KYM67130DZgZgJoSAjKSEczpx__knY8--WyyGYiAUFWlgoE4BWJUsZP1KjOMwxCAgicfgmPnCBCw9YEYCOzm8UWqjgBRHUNg6prw4osvvPnuWwXp3_7lT3712TeCoSJOArno3sHim-uBG9d3cdHGF3nx_aZZORtr_uSbZ7_--NtnT6-fn22_Prs-u9j8-tEpmF_04c3XHr7wwr3VcvHOK3eO1otV1_QIKaeDo_Vqf-_J2fN_8-d__v1333r09NsY4m6eXnv5IQL-_Ne_aX0cdpeaZs726UefzaWM0yw1gWkpRUUZ4cuvny5aN8_z6mgPsvzHf_ZngixV0pisCojuHR70XUtQ05iW_fKDjz8qc_3e26_s3TqoJpvNnMF-8euP77346t_97YdMdHmdn14-36a6282Pvnm22WzMDMgOT_ZqyT60bC6nSkZMvJ1SNimlqFTvvNt1TRtdbPp--fibr-_fu7darkQ1FXl-cbbZ7O6eHH_vd74fIrSOFiE0Hr__9tsv3D7-8Le_8t4T6-_-_o8uzzbkfXSGAARkaif37jeL9rPffLw6WInUEL0BYiDnzCGRmDNg0tNH3zDrP_z9r6ECKMYQ9vb3fKDt5RUTnT87M3WKFGLrg_PBK-Irb7380huvZkmX52e7YfPiC_cvzy9Xi6akKlUO91cO3LzdqG8t2TDVapxr3ZW6202b3TTVcna1cex_-eGXv_nk2dHRwcmd4-fX06PLy0fnV2ebnXPhhTsnfYhIWHNxxOCCsZ5db168_2LKBdAYycdQqhEhMbng0NA5j0A__fCDhy8_DMHnXELjPTokFxws-v7nP_nZj__w93bjXMSQXNNEx-y8NzBFEBFCC959Jwz-TvynnokBPVNkJkDnHDnfRGrbcHZ6HhXmUoP3ABYcsyM04xurnxqj3bhsyZkZqJqq-hARgQC8iwDUxg4NBaCKApPcaMbAECHloqgGWsGQUcBU9ObdQ1QI3E2iS6qKmKqKKiIDoNwwBksREEOopsjkvEczJgeIhIBosYkmumh7UGmj7xdN28blogOE1aqPjUPEGByaNJHYxBF20TWB99fLiiZS2VOuFUACg9TqHO91vfcusFu1TddGRlsv-0UTu-DXq27VhXUbl1276tt11yxdWK3b1TJ2kZddbJvQeLfsmxiddz5G13cheIyNV5C-ib71q2VDaK0jEyEkNWmC84gEECPH1vdtcEyenHPcd330zjFGz6Hxd--cvHTrOBLtL0JgBLScUk0FwIDoepwVeb3Xd32nIt5zcCwlVdPzy6tisJmmrAouTPPcr5eXm81uTs8uz1brZa3SxEjkUynjXE7Pt-Ocr7bz6fl1RWBHY8pKwM4hY1FxQEyci3RNWLRB6rxaNK33o5a-C-xoHmf2QcCC9x4tEkbHBDinumr7tm284yZGxzCmxMBFbJNHx8SEzoXQedGqUg0JkNRgm_Kc8rPLi4O-aUBAxAVnSoervTQmULuyfLxYtl1fhPb2Vu-8cv-123e2m126Hpc-7C-Xy9BmqGfDcHG1OT7orzdT51v2_Nnj7XaYDg76aZvQ1MzmebwcxzTmLngRcOhiE2SaD45X3oc81RBJx4mcqUiVGrrWsZe5Ssknt-8gMoA8efZ8f71oyBjNIT98-AIDr5qu5vz4yRNSnEth38TFgpiKzrtymcb5nffeTimf7y6C87s07h0ezKVWhO00XQwTAZpUUDWptU5VkWopqKKpgBkiqQrWUnejoZkz00qg3jvNFUG1ChFKElM2BcYQvNNsOm19IJVKBGERNVVCNMNSqhmk7eQdym6SIUstKga1giojlu2ODG5UepAz7rJMVc2UAcGsJNI8ba8NtZYMoiBaUoGqMhcrSgiyK5DBipioTlmGAoCmwI7AwNIMWpGpzgWAEBGqAAAiYVFWMwUEYLXt0-cueklpd36muUDvjWw-3_kF1DlBUigFoIJUvRpQRHKpcyIiqUKMJqIlY65ISKHRoeKCy9U4f7tFssvrXa750ZPnTy-3k6hvY04l1fztN9eOIA3zfF2m7VjnabMbhOWnv_7y8HAZPE9D2WZ4_Pxa2SpBNVMw0XK2K5uppFrGkmYpQHaZ8jdPh1xAAWoqlifnbEppSNM3j7bbcZpD2c4b1bobcyCkAiyAixhv9W4Z3zhYouJcSpGyneYKeGvd12yR46PL3e-_fiIVIvjz7eZ6ntyie3S9-_T5pXKYjNi5g8ZfXlwr8_VQTq_HXOV6mKZaY0Onj65TytlknPOm1os0f3u6nUUSgcXOYvjoaVKVi7Ph1t3FPNeys-li2j-KAnB1ttGqy5f3n5znvEuvvXz3pTtHew3vcjq9zrMgcyQG50LoOnUuF_V9t3ywVwgKgAEiYegaZI8YiJoQm68ePb4axlHNjrr97z9463svffKbyffxT967_0_u3t_v6pGTzW67mbdDElU01bPLnQWd5hEdjKWq1qqSiw7Xk6ju0i7XbKgIlfqwG2eMnqMrIGqWklCIpUipysRtu2Cmpmt315s0plKKqmgRk6qi18MsCkjEHtVMCQwp1SKq7FgMCB0wTnPO1VIthlTVUpEqyhyur8aUq6iNqVTAuRZTnaYEQMRY0QBBTREsOI7ONd555xxTG4Njh0DRewZwiM4jIaKoQwzBEQCSV5MuBu-8Y6e1OMeEBgpgYNUYABU9MyMwknfkHcYYpapjRjPnPBOCqUcyFUNj5GIlOGZA771IdY6ZGdA48M2qwXtG1rZxDtFM6KaUXKoiGQKK7rXN6--_8w8f_H2tykCOkc0xCBKNaVLAKjUQL6F984cP_-aDj4SZkBhJVQGsaiUlBvQKb7358JNHj9ERmTk0JmYjJjY0MQBGBVOTGzmoR3JIbeTI2Ht_tF49fHDvle-_frGbf_HLT4apIDtgOwpxe_HcI7FCJMeBzcVAoSUfutD3YVtrNelW3fJ4Ueb0Rz_4_mp9MIzjF58--snff-iNHJkK_PD7399cP2_ZHa_7O7dvb7bDvVsnu5yGPG-fX6Qqz85PpepY1BF-fvrND95__cuLxyerVQweGAlNaiFmU_xme1armNWDvRWB3bl76_a9O8zsvAMV71hyQQUZi85VgD795tFuu3Ou-d__2Z_62JtWg3B6ev71t99W1d98-tG9Bw_GIVuppuydCz5oLX3bdl1bRA0xBCcmiEQ-hsYxY9NGJHOO1k0IIcw5rQ_3HTXoseZ6cX4BgLvriwh-_3Bvr4sRQIv0bcdkB_t7e_uLzfn13tHtWiTtdu_96Hs3NrFpGo1Mkuyvjzofv_r4i_d_9F4g55sbBqKyRy1TTbPVWud0dXH11jtvf_7ZF03LhAhqnojBa9VpOwLZ5fkpoZuGARTvntzVmu7efpCn6dMPPjp_9GyYcqT25GgJWlShlLTuOjW9HNL_-G__7v_6D_96l6ZsokQgqmY1Sa3qmIdpZtDXHh6Vkp-eXjw7vbyeCnl_cLC3f7ByCExAaALg-4gIDPz86vTl-3cRkIBEFVWD90wsorUIIwdiRPz6y29_53d-zEBFVZHAxJOPTfv4ybMmxmXfVxEjNFOpGQwcsBmICUUmvpHjgkNGxFST8x4B3U0un4AcO0eBuQveS2XDNI_rLlgpBND0LRAYWtYCBCp2M46jGTECmxogs4iAoZqKVkYiAFNkcCXXkrKIIGJKFdkn1XEuCjylmmoFIiDIVWoBRLoBegliuXGfMxqigTlHaODZhRDnqQAAGCqAmSEzMvrgVZWY2TlAUKhiNqWEDKFxIXLfNQDWxLC37trWEUMTHYNGj_2iXa-b_c6vIoLKumlCYE_QRO8c9J5jw2riHASHfXB98F3wjqFrQxvd3qLvojtcdIer5f6qa5gOll3btSG6rvPLReMCgikTtI1nBAAVVTANwQOZ3ZxWmAHcUCDRxyBmiBajb5oACjeu1K71iyZ4Z8ysKjH4vd7_4JUXOqTAlHLe7cbr3bwZ51FqFVBFDm5_6VvnpVTvQy3VeSxaZylVpOTC7KY5jdMsBtOUxiHlUtu2mcZpteqO9ve2U35ysZmrjKUS8zjN6Ghv7XdTybmYmQsupXzn8JDZ5VyZUA0IAVTBTBE3w8zMc85dx85RGxyhISEQnQ_Too97fbO3WphWR6xSS61iimQGGjgg8qJdzPO0poaAEAGZU627XNhoN4wB4dayN0AjOL_eRNQyDm0I13PxRA6xiV2tsN-tWuVcy3qxOt9u33vvlc3VQMvu7z9-9uuPv10sF98-uTYxZCS008thf93ADJiLpUoiHvDq9LxpWMHAVK0SsZmdP3p-cLxHnvt1f3V-3XRd03XgvACFvjdJfdtfX-2IyDmeNruX9xal5CWFjvzB3qpr23EaQcpHH3-GbIDsYsgplSIhht20uby-2luvstrjJ6eujeT47TdeI7DNND85u_zmySMiQ1ABMHSodVAydN7QEIwYTECLkmNWYRFMBVJGqWWa3CpIKgg3UPBABFoqEICYI9CqKgZAUoyUCRhUQYHIIVrsQx7GwGxqVkFrgSJQREt17LBWZ6a74pEhZxMBMxCzrFBVS2FjUyUzNDQRNKspsQMtCcDo5hYWsZSIFXMhM9QKc0KpAKSliFQAQBFC0yRQq5aqOVtVUHHsZDcQgmtCCIG9Q1UEsFTABBurU1JJyhVUwYBbZ-OMpYKaVoGb007U8fmlGigTRgeInimdXhHrbrMd5ilLrl4yWAUy0IplyGm33SgYUN1tBzEhBJMqSecxo8fYYQG52E7Y-KnIdiyV4Pn18GwzPzrbXKYsRLUaO2KQYTdWqVlrStM8z8MmpylJyVRAdoNLs15NeJ3r2a5MWg2bhHf3Fk8--bLs5n_67os5lyIZWZKUXS6BaK-JjenTq-2U6sHe3tHecjcVYD8QDwB5EbhruXP3HxxZou12u1j4XUpXOQvyam9xcrS2mpvok6l515-0yxf2zTNITVW3Uvxe47yFWq63u6nKm68tfvPR83ms4MT3HtDbbIsQnenpb0-N61sP7txdLTjAdrvZXF8PuxEVCKfp_BoNY0TMJU9FEObr1O8vqYm-i7FtuGn8Xji8tTePI6J7-bVX9-4cJYC9W_ttG_7m8VU4aNerPb9oRpGzrB9tp19vdxeKQsSkqOWlk8Xpb8880bArYLQ-WB7e2mv3ekCSVMlgt6kk6Jft3rJz7EAqqnnybfSLvc45jE148PDu-mgvtpEdA5qWamBGVFURsFY1wFKVGVV1nGoRzaVud9M8VwWYS6lFFXHaJVUUlSpqAM5HI0SiXGqpstvO5hjIZ4VxKgpIpIFonopWbEPw7NoQPVN0DgzEjPl_MQo59P4GEsUOiZEQkAjJrGsbRmDHosZ2Y-YlUHHkvGMmDM45YAT032mT0RF5dGgWoouOI5MjILEA5Nh5ZCa8wZcwsHcuEJNzBubwppcMBGBipsDMBMjM3nvnyEfHxIFAEbSq5Xp7ffzqK6_97Kd_DUgOfRscAZkqE0rJGEhEmex2f_TavZPffvQRUPTsYgwGTIzEEKJnRlf5we2jX372RXTsCB2Cb73zxA6bhpGw3mBJbkRogGRABt5RdBgY-uCP2-VrL96_e-vo17_56MPffD6M47pfbp5cgBISsVl0bhndugvrZXe0Xu0tulcf3Lp3a0-roOi6bY7vrBzwvTtH4-XVf_f__cuzPD4_vzo_v95ut8N28703Xvzy0Vc__cUHx8f77TLeuX2ym67_9J__k2G4_vvffpRFX3p4__j4jqg7unXw5Opqb28ZmsYAydGqX-yGcU5TqAwcxnG8dbBnKMHjCy89VODlct00zbDZzNOOrECtNaXri4u-6f7yH37BRn_4R7-33F9WtbOzZ9t5_OrRabdeXpxvrk7Pbj843g7b_f3VdhgULKcybYe9rjMDYnbBi4LRjfnVp1zIkYEyuehd03emSkrGdbi6XDTL0-dPlrEp07xYtkerxe7i4tnTp3fv3mobX6S4hn73h797fHsvBOjaRmt574fvicDTR9-uFotUStoOi0V4873Xd9fbcTON48TM1UxViMg1zkiINU_DcDXsruYqN8kacAxd17zzzpvrZTuNY7toP__4sxtKVinlYG_d9_2jb7-5vtzefnD7P_nf_qfj9vpse7lqF__-735BAk3fHR8esXe1pO12-68O3-9d1wV2SOQYv7uD6kdfPH56vinOnW2ms4sBDfq-O1kt9haLwMw3awxQYsiS91bLUsExnT3f3D26fdPpcXDjDTM1dUSiJiKq9fnFZr1oF12sUmqVtg3eBYfGjv_qr_72-z9-P8-pioJa68PNMCBWkdAFH5rGe0_sfPDEGLxvQ2Qmx-SdC4xNdCFw17muc2_c2v-Pf_Tui7eOr4Z5ShmBTCVNqWmblGqVomhV1dSAGIhLFQAzglIzEhiagc2pFBEzkKo1pxtTZBXNqQpCrkVVyWHKiRGqSMqpqiGggdRaa6kheBRAopJqKQKItUgVVeRqRgjOk5qBAQjUaqVW9KymwTutAqIEZIDkabHoEewmceQd7S8W7HnRNQ6hd7Hkulp0ffT7q74j33rtkRVqJeu9j961jtdd3Fu2vQ_H6-XBsu8crxp3-3DPod49Pthf9qu-3Vu2fRvWq9Y5YKIKxshEFEJbi45TmqZSipZSnSM1LGLBO1PTomAUvQOFvo8-uCY4R9T3TdPFEHzXeEcYg--7EBx1gcnMEzJC6_3eul3HcLjozGxO85QyeUy5GCAT3Sxx81SaGMZUABk8Os9aRarWIt6HnCSL5VTRSIvmORUVIOuaVsUQ-HKzO7u4KmJVKzKMUwEiRtpdJalVRckgenfv-NgzKZjzvu39d3Y275g5EC26jojaGBvfENqibUE0et_28ZUHh9FhH733FNuwWjZN8LUCEqJCLWqE1cQHrpIPmialxAR9F8j7LKoEbePefeV-yw6kAsqEte-a7Xa6LNk3OG-HPKTY8DBNrx7tY67Tbvr69NnBql-F2DbNF88uha26Ehbx8fnVyy_e0Vn6rn387GLK5dnVbhynqjWrTCmtmlazaRZRrVV20-wbt1isarajk4NcqqpcPb8CIkYGtDyPvom-8WbMoZ139cl4-vR0w0hdFzRPx3uHIfrd9eWqW4Tg29gTU0kztY1jCo6fnz85OdxP03x-daZWEk2ro8U7LzxYdF3XuG4d_ueffUiiAmgmClWRWk3FtCI7zQXUQIWiUxFQ1VJtLL7pmECnYrOyITORI7hx9gComYqWlAARAE2qaUUkYmLH5JBDQCUZ5hgpbbaEZrWiolUDNfRcU_kutEdkUkgUCqAAeQQT55DNPCBlZUNUJVNICVLSKaMZVWQkSwVSdaqclRElZVQBUaxG1RAIioGo5iI5WSnoGRCrqlTRInWYwHtzMQ9znkZJVWu1KSEDVC1nGaYMqrATCA6uk2UxAwBjRJCqc4aq3BLNxQcv5Oq2OHb5egIC3Q5MKNs0XmcpUAwY4fJimie7OB8AcdrOVsyKlKmk3cyOh-0YQsPRnT8vqggMV7u5qjLB2cVuSPlinmcCxboZxu2c51w_e7oF1CGX3bibpzwPs9aiJiJikhof8qBd2x_vL5qW_JL3Xj5ub7fdui0Y3nnphQg-TyJWng_j-ZBzNUecxrSbinmOMXaoKtWkxrYDol21EFy3H5ZtuHy6-53XTqzqda7nc76c5qS2Cnwr-v0-Xl5spcKdF49Tlusn2y8-fmzBD7V2e6vdjBPgt5NuBcdW_u7TqzKBmTW9TyrDXJoIs6bJ0mo_Hvfrk4ZrGh9fXJ9ebKfr4jMtO4KUuoPOdf70dHN-NfAiGBoiTLsZ2bngFYCdJ9eAC6Ft7r5wC0hBrFsvpnH8m59-dHLIv_Pq8sEeLhvbynDu5vMoT1SmSovASGZNnGp9-e0HB8cnD1668857L6y6tqaqIgVk0LIzCIdNu7eolUTx5HB9sLd3cHCw7LvVottfLVZNPF6vHJADV4sAwDwlIyLv5lKyCAYvjMBsBqYwTHnOkqpVwAqaS52mjEiKOIzzbs6b7TilmquYmaqKmRohU5FqZNWsMoGjVCSVihSC92bQNw7MAC0EXi374Fz0vou-jS5GD2aOGQxi9Df1KkLznhAwBE83St8QkJCMYmBmcrFRVSYKzuHNkTgCEsTI4QYe4Th4F4MzAOdYzcg5DoyOXHREJGDGmKAYANHNOoKJ0DE5x2QQAzPefAjBk3dEQCaGCgbmmTiwgFKpL96-d_vl-3_5s780Qu-o8YEACIwBpFY10KKo8PZbrxWFbx9_a8BgKKpaxLQqVGJi0oPVmgGHmgnIOcAsgdATOyAm13kPBGjkIzuP_J0PDRxxcC56ah31wR3vr37w7psLsr_88w-mlL46OyVSh4qMRIgAN9VKJus77xBLKqsmHu_3y6aD4Pq-7drm3Xff_OPff_9f_uMfFy1S5n_zH_7Dz_7-wx-__z2r1LfNs9Pnzy-eNYvwkw9--S_-xb-os_z2m2-med5OE4O9_ML92-tm4WPgcFOimNNcDeqc_j-__tnv_c6bApVND_b2kRkQ_vQ_-sMmOM9IBIt-kec5pck5mKdpN45vvPrm3_3yQ0n1eL3_e--_TQK7y03J5e9-9vN2tTRPX339xfz88oV7dw72D-_duefYD8M4TyOAOGJsGBmL5AJioM4T3uBr0BWRWgUdO3bzPDqyuW7XR_tff_X4-PiOmbHUvomSx7u3TwKZb8C5m_WRPrhz-_LyMsQWQUAEGZn5008_jW2bc-6amIvcfv3B5fmz3dXGAFNKSNyEiKZgwMjknY9h7_b-g1fuPH70dc2KyKR6fHCYcrm8uMQQrk4vyQUfffB0eLRuY2ib5vb928e3bn_6-WdfPHry-PRxEPw3f_Pzg73eO7dcLLuua7suFdm_c6ddNE1gBkMTUqumkmpH_v7tw4ODvW7dH-yvmjY4ZjQAsxvoFoCCAalt5zn4oKquubEeATMDKSMG7xofqlo1KTdsD-f-w1_95Q_ee5-Zck4-OCL0bF0f_8Nf_uR7P_weFEVwN0MdqJDaDXBLQR1SuLkxvTNA0QqgTesdE5ByQNd7Ynt4d_2f_M7rf_bWS68cnTy72v1P__Dzf_fhp8ABfTCjOcs8pBjjmOtY61SLoOZSDADQ5aR5ToF9matWswoIWER202QMVcEAi8Aw5WJWiqQpz3OpBaSqCWgRE_DsVEWrlKoGdBMWAkUEs6pabnpTggg5y3cxUEAgMDLnSNHKWNAwpYxIChKDdx6X-x0zxhA8k5nG6EuppBYI91e91kyAwfOD28vb6_bWXrfXtHvLJle5HKa24ab1PjKprJp4su5P9hd7y-5wf9G03iTvL7s28MmqOVq10VMXPSNut_MwjGYwl5qL5FLmXOe5eu84uFJt2M6AgISm4AIzIzsghzcpF3bIzpxD5xBAmuiZiQmWiwhqofGIuN7vvKdFH7voyWCvbRvmKiV4io5M4Wo7VtXdkFStpNwtAnsqRRU0NUwHdAABAABJREFUT7UNQdW892nMMcY5FcesSEWqGO5SNtCubX1snA_bVJ-eb4BpnPJwPdcs7KgNzjtOpRJg13dcdS_GvcaJaBX1wZFZDAGAHOK67YP3KiU6Wizarg2rpglkR3uLg1W_bqNMdTumlGvJ4kKYsmyG5D3nYuidc9xyjCGKatqlo_UKAJmw5JyrTGl2gAHcOnaOyQiTyDimJxeXV-PQL1p19Juzq7iM2jRq0DvbjDksopT8T95-5V7f_PbL0-vdPCfJSc7HtBNlwlzx8Xa7y_NY05SKoUEgIWPPSx-mzRYdjvMcmpBFRGwcZ2NFIqm2PtxnREYs08QKoOpCqETAvNpvh2F75NaZqVptQlgs276LnlyuJbZhdLpcLdEFBVvePtjmtOxWjz77Zm-xpLZ_dvo4kosxvPXgAQ953o7Z8SePn_yrP_ldUgVwhKbknWNkNSbWWoGRoyNmDt7MAA1LQe8gz1aF0Wyc0AzMcq5KgAEhsCGZd-idSXUhgCgxljkBE5IrU_Z7HQesSZrDIwIAUwMzFbyxjO5Gx1SGCUTIk5ZCpoRABjBmq2ZAJFXTBJK1Khpwqd7MOw8CaIZSZTsSm_c3mwRFNVQBNZVqamDgHTEClMqmaAJqlotKtlpj35JRycUvl4CCVqlWzDPViqYuMpjadgJmM0IT2IwQQBEgApuWXSJR75iI8-kOvYO2gVqJwTtb7Ds0A7U6TdR6qZmDU7PtlEK064ttnjOAAhEHYlBWULGW8fp6F9ZhNhzyrKRZs4FmhacXuymLMl5t07CbKODjsy2pmua5VADNmi2XcjVbrmzKQCglX89c4bXfefWHD-7a2RwltODz493FpxepyNv3b-8F7p1UKECQKuzmaowGWkAq25zqZjdeT3NWvZ6Kgqmj3VC-Pd2dnQ-12O2D9bhJPvBO5MMvHpeUh92YZ7sY85tHi6urYdHHuWRyTei7t9-7n6WAd1fjNh7Ebr8bilBELPr8fIOOkd04F0NEKReX12nOrV8ee39MYk399snz3dWYUmkWnhoHk987PILQjqV2J0vuvO-51GKVpJJz1PW9qAFjAWzW7Xq1fvT4HCmQcyLpbCqv_fCFl-4eUCpQ6oXWs-vh4nx4_u21Pp_22KLA3nL1Z3_04sPDk9dPDvvg1967JCVLKqKIi2V369VDWPnNZdpuNsFJTnmcSxZQYxfjlKxUdOQ0q9a6udrlLIjASOw8AC3b5YP1SUnJITFB8GSiLoZhnqdSdlO--a8sRedU0pyLakqFg0MGFZVq0zw7F0yhVE2lGuA0FRGVCsgGqG0MITIzOUdk2HdNE33buK713lH0zhN5pEXbtN45IiYM7LomxhiC56a9KZZhEx2jEXHoPDPdHGi3bSRCuBlkHcbgGZGYmCgGFxg8A5o1gWNwXQhECITk0BAQkQkadoE9ITi6admyjxyCu1ElO3LOETN7dNE7Imq8Y0QXnXfOzBwReZJaTcvrL71y-_b9n_z0rwX8DSwPjfQmMxxQVUCrpfI7P3r702fPZhFAis477wjZATsmVDLUew9v_fajr8B5RvIePcKNDhkNbqrSwGZoNw8xNHVIiEoA0WOI5B35yG3bvfP2q3_6L_8RO37y6VMAZUAEBbObLyEDIjIBRxxjg6aXl5MDbZkkjZvNdd-2L7_44OHxcSR_vFx9c_n0n_3B7_3yb_72X_8Pf_XivVs_fv_dq-txf3mQRjNxF8MkSduujb2_vNq8fOdwLHTQ32ABsWXXhbbr2-UiDju9uz4wNfbuzu3bIlqrdIv25OQwtB2YmZUQ_HQ1Hx7eAoVhmLTa3dsnn335OZn_X_-LP_Fd45jnVLeX293l5tb-yQ_ff_eoWRzu7d05OH72_HTRt0eHR0dHRy-_cN-R399fescBvmt7R8cMSAbBOTOFLk7z7J0z4hDCu6-99f733k7DePvk1v56L4Z4cHC8XHQXzy-_-fqbENCkAtYuurdef_NXH_72wb1bTevXXffuj97bXG63F2OyAih9114Pw2p9cLHd5GlsYvRE0TlG1CIgIrW2TTw6PCjjtO763_zmc8_oCNmR9_7O3dtNv0hTiY178sUXPoSUU86w2l9_8-jZ9nL4u7_-W6nl04--fPb8DBR_-NZDNETwCvXw5LZyyFm7RTeN6XI3XWyGy6vh62G33Q7fPL_cP1kDs4piAakK3zGpsIrcYD0ByACQcR7nO8eHtQoCO-_NtFStFeZcShEzQDQVQHQEmMd08eTi1ddfzalmqcum90gAtt0M1-Pu4asPU54MLLBvgycGdl4Bcq2gxA7LXJz3gGiqCIhmh_0qBGqjW3v3n_3eu__nP_7ePzm5U4anf_nlp__1L37zP3_8zbMBH52Np9uyGSdg9s5NU61q7JyollpVzbFPudx0QopZqtnQABDBEMAEiuqci4CWWkRN1WoVM51KDp6rFGQyUABQ0CpVAUxNwYrWXESJjA0dUqByU2eGG2q3GkLTRiQEwpqroREzegZHLjog8y6YKaNrGsfONU1kZiK3aGIXPYpEh6s2xugXkVcttx7b4FZd0zehDR6r7sUAhos2xOhvHx30jW-jD_wdvcIRdW046JvOB0cMClVxSnJ5PaZaQmx2U8paq373253nVKsBMIEBIIGPHDsfPMcYTK0h5x22jgO71rtFDCDWgFv0bm_VtiEyQNe6Lri-CZJKG0IMtF41fYh3TvZNJUSHzqni1fXgPYmqmE1Tylm14sXlaEgKYIhE3MWW2Tnnqyo7n6QCQRXZjYNjWLTduu9U6jSlaZjaJijQPE9zTVUKM9292-ecpFqpVaW--sLR0V43TFNJYlVqrmgUnfOEkciBgpTItLdeTJsdm5HVZdMGIqhSizLyousMHaC3rKVYUQ2xCT7McpOKUmZixr1VdwMyVrNxmESEFLWWk731ipyqTkJfPbkUz875F473l228QPvy4upst8lpPPbKYF3nz55fvXv3rmc-3VbqPHShohmpMb_68l1J86Onl18_OsO2vRrTnIrz_v7-YZ5TSamUErzLefaOyLkYXb9eXF1sCG0chjRN07AlRa3QNK3mDKocw4OXX2DHkdznn__2hXvHWZNHkyrByIEe7629c03jGnK73ZSnCYkUVGq53F7cvnuyXKwunj4iF-dUrs8v7h4fkdXA8PT8mXPN1ednhAA-eJUKczJPCgBoNzgySBUBkYg9MwABOw6KKKpiUuZszIakuUgRqcZtW0QV0ZErRTQlJAZRE2FiNQP0kBQFKYbp2Sl7LwYYnIKZKREQIlYhMZOqpeLNkbyokamBoRHWWqWmKoRAiKw6jDIkUCAwAJNaUQGLyjQDoYqYKTKbKQBoLRy4ZkUfqPFoiGpQC6JBFVBQMbDKQJoLKMj1rmmiU0EpjMRAWAWr4g0tvVQ2RgPIitfJUmZSQDA13wabJyTOu4Gchww6pN1Xl1YKqEIxzQq77AxFIOVC3qWcNRuYhuhszjc5bjNL2ciIgHfbScjGMQ_blFWGlIEBo51fbqVIreXiYlh5xFrH64RJ8pS2Z4Pkit4QrMwJVTVXm0rb9HsUfvrzz-_ev0N9357sFam37hy8-9Ldg7btvTsb5m2RSaki-eh8dPM0qaEQ7SRXj_2qn6vE6FMFcEEYfOOyaK5y52ipqk8vhtPruVQV55u-uxqHQe2vv74Mnn3AkuF6kyRSrTYNKkSVgwhMxZ5vx6bjizENU3UBp5oFdHUQ0pgcwQtHi9eO-suLQS1__O04TiBzbtoAUg_uL2HlhqlOqXDLwzhXNPN-ebJ84_2H7_7ua74JSQo3RF3Yv7PaO1n7lTu5s96Nw-pgOeZ0fNzeX0RUvYj8W50_3IznmYYE7OmNF9fvPzx4787yeyd7l1-Mr-z3q75ZddF3YUR9Ngyn46i5irFc2nqm-yeLWsrjpxdPnl9dz7tcc5GMbHHdVJQkggTTZnbBOY-ePQHUlI1oyunZ7gKJ2jYOY7rajgI2pVzVFDCnUudqaqqSc1UAVVWwNKdSsqGKmhQJnogo5wqKtQgQgmjJJXax8b4NzgFEHzxz28XofesbRurbpmti9Nx63wUfmRrHy6ZxxIwQve9iaJsYvIve99EfLtvWB--ZiBDBMRGQgXrnvHMM6Nl5R13jG0dN9ETYNp4dheiM0Hv2Dr2nJngyC46Dc44IDdiIkAiImMwUFG70Ao6ciN68CYgVMCOzln0MngERgRBUKhqA46oCUt9-_c39-7d_-uFPAL1nio7JsWOQWimwGBBgq_QH_-h7v_7yEyOHAASoiCJqquw4eL9s2oPb-5988Rm773RoVsU7QlLH6Dyz4-iZAByhY_IOkcA5ghvTaqDgOAZm5_vOh6b53fff_r_9P_-r7QjcRGZGAEQjZgfIgKBqWgHsm6-ef_Tky_OnZ8M4fv35N-M8RLJaRqkp7zaff_Hs-6-9bN79o--_9eTbR2ebyxjCOFy__OBEGP7yF78gwJdefmmeywe_-qRz7TTqrPXP_-6DQAAOduMOmaDBpunaVX95tgvIhkhmwdHBqn_5tZcZkdnnWkzFrA7DmUlquubLz3_zv_tP_-y_-_N_TwDrw-Wbb74spXBwQ0n_9X_9r48f3nr69MmD117667_5yXYz_s1ffaCmsXUAcHJ4BCa31kdEDqV6JgfMBFmyghEBmkaHJc0O0cz-4z_544P9vQfHh8f7-18_-qLrDtTxZrhe9ov3vvf2MG4Y3e2TW2lOZOVgtVi2rQ92uD4Yhu3LL9_3TTSpX_zik6Ztrq_O79099KTr5bpbdfM4cGDT6gjRbigUVLJCEcfx7t0XLi8uHTMAMQIjHB8fE_I4bvv1-umjp3OueU7X15eLxcJSGcfdm2-9fHznjnPuwasvq5c7JyenlxdsJirLvvMu5HEatlNKuVYT40o0DUlNhu10fLQGIR88GpDhDaMCAD25m6kYzOyGWQ6qUs3k-fn5veOTnDXVgqgxOEYU01ptnBIBAtlf_PSnL71wNxBWq4pMiKRqwf3F3_7tn_7zf5o2oyIbkcBNZpDVjD1JBfZAAIyIaqqqIkDqmjimoWP6g3df-s9-5yXcpV8-Ov9_ffB3_8Ovx2_O3aOz8avT7cV2HnOe0rwd5rOzjXcGCKWIKUAFQ7jejjfdwu9S64ipyjCXLJLVFEDNiMjUUhJDEjMEKkWqQi1WRRUo11oNUikGlKqWXKuZqlYRQ825prkCcSmiaiVXcm4cZiQuVWrNjp0psGPPTqvckM8NLEQPWp3nxnuv4BA943rZ7i2b5bJBkNUy3jlZM8Ld4_Xd49XRst3ru0AYPMbgg3c-uhtWz6ptj9aLZd84ZhXYbIa5SKm66Juj9Z5jZ2bXU3m-mS-vp2QIhG3b5VpBoWnCwTI4F6L33nH04SZA2fUBAAgpOm4a7yP1bVyvmz7GmmtkL0VKrssuHh300YiqOAZG2N9fNI0jgiZ4ImhCiDF0fSRCRlQEMylSZ1FEmqbiva8GyMieazYf3OUwX49JDVIVUyB2XdcSkfPBKky7BILexWXbjXM-P98-fXredlEAt9tBTQ3AALzjJ0-mWgxZ11149Wi18D5n2U061dJ2TZXadi0jesbjg30iA9OXHt6bNtv7J0d9Ew7XK1Azg9g1N7bsKpUd9Y0LnqtocD6isahHJEfeOauy2417qw7Mui6mnIDZOx8b33fxeNlnobHoo4uL4lzrO4fQxWhFvjzdpKvhZLW-PL946eSYAR599W2sul425MLff_IVNG6b8i4XQa5VapZ51kW3GOe8227HaTRUI3v8_NSqEGNFiV3z_HKK7WJ9tFKGNMw-8DinXFPoPBGWktjdMJaInAv9anN-vd1tur3FR599_dK9V66222-fnU1levPlh5cXz9958b7lXKya1ZwVDZbdYum7ddudnj27d-tecO3XX34SXTOnqfHhD97-3rhLl9P2y0-f_JP3Xn_9h68RO9ZcCcxEbcoAVquagomAVBNVslJKnRMhSC1mplWocSYVUFUKIgCTlgIIgNScrEqa2MxuCvemjKBSiYkbX0riLjpGLKZTsWqqoqWaKgDoXFENagXTMia82ddnQURJYmKyK4RQSkFmKVmzgCloUahiBaSaKiFZFgCr42RSDVRVEExyslpNilap00xgebe1Wr87GvAe0CAlRJJSkQEAwHPNc92N7ELNSTY7RxXNDAqkDMZWK0l1Wi0XnYopmCIxlXEnRRSUvQMzBpVcXEBQBSbwCCaA5iLPKY9jGsepTNnGieeSL7c6F1MVtRiCVI1NFzoSE_YkKgKSUxWVCrLd7KbdPA-TgpVUtJgYSq1IpZZaizgGE6tDZrF5M7FxEjq-0__1v_n5MM2D4Ctv37785im4cP_-kQO8fdiNJZ1vtjnLlOtcqxHVIkikqrFhbBxHHku6HqeZdIL620fPrqY0qV5r7bpmV_JONPQNrJxbxCeX4xi5X3GwdLW5kkCZbK5ls90x-c--OrM2TKq-66xxl7sBon5zvh1TAQe5as7qgx_Pcxviem_9zsOj6-0cD9sNwWY7zELx3r5fdgI43LzXRTdOueSKkSyEqvTHf_rjl-8dHq17iF7RutsHxYXbD--Etjk8XHdtnOacpl3ZSYsxX5VC9uXV7rMvr3A3H66bVx4cvnG0fGmxtE3d8w40I-Iuho3WGXEnZTSWGF-6e3C0dh5TRkmso9RZwEdnXIft_PziekppN6Sqyj7kakWrjw7JUinbeRAw54PUpDWLqtS6GycgHMZ5N-VxTqnUVLOYadV5KNVAAUqVIlqqIKOoVAUg9MHNUyYmQUNHIlpLvTlgg2pNoPWi8Z5ipLYLfRf7xvWtW7YtGrTB903TBNc41wTXt7GNrm9CG0Lw7Jm6NtzIblZd03rfx9AEbpvovXdgjeO-iU3kvvGrddsGt-yb4DiyW7SxCyE4iuTAsIlB1G7QmoQQnMObvyNEBUA0BGCmyOzYOWJTiczIEAIjmnN0QzF1jsUZEcTgnXMhBBc8e2aGotXErIzvvvrmcrn--1_8lCgiEAPe7AXBNDTeQB3hOvT3jw__4ZPPldiAyNAFT46byAiAYncPj4c570puyHnHNzbixjtVu_kJjhgQvzPZAjAhEyEgIjAhM950oPs-Iuif_os_vn_v9l9_8Pf_5V9-WIhdjGpoooYIZoSERkROzU7nedqNhDDn3HURpX7y1ZdQpiLSRr7ePv_Zx19sdld7J4f_8MtfHR0d_Ju_-Js__oM_FJXPv3niONw7OSago5P9l2_f_fSTL7uo_5f__s-_PT0lhhAdUemWi--98tLO-PHF5bDZ7a0WpsaMwfErD1_wsalFEFAlM-r188thHL_88vMxp853j8-eP3n6uPX9v_yTPwKilIrV8uizx3sH6-V672rcLFb9l59_IZZi8HNJVfLnX31F3j7-4uMQwDNpmq1mRrxIQ4U61LKbJqhcpjE23qy-9OqDNjrNw7JvNtdXCTgQnj554gg9wssP73_44S_znFZdP8_zsml-_w_e-6u_-LsK2naNZmu7RomuL86PVuuLs23X9DXb4eHe4cn-V5980vrogV3j0DsB3U3znGZEzkWmGWLnUVUNmDjG8MY7r8XotMLZs1MX_Wcff7p_crK53vXtYrGM-3ur5frg6bNvnz65vnr-3BBfuHPnL37y0-io68LJ0WHOCVG32yHXikDOMZNb9wsQCM5rNROtRcxMTKporrWqZq1FNRdRMAObUhZRYgbUp89OX3rjQS0VkUtVU1M1YgA0AgzBRQ6f_PbLf_zHf6il1Cpt0wQG78KHv_z4hZdfqTffKMhogVFMvyOHAqLHVCqRu6H3OmLnOYaAUEPk_-i9V19cLz57Mv73v_j1z754cnUeH51fXkzDMO3GPA9Tqiqb3bTdDuM0X11MzKy1aq1aBaoyQs5JazEDrcrktCgAFJFxztksi9QqKgYAuVYxzaVU04KCBKK6HadsajeI-lLVRFTnlAUhS0UkAyPGWsTUahXvnWol7wwIxFAp5-oCo1pANtEyVhJAwzLXG8uHD8jGlmtLzqn23u313dFe99Ldw1XrS66rNq7XXXTsHBPBqm0JDVSnVJro9vdXRAiGuyQpy26ciHi32SFCw57RslgSHVJJVRUg58LOz3MiwvWqI7WzTc61GADid-O5JzaD_VXviU3UqiHQ8cGSgK-2Q9PEWnPXt-t1R3gjYQEwa4Jv2zjv5mUTD9eLxpNj6KPvu7i_7A6WXZEiuaa5DLkgEno_V8miUymb3TSXklKa53o9lbMxTaWmXMeUspSL6yGZPD-_uB4GA1gs4nLV76b58mo3TPPxrYPVMg7TlGvNucySCHHYTVNKpdaLq-mdt1_Y21ur2jyLIIQmpJKXy15VmsbfPT7cbjda6u07h8-ePd3bX3gHgJhVFVQRttt5GGcxfXwxmGnO-fn5lpjnKlOpWSSlVKbkHAcXdin1MZIZKVQgM7y83hbRRYhADAbPr7cJdP_g4NnZ80XboVLbLT5__PzO3YNvn539-KWH-02jouu97v6dfSJQxhFBkZVgLvV8s7na7ZD92TR_cn6WEDKia2IaxsvzTRFFombVxUU3qhwfL9frxfZ6PDrYr1XKOOVxbrpeik6XWysVWQDM-9Dvr5frlYG2ISz2VrdWq9d_8HpsF3du36oiQPr6Cw_nmp-fXwzzvB2mcbsl56SQDIPWcnh04B3vdqOhH4YNKzSRLaeSRxB76eGdJHJvf01IJHNGRDRFQEAEBGRCUwKTnHQu5AI5KpsdiUGpkKqNM4hCqlAEDU0yVMViUE0mBURgMjN2DKAqxURrvrmy6vx8q1MB1TSNDtFUAZRMAYkigBQyIURQBTXNxQc2qMyKkE2KiTIC5QwKgIZmIKZztqmC3SAHFNGgFu8IzGyubKRZMCcsFVSRKcSAhq5mMiN2cNOErkVSJu-JWYbMxXzb5EePiL1njsR1uyvbWUuF795SBAxkLFgExZDQRWcpM5jT6sn9Lz4WM0l1M0lRAINcYS6QBZAhwLgZas7zdoIpQSmogKIyJq2iKIpWs-zfWe4uCyiknKY5iUERyTntNuPmfNK5otV5THUuMueUpmlO01DTLAymc_EANSkB1ySK2O41v_3Vt9hwjX6Q8ctfftz3zVtv3Vsvu2A2TlOukgSQwDGTGaghwt664xjOd-Xbs812GDPRDJYILrRc5ryRsh3mo77LIqlmZSyNfv3txS6LetwMo7Xh68dn6MM85WIwjandbx4_fkJdnBD3Hqwx8PW2FIE0lXGTprmqwFhKWLGVQnPpOLx0--CrJ5N2HtfNR5-fzUPp157HRNPY9tEEqjOIoB2MRPdfvffS6w9_9MffS8a8WtFeUw893lr_yf_qlfd-8JJvo99rRilh2fq767_55uk_-o_e7roG9_a-OR8vLgd_Q2g2vlXsxFGP6s2SgBIMaNd1Pp3mp5vdJDalctQHRjw_z2dPd1dnm-ur4fpsm9KciyD5TDhqubjeXFxuNldD2g5aKoqZoGQBszTmNOcb0CYgX44bImJAFUOAcZqlSi15HOc55YQqpiULM9VcEUlBgZDYp1RKLlLExIZhmodkhgbonAe0povR8aJp15FRxCNGdq1zy6aLjoLDm6P6LnDjXRN50QQPEAj6xveNbz2t-3iwaA76eGuvP1x1Dw9Xt1Zd4x0jNNF1TWg8N2jL6PrGr0NY9k3jXev9oo2rzi_a0MXGB-5iCEjRcfDsyZkAIRNB9A4QmRCZmBFM6YbZhkgIIIpIYObdjeqDiMgMVTQ4TwSNcwCAiGjGTME7vXmKzPMP331PCX_y67_npvGBCcE5QgCtgowG4B299cqDiHQ5jWIcvBMRU6uleuccA6l8_3tvfPDLjzA2npkdGwJUAARAYEJECo6JyRF6ZkfsCGN0zqFjQlRHN4gIILBF7968dfs__-e__6fvPviLn_783_38V6KEzoHKXGuWqmpMKBH--ftvmHN7ewtuqOniqm2-vbqCah8_fvzj331nN-XD_V6dq6Z3Htzq95affvr1nVv3r6dhvN6ul4sX7z043l9Hja-9-fLh_uH3X3vn-83Ct-vPnzy93G3OLsZhlsP9vetiX3_5rRkeHh0ZcwUrqvtHJw9ffFCSsGuibxyTiCz247DdnV5Mv_3828Nbx__3_-q_vZrzW--8vL8KmmZVqZoen18Mk11dXZydX8W-AcKxWhWrOf38F79p2Q3bwSFudjszq1JUyp6PaCAowYXVspEiIhWJGD2oypxff-nFcTt89dsP5pK__frrvX6xG67u33vxpRdf_uSjj5u2WfWL3W74_ptvPLx15-OPvgx92zXN8a2TrmsZ-atvH4cQzi_OAmNw4Z33v__bDz--_-AemTl2wTcqELyrtYSm2W6vm6bp191nX3zBzDdoncbHzgUQGTZb5-Ppk-dt2xApo91_eK-UNF4PTb_-z_-LP_n1z39ZJDW-2VzvVu1KhRhhuV4w87ffPgVyCmAqpOoMpGqMDhRuatk5ZyREMCYmREIiRFE1UVVLWiOiGpjAk6fPOuqlGqNGR6DmkEFgt5ujD0z4-PQsIB6f7IlABXDMiJrm-fL06esvPtAiYMyOiiQAYGQiJEQ0I6Q2NuiobTwyGhk7Ioci6Y_efvF4EX_6m2__9suvpYZkPpnUsfoKeZq1lJxLKZJymkoeUh7TfHPZS63EIEVULOcq3_EOSIuYgRRBNTBAUQNVUUQy0ZqEDBGxFslTQUCtRoRStNbKjkQ0jRWQkdHUHLsqgmBmwohmIGIqio6dI4PqG8dMSFjmikyiQEghMIUb4BOoglRCRTHoYgwe1224c7i8fdjfP9pfBS9Zjva6vvWR3LJvA-Oqb1IeW--6xu_3bReD5FKMhkm_eXw9JIl9rybHh6uj_WWtWRXmnJ9fDblaRTKj7W682OxidLFpBHDMlkpFJOf9zVrTEJmoaRq5IZg1frXs-ybuxqwiR_tLYmyaAFUcEyOkaugdMOZc8pzaRWPC03YqtfTBr_umQesd1VRq1ZzLNNXIwYeA4OZcrjbz9XYyopoBXbNLaZZqBF8-vdzM-fx6ErV5zqKWckHHuRY1m6f09PnFdhj3DharVX91PueplpSIeDfk_VUzpzKXlKS88_rdAx8WC5-84-hSEQWrRazWO4d7y77JedrfW9y6e3x9fnn35Gi1WDjnPbtxzgXxejdvx1TNjOCtF4-j5ynVSXLTIJEbZjkfp2RQMiCQagG2g65DQyDapTKWOteSxmm9WCG7bCaEXWgePTu7LPVkrwPDbzabVFMWe_Fk_-VltDk9ObvYW_cv3zpKRX7-2dcF9fnFORqhp4zmg7sehmdX29OrXRIgF8DUk2M1Umgd7_cxzQkA16HbXo4H6_VuOzDicrXeXUymtjhaayo1JSKniEWqj50WCdGncbx9_57f22fTVbdIMudxN-Xdg1vHtw72H599e73dHqz7mpJvnA_axn53fvHKw1f6_b2z7ZWpt5Ibh3_4_g8962Ye51TefvXlq6-vnl7MZADoPCCaKd-g8VU1ZwJmjIyoc0ZkU3LOESAauba9YTVgzT54JiRFF5q-O0Aim2uztxZV9Cw5gZlMs5QRCSgQN943vtuLOs9tE8qYCBCKIXEdRkQmx2hiokhqVlFNcyVTqALVrCoSmhmocXREDKZQq_PsPBMYFFVAEyFVTVWL-OBMKjARBgNQIhNVUatSq6GCqRIjVIFyo6ET0OJRQTKUCk3vnZOcTAoJ-kguEty8iJLCjeh4LpoFgDRL6ILMKY3FAmPjkY1UWHH5cJ-jkioIgCncZC1LhmGW7Yi5QE5IWIfZcmHPgoTVNAt7Hq4Gs1pTFa1ENE-Spjmw5GEYd0O1BE2Zx3kaMkBN17vh-UbnGVOC3axVcy6uoTknjohoNUlmnaOjhW2m3WB0cHiwF0PIeZimVMpmTOxd8FFKBbPrubZdM1abA3x7PbNnCeF0k66LXKmcXo9nU9LA1PpcdBhzJXq2HT768vmT0-vdnLa7oY7jp796vNmm891s0e-uZlXKk5ydX_av7GvvszAggkeKlGdlYoeYpwlSpmo6Zqzu4HjROhpSzbl-8-WV6-PLb--Dl92Yd8WM3VytP2zNu8vzfP_1-_vL1arrHMfPTi9-9fTZ46vL3_n-S7__3gvbbVw2TWgcg966tx6whM7_p3_63uXTqy7Ss-vLx8OwXDT7B4u7x6v9htmkGlzuRmErhNlA1UqxZ9dDaIIAeOd8F59djZcpWWCTMm-3onUahwo21VnRgnfKplh3m-uLzVahmkPwCGy7YWYiNZhL8jEg2cnBARKUKqmWIgJmcylSpWVvBmmc05xzrrtxykVLEgUj4lpLcIwAN753QygiSOB9GHc7B7hwbtHEu7fWy4a7SK2nG_hME3DR-lUXAqNn9kR96xdN9EyBqQshIETHXeP7NvSOjpZ9QFr1bdOERR8Oll0bQ9e2Xdus-rYNMTCvujY610fXN75tuIvRIS36hhBjYM9App6YATxRcExoDlBEmQjN1GpFjdEZqHdIRKAIhDdBPlONzhGiVg3MKlBFHTsD854RkRBrVUAAMCCtqmne_eM_-N15SL_89S-IG0QysRuyOSF677BqLvJ7v_va6ZPnk0wi4B2DAgCICgA6Jqj64P7tn_7qFyFER-SZ0EF0zN8l-c0zOmJCRDRP5MMNQAmJITh2jJ6gDd6TxeBGM3C26Pp_9qMfvPXg7oe__eivf_aby80cnYcicymEeL4bXjg8UsKW6fx6YFUptWrtQ_zgs89W1H_19NlbL7zwxgsPp-sB6neJkf39vV_89jMjFMNvnz_fbXf9qhXQpnGvvPHm22-9sYzhsF89vdzeuXdLDR03DGU77FzbdI3PqTr2291wdvak219rRPCk6IXQ1LWLdQXd1bKdxrv37n3-5bdffPkVuvZ333-PCW7KY__jf_M_rI8OYuiHp9t3fvQjiFwme3ZxdXU9TbkqaEsBKnhTzySpINjBeglo0TnvvHPUNo2gxY4llTxlsPrg9ompTvMcfHh29rxbr72jx-dPQhtffuOVX3z4q_3FYtm1pNYvVydH-1pKE_jtt18dh51a-cVPfnV4997mbLN_eDxOuzTk2HuoBYCmaVRENTSiUuaDo4M55yopz-Vyu8kp11pdoFLzuz94r_FutV4iSWj46vnZ_mL__PTsYL0PZFXrT376s5_-9B-G3bbkKqL7-8vtON5cG3dOTlyIl9utIMxjnlMpolJzrgKIqmAAZSohBBCEm2iqiYmJqBkUsaJ1t5szFUZggKmMqlXMwFBEq6lIRQLnvQtu2YR_9-9-9kd_-o9kznOeYwjRAfrwFz_9ye___o9zymY3527m2QFqrcKChCBiahZ9MFHHDlWd5xgdWv2TH7xzf3_1k189-fT83Jivxnke0pTmpOVyO-RsaciS1Gox0CTVRz-lUm527AipViMwBDU1BhXNORcVEwUEKZVVnQIIiFqtpZSCiKVkFQGDqVQ2NjWoYkVvBAJqZgRm8l1KqmrjIwATkFQ1QhfIOydFHJMjv-hjUSNE9kyBXHRmVqq40FSA0AX2xASOwXtc7YXjg_74YLlq3HHb3N7vPOGy8XfXffSetXbBs5mWumoaz45uhANFUpbrMZ9vhm4RQxvneULA4_0FiMbQbMZ0sZsVkNgjQEFxISzXi9g2gQkdXex27DAwl5RzqkUkNKFrmnFKWst62XYheERSYKQmRjEQhVyU2OVcp6lWsXHKqiAigLDfN30XFuvF4WLRN1GLzFMSVRU1U3b-8fSVgXnEzXZQUf2OC4njnOY5ueCBeDeUR2cXilDBUpHzbbreDKo0lzLnNIzT8-eX05SGG-RTld2UUirVTAHWfZcqKSkAVdX9VUdZnNKzy-3zi6332PVxvWxvHazawCVn51zft_M4dP1CxeaUDXGzG2vF603KVRVhsxkOVktGIoUhZ0I-Pd3WnE3sYkimFPpIZuz8NpUQPRFprSGEYZfHKR0d7LFBLnUyLApPLy6fnF3-8JUXRSCDPn525T1fXo1_-PpDK_nWqn90eXm-3T2dp_M5TUSui-u9fWAj7-cqBwery92MntVgTnm43HlyOWUCX0oFRSRGwC7GXU5VytnZeb-3KKhjHlIa4iKWuXCMkmodhiqVnQv7naWSN9uD5WK8vHrpwd0616O9tTd_59bdZ-fbtW9eOL77yr1bVxdnzrDruju3727Pr20uR_fud22Xswx1ioFrmknrP_vBu5Dk-mrnEGjKgf3th7foZvQHAyaSUgyAOMBNV3W4AlNkRufIM5pYrVqK1cJEWioBW63sHIIB2bB9jmRlnGoRds4Ia66MRFW9ecyViPOU6lSG8y0SWK6MCKaAaEpYFbPUcVYRrVVL0Tmj3ZjErFYlT9R4reqZbcwoqNWkVlBBAy0FzZCIoOowaqno2ABEBMQIwVARwTkGqSBV0nQzWBigpXqjOUQGq1mnSWo1kToMDn2pRVKxXFmybSarAopQim_QqlJDmjO1bGaSKzdRi3oCILNSNWfMOefMgvVsxLkCGdDNaGKySTDn4EBzAlXLmUhBap0LaHYgZZtcQ-NmrqUqSE45j7OmonOFcZo2I9ZSquzOMlhVSSnNY8pasmqymi1UBZmHJAJESMB5FmMgF1wT0mx51FuHx7dO9uqcz652i73ufKyzAbLbTbOa7hQLGiBc7fLzi9z0zhxXNQw4VTlauMtUiZwReXQqZgA7KYPK06uBGjfkerWZLrZZyR08OFnuLcC5uOg50G4zx73V9rz0q363rWroAsy7uXUIN5lVUVbQUUSkWcf1XvvF0-ux1J0ae7p9f__8PJUxF49hPyauLjKzX95a_qs_e_-FvX2KTYr06dXl__TBFxfDcPvoaN-3sel7r7f2_K3D9nS7--TRxd37R_f3l7G644e3au8zWMf-9pLXjTsmhTz3BIOYoUNPY5Kzy_np-XA5zEfL6MlcNVT99vnOEDXnMiTJFZVJre0CS2qAIFcPpEpCHrtmHqdxGKYxFajchBiDOWjaCFXQIAbPSMyspipSqu1SmnIes5xeXQ3DkESSFEXdDWPVmmsmw5xzLiJViQkJ51TmOcUQrNaUEwB6JFI73l-uY_Do2FEXXR9927g--sb7wMRg0VMXuY0uevKeY3DB0aKLiz4s-7jo_N5et2j88V67aDypOrDoqe9c17gu-tZzE8Ni0ayWoW9DG1wb_SKGReciO2cQPFe96eIbEgTHTMYEROiIAYHIovMAhIBVjZhVAYnxu1QMiygS51IQyQc2sxAcEIABI5kq3tD6Gb4L1iMrgCnkKf_TP_mj6-vdZ19-EkPnnbdaFNDMwMCAPLKr-Ob3Xnz89LSgVjFVRQA1AUZARIPbh0dlrps8Bee9YwYGBQRwRERASMHT_wLRQwK8AYOyISmSGSOgmSN2gOqwFgnkTOv-weL1lx---Nrdn3_z-P_x098mlovtaKjswnq_TyoqNQGxYS3axQ7RzdP2gJvbt29trq8_-M1v2j7upnR1sbl359ayW3x7egaKt2-fXG22p8_PV8sOagGBLvjDg_3l0kXqPvj5F59-_mWAcHFxfnm6udptjU0MDA2B0jxOeQzLVqKEfjGLeN8AUowdAg3jEPs-kHMN_7d__ue7q92Pfvxe1_g6z0h4cXrVNe2tg_3DOwef_Oq3Z2ebi-3WUeO8f_HBXZ3LP_z9B0-ePXt8dvbs8mpMaZpyE6OoMTABOXKilZ0rpRgQmprURb9Y9B2q3b7_4OnTU_O-7_esViDcPziMnp48f9b1jczzwf7q4cO712fXqHp4tBc7j2Ci5Xx7oaTzPPz_iPqPp03TLD8PO-a-78e87nPpM8tXV1W76enp7umxGGBIGAFDDgcERUhCSDtpo6V2-hcUitBGoighCGLBQCBiRBIgCIiAMMB4193Tpqq6bJbJzC8_97rH3eaco8VbI-UuF2k2-eR9zvn9rksRUhkXJ6uPP_qwakLcDc4z-dA0jSe_XM0kJhewaZqPP3jsmBAJkCvHp7dPHFJJORcNwf_gz394dvd4vx9Q1Hu32exsir_6H_5avx9BQQleeHA35mQJvMOz-bKY7PtNAUoqiAACjrnrxtmiMUMFc84xgGf28EUkTkQQAAmzmJo8vb6-v7gtxVS1bdtcSlbNKiknJMymRSSl4hyOUx7Oz9945dVJcgaoyAXji4tt2yzbugawYgqoTBDYETAjGQgSOkaT4ohSyiUnNQORAHD_6OjuYvXR0937z68j8L6fUklpGnNMWfOUDyUlKEnMXMyC5BRURaepGJMgKOKU8xdpoGwHVpmaCVo5DLaACiAiBmCMk5TDrzIwVfWekiVEAyJjIyZRMAQRRUcxCSAR8xAn05JLIUYEYMc-sHM8aysGEFW1gyBWVCFr8d4xIQI475nJOw4B7pwtTGw5q0-X7dm8vnuyar2zooHoqG2Y_bDtSFFS9siLdubZM2DMIshXQ7nuynY3UfBV7Q0EzF58cIaAhBTNnt3s-5jHLJc3N6VI0VIFdoQh-H2Xnj1dL2dNIJ_GZKbEVFe-Cg7I5m21bGcoCGZ6QJRY6fpRRIuaIPWpXG_jkHMpqgAxiag2VQUGjedZcOgIi362XV_0w6dX27efXkUxALxXv5hTSaLdOJFjBUg5j5LHlBNajmmYymbfX-2HqyF2qUTRMaWUSs4ZDXxVC7s-JjgckRxHlbEkql1dBWLHLgxTYq4UEEGP5202vNh3m13MKqerRRzGWVvNvMsxnSxnbVVfXVw5dLdOlqhSOV9SUeYoOqSkBMHTyw_uVMxouB0n8mxI_RQBMIvMAnfD2DoPCjEOb95emhiYrruuqZrz9fb4eNm4EFNGT8-u14-f34wF794-if3eE6jC58-vK9XjoyaALqvm06774efnp8t2N6Q-lifnF47DdrfXLGDKUZnc5no3deMwxHGKWcTAAFWlOIOUhNAROzE1lfMn1_16h6hpFHQVGKT1xOxLFF9Xw8149uiBpqKbadruPfByvpjPqmUTPnj_vbu3bisTM232o5G2TfXKwxdBZN1PMWZgV6Hv95uz0-Pah3bOMEkeeqPiHZQxPrm4_Ozy-kcfv1sIXn_l3vOPLkjE0DtyDkAlJjOVFJEdgqoUzQkJQKWMYx4n50IzmxOC5Ww5gymomRYrSUvJ04TucLwn8oxEdPAFMes0sXOAzM6BKaRoWsyEWSELODbNACIiGAjIiMCGxABfrNhTQRGbct53JgXNXHBkYCqmBRDLOJkYKIIUzcV5RwcuN6LGIrlYUUQEgDxOhAxG7L2ZIQKhmhZUhZzIwGLE2psYAXlHVpJjMDNNiQDBxIqACiiZmMVkQzYRywqSMatKRhU14LYmNFTwIVR1GK9vCFANoEaAAtMI_VCedwA6rneAAlOGMSkUbBwwMzAW842nBopMZqYgBprHaKrobBgnGKNOWdZ70gmSUD94iKYRUuSpqABmLENGNIQMBpI1LCsEHLqpOWmyQLtYvvjgBGPyTkLNz9b7UVXYmefEmBwPZhy4iwU8jmi7HMHr003_-dVUkL7_dDem3OU0W9a7fjpazjFwjOXzmx3V3i9rDORC_crXVpOWIoLOFQNgkaJYVb5dVVUgxDwl1bx_tp-uhiIZRFSlqgMDmWqzaF550T97erkdp95KKTKfcx4Lmc3b8OB4HkTKmpZVfWdWcwpuPutafNzlWIf1bvjV77zAR621PlRN3E3gwqi6u-mY-fUXT9TSyawy556t-w-fbGrmu8dzykRT9qCVg4upJNERJCe7ntIQyKowX86YebePu6JXo_gldzc7GAqCmEAF4EBrCKjmFWpiE0HTKcVpGMmrZ9rf7OJ-ikMqOQV2OUUmklQYmYkB2QjVNKUkAqaW4lRSziWXnMls6kfnwoGXnIfJVJ0nJJtijFNSQ0SSmNmF5qi5-_od31RN3dy5d7Sa1865s-V8OW_bEFrvF21ogwuIi6Zqa-8JKsLKc1v5pg51cJXnNvhFHRrCRajq2tcMFQGztU2ogm-8bx3eO25O2roNfl57b9BUXFVVIKqcZ6Q6eMfEAA37QOS9EwDyxHwYw5UZHRESFbbau0BO0UwNGAHFee88EUBVBSlCjnMuCsbBqYEnPoSngwsGgAzMLjhHjo0AEQQEBLTrfvlXf-XpZ08-ffJxoOBccApiqABVBVaEEZbkHz26_fTqwg46JAGHDgDQOSYg07e-_Nof_vGfo2vYmJmqwNUhJIQgpmBAjAd0EvPhAuAqpoopMDMgEzJaIAqhMgEw84RkMgt4q61__uHdv_3yg6vL9SdPL_t--OTJJZLb7Hauae4eLUwREKcpTpI--vTTk6OlZ0dVfbZaeeTjxSzmXLctkD27uGrn81t3bz_-7PNt3zvnPz9_mqc49MOi9ZCtbur_4Fe__eT5dH59fbRc7a4v9ptNM6vV9GJ78_Kde_NZHTw3VQOLpl2dZnSuCqLGgEVUcqk8pXEs4j_6-Nn5-fPg-eT2aSF--NL9Yd_99Ac_2u6HV1998OHnj6c0vPvp42GIi5OzWTV798nT8_Pnw34XJ3nnx--fP30-xVSFSosggaowERjOZy1kLXHcjV2SNJu3gFo3NbLef_XhD3_y56FuXnjwcrfZEtJ_-Ou_9vmz59M0PL28qL3zDt7_6Akzo8KXXn2JQIHgp3_xdrs63q7Xgd2srh_cv__558-Xq7kpeu_rZjb0yYqYqKNAAOM4NYsaAKY0HjaXksorb3ypmJ0_fZ6SDPux5PLCo3vPnj157ZWXh2F66eWXvv_n3_vad74apziN5XQ2e3J5zghm0DZVFXwSudl1KsBAAFC3LsbifchFD_87DKnEIgKQRUwsqY6xjLkImhpggXq-BIIxTicnx1mVCYP3VR3UlJ3bD1PV1t7zv_q3v_viG_eZoOsHrmcGxj5874fv_PIv_lwc4wF3oVKIqIg6RE-WSq4cg-msqUvJgdl7RDM2WMybrz-6dzPGJ7vBzysVnWKZRhmnTIRgLoMUwmw6aR6m0QCncRKFVHKRcijgFpFSMpKpSC4RiBA5xaSIRJxNkpVJM3sGAxURMwErBzgHYonC7LJCUVBFEwBDMCREAEIkRlQ1ZgKCqnI-uJLVE4OhcwxgvuaDptwzzWctqDExkauCR7O6qlHAIR1VbUm2CPzig6N7i_bh2fGqrSTlYYrzNqiBaVnMmwOntakDKKhZURhy2fYxFkuqajjFfhp6z3D_1qryjgCRaTtMxI6QDz4y7-h62x8fzQP6OOUEMF_NELGIFDFHDgAIEQxizqvlXAkUgaswlLjrxn7Kw5S2u36cUpYChOGAz2-oqGQRH8Kt42XNbhS56Kebfvzg-brbTc5XN_vx-c1WxMYY68bVTSVFZm0jAMTczufEdLnv-ph2qeyHIUnpUvrpJ8-uhvRsM15erfspbvedIQL5GNPYDTnH9RDjFPfduO1GYCyHnSw78h60oOVvf-1Lc-dFdRrj0VGo28Y5Pj5aHS1n3nMdAgJe3dz4EBaL9upqq0jbXb_ejTHqGMeqDiXl1ayZB-fJ9nnqRcTMVXh6upwFRkDJBRSy2AGnMK_naAiCPtSbaXh478QDNsGz45vN9jp2yA6ZnMlZPSfhYYwpltls9pu_8LWKvAj84fff-Xvf_UpV1Te7bgJ9cO_WuN-fNnM2zJvul3_u6xfPtmAwmUCNzCQpz5bNKJZynJ8sufLDVIgdqCQroWLX-Kun17Oj2dhtCMS1nhCqWW2OsQm5L4RYpmgIddsc3z5--4_-_Fd-_huvPXjp6uKidgze1004H6ff-f73Prm4wKZ-6dGD2XI-bW5C4MB8tjrd9v355RXGlIvc3Oz_7n_ym7uhn1L-G3_rl_7qN39Rx5zyuGgrAkB0nGNE5xDBxIBQVVQFAWzcqxQgBHbsUFPMJSuaKoQmmGZVLVM8UPEAoaRkJiDpoANwVRBR0UKOc4yaC3tPzoGqiVgWwtpECcFKsSykqNOkU9QiLrDEjGYASp65CgYQnPOIWoqKiioIkiJoQQSNBVRNzVIhA8tIxlqKpeSYtBQxzbmQ9zlFCgSAiEREKgo5ExgxEyho8YjsAMpU9r2qAqKAqh6CCaTJoIh3TNEgTzaMDs1KsphVFZFzN6LnMkXNScHGMTeVz1MkYgPzCWA3QZcgZZBIYLDpaUigCRzBIBYzqrJq6mOouT-fEFSmUacoMYNqjkPqpvVFLEo6TlAKCcFudDGX5xPsBLOBWFWLkyz70ZnJPoOhescUhst-NqvW5yP45vWv3J0Z7a8GUbrYj0PJLvic07Ab-lie9VMXo3e8H9PW9LNdd91Pz7cxIiTKNzFeXHXJTE1Sht0Uh5gmiTuzqOZn9TTa7Hju5_jeT66HKQ4p7fYDONiu-1RKmDkKDOT7YYJgYtnYxBSBM1IRKaKoigRHq_DJx-O-1-w9B6g9N1VztqwWJy3PQylx1-dvf_f-W68fn7TeMfXOfvLhVfbwZN0PMRv428cLMC15OjqqCtim6B7s0b0jMhtuulvHM2X8i6frVx-ubi997TBOWju63Kd1L1cpJ9Sk9nw_DVM-autlYItp3WU8bXdOUfLmvQsepWl8E0LTOFchh8oqj1VdCCYsCaRoYYRQ-0lpyFafzF3FJlmLFRExAcKmrc0kx7y53o7jmEWAkR1JLlJEikkqaUwq4gMzU46CSt6zZjtazlIR9py1FM2O0RBKmh62TdPLog3HJy2WUlJpaueIF1VVBZ43gQEqotpz7ahGbivvAwdHjiF4rCqetfVqXs-CO17MaudqJk8MRZEQEeY1z1s3b7hlrD2frOp5cBWjc67xVAUfmJm5qjwCMKH3DpkO3k4EJiZmDs4hYuWcJ-aDDQyxiDomInBECkXRiBFMHZOaksdDDMB7RDQFJXIE2obGo3OOxRSKoppzyI4NRA0hTX_jb_z1H_7Fj7dxG2ofAjVEABpjcY5BxQO-evcOAV7eXCgzMBdVKYe6IYJB48JLr7z659__I-89ExzcZWDqiBBIVciQGD0jIQRPxICE7BgRKu8ckSMEkdNFjYcqgikDHNyiWNN-2OdJ37h30gTXxtiyq4nMwaptn-yvSrL1fjPG3O33t-7c2-zH59frMKs_vz4Pgft-__rLL15dX2ksr738wlff_PLZnbOvfflL3_jKV9vV8tNnlyXrj378TgI1zSfL5c-8_uiHf_bjGKfjo-Ob5-cvProl44QC1_2-3_UAxhRPV3faReswMDsAHHZT4GobJ4yp8XXxhoj_9t__7rYb_s5v_EfBh6dPnpKjP_vzPzs9PUXB2jU5yccff-KoulhvqlnbTSP5ZjuKCd29c3e-bAGZZz6mLGBRigvOvM9SVqs5M89ni5hEDW6fnSjozfPrRX2yrI-enH8qWhazRbffd_v-9OR4P06fX61VsmT9q7_6c48fP3XOnd0-KWLL1Wr3_LqpHBPPZotQ18t6uTyZxzRgFZTo6PgoEAXnnjx-enw0D0wnR3ckyycff2bGkqUOwRE8ePiAiNNUVK05at99553FyREiZimPXrp3c3X9-P2nQvzZp0_6Mj189OhP_uRtx4dmis69M4MnT543i4oJs2hKYEjk2HlXTFTVOQKEAwCuiDISgIGYHLggTLMQHPvNfnc0XzGTmuWc1cx7JrRZ3czrAEI_-vG7f-s3_2eSMAI4Jgr8w7ff-YVvfc2yGhGw8w6YEVVIFeELMj4jfFGhRwAEU5BSgOyl20c__fw5CojZ-rob-lRKFikIMI05lwJCKqKGiO6w9SAAAFPEWExKCUgVcsXOkiBBKZqyEAN-oTsAAEKzLJJidsyV9yiApshYTBDMeU4lVoGBjRlEhT2baTsPRBAaIkYfUFENyBRVyqwNQOgqOjtZVFUgZhWpHXrnSi6OCQlDcL4KxGiW5_Nm1gQDOT1pTxfhpG3OVsvKOceOHZ8uGgAgM4fs2BkaM5GaFpWi15uuKEyxKKABKuSmDg_vnK5qXzMQIBI9vdxeXXeKNKUipIa473evP7gDit4zetdPkYk8upiFPTvv2NHp0bwmOl3MSTSnrAHOrzfb9SiCu80ITMZMjhQsFY1SRDVPyogPbi8fHq88QZ_SRTc-vxnW-2lUxar67GK77aeM-tnVmsFMoRySjmCOPZMDo1k7R-8KQM7qDefzRds0igTBnpxfTSL7YUTgYTcWLVMXpzEVxWVdAzg1NVIFdaEChMr7PMXQ1Ipwd9ZOuWSVq2mErHXjx2nySG3wCGBmY5qcx7Pj1fXVetk2YjqJKHI_jXUzIyu3T5Zns0ZUbvZDUazIBWQs1DgvUvpSxhQHmTIqexcCPzg7UrPdNFGoLGUr0lQBGVOxp1fbedVEVQNpQj0BP7vZfPxke3Z6ci_4I5TK-Y-eX7720p31Pm3Wm5JtGKf1ph-G2E3TJ4-fHi1mP3zn_S999_XrfbfdxYurHTkHSDEqeQezqgTuh5hTqprADOMQka0kBXKStF0sJGvsohlxW8WSkJ2kPqtEy_WsBpDdzebk7Pj-0TJgqYK9dO_4z97-adfHH7zz09__k7c__Hz9ve-_O1vUX__OmyJaUrp3_w7VOEF6_vSyl6iOvvozX-YUu5vc9cPF46fHZyvv4NPHn83rhoBI1YBYUgRQYmTnD7FFEOAw84CWhbxH9ppjs5pxCIaas4ISApqISWFEM9QUsZS03Vf1KRmDkYoZscbCyN5VBgoEqIUAQFXGHRFAEQZ1zkEpFc-ZyDFbLoygSbQIFJOUycBKATMt2QWHCJazY2Zgx4HNbJqo8kiEhgAiOROhiqAnJDq4v0EKqMgQTYqpSREocqjzEmGZIpnJNGkuMqVqMQ-Vt5RYxXIxAmAjKw6MnaEV57xDBlUSZQYAjfs9eidi0k-oBCn7hnaX1-R8yQXSREVABNKIjYfMOoxEqJsBUoJxJDAWtJxBRLop1JTHGLxnRk3JUi45IWcpUUqGkhEJHDd1cVJoMkPwpAQmxWwwmQqhgpSSSpnK6m7dX_YuhDBnEX35rTtN5jxJNQvXu1GYwqzdTRERMxo425YyqaFTc9jHmFX23dgNOYkImqomsGJYN9XNul_OakREouvrzvvKzUPW3D3vKJNqyWZZdP5oPm73kiWruZZ8cFK09pVl3e9izOCaMKUisRgYO6banZyGfpd2_VQ8NzW3NdeBZEo3T_u81bceHh_NVz_z5iMyNfQf71Kp-bNnvVRMTbAKTx-drZbzedPOnKtQULUfxqv9sM8COe_W3b3l8tn17tnF7sG8RTBOmkZztRuzCLlBRRGA7OkmPruJd24vY6_dZMkgil6-dzG996T79JwEJCmIy0VZeVE1tasxm08gvTYW5tzMXe2RGLBxIQTygHE3pJxn8_rmZs-ATahyjMwcYyLGUrTv0jSlXDIQZCnA7EKoQsXsCQxykTwO3YYc-cqNk6Rccio-VKRmZiJyvFyUIuMEWrhk7dYTEZmpqAJBXXtEPRTxHVNTh7p2lXcV82EzXXk-JHk8Uet9TXzoRgfPwVNb-VlwDTsznYfKh3BoBAXHVR0CmAN0hIRYeaIDktk5BfPeIWDjmQAdkUNnBygJgGN0zI4QCZnIAECMkOiLZgMcCs-OiZmJycxAjBC94-DoEAn2jATgiX3wBzS_6gEIDaYQh-4_-ru_8T_883_Zj5HQAxipIlLKGQAYdRinr7310sW-76ZBEBgZABXsULAok9y_ddqlNJZUo3OHpqr3oIagTHwQe5mgg8MkwJ4RCQhRrSAYESrCzLUqwoBASEDBewAkpNdeuvfyy3dXy8WtW6ur3fpo3ty_tSKieTsfizD7MY6iua349rLphv6lB3fHOHJx3_razz757LNvf_2bP_jJ2xcX500In332YUnTgwcPv_LVrz66ffulFx82wT1f9_v9ELMA2J3bx-P6ptv2w24z7sfjWdvH4ZXbZz_8yU_u3739-iuvURxfvHunbuq2rUiFwBR1PmsB4N2L54D8YHlU-uGPf_dPt7urvtsBYt9P5P3F9XNMuRvSH33_jxjpt__lvzm-03Zj-uY3f8b5SoiXp7fP7j2o23q_z33fj2lKsUxpurx84tlVjkrOU8q3z46ZeDdMCpbAlMmQdjfXr375jWk_ISohi-rlzfrhgxe3KRWB9TA28-beo7vr3c2yDi8_eABcKXMzr1LfT1OZptjtexBtQru-3sYxxiHXTUgxsXfPr66qUEkpGDwAvvv-YzWcUhRRxz40NYIR0c365upqfXJ257233__SG29u1h05P8Y0W7TTfrrz8G6_H0LTVBUEZiR0jl988SUXqpzjom3AzExjTKH1WtBMCNkO7bBiipiKRJEiYsAKCCKbrqucA0JHtNn0d85uM6NzyEwl50NmKASeBfd73_vhC1-6H2rXlbiqW2_a9blHuXf_dkyTKh5QuZ4dAXpHRHDwaRCiQ3TE9EWvBSpfffmF-9to7z6-hJrPlo0ZzJYeAAtAyiM5QEcGBdSSZESY8aIkRUMVZaIcp1xyLkLEjpzzHgw8opk4CIRgqt4FRwwGiMaOpRREqrwjQ48BgQ0QFZlCKcDABHjAs5oSI4FB1TZI7NDVPlQHoxFh5b1nnLczQvbeq0HOmQiY0QWsZnUIvq59U7lFW68WS0_gAc-O5rWD1x7deXRy3DrniEzt0D4qKasakBlomfLR0RyQiGAy7VLqp0whjOOUS64aWszr1mOZEiOr4dObfVQwpiGlJBKCOzmZLWezynlPlIqur3a14yLaDcO8rYBRJC-aWhIcZpCplL4f1tfDGJORJc1NG5goeEdInqhm74mP5u3p0eyonVccBPRmH5-t-2nIXT92Y0oC2z4poSBlxfnxogB450REHYxjJICckkjpxymnst50j59e9P1kAKlI18e4G_opKugwJXaURWSaxhjBgw-4WNTTGHMWdmRGMWZPhKB1FRbL5q-89VpgcuSM-d7p2Wxe1y5U3rW1oyxVcMtlvVn37Wy27_vj1SwVvdx0GbiXAt5Naag8n7a1iHTD1A1pHLOiIMFq1hbRfcrOOR_aqq4ZWMis5IrUTJ3nOIzJxAVezmolu-z6ociUCwLN2rquebNbb4bRFnDrqPr5Nx9WVD-96T-72jx4dPvHn57fv7MqmkDy2fH8-FYTh_3f_LVvSxdr4k_f-fz4xePCJaCCaVW7zdUOMSCzFF0t2n4z5G4vJTsC1VIklmma-h4dh6oOjiUm1zY8azSL9Nkh-aat2iqOeT5rv_rai_UYX3vp4aJt3_v407_43nvHR6uxn4ahb2ue1eFLr7-4u-7MsD2uj1ZH-_We0A19F2rOCr_6y7_w4M7Z8iSwxaWvhq73TKuj0ycXazIEV9cgxVRARGI-eHLIOUCwQwWHGYjMFHLKu841jQAjIjMiqnOk_cgEXDsgFsloOtw8OdTqjY3ZYeuI2ZERkhUF9iBCZiCKqaCqiFqJgCWPN0CgWoCKaQECHwKUfJAWFREphYhTv5ecNGVkJ4qiCmggZqmgYcmZnTMRMGUAjRmKgKgjMgX8yxC-qRABioKoxASlmKjkoqLIqqo5pmoxc4CWCzpUPcAaQHMyg5IEQM1ERDRGzcq1t26yYtx4ELGUTSV3UYaoagBCjko86C_Fuh40QUymAKogCkgGKFMhQI0ZgHMuqpKTqGZJRfqs3ShdLtvRpqQxYRFKFi-SR1KEkiR3E4CZFbMsWcxsGiJXIZw2208HUcLAm6sxOF-LK10e1CLYqCUhKCACTgbo3flYYpaabBzkcsifrftNN4jnYYppjFry9XYQxH0_5pRD43yg3TCJ2GzeNo13VqwXy8UFHUeJhjzzZTOYyFSETxcFq5uroZ1XwxRFVBW0iKj5wHk_Vc6ZY0cYd5YGNhfqeZhy6buyG9NulLPb8__gG7d8D99-4WzVVH45-2Dd3aimtk6OCsLQ7c2gDbgKvhXLU8pC21i2yVzVrBzMzZbL2VVKzzrZG87nbihulxAQukGy8rNdGqPtRvmLT68d0727S03Q70Zoq6sx79ZT2o3VpNZZ6rKrwjRFzDD109CXpq6Pjua37549eun-8Xz-4unRiw_v3V0d3VnNv_ni3TvLI1Jo2mpet6kfT1fzpj54bUMco3NeTEvMiOCI8picY1V0TLO2co5BVI2Gvis5AkC37USsiDkmcm6chqI5l1TP61g0cQgthRoJtandFMdcNBXdxzTksutjVFECBUAE7513DtE8IR0sSMyOODAHx2igXyTjzTt2TJ5o1lYnbTurK1UgQu-ZiFEOOX9zjOwJDUpMh58eftBhQwiKxAZSB09MamoGRGhMiPiFGYDZ1JiJGNHMeVdEDrH8A5kUAZgdECoAMxcVIDjcDTwz2hemTDADOOiMyFL-X_5v_zf__F_8c6WD6guhJHTInkWBkWySb__ca5ebm36agJGRwSClYojsEbJ8-2e_9Tt__qfU1u7wWPqiBkBICAhE5DwRAYgxggGEQxuYiN0X_sNAfkoCZKjmHXgkKzprAgKezJs7xwsVe_XeyRCHBvnz58-Pjo72-15Lvt6uwcH9u7eHmC6u9vfu3H__k0-v9zerZfjpTz-6e9z-8Q9_cDxfPHzw8p987wfvvf3Oqm1ffHDattXtW4uc453jxrMXhKHvxn745jd_hhmaJjS1I98o2vff_uh3f-cPLtb73b7_9INPvvrql1HKYtEqSGBEkcDu-nzzkx-8e7XeSBriVKCu_tlv_ysS-k9_46-XUm6ubyj4__fv__vTO8dvvf7qa6-_TkAY6u11_OjpeVu1q8XRvQcvsqH39ent24p0-fQaWFxFTWhCYGLIJWbTfZp88P04KZtvKmMSzHfu3mIVIg8Gd-_dnc9aRZgv5v_uj95-dPe-Mcdp0Djdu33UD2Nw7q2vvLzdd6Fury9vqrq5vryKaSLQ1ofWhanvq8q3Mw9I7KhoDs6lLI4oC_VxnB0vh37w3iEimZ7dPlOQYRjFEElN8hS7B4_ubdf7F154sFguCaBdzbc33eZ6N4y5MMaUs8hqPiPgaYibbT8VMZVumGZNZYBAKKqlFDMzhJIPH0RTM5Gialnker1fLNqiYGqxZHaUsqjxlIpzfhyjCgTvgei9d3_4v_iNvzX2MRds6zo4_9F7n__iz_7sOIxAjhjIo_fOAxMDABqoqTCSSgE0IKuDb7xHlVVbcbHvv_uJa2i9HU5Wy9ncjftUFIFwlBtCx2JqB-8yiWnESawULYBEKi4wOI4xqxoSxyLsPQCAWdLoEB1RzpNndo7NAFSJUHJBwi_UV4EOLgZVdZ4PG1wfHLkvDBuk4Mwco3dYBz-fz9g7do49V8F5R_OmNil1oPlyxt6Fys_qpg5EJmQyr0PwXBEsqvqbv_7G7WX94q2TV-7eqogPwx4jBO9Skpikn5IBBucXi1ayOuZJbDuWBNj103q_83U4fNCOqsoBtnV1sORe74aMkEWY0NXU1FWK5WR5FBwLwJSKIjZNXUSNyXnHTHVw87qqGNn5_Tjt-qmPZRwmyVI1FTOzJ8kiSW8fz05WCwY4XbVHbXBIzDionG_7ZzejoIMi6Dkp7ocEBCg29qnfx_OrLTNmNcnaOkZ259frbsoxS9dPhny57yYrUfPV1c00xd1-6LOR976uuarBcTaZShE2dM4UNAsSDtPUVLVnjHFihuVyhlBevX_rZLn06IAAgPtuPF6uSsl15Y7blokIYX29Oz1ZlpzbuqLgN8OYFPssAEhMDOXu0RxNo2hfAIiPlm3rQxN8LHHIJWarKz5aLdaX25QnQDlbzBgdgPnKF5PK86KuUOBm3bPnu2cnmqzxjgynIQlgvai3589fOm5vdvm9z5_5xj185S4RDpvs29Dvp2UIsRuqydJ2cml_cjaLQ9xf99NNNtWcZdpPLDxfNGkcLcnVx0-H7W7W1FHw-ZP18tYZI6V-SNOYxyRS5idL59kZrOazxXxWeXRgBNLOWyJ4-eVHL9y79a1XX37l5QcljT_-6Qf_5g_efunNl955_OToeEWOj28vvv7116-eXJ8_u7pz--TBvXtpivce3bl6fqUJ-376T3_zbx1xbezNu4_3F7duLSvyOWUCczaRFisxIQdCRsdgcOByK6CIkucDjlNyFoPQ1OOztag3Q5WiQADoQ2Dny1BUAESRmNChQI5ZS3Z1U0r27Sz3Q-pH7xwayDgAmpR8YHqYAXOlhgdUMBY9vMVBFU3LNGoRJFYTIgI1TREAQ12jiZRiiKaiRc0UGRWMAKwUQDBARHQ-mB7oBACqBAZ9D2ZwOM0xASAzq2RkADYAxWJYMoHtPj8vpofTgUrO40SOdCyqULpRtJipqQChOTRSIGVPZZwAFUzdoip9T7OgKQKC5mRFEACmC8ACVgARJIEZEEEsJgpWEE0kh7kf1z2YIkrcR8vFcoaUERNAAS1oqjFq10NMokU1IwqZ2TSxFOkPqAdCAyYrmxx3PbeIgU1Lu6jBQCqcSDZxGFR3U9qlFGpCgue7cT8qk0tDfn7TXXbdqFGdbbfdGMWA9n1KJU8lZRFTLVPcbvtnz2_W2-Fm3Rvl9fk-T0nAFLVkIYQy6fbztRRrjmau8tMo86PQdd04TX7Bplml1HPWbKFptKK7d2i7HsdsYcWzVWWOJBXnsPb87TdOvny3Tl1h1lhZrt2zYZwc8ax5erm5vOkIsT1qRHDhmn4sJRcw7HK6nsoWrFies5uK7rN8shufWFksK-_wpu9H9l3RYhKLrac8VrSZYlOH5cwdNTbmUZxeXWx2193YDQDYR-Q6VBWZ5fbYUQBC5plTBqZQkLuxNPPZTRcvzrdV2yLxJ1e7_TANaRpS3O339aw5hFYNJMYxlTTmYewTOTeNsSQDRjBiZEZMqTCDEU45JsOpaBLlpokpd_1AyLmPZGhZgmeLU9OGZCUp9NPIFWWzmHWIpRvzrkvPr3aj6Pl1vx1jH4sYZFEDRYAMMTAxYRN8FdgRmNph747Ann0IvmIXHJOWRescofcQwgGyZ77yntkM9PA9ASPHhwOIJzY154npINRSdqQAiOiDM7RD45cQ0RAOMtXg2PFh1-WY6uAPhQJWQFNmMpXgnHOECMGzqBKxc8geXeUcsyd_kCWjQzUxQdju_7P_1d__7d_-7cVyWaFzoXJIWYG8ZwIGqDK9-dIL5xcXfZZiBgbOMRKw88yEqC_cuvPTDz5gdgDskNixd-wIgnOeiQARyMCI0LsvzgKIoKqECKZ15fb9gIh2cK6YmKl3FHMaumHb7fs-Dx63l2t09s5PPkiaPOCnl-e326Obfr_ZbLd9d_fOqq7bO8dnP_v1rxWBo-VxQXpycf3mK4_O7hxf729ef_3Np9fbjz963HdD8EEBLqD3bVUHd3S8DHVoZnPfhGp-ZIrzk-Pf_u_-5fvvvTOU8l_83_7hP_un_3x7vT89Ppk19ccffl5MwMs07Z988jj33fn507Hbb677qyEPsXz46fVf_Ohd4mq5aEw0TqnrhtPTs6Nm5WdN287_8I9_cPn0MvbT6dGyaLm-_NxI64br2q9WM0euZAm-9nVAAgYHCkVzwGAAq-MjQ-ddOF6d7S7G73z3m43Tzc328ePPxxhjzpXzu_34jS-__Pj8adu0m-u9qn75y6_d3Nw4F1568VFwHrDs1-tutwWCjz76pM9pNqvYcVsH8vaXS3QrcfCej1ar2XJG7Pf7_W7XA1PR7BCdwy-99UZdz2LMHPidt99-7Wtvff748-OTRVP7k-PVNKWbq_V7734oUlKeHt09e_L8Cg5ZNSZGM9OcRIoAwnbTo4EUjbEUsaI25ZJFs0hRKWZFIIuJWkl5O06IlEsRtafnFwZgquTABVKT4IJzwZH70bvvL4_bqq0mUVcF34Tvv_32G288NMAsAgagGAhNC5B6x7M6MJFndo6q4CvvgyfT4j0vl-2908U7T86rgGO2x58-Q9LFrEGCehYcINFtEGida32jaogMDMTgmHIWRWHnVcAMjUw0O08hBBFjZgQqpkjIBMyMCEgIwIDoHCKD8w4RSynMhIjes3OEgE1Tm2rtHAIs2tpE57NQOWq8W8wbQgge5_N6dTxrmzCfzbyjlJNDCo6d43behqqqQqACnviobSuEZR3O5uHRWYvn-6-8dv9Lt0_nwTsFNUNUJAWzmIqAAaOBgRkbllLGnDfdaL4CIGZf-0pymjfheD5b1pUZVE2lBLt-Mu-mXJz3alpibjwtm1pK2fbT-fW2mwZi6PphVjVq5gnmdbVazdUgkd2MXdeNU4wmQGCzeZNj8YhHs-b-neP7Z8u28vtdf3zc-gr7UtZdjFJ2Q9wNcT_0XT9uhhRjMZTFvHbkun6cpjSm8umTK_IhZilm23V3td4p8W4cxlwESRXiVNCIDAFA1KiicUzkKIvW3pMhIxhD3VTHq_lyPm-qpmp8TbxoqlkVTmbNiw_vrxz90tdef7CaM5ialiII5bgNklNw3IRqHEfHNE5pMyUAvX26ROJhSPtYBChL8d5Lii_cvdtUQcEuN9tios66YZpKjjnmotkACaWAKNSzmsX6_f5ktZRcHFFRLVJiTqUUACW0yvkxqiE6RmY6XR2lJOdXVz__1deQ-fs__ThN6fOL6-3VdrvuHtxdSdQ3Xr39yt2TChz05esvvnjazB8dLR8-PJumgUkkl_1ul8fBJO0ub85OT-dVDZMsTpYyo9BwmFW7y2tunG9rAmQyAuy3Q-UcaB43u-AqVcj9ngTmxyfzmd9ePvu173x1Gsv1ze7xJ8-fXG8Sihpvd3tXteNkLI6Qb7puc7E7u3s0bsc4luPj426zbpf-ze-8-TMP76x8bam899FHf-e7v4gF26YqQJ9v-__Tf_8_EQAAsW8rQCDRyleWFEzROyTSnDUlYFBVyTnFGGYVy9AuZ4pweBqUlBANtDAjgLFnSYlycmQgoCmDACG2q0UZRhcawkDtHOhQCBYCZMdaJvaemAgMikgS0KKgAEZkkgsYIICkDEkQAAHLNBmi5kzOIwB60i_IH6CiBIdFIwGApKjl8DtYKQVUrRRLgo5VBHNBQ50GEwUBVLNULGU0g5K58WnoEYEM0YCJABUZMSewgmqkiipQBDI481BApgipQCxQSukGUDtozqAYKmkcmQBKS9lhV7AIioEBqAIDqEAWSMl2yYqYKkiWbvLeEAVEYIjWC6hBTjZFR8SgIAJFiBStYBbIxfoERdgBW8Zc8pQq744eHJ-ctN3lOjA58mIwUbnYjzf7NGapqqob4pjytktP9lMqcbVwnUGqeR2nzaYfugmJc47Fle11P-7GPCQ0lawgmkppF2FUMZB-F_vthF4zytRFiQUdlTyCc7nQ6u7JMOSYxQd_dblezHl8tmMAANSJrdjRsj1rq6v3Rha6-6giMDSM-1KZ3J65n3lUV1K6RNYEWtQXm2HTjX1XRGAcBmRwAXdjvNwODx4sZySiKSL0Wp5P5ck4HgV3XNdCYW_0LJUP1tOj1QzJX172g-jz_W4QmS354_WwGfOQFVSOa7ffdJ8-6X_0-Oazy-Hmpk8xQ5I0Zj-z0NhqMXMx8y7TmGsHPGXt95i73O09CEG-fTa7ddxePr_pB-yn2A3DOA3ec71oKPAwpO0-GWA_Td2u23exXVQxRwAwKHVVT92wXDREMHZ5ioWIDgMjgsQ0DdO4229FS9EEoHdvLY-WM09usZiPfW8CeYogxQTERIzEIGbZ7aaskLKEynHgIqVLZUxJEZio4toRNSE4QhMzEef5sLc_OG7A6HBYr0NwipLLgeCNCEgEgEUNEEUMDZx3B8sXqM5qv5jVBEjsDmB8MnBEzIwGwQdC9EQHbRYjMpOpgigRHjJBCsqODjcB9siOyIgMDsIKVfHeg5maMbEnYgLnDg9tZUbyTAdZ0JR-6z__e__wv_7Hs6MjBFAAFC2lFAN0LhAv6nDrdHl9c6XIdPi0mBUVIJJir7zy8nsfPoZADMSODhJwz0QESIfrKDjiA1FNDuCjwxcJwQg4hGyFER05ogPuxCSrKHTTcLXeXNxs3nxwKxaoQjX1XVVVVOxP3n37V77x3X0cMtbqLOf4R3_xg1dPVy8_ePCTjz948YWHH3_6OO1LyRjT-MGHTx69cPdk2RKBmW43O2Q_ZyemYBqcW8zaUHnG8PR8P472xhtvffmVVzfdzfr8apjiFIf5Yv72D__srS-9du-lW1PS3b7cf-31ey-_WBFaits4Lo9Pm1BxxdyE3_v9P6C6CsymhimfrI5-9P0_PVusnMKyan70-JMH987Wm2nRNHnsLeb11fVuu8tDZIRZ29iUsWjtQs7ROUJGZ3ByfMSOTlarnGNbVyer-YOz2ydHTeX862-8MKVJU_QVN77qu-3Ld25_-PjT5XF7ctp6zw_v3dqvN9M0Hi1mjT943-pu2K_OzlQyeXTeg4mvQ59SBm1Ws6Zpus3QtpVpqT0tVm0I_KMf_UWORQmJqarDnQd326ZxzsekV5d7Mq2bxgMbIWTVnLTYxZOb1956a7sd7945HbMAQvDOETy8fatMqeRiBprVVw4YcypFDhAdEyklp1KKZlURcGBgBTSr1C449imXKaXl8eIgyxI0dJxFkBw7QqJ__W__9V_79b8aIxSV-Xz5_idPxm68c_u4TFkNFMA0g5pnhwAIpAAO0TERIR_CNQomZmS3bx1d9tN2mKrKeUIthmNuKicCWJSYvXcYyHNgZfYO1Rg55hKcY8ciUkSYUNVUDJBM7fDYqoN3QARoCF9EiQmI2FfkKkfeA2DwrvIuBG5COEzRlfOo5gABoK588NzOwqypPHHjQu08mq6O5hxcRTyr6spzU7u6cgzAaMGxR_LIdfBNG-raNc4Tc1NXVPThreW9Zf31F-69dHrikFAAEEPlpjilmKcpGoAPFTlWlVnlnXdjkv0YxaDb7g_souCp8XzreDX3gR2pGRgOU4m5MNJ8Vi_amkzun520LtRNpWif3awPcSkyJCZw5hjaWTMLvmSJol03DcOYpHhkRJiv5nGMt8-WJ8eLZdt6YgDcdZNnN055O6Tnl_1kZbOP11d9P0oSGVOOxbb7MWZTgH5M_ZSSSBTrFT-83GQVJc5cdVOsq5BSEU1D10_9sJq1FeOiqSvvgQBVciommFP2DscpkYEH5wFPVis4wERV27ZG0rZyjQ9ffenulx_eqQC0CAc3lbLvxm6YzLmccghONLdVDUQx5-Nlc7palb4AYlbLReqmdsFXnm-vFqtAjEiE_RAZTZOeHbeLpi6i3TBVwYXgpUhbhUXVFBNnejRvEEnJnjw9v1xvF_NZFcJ611d13Y3jutsX1GRlTIk9V0DfeuX1UnC7T7tULobh6vxqej7trodf-u6XSszHTFktpenB7dNffuvl7nl35Kq_-Y1Xj-q6ZVditim1zWx_taYsu2fPVveOaN5cPrvZPdtIKQDU95MZAnPJmRjHzT5ud1kUg49FY9SqbVRlNg_bjz9eLRa_9AvfWtT-3r1j8_T-xdWz3f755eaTx5_fvnv34vqirf2t23efXYy_8-_ffu31F06a1oEtZu1-c7M9v-Rov_rwTWcqcczTtLm-Pm5aIE5q73x28eHn2---_iUichBFC0BRVQET5wkBxVTRCOkA7QF2yE7yJHmSYTQhDvOYRhWSGHVKEuPhxa5ZvGdSgb4nLZYNVGyIJZeipbt8ZiU5X5mKpoyq7AgBkchKgpw0FzXgQASOkA6pHkYAFTu05RybGqj54B1zyaKS0UAV9FAbLZkRTRTkwOkXzMKHgrMZk0MwMiFVIgYRM0MzyNk5DwBIjKqWo0nKuSgwEB9QdARgahDVYi45ofcIzlQwiuMDKkgdYnAMh2I0KBE772yKMCUAs5IR0ESBa0dMUkgKxgRThIPtsRg7liGBZwxIYFAUc5H9aFOGlBAMcoRNB0OCYdIpooKOBWKGocBURNR5h0SOGPYTxkJAi1tnEIJX3l9d1x7HXXrwaCk5d-PQp3g4ZMScDz3wy2FgVEd4sZuSp-vNuL7sYywqkqfERA3bME6-QsNikosUrkrXx-122O13MY_j2I3DIDlZsXwA1Jhun20NPLZ1LgiKszpIFk-Y-wIGpmCqlsfj1cyTcz2UfWoW801nabKYJKV4997t7QDP9-5iwLHyN4qfXw-dyTZNu5iBgKvA3t2_N28rTxocukGwy2Wb8_OY1LsmNJXzMcpO5HwqVwXOzhZFdbMfx6YyxiIgoD96On606e_dmk-DgvMK9PR6PL_ZxD72Xa-plInUSMUHP0cN3dXA6EucZJjSfrCS4368frbJfYxD6js5v-yMXKid6DSbt6GuPDeqtHT1OCUtRTWtN_tpjIqQSuqH2O2mHCOwUWW-CnFKCMQBwSymKTQ-p5KTlCwlJjQr00iIpeSz-4sXX3nYNnVKmYAD0dgNKcZhGB0HcP5qN15tOwy868ddP5nDKlARW_fTPhYjUjisBYgAQKWUdBBjm5maZS2KIGoKdgCWq1kBLKKpaBZVhDFJFM0KapgFpqn02XztuQ5IBio-OCBwjg-tR8foCByhQwjMWpQQDUEOG3RmJnRIh-X64d8aGgIgeeeYKu9qzxWzZ669d3jA89Ph9a_6Rd8_BM-I3hMwEquoYZx-6-__xn_5X_yX7WJFhkhABFoOEDdkwC-98BC0PL16ZuwPF0NHiMyMWGL6pV_9xX_5b37X1xWq8aEbbQAGJgAIh8IvIZkBgDERgjEBEAGiY8pT9kwIVEqJJapBP44fX10_3fZX4zBJmrL2Q-ecM86Na6YpVwHv333p_Or6W298mYgkTR99_vSll15__Pjzd97-7M3X3_y9P_7Tl-_fun3_DqABuLdeef3O2cnFxVoRxxSzaB8nKTkwKcHNZv3Hf_GTm_XVx88vr2_Wm4vN8a3b8_Z4tjwahrjr4nbfeZDa44OTxde_-53j23c-ff_dd__oT7cXFxefX-aIY47f_LmvW5oePLr_4P6t9c3lr_-1v8ZkPrg3XnrU7YfV3bPNbv-_-8__Xt4P__QP_vAf_uP_5ic_-umHj987OlkmS8bWj_t-6Jtmtjie5ShHq8Vmt53VdcVu2TRswMCOGUBnwbGlv_v3fx2K7LoOzd547eWc0-byBiT3-_20j__6jz54-tmzxclKirLil15_pKI26aMXHoxjillFZNgPwVUXTy6ckYkB0CClz0VIiX0qcT6rQ6hq36jBOKTjs9s3623wznlGoG4bXT2bVHb7Lpbhs88-Pz07jtN41NRd17_86BEaA9LN5ZUAPLh798PHT77IhTE9uHs7DtP180t2jrzb7UdiB2imUIqkVMAQDNAAyMxMsznHKAYEmYS8Q5X9MBwt5wjo2DlkhxyqRgGQ-JNPn7RVdbq6lcQIKrX03tsf_-qvf7fbj6pqxci0risEMgMwFNUshZCcd579oRQLZs75O0cnaUxPrzZKWt9ZLeazdllPRefEx0cNkQUHdc3ECJjmLTeOA7M3MjJxUDE35Cvv64rrKjRVRWpMWDlHDILoam6q4Nj5ylWOG-8BjAGDYzIjogP9xhHXwRNC8OwCV3Wo6zCrK3Z4GIdWR7Oj47apg2eYzxsQaZlnbV0hLuumrTyBOsam9kfLal5Xs-Bn82rWtIvZ4ni1ODtavvza6ddePPvWm_e__tqjVVMFMjIjRnSQSi4qsUhUS2pjiUUKE5UsKpKKjAK7MSYpBw4bozXBtwytI8lCX7h8dIpl7MeaufY0DvloVjdt6Pp4fr2f-5ByjlMa0hQCj0N3dnxUee_YA3GRvN3uNRuzI0ezeV0Fun28OJo1y6YqIogQp8LEWmHUnLIoad_FPkYliDkXMyI_aVos6rp2ZlaKVJV3tS9mfcz_4x--s4l5G_Pzrk-CXT9578YhkVnTNI7YkhW0ahHqKqzaWdt45yAEvzhd5FLqKgDjfLkYxtw0LSM6tIr17unyjRdu_9avfePYAVtRMQA6v16XAkzMLux2OzND1Sp4tLIfRkAytHEciayUnFXbJpiWCpFV7h4vKvY5puv9VNVhNmurKuRs4xgFzNgObggiqL3zntvGP7hzB80AcBxzIZw1LRt2_TiftWZll1Mfp27YA8jtk5NPPvt8UTk0EYXf_dMfffLB49v3bn37r3z17OHi1ZfvzchLKTroR29_8vB41rBNcbNO6f3r6__2j38y9MN60xMwKoik03uneYzjzW7Yj8f3V5x63K9tGtM4VEwgJW2H5myOJmW7K9N0-fkzaCtAKyUSI4dqTKNX3l-v33z5gaUUDH_wzqcff_L8_pdfufforgt4cXmz2Y0PH90_v7jZw-jZ6hour9bz1Tym4f13Pvj5X_zab_71X_nql16GYbx3skCVn3v9VWQkws8ur65kvHV3OYCRGQE5dh4JDqpAU0BkAiRiUGNE-4L2pVDMOa9THrc3vqkMOeUREF3wSKj7vSNzjk1FxmRZdZqIreR-2u_DfOGrer44AjXPTObosCFMYmZg5iqvpgiKpiBmMbFjQFTUMkYgUFEkAgJfV6bGhsyeHZMIu4adP9gWJGdNybSIyKHKrDmDmCZB9shkuUDKljIEVDQlOUSBDn80ikJKlOywyrSDCmiMVooZgSmlDA51jI5Z48SEJEJkxGQpOTJI0yHnC4g6JckZihxGEThEAVJxbSspIhGUAmJgBjGjAQM6JIgFihJSGqNO0XLRWGCMEKOJ5i6DCIACClSmfJjcrKSCIqgCoJaLFYVcsFiznANCHNPFx092F7vim9n91X6du2568nw3pqKEw5S6MY2GH2-G9Ti52pdU4qjU4nq7FdNsKIZVVQemq-cdA41jLqmgkSS5eD5MUxyGsSRJJd2sB83iEWXX-VTYW9n2y7ph0tMXjvfXXXDsnMY-Ltq63_UGaiZ17RhJDVxLF-drRmhOedqVKdl2P9RLv2fJ6NysxbrqkkySLdBll66HEhGE6bqbKIR3P90slotby0aTPdn081n1vM9Pt6MozpumTzqC9oo3Bc4WTcsOgV1FWeVmN4mW9ZCnJG_dnQ39yGWaQD5-ur3Zp25USGAR2orvv-S4xTv3KxfUr3D1qI4-9Yb7fS5Dnroh9RkRyMrY7SXvTcpmtwEwUx2GEQjqxvvG78u0vt523ZCGMk2plFKKpCmXMuU8llzUaOrkUDTJUpxzCACA43ZULaKiUpxzRQwIp3703sUtmNpiuQxNVS3qYhJTNmARy6V0QxqzjLmMqZB3_TQR0WZbuklSUlPt9oOpmf7_VZpFRRXR0ECLlCmXMaYiRQEUAIimYlm0G9KUZLPr91MqplktmY0iWQ2qA2knGQACH7xabAd_FqBzAIaHZ7LaAe1PAN67KnhCBBVGcIwAWjk6wHMcoSNCBe_cwbvrmByid4wIiHSQAxBgFQgJHONBKgIqoHKoIaCSE_6P_9d_7x_91_9ovjwqURRQVaYpFjXvAgj87Jff6vt4uV0LIHlGIBEBQybHpi--_MqPf_pT7wIQIZFDrpxDADIEQD6QBtGIyMAQSA-CMkRHMFl0SIQGYASoJVfMpwiPjmZfe-Hh2ZzuVE2ZYk3l3fc_gNj_9Mn7DgzS8M7776_qxmtfSzpZ1rdPVh89_fRrb73243d-tFwsf-Fb3y6a92Nf-5lpOT5adMO4W2-rxk9Tn6bsmHxgk_Lk-RVhaZombi_7YbzZXL720sPzy5tXXnn5ra9-xYiHmH7vT7732__0v7vZ3vzp__Qvn77_bn-ztjQh5d3m-t_929_ph6nkDlO6ePr5vt_9_r_7_Tffen3YD8T8_nsfPrzz6Edvv60F_83v_7thu6-H7uho7n1199Y9LVLXtWnylSNyUx6quikxFtHNzSZNo5Tomc-fnQ9d3_XD1fOLmNLJrcWt4_rq6jr2UaWIlpLTT9__cD5vH9w9Zaf_yXdf3m73zgdHrgl127SfP3tioK8-vNfOmlRyPV9cP3_-pa9_6fr5mknAuJQMySRlNVX083mz3W4ha9tWp2d3bm7G683150-eSS65ZGY0ybO2mTctmPiq-vzTT5cnqzjEr375zaurbR1qM1nM6vd-8vZut1mullYSM5esKrrwlWm5vlp779WsnQUCOqiyEIAZQNVAq-C-SLyQETIzJrWHRyfL2cyT2-12R_NjU7QD6drQCjjH7N0_-x_-21_5tV8AAxV1VfidP_iTX_7u12wERRAAcniYK9CQAAFRixKgiOVcxJSMci4OuWmbFPNHn19KUaBGb_pZher09HR2tR3zFFezxjsm1cqTAEw5OQLP7Bi99zH9ZZ7KDJG9WeVoXldWNDh2RN4TIoIZE7TBo2lwB4OZm1dNVXkmqKtwwOCQ48pxIApMzFjVzgUKnhbz2Wo1r5xnQEabz0NTee85OGY05zl4QlHvvPfsEEmwrVwTqHGudkSgp0f16w9PfV9ef3hrwVXlmAysgAGqqarkIoA4ZNl0ad2PYxYtOm8rQCJi8K6b4phSEmkWNQJ45NWs0SSz1k-5APOmT5c3nagSQeXczXr36sNbZrrZ9FFtzCk0dcylbuvlsqlrX1I5W8ygqBJdXa_Xm87Y5ZSrulqsZtM4tqFaLRaaxQEnhc22G1PpBr25GnfbOA45JUlZplhiTACQRbtpzEnIBVXq-6hFGVyJVlUVMLrK_85fPP7pxeX7j5_3OYH3TVu1dVVVdV35eevrOjCQF1pWVVt5B6gi3vOwG45WTTurzo4Ws0XTzoJnmva7OvBpXf3KV1762qN7Z_OqJInI5Gicxtl8nrUY4hgjO9c0QUpmKc6RmqU0OdDWs6v4ct31wySqIGoSKycBQBWvu2kY89HJsSf2SHHMUyqAXIXAZrO6qhyrFiZEs-PFXBUVEYmqUAFiyaVi57wzxcfnV6lEZtIpV1ZmwTvnrnbdv__hO_ucmemDD5999On12dHRatbIEE9Xp92UX3p46-UH7eP17p_-wdsXJf_xjz-_2aeIPA1TKWWxOJq64ipe3j7hefX0J4_rpl298qAbhptPr84eHoPXYTuYifUTIYfgg0ONMW426Exy7PZdcXR0emo0_ew3vhT7SObsLLz92aehmW_Ou2GIUqTfbSrv7t-9vb7Zb59vvv7VF4dxWtTzV159abPfHq_a1x49eOutl9fnF5999tknzy5ndX339q2rzfTx9fbtz65e_-qXnp1ff_zxp-RCBcRWANEDAB4Al4hgwJ7JAE2gFCyAYOQ9Evl5Q0xaUmgXiIRIUoql0lQVJCkxAiM5zxWbFLPCVQ3s4jSJ6v7mkswAGdnnrEzeRA-iLkmCxAaKJsyGCFgUrKAdGGVguUgqIkVShJLLNGopTK7EpCkSejQr48jOaVHDA6w0YCAwJVMmMslWsqkiAkjRWLQYRIOUwNRSQgLM4pwHUUZ0yCgFVXUawQBK8cy5HxnQ-QA5kxxggyBioKolak6lZEAFyYSIBGAKWcCMHULKIKbFQMFKsWmkKCAFAQHQEcmUJSXwCKAlRhhHJDMraAJWoJ8QFCVBziAFouiQwURzkpRARHOBLAeaGqSI7MCHMK_R4ri5ATS3mmtNt1-5vdtuC2tSEWfZVICgwilNu92gpeSU68anPD39-CZ2o5QspSiAoU2jsEPylrPM5i2iSSkCUiALSIoTzShrwQBpjJazKUxdHvukzEph2mbNFpowxonAKo-WDBVCU42b5NmXWPbnmzxNNmPRscQxxjifVXkqm4vu0etnmUpX8pDyZki7KW1ziQZF4epmaOfu2cU-Rz0-adDATHzF192YQbDyhWjKeRNTYXrWTUNRJRqjTobR8MdXOyKZzbgbIlc0Ffjk6T63uN7u9_sxxxJHDZ7vPmxevoVXn_RxgL7XuCvb8-nZ451GEjHXEpGoFsWSuv049hXb_mY3DH01q5rgCExzyjFttrvtev_pJ08PSIoiCa2wcylmlNJtdlbMAB1g3fipG0VlGsdhGPuhV5WYUkkiKSNQLsU5ZmRRWCzm-_0-uDCNU93W4zD1wwRssZSqrkrRKachlfV-HGOMIkQsUTZD2o_RCApQFwsH37btwX2lpo4ZAIrIlHIsJSXJBkPM3Zi6IQ4pT6k470IVUs6CtN6OUyr7MQ0xdWPqtYxi22G46dLFZpiyCgAR-uAICIFMjYhNEVQPVwdAOIT-PZEjDOwcozucJggr59iQCILnxru2crVnf0B_MRyyyIZaBU-Mnsl7d8CJ8gHPDxS8Y0ZkQ1IybLL97d_8j__JP_lvTk9vcVHCQ6LHAMkh5hh_6Ttfvji_HHMqYgYYvPeBCdEU7t89-eTp01HVCxIhEMkh7c3oHAGYiQEiAhAx82GjAAhIxBYxOKemBiY5I4AhXos83dxUgcn49P69WT2vQzVvayv6px-_99qdlzLItpt-4avfuLm-uDq__vzTp4PZzRCrpkIrL7149_Fnn_2VX_6V9z957-_-nV-ezWYvvXD_7t2zjz5-3FSenBeRNjhiSDndrG9ee3h7vgiOK2zCoZlZEz946fbLr7_kyLrNjcb0wV-8e_PkYvvsCtJYxkGCy8UMFUCffvDue3_-p9PUO_IpJkf2ySefKvDUD0-fPHvzy1-ZL-fvvffu2e37rz189PU33_rs44vF8ZEUZsLlcjYNSUVc5XxdzWaNrwIxD0N_enqcRW8dLcc43btz9vn5eYkwjROUuF6v_-0f_kk_DYDaNvXQ7ee1dw6OZn7WNM3xWcwFCpwdr7bb3d2TsydPzysH7ayqqwoZisSu74dxnC3q9W4bPFeEy8pb37siUxkXbX35_Bk6gpJPFrPT24snnz4hkDQlH3xwbrFoX33rpf0wbndDErh8vmUO6Ko2VO3Md7tdKYWRuKqf3XQDun4aCdA5z44DMxTYdvusWZMSkZH5yh8kEyAACFUISFgFV1eVZ6o8OUZSPD5dsedVG7q-u3fn1DmqPR_4Ut5XwbunH39S0vDG62-UmAzxydV1XVW3793KKWU1UzE51H1FQJG-APEiIBAaAjkUNHYMno7nzdVui54pkFHJyWLWm8t9Nr11e6liMo2MpEXMBJHYMxiiZfLmHTWzatFUbQjek2NqW-eZDLEKHtCayjfOzwI1ntsqBM-hCsjUBO-9A8YquKaqAlHbhKoKgDib1bOmquvQNK5pfBXcYtHO5mHVNojWBrdatG0TKs_LWT2r6tWyvX-6mDehDt6BLtrQhuCZZsEva__gbDav-HgWbq0a7YfXbp--cPe49d4zMfylGjTmqIKOB7GoEEXZ-VIE2Rwys8umpSgCOnIE2FYz5-HBnZOaaT6rYtEh5m03FEEkCg2_-sKdm5v1_dPVct4a8tW2X287QRxjDlXNhKerOau-9sJdMnNMU07MjKBxGpxzjnye4v3bt0uWk9WCyaci602XENXRLo3gIasOYzQFcs45NoCqrgiorlzjXEVgRYvCpLmfRqo4i6aspch617399pMxW5dUAGrHyzpoEkRlwlntG091RfMqBO_ElInY0ERqV9U-BCBXuAZGy4vZ7M7Z0V_9ha-vyDUMQ8qXwzSIVpVbLGbDEKdUskldh5Pl8ma7nzW-CQEIhzx5B6smxGnq9qNzbshZwXKJy1l9-3iFpvuhN7R2Vg_7vqSCiP0whqqRoiVmTxSI-XB69dQEmgWvCsW0GAib874OVWiqIZf9mGa15-CenT99cHYCuZzMF8nj5uq63--nNPzuD37kwN6486ByxLmQ427sxNh8_dOL4U_efvJs6DY4jXm63mynaTRQdtTte0K-er4ZckFiB_niR-9N57t2PifJ23ceE5NnjLteYi4piUpVt2Tan1_5qvZNPT9agfnd9c1ut3vj1ZdnTT0VeefH51psSOXy_HJ3vV9f7yrHP_Pml2-tjt798P0U0_VmPY5x122nMY_7AT2_9frLD06PPry51Hp2djQ7XbVdly7207tPn0fCP_3dP9mPfadMwN7N54roZzNTIFKLk5mJoiqZEQMxM2jSnABBtOSUiTB2-zT1kkvVtiEE9pyn_ouVNqKCWVZitJi0qGqBNLVNrd0eDRwFBXB1UCkcQhmjGRpYiQWJTaCkoqqGoGL2BYkRJSZCcBx0Si6EeLPTmMCQ2WuOGgdGdE0NiFw5iBMDgBrI4blvKgKiYGCmpsUkowhAQYeQBQFVFcgBASCQI1PVKXtfgainEJwnU8kJAUy1yAHaoBIz4Bd0FI0ZDsowJADQIUISKwpgoOacYyYQYWaVxEySRWMBA0QHSHlMKFJygn5C78uQQdSmCFltitAnSAWk2H6CSQAMCCGJdoWYrAiBEaLGZGNEM4vF1Oo78-5it398QSQ0c2XsZ4GnqzEV3fajAmgxQOjHqevidj9lKVrAOb666ra7tNv1ecxUhAH10EqDw7gh7KhbDyqaJY_bIXYRi2G2eDlZElKN28EhUeXMVE36krF2u3E0wpLy_qpXkeuLgQDM1LKCZfTl-Jbvnlx7ctyG7lkpoxKKmW6ebl5-4TQg3GxzH0ssMolspnTTTYlwyEXBRjEppZ23-wHQKOXcT-liGJ9uO1eFbhyHnKTiZ6lsi3hPXcztWfWkn55tuleOWkB3ftWhs0GG85tdQtvsdHMxqkA1c8v79eLUlVw-ubKk4GsyJ4rRSHxtRTOqeERDjVL6NEXQYSpRhYiLaBzibtdNw6QqqZ9MymIRjo7bZhY8ExKWCE1oibCk6H3VLJrl6ZyYLp5eiAo7PKSkXB2SpBQP8q9aVMCIjNVstpwh035I0zSWHNfPryWXNE7OOecwTWmYZMxydbMzMFHs9iOiu9qNU5wOWb8CoMSHnbV-UU2x4FhzKaX0U8pq6Jwg9lOKIsVkux_3YxpTUSR23E9xNqv6WLp-HJIo0ZTl2fl-mmDdD7s0rYcuppwFwYw8EgLjATeE3rFp-cuIDZgoABhAqJiYyWEdPIDV3ofgas_OESOCWV15BCKCqvLeM3v0nsnwL9_b4BiDD8Gx954cEpnl4p0DRkQApZbpb__Gb_5X__gfHd86Y1JDI9UYRzEIzpUhfuObX_7wo48LkCgAqBkAIyNBhG_9_Ld-54__DKuaDB0BE5OBAZghMhHjFzZZADRwjgmAEVWVyJCBQBHMBXc4cdyd1zIMDfmry5vlfJWLXO37VX3MCEXKa49e2ZY-J7v14IFrKqvnb73-lWmSZbP4o9_70699_Rv_4l_9f2rPfde9_b2Pv_b6m2x0s745PlqcrOYxZU9gZiklQCymTDoLlScwkbv3b09xArBu3y1DezqfnRwvrs63_4f_4__-Z7_7lT5uvQNGbdpmvlqGk-Xxw4eI0ve7_eZmu-2y2MPX3xBEahf_4B_8FjgAyz96_9Nnn31mpB88fi9C-uvf-fk7904Ry2uvPXj2_BkbzdtmiGl1Z_Xs4mKUvO32fZrO7pzshjWWyXsWmDb9-qOffnizvpmdzF568ZX3Hz_9Kz__M6ujo6OTo3EcHz95WoTZkwd0aGfLOQKIGIFcXe7Gftzt9wSGRg9ffAFE0pillO3NvhvietdNMZ2enXhWbNz8-Mihq6rqz7_3o6quYoo1QUD87JMn0Nbvvv8RB2dMvg5H88WdO7dmTTWNvW_dhx997IPnwC-_cB8stSEsl8uURkBKJa7aeooTOa68CzXfub8Alt16Lyos1oTgmJrgqzr44Oo6OMfBO--c91x5V1eh9p4Im-AgWajD1XqzWh4RkyGqqGYhBEP8J_-v3_6t_-zvUgFEgTb84Ac_-PVf_fawi4cGCzIgqiMCZABIImpAyGZGhEhURKWoqtXOP3m-LgWZArN3yH3O_RhDFa6HYRrT0XIGyJ7BE1XsKyY2rCquZpUPfNjBA2HlPSMzkwvetR4CVvOKCEOoQuUq77zjKngXfFVXRctsXtdNVdehrqpZW7Wtm9d-HnwVuGbviFar-WzRNLVfzurG88zzalbVwTEjglTBr5ZtW_HRPMyrgAYekQkXs2peV7PGHa3aO2eLR_dPNMqydsfL-nhVvfrSnTtnKxM1MVBFRmIyUAEYY15vx-2QDhWOXPK-G0rOhECepGgfk_fOzO6fnl48v6ib9mxeMbhSdLvrbx_NRHnbDwZaRD2ogc1an0Rvtl0_pSLiiLz3BHm1bGsfxq6v2QXvuhTPr2-SqfdhtTrmwI51uVimaXh459buZhuINv0QJYthUdv1B0OTIJMBllwIGdn1XX8gAjK7fpi6IeZcwEiJ05hJTZOqWGEXzWLKRWUx8w5w5it2TAaAQBXP2oCmFXPOmg50dbWmruvAPnj0mCQaiCe-tZq98eDWSeVBjAlKklXjb88qIjf200H8rEhfv7XcbKfTxWzRzhy585sOVb1zTVNXVZWNikpbN2qKCHPvF5X3bZiyMHFdOUaaskRTcmG93QbG5aKdtdVyXnnEPMXlrD49OnLOIWMf081-n1IJgUVkSlkUPn7-_IVbZzmVWydnFeEshGw2lfzf__n3cpze-PqXqZrfe3Rv2fp5Wz-7WF9cr6_X3eL28ViFxzfTWGI3ygcfPN_1Q1ExRPKgJSdLyxOnJe8uN-3pHJEo5bTdypCPbp-YQbkcPNLpvVXqJtd4LWWMA1UBJQ1X181JkzX6wMvlPMe48iw5hbb6_u_8m2nMWfX5k2fL5YoZG_Oc0mwxu76-ev2ll6pQ3b9zJzDtr579-i998-9852cfzmafvv12E_W4CaLp_PnWLRja5tMnz7p9Nw7x5nLzd37jrxGolRhFRZBdqKWoxsjOEVOJGQi1iEpWKS40qqpSNEXngyOWcaxn8-5qrYChXYCvFAt7T4DgvCAAmgsVI3oTyjLud_PjM_BMi2XVLsxQgdSUmBFAkrgQDMBUDvpPLAKgaAhFQBI5B4BWiqnI2DtPBFRyEQMCZFVWZeYyRBABMxCDXBAPY4Q6x2gAcCjykkODIoxoKRqY5gxqNo2mpoilJMdkJpJGQkQ0lMhmbHLgiiObpQkRUOQA5GFCyMlSCouqjCMccpwpQkzIBAA5RstJp6RadJo0ZTK0UohRUyTvHBqaoQBUgVRBBUqBlCEmAAEoIMXShKpg4oHBlNUIxaRozCYCuRCqHaLGQGBOr0cYp7yPlkUFcXEclquuS9y4lEspkqGMw2hggmUapChgZdMwpJimMmmWqvGoRcbD31zATFQQFEV1jCUOJpOMiRQgCxRjSRWp7MfArEYuQH-zyVNybSMOiJxrKPYjkRWxrIIHz_JunDsPQpvPOuecIoqIYcYilnPXTy-89TBn7EcRA6x8cdjnVMwSYcxFxQrA_rKfpLjaTzH3sRRDX5OQny3qLIrkiHA7Th-eb0YV8EiMn13sJoRCZAYlmYAz0H49dtveJG-ebb2wiD2615TruN7HiYbtflDRUFtJ47gbrRRLCkPUaXLsjbBuG-9cU89miwYyKfOds2V3s9ldnt_cXCrwmGPlqnGXJMN-sxumaXu9xmBjWpc4okIcpoBsKfXbfQihaQMRHXA3JcYyJStqJUPJkIullDUhIREVlaOzxXq7M7VcJEthZiJq68aQun7c74eimoupQTZQpE3XMTE7l3IBwPm8RgI8jJcIzjtRLYR9yUMqQ0wFBQhGtSGW7T6K0X6IXR_HMWexXZdSsSnlgrwb07obh152KV92sYty0ngvFicpUVJRNHUOHZMiABEyVsE5IkbzDoNnAmBmQ0DC4KhibpwjBCY4BOwrz7M6VI4dYVtVDBi8YyQmCoEZMLADQzQkAM_MBKhIRM47E2EicuhYQY0g_Y3f-Fv_1__7_2N1cjsQg4FzqCpMWPvQIL72-qNPPv3EGDQbIBChd44IA-CrL7z4ez_4s1B5RHJE3vPhPc9mzGxGhARGagBqgIQIZjqvGikFEDwhGZooe1ezG3IhkzTkQDoLzbuffPqLX_vOen2z3dw0TB8_OUfjIvjk-dW__9H3H9x5kDR-_P5PF8ftN77xxh_80fe-862fRePFvG7akErZd8PV1fqFB3dPFws0fXjv3sX5Wk3vntx680sv3713sqoo92ON3DasWlSm9376tpRhMZ_9z__Bb_3gxz9e3b477Mdq1iDwNKWcVItWFdWOdcqhaoJvxxiffv55Nw7_z__Lf0VNW8YpjeX-_Udxvb_69Nknj589fXL9f_4X_9yILq43d-7dWx0tcomi1LZ1GouUIqkwgY7TnaPTcT94rH7zt37js0_P33_n49ms-t7Hn9Wh3m62COW1Fx5mzX3XP7-6uXP39PU3Hg27frcfJWlO6fn5BUtZ77q6pmzw9Tdey-P48ZPPXrp_HwBRS04FRG_fPumnqZ01F08u23n99NnF6a17y-M7bTXbXKzns3ldhbppH7z8gvf1djNc3XRAiEAMmEvupwGZ0bCofvjee7PlbLfeffkrbw3DiIamulgdg-B773wwb9vZonWOSywK-uD2XQFZ31zlPK3mdcOu8eS9q4g8c8UuMDlCMvDsgvdgwgcdBzspmQBWizkTOMDgiQjBLKB-8N5n9ax9_eVXQIWr2b_73T_-jb_5K1MvBgqg9v-jZMsBaQdiIACpyFQ0lkP_7NC75evNbsjJtaGolKxqpimxg3U3XZ5v3n5-WawQU105cqzyRQA7IHliIvLES187RhfcrK28czUHp1ixcwhV5RGUCEJTBc916z1i43jWVFXla-8cIhN579lxFVwVuK38ctUulw07m89CG9ysqZdNvWgqDzrzft4287Y6O1oGgmVTL2t31Fae0XtcLurZvPGeq8b9ws-8_PWHp5XA0aL2Dd87mr96-_Tuqp3VzHTIR2FRnVKeiowxxSR9zKqQ8v-Xpj991jW97vOwNdz3_QzvtMczn57R6EZjaAAkQRIQRUsmJZGSSIURZZNSIsnKVHYqjiqJXOWqVOJKPqXyIXHs2JYYSZFpThJFUqJIUUBECBNBDA2gAfR0us85ffpMe36HZ7iHtVY-vM0_YH_Yu-p59nrW-v2uS7uYiV1VeVMDwyIymCy7YRgiezLNALI_a3O2OpB3vJhPT9axEAbvQ-CnLh3ce3D2zLVLoa5Lli7KmLOvmr4fhmEAxGsHcxCbzaaEenp-cb7ui2pSGTUJ5Lr2e7uzinExaQNgXYXVELs-xSyrblh1XdOGnEuUTJ63kYkhj2JlPm8mTeUqKlB85avWTSZN5X1bV-yocmhqMReR4oKrah8qF1OctpULbjENW6ABC9bet8gebFb5eVPvzSYI0E6qENh0y6oqoalchbXp5VnrGYiw64ZxGOvgsgiKnK26pCaIIYS31wnYqrrOqoOqY17MJ0SuccEHHyqvhmaKiG0TDnZbEB36iJUrZn0XFSBJcs4NaWgbnjTVTtt4xBzH-aQCyfvzyc5sokVyKaLSj1Fj1qy5mIo9vlhatrfvPbrY9B-4eb1lT0jL8_Vr77x3Po7nRZbL5af_7MdfuryH_cCqD84v3n14cr4e3zu_OF6Pr79-L2mB1gNZPQ2TnVpzbvcbFeFcHj44qcICcjccX5BnUeyOlxJLitl5p7EfNx3yhF2ABEQsKZfYlzH1j843F72vqvsPLyazyXxvp2TtUylZdq49WU3qItaNmys3bgyWX_7BD5-en791-17l6_PNeVVXYml1fjZvw0c-8MyzN68uLzZI4crNK7PFbLEz--df_O7rtx-_ffuOlNKPm_U43Hzm0ocmSpBz1Uw5uLHvjdk5JmPNZgbg2FBNFdQsrtF5rio1AdO8XikgcRArzc5k7FZxWDeLKaJPKZVUCAHAAEmGiMxqJjYiahyTpFyGtRBTW7tJrUWI0QgR0TkHAsQsw2DF8jiAYwPjBnPXMyK5yjSjGZnyFtG1jfWClGEEMebAjKpiqTAhMUsqpka21QgBgAHRFrlARKpG7J33BESEqEDMmgsolFIsFjSUlFRLjqmkokXRDExxS0vIGUohRDPQnJApJyupgBmCoBrkggamGWJBZR0LODY0MLWSURXAJAsAaj9CFnYMZpCEAoIK5IKgIAWGjKNAMeiLDRlKzus1mJkWHbMVhVRIUklJRBBAYqG6ctNKU2aTuiXPAIBhMsmG1LpuHA0USIfzoQqUxyQxq2S2op32m5xRxZU89rLelOXoCFzLUiSnRIapz9vfLq9jXCYdM-RCSCpaBkUQEAADFZRBGuOqqUu20iuqaZZhuXGe-663nCWJFsnrIammoSzP1mZgTnPJqRMsqWm9I98ErwYXyzFpiVj6KKnQUEog70w0xdkEU9aAfjLnojljGcY8Fl51cVIFNgDEQnje5-m04lzmU_9oNZ6tx37sHVEe87AZqaWz083yOOYhWYwoxVF-4oa7d_ti2MQiujlWtBws58dnuumw4jL21m1kKBg1jT1zpaPuTBaeSPqSc5YEF-cbREQX6qbq1hfOiklEFStSV76pg5FtzpbdKo5jEstItr5Y5pSRgZhSylrMV-wCWympG1WyIaaYEFHNVNVVVREBIiiYxlxEclFVYHLsAlVhSGU5pFU35qLo3ZCSZuu7KEhNXZ2uB3ThfLkZxmyGYACmRAyGqVhUHYu0TZBi3aZs-rLq8ulqGLL2qSDzpktdjF3MB_vzTT-eLzdnXXe87k669M7J-XLMnZbjLr7-cPPuMi6TnPZDlwrg9tqAhNssISOh2xIziQAwBF958sweiQAZjRAcgWfygarAbVsFx03lq-BQlRG2IF-HhGaOCAn8tmkLSGSOqK6cJ2bAsE1klbJt_1qBedP85M_-xf_3P_j78519UEtFi5RYCigw0PX9w8uXD966_x5UDsBMxAAcIxkeHuytlkNfZNu-NyQpYmoGaApEQO97j3EbfTaworo7m40xbTlGTe3rKnjGNJa6gJb4-OS45iqn_o1b784n84cnx7g2DvXtu3c4ASj4xc7Z8fkTN55ejd2d2w9-8s_-FHh37caldhLevnNHSau6zlKWF8sH9-8nlcbxajU0u1MNVSk4xiGthgabYVPG1Qpivrh3_3ydp9N2sTN9_uYTOzvT27dv_f4__d2zk9OSFIMXIl-H2HUXD1aP7zyqqtr74F01W0yrUEMaSylVhSdnpymV827zb__gN4uWetoQwL1HD2Eok3Ya2K9Ozj_6sY8jUJJ8erocYto73CMtM9-uzy8eHt__4DPP_PW_8bMEafn49KUf-Fj2brHYLcy7e5d8U10M_eOjkyTl8uXF4d7OC8_dPNjbUXLi3f3lxWe__8aQx5LNUI4ePfrgs89885uv11WbJD791BOiOUyq177z_WtPPrVZd48fPxDM7DwERyw4rsY0IFo27btkWJ584klkPj_fjGK33n50cbHKUhD1g88_ExyvN91y2fd9rBGZODAf7O5slutxzKZ8cnTmCWZtu171m65jz0XLtYN9JsfOIZT5vA2OmyowQgjYeBc8V95VjpvGN54mTe2dM5OaWdQqxzHF_d0ZIzDCli8XPFdN-Oxn_9XP_uyfd2qO6ldvvXP58qUapyhFt9VaZwBGSO8Hf4hEVYuQJ-eIHUlRLWZM3ZiiGjuHCFnf3_6lpKnQpAmzRb3HIWcdknBw7Jk8oUfyTIENLXjnmbLl4H3jq8pTICKC4KlCaJpQ1aGpq8pXe23tKw_Zqsozw3TS1uR2pu2kCXVwk2njPAfvJk3lHTaNa-tQO-cACIEZ2toHTyH4EHjS-sO9ee3wcDF94vLu7mzSBMfE02nrzFrvD3anH3_mBkdrm3a6O4HKfezpyy89cWleeQIzxVLMwJCIkHKRfsjZIIv1OaWS1bavAskGlw_3wFBVUiq1pyhZUr4Y-8WsnQVWkZxFDC9W_ZCzqrmaAWy5GabTmpnSICfrftmP7Wy2XC4vX94vJV3ZXzjDNMa9acPERURURMpiZ6cUnVRNIEYFMmhdJYbLLh1frJWhruoxZlMpOTdtncWAyQhcxe203t2Z1VXdNBWTA8NuSKbQNJWrHLMRoiFzxQIamAN7JJIsjx9fNME5hKYKs2k7aUNV8bR2deC28juzZj5tVMu0qfOYiKhuQltXwTGahYqffeqqR8xJDC2WXAVMsaDCyaoXpFhKU9VkgCKLpomlbM_X3iGa7U6aOOYienSxqlqnYrX389Y7MRMbc9lsekTa9CMQOHQX5xe1D0CIoKHyk6Zanq-J4HBv7sCcmYjEnIrZ47PN5Ut708lsM4x9zEmgqpvX7tx5cu9gEWrnfRKjvcnt9fqnf-rf_9iLz02R_s6P_nDleBjzuw-P9w_3d64cLq4ckndvvX2XGg8Vb4aUuxGy7bgbjfPlcbe_PykiZZXG9cZPJymm-d4cERY7UwdaFMJkyoAWJS3PuWK1bTGjaIzeVy5Ad3yMwR9eaqn2872FWfGTkKScSca6Wg0dhBoQru7tX7t88PRzT58sz1_88PPMtQGtL1bzebg6n80cO8VX33nwx2_ePjk5n-7Nj0_HKhYzun3n8e7e4nS9fPqDTzWNv_fojCAnlUjowmRmaiWLSXZ-q-QQMcO6JuddtZCxVxMzkyIIiFaIoYyjIpMPMo4yjsTM3qsUYCRiK2pgEIuMWcYMKbnAbDaenno_E3V5iI7Ae0cqqlpAgakUcd6DKgIScBkSqPrgZRDVAkXMTMZY4qA5OkZfBVBgQlXNfbc9doKJSbaUiL2ZiCQTUSlgIJJtq-PNGUSl28B2Q2iGpqqKzGZKBEgGRVANvMfgYRv73eoTjTgEBmRRUkUmICAA9ugcgRQofwIO6gcwAQemBSQhgMUMoFDURIjZikJRtu3JbERDMNBUMBcYkw0JUoZYbIyAAKpgCjkjEKSCkokBioAWLbrlBOuQ2AU1SeerYbkaUl8YipKbT97PeG1W46ozLdolT0gI-XTZP1xLyoq6PF_lIWqJ8fgCxjH2oyPQrHmTmY0wj-uNiUqMhFZVrgwj5FxiTEPSmAlyvkgyJHbIaPFiBOJ2b8oAoXKOAVS0lKIJNAGIlYwVQeV4wlkjOhASPzUdU-miAWz6GCqfMhSUwUofY4wpldSNQ9yk1I8BnWU9P-220Nd8PhLZvOaL1frsYgW4PQJpX_LJcjjrtS-427rTk_Xx-UaIJgFAk6q1E__ozulmORQc0RuqmSnVfHKWxzFVM0mbzXDW5UFyl8tQ-jPtHvZgkAoAWJj4nIuUwgRxHLIKVt5QVIcxDv3Q1dOZFXXMMaesaqTr5SqnEsdkiuDdGMcxxTHGbDJa7mNMWYa-jzGOQz_0Kcc8DllQXV0pqpgZEDJ679PQl5SsqEkWsCICSGOKxZSJxy6eLVdHp-dJrY9xyHk0UcJR1MCdjzE43vSjQ6uRhmFMuQCRyLYug3ePupTlrI_ocJPyebf1vtM6lj5JNgPCGLOZqqgIkvcxy8lmfbza9EkfXWz6LIo2ikbVTdFBoE82ZDOj4HlrF_4T_gcGdg7JMSGYZxecq7zjLQWIiNEqz7XnSeUrooqdmHrPlWcmYqLKO1TdZggNAGw7-my__YmZiBCZ0ICRffCIqGQAJkkuTyc_-Rf-wj_-5f_vwe4hiW2fdSVsQu2Mbhwe7tbtG7dvu1AjEJiS463F9OWXX_qDz3-ZXYMGZOiDJ8Tt3I-IQGCo8P6LBggBEOZte3R65oiYyCE4RhL1nnb2pox0670HjYNOx1ldV6H95ttv_OCLz57GIS8fP3vjRkT3x1975bknnlgs6s9_9ncPD648-8STv__7fxAvyrUr16jyphnMiuaSlRwRoiKow6lr37p1-4uf-8O4StOdeSb5wue_8LU_fmUcun_1-18KzeTtR--KyK1b73zomWdffOq5xWz24L17T3_4peXFGjn0_dgsptzQ4nAvjmM7nw1jVMHDxc3Dgw84DuDwK__uy8187mr-3rdejebvvPt4OYx7lw6Pj09Pj0-OHx0DwPp0-eDB8Usf-ZhISmO_Xi6V3LLvP_nJj_0v_sO_euvWO7_32S_9s9_5bE_l9OLi9t2jcbd6fHzUpYvFbMqunk9mbVs7x2fL1cnxStBjXQFa46on5k3jPaJN6urh6fqZ65cWh4uXnrkhaXzu-WfimJl8UbnYjI68dzidzs9OzxchHD2-MzvcR--Kylvff7Vtp9672rGvmoK2Gsa7t--YFc1qarN26n3L1cQv5kPKb7xxq2mb8_Pzm0_d2DuYmohEuXL1atM0_dAdHR1P2to5V4fq0sG-lRwC9_24M5sE72rvpnUVAhMbMzGRc64OwTM7REYbx7iYTRy5pvWrzfK5J55whG3lScQzMfGj-48p4wvPPp1LPu82q7PVp37ghTL2hAxGJoKGSRQI1QwMRAyNDEkUxFDUALD2TiQfHa_bpnJMJqa6_cgFJExFaNIMGcTjmAo7GLvokRg8ALJnMSMOSMCO3i8dO3XOuYpcxYt24h0zEm2ZR2QJsanrdtLWwddVbUWcI0aovZ_P2srjYjJpgt-6tOZVxWDzKuxOJnuz5vrefF47Ntndaa4czK4dLnbaajFrF_MZMoOjYUzOsYhO26Z1ofbV4-OTymEbwhOHi888c3031DU5NkRGYM2iyMTMsZSkGlW3IX5AIEQTQSZA6GIO3gGhqd45Pm5qX1VcheZ0efbM9Z0ACCBqAmBZdYhxPm1jKo69GVw-2CfCLuc-li7FzTDWVQVqOztTH9zh5cVy2V-_uj-qDilrsZxySWl_f2_s-2euX7FcZlWNDETapWhEQ8pDTHVTqYJDTEOqglc1R1RSQdHKueAdMWkRBGVED5y7YepdQ75lh4BkuJjVs8Y3jvNYCGjTxapywTnnPBLsTivPTAhWsK6dqppBKtI0nh2rASN5x9Omrn2o2S3mrVMjhJwEAKLCRdcPIkMxAQzBlZwrB867cYw5GzD3aSilVH47GohmUYSiZGCN58P5tK4DBr53cV4FX4q2VUCgnDMRGmjj3KyZSEwxxv2D6WLSzCrXeDbQ945OVn0yg5uX91PWs4uL77_zABGuXtqdLirL-vzVg7r2F6t1l_Vi2T1_7VoZ89nF8Bd_9BOtc_1yfefk9LV3j6u96d2Ti0lwdeUQsSD4-STnxODU7LS7C6gKsNmIAtTTytI4rDosNnQDOSKGSV3nzYAefBU8gcaEApIBuHJYWYaSxICa6WRztlrMZiWnj378uWxgRXyo7711lHpNRQ8PDs9Pj_69T3wUzZ2cnZ2dLmd7s_P1eRyGelbfuHz9ox_5kBq8ce_o9XfePbnosOUHZ5vPfum7z3_0OrMeHrbmqE_lqSf3hvVw4-ohoUTt-rbdz-Po2sZ5xwiWEqpiqOB9erfRlr8DBibOM4FhQYnJ1yGu1y40s-k0rzpEYuc4VGVMFCpVMEQxIYdQIhCCGSo5YpA8378MwCAiy24yv8lIWswQEUmGBLpdDIpvKjNMY0IHUATAwLYG7iL9RkUBSVXNjNDMTFSIHQBZzpILEhGxiYAaKlguTAG35hHJqMa-tZxN1f6EVczOOe8lZhQhFSQCBSKyksEkdxuLyWJiAFCxUhARSsGcte8hptJHNINcmBwUcwTQZUDQmMGQRCp21SRsiT2aMm_hDGC5j6AIqLAdV8YRtJAoiIAqipIJMEDO268XYrIsMBZKufJMTCBl2wQoqkAoJaMKokEI2LZuOombVJKkfihjwmKBvWbVktJmoFzaKQApijgS1mL9wFJIVU0YEaWkrhtWA4iCZDJAp0McJW4LGwYqhJLXKa8iEZUcS0wm4EKVekFCK2pJrQghyFBAFWKBArJJkIoUyVriskdR68H67GoUtFI07LgsZbmO62401X4du8049KIZwCBrlFjiWa_d6BnJ-3HM752v12NSorqtLlZxLBIBTvpCavs1ZfPHg4TGY0pxk85PhryAo_UqbkZdJViltuFxtaExp01Mw4hZ8nEqR10AwRRLymM2nKBfMBDQNrG07hBUizrniuQSS0nRRErM3WoNCv1qjYQmUrKMQ1yeL9tp22-6FFPZshtyIVMCK-OIyEgoWhAxjqOCbZH_QFaKihRDEFBic4xxHOKY0fkxjt2Q27qOkoEgFe3H3G36tq1SsWZS90MmdJsxc6jNcyaMJv2Yh5SGWFISx7j0cPdsueyGWCRmjUUvte501V-sx0ersS9yshki2Ol66KJsopwuu7NuuH-8Wm5yKYoAbeUr53Ymc-9IrBBYP8aSRQ36JMhhPcZO8jrGotsrALGYQwyBt28g2i4uiRgBDJi5qbwP3juutmgQwEnl28p7TyCFTREhOEaC968EhA5x-1g42pYeiREZwHt2TJ6Z3Zb9Jd7zdkqWJFd25p_-0c_8d__9Pz44uGQiMRdQKVq8dwz2kQ88hcCv37mFnnCr7zBgtGkbdhY7b969zeCAEQ0IEEwJtoRiI2RkBFDadoIBau8fHZ845rRlxIiY2ulqiYieXSyJkN568ODyzuXC8tVvfPvTL_-ZUtK7Dx9Op_uSlrcfvBc7CX782rdvy1hP5vOR8IMvPF1V03snD378xz8zjqmYGsLOfL6zOKhcM6pa3UagMp2fpfL4tDtabp776MsvvXyjWy4N9eE7D_7jv_m_fvO9o_vHx8niarhod_eNbOw208k8lUQGVdsq8JCyGgxpSGXsuvO7733r1q2vpjzG1K8u-vnOTh2qK9cP-_X5bBJM6fatu7v712LOk4PF2aa7fffOzsHO229-58qlqxfHjzHnn_7JP_0_-zt_Lq4u_p-_9A_vvXvv-RdeWK3Tv_6XX1he5Jc_8PT-RXp2__C5a9d2m8nx0VHj_KRu9uc7-7PFxbI7PV2WmNMQ93YXzoe69sTsaj8U45rXZ_HV194s42hDvH7l0jgsvePj--9dunZ1dbFZX6yslOtPPbE-746GwTUNePcH_-6bWDlCCwGf-8BTYxk3fXz38YV6N8RURMxs0rZU1d2yN3Rf_Oorzawxs7pq9g8un11suqFv6goJ26a5f3rWbAkABASK6k6OznMGBfAOJ5WvPdfkA_vac-1dFVzFWDFXzJV3674PDERYsbt_dLo3nVaOiYwMGAkd_9rv_t7P_OUfD8rJ8NV37n3qkx-xZSZ2ZsBkpoUAKnJkQMyAaAg-sPPMTN5ziqUUUYZHR6t2WlcVq4JtZR_eEIGIzcybsikjliJkFmOeVR5EyECyOiIQsWSggAT-T2ppoMaAajKZtoHZEQbvmiqQYe1qz9SGMG_D7qIFMMccGD1Y7UNT-0ntd-ftxHMd6GDWNJ6mHhdtPZlWwcGlveluG_bb0IDtTZv9WWtazMwAvPdoOp9MptNJCJxjt5hMm6pSlHnwBOaRmckIY0oxZw4kKsMY-1wUEQMZAjE5dt6zIypZYy7DmLdshphLxWExn8ug5GlS1YHCVgzc59LnlIsqoGkZUwLCKjgPljI8PlsXlSpURcu0bVCV1K7sLZbH_ZXDhYgyIfngPe8udlJKzsrh7oyL5CTqkAPffXiashYzUDMwkzKbThWJEGrvgqO2DtcP9y7v7jSBCW1zsU5jRkNHQPg-Oa2ufNP6WRsazw36UgwRmTmXvLPTFFUwlZRILRhWTCo2n9UMxIaa86QNzNi0FRIAYvCu9W6xmOzM2na7FCU7Sd_35AlxNp92McdSEDSQz2msHJkBORd8uFivkcjQDucTRAw1L_vREUkRA92b1hSLisSi87r1RCaCgF03xBQDc8W0aBpGLKUgWOXZs6EoIPQpu8rVIYx9blxIBcTUeTPvWOTfff2NH37hiUkb4pDfO7k4Pl-9_c57Vxc7V131Vz7-kjPWIm_ce_CF7925fO1Sv4yX2nZYrWeOVlmGOKZYPDN6V9CKaF9UFGIc0FEG6eOwszdBEBZB1JRSTNGB9EdLE0VEUAQC9CySnGNXeSJzjuOyQzRm3pyvG2kv1l3l6369-cTLzwfvGh-aMDl6cPTUtUunJxeLZrq7Nz88OAxVNYzdi088c2XnICmeruPto5N6wteevPbg8emD9x789E_8yM5sxuTeePvByePTj33w2Xi2-fhzNyv2JF2v_Sgx1_O5pKJGZurM3sdzDIOlZJotD4Rq2ZCc5WQ5gQqCaUxIVLpVjINJiauL93EXdZtjdG0jGQycoQOswShdnKbzh4w6rs-VoJ7tlTErQepPXNsyV4RMiC5U212BDNGHoKUYCICCFjUwQgDg0DC6UNUgAgBShMwcOChqRc2AvUcDUEFyAMTsyAzNzBSKaBGNiYhAxQzQERHkMZIBFjFRNNNUchqYCc3SqicmU_NVy45JFU0QwcBUjMi5umbnQMQBgBTLBUxBCuToHZIZixKQJ5f65ICki7DNCBiAmKakCiaiqkSgY4QiPjgbRsgCSRARSd-f_ocUam8pOWbMidXikJCJibQgOK4WjfTJlIwZ2BUxN29BUlVjOl9LVHs_FSUaU_f4HFSzgGVJ552NGZIMp70OIkVU1ErWOKAoGlgpSKRjkpzMRIeIUqSLRkVyykO0sjW7lbhO5Bwi5pRTzilmFTUseRgsZRgSxAJgxObZ0KSMow3CjhAxDUlzYYQ0FBEjh5t-zDaWEnPMxqWYDkOOkkKTxnUch6SqWLR0fR5iXdOYMjnXD1FS7sdoYA8fXVys-919ZtL7x8t1N3argRnbwLnkdhMfv3vmcgbI0wVuLi7Ykboc-01c9zGmzSZXbZv7EmMpon4R8pBgSIwqw4hSvCMXRTar7vQkrtel72QcmZScciDbLudjTjGGQOwkj32_WhrY0K-lxJwGH6iuApNHZMgldX2Oses2oW5g2z1XMdW6rup6AoC-9kZkxL6ZuKZ2ziGQgZwvVznmOKZhSFmymF5shoyqRAogROT49Gy5XHZDzEM_9l0vWX7wIzf2Q3h0cvHuW8f3zlZ3z1ejqZqthxgVmqpexXKyGh-cbs5XXZ9ECDLasu-GpN2QQu3PV_3JchNT1mKOcFpXNfvYxy4m8pzUshRBWm6WviYVQQc-IBN4RyFwcLxtAztHjOQc-MDMFBxW3iEhI4bgmtpXjidN3QTvDKXk7a7dMYspMbhA2zkbEDy_Dwb1DLV3DtkMwAABFdQhMjtEQlUkMzJEzTFdOtz90z_2I__ol__JbLEPRXIRBZUiDjGl_PJLz3XrYbVe67aoA8YMmuTDH3r-62-8boysgAZE5NibIaIRkpqCGSKpCiAQgUMsKsF5UwVEAAyI7x0dXVrspgKGRmB3Hh0dtvN1H1er_qPPfODh8b3H7z144okn7p4etdX0b_yNv_NudwIYP_jycw8uHnzli9-6cmlRbBhXy_6s84GC5-OLs5xGxxolgZbjh6e337v7xT_-5uu3337t7Xf_k__N_-mf_rM_GNerAiWX9I__0d-_fONan8dnXnrpe197fVJPDi8dXLl0JfW9D8EzC2ApKlaGfsgIpSgyA_FmtSyliOhkPkMoUvRw_5L3XrJ98GMfqTwbwGuvfv18vXbU7h1cuXfvXk0-xdydn7344kf-9i_83Jc-97n_5v_-T1559fUy2HKTbr_73snJgzDhqsKvfOUrb7z62qf_1MdTv2blwGEs8dGjs3HMYMhmonG1Xgnq_s5kPm3r0CwvOujkcFYPQ96UYb3ejP145_atj3zog2TEDP364vF79z76Az-yvljnsTA1bjL3iipKWNVscUxRwNf01M0rFchqtX708PjOu2eC0Pgwa5qDw700jhfnq00fc4qEaMBqutjfOz8-glKWF8dtPcmKb9956EIwNJMCZE_duDyUZJL6Yd1UARG8Y--pqZxjx2QEQIjOOSIw0cYH77wj8mz9ME7qigDNwEAJ4fRsU6x85CPPq8p379w9vLQ_n04UAMAIlMCCD6pqiGpAiCrmyI25iJkRiNqkqerKr5ZdMfBMIKZaTIQBK--ryrOjENzUh_Ozddcn267DiJw33j6zRCaAak1whGAq3hMRiZQ6uBJTMVGUpq0kCyMEt71LKAIqmQsYmNrgq8BNVTVVmLd1E_ykbYKnm9cvkcKsqa8e7B7uzS8dzA_nzaX9xcGsnTc-SFlMmsAkWWIsfReHsZB38_mcEItpzvlwb-eJK4dN5T0AglXM3mH5E-kfEUkpMeb1kHKRAphFsgmR1d55pCRAhEVh0tZ91pSSEQOzEQOhmd64dGhZPGNTVwLQ9zmKqpmJ5awOaVLXqnR8sWYfBHiMiZmv7O-2bTWfti1Dt17vLloRy0lykTHFxe7McqmrZn9v0Q_D4d5is-5Ol30GWG_3PaBasuOQcgJQQFQphLqYNm1wk7parXvLMmkbR4BgIfgQaO_SfGe_ncxCcIwGnnkyrSbzBhwRYeW9Y6YinvBB7KHI47O1IxyGOJ3U7aRhxhD81luKok1wjEol7Uxatvzk1UskoFZkTIf1h9TMDIckxayAGplovLI7r5kAEQk23SbGXFVud1ojCJilVAzRIaFCYJo1zhGJaioyqRsFBDMxrSo3aeqKOBCnlLRkJJg2oWI_rZrJpNGcjk_PJ80kELdNte6GrtsA8XQxLaqr9fBDz169dvmKFHl4vHnr_gNfQ900u9MJKe_MGwSpJpPj5eYHP3D9yt7id7_wzRs3Dk34rcePBhkyUhZ0dbW66LF2mcACUeCcoiIjIEmWdQrFuuNlVYVSQIlV0ZSlqGgxMpOyBVL3MSkROIbAYOoZNhfLg_3dT374yQfvHSFSLOMTT147e_RQY8IsBDRZ7HXjeOfh49PjpWo6OTptXHP10p5Dd_u9oy984ztdP-4c7H_pj74upAlLdTWcnHRfe-32zcPLn3jhQ1MLD-6c7jUtgScf0DUwdkfMTL41YmNXusGxly67xVRFCUFFRYQCk6NtahZKcqEpWX0dNCdJEbR4T2W90pLN1MilmLkKHDwHj8jhcIaAaErs06YrBYxbP90N7bSMxRRMTdSQHJixD2ZbPLaEyRTV2IRMwcB5D8gqCqpl6KUURqqqSrJoGoJ3rEqIpIoIMsYt0t8MYPveLIpMqAqq2g9bv2mJxVQZDUTgTzavyGZjtJRJwFXe1IgIVNHIFFTMijK7Lc_cYpFUAKH0g6VMCKBFc0YVGQsCmhkgFRF2nJZDcAQqWhTUnCM0hHFERlAjMh0ixCQxGgLkhGogaqOiKBQFdrIeUVVy0XHQnF3lNQkSmCmHug6BgEJbAZMohYN90WBGJWeQTKQABaHkvi_jOJz1pqpQ4nm0XBzkMg4ECSxrTDJmLWZiYjp2o6asKYJI7lIaRaJ45yEmuxgwZUuCVghK6cdmUSNTvTsZzzegAKCSYlltrB8tRbAEVkCL9Un7ZFkdI0k2NEPVGM3UnJKnuq1ilxFkc7YxKSn2m9W42YypRFBZP47DkNEMVFEzmiLa-fGyWw1JCpgOXZ-KbnJersdpFdKFnF8MYyomhVUZynuPNyXn-8crBKAa6jmvHo2cOaeUhpQGTRvRUvxUo6yl0oLKExMZqRREADNg3vrrsiiiAzEs5hms5NxFFSs5l5LNipVipWjWftnJlnKcIxRlUtMS-z6lJKUwc84ppURMs52dkpOZlZQglqaqJpNJ7HpHDhCy6JASBWDHMUdBOVueDzluulQ3znle970orFcpDjoMERi6FDfDMMSYTXKOpDqfVNcP5jRmCE4MKkex2IOz7rt3Hr13sTak82Vc9kWRNrGcr9fgq_N1t-rG02VHSD64rDhk7XPqY7rohtVmRHQqQkTOh8qFkq2u235MUrRq_XRej0Npva88OyaH4Jk9YmBmQDIMDh0xqnlHhOjZKqbgyHvyjhvvgmNUYMacR8_smOrgpnXliVmx8sE7xvfXgVR5Ds4RICF4BwTACI63Q7kyk6pYEZOC2z5AlquXr_zIj336l3_1l-c7-yWmcRhLScxcswsiH_7gs3cfHCkR8hb1C03FQeQHX_rI51_5tvPV9p5gBg6QcHuXQFMAs61QDACN0QQAbDOOBOqRPbtus9lp5wa8mE9yktXZ-XwxH9fnMOTFTq2qe3uX9vd3xxRvv3a0mM0enZ4-fLD5-b_4k5_911_anbbjiBzC3bv3r9y86esApiKSlTdd9_joBIE_9MTlG3vzT7_8iTdfv_WZD78AXcnD6jM__ef-g__l36ocHj8-H2344Y__wK_8-m_82v_vV379X_wzMr12_Qk0JnKgBmgyjvNpO2zWwXtGBgXHHONDj43GflK1h_u7sV8ul-tu3e9fOTx79PDR_cer8-Wm6688-eR7D-6cnZ3M28nJo_svfeCFn_vZvxRk_C__6__27KJzkx3z9VgsZ9ksh34sfS6d2hPPPfnii9dDBd_53puvvH1rOW5m7eSpJ69572ofEGHo0-2Ti1XMtQt7kzmSff5rXzk6PhrzsFp2Qxq-_cat3YO91fF5kbR_uLfpxsq7cUgP3rt_-eqBgX3v1VcXO3uTugURNDODN2_fKlHGITWhqsjnzUo1_pvf_cpmk3MudV3t7Mx3pxPPoClVk_ob3_5ORkS2KrirNy-NabNareq2qb0_mFWolkp2hIDw3FNPnS3XY4pq3nn227MVQOVd8BTY1cF5YjLzTIIwnVQEwITOO3aecSvdTo7RO_ziH33-hz72Upi27z08Nq1f-tATZNk7BhRzJiJkgEzsEBFECzs0EDJhBBDzzCGElAoBH86apq4UQFSNgAM5JCby3qloIOhTCYHIETIZwsUIjqkK1ZYj5OuACASIQDEXZhyzFCvsfSlGRjEXrpjYKUBVexcwBGYmBDaEtmECIIa6dqilCRwczJpq0YbD3cl8UnmyOrjdJqBiRVQ7N6-bnZ0ZqvV9Pt8MW4GhavHBk_N17duaJ5W_sT-rvDMxhIKIMeWYBJBccExsCjlbVIumRjh0g4kdzGoCKDmPQ-5jyiUXFe_o5GIFRGJQBTeOsa4qNL26mHv27Plsvc65CKiB7swmW3NQWzkpMqZ0sRlWm27d9967g73dcYxdNxwupv2QD_enF93Yxfzuw9MUU9PWoBIC786nDknBP3h0HKp6VF11HTKL2jCMXDlAIwRQCZ5a75443J853_hq0_VpzOycgTVN5QOBlFlbcQbr1RVcTCez3XY-bQNSTqWYFSlFLGcYjQDxetXYlpoCWPvAiE3jmzrs7kybqvJEYbs7UZ1UflL5Wd1MPW_J52ogmpEIwWIct93LynPlqAkMgKvlZuj76aRtahdI99rGMzuHakiefKBc4s60YsOm8hxQS2GV4L0YeEfBM3s3SuziWNfBezaR2WyyM23r4ByRioHKbl2ZUk4goJPJZNLU-9NZ7d10Wl2_dmUo9sqt--djd-2JK242m9aTAHZlpx7GFHP-0qtvPXHl0s0bh1cOZos8EOZv3bnz5W--fX40FsE0RHQ0ubrI3SDLtdecxiQCrnLUsjAPYyIfJFseSmiDbysFQ4_c1K6qUUFidpU3xG05UIkFoOTsiNj75fHq-PHGEbKOHjEAWClVy4eXd_cP9k_PTt-6fTfmeHB5XtfN5my1s2hQTYXWfXz1u2-cnJ9_41uv-ap-_uWn1yXb2el5v7o6a569dth6uT6Zvv32urvQ1ZjIwDQLQs5979oKQoPEKplAyLEBaVEA0lxUFBQQyMghiOUo_aZqZzJG5wMCWBY0oO1IZEKMFCoiryVryYZmGYxqQxpOzpBQhl4MoKoEEcCaxSGKEqAM2US1CAFCKdvjOBGAFKfgyIEimpoIqjC5LT87x2E7cGspqsrel6LBOVBDQBPRkoiJEK1EM9zSzxgJVYiZHZeYCNFMJWUEzFveTNMQ6NYcZACSM5QMlrdYP8lZcwJTYpaSCJUYiTDUtQ6jpgwqQM5KITVQsZSZ8E8USFaFChRCXUMxVEDnLBWQjGaYM-oWjqkAAFrIFExBDLIQoIk57ywLuQrNpI8MJjGzcwi4ebSEYq4NWgB97SdcxjGvN3LyuMRsapZK2iSunZWsJVlJjFHTCEnKOsbN4BxKLCDq2NhANlGH4ivnKpIYsWQGBSogkiVBzARMCKhSzjYQsyPWDGC4WXc4rwUBwMoQq0qtREgFDCAJiJkl5wBSJClaMs1YRNEMjVJvmpVqh6j9ZihFqbJxyKY5bVNbBDEX7zWNg_SjOq0OJxcXHRJwbUkyMikoOT07W6KDYYjVBIeYshUGIxo3XZdLoQb7TYdQuk0_doOVqFgQM4yDDIOhQgWIIMpBXR0VH6_4QVcnkbPV5t45gLrGGYNvqgLAVUshFCMAMrQALGOWmPIQpRQy0zhCjpZFYgFFQ2RfTee7PngidA6kJCRC7xSw36xjP5aUfaiaxUxAx3E0hwZK5BitbSdQqN9sSFRjmU3mTVXNp7WK1d7VVR08Zs3DMMZY-iH2Y0rJSjHv65LKmOTa1f1Lu9P1ENeroW4rdr4OgZnfuHP8vXcf9wbmcDVERJpPuG4mRyfLo2W_GlIX81k_blIRxKKQC5ytBgbapHRyvjpfD-ucQ1tXTaOC6-WmCdWwGYN5HsvLzxxc32lbj46JEANTHVzFVLGrK1d5Fxx6R4GpDuQQPSEDeKJJ09TBtcE7piLCVJkCAPrgHGNADJ4BMDgXnHNEJOCIHKILwB48OwYI3m0dXYhoBszMxD44QFMUMNOUrx_s_Zmf-Ilf-dV_sr93ySmoKpiwpyZU13Z3X3zmyVdffwudY0I1deRd4EsHM-vi2eaCBAEJAICREFQMCbftJARTMATIOV_ZOxjHlIdkpsTkwI5Oz9rKDyXF2I8pkokxr1bnO7vtfDp55fXvOwYo3bvv3rp8eXH96jVgJonXd6maTa7t7__on_rhktZ37r_3_FPXsmXWspg2hzstehiH_uj87Gx9ceOFp6rGf_fb3_0Hv_JbB4eX_rO_9z__j37x5x-_9f2_-7__z4n0P_97_8W8nn7oYOcHX_iR1NlHPvT8B599sWnnk8V-1bYEUGJuZ1PNYiWj5jxGzTKvn9JxYKBH9-7uX7uORCn2q-Xy4vh0GPLB5Uvz2Xx3Nnl8-20qaXV2XjXVX_lrP3dwbe_XfuvXv_P915yvP_DxFy9dv5yydqvYzup7t--uztbv3T1-59adPPT_4X_wMyf3N5_7d1995_793_79Lzw4OkIp-7vzk9V6SBIL_NFb73zpzVv_-Nd-67mbBymWP_cjP3hyvt5p5o-Oj2Ic565-9btvXrtxNcZ45fq1dlorAJgo05DijRtXWMaTo3f7YXPl8s39S5c_9vJH3vz-W0YgxYrAj_3Yj3qmWd1-9OUPTCZNzlKyMPNsUnvHmjOx-6OvfwfBQNV7furJJ48fn1wcn8wmbS5pPp3mISNiHRwSTdt2HMtmKIFdt1whcsoF0TyTZ3J-68IwQFO1IsKG7Ln2OEa5crgDhIyoSs75OKYHbzz48z_56X4zfPuN9z79Ay84UQLEnCsXJp5nTWgr1zp2ZpPWLaZNzeQBK--HIdW1r4JjgJhzPXV1XZkamPrgVU1EAYwYHWOMI4gWEwUEIBVrfDBVH5gAtikOREhFCmioHBNoseBZkjGjJNWsYhqIQUQVUxHnqfaOBdnIIVXOzZswq_28qadN2I6Vh3tzErtxad8jLtpmt27iGB1i29TTtlWiMVs_yulyLWIpS0yxqqppUyPqGJOpPnFpb-Ir7whR2XlRMTMfnBmompkVhKGUJEVVxzF5z1Vwy814f71kx7KVpyGIAhgqsSH0MSFAyiKqk6aqPCOIqjnmTjIxOoZri2kqMp9UxVRUumE0VDNt6tqxa0LFwWWV_VnVb8aUcnDunfcezKYz510aega6vLczDewALrpufjBbj-Px2WqLbgMR5_y2KoAOmdFE9nfmLfOirfuSUs6LWUWgVXBtE2SMT107qD3VAUEViFzwlQ8pjmA0qdtJVc1m0_3FHImGISri4bWdWdMgcT-MhhY8WZamCibqGNum9oiMVFJpAgOUScW1c3XlyBMaMCEQFiADNkDP3lT22joQOgIiIIclddf3pofTtvUsAklgLBkAdvfne_Nmd9owQtGyvOiCZwRMMYc6zHbalDMCtm17uFh455i4qgKagUod2ERPz1d9yZsUpZShpLEkUzk_X15aLGqmbHzn_smXvv2akra704cn5-_cvf_MjcO9JixmLTt_dLq5_fCIJg7BffZL3_mBH_zo46Ozb7_5bmGnxKYGpSBWuWDd1NKNIMkxBeJyvqonVagDEhXQ6V7db3oFijmTd0U0pYyeQc2KpH4Ii8YUtGTLkrreOz_0nYfy7DM3-nF4_fbbX3vn7mtvvE1Mn_7xH9g_mDezyZVLcxX84Aeewtqx5zhsrl7d_9hLLzjC19956_XXX7vx5OXjsxNDvfnk4QLrcTkaN87Vrg2Lwz2uGz-ffeaTHzpZDp__4rcIAKd7cxtHHYc8DFDVVlVceUjZMXEI4AhF_HQCahaTKTsXiIOrKgAgVHROSgFDYtaSpZTSbUxUSgYT8kyOJW3rnoUqx40nZ-xoXC_B0nR3HxwooaSuiKgaVc57b2O0VIBYxqSpgBJ7l2OvIuAc-goBCdHSCAqEjApMgCqSMoGZCToGAxcqUGMiVJWY1ATJIxIyGoiVbNsQj6gPAVTQjOB9ty4g5Jg0ZzNDjxz81hKQVh0QAQCzg1JkGCRmEyUDSxkNLSVkACmgimBMbGNCESJ27FMcZByd4zyMzrF2A6KpWGCCTV-FighIlZmsKBiAimWBECwrmzmm952ROUMpKGZFScyygBhXYXJpT1JuFtV41mPbUJjkhDBE60cgD0V0VEQo_TBsetkkKAqrdRlzSaJRSCU4LuuCBViABC1l50i7XpaDjBmLYVIoqqNBNlQEJBTTsdgglCMMKcfsmoYJ46p3aCZ5Ky8b1xFSBs3ABSSBKBnmVWTntUcojF2RPmlOaEpmUNBVOIwpJ2HT4bS3lMaz0fW5EsGscj6UsWx7lpAhno6I2PdjGQsb5m6EUtZnm7gcbEzTCT9-1G3WYz90MaVumfu-CJVu6HOfypg0GyCxc-kiwiraOnERi6OtCyVbTL0MnVmRQbz3gB6xmkwnKKZRcl9aR82kFhXwXsCEMeY85IEcl1zA4TadZoDAwUCTFENjAi2iKk07QSJRiDmRA-8CV77EGIIvqTgfyLGZASqYWlZCnTRTSZkBSkzDZo1EEksTanZu1k6GXuvgR7HlunPBZcllK_uQhIjdau0rd7iY1kTDmFbdGEvp-1jMCGl_OjvY23Eu3D_rHi6HTc6Pzrs7Dy5Oln1fpBiux1Q5GqJ0XRqSgGFRpBD6bF1UIloPKcZcUkY1RFATIts_qK5cbp49XBzM2olzgcgxOk9ESATBUXDoCZmxctRU7BySgXfkHNeVqytPYFXwiGgIhlhVnphMFd5XClLtfFX5Lf8nEDuiihkBVIUQvXvf-ekdEoInqpx3RMSIoCDKRFtGhmS9NJv8pb_0c7_8K_9kdnDgmcZxKCmXIlLk2s7swy8-9_1bd8SwDi7lEdFA6UOfePFf_uGXjRjEmAkUTdURbNFfWxSZGpjJWNKl-d7X3vjuKsa89XgYlhwd0JD6gvWy67NE6TfvPHr36avXun7z-tvfn0x2Ku-__Edfb2xClL_1ja8--_z1MQ7vvvP20d17H3nx6de-9Z2F3yeTfr0h76ZNDYgXq37n0t764uLlF1-4_f23r968enhl_p1Xviotff5rr_3mb_7m1776WiZ9dHT-xje-cfnSpY_9wKd-8W__NV9Pzrtzb_2Vm1eLCvlARKXkuIyVd2aSY6y9d2YSIzt2yFLo6P4DVzdjjPW0urg43XTdZr0kRslDv1yenfc_-5d_8kc_88nf_xf_4rd__bc3K1mejy994pN_9IWv9X0cN0lNYxxFtCA0TZjX1cm9R__l_-Pv_9Pf-G1Eeevbb0q__tVf_a1f-Ye_-ep33zl-eDoO8XN_8MXv_-E33v7jb4Hlvfl-Lnmd5F--8sqj1cV7j89i1Gan7ob-pOtKkZ3ZZOdg_3y1HrM8vHv76tUbb71x-_r160MXT06P5tNZJXbn1i2Q_Mbtt9cpldRD0Rc-9oGL1fnRw_sP7ryXciwydv2m7_vYpa5Py9Vwcb7xdUAOde0_8Pyz5NRXtO5GAt5ZLDabDoyaqi1SKo8CqThbDnGVUiBziIGJt4k1Is_omLb2CDN1zEQYKnpw_ujq4YGqFUkMyo7_5R9-_oc_9tSTe7tf_tprn_zkBx1IEGPCUDnC4hA8ExM2gaaN2_E0J_AEbeWqwHuzqiZkgEePz-eTJqBnBIdIWwIXgCNDE1ADst3FpBsHUPWOEc0xSxFAc0TkmD1tr3DeOSKnAoSuqUNbV-TQ1OqKDU2L1D40dbX18YFB8OQCBYbKuyb4tvHTyreVm0-b1vPevHEg87YClfm8bSu-WF4EpsW0DsxiJgVWQ1qlzKFyjpkweJ5OGikRzZy3q4c7e_OpCUrO6FBUmTh4j6A55a4f-zGlXNhR5b2o0lZ1FMs4ppuLvVTMATJzCME5VxQen2_uHi-7JA9O1waY1UwVihKalpyyVM7t7-9OfHBq45gMGJkHiWISnAdgU3De55xPlusC1njamTd1W1We173GnJnZs5-11dXF1AGOClny5cU0Jal8SCZDiuxdzYEAiGzaTtuqevLa4cGkmTd1E3C16kS0roJjOtzfbRt-8bmbDDhsRs80W0zqOpSSjx6fqpaYcx7H4F3tnJFJKZu-JyutsBps1r2aqmkaYwjkGVNKk6pSydO2mlbuxqUdD3QwaxZtBZJLyVIEERC9IhYDF7xHnATem7W7k1qjrfo4bdzNazs39hdOFBWy6pCymQLiznwazzcTdmyGCimLJwoeQ3A-0P58Mq5HLAJari12GDENpR_6SXBpjJVzakCOjODGpcsyYlf0_upsMZ-mfphVVcmy7uOr79x94-67__4Pfzx26dHxmXPuhaef2J9UTHBx0a-HdLzqAOADzzyBDiYG7X77j37zqyvg03XJY3RkSJyG1Fbk2Lez6cWjIZdceS-Z03kGJMdUhuR95YIzAC1gBlhUk1hWBHTelbFQPSFUKAre-VB5huV7R9xUi72db3z7O_P5zpOXLz9erch7SppTrIML3jvMs2lzfrGahvrV73zvyStXavLrvn_l1bfaeSMi7z04HrWszntI6Yc-_IGvfOmVa1cnyvD9W7fFuTfevTe91L7z4N6PfuZFAqTx_CLUNauN6wtfN-TnSUFzIXYQs_PBinkABiAgEAFyaiaiIFqGLrRzIybHAISGrMoMLLnyNaikYe2altmXmEtXwIV-2SNQM9utPfhJNar4vcvcTAh5cfM6MJciagZISGBWTNMWjSBFzBSkaBr1fZielXFg74hQs4iYmTECEmrMpiXFER0iIiBtN3IMgMQmVtL28KCEgApmZqaEhCUzIAGiIQOQCSCUYUt3NjV8f6-bZRvJBiZ2AUzRVEtGVQIjNFuvzYyIEZkIAZDZI7OAOSTrY4kjALBzmmX7E6bqqlqS5k3SlDRnKIlMyTkEkm4DohYLoYGY5lRSMQMzZILgUFIEz35Sr47OwAetKwWr2wrQvEMYY9VUPgDEbJKhFBhHXxlIAVH03rKaFMiZpJRuBBNSYZEyDnkYEZTAQBREISUyARUABbFtHBUATYulbGBg5PanoAjbtIMRKECJaAXHREVIMmwGAIMYHYOOCS2rZcSCZWQtJKqi7Nk76E8GSRlRTURygW0bOwslLevBObQxbROECspsEkdJ5r2DIXpTl4pcZMi4c43TOvZnXRkTxJK63lUsJaaTJY4bgAIxkVeJA6RCfaTzgQ18oIBARVAhr3pVy8puMlFywkAeJSdiDZ5Ny3oYVcwIyXO1aImxXUz7ridDdo4MtKivKvbVZLbwbVO5wEhM3E6mhFjS6IOPKRERuZBjtCJqGNMYmuArN266nCQnQ2AwRWFEZoSx3zBiLKWI-MCbbgBArHkyD6CWtITgc07OuZJVUqq9V0nAtDtvr13eXa3H82V_vurPu_7xyWq52pjmTRxv7jVS5L37Rw-Oz1ebtOp6cK4gCsGQc5-1YzXUpLYe81k3ZtVVTEvNCeWij2aQhjKMw2bTp5zbthnH8drBfKeqApInlJyQENUCQR1oXrvKcdiiCQE8kydqg2-rUAdfe1cxVgSV58o7IhRVIkJCZiQiJkCwygUEq5wLzjvCtubGcc0cmCtyDbv3e8BEtae69s6zI3K8fVAZkdCMCNAZg5Witde__HP_o1_6pV8SrJqqBVNAVZGY8t58MptOv_PGm2MuDonUPLNH-OQnP_RbX_gSolNVQiBCMwNTRjJUZmM0AwBSRPrWd1-_fni5iJnZJmWunACcL5duXvdjrn2TuvT111_7zCc_fdZvTk-HG1cu7yzat95541M_-un16uJf_eYXGxfaab0T-PkPPFGX_LVvf_f_-B__1d2qXXi3mNSXdnamdd31neR09_FFtz6ZT2bffeWV__N_9p-szstsNu1WMSV-6urNf_Zbv_1_-b_-vWeeffIb3_zCT_3MX_7ql__4p37i0-_eeXjtiauHOzMCKBm885IFSg7k43oModIMpYiIgKqamhSVNJvOJWf2fjqZTycTKwU1x4394A_94N_9u__R_-fv__Ln_uDfZkVs6npSidIrX__mB1_-VOzS1ev7N25c2z-4FBr_9Aef3Nndf_apm_tXLz04uti9fmmIlAHv3z9ZXgy3Hj7-3Je-cv_hya_-889-4xvfwzK8--bb_UW3u7uTu3J0dHr--OKPv_Wdr3_r2z_80Zd-7qf_3NN7Cx3FGB-9d__m1Wu5FPZ4dHzceJtM2-PHj5yZjOP9x3erWRPHcVitv_1H3zBSJS4m_XnnOB0fP_rKF78S02iCB7vzJ5-55hzSpFn1Y0rlj776NUBULZtNN93bPVuv7t29x57257Nvf--WUxEpBFg1oa1aYnfr6HFfpIgCmIrgVggPxgiOkAnJUcpKjIFd68Kbdx8e7C0UxNSc43Wf77598jO_-FPfv3N_Z3_xxI0DyBnVVBVNA2NgDJ4cqSMMTEVtIK0Ds4fG46RybCqaqYH5tEEzAgyBmNAToqknMjUEm-1M54v66qV9AjQ1JAYpCGaiQ06ChkYMyABMyKQhIKEBIDty3pEjDgyERKyorvLEULXeB4eeJ23btGESaHdWPXt1fjhrd6dVG3jScu1p1lb7O60jdIgIsDOfzprWREvRbkgnF-uxWJdkMpuNKfVjrCtnotN2apIax1dmE1RVKUWkjMl7j8SSdYwl5qwAAuCdnzV1ympiCqoGnmnaVORIUo6iSRQZUiljLg9PV6uxRKQ-lXUpo5QhRtqqlBnHIQ1aGJWJB8neUSm574cS02IxH4fsHDpHZKpqUVJNVIohURrlbNW3kypraZpqMZvO68CM7OD-w_PJfP7gYtWnlETXw-C872NEhjr4WVPHfuMJ96bNYlqLyfH5Bkx2Fs20bZFA03gwn3nnuj4e7i3UgAHimIcxpZTZB_a8tzudB19MDMA3IRvszGfouPLctpUZIOB00lbINWHjHJpU6BxTVfk2uCYQqFVkAQGKlCKh9lXgae2yWB5HBmXQdlvvQ5lPwnRaN-Rjt6o8qemYZbUexpiHIW2WGxFBUUfsPK-WIxigaHB4uDs5fnCkqsyEikCqJoo2xuiIKu_UQETHJIIEjkbIm75_9vBwWlWzdloHP475rbsPnfcf_tBz949OXFVVNe_NJ_vBzb23VDzDKvb3u4sP3rh0cudsfbTaKHz59Xt9y3h9BwIxAxclk3YWRHXMBdnv78xxVQBhOg8lCXNdRJB5GCMyO89IIKIctgFyLmKOoKpoePAw1HU1m_iqKTm5UF25efPZp5555salV751Z_dwgZ4c1ifd8pknDj_x7DOUhmvzBSBTlrvv3G7a5vjx8lMf_0jepBSj1nZ6fHH33nuzncUTz-z_zb_2k41v4qarZvN7R6t3750lka9-4ZW3bt3_zrdeu_tw_ZU_fpvYkeYiRcmxdzyenwGCm85FAMygiAwJGCVG7wPylh-cUJWd93XIw1iGja_qogbs0JBDzcBliGTK3ktRSRmQq7pOqxUBVtMpNq3zICk5KexdvxlyP6TVWged7B9SWysjOTIzMiRyue_RO2OvxNskI6oRs4GSqY4j2Hb_j4QoOZuCn04kC6qUmAAwl6xbbH4UIKDKba0uBIZmKgKAUlRLAcMyRgBtmhpNLWdUYUegRsQ-1EjEDgkFcmbHRGxbbxIoqEHJGnsZopvusLGWrJJUChJILkAgqZgpkWkWLUK1t21-HcAUDQAQQAqlCN3I7KwYAFkRQLIxgTMlkJzZoQ2jkYEnRRRTdGxdhIQ6dOyo7ExgVqWi3Fbd8RocxM1QYgEiKGq5gGFcjlAExmQx2Zi0-xNfRpZxk6yIFLEsJFqGUVPRnE1Bk4JaXvZyNrJnU4GUZR0hqZTCxCWXaqc1NZWMUCRFEIEMNibLol22pCAIUUGxJCUFGUrZFETKa7EsSKYAopazatGSVXJKfQSDMiYruUQxEbNiotInGDOa6RCH5aBqkpOl4omkSN-NRQqRXtwdkyWsQGMiEx947CMOBsXKRiAZmOkgIGCSJ5eCBjQ0SCZieSjsaBzB-3rS-vqgoZpVimpJ3ZBXOW4GK0ViFklEUEq2bAioglXTcnCOvWM_XczYGTMYCzn2ISBTs2hTyX0_iOD6fNM0ddO0cRhDVWnJIfjgg3O-Xw3omBxLLkxkwFzX4KgUHTeDdzWzT2PshqHrekDMY2ramphyH9u6qpwHtKryWy_HsImOvQpcrOLx6TraVmfok9rx2fJ8M2y68a3Hq03MwHi-7s9Xm0dnqy5JJ0kNimoscnQ0bJJ1JWfTXktUO77ISaxPsonFlApal0oho8Dk4GB3vjdv5lXlq8pMvPOVo0ntgmfHIKoARoiVpya4qvKOiAyqipvKtZ7rKgTnCVHNHELlHYKJWFZVxBhzFXwVHCExApN5x47ZbT3CjirHwXMTfHCOyaGiR6yYnYMtnR8BnGO3PdGKFgNC0gJt8H_9b_6t3_jnv3HWj4weAJHYee8RX3jq-pWD3ZOLc0FQMC2pQj5cLCbT6htvvo6AgIhIBLSNAuE23WaAoEWtCu6NW7dDxUhIavdOHlw9vLwZxpxETB-cPZrOpyfD6brfPHXzic2wNilXn3w2yXj--PyjL7z02q1bf-Wn_vTJ8Wq1zK-89r27R49Spt_9xnffvnu_74fdxaKt25uXr1zb37-22Nuf7T6zN7957Ynnb16ZmfzOv_nDn_mFPx8aN0j-4hf_aH71ysWDx7_1u79XX5r_8q_8DmL_d_7m3_rQC89eO9i79fZbh5f2KFAJWICH2BUdVEsWEAMFY4c5qipNdnZ9FdIYx1i8d4eXLpOzfnleef_8s8_91Z__2a7v_qv_6peqaVvNZs-8-NLbrz28ONvEsX98dHb_7hvswJydnJ4OKa-H8f69k82Y_uEv_w9vvv3eJz754tOXLw39eHG-FHJDkaqh--8-_vRPfezk6KwfVmMcXMAH796_f__-r_yLf_07v_tvhuXKoj5--_TH_sbPf_nr3753fPLCC9e0j1_-169WCC996AMlJXZ4--Hj3cNLRH4-XzS-NnYPjs_UYDqd7Uym3_yjb4La4d78Yy9_-GSZBil-4m7fflcM26ZuwqRupr6akCNfh2987btAllMCkJs3bzbT-o2336Gqzgp3H50tduaxAKoC0dM3rmyy3H1wOp1OsmTHzoiICBHUzNQQgZmIIcfokWoMNfvlatNUCIAA0Pjq3_zbf_fjP_5ymC_u3D75gRee12H07A2JCQDFMxMggHnvp8GDAREHYiDAog7RoyMXNl0-mM9MC6KBI1UwMyTwvCXgcAh-c9ZXWFXkgRiY0EDUGKhyzoA8BQJNknIRUyEDNkQmFUXDpq6IKVShbsKkCcEzG1TeMxMzO3Jopa14p_XXdqbzUF3bbfYnYcixcS4EXkzrynNKaRwTMU4aX1UshvcenZ6v-4JOgMi71XpTTNtJNZu0nnC13iDZs1evYEFQFTAAY-8RCAyyyBizIiG7rKqqmz7GLIYwpBQqB4xm0Hg_nTYZbRjHrhvXm7juk6_CyWZgz0VlHONQhKsAyKIgZlXlvJpHHGPejElMckzT4BB4MQ97s4kPlYhmkXXfxRw_-NQVFUOzovD9x6cA0sxqV_PNw72Jd2g4JFUdX3hycb5MmzGNJbdVhQRq4Lx3iIxUB_-B65e8YRU8AI0lHSwmdd30XX_tYH_a1G1VaZa2caHmadsCEoAh6O7OfHlxMZvWqDbkLFkAoQ78wpPXKudAS0mZET2zd242qwGQyV3oUDk3n7dt7WdVmNZh1tQmsjOpHVEILKJmmsecxpRSnE6DltIQTipHCM47RqyYNeXJbG6GY9RVN7InMBxTct47741RRM-Xm-nEB-9M7ex4vVwP6lwqhZwXLSmpCPZjJHZjkZOLtQtOEO49ejStgglUrgqemBAF-lwS2qPz5dkw3rx28IVX3ohJLl-9FDfdlIiSmshqiJ7dH7725g8_92zsI1bUYfXG2eZ7t04stP3xgLUzKjKOkAs44BDQuaJilncOd4ZNJ6qh4dj3VTVJMWoqY5fGmFUNwKSomeU0IlrORYqamoqGpi5xZCMpZe9w5_TR0ddfeX1v3ngK83py4-blVZaHF-PlS7t37t567unDW48eWVUr0HI9gtJmvUpJvvHt71u2-8fH02beBnd9sadZvv6116WeVvPF177_dl9kZ3__U__ep7TuX71968UnJ5_59EskyFzNTUFzcmaT6f64WfrJRJm0JFSj7UNTJHVrNYVUtsEvA0FiJpdjH9qG2JdSVM3GXkshsHG1Nt0OtEhmojm0QWME34jh5vgIRdanx6Z5vrtn7NFKFfyWkGHoSlZiQmbA7ZaTCGnL8mdCUzHbtsxBx1GNMYTtTt4Hb6qqRsT2fm_YXN0aGti21rLNYzgwlZJLHCl4JmJiIraSzQSLSckoAghljMgIZiYKQCJgADJEMsScrZTtcsIUtnEdVEU0sAygzGSimhIYmAkobKOHCmQAhk5FCVBLJoQiBQm1ZB0TkXOerRRyDszAiqUMYqqGBJpEUiLnOThJWdS2fBg3rfvzUyy5qKhB2FvIuCUiKcTB4mj9AClDURCFLAwKaKAKDIAARRnBNKEWU1EtRYqBaSkIhixgCqmA5iIJTEBMYjQ0CEySSQRSRiQdk511adPFsUg3mAl7BAdQosVMzswKbP8GpgwKJaEmqEG1YCmQU0kJipQUkYprJA-9SdGU8qrXOAI757gMgw5FUkQpoBnFmMgzODBYDWxGlZVhXJ-si4ypG8swlFzSqi-rzkhjP9pYkI1BdLUBzZCFVLd-rriOqopgeUygJUxg6KKa99MJMawfr_suYuVp4sOssX6NZQyWXRpxM8hqjWlMXceEoCKqAkqTIKg5ptiPMcXVchPHNKYhlzz2sUgC0xzHyXRiRUyETE0tjYWdd3WdcgmzVtVEBBBUlTwDqmIe4uDbkGT0tUMHAKZkQ04xlRwF0LwnUSFm5wJ75xwpWjNvRGWzHh88eny6XJ2v-9N-FOZNKp3KRRePLzaPz9clq2_qnb2FOXbBPX58wsCnF904JNGCqKvl5mLZ9TGlXIaSW8_9Jl0sx1G0AIL5ummJCERllOB9W9Vnm7EfRk_UthUBokII7JiAcAsurCsOjhxg7ZxjJICmqZEIgcjRNvRZtuE6JGYMlYP3n011Husm1FVVee8JG--D90jAhME7AkRV5zg4ZiYWpK1ewLkqeOcYkZjYsSfnmEBA0ECTVJh-4Rd-4Xd_53eGLAGDlASGzByYn7x-vV-PZxdrDp6ZUIsn_-Jzz7xx5875MG5lAkgICNtDJMOflIKRstnqYnWw2BdlFfrKq9_82NPP3ru4iL2h-jGVnWZ6cn7RBJdK_-79B970x374M_ceP7h2aXccTjmgmD3z1NNvPbyT-tKPsrM3m2T4R7_6W__gN_7pxWY9pAyeoArHm-Fik5ZDeXj0-F_-68-Xav5f_3f_fLPudyazV776DSF3_PjBuM5G9cHOFc_-f_o_-U8n853Dw6uI8Pjh48Ori_3dOdV1kYLoc9ZsWNCKKTqXioTgQluF2hfJUeT8-LgKYejWaHjl8MrP_cJfPbx59Z__9j995VvfOjvvX3r--Y997JPf-uZ3XvrwM8Nm8-zHPwXIb75-p97ZdxSU-awb54u9nUtX9w7bvo_333302tsPP_elb8S-H4d40W2iyJ27j-6_d_6f_h_-XwbZgJq6-bN_5advPPvUpz_94Ve-8d3T0wsjIrZ6Wt_-2pce3X-8Hsvbd44mk-Yv_IWPXxydXd3dLf0oo5Rc-iGtlr2bzpPY-sGjmiAlWW66gxvX-1WXU8wx78zmL770QkZ3cr7Z2VlszpdxSDKm3f3dqp4MMeWY8pi71Aty5eDJG1ePTy9ee-vWIDkqhQbHlPs-FtGYy3NPPHV8fE4TihmMt9Zbb6CM6Ji8J89ICJXzyFRXvg4oSRcHUzTMRQ3w4er87msPf_7n_9Sr33zzmSeuekemmEUIwCE5diJS1FSVAZMImokIiAGAq71jUpDTk-Vk7j2jKbrgHCGCqUqRAqYOiZGgKKsik2o5W_eq-r5LGFXUUFEtM1DrK3KExMF79uy9M1BVBTXHTEhohIZNqJraVYiN49msqRzNm2p_Vj17dX5lZzqvK_asqtf3Z03lF21VBxdjDp4Pdheq5hyXog9Ol4kQvVuPcdMPJhpLRsSbV_fHISEiou7N21nteEtcZAx1JUVL0hhzKgWYgV3Ksg2ZlKLOEwBOm9oxSSpV5dWsH4XZcfBimNQywLofV_3w7uNzcLweUzcMCGgKgHS-iStI0yr0Y9KcjakO_nBnp65rBsyp1DWpWS7a92NKeN7187bOoj4E9Pzs_s5iNnXIE1_VAaeeUeX2w2MO9WpIfREiquoawcdRpvVkPml84Jzztf25Z5rXYXl6vlxtUi7sfRyGa5f2m8q1VXV-sT5frkQMya37YcxZ1Nj5nOPhwe77DYcijpARS9QGLSYVsddPj8_69SbGWBQCheDY4dM7-00V5tNaigZCFWPG6bRmApUCqnXlQQ3BpFgIVAeeTkIbfFDTIls1iqqWUpg9EHcxDrEAMns3n02T6HLTqWkpJVQhNNXWErl_aT4MIzEZY46pqmtEU7asYmq5GDp_frFervrzrmfHhNQPw6QKdfCxyKPVpphbizx1_XIe8g8__0xdt1_8_Bd26vbJS5e9464U8-6V04ef2N_NKS27NDj53Fu31gQdmhDFLFXtNVuMEbTk9eAIp6HWYZMk9rljz1vC2xYGqgzIjrb12CGxIw5sCGLKDppZq2Dzg_3cd8PpGQMiw7DunvrgB0nlS3_0jd3DRTYbk84m067Pb99_b0KwxzgM6WvfevN0eQ6sm_X5T_7EpwP54PnWrfvVrDmPqU-yulj95Kc-cXTv_GwYxfuTbn3z5uXA_s23b7sxf-jGc7_4Z__0y5_86J3X7lI1Wyixn7ZooCXbeOady0XCbEaBDYAYTRXBANRS5FmTs3Bwpoaii2tP2ZhT19GW3ufQBBAJEDULqAByHgYACK4FNJFS78xEpaprkwJp1G4DJU12docsqVvNZwvyFQDSNupcMqFt5eHk_PsWHwqm2wtjQAL2ZFrIMToGYgIjYgR0wTOgxex8hc4ZAKKFQFAKMIGpqJFDSb2lDGaqZgBbr09JEQF1C_n2KGmUmJArlYJoTBjqqowj0Ha-z8576SMxohoYSD-AgKpIytvVS1ktQUvJ5f0LBpKrKwCQvteYCUiGRERmZqDsEEVAAYqBGKggogNDMO9RY_IeQwg6lhACEleBLSXro2WRTZIs1qfpziQPCYjqALDuQQVyBg4gAJpBDEQsybZkTMVQFcRsHCt2GBVSYUArQgBooGMmQBCBopAFikDKEBMUszFBzChqo_qmTuuRTMYHZyZW-khNQEPKwimTKoogIbIHMQRjKzYO3ozVKAslgZTZ0BCAgIqRgEaBuB30BbNSb7jOVAZEsRyxiI5ixTRLVXM-25SL3oUAow0xDmdr7BOPWccxx5y6qP0AprqOxIYspetlKCAIsYADHaOsImrR9QCi1DgD9eTTsihgPatlSC5UYIWd6WbQ5UhZuA4lybiOachpM5RNkj6XfkwxxvUGiuQhFSmqmsax9CNKMc2qoknyMHYn593pUsbknBcpqUjf96qScgzeh6oGNWKSksysWw3kHAdvhpZUonjvAJnAoXkzVwyQWCTnnMehQzUH7B27ytkWS2WmAhwqdHze9b3KJqfT8265HpfdcNKPI_jji-FinVRt3Q_L1YYInHNV3Whw6zgOMa_7uNykddZRbIxFxbJaLJk8mtNBihJcxH7UMUkOxKayu5hV3r37eP34bPnwfAnMAFBXPgSHCiCgYsHRtuDOxI4IARjAs7cCzjn2PrhAgKVkUWPywbsqVM6o8o4dCYIiGqBnF1yoQ71NVTA79kRMCOjbELxDNDXdEgRMjbffFewcMwIwIzMwETOZAzIrUQPkv_6Lf-NXfu3Xz_ph0syZQbKa6GLafvhDLxwdn5yv1qGpyBNrbg0-_vKLv_f5Lws7MGNExC3x18AMDBjABMjRxbp3bEiOCN66fefq5YNbD28fLvYQcFHVm344H9YtcdvW46ZjYxf823feunb58tHRex948tl-zH_7r__ttp1Xs-nP_czPpJyW5-uzR8ef-1d_-At_83_7v_sv_m_HebiIcj7Ke_fOvvjt1_7gs1-5-vRT3_n-a09d3f_GV771wic-4r1slsdVKD_-5z51eHn_0rXrL3_mR4jsd37nd0LVvHv3Xu2bf_Gv_qCM_Qsfei6NyQVI_aCmwQUEmh_sEJERVk398N2HzvM4dP2wjDHuzw5_4Ed_bHZp79f_-1_7wr_9wny-f_3ZZ4vo7332c1_4t_8meNs7nDb701vv3Ll87foHXnji-ORBmO7Wuzv9OKpnjWkc42bdDU6W6_ONHy9WS8Ey8X7S1FdvXptM3Md_6KOGgK1XpO9_-7vtYnb_0dm0af7Mj33qL_35nzjYP3j-Y8_9t__N__Du3XsnJ8cPj0-5XtSXDia7zTiWD334hZd-6KPnJxdDtwltk8UY-fTo0Xe-9cre_rUf-Qv_q6OjB904_MFnv4Ac0jh-6NmnJpM2F90M8WK1Cc4PfZzU3mLfVmE2353szn7zN36vH0ufSu3w0uV9lDEOo5YiJt_83q2z05OuX40xLuqmjMOsao-PHpNz_CeeCtr-F3VbVwSIKZE1bW1obz148MTepSLiSIXgd3738__jX_yR9aM-gLt0Zd8MHHtCIAdbFA8TOyYCYCIFJGbPhACWpIgi-Xcfr6aLtt5-J21TamhI6J3zjisf0NQRmSkhBoK9nQaygigBOGIEBgfCisCgWjkOziOTiJiCiKCj4LdJPEKzKnDdVMoQgveOWiYn1jjYnfrDeXs4n83qMJlUdXCLWTv1LhCiQikCCHVTF5PgHSIVwygWfIjFhiEXkc0wlJIv7U5jLKYqZiDpxsEeAxiAlAJgaOiCA9IkxZiIoIyJCIL3RBRLIcT5tJ1NJsG5SdMG780oiRZR9h6IhahLJQMMKR-dr6HCs3W3GcY7j4-UABHn03aiWDsfnBtUzy661aYPlWeB_dl8c74OnpNkX3shVIJihoCenRHEcayrAAho-fJuiwUky_lmLKaLWfP4qCNVxzyOcdLU80kzb5thGDTLk1f2bhzuTp0XtTGWPvaLnWmOaWc6aapAiCqyWW-mk7Zt2r7rm7ZBArXSVH7SNpf2duumzmKqxTtCQGI-Wq6VDI1evvlE2zZN49vWWxRH4B1VgSvvOJcGqW38rAlN7SZVYHYKaADsQMQUIBdpkPJYCGzaVuwYUcEsZxERQvKOx6ICpmiGAFpKKjGmUHkTVQByFMe4dRYbmBmuu-H_T9N_BtmaXeeZ4DJ778-cc9LdvHltWZRDoVDwjgAlCBIpelJiy7RGJtq3xsTMr4mZ6IiJiR71KEJ_NNGhlqjpkYkWJVEkJYEO9CBBEgSqgEJVobyv6-9Ne9xntllrzY9T-pmRkRkZX56zz95rv-_zmJggANLJejw8WzZtS94tVyt2VBBd7chT1QT2hB4Xi24UGwDA4WqMgWhSt6tubLYn711_9_yFcw8f7O5P6sHs7nweQvNgu3flwqXTIT9z985vfPedxXwcinbrUURNFU1dzYvlEZhSKRrNIUzOXTDykoQ5SLbUp80Q0QeHZIzmVL1DUtuobV3FapZitKTd2VKLaiklDs4FX4XXXnqzhNqKTmeTS1fue_6Vl-dd99zLb777_p27N67_1Z_5ydsnZ2o5g-zu7d949-jxJx4-PF2f9n0b6raZ1HVzNIy6Xd1J5fbJ_Ny53Zdfe3O56uo63D6794mPPH7z_Vv7TVMAbl-7OwajPGQgoNBgVZlh7pYoBXMxBXTBiEQUwSQVZg9qWgzIIzBESTGmtKy2Jtr3zocPGK0GoAKq5FCHxMxkgICpXzFycF5i9OTXi05idGCr6zdljIrKddMvVsfX37_48MMqCs6boRXbYHzQoBQBhf_ETy2gKjkhkoyDQwBEkVxSYuct55ILAAEigoIKAZlhjgmQmNAjgmysdsTOo2RC4MorQBEFBe_YUoINbAfZGYKVMqwNAbnKMYsI-2BWNmgPyclNWxUBZgRwVWWlMBIHpzmaqHMhtC0iIWwahmiGNkYooiK22RZsPI0qkIuBmSluYOZFUFWibHzgZKhZLBf2LvfFREURVDUmZmSHZgJa-sOOwYHjNERgBQPoI2gBFCAEUwDVPkFWKEo547rDklFQ1h1LgTFqTMgIQDpETllXAywGUNnQ1gCMNlsoQzBgIouDq4lRyUoZBt_WyKyiGgsBQC5cRPrRkVqMrMhmUMSJyRClmIIyFCfFJHNAiEKgmpL0EVLhorIaoc9sijl6Eu0LdBHGZJbQA-SSlwOYqKirMK-HCauu14QAABAzEoImyAUUIRVdjJBHSwlSBMfgADQDMRI5Ae0EFdMiYSDH6AI1swqgEFu_7C2rrQbrBxyGcb0UBGo9NUxkTBACS4lIlroepWBJ2g-yXFoeNeeSYhp7zaWUzBWxp3o2baZtmHpXMYIQgfPeea5qHyqfhk7NECB2veXSTuu6rqVkZjAUIAxNzY585dgjOsw5A2LJgqYlFyYCgr7vYzeknLsxjSmj5zGmTaq1z6bok7kulmSo6MYihTCzFcP1ejw6Xs2Xw7B5lYGBWp-SgiaJZ6eLwgKMY8wZYMigyFmoDn5c527Vi2lJGlOqg0ewae1Pz9agqoY3j-aAYAhIBgDrMjKBgnlmxxw8e0fMWNcbeSIggNvEaMyySVFNJRsCqI1jVAAjAuCujwK26YR7ds457zcVQUdI5Gij3AaDQAwIDCAqpoaIhABqaooIAFREQdQRGhma5CiI49_8r_7qL_3yL7757rve1cExAkgsOzP3hc994r0331utunoD3AY7N9t67JH7f_5Xf9OHgAJgZBv8lyIIbphe3mPMo0cQQO_4vVt39_cm79y8Pau3EDVmkVxWXaeAd09Pfu-ZP7n6oYfW6-HZF19Jw_Ldk8ObR7dv3jl98tGH_u2__XnvKvbV1csXFoedAUOm1I03X3_n__p3_-9_-kd_9Ev_5pf_5Nlv3789e-WNd9945Z3nn3_FN_WVB6589Rd_cffilSeferpqJ3_uh__C4t7JR57-0gvPPtuV8htf-_qte6tPfPzTzPJnP_-la6-9-eiDVxGFOSDxua1zlcPGV1UdNJV64nMaTbJCzt3Y8PSTX_6h8x-6_Ee_-5vf_95zVAUlevv969ffvokEQOHG7dXidLh1Z_7xpz_x8P2To8PjIZZ6Mru1OMqok1k9pnR6fHj3nZvLs-VqtV6frI5fP9zfmdx35UJDQmn97jt3_8v_9q-9-sLre3tb91-976H7r1i0fh6__9q7Y0xvvXPz7Oa1Sc3f__b3A3Ldtig0DqpN9Qd_-Owbr71_enJ6_dqt9WIx22nGbnzoiSe65dCt1wqIyGeLO6__0b_CUrSUuFq9-P2XU9b7rl7a2Z21jTs6PX775s0bN2-ezherrrvx9htMdLg8a3brnFIZ15VzhHJue4-bUJN2OW219RD7in0_lrevXxvNYpd8sVu37qRUVIqUUkzFNiYYAzBCI2RlbIKvPP7hcy998omHNUld1d9-_nWH-Imnn7p7uL543zktG2-SOu8Ds9-M3Jk35bdsagbFbIPVRsa9abh3Ot_aa7xDAtAkBGgqaMZEjOzYI5oPjARMBAqn8zhfxXar2nRtECwwl7IB-UuoHDAYm3PU1t4zMVHOxUDRASIBETkMNTpAMECktvIBbNa4nUC7Te2YHJMj9A4dau0ITZhAUm4qD2qN9xvw99Fi3ba1EcWUnaekxQXX1k0qErO0TRXTMGvqAFCixJSyJOdITEU05iIIY0xM6CqqvUO0YRwBUYpILnHMzgcgTDlHyWNOY8x9zIOUrDpq6SQPRVZ9f3rc3T0-GUu5te7GkoZYwIAdFy0F5ahP33rj7Xvz1elqWXneaj2AEIOJAtrW1iyW-PCFfTRCFUcYan9vvp7Vfm82DSqMlkQ6lfN7O0yYs5hhKsV719a-DZWiBhc8u0vndygWHwjQqqaaTSdaFEC2Z5PaE5t2fT-dThCp6zrv6r7rS8lNUy8Wy4Nzu4RQYhYVQxhiaio3pvzMq9eHZKPKIGUymVHl2sqRGBpYLgGd5owArWeP7IkcUVN5BMgqWYvkAmA5F1AjRjSdTRrnqGTBTX20CCIG59ZdGsaxTxmAQl2x9_0YASEXRc9dH7s-Hc_74_m6z2W5GpfdkKykXJyjnFM_jAxYRPqY0ZEhlizv3j7e3dlSs5zKGNPe-a0iknMJjlPJzG6xml_Y34JUkuoPfuZjgbkUe-n24Ve_85YnIeYcy5--8f7JWO6sx1UF5hAYSy5YuJIaiKazc6YY-4IlemZy4HzIYlLEB0YgKFZPK-99XPcWNcUEZBRctZnlbcifs5aYJKeqDTklZP5A_0F079YdJHrlzdvz5eL6nUMj3_fZIXWKO9P20Yfuv3DuXGiClXLp4rkUi9R6tDyLqENM5KvpTvX5Jz4cFsmjXtjfr4xQs7P8ocnkSts8cfn8TtP2afz9V174v_2Df0Imebq9Pa478tMwnRIQxp6haEq22W2CkavYOzRFQ9iE3oIDRz64vOpCMwPH43Lp6lYN0TOoEiKa-bpCRkXLJRGTpjGueqpaBQFTBpSur4Lrj27nVGbnL3Cg2rn13ZOqnkBwYsaVs1y05JQjEQMzMWocEFFVzFTHgTyXMTE7UyQCKLoJ5Uve6EdUcwZ2AOi8txQtFSmCm2gwIUoB3bBGFdjBRv2Nm802EpPpB78KrKCKaSHnIKVq0pgCBYeImrIB2OZHiNEM9AMiqhkSo5lClhA8A6ELFAK3FbJZLoiIHoDBNn1eQlEzJC1iZmWM5FhT2RSTS8yaMyOWKJITKLi2yv2Air6qcxJVITQAc1CQeMMqhT7COAAb9AOUDJtdb8owCuQEUMoYNYoNWRGMqMQRilkqFkWGEUFtzKAGBoQGuUApMA6Qk4FAHDd3FCBWumJGaEoq_d17BAqhgZRQQYvlrjjvdDFQKliSZcG8sawWAOEssugsRS2iSQBVRCwXIAMTlIQmYFpS0lhiBhODYUDJVkRXI6QEMeuYNCeNAgxn18_ACCa-xAwiVBU76yBnQAFGiIJm1icwhZIw6-ZpoKbSdahZrRjj9OL28jSGtkWlkos4lZypFMpCJmaqyVRNh5RWvabCqM4B0cY7C5qL88weLJfcJSKs2ikxb1bGEiMhi8kwjGkd4zBCXfvKmarj4JDTOIamcg5T35sYEIZJLZbHRdJSnHeEhGreu6oOztMGHlJ5RjAxCVXIOTvv2JEL7CuvJkBURFMqi3UXi8y7rss5q0bRm3dPkuSYtc_SRS2E053JdKc1QxIaYwKiLmZAiGMcV7GLeRgEAZl47JNjLijDkErBbMIOSxYz4OBGIQOej0UQo5iSu3eaANWKBF8BQM11CN4Hx569ZzUjZMeOwAXvnfcAgqpqmktRAUJkZgU4Xc3JoYiaITu-d7xarLrVMJqomTmi2rua3aSqQnCBkIGJKHgiR0wcQiBySGgGaoiMjhgQwTR455hEipkqAKiVaF7p7_w3_9Uz333m-2-8Fnxde4di0uvEu09-8qkXXnzxbN0770MdGl8_cPHCzm74uV_5TWAmMwWTjQ6Miqqq6LLrZ9PJEHNMSSSveiGSu_Mu4LhaDxVV9Wy2PltX1S6TXb9xa2fr3LtvvXfnxrpb4WrR3X7znbZqf-vrv3f9zp0h5dC2Z6dD3dYWwmTSXrp0ZWt3vzl34fnnXhxjefWN1z_7iU-nvjubz9vZ5OknPzGfL4-PTj71-S9OZ-3Tn_jCL_3rX0jFvvmNX8eCFy5caqbNP_pH_-DBBy5NmwmiNrvt_PS0aWZFC3paDycAOvSDSMm5OOf6bj12PWR69OOfcrPmO9_4xh_--u9K0dRLP-aTu3OPIQ1dt-hykoNLD3BwkuNz33zu_vP37-34oR9Pz862660rVx7a25vGYVUx7063A_LDVy61W_7o-N6960fzu4e14N1b8__Lf_-_e-H5l-qhVD7c9-DDd46OkDml_td_7Xc_98WPvXvt-lmfP_nUU7PZzoX7rswmUxHCgL_7K7899usu9tfee-f43uFLf_JSXPXn9reOb15fzY-LZlXbO7-_Pjr-6IcfZINuvXI1vP_-e85sebj42Mc-S4Kr03lgf-v4FByoxNn-TtXUx3f6N194_3S-_IWvfg0MNNqnnvxoHsr1W7fHXIKv33_3uqVcN1vPfve5xWrhJ96z3bp7ouizGgBuUArMbIYpqSkMfb_tqrryYHbj5NbMMznr-u6N5974oa98VjM0wfmqMjJHgGwAoqofxFFVADU4BlUGIzBQyGZVVd08WovRXlUZUFZwFakV59gjeUQmC4TOOQJi3Bjq1KPNF50pGAB7RMKWwRDMQLJ572AznAIjQjN1iJOmJkMWq4JjQkeEBQNiU7lpW-3sTLan1c60vnyws91WfnNbAZpz7vpBzGLMlffbs4kWqRznlMCw9j4ZEFM3luB8KqUKoQq-bSsxAvTzMd08nj9w_0VHrGxDSUicYtGsY9Z1LqOIIcaYa-eCc6ZSBQcqs7YCtSySRU5X_emyWw-jAY0xJ4GmqQG15BKTrIexH8s6jmrUjxkN7y7WKWUt2SFlADQ7XHUc6mWM79-7y97jB9ohrDzlMbZ1C6rOYUXKjscYzfBgb9JWoQbTUrznQpDGhCZqWkSS5BBcxYQmMaXaB-_03E4dwJqmroIrKhvAgeQ8bZvGM6tl1dUweu_rUPmqWvdrdgyIgfDqxX2H4MmnlNpZm7J6F1brPqccU1n0ay06MVeGoQrubN4XUWT0zoVAzFgF52sPps4BiLIZEXjHlXd18M654IPzrq58XVUg4pgNkSu34ahU3mXVYYzBe09ch-AJu37g4NW066MYgPdDimNKsaioAlMSqSu_WK9L0VJsvu5KKcvVejoJtQuo1E4nfTdcPHfOh6qoppyRKIveuHlbkxyfnh6fnKYcYz988-XXHjvY8wZi_o1rR2-8dXvKcOd0mQX_5Ysv31is2FfkPCtvnWuRDbEgS5FUVhrqhmtKsUekbuy2zm9XjTMQRfVNY2Yh-LKOhsbe8yRoKZa1RKmalkBT3yFC006cZ2TqxhEqRg_rszOsGjVDRmD69BefVuXDw7NY4PJW672OsXjmNAznL-yuz1bvv3v7i1_65CsvvPXCy2-cdcNyGEWQ2U23zw0D3Lh-cjTvgNL5c9O8XG5D-fJnnq4RT4f089_-9j_52te__szdvXaPAGhYLXwVhtW8ZDTnkVC7rsQRvXOhCtu7Y8yGRMhkWle1dEMqmIZsoFBKTpEJXajj0GPwWpTIBccOAVJ0QKCmWkrKVoQpx-NTEZEiWFXMrCnpuqMch7NlSslQUeJ0e9eHCpyPQyImMNVSjAgRADGlwiFscIpUV0QEkBG0ChUYxDhuEmBItNmxljFJUWRvm0YeI6mRc8BOhkTOgaiJujoQs0hGQo0jiBghba5NAVQBN5o355BISwHn0FUSo5l6x-QYnVOwnPLmFAECiGymIGIpQsxpvdaUNg3Dso4mCqCmRUsxVcvFYkKBzblh41MD0zJGQDIxKdFyEinogD0hoYlYLkSE5BTRTE3EudqB5vWAgEzKopAFRIAIiEAFi6EApATDAE7BCugGkKRWSslRNxpjFXAGaISoKZLDD7DYKjBmRwDrHoYMyJA1DwMgkKgVkTE5T96K9AMHBqIyRjQFBCyiOSmJMiCC5Axi5ByoaZ8cEyAbIoiCFQKBkm0sKCWvRo3ZUjRJAKCxaE5gpNG4dlCERSxlyAUJSyoEaosBAMsYLSaUooc95AhskARSASsmEWKEWEDVUoGcQSKuexizmYGSIQ3zSA5LKvFsgbFLN49tufSgTgqpcdFm1gQyVGPvSUFTHvoegS1lB-A855hyKrjpnygYmBkwMQGQESJJzlUdXHBqGrt1inln_7yvAyKFth36IQ6jqRABEpaxSErb-9O6roJ3u3uzpq6aqiopNT6ACBTpVp2ZBheq4A3M137StsS0Xq2qqqLggChmAQq-DpWvV6tx2Y_Xjg9HlTo0Q8pjtj5LND1LpR9FTEUlxjj0GYFm7bSaTHxdm4GIGCAwKohjtCyMSGRUcd20m6s73_jAZpCXqzWymXeDlp29KuYPHGreh-m0WXddcL6qKwAUUSRzmywObrj8WcwAyXk_aWtHRIQO4fzOthqKWhZd96mZ-CSyHMazMY4xFxFR24iKGAkATAyNAXlzflAwYmRi2AxmmNi7TXF3w5YlY3YMBMqmJmUULsPP_rW__vJL33_uhecNK-8JRCWWg_3tz__A5996863Fek3OhcBtFT799MfHfvH3_-k_M4KSTQAKABjmmMYxXb95d-fCzpCSSDpenE3aaeEgRbCt65oLalvRyepse29LtAtN9amPPHn-4n4a-9n5nQHt8cfuq0L9S7_62z_z0z9hmD_7-NVuPb9wZfvg0uWlZkF68rOf-9JXfuTiQ08_880XPvTIE7_81V_amk1Ozo4effCJr__p16_funPvuPuNr_7yT_7szzz34rdefe2d-fzswsEllNKtuqTmQ_Xvv_rrl68-0I3zB69evvbaW9t7lTfQmCWlHCN6EiwGIJLRcLZ34ZEvfOLtV1-6c_tO0TzdnUm2_auXCEmsDOteom1t7yHy0b3bq34oGba2p9969rn773t4f3vbAaxPD4_eev3Rhx75-EeeiOuzdhYuXr7UbO0i0tWL53_yb_7oT_xnP3Lfhx_8ys986ed-_hf_7S_-3uk43Dk9euZPvglZ-3FYL-avv_TO2-_cOV4svv_OO__8l3_zC3_myyB66eqF8_tb88O5WcmlGHI32P59V37gK1_Y3d29-sCj7Dk42tqemuOxH9D5949Ot88fINDQl5N7JwRFZXzmj_9guVoNuRydHOVU3n73vbtnp9u7e1ce_8xjH7q0M21QsevSIqWkMqvCw48_eHh68uIrr3Tr7uh0VU1qdmipfP25b-9Pd1koFTGypBuUNTIgbSLPBOxdyuNWUzuwm3dOPnLhPqiolPLLv_UHVy9deOrjj5Yi9ayRpCaWRQgJAZHQEQXPwbnKOUfkEX21CcVyFULKeSDb322NgAm8x0BUITNgUUNAAgYzVCyqgABgvgo7-5N5P-AH83tUwhKcQ_ZkxEiM3nPF7IhAjZA2Eu6mCc4xgVWeWh-C461JPW3q3dlkOgnTQHvTuq08b6rHpmaSSjGkMabLF8_N6rCRkOZSTpaLJri7835MabEaspRuGJxz7BgAnAvT2eTwbL4a0uUL2613ZtYPfdM4BAKAZLKOKSMVUx9C5bwDFCmilnIKoVbAAqYKZ_P16WJ91g3sq7atkRlMT04XcUhjisV0NcY-xy4V7yiZuRC---a7RB7JjQav3jz6_VeuHa3Wg8G9-fra4XzGJgqz6TTGsQ1ce7dYnHkoj-1vOyUyIKSYxt1pUwevWupQpaTHq46Y2TTHgo7imByhY1ZF71zOWUp56Mr-pKmzlJPTxWLVZVFQm00m-7PJNPhcyu17Rwfnd53jFCMh1pUXFSzl3O72pGoY8c69u8gcY5put1XjvHd1CLNpfXiyEkTwiEptqBrnN9sBFQOApg6E6BnbxntPbeWJYBjGNngzMgMXnPO4MaQ4smldgyp7zDEZmQEWUVXdmlbsQIsgmBQRMQAbYlGABLrsusV66FOs2rof0ulyXUyNoG5qARA0Fzzgpq5d-eBTTqfrvp1OgCkwrrvhYG8nxbJax3bWFhE0uHrh_P5se1K3f_7jHz432d5tJ-_fOat3p-Th-unpatkvx-He0WrRJVMr_cAl9SedA5g2FeSScmy3m1BVRuhqp2aGdHoyF6TZua1QVTkPIfAw7zQLAihTUdx68ALX7OswLDtmZuBmutOfdSVnIAp1MCnMvHVwcf_gQjf2oZ2hDxJtfjbvunR8fLrdTh6-epnVzGwxX3zksQeOjo8fvnr5vgfO3zs6OjtZ3753r5pNsqRp2-Y-Xt7ZbZv2o098aHtr6-6945_4wU88-fgjI1Qv3bn1P__7r77xxvVlP-J-nWYzkiySDIydI8nRgNBXZNoGp-s1agFD3zQAKjkxocahnk1CYGCUlLUkWS8AiTy7ujFm9gyglhPBxr0LxFy12yZiYJZGKEPwvtqaZBEx4CqEykFcTiZu-8LFmFM_Px1XC-SgqOSd4oaxY6gCSIaIDiUXcs6IJCZDNAU1ZUccAphqzAAmpaDzIkJkZOK930h_0QqqkimhoifNBZnQQIeEBs5V5LxzDkwhKzEbGBM5R5YLIktKgATE3dFxvbutiMAkYzQhJTYAFdGU0CSNg-bkfS1jspJlHF3tUt-RZogRRUwEs0IRNkR23E4BiH3FHFAKO0IDYMBSmJFAnXM2FExF-lFLARHNGZBsk70yQEcQkxhKyuWkUynkOXUdIAEgZAFTMEIEUgUBMIJCYAomMBaIGbyBGBQBKSACsUAuVhTMdJ0ACIpATLDqIRcGsz5DFufJOYaUdYxk4nyV-mhDxJxYCZhBBFPhVFjNewerRNksGSNRySTquPJEmBJLciljFyEVGRIYYCm2GmEoWBSSQAYAs1Ksj2CGBeysp5gtRR0iqEg3aCpxuYaUsBRLAqmgKCUBJSgGqUAu0Gc7yaAAY4LAmAVSgcVah5FRNyqeuqGyTmwQCDFFPRugL4xoKYPJVhOc85xFuwSAzgVyzkJlxEhmHrNozgXM2FNWcd5LLiYFAaWoEbm2yTkTezBUxKadtJP24MJFiRGNyHMaRyYoY0FDLcpMVe2QWUGmWzNQ8ejqtmomVdUEX7lQOV95DlzXjWNCMO-DiZZSum6YtK2ZTSf1YtGlkhbr1bIboygSDmOpuPYuHM-7ApDR-pRPV_3Zeph3w-Gi7_thOeQCthqH1TD2qUTNVe2KWJQylBLFVsOYdJP5KmZQbMPf4CIwZO3GnA0sQ9flfpCCbpWhy5ZFkVCL7e3uBWYr5shNJjWT24wRVNVMmf0GSEdEYIjMRUQVDbhumly0ZNnkd4hcX_R4HK8tlq8dnq5iKmoGQMTeVz02bZwAAQAASURBVMQEZpKLgvrAAsqbQaYpgTEjmHnP3nlGcuyIyVRAlBCByVRLVM79X__P_vN33rv2x9_-prkQAoOidrrXNh97-qMvvPxyzFJEDXTW1l_63KdKkP_6f_h_C5UgBCJNG67fOaxbeva1Fx976OGuKGR5_tp1z8E1W-RdV3JwYYj9pZ0L89XyP__pv1JNdyZhUm9tP_f2K8HXT3706fP7e99-5dVnv_eiOrz29r279-T8hZ0BtKZw7d13xtjvXjj__luv_9Hv_Mo3f_93Hnrgwu_97temdV1RY8WWR_cevO_Br_zwD3nN9z34wDPPPvvW6--g49uHx99_5bmxJDA5Pj07WfTffvHFRVptbe_u7Gy99OLt6db2ZgHJ2cSIGrc8PHXBScYrH_5wjN0Lf_inJtqGBpDiKKWkk6PDYRjrWbv_wGWuGNCmk-l0e8s7Olt3u-cfqpv2e8-_ulgOO7PtDz_88N5W9cI3vnm13XnqI0_EXj7zmY8d3jo2NK3dn_zhd_7F__ffP_ONl777xy_mIe2fn6RxuHPzZH44f_BTX1ierNFXs91d31TBu9V8eXZ05z9-9V-P3eJ73_7unVu3SxmzinPVztX7rzz8wGNPPvbyq6-muH7t5RevPHT1ykP3bU33QtXWTTNp2jdfeW-xii7UOQ4W4Mbp4t66Wy5P2sY9_JEnrl65uBrXR3eP33v3er_od32PKP2YYpEquD_91jNQUk49onv3veuvvfQSWq4rm2w33XJ46-49WxcZ4jjEIaVh0FgEAADRADcdEWLs-nXlfOOY2f_Gd575sR_6Yr8aX33v7svP3fxv_-sfK6uSDcg5dhQcOkYDA0NCIAOHWHl2blPN4xKlGBCBM3n_uL88mTr2WoAQgneiaqRZhBnAITtkYiIwNdgYnQAsSzIEMgQkQjHLIJuuFiNIURGrggue2VHTBEe0odqFOlSVq4NzjB6xdrzdhu3GtcQX9re2JjUKGKGqdH0cx-zIOed2tqaOEJEXZ13K4oNfDh0SHC9XjmmIJWcpSF0c-yG2oS5ZF4tBFbLkg3ZSuhyHGIKP4wAAsUjMhQgI4GBryyE1IYiaQ-xTF4KfTf18PoyjxFxSkZQSIg0p93Gc98O8649PT3KxVHQoRQFSlpTH4249pHy2HLusR-uhG7MYv3j78HCx7EVOum5VdMjy3RuHWZSZK88pjmbQLVcE0E6bnIdxzG3tp3WAnFGlqioAMIZSdGdaO-dK0Zjy3nbbBM8IVfA5jVVF9x_sNgAgAoRHZ6d1431VOcZJCG0dSkqlqENksDRGBB6GoW7brutDqEwEDdarQYGIGQxLgtViGLsIYIauK7IkvT3v26aan3ZNU01mDTNWlXOM57cbJpjVzhk4ckVKP4yTugIELSIqKWdyOJbiGJsQnEcwG4eUsxoSMXnPzpEjzoM4Bia2YuxYxNRgjKnrYjek9ZiS2BBLFGHn0cD72gCLynLVx5TELDifUgZEKTaMw9WDnUnlQRAF2LECxpKD90pkSfe2J7NJ062W06o6f_HczePFupT37p5t7W5f3Dt_cW83JTGHofHF8jD0RBSjiKAxrzWvxlEUBCTsTbJIL33dhlnTlJRSF0WLq1k0oTMiR-RMUVTHw7VGTONgObFnzRYe3ZUxkSmTM1EOVUyyfW4_xvH48IgZyFEe4zhImLQ3bh1-5otfeOGFVzxh1Ly9u_39775qCfYvnlv1_Qvfe4tVnHdAGGPKsXvw0sWL913Y3mleef2t7mx-_1Z7Nu-zhn_5W1__xV_7o_feu7voxrhM47IoBZpMKueon58ieysCYCXmkkWLQD8iIjEbh6yO2JUhao5EiIbALqsAgGdncRyXC7-z63wlYGomRS1n05y6jiqvoFzXRAgAPnhwzlWVCFLVpH5QEVmuHVWumqoCKuVx2IhBiD0AMTskTIslIWtWX9e8MSuZAZHmBKjSjQYMQB8ANwyc80ie2ZkZijB7Qio5SymgRcdoqgBEFDRlLQlBiR1XTSmiXKEKg1gqBmgGBEIoWjI5rzkjExGn1cpVAaSgiPfehZqIAYiQXXCsxmZ5WJsW513ulqiEqqRYT7dBjauGiFkKpsyONI0kql0HZlAA1BiRFW1YfeBX1sIgHoDEGBRUrYhKNnLIDh2BKFQBUbwj7VaOyXMAR-gZiIEZskKMaBFyZCuQMqQRxoyKSAC5uJhZDcZCZoAEZqTKzoGB5YIeUQCRnXesyACYC45FU1YTALOYyhiBuD24AEUrNBwH54Mj9mAeEGKCgt4HFkMsFpMlIVAZluiMRDRmQETniMkxEwDFwmiQkqXMYJALLEfoIhKzc5ZGZiUrmNVEIZfNHBeSIjpLBUoGEGYo_YAmYAk0Q8mAArGAIqjCqjcriAbZSNGgSEqiVohIrKlCXq51SJCzY2CEIjml0m_KU6lwVZkaBbImuGYSmrZEYfLZjNA5rmzAUNVEWE0qJOTgEYQLmGZEQsSqretJG2PyoU0l-eBFNcURRSBrcAyACsbBO6Rm0k5nM4e21U5ASuUcA9VVRUB729tbs-nWZFJVIXjvHTv3wfs1hCqJSimpZPIMADEndNSXXE_aUUvbNs5T1LRcjoNGJIypLLtxKLqSkljXsXR9nq9jzLmoCpKo1XUAwqGknKKSreOAjfdNCHUoUth58xalCFoyKWbmcd0nE5t34yrG-aq_e7LoswoYOVJDA1NVRAQEBRHJKca8UQ0Sl1xKyqmUmPOdk-V6yENWRCC3Ifc4U0pFZ5OQI_SjrNbx2tHizcPFMmtWA4cCqmYi0vcpSTlZjndWfURgIkIkRTYlQ6KNYgw3WSMisqJmSp7BRLOltPzpn_mJk-X6a1_77QgeCQxUC-5tTz_9qU--9ubbXd85dohwYXf7R7_859PK_l__8B___X_0j3_j27___unSfLU923v-9bf-wuc-s4h9U9Vf_9a3nrj_wX4olyfV9197JZ0d_d4f_u6tO9fuLU8dxJde--6FnTZs69e_-d396fRzH_0YdPmN197FLn7x049PdvZ-9-f_wXyZ3n79ne1ZPfSwOlkzQV71q_nitZdfv_LAlU985KmT5emde7fW3eqoOzlbnP3P_9P_xJNJHjWeDY5C160vX7pUVe3O-b1lt-yWK08A2X7u5_7Xj3_qM5_5_Kf-ys988cknHleErBLa4ELQlEHJQXjwc19463vPDV0fqipMplx7Q9o5t3_p0z_mXY0EjkAk7z9wuap9yv3y-JCd9yFcv_2WAdS1K6m7dfPGt77z7W45rLvut7_-e6-_-s5nf-CzLzz_8qT1JcrJjZPU9efOb9MEwRM1lRCq6IY7ffvo-qIfjufjus9KDOD6LvarvuZw48YtDm4YR0VCpAcff6QxuXR5_-6NewThicc-PGn89__kOVuNd29cf-xD93_o_qsH--cvHux7No_U1k3F1bTdXh2fjotlMnnl29_buXyFgKtQNUnjyT0uA3urp3XVVBL1-PDEASxXqy99-lNOZUIUU777_r1X3nhndXL33u3jn_wLX9k7v3PfwcHB_mzenZacnXOe2TN5Ro-IADmXSVtDyv163GJXt5wl_4evfetv_90fGovmXIiZCR3j5pxNpt6TI1Qw3MhvANAUGRG5Db72-M58_fDBDAgs5Tp4RgAR9mSI3jskMgXZDPkBAjOiIWLMFnOJQ1IFUyWDgGQGVQhMH0g5mADJvCcm8oGqhr3junIOyTE3VaiYJ4HryteMW229VYVZXdXEVeXNrIgqmABUTWDTihmBFot1M6139qaWZVLtJLWYi5gNadN7g2lTlyJmpmoxl01J4IGLF5IIIhJxKZYkF5NbJ2fHi1Xfr5frBYN4R0ykppMwJfJDX5JIUkkiCuSrUNdVTGk1DENOAqroisfILhYCdh4oRxnHmFIZVU-Ww_ffuTZkKzErQFesi1FVY0zZ7E9eeDkhaZHGc-XDYn0GDJNpvbe11TT1tHVkBXJmIEl52tQGuOxj5StDJINhzNPWzyaNqJWijABojDCpgkPnmEzl8vkDM0QFdjxpg2dq6ooRLp3bR6O6qdBDU1cSY-P87qSuGIduSFG8D-OYNhlrEVHQVPTifdsEdvfte6v5Chw22xNAzElCCMxMyH0sYEpIBqCqzrm2rhwTA2323LnYekjO43ZTgUHJFksRM195US25lFykSM4xl2xoaiWmNMZIgXIpYLBaDl3XZxEKfj3G-XooKi74s9M5EHfdsLmrQqZSsgEgAjHfu3N7KxAVjcOwO2tmwZPCtGl3draGdXf50t7OtLp763i1XJvhYjW-8M7NUjfzoSzGrJ65bQ6X0RRdE6p2QsH3MRYEHzwgm1PwmLWIioyFfAhYSRYRKTGpwrBa9fMhZZkcbBVRNUWmGoOmgdk0FdNSUiHicnMuVrIBmYkoGh5cvegIKkePPfJgYNjf3j09m1PA7XaiaC9___t1BSeLIxds4tzW9vbVg4Odg73XX31_a8ufv--iqDWTxnvXBv7Spx8b5vP1YnX_wf52Ex555P6t2c7_55_869u3D3vBrfM73XotIiJqwTOe_5AWIQJ2JCmBZ1dXqsIMphmISzYX6lw-KJiCmAH5pgEzFTHLFlM12ULUvFpU7baZlZLI1FSNEInZ16agjBaTCyRjwqrlwC4EFPEhECGoDuOqatp2a2d5ckw-SIpbe7sl5iJqaABMKKGqckxmxj4QO7BiaqjifCBDM5OSVYWRuKpUBRARjZ3Tos4HlawihOC8141EAtEQCAGIVIQIEFk3-P_NnSSimRCzAeSYyLN33hCInUg0scneQek7A2OuSs5WCm-W75gBgELQPDAzmRg5JaTg89BxaEuMvgmQk8YEZgZORcK0zuueEB0qIkpWZtQiaACmVoQBwcBE0ZGxM1UgR8yoQs4boIFDIIsjqdTnzhmaqmk_gGxG_ggxm6CZmAhIRCUoGQRAAAhVBMUsF1e3agK6aSmwmcFYyHlVQxFMmVTMxLw3A0tFAaAIm2IpSh6bSV53DtWEsWYR0ZIsJ1TjQGZoCAZqWUhVSzRXKWz-EjMkcKwGWgojlCwABlkhy-YcBIhkCDkjKphKLKYCikRoAGCEtcNcMOcPtKtiOibSYiVvkO-QCySFrGAFsgACg6Gp9SOJYlFzDOTYs8WUu945gQpATMdsCqamAowAKTOzcwBEpcsOmRAlS9U2iOh9xY6c90Dog_vgQ86AyJtRs9X6UBHzdGtGRMH5ejIjwhQll5ziuKm9ArGrHYfAPky2m7quJu0kVG5vb9c7qkKIcT2bboHZdNIwY8Ourmt27KugBmqWpagYETtPjn3KUlV1N46mVqRMplMp2TtnAuxo0eeTVc_kgE0EBZTJxShTX_VJRCWbMLPzTExNFcwMDIeY68rnlJq6MYVcNEthdlmUyJtazjmJIWNwXkRczYv5OO-G5RBD5aQomHrnACFLkaJiZgZjln4YQxPELIn54LLpYt0PuSQB8mEd06ob0LnFcgRH5NkUh1zm82HMMhYpaIBuLLlP6e7ZIorMhwEMI8C09ndO-j6WLDpGcQR15RE2KFIkIt7Ux80MzdSINzc7qkCMiIYI8tRHP3b99u3vvPDiR5980oEaoBYIjvcO9p5_4eV2e7Y1mRLC1qQ5f272O7_5rXpSffO7z_-1n_yZqm08u3_3H3_tv_sbf-l0yNO6_eNvf_vKhfsffPjBb3_32edff52iriwftLvPvPTqD3_mcz__H3_17bduPvjoY9_83quX98LZ6oi8f_Gl7yeBH_jiF3_lt5_9-MceOjxZffTTT_zYj_3Fn_jJH-9KefSx--q2ffG7zz_54Sffe_etw7t3qG0Z8dz585_43A88953n_-7_-f9wbnLuvRvX__W_-g9f-Yk_55lu3Li-t7tLzl1_93rdtLO22T3YS-vRuFy4eP_d4-N7R4e3btzDBJcfvH95tgzBuaoO25P3X_he8DV6x77q1_24Xuc4dsNiPLxeT3y13awW_WrRSRz3L5_f3d8GgqauEYA87e3s3L59p6mrwD44ErOHH39kvloR0o279w7vHe9c2MtJZjtb7NzpYjGsJKXiiJeLVRpyjtkxai7Tc7P1al2yqKghOKJSBKt6Z__8ct31q6GZtkx2enxvSP3JyWJrd2v73Nade4db27v9cDYM_ZDGfr2eHy8feeqR2YXzJmV-vJ5MqqL52vWbgIySyzhqLg_c9_BkZ-_sznWRrKFuD6689-o7KrmC-vM_8PFZ2_Smqy5GtudeeePo9tlf-qs__t5b74W2rfea23dO_vyPfhnEZrOqaet33r3x0ccfCYgASgimpqZjjKnI1qTtIz77yrc-89Gnu5Sef_XasF7_5R_7ShySuoo9mUlwzLCBygIDAGzaBGhgBBCLqCES1Z5fvb68b39LDNEsVCygCIREqSgDEBN_cI1gxJu2ugIiE5rqtA19zKXoxpKhCkUFFdgzqHhmxA3_kADBMaFZXTkAcrQRJri25qbitvazuq4QZxPnCcOG8qtKzgnQqh8IoK0aRMxZo4kLVUqCSADYTqqCfLYejRAAk9jutF6u0_2XJ2fLUlRc5dTg0u6MiXxw81VfBI5X_XvHy1Ufm0mdRCqGaV3XweciSDimQp5TKt2YyuaZERqBmhwv1osuitFYLEmOpWQtRQoVy1LIeWUkQs0qpt0Y-2Ra4Y3TZSoiBnmMYGIIRfCLTz9syXIeM-LNwxNTffjq5YNpTaKmqqoKuHlujsiIhyKAKIaMmySygaIRDynWdSVS2to9fvnAk0-S1v3YjxEck3N1xZXjhqkYjHk0AwxeUM_OuhLjdDbZ_Me7PsYsMWdwVLWVAK1Xa3ZOTT2RrnNJetKPIsV7zx4DQhtcIAiORdWKNHUwxA21FsCYiYGKqGM2oCLqPRkAo8ViWTVmJQIwzLlUlSck5ykWGFMeckTEMWU1ODpdRYFYStf3YhZLNtBuHKfTVhTW_cjer1adIaacHLtxHGdN3VSNST5eLaetv7C7gwq3Tm5M262xlNMhjVKGnFfL_qEr5wldCIR1dfPe2Ytv3g77253oUNKY8tnx_PL53Tffu3t3WPSi4CgmMceeGYqG1onRfDGvJjWxKwhotDWrchdzSlJKHpNpYcdpVEA4v7fVd6OpGqpk0VSIUbMwsQ--pGiKm0YlE-exXHn44bjuGGxna6dfLdpQXbpw0dXh_fduzKp62S3ni-V_-Td-Ni5Wv_fMax9_6kPJ8_s3jhfWW8a33nz_oc8_vjxdEuSHHrjy-NUrQeDm9fcv7m-1s2q1ln_6K79_tFgXV2WAMJ1Y1YZpO9mbWah4cv9TKRdHKHkMVcPEIkVzIgRAkJJc5YjIBZ_Gwbc1lEKiqqZgYIJxQASNEQ3RQJAwODQyESZGMGQPziEjoQctNsaSS7O9owoqZjE7xyVGQyhZwmTigHk6TYtlMGl3dl1d--BLKRIHxwyGSKQ5Izsk0CJoiraJVRuCY-8kJWIirtAFNEE1KcXMyDvbgDZzUSlo5kKVYyJCYK9mGzAoOOdcsJw3VV7nPrD4KrBv6rI8o7pC51XAMYFZycnUEEUAq-0tGUdLiQHBChBRVUtK1o_kGQz8bILEikwEmgUJLUZSQUIVdW0rRUyMwWyMSOBdUDNVZe82d8OIgCYcnBqS8-SDigIzqaBzkjOFYKVYypoiz2bZCNRsLKiFiEwUAkMRct6GHhFgKMgERCAKjoDQkkCOgMUYYUxABABMBDkBMThEVR0GKglMrapMFEwxMAGAGObEk60xZUT1jsd1dluz3HUKpuueQJgcGKlmBLOkiKCA4D16yuuOAY0dVt7ALAk6spzBBIoiAqhCMRDh4BBUUyZFZtKYNlUNKAJqxmwpWxyBCMDAwHm2MW-utEEBAkIqwABF0AxVICuoWMxWMhGRD2YoWS0n3IA5RCEl51jFkDAQQRolZUfeFAAMARARyHgDsnHsnUcyF3wzaQTQ-wqQnGfeiKiQjaiuajD0tfdVAM95TKaqUmQsvnWIzvvguDLDCxd2ah8qHxxz27Z1XVWeJ5MWkULgjQjX-1BU2DtlVNNSVIrYJsCGAMwGGIsO695UwdSQ2qb9T6VzIE-rmJBBTHLSbCqAggAAq1hUrYABECJULoCBJ5Ki4EnUyGwymTBhEV2PEZAVbYM8iEM2sElbERAx5JQVsY9x2Q19zG5SEdF6nXKKbx5db9ykG7IgMOO8G1ZDWo0jsr93skIPVRUOF91yHaNaIS6q2awf0sl83ccyJEPnujH3uWTVPpZohs6JyNDnOIxnq265TAqY1IYCo8gQcwboc6mbalo5T8xMTESMmyEGOyQiQHRIakC0iWijGqACaHzoQ4-UKL_xK7_z9Oc-SyKODYwrRxcuXPzu869Wjd-ZTSi4y1f2jk-O3rt1PC7iz_7UD1uxdnvyneee_amf-fGX3njnicc__O67b33kySf6WCqGP_jmt_76j__13_ij37t66aFXrr1_9erVr_7WNx574sNnGV965tX_5mf_4rPff-v8pXPff-u9xy5svfzGW594-iNPfeLp_-3nf_l_-bl_9z_-vX_0ve98-9qt29_79ov94bwI3Llzg5mruinZlDBU7b3jGz_1Iz_6a7_2y9Pp7LXXX__M5z51eu_eulteuHBpfnzSrVfjMj7-0SeuPPqxm2-_mdP48gtv_uhP_OjqdPH-9VtHpyem6psqpeKD71fL9dmi2d2u2mmM0dV1PZtWs3r73PbyaCE557Gs5yOz2z-_u17Phy51p6u6rvYv7S9PFnXjTw_vmWo7mx0fH50_d3HV9dPd_b6Lrg1q-KGPP_7Om--Hdnp8ejL0CZ2VlIGgSEbcrPwKCESOQwsgcYy753a6vi-5kA9Qcz-M61U_nU63zu9I1uVR10yb08MzX7dpGG5dv1VNQ9XMuiHtP3D59PTectldu3G7kJ2enj36wH2PfuLjOweXymr12CMfqap8cHAgIouuW68Xy5PjLLCztw-YDt-51k7DhUsX3r1-5_hsef3OvffefW91PF8sVw9cOPjSn_309XevHS7mLzz78myr_amf-vJr33ltNq22d7dff-f2559-lAFUimdnKsH79TA6oKauXrt2DQH2zl9epOF__We_-v_4H_4LjVIAN4KdyiEoWFEmRjUzGzQFdITgmFIWRwTAU4ev35tfPD8hAg8aHBuoCRQVBGQkIkIT22AciRjJAHBD0UNsmiqnogaCQIxogIBi5hwDGDMDQiBXVyE4dEDeoanUwTchNMFVaNPKVWTbk2p7Um_XPniq3AbQiyoiCqv1qGp1W3nnPTMBDCkDu3GMfZTFqtvdnhXAk2WXDGRztEME1aFLVeVPl8MwjIIwP1222-2s8mfLYW9_eu14_s6949o1Q1Fit-r72azebqqKWRSQqY_JOx6LjGMRRBFxjic1DzHdODwD9qs-rsdsnhChjEViWY5jLkI1g1gIPkkppZSUhphuL1d9TK4OomJFyblkULfNtduHH7l6HxLcWSyLQjcOT1y9uOtcE9gxrbphU6dW1aquVn1E5m5IG_LpBssuRqKwGmPF6Bzdf7C9UwXJZTkM00kzbet2Wovgehh2JqGt_KqP587N-qHs7E7OzvpcbG93y_vgGIc-9jH1MSrScj0Y4GIZx5Q3wvLKY1s7UDw4Ny1JnKccY014sDutvQNQRmDHjGiiwbtSMoC1tWdGMFCEjds6ZSkpZ8CYShFlQna-5LIRIrnAWXDZDUY0xujI5SxDTuuUhlhSzmNMY8qiGrwvpTShUrP5eoxD3uizxnH07IloZzaJKTqkt-_d_dClcwfbW2Pfn9s7UCkAlCjMh8E7d7C31dYVE3apvHr9FlVh58LuPKblkLphiLE4goceuDyrJ--fnSU1Y1r3Q9VU3leeCRAHEQasHBuAAcQx7bXNWPLYjxBIxhzqmpHadjKsupKSq7jERJ7QANGqaZWTbqqbJSZTLCWh2Wbr6kNAoLM7957--FO3r9_yxDu7W8f3Tph5qcPHHv_w_Pj4449ebZ370MWLf_Lq29_83hvHJ8dt1bz8ndf7dd_6ysTue-DCT3_lBymmaROO7x0__fQjifDf_uYf3DldJRc0CAeXVJXc3uWLoakZlMvWgxSc965I1jFuXb4UV0PVBunjbHs3jz0ScagFvAGUoSNAdmylABF7yjETEhMjAhKkOHCYoKMNfsfXlaZUiqGvwMC3MykjAOecna_r3Z0y9mWMhOir2kS0JHA82z23c_5gdXaS-lGK1VUFCNIPzvMH0X9RBEPHKkJqjBvWL5F3m_2Jpg7YI6DzVR4GcmSmJWdynghMhYF0Y-xyhIRgQOzAhICI3WZjZGres6ZMYAYIzGiGIUgsvm4NsJRIoYJSqkkT12tTNWIfQh5HAmPHeYzgvXNOtZAZAFKowAcwMhEAZEQoI2-kBgDkAiBbKd4xlgRFTM1VlaRCuGlJbfCBaCqAhC4AkhEykcZRcwmzSYkJpCASoglXUE9kWIbAaEhgWIpHFhVm1T5XFWMRSQYAm34wIKEixDUWMkcfTMfRqahjACBAQhWIhVTJtCQB50EUCaEUJrKYlJDroFnJlASqWSNZrIyVAReBDYOUcSNGJUSNJ1hNQQ0QSIEQwcTImYn3BJvHUza9ZIAsYKhGoAqiloFUdLwNbvuD6T4ABAd9BBUwAkZQIVVNeWNqAyLIAmMBho3TgBQAEHNBkYCkY4YQ0DEy6KqrKgdmtJE9jsU5D0UhZotjIMesGHOJQgxgggZazFSIEMGKCrkABnXdACFzkKKOXahqcuCqoLmUYgAEqnGMqIqmhOQIds-fA8WDC3uTdrK3tzWpq8oHX1dN7SvPjFBVnsBC5RSUkDa3I0SUSklZpIiKitp8NYCqGiUVQYuq_TgWkVHM-TrsTtfzHggzwDKV5SrGJN1yAISitrkZUzVVEN1k6W17q12eDZNp7QOrgIIRofOOiNSg60df-5SzqklRMAAEFQQAF5wDLAkKkhQtAMYcoxIxBVqsx-1mu89ZAMjhsstjKUQExGqy6scxytmqn48JQ3UyX50uh2i2HtOYdd4NQLzsxmWXfKAhiiggomhRAUMSNSFUA_Y-lVKy9TnXlUvZjB2guUA7VeMI0GCDjlVVoE1j2wEA4oYsALABGTJt4L2o-dLBpQsPH_z__vm_efqjT02qChBR0Tt-4IHLf_LsMxcvX6pdVXn_1NNPffW3_vjhB_e_9czLP_WVL_3i178eD49_-is_9nP__F9f3Jr98i_9ujkhZZXhX_2Lf_M3_9Zf_6Pnvvl_-tt_8613b_zQl77QIu6fPyhDvn39_ZjmwU3vnNz53q997-qj93Gz88Uf_ZF_-Pf-3tQR57Q1Dar2Z3_yr11_7cX54uz06HD_wsG5nZ11v3748gOni9OTe8d_-7_4u00Vvvmd595_8_1PffJTKcqTH37ywuWD-dFdR35M_cnh2dHp8b333lidLqa721jK4emdRx__yI33rx0fHkspiqSIQzdAyYgIjuMw5jh2y6UUiUPWIjt7-1VdSU6GqqaajYB3zj-4vbt17f1r61X6-Oc-eXrvKJeyf-7ctbffmcymDnkYhosH5w9PlnfvHu9eOLj-9vW98_snd-8wGIKAInkX-5E8mKipeu-AQIvNLp3XiJLH6V7jJ9W9u3fD1qTZ2dvZ2t67sNXP1zHmyvmd_Z2SMxMtjo_QJA2rvl8j8qLr9i6c78663b0Z5NSvlqL5bH7v-ltvnt65uVgc3zu-nlTczuxsPb9w6SpVdnTrnmvqhz_x0Xdeea2q3NUH7zu4cv7u4UnXL9Oq895570LgL3758ybZu8lLL7-yXq6L2KMffui5Z179ob_whTHDi6---sXPPslKRYv3IeWsYAyIBHXTfu0bz_yFH_hM18df-LXf-sKnn_zoY48NYxYAYgYTRkAAInBEBlgMKw5m5phEFAANsa38i--fXN2fOvasYIQOydQ2lGw0BLTAyEiA5N0Hij1VZcebkXg7CWNSLUJEqmJmooqAKsqOqrpCpOCYEUEteNrbbtKYt2dNqNy0rmZtmLWhdnhuq2m88w7JhBCYEAxUNWZxlWubigFLkSK6GtK6i8lMDRUsl9w21fVbJ4OVqNitx5QlizBhP6QhaxJZjZkABOne6erm0dnz710fwd65vThb9aqkTNuzVjFPnN9pmkA-F0EE9tz1Y8o5ivQpqVrMOZuKmK_DOufFcl0AVt1gyOhpseqN0JzlPk-apqgiOVAgYkBUxVLEAEUMFUwxGUzaIDk75r3tNidd9ENw-OkP3T_xjsg2wHtDM4WiMJlU6z4l1b6LLvDOpClJYxFkjiWjGQNM62q3aWaVz7mMJW1Pa0M6X1X3Ttd7k3p7Mp14NsM60JiACI9O15NpPZs2Y9QYywvvv_fgxYP1mJDYnBuTzNc9kIFIU_vguK7r7a1J43DSuKYJi279wKVzkyqomsTiAqsqM9l_2hY1VdgcPpEpplKKGFrKhV1ISZMU9mQGaUzsHTnshmiOito4JjVjRI-cs2a1PssQU84FEAHMHITgPLumrlLR1SqSAxd8LhpzqavgEB2jFjCGkvoHLl_cqevVuA4VlwIJ8HQ9EIIZzJqqdtTOtq8fnhTD_QvnUrajbhhLXvbdcowF8Gje7W5vnw19n2Izm2qxOgQZs4i4hheLPnxQLk8bpnxSGGNUs9THAGRSICsDNAGWJ8uqboY-tk1L0wpH0TGG2k_3t4_fv9vuTLVkK-I8E7vp3i6IgNlWOzs-vjv060k9CXXIqQx5-PGv_PD16299-LH7n756pW0n4uU_fONZZ7zu15ri0d3T8_s75Onc-Z3PPPX4QVW3TXu6Xuyf27l-7_Qbz7_25vvHdw7nMefYj0OX0eHu_q732PdrksLbH_mBlIoLDiSVLEQY6lrGbAgqmUpGLWOKrmlDmJQ0sg8SR9xs4oiRWQ0Q2VSRiBBcUxN6DlWJSXMm5wABGJGDqdZ75zQOqKAGblqn-UrjiGiQMhKUMfXLwU0aEqVmEtcr51zs-n7duUBmttn9ImCoajVBRcmF2QGYqZgK19UmzYGEhOiqGoCQQVNxTZAijtnA1IwcMbOmYqLsasmJKZgUMHF1w01TctaUyDnNiqDkHYAnIlUFLaHdKyWDZR0zoIIomITJFoghkwy9FXHeORfUjMA0J0LUIlg3iMTegwiSOQVI2aSgGgaPoTIziZEQLGdA4KoGFURAJlBlJDSzXJgdOhIVzQnBCBDEsHKaMjofmhbSQFUDdR1qr2OcHVyKZ2dcDLKgYxmGynkrQlkMjFqHxSxnYIQkbAgKWFWmSqpgSN5DLhKTm04sFyJkUxAFQGS2UjCbGQAYjIMWxaYGwzpUZbECZjdtZMxUkjNDYHWU-hGZAMh5V6L5abu5-SZCzbKppxFTWQ2OSHKBLMi8OXpTFaBiS5k3sSgTdFMtyp43vmQIHoigj4AMLJCTpoKa2QC92-TMoe_RG8SCubBDNIQxEhhxcJVTEfJOs2wYrihqQ4_ZvDMyQCkk4gixABQBMxe85oTsfFtZzjoIIRJjHlNOWk0rEDVFCt5Pq7qu67ZJSX0VBInRWRYCy2Nhx2awu79TN1Ug3D-324SqaZrZVhuY-5Sb2iMgAhFt3nCmhqUIMjumnIUIcy4piaqpgSmw90pYAMQsxbIeBiYCzyY2mTYT7xUwma6HuOpGAQVC73mICTcDfkQGUjPJAkTFBIpO2gbMiog5UEQpWgVnBrEUA3AhAAAaIDIgBFePMRKxdw4ZyOM65s1tTZbiKp9VhlGKQRQF9kkLMt07W5vCckiGaICq2vUpiWTgO_dOouB6TKKWVAtgEujGgoymRsRJdSwFXT3G7AjUTBBEAZljKs5xzFIUFMmQRdWsMNj-tAG1jXSAGW1juzDYRIF0c5-xqSBvbIdAQLqB005nk6c-9uT_9q9-cba3c_X8JbCEwJ71gQfue-3N95omlDH5pnFe79472Q7VZz7_9D_8X_7l3rS9Ocpz3_6TejZRi-e2ps-98v0f-tKfuX5092f_0l_-d7_wi08-_sRrb7z9_vV3Jk39zAvfm88XSeIXvvS59-4t-sXyz_zw59-7fnt-7_g3f_GX97e2uLE7t4_uHi6LpuuvvrA8XcXlqmkqSfHw-NRKObc9uXe23N7aGtCcwq1bN9Yni5vXr1fT5suf_MIbb79yfOveycnR7Zu3QEtV1f16GapKDIb1cO3dGz_4w19ezcebN64poKtacz4NkdBAtMRkJZsUHwI7MilaInojXw1SAMgUShpEdejO5qdHs9lUdXzvlTc2jIdY8oWrV0-OToZ-5YO_eePm9vb2_Y_dPz89A5N-tSiSmdC5kMcc12ky20bWNETnyDHNJtMU8-L4ZNY6K_no9vzipfuHsxNPJMt1f3zSLbr5fHHh4sWYUgbr-2HWNCClaZs4RK7q1WIBUk7u3gPQaTPbPrfTNhPH-MDVB0-PjsxgjMPZ6XK1XJ_cPc05v_fm2-yrsevI8e2330rrgj7c95Gnbrzz_q1rd33A7b3dku3v_I2fvHvr5NOf-8JvfO1373vssbffeltHExQD_PwnPnrxoQeHLr3w-quf-dQTx_eO29lkebIcVZrglNA7vnW2zHm4ePHgzZs3nv_m6__9__6vpr4UA-94U7NlQAAgIgUz2pxMTVQNNjhqaCv32rXDi-cmLjCbqZh3yAQIWgzUAACAacJUAIGQmER1s5SrAaiJYWhcSgUF1AwRkKhoAVBPjpEMzTvniRjUijpHTR2mVdV43mqqtvLTyk1rrqhMqyYQEahZYcLgmJCLacylDgEATG2xHNcpu6pC79j7IZUx5eVyube9dedk1aWSkmaRMeYPJgtFogiSE5MwbYchllTuHZ5WTX2yjIt-XI-lmLXt9PxuI1n2Z9M2hMZVRVRNNuOSopaRxlIMxDM1IQxDVHZZad0nF8gxJyi-alPOzrEkCCE4JGQUtLGPLngi0k2cGJ1IQYV-SOgpFyWw559_55GP3X_9zmISQgj04csXnCgSFjExFbEh5dmkqQKedWNWNZUmhNrT2bJDoj5lMQA0AmgdXzq33ThMuXjHngkNzvo0xjSdVh4YjcYxmuhqTMXs-LTf3W4V4OR0devwdBqqpmm7VFbjOMSyXHbAnEqezVrJeW9rUofg0aEVYswqB7vTc9NJ7ZwH8METAhEBWB1cTNk7dsSOEBlFbT3EWMpmpRWFfoixCJPLpbRNDUBdzF2fo9jRydKA-jExsxkAQp_keLla9zGKIJOYxLFUrZ-2lWeXVFMudVN1Q0Ry9-an27N2ezYTKc4zEE5n1cXtmTM5Xs73draqplp0w9GiG2RkgCu727O6vnZ4Nl_F_Su7VeVefP3aIidqKiVS4p2d2fGdRTsJk2lzuuoXq877ALk4wjGnxWLtA6eYmd0Qo6kammMosaQ-es_pbE1mFmNaDQ4pJ3FAJSuUrF0CEFAIVRXXvXeOtFSzdlyuAJ0hV029nJ_N2ubixYuLs5Oc0wMPPbgxAlouh6d3g6cf-9IXZiHkUZY5P_v6O3cPT6dtbSbbezMTNdHPfPzxj1y9OPZD5b2k1DRtz_oLv_R7i1XfxZEb75qQlR765EPOaL1cLo8WwsrhoU_52e7q-Agstu009RGRkMnAct-zmZpKTq5uzQxcyMPgAyMSKCAAO7eBjzEySDHTMgxha0uKqZrmSAZqwi64ptlMZzWL9545jH0iJlBBEZAChIrU7GxrGtIQty5eGrpVkexcbeMqTKocM4JpEUJi70QVTMlRToUI0aGpMFdoiOSJaOw7YmIfJBdXh7juN0JTACLn0zgQMm1yESKbIwOhGpjkSL5h5pIKIbLnzVqDiBwqI0AiK8VVjUkmBB1i3VZlHCwXrCoF1JQcKYiZgWsaFVUpzrnNowJi2YhXgNCK5YKq7KDkDMjkvcpGu5s3SzAxAeAHq7UYFHEhSE5KDN6DZx2zY5RYqA7IrAXAFGI073hrhoZp1XPlLWfNBcUIsaxX5AM5JzGBFEICACQC56AIqWBRboIWtZINmUPYZGCYvcSEZpoiioChErIjFaHaQxLLkQGNAvmKwKEmG42bSU4jpugRRLWIEQkGtmiEZrlgqJBJusG3tQyZg1cjBPWIMiQA2KSMWICKoBJ4gCyWMiNZjKCKzBpHMETvARiyQIrADN6gS0hkxQjQnEE2yAApw2iAQCYSCyJCzuy8EnFwWsqGAglJ6mlVlqMH8MSQxVLCJGjAiITIFUsWAGPnNYukTIjsfclAgIyUs7AjzdFA85iDdxsdTwhVH9NkOmGHzM6AmrYKddg7v10F79BfvLh_sH-ubms1m05qRzhrajVxwROAd7QR28WUBUlURS1nA4Rc7IOL0iLkHHOISRRNQIYxFrSqqs4d7KGFpq61aEZIosuuBwZEyqJqIAbeU1VX7HiTm0OmlONsMkMER1TVoZhuTqGO2YqmpN26b-vKVFGJHW9ys5vklSfzwWkRQxizgkgWK2YpFRUeUkQiMwTCktQAUhEwNYD9WbXodbUejcnMYs5KHEvMADEVCsGQxyQbQqhjmvfR-yqqbuI6QJREc1ZV8YwANA4l1I4I-pgdu1JU1Yjx6rltzYUZrdjGDGAAYIaEG3y1GiCaIYqUzfcQEJAVFAWDd5_8wid_6T9-zTHcf-WqSSFzjtz-3nZMuXKtFjt_8eIfPvP9H_-hHzm9t_zei8-_f-322fJkZ3vnT779zBMPfeTipYOO8XMf_eS_--qvf_GTn_z13_yDULk7t26D6rV3b964ffojP_aDb731_vz48Dt_-tqjjz1648237ty4u7c3c8x3bp8ulidXH30k9csL-7vbWzMHlMZ85aErPrQxjc7s2t2799_30GRr59adOw9eeeibf_h11TidTZ74yEee-d4fzw_PutXq5PgUTC5cPG-qq_m63Z6yQdUEQDxZrA4uXH7l9ZeDD4RBvc_jKDkSAiCxJ0IrqbgQHKrFMccc-2F27lw92yo5lhwZDcE8kxZBwMn2JOfkQqNSFmfzj3726dXJvKpdUYs5kuE4xu1Ju1ouEKxp21wyGM4u7U3a-vTOka88iIFBieLrSiHnNFbBr1drz4Ca67rK_Xhw6UBVuPLDchGcA4_sMS6WO_v7Jyen7WxGoGkc9y6cj8PYtOHw3lE_xunOufl8FdrZ_HRxcOWgCdPJpOkWHaJWdSMAOxe2h7MVedQk5y5d8gw33393dbaUkvfO7-8EvnRl__2b1yzZJz7xia997Q9KTpcun5-fnEy2psfHZweX7nvh-RcffPyR1956rfXVO2_d-fSXn3rpubdoSHvnt5TQOf7Gsy9--qNPZSj_8ud_9f_4d_5KO5kWFSAS1EDGSIwoImBGH5AqYGPpQiQAYHbv3J3Ppk1b12ymiC4QqjpAA0DbIDMQAQSQEUQNjMVUshCzAmyCcPW06rpopgRADjdUAd5s-wi8c4RQe1c5DhUHx633jae2cpNAW22zNa2mzHWoiVClGJgJVMEH7w02gWI0k9WqN-CuFEXOKm1dFcHDk1Ml8-yB3fXDM3V8uugliyGQYw5eM6Dzw5hc5TJbv45xiFElKYTpdEhJANZxfOSRS9DlEvP9l85V6BihlOS8S6UAQCmFOeSiKqUJlUdc9RHJLbpeiQ1IFdV8N64RMKacotDmcSBEESCwYo54Nebgq9UwKOCy64yYkdpJM_F1Mwl3D9eWrW5rlPjIwT4BCMNiOHRQC4IY7syamORsFYtp5b1jZM8IKEAG0Kd8cG4r5nT1_Pa5SR0CIdjurFXRLLYYEjqahuCZCAxBBbCPuc_ajbGq_Xo9LvuUSiFyXPmUJBuKWh-z8w5A2-DI7PK5LSacVhzHKAqTtt7dmuxUNRP3GwAMAoHVPpgBmAXPnp0B5CxjKqLmPKsgeQ8GWa1I3uDbGXksMqZUSG4czpPKkMui66rg-yGp2bwbs-rRfFk3ta-CiGaTNoTGV4iuj1nM1ushxgIIwzjsTFopQh49u6LiCe_b3yWD6WTqPZnI9aP1adftztqD6c44Duu-v3WyEIRi-vb1o8NV5-oqVJUSLBadRyKDJLHEPIj2SeuqbmbVqhtW3SimDGzGQKhqY44-hCxlHKOU4rYqFUG1PGRTxeDarWlcd6EKJSaVjNnqiY_rAdQmW5NhMSCRAYQ6gFld1akfgq8U7OzsyDu_f_XiM3_8rfvuvxJLOj09cWofuf9iTpKV_tlv_P7B_RcW8-HTn_roX_z8R_-7v_WjH77_oTu37_30lz9DxOjp9tHxzu7Wcy-88rvfev7uyXw1xnZ3SxHBcR2aaVX1i2FxchrIERHbhae4acC0pM5VARFMIMymue-1ZP5gs0I2RJrMNiMxKXnTSd1wOdQ2lSPUkpkI1VLKbjJTVXQEABxYRIXI-QqJzUT6bjOiwCqkszP2XlNBhxQqVa3bSR4HAKy3Ly5XixAorvt2ulVN9-J65b0zVRUx54AYRTbyWxVhIgIuquyZmJBYJFeT7ZxGs1KFAKIi2TczlULOaS7ASOhMCpgiO1P4T3tNb0ahnZaYwBQUSQ0QyVdmAmKm4mdTLVljdN5LiszOSvGTLQGTOFocXRUIlLgyU0Mr3Yqqxgq6ycw20f5xcKCIqKVsKsdU1QbqnNecTIWJwQDMiNk2AmwRMENVIwPysNkzFSEAYlYgDF5FiRliNIPq0g4B5WUXZpMNwRPVpCQm3rTNQNRi2nwYmAEQQhZWAcnywZd582JVKSQFw6Z9kVCVSiJkBTNPUBQ8oRibkaqrArPXXGwcUK3anklODGolmaGbTHUclYjRMRqaATkwBXSACEXIM2zGuWMiMiC1Yq5xNhQuYoBu4mAsCKaloBl6BBFLCghAyNPKxgJqEBUcQlFEQikaE9fOrEBKhGBE5NBiAjFiJoBSkm0CKwYIZgioEFqWVXQGTkikbOywVVVLiZLVVw6BQBQdgoJvKhcCogXHpmKm5JCZZMgIwN6lYWR2YFDtTNu2BdW6rlzrL1481y2zC25rOjN1jz9x5f5L-464ntSIOOTknVdQJMqy8aZrKsX5IAApFxFLWWaztoiNMauaiAC5YrZedgJGYEXEkJzze7szoiCiXT8UhGwaUyHnSsqlZFVTwOmkrpwDQS05RSFH6KBt6pKTZ5_GBB5jlpILGFkphARMVVunGBHYeUrjOAzJMZPnMeamrZomxLGwC4suEqgYbE0aMZUizC6lbIibKeM4JnZODFUNEFZ98o5jLlVdtc1EDQxxPQ5IXIxiEkUUMEFwBiOimfVFZyEUUCmWxYac2dGGY83MRUpbB1VEplSEPLbB729PoIjb4P8J0dDQAFFMmRiIAPEDNiITGLIjBdhQERGM1BzB5z77ia997Y98xfdfvl9lMMUQuArVOKT1cvXAg_cthmHoF__4n_xTYlycnmztnFvdPdo92DGIr7_26m_96m8__vjDzzzz_ZOjo2Ecps3su888f_ny-bevv7dexqsfOji5Pb-8056dLn_wz3_-zp3bgphSWo7rH_mpvzzZnf7Vv_U3gqb7H77_c5_9zCMfe0SBbhyegPFqNTcz10zmXXf-4NIDH3rk93_nq2enp-uu_3_-_f_x3_2bX2qaRlW6xTKnfro1mc_7-cn63H0Hk6aNKachqaabt-9-6jNfnC9OulVfMnDTlDSCKXvajG_Z1HnOfWRErgIAbda5Yd1tXzqop1sKygo5xjiOWnJJOQ0RCRtX9asRAe5_5KH1cn3u3O78bFXiICnG9RKApD8ydaI57E2s6PrkVM2MgAyc82FrNg5dyUUEm-mHIJ9dunhxMZ_nlMchJuLd8_uBXb_umslkfnTaNnUe0_rsFJhVi0nRQpcuPtivl6Uvjnh7Z_fw9t356enZ2Rlons7aWJJnPz9b7eztDTEe3zqSXNar4eLlC-cuH8zv3h273lcBKexd2CfI7791m-qwng_L1fi5L34mxdOb147vf_LBEses_vGPPXV6Nn_v2vX9-_a-8ZvfeOn5165dP7744Yf_xT_9hZ_8yT9XB6-mfYHXXnnrqU898XvPvjAc4Y_82BdKThlg49klA5IPKr_esQqAqvdsYEQMAJXn22cLF-jcrCFTVfSeCVSLZjUTMCQw--DFvlHPABhZASUiUlAzZDYxNNvYNQGBgJHZDETU--CcA7TgXB1cE3zleKutPdrurG2C94izNgSC4AhMddMyIHCOHSITm0Euuuw7QDIknPBqnQtAH_Oii6fLZUoFGfd3pkOW2yerZJZExcxVARjGmMBQAIYYTWGMcYjjMCQRKahDEmDIIma0s9umfhApH3_4akypdixmQz8UUFGJqShRP6R-HHe3mtr7PuauyMl8laQAIZhqsVIkSiLnSi6O_XrsZ5NZLCo5usozUtbCBASsBM2kXfR9xVQFLkUU3GK9YIWo6ZH7Ll6eTQhBVBFrQlYzIvKMKYuQjmOc1L6tqhJLVl2PKRUZU0FGTfnq3qx1BKox5rYJWaRPMu9HMK0dp5wB1Hm3HsZsdLwcYikhcC52tu4VBJjX63E9JmNad2NSq9rKe0dFzm1N28rXjjw7UNw_2G6CdwQBgQDaKhBK5Z1DIsI4JiT0jsywiBQtokbOx1xETAzGVBbrrs-pCh4BjShLOZyvmgpunPSni26xHm4dnXjnSrG6Dqsxd2OaD8OsbbmucoyTuppMmoDknVssVylrLDKmFJpKVLbatuQ8nUzGMYbAVw92Htjd68d-a2d6ejw3sbvdyI7bxlHOB9tby3W6te644vMHW9eP1uuYp3vTVTfEXHopbV0tl-u33rubUcXQiJLIeuyHfpx3a-fIwPpYyHHRrAaieXXWEaGrvGYtY9LNuEhERb2vSombK2PIQMVMsipWuxNUHVejivkQIJvzzjFX3l168L5x7Pth8ME3zWx7u7364IOSU04Ds_7En_38bDaLIf_Ob_3pnbvzrBbX6ZU3b__OH774zlu3vvf6zc9-4slJCHu725N2-5133ztbDXuPXX3xu2_6aa0mddPknCpXiWJMQ993Im7__BbvPvWlPme_GUTHxOxUTQlyyUiY-84Fr8WIIceBq9bXddFMAL4OIGpKYmZgWhQZNh_XpiamgEbOby6FUYqaclWLFOe9iDEhVxU5j0RAymZARobV9vb65BSdK7mTsTt3-TIWAeaMAJo1jmhGCIaYRTeOcVTzTBvjbsnRezLRDapfiqjm0ExiHP4TY1lNhUNQVUOwYhwYyUoWIAAEUAADSxEIEJ1vQo6JAHzTmEjJmZ0zBEkFxHxdaymAgKZaEiLl2FEzc76CHM0UVYiDgpmK-8AIaEhsZuycpYGYENEAyDtkQkD-_9P0p0-3Xud9JnYPa61n2Hu_45lwDg4IgAAJkCA4k-AgkRI1WBJty5JsR7LVjjtpp9MVD-XupJKqpCrDh3xLOql0paor1aXudsfpjqsctS25ZUmUJVKcxAGcQBAzcHAOzvQOe3qeZ611D_mwj95_4K16h73Wuu_f77pSckCQGmPjtRJFMwEwd1AR3N1HXDGQilLTIJqLowki0ayHyJazi4SYrNam26vVDJCBAyHUyq7g6ubA5GpeMpO5AO0qFpR20312c0DHACoASCESI9aixULb21SYHMW9CjA7IwxbamYgxqBYNC4OxCA1jWwHNGv29_I4mVQ2dXEIpFoRSUd5oJYJUVV2awjLBRANiQPXYUBRIjZR5ADFXAWcMbFOE5iiuY8TAJgYxgBZgCMQQhZwh4YBDdQxoE-VA1MIljMURXNwj5GgSIAd7AgMg5uig1djjpIlckAHG6aAGJ1ryWTmAkzIiFKNkZkIicuUY9e7gtUHfeuQGAFC09SpUGCp5o7EBKopRgZA07IdOEQQbNrY9NTOmlnfXDqaPXJ4cDTvL876YZvHkjlGcEcgQ_dAaF5Em9QWEUQWN3cMgXMpudaqBoAcGJByralJZjaWQinFEC4fHTDG8_WgVo1pM2zHMYuYmWgVM3XzNsXEoYgQwzBkdw2RkKmWQoSMxJFNvaq5qSl6FWY2dxHFQBRpvR5KVXWlyIgESF2XAiByqCpuwok5xFK1isNu2eLoBhW0n3ERN4VStRbbjBmBVC3EOJ9101hMtG0aBcpVjLhUG-qDe8O6ahZ1REQ3gGGs21Ld7UFbEchxt-MMRBxiMMdaJERCt6P9GVVB2q0N2N0QIHBAtwf_LDsGPsDOjwq4W1EYODqRA7AAmX3kE8_8_h99-d47t55--ilXq6JEpFoWRwf_7X___3nhlTdfeeHVtmuL2NHx4stf-9aFi0ck_MrLLz751Psg4a_97S_-P__v_81quzo5uff2zRtHR0dVuVT55E8_t1mvNrdPPvSpj9-7d1rL9J2_eLXp6sMPXX7fh5555gPvPT46-qM_-MP_yd__e9_85jdfeOGVb33lO2--dfN8vdQyyTSF0DSz2cHBASLdeuu1e7fv3r3xxl_99V_72te-vrc3v3_vroue3z9Rkc16yGZHl47nB_1ib2-xt788O1cTK_XTP_9z79y8ce_0hCH1x_vjeo0OjiBj5YYtC7o2baq5mglyBIc6ZUQo01SzUNO2RwcySEytjMUBiDGXOmzWsY_TZnn77Xf2Ll9ipfl8Piy3ZLaLiudKBojGi0sXEvC0XhODVuMYjONwvkEEDGgmPpwih8Mn37W-exoYY8dnq6HpWu6PSCvHdPDQQ4x6fnoOhODeL_aWZ6cXr1-9985NrXrl4attm8btZrNet33nbrO-u3f79vJ07cRNmx56_7s3Z6ujy8cE_vFPP3fjhZcQcHX_fP-hCwcXju7fvrM-X6eubfcXm9UyNVymcvz0k3_x5edvvH37Y5_-0PKdd64_-5HR8Ptf_8b-ov2Lf_f1POkj168-8p7r3_qzr7994_Zv_MYvB_Zs8sJrN48P9g6P9_-z_9e__l__499kQMCdcc8IdtxZNDBAcjckIgKHB-2whvnm_bV7uLw_NzMVb9oAYKoamJFQdlpGBzXb_TWbQ4ihuot5IGIHQHICVUUiNw_MuzicEylpDMGqxBBCoIjQNSkyoluIxIRN4sDcd7FhRrPdwaem6h6I29QEYkIw8OVqWwE4pGGsgHGbiyON1ZbbTS6iopG56-L3X3q76ZqzzVjFs-pUpajKZIg45orIHHDnD46JiVAMzFDNGSmEYOIiQoEevXo0brZEKKW0XZNLBcLqQCGena8Nbd7PkHCd8-lquxnKapiKurvFhJHCaj1yZHM0tUmNiCNzFUOgamoCqWkNfNHNxqnEENomJI5lM7apMQAgq2w__-EnW9u5ShHA1HbmcXfEKddtllyka2LD7ESr7SQOVczU-i6R-bX9eQRe2dhzKNVqqXeXIzGvNmOf0vmY9_uGiJBDdrx7tk5dV8S2Rd65e2pIq_WQ2nYSEfAi4uABOaItumYWaa_vay77iy4ldlVwaIgP9vu-CVoqEzGAOYiogYcQzKDUHSAZRX3KIqpiVqpOuYhLSm3NJTSpVL2_3Jwth0Hsxt3zTZ62Y3YEUZsvuvV2GqdSd0M5DsRYpilGnrep6xoEB6DNMKoDcXC1pk_gHmOodQox5u32fY89RpbXy7PF_l5q0yt3VjlnY2hiePjyhe1kX3r1R9cvXnDik009WY8F1B2X621ROxvH5XbbNc04TU3XDLlwCLnmnIuU2jUpj1nIKSZTaSKpirEDADkQAhOXPDETBrIsiOBuJspdKuscUakMWiSmlg_T8q1TIkKV2AZx2Ts8ypttSP38wtHd27eGzeb4yhUtWcT6trl_99bFS0ef_fgHH7tw6XQc_vf_6X-pBSrwxz_97O2331muVptxe391-k_-8d_YnI3Xr1zq99Mf_cGXD_cvPPGhy__p__VfpjY6Y0QE981q6uYdhfb-zbupj0xNwshTc6U7WHRNJyCgFiJJycTMcZeCIGaG3UaplBAoph4RJBdVBWKKEVMEQDcljghorjtv5-ziZSvFQNGN3NA9T0OzOFCF0Hd5swX12UMX6lRdxHIOgRCojX2MYVydM-j25L6YXH70vYvLF9xxXJ5gVStKITgypPgAIyACCMaOgF5qjI3V6sTcRtMq05S6fdXqIgQQmM3c3Dg2CE6BdcrUtmaGphQYkDhFcgf30DTogVNTSvZagQicMNAOFQqqaTaHXdkHWXN5oB5uE3FvUrxUdJNpwKZDdSR6EOlpEvUd0U4umd0MRInJVXXI1PVmZrW4yk7ti0AhNSrKD2aQRogOwG1HzKbGQIHJBKBLiKzTRKmLCMwMoaGYmDghyjiBgpSp21tokdiHOmVCRBNyBDRCst31Zif5UnNkJGARDAndSYXdATG0CaT4MHGMqWsRQScPbYAirEpuuVSezQlJpimlYOgQGQ112DCH0LSqCuA7_qa6G6JWQWYz513KMLKLQhVSA3BIDEhgQOButtMSI-72FQLuFAkUEMlNMTKogQERelVwRzVUQRUMZLXCpKAam-hFyAzEEVFdQtcgoheLKQEoETGhqzJgJAStJBYCATgRUQwc4q76Bgix74iDlYIOoKqm_V5XpupgIRExcheRIBCFQCFFRExt3856BOmalpgOL19wsQiB3R463J-16fLhHhucLDehiYCkpQbiWkVUOQbZDc5V1UDVaxUKdLYa2zYxNmAotWJkqWYIBmDuhwf76DCpjUXEtNSqCEiI6tOUd-ReYJ61jYnqVNebsZk1KYauS7UohZA4qOt2MzVtk4swoakTUZkqMamIqqhIbOK4zjGF-WzmZE2MfRPdnTFUNScSMWpaAy21gpkbiogD7ZYQaoaM01RU1QNxYCRQAwEzQldfDWNomuUwRmIlWm-GLBJDdHckmnKJHGtVACiq_VGj6u5AhCGwqWWrfds6gpiBo6kS4qWDvYaB3cEcwZiRMYA5EyEg7or4QMz4QB0M4LbD0Bj6rtQPoO5m7__w0z984aVvfvP5j33kQ2bV0VKI22l79ep7_-Xvf_naux569cUXLz18-eLDT_zw1Zcev3pxfbqe7y1Ot-WRJ999PltcnDfv3LwzI3z2o89-9FMfe_a5J85v373zxq0ffvf1tm3evn1n3JbHn37y8oX-I8889fC1q1uRP_zjP_rwY09-8tPP_emX__hP__BrZyfLmHzajMvlpuRysLe4cPHCY48-_vJPfrQ8vatW2rZZntxdLA6vPf54Xq_P7t8bz8-mqdQqlOKjTz3lVfaPFkhxdX5ipQJ6jPQzP_-F5cnq5u27iCG1fdWqom3XMBGYesmA5GJuzhysStMmAnRRLxUkey55NcT9ltvGHQKTTJOphRRItdaKrpqnszunHOH48nHYm2EbTdwiLa7uNbPm_OZ9GUZDt2opRVczMRAx810rNAAQ88Xjg5Obd8sDELDl7Xp17xaYiRRE326GveP9tp8h8-LoYHn_3E1W61VgdKhnZ-t2PmPgy-954mCvXd5bzefzEGKplRlvvX6rbKfUNdPZ-uze2zL5_dOzd73nGQa78dLrMaT3ffJnzu-8cXZ2Ppv305BR6OFHrzz_9e82Pa1O1k2c3z5dYxfk7N6sjVXKf_i_-aff-drzV9_95Juv36gJ_uav_Gz1MmzKT1679e73vfvPvvPdi93BZz75_jwVB3L0AB4ooIOjM5OboQMBGABRQPeuiW_eOaEuHC9aQgcFCgju4JAig6OowgPjGKgpMQGTmKACIO7Oxx1OwxFSZFFhJFUj3rEc0cyYQyQm8iZyirQ36_omNikk5i5yYgqETeRAKLWqea3V3B2xbWKMDIbuXlQn3fmHcLvdaUmkCGxK2W4nRDg8mO-nZjZv18U2WaYiY5WpZOKYx1pLSSGVImradE0VA0AK1KakxojujADY9e0wDkezxV7Chw4OxnHc7zo1Z8aYYi5VAAyx1NKl2McmV71596QEKMDjWCapuygOIPQxDmNm4qZL01SZcT90BqBmQLjou2GzAcbF0Wza1KZpxHS-mA_j0KUkprOuuXDcffD61VCNiShgMTU12NFfAWs1BWub2Me4-1GfrsYiOuayw5Uc7nUX5j27Hc4W7lBEBfxsKJwIkNqUmpiawEQh5zo5nGymogpMd-6fYyAD347S9O2Up6kWB4gBgyqrPfbuiw0yaG1SyMMQA4tIDHS417QhooGphoC7wnKtYoA7Zv8wTY40jFNIIWcRs1yrGYhq07ZqMo2CzJPUm3dPFXw5VCfs-6Yolqrm3nXdcrMFx6EUM2MEV2AGq3L5aD8QEeJqNUrAYhI5qLua7S96rZanoUn08IW9d1-7MC43Fy89tN4OZ-O0HiunIGIPHx3OUrxx9_RwvhDE-8vVeS7n41gAplqBebkdHMgRp1pjCgYwqav5waKdJq2ipbq5hzZq8bZt3es4FnBy4pq305A9BmTP6xzakNdT0yVisiroalOlSBgTh8bEYBRkDxRiwyredP3R0f69d5ZPPPX4er2a8sSR5oeHbd--_6mn3rr55kNXrkktH3nmfST-wxdffPXmLWxnhxcWD73r0je_8kK3SBevXnz_U4-1IT56_aqa__iFVw8vXZjtz_-z__J3q6AvUhWriuuhHF-9cnS8d3bv_mZ1zrE5Pjp-6oknmQ8fEdHF8b4BlFK8SNe2u0U5GCASxwZj1GHq-t6kGlqc70sVJHBTd3JHitHRkQBcATl2LbhLGZFJc5FhRDBCdkTVijFRCA2x1WICKSUH1zoxk6lKHqntmn42DWvmiJZP33x1_8rlQHx2vkYwAnVEoEAUgaJoAXM3ReKddUDyhOxSamxnxMERx_XZbO-wToUCAoKrNt0MHEXNTTil3cLa3HCXg1EnBDA3NY4BOKgqqMQYAYFiCDHtEsC15BCT7gJIyKCVADRnDgFSJ3l4QIgUAXBqW3MjZiJQQ-cAbkgIpVJABEAkcA8xqRkTyZjBq1dFROTg7rybSvqumOpADMSAqLWGwKgY9-Yq5hxDaLxUQHAk7BvZHcxui6PD0ML523diioCoVREd1cg89H0V2c010ZzdgcAMQt9ZLRwaYrKc2SA0XZGKyCBKQOQIHBBAzdjcpsKI5hZn-64WQ0TTaayx7a2WujxPbQcG3LVa6k47ABwwkElB3iX1HdyRoquQCak7ogMgB1MjcjCLbTJVqwIiZIAOoLjzxHoV4PjgwosIDKCKO7p_LkjRVMB238UQHNRgp5TFsDMA766DZr6bqoEbmIMqquIDSU5AR6JQx5ECYwjEsZnNRKqJhyZxEylGd3REybJ38ZiIm65v275Nbdv3bddyiFOZ-lnbdp1UaZo079syToaGYIWMUljstUABybe5EpGoiaroLvkMgKQAoj7VTMSiwikh0Y4oV_OkBBRYzIwM3PYP94njKLaZpuqCgF6VQ6Pm69XGwcVtbzYftlPXtiI1l2yqTZNms369HkNgA89TAUA1tR0MBLHkSkyxa6acx3HiEF09htgv-rZNVqooBObd_6ehY2QziSGWcVQxqYaMTAwARWvTRIyYi2-3xQkASA0gIiBtxmk9FUcMHBxptZkm0VWumyl3Xbc7dUqVtklVZGefW21HJiYnV-9iBAcmdoKtaKJQas2ihIRMbUjRjYmaxIAYAiM4MwGBiOnuVcC7iAUSk7nv3KtA6O6OZupIAcBREc2eePI92oV_9v_915_6-IdUHigsNiVvW3rhBz9RhU_-9Gcev_rYv_z__cmTj19fbe8fX7kyblY_-uHrr7_0ZgPxpRdf_M2__9svv_LqSy--9PzXXzxfDh_72LMf_7kPPnz9yksv_-jihcV6M16-cOnlt978yp98-eUfvpQofuf7z3_yuU_98PkfrtbLjz_7fo_N5YuXLZJ6NaL1-dnzz_-om_c_9dNfuPrwo3fefuv9H_7kdtq89vKrP3r--2W1FC11zP3e_Llf-vwbP36xaZvN6fmtN-9VzU994IPD_Xtu8Mgj73KlV956s9QK5kAm4ugWmAm5SjVwDkxxt4ExMHSkdm8PCctYCN1NrVqdcjdru3beznoAa5o29k0Zcs7VasEouYyn79w9u3vfpRJYh9SlSE7UJZ1yDHEat5YnEUWH0DZEEAKalGmzPb7y8Gs_esEBxyEzh7pj-4KaGDJuV-v18ozdtNre3mJYbQ-Pjpnj0eFhzsUdS51cK5KXzfn5_WUgnl-Yn967i65FpjwO8_2OkeZ7i9jNMcXZ0WJ7cnt5cmLg19_7xMvP_wWnliLKWEqu7__oh5__5l8My_XRQ0d1mz_7-Z_7-p9_7c4b73zis8-9_vKNvfn-r_69_9EL33vtfLUsm9Xjj1_57MfeP4169-Q8Ip6X_JXff_H_8L_8rbPlBkOAQIAeCMEN3BERDIiAEdyMMbh7iuHt--cC4dLBwhRMbdcUZqZADKbB0c0BCYHUTMHRyRx2S3P3Bw13fcCmQ0YEf2ClF7DAoUrt2s7AmhQa5hCwjTxrQhu5CRzJupTAtWsigDUh7JDz6kAxTlMhxIYDOCKTOijyVAUJpyqT-P31uMk1izl5ILh24WLEcOt0tZzqJhcMaTtmijFnVTFuglgdpopI05SZuZ2lO3dXSEAA6A6BMVDXNIBOYPttE8ndnNFSCIGiP1g-lLvjsBdT6hIYnA_j6WrQkM6HOo4TMLlqCBEJKUYVlaq5lBBjLdXRYgiGNOapIRZRd3CF-SKSw3o1Elk_2w28AImsTB999HqDxISiYqZZpYiYWd-1MfJ6LEzUplAmHbI4oiNVc3BH98uHe_MYAnFgIKbzzbge82aSdjar4k3b1lK6JppKFX_99v1RdLneFtHVZhpzdWCpulpvXGG13cbIXd94zYeLPgLOuzSftfMu7UjVu-fBpYN5RGBAZtyxZUvRqq7uUxEkJsLdEqCKb4dcRAwJA5nZdpuZOLXNWGQz1lwLEqw3WQ2mSXPOAGDmw5SrqAGIVgIIITQHXd5sj_fmFw7n56frPgVAKmpApKJ9147rzaxNRHDt0vGLb7z56Wee3E9xM20P9vsqlqsVcAfvYjhazE-X6x-_cW__oH_p5h0PPAFu1U7X24O9g7uny90DeLudpCozN31wpdU4zmdxtRlVzZH6vRYcpyKxjSoyjtlMEZUwAurmdBMRdCrzrpEx16m4OrnXMUPVECMwN12LEWUa9y8_nDfL0MSaM1F7-62bz378A_PZjJjres0htbP-8UceH5ZrjjRu1iL5Yx94_yj0p9_61lAgdZ0rntw-25_vbUs5unT4zqtv_e2_9otdxCb03_jm9z72yQ_82Y9-8vJLt7ujWW1xsy2QMDSztmtPl8s3X7l15dGHVuebJ5-6fu_N13l-7dFxtYz9niKCQTlf9XtzhwdNb3gw40JA11oRrOQyO7oUYyw1AxERxbaTmgFAxwGAkAMQMKG7I3LgYHUn2WUzie3MzGzKVZQDi0jaX7D7uB5Bs1ctIrtLuInWqaYmWZmm1YZm-5SS5BFN3SC2LREAE6ijG4HjLqkIAICBGQDB3RGJ2B0MvZsd5mmN7q5ukpECArl5ydnMUmohchmmSKTmJsIpmNRSa5zNmBPGNm-H0DBBUKsYkpYC6BCZgYHI1dEMGBlAiSA0oIg1OxAacL-AyKZGgGii6mlxlLebwOQGvguN7BYtoqHtEFFEAiOYA6GrOIAD7iJMO_yLAxmSE4EDuaG5B1Z0woCBbcpglWPjFNTN3frZbHt60h4e1SLkhmBSxBGgZCKwWpwDInsewd1F3NU9eGDfLKFpmBjMvWR3MiDVAqaogg4UyNwRUcoUiUwFkDC2SGwm6KpF4nwGhpa3gUCqh729OgyBdliJaOCkBoCEDCAAjjv9qu46ygiEvhPEqlpWZAapWioBgAkAeCCM6NXADJsAYshEEV0MSiU0FGUEU3cHdoeq3EQw8JIJnSKDE4eAAF51V1WmAMisVdjFSzE1lcrMgQMzuSm5c9NwSDEEU5VR3D2k0PQtGtYiFKibd3WoBxf2m9g0qU2R26aZao0pzuZzQA9Nk0JsYqy51KwhBDILTqenm-1Yzd0AiOKQs6uuSwYmRIxNQnAVHUoGJFGlyA5URc2salEDEQ8hTqUYUJy18743wk0ZV-tt2zd1nER1GMfNZsvMHBiJTC2FQMy11nEsgNT13fJ8wyGoaJ4mU1c1MzDArk85lxA4MI_jBIgxxdiEGJiJYyQEKKpNGxmxiaGKitp2OyHimKdIsYo6YC2SQghEIoKEAFCKUeBJSkxJHBzpbLXN1YYpi9imqCIgcFGvZg5k7hxiFVFVA4iJCQgIhqmWUh6Q_AGJUM3VPQKkEESrOtSqFCiA9akR9a3anbPldj12s-4BWxVRxQ2RESlQCOxuqgZIO1snAJqBP4CzAyGggYNev3rh0Yeu_eitN96-8fYw5PlsFlN89JGH__B3v7I6Oz26nD58_d3Pvv-R7_zkZef08nd__LM__4U7t05mB51ssznuH3br5fbwwoXP_exnXn_l1bunyz_7g29_5_kXqE3_8D_4DzPL_dN7L796Y3-216fw9BNPj-vV17_7rU8999Nf_sbXjg_23nj7Vi1T2-_Njo_Obt-exunTn_60A5iVWjOHMKy2d956o06TT7ltu-VKPvyZDzd9f_ONtxf7izJMqeuf-OAzeXX2xssvlqyGss7jJz71me__4Ad5yl5tduFwdeck9GkcpvnBPgUCQJGCSFZETXYniLla1dQ2hJyHbEXBzMHKOJSS1bJUTU23ePRSE1oXA_U6FjAJjmCgY81D3i7Xm9NV2WzLekSiFDi0sWlaCExuiC6lEKYrDz8ybldqFvrWkU2FCfauXIwUyljBAFTR3Uq1mpfLc0Qbx-ni1UtIoV_sIfPhpSvb89Nm3o_LFYKJSJ1KSMkAwUEmkam4w-xg7_TeqYNRCJvllql536d--q3nv8ttQ0Spa-tUqN3_K7_02W997bsK8L5Pf8gzPvToc_dvv3LQN__R__YfvPjtFw-Pj6rRQw9f-8nz390O42_93S9eaPenXO7fP-0uzP_Zf_2V__m__1c4sNhOgUPgwAhg0MTg4khOiGpGHAEgcLh1tvRIlw7m4AYKHCn8Jbl_R_fZ1pIZzI09qGN1iSGJKYBXcwRyQuRdpRgDIwBkM-bdZ3AgRmaKTH3bsGnfhL6NDcGcQ8PkqilxAIiRmxhcIavmWgGpGpiZiLSpaWNCB0Cs7tV9rKXWihzvnW-UeDXkKjpN-fhgnoi22-mFG3e2uW5GGXIxhDFXqUYYx1yruCGYu4KlJkSKkXmzHdrYbEt2hchEiBxCbPAghkuL-X7fllLavgkcRC2GKGZd4FnXD0OhwCer7XaqGWEsAghTyX3b5FyblBh2uDUexzHEAIAGGGJDRE1gdQiBZKrdXq8V0L3rkhZlDDGEXHKwMoP8iXc_tgNIOPlmO2TxmEIIIVLI6mOVyNSnVM3EfBQVB0MityaFPlIfeX_emQshDVm2VSczNaxq98_O9xadiQWmanB_mFZTXW3Gbc6nZ2uMvFkPVg0FVc1IZ20DqqhyfLjXM3RNPNibuxtxyDk7-MFBPwsM6kgotRpAFVU3cTcDc6gm7sCBRe18uXV3QEyztB3KWGpq0o4iN5V6vh5X2zGGtBrGLGU1jo5GnFxUtFLgzTgu-h6QAhGJtU0gsMv7ixRTVR02g5hzCMM0YtEUmQgTeZvg0l739LVLAWCSwoQM8Nb9UxEMgS4dHESz02U-urwnkWZ9V2K4ee_sZDVtXKdS2qYZRGq1u_dX_Xy22k5dO797ehZT2ow5lyJVwBWJnRHMGbzWutlOhF6nUkuxWlv0qFg3U7_fBeCA3s2bMmUV7fvWDS5fu7K8ex9KAXerRUqdhu3xQ9eU7ej4cL7Ym6Zyeu_-my-_-cynnmliFyJOU37phR_O9xfHB_uf_9Qz_-1__0c3bt3TJm4207xt2PD2nSWSHh3s3b1x66_83M9EwLPVejZvRyu_9z98Yz2UxfWjV1-4RaCEzf7lYwa9f-fe_GDGqbl25eJwd_3yd3_A1h2GkJrFYTEHs7RY1M0qtt202gChq0ougGCqoA-yLiXnZr5I7XzcbhAgcgOBwAyRYgw1ZzADAM0VQ-QmOOwauhBTLEPmxZ65Sy3NwUJqraPM9g9T4poHQmu6dlrn2eEBNykPI6FDVbC8uf1mtz9r-wNK_ZSHCGCOJpr61kq2XCgGr5DmeyrFfSfxAQyMxCKT5hKaEGNnVkMgKYKOoW0AIDRdyecOHFPDbVumMcZWRUB1l400qcicZgvRaqDoLOaxaThwrQUQQkwq1nSNimqpxKZVKcbUhDJlQtuNCxHZVdFJxuwMqY0YGzN3FSaworBr75eKqTMVDsF3APtakQLFBK4YWHNFcOAAxI5IISI4ihKCijtiSB0gokhABAdqYx1yjAlNQ4yr8_O27bEWJpaSidxzod0yWM0jgmJKiWp1re7AXXJxBHZBDoQmVjXtHWgtgYBM0czMHByIwYFEYpMAjNseiEPaVbQrhmRgKJlMxRBTcHCfcuAIQJySWYUdaN3Eq4a-NVFwQUdVdQeMCYjQlAACY5kyACIImu9GVeAIBhzDbpPwlzJLAHRUhSJgvrs9E6KVQiGRZMgFAYEJFMGBiNAgMpiUMG-tQupam0bPlQKCYWoaRDK33WFAIaJ7ahqZMpr28_muIZf6xEwm1vRdN5_N256IHWh_PgME5ND1HZAjctM0IIoGqiWlpknh4GCPmUupaooUdgt3ADBHVUsxuoOKmeNmOxCzmtWqqWmkuqoi-5grBlDzlGKuAkT7ewsrpuCbzaAqXdfKJAJYq4ioqbcp5lJ3xT5XXa-2KYX946NhMyFirWXcThRYxUMI6r5_Yaa1SoGAoNUMnBn35zOrtenaWduJ2jBljMHdYgjiXqVuxwmJmAkBqpkjEFlk2kWcs6gbqNlOz1aKAQIH3kwyiW1zabqmqFdTdaiq1aDU2rSNg4fE6Gj-AHFuiFMWEdm1RsARHKdaMJCpBYqBeCyVOKi7GzBiaOJQ8vlqzNW3BmeT3DqfFouGmMxthxRiwMjoDggOAIRAhADATERspoBATOBOTrVI2zRN6L70zX_3v_o__ee__Zu_YoAo9ec_8cH__A_-eFyezy5d-dWf-qn_8-_8Ny351ccevfnmG_3-_PXX375-9ejb33x-HMe7N-9euXjpxus3bt54-_47d5tF-u2__kWe94cXL9mk3FzfvPPGzXdu1Cm_c-ftqrBZnv_MF37h61_9yulm2VK8_c7tk7sn07CppfZNF5k2wwrcqGmW9--_9fabhEKAq2HsZ_MnP_ahsh1O7p4eXTlum6QETWpf_t4Pzk9OUIkBAXx1dv4rv_Yb3_2Lb682G8s2OzoYp2x1alJTtmPTthxiqcVAm7Y3cxdD2iEpKTSxFm33F808uVYXMbeYKDABmxUpq9FEmi7NDub9rC0CasQB-r5ru9YB47xrQkx96zJOQ-a22b90wUzrNJKZqoa22T-c37_5ToiRuyRFQMStdntHpThbZULENpcJAbiJoF5LNannp_fPT8_Ube9wHz0QUYrzOk611IAokocxx6b73C_-Qs55tphplbO7dymkYZp2B19o-MarLx0eHraz-Wa9HNfroZQv_MJnf_9f_OvtkC9evTQsx7h_9Por3y95NW3Gd1-98sS7rnFPd86W6_Xm1ptvbJZnf-c3_prniRBfv7P846995wMPX_nMp5-VKkbEDO5O4JF5F-DB3arUjCgAeGS6eW-FlI725wyo5hgY3B4sl3fwYzUEDM5ZXNyJ0IEY0N0ZAIl2L9uApAaBiADNEIlElAMRBVAl5xgosO937cGsaxPu9U0bOAUMzK5ChDFyikFUq1QMvBmqqKs5EkbExOzgw5S3tU5Vt9s8ZDns2_vbmt0m0VwV3MZhe3F_sc5y--R8LFoNIGAM4WS5ISR3k-AGiGAQyczrZLNZS-DVDAKpgpr6roHg8vCl48OuuXa8H2Ncboecp5BiAIgxVqkhpFJ1KpUjD7kIeCUsRRChmjJ7imGqNY9TbFITQq7VEYuYOUQOhGDFcq3oPp_1w2bY2-vzmJvARWsTSKsEAmA7svrxZ97jKoRoaGqu4pGDq6YYh1LFlADbFIuauFVzA5qkdDEx2rWjvYO-QzMEH4tUh6xWqonCVMq2SEph2ExMtJ7KNtflOGUxSnEYsoqrQYAwThMSE0EgQNSnHrs8bsaAeLDXR2YEXK9Hd2eiRdd69cBUphIDm3uIoZoboIiqm5qa2bxpl0Mu1YComocUzs62TFgUpOp6PS7Xw_lqW9SW63Gqcna-AQAKoQ_ku1lnjCIWEOazJhBLHg_2Z1cODmZNE1NYb4az5UaJh5LPz1dtEw735k3k44P9RPqx9z4akJkxtWmqfvP2aQVericd8vULC-Z0b7MOAW-fTvNZ--rJ6ta99eCmu0gaITfprZMzRAekponDME1FItP5-bZoZXdRG2sZx6JZ92bp_HRpYG7q5oCg01S3EweWkt28v7iow1Q3hRkRaRynhml57zwyc4o6Te5-_anHLly6TNTM9w8i49279xcHe-PqFBSPLl2W6jdefTVLcckXLl98-OFHf_TCi6d3zwvQZjsc7B3MHzrYroez8_WFKwevv_LKxeP9n3vu07XWr371Lx5-5Pob926_8tqdzSCTVfYMiv3h_qJrtveX2-X64rVLMcZZO9veP7nzxqvcHj0ESNvlcnH5qhuKmuaJCAkN3GqunJhCcEIwDzF2e51uttT0HBqT4kVEctu24GCqgEiBkQhdXNVzje0MiNBMy4RmqKIq3C2QOd99pz04DtzWMvSzBaqV7USISOyxM0Ju2KQwoJRCHJjAKHVHl9uuG7dbBjLRHZXbRL1WA0v9bCdf5t2ynklrJfRA7G5AEd211ICQp4kDcWrcLaZOSgECrRK6ueSBEREJzLgJRAiAse_6g_mUpzKM_XxmWjgmdLWqgNjt7ecxU2xiamUYiMFViBqKneQR0blJDixF2osXd_sKAw_zxU7YjipWlNqIQO7GgTEwB7JaZczcBHQIMZqagSEg7ZTAFLhtzS2EALXu1BnY9xQYKch6GyObQNw7dMloGvt-dxpPZ-cRFFXMzM05RavKMWiF0LauSug6FGYAYNoRxcAJKcWmbDdulvoO3GyaCNGLUAwUWafKzOTktRCjA3uIOyFtCBEBDQFVZNyGNAMmE8EqCEDEzGhlAmBTQwQrW47tAwHvlAkMAJ3JRcENSnERjsFKZiZXAwUSQXcQBURXd0RE5IagOoiiCIo6OERAByQid0bEWgOy7lIEDwJAAGYEqNU4BRfyMgZAyxIi16yhiWBIEetUu65T0YjMkacxhxi7-Z67lcnaNnEIqe2brj082AvEiNz2TWDiGBDItAAgAzbMwWkq4_7eHhK0MXFkirSYzcwtdQ1gGLeDOVXV1LamYk5TLmYWQywi6k4YDFWqSinmVsxq9RjDOGVg6rvUdm2tam7VxA1yNXd399X5OoYIwTlEVW2bruYyDONmPfQHCzU10WnKtQjH0HUzJ3CArm1dtQzVzTiwqQFSinE7jLP5whw24zgOU2oTEXJgE6tVpao7PCABmjUx5qKuHgO3TVTVqVZCENUhS9s3U64BgwKK25QrBhpEDWmYChM7QuiiAw1jQWZHqGJi1qREABzCMOWUork7EDKoStemHSN9py91cwws6g5YVZAgcZxEt1UFuKgpwP1VPj7cy1NJjEy4Uy9VUyNLgQCRQFOMRIAOO0WmqxGjoyMCuPaz9NTTT__z_-p3f_9P_uRv_NVfZKLa0Ac-8P6vfv27Z3dP7m_kZ3_6s1AGXY8vvvb63_jiX__Ys0-P52d5WH3o6aduvfNOF-WFH_xofXb_V3_7b37gqSfWw-bJpz7wo-_-4K03X37h-W8fXjyScbp793YMEQJHDmfT2ec__zMv_PD7F_Yvbobx4sWjaw8__J73vPfJpz7w4x98p-m7h66_u4H0wve-u10vDy9cnsaxbecXr1-e1ksVv_LI5eDkxOe3765O7i9Pzt_71NN1M4W-NROdys_92l97_hvPbzZLzfboE-_aLAciA7Q2xrzZzPYWse2mUkyEYhP7thYl81rERGIbEVDGwjGAmll19TJUr4IPmKow5XG7mUS8PzhsFmlxtJenqTneVy-11HG9nbbDbuyKRGUYDdGLEoM7Xrxy9dbLr8auBcQ6qVVxAGbcrofrz77LNlNFF_Cm72JgTsnN0dHFCAFFZRpXJyeb9XkthRfz2MX5hYsQcb7YW6-HWR_fePEVqWUoebZYINFUyvzoQFRrkXY23zs6smph1k3rbZPCe9_7_huvvzoM097xARCGtjOnYb0EKduzzd__937jYN6fnt9Mi-PvfeeH2_PT7Xb8O7_2BSmZZvPf-9q3b75w-z_5R782Ta7ohA6ws1buVipKCKrGBMjM6CnyzbvnHuj4oCUAFTe0QMgEgdnEzM3sgey-mgIg7VQWuyTRDuXhQMSOTkQ7DJoqGCghhBAMHYFiwJi4a_j4aN4gMfmsTbMmNswAIFKZkQgDk7mXKkMVRB6rqIO4iMqi71piU7i_3mIIYjCWOlaZd_Hm-VAcV2MJjF0XT-6uFvv9a2_fwZjOt9kJzeH8bONErm5mw1BCDIi4iKyOWmwx69x9lIIhiEoeCzexmiyapuThsYsXDuddQjxdrfuuiUAhpB0WiXkX8DQRNeLVMCJxVWemlBJEuv74wbRScEttJIeaRdCruZQaQtilexIF1UrI7jprmgA0lVyqaZ2AKTEfHS5-5iMfOEgtmjdNGqZxKFXdmN1VmcOUZTNmJmpSEtVcZMh1KjVwYoaIeuXwAKuaaNulXG0Uvz-MpVqM4XQzWcJAqEVDjOfrfLKZ7pxuTs-37V73zq37iK4G4zDOFq2ZROYmxiaGS_vzUvTqxcNAHGNA8M12JCQK3jRNCqRFdu__qi5uxXwapiwVQ1CDvm22U63mEJgDbbOYuRoAQYiUc90MOQOMWpBoO-btOJkBh4iIwzSlpg2R1euib-Z9O591UiYEu3xh_2jee9X1kM9XgxOWoioeENo2MlsdxlkXn77-UMuMYl0bleB0tb2_zU6YVT73gYdd4Se3l_fW0xnU-2N-82R573xzLkUB2iatltsrB3Mp29OhuIOp9KlpurRZrctUimq7aGrOfdec3D69cPmYmJtIwzBOeRK10EYZJx0nDhHAZJgYYt1kMs_b0YuJysHVS6u7p0eHhztqWS3TYnHQ7B_WKYP7ZnliIvtHF_I03Xz1RorpyiMPTettE8Nyc_7Msx8e8vKZDz576879s_VmfnysaJtpc-PVG9tpil2YzXqt-qu_8rOPXDhi9W-98MLVKxf-9b_5802p58M2q6h4Nbx87ZG6PTu9ezY7XkiVvdk-o936yZt1eca0uOzIFOOUc9o_EHVg0LG0fZKqjpSa5EUpRMs1ds14tjQVy0NzcMghjSWbuYvM9o6tZjMhZiniqkTo4HUaue1j29dpAHd0AwAMMTSzdn9v2mxSm9pZv11v-sVRGQcziX2SPFFIAKSuWkoKAQzcdFquur19bpvzO-cUfXfItosD2A16HaxqM-8AqEpVsxhTbBpykDLqVGLo3EG0UgxMXqaCgF2_cPdSMqJx07hoSI2qMgUEc3UHdxVVcMD-8KjWaprJWascXnp32d4xD2Ae5vOcq6uHGLxkBkVC4sZqxRDrWHbq3rwdZw8_ZLnUMYOH7vh4Wq85sKtyjKBCgeowhdTlUgjRVZHADYACxaAO4IZgYOBAFsMDPltVAnBVoOCxASd0I0AAcxVOAc21SNibUWTS4uNIO4A0BwfXcfxLEgSZGQKQaCBwVQACDmDqjiFGkwyqFFqOQUplREY3Ud_BJByInQFdiyrEC_tejGJqmnbcbtKsK5sNicVuZhjMKqq5ORi4u-SJQ3IAArdcQ9M5A5jCVGNgUICudXFmgFpAATDuGknAwcUQzHJlJm6jjBPF6KLgAIxgBrkGcBBFQ3RCxt1bgnb9KwCrlULcYQGZaPcG4DbqmLFkECW10CTJ2vaNKxCCTqWbzQghpeQizBwCB2JXaWJo2tT1HXFomsRAbdMCWtc0WmtKARDUQUp19yZFU2FmYibmyARAZSxHi0YUUD21seYi7sU8F3EkbikXUYBpyuNUY5tUPZcy5UoEgXEz5KYNRGzuqjqfz8btxG2z2Ww1CwauRWKg5emaiKTWbrY3bNZd25o7oo3T1LYRgctUOYacMzK083aaphAQHGbzNG5Lnmq_16kDkUtVRExd44xmNowlBK5TJcdSdTZrS5Uq0jQxj6XtUhdDrtXEUqJFn8ZBFKiKORgTG0EIIYRoDmMupdpUCxICBXNDxL5txqLENOaqO08vcS6CRDFFV3ewqlprUQcF4xiIUMGRg5rN-kbEnKCairkHADet1jYMDqoAiApg7iGQg0WArg2MGJx2lJUGcN6FJlBEYgJ44A92RCB2JgQgRGdAkxr7_vZbbz3__R--dfPmFz7zWTRdzOc__N4Pbt6-eXZyb31-fjw_KFqPji_-4Dtf_e53vq_uH_rccz_9C7_40gsvZcenP_Khh9_z3qBWO3vpx6996Q9-7623bq3ON8M0feTjn_32N79--doVhbAZapov3nrtjU9_5gt333j93tlZn8L1dz1GRLUO79x89dqjj4_b9Wsv_vj2zbe6Wffhj360LDfrzXSwf3Dh2kMPP_bo4-97P5K9-qOX7956-523T5jCL_4Hf-tHX_uL1bZ0bQwd51qe-6nPvfP27Ru3brg7glVRQJ1y8VL39vdP7t6PbdfNFsQRA47rAjGElLiJAECEJlV2Kxk1DqHmOrt6EIC261FVtAoGSin0x4tpva3jlLdbzXLh8uHyzrmr7B3tdwcHzWKWYmzm8zJObZuk1s35-PiHPnDntdcpcuyaPAkzeqlqHpoo620_6-6-eVcY0LDtuA5ZRSmmON8HZKCY2p5jdANT0VrHs7OyHVanJwBYRI4vXugvXdyb711_97vEaBgnwFDzZFJO37kTup4AtpthtTwt22WZJhF8-uOfOLn5FjSx6Zthq4apXeyfn9yZz_pSpy987hNXLu9_9avfeOTJJ1__yWvj9uShvfnnf_rzt0-3N27f-fM_f_FvffG5q5cfEvSddMdcCB7waREBAcCdicExRL5zsp6MrhzOAaCKcqRAkIh3UyF3VHAHqAamXtUBw-6zXWwXTnfcyQF2MGh3xgct4UBMDG7KyEjepOBmR3t9G2JCmrWx72LHBIBaKxISc5XSpQSA22lyQHMqVaspIbrp0aKPFIrp_c0ggEA85mKOo9jd9TRUGUqpoqqQWiaE1bo4EzRxvR6ZUcQZSc0RkBLnMSdmMVA1AAvBZ01TRXdlubaJDH7twlEIMK3OPv2B98w43Ts7J7MYed514ODgwzSNIqenK0dQADcbi6w2277rmEPOEoGixXmblsvNVLRvm4uH-8v1lgMzB3iwdYSwi78CjqUs5j24Y-Q7wzv7YR4CHxwsCOm5x643wCnxlHOWbA6EXFWZ2QzFbJjywd5M1cx1OeSpFsfgCHmarhweHPddF7mKIsN2yvdX03rMRf1or3v57bNhHM387GTddO16KoPq27fPsoiglVyr2XYaQwzjMBogEzRNamNzulo_8ciVrmsYfbMdt9sNRObA0zjusl4EHgKVrEiYi6yHaSwVkAAJdnJ4RwEoRaWW082YEjmiOSyH6XS5pTYNWc5X24eP9u8shyFnM5svuilPQMjISOhgB4s5iMYQRMqiaw9mzSw2taiYhNgMeWr6frldNzE0KV6-cHg8ax-7euWhw70uxW4WS6n375-fbqdi3jZpkHp8dPzKrfW97cr6NCqfrof1WJfTlLU083aqef9g7_5yc_N0pSKU0nq1uXCwyFVP7p3HNhBxKdXH8eT-KSHkMh0fX9iut2au7DULJ6qb0URAgWNAd50kBK7bMabkLlZcSyan2DbDODV9O66GxfHhvTdvENmNH788n_fb7Xj4yKVhuSKpB8cH-0cXz07uHh9f2GzXxxcPTCV6k8mb2eLGW-8cP3zFBbqYtObHf_pDw-17bvjzn_lEEH_r1q1xHIax_OTGrfNhKmiTAgY4vnBxdXL79N557NLicL8MY9elcr7Z3rzVeeZweC10LSG4SHN8ScEdpJ6vYpeQsEyZEKRIO-9jYDcFFyRwKeNqPTt6yAWYXaeVq-LODUGIYO6oVULX0E4RV0toO6_qpkwAbhQTc2SI42a5uHilbdthdZ4We9PJfdNaN9tmtghdDw5aMjKG1NRcAL1sNh5ms-PjEBnV3IlTrONIIRAYqkGIGMKDNrC770RaVncz5tjN1LSMU-x7BlNxA6XQMAd3KOOU-j4gmZmKhMCuVauAa2g65LBermPbA5KVCV20bI8eemrY3EMKopVCtF1QysGkeq2x7XbzR2KWPHA746aVUpCRAwcKaqAmVgtUATXTio4cyAm5CeY7TtHIBBwbD0SEsl0TMwKZW5i1Zm5F2IxUuWkNHJoZgZGDl90HbIIYdCzuQBEtV5sy5OJZMDaYomUhMLfKEJQQiQAMizIzqCAH5BCIoCqlxktBUHJ0RGIyEa0lxsbMgWCnkNQpMzNASBcPh_MBA1jNgQKmBKo2jkDsTetadBhD0xjIrpLrxBwZxNgRgI3IaoEsgdFVMUR3syrEAU0AjNARXMzBhM2JEZAV0Q0x7NJECgwwVXAlph3IhZgAAKoE4geVXyIEcgAOJEUIAHfaByZXY0Qy2xkQEYlwhyUAFU1NE4iYScQJqeliisnNOYZuviAO4D6bzUSEY3D3JgR0ELHUpDxmQCi1cAiIBIDcBTJgx1p2130jZkQoWVIXi3uu6kBTrkRcctmOZSq5qouam1bVsuOoKIhaDKlm4RgcMbYJCKc8jcMUUzKzMhU3qGoihQKbOZF3qa1ZVGGz3XZ92m2BpVSpFnaokKzzRQ8GqjqNhZkx0HY1uDsRUoyuRkzTmKs4Macm5lz6eTcOYykaYywqTByIqlqpmpqIAu6009w5OBOJeZNijKHmquZmbgHWuUZmREDAGINUOVo0q81kBkWkiuvOpQHQxTCM2dyQuKpV0SpqbghIAGIWmd28ui83W1EDA6lqaiK7IjnAjkwF6ACBkZxcZN4mqxKIOFAgCMS4C2EAmlYECDEEpkBIhGGHz0Ig8EAU2H_q85_4F__d__D6GzcvXjl8_5NPylg--Owzf_hn39quzrqG9_ePrz72rh88_61ZM8NIv_Ibv9w3B0UssB1fuHj77q3vfu1bN9-48foPXrl_83YXmybGCxcur5ZnN--dzvoeoFy49ti4zav1-mj_4M7923_z7_7ml37v9xzhrTdef-Xll958_XUwcMNh2FSR9z_73qODgxu33rj7zvLy9Uu__Ld-6c6t-1__gz_-1te_9toPf3J64952Nf2D_-M_shJvvPza8YX53_-Hf_cbf_rnTDRM04c_8tE8ja-9_mYINK02Fy4dnZ-tVNRN1fJib2-5XDZtG1JCTt3-ATC4eZkmDqQmVsXUyB3MwSClgCFxxDTrYtMgACeWsWpWNHWAst2mthm2m9g0yCnGJoQkZqVMboIIpqKjvuujH9jcurXdbGPX9LOFqdVxi-ZI3CxmKbWX3vWuabtxdBBtZp2JuaoipnkfLh4xhXEzpaYDdGb2atxGmwozaJ50GFZn55uzcwG48847q_OzPGYGC00YN-Pe8aW2aadxa1L2j_ZRLXD3sV_42Ze-_Y3z1TCVcvXJJzbL3BzsP_q-Z-69-UpEPtybfe4znzzsFu-6dvHe2dan8vKLr_zt3_zrj1y7_sqrr5729fVv3f3H_9EX14MBurlFJgKMxG7u4Exo7hyDm8UQ7pwvJ7Srh7PdHy4xcADy3ULUnYCRipogFlExI2Y1ISCDnfgGABEJCPBBrA2cd8khBNjpwoCYoYmxb2mva-eJ-0SJmRlDYHfIpZRaHCAwzdqW3KtKVlOAQDxV3fXEUuD9tlP18zHfPFmNuQggETQpVtVbJ6vqkHMh5NV6Q0RHe7OpyCQaE1l1ABA1dWvaaE6iHgJh2DV8qGZFxH7eAKBIBSAKKaCvlqvq9qmPPP3uCwe1TMNmbWQIfrh3UKoy4_31xgCB2RE2w9TN0pRlymIITdeiuIuG4PO2XY0TEdVa9rtmO5XlZui7lKeqqoAeYtzxwgydiVKIYipjvbR_ONWSYkwNf_hdV6I5oI7jBAbLWgIFND-c91O1UmtW69qkWZBpuc2pbSZRVYspXDmY7XcxIJYi4prNbp6uFWwYVJO_-Ma9LLUiDJvxbDVm0XUpb92678Tr9TiNeRynHXI5dIlTZGIODGBd4oN51wRywNVqBe65SGTcbse9eb83b2qRFMgcTH07lmqGHMaS2xRTTGZWiyDRWKVtmu1YkAjA756uh1ymall0vRmr--mYxURUx1yOLizGTW1T6mfJEcdxunz5yKsGAmY_PuivHh9HYlPFlIapiENMXSnTYj5vCWYRO8Kn3_0wibQJHWG5He-fDetqb5-t1tvtlcODk_PNzTu3N9Wm4merIZe6GcZhHCOzZKWqsyatz5bTdmr22tT1CahLYbncYiJAH6ahaWMtsqNUuwE4LBb9arVq-jSu1zZODDRtRyDiFFyNws5tUVXr7nFYt1NKCRlrLcRet1m26xZxe7Zu561ORQxmFw_u3biNuTz2xHtv3bzRxuSgWu18eXb92tXI8Uff-8HZ2WZ2tD-uVuPZ0pz2DvtmdDN_5n3v-dBj19X8S1_59jPPPPaHf_bdk-10Pgx3T5fdbN7N-_XJSTvrN9Ow2FsYybSsx9eu0XZ1_uorMQCnC9cXF44tT5gCIPQXrrkpBWRCq9ov5qIF1BghzTqdplpqSq1pRcJcxnY-k6n2F65KHkwFkVSFmXH3sSIKRG5Qa0FiME9tMhFw0DKlWdf2ew66PjtjTg5sovOLl8rmXMVUJgQPbV-1mCj4LhKjiD6tToDt-NJlnu2t12tGtKo7ERiAlSmnfu7gsWnKduTALgZmXisSmdWmPyDEOg6IzOhq7uaxaXbCXckDODAlZFcTrx4io0Etk9VMgct23L_yECOUYUvMJa-7xVGdJgwR0EHdADkySsUQbNwCAoXAkRypThPG2O7NJRcHIMDYtqGZq2QCd63MqKXsqu4QGjCMTbCcCayWyt3MzYiDSyHcsRPZAXYNLauV0CE12DRMKTStq8TIZRwxNc7kkjVr6CKaQK0xolt1CCGAlAxiCMiJdFs4NlDETcCcKAAghgQqgYg4kCuop9nCzVyF3RnJdmlLRHcDMQ4kU4HQPvjBioIjUIhtK8PaHambybhlRDRDQB0zIjsFMCM0EMfAEBGkkFQyQSerxXbVb3KfRjTAyLVURGA1MgAzcIcmeFXYvUNFAQBUyMGlIoJWBQQ22pnoAJGQbBccMgcErxo5gSozYqCd5oQM0BzMmQMhuRoCWq0xJgxohuQeEhFw7FuVmpomtl2TuGlaFAtM6kYOMUY1CRyrmJPvRJgIOJ_PpixIwUV3yjkzACI3VDFswljqZlOAfKqFCHum89VmypUD5ZxDYstaakXRgOSRylTa1ACRmJpDaNI4ZQi8Xo0cA0IAgGmcZKdOU9ht1UMTS64qguqxa8tYPbBWAYPYpZK17XsgHIcJdp10ACkVkVSdY0IiFSEmkRoipUAqMuu687P1ziJUxBSgaZJUKyLIFEMgIlEBomEaQyQFcJOUGkLIVcwdCIoqMyFi36asam6xbbaTDLli4KFMIURVbZqUpQqoOCQKw1Tarqmq2zqlQADQNHFVpoY5pihiy2kMSO7gDABoO26AQ-RY5AHvKRLPG65ifcfmCO5NoEi7Jgk5OiECovsucUG7CEQKHBAYAdgQQSdp5vzC91-6fe_0a1_7zs__wmcP5odWx1_5_E996St_th3Xm2H8zre_e_3dT04mpyd3v_HV767O3_nWV7_2gz__-qsv_eT09kkKgZybJs0Ws37e3js5CbENkff394bt5rHH3_v5z_3t1LZmw96FvS_-tV_9yh__m0cef-ruzZt7h0fbs_Or73q45Jzrtp0v6jB64Fz9PR_4yM___d_qOf7z__q_e_VHLxah93_kA08_875_73_3jz7_8z_7J__8d5fr6Xivv3bp-N7tu3_z13_j5Hx55-6dK1euv-d9T3_ja1-TKl5rmPW5VANFMC3VVMB12qy3w5i6OURKzXy2OOwPj12qGogYJN4x-zkFB7CcSUGyuFnNYmptPwtdnFabPGzn-7NpmpDihcvX9o6ON8N2u10P08hqbdcWKWU9Xf_QB5c3bozroWlbd0BikeK1hiZy08QmTLl2835zvqIAbqbis4ODvF3iNB489JBXr2MOaASu6pFTt7cXu7mWjGrgTjs8Afo0br1WAAMzdtVcCNnBl2enoNZ0adiuzcP1J5_4yfPfy9PUHeyDIrcpV33y2fe8_K1vBmSQsUi5dDQ_2FvsHx1dvHjp93733y6Xy9_6B7_1zpv3_-gb396u5G_9tc_0s4VVQSYH3Y0czHa8f99llwGBAO6vBpBw6WgO7qZOkXYFFaa4ey6LmYoiwm7bunMImu86wbiDfTz4cn9QYkFmJkcn5t1Mz1SayE0TGqJFE-dt41q7JsCuH-wACIGJEdrURCJxL1UFwACaphlL3SFBZm0zbzpAuLscjSkrEPJUJaUwjdWZ8q7uhZCYXBXAVGC1zaFpjxYtAY6jqpqBEzECOCIG2nW7CAARL-wtiou57c1muU5H87mZ7e-1z145XqT2nbv3r1w6uHVn2fTpeG8fELdjyaLKfL7JVfVkuSkii3kzlTpUnUSllhRiJEakWqWquHmMIUVeDiMiuvqOl0JMhFBVFbxpU9-1yLRdrRezXlz6lhnrxx97V8PIEQH95Hybmq7vWyJOTOuhFlMg6poIBsCwqTuqpqYUxpLfdbzXh6SSq-lyNW5F15OeLlfi9M7Z9t5qXdDu3l2L4jtnp4J08_bpdhjNvIiUUtqmqVLbNhISEqUQEKDr06X9RWKct12tOUVqZ52qtClILV2bIpCKGYCqOkJWNYcquxg8EMFmyuZQ1Iax-l_2xNuAN26fEeJkXk1z1e12Eq1i6ADDMLZN26WQUhq3BdEi4P6ia5hMpv29_rHLl_bnMwBYbQdFQGJOUWp10ysX969e2JtR84En30UIboLgp2fr5SbvHx1cOVq8-_LB09cuXzuYH8znTz58YX_WDsvNYq9rZ7jc5qff_dDDh_3lve4Tj1zYFLl9smnaOOu6Mmkbyczv3z8rtY45E_M4jXUsiDAN237Wi9vVhy7dvnNvvdnkYZJt8SpIaGqxY6kVnLQWy1mKQQh5yP2irUUJA4q6iJYSUjDgpt-TOnRtCym07WyzWnUp7R0eg055GmPft6m_f7r8-Kc-9KU__GbbxGvPPLo-Xd987c1m0WUZ9vYPcy3H_eLXf-6npu1YVG_fuPPTn3n6T779Ss45k2fJKUYoElKYahmztG1sm04M8jDefP6HEZ2p4e7qkyIaY6MlT-vtweVrIjiNGcViTHWamGMdxgBqaqFriEiGgZsEaprl6PEnV7fvcPSmXaiLaQkUCHfXGiAwYDDVNOsRSEUACZms1p1V0CC180OTAlBNbBi2bthfvFxX52hWS-kvXkBicIwNWxEHl1JiAKiFOIX5wWZ5hmAEQUsFFTcwESKs4qlrwBQAtWRqGi_FXUUqBo6xBUJVRSYwR3N3B3OODZm7CXWd5Jr6HogkZ0JAE2IKiIHZzUNIyLFsNg5gZsiUh6nt-7i3J1Xa2dxq2dWI0dSlAAZezCSPQFCnGg-OLWcUmYbt_Oo1plin9a5HgUS74WXsWqZgqlrLTvPCTePFEF13V1JGTC2GQOauDqqhaQHQFJujQy0ieSQERmYABUypJcKm6SVnzyUgo5qpUUMgqrlSIAfHGEMkqEJMaGZaiNg4esnoSKEDK1CrIXIKqOK1qhkicd96VTR_MDVP7BBi3zugTJXAmr0FuOfluRNz38u4SUicEtSCWoEodMmLoDsWQyZjYgXSyjvqJSCnZOKEDrWCAjfJVdmx4WBFCQ0MebawkgmZUyAiL8pIOzkXBzTxZr6n0-5dTrkWAAxEKkocYtOAOZuDGZhzjGhOAJALmQEhh4SqyEmltE1iwHY2HzdTbGLbtRRCbJNMlRz6WZvaNobQNIEQ2DHE4ACIZOahaXLJ9OAeye2sc1N30VqRaNbPdw9JABOttbqIAqMhjqWEGLZjUXA1JIZhNXZdK1WkVlRQFWQMHKqoAylY1zeuuksyqEhqmlqLq-ZcEIJ7TU0kYlCnQLVUM3dwUw8taxF0V6uxax40wKS6GceAjnUqDqTujhAa2jVnqlQKCQLmMTdtU9WZAyJQ4CKS2tgkrqpmEGOopbi7E6obhx3mFdtZGxGrmjtQDOKGQMTUNk0pYgbMpG4GRoFLEY4MDoy8SwRxDCkkcyNAA0CCxEROIcS2DWWU1LeMvh0LEOVSIERNINUJaJqKI6oR4u6GpEhoDmMeby-nELiqLPqGYFcrBgRABA47Qjo4OPpuaPqAvI4EjujmtU6_-Fc_9ydf-ur5_dPf_-Mv__LP_ez-vF_p8NmPfPD_9ju_u7l9J0-bO6-8duP11-t2aJHe_PFrWoemmZu6OfaHR-EwhRTKlKeyrQU--JHnfvTiT5772Z-5d_ekOH7pz__t4cUDh1RkfOKpZ15_4XuQ4nx-eHr_JMTw-JNP5kkCBSk-jON2qOMqt33_2je-tVwudYL9Cxf-9t_91R8___Lq_OSHf_r1H3zne7_0K8_91m9-8XPPfeDhR68-ev36a2-_9PzXv1tM1OmDzz77_He-W_Lk5uNQDq9f2ZysAwMqmENIIaYYCIezU685cJimTT_vuWtn-wd8dODIbiRmyMwhghsyArohphQXR3t5GGWqbtL3nSmRxyc--iGO_Uvf_wFSmO8dxIBaSpm2MtgTn3ru9KWXhvXYLmZERoGbGGPL2_XWEYkhtS0RPf7EY7du3Ko1o0F3sFc2WzF3nnO3p5OkLiChiQrxOEzdwVyG3HSB29bdkSOGoFMlhdSmms3V0ZEozS8_brJNKS4OD_JmMz84uv7oe3XcrJdrQer2epWaJ_u5X__iD_7kT5u-Xy9PAob_x-_9Xz7x8ONR_Edvvvqxpx_5t3_y7THJ_-zvff53fudPZjC8-tb9v_ebv5y3omSMGHjHxQOiXaEadmGqPoRXbpwcHM1nfaDdMx6dEJCgiQzqAF5FzX1nktKqyCyiAIgOiOQ7n8kDqR3uNn6E7OhACIiGAAiRMATuI3dtWnRt18Y8bLuuJXQmNFMpNbYNuANAEwI4qEN130lhU0zmOw05ztvEjqr6zpR3VCIkHLbjfN4UBXUr1du-2U2R9hez7XZMMWVXNSiiHJGBxFVEd_nWampm6LiXGjCvkg2973otVUWr2nzRq8i846evXew5uXvbpBi4b9sYQgK_v9psplIpiLtqzVW6NtVcnehsHEPg7XZMhIuuy3lsumYqeSrTxcPDQHi62qCDGdluBYqEiBiZmGZdW4ukFEJirxXBF217897JT73niWhgrlMtJt51MVJA31HH3YCK1J3iygGWqyE0YSoaQkiRrh7uyTClFDnxejsNpQ5ib985xya9fbbejNNqKMM4DWM-Oz1VxVxLnSogmRqYM3PdVkDsZ_04FCTYn_Vt2zQBjhezQOC1MhEQXLqwIAAT6GJMHBABHERsrFrEJ3MVC0TuPm_idqrLYQTiXETUOJCoF_Ftliwq5BzjZjMSAiCpqiHEGIig7zrJ1VX6tmHCWddEgCbi009cb5HbGMTs7vmyj3Eser5cMgOYzJp0NO_fffVK27BMOUQUt_VYur09U5l3oYshKwylvnFv_dr58myqr6-G2OKd082k07bU09V0Z51vDuWd5XYwK2pWZbncMNHJ2ZmBbU6W_cHs5PYdAGJ2A9Oqbt5wGvO0Xa3VFN1lnGyq7byXTWZHUB3ONgkJGUU0BLQs84N5neqsjxhpcz5cefJd6_PN4tJxHrcq43Yc5sfHIYTzs_P53vzk_t2QcCz58ScfHbbrdz98lYlDF_eO9m-9eXsap75tCTA2KbYhWfoHv_4rb711-9V37v_klZu37twJ-4uvfvXF2OHe1eP7t89jjP1e7-oKWks5vnBpWA3NrNveu2n37kux2eXHuH3kfeOmaK1AjMzTtE3NrD06XL1zZ3G48GqxSYw4rN8GiMQxdl2ZMhgRUzraL8MKQaVqaprYL4btWqaROXAgAFczEwMzVUMKlFKZMhOFGNFcRFRraIJLzcOm6edt10554kD9xcua1wJUh2H_4hWZMkailEyEA5Oju6_u3FtcvUSOCigiTddKyUjAKck0gRtiMjBEciSpJYTIgQnId7N5IzVzUzClpgetzXxRp5F3lxIpcdbVsSKzgYaY0NTFrFYTAXNVo6YTLQioiLHpkbxMEyESUSk19LNaNQQiBCsZHBwg9gtTcUcHD7F1Tsw8rYdLj17bnpzDXzaBkMldoVpsegfQWr2MTKRFw6xVlZ04FRBAjZuGKDohObgqxYiI3M04JSfDKjEGzxIX-2CCtbRtQ0SSR1dHjnkSdwez8ADESaCAISCh1QxVmAiQMEV0dwQABnSrowqEZuZazIECu5qVaac9iClqLZwaQORuRgi4C3YDh8gmYmqEBKbITAF0GskEgLFtrBQgInNi0ikjGIHZrjpCaEgxRkf3UpjAVE2NCd0I0QlBqiAY7jC07mBGxAAOgUzMaw4pqpQAQO4Yk7q7KCESEnIwqSEGzZUIVT32jUvRKaMKgTsg94mIITA4ojsRK2qIgRkdKLYtEZl52zWpTSaaus5E0N1phzB1MyVijuwGak4IAMQhgANyODs_x5SqOSICooogx2HMTYqOWKqK2aKJ41R3MuxSCzggey61lAq7KE8gNQVAQ1TVJrWmVsXGIXPgMpUmhWmb4QF3KKAYcgRTd6vihO7kyEiBy1DYkUIgxLbvTAUNaMdqLdURwMzRUwyujkQOQBzGcWy7NsboiLrjRLgSk4MzMribIZgSeYjJpIYQkNDNCTExRw6wu7K4ItNOyMBMunNm7m7aAMxBzUotO0QSIjmCO4BDl7hWRYSsGgIHCMTccFiPhZm4CUW1iKoDEBGhVS9VFBA56K4HjlhEdquYIiKORCQmbQp9iGaIDow7D8fu2oSI5O4Iu3HgLkLtiO4IiOwOZaq_9Es_W8xeevm1f_ulL33xi784azrsu6OHH3rh-R_qMOUiqYmHe3vDUC5fu9zv7925f_LE-95bF83Tn_1YuX3m49TszxYPXfylL_7yf_JP_sk_-51_cfHCxbPVcHR0OTkY1L4Np3fe-bM_-Ff_0__4P37z5ReWpX7hC78gIt__3vfW261Ux4hPvu_9n_zUc5_5_GcOj7qbr7-8Pj1zMLbmzdffSI4f_dDjn3ru2b_z937tySefPF2evfjSi7_3r770X_zO__sbX_7uNJWmb2IMn_zEcy_95IXT0zNXoRRTMzPf_ZIlpiDVarU022u6xqrolF1tdb4s06RmHLomNPt7h4eXHqIQYt-BoVSvagTU9nvTZrCqqU3TUBDx4ruuH1w6vPXyq7ffvtWkuHfp0rQ-s1q9ilb-5M997kdf_Yaqxi5M4yQqNStTCG0jg1SzBxNuiilRniZkNIHDh6-O988gMHFsjmdMWLI4pzpKERHTQNQxjEUUnNpO1AAZU9McHORcODUUYkDHSDJuiNykimSieHjhymZ7cnbvlFJbxBQkhlDX1WQ9aw5fe-0npeYB_cff-NFhg2_fuPGDl19-9dbbMMFv_61fevXVG__qD75pYe-f_tPfbLgpWTk4uDESATLuRDGGSMwE6K_dXV68sNc2CR3VwAgMd6UnYjc3UzNFUMAqtsupm6khmTsjGigR7YL-u-n_bhwBaAi02-VGZiQMhIFx0TdtDImRCGZdalIwh2kczZyIidBFQ6AmBFFXB0U05KnUHfzXiPI4IRAhr2o9W0_bIlOVKU-ny60REpK6i_qiS8MkXYyzGBeLWVZrZ-39kxUBdakNid1EzQA5piTVdygbk9o2Yapa1fu-DejDNMaYZinmWto2PXrtof3IbQyEuJj3fduUosv1uJyG4nC62Zws19XMXQGxa9ux6FiKErpDraXrWgRYj2PX9av19mCxAPTz9TY0SQEUPHHgyIEIiVWk79u-bUueci6AEAKntlW3X_zgu3di8c12amIIRCBSqyJRCM1UMgEWtSbFwDRMGTlMoo7o7kezJiEBgSqspupMk9nd8-F8mG7cPBGD7VCmUlab7VTEiGJKRpCLxMiivpO3cmCKUVUD07zrrNT9vnnk4SObqpi62Y5cmcdydLwPSFXEzEKKuZSh1KoPQGfMWIqMxcZas7o6ZpVhnEIIhEHdp6lmE0xhtRzv3DlDwq5NZlRLjiEAQgyJCBnc3fZm7dHRIhEc9c21o71dKPbOvZOUgnNYLpezpl0c9C34tYcuPHx0gQzGcei62HRxygVCPFsNqzy8fOv8zTurb9649cq9zY318Nrp-Ssnq7dOVq-frFfFzod863R4-_4qVzxfjptap6rjmJebTd_32ymPw2SqTlBzdiBz02r5fBvapGJdOzu8cOHuzbdLLaVUKZWZTCSE1HSROLhoYg4p1FIDEQKmtt3bOySKknOTwuJwRtVUbdxsY-JxOD-8dl1Eu67L47ZI7WeLfjF7-623KcTFYnHt8cu-KT_6zk-4b1KXppIRIJDud_2__ytfiE38watvLw66-8P5rXvnz3__tctXj-_fXw7brGr7-wdTzuY2bqfZvOeGA3PTpre-_K2uiVefeYqaxN3jz5pAaDvqOy0W2naseXZ0AayOp8um6bJMhA4WdvUsVzBEQiKONZcQErqiCMeEQDH1qlVzbuczYnZ3ImBiN8EQkAiZpVTbXYcIzbXmzE3rWoftcHj5CiFOm1HcuqOLvt1orcSSur1pM8QumajmioFdaky4unsnzGcAneQpBGSOWiu4IwBHRhM1d3dOEU3rWFLTBI6gomAYA3Ny0RAbqSMAWclh1tdhCilZKWbObUNIyKxlRxU1MEXwEBtVmaacZnN3OHjokVq2aGS5MHvXL1Sllry7uz8YQqoyo5Yau07GKRBW09DvWzHKw3a9nl-8Ni5PoSgymjoHIjOL0cCZg4sQGgBwnJtUd9exEAMihbY3cARyFWQObaMC6eDQI3ftYlieIRGiIwE7oso0TWneJ-KyHdAV3SC4ZmEANHVwM8fYqKub8i4FiugUHUBy5sAEYKViDLFrVUSrcUArJfVNnYQjuRqFB8qkuLdARw6hDoOZm4FKdStojkhmZmpeCqEEDtQEyZXYfZocHWJkZHTTUkGMErs5BXYHK3mn4HY1RAxdrFMxq4SADhyj18ocdq10CqTVdgVNBOYQYCrqzvM5IZpoYHZXq4bEqkq8S_wBc1AxRLcsHEkdkBsirKrIxASqFppoBiZlNuuZIjEiGHHkwKFJxGjgYy0OBA6IOI0ZgFTBwZlZanU0QGy7XkQQ0NzNgAkQPMZYVR2REMskk5mKTaXmqkU0lzqNuVbtmmaa8jRNxICBKO1K827gMcWUIgYWNXcFIBVJHPNYDExEXM0JOTTEqO5GzoHGaUpt8uK1VEZEJtxddd1rEUSYpqzqSH85BGcOMQQOOyIKIHRtqrUSYilFTTkGdW9SJEQAKqXEFEAVgWKMu4ecuuOu9OBeqhQzQN9RvEUdCZsUEWmcChN0TSNVS5FSJYTgTogEQNNUQ6AmJjUvIiIWOBr6QddNarnWGHiaRAGA2IHcLYYEAA5k4OBOSNUsRjZwAGMiUZ1EHSCEINWPL83vnmzvTZthLLM2MiAQmu1aLKZqRMi0w3yjgZuhuQNRhMDsH_3oh4cyfP_bP_7df_N7v_KLP1O2pt68-spPQHyxf7TY22_7Xsyf-MCjt27evfrI48O4uXjx4tPvfe_L3_oLOdv--t_51ed-5rN4b_XsRz_y1a_9GXNY7M-kjnfu3dnrIlm98eqNNsWUwt_49f_xN__w9__0K3_-0ksvf_JTH37fhz70T_7h_-Law9fHOvy7f_snf_ynf_7D77wwbKcG2_c9_eSv_fYXP_Kh9_7Kr33-6Wf__0T9V7BuW3qeh31hjDHDH1baa4eTQ_fB6czuZqMRiNBEZgMgQKKYIcmWpZJclExZdFllV9nlkkvShXzhKpsul0ixSIABJEASgUhEZgOdgEYH9OnT4eSw09or_GHOOcb4gi_mhny3rnatXWv-_xzj-973eZ6_9eijl7vt3__pf_7P_uUvf_KTn3v79lnfr0PsD45PwH0adn_hL_zQ7du3X371FVDl1JScQxtdqhRFRERH1DrtKTAaNe0yRm6axlXBXXN2cdVitVATm9QtT08Pb9689eTTR8eHTdNXlVKGtl-B0_HpNTK9eHBRxtIuFsuDRbnaklsZ_dojt577lvf_0W_-rrNz0-UhI2DD4fTZ58pus7nccoohRiZgDO_78Adf_dpX81gkF8AmElmRauBqB49eA-AxVwJPKTKj7CdmgICKsN0UbAICpr53AMnVHYCxjCOHaA5EaK6lFML4bT_4lxjL7dffVIMqGtuOMbrzj_2f_nd3_viP337jNtaSUnN6vPof_m__1ycX_R99_itv3x--fvvir_7lj391uPx__39-nkK69eTJ93_0z9ZsDsIE7DAHfhBmrhSGEHKtty_2j9w4bGJwVTNQ8BiQgCLz7PGsBhWckaqpm89eRGBWVQREADCIkWnOrsBMtoUYGedopAMBEjgTty0vEy9SbAjaQF2bAhMg1FxNDQmbFA6Wfa3SJSag_TRV132WKgZMJYshOXopGpnPN-Odi62lMIkbGCAuF_1-KKbWLbrtdqhF-mX76OHy3tV4ctCP03S1G63aVGWaJiLsF22iWFQIqQnEjlp0qFOXuuriZG0MKTAxI-GqaziELqBpOenbhmLbtuBeVPbTdO9yw117frmr4Oo-5LFfLPZDWbSNIVT1YZy6RVfGYi5Hq36_LTFRVYmhcdO-bSd1J1Q1RgpIjBiJpPpq1TAgAJgrR-77puniux89ff7GrbwbxzK9fLG7voqpibmUrm2EwlBl2E1t16g6McySa0PejRUDWS2rJi1SLFUccDfUCb0AvXp2sd3Xq03OUoFw3A3qnsccUnT3WqpUiU1wxHmG0jSJIjYxuNrJ4RKynB4vl4HAvY1hfbhMDQfEJoTYpiqmZjGQGwbmEOJUBdyJuIqZGhDmqqGJpVgV2w3jOOUKaG4lawU76NLVrhJASJxNYx_dwM26ritT2e224N4QoCmpvOOpG08crRYpEWIIOBaZiql5kbJadOT1-vHB49dP-iZMeSC2tkvjOG3GbApv78blun3h7auc6wv3L5d9Z8xN2wjCpCbmV-OuGGzHElOYw9qhb3KRs4vtrSdPxt1wdXE1DeO4H9yZUgIjGXO93MRARQyYOMYHZxc6bmtVJOAYXcSdY6CUUtkPQZ0ZZCw6zSIy6toFAnjJdbelGFLXufuwHfOw6xdd0x7fevzxtksy5ADUN22bwvnF5emTj14_vfGhb3nP5373s5fnw_L4uF-nH_6JH33hc19ZH7RLSv_Zf_CjbRv-u7_3C8X1wbS93G23V_vXXnn96acfv3P7LnMsVQj82Xc_df_22emNo1XXl12OnPb37yTJizY1z9y4f2GsB0-aUdO3zXIVYqNSmag_OW675TDsMBAjeS3cNDKJkzk4hcSpdRNVh0mPPvDc9ObbQKhVY9c23SLnQXIGcRMFNQY0Ua0VCDgER0cH4iQlo6G7haZtApVxv7148MjTz4TYATTDZnf9Xe-KNm2u9jXvUr8oY-kWjdaqM7OsWkAv2_PQRQSXydv1gjmqiNdCSGgGTGauJbeHB4FYanVRItSigEQxGJBoQcKmaUxrnabQdETGgLkWIgQEVYx9dBOrElMC0VoLuHRHR5In7hZlyutbTwGCyKDVxt1ufXyDkTCSilDTeK0hNZozBZZaGNGlUGzUfXFyw-vkUpvVChnzNIYYYU41mFo1DInBzWcNrZooNwkMCRTcCdyAOCZEJCKrQoiBg5l5Ld3RSR52XkpoGh0rInBK027q1isOqZgH9L7tainmQAT4kJ2J-HBYS6QaERGBQnBEBGdiDtHBkNDUmRlmnrQIiOIMvwXXqhSCStYicbmG0Ob9Ds279VJFvFYdS9O37soEPmV2UXFoGhPntsNaCR-amH2Ok5mbVKwGxO5OPiudCiKBzfR-creAbKqIDlKsakwRHi5LHB0YUKul1JgUUEGKSOTmVmsISWrhFGUufxrgXC0DQ0CU6i5gEPvGzAGAicjt4XCZaA7qHByeuGsMsV0s5rVpIESkUmXO1QKAOQBjjLHWmkIk5inXh-JtcKkV0N09hBiIQ9MMU54HdM58_-yiX3SlqqAXEVWrJSNiDM2oGfDhUoIwBI7EQVWbmEQkhJRrdXMTIwQohoQ1z6N3QkQmBkJxdQUiGIeyXrbqYKbMrOCBA8UwTRNHUlOrDoyzW8vc3LFJEYD24xQShyaWUhDJEHKpISAgITysvhtArSU2zIhu3rapSnVwDiy1phTVYcyVIqFjpKAI1SSl0DBXs2raxRCJs-i-ZA7cpCaLBqIq5gxNTKam6NthSDEQURNiFpukFhFmLrX-Kb4f3HzOJyB4pGAOSKTgCMhM4LBMUQHdTVUDs5rv9qUomPhUShFNKQYOiIDujAQIiKxu80EYHiq-gSgCuAog6Lvf8fwP_PDHfu3XP_HTP_1TN24-cXLr-Kt_8pVXXnv7He995xtvvu2gXRusSMXKiY5OH52k1CIn16__n__Hvyu78eL1N66fPvbOp5_8rd_5_TsPLm48eqs9Wn_jq1_nppl2wziO73z3uz7_hT_-uX_80__dP_nH3_jc559_3weuHR1d7us_-p__0Zdf-MorL7_UKT52ev0n_-aP_K2f_NHv-oE_983f9mcODhessNmXL37-i__sn_zsL_z8b7zy1TcsZxaM3cogFUcFQ2JH_fN__s9f3Dt74SsvurqIcGykVOJQxzEg6FSYg5kVqehQS9Gcy34EE9NSxqHuR3Qb9mMp2V1LtcvNrmYT8GrSrQ_Xx9dj1y6ODiHEXErsFk23AEQr1cs07oa__p__9csHFy9-_oW-Sanrun4ZmzTtL3PJ49V5HifVmsdhxpTXrEZyee885xGB-vUaXEwcCd3o-qM3p6EEDljEi7pYiinnDJyIKXU07XfdYtm2qZQM1Y6uH5fdGCJTSlIyheBu_eHRk8-_56UXv3T3jTcDMAYCRkUghHSwfOPzXxz349WDS_EySW2Puo9__3f905_5l8-869kvffnVj__kX_iTF1_5kz_6xoOLqzzV_-d__3e8srjN5AVQZeZAZG5EEAM_2G6vRnvs9JCRwEDEnCEgPKwpmAUmA6zqBlZ1XsqCAZg6EhIAgDPjDPwhRCKeS76REcBjIHMjJgTomhgiLvu0aEIXQxtjIiB0RFTzIkqBOFKfWhNVrW3TbIc8mYaQskGpNuZa53Sj-eUwlCJFrbqp-D6XcapTyTGFg76_uNoreIxxsxuaJlwOxdyucrl5mO5ejA6YYjLwacpMdLBczGOIWmvg6IjZSoypiIZAiLzsWibcj9Pj148urrZt5FffPlu3zY3jQwYPmIbtfir15QcXOedd1ttn5zcfuVlLTWFOc2gp9bFb12_fu2ybBgBqlqZJXd9MuQBi1zZgen25vNhOYy5mNhNVCWCZOnFF165pNrtdZFwsl4TYtu2N9eEjB8sH9y_7Dm8ctHmcmANSAMRctDptxnHd9G4emNw9ICuG8_00VgX3ddcmglI0q9y53HEIm219-8HF1T5fDrsqs5JIcF7dBAKzkisguauLcgpqFkLSUmNoJOvp4RJRATZPnJ4m5piYDEy8bVIkzlOdpkLoCIiI1Vzdsqi7p_mlkNiqV7NadCwV4GHRDwNOQx1LQYKzi2E7loNlmrKMU5XqTNi2rfmcBvInn7jZLSLX8oF3PXu6XvSxAfeYQq4iKkAMgSVPR8vFY6fXrh8eMFCext20XXatmIuoELx9f9oX2eyBmyAE5BYobnf7aZLN1e7oqAPW_b5OpQ7bKTCbuQeYVGqR42uL_W5fxrw5v9SppkilWlr0pRYbhqCCxO3BcntxcXC8Hq72XvJiuShFbZLAVC5fYWu9qIpAVSvFhjKHAgC8aZsU-4u3b_d9m0dHRNC5cqlI4fDkWrtoL-5ecJVbf_bP8nRlyAjwsW__5g--5-nPf-IL41Ceedczq0Xz4z_54__qf_5nTPH5dz_yn3z8Y7Fpv_z6vS988UUOePVgf37vwdXlFqTWIqvDw71NpnZ4fAiuu7OrftGg0W7YtcvF5o07AfCx97xnKCbbgdtbz-VxG2LbHh2Lardc131Oi17V4qLP28u27eqYuUke0IubWjpYT5dbiASqZu67bd5uyzRpHtPq0MAoRKuSmsZyAYT5nDoDQFPfI0UpMrsyTQuRT9tdbA-Ojm-O27Pze_cR9ejGqSNt79zvT25wncp-nIbd0c1b44Nd6BtMERzcxEURMHaxXx5M233o2odiHkci0lLBPTCpWmDi1Prs7FR1NxfBENvV2rWaqIlwiMhk415Eu4NTKGPNEwGExaJOJfYrB9CcH8pRwAmBA7uDh1RkDE1TgaCUQDBenTeLnmN0B1EzNFClSJYLBfIpgwPMYFEMTpQ3O6271Y1HSy4y7UFUS555mHHRRQwUYs2FmQEQQ0RHFUV0AKjVQrdEcOLkqhRDaFsdsyMvr58yehnHhlmqeMC4aK0KTBOvem7benVF_FAsPw_UAcCqUIwA4KVAqSlEqdWBqDuyvIvobuCEiKhFiJmY1ASqEhEahkhucz6WoYpX5_WhCbq7j3viQCGV3Y4d--OjPE4E7lLnk1FsFmoGAKgOVQgstL06OLjmEpqEM_chRAQncDQHM3egpnEzBFIpTdupFAQCc0oBKcynfzfwahhItTA4qoSmN0LiiG4mNXAEZqbgZibKAYlJXZkYzQIxOSNSaJoyFA7sprXqYrkoQ0Z0R4yLNsUUYyLilKKKcgiMmMcaI6tBDGnKxd2JKGepLhiYmFwF1EqpzJRrZYohxeV6UUVKnYm6OOZKjGY-ewCG_eQIrormxFirAACHCEAhRFMhIjNgYlFVr5oFZhtorUSx5NKEMH8i3L0J0cxKnVv7ZuJN32g1c5dSYtMgISC6meQCjuCA6CGmOhU3ZY5InmuNKSE5iBMREJnrNOauiaVa17aEYKq11KaJKsbMMQSROlVFQiBkpIBYTbNIisltXluQg_dNlKrVgJgis4mPVYGJkB1A1fomTVWq1EWXplKmUhxBVNrUUAhjLkWEmOv8oBI6oM1jTwNzdzVmhgBEEABhdnw7cCAxnztwAEAOuzE3bRJVBRrEhupHqyW5mwgzi1VGdjQMjAaOMG8AHAEJq6uZO9bUtN_z_d_1jnc-94k_-P3PfubT3_RNH37Pt77va2_fvrp7p214f757cHa_6dMTT7z79Ttvnj84WyyWP_KjP4B5GK6Gk6MbuY7Hq6PPf-mF7ZiJ4vVHbrzwlS_UjKMOEclL_Vt_7Se_-Vvff_ull1-9c-flr7386X_3R7WWVdt85wee_et_9S__xF_94Y_94Hc__uwTZjGIgdUXPv_iT_3UP_2FX_71Fz7_4uZiS05eatsnVRDHIiRqaoqEavot3_oR8vjZP_qMOTAFCknMzZSYAhJHBpi9kZyOD5gQvOqYKbiJWgFCAylQRtnt6zhO24251LyVPGieRLXUzCkaQQhxsV4v-p6Ja915KST8A__F3_y9f_GrL335GzGyVimTDPuNlppSik0QETPglFShWxzcevKJ_eXF6uh4d3kVY7c8uubm03YjRnMH9vSpR-verExkLlUdfc50eeCHhLDQptjYlMVEhiEEUBXVGiLHpgU0xHh840nu-jtvvDoPUJomxWaJ1Dz57ufrZjeV0RSarjm-du0j3_Wd_8f_6r86Pej_wT_-hQ_9mXf_xN_8-L_6l7_3-S-9TA3vR_0P__MfP-qOklFM5G4zrH3ewpo7p3DvwUaQHjtZzaF_c6cATFhVaW6tsAOgqBqAmqvNO5mZX0boGAJGZAdAhBA4EHEM85KvCRwDI2EbIxM3kTlgZFy1TZ9ClwKaxXk7SugIRdUBll2TkFQEEYvoOFZPYVIbJplqVTNRw0DHizRMruYY45irghd1dUkxtm0T0Ku6OuSS2xTNcb8fpqnux3Lnaj-O01bqoKIii0W3u9rFNsYYXXQSDSmIKDOagZpQwOPlqua8XCwfPLg8PTrYXO2Q0FSHaXrykZsMGJmdeDvmzThcjnkvMtQpxPDkzePtZmCmWkTNA_FYclVDczcVs1XbgdpmGI8PVxeXVycHB5sxV6kcuI3JwTlQlqlLDQdcdV3JU9ekWnMXwo2DdUN4skik0q8bcBT1FKM7FvP9fvjC2w_GUlZ9GwLFQDUXjHGofjnVqdbL3fbZmycByN2z6ouvvd0uFm-db15-_e7F1b4AhBil5BRjHQu4J4o1T8QcAqsKETsAB541bYHw8KBLiAzw7COPrfpAZgC66NP8xqlFhlxKrX3bRiYHmKZcDcZSwcEZF22jatspV7Eius-5mmfVxTLudnXKRUQB_Xy_RwpiEkKYsoRAIXLbxMDRRJuYCGHZ9k8_cm0d8Npq1bcpBFSRIjZNmQK5a4x08_S459A2qUrN49C1TeAwFb3YDq_cubpzNWCID4Z6sR1v399fjcIMzjRmqdW3Q77alwebQZCath21vvXgfF-9TBqZTCxP08W98ypWSlkeLktxjjRtttPmIoSmW_YXD85Xq2Xbpd3ZRvJoqCaqQyYAK6lvGpy7o-A1T0zoiCEFRAbTPAzgujg6APAYaXN5tThczBiYR556smnig7duaynvvnX01v17XdN-87d-8Khb1W3ZTbVdNkeHa0f6zKc--f53PffGN978j378B3Z7_-yXv_Z7n_ny66_dOblxYOZ52F1e7VSNU_Ph7_zw66-8-dSzT73x8luSy2OPPoLEm-3lcr28-9WvBobtvq6ffGJ_eT7cP-P46De1h9fA5H9xJwFYGUc1PTg9vXpwpmWK7UKqM6d2tQYiyQMBcgwgghRNK6lyJCQf9pv-8DTGvtZJRJjR1Nw8MFIICC6q3IRaFVxDalyMycBJa57G3eHJ6WK5GHYXD95-a_3kO5nx6v6D1K_7RTcOO5Hcnx7LKOCOyAAQY_TqPlXNo5ohIocmpL5KMRUKFEJENEL0Kk4ASAbmBiFQbKODOVB3cNN0BEeT2i6WhFCkSt51qyU6lKqgEvu-5EKB5wPHvCGVqQA4BJ6m85CWBtitj2QaY2Bk3G_3qW0Ag5qkxbJM5SFyqGpoInHUWihFLWV949H1yY3Lu7fdsD8-yZsNEqIDWYU5DcKEIeVxAnBwMLUYA6AjGJnHNqkZhQAIagpOYdGDm0xT266AabffWZWUmDwwh9XBNVWpWbu-lzKqaEip5oKungsiYiApFlODqiAG4IDuSI6GZhRYsjTrw_lBJ2IA4sBeJcboqo7oRMjJ8sTEZArrRoWhTm0IxKlMIwG4lUQRgVQyI9o4PZzIzplTc3QBNUAyZjdA0wBOc2IVGeYfVJmcCK0KMZqBS-UQ3R1MiAiATMQMTAFDsJqR2HJmZnBwKdS2IhUBCBANUt-aGadgY05NkqkgEiF5FuYAjsisBiGlWRdgYs2iI6Qy5SZQSA1RaLsWEFNKVSWEOE2ZEN09F-EUgNHMnFBNHV0EDGe8nTRt4-jUBALuuzYw5SJV6xzgmUoxx5qrg-da1YTIEYAA1MzURZQiETM6FhEnMrOua8dpVAMRocizP1QNAF1FYgrIoaqlEEIIu90YUgQHUE9tqkXcNKQQY0PEgJBSW0tm4iaEUmrXdrkWqWO_XAEAGDEZOTZtQ4g1F3cAxzalUq3vQ80GgDDD-wjdjXk2FTgxEIU53qDqkQnRmtiMtYQQAkEbYy1GTGbStknEZ7vRw2CXAxBOtcRACOiOu2lsUlLV2DSmNpZq1Zjnph4AkYEjoZqpG6CHwEhoDxs6DgjuSg5EVNUIsJrEEFMM2ey073ZFAVGAOMXNblgkbmMAt7lQCXNsC6C6kgdzU1EgVDVkVjNyD0SPPnrzfR_8yFuvv_3pL_3JfjhfdSvHfLQ6bB2mWmKbuF1CpG96_tkvfP6Fv_tf_5fPPPqUTPsmsYgz84tff-n12_d3u8v3PP-OzdlVy_Bf_-2_-_Q3Pf3mW6_8_qc__Zk__PzLL75sG711fPLf_F_-Nz_4fd_xHR_75vd884cPrl8vGi-uNi-99taLn_3cL_38z__zn_uV3_7Ep-_f30RqDw7X4LTf7ZkJgPPgEJriNRDFSCk05vXxx28-euOJT332k6Jas2Fkx1BFKYYZU2YIQMhN9GxWqxXhyITOSOn40LSWKbtSs1oTI7rplH2cymaXt1fj5fmwv7y8c3tz9-7m8mJ7dvfBvdsXD25bLg323_a_-huf-Ol__eBy-_z733V442auNTTstagZIYp4rdUBmJvURk7h4t49VXOX1HZ5nICgjAMHqkViCo5wfHoSKAIYVszTSATMMYtgSgjoxFJq00ZwH_dbIpwhzoAIgEwRiTmlPE4X996e_SFNk8pUnIOqP3jrLQQ_Oj69d_d-EzA08fOff-Gv_Oj3b6-2_-43P_mTf-NH_tFP_dsXX37t5tOP1SJHq_XHv-87DmK76iIzBUNCjPQQdQOAl5s9AD5yvALzh94VAEcwAXN3A1VDA1dUcJ2f4tnNgjPhyhEhEDFjQEhpbqghI8RAKcxItlkP7ClxEzkSrNpm2UZ2SEwE5jADe2mYsgPEEPsQGOcvZsLIal7USrb9lMXBgLKYOhR3qUKBA7EZDDm3XcNMDYdIwQ0GqRTwcrNbLfpF151dbp0MHIchL9aL1ATmAGrDfjw5Or662qxW6ybRlMfUtFIrOT95dHSxz1XKPPJcLtPZdne87ooIEQPSwclyPw0ciEzbwIPj5X7kthG0pu90KqeHy9Ski90-pZiatpg4KBKXWtGdifo2MuF2mo4Ol1e7cbVc7CeZ6gTERJhzYUIxCTGa1mXbOsBQslVf9z0tGjA6OIhdltQ2zWx0Rsxit-9v3tyMgPD22cWta8cEGANv9xMQTQJ7qbnWs_vnzzx-k8zBYajlzbfu0SK98db5vYvNbp_dvVlEqwpMWfL-fOjXrTkyMjIFTjK3dMyQKMWgUhdNGwOcrPsbx4uIKJP0i7ZWDSGUolfbvYEhh9DQ5nJXRMTdzGNMeZhSjMY45rLdDV3fKoITGVituh-KqHEIQ9aj5WJSK7WO-7Fp4-yJCzFwCLUUrRaQTg76DzzzyMmqOz5Y9V1SLaaaq45T5kgENGyH05ODo8WCMZQ6RSZl3O_y2b1x7jpcjGNWTSmcbycERy3f_t5bB9GWbfO1ty4UTAkvhlINm8hKVNH2aEeHy0UTWwBC3w95c34O8wHYvAlx3O7qOIaYwEOIXIaJKYLBeLGNqGU_zT1DEGHQQFTHwV3dFdQjsLubVBWLbVuGKbahTmZmedoHYsLoXonb_uCo7Mf7d884heq-O5--7Tv_7DsfuaUeX3rrtnh99wfec3G1nTb58UcfObx2OJxfvOu9z332xVf_-IUXH5ydY4iby6vF0Xq_n-7ef_DBb3lfSs16EZ9617N33ri9Pb968umbeZxObl03sTdf-Hq-vNrtyunTj0HQi1fesGngw-e_ZdhsmCh2i1qEmDBFNjIFjNiv1uN-H0MKzEAsMsWmQQNTjSnWXJE5MJkokEuugO4UFCD1K52mtFzZNCE4M4G5lAkdKEaKQUpBhHbRaylMhCquopIll8jsjJv7d2K7dNnlqaSDxfraY-Nup3kCZhePbSrjxIHisqtjMcIA2J2cuklVo5RUxWqJMdVSCCEAqhulRDGpOgG5GLpy2467S6TgUhHcXSkmMLdSDRhDQnQwNa3NYqnVOEYzsloxMLsDmIuGuODYhX65uzhbH10TKZrr8vAw55yaBsjN3cElz2hYdjNAIqbZnxUOV6np24PjzfkDIuvXB8PVFsygVE4BcqXl0hwoREQwqRwohOimUgVV518p9AtwDymq1NT1KhLa6Lksbzxa8oDgXd_XYWJE1zlYyKEN5C5SGMgRvSohAgMSg0FaJKsCJvN22BwwRAw8a8eIiTjqNGEgAjI3UDfV2TrjzACEJkxsqlohLFboKPttu1iLSopdvXyAhLFfuoqpgMoM5cTYuBgiW50CBxWjboEqWCqYoDtRgBgIGQl0msAshgjzlpJwTqSk1Og0kUNsjkxHAEIidJ_lrBgYHMCczBy4Wa_qNFmpMYQQ2AEpkJbStgnM_WH4Xb0WQEcijEwhECEhoDk3jbqlrjNRihE5pKaJhG4OZCYWYgBzBKhoqp7aRqs6gogxBzNfdMtaJ2IObTNN9eDoKMWA6og0FZlyTandDQMxz5IiM5-mkmJg4mkYApOaA3OdcozzcmyOaiA6Ivqs-RRVImYizUXNRQQRHUHNaynuZuDCnppI6gHI59snQM2169pS1czMrOYMZmJKTGaGaohhLgYBUhNDFZ2bl1XVHQPBfDpPkR1RqzCCgUvVGAITVbFi0veNqWMkcVV3ZiIFCFyrNk3UXEMM1dUc1CyGUKoJOCNQ4Dn8AARFpImJiKZcKKCphhiaEKvoVHJkars0jhmQHLwPC9NKQADAzK7KgCmEZRsZORElJlRwBiBCsBgiIZk7ImbV6iYOhlAESqn7Ybp-sAAwDmwO6BibcHUxVcOY2ByZwBBKrfTQG8TgYO5dap5957Pf-u1_7vx8f3F2__ab912kjlO1uuwPLMXL7f6p55978YVXb77j-DDQIjWnR9dSUAe4ffvyM5_7o-nq8vt_9G9_-ZO_dO3RW3_wh7_1a7_ye1eX2-eff-df-0s_-vHv_dh3_MBHv_sv_LnF4ZED76f6xhtv_vtPferv_8Of-qV_-2uf_YNP_ckLX7l999wwrU-upW4RI4c-bh5cmZIHzHtplitKbeza6x96zyMnjz944zUk7drmgx_68Cc-8YlxGMHJOagJEIEZOkgpIYb5xhiIXKupIIHXqkWWp6djEdRqyFbFHaRYIOblEghC34mZi7dtG5jJDWbiGREoFK0v_9HnQofNsr13_8F-tykm7WKxuH5zfXyyWC26vh_K1DQdJzapKgVUCCEQ53EAJnDxWkHN3FPT1FKOTq83XX9-fh5inPLeETglNTdmqUocVSS2SQxUcmAPzhyCmZmbSIEQY7vcjxspNQSOKWg1D7FbLYfLS3Rrln1WyMOwaJMCHK-PSvDXvvH6j_7F7__7_9PPfOXLL737I-8e9vXq6urH_uoPP3njWh8wYKhlInU3ZeIZE3A1DFeuT52u3dzM1VzdxNUcDFH1T5dUiPqnAH91m6W8wAgAzBSIDZyIHuKrAIgI5tgngQMyEYJHoqYhRiCXg0UTEUNgYlSpRBRjUNWxiAI0TViEAA6TqIMbwfl2NxTZZ81mRmESEbVxzOKzj1EQMRKYWimlFqmipVo1mwV_bq4OR4ddzjbfssapZgNlqlIJUBymkiPidr-7fnxNqxiII6QQipmSq6ijH7admEaEg74PKeynEZEawr4P3_j6621K2rRnm-1mP4y1HB8f52F49PDEazlcdNss5oZApjqMJaQkqmbehNiG5G7VYL3qdvspMCKQEQCxOkRmIgyBOVBi72KqVYFQQa4dLE6RI_sXvv7KslucrntG3O_LVLXvmk-8cSe0YXI-u7y4cXTQpxgCFVEH2Be5f7ndT2PR8uwjN9lxmmQzjJ998fXFcfeFL781Sp2qcorMLEVLrUV0se5lKhhnlgRKqYQYU-raDtUDE4OfHB8cHCz6SEfLrutj3zUl55jCZjvsp2zgIc6mHOhTTE0joqLqCgYaQkDEqp5CBMQmxe1YSylNirWaghkYOcREVXC_33Ztu9tMAP6wJmQQA0WA4_XyPc_cWDGgQdtFNx-GqWlCESfya7fWJni5zY9dX8cQplxKnYaqZ2fbXOXmzRvcpzfOzrfFQopv3T0_uxyaNkotf_LW1cvnw5dfuX21G3jB5-O0207gwk4xheWN_uz1syVSH5rN5VXf0O2zi3G_iyFINTRoOUrJJVczR_T-YFn3Y7foXW26vGJ1VzXjlHrZ7qIjmpVpCswAROBW9aFzyXB5tHxw-7Wj05uqTtHH7RYxAnpq0vJode3m6duvvqxSm0W7PDo8eeT01uOPTWP5-itvfeqTn-z6tN3vvvLFr7ZNOj48_MKXXvyu7_gz4Pgbv_sHF1eDN8ghjOO0PjwctruYsO-6w_X6h771o1_80tdffvHlZ55_8pmnHr_71tlq1e7u3X_zlddSu7jxnicOjpavff5rZchEyt0zHyzGoU1mdvLIs9vzO1XMGRFxf7W9-cSTecgGsDo4rCJaLDWBYnLHIpODI2CzSGoOiM2qV1E3WRwexdhQ4HFzFdtGSmYmTgnNHKHm2q6WQFynzEhMbGJIpFWZ0cAkF3KPTO754OYTbLVMwDEc33j6_P4bbioqTWpDDHUo7eJQLXuZbbs7kxJS6xxiZDMD09Q3mos_XEk_bHIwU2hbN6-5tMsDQKjT3kQCECC03UJqVjMOlLqeGEzR6sQpln1tVp1pdTXiAGrozmAy7RBscXSy3152y8Ocp_HqKqbWRNxcZdaMEBBqraFpwB3MuGmYaNxskJHSMvZt3l45cNM1oAUB0D0E1OrED9NNAEDgMTQASJFc1FXpYU-X5tXBfDwv4wQmoYHFwbVxu0EzQiJTN6UQQozo1i8XRGxqsUmSM7q6WGgbMzdHSgTVvSojmgMAEjOYA7iJtgfrOk6xTZKFUwQwInJxAAcBJwBXEKHQeM3cdzLtQ0qxSQ7MHJBEximkzkFUDd1CYCmCIVKIJkLghE4hmVRC4IBglmLQWl0RAysYOTCgVQGzh2shJBONTUuIJhUtmzsYUgzoPud2ZkQLSokpuakhE5DmzIwuqgac2B0RHNSQIoK5OYIhs4phSADMkUSrGcwvWEdnRmSiponEiUMXW0AC9_nO5QhVjQK3MSG4AwGgiYATkjPHknOKAdyamGIIgdlApzGbSK11fuUbABPVUlxBS0ltqyJgVkolImIin9cjqFo5JEKMkR92i3Ve4AREL-M0u1pi14E7ghEghqjVYmCdChoYOAFoUQBvV72quds0jiHwfMcg4K5pd_t9CsnJgXF2u-72uW9TFavFQH0O-iOGGNN2t08paa3IUVVj20y5YkAzJ8RZLTBlcbWUYqQw5gIIMcQQQq7FgcQ1xEAIpfrM-UFmN1c1B8i5xhiKiDoAuJo2sdViY66MGPsmlxKQFZwQ3HXmljJTE7htYhOpIXZ1NEQH-P8zUkwd3RwcxA0dx6pz8wSRRVQMY6CDPjWMgDan-5pl_7_-H_4f3__hb42RZwKLPfxH5h3DvGVAVTMIv_Ybv_W1l7920K1e-_orIHW333Z913Tdg7Ozpuu_-4c-_qlP_8GPft-3oeFBGxlIWRHxrftnn_j0p8xh8Qh_6dN_uL-8OD24_pN_7Ud_4i__xQ9_5APrk4O9oCLfu9x-7Wvf-PVf_rWf_bmf_41f_s0vf-Gr09llA87miJExEDdTkc35btrlcbsxkBhbAsMmUqIqBQjyvbtXt98OGCla2V18_w__8Gc_-5mr7QYMmEM14BABwVVo9nObIboXdRVGpIBuld0BvFsf5d1IzERY1ZDZCSRnqWKlAgdaHsg4uM0zbIrNAjlM49Q0yUzyVPaXexnHut_JfpuvLrZnZ9uLi-12sx-ntknHR6er9fHh8c3V4TGHOA4TE-aSfT4ZM4UQzVTdQhO740NwOL_7wEm9ijOHSBQCELpbbBpknLbT0a2TstmzAwGqCHNiJmCqtdZS0J0Bm7SoUzGked58fufB8a0bvOiv7j0wKSGmy8stEH39S1_92Pe-_3d-64--8OIrz73vuTzhm7fvNW3z1_7ix1qnBE7ui8RaBBKjYkU31WEYn7p-ANXNQVUxoFRXwKw-FRFHdycK4i5qNk8BEAMTOODDzCa626xrZEaf1wfgQGA-F4icEBmxjbToUxvCqk0JsQ1sqlKEkEIIFKgWVUQxXzRtQDRTqeJMCrbZ17HoLmd130-lmosbAhRRcZvbxQ1TCIEQ-2U3VZ1XE6u-J6eYQqn16mofOHDg_TSJO4YgUkWtuk8m4IDAkXm_3187PNzst01KkwgxabW9ZzA_6PosWnM5WK8iwZRlbjUs-2a32fCif_WNtzfjWEqZTHOREPjaum85poZeu3txtO5H9cO-GUp95Npqs8_VjJiaJi1j2Bc5PVy7gZnPIw9VG6bcNglUYuRZkb1er_clI3hK7ePrxd2rTcPJpeyiHh2uGoSz7Yir8Muf-doTx0eXxYax7GW6f__8mVvXTVzMShUR2YxlFDkfxhvXTlqA7Tjd32xf-MYb_Un31Zfvi2kWN4CmCVYUCMZtPjjoh6sdpwgWzSUE5pACs5mpKYIdH64DYRfD0WpxvGoDI4LXKlVVHbjhnEvkaKLLZY8AqlZFgNBMUxPd3QFcddmGcagcqKiXWtsUHGE_TIa4GycmzrXut-OybylQ2yYMKKjM3KVm0YdIsEihDRGYUwy77Z4JShEinsaKTlfb4da1NSjnUt64fXFwtFbAqdoui5NTLt0qvn7n6uW3zy4u99rR62f3X3793sG6vXd2WUVi31xeDnmYSsldw6XUOuYknhxOjxfbYZyK3L24mvIEyGXIRMwE3IRxyEyIbqBoaAYMHKQURpRhCou-VAEtrNY0xAHNDRWX_QLUXa1KYSagQIQq7WKRthc7QidOChZjI8VOn3jk3tt3xsuh75vTxx4nx_d_6L1nb985u3dx5-7d3TDcuHGaUtxfbX_kR74TGe-dXZwc9r_y639w--xCqz377mdNoVjtFp24D8OQRb_pHU_IXj73xRc4Ydldfed3ffvZ_bM33nz91Re-YQKPP_dOYLz_jTfzbmq7eHi84uXz39Icn-RpmPaD6tj263mSGgPJWIvkdrlyhTwOpsXFpFZMIfZdncS1psgIQKkhZKiVY4Ss1DShaRwDknNqtBSr4lUwhEDIMap64ADuXisFRg6EDOToxvO5zZ3dpUy7u7fdIaZ-rCo2njz2znG_5dBpnRiiIzsa8Uy2CpoHqFpK7o6OmNgB5n00AqkhwKydpuX107ofHF2lqFYgpNTF2AKBlwnc1aBZHck0oVdVFBVQ9SJQK7eNlNoeXzN1n00qDuRG6NPVFXFsD645-tGNG2UqrsrgqhZCInQA8rmqK9XVKERXdVUvpaqE9VFslmGxKsMO3VLqy1RA1EXNStMvkBMyi4jVSsw-p01nBbm7mTfLIzd3ye6Rux5NSG0ad_3hNXSq0xRSJ3lkQGR2UzTsV6v95VUTO1VVq14qEXk1cIhdg_OrwwyZkQMghhAhRkQ2x8BJQcEcCZE5l4ocHgauEMEUQyIiNwmBKKSmXyPS_vJycbh0g7IfQSXGJCpWDFzRMaRUS-YUABhFyedqAjNHcFBRV0VCRMemwcCIJEPmyOiKD5MgDu7mjikggRcJqXHRh1pfM6sCBG4WiVzVHeJqwaEDqYhkKhyDASGgi6ABIzgYh4gcylA4MscAALFNCIQIMSQgAjUSabpORdu-XbYrB4sx5CkDY2hY1RCBiEhxNuzgfAw0M3AmJnDJGQGatkdEV51KAQMEMAMxwzBDTrHWKkXaNqkqIXopgIiAHKhpUqkaAnAI5o4AXRvHMTMyujaprVXbps1jSTFWkX7Rl1IThjxO3WqRp9wkrrmgU4jJzACcCEOT3KCWwgCEoFVwhsKSIwIxh0hMARwCooFz4NkQz46IwCnGFGSu3hIQIoBjIPvTWDk4cIxzscDMCDESE1Kd4T4MSC6KQKQmDbOJFXFH4ximcd57GCK524yneHjfBuhinKaK5KKeQhjHEiIl5kQciYi4bYKBByJXcydRK7WKKLirzekyA8SY5larIKIZyDytdHDAKjY3mDGPN45Wbg6AzCyV_-HP_Mb73vXcteMFOBh4rjJKJUKzWQeBUh0KPzi_vDofn3v-vb_327-3XB9dnJ2JlP1Q9qXooMuT43d_5H2_9Wu__9a9N5MSRz08PmpjyAKr1eG_-plf0P2Ud9MH3__ev_Nf_mc_-EPffXzztBiW7fTam3d_7_f-4Bd_6Vd-9qd-7lO_--_ffPmVuh8JsOsTVuEYipiKlVFcm8e-5VumN14CqG5w-MjN9_1v_-rtT34-pGgiTKTTyOAUmTgAuNTx43_px1_44y-_-fZbbihiIUVXAIIA4GqIYGqu6uamTuQu8-FPhjE_-vy7zu_cdQcy58gUEN0Bld0QqiNRyQAAwCaZKLlVBTQFRNSqCNB0bWgCE1IIyBGIYf4gqdd93m-vxt3V-fmdi6tzatLyaHV87WR97Qanxjg6OyFqIAoJCW888si4HxFstT4o1Zo-afVbzzwDYCriDohMAIu-Gy43ZmpiHFnMYruUkgkp9YuYGgJn5m51MOvQa5G27yxwaGIZhpuPPhKa5lu_93vzNK1Xy8984o_vnw-rpx-5nGQaYCz68b_w7e985NGIlhigSubwXf-Hv_MffN_3zCW2quXaSW_VEakUVbQiJm6KIIrV3ObPm4O6M5E5EBLYTMWdaV3w8G9hgIABAwCYOCKaGs36XwcijIkCwLJpmTwFmhfjZv5w8Uukohf77DOhy0CrlixT1aK-nWQ75lG0qot5KWIAVZ0CL1PajSImw1TFLTAFRnCcxBCBkFIKpo5my75V88vtdnG4IOSp1pxHd4xdo2LgAGoVnABGKY-cHDch5VLmUgE6qANHCoiOFlpeNC0BbMcJyN1tvepNoOnbYZwcKTZxrHV5uNrt9osmNDFwCBTDbFZPAR9cjs8crS72NUvZuyxS07BfDnm17Bj8YjMcLftStZaaRSMTAKeGc639sm1jU6qEJqSGrx8uH1wMtx492uz3l9saUrPdTF-7d3Z3kjt3NwoQU9zt8-VmP07y3LOPQlEmRObdOAyi58M41PJNj97wYrux3Nvsbp9vHmzqbszcpFqq1XJ42I-74gQE2KYIyKFhKSVGIgqR2d2RYLHoV31fhqlr20h-vGiXbQyIDLAfJgpxN4wArKAUqI2BgVR0sx9DCMWqmDdMgKhqd862HEnBh7FOIjIflw2IaRjLVPPBolVHJixV3v3sk-ebvQMuD5ZeNQXEWp65de2R44PrpwcpMiKlwFPOVZUpIHgRA_XFss9VXn_7Xr9cFrCL3fjmnYsHZdoPWR1ff3Dx-tmuiFS3j37zE2--eonuEvnO2Q4bHko-fvRgP0kIMat2fQLE7Vil2tkwFPdvvPami7LT_uKiiYHVZcz7aaAYQa1dtFbFFNs-1mlCQpkmF28XjZtAUSzSNmm82s8OODTQWtwwxUhM7WIBSE0KQORSicjET599zEqJGIdhyJN0bbM6WD71Z95x9-U7ddp-7YWXPOLBI8dPvfMd2_3lZjv8p__Rj-X9pij985_5nQ9-4KlX3rq_vHlw985Zm-J2yN_0jmfHMr3y0isnJ0ePP3r96ePrr9492-2n0LWH107LNj_5xBO__ou_GgJ2fX986_qdV1-3fVZ0boOMI_fPfKQALteHSHXa7kRzvzqSLAe3boZEeZrUoGnS6uBgv9lXzauja_urAZEPrl_Lm63U0czduL92M--2c_4kpbQ5v-8isTsYrjbNagVaHpbQRWzmK7bdw1mmAzhQDARUS0HiOWdBwKBC5K5VJEudpEI1PbjxmJpyShQ4tElUHZBCcPtfNpuzOS6lblGlSC2haTAQU4z9YthMITGmUErhENplNw17iolTK7WaGbrOGZe0WJY6gXmzWlqtiIBMXgoEMlFgwhgR0cw4RHCPMZWyl_194WUuZXF0YqYqhWIo-5ETIyDNXGXE-dvT1ZBmIINbnTB1FTF26zxeYWwokKpyIASQPKbFoiqkg6XkCgjk5LPSBZDROQbJOS6WCODuGFtOidCIOA_jwc1bw7Bzt8Dz4Qtj27arRb9oUtvszs_75cHsa6AQ3ZWYrSoQm4OjgSMiUohuEJoEahyj1tKulmU3hnkeQKSuMSbJBVMEdwph9syAqmvtDg6M0dQwhJia0HfT1VVsk2GsJacmeVGXrFUBGQOwGbhoVas1dK2rYiQby1x9NgPggIRmQnNGw8EIKTACmghSQAIVcZs9jc4hYmAzNbXETFKZA5LLVLltDAxMYwxaLS4WHqjsBkQAgCpKoaHIgMCIgYMjU4yuNhuemWJKjAomgok5hPDwnoAhBGcSdMmOAFZmj7GL6MMYOrIZiAoiEoKaIVC77Dbnm5hCHrOoDrkAkuQauybn4gBWNXBUqRSo5uxzeBfJABwdZ_MLIhPXXCkEFSUgIMTIZcpmCuDEQU3nImwtwiEoOCDUXJhgJvM4gpsBkQGM-5EQmHDONgWKbsZMaoYcMKCoJQ51KiEEdQPz2YXnYBwYEKVkJEKAUishz52EEDgwE5GKzS94RyciVfWHt2YARwMwNzc_7NqxGiKqm6rGGEwVEX1m9bjN_oRZJqDiD5dDRAYqri2GJoXADITobm6u5oil6GxNVjUOnFKAOQvRBSYWsVIkMAdi4tn44zEwOSp6ZGhbOmyawz45uZma8tfunv_mH3zmkes33_1NT3gFJBCbCVLoBghYRYzDr771r-XBwonubs9f-NILHMPu6jIlbGLa7LU_OvqR__Qnddp97pNf-Oi3ffDppx5__Prxyy--9PSzT1w7OP7CV776hc99-b__v__v_5P_8Ce-67s-Wih89Ruv_PZnv_w7n_jjf_Wzv_Brv_Tv3n75pc3dux1iH2O_WqnN2y8yVSTOk4NHNSuGt55YPHj1DTNFtPXB4Xd-4CN_8tnPGLE7OHiIoeYCGFJKikXy8Bd_4q-8_vVXvvz1F1E9hEgpqj70SJnJXHNHcqtAISAigcx_8VL92pPv2Nw_c0b2-WKeiBABgCNSNEQKkbukphQTOjmiO3BkbhOoABM2iWMwtSpzsI1D09aSY4rtomUiDIjA6CA5D1ebi3t3Nxfnm80VJ05tG1J_cv36an1weHp9GidXHHMZpxy6FFIzjGUapn7R1TETB0djwBhimXam4giOwF0nUjiGYZoQyNHKMGLbQUPjbl-n6vOcJQCEBISqXis_-q7H7nzjjb7vGZJwt3f78Hd-5-vfeO3WM4_88Pf9uUUIKTKARACE5h_8v_71OcRved87IvOsEKwOs_WqqIm6KohClkoOTGSm4C5mgDBf_h1dAUyNgeedACABIs8KMASYdSkIs9guBiYCJjg-XJJBJAyRwE0NTc0AEZ2cxH2qJoC5KiEy0jRVSmE31n0uedZYpoCEHEIRNcdJ9SimEUFUgdEcTEHMIRICphQWy-7yagjEzEiMFHiYyn7KB8tVDEEMzVGyJCJXRUZAOD5cV_Gz88unHj-9HHaupkghxlpz0_QpBXNX8xh4vWgf7LYpJnBYdItFars23ju7cuK-aye3Rd_du7h66vSoT10uYoRd14wiR4vucjM0RAi806LgR13bEGWRFEPDdPdqu162l1dbTqEY9G0yt2uHy_Pd_trhilOcSs5arx0dnCwafyhEwMrSd_29s831k5PbF9v9OC6Xi7aNDzY7BepWjRRZtl1V0Vr2w7SZ6qv3Lw3hsaN1Heq-ljcePLjc54tpcudSq6lTgJSCO5YqbpC6REyqWrKmJkw5t4lzzoFm_hMcrJdtioeL5ubJQURws3HMGEI1z7mMY0GgXMqybxl5KjWEgG7Lrjvq2hRTrnU_lPWi3YyTIavDfsx_aqnDIlaqTlmWfatqJefrJ4e5uLmAc2o5MXZGH_ngO558_IZVZYTVoiN3c8_TBIBSxQCzlIPV4v7ZbrubMPHJ8dGbb51Vg22Rzb5-_oXXi_hm0tTw0Y3jcZL9pjrg8mChLpvNrphvNkPeT9DBNpep1KvdOI5qjkbuZFUKTwoi5WpLFMyclAigTDWExEwX995u2hVSkGl0o9Cz5omBLAtRQDXOhU2rmBTBEKwqRfJqHNjBYtNzZBmrmcpMrAqpPzzcvHFne7nrFt2jzz1FVmWob33tDdcJm7ZW_fDHv0OqjmMum93f_PHvufv2vddef_Dbn_zj7_y2d7vFV99-O_Wr7bA_Pj5-5ol3tE33R5_8JAd47Okn1otmt9_vaqWQXr_91kfe_2eGwf_Nv_wZBECnD_3At7_1-u39g63lcvj40e78qgzC6-c-2jXBMQ37K0YLIQ1X2_7weBoGomhauq7fnJ8vjg7Wy-NhnEzr0enNacqABg5WBNRMik17bpKUrGNWF0auJt3y0Mx1yhAiolsVAHdRCiSqThzaRmsBBA4hpgWSyVQpsgPOfREtam7EoT06ialrF30tY4gtxlZFS5mYm5onGXNqGhEJqfVaTaGIOHK7WgH4eDWsbp3WYSpmi9UC3dWKKdYpqyoYlCGnfkkUyrjnFKRUU0Hm1C2nYQ9SQreSnAk8thHnQYrD3OUVU6uVY9JamRvlpj1YxyaZamqXw3bn6u2iI3QbMzI4AhNKrXUssW_rWMwUTUBkHId0csoBIHR5GPuj66CSxwHMQETcMLSA0QE0lxCJmOaO9YzqR0RndnMED12HkMTEc2ZT7pqmWeZhIgcTd4X9WJYHqzxOjDzup0ff946Lt-8TEYVQqzCCzwhOAq8eU3RRJEcgTo2aBA4AmPoWVcE9LNtSrWliHScg9kDoSMjm5qUSITOP-_HknU_vLy4ODg4vN7v-5Ai9bB9cLW6cSq1EBA7k1i76mgtxcHjYSo8pahXqWgIANwrkjk4cug7UmdhqdlF347ZxYjRjRnTn1JkW4oCB0Gye3M9LBVIDETCffcrULhxApiEE5NhqChAaLyMRzMHYfnlYx8FVidHViZhTAw5ei4OGEFJIbmCMgKQibdtz4NgmE1XTGJKpRgJwrCLcsJq7m7jWIuiIMAdM3F2ZmYBSG8dhbw4qSk1yUwdvmliymFspNURyQkcEAnWPIalo6nt3A7PQNCLWNgkQc81axU2RGDk6Gar47HMJAR8a5CoAhUAKqKWiqRNhCCratC0hznZgAlQ3JCZwrZWY5xgBBQJwqUpEJmLoTgRubkbMao5MUisFioEdQMQxzPlUMncXCTGYqojNyHMinooQE4BTCMRIROZeVSmwAuRq5oqIVj0QmbmqV6vzk5MCM2CtQojcBHcg96yVkfs2ReRqkqvkUgBJxPwh-JzQvWtiCAhgPPeVmMABgEJiYnIxZsY5F8vBwYkgEpHbjXW_XiRwj0QQ4y_9zidevXe5vSw_8LGP1GEU8DnrFpgRWcxEbRj16cN3HR4tqWlz6P7gE5_pu_bB_bPlaqGeTPz7_9aPXe-Pvvi5P2wg_f6Xv_LeRx65uve2FHzmsZtlf3l0ePTjf-0HnnzuufuXw298-lP_5Gd-8Rd_4d999hOfvPva18rlZROgXyWpEho2QIxUipkDOTgAMcdF0y0WHLv4yI1Hr924-9JLSOqmlOIHPvTRP_jd3-MQ2xQAFBEXBytXQ3RwK9Pw4z_xE1d3zz_zhc_FEMwIEKdR58IHzmve2YrIPLN0fbatoxNTs1yWqZRhxHn-bNkRgINqNXBDMBV0AmIHUBNkcsfYtAhGKYS2nYZRclEHcgQzA7MsabF0lbDo8nY3P5axaTiw5mKi4EjiMo7Tbl92m2FzOZXRkUNqifHw5CjF2C_WuU7uTIxdG4pqRGZyHUu7Xk7DIDkbWEipTDU2UQ0AqWhtY0hNt9mOJtouGkCMbYpNIsTu8EClphgDhxB582ADOVcP1e07_sqPfu2Tn99d7f_b__Y_Pn_76nDVMzmDkUEx_5l_--tm9uHv_pYFZIRQXVVcTKuIiDtSFXOEmSHgs3Pa3QB8pro9NOsRADo6AcosrPC55A9IDz-AHNjdmSkkDGirNrVzIxhMbb5lgzhGJhEPKeymaomnaoDohkgwiSh5MdiNtVTjEBZN3A2y6ONuFDFT0AkQTQFoKoWRzaGoIjI61lKmXHO1zW6rBl3b1Vq7tt1up1xGYwocxrEwUZ5qQD7oGyXe5eJuUvR4uVw17flmyPPXiEOIxEhShQjV5GS1eLDdxaYJRClxGxgM7l5cNIs4X6hCagDh5mrN7kUcA6tpqdIyXe2mJgYguqp5MD1uuwBoblU9Ba5ifde2MQDRUKqWqmJ9n7a7fLDoajEAb_vm8eOj1r1KUcCxWlZnR3B768FGAmW1o4N-GOokMlUpQm_fvXj02klDIKqivi_lS2-cARNVTRRH0899_dWxqhDmomBQSo4YQgymYIDTOK76pYk40n4zxIYTBTNj5vV67eCpTevVQkW6NjxysiZ0VXWEqer5dhebhESl1hTwxlG735cpZ2KMTRMQRO1qO4h50zVFNFftFu1Yq1TbDxNREAAHHHOuUm5dO1AnAF0vVyIik-U8ZZEA_s3vffZo0Yz7fRu5SbEWKUVyzuNUmENswou333zs6HizH3f7YXW8OLvaxkQZ6JU7V9uhbvfTetn03eJqN15ebMHcwN565d6bd3Z371_sasUY7l0MVWST67T3ss95qmUYMVqp5ezscnnjoI5S93tXEwOOoV00027rhjEFB1Wt7fqoSZ1rRbLd7Tc4LfIwynbPjFqrizACB8IYKFIdppiiFHEDYihZm9VC1KfdfrnqTa3p23ZxMGwuQTTE-M6PvOuNL78CU908OK-arz16ev_BxbWbtxBdqzx67catg9WtayenJ8e_99kvbje7H_qx7_jDz37p8OjaS19_-fqNR_OUH33sxh_-_iemaXzP-967WLbLtpkcHlztX3vr9vXr15585Oav_tt_M22uJrXTp56tane_8QoUcTbQwcWbtufD933nOOZlf5Q912laHh7VUhAZ2FNqSikxQkTaXm2Orh0vVof7YeDE3Ka6n0IIHFlr5cTuagpNu9A8xa5DgKq1lrFbr83JA6EbpeDu7gZEhEipoRBi0-Qp-_ziJwJGdzNVcHP1mCITqBiYlJwPbtxaHF6bhjE0cXl8PQ_7mEIAnrYbcKs5m9TFtRMrtV0fhLbb73ZNt6gmebdZHJ6mNno17lotdnDjZs17lRqQUt-Wab86Pk2r9TTtOcZAaKIhhNQ1Vaq7LY-ekOnKSnVFClzzZAoUMHad2cOoDMyDvd3GauXYE_Hq8ATQyjjKVJquL8Ng6rHpQt9qLU4A4LM0iAkRpVyex34RuoU5TpeXi-tPEIrkkQICEiE1TUIm1RqbVs2RZgI5IszJFw-LvtYKGPujawCGquw-nD-gFJcnq2HIhERMq4OFTLlJqT9Yl1z355tH3_HsfrNxs7ZrtEoMwatR08o0B0jQzLjvpRSMDYBTiGYam-jqWozmBTECR6q5Lg6Py5RjDC7qZiAKxNhEz1JqTsvDcbft1gcxkpac5megloBkauZmUggRA1rVOWLEof1TtSqhA4fgAhQYGR0czQKzVuEQZyYOGDJ5aJc1ZyZEcDCbUwqm1atwCK5CgRCpVg1thwRsZllCs9Q6RQYQA3NAkDF3y95UVWqMEQB5fskwS87kUEE8EAaqU2371kxjalIMKSSt1oRApoxezZBRAYkRGfWhSEHDTItqEyG5etv3ZuJIokaBDFlN5zW9AbhBCAjugRMwugjH1lWZ0N36vs259ilNWZbLtmbRGdHhllJjAJqruYGImhpQ33dmYtUI0dQgcp1yJGJgDgnNQmTm4Aqohm4IFCKbSeDoBoFDmzoI1MZ2mias4uYhNmaKCITsqqltiRnVUgiJQi7Z3dquRUcRzbkQIcUgau4Iam3fgBszIzkYNikSBTErpcYQ3UGqIpOYMmITAphRIAFQV5ypWQZFZvcwJApFBYBAZbXoY-RhmGpRB2BkRw-RS6khBGJC9IgOIozcNNHUa1ExTyHgLLbjECMHhBCgigJhYGK23U6ev7VOgdwcDCiF3_zc52-fXdVaP_49H61j4Ugm4ogEpOqExMxtjIjYtY2jvfDaW1_8w88dLJf3bp-3bdgVAeC2RZNy9-zOwWJtefNf_MTH20V7_cbR4cGBGRjEi-3-9z_92b_3P_3zX_-V33vza69Szj1jABRRrW5qImCApahDeOiUM1AwMXOHxJACnZz0y9i9-cpLBIbRv-n97z1I8aWXvwGi5jr36wPF48OnVot-Grb7PH7fx_58is2__-QnTIwoAAWM5OCBcHaAoIPDQ8M2EIA5umOMgD6M5fD6yf7y6iFWDb2KIdGMz6dAgJhi4kQmwgEBgAkYyKWYI2Pol0sHle0lcRfIwRyZECHvM6qQ6fyfdzVTaxeHMZFJISIiZjcEAFMpZXd5vrs8O79_5_ze_ZjicnXQdP3hcrVare_fe5CLjENeHqxnfxagQZ4oBlc-fNfTeTsGpnaxpohlHBOllEKKiI4AAYHb5XJzuWWORB6JpCo2lB8MVpHa7onnnhruXb7-8qt_-W98z-n6oEc6POxJKzuoSIrhX_ybX1sdrL_4lZe--9s_ULNnr1LNZknJfHgHIMbAZPOJPzDgTEHwxAwOCOQIjAgOzOw0A6oAEB7mNM2JGIncDADBbdGELjD6rNs2DpxicIdIEQlVgTiIoxpWNXdQ1VKlqo1VhyK56pBLrQLqBr4dStd3U1EwIAdXE7X5S6wLTRWVYqerFpGnWvquGYuqWq6yXq7cITVhyoaI4zBlcEG8GgsxoToC1imLKBHu97tnH7k-Ddk5oMNy0TUhgLmDE5KI3ry22pTKSAAQAi67lo3Oh4kjB6ACENrkbo8frhqOFYobIeF2nFYp3d9sUxOYQjFj84Nlv-hSiKGKLvp2n6e2iaerfrubLq6Gg3VPTJHDxW57sl6PuylEcrDHjhYg9uDsAptmNw5NbLrEpLYVOB-m3Tiu2w4dkelyNy5WDXb85a-8-vST16r4KHaO9tIbd1NDY9a0Xr14-_Zrb98HxCnbPNISrTGFpkvTUBxc1A7WS1ArWcCMCVNMota1LROLlEXbrFeLltO6b9ZtBHBjoBjGrJRiFqlTJWZGqFXzVFKbQky77bA46HOVy-1ITONU9kMxwKnKsJtKNQNjIjDghoep1EoH606KoWPbxu1u4ES7q6uDVfeR9z97vW_LLq8WTdMQmgvAJJKrIxGgEfAjx0dDkVyrML9---JiV7RbfvHrb9692EDXjmOtao9eO3CtoQvn2_H2ZshioQFgwkTTVMU19pE5nJ-Pi54BvYrsrkYz7VrKl7vD9bqO07CbmrbtA2AxMVe3YCDDEJo-hiY2Pl1cgVizWufNfnm4rttdbBtT8VqI0dzN59ABmRjNvWkADpH7ZtrtmzaFGaTISACJqVv0B9euWYXtnfs67bv1umg5PFoN6u9-_pn3f_A902bDtUb306OjZtl95Wtfn8bx6NrRV7_0KrYg4AeLdYj8tRdeNNPVan1wcnR0tOz7xcVufOOtO3mfP_iBD33j61978ysvcmzM23d99F2v_slX6m5DARHZpskNT555lhfPfSTn3XJ1xJFEreTS9Iu8G0MIIaQ8TVqqlsKA-3HPXZ-adtztFgdrUAMgik2zSHWcQMXdQhsdoYxleePRcnnGUtuDa06IyHW_JwoO4OpErlVSk8wAiJq2nYkNyAGZQ9MhPuScERHHAO7IkAKfvf7q4uiUYhrH8fLe7cXhNRANTWxWCyly9PjN3f1LNOmODyTnpunafrXbXh3eOGWO0zDFts3Dbtjs1IwZYtOiQR0ncDEzjGFOlJaSIwfQOuWMCIfHj0zTVusmdWtVMTNwSymhY96PHAIgxcO1q5k6BYxMDobu4yTNokttR4G1VlMld2TO44gUkJkIKbBWQWYZR0aAPJWrrSK13YpSM-0v29UxxT5PA5RKbhxDXPQP1QqEbdfUrMhs5iFFIOSU0NHMkSx2jZlLzimEOkzd6qTmUqUSY9N0JRcHSItl17bjsI8UuvW6jKNXMBVUpy4BMqfQpFZq5b4JbU-AiNgvekJ0hcPTUym1aRsrCgar40PNBQCJ0ABjYMk1pgSBTKEO-5vPPb99cN4ulpHDtNkulusy5u74Gpparmi1jFOIKaQ4bcb-cGki3DRWhVBjv9D5cC-SYpKaY2ptFjlJJWZyR2JKDaiwm9QSV0dWK5mhg5tKzaFb4ow2NQVAB0BCQuJ-YVVtKkREiLMgTKsEQg5Up9L3KzWd6TcIpgapbVSViJDBqnDbmQiAhxTLlA9PriF4SmlWAkHkOquAkWbgPZiLWqm5iSmPE8dAgECoUlOTnNnMplKYSMFMFB2amIoZAGqp7h5TMpXAXEqZxb_EITaNq0lVAFyvuikXUxERB4ghUCA3l1LBLDZtFVsuFmp_Wp0wbZZdGaYm8NxwQHdE5MBatEwT0cOygSN4VSYMkc3nhDCCu1dhJnNLTSKEOkwcIiAyE6i6-1wmC6lp2zBNlQKDQwoB1KqqmTFiEwMiq_psKupiylMlZlEAN3QEppyLmtJDpJ08xBO6N7FBcFDIVRQAACJTlkqMfWhdXdRyFQdPHACwqCeGvmvm3UskSIlTTAiOSOBOTE1sx3FqYoghMKGKze6wedbYNtxE_oH3PA6q5OYg9y83v_7VV37lF_991_VvD_u__j3fMo5ZXEwdgZB4di-Yg8_rDuaqfu_88rOf-JxVU_DD9Wq1WKXgjz7y-Guvvryvenrj-Lu_69ueecej106OQ9tdjvs__tJX_7__-J_-9D_92d__3U--8dJbAXzZNk5-9WBTAU01BCYEIhIjpKgG7qDZi6ERLY6OD46W-81VZF5eO172i9uvvkIETvaDH__x11_62t3791HdzOd0-FTLbneV657bBlFv3Dx-x9Pv-NQffnrcjFLnilUwE3SZ8TJAgIEQEQjdFGbFGhOo1yFfe_K5zf3bM3cSwAMHQOSZfizexISzTASR3Lzq3HRCRq2ZQlAwosTrQ1RTUUCsomgWyL3UEBhAidlVHGzcbMKiGS93iJzWh2BeytT2nTlYFS3iYqh6-eDs7utv3L9_T6wujw-XJ9faVRdSKtMeCIftDsTAwWqG1IJpGacp16Zt266T3VjyyKh1qhTDrL3vF13ebbnnRbes017Fu9PTVX8sNSvS-mD1-quv3nzm2g9_70d-89d-9_l3vzMRtICuCsiBws_-m9-6cevkGy-99Vd_4oem3SAuKjbz_M2AkJiJZ_Y_zkcOcHvY9yVHEcuo9DDtQwZI_rAnwIiBZhYuAQITEUJg7NvYRw5mM0qXmJhJFZBIzNzJwKv7MImaKcCs5Z7mWG-MOVsRAYQUopmnGMVwyKWKRAQ1cPeixRwdqc6aJ3SOkRDUfchFVVV9mHJV7Zpe3aqIAsQmZPEpCwWcqQ0-k7sYmTBP49OP3WSkXS7grqLrrlM1rdqkCOg3jw6zaFGNiRX0saMTE7jKewsUMGarfZMuhv0j696qtG0DQBdXm1xL28bdMHapUcTzYUD2NsRFkwJjEV30zX4qJ4eLFmk75aGW5WohuYqoO6wPFq6ampgCPHm8DhiKGUV6cDU06_V2tzs4XNzfThfD3hwPuiYwj6Z3drtF1zIFbOgrL71Zge9sp6_ffjCpjEPd7_ZXUz273OzHrO7MGDlqraZGEJ0wMpvBdjt0izYQDtOUOE3TGNvEMRyulmMemhjR4Nata9N-CGR9E6UoMnmw3S6XKsOYI7O7Xjtcidp61e33kwEogIqdn--AqJoBEseopq6uBmPJzIxEIYZpqmIWIh4eLEGhb9vt5TY1SWtuU9MGfOczj5M7IlDw_dU-F5lyGbPtckmJF4s2q22nOtQ6FH_xjXvbsWxyeeWNe5Da7tr63r2racoh4HbIghB7ev18c_t870zpcEkch3HaXl41bRquhjzpchEDA0Qca1H1PNa63ctYylRianIpeTflq61Vo9jWPKHW5fqgaXspsnvrTXSC2YykNaZmuLxkRCkGIoTsYGWa3AHMKKUy5O5oWabCgWPfDpuJGVWEQ2r7Lo_7Moz9-qjpF26l5rrbX_bHh5vdVpGee_49N24e2zj9_m__0ce-4yNPn5ykPvzCr_72bigFjKl97OTg2Q-_45WvvAxKxnR1fhFjeO_7PlCKdpG7bvXiV19--7W33_XOZxH9t3_5Vyva-77121dHh5b3Z6_eNtXUNXmziSH0xzeXp9d58Y4PY9dtz86Orz9acwldAqB5MetqppUArj3xmJYiauJwcHq9SqmlhBSnqQCgG5ooANZSTCR1i5hinfYnjz-5uXpQ6tSuVykuYr8cc46B2kVnYjOsHRExRqnF1AjZZP6iVw6Nq8yDZ5UKim7gbqubp_du37_x7DtialPk8zdfaleHppq6rorkfb717m8aL85kGOo0DdsrdD1-8undxWV_eLrbXJZxjxxCwLZrd2cXpri-dasOO0SjEPJuf3jt1hyjLDm7Y2BQsZK3XbcyEXPFwGpGD-tnyU2IwIlkHNvVKsY498bAAUgBqglS6Dh2JU-IFrvedJ5zOoAjMhIRsdfCyDzj_9FcarM6QPD5AyaltgcHMg1EyiGWrKePPbG_vMIUEQNwUGBk4hQBERzWt54u0yY2bQiJAqlYaBIGmva7ftk7OMWEgEjOiNyE1fXrmwfnCND1C2pjmaYQE5h2B8u8qxhjk5KKcYhElFI0teXBmtnXx8fuhsR5yrN3XWpNXVvGDIbdalFLJgBm5tBSDIR4cefu4SPXp3Fy4MXhgYkAUn5IljQkiIFNNaYGiTiCKoBav1hMUwVEamYRGVgVYFKV2HeA6KY0kyAdHCA2AVSQWKt0h0dlHAEgkiMnk8pNcHVEQ0QToxilVopNe7gaN1sOzDGpKYUAJqBKiGjODTPHXEoK0U0psCFyCCrCHBw4xGSm4MgAbd-WcezXazONFEUViEQB0EsuQOjzLJYBHFwthJjLGFIjInNmpmkaNZ-mYurIXIvMSRt1qCpOWKtGDiKiZgCuM3yTQrdaDPvJQYm4mjFzTGEYMyFocQdUqw_P-6bEAQiRuOSCZggcUpScXcXdZtZ5nsbUtSICYKBAMTVt3G_2gZlopkU1Y5narhn22U2tStMujMzUVAzQiBgjq9b5aS_TNHsG3NDdyji2KXKMOWc3Z2ZgMnc1I6ZcpOuaXF1cH8LPmV3d3HMpbYgwf1kRAzqAU6B5EVdUAayJgQBVjZAisorlWogJkVPiucHeEKEZOqADIUSO8Kd-tMBIRIDexMBEpooAIRAxm3kb2UwBgCkeNN4gMgEzNW3zzsdu_M7P_e7ykWv3zi5-7Hs_KtmMDBycyNWlqgGImxlqNXFcLpf_8O__i2uny6effPw973_nG6-8tVq23Wo15fG1N9_8tg996Pjg6PmnniZKL77y6t_7B__0X_3cr37ik3_00tfecIkM5MXIfRrrfjcqOqdkCESMhEBRGTUgdW06WLYnB82qWxweaK11ux_3o0qROq2WR7ffeAMIspUf_PhPfOHzn7t4cI7uGAgJcM7CEapo0y_JxMC_5Vu_9dOf_tTlxRU4cUyANnO0ZwGCmyMxztFzc2QmIndFIhDBFDBwmaYUw0z7MTFgNHeMSKbg5m4IiJGZqEyTkyIAhTSNIxPNRgtiokCiFtoQCN11dpHP4RV0UDFVMzEMAQJ7jJILM-YMaXXYHZ2oqwylXa5m9y5r3W83d9588-5bdw6PDki1X_Rvvvz68clxbMPuwYUB9utViE0tGYN7taPTx1DzXKpBQGRGCmq4OrkmtQxjNgVwAbCzN97a7jcKEDneuzjLU_3b_81__PI33njXu58-XTYr5IhEakiBQ_ypf_k77_3oh196-e2__MMf02matfRmiABEHBjnXVNRM7DEzIyRiAATsyHNHit_mA4lxJk-6zOSmBDwT8nJiMAAiLToYkIPOMOvCAhFfMpSzXIFQagGV1O-nCatVlTbJl7sR0RI627c1VKrArhDEWmb0C-ai10WB3MoIsWMgOZCcgxEROYQOTj5wbIV0anUaqZIITUGM8CUd_uduSMzouVSmYOaITAhxBgYvGsbMQPA9fH6ardrA7vjetHvx1FMY4yi9ZGj1YP9UEwZoEl8vFyY2Nk0itmqbfZ57Pqm1vyO0yMtSsSA_PbZeYpUs-VSuYluXLxYAKp2suzdfbcvq0VztttfW3R9iLcvN-a-XC1i4P04Hi0WYrBedgh6a9WtmsbdN_upvba43IwpsFadBG-fby1gWsSjrq1FxD1rXbSdIw5TuZimXdbLUve5AITNdschnJ1dVRUIoOIhMqCb2pTrYtVVEWCupbpbE6OaFpFpHFMbAbDtWnCbxhJiXB0sUwg6TceHy-NV72i15M3FkEsRc3OP_NBDTRSY4GrISpCLXO2HkGKulZAErKrmLGMRIpw50bPnQd3AtWlS3yaZxEUjw-HpgalN4_CudzyxatqA7iZtCo5htx9FTMwO173Uena-bZtWzM620wuv352qivrZdn_rsVt37l1cXVx-8InjyfFyswkxeR---tr5229fOtnmcl_3Q4hIzBzg6uxiGvPB0QKqN8j3zydVU4Ys1cRCbMbd2KYoptNuYGY1VTWQkqhJ7YLbeHXnDOroCLFv65TzMGoRioBKzUkD-4yEVkVVmAnAXCH2SYsiULda7vdDisSBUr_gyAjWcAA3CuxK03ZnCEXyYtVL0Q98-0eunxw9efPm5uzBaonvfvbp_eXlF7_6Mi-b-xeX126cQq3f_pFv_qWf_608ekgcYnvv7r1HHz2VOpVcn3vsiTdv33n7zXttEz_0off97i_-qkluVteu3Ty9cfP4C__-MwTgpuQKjNNkT3zkI-evv8zrd35zFUvdQnQ8uX663-04xDwMTRMhVwJnpilPMaU65RjTbr9b3zhxBSnj4uAICEyF2w7RKSQwDCmW7Z4Iq9jhrZv7--fkwP8_nv4zWLf0uu8DV3jCDm884Z57b9_buYEGQDRyIAkQJGgCYhJJWWFIDmVZpoIlyyOPNVJNlTxlj10ej8uj0cijkWs0thVGEiVKlEiKASRFAiQCA0CQCERoNLobHW8857xh7_2EtdZ8eJvz7VSdqvPlvPvdz7PW___7xaig3sdxt0cgCmyqVg8WH2Tf1JoR1YdA5FMaNGdyznJF5wBRVZCppqJgsWmGcdevT5rZInbz81t3lmdXbRqq2bjd5svLZrbUKUlJCJanLCXPTs-m3WU7X7FDKaWdz7RUcFG11Jx9P2fHdZwQbdxeEHFoF0ChjvsYPQEZgkgBcGbiQjAkzUVV1SqHeFi_Wq55HCi6uDhWMXLeikq1tu0MTE26bjnsd1LFxwiqRCSlImBNEwdHCKhVzbRU7xnTOF2eczsLTeuCj_2qpP3s6EotpU7JMUIA54IBgJESuRgAsNbM3iMzOFITVV2sT2rO1ERRDLHz3vmmAdPDKLNMmYl836hhN18Mu_181TsjIQar3XwGihS56XpFbdrI3rsYffAnV09WJ8s8pMcefmC2XF5cbELflWmSMbngmsVi2g3eu9j2UjKrGlhNuZn1aTPM1ovd_fNhO7gmELqUCjHki4u27YBQqmgphIc5Fsd5n3d7RgBTDrGUw3taVSuYhnZWS47zFYpqFUTUKkRASEpsVcAqIbh2BkSSM6gQea1C5MwOjG0k56RUJFIk8sE5tlrrlJvZLE-T886q9fN12m98bIzJOy8pNU1fSuHYmiqhmRQGDG3HzkFVIAqxRQLicBiEs3dABtVUpPGhpOwckWNS1CTGME2pn81qKc47MwOCru8YWQ54S8IigoiTiG_CYTPrSJmI2KWclRAJmq6ZpgQE3gfHhABIvpaCjkqpzHTo-TFxLtmM5rN5nib0gaP3iJIzHHgchJoyeyci6JkImR0waS2emQEJQRmH_T7EWFXZeyRXzZgQrYKYDwGYRDRPmT0DoPc87AcKXkXBlAjZMaKJqKkGHxTAAKRU7w_0aTQyh5xEQgylVlE1BOe9oTHguJ9CE02hiS5XzbUGx0PKMfh6MISpkFkIXkRFpGkaVa1SqxoShMAq4BgcgJomESQgw7aNh8B6rZV9MFVEAkQCBLBaKxw0wkgI5h00jtoYfCnDfrhy1KmqmGWxTPauD77z9JievXX_Fz762fe_68n9kHOpOeUCJkClirFj55S4qN67e2FYm_ny_uW97Xb_9S8_84EPv--lF148353fuPrA29_99sVqfv_OnX_8z_7lL_3ir9165XYd1BEO-9S0bcmCyMP-gOESYKfM5JwigqKiGzJIYN-2vmnIOxkTasZULE9WRcVkyG_95nc984WnM1RB-9M__mf-xT__GVelFjMyNS6lAh068GSijLDPw_d89_d_-UtffP75F4FYBIGZPCNYnQqxQwCrgngIqCigqSoejqNgOU2Lsxvbi3MEImJ0xM6bgao4ZlMj5yQlUDMyBQg-SBEgAiRiRkBErUXM1PUtqFjJ5MnUVKYDuaeWLIfwUtMAGAcPeOAFkW97386Ufa7WHB01i8VuNwK6w8NmBs4MVDevvjpsLsZxfN2b3sA-qqGYgopvglY156BWREbmMu2YmJHVhNEhuVRTzrlZdPDawVtVrQ1tbNsYGyNsV8s_97_8Dbt1fryaHR_NuqrL0KKZiCIiefwH__Ljb3nfW5998aVveeots4YNDsy5Q28aRaSaiplz5IkPGxc0VLSiVg71GFMAYCIC0EPwH4CJX8sPqSIRASCAI2qC8wwRzRBqNXJkyApYVVPVokAecpascJBRFhUX2RRAEZFFAREVLEZvaMfLzhu-upuMaMqlipnhwcJHAN65XEQAVauKzGdt48LFfixqyM4Im-BTLrMmINHF5cYAnKckkFIGw5IrGpSSEcmYUh63Q7r-wBUr1dTGVI4XfcqibIqomq-vV5thULEYfcN8Nl8CwisXF10Mi67Z7Kf1cqFWHj850qrO02Y3FLBZ12cpV4_XuynPm5bJNd6t-27VtwS0z3XRxzuX2wdWy2VwtzdbARIFRrh_uV_N-iTat2E_DE899pBH6gJ3y-5rL9xSYALoQrPd50kkodSq665n5FEqIPmmCd4N-8SOZ1cWuyGJwjil_W5w0decmHjaD6gK4JxzpdT9kLpZrEnIcamFDFxgFc0phxCrCjF2i95AyJFzuJr3037oG3_z-poRx3GaprIbMxDBQZEuAqbr5WzWxnHMtzY7593lZhBR9mwGu_0ezKporQYICkZIYhq8O_x3kMgTe8e9Dx6w66OWPGvj2cnqgZMjrHXY7Z33OUtKJVd1IbAn0zqOqe_7XOouFSO8sx-unq02U_HRj5t9G9zrb6yGi_H-ZtiOaRrk1u2tBB2rYO8u79_bXlziIcJt_NanHvzK0y-_-urFHqoyBs9J8-Xl4Mhiw1Lyct4Om8t2vpjGyRO7zo3breMQYuvbsL1zO02jImguhIZopEqiHN10vo9XOt1Mkgo5whAMyLGj4CVVEHSt922wCu1sJklAK4menF45f_VVF7ujq1eOrp2UMSlKN4_smriYP_Toww8s5o8-cPq__sN_9aM_9H37y7uxmT9365VvvPwiNf35xe59731n8OEPPv-le3cvbj7x8O3bt4Dpbe94y8vPvvjoY4_M-vlXvvL0vTv3HvmmR3_31z--O99BbB9_0zdp2b34tefKsPcNDduta4Lr5r7td3fu7O6-yqs3vHd5dmV7_9IxO-am7YBRpMa2VzFVYM9gKlMmIhc9IwHa1YdvajVV9cGXUqRayTm0kYNXs9i3VlTEXAjrqw-l_XmtxXmPor6JKgoiKsJNU8c9EJmKC9H-MFYByLVkCgxoWgWIAFCqcNuoqGtd3e3HaeraBVLMOp4__yVql8FTP59N-7HU6RBvjjEyUskpnZ9DaFQkzJZSyzTsm26BVqsW53zoF-N-CLMeVIlYpdY0xX5OqLkkZEeABzNoGZOqzpZHiCQqAEDkSy7cRWbO44BmZRj8rHOhYd8VlZKGnHMzm3sHPs4UTWpq-qXhQQ4miKRT5RAOBVNHTg-pEpSy39Q0uLb3wSl5Yz5gUbpZM20HQ16eXsnjBJ5rkfboikhSNfbeQNt-tR9TP-uLqGti7DoklGqqenbzgWnYEWAza4L3NqVaZHm6YMDtnYv5ouuapkoxwOV6NU1ptp51i5lKPbl22s_69dlp2_A73v3mJ0-PvuUtb2ZEYXf79p0QgvPMjvr1UsYprhb7O5fra2fDxSW7QwhYxRCZbNx3HQciKdKfrsftbjGfA3NJZXl0NGwvidBxKLkic3d8nPZbAvZNNDXJxbcdGpSSfHCqaFV8FxUJVZx3YKhirg2oCqAgUsYx9r1znEsFEcfoYyMlGRgCW9XQ-MN-OjTBFCQlAmsXi5IqEUquVidQKaWyCy74kpNJ9U2rRWLbWqki6nxw7AyU2alorZUIKHhTDc7h4b1LiADO-SIVEWvSNgYxMUJgglqd82rQdE2tGl08vOzFzLMDqUxoSO5glCJ2RCXlJjZF5QA-MlXngqkgkIqiI0KSmp3jkrOKSdUmRmIuVbQqqABAFXE-IiiYEjsTJYQDrkerIRiTI2I7wO0VmxAAQA48ezRTrCW72NAhzyFCYAikeEBhFmICAWY2A3JsRcjQFA4XjMPmNESXktDBPfuaYo0PAeWSanBcih5Ur6UUJLJq5F1N4p0zUFOoYs5zLeo9F9FagQAJCIirmomy48PcnQAcEZnN2ghmSDTV0kbviAMzmoFRzeKiQ4LXcKIIbfRSxRCdZ0D1TOywj7xcxkfmzdmV_ndf3RxHd0iPDZOOkzQNXzs-efDk7PNf__K_-vQXdqAPPXiynDcQHBK6wFXsYru_u9knoK985Zlbt-7cPt8NpJrqrdt3n3zqkS985ssPPXTzfd_2rZfp4l__xM9_7N999OL80mFomplrOO-mcZiKlW6-dMyIaFikFGBfjGoRqabkPLujB64uHjk9PT5Zzma-VtntvJZxswM0ATOrKdfv-u4_-rnf-U1xEnz7x3_kB__J__snG0-Hj62KOCazw34RGDk43O43P_DH_vjzX_vaV57-KqAHIGUyhddCYwCHqrQhqAojGpEctGumxk5rbVYnoFprcofENntDYkJGTGM2w-AjHSC4CuiZnc9TcY5MQc20ioECIAo2XcPOazH2zogkF2THxIgMzAAkhuya5oETqoJEQE4MgAiZ12en4350PnTrJXoPIYqgKjCBd2Qlp3G6_dJLqZbYdsy-7We1yjBNi-MrJSfTGvsmDUlLJoqlvpbtQgQt47Wb13abqe36Mk1khMGxD7txG9sGfH3q5GQ1WxzNl_PonWgfIxmKiAEqwD_5Fx97w1OP3T2_d2N2-tADx0zGhOzRIakCEVcRdyBbAxAAI6GBAoiTfaZrAAEAAElEQVQqI4ECH9D-hxsIgh1qZAQEQEQHFZhjjI69I1QlosPTBHhwzlgVG4sMVbPIkHRMFR2JKAAY27SfPBMT5VxLEVVFgq5hT84T56yT1H0qRQxQEUjNqtaujTHQJlVVRTP0eHU2FxEkFMJpqtW0Ss0pz7qewIg4qTY-isLh-o4OQ9dsNgMZPjBfXOwHT3jl5AhyAjNBurqc5VI30xBat8_l5tHsfD-lktu-MatH83kt-YV750fzWeP9LhfvySHfXPckFpp4bzcNKbW9N0BDu0h53beTChIczfqAWGvdDMOs9_d2uxurRXRuEi2ophgb9-Ld84eun9wbxt6zY3xg1RPYfsgXY3r6-VuzWQNEQ6mv7PbdvL3Y7ed9s-67fUrJqiJIrrPG5VSGKS-8v3WxL6VcbgZAyFMigXFKWSo6R-wghDQkAJvNOlUrKlq15skQffDb3T5ED2QG5GPQKh7ZEZNZ18X1rI3eW8kXu5GZCkoVS0lccKVWA5v3rxkARNQR74bRs2PHRGBmRQyIplwPHGRAQEIzA-QQfE6pDX7edVLTvI2Eena8aJw7mnV2gDoxEGPbRAPLpXjvdvsRmF1oJtGvv3hnO5aLfW6iG8a6H0c27fq4Pu7uF_jqy5uX7u7v73fHR_O7l7vlfHbn_P5uP5JvlGU3pNa7O5f723cuzWCbh5rrsJ_QQ64JAQhsPN_PZiGNGcBVKci-TpP3vuzG_mjpvN_cuZA0IpmWggSaldnZOCJAs5yl820MIV2MCOCcM1Gto9VCGMHZIR4fYwsGZRxQrYxj17abi3vsGnbhxpseLVPNu8l5KAqXFxfv-Y73LH3AlF9-8aV3vOuN-4v7b3zTG37hFz_25a98_ejqyXp1ZZyGq1fPfvkjHxunlNHOHnvwxeeff_CRm994_vmHH3lQYvjoL_3yrTt3g7Mb1x984evPL0-WrvPHJ0e3X3wpp2na7Emybxtj4hDn816HS66ZV099uwLGtpVpFJXF8SkiKuCwPbSXoJnPiND7AGJlP4ghEpeSEWgaxmm_jV0X-wU7drE5jE9SGn1sTGoRycO-Pzod7l8QYegXUgWJfBMBSdWIPSmoyPzqWbrYmpWas_PeTKxUcoGI61Q5emLHjFi1plGk1jRVIurns9WJ6-aXL96OXYQqRJGDY88qallExCGFvo1NKFNBTwREjqaLTb9cMnAeUnu0mi1XrulNREpC0zpNzNQvT0othIBmOZXQtJ4dhjgNWxdbF2KeCqj4NtYpk_c-tJYyMpVcFIhj6_s5MjjQOm3FsFksQmiLas2JfSTEWjMeQJmghwcTVQBBcmH2jrCk0dJYam0XR4razJalShqGpu3KVNQkdDM0MMRaxmY2PxSp2Te-a4_OTtJ-aJomdi0xa1Um18au1LxczTnGnKvW7ENDYuiobbsY2lrz6QPrbr42c1ank-tXiPmJtzyJQ3nTUw_fuHrSR16tl6-7fvrEgw8P4xhdfO6lF4f9dIiI9YvlsNkQUr8-Ob9zTp4UoebM3peU26Nl2e6xiFWt20m0-kUn1W23O3Y-Llf73TY2PZhJLmQASECEZlpFS4mzuaaC3huI87Gm7ENw7AHZhVhLBTtkxA0M3KyFnEHNRNTMh5mKIahJ1VrdbHkgjRwMTYQIIobg5ktUc84N55v5jQfKsEcDrJWZJBffdCZK7hB5Iq21m81BhNiJ5GY-A4GUCwVnYAiAiiHE4Nj5xnvy5IBwMw6-iSZCQAaVohNUVAZTxw6Q2DMjmVlsG1FT1ZprZI5IJtgd7opEJafDcZaYEPBwi855Wsznqpim6aAtY3RSKxpJMURDgjDrp_0EqMhoBiq17xaH0_847AGw69qaMzHXWkKIKtJ1nRmUUtJU2WHTzVXFtBLSgaQZmo7RGFmkatXFfJaLhOg1VRUN0TvntAoR1lQPpNq-72pVMNOUm65LVZjBamXvyTkO_rV0sgHhgfNbraoaBBcN1NQ8IiExEiKJaNc0ksUbZFEkAq1901Y1IvTEATjV4hwhgXN8GJcS4y6PfdswIog5BvZcijCjD15EERgQYgygqmqOnZYSY2S21uOqDU-cdA45GD68DAUsEhPB7c3ucy_dqVPJY50t19_6xtd_3zue8rX51V_8zD_4yU_-wkc-8duf_eKXn30uqTgMU5bf_s3Pvnr77nMvvgghhM7def7lBgEET9enb3vPO7_w2c9_9Gd-bbfZOR-6eWd5evH5-2yYx9q3Lar78__t__nNTz72O7_xa3K-O7t5mgs0jV-uj9enV9dn164-_OD5nVf3tzfbV25fvvrSxd079e4LtUIbGnMG5hR9e3T8-jc98fu_-WnX4eOve-Ktb33yIx_5WOucgqZhct7FNqqJGUXvPQEA7oftd3_fh--_dOf3vvB5EdSqvm1LKaUWJLRSyQyIapVDKsYAEIC8N0VjJMa0289PHph2l6IgZmUs5Mg3HRhww1qr1SpiYAYCdsi9eF9TQUAii7M5MpU0maqhkXstTkkhiIImcCEgMbkgpq6JoZ_ZWF0bVRDZubYhx-RiqZam7LvWx7YaWoxyb3Po7ElR1zZaiyfGmoeLe2Yy706LTU1_dP_OrYfe8rb9nVtALsR2GvboI-IBLFti8FrAN23NSiYN4343rI5PzaGZ9YvZG9_85Kuv3mqb-dWjxdminfZp3jcIVKuoZzH5yL_9XH_U3Hzsgc__7uf-vQ-8w2oVs1rVzHIVMzs8ffCHdV4Fq6JFTc0Q8LAFO6D6mZAJgVDBmCiwRwIgc4jBcXDoCBlRpKoBOyaklNJYtBwUvGqmeLkdD3zumpUdn82WIkIA0btqwMwqwgghuFokRp9EAeFin5kZCVWNGAnQs1MgQyhQm-BLTuu-ccTIPKRCTVNFUQEBpnG4slic74ZJ5BC7LaqjVFHTIiVNjFgZS00IcLpatoChcfs8rWbtlMpQilNk1GvzmYFVlfV8Xks5W8xq1d04zbrogIpCJFpEfzafLUIkR_eGiZgC-1wNzC72w9lsvp0ygF6Z9w5IVZCg8a5Cvb5Y9YG_8MptclyNPMMrd7ZHq9k05RARQW8sWwOI3j_36nk7nxVTM0Di0DQp51vnm7Mry-O2NYR72x0SajEf4_3LjZje3uwP1aZpGrvgRapKrVAymOdgZlL1oGBXVUauVUWq0WtwJyaWamrqg3cMaOiZu-hrkdPVovPceQIgJDIiBci5oMOcq6mRSdrnWd-YAUe3H5L3_sA_fc0cTZRTZSQRDc41zIERAR1iiF5qvXJ2NG53865hhpzkeD33CN4zkRumsWkCk5MqU66lllQLIbOPL7967_b5bpfK5XbYTyWleut8U1JVdftU726nr75wdxJZX52dHK_TLrHDTdmncapaLu7cralkqauTdZ0mM9vsxv04ENbx_uW0H1ANCpRd8s7lMWtKdcyX9y7aflamYdoMzjlEwpKnzc5EYuc1V0QMIeb9jmoFg5IrMVophKCloKEhEHKzWmitaGiGrmt804KVabN3nkPXEtqw3x9dOXr92980DXum-PTvfDY0xNw88OjNVd_0wQ_7XQz8wfd_8-Zis-xnv_LR32bEhx679qnf_Nx73_v2zebeF7_63Obe-cNveey5rz9LBR579NFrV6-u1qvP_vZnLl96RTTffOSR3TAcHR0__9wLb3n7U1_9_BekpP39C7SKDjj04NqH3vi2O09_XofsAvPV93woF2uaIFoAaUrVNY2Z1VJB5EAQB2Kp4r2jEF3TVlMRPTo-HbaXTd-LaC21mc1rqv1qXdN0QFznnGITwIWaJt80tU55HNr5XJRFlEKDYD4G33YiWtOwPLua91tCUhXnG8nVzDAEZDsw5JBj6DpGMwEfcXd5P_ZLyaWNPTduf_-WArmIzJ59nF1_0MpEDkMMZappvzdTUKxVmsWi1lzGvRj0x8s6TS7Oyzj0q_V4eWFg7HyVlHbbbnXC5A9x1jLum_mqTntgKKm085WPUQFAKoUoRUKYAZKU6iOpiRmUkptutji7sr-8l-shg4EuRORgUH07N61ixt4BkZSC7BCQnQcwROLYQi3OoZU8bDbN_GgYpnY2W14929w_58Cx76f9wNEfOnfdYq6iTd_GfrG5u1mtj33wgkZI7LibdYC2uHKEVXxoYj_30TlygBhWSxByjtZnaxf89mI6vX5y47HrDUM_n8_79mg-u3G0unG2_OMffq9M-uQj1yLByer43uXWN_5rz73SLHqOcXP_0pudXL16__45BcfB73ebtu1KLkjk2RuQayKIcPDsAweXhml2sibk4fK8CS34oLWKmkr1IUgVM3XOETlTRYCqxWqlENi5Uov3QUU4Nod5lYodBJOHibgPEZFAjR2KiI8t6GFCb-iQ2GkRIkTTw9RZAY0oxEaqahV2Hgi0ZOe4DhMRV6mhaw1MTUupyA4Im9gh036_966n4A81AKsaY1Q0QwrzmHJh5wgMiSgwe6pJrSoQH14HWiohHaLspVQ0QERmNMIxZTAgVUBNuRbEmst83k6liCoCghyc7VSnHHzI49Su5tN-REJ0RKaAVEthIHYsogCEDKqWJ3EEDqqU4oOrauSdlhqDr6UCkZkimhUj74nclBNTJWQwMoIqYgqOiZEll6ZpDcAUtKhvIxiKKjOjKKkhH2DmKrWAKiOhc3BgQx4mjuisVkQLMZgCH5JIqgig-lof9AB1QVNCrGIiikyvqQwUTTQgesRUFUSD45wzB29yeE9aLdU5NkAAc0gN836c-hhBtfHsiEtVsQPLGiN6IAqBmblhIoTgnGMkZhCJjbOiN44io-9CMLCK0PnATD74WQw3jvsrq77r2lkXms53fffQleUH3v3GP_Hhd_zg9753fXz8a7_zmeeeeeaFe_fuv_pqlanp--_47m9j0Tzsvvo7X2ia7g1veP3iweOf-xc_-41nnxfVpu2nfdqd78dd-SP_2Y9tX7zdHjV_-kd_-Hy6_-zvfeY93_yu7_7j38NFKLaPPPjGIpKmDBgRg-4vmyYsF100VNDWe_CdY5tqnq3n_nR99cFrf-HP_0cG-Jsf--S4Gf_q__6vWp5-9zOfS9NoCE3TGFkpeUoTIajVPJbYeBN96q1PBQi_83u_qwfmL4gB-S4aAiOJHRTTxp4PHyMiVlAwYOLDdx0wOhdznRxhCJ7YqVYfG6mCB74eIqgik1YFBEMIXYcMQKhFfdsdJgRlSodQnyh4H0PbO4eATgAMWIzsoP8NTg0VjGNTalUxagISxrY1ou39DYYm9G1ctrOjFYopmQgacWgCmmopVNN2c84-tN0KGSynaUibzZYdhbYvtTjHoEIIpgWZsxg7cuxCIEvmHB-dPWx1yEP97__WX2mK-8zv_8HRyeJ1N29cnA_z1hHAIDUbff3WvWefuwQq3_unvuPf_sSv_qk_8Z11qoaoVpnpcOYwNWIEIiUsqgfbPR4G_EBEhgCIdMiskSECOkfMzK-N-DEw_2E3AIiMCWP0Yrgf83aq5FgMdkPOVYtBPjzwRCLSN3EqWcwAXTUCoqqqZk3rc9EqdPdiu1p0uVqqYsgIwMhE5NghkGeuqqVUZqhVVv2cARzzxW4aUxHFKsUjm9qsbatIUhmGFEMYS51KRQACjMRJJHhvWpvYDGW6ebwW1Tvb3byNOeehZOexTnJlPQcEJKqlGMi67a2WsdbVvLu_26MqUe1De6WNgVwy-9KtO7OmAbPdmAxsm_Jx31-OA4DOgmMxBfWeJ8kC9azrIrtb57um8YiOGccxr5eL_TiGAE-cHvXOj1Mas56nOtVC7IkYmcpUwdF2Gq8tF73zxeTZO5dHy56IEG23nyDwvYsxNs1UaqmVDGuqaDCkKWAkA0IARhGrpXD0wFAkg0HNqfFRS2VPKkoEXdeKWQi-n7eMsJr3J-uOhhIix5aHsaRShyn7EMxs3E8--Bg8M4fANRVE3A2Tc0QIs7YBtZMHFpe3ByZ20RFCCK71WHI-ms98COM4OkZP1AVqgguOFvMuOKdVVO1iv-9jFLN54Grw4r1LQJv2pW3aIcu2lmIa-64Y3rp3gZ7vbfaz4_n93XC-GV-8fWki4346mTdlHBURnNy5GFMpm4vLnEoRKbleXm6571Kt0zC0XRzPt55AcnEEtaqxOXZSRXOOLmCZzORwlHUuuCaMFxdUKqhYzgf7naLJsGcR9AGYTApWlZxNhCOjGaND9mU_-BhELHadKYy7LQFiiF2_IE9lyteuPzA_Wt_6xu0Xn3mO2xkydKtV2_mHr1-_uzlfz_p3f9Mb7t29mwX_5S_-Ejo-H9JY0tUr1wj4S3_wte3lvunjAzeufuVzX_pjP_T92_OL68dXf-2jn7jz3HOrq6vnn7_17T_wR7702d9n0abp3_jWNzzz2c-VkktOChpiY87F2Wy6fxuGER0SRfaPvbObLcm71dUTMxUT34XV6WlN1QBCDJIyOtKkLnhuIhCzIyTaXWwXJ6sypZottK3VLNUUxTfd7PSK6-ezxbFURbCSc0ljiI0Ui_MlOuDYl2HyzDWJoXX9LO325BjAJCf-Q7GLqSAoxsCO8j6DI00TeVdzOgD7pvPz9dmNIY2Lo1MIroylTuXkkYfzsB83F00bmUIek2sjKnAIUrWWolrb-amBoEHeb5u2u_uNF30XiTC2M_IBgExMtWjNUjI1necAAOP2fH58VtPEsd1vt-Q9IZmZ1gxokkfuAiOYHN59JilJFSty7XVPbF65ZaAlp7aZm5ZSa6nT7PgKaD1QgAyREBAJilCIcDjPGshQCI3QyjTEtilqCNoujvabDZi1fdvM2nFIhEigi-VJSmPTtGRcTR97wxM159i0aZyu3zwruThyBLpYLhFs1rWhaTn6ftYF75brpSOdtV3fzjj4xvsnHrp67fT4aNZdXfXveurx1gXv-cbR4uh4hkqf_9ozuyE__fWXBpGxylSx7PZgZiqxa4DctB3a2cLAiLBM2cy01Ga-VMhoh5a5oJqyR0BLxTUxNo0RNH03jRlBNQk5ZyqvjbIIibCKkgsm0p9cKZtdN2vRBUPyjlGBvNNS6LUQQjBTrYIAVdQ3XUkJ4dAZBVPTWh2Rc-4wnTRV3_R26JyR5Wmk2GspUCuIInOp4vsekQTUh6AqzoVShBvfdt24261Oj3IZAQAMa8mh78exNG0DSI54sWwRmTmkaer6XkUZgSMZ6AFAaqKHtzU4hprbrgcwA0tpaqMX00N0BE09mQDUKiE4Jldz5cNGv0hFQGZmQjATc84BAHg6QP0EIDQNgsmUiTlPY4xdGVMzX-AhRJKnmtPi-DhNGcxqLc2yFxUfIyPolFUNHTsXai6HaSSCGhjFYAiBXU1JqsZZC0RpGhkEDSAEQTUDAACVg40OoyMgEEFGdA7R0FCquOh8E1QMgLSWnIv3IdVyoOZ4R8QMjO5QizQ5mIAPf9zQqlUAFVUOrlYLjlSVmJoQQKGqhuC74KqIMYKhKpBjMyBGQSBixsPtBbvoHQKoSjUXmJgJzBN1LT-8jvPoIh1cqUqIRIQGZIBMhOTBO2QUs2reBQMEgmxYDK4cH3__d7zve9_9rb_76a-2q9W73vzk77107xtPPz1uzjtu7m-2129e_-APvPuf_N1_dX5-x3ni0IyJVeUNb3njXsY3P_a6D_zAd3z3t77nF37-5-bz2d1nn_2WD3zLeGdDGF66f5_jrLf4lre9-8qy327unc7clWuPb3Z37m4uTq9f5Tbeu5A3v_dbf_CH_9j7P_SB3UV-6m1vv37Wjhe7T3_lKycnR3_qx77vv_-__q-b8zvRRyK0qaYpS9XV6XpxtH7wiZuPPfn6t7_zHS9-_ek47598_Tf96m98TEUBiRwfWJMKKmYUgpmgAqqhgRmwC4fyNAIaACBMabc8Ohv3ezBjChXMAGPbIrGaSi3snBrUUtkfrvgHMbY5FxFUUzlc_ZxjZnIhAEDJEyAik9oBjObIMRA3XYtIOVsqNfQdEYNUdnAQ9tWSQwx5mqZdBqU464OPvu-KgbHTXB35QxsaoaLKtNsCEQL08_X8-AwApmHfxKbtuppGUEBRZO9cEDIQ65azu9-4dfbkQ9vN3RCCQ_7OD7xDtCmb3SduT9_82M3ze5voXRLk4Lel_runv_rFX3n6lRfvfN_3v_9nPvvpH_7QNw_byoyvIVUP1C0ECliLqYoZGACa8SG4ZnrwASOhoB5ibEjAhA17BUOtzjlHjGBoEjy20TNTVU1FL3Ntoi9iYjiU5BtXqymSGqgporXe5VJLUTXaTmnKQkgiyoCbfU7FNvsJmGqxoUi1w-VE2aE7oBIRFRFMCamNPrIPCN75YjDVKmYiVbQCUGCXS2bf7Iexj3E7pakUREQzVUWt7DwYBBdKLo9fvZJKudwOy1mXtDo-MMXt4avr8-1eVI3AMy58WLbN-XYi5svtdt7PprR_26MPzVxAtVc2W9d4QiemY5Zispi1bQiOUbWs-74P3shi9Hcuzx-7dtq7JjLfniY1LBWr6n43CCqi7cv4-tNjFgHEFy53Q9VdyskkNtEDbYe8T7lp4wNHi0guSS1SiH3XuIt7l0aURO5ebr2jYT-VWkqqrCpFNmWYxVnjemSoomBIaAfhTKCw3e3b0DS-6Zr2ELpF01y0bfu28Xk7Nt71rVsveygmpJuLQRF2KSOQqTnHSha9B3QH7PaibwHJCFVVzRxzZJf3mRiJgAlnXXN2suyiO17Om-g3uyE4N-9iZMeqs76dd60PLKXmkgmwi57AGLGK7odJGRZ9j4xV69dfuptFZ6v2YpeLWGzj5cW4Olncunt_ty9DTkh49ezo6KjfpzRl203l9vnm_HJwbeR5ByYlZaADgQJEK4hd3j5fXjkZt1sUITLwzMFbrXWcLFepBaFqrt1qPW42pKnsBk2ppoqoaApMrm3ydoCawDQs1mWcQmDK5bDbVFVEJA4IksbMIfiubbtOckYwJF5eOcnjZICL9bJpule_8aqCDWMxssff9HrH9pY3f9NqFi5u3fnu978n-Lif8vmUL3b7EWp15Jv25Gjtu_j5P_jy1bN17JueWvJ-uVzN-_be_vL3P_lborWa_tk_9xef-dIXvvh7Xzs9Pf0j3_2hn_6nP-GZSy4c2RQQ3W6YlsvT3SvfAMFS3Qd_7M_w7A3fvFzNcqnjPl27en21Ot6cnwePvmlqrbPFnBtXcw1Nx46BXJWahWSos1Vvf9jnO3_1Fnm3PltP26lKnlJhci44IPZNT8GVKmDKXZN2WxfbWtREQt9w4DJmRJitj89v3ZkdH0spegj8inSztamUScJ8DVClViawmo0IANu2Ma3nd15ZXLmSpfaz1Ww5z2m8_cJLs-UMtQwXQ7da1SmpgY9NHjMSdIv-kAJZnVwJXZeHIZeyOF6n7Yacd86VXGstTT8vqaokJJJUXAixWZB3-_0WfDTU2HSIDj0ih2lITGSqZSq-iSKmYoZKagAmtQy73enDT-RhW0qRmhh5tlinNEhNTZw5cqUUQDsMucl5yfkAi0RiP-8RScfJRLUOKEXRd7O-7fpcqhlUZUJjR2mfDAyd9yE0beOcH6fUtZ2PoZt3w2aMTX95f3fjwbP5os_TROSWq_kjr3-0ptq2vnXsyfXBP3Bz3QZsPa8bzypX1v0bHz07noXTRdcxdY5A7O52v9tP59thSPXqjavPP39LkdJ-60ydi8MwnD1w_fL8wkTIlIgOKw4OLm323nuVCkBxfiRSNaduOdNavXdVxbMPjT-4g1zjwFSLHCh3hKRmRETIWmvbdGACYFJqaBopiYkRAMFEKhBrFRcCEyogxWBajQwAgQgV-vWJSFJTBIRqRM6k2mGcTI69O-S1vCdEYELJiZ2vUpFDTSm2PYFBLcQuNp1WNRNPLoSmmogoKdQi5MxUCcFHDwoxNgQYg1eREKnmisZkSKpwkPcwqSgxsXMo0v7hOs6HwIRVhcgzUxsbIgA0zeYICbRkJc9IUKoAIprOF_NcZDHrwFMV9eSrFQRLk3RNzKmYChFIEY6u5tzErpQyn_fDdt_0c5NapEpVRFARDo1jZKKqhmpd09SDThjQTNEsF236FkUQAMA8MxIRE6gRY8nZO3d4cROxIzMk5xsyJSBG59ghGqgaEwERHAAwhGhSJQZfazE7jJoJiT06VGAkM2jYS5XXXGqApVQ1-UOaKxICE1mByOHgS27YsZoR51IOqwbnqAs-FamHMiMDGzJSH-OUc2SeNcF7JjSHEL1rols3kQwPGxtQ9ewQ0ERNjQEYyB0kTETOIRkAikM2A_carwp2UL7tvW_75qeeBGzXy9n85PjFV186Oz19-aVb7_zgN__f_-bf3m_2JsU5pzT_lg9_54f-6Hf-1kd-_r_6W__d1z7_u5bhH_1_f-LZp5_52vPPrpr5l7_w9Hve9c7dsBVn2_Hy2z70g7_xWx_99Y_-8t27L77w9PNf_-oX76XN3_kf_va73v-BbnX8Qz_2Iw7N0P6nv__3V-vTbRpvXr3xfT_0_t_91Oe_-3v-yI2jxU_97K8EhaSUlc9Olu_8zne973ve9cCNB1PREcur33jx2S9-paKScx_8ru_6xZ_7SFEtkzjvEVmlGqKJIKJjbmdzcsyOidkMTFS1gvNWhBwD0DjslkdX0rQ3M0YjojJO3jupknNSRCJ20SM5QCCmWis5LjkheSKsUpiciBGQiIqqQ1KRmquqATOib46WBFjBVEEQyAWoxQVyYuTo4uWXZBzbWcfEPvTtsh_PN4vlMnSdWT14zbrVzCOUKSsAqhKwpAGYay4uxuC8DxGZtheXBsoGsWn9clWn5Bo37Ufn4vHDV-4--wpFn4fcdjHGcHlZrz_x-Fc__6UPveXJ5axhdi8P-2fOd5_87Ff-7t_9qdu3Ls7a5i_8lR9431sfffkrr37p2Zfe8aaHqwEBiJjoa8LsA9NfxcwO35B4gIEekE3IrxFZEdBUifDQ0yV4rdmCTJ4pemqjd0QAFqIXQmKuYoyEAEeLZlJIxZLqbjeIqEd0zoFncZRq3Y_ZDJLUiHS5T9UwqylCEe2asE_JDMzEM6sIgjGhiqqa0eGrpSxnXYMEiJNIUkipMqOKOOLGexQQolJK24WiVoo6T3boBhoCmGNPZpXSEzeuDtM45el0uZhynnXN5bR7y82z1nkFuL_bNcEj6pX5smn8C3fv97N-sx8W83Y_7p584KxFdt79we3bhlgFpAg6t-haB7hq2ynneR9nIQTiKVfvWaCe9bPGeTIe1CrobjsOUwKRxWIBrI-dHl3rmqEUQ_vqnftIfqjVE6MaiJyPOZvEGFdNBEGhuq91GvK8by4udrFtNkOeqqzm3XaXFAyqWa4c_HYYe98R6kHrRvTaP9c7z_gaLw4RkKCQmggatE0sOS1CKFPpo-_bFpEqlymV8_u72Xyx3U-qwsxN8FrVEXddQOTD6xsJDqVHMzldzEsVlRp9DH0E07aJhx65c05UFUG1zuddmtLx8cJ7DyoEYMTDOHjn0LAaiMgoRo1nw1KgFL11sauOkMNmn-9dDOfbXSp5HEtsw8t3tstFAIQ20rgfpyk_f-vi9r2LsZYpJUBNWutU5rMZkJMp6ZBkEq0ARSSX6eKCSjE1HaTuJte4mkqZEkjBw5hAJA17F_6wZ-jY0EyBAEzRN1GmwUTMEFQEFMwIQKuqVGYq-7FZzOs4ucPJgaPUKlKZ2BCbvhNRFXj4rW945flvmOhmtz8-OTk-O3bsqKR3vP2Nv_nJT3_7O996_Xh1vk8f-8znzku-d--eGZZsjt1iPrtz-9x7Fx2NqTTRP_rYQ1oFGH72n_3MrIsX93d_9H_7J2ve_rtf_Dh6fuKJx-_devney6_utpdsSKbsPHLTzRcybvJucv3sXT_4bZtbL_PN9_3gkNKs67fbQaTkUubrFRO3PjrvL-_dRwMVtaq7VNq-xyYoQbdcjueXR2cnaZzavmsWXZ5K2g5XHrm-v3PunZU0XZzfjrPe9yFX7RZXOARQQjAkdMG13UxrBUTv_Wa7AYR-uSop9atTSclyIkbN2cW-SkEA5EDkEBBEzRRMUA1VVOr-_jkALc6uy7iP81kz7-48842un-eaNi-_Gs-OoGJJGcm842k_tMslu5CnUVVWV64y2P7iwjFrKsNu061Oa07cNXE-AyOV0s3n48UGPPSLNXuHgLWKobkQXNMpSNP3OecQo_MOCNl7UAGphuhjU1Mh7y_O7_rYHp_d2N2_U2oB0OOTBy7P75hWjpGJfWwPkHV3ABfWaoYw68RI5ZBl9XU7xpbyZrO53HTHS-ebQhTamLZD8K7p--FyF2LY7_bNfBGCCz7sdvuzB670TadI7Gm17Gd903nftWG1XkrRNAyzWTOftcfrNak-evPsaNGsF73u09l61Xt35Wh2tGx752YxaKmOaLsbXrh9ce9yUOfu3ttOtZzvplKmabdFVc_koie00DZE1DRNTsnNOwSxLKbCgQEcEJgJonkOZRiuvf7Jza1Xjq7fKGkCg_nJ0bQb05S8d2BKiHwIMZoiOxVr5r2UHLveeYcIy-O1QzMFZHZ9BFWrgo6A0LUNmCGTQz65fvXi3uVssQSyvL-MfadZ0MhEAYFcVDAOIfiQxqnmvL7x4LDdMTtJpZt3gIxELgSpGUp2TWelECI7R-QJIefk2g4IAQhEAQHISZWj0yMrRQGbrmFidg4UyRGCShFA8I0DBFCcSiVm572pqch6NTvIMtOUnWeHWHMxtjaGxWKdxlJNfB_qa5h8JUBmqlW72SLl1LcdM4CY5Cq1jLvUtE0ai_OHcAUwUgUhYjALbc9MqiK1IgMCHsA-IEpM0bVkEEKTpgQggEbBW1FUUFU-nNIUnGMwFdHQBDETFc0FFHwI3jtA0lqKlkOm20W2qmgqqC4cOJuKZojAzh1QJUg0DmOMoYqoaKk1thHUiLCWejgR9m1QETADABeIkRwQADrHTOiYzczIQjxYrtUFJkcHTCQYSLHDRUsUU8pNjAAGYG0TvCcm6pvoEBukUooPDgxmi3besofXHLdTVecJwA6EIEM8hLjUgNEIX7P1MRwGsUgGh_aYpPL3fu1XP_jWt4yYsQ0v3b33xKOP_sHv_wFXfeaZ553HUuzo-unpE1de-PwXh_vPvPnt36TT9g1PvPFXfvnXP__5r8Oy6ZZX7in96k_-7Cc_-9FrV64u5rO75_f-_t_7f9z6yjMwZfDhx__if_2eDz75Yz_2w7_-iU987c4rf_pH_-TP_OQ_-9IffOEzv_3b3_Jt72sMbt-6_e3vfs9qNf-Zf_uxP_Mf_uD-4vwXfvqj6_Xpn_nx7_qBP_v23_v0iy-9-NxnPvmFz_7279979S6OIiMOe7l682wYhg99z4d_-ed-OeeEyOQdER40oqZGKsxUUgI0EzNEq2JwMHEBudCtVnXcM1hoWlWTkkxBpgkQc8ndYk0x5JzYDJFrllqrVVMRK6pw8AojcTiAdMkxGbFztRZ2HggpNIbgm5aDr-UALsdDrYgZdKoh-DrtaBoh76f9pW-Cn5-YZEu169u8H6YhN_M5-5DO76fNtpmvuG3NlAApBKkVkSRN47hbnJ5E3xoBAE2bS9-0w8V9E51SIseIPq5WJNX1jTNAsTKmr3z5uSff8vr9ZXr3N781oq6u0F_7f_7Dj__857_6uRcfvbF49_ue-vEf-eDNh09jQ__x3_xHf_1PfmhxtEAtenBHGjIdqLWHxhOAqneOX7s4IyKK2UEyafqa_8sREaFjRAN2GJ1rQgiegsNDyZsJp6J392Wf6zCWajYPXhQudiVXKSbeea0KZou-qWL7qezGcqiG-8Decy5WBCogEaZS2ibmVEXtwHfyTETkiRUNkAQsBiawZezQKhPd2Q7FDIwMlAEccQhcREqWEHyaMiLvx8SAqRRm55D0NciSVS1PPnR1zGk37B86O9oMe0Z8ZXvx5geugNjd3W5fSvQ-5_Ha8cobvHxxOZ_1WcR7YNbHj88Onenb2z37CMBTSY2PbRugZEd8vtm2no5nvSNGs4v9bjPsHzlaB_ZDqi_e30y5TFMVEcccY0C268vl3Lt7lyMAme-y2GYYFq1fOzbQ-0mYeUr52rK3Us93-7FU75xnGnYDuXBvs5-merzu797bmoJlBQAgzFMmZzHGJAUIasrEXEplRkOotVaoTdcgYy41pYxgauaYnGcC6No2tGEc0vZyO6WURWLTDGkyVWRumnBATeVSmSkPEzESsoiUKYlq38dxGGN0SFj1gIxVAupiqKr7YQCAo6N542m9XMTIjrDk6qKXWgGUvdvtJudIzXY5m7lcCgK9_OpFRa8A9y-32yG5EFzjVGw2a8f9BI5EdLPJ7ay_v93u9mlM2TcBCNBhHnMapmbWShUXTMeUNoOhcXAUvIk6JsnCjN4Te2QlYq65AjKpNEcz2I9WdXF2Nl5cokn0PuUJVY3Qe1_zVNPkXPDOl1QcOTKRcQLQ15Qn7PGQs2V2bSSkWhKzz9MY2nbc7Zu2I6bh8jJtx9lqGWO8-vD1-6--fH55uVwsxs3lB97xliduPkAqX33h9heffhqdvvLiKz76e6_cefx1jyxn881mN-3TYjaLXbdYLo_Xi_uXF8994ekp79MkH_6h779yPP83P_XvusXs9NrJk2987DOf-K2Le3fnq2UaR0ZE59F31x54YH_3zur0dHn9Zq32hU9_ifHhb97u8-nV1fpkvdtuHfsp58V8ud1s5_N5bJthmI7Pjg0xNM1i3otY7CJqnR8t6jj62Oz3o29nTYwqteySVtNqpMZgZbcbL7fdYgEg3WzGMfi2lVqRaTZbSK1x0YsUAs6ptvOVFq05-baTnEFVAQBVwZgdhoCvYfINRKyIAYBSs1wxS57G_eVmdfPmvTsX865fXTm59Y3nF-v14uoDMo6z9VEtWUBKrrP1-uLOHVNZnFwDk93FdnF6nUFFxHuXSpU8NvPltEttN2uXi2k_1pzDrNdapIgZL49u-ug2l5fsuObiQpumfWh6FdFaQM3Umn6OUGs1MwXnmNF5LqkA2XxxWvK-pJLytusWaUx0-EYH9M0MSE1qrQJE6D3HEGYd4WFGrBQCGjs2T5i329D2osrez5br-xc7Yop9NCkxtGmqy-tnPnrVmrOayWq9QkZDVqnTfjo6XjYxhNbPZ93cu0UfHVkf_UNXVy3xtB8eunbUe1j0zbWT-cy7PgSHYAbG8PXnX37h9iYZ9MfrkuXWrXtx2d5-4U7jKTr2weecS5Wm62oupoDk6lQhF9_4UiqiM8RuPa9jEsWm7a0e5vKQttt2sZQiJsrOaxFEcMxaxQxmRyszAEIOHghj04jI6vREqkyDPf74W4ftPXS-DpWDJ2ZTRYPDoQsUybk2eB_DOAxs5FTJRwWTouTZKrgmILGAIdn6-Gx7_z5570JEojSMoARiompgMTR5SnYQuxILoIsekcdh7OeLKiICCNC2fU2FgAC0mfUlZe8dI_rgCczEmNwko-OgWX30YOCCI2KPwIERMSWNbTAQAYjeQ6mCoGYI7Al88GNKCoQMpkbeO8TgPB2giqoqQuSQ4LXpTt8QWNPFNEweXZXcd_P9fgiRzEBNHVHT9WMqNaf5-lgOm_2U0cxEQmTDQxEipqEcNjkI6EOstaCqD15L8THkKcWmrWCH2JKJmIpzHgkAseQagstj4tCaSa1FDJG9qKioAqhqDFHBSpWmjbUKAqBzuVZmZmIkq0UMQQBrVe9dFgE4nDNZaj10MZEJxJwLB_cGeVeKEFEqxu614DI7JiLnHQDkqkzECD4EYu37hhVEJXrXN8571GqI6Jg65s55hkMYAYoeti5ISIdV1UHOfWDi4yH4ZIdfoxm8tt4D8A5-45c-_sTDD_fzNtd6uUlXTo7yfvOlLz9_5ebJSy--9Pjr33h5cfme973viSevP_HEY9_y3m9DZ__oJ_71e9_11Hd9x7v-k3__e7_tg9_6XU-94XMvfuGxB1_3qd_9jfXi5PWPPnHjkdefD9O3_JFv_z_8uT978kD3ukcf-tSnPwXd6k1Pvu1v_Od_7d79e3_5z_3VvputOjfcuffYQ4-87sbRP_3Jn9xtyvu_863_-X_xt-puNz9efPITX_zpf_yp_cXl5eUWMt988KFv__CHn3j7m7t599iTj89n_NKLz3_bBz74m5_8zd1-X6uCwQH4IqJgRmaSSy2ZAJGJmEvKgFprlSpMXNLEhAY2jcPy6HTY74nQx8hMZKAgxOGQ6gFkAGPPUtW3ET0jAfsDmIhECzk2xXC8sFxrraqGPoiICy0A15RNIc57UzrsiIgJzSjQdH6OKKYFtZZS2pMHjVlSmsaCoYmLHgGcJ93tUCSP4_U3vSFlBe-RvRrM54sqtYoNF_cRoxouFl23Prlz61VUaBdr8uBiCN5r2tfDeQMNik7TUE3tKLzlA29p-vn_5W_8v_7hP_3tzZ3t93zwTf_Jj_973_nhdz_x4BUL8SLXv_m3_-nrrp79Bz_6fplKEZNDLQdRDVQBCfSA7Cd8je5_4KwCqBkhHfR2YECIyOiYCAFRG-_76BwBmTrm6F0Tw1DkzuUwllLFqmg1c8Hf2Y73tsOwGxXQOa9oyNh4N0y5iE1JEMgAPFMgNwmMtVZVEUEmcogAgqhm3ntE7NtQq-1LBiQ1CA5V65XZ3AMbwMWYgHFImRA9c-_DNE0VabPbXzla3T3fus5vh4yEU8kheASYpgxAgVlZXv_A2W4cNrvxodPj2_c35PjrF5v3XD_J4l7d7M0kBufIHj46Sbm-cP9-G4OIIum6ax-YLwEglfLVW3dmi_mQ8pTSuu_H_UBoKuoYrqzmDXLKUqRkq8fzfhWakmsBeu72OaAhO_au65pXb931nh88WiOiVFsfze8OpVZTwpvrxTjVTZLtOHnPTeC5d4Bw93ybQAmocYxAuyHf3-4RnJqOUzJTVBWDCjpO2TcxF0UjDqxVCaBoCTEY0JiSqTahAaWURkfomUMIChpCIEbvCByXPE3DVNXEeD9NQOA8I7MjV1VSLaJCAE30BAfHDxBSNembqGLdvAnRpzEzY3AkYoB2cbFlolkXHFEbo3cOVQJS0zSqVatW0ZSrAuRU7u73wfn9dkrFLvZJCLKV3ZTOL4bgXUp5v5_SVIPhUEuRUgwUdJym832qKr7lWmV3uTOzREJM-3E8v9jst6mdxWbWD7tEwQNSyaIlx36WxlGqkAuSa2yCKDRdU6ZB9wOLaK3jfjc7O9vtLtEoNH3NmVsPhpIrJbVDmUUKOpCxgGQCq1YRCckzglZx0aWp-K43tVqmA07DOQo-lmmKfezni-X6mJG3m8u-b2eL2esffXhz99V3vvkNbeDfefrZT_7-H9y7d_-VF-5klZzKbDl7wxse-eLTz7_6yr3lql2ezNN-V1J5-MEHf-9zn_vKV7_quH3nu972tje-_md_6iNhEbHi-z74zl__pV-b7m9NU8lTrhkAfNuePP7QeP9yuBwef-tbp2H74ue_Gmrm9Zs-0AY3TpOBxq4PTas1S0nr5epyc79vZ808ohJ5Xsz7WioHWK9naTLnnCG2_RzQaqm1FOdc2_WIaqpIgOwdkGOYLjbj5UDBcWhENU9TnkpoXDufn9-7jIt5bCKTk5KdZ6kCRKGZqSgeqMhifjYzQkDKw-C8I0NUZWYAKKlItdl6Zjnfe-ml9fpqlQRQV2cPXty55RB904zby-XZGXLIU85pDKFxkco4lJRF5PLerXa2UFHXRuddFiGktusNFX1cHZ2JaRomYo4-SC4p7di7fnF0GG55F0Izm9I-Nq2ZolYTKSU3y2M4dDTREEirIFFOadjvZ8uj4JyB1jQAgA-RAQ5AxGbWKSAgm6kPoW73Vg3ZtWdHNomBkXvtgffs0ubcN1GJDW22WtVSvA85VSSYHx0hiop0i5WZzmZd07r5YkmM8749PlqEwI13y1nz2OPXG7Brx8vO0UPXjq6tZ-s2PvLgScS6nvfLNgS2ln0bPBGK2FRqEs5IU9WXX7rrZm30UIeSp-Q9NW2cr1chtMN-Wh0vU85N2wGgVQ0OY-fJOccBmdsQfWzaZY9q7aIf9_voggC0XWNVm1kjpYSuBaAyJnbOBZ-GiZqoYkgc-z5Ppen6bta07TwEjzT2s87HaEyS82vDLrNuviDBN33bm2Gbxt1-Nl-WXBGMmDB4dl6rOOd8cEAoohiCGapUYBaT0PeI5JyHKjVNvvFaBdDIOZHqQtCSnG9EhBiIYNxczFcnhspMtWRCcMTVFNFF70nMtc4TN94H7xTRe-fJIRsDsaOSRaTGvqlJyBMT931rgIY67Hazrl-sF-OYHGHTN0jASEWkbWIphYhVDU3NLHZt1YoA7SwSuxgbUK1pmq1mRGG_2fkYqgqizueL7cUmtl2eEjCGNrZNm8cppeJnwaSCgVVhRNcENSRiFEEwcIDE5F2eEgIaKJHru66k5L0bp2GxOsopI1KeEpL52AbypQoT5DGH1oua976qClgI5IgV4RAPBibmMFZxDlGN0KoIMqOJVYlNA-jMlBi993nK8zZOtcIBHAWIBFmqY2dgIThV84HZ8OCKQ8eM4L1LRdgTEzEhMOZS3eFnwBh8H5kUpWrX-cAOFAsoOyazGJ1HBBNkEkM1UMAqZgeIIoCBHWIZh_msmB6M01XMDuAkAzP10a-Omy9_7cUHb15vOv_s577adnF549rXP_fsC889C0m48Y8--tDTzzz_0CMPr5v2gSsnLz__suf4hWe--k3vf9fsxpvf-NiNs9MHfv2zv7fb7ndpCtS8fOfVXdo99sbXv_dtb2yXi0nzDOmLX33x45_43Z_-5_9mfe3kP_zxv_Abv_qRWy8_692Yh_GJx2488fiT__Tf_vp_8IMf0jH_-kc_vloun_3GSyjSr7t-PnvLO556_x_9jjc_9aaPf-qjX_z933vmK1975RsvvvrKrVryB779O5792jO3bt8BcBidHm48nkHEVBExei-mJRdVbY-OKXoE1867WqpjMhNDsJSryXx-PI07U1PREFswVa2ECKaIzOTJh26xLiVLUatK7KwKipYshOxnLaiCGMWgaohsAD42wFhLMUQkpwrEZGZk7GOQPJbLrWvIqhoSq2seuobAl6-80q8XcTnb7zYm0K3nu1dvoyE552b96vTa6rFHh82u7Idcymy5bvq5me1355br0dVrpeZ2dULM036Hqu1qubvYMdvy-FhAkEizIFnTzV786q2vferLP_NTvxKi_B__yx_-yz_yvW9886Nx1hXTe0P-lV__7f_bP_mZH3zf2__aj3xYipWcxRQQzbSIEREDMJIqHmoogdgQRPRQ8D1ImAHAEROCD-wdBGYxjcE1IThClapq3jE7UoV9ke2UMXhBFAVVG1LajoJMXdvMls041aP1Ipq0IZ4PU6mWRJBRqs3a6JCmWi-n7JBzFUJwSI0PRdTQHCAitE1AsO1UuhAY0TNkyQ8uVgYKZhcpVcCqKFqsyKJvpUo1uLvdnB0tLy734HiYqoEOaQrOEVPJpfPeEWlNb3joek7lUsrN1XK7GyvqY_PmeLHaDemFe_d88ESQ0_DI6RWtCJ7HUsyo2vjgcnmlnyFRMdlXaJtQBcY8Xp0vssh63hGS99gHT2aGNExpkPG47-Y-MrtXt7sC7LuwXnTL1fzu3fOTKyeq5eq8f-X2-fG8r2x3NlNVGcf0wLLfZr3YjxWg1nplOQ9Epciu5CFl733jHBhtcr7c7prQxDbsx9QQlctcVMFzSsUH5wPLWH2g_T4pSeTgHA9TJgDvfRPY1FIqWrUJEQ1AKpp5x8E5BqolsfOpqI-cU02lzPuO1ILj6BwRjNPYxnCAZqKBZ_KeTbFvGwQMkdJUh3HqugYMD9goHz0izhadFQ3B15JrFiOoWmu1YUymRuxULed6Z5vX81YMqloyGYexSIUW7YAaUHNEUvPlfrrcj8Vwtx_Is6iOeQLCbtkXLUfXjyDWilgFTcy0-OAVMFUBB0BWx-T6Bh0WyaDgvDNVAivT5KIP3mGtJgIGRJSmijEiQBpTCGG82LjgTLROmVA8Y60ViUEBayW1Ugv56LuWzMqYvHM-eKk1dG3Nk07JBV9Lcq5pu3bcDxybxWpVazm_fWvYba9cu47OYov__oe_4_pR-42L4Zc_9bsiIxptXrz_xve97WK3C7F7_HWPfP2rL7_1TY_Ou-V-rOP24q1vevPLLz7_9NPPNcvV937Phx-5dvb0M1_50leeO7lxlS1fWbQvPPvS7ZdeIZUQgpkeDtjz5eL85fOjGyft2fFLn_mcj352tOar7_4whXZ3574PTa1Sa_Y-bja7GKlr2yrZIVeVJnoFIsdZMGVdny4Php3g_AEPTQjALqfSzDogUwDJGZ2XIk3fsAMphQCNwJEtTk52m71jDm1XpwmNYt-BGjonZlKUiNrZMu13SEzBYXBgEBfzkjJIdSEYAqjhoZUVQs0iKTu2i5eeW6xWU0HvMXbr-3duq5b95V5UfTcjcqHrCWHcTSpVSl2sjgjL5v5llVqrztansYnjtAdEAYzNHACbbjY_urLdbc3Ax5BzAiMfY-i6NCYg1VLZNSrFDucjdmpYU3ExOOe0KgUvaoDGRExU0lizrE7OTERR8zgiu6bpCO012HwfAEheW3KjKGC1uOhNBMn5-bymigete01lmFw_axrnnD8oclzboFVmj0Z5HNmx874Nvu-7vvGnR_NZ15ZxaB0vYoiOV12cd-7K8az32DB5IrSahrKadY5QSp13DeGhTwZ3728yuv1UYuyK6moRb79wN-3HJjbIPO6mWtVH74NfrtcpZyliSLVUTyYVu-VRt1xoKd6TigUfTx55SCV3qz4XwarjZtN1qzqk2LVScmgbQ3DRkw9aqm9C7DwCGVHwfOXa2bxrmCk4fOKJR0rOB0lm2x0-zDX0rWeKTdOif_cH3vXq0y_6SNv9YIg5ixr7roVaaxX03gCVjL0TA1ObreYmYKI-NioSmoaYRaqUQszEZABoyuylZh-8D877qABNG8lQTbSqiwHIDrbatgkQoCRo-ugQWLnxjKrIhIoKBmAheEMsqSz6Zhwmcr7xwTGBqmMWtTQOr7v54O1798mon80RdUoF1TySGSKaIgBQqSXGICrsfeND9H6xDHnMZmSohFwlqUIpho58E3LOzCSl9rO5mRK7WrR13qygGQJUqSYW21Zymi2WtRZk1GLsUKEioRnmsTSLzkpWVTMIwTOxiqKJgVmREEMWIU-lFk-ezBwTAJiYI0QAFYvelVKkamw9mDITmPVNGMaCIoFZqoiZb0LNAgotOzTznsmUHEspCBC9G5OQQxXzzFrFITlmVEPEKtUhtiFOuSJgIHJIAgBFzcx5V6u0PkQiNDNjdtQ4BkMRASYVELO2cSooCrm-pmc9FIFFQQyLmhGVqllUAdFxFTusBFQNiACgimaxqdBf-k__Tx_88PtPlqcn_eoXfuHnP_4rnx6G8xe-9NKsXb317e84ubnSYXrfe948a-PZcvWF555u4tVf_tinvvr1b3zrlfnTX3vulz_2yePj1WZ_8cQjjz_2yMNX14v5qlmuutPj1d_7Rz85mdx6-fZHfumTL9-6_NN_8U_9qT_2I__4f_57t155-Y9-37f_2kd-8w1PPfqf_dk_99f_y__hd379az_y49-d0vkv_uxvlKKhWzaN-6a3vONd3_KuF1_52qd_67Of-ugnhmFqYyTfhBBmi6WgfNMb3pSG4SvPPCt2SKUTMGhKjIfkOVQR50K7ngOQSQU1RkRAq7VKBRXnvQGoiIueyVcpHL1WhdCk_U6k5pK9d03XAjpRbeaz0DXAoKJGpoa-jdy4sh8PGUAp4kIDiC60alZLFTHftFothKCGeazz0xMdx5KTI2yarj26YTKKUXd83cQOWgwyx7FFgxhD2u0Y1DtE7prFqZQyWyw3t2-rCip1pzfysE_TJKWcv3qrX68JDF1kBqm16ea-DSp13I2qDJ5i428-8kiz7rd3L1LS__Lv_Md__oc-VJJ_-vln_ruf-ci_-Mef-siv_tZnfutLTpt_8N_85SdOjrOVcSxZSjVAhCrqmA_bJEfmHRNacM4BIZBnAkRAAEMDJTRidASBMDhiMMfkvfOEUq1kqaB99KpmSGK2S9Iy7ZI6hpQlVZ1UCamJAdWk2DSOTaDOu1I1KaghIhnCvPUmdpGzQyJCJKwqTRNm7Da5TLU6AiTsfATibR4dADMxWjG5sejFoIjc2g7AmNQQrJa86LpaazW7u9k9dO10mJIFl7IgQCklNB6U6bUpBGUnr7t-JUmxWleL-e372yrp9Q9eZ3aXqV4MQ9M0VXLT-pvr081u2OScagFSdvC2m4-x2iT69Cuvtm0767v7w9B613hXSz5ezqaU8zStZm0IIaWyK-ml88unbt5AQ0G4PQxJwBP3TNN-QsU7l_ceunp0NOuZ1AE---K9yaiABocGbr9Po4kaTNM0a0J0nKpuh_Fiv_PBtS4MuZzvhjEX54MibPb7WYx1qH1ojBlFveOAXGoJwZciXQxoAMEhIBuAgpEBkpXEjtmTqBCBJ0eAq-UixpBzRWZBa2MYU1azJvjGe6l51ffgnNQaQtBS265pu-b_r0MhJoeoBpfb_XzWEVFwzgDNQFXbprEqs1nrABwBOZdzqmq5qJipWBVxMQ5jboLb7xOYTQYvvXofiKZJp0nGlFNVDpxKvdxN58OInmvNQDwM4yQ158whnN-5ANPtZhiHMtSSdhOpRR-n3QCvpT51c-9icXyUSwKGmupqsS5SJRcrRYuAcQiMJmW_wUNKDmncD92iL1MCEwbTWgzUigKaSGHyLgYjtVQ8I1RlH7AKAjpyfKBBBM8cUEVqJeamaUysltTMFqFpS05pn9M0PP66J0KwOu2__zve35hd7nY__Wu_9cpzt7bb6e7dy2962xPUdBd3Nq97_UMd4Fve8rpvfP2lzd07FfSJ62f37l5-6Zln3_KmN77rnU8xwh989vOf_f0vc3DXHjj1pud3tpcX56am7BVyvz7aX14gx9MHrm_ubxfXjr7-8d9rG56tToQjz5_6Dte1sWtqSUSw3w4u-G7Wbi-G6zdvVLO-n7VdX2pZHq9yLVfPjsHAARFpbIJVY7L5sq9VAEkVDB06Zhe4ic28709W6XJHCGW3L3lARWYPoMvF0ZRTbFsmp8gI4LyjEADATJFZweJigZ4RSMREsDs-kZIVEA9HfzMkBkL2zkzzMPGBNjDuJY_n9zftchn6mfdusV6P271KbWarzd27i-PTbtbpOHF0ediFfomIruH9-Wa323jH66NrLrpp2OVxaheLMJ-pVGrbpltM456IyCynATwzMwIRkWMqU25mM3acpkyEAIBIUoWD5xhAlNSInan6EFRURMOscxxE6uFWCgA5FSAMbUNdq6p-1vnYGpAZSirt6ZGISVEXA8fgmhaAHILuhirmutbH2K7Wjmi4GFZnx8EHUbpytl7O-7brLy8v2-iP57Ou8etZd7LqT5Z972i1aJdN8GgRsQ2OGes4LWZt9I6R-jYcBi3MXM02Uy6KpWqS3ES2qvfvXi5Xs2bW3bh59f6t875rnOcHH33g1vOvnj1w6sgjQWwiADgfalUSOLt-1SEt2h49tUweaX1yvNuMy_WKfYjBe0eLk2WVCkjtclaz1DEjmnd-dnTiG68FkOnqtavr5XzedjeuX71xdZHHfLReTftp3jShaxz7tvNN4x955PqjDz14_uqda9fPxu0owOhd7JqaMiBced1NNKu1chMAYHHjZh72TM6kIiIY5nGcnZyVnMXEuyClHiQ6zoVDvhDMkJ0Ztv3cSiolnZw9MI0jOadouQipmWiuyXEMjdeSneeua4nIBW-KB00VAbvgRJQIQhulFDNVqVeOj0vOpVTnXVFLakSUa2piaGPrvFNRUVmtlqVWVPPsci5934SG61hUBVWvnp2UqtN-RMOmadKY2TMil1zbWZ_HMp_PTGTYTf1yToygkoZtN1-VKTvnahEjcOR801Up3WyRx0lFXRO1AJOvKcXoypSPTo6HYUBTVV2s1iqSxomIpEpsI3tnRVG1puKcL2Ztt67TQKZd19ZaTTWwq1WDc20XS8qoGIOnQ2cXEQGrQtc0tRaPiGRkmFNpZ40UPQD7u9gUUUYEIkaKPqCq996hefIIQIR9bKsqEjqmEBwYIAAyA6AnaFsfg_NMgFAFusiHgmWpQgypqBp45xDJkMYslaEYCLACGHASEwUBEMNctb428qeDAF0MqlViz4THs-UffOPZ__Hv_P1__S__ze985vez0ns__O1P__6X_6P_5s889bo3vPeb3_GLv_Rr_WLx7R94V4xhPuufvX_nG8_dfe7LX8ft9Jf_yo947tTHn_rpn_vkJz77fT_0vpdun8-XM26jQPi5f_eZj_38p--fn189PWLv__Jf_0szcP_T_-d_uTOMjz947Zd-_uMf-v5v_pt_6c_885_-pX_wE7_4P_79v7pk_1__F__zdncJouN-SLU8-9ztl55_5iuf-_ru7r6fz1erk_lqjcgy2bgfkdJytXz8scd_69OfMUOtplXYgIjgEAOq1fuopnXMKqqlWBWtpZZCzKBCIUrK5JAAp2noF0c554OEjkBd7NquJ_aayzjsiYhUpnEsYzIwI0fg2_ncEKQogoUmEhEBaq3sXa0FAACJnafo6XAXBSImk2JaY9sPw-RCIKslTYA4v3aNKaCnPCZqYy5lsVqrCahN271qWVy72ixWXe8mScP9TQhummp3euQiHV-9oVkJS96e7y-3_aw_vn7WnhzdvXULia7ceHzaXCLzuC2n14-3987324nJ_nf_1X_6z37il_7WP_j5j_zm733iC9-4Ct2P_olv_-Ef-M7v_s73fPBb31RTGlNG9odmLzs0BUQUUVADNCSsIoBY1ZTA8CBkAlUQNQJlZjBZzppZdN4xmAZGNVODKtUxAhgTliRGcD7kzX7cpFJKyaUCWFEQQTGrFcZcwWEpmks-XswmqJOYqTEzgB11QRUvxlzN2BMye8et44bdVERY-iaa2fGyvXO-9YwO2HvPpM7DWdcfNmkXKStirspkpZaz9SJPgg6_cX7xxhtX7t3bW8D9mAHNRL3zzARizIygSvLWh6-D1CwafdhPaarpyWtXp6wvnG-zFOdorGnV9VeWfS7wjdt3BQWYItvjV84IUBGfvbh_Zb1K4_T0K7duHC_RbBbCuu_ubbaND6fL-ZRKMZ2m9ODZ0cxFFExVXh3TOFWRAgWef_n2rJ-R89fmvWTtokOw2-e74tzXX7rVBPbkarVb98-BaZqmB45W1VQNN_sxNE3TNIFYzEbVUnQ270oRUwEzqVLMVA1rbV2QWq2IMWjVZdvlnIhBFVEqgZWqPngyxaKxibUUFev6lh376IAZCAQNAUyUCEMgVAvee2JDDcEDQyCOIYBZ10cVraLro9lBrVdED854Zl9EnCNDPUjpujZ6fg0DIKKillLdj4UCsScxE4EqBmBVATmeb_cucq2asowpq9J2mC43-4vtmKvoAR09Sil1lDLvQ0W8_-rd2PpxGAE11zJMU2i9A64p-RiVgJCQue-bvJ9m85malGEoaaLIyFrHyQWqechp4rarU3bsDMmIutlcVasUOowlphEOVgViIjQx9ABqkKuhOnKIfDAeIigokXdx1tWpyDQyMfmIKlnzbLaMbQQiEc1pf3J8YjC-8tIrP_6n_zdnXa-Av_bx3_78V5-Rmm88-sByvRryMO7SerU8nS1Pl6vbt-9_7ZnnXnn1pbe_7c2f-NRvzedH128-6JDWJ6tPfOxTz3_jefZ-d7596j3v_OJv__5itmjX81dfePnKIzcMZDrfe9-ePfw61zdps9nfuSRLMcRUa5zN-OydH3Z903YNEUqV2WKhJo6p75v7d-7Nl7NpHBikm_VSStM20zD1fXQOnQveu6aLMbo0ZXBsau28cYTgEFS7vhs2u75t2LOVyj4CODPzjd9fDhQ9uyAqPjY5Fx-iSk3DiIapimsaRJRaVW12fAwO01RC04KBAimaFkHkPAk5VkNmWjx4Op1vfNeamvOFrew227ZZjLmUKj64MY152Fx58MHh8jJ2DbMDs2a-GDcXU8ph1nerteURVHMdEPD06qPVxnEYtWQLEYzH_X51elqmqUgBYhFbHB-XnMfd4AIz-zxlF4LvYsnVVNE5q8KO2fnYLbUmU9CqahbbDkzSmGbLhSGqiJkZQjNra84IgZDnN4-n80kJQ99LKqUqUTBEPGhxgcwIAL33YBDa2MSA4CVV5-Haww9vLy_Prl8hgOV8dnayqrWsZt1q3izb6MCOln0fufPcNexRJZdhGEC0bxuH2LZN8BSdD0ym6hzHEErVpPXedp-TgMfz25tSJU_VEXjnz07X92_fffjxm44o53p25Sjt0o0Hrmz309HZ0bAfmy6ePfhA3mzOTo-JwCHNWrh2ctww9k3ouma-Xg77dHy6Dn1AqcNuP18uhst9CGG-XpVUmr7RKmAWmrbpGu9dyfnJx272bTg7XrZe3_f2N-dxe_3kSBz1nXvnt72pVnj05tmPfugdTzx8_TO_-ZVHrp1sd8N2GDCGxXo5DmPTdWWoJ9evIfH5nXvNfG7T1C6PVMSI6pRCG52jPA5hsU67bZzNHFMpxZGXJG0_qymho2qG6Bh0fXr94v59DOyYHbtcChh656waO1fVmtj7FvNQY9MgaPDOwMzURW66CEWQDZinXM_WJ2MaENg5N4sh1TqkKcToiAC01OxDHMd0sj46hCNdE1XNOwdEPoRxytevXjEwKSoKpnLl9IpUASZV8g0XFUTwnkFgtlqkaSIm0Rpj0Fxc6IhpHHZt2yOQ815FVQo7AIMQnfd-GCYybbs2D1OI3gBCG9KU2uCLiqkyew5cVZAQoErREFq1Su7QTTSpSiRkJjWT___x9N_f_rXpXR92lbvt8mmnf9vTn2d6eVRmRm3UPaMIFUBYgIHYC_BKYkLieMUrsYOdrBU7dTk2WSwbE8B2EpAtihqMQAUQEhqkkTRF0zTt6d96yqftve92Xfnh85B1_oJz9j77vu_rfr9fL1TAMcYmOBWRUubB56qo1VufRQBVAAxzroIAqlBrMUTWOkCoWZrWi5QqgEykCEj69rVIZSIBQQBgKpKVyBDXUg9JQmuYmLToQaVHgMaY4AwjigparUWRkJhKlQNavRRRBWQEIGIsFbKAqGaBJFpUY9GiWkCLaAWMVRTg7aoyaBEgJAPMqN_x3d95-fhy-_imqToZ_jf-7R_99d_8zB_7sR-ZdzME-MpXvgEFv-d7PuwJz1bHBfSp55_9hV_7pz_653_8s7_71b_2D_7R3_vFX91tdrMuvPCe81vHZ8G5McsmT9_x4W__hX_wiW__lg8-3l79pb_45994-MZv_fanrOUZw-568yf_xB_6iR__-F__r37q__jv_-c_94n_4Qu_98XF8fznf-YTziPUKoBN1_zAxz86XO_On7744Ee--X3f_MEX3_VStpRzLXF3-4VnJd48eXL9Qz_8o7_6q_-kiEguxprDdI2NlSrWWuOMlGqCO2wImBlEjTVVRFWhFvKOgbgJNdcUx_7kdNhsEKDmpKK-nfsQjG-G3U6qSk1E2i56ZgYEF4KoKqK3Ho2fxnRQCyEbUQAg2_W1FuO81CKlkvWqRaTmnGwIiAadL9M0bbZsuAh3JyfoPTCVkoGFjbPBWuZpP5X9Hgnt_Ki_dVbGSYqsH92oKBseY7r9_FM3N9PFc88vj-eX9--TgWm_LRmJzOmzL7Ftt0_uMyKHZvfgkQ2wfrJp593Kh5_7O__wXe986n_35_7oj37PR374ez_4Pd_xvpOmaVoTVFMpmkSYUaGKVFRUShUOSDRAFcQCmIokqaqkCMgEolWEiACVERhh3vlgTGBSlQpQBGpVYrbWGkMpSuMDEU85P17vouhUChDnXIm4AhVQZQSmIrVABcCq9WjW7mNWZEEkUgLyxpSShSnWysSgYAyiqvd-X0dl9ExV5WzWPNlEZ5gQmTFp6a1ZNrbUOpSyy8VYm6WC1FrL08eLWmTIeRiml-6dPbrcFsO7fVLJB0YQIaFCrNkZ3tX6wTvHWiQLWmNe2189v1g0LijR1588dtYRM7O849YFVZiyvHH5uJv1FcuLty6OTEDETUkPn1wuZl1j28ebm2dOj1JKi7Z9cLmJku-eLFC1lNz0_fV2MKAn8xkzffbVt55sBwG2TRhiGasczdta63N3zy6fbIK1V_t4NSVwXqQgoGUzZr3abrPKatZ7y2OuRaGoxlRD4x2ZonU7JKlqgHfbAZVKyrWU9X5IMTvEXIplBsA4ZlIyrDmJAJYpYxXUWgERwFmDCvO-jykHd8DHeWuMsSwiUMUwQqmMhISzvrGW6V-Z4ADVeRssS6ptCIzqDTtmZ80B6lqlHqYazAQKIKKqxhjD7JhjLETIzBWhFkBzqBEXYJO1rrdTTCUJ3AxDQUhTEYCkRb29udmISBG0gZXJMQtqqQVJd_sJRFMp5A_-HBBBEmMQ882WGshVhlhc41GEALBKcBYFqohWkZhQuOSqqmScBxfHbJgUAZhrilXAd73UktOkRRiwP12mGNmyxInoMCEiU8QQ5O0AjPD_Z1sjIIJrWtP4MiUDkmIOXWuYrh8_WZ6dk3PDfte3XdM1BGW17F5-z0tPnxyHwJ_92uu_-Ev_fJrScy88_QPf-eFf-43fTVNsQ3j2hXsI5Pz8rUf3ldlb81uf-tzHP_6xUuubr71iG_8HX_76zfX1eruvKd594elHr7_16PW3Xv72D9m-efXzX_nI93_sy5_67HzenzzzTHfr9OFXXh9vdmyqVN2NU7M86lYLfuq7fgSJ9vsUPF2cn9zcDM40SGCNbZp2c3XTdx0wCWKusL3akkNCGvdTM-sIGKU2zvvg33x0vZx3cZyW804Jp10krPPV4vFbV-18HnMRUTKsJYfGE9I4TL5t2RhRCU0bx8P01xjnjbMqaq3Jw8jOqGJ3fDJuNxIzeue6jsjkUpCJHRvvpORaQSqgKFlbdkmFQItBXl8-7udLbhrbmNniSEoeri-9tTlKmC1366thvZstlt6H_WaTx_3i-Cxt1ykOkuLu5vr43jucATZWWJHIhzCNg3HN8XNPTzc7Y0xKe2t82zU5RWMtMeUpkjG-nZUpEYP1oeZJq-Y8ucUcRJjZWB-HMfSdC836arM4O3Vth1Vc8HmMaNnPZyosMc1PzxEZgbq-sV1A64hNc9RjBYOkIMZyKeLbFgCdC5Whm_fdbJ7zdLSYba52ZyfHlhRFnEHruEe8WPVHs3bZeUacSg7WBGMRAUr1PhzoGsawtTblUgSIgAwDgKiUrNa5WrSkGhrfOSu1GmYmrFM6PT-dYmy9996eLOZpzKiqVUstLthgrVY5OV7dOl4---xT3hg15t_-U__a-1985uT09LX7D8_vnGlRBdzvR-sdW2K2xph21u6G6PuOUELjUTRLvfPMO4wRLfKtH35_y0Q5zTy1nm8v58vlrHP-4va5TPX87OiF22dH3dwSPX3n4vzi6L0ffOFmSqmqiKQUp-1-Nm-lEoIcnx49fuuxqChUwzbvRxuash_YuVLUBOtDM212zXyRp4i1sCFS7ZfHVSuIGsZc8hTH1fHZ5tETtNYF17RNTtU4W0pFFBAFA6XUpu2G3W5xNNdam-CReJyyYu3arpTDCq-1ZrI2xilHWRyvVNU6u7vZhxCsNTVL14YixVrjnFEkREylMtNB1hMal7N4a2st1nLT-GmMXdOPMRKYaRr65XwcJkm1ih7Yo_vtzlkrtXjf7fbrvpsZ5pISAiFqilkBpOZ-cbzd7RbLpUgB0ZpSt5xL1lxzLuKa4A3HMQtqO2udbXLJoBjHkRmt8whcpdZSS4lt141jDG1fUwxNh6QCkNLUhCCiXd_UCgDVBweCWXLOCQ0ZRFS0liEXJUQEBkQCBAKtoDhJmYU21kLMUjKwkrVMxhs89CVjis5bEahSvDNW327iAygbwyDMuOi85pqxoiIBoKJoVdVyyPCI1EMNUxERiVgViogCZhARKlIrkQBWOBD8qghUqYCsihUVAbNALkU0ftdHv-NP_umf-LEf_6GP_-B3lzz9yi_8s3_zT3zcCgdDf_D1V548vvnRH__u_fqGCHZjfvD48l_7Qz_85Vef_L__6k9t3txApjHF3c3w3d_7XS89_Uxr3Djk3_nsF5oyfeu3vt9aODo6OT9v-_OL_-_f_nnPzcsffO8Pfv9HvvPl9_6__tpP_dd_-af_s__-P_3Ub_zWe77pnV979Su__o9_W1ViKQngwx9--bkPvnB0tPj2b_2mzkmB61_8-z__6he_NNxcl6kMV1djnG4u13_yT__xf_jzvzRNSYoAk1Yg65gJUQGwTEkRsEot5UBtBAI6dFdrPdy851hEVbVilSrg2q7G5INDhjiMzWppjfH9fNwMJCVNqWw30zBWyIAU-qZfzMhy0zRN21pLoQm-a9jaLKnG5EPrgkPSdJAq1iK1GkZugoqCQRSBChza0LfjlPrlsQsu7XYkCFlOz4_GsRiAtF6DgKI7e-72tN0ZpO3lNSMJOjvrn3_fu6ZxKnmnWqcqkhMkRI2qup_2tWZj3BDjuN6H3sfNjm1I03B5fTl_4db__H_5P-mPj6q1qvzKaw_isJfKs75jQEQwTAAqWqFoLiAVq-jB5gfEUhUOr66IVhWBf3U-UGJkJkO6bJwxNtcitUxFSgVr7aEOkYsioPc2lTJWuRySIk2HwQBCLhWRi5Ao1KqlVBVFpZTz6bJPUQ7LurUWsyIJEipQLgCg3lgV8ca0xmCFRddIKZZ4FvzDm71BbUIgwlHyU8u-N05Ed1VigVgzI6WcmsadeD9NeZ1TAn32eP7qo5simFMxBqQCAhEZUREVRjie2xdPjkRhSllYdUrP3z5Hpavdflsys0esmvJz52egcD0lIQQSUn3XrTudsUnkqw_ut7Nek-6nyRHPg_cGrQ2P1utVG-YhoAIZ8-bltQI8c35q0OxzeXMzCtFuSJdXN6mWi9Usxeni1tGDh9cAAABffv3Bo_WOLKeayljmffvGw6tCeLPf3z5azoMvVdb7aTtOsebzs-M4TmDMej_mUo0zpco0DW1od_udJzZEtabmQJZURU9EYJ1JUqqIYVapgGC9ZyKqhYkqqHXmAOskkcb5UqoxpKUwouSasrAla5gQvWXnLCESYBucBXTGWEYQZZC-bRhQoQ77iZkPSDMmklIVxHt72AzkUkoWQMxFSoUhJyb0htgaALm-GSpC1ppyrkQKmEseYxHlKU0lFxDIubCxu91QQaqoENSqjrnWvN6OgFRqBUfTfpdybNQDY4ql7UOaEuSEVYLj3ZPNuNt1y6aUNG12B8sBE8ZxYBWVYixKruw9VBApaZi4tbUUkYK5MmHJRYuKxhKzZS-5gMIBc6cqzBYUQNW6ILUCQLdc1lKn_WCNYTImuFLFh355fi4xSkygxTIO--GF55953zueX87b0-PFr_7Gv7i-3rZt--GPfuTXP_l7b71xf967-fEpIL72-puV6uLk5Ld_-3dzmj72sY_dXD353Oe_2M3aJ48fP374mBDb0DVtWBwvvvHZLzTBz05Pttf79W6d0pCGybaz5TO3v_Gpz2kc25lni2q82vb5D753GiK_8AM_sTg5ssbEFBGlmTe-9db5Kab15Wa2aKuAd60xpvHWENcs6_VusZqvn1zP-kBI--3OEN4-O0LU2VF__WTLbIhIFVJJxno2ZKxLufq2qSpxTP3JmWEGROOMD8Fa40KooC6E3WbfdF2JJcbs21BSyVmRcb46LWVKMWut3HSq4GY9okipSMyNrTmVLGjZ9872s2kYLQEi1mmPNaHxHLwlNNZv1tfdbA6lrk7OlXDY71UqkysFyhSPbr9ogcbtFRJsbp7Y0KZUxv3UdbM4DIvlCgNfvfnw5Px2s5hfvfVYANquB9XdehvaVlVylpJzf7yqVXPOfrYsaQIlKWpny4PfxBqrbGNM3XyhGZnQ9W0ciiqw9bVAs2jLFKd1apbz2XxWErSzfvXUad5OwTc1VymIwSKR8aGd98uL0xSlW60YsQ_BWnt--7ztrYhaS867tuuZ8Znz1e2T-dmiIRBn-GTZtN6Owzjuowu2lrLourenBRZjUhVEgia4WusYCygBQC4qAM6FYRi3-_H2nWN2Zt51-2F_fnLSNs4AjuPu6bsX73ju3uVmqwqo9d6t8-OTYwPw3DO3g9MPv__57_nQe1Bg1TXH8-Zdz929_-Bqs9mRszYEALHW1pz6di65zE-P0jg1bTuNIxsOwV3fPD6_dWu5aF995bU_9IPfdmc5b53ZXW-Oj7qTZXd6Or84nRmkd9xaveuZi-NZZ1BXqw5RnWEyjIYevfWwFFkczXPMCLrfD92yXz59e_N4Tchd1xLj-q377dFScgqzTmoJTQ-1VJXZ8cmw3RJRGnNOIzsvADknNl5UEaSZzW-eXM5Xx7kkH8I4jV3flFpVoYr4vq05t13YbobTsyPJQoRNG6aYjeW2C_thNMbELKF1oAJI4zD2XcdMqLIfpuBN0zY3N9er1YJVBdAaarv2AJfMtYDIoaXgvS857bb7pgnMdHN9s5jPF8sOiVPKIYScci3VeWuNRYKcS61qDNVSSs2Lo-MYJ-NdimM7X07jQIYBEbU2zldRaw07N-32q-Ws1hpLkQrL-axUSSXHMbd9611wzCVPKii1LGd9yQdVKuZcjbMlpgNPrQmuymF3DbVIVe2aMMWYp3q0WmjJUqWk7NjVWJBRQSSLcZxzZmO948YwIo3jhIQqFRGMpTxVZGLSwIYQD1JkLUURGJlE--BLrgBQBZgA9IA5JQCoQIBqgLxxqqBS5aArQBLRLGqZDoMgS1xEDo8YCAExFVHQInI4XegBYCa1SBVQehuYAKoYJUvNpBZYJNJvfulz3_6hb6kxQaVf_9Rnh5y-_3s_eH15Hadxm8rnPvnps9XqyeXmC7_z-eWsgaabnx39T_-9P_OhD74Lx9g3PXO8efzkdDlfzhdPP3OOhDpNn_zMZz_y3nf_6Me_64Vbx2zhP_iP_stf-ZXf_Js_-1_-7q99-oPvee72UfuX_uO_QrUYi9aZ3s_-0l_6t179ytqq-eIXf-cX_u4v_sHvfjXuJyvahACIlk3T-mkY__Af_yO_9Au_nDXXqkWBHAOaXAEIibnmzMyiWkp-24mApAhAhpxXRCKyIWjKxjo0XEtq-6WglmnSqgoYN3uwxjZtf3rctH3oZlKBjQEgSSntd9vHj4fLq9315bDbDpsbEdlvNuOUCM3s5LbIVESJGYDifmJ2INk2LSIzIiOxC9T0uyfrOE6-n3enZ-zD6vZdQ6y1xCkaMu50cfXGW2wZrV_evj0No23C-v4aSkUmY8zi9Ng67rpWqqxu393cfwQKoWl2l1fb660Jtm2DkkPIbdvGIbWLVgRMcN_-g9_xzmdfgJjzEAkrbna__8q_eP87voUVmVFFDDMQplxFtCIqooAIABLWqlKrHjJXiCoKBADAjExACE2gzjpiVoCYsxImxVy0ihrDTcDNULZDHnOeqk6pvl1kR8y1AqEigeEkUquCKgFaQgAE0mXbsIHtPoIik1pEIA3OzdhNCrFWZ9ga6LwzCENKJ_N-P0yLLqDg1Tg1xh71HQKMkl9crpg4qt4MUxYRhKNuvt1tnrk4ak2jiF-_ujwOzaLrXrveHjCXhimLKqIxXKRaInT4zPnRWd8C4X4qu3H9zMmxtc4b89X7jwWhIjDD7dl8ERpifnO92-y27axZBPfMasnMyPilRw_Pjhae3FtPnjx366KoGKXtlArqyWrOAqIQSR-vd8R8MetyrVnh2knn3G4od28v7y3n91bNZizXmygqfd9WANt4tK7p2m-8-tbRYta2zXqfYp18cKfdnAkL4ZObbVGxbII1BulqsymiJdUUK4rUXLUmqqBZUGHKUaB450uujpgYybNUpYOkAhUJnXe1VMdkyQCKYSu5KgLUGprgrUv7IXivIkwQmmAskYL33hK1ITBp17SOAUQtkzHUBusse-tAZT8ma1hVCZmJxpSCtwoQnJGqIpByQsKUaxYdpgSKU8xFYYz5ZjOmKjGLAI5jAsBaiygUFbGYpljG3HahcWYzDLnU7XavIodai4LebLa-C0AwDXG26K6vrnSayjDVimPVPGYm0pzjVJpZp1XydhrH2s0bFEwxxmEiVO9CjZGtSVNCa6lp0zAxQqmFvQXRuBkOa4vzRkVUVGM2iEhQayHFmvJBa4MIimitLSVb3zazTqTEYTTWSgZylomN8yo4Dbuz81vOoGL54MvvfuHW2dN3Lzg0P_czv_i5r761uyr_7r_7Jx8-uf6VX_zN41l4-qmnN2N67bXXFsfH693mjddecehefvkDpPgb__STd569df148-j-_aJ0enJ857nnHr3-yuP7j3c3-3FIwEZI5vP5frNLY33Hhz_wld_4Lc9ccs5TDX1bjT26ON09uYr7kd_zwz9pnEHmWReaLjAYjdlZi2xsCMs-jEO6ud6ypZSK73zXtZAEsJwcHw_D3lrLxpaqxjhFnS8aRi6lAsrZrWMVzDmTZVBWRKlFipScSdW1bRonts45K6WGEIqUYRiavlNQ2wYXvHGWrSdDktLV5c3R07ecC6hkHIbFctzs8lSwZEUo-wmZVRFEVdHNAlQpqdq2MaqAEMdxf30DiP3iGI3ZPnnsvZtS9l0X5kcxlVKyTHvjeXf92AY0ZMsUSUGkKIFxzbTf3rp3L6Wx8U3XL29urojh-OJOHMcq2RrrnM0p2xCscyIIqMZ5qKpSFAlUyNqSM3kPgIBsG2-tF9XzZ57a74cq5Jc9AFkffLCg2izn1lis5BBMaPplT6G_dffi2z70jvd_y0s313r-jrvj1SCxlJRtaNCQMQSxNJ07PTsZx-HOM7dOVvM6yb0XLxa-kUzP316e9EGqEGnXGAu6vt4cjDkqSIyAYJwd9uOTJztkVhRrrZQac5ly3U9jVUE2wFpSAYXgfdeEaTs13jNRMOyI2tA-2t583ze_t3NciZ5cbRd9c-fe-bJvO29P590mpdvnx60xBqn1HJiklLceXjZNmxFiyiiyOl3IWBEECEMTRJQQpALU6r03zLkUQ2SZu8X89lHbB79o21nrneF5MPPGXSzbZeN7a4IlInQE45QfX6-nUjPTNMbdOp7dXT39znuX33h4fno6xDTsYp4GLBLjaJ1r57O63YHUUnK3OJpKmvfzuN3LwWdDQAi1KhJRCBWQAaBkAXLBaqklDk03UwY0nEo5MFgNUxkm64OU2jTtdrs7Xi1LVQAx1gzDZByzszVnMpymaNjUkhlVEQybJlhPDJo9Eeih4Ycnq2UaM4oYY5y1UqWbtYaZFZCUAZvgUowhNOM01Zh855umyTHHcUwxSa0ANE3T7LiTWHIutrGz2XJ9vfWBu36WpkmBqgqzS9PkPKloP-ut9zFlKblpwjCMvu2gZkIzTOPqeLXb7J0zVSX4ziAhckqxTNE4ts4TkhaZUvKhJVEgqFLbbo7AUxyNMSAKUmaL-TSMqErkbLBQVQ5Xv4gC4NmpVkbkEFKM1gZFDNYqSM3lkE-11lkVKMrOBedQWVQsYXAupVJFrKVlE5C5irA1bFmrGiI2HJzJtUhRIDpogJEYEQ-TfjR0cI9VUT6YUAkFEZAUodSKxFU0l8qGQZWIVZWIRFVEBUAEklYBUkMVFBWnXXw47P_7v_uz3_WRl41Cyvn3PveF_bD_gY9-y2a7kVqHmDOU-bzZ7vfDePXyyx-4ePrun_z3_sRdtGm3W816AMkSmdNyfoyIr33jaw8fPNlubz7yLR96_3PPyXjzMz_1d_7yX_2pt97c_if_6b8TN5vdbvfxj33oj_zp_wh1UonMLLU2x6tf-MSv_fZvffqTn_rtr3zxaxaMI79aHR2fnn3L933bUy-9950ffKcp8f5r93_gYz_w6d_53OX1VS2KbNh5hcqW1RAb268WSHjA6fq2RWuIyThnnQNDqgCMUIttfE1JpJDKuB9mp7fiOCAoGW66oDXtdjfDdlsMiTFm2YWjZXe0ck3nnAvet4uV9Y2qWR6fVVFk1x_NAWC4eWwsGWOcs8zGWIMgJSWJkQhF1DYNOlvRsPOz05M0RQ5tqfLWN16tNXet70OnTFxg3G-qCKg5vnd3HCfn3G4dqVbnjWndbLkEZq3CaF77_S_IOGSBsFg1fbdYhLwbbq5viKFt-1Ryf7QQRCAE8rPVyXve8cKXP_NVHaZ3P_vUvbsX737xZSnReQR9W-qVUxHQVBSYpaoiVFFRLbUSEyoyIRDqgTiHgILBkNSDIBmJKJYyxCLEgBRznXIBA1PW3RiHVPZTUqDtmApAUTz4mBXBeVcBc9FUijFkmC2bophqsY6doVgFEA2CZTPG2AdjlW5yqSBt40nEG4NQL0s86ZrtMC0aXxQeD_uV9_PGx1JGLc8erVAkiWxSmVKZ0uitWcft88eLOpUnQ3xrv37u-Gi7G66nCMhSizWwGzIHdtbVklsXKtT33zmZ-aAio9RS4gvn51UAmR_eXJMLorDfb99x-4JFc6kPxkmqEJWXLs6PfaMAm1RuhmHuQ84iJR0vFttpJKYxJTJsAFEEiC6v12jp3nIekLTKZZYvf-U-W55S9ZaDs_cf7R5crl3rYkytMV9_6zLlRJ4RsVRYzWbrzbRNqYAYokXb1CKbaZxEU8wllYuTIwM6pXp9vaWCACg5GoBANk5RUNlbApp1LR0kb1JBBNnGaSJQsggAKEiEwZIFqrn0sx5QnSFV8d7NuoYZGcUwkaEDC7Xk1PetZ7TMUsUZM2utNyYO2TfWGZ71jSXwxgDAlIozDMCqwghA2HgDAIxITDmVnKuxzhAlkSlXQEyxFoFSdUy5KKRcbnYDEdcipWhKBRTjlIWoSs21jhVzycYYNFRzEZFS6lQytzZNOamype16z94h-WkYyJN3VGNkOriwKe8mVKklGWPG3Z4soiqraBURscHnnJmwpGosS0paCwggc02ZGaylPCUQZTYlRSqVrWXLMaWD2TCnSMbkkm1oSkm2abpZF6eppppjDZ23PiiI9SF4W6RKKaExw7Rb9bMPfeA958dHRPXLX_pq7Wdf-uqb_87_7I-_9dblp37382-9-dain-3j-Or9V8_Ob19fPX7m3r3XX3v43d_5bc_cO_vpn_q551945ubqehz2i_nx-cW9IuPXPvNZJBOahgw5T08_c7ebzV7_xqua5fjW6Wuf-YxnU6SEeZ-zgnG3X3yHdcBFmpb5xe__CWvdMjjJ9erJWhW-fvXq2Wx579ZpHdPqpF-dLkOwbE0WhMNiuZqp6PV6vY8JSdvg5otZTTmPAojEClIZ-ebJ5tatC1C8udmys6H1UkpoW980ImBDMM4cZKPOh8OHyjs_7vfeB-sMaWXicYpsjLHWe948uQlN6_p-2I8E7EMnKZWYjEM_6_KYnLeu8TmnMpbu1rnGCKWkMVcBH0KZBigyjrt-ceRCuHzrlSmKbzpGZeNrhRiTD8Gh1iLEDpWssXGYFMUYyoglptD0Vzc3OU5VatP2kqZ2vmDDUjMQSQUOIcfEaKRis-iNcSpqQjjA24n44NXzfWOsVaSj84txs58fH5VYXeOt9zXXxfFq2JdhKkenRxe3T-aLeTdv3_fBl1bL1fufu_fUauWrb9rgkoTVfIhldnE6TGm2mnd92_YdE9WUCE1NpWF0jp86PQ4Az50vDSEqjHEsKqyUpmKYfdMAISkyGQVh69JUfOOKAArEaWp7P0UhhAIYs9xsJ1EBIovcNNZa0_kmxTSfta13DOq8Xc5np4sOALx107Q_O1l0XadJnrtzvN1t2llzPGsb77pgU0ogGKe8OFlc3qyPz-8oyG69S1N6-rlzFWC2-2FazWb73b5vW5HigxMVlRpCYNSZD-dnK4cw71steTXv5o0zSFDVMjEhINxstlNO-3E8PloBEyG1ITSNMWRu3nz47L3b0xCtdcpkHUstBCbuczfvwrwft1vXNDFG33Uilb1nZmd4GkfJha0FBSQwzqMKEBh2zHRx67nN5glbe5C75VQPXatainEup3K6Ookp9ot2vd71fWuNBVBjXUp10fcE4ByN0wSIu-3o-zDF7JsWREX1aDG_vlqfXxzvttPlrnzo5ZcWbcuWEbBrgogy8fJoEVNpvam19vP2-PQoTtNyMc8pb7bDbLmYz2YVMI459A0oopJlnq_mMcbdfkKE-WIxjXtkS8xd201T7LoWkPbjvp_Pd-vdvdsXTG4Yx1pzEzrDBFWrViCuOR8tlrvdBhUsG2NRFXLOtjV5qgDUd20uUkRAq9bqnE0xqkI_b0up4zh5S8bYKaaTk5NhP0gRZz2T5iK5Fj6k_EsNjRMpKuoc15yb0FbJWiVXMYZFFYpaMjZQHBJZIAYCIhDQaryPORnAli0YVlBVsEwgYg0D6dJZUCggiEQAxhAACqgiHgrBCPyvlFQIjKSHCAaCCgIdgDfGsBwemyghKoIoGGtFQAUEAIgqggIT0v3Lm3__3_vfP3ly8xf-F39ivNnFop_8zOeA8Nu_9T37_U6q-GA3b94889LTJ0f99VuPuab1m1dH7L_-1S9fnJwigYJ-_dVXd7tBHe7G3fHx_N6tO88---Ik-Nf-5k_99b_105_6woPZ4ui7v__bv_fb3_nlP_jai9_7bX_rZ37x85_6rIfkjI25IpExLsfYNGaxmn_Px779Pd_03lvvfMedd7zUHB-tU33ty19-8xtfuVkPk6QXX3zp6urqzQePQEGQVA7dQgAiQq41x90EUqSUklMax5omVZE41XGo0yhxAoCcIgBCqew8VMl16mbLaUxIFLd7BMFSlLGMIyNIyhLztBt365uSKrFj53zXzZZHZGm3HnzXppjiZgTNUKbh-qrGsUqtNRsb7Pk5wcEYgTGqgAFm37TOOQ7GdX2d9pTH4erJ9Wu_H7VpmoWb-f7i-ObRQ0BaHM-JjGv89nqtWmstyPb46VtxjKrqjLt6877mEaDWkqUkQ0xEtVZGlFJ907jONYazoCjMVidPv_O53_6NT_7OH7z6a5e7j3_gRRiSs4xEtUhRIaZYJKsKoCocDpAqyoTIxAiqCqoHNTAxkuLiVqg7OYicUEGJplQqKDONU92nnGpVNNdDzFVjqQUg5hoaW1WHmIEwVyFmAspFp1IRgZAUwBkDRAaqZ9s6nnIxTDVXb7iodK1BxZuYAdUZC1KX3pHSTqbTxkmB1pqY5Xq_P2obZ-0wDY3h24sWQG9Svd7tAVlJOu9jjneWs5h1O-orD5-87-mz-0_W-30tWiUnBNgNIzIF63LKzpgH5fo77t5xyEng0WZ90Ybj-VxUH16tr9cb4_0-jsHq86enILjL-fUHD7tZY0Dec_cuF4xUv_Tmg0XXtG2juczniyfrDRtcdc12ylfr9XEbWmcDm12qzPV22xPaovX333pMBvdjYRVnLBbYV3nzap1K7puAStf7qW_s4_W4HyMit8FtxzTmHHNugjvp-5TqFPNmt8-19MHPfVDB3TRttyMSocXH60vK6oPPpcapEHPJdTFvY8y1ai2ViYBEcpWUvfPb3dR3bTvv6xQN4GzWO-_ilBd9j6SODSsQqg0uxewsH0Lws1mfpqm11hDMuyYNm0U3IyRSnc28ZeOZGMk6U0WAOBcBgCIVmRCRmEAAkFIugCAKgDDlvBsiMxWpiJREhlRFJTBuYwYGVc1ZikpVHcaYRWspUktKRaUqCChUkZgqM5VaSy0I8DZuUW0WSZJVcmg9SJWMznphGfajxjyfzVWg7PaIiRXr4Y-Vq6py8Hr42oCWUjmYkjIqEBMwa62sIjkTs8TCzkpKWop1IcWoTFrK4XSOhEBsmEou1ja-7_OYSKtzTg8cIlVrPVsXa7p9fmectiD1nS89_8Izd7qu_-SnPv3bX_zqC3efeu8772SR3_vtL10-fNg13bDfCFYFPL44-9qXvty07cvv-4Cz9I9-4ZettYR066mzcV8ubt95fP-N_WYfh70Q2rYbtuPHf_yHbLP4jV_-JW-9YYq7rcTU921zulhfbdvVfHVxalSv3nrIBG4253f98B8ftsOUymzWuWCZ6NmLuyVmRjDWfPWrj1SVvd9PEQgVAAkFoZ91i1m3mredb4zlPvgi6oJVFWNN413O2fqQSmZD7axPKYe2LUVqUWccEmatzvmSchPaWooqgDElla7v05S1ai1ivUWFWkVqrbloTiVNebdvu3YadiWNzcnKuibnkmI-yGa0VEIA0Hiz8YuejVMRRCjjwM7Ypg1Nl-sQ2lW7Om262fbqcQVcnp4tjk9izIrAxHkqpMBEJScTGFKZxjg7PSG0ZG3TzUzwbdOury5TyS64aczHd27FKbvgyVgbgmqZn54N2y2FFlQl1cWdc83VNhbRxCirk-Xp-XER6ruwOllJKcfnJy64bt4tjpbOh8VqdnFxQkj3njppm3Dv9q17t1fvvnNyseo9ma5xrz-4gaa92U_Ncq7E7G0cp76fheBBdLGct85KniwbtmQNHi9noJJIv_7KG6-8eXn3zmkgNIZTqalkNmZKaT-MuyGVItablOshwjQJzGbNfojAEAuMuQhIrgejvBw4Ks6Ztg2GqW-blNLJ8fzu7SNvPKhEic7avmtmPvSO7ixbx4ZEnOH9brAMAvTw8fryarOLBa19cHmpqFpg3E8AYF0QVEZogiHAMiUiWB0tQLTm6r1Zztp533z9G_ePjhfGURNMLdUYNsjWGCSOORnQ4FzbhFnXSy6zEPrgt0_29546_ZaPvPvi5GS56D_00Q---ejGe8OhyVEkx8bZlCZVCG2bhqki9n0fup4Yd7ttv5hJVilqEQ0TEavI8uJs3OeqBQGqlNC1V4-fHB-dqIgPLo0ZUNm4cYgClcgoVijYdE1NBQ4GJURBHfa72aK17Kxx1rB3JseJCBVESlktZ4b54uzk7HR56-hoqsm27mQ-n_V-1loDZLxPKavKS8_eWSyW15ebs9M5INcsRapzJlcpsbShMdaSMTfr9XI-SzmDwpCm5a3TOuWasvXBudD08xz3cRob3-6H4enn7w77qDkjaq6ymC99cDlnKZFUj49PbjZbZw-FKSQkKUVVV6slKqhiHiMiSi1ARMFArQCacnbOMaEKOm-FCEFrKVDVNV1K2RLlUpz3rKAKVSsRMGKtCqDGcOt9GaMCEOOsaxmw5AIgBikXAdYQGtRqBMlZRD3UVwSUCVHAtZ6YCBmkEoMFLocss8GWubxd-CUFYWZmlipSlQ60y7e_UcqGCJFUmIkRqygTHqaplkkUDuJSBASiKqKA8nZim4iYCKziX_6v_9vHrz-5ebz94R_-7pQzAP7mb3_m7r1bT9-5MCjjEK8uH7_83ne3je1n7W995gu7hzdXN_t3vOPucrFYHvUplzHmlOpideaQg23u33_013765__Kf_fzP_eJX3p4dXV-1n_kwx_-N37yB37iR77r83_w6uXDQbn57_7y31gaKVV3YwQlZPvUu-42TTMUvPvcC2jbN159dD2Oj8fHX_zCVx6-9sZufXP56Ga_zWj06ORkuTj62le_kXIkYq0FVdkZACjjkMa9lIwkUIVQUfUglaODm0qRDEMFMoaZa8m1FmKqMVnnQzfPcWTVkqJqkViNMUZRRUuKUhMqWs9sKe724zjsrm9SKWxtf7KsKaX9brboIRffNjWlMk2aShpH2awBtOQMiM2io8bUVFVYtVjvvXdA3rlmdXzWnt2rdRymfa318q3Hz7zzHUenR8vZmUohknE_jjdrcrZEvfPSc-v1tuk8Sl0_eNy2bakqORoiNCaXHLqOiVOOKurQXdz72ObB54uimzWf-JlfnZ9dLJ---_rnH_7x73-3VBUAIADEg2UsH66LBJhZAKQKEtKBBQRKhMYYwEMRUb01PsNQqyq0ra2iUyxPdpNldohDkk2MCFgqxFK9Y2dMTBWRrDOiELNWUECwhlGxCMaSa60HXV5VZSYppbHQeRdzdY5VtAvMCs6wEE0lO2usIcfYOMeoU64XfZuLIlMRSbmcLHrPNE77p09Xnk0R3ZYyiaScgnNTic8crYyzj9bTK1cP3_3MrSnDo5stIQODdz6WXCssjuYNG0kFGe_OZ-84P2ZEYBzK9NTxERdxzr365KprupvdVpFay_eWcxH84mtvreOun7Uv3bpY-QZAC8Kl1pLkhePOsXvt4XWF-uztk91UXnvw6PxosWwCiFwO477kzTQ9f3QsgkOUz91cpihTzl3XLuZBVJ8MkzfmerurAgLQBHfvfPnak0GBjOExlvV-VItK2iBZttZwKppARaFrwmo2izFuxmG3ndAQKHYmWMJaZZwSOVas3vqSC3sbS1aVtnMqoKLGHm5pmFQll_mss4zeGwKxTSg5WmvYsrcWLRni4Iwz_K9-yAfTO6-H8X8zc2wMkWvYGHIIjMSIlqkiHHJiSGCYGdEY0qolVyQEBSQCgVIqEo6pWGNKVSSMueRaFXQokkRRMeVaKwpKzmXKpaoCiqh0oRmnyEjr3T6lnHMZ9iMQAqpBHHcxxUkksWEhWl9viRSKYhUlWd6-O91sYJhSTNSHOk2GuCL7tjFIICgpkZJxJm32bFByrSWjItVqCOtBHnrgzBpDkg_tZjiATg0SspaEVQmRDjIYVGYOfUds0m6LZBQZjAEARLShFa3Be9_5WuJz73j-ez_6rctgPv2l3__Cq_dtzt_14Q861_7DT_xTG9yTx4_n8-NK0nfLj370Ox68_tasn33nd3zk9sXR73329zc366dfuHt5ebXdDScXt9587VXWcvnwoSKiC6vV8WzW7-P01S9_xaJqzbvtdn15tTpZaBVFH0c5e_pieXx0-eb9NA4uhMXxku989McEqFTY7UZEZDaqZTbr9vtRqh6fLoEQQJvGu8DBWkPknbPW1pRJoW1Ciulmsyu1MENow7gb5_N-mFIpAmiCMTlnRmbHROiMlypkuF3OqhRm3k03TM1s1umh65RzN-trqaJagUI3A6glF-MdAaf9FsjE_X52slRRrdAs5n4-F6IcJ2ucCU1BsNalIYOaGhM5JyUb52qu1rs8jTXmXKZ2cVRrmi2OBHDYrXe7_eLkZHa0EAQ7n9eYjHeISuyqSKlS4ySlkmdUrlV811rrt5uBAHzfbm92J_dulVSqgPHWhDbG6Ns-xzI7OiOWaT9Z7wSd8Y2xmIElwXu_9ZvKWE4uzpq26WZtN-sA6da988WqU6XVydyQeeGZu-er2XN3lrePFhbRiJDBV15_Y77o1BggLDmFxqpU53k2m8U4hcY7Q4Tgg23asLncHK96VYilrHf7zXpzcdSdLHpn3PV6a40B0v0YbzZjqdWwbUJIqZQqlkkJpUgWNYZBZDul7T6mqkng5mYTcwEmMkRMoOIsxxiNMU2wofFTzLHmKSZVaZwzhgMzE0VRAchFpyHGXGIsOQp5F2tRpdlsvt4NT57c3H7qfNwNgDhbdDlOaUpdExpvvXOqRSp0fXj2uadY6slxf7Roao2vv3m1aIKUChWDZ8PIxMEZg4B0iHdjiQW0nh13i-P24mQRd8kgnZws33j9yfXlOqeUY94PgwKxNYCUCyyPj4ABAHMq3nHbznzottfXh_1oSjGXCoCK6C13y8U0TsbaGEdjTT_rr25u2tAgig-2VMmluGBBaIoTMVOw0xSbNghI1zgGYWJjbUmlabxBdMY0jR-mHFpbYsylOGviNKnlq_U-lfSuF-7ttvv9VFLKUcUgoMrZ-en5vK9FZo0_X3Uny6UPgYwV0bPTBVRwPux2GzbGW4eGqoCoAAqiSVNaHC0ZapFac93vti-98DwR3dxcW-v2u90HXnr-weMbsFhEickCtrP5uN_VWkVlebSY4iSgSmi8rVKBOMWp73rvXM2lQtWajbOaqwueDY-7CRhA1HuvVWazudSCCFVEUumXTclZVXNK83lviUtKJWeyhg3UUg_oQzIHfg_mkvu2JdQ4TU3XS8mIVEsOzgq8zYizyI3xAgdxGhJQH7wWQYJSamudEhQQAJ47JsGxFnYkVRkZpDIxWxbRVJURVVEPDN_DjTgTIBgkVTWMzlIpAoBEkKsemBlEBhCQ2SAJACElKXWI_-t__6_M5r6d2Z_8yR8eY0SW3_q9L927c_f89so7fvzkuuudc2beBET8tu97-esPL7_zIx-6fff2O9_1vG_tbNY6Z9MEb13vfuf3v_if_ud_65d_8V9ub_J3fug9_9s_9f3f_eEPvO-dz7__XU_dOW4_9_tf_X_-t7_2we_71r_3c_9DeeMSoU6phn4maLpZv9tMm-v9IfTy1jdef_Lw0Xa9vnz9EcakcUIBImyaBrA8eXD_w9_7A5_9vU9X0JqrNQiINVXq-rLfM8JBrkzmcH5VIjTeI4JWIWvVGEBAZ-s4sLVaqm-DFo3DwBZD28VpzwaVnbGmPz4dL68UxVhnvGv7xbS9zuMeVQ4XC7Zt5-er7eWVpJzjVGLJOZYpWxfaRW8sE4HmrFKxao1Jc4FUUMV4r1BjTDkl8A4YkF0V2E1D082sacjgdrO__8prueyt8aFvh3Fa39wgInu_ujgCVbZkyDx55XHKiZ1Fx5oLICuyCNpgmWnY3JC1Nb66OOqb2XyKUz-fX19eNoFbmH7oo9-kIrloBcmlqkBVqKUcPL9FRaV6Q0QH6wcwER-SVAACcOAsxSK5aGgDCFSBIYlUECJVGKtMuQZni0gpVWpNVbMqMhZQb81uKgqAAJ6pFK0AQIiglo1hTpIJELQy06yxuUqtYgzO5qGmkqog0BhT8M4ZAtFZ40quVeR43mz2CZyZxgRVln0jAkOsz99a1aoisJ6SIvRN0zcWxnRruUwib1zuSkwfePbi0195UAlikRDMlOKUMiIs53PRmmLJmF66dXIxawziTZwU653jBQJNVe6vN1NKYymt4-dvnTXMVenh-gYYT_vZM8crRwhIb222037__PmyM_5qm65rvnO2aIG-ev-KiI-Xs5JylKJET8bte25fWOY4lX_yyhPnKSsx8n6YHu-GR_txmNJ6uzPeL2ezz379zadPV9upZtUo1XtryT24vu77Jpf61K3TksVau5lyIdyPI6DOnCHj_uArr_nGO-Obzu-u1iXnWmvbhSJ1Pm9qqsZwHCMDEQIRTsPAzN6HnKN3NjhvERrngjMAQNbmnEpOxjAidMFB1cZba6kPjZTijPGWWcEyhcZbRm8MOz7QWr0zztvgLAEgoFSpoiKFiCRXRHDGiCoRlXqAbyGzqaUIgHMWCMcpJ5Exl2E_KmIFkCxZa6nFWzNO9Wp_461FkaSSYkxShnFKpRYQqWKdaWZh2E81FjTsLO82Q1X1zoCC65sxxpwL5cICadyzsapVgQxS29nt1daGpuSIAlzVIezXQ9s2eRiNdWkfyaJGCV0LtaiqC76WzMx12kMWqQIgbI091LpiJAHDBomMNTVmJUKyoZvFaQ-KNvg8JfY259T2M2Y-uThDhfXVo29--X0f_Y4Pf-Nrr6xjeuWNhz_6se9-8daFseYT_-Rfbnf7h5ePaxbm6o27uH3n4eWT9eW667v3Pvv8195482tfewUU50eL3TYy4cP7r8eYNldXpxfn6-3wXR_7vusHD7brm3GzS-NorS1xKlOZzxpHWCtq8Ce3z2fL2dXDJ9cPH5_fPn9w_9qHhk9e_oH19Y1v22EafWBmril3jW-8y1WQsW2CVqgltyGkWPIQG_s2SilOCQibNjCaYRiMtSpqvN_e7OaL2bSbQABB2VpjjUG2zCrQGBZkrRKHGNrgfRusi8O4XC122613rpnZQ-_CWJvGaCx381nR6kITZguqIprTdqOCNZUqamc9WQ_s2DokrIBSsnH-cGssB7drrVKKSnHOEttxGNMU--WZCZadNaEFFHJO0IIh2zapVgAgNtb5Wury9KgOk_GkKRMbIp724-x86a0VBcLDQjW1854QXNNZY0rKiMDe7ja7k3tPtV1X60Q2lJJvf_M3xfVagI4X3a2zk7ZxFkiSXJwdW4B54zsXlsvudNY9c_voZNG4KkezwIwWwBBirYaYEVIuVVWrGGZryZKZBT_uxjTuq9TQBGsQKhytur73JZcnj68rViByzp6dn0iuB5HafpymJGroeth3bQuEw5hi1lQLACAAGTOO6RuPLlEJrd3nPA6xCuRSh12ybEtVg2QMeGv6vk-pOEfjcGh2YozZ-yam4i1nQUFiQyJacxEBIgJCAFislvvN7vryaiq1puKNA0RRIAEffGutxGwNPvXCrZKFSQ3bxtK982NnkVI2Ii88fa4xt8Gulj2KWMeGUEVFxLGx1lnm4I0PgRlJ0VluQ2hcU6axVnjlK6-TY-t8AYwxV9EaC0oZ93vftpKqs36YYjub11pc6HJKzBZUkfEgfohjdLPeN36_Gxi5VGU2qjLshuACIZHhWhUVEKiWXOvbK-whUaVSDRutIgComHNeLee1inV2eb6sWQ2ZO_cutJSayjDEIUkpen2zHnZpvx824_SlL761XM5K1b5v33iy9sF5do1lQzAPjcSkRR8-vmJnU0opl9XRgggVsZQcmlBjsmRqLZJz23dvV2CQ1sNuNpsv58s85Sq4jvni9tn6emsZIedSCxtoui7nnFJCwBACG6uH30sBEFKtxqA13rdditkHn6bRWD_sx361QJBpyGQAieIYfWgRiZhVQUWmGEPXl5IZMcZxtpx7Z9OUybk4RUMAwEllOVtM03AoS7R975lKkXEarbMsIBUF1RvnmEghltw2DpSQgAFqEeuwdZ6JQQ8dSiKgKlUVnGdiU2Kx3hISATIR0b_a6zMS4MElWXNRQZFKyIaBCAnoMEBFBEI0b-_4FfTQsWQAVURBJTar1epTf_CNvl3YDn7k499bajYoX3_t0dO3L1564cIBvvTC06t51zJ13i5nizHXYNtnn7lYrSy5-i9__7O_8k_-xd_4m7_4s5_459dXV1_83Cvnjv7Cn_3YRz749Hvf95SbhSb4xempjPK5z3z9__HXfmoc5Q__5PM__V_8vY5t4tJ1q-N7ty-vb4xjy9zOAiHkoVaJolpiLjmat4sQWFQV1Diz2-y_50c-9sl_-i-L1poqIpGCsU5BtRRQJcQcE5I56FsESQnRMCDVUkGgypB2k5stQIStrTkriLU07bbGhubszrDbQclVJO02YJDY-GARTZ72hqnEJJJV0TahTEWqTDf7WsX6QC6gqvGerBmHmGOpURBIAAzR2yaQmMs0pv2uCcEAHbx-TdPUGlWz866gdssj13VhdnT29D0o6WCCs03fHi_yOOk-t8uWjS0iUup-swcAMNTfvp12AyJgBnY-xVSrxDFqKSUXALffT-1sJSW3IcRYj4z7oR_8cIlVCZAxpVJqrQqHzFopag06CkXkQDUEZEIChSJSVSuoitSqQyzGmKICjAoQiwoCIqSKBUFUDVCuosSiB5Q0pSo-WDYUcwGE4CwisOEhZuNIFQwjEVEFAigEM8er1sVYVIGZFq3PseRcyBgRMUQOwbNZNO56mJZ964g3-zEDQi1EeLqc7Yf9-bxZzUKpJVW9vBkQgYmn3f72yQqJHl1PX1uPd28dp3F8cLNPFQXEOxrHuN4Ns84fz7vr6x1aaxC_-ZkLz0QM92-2F_PeIiPCw830jfXlMMRx2h3NuqePFyr4aBsfrddN4Jfu3j7zHhDHIl9_88Fzd0-O2qZk_fzrT05P-4U197dxSGW1mhNB8EZFXr-63NfpHSezVFCBL2-2g6mX67HmrIhvXm1KAgH0wc9njYg8d7ICpOvdOBYZp6QgtYoSTlNSwturWUyghFfbYYp7FeksHfWzm83OeAOC1jooedhuxzG5NpRcmY1l0klyKs6bmrJzFkgZyRnOKYbguqZHLQbRe7NczEV0uVzs94NB9MFRxcY6Uu1aW1I5O1ohgEHyhqWqZZrNOsvkiZ1n7wypzuYNIZlDolGh1JJSMQcNGZkDHhCJpQooVpXggyCIVGtdzCWLIHHMIgBkTSpVFEU0pmIMC8p-mqaYGx-mVHb7IZd6c3nNbGKKY8xILAK5ZClibLcfNr5pGWHcbHZPnhhn5QC7Ahk2e-OtVHStl6nCMNgylTQRGqjFKBSRkgvl6LyrJQFUINKanSNNFaHm_V6RrbclJULUlAhAJSGRtS2KAGEeJ2dMaHuVWnKywQOga3vj7PXVk242E1WVCojAtpvPGNg54wwOY_3Xf-wHyn4_n88eP3my3m2Z-eJkdf_J9nc__2VHDqBe3X9yfn7r3p3b63EzbKbzi-MPvOddOZXPfv4L69326Pz8ycNHOceS6267UQA27l0vvfPWndtM9OoXv2EtlzhqKWm3a7qOkReLJXkfY3arRTtfta199MaDtve55G7WH927w-_8kT9BFOI4kdFxP-53-_1USsWm94y03e5TiU3j2ViRQgA55bZvilQmMIbbJhjGKqhEm_1URJwPoCg5IeOTzQaRfdPEnMmwqKaS5otusx9Xq5l3DkCNNWyYGUHFWFursDOrkyOoAEjeu-CNVBmHnMZirGU2YbbSXEGxCTbux1qVnO36BTO5JrALOZVmvgRFakMtytaYJjjH4z4RszIwGwApOY7j1J_cmsbd5mYdvJ8fL8chllL9bJHiqESl5ND242ZaHF-A8xLjOE5t31kbxv3UnxwLYJY6m8-Mxd1N7BfdS-98r2IRBGDuT5bMtLne-r5dnd9arI78YrZ_8OjFd7971jaA9Py9u4t538-bo6M5SDpZdk_fOcr78Xwxu7XoPTIROEu5KCBZR2FmUyrX2x15E1UPxDZiyjmeHq9ms4aZjo5WznLXBhcOARJbitQi2ynP595be-fOAlMFgJRTqrUUWQ9ZCZAwOD9OmQ1XkVTq_au9dW6MZb2ZVNT07mobx1iy4DglQLLeShVVYKQnD65D5-fL8OjhzfV6x0yxigs2VQ2tPzCbs9RpmADQNxYKK-Jmux_HMddqvCm1LJf9i0_dvd6NOaem9fK2zroSgXcMoh1r533Tt8erWe943nhD_s7Z2e3zo83V7mjWNcHO2wZEERQUKmgBZaLgnCqIaJVKCt4Zy5yrjmm8uR6erNfd0XLI5Xq9a1azXMs0VXZsnTHOjZvRNZ6DR7a1VuucaK2l1pqd8znl0M6QVLIgG9t66-y424Xg-8W8FhGtpZScc9f1Atq33XYY2QAbjqn4JgwxOe-QFdlYywaJmIBxHKbQOkLOU0HRk-NFlerYus4fHXeu820TGPHuS7dTycOQnn7m9JVX3jTIr7358J3P37aIl9fXIXhjPTvTW9s34dFme6ArINIwTVVl1s-mcZimSQSUKE2lxJpzqQqhaYxzWqsLNqdhP45obSnJE50tT6YpxhpFxCAy4mK1SnH0odkPQ9f1bK1WcdaAig9NnpJobrwzjkvJQGwdM2vep2Y-qzVVgVqisy5PueubnGuFYg6wFlXnKOfYNm3Ote9aBZVanDdSlR0jUZymO0erVEqJNZfats6xU5IcI1urUpkYAbxlZjwcPYO1qKggxjEjd96QHsg02jDnWpUUEECACQUg58zMiIBAopUBAZQQkbCqEBEyllLJUpqqErBBi0QEBEQK5pDJBq2iSAj1EJYXJGJSBmqD_9t_99eCd7N73Q9_-zelnAPB3_8nX_izf_jDjQmQUmsIqziAvusj0uMH67_wF_-v_-Dv_Ow__oe_9t__rU_881_85LCJL7_nnX_uz_7Rj7z3hWfuLn_g-785NMZ0bdt0tdj9WL_0jVf-w__bf_PFr77hoPk__J__zf_gz_1fOm7BoesC26ZbLaQoGWLkcT_GWHJMU05Fagjed8EYBiayVoldCNbRzc32O_-17_mdX_90kSQixGzYqjUV3lYkiohxRkTZWBGhtyXurALkHLEh25rGYy2IyIiAhHB4LBKnQbXMF2fACFoUAFFVNO3XNU0gFQmsMTEW6xoiquMEkgHVWmOCrwdRrfe5VDfrqQ22bUzjydppGG03t40rKZIiMtRxmnYbSWMZNps3H7hgJJXgGuNMzsUyszMlp91uHIYR2LKxF3fv3H7P86jZt853XZqisUygxlqpePzCM-PNdVon1zjbNSSqpYgWQJ3N508ePPAtp3FrjW98UyF-9Ee-673PnE1TRcAKVUCziCqBKCAcMv-l1oPaAhEQ0SBVUQBERAUMhqsCEaVSDmKKYSox1wqAQBXFMi9amwqAc7mqABCjIgiANUSCRQFUg7e1VmeM1Oq9k1IREAUJavBWh3LnqOUqpGosGVBvUESd55Szt-wsW60za_o23Gz3F8s-jkURhpQbz23jW29qyXdPV6XU7ZSutiNaAwCSSuPs0aKXSl-7vDYiT5-2X_zaA2abtdYq3kAptUp99s6ZZNhu9mT1nbdXL5yttsOIjFOanr-YS6XW2tc3Q5zyfhqc1ZefeorA7nN99fENst4-Wb10fqaKSerlZuz7YIE82yHWb2w3L57OxwqX-7FpXM25dQERq8gX33z00RfuWvRj0t_6-v0tlsv1tBunzW6aUimxAInzLku2zm-ebJd9N-WSAB5frRfLWVV1JlxtbshRyHXuQxVZ7-Mw7OMUDUDjLSJs90kE1HDN5f4bj8hY4wwarLH4xuapxDE2XUhTJNCUMigwG0PERNY6w0oIs9mcEVCga7ubqys2RAhd24OKRZh17X637vvOG7KMNRdjLDJ0XbCWHZEFQAVnrT8IFAgdGwLNVXPJRCamnKs01tdamQ_MfQWFUqtUcY4ReRxjlpqLZJGUCxCXKgIkUKUogo5jyipVBQj3u9FYLqrDsLPOEphpGsnaOE3W2jSOZLFCUZE4JVVQSQgqY7TGlFg0FhdsHAYsoAIMILlSHmuGkjJbUxFKUZQKVaqgEJZUFYGBVFUQUIqK6qHhy1CnERXqOLBzmiozCUiplZkJyDCBigqQIWuC6Q5S0UOFL7JlBVxe3JrP-5pj37e3VrN__Sd_LO22VIBP_M_89D--ut78-Mc_SuD_1s_9o0__3h8I0-lxc--pp9__zd8ypuH3PveFWducHZ8E677y9Vc2u912t0O2UmRxshi22-uH14ujozt373z1D77x7AvPvHH_4fWDB7P57PLBQ0RIuXgflNk07v79x-F4TuhcaNaPn7jWsm1Srce3jh7f3PBT3_8TIuq9TTEuzlauc4Zgvljud0MItl8s2BrD5BBzqcx2Nu_GYTpaza7W-6N5P4xTTEKBARAA4pSQNFg_xtzMegbc3gyIClBD0xABO6NELrg2NCVlGxyxSWN03kuBIpWQAXjcD-4QzlP13oFhYwKRUylVpcbE3mpBBQjzWdPPAWG_3vaLI1G8uPP0ZrdNpZjGS9WD4llVretC32qtCCQgxjpIUaVsnzzpFquum23XW9vZ89OLqVRm18x6v1gQ0ubxE3YuT6PkpKBIlMZE1rtulqbRBOu915qXy9X8aHbr7m2VcnZ-0q2OikpaD2VM3nIa9rvNLuayOj6ezWbb3U5FZsvFforeubYJRNC2jfdm3gdvjDVGqhSo2yEyUcq5FkGF7WbMoMa6YYpKtFnvF6v5Yt421kEVkeqcNY6tMYaoaxtj2SAQMlt2XvIoWGHeeG9MnOLVekDHyJwFY66laDdrpqTDlFKVmKRCZYD1bkI2-1yHpOt9rBUPgYYqwuxKrSE4tsSG274l0UdPNsAgglNKxlkwZK1lBSny1luPmsYba5NAjKnmEtgYZ_ZTTikiMTuzHSYmJELjrFQFQkYyZAxi3E-xxNP5ogxT1zQvv_eFp06OHNPxsm1QLk4WZ2fz42UHUg2itRZVhylOpXjviNAQEYMxb0doKxzOA0JtSKIZEJwRppxLu1hOQ-yPz6btZM3bU3lVAQBj3H7c-b5t26ZmDSEo0H6zJUY2RIDjEJenxyBSckYgF9zmem2Jp_3QNA0oIWNom3E3qVKKhTwZw7UmJE65OmsJIOWcs7jGemsIoLV-Me_IUJrKg8frhzcTKN1_cP348mpIev_N6yrQOvf4rWsbDBAA4M3NPvTt-urm62_c58a88tqj2dE8q1rjHl1uuq7xbVOrsmMCYOJcNaYSc0R4my8UmpBzyqnGMddaT05O0NrNzcZbE2OqIGdnp6XkmhILxBQX83nTBNeYYPxmt7WGV_OZQR5iUZUQAiMapr7tc8ylFBCx5BQ4l2KdBdU0ZhBB4oLi2jbnRAqGmKwngOOj0-16b5mR0FlbS80xtX23HxJqBaZcqzO-1owiAspsFm07TUkUXTBaCxIL6KzrqwIUcY7a4A7WnMPD7ed9KVVV2tarqtYCANZaVCBEpEPfixCJiYgMEdVciVhJRQQUiLAWORwJchJ74LAgIIAhZGRAQEZUMER8KBcjIgBKDaT_8O__s4r4Td_8nm9-7i5VbRvONX7bO29TlqN5ByA1Zxc8W5OjfOPV-7_-K__8dDH73u_5jkevrf_Un_6jP_xDH_3O73gf2DoMm9Wtc62SppRyfeOtR__Ff_W3__E_-OV_8Wu_Y4R_4s983wc_8NJ_9p__1AxpmCZuQpgdTZWWJ7eurp8E7_f7SSsIYqpkumZ2vCBnSwVQC2yAWSoZazXV_ZQ--PI3feWLX8s1SWURQcNxOgyDKwCAKiADYRVgImICABURqXooTSBrKYd9jKoqgCpJLOTYIteS6jj52QoIXLfKU2ICqYpaQaGKFgE_n7nZgiWp1FISsck5sw9K7GcLP--NsSnmOgxlv8uKwOy6BZIdh-y6xfKF97FpkQ2TjUOConmqMqY8DPv1dRp2027LhM5ZBJj1fdM3ioy55JLWVxtrWUBns9Ww27VdMw27YbedHy0lJ9PO_Ty8-L0vP3rlQUzJMVnnjCVWAJVpc5P3W8l5P2zdbPEf_8X_cdnsD0fTmGsqtSgAISIaNgoqKHqIPxKpYhFRBAQUhQMMtKpWAQWtqtNBLqlYFKqIiBbRzlkQHZIkgQpaaiVCUQjMDIDGpClZy1Lr4aU0xCllkAOkV5wxIZAjXThqrEGmXAsRWMOGDgV4vBmnlqTvQmd5n7IiHHX-tet9qRUITpZzrQVIzuadYxSmJ0PcppKrllSb1t1atJbkCw-21_t4cTH_xms3ChyLjjEvlv3V5dqw0QpPna1udmMRVU3f-sLdZeP3MSmBM7RsQowZjf3MGw9nrd-N44u3bx_3vQo8Wg-bGptgPvT0XVQgpIeXm-txXC7D7b5NBd642d5ZtooEtWSEPjSPrjfWcgguS1nMmovZbBp1E8vntlfEdkjlZtjHnNqm6dpWc33y5IbRVognXd95k6SkLGPMoQmllv045Zzb1t89OoKkaPnJdrOfRgVg5jvnp3HKSDSNU9N1u-0eELVWASw5IRI6U3IppThLxFCLuBBUtQtBSYnYO2MMWjJSkjN21s_GuDfOsmVFYWu7rvGGLXHXN45NF5xz1ntnGC1T37QK2PngGYO3wbJjdkR8CH6JHsglQ8xTqW0wdBCzE-VSUy4KQkSWDAFWlVQLkpniVBWLyhizAhapIphziTE5a6vAfpykaCql5JJFSs6awRAI4TCM1rlxu2Vjx80uNEaL5BQrYK1JUqw51pQcGsnFdsF6X4c9Qa1Sa4zL85PxZmCqQAKGCbGmZJFqFePNuB9CYyVmkSI56-GccOA75FxFQQoRISL5RlGIXSkZshhrAEhBjWER9E3numa_3c-XyzRNFo1xXgw1fae1dt7_sT_ygyfeOW8fX63jbvuJf_RP2IeXXnjqzq3br9x__Duf_tKtu6sXXnjmwZtXL3_Le2a9_cQ_-qdTlA--_L6jk-UXvvLK1c3VsNk1y9n19W7ZL1567wuf_-SnvTfeBRZ-6b3vfnJ5__6rr0nOw_VVN1_FFFe3Lpg9WHPy9F0sMl8ta83TzfXy5KgQr6-3rXUvfusH3vjim3znwz_knbHWpVQev7Wepjzth_XNxluHiCoiWVLMBkCRgreNM23TQJVSYYxRVcaYDDBUnc9bIhNjKTV7a3abrVT13uaakM04jG0IjTFIJFkOxYCSKhlyjU8pgSHLhghLBectMQhAVWVnSq2KwNYAsFQxjS-lIFEBYeJxv18cr-aL2XZ9LUV2-83p7TsA5Ju2pOq6gKCAmGMWUAa2oak1l5QO2hQ2JsVJJZ8989T146s4TsgouQChivimtSFM4-gbD4BExM4RkO0ahFqqOOtt4-fHy_lq7qw9mvezfqY5dV2zOJoVhN16XN1aABJCbft2mibrmvWTV0_P7_azlrAeH82YVLQ4S4aJHZBiVb3c7TbXW2MYLSpSSlPJsetbMoYB29CuN3vrXKk1jlFK6rs-p3gIJiBA8L7UevP4JrTeOUZEzSCgp6ueAFOpMRYlzEX3-8LWGGPROCC4vhkKoALFLOvtXpAUcIy5qMYi01T343S931tmUVBQNlwVSpW-75hht51C53MGQKgiIGDJ1KIgstvtj0-WRGa735dUVQ7aMXXeWmMYwVqzsl3MsXFus98LEDo3jOOdiwuQeryat62zLpjG3T1f3VxvNruda8yzF8t5a44X7bIPJSapRXIGIGaaUgGVrmtLzIdGpoqMUxpjyjnvx5RF2fGYJCfZxyQgOdc4FVEAobQfZrcW42Yka0WV2KQU23kfY5otFjlObE2csuUAoCpYi5hgALTWcveFp-IYi1RrbGibkid2dr_eHF2clKShtexciTFYk6aMCjkXbh0qWGsO0z5nbY4lxcLOlCKl5r7xq252-2x5vGrJGgvStN5bKlKUaZpSZVABQfTOTLupm3mtsLtZX9-st5v9zWbcbhNbKiWPqbA1XeN2mz0CtH1wlruu2633oXdIpAq1gg2OmFCBCOM4PXf3btO566t1FQAoxphaamiCsWaKZZrG1WKhAs_cuzCIgma73Xezdjmfx5xLzlJEVQ3C8fEqH4wvSE3bEEses2kcoEgRMqwKUkrbhpQm5ywRLuez9c3N8fGy1gJQ57OFcwxIoOA8EbJWqUWdtYBgnUlTKirHy97aMMbJEJF1RKCCVaVrrLKQkgscjD2kPA9fPGsJQFORPpgqUHMGBOtdTtUYQsApZUIAPHBgkZCZARSJULQy8cHKqgCCWKoeqpNACHLgK5IhtMZKVYK3d7x0GLl5-uVPf_nm_vpD73_pXS_cdQTe0_e-917cl1LVeFJAIZqquxrSz__iJ3_rs5__S3_xz7RL863f9eH3f8cHnn_m9qqfZzEyVt_215ePf-lXf-Vv_jd_99f-8a_81j_7l_VmxyitpZfunfyv_vxf-Kt_6-evXn-d0mSCt_28glHnCCgNu91677wLXYvWt8eL8-fPx83I7MQ7AKyoAIDMoCDKxehysZpy3Oy2zJacrQXZMhKqSM0FiLRUNgQqAIgqgECKyHwgJhnvQKuWcpDpACMRkrXATsYMyKB13N1QCMhs24DESFYBgaiUaqxlpjQMkrICMZFxFohr1u7oVGoBASBmF8J8ZedH7JvQzdvZHIxpZzPb9jmNpnGVuD87Wdy5y2H27PvfV2pidCoVimgpabfZPHqwu7mWmAybEHyp4EJQq9OQpRTnw83NjSU0lqBm8t4YnC2XoOzALo4W99-6Cot5jNX7tiLd-vALP_SHfuw_-A__N3_mT_zkj__xH_tjH_0WzPssUEDHVFIpgAiAjGSZ32ali6oCAFZVIlBFVaiiaA5ALDnk6XNRACQyClAVD69iFTWMi9ZkhVgki4Lo4TV2xsyDUyBFqiW1wZVSreXOc-PNFOshakoAhi2hHM39ovHKHFMtImhwcdKxwHaIrbOBeN7ZmXdjqorUNM2DbRpiXs466zlOI1c9X_WL1m2GuI714eVgQ6MIhuF01hiVL7612ab83L3j1167zEWAaD-l4LjkLKUa0nc8c6tkefWtq8U8XCy6dz91XhI82eyZ5XTWOWtrlquhXm1HY9hJefHORfBOld-8WpcSP_DcU53xzBSTjjXN523vHCi_cbW9GffLWccgqvjK9f76ZtzH9NT50Xx1_Mk_-Or7VzPvPbP7zS-_MU1ys41KmKbctMEgO-MLIxuWkheNv3d8tFmPT653VVWAdjf7MSVnXEqxMaa1QaXu0pTHogBszcXxqjXsnNtt9jnl-w-uYilPHj32znRtm1LKWUxjypC9tYeMonEmtCHnnIa9M6YJTc3p1vlFcLb1ngmcNypaS3HMli0TWcOMDFBDsJ23wTnL5IytOQdvSWuw1lvLhM5w2wQQYTK1TIdTaBWNRbJICM6zmabsrdlNqZQK-LZJkRkJoYoq0pgSM-_2E1snqDmXKlpRpphVoQhUhf04ItE4jdaZcZrilFBSycUHv5-mYb031oIoIqqWaT9S8DllYy1bE2PKqRLAbNnsxzLt1sYeLOFcYlIWYxxjSfvijFcQowo1G3IAiqV4RhXRIixonWU2qmQsqxRnPJRsGGsR4xpVqTESMYMiUcnxMP73TasCQgRVrDNxO3TzNgPMF8vbz9-5fTx_5uQkWOMX_eJ48enPfe23PvP7pmnvPfvUi089BVIuL8fPfPaLL7509_HVtu37Z-_cevPNx2-98sYP_o--f7Hq90N69ZXXpv2YY33uHe-AUk4vzr_4qd_JY8oAXb969sVnv_HVLz1887GmahR80-x30_LkVEWUqF8eaZQ6TV0brt96MO5Su-i7k8U0Dt7aR68-fvcHX-J3fvxPJc0A4Jq2n7u2wVXfztruaNa89ur9m-2-mTfBOiXap9KFAETGEBJ4Z9rGS9FSayqVkTfDmGtVgdcfXHeNQ6UE0nadMQYME5IxFgFKqYRUchGthOTboCKINNzsmFFFrTMueBtsP2-8dTWV-XGnRQRqs-yICNiIGgW1LuQ0aE5xSOz98cW5s05KSikZpv1-740ddpPxzlmfa0ZAIUAk07So0BwtJVe2xjIM6904bM9v3QGtUmW2mlfJeRdVS3c0b3ybYmFju9k8p4zE_dG8jmlxvPKOXWiMscvVog--ab0hattWUqYqYHwz7_fbqZm1jpypeHZ-Krment27fe_EW26s9cQpZ0TVKlCBFQEhV9nup-Wyy6mu1xMaBqmABoBzKkVqjLFUBTLTMA77wRpjnFXUA4ijbzpnyREfH89JwRIxk4rOZ6FxnKoo6FRlilmRM0jKOkw5V7m62bZdt94NAjjEaIwLwRvvbnYTWrPZx1SqsWbWtBZN40PKWRVAQUXXN9tpTBWxVCmi45R88MRGi6hgFfHBqQIxDbEYywqESCUXRMylKGLbhu0wkCISBGdzKm8-eHx2cry-WtdaROToZD6VAkZd8OdHqzrsu771qI11i8ZjVWu4ccZYk1NWAGC2lkspVRREDZMcLIPBlSKb9biPSRRKxZiylFqL1KrWuhizFFCVNBUOjqwtQ7LehL5X0Lbth5vN8dkxAoz76SCgJTbGcs2JFFFxfbO588Jzm6srJLahybmQ0EHaXmoBMMZ7UpCSQ_B5nFS0pIKAtSogEZtSsrUG-TB-03HQVPKhMDqbNVwB2ez3kzMOBNab7c12zLlYbwEADZLBXawmmONVv9un2aLLJVfQ65uNMX5KddjHlCIhjvuJmSyRgnbzXpFyznFIpPD4ah3aYAzttkOpZb3fr5ar-WqutQzbvUJtuub6Zu37cHK8SFPZD2PTtJthd_fOuSUU1WGYFEBQjXFxGKzhVEpoXROacYq1JkLx1hFRjtMhAFVSdtYEb1TLrJ_tdnvU0gXLbHbDtm2a_TiJluPFHJDHKVapxticCxMeIvXBNYSapyiEXdew4WlKxFilMCIQK4Jnz5ZKTG3TAIBobb33BCllw6iIItK3gRCkVNFinM2psCXDXEoFEkakt2dEYJnpACA7WFmlGmJQrCC1SAWQKs4wIh7-BQ6sCUZEIkRiUEZtmX75X3x6fXXzf_8__VtlO5LWzWa0BAkILKak-31-_Gj9V__2P_ipn_2ln_kf_undu3d--Vd__Td_-0svvPj84zcu7z944_U3v_5X_j__5c_-vV_46Z_6e7_8iV_6yme-5KV444ILaCww-c7Pz-9dfPNP_Ozf-OsBiuu65Z0TcIGdUUPjfptL9W1bBS830y4hEY1XQ8nTbkr7bdqN6f_H038EW7tm933YCk940w4nffHme7tvJwANdCMQSQRIGpSoQIqiZJuyLJdDiZq5XB6o5JnGmrtcZbtcLstFyQNSlJXBhECAIIAGGuhudN_uvn3jF07a4Q1PWGt5sC88P-cM9nnr2et91v__-81Jui6iD0AY-qbvvBhdXF7tdntjT96rkWs6NG43l2U6oJpJRURUNRE0UxUihpMZGNHEVE7kJwAVneaKqKha1RhBlD0hgaZc0kwcTMS3jpoGCMBQpVouAEZMp3VWLdkAQtvO-3uoRdK0zKOYVDOtQsGLAjgf-8E4iknohpQFhlV1aOwzYi653Vz0Z-dX734FqB0ePq2l6DSn45TGw-72xe7F8zh03eaSTNfrTb9dJZm7fp3GcVh1u5tdCNGIHr_6-Hh3rJKvHlwkYFxth4tzrWrO__v_wf_y137x6yVNtS6kNUuuSklkydUACRGBRE-QTwAEMcuiiIgnbqydXh0BEMxQzUTNENVAAQTNDA1RzQROlSJgshZ4yXJfTpxGMAQx2fYNG5nZUk2rNJ5SrkMIsXElWc6iBjEyAQTCdR9eXzVgyEjZDFE3bWDE4-7Y-bDuQutw3fgl1aNoKnq9n713w9CpyXS3f3K1fbjp1128W-r1bq5EijTlPE7L5x6u2fTZLu3Niun1zWGaEoVwO44h-mVeUimt95vYnA_9R9f7eVku16uvPD0Pjg_j7ByeDV1DXIsKuB_d3m3XQx4Pbz55tAnBDD-4241p3jb-3cdP2FDBbuf0_HB47aJnw_vjtC_lbIhDaMDxxzf7T-_2d4djKvNPfu7V737wyUNHT7crEfvR3fyt_SFc9CLoUN95cLZLuRbdjcfK4AE6716_Op_nTMElx9NcVCSEMOW8Hfpcl6cXZyZWxcz0ME8G0Effe9-z343Lx89uKXBeqogN62G_G13g9Wa15BqM8lIlzU3fogExl5ybEIJzjKRSrrZnhIiIbROb6MgUiWtOjpgI1sMQgg-OI0JgCsRd23RtKLlGR545EHkiNIvBB88O0Ts2qczsnMulpKrTvJxckJ6wVKtVwBDdqSAAhtD1jamKYa5SioIKOl9rzVWkSi5ChEuqgOA8HuekVgWAiJd5LkUAYVzSej0cx6mWqiIlJzMVlW7V1VIlLzkX34aSK8Ug8-gQVBA8Qak6JzOFrKS5JgVDMoOSPSERlWmBKkxkiGzmHKtITclAUFVRCYnA0ERSjj7keVETQHU-SimoSsxELEVcG4bzbVmK71o0lSxSK5N7_XPv9F30TXe8y3_jr_7ym48vYxOv7w6_83t_cHcY7w6HV9969Ts_-vhXvv6TzPTtH36_SCIP7777Y9u22Vyuf-uf_vOf_NpX8zxz7L__vR-VPHdt8-i1Rx9_8OFrr73-8vr5x9__YHW-WZ9dfvXnvv6DP_qj3c0-LfPQRjPJta6vrsbjvtkMZV4evvnweH2LUm5vbkM3vPLuW7XokgRB2u16-vT-3DfMn_vaUqQU6FsXHN7dHFFxGRcR8z4yu9vbeybixjfO3x3H1nEVEJEucskqRQWwqBjAMqeUkqpG58Z5abpBqtSS0FCrAgCaAbKAGUgV7YZufT7kOXdd66P30XPw2-3GwABQBfNSQgjERAKMXqtER8DeVEMfc0rsAiC5EOtSyMNxf1A17-PDV98odabgwKzrW9dGhdMpqWjIzExswCawffRKKTP6mJfFtyFNiwk8fefdcXe_Xl-E6MGsLNVHRnKAZEgKaOhX52fzYSbkbugN6Gy73q5XKOL4VAlUZ5TmOXYRwM6vrvpV_-TJw9V6ePT0gY_Naj2AqUNs20akplkQMXTNYT85RlMc5-QJBQhMQxMRQE3X6wFEAKDZ9ve7aamy201S1XmKMTrHjpmIYuBA5BkMbB1DttNlD6spOVeSTEvhQKqoptUgZZlrnZa0LHWccikiVYip7TskbEJ4fnsUhXkpBUzVyDGbQjWVWs3EwJBEbJwWdJRSJTrJ4E78aciqhmgAKCYKRBQar2JqYGqKWKoAABCczgUxicx9G8jx9nxFDGlZHFNJuaR8drH17GvKOSXn-dO7m9cfnl8MsYuewbxnBPDOBxfIYeOdVjEFFcmq05RzrsToHRNRbAMhqUHS-uGH1-O8KAAij8f52ad3zCiGPraiAGLdpmfvlin162EY-vEwHm7u-_U6leKDByDvnY_OzLr1Fs201rws_Wolqk0bmrZVre4Ero5xf7tzzrFjKcZEDGAKVi20nWotiyCBi05ydcxWNQQXGzYF1ZpLHY-5CW511t-NmQC7PpphG9xuWowRqqZSCcl5Xq_blLIBHI4LO8fOT1Oel9IOjZlIkeC4bbtlGR05M4zkcy4-utCGCrrZro_Hqe3d09cfHQ_ZezoeF8n6-ltPAeDubq8gzodxXIah355tUimh8QYoVS_P1s55MDRUzw5Q-67J5ZT114dnl23X5bRUMzXs2v6k4A3BA6JzjpC0mGP2zpVaBbTxIVddcn7w-PHhsEeEVduu2iGVimA-Uqn1dLdca1mthiI55-yc3w6rwKHWDGBm6Bx770WsCSEEv8zLZmjnVBBsPbRSRay20YuYI2pjOKm7ACE0LmdhQmY6nSe1VgpUqxLRCZaCAME7BDIRYjYEJBaTKpZE5LNQB5wmf0IyUDNjRMeMgN-8v_valx_8pZ_43Ps_fOFiULAQgyreLeUPP3jxf_8v_vG_-IPv9F3zhc-__lNfeePf-p_9ladXZ__V3_sHf_S7__w3_vFv_e5v_PY_-43fvf_w1lVlxc2wIReadnXx6OlcaXj4FEwA9G_-h__BH__wn_7wd39vdbmZ1KrQYZcFNJeCpuSdVCvF3BDCxouUEEgNC4FrfNuH9dVGSwnea87M4GJUg6evvn7z8jabYAEFYDA1KMvogjNTRCNAQyU-pdVNxfgzrRU651RFa2FiAMQYnHdg6BhPvCQgLKWeKHEmOcRQcwFR8g4UiJijMzBUk1zNAIiqaOhXZUoeFaSaFAIlUwAAQB8a9J2ZGfiUkiNE78Hc4fZl58M4jl3fGZAyGYKAGrv24mG8fHz26tvgWEomtuPx_v7588P-sN6eqdqwWpEBsRm6m-td0zrAcPH48oMffRgYu8bF1UZ8cNH3w6Ydmtvd_Bd-6it1KYpgZtmwmCapRfWEIhTQU7JfRcVAAABRVQDUCA0UkfDEZPzsowEAVDMxZSRk_KwrTGCIueSzriHDfSkGXKt4R55IpK5CIEUxIUJQiYG9wdD6QJSTlCoMwOSz5O262QYXiQSo1GqgCLCNwYNFxLZxbeMLwH6R-xnmqoe5rFY9Ik67JbK983jbRxcC3x7re88mdDxmPS6llvrawy2L7Gf5dJIPX-xi68alLrkYs_O4zHMqBbQ-2Kwvt32qdHs4qNrPf-m1zvHN_WE19MR4tW7bJo5zWap5z9NyiGBvPjgL4G7G5fu7_eOL9ReePmwAQe2w5JtxfuvRGStNSWYBBL3crpTwfr9869ntlMqw7mLjLzarP_zWRz_-1uOpyFj0d9977hxl1ZTL0Phv_uD6cJi4CaGPvW9MNFRad03swu2Ux8MCiGKas-SSYqA85_PNqprd3OymeWH2zvuXL3dvPjwz4A8-fj5s17f3RyJX1Jip7_taq6od9qNI8Y599Kq0fnB2-_EL75yZ-OBj9MTubDUQEqg6hNu7vXdMSKrVOw4xOCQGJNGh69Z9E2OIwdcqS8nRMwAQQRM8M7bRO2LHjKan_jcAEnEpwo5NFY2qyqkBLKKlFCQSq9F7R2hAuVQkrCqIuJRaVcelBKKqAGRmKKo567JkVakCpZTjcUIwAwQwNUy5qJmZOOeZeZ7mro0--uPxqAp5Wii2ogpaNBdQ0LT0q3WV2SZzaKhaTdptP98eHULNio7AVHJi70tO5MiQai0m1XJBj7VUZCbCkkstwkxgQsRiaCqEiADOByQ0sdi2UhSQzi8u5mkEozA0V6-9fna5Yee3m83f_LVfdFq3bfP733rvt77xp8xcVdZnWw78sz_2xbO2j01zd7372td_8tmHzz_35ht5Ln_8B9_80le-eHm2crF9_8MPDvujiHZd-PiT57fP795-950Pf_CeiT1-862zy_PvfvM7y2FUlWXKBBKa-MZPfG48ju3QN93QDevDi7syL_v74_nD89c-_5bkMi1z7Lq6LMfx8ON_4Sf-4i9_nd_9V_8Wu_D8k28bNIrw5JWH3_3u-1fn50nKNI3oOTp_-_JW0HLVorpZ9wD66e3tR3fH2AR21sUITJ--vI3ejamGGEIbcy6OYJqmu9tdu-rA8ES9IIcppZMLUkRUNM-lSO362HdDLsqevXMuuGFoSdE3vl93ktURNU00YCuQcxKVpmuAIDRNiE2ILQKsz7Y--NuXN6rp7NHFdEzjOJ09eDQeDzWXsB4ASQ26YUg5o_PknNYch02puVsP-ZA3lxdpXvbPPhYtt89e5Fpc8IHd8bg8fvuVeT8H7zdXF4rQDC0Hf3l5pSI1l_W2ZyRPVJfMiEstt3d7QAcIITZVinOulLQ92xRRF5gQPJOqlVK9IyRz3u8Pxxi9qi5LLrUCORddG2KaEyLuj7PUsl33KdfDPn368qbt2lIlpUREIoWJRcxAQvCoZmqq5nofgi9VfHSqgp5KLmqy5KqARXRJ1Qzv91MRE9Vu1ZlZE0PTN_e7aUnl-YtbYs5VpmVWYEPISxqP0zzOc9EKoAxVdUkll4LEYjqnkopWUDUgJsduXtL9cWxiKGJzqvNS5yWlXJOUYobESylMPKViovNSwaBmUYP10CHhZtWS6G43dpERKB2msiRkvLpYf_nNp1frrvfsHKiIqIbgwAANRPXuON0cp7t5mlJp2shEgDTOqYI4T7lKWvK4ZB9dv2qbNsSGjOijTz55_c2naSnc-N1h8s715ytmBmYDVIHQNUTkfHSe2DMx11QQiRiIaDwea8ntMJgZMRExEoXWc_DzPIPZsDlzZGlKqIqogIaKJRdPapoBAD2Kqcpnx6GLDgEUjJiZkJiaEGP0Uu3hdm1gVA1qNZHtathsus3QpTH3njdN3HZN9KGCLtNiokxcqxgZAIbg2LvTk9INvYu-awM7RENVNeCiwgJENM91mdJ61Uq1eVlKLvf3-812fXa2ncYFTKwIEhnY5eV5EwMb5FJyzjG64BgRtEqaU9s2BFhKcsy3477r4na7EVGRiiZDuyZEICu5mmRVIXYA1jbezIpIf7YKSGpQdXnnlaf7w-yZSi7r9Xqe51pq0wasKFKQUMEenz-oVazKXFLfNn3TpiTMnMrSNU0RAVQmjsEhWNfElDMzdtHXWtEsNoEITo7M080rK3jnREzN_tx9A2DKjCbGhKoaogMA51wgJkRwpKfWppkBIFJVqaoABKfAChgSEZqJitmrX33lrdjJ3Txa7Tar1vGx2t_7h7_5f_5__Y_f_e6nrz0Y_hd_65d_-aufe_cLr33hS29GT6--_eqv_4-_a3lhVMmKLhoFQN-vt9s33lo_ePhjP_trQqC-Gy7PqOary8c_86__hf_bf_J_ibHxfbMs5mLHntCUHMGJDGNGjsgBGKAjIBTJHAIyMzkrxZPDP8fRxiZotsdP39jv78kHEQlNS-xNrS4JEBXBREyBiU6NP0CHRJ69oYpIWebQtaeVCBA5Fw0MAXOpxOS8l1LxJFtzIbArSypz0lpqKgjo2kZy0VxN1TMDoSAiOHQBQAkBgYBYc3EhsnN5mmuZl_0OkYjqsNmCZwxBsazPVnWa-80AteRS9ocRAzVdM-U8lVqdTyb95qI9v7r43BdDu5qniZb5-Yfv3968fPHh98_X5_36TLRePLh49uzlerNiK3fP73IuiND2l3G9AhM18p2fjvuf__mfYCkIiKYiYigGhkaiUEXAUESZPhvrTRTQmKiKAoBWFTBGNDiFywwB2JEBmCEhSTVRVETnmVDXXWyZAeBuqoKnapwZah9i7zAL5JKj94jAhN5j41zksFuKmTEhkMXIr266ltkxLaWSMw96te49s6iiYybepfribrnLAp5RzTFKrSVNbz_qH2x7QqvF7pJ8_-M73zlk3s-T9_zorHUmt4f8wW56tpu258Ocy-3toe3bcZ6lyH5czob1Kg5Nw5HdzZxe7O6__oVXnmy6T29uL8_Xnn30fDbE45QUcJcWzyhFX7lcdyG-2E_fv3656eKrF2cXzhHhkuXDw8G37sFmSEuaizhHnXeesdb63qcvj0k10sv98ms__s77P3j-1itn4Hjdu299cLuXsqi9uD6Uqrc3R9LatG2pFQznce5cePfVKy1yd5j2Sz5JiqpUlbpadau2XcVAxGYwldyvGibOKb_26LwP4bAsc8m347wbZzEj9syYUzrdK9VS1EwBgouMJscFCKJ3q66ReXbEVxcXZOJjnMZRpHoXmjZ657zjEFxgjs4F79vG911oA3vPjllU-hhiDN5x17QqxsSOgAmCY1U54X-QaM415WqfDf3VDJ3zS66gqoBmhmCeiQ3FdE5VzIraXGqIze44p1IQIIuGJqRc05Kc41wqI1TTWrKInKhoKIoO9_vDCeJXRADMEZQl5aWYY1SRlMf7nQueQ1jmTFai5-P-EPsLSDMVyJoRGRQJTuwP4ui05DKn0DUlFeepFlWtbMDM6JyIxaYFU61FiyKfjiQgQEAyqbHrDRUQQ9f4EKTa2dUFAC6HmaLvVtsHrzz98OOPfvprP_Hlz7-xHpou0kc3N9_81nttFzl2n370_PLhg_PtcOHbs9XwzW9861vfe29_d_0LP_eLXfA_ev9Dv-6QODbtDz744OZmd9jvnr76aDoeLy8fPv_007PN6kc__PjzP_6V1erMRXv2ww_axi3HQwyeQIEwuFYMm9Va1XYvX8QmvPjo-dmDzeXjy-tPbg_3x4ePH42He-fwcCj_yl_7ldaIH_3Cv15TXZ-_JmW5fn4EU-dwSml_f9istxXqYZovHj0kz-NxMoTb2_v7w7Qcx1WMu8P-fjcqwP3hqKJDH2uxXMoyJwdQtJpBVZEqiFhEStUqhmYEWJYlRg9kjhkQTbAPfZE8z6lIbbpWqiJYCE6N-jZ6drnYi5vrZgguBlV0MajUfhiWJW_ON6o4jSMjXl6e717epCU_fOXxPE0pzW3fK1IpEroGvU_z4vtGqzT9wEw1LT64EJv2bKVg7BtAsJSYEBHn3ewcI9HLDz5dX6zXZ5tciu-bEJuU6_ZsjYFWfbNatc4zoTEbEtZSQ3SCCADOIRGyA-c4BF8XE6l3y5EAQ3A-hpIzGpywsnMuQ2yKSJoLEB6mdH13FFQAYKaLs5WKGNDu9m69HtJcus6zi2qKYKfPmRA9MQE6QhHNqRKjKZZUDaCWk0Dep2IAgAiroVlMBEnBiKjmEr03lZf34-GwzCn7Jow5C4AAKmoVUUBQIB9ySQaGzAJQqoQYwAyJzMwQatUYAwDcXu9PWNVpyVkxi4zzkksVIoDPbrDUzBAUrIoS4fsvPu7bbujaZcmbtuu871r_ytMrI2QHZ9th28cvvPmki_6Vq03nXZ6TIyQmU2UkURmneT_OgNh5PzRNjO78cj2PacnluB9zrsiIHp8_u19yViMz4-B3-_zJi_sHV5cpl2kq98cpV3WNK6mYQj8EUxiP09mDi5tnd13flVx8aMBk2PTT_uCCAzPHJ2Ky5VLbYZCSu34ttYTg2q4zs8N-H2LrmOoyOe8UqVYxFAdYihqYqACTmp6-KhDAxBofjuOMgLf7Y6qFiZrYoNV102z6lkNQJAoOkCM5JjaGwyKrttv2_dl2Q0w5VwWrImqGzEvRampgzP6zO2lEMuja4JwbuqaAtuuBHJoaiAIREiNT8AQGeSqoevX4XEQILS8FAMd5rCIPzraXQ8fsUPVsaL3zwftSMhCGLiAzMJzUaYFpu15JraJWJHdtV2rZbFZ5KeipLAIAIXpTBaRSpInhbLU-jMdpSqVoSlPbdSplvRqQqOaCDIbmHBvgcZrbxjuHOVUCbKLrmta0AICasUdQJSIkdESBkYhMZbVq2STXQkw-BO-CiQxDe1rtscMYvCCCCRie_pQZ1lMn1fS0B0dAJgSASOSd84yGyM5Vs6wiIifAqKoZmpgBoQsO0N19_LJPIw_91fm6NvCf_93_7u_-l7_-4fuH_8nPffnv_Lt_6Sc__zo2DExmRNFDNVH91b_2l_6_f_-3fuVv_Vv-6pUv_sxffPcnfvxv_-_-zs_8yl_56s9_9X6af_DD76ZpZM9EMu3G1Wq96fS7f_AnQDwdE3dDWA2lSmh8qYkAzSqkgmjOOWTMpbgQVNWIgfj80UOdpzpPw6Zb5qMobjdbF11smpxqEqUQFdC1XS5VRAGw25xLmU4vRUB4qkew8yqfiZGZHZoREzvv2tZKyUs5HVN2IsMMg-9a9gGq1FJMxXcBVIgdkwcmSwkJiEGrVPAuBBciew8AKsrOcdurkQhqTgyEAHEIUBaHkm_u5zmdlHDgQmhjc34uau1mqFBPy20A4sigNQbnmbRazaVtV31_9vDtz3vHYJBzvb-5ffn8evPw4WoYzi6vkubxMCmAwkJEVfX88eNSaio6rNrpMH79Z7_anihQiAC4lFqynp7GagZmImqAJ-XqqTx9wg0jAAE45tNvGqABInwWFjKwzwDKRN6RmUbGbWADGlMlAmImInbkiVrHiLRIVdW28VrFsV2uezagAHPSUkvTtKbycDOsPUfGKWc1HQKtu8AAS9GCdDS93eVP7iYxCCH0qwhZlpwerNyDddMHLkWy4W6R60NqhjYEmpbl7uXtK1cd1Xqcy8sZ75YcAk9ZXr64Pe9jKjYfEzL0noau2UZmF3dz-ujT67def_DTr1z94MPnV-fnfdc0Hh9sulrpflx89IclR9JXtisynpN885P7pglvPdw86Vpy4Tgt798eLLgvP7o4jgtUzVI9Qdf4_Zh-8PHLH9wdNPj7afzVd1_bIgWnV6vu-x--2CX7w--_KCL3-7kdouRS5gWdq0W6GM8utyuDLz05T0vxkd57vqtVi56cRtD2kYpYlfW6L1XVbF7K0LdN14LWTdeR42985_l23XOg2DTH47Gk3DeNqBBwSmMXm-i47fplGh2C8zi0zbDqqNQnj570624-Ts6FeR67tjXTi816NURVqzkzUfSu8R5RV0PUom0IKtoEn2ttPJcirfcKGrxrPBMgIZLHXMQxmWpVOJX2qgiBMTtEMzNVRWY1MbA2Rsmlbdq73Q6dM6K5lFxqLjWVSgAcfMkiUuYl5ZKrqpkuOY_LIqKqQgAAoKr73b7tu9O9-5LSvJQQA4rlkh3SdDgCo9YCgDFG51yd5loqoIOaPaOamRrxSddrVqWIeGQzq0sN0ZdS2RGAkQGpnACtyOSckywk4p0rOTkiVY1Na1rJhZoSMoOoD9E1AQDIsYn56K5ee8KejuPhxz731lfeetxEzrX83h9_5x_-zp9owWHbfvfbP3rjrdde-dzrzz94sR3C9c3uvR9-OKy6t95---1Hb__xn_7p89v7i7OzbtW9vLt79uzlSX-5Wq_vd-M8Hb_ytZ-6eXn91lvv7Hf367775u_8AaFqks12W81qlTj0j1_73KcffxSj_-Db3-tXK0RqOv_wyaOyVLHy2ltv3Nzfnj2-AoGv_9gX33lwMbDny5_8S4f9XqrE6C7Pm3lZlikBoif9wZ99EPoWnXvx8Sc3H79QlsiODQVEs-QlOR-cpzknNBqnBAL39_tpTOshSNVaigGo2n43Nm3rowOwsojzzjdN3zfzYSLvRCwthcgbStu1wfuu6UUrA0nJq_XQNfFudyBiZLg8P69zCd5pBSmFDedpXp-dTbujCw4UlmkJw6pkAaTYt3WapBoQxX7jmMkABWN0kmtsGtWC5gBpvjt26xU1kciZlVLMkSPnoIqPTkyRYLtaLUvpz4Y4rCVrs2oDuxh92zVt11rVrm3Rk5RaszITAmiVOWcEIITlmELwXOXEt2vJXazOc16knPZLFmKoVZZUibCIRN8UtTTN6Og0mnVd7Jo4zUtonAGqWSliBESYU_YhmIKCmZqBRudOXySfXQw5NDRZSs4VEAy1CuZUatVxkZvbwzFnx9wEL1VSzoclZzVRmpc8LknUDofj_v5oyNM0lapVBU2RmIlTzkgEhMu0EDkgYmRR896nVMQso8YuXN8ckQhdPIzHZUlV4RQQUjVmUrSUi4kd50VM1v1mTpU8O--qaPQYQ8wldW14eL5uvWsQ87g_67smUONcDBi8M0CpBvCZwWCek3mXRb_94vnWNyq4P05N5LaNtVpVBWRVjLHJudQqYjAviSg8-_iaAq8vV8cpE_K83ztyx8McGvJtm5ZS0xyCLzUx0N1u3w-raXfYnm1V4faTm_VmUCUODlQIIad0f3uz3q5BwTluukaq5jm1Q0vINatvHRFatVwKMKoYGvRNAONaS7_uDeSkmmq7RtB85FILgDnkoYuO2RGuh-7xxXC-WnnjVePPztYX29WDdeeMb-7vFezB5dnTJ5eH_YIn3yFxlUpEPngXyEoltCWXoW_nObVN8ITBBSOTogRIAFWqgqJByZkQhq49jse0ZB_Cg6cXXWiDPzHU-AR_Wbcx5VSlukDBMwLlVKSWbmjTnByCQ865GFnbdl3XMjOBETlE4NZpsaYJACpV-9VKagI1MRCrfd8tS2GHAJhydkRzmvomnp9txzQTolYhRCbywTnvlmlB01xr1zXeeyQGBOecnbg9AIDWxWAm1Swt-cH5hZiJaKn5BP000KYJnh0jeiLnaAiN84iORJXYwBQQUSGVAohW9SRzjcgdGAB5IgfmiQmAGT2zAQIgmCIgoMXgvaMrp-fbtQ_-R9_7_v_pP_5Pj7vpL_3yj_2tf_Mvvvv6QwFNpUYfCZjIBcQ2hMDkkRaHf_jeBxdvvSs6fXLz8geffvTtP_vm7__uv_jGH36zMndNqLV4T_cv9q988ek3f__35n3mELvLc3LhMM5GSEi1lGUpwQXn0ACqQSnmfSQOTJ5i7Lbb48tPtVjLcPnkoWV86wtf_tlf-KUPP_6QAPvN2X5O7bpB55ZpqiV7cuy5LrOPjalKFanqXCRCYtIqZkqE7AOSnTLtWmtN2XWBvUdCIiLnDEmliioBUvSIYKroWx8iMpoUKdWQtRrFluMADkuuw-WD4-09gZGPxg6dsXdu6NvtyjmvFex0I2Xg2aAWlbK_vVOAeb933vs2tF233m5ALTZt8H46TCBOpZ5tz1wbDTHVMpWK_SrE_uLB4-n2FhzePn_xyfOXjx49GVZb8NREur27Xw_rZV98w2EYlnnZrJsi-X63__GvvKOLyAneAyqfPY1ASAAmooygf44BBQUzcI6CZzI0FVAIjs_bAEgODO3Ue2IVYEYEIBPvaB29RywEc4HgmdiJgplER5E55UpEMTo0BcDeu8F7AMhqd-PsAnuGTXSvXfYNUSqFHXYMbfRmcFjqfam3Y9rt50XUQK8u-za4Ms6E-vCqW0fXeCcV5qK3U9knyUi3d8fDYe5ceLRpm4D7MX96Px2KpVJy1t1ufnLWpCrjVLqV77wPzjum2MQq5cPr2ydXq7_w9tPn14fN0PZD10bXOqiK45yymUPs2G_6hsAdk37v4-d9Hy637Rvna0Qc53yf8wT1c48uairzYYlN2E-5aeIuLbdz-mQ_Jm_Pdumv_-Q7Fxyz2KLyT777yV6VEHdTHs77m_vRck1FOXgVDcH1XbPcHr_89EGtCgrXh-Qd-tgYwuXFEKJ_9nz3-quXQ9MEdrf3U0olOF73ww_f--R8u1G15y_23dCMywxEz5_dWZW-6WrNIgnVaq4ARkTM5Bx6R6b45LUHjx5dnPXrXAo7jtGDChOCASGt-raWzEw-ciQHCl0TTK2LvmubGAITgGr0XlUco2MEtDZ4QCBAMyxV4WT4UkOmKpZLRYIYGwA4JXgBKZcKaKf_ERHlqkCsgGkpgV0VGU8kQxNVYwRErFWYuYggwpJTMTOTUrIBEoKZEDECpGkZp5GdIzJTXaYptq2gKFNNyTFoKmZAbOx8njMz6JIUkBxZKQRQijR9V1J2TFIrM5MpO0YiEAVDqwqiplJrJWIfgpYqKZ9wzyf1uw-dmgEAMZ8iW-1m450TAEAHYOvt2gdcUvnL_9IvPro4u9hsUp7-6I__5MWn19nkz_70-Xbb_vJf-cVHr5_9o__2t5-cn7_15tOStRrExn_xc-_84Tf_8AcffvrW269eblc3t7vvfPu9otJ2_uLsTM2Y4uPXnlx__PLdL737R7_zhxcXZx_-4EdMyo6boQPn0mHqh_Ww2VRd2r67_vTl1dOHmwcXh_u7frO5vbk1YXYoajcvb1Zt96t_-Zfeevqo9y7NhV_7y_9mNV9KESnCYT4u0ce-9c7MB__s-cvo8WKzOr_afPzBR-PhuFpvx2k2lZKza5oyl-ubQ-PZBb7Z7VZt3C-H4-0BybxrqmTnHAKkeZaiSERk3qFqLaW6EHLV2EbHLEVOjbi2bwChFvExeO-LVAGrKgbWtjHVGlsX2oYQcy5Ns76533WxCW2zu9mHNlIMiOi7SBz2t7uuH5CsKmhNjNjEdnt1piLsnIFqsZOWMwztcb9431ycn5dcAf2wHdI8A3ApAkhazbVNGpfN1fn52daI5-O8Wg9N08YYHDE7do4YQ8qZ2LngPcciRYBQDBBDE0sSNQA7cS0hn27FvF-WHJsGCZecHaEKdG1TVD95_iw0jaqgIZEN7E3RFIFYpBaRajCPS60mJzm8d2oguRC7qrYsCQid94x0fTODozGl3TGF6ItpqpazzKnkImmpjy8H59zt_XyccwZ-9mw_5SWVZRznu7v7_W5_d3MIXRAAldOKQ1BOMX5YUgXAGD05r2C5aCpSDUSFyKmiqo1jLiq52nGcSymGnK0akFT17ErVKedSTcGCD0UUiYgpTdl5rKi7w_jpy_tpTm0M97u9qbCD67K89eDq8nztEcHMANrA0fExpTQm30YgD2bTND8cVuz9cUzTUnyMapCrfPjsThZB4DmXcU652pLqfj8fxqlp2sMhtdHdT3l_PLZ9S8w1VVWc5rlpOnZ8uN_VaioaPDHiarOquSzz0nRtaHy_Xp9MwDWXtmlrrdPxgGY51e3l2er87Lg_IIGIGlipgGbdeqglmyGym-fFxMg7JFeWBMj78ehDB0Rm1AYPQgLler_f76ZDLlXNexaD4FwM8GizWjVh1TS1Sts471zXtDknUgSEGLgdupyrc0Rojh0iXj14uqSpFkklBc-7-3FYdQEwpfzg_MwU2qHxwbcx1lpEATxlKegwRg-A19f79XZbrapqE5oT2vIwT9f7gyoUkb5rujayI1FjJOc4pSJafAyOnYpILW0MbROdp7JkJiI2JETPiESmjp3zTmoFw6YNwXtDK0smEBd4GhMYgcnl2Vkf2xj8Mhdi8kQIOKyimoQQpJojaJvIDFKUkdiTgRFgkTp0jSoWkDmloWv7GPk0mYKdHnIzyVVyzY7YO0LA8zYG5uBcdF6VmEiUFE0EqqljmkXFKIsuYAYoYFlE1AhADYoKgC2ixSEh5XHue94493_9f_79_-If_MbDy4f_yX_6Hz5dX4qqqDI6REdMjhjBAjsC7FzsYnjn7de_8973L159cv9stxtHVQOR3X6cdvu2D1gEkH2zlTJ_5zvfrndLNTQXXDe0ffPlr78DCofj5D0Ko2-jawKwc30bmth2Xc3Fd42ZdU1wzJqXvlst83Tx4NHP_uLPf-ePv5HnRM49evO1_TTmRYbVZllmQk1zct4j0ZIWIu8cowunK8NqCmDsnFQxPV1boAGQIwoeDBhQtBqAd0HBakpMZKanF0KKbdM13Meyn1QV2JtUalpwfJpeCL0BMqNVRSRgIO-tynycaioAyN63Z1dpSoBG7NNxZsdtE0EripZ5Lksm5JRnT07RagVADzVVlU-mTyJvTcAFhCpNH9E5H8Lm7Tc8-s2rD-7v7m8__fjF9cs3Xn_7fLteD8Nuuq9Z1JMKxNj02xWSe3G_-4Vf-grOYgBq1QBOyUVAREBAdETMqKDs0Adad2HduYvoAnBAio6GLjTBESCBKYKYTYs6h9vOMyATRU-NJwZaiqWixGyEPVNRcADRYcNOAQnUI5SS1w1v2nASD7-8HwV06OIQ4NG2axGXJYfg28CKNme5PtZ90uNcTRERY-O2K4dFp_3UeL5chc47UwDk-xlu5zQmmwVqSm3gzz9eaS4u0Pufju8f882-sgNwTqpcbPyU5DAvsWXyfs5ydr4uhsdx3h2XoW1__I3zshRyPrb-0eUKVaWKVp1T6hvnDdaNF-C5wnufvgyNf3LePepbx-Hm7jghH6blyXbVBL55fnN1dVZOmzz2H7y4v6vw4vauQforX3hlwx4EfnCz_5P379JSfvwnX_3kwz2Qq6ol55SSH9o5FR8YGR3Aw7Y97ztkWtg-ud3djXNKmRxf3x978m1wAcijq1CLWPCekT_66Pn5-fD44eb-bhYC8-7li7tpzOM4m-qjs40nUrD9YVpv1vO8OMfOM9TqHZ2tVk8263Qsfd_VlKaU8pLTNHWrPjg_9G1ekil0fYNqPsYm8gmEPQx9672ZxRiYySGwc7nUxjlCPK2vvfOiBqAxhlpVzboY5lSAlJGD84I2L_dEoWmjqBKjQzJAQBRAERGDInVJJVcrVRRgWTI7BrVqlovUqqKqqnMq8zwxcU4lp4yEnznFVJHZhUBEy2EyVRdiLcWI1aCMSxud5HJyaM7HQ-waUwERaBiKfNY2QtaaRdRqJSQTCacaXtdoFWKUlO3UmVdwnoFIRUzFOTYwA3RNrMuCzqOdZJe1HVaxXS1l6VbbWudhu52nKbbNz_30z1ysutWq_WR____5B_9wnuvm0ZMnV09bj--8-5qp_KNf__1lPDRt_O6PPlxv1pPkPrrDOI5jOowjh8A-fOtb30Wizfnm0dPHx8P07OOXn_vC52RKP_PTX_vNX_9HQz-8-aU3vv2N74Xgzx9e3R9GQ0bnLx6eXz55cv3seYiNgG4fP7r5-EWI7uLJlYoOq9V-fwfOf-HzX_rKl97ecLjc9vM81ZrZv_uLy5SqlJoXsrK_35VxBMRStcwzqpQ53dy-VNTe98fb6-cf_Ohw2O_vbpD8etvlOTWexiWxa4-Ho4jUlEUzojHFw3GKTcQqtWQkUtB8nIqIj9EFHxznJZci_dABACCF4POSVSAE37Zxu10RuhgdiKWUu7bJKU9FdofZNRTartR0dXmWxqnkvDo_VwQXAwAyc14yoxO02LcAUA-jVqlZ2LlSS01iVTaXF5ITN0HNkEBLOezuQ9OYQEp1dbH1bYuGoQ3tdu2ZoveHl-ODNx4z6PnlGTMe7nZN27jgVLQu2TFKlVJr18eb-z0w3IzL0HoDRBEmPFU6RNVqkVpD9KcXd8eYap2mpX72Y1BKPjs7I4TTg4gGXQxVpG387u4wTck1UQ0AnUiVKs7TcS4iKoa-8aXWeUlAlIuYatu5BWSclqp6fbt_frOfFkEHzM451zQ8T2W3X8ZFlppv7-7GcTkeDsfD8XicpuNYtIJzRH7JBQl8bIhI1fquOU5LLnVOORVRNTG7HydDSLUwsxkaWi2SSwGgUmVKuRq66AFdFWNikRIJTkznqlZUlipKLFqDJ0eISGIUg7dq4_4IVTer5tHl-ZsXF47NiiAoEaCeJKRIiM-mAiJ5KeAgAznvawHfeKn24mafRR0SsTExO9zNcyYCw91-MsS5VPLsnP_4-b2w301zrRVNmbBt2_vdOOdxe3auubromKFzcToe-2EgRlGVUpGIGAjRRJHIOfIxxNgAaBvbVEpwbnu-0qqe0XnmGM3MrHSrjZoCWNtH0JMzCsGsVvPOi0gpZSrZexeiO4_NItI0eJOXrmmyqg-sAN5zDF4NVC0EBoTVegWgIXBkDuSLSE7l9deu9vuZFGpVIsyHvQ-cU65ZBKTv-vE4NSES0TSNQ9suKXex8cxdG7fbPiVBFUCDomjSN80yTz54UJjnWVVjCITYOAJAVZhTJqbTumyZ82YzbDdrUzAVUhOtq35dawqxiUw-eChGyFIVkGotJVcwMjNCFNFaFZmjb9hTdK6m0g09Ah7G2YDMIET35OLCEzI6KSVED0YI5pBySt65LkZyZKpQBfEE6KQqEjyScTUpYkvOTRMi-eDZeydVAnMXPCDNtUgtYChghMyI3jtP7AN1XWiD6xvvkACQgIJXYmwYh8BNoOg5Omwct8F3jY-Ogvfs0BF2Htee_u7f_e_-4e_84Nf-5s__tb_6i-mQb27ns7OBibxns8p0ynkrIwGRiGoV6sJP_tgX_rP_7O8nmb_z3e8t43E61uuPr_tNGwTMrCgX0a5tGyxoNi26ujpnpmrh3_jX_uK3vvXDL33pne3F9tOPr_vtZt2v8pJVTKvVKszBe_61X_0rLz_9uKa5b50P4fXPfe4__F__e__1P_hvbm_vg4fg2835-fFuNIOcczpOKtU7F1aNmagoApEjioFdADYA1KocIiISoyEike86KVXFJBURRcDYRK1Fcwa0mopJQXSuG3wXy5zqNJsCILkYEBmQ2HEAxtbLbOvXHh4-felilCJmJqUqIjcNB1dzEpFlPnIg9k0u1YVoinWpZubI1SVBLtNuJ0tJ-8m5IEU8ub7l84uzAM2wipvehTZO8zKNy9nlZn-YmdCHNldqmuHs_Dzt7z_54Q9fPn_xhS__eIyDME37HYjGrgO04AKhfuHdN3rkWgoSqUo2IEZTRUIzZUeeMXh8tIqNcx05URhT-SSX2UFPLiAUgblqqlbUzCAGJiRiQgACPC1bkHDOagYiioi1Kqp6xlX0CmAoZ0MsqXTRb0_BBsSsOGv2jh9smgdd0weuRYDQBcpF98Xul_LJbvSOYxNqEcnlat3OU0KF7brrmuARCInYz1nfvz7eT1nBgqNHq673XKqWXJ7Py6f75f6Qzh-ss9g4LiiyQr4eSwg--LAUON8OprqMk2g9H9q3H6y2fQQDcvD0amu1jOPSNM1-XLzzNUvjmEM85HK7JAO96to2usD--v7gQgDH202zacPxdtxsN4juxeHI3r_c7W9zur7ZbTf9L33-acMhCbx_s__2J7vA_smbW5nzi-eH4356cbOL3nWxQ_Iu0Lg_XrT9w1X3xsUKEW8Ox2ef3ofYIMCc09D2oNB6f7bqVk3IVb_7_rOrBysw3N3tOfL5-Wpa0v44uybujvuSa86FiFXxuEzbi23NllNFksh-Wcp2aEuunXMX696xb9tmWpZpnIAJidquPbFgmxhKFcfUNA2oAejji7O8pLaJwZFn8s7jZ-UcJaLTcNVE75zLpbLDWqtnVlEmNrCiqqgheDASrQjoMSCiIqiZFPHeMXIxqaq1nvLen4lRTglhcOQ81VrBc5FaRcxUxUQEDbQKGJQqm_V6med5WQgtzYsiihQrVlJm59XUFEDEETOedoQotZiCpMTMIiZVPFGtuaqxYwNTraT654J31qoUXZ4XsQpI8FloDhFIgMjTny_dwK06YidmMcSSiwG62K6261pyCA17LlouLi9D1__iL_9iBGCOc777_d_9UyjVVHa3hy52X_rKW-su_OY__e3xMHdDePOtt7LKO59_8-23X9ls18ejfPDyxSuvPWXvPvro42VK5PjZs5c_8_WvfudP39sM_RuvPl2v2t_9vd8_7kcOYfNk88kPn28vNktWdO7s8qLp4_bi7PqTT5rY5CKvvPvW9Y8-dsznl5fTlLq2X6ZjWqb16vwnvvLuW6896gNXqu9974ff_c4HHF77SrtZv_L6o-vnL65fvARTVt3dzd1qWI4jexZNWurt83tiTOO4Gob1dt00_MF77093-_v9jpjb1cqhBsP9fn_58PL5i2vJBRRjaO5f3HyGTQVwwZdiOQkzTYekBnHVTMf5uJ8Uig-e-ARhNSSQgs65Lrih8XMWJFpS9k1ENPY-Z2F2zlPNyoFX59uUE3tvgJuzAQhB0bfkHJRpSUsig9A26FyaZyZuhx4IlnFp2rZdr8b94puoCqXY-nxFxEUFEGvRy0ePSik5QdPF88vtl3_2i5_-4OMnr76aS2r7Ica4zAkAANHFMI6LitWqNRsoVpHe-7aNpRRQZARV6Bqe5-I9bzbrKto3DRFVEUAM7BrvYwwn7nr0ThXIDIi7vi21HJdlXnJRq4apSi5WS82pLkXud0cDEkPneJpTzlLLsqTRlNBzSfXm7jhO-bg_pipiNVVpop9Tdp6dxxf30-1umsZxSuk4zkvNKS0ZteRSS6mlEDGoiiQwElBy3PfhMKfjnAzUiHIRVWXHgAingQpQqiKyVMv1RN7joiaGy1LYA5OzKnlJi0AFmVKO3qvBIp-RxaJnFXx5l4Fh1bdq8OTh-gtvPHh6NgyNC4Gl1K4LaRqPh7FpvJwOFbFIiIzjkpvOB-cU8PaYvv_xc-ccEN_sj0B8M83d0Fzv56yWFW_vxlrr7XGqgnOuh3Fpu2afZ1AAhbqk6KN59t7Px2Rah7avOadxji6UZSZC73zXdUtJ3jsiHi43x8MYuw7IfBvTnEPbcfAq1SE7g1def5qmBESx68FAiqhJiI1WBeVuWIEzFc1LFYNqVarELrJ3eSo5SdM47zwZbUPI0-IJb2_3VazrfBYx0k9vR1NzwStYw36e66ZrQgiN9y7wPOdu6JelqggiAlopNQRnAAIAhKu-r6h91_kQREs1XVICU6m6bpvYhC5GM4iOi1kTYhFzTRj6Bh13wTdNNDVmhwTRMxPnJDkX74C8H49HJnKIasrB-RDSPAYXVIWQtZZ-aEN0IgVIfQgIqmYKWFCbtm27hhDKtDTRrwbvvEfT0Llh6ESyoalCVlW1q22_6vtapO-6UqpzJKJEIEWHvukaL2YI4AKfWiiI6JxLRYhAVJeUjSAV6YLz3uUianDWhMF775yaZCknCzIAMLGdULOGRYCJADA2XgVPtQAzraIM4JkDOzNlAFJFguiBTS8cVMO_-_f--X_0H_3aeJ8u11sX4sX5igAcEhGd3MRqgoBZdU7T8bjLaemG4WzTvPvmuw8uXn3w8JGry8U6fvzJs6GhhqJKVo9397syjvfPXwzryzAM-_3IsfPBH3b3P_blr_zh7_2h7qaG_Twdx91dQ7Eb2lwye2agh48f3l5_Ot7dv_72m4H9__E__j8c7-4__uTjDz65nuf50cPzw6E8ef3Rs49vK0oZ5_31nakSuXG316rEqCnXXICQHCFREztu2loVAGqqSIToTUoVQQJ2eAK6EljNxdCkFj-swjCAb4h5uR3hRMcl1z66KHM2oHazRgRJpZipgvNuuR8NAdAAwdCqmCpIVefIMQEBINWcXRtLLhy8a5yZAWIeE5iSoiNvOcu8oIr3YZmLKKy2QxonBzQX290eCfXs6qrOuWsdGMbgc5F-c87oQwyH_f33vvVnlw-fnJ2dNzHevHyJHgkYEJ2HMs9ffvNVlOoIoqeu5YtVXLfBk3WNC0wNkz8ldoCWKipqRD3SigkJHPCsOhWpYlbEkNQq6Km5CIDgPIuCiJ3UAKeM0AnZ2DVcqzrEpnFDE3Ipqy4gEjHNRVLORPjW1WrtnQOrohUMGCfR232-OeQssOqbWm0-Tt7h2eCriHc89I0ndEQY_TLVF_vy_ProWtf1fsW4CSyqN7vlesl3x3I_STXrujAd5nlc2MG683dJmBCdK9Nytekp18Nu6qO_3PTrwO88OV8KpFSuLtdU6zjO286lXGNw9_N8terNN9f7UU546uPu6dW6afrbwzyr9cNw1jiQko9pte6obfZ345yzEM9judr2X3i4frVvD8nGRT44Lj98uXdMQx9fuww_-P6NMnHwamJEDDys2hfPd5sh_uxbVx4cEd-M8-2ckOhwXETMxWCmjaMm-pWLc8njktqAESmn0jVhs-ru9uMHH1wbwe72eDzm45iWOYWukTJ79sQcGderVS3V-QCgZtA18exs3TaxjU3Oy4uXOwBtgmffimrXtEvKzgEzeXZtEx2jRza0wBh9iM4RmvdUc2WiGN2JaQYAaHgCANQspwKPqqlBrYqEIBicK7WG4BDQFIqonaTmiA6pVEulzssCgGYopgaohkvOCKigTFSLqKgISFVDVDFSAEOr1Xmfc_WMCE5Fcs4lKyIF9iUXBEwptW3LHI_jgYnznFS1abuSMphBVY4EBkDg0ZsUWUpc9VgNxCRnIDAlAC2phKHRVMmzFWEGViBHQKcknaiambGL3Xoz3d43sa9Ljl1LIYS2e_jqK2WcS8no9J2vfPF4PLz95tsm-cHF2fN59-v_7T9jtPFY06y__Atf_Zmf_dI3_vjPfvM3_vi4mxXKxaOr3XH_xpuvvvHgzOo0xP6_-M__hzfefjrEuN_Pf_rN9-ZlYe9_9ue-fv3pp2mub7716lzTRx9-9MPvfzr07cXV5s_-6PuPXnlMvnnw4KK_2Oxv7kzhuB-Z7JU3XgHE-Tg559fr9f76_rV33rh9-WK12cxL_Z__9X_56cUqT_P9bv_sdlJsHr9-zvHJu2cPrupc0FOITTEJja_ZhqYHLLcv72IfQAHLcry_JtTjfr-5PPc-XDx8fLy9JiJAuf7khRmxd1V0mqcuxuXuSB4R1Hs6HkbHUFJqVz2CEcIyz92ma9pw2E9E7jhPqLjf72pV75qSS-h8bEOZFxdcrdr0HToK3tViCBBj9M5LzlZBq5BDUwQmFW26vtYaQqOqnkMcekk5Os_OpTnVJSOAj1xFfIht35Wca5HV5WZ9vtVa-1U7HxZwzje-CYEBSjowMRCvVx27CNXa1XDcH467w5IzIYppiAEMckrMLi-Lc3RqAJIjBHp2fbvpBwP0Hiuod6QCCirVTlKOnGouFR2rqqqOSxqnkmvNJZ_U033TlrSkVD94cbvZ9EZ0PC5KYAgll1zquKT7cQRC1zeHu9E5J7WmUtarrRRIS94djx--3FmVaVrGZQmrvnEOEZelCMA4zd97_7mB1lr2xzHljKxqWYqmJVktLjRTLt2qc87VUlJSYlerTktuPANDE5u2aU7ttLTkXKuLrZiw8zmnKgKEFMI0J3c6ffgzA8CSsvPhuBRyrol-SVkVq6oakELOkqoKikMEp21HDy7Xj887ARNVNnhwvj4eRzAzBQUNLrjg75f5xXG8XA-CvLsdP72-KwLPn98gueOSxGrJpqbHJR2OC3qSKof9nGoNDhbD5zfHWrXbrF7e3jG5WmEcx5rKyWvmfCAzUOj7VlPJ0zwfj_3Q7m_3q7NtrTV27bIkRxgbT86VZT7B1BBMShEp6_WqzklL1Tx7RgLmGC1LCKGKaikE4BxIyVbEqvSr3rWMggRoipqyiqjY_X4kpikXVZtrWVJuoxeF-9308m5vziWVw3G6Hec5pakUMX1xvR-Glr0nMECelsV75hPdzLnN2RCQc5qbGGuVruFxXIrW2PjgwmrdEzkm6Bt_HJeSEhJuV33b-rP1atWGfujYOWbXNSHGgIRIUEjQULK0TQyOl5xLlraJTJyW2XnH7HaHMXo39G10nOYlniq_AGdnPQVfszg-TTDmV62kwoxQa3TsmPOyiEIMXhGmcW672MRoomCWU0qljssCDqILVep6M6jVJgZJlRhQUc1849hRkYoGoid7l3UxwIkcgSSiKnpcspkispiNWcTAO2qc79umiKVa5pTNDIlS0TaGxlFAjAQI5j0wI4F5QuccAhGAmRIgIETHkSl47JwLFf7omz_4hb_4xQ-e3T7_6PaLX3q7CSEwgoGZVrOq6gjNZEnpu5988q3vf_D3_uHvrs7Pbu-nHz6_-fZ7n_zd__rXf_zt177w-itf_8Wvv_32az_88GMr85TzJx9cP7jaOOevnj6kQO0wDGfbdmhX27PpeOj7gZBffPrpy_ef_0___X_t6uLh8-fP8rx8-ctfNa0qpWXr-tWDy4t_99_7d7_6xbf-yf_wj779x9_flYkZD7tjKmVO9eqVqx_96FloyBFJrWgmOaPjuIogarWCmalpyVpq1SpSkZBj06zWrm_IeymJT4O5oJQCKlKEmV13Qa4NwQMQgGleiIEcgiE3oU4ZRNk7SZKWZEjoo4-h1kpg4B0CgGdHSIDeM5qe_M0qxuSrFEZXpYAhEABQKbVbdd16bYjsvJZCbJCXskyINu7H8TDHJohDk1rLUas64prTvNunSrGNBjCXeX_Iceh97Ner_vmnP3z-6cfzPL_7E1_0wuO8hMCIjhB-4Se_2EghZFJjwFqEDQFIsjhyRGRVonee8DTTg6ERqkHKspClqmDATPHEzyUMnhH5xC5RUTMjIgOsxRTUM1bTi3UTEIND73jbxQCICMG5acmlFh-YCR-uu44RVRVoEVkM7g7LbqlzNUMwomVeGKlr3PmmKUXa4JuuAbPAfJzqtMgh6VQEHK6GjlVBKgf67sv9XVlud_NcYRFZ8mmXk_s2eE95qkLOCGPg1TpaWqTKumsbxot18_qTS6uyO0xnF8PK0TLn7aZHYkV6fneMgTh245LudmPfRBmn86vNWTs8vx_3KT2-2m6iL_MSycW-KYBzkW--fD5r7cgtFQbf5pRHle99evf-3f5-rtf3CwCZ6SefHqZc5mIl17aL59t1qWWZ8yvb9eNuiCEMrb-e8n5KyHS4O-aaiZE9BkfnQ98Fv5QyHad9Sp13wXlD6lfx-c39XOywpND4F9e36FCRhEQqeE8--DQXbmkZs0pZ5vT0tSdmpYkhNn5oWlXd74-x8cRuKYUInWciaxt_PM4heEcYvCcDJmIER9w1AcG0VjNlZkQiNEdsiMwYvFfT4E4YNDBGAETECuoAfXBa1QyQWAFFVVXAgL3TaoCABHPKBJiKilkpUqVW05RETU1UxVRMKxStqqf3fRGpU0qGgIyE5Dnc3--GdT8vqW3bmgtXyUUcUhGJ3tdSRU5TQpZSyzwxE4jJnMlxnUvTNnVewIyAwirWOZkYEHAIoEoEViGuYp0SIticCIAc11xD1576Rc55DjHGmMclhhiaFsBCv0qlPHj0aDnsSsmhjU9eecXH8OjBo8tNb1WGSL_x678VXFg_vrjblZ_4ua988etv_cZv_Onv_N6fzMu-a123Gf6Nf-Vf-me_992vfv6dbd9hhf_mv_rN154--spXP49Av_vb31i3DJ6vHj2Yp-n5x9df-4kvrs_67_7J9z_56Jl3EBwtWfuzgdmtVitiXKacc3LBE5gjf7gf58OYl6UNzZJq9Myouepms_7VX_q5WLXx_Onzm-OcxySujS9e7hmv3jrc3V49eWW_P97cHB07nZeuC7vr57WWZtUtxyntdgCAUpxzIgKisYlWLcSusr9_8dI3wAiq0vXDcTcSQGhoXnJJuekiASLAMh2mw2G1WbNzQFSKlGVGcof9oRmaWrJjIu9Aten9kvI4LZvtqkplYiSyLH3XDUPD7JjIAOcpAZR5TgAUQlhtWu98KYWDt6qoxmhD3xuFtmvb9eCbGIf20dPLm-d3TdfnlEJwIQSOoYnNeH948NpTk7q9uhgP43ZzvqQcYrfk2rbtMPQ-cNt2ajrNmRi7ro2RKXCIDk0JSK2iqu_CNC3d0AEYM4pIH5qhi2pWxaaUTYwQu65xgcfjnObinKsmd_fTNE21SgV1npc5tV3btC0aGAI7Z2Bnfbcfx2UppZT9fprnZUlVUI_TMk5JRUtRJPWE7P04ZjRzRKnKh8-v285Xq6Jm7O5e3A-tn5fkna-AS66OFSKJ2OF4JII6zuvh8n68ZzAXgjlXreZUFMy3bdO13jsweXh5vrvbE7ntWS-pFhFiEoUKkFJxwVeRE5Di5OAtaiIGqiSQspxqTbkWQDyRgIipqITg99M0dBHAHafZEzbR5TFfbc-cgSc-3k8Xm_5s1cfgLOe-65ouItP1bh9CaEM8HnOtknNWMEBw7Mg7DlQRV22zWjXrPs5LFcL9cR7ntDvMOddjEnO8iBnjeMzHY6LgDrtjmjJ6jG2bs5RayXETAwKg53maEEhFKPplmUPTU_wMe5qW_OT1x-26OdyPBni27euSm-i7xpnKEGHV9w8vNrokQE2lVJGm7zUX71lzAgIEAEZ2QYrFpikp5VrVQEyI_LEWVQOiWZIC5gTETJ4eb5uXN_vDbr67O2zOuixwOI6L2uvr1YvjNE_zqb-lUsUget5sNtOySAUf3NtvPWSDw3E2oNcePFTD-8M4zlMuBYE2MdQKtZRUxHtHzEyciqhhASyiYGa1LimncapmoMrEmzY6wMY5QkbEvovjNJlJKWIAQ99tNwMxO2bvXWy91NJ2sYqoQheaR2cXBuaYFSwtuWtbmZOC1WqOXGw8ECHh4-3GxYaBhjaebdaE5INHs7kmUwC1XGv0oQsRTfuurUU4EABG53vvDJkIwRsBEREyEVGIPjguqsQEYCpmYIjGhEvJCoyGzlHrXRN56NsTZNZMRU2rFlUEIzBEVDEAI8eq4BmRICCZQRNdjGy5tt6TynGaz67OAOhP_-SDL33x7S644Jz3dMJoekJjTql8cH1475PrH708uNB95Uufb90Q-i7l8u0f_OiNtx_-4fPv_j_-3_90Fdvt1eW7X3zn8euvexd-6W_8q9P9zYNHj_s2KKMwGnvftWebs261GY_7v_p3_vY3f_O3XbehIXzll75-_8nL1Xp1OO5fvryLbfh3_u2__lM_9dW33nzj4_ff_-__8W_lKj_3qz_9wQcvr293KeVu3U6zPn3l8bSfvXeAdBinZVpi0xLSMiYmNlUXOPgWEZkhHScODAZ5SVDqMi2OmVxw7cDsjJhddN0Q2tb1PaERQK217A9WakmZ2dcqLgREIkcABs4pAHkGhND1eVlATFSRKPQtIkou5ByIhaEHFEAmJJEEyHmZOEYXgiExYdN3NeW8ZNCT2ZTNTMzIhSrVhWCMoloBlmPJdzsraqLgwK1WbRubrs1LyuOy3rZktEzjcHa2ffBkODu_2-0--N77ojU2zfrisooS0ztvvXIWuUHsGx8IA1IMvnWujdwFdoito7nImEo1SEXmIqVCEhHFWs1O8C6kk_ToVB4wNWIkwENeWvbMJ_CPAUMTiNn6yKzWt9xFDo6mKYvaCeF-vu4ax11woFUEC9oCeHusx6UsFQBdEQOAWiUw9p1ft1EEjH0qMM61ZL2f5DjLXFQdXD2gXGk8zvsp3yT58GXazyVXrEmqKaFV0Vlq0wUGIkBHTsGenvUmddwnDJHQnw_h4eWwicEMb-_HVx-d9Y415XXXGPEy17sxF7VV213f7qfjvOmbzRBWbYz95r1n16Lw1puPfc3T_rjZDs7zUuHlft4f06Ohf9p3HqGCzYfxB_fjt5_tP76dFiAwE7WSU6kiplkkOj904emj7cuXx8NuPhuaFvVqPcyKH73cv7zbY4jLfmyGhpy_2HTPb9LrD8-dWRPDUiQ2fh19iP5uPznmQ653h1SKgCMlzCZZ6lxyEz2odX3ftU01-NGHL6ZlYc-51JJr9P7J0wfrtvWOJOfHTza1WK45-kBogEhgJ4OhC9w2Ec2YwZk0IZwc87nObYwiSnAqlwMCnVhzAOidKyUDgvMulxqbBgBUzTkyMUAkwhPjoYgAIiCqAhiIas5VTpUp_CxZuuSSluqjNzsdgaiixTSXKqCp5FyrqSylGqDUCopIVlSC86pmjMucT3IPREz16Hwotaqp1IwIUgvYiWkLpdYw-DQWF6mmckLxyamqbKpV0bFWQQAiRsd1zmTKYFJFDJjYt81yGJ33QI45MvOpW-ijZ-ez1GFYbbfbm-c3ztM7X3h3yYt38cmjR32_TdP-1_-H33nx6c3_5n_1b5clMfGTn3r1N__-vzjOCznYrNYXjy5_4m_80nv_4j3vwi_9xOfIsRq8__H1m5971YX4G7_1x1pKnqdUdLUdHlxcXF2c-1X7T__7f7a7P4bItdSwGrr1-v5u_Kt_-VfG6SDZrq-vrx4-tGppXtjRdNxLrW3fIPuUpsuL7cWjB17iz__0V1bRM9JMeTfKYa5C-OJ6N5WZV69-vpR6f79bnT8Yhsaz7e4Oj157lA_Hmmo-3E83d4hAoABcltR0YTns7549A4fNaiNSzp88RNT75y-aNk7HfWxi04R5mVNKMYS8LMwsUkhtPuzSOBm60AcyOCxpe75xkcf9HIIL7A7jOI1LOzTLksuc5mncHWYIzjObgSLkqtOUllRMARH6VeubgITXz3bkSKu0bez6qGrrde8cl1yYkAi6oSMlI1uW3Kw7rbkNUaRePLqstbBryLtxf-zb3rdhvdnUmoe-bRrnu-AD12U5OztjR4A05_lss_Y-IBICROfQbBmX6F3sYiBXqzbROYLgQirSd6GKgAkzBkeg2jchlzotWcVCjDkl5pByUrRxSj4EM2vb6AiWlFMqS0rsCYmL6v1hREBDQsLdYfKNN4Drl_eANo-TADj2fdNklZKSqCjW_ZSNUAGVCZFBqhG5EJZ5WVK6P05jKkKmSdF0Phx1WZaa78fbPBcX_VIKOKwizgdA4hg757UqIRtBF1pDlFKWaSlq-2mpRKJQSvKIaclM7IkAUUFKqWPKx3GZpSqAAk3zgkw51VIKMiP8__N41oRQDaaUHBEAPrhcna37dYxD4x-dbWrOy7zM83xxvs0pV5XNed9yk3Idj_Nq3TMhIfjoi9jdbrqfjldn68fr3jPPYxqreuf3h_k4L6fXEkNYshxzBqKUq6qUJc3j0rRNrnlZMjpqYrvfHwms67qaFvZhniZ2jAgxBDAsJXXrHom7rgWg-XA8Pz978MpVnYuZ_OVf-dq0G9umaTzE4P_3__6_fOXc5fk5uSAmoJpzDs4PXQS2s8fnsyyYFBH4hFvyRCHc7_fkeJzGgDAvc85SsuScS5VcKpolUxN48eJOCZ_f3E-pKOJ-mqrhtCymmkTXfY9Ent3t3b5Kvby8dI6b4O9vj2-98oCZ51yOKRFR37d92wCYqCFD23gffbPpCHmac05Lznk8TtOSDICJV12HyEvO02FGpCWlaclF6iGnChiiN7SuaZldE6Mh3t8fQnBn_aprY05ZpGTNJHi2XYvavMzOOefwweW2dcH5EJjw1KUtdS6lFplLXooKyKtnG49xWuZpnk9K56YJHjwTMmsXu1JKWrICOI-roTWFKrWWKipN5LMuzMkQLefqEFQ0l-oA2zbwqWGCeELgERCxQ7BSbVlSUqtKokYGorYOvnMMSOgY7USRJjRURFNAA0eoVYkheCYEB7aKIaCC1o-udxfrPiXZ3c_n593Z0BOi894QsgiR--hm_v1Pnv3w9jpna0L71tuvvPvao9iG25d3Hz-_P7tYtd3qrLl67cnmeHf_4ScfPPvg-v0ffFTScr6O3_uT7x4Oh3bYpmrsW4qx2wzkfUrz04ePl_v922-8_jM_99OvPnj4B7_xL37lV__CK68-_fZ7H_6lf-ln_s7_9m9Xot_-xp_8d__9Pzkc79_90ueHzfkf_dG354KHedKUfYjnV5vNZiCiJCrsS62MZFVATXNmzyZSqyqoERFxbDo4EaIByaE7JX1FpSS1iszgSFXMVHIxU82LgpD3SC5segSMbUuORLIsM6KrqiaGAOTQRMGkX2_JkywLIGipKvXkzCVVU9BcAM15x01kYiZ2CGXKJnYqPgKIIzQydEyNFxMwPEEj0DRPi4g4T9OLZ6HlZtULMgYXGefbe0UEk5xT1zbeaZrL-sHlkmx7-cCRy4eJURRRvTttAb7wylVE-HMfHAEiAmjRVHQWG3M9FhEABSgCyGQEpUoVJcRa1XtGQtUa2AuaJ2LPDiBXWXnnnDdTBHBMatZ5OO_jWeM8oyMEERFgxnUbGDEGRrNaIUlVg7spTbnuF0lViDmLmJ0QW9Q1bt2F1lMGPi51PJYq0A6hEGSEwjhVOaR6s5fnLw-343IUOyadVXzDp0vcE4xUVNfbXsf8eNV2bRCDJ1fdmPIyJcc-Ml0O_uG28wQ5pVrq4wcbD5Dm3PadABzndDvlaVmePDi_fvGypvz04dn50DIhUPyzj56Fzn_51as0TQ5h6BskKoof3twXlYvzbUoZia-n_HKaPjrM7-8Pz28n52Cc0uE4ASMS317fkelqs3rlbAOiH3xwzcG__ujCO9d1nqN7ebPro2OmB5u2JHn6-Hwccwz4zuuXlsQT7Xf7H14fVtGb1N1hqghprvtxfv787nC3U9Saazmmuujd7rAd2nkq6yGkJauZ98xgQBicQ4Sz9UqWnKc5z2V7tr67OYqaqZgaM2-6lgGkytC2kmXTtZKrql2erZkJzNq28S6YqlQjz47JOQef2fnMexIRBFREMABEMEOEUuT04BPTNCcwNLC7aYr0GSo_5ayG1YSJK0CqRcQIcVoSE885AWJRZc8qkkspUkV1WUoIPouomoAysXNuzkut2q2jVEu51JTATh7Rk3AFU0ouUB0XYNQibQjH3RJbvywlOA-galZTITPn-CTMJkLnPRFLLY7Zt0FN0RTMVBGcY09opASg4GMTz1eW1aSWeWk2K1UoWi-vHjRtPOzuHzx82LbdxdUVA5yth1XT7W6f_-j9j68uz95858nv_-EfTcfStOEb_-QbPrjVxfnNi_tpyUPX_uwrT7PmH__Cm1cXq9XQ_-N_-gfo6UcfP5fgfvSDD9s2bC-2X_vVn03jMvTrftP94EcfAUjX8_44nT99uL68igDvfOn15x89n6ZxnA5d31crgLBaDVSsZHn69tPzBw_319evvvL45sVuPQw_9bXPnfc9O7vP0_XtflYZztfkWUtm9swP3wnDkKWolovzB6XAuMx1HIFZSZ1D13lJ4kNAApVaU7ZUzGo-3I-7OwpNw-TbftyPaV5SrmWers62bdsT0TQeQwwIFtq4vz8YGmjZvfx03k9zmc-uNvmYu64N5K5f3oUubDZrcm5_O4auJ0dSKnu6u70XVR8YgIitjSE4nJYZVK0oEYHoaruZjmMT-mXKwMyMJ4FcCL5tGtc0y7icnZ-zd2DQD10Vc4Gbob1-uYtt76Jvmy62nXPu_Gzdda1nt1o13ar3Pjx59UnTtM771dASY4xeloWYpFrXtGmZd4cpROeIT5ys1jvRWos4PqmAgBi9c2hGyKDkvGMXDtNIhEZgRPd3u6aLPrhStfHeMUkpYECEU8ohxJorAoxTur3be-_u91OWSuyXeb693QFSygWQ0KEB1qpFdVryy5tDXkTUckq16vGw7K6P87Rg4IXK4e6w5GWcDsf7_TwuBKhSpuNYpDDxPM5EeJKFaBEVI-ec45QSARjosOpr1sNh_8rjC1U7josLfpGaUy45S1URRc8iFYjGVJYq05K6EMeSikqtkFJGj7XKkiuHaGbI-pEfAwABAABJREFUbKZqoCIOKRAvuRDBetO_frX2iCUnrbVtvA9eq9SUfeDonVTLi8QmGKCZAvN4WOaltl0kz8FzE2PnwrjUqertYSYXdvfHomKG3pNnVsM5pf2com8WqXe3R1BTs25oskg1yaXGtq0inrhpQil1Oh6vnj4a74-hictScinORxPphjZ0vhu61rvD3f2Dq7OL81Xbtve3xx_7yltf--rrX3zlwVc__9YPPnx2eb4ZGj67WIWh4dZP4zE2Tmr6yS--8e_8ytcebc-adfvs09smBhMoai5w7OPti7s2-GUpXdeUXFV0WRIROYP9YV6FsBsXF-g4jYcxTfM0TnNVORwXNRnnXGq5ubkdhsF77GOTSjEtp3JC9N57x46WkpZ5ybVO85xzBYBc5t1hXqQaYhtj34WzTff4fD2sh8b7i7PVatUZ2Tgth_G4pNQMccnZxFJKalqsKsL9_cGzO0GamyYw0Wq1NhNCcs69cr6piuO0nABWp4TMUlIb4rKUvvGGGlwksmHo0eOw6lZd3KybTRvJ0_P7A5IiYt-1ofGl6JLKg023ik0uKiAKGqKPoSHkE1idmb0nQJJqNdeu9X3TrptIgEBgCIFJxZhxaILz1EdvAI5ZAIjI4EQ2Q1MVtCKa1QStGpzMXmKWqiCqZ4yePcHQBEQIjocmINaGcdWGwASmd_tjGqeH51updjgehlW7XfcdBwdwmpv3x_k33vtQ57qO_bYfdC4y5bvxcHszTjntUzrsp-OU1-fDMtaHT55CqRz9nA8_9xd-6U--8fs__dM_s1Aa54OjeH1z_dbnPu_ZTePIppHCMt1h1Q9evPibf_Vnf_rHPv_4bPvKw81Pf_0rMQ7_5Df--fPb-29-48_efu3ha0-f_uTXvvz-j56XqktDgdyb777uHDbegePgfVVMUopozckM61w5eEOg4E2VgpNSgdDMRMD5SIRl3pFvnWdL6hxYLpKL5MyEdVlA1aogEiBUBQEUQACUUkzFAI0wp8RNyzFSDIBsAt3ZxTItrmlcbKlti0FoW6lKzCqViIAAmaRWQEaA0DRSJXQNd0FKCTEgUa3VCCh6Q2hi47o2rNcBqYkNE1QRx7B_ft0PPbXtNKXgQxuZDaqZoeQkXddO-x1Tt70YyriQU9d0XePAdEnFRV6tuqL165973YECAQOqERAUkUVlWooAqJ1cTHzi_J_yPWon9I95xwAApmZ4siycFvUEwEzeMaluhhgZAtu64f8fU__xa-2W3GliEbHc67Y5_vP3uy7dZWbSm3Jiq7rUkqqhhtAtQSPpnxI0FCAIDQnqUQOSGupqiOXIYpHFqqZLMjOZmdd-9phtXrNcRGiwswANz2QPzjbvWhG_3_Ocd6FRRBUy9v8PnobldN1SGHMd5xxFY4HjkquSCpAlFY25gGrb2qGxDkGU7sdyGLMIdK21Bo65vntId_tlSnwc8_0-H-blmFgQkUytnGuZx8iVgQwDiKqzZFL91pOzHMs0Fxd8jHU_ZzKmcfTs6XbrHKnO49I17tH5GoRB6nrVHea0pCK2OSzLxWb1_vW7YMyLpxdN08WlLGC-ePP-wyfnj8_68X53PjS-7XZjfDOl3THFnG6uz_LhYAy8iemvP39_N-fbQxmPOQRfUwqN34-zsyRIqZZnjx8tlddED_vDatWu29YY0FTEh1evd-NS0VoL0Hg_zWU3L72x511rGbkwunA_zleXa1RkxPvjMud6c7NZ5uKc6VbB2ea4S9dnA_beKKWYW-9UpA0-xpzSMrRdKfnq7OzqbKNcG4NnfXNxuXn9-tY7d4KYCVLbBEsoot76oW3ON13j_6MCzBuu3AZvCC0RC3tnrTWSKyB5S9YaASDFUtk6W5lFUEROTRsyhoxBgwpY-JdtXWsMIv0y3nOKd5YqCikVASACi5RqRUIVLLWogEGYlxxrDt7GXBWlMhs0iqgq1ppaqlQumX3jD7uDgHLOgGicVYVh1QHpPMZ-1UnW0HippS6z84aFETl4yyoggqrO2MoVAK2zWtmFptZMgGSMJRunGREBUAyQgHUmzanpWyRbWfuzbZpnqcU1zq-HZZrOrq6WaX_z9AMAZM5PXn5wf__O-7CbjoGMN_43_7Nf-fKLNz_98y_mceHCOZal8rAZlEGKrtbtP_57n_3rP_wLy_rk6hIZ_sUf_eXPf_71B9__OI_p689fucZNx6VrVufetY05uzz7o3_1J2XJ8zhbo6vLy67tri82Q9vevb1zrn3_7t1mu2Xmq_OrR88eGxIA7kLom-C7psTFN-Z73_74t37lQ68gIreH4-evbstYWx-WnI67qfXu7d3ODB__sGRGLnl3n3TpN8N26GuJAKDM1gUFNGglRUlVq_rG1iVbUlQRiXU55lx80zdtV6Voiljyw27Xr9ZN06Cz-4dd2_Vt2xpvp3FMu2O3blzwmlirqnBomsq1Gbr7uz0YNIgumGWetVZjLRJ1XciJ160rqnf3ezIWLalAZWBFTqWSIhCSAeDgkEjTcS5Fzs82KZVf6k66tpZkiTKztdSv1rVou16tguclHu-nYds3TQCVeU4lJiRYrdcKMHT9NE7WWR_cybleU3beex-sMzWXEEI3tN5Yg9B4C4pn550wOOtZat8FZSilllLIU-XqguXKDw87RMq5TtMyjXOc0-EYj9PcemcIFYARv3lz5y2J6N3DQViMd7cPu6YJpRYbnCEqlacxMqvrXJxzrXV7eV5T8gaXlMfD0RooNeZcU0qCwCpo0bdoWzPe7Y73o_OOfKcl1pxqzvM8pSXmmBSEuYgKWGRmIlIFRPXOq7JUtsE5Q8uyjIeRvBOWVHhOKabIzAqQcm77BkDjXIQQCE7rwyVnAlzmRQAyl1XXQAUAzFwUkFU2XZ9rVRFwVKtY65ZYNv3QNU4FPv_m7ap1xlATPACEEEABQRsXKkthedhP81JU5f44x1wUjAd01i5j2i_lp1-8XmJpmnaaF7IUvPGOdvvFOlOZnfOPbtYPD2OumuYZEPbHsaK6tospNm1bSyFAEVUQIlNqabv-dAJ0NoA1oBqCZdEYE-dSUwnBp2l88vzR-dCOqX7_5eWvPLp4eXZuUXe73XYIL662nbVxYVvS2fl6E7pg8Hd-4zNf8enF-T_97PmI-Prt7tSgUuA8JucIRG0bUi1taGNaLJk4LbkWtHScZ2NdzIWcqzUX5lkyAFhvfReWlFEx1rpMKTQtEhpjD-NMlo7HKS2p7ZqLvnXGjseZyM_TFKekBN559AaFcq6V5f5uLg4PS8yRq1YQ2c-J5xyXpIjWud1xBNHjw-QsKUgVCWgsASssMZ8YEcZgFeZS3j08eDKJeT20l-uzrutqrQISQqiFS8mN88p8PqxizmpMzGV7tk4x5VjiUnNlrBgsKctpy0TkggtEJqZcWCiQ9w4USsqVc0yFmVd90zqneArIkjFkwFYFIB1a17WuddaBcYa4SC7FWLQA1mDXe0U0FgWUDDEzq5xkahZOFTJcUvbOBkurYL03p2GtMaSqXWsRRLi2zmza4A1Vlsh1rOnxxaYxZAzePjxs1_1m01kEVU6F__oXb_7Du3dr23jv-7aJx2UphRWcs7fjsSo-jOOwXh_npfENl6KVHz159OLD5xfbIR4PreDd-4f_1f_-n0JO73725tyDxON09_7uq1fnfeBc__7v_fbv_eqv_uDTl6LVoO833b_68x9_-c27f_Yv__jm8bUhHef07Y9f_PSn37gW_uw_fH754rJmuby6zrv7zbb98OUn0zg-f_L0cJhjKbVIKdUouK4lb5QJiATx1M0V1ZqLcbak3LS9snONPwnVQFSBAMQakpxRgRCMs2gMCtou2MapcF6ybZxxzoTGh-BChyWScl0W5YJGa559CCqZCFkLGGO8D33vQhu8I-9BAERR1RCBsJQqXIwCl1JjPKXApFQCklzbtkNEqWJqBoWiABYdIiLncfK9b5oAUnJc6jQrESIYA1p41TdStSg6B8zYrte373e-9-AsJ3FtF5oGUP_er32K-VT0xcIaCxfRwqqErJgKA1AFISKDCKBSWUG9M4Dqibw1p-moN2QRSSVY4ywalcaazhpvEZg7R50zrSVR8d5WlVLFOaMKsfJhyUnhEMt-zErgvckiilCYrXM5Vi7sLJ2tQuNIgeZUv3l7BIPd0JKhmMthKq9vj1F4jDkzgwE2zEaPh4VQVJQzG9QiYo0RgSaENpjr7frJyg-B9nPpWmuI3k7x5mLTWvfdF2crQyXVxtNmCGerRmqFUpuhf3u_S7mKmtfv74feD84g6Msnl30b5qWO07Kfjt_56FmLWHJed8Fa83BcHpbSr_rxOA2t5Vpv9-M30_KLdzsKw2GOcyqhs4CSU2HmEOww9CWm68tVD_ji5tKQOMRxyWer7uEYl2mZ5lhYLzbts8eb7arPOQnLzdm699Q3IcWSVY5LbpvmcJxqWh4OMxgcc5zmMtUSc80qjy42meO88KOr9SnMEzr35ov7EFzJYglF-ObqMi-xcL08307z0rUNKHjvHHlVMN4F67w3m64J3p6tV21jW28MQt803lFcUrAWDWk9NcjUO6eA1lprjKVTd_ZEXXZVqg9OVJy1pZ44OUJAInCC_RljYs7GWgWozADKoDnXUkVEEGmOSRXnnIw1Asi5chVlrpUrQGh8TjXnTM5V5hNDJc3RkOVaiQyodk2IMQtILbyk5J2vlekUHS_lxPtSKbLENC7krPUegCQX532ek7NWKyChsYSiWISFQcW3jXHWWjKIIkDG2OARpEzZdx0i5MLeNygKoiJy_dHzeBzPLs67rnv09EOpibmu-n7YDPf3t-3Z9sXFTXCOO_3TP_ybeX9sNv7hzRuD7u4hXlxdnG3WNTOo-_s__Nar1zsE-Pjbn-RSpzR_-c1bG_xXP_96Go8l5_3uePnsxdObc8fgjLubpvv3D6VUIJoLOReu1isQKLlsNoPWWkq-PNs6a7uuuf3m9XqzXa9X3htEnA_ph7_-2W_88LsrF3a7w6brbh8Ob16_Q9FljKFt5kN98fGjmuLV9ca0L3-1P3tUl0lqzdM47h769ZkgPjzcrVbreMxN14Fmax0YCGet1kJ0MoaAVrbBzvdfg-uAbBgGRDvud4qYl6XtWmvbOM_T4ZhzFtHQtGneaxZg--jZZ0UP82FcxqkqowECBtUlljYEa13wTlXjXBBsjvF-f1xiDKF5uN3nzMhac-7bnmvKC7Pw0HljjIjGkp0z1tCyLIgEBHFZ7o-HGHMztERoCC3Bat0TqHO27frLJ49LKU3f2WDMiWvGOh1nH5wPHlVzyipaiigpIaYiqZSSSynVWptTmqepCQEsWYM5ZocICqcpuBDmysI8jrkW0fpLAPY0L2TtsF1ZQ8ZhEyyKbDeD1jrOeRwXEAbVvutEpbLsd3sVJWNDCLVmZYw5AxABDL3Hk3aosoqQC7v9kWtV0Fp4WepwtQGqyxRZVGvZvXtIx4mcHu7u0u59LZxzLlyASGty3pa0aBVjMc-FvBMRVkWiuKTzzdl4nF3jljkfp-gsCEvwflpSFilcamEXumWZSKhvGxYFBRXIuXgkYVimSIamVHKpItBaJ2ByLYpUWQhJQcGYh-PMooBEBISYYy6piFRRmFJsu8552zSu875ynVNaSn31fneMyYVQFN7vxtB4ERFPx0OaU93neLXdskIWnpc8xlSzFNBg7fv9EcgYwGmuheU4zk3XAiErchGtQML90LmuqalW5tAES6YWSXPshxbI5JLXF1s02K3avCzWWxGuUJfj-Pjm6mzVv3y6_c0Pbp6f9ZerrrUOQH68_-IHT58Zct6by83w-W6-Ou-__f3nnWv_k28_AYMt4YPSz3_-xrduONv6wdeUWaVZNUQmxWSDK1x952OqufAJYnB_OHShOxwXh8YYU1lTZUlF5uLJIxEDcpGKkGJMhX3jjffzGLu2WWKOS1RlUHh_t081plwRUKTmVKuAMO8OUVT7we520zSleUnHwzgtybWuX7U358N2FUQ5eOc8dd4yszDEKKVyMzS5VOedqNSqCBQsWeuN6sN4nMaFrDMGjbM-eOdt3zZDE6ZYDnHax-StHYIdutD3TS7paruyCN5SLfW0abPekwFrTSqJhR2Rc9iGkAtba4fOIbpTT65WEREWjaUG59RAZQVSIEFQMEaygAACpVLQYGgCq3jjrEVS8kBr79feemMaby2ZlKsK7GoiQxahcUaUhRAALEIfQqlsAE8UBEe0HdreGkdgDSlKLIW5tk1LSEr09fu7zdB2TQDQAvKzL98wuhePbs76ft21S5zR20NMm03fdMOb2wchEmBm3qw3SxwHFy5X6y7Y3du7n_67f__pt158-ujRj79-30v9L_7X_-mvfvbx__a_-J__V__5P_n93_7N_-X_7Pd_-9d_8Gu_8p1nz6_-7b_99988vL7cnm3Xwx_9xd_8wR__FRdpVuuLJ4-fP39y_3C8urxozXD1_Owf_P73v_zm4dVPv7nZdEMfUtKrm-tc03bVv33zAM6Mc5zuHkAlLVmN6c-2Tdcyg2va6TgSgfGWrAWyoIhIJjhjCAAZFBS5ZOsDEZC1nEdAiwim8yAS94uxJqxaQwCqCJLHo5QMtUhOCCJ5ISEpseYo88Rxqcc7zAnSVJejGpkkm6ZfXVytV2fD2RWStyGgQUCstZJBVBIVrqoI1hpAgyog6pynEvOygEcWFgVktadHISMAWONt8Kc_yRpVM_RtXCILNYOrQqGzWLhpPKA5uz4rpW7Wg4I-f3zdEVYWZklVcq0CUFmIrIiQQSDgwobQEgoAgiJQVXHGgIohMpZYuPXWGWy8RZXOkXPUOOOICMFb54yxZFi0KmSVyspAS-bdmA-Zc4UCmBmdM8aZWvj2YQFhQEIAY2DogzcoQvcP6TCXOdV23brOLiU_7OPr3Xx_iMdYC1IuvBSejzlnXqbogznrwjdvdm1jwZqwavrGe4In6_C0b7fBHefyMEdrzPnZKqfSN_aq9-eWMBcovB7aUkrnLQER2Qp6f5gFnfXtfo5D4z5-fHb_cPjw8aXrhp998S4xh8Y_f3SJtQrz0Pmxwvv9vEsMzs9jXJboOv-jz999sY_7RbPi27sHLlUIWGSaFiWKORvrAtJF392s1ud9g1J3x3w3TqFtdsf0sJ8vrzfXFxtr8NnZYMWMU_TONI13hgzR_e54nMv7JXfexVSfrPtD1v1htK1_eEjG0HE_51oy1yXXec77ZX_cp1qkKDNrP7RIpAiI2vatAXLOPnl0zTk1zl5sV_O0bFZD4aKiTTCPL9aNMf6UaEMBUesMIJzY4n3XIqACh-D0l8EXRCQ04KxlViJUFSJSqQgIhJWlssoJT8fAIIrIopUVEJZUyBpBqCygEE9sQYVUWCqfigWG0BoXY1alKtW1voqmJVtLCswVS83O-5wyGjRAzJVVvXdd183TbMgAgooqV2uNcrXOSj2lh5hzZc6cIioQUeVKxiiLdS6n0nYB6IQWNiAKAEgQ2kYTi6h1Ni_FtV6rSKpSqvHGBJ9qadrGWisWLWjbr0rM_Xrtgz-_uN4fDo-f3KzXQzc0P_3ZTz756NPvvnh-3vpxHL_6yS-uHg8_-tFXL14-s-fbj7_14W__zq8__85LR7BM-eOPn5aqP_npF93ZwEWOS_qrv_35T_7uq49fPr99d_8rv_XZX_7ZTy4fX334wZPLVfdwf3z2rSf_-g9_1A_ubLsR729eXl9vN30b2sYTunkZrcHtxblK3qxW-_3-_OLcEI63t0T0-NH1p5--2HTtcZqYWUAX5iXyJBgGf_nkcvDm_Kbb3x_m26MbnOmff8aSjO0UBFIElt14sKGRCuv1UGrK82x9eyrHpTnlJbsmSGVC4FKUq9SsCcb9XgBD04ahL9OCWkW1VD4Ny3ONTddxZvJtnSbJdT6-0VoJNc3xsNu5xpG32-0wzakJvuaMRM750NocI4Oo0hyjDVY5WyPOm2VafHDGmNVmXRhzYts6QDpOKXh_mFPwzjuTa-YibQiN8ynnmHheFla1ZHOqxhi0jmvOsdQcnbGA0A29IdN0gUXSElnAn_IKBMfjGOdUKqMBAWnbEBqfch5WXRVZ5ppiensYuQIYYBayyAZyygjAIERqEPKSlSjXbCyUmG7f7WouV5dnOdXlcDTBGGenaUqpdKthP83zPOVaa8ohhP1-n1nXjT_OsVYpla2ROGfjPBDWUkU0LqkZ_DItlogrz1OK05LnMi9FueQ0pXEqKZcl8zJJTXGasHHMCmx96GscRZThlKhFFkVHJWfNNaUy5wkQAGmMC3B1Bt--OSSQzDwvswLmZRnHoyqUKk3XxXkRFhFlFecsszJqBXTBCtdclLxPzMYZa93JCWQMlZKVMJaaSwEAUgEDxlkXvBICWnL05s1dyrltbOtcBdjP8e1xMsbe7RcK4X6KufD5tmPFJfF21XjnAPH2uMRSEksqWYiEgZlXXWctWIJU2PqQaq0s6G0tCgDem8ZarkJkCZCrkKETL69vO1U11njr0xwJTds2lojniEhY-eZ6c71d1Ri_88HN4_MuL7O3pjIvS_rs5nHXtinV4G3XhR--vHr56OK6bT97fpkTG62rodsfj7_44vYXx3izWYEQAuzuFmsgNJ5rJcG8pByL4EndjrVUQU5LQkPzcVEy4NgTjce4cOFUq-hSMyMsOQNCSWVMCQ05F1jqami8sUtKlxfry_PNmJL1LqYMDNYY64xRARJr7TilqHy_mx2ocDUGOcsy5fv9fHc_393NMbMhigsrUdd7a4zz5rCPUlkBmLVpG-Y6jkupdbvdWmusoXGe7o_HmKsPYZ7jw-5gLF2sN8HQJpgllVS5tT5YCwy7u1tnXeN9YmbSzaZTFiRtgrdkTvQeREBj0JhStZTaBOuc88YCIAsTYWVJuVaWwvUUyGNBQ1aqWLJdazd9sMZoKSnXzFWqAmHT-KUwK6TKuYogOO-Cp431BKesIoIqsCoAqJbKFolALGEfjCdaeesNqGqMcVwiGGqCGZwjNLGUL1-9D46uztbznH_8s68EXLfZdpbuH_bTPI0xrbbbwzgjc-j80HV_-hd_88GTG-uacb83VcbjNPT2ert58fTq9__JP_jo-bPVevM7v_XD1ar7259-Ydr-6nrDChn01d3h7169Wabpr37yt-8eDo8vH3_04hkJHJe43qxCOxhrGcHYQAba0D9-8fjx4-s_-eO_-ebr-2cfPql5ubi6BENDax6dX63a7ssvXmMbqO0O93ujqoDg23laQt-VXER5GNabq1VauBbBEAAtkIIqFwUi4zshsl0HgIqkikgByEjJUrSWZNtOQeo0YakoKrkA_jKebK3jAi40xhIaQ4p-uIIyA1oQMcapAC-JYoFlScfdeHxY0oytRefPnr7YXD9fXTzabC77YQuEoAIqSBZADBkUrilKyTVHVeXKiBRsGw87S9j0PZERLiBqBKz1JZW-bQiBDO7HtFr3cS5N78uSiJSNoqV8rMOqI9XNanh03iOe-uN6ysgpKiqqQhucClhjRUSqEKEnQgABbaw5jfwFtfe2C9YAOIPBW0NkDCFCzgUNkSMRLVxjqnMVUcysS6pL5grqnFHCWkQVuFYuzCzBUtu4EFxjKRhiwCnJ_WGalmq8hdYVkdu75e39vJtyBK3GKOKcS0xMgKAZgKqCA1dVfYCUioIMbROUP173121rDNaUI6dA9Ox804ewXbeNNQ1AE4worDfrmPO664xFEPzy3V5UrA-RS871-rz_9uOzu_uHy-3GGve3P_-669vL7aprgwUABSRYSv353fR24pTZWySR1Sp8cz-9fZiqo3nJXDnOMZfKrNa5otWTLVx6ap5cnj05G7yhCphzGku5vLyIS0KgR2frR-erGMs8pst1o6p945yzoIKnfQcoo3EWnDFZ6uv9mFIOfSgsVeHp481xyjnmEEKacmHVhRWUyBjn5liDNVfXm03TXFye5xg3feutXYU2lTKEFlHPNuuyRGtM4-3QNVWABVLlwzglLkhUSgUk6wwgISoROG9zKjHn4D0hECALd-E0jmEAaLxThVT4uMzG2FgKIAjLqS2Qq5A1ooKoAKgAOdeYCosKghAWZQCopVjrY8rG2MpcRY7zaJxFpFOaoHLNrKnUzKfNm-aYyNA4zW3bCQiRqaJAhrkAKCoKQs3Fd-08LQgkyrVWayHPGUhVobI2XQuqXBkUyBot4ocGEMuSkYwNnqwthdt1Zy1xqaAAJ_oiiPEtq67OLzdX52VO3_7B944P-1qrb8KHH3282XSoBCA311f7_X7M0-_8xq8_uT7vgy_L9Af_7N-c35x_6_s_ePPm1fri0fn19SefPDfA_-Of_PVXX3zz9MPHFzfn725vLy43q77fbFY__unPRdUG3zft1dXVX_3Fj771_Y-Gvo13u8dPbsY5HecDgbLoy299tMz6eLMdhtYCOdA3r-_bNnz44c3zZ9eSdejCk6vHxsJ_-NHffPTs0ScffdCt-hzT3fu79Wadc3r_7oEMXVxeTvOU5ooVrtZhWtLDPlrS42E2sn1RFVWL5mJ9KDFyScbD-fnlHJMx6EITx2OeUmga41G5Mlc0hhxiY0HINStDSg5OYqBus22aLualCnIp3hpVZEbkalunJa9vrngelVBqNeRzXhB4Oc63r25RQZMYROX6_u1dZQHCbb8SgwpwkrE75-93u_kw9mf9cT-TwXlJVgVJlQFAEBkRh77p-65vPRfpuk5ZrDUhGEsYGv8wjUbBN36a5vVmxVwut1vThhxL03hENEB5TmkpQGYal3mJCJpZgnNgrPN204WHKa28Z1HjSCqLgvNQmb2hyLyMEbQusY772XtrCKXKMadpjt5gH3zTNM4aHxxwEZbrs_V4OB73MyCOh7EWbtvGB9w97I_jFBrbNQ0DZCnzGFPKxtrxcIxT8j5UxcNhqsIppbQsOebKNWU2zi6xVJZ2cDnGaboNXTuPUz4eCYSIAcS0LTjvmwClgFaedyCVSxUWtA4VVQyIBBMqc2O7OE_WOUAb56VpQ8lZCUopXDI5N89TmpNgBTIxRjIkVUot0zSLKAOcKgopZ0WKpTJILoUIRSXmTEjGmJrTqSVURVSh1Gqtdd54Mq0P3jhUuLt_2O0PYGlZCgEVkfcPU9s2Jrh5yllxybkyrDbdj35xa0THOQWEn79--NnrvXUmVbHOqSggBOcURUWL0FyKMaSEKVcTHLAKqjV2M_RVhZmFWVXRUNu3IEgk7dCi8PZsBQgGFUSEpQkeQS8uzoLFJ4_OXlxvv_X0euUsWOqdmccFlJGoaTu02LTeogFERxiQsuhhXoy3qmiNffrs_Psvb66v188uNv-THzxp2tD2HSCBqvEEigAqotaakjOzqKASgDJ6k2sOxsWcnfPKYtDOUwQyWUoqbIissXFOpbAFZIAUk4ggmmCtJRraVhBEhSz53gdnlqTBmMSSSymgWiuqNm1TSjWWci7dyngS57HrXSqJQbz33pAAnEByxpACGOdTjk1wOVfrnCVUFt94IjPFqFUedoftdjCGvnp3mwvHlJomnK37vg9kLANfrfvN2aZp3KZrPrg-O2_9zWb77HwNAKs2PByPClpFgg-psgIgqCVMuaqqCLfBn686qdo0wTmLiIaoCuvJ98vsg2GpsdSqgsqrLqy9A2uaNgAhC1siUGmCDZYQYRVMPjm5QZ21fbAnG1MbnCXsgjWGgjOdt4M3Q2M7C4RYVGutCtoE11rnkGJlBnhzt786O1Nvvvj6oRpTTcgxHcY0z3HJNRZug21aH-eoXLfb_su__fLiavjW05uzxv7KR8--9_Gzly8ebzb9ZrviVN7ePvw__9m_eXv76u3dw-_95vc_urnq26Zo_oM__Q__4k___C__4mfD0H796v7xo5urq82vfu-TGvPtYfnZN3eb863UknKtS-6asB262zdv7u_2d8djzHG9XTsUIL15fPXzv_nF3_udH56tu59--Y6V5sMcjzMBorGnTnwTbLvZzPtDnutquw3DkFMl604_2SDo2g4AFVQVCQEQjSFRJbLkAlrr-8E2jQJKZWusseaX9VVrUQEIwRgkU2vRU0BVAOsMwgjKJ6snWgK2xlhLyqyqxJKPh2X3cHj3xe7NL-7ffjXH_Sy5v77eXD6-evxsc3Hhm9Z6R94XUSCXyTAoeCtFnSMkqaKr84t5nnLKmhZhRQQwpuna034jR91uu5RL0wcsptQap-ob33rrrLfWdn3z4ZMtViEicqQErEpEv3RHiBg61cnEOmqcIUIE7RvbOmMJWmcaosYbEEZERCQCQ6QEXFUAa2URFYC5aKpSqirSkmuqwgpFRAGWmA2gt9RY604ZCRBjrIiOc9kt5fX9cT9m2_iLaz9Xvrub7o_zGEvKchL1LKmAqLCqaHAESBWQmY3CdtOGFm7O16vgPzjrbtomNO1U5PNxRoPWuKeX240lEJkP06q1nQ2CKACAQpZaZwrDYZwUxVg3x-St-ehqde7Nm3eHrmltCJ-_fv_4av3o_EyFVZgVhGCu_PqwjEspLFjTdmj2sfzk6_s3-9m3fRwXZK6pKFcxONf58tFVnpMDfHx59vHVZnBGRJaYf_7uLs6lGYb9_aEN9tMXN40CKM9Lfnq5MkAV1FhXQeMSd4f5flysdwV0ifX-OO6OsYKmwvNxUaXdflqW7ByxqLc2Llly2p53hBZUJHHXd6t1yKksUyaF1pmh7xtrrEXnoPHWeitaUCCOS9c3lSFmaVtfRYxBZ6x31hoqhVddKCyWEBFAIZVqLDXO18JIQIjO-iXXxhtvbRWOsSBi432t1RgDKorIAKqaq5TCKqICVQTgl_aAonLC-ubMImqsmeLiXZNTNMbmWtGY1jpFLEVORAtWZQQpFVSZaze0UCWE1jljiZq2iSXP81xzPiGq53HqhrYsnI4joeacidAHq7lYY6uI942KxJiJyDpXuVpnAbDkgqhkjGvccpy98-ePznfv98qihKlEQEBCb61W6ZpOGZ4_ffHNl1996-MPfv03fv1su9kf7tfbdd-2_RCO-92js6vr7frJ1fl2PZRg_6__9f_rs--_FKCvfv7lcHnedX1jqTVmGFbv7g-r7WDQ370__vjHX-3ud423X3zxygfLqb548vzh4f6677744vX5eV-WujlfXVxc3N0_fP7zr8niMLRpyZeX6-c3l29fveOczjbri7Ph8mzdWdM6M4TwwZNrRPcv_vpP_pNf_cEqdALmZz__6mw9bIZ2muaa6_Z8XVJ5uH-Ic7q86D94vH57n94-TH3rjfePXl6b9vn3Oc9S0Tgw3lnvLSAs8fj-rh3aktg4st6vLs5rik03xDFyqcY6VmVGIrLW1ZSsdc1qVaaZjBUBIYq7O8NFQMBiaBsi27Wtcl2mZbi-ctbkJTMn6whUrz98RFrS4YBapUbJFbTGZSFUVqmsx-OcS_XBh8Zwynev3s7Hw_279-_f36I1pSRvCQzM8-SdKyKlVCQ9HkZj3bxEQThMUViNMSI8dL0BzCmXXN7c3idB0WKMQcJxvyioEhnC1boBwpQKgMY5IkDMhSub4OY5IcI8pyq8P46p1nFcYhJWneaFiyDW4KwaiLFYZ3NJhgxXnZeKwMGHwzjev9ulND26uS4lffXzL7p-tR_H1aZ33pQYSfj-bl9Eai6Emua0O0xkcZlT07mS2VjqVk3lMqXEUhUEQa0LRIREQsCoh3EkY0UMgxg7pHGKDyMSkEjh6oezXKpvggJA4VO5GQ2CQamszDZ0oJkYSikKwCUba8dxCn0X46Is5QTIA6kli9A0HoULIhVREEW0LFxqRTSgknNWQEUtpRSRpdRSK4AiERAAAKGJ8xKcV9U5pdMHEol8CFKZmU8OAWcQnXRNNy95XMqTR5s--P1-uZ9zFgVrD1N2bSCCZeTdkkU05bJb4u1Y0WFFTIX1hJX0YU65611OpRbej_M6hFq1soDICYXQ9M00LqWk6ZiQ4PGLJzlWEDVExAwqzlDhOmxWxjfDanj-8YtA-Oj6fLUOxPr8cvjOs-vnF-tV47HI-_vdv3r1kw22zlpypnUuzclZZ5ARqBKWUvwJXyBaVJ21CLBq275t7o7RG9f0Latyqc44UKiZT1jPNgQFROFS8onqRtbEJSsggnrFFBNZn0s0RKjaBLfMi_cOQMe6ECAZEkJEiUm6oQ3OBPIxFRGdphyjjlNkla5pQqCSxRinjMYAqTUqzqKz3qLrrFtvVwzUhmBF52PMWYO33mAbfD3lQZmnaVGVOKVlia134zj1q3ZoGmuMQ1yWJTgHZA_jlHNJtdxO4zwna62KgjGNs30_VObMWqAqoffee3JoyZvVpp9iHJeoLKhA5nTTw1xrzWyMHWPsN90SizemDa5vPIM6iyC81FqLMFcFs8TknC_CbOG8HWLhGHOq9TjOzCqIRBYUWYUAkCwhemPJIhEE51DAGtM4Zy21jbFczprQO4OgXGsRqVwVoTGGiAgU0aCjN2_3zthc4H6ZUhWuMueSuO6Ps22sMzS09v7-3qksU1z58Lu_-elnHz256turi-3Q-JaMFPnq7u7__N_-s__hD_7y7e39D3_wvZcvbrar9mzVb9dtAH319d03r6d5jP_of_obV482UHi1DTfXm1UIx920MBdj5lxWfXd-vr25uc5pXA_ttz_96ItvXjVNW6S-eXefDuOTx5fE_Lu__r1N19VSb1OuCnmJRJRLCf3gQtAqqJBy0cLDerXEOu4Pq5tz6zvjrO17JLLeC5pa1HW9sCCZWsX5VoHIEnonhZWIa7Xe51zI-RMMDRC5VnIWVYAMEhGRcQaZT1YvNOZ0_Cej5AKzum4tXDmrD0EFtcjJqYeidUl8PI7v3u1ff_X-zVe3b78cl3FB3N5cb589uXhyvV5vbdP4EKzDsuQ4H4eLK-Od75oQGucsiOTMNUPXt4RGleMU-1WIS_bBcq6CGjkHZ40SkGnaYBC--90bqqDMACQCANoET4CGKASHqspiCb3BVeMAwVv0RAbQEHpDCqyAiMSnUzMri8SlVgUGLVkVMWZOrIonNZpm1tOIF0AdYWNpHbyqigggJFUFvDvGw1yOhfdLaoeWgo2xvHq73B1jZB1TmWJVRVaojGNihyjEwVprMBUWFsW67mxjqU768dOLp6s-iA5dd3-cKulF1zxat2d9GDw5axFBUZxxigiiSYpzdHPWKcCy5PfHvOn7UsvV0Hz6eOtB9uNydb4Kbfjyzd35-Wpomrv9lFMFQ4p0e1zeHNOPfna7gN3F-XsfnAGYP_vF6znXRfT167fGUlySgjrjcy5grC3gkZ6dbbah67wxVt-My_5wXHdd2zZaysvnl482693DwRjyjR-GYC0tsZBzrForx1IRjfV-iflhv5DB3XGxwS8lioi3bl5m75xyzak0fROCDdZKrVyx2_oi2rQNF26MjXMK3nunITSIcP3oXCoLgyUS5q7rAcAGRwiqgAYFWKoQEdfTDkmcMUCQYnLWtk0omVm1MiOStYSInkhAiZCQahVjjCggYi4FCEutwlJBGmeWXOXEyQE11sRYRJVFDJpcGciUWshYARVmJMdcljkzqIIVlgowTYsqppzJGEBg1pILAFSWs8uzeY6lVLI2OM8lp1Q4V1StKbNAM7R939VSudTQ-tB103HkZUHAFJOxxjgbYwSEpvUlFyIKbScqoGKtQ4TuYs1T7VZDnqN1Iael1up8iyLO2H7otdShHb79vW83Fr7z0Ycff-sjBVWLL148YdGf_PSnQfXDl09_-O1Pz_qeyN6Pu3_zR3_64vrq3_2bPwdLTz589ouff94P6_3--Bu_-j3r3OEwEZDBenw4NI6--73n3_v4o91ufvm9l6uuOT8fHl9dvX24v3580Q3tenvmjZ-miax9-uyRMya0nbW66c_mebraXjy6ubTOcq1dF5a5GKLH1-cW8DBO333xvHVufXU2LtOLx2eDt23wq6G5uTmblpiWxXrXdR2yzLl-ffuQVIaL8zzPdc5m-PR3_NlFHveoNY6TKHarM42pxsRljvtDFW1Wq2WaAenh9s4Ez1oBVaoaYyQVVAkhKNqyzKwiRZxvrEFrbYrHGCuRhhDinAnVuwaAjrvReY8Ou6Gbp7lknR_G7eVlPh6X4wiARXh1c9M4rKrLEk3wVWrXNiGYeZwVxHgrldt-AK1pnubDdHjYc44P-90SF79uuWRQtmSEhUUQQBj6zouwMwatPblqjaGL9TDv9lrUWoPCoQ2swoVrZQBhYG8tEa5XbTd4ZkhLscYsyzxPqe-643GSXPKyGGMQmFlEFFGDc4clzksJHpfpSAK5FBUgAim18WEcj11wvcf9w8M_-ke_8uM__zshQYcp1XGKH338na8__wKtAdWUkqYKZFYX_TyOABCaZh6T8zbnImAqV-sdoczHxTgqpWSurIoEwJUli6gwo0jXu2k8kFFOFUA4LYinRqIAWdVccyE1CgIIUgVJjDVcKwAIFyQUgCVOZEiVFQCAVZEMVBWGUnM8kbNiKi5YzoXIZqm1lK4JS85VlEHQGAGMMWqp3rnNup_mKCw1V2YlVGsNGky5ZJGu6-Z5sd5Ny6JApeRHm65WNITPrs6mZalLQmcZ6O3-mBUP44LGTJG7VbOfcqzy6mEngIescy6lqiLkyo23MdeUS9uEcS6BzBhzzJWQgFCIaoyNddZZAEVDhnC16kIIWtkZctaiqDUuxiTM4-EBkKzRdRfKNG6G3oBcXWy_--L6N7_z_Pnldt15IjVIXRt--Ox5Y7xxvuvaeYmHJb662-3GJOTup-V-d3y926-D6wffeTKEFmm9blQlxdp03jrbNaEWAQVjDRhcplmQci6oODQ-lnoqp0oRa2wqKc0RCFHUGuPJzOPS9k1cTvIjrCwMJKp938acu3YIrT_sp3XbeG_OtptSpds0wVtD2PftknO_6VfrRmrdrBpv7QdPVmOsCnp7f1w41yrTUlIpaUnboS21pFIBNWUuIogIiLFkNHiScC2F0YC3Ybef2ibUKqs2ONeOcVmtemeNQ0sAZHE99O_vjynJ3SGlxIdxtM7UnPq2MRb7rnFkgaixfh6X9WoAocaGlJhFSmEA0F8uaaQJDSBZwFSKVsmpBDKDM4JGGckRoDJXQnCWamFSl2pB4ct1eyJBkcWUi2g1iCWLdy7X1AYCAVBVFW_QGXIGgiVD2lvc9E3vDKgiEQuLqrUGQb0lFW1bBwJF5TjnXGtr3dv3By51ykVQU2Vnsdv2kOqrt_dU5bOPXzy6Ovvg0dl66A1zyjyN6S---Or_9N_89__DH_3Z3_78TaB-NbTf_8EngIpAtsCT6y0p7Mb49bv9FOOwXnvj6Dg3TbvdDp2xT66uHJrV1frzb97f78Z-COhMaPx-v1913cJ8yPyjv_n85SdPnz25FuUffv97qvXZzeVZ183zfHuMVSGzzjGmIqzYDKtxrO0qcOGca7PpS6os5cQlrKyEBEhV1XUtK1CwgsoCoWuJTkEgg0QA8EupL6Lr-lwqITVdf2Ig1lpVCMgZg8a3eVlODiNCgwRIxCwAhgUUSUTJWiVwIQgSS0VVROtDh2iMM4TkW0-qoKopy_Ewvnn1_hc_efjm8-nh4NZeGIZuGM43yti0vu8H530p9fgwkbEFWa0JwRpvVDEti7NYs5B1hSshomjXN1zEh-CcaRv_8fMbr-qNAQTvMDgnLM6QNYYAHaI35I3xZODUVSE0iKK_5CaXikXhxEcCIgVk1XwaCwGwYqky1YpysjXqlDILe2Pb4BxhYwwhVpVUeBGdUr0b81S4KFQ0gqCAgHB3Px-nEks9xMSq-6V6FxAESFlqcLTuBnFoAQ1ZZkWLXecfX6wGZ17enD3uGg8ahv7N4bjp-4vOXLUOiTRXZ8gYUgJLjgEMgLEwLel81Rk1t-8ObdNc9r7zeLnpNr2vue4Xbtp-KfrqbhzWfePN_RhTYbR2LrqL_M399G63ZNVuZT94ti1J_-br3ZLqLFJzWp8NuVZjDHpba226YbPun277R93QGiMoSfXNw7jM1TlnhXLO33m8qXNacrkaVk3f5pS985WVVadlSYXvd9MSCxPMc9rPKefqg8u1TOMyp4xAArzuwnrwKXPbutDZ-ZjuD8cm2K7z_Tbs7vJqaJq2aT2dr1tSXm8HgxiCyzHXUs42g3fWeqtcUbX1Vi2mVBAgpyq5GmMINTgnCpxrYRDWxpucq3PWOeusBVCD1hgM1rEIIp2ga6xMpKd79JIKOadKx2N0LqTKoiBVVDGdSo2iRKggc8xLyqyQS0UFURXRnKtYBNVUigg87A5tF6wzqowGa6nTuDjnUszeOQBMqSrLxcVFyjEtEURF2Dh3Eo8JK5IdDyMRGutYMU6LSNZaFA0iCQAgOuclFzLWuRZAAKTOGRCatqtLrSXZ4JdlLCzWWQQMwRkCAsyprFfrf_D7_7Dz9vLx5dXNxfv7-8-__No1HpUtSw9-6PzLj5_tY_zJzz__yS--2nF2qJ___LWh9uV3P7UK7apLtX7w4tnHT5_uj8uXb24__OTRL372jbHm_OyMI9zt7q-2Z49fnL179fD-zYFZ5ikvcdmeXxx3e-_plGNUUAHY7e4_ePkSUjLGXJ2d5TQhwmbdr4cOVT9-cdN6wyAAapWq0pJysNYgBWunaUJLb98dpzk2bQNkraE55fu7MVUZmqYnBeF5TObst__xcbdv2kaEAUBiBhHhyiWDqgsmrNvj7difn1fhpu-MxTSPCITWEqtBU09DXGekZFU2xuZlIWvI-NXllSGUmG0DPjRoDQU0xthg5-PRN4EFrbfxcESy8TALZwSWec7jFG_fL8vMUtuhAwAWNIZQ66Pr6-k4p7yomiLl6unj-f5IpFJiiTEfx3G3l5gfXn-zv729f_265FwlkwFRrZV906ScYky51lpYhBnAN_7Jxdmca1WOKR_3owAvczwcRlE4jnOKuQnh3dv7kmvbunlZxuMCIAkK1IoAxmheMhBl4VzFEALo7n5kziisgh88f7Y7HHNJuZSzTZdivL-774J98vT64d3D9bp_f3_8zqcfH46TAWDgV19-iUY4Zxvs8X5fCpNzXNlYM0-57Z2oLDE6b-OyEKDUUiNLqYrcBDvPqTAbgsZaAFimfZ2X8Tj5TZ9iAgBFRlQ0hMYYspUrnR6EnMkZFBAuaICIco4iUlKh4FiYpXarfh5HYwwgIIjk4oKJ4xJz4tPIgEBEECGXApZO_242yiqFxXuvLDElItKquTA6M4TusD84HyzB4bAMq1UulayJJZOhknPO2bU-pVSEmzYgwGGO4MxZH96_i-frIZNOuUxZHvbzlOpcyhxlkaqEMddKeHeYEQ0a44L1yoOl3SSC4ryzqqlWhdMpwJkuxJSbEApXsBCCNYDWUvDOGUJAQxg6RxZ9Y5rWeW83Z-fWQNsEqOXmct214dMPbn73Nz68afzVttsGCzUtcwQDNrjCUkVXfbM_zlPh4XwzTomcnWMcx6WygCIC3N6PZWHrHTAcd9P7u_nV270YqllyzoiEoieiTjt0aYq1lpRrVnYh1JKk1LgsSCgixqAwp5SBwDlbsxhj5mWphasU42kZowFIJTdNNy9RKhsCrtoEr6KXm75tXUPOIHbBE6IDrUWFIRAJYilyebWyROttx7Ugqg9-PsyNoWFottsBDWbOzlJOLKRd708Qw5RyrYwG748zgBhnlyUDom1t5uq8VVBrbGj9dlg9HCYDcHmxvjzv1q2xKJtNN6cipdZaUemLr79eZr497pvGK5tXb-9WQ8NFgrM55QKnBCo7Z7omzClN86IIBmmJtTCfRF2piHWmD75vXdOE4BygblZNG0xAFJGplrbxrGjItN5bwta74AiZtbIlaDvfOltLjVI6REsUHAbS884HAmvIkEm15FIVwVuzahrvLAqiAQAsrHMumQGNuT8eQPX97nB5uT477998dbvE-dF5_63nN9_76HnfN52zy5J-fnv7f_zv_vkf_Mu__PKbd6_e31-uth9-9PLq6sw3fnccr67OiGi1ap9dn11fnvV9uwh88-bh5uYixmWz6q9uLj55-bzx7uMPnztCQ1RzfZjSZ7_yoSmcEtdU9w_jk6dXperDfhza8PjZdecbT7RqDKh89q1nXvDt-_f7RQ6RpyUhusoCxkoFChYI-_UKEP-jTchKYTJUi6iqCq_OtxkAChNZ8k6EyHsEQ8EjWmZGS1yEWci5UtkQkSFgpuAR0RjHgCIqnE_nVRBgyb-8NqhaawAIDCmzOUVkkAQQrMETx9WSonBlQlK0zvtmOJeivm0IvXPBmMagB4Hp_Zj2--m4n97d5iWOhz0hqVEXXLsdbGMMepGqMVVFBhSOCOBDU2pSRGEpS95cntWlGm8FEA0-enSx9RZZqyohVqlKaCxVEWZOiZEQEFS1ipYqlRXBlCop110qLGqNRUQRLlWWzKVKFWXRuJSqagwZgt7bmCqLOEfBOmuQmZVVFLLIWCSxHpacBIpAVRjndIKQgmiuEpmXWIHMlLICGCCPbECL6sLauha0WoIYmQujIe_MxdA2oJ89u3l2uXIkuei7_XjRd5tgg7GZuaSqAsaRqHrnnXdxjkuqd9P05GzVeDsec-j9qvPWmNZZ4w2LzEudit7u0_tDBEsW6e6YjlNRBPR-N-evbncZyFjot8PbL-46xcMS7w7Tm93sDG6HFoWnY9qNo1Eh4wZrH51t1t4KwrHKbncg47quNcZ2jlpnPvvkEYu-eTg-OVsda314OBLSHNM0RbLGWTPOERV869s-VOFHl0NVub2bYxIx8Ohqm3Mtubx_GHf7SQ00rZfKXNgas-56yVpmDd6uu46Xsl21nbXGYJ0nEbk42zbeboeBSFWUqzBXYcksD7sphACsIuJ8AEBhQUQDaAy13ve9RwBV9I1DgMaaUkVYuLIiqKh1LsVURad5UYCqWgSUSBRqrd66mDIZW0o5CWFyqc45Mmac5iVXQFO5CiKrliwtmSnlBDzH1HVNZo4phsaz6hITKKYiuXIq9eTXa9uWVRCRuc7znGIia1mErIk5T3Ns-9Y6Oy2RFFfblaJOu4OxaAhU0SD5xosiIoSmqSLG-7ZruOQ4J9u7pg3IUlJsum6exm695lyI1HnHNYOaphu-_d1v__pv_Jq18ovPf_HHf_Sv__Yv_-rzv_sFkXn_zduf_uU3w9B__PLx9mLb3Qw_-fz1T__2Z3Has_JP_uorwfBf_h_-F3dfvvr882-avvvwOx-1Iaz6vqh-88WrLz7_Giydn6-J1AC-vTv8w9_91h_-8Y_fvbl7_PTqsD--ffPu0YvL8X4Mfbg8uyCi9-_fdX2PKs-fPC1LtkRnm6ExNue47gdHYAkfX571jtJxiakSmpRrCM44qrlcbFdcRRCmJfkuuGDnJRFaQTjujk0XQuudwfkYucKv_t4PjH_ymfG25ByX2XcDgbrgOBVy1ocmjoe0P_qmqWWyxlcWa02_3aZp6c42isKFiYBTJWeADIiKpFyWmpJ1Dq0l34X1MB2ONdfz88vpsICxCtIOa1TsNhesNay6NC-r81alCiAa0zY-p6TCpZbxMGFwhNg2Iae6zPPFektEw6qvXA8PD2c3m_Hu0K7WImW12YTeTw97rNz1rQinec4x5pwPuz0pHPYTIYry7m7nLDRdc397ROeWWO7vD-P-AACAUlJikVyLAqdxIZDDYcyliqogHvezsZRiLDlP-wkCVWIuXEtRwJzrpgspF4PcNsEY44yAlOOShWvftdCCLEuJC5R8d7-fl_rppy_evL19_e615Bi68HC3q7V4S6VAd7lZ9mO3tn3ndre7xre7_UQAbRMe7h9qLtMY11eb-TCBVCI93k-CxAhpmoNzFihXHcexXXWN92l_AEssXGPyztVSRCHFbJ1DkWZYL-MIrMaGlKKKGN_8EogFSEjKogKARrg6606hqRxlNWxKziZYEVVlEgUAEVzmTMEbwGWZY0rMUnLiyrnUynx6KrvgHvbjsizO-bvbnWmCKnuDcyqVpVRJqRhDKWey9vQzFFNdd61vu_vDUVmf35xzlff3x0Os2tgsMC4lg1SVXEQFlpi-efsgpGJ0qnJY8kPhsQhZJYM5s0FVoByzcaSg02EmQlRGa8Ag16qZHZkivFmtTr0oRDQELjjjyBD5xiOC1Nr23TzPoaGLIVwEd7MaGkfjePj5l2_GGNFgLsKZFdBY-uO_-Hzo26XIcYpKtN9PJ7Vw2zaosmq98X6aYi1FGWIu_fmQS2EFFa5S53F2ja-1GtWicopjLktqnGdhZrbGSKlQ2VtnHCFRnLnm2nYtKgMLoaaUEciQOSHGe--JTOZSWF3XzDF666xKnAopX3SNosklIxgFEZXGkkMig4TGG7RkrA8111qqM5SXpMo3F6uLs611xpJFlGXJ3tm05GdPL30IVWG77o2SICpLVTBkdvtRCeKSSi3eeuGCUF9ebblqHBcDBolyKjHVGNNm6KzBaUmr1aDIOcs0Ls6hb_2yZDVgnTFkWBSJ5sKEZMOJbAveO29RQKyzymwMNd4agqlkUGi9S7kSS9f4lbVLrqKsqoZsZ91ciqrmWlpnL_o25tw0NjEFMqsuBGc90noI1mAfaGicN6giiFC5gKjz1pJxxhpjQaEqlMKlylJhXOYlJbKmcgUD1pIUvbt7WPfh17_38sXFWWt9jPFHP_3y__IH__r__d__2Y9--vXL9cVn3_mkabonT6_VyMtnj1jx9e20TOXp47P1qr3aDk8fXVBhFamK37y-tcBVITi3O8yX23bdtl1jQSQ499Wrd-_3x8N-fvPqfeMDonzw7NFhN_7sy1e5SOjDr33ro3fv3nmCl8-u5nH64NFlY-2bN--j4MJ4HKMA5lzRets4JBunYqzxPhjfGOfPri-n41RqbZuu5ERKZJqL509KouHqPJytpIh1HoQUnQgYS4hGKpjWA7MxVmslAGY2xhhruDIAuuBCY9NxtCEgIgIKMxIpAKE5FQxOJW1LBpQIKHS2ThFUDBkAQEvWWgAFVc4FQEpOgEiuQdchIiE0q8CFvbe28aSa0qJ52b95dbx_KDEF7_qrM2dN6AZqLIB1Q7uMU7_uDVHTuX5o80O-eH5dUw0htJth6G2J-eXNuVEQkpQrs7CIiBSWKnLi_qRcczkNYYHIpFwBEQARoRSpIinXqUqqUgQKS6niLCkDEVlEIioViMhbg4CWJCYRxKKSRI5LzVkKgwAKUCp1XtK0ZEQgwLzwMnPOaixZZxDRGEMMdUqWTAFoG9s5tAjMrArWm67xV73_9Gb97evtZecI5H63zPN0dda2ztwdpmkuomAsta0TVQRAwpSSKnhvr1ets6YUJWMsofeWiyTEw1x-8eZwu0-pltCFEPBs8CnzFJNr7eOb9vOv97vddFiSiklTlpk51cuLMBZ9_e7wyYvzTz64Eama-KztPn588fi8f7pZnQ1dnPLtEndLHuPifEBRVew8nW9XTpFTOUzp0c12TnJ7d7zYruY5Filt255o99NSm9BMcZmmCGge9stut1SQzrkQjAGcp5xjaQNthjZ4a8lLFmcMgrEGXQhGdbXq53n-4MV1qbzbT_2qPV-vLs83IsWiBdTKHHOB0yeZMEdugiUiFjFkFQAJUZQMWWeCt433yxxFgRBRQYpMMSmQqACCiAIQg5LBXKuqAIICVVVV4MK1iiow6gk6VysXFmtdyklRU6lIJpasgCmV01rqMKVa-YT0BWMyV1WMuZChwoIIiaWyqKp1lqs437DwdJxERFVcCGlJofesetxPlzfnXLhGzrkQqKLmaQnB1pzKlK1zxpBwBQXjXMlsjF1fb-JhVBFV9U1AxVqLgqaYjLdtG-I8W4uGEJvwu7__W9_6zrcvnpz9-Z_8xU__7u_G42Gc482jpxcX282qhVzPLle__ZufvNvt3UX3L_-___7P_-gvSilD2719e1hdbX_1v_ytv_r__Pu3t7snLx799j_9T__63_7Fb_7qZ-fbzR_8y38775es8J_9499883r37Pq8bcL1o9Wf_bufjMt8dXV5POzzEl9-_NQ637ftBx8-Hw-Hn_7dLz755EMyvg3u_GzbeHN1cca1fP7VV1dXlyUthuDyfLtqbONt13a1MgAWlTa4-8N8uRnqyVCvSMYyizKklJHwfn-4O87rzreNB8Wiul41PO6Nf_ZrfmhCt8LW8hQRTg9zC6yVq28DEZGy1irM_Xa7jFPTdqycl4WEQIAAjXV6KgzVqsxkwRGmwwicS2U4aTjjvMxT0zelsPNtWkZrXC7RhmCMvXh6sUwxx-RCl-YqLNaHsO6bIaAopEgAQOyte_9-3zrjvCGDXdPWKrff3G6uzuI0qkipvCyRWYaLCylskdoupBjH-9kZklo6H8bDoeYUPCWuKoiGLeo87UIw7dAvhwPnWlm6pjXB7veHpmu1FnREIJLzw93BN6ZMc7PuMVdNvMypHrNzzihaF0hqiotzDp2Nx5ELB4P7h-k73__gcHevKbfoSMv52er2zX3bBQb58d_-7Ld-87umwu_83mcP7w8P9wcpioDb8_Xg6fWPvyGy5-fnS1wsGtDiEd5__f7xB4-Cc1w5zbMLYZzi2flWVOZp6fq2jJMWrQBotO37N198vV6dEaiC1pwAwAISKgg2qy60fUoRSJ2xtRYCBVBV0ZpUgQihioIYSwbAOEMKhlBYfOO5ZIXKKhVAFUi15tq2fSlLrWydhRN0EQBRQnAlJ0JMS8mVkVBJueoUo7Hggp3GBUC2Z9tpmshBipmZQ3DooKgYiwENCDR9E0sK3g1ts-09ks0KI8sUeclchA8x75bFemOMBUSyJivPXN_tjkvNIfhaGA0hWQX0PhDIqm1O-8_QGIPAiXOpCAhVuUot3FoLwADgLRGBAVUWq-icI1Ct2jrrERvr0z7-8JOrZxdnZ2edAUGBrmv6EBBpnPN0WFjxfr9cXmx2x1RVa5VpyX_9sy8RTbvu3tzv55y9s1Xx-WWzO6SY864wq8xLud-NZOCkaTvsj2RcjWk-LsaSshiyKcYuNKkUg4QAIJLmaFwwFoULGSwxOe-4VkOOQBEQFFJOy1yqiusDuQBcpZR5WQRoWA993xhjhiF4Z1PSzoMjer2rHz9Zna1CmiMCW8CS0tCGTdcEZ60xfeOtddcXq3kphuis98poDD263ty_u3fAioazDH0roqjorbUAWOuSChcOTcOiRSTHZJ1rfauE7dA_zLEClxOvEXFO8eJy2_RdqcU7H6zNicnSPKf7caqCacku-Na6vm37JgBhycJSyZhU6n5cmuDiEi2ZcVraNqDRR5sVg5Zcg0WLRCIIMLTeEAZr45JQIThDqqvGOUJlHQZHzvQe22A6BFVZdb5z1hkYGtdaMoiWCBAAGAER8VTwMIhIgAiiQNZVllJqFu6H5rifWKpHfH69-v6Lx9999ngD_g__xx_93_-7f_7P_8cfvX5_fHp5-d1vvfj2Ry_2dYlzUuS-aaTAd7_99O3t_OV--a3vPru6GLZD-_TyfAiOWNsu_OzLd0-fXijZVdd1XbPufeMsIcQ5nQ39fFyq0sM0GaK2D-NhfnR9Eay5PxyP0-yaLo3HmIsj0xJ0rV81zaYLwduY8ijmMBUGRcXD7lgJwfiTkxGNkvNLLmCsqrTr1jtXSmm6YXVzDmoArA0hV4WERNR2vSqRcaELCrCMiYKDImTQGltLJgIt7JtGcipL8l0rtVjrRVRYyBDqLyMxACdZFgBZNAbRGNuxZmDlolwrqiiLGDXOo6IC5crWGeZqOl-z2D6wlpqP1oe8lHa7VUBOzKLeeQLjjSNFzbHmOj9MiHaZj8JAVIdVv9yPm1UrCgbRAg7bbhknzVUQ0Lu-a9Dypy-vOUsFQEsCWKuIwhIzIBaWXISIkggZKicaI1FVLcxFmFWT8sJ1qlwUDSAAKYGKEJpcypxrPgVDFYCogM6Zl8yHOdeqS66VFRFZNS0150pEq3WTc3EWljkrCDoqtRoLFcSeXpnENlYRvXPMYoFUtDBv-rAO9uVF970nF4-6MLReKs-5PIxL1zYuuDe3y5IZDRokIHCGrDMpVgS43Y0K0ATjLS1JEld1lKrsxnx_iEut45Scx6vrHoxZUqIq41J_9uX7ivr8evsXP7l7e394u6TdnIOlR-cd1DQM7bDytw95u2rOt-3bb-6XYz7frDpr2uB6b8nYifV-XlggiQiDiLy4OQ_e5prHJXKp5GnoW2fN-90xWMqljjFdXG5ARYqM4xK8m6Z56NpSC1cutdpgQEkJ45JzLHMs3cqFtt_tkreWS3XOzHPcbPrVEAzXoWsutn3TeJQavN2s2u22MwDWkLKwKGstlWMqwTlmkaynID5LXQ99KqVpXMzJN9Ya66whhGlJ1hlrjTWWiFKpLAIIJ5ad9ZYMikCckyIxS0xFFBFIQac5WWNz5XlcfAhVWBENuWWZjCVDptZaRKuCCNcqiFAyMzOSXVJy3i1zUqRSq7WmqEhlPQXVRISFVUMTjvu9KlY5TUvdCZ-WUwpNo4wKkOYIKs6H6XhUlr7rjvcPdak-eGuNiFjvkdA6B2BC05yMq2jQGqslpyUZa1mRjCKASHZNd_Pi6T_4-7-7ajut9dXnX_31n_0lcz272M5ztja8f3v48IPHS4Vf_4e_9uTJ9et4-Jv_8OMf_fUv9rcP1piXP_ikv1y9e7d7_PTy9m--edgdrm-uP_u1H7z66c9_6_vf-_DJ5U-_-OI__OlPtper1XX_xed3ZNzFxebVN-_ev93vD2NwdjzsocrxOG_OV_Oczzeb6Xiwxj66vkQLu93dZrXaboaz9Qqk5JhR8dmjy2HVX5-vz1d9jql1PnhDhlLKoLoZur7xFrUqd30DRHHJIQQgMeSJzLKU6-uzxvmz7coPrSfTWArWGnrybUDhWh1Z5y3nVFhrqaHrckzGOeuCbbqalzjNxllVVEJjMHRDyjm0LRoCEhdCjdz2K62ZCwMSAFlnRGVZsm_99uYJChvjUoopTb5rDeky57zkxlljbOi7CthvttYjKlpvQnBxzO4k2kwlzgunNASMcemG4bBEFkZBFxwR3t0-hNYDaF7mprXK1ZIIF2UwPjhn-uuLOMd5mmqpaM1hvwdBQa0pg3AtWmJRkW7ovbfOepUy7iZr3e3r1-vtxhAFH5xzoXHeUZE6j4sz2PRNP4SwboMBdGa_v6-1uMaVVJEzcnny4UUQAeU8Js153h_64J4_vnr-4dXXX74f1k2JCxGthv7V17eW5atXbwrXZy8_aEMTlP7up191Xdg8PX_7-RtAYsm1lNV6tdSEaPKSiawxCIgqPB6XNGXgPD3cWWNzSayCpIbAO8zL3HiXUz4JNKFkybGUCgjktKZIatAQiLCwlOicExZhJQsIyLkgAJJBAzWmGjMiYcA8LZwzEJTMCgIqRFCWmYxXFSkVkWopXFOJGUTImrwsXIuxRATLsiCqM66W7Jw3RCmyYt1crHa7MZW6xBSX5fzsTBSAgYzJpez3E1oLCmlJm6E7LjEBPyzLfs5TYbCmGmUgFmURAvDeg7NFgAyKQknFoCnMZE5w9hqcK7UawAKwpGq8BQE0TkFzyqE1bR8Q1SCthrZWRsCuCYaM89Y52zgbnLm83G7Oetf5f_LDFx892lyc9cq1b5y1p7aiBaTEokBKVsnc76d3u_2r28NX795X5_7m61eolC09TIsI7ubESGMBr5pV98f57hAPSyoM07iQMaWyb9rd7tD3LRqcY6ysSIYMFa4AWlkqs_M-Z67MLriSi28cqJCCVlZVg8CVV6u-cgVCQVrG2Hd2u2nSUons-8NYM3MtzqIh8IYuG382hOfrtg9m1fpSdLVuSyzrdZtyHfejb0PXeuNsqvWj5xe_9fHjxlqDdP_2Xcz54mIDXK6H5vsfPf-v_tFvjFNecmQBBRTEvm3GXGzwFeGYUxXZHWaL9s3duMRivF2W6LxT1t3D0Xs_zbHvO0MGVBTgMM7W2L5rhGU9dGgcc06lksHKfIzVWTKC16teyCyxgqpVqYWLsHXGN2GKizV-Til4i6iO0BtIc3GeGkuppmFovXcEJ2-hioh39kQ8syIX510AyjH3bfCERGBVWmcdGW-sAosoyy8V9aDqrQVAIlLAk9w1pYzGHKZYWYLFF48vPnlyte7WuvB__cd_8n_753-2208Xl4_-wW__qnfd9nyYEsfM37w63Dy-3A6b7ar73reeXl2d_-LAF-fNR08vXj67GRp_thpIVEGFEVGtd967cZlvztaXQ_f2Ye8cDo3vu6CKb28fhovtq3cPm_VmnKfrq82rt3eHabq5evT162--_b2PHdJ-9_Di0aNxGr_36TMp2ng7LXkmc4yiqFqFGVJmsP7i0WXJRQGavrXWA6ExNo4JAEWEjK-svu361SAq6-1mWDUiBGRc27IIIFFw6CwQcq22sWWJQAAn4kdJhGBDKDmpiGQOXacslRlBkVBVtCoAgCoZU1jAUBVGRGZRA6CMhoz3pYghS66pXEtlRBJAAtMOK80sqqDWNS0aC6JuaBVUSfKcm6GVqqHrDKEUDqtGSpaSuaQ8x5KSct093NbCS06H-1EtUtczp1gRyTRdl2u-2V5YREQAoppZEQsLArGCisYqCFBEO-eLCCDVyqc0RYySBYWBAY2arbOiMMVURJaiYyxqTFGoqoCQhafMucphKcxABIyorCE4bwkAEDQ0xns6HhYiWmKpzEKooFWrIYxLtpYEUAWsJWcNkrJw01oKzhj30dXq08v-w7PVqnHOUEl1P6cx5hCcH5plFhY2BgSg9RZYnHPC1TufmVmVEHwIifX9Md3uEyrMkWPM27OusKJF9P79bn44zFV0ZP3JV7dPH21ePL95_358_3Ck4IRxbfVbLy5vj8thzKPqL77eXZ0Pl-vOqO0CPbla98GIsXPhn7w9vLlfvtntHnbp5rzfrLsPN92mG5aYliVWURQFQut8LfLq9kBSt-u1aH3-5MKRxCxfvb5PwiLchnBcoiqJQUASwZyyI9xsHApebNz5ynOqJ7jw2eCvN-352TrXioJd31lj7vYHRyamtGpbAycsLKcix2mxzpYsKkpkhuBFhBAZAPEEwFJr7e44eWu70BgCRBJQFrVEPvjTVaFWtvZUlDen7wgZKkXg9MbDLwviyhRzIrIqkEpquhboBPfHuCzGWiBDimRs4ppyEdUTlLyKMovxhkEVUFRVcYm5VgEiY21KdVkyoipgXBJzFcVlnpwxJdeSS9d2x_1xtR6WKVrrq7ABJetqLXlJTesOu51UXW1XYdPF_WyIVIV8A4jW-KYL4-5AZETYGDseH7r1RkHIOeBiLdWi_5v_3X--3gw__suf3L15d__-ftxNMZXtxdlv_87v3d9Pq763c7x-evn93_jeq_f39w-7f_uv_1oYaimrq_Pd3eE48f2bXRtcM6xev367ubz-4W99f3p_9-Tq6smjyyjp__Hf_mHvrbE2RkaEm_Ph3fvdUtM0JVTu-2FJZX3W9Zthsx6uzi8ODw-x1KZxm7PznNN2vW6D36yHNMW73f7y4oy8_eDpDdY6NI64dsF574N3olqVfeNFBAWddycm4GFahs7lVJwxPjhWefT4XJkvtn2Mpaa8Phtab9OSzOpbvxYrzLvFt7Zp2-5s40KTq6qIMeSCzzHyEk0IIFpjcm3T9mvmosxdt8p5URGpXJcIgMaBbZwi4KmXlVlL9p2LxzHNk1SupZgmMOc8ZeHSdKuu9QDigpvGo_GNVA1NQwTOuZgiMyzzAkV8txKorgmH-_1wuSqSRSku0XonUlGxG1xZCoJgqTXrtDt677lKrjyPc980y8MDSNVa8zi1nedSxoedMaZydtY1jZOSVAlIS6615CUmG4hrtdaBAzR62B2Zi3WWvLVkQtPmVJ0ztVQtfKr-KGHaZWs1WDMfxjSl3_yt78X9CFxu37zdnA21cLftLi4ufvbX3zx-MvzwH37_7ev91UU375d5XKa0fO9bL7-8vS8xjru9bwKKfPzDj6e7EST2Q7N7v0MA04TlGGvNaVrmZd5ebA0aJOLKy7hDEBSoKbtglsPU9R2zoGA6TtajQYo1Q61lnMkZMsglc6wnrbJrOrUAtQBnVJFaVQFOzTlQMlSkgKqgqhRFrJU5JxXGxooAWStL0rhYY3JOSEZREaHWAiooRTnneYrjElZNydlZi0g5RmPIO7fM0TeNJc0xM8Mcc0kRCIT5sD8qS7PqK3BJHHMy__FJ6Y1hrt-8u68Gx8zFUKqcWMRYVlUpbetVTDpJZEvOXGrhVPLVxdk8lWBNER68W6YZEffTDNYw8yJ1qtE713YdAXhyCmrJBmubpkHQxhKgnq0G5KqSSqm299_59On3njyyyn_39iHO_O5hBNEx8nGq85xIoSgo4sOYbvfj7TiGthFQcuZhPzcufLEcvtktgfyScprjtKT9bvzqfnx7nFdnq4e5jqlUVbRmjvEE6d9u1sfjKKrkfGaJSzREoiIqy5zJEAKICDqqufi2y3MCBW-I0CiAcAWAymwaW3IBrvE4oSKoMd4QYizFGGHAyvrV7YjBqDHt4Is1q75VAxfDQIjrNszL8uzy_OJ8ve39eR9SiR89uULQJfLzx49WTeuM7Rq_OWt_5aMX1-frH3zy4RyX5xerH3_57nYcG-9SqYfjiT-wgGqsxSkmEQRpG1KkcUpkrFSxDtZ9Py1L24WH-8kaEDA3XYsuqOjDODIrG_Te11TWq6HW2nh7Aik4xJjEElqHbetFUVEa7y2iNdQYV3PqrDGoltABnp0168ZfX60bBKvGWUuinoyCGGMaQ5Z0u-pyLr23KnDe2iF4Qa3MbTCtpdZaQlBQACEyikpAhox3Vk6taICT9GeJkax_OI6ppqFrHp-vW2OnKf83f_An_-YnPwWw2_Xwe3__sxRzsDTPpW3DN6_2juD8rHl0s3580X32wc23X5z_7CfvVmerq3W3MTZO86ZpNkMLot47rmIHf9hPq3VPKmvvg3V_d7e7HPpu6Eoufdu920_7ZfKhyaVsN6uUincBjX399u2nn7y8fbh_9vhms-7b1q76cLZaeWuJ6GE3HxmnrDmlOsXCOqeK1npjjEMXPABYZ5GM8y5LZlBnHBhnnHdt0_Q9g7HOrs63JgTTeHVkrTUuxLmiM8bZmtU3TlQIoKZK1qkUrtW0DQCWnNCQKCCS9U1N2XpP3gkrAZAxokCWvPcAmuJiCF1wNZVfHn_odAkDBLGBUDW0oeYiKk3vyRuplawJrau52OBjzL4NmdlYRERBJeeVyLWdsPyyctkERLBo236oUkUhHhfjrBQx_coYAwatQWtwcKHzXoS18smoWlkYFAjBIgDkzIaQWUuptWqqlUVzEUYgotNtQZlzqVOpFRENVVZVzCwnapy1KAIiqgDOEZERQRQ9wTrnJTmLXWMb1LtdrLkahL4PrTOk4AA8UdeFFHNjyCq2znkA5OqtaYP3nj653vzK4_XLTXve-taQGJhTPcY05TrFCgDzwnOMcy6KEGv21jpruTJae_z_0fSfTbZlSXom5u5LbnFU6Hvzps7S1V0tgQbRAGbAAWlj_I_8CSSHHKMNDAODARgYgemG6p4GulpkZWXmVXEj4qitlnB3fojC53PsfNlmZ_t61-vPMy2MiJZ8DIdheTwtQ8nRWyDKpTaNV9DjaQreHYbl3cMjEQRveUpf3F02zuwfz8elAFEXQ7TU-HBK5d1-ubjsg8jnrzbr6ECUSJ0xlmBi_eb9YUl1s267rtn28Wrd1Fzu74_7JWXludTn_Yfdqp9TKYWXed52zXrd5VQMoDf45n4wSLbxV-vGWPvm8ZxZKwIYWEoteUFnzilVCMcxGxdypadTJuP2x5msO-f63f1D3_RF69PxOKe02W6Uy83N1ltTalUAtCZlFlVLRqqGEFRqZUEA5z1XJQPRP7eA1DprjZGqBomZS2VUfJZKIGLlIiICoIAsrKyqUJhTKgqqqqmKqBrCKkzGlFxVlQypAiCdh_nZSaoAhtycUi61FF1yBlVWMIamOangYRya6I-npWvCvCwKWEoBRC61lCoACmCsQRApKlVSWvr1hrmG4Ms8i0i3WtUqy5K996XmlHJaFmdNmiZEIyKx6Q4fPvgQRYtxnpFi18fg52WKsbWt11yUOcRmGab1xVql5ly328u_8w__-Fd_-_Y__qs_nU-Hz774hGv-8PA0l_r7f_h3_-qvv64p_4P_y9_5_CdfCNGxnP7tP_v3h6cDC5aqF9frtEgWXfV9jP729m6apn67_fHv_OTrv_r6d376g49urgrp__T__hfOutXFdnXRplq6vvfeCsD5NA3DCIACvN1urfHG2FXfWzLzPKzabr3dLvN4ub0Izl5utyhsDa76tvGua8LFurOqKtmIrLoWQEVVFJoQBFRqBTKJKyKdp4XAeEML11SEARgoLVVYQaQUTlOxhAZgGZNpP_659W69bpZpLLkQGkvBOM8lG-_m8-yDcyHWJXEpIcZlGBCESykpOWNRAA2Vmqy1zltlEREg42PMS7bekiNhASnKFZWLcF4m6xpQQZWUFgSYx3TxYodox9N5tdnUpXRNM4-z71eZ2TXerUOZx7ykkrIxbjoNZRjTMtWSzw9P3XbLnEpiANjsLvx6y6Jx3ddlAWe989ZQjL5KLZnbdRsaX4u0q5UgS8oqCVI6Pe5taNJ0Ph5OPrrhOHjnAEQJEQVUOVeLCopgJIsGj3UeCaFZt0SQlRUpNC4obK5XqMUFE7zlPL399sMPfvDZ1Wd3D28-HA_T_-1__AM-Tau-UahPD1M6p1ef3zqmN9_ev_jkltX-7Te_AtDT4dg2UaH4Jj69fm-8b7uoBOPxvLu5ZGKtDFxLTmTo8PAU2j5zttYASp4TIJbhQ03FRTdPMyGs1luuaTid0QawUNNiSUEgD8mHaGNQABbWUqwPz5UEqTXGToWJEK2xztVSrLdcKgJpZSBEFVJAEc5MxjFXRADSPJ5dDBVMWUbnPRDnaSJjUVBLIoen8xkARHXTrVhxnhJZI4qEYK1xMYhiTgkdFSnEyFCr6jIXETFIlkhVC2jrA3JVgO_e703rC6IiiQEByLUCwmkurOq9BdU-WDQ0LAsbAGuGubZNOA1nQmCBm64v_w1l4IxtY7CGpIIWaRsDljyS82QRYyBLYA28uNquG7fp2l3fff7Z3cc3u5Z1meYzw6ptweiqscOU1GB04TAN__c_-9ddXT3O81hlTlmsHeflvJTnN42g-fjVbW-VFMckPrpF6rvHw2maT6l8t1-GOaFDFlUAVZjOc-NtqdVbiwrj8nweFgEMwbOopWewut5eXQ3DFGNDTrXUNM8sLMLGEaCCYimioqwSgkNAJOBcl8x3V2tA2p-mED0BrFY-pZTm_HZ_7ly42TXOmGDxdrNeR3-z6ber7tX19vZm23nXN_5m3V2su2CN8_awTJ9_evvJi92n15fXq_bLu21jTYPmlPKPP37V982SuelCbBuWKpWdMcO0eLJTYRAUwVJZlee0pFKmSfyzPIwsWhxSqVLnKkteqqr3YZECSsuy9G0otVpnFtEKUKogqY9knHGGmPXV9bqyBmeM9dMwbrfNeJ6tR2YupX78YosKrbPI0gS_buKUFiQgkD7EvCQlLSzRWuW66ptoqSDkUpyldetba7whQhQpzKKgwmKsJ0TvrLBaIkBEwFJLrnVhzqxVqwivoxvH5T__11_9yz_5y67v2mZ1dXXhnJtPBZay2gViGPPCRreNv7jZwHn4_Z99sglxGPKSxBmVknddQwi32zWKiNTK7Jy9bLyAaQyB6i7EQ0qr1kdLZEwTwjilqspCwzhdbNYp53kp3z3c391ctl0ruXzz63cv7i7ysqz79nK77qP3zgjX03A-ZT6MOedyPE1x1b59t2-b4JwBBDBExtZahcUGowK1SFh1JnjXBUNYRY2qi6GA-iZUwpIFyDBDu2lLqc7Y0Md5XMhZqQLWEQLXIgxgjPURkcqcjfWZBYBMGxWIgQAQkFRRDAEZROTKRIQi9JxZWgvPqakh4z2wgoIwSK3GO7RGFAGMADZddzqcnXPkPVThWgjJEoGCMQaIQKUWRgRg6C82LFzn4qxpYleLWEvGe-JknWMB530tue27GA2h3W3DkqoAPEdXLFoFCKlkFgZCqgKlcmbNAkuRqgSAlQVQC8uUSmFYAFKCqiospQigkgFriUBT4mUpDKAsqFhrBYQ2gDEOQZ-vtIyCCkzL0kbvjena0ARnRNpon7LeNe7zT3dr727W7dW66aJvPHx6Ff_g1dVX17tP2mCNegSDmBSGKZ9LLayFa3D-NIxzzqXyaVnarmHhGHzoHCsqQgUQUfVmSXVaWJCkcNs2h-Ow7gORfX84BBdO0-KJtpv20-vL1tHLi1VjCI1Bg98fTqtNN5T6eJxmhXOSH7243DRx08bGWiAkBUaTcr0_pYfDGINfr7qc8lxqTrmwCNI4FyQUpMN-BKJlyVLrvCzR2VIqK_Sd363bddvkwtPMXeujs6q4FHHWeG_FyP5x3B-mkXkpxVi_pCUnQSIuuel8bE0Itl_HvJSrzfrxcLjYbfumab23hjwCiSau87iIQs6CIE0XuVZCQhACsIaMtcOUQjR94wkBABUVFEAhhjBOo7HGEXlvVLTUKiIpZSTzvP2rooBqDM4pOWtzqQyIxlbRWkVVAdV5ZAFCrKylVGMNWgtgKhcRBcR5znNJhKSqrYtTqaqqiMM0N6EhMsu8kPGiwpW5SqkMAISEhoZhNGQLF5Hqm2aZlr5rS-FpnJu2FxFRLSnVsiiooknTTISiiqBNv6o5c0k-Ot9GZWlWa-d8LUsTG0IruXCpzIVYTfBkVIt43_72H_yet_AXf_oXZTqtt-vXbx7_3v_4T77-m29--nu_-I9_9ssffnbzo9_-0TANf_3N61__7Tff_uVb5xxYv77cfvmTL998-4YBMDjr3Xqzq1xO-_EHP_x8-PD43_-d39l0DUX4F__qP5zHKTZhnkpNLIqgGoN_evswHA8xuJ_-4DMWHc6n6N12u9msVt9--601drPdTMMQQ3DGbFZd3_eHxwcfQvDuWc0RnYnWnE7Dq5urKjXngoillHGcnPWIYJx9zgumpRhA7x0LDnNpvMulxmhJdZqXrm27Lk5jJktx1RjcvqpSu7j2XZBlmo6n83CybevIubYlI8pScxUhMjbPM1hcrVbr1SrNo5TSbzagyEg55xC9BbssRUAVIMQGBURVChvjdH4UCRYJg9FSQMlFb6wjLbXU4_5oglPRPE5N11aeV7vLUsWHiBXG4wFNaFftcp6MpfWun06TiXa1apclGUIFDT5yyTknLsv6bh2CoehC4-d5iaFhERbd3l3ZLqRzVtVpGL2z_Wa17Md23Ycu5PGcDkvsGpVa5uQslWmahuniruOlEmjXtFpLzuKQlvNYSzU-pmEa51GKTE-njsgizMMYfXj88OCMW8azc7puuvs3D2jIQL1_8ziO6asvXgjr3Yur88MjGlOLxCb84__hd75__bA_DD_46Y_TlH__7_3Oq09elJzffvP-8nb98OHD13_55tMfffLu-w-f_-SnT49PIdqvfv7l8f7YNk0q6eLmMi0TAR5ORyw1tqvQN7UWYNaqVdn5aJ0fz6e27cswcqmWKERXS7YWkaxyTcPknAdBAJSS53FomkhIzKLCiCC1oBCIIqp1ARCAVau4JtrgnPfMdT6OoW1yzgpsCOpSmm4nZczjTFKZGRXai9VyOmktw3kAY6z3NWdQkFqrKFkLqO1qzVxyKuN4VLJpSEA4z2W96QAJEZwNgNw6zwxs6LyUWXniyoRiKStXliRlzMuUlhB9KcWitdafz5Og5MpTLp99-urN2_vTaaIQ0pKCd8N5SlzJWLLOEokKgUEEZQ4u3FzubGO329XVZqUI0ZMLpu2aXdf0zjQO-uibaA3y4TS_eThn1YW1lPp2P_XVj6meS_363YMGuz8OGVSJSqltCNEgiKYkqOqCiU2omZea9-PIQKx4nhKDFhYAkCpl0coVERDEG1tYc-YmOGXd7_fOmb5dL9NMCKmmGJo0zd43lsiSzuNiDGmtAMY4YwyiIxCspbRtq5VLraz87f1j2zdtF5clZa45i4KOS9qt26fDCADnofgmVAJGbWOjUsmYPrgYYxPjbtuvmjblagy1MaS8tI66JggLIVqiJHw4jfv9o3ema1oATqmkRbyzaUmePIMqikNbuSIqMztLbTCipTAvpS6pfPbxxeVlWxLcPz6J6pxLqRXJSVIuOp3nNsQq4A313oEo57rd9WVK3hsUGYfZO-MRHcDNdtU3_pMXFyAYjO0tERee8_W6vVy1bXQotY02OtsYsz9P4G1n7aurbes8AZyH8zBOtWr0LnrqnDWglgyrCDMZC4jeBalCBEgoVZAQiVhEVJJKVp2Wgobe3z86a_7rX3-7P48f_-gj2_i__Mtvb24vnx4ObfSrrts1vVqZq8YQVutw1cfdun314oIEnTWv3z81rYtNbIMLnvrGcSoscJ6WJrpcuOacUmp8SCxLLaCm5BwMNTHMc57HfDif2q4b53m3WRkkBQohqLBx_vZ6YxA8UXCm92bdhGehT87l_XkeZh5SmisPqZqIoCZ0UbMyKKoGZ_umGU-TD86HEJtYs4BgSqVtQxObmrjd9GQhOi-qBoic296tAd35PPo2sigroCHjQq1MiNZ5NDanYpwz1iGBdb6yoAoiAWrNxcboNitj_G-uvHJ2RMY7lYqGJFciAwz8fOH5bP8FBFUyNmchY5FIMiNScIYVALBUJlBrPNfCPIe4RkvCjMZYQyWlCgrVgDyDzZkaVINhtQIGF4P3gYRDdGTBeytFry-bKak3JECApIgCyMyFAQCtIrA8LbmwCCAjiEIutVRdimSWXHkpNRVm0FRq14TnoohUyJUBNBVJVSzSkqsCOmdDoM47VfIBr1dtY2wt2gc7W_1i173c9XddeLmJLzfty7V7Ge0nF70Vudt2l12z7cKLXX-77Xdd50MI1rIqKjtrsvKQy35aRPA0LNbRnPJcM4sc5gkIvfN14VUbo7U5c646zLmJDo19ejxNiQ_HoV81OaV1FxVZQd8vU2vQIF32YR1DbwwBODIeFC19_eHouu7dfhqn3AR_t-1-8NHlZbRzLp7MaZyzaDYwi-zPCb0zPliDqVRQOgxnY9241NNp8o01xj6dTtvtqu2DsL5_PERvtn1PwXStu73o--hBNecSGy_KlfnpPM-1krPLksexIMBSkoDOiRVEFW927bZrrLMXu9U8pejM6TAIc9F6dXHhCZj5GewTo7ONmYYSvLXeGDUiwLW0fWMNRO-cddagKMhzqZ21FH7WZT4P7srivOt8FNW0ZLKGyNRSRVUVnAmqyrVWrta4XNkQobEKmnNSkcoMDFlqE_zhsACw8TanKoiALqUlzUkRpjQT2lRKcB4MHM-jkqmVRZWIlpRIAQ2O46D4LFcUUc05q2pKab1uyZtlKYBIzqxXq1pyZW77Zjyedtvd6XD2wYqCQVtzUuHxPFgbjDVEkOYJwIiCsW57dYeg4zAgQGz6ukwlF-UstaAlInBt89HLz3_6s59Ox_N__rd_6o3OZREC9PE0jxd31zd3Nz_98tX2-uL944f_9L__5_P798Npurzd3X32yf3792nJ779-IwDqXBPj9vIiLyUN-tu__cWPP__044uL3aYbxvH_-T_985xLrtL2bh7n58QcmN998w2o1lIVsIACwPXNVdPEvmtFxQd7e3N7Oj3dXl9d7y6tgTb4-Xy6vbrcrntS7oKPli43_apxzhpU8c6H6Guth8MoBKVqZV1Kdt4cD0PXR2Mo5-zD89fZOVeLLEvy3nZNYFFr8HK3MqTGbF6pVi4sAO3Nq2BpmbK1yCLC0q23iKYmNtHGdY-AzDwfT94H4ZJyZlEXe9_EWpdxmOh5uFC2znnbAgEYsNFY48htVv1LTucyFyAgIhdDrRkQ-m4lqDWVNC8xehGOq42Waq0FACAwMa4vdmmevTEiYJw3DlD4vD-17Wo8n-fzmEtar1btaouieUqWiICsdaLa9tFY2l5f7d89BUPrm3VdlqZ1D48ni9perJwLT_cfYtNcvriMbfjw_ftu5VnFB3u-PzVNX1JSrVK5CLRdlFzqlNXgRx9dgMp4HPM0XVx0nCuQG89nMFJS5VpWMSzDuN1t8jytuvCH__3vfPjV69_93R-KMf_-T__ir_76m6urzdX1zvsYSeel7O-P3_76-9vriy56yumbv339X_7TX_7BH_18PJ23F9vgzGbb3X324ld_8V-ccaBy__pd00YWBtRatFZmrihIpVpVKdU2zTyckZBzRWMAYTo8IldEMsbaGIALggJa8lfWOuddTYuLjbKKZERABCnCwmQtlwIqiKxLURUIxAKgFaQCIMVYBRAJtfI8oTVqjVXgnAQWVSERKRWYhQADkhCXDMKIThDBQGxcLkUVrTXOhjwl41AB6pSFJXbRANY8xxgq6ZJL2zktogo3mzAxn4XPJZ1zLlorQlEABGcsKyNCqQzkEIhUmsaLggtNrXUYput1TwTD6dw0cZqXzWY1Lgsg1KKlcvBuWWouJTojBMuShWGcUts2u1VnDV1t-7Kk07T81f3hKcn9mJ9Kehzy07Q8DXNFHXJ9POf9NBYEtiYxu2iAQC0MOY9LKSynaZlSWapYAxVRGUuW6y4CUmjCVHlJeb1uikKac4g-zVlRkQjVOGfneSmipbAzvpT0HEkyp8vdbprGnMpzBSXPWUV98JZgnrKzdsml79s5pdg1OZXgAxBxYTTomqAlp7Gg6mrTeevSUlIuxyHNqdxdr5ULWp9KrVU2bXAgoQmNd86ZPoZtF4J3hNI4aIN7_fbhcT9NS9mflqfzsrCgtc3WjXNpDAVr2-Cu16uW4PvjyRK169a4wMpNCNFZFjEEIDhxraXuzwuopiWNU9qf89PjQCrG0rKUwzAgqwq0K8c5-YDRO4_m85u2YZmOU7_z85T6tstl2fQt1Lprm5LTMs13V9u6zLt1b1RuL_rGoRf-_HbbRbdug7eEirXm8_lcKoOFu65vorOGci5NdHeXu20X2-i8s5iLNwaBVKWWQpaU2fsAqgqSSwJWNEaf92osFOVpnFgxCaSagSilvLu8OI0lM9y_P3Wr6D0BsPfm7m5LQsMyfXu_XzVNtHh9ud6u-947matBosYHb70no9L5gADem9N5WPetd5ZAS-EqNYamsoqiAW278P7DN9tul4uc59l5WyukZbm83FoylcUH761XQotUc9qtWkPYetfHKCD3j09VcKgwMxfQVLhIBXLzlK5vN1rVRToPC4s47633wGpDIDL9umfmftuN47y53qE3TdetG2-sSUWsoW7VWuOncd7uVlq5ZBYRBHTO2uCFqzHOxqgihlAUFcj1GyRAUMkZajWGOGUyBqN1McbQ2s0Fl4IKUioaA2TQWrBGRJ0zACAsXNh7J6USARo0AOS8jaZULilTsGXOvnMlZestkjXGxfV2XmYXvCgioYuRLOWalYuPLaByUq1qnS-1ODJSK5EBMN67mpTIPKsAplQAjaJWkSKaK1fV45ymWpWgMnKpylpFkShVLqq5Qi2aWQTBgDYx1FwsERFWUURSxFoVCZir9U4BVTVnPg5J5TelEevodhM7Tx-vO29M6yk68_yUg_MOuQlN14RgXRN8dI5ADaEzVplYdFzSLDWV-nRcUq5zYoXaNN55ux_Gcc4MMOZ0udkiwnbVeGfTlJ6GxKrTvDTbzdd_-84EX4Uvb7pN20xTUoRfvttfdu3Gu7vd6qL1zhmLMBZJLL8ezr98t_8v3z_eH-Z1cB_vdp_fbF6umlX0HqAUJiIGGKS8PQ1P53Q6pnHOpZRhWsZp3p-mcUm1KjrruxDbCCz7w0gI3tDjfmib8Op299NPb5jMaX-8vVhdr7poDYsKaFVeluqjA8XKai2cp2QsIYCQQYAY3N2mu2y7dROP57nxYZjOKHA-j110txfrV5cbUlWwc1qa4ISha5rTKQOoinAVAQnBhRgAxJAhYyqzCCiBJaPC1rpSijWehWN0RKZwNcYAaOUKgICAxgiogkTvq3AqGQCYhQwaNMG7MS0lV2ZBBFXwzolCKkwIVZVZREVAUsosbK0lY8ZxEVIBnJal1GeGsghLFclFyJo0p1xLZkUiqQxApdZUSte0BABE87B46xERBJ7JQnPKq77fXV0dj4clJRvdsuRxmobjwCJN0xDRZrM9PO69d7FtQXG1WRnEZUzBh5evPp6ncRoGkcIpN6vOBEeMn331k5u7u-nw-OH7t7lMp_0BlPrrq3a7c8b-4he_00QHHv7Nv_uz99-8NqrTVFBBrX98vzeNR4DYx3a7-vSnX9YxGzCk5o__zk-3beMJuovN199997__-V_UUk_HWUSmcShVNrcXztp8PitaVfvbv_93HJTgfd-3ZLBrm3EYl3narTeKfH15oSreompdNVGFDWIbvZTqvbnerrZ9RFBQaWNoung4jg-nOTbeBS8C3hnnLZGphStz37cpJ1AIzoLo87pgVb7ou90ullRvrrvGG0jVuJsvXdeRqHAuw5BLim0saXHBO2POw9E3Xbtak7MIWKGCiIhwzUQINXkD6A2o-tD4pj3vjy5QDH2aJqkJolfRWkFZrTNSBzQI5AmAudqwmccTGRu6VrgCgTcuz6MheHj7nhW4MiDG6C7uLvb3j816XaZEBsoy8pxW6zUhLuPQdO0yz-tVX2rO86ygzapBMs5QLeyDD9acns6IEp0pOfsQRXR7tQsOY9uEGJ8eH9rVBmrKx_P968du3e4ub6Zh4pLaTSSQmoq1pGrCyqbhjAC51lJY6hLQp7xstitrIKWkedlsemH9u__dHwxvXkdvX7y8ub6-evXx3XQ8_fDLT2uFi8utN96x_uN_9He_f_P-R199_KMvPkrjkrhOKf3wpx9_uP_w09_6UZH89vV3L64vP7x7-OrHX37_q9dXl9svv_xsnMrhcajKqNiu2nEYcsqnw3m9uyADPvjz4eyda6xZlrmwcGYiJOZaMhr0TbuMi_fWGCzDGWqty0jKNQ_ogMhba-bpTMZYY3nJAKC1oENE9N26TAMaIhYQqaJqCZFUFJjJWdtEVc3no7EWVCVloGffj7Ail0LGWm-kljovRKRVAESBKqtzJja9ABAASK2lVALrDACutpeOoCzZOYcMIGCCraU-58Qsutl251wY4ZjyfpzUwrgUMp5r9tbPy1JrVYDntaSa2SBZMsM4emuNIjOgkjEEZFjhw_64Wve1MquQoVrZOYckqcrt5XUqaVqScWEuPMylKr599zCXfH293fT2w5j-03ev51m-eX_Yj_NQaiZi0sd5eTpNhXUBGHK2Po5L8iFMS82lTstyXBYT7HleBE0VAUJvbWI2xjKCMAjilIqwWkfzNDvnAMAoplKnNL683S1ZCIEJWTkGrwA5VQQx1tfKz0AUBRAWkdI0wRgSEedcLcwMzhmDxhCRQTDAuUzDIiJNsJXhcFiaPrarYB3kms_DfByWc6rO23FaDuP0dJwyQ2E4nCYy1pLWqsNUz8P8q_t9Zg1d0zYus1iC9w-n798_LqLfHea3b5_e7c9FKDSBa2qtv7xYCauwbPq-ihDCH97dnAs3jmy0tVQk5VwRUcE03hhlh4iEHm0MHlVbH-ZliRYRpHPu6rJbt-3vfbL2sfvqdpeQuxiOx-Nutco5bfp23bqAcHexnfdPN9tVmsdtG0Xq9boN3m1XTeudgrJILTn6sFl13rtgvfcWkKRy00aDep5Gb521hKV2IcbgAJ7fvwYBjLEGiFVSWcgYaxySeZZ7iEphEUQAFUVAJCVEHMZlWGYXwtOH03bbWdR-1UxTWnmHqr_-9oGs--kXL28utlfrtTe467omeLJWEcdxts5Ea1Y-zCkxy5yLNSSiBlEJvLMW7FIql7xZt85QH3bG2Q-Ph-vrrRpKJd_e7Lrgh5RUaEkLAJ7GAWtV5U9urqyj24sNqcxzssYOU9682L55vR9PC1d9jqYUpfHeOmet8cYSUbNpSq4hxmlOTRdTyc26NwDOuqnW4CKKXl5t2hgqQ9d287jEEJQVDIFS0_ciCqLWWxBVRa4MIGS9IprnP65SXPCECMLOBWAlkJprnkcRrmVRyeRM7Hq_2qD3LnaqYBQJEUC0FjIGAdDY518sKVVR44gERJVT8c4QIKqWwt45Fflv0kAVFS5srDFowdhlWRxZZTXGkCNE0SqEpIqGLKBVR6GNdSnOu9VFy6AsIArjkFLRisqsU8ql6nkuuSCIBO9r0Vx1nnPKtfIzKhSNNYSYq7TOEqFUXQqzalUR0KpQRapiqRqtUa1TZmupDy5G1wTbRSuqIkAWvTUiiqDeGmNRkZwLz1IFR0iELCqiQCoCrLLUkkthgcS1KC65kkVnsPfu7cNpmRdVfV6lvb7croJfB18K__px75w7D8vN5e7wNFjn0MDlRXe9XX335iEEt-T6oxdXbeO3bRuecw2Rb4_Df_7wwSrmDDeb1WXffXq1IUBnDYkyKqscl3yu_HSav373OExlKbUkJoPNJtbKaeEQbTXQdsF6x1JL1ppLBVWAaJ8LP9I3za717x_P0zBcX25ebPoOLdd6v5-6VVQAZwwLplzleZ52VhgL8q-fDp9dbVvw0RNY-v7hqESNof1xuuw7Z6gNoWvbD_t5nNNpGPT5RYiU5uyj884ahNjYXd-dziNAbb1XERGtlYuyM05Y-rZd5sV5_2y7K886CBDvTKlSU7XOgqohI8Jc2Fuz5ForE6ELAQCdM-OS0lIBAYwBZ-tvxKkyL9lYoyqKyJWXnPn5MACgAKBorEmljuNEiKUqAI7zsumbx-MgpQKRs0YIljmrsIAqgnH2WUMBpY5DMc60bRd9mM4nVYiuWa97AM3Mzao_HY-WDFe23hFhEzsiynler3doDbNsNhvr7TgsitqtupqX0-N-1ffHx6dm1dgQom9-_4___u5i89233377y2_m8yM8t1lie_Hq82la_vAP_mC3DrPIv_qn_1uZTjH6h4dD2_XdZgsIojW2QUS7vv3H_-Af_2__8k8-urmKbfO7v_iyjW7bd83a__LNd__hT_58PA--6V1jiHQcYLXb9usIoG-_fWhX8frju-9__TfW2MubS0e_aVNvN9umiV0Iq665u7qCWnJaXl1fdd53MQZnlOu6b652fWsMKpRcm66pzClVRGpaV0VVAIDIGUMmV3nWXFpjS2ECaGMkhWFanLOXm94QWjW16K4PzqEHMe7lD9XGZZpDdFiLIErNZOn8eLREVamU4oMltC6Gvt-UnCjYUgohcWXltJxG8o1vIrD0qxVwHYah3-2qgLJab51zCOgaL6AEvuRkYkBjWOa276bjgKAsmnJt2qbmxFzbvo3RiIi1lois88ucu77NKSkKIvWXF8N-X3MVRdc2eRmMQp4SCC9jYhGLBtBILVyrcLm42lprm3U7z_M8jt16swxna2xZ0nq3WsbFgDiPcbNeb1cEJMhSso_egC2sq9uNMb7b9sPDKZ2KawCKumg4JeNjTRNJevXRXRvDD_7-7877h_PT8Pj6zTaGvl_93T_63f3TeLe7ejoNl13z8cvri3X7F__lr7yzv_PbX331xYu_-S_fXbTeePrrX79ZrZvPP_50HBOnXDO_eft4t12N4_n7X7_ddO36ZvurX3773d9-B0aubq-meZIit59-sn__frXtD497J2oNoDfHx0cXvYgKIlpTS3Le5eG0nKfYhM3V1TicAQBqIhULtc4TCKNokZqWZJ13ziuzcPbWWktSaq3J2iBcuDKhBVTiA5hWS3mmbdS0WNdYi2nKqOIsScmqCgjGByRREGH2nhBABcgYMCqqzLnpei6Sa223HQFkETSu7TuWzAXKPF-9uD4-Td67nAsZG7vmdD63XQsGKmhFXIo8jVMmFIenJaG1IsyVK1fv_ZAyqCy5WOudo_E8dtGlWpciZMj7ME4TWmKRtvG-iZUZEJtNk0pVFlYgModpVpVxzoyQWeY5rzddBBmX_Bd_8-7NlP_69fH9wzkrg8GH_UjWCMJxXJ7Oc1YcyzLkcjjN3vt5WRDcOaXoLQswKloCBbJmnCYyLpf6vNsTnH96PIcYxnmea6mKjTFi3DTlzboppSoiGZwWWTfeODdOKfbt-TT44FE05eqcIWfRkLAQIQIT2rQUFz0ZqJWtM8-GIST4wQ9247mSxd9AT4xTosLsHIzHcRyrsbjqGyMALOdl4aJIZknFOZOWcjyPXRvfvt-3wTYNIcC7d4_f3z_mqktaCsOq75eaHp7OIkrGHR8Pj4dByDycT_cP575rQxsaoHXjPOLpOIBVNHgo-e5qO-cSnPHeO7SJwTtabdpoTa0cg_cWnbPzPPd9J1rXmzUCpqzO0qc329tNO-XaBGcjBe-2u5aMIoi18OLqwkr9_NXVRxf93c2ua8N5Hu42zfWmWwW_aYM1hktFIkPorCmVjbVcBQ0REAAkLveHoyFou4655qWsmggIBomQyBAoGLCGCECf8zkiCwyggoSoWpmXUoCwMMxzFdVSsvdOqp7Pc67cruI8LbvNuvFu_2H_gy_uXl5u3747fXq3We-61jlnsDHUd8EQPZuIrbWVddM1ZAwZyqUCgjI7Y4ioVHbOFVXjTM4JEM_nebvtS2VgQUPjuERnVl3cPw3nabq62jpnDWHsmpcXGyQIqCyyamN8rvDV-vYwnoby8DQzCyLN45JK5VwBKTaBCL1zgFTm4gyRASRVBUCsOVtnBIGArKPbF7vzae5av-Tadi5EX-albaMYq4jMrIqgKqUCIRpyxoICAKIhRCPM1rnYBAREJBS0wZNzQJ4QHQKXRSrXZeRlqcu5clajtmt90603u9CuzHoN5BgJCYSFc0FjCOn5rWeC5VKJQCp7T9ZazRkATfBo1XhvjHPeqlYEMs6oiEUENSb6Up_HPEvWOWvR-ZSzMQ6wNjEAASiWwqwsrKIgAM-ARWZVVmeNAVHBCnqu9Tz-xq1eMhtrQHVJ1SAxVwRIhceiS2YRzakoEoOIai2yXrtlqfsk68Z3wapUAikA52E5jMvDaX6a0sIwV3l3OM9zMZYQsQogYGEpqT4nUOM0TUteEh-nyRpjI1pjHx_Gh2EU5lXw1rnDuHzYn4HIeU-Wvvr4ZtO4ltwwpD9__XTdt5frtuvavJQqDKiXl31r3F_98nUXw9VmdbVpozEsKLm8mZc__35_mLKz8bPdhbcukBoQYSYQ76wonGt98zA8jOVpyt--Pw5zRYdizJKL8-7pPD98GKdzajuqqu_vUyBi0dNhXsZpHKZauHGm7f0wTJu-_cOffvr61-92m9U-5599_mLbhGCdMKtBFUWAPJfEte2iMj48jiLyYretyg3q1aYvuSYxv77fK2IXPHPt2qBSN-te1ZynSRRSLgoQrFfVSx_AWyTjLF5sus740zBs-jYY750l1SoioDEEFXluZFhvhBlUQgzKis-OADQpFyKTcyJj5DfcfZeZiyogGWOZFRH-21WARQIAyoWdNYQ0zct60-dSnXWsWqqI6LwU6xwSCkvfNufzdDhNTRvLc79IuBYF0HnJ674xRMT1sB-IjJQiFZom7vdn30TvfSpsrXm-VVimOTTt-el4dbWdl9GSFZFpmpQ1p6QKBrTtOhFpunZZkoC0XdO2XWXu12tr6PaTj4h1GQYTQzqdV9eXbLD17c9_8QuD-rh_-K9_8VeWWFkxtuD99vbm4f3w-7__889ebavU__V_-dPeAsw8zSV4v7m6LFwQcHN3HWIIXS_Mb16_-8mPPv7k7vb2cr1ZdVn4XTn9z_-ff_nmm_c1VSNqrX3_7rS53vS7nUOlXN9_9-767qrrmjSPzhmucnFxASrnwzH66KxBkE3XhuAMysVmfXe5bdugeYkhjPNgrFm1za5vDZC3NngLyCqgoONSjudRBBCpcKksqZbDaWYuTQjGQBtC7GJacua67cK6b2sp665tom-CMURpnqJ3Zvuj36sMxmheZlGVXNNc1zeXxMUiAioBnPZ7RDwf9qHx1vqbH746fBiCt877OiUyqsLDfmqvr-o8d_1aBLUu1jphLUsJ3cZYqqnWUs2zqU4EUbWIA9uu--d2bOxbZWm61jsngtN52m53sfHHwzk0bUkZDV3e3qq1ztpp_0SFrfehj-NxtjaQN9cffZSmqWsc1iRcd1dXx6fHNkbnbPSm6bv71_cvPn6Rp4VraWOcz6ebu-v71-93Vxer1WYa091HL2suQOKtr5XzOFkXkND7Rqke3j06B11Hw4epYumaZp4yonJJ5TS8-_5924Sf39yGLv70Bx9frDZ14f_z__D3ndcyTD_88uZut1434fZiZY15GsqXn7yoy_L-7cPLz-76EADqskzvX58_HJ_WrdvEmMrS934e5l_8g9__6KO7X3_z_Rc_-XKY5_Vu1aza_ekUfNxc7sb9o1u303nZXaxZoLtYK4MhKjlxSs8Lu0jA46xS29afHw6h96HpxADnpZxHFzoEB4i5FkJa39zN4yAptf3a-TCPJySyxqeUkZSsB9HnfTqRhhCMJRTVWkGh2WyZq3W-LpOUgsKa63N5gwhBVGqtKaECiCgXF5u6ZOKqUrzvRBTRIiHXMp9GYyG4hoxRrcs0rbarWjIAp1rWF2uriN4ywqptkVmAZ-EzC1s8TEuqXFS6tslJraE5F1CY8qJcUWDVdSXlENo5p3mZjDXPXkMky1WC9z40S07742kY01jLfpyL8vZ6fZ6WGMIimlhc3--P41gErImr8Nffvh5KfjOMYt1UdXPdG09zTocxqaG5FhU1wSsBACqhQTeUnKoIyFKfN6-0C8EFl0stlUVBQadpaWJzHAffeFA8jdOhJmExgKLaNSHXygxVnnt8EpqYpqnb9MNx9NYE54mICyuAi84Gx3M1llzfPDvCQA2Stt3KWmNNQBdj4wWQRaVCCMYinh7OwIpQlyW9_v6xFm26eH29KcxSoTr10T0X_YvAaZx8Y4YpH6d8_zDG4C62a1BNubx9ePybb9_--tvHY0qc87vHPSA-7E8fno6JlS0-Hof9YXxxvWXR0IVt3wzDHKyRUpVZQT3ZSNRY-9WL7c3VdhoWa7SNlrkET79BGxnNpbzcNT95tblr7JdXzXUXkPWwpBerzhmTn1FoMaxjlHnJ09S3jbfURbOKDkGCAQdgnhHZgCJSCudaAZEQjcFceRFJAk_784dhNqQAaK3Naep92HUNEhhAY0kUmCsSEqGqgAqDIqAj--ziAZFaa85VQGJjUtY5ZWFGJFVWwONp9MEBUsp524eUE4h89GKHSEsBdHp9eRWc6UPoW2cRDZECzCnnUtZddNZVrmMqhGiMAYBcSozekjGGuPJhmPouhhg36w4UhQWtzaVe7ta11l3XnKalFCVSbwMSGkPRGyll3bdN17QhpFysoTnxMCwazP39mIXRhsTiQ1iWXAS6vk8psxRFUYHonCigM8JijXExKBq_9poyzozOpDlfX2-b4OalNp33QPN5meYFRbSKIeOcc84pIPkgRaECGeOblghVWEFQsFmvh8OBFRBNBRWp1lsXrLOBEKUqGgNVOFdNOQ9zGo7zcJzn07wMNaDvYtzsutUqXN_E2FgXAUCtJSIAksrWWckldB2zWAtpSXlJCsxTRmOksnfRNo6X6rqISrZzNVUiAyLPlEZAtm0UKcFGY41URYE052V6timBM7Yqp8QEhhA8EaJWgf2czsPAIsuSvbXOO4vIwoSoBASiigtXJazCiGCMKSxcQaogaa4sCgHQOWTBYamH8zIUPS7lnDiJGmML8um0iAooC1JiVRXfWSDIonNJh2GpCKwyLFkJj-fp8WlkhiEtwGoU-z5OS8mlVNQu2BcXm-vNxih7xPO4PCzTJxdd33WEOJ4nRO27pmvCMqXDcbi9vYjk--gIAaT---_eHMY0nsvlerXrW0aVwuOyPB7GQ8qnpT7My6HkRfiUUio6TOXhNDLAyPW4n4YpH-ZlTllQOudAeZ7m08J31z7nMg1ZhGPju74LwW9XXS7ly68-vVuHb75-3QX_mI6_-OKji8Z5IkswV65S6TluVVbBlbdz5nFIq7Y5LzOo9G17HtOqjedaz1O63fRt2zqHBrFto3FovIjg0-lMBDaED-dBqnStJ2Mq11zrmJbKGqJvQ2SppTKXIgoIQAgiIJWbxkfnKxdrHIuEYBHUklEQQhO8RSRRDcGlwqpSWOZUgvc5ZyJ01uRSUmYASjkjAQoI15KLCDDwNKbnFXpFqixkDFd-_hSRShVjbK4VAFRxWZZ111WQmrmJjSqnxIiEhLUyIKiii65rfSlyf39qgl-WhQBCiC64q8t1LeW3vvzy3cOhLmVJqeasglXYGiJngMF541047E_b9XpO86rryWDb9zUtJfPF5WoYZiUkoK9-_MMf__zHrafX7-7_45_8meWSuYJBu1qRs9128_Of_fjHn714--7DP_1__esmgEf37vXZ9_H3_vjvnp7u08z9RT_sj8M4c5UffvnDn_zss7vrKwFoY-Q0_ot_9S__659_rZmDNyTQb3vvvad2tW5XXUSpSBi8X1_0IjKN0-3Ll1bBIDski3i53W43_XbVvri-OD0dVn349MW1cA3BdrErZTYGL9Z9MNQHbywaA1xrTnU_jaI4DJOo5lKfcw9nzZwKINVaYnSxDR_f7QwKEjlVqZVZ111ct9E7QywOBbk2jTPm8ktAG1ebZR5zqjF4KMtyOltj07wYA4ToG2Mc-eAPHx6YNQ3p8x_9aDoNrlsp1yUVF13sm-V0QEOPDw_by3W1CGhsdISGF2kvWkOmZG66RggE1RizLAUEcpqADBIIc-OjCm8vr56eHhUxT-e0lMp1tVkJl2WaQUgBrDNt1-0ur40P52NdX63CyiHaNAtZJBapQGROh_3Fzc142KPCNM7B2dWuPxwO_Wqz3x-a0FSpUKszbpzni4_u-mAt8nAcxv3Jebu6XIeu5cKri01dlvk8hdB620iugsJJSink0TkDJa_67uWnL-swff3tN9H7zXZzOjz9_T_-I03zv_s3_-HLT1-2wd1cbu-Ph816Ey199tH1btN__e3bn_7g0zSlJro3rz989cXH_WV7PJx3u81Xn390fbH97KPb_dMQQjiPw_l8-vyzT7_-9ffHD0858x__n35r_3S62V3cPxyr8uriYjiPwXcp12phHseuadUYY223XZGqjzEENw_DzccfzeOQliXsVkYMOcdcFCVX9tsdkel2l0ZUQYHZ-FiZ87IAgHWmLouxQZVBBAwSqRoi8kRIwgC4TGNzsZlOo_ee86IsRBpDlJRVUUGNdcLCpRpAZUVAixYscAHFClIQjACsdlsVTstc54ygzoaSS8llt1vNYwLAmstmvQIAb01N2ftmTMmEZiHOqsbgxDzWVFJtgiMgA0BouFSyFvKz0sR6b0nVOZ9S3m36VLSyGGcMGWMsArVd88wgc8EeT0NwYSh8HGYxOKaSS2GlYVguVk1hLbnu52Sc5lKs2jTnz642Cm5RZSvLUllkmlPXNmMtIrCfJmPt875grvU8zQqSSjVkEE0FSKVWAQQhg8b7_X5q2hBjPA-zqpKisWEYU984FRFUUHHGoDABSWEb7TwtiIAATdeCRWRMU3HRkTHGWBCGKsabbtUCQGxCiLYJ3hhjrFttm8urFc_puB-btllSybm42KCRsiwp46TSdyFlbromqDgbhuOYpmUs5c37_ZTLPOVpXirhOCxtF2vlw2kowH3bJK0vbrffPewFhA2kwqmyIM2lTNM8zMvFuiWLN6vmouu84ejD8ThbZ_JSh2HcbVdFITr_Yu3_8Cef_OFndy-vtpu-WZv6O1_efLz2f_Tly8vO99bdXq122z7E2AWz7YKCWmcsmVr58f7w9runftO-uNzF4KZx8dYAoSKoKCCxKjhMXE9TKqBs4DjnN-fp64fD42Gcq0xLIWtWXbjarK2lqtwYuux7i4gK1lhCBAE0IPBM4NHEFQiYRUVFxRirBMIKiCKaCk_TAkgKmHOy1ohqbNo5F2EtpX708nKe5i8-vtutVpe7XexiLfVm21-uO6il8YZUCYEIxpRisKs2SlVVJCJmUQDnLBn01hmDoGCtHfOy6XqpSoTzOFtrqkriqqpdE2vV_eG42rTMkpYFCbjmddvllIKzbfQG8Hie2j4Oc9mPs1r__nFQMuepCgIQ7o8nG2zwMXiccmaV3xjQDJHDZxHHcFqIkLN463zA0-PgW_83f_2NGnjzZm-NKcKu8R_eHMCIc-h8sN65GLhKu1mXyib6sGoqi6iiMbXis-4UAdUSeCcqz4jzmtj5KCyAyFVD0xjvnHPGGmAxhFCLFaVc-Hzm49M8HNNwzpKYuN_1XdfZrg2xadcbYwHAsXUqUnL1wQsIFjXeKIhUVYEQVjUXtBYrQAyVRQWarlMB3wQuTIZcE32wwGCsA0fzOE1zAkOVZSoVjBZhAWWFca7DwmPlCiRVG2usc5aoVs6lCitaSrkimKXWaUnPqH5h5efqSFUVTKWgMwYxRiOKE-gxlUV1XOp5LqlyrZpymaaccq4icy7nJQGiaexxSPf74d3pdF7KnMt-GCvrwlIqzykDGUDILG2015e7eZimVOa0_OD24qOLzaYJAdQQcdEP5-li1XlDmuVwnqrUgng4DnlOJdeLdQ_MKZWHD-dfvtt_-zCH4C62q66jNOfDkA9Pp_1SpyyPid9O-f6YPxzSu_vTtx_G9--nc0q58MyiwOOS2j6KVBv9035Mc12WNE35YcgGYUo4DIvvraqyALOsViGNC-Tqhb_46MYLiDHbVfjiemsUlqk4i1zZGZznUrLcP536VTPOcv9huLjwbQjLPDdtezhOQ0pTZhRdebtq46fr-O7xdLGKy1yQackyTbMiICMCtG0wjgQxVfAWyKg3po_BWVeFAUAqAxEgEYJzHkHbNqhgytkQAYCIEJKIeOesscIsqoSkCLWIIXDWElHw4TcHF2Yks6Tkgi-1pJRqYXLWGJNr9SEggHO-lIqEQFhZci4iYAy1sXHGTGlJuZRaY_TGmCrsY_hw_7TqumGcllQO4-QtZa4-BAbwznBlY0xONThEFEVAQ23sUGvXtDHG7z7sD8ehlsU7_wyG2qxXTdvkOTVNrCJtE23w276zzjXB3b283T8duOTbVy8fH-6brlmvN69e3H7y8mXW-vVffv32-_dAWpaENn7xRz9Lp9x26y-_-PTV3cW7d_d_8ctvUxq3m-0wl5dffPTbv_-DP_t3fzYN03q7UQXLtLLuF7_46XbVC5l5Or_7cP8v_tm_ef3uYTzyPJXt1SpaS96VjN753VUnpSBA7NqqDM6J8vby0jp72O8__vjjp_vHVd877y7W_WbdOYPewEd3FzfrvqTlYrvuunZOc_TWEVzs-i4GQqi5sgoRVpEK8nSan7tY1hpEbJugIlXAGOy7Fghbaxtn18GuXJzOMxiz27bbNrpgHSIL__nj1xe-82CM2X3iGmeIKFgVRQQQJgDIGblKzjkn68N0HtBYEwynUnI575_6y13NtbvYEbjxnLvVGgDzMt9-8vH5w353fZuXks9zno8Xt1e1FBC13uR5sc66xrnY-xBAilERZGAlJBbp-36chq5dGUvNqrXO-OjTNHebTdOtcl5Wu40yj1N2wQJqt21AWQprlX7Tc6lx1YdVG5rYdt0wnK3xJtrbl6-Oh6O1Qase96ePPv0ozdP1zUsAdk0jiK2J03wShbaLF5fb0ARASFPaXW3QmKc3392--oSrQq0U8erjK6yCAP2uszY0_fqTLz69urgJjUOU3_3FL6IN2-1q7Z0lN07H3_vtnyNqIPPq5rp7rgYbaw31SNfXO-fsP_23f_KLr7767t37zz766G632fT-__HP_9PlbvXcZD0Mo_fh9vby3Zv7eS7OokHYj3Pbh2lamIVUtebD43maT8G7PrTG4a-_fesC3X3x6dP3b0tKWkuzXQ2PJ0Ld3r28_9tfSc5aGV0znc4mBrddqYmbu8_SMF3dfjS-fYfBh4utZC7zbAxIKb8BaSMCA5dkoxchASFEKQUQVGFe5ufBAgyWeQZgQGAWJUBDzKIoRLaWYp0hhMLZ-lZV6jLlcXCxS1Nquh5Fl2EkwHbVAAKIYWZBtMYiQmxbH_0zDWGcRkZtQjyVVAEXLt6G4zITKomWIoQQ0FbWrPrhab_dboZpeS6zBuMr12XJuZambU-n0zCOq802lUoEJGjJOB_e74-hax6enuZ5OU6zbdyLq-s3909cdJYESCD44mJbQM-pfHgaQhc_nEZyMRUJnc9z2R_HXGqpsl3H81KSSqlFCHOtrW-WUpDMlPMwLoJYWZVICi_jVKWQIWAUkDllb6AWnae85NkaI7UiURUghmWqvvHeGAB11llrQxOQ0DvLLNcXK2PJGPLGMnMTXPBRQZ11oozGuOAM0u5iE5wn1fHhkTO_-ujmcJjAYdO4to1LXoJ13vrW22lO-6eUSnFQ88ynYWi6EFYNEjXRItLzM68lK4IlU1G7vn1a0rrxjffOOTHm6bQY456RxqnKPNfMWoq8Pwy1igrfbVbW2Ntd_7NX1423r7a7KrhbW2OpchqXctGGLrgXl82ri3i13YQgfbCTigHPaIFsQXOYlyJQETZdK4amZW6auLvshUAMZkNJGB0uooeU70_TnDhb--5x-P7p9Obx_PYwPixZyB3O82HIrbUKwFyDJQDlyu9PezD82eXFyjtvCQkqM5E-C2gNYWWpLEWkqjALECFCiEFUmCXVKiqFdc6VFTNLLeycWTURkQTNw4eDMWa77nebvolNF4IBMtYcjqcXV7toceVDLcUZSrVYY1hxWarz3hibqyDRMM2FGZAsURNCE4MzZppTXkoXvSFqgz-dB1VMOZNx85yApQ1eFZeclet2vbGG2hi6tlMp0ftaUhdbAD1NizE4zGVMqQDtx6VWnAuDpwqiCFy5aVprqFYtoEvJXGoIzzD-nFJuoyMCFj4_HBVZRU6PZ2tgmWYQSXMqwn4byJCmMk-T60Kp1TeNcRbJkncCZEJTcrXOAAAIusajqvUeiUBUCZWBgACw1KKgxnq0yALCAGQAjLHWhBbRIRKQA7C2WwEZMMSJofB8HIen43w4T-eRa2YAH8Lqepem3O-2gArVAhKC4yreN_RMTiSw3qOzqkDk1KCzzpAhIgB0sUVDrgnPgMScioga65dcimguVRTPQwJFRigsmSsYwyLMvyGrIGJRfj7gVZYqslQBVB8CKKAyV1lKnVP21k45O2_P0yIMS-Eisj8sY8m1cCo852wIrSECTbVcrJrrdQOEwTsVHYbl8TAcjsOQsg--ZM6FnfPW2sNxOM0jIu0u1uOcPn1xs388PB4eY-O-eHFzuWqfZ1NAENAlse9jsJhVU5VzYROaKjDnum5bH32MdmKeWCdB07jTnObC3z-en8b0l999-HCeH4sMFY-lROvGJQ1jmucZCcEpSy5Zi5G8MCAmZk-uFF7GxRsjKggwM2eBaDGd58zFBYvGLcuyvegbY2rl8TR8_OJq1XXZwK4P6zauQojGWoui-mY4RPJChkXiqhHBD4djvw6KxLXapmEUFvXRGwJjXBuDEh2nKYSQlhobt-vjOKfTkGK07abz1ucqtWrjQk5LLmU_TJ_cXnuiaR4N2fE8N10wZJHQereMc_QeEQ1A5sJcvTVAlOdsDbJAWhJaI6KigkC1VmcsEoJoFWHRUkuMDdeqgLVWQcyFnXfG2PMwMmiIZpwWQ4ZVRbGyjuPMqsLc9S0glVozM3p8NgoE70rlmkvTRkAAxVxLjF5ZAAGtcwYN0XMVapnnrm1qrruLC2PMw9P7l5c3BgiMfXrat43vNqtapWkiKqyaCKIuhBAcIDlDXdf2bT_N8-31TZonrrXfrPf7J-f8lz_4wfXVxYtPb4Z5_vO_-KvHtx-4JGWap_Liqx-mp1OIq8-_-OSLT27P0_Qnf_p_1JKv7m7IEBBFi_fv7qXWF69ensdzE-Lv_N7Pf-vnX7poTufTP_vn__rXX3_3_vUHZ9ycCyNbY0lsyaZv4nrV_fyPPjMCohQaK6KXt9c-hja0KLruNn1wluT2atsEv-rDJsQlD503d1ebj3YrrjU8W8-IhnFY9R2obvoVqrLwOC3GW3neYFRKOakCEhHh9aY7j9NxWAAVAGIMwAJauZR1HzNrG13fha4NhKC_OcLpj1991HW-9cbo-pYIEQ0rsCga5FLJGuXKzKrMyhgtaq1VjPPW2OjNtIzIHFbx6f1-c3W12qy4cre5mIfReVNLPj8-SOF-t5IMy3kgspWl7zuy9llDzVWattFSWdFYK8LG2crctA0hDseh6VenwxB8iK3PKZd5MZbaVc81RW9uri9OpzmncnOzBTIvX9ydj6Mh7NZ9SYXI9H3DzI5ciMF5J1yI6OHt4-5qe3Gx3j88XV5dnff71Wo1LsswTesuWGs_fDhZR9754-FUcj4ejtvd-rg_hm6Ta3KNWaYBWfOQV5tGkdvVZv9wuP3oZtofx-M-WPuzH3_5-P7ti6sLInBE33__-g_-4PfSdHj14o40r1aRhA3puold698-vV_mvGnaF5v1Zt19-3ZPZH2k6Tj_0W99uVs3wYau622gy5vbDw_3r-7u_uqvvyGDLz_59N2b-9_67IsFYN4f-rbzFr_46WeP7x7rlHjJXdP1u_VynstxFCkoqoTLMGzuroYPx7xMJEw1qwqiOG8QaHV157u-CIhASVO3Wu3fveFcQ9MpAJfkfBBhQ2QMGWOBUAkpRq5sjcEqhdl6J8woTAJgo5SFAIAAVMuS0VggUBYEIQdQf2OzUFV8bvGiI8MktYzLy89fqWiakrXeu1CKpFyNe0ZV2NPpHNvYtI2ypHk6TRO1cVItKnPOxlByOuVcSymZm66bc1YkIBTh-6e980EQRWTJi_MWCcbT1LStN3g6jXOevLfCEtuIqICoKKFrxmEBb-eUTlN-__AUfBiWJTOfp2WYlqVI9vLmPIKzj0_7j24uHZntpn_7fn-5ad_sj1nEGoMFBOH-PBpjppTGlEV117cCoEpibCpclVh5WZJ1_nRerA2qYpAS11TYWTuVZKyZp2SsZVHjDRI--7yQrA--CU5Vf7Nj6h2BEFpQDcG3XUSCZ36csfarrz5Ky4ICguKsM9Zsr7d1fsauLZnLJ1-9Ou7HGIwKzlOtwt1m3a5X1lCqab2OoPDuMAKQIJAhC_jqdn2_X-acmcuy5PvDsZZ6sVl93oaXt9f7_VRrRYEqAsYICjhL0VaC-mzvirFUPqf0t28OLHp9teIqxujFJm5b-sGL7UUffvpy87ILv_P59cUqzLnOlY9zVTIZwznjh0mHyvfDdH8-70_TOKfrGBy6w2n8_s3juCQbQ_DmMJfMfJ7LmOqcaxZ4e398eDhXoXf3R3JmvemrgvUOgGqFOWeLxKi5pPW6qQpjrl_c7D7ada_6ziARAiLlwoAK9BvhPXOtzKxC9Dz0qbUGAESKsKaS0aIqioISARJXdd6DCigC4HlaWHm76kNo-i60zkZjUbX1TkR32y4SLUtuGq-Ip2Xou06qxOhBgAUQ4DjMAoAGgnPROyk1eGesqUUQgchYQmNdrgWMOQ8JQBWRa0FEVfXedU03LxMBxiYACKfStrGytl1Xatqf5xjcacxo6HAqE3NiZTAp5VpBUEA1uGAImdlYnNJysV7XJH3flVKbJpIx87TMw-w8liwuBkZN06SA0Qcopcw1DSkESqcxT2k6jN2mMYCh6YxxouCbxjQh1wKIZIxfR6iqCojW-QioLjS1sDIjIQA6FxCRRa0xNgYVBTSqyAqABoxhQEYiICITm1Xo-pJTCN4GDwBkrQpL5VIKiEopUHLXr2wbjA1kQ7Pqy5JBDdkgqqVUHwIQCqi1Fg1drrpcxRjnghVWQgJEFa2Fn0MTVeBcCbAKqyrhb0TRiJSWJLXmzFVxPC-VJbFUFVF8XhJNXJHFGEyFh8znJSnikhmfU0MLqqoGl6WOS6nKVsBZ00VniIIxu9YFQytvbxtrBBRNG2xDpgnWWOca572rWVJOZAhYllS6JqZS7zZbQ5rmhFyfTsMPv7i97vvGulS0chWEVLiwVqTvPzy--XB6P6T3x_FhyN-_f-RSYgzDUn79_ftfPZx_9e58Eng_zN9-9-Hd4-k4LL_69uFhP5zGMic-zvnh4bws9ds3H87zeB5nTzSnLBmGYSRjx1PySNtVQKI05_MwWWvnYSkF_uM3v1oreoFSpbtsyTko-nwh1jq_lJLH6eMXVwbFIvzssxecy3bVbpoAoAL8cDxuQvRNK6oMVFhP4zIzt94vVSprLSyCLDrPE5FVVC4ZFFmQDDXRrdruPM3TVProulXrgaqAMVZBrTe5pFTylzfXMUaDmEq1BitL30YksAqA2jUNEYHCME_RWwTTxsAsMfrgrYgyi7MGkUQUSa0xUuV5f3rJWVhqZUNWgbu2WVIRQH1OI1gQdZ6XVdeCogiTMczCLKnkWktl7fpogHKpvnFpTm2IwOCIjDGVpaTqg7PWoLG1VlWolXfb_vA0WEOffXzVXvSn-9l5qql0fRyG8bLf3t1eFuZaJaeECAhWCq_6frPqU0qXlxc-BkIU1o8_e2UQXHBt9Jbs-XiMsVtKXgX34x__EJXbaN49Dv_x3_3n0_5QFyaFEMOLH7yq81AX_OJHn_7u7355un_45V-9TvPyk598tsz18HS0BPvhDKirfsUg5bj84vd-TgH_-i_-5n_5N__--7_6HqsIkzXexfi7P_7dd_fvYhNi0_7uP_qxLsuL68uHt-c887LMfRdj2-8_7G-ubqVmzXk47q-3WyLsg_-Hf_x3ncr15W7I6eVufbntpZZcOTQejRKAsnQx9G1cNUERcuZxWoCwZGGAvg3jkg2ZJvrgXK6MZBdlR2iBaqnKkutye7n13kQfaq3G0TRMgGCt6bvonWsiGebDu9emf_n5NHMVNtE771XFeQ_OpHlAJQBFBJ5GZ42USkhcFY2JfZunpYzJeFfGMaWFLD0-PLbbtY9NXK2sDaFt85IMGeZqUTilpZSma_p2A0ScizEGLK0uttOwgHCZJiScpynEXlRqyWTNvKT1plcWznWzW-eS1-td5-2csnee1FKuxpjX3717-fll08TpNJVSui6meayFORff2JqrdTZE33SBHJGK8T76kGq93K2td5e7XV4m44IoN9acTofuogWwl7dXxtjd9YVvfeYSWl9POcQQI50Op83FZpqXi6vt9bYreVyO0x__k793e3N1fnj6xW_9_K9_-V8NogLUPP3Oz3_yeP_hk4_uHKhwXebUNaEsdduvuqbxxsRVU6vc3uymsXx4_dp2Mfar6Nz94yOXtOpWy5LPD6fTMF7sttur3a---fru6oIMHvanX__t693F9us3D1Lk5pNbzmoIm7WvRTD4PKcQ25LLfF7qkmpeQEW4uMZLKYDPqEtRhSUtvltb1wyHp2VJOaW2b5engxpjQlARQuCcUBgAfWxYuebq21VJSWuVUkwI1nvLqmlhFeOcNY5LVgUAIENERALWmJIyecNcCBBqInS5FCWLCmUcQBUK12LI6pKWeZ4Uoe1bRUnjYjzF4A2Z05BcZ0MT1rExPkxlsdEzAADNKSPqdE4gFVWWKRkXFDHlPKdUUFLKAOp9SKVkrlykgswpt51fb1ZP98d23bax2Q_TZnMhwtNS7k_nmxfXJQkqONT7x6M6h9E-Pux9dKc0nVLy7SpYulw383l8__hUhG1wNxcX7-6fXr26PR_GN_f70NkQuyya07Lk4q15_XTqrU1FVk2riPOcjtMYQmTEpeS28fv9oKAK6mzIwpmZVbgKl5pFbXQEXiW3bSNL2Q9nH330vo2uDYacXZZ0cbXxRLUKgVhLPgSDFILtu26_P3z86tYHj0ohmrykZRwVBbV6506P5-Bc3ziyLgQX-0CAvo0s4hu0QIal5LwOIVo8zNN-P17s1ucp_-RuhVmQIEQbjC3C-3H-dhqPp_n2ol93vSXTd411z-I4GZbleB4JaJ5SyXVOKS1LbNz-dHx9GEPfPI1z07SuDYxkWzNXZaRsKBc6ZRmzPpzy90_Dm_3wN9_dH4cZAbDWn3x8_Yu73SdXm1XjhcA5mwHOc_5wGN89DomZjUnCxjtVGOfiHPnglHS7iReX_uFx-vb-SQnGWh2hZPQNmczDnF5cb15d9i82fUB1xkqtzEJEtRQgFObjPBKa6B0aM6eFiIJ1ZAhUEECAVGVJKdWqQKlyBUVypRYRZZBnhfacytM47jZ9E4OzJlhz0bcGSLjEGJrWezTB2SY4Z827h_315Y4AEalyRSVB5SrTkgBhvV4ZIqll03e1iqggofNOKvdtezwM1pOASbmkkhWQpZIxIfiu8aL63B0yquM4NTGgMcHauYhwOU6ljeHxPOfK6v39YVhyneYEIsa4aV4QTQhtdE4VyNhcxCHVKlOegVBVWXROGRGsdX7bLuOs1lhHwFIq5IVXl2sg0IrCOuyP0VEeJx8bcs4E7xuvRACGVUJopYJtgyR-3phVrc-TsQneWGecewYyqSqo1Cw-dFUrucCIqgjWAWrlqiJEAFqVMwMoWVFFNKBUGfqbK2O8C1HBgCAh5HERUCYExfaiEzDrqwvvIyA2bcwpr1frWlhFCQmdRUBWIGtUoWkcFxYWFZaqaE2I0TvnLNVaYwwi8MylURAQXJaaq1QW5y2oplqNAW-8yHNeK6sQD8OUCmcWJFqWYo3xzudSlqKAqEWGKYlqKbru21JLKRq9FZXzlOfMGeTNYXoqZRFNotYaBKogVSRNJeWEDNG5i01viULAz28uY7BYBdH0K__q7sYoGGNT5ofT9OZ43p_SN-8PD6fp2_vjuebdavX1-_1xTLe79d31DpEOy_Jhmg6lPpzHD-f5aX_-9s3jqu_uD_u5llTz-TQWzkK4lOy9dRZFhQQXlQCODAKUw9O0auxq629W8f1x_u7b1--nx4en09OHU7cKQPTpi5fRGxutcWDAzsM0zXNdykd3l8KFl7rdxE9eXOfzdLVdPZ0OluXmYuURllxB2ZABJGFeUkaHRfQwzqiYijwehzYGa-k8zOM4WOt2m_W8JGFprQGVdRtisPM4s6qz6kPI59GQUTRZSoxhyQkDfbTbXa46ZVYEruIsEaGKShUVQdTggoAggDXWO-O9T3NqG2-sIYAlFWvtc2mEEIgo59JF_1zTQiIiAoQm-FqlliIExrrK2RqnqqAYY_DOLbkQIBAKQOHKLMZ752zNpVTJOVeB83lhYVa1lu4fnrqu8S6K1qYJwtw0jlm--vTqw8MhuGZ3s21jc344t22LIG0INZef_PCLSDalogrn8-i8QxWDFINr2qbm4oMX0XFYvPfWG2LYbrYqtQ_tvMwumpTTV59__iykr4Lv79-9_tW30_mcEyOZj3782eH9k0Ewsfnqs7v_6z_6-b_8__7Z3_7yGyGJ3eqXf_Or82ER4KoFUJc0l6TX15f_-J_8g1WL__x__f99eHr0CoTKXGLrz8fZRjeVejodK_P2bh2Vjk9jVc5cur4lgtVqO47DZrO2BqN1l-vdpx9_tN22kuXTj286AzeX61XjVjFs27CKHhRi8KC6TLM1ZAi3m96QINC8pMzMIt77JXMqZVwKIZUqV5c9Ev2mHom4W_XMYgjbYFZNs-rbYG1K9f3TqWpVgHXXKCIaC1wVabtuTNMZXd35PoIA50I2iqgxyFVVyASHoMYYSyRLVRAVjl1bKhdWIuubVmtN8-SakOa5366Ec5oW53zTdTXNCpqWue07IHo2PVnj5mWObVtS4cpt15d56fp1TrNxtularpKW1PY9c7HGTMeBhV2Mm90uLaPxYV4mawOg-uC4LnefXB6ezk0Xow2c6_qizzkRGbLu-sW1d8CiF1ebeUnB-yZ2wzBuNxvvrY-mFHbGqWpN-fL2wnd-GaZV59fXm8fXh4uLVXA2z7kPq-Hh8eOX1-PhBETzNJ6Pk4u-b1fCEq0hwre_fvOP_sEfApSbrv3Jb_3sb_6PP_9H__CPu2B__OMvv3x5vV43kVRVnME3T28_ur4yxiDKUrOzNlhEwOOyvL9__J__xb8fBH_-1WdYeLNph_P08Hj62U8-_uVffrcM849_9sX98eHjly_ffn9_c7H76pNXv3r9_fVVf_vqyilIzQR6Po_7p1Masmt7MCQl5VxQNa4aFw2qci1oDAoJIi-LVFXRsO7rVBR0Gs5Vte0bMuCsJWdqXnwMrDUvS4ghTRORRVQF4sICioZAKpSFatElkXU1TyIMAkSmKqkKgljjpAogqqp1VMYFETlnYwKRVWIRMMYjiQCwaJ7PsWtj2zLrch5cjE0MPjaqetgfrLXGCBK2MQIiepc4VYTMtW36wrzx9jTN-TxZIG9oHM7OeB9sSrmUZEUNoLFmXpKPsQgriAo4G0opoQvv3j-io3maqoDzpmu78XyOPgRnlbldb4hoSUvTxJTr-XzabDZKmMZUTkvJy6c__DgvZSrL6TBb7_q-f_dwCt400ecsy5yss8_Z5zjNwdvo7DLn8zCtghPGnPN5HLfdmgANc9e0S84AMOVMQCzaemcVjAsszwQMsISF5eb2olZeyjwt2Vm_apqbzfqZhkQWBSogOuvWmz4Ge3mxXjWByC6pXm6a7dU6jTMZ5JyNs6JStcamGY7Dzd0LrqkqKBoDmsb08d36MkZN5bOXlz74Zc7CsGr83eX68WGfqr5-HEB5v-RxrsM8W0N32_U4LIgyF1lq2rY-eh-I7roOiJaZI6EH6Jqm5kyISWV_OKmhXPjd_rQ_Lb96--HXb5--fTjuF_7mcVzQHiu9H8b9kO_Pw2nMp6mUVF_cbX7v05sf322_fHHZRqeG5soZ9X4o78dZDU1ZDlM5zksSAcCCxEqZS3C21FpL9cZcbfp5yNSESmANdAV_fLf96sXm5d36chUbgzeb3gNa0eAsKAJQ6MJcKiu76Fn5NE2r2ABQysl5G7yblzzNC1p6Zt8q6FKZEHKpzhpEO0zjNCVAYOYYA4gW1uht00Zv7DKNN9drg3p4-L5r18EZA9A4awgIaU7JBesJvXXMAoZKrpWlVPbegTHKxZNx5plF9BwxI6kaQ4gIoM76wzAZZxUIEH3wxprWGVVghdWqlSoG6HQeNut-vYrDWJZcWGWeShPtMBYFTYmHJaesQMY4g4RVeJmXZ1WwgAJqreKsNcYsZSEg511OWUXIEAiU80BAXCqAVMS274bTBCTn4-S7dtW7nJKIEiEr1MrkSRWVTGx8KdzESNatX2zLwGRI5LkGTYJEZBUJyBICWsO5AiJYw8wYQgUDisZYHwODPss1EQnrTL5lMhSCqJILdtcpk3GNsL385CWhmadijKkpl8pcq6rUCrHrENHYOIyjDxEQRVgVlMjHAMwhNoKkCkgQfCy1hOgA0XhDaJTwmeoDiKxCBuclVYVlqUvOSyoMYB1xEWFIpSCoVAaAioJES8pKJosYQKOIqkRUal1YVKEW6SItLIKgAPOckABbN87_f57-Y9m2LTnTxFwMMeVSWx55Zdy4IYAAQADJShpL0GjZYJtmfEbyAcgmabQ0WtKSWczKSgARCHXV0VssNecc0p2NHcUnWL0xl7v___elJdSMgExLLOdYPu2XonVK5eEc3j5O01QIcTs017uVJr3YjkPnvLfrrtFccyopp9O0XD_b7R-Xx-Py2x8__fDhcLekqHh3nNS6d3fH7z_cIbuPx0VFL7frlunu8fBP7-5-fPvw5v48Sz3HvD9NOcsS82lZFPnD3UnJut4b5ytzzPl8nPanOcypG71lmucwjh0TNWP3cDydpvThLj7en4DAWMtVnz3b2MaPtoG8ENHDsgzj9u7T_fXlmoA2fd-1zht7c7vdrcbzw-n59dWff_p-6PyzmwsGjTFOIVs2RFirgAIy7U_hPGdvLSJJlaFvROV-fyyqRMZYcwpL27qrzWr0pmXuOmeZDFHfcuNciblrW0QEMrFEqJUIXl5stq41lmMqqmqYCbnk4q0jlLZxjffLvDCitcYQMFNj2VtvmOMcc_0LA7prGtHSNj7lzGyk1oqUVZhJBVLMSACAAsBM8xJBoZSKbAhRgXLOxKbWqgoV9AnLLlKLaO8bJI4pVxXbOhTKOeeYwPBqHPu2qQjTKcQY81JV6XTKALS7GKbz5MmfHk5__devvLUvXt42zrXWGaC2a46n87geRIHQCOo4Ds5aJiTVxpmh9W3jHPNmvWLVWqHWiqhjO7x4_kxLLsh__O77T_uHN99_WKZFyOwu1l_-zc__8F9_d3G9Y27-6m9__fL24p__y_dTypvXu_3x9PB4WGIYB29aH-e5827o-v_Dv_tvv_rZV__3_8d_-I__8Z9jqZUoTDFnyTGNqxEYmSjluVs3Ny-vn716VmP03i9z8l3bj731jlR967frcbMejaVn19si5fnF-q9-_nrbNjebft1YQvZMCFhievtwah3ffXp42mZcXmzyEtqmLQrH0zSHVJWkKhJOIceSaxVvbS1VqhAZAfFsTsczMXadXw_NZtU7Y3OMKZdlXk7z_Oxy2_bteVoOx5PvPAKcHgMgs9m-AKnW-1qLEjZDDyW7vqulSJxs25c5PAkREQFFVUqttZYiKs4aZG0aP-_3IooIMYbt5fPH-zsAGYaeDROaXPOwWTNR2w8AKlpBxFgexr7EaBqfU7CNt9Yv55lY-65dpqkbVimmfj0Q2RhD27cPd3sRudhtHz4-XFxuc5hR1DeeEIfOS605xs3V0DStlHx1c_npzbsXL55td6uayzgMxmApeb0Z5un05RfP3v90v1n1xvHjpw-3Fxfn82KtWa16VIFKm4vx8nITY84pXWxXgKWIdJsdtzyM3c3Lq7b1AAq1_N1_83d5Wa4v1r_61c_uv3_37PpKc_zZV5_1vdtuh-Pj_nKzun__6fmLK0tsCS_GbQgJFUT0fA5d63KFeY6nOXtvv3h5-eJq2wzdxaavpUhVqXXcNucprNf9lOPLZ6-O59OPP3yUnD_e763R3dVFmuLx_nD74sWnT48KyB4IOJUIaE8Pj_04rrY30-OdpgJaQfSpEQiqZAwjkSEtUUuqS2i2t6ZfpemM82MRAqmkxXYtIpYc4YkzDQoiIgoIT8BBYgMqT0hPIHKrVTxN1hpgg8ZIyprTk5geAEzjtFYAUFF2BmpVEQRGgG7VqyoQNK3lmvIyCwKg1qoE4LxHKt46JQop9ptVrkXJrtdr0QRF7t8_xhTbpsVaqxKgLtOcYmqMDXNiJi6gteZSzg_HdT8i4jLNzjzR2fX9uw9d2-1Wq_vjoSqmUlzjT6e5aZqU4tD2Dw_7vhtzLcfzdHl5GVNxli42m3mac4zeNwrVNc15WpZl_uaXX_743R1TJdTt6kJz6ds25rAsCzjarNcf3nxYUsqgc4ypKDLPIX46HBNo7xqt-vDwWHIRoiXnKsUYCwQKUIqEkkuBolqkiIiyDuP67jD3DRvnJNUodbtaZRBraDOM1tLg3Pk09Z1frdeH-_uuaQk0hkhEjqDUogJMvBqGcbNuHK82Q011aBxXnE_z5cWm7zwz9a2TWP7Nb16XKWupq5shVCoA3FlvKU2BLbeNjZKiZeedZWUkMFYYbeOdsUU0xPz-8TgtybXctW7bd8-ut7vVum2br9aNkj6BD5iodRYILPPQmpqiQWHFaQ7OmJzLw6fD2_eftAQg-vuvbv76xe5XL1dfXw1XY9MRxiXnnP_0cP7djw-_-_Hxzx9Pp1M8xHqc56u1f39_Pi-L9w0y9V3z8X7qsJI1raPLcZQqcUlvP57SMv_Dlzd_9-rSWbM_zf_65uiZRmcH31iRtmsLABKKSFxSzPWUco7p3f742fWOjNEqooAIpdRQy1IqopKCdbZKSeV_UfKxWWJeYrbO5FI9WzYcUmm8FREDpLXeXG-NYg3l2bMb59gQMoL3jpmyyuP-PHTeGIasqQoQznPwjSN6ogTW7Wo0AM4xKDwBiUouRISKc0jG2SXlKRckyqUQGSZCkSrwp48PBtAaRoWUy9h3zDyFvD-eBZWYBcA29tPd0bd-ivnubg_IWUmrEGKMSXNhZ5BNkoqGCLHUmkpmMiHGkqoSxCU0zsUQ65zjnBARzNOOxtRc2KFUHJwrmjPQEiKoxOOUltCvxxijMc5YttZba401eSkEhMYokHHOr1Y5Z1AwzhKBVgWp6pwIIChZK0TcNRKCMR6sASBiV2JGFHJNSZWcI9uXUpUsoCXDhh0QytPrx8Bk_TggWmOdc61v2na7BcXV5U5BVUBBDHMtSoats2wdMQGAcxYNIZHhJzgjEJOxBkmfLgIoqIhhSQqcYhSVECIy5awIqKpA2nVtKdVZJwCnc2BDuZR5joBYUklSgFGr5lqXmKUKMp6mBIihpFoqEhWFecrnJRyXWFMqIlmgIlmDtaphG2L2RNYRPn0OjWm8jSGHUIk5VTgvy7-8-fTbNw_XV2sA_P7DISKcYznkmhH2c37_sK9kP-2Pj-dDTno4zD9_dTuOTaXyH3_35vF0ysT74_lxH85LAKSQsvFujnmOmZvGkPv47gFUT9NcpLrGXm7H0VnfuqylaWyJ-fd__vN-KjVLLLHUOJ2nwnh8TJf9uBs6601Mms8nQGrbbpnPzy53q7G9WPWvn1-KCDnyli5W4671g-NnV7vO-xyXwbVA4A0DoqhWETQcsx6mIEAVcDrOZB0BfviwX60HEbCWDKGx5tevblLOtVYi9JYA8DRF46yUysRKWCsgU4mp8dYS_Ozmwho-zQsRWmYCFBXvrWUWqa1zISYiJmaVaq3LIbddYwyCaqqFmNmwVk2ltNYK0BRjLdVYC6CAqCCqQoRMVGohyznnWhWBFNQatpZzrYpaRa21WqsizUtMKVep5_OCRIDIhpZUvLXn85RSbru2Vu2cnWOKIT3lFxUqsTZD46zpumZsvLHMKF--ury92nlnalbDhg0dz-eh7wQEVZ1t2HDX-FIyqBpjrOG2a1OKzjWGqEpOKdeSnfVN1y4hHabjj2_egFBc4u5ya3yLbAHM2DSnU-rXF__4b37ltd7v47_-8Tu_cm_e3BXFnJKrslntHt7fta1b9eNv_s3f9qvu__x_-b9O0wKWhFVjQgUy6lunRVbbTTM4zXW13e0uroa2_eEPP3VNW7AOrS8pf_XZi6FtCeq2b6d5-d_-4y9uN-Nm7PqGRme8Y4Mw5_gwLQTQOquIu83KIHVDiyjD0HpGw5BznZYQYi6qS4ilFrbOWpqXxESO-XieDCMget-knAT02cXGOmsI2sbPS3yYZiLz7m7_s89vdiu_n9JxTofT_OH9_vnnF1kxxszu8gU8fSEIRKvUisZJVevbqoSq1hsRdb6rJSNQqWqMQkkp_0Q6kLE5La4fjGU2rFLn02PXD5Z4f_eoUC8vr5Cx1lJKbpo-xmidrQLzaVpvVkRGtaA1CPyEiFQBQARm6w0xOe9t2yyn83q3bhzVlN-9-Xh5sW36vqZ8eXUV8yyxNo3d7Abf-NPjbK3pOmfJbHfbP__u7Xo1qCgSDG3DzDnkmkFFvnj1fA7zuw-fGm-fP3-uBPv74-31DpFyLBZJRWoqrz5_nVM01kFjU4ge4eXzmzIvqLLerAzT4dP9b_76514ylPp3f_PtZ8-vHj7d3W7Xh_3x2Xbs-3bd-_fvP11ux5Jr11gAaIxBwtN56oZWkX734wdrzBRiBHl21Zegy2kGkKbvYzi_-7jXSn_6_sPV9W4cxu_efzQk293m3Yf9YX-37rdv3n26ebbOWdViSCWF3HZDDBM5Ywy3Q_f48aOm3G_7mgMxlZhrFXSOHKGIotZ5qlUQlAyF4_1wddmsttP5JCW3w2o5HQXResYqMUYE0CKgAlLIGDasREyIpJoTMaf5RK6zfSdplpwB2DtbawZQRgBVyAKEUAVESRRLBQQpmS1DiauLy9P-RKCSslTJpfbPn3uEWsUbu98fKyqzITZxObHxSJym-ebywjduianUet7PF7vV4ZTGrj2lBVIqNXnbTselG1qDWorUGIqgAo7dME9zY30VWbR-vD-i4c24PpxPUwhziKbp7h8enPdPbJgq-XJczzHsj48A9HB_9Iyr9SaEqKA1i-9bkTqHcj5N3_7y1eP9XJZlP53W3eZ8fPzy9etP-_vjebbeI9D5PANhjBGQUkmIMIdYi6aSENkauz_vQekcFuvstAQ2PtdESKVURSlSYqql1iXWpvMt45P5hS2XnGstOddh6Enz0DTb3oFgO_qUkrfWoDKQ9w0y55JT0ZorGzBMzDi2XQrx229feKKutbtt2_Qu51StLSLWmN2mdey--vzZ0DelVlL44nbXeGi9n5fsrLG-nefAUfNSQGWJ8XzK85JU4bykkuV4nkNKd4-n9w_TKSbnaLtubjfji03L3lDnu43_zetdtrBp3Wb0ji0BOce7sSemLy9Xl4P79nb1919f_e2r3be36403orUAFqnvj-f_-Kf3__ru8af7dH_OCTFIHbfeGHn7ac_M3LrrzfrDpwSQP52mQeCiM59fXyBzypKl_nD_GBW_ejb89c-fpUo_fpz-6cP-_WP8my8vt127HXtS8d4S6SlVVc1F9jkf59N66Lzlq6HXAqiIpAVqrXKO8f3jcT22CNpYU0rNpQqhNU4EKui0RCBwxjbOqkLVGlO2hpgJQBpvG--cZWPJG9SiTIygwIiIpVZDKCKN88SkqtM0szUImHNqnLGWG2dryYSmlFJBT-k4-oGJEYG9W1IOpaIzp-PZuWZ_fDxPy247KBBJGbvWGptzecrxlSIPh8l6h8YsoeSqgniaQ1Q5pfzTx6MQnqZFAUIsIQR0zeNhGVZdzBmqPm2gjTMhp5gye0tEMae0BLSuaAVCFfq4f-e7DZJ2vVtCdtayBWP86XxyzoR5UlBAmedQsqaSnfWAaJiGfiCFNBdE9n1nWkoh1yoiysaq8Ob5ZZoCKCEbEQJEUcvWGWTbeNPasmRjwHgDFYiNIIEaZSTDxnlCBjJkXRVp28H0jdSqgIpkugaNizH5phFF13gylqxZb8cwLyrqW49EpQpZp6pEttRi2bAz3hoiI6jGGmJTkyAbgL8cLdrOL3PIqaaYnqpTxEAAKIDIjCbXKlVCyqJSUilVkCillItOMS0hE3OutYggKSmowmkOQJSL5lJVNeZcsyoIApRSRaGKIFGpOsXgmbzjV9er1dqFDA_7-eFx6rtGmWKM__zjh3_649sqGnPd7cZKVZj3U3r7eHw4xymXh9OckffzSRGWmH_z9ctX11us5T_9y3f_8uPDnCpaU5LmkJJkYmqNPS-JDO-PoR_bkijMM5MQ1VU_MPDYtj0743wI-eEQ2t7awZwDxDlWFUJblbVKP7rVyl3uOlDMWn7_48fDw2QspJq269Wma7Zdd7keQOr-OLeOW2uvNiusuTHGN8Y5Hqxx3jNjySXnKqClCADdHydFOs_Be8eGRODu4cG33lu-vVw3zm07v24bKbWUbJ0l0pzk7uF8ue5QsGETUhQE17jj-ayqtZZffv7aEk0hFJHzaSo5G8Pemb51hNI4m0thIEUtNTeuwVp3u5VhJIBcqoCCAgLZp6UCwfEcO99Yw70zzphQ5Sk17owptSjyPEUQRYRlidba1rsQS4y51mqNmefFGnq6bHnvu6FXkRiTtcZaC4o5ZxFpjBGC1lpiAnnKAnnD6Jqm7RrbuLFtltNEBq3BXTc8u7z4eHfOWfrGZdQ3n-6mmIhZn0hHKk3rxqFhAEKSUp33cQkiag0rwNv3d6K1bXskSjHsz9PdhwOgKUk-f3WzVK0ZV5t-t-v3D4-X2_VXX76kmObT6SHM58fjp3cfRTUvgUoe15tlmsbGff2rL7_5_OXvf__Tb__wJszBWFWhMtWfvfjlfvoUA3W-GcZeKqWUTeutt4f9_v7Dx-fPr4fe__f_7u_HpvFotpv2q9cvSoy_-cUXv_zyWW8Qcm4MlZJH65goFvl4mD7eHbaDr0q-8bGUXDMRNtZseldisZYf93MRRbLe-1o1lVwBvHcKiAAI4LzNNfW-FSlD31xs1jmlzvu-7w_7UxHdbQaV-vJ6uxm7OZY__OEd-ub-cO6vxu_eHd68v29f3LC9_lxFkY2mCDk1jZ8OR-8dEZD9SyAMkLQUJAYQYzjPyRpreY21QJWUIiOISk1pfXmhJWktlo1x1jm3P-7bYfTdmItISbZpVqvduBoJNc3hfJ7Wux0hIEKtst6uh2E1L9PF5WUOS9c0Uuv-_uHy2c3j_eO4WuWUhrEX1JgSATw-3D97_oydkRjjnJrGN41H0NZYBUTVV8-vGSsC5Jyvr3YxLLvNWkF2mx4U57DcXO7Gtt3fP6y23W67Pj4eNper-Xh89vwCRbq-7byJ8zJsW0rVI3jkeDxYAKllOh29oXXfeUN__-tvvn71_M-__9O699988WrsfGvYMRIB5Dysem8MIeVcRcQw5yKAfDyHmnIV6NsmV_nw08MfP-2_eHWx6hoAzlXiFNp1570lxP0yffPyav50XPXd1cXmjz_8tNmMP3_9-od3746H0Pb-7XfvHj7eszNZAYi36x2wSBZRfdKBi2qzWpVUkYxZez1nyZUMGm-tc0-pZFBFz9yvjW3z-aRhgiL5NLmhYWJkLqVoycxUU1aUWkq_2ZQQkExJCRHJO2KPCkRWcnTWIBggLEsybYNVaixEpCKEyoRQAWplBsyqguQMIcaUARUli0J8fACB5XgWEgU8no_kB0RturaWUnIhBO9s0zYICrGcjhN0tEiuubCgqUK1GAWtYTlHt1qnnOuyMFIo8WHad01fsxaVMCfXmcPpzMYKQ4o5S40xhhg3mw0Recfn_fE0H7eb3XwOOUS29uHhVFW26y1qneYplfj116_mU6QKh4fl-ubS_aUFmJbTdK7h9vrF_nhkJibom-Z4mBpvGudQtaYICjVXsv48T61vUWvK6anXmIsgqGerVWqpOWbXdmS4bZo4hSq5b_qqkkptvAdUFFAAAGy8NYCd96vVsIR0c73tW--MKVWRqyVghM3Q5ph3637VNyQS5mXoPGZJc3z5fPvVy9swpc9f31rU_-7nN-uhD2G5GMb7_f3I3KAZuvan794dziWmlGs5HM-21paUQMa-eXK-3Fz11tlSagaxhI03wNx513qnOZ1OYX-aQ5Djkns_fHa9frEbb7bbr1bjzTg834yvb7df3m6_uNm9uhq_vN2ue9c5Y60jIhEFhlOO7_fzm8Pyw8fzb7_f74NWazNjwHw4h5_uHt7uH5dzQMBlru_vgwH4x7959tXV5mc3m1Xjtt5mFUcqRAz6arf6-e1qEAUFEmSCX312cTu6TeecY82FiARFSs1K52X5p-P7nfFXq4GBOFdjGVEAa6xFVP7Ht2_Oc9wOvTV21XVVaooF_yLlBQDIVZAJFFXEWB779nwO3llVudqMKto46y1rksawNwQK-pdrvqrq_hycpa7xTDzPURH1SUMG4K2zTJbJEhMiExIRgXa2h6eOIHOqdY55CrHU0vf9Mk_W2ZurC5QaczVsAMEae56WcehiTinXT6dFEM5TjqUWkFTqw8PpvOTTkpPkAggA1jIxCaLpLJNxBpk4lWQtZ6loGQBiiBmqaXzJGYiACbSi5VJ1vNwZQN_YaX9cYqm5Ljn211squBxPrvdVJacEKogoJYOFcFoMMyhIRdt2FQBVa4Fc1DkrCoZcVWDvyDgAIm_ZWbYOyBlmdlZzFSAtAloZGYwVVeudda6WIiIgbLy3bcuuGS83aUm27yug8Y3re-taUSVrmrbb3VyHJVnnU0qkCoAiYJvGeKvI3nmtgkCGDRMpKCKRZQQAVVAhNoYJUI0x3vAT0aDx3jAZolq0ZPHOIQATFa0AWkrJVRQFiJiJGHKRmHLbeFUY0E4xhVhEaimFyER5ssKxqFSRFKRKZeIlhKXU8zwDoCHXtPz55XB_iPtz_HBKnx7ivCyeLRpC45_wr9vVar0bDsfQD-2nx-n7P316OEw_vP30sMTVxfrd3QMgFhUpZeWbb1-9eLlZAeh__eH9x-Ppx7uHEGoMy-lwBCq7y7VqPR6XtvVIhkFbS2kOBkrX2Jvrm_kUtqN_ddGFWjKWN8fH8-H85k8f373ZhyWAQKnZW5elPr--8Gyb1jBjTfDD27u-76-ut6vWXF5tG9L_7u--_mK7dqB_-O7Dq1fXvXdW6-hoxU60nqfT2LZj30PJpWpVRQBEEIXDNCHb8xKd90RUS1XQInWzGZw1CKy5WIONMVJFQLTC_eOxFmkbX2s9HiYBMN4hUlyiiFhDl-vhatVBlZDzsuSx8845a9gyIahzdj36GGsVySWztTml9ap3DJbtYQpPI5yCoiojdt4hoVT1zhDSPC-nGAWArKlFvCFUiKXWWhGA2T6JJ8jYOSxEhKjeulJr2_lpyYpYqlSVxjkp0vomhAUBkamIOudSKa13SLQsi4CWlH3fPtmCWdGqAqphur25-OLlNQhYy613Iee0JOts17bLHFbrTUrVNw4BU6xPp8in1n7NknNpG_e4P6_Gth9XjHh8PCBzrtU5M65X3dAignENiMZlIsLtxYVz7YuLzXc_fnr709v7j4_LlL_8q9fhFAwxGF6t175v1rttSvLv_9-_JQdLmuMc0dpwmNDyAtNm3V_ejJcXO2Kuqtcvrtp-aFzz4tnz18-fpRzn8_L-3V1rzdevb3_9zRe9ty-fXQyODNB0mgnIAM0pXa0HRsiox3OeprNzFtHc7w-C6n2jWq52AwoAQC5QVNnakLMqKaJoZaKnmtm6bQ1jCvH66qLmQoyrrif9yxn_8fG4LMk1LszBOzN0_mF_Pp7Cp4c9Wfuf__juMC_Ndvj05v4Pv_uB_bMvq4Lmyt4imzLnq6-_Pb77CdlVVUQiMgCKhhkpxYKGwRAo1FIJ0FgCVRRw3uVS4hyaYdBaUgxt11lnvG_Pp0nKYpxLKXdjD4TH_T7Fcvni1hCd5sPxMFnvGt8Akm-9dW467Int_ccPTTtUqJZNhSfJI9aSLy52d_vH7TiGZa65Esnu9to7g0zbTQ-qhMwIq7EF0PV6dIbXq3H_-DB0zdiP0zLv1quQKypgzV-_fjms1vMcvKOmaRprm8E_frjfbrfOmcvNuF6P3rGC5BgvLy5MYy_Xa1BpWvPLX_3i1RcvHt-9_fKr1893q4746mLj7F-ecWtwOoehbYsKqvjGzkswhoAQmEMqFcBb7xp3OC-2Ne_uj7_6-saga7supDy0HhlXQ-OJ2LnjFN6_v2Nn_8sffmoMvX3_cWjbpeQvvv4SoN4-vz0c58fT6ebZs1Ri23aSgwjGEC6uLg53j5b5fJzTEnzbunGc7w6asumsCtRU_WpkBLI-TucSQrveidB02Buk7cVFzXOcppyS7Yaac6mZCMlwLRGRVJB9q6qiKiWx8bWC8Y6MrXlRqd4wgBGtNUcRZYMAaohFRIoQM5AiEXlTS5KibhgVNS3RWUtAIhCWZfvs9v79ByRAFIOWWhdTEQWVCLUiuRTKdty0Fqd0PodcC1QpXEVCeSqiGdMvacZcfOem02PNxQFgqVXEN22RmnIAxJSLs3ZsmxoriorIZuzfvv148_z5_ae715e352VJMRrnQgzeWeddSTks06--uF2KHM7nH_784dmrm-Nh-eL1F6fjnoFPxzMp7K6uT_P5cLhrfItoYowhZtdZyUoRf7G9OC3FGJxjjLkY63JYVv2QQjLWnqelbfxymhvXVKlEyMwlZ2-sVhnaLsaQc8la2RAJejZsuUi9P-z3j-dXn-1qqS1z27sUCma5vli_uF7dbLeosOkb37rGOUBMuTrD6_Xw_HJctU1KRQGMMZvt6hyTI7hpWkdEzvnWhhA2XQOs02mal2C9HVpPBhlFVIgxqNZaK5NrrBTcp9g4u6TokIQwhOSdY0CUag2tvG1aHhtPSI40zTEfQ1hC62zrXMfsDVORUpSBQshgbMzw0_58yPX3n-b_-K_v394v-3NCa4U5iZymZYppOi3zPNeSsFJM9Xozvrrob1f2anCshIiJqBhzSvXH-8M-xJTyxa677Lu8hP_bh5-uvN-27nLVdEYbY7wxDRlGKjVPKaM1AlJr-bzbdq5zTBZrJp2m-dN5Oat-mpbvP-1H14xDe7kdoQKoqoIx_JdkiGottYo-Fa5KTt4YERQVImi9V1XU2nrjiRrHDJpzIqaUCjMDYSoKCEPXYoUYArMNKXtnQdUYJgDRYsioqiFURYOISKJSRY3BlOopxJSzAvTeA6izdhz6GGLOEqtYwylX1zQAmoo4648xFYRKdJzD42EKFY7npYpGgcfDia0_nAMQi2IlEgFrDQBaQ7kUUSBVRV6W-JctdchxiUgoWRD1vD9WAbaGQQxQ2w0FayqlHbqSshYwxoXlrKpkzcX19rxfdreb6ThPp8WvbJkTCLA1QIqA5Kz3ZgkZDSEjEhITCqii9W1J1fmGnENjkNiP_TxHIKpFARSUFIjYKTjfrgQgJGTnDRsyDbC1vkMG522pioaZrLVGFaESO-tcqwiA1RojuSio9V7ZKEDTtMRYi7BlZiZnQNVYC6id65QUEQGg61sAspYM2actsqiy5SxC5NASACBgqSqERaSKoKF5DohQSw2hiAACh5hVqjM0xwQIVcp5Dqq4xJRTrUXIoACoSutNSIkMs7FsABVDzGnW85RAsWntkjJbOse8n-MU4sfD8X4_PUwlStEElfh4nudYl5qOc_rx7lAV7s7n4zQBoGO6Xa9__vxma-3dEv_5x49_-Hj_GGoqUKGq1vv9Yc5yCOG4n4GIwaY5GkHRBKi73WitLTWCpaF3f3p39-bt4af3H6dDMlo_-_IFgY6de_b1tuubKnB1s3IdnvZnTXIOmY0LS2oNvrgcGuNqWv7m61d__dmz1tjHJQpD25jdMA6WrzdrqfX_-d2__O2XXzTWxpidNaWWouIcGzbAGAtURXbonQshHac5FbHGqtRV34UYrQMgElFVXkKM8ckM5dlySsU3TvEvgvmYS1G9vlhfjEOOSUVLLa23zIwIQ-8ba3LK1tqU6xN03zA7Z7rWGtXWuSL6eJgQQRWAgIlb3xrLh_3ZOquqKloVgU1OsWEGhSXmWPI8z41vapVUi_fOOBdDKKWmJVhrc0nO22WO6902hOUJIuQMG29TToCkqJZQQQG0lAqKQJhKvb5Y16qkkJYQU5Jc-6EjgPU47lbj2HgiTjkB6HlarCU0puTsnF9idI6RyOATMg0RoZQiWl3japWSgejJLFZSKsxuXrJzbNgeD2dCzqXOy1JUulXrusY2Tdu5H398v5SCjk_70xf_-Js3v__-eIrCth-6ftX4pnl4PMypNoMLOadUcq6rXWe9bUaTYhRhtu3-cS4qxlkkE3O5udrMca4prlfdL7_6bNuaf_j1z1_fXLQG140lLZfrsW-avmnY0nrsnHfWMqO-_Xiosdin4ECMTefH1VBSGvt2dEYrgOGiNeYyhySIc4wigkwlV2Y0hgkxprjbriyTszbnXHOWAtOSnmBhAsqgKadlmpeYUHgKxVga1uPd6bw_LN__9D6K_PDpgWHzebf-XGWqNXtvU6xaF-tcFbDeIyIaInbz9ImpYccKT-r6SkrMIjEBkCpIUTLGOBfmc81VSk5LMNZWqW3TnU7n69vLfrV-fHhQLSmmcTXevf-4u71e5nkY1jVGBFIAtlZQltOp7bpuPdRSVer2Yjvtz9uL9XSa2rZ5PO434zjPs2MPWhvf5pLZuGWefGMdc1yCVG2ccda23t4_PlgG750BDjFsN6N1NpcytK5vXAFJKW9WA6O4xlepQ9f7xjlr7_bnoW-7pnn_7m6zW6-GAbRIKY658fbXv_xmOe8hhn_4zW-ux2bl_e3ttvWcl-S9KyHcHw4Xm5WogMpq7ENMj8cDG5OyxFKqABmSUmOpIRTj2VlsXOtdE3M9nY4_vnk_NP6n93dkcOz603Ea2iYrfjod7qepdc3t7cXu8vKn7386x3Q8HM8x9kN_etgPq_Hx08Pu8iYs8_H-iCTtulXRtu9BhKxPKQMqd60mASAFQOaqUHMx1tYgx-m0ef4KtcwfPhAb37c1JRCtmgHQGE4hEhGTkSrEptTK3iKQCiEIswFgJCwpyhRyLWitcZ3kyJbqsgAgkiEEQFQGYCxVRQVVQTClZEbLWeISEBUAFaXUwuxrDIYwh9yMm37dpvOsSZTN669e5mWZz_Nq7L1vUVVTNsbEXOZlrrXmWlULioooAlq0ZYkIKgWQKEMhYm_ddDx4NGnOJICK5_MZyaTlLKUc9w_M_OH-o7VtiKkbWkb6-OEjs9EK8xLe3x82u1GzhJjevLnLku4-fkSgD58-eNPc749zSb_46qt4PpW8LCGO6xFFp2UJ55kAGUmIjCGokHJCgVzVNL61XlLNRWKI67FPMTP7musTS_50mpVQFaRKrhEAU0retwhaaxlXI1ZBkOM5zimtVn3KerkefN8fztPxHFIqBMqO10N_c7u5WQ3IfLnuB4KVNa1z24v-H379jaYKRk5zGFq3xOwaXy1Y4pTScT_FLL7vXWtTLCnEcRyUOEVlg9MSilQtsNRUcsYCYQ4IEGOMMW2GzjDlUqPqwpXIhKVe7Jpt3xCoWm5Xvm1aJDIOgfHusLw7nCaB9_vjIdZPp-nHD_tU6v3jsj8t0xKF8fMvr6gzWaqICopWqFVTKGyoafjL2-3lykmBAhxAf_p4__3d4e3d_t3j4biUVPTbFxe_fHbx9c3aqHoy__bF5WXfds4Tg2NcQvHG5VqeuDCJzfv7uxDyktKmbwhQVU4h3eX05jj98bQPWWMu1nLjnQHAUpkIUIkQGCWLcwZUS9VYChGWXLxzhhlAEdQaskxaa-eMYUIR50xONZWiSNYZAFimQIiNd6gKpbJhEUGkCsIE3hgE8MYyE2q1xqooAlSUEJJxVgFjzqqEhGxw1fcxxM5bY7hW-Onjg7dWiVChVEUCAFhSSkWCyDlKrBhyPk-zAC-lGu9DwUXqkqSKVlRARqRSCoCmUosIIoMqIiLjaZ6REASIMKeIKiDgm76UMm77eJwhi2lYLKdQJScUZWbnPVtOSz7tTyXXUuVwdwSRcHxc9sccogCXos57dui8Y7LAJkttu75GXe02UhOARUZRqVWRLXtvrSfvkJ6uIk_Pm306uANSFQVr0XliQ0RknLEGFaWC8a7pm6e-liCaprGNRUAgdIZjiDmWbrXqxzHkXKswUQ2ZDbvWk2F2bIx56kQ55woWaw2zQSLnXBVBUVXQqiqqyFWqKiCKMQQi1jLyE4tdSsoppKbxDGgsK2FVVRUkzSkvubrGKEMI2bY-pcQASFiypJRjLAbtMqdSZclSSjJsckwGwTOWWpEJCRV1Osc5LB-P-2XJCfjffn35cZrSkvcpnJbl491hyuk855ALEpVaD8eDx2Y7jr95-fx2u15y-v_8_rvf_vTm_hznLO_f3aOiBUTBxvvWdKXAzcW6WzVctXX8_GrVNfbbr24Gb6YlTEuYUtg_Tj-9_aiVcoH1trtcr0SViVHLdI7D0Ky7FtT89Kf7moo1cHWxFa27TXex7X_9-TYkgZj-j__u7zfOz9P0w08fo5Ttaswx3uzWLdXDfv-3X3zmia0xoFq0zEsOqbbepCRsTawyL4GtfXg85lp85xEJkZg41pxTEuCUihKJiCjGWp1v-pVbUjnG3HrjnR-6NqYUchn75uZiQFXnDTKogNS_0HgQNIXc901jDYKGWIjZsgkhjl3rrWXmh8PJWFekrFdrUF2vR8MgVdhaY6kqzjmHnIoURibinHIRLalU0arijBGB1rvlHIyxBGCYpGRjHCKVKiWXJ1yYd84yadFpmq0xAEDIJRbrrIrs1uM8LaQAiE-a4VW_ItGby20poXV-Owy3FxsiLCDzHJaQ_vKXfQ7A9mF_9N6PTZMl51xiTqnUWmqu6ho3zSGlAqyA0PZtkioAyxx86y3ZJWZmM65d03jfeGICxSXk8-l8npbH_WH_sD89nipoOO9VzfpivbnYjJthCfGwPy452rZ5CkqwtWVRb4mYn13d1KLeOVFgY7bXW2NtjfXmYudRlul0sds8u7y43q2-_vzV5WagnOMyj0MPQDGmUwgxFUBc9R0CPh72__rnD_vTtB663358-Pr1s9E3l-tumkPOedPb1jqpQoyxSowl5AxAUqVWIQAitNaMXWsJ1qu-984a8-Z-z4xD3xOT8-58XlShIgxN88-__9evXj_bbnZsKZYUin53d3icwv3-WBT3h_DxMLG__TKlA5OKVGbHRLVkUEypqmRmo4AglV2nufquAwIR0CrOO6WnJKGy4ycfCQDWktAQaDXWGMPz-byE6fOvfv72p7dXl7u27VbD-Hg4LWF58dnLw-O-Xw0kYK2dl6UWmOdJtG6vr-M0p1C_-NU33vKHt59-_Y-__td_-uPuYtN0rvFN1WrYvHjxIobFWz7dPzZMXdNIqZv1YAyvhtZ6u12Nf_jTd5ux78cBCDfrwTjbeNcNjbdmPXgl_PDh7uXz6zSHm5vLHPPV5e7-_v5yu3EWr68uhsZi1mevbozWlsk79_UXr6-3q9XYWpBXL1-8fHH1T__TP3_z2e26bRDUIDlvEYQAhr4lJESsIoYppmyIWt-kXFprY8wxJmtIaq0Aj3cHYufIOIZaS1zS43z66uvPNsP6zx_uzwVqzfspdMwvdhef3dxcbTaf9vf7Y_wv__SvL55df_p4P7T9HPK8ZNd0orCcTkoQp3PTdKuLzTIty5zW2xV7E89TmJIhcKteRQFVAJBIqjDS-sVzVQVr1ptdYaohgioxKcGyP7C3bCwbzim5ptXy9N0DUDTOGksl55pTO45LiIYdoCARlEKMRKaExT8tyRSMsyUXIAAiVcUnDedTuiGI5ghEIMrWxGkitu3lZtmf0ZimN3k5e26fPX-Raz3P8fFx77qmsX45xdvr6ximPEVkI6g5LFAqlmrRlJTc2ILUGqMl65w7nyfXORHpXA9Sh34FFVQKN7akUqGejydgZrJhWbzzqlBKPB3OORVDakzz07sPaqTkYtsWDJ6mJcRqDKBIyakbx3maDZMlLFKnefrNz79ewmKtk6Jj1yvAx0_3dnDe-LQUAuyG_nReilF2ti7VMHRtd5qXtm9CSoYtaCXGWnKIAZlqqVXTzWY1TRkQYiq55M1msGynaSoIxjrRWnI5xdh0zTlVNNh4D1BZhC2lJe62K1KoorfXa6hiUL2xw9hZJpE6jv7ZqhudXU4zG3deQt_2IcQSBRlXq0FViKlt-WI9osiz1r5-tr3ZdX03rBq_6Ryq-exiGBr_zYvtum-Y7Iub1crw57ebnz-_eLbuL9rm9arph3Y-5zeP87HI3cf5HHOs9afH829_enz_adrP6TDF4zQfj6EKxKpSCxItMQyjv7xascCqs29-eDhPYT8t-_PC3mw24-fPx7_5-rJv-pPgm7ncS_n-cPjT_jBV7cl2XfPl1fp_-MXzX96ON4P1BDkXZmwMKoEAGsIccwy5aSwgzjklwP0yl1w6wxd91ztTBEIt3y_zbx8Pd3PIqQyNR4Vc6vVuLfNyu1sbMgLKxCnnkoszJqQiKlme3lEwlp1lJKy5WGtKKd66vve1ZsfETERWVLNWZ3gJS9-2qGjZECgpIJOIgGIpFVG6trHWggIRkSIzKyohFJUYk7EuV5mWUJ8QDwQxl23XAZFDOi7pMIXVeshVU8wKlGsh5sNpOcVyOJ6XrPtYphDBmIpwOJ0EcclSqhaFXGqIMYSoCqJSqoClnEtc0pONLmXJIg8Px6ZpgTmcT2F_IiJvPZI2XXveH6-unk_zFOYIxM47BEmlWHZYcymCRNvd6u2f_sxs26sxH851idYAsvqWNaWaqzHWGPJdI8pSyzAO_bpTxZjE921FNdbIE6N0u0F26-fbYT2EubBzoEDOIWEVEDDN0BEa453xXpBEqVZgY5uuyTHnUjSLsU4BFNAYowRVtaqKVN-0VcU33nrHZLq2E1TLpAiG2TgrqrVW5z0SpVyJmRAN2ydthHfOW2ctKT4xWtAQe2etMcawAqZcQcQ7o4C99yQ4Wr8_TSqqACKSQn6a3mquBPgEbmI2iFhzRUQRLanmmm1rs5QUkgU8neYiFIsoYhZRFagwLXE79AgYS3oIS1X-l3f3YcqPy_T-8ThNKVI9n2OULIB_wZYq_8PPnn92uZok_Y__9Kf_-t2PaakxQYxJcmIUBekN16xXl-tLh9tN55hqLM837tnV4CxPUd5_Ov7pz_fHw7TZraRILUmybC7bbnCdc1HrtCxSKwBu1isL7XG_PLvZXF30X3x1_ex6zaDrfuyJagyHubS9-9svbr9-fiMhzzG7xlxshrZth8auWm-Zu7FnRgYKMQHInHIspW2dewocIqRYfetEAQGddbUAEStijHkKgdnvj-dcJRctVYrocc7MeD7Gw7Ssu8Y7Ozh3tz9Lqf3QSsyddalU4wgAaxHDBlC9ZQBw3nljahJCJkOioFrXQ-etEcGqWgFKKd04pBg71xCCAYxFcs5ZIKRSSkWCVLJ3Zp4DG7OExITErAKiEJfwNHMqAhEZa0sptrGGOaecc7HWOGfTkgjAMLu2WcJirY1LcL4BlaZrz8fJNw2ikiFU7LoWRFBkGPpPj6fPX99cb9eWKCwBmJeQkVAUS5GQSlXxfa8K-8NxmhZnXam1SgVEspxLBcAPD3cgFpnnKcSQkaDt21qLJXYNE2OsNSVJIcYl7U_nZVoc-fPpnHMF1c2uHzajVHTO9V3fen7_4yfJ6lvfdv5wPOUYTx8PmGvnbONNjmn_eH4KW1pvqogobMZxXA_M8OHjB2PNP_71V1_c7p7vNje7tWdeYmKLXdswwN1-vz-cvTN906WcGsfetbHWcWj7xv769StnOSzphzcfFYkILodOq9RaQinzEp0xf1lGECJoDBEJLrdra4xjaq1V0dN56RrbNq1INcyCkKt8ut9vt6MBPC_5ard5OM3n5ZRE7-b5j28-nUI5Tmdu7N3Dw8V2ZHfzRSkCpRJhnGc2bNhwN7JjJsJSrTUlFINsjUFjtRbJ1XgHgMxMyIBP3hhsOh-WxTqXQ25WY5kCoEitKvxw9_7m9ub733_fDJ1x3jnnrTsd9tfPnu8_3VcR523rXdN5qFKKIiozQ62n_QMh376-bpxZDd18mj59fPz2r36mIioa0rLZjfv9abtdk7XLXDa7TUWppTrGx4dz1zeb7ap37ePjabsddpfrEuLQ-5il5nK97WuVlt3pOK0v1g-fPq36cQ7TxfoiztPrly9iXFSkNS7l8Oz2Osc4DgNDxiIXq753TmPovf3F61fXm8EQSqnIBCj2KSUlFRVEhABUARCYOeUCIrmUImK9AwQlyim7tgEFz_bHj3e3V9sQ49V2F0I-TwvGYpw57A8_fvj4H3773fXFaopljtN2e_37P_zxy88_e__u3bAa0diP7z613n311ZeHx4fHu0dnqFZtu-bDm49MXFNsulak-qFph0FrjccZGA25tMRaxTYeEOcplpLXm3HYXQGZEoKxdpkWAGSmmnPO2Q8rVZVa2VqVis6w8aCiRMYYKSXFhYgBBMnkMJMqGqOAgFRDZgJAfcJeaBVUgCKIICK5VkOMKFgVqnLTimTfdyDA1rE1WgtIjof7w7tP_e6i3Y0V9Cmz27ieQFXrxWZVRfJ5Xs7npulqqqRonJMkCHXseqtyfpzQMgJgxZISVmn6dppnY20IU41STUVRBQkx5RzHrpuOJ7K2qrrGzedj43ok7TfDeX9yrXXWLrEo8fmwb_tOstSYTePW_er-_v1qs17mVCpe7XZO5Xg45lSMd0R4MfaHj0sMoV-N0zKzJ9vaOGWUsuobwxyectigKaUcwzKHpnHOuBQTsyGyIRVh8t6knAF0Cckay0TNsEo5Ji2gpAQ1g-3bJYb7u8N5iqpUFWPJDfv9wzEXJe9CSs7ws9uLcdWVXKTkcRja1p9DnI9T03hVQoAiIgSS6g93D9t-PE2zs_Y0L8cQ3314vJtOueJ-Ctw4UNnu-qttq0bXQ9d74625uexXzj3O84f707t3j2_OSwF4exc-PU6PcYEkqHXVc8r54RCWeS45xJQNgaiGGNC7xvtDCJYwTXnVt6u-vbs7UMlIDkmwdV3rV6uNdU2bsmb6l59O_-HtgYGfr1Yv2v5q6P7dNy___uXN_-4XL3_54uKrqzVotYzncDZgRCsqMWFN1Vk2RExAjFhgyvWH_b5pm2kJF8NoyYjkpcofD4f3y-k-x1rEWaeIc8ye-LJvGsRXl-siUrM-xbe0KjE9KTljLrkW75xo9dY4ZpUqqkTQe9c2vuZUoLbWWbZVcYrp_0_yZGAEAQBQLVANc6k1l8KWGdHh0z8JYkJ9WrojPDnkgVlEl5gUwPlGVb0x664zhsO8pCLnOTWN986QoVwwicQnWXXIShSrTLkuFUIu7z89Hqf44-E8Nl0RnGNKWZcQRRFVU83P19spJwTIqRpjappVQQUFCoKmuEgIaZ4soeYynU7daiBkEYzhjKQpZEO8TEu_W_XjICEuMTBRrqXp-2We276x3i2niaBACH3n03FfU-HWEmLNpRStVZpxtN40vhEgYLbe96sVgXO-cePg-0HJ9t0ISmisMrNxzre2G8k2bByhKwKK1o296wc2xhprnOkHv0xLmoJtLZGKoO97RCk5A3GpBQVzLqgqqoRExCLiXMPWSlVVtcYCgmsdMbMl46yIWGeZ1BtTS61FiIhIQYHIWLYqUopmkZRrzJJyIeaqxRsfY3ziTTFjiGleEhKKQpwjW5JaFSoxCQKAEKmqAjISWm8BsRZJqYKIlEoGiDWGFFM6pwAKIUVVOC_Bd3YcekTXmFrnOIdZgeYllYwMRpLWLLWitfbr1xff3t5Ywz8dHv_lu7fvHx6kgLGuW3VxLjXLZt02aNcrvl4Pr57vVmvnPMZau67LgP_znx7_9PZQQ2z6ZnfZrS66ZYrnYxDRcbPtfGNFXWPTkmMoY2tvLtaX6xE1_fKb51et23QDnOaQ6v48pSyHh6Vr7c-_eL1dNX_71asGCKS-u9sPvfWNR1DH1FvjLFephhGJmPlwnOeYVKr3HhFSLsfDzNZUgVRrKXqaF2RKpYSlACkTnc-zcYadCSkrQBZKkgCxijrHpYphnkNCg9ZZg9i6ZomRmRSl1GrYMpOUjAgiapnXY5dyQaYnBhETOzbERkViKgpKyLUqM3pvmUgBQ65F5HCejPVPg-B6tS65xFTRcIopV8mlPH95k-d4cblVFe87BTEGQaRWsUyMxIacNSWmy5vd0Lj1etUPXRXp2jantLvYlpQ3V32MxTVN1xnfOmZnnTvtj23jbq53Vcrzm4vdatj2jWQRhVJUVQFwCvn-_Ng2fQUFwFJKWAIiZ8lsKVestaZQnoZJQ6Zv3TIvTDBu-2UpNeci0q3ah8MRamVr52mWkrm3MRVDmJYYQwRG1_qh6__4x_vVyntjfWM_vH_0nrYX4zIHzcV1DZPbbobWs22Ma32uQAyri1Uz9mGad6vt-mK3WvXrtlGRfuh_9c3rtW8k1OvrrSE5TdEZVoDGmKry47uHzdj2fX84HUPObCiVulmNV5fbGOtu7GIq-3lpm0aNXF9sBsOMFFMmy6Xq8TwZ5xTRGmakYd031qxbT4hUAVEsUVWtRWoVQro7zH9-_ymXAoDjMDweZuddrPLTm0_3c_n-bv_HN3cPh3MGOJ5P47ofmv7Dj3es68_YOZCKUoxqrZWIBJltU2uutQKoazoEzSVNx5Oq2MYTqHWGDKooW0Y2jfchBCDudldpmdvWj1e75XiqoqvNbo5lPh-vnl_P03mZwnq3tmxW69WP3__47NWLpu1qSa7xOSZA6Pve-QZK3F1faS1d05IxY9PnUoeGn3_24sOPb077uN0Ov_7q6-9_evfll68YEQBfPduGZXbsUggp5FevL51zmOv1xXB5sUGVh48PnSPHLKIXwzidzi9eXBLz7c0mhWW7Hhnk5vZSS-5bP3bNNJ2Hrrm63Nx9_IigvTfLNI2t75z5-Onx85fPwPDPv3626hpDiqJkbVwWa02VGkMsWdgyARlrAQgRc6ls3GmemE3IRQGmKR6Ok_V-WmJVyTn3m6GW0jiPxsQl_XT_8PrVMyD-7e9_-NtfffvLz56D1JBC23bfv_tgGB7ef5yW-LNvv_if_vN_vbq-7Nq-ac3xdBatTd_sH-Z-1dx-9vJ4Prq-NcTeW2s5x8LGEjM3rTHU7rbT-dT1g2YZLjbG8nKa0Xi07XR6MMbWWrTWJ1Sd5EqEygQAIgpaEREYkEwuldkaSyVERqpQ2VpQEZUck3GOiIpUZETRGrNKRTb69BoQ0lNImQCyonGAUEpGQCBTS7HOG98gMwKgCFI5PNxtrq-ta0uqmEuNwXhLyHOoX335NakU0FxKSqkokmXvnSQNS7q4vpqXKcUIgHFZxsvxfJoFsFv3x2ly1oYSLbmkIYeMINZzTdEYp6BoWUEVcD6ekYyUcPvi-Yc3H8Lp2LWOarUGl_MCFVhqnE79pnfePjze991ACO_evvurn31TAX569zaJGjZgjetdLpJqIksx4zCMKlJSFVIA9tYRgQLUWgnkSeKrqpZNCMk6o7WowHoYngDzxtLh8TDNszW2H8eSSmNtDGm93k4hWraN91LLcp6Z-fEwj12zWfXrVeMMDZ3r-6ZMYQoREeYQksD7j4-h1OOUU9UIsoRSBI5T-OnT_c1mBJXGuOM83T6_OZ3mmMvhGM5L2B-WEPN5Dj-8fdyfwtuH4_uP-z-8vb_bz797d_f24QBsqHGms33XxlzJmnHwzlrnWBAtuWPJCvUhFijVWHO5HgTAsv3N1y_--rPtxWZ4cbl6ebO5ebF2raaKXe-MZ-say02tucf69cr8zeurm8v1MHT_p293__az4RdX45cb83LT3nbsjfeEUgAJQTALINjGsnfsrVUEZkSLMWdFapw753ofQ87RAF4PAzPFFP7leHxznpdcKrJHZks5LFeDX3fm9apdO_ZEjCSCAIgMT8LmUqSW7JxDhaE1BsgQPdUD5mU21vRNSwQqQoxSijMeAHPRIsJIItU727amVq2pKuIToBCIQMFbfAqmM6gxhhARUVFrqTllYktEqRZCIkONY2ds6zwhpVK8YbauCEzLcpriaSkh5_McisI0JzRUKpxTykDHEHMqZAwZ2Ax9LhJKCbkuMRFITtn7JsTCzhSpKUsOKYa4TNGMnliLwPnxbAynOaQlVi3eEUgiZOMbAVWF-4fTajMSklTox8EaCCE-3r8rT3h0Y0CUrDnfHzRlqBFqDceTYRPmhCghBTGUgg7rLi7Ztd45y8jGOjbsvI25tuPwlBW21o6rvubKxrnGAxCyI-tBcXt96YcBjHV9C0RhScN23Y7D0Hcp5tVmbbyfTzMokOGSqmsaJCylMllEMA7btvFtJ6IgkFNOMRGxddYwFRGp1fuGjQFRBQAia50KCIg1iETAWouIQCkipRrjU61VdJ6CSG28D9MkQFVqriWJVJGiCooCKlJRQQFTqCkWZkqpqIqKhiVWgVyrNabmbJir5Ce8c5GCRKXodddNNZWiqeRSlByf54xCl42Vio1zDGZedOz9qmtIcRib7c1wsR1vr4Z162-G7hzLP__4oYSaopzO1TsviuPK_fXXz9q-vVq1r28vn19fPBs3f3q3_-nt6Q_vzylJa-x5zhdjd_Oi2-1GtHye4_7uGFLUWtu-64cWiFddO03ly9vd188vfvn18-fbwXtzuRrIcVT54d2HN4f9fj-fl_rZ68vXLy9ub1cseWjNty9vLaGq-MZorc756TzdXqxJQLQuU_BtE2KOVUKuzjpiDkvwzGiYvI25TksC4qr1MMeU6xwLEg-dL7VOc6oqperlsNmH5fEw1VKIOKQ89h0AaFVQHFpvrZGCRaoQ7M9zKcryRHlRFQmprLrWMj9lWJnwqf3FjKVUZzgjxJSdt7XUIkrIzlrLptSKjFUVgJa4KMgyhafTn298CJGRay0vn113lvuuc8aIwn6_d8YSKADmlPqhZyJjOMd8db3TIn3XA2itMh1OOebVepVDNIYd2xjCuu_WQ19SneeZVHZDO3RNKqXv_WpcNYZJGf6yg4CUS8oypTR0XX3i2cvTsVEQqSRJRXMup3lhY1RARNumOU3LMPRzKoafeMJUVXLJxppUawixxOpsMx2X43FhVVTc7fplSXFJbe_Xm65bdYI0nZe-bwV1Oc-Mpu_s6TBbb4fdbprOaY7IxrfWNU2YE4IhhH7sh9anOTDUzvCzq21raLce3DgcHg8_frgbuoZQx75tGUNKu_Ww3qzGrhu6rmmakBKRaY3NuaBIUQCBh2mOOew2w6btPJKgAmhRBQQVTCX3TcOAXeO8MX3XeDJD0xCBZ465HOZFAJjt_WH66dOjd8b7znlHlvrB3d2f_vWHd4HNTw_zp_O0n6ZTmEtOYO37u_Orm6ufPbtic_MNIOoyP1lanxruoOq7JqdUUhYpzvtcs_HWOLauKTlLrilV23pACFNg5LYfgBURSorWcJoDG6taiREMDUPvu-58PJYiIUUt-XyOF9cXztm4zFIrqpQYj_vjsOqMI_M097D6xl9fbfcPj0M_PD7uX798Pp3Obd9_9vnNcf-4Pzz-zV___He_-_Or20vyOva-girI0DZV66rzcwqX27ECzcvivR9X_Th00xxeXF8CVmedsQ5AvYWb3TaV3LDpGi8pkOhuu1qmcLPdhpR22_XHj3e3F5vG2YvNmhF-8c1nq7W_GQZNpXdWq1Yp1rAilpxBQEEFJJcC-hQi5fk8VdDTee67rqoSoiXOpRrDiipVRaFprJTS-DbEeLHpq8Ju6EXg8XTs--63f_z-13_9s-_eflyvVh_ev7vYrT_cHb7-9utvf_2ztz--E-ab24vVOP7uf_4n702pOqwaQpWU7-8fiCmGIHMIy5JCPh1OZJQIpvP0hA5zXe9bz94s09kNI6I5Haf1Z7eeeX9331hbUi1ZmIGItBRkrqIgAgqgyszEDFLTNAOoc5aApBTNwfhRVSRlArVNj2w0FaiByRBiFRFFImBE_AsdiEEFpQACsqk1W-eZtMRiG4da83IGAVGVEu9-fE--X1-u-n7tGn_14prAfP_j-4f9fj20u6vd8TyBKJHWXJxxAiKiRZUNay0MGNLCjYmiarhU9dbnOFMq3tmSMiQ1TMunU385qGBKqWmta21eklR1zpdaT_Nps14vpxBjdM7ZtoGieQ7D0NZSD-flxctXaYnzfOraNio_hmUcurZrc86NNSpStUqOm9WAAlUppNA2bnB8PExLCk3jGNEbBADJpTFWai21EpH3PsZkiIGgQG1dk0uWVGvNjPS4PxJZJnLebi82IpkJc8rzOZRSx-1gWrpZrwiFsDaOHZHGEqdgvJum5fHxWKTWVGqV0zHkWnzjVqs-looEbPhyPTSOiQhVhfA0BajaDe7rL65LZibebDpnuDPkGa82q8v12LDZrJvL9bgbWmrIAH7306fz6UQiUxaL-OF0krQwwdDw5Wr111_e_Opm-2--efGrz28_u1rv2vabFxeDN8tclhBFa01y_7DUVLfrzhsjc7oczZeX7f_q9favXq5uNl1VWLX41bUR0JDkieQiQBYJCJlsroWMnZZQRK0BsqYAgELRp36vHlKOWb-_e3hzt_eWx7a7HXvP9O54-OHhcL8snW9iyVXBGUrLcrFutl07Mmcyh2MsRYC5Fg05K-AppM7_hfmIqu4vjI4IhIRcSh7GzjvrmEGfFJTFuYYAVbQAIKmxJufYez9P0RCTM9ZQLppFQEABrCFVYHqiIaAolJL_kswlFpVcqoIay7nkwfsnzEiIiZiYMVWdczlOIaskeeqRIgg8HhYlOC45SWlad_9wVpBaVJC6wZ9O4TQtyHQ-TqXULIiOCDCHtJSynBeoBSwYNh_fPcZSwhxrSSXnZV4MUyGZD2et1XZdrWqsAZW-63MNJUVr7Dj25_PEjWe2jTECogigWnMuMUiMUqLMs_W21iwlS47xvNiLHorWkgEIRIhRVYioaVu2PO42qVTfNL5rutXIhru-j7mwc67rwFhA7Narph_bceg324xovbdN4xpfVEUAAJIoArVdY50zTFBLPB1zykhcq6SQuHHAuIRSQ8il2qZhQ4pgGQ2ybxtjLKgQkgL41jFTSWUOcS7Je1dy1QqmdVKh5IKGcinGGkJyjWdmEHDejUMjginVeZ6t8zHGEpMiGEIVraUSAzGejxMZG2KRUtEwECBCLk-XIdEKKVfnGAQ-PZ6q1KnUdefPcwJRQVzOEQydyvLjp2mwzlli5tvLlSi0zocIFz1frPsXz9a2qif-84f3v_3uvZZsm4aZV2M3dP75s3U4zofHfZnT_jjt98v-FH3f7Pr--YvNdedur8YvLzaL1KFvP36aDvvjtF9yyiAVVa2xQ-9Y6_N1f3sx_uzV9W5sm9Y45BBLqMJs__z-_e_ffvjT93e73ebFzcWrV5eDd3lO0_5cU20Iv7y9gKpoVEGdsSWV68sVq1SRkDM7E2NeYgYiBSy1ImEVHTqvIDHpw3E-LTErKBljTZYnnZ8hAlE4z6GUPIWMjq1jAui7bprDMLSuhbDU8xyO07LENOcSUllqLkVqVcMESMZZZG0aQ0jeGxVki7nUOURjGQFzLvvjWQBizgI4x4xExlhRYdScUxW1jU85V5GaS621bz0Cet8gIyGhgm9sx9aQ2fTDh7u7EAMTEULbtuuxVUQCbRtrGL21jkiBDJtlme_uHkQVrQkpe-t77xEAKgxd-ySmcIaHrmM2EvJutyHArrFj2zJIUV2mmItIrRWU2dSquVY2HGM-nM5MppTinFGQ03liRBFhpmlZGmeMY4OwWQ-nc6hFkCAsqQpWUUWYpsSGU82hpMbbnIKgYONE9PJyrVW7xjvvD8eZEE77PQLHEFWkCnZNw4KyJFAZtyvXuBDT7uKyXw2Xm_HZ9UVIUbHO5zM714_9-Tgp2mbo4rwsy6K1imIVuTsczyEq8u3VhWUKMWqtBHA4hfvHx3OIUqrzLoS0P5yWUrz3jDo65y0_JUVEnqajNA593zWMmGIuVUix8w5RCUGqnJZlP8e-67LKv37_YbsdrG-zVFF4--7j775_v3882XVnm_GHd-9LiufTMc4Ls_31r3_9v_-bb19fbUeLPHz7v2a_LulsjBIRsa2qiCZnaTdjOJ9838Tj3I695KqiouJbz5ZrFUAoqbi-RWTjm5xjyYUs15AccwrzzauXaVmWObRdP6x2bdOKSDifUOXJFL2kcNwfr24vc4gphm7s5qUMw-rliy-knLDWkJbV2CGRa-zQ-ZwW58x8OF7cbkhpnoNzdj30KUZmgwCpiEeyzjjDDdPD3WkzjPvDUQsuaV_MB5QAAQAASURBVBna1lmz3a4k5fP5_Ox6bQmkllByLbpZD7uheXg8bIbeW3M4nK4vVl3XEqph8_xq89mzq9XYG9K-8w5Valn3jcWnkz0cQ2KGnBIBsWHHzMYwkbUmx1JrfeK3ItMcMhIqYK1liaXtXEyl73oi_sNPn6yhvvNLkHkJIppyeftp_-LZ5T_9_oe_-_U37356d_Ps2X_6T_95msLrZ88OxwlRP7y7jzmOfZ9j-fDu7XKeXOP_3X_73__5uzfby914dTXPUzuu67xsry8Q6rLE7dUOVchbkerbRuSpC6DsHDD5trF9z1BQaL1da6mlVmIAFSRGglpVSNmgVrFdJzFJESkFCQ0RWxuWRat04yYuZ9Hq2k4BkLHEZJ13vk1hQVVGqKrEyATsHCsVKaU87QMAgUpJxlhVRcKash1663G6PyBoMwwlFW4wHvc5yXB1hYjn00lq6q0pOR0OZwX49puv7g6H6fFYSshVao5t2-al5prnZWlX_fnx1HZ9jgFyYaht18aUDWJR3F2sDo-n7WYVa4YohCBZvW3SvKx3F4eHvWubVKRWtK1l406HGQHzEsfdGlIoooQGFU-HTxc3F_d3d3OpoMqMsaab3ebD_YGFry6vqBYHOE_h5vp6__jQtkM8z531zLZkQYCyRFTsvAmxSJaxaWIqhEiWAdQ5T6SWLKo0rVHAHAtbRmPCMvW9V6TeO0hy8-zicL9vvb3eDauhfXW7DksyxJB4XHXOEIBsVu1SBAGSCJLx3hI7AHGte3g87Y8LEZFjViqltN6d5gzoTyWObbss0iKh5d3YNsY4Y9a-Qde8fr49zbDt2qZt6iLnCjtvDZiVdV_eXnx2tf785uLXLy9-8WL35e3mH7569vOX159drIfGWBBD7KwFAChiDWuVOZR9KQR0H8J8nKWUkHPHtOvc86vxemgaQwwYsqjy0HkmDUURzJN_ySJ33nnngSiJGOfujnsm7Fb-0-Pxp7Cc5nQ8LaDE3v3737351-8-HsI5LuWyaW523dj7VPW7h8OPh9n4FgHupoM39Muri03DhLJuuo_3MyhPUa3Frm-LKiAiQqqldYZQRQSfKHqEy5KQsLE2xOSsBUBCYGJnrDVESEycUg6lznFxztaSe2-ddYZIVJG0ghyn-HiaOu-ewOGsCAiGrYoCgKpaa5lYRUCRGJrGMVHnPQGqyJxqVWVDKjrFHAoUEUGaQq5AIaZc9Qmmb707z-mnDw9j5-dQRJGIl0VCKec5xVLP58l4l7JYY87n0LTN8XQiFXY0LTGE3I0-HheSbJyN56ndtIe7PStoCFUKoBEV6zwbLjHvP9zZpn35iy_Cw8k0vByWmlLJgY1ZpkWhprAQQpwnSdG2Vkp5YhwRmZxiCbFEjDloEWv59Hho21ZyUQAkxCpN0ykoG2MNKSgDkeElRQVo-lYJ-2Hl7FP7EbKAc862no1pOm8c11xQFYmlpBhrM_RaajOu_NgDqnXee4uAn-7P3iEh5VIAwTeODKMiGZNyMUzWWBF1vgFQFSBCJiBAUlDBWmUOMYec61PbjojJMaWQCQ0RGUNhyZLrkxcizAsaE2POS8q5plS63qeQc8pFBAVqKXnJT7-UUl7moAq5SFwSATABKvTel5RzKkvIVRVBc5Eay_kUSajIUko-TsH3Ni3L5W5YO3q59v3Y9M7loIisSsL2Zmi_-eymquY5DE4Z6npoPru5joLPL3fXN9vddtiuWnbcOmZLTNCQiUke97mxZjU0g3W3l5vPnu9ut-Mvvnj27Wc3t5vuq-cXfWOl4uk4qaVzyj8dT2_354_3jx_2B43w_GL9tz97dbtuDFsW3S_hdH8oBsXg33z7-fPtgBWeFsm5lLbziFyV94c7NNawKyI5SymlVKlSiKhxjIha6e4wKREwH6dwnhOQ-f7Nx75vEajrLJKpUH3XONukXEhIREsqjW9KSiIglaawOO9KlWkOKRT2NqayxMLOhpRjLpbRk0WyzhsRySU9nJaURZWAuFSVKgS2ZEkle-uQuYqo1OM0x1Ca1kmSw3FeljiMrXfGWVtUQ4xSxVqjtTri1WrUUqcl5FJEtW3bxrlaizXmardOKYcpe-83q7FvvXVcpMYYO-fG9dg4Z5jZYIkx5Xh9dYEIjbVxDs6StQYRdtvND3eP1-v1Zui0lCRynkNVyFLmORUBEaiq8xxzluV_IcGIiBIdT3FecutcVXjqsg9tn0t1xj08HKuCIMWQgLhIGfrh_n7fNj7FCADWGcmF0Zym6I0rUnrf1CqM5uPH-_Nh9pZApe08qDZt016uwmkmAKLaen-eg1TdrYer6y0jeuvvPz18uD90fbPebkxjUWGzGbuVzXNcllylXF7svGc2pkppmoYME2iNkkJ2g5uneDicvbMIsNtuvDdd3yZVAY0pWoLb3QpADueziCCzZWoa37deix7OoWrtWj-2jYKwqqiyMaFK23axlimkrnPd0BaBx8M8Len7Hz9Eqb7z48UWAP743Y-phPP9_Hd_9fn_5lc_33VtK_mf__z9_-v_-1-4ji-qBMMIArbppFYRJOfYGFJFQMmZrRGRbtyoSEnFOMPGqujTooKNUcIUIj7Nj4qEtBr7nEsKc9cN3bBKMYLE8-lIhlzTVQFCyinGJXpvzue5H3eCDCL9et0OzY9__m59uf7yq1eS67OXz6zh48Nj55tP94e-a5qmP--PX__88_lwFBDvXCn5xbOrwdsPbx6-ev1smZeLzeA6t9n2liiLXG_X49DfXlwQSZiWEJbdulvO4eZyZazxykPXQNWPh-PLq4vNbqypdL03ADc3G8PsCAzQPM0otWbZrrowBQNl1Q9a1VhjmLvWllpB1DCCoiKISt-359PZMFfRbmznkEAhlwQAfdMoogKoiHWWGGLKF6uuZFmvh5wSIyKTqrTGnKf5erdiIsPmcX9KITx7_uwc5u12M7Q2nef3Hx9uLp8vcW6cuX7-7PHT44_v34WSa63vfvxxvd4s50cCnh8efDOkFEqMyAwi3vsq1TjPhq1rUKHtu5yT1vLy1XNU-cXXXxTi6Tx3qyHNS02VLatqOp9d441vNWfDLDVLLr7vkbCkoKIlJ63JtCsVJUQiI7UCChJCEfINiBCCiqCq1IqOEQSByBokIuQqai0T85NnuoZk2C7TQgjMJk4TW9aqCDgMfZhFmRAEFFer9ZdfvLLWjb49x_jZsxc3z5_df3oQKTmW1jlmtkRLSI21njDup9X1moVYyDWNAkGt8ym0vpWqoOyJEHDsemPsMk2uXZ9Oj8M4EtB0POQkygyI676PxwmJtJR2WBdJWjOplFASwWq3PT4sRmqa0_54prGfT9Pj_rA_TrubGygquZRUkBAFqoIUQSWQiiCttSmlbjWUp2UdViZGAMMGqjCBAdBaUcl5x8626zanag1765ZpydOy__gJoT4el__mN39_czV409w_7O_n5WLVX62HL17sdn3z-vlQAi6lLDHWKnPMF-vRe2cNkqWapcbaeiuixGxbIyKrsWVmQ9i1TQnRGehbI6kQYTu6tjXb0W_Xze21vxrHy63_9vPrz55t_ubl7pvnm589v_z6Znh1vXqx7XbrdjV4AB19Y5kIEAmAwVvuPGOVw3l5e17YmTmnas2ylIfz9M8fPm3a9ldfvLy92jzbjTHlEELOIcVsmYHIGyu1hqRTklIBFYxxIgjAc64h1Yc5fjgewVCt-l_-_O7jJB74om9eXHUfpvQffvvm6-ebb16Ov3h5NVgztn4c--P5_O-_-z5kTLlMKY1dv-6b0RKA_vn9Q9P6nz5Mm7bvrHWW-saaWkouMeRP89w7s-7bkqqzzMaGmFIuZJ2xJKJd37St11q9NaDKCIQoCipSQSuI88YyQ1y6pqlVQVlAVORhigmtsRrO4WI1WGMIkQhFBEBL_UuyRAGISaqIKihIqc5yrZq1PBxmIFIlQUqqn-5Pp7CwM0uBkNKn_VRQS9VSJclT011YMT7h5Gud5jCHbBqbYokhusEiclpi3_vpdISSYoj3-xO1hsnUOJdpRtECks4TPX3Pjo_eoTU2p2i9W2-2UuuyhLbtY8y9awAkp5TDPJ_PTdfFlHc3VzUWrZrnRStKVlBAJDCsojlmJjbW1poQNE5xvOpQNMcclricAxgy5innbaTiaT-13nnP3rCzrhRhRlVC5Mba9TgA4dXVRb9eA5L3ruSy3e5qTiVUMkZKUZBlPseQzseJnAFCAPDGrsehaRyzIcdEnGNMMccQ55BKrW3bAFPTOLQmhEhMRbRqbdqWmJ01AAAI3dCiMwhq_P-Ppj_ptS1N0jMxs69d7e5Of-_13qPNiMwkszLJIlAoqiSgIAgFaKAa6A8IAvTzJECAAKFqpIJIsUAkyQxmZIR7uPttTru71X2dmWlwgtMN7Mlu1vqW2fs-j88hLVMQUELIAsahCGmN2mildUlERFS45IwKKCf6LzXzmLJSSlgol9rWKZacoij5M4-2MAAI4RKW2tqUy2sxVCGAwiKSl1LpRohYkmIEKiWX6RyWQqdIgUAjVK3Vymai-5dpOo9aI6ZCuVys2nVfXe-2FtVxP56mZdfXTeP6pq6MrZy1SjMzIBameUlCpCrjtQGWi22_W7fWaKW1spZCvLroQ5ak5JBiApkp__HHp3larDFfvX3rvfvNV5833gBKpvwyDD89vgyHUUS8N5vN-q---axBFCIGZmIAdNYxcUnEqK21IZaUaZwmBmSRwoyovFGIqgBPcxJrssgwZ1Z4Pk0AoK1OJe8Pg1ZKK6iqqlI4jEuMJSzBuDqlhKhR6TkkhXaYA2pltXbWzOOSmVPhApALT9NijbWVZ1bDGEPJx3FJDARgjJ5CBkQB1FqD0qVQu6nnOS5TiLmElJ1zMZbCDFo1dYUgu6aB14dbBiaJIdeN75qqTEvVVofDqTCt-r7yToAkk9O25OKsWfXNqqlfCUciDIQ5piywLAsarLzVIptNv-46A4IC2mqlFJX45d2NCCLI3W5TVbaEaIw1FrXVIZQ5JFF6nkMRXmIuArkUZrHOhFy4yDBM1mkFhCimdsrp3bqXQtaamKMQMQoYZZwhYY0qLKNxejqcm7bJMTWVp1KctdcXK-HS1k1c5tVmNYdZAXTrWkoxvk5LrOqqaeoyJ2VfGa_WOHt3c_fVZzeb1eblsL9crx4enqZ5Xq-avu3CtFit6raSkiXTPIxXl1vvvbNKWzMvUWkjQiFlErGVMwoolg_PxyLlareunJ-nOU5_LkkViX3t103llcqhGGe0NSBiEJw1wFCI96ep9nrX9QyUQwRgAUmlKGtiisO0oLYhlyXLw_PpOMzH8xwznefl4vLiu-8-fv_9j96rd3eX_-O__pvPL6-YgVL5n_7t3z8eDqfjopvPfmG9a9t2SQsxoALnPDNq73Jm37XauhKSUoqW5OpKgCmTNrrt-rDM1vtC2XoPAAxkrfVdQ7kIcMrsvReAQqWu_PlwNs42bQuIoLDpeued1tjUNTCu1p32woWAcprnvm2c0-NxvLq50gq1wN2bW4saELY3m-3lJs6BYiSSsqSvv_lis26G_akQOK99jUq5aYmVcW1drfraCOz66mKz2h-O2-3aOaSS7m5XxLKpq3kKde1BYV-73bq3WlNK2-2aqDhvWGS33lAJm1U9znmz6tbr1lrltN70K0RgJkEA4VJ41fqPz89aWRJ55bFopViUc8YYE6ZceSOIVpvCjCzTFAuT0hoAn14GhWgbv4SEoJzT2ujH52MussTYdtUUy8vh1G_Xv__H74HhF9_8_OHlWNfuP_yn3xPLarc-noYvP7-5v385H46f__xLq9RwOh-en5ummsfZuubtF5-fT_uwxG7dxZCdM_M0Ka1LSE3fMwOAIsrLOPmqViDV9t3Tpw9P-xdr_XmaU6ZmtRZkBrHKru_eLudzyQmNISrWeVBaQKqmE2EFyDkLoDAp65RCpbSr6zQHAQYQAPkveTNlrCMqnAuAUlojACAqrQRRmI3zxlsphCioNCBxKVLIOB0PA6LJmUQ4Ueg266Zu-66_vdv8_vc_PD8fljjGadnvT0bKV59_-f79J21AeR_DgiDWuBRp7WvRiIIpZlAgrHzntShmKTn2vkopUs4AWKiICIGIIueaZRyaTZdiyiUpMFoMpQAMCsQozGFurrY5lcxSCgIpV9V1XVXGvTqijk_723dvKcSScpyX1aa12iKSs74gvLrSjEJhWGKuK49alRg3q6bEpLVGxFcu-GbTLXNyVpfCvnKvxfyqq1-D3dN5FmIhmuOsjUaF718ew2kclnHVr6676tdvLm7XXVN5rzVNRSk0Glbruq38Rd81jctTrI25u922tSeCuvaFRYjTkry3CrRTSmlgYY2IAktKT-egRTXOiagC_DSGfCZtdOXcYSifHk8_7cd_-PDw4bC8P8R_ejh8OMz7kD49z09DHBM8DePjGP_0NESSw5Tux_APH54_ncd5Wf70eDwcIwpsKrPr63_-ZretKiKO0xyorKpq3bZ92_Ztgygh0n5acioRuLa6rp21hpUgMhv3eJhOUzzE1Df1fpzmXP7N7z797KL54nq1JP5__7vfH8f5Ym2lpNWqfjwcF1Dtpv3__nD___vj_bdfvhmXpXD57Vd3RCnnYJT74_vnTdtPsaxXtm_rWFLj9HGJUuQ0hYJ84X1l7esEDpWZQgABRhQmEGGi1jmF2mlttEZAEBBgflWzolEgjXOV0toYIGDmjAwa5oIPQygshcPVbt16x4UFgIQRkJVCpRER_lzx0oioX3UkiEVkCvHlMJOoJebM8HSczlMc5hQzDSF_sW5_eB5TKSRQCrMgeH2eFq1VYVLGDCllIhL9-rdmBqZ4fJ68s4KQucynqK3KOaZCHGM6DctpRAawHKY5E83H8-ZyPZ2Ctvh6NdhdXoPVOWdg7vpOOzedzgo0O1yOg9N4ejpUfRfnWZjarlVoNu8uOREq1M4WFmLRzvDrwQVIKYhDNG1XJOY5ISJrmM4jERhvQTEKuEpP52Ccw1JQozYmlwKoDMg0jQRcN60AIVHft13tmqZapiXFcnFzyUIpR8oJAGvjFOQ4jJSyMKPWr9oHpU2KSUAzk62sMRYQGESo5FKIiYiYmUtBkTgFADHWGm0AVZjCEtJ8nHLOYQlam_8iC0NEmXPqugYIiYSYuRAiEBVbVxpEofbWhjnMc2AuTGyUKiWnnLraphypEKBw4WWeqZA1hojneTHWMpNCVKjneUkxZ85znAAoZ9JWT0XUtos1D8eZiNKSD1MZSB1TjpTXlXlzWW88slZV1zzvDw8Ph5fjcdW1d7cX16uuc5VS-vk4PO3PL6dxmOMQS8j5_jCuO6eN3vRVt9Lrvm57dTy-DolzzmXO-dMp_cOPDw-fjvcPh-PzoNG8u7v8659_8eZi3RhcV-5lms5D-O7x5fk47U_TaUiVr375m5-9_fXtW-e_utp6AaXRWINKIUAujApT-fNqKDMziSjQSpEIM_ddqwBL5ueXCZzdDwsr8zJOmSEUyiJ934qwQqic1lpPY_jxcT-GmJkL6mUKSpvCwhqpYCxZKz0NC1hzXuI5zLGI0u5wmhjkdc0TYwGDovn-aZhDmQM_78dzSIQogiIoiCQgSjPzNARrjDJqiVRVXhu9xIIAwNxWNkX69HQSDcooAairyii1WdVtXdWtC3O-uliJwmmY5ylst701RiH4ynZNU1dOK7OEsF23T_ujtRqNIua-bbzW1ti29s6Z2itj3TxPTVMxs7Y2xVx3HVOx3hi0BHAeZhAc5rSECIDa2JILgwqUXzO9RK-wAZVyrr1lgjlwVbs3F6sSirGWgUMo2hg0ikgoAcVc19XpPAsqYx0CaG_nmIHQ-UobZZ0rRE27jiFY7ZYQjQLr67Asu-06xmgVFiKey8XF-vpit9tsAMR794c__AgIU0zE0K5WtxdrY4zSxmjdVLWItF19c7vRqITKuq81QlP7L29WhbUgMsAr1nlYlsbavq27tnbGKMS6rjNnhYAKr9Z94w0qBSKMjIDLvCitUfSypKfjeds3lfOxUG0tIKKWqvLHYTmN8xQLgiLGcV4e9ucxpHOISqnEXDU-xvy7__xd5fV_8ze_-urdTZjKP_3h0394f__7D6ePp3EmrgxrXN0xiHa-WnclZckFtBalAV-Dg6xQizCAes18C4h1TohKyWiMMuiMKaUwi9bOeR_O57pfc8naGld3YVkurq_iNF9cXb08vqyaejiNq74HEaOU0e48DOvdxigTQ7y5fYdClJI2LoZ8dXP76f2H-4cXqM3V9bqEMofgjAnTAhr71aZufNc4Ucpb3dRuvV4hSlv5u7tdSWm37j88nZra9qt23TTjeWy69jwOl-suErTOGutEBFCd53i52xDxqm_bypZc7i57EVy1Vds0Ty_7693KafP2zZVBLCl5Y5raU45E2RiNqFAk5TxNqarq15Kf0sYYXYo4Y-R1hkeQmIzWAiAscyikQCmllM65FCat1Dgvm3UfQjSICMICVe-8d1rpxjqi8vvvfgQW48z__L_8W-uVVvLm8qaI7F_2t3c3Ly_P9OfIMcaUh_PkrK2angpN00QlgUBcApdgvdcGq6YjKs66cJ7X27UyePr0uL65cqict-PwfHF1cd6f2tWqrmvlzHm_Rw0KdKECCIigjYnjjBqN9UIph0AlC4C2NSALMQJUq12YRm0NKmO8l5KR2fqqvGqBQEBEA6rXsa_zJWUgYBJUCpiVccpoKgUVMNF_4fZkZbWtO0C8-PzzNAxxWQD09u6tEgxLeHx8ySWhreYUu3b1cDhsL7a__MXPH15OeV6AstWGqBh85WCgsd6gKTGRcNU1QlJyIWFA5SsYYuAYWMi5KiyTrSoBIcFSyvZyt5wXpuydSSl5b9vGl2k2VlNJpmnBao2KUymFur6jnAig9c4YtQyTEvVqJRRjUsp3V1dpXHKIBsVpE-JCxNZqZ3DTNGkpRimrDRd2zqHgPIW2r_uVd8ZZ1H3ryxJqXzV1pZm9tau110oQ5GKzqut6OY1XfXt5vS4pWq3jOP_6y7uNt1aD5MxZci7WmziWp-ehquyqrY3Slben0zku6ePjAZ1mFu9d7S0yKqUARJCf9lMivty2KUndWW105e0Q8uE8o_BjisT2u_3x6Rx-vN_HkuckXjlhAAFrbE4yTSlGGg_T82kZzgsRd84wcSl529XWqHXlfvbm4t22UxqN0VorNCqB0gYzgLPmOC8EeA5hSiUyo1ZV67UDURoRDOKH59OP98-_f35exrIfwlzyZrfKSO9fTseYPltXf_GLN-_34z_88KlYrlf9j0_Prm_-zT9-_-Ect5t-WPLH-9M_-8t3L6dTpPSbX7z5x0_P5zko7X56fNltVkspC0hfVefT0raWMsdUYsnOuW1Vd22ttRYEZ8y4BCqcqKBBZzSAONDOWYPKaMVCWmEhJpYl5SkmIqmtaowpxEScqZyWkFk-7oc_HIZSysfn-3dXu3VVG0ASYMSU6BTD0zJ31nrvmJiERVgQnH3N8-EwzYURnQ2ZEgs6_fhwOA1L1Tf3-wEU3J_DUiI4M4eMxigLhzFMc1xS_vDpeJqWzCKNzVnyEgvlw_4kygynQZBSzofnF-BirPLbDgqFYZKcQCSG2XROK00LYU7MaXW5LTFprbp-JSinx1Mppa6aDBLDXFUOgA8fHxVLjNE4l3JCY4BYacylMDForZVBowBEWQssACqOs7WaUgaieByW40gAolgZY7wRlmVcrDVKowYE5GWJqNFX1hqLAA8f9rvL9c3lrrA6DuNus06FkME7Y5xxxolSyxJWm_765qLbrI6HkUvRxipk9YpdSqSUDTFWbWus0aibvhvPyVijjTJGo0ElUHIBxBwSICijrXUMnCKVlErKJRdiyTmjhpzKPC3K6EKkKy0gMcQ4h7CklJO2TkBQKRGIYSmF0hy01oVIQBAgLLFpKi48zfFVHTpOi1BhEs6Uc8l5AWISCSEobVDrkmNbr3IpRpklRCoUclnmpADj81llIMnLGLVD5UAT7--Py5SeT-NPz8eZ5Ziysn677q9vtm8-u7VGh0jHJR-n-ePxbJxFpTKovnFz5rjQw_m0Pw_fP7-cZ3rYzx8fx2EoU-LjaSGSzbq3TXU8TQYwodxc9p99dnmx29TWauRpWuZSFuT9PA0xPj6-lBSr2hNiW7W8RDpNX91s323XGkSImZmBYiI0mHJ5Zd5nkiWV9Iq3VnielrryRiliyamQUqHkKdA_fXhkgCwwDNNq1VIhFmgqt-46EJ5j_OFhP84zGk2CYNQrBjCXMk3x9ZDgmvo8zIfzLKiHEKu60rWhUvi1NE9sNeaYl5gJYA4p5BIzxVyICLSqWxeWQsxM5JyeS05JjDORi9Yq5GK1JgCL6nwc67otwsbYdddwptqYunHeulwKibx2FrVSfde9Ju2NNVqhc1ZEvDNdV-fMRlvjtDPm-nL38LBva7fpe63UunFd06QcQdscYtf1zti6quZ58t4ZYwVRSErhJZPW1lo3hkAFciEGyKkQSM6pdjUDlpS7bjXPi7KmblRX1Wkuymqw5vhy1ka9lrMEkXMySqWc-lWfYn7zxRWn7CuXi_SrpqucsLy6rISltu48jJUzVVVxEeec1YKgSeSzt3eXb7d128bCY4pTio8vpxBLydEYPw6x2zQoKixBECtv68pTpr6prdFOq66urFbLHG4ut8TIApnIOYtKFCqrdb_2TuPxZbi9XGtlFLOzFhk0YOOMMxYQ68oNU6itbbrGO5epnOfFOoVWC6BSWKg4q7W1L4fT0_4s1gCaWMq0LE1TT1meD-eCOAzztKSua_7zH3642Ky-_uadtm6M-f_1P_87qGys7Men45jCy_Pz6fFFu91b1ECxkKjt7S2lgNoBKm3M6-8VQFBrAFDOvspeEcG3HRE555qqVkYprUGZqqustXHJiLjabRiwCCPIMk0COM7j5vIixNJuN0hsGu9bt6TYrVtrbSwl5fn5_aeqdda5dX9hnBvOe6ukafyb6-u1dxq0q82rIK5bNVDydDq9ubh8fHpZ5kVr1beVMarv2ufHA2hVeXN10fRNb7T--OnR1LatK8lpVTcGse7qxjutsG381aZn4a6ux_N5P8wKMeXSGoMgYZq2Xa00WlQxhGEer1a9dw5RiKhyDpVCkUKUMqNCY6xCRG1iikxcV16UaIVLzAPFnEosf-5VhkLWKmfsEhKDUiivfeFpnJclXt-swlIy0cWqGc8xxmIMDue5bxrr1NXt7cVuSwVu3755OZ6_-8Mff_Wbnz88Pf_93__w1__it2_f3B4P59NpWl9vpjl4ZwExxaSUALNRkELR1pZEw2ncXW_zNCPTcB5TWLY3N-N5WF1cTON0fjkDlZfH59Pz89XtG0C4uLs7PD83XceUiLkQ-aoxxgBCDtG3K6BSSgHUlJNregBmIYqhXd9O5wOAICgFkFMUKUoZY5WUKABaGQAUUMJiuooLWa2NtzkW4x1aQ7korbQ2yGCMB80g8jpI45yNaNRAyl399lfxaT-ejtvdutu1IPLhw3OIC0j-8MMnZfhnX3w7jeecQ4plmeemdiFkBSrlst52nCmEgNrW1lokNiqnbI3VCpAYSbRV1hkq5GsLTBaNFrm4WJVScg7WmjAEbTUYm0IyxpTM1mm_7Y3RKZFQaZv6NMwgRJnSkrpVR8xawzwnULBZ1-uq6toqzMv1m6tSinN21VTDaaJMXdusV1Vd1SnEvm-N1rV3JZZttwaG7bpVGrRWwqylbJomLUu3Xlmtq6ryTmmdP7u5WfeNyfm__9__V__4D3_8y28_-2y7RlCn8WxQ_2P8X6_9Z9qqYUlP-8OwxIf9dHe5WtUdJdpuG1-5kPKfvUUiOSYWcNZM48KljONcNU23aT49DkSkvDmPAZG9MaeHAfO09saU-O7zVdO7yhqFgCLe2qZyq0r53reNX62a43m4vWpXbdXUlUZde9sYvW0qpxBBaa0qpwAhLEmUVlahQVJ6SBmUOpdyGOdPp_m8pP1UPuzn7x-n_T4sIZnKWGOO-_k0529-_tm7i_Wbq3ZTucfT8TCFn39zs-mq333_-Lv399DbU8gfn57ay-anj4-trX717uaX15cv0_ztz2_GYRhT3rar__zDUwil7dphXrZ9b6ye57mrtAP57HIVokwx1NYYoy761mtTWZupgMIlppCKKAg5dU2TUgThTdshKqtAmBBBKRUyTTFNKZ3GsOsrozRqZaw-z_MYi1h7mMI5wZTpu-njb9---2q9MmgEATTOhZ6GMxB12jRdU3JRSrEQk2itCnMqZX8eRZm5kCj98HI-x-DadkrZepeTkHAsMi6BWM8hGludjgMYM8xxnAMKmMoxg6AsYxiHMYQQQppDsVZ1245z8m0zHk9G4zKE8_MZlQgRxeSci6eztZqVOG-ccRBLSuX2q7vK1zmlru_Xm_XF3a1xLs5z5SvtzLA_cgjeGiJCra2rl_l0dXMjwiXn10qw8W46jSmzq6rmYoMGEQSItbHIYq2heWIuTBJTsc6HcbSI42EwSudC11fbGJYwpmUKxlir9KpvHz89hJQqrZ2GcV6UtiFGAamd89as6sa3zbLMyxxyylprRGW8RWXQ6WVY0hKNkpKzABMIC6775upyu6or42sATIX6vn0tpmciBk65hBhd5ZU13nmlhUVOx7NvmnlZnDWZmIo2WjFTTiUuyTvHUlJKyxyMMQBijUk5K5Tz-ZgJcine2aqprHU5R0RkEuZijKYUU0jC7H1LOZZUYkjCjCgpJQBRGl8Xnwax9lZAgAQAkAooyCnHzACKCcZTDOOCWsI8ZSrLmCvjcqJxXD4-7h_34zjNP9zvASQbaZ0dSJ7O4xgpIxxO008PQ8pRALHA4TRRIm9t3bqQKSbyla989fxwPOxnY3nd6FWtN2sPoDUAGdwv448fn58P5_vH8fB0iil1XVVZFZYsx9hV-su319fb-ufvbnprNYKAsLAoEJaUKaUCGpkgEsVCypk5ZGZOhYHJOxcyBSoFsDCexziXKGAeng5t1wzD1HdtpmJQK6VK4VxovwRErZRalqyUEZAp5P3LOTPHJSdiAJiXPKeiRFiwpFQSxxi1dzEXolcHnH61bofMDJhFRSrEkAUjcSF6ejmLiEGTo5hKrxs7BiBg7WyMGRU6p8FqbaSuPItMU6itaRvvlKHCU0gaABRaraxzWqNzFrIc5_1us_HatLVDhJKLkBCzAvHan-b55nLT1423pnJWofnh_pPVtva-6yqrnYh62h9c5X3lgBi1iiUvSyaQkCjkgIhzCqAxzKkIl1JyKVqj0loEiAWdXs6LM1YrVVAEZBwmQvBOF2YiPo4T8KveRBXiuvIUS6WtUiiABiSXMsRwzKVSSpibxkXOGtFo2zaNMarv6rry_aYXxOPh_PR8GE9TSKHydcqFcr653LBQVfm3b64fPz6xsDemX3XzML65u2y8cVo13hnAvq9uby4qpyBxiImZrDGFwXnDubTeWFRX2y2D1JXLxAZhv7y8ubiqrRNh5hJiFBFtjQgaYwqBoNR1Za0blhhC3B-G3bqPIU1LbPruZRiXmArTyzAlwD--fyjAT8eTQp1zbKrmvMR3b69cU_2Hf__9_jQ8vIyHc_708SELjfMQ5pnjrP3dV3a1cUrH87nk0O0uw7xI0XVX5ZwBtKkrEABEIdJKo4KqrkCAhSlTSmmJoWm7rm-1NQCq6loQZODCVDL167XW5vKLNyksQtD0XhmPwMfTeb3eHIf5YtVRKXFcKufrplpfbeY5hDDXfbtbtU1T5RDHGLb96vbu6tOHx7ub3eWuXQ6DVwpBQKmm8d98-2VakgD_7JvPTsdz29at99ZohaqtrLfGoFr3jddojYsl77arZQ4p59r7tnJKowFEjUD45nKzauoUs7eq9g4AvNHeWEBkosv1WogBEQR85YmoZHoVyDGIIMQQGTETKYXGmFKECo1LyCze2CLKGW20JkRl1DTFmLPxhlicM0pQW2W11tbdP59Xq_Z8CsJEIHXlYslLyk3j7x_2rqoKkRPu-maZTo21YPxv_uJbJ_L44Wl_fHlNg4jiknPV1FVd_fo3v3r6-ImICzMTGKtzTCVDJrr76ptNf000USrHl-eqbfb3-9vPPkNFiNw1fdv2L09PdVMJF-fb54fHi7u3tCw5lRyXZtNpbZU2cRyUtagNgPpz79BVCl5F5KFq2zxPIGxqr5Viopyjb2vFWkCBMIuoV8mm9ZQLKsuA-lXEmItCpQF4XgBAWeVcnUMUQVu3pVAYxt31VQ55PjxpVcdA8zKFTJn4-u4qDhNReHd7ASVHSl_dfXYKkXNGASUqzokpF2ZA8HVtQBlSBgBSubu9nM8TFkIlQFK7aplD7WuNBjJZY4VAa0NMtfc5swNALikUKVS1Db4m8xnqvsFKrVdNW1dGc7tq5jFYa0REW9CsJLJxmJciznlvu9oRcYyh9k3OpJQx2nS-YmDOxVvnjY0xV7V3xhHR12_ecE5KAypYr-o0zq0zVqCtvFHKc2kr3nWrX1xe_V__T__KzMIp__6P392sN3_7my-8VoWK0ZBzXsmNNvrlPEFnxyUhIiG_u71gSssUxpiaxh1PMyCkVJw2xLTpW4W0LEkbs-q7JaZEkFNunA5LuerbaNQ8JFeZ9qJ9PETQ1f3TZMA8H0aLylVeIQxzOMwZUKY5TPO8xNjU7rzEENKf9qeYaM75OMaUOLL8cP_y_ul0mGJSsh-m__jH93_8uP-0P-1zcK3748d9AjiMsSSKC1VN5QlIcgB4fz_84f7lOU4F-LifHp9eMC3_059--H_8h-__t1_fPjwef_j4bCuDrbpcrT4cDvcvLxem-2J79d_--ouLxv_4OJyn8WmeX47Lw2kcY1QK27pikMZ5JB5juN1027Z12i5LBOZCtG4bq01rjdX6dYgbyyttRahwbQyLUIy3l5dCrAGV0SFFUGopVACtr88hXq_7VVUVEWZJKUwEY04iJolaKH53vP9n12--2l1qUYCQwBzP89_fP6RQvvz8JgsgiTY6M8eYtHUiEiIlkCWVJDAHGpb8PE7nKQaWlLkIjHOJIi_DuJ_DFDOR2h8Pdd3MS3wdl4ZYlpCMViHEEDIiGAMpRmaOKZ8Ph7ppBGA8nZFJoeR5ISG0SKV4YwClhFxYudqWVMKcjXdV1Qyn4er29me__Obx-ZRCzjlBprjM2pp5nIDKqxioX680YApRK2ybdlomKRkF45Sbvqu3G2sNM5VITAQswKRFBBQJV3VlEDxgjoFj1Bohx8jMgqdxlhjneUJtzuOMRhmlldXn43wezv2mQ4TT_qhQHp4Oh3NEDXVXp5KUcdPpeHW1m8aExsYlDOcpxQzExmhBVbU1M_naN40LIduqss50XQsIqbDWJhUyRmsFf1bnKKWsKaUwFCAQVFl4mWfKPI1JKyVCGghQfOXmeSlCiMpoJQIxZxaJMTjrQBCUSzG0TSMkgtg0LROTQAgBEUVKbSwiEglzrqoq54yoSlhySKXwMo5EPE-zNZUoUdogKkaqKnuK2YBVKEqrIpkKK-Cssav8sAQhrFZuSUmU6i4aBLne1sdTfDmcf9gfXo7zP_7w8eHp-P7-5Wk_fPj08HI4atTjPDNo1oo1OuvnVOZzGKdAQIXLtARU6L17PE1ThqdheDmE3_3x8Tws-8Nw_zjGnKqm7vputetd7ZiFWW23q3dfvXlzte0rVRv9-bZb115rAIUxU065MLFIIdZGZ-IMwAKpEJNoq0EgF9bWPDydCnMSzmCeziOA3h_PvvLMHDP3TR1jNqi62g9TPM3Ly2kydc0kKEhcUqJ5jgxijFtizJTHKc6xMCJLLqm4ylurV10fUtLaEjMaOy5FaRcTI6LVuvKKCZc5rDubIi8haa3HOXrrEhXKsD_NwxS01ZxJIzitFWrKBVFZawDUbtUqhVVVOWNSLHVlQ4wImgm0xrqyCvVwnrq2q7QpqWhUTJwzzcvirEspu8p562rrtNGUS11bKsWgbesKtRZAIZpDCCkLc9-2CnFewhJSASjMuRQCmJektE4hhVSY2Vrtnc-FldUsorQpKXSret21rLBkWsa56ZrzaTJWAygp3Pqqrq0o2W36nIu1erfpX9-MDE5Jislpu6kro6Ct68xUNZWvamOQRVIsYHRMVHfN8_OBiV9jBUpkCdF7Z62aYwCEb3_-zf1PH1abtu2bvq2MkotNxylVVluDb95eaMSLbecUEvMwLS9xarzXSnmtjFG9d3cXq8p5IhJhEGgq453tq9YiAEpMmZjGJRlnYsg5kwC-IuO0UschHIc55qKt3q06QDjHfJhTLPnlcI4pgVK_-_5D03VZpBADSN02zy-Hddfr2o_TkogCF-3UPM1oYQ5hmZdlnMI46-r665zZ6lYrySlRptXuonCeh8k2jXa2ampgYiZj3Wa7y_lVWfVqeBRbOa11WKJ1RhhTWG7u7kQhIhLx1eVVisE5P53mr3_-W8lLSby9vcwl9X23vVxrou2q6berUujqaq2MGw7jX_2zv0BhQmgr9_33H96-2cWYf_X1m6fHc-byfD_t1nUMBMA3b269c9qq8Xy6vtxahfM4N3XNJVdWD-cRBVZVg0rqyv708ely2yuNjXertlYMlxebeYnDND8dh-vtel7C5XbFTL5yTWW7viKSFLNWYJ1l4rapQNgo7b1hYRAQEK2VtQa1Ka_Bf3ilpWFK2VdeKRVzMtqAUnNMtTNzzABotMqZACEzIyoBKJnmGAygtdZZg6BYqK1tShxjDIXfPx7fXG2mOfm2Ojwdnk7Hrz___HgYvvv-_te_-ubi5gozVd7fvbsehkFACUDfr5jJWOVd_fjwaJVtu2Y6L7vbCwBWWq-6VUwxLss07IGp9nZzfUVEUojjuAzLeIq2apBpe301ns-ija1s0_efvvtjvVoJFQQAQWaouh6BGYVKRhDtbIlsfWWtZZaSIgpa78M4IKCtKq10Tikvi_IOAJQxtqkoi648aM0CqBUiolKUiUpWKCDIpSADiFbeK6NSKGAMGp0C2bqZxwWVMdY77_fPL4B-s9nsKnu92zw8nj7ePxmt948v2uCXd1-wgnGcBcUYJSDWqpyz0lahtgqQEYCmpXx2d3s6DUBCAr5uQMM8pbu3l_RqaQEQksuLXQihlKS0BYWCYoxXRrXbNqaiRJDQG7_p2xoVZFnGsa79EqLzHjJ8cXcdQmIsutVhYtfVl5v-ancxjgMC1E0HClKKm75LuVinReDLu7vC5K0Ggao1wOn2YlOIgQGB26Y-vhyrpmpr--1vvr296KOq_2__w998fnU5neOub7_-_PJme9F33c2mFQJnjQBp0YXEGruEwJrbtjlP0VlNnLdd9QoiyKE454_jvKR4e7n58nb95cX68eFYVQ1ArrsGBEtOTVtNc7BaAeKX_fp5HrSSfQi7ph7G2VpUgN9c1LPoQjKGFAqBwHmKQIzO_eWv3j4cQyySmJW2ucA5UCz84Tg-jPFhXB7283ePh_f76Y8f90nraNXLGIbj_J9__-F8TmGhFOmqXzmja8CJS4zxcD6dQv7hfv_x05NofDg-ozGfFP_ud4f_y__uL1br7g8fXxYBAvju8fnxdLJF_9W7z_7557fXbVNp88fn6eMy1Nvu-RyGZe67bp6WdduI4mkejdHA8ma3varbHHLO_H586a1ft23vTV_5zlel5MM4x5SapnZaM2Mu-f74sq7rq3UPJJWxSpuYMyjIoJZEp0T3w0kDX17sci7n09jVNSs7pVD5akqZKG0a91-9vbuqGquMoFqYfzqMPzy9VKJQG6OwUq8eEkaRAhhzUUqL0pGBlD7Pi3E-lqyM8n0zzjkmGua03bTv98NxXkigqer9NE8xJyWn0wAaT-dBK7PEYLSdczR1M50Oy7AM58k2FpkpJ2ap1m0el5zyq9KWiAVASBAygK26Dr0KUwSh7cVGORXn5fr68uZyV2kjCg_7g_carRrGSVsVp1kjxhD77SblMk3zdrMqKa9Xu_N4TDG6qjJeG2eVFA2KQrIWuDDl9MoyL8i-6-Zx0s5zzFXlx-cXoagrX7ikkLZvr8anlxhiW5v9_UtdNQoBjUIlyzIn4u3V7nq7-_jx0VjTNIqIDoex7ZoC9Obm6k8_fNjtLq3BetVrq9eXW2VNIfJtU3IpqeSQiOjm7YUCQVSIiAJdWxHxdtULcmMds6RMgup4OKVUxvPsnWFhAdbWvZ5L6tpVtTsfB2ssKtS-YkCt1TLPOZe8xEK8LKnkjForhKZuhuMxZQKEkrOglJRs5VKcoRATe-tBBFlyia72JQdgRUqss1QoL0EIcolxDJmprrVzdlkW743SrLSq-xZBt9vq9DLTkvfPh1LkJBEISEBbfRznOJf9YXlNT_VdrUhyzllIKFkrRuEUk68sGs0IpyGklH1jC5V-61atW19tlhxPw2K8neY8LHGZ5toga3KNRcBhjrXTjCBEw3H0tUXK3uhvv71ra79ua1rSqq2v182Xd5cWFAEDAhEVkfmVgoOqFJpTVkalwqnkkjnmUgorq07n2XgzzUlAHYdwnKYlppBpWmJdV96Zyrk5zDmV43m03oZEpPXD_R6V1ohL4jknEjBKz0vMiZwzBACI47RYbZmlresllUJMhUKMSlsiERQEiCnnQimXeaIscghJsX59BZCNMbmQMCltlhi98zFFrbXk4q0lImEYhn1VdUZrrVGBMhqJirUaEGImRKUQhUQbU1iqxmtU1lilBARf9oeFOAZKVJz3SqnGV8JslaorB4gEQiIx53kIqchhmGOizHx9uUsxMIBCFVIBBECMMb5CCUohEmER76x3WqGyzpPIsgQUctZcb7dFRCk1DbP1WgCMVdMUnNMICjXGkBQqpZVB2PWt885okwvFadFaCYB1nqkAoAJIOTrrCOS1DtWtWo3inD0_n2JMMVHjtTZGCeSYfeNOp4WEu7rqm7rE3FTVxW7lrUpzaBrfNdVutTod9tu-3a7aWhujVU4lU-kqV1euRHIGRclV39XGAAAKVtZ6Z_HVpgnwZ_dZTiLQNxVqo9AojcRMIrqyucD-dF5itrWtfd1VPuV0mtI4zNq68zAx0Gq7-nD_TEJOu2GYqtowoLaurqt5CN9__8k6fRimw2H88Md9f9UuYQrDRJkUaO2uv1ZKMzFosMaJSMxRe2-MBYEc8zxM3XarQRABLQhxnEK_3VBiIbHe-bap2o6odN0qhhBS2l6ubm-ujsdjv-2BuK9rZZFSaBrX7brK1XlaunVTQm6q6u7q4jyPV2-uwnjWSgmXn378eHl7KcDz6fzu89s5LFXd_su_--rxp_PhfHZarVZ13ze3t5efPtw3rf_9Hz_88udfUChVbWvfnIdRofRt19Q-LImEn0_nVVt98fZ2mcNu23OhlFPXN0zFWeOV3vVNYcYiqIRLUVp1jau8mZe4XrUlZadVU_s_B_kVKEAWJmIqBIACAIAsQsIAqLXR6lXoTVrrmIqxhoimJYlBDfByDkoDg2irAfUrIZBJQkhGqyXllGmcAjBXdbUsYbvpRcp5ml_O0_XlVcrRG50CvX1zeXG5aWp7dblr2nqZw8XlZs7Ln37c77b9et1_-uFTs-r7tsmBXp4OaPHq7fV0OmmRi6uLh48HbQRAaS1aCXDebNd_-vHp4mL1q7_82fFhv75elyKFklbw_PHD7uYda-2q2jnf9NucqW4bX1XLOGtr4jIbXxOTRvOKDleATFk0KG1LSpQzogCL0YZKIWbfdUCEjAhYCpu6ARZmoSLKmBSTqz0qlZdkvZVEdtVQKEqBMjalpKuamZUzzJCoEBclwAyguLvapbAshz2FsLvcnqfp4mI7T2VK4Ysv3v3ww72v_Xa9ubt7dz4NcYmIQnNadx0VqlqvALquUaBJWClomoaoOKVVrSRJjNTvGg1qvVtr7VIIzsBus44xEeX-ckWZmQiV0lo-_-p6PEQtWDXul5_dhClcdfX-PLVdvb7YxVQATS68uq7rrpEFjOYUGZTetP5mtwlLACBU0DWNr5RAEUHUrDWs1v1u1dhKN94XKhcXm65unDVd463Cu-udId5uum2l7rrq15e919pZb2trjJpj2Gz63luDChXEnEQQNBo0S4qg9Fzyjx-fEsH-NByGsFutnNbjNP_Tj49XV9urN7vzfry93hxOkVhu7zaX2y7F_De__vL-4TExjXMIKU5L9rUrteJcAFW2IkoLlda5M9GnIUyJp5imHA_nZZ6zEDlXCfP9YXl6Pj4fpmNOyeDjME8qfXg-v5yXl2F5Oo0ZhK1aUoipSMlLjPvjqaTou-Z_88-_VlndXXSR00_70z99ePiHHz9-fD7--DSEnED09uoywFK11beXVx-e5__hbz_nCH_408N-Pn7x7d1-OOcsm2rzt1-_e7faWgfrxvz-OP7h4T7Wagoyx3Sx7sMcLvtOWI3j8uXlhSb9i6vLkvK0xJxy4nRRN411dxcbi-itDTHOIUYqu75TqFPhl_OJhL--ua6Nt0YrRlPZSEUUGMH_z5_ef5rnj6dTb9Tbi63SgIUARDn9fD5tuxZBH8fzrm02TWNej9fIUy7v98c_3e9RwW9_-8XzcVzXtmlrII4xfjoPJQsL2NpFFrB4GCYGfD6eBCWJFJLzHMclLoUPIe7Hec4UCr-cxuMwx1LOx3MK4eFxr6wdT-e2a-vKn5cQziNwTlMYT_FVUxmnKAhK23meV-vtMi8llZzJ-SrOo9Pe-k5rYVa-rpRzbe2sMV988-UXd5tv7-7G0_T8cnJVHXMqlLW2OUTK-dVo4eoqhMgAAtR1rbY-zgMKKGXRQBwnKmU6nUFQWITIKYjTwizGeSpsK0ciAFJyRs4lhXQel9OIwDQHZezx8TlOA03T8Ly37SqXaFER8E_f_XR-eQlxnscwTYOtHChQGk-nkbkohHXX__Tj-zdv3ooS0D6X7H3NgpJzv14peCWeqXmMKZYlJWNdKaV2ThTMSwAE0Fg5LwDdundV5Y3lSFVrrdbEcDpNm25tARUxi0zDkjON85JTSiGAwHA655hsWymnfWONNsu8NF0jANoa5x0T5xLrql6mSTu3zLMIhrggAirttCOhQqSdFQRkPY2j9wYVCBUuBTRQysPhHGMpBQAgjON8GofhdJ4WCXT3bqMU99tKa3RKP08jR04Lz6fxP_50j8BzykScCzW1u7rYXm77N9vLUtCaqvE-ltJYW2mPVHZ9HeYlTunT0_JyDL_78JzGKS9QGSWSlSrzEl1tKMH5ZSo5xykTYWK42XarVROXxYG63m48OseqtsYqtASf3V7crCqDmLjkVCJRySUkAgWA4KwNhXKh59OklI7E0xJJqLAQglZmSlFpexjnKaTjvEw5D0uuvF9tV4f9-XU1uj9NTdsOMU4hpcLnccmlHKfwSnMfx5lEmq6e5rkUEY0FgJltZRVLpjznNM9JRBUqREK5CCIJL3NkBO10Ka8qwIIKc6KcWVtjrK4qlxOVQoyQmVD46mqrQZTRCND2vRBbbZjIWIihxEjOaxZgAUaltbJGF4YQCyD6yuZcWCj8eeRvXWO1tVphzCzMJRdQCgBiocMQ7u9ftLEEmEoy2oOCtquAuWTqV11MKcSSiIwxIAgkLLLErJwWgFxomWPVNCllZqGcUim3VxdWaxJ5_rR3tSnEgmitp1jqtgpTJCYSKshaaUDcrTeFiCSnKSqtWKCqu8wFNdrK55S8t13TnMcJQaFSTAIE4zBab6w1KQYRYibU4owREoVlt-6UiFXq7ZvbygOwGJQ3t9dGa6SiDV-su77y67puKns-D1Vfa21CiLWzzprau2kZ3u12lbGoQCtEhYqFAZgZhWMpL4ezANZNJaJCSAUYtCpFtFag5eVl-OHhURB2295bk3M-j9PrxsB789ndZde2THKawzjO--OwzHPMOQkCYAjh_uFle9Unys8v-3mMmytLmYbnAzGLKATU3Ze_LUoBMyBWdSMoAiioidlVvmvbIqnkZJzLWZY57i63LGVZFkBQ1nAhLkKFECEu02rdt85YZfq2Ay3Pz4fbtzeiVAFZbVbLPBnrpzD3bS2Rbu5u0hJySr5pOCTv7TKcjdHb3SbHvN2sf_7l5-M0_OXf_LKQ_Pzd5XRO7YXv6iYXud6unz6-fP3FG6X5F19__t13f2rrJiwBUD0-Pr97e_P4vBcqu12nFCqQdduiqO1m9eHjIwEbEGOsRqBChanyzhu1aqu-rzXiunYxpFxyVTljVOWtNUaYjdIkUEoRgBBGrY0xGoBzyogoDKjAaAMgIhhzWbVNSsTCWmEmioVc5UKiyikWBlbE0DuDxr5_fDHAbVMZo0LM1ppUiqt9XGLXVqBwnvPXn12LqP0w7Narp5eXn337bgox52K0RqWWEKqmPR6O7z8-bi86IW63F0uYRNIyLh8-3H_57ec5JG20caqQoPGXt2sq3HStMjrMU9d1Vdcsp9E7V6zlTGgUWB_miQvbphqOL4f9s0KttQGlBIWIlLPW2TDOzvs4zd16K5K4iAgbq4GEC1XtWiGUnBEEUAuXuulLzJKyrTywKG1SCEBJGa2stc7ayoGA9R5AKQTtLJMUIqVebcq2lMKilDU5J9SGlths2v7ukmLMueSYqroqUobz8ePHZzTmYtfutjsWWIYJtDocT0R8s7t4-_by6uL2dDoKijKqpIyoSs7bfuUaG-eAYITAK4Ms5_Oy2vbea1XYWr_MYbVdcWFKzJR264s5BGDUVaUQuBSvm_OwfPHtV0Sp6dqnx8P1ZvX29uLqYivWxJhA6bqrRSJko0S_ebsriRLFuIQwp5XFz999hpwZJKUCCJ_f3izLQrloY7q6NRraqmLK87xstytUsu5rSvHd52-Q82dvLr9-d_nl3eVFV2_WtdfWWA0izGCsaZzRSoWU5jgdpvj0fIpcQoyneWGlfnx6EdExc2Yw3n74-Hh9tT0Py_cfnoWTFmMtlkx1bdd9Y40CKl1jPeq7m-2ubXzXUy5EmbV52Y-HYXoZAyXAwlOhh9MUpvw0F1iy7_X5XIgKNDoKPO6np8P04f75-TCRwmnJL2PY788Pj_MwhFhSzHmJaZpmCjyM4-n5MKXw9Dz8q7_55peX23Xrn6b5hw_798fDdx8OD8-n_RJfhsV3lTiknGIKMcdpn_7u67eXbaPH4fO7K1OpPz2e5qE8n8-Hfbry9V9-fllJSSnNIH86hA-nqbtolNII7LSyiLowAqrCX2zWrbOdM-9fXqiwUioLX9TtxXZlmZ2AQlNKOY2LNdivGq3NMMzDOLetf3tx6ZXWqLVWqFUuhYt8XOL3L6eY4ruL1W9vr1eu0iDzEOYQtdVzymNMD6fxcTh9vrvy1k3jHEKJIMOYPp7HolTf2JvLzf37RyGqK2eNXZZ4GqaurZU1rzWkJVMRCjkrhPefjoCajX4alnNIokxIFInmJccYjXUpJ6VUt6pXu94Y7ZzRxi5Lqp2dljQvkVLuNmsuXHf1eDwjoiALQYpUdT7FWVKGQspgjkvT1Lp2trYkrAFtZYBld7H23n9xu_3555_9xVdv__1_-v35PGmnrXcx0TLMX_zyi8fv7wWg2fSn0-jbNhcOqTjrX16etYKq8XGcAVAboJyIWNe2zHOaZ6Hiu7berF3XlizKaOUdEjcrTzGRsEJRBlEoTWO72lhjwnBGIVB0uL_X2jVdW9LsDdB0iiHUlZMc9veHnHJOZT6ecyFOcXO50kY9Pe2nJWzXm6YydeXXFxfWW0CwrkLtlLWgoHCaliVMi1KGmJZlmcfpOE2vW-SceX8cjFaV1V1d5RjnOfi2JWYq2XkzzME6qwzWbW0qba0L82ystgatNTGmtGTOBRFLKTkWZdD7puRYmBSaeZm0NdaZEANTVgopZEBFlOISrXfjfkANqjYomUW6Va-0ToUBlfIOsaRcEIo2qvWuclZpE_ILihleRgGTl8yiQEnvPCpoW0VZukqBFERwvT3MgQHPKTGzbuztur3cdBe198pvdv2ur9quW1KeQ7nYbfre3V6tL5rq7nq33VRKqxLwPESvtTO25AQowtxW5s271X_3d2_GGabT-e3t9m63fXOxfXu1MohLXG5utru2_vaLaweKmAqXeYkCQgIMigGWJaPWSypLyswggKlwJs5UYmEiyZnHORdiVpqUzIS6skOMGtBpO4XIxFOIWiMInscwzzEzLyEy0-F4tMZwKUohEQzjfDqOwKysTqUoVCmUvnLHZdmfk9ImxRDmnFkKF1JKKdTGMCsWqKzSShUSYUBEETZaGatZyauzQJgvLtbuVcb5GscFJBFAnJdojI6BllS8t4WABZkFEHMiYimFY86AYJRe4quwSJRWGrUFfRjjeVnmkI21heE4zEsqxzHGUpR1S8z9ts-FQ4jG6rbyVitrTCw0T1EUCqBVulAmkULMgkYrAEClQKmUEpEsaWqqum9ap-0S4_PhuN50wuydq6s2LFNT-WZVD3NUCKJAW6uUan3lalOEHl_GrrHWKFRQSkGt2r5NKTV1g1rFlH3l2q4tKccYAdQyz66pXlUpvmnOhwgAxtciUntnFX7-2e3NxYWi2FS-q2pBFqbama6uNPLVbtO1vnGOubR9O02TM0ZrXXKuq4qkbLruom2EAAAQgZm1MQKQc2bEcUmA6lXql1MRFGLOxARy2k8l0RjjNMxff_F2WfJhP_jORwS05uH5WNU1xeyUWWIuKKcpHobRV9U4R1AVQc5FYkp1ax8_HpVxGgkA5nHIoaB1wgwiuv7ir5rNTiiiCHEuMYPSxruSS931Mc3b3VVJiYVzSVqpMC3tZiWMWrsUg2sqpiSvy11EayvmDADnabHa3tzcXq9W1uN8XuYpel-9fXP7-ddvnu6fVn0Twnx9vb15e7nM42bVI5TNetW3HbAM50ER7Pf7r262Rrjr6g51mIvyGqzerTpvsK78NAzr9TbmCCTXV5cppRLmn_3iq7Qsq67t-3bV1ACoAHMucxxrb61Sb2-voMh61X733ae6cetVG-cFRIwBZ43TRiHknPumImJgAMSSojVGFCoQZy2IoNKoEES0NcuSnTWFBEDFlKgIsyQhIq6cpkLTnAUEAKYpnodACCxgUM9THGMMMa27iglQAQgqZ8dp6br6YldzkVgo5DKHHEgQX1NGiFqsUsfjoo01iNa45-MgMeaUDnPgVE5j0AZv310Px9H5GqlsL7bnw-HwfBTR26uLH__4w8Xlrvb-6ubm4cPHpmqM9_268t7suq7z5hhnYGnXjdFKkcRElfNf_8UvwjCD0a6qqqYT1M_3L1VbWWetUs5W0-msjF3d7RDUchoUFKXNPJ5dU1dtm0K0CMJcYtSvtGT687JAO8sM1noqWRi0c8CsrU5LYhDQSgCUMSxsrC05oVaA4OoG0KSwrC8uxtOsre1udhQmEbV7c9VvLkX4fP_TOJx_fNybyu_WG0b0q7p23jn9dH8_hLy52v72N7_sNhsp4JxDhSLYNvU0Tm1VeaMv1muh7BrvvHVGp6UYq5qmJc45xa5tNEqJab3rau-ZdVXZtvMrX2vQ1mhfqZvbjdOolDSVo0I_f3u5bWxd1edh6ne9JSkxMnDM_LPbW6WNSN5tVof9KS3LV1-9W7UOUiRUMabrXbPpWwrcrVxjDTE5bcJ5UogoAiVvNr0RNgov--ayb7rKGwVKJKaUctRKXk4D5bwsyWmaMz3eP4myS6TExXjHldofF8pYVXYRedgPU8jDvHz7xa0S7VvLxjw9nbz3m6teJdKIDy9Hy_Lv_nD_ze12ybTt3P_yH78jzkqZv_7s5q5trXCYwnblf3w6sLfjErVGW4oAOQMjEQGMczjPYeZ0GMclZRIoKMO8hCVxKsscK699a7ttswy5tqrvPSf427_75d1u9_ZiS5k-7Ifv37_84Z_uC5E4fZ4n17ndO1tV1UXj45hU5q72b3cX_-f__jealZXyy1-8ncLy__xfv98fZ9tXCP1X17t__avry4vqxymdw_D3Dy_DNF_fbEosnDjFclu1ac6f7VbrurpbtV7jYZhiiJV3WkQhblfdzWZVpqXzvrZWKYg5odLTkiplnvcnZ03d1Zu2tajDEhFRaUXMRdQ-hu_Oh_MUNgq-eXMriac5gVJ1U-2X7CufEObET_vDzXbXeTcsoWuddniawuNh3IfQVU3duGmJh3n58u11LtxZeDjN5yWC1cQoCOdx7vv65TDMY1DOAAODejqPT4fpOCzDNDutzqeI1iitlzkqpQ1CW1WvponCnGMuQq42pfBwHlEJqiIKpvPY77oYMnFRxjjvltPAS0rnBRTYtmZRLNLf9Pm8yBxJqOoqJFk19qZv_w__6q-_fnP908fHf_zDp82mvri9FoDLq01t9PT0Yutqd73WxopA3bXH59PF1UZQgNk2DVqkwhTCfJqJqNr2QEJxVkqDMcpXVd_XXUulGGOrZlXyIqW8Lh-ds1prKZkLirY5BUHJp7OiiFhKXE4vR7dqpofHpmuW8zCejt12l8bJGEjT2VgUlsePj8r4umnbrtGoDi_HzWYVQpnnpa1bMJq0WO9zzpv1SgAMYslZKZUzgRGjtXduXpbzHLfrC2s0og5hMQo36zUTLDG2dT0ezjmWGNK0pGWcu3UzTjMK5Bg55s7WRAUVCJFRKsWUYqrqZv9yinFxlVcKjPfCfD6cmrZVALmQt16yGKuRSVkM42ytyTFSSBbVcp7CaaCctJI0zbKMqJBTySlzljgtVeeZlYFOl-yU0ippg-dxUVrHEPOS05xBoddGREkoMSZJJaX4_Ol5Wpanp_Nhzo_nMaIWB05pRO2Ubry9vlo33oSQtcLEDIUP90dhQgfe6a4xqSRr9c3ba6er1apdWfz0cIYlTMfpze3mb__6268v-0_vH06nKZO0rXu77rZdYwEKlcKUEglgfj0zA-dMzFgKh1y0tpEoF3LeK4DTFJrKj6EczlMstDAob44x9ut6HJemrgtxoZKJUipVXQPoeZmVti9PB239vCxloap2tnbDcRDAzNlqFOGcKGVARCA-hKkkESbQZLURq1EjIuSUmaSIzCkJgvDr8FaJgDYKXtvlICXy4bQQs9IqFxFirXTMmbXJWUKkw3mxRosIA5BgyAnRhZRjLDEWQcjEp_PsvNdWF4QwJ0A1TFEQGWQKJSQCUCAoWi2hTDGw4GkKyqhcCBXOSxyGebVuEFVJpFBrVKmwAIIwC5REmenSb4YUC1EOyRobY0LURAURtHZhmq4vNhpgGCdiMUYLYghRa6UQNrtVmBclKADLnBtr-6ZWzAYQlEIRYCERZkGNVV05UCzMhTIVEfKuTiWCCAhM89x2zbLMVdsKF-tNv6p2Fxtt0XhzfX1Ve3u1XTPlFENTOSpp06-8s13l26ZyCG3lLzZd19SFaFlmVCbGmHLpu564dH3dVZUF5YwGjSkFbRwDvyagBCGkkl-fhFAVKmjMHNJPnx7W65VxNjPPc3HePe-PVxer8zSNc7hu28dpedif__GH9wMVYWnrOqT4cDyPJU6p1E1DTAgQpiUuadX554ejRk6JxuP56fEFnGalyhikFG3vflWEEdXq5i3HxToPiKgUCgKTNlUYx369LiVrZ3LJ1jkQqKpaGVW3HVGq274QWec3F5ucslLa1_6Lr7744Y_fV1YPp8Nmt5OSv_z69mdfvnv4dG9AG4af_fxLpzUyIJX1esVMh-fnLz_7nJVgoevby-vtKobwzVd3KNBW3ikbplkZ-_h4vL7aOAVd35xPUwiLt857W9V2t1ulGPq68rUTZmMQQCnE680KFWqthmn5_O3t8TxcXmxSCjfX266t7z89b9btqqvCQpV3YHSO2XmLAM5ZASw5WWuUNlYZRMVCzKK00sYscxQQo5VWurDElLVCVIoBzlMyClORJRZjEBAR9ZyyUppY_lwVUBITWadDyN455zUTNLUlgVJoHIKvfcqkrEGBl6fjaZpDTrvtBgQq6_qLZhwnRJjm8P3v7-tV9cW7q8M5CqolxK5v3__4kGIpJX37Fz_78MP7zz7_rOval-eXr779-ng4vLm7nMblp59-vNpt_tt_9Xff_dOf6qp6eNgP--Onj08XVxeZKY-hbdqLz7_d7brHx33JS8klDYsgppys892qTzmCNcQMrIw1ApKmhCJ-tQEm0AqYuBCnXK3Wr2cIYVSAAgIigq8fjvFNxYhCpLRJ04LKLPNcb1ZcSphm7aqyBL--iHEGYb_qtTFaa193SiMANY0_PR1oTlXfUpiG5zMV2n3-GYpalpEZwhRuthtrnBDkQpLz7nLtrToPw_HxeHGxu73YVMYWEWWtAkTJXdeEGLbXG6WQqDR9m2LaXe6eHs9t563zJWbnlLV6vdlO5-Gbd28sEhXqar9uWgG2SjuLf_uzdwQ4D-Nmu9JYKutuLrdr644hDHN6FZOFlGtnj4ezQWgae3o5NF0dl-X8clqvmr_6-tYqNt5Uvm2MarvKKo0iXNhbXbX-ze2lUaiYrncbpXjdNu-udgbRG20NZoElpsP-nEoGgUQiCIkx5zJGmUOOJMMcj_NS77r7-zGXFAjmWLDxQTgz_PRpf7lbjyHNqTTrmnKZprCu_DDH8zA5b9vavByGxqlxIY-sgO_35z_cP346zmcqde1zSj_sgzOYI-VSjMfzMr-MYSJWlU5EcYq5yPk8G21zYW_9eV7ilBC1UnC52x73Q1_7X35zs-27bVvfXm9jzveHU67sP_znD8_nIMrXq0p37vH5aCvNio_3SziHxrpra392u_2Xv337bt2pIg5k6Ku__6f7f_v7l8vb9bvL-t1V9WYFb67aT3P5N394-IenJ2VMpRwpobnExD-_3X62Xr3zzlv3zeXqZZyp0BCLds6gQoW-qpBpVztNeVU7o7VSkIosMSmAlW9DzJ3zJFwb57U9ngetlW8qp_Sf7p_3U0Bj37btm86_udw4gP0cgOGY4qfj_HE8P72cv_vxYyH67OaqNu44zwIyMz8M6ZALV5oJ9qfz7368r5z97HJHGec5nMd4nAIyHM-zNkYQACEIfng8vbnZAkHvq_shfP9w9JVPVIxxp3HWBrXAuOScpSgSgDgv47ikLO1FXRZAEqX14eGsmJXwOIW85GVYSAgUoNamqsIQvHcUoqA0qwZJuIivfVPVEBYmVuD_4p__bKX0F2-v__Vf__xnt1ujxGk1zRNa5auKc_zi7jIc5jCc__Kvfn18PpyPp75tl2XabrdxifMwamfCPIclMxVrbVXbMCUIiZZZREREV42zziqFyoynue47YAjzWKbAJWMpFJPr1zml10FjIUZgo1lyRGtM5eMUQCBOkyBbhUhlPh_77WbaH7yrp2VUGrgUzjnMMczz9fU25XQexrZt5mXgHCuvt6uV97rtm9eSTOV95S0QV9YN03h-Ps_DKIyn51NOy7ZvEDiFeDjOm926iDhvhGS9Wjnncs7KqLatmsYDQEyRYs4pL_NciqRStEIqgkpppU_H48XlRckxhpRSrrw3RoPwPM_aaFdZrYyzVUzLsiRiFs0sAowlZet0ZQwCoZI8hnXfkpR0mEQyAAAUpXAZgvfWNSgMCvQ0LBodaCgpudobp_pNQzFb55ac12_XscgriWLTdUWESgEmrfUyxznF79_f__jTp-M0z1Lun1_GIRmHtvWQC5M0vWOE7WWnAec5tJcNJD2fI2qiFOeQwGDXrX_97Zv_-i9_3io7TcuP758DpX7drRr_i89vGqsBpXAWEVI4znEJeQqRRRhAUE0xwutoFpARMvNpiqmQACJgEl5iOaeFCj2flyWkkslpXXsTC70ehGIorvKRS4gpyysTHFMqClVYkgiM4wwiLKxQUSk5J6MRRI3TQkxeq7AUVqo2NgtRobhkUKCtUtpOU9RKF6YQs4Ai5JyL9TYRxVIQBATbVX2eQoqFAVxVHU7T8GeZswCqlIu2PiVSoBlEKTWMQWk9zmGOxXgnIKXwsmQEBAWs1GmaiXGOKWfWzjJLSpQyL7HkQiSSS6EiSuu6c5VxLLCEYoxngOM4HaYFBABAAJjYWnsal0SZhH3ljdWlCDEJiK-qHEO_avumKkUS56qyObP1etU11uraOCFADUDyNOTLTVNXrqkqhco4p63iUkQ4xmy99t5L4WWJSAQiQmyMESqUJcXkvSPBqnIhF2d0IQRUF1ef1xZiiF3T9JVtfPWLb94Ow7zt6pxS5RxzaSpXews5XWxXF9u-doZKUQoRtbNWa9X3PTMb1KumsVo13mutEJhBxRhTKTEWARBQqHUujKiYJZbimuowzpzJOj-UvIB8un96OZ6WWMSr379_WDj_08fHf_rxfonlD3_66Jr2_vEgIr6pMgGhFcHPLy5Tyn3tz9PSrH1M-XwYA6VpGJdlbi86KeI8GmCtlL7-9b8E7XKOeZmZSRi09QzKWut9pxQh2phSf7G2tqIlKwRjdS55d3O5LBMAlpzqumpX3Twt69Xq7Zu7u9vrH9__tNls2u267Teneer7znq_pBhCuNuuL3frjx_vb2-2NzcXy7ywiDV2t9k9Pn1a5iWXdPvutqms5PTuy5uHn54MmlXftq03Wq9WNZO8ubo8nIZVV9dtXXmntZ7HRYEtVJjLy3746us3p5ehqb2wiFFKq8vNqgSmknIq7ao6n5d13-acd6uVtcYZZYwFoLBEAUEEa62IlJRZBBUqpakQizALKJyXrBCU0UoprTAVSqlYZ60xLEgiSqEw50wKlbaqEJ_HqW_bcYoF-DBM3tu6clahUjrMiQEQFQNMU3ROM4NSZhwna3whHs7jbrva7fq2qqhI21SneUmBPn089J0T0OvN6sPheC5cgErhzXZlrLe-juNkXY2UK2fvH_btuq2b-rA_tH2nQJz3IS7XFxen83m1racULi4vpmm5vLtblphDqLomhfJ0_3H_-HR5dzsO88X17TCcAESMMt4a7ZXWORXOyWg9D3F7eWmcHc-DpGKaxhhjjAERIVJagalIRAFwiKCQsyitfO2lkKAIizImLcHUDpViZrSGEVEEmQEkpVT1GxYpYVIiQGSbRmuzjJOpvLG-QC5TmI5n6-p5GkHD5c27LJSGSVF-evxEJaWUUZu2r4-H6e7NtVLmPE21bUXy27urL-7eXF_fTjGEpaxq75xdztN61Xlnh2Fp6so43PTrcB4VYqVV5a1GVTtztbvY719-84svt13zeldYrertqqud_3Q6fPXmGgBra-rKJcLrTcuoGudZowgAIBQOMWnFu3VdadRa9313udk0jbWoQ8y__OLuYrMCkU_Pc2P4L_7i8zQkC7xbNbfXu1Xr7z98utt0lObPb69Wra-0vAqFU8xzzPMy50JLyNY7bU3MZY5pmBMLJoFIJcc0zAsVXgIlkmHOxtnEvBC-HM7Hw1QMvtv2mOlPPz6exiUEca0mrTLInIoQf__DPWh9_3xu63Z91XpTnc9TMRQifXg5V77-7a_vhuOhqZv3hzES3z-PCPBymsuYpVDJrIzSTis0WmkQ0EoZV3uva2eEBUBWfY1JTtNUnJpyfv9wqBszL8ko1W56QJ1DppKIuDIoudysupt-9bOvr3_z7XW3aayyVVedS8xW_fvffzid05zycF6gZA2Y0X08xX98PFrNFfthSKvWG7T_4mdXX27XTRERchZ2ff00zrrgOca2qoj4v7CA05dXO6fEa2W0ApTEJYMoVH1ToVaxpMwsoKx1D_uj1sq1lUf1n378lCh_cXN3OBzWdWPBaKP24_Ldy2HRsjjFvj68HOcl1N5fbbcKcAxZeau0-t1PT__0_ceX4zyExMzjPP3qs9vWuVJEIx5DOE3z-mLT1c2SUlNX5yHUrXs5jq5qHw6jWP0U43ePh7pxzBJCOZyXUyrGqVIKsao6C406PI7MhILDlOdzBMRlmpxzrnLOYSmsjBMFtbeSixbQSlnnQKFrHCqp1900TEZbW3tjTBoXrZRWyjdNi7Lr_P_4f_xvfnF1sWpqRmGh1eWqX60Vsdem8zrNcXux_uKLm3Vf_8Vf_erh4Wkapq9_-c39-0_WKus0EysFJSSh8kqwAS7CooxCV1Vtb1FSziRQmLQ1TIIKtBCFWWtEpeOSwGhkMtahrdIUqq7XinJgZNJeQ8qvDmFhsd7mxCVFaxWFmVMcx5FK8bWXMCzD8MN3P-i25pwefvhxOrwcX04k8unj-5CKQjOO08vzYT6N__inD-t-6yrb9Y0CrLs2h6iYhPM4hjHM1jhd21QSC45LsNaxgFZQeX8ez6vVZppn1GoaFxCY9icWFhSB10WxGG2EqZRiLKaUx2XwVb2Mg7bWOrfZbeMSOFNOQTvDBZVHZFqOs6AYAI2QwoyIOWfFgFridEYGDUViLjkgaGECJXmaKAQwAFqqvibJzlcgJKlwLPN5LMTzGNGauJ9B67gExWYa5sLEKG1bV86XJRqldtvmatP52lPknIhKosxpKvOUYkjGGBA97KdSRDk9HBYUNA0-v0xE8fLNZcl8OJz_1d_86rZrcwhWY-Jcd_Xd7cU3t7taWCOGFEHjnCgXmhOl16w9qlw4s6DWOWcBPYcUqWinj1NgwQRQkBNBYZqWBGjOy2S9v384tJU9nCdnzRgSFQ5zGOdwPk2HYbCVG8dlmIIACJECjCXnQgIgxEtYWCFqDVyU0gIoRZTRlauH06wMpFiYmYVTzq9wTIWYQxZgQB1zzszOmRJjJklUqqpSCsZxzjnHXKYpxJyqyrnaHY5TKYVY5kIkwAqASRCXmAWQiAAhA8RYxnlxTheSEJJyVkCs1rGUYYmk9BwCiRSGmLNznpG1UiVz4rJu63lM53EuxL5x4ziGEBmxaVwmemXvOm8QgKQY67TRzK-PBggg2hrOJACrVeeNiUTw57K86ttOCXvnvDVPn55urq4S0t11bw1KYm2MtlYpBlTjONddpV6Vx6Voo6ZQvNOmMkWYSlm1fUwxFwKU9bpD1M5qZPTOVs7wMk1h7lf91dV20zTWqNr5FJfKYFP56TRfb1dNXRkNXe12m1YBW6VSyc57AVAKrbMppcbZtESvcFVXxmkQIZKUU8oFtVZKFYI5BlFKK13o9fuVpcjD43GMoW_9nOnjx5ccy3EYv_zyze9___79y8tC_Om4_PVvv_3Th-ckdBznnODDp8M_-3J3mBgQNZghRA0wLWGcFmvU-z89pES2rdM8103DcwEpUPhi_cYYrf03_5JSsbVjKQpQtEFrmRVqU9XNFJJSjEoLo6Ty9pvPpbAyWhjH8_LlV7_KaWbhVHhZ5i--_CyNi_XuNEwaEIm8RWftMk0Xu_7zu6vjcELhVdsap63iuqrvH563q3636W8utqkEp21b2__67_5qGmenzc--fPvw8PzLn33x2WeXh5fh5mo3xrmumrbyyxKAOIT57uYyxdit2tr583i-uthYo7frzTTNu4vVMgUEFJCLVSeg2tbV3nprp2Ha7jbzNBlramdyIa218YZz8dZ4a4zRBpWwCIq1qhRChd7beY4sAkpZa1-vstronOk1RUcKlliImYiqyiAqAAClKBfUumQSQe2M1viKuxbiwvK6Ls-5lEzW28b78Rzb3gPCMC6rdZ9Lngv1bftyGNKSqtYrY16ezhTzetuK1c_7MZbSVD5MMQWOiVHjcJp--NOHm9urMI_DGIhkfbVKIStrm6oCkhyDsnaeZlRa2cbV1enx2RqjlHl4eqzrbj5PVW2artsfXqZxISqua04Pz0pBOJ_nYTHetVWNINd3t4eXY7fu-8vVMs8lkPOVMqqkmQop-0q7AiZCKXXfhDEpX2lf6arinFFjTtnWzeteQCmNyjCLsS7HqESEiuQsxNZbX1VN1wPq5XxCXcWwdJfbNI7TOCmEumnSeVDCykI4npfTWTnTbS6rrp-GMxEiJ6D88nS2RnfrDhNNSwjDZKQc9ucpZuN1nOd3F9t_8c03U6CXl_N6u3p5PnhfFYp916JSoGTdt_12pY1ehvnt2yvKOcWgrena5nazqbvqdrsNcXl7s12tGixgrUPgTe877w_n8cPDUybxldFaLyGyknrVaI3GaEG42eyuL3csUlnlrPYOW18h2tbrTWV_9dnmy5tdy9B6XXvd1dYovl51b293X3x2e9F13iorkojPw0smnYlTzKg0KI1Gx5hiKEss52FZQpljIoAl5kj0h6chxpgK8GsCYQlECoxopUbK__inh8fjCAJj4G7dzBznuYQoRfg4xmmZXWNToi8-v_7wuH9-mjcX_aprnWht4OXxvG61iL1y7vZiy84eHh8ZuPWu6xwpAgBdWRBQxikD1hmtALUCKOttfblpHOdvP1vnVIYpieIhpef7AZhL0jkRKrDW-BrSOPet9Ra-_fbqV5_d3ParbVvtagegjLMz2sMx_sMP94-HOZbCVD6_Xf32N5fcVkPkl2MqOdcFpiF-c7v67_75V5cgX25qShSXaC04b1Hr-9P0fBiNUYmKVUqIura6rP1n25UGVlTYamY5LukwhUpLWztAdVqWmdhXFRk8jGPX1W1TcaH_9NP7mcpvPv8ccrlYt1rBeQnPOf3f_93vnk8jmypO-eXlqFBaY6raret6P4Tn0xQA_v6fPoDSb9_cxJK_-3TfO7fpW2Y1JR5D_O7-JeTsu8Y5EzOx8DyP85KWnFHbOaXjcchFPj2Ox3kWVhrACsyhJE3PT-clUcmv8YBlWaLVxnjfdI5NGfazd3pKS4pZQBhAjLIauqYWEfTedw0z5Lmsdr2yOofses8paQEBtkaDoEL55ldvf_P17b_-Z798s103WrNAAZlD9Mb5yj0-vazWzbu7m8Px8O7tVW0sKHm9Xr39-rP7D--Boaor3zZhjJIjZzLWl2U2bZ1CANRxKVXdcoolxJji_5-m_2raNcnS87C10j72tZ_bfu9y7Xump6fHwAQISiIIkEEQIEJShM7083SgQ0ZIiqAUAklgAGFmMD3dPdVd1VW1_ede95j0a-ngG_6GjMhYmfe9riunYIxs-iVRYoFSq5xy8kkZgwKqtsk5g5BCqeIm8E63WgiBgMXnFKJE5lxyYQaybc1ccs5NW0nBAkWJmSiH04gEMbgwzZjifDyE0wCSNFGah_317nS4325WxgqjxNmqef_2A1Dc7Q6H-9Npv3ejLzm5cZLaunHO0eeYkvPjMIyHfQiTG91i3WYqORaUomussnIcJikfQuWktBRahylI1Nur2rsCDMNh0rXJMaXZ1XU97A6VrUPwbdtALtM4U_H9qtZaAWC7XiALYzUQsR9QWcICTBBi8C4nkvLhywKBAWKBnCE5kfN0GFDKMI4FSFkhCldNXTXaaCkExtnF_W-bvq8kWK2Fz6fRSwFVXcXjKcwp53yc3aKvppkfXyzbziz7vrYaGJQSm21vOrs7DAIxU5mO0zfvb1arhikjYiJ48cn5cX8Yh9PFevWv_skfqsRa0dfvPz55el5b09f2fNVLRuLkQwApqFDKnImJmRFyyinT7NMwOkIsjIXYxYxCjT5NzoVcEoHPUVh1HNwc4uCC0rLr6uiCnwKByMTTOEslYy7Dfqp6WwDn2SktSyxCqlIKARZiwSwlEIA0CoVkFIVyDFE8_OEDAmeBSMxCgUAZQxJCpJiB-OGYUojM6Fw0VpeSQ8zeJakFEhIV77NtDKBIIROjm2NmjCUVxpJJKIy-PMDmw9_vilDIkDJNwWtlCgtiKASpMBAbpUIsiXD0s9bK-0LMjJiYYshCKiKe56wbnXO5vhulVCGklFLb1FQyKOl9iikbY5QSsRQiUUoSIFwoCCQESKmUUi4mJcRy3YVYSi4IuOwaXVlIuZQMQNM4aamklYgyE2ur6spKoxgohBR9EFpVSmmhqGSljZu9MYKYSyRmsMrE6JXSJRMVFCAWyzpnQoYUQ98tQvGr5UIKWRnTVkZiEZy7xjRGXZ0vnz85b63KJZ2fLS7WCyWgb2siAuRpnqWUJRXnQolFKuVzfnS-Fgyzcygw5ZKYYy7491jVrI0CwFzK4TCqyqZSEuD98XQ8jLrv33y4Syk-vTzPoTy73Bz9fD8M13fjcXBvPt4xgDRqjCnHnEt2KH7_5qZwMVa-f397OI0hlTB5gTydnJBIhRFLGENjKucGYBiHU98t5I_-2b-ybSu0YAJt6hILA1VnnUbM8yykqBdtiKVuG-8iICijXIhVZeu23p_uUgqb7dXsRmsqP07aVHVtHnhYTx9d7vcnyKiU2fT9NM05ZqnEq2dPZzfnlGMIn7x65by7Ot8w5QeJ4-x819jPXjzhnHL059vloq1LKKBk21VCKhRU19YKDCG0XTNNs9XaGg3IEvFBT7vom9PpqAVqrRd9K5jbunXez7NbLlpkXvStAhAIh7sBBHsfbWVSjFLKyhhE5JhBYCEquRitfcgIkApJJQlYKFGIH6jepXAhflgNIgAUUksxOmeUComIOISgrWIGFOhSNrVBEDnnefZNbWtr3t_NAooQYnCRgaiw0irnIqUQKKbRmapigJxjCj5maptm9j74QMA-ZlsZ1S0-frgxVgmJIcFwHKSEVMpqvTyeTn3XnD89Ty4w8bg_vbveNX0LXJ4_fT66edl2Q3AA8N3vvi1M2-3yMLnFdlNC-OTFEyWrb799u1xvhNTMgBLdaRZCnH_viaRS5jBP08WjZ36eL56-vL-9Q2aBgkEwlRjy-fNXaR4hp5wiSgW5JB8B0LRWWiu0LClobf3sddtIIdrV2Wl3kFIRkY9BVQ0K9eCeU1pJZM45xlQveqG1bPs4DVopBPHoiz-Ip1vnQpkmLaUQnKdpdb6UDIkAhSHE4OfkxzhOw-RW26v73a1SKositCalPtzeXz2_mOcYi392-XgM3jFJqy4fn8eQBIhEuTamED27Oks-1pXRUkopzjbLRVdvt-eoxR98-oISTc4brQtnW9muriqjH59tfUxWmbNV3wpDESur26pqlHy6XV9ulqu-eXW5igVObuZMcypPzrrn260W_PLx-bqy33t1ta5UJUVXqb7RbaURqa2qVV9tVu3FZoXIfddqRKKChXzK0-x9JGLMBJmhUMmFrZX7k1u19eQTEyXikMsweyFUhlIbObviI_lcXMjT5GcXAagk7s5XN7vjdJr7J2eJy5ByQeEJWMgpJpTCAA6ZDiGFkEkgSbE7uMWiToXWZ8tu1dx9HP-LP_vi7YdRIa10ZaQE1FRIWgVBlUyGiSL7WJa1wUISsKnldtX0rb29Px59-N3tyQ3T-_v7aUgKJSJ2TVcI-sa-eHGZ51QRNErlyI_7_uXZFkLR1p6tF7Yxpxi_-7Abx3hzOwhlTqMHKk9eXPW9CS799s29P00X0nS6_vPPX_7w-dXzZeNmt-3bLGmeEwIWifspvt_vofBy0bZVtd-fEojvPd1aFMtG11aXkJvWuJB3s8-JVn1jrQmxvNkNoJQHfrPbj8dpu16s6iaEeJgdlfJqteYiFDAjH4Z5T_G3N_sYIhNMMceQZheBcXO2-P4nzwcf7k9jv6rrRf3bv_uubvV31_chp6uzxfN1X6-7BOJ_-fWXpzmOPnVdf7M7CICYy243_dU3b3766eO-tzuX7g9DvWhBiw_H0Zjq481h8O52CCRA1TrG6F1EwBhSnOPh-igkhhhDdKkUXRktIMzRNhaRS4glxUrp4XDSykqlmq6WEptFk1OQpKCwlNJWtl0_Ngr6rs6x_PSnL3_2g1efP7lcWHnVL7WRCFCAtFTeudMwa61ePLlstPhwvbs8W9i6_XhzY20FBYdp3N2chuPgQgzOm9ZkH3JJADLlqLVJOdvatosuDCNAERqTTwKRCAhYCNBNJYySbU1ASsmqaikX2zZV3zEViBGIKTMx23aZklNS2qZCKUGgEMxMuqlBKgEiTDOw0BI4uBR9iskPB8HFz7OqbYkuzdM43JH3kgml2N_epQyFhfe-bxcxOER2zkuBDKSULlz8NHIhBogxtstOSi4--uNQcpZaBReDC0JIlIJzqbuuFCiJ26p2J5cz68aaSpcC03GikpXRyc1t3xfvgQswpJxsXaccjDXa1sHn4HxKNJ6mUkgqyClbXaPUqBSgCOMktKhsg6J4V0ytIT8QQwrkBIAPlWuOWSFgiHlyOUY_jX4K_XbJCBqh2zzWkWJiP0fT1E-fPbIGKmvG-2NIERlPhwk1OOevT_OQspsjKgEMMeXd_XEcZyIeh7GujTR6teo4hNPhEEJKcxgP47j3__if_LmB-bPHV52RSmAucLs7PDrfGqlWjZ2nKedCwDGUlHIsPLnkQoiRQImQi9DaJyLgnIkRQikuEzGjULnQYZrvdqMysuq6RCW4KLRabbrh6AoxI_rgpdUEmEpRWuWcpDHjPCGJnKMSknLOFMmHXChlRhTKVlJgCoFyYWLvPSBIrYBICozOKxSMXJgoFQYUEnOKKWdtZaECAFILBEChGUoKJQFJqWKhftFJRCPlOM5zCKtVP4bMiFIIRMkAxDSMfj84YgqZCSCWwihzKT5kRuDCMf39IASI3qfTFARCZsopm8rmVHLhlJI1srZmv59GH9uuAoSUk5CKCqdYxpjKg7GLKMScCuynefZRKSm1BERgZAYipsKL2ropzN4LKaXSMRfKFEu2lVLadH1zvl7c7o-LRZcLNaoiIiExx0LMQgg_eSVloSwAx-OEVmkURCwfZDpCSCP_N-2AMVqWUgQgYDnbbpgSMIsCm_XixdVWUsrBS0Gdrbuqeny1zTnFFISATVfXle6sFVLkUg7HQWpDmYd5AqWqyhCXdd92lS6FhFKFKYbAgMPopFRSSQBoanN9c7g_Taaxp9mdJj8nPvqwWNRfvfl4d3Il-EebZd9UBeDf_c1Xg_cF4TROUgopVSjw-atnh8McXJxCZGZ84KZLDDF2XWcbmbFMp2BaJQSWSLN3AnJKpRBoVTXGyO_943_x7NlVBjieynLd9pv14UjIaGuTvG_bugBvHl0iU_BRa2WsRZQpxKqug_MS1eGwW263QimXyuNHj07jSSBOp7FftqayTz95dHmx9W4-WzWrs6XW8tMXj93kPv_0cd_3ouTz7fbucJMKv35_U3KkGP3s-7ZZ9N27Nx9_8uNXccrGCNtYwXg8nVZdW0IKcxjd_OTqrKqrafSLtkaG03HQWhopu65SQszTvFyu5mmsKmuNRCoCAJmMVkZJN4XlomtbI5Rq64qo9HVFmR5cdFJrAAZEBGBGRtRaEUCIWSjB5WHbhKWUDBBTVkoYo5VQRDw5Z5TURhcGYo65AAqBEpmFUD7E43FKORlrJGMh2LRWW5OJm9Y-lAWNUUar4IOUsl_11ze7ftHe3A_W6JiLn_NufxJSGmPvD8P9YVJGnY6-a5vjFMbJLZaNQrFZL_tF7UNklm1V725Pq-2CCBZd062XXdscTnslJCPu7w4IfHF1ud0sx2H-9Pln17c33mUhpJt98KXrG9VVp_0EhYSC6Obp9hRdlFIB4v7mrr-8HI4HW9mC2C8WVV9Pp5Oq7HQ8LM8vjK1QCjd7U1uhTfJRVw09bAgJKaSoFwulK2Jyh722FpiF1TlmaRRLBCaBlMdJCCE1-tMAQFjV0kgk9M7FmMfdjQDO3gsUlGI67kEIVVWQ3bjf5ZD79aaqDBCV6JiVP-7PFvW7b97dHsfufNlbq7XMyU_H0_WH_TiNqZSz7Uqh0hJXTXV5tt50ndAGgVNMVumPt7txmpeL9vJiK7Uxxi6sWdbKam1qLa0qmbrOrjddrdX5ykqt-kp1XU0haqC-a_u-nVKOJUdiyKABmqr66cvL_-oPP_mjV49fnG9WjXh5vl73ZlGZ2gql5Ow9gBBEx9G9-XA7jSMn6hrLxEZIINjtx7fXN4mQQMw-gVTOB0B0PuSUfSgp5t04ATMDupgABaFkkKdxMtpMIY0-FymmWMaSJwX3w-RcnH3-eLPTVYMa373boVFCKh-zMDoUJiHmOWiEqmqsMS6W63Humvo0z_vdvNksEsHpZjg7b09Hf5pO__nL13MML662rx6dnS274Tg9vdo8XfdCYF9VRst1U52v2ifbtZW6q21rLEk5h6RRnF_0iLqqKi0UCmGt0YI2fQP7qAp--mj9_GrzeLO8OFv5ybOu6r76eDh9vB0-3B-PJ3c4TbpVzy76f_CL89WT82F_-Pr1bnc_n5v6Dz57_v0n5-u-VRLH0zhRGabyfnCHKd8cnC8UqGgtBagMTJkQ-HLZvbraGoZKolJq2M_S1JHw_jidbRdt13CBe0_vpwm0uXfuq-_elUQvL9fPzhcl0e9_-4YFPl6ubdtYpW_n6XcfPn51d7qbaXfyU4opp-ViqWtlK_Xk0eblxfbm7vSbL1-HVFbr7i_-42_-6Keftl23qevzRxtM6W_f3v3mq3dfvb_t-0VhDET3h2OzqC6363__y98u2mbbdVbZ3Ri-urmvjH1_OxxdAC1vrw8Jyv7oq9pkYjfHlHLd2uPeSaXtslquW2NVDjEkbvpmOI7WqHGOTdtePj7v204zWSsM6n7RPv7e09P7gxVis1350SuJPswCwdZWIwmgRV8v6_onnz35_pPLJ-erR5u10ZKJgImAnQshs9Ziu16i4NPBm85orb99d_v-5qaA_vrr1_d3u0IQYyRgLlBX9nh3UNo8cO4FIiFKoU1VGaOFRFQ6lcJExurifXQBc4ECyihllHcBGAoVqS0KWYCCS7rSOWcpNBpFJQupHhrVgEUpGyavm44FE-cYUvZpvb7K0QktpQKljRTovTOVUFpKDWEcOWWUAIxcUkph3O_apg1uavt2f7cvYTLWpmkulM-fP2Zgoqy4ZOI0zW6Yko-marIP82EkppKj0iqlZLQRAEKK2tbFBRIWtWiXi-Pdsa1tnDxBjtMITIxQ1U1OyShVCgHlOOfC1HZ13dSZSnChqdR4GhC4biqtlURgJipFayWVEFpK-RCDSawkoBBKglIPEBtANFUdJmeNLjFkH3QltVU5FkR0MUDVvHn35nb3jZQLgHLY34fBF1GEVFLKOc71uhr3TrUmc4KcFGIOEQSXTIxIBFrruqnv7wepEYnn2Wtp5nFWUvZtY426-_j6cDz92RefLZtKSXVxvpxDbmtTa221KjkVJgTBCCHT_jDGUgoBKBFLkUoMc8oECIgCQyaWWFj4lGNOU4gg4OLxxrnoXNK22h8mEEgFiRElpvRwIiUzSYl9pwHF3e29qar9_Z6Bs49N3Xs_lZJBICBWXZ289-OcEwGAtRUKKIkfcBfM7CePSCVTzqytRiYfMiEQMxFoqwSgcylnIiAiLvyAL0KjdIqltrquqlBgnGLX9SFmiWiNzSXHkGPOmRiAUsoFkABjzrEQoPQxU8kMVBgKQUjkQiJEa7ULtO3aUCjG7ENCBmKSSoZcUMgQc22tVFoCGm3mkAvAMIeY8oOEVEg5TE5J7Ns65yKFlBJRilRyBponn3MG5pjLetWlmGxlY3SIWFc1CpFiHp1jEG1Xh5CcdzHleQyZiBHGcdJG60o5H0phNIJSllKElGqrmUlIFFL0fZdTFAIBCQiZclNXwFTVtq2r1aJ-crHGnN0wrPtqs2jPVt2mb4fDiSgboxurz9ddSWSMGqc5hIhKGVQpF6mwttZWCokuNwtgQKlccKdxHn3MhQqw1GqeJq3sFOMwhbqptNY-FJIClXx7vQvBv9lP8zSlHO5vD-uLzcGnX373dp4joMwCWMlQuDUmI79-fTdPTmultUQh9of9anu2Ow6V1Sfnhv3kfay7JsxOV1pqeTqM9aIZB9e1rZJF_uxf_p9HH5qurtZ1CqAq0226btVorZpFn1PkDJMLbdsst4u-XV5fX3eLRQyh36wQBDALJZSVISajVdNUrz55OQ6n7_34-0aZ6OP3P30yje7Lr7693CytrVdt5_zUVNXDLlTb9l_-9vefP3t-c5pKLk8eb188fypBFYqXZ6tlY0shrWTTVofd8ep8Pc8OGCptGVFLoYUAgKapD4eTFKLvOiVQAIyjqxvbt-08jcu-SSEZo_quEgK7prrb72tjrX7QPMpcSorx4Y4DAKM0CkDETIQMwMgADzYrKkTEQqDzEYARQEoZQ0ZEAsyJYoqAXBuNKJlxGCdUIhfOqUiBUijvozRCSRFzqYy0UgFALgRS9K0-jAGJMxfBYLQsBADCxxRyiSEzQtNVMRXngtF6fxrbpgk-j75kHxaLKsd8GuemredxOJ7m7_ZHa_VmuZBCYIHFujsNg6laZe3bNx8W26WbXHDzar1obXP5-KLv248f71fr9emwv765YSFDyMv16uzyTFsdfCola2soZSWtH2ZdmxRTZYyt7LjfX109oZLb1fr24w0F3y03OUah1DiOzs1VXVVNF3OpH3rxZ1s_T9MwsUDbtjFl4pJjQpBMTKWgUkAEACAFZmZgRMopIQopsLjkxolYdItF0_dxngVnBCAqgkFI1Z6dcQgxFJGTQMZMp_1-sVwv2kXhEsdZC_p7m71It-_ef_PtxyefPGeAR082WohxnJSQ7z7e7YfT_ckVgKYydd1Ii68eXSijF-vlROXxqo-Bbk_Dsm3OzrfWyFwKCvaxaCMF8-yCKPzu4_5md_jq4_Wyrt7f7l_f3f5y2FVKCubz9eKsb5aVvjjr28oYKx5tuqqyMUZHRVlzcziNJzf68G4_TD7NLre16RddW9d906zWy8oYgbKy5rgfxtkJwG7RV309Ou9zub87ZOZEBIBGSwIMMewGx0wpc0iZpQwFBh9YiP00j1O8m4JzYUr5bj-hoOMpTi75GH3OIeaYaM4p-bw7zaAUogipsI-7w3RKSVo7pkRKBcq3h3mcJlvrKRIq-eRq4-YCOUsp_uxnn37569dVZ-9OPuW02Szn_UkbuV4067p6sulzgsumRc5zKvOcUyK9qJeVbiqrdSXI_PxPnp2fLza2ulpW33t18XKz1VJfrKuur-rWmM5kBcrKN7v9h7e3H--Pda0nn15-un36ePEnz5a-8P_8l9-9vzncn-YXy8Wy7376_EIAL1sDWiiNWeI-p2lKX328pZTrXvda7U4hhmAELpv61dWFFXLb1ZWWSoAUWAQrrW-Ow2lw7bKxRg8-Dz79-s07wWqc3H_47ts_enT2vWdXzy42373d_c2Xb84vlp99-tw2phLVr96__-XrN2TbYyqOy3LVpFBO49S1rTU6TcEw3n-8f_3xjgX-8PsvFODkMgMJiVKI97en378_XDvnckaUhaDtWqBScnp8tlKAp3E6hPDq2Xml9TfXtx_3R4FqCmE_-HlKKFBL-8kn25vdfNyPSqvo0kOxtlvYw70TgoXGqtOLunVDFESRsGvq83U73J36hV5uOgHm6aPts2eXfr_Pc1p2tW2UAJAAptJpCoJJCxSIrx6tz1r1j__sx9uurUC0jULA2fsQkov5cBpQmlTYheB9OTmfUplDud7ds1B_-1d_9_r1zdnF-rAbQMqS83iajVZucpyTNFoqyTlroUrJKfiqMahM3bdExTY15VLVVkhGYikgp8TMD-6WerlcnF3G8YgSCmQEJIL-bJ2CTzECF0QuKT6AF_tlRzlYY4JzEkkbOe0-6tpIKaJzQEVokBrTNKbZiarG4qRQSGyVJoqUM8VIIQhTaSu1lsnnHOfWNiXMOad23ZWY53HGnCBHziGnlHMSQCHPRgtE8CH2m5UPs7V1oZxzMn3dnXVN1z5oK4f9rlsviCGnKBjCHKlQyYmIhJZSKWElF57nGRULlHXXKqkJoGmqMHqArJX2zoGQghkzxFKoJCAqJRGKqusYGRi1lLq2pq4AeL1dI6Ku7PoHL0spfvSYA_s4T7PSQgq6OHvcLtp5HJtOnz3b3N8d98ebatGVOR_upqY2HAp4SKObj4fh7mgac3t9R4W7bhm9Ox72SmOl9XF_7BZWVLi4WF1-9qy3dXCDETKHw7_4s18YIYBLCKlqlZHK1jbHNE1zVVVujoA4uZSYGNDnUiv97vaYM-9nn4lCzCxkBnIxHYdZCjF6X9UmJgIlpykCqqPztrY5EwiVQoo-gBDT6Hyg4JJEjjF7l-YxsOCc4nzyLHOkmEuhgillU1s_TTnmUhiVVEIUICqMUiIySgzBE5WYIkrFDJxzSblqa6I8z0EKxUAllYObTtMkpSzEORQGFAiFitEVEsScAMUcUsoJUSCxgAd4KKeUWagUk89c1_Xkw-wTI4_eOx_ud2MgmmISSiGDMibkgiwy0eBizPk0uJyLkAgCwhRByGF2KUUGKKVIpUvhybv48ECOIeTinGfCTEQgYszG6FwKJcq5hJRLgXEcKquEEm3XcikAD7JOoZXOJYUQ5tn7mLQxMZecUoi5rmoCGmavpGzbtm2sc74UfqgmmsrmnFeLfhp9ZUyIpW9b571gAKBl11NKSkmjVCppte4qq86W7dm6k0CrrlovGyS2Slqjq0oz0nbdQSElhBAylUyp-JxzzsaYlKOSEqF01myWvSBggNE77yMLzoiJePIBmLquBsQQi4uRUCTKQ8iRyMV0GEMS-Lubw1c3h_X5SlgZUvlf_-o3xynOxGOMxjaBEhdYNhX5fBjmUsLZ-WYYhlprH_L5qr_f7UsIVtnbm30YRiGF91EbdXl5gZJSiotFW1mFTPLFn_9XwUcAtNp0m64wa6E2mwUhxJSbvmv7tut6o1XOWSgppMiU27611hKXQvmTzz-bJ_fi1SddV6XoqEBwoW6N1hpSaReLEhJQvtxeLNuqNirH8Ojy8uOHj7Xt3nz48NnnnwKwaquutbcf768eXWQiwaQkNNYiQFfVHz_crjar6IIQsq6rApRT7JumruqPt7tV3zBDY0xTa_OAJVYyxzTNrq5tzrHvWoEoEeu6Sj6s-1ZpJSWWQjHnvqmbWudU6to-WK9LSkKKUoo2WknJzFIIKhwSZS6VrjJlJoKHHpxURstE5eEJwQz6IReOsaoMA0opgMkadTgMXdOknKWSTWsYcBx83Ugl8HjyDLIw9Y1lQKNlKSSEeKha9k2ViKEIF8Nw9IXKctnXTeNDbPuutkZbKRDfv7-LMV6erQmg6WxtNfkChKfJnV0ucgzeZ6UVCKwbfff-ZnN55l087Peb9erm7j74tNgsD_Nxd3OnrVFSrjabmPL-5u54OIRQjK1MXdW1VU1tujqlbJQxjZkPB2Q-HA5d3ZYSLy8e-eCH6QQAddtRSYVyiUk3bUgEQrftIk6zbdpm2XXrrdK6X62FktHP0Xvb1jEnIFqeXUQf6rby4wxAkAsKpJSgsK5rTlHAA54rUkxKKql0djNIpJwoRlWZemGKLwQCsSjIp7t7Y-zy4qypm2EYfCYEbut-ffGs1uXjN68_vrm7m2difRhy31ZKqsNxuDg_uzvu7o_j-7sDotRWL5oKgT6_Wp_33dWm-8Gri4u-zeP45vXHr16_DSH0da2VGA7jqmnu7ncc0s18uqzbs2X3aLt5tl39wcXZRd-vuma_OxqjgTnHYKXQKHNMH--HX30cQqYQipvTxdmya2wiBOZ1Y6DQx5shl1JyAgZrdMlw2I9Ga1PZxHy_n-53p1h4nBwLYJRuDjlxCClnGmevpXY-pVSUsbnAcfSxkEulsLw5uLv9kKU4Ds6Xcn1_8iFlZlISEX2MtjfjHHIpBbgQA9Mw-UqjUvw_fXfdCU0sB5_3YxhydoHtoi4x3c_umze35-dtVZnsQlebwYXNeaeU2O_vkahp7Oi8S-lIRVcSNcwpkBDrZdVaA0R9pWsD62W_H8YKuAQZDn7R27PNMoB4__G4Ox1lhQLVzcm9_3i8OY03t9Mwzs2i0UqZRl1cLkOOr29Pv7kP3rPpu58-uvj88dmzTXfZGATwMX57PP769f2b3fH2FD_uB9NoW5nJzW4O1pp1V0uJry4266ZupEBmIxEYCSAQXR_G_TRnhs22LVLe7cYP96fb06kxdrNYGi6_eH65qGqj9f0pu8JXn6xlZcbof_vNh795-_52mGXXfbjfhVxCiPv70zAMy9Xi0cXqdPILq866bvL-1-8-_MGnzzdVzSwaLTbrZWDc5_zv37w_-TTPbne_b_taG_3d249ohAt-0XVff_vh1ZNHj9Z9re3rD4cvX3_oFu31fpKojqOzSgOJZ9vmt98epymk4ksotjbDwRspuWBIKc8BWAiBnDNHapfV2Vm1vVyhLxz9drlGF7_49HGl5LSfP7y_6xvVtlVlJBfKKXeLpl_Wbdci0eXZ6gefXv3sh59frhaauamtUSIzOR_G2Y9TBq1AoAvxQQW9G8eY-HZ3urm5B5ZnF9s__i9_-Jv__HUpaY5BCEnEyTmlND1ov-q6W7bSmOiDBCmklFIDC6XrlFKJWQAisNCWGQSANUYKIABhdXIuhUwpLi82ORVbV0ylxKyUYiCinFNGJaW1KYQUed1vpVXT_sDMyujpODWLJZUcXWIigYZjKCWLkihlJVFpTpMPbsopQskM5I8HFLprV1JLN0_Jz6mwkUKr6vzJFUUPRDlxu1wF76UAKoUpQablxaU0dt4dIIXxOEijChGiIGBitpVWShND3TQkYZ69MookSC5CiJyzrirvI0hRN7UEjimbSmcq3jljjVLy_NHF7m6XqYhKC4GMAqSQ2lAiXdWAgkspMSEVNzlE1JUBhLoyD5gQXZvh9j47L7gIKraqPvnFE0wynvxm3UghpGIqZTy51iy1VHEfL55dqo0QGWJOKEX2cx4GWcv5MBROKEWcBj8M3qW278dh0FJqodePt8tVM9yPCrDt66prX33-9J_8-HODSmolEK3SXIpEdC6hBKVlzHmOcfQhEyUWPsTApLS83g_ayFQg5uR8LIjz7FyIJRMKoY0pxHf3p9M4m7aefZwnF2KKzCknIWXT6PfXO5TQrxohNZVi64oEu-gZSGldSkgxMKM0QirFpUgtQQihVV0bASLGIo0qlAAhxuidLzkXZqailc0pVtYSQS5Ucqpbw4lCSgKwrmtOGYRAYD8FFiLnQgRdY2IsIaZQcmKOIQJyLpQSJypMHFMhQJ-pUubkQqFCBU6zy7kIJTJTAcyJSiou5uHkAqWUUyrFOZ9yUUYTU_DZ1nXm8iC3ZpbWGgDeD0MIKZWCgCmXnLNtDBMQlWnyqIRWMsQSY5znYBs7T3PbVjGX2jYlJGbMOWlrUCCg2O0O1mhC0fcVCgHE8-SVVDknZkatBZNkSKlw4fWqJkCNqmk0kgQoxigGqvuKSwkxKSmFFMoarSRA3p4tl331eLu6XLTMLICMhkVjK60xl7arAco0TN6FSiurdC4kBToXUQmlNTDbquaS6q6upN60rUAAwMB5N80MojCOc5xD7PumZKoqmxNMs0tEmWj0YTe54-Tf3Z50VR_T9PWbfaWlz_nD25vjMCeAcQxJklLS--hDpFCUMrY1Mebsfb-qkaDrm-NxAClA4HgcT0MAYiFhnoacWQh9_mhDifzg665dX12c7o_yJ__Nv84Flqu-ZMbCm0eLdd8f7sfLp5dVVQfvz8_OUopG46Pzp4fTYXN2zsAAeH5-fjoebVWN43i23dSVWi4W0c1Pnj4uOVdWPtmeSSO3y0ZXIuS0rOwwjZJlzMloXHZtTGm5WALlTgIIM40j5-ydO79YV4BdWz15dqkIpJBKidrIksnWOqd8PE3LZaOkPByOl5frutaF-DDMbWPq2lRKDJPbrjpk2Kw7KaVgAuK6NiInJqBS1usuRbJKMBAyMQEKbI0BRKJijGJiJpAKmUEgDpPLTChFLgAIMWWrpQSVmaUSOWdTKYGCYlJCU6GYMkuJgKVw4SyFEAgAEglNbXwMlVWQubY6FxKIQimigsgP9dKSKZW8brrBuUy4P40p5xgSATe2atvWRW8a7WO2RqrGTOOcibpVd7btb--Pfdt9uNsb1E1lPnzYLZaL4_5U17XUKk2hbszZZolFUCFKeZ7DZr387vV36-Xi483N2eKsXfVW2_3t8OTTT95-9V3d97a2tu6GcTju3gnTznMEouXlOcfkh1lIXWLRGu6v79q-jSmZpjKqno4HodFo03RLBuFD7BZNv-iPd7vgfcyUcwbKddtPp2NyPoUolSgxCSmV1NFPD6lo1VQlZSEkAEMpTFhSFMoIIVNM2tjsHQIqWxlr0-yRSUoR59QsekrAmTiFEpOt9bg7IqvmbANKUSxSInGM83S2vlovW1PTdJx89pox-jTHkAVcX99VrdVGPL9ahRSv9-PRo4cCWYwptrVFpXIqySeQ8mK5KTl-9d3Ou7Dtam3tZrV6-eTi-8-vNn2vUNRSMopEnDLEkNd95WOKocw-TZOPgFobo3UvBaI8eTcN8cPhcErp9YedkNC0VVWJu_388e64P0ybbe9jiTmjEiHR7NNhmO4Op8hlPzhiMYegbRVTZoBcso8FBQqjlFKMIpV8fzuEVBKCVuLuMARKodDdcWCjnQu74YBCxZxDKkyQiGIugjjEAgyR8pTSfpiFVoH5aVWNczz4IATsJ3_rsxfq7c3uGAMTjyFOnoXEi3Ubpni17harTlLp6jq4eNpNP_nx8zD53e4Y5jT48HG3Pw3uw80plkzIx1PYHeL17WlpDBOVMg8heC6H43Q6zmDo8ednzUK-eX1bNWr2ruRycLOtrEEJUrRGR59UBp3EZ9vF80W_qarLGo0Aq0Vl8P003o9-SrTedKuz1tayMzZTCs5JhB9_8qRC9ex88XizrARKjRUAId0ep9nHOZbjlGxlK6OzgpLwNPuP46CFXHYrTZxTaa1qK8XEq17_1VfXv79-z6b6-rvr_Ticor87nYTRysjRBSUlA1ornz06DymvraZY_vDVFQjxP_3qy3_95z9ttFFSfPX1e2Oq39_fv9kNv_792-vT7H087edK23W_POwPZ8vlojG_-OnnMhajTFVpAGgX9Tfv91fP1ruTn0KMOUshxzF0TdUL-Xp3RISYCxAJK5erdrOpP7w_NI3KISEUiWSE6lfN519cvf_qVLPoaraI-_206aqLzsaQ3u9On7-47NrqFz97dtwNLy7XVd2UKWy6ujX4eLv63vPLP_jBy1qop-fLqlaCwbmYmafZFeIMchhdLImZQio39-PhOCWi28PBh-xS0qvmy7_-2s2zsoaYQ_C2qrXEyhohha1roKKElFrnXCjnkkshphxTmKVWOTqOqYQYnfOngzJqGJxuW9vUtq7DaSRgbQ0g5piFRM4lp5xC6DdnwIRCG1PpqgrTWFKa80BItqrdPJvGAkGhhILTNCtBxQ2CC-SMkKXUJSYhVFX3xc9SMGhVQqg7m9x0Gk_GVnXTm7YHgOhdXXfzFMbDAEC6VuS9kjI7z0RlnFdn5_vdPoeojKmrlikrrSvb3HzYCUShWKK4_njTLXqpURqjtS1AlbbzcTLWIGByoaktljQfTjnEnAsIQEAmKCkKKUou2tZ128aUkVBZzaVIRimxhMilSCmQiYEXl2copEQAKHH2y02_vx-fPj8vXNI4WCu75VpU9cXL57sP9xfnW4GYvG_XC44ZFEpBnKhfLofpKLgGLJIFpcyF6k2dXQqcKUCeRo7BmGb7_fPFxeJwe1xtemtMUzfjflg3vdQCOIOxz58--snVmWZUWgkJSiJRxsKDCwKFkiqmQgCp0GlKkUrKZQ6ktPi4HyViKJRSFkomKplBSnMaPQisGhWIvY-l4GlyBLBo2mGaXMicc11XUwjTOCshGCGmtFi0x90hl1Kfd8fD6EdntfZDUlYKpUqMUmoWwAxSyrZtmR_a-ay0atsq-mi0BhACiQpTSlJpIARCYk4xt3UdQsyZhUQJ_DB1KK2VFAyUSmECW9ch5tn7wzgT5dl556OpqjkEBAABhYGAT0dPglPKIeQ5-JwKMUstESDlAqXUTeVDRCXm2RNAzsX5lBO1S2WUpAyIyCRCjlLpcZhRgPdpmCZAIEAEKQCVVoo5-MIChQBgBGLvA6JQ1uSSMoicqepqIFZKsUSUKsRUcskpSa1tbVLIAOxcFAJCLoCcSgmJmrrOFHNKsRABFwBmsAoLZaFkiklKZayZjs5UWgrJXKzWRsll3z063xolNnWdYtAStRLTyVUCpBCbZVNVJnlHuQiJAni7XIWYVuteAM4h5pxL4baukYuP6Wy5aKsaiUphl9Lt4XT0QaBgicfBCQHW2sJIUJyLd8chg9gNY5GCQd4Pcyj5-mb_-NPtb7652e1OrRW1sV3bjGNkIVhLECLlvGjrRV9h5h_98KXR-M3fvXv0aPUP_viL2_vT7e1-uer6TZ9LEdZwDsigKs1STCcvtahrM01usViAJIpZ_uCf_Suh5TyHi_MViVQiBO8fXS1jjDFF593Hm9uu7TOXqjba2MP9_urJZYolhVB1TXTzctNP03h_v4dC6_WqMkIp87vXX18tF13fzdO8uz999uLJo6ebVV8_evIo5_jh413fNo-vzs8uNofdoWksM89z0JUuVH733e7z54-sEpVUD5TPEGNljQ9xs-7cHJd9q41uamu0YeBaW-dDZbRUoq1qgRhj7hqLWnoX-1VrEZvKSoFKyLatcspKKmXk3eG4aGophFFKSQkoEACELKU8sIOocI4ESgipXMo5F20kFVZSCCmpUM4FmFOIDFhSUVqhwJBLyIRShphzTgCopSgP6geAmKJA4UNGxpTSHKJWJhIVYirABEoKJhBS-ZyEwHH2zgWf0vpsfb0bc87Xt7fT7FfL5eEwllROo0shAerjaUwEMcbd4bg5P1t0lfNBalVKDj6vV93pOM_BK2Pvj6Otq5vre61V23dt3-Wcz87PiMv9_V2Yw9UXL5CZiPzkEHKzXNzf3UolkbTUql20VlfJeyqM2jKKyx-9DMcxhuDH4zTN7XplJDLQ4TAslothf1RS50zGGFmZXLIQlGK8evZkPByn08loW3JUSgAIUzWryyfKKj8diAsULIWEFCywRBIIUkolLSpZcimAFKJkQCrpeFR1Y5s6UwbGXEpxURqjq4qZRVUhEyAh0Lg7mn5hjRmPBz_7HObxuD_sTtacgVT72-tOi5xTEbDZLuF8OZyG487d3pxurg_j_aHTvJLy7755fzq6SPz1u_3N4Tgp_OxyuVg1zzbtxcJsLvv3u-O37_ZU0tfvD2nOytjIIjKMczwOkYx5fxiGUJZt-2__45dz9FPhWOhX3324vp_vTxMJePl4-d3RvXt39_H2NEV6fX3cDfl__svXLKBqGheTripZaRRSNQZA3OwOPvPBuynx_Wm4uz8Now8FQkzC6smF-5NTWnEuKLAUygyFZeCijbg7hsPoQko-8nHyBIwASuvClGJSRhIX76IPMaYyzz4BjbMLsTDneUpNZw9zbJv6425UAq6H0-3d6XQaI5QPdxMZ6RNrCW4Mm64xUm77btgfDaBEmSI4AaxNSsUAV1aXkJpFjTmhhAxlmINpVVVhv22259366RZBVbVNPkoUlVUxluEUD3eeBRyPbgxFGhO1-vn3H_3oxfnlsn--7HpTv7xYf_F0s6iqi0XbaJmlvB-nv3p78-X78es3e9ssfKICPA2FQllYWQvxJ6-e_tGnzxZSCmbOSQEy8XHw95O7H1wkrto65TKEgIyR8s1h_N2H21qqEPPLy_N1ZftaN1JMmb-92f8_f_Xdf_jd7uBc1feTL-9v96auv3n_8fLq8vZ-2B2n1_v9jz-9Wi8X28USUy5QrFIl0brpfv3Vu1-8eiIoE8Acc-Gcq_o37z66Ane748XZChT8D__wx188Pd9Y8_0Xz6zgz863PsS7m_u2r86XSynV1998WG5al3NiCDErKY3SbWcF4HGIU86lpL5vtVIU4p9_72pZVfNETWOEAmmxtU2t5fNHFx_eHt589_HqrH326Yvzuv7e4-0PPnvUCv7s6Xa1qFpr-rbiTGEcfvjiartY_ORHL7ar5dvb-b_-k08fb9ebru7r2ipJOSOKyYfjaZ58zIViZlDy7btDCHGY83GcTF2P8zzOoe26brn45qtvc0wxhslP7Wo9jrMSAkhUXYNSxsktlu2T84thHITWiKJe1EKqOPuua5USOSdhja4rpdViuyiFUWmhlBBq3p2AqVt1wceqboCzkCrlpJTyMbWLGoQylTXSxOCbps4cS0g5ZtNUnJmJlRRCyRSCrjWF-LDaWHeLkhOD5JKIIfm5bmtUslABhuiDFIwY5-MglWYBRDyPPqciBLjhhFDiOBUma9tu0WnBIHV0jgmIcg4hhVkZOxwmraSUAkqZDsfpdNRCDoeDkDrnpI2hwk3XWmO5lBCpWXWATPRQeEdAMdyNxpqSy-Huw2q5IgCphHmICKQSRqVAxCQUMAAJEFqClto08xzWq83j86vCMQS6eLT93_2XfzoOx5t39wCZEvfL1Xqz9YehEqJd1AgpTHHcz8-_eJWST96p2s4PfFWpBLOUqABUpTELN7u27ZQAJUJTt2B02y-vf_vh6YtnlTXxNEQfzpYrJYWkcvHq4sXl9r_9w-_1ILSUjJRKLkQx8RxzZtIPEk-Ju8MESmfEENPsYmJygXyKhLIgMoCuqtllHxMImXOeQvSJTnMEISKVcfbS2uvbG-djSKWpjUCMRON-Wl-tjjdjDKQhxNkba8eTr_o2DoNiUEJmZgQkYEpZW5tCausqp6S1JoAUUt22IaaSSCIiQwwRGQikrQwKEVNCgTElKSHnQkRhdCkTE4MU3sVl38ZcqDADCGSBAIjex1RKyinlxMQCBSL4ORSQmQoKOTtXCmWk48HFHEtK8-y8y6mQUJJBKKtyzlKqEKJPCQFzKZSACGKOCDDPLucH3fDfw9OZSGjlfSilEHAIngAZEQAyEQJqJaWUlHNhXLft6ENtVV1VgiGmQiwysAueCgMiA_iQuBSpNBCzktPkCmFIJYQ0x-RCIOIUWSklBQqEcXTMAqVQWimWwFxSUUoarQTD1cUWGAolAaSNqiqFQtzuDvv7Y9Pqp-fLHHNTWRQQfCQia3TfL4xVlTUUSyzZBd80LTMDFSXldrmwQiJzYZyCG1zIiN7HwYX9OGaCVDilwojEPMxBaxWpgEREcTecbu4PIZfjaYRU_NE_-_nLOGcawh___JPTMetKLp5snEsSmUumGGulMNG3v_vuJz_-FHNCUb19c_3Z957-1V__9vJscxjmd2_uOQKQqHtrurrtao4xl9JtF94nCkUrlD_4r_81oiQuKSdjK6HFdrtpa7NtO9Z6mGZK6TgdBWEo-ZPHT4-nsWpN09VKihhj23dAwMx9Y5fLJcUSk1svly2LftUJBqVFSrBetrXWIRWJ6Ca36LuL8y0X-OabN8vVsu8bU9clpWVfX55vv3h53hrTNlVtTNtUbo5aolaqbusYokAplNASnY-IaLUcRseFukWTfVRCCIaqMUoIJYVCCUSVllIiJ6rbWjApqZrKRB83y05K9UCbEohSCEbkB0dSSABojWaGwiyUIOJUMsCDukpQYWIAZCJmIaxWIAQAx5QLQ8qZmBkQpSBiY1TwQSAiSkZOqdi6zlQYQChptADAGLNUCoTwzoMAgUAMxAQSrDGxoHfBKFVK7pr6eh9rhV3XVNYIhfMYUEC_6vzktdSZ0c3hYrvNCDmVB5yiYFC1beo2TPMw-VzyarNu21YIMU6TFBIKjccBhZRS5Tk5FxgFChCAh8OpWy2ziz56qSvnJ2sNlSKsrtqOJcx3h3q1TIWFMn48uP2QhXzyxWd9t7i_uVufbZar_nx7djzs99f34-GklJZazfvDdDxVViGwDz761K-2xsjj7r6UdPnys8PdrUAhlYgusNQITD4Dg2kbFgKs1nWFKKhkbSu0Npeoq1oYJVCUHIXAkkFXRlZtnGZmjm5CVDlESkVVdX--qerutNtxntM8nU4fBIV2uRiPI6a4u93d316XMRqUx8HVteqXytb6-u54W5KSnEIYshuO82GYvvnm7a--u_vlr9_98t3u4xB-_dv3Y4yHw-Hjbmz6apDym_d3v_rq3dfv7z7s9m8-3v3N129NXQ8qf_36_ji77qKdQ_6r_9_fKYks-f4UciV3Mv3H__StD-nN-x1LQoPH3RFFDoVcTCjx_jB--dW7m7vDbvRTCj6X68MwzO7mMA4-J4IpFpdKKrw_TqGwkGo_zVJoBhFz8ZFczsM4R6K7wzQ4XwDHwT14F4JPqq698wSYUwZkKeQ8u8yMRk6jkxJ9jsQcUiyIwxC8yHP00-yPp2F08_vDcXSOBE4ujlNQIASW_Wk433ZX58vL9dJo_f2XT7VWP__h81WlRSpf3x6ISWnVGtmbCokWTfXk1fnFWQ-J85DSnMJuno8zZjJKLI1hymHyrdHbRRVcvOzNT19e_fzVxZ883y6VPO6dn4OQ3FdV29iltSzRFUoS__ZmN3p4ez_1fYtaCEDJQqT0YrN6uel_9Oji8bJrtYglZyqLWguE2af7YcoI3aLpu6oAJmAXIgpkJf79b14bLq8eXW7bzkjVSJNKmX0OUvyPv_9t1nby-RDmWMocgq3F_f3xcHequlZzJYr60aeX_-KnP7x_80Gq-v14evvxuqQiGX746nEI5YuX297o02kWUtXGtlXzN_fXvz2NMeTHj8-frheGMYcQCK7Oz9_v9spqRvkf_tNvUOJ6tXn39jqncnm2-XCzm-ZQQOTZJx_nGPc3p6vtaji6YZgLFWN09vHk6U8_udQoX9_vU4pYC4q0aqsnl5v1pglS9J253G6eb7qrZfXi2bo3GhiFkvMw913bWo0pv3p0sVkvXl1dnLX15bb98avtpm-Wfd3VVWUlMOdCg4vDFAjRlzK7dJhCyiWWlAnuhzkxRyKQ-jQ4bW1K-TTMMcR59sggEYVQlTElERITQd1V3apdLlezi1T46tWLMOzjNAsBJUVljFJ2GAcGoZWs6u5hVKoqI5FyTMooIaDq2hSiEFA17TxNSikhlTZKaqO0nU57Y9U8nLRpsp-0qnyIDBDnWDeVkJh8YIo5JGZGhTk4Io7J69pwphIDS0qh2K7Jo0MtkgtKSaAynY6lFFs1pqu6xZmWMM-zqSxHRy766EoKUlipdM6emTklLVUMUWjDLLS2ACwkKBDJRyqJGEqObdcJKYUQKUVitnUla5Gdd8eRci6JcipSS1WJHCMwLdabw37Xdb0bZ6kMI0mtGYGFFMagEaZrfEgohETJVLquIQpjcHVdVZ35Rz_70a9__bvOmDl6AuxX_ee_-LE_nqq-lkpD5j_5p7-Yb2_P1gs_O2aMLjAjCnRuBIlhPHBJShqpxPFuJxgM6tntoSih7eWLK_beHYf1ag2UFKCRGKfTtDvVSn7x-Xnl0k9fPtVCSCl8jKfhyAJ9pN3gUCARhZgYMBRyiQJlAjFOnkFMLoHA_eSIWUgdS5l8mHxyMYWcHnerm8mFlKcQXMwlUxjd_rBv2lbVdrtp93dju-im0QslImWkcri9CYV9zvWqn-6HFHzymRBMU5WcpNLRJYSCiDkXU9VCo6p0SskoFXImopSiEEJpnQmWZ2uGLKR62Pfl8jBIY05ZGE3MyqpGVT6nVErhXAikxJBSXVtEiImqqkqJSkoPc7yQ0libcg4x5lyUFG6KUmsfQm305KJWSllVctFGCqViKcPohcJcSFeVC8lYw5wra5UW8xyci9oqH4JUSmkVY7LWehdizIAghAwxCZRKSS7sQ9BGlVJQSGLWyswxFGCttZCCMgGKmONhmKRSjJwyWaOMkUwQQmaWx9McYhnGORLHnFEKF5IxNmQWSAAQfQShUszADIQCMeccU94-WeTMVmuh5eDc9f7gYtoP0-3udDidYsqAKLRYX65brSWDEhIECynrylbaKiH7uirM97uDsdY5j1zatrVK1ZVFIBA4OudiyQiy0qc5BMS7-yMrXC47yZyheBdcKDFlrbXU8pvre-9LzPnF80fss1GYGZky5rzpa4kaQtBWvfuwS3OWUColXj66NKg-3t5fbRY_-dFnPqT_9Je_kUJ-_yev-qY-HI7DaYopCUBWKLVQ0nDOx7s7iaJdLBEZUnKzl6_-4T_3LszOp1hiCm3XLNouBn-cQ1fZRmtTNUqbnPI8p5sP101dUcnIAhG0sX4aV1273-0qYwDos08_sUZ9uL599Pj89buPTdMc94c_-NEn60Wz2x0AxLKr26692K6ICjNYLV88vRyOAzB3vZ1P09XFOeVUV3bdVwgoAYkBoWit9ocxFWZmyhkJqHDVVlpKIYWQYrc_LhdtbUxttUAkKlYrIRC5-MyVEk1bCwQtFTMTUV0ZAJAotVRCAAIwgJQIwDlllAiImViIh8oox0xSSi4AiA8K45yzT1mgQAGFwRocxpAJY8rETAwhJeJipH54CyiliuAQojTSh8gMQkhiEEIUYqE0ERFzSLkQlEJKq4OPGkUkSFTaSodUfEwo5OPHK6GQqfgAwzR2q_pwnNq6BqkLFaE0Skgh7HbHkvJys0wMDLA5X15_vEcp-sVydrGp7DS7HLMAqI1REqY5uGlsus4aY6v6MBw2Z5eH3e3jx1cf315rW-cSk_fSqHkYKTMhARShZdt3-_2xKFXVtln2bbc83t2c7u9NbRkgxVgZ671fLM6btl6sV877cXeyTdVYwyDDPJumCnOgkplBSkXMOUzrJ0-Od0cGNHVbkgcmIVAIlVNEKYnR9ksmKilwylAKSumn0TaLqu1LSQAotSwuoBTCKEQEYzgXpRWAz_OcYu5XKwECpSo5KoFcyBpLWV49e3qx3b755n1K07Q7-Ry8i9c3x_1-jFQi8XScbu-G8eR2d7tpHMMxNr2knOZxur09JC6Dj4f96Ki8-zAeDu7ufn8a3ZvX129eX_tUjsfTcRjv348uB8p5dxpff_fx_GIZQRzG9N27vdXim99eH3eHxJwoosD9ON7d7AqR0nq3HxlFXemYvAt59LGtrZT6yeXZ715__O13N1lAzNklPk7BldIvu6NzQgiSnAoOkw-Zx2m6uT3EzNe70-E0FSGmOaSUjqd5PwwFyuwnEiIlji4BY44hluLnKAQrLVixm1xKKTPFVFKh_X7MEqdhglI0CKERRc4umKUpLh0mbxqbgWWlzxaLUMqiUUrA-bqBXLaN_fTx6uVy-cnF6mevngxDkI25824sZavbMISX5xda8g8-e7Zt1I--ePyDR5svnp_94GrTUPnpZ0__6PPHL8-Wn1ytn20WTWUqpSZfjpNfLtvnLy-62ta9Oo7uL7769qt3-1_d7-724TTkSIV9KLnITC8v-p88u_hk273cdpUAUQoTAINz6e5wdCHvBheIdVXJyu7mcH1_3M_uepzcnAcfGm1Wkl9crDWIREQEVOu_u9395w83_-43H6ddULY5Hk9S4TjPAsDU7f3t_uxsMRzCf_vzT662C6uq_-9f_4rq9t3xGOdyuWj-9PMXj9bLWiIShZB2g0NjTdt-Nbj_27_9y2s3X9R1K8qz5WIplY_hdnfst5v70ykX_nh9-_rdx4urrZY4jPPF2QaA2q5pGv1xPxYCStla-d13-0fbrjK6aaxuq_3ef-_V-aPH1bNl83i7jMCxgJDi-sNu0za1FS8fXWpZnS87zimnBNn9_ItntbLW6G7ZOzd0VQtAi67eLJrNerlomkrJxopKyq62ArC1BgFKKYPzPobdcdJ9cxz9MPrBJ19oDmF0eU7Fx5wzJSrO-X61mEO8u9_Pbo4xGsuUIKdsjC6RSoxVZZQxT589224XddOlHMfhCNGH0xy8M9rMU2BgFmCsyTkarabZVesVlcLEJSdlZNcvYwhMCAxN0yBT23VKysVyG2Nq-jaEOA9Hikkp46ZRCUWMqq0pJKsRlZh3x6qrgIBLFkJoY5VEpXWavJRCKCm1SC4QamUlIFDKQiouJYWsgBBSiZEQlVZ11TDy8X4ntUAUyQUhFVAxfUWMwzijqXPx3Wod3CS1opIyFW1Nvay4sBRyuD3lXNwwDYeTBEyTTykprYL3VVVJrYGYJFVNk3JAKQSIlCJzIUIELDnFEMI0BucROeVgjIHCQNy2rW7rdrUBykIJ52K3WPTrdU5pc7aysrq-vjl_dpEK56KePH4exokpXG7Plk1d3FR8KDHM0_zqi1c5uqefP5Nru39_6LqqMLqhIOuq6sfjftGvMyQipALnr54Kl9_85uur55fzNK4Xy0ePtmZRbbeL508f6TANkf77f_zHfWOMQGAhFKKSAGJycQ6lrqUSqgA7nwKVeY6JcSnURDz75BMVxOu7cdHXh-M0p-xzAa19TjGWd7tDYiqSU-QQwna7Go6neXZUcl23KWWtRNVYLkQIKaZpd1RWxRAy0TzO9bKmmJIL2mhgZspQCiIggjCiZE6UALAACMC6rmKMEgUBpZiERF1ZyhlRppQAQUoppGDBwFCYKGcpldaKgWOJQmAulHMGkM4HYHwgmoynMaUUcwQAH6OQynvvffIh5pi4cN1XiBBDVlI-1BVcSHXTPKQTOdMD9BwFxlQYgClJqYRUzJwiSQk55bZtpJIMjADED1RTZKbCZKx-qFqkmG1lamMzFSocSxZSeh9L4aaywUdA9DHklKvaAgAwSm1CKtPkUirA6nScI5Fzc2Hw3qecg8-FSslFG6wazYggQQIIJkJUAtuFqSsJQgUXAVE15ub-BCAy8TDOhXg8DikX1NLNrutakdJm2VZKVbWutFku2rpugUgI5bwb51BVpq4rKUTXNLU2EgVQycRzcGOICWFwnhmPLr67u5MCUWoGmry7O45H7zZddzjNRfAxzB8O0-Q9My1sI5Arq5999uTv_u7N_uNumpwW8nK1_PH3X_z6q_ducgRxu13-ox_95HQ8fPri0SefPLm9uR-nst_vnj5_7PfDT3_yaUHx_mbPgCEzAGTgEjLnvD_NArmqGwZqF-3NfpA_-Zf_RttK21oKVNKkggJh3TVW2fvhmMZ5P7kUk0BcN-1q0fh5nk6uXbR9VwXn59mfxt3ZenV5eUExtY28PD9ra_Xk8flm1Qvgi7P12zfvNuslC9RCGqNzim3baoEMsOybyc2bZZsCxzlcnG2G-2HV1Mtlz5RP07xdLgAJmJ0LfVdrpUII6_VSIDKUVsnCtD84pUVXW2bSWqWU1otmnrwSbLSqjN4umhiKVvgA9pQIQgjgIgFRSiEBBRABAjNTyQWVfJDbJaJUMhGEmHMiIUUmAoAHdLpSEhCROCcCxFw4PsQCQmitiJkJkf8-vZpdtNbkXDIVIqbMhTiXhwy5IMpSSvDRpySlyKkUYCmlleKBRxZLDi60TaUqW0oWgCly29fOJ6s1ATwYJWJMxKWuTF1bKtS2PTHMMWipUoh3NztGGUoyRvsQQvCMSABNXZdcPnx4Z6t6mlwp9O2Hj09efOLcPJ2mcTitL89DjsPuaLVM04xMcZ78aZ9DklYzslQGlUw5C2Qtq_E0nj99Whl9OA1Vtzzs7o-HXQzj_e2tGx1ozD7VbbM834TZN4suxyQlMjDllJNnQpQyutBv1wyQUkyT102ttOZMJcRSuOSsrGIoWGksJc1OGi0FEjBRKZSr5QIYc4wPddJA2axWkIhC9M5VtjJtF6fRTaNZVPVigdpoId1wCsOh-Gnc3bEsy-2ZFEr1lW07N-41Fz8MKQZFgiSqWkCtkivtyiyfbo_Xw3AYq05KI7GSu91eWBQWA8WUwxyC0NI22nRaGVhue--cVKqum7fv7m3V_uBPvj_leDy4QlkqOh4OXKLSShkpteoXy9NuXHWd0qakUlurldyNk5DqMM0AuDvN3767_ne_-u3hMDgok3dvr-9jiFLIcXACeHLZh-hDEoDD5EpKVhtWahhGUjIRHQ6DTzy7IRciwSyBhXIhlhi0VNE5K03MUSjmlNHq4FLJKYWcUyoEiRIIjlTCOJWQpWniPIk5iZj9YZIoHsqcOUarxV_-5993q-XkHQk8WzShkBXoS9ksGxSqtuqLJxfPN8s_eHb5R482z7f1D19cLFv5o08frSs8X9S9VVqJFHPMue-btrJceI4l5wwCWMCc6JTTCfI-5n_3t99-9d3t79_v3t-dWEllbaUNKdZoTqfwgxcXj7rmH_z45WVXN0YaLaUAIYWL-TDNh9FPPnWrXlusKktob44DozymEFI63h2frrePl4vzZbu0Cgu7yFNK__bL39-W8he_--6vv_oQIo0-tMv2q6_ebs7atqo_vL9rWmOl0EaqiP_gJ58ml0IpHw47Kc3765tV1_7s-eMn6w2lLABDTATUrWqSqkihZPl__eXvXQ7ff_Hooq16Ie_8_Js3d3_z_rtHj6--_P2bwzDHkDaLBRMT0dV29fPvfXLYHe5Ph_O-eXK-_Nuvbxojnj86L1SuLvo__sPnd7fj-rw9XzdPzvuO6fr9qap1csW2Xdc1Qsqnl6sXzzbr9dn7t3c-5nEYBWQtlFbiarXgWJq6Sj4YKd08pZTXy7YzWiAYIUsmfHA7CyEQEdm5MIzzcZrGMR6nCZXyOYJSGfLo0oe7UVp9nP1xGlzMX7__fV0tp3mObso5A_Cw24dx-jf_8l--eHL5_vr-YrNYLBZayURFCN4u-7Zqdve36832dH9DxFXb5FS0FkJhYlKV0toKbaSSrAQAdf0ixdT3TZjHB0EqEJ8_eTIc9lIpVdn97lD3bQqBcig-aa2TdxSTUIKAta39NCMViiV7JwCAIecCJQMyMDOxkUJJxVpmn7QyFEPwHqWURkmlgUhAQeKmaUqOkih5V21WVVcXENJqzqW2NQeKIcXsQWvTd1XbKwXRze1qEXKs6t5Hl2K6uzvKyipjNpfn6_MV5LTZdsP9DkqaBxf9KFne3d7ZRitTMYrgY1VXYZqhUHS-EAlAY7RAyCnUfUcphdlhhpyirg0Ts1IAGCZnlLCNUVIjkZunZ4-vUhymwwAKVWeNrVabDqNfVMZocbZerRu76tXleqUkffH9T0vyrz7_5PZ6z1H4cdJCooJifM6EIgohiypCCiy4fXbZGzTIq-2639iK1dPHZ92q_T_9F7_4o--f_-1ff1mI__X__k-utqtKIAp4GDozkUsllFI3mpnnEFkK50PINIcYM-2dOznnC_lcSiFUUJALo2f2McXMBWEcZpdiVdsCEEJerhfR-eBScC4VVlbHEAtKAgTJaOVpdyAfjYDuxSc8n7IP_jDkEAVKJkEpQQEiUkbZvoqcpdFUCiJQLtHHzARCIIBUCo3JqQhAqUQuJcb4EPIgAwjMpaSQpEBtjJQYg1dKT7Mj5pCzUFhiBAYXPBEn4MJQmIKLyUcQwASpRCKizAQklYwh2sr65OvaKi2b2iCiVhoBiGCeghBY1cbNQQosKVeVZeCcMwEzE6AABltZAIghHo8DAygtbdUUKpvtGoCBWUmdUp6mUVsNAG5KUgkfopKARIBcW7M_DLnkrmumOcaUGEqa_cMjYXaTy8nHWCQeDkO_an0IxGSNpFwosa3s3f10OEzAJK2uKxNzml0-jmFOaXSeMo-TOxxHFxKjjDHVVa2ttpUphbSCZ-frZa3PVguJOAyjVUZLJQUKIZgLMxurlTExZqGkFGi0QQQqOTCdjvMQYkjkUmn69sPtoUhcbzdtq65384f7XQK-Pw45kdC47uub3XCYfYgRoRyH4_Pterlsvr25jz4HF5bL9s9-9nlh-ou__jIyMvDjx2eco5vDx-92f_pnn56dba4_7P7jX__tctH-3Ve__0d_9jOO5Zt317e7CY0sKZeUhv3Y9jbFJAGbZfPi-aMP7--8i9oo-YN__m8QRK3N2eOl0tjWlRLYVNal8Pbjbd3VNzd3lTEuRs4MDG1fnz9_lDONw3R2fiEk1nXdL3qjxBC8ReFCMMa8e3t9dXlljFi1bb_oTqdxveiFEKfJPT5f3e12RBSD325XiqFra4HEKFaLylS6ru26a5G4q2tEFkIoJa01QAwASmvnXVObnHOlFYHo2poYKqusVohotKgrA8SqUsYoLaVS0kihlZQogBkAkUkq-ffuCeCSqaRMyDkTMSJijDkxIyII1ELFXEBgig8gUJJCGWOIykN64FPW2gzzDAyFGBBn5zORECiVdCGgkJlKKZBiSamUh4obUQLsTeVL9i6ikCikUYIBH-zYRMCSS-JMmRkml3PKQojj4GqtCyBKOc9eIEslUyLng5RaScXEzkUWmHJKMeVIQGCM7pZN29pcOIa42ixyKgwspTwe9pvF8rR37bJr1gttLAKXTA-8iKat67pJOVVNE0ukQqWAFLLuO4bsT_M0zX7yl5--dMehtrUQHGeXUyyptE0vUZ5tz1L0u5t7rXmxWETvuuViOByllCWm4TQYWzkXbNsKIWKISkup1fhxz9YobZvFsiAIJRClrVuhQPeVkAIQ0zRK00iDKLjEyFIKxKquSiRKRQicxxmFQAFcyNZVZdRyuTZNXYjn49yuNyHMFBQAgZZucLquUyr9ZiEQo4tGW6WNIEs-5RTdaezPF5XUskbTmtMxdrV99pMX-TTevr5_CKtYsxvjx_sjE4DUw-BLKoBCClWImCC6OI4-xHw6-c9_9DKHUhl8-uLyL_4_f-0Hj1BSzhkwBjJd88nPXp0tt7v3-74xzx-dPXty-ehiIwr1i353OMmV-bifUqaqqg_D_Pr6JuUcUrl8daUrs1h3RpimsVrLEGJVm2GcBGICPs2-1sqnHGJCre6GeX9_dDGOfiYuJSchEAq72QGxYBHcDMQuzNIKABmTBwbinGNgIrSCAZP3otZuGJPzhWicjgycoxeAIieOaY6BQI4-rX7y-e63v6c5MIu__N2bpmo-DtEliKV8uPMvn6wDCBaltqqqzXLRGVMt6mrTVhUKyDT7cj8O96NDFoVZaIMSTrncncab0_z7_eHfffV-f3LHMVLm02kGylKLKYSurZXWqJAS5Qx_8v2Lnzw9-_7T1aNlS1wg5Vw4hjwHmiOPPo4hMUMR2Bl8v5vf3R5uT4Mx9X6aKFJrqqdnZ9u-TSw_XB9_f5qCNv_jb7752_fHj0MYAwFJEtjUdcz4o--f_9N_8Hh5dv7L__zVixdXm7MFlfLicvXZk6uzfvm3rz8cRpe4ZM-fPX30bLs1AFyyMfV-9v_r199NUv32-v5_-eV3N3fj672zWj4632wW1d98-fbbw-nL93sh4fMXL9-9_9iv-tPxBABa42F_-P5nzz9_evW73797ezy-dqefPX9eEu-c67pqtx9vb6Znj8-nk9u2rWSggn1XBR8JwGp7-fgMBH78eLdoq8YaKLy7n_anoV_Xfp4vnj3SlBZ99cWzi1oqKcqyqoySRsvtumu1-Pbt_sub07pvQohU2FT6YdIIVEaf5pR3-3HvPDBOcz7N-f443p_85IttjEs5plx3daay2p6lkLiQ0UYr8fM__vG67_8v_90_P1_1n189GU6Dd_7mw50wanbx5YunZ-vlcX_KMQrI-5uDberp5Ju-ST6YtivEjW2AsyAQBFhIVZV4YBBTkSjXZ5umqftt5w4HIYRA7M-WWis_jv40Jj8pYxkxhSCYhBAgLAhEKkoj5SI1UkoPN84DhpVipgIAILRixDh7pTULVXJQuhIEKCVSlqiEEHEKJRXgTMCZiIViJj_Pq_VGcdk8egIiq8oYXSkl4jgY0w6HUVWVtc3u9qZqWmk0MysQUkmmvL-9ZyLKIhXW2lpTl5QQMhCVkomKMFoJmX0QUrg5yMoAUL9YxpirptWV9HMwuhYIDESpUCl6WUFhrVEwWa2VgD_8xZ_2vf301YvK8LvXbz95-fxwnGtrlsslp9JXqjFKZ9qu2__uv__D48dTrcXzJxfrZZ9duVovF6vV2---TT5lYBYaSSAhCiwhC62Sz8ra5aoXspzG8OjR5ulnl1WarIb_6__xv5mud9-9vfk__PnP_ukvfni27CohiDlkT8gp56Pz-9EzKiElgmApmYuLeQ4hZCqIp2kqqOaYQ86lsFZy9FHY5m53YAQhJQkxjdPofCmgtSgAPqU5-JjKYtW9_7hbnHdEoJWa5xAmF2MKc0hhDiEfr6-lgBhSSdQsFof9WC8tGkm5AFEKMcUIJCgTkkjeu8mhFIUpp0zAqRTvg9aqpEylBO_9ODGXHLO2JqdUcpFCmMqmkKU0KWVAmGcvBDrnEVgpCQw5ZUbMOQsUdV0JAVVjU8whRoEy5WSsTjGHOSI-HDMrIaVQSipmABTBh1iIiNCoENI0eG2UNgaQgGGapofuf4q-ruqcUgqRiJVSWsmYo0AGIiFAS0kFysMfHUIuApG1kc55IYVUsmlrN3sfU87ZWDM5J7XMmY6nORcmxGkcY_Yhpiy4FMoQCz8A7goQaK1Xy46oFJ-XnWr7uhBmBEJ1Cs5lPuxHXWlCHsa5aZvZ-5hSv2hD8k1dE9NmvbRC1BI2i367WQoQy7ay1iCxkEorAcBCqL9vaGcSgJXRBADIu-Nwmp1LpSh9HOfZ5cE5kNg1y-Dd_WkephixXO8OrTamkqtFZwX8P_7Tl2eLdj-NaKCt6j_89Eki_PK7j8M0x5wqY7ddlSK5jIEhpPj4YhFn3yr44cvHylS797v_-Muv5uz_4T_8o7_71e_-_M9-rIX693_x68LCxxB9_OyLp9M0NW0NLIC5rhQLIY2ap5lRyBd_-s_GeSYQPhRpdKFcVzoEP45zbSQVWq-XhTFGWq0X_UK7mKbZxZgQxBRma_SLl88lUt225-tVCeHp4ytK4dHjy5IjAEirHm3Wx2ncrBdX22XXVG1dzT42lV30_Xg6VZX1o3t0tW20jDGdn68qJRSKFOKDCrfkjEIAYgpRW-NcCDkDQ1vbUkhpXYgQOKfc1ZYLGSlSSk1rjNZQSCKWRFKg0pIKIQjiQlQQEYTIuaBABEQhgOGBuQUIKCRKMcxeSpGJcinEgEq44AXKQpRzfpDASYUMDAgxZynlA9dJaS1REvPDQn3KNAVntGEAEFwAfcwhl0Q5MpVUAJAIcsn4sGLFDMRSS4GQEiGIlLOxRmkBQlVGKaOFlOM4zXM8nqamb0EqFGp_GIxVOZcYQkllOE2HeahtDcTSWudiFkDM1poYUkE2Wu0-3i_Xi8Nxf_no6s37992qF1r6cY6jW59vp_HUdHXxeTqNVtvj9Z13LqSAAoC5aZumqVdnq-TD7sO1YHG8uxNCosR5OlDO9x8_SGRTt8qq9cXV6e7gTqeHzaQCoI3W2qwvroSguu8SUQ6hOevT7FdnaxcDEbIABm66FUAqhfxhL5UJ88yZUKnknFZmPrr26jF6hyUTZf571nVBRNu1yug8h6aqp5u7ELJqbIo5uWRa409HVVem1m4ajBJ11clKK1Q5Z6NlGOfh_p5CcMOp6XpdGdM22yePp_vjtD-Ox5BmzyHv3txZY2JO29UqeiquxJRUEQIgpUA5uTm3tSoxL7p62VfLtvnFzz57fLberBrBuGrrtq6uv_v46cuLR5drBZIB9rvJNGbVVbbIklNbm_VqwQwhpNv7w_Hkv_zuLWux2x_ffbhLMR2GcRhHYOHGEN08HcbjPo5j_N7LJ4lJsAjMTd-mlGYXQsrH0dda72e3XDbHFO_3J-8dUR7Hqep7hkIpppwBMMWIEhgZOE-zk0oWTsFFKUWBEr1HQBJEVJTR4TQLLSlDcrNpNaNgjQACSkFORdBpnFjBh9fvR8-bP_nh3_7yN4OPNzl0bfPd3bzZLt7ud__3v_5m2_VHX1pjEqtKSyTxED4zkBZSKt0q29bVk_Nl0zXex199c304zSjkoqo6KT9d92dd3bVVSpEFLdvqfjd0TT37dL8_SuKfv3r8-cXm1aKpNFRGzyF-9W5_dHF38m-ux6rWQquzpW1a09UixXTKKRb43bvbGMMwOSnU425x0TVW6cT8u_Hw__7t73_5u_d_-_u7mIoPPidPXHIunMEauW2sO6bdzr95c7_5_7P0X822btt5HtZaT18ccea54l47730igAMCPCIYQUosiWXJLDnIJctlV_ne5b_jC_8By3bRll1lkSURIkgQBA5wzj47h5XmWjOM_IWeWmu-mLgcN-Nm1De-3lt73-eZT4Dsdju8e3b0zvHRsm3-3Zff3Ha7qSnPppP3Ls4qZ3OOIeVszZrp27froOQQ8s16m5Kfzaq9p0lbv_N48R9---Kr6-shYPZydr5crzbex6EPxpimrgprFlX7-GTZ-fTy7raq9B__6KOTujZGP3v__O3toVSuLrX3Q7_rb3f7Uhe3d-tJ5awtt9uDVng6K9fbPoSsjc7Eu9Xu9m7_y7_98bK0JKLjYBX89L3H87JkSimSMDFAzCIMt_u46se2sGJ1FtweRh-zj9SHdH3Tr_ejKBVIXr7d1HWZiPrBG-tE8ZgoZO76sbinV7GiLCJsFUpOWpkfPXvw3oOT0lWj9zeb_Zvrm13oJvNZO53O59N2UrJkFHn9_If9uivranl65IO_B5_7mMIQOA5H89MU_KSdNHX5zkePHcMnv_uRAZzMJ8IcQqqLQlsVfZjM5rYphkPX7zqjVN1MwDhW4vcHBShKFfNKIfbrbn56OnSdcMYswAkRQCGICLB1lplYKSAqSpdyQhBrSgQWZgpBsgAKgujKAmcQYWLXVihgTAVabr_9xpX17fVbWxfRe0Ss60aEUbE1Rml0Ta0VRO8L54REKdV329l8VtVl8KFsi6JsVm9XRiMxEMeyMOwjM2NiCsFYo5wRa6yzaUwUg6tKTikNHQCJZBAhJm2t0ej3hzCMKQROxNE3ZRH63fnl8nI57_b7H3_y4fHR_OzsaD6ZGOLlrP7Fzz-ZFsUvfuejWVlWypyfLGaTWnLQKB8-fThp693gr67uPOXb2w1FcOI4RWZAlHrSOGcev3t5spgcLebox5__7U_PIN9c3fyf_4__VRHDg4v5g8vjo6aoKpcT2UKPKW13B9F6TBSYY6Zu8F0_sFJNYYfBv11vjbNj5G4YE8FIcjMMu36oq3KIqQ90t9kUbVXULmehnMMYgJSnZAonCZjyGMLYj8pqP4RqNjGoqroQZspx6A--H9FoigE5D6O3lQM0ylnUeF8ZB-GyaYhIhJEZAE2hBVCUvlcCK6e0wTiOTEzRW6NjSikmYzUKEEPOSViKuhYWa1QM3g-jNsoURmsNwkXhwhhdWY1jr5RmZGOsEFGiqqkF2Pch-AAgMaacOScCFlAIIDlSUzegMaYIlDPFlFTXdYiQQhz7YTqdoIKqtGM3ciJrnNKotW7qUqECIuWcMjoTU77H9-Fk2hbGgUBVVev1XjvFRMR871MKORutUyQGESHKuSiKvhuNs90QUsza6pDj0A-MpMBEyoUr1ncrp-2-98ezSVmUVWWrwhptEpEAiwJwer8bAfH2Zp2JVqvN2I0EZIyJOWl936hWVV2QTyJ0fDI3KMOmvziaPzg71QIW2FkjIoKYiQABQcYQYk6CyudMBCGlfhxv1ztROFs0t7thve0iymTqvnx-7Vy17brdELbbboixcEWOyWozDOPl0SSCevXyupqXs9n0-Wr3T370gd_7yuo__eIVo_g03h36X7z7yNn62-vbIUikYQyp1E5YPn33oUYIYP_yN58XjWln5o9-7yeVMn_2V19crw7rbtBOg1GQGEUOMZydLEXI2XJ_6JrFxFptrNPL3_8H9aRZNFVRmhQCiVitxWpJXJdlWZSgdAYqS3u0qHOgYR_mR5NJWymnhHJpDAIc9gc_jkN3OFrOlcJ91zeVBaIwpIvTY0rp-evryqAt3bQsr27XR7OZ1vj4Yl6XJQoXqJhJCyxPFsknY-ykKVOOGgFYMlPMqQuhqZswBiIu66IprTADICqVQpzPGmOQYnKFJeCisChQaq2UQhGt7mH8oJTOOTGxMxaVhvs9WsrMbIwFQaWUsiplJmIAzCwKYAzBGhtzFhBnDYswkQCMMRbOhkQgymeyVufMMWdXlj7kMaQxpERUuiJntrbIdH-wFxGJmQEAlAIFKRHlDKBSSMSYGJiYBHImH1OMGZVW2vhA1rjM7H2IMd3P7621RVtvtz1oFVNsmmrw8e3dpigKbW3RlFXbhhCKokwx3V9IUpIweKXUo6NlN_q6qQDB2qIPw-lyubrbXZ6fZaKrq-vlYv78uzfT-aTbH4hht9m4wk2P5il5P4xhiAl47H0MlLMYkLptd7db4VRW1WG1QWBbuG672tzd6qrRBO1sIYLDbj34GMI4mU198DFTTFTVE6VNGg77N7fJp25zcKao66JsqjD042HrXG20BWNEEjPbqkKNDKiElNPD3baaV3XV9vuDUgAsGoQp5zFrZcpJFb03TYkCChFEJoujGKIolXz0Q48AQz8gknGubCfCud-P5aTRxiCleuIixeQ9ALZHsxIAXHH5_oNJU7nKzY-nqGzb1E1hH5xMTy-P0OiPPr547_Hp0bR98vDknQdHHzy5eHxx9OBscTqfnJ3MpnWBiaaT-ux40S4mFON0Vk9ns4lTj8-PTuaNRjmaN8fT1lqbiavKgUJwuj90L96-ff3mbnk-BYu-92nsY3-gTFrrpq1OTuePHx4DQ1VVs9rs9z0lBmVYMPoUfVqv907rFHP0PmY--LBZH0JMOUYAcWU5dkNT18MwjIO_71rEGBUKCx_Wa1eWLDn6SCI5EAmDD0yZGZKPiErdnyFiELx3BAmliMCJmJUDZuaEqKOn7_7qiyEPu_Vwe31YfHrBq-7li5vr6-4_evdssz38f_79V33gu274l59fzepS2ZK1HhOIRhKuNYpWKXEakiGFyjZ1sZg2pbNaI6Lph-gjjZ4oqYvl7MHZ8vHJ8ftPT3_y7sl7p4uZMaCxP4S__u76y1e3L9_sQvKXF4u20E8fTgqHd5vum7err67Wv325LmyxG-HlzSbxeH50vLDFvK0mBt6u1__tb7779ddvv_x-FTwfnS_f_dHDH7563pQmBjo7nlHin33wMIkcT-pR02GIEE1TFvPS_s57D54eTU-q8vnrtbKg9nd_-PGzWVVkSi-228_evvnsdrvaDt--vt3HlHxc7f3Vq7un75xKyEfziXf53_7F82-f30wn83lbJ52c8D70gGYMhw_ffScOQ1O4J2fLEu3LtzdN5WZN9eD8uLJF4Yq7FH0fYiIAaUr38MHZ-emRQiwL-3a1n7SND-PlyYxF78eDsTYLK6Mop6KACKq0VgGzM7_88L1lUzqEwzA4g6gsGksou8DbvT-6XA6eN9sOlE4c-yH-8N1qOwwi0PvoKr3Zj6W1otTt3S4DbLohDHkMWQGiVopp6MMwhsLZqnbTtlpMmt_92cenbZsDeZCvv_7-5Zu3rHTdVg-fvNMP-9lykn28f-5vbzaXZyc__ns_-uYvvz66PO2GwZRmHMfsx9lstllvi6qonH3__acf_PiZinhxsjhdHk0m07p2l8_OndIvXl4tjpdE2Wi7223LwlZtO3Z9Pa3H7U5irmY1ExtTAJE2SjkgH6w1SAICqAwDS8ogICxKoytLVzlB5ERlVQpLZjFFCcBao6QIiDmTNlYpVVycpvVKkYgCTVLNlkO3bWctcWZm72PwQ1k1RLmdTLerNVNuZ0dKixLIMWmlrS1Wt6vZfOaM26820YemrW2h6kmVWdp2AahCIOGEStBaRN3Ol6kfETh03liFQqHzkhJFQo0CKJwRjVDWWlkNR4vmyQcPG1eUTn305MHq-vbsePb3_uCn7WSy3W1F6INnj5aLeloVYRwfPTp-eDIb1puL01PO4fxocX52jAq3u_2_-O__rKiqDIAGMrJGPOwGXdpqZiens6ZsHl0cnV1MTxeT1Tr-n_5X_-gnT975R7_8RYngnDHG7Ha9qexq3W_7oY9hdxhdVeYMxBBZuvG-VScpM5CExDHkonCHIfiUQyYSGHyKOYNGY93b9S5Gb43Z930IooxhT8fLSUDott467UrnQ2JUjy5O94fBOeeMTcSgTYo57A7FtPJ976zRVkFmXVhR2jWlLYtqWiPi0I-2KZQ1zCwMxJkyp5QB0VWVAoVA_aZjYsqZQkop5pRyTIgCIiklETHWIkKK_rDr_kZoK6wRtTYpJiIBJYwsiXLOLMwCQISoOJO1xsf7MkBwZUHARiujFWUWFG2QgL33-32fco6Uw72BLgQ0mpnrtmQCBWitdc4kyk1VAiitkTO5wqy2B2OMgKSYMrNWqq0rbYxWuO8PWiuibIxFQMq5rSsBRID5tAXhoigoZRJFlEHpmPJ03hy6IQXPIikl4xyC8nEstJ4vJrO2toiFUplJoQpEq-1hCH6_H67fbJQ1h10XcgbL3T4U98ctUUaj0RpRKSFiUkzLSYs5L-rq3cfnF6dLH-JN_tOz-gORpI1BBYll1-23h3616oKC9X4gwHZS50w3d2tXWtaqcurN7X7r_dV6--33b1VV9XH0xAnFcwJQqPVusz2aNX__xx8Gxr_89Q9Hi_ad9x5prR-dLC_nk34X62n1ct9vxh5L-_GDi8dHyz6lz75_62o3xhjH8On7j0tjjybtkPlqNzx-cGktf__bb_7ZP_7lm23_F7_-vp1NWEMQQa2rQhlj1qv-_PFxYYxxFo2GLBRy7Yx-8nf-aVXo3ZiWs8aPaVK6TGm987XRdVkGztNpVVXlpCqtoGEoHEYfY8xlU7NI21RW6xiCQVwu5_P5tDSm2x_qQp8cHx0vZk6pMYRnj84-_PDZdrNJIdVlaZwex6iUOj1ZpjHMF23tLLNUhRWWwtnoQyYqrdL3oQ6np2XtQ3BGx0SLaUPEklJT1zklVKAUOGes0YW1xmoAQIbCGgExyihUwoIIOWZQCpUSYVQaUYiYmQGRM5MwAThnmISBGaBwLsRslAZkRCUAMWdiQY0GjUIEEK00CxMBZWYGATWMPhNlZqXvMToq09_cKLTWPuZxzGgQlM6JUuSUCLUCFlCAohCVmHtXHwAgIibGyKyVchZzSkQyxqDRBCKl0RltnRUCH1Ki5ENUxuz6IEqfzJr9EIE5p1xas90NZeFyTshQFPbNegdKhxSrpmFEpcxmv318cXmzXu_3--OjhVKmKY0uCzTY1o0k2m_2bVuA0oDKlC6OwTgjQDmOIIpyOjo_TmFUWjd17XcH3x0mk6bb3MTtZr9eF2WDxswfnZXVLA6eM1VlabTE6G-v3qCGupgunj1JY69YBJk5xb5v67lQOqx2aMQ2NYAo48a-L5paaxM6X5W1JJ-joEJbFDwmpmi0MtYxZeFsnS3mcwBxxvWrfcoppYx4j34CBQzCJ2fnfb8vTDkMXdPO2uXCj6MBbazutjs_jIt5nQ4H2vYnD86l0IfdeLJcEqSj6TQEf3u7CmOsm6ot68W8yazbSZNTLrRzttzuPQkaa_thePn27b_501-9fru-225evV3_D__jf_jqy1cZcLPa_cmvnh9CcIULhGXtgGG_99W08D6-fH312y--6roenNMaj5ry5vld2A-HzXh8eoIKCuv2uy5meefDRw7NfnNorPL7ISaKwqJEK9juupxTCKmo7XxRv3xxY6wOMQ79mCKB0mEYECFSjINXyijOcRiNs2iEYtQCnCNx5EzGKD8MQF4bDZQlp5yyMhacizEVVYHEhTPjoRMURowhojMKGe_Ja_e2i977bszR_-bPv3n6hx-Enr58c_i262bzqqp8n1IX428-eyXOrhr1-Q9v_7vffPcmcAKMIIW2XeenVVHV1aQsKlt0frg57G_2_Q-7dRR8vGzfO5-9dzFzzh41xaTQmrhF5ZwW5NsUtTbE8sn7j42Dk7baj-Ptfvjh1eb7m93Vqu98EFGKpI_pu6vV7rDv9-Oj4_msaiZl8e--f_6rtze71QDOzN6rX7xa7297yaLIzVzx6OxoVhUq5nfPqnXvO9_3Gz_V7nJWf_zk8slR0Totib54eXPwCUX9zsdPDagX2_63b1Zrzoxuf-i_f7vKhMvz4_nRJCdu6mKzG_7ss6t9Gl7fdW9u1vOzyaPHl8rkiS1Zq_PT0xCG_TBAF6fN5Jc_e__0eLEdx1IDG_A-PJgtpk0VM33-m-_2Xd_3vTLw-OykKpxlaYpScW6qoipsovDR49P11teFeXh-zIKAHFICxF_--INHi8mj4_knD08ae2_Q4sPolVJo9aqLz6_XmzFgW257L6itNa_f3O37VLRF70Ng9CQ-02o7BhYCfrvueh9vDx0T36y32hkiGHvvCkdEJJRirAozm9STuro4nvej_5M_-9X1zQ0gCqjN_nD54OL67ev5dHJyvNit13Vddd1wNJ9ro9uijjmbQlXtNMSgGSfTJoZQGfd7v__h7_7k_fefXT4-mp6ezZ3WTiAMQ9vUDvRuu53OZ74b27aJKWxXHQtvN93J5Wm33QIzghjjJCantXaVUC7KIseYU-aUiBMoFAOaQYGwMGpLTK6aKKWZCQRBBBCUtZASMivrmJKyVlJU1vDuICmOw2ANiFI5exattGpnsxA8p6wVjNtNDDGGfjJZbO9WCBkS9ev1eBi0Q4MaEWPwAmDr2hUVCu9XWyYOfhz6LvmgFStNzFkBx76X5JXTtrZOK9-NAFlEjHOSszE6p6DvqQ8KEQUyOas_-ejZdNZMFSqR0I0PTmYns_rm5ubdB-ePHp41Th32u_eenL_79Px81rRGTyeNAcyBtVKFc8HH759fcaG7mEKmoim00X4IVtnKqvOz49_9gw_qzA_OpkcG_-kf_s4__3s_L0G1pTMGFYLk3HUHoJQUfPH99W6My-UElPaBBNTO-zGm69tdYo4ikdgW1qekjc4i-yEMkdgoUmpIGbSetu56c6gnzfrmbrXeHV8c3a321mrtbFHYtq4yJ1KMTsUsUJmrt9cGMHlvtNqvdiGM3e6Qc9BoUswkWZRCo5enD4mDtZWgQmt97421gTimQChoFaBiROOsLmxOBDkqROesqTSyoFDOhIDaaVdVaDWAFJUDjnHwYz9Wk1ppzDGPw6C0QaVsYaMPTmtKEQEoZxY57AdA0EoZZQbvWcAWtqzKlDJlKoqKiau69WEsy4Jy3u_3zlrK6dCN_e6AVhdl6WNu6jqNPozeOquUQoVM0jRu7D0TF85IpjAmpTEzgUJhLq1BEBHJie7WB21UDJk5W61Ka3b94BAEgEh8H5WSzmfOJIiHw-BKx5T2m4M2LvRDXdpCad_1pycnSpuYqd93h0MHWgmq3g_KmPXdOowjCc-P27EbRdGhG5nEh1RPy3sZ3KHrhCH4mIkenp00k3I47KZN9dOffJB9PJpUs6a8nH5gFAmCRUhMPsUxUQKMIhlV348EnELMnMZEzND14e263-eoy2KIpAu36feRwbiyH3qjTUqRcmy0_Wd_9-cWZLM7vN0cKPuqcNdvbv_-3_r4sB6nTXl76L7b90VZ3YX-8WJ-VJTFtPqT3_7Qzme31yvm_J_88kenk0nv6evnb__dr_4qp2FWwf_uv_wvXr--_Xe__m4zxPW-C5mUNm1bd9udUSYyT1w9bapxDKSo2_bvPnz41W-_0R_98f8sJ4mExhXz0mqrb1fdo6MpZ069J-LQe4kphDgchn03Lo4mzbQJKUynkxBDU5ZxHBXys6cPm8o1hamrom3Lg0-LxXRSOp9CDskZY435-rvXxqnT0yOrjTNGKcwh1mVRlEYjEGetFBPdT8abqjBGMzGxZIIQYgpkC2usoUyZsrEmh1CWThsVQixcgQIgEkO2RhmjUMRqKwIKFWqltQJBpdU971MEtMaUCZRiFuusiHTDiIjaolYaBJk5EyMCgmKBfvSCACDO6JxZAIjJE-0HbzRqoxkgEzNzJEIQZryfRo8h5USBJBIppYZw75mXmDlmcs76zFrdE3mVgDBDSNk6m2JWWg8x35szDvvOOCsCgpqZ1ttOGxOTjDFvdofJtGUWrbByhYBGgNGn_aE3TscM07oKwBpQKc0hjYmapgLEfdcLg7EGBW9u1icnZ-vNpinq2812v99Xk-l333-3PDp58-ZKa5OAxs6j1q6tkACNcVUBmYqypJiYiUMUgL7bG2cBEZXaX901p0cgSVKMwz7FHIiraXt6dtFMZrvtZr87FHXjSiM5CTCAGvejLa1VhoeAVo37nWKo2oKDD_2om1K7MncDglZKo1MA92_fpJRBlmo60xr86CWzsYaJcsxOa2Ep6zkqO-wHYwlAOOfF-UMKARD7w9YVpRbMOQGRc6qpqsmkNVXjh6iNjqNnZgDZrlaH7cEZjClWi5kqJpPSzeuymVRvr2_v9gOCckXZ9Z0udXl6khMP3q_73Q_f_PCbX33--odXoQ8UU7fZXb2-gUQf_fKTsN8ipIkRChxZxhB7ii-u7rabbr3e_PDty1efv6C-890Q_FhX7u2L2-nEMeTJpLq929R1GYU4k2K4PF34xEqpIKys7WPcdn0_hO4QUoz3W6_Bp912cM4Qy_r6joFB4zh0wkCcxj6iQg5BsaBGYeZIyQcEyd4DKiROIQghpISQJGWFoJUCBSJgizL7VLdtCoEEUiJERADyGbVVhck-oQKNnGMQykI5cfj-u9cHJa9fXN-u1n_5_dsfXmyuV8OjZ_PNdjish7ev7qBSh-vt29X6L754_i9_8_L7cf8_Pb9ykBeuUFrNGjMrnDCANhJTllhV5QgCqL3Q9W4IY_QiL263z282X7zZfvt8V2pVz1qDsj_414f-zbq73g6EenPwROJqm4TaqhxTevbg-KNHp-89OJ-0LRvzF9-__pefX5VgAVBQ9TeDU-rx6exoUn30cPH4tFnMqt6P6Mo3d3tr7Bji3_rw0c-fnE6a0t--HETdrA9fXN2xtRFEUO8C__tvrv7qxVtdl5zhu5dXVVXNjtq__aNnVeZ159frXR_S8XE1JmZANjpwTJ1frzbb1bg4aSeXx1_99VehH88n9YePHv7kg8ctmz_5q2_GccwAiPTxo4uH8zlqEB9Jgc9ZABSq08Xi5cvrw7YbxrCYTx9dnvb9ARhiJud0U1UIkil_eHn8k8dnP3pwNimsZiiMFgEQTCnuw0iEIUMmDCwpixh9t9qvNsMQadd1IdHl2fTg0-1dp5xJQjHI1U0PALuDjyKZIQPu9n3TTgY_agUk3HtfFNUwpgePTk_m7aJtZ3Wz3-22m_3ZcnKynD24uHjnyYPSmKoyF0dHQvDmzZu727uHD87LwpWFExFKlEKYTadEdPv2tq1qIjq5OPrZjz764MnFo9Ojj5-eOiCdSQug5KeXp-2i_vzzr7ebw9HpsS2L16-uWJiE-xCLoqhcIYD9bq8QlNE5hETMnEFBHMeqrcMw5uQBUVDnlBQoBdoUzrqamSGndjLxg0_EIOKqQhstlIWFRVAZ0IZiUkrbpgBEuh8dpcScy7ocu8774KyO_VA3DUC2ttyudqY2bdXu12tUOJ0trOIY4mG_18YCiiCnRN1-37ZtNanRqZB9VVdKuNS2RDuZH6fgrdYU47gbCNHWhXFuGHLdVpBSXVR9N_yNNADQFCUIV3XZNNX1m5tPP3rvyaPLfr_5O3_w48vjmULZH_azuko5WJAnD8-qws6csaA45RQTgiqcsWUxjn5zGF9vOg9qO4xoi37Y9_theVz80X_9D_W6__STD_rr4feePfwv__Ef_Ozdp8dNWVnjjI4pZ-KB42fXV7_-6gdPsu5S2TRlZQHUYd8bZwTpfGq-ud5nFlUUfUyB8r4bRAAZlDHdGCIzO73rw2GIIeUBsPOZKB22XQZgAWfK2cQQyGEMrnbbfhBhW5daq5xJfMghaGUIWBk1acuh80XjYsrKolEmhGy0VhaV1awMa1CIcRyUZG00C8chohIAUM4aYySlmBKi5ECFrUIYERiV1cYqAznEFEKO2RidiThFRChKiwpF2BZGayRmJtZKA0Dw3lgnxCCEoEFIKaRAxhkCSD4461zlhMQVjolRgTFojDEG6qJmAEo5JaonNWrMiRABUCElBACUlKLWunCWM2mlhKGpC4WIShNKjMGZIga_mM2IySjNDIfddrlceB-s0cQyraZ3u633qazKmKK1OpMQSNW4RLBbHUxpUXB9tzMGnUVEaapyNpm4wm1D1-37gx_6rsvMmXm73udM69stpQSIt3dd1dar20NOMWfOPvohTmaz7jCCwHazSzGXTfH00cWbmzdGpC7MyXJihed11da2LmxllUathCLx86sbBhiz7H1UZfX91VsivtlttVGHHHebfdnWOeR1H_Yxv77btdNpyjTmBEqNyQ8x3u72hdbTsmgNPDg-OezCEOjTT975-sVrrc3mevXz9590u75x2gmw0VarbnP46eXp7s1uHf2bzSEJ9dv9Ow-O3js7yTH9i__xL7_75vl0Uv7x73_y4PSsnDR_8lfflHX93u8-XV0fLi9Pz06mZ6eLH7582dRV0zalM08ujm5W2912nxIrxPPHD_Xv_C_-a2dtP4bSIRAnZmKu6oISV1YTiAacL2cPT08F0Tnr-75tKlA4acuisMN2a7SyghnTg8uj73-4WSynJ6fHp7PpcNi-eHnth_Hj959utofZtJ62VRjTzWo9m7WFdSH4timawiJCyrw5dKUrFN4TW9kV1qIilrJyPiSjlTUWUSlEBmnrsi6dtTYQG4UirBHqoggxNXWljVaICpRCQFQCrPBvUv4AyCI5sSgAVIQICDERosrMTmvKkhIpUAjQj55Ycsr3RH-DyhjVFkVm0ADE0o-j0rqyhQKMGUQ4A4SQmKUo3L1UcggpExVVmYnGkMaUrNbW6O1hGMYcYlRaMQMoEBIWGXxgksIUIUVQKAIxEwiEmACRBLUxxlifUlWVWmsA2O17W2gfQ86w2nadT5lp2cwTZhSViJS1PnFiEQAfggBGZGfdGIMrir4by6rsu246nWZOykJVVSnl80cXNzfXZxenwQ_Pnj7b7Q-urHRVhDGEPtrCsdCw2duynj84H7cH50wce-MME-3Xe9vWyFJMHKcsCSCT1QYwUgzdamN0oSdVPWmr2XEMnghj1wFA1dTNrF1dr4xVrjCSCYRAGAWcK4UpjsnVVVFUWrsYEwi5qop-vN9RD7stMSllJJHRBogEsajqeNhrrbtDXx9VVdsKCeWA1h62G-0K8gGEOZIpsHBFjhFQcaZMZFpdzxqldE6RSKq6FU7lpD5sNuQjj8P6-YvV3Wq164rWLs6OyEetzNu7zasfru6uO5_HV9-_vrvbjt1u-3YdxzGHaLVGo0xZAEAYwvp2ZQp19f3NZje--zuPP_vrb27evvn2m-dj1_XDoTwux8MQ_TCd1dpVrm6N0b7rSamxT0VTz45Ptzdvw5jWt5ucuVsfYkzM-a-_v04pJaYsSCn67kCZcvC3N7cIhiELwjiMqNEfOgBkohAjAwCiBM8xcKmZWCOmFJFJOWBOAMA5gUIQQIlpTLapOcQ8eHQ2izJK526fhgOnjIVlYhFRTNoaFOYYQFAi5UBKseQkggLImVRZlPN2dbtuOfN--3Iz_vBi087qox8_3N8N-_UQQM4uLwunbl7d7La9Bnh5vfmLt1e_frWZ10VdlQ-n7byqlrb-9u1mzMPNpv_Bd5BFMWtETtKxOGcfztufvHuyrIreBwVwu--vtjtty9XBG6V84tPT2W5_2K42ycdGlY_mbVu4QitV2t-8vtqGVFZ2zHEz0PtPL8UJ53Q6KY-Xk7ZVt2P8q-9evlkPBQIanJXFH3367rIsktC3620H6m0MN-uhYwkCBx8enzY_3G1_-_0PBlRIQH6khB8_Ph-8d54L4WvfPX-x2qegnLtdDd0QQqZCzMN3Th49OYYxRx9_-OL77W5zcXm2Oqj_5I8-nDu334_M2ZQm5vzRk8cXTVVrRcTPbzeQRRRqjWdHR7u7zf7gz04WD85PCqOuV3fzpi4q1bbVB4_Pl209q92j5eS4LZVSzDkTo1Zam86n71-_ZcD1Lpyfn6Ex3eDHyK9u1q4qN13fhXR7t3t7u3-7PQSLt1e7xBQUALIPOUPyxOWk3oW47bwP0WjNIsv5MuVc19UwBG1sXWpKWQsqIiWUGaazej5tGZiAXr--LqpCAPa7zo-hH4ZKuQcPzt999rB0drffAEBdl2cnyxzT_GiihIeDf_zo_L_6T3_58PzkeFJaBcjS7cf7sQ8a9fXX386PFo-ePLx6e6u1_vDT97f7jYhCa8MYox_iMKLWlL2xWkCYhYjr-UJEBARBYmZVOqtrazXnbFyh0cSUyqZVwGC0cUWMuZ7McvRhDMpoFFHW6NoigtaaiFmUMlarex415hB835VlpQRDtweGnJIrSxa2Tve7nTAZg6HvUgzee_JhspyJJAFRTmdmA6gNurpw1pJIv90VrmQ_ENA47EQEjda2VEajQoosAsaCMQgoSquybZTGejFRiPdkRgqJcnr26BHn_pP3nv3u737iONeFDX4MYTw7Pi6sPjleoNB80ja27PeH3b5TWmtjE0mk_Pz1zecv33718pUqy6KsV9e3P_6dT8GTMVO1S3_083f_i7_307_13sWPnp3XzhgFWiERx-g_e3193ffXw5hEt5OJdiU6S8I55jFEpdTd9hAEvl8NgSEpvDscVFsMY76522iltdJJOCTKKH1MO5_7cex8iAKu0A7xxQ-vXeHKsgZUs3ntPZOSMSRGysKISqGmTMO-lyzG2jRE61QfQvLJTev-ENrjWYipnlZ1PcljAmMocQoxhlHlnGOinEEAQDgKsdJGS4ox5ZyYmY3WIhRSCGMCq1GDEslELKQU5hgBIeecY3ZNBZz8GHPK1hnORDkDqhwjMwcfKCVi9kMoikIpUUpRTsQECgCAMxOxMDOIdYUf-vvPiZI11hUuhpyyn0xmIZK1OqWQY2AAY4xSkHMGlpRSWVWAggoEZEiBMhFRZrJGF84Gn4iTsDBCJkrMKUYAGLzPkgQRFFFgU1gR3B32mXLwAY3mlJkFIGtj-2E4OTtVWvVjvLnb-BxC8LvNph8Gqy0gjMFTzGgUCYuAspBiFEopRe9jUZV-jMzEkJKPoMi54vhoebu5PZovUPh42lZWXZ4eOa1iHI5nM60AtfiUN5tdO2kLo9Zj3B6GTT-MiTb7_ZvVtizcF9_dvPPg8m7XgbFbyterbVYwpuhDapu6bZtE-fioXTbtH_3k6Wdfvey69Lf-8NGf_fbmi6-eP9_t3n_60If-2eXZxLmmLgjVn3z27Zfr_XY_gKQfP3koJBuQz17fSEycqVX47Pzs7GT-xcvXzz564lfdf_5P_-D0dPkv_vt_f3Wzvzv0v_3195XW_Xr3zvvn2_6werGtp-Xv_d6nw97Pm6r3gTmPgy8Ku77b6ge_-GPtLGRRJMQ0Rkbmfghl4wQlE5HCsY8sPGtdVVtbKKU1Z26r-uLieDGf15V7cHn66PLssNqfni7a-URSrrRuJ-3Th6dGq8Vyst8Pi1mLSs2n7dFypjW2hWXhFGNTV4W1fTc0RemctVY5be6vsFYpEeHMSqMxRlsVUrqHeJaFE4BxCE1VGKtLY601ISQQsIVWiMhgjFEaRYBzvl8_aaNYwNzf64TH4DOR1gqUELNSOmUyWjtrFSgfx5i5Ki2JMAgAaKcZAASGMSFiAmZBEWSATJQjoVJaAwsAolFWRB16z6gSMVFSSpOgs4aFQ6LEnJjqquiHwAQpkjVq7oouZxG5z-xVtdsffMophJxZQkg-RkBFwixoUDPjvuvLpt7turouQ8qgUCsFgsbo7b7T1oaUh_0YfEopiogPEZRKGYzWaFSKcXl8NPSDNcoU1du313XVGquEse_69z_50WG1ctYNu2HSNIkZNIKGZjo9HDrU5uzxwzGO6zc3RdFYVxhjGUQbnTMpQI4JAI3G5mhGQwI0ofNGAeeOxv5wt64WU0FqmtbZYr449Zl2m01VT48fnMUYY0q2KIBEUkwhpcHDfYs6pOl8Vs1nSkNKOY2pnS_7bUdC2jnOLERF2wpHQZVCFhEiAhREFcdoCytKae201TFFpdHVtQgZV8RhyCmhUsn72Xw5dodwSMkH1goJE7EolVKKYdT3fzD9EMYQhnF_t80Eu5s9k2y3d8N6pxWnsd_f7G5e3T75-MmLz7_vd_29tswoyEnS6HNKEHOh9e5uxzFqa6-v7rrdNgwjECmUnPL6uxtRQhx9729vDu3UAKbQJ5GcxvHmzWbo1sCcQ1QGQWFMiUg-_cNP8xC8H-7uNjF6ZUz0yZYmHIZ6UhujwjDmnG1hKI5ozdh554yAaGPy0EGMqKTrOleUSus8DsjEITJJJgIUEZQUQRiBmEkyK6dyyHYxoZgNE4eYA9nagChA4My6tByiEcWZhLMpjRJIISuncT7jkYmwcDUwp-CXD5bTmdm97QG1X232qw1ifP3y5vbF6---fPnTP3z_9e1-db23Tb1djz74f_ubr9-udx-__6At3OWk_OjibGmdU-rBdFKXpXXlEMLLfXe77hh1zvD8tntxs3uz2b1ZHfohHcbMAGyprFzTmrt19_hoMnr64Gx5uphEhBdv7v7b335x-3LXRfE5-zH2XT9pXRzHvutOHkyfzo9ShldXm7uDL1F_cnn63sXi44uT88VsHNPnb7d_-e2bm84fPHZdTkr54EWh1Wq9HVbb3bfXu3_40w_ef_e0Neb9d8764K_vOl_qN0TfvlrbshJR2_2grdoNW-J0tJhOFvPbdXdsp69v7qqy-PDRxYfH9T_5-Ye7bbxa7b7fHg5-YEyPT87emU8rq63C715eX282pSsKWyil-r4_PVl89Phy2lZIaXs4vHdxfD6fXCwm5_OpASg0GkSrNQFud8PNdhh9ylrf3nV32w61fX211sYm4RhpnyIZCEMagA5DfrvagFKMErr44OH07VW33g1dpK6P2yGg0lnjdjsQs2hoCltZI8TdMDRNmYWnVSMglbNKASM0xvqUQOF8Us_bZlo1wOx9EoS2br_6-rvbu7uLi4vLBxdV7WI3TuvaR9_33dnx4vLy9PrN6vjkaH40eXxx8b_-Z39nXpdOsGpsCDnmvB88au2cuXp7fXa0nE1niHJ8dJKFKMebu_1w8PXxol_vaIwslIehaSdD11ezubFWuwKFfTdQCCigkJEAOSsgEjDOsCALaI05Z2Zxda1QxXFomtaVOsYgAIDKFY26510oDQKUo1EqByIGBq0QmXJhDFO0Smmrkh9jDM10OlvOt3frejKJh701WJalsCiiPIY09pxZKCsF_WbPRGXhrLEpE3M01vo-guY4hMycMxul0tBZZ5CBiZkyKKOVYk6oLZBobUBrZ01RlcvllDksavfes8tF5ebTiUYI0U_qYj6bTps6Rz-rJ5WzFNJ2v78atxpLrbGdtte36w5g1Q-mKg_j0A87W1bnR4vH0_Z__z__O__od9796OGZdbp0BWqdfPREOz_-6vr23353dReiK5uYRKE1qLNQjnEYBkSYzuqQ-Yerm32gLsO2H0lkTDSpzPdv7vpMCYFQ-ZDimCPzevQ3XX-32Xbeg1VFWTBJyjwGfvrxg36f2lmRATJT7wetdc6ACocQtXP7_eHoaOJDGHdjWZjt_sAErnY5xKJ0xCKMAoAGh3Fw1jiN3e1bEDS2YKPQKBFKTM4YiQlyVkbfQxesNZJZaaNRlNEAKMAg2A2jUmgKRTEAZ8q5qRvvvXEFMRPdj9iQmQElJ0ohocLkg7LorB77qJUWhnH0DCwKukOPgMZpEYwhACJqPXSdc6W1hihZZ4mBiJTCzPnQDVVTWm2rulVah5AUgtKKKTtrQogppkwSQlBKj-M4n02IeRjHYX9gjUyCCgUkhuCsBgCNarffVWVZFEah7naH0lkRBoXMGQS0Vahw6PuLh6fr260rq7vbm0wUh7Hfh7osYh9n80nwIfpIKfUHr60eRw9Z-b4vagck3WHMIdnCtNPJ7u5WKe19_skvfrq6fdtU9e3dzTuPHywn9bRwTVlYwymkk0VLIRnnQvCgVWYBUEPKfYq3hy6THPoBNJ6dLqKn2bwx1u6Df36zmjXNbhiI2BS2H8ZPHl2-enO3LIu2KH773Zvh4MGor58fbrbb6dHs0HXW6q-_ffEPfv-nCsBah8r962--1Zl98JeL6aysXVn2DgplYqJpY_7WT9_9xc9-_G_-_Ne3t5sfvXP2bK6Op4svnt_9m__wbc9c1ZOPP323pHhxdtT54V_9f__q8bMHKdHTn1x0N0N36H3K1tm-H6aL6W7o9eO__R-PiYwxs-NyjFFAgvcsFEnevF2LSU1T17ULkcYYFSAjz-Z1VTc5p977siwB0vF88uL7q2fvnjXWtNqB4Oub9aMHJ5nS8WLuh9A07rDvN-vN4mg6rYsXV6uyMMbg0WxSWFtVNvpsCh1DFhZllDBprRSA0goUkmBIsbS6clobrQSsNePgS2cZ0GrtjEYAFECjKMe2KnImrVAhMrM2GhFRIYMIi9aYiFImY7Uxtu9HH7JSKqVUFoUwodIi4mN2zhhnY2K-d3SJ5MwI6GMSBEDtIymtFRAghL8h6gKRICgiDjE5Ywg4JVEgMXPKOVOeNuW-88RaUDWtzlmM0cZoV-g-MjEjYEh52jS7bQ8KjdY-0LQqQEEmycSRIBPlTKvNviyKzgfn7GpzsLZgEUAtqGMYY0q7fecqh8oYqygxIhTOZZamKokopxx9MBondaGcZRCFYJVCwL7ri7K6u31T19Xtze3Rctn3PqZoCqdEBx-WZyd101TLRQzBWDvuD0VlYxiCD7qwRVXkMSpjmumpD13ovalqStlao3JSppCYKIz7u7t-t2OBerlgyPPlkavKYbsnykVVM6qcSYiRpGgrUxSoUBAhC5QTNNYYk8ZwH4gs2pZAtDEaTQ5JgHOIpiiV0sJU1AVn0kYZi91mUzUliWhjZsuj9d2mnkxzSsCgrcmjZ4oKwXedLtBqu98fqqrNTMaVooCGwCQpBr_tWCRnahatMYpiSP1hvzoIAoIpimZxdpyS9znlEBm4mZXAohGnR0dH5w_atqmm9cX7lymF_d0uBQ_Cw2FnjDLGGmdM6YTJqEyevE84cceXCzr4t9--oUSFsyKobR63B611dTJppotx3wHqqi7fvtmEFBOxLkoE8P1AISnE5EPyHlHAQg4RQWJOlEhbk8LgiiYNByWKNQBaZbQ1mpPPIVKMwox8H0ggjSgsIEQpGldyTgqARbAucj8aBZIIFWfvwVgBUFoTMGeCYa3RICVlgFmDUSyiFEuIOcXqtCmLyWG9F6WAUHTQld6sh0RUttOmLj7_yz_jZfv5DzeJASiePa2HvV9vdpnpuhv-7KuXz_e79y6PS9cs2nretJ0P3zx__fzm7tWmQ8BHj87PziYvNt24H9eHTonOmfsYlTIEiUPyhy7sfYmKiD59-uDZ-VE9K9dZrm83k8oVi6ltzHgYi6K0lnVgIv34aHLZLle7DiSzU5Vzp0ez1ipnXAT15c3Nq_VufRjB2rIox-yTT-v9brmcHM1nInwym8zb2cOmenS-ND7fdf1tH37z_A3O3KvN4dvv3zLRy9dvZ_M6xmCUEYEC4OHp0W_-_GuJcXsIlS1_8dP3Lpez6XKOLH_12bfG1XpRiHDfx3_w8bPW2tKplR_-en-bGCtQ1qmickLy7sOTk0nlh2HZFhdHc6OVQimczSwoKCJJpCzs7SG8utt99Wp9cjSPiVeHHqwNWRjA5zSfNoc-_KsvvwbPDOyq-tdfvUyUx37UhdW14V1_u-v7MW77LqYkWnU-5yQxJqMdEYQY9-NgjLXOpUzKWhFpyjKzbPbDet33wY8hdUMoC5uZxhBC5gygrf7st18B8k9-8lOldekccoRMVy9fvPf-Y53l8elxUxpiPj45vjxb_sGn78wKY4WqwiolALLedK60zhhEqIqSGe62u64ft0OPxn77zQ_dMKLSoR8BmYg1smL0fliczO-u7urZdNxtfT84i9YVcYiTxRKEjELMiTL4kEFrow2lCAo0KhDIMbCwIE-PLoju3S9MmShH0IqZUMQYi0IIoApHRNZoyRGAtdZ-8K6wRiELEzOxFNYAZwSlwEzmFxQO2iBQzkRaIyWqp01ZFkwkyKi11RpAK-T56XHOVLS1NlYYjEHlDChtmxJQSRYQ-ptoLvJksUg5FnWtDR6dHBurrVY__8mPHx5PjyZ15ZRzer26fXh6WhbOiBRWL6Y1pCyA3928ef_y4mQ2tYVb73ZdSEoZU5chxf1ufO_pk__mn_ztHz26-Mm7D46mtVMGJEvKRuNN1__m-sUmyHXIe0Yu3elkkgmiz0BMkra7bghhOmmqotSl-Vd_-d3Fg8WdT0HEUw5E3RgPXYiAoNWbzXZ3GBdtG2N0Tm-TXO33ClUQ2I7e1SUx9H1IDKYsFKTIUhYqg6y3vSuctga0bLeDqY0Q5zEWVSlCoEE5W84qo5U2GpQCo5kySRYm8mMidkVJEQvjfAiUI2gBNK4uJIyxSwyknEVnUUHdFKEfQUhrzZKJchxGXYI2koYREMKhZ4qI3G02IhJ9FGEmpkxKa04Z4D66zAisUVO6P8RkASAgFMk5dX1fVmUKgWPyIYhGQMgpZaJ9NwzjWFYToqyVImZtrVKKiCDnTOT7_XAYrLNlaTizMy7lZJRSRoOCHBIAW2s5ZqXVft9VVcnM3nvQKBmIyFgdAwlCU9YooFALMSjMMZZVebc9JE9la5gl-qyUSjGnlNbrjQiMQ0QFRCTAqExbTXb7TUpcOJeJnLNVZY0Szvmw7myhrTX9bj9pK5BojdVWffo77_32V799972n67tNDPnZ45OfvHM5q2tFMcewbKtZ0wgIAxxG_3azYsbfvnkTlApCb4cBSA0xNO2krCpUjpT4SN-_vtvF6ENAhKKsx3GYNs1utX94umys--HVtRjNgO1kuh_G-WJJRNtu9-zB-bx2D0-XySdU6rbr__K3L2yh73bjf_PHv2vFDIk-_-rV4eA3m92nHz_9ycPzz7767q9__f0f_vLT33_29NPHD692w__rX__10w_O_uN__ss__bMvVq9uLs5mF8v67d3hzZt1VdooKIfUWv3D29ftvBGtDutD01aEWl_8_t8XpcfRb-723Tj6mH3KTVvn7ClnZM2JQemcabvba1TEMpu2ShlI1JRFaXRpHflwdjzfHAal1L7vrm9Xj88Wm83u8vioLNw9WpZSPj5d-jE0dfXO5fkwxovzI6sUkCiFgMoaLQACrLQyyigAVKCVzsSIWFit7sEjJPeuO2fNPdsHQShH7xMoHKNXyoCwRjRGa61BwFjNomLO2iir1dBHADHWgmDO-R5opZVKiZ3TKXHhLIloREHMma2xWmtrLLNoa--VWyjAJCycUj6MPuXMKKiQWWIiREClQCGLHLqRFXTdEFJmEGEgRkR1_2LY7bzRSiujUQBUzCyURdmcSCktGnNMgTkSGaMyiTJWGU2ZrTPaoCldN4xNVcactLPr9a4qStLKj4GEo09d75umdc6mTF03breddS4Lhhy7w2istkZHH4zRCAoFY8ig8c3z16cPz5pJ40xxd7M6OlqMfpwvFp6oadt7E2FT1n6IBWrK2WqM0ff7g9PqHoZQzCYUoihI8ZASoTJai9XaFM7HqJUp6xoRrXN5HHO33V1doXXTo5m1zhRV005M4VxZC2LoB106JnFlgUqVk0nyvj1eUsxlWfaHAwJoBk6kiyp4LyA5Ra0RFCijjTHaFaqoUCnfDcBAOXPwIWR0miVNFzOrVeVKZm4nUya2ZREGn4lFVIqJBYP3xqrm5IiZ5kfLTKSNdU0dMrBSfgxhjL4bXVUdX55N5vXqdu2sffLOkxDjB7_z86vvv8rjGIeIWi3PT9vZ1DoYxyFlGrscOm-q2hY2p2SNcqUZ-z6FJAGAmEIiiRy5aSaaRaEmJm3UoRuMsznJ5OyYKedAnLIwHp-ejruOmQBktz90h96HYAt39tE799kC15ZD7wFAKUU5sghL1hogc6aUYgox2aYUQEpRUo4hKYUKRXJGZo4joCijJROlBNYyMBIAChqDxlitVA4gYMtaGUk-K9HApJ0FYgkHC05GZrSEIqiFmbukTCFMqfMwLeJA_XrPSYbD2HW9cpAyeD9abZ9-9N72dtOU7rhUcfTXL-4uPnq8vd4PI0-PT6bni--_efXXL66UVu-eLmxpTifF0_nRsp12WU8Ku-3G29veZ1_Yoh9DyrkuCuWKdx-dgDaLul5W7YePzz5-cvFksUCCX72-_vUPd9-_vu2CT5nGPlCMQNjtxpNmcj6vfufDJ--cnWZmYFW3VQYuC9dq_O7tm9th7EYipvlsoVAT50VT3-06UVw49-z8pEJdoZvWTeN0W9erLnz1w-23m251iImgP8TocyKaTuuiKY1ShdFoTerDO08exODraXlyPP3Hv_vuTx5fkA_kKc2bv_jiG9K6iyHu_UePz_7ZTz-YGBtCzJwT42UzuZxUy0XTNlWj9eXxTBMIQllY65wx2mqVQaE1wzj-cLfaDcnHfLNL3RBSpvPlJDLa2mSNu67f7IfE7Eq79f6_-_VnPzk9aZppivLd29XNajubNEHJV59dKdRSFvtdv-_GQhsozeKk6nsC4LqtWAgANpuDVmo3jHd9B6iYpbSl0ipFCpGO5hOtlXV6P_rE2VhLqFikcYVCdTSdvvP08dF8Wlts6jp6f9hvT4-OJKef_fjdZ--cffn5t-cXJ2enRw-PpkfTqkQNwjHmMEQfUllapU0MCQDRAFqTiZUx2254_uqqH3I39GisH0dizpTr6YyBAFXy8fTdZ7vNnVa6rOvDtl-cnZEwcM7EmbhdzlEbIrHOUEymdICotDt750m32xqNRVFRzPV8hkS6cGXtBMSPg3UFCgHC0AVVFKCULQvtHCqUxNoZpZFypkyIqJWxrqAccs7GFq7UftgB5Zypmc5FiBlQYOiG6dmxdTjuR6sLpUEIYiRjFaISFmJq2gYQbWEzowY0RS2UjFKosWlKrR0CodK2sKdnx1ZzU7onjy7mrTW-f3R5UhpVO3N5dlqXRV0WTVMpYIM6ZVoftg-PTydNCyKUeD-M62G8vttITr_46Nkf_c5HP350VhpTacVKicg2hO_vbn_z8vl6gNf7Qx8xaQO2AQGrsEbFDIkJUFKmF7fbh2eL05Pp4ZBXm76eFuLsug9dCACKQAS4bEtBvevHe0o1MigGEHnTj0OKpIBQupCbWYs5KwQ0ULRWGTMSFzNnnNt13WQ2GcbkY0TAqnTDfrQKdFOkMQUfJ4sZGj10yRoDxhBnzglEGaXq2QJRmBmJlVWUWXIGkqIqfe-tc1gZgiwsQlRPyjgGQcwQUgq5GziOkFIOUdsSJFMMCoQ5K22BoginGASBSbRzQinFmEO0VuWcIHNZVcQxxISIlFlZl5MXYQ4ZcgZByRS7MaWACmOk-6ZB6ezY7VOiYeiUMqiROA_7LvqxntR9Pxqjy6IAAOuc0RoYqrIgoqEfAVBrJaLKpur7rqrKnKLSdvRBoXJWIaK1mkU4E6IAogIQBTHGzJkyCQgYSl3OWRhYKbPfH4D5sDtUdZFyDMkDKDZGGMahIxE0aK0TorouiCX5IIJ_k_1WRlD6Qx9j0NYQS-ziZDJ5-eLlZN5qyYtJ_aPHDxurEfHV7refPP3EKtRW-RBXu512RTmxq90wacp9H5GRUGLgpihBGaXVrhsOkXa-78YBnWGEXb8zGj9-9GDaVot2su39zb6fNo1PHGOqJk2zaJmD74eZNT9-5zFRNhop502S59s1KrM09vHyqBf5-ptXn339bV3Z3_39T795_tYyvffw4YMdyio8AAEAAElEQVTj9sePzqrCfnW1_xd_-pv_6B_-bDxw3O9utocP3j0_rapa6f_hf_ry5HQSYsoxP3nnDAJ1_Wi1K-uindWg0Vir3_sn__nqurPO-H5nFIFCFrSFGzp698nlo4tZJum7ESgBSA55OIwhpNAHFplOGgDY3N7Vhdt3_uNP3lNiwhhOj-dGmcm0GcagEc5PjkpnZ_Om0ga1vlmvDfJyNgEmztlZ04--LgtBxfdZeKaycchgjGYirdFYrQFDZOtc4bQIUGLrDGUhYX0PKUSwTheFBWat9f34PyVCdZ9aRBFgZqVQUDMziogAKKyqSgBERFvDRCIy-KgNMkpOPPqkjeZ7KRhqJtodemO0tbYbA4DKKQFjNyYGKUoHCKOPLATAzLA-DKwEBEPMqEwIiUFN24aZUKHP2TktDIJiwGTKIycRySxGq5ySBmGlEktIycec7_kRCkWgtGoMMQtuu56YjS4S0XTSjmN8-epKGYuAk-Wsrsvbm7t-GE3lZrNJaVzfDzFmraFuymk7ubm5W0ynk6ZioWbSWmOYuWraOPjtdk8Am-1dW7XbdT-dTQQEgIdunMxmRunT5dHz779rqok2RaYgCMwoTJwpRyprSzFyTtYWTClu1hk4pWjbCfmEBpk1iNKussaWTYMprVer5ekFM01m86qut9vVfHkOBjQqUJooCUOIyVXl4tnFfLII46GuG46RmYCTqwtVlnGMzXSiFIBICgkBtLPhsEellVYibJ0z1gIThDR2Y1G4fnvQiJRzf-hnZyca0VkHzIiitWaWalJqjZu3t6awglg3k_Z0iVrPH54Xzngfy7ZWpSrrev32zvtYlsVPf_fjr7_86ur5y7ubl85o09aLo-OTJ-dKAwitbm_Hvi_qutuvu92WKDMD5VgY2-_G7LlEY7UgcRyGHNi5wkCOwxh8XFycpphRoG1LAdluu7puLt95bAs3W8yiH-_bvSR4_ugClEKU-cl0__rtsN4pq4gSgnAYU38AgHHfKWWAGYRAEiu01hirEEEopzggEYtwHAFYRFBZEQXEVmtBkLRTulSAFLxxBVYF-8whW6uYPHKWHCWzLQqKqWqnPATUiEoRJeUKKCwRCbHEKCTAUi6nOXEIARUYFB8SGi6cPqz2Vru6mUSOu81BFEhiEbW-XlendRjj0EfRsN_2PtsvV3f_969eaOtKZ7PgrKkeH80WrtwPPo1jN0YtrIw5Xkyt0ZUzJmej4McPl0-Wk2VZKJQfhs3Lu-3r1W45n04XtStNWZTLSfvu5cWPPnj0ex-enyzbk-kEgK_3-5c_3JCVkJMF94unJ9a4TRd-8uAyDKEAw0Szpm6KQhuonfv4_OiTy4XfBYj50WKymJSNM99cr_7k66-kNqs42EITJx8JlEG0osy0bueu-OTR-UfvLCdNediNr56vP_nw6fuPLkOi1epwu1k_ujweo__iu-eW4fzs9H_z93_2TtPWBlFYKwUaBpbMvL_bCVrFWRvFoOIY90PMRJsx7nza-Ljqwqub3Zv1vg_56nqXCD1JPSlX--F628-nxQ9vdj9c3f76-7dlZfb74fur1QcPz_x6OGvbwxCbiX1xt90O-5th3GyGauriGO_erNVE5cSA8Gp1qBdFdxiXx5Pn3701VplSK0RXFVqpZVU7gPuOWj_GDNBFrxDGlLshEEDRlCmEr364GkMImZy2bVsfzycx58OhY86TtrUKnMKffvzkdNY21lyv9k8vjmZ1VSisnBGmwfsxxkRMIFkkpITK-BBM4fbDuNkOV6vVm7d3rna72y1ozTm5oshMyOb02eM4HJy1ZdPEsTfWxpCH7WH56EyAFABlMg5zzGEYlFbGubqttS3ikKpJIwyAkDMhAgoCoLNlCrmZLPM4iKBSKERV04oy1WRirIkhVnXhD52kLEpcaUEjAKLWZVULSI5BREcfgJLWxlhDKYlQjqNxFlAgkbY6HPqh74lkf7u3bd3Oq6aq7t6sCqcQQJhQwX0DFbWxShVOA4hCMcYYBcAsIO2krpw6mc1KlH_wR3_r5-8_XlT606fnlTPeh7oslUaFaI2hFAHU6mZ72x8uT47KokBUReW-ff7qeLlYLiaPz47eOTtunLlHWw4pvB3Hv3px8-Jm93rbb_oYxCVl0RlV6BxlGMaQQueHDAIitXMsEDMVFqum6rocM0mht2PcpriLKYEwgmJzupgcQtxJ6nOOiVPKqNWisJvAHechpkMXHr5_urs5WMamKrUCFMjWTOri-7fXRVWxVilnVTgykkmqugz9wJEmbaWdK0p3_WZVtBNdGCLuVuv79SgmASZjSxBBpXJmWxTdMIICZVkbm0JwTsUYBNgYk1NCJRoNaxn7nnwEjkKJmVjknnieUwARQAStWRLcb_ydAwFUQiGklFlAaSvMKUZUEEMomtoP3mpDQve_oyhdVqVxJo6jMOWcjNMh-DhGAFBKnHWMWFSlQjjsdzkTEQtA3ZZVU6dMx6fH3W53f71sKgcEAtT1gx_HtqmK0nk_hnEUhYf9AUAIuCptSrmqy8Ou104HH21ZRD_GGECk96NSehzjbD7pug5FYiawOiUKYSxrl2IgIha2VQmAxHRY70DIlFZZxCxKYVWWiMCKxj743mujjFZZZLfenp6fglIAMpnPReRutV4cLXzMP_3px49Pz_rt9smDs8qZs8nZpCpQYHfoUctqPyBqwCIlOp5PrreHPmYfw64f1_0ugo5AnLGLsdsftHZlXXzyzsOQ0y8ePwbAxhWv3q6_vLpSWuvSvLy6ffzoQUxBo0opBD88nDafvPNo03XTpvnss6--vb6107Yq7LvLRen07fbQB09ZmtJ--vTB_nbzy598-M23Lz59dHq0aDOp__ef_3oEuCjtT5_MQfAvvrr73_7x71lQy3n9-q776T_6sDCm33RH8ymRoMXFfHIYYzubWoW7TaePfvz32-XEWAmZs2BpLRHVVX20nE7r4up62-07AGmnk6oujVPL45kxcHIyf_bw-O5me9gPFDIgWmsoxPVuY41ezKfWwJvru6dPHxRWb_YdI-x3BwRpqzJz_nrdPV3OqrrMIRurYsrOIoAyCFpjYU2hEBGJmbKgiDVaKUSFSqEw3w8vlVKZWGttrGHisnIKlNUGlKac768ATIwIDJIjCbDR-r6YLwoyU1MWCpX3SQBEYFFan8Xn-64scgbQShndDV4AQiKF4GPWAEXpYubBe2t0YlZWKwXK2vEwKmtDpHsVdsgkiCKgQCZ1WzgjqDJlo5VSmEWYxSldFC4ndkYLgkEtzHVVWaUZ0BSOiZrCxcxoMKWEaGNkQBViylkO42C0M9qNMWilGHBMeQheaZUFrLHd0LfT1sfkh4DKdl2nlDhncyarNWgjIsfHs3ZSXr26GYdQFnZ5NLeFvb3dHJ0d3V7f-j6eXBwfnZ5s7lZGu9GPTx4-IuGqcK_fvvUppRzLol6tVwAgCsu2Hfadcy50aXJ2xDketjtjnCnKFAIo7UpXNpUIkHA5m1Am70OOiQHHbhsOQ85y2HXNtJm0x3d3t1XbMtpy2gJwFtDaFk3jsHhyfpFD6DadUSpzDj6hVTlK1c6HvgOAennqrE45ocJ7BZvSqJ0lYiYRYVs4EOaUtMUURhGGnCilftc3y6VyNoTYLGdaqRgzOn18dpriyILDtreufHD6YL-663sfU6qqyWx2ZOrK1s3yaGnKUllb1g1qlXImAc7Cifpdt3n9-rDaxEDMJnY--0EbjQjKqLqoCKCYNvXp1GjrB8-ZRIxtinIxCf2BCFxZKeG2nZ1-8NSvN8jw5Nnjpm4IeHu7Oex3CiULPP_-6uhssdvtd5tOK-hW69wPCkEQxu4Qgo_jYKwFrRAFgLRWRunkA5FM64uUDopEWMLhYJyWnCkFZkYLIMCCylkJHhA5RK1cTtkolWKG44n4rIAxUexHIZJEggCIlAWFAFL00dYFIzABA4i6102KskiZh22HVQHCSFJPK2EZdj2AWFTjfuiG4fLhqWi8u16Xs6kkn2KKIylEp2VSIipz2HfEukxpkPCXv_nhT7948fDBSVkU561-53T-_sliswmZYqJ8PKubyr1_ubxsioujac385jD82fXV1y_WL693k7ZezueHoY99fL3an1TuyaNjneju9q7QZuy69bZLEeq6fvTofD5tnz28eHg8f3853x_85bL9ycWZM-XF6aL3sesOlyfN09P5H56cvF4Pq_3QtJVp3EDpu-vVr19ffXu1soU7vzwb9uH6-nbwafC-cHo6L3___ZPH75yeuNnXr25-eLHqex678NG7lzHkOISD0q4q9sFf3d3ELk1d_X_44z_45MFxRZSId0P6k8-__NffvYrJVLP6QPHLYf_XXzz_8modjbradi_3oxj8f_z5F8TqzX787mYnRt3thlfXq0RoXbk69Jnyzbp_ebVl4fKoGEb6_Ie3H797CahWu-7ZO-dZxGp3ujx6u979P__NX95e7w6dH8aoEHdvd77zfjv6Q-q7UWm1uttfni1Wb7t06K-uVs44FCHCoR-OlzOLgIC1sQD0wclMDPrAXT-wRjByte1vb7r9fshCRAIAhbbHy_m-73792XfttLK6QIlHs_rjZxfH8wlEIla6wnlTIkFb2qrUCuXQh5TypG2ZefRRWzd4v9rur2_W230_ZLp6e3P68HR9u4pjX5RlHEOOnIa4WE6661VbtyIcR58JHr77LiJNFkdOY1G11rnpYjaOHrRGo1xhTVETQM7cLGeT2TJxYErNtKZIOeejJ2eHuzWl0Xdb6wywUI6ucKBMUTbLiwcxBmutQjVdnOc8MEseAzGawhXOotWUojASxclybhRkyb7zk8WSKYJIjjSOoWxbFFZKcspWq9nRDHKCDNbpyXKaYkKFgir6hIiLk0X0wWglIE6784v3tMmck0bQqGez6tnp3PtxPp2jpIfH81rJ5emiMMWkrbRCEDBolAEFCpURhWcnxyigBFHrz7_7Yblc6KpQLJk5kYwxvtkdPn-9en4Yrza-y6yLEgodQZHA8WJSgbq53YHVtsK7Mbzp97dD2CTYJnrbdS83m30_3AtZtTPfvLq72Xd9ln2KEWHbh4fHbRz8XZ-Lpr7d7jLx6uAzYrBmP3hVWg9pN4bdwZ8-XBw2fVvXILwPsVzUh0NflKZdNMwiCgjEh7Q_dNqavh-0yMOLk13f94feViWhypL3tztrFGkBUQaRBXLMgqDNfSIsCXCOUZBTyslHoYT6Hv2XmTCNSVV2PBw4JgWsKAmLsAiiNgYw55SUFlCoNFCIWmuSe1UpacTo_X39zxQFAovI2PVodE5knRPgFFhQx-DrphGDqRsoZY5RGZXGkbOgUsw0DqOtC1AqDkOKKcUYY8w5E_Hp2cnYj2lMVVshKGN08gFAitoOo_d-0MqMfX_oOlsUymDw3ho1hiiCk3aSmAqtQOvS2XFMQhRz1kYbY3xKCJAThZz7gwcFpnIxkCJWKCml0UcBREClDQuPYxBKy8WCOTtljpZnAJKFAbLvYtqNhVHaGCJhyovj5TAMzNDOJ8y8ulu7qkClzs-Pm7pATI_PT5eTsi3spKpLZ4mJtGRiyjKfTrp-OF8s3t7u7w4Hn-TQDYAaUbQCo7UoUVoVxu2H7tnTy4KoVWbalGDt__jrr1e7wRgzW863Q__w5Hgch67v7m7XeRz-s7_7Byf1pC3Mr796YQqTEU9Pz_7811_-81_-zIgSjWBtzDKx-hd_8JMStR_j7e7lu7Pp--8-ylH9X_5v_8N3b9YlFp--d7JPytry8nw27vqyxK3PV9cHV9j1231hzM9-_un-0OcYJ9O2KC1FSp5uVjv9yR__L5tpZa26ux2MxaPTBUd1cjSrFW63_b7v55MajNbWaQVt2xwv5hoYM-23Y1HraVUXpTu5mF8sZjd3u2lTjznttjsfwvFyvtvuy8I1ValARp-1UdaZeVO_s5hnImBBhLatEECBYpL9MDijRSTmTAzOGQVKKaU1GqVEQFhCzsJcNYVSyCKIAMKoMBP7EBNl64zVGhiIyFqTMxnj_mbGr-53A4AIAphyViio1X3neExEnBOBslqhFlSCzFlIFDGPQwAAa6wgpkzCjAJyz_0ERIVj3yuFxEhMdemIIRFzYmcMIez70eesrEKWxDSrysRy2I-9D4JAmVPOxtrRB0AMMcecUOtMCZTadqNzBlly4pRJK-VjSkmSSN3UKcuuGzhlUxQ-ZQK21lprjo6Xb16_WR6d-DgoZUGBH0dtDCgoy8IZTcSAqnIWQVY3B0A1n0_Lqui7bn271pVDYw6bw9n5WaYkDEqjrapu1xV1u7lbaaMn0xaAtquddTaGRIm0s1XrfOeN1eWkDsMgAFUzUw4RuGoaIEpjZJH6_Igi5UjJp6Isyrrtx_Hh-x8JU9U0rlBHx0fR92VVGqe79UZpfXRy6vt-eXrClNNwqBbLFDmREsZm2Wqj8xBCDraqNSgm4RxmpwsiESZQJnkqmppSjj46bZQy3kdUxipJIScficjZIoy9c8X2bovagFGr19euLEHJsDkISMxsbFHUDpnW67e2qdvlomyro9Nj4xSgLM7mrjSYeXv3JqbAiKq0oT_49SaFDjlxziSYc5ZEKXpkFUMSwqZpc0pDlyYnLeY0HAbllKmM0VYBd3eHomlmZ4uj85P19U2OESn3Pr3z8QfLo9PV9e3V81eShjD4_dA5q88ennb7bUqpcLosdOiG8XAAgDSMwDHs90obDYjCklPyqSwrFKEQC6fjuCrKmoiUVXHotVacPDJLJgTRQshMlJRWwoTaSCZEUcYwkapKHiJ7r7XmNAIobVBSImBTtTT0kjMYhZK1VcxKoygEAaULiyxlU4jkaj7ptmsRiWNuLluJgQZSWhvt-q7f7PZpjKAVEVsNxJkCN00tPgJqZTCmLKR2hz4JWMc__HD1P3325a_216tt_87xUhf24XHzwfnR-XFrNRRWoYK7Q__lm-tfvXjz4m5TiCtAQxZFUGp9cbp89vjs48vl7757En3QnKd1laJvVRmA36zWI7Pvw8PFYlqYOqVEaTlt2rokkeNZZTQ8Plk8OV-USu8O-99c3UTOTVM-77Y3m_2r21VHUjRVM2ttVe57Pwz-5Gh-dtw-PZ_NSmwbmxJ8__3q-ZtrQprNptPKffzk9D_6-ZOYbebMMf7my28LzY8uHvzjn3_4Dz9-FwWUxpBlJP9__Xe__vbt7uk77_7V9y__1Z9_9v_7i29---WLH95sxiH--uX1XZdfrDZfX69Xb9chw80wbIfhy-9evbq6I6EEwkYfDsOzd87e3Ow2m02v5ZtvX0MzefLg9Prm9n4SMdH42bdXzenkX3_7_N__9ZdhiDHy2HfVpJJIGtCiKidOI9nCCCQQLMsiD54Vn53OD32nrMlZcuZ-DCFIH9NNN3xxs_pite22MeQ4jCGTpCzztloeV0QCoPd9HyLNZpN97LfbQ3u02O07P4QYw6OLxXFbWlDOGWWwqmohqJxB4Jx4CGnbj5NpM_ReAJJgN_S7bRdScEW1Wt1dXV9PZ9NuHPwhSjH55__07_7Bzz79w198dHw0_-aLF9YqglxV1WQxf-fTD948fxXG2C6bPIToc7OYIeT58SkRlFUZAqtCte0UROpJxZJBKS1QVcV48FVTFbY4bLZaQc4cYzKlU6Bz5uOHT7XWMeUcadzv2-kkpywiVdugBiGEJIVz7D3LvZbeKo3t8SmlgApZEiqjjDXWVHWdYl-2rT8c6kkjSlMIrrDOFSGTdlYZKyD1ZJJ8dlUNCo8vznPwZePqukpxP5k0lw8eTac1MBzNF7_85d_-9P0nmIcY4nvn7QePH0yaqjRWGx28d84ZpynlmCn42LQVMgBi5Dz4CBpCVmOiqKRj-fXr2-vB3458YJ6eLg5EYLUzEGMafdz148ViMgGsa3cTw8vDcNUHMtUmZQ_4er8fmcDgnoIQdEmGmN7sD27R3HZd3TYJYB3CQHG7H989PnnbdYzSC5ezUhu0Go1F3Vo2qp3U2_6Qskl-BAHTFJ-_vD45mQaUsi4taqWQEQNRDIkAwEAYMhPbokkxeU9HD44zp_XNBpnbozoMPgzBWlfVTXfoVGFAAAFUafyhM6Wrm4J9qq22Vo19TzFwAlU4lJyDF0nAAizAQJG01qa0zKy0Ip-VRgkhp6iVtkaLCEUqC2fLEhgQlClsJsopmdKhAooeGWKMymimDIiojLBwzEAkiRVAitEVRfRUVg5Ri2DbtAgwdIeycgiMKCQkJGVh-26wSnWHg7GGU-KcnDHjEIlZSATIe79YzrSzlHJ_6ECkLItm0mQ_xhCI8-3dXdO2MQSDMvoxxAgACjAGP1-0ox_L0jFnyhlIwnAoCwdKp5iKwuz3PQmBVoAyWy63t3eIuNsMh65nkEyhu-tlSAZZIaLWQkQ5N3UVUm6nk5Mnp4dNF8L49N2nh-32sNpeLObTxj06PfXd_mw5LaxRSlKOAHrX9YB6UdrOZ0vyxdubu24gVG9uVxk45PHB4jRm4RhB9G53-Nkn7zxp2z__t79678E5CX7z8oZVdXo5LzT-5WdfNa4uFO723ZOHFyeLRvr4D37vQ0Wy2fXvPbswtvj88-ff3KxfrId__LP3r-52Xzx_c32374f-yaMH29vbxlZXr1YfP7r8-U_er537159__6u71--_c_mPf_r08vJ4G_Wf_urzadOg0pucf_v67s__6ss3d7dXVzes4WR5FEPuYtBKO4VFYWPMu8NBf_Cf_fM4hrN5u7yYhZAU6SePjyxJUbjCYZbsrF4uF1qrs6NZqXB1vZlPm7PlYlpVrTVH89Y5ZbQehhERl4vZs8eX06rQgMJsCl06t5hNDof-aNZaYyjLpCrqpuDEqFVZuvEw5kRK6zEGHwkQZtPGJ24qQySI4qwVBspknWWSsrIIiCI5E4NwzsoYQXRGA0BZOBQ0SiEqELRGo1b3CFtEFVOy1gBDJu7HwVqbsyAggCDqTCkmGUNkAUFUSnOmYfDGWW30EDIKaKNBQGstwjGxD9FYkxO1bc0EmSCxZOLMEmIkgMN-yAA-ZkalELVBumfpKd31vUIEhbawpTY-0Rji_ff3gx_HJAjE98cjPHT96OMYclGXTDkS5yw5kwbVp7Ta7GbTVkD5HPv9IMR9P3b7PSp16HZ11ShlRUQQjNZ5TPt9VzW1NkWWBCzGuOmimc5qP45j3x9NFzHnvk8--tPLkzCMKYnvu9lySUTtpE1hdE43TdMf-v1uaGfzrt9NlvNxHI1zqQuP3v3w9uqKhVmxFh3HDlHZuurWe-OcEKG2-RBAYT2fucpVs5kInF5eMpMpqj_4_d97fXt7d7u2rnAKlFLNbJp88mOnjJ0fzzOimOLs8uxutZ4up6hk2PftfNqczbY3B2aiFEujQMHYjfVsSUR1M3F1Q3APsEFXFgBoC9ueLHKMaLQpHCUyxsbERV23s4Ufx6ZtiqYAYFsX2haZ2djCWrc8OUvZl5Opq8vCunoyBWAyuL2529y8fvX5Z9vrG7_bj7tu2HXDaoMcko8CEsY4-jyZz9EoUSqFNDk-Ork8d5PaqpxCfvqjdxpjx_XBKosWnHVxCOCwmjT1cgaZdne7lLK2Jid670fv28K-_P7_T9N_9WzTZmma0FrrcmFv-9jXfz6_L21lZvmurjZT0w7aCIYZjRoJRoIdhAb2AIn_ggR7IyQGmA2Y6e7ppouqrsqsrLSft6973G3DXX6x8RT_IDYiQhHXeZ7H8fVhu-XgdKEYoaqMyNn6qZ3NmNFNdrjbpBghxZwCYaYUEaGoKoTshhFSUkYBCkTI8W9EAffjwunQYYhaK04RcsIUgFkKnXPKDPcYO7jX4DGAEBw9lQ36xPaA3iMwAKh2AcHnKTFk09QQfLIWfUwhMBFozDGjguQ8Mqec4uR1XZIQ9noDwGk7Cl2kYJHQO5diMoU2jbHdYLvBOu9DLtu1H3tE3O22KeLibK60GHu3v-rf-v139529uxuqtvr0869_-eXNd956oAotgI0Q80Iu66Zgut04gUpLEQMuC9025emsOD1pBcc4OQSsteSQjsOktM6c-8ltvb9cth-88-TRonn74nQ9qwzzvK0UoZYkiUIKKfPonQBSKJu6mFXtF1fbfup3kyu1KdoiJu5t8D7vx1FXcgpuvWhOV213GIfDWBWz280wWWiK0khxfj6_XLRvLmZJyT__8Kvb7d5Hf1aq_-Rv_84fvPfmb12sNWEa46v94XaKf_rTX_-bn37x8mp7O7if_uyjIYaDd91hsDGSVhHo6uboprg_Bmu9tfDt333y5fO7ze1wfbcdbHy1ObRt_cu__vL7P_zW9Wh_8ssv60KsFs2__ovPns1nu_3h4bPT42SDTc9f3G2m4cPffP3iq82x66VEqTDkiAq6_bjf9s28STw1s6rv7PXtZraeffP5q_MHp97GGMMw9MPBi0o4P0qA3eGYOM2bulEi9nbWqKJRUqrIfLvpJ-vbomREWQhGKZTpO_vi1aZtZ0JwKeU0TRdnJyLap5eXhdIoCJgBQAghCHxIPmYfY1UaZBBALHCw1oU0TZOSerDT6fnZL3_zze_83nd__J23fvju07_342-tC90WBbD-9a8_GafRR290kZiXp-sXn38V-0lk3l3tF-fLvu_y6MpaCyGbslRaLk9PhC6GYbx8-ODZowdkhKmqYz_UTcM5Xzy5GLcHEKKqa1mYBDnFDFI2y6VQpmlmzMH2B0mMzMEPPngksKMTSmlTCko5JFkUzWLGKUOm7MP87NQOE0pJRDmn1Xrdj4PSZSGKxfxkGAZhdM45BpaF8ZNzo5WKyrrhxEZrEKClzMGZQglBUpAxkgSl6Ast33nvjbY1r1-9Wi_bP_rhe-89Oz1tm3ldCgBJEhikkkJiDMH7iIgMVJXFNPrjZI823Vj3erTclh--urnt7c3kdz540p6zbCoiBsIHZw0H9-rm6Nl_Gg5vLOZ3B_tqHL_Yd7sInY8WwAL3zpGWvfem0PO6-ODRiQDYdeM-x5t9B1qGDErgzTiGmAPimD0pSiQY-fHFuhaYOSdG64MxOiOzMcduyClzhsVJ3e-PhQYqtFDi5HSGhTwcu36YYswohZ9SzinFhIJ8tKpSQCJlLrR0w-CGkZBzTkopUZDSuht6oU1lCs7Zx0iSbD9ADALBp8SCGFlqlb2HnIWWYUxVWyVkFFJVBgRxzjmzKkzKGYEZOKUEGYQyAFRWDeQQBiskAQBzBqSUEuQMgIKAYwZCFFJqQ0pABill8gESC4lIPLkklRRaoxAk1eJ0qRQZY5wLbpzqui7r2WG7kYKccww8W6-cndw05ZxzToIIkIuinKZRSrFYrWzfa6n6oddCIUL0gSN3h04pHYOt6so5G3yKOdeLkkgYY1LwAmUIKSVKMXDKXddLZZx3QsicMhAGH8qq5sxhCgKTn0ahpHUTIxSVnq-KzfU-QRaCGZIbnShkdL6sG5SibKvZrO03h_12_8bTB0N_jDnbcVwuVsfd_nI1f3QyawolgRBBIlrvbYy1Kfad9z73OX_y-up2s8tExhihRNePdV00RRlc-p3vPj01xbqqP3_--lvfeky6fHm7P45pGIbI8dgdP_rq6tHZ_P133ySQL169aJblf_ydt5ui2e4OpCRkvj6Mf_Hp88PY_Yu_-3veAZTF4OJk7dn5uVTyp7_8_Onjk_efrp88OKuV-bd__pv_5s9-9Y_-4EcLjs2s2R2n_-q__cshJ1XPtoP79z_7OJI6TtOYw7vvvxnd2O93Dx4_2Ow7H-LFg_V-03dHa50Vp9_724fbG5eQWJa1iimXJDabHpEY41uPLnabURLJzJDSctZopNP1_OmDNaQ8DkNZmmPn33hwpgshQE7DkTk-Pl05n0_PZqfz2bKpXl_dWutmy1qSkFJqoziz5ygFKaUEYtMUMbP3qagNIipCTQIAJOG9Seve3UuIJAgAMAEQSimd9STQOS9IJob7u0QAEENKSUlKnKQUCH-DEFZSCkkpZSHRFGaYvBAE90ZfYOsjIjHT5D1n0FJN3gEDIGWiGCIJwZCt9TEmH2JRaq10ZgTEfpyUkt0YnI8xRet8WRU-JueS96GsixQyIOUcCbA0elZVRmlJlJAmO4XMKaYILDSFlIWUZWmYOcZ4TybNAkNInLDrRueD1MbnUJQagHyMdVUy5BRjiHmyvp3XmRmFcM6FEEmQddE6X5oyxWh9mC9Ojvut0ro_HkkIIXScJlPqYP3Q2QhZCMpIIHA89tM4zWZtiEGbAhCkkMHZ-XLJCF03FLOSBNnJslSISDkfDnvnxvpk5kYnBEHORBQnT4S6rZJPUghMUWL24wQpnj55NowDSnN7d1c3bXuy2O4OWpsvP_-Nzl13tGePHwBSvV6cnK4vn130djo7P5s3ZYEiyUhK-ymUVb3b9yTF7OzU7XoigYKTtaow_f5AQvnoTV0IKVHKcrZOnOtmMU1D8rloGu-S0oU2pSlNs14HHzhlbQo7TUqVT7_7weST0Hrq-2mcylL7MILQKGRVNiDIjsPzD3-9_-prf-xjN7DLdVFyTnFyHEajwPX-8oPvLC8eCaOMImtdaarH77x5-uQSGIdD323uvAveZsy52x1DSt1xUGXFjHplzKwedjbHmEPYb_amrgghAybG4XC8vb0O1q0fPJ66vfeJBNy-2rbLFTK7sdtd3-Xoco7OjSkGBGIAKVTOAMBuHBATMpqm8XYMoxeFZMi2n5go-0kIiMEjQk4RUwIAIMrAKCTkCDllgPuNDRFmACQDgjhFzIA53V-mVC2EMafEKbIShJSmSSlKMQASTxNnBkK9Mtl5IvL91CxPCJi9g-gwc_TROUcSATnnHEOSUiuiaRgIcxz3UsBxu9Wl2b_aq1qZElYSt3ebLz55PYQ0jNPxuu8Hf9cd_-KL6y-vjmfLhSIFIEkowXi-KN--XJ_M6lVTPTtfzevi4eXq8nSmpT5ftyezBlz46Grz3WdPzlfL0_nsjbP15WKWcy61rIxuK1MoNBIFRCEkIZBSksQYwno-04p8yjEkFHQ-XzS6uNnuyqq4uztOPs0qowgXdaGRDrtxxtjv9hgcunw8jH70y7IsSFfBvbmoFlr99JcfffbqptLw5sXqn_3uj7738FwLIoTMcRfdf_WnP__4m9fr1frk4mz2rH657z759HnX9aBx7KddNwqp-95Pyc1P6ziFcXCL01JI-eHzV7urY9dPo3X7rlONudlu97ebFCMS_ODdp2GMQYHO4-1mZ0PqA__qZx9uNgcu1PXVdeTABXGEYH1ZKTuE7YsNendxceb60U2p29s3vv_o-HqUQq4fLt0wjtvd_vbgXb5843La97urXdFUp6drZAohp8yD88SCIqSExmhViHlddp11IahSH49TpQkJcuTj0EtFRV00dVFrcXm6bkolgUBASCnEiAJTTNYFm5LWqu-sVOrQ9zGDDfF6u10vl86HzPnQH__kj3_0cD0vUNSFSZmFkFMMr4_dT__qN1QplPrudpdDHPpu6kY7JRJCSklKEAhrrR3zft8t5rPMVM6qsmr7wwiCE0BhyphTVZVFUSKHbtuZugaAaXJSkdQGmJXRQFS3DUrYbzcSKcVUNW1Rmvn5w6k_IkqOHlNMMRhlRuty5sysy5KZ7xXbAmk6dOWs7YaekaOd3OGQYJzXs8Ouq4oiuDBftlVllNBSF3VdG60evHVJiZVW0buTk9U0TLUxdaFX88WsLC7PT9qyWM3LJ2enWkZ29mTWLNtGQBYClZKZOecUUpwmd7U_MqMuTD-4cfKqLdt18ddf3UKhX_V2N0xT5iSwt74bRut8jHGKOdrUHcfuMJWV0fP6spy93vabvr8JbiMiKO0YkqCMNA4jIQkSq2XdBVEAGKZkxO3ksJSgRWCUpbnejUP2baGnwQ0Zj93UzNtj50qtXEo-J9CSBCfEdl3vNuM4TSGkAJxiPD1fjS6VTekTCw1yroYxMABq6g69MqVW6Ppj8FEX5d2rHSFoqQ-brZQSONljJ41Cpb1PbV3cfvNFUbWqNMbo7nBAzMH6nFKEpGdVCiFZl72LMWaBJCVzAhIhBKkE55RTiCFkyAAIxMlHFIBEkBkFJe-IKCXOMSGhqQsikXIGzimEGPw96d-UTYyxmrXBOSlFjjlFJiIiycBSK6mkLgwnns9nhMRCBOvsNPrJem8hRyUFCYH4Nxt0IkFExmhttFLGOccAJEhiRpLWjnXTHvb7zDxbzsahywiQ2VsvhbZ-kkL242S06Q4D5CCVTMGroow5c_RC6ZQzMutS55xIimnoQcicHDJ6P-WUhVQP3nzSd0OhjR8scTG6iCmyTXY81O1ivzsWZSkrQ0KsV6ckxeb6ttBquT5B4NOLy0JENxzWy_qt89V61rR1UQgmCTGGyaWjs4MNu-NR6uLODqPzZKpj18_beT8Oy3bRVnXF8t0nDxjpZ5895-zefHgxevrZh58enfc-TNFenq42234-a3_vB-_v7_bfvHp11x_-yffef3BykkL6_HpzdrbY2fTVze2jNx_KhE9PVjmnYzf-6suvL87XEMPt7e1_-k_-6HzZQE6lEV-9uvr__PTzh29enp-2l8vFr798yUr95LMXi0fnL7tJzcqjG19fbQ7ToKry448-62-3n3_x4u__R783Q7UdhsklH9Nmt12eLsSDv_0PE8vVfFYZiYJyzIS8WC-O-8O0D8vlYnna5hBsPykpuq7_4J1nhUJCms9qXemM8PhsloD3-65pKu9ciJkzrFfN6aK923RamS9e3pyt2uCTNibEgESC4fXVtjKKmaWSMcZxcDnn5awhAGRQSmqpuuOUMQMCCoGMwIiMUpA0OuecQyRBQpLWijkbLVNMRGi0zHxv_eKUEinJDJKIEQEopcTMRPe0H0lCIAAgdp1VWkZGFzwJJYmUEcfjqKTkzN7FzJxSFlKlDISQcoopWRsZUREkwL6bWAhjJBIZU_ngAUFJFErbKTACCuy7KQMgCBZ0_988a8zQRylFyDGlmP7m7wYlERE5F5WUROhc9CFlzKZUUhtGdC4UurLRp5ATwzjam5sDGWXKwoeAQAmg63tmHrqxO3SL1SqkIJSQ2jx_-c1iNhuGvp7NGHjWtgYBlAFkEGSd9SGklIq6RpJuGpO3Uz8BYlk30XvIpAstlOx3nSpNt--a2WKa-rKq7DRKradhMkUVJhutTw4JIKUUQvKTbxaL5EIMCTMD5JzS5vZmdrquymK2Xu32XdM27Xw2Ta6qa1Eu0-RTSvP1chqHrusFipyAMrz97FGOKTJMg9WFIU66kM5FfxzXT8_sdptsiImlkASAOZFAHzJARga8x24TGVOSVNM4Fk3JxLosYopEpEwpC9XO1yiwXc9ur26evv3OfnN3ennZLOamLJtZzRK74_Hm1fPudrN__Qq91wRFu2bXKaMRdHIDCRGsjZMNIWROUvByNW-Xy7qsEIVS4vbr1313MFqOx938wdny4jJM_XTo0QhVqgwxHPscSNambCrbd92xN1VRzqv9ZjdbzJcXp313nLqOM-Q8VetZHI9x9CTIlOpivX7-zVfRhaZpUnSUstISUgROUmkhhLcDxIQASJK0dP14L0PKnCABYYIUU4yIiCkQIsestMKUpSlyCiQExyRQECoiAmChBKAEYExe5gzBEaccYk4-53tcdBZCcIqUEyQGZqkwMQIDcI4HyzHmwDi5GCEDunFUSifnmSm4ESRQRmD2k0shlI0RRCGGbKPQRJ7Hbqpn5ebVAcZclnWGAIIw5LOLppBytx184O_8_gfb13effnNz9PHRxVyBAIhFqScflBQntdGCrPWV0SFEhdQ2NafYFuqdx-eYsiLkkJQUhmA5n9dSiZwLpbKPwOnl3fb6MACST9BZG6y73hxf3hzKqgCgQpFScl6ai-XyZN6MyYfsA_M0hafrxawqf-_tN9-Yryrg9x6e_eCNyw8erf_Rj9_77bcvHy3NDz54fDmrfvNy-8bTk3_-h9_6nbefvLWYyxRGm47Of_j69uefv_roavvly83f_1s_uDu4r7653nj3yvrbb26I09XnN2mwmdD1A6AUJONg3baTgtGJm5eHYzdM3TQMNrkwdX6Kceo9Z3F6NjOm3gz-2B9eHY6ffn6XhVq8_fizn38MKVs7XX36ShWSNW1vxlKppjIm5lmt33j7USF19G51tlS1nkJ0NqhSLU-bBGp73T1451l7Ui-Wq-sXdzFEVRZAmEJqV-Xy4WL76qClSJBEJudCSlmQYkBk9pZdZ3MGJWk_DmVbMsBitfJGzrSeV_rR2aI1JQFkTsGHfpxSYknkUlRKuhByTNYHqVRKvD908_kcgWtTnJ6tnp2fL-fNoq78ZI9dXyi9GabDaD_85GtdVUKJsp4lxLPz1X7bAdPyfLVYL9w0KiNzBkFIkgDSNE455_5oi7J4-PgyuUkIPHZDVVeU0th3Z2eroqgjeKkVCiZSAHj-5C1MTpdVjsE6n70vtZo9vEAfq7o63N4m5-t5I5BjBqnMNIyyrmIIRT2DnGRRhGmKLpw8OK8WTYxhfnnu-k4rycTJ0xRCOaud9bOThe1HJipKFb2HHBdNAzG98fSyUMIHNlqdnZ0uarM-XQLEZlYaLSpDDy9PS5VqhT96941FW2milJKQAgEBUggxpOxTWi2WstB323704eowvBzHn370eu9c5_K2G6cQLx-fl7Wyk5u1hSjow1d3v_vGgwCkEctClQKONjjvHi9qU5VIojv6KcUMYF3wwUuBnxy3SbJ1UIssScyNOvp8CCFQDplBq6MNHtKDtlw21RijQ9aVSJBJiLpUR2v74EFi79JucKIWXUw2BDeMsjHHXU-VnL17Qd10edLuNn0zK15f7VPOKeI4-ZxyTsluj_Y4rs5b56FsTHDTuD_mlFEApJRiBmRVGObcNiuOHBMzZ6GIY5JaIuScwY8eJUpJHDMI4sxaS07A7CF5SYgAOTHdd5VjJGBIGSIDoCBFSDHGnBIScoyMVLWNn6wuDHKKk0shErJQiqTUqsghpJB88MaUOUcUKKRgIAbOjN75sipQoFKaUbppVEYj5qnrmVNwoZnNc0xCCKlE2zR2HOuqhpzrqgoxAOezk2UIWRK5lN3khcAUgh1HQJj6SRtdlUYQCKXo_oq9IwQE9t4b0xy6HYHIMfjghBAhxLaqtpt9UWpZKDdZSDyMoxZaKQohAKdm0Y7Hrq40IEgCozQJ8AGrWV2tF6auSAgl5bDfeWulpPXFyc3rF1U9c1P_nd__vnbp8nzxw--8YzALZKnUOE5Xt52QoiyNYNFHN_jw1d1tzLwfOlLi6Fz0_snJ-vJs9XCxoIh_9rNfa-CT09X6dP3Nq5cff31rjFmfnxgFv_jVZ8u6-od_9P2GzaffvDqI8Q_fe-e75-dIFHO-PRx8gt5zCGlWFad1UQkhTfPvfvKLH37vbQ75bnP4ne-8BUS3L69CiI8vzjY-oyn_0d_6YL8PxzH_-cfPXYZPrraPls3kU3u22HXd9fNrsZZ3t3dhmJK3UvGvP_z693_nu7eb_eVq6VI8WdfTMInv_IN_TqQRaNYUkYOWkgg5gxGoS4IcgagpzHJeV4KIQGCWzLOmnNVFCn5Zl5WRt1f7pjY5pbPT5aKtUxSX69b71LTl_tg9PF3M2pqZTxbN3aYrCIQUSNjc94wJj910GG1Zqck5RDFYXxeGmY1RRVkMo1eCUFCOjIQIQAI5gxQCEELMWkuByMyYQQqhlbA-SklEyHDPjceUM3MmQSSkc5EQ79k-KWUtxeiiKbSLkUjmDDFGEhRjBgQSKIWKjCmzjwEwSSliQhdiBtwdJkaMGVLi4ziljCEFpVXMKUb2ISojY-SMIJAAc6GVMmazP0wuAQqlcHe0CTiGnFIuK4MM3dEC4mStC0Eb430QglyIjGKYQlOV1kdOSSk9jCOhSDkjsg2JkFLOzHB7c-uDTzHPV6vjbhdzMlXlvTdlGRPvj9352SkAtrPZ1A9CinEcpDZSqm4chJSb61smwUAhhowsGLTW8-XSWV82tdDYlCVwLox2PoBAIhq6Y1W0IYRq0Rhl2Ac_Te446UI381qIex-KlEZP250kCQApxvZ0wZw5JXfY28kWs7Iui8n74_7YtPPgQxzd-z_6tj0Mx_1hvVohRCQUjMu6HaZh0apVUd9cHwSmlLPWBSl1t90yK0ZcnJ8RYUpR6SLFwDlxzt1mJ42K0RtTxRxni5lUWhdKGxND8M73m44k5BgxQdft7sdGTdvcXt3qojhu9px5-_q177r99VV3e8vOQXApeEgxhRTRx6mPIUD2RJgzi7Iys7Y5Oe2PvRs9Ag3WcQhKiVdfvRj2x3F7cHZUqgg2H-62wToAaE-X_XYfhsBI7XrleutGC1ImpkLLMHSmaC4uL0OIN6-uYohEiWMed13wjnNGgcrIcXLT8QAZiJNkkEKlMEUbhCkRKSdvh14RmbrizKRVigEZ8jQhphyDVjqllFOQRDkEAAAEzMwAOUehTegngQTMzEAEnHIK0TTzlAMkJwgxAiLmKaEUKIUkkXNmIGIQnJBzjC6NTlZNThGAEDJPPSIWWkc3mUUdpjE5x5GlFEbK1DvSpIwiIGSILqCRgoRQyg5OP_12GfswTu2s9YCoZhHjzfPr9Wq2uR4fffCGPjNuN15_9crUEDN9_OWLP_viWpWw1sog9iFpkj6kUgsPnJ0f-_H2dhcnO_pYao2UFZkMGHwEwrI0GpEZOKccQ4jxN9cvUdenbdWUFRDlDC7n_dAfe3sYpky0348MSUrUSkgjLtvmrKqeLuerRi3L4tG8XpSS2D04bff7Y1OaxWIWcnp9t2vmq683xxeH4fzy9M3zE8G42dljPyWpf725-qsXrx-enTy6uFgsZrcv74qy_PTl7ev98c_-_BcvPn1VlNCeLFaPT8_fOnt4eSalFExtZfrXO0xYt_X-0L3edlHGOEZMyDlJ4pMHc2BuC71ezucPTn7-8092h7vu6FiIyJ7jFJw77Ptn3_vA9l1pyn5n63UjBSoy5fxksZ4nIV6-2gshWZMdw66LbVO_-dbpsJuSTYsHyxe_-dI0beK0nq8QYwpOoKiNpow8xcmFojVKSCmQErWz8uTxshtGqZUfnZD57NEKJXifACHGgM5zN-YwVZDfenyWYpQE4zgCcYiMmK2PMcUEcLPdF7qegvchARIQTOMolVzMWwDWWtWFcTbc3u2NMUqafrS7cQoxh5AHn4Hy5dnJL3_2q_OHD1JmZaTzIfuQci6bcrIjxESo-sMImIUSpPU4dk-fPPIh2eBKLUtTnp-fnp-d745HFIKEYmYhxGw-G7t98AERFuvTzfXr7P1oj7H3mXPKIYXAMeSQ0BjOKAQiMhHdm17s0DfLOXKSWqMSVdP4kCBxdlErNHULSqpSm8LoQlfLtmqLdrHgFJYni7oshQCIjISreVMWxRTCxcVi3hQnqzn6eHa6XNV6Vpq5RA342--_3VRaQJZKaK1SToCcOAfgr6-3r7bjall3o_vo81szqzcu3EX_8atrVmQFFfNa1RXGvN0Oykhm2HbTty5mKsS73t5au_PuxjuXwif72PmMwKpQbV1MIStFF4vZo7bUQqzrSqXQTw5AbFzURbXrBkDYDV5KsFOyEderdj2vh84Ws4KBB-ttSlVZLpQkiVPwfQhjypFwdwxmVYaY-l2XU9ZGFG2ZHTUa27IMg90P45CyDyH4mCGlnFDiuNmLogQWIMTkXHd3QIHJ22BHAbmZzW5e3LWLmQBNSnhrtdYgOOXsJyeJOCWhFBACcMwIjIJIaJV9yCGxdRCidy4lzjlrJQEyp5Scl0ojAiaQSqYUODIicGYSIKQKLgAwp8Tep9HmlACRmYU0bnTNrClnTfIRgAkxJdBGoaCy1ilGqdS9-BSlGMfBj5O3AzCbygQf29lMSjkcez8NOcTucCyrUlCeNXVmHscJcg6J72439yeu2ujNy1dVUy4Wy91mR5yYs1RSGR2s8_f7Cc7tYiZQAOPoxpxyTiAk1bOagQURczRGA2GIwU02WCdJ-GiJ9NBPbdskm8exny1mdrJ1XQbnUOuyLU1R1MvWeyuEHPuOEZrZ7PLRg_nJuik1pNBUusC8ropHZ-fPHpx8-PFfvvPsDanlq5sdKDmmPDp_13XHmDZd9_x6Mxy7ojJ2Cr_3zne3Q_itNx_UTfnq9ur51c3lg9W33nrmfeiG8RefvnBTfPODpxrcJ5-9zFJ-6903KefNcAStbu7u_os__gPKwjl_2w-l0UaXo_XHySKnFnG9Wmx3h6-_uWobfRzCH3733dls5nq7PfaPL86Off_vfv1cF3oYp8nBn_71Z47h5J3Zv_qzX5zPF288e-uzr76-er2x7LnAMA2-G-M4SCUKFPOLs1k7v9tsE_P11R0XSnzw9_8ZC1EZmWPWRpdGxQgn520KPHTdatkWUiTv6kKXlRqG8fGDdVPJttQKlZK0u9sWhZrP6u22Oz2Zb3dd9vbh-UIKGoM1UlWl6sfxZNEiyqubLSIvF7P9dn95dhJzHsa-qapMXBnSwqTMSikhEQGAOXFGAK1kCJ6QiEAKAQycWSiRMzBjUWiBmEKWUgopJREDivuye8zAWSqZ8r3TMOXMIbFUlGLKAClmH5P1ngEQiYSYnCtLM9lw72NPKSmlc4oZeHfshnGKMSemcXJ1VWbAhDnF5MZQtsbFcJimoihDiM5Fo2VMeRx8N7oshItxHHyhVc6YUfgYvA1IQisV77M6ZBujt6kwihCci0gEnBlomJzLGRHvKQTBByI5Ti4BCJAuhK63SICIxqgYIwBPk8sxDcOQcpZK5sRlVQ6TLYzKkDim-xRvfbI6Hg6EZCe3mC9SCuPQtW1NUr58eUVS3nx9W1VGSUIikmLoO61NcF4XxlsPCCGEnJMdPGOSStneYc4khS6K5mx92OxMpcuqSIGbs3m-B4kJFJJUIcKUy9lC64JjzCHYrh8nVyxbURTD8ViX5XK9SiGIsoouvry700JF5ELpFMPd7fb51aGuC1PJqq22m43nPAxjYljMFkSY3SikAMh1U4cQUoxS6WY-i5NNLhJxCinGZKoSGQHRFFVRlPOT9fZqC5iBuTC6O-x3V3cxRUQ63NwS5Gm_SdOQbA_eKQJTF5AShCgQcwwEmKLn5AQiCyWLQkrjEvddd3Jypo3qD4f99evD1SYLOru4QBJVaXIEVZTtejF2vZJohyE4i0KapmnPTobuwN7lDNIoo1U9LyHigzff0K25-uqlEpiiA0RgRvZumIRWmJMuCj9a5CRyyt4TUoqenUetSWsgDuPAMeuq9JMXUgYXcmIizHaCGJgBEYWi4BzmzDlnZEQBKKLvAAQDkiTIMSeWpQFmSEEQxhxRmuwCBy9yIkBRV5yCMMb5gFoyZK11jilDIoFK6ThZIIIcwTqoSmE9RwYIoqg4pWSt0gXEXKu5LnVyFkJKMQmhGBJkEkZmb42mcP2ibsrROecjCQB0OaeiVdevXulav_r86q3LZRn5_OnT4c4WVfl8cxCcvtxsfvqbV3_-_Lqq1GGYalUUhY6Jm6bWZdFWpSZxtx_-7eevD9O0qGtAqsqCCGMIMSRJJJWSkupSPzhZLYyp25qlPEz2-tB_-epOFPXFxfmmO15vt08fnX36xet9Zy_OZkVRrktllNFE56vVvFAFChfjqpnlHHXV_uKbl1_cbn_z9XUfYHIp-lRWVR7ssZteXR9_8fGLUfFNZ79-cfxbP_z2xWJ-7EbrwnK5vHH2F7_55OsXN9ZP68v1duu3fa7LphYmOTCmrdo2kEQS9bOzYPA4xKKUjZHLD9YX76yFxMN2YBS6qr_9nQfzdftXf_Hh1ctrQtptD8e7rtLF1Llw9HYIx9u7JxdnkxtPn53vdgeRc6PkYmEy6pzg8snpPYlcadFoFTuPlpPPVSEUg6rkNE0hwHJuLs_Wu70r2_LYT97GmJOQark-U0bM6mJxMqsqM06xqWtAKGdqtZ5bOxHT8Waboz8eXFPqN7_9bK7U-Xzx7HJhXTSGphBjyoEhZpzsqHTpXZJK99OYgH2MUlCOsS7NerEolZzXNQLEGPfdoI2q2wYJfUh32-N7bz96-vTy_feefPDuGz_56c__6T_-229-8HR7dbs_9rvbjZAqpNTWZUoslCqKcna6WJ0v56vl_ua2NgXkaO202dw1VaW1rtu5dSPmFJ0jwnHyw2iDnXbXN0VhuuOQmVMMSqrj9li2lS4KVRl76DMzIAql7jGO7XLFKCCjm8aqbb21SFDUlVLatLUpin630UokH4t21rQn0zQKQZCBY37w-EJIFETRJaVpuSibunj11deztj1Z1T_-4XvZj22hK8kPH5z-7Oe_enY5f-v89MfffvvJ2arSBDFBBm0058SclFa7bgw5VXWhkXe74ZhxH_3z3fHF3XYzeaq1nGkqZddZKagAeXQuAmy66TawYPG887vsLeTORkiotF6anL0TQtxOvjSqTwk4GynYMwTwRBNLr4WLwVpHArvBmVL1kIfJRxRb5-ZNKQA4M0qJAjkzqcJ5Pp1VLvoX20M3uoRoXZzGhEpsb7Y85oSRdMEEMfHJqiUizOgID9ZNk3XORZeBIYSJIofIqDAzIIHt-sJo21lBJIhQSFkJzDk6h1IUVQ1KxpBKJcfDgWMmicAcQhZEQghRFH5yGLMggchVW1jvhRCCgTjnGJP3mDIyphAAsyAdY2QGALiHg0MmoStCsuMEnJKfOEWAzIQJqJ6fCCmkUhJJkACkGJO8N-9mrttZDEEI8ofehhBjlEpEN6QQhv6AKNrFPOW8v70WiNWsmfzUzObDcTDG1E35-vWt1mLWzKbuuFq0-0MXQgQGUxRGy8Oh00pMzhZ1mWJGotX8YrfbkJR2dHVVWTs5Zxk4R68VFWXR9ePJYtH1fVNUnJmJvAsEuarKlKLzEVBkREHkrI8xHvc7QkbvMyFJrGctx5wip5CGYVyfn87P1vv9ztpx2B3r0qTsz-btmw_Pf-_7H3zwxiV5--D0odby9q6rF-11Pxy7cXD2kH1kuN7tpTZ3h-O6bYuiFtG_83C9aJqvn1-dLZbrxXrqe6PE0bmPvnl-tel1WSqRX1_tjvvu93__R3nyn3z24s2nz7rh8C9--wetNCiEi-7_8tOf_e6bz6ILm2Eao3v_4Rk7Prk4-T__t3-2qMw7Tx48uTi3Pv7iw09-8_pmtxneeefJ59fbf_-rz15e7z_--vbxGw8-f3GnFO1v-5ur_T_7p7_XJfvv_81fxhhMrYabfRyneOy0Fihks2h-_rNf_fEf_47vgzHqbr9_ddyJ3_-n_7J8UNdSGyJBUBVaknzw-LQgXDb1atFCTD_69tsppW7svvvW02kYl3W5mjUA-Xg4zptquZiRwPms2h27t9-8qJWptVAK3eCQUUnpbdBaGylud8fFrAbgsijmbfX6dmOUICEAKCfYdsfMWGjtQlBIGWAaJ2YUUjRtEVwsS51iFuK-xC-IkBDuiZ9CCE73q0RwziKJlLMplBAixoiAkw26UDFmICLCnIEIc84JMSMogc6nmDndf2en5GxgAKUVIEJmF1KIOQG4mCYfqqZkzolhexwJIHEOnCNmY6r95uh88jkCIgIBkdZ6sD7EaAqdMtjMbV1yZgAIIW4PfQJw3jNj10_3BgBmkEqVhfYhVUa5ELVULnok4WNKiRkxATDkDMnFmDhLSc4HJYT13rqotQKkYRxXp2f73T4h1O0MAKUgzskUmn1UZbXZ7MuynPpBCiSAmLMkQmQfY1GUGaGqSikghYRKrU_WIaaLRyezWUsAKYRue5wv2u7YC6VIEacEOfWHg7W2nLd2Gk1VdduuKmqObjr0QpASJifMOSeflNbsXQhBSNHM2-jtNFg3DMEH1ZRC4uFus9keynkllKoU9ZOrK9M2TY58erqAZBNk1iLYKAAXlycEyCkTB6XM2PXtch6Z-75HAgB0U8g5lVVLJAhRloYydrt9yry9vZNSeRdRwGw5R4lCyOOhE8SLi5UfR2-n6Xjg6FzfRTsKIYzSKaTsncwpRc6cUSIRyqKUZeW7MaXEMVkHMfNyteLos085Z4lczGeTcy6zd6mo29l6_da339nvbjkCYdRlKYSZnZwvL05BYTh0wQUAnJ1cHG9u7ODOzs-Z9Id_9ctqVgKwmyYEDD6F8Siklka6YZgv2m7T-eQxcsyRc-KcEmeSRmgd7ASck4_FfBatFQKTs9KUYZpIEKSMgFmgUBKQ42ilUjkElITMRAoBiZBjAkSge_M8IhE7zwSyapAT9FshVIwhpyik4JxByZwShSAw54g5OIwpeQ-SQAoQBCgAUCklC4kpRhcX7zxLxyEHLwV4O0LyKcc4TaTEfQNVCQjexQCpt0pSzEnrcjjuUUDXj4uTla7K2WKxe3kdg7u-2Q02bTebN797cXOz7Qd7vT8mD4--e3rz1fWnL29_-vLmOvNn13smNWuKCFAIlQGWs-q7j84erpaiLIhkN469dURCCGLCxBkyM1FKOA7hF7_88qPXNz_57OsXN5t9b2_uDs9v9-vzxbazBkVOrm7MIaTtftoNtiCpiiLmlAFDzM7nr2_uqqKotH6yWn7w-OL7zx588PD8oq2-9cblel4qJU-WTVOV5xfrRVne3OyePDy3_fDlV1cu8ePHZ3f74RcffqWX5XzRtOv5_ubYLmfrb5_PZgTeRQBSnCGM2ZOhzfXW7aYcUvSxbes4YjpGo0S3O5akAsk5qV_-8ptx7KTmcRiVkmVlALNCevzWeZgsELz9wXuHbpeSn6aYWTx5vFKSCdXubr-cl8tKnZyuX73cPn3rQgshEWVhSKJYFkRSMrCLmUNMvFrN3370oItTWdWbzXa1msWUF00RUx58OBz2mdPxMEoEpcxhP3b74Wc__-lpNUsun53Mnr1_OXxx3S6qH735UAD55Dlnn-6lLgTMJERm9DH7yKMdlTA-ByPVOLm6LIuy4px3x96HSFK5lIOPZVEw51e3t0-fnM0bUwqkyP_2p3_5t37re5no9mbPKE-fPRCEKcaiLJDQaG20ub7ZnT888d7f3mzc5JqmGu10dnEaQk45r5bzWVNcXV3dXd2tVgspVb1c5ZwkQtm0KJWQOrF_-O4bbrL1cqaLUilhj0NK2K7m1WI-WWfKBjBLcf_ICESUkprlwk-uWTUp8NnF42k6lrowdYECpz5mCIvTtmka5Pz2e28ebrcPL87aSrdVcX62WC-bOHXvvvmo1ni6aN84m__O--88Ol2rNFWS_8d_8gffeePJ47O1ESQRFQkiUoom66z3Wuq_-NXzk3XFKF3Kr7bd0cYD8-evd8FIdVEOLkw574_TOLqH55UDHL0fiKeCts5nSE7Ev9odp5yDFmPCY4h3U3ACM-AIAsqi49jl1Of45fHwSbJ7JbwEKmVbmWcLs-_tfvSikENK7bxshNyMYVYpI6g0ZY7sctx0_WxZpUwUcFWq17Y_uqCbQrSaBEmtbAzjFJdvz2Ut0xi1wsz54rRotd4dDg7T5nBkyily9CGm2FQqjLGQJAlSinVZuOMRJWZmAaC06kfbzJfJ-ZwAtAgxppjsOCCwUNI5B9H7yQJnIkISOQWpZYqBGFJ2LCRKisNIRMFZXVScE2ZkTlJIEioGL6UKzkujSFAOAZhznGIOmJNUmOzEIcuqRGDTLhBB6SpljBzLpvJ2EoTRWVMW1jlZqWnokvf3yL4MedjeCRKIyJyYpZIiOuunAYB1pTlnTFxVRXIOAKSWbdNm5mkYEkNKUUmxudspiULI_W7XtDXnSIAhBkG0P9yRJshsSq0EdfvDcjk_dOPyZJ1zvs9G-v5oTOGsM0I5ZyGDkqY77qQyMUYGllo282oaxmkYnHOun9wUQuLV6VoIOna9kdI5P18stVbAmEI4X61njZimA8Xw7hsP_s7vfP_xWSPumWeEPuW61n_5y8-FFsdhOvbDcjHfdv3mMFobv_f9d3_09lvWwqw2q9ns7m7XTcM-iW6_e3yx2O2nn3305dEGFKgVFrq8uz2-9eaDZw8ufv7zjx5enDy_fv3q1d2ffP-9yhRdf_jk-dX7Z8uLVUOq_MknX_3933rX5DxfLz788AsyShE-fPLg7vbw4VcvjsP4rTceVIWuavN__9OfR6Fe3u7qdWEty0KumoIlujEMBf-7f_1nx9u7VMFxs7OjzTnj1Aspp5CIJNvw-7_322yDlhQDvD5uxN_7T_6lDPjDbz0goQotz84XbVW0peGUiRLEuJq1JKQkuljMz1btrG0u1ivmdH19d75q2qbyk5s1pSBoKoMhC0GCxBevto8vV4VWyEwSY8qmKICzVFgqo7Xc7vdVYaqqzACcEiMeR3exmrsUOeXM2WijjeQcBQlOnFI0RgFSTplIpJj_Zn4uxH1whkRIwAyChFKSgJgBElsfpRBKq5CSUTqmzDln5kaJo4-D9YiQAKwLMefMeBhsziy0iDGTJO-TCyFljpysj4zscpaCBICPfOwHQjK17vtRKj2MloHvl8rbm2PRlN57Bi7K4uauVxITIMfkJudzTDGnxCEmH6IuVIh_E-N556VWDNnFaMdwnJxSggFiRjs5qVW6H_aEGHz0IYMgF6KdAjCmzC5MgASIu91BkixmZfCWgbydqqJKKSmpjsfx7OxkGIbZvJkmW7fN2A_We0aeNZWd4vMvXr39wbOYs1CYQ3TOWuudj0VpkHOlVaEl5DzZOPZj2RRCY3-0m9srIpVj0IVBiVIXqmmEIGd7YggARTsvdPXOt9_TtZ5cNlqlzIETCYoRUyJdl38juB_99sVrzCG6cXezcdbPz1eUU1lVu5vdg4vVcOxiikYbI00hNHDqtkclZdWUx00vtVGVPmwPRVUz8_E4VouZqQs7Ba1EziyF9C4Ck_NWKFEWRhCXpd7ve10oBpBCI6KS-rg9CqWT84JIGeWdB6QIiHhvyoooUGiVgTMJUzZUNai0aeePfvD9qplFAt02mDEj2mkMybvRFqvzJ--9P2_qZrl6-4P3mnnz-qsXYfSP3nvjeLsbJ9e0M5DY7bavPv7GlIXUQpRldKOd0sO3n84vTr781efGgDEUnEsxAKRMoJGl0n4agak4XU27QUv0kxcCUkrRx6Kp7wcwduiV0ZxZSBW9A8YcoWjnwXsBUSAIY1xvUWkAQE4SpRAypUgABIRwr70W0XshkZkhAaaoTJm8BxKSFGcUSgkpGDEFzpHVbCaRsh_j5KWSqihysEBEmWVhICcIERVl58F7QYQhoo9Cau-9RgLIKSXgzAKiT8DICZRUqCQiloUZjnsAqQstiFPmlCANtigrFEJkSDkrIXlMIfibr_ayJIigIwjM_db3k42WVUyYQgz89Yubn3z58r__zad__fmrl9tD3RSR6WxWYQTv80dX1z7nn3zx_IuXV59fbQEw2ERCekGS8NV--Pjm9nozjlMIjIP3zuUXt_tKmQ_eeXBzd9zsxnlbzUx51fUBxevN9lVnKdOnV3d-GE_Xs1VZzttyXheNkYXWgtkIMfq4vesCoFE6-AQJRjfJLDwngUI21S-_fPmTD7_66JNvsgBrw_720B-mLDHEcffqrns5HV9t77bHcTdNd0Oeot8cxrvBjgFiPFmWptK2s_O27EcvBVbz-uzBUjp_dX0QUkRvRx-U1qTFMLmhc2eP1k3bQnC3r19JIb_4ZquQSkN28lNMm7vD6dxM_YREbd0EH2ZtJYxoZk3KXBXl3fWuKkuOAZA_vupPl-3F-iQy2sk1tZ4tF8u2VkZLqQDRORcCjP0UnCNGb-3U9ySSRLN6vH7_x-_qhO8_Osk-_Ys__H5pjB1GUjSMth8mUhR8cs6lzJnBOgeJhRRCsFGafSgKraQizj5DDIGkvrq9E5KaugLikMJsZmZlddgcso8vX11__-2np818uZgVpt4dD7ebXaFFofU4eq3UW--_rUD-4Pe_70b7-uVtxvStb72rlFyu14ro4uFlWxcny9mwPXzx-Tc_-K3vMCGidN4uT08Om107nzWLk2kc2kU7DTalaOpq3HZutFVb1bOGJA3H4-zsNKdYFNIO0_56rxtV1nOWer48QQGHXVc31XrdamkS5MKo04tzXSghaL08Gbr-8sFFqZRg8ejR-YPTZr1sTaGnYfitb39wPq_PLpZaYpa0bMSiFG89Pnt8vq6MqpS-R8sjAxEpKXJiqQUjffbV9flZS1V9HKb_159_tH643oT8cjcEQREhCrrZj4FStSqKSr3aDbeDv4v-kOLt6HbHfjPZm8HFzhPiGOLR2T6lJHGc4iHGkcSX13vH8XYaXxz2MQFxDqOffLQBXODb3h2O4w7iGKJn7mM-xviiG6pCDS4665qiWLR1N_jdFH0IMHTHFLYHX1XSFCVkYITJpWmYJIL3cVbrcT-lwMGn9ckiWP_i6mBDThGSSzklTBmQfWfZJ120nH2_7ZL3nCClaBZFcj7HQCBNVTo3EqcYs-2HZlZpbdw0Sa0hR4GQXCBCoQCYYogggJCQkx-mFJKqdWKImIAo9FNRtzF4MtI7B0RS6xS9Kstoo1AUXFRK5ughJwLglDAkoSULJCahNJIyZSULOR57AOGmMbkphaSMyjHbYUje-6FLIfgQ_DSEcSorY6dRaV0v28ro3c2dUCJ7yyBPHr8tODLk6GxZN9a6tm37oZNKZOR61oSUEHjeNJyjKc3V1R0RaW2mcWJmqWWOKSdG5BgjAxgjOTMQjcOklZZSKk2H3W6xXCLC9u5WGy20iDkdj_3ZwydDP1RNmWJ2oyNITV2xJGWKpq1tP_T7Q38YVVmqUgPmsq6c7402UufZrE6T_8__h3__j77_rWVBh9sdc64KgVIEgs-e372-3b315oOb3dE6z0J-8fXr83X1nTce6kwvb3eGk9B6v-t-89nzh2eL01Kdr2fj5P_r__DXqtDd5LRAG8Jh373_7htnp4u_-g-_ZJKTd7tu8z_44z940M7HsXdMv_n66tnjlY_qF5-8-PYb5zLFUqsp0YvNYXnWCiG9z9v9IUvRO_-rj7_63e-_Mzn497_46HY_lLPSTe5ue3d-uv74qy9__dXzIdrbzXa36UcbzFmbjkP2PkenKSOy7VNZSJJ0d-wuT05L5Ne3d8e-F__iX_7P7lyUgS8u15UxYbSKaF01p6tmWZV5tG8-OGlKsyr1rC5O5_XpvBbEmLmuzLwySgjMICRWRgtCSNyUFTOftlVVGq0UpNw0Jqc89VNbFU1TCqLr2928rU1RAEB3HHprAbCpyhD52I-zprHeawIlNQBqo4BZIE3WSyUys_cBCYkoZI4hSiEYAJEJ4f5oHxAkITDknKWQAJiYAcCHAACmLIBh9DGkDEguxMmGzFgYGZl9TCQFIAUfE6eUMkmRAJyP1aqaBl8VOkxeS2VjGm1IDIMLkoWzbt-PpHTXj0YpJMw5AuB-skKSVEIQxRhTSjGGlFgKyQCMIKTwISLJyfqUkiA5-SiIhsGSkvehBACFnBhFCDHGHFJyzpdlAZLG0QEhA3NOPgSSJsa4Px7rum5mi9evXi5PzqJ3nFOMqShMZh47KzB5n0yhJuuKQgoU-7tjVer5fJ4xtU1l-355utzfbJtmFmNanCzLQnebzbxdTINvm7poCm1EIc3zz19KdT-ZEEVpUEof0267l1qlkHIOhSkyoiwKb6OPuV7OMJOHvDg9j8wkZL8bCe-L5OBsKJoCsi8LnUKY9v3q9EQAdJtjdziGYSikma_a5YMzDjnE2CidU2p0tZyfDOMkOafIx2Gcz2dlZZz3SmDRtJOdmKGoau98ZpBaCSlRQDNfcE4AOOz7xOnxoyd3201Rtt1xf_H4MYFxziollNEgJBYFCUnKmNk8pyAIGYWbBlIFaV2183w_G5Faz5p-GEOOD588c8OklZiGMSYgUzx5__uLsxMknvqhmVXDcffVb349He-ULg93t87FxXz13t_58e75lXO2qZvoLQBLoXRZCqnWjx4d77ZSUnsy82MsyrJanPW3VxJy9pOQUmsdpySk4Mgh2ByTIARAAgnIShcppxSi0pKk5JyKooIMQhAoghxzzCRkykwKkZkjc3Kcs1CaU4TEQsoUQ0oJlUZMHBISIqJA4hSZWakiI6GAlBgFAiMS3m--_4ZZ0Q9SQLYjCplDxJxz8CgV3NuCgDEljklksNNUzJaYcooJUuYEQkqBklOSnJSCMIzIpIVgZm2qvhsxRkmasygNMbAbXc5cr09C8saYsi6Ss6oQrk9khCRSkaN3oePArtTq5fXB1OpoPcs4nzfDON3c7P_9Lz7713_16b_77Js__-rFn335_Pl293LT9S47l_vAN9v-883x6eXFYQg33n31avvzj75YP34QmbwNv_397z86XS4KKaT89MXmwy9e_HK7q988f_Vq3zl7szvYEHLkn3_-ChM1s9mvv75bzcoUUUtyUxCEEgVqkTIe93Y3Dbd7e3O363r73_2Hj5eniyTUh89f_vlff7o_DGxwuzvudx0zTC6GmO3oj89vSubCCEAoGy1yijunAaYxqdo8-f7D1fk6TK6tTfQxuQl8tmOYrRqRwosX12ZZhcmljEpoqSTJ4o03H8SYSq13d8f1vF2fzDubbJ4WzaLWFAc7uTAO1nBqmsZNsayLstIKSBqz2e7Oz5eFwNP1mjMjUdGWz56dhsOgjDmOPWfWQhWkqFAhprEb--1WMEcbpMKp73evt_v9AQSWbaMKnUJUAhugJ-fLH731tK0LzAkIlILJx3sRJDAOkyUhAdH7JJWYzdpCF0YrhUIZFX0aJje4YF2w1pdlebZej2MfQrw8W0OEw2Hfaq2FJIJa1YHjNE7b_X4a3fXt9mc_-7xu9XAMWqrTi_liNnd2RKE3m13TtkbC0A-X52fOj5iYJKY42cGfXa43t5uTs7mS5asXd8Ph8OjhRTlrDt1xuZgbrau6suOotMhAl4_PTx5eDP3YNE2zXKUUHr39VAArbeYnq6JQ67NV8JEkr8_Xj9-6rIvi5TdfV3URpnB6cemm4eLR5dmDdXKhqdtvvfv0Bx887A7Dybxa1eV33nm7EHhxvvj1Vz87ma--99azR-v5m6eLRVsu6tooBEAjBSMCc84x3QPpIaWUvfNX--NiXZXz-usXd9fbI0j8uu8_vdslpQJxloIl9zkGKV_edpt-2udwiNGJsO2HMTg1046zMLo9aaiUmRmVECXWBd_sJpdC2YiiwBHSwLlzVhQKAYUgx9kJ0lK5nIVWJJCB990YYxhdOLuYOYghwe5wXJS6lsbFvE8OBRVh2h3cxlqjdQ6co7-5OV5vugyQfUzBj9YiUSYoMbeFAQLn-Dg6RLDDlAEZ8rjrKUWINo7HTBmYJSIKTC5wQoGohI42lCWGMfjBSQSJYMpKCC0QgZMfhhS81AZBso0xWARIkw-TE5BNMU9u4hwRRRbEPgqtALIwGpgxUwqeOOeUQZHUxIyILCVizMlGAIAYog8IKE0JzFIZZQoggUgI7K3NflJlIRRBzm7okx8F5KKa5xyQMHvHMREJQRTsONzu_DQBMApkwKJqXLcPY6dr07ZtXeqmroZjB4jTODDiNI1S6ePtHRHnFLQprJ0Sg3fu5ORESnHseykIBXrnpSCpZLteYAZrx6osBKCbhrpqU-K6MgQktQ4xCyNzzP3omqYwinzf5RhJkdIGJKmy1EYbLbQWShfz82X0Y1EWEJJSkFNW0l8-OHvzjZN__Ac_-uDJqSHQksdpXM6q-zn4YcqHycpSDAfXu7Caz_b7w6PT2ZPzUzvGj1_drZfzbz98NGH-7ItvRCFm7cw750P8v_7lX5lFUS-q25vtxcOTxWJ5droEhBfPrx9dPn5-9VxkKYr8P_q9H0OKUuFz1z8-bwVQ7xJTeno2TykSiX_7F5--utuaothue-9D1dYfffn5-WL5-Rd3H3z7jf_bv_4Poq72o5uGaRjHr15u3nhyPnh-cbtZXix_-YuP5peLbjym46CYY-8JWAlVNPXDd57A4E7Ozz__8vqHP_xOFdLLV7fVTIn_8v_4v48unZ8tckxn8_JiPb9Yzpa1Oa2Ldx4sH5yv5k3ZSLFuqkLeF9VyDElpWUiRmJQgF4N3EXIujSlKk2IwhUGBArAplE_RWp9SYs6SQCvJDFVhyrIgIs4sBZZVBQCIaArlXWjawrvQNoZIRGZm0FqnlAjBGJUZc85SSkQiJBIiJQYGKURKKSVGAgRIMSmlGAQwpJRICKDcj4NWKsREQoyTYxQZeHJRCkFScuLBBecDZ06cJ-tHOzFAzBxcBGZnU1koQgEkAvPdfhBKxpTH0Zal2h0nU5rt9kgoGUgIRICYcT_5kFJlTIIcEyeAhCiUjBk4gYtBk0yJ7WibquytI8QMoLQiEjEExPv6H4ccU8w2BHEvD84MiMH_jYfM-8BZhOSL0uz2B2AmkH1_nM1mx_0ekDJnEEIp7azVhTaFbpp6msbVYu76cTmfS6VjStY6wlyWbfChUBURjOPQLubI3B-7-bwp6gIzINHx0N_e9cMw1Ks6-CSVFkoKKaMLpKRQehysFMYOky5UUc9mpydlaXzMCMACymY2DcPq7Gy-XM4vzoqqVIWxzreLFoCSj2EMkqRpaj8Fb6OQsDpZFsU9nBq9mybrQ8bCkHeOc-y855xqo2frhQv-eOghRY48DlNbz0goJKG0yICi0EVRACBIMVssunEABGHQu5gwgRCcuSiKqR8l5tlqjoj3Zw9D73RTxBC10uWsztIIXcp2QaKInkFQs1gun1zWq5kdnECs2vnVq5dPHj_NQLPlsl2t337__Vld13VdF8XuOLz--uvNNy_ZWXQhZRETPvnWt4ahe_6rT5rlSXfsClPGySqlGej0_MHq_OK4vbXj5Dk62ztvh3Fw2ztdq6oqXAxTF8goRtBaR86ZsxACgQGJOE2TV0WBUrBPKITQhgAhBgSR3ETagKKUAsd7yZ0MIepCQogp5xgjIoCQjIx8b6bPKCUAAwhILIUQRAyQQsJCJqSUI6QI-T7hQ2YWpkrBExFlzikxIBIKLbLPhMSA2UcSxJApsyo0xpwBWAqXIhGqyhAKSGR0kaLniChAyGwPtmjrnLMyMvgJQeUUpZIoZE6JMo-Ho5nN3OS3m05Xuh9svag2r0fEDBpyoZ9-7_zFp5sAiUH1Pr733u9_-enz5aLuBzsehsgxBv_qdo8ACeD6erfbD4_feOxD8gmW8_n2bh9Y_OTXX_y__93PP3_xolmuv3px9erldczceffrz77-1Zevb7fT9d2h6wcR8Jd__pEl2B6m51c3Hz_fEMMff--tB49mnINW6s1H5yzElOFqDL_65tUnd7uXXfz0enPnJiWkqMq6rZj4xz98-qc__fz5Zvfiet-ezVHQ3c12szlmZDYMRo5unLqRRBZGSGNi5jBGAkKZpKHqpFqumlrS_ssXcUxKs7eZhDGSfvS9N378rYuQ8zCFoRuYUGjyE_d9XM5mRUp-CkVbrBYzaczIqWMMnGM3ffuNy-tuSinJUmbgoi7Kqjru-0oXpdS2H86Wi8WsPJtVr-52mWNIad7Wi7outFQCbYLDbjs_qZ2LkfL2dhMHG1OMzve7wTu_eHyilG5nJRIzsJJS5Ryt-8PvvvPb7z5ZNiVlRoKQ46EbY0zWBy1VBI6c-8nlxEbrojTW-hQzgOyd2xwOPkMgCCkN40BCPj092fXDX3_4BSFNozNCVLpCwpxhNmsP3eCCF1Lcbfa3h_7ZO29aN3jr3v7W0x_96J0w2JPT8812-_U3r99979Hf-oMPSjJt3ZyfLcuqJU5PHz8K3hd10e-Oq8X8ZLlqyyLn9P57zwBAGamUnM3mdhpfPb_OKC4enWIWTVlC4rIuQ4wIcH55tr_dNM1sHMayMOfnp8f9YX26nC3nAtWibbz33XZrSo1Gbl7fLNer6F2cRmv95cXZ3MiK8z_-k9_ZbTerttrs7r791tMnp6sfvvX209PTQqlZqUotpm6QJDkjM5CgcbTeOSElI0qBKTMzWx8dA0jxk598EovqxeA-eXXdxRyksCllEgOEq67rU7o99IjochptvOl6JFBGmarIUzpMcV2VS6H6zgHKxBBd7Kzvk00SD8eRpBxjGpwrZ8YH7zhHxE7CyOgIRhucDcSZMs-aOk7x2Wk7DunqzqW5GLtJRr5oahRqO_SdC_N5JYU--pghRCmmKUQflIayRBIUnOfAGYgBNJGLMWc6WRW3_eRDjCnHlDOm7LNIGLu9cBxSyAxKqRASxCSIhSAGGHf7Zt5WTbvbHExVcmJgME3pBgs56aKw40iMirRRxk0uxyQEQYg5c4oemYBjjigLk0IWRMlHSKiLkjkJpDh5Qozeo5BIxJkhBJkRkRAZUkJB9-_-xChNKbUBBFQyTmP0jjDZfkqZ28XycHOFnIOzzFkghGmklAFQCJmiL7Th7PzkdFnookwp6UIhJkmqNNXpeu2tR0RRFHac2nktBNneGYlSwN3Ntp3NY4xnF5fWByFFikGSmEbfzivr4mxWZ4a2KLvdXhsDmKuqTJyRsGnKw-EgBXjvJVImYGTvYyCO_SCAjClIIHMO3scIRWWKWeNicM4f9wdjzGw-L6vCCHz41sOC2BTtf_mf_YMP1usHy7ZUknOUWgzWb4bwxde3nc8vb_bjMJ7N2pzis-Vca-O8L-v6v_43P70bh7PztSzLn3_1zTgOPofFvHrn7PzFzbY9qbtdvz1OTy_P28XpNA5x6Jv5_OWLl7PF8qPPP2POWAkX-r_93Q_CMB5G_9__6a-ePliFQJNzDaKW4ni039ztE2JRV0i02x2Flj_7xacx5QeXD2TyZaG_uNl1o51y9N4djkcsE8r6MIwp883r6-BDdCH5KIQQ3lLOSMAZLh-drcr2sJ_s2EsjTx-0D9vZrz7_6sHTh-J_8b_935xczBZtdb5sGi2A07wpCi0LLaSULvmEQFJu7bQZxrvjcQppe5gyk1RKanl3e5zVxXLWSCmi98CcMhfaZOacstYKEUujtFFNabyLWutxtELIEGKM6dCNUklBlCPHEGNMQsq2Ninkw-A4p6I0MSQCZvgbCUBwMQJ75xlBSOLEJCgzA0JmlkqiwBTiPeeRBOacpVaZs0BhlGZAAJ6cZxL3rRut7yUHKWccnVeEGURmJoEkxGSD1jqke74OTTZIIVyIU8oMEJzvDkNkRoBMkBj60UVEBkDAEJNUMmMmJgw8jD4TRAYlFeTsJ-eDzzkzsBaYkQRIVGR9lCTGKTAhEHHKOTIRAoPPmZByzoJlSCnE7HywzibOKSaCZJ2f7GSqCoBVYbQRdpxIqt3tFgm9nZyLVdvM57PoIyFpJQ-7g5CUkMuiyDEmzoTYzBoGjjkP4zCfLbRW83mTGXJMUmqjFcTsUzClHqYRkAbrQMjok_d2fnLqg6vqmpmtHQSz0ppkMfTDxZNLY9Tkpm44LtslZ_bj4DJnRiFlysn1E5EEohwzZzB1oYtCN7Uq8PLRhQtx39kf__a7q-XpRx99-eM_eG-zOe537slbD2UhXt3cbndD1mq3O1RNGyfHKRalruvWx9jOWiCsqjrEYLQ87g-maLSS_WEwlem6UQAUZXU89NZ7UxRlW2lF42BNWcQUpBAopamKsq6qkxVmUqaaPzwpTxelrkgjM-aEclZuvrrqru_82Ckhr65e-MHdbo-mLs-ePpufrJrSQA7Hzc3Hv_iZHfeUOE8TEbIsE8qHbz4tjNptd-Ws0mV5_ubbRVu__cF3n779xvzkRFZGSLp68fr8zSf9se9ub8ftPhx3plAAQuhCqyoRpAQAlCK0ZyfTZk9S5BCtTYykyopISEFhtPWsISWTnUKIDEkXpt_3ZTsP04SYhdYMTNkTCUgJmEFIyFFIKZWOwSMzMBEJyHw_QEdEzpwzCiFCDGQqTAF8ELpgQFUYSJFTACLmnOyolc4xwn1EAAkzC4GJUQgQWudM0U0QY5y8mK2SwGgthJB9RMoAiUNOEKJzUhoWIvoolRBCMxIwAkdInL1PKSlRAzEmIpIAbEhxDByCUaiQAqdhM3Ub21yUwxD3XW-Efv7hLwHsr3_zxe7QT5PVSjqblVKo1Ddf3gFkd7BffvnSLBsic3u7W6zK7f44DKOpFUm1Ofaz1XzeNtG5F9-8OvTd7e0h-cDEVEhd6R_89lu72-Hq1V1KRDlZm372xe1Pf_nV5893l6fzq8Ohkubahn_9y09A609f3f3iixd_-euvPnnxEqriN1_dvLrrN9345dX22A-ds1Lrw-1-t--KtjBCTftRArnR37147a2ddmNZ1s6DagvIEhGS53LZKKPyEKZNV5v6H_5P_tbV17sf_OCdN94-Wxj11uni3_7pxz_89rttVb77g2cvXm3PlvOTi2WDdLLUdrBGCRdSs2h930lCBuI-zGftTNRZMxgBgSJz8DBvy3ZZF1oEN7GgyY2reXPoxxx58m7RNs5Hgcol11ZlThFEOh7d-nw99VMYpqrW2UPOKI2cn8ymbhSQjRTGFAKJkKuqnFf1f_oPfodCKhQJQh_9Zn9kQpLSO88ZtNYp5MQsSSJgyMn7yIDex8l7F0NO0SWfIg6Jv_f2Ux_8n_3m48eXp5nZh-lkPo8x7cZRaW1zPHS9LoujC531VJXb3damVFUlk1w19cPL027s7m6Ot1e3jx-eEmkBfLZeM6Tj7nCyXux328v1idSqKUzwbt20h-Mwa8z-OOjCtLPGCImQqrKeLedVWwlGIrVYts-enqJQZdU2TZU5tu369cvns3ZeFirGdL4-WZyvjneb1aKGGNinZt60s3lVVotZXWry3XhxdnJ5ebps1Xo2X5_Uz55ePjg7KQS_8eB02RZKiVJJQVCXsq7N0A3SFEjSxyiEDDFEzgk4pRxYpMx9CMPo_09__q_eO39jPzjQeOPDr7963QuOSvlCDg66cQRDnY8H71MCENi0bVnoNx-s5kURu2StXyo6LcuK4zS5etFoTbWkmaITo3pWI6ccIyAkwCmyUNL5PPWxnxwKGoYAGZCTTomYV01ZkqpBaoXd6CcEm4KAdPN6B4WWKZ80zZjSZKfj5He3GyzVmClyUEZ2Q0yJ7TDlmEEJZSQrdXfXKV0uFsVunPrRB8whxuiTrCAdxzxaSjKFqAoZbMyYiCn5IKRgRZASeGDGRMDASplp39WzFoB9P7hxTCEIhjjawCFB0mWFBJQ4-UCEwAzIuq2ZMycgBEwsAKQgNzoGJikRshDEIQkhMHH2kRgJCDgiAjKQkEIpQCWlqZcLUxduCou2ubu6wnsAKGLR1sfNDSISQU4-2DHFQIAc4z0MNKTAnLQpiNTF2-8E1yefck5vfvDe9dX16cWpG4eps-vLVXc4dtujlJAhO2slgve-mdcp4zgNUmtErOtCMiByu6oXy2YcXVVpyRi9AwCjNORklLbW6UKPQ19V5dnFiUCRgU9OT9xoy3kjMkoS0zgIiSGm2XJpx6lezCDl_tCDYyUkO1eXCqI1Us3b8tFF-_vfefs__7s_bAWSJGNUyHnw9r__-ecuICMmicB5svaNB-ckoNCmLuo_--gzr-g__PwTj_j08YOL89WhG-00eUiL5awbusTprccPZNX-9MPPhRZFU756_vJifcIROGapREJqFs3jy_PVqv6f_tP_uPCx0OZmd3jvvYumaYbJM0KhMLrwxavrEWRu669fXN3e7q_3_enD9ccffZljtM7-3g--_9kXL1_ebW83Ox8ZEXb77ts__p4hw0TXV7eqNOKiogzgLNgopUTC5ENhTMxKFHrc3u67YXGxPGtPP3hwse2sKLX4z_7n_8tZVaacqkpG5293x7Y2Lmehhc_pens4jmFweXTp0E3dcUQhpZQx5hDz8difLlulJMc09YMxGgGUklpLAQTIKQTKoLQmEDEnqWWOOaUYU9KFRkIpJefMTFILHyMJNNIgUd-N81klhIwhKiVJ4OHQFYWJkUMM9zLOlBgyAOf_Py0HSJB3PicGZCllBmTOnDnEKOj-O4NizIpkyuxDAELrXQiZkawLJIiRYsrTFELO4-RQEAJa71AQEoUYusGGGEeftrs-I0ijQAqfMoCwkfeHXpB8cXerlHLWZyZGmpxThN5HF3OIKfgIDP0wMSMpses7oyqb2Mfc2akbbE45pMQIQHg_iFClnqbgQ0AhcswJABJE5sG6jJBzCiFxTkQYY0qJgwuLxYIZUmaUYr_bV2VBQggpV8uz_WZbl4WdprvbvdZC6GJzd6jauik1kvY-LFYLRm7auij0YrG041C3zTRMpiwASJfFvC1DiFLJ7tALoYTgFJMQxJIZ2I5jTBE4lfPadqMpS2BOyRPncRylkYd-NMKsZ1UGlkWdchy6QSp993pz-eQRQ0bExLGcVVKomOHy0YPTR2fb19cuxDcfX1RSVUYVjf76i5dvfestH1ya_HCcXr-8vnhyGmOMNnOOs0WTmPf7brZcaCPubu9IyCTw5OwcCZrF0odUNvV8OWcpBFK7WkqtpZakFAkQoDhnEHR7s6mqIhIFVkYX_WFcL9cI0fXebix5wBiOtwclJRDHfkJMwU5SaRY0my_-8O_-nffff-f84XmhlVTw4a8__PzXv9pfvaSYJVKKoE0pCx0R26ZZLtcf_urXhPz9P_yjFJwu9DRaqakfRi21quurb15kSPvXd2GcqroWRKYoMXjXTYUpZVvnzEJSu1jmyTarxbTvhEQhJSlhqirGTALdMIQpmaaJKWVrOSdgzjkrbUgQYCKl2cemXjo7QAYhRU4xhyCEztEjoFIqxwQEKIQQlHJCQMhJkAACkoREuighR85JKSOQ2VkSEhJQYQghhXTfGARJkBLHxJAhJtIGEREoEwlkIJKCkuvr2UJKFb1VWkYXIWdZiJgiS4B0v8dIHAEUllWFmEBQcF4XKliX4-RDJIDZw8X67LSoZVXWKfD3f-v7gx3tkJq21lr0hyAzlLoQKqHKg5vqugAFpaYIEH1MNvkpGIlaq-1xevzg3B7HNHnM9Or1zWGy1oazJ5dCqJTIhaiJzi_WhdZAUiucN-Z4HIYpZJLPX-92hyEDsKAHD1bb237bDS5YZeTXL6-_eLEpV6f_3b_78-5m--J6d7s9eE4puP4wjDE56795_uq4H7a7fnGyvrq6tZOTEoFhsz0-eDKfL2cI_NnnV48vFheXy9Xlar6oaHCKc7XUkMLFm0s1KwopCeH61eHBaTVN-R_-R981UAy74cHJ3Ef_9M2HX9_uPvvoxctvXpuysCHQyG8-O_n4y5eDy-9_573PPvnq1dev-mNfgKwbbari0PWyohyFCOFkWT95ct601bgJs1k7W83apizrsm5mfdcNwySQ2lmhjfY5ry5W0zBFn70bK2UYUBNS5mZWtmWjjapK-fTth9PkNOFysRiGSZaGBLz7vadlQb_7xsOL1rCLWpFALLTKzKOPMWQhxGBdoYsYY1mVIWUUuOkmgOwRnA_WJ-ucMvqr3d2f_PCD9x5cdL39f_5_f7Zu2wBUKHV2soopWu8Sin4Kt_v-ME5j8M-vNr2LotTR53GaIOf3333iXH52vvrky1dK0npdLVaLl1-_2uyPJ2cnm_3u9PTk5YsXRmlvw_npGmLsXXj88PzL55umKp68_fT2djMcpxhCoQtrpw--8_Zx35V16QarjerHUBSlGwZBUkphx6mqirqpYg6LeU2C_Dj93T_5o_3VHUAGSjnnotTnjy5WiwZQzBdNzPH5oXvnyfk7jy7daA3lutQ5hUVT1lIE7wqlUo7Oh3Ec73orSIzWVaVy1t5Ofjv2_49_9WsLaQjh86vt-emqH9yb88thir_6-vmvb3YfXe-OOTslp5At5Mzss7ve952zQ4ztvEJNi6U2BbP1NXFt8MmqYi1f7IdBUSjVwdsIMSG5mDHkslYPSrkwBUcoi1JpMJILI7RCLSXk5Kawud0wA-YkJaZSvrw-vj2vuoS9j4NIN0O_P1pE3BzGB7OZyKCJbu_upmnQGrEs950t5vI42SGkEELMgUGglCjIWhdsmC9MBt5vh2M3ocDkYrQ-dyNOiVJm71GwVJpDwAQCMY5eoNRtSSm3ZRV89CGVVZFiUgRKiuBDniyEwCkjAKHw1kkpUggMwJxJiOSjubcEOJ9DJiDK9-DjSCRRQEiRkQH4b4aPzJQYICMwQE4pMgBJiQj3wT8Kyizc5FWhuv2eUkwhyMK4YdTGpGCTc0094xyAIaUo6F7yDqrQSOhi4JS1LqIdsncxWFOWhFSS-uM_-mHfTVrrw35_2I9aYeKIIDLnWV0ejz1JKrTJOY_DYJT2wc7a2W67U0LPZs3xOETry8osZnMSdHv9erlcrc5W3lrI2aiiMOYelyKIDoctS9XdHdbzZc6h0MUUw-Q9CcUIdnS6KCEFOw6mpLKAthK__cF7_-v_4p__vd95_7ffevhg1goUx8MxKCmMfn29myavCNaLenXS2LG3h-PD05Uk_MmnX15P9i8__2YMYT_ZlPM_-ad_4Dr7819_PDn_zfWLs7NTAmbvH188vNnsr3b751dXb7373quvnpdSI8Llyfr6duNjevvpY5QUrB1H-3c-eHb36mit7VJ-763TQx8--uzmrcs5kUwJqW1_c7fZ3O663kdBt7e719vj9XabEzx_8fq3v_f-f_NnP9lP_eB8iLFdLKKLpSp--Pabf_2bT7u7HSCSrvNuI0NIvSOQSlAOTspi9cbF8e7m6ovX62X74Nmjy-XJ04sHH33xPGkp_lf_h_-dBDj0LmXKwCRUCOlu3ysprm6P_RhCSk1b9J3th6mqy5ByYlBahuC0JFOgFqIqC2PMvVFXSikgI3DKSUqVc44xEZFEFFIAQ-TcD261rFPkyVqjhZIKMBdGreYNIuYYV4sWiTgyE8YQEUmSEEQAiIjO-ci5MIaBpRQxsQ_ZhShICCGAAIW0k7t3AISYY2YGiikJkEgIBDEzEepCpgwxpb4f7zluiOQjJ4aYY2L2IQohut4Zo7tuMkp3g2XElHNiLuoiMA8-5BCUEHaKU4yAUJkCADKDVOLQDUNvgcGnjIpAkiJBCBlEAt7ud4vZMqWERBlzCGnWVCknASLknFOOKSORc96G5KxjRBviNNkIOHmbAAAAORORUPpme93UrdYypRxT8s6WZRVcVFKfrNabuw2AkPT_4-k_m3bftvw8aMz8j3d67ieuvNaO5-x9wj6hu6VuqduykCVbAmTZVWBMEQvbwnpBlT8Cn4AXLqjiDa8Q2GAoAZKsRrY6qMPp7hN3Dis_6U7_PNOYgxeri-8wq-YYc_5-1wXzKvfeCyHzTDEmOOP1vN7e7HyICaie5ZxzwTlhyvOcAUMizhlxPo22LIquaY3UeZEHF2xAAnAuMJmNXZ8VOSZ4k-QGxoZmekPZA4zDofU2AKShn6q6iFMkAq1N10_NvjVSBdtX8xUwqMv6-P4JeptCkEYO_RiCCzYuzhdvvfP26xevHj26k63mH__Fp24Kq7OVoFgJOgyuKk13GExRogtu9BFDlmezug7BxgBKKcHADlPXjzLX58drKUSeZVwwwQQKURaFVpkpc5aYYkJzrqUKHud13TR-PiuP7x_70eG4FzrTZcVNwY1SAoiQl2XbtEZnypjgoZovSQqPbHZ0NF_MGNJmd_jysy-_-uxT2w5xiikxxjJiHImnBKf3H3zr-9-JfujGvqjqx2-_NXV9iolLsahqHJvDvhntmGUlEl8slnmWD_3ej4O3NgVkXLyJb7lmymd1sD64kJmCGDEQMWAISSkjs9z2AxFwxrOyypZVGEcMyFiSWkUXpWJVPSOhbN8BsDegqTc7NCBTmeEchJDeWiml4CqGSJSEkEAQPXLB6Y02mzElDUMn8wKIpxDIWyBIMUXvRZlBSkIKdI4Lzii9IWIBImPAKHFtMAIjECpLERMGTolxXiyOQ_ApIGcESIlzWWRsCBSRYhJKqlxGFxhjMstTQp2XUzcUde2tVxwYS2Fvj1dLF4Lh-eJ0eej6oztH-aIwJAWwItPNNNWVUYn5tgXQXTfxQE0Tjtcr4vlHv_UjLtRqVc4erO6dnW5vNiGlalls9vuby-sIbLT-8tXuZrvHFOvZXBp-9ao9WS27ob-6Okwhds2AAvqxHdphioEkd93UNW4_9ttm5yc3-kkJvt1vP_vsaQI6uvjxtnnRjs4H2u0bqbKbzV6URnDa71ohhVDKxnhxdsqlyJU6PZ6JIATXm_3haF7aPqzPjtcnZ0WeA0dMLIHUUk9tKEy5vT3sbpof__DtTKpc8t2uc9OwWizun64JRDKmG2yes5ToaruTQqcULjeHhHgYbAq0WpbO-_Vy3tp0cjw_PaqG3m027WpV7zZbo0RESFO6uDMDjNFHIYWU0k2THcaL89OyNu1hUJopIQwQI5qsq_ICmJif1evVItiUkEAQcKpndbffF1opKQLE1dnRk4uzd89nw-XheLb4jW_fLYU0WiSMWgkCSm_wxIys96bIXMQ3PFAU3PowTJZJtdvvTVYIJQhpfxh-56Pv6QRPX17_X3739xJnWzvlpeHw5lcKDsN0tW-eXe0C8eeXN0hSZ_nzl5d9P43WDdYdnx4rIdHaw_bqxYtdN7TrsyPJAWOSKd7cXF9fbfqmef-tJywipLSYFfOy2O279x6fL1f10bp--eo6WD8ryuC9n9yDO6fPvnqhpKqqLDP65Hg1q4s02aHvyyIjoKOj1cnRmhF9_8cfVpmUDBb1zDc3Z0d6tSxP19UP3n_4d3704XvnRw9Pl9__1uO7p_MHd9f_3d_81g8e38mVvHu2vHM8L40pc4neM6QEJKRERK3kYbDOukf3jwWT4zj9059_en-xiAIGF15ebuZHSx_iJ5-_njBNwH_5-urKxS83jbqzGGM6dF3wCEo7AdEoJliQxLkgTEM_bXaHZ1f7bw7txsHVlG5i_OK6cyG-6rvG-sMUnKBDCAcfno8TJB6FJJJG6RBp8t7a0E_oBMcEdsRKZ0WZaUSPuG_HfW8ThANSEuK6Hx16F0IcR0EMCRHJGCMkX-rs-tCOLPK8cDHyKOuTwh-823dJgJ8iICZEM5Ngo4oYQwycrEPGMTqffBQsYe84pThOXDJMkQETnEmCjFHwXtd6bHsl1DiMxawMGKu6Gvvx9OGFbdrovOT8zXBOkkml4hQIY0QMLuhFzqWimFhKGDwnoICMKAEIxTnD4L0pK0pEARGDkFxwAGJSSrSeKBEDRAQiBgCca50rY4hxAFI6Q295wuSdHTrGgREwDiF6oqSUwESSMWU0Z4xz4a3PypxLhZiMydBNMWB08fjxu-CD5vT1N8_ffvd-c-jbthOczRcVI1avj7y13W5Xzeq2n5RWOsuIkEuhpEgAUkKZl8QFISrFqyq7utkoLU-O1pwzruR-u1_OytOLs645HB-tvQ373QEoAQfGBaYISHldde1YzSqulevGGGNRGo6RC5rPsx988OQ__V_8gx--_6QSSSaUnINgfrKtnSKSFGywE3EZJfviq8sc4p_-7Pnbb9-tcvVHnz19HafGujGls7fvfPHs1VuP7v7JT351dXNjTP7y8nK5Xjs7VVL-4J23OJOvN7s___knj9555-OPP6nyIkYvQFxttz_60YcXJ8fzsrp9_qrg7MEqu6gWZZmVi3xqp-YwPH169a23F5lgH3912QT8r3_56cdfvpBGC5198_R1PitfX92GhAiurIoP3nryixfPRh-BMyWlDb7vp4s7x58-fdlsbmx7SG6k_oDdKMaQS0logx0ECBDcuzjeHhIykc3-vf_Oj198ffPWw4vb7f6m7cT_-B_9p70NKlMJqGmnfrQhpsn5GAkAGONZpsY-TtYLLYAxpZTWen9oqyKLLsxyUxU5SxAxGi0E594HBsCA-xAZA6W0kjomHGzwPiZMUsq6ypWQ-32XZzrPs8IoyYUSAlNiADEEKYXgkgmOiACQ54aIQkAXAmMcgVIIJjPWBiIKmKQQBMQ4CyESJWVUIiY5GybPpBDijeUu3drrTBQJGGeMA8WYiMBOPqQUU0pExNlkvfORCCJGAgacAQPrAyVyLnIjE4OIiXPW9UPX2n3Xc8abZhwmizwlzkuT3ew6DE4qNdnIBPmQQkAuBOccgDtMSIkzyIqMMCXgwY0h4IRxHCdgLAGElIAgUXqzxiAiB5aIGGMgRNe1SmvnvOAkuYhIiAkRjJIhxkgsuKAz0zZt2_RZVnLJYghA5KybZSum-OS84GKcPOMcGBRFBsTysuCcdf009GM9KzMtJ-usdQGjEFIIwYi0VrnR1nmRy8EGKYX1vp6ViMnZaRpGDG6xWI5Tx4E444yx5ek5UAreG6WGwcXJF5lp2lGWRghxfHYiOJOZuX_nLuNox2F_vT25_2Boe2Wyfbuvytnp8SmPOK_q3PDTqvzyi2-IfF2b57_8dLU-3XeDCzj1051HF6PzKYWL--cUURv14M7FMHqdZW3bEZA2us4NEO13DeMcfdSFEYJpIZngTPAyL6RS6-NjrTIu5Ww5l8acnayr-azvB0LoAi5mK2_9Yr1Qhkkli9kchKxni8XxMqvq1enx-VsPLu5enN-_V1dzG9zV7c67gXPgnCngJ_fu333n7dnRIpuX6_Val9mrl7dSpIfvvltm1cMnj4rc5IUxs-qrX_7qy1_-7LDf2GFw03j7-sX-9kZnmklezuayKKwNWqvZahmRC50vntwZN03EJAVfnDy8evrl_W_9IDMMifJ6js4iUjEvVZGnkKJ1FBFSlFJKrVbrs2no7DCWiyMQwrmJIwqlEJPQRmoT3EQB81md0EfvOFecC6mLGDxjwCUHeFMLIEasXC3DaIPzxWJOESMQEwKAmODJRiDgxmDw4i_tY0xKyYQSSlKIb8jWTMo3pz0vNERMAREDKG3bTkrJFEPkuTaKc-AgpIyRMEWMQSnNGEhtpBFCC-dCvZoLLTHGqKnZjMEGl0Jp9KKa4eDXx0cJcTGvjNKR4P0P3iJPx_fvVctVHEEocXI0n61Wy0U57tr1PDs1QkUhjXbBk5IBoZ9GkUlVFgRpstM0WVDMuqndtqoUtze320PnMSXGVJ7trjdEabs5EEDfbFOE5XHV7A8pRamFC8ik2g8jJep6d7v7mhiSSO3Yj93IOAMjtrcHzsB6V9XVzfV-dbrY3Gx2101RaIhsGvoQ8Px8Warsw19_v7vtYjdgCAng7N4pARZZdvfuCWNcCnb_YvneOw-Gdrx_djIrs_v37izrbN91YOSrl5sXX10uVmU_uOf7MRMp9SHEGCidHy8Ko2NKkw2LRV7M636Il692s_W8aQ4hJZXpbcPv31ndO1umyJRRp2cnirPSaGddCp5xWs7y45OjzXVbZTqTQjHBeFJSEjAKkQOVpcrK_E0wIVMi15K8nZfZ7_zV7_39H7736Gh1sVqVy-r9u-t1pVNMRotMK0wxEfmYZnXmfJxs6K0LMWFCzkVEch6BMe-C9z5yNtfy3Xun7987ybVuJ_rjV6_Ozs_WZyffenx3nhcmKw99_-xqe7kbkMvZctFZx6UCKX2M7TTFmI5PFnfunSxn81KJFze7z5_t_t3_4K_5bsp0dnmzPTtarJb12fF6WeXWk1B05_QojE4insyXH75znin1rYcXRa6JYFlXUvG6LL73m9-B0W13h_OTk_li9uDth_2h2e33zo4U8eL85INvvSOZ4-Afv3Uv-f7XPnjyt__qh3_9W3cvlvVvfe_9d--sv_Xg_PH5el5lpeYX63mp6ahQR3VRC0ExqYR1oQUwQp8CJsJuGLrJ7ZrhbL0QSuS58cM4m9VE7A8---rJevnicit01fr4-J2LzfZw3U6bobda_uLL5192TS94lzBxaA49E0KXPHJOHHIpPzyZ6VzqUnsX7jyYEfDbZloucqRYlJyleHaRtZO3HiOmpu33h6E72GkKU_Cbph2s67wDw3XG2ujbzoIgopSAdKE5hEiwb0PKpRAJY4CIpASv9dQ4AOIRQ9uzREJIbuTgPXqczbKvr2_zsnQ2KGOMltrF_qaVVQYZTwlDIK05Ic5mhVEcEx1ue-AYQ4xTgIRgA0yepQDAMAZIAEyEGFMIPtgkRQikuIwhhIDVYjEOVjIZbWBCTO1BZZpLOQ2T1G-Gk8SYjMEJwYUQFIADcCmjc0gopIAYOQcC0jpjDKXSbhxNmTESFLzkDF1IMWVVqQRHH1SeoQ1cSmCcgZDapATSyISYMKQYKPpoJ0rIWTJa6Twb-45SCt5G702d2XE0eel90Hler9e6yEkoBoTBY3BMimCdlKw9bMYhLLLZMI4xpRhYWeUssRCtm5x3br5cIKeizHbbQz2rpZIXZ8ecWPTx-GS9221zo-fzUivBGVvO54woy3Xf9Zk0TdtppRbLhfduHEZiSRlpQyiLcrffMYD9bsclmCq3k5OULh7fw2nQhp-e1f_R_-jv_c0ffrRSwnDJBROcTT5Mzh_a4Z9-_upOXUTieZ7dbHa_-PT5W3eP58ezBw8vvrzp_vBnX7_uRx-ps7G3dvN6w5V4ebnJ61prE1M4PV2v1rNh333n4QOjzNOr2z_8s1_euXvnZz_7RVEWKuMc2N_-N__a5upwtpzdX88_-fTpZrt5dXlFyH7z--9pKZHD7bbVhV7kghV569Pvf_l6309fPb0ap5Av58nH9b31FEO379t-78J47_QCHbzcbZq2DT6GmCbvgGi9Xt9eb7vDHoPLy2rqRgGcXKToSaux31WLIwA-tAO5wJn44Lc--tVPP9293n_3o-9-8clXR3Uu_t5_-D_vpxAoxUTEiDjjUiQGznkiiBi0lCmBNHwYXZYZxMiAJIM8U3WmF3Ve5VnwAYikEgSMM54YXPbTzCitteDcxTA6XxaZNlprLrhIAAxSVWbwhqQYMMXEJZec-8mO1lvrun5CAMZJcCElC9FzIRkwTCi5VFpLxRHBx5gZjYlhTEpLN_l-CnlmMOEbyCbjwAVYGxljPJmEbzjQPiYigMkGqZXWEhMbR4sEAYkLgSwqaThwTIQJTKHGwSXOGGPdMIIQk3dSKxKCIwXvQ8DJeY_IiPsUJAePETkPGBCAc6G0IEqTdc7HlBKXHAgEZ8AAiGzvpFGJYPIxxIh_-SpKjDFKaegt__-zjJjAGBiAtz6mREBIpLWxPigpfYxSy4gYQ-BcKJNrI4UU--1e5UWYJiBq-gYpKSWLupaKZcYoKTHF2bzA4JnigqkiExjjvumMzkxmtJSMizzXWilMxJmw1iPA0FpMKCWPwQOCFLwscy55Vdb7w14yZfJcSH57e7M6WQvGGSdd6DBMiFgfr7My85Pt2xaADcM4Dn1mZF2v-rGPwUuthGaSs1oZjOP58cn19YZLVgkuJXv-9CmnJMC88-3vz5f58vhoe3WD3imh-raz0S1Wi9vtYZi6siydm-rZzGFoG3vnzsnYu-ADlzzGcPnqsj0M3vtunEjK4ANx8MFXq4oJeej6al4dmg59yIt8u7d37p2CojzPD9sD48CkaJuWKa6URpZG64DwsGt7HwLFvh-effp5s98GGzIll0cnCf3m-tK5cTafo3W3231V5kerZZYXyCFEVJw_f_ry0LbPPv8qjdP8aI4xoRtjdG5ySrBuczt0rTQqhpDX1fHJOTF27_4jbVQKqT00ztqj9bEdusXxot1uZGGyupqfno59P3V9uVxM7Th2veAQI0oGYRzy2ZzxxBiNbc-MzIu5t44j6kxFH4hxIGQAzgYmSFUV-kgUGBdvllVGHGLkSscpMA5ccAagy2pseq4lME6CfD_K3DAuKUQuBXAgiikkIBKRgDFQDIhBIiAUknMuCQgxQYyQUnLRR5dXc844BATgxFOYJsZAlUWwXioGmDBGzZWbJkZCayOMEspE74WUi3sPZJTBD85ZFjDxtL_dbQ5t3_XH52vyIQa8s1ww7yGSlHJ1VJ6cLI7urTW469ebbhjuvX1R5UVpZDfhp9vdcGjaTevGngFFKdpxEKVOInGhx6E7NL2dpm7f7bvG-1gtZ6YyXXMojD7cbparuVQCONjRR0_Wh96FxcViOnRutNeXW6VYNa999AmTAnbz1UvNS4qQYhq7xg1eGT47rsfJ2346uTj-1lsX0ftxws-evlqusmlImVb7202YYtt1lFJmsmkcFTdFkWUm99bnWi8KDYh1ZhiFe-cnkoMgEIw1rRsObVkbCvH99x_Nl9WjOycPTo7-yvfefnV9EELudg0HFjwmCXlZAIG3o2Lp-HhWmqIu1Z2TnCfw47Q-nSekPFMSoN13WkiTqehiWdXD6I5W8zo3iUGeaaGE1kpl0mjJgGdlKRiP3uVSMUZFrl3vfvyj7ypEJcgoWZfydF3mGhix4JxRmnMOwLrRh4AYERiTUjHOMYbdvoFE3ThdbQ6TtTdTd9hN33v3rdM8TxhbF59ubv_08tWL141lBEoduvHLL1_2EyKDb15tRh87714fOgsJUyJM1rnr3WG-WnClc6UBCTCtZ2UX42ld5_VsuaxXZa0FwxiA8NH90__-v_nDx2enhrNVme96e_dkVhX58bJuD127O3z64pajvXd-tphVY9O8ut4Yo4-W1YOT1ePj-flqpph8fHH8-P5FDOPrVy-Gafzt3_jB3aPFWZ2dLOaSMMVkihwgMhJK6QAiIAgihFRqU1SZ5ipE4owJrbJMcikmFze7Q11WRV4lSkrKcZp-9uL1cVYWs5ITdyHwjEXBfUzXzbDZt69u9p1PTUwdk5-_ur7u-61HB7S8fzyO8cN3VohQi2yaYiUFMXXwvpnifohkqdJMcHZ0XGku_RgwJmdjN8Zp8i4l61BmQlaSAcUUXUBK1I2Tj6kbp6ttd2jGYRiHybWTQyb7fRdc2m66mFzEyAgJmR2sEMxNznW2yPQ0TFNnz945jw5zIe3YHdWlUTorTHs7MILVeXm43I-3DRcyRcqXmWJcMZH6ocoykYRLaX-7C9GLTFIiQOIYkos8JAGJ3kRufGJCJAwJkXOOmCAlOwyZ0WVV2WnSUiVEnhIQuKbhiMFZIia1Cs7yzCR0WVbEEBiQUMo7yxnosgIGXCjARG9KwM4qk_m-h0QxRmJCCg4-KmUihoSeC8ESQCQmQEgFTDLGY7BCK0wxOp_nZtztMTjGEqQkOPPO6qLgAME5LgAYy8pcKUVAUiqlDXFCa23fT32XZUUKSQlhqrxvDkVR3Xvn7jvffnL5fHd29yik5Ky9f-dssz0wIq0E4-ztd9_ZbXenJ2uWcOzGWVGkFO7fu0BMMfqTk5PtZlfX1TjY5XJ2Ol_04-h8NLlOmPIy8y44FxIE52IiCCEpyQXx4EOWGQ68mheaA4coOQhDD89mf_ev_PjJ_bNaawGMcRYIXlxuf_bp80PbNYN9-87qZLWyIX7-1Ytd748X2cO3ztuD3Y3jL5--vGx6VoqoRD9OfvJMsvVicXt9Y4T8-utvqqpE75KjH77z1sm8fr5r_vBPf358unj26kobOaurYMOPfvy91LT37x3Pl_VffPbFp58_15le1NmPf_DBaTmLiF-92szqbNP186rYT-5__3_9XRfC1693NvpdcMljYWTXjVevNpP1BEkJ_f7jx6-uLj0gAicXg7f1cr25ub139-zpV09jcEpw27Z5ZoKb7NjosvLkEZniKnqfEE2hp8FVWbGYVc-_fv3jH3zrsNn93p_-hfgH__F_ElPCkHxAAqa0Hm0Y-6maFULwthm5ZJmWjPPJOy1UjHG9WmglQvDvPDrTIGIKdmqLLONCZJmWQnDGFlXGgAPjAOwNriHEmCIRECHlWmmpgFiMKcsM50xqAYwdepfnxpiMGHcxEKNMK611344YSEgZEDkwJNJKOo8pEQOmMxURvYtERIzy3DjrEdMYAnA2TYEzxgVHJCYhxERAQnPrcbBW5SaF5D0KKSPGkNDa4HzITBYTcc4J-NCMUvOqzDfN0I1TSnwcp5ggEESf3GSBsRgxYsoqwxj3PhpjYkoJGBEEHwSTPrjRBi4gpiQYl4wXOhuG0Qdy1mpTuRCBc0xpDIEDEbGqLq11lIhxZowcBguCTZMLmBhnHpP1nkvR9ePkPAMCYDpXdvKH3UFqmTBa78uqpAREJKQIMSRMiVH0ASMyBoN3hckYA0iUZVmIYbfrQOLd82MmpFA6y_KEGAKWVbHftzxRnmdaSWOkd04wHpybFTMfwmK5GKeBMYaJxmFYHa3tNMyXtbNOGeWHiTFgknOjg4uMcwbUbRo39P3mYCdblaUQPNNymLr5Yh1j5CBSnM7unEut9le3xxfr7W6LNjx5764bB-vC109fHp2tx9A9OF03h-bi7unR8bHWospzF2MMblXXUimZ5XmeTePw4OLu0bySIa7Pz2-ud9PQR-swhjwXRBRD0FJ4O01NH0dEHwESpnRzeVMtKl3kmLCqDOMMMSEl4ExnmiUkBd4G4sSBuJRIGKKf2nHqXHcYl-v1-uhY56q92T79-qkdpno-D4mNzs5ns3m5AsKHT97LijxEv7u5Xa0XX3729WBHN_YREiJken5x9z2pRXB26g4U0E_WTWOM3k1jpLRYHTNOIFReFhf37i7XJ9KYejHPqlplGUFiyNF7k1Xkxqwo-v1OacYZSc6AIsPwJurDiDgwN0w6y3KT2WlMMWqT67x048AZKSUxJkI0sxk6zziliEJoaXjwgXMu80xKGaMnxrmUGALEAFIppRMlzkAoBZA4JQAAApZAGpMQCROLRIk4ECECZylEmWdSQLCWMyEYcC4S4Ww2T0KlaDOtGUdCwohZOYsYEyOpjZtGpQXn0HRDZkxVz5UAxmW735sqiy6sT4_K1azMstOHF4t57eO4uT547zy5__aTX67r5fHxvPH97vpQVIUb3dGjx4_Ojzeb7eRxtVwSphD9Z58_FaOfL4vlk4ubr1-50YWIrvPOprHv0dP26sa7qDIWMarM2KnpNns7WJuCVhIDq-rl0DQ4eSEhhDRZlJyJTKnSSC1Dn3SlMsP6wUfHk-VS5ELokzvr_W6HE8tU2bdTSslFzKXq9_1u33zz4tU7b98Z2okg9U03DW6zO9y9cyoFjP1YlqUd-tPzM4wOR0fBX5ysOeG909MPv_3uItNFpgsj2rH7809_5oOKkEw5-9Off_X2vdOTeZkQvny5G8ZpNq8S58BYuSjni3nfjZpEHAbOpGTi1378MA3x_nq1mtXRpqI289Wi2R0EZ0CkpPDBZXkuJX94cUqUYgghJsEBBNdSpESzqgQSw6GnGJKPDNJb792ZZeatOxenC1NqlQHO60ISCgABnAMrMiO4IEwBo_eeGLMuGq0Ko48Xs9wYzfhyWa3n9b3zxXcenqzy6qIq7Gg_H3b_xR98-qtnNy8O48vX_dVmqwoTpe5Hq7S53jUvb5shuqLODsMUGIWIweO8KHzC1Xym8_x8taizsjZqnAbJ0r2zxWK2wMkdzao769miqGdVfu_s6Kiu236KdqrLbFXlT-4dLcqsyLQQrMzMvNbvnh_dXSxYCO89OL93PP83vvfO9x5d3FstlnWuwBrJvv3enfceHh-vyntnJx9-6x1sG4fRNc8enD8-Kk0hpZAcBCMugTOU8mDT883hq9utEOzrq77r_BtF_c1tZ6QQXGy3zXbXrFcLhqzvu8XRvDBCKfn-nRPGWD9NShsknDw93xwu9-3NvifJmsE13t8e-n4Yzu4elbNSaM2USh6N0W5I23baRZdxMAtTZyQSOO-jCFUhCaQUYkaILtV1XhnNkKELw-ilkSEhIqFDTSkQ-TFiTMQgRQgxJmDOu4COKxlicoNDRDe51E7AiDymlIhY7KJMyTYjYuIaQnTYDibSvaXqWws-xkjD6KqiMqXOcj5sxzovhGB-aGOIZGMugCSXwKamr49zXejd61sphaiUbdybrC5OgfvI4U0xl6cQjckh-OR8VlQskWAgAASXKabFyVm73QVnBZeCgR-HZEeVZUIrSJgQogtSaz-N2hhvbQpBKBWs5wwAOIYotEqYiCIkSj5oY8h5JgQhKqkxRMZIKhkCQkqUEIilSEIqEgpDyIrMTZMUKrqYz2rC4N2b1hBJrTAkrjRIHu3E0HMmgMnz84eTDfP1keTCOZSKYwzJhfX5ClMoqmocPQPijBklDKnB2rbto_daid3hAJS4AAZMK9O0HeeguTg_OwZGd85P3TjkmXn-4sW8yvMsN0YApdOTY2uH20O777vTk9NxHMqqEJJrrYQAzkBnymOEFLXSQ9-XhS6qqpxlWkCV89Wi_Lt_88f3z45-7VtPFpnZ731hlNTCxfDsarPZHXSuweRZrmdl8eXXL_vJcilcCutZnmL43Z9_8_EXLwYfTh-fRue3m6a34-npMcS4OzRTNx6a3cOHD8_Wy-7Qf_fRvZP1ahrd__13_9hOw5Tor_7w-4yb7Xb34PTsYlGcLkqP_Pf-7JfNbmSKHT887rbNTBglRFHnu81eatk2-4nJ33v66ptPn1dHx8-eXXMhBImT02W7ba5vD57efIZHafTf-v53Xm3bKWAIwY0uyzMh5e317fJkNe07JYQ9dFplITghwDadqow0hiNkeSW0UJUZfUBP6_tnGO3t1fa3fvP7N69vXt7eiv_BP_pHDCgELPK8H2w3jkLwqsiNUpKxTPNnLy-PllUImBmhhAQBwEhQqstilRtGaCQXXHMg7wPnwjqLRIkIMXEuuWAxEUtp8uhjBMa9T4xYIubf9OUh2ckjYjcOb9KNgjOjdVXlkksMkQPL84wLLiXLM82BBx-UkimB0Zogjb0lIim5lGLoLZeMiPkQZaYJgYAHShzEMDpMiTgnDgmi9xgRhmGanBdKcQFMCe8whIAEUvDwl0_xAAREMMbYj5N1bzT1XCoRXQguAIjEWRKQlzo4BEyj923bMc6QKLo3fi4MiN5FliAz-dBOjFPXTcQAiYGSoxuUVqP3MaUqM5AYEAvehUAxEeM8JsIUrXMAgETW-ZASMRZ9AAYJGAOeEDGmiKiUssPEGJdGa85josRAaWVMxgTXRrvJnx4fT6O9c3xsncuygjG22W6F0lqZYUjjNC2P5uMwSQ7aGAGibbrcaMZF145ZbqZ-OjTDi5vb2azqp74uq9vNFRElSHaaqrJ0k6sXc8ZYVVazqkoRElJelYxLnev1_Tvd4ZAgJUz5rMwKWVczN_YXd47t5Pru8CbmdffiTts0u32zmGlAZAx5CJqzaRhud-2dtx65ob95ed0Ow8O373359avZvLS9dXZKMX7x6de7w9YYLZjKtCFif_zlx28d3-OSd-0wBb88Xtl-hIh2cOgiAEQblNZnp0eTHf3kuVDNfl_P570b2n1_eXWtuHTOTuPEOM-M3r2-DsG3t9sUgkDqbjbBuRSiYkJywuCF5nYcm6a99-hetZ6fnl5gCDyTs7yegvMuQPL1coVou6m7ubxtmn1WVqrOb1-9kIJP_TC5ydv9fvts7Paz5Sl4EkbqokwhEsF8tb55-bI9bHfXV9vNTggWgDnnbQwmM8rwRBB9DFPw0_TmzvDjUK2ObdsYo4iI-XB0961-vwEMfnSIUUltXVjdeQuiA4IYEAiJyI9BGw3pTV835vN1miZKERJFn-YXd733nACAMwLGBKWkpWQMlMntOAjgnHHBGKREmPJ6ASEqAW9ieJIBZ5CiF0YLLlLwjBAwmbJmAMAE4yxaBz5wrZUxwfnoJqkqDEko5YdBZVlMkUJM0QPjwTrBOKTknddZFkEwzvaXV4zB4dDWeX5zff38yxfdMBiTCy0TRiX0ndny0PTNoTu-WFMkNwy73fjim28Cj1lmrp-_qrWezytO-ItPfqGU2h9sv2nyMx1C4pFNw8RMIheGoVeZyoo8xRAsdrtWEAMJMaSsyigxux-AeU5J5JxxRYpMTAhRFVnCWBjl_eS6YDIZQ3Q-Ht-fa0GSISJSgrpWFxfz4N18Vp1ezDVFb904jquj-c3l_uLuepqmsel1LtD6vNZ1XdhhqIq8Kso42UyxYMezo9mDe2do3Q---0SmoJUA5PuuaQY3jNyl-PL1pgtxuSqLvDgcBhDq2dXm5GQ-BS8Ywyn0hzYOk4hRSy6lvrhYF1UGJJ33l9t-Nivv3llASHWZu8lRjEZrwakuy6PV8o2a2iiJIYQYDRfjOJ2tFkbJQsiMc63Fm2xelqvFMj_L8v2-PV4UAqDvu2WhBQNAYgw4skwJICaFACAkNoXYDi4vjFJqci5iQkY-pkgkhL499NftcBvGluNnX990bbtp-hfXe73KSfJDN9zsOxcoACUpP_vy-a4ZVsdHgRgCU8Azwe0UxsGW85wr8-LVTYjh1c1tQH7Yd1Vdf_jw_uT9ft9OLgTn81zeP5oHBhgjcA4cpDZaKwTSSkophNZ1kW97W1TZajlLlGxnhdbEhRIp16LIRV3kQ3_wvS2KSlTZTz_75uJ09d0nb7314K15oRmkELEfrOf0i97_kz_46U-eX_3i2c1ffPH6yeM7F0cLnXBeqABQZcVqUXEiKfkw2NVyDgSCw7KapRDboS_KYhrtq5vdssjc6HbT9MVmK5az68Mwn5UyN0yrk0erxVFmlLQBRxe9gBiwXlRCqm6yVjAyEis9WPtN75BToGQISuLeoQLuI0UuGEGICRG01NooZ0Owvmm6MAQ7OhIkeJZcYBIY0JvtkVJkEWPfc8HIJT7LgYhxRpOFBEJxUqRSkpSmpuecW-tSQHKYKdE0NiLNq5wl6LtDXRf1LB-a8frV1eQmgcGH6DERkHcpJGBc2M2otGn7Dp0NDllG8WAFUDyMsbeKM0AETJEQkChGznmKwJQUkkfrJNdSqRjiOAxFNQOM1Xw1dA2LTlAKLtWrhbeWERAiYeCc-2nKTAbJcwABLHgnxF-iwFVe2GHQeQ6M80QMITmrlWAJCIABT9ELJVNESKi0AiImBGESQmDwRTVjAG5yQjJlFDrPGCVEIQURcQYMOAYvlWTKnN95sLl-GZy3w9C1XTUrm-3u4sEjpbOh7auy9lM0RcnIL1arqjbf_d67zaHvvc2MwRgYpaoq69mMYdTaMM5Pjo9D8LP5zIewWCza9tA27cWdk9lsnhl12Owu7pxNwzAOVin99OpmvZxFjO986203WSVEDME5O_SDEPzoaIUuxOgXixnFkAvx_e88WRTyd_7KR6WUgkRM6elmc-90BoJ13djZaXln3h78V69u8yIvjerb4enNrl7XTsAf_-TF9b5JZf7Hv_gyQppifPX1lXMuJOJc9k2727RIiJTunp9AcEM7Pjw7-eDBvc1--D__k9-Vhh2dnLz15N6f_PnPaRz_6g--887p-nw12_f-T376KxSy63ql5NVmR5FXi_ydxw_Gfijms8vrG8V1NPL_8a_-PAZ-eXVrilIIxRgA4vXrAy9V8hgxEKVg_fnZxc9--QUJvm8aOwxNu4sxlkXOCZrbPU-JEVBCTmlqmsxkzCgiXs-WUvCbV9fZrJisY4pnWZlS5Iz_6EffRYCbmyvx7_-v_uOEKctNisgY1JWZ16VRihi50ee5vHO6fvV6P5-X-3YqC3l-NBecl7k-mmW54BxASJEoBaQ3jUgOPDOaEhsmD5xNiN1gBxc8ptEHLiXjPKbkQ1RKeYyjDVVpqkxLpb0PXTMIqRCxGSxErMpcS2mMPmybqsqNEk07aaP2Tce4mJwTXMhMEkDEJDhjTAqtfIhciWlySEAEKSaPyYWYEvhISMm56Fw0mWacJ4Jxcgy4NoqQXETgfBxtSvBmYQghxgRt2yuhIiTGGXA5jJYlgTFJxruhj0jD5K33w2QJyXlETD4iAaWYgHMkYowDJOtCbkxIKXERMaREGBGRxRCI86aboo_Bh0QkpY4RgQFAAuARY16U1gfAhIkAOFECYgQkhLTTxBgbreNSBO9JCCGND7EojQ_BTp4hSg5aZftNk-dZxGTyou9bYJzzxLmo6qWdJi14VWnGmEDW9QOCEEApJa0VcUBMwaezowojWh_z3AAT42DDMLrg9_t-fbbM8gK9r-azME3aZMM42WFICUym5rN5P4xT52w3SsE5V4LLME7OBslAMRib_u0P3gvDqHM9XxQsejcODx7cq4tyfX66PFp-9OOPtrvNvfPzPMvNrLy62hWF6dqBS_30y2chpuOZ_uzjr3z0s7Ls-wkIxn6qFnPGWI40jL3Iq1TCvZPjZr9fH5-Wi3K1WJV1jZGZoqhXy6abum5KKY5jZzR308SlnA7Nqp65cbLjpExm-3bcHaamx6GDGABBMPDTKBQLk3WHLQYXrWMpgbPNTXO43rx--hIYm6_W2-2uXlZP3nr34vxstlyqLCuL6vXmevP60g19s91sXr2Kfgr9QAiLxbwQwo5DdLbd3nLOGWdT12udMeJCqvNHj3AcXNck28exbzabqWva3aHb9SHFvK6kFjF6Brxc1EyI3XbDgWW5dNZ67xMA-jHLCu8scZ5SkpkUWlk7lfOjvttlWQ6UiBETPAFHjEIqSJxBBKDoA-MkBMQQy-Oj4D0gzs-PKaSInglJERGDUpozHrwnREIkTJCSNAaRErzReRAkzqUGAK1zLmRKmBARg5SaEiiTvfH5Tn2nyqyan9jJamOYSCFGXRTAeLGYBWezWeFtEEJHb_NMxBBcjFJpClFpMbStHUY79HVVUop-Grt-cL07HHo3hcfv3IlhPOwOl883rR23-zYTQivY32w3L1_HFLv2sDg7_-zjZywJ5521NrJoD95OyCjKSrrBuW5UQo3NqDMzX9Z9M-S5FkL242iHHh0Whc6XGQfW7nqiJDIdHHJQYzfYZiyyzFsMXbrznUfdZXPYjw8_eHTz9WZxVp386D3s7EmZl0oTMJFlLEAMJExmsiIQJRuOjo4317sn33kkuZodVZKLbrNLCVfzar_dnpytNWNni8VH33nfte1v_9oHDy-OSwlhdNqIwU7t6EaHF2_d27VhebSsy_Lzzz8HaxUT19c7GRNE__j87HxVlyZ7uWnfe3JeZuWinh8v5yz5eVWslhULOK-NUXK3HbLSCEhnJ8vMCClllqnVrBrHYVYVWqjD7rBczhP6KsspgeDMv8kvBr9c1BzApbg6mi-yfD1fVJmsCw0cztfLru8ZY29EKJmRgnFjlOAUEjSD21ovBG-aYZr8GNLogkusGX0b8NW---RFc9un6y5887yhUjU-2JAmQo_Q9TYxZgNa594czrzIzy-Ov_r6xfLkyMfQNH3XToduut42m8E5jMDATm6xXk6Ty4RWYHZ946eRuECIIVDiUhT6y5vm2fbw0-eXL24PX7zabZxjJrsc3Nc3u1fNuOmsNJoLAwKqSheLYugmUFCVRphcFhnjrMgzF_D_9ctvbp5dv_fo3v27d8oyIyGs97fT8F_89Jf_-e9__Nmr9uefPZ9ArE-OTo-Xw243TpOPeH40a8bh0y-eHp0stYDlLM8LeVQV_WTzIksE-65rx_Hi-EQkCaDKuuqs-9PPnv78-dUm0Ncvdq8OPUg-BlRZ9urFZqXMYfCfvL6tyrxzfrGaNe3okTzwLOO5UgiusenYcK4Tx7iL49ajZdRY2wXfTq4ZnPORZZpYHNruqDQ2xujxTcAY-1jqlGJIo2cMOCFFUpWCiIDAU6CQ0t6aggspo00CUXjEKQmdcHRoA0SHAEIADxExEuNMaa2p2bdDN2peJpCg9M3la4o--IjaWOuFMQjACBJGITkTZJsJEKMPQnCcIjfERs9CZAwxIqSEiOSRAQMiJiRhwhCFEITJZBWhowR5lZF3jEG0LjpnjElIQCwhokPJebJeSiGkdG1jshxjTN4RIicUXMQQGee6KIK1RVH6cZKcC8Hi6AiAMyalQoyQGGEUnJNHkWXAOHBQWYExUMI39V_gTL7B_sQYA3IhlClCCNpooASCA1N2GrRS9Szr-i69-WeTXAg2m83KwnR2XC7X_dhe3L8Tov_og3cNyN6Gybm6quwwHq8W3tu-7Y9OVoAktCwzuayrusgFI6OEUpxTyjL90XsPdk2znNfovFHqvbcvbm73Z8vZ2HV3T4_3N5tMK-f9yxeXdVUorY2SmRaJsNDq1__6hxnnH7x77-L06Ox4qYSSnM_WM6T06dPXcyF3o3cxZmURrP-jn3797qP1fGZsin_xiy83k28n_82LzXKZgxTPnt-82rS9mxLAxYO1qXI1KyHFsiwRo5bq0TsPguuDZ0eL6sff-w5P8F_-sz_ghhbL1eP3Hn_28ed1YFJk3__2vbJQl9vu4-dXnrNsXu5vt94HQLi4e_I3_8YPRGL_9F_9xfPNZlbmnun_wz_-l9Z6qWU9r5Ng_TAhImMgSz1i4jFNQwdMJfQny_nlZnfb7CCRloIz7p0_v3f27OtnFMFPViiRMDJO3lqh9DBYkxdCKvJh2O4jBhDqeHVSzEy04_ly9e0nD6-uts9-9YX4D_6Tf8gYGcmcTVLwTPNCC4wp-sgZw0BMwPHxkhOblZlkrDASYiiMwMkTxqrIIBEAz3JDBIgolZxcMFKRYISp7SeTm9HHvCg8xmHyXHGhRMAEQIMNZSazTARgGBMXIs-N80EIPaszzvgbNYb1Ict1StD3I3BW5IYLYZ2TWmFEAhpHa31InBHn_TCZTO2bIRGAkS7EySFnLKbkIrZdmBVloAjAHWJABGIA0A3jNAVEkrkMkaYpuBBsiN5HpQQBUALOeSASSuybPkQaxilEREraGEzkIg6jx_iX21hKCUC8KT0LIUJCTDTZoKrMYVRC9MOESKNzJtdKKmsDCE5A02Q5lz5GH0IiIgAiCBGJWNf3fpiIUSRywTPGhOAxgvNOmxwxvBENc6UxRiCKwTsXeG44kxRRZxkRzRYzHzCb14g-YuCgrzf71dHCT85kGjAJKYWQPro756fPXrzOVDaGcLQodvuBAwsxDOOUSICAEJAS2XGSkp2endSzeminajGz1hlpTKYE422zm1VlVdWLo3nTHI5P13YcCmOiczpTWaHyLL_z4BSjd21fLeqxHwngyTuP91fXfducXpyPzj57-bLthg8-ePv3_tnv_dqPPtztmhcvN1mtj-Z5c-gSkWubal5G67_-9Jt6VQ-DQ2LIBfpQVYVSarvZ7_Y7bdR-21DEsQ993253e66FpaSlXpwulJDD1DprEzkGgDaWdd3srFKCE6PoGONA6PoujF5n2erkGCP6mJSUYQxCSEKARBQQEtNZnq9qM1uqvDh_eO94vdw1zevrm_fffzfLM-_90Ha__OSTtt2_-PqLm1cv7WFfzWdZNlNG1EdLbyfJebRDsIFxJVVBJMJk4-ir1QIQgp9AJDuM1bKuyoUfHGGaHS0kg9M7d3zoc8O7Xbvb7IlSVRVMccRgsnLz-pIBM1UZffBdl4BjirqeT5PlTFJIwAQkJssSfcDgldJ2sIwRE5IrRTGyBAkxUdRFFZ1nhCbPE1PEwPVDQqzKpbMuhWhMlmLEkGSWveGNKqM4cWDEhCQpU4roPBOQQmCcASUmBQnBgIGQkIgrRUSMMakLgiSYhIjIohA8ulDVc0yBGO_3B8ZZUZZ-ChiDEpxL6SaXa-3DOHUtlwwSmFmVG6MUGwdLkZHg-az0w4guYLD9YF2EH_3OX6tLuT6ZrY-XnDjLDSRGavbBOw8725-enTrrfvri8yqfxQQ8gspZwpRnlW16O3jgZIRQSgeXbLRZZiKmFCITHEJSHKZuJBCkpCJQjB022_nJanJBVqLIxNhNArgdBhytWLD5cn7z1evjo7kbcc1kUeuXr67ylXFAu824PKpmdWlk1rXDNE7r47k2-uho4Qe7vDiVxDTnldbo7LIsTo8Wjx_cf__BedsctKa__sNvq0SaEWAarCVKl9c7D3w32m078UJzln75809UYkDpve8_6ppxGKf20H31dCOKkhI9fHQSExW5uuw6QbEqlODcOzdfVAwg06bKDSWqq5oxRjFxzhkA59y5OK_LLNcpxGmywzSVRWa0Kou8LgtjDFFiKXIl6ky-9eg0DE4yWqyK-bxelcU49Jt-OpoXUshMSy0khkQpBUy9jX2IWaZVbriQSXBdmFzq28G2Y3h-vRs8vj50t12_6fr9MI4OexumyQqpbzbbV80LAuUDAhDGFEJwAdeLfLZavnx9eWiG0blmGFvnk4B91_iAEWjXjDJTD8-OXjzdffSdB7vRRpO-PtgBMWq-Df6zzfjFq9s7905ZXTAFrDTlrLyZpp-_vJ2IQMjqZNEa-Mf_zU_-1VdPv74df_Hi5mffvP7yevPPP3khPK3rcojsJ18-_3_-_Kt_79c_fHz3RGcFJgic_uuvnv7jP_zpp5vdZZfKXFntP_z1h19-crXftsM4QLIn8-JH7z5MLv2_f--nVVV0w9j1dn20uHm52Y2uLnIbwuQDE3y5mE8uENAU4iffvPoXn3-1d8kt69e77rrpEyci0Y02JayLbPBhluVHizL4KLW63B2QwJk0otdEIgRrWRvcdT9st93zfkqaOyRe8q4Ps1PRxxhc7Iap70ajecB0uW1NXoQQxqbnjCUIU-tMKSEG1lpmp9Db0EeQjBHF_QiTBcQ4etIgSGSMU4wpOvQenQMXuaDkAtdSJZgVWZkX7dXtcLtren_y6E6_aRfred_uZou6aQcuePQ-WpswUIosQp5l0Y9-HBMxEoyzBClJINFMykawHgMyxRlwISQ6L0FwJblQjBJ6l7xnTEC00TpAVs7Lqem7_WG2XPqhI4CEqahyTgQpcUpccmcdAOccKEYJHBAZJKUkUOLAI0bCBAQpTJkp7DhIrSkmTggJoxtNWUNiUjBIwICAUSLiQgkt0dvoo9QmeAtS2GEgIKY4-iCEKBbzFKO1U15VjJMQEoOzfVfN14IxH4I2WjLeN129qJ-89W7XNSpTY9eEEATXH33vfd8761zijIBW87mUQkl1__55kWVK6VfXN08e3CmNjsFpLVdHS85gUddGQW_jYl5mRgDjznmElFdzH3w9y1eLRXewAcPx-bHkvMx0XecSElCaleW9B-fCux9--Pje2REkmqyPEfPCROcvX28poffp46cvYxJ-Cpvr5vm2-9Z7Z4dh-urZ5qffvMxn2SjE4AIzuvXu_LTabNtMqHpZLMpic9U220aACBE5sd_68fsvn19xJr777v2__uEHY3T_u__jf6UK4zn8jd_5tT_-ya9OyuXdu-t_5zd_4EJ4sW0_ffrqgL6qFp9-8oXOqhijUvLs6Pjmq8v_2__n909Xs--9e-d0vcLkfvqrZ2ePTvI665vee0IOSsnlqmz2k2d0-c3XWgIpvVgttttDb33XDESY58XN9Y3RZn16_Pybp0IIRkkpHqwN1iKizgqAaGQ-m613ly-0ySlRNZ8ZrS-Wa0B3fnZW5Prjn312_vBE_Dv_4f_0MNpS6cKILBOZUYf91He2Hccq15Jzyfl8lnOKmZEPL5ZpikKKQovcyDchMKJEjCEmImqtL3ITEKWQkwu7qZdS-xiU0odD6xFjDFmR75vBFAo4OB9dwt129C4GwOgjpiQEjwltSFqyBERAiYgDU0rLLAMGbTsoKUAoG4JR0rrAOUeiQ9MrpSKkcXKTQ-vDOEZTGgRiXOybAZT0FJTRh30fiI82vuGL-JgOvZ1X5eT90LvB-YiRcU4EIUbGeTtMTPBd0xOAj6ltpsk5qXiMKSD56EcbvPNFKQOmCAkljxgJADFxEIwJ55y1QWppRx8oTZOlN4bfxGKMjIAJEYPv-okgxegRERgwEIyJlKIy0vnROs8AIlBECMEDgRB6sh3nstsegDGtlbPeh8C4CN4Xs8o5a9vRTWNK2G4PMUTNOXDetb3kPKUkpFCK7W8O8-VcKFaaDBOPMSlIbTcZYzCG9tAyIYEzKQQlMjIb-m65qIdx4oKXRg5Tr7RZrhbWe3ROSWOnYVbP-qFfLpdKqnFwRa7ffnJ_u9uZovTeB-eVMc1u-Nb33g3T1Gy6e_fP73_7cZUVh8Nu-_p26PuIaeqbvp_u3Ttdr477bpdTJOC_9tc-eP3sahom17m_-tt_dXV23B165zwwciHNFnOXwumd09nxsl5UrusTpXa_mwa7OJrdvNoBQ9v3SlKM-PpmlwDK0zmEqEzGBBitizwXjM-XVTGrmACpWRysnzxiUloxlpTRADD2PQlOGLnk5VGVVbOxt1IqXRSyMEwy29lpmuplGSkujlbr05M7D-8MfUdKExdfffEFhak_HATJxekFh-idH4cOY-r3B2myrMilFM4Ops58SGZe6VLrTNuhh4SMc0bJ9p2PLBCVVeXGyY4dArTN1N7uw-Rd0_Loh83GNYf-cDi999BkmS5K57wxWmYmxMQY45wppcuzc3vouFIgmJsmLmG-XGNKUqqjk9PRjkIKaTQ6r-cloxQ9phhVkWFIwXshZfAh0zoGJEDgHLiElIJzXAomSDLhrRN_SXoJKQYumFIKETgmZUzCSMBSIhCSK4POU-IAxAULiAmj4GJ-csoZAMC8WgAn58Z8NsfgiqKI1nMupRKIiBFTiMCYC4GIJYxvCuIhBAAAAFPm4zRopbrbAyJqo4O1WlKK8avPv-QGmpvd5ra5vLxs97umH-ZH5dVmb4nOj5fKKBxRl8YOI1Cy4yiEBvTeWhf8vC7arjdZmQizOrPeJQ-nJwtk6KaQlfnYdFpo8rE-rsbBdl1iCa1Lo_dZMQuD54xpxTGF5Hl0jnECwP3hcLyazVfV4mjx4ptbEuLtR-sy066fdttDWep6YVhIWZ59-NaTzc0W3MRCaDfbk6P5d374LRGwP9i_9zd_7e2z1aOz5YPVkWSkhRBCBCCP4fmrm3y2sCkdmqG3kQvx6unrprU_-Ohb4-i__9EH_-Kf_8XROn_nwydQJKX4dtsJJTKdVSeLnEgAW85rrU3AuFrUi1nFISkpMHglOPiQZ_nJ2RwQiFiuVXCuLrNMqUwrI6QA-ODduxhQaaEEV0rMTNF3zaPz8-nQCykYYGH0vM5liEbJoyoHAJFACim5YIwQqLPeMxYideM0jmn0kQSHRE9f377Y9IduajyVufrqeo-MbjZtwDTF1DQDNwIZMCWWyyMOnClFjBIlxvjm0ATOR2ubdrQxJYwBIwPhkxeCR0Dn0I_Oe7zaj4-fHHmZntqpDfHry33nxte7Yb_zJ-uFqrO_-Pjrm_141Y3fXN9e7bpPvnlFiU5XpUf--Tc3P__ypeBsebx8fbXZd5MlGmw89MNsXv7gg7tllRtK_9aHj3bt-E_-6FfPNs0__vnnf_rxq1dtXy5mI4piXS0X1c2LaXs1urZ99635oes--fTy3_7rPygBfv9nn84y9Rs__sHl0L-6ufnTX3zDlHxxuX16eXm8mh-t5tspfPP8JZdCc_56aP_F51_EKbze94O3Qz-KTJ6dLglIZarrRuCQqyxaKoVBxkDwbTf1Mez2k4uuG4cmJb7WYULj0uqkHqy_fN3YfWgPFi3dXrbD3k6TQ0wu0e4whIARoe2GYpXHmKbBKqGQWByCUDJYRItaMoyePPGMkxDgEyQOPhEKMzc-xNBPEBNLCPhGsCEoEo8kOS9W1dB0frM3iZ58_zTVcroe4zhkQpEQ29udYCn0HmJAQKm04KyohN0NNDkCDpLh5BhjjIiNlg_IKUVEIWWmVRitTMCACaliilww3x-q-YoDkHUcERKcPbkLIToXlQStNGHURg37XmcZA-5iBMEYFwkiUaKYiqpKMaWUcBwZE28elXRRJnTRe2BMZBlBQoxSMEEUYwJAxhlngpASAcYotQLGTV4A5-M4KaO8tVJJqWVw1uQFA6SUuJSr-bG3jnMWXSCCFB0X0tqpWs2KvGy3u6M799BPs8XcWur3NzGEajm_c_fs_sOzJ-frsiqE4iJTdV3aYei76fz0WAqhOK_r_O0HF8eLhXMjT3hx52SWa2unECcp5TuPH_RtV-Vlpk1e5lLrYIN19vzs9Ha3L0qzWC0EAedgCu367uRo_uDe6a9_751VoWutc63b3k6D2_WdkNJxePp09_L1btdOQ_D7zv6V33jv4uLo1avr3_ze4922--bl_uefvWZvMKPNFFxs2kEvsk8-fSETFGXeN0Oe52R4YbRg-uGTs3WR_eKnnymQSynWpgyd_d3f__T0YgU8_s3f_ugP_pufnR8d_fiDh-ujmeT6Z589_8VXT--_-8RzfPb0RYyRSWGdffvtt7_8_PPFYnF6XPzGb35_d725ODn-P_1Xfxg5RqDxMEYX9_1kuDoqSxhGbkRSYvd8c7SuhZRVpiMxouSHoV7N3dBrKfwU3v_et189fc4Sy4yBhOxNBDcRxSiYEEwaXfbtnjEevcuMWc2OBYSpa3_80Q_HaQBBf_IHPxf_k__NPzqez9BHREYpOhuIqDTZvMqNFILxTEtrJ0jACTgDxfnxST0rFHosjAouAIeqLCOGm7aVRCESAYwuSCGNMkBJZ8ZFzHIFUtRVQZECJusiE2xoLTFuQzBaJ8brovAxvLraIQMumIvkQ-yds84DQVLax4iYhBQIkBCAc-vDZD0wmYgwUfQBGPcJvI9EII2xziPShMGHFFPMc7Nvh7rMmyZ6iEgMkRKnEAmJfEIA5lLaNR4xcimAcZACGCAkYNzFgDEJJYp5jiFhTEUuQ0yTjdJoZEggfKQYsO-mhIkLWRgzWRsREkVgjDAhxZgghFhnF87t3-gOEnoMFAkTACFUq1mwFhgXRlKilJL3cRoDE4IL7lyUQmRZNtopOB8RlTFSChDM-8ClDNYKzvu-984xSClYliJjXCg5BS-N5oIDUbmYHXadMXlVlhHjdnuwlBJgVZXTMJos2273WvFyUXfjUJii70elNBFKqQbXZ6bshpEBsAh1OR-mQRghlch0JjXPjcnLYhoGKSUDVlbFoemzTAujwQbNedP0R-t56PrdZo8xvPvhYxrdq1eXQ9uen51sbq_PTk63h8O9-w94DHac9pv9r_3GR-3hoAleX26PTo4Xi_mX37x6-uXXSstqMUuQ8rokxqyH-WJeVHXbNGHsE083N-2DR3cXJ4vgkPNUlQUXInFutOSJTfvOWbvf74VUu_3-fH2S5Xo-n_fdIOp8OLTVrCoXc5KMISUG-XKls3ryNqsqkokJLXQhGRqjBFMgBUYK3pfrmZbKjRNwkEa3Q__lZ8-azR7DuH32teu7ME1GsMm2_eaSUhRVxSkihpQCxkBAIEAK5oaJK24yFQICg3p91N1uIGGMEaMP3o-7xiVa3b3gedm3AwYrWWQx5FoTE4uzCzMrGGOvn75enp8JrX2Y3pizVJkzYloXEd20b5cX51xLwTPFNEW49-Hb_W3j3VjUmfMJBOORUYqhd0xwISUQL-oiK4oYEwaUmfbDKLPsTdUeveeQdKbj5AUXXCn2hu9vMkqQAuZ5yZjkUlAioBRD5FzESAAEQgAnIWTCoIuKUoKUiGgaOsa466eIoSzmIYax7QSx6L0x5Th088UyeO-d1Uah90wypblighEBJJaSHUehudBSEPfTxAQmYllVmUw3myYRScYgiZvr66O7y7Ydrl9e5rnxiCLLcZxO1yvDizGFbt_JXNvRHZ2eJGJuskhJlcX2ap-XhZBsGvswBpl49NFPo1A6sjh03eJ0MRx6ASwi46UuZkW_t_XClHkW40hIyQYi4EJgwK73P_itd47P6sfH9149v52V1W7fHq1rSUKA1Jl59er29GhhjFBSSaULYuMwlkYCJgV0drR4cO98blSVqf_ev_FjcNZIkeeaU0IfBOcIFDA27ZgV1aGdEhedS94NzoVpGp-881AK8ez5jR2jFKDL_PKmvb3aN5sdOj90AzHeNOOiLvp-nFeFc-7kaKWEcJOLPljnZkVpMi2FKAtjNHifOEBudIpolCjLrMzNZrc_mtecccnh7GSdG2GA3TmZn5-sOFHCYDKVK1VoWQAZqSKGBAkSFZlRUgJBiOiQtqNzkW73LRLYiNb5wfqbXb9r3WYcbWKq1C-6dt9Nw-SHEBHD5MPB7rg0pJWQ2bw-4zkXQlhnJ-e0lF0_AuKEse1HlYvgIsQYvAvhzU2ULe7M3Dg2hyFqAfMs5OL_-3ufvXp1c3O1S6UcbOS5np8Wn3_xateNRaV7N7y4fL0o5xH5b3z4rpgVf_bpsy9fvOhDXCyWP__s6dev98T4_TsnR6X5Ox-9-53HJymmX3x9dd0NHch_-bPnX9w0aWmmLqY5S2fy06e3QkvBxbOvr7WAFONiUe7HvrPpnQ9OH5-sv_zk5fHJDM7nH3_2_Ppqi5Qevn3v93_6-YeP79ZlpaREwT5_efvVi8tvLjcH61_uu-Vidfr23SGm55s--Olq2xutmzG8fbGKkF6-2LBEjBNgwgQi44lzF3EIXbNv-3GaIm5f7kXBXtvouTiq89PTol6XQsgwdEQ-gEfAaZiU1D7GYpHZKRBCOzqeacYoDBYQIWFyEbTggNz7ZD2jmIbwZlyGmIAJQEyJEQ8UA7hAQMDeoK2TETwMngtJkNy-C5uBGenysn2648Q9JcKQ5xkBdH2HPvGUytOZd0kEpOB8P5ALTCghGdiolEzDSGNgnpigFFBqBS4xTMn5BCS1oTdOLtBKmzBZnhJLkTHYvL49e_tBaAeudHd7k2WZVHroBqFEQAdCJEqYEpdSa03R28nJLFdSUYxAiSVkjFPyKisZobcTl4IBgFDoHWeCE0sJBReUIgMQSgLnQitMAIK_oQ4ySkBInLE3yHBKKaKUErjwY0cpMGBIIARILaU2xGQMgSjlixx9YABlWTZtM_Y7rXMuNGKYKfHRt96ZGTk0o7fu6vVuPquqMq9zjd5zxpWSZycnCX1z2C-Xs6HpOMGsqkymT49XMQaABACHtjFGo8eUEhMkCOwUVsv5ZC1n4Af_-N2zeZHfOz95-ODMDRZ9rOsiK3QktulaAtY2_TdPr8bRN-2-mpemkKU2Z8cLP9mXV11Vqz_7-fNRU8dCwnhztc3mlYsxYZgOFp2XQnb9kBUmxnjYdO89uqDow2aIfajK-b_9mz9aL-rl-uRPP_3mrffvgWAnp_M_-pPPV8v5b__oO9e75q3T9ecvN__yj_78o48--PiLL7wLr17cpohcyXt3Lja3VyfHa21Uiu64KmqjjlflP__9X9TL5aHrm-2WYgClhM7S2K3KCrnsxkm4Kc-rSPzXvvfdm-ubdttzwU2md1e3UqnFaiGM2m93gKwsiuicHVqKMTGQWsYQ5oujcTpkppzGUZe6qquy0G7qj44W77_z8F_8s3998_rAIYn_6D_7z9zkFJcPH9RvRg5gQCwxAB-cVtxoIYBJAfMq00Cz0iTnAUFyyDLNOc-1ds637e5oPlM644IVb3LDkBiDiMlPPsuzTMhciJnJXu06T8n5AEJKzj0kzvgbMkjbT5rzsi4O_aQyHYiQmI34-mZvMnO77wnSfrT9aJt-2g_W-TA6L6SyzgohkIgLHhKN1us869pBSLXZ7QkYcP7i9abMdG99JBgDDs57H2yIbTeOPmRKJ-IYoWlHqQUXQJz7gCEkYkwYjRGHfvIucoCIpBXvO2ckDy6GEEEKYgggpZSUUAuhjWKcY0o-xoDIgKwLSinnPABLCZXifX8IwZMQ-30njB6d40KmBIhkrWUALgRpTIoYETHhGz1hJo0LkTEg4N4HYsw7n5s8-BCc1VnWt71Q0raD0gIS-XEMPsQYtZLOhq7tidI0TFxw66fV-miabFnmGWNMchtiPauD82WuXQgnJ6ubXTufLdpxYgyYYlrJGJFzGUKQmvvgp9HOF7OqysdhDCFmWe6Do4BMQFFo59xiPkMM9azQSh1ut1Wmj1bz-Wqpjckz1bWtG_2d-3c3N7eCQ27M7c1-uViYKpccOKQXz15--L33bN_tt4dNs_vh974bJ1toXRzNP__s88mOgLEqyhDx_M5ZTCkinp6fpIBFUZG3y6OVVEZx8-jtuxjh9YvXTMD-ao_AnLUpEI4WRhu6TkuOYdKCH3btYlUDB11U3X4_X83J-eCxXNSSgcxzKaWbekaYEgYfJWfzeZliWh3fQwxai6zMeC4SkWAsTGMMCSMmSjgNyXfj9TZYqySnhIiBhwTRpZDiNHHJYj9poxhhHC1LkFXzFMLYNL7t0foUMYxjuZpHPzEAJNJ5FsFzxMmNIabVxSnnchpcjC4hBvR2GuLkpTE6M_3QqTwvZ7WzsahWQGm5XoUEh6utLmSKSFwtjteru-e2OQxtd_H2w2azv3l9-95Hv7m9vgwhQoL56RFX0jvPKAIJweR8fTIOk9QaKUXnhTIQkpQMbSQgZQwxQRiFUlxIEjKlyAVH65iU6S9rJkkqBZyLTEmpiJLKyhi8EDJMrlgsKSGmxBlPMXJOADD07Xy9FhLs2EspMQamtJumYrakhADAiQQT5OMbypHkEihRQApECOW8wIC6rLz1gkupNRIILdf3ztubW5HUzcvt448ec4rWur61i2WRFDRNOD8-5TGpTPDMBB8WVfnGNZKXmUcq62y-LmMM7X4SSmSGz6sciMJkE2NEQEo5HxNLQDIhZFm1WCz8NAERBnZ6cWKMVFJa507uLgxnrg1Ls6iKfHY0Y1qWeU4Rj9Z1DOH15eatJ3dt11ZZjs6is_OiqHK9Wi_unq_LQpZanh3Vj8-Oz-bVyaKs80xyLhkg0RtVFnIYRh-IfCTv06Ydb_d7rs0Xn39z52T13rcf2XbK8owgZlo14zg0A2MMvZ1GP5vPgo-Q0vFyxhnLjaqqUgEB53lmGKPlqlpVuhttpqRkvG8nDiyGwAXPM51nOkVEjEry5ayQnFVFObVtoXRV6FJxpXTCeGd9FClFN81ztSpLIYSbJql0URQMGIWkjbYxHqyzIQZMgwvABDJGUnCutk13GCduxLt3Fn_08dXrm23vHJbconcuUCYjFyC5EDJ5H9DF4JWWLmLbDvuhl1zkRWldDM5NdgjWCyOFETLTQgtV8v3tREJe9XthVGfhq09eCZFULhfz0vn09XV_58nq-Ve755fXXjDLEoVhezs-eOvO3_9bf-VF0_yz3_3p9a4x8_Lb33n7V59-4wKvy-zv_M4HGYHS2ba1f_rV1cfX-3_1qxdyUfzhz76-OTRZqd_6rbOf_MnLbj_cXO6effISeKgWFLmfBpzAH2JIBJ7iD955uEKWSP3846cFly_3DQC72tx-8N6Ts_nsweni9XY4P11et-On31wrrf_Gb_3oJ7_4jDHVxdDt7N119fd_fNYGUdYlMhxd2A_EeXp09_iy6SakbQguIIvAIJrMRBSHfuI5YzEmBoFAkUro9oPb3gSW6aLWWZ0XWvsJu3YSjHWHkUnV9RMjmWLyvQOXZApxctB1gCSkEFqgDwCJEmnGknMMOdecGAAlINSZemMzB4wAwGLkIaaUUoKEAIIRxLjvuUyyLv3BMh8CejsO0YWyrDgXty9eSW048CzLOEIaJs6SbQaRksgNo8BDFBzTOJGNQiQkhphUpn0_CU7oI5cMGOgiT85RBGmUH0bJQErj7WDyfPPianl26qbRDbY-WUWHXACjyIR0zmmTMeBayRQDIEICqQzAGztR4sSM1ug9BtRKMcToLONcSJ0oQQqCS2WUtU4KzhinhEpKxJAVFRc6uMmYGqNDdFplgCl5D4wE50W9GJrujfbLB8c458C5kLP1sXVTVdfj0J_fuT8O42I-f_LuW1fXGw4RAzx678Fhs9GYPvrgW59-82J3s3_48GKyvizUcl6uFjWHdHKyKrTSWh5u93luTlYzrcTd8zUBlbkpjEkYl3UtGVutlimEQ9eazDx__erieD1fVNE6JWWWmzvny0WRrVcrlhCQMpMBh97ZpnU_-fnXyMH6eL0bHdLloT25d8YV_-LZ4a_98J1Zptvd0KHf7KY-4HZ03eCbtpdKeopZppyNKWFV5troapk_-sGT7nJXKgOexRHnVbYsyw-e3But_eSX3_z8y2dPPnyLYfrlJ0-3t93x6ezb7zz-2Sefns6qrYv_-icf_4N__2989er1zeXt_rbjXK6PFt_57e_unl0Vgq_PT77884__3b_146vnrx8_uv_F5dUvn15fXu2Z0i46IiaUnA6HZV0HUH2Im6stS8m6yTAdEl2-fO194JwrpSBh33T3njy8fv7aOweJIMbgJjd8w1mVeAIGpiiAEWNgcs04G7r-5M5JxIg-XJyclmXx7MUrJUQKQfzP_tf_kDEoCz2NUWupldJaUQgSmFGyyNTpuhIEZaYNZ9ENmRKFyRQDzjlhMkqZzGAISmpGHIgyJQETUQoBY0wANK8LyUVA2m47D6kyijO-afppirP17HCYYgjXbVdmWZUb67xLVC8r64O3YddPMSYuYPChmOVNN-72A0iOMSGk2aIMmDCEKXjJmTG6bXquRJbnHpMQ3EcUUmhjfIhAVC_K_aEPIQ0-Mk7WY4hhdJESeQSfYsDIOPMRgXNtpHUJEZXk3nofIgeWEHOTjd5xRsYoxgQTUkiWiJp2BM5SQGDcRRSCs79MIEBwXghJjDEBRCwBIFH0ARkhkOBMa2X7vlwsm0PDGUtEJDjnjDERXNBaCyGI83HyGNH7IARTWllnvQ8xBK0NgQdGMSIgcSkSBpPnOtdMSKk1AxZtEAqIiDFQWpo8l0oZaVL0IaTtdl_UOVJiXGD0eVFwlozWm30zTmMAjwl9QK0VJRLEGEUt1eXl5nh9ZJSKPmSFRkqzeT10_ays3DQUVZ5nSik1DtN8Me_bgxQqoJdSHvYHUZi6LoVhuZbzWXnn4bnthsWyIkhSsrv3z26urqN3x0fH9-6v3_v2B6-fvTw7XUVrV8t5mMayyoq62G12Yzu-8_ZbiXGm2HJW3Ds9vr05rNZL73yw0_X1zeXrm49-9MHYj5LzfdtCiEkoLslNkxDcDQN6W85yAC6FDJi8D0VppmlKCU6OV1PX9U1rDy1IFp1HBFWoLDdxsoxYQgzBp0Qao_O2bbbZkR6mqT8MwcVmcxiaMTNGaTF1_f7qKlkvGZPqjWRPEYbkguJCSy0EJ-dZDJz9ZSxHSJ3Q26HPiqKoagheaonep5TIWwImqzyiTT6KohSZEZnSWoRhKNdzXdb10TrExICRG7JZCVLde_T-fDFHIiGAgLW7vRLSOy-NMXURPUqTT8Mw9M2432NEXc1knh3fuTPaqdm-fvL2j5AlwgQMvPeMmAQQkvvoE0Ze5sC4WdQpJCV4jEkqrfNCGoMEeVk56xJBOT-KdmScAXBTls4GU5aEMcWkjXGTFUoDY5hIGkPAODDGBb252hmk4NEHwVn0gXOO6BhxobNut6-WC_RWF6UPljMmlcGUGEYgiN5rLb0NxEAoiRiBcaEEY7wfRkYACRlnQMxUBfCEw4QYizwPAZ58-J2uHedVDTxUZZkx5cbudLl4td3Wq3UMfrhuGONMKO8s-Rh6p7lSWsZAkkgLLYvath36WJ8tORN-9KbOht4zIoquKrLtbjOb5VMzSibcOClFtrci43VZ9MP03rfeXdbVYjZbrCoXnT00eZnnRdlP09vvPOoOXVXVFKzhUgn5_W8_YTEKwnsn89CP333v0b2z4_Nl6adxNSsixjwTTTON4xv1KPSD721IwANhIPAhSq1vb7bbm8PDdx7863_-Uxvc6qh2Dj_68P3n168P-7bZNtqoofPr9dIFx4lc9EVe5HkmGYvBYwx1lUshgwspMRbxaFEWRda0fVUWZZkxlqoiD95LLbQWs7IoyxwSy42eFXliKSGGmNqm77uhn4YU4_GiOq7rTMsQUCqtBIfEGHLGwUUcvLcEIZLzkXMxuGk5r-a5-ebFTTfY2aLeTe6PP389jHYYRy6FTVzVOVMSOScmgUvBpBSQKDoXfcR6UQkmEhI3fLJvGnXMLGZCAMRIxK6vdvNZmSZkKW4OHWfCKG2tTZxEnu12o5vS-bunq0XO7NRtDwAw-Gm7a8iJv_tv_caTt-_803_-x3_2F5_v-r6Ylz9678GnH3_dd_L8tP4f_u1vRRf_1V989dXQ_P6fvtCC7r93_NXzzVXTf_bs-nbf7aP7sz95GjGZgo3OU8KqrnaT2n59uL5tXUiAlFKM3l8sVkfVjAh-8eWL8_uLj7945l1s_cRldn60OsqVdzibqT__1YuXV9u7D88_ff5iVhcvXm5eXt9EzvrJXR6mFzv7-Hz986ebeZHb5IiZdorlLBNGJABG2AxOMo2EkgvgAAlSorLI2n3n7JiXJlLMjMCh31_11jmmSCtVHlV1VU4-BeeMkYzIj5ORoGIkxuQiSx6Z9YCJgLI6920PDLAbpBaMEgYEKUAKaAcOrJgpPwwwOBCM9TYFDy5RTBAjiMQT-cNAuZZ5kbyP3QiCCEgJXS9q70PClEKQQkkj0DrOKXiXnANCpXk8DBwTxUguJBe4YAmIEReSUUBA4okYS-gTkxK9ixZlpuI0MAKZFyE41zSZZOOhm4ZpVtdCm3a710qQc1m1AEycEsMklRaJ0E7oAufEhSAG0QcGTEuDMRAiMDK6BOB-nJRWlCCGyCXPqhoYpRiFkIwgesuESAQqy5wbU_Scop8mLjkhcsE5YxxYvVr7sQNKjLjJMoyJAZ8dHflpVFIJzZfLJRdQFPl3v_NeiIiQjFFuck8-fJeL9INvv3_neHl6NI8QpdHoPRMwK4umaZbzOYc0n9XopqosGE_r1UwJ8WY5EZwRYUpMcF5mOniHiZppMlI-efwgxpALzQXL8jL4aV7nmnHFuVG6rLLeuebQ_eRXX1obmOB-8pMNQqkPv_vwwXq2WhS5UL_x4V3B4PK2-2d_8gkCTIXs-mG77YdhYjGyRHYKdVm6wb337v2bq12R1ULq8apVBI_vnbrOfvjtB-enay3FvNJ_9NOvn7x1rzw__vyzL_rBlUp_5517Qpuf_-prVapHj-7_8V98-vZ3Hv3qV89_-uefLVfLYfAPHp6_-60Hn_y3Pyu0-f6vf--nP_nsH_4v_24lhGJCVsX_9j__LxnTQ0zN4VCVxW7XCZHu3T-viqoP4fb2evKWxWgyuVwshqGNIYSIWZ51-21WVlmu66rY3-xmJ0vbTYkwBZwOU2YqYlwZE2woZrmf3ND2Wa6L_x9N_9Fr25qlZ2JjfH6a5de2Zx93vQsfmZHBJINJ0UJZgFAQIAgQJHUlCJCqijIsA-h3qK2WgBKgNkGUVASLrGIyTZi8kdff47dZe7lpPj8-NU5WZ_YnMBtzvOMdzzObnZ6e7u7vqWKfffwxMvzuu1eS82574P-n__KfCwSlRKNk9FFwZmpNpRgt7uLdVFSMoNaaIaxmjRacISIDjpwz1NowxhGRc9E2leQSM0jOpOI390etFQpkQqWYCQog1MZEIs31mBNlBACtmAtJSBFCrLS2gz9Y287qm03_-s02UPEpjzH5kFDy7cEBJGRsHJ33SWqVYu77QUg2jn42qUylAdXook3J-ZRLyUQhFVNVowtG6O1-dDH6VDrrKqWEEpnKYm72nRuszQR2SMh5orI7jCHkXEoIKcaccinwNqZE74IPEQD73vqcXEiUc8hFaNkNA5eCKBVk4-iYYKXQ8WiF5ABAOSslQ0wFwPpEFAl5jsloM2n0bDG_u91CAYLCOfMuuugQmVDCDbau6zH4w_1OakGFUs7H7si0fmsgR4Zu8DFlQlaIgAplktq4cSBglHPTTrWpnLUFcbTep4xS2mFkyAhpMV_UlXLDyJV4qwZvTZVTmq-midJ03lKGqWm6IdRKtjU3UrZNkxItFsvD4dg0RhtZoORCOSXC0tY1AB2P42wyjcE3k2l_PExnMzc4rXXVNrpSrhtSDELIw2E_nc5_-5e_Wy7n6-V8uZhTCfvt1tkwmzfK6BRzd7dJKU-r-n_5v_jTCqiutJlUL5-_DmP89LOngot60ry6vjPS-P7w85___M3rm-DT57_9_Cd_8EPFeNcNx30vpATEw36fE-RMoFihTARtWzlnFxfn_TAwwXe7UXAWrRMMu-2Bs6KN5kbISo2dVUI2s_b-5TUjiLE8-sHD7tApJXSt66buxjF5QMlDTJS8xKSqhgSWQhRDydkonksZDyMyMV0vsZBUQgADwug9BhBCQMpQSgqZQgBAIQUA-uOh5MJAyarivPhhIMAUc9OeAitxtGRdHkPq-9Dt_aGDkpkSQhihdUgFCQLRzauXibJQ8vLBhRGMSyEqlQU_7LrJbEacj4MVlXLdYKqqmU0p5_3trp1PjdB10xD6k_MHi5OVricxxxiCbNvgLecsJ8qEjEvBtZAiBS90BVpzZYLzMSRpuNbahZBDYFxMFgvGGRWAAoQApZRMRivGMRcsVIQ2wfl60nIuMxEiY4KXnBBQVxVyYWYzXrIf3dvGdj2dHm5v2-W6UNJ1lTPFFJhUOWcUPOfMEOEthLQACiGkgJAp55STkAoALt590FZtu2531wffd6urdT8O7ui6ff9HP39PG5Mycy7-z__JL19fb6rWZKO3N7dGGl01kfLmdtsfB2142xo_jo02wKH4pIUEzdzOQk4CRVNPc3TDTffkk0c5R8HZ0A-MoIQsBJhWZUnR009_-LF1mWFWWs8ns8V8gqXcXL-5ud1UlXQ29n03nbYxhsbU_f39g_PlajV9crH-4YdX07oGO_74s_ceni9P5pNGCVYKIpNKdqNzo6MCgCxlSrmMiWxKQz_sBusjxZg2x-7-dvPxx-8dN_vHj06Wq1nMJUT_17_-4rgffEyVMgyZrlTTVEPITz967I_uZDlfr5Yvnr_YD8OkbbQSHNEoGVM8nc-QcTtaKUUIjjHUShmtKabVYoqlzKatENK78bjfcQG1UqUAISopheQJ6aPHVwyw0ToGL6QUjAGAVipnKgy7EHOCWa1DQiylqtWqaTGmzbaXUrxzdVZVQhXYWJ_IxUKHbmRCjUfrbTzse8FBKERE71MMJE0Tok0pJZ8yzzZEUdBUmjEUUjRVW1capJqvZzFnn0goKbUqUMYUc8425Kquzz5Znv7qsf_--Ob729vdALxGISSPl6eLv_-rT4PN__7ffXGwHrQ6fbD-T__Xf_jbz98cB3z3cfunf_LuX_zN7X_4mxe33TEMmQr96p9-_K__3dd33ThEf3Q2YwqYY85VXR1Gd9hbLgVTkMcoC6oGvfdVLYgRpfDh1dWybl--uvv4w4d1027HgXG01k0UP5vOFMp_9ZvnnMk32_3VyXJ76CTD5XL--xevq2kbteqJvrrubm-Of_7y5scfrpdSuEibvmtr01tvfRqTKwkSkU3h2A1jDvW0ij6mUmbrer2sipTOxuPeF0AXYsESYi65xBg54wxpOtWMiWFwy_Vs9CH4JBjPkQqCZBB9KDGXjFpLrET2GREo-BIJEKGAbnXJhWUQSlEB8gk4YkwACDkBZGBQbMgpA6Bc1m7wQFkwYBKrxST1PSNWt40fLSCWnCkX4DL5ULwrPgExoAI5vd3Vgs-YCxICFYaYgqeYSyolZxSCUpJKvh1OhJbZOQ5YGECOAnkBSDFpxRjR2QePD2_uMMdohxR8O13klKiUkkApVWJCopLJW1vNL3N0OXiALHUTnGNYUkjIuZQs2oFLIRgwgEylFALGABEL5py44AAAjIVxREQkYoLlELngWIgysYKZSiaPyFOOs5N18HGyng3HQ_RRVdVsOlnN1pPWSMJ3Hj589uyNnphhf9C17vtuMp8-vbpcNs13z56_eHVXsHDExaw9mc9zSsvlVDK22-4gpweXJ4yL5WyCmZSUUMrQD9O6kUpxjkPXA-CbzY4zvppPJBMvX23bVmutuq5br6ZzLeeTlgtICNcvb19d77vOUSpKV9PWrE7mhvPP3j07ker7N10NOJk0KZdnr7bf3uyDT5eP5s--utvuu-1hkKIgK6zSgDz5_Nkn726uDxy50fKT9x80BS8X8_WsPj1bvNhtvvjq9Rev7wYXl5er13ebv_n86ydPLkdnV7MmI_-z336BnP3ijz756998dzx0t9ebl6_efPTuQyo4n7S1kXfX2w-ePFC6ebycXE6qi0ldQqmqign2L__lX5Fkg4umMRcPlrvr3aqZmKraH_tvvntFPsxas57N7282q9P1cTeUQpeXZ_1-L6VijK1W8_lsttvuvHUUKVEoORfCdjJNOUqtV6erSTv9_utnDx9eJZd-9Yu_9-bNi5zTr378s1pX_-4__NX2ZqeMxJL5_-E_-T9iAf5WepSj5EghVVpozs6b6bzSArkW3EiRUlSaBRekEErJnEgwpEwFCucshIiUtBYMYRhDXamUiGLWlXIxUY7WRcMhZ9h1fYqFa355Mdl3kXH0KWklG6Gsi682x6ZVqSQfKCGgUjn6UtjuMMxazZBdrCcp4dnZPIfEGddatXVVaZ08pUyATHFBUBji3eYglIxUYs4-UAghAaAW-2OfCXbH7v5g66a5u-t2h04p3Q8OGErJK6OQ4X5wACg1k5xZ7zMRCuBcpEBMoEBmx3i_7RhnvbX7_RiBMcEP90cUoht6LtU4DIBCyreUc_a2w5MLhRhSjEpK19sYvOaSMXa33TGhMlCKGQUvANJoJNJKSiETUUxZae1s4JxxRKV0poIcgnWFMpPGe8s4E4L50U9mS9sfuJAMwYcQ3EgUCIBKMm2dSxFcKMFSCAzZ0A21MZSL9yESBe-1ks46hpwJnSO9fHGLWCrk5EatNNeqdxYZC9EZWXk31nXFGYvRKyUE41CyUbLS-q0b-vWr17PZxI5jO22D85VW_eAUE7Wpg_f7u22Kvlamrqth7N68uJZcXpyfzqf1L37-maRysjr78ovfV60BDX_2l58_enQ6ndQsl-mkfnx12Y2jDeF0PZs25ur0dOwPP_7BJ999-_2r129MJc7OV0PvQPDD7fbB48vR2QIl-Ng0lXdjsglSVKbOVEKMmDFHrytZcpoup865amLqtj5uttPVPAbSUispuBR-9NNZWy9Mv9k_eOciuhh6ryoVfSDrdCVVo6GQt6UwNT851ZVABMZk1c6ZUrIxnPNkY3YuBguEWptJu0ResCASFCicFcGRUigxI2UpVQg22BGAVFNDgZIyOJdpYJLpelq8lZpD8Frp7H0Y-uRiCEHN2mo2j7FkH2qDJcf7m82bFzeXT65KIkIhKj07Pe0Oh7qpl48eADIudPYFCgJCbWpn_Ww5N810s7mfLReMFWRw9uhjW1J0UTBMMWmlJotlTjk4XzJIKZfn59a5lHI7adr5DBDr2YwxRgBSaW1qKoTAuNKrs3NKGQFjSkIpzhlRYUxwoVDwFDNyAIKcAuMCqCASkyo5J-saOcaYmJKMy6ppY_DZhaqZlUJUCuQkpUaGHBkQIgIAQ0REVmKiGIFx05jsQzOZpYymqjjE4-02eUpUhNQopNb8aON8tvbR1UK92XeL6cQHLxiWRN1-qIzAUqpKzRbTpjY5UT84FJIzMXRuup6VECikUpJCM4ZUQhBc1lU7mVfdXb--OCGf7ZjaZdM-eMy7MHa2qTnFqIwWhX380UM_jK9fv3lweeqHsF7MCSEc-sViAVROpu2H716dLia__Nl7DbIw9B89uThdTo0UlZKaM86gZBKap5RKyTEmKXiGMthIgInQWk-FjK6A4_1uN19MVuvVOPQffvj05Yv71fni5mZzd7-_ud5JLT58_z0uoZlUKTDTQFtXcberptXF2Xp_OCwm7dlqjiX73lVNdXmxCDadrSf90QkhpBI-xtmsZQiCMcVEKaWpTMl5tG7oRxdSsmPMsRAYraQUlOKqbWstjZKIyBA55_i3WcxbLWb2GQbrXSwxRKUFAVKmMURTG8k4IjZarefVB-v5f_e7b683O1WZmLIxejIxj1aL2hgAtHbY3h_82Dk7QAJ_7LngIRaWyUhlh4FiPPbW-ZA1ZGMYMN2qzFhkvGTOtTp_cKK1Orlc1o043Ibj1_u717eHvZ0u5-2qXp5MRMp_8sef_O7rmy9-_z1WLHKma_6rP3rnv_033371onvwZPXOg5OXd8dff_7i3lmppdZivqx767_9_jYAIcdxcP0wCqXHMdS1sMXnGNcfnm-_uy0AAVL7ULsUDvfjpBb7_eGf_ewn3lqWWe_6i7O1j14bZEinq_XVejoMjnkvpkYh2OAPvVWC_e7L715txx_86sPffP7yq2fXvsQYo43D1tKITE4ns2nbjyNRNAi7bd8l3yo5xKRaHXOx9n_spo7xMGYpmGiwqhhzlkZXiHxvSww5lW5vGbJCIEDFkMZjZ7QKxz6OLo9jCSnmLCpDwwghxXFkvKYQsQDnHHKCQkCFIaMU8_6YGM_RQ0oQEmQCF6AQF7IAgxgRkLeKxlAOAzmXQ5Sch8OAjPsQ6ll72O4FQ8SSKUKKAjOPETMBUc7EGaUxUALIAIkQiQuRYyxErBQsBAioMLqI6S29GFSlo_UMAErOOXIsopFIiETDwWFrhps7AIAUhBDAJKDgipUYGWCmDPi3EHCmsOQElEuMlJEJLDkDEjCAgpzzHKIQPLuEHE1VD8dOKEkpsrchP7JCKFlhKVd1BQzjMEougIgjIGOiNqZpg3VNW1FKnGtlZF3XSijCKJH80P_spz84mU2kErOTeddbzUVOfjlf5xL-7s8-Fbm0jW7a5ngY2vmkaSopsKkN5uxGO5s0i_m0aer1vC1EQrBSCofSGMMYIhTKxUV_6MZ22kybRgnhXZjPDUM2WDeZNU8fn1IkwRgX4vZu62PmWuRSfErnp8tJXUmg1aJGkH_21ZuTpo4MAeSX3745uFBqHoMfXNxvd8oIhFQ1qgjxgx88GA7DejL1o59PGhTs4yfnFRfrduZT3Hf-GOLmOAaKH3765O5mc9yOX7_Y_k__o7_XjX0_Dij5X__uex_8H_7dH_3ur77e3W8ns5lq5Go-2R1G4Mh5qY2xvT8_PfFdt1Dy0dlsqvRh1-0H91__63-_2Q_Nyao79qvlrKlld9dPGyMq0_cjV-Kw3Z2v569e3Z89OI-lhBh5yXYYvLWZ8nyxpJhMXW2ub5RWfhxSSKwAwyIEMsFcH84eXDCOxUVAmjbtzeY1A8WY-PGPPiqZ399tQvYFkDLx__L__i8qoxsjUibJGSK1TaUEDzEao5VQQGS0xFIoBMll3RghOEOmtc45CyEYYwTEoLyF3gCyt2hvZExy4UO42xzv-gEgecJqVm-PFhF9okPvoJRUincJkflcrLe1lveH4Th4kpwbfXu7rSpJlI_Om1rdbsbdaPsx7I9DW5la80pJKCg5cy4GF5DLXTcO1llHNgQbIiAHIZXk1qftrkcmEgDlzDlHhBji6D3jrDAuOEsZCpX9cSisFCKfM-PQD54xXgp0nSOikAJjeBxGLrAIPvQj44wEWutLzlywHMn5ZJ0zRg-DlUJRKT7GTJRLySl77wmgP45QSAjZb3pUyrRVyLEgxJQAgDHuXShUoBQuZc6QC4UUc4ztvLXjEFOGUt4aUmPKOZeUQg4x-oQImQIi9N1QNS1QURL90JdMVdMyBhwFZdJSFsSUAREEI9PUqETw9ODyfDgcZvOl844XohTqSX049IvFhKHIjCfGCmQfXFNXBaiqq9vb_Xw-I4rGqBzT2dkqhSik2tzv992gKpNCrE1d1YZB8T4e9l1l1N3mbj1vKcbFbP7LX_1UKD0cOqagasTL568fXl7823_75yj55uZN8HGxaK_Or7I_fvD4qq7MV9-9fPbq7g8_e6eazre7_el0CpQrwR49unr9_LrreyXhj375083dvqSoGpVT7Lrx-tWNllJoMW632SWEUqhY7wiELOzqwVJXVQhJ10YI5V0sOclambodBn_25MRoedwem6nkKKJLP_7xTzZvrv3eLc4XOXqiwgRT2jgbqWClja5MzomCE1wAUdW0BQgL2cFKpYRghRVirGmmTIB3IzJWT6a5pAzAOUfAHDLDklMGLrjSWEoOMbpIyKRUleTOBiiC_Ch0A5RZYWF0VdMQEZZIOeUhphC4FEqY_f3Bh2gMT9F2-_1xd3887sfBDofddD31vSs5m8ZIZeanS1NVdTMNMbfT-WD765fPC5T9ZrNYrg_HA_KyXK5Oz6500xy3B8QSUgFGup0B46ePH7366lkzmyOWqq7t6ICJEONsdsIYABZtNDLsh7EyTfB-spjFGKRWOeYQAwpJyBBQVirnXCiR92-_VCEx-lxSBoZhtCETItPaBBvr6RQpAmNu7JSuYgw5F2TIGENAU1UFkRuZAZkSCMCFAARdKSh48eGjdBz7Xbc6W8QQC_Dl2WmzmDDk97d3s-lie9hdv3pDPkTy293xxc19WxlINJ1POJDLyZh62HfT2cT5t8JBzgFzyWF0IQXI2dRVADJaEishJQ7FHgeAcv70kT_2AmPOBY5DNdVPnzy4vz-8_8F7k0kzW84UMh_cTLeD7U4vlt--uFUCLx6cbu_uGmOWU3W-mFWM10LMtZpN6m53WK_nRnAleArZjiMTDJCFlI_7IWTyIXc2uEw-Utc7IZmQ0voQCuwOR8G5EjibTne9e_Xi9cG7X__mu2HoAElI2By2r17fSaH-Jz_-xa-__DLaNAZf1a0SGhC0MIi0nE21UtNJBZEgQ9OY2ayJMQHDXEgxxqAsJ22lFGcsx7Q_HAuR4KIx6uTyVHImGYdSJIPT5bzRWjDB3sLgoLwd4ELMKVOMebA0hpgLdta5mAcfgYkAJZUSUoECX373hlGJqeytmzQTW9hsOUGGtVIll2hDo_Ru9PebwSbHtTSVbCojJwaBCyNni0nKebKYVicT0xpZsRQSIkyXJqVo5s3spG5quT5pdcOyS-PYf__FSxCsasX66vzpR5dX54uzSd3d3q3fOf3u-8N3z-5mp83BRlXzp2fT2-f3332_Pb9cTuZmDOm3n7_c7Pezk7bvxmTje59ebO86EOz5s9eFKETHJffBJWtjoVKwkOAyJedDCkOgu9tDW08AciXEbuz_4ccf3N1tZm3z9fOXNo6vX90_e37zwfry0eXZX_31iz4WqdjdscuFXW_vf_Gzz26v7__JP_7s4P2__m_-ajd2IFiEfHBusmhG73xiE6W5xKlWJUHMea3VV69vzqb17XGIDGyiwlksxVMkgTnHkghsamUMLgvNiWVjuB-GUki3wo-RQ1amcCbDYE1jcsoUgyiFhUDEoFBVN3H0EKnEzI2klKGUEiNyDjmSK9VZm7ZdSRl8gFiACCQDShAC0xIYQoxIgknOQ6LeQiEzq0pKBXKOUTUtl7o_HJhgwTnOAGMuPkGIBSCniJwjlRIjIEHOWAogIhTOAAkxEVDBgoBQUpbIIAPngivBcmYMi7PZBQSGjGUXOOeUUn2yDNt7RFJSA1AOrlmchBycdfWkzZmoQMkJECmTrKaUPMTAEHXVpBQJAHPGAtpMk7NCcSwlJSJKqjIpRc5EjhGF4EozoSg4KLkQpVwoRw4FGcspAReo2xwzK3j56HH0YyrRaBljyCF88sMPf_7ZB93d4ac__8T1w48_fVcK8fL17e7upmkNB1a1-heffRBHb2ptXWymjRCoOE6qSknGJR-tPztbNlXVH7tKCgaglci5RO-VVqMPfe-kFoILwfm0NoicgGfKxFnfj8v50kjGC7SNYYJ_8-xVSrAbfa3EfrQfP7pcTuqYoiDYuvzNm_vVtEqCl0b0zm-2x86n3baHTPeb4_Ji8ub6sDhZkmD90W936cF62Wj55OJ8WtWzWk2bCrB8vd38-tl32YXdYTRajsFtb7aHo_v0Bw9-9pN3Nq8333__vF0vN6_20fkn71x9-bvvm9ZMmtluu_v5L370V7_9sm1qJuDs9CT44eGDCxnDj99_tGxUpaWQbJviX_3Nt59_9aoLFCjGFM8W1f7NIYa4vlzfvt52Xc-AKaMypPlsoqqq67uSS7Qu5ahrnSgu5_PkffQuxni430kpKWeytqqq4bidz9eUqZnMKJLmErB0Y9-2EyrZGHl2cfbbz5_dvXi1ulhurnexMP7P_8X_FQtopaiQ5phS5owpKdumEQwZA62l4IxBEVoiwwIoOC8IVEopWBgCYz6kENPgPXDOmCAsMWUheIzEJCei1az1GV9tjinDEDxKvprXL19vB0u7ziGH1kifw-vb3dnp7G7Tjy52LlprGYe-D9NFbQPd3Y82RioFkKWUleQMgApzIWTGKmO2x6F3LlIpEkcfCGBMuQi42x4Pgw8xKK1CzrvdkTN5GG1lzL4bgMF0Prvd7DIBpeRjQMDrm62qzTi6FMj6EFIBRCIKKeVEz29ujKxCps46AgwxIPCUs_ceUibCXN6KegsA7PcHZkTOOXlPVGRtYkyUKadsJpX3STc1IDgXmGCEgAUKFSOrTKkULMiHsS-FqJCqjJKi7_qC7C03nXJOKSJnABkoAyUphe3HIkAoxTnv97s8HsPhkKyP3d73fU5UoFDEGANTnHHeH_YM-XF0UIqpzObNjTFmGHvGeWuEFFJrPQwuZD90g1GVHQctjM-JJ6q0kpJpKWOwXdfP59P5tL6_va3bSXc8zuYTBIghlpju7rc-hPOzU84xWNfbEUtpKjObTlIJz56_sd4tF4vk7fL0BPy4323PTk6uLtef__r3D5483B92da0LsI_efQwEt_eH0wfrm7v9o8uLu7vb5XJxenLW391fXJzd3Gze3L65urx48uDkL__iy0nbFg7Rh7ubzXG_a6qmP_acQ2Wqs3efBu_qSTWbNaVEITDnAoy10zaEWNdmvpq3k8V8tqASb77bz5bN1aMLXrgWrJ1WBXyMwdSyZISUmeCUSt_1jHFdGeedqaurR-_44T70o-9GFFkoxTQXgg9jP5lOdduWwshFKbg28ti7mAMVyEQAkCkzxguBrEwGBlJwaVAIxrDEjEZ661VlIGfEQs6XlEspyFhwI6qKM2CCsxTTOL71U1arlZTt2A0MshtszrkUqkwz7g9ud9R1aw_dsDke72-F4EPXZchMyt39FjlvZzMpDedqsANnerQDF6rrj6ptHjx9urq4VKa57bqrRw-Vlnc3N03b6sogCp9C1c78MGhT9cdDXde5EOU4Wa5yTn13XJ9fhOCa-Xw47JVWzWIeCyGy7FM1rZP1kSIiciYQQNUNQCkFKCRZV9oYillKXYiSs-18GW0PwHNJdd1SIcY4xRRCyESry7U79EyJknMpEHyUSjIhEHG-XA27Q-iGwti7P_o42WgEdz5sbm4vLs-39zvT1g8ePLi92Z2cnvz0D_9AlPTm5varl9clRy0bT7lQFlp0fX9xfn7fHyttxmFo63ocOnIBGAsUk4vT00WhFKI1WjBEKlIYvlrOHn_8sfOdqHkG9ubuloiMMT_48D0qOdjw8cfvMMGQs0xwdXnSzlp7GM6Wc8Hjpx88XlbybDGbT6qmUZNGt7VRXKTgMxYfXMqZC-VTdC4BInIWC8RSQildPzIpA-WYCyAriIESUTa6iRm_-fbVbDXjRpqJEkJSTttNv1yv-m6IKdwN99N55V2WTEkuLh-eBh-AopIKS1lM29W0zoW0FExyIVhtNGOZIYYQZlWllNQCCwIAeO-NMQWKEGI9bTebfVur2hghZK0kUQEo9JaOVRgXnEopiGMK4-hdLGMqfYgg5Ziiy3nb2zd3-36kfT8eRw9QVovZbgw5gdAGiG0OR86AORetux_8NiVTmflqfnF6tpxMa6Vj9DHQcOwQi83RR9cdjtkFP7o4BkgFY7E3Wz_kbojDph_vh250X_3u1b4bhBaLsxMmdDOZEKEKpBM9e3F73TnWVkM_vP_J083NptLqj374SWPt77660cb8_V-89-e___77717urBvGUely--J-Mp0bo7_58sY6mwlnF_X54-X9TV8IcynNaiKNHu52NEYSKFWtK9MPo0JczGfaiIeni3fOz7f3-9W0Qc76Q6e5aqtqVuuP3nvwN9-9gUZufH96efLrz7-dVJOb3f1i0f7L__Z3y9Xk5uiaaYPG9JG4EPvdoZq1MY6vXr45DD74pLkMkR7OpoH4wsiscDfaRFHwMlHMpTSMliOzx7637n7jji6kSOmY8phrBcFZzMQKJZtKAa45uTBu9-184rqh-ABUShg4JPJOKJZjBsrAOBBBjJASxAhAUGPqBggRMoFkIBBCQsOEQOoIGTAqxQdgWCZYOl98Vm0tBIs2SG6olGY2yQWG-z3DggiFCssZUsop5pzhbeoeYgmeZQCkFIgzVFyUnMinkgkBC2PIGKeCOUEpgChbE7qBA7yFETNeSs4lFyiFGxlCyN5hwUwkpMpu5EIB18E5QAbAgWHJkWPWquqHXiqZho4zIEoADBFKJkqJMeQcIXnOJefMhSCNASKKWSgenSMOBVkpCYlSCMIoBsA4BwQmFGopq5qVWNX6_ubm53__V93m3kwMIzo9PV2vlz_45L0nD8-uLs4KlUryly9vnE3aSMbw3feebLb9eyezWdM-f30jBJ_NZwrzxWJ-uN9XWhljVstZAWKlNEYrJRkCleJ95EJwxhHxrbF4HJ2PyVSGCJzzOZUY43Taejesp1OlVHLepQwESsnFvJnNmlZKowVwvL09bL3bHu1sXpPkBxtv7g7Xb45D9IB4OHaacaX0hx9d9COsFsbbvF60nzxZT6t6NmlioUSUEQrlTRi_fnbD-9TW5vzs4e3u7je_fXbxaDVdzp6eXd2-Pnz-5feni-W3X7zqrV2fTbVUu_u7i_l6ezxUXAyd7fvuwcOLaV0XH_fbw0dXq_cenFaMKSWk0ffH_r_5i99_9WzT-cA58yG1jZpUtbNeKjGdzrwbGcOQUl1Vk-kUiZRQ-91BIqsn9ZPHV8Ngh86uTxaKs939ZhwHrXWwlhE56xgrRAmFPDs7v7y6vLu-m9Tajgfn48Xjxy9v33zw0fu8rb778rtox9ncyGry5NED_p__V_-FELwQtJVGxMpoIYTkgogAkDPOGSsAmTIylJXOGX2icfQhgSNyIblIwDAxuN4de5ucT0OMN_vehiQrg5wR4Oizz6XvIxcspgKUep-aVr-47wihrtXrm-M4jlVVmcaUgmZW55R7nxhjuRAIPgyOIbZtWwDuD0fTmsH542h3_dDMZouZudkcuRA2OK5VdmFvc7uQ37zcCuS9j4AopUo57wdvY0AGuRTvExY2a9qDdcNgD8Nwdjrb7RwTDBCt8wiIgEpJYDj0rmlUQbjfHmfTtkC2YwTF-74vCF0_hEgp55wzRxYopkQAEGNKKQbvqUCMnnPlfQzWumHUWkktWaUpRSEZIljrOXJnPVfSOZdjLkCZsu-PBUBKzQC0lEQkGHMucCmDDwVZSZli0lL9LUsROXIOlLlg2ihnbV1XFGIGRABAJrVmkjEUfGKGQyc5k0oAJSmEVAKZOO53Uslx32cmpm2Tol89WO-PHSBIxpUxDBlnUDWSA5pKIYIUbDZrm0qfnS4QMMSUUlRKsoKdDynlHEMBXmLOMZ5erK8uTvtD_-B8dXa-evXi1YOrKzsc28kUML95_uYf_8d_ajd300b9xV98sZ5PDtv9k8dP6or9_T_4QYmEKHbbu4vZbH0696NtjFotGi1L09SLac05_-3vvvnw6YND56YTxTlnXMSYC-Un7zx6-f2L6XoyHEcmhbdhfjrXtcIMlNNok5KGqExmrTSmMdXJ1UXyYXu3XcznD9-dH14fZpP67PFq2LnTiyUCY4L5EGfTiZby4eOrmBIQzC_mULIdRs7ZcH8PMZ-sVlKa4bCLmYCykkJpRVQoFy01AmQqjoB0NnUNDLhAXVc-BK4YKlUAU0iQc8kpB0qUhZECkWkGHAkw2cA0zymjACzAlBIa0xiTi4CMcgIsUAAEA8600VU7k1q9lbjZoa9qzRDd4SgEM0K7Y5dHqyXmlKMdJ8sFMH089FKJxcmsrjkhjdsdMGScun5IuaDiQqmHDx8x4KcXl5P5op0vxmGoJ_Xhfhetq9oqx1RP5sghOF8Ys4OdLpa2641SCUoYh2a-sIeOAaHQKJh4WwF3SRolkAMAMqQQVVMhojQ6J6KYtKlG2xvTeGub5TyHpI3BAiVGzkR0tmoazmncWeQMAXIiBF6A6XaWM-WUqrpFKkM3cMEE49ub_Yc__-z85OKrL75Vupos5oHik3ff8z785LOPhBJffP3N9c3G2fjo_CyHuD_uRhc2-4MUomnbcbAPzs-AMpNKGAUEVdMQh8m8ZZJNTJ1zqtsWUK6uHjR1HaPfvj4Mx8P66pRjo4SAnJu2aVrz7Xcv7NC98-gB5fz46mJ3PCzns5Q9A_j46RWWxGJ859H5yXwyrTRgNpwx5EIyRBqc7boBgBFAihkYUilUCuVCBFwIZx0VyIlCiGMIUgrvvfWxmTYhFp8TSH7Yde2iefX81nvPUYZcpOTB5v4wisw58FBoOp-s1vNuv797fbNYz8Gn6WwikPUucIZtbSQXknGGpRD1nZ1O6qYyrrdSCCIiIl1p5AyIhODehdV82rSNRJSCM8YSZRvjcegJWM5YGCjOPFE_eEKeGKeCQyQX8_1x6EZ_f-wH5yMVG8FMm0M_fn99N51Nn73Z3W6OTGLnfaRyMp-86exuDJExI3lwTmne913fu_2-c85mF0rJQIXz0i4n2btoPUWI_ZhicCFRXS2u1kXD2I2jTVXL56dzBKSYciHBytD1plV3x_5md_zspw-H0adSdre37riTtXrx7NV3L_f7BL_8o3c-f3737RfPSfDbzXa-0Lt9H0f68T_9wVe__tr7nHOs5lVw0d77FHPOpa2qdz46H44h3R6EZrquS4KLhyueg0DBlaqMnJv6wXxpJD-Zzx6dnhstskvLSXtxdsaBXu26L59f9zubgG273kf3H37zTe_8cr48-nG7O26HkBn-nU8vDLLVcvX1ixvO9aa3iec-hOv9oal14ZoUWxmdCCbTSnIJGSSLhDCGIKcsCxZTCRSBsRioXdWiZDe45HN0GRKxkgYb5ZRp5GH0OZEULHpfQoSYeEaKhRtZci5UmJKFC4gBEnEsZRiAKeAIPmBKEDJQgRyhT3piwAdKBAkgFQCAkIoNUEBIQT4KrbJzQqlmtQgxZucYFKG1kMgBQzeWmJEKZBJaluDReiAEhTkk3Sj0RUkeOgeMsUJvF_UlZkoJGcvICkPMKVrHEQoWznkcvTA62lAYUC4CIXmPjOUYocTgcrM-Sc5SSgxZ1UyGu40UmELhVZ1jKDEKZDklqesCQMkzFJyBEipaDwjIWYw5xcClggxcciIyTQ0pMwa8ZFaQMeTIGbJEJWcmqxoKxBAFg7quXr54_st_8Kv7mxsQbD6bXl6sH11cLNpqsZwkigIFCtzu90_efdAaM5nVHzxeP16tlFTXu11jVLChMbUAJEpcyeC9YGiEFpxxKXL0RptxtIxDpauUUl0ZhrCct9ZHIaSPdLvZWeu5QGRMSwkcFrN2d-wpJaFVzjlnqk1lR08EBGx_tLqpkXE9URTL9e3xftt5H_vRV7rabbu6MV0XTxcNAS5r1ZiqlezqZF48KM65kCnn-354_fouARv6TDGaSsfRu0BclHd-dLVQlXBw2x1e3ez6o8-sFConq7UbbCQ47LrTk8U42pPVum2bH_3go1lT95v7OeIf_fDDqdBtoxjnfYj3vv9__tf_5n4_AJNcYL2abW43lZLBhxjDbNLe3d05H0LIP_3RUyQ43B5XJ5Obm42QDHKeTlo7jgLIaHm6Xq2qerC-nVRu8FiQW7hvJgABAABJREFUA-SQgh9lVTXT-YMHT8GwV199A-EYAqlpI5R68WLz_sdPn317HboeocQI09nsJz_8lP-f_4t_wZAxxsrfGrdAy79llFRGQYEQs3OpMPSZGJd9SJHKEMhm9AQoROfifvQhgi-FC7WP8WgjGHN3tPuUdoO73nbAhVCqUiq4lBW-uj5erNudTQTFZyrIueRPHlx2_bicVUPO_RiG6FEpzVkBvLneA1PHwU5mleZ5Mp3d74-j84lKILIuHV05doO1NjH8-uUmZrQ-DT4eeutC7pyDwvrDsO87QPXt7WY-q9eTuY-EUEZrbYylgFSSM41ITICWysVUK37sRu9CKFlxYUfX29B1IwP0gUjCcd8Dwwrg6AIwHIdRalUyCymkmJ11RAkS1vWMKOdEqSTOWIxJSJVtYEIGR1zwGDIgA8ZSTHVd2WH0IQBAyhEY01XFgAGl7NMwjmbSZCI7Wq4EpRjtQDkyhBR9DiGFCEjBhRi8riqKKZecQ15enRaAEIAr6X0ojC-vrkJ_SCkxQArxYvmk73aFCIExKXxvTa2pJECYNk10frlc3b3a68pEH9arabDe2dAupiEmJGCMpZxXiyVAmU4nyUfnfC44eOcTcY6Lyeyj99-ptNrsjqpWOcac8rQ2XKDgLLlRoLzfbM6Xa-8Gu7n7-J3H-274R3_6j7rjfjZpPvng8e__8ttPP34wqavtdsdC2B33y9lSa95tj9Naz9uWYt7fH7a73cPzxcnZCZXSNq0LAQXLlHfbw4MHJ3dvtowBMB5DnF4s_BBtFz749NHdi2tjeFXrGLL3mXP29PFVrRgCKYHBjtO2ubiYg02GseViIlEejsdHDy8qZUoMH77_6OX3z493W8WxbZsPf_zJd7_7ajGrGZJU4vrV8xBCWzfj_uiGIVHyo1Va55K1lkIq3hq5qJPNrh-VMqF3iGwym4fBEwEhSK2BMV4Zfd4Kzm0fIWfOdHDZGCEkFAACKIUBotC6jIEhR0RAkkpxYPYwlJCdt7qZ9snKqsnGyLqdrk5SCCmmHAP5UkpBAkwpectiTBQZY4BYzefBh7vXd_OLk93NvR_d8f5-PHSCYXR9DETAtJnUs_no3NDb--2ubRZM4KPH78cYGIPkgre9rhuGOPSdVCr5WNV1pLxcn1nrcopK62Szd0lpRSmlGJWSUKiEWCgjIOcixQjImJIMoKTEuOBKlAKIULAwoe0wcCaGvlNScylzCqqZ5hglZzmmgkJWZnKycKPlSulKr8_PyKdDf7h6-Ng6m1yan6wGt334-Mk4djfXN0-uzk9OT06ns8ViMqvrkBPjOHg_hpgz1EYuJ9MYxhwp-uRT7IdBKr44XyvDhVba6NGFgmU6mdrePXj4QFc1l9zU8tj1iOTsIBl3o3d9V5CSI8ipbepkh0qbtq4eXp4exyEOfY5BISwns-DcybQ9ny-v1svzxaxQvtt-0egVYxhi6ux4PB6l0ilRSrlpGyLa7QdA9DnnAv1gfaKUymCdkEpKs9nt_JicS1VlhiF8_uVXOWRr3XfPXs6Ws9E7wFQZVTcNUG5najKtRdueP7m4fHJuD2OK-YMPnzaVWS6nVa0Zcnyb72fK0VdGC8SUI0M-qZWUUirJOTJAo41WjDMUDNrGTOqaA0ABhkVrkRN1XdcFGl3QWqGQw-AQcAzxi8MxFn50sUsRpLg_HD2V15v9za5bnpz0IaVSbu_33eB_99Xrpq12zlEBG7NSChh_se_3_dhMmstF4_o-F_b982dD33ddxyTTkmuJUmK_21GIqQs5ke1Dt-tZo4RRs8fz-rx-893rcPBhDHpSV7WIEUpJRvPuMFibTi6WXe9vrw8PLteSi5vb4frNPiSqTmab_WgZgBCZg5jqL__6mY3Oh8SlyFC6_Vg3Fbi8u93mXJgU3o1h9KWg1BwyNXUVQ07Hbtz2wgiuVeh9tz8ypkbn5m3LGPuPfvrDL799cXN3nDZGnCzysWM-AWeK4f_j__Nv_sk__NFvvvjOBX-7G3aHcXG-_tkvPh2vb569fPPidotVhVJd33fP74f9GK73e91q54Mxqju6ojgAPHt9E0qqq8rGNKaw79yu730qh5hIMMF5v3MFSjU1UND6KGvFORaEkCkTgXc5JdOo7MnvPQgokfzg1cSQD8VmAIRAwCGlAAUxU0mJiVIow3FEKYuPUDGwAXwCHzhgiQkyQS6UcymsUC6ZWClgEChjYciBYkbGsvc55bppSi52sCkVwTG4WDfab7tsQ0mpUGZSARH4QKEwxpiSOWQOvKRMObvRM15KJs55yRlS5oJnIq5ZSZmSZ1Q4E1xwhkgxIufI0RidvC9EUioARjFwLCWBWZ3mFIzRGLPWMo0jMsoh1XWbUgAihlhihhKVaYP3UsuSU4yecyhYciYmBQJwLgoRA4QCpm4opRJjSZEBZJ8LK8o0kXJBAAZSKWCCc6604kwAQ1PLRuvlYlEb-fjspDZKFJJcWWfDYBHQh-EnP_rw298_-4OffLyaTKKPVJJRkjM2a5taKy2FVlJrKQoglMmk0ZLlGEvOkchofez6pmlCCkqKm13PBAfG9sdxUk-4YFIKKYTgOG0bDSVCYRwZ8hhTO6kKvV0Yqt7GZjYZUzx2PgR6vTkUhqMNNiQAFmJIkGfT6uJi8smTq8N25EIgsNN5o5jqQ-CV-vPffrU5HCQXPmXGwDrXDWNyuZ1PHzw89cW_eX5_v9ktzpq7u8OrF2_apbl-vV1M58NwfOfJ49s3rz54-nS728-b5uxilYPNo3_98s2vfv6js_lUSKG5DCVtR_v__pf_9ndfvYwEhXMukBvx7JsX0_nM9W4yrdaT2WF_uLvdLlYNkTyZymFISgmp2O6-A1aSc_2xQyClzWK1fP3yzYfvv3-z2aQQhsHVTZudzTlOFvNM7N2PPzZ1-_u__LXtehRaT6YffPbRqze3jx9fPHz44Pe__rw2POaM2lxcXWCy_P_yX_3niOBT4IwxxqwPpUCIuVDJufhMjHGfwFP6dnfTVpMhlM6HwLhPNMbUuXSz6wryXOj1fRdL2Vu36cZXdzvQ6uX1vVB60_W7wYaCijFtBCRinHVj-vz7LUFGLMT44IIdbGZUMjx_tYmFuNIxpWHwzoV6YmojY0w5wqaz2-NRSOUpH46DqWsiopxvb3emMXUlfaTBOZ9K11sb4-44xJwpQSEYXDj0neBFok45xRSBkGkBDGPwgSiFmChbm6RUGWi_64_9IKU8Dk4IAYqNzhnOMxQXvBbqOHSH_XGIiQkeYkDJMBfBhI22JEKAQjllCslCSpxzhsJ7D4Ccc6l0dxy4EgiUU55O29H6t1ldjMTEW1UXCs4Z4HAcmEChpLVvAcAipsQBgaHznklBVCCn4CLnQmiFpQQXsSRRa1ZYDokITNsiK4WxlFAoTsHlHP0wCkQq5MKgpK6XU4qBFVyeLMZDjwWGwzBfn2RIk7putIpAk6YxWqaYmOR6UkMBjkUx1jZVf-zWq4lgDHOJibpu5IIj4rKt3eD2-yMANbVJwRkpl9NWKlU3lShs3x2NYFrKdlq5rg_Jr04v54tGhHA-mz354Mnrl6__8T_-pbUxRP__-lf_3afvv3M47M1kwnM6nc_ni-mkMd9_980n7727XE99SIf9MWQ_nTbPX73ZbXYxxpP59PXtVgkxv7rY33eUY6EikA37--tvXvzyn_7h7voYU_4H_-jvD_3-44_f27y6YUBtYyClptbfv9leLGdTzYc-_uSzpz97_zITzYy-vd1Ma_Pk8enZYvr981cXl8txCG-ev_70px8ln6QR3aHTgo2dLYBMcMYY-ahqFcY-RxpHJyvBiUtgkvEwjn7cVe2sUBGISgsUwpjKuiAr1WhTgS4Axhhd1cA4AQjOuNYhsubkojhbALXWIHjhApCkkIvl0vusmiZbj6xkP9SmMpUk7xtjeMlSGVS8Xczr6QQlm0xnZjK140DIusPABS9UeC05iBiSqcz965tCWXO1XM2G3f3-zQEwQ8rH45GltLl5c_3s6-Orb5hsiIq3h-5wQMoCubcuxHR69oBK7I4D44jIUqb5ciWVJGCjd1zKmIsSEH3kHHPICJR8AiwgREwZGJimARcI3irvoV3Ox-MglITCcoj1fBqGXirlxrFdnwy9VfptNo4ghHehrrRSyrQ156zvxuVqFYNXxlhrUynttEGA-fLUB1sb9eFHnywWJ5cn8y9evviLP_vL__7Pf3t2diqE1kYdusMY7DiMjAtAKgWn60WwXiuJAMPRdncdAYmKaSPIZ4CCqPTM3N7chcF1e_t2nuEoUCqMkUvhxrhYzrRR-8PeGLM-XVycr6tavfru1cXJinN8eHn56OI0DP35cvnOw4vZpAZIb-6_PJk-ntYVF5gSpRS10soYKFAYcsRhdG_vxq1PwNgQIgEGIiakj3GwjgoTire18TGFGO_u7s_Pz3aHg_PBZ8-U3G8GhuBHn6kYozhjk2nTVlU8dna0SnBlpNGqrk1O0dsRGebkp03NAeeN6Y7jvh9T8kpwQi4ksyEqyb21bhgH66UUs0mLiM3bBQ6U4JOPiYDZlArybvRNaxAAEXtPqsD2OPQhQqbb-64QcKkZF7qqr2_u-tEPLsRYtJInD042d8cMMIbw_OUNIpNSvLnZDuPY7fZxjDZE6x1Qqapa8pyHgNYVKvujczEVSu16plRbXcwn64kS4jjEsHOHb2_LSHa31ataNXLo-tmUD7f90DkSAoVMsXS3Gynk1UnbZ3fzYq94VgoPnS1M1Ercv75fTOvjfd_3Yyw5-KBbnXPy-8PJyaKuq5ubDdMi5uhToJyFrnJJwfrp2Sz00fW9UcymiI2AzITEUKBA1kJH56ZGOef66K53-5fPr7959lrV9cb1_9_fffPTqzWvqtf7_effvDS1Gn2MCG9u9jHGUmCyPPny9Y2qK5Q5MBh8iKX4TIMPup4088n-7pgg1bN6e3_sxrGaNVHAth88pW6wLiRELpXkWoi6iiHO2hqRY8lxjIhcVDKnCACI6I8OCyNIhIVVLNlYUikCQTBIAZEKEWTgjEFOxYdCBAwhZmAAIUMmiBmwYIglJuAAjEFJJeVSOMQAqaCAkhLc7dBoxgSFKBsVjz3nUi_mUhs_johFchGtn8ybcXtghd76kDgXJaQSM2QqjEPOQEUgQiFyCQthzkLIQoUVhJg58pyCqmso8Dazx5SBCHJCZIWISZlLBgLIxBlHQKAsOEfJhRJSSABOIXKGfuhzdIxSLplLnWNMIQjJci4EmQvJBStUUoxAwKWWuilv_6YyceRM8EKZcQSA6AOmzBBEpWPOCYgQpVRcSik14-L04bmp1GFzKCnUVT2dTq-Pu59-8t47jy_ccJhNTCz5_v6eIQOOv3mxWbXNh08fPV7PFXDGMcQ4DLadtJLToq6wYIFina-MHkarhey6QQqeMgnOY8xam-PQRyqbXWdtrIxOqQgpj8OxnTQA6X5_PF0uICdrg3W2ktL7yCVjjG2PPeciZABk3TASkE3xMAzWpm6wGWAIYbpoU05tpYNP65MVhGwkuzhbR2e5lN3Y-4Jffvns8aOz8_OzHMN6uSg5eUzjGDLi6cPFoevevN4arkCI495TwRhjUzWq1pPWvPPuk5tX1-20NZVeLpvT5Zqcb6VaT6bvXK2N5EbJSHAzjv_6P_zu829eRxAJxOYw_PDnT4ix65f31vpHD8-V4BcnJ0LLN29uLx6s3vvBu8Pt4fR0qarmfrd3o60aA0xOl_PHTx8P3WG9Prl58-a9D9579uz19u7O2WEYxsPhCIhMCDNpc4yr83Pr0_H2NRfItH7w3odvXr2mXC4fPkBf9vcbIYAYnl2czqZVwzn_3_1n_5nP5EOmTCkVrlVmaEcPAIFgyKUP0fmcgFKWgy83u-PehUNvUXLNWR8TY2yMiQruRr-ctBlKDKkLcRh93bb3h4FJ6UrxOW32_c55T3AynUZi52vTd67rbc4kBctEw9F_9ezVYj1BLl5d33IpUi4h5bZtdsMQYkIuM8E4jEKZt8wfqaUWYrs_1qoeovcEqbDjYJUxg4v3hx4YhpxR4mADCpWQZrOJrvTt7bapdQLKkTabPZdwupj3RzvakCEXBsPgXIyC4-Cd0pKI7DAKrUNKbnTKVGHsMzBg0B0GZUSmUhIUyDlmAEjBa90AZ_ltWmAtF1wqDYDeWqFEyFEIUai8PZbgUhAC5yKnxDjPKdneVVVDSAWRS6AMqWRVVwhACIwzBEopM0QpJXKMx54h5JiAqHAUHClTokSZEFAa7YYx-IxSrN99KkqO3h8P_WS1JEqCS9vtE-Lu7jCdLSMlSmVxutRaMQTnXNtOQwqXlxdDsFxIwaHSEoDllBGBUUFWTpvK5xKJ3GArrbjkANAumkoaxlj0Yb2ccMFCCOv1ydCNs3lzebq2x_2L56-jc0_feXh1cfK73_zNpx89eff9p22jXz6__fM__7NDv__knUc_-eMf_vv_3__QjdbU1aPF7Ori7MP3nqxX02--evnxp4_7Q1cI5_O5i5Ex1vdjVdeZ6NP3nj579jq4MJnPDl3_6fvvgDIvnj-v2hoTMcHrpnlw-WDodvdH11b68vH5dD4_HI6X61nOwXfu059-Mquby6vLD69OHl-dDEf7P_vTP-r6QUnT2wEY1pVez-eCsXFws2Xz_ifvb99sJWccZREk6uZ4PFR1ddwPlACISiYpRMkZM0uUtOBKcoHMD33dNlJKFJWz1symHNANAyAwLYmAgYTgVSHK5X5n10-vGOO6agAZ5MQxDrt9ezJpTxZ2PyhT5cJTiFzIMIaQUxh9tajaibHHAznbbw6MgeBSawWAwOTheFCc-37IpUjJuW6qybRezl3nUIh4HCfLta5Uip4rUaBQjjFGIYSZGMX52PdnFxfHvmtms5OHTycnl8vV8urhxXZz4wY_Hg9UEGOJkUY7TGczEAzfkqsj7YbDdLmYr-dMCqkVQFKVYsDnj09i77gWmagAy6mkUozWlCn4KJXiUkitgwtaqmY-l1L5fqwXEzdYomDqxoU4Xa_sYc8K1JOGACuj2knrnDNtzQDW69Vox8V6baqqQFosV1IJU-nD_vjq-e36_KRqJ7IWN9fPv_r8y3F_UAxvb66l0sv1kjJIrceu68bRVNpTOV_OnfOKC2U0RQ8le5tKQtdHoiy1ggLBh-QjBWKaYYLxMHJWTh6eohCmrSYnU4z-7ds9fHK1WM53m22t1MlqznMIY3-yaFiKtVY__eHTFKLiBanMJyuGLOUiEe4POywsEQQfCTCGIIQAzmKgREUZOdgQKQMI63NOuXeuEmoMVgqBHKng85u70_Vid-iEYFpXu92wms1NLWutm0mtpNCSS-RXjy85gECxXq0Uw_HQKS6C9Y3UQgheSDA0Uqzn7XpWx5SNllwwylByqaetAECAt47wQtA2VSUVlUJEKcWYkx0jV8oz5kK-2x4jATIhsIxjcAxI4qGPx9Ft94NNiXERI41jcDYKrWIuQqvVYvlys3Mubq2LMdgQ9odealGgnF-eAkGKqZ6a4TD0h52SPIcgJCeBopIFmE3MNM1itTZMkRt2b7bD_uiGPoyOG_Sx8GUtL1utdRy8iGV30-dcmGL1tCHr0zBwLn7599798__hK29jb7tKy-3NXS549fTy-PKGUn7vF0-ffXsLSN1-B5DrSXW43QPDhx9cbTf97njUlTne3UGOup0EaxnA4aa7fLJyvR_2R8UwAiuMSc5N08ToFRdorZHm4Xzxr_7qi1_8-JOcwtEeS8zSyHk7mUn2wXuPtofhxgZZKy2bRORCak_b_a7fuTB_WrlAN282658_efnN7eA8VtJZzwSzzvuS5o9mJEu_HaEw66yP9vnre5-QFAkGru8pUyklEbjRB-u6zWFiFOQSXGKcB-uF0ilFSBkwocSSIqWcUoYQS8olE-QEMRQbGGcAhXJEYCUlSABEABlihlKgvH0WiBmAAJEpiVDeAkkgZQBCzZCxUjWq4tkGQGQFCpHU2piqv78tqXAtKEQhWfQxjLZkohSlUpBLCbGkVApwySlEo6uSYyEoKSHnvBQAZJKRC1gKMmRKIeMIJQwjB0AgKJBTQsGhAGeIRKVQCW-7OgSZCjB8yzzQTbKdAICcCyu8AOeCUmK6KimWFI2poZSUEgdAxlIInCMCZIqFASKLIRRAAQywpBQLAdcq-8A5Q2SJ8C0nHgoyBgwkQW7bSTUxZ-fnkMsPf_SDquIP37laT9qHD9aLqrq93Rsjj739-sUbI3ldt0_OFqfLxfnJZFlXCvDzN9-t2onSRkqeYpRaKYabwxEYUCltVYfoG6MJoECJVIzR3nsAFlJORAVYQaZM1Q_9-elZ3_dKycfnp5SyVNLHdHW56q1vq3p3PBIVptiynXXOZSrex6MLh6O1IZaCjDGmmBYq56SZHIb0s4-vTmq933emrUbnnY9_880zoytnLddca3Wz2XaH8WQ5qbXeDbaZtKuz2YSxv_7td6-2L5az1XjokJMQXCl1dr5czqaM8t2bm3feeXy-nP7hD354d3OznrTd0L_39IIjq6oKoNweh__-z3799bNXuYgIMFlMYrbBewC2fXlXSpxPpyG6955e9b3b7bcXFycpZ7T58uqiqvTgQjd2qjZKq3Y5ZaXcXr-hTGeX50YpyLEbhuWiGbqBKyOk0KYe-j5TvHr8eDZtrl-89KOtp9XlO--VGJAoWPfe-0-vX78ugxOVamfT9XJdojOc8f_tf_qfHA5WatW2xvs0xhBSKQWGRDfH8X6MBTFz1vXxYN39Ydz1x5QQOb_dH9_cH4my5gwJrfMnk0ZxvlaVVtJncjEDUEF-GHqX6DB4Qii1fvZqO0TgEppWH48hcyaMMUpKBpXUGRjjLIUYKQ1DYAIWJzPvaLcf2rr2KYUUjTHDOPbjCChywehi11kXk7U-FQTCSCWEPFp_HC0wNmYfQj4Odj41-7tBS-lj6PvRxziOMedcEN57emH7YBp96MfBWesDFJ5zhoIhhJP5rBtdpZRgbKb4EIlK2e-6wln2UdQ6-JBjRoS3A3_KAZEXQIKCULgQXX_kwAtCyhkYSykD8pyRcTF0vakrH_Mw9CF654K1jmsJUArkECIU8DHousklj90gVB1CUJylGLKPnCj7GEbPOGOlpJyI8cKYrg2TzB6tkKJgyQSF42S9RAb2eKgn8xSD1ibnOJnPU0rEeEyxntbasHY-64fejaHvR-AslWS7TigZU1wt5zH48diHGErBu8OhMhIYSin3zgLn-9s7wbHf9Uzx2aRmBXIqzo5ai8VirrU6HrvT9XQ5aXIMY-duXr86Wc0fPrjAEin509XkBz9893e_-faL3_9eK5RCaFP_5V999clnP_rtX339kx-9Ixg_PV8Lze9e30yns_myrbScTidSSUSYTxc5J1MboRgyvtsfX72-vdtsPvjg3fu77eOrsz_-6U--ff1y6H3wXleKSe7dmEL-2R98dnFxGkc7rUyh8vL5m0LpH_6zP7558WoxnUKOtZYni9nj8-XJyeJytRQcq0ZzhlIIyUlKfPXs9cMHF3c3t0bXy9X0_Q8fOBt2mw0Q6LqtZ22B1EwngFTPGiakG6zSIvocbQDIkOL99aE9mdVtWxBTSsbo6fKBpzDacPrgkW51DOn80WNg_NHjcz2vj9uOfNBSjP0AgNWq7jeuROCao9L1dFY1dbs84bVpF_OMWbR6GMLk5GHJhJjscSjZd7t9TlmahkOZrRaCsZtvv4qUGVcR4mp1ZmbTXCClklOwziGVGO14sAyS78c4OA4sxky8bDabfuiBla47ttNmv7tnIO7vt0IqAAYlz09WqjaAwLjMSnIjZ6v1o_fflRxyJEZFV5WzlgnZ7cfV-cofrXdBKMErBRwRGAeeYqJMpq4QIfqQE4i6UqYugMN-J5UMzrcnC3_suORStcOxW50vjeQ558l6NfbOeXdy8fD-dvPBZ58JwXaHHjlfrVZKcY54e7N796N3IeeH7zxKwQ27-9_-2V-__u5l6HrG-frhORCNx3H78vbBOw9ZgsViWSjv7l9J3g7dIKWKmexujC7FRMqYFJNppR0cFkYJGLK3N3BMy-CcFEwrE2xwLiohRYHkg1Hm_R89bczb4H85n9Y_-OzdZVN_-OTy9fWrn3_8wWLS8EIVRyMlk5BS9j4yBqMPMWcppZFaSCEFM5XZd2NMmRBCpBDS6BNyJGSFMkFJmQRnx2MvGBJBAcYgSaE4g26wmUgZ_f3fXLetOj1b28F_8slHT07mINT-fpdDlFJiTIvFvGnqi4sFUaIclGKnl-du7BmD2aSpmtoOkb0VPVdKSuEGO45WSSm4UFIXoMooiuSDS6XEgr2LvFLWpcPgQfDeeuDchnR02ReyPu0PfoTiC3O5uJTNXH357W1vrdSSClwf3A8fLl70h-jiru-qVjnvb-93MSUoeHd_ZEIIIVzMDDnlbG2q2yaFhAS5lJRLoCymSjcmWgr9MA49lIAcSyOZVKxpIpVEqAT3-yEcbdgHKlCttO8jCz7Z5Pvw7p-888VfPh8OviC5ox16z4SYXC7truu_u54-Wg4BNq92yTnqBjlpVdXYu940dVVXty-3UgoKI7lo2ka3U9-7Rqro42Lddts-dqFe1IGYbJXWcr5c7m5vjTEuwH_88x-M49hvDyTFi9ut0c181trBffD0Ic85dPZ2c7wfbd97YZQ0anPsADE5mxhs9l5NJ57T9vUegRVGlKFI5FpFF6SUsbehDwTMumha2XdeGB4oHbZHyhEo77a7DBBiZoI9OFtXCmw32KONKUXnc8ogkPECziNRCQkSQCmMF0hUxkEYTT4AZQi5AEJMkKE4D4UgA04FxgwhIhZgBDEDKyAQ3GuQc4i5ZAIqgAxihpxEa1hm4EP2ERJppcm5EuLq4eX-5a0AyJTNcj5sj1Jz242AgClDKhyBYswpYy6A8NZdSDkjQKZQMiEWKCWlzDjLo30b3klTJcrJWl5KycQZTzkz5DF6pSpEFnxgCEJIKIUzpJyY4DFE3UwyY-PhUBsTY-RclxAAKMbElSoUKSSGgIj4tt7TTpIPJRERMQ5AqJSEUihnxnlOUTcmx8yVStZJoykT5xoglgIpUT2bSKOF5IvVnKiczOfTtq6Ntl1_dbJaL1vuc13p5bwpuXz77UshOZe6FOSKa4EXs2mjNeV80s5SJm0kEBTKQohhTIly09RaqxRTzkkbpYzY996F2I2WuBh9fP76TimljATErjsqrfu-4wwrY0pMuVCMUXCeMwSfRu-FFMA442rfDZnKbugSsF1nY8ox51lduZTvt5u2bqWU7UQ_frhcm3qzPYZSKi0jFe98O2usD20liUArPWtrY_RxtK9e3d32trfx6nR23FnGOUaZnFudTfeHsVb66uJiVpm729vjsXtwfsoFJ4re2eW0lRQ_e-8JQsk5jJz-7V_8zW_--uvt0V08viTG3nLYlOCK8PmL28lEr1bLY98_ODm5fXP7q1_94XG79dbnEP_k7_40WB8y3Ly5BkYxZwHCGL2aLW5fvanbSjAupF6fn-y2u6EfARkVmi9nbhi50qcXZ-vFWs7nw2Y7m9V1rd3obdflmExdK8VffPXi9Hz1-MNHx103m06Od7umnfD_1f_tnxulDoOvFWOccc7uuvGLmwNlQqMaw17vxr53XQj3BysMZ0yKwjljPMHhGGe1vN8PGQoXDDK1lXYhFcqopCpcKv7ofP79zT5TlkoC8u1-rCp93x2UEL_-7joyHqCMOZfg3twdnlw2g0dE7HJiqBhHZDzlFBA4wGAdslIIjv3Rhfje-483u2Oj1RCcFBwYJKK-95GxMXoAHJ2nEn3Iu91AWBaLuSyMS-5D9CFxwX0Kpm5Gayd1rQXf7W1hhYmyOwwpUKBAhSkhqNA4-JSzj2HobNe73rpuGApjIYXRu2EYpeQ5BDuMCQsyHlOMMYx25ErHmFMOk8Xc9UPOhRBiSoXzDJkpzhEoJi5lKil4Dwgp5qoyBUsKcRycNlpJTVjGfpBKUCaheRgcAxKyGvaO68IZH_sgDOcVZ1zGlJSWkAoTQERCsJQz5azamlICn6JLdhiamYECnAnvwvJiBcBcyMgwOmdU7WMmCJwhCpZSWq6Ws9oMzueYo0-JMiDGRO2kSiHXlRmHAQB9iEYJLqSqjOFCVdp1ruuGp--ejkcrGd7c3j04XdlhWMwaASWGlKNjDP_uz3_IOAcU00pPq9b7-PjRxWI2gYKvX95UU0N2-OO_-8Ng-9PVKhd2f3t_7IbppF0uJrvb3YOrCyQSyHOKpRQB0BhlmJi39Zu7zWrZnpyfvrm-__Sjdysj_vW_-4u-H2fLSW30o8vlsO_vb7ZPH59VjH75sx_d325S9KvFwh2GiZbvP3mI_Sg4nK_nspST1aw1elppxKKEvLvfa1bW0xYz_9M__TvPvnl5drpinC1OZierZS65v-_OLi_2-91-uzu_vGCMonWUqB9DpYU2KlOEUqCAqGSm4AdvZtOm0cboidY-2ZCiYJwjTGbVxx__8Pn3X8-XK7C-JNrebptJXVWyOpn3wxB7y3NE8NHZFJNpWwJyIYFgUvNSaOgOfn-03S15q2vNKbj9nlEIth93eyPVaHstdHv2AArP0foxdv0eOUzny_XVg_s3d-v1hDEUWrWTibUWAnElYwjBJ46wWC0Qsj_sd7d3SmrGmVISEMbR1koDAABJY7ruGINjyDnjbnS7zU4bzREOmwMBqqqSpiHA6WyecmCcx_g2JAPGOTKuqkobBYApZV03whhdtbpWru_IeyIqwChnAFbV1WS5KpkVwB_86A-GYQDgQkglldJitlgd9vv5eiUlSsEpxGEcV4sTLvj64gS5GIbB7brpvLXBpRDWD8-H3vaHAYCHwzZZt7vbm7o1rZq2CylaUyttJGnhxqC4aNpqcj7xzvVbD0BCc8aZNlrXmhvJG8mWFQeutZYcOReQ43TaOhtOLhcXV6ezepIjTJvqcjlZtlUl8Op8pQW-c3nRVhKQaqMZlJgipQzAkJW6qY_9WFcGACQiEBakmMg5HzI5F30KBTFDyQXiW7r2_3j9NZ83istucFILJoTgTCuxXs4V54azx-8u33_3yfWLG8Yxx7zbj1pKIVllquT9ZNrKnBHLqjWztjVCYI6Yo5K4nk0WdeVHVzdaaUU5vxWHU87r1SyFuJovfPCSs8pIn8LgHJWy6-zdcXSpEMPRp4LUu7CeTH__3fXr--7mMCTAF9eHF3ddyPxgHXH25dfXN7v919e3XJvtMErJnm27u_sDk-Z6e3TetTX3oWyOw-lq8XqzDSFJbepJFXwulObns5ASJHKjtZ0riYABIEtDjM45ex-IYgAmZEHDtfJjJ1rBWMxhHDd9oSwVqgd8vOvS4DVXidJyveyuw_3NXb3QPvRCAuYoBGtOmvH6EI72vT_84LvPn2skt-_0vM1MVq2MvdNNQ6pgysNuDyxjLIvzM0ASKZcQgs2z05Zi8c6j0cgUsDTsjhKZH0Ot9d_58WdLrv7sq-_Of3x1-3oPMZCE-bzyQ1xVk_2-H_uxL8Fiud9u90c7fbIKY3e42bhxKFwULfZ7m4GDwjR4Jgq0MhYRXaqqGoIr40AFfIyykbF3YXAgOAimW8ORC22kkvYwGCND9G4Is-XMHvv95mAMKzkAJerHUhjGjLmUmIEKYC5UAAXkRIMzs0kaHAAiJEgZEMAHZAAxARCEAJkgJsgRACARQIFQMZCsJIyhAEJKGCJjBRIyLTAXzrhgMnZHwRihns0Wru9SAeQMGFDOSIQxc44lZcmgpAREyBmkrJQggFKAE5UUcqCSMxYgKpxxjJRz5lpgKVxKACjBc2QCMRMBAUqOwKTmQKUUklywUoigpCgqRURccGWqTMWHUE-nzvlCGSiVGIQQyhhkLHmPCFQy54xx_hYHxBggYFu1OWbGBUMuOMcCOWXkCIhq0iTvkTPGeaao6oYrKaQuBAWgrirgUFXVD957l6XcddupqaTiE1O9_-6T9aJum4oLdnuzv3p69vH7D66v7yvk81krKM-aSitxDDEn8t4ryYFIcGljkIJrJXLG4KNUwvsoC2wG2x-Hqq77wfmU60YHH6dNY61njAsuEGE2aUsiRC65SCVXtWGsoOAxZimF88G5OA7u2NtEOI5utL6qa6I0-qCUuDg9MZJzLTkrJ7PJ_d0-ePvk0QNWSlM3pYDz49XJSYh5sz1OZxMGOLo4dN3JxfrV7ebjjy55pvv7Tkj-5Oq0bs3pajWftLO23t2-CT58_M77mvFGy-HYzdrqFz_-yBQ2bZsUwrbz37149ey713c3dygQuZw2ZrcZ1pdzrpU_uJzL1YPVxXK57bqxHya1_pO_9wd317d3m920bgMxIcTh0B-PfQh-uVr6cSyUycfr65v1ybquW-vcJx9_9OrVy75zPsSLy8v1yXKzuUNgq7MTY6q6rjc3b2zfDbvj1eN3nn_1bLGcxUKL5YpSqmpjKvP6-atJ1TRNbbSQUPg_-9_87zMQR4BMKURAlkIGVmIu94fej3TXW5fTwabKVKONTCBXyjnHGX96MZk2aoiEkgultOK-pEAlUhKCt0oDwP3eLSZVY9R2N9wdRiX57X7sRtuHFH28vTmaiRmGseusdeH5_YiCMylyouDp2B-VVv3gGQetRAjJVCZEevzofLMdnfM3u85aC8CkrlIuUmsmeEZSkm0Ow3H0MZOPwVMKIbIsJs0slDz6gAIBhYth7IfVfG5HO1_W-3339Rcv9oeeC4ZAAGjq6jCM3WFgCmMG592xG1xwb_HkOcRKK-d9gWK7gYFEIQBZ9g5KRi4KZMpJax1zopQ5Yyln5DLlyBBRyFwAoTDObd8zxnMugrNJO7PjqIXggmujox9LIqFkKaCNtscx-lgZLYQ83G5MxbNAQqgnNZQcfcZG271P1tWzKkMx85ZrrWrDQTLJBeMlx-hsTinaGH1kkkstSkFl1Gy94ow5F3LK88WUCgqpBOdVpXJMnAtnnTZV9F5KJqREzuumAiyUSyJiwHKKQkmkMptPY3BCMyW5hrycTXw_zpbTY9drJTkwY8x0PtvcbSql7Dgyietl2xqxnC2evXj20dNLXuj07OSzjx7-4KP3BXnGythbJbD3_t__93_BhZjOJ_0wvH7z-sN3H0c3Si4hJcRyt70fu-546JTSr-_uTlerlFOK4fL8pBairZt9t98dhtm0_dmf_MFXv_lqNZn98h_8ZPtmnxP-8R__WBrZ7Yf33n90cba4ue20xIcPTptKTev68nSuOSymLRBpZNm7ppZnq-l60vQ2UMmM8bpRxIqS6uXru6__5pvVanY47K0NimuFdLjd1k2rVHX63jvDdlMI5oslWY-C237kgs8mZry9Z8BciA8fnoWYc84X52ccYbFaIRHXqlKqbs1v_vzfXz15uN3csso4GyrTQk7JBdd1XDDGwR_3YRxSsPawo0T1-akREksOux1D8PsjlqJNTSlyKRFICuX77XF7ZJyJyihVTyf1YXNnu8FZ68bjkydP-_4--qiVySlyoaz1gAXf8kYRu-0eC1Na5BTs0LvBc8madp58bCe15HJ7s8klm7qOIUuFVdUGHybzaTufHPbH5emKKCldeReVkG2rudJDP6i2TnaUkqfCmBTT5SyGxCSjgkwqhkLX1eH2tpSSqXAlhamFRM4Z40iZdG2UlpFiO585byfT5uL0tGAJ0Z2cnhDCen0CQM4Npycnk0kjlKKcb292z37_zery5DC43bbnppJcXFwtmZGYiAimF0te43FzHDvvUqhXbc5BG-n6sdHKNGo6l10ffZenU2kqiZUAQt1UUGAyWfjB8QCIEEcfA0jN5-uFEYzlwggfXDwgN-zuD8N-d3m5khA-eHR5NmkNirZRHFguBACjd92x51IWKIiccrLBnS6mWBhR8T6EDNZGJgXjPJdCiM6FlAsT3MdIOfucY4pSylpp50LKSTCctRUV8KOViIhwOpsz0hR8VZmT5QxKYiVKqbrDPqX4-OmV0VJieQtMr4xezZvTyaRW7L2rc834tKmMUQDgrZdSDtb2_djUtTFq2rTe-rpSUghicL3ZmbpB5HrWbA_DEOJmP0ohrl93nNjtOO6t2wy-i-lm2-_6cch0349UAIW0MdphFICvr-8Zw8xwu-8PvbMx5OAPW3-2nJPkKcTt_rA-P7fexxQPu8NiMQ-ZxqNbr6aCo2Biumzn65nUMnOI_QAhlixMY4ThwjCOIR87hZxcht2YDgGBGcl5iujR2ZEzxoC5YXj4zsWLb15JVii44_URSzQFQJoS3e5mp6pq_u769ouXvKDQjHNRn01iZ7nLGSEWisc-x8C0JBKrJ6vu9Ubkcrjfrc9W13f3SIicJ8oMMIyWbFCKTU3j9rtffPTJ3XF43u3ah5NXL7Yx5wSo5-b-tjs5mxzG-JuvXngtvn95GwgCg82bnWpUjJmQu8KylAkgQilYiLJ3EaumSF4pWRmmtK6bmgs1HAfFgTPQNQuDowLKVHZwJSdlOINScubIj3sLExW9FwDDtgPKnAPFDCkzgAIFQgQkYAwiAEfIBUaXKUHJ4DPA2zY-QcqYCQiBA9gIDP_W-RUzMs6QIReFEmMl-wyUGEJJVARHQIpRcJFsgJI5ABR28v7V5tlLKlgKtaeLEGLV1mHfGabJepFJIFGI2UdAZIxDAcpQEknFS6Q49qZWYQxSKoaMYuCM5ZS4NIUxyglLYUScy1wyAjAGOSYh5f-fpv_62W1J8vSwiEi73Os-v-0xdapOma7qaTec6SHBoQGJIQhSAilBkAcBQX-jBEikIFAENZxhz3RXm-pyx2zzudctkzZCF7t1v25WYiFXZOQTvweRas7C9VPOigh_qm5XF7eKaDqehlWfl9iuV8v5xCkAApEVpUEAuNQcAYAFmJmMqyUDIBKhxpQygCCB1lYp9WnJRAiRAFlYlFYCjMpwLb7r19ttGMfNbr27vCSC_-if_GmYg3L45edvUl6-eHnXd40i2h_Gb767v7zekrHP--XX3z1--dk1Mb66vmyMLjV740IKDNIarbQ9LSHmTEopUinHftXGXEMpY6jnKbR9-4kpWFImbVKthND4xhhduWJlQdW2baz5fv_cNU1Y4qerkiKQikwhe6cF6fk4da2bQlivh8fn42qzaq3ZrtZOK-tsnMPVZnvcj_MU-mGYx9PFemWVetzv39-_v9hsiPDzz14sMT0fDo_Ho2va9-8_Xq1XYVq2Q__q1d1-fxCWfljdXl58_933ipSAXO2un58_3N5eKUhfvnn19vYacuoNLgL_89_86ruHx3f3ByXQDcOf_NEfCqu2MZ-_XeeSfv2b-3NIdy92q6b99bcfAMo__kc_tUXdXq0_Pu3DtNy-vmidaZr-_ceP-_2BlD48H6wx1vgkVTgPQ28d3ezW9x_u4xKu73brYXV4eHTa7p8Om_WqbV3JNcay__C-xCAI-8f79W5lvdXWP354-rP_6B_XJf_NL__6p7_48XSabeN3VzuoVf35f_XfHKaqFDRGxQqalFbKWsNCx3k-xRRLEcIxVuf0ZWfnXKLwORZt1DGWwmKMIVKPz-cppv_599_PIf7y_gmrxFJjKIVlDBVAtLdoTMqlorxcrR6O8SdfvDrGcDqc5lqnEIFpToU6jUDzuHSdu7vafv_dg7PuMAWoknK5fzw1nS-ZRSAxI8sSlzTH43m2jctVnNa_-917VLCkyqUySRYg51rf9P0qxBRTXEpElpxT4do3zXI6hZi_ffdgve82wxQDkhKWEEtmAebK7JvmeX9mZOudVKlcmSWXSoAhRAKotVaplaszTQxnrizCAIpZEIEAUyppmZHgk5bIOZ9iWsYFkVGhAOaYiAg0pGUB5JwSKeRaa-FSqtZqnhfXtCVGCZm8qQrhE01kyO0GyqiUy0yMMFw2XdfZrkNrQKlm6EuMHDmdJkkpxtCsW2fs4eFgjE5Lvnz7ejoez6e5W7ciEJYwnoN1CgERVS719ubieX9snI0lcREg5a2tIkZjKYxE7aAUYw3BWb0sy9XtbjocL7crp_Wqa3pnueSb6939_fNnb2-1Ii5l3bXjPHbO7jbDer1yrS8x3VxdTudz4-04xSmm794_Pe5PoODq5uJit_v93_3-i6--vFit766udttN48wPvnh7c7XjFFdtZ7QmQmYOsVxfXxlnGPH39w_Xu4uQ6n48_fjzz6yzy7IcxnAOy_pq-1f_419qoKvt9r_83_9HX764_cnnL0qYp9PYD83Qdp9__uonn724WPfGqfk4vX2xWXeOc2yMPk4jAuRcrFGNtzHmpnGdbSuwIHX9GkCWKQADl3r39hYrcK1XV1daQFkdY5RaKnNagtZglCbSacmGqBZoV6scY-f9t99-13Rd07Y5JeP83cubbz98vxwngPz-2282m4vj_qnExFFymE9PT23fo9euX8lciARL5VIsoSxLDVN42o_7J0jFGIU1Qc0lZSDkKlorKXne7623nEIez3E8k0egenn3eTtsjvePSvPH979VpJ--_66E0O8uhHB9tatQEZQiUAh5SaQwTpNUsEojRMjx8d27rh3iPNXC28uLeTyVyv16vVrvzuPZWff88ARSlNIfvn93_eJ2HKduve5aOx0m0rptOme0M7rpeyYyzsd5nKcAqJthWF1dNKs-jGcQiVNoNysirEKnh_nFF5-lJbfdgAgXVzdE6vH5cXtx1bXdT776QlCWkEKa16vN_nhYb1bXl5dt0wBUEFliEJKXb1_P4fQpWklZxYIxZaebnGKJkiMaMsprbTAeFwhcE3CA5ZwMCFljpQtTvn27hVqdNfNc1kNntFGAILnvemHum04Erl_vXNvsn45N47cXw89__pN5WiRLO9hG4zC4u3X3k89ftY2Zzyfv7P4wWm1zLVK4G1pvnHM-52yNaqyppaZUs0ABKZUrogDkUpmAWXKRypWrKFLGaCRqrDUKONfHwzHEqBUBg1aqaf0yh_W6b4x_2u9776yC7ap9cXedQoYU27ZZb3pLoKGuWne56f_4519_cb2-WvdD74fet95Y0gIyz6FpDCG13jS-ubjYOm1qFuutsRZIYoqH42K8rajuT9OU65LSHMqS69PzuW1sXPIpJb_pnkN8_3D49TffHeb5OIbD8ZSKxFSBYJyyMgpETvuRrBm2XQ51msbzNJlBfXP_9Px8vthtp5hYJHO1zlzutqfx1Ldt17QI2DQdAXmlpzmmmD7-5iMnViDdujMNlpTLUj4B5vMUlCWpDERoFKQqmQsCM1JhrLK-3LaDfvj-CTVJTSDJamFCN6wPH5-Z1dUvbn_zP_69Icg51CrCAEB1WvJpGS4G3zf54YiI6qJrhm7_u_cQFjaAgtvLfrVaIerV3WoeM5Va5rlpW2dMSeXf-7Ofr3v_P_zNryYsv_vmuZYchUMtJXFY0qvb9q9-_W4fxo-n8RSWyJwrgyofvn0IsUDn1Yv1pz4rExaNUUBZVQW8QiNVgXBNMcTCFRRUrmh1zWKF8_kcTyfTOhENzCSUaplPE4Egy_FwzDFCzJICxwwiUIowgBJIGZYEcwBiyAlYoFTQGgpDKZAyIAIyFIGSkT5VtowKIDEIoogwEimoFUvmXFEAuAgDaGX7tk7BIJYlihRiKSXbpuNYSwhCyIBEaG0zH44YohJWiFSrAsxz0kYREQIhKWBGEAUgsRAih2K9J01lXrAyaS0ASmkEzstMAPTJ6PPJzYKorLfGCVculbRmZiQEFuNss9nVwlxyTsm0jVYGFUktxOKbPuVsvEtLQAIE0NaRIgCUWpS1KCLAzIxISqucElkjNWtlOGdQyjjLhRGVCDjnhRAArbVXn71M8_zHf_yHbeO7ttvuunXfxhha5yrWX_zoy2Uah6E9nMYpBGs0oNbGvrgcrFI3lxsH0lgdUkwlF5ZaGAgR6TQFQqhcvXOHMXinllQfz1OMRQgbq6d5AU3Msh78xbAyRFIFCj2PU981XePP8zIuoYK01jptp5BSqVXJ4bxk4CIQCytjYy6a9LxE7axChUjrxnKGx8Np6DqpmYR2267X5JXqvI8pPj-f_-DHXw1N8_bl3fv75__HX__1l7e3u9X6cDj98Ku3RmlIJcQ4nqa-78_HE4c8TZN31lu77toUAinadPbHP_hi7fXQOK44LuEv_vbvz6dovIkpv3pxR7Z5_rB_8_qmNfj0eHr_GN7vl4t12_Tt9-8fFGnv9Gc3N5_fXfvGfvPu_ovP3v7FX_7tz37yo48PD-fzWAVKLTfXN5thPcXpfDi2ri0ZpPB21Vtn90_PF6v1eB7jNBurS2FBQbSEeH58WJ7vu9UQQ_Jd2w6rbr0Ny_Lq5R1V3j_tP__izeFx__LV3cXl9te__FXvvfrn_83_VRHWUt8_j8bayhKn0jvLiKnWfViIMMS82zTHMZ1iPoKM5zSl8DxO85yDwHFaKsDxNKVSnFa5Fs0SskzMgTBYPp2nD08zA4MmIbzo_fMxjPvTcQzbS9uvmjnx4TDnXOZaUoxCUAuvOp8rr1fryllrOhzGi3UPSONp9kb7ptvvT7FWFIw1a6vnaZ6XOOfQ9v4T4cOCIUTb-JIqClhjS073T48xF2t0joWUznNkrs7YJeX94WQ0AlIspRbOJb__7hFRuFTlFVcuzBwj5FxSYpEsnEstqdSUUSDNc82MlCtAkU_3a61WWmutiEhjykmggqDv-pQS59q3XWOtNZ_cfCqHjISCzFUAAEAIURk9nqa2a5U1cZmVUQI1LCGFoAW8UyhIVa5eXFhrVze78TwNXbvZbck3EdDb5k__-c_uf3dfUvFtw1pqBQFwfYcAJWbOlQunmAxRycW3rSLyjecUEEBZt96tYsyVKyLFXLTVKZW2c8fTGYlizIrx5cU6poQi2pjTIay3XZjD-fHY9564eKucwlLiz__oy7_9t78nlN77mMLFdjM0fj34m-vdw_cfur59frznJcWQuq4pUnWp1pkvfvBDjuUv_-0v_9k__3cVld9_8x4UrzZDLTkvi1G0Xff3T3sCqCLGkDEKEac5NW1TalWCoeQY4puXd4I4jXNlmJbwo5__YPr4REI_-vJlS_Zm3Y_HY--90-pi3feN9sZcrLvCebPuPnt7M3gLAs67wjzOi5RqrK3A8xi-O5xvtkNhriyt93OM8TwvIZJSVpun9_f_4v_wzz_87TssfH19_S_-i__w7__uN-NxSjEBIDM722hvm9553-ScdGNP45RL3F3sSPRP_uN_5_jtx1cvrt598_1v_vI3m4v1NIWm7d998327GrqhAwTX2RoDWL3EDKUMF5eEwKkiEAoo46BmJICSEADKp7lwRhRA1JZyjFArAEOpNYNWFUqI59MyL2xJW7Xqem_U88MBStYkUtM0Tv2wQyTru1pSiAmE-puLcDySsowgqUqBPAdkyPO5cXoc51Tiq598xZlt28wlb1ab6-vLy-vr8TT2q1439vnxaXV1OZ7Hvm-Ms0obAGEiax0iXd5d-84Tubc_-mx7e9n1Kym1xDQdJtu4m9evz8e5W_Xeu8svb0qMpvG5JlD4_PiUUqw1CxcA-c1377RSqnEhRAOoCK0x3qjTPGvljudJaautqak0vlmtVtZrFNIKEdV8XtpVawZ38Xqnqhz3y3mMRcr2okdA35BftceHcb3drHbGKAWxzKEMu2aagndaG_f27SsiTcyarNJ6t-1fvrwG5BLrm8_vVk1TUxoPE5dwe7vtG_fqdvdHX_-gMy7Ni7bm4eF-u1kh0vE8We9732hSKNK2ziA8Hqcl1ZjLnHJizIAlleNprCKFGRAFMBdBgcIVRCEKIXjvl1Caxg-9RyDnHWnUSrWt6_teUvaN_uGXr754-RIIUJuSAiFEqKve__kffvXmYvf1Z3dvry8UF6tUKRkQusYDYAzxNM-Za2VUWqX86eoCiLRzTiulACrXClgAziEukUORh6fDUvg0p-_v9-_3UyqSlcwC7z-ePj6el8oCEkOJOdumGcd5WpbK8P5-33fu4m6HhOjNPKZpnGjtP3zzNO_PkNlrOo8BNNrBEuD5EIy1yxylVA38fP_83TfvzsczAD6938fztLveXL--qjHm0xznpRREAdBYJ1E5yxLUpxDoXHlOVKsyxDl3zocpf_UHb3_9r36HRrW9By6cUslZscKcU062b5XocjxZrTgFzsyV253Nh9kU-PxPvvru3_4W5mh9A0OjSuXHpxSLkFJAr1-9Wm03aWZC0oDL4ei8Xm2HxjdvtqtffP2FePtvvnmXMBPR-bxUEPY4LSUp-Dd_883T4VwsBBZsbaqiBisgOUXXGtZ6Po4hJNN7MzSEvOQINXOuIFURxJJqZWQmg1xqCKEyKEdhLkqBcK1zJtRgtFKETuVUZU5pCuv1ED7cgwCAQK0AArFCBUBGKVAYSgYGSAhOQSpQmAYnIUHMkFkNWpYCqUBFqBVEoLBCRPnk-VIKiYzilKCwcsiMIEjeQUiaRWqVnIkQhTnmi5d348cnKMU2Rphco5m5TMFIVUJaoTCXXJWzhGiMK7mAsOSMADUlSUUhWWuFQSNKTAgAKKT0p9w_SFkp5FyhVkAAEW0cCgAi56KAtdIAAEjONQLYNJ3Sdrr_4NsGkVAocSUEZGr6qxLOOQeldU0JgZEFPr14BVKk9KcpaLbWe9_EnJTWSum8hGboWJBjRkVaWJid9-fnQzestHFGoVbq1asXnVNff_U5x9kZ89mrG9LKW3OxXTlrcy45s2_selj1ba9QWms14GZoV31jtAkpABAgppIRcFkSkTZGLTE7a0JI3rlpTgSiDa0GRyJOKW-sVTh0XlJhIev8v3z877--_nEplUiP0-S98cYpQGYGRDKGK0uFzEWqAAJjLYVP06QBm9ZJzS_vrlpnvn1_751utZqX9OJ6ux7c0LjNumeEjw_7H375UhGx4P3D4Xm__9OvPhsa33lHqD4RWX3XplC6ttXG1Jz7tjVKXV9cagWNNder5g9-8PmL7QpLsW0TU_rN88P33z-9f3j2bfP1F6_vH8bXLy83Xde3BigTqf_vL983rfnsenU1NCmm034k4p9--fJHb19pMv_qr_6u7V0V_MHnb-4fnr757Xerzfp0Hh8Ox-vry3k-v_v9-2HVW61Q06u7ayLcPz3f3d4cnp_X683j_UMz9P2m5yLON2D08fF5WA_MJTP6vl1vru8_fthtt403XeOtIin57sWNt-bd9x-6ttFQ1T_93_1fkhStDaIgUWF6nkOOqbNmvbIvVsNx4XdPhyUURGLEFLIF3rY9KcosschcEjA2vllf9n1vf_fhvN3141THJYRSn56nOVZRFCOnijHmaSzP01xqOUxhKurD84Q5paUAsLY65HycojX2ME4hZTCUAUqFOIVSs3UGgOYQlyUqo2MsLGW92wAjEJAiIgJSx9OsSRNS4RLmpV9vcqnjeCqIRWrfdFor19h5XHLMaYnZkWidEmfClOo0hvN0Vgpd47z37dCWUpYpLlOsUmuMMeSYmTTFFEWwAgOQtdYYE1NUzpKwEQjjxJVt41gkzFEbE8cRsri-S3FGAYU0nSeWWliYKxkSFqlSauZYSkmVBbR45-bzWVvdtN0yn1BQSsIQoXI3-BgSoX795m3jbeAyXO2OH_aXu9X6qpti3a4a17jjwyksUz90whLnQCTTYXK9UxWd0fO8b9pGEdXK0zgOu61zbhzHod_VkqXCsG4F5Xl_7Fs_jmG12WTO_dBzKQjYd35aEhnbDs5oNayanNLldqMJtqv-8xfb28u-Nf5wONmqnw_j1Xb15Y_fnvennEsK-f3DQwzJOruE8Xq7W_XtyxdXF9frv_vl7__oj3-qFE2nw3Q-h1S3jV2vh9YYo7VGBSLXV5d947q-48rD0DfWIEicF0F0Wj8dT1cXO6VtzOFqvVbW5lz-zV_-PVk7nk7vvvtwuVn94c9-eHe58VRvd7vGqKvL9XYzYGWs5c3tBZfCNa76zgApRSCiiEpOIBURNZHWSit6cdEzi3N2f5yKiAKeQ4pxcUY11lxsGzizwfbnf_r125e3__1_-_-JBUTqPM-lcNe1q-vL1z_6wdPHx_PxTFobZ9YvrprGO-esNlbw_tsPyEkYlhRWm6tvv3uvW1tSbbaNVJ5Ok-k6Bs3Cfr2J8xJD1N67fmVcW-JcUmFmKQWJDCEiQc2EqK2TKizguo5TUkKlskI2zgOiNrrOY3h-mI6HeZncF1c8jfF05DnUknNYQIrp18oY75slxfG4SK0IUqXE42xaiwAgrFC0Uuf9gTQJyOn-SaTEsKAUZh7D5Lztt7vC9frmZWIEqNdXF4TUD43RCrUixH7orTe28blwvxkMGYP2-PFRBMmo7fVtLUlZ5RovwNqSzPL8dLa-CctCRMy8udy07co6X0tO09R27fEUvvrxjy53G4ukkZQhY_3hfKpcpcr5OFaux3k5LotVyhm1u7hqu8Y6U5REhPuPD9vbF93lqt21m8vLZYz90NcqYS6bq1VjzOH50A5tDhUYfvjT14TqxYsbY7Uz0rlm6FbK0-ayb8k8vnsyrd9s106ZP_z6J0a7HKeURxJaD_3b291nlxeKwVlNAEbptm1KKaHm1mhFyFxRUa11CrEyFObCEEPJiMuSQkiCKhVOlRlIBBSRsCBiLqUU7lq_hNSv-sZoa5w3pFFxyZ03675dWU2KJIe-cZer7sXVpUPedf7l6yu1af7syzcrazeN671FYQDQBomIBVLK8xKfTmdldC0yT2Ep5fun_TzNxlgyOpcCIksIzPXD4TzHPFfZTyEUyWgOY1DWjrEsxPfP07vHk3Hmfj8ep2WOabMZmCRJnZdwGsdcSyp8fNqf5-ndhwM6PD48PX98nMOSqUKMRBzyYp0vDGFZwhyboVFcj4dT1_nHdw_XNxft0F5crIQgpWCbVjlfAR-_e1CKnDPUmaoYhaUkYIYCSgmJKC5lzFKo27VaaWE2iM1q6Ffdx3dPpmsZMzLnaRJhDRqV930PrQqHsyYdx5mQuVTrXXPRjt8-O2MY1XJ4RsRKkGPKh-eyZBLueg-xpFCtszXFw7sPKafrVxcX6yFn-id_9OOf3d48hfwvf_v7bz88qE493O9FCihqLtoEvIQYY0BD7PScCmpipVSrQyolI3oPF4NttfWN9p4YuFSuTKwACKGenvfxPOZYc1zyEpEUMBBgDrlpfc2LPB1916TzjMblUgqwlApc4HyExooSCYkIpWSoACJIDMIQMyQBQSgFkPAT4cNMNUr9FO8DkgqgQEzIrAxJqYSApcon9SEIAkqMUERKVcZwqsoZKqVMgaTqxpcQNIEI9hc3dQol5xqDMqrmOlxck_D0uNdaeIlkiVPKuSAiaSoxCQsAE4GUgoDIrBUyg1IkpeQQyRkgMNankEgjMiAIMCutSmHSBlAQSWsqIZKgNkZ5JzVLlbbfGaUJKY-j8c64Zri8nPZ7rhWVYSxGcV6idT7FqLWCyoBARMoY56y2OqdYYkakUiMCaGWQa41RG6OcLylZo8uS--s7ZdAYO6wGJGW8fnlzfXO53rXu7nK99n48n_uhs14Bl1XnG2u0UYUrIQCpMM-t9afT8XKz0kjeW60wp8rMSIqIUkwiqgg7Z-eQCFU_tKWUyoIAh9N8d71Nqew6R6hzYQSw2hSQaVxu2rtSqtZ6WmLmsm27JaVaZMxpaNrTPJ2nOecyeFcEQuZlSbXyfpx362Ycl7e3lxbh8flUK7-5u0AkSxawTofxctvttv0yL69ur2JMRGS1_vDwRIhu6J-O88enoxCGkA7PhxBTLXWz7kOIp-Nxt1lfX-3ev_tuHscfvn17d7G5u1zNc_DeVoYQYwnl6fGw3g1GIwtd3-zuXlwqhfvjYbUd_u5XH168udSOpeC7x_OSA9e6zNM__7NfkMiHx_0Yljd3L_aHk1L0-LCf4mKc7db9y5cvPrz_OB6Ovmsypy9-9LrEvOlcp1FyxpLapp3H8dXru29_-20O5cWbl6v1cDweKosQilbtsBYQ52zf-uvLq3k6AZftZkeEu4uNUvrju_vbm-1q6NUv_vP_LSgFCkmjaFVrVQC9p4f9pEEFZhHUCp0z1tso9XierVNxSWR0SExKxhyP0wxQS8bXjRXjKlA2FGLJzOcpfCL9TiG-3x-Eq5AwVt-2U5xFmJidtcfz1LWrUjhxJUOVCxoan09LjMKITjujAVA3zePhGHOJU7TWVymFuZSSYmZBg-S0TTkiIVfmnKx3THqaJwFRxvCnw3JhRDiPYYmhlmRbH0JllpwZQA6neVpGZdQyRyI1TrPSupQaQqxcjTdgVCGonKUygCCZUiogIEsVLlwR1NB-mZYHRcSVxzmQtkiEAFqbEhNZSrEojdP5rKxCJAFSGgG5VM5cNTHX6lo7nea27UPM7aqrzLXWFCIpIq6utSCQpyxKMoHZuKurzdN5XF2unj4c37zd3X1xfT5ML97cXG5Xc8yn4ykuqV_3cZxXm3XOkUUxwO7q9vz8XHJZbzbeOxE5Pu77zdp6__2733fDyhjtnFWI_aoDkHbVhWnxzsdliSEZo6w1qLUkJuS-8ywQ45JSur7ZxSUoqVfbwSqqKTPyZt1fXqy__-Z9KeVis7p_esohoaHNZghzHIb-9mYXl2AUvXp1u3_ag1DXtYfT4eZy16-6w_FIIO-m4_VqWA3d0HoAyLE4b0krZs4lzSHGnFPN6_W6c_bf_vqbF9fbru-4ZKP1sG5W63Y8T977_-w_-2fbxl2svFb44vrCmn8Y0lqt2uuLFcdc0rTre2et15-U2NJqZKGcKyIqo5xVVqtSWZHKuaKC6byUkm3jlpj6rlEEXvmf__TLn371atvZ293Vd99-N6z7Kuniszcg9e7Vi3_0s5_86i_-2mpy2ogxP_zhj9OY_v0__5MYZtN1jx8-llSMtS_f3pxPY84JBGxrsOTbn_xg_7vvmsaj0cqYLHx6PmitjSUFGMOsDCjfAEt3uckhkbOSC4pILsZZsBpEVNvVOZm2ocahFhZGwcwVAAkRhTWUktLycKipKgRN4JtGpCKmw8Njt1qXUq1r_dCE8WTbVmndX10iklt3zuoQMwA2m03JxVoHxJzy-elojITz6fj8DEZpo7fXFyXli93aaTUdTvM8Pz6Mbz572Q1t27Xa2GlKnOXx47MB-O7336cUfdfaxpE14_GQa80lNc7GJW13a9CkFOSUQoxa681267oWPmXOkRhNu6vt9nK7TOfxPBmHD4_Ph8P58fH5tJ9zzsaqxNw0TnsKpwVKKQVB8fk8oiALNE3Xr3qHrll1uoq3dlg51dha2TRmvetBeJzZKDdsfdUAoQ59n-fQN-75aY8CpMV5jRVSKhe7ftgOzw-nH_3sbno6ToenEBer1B_9s58PXD9_cXXVdVorZRAQUxZCnENylpw1xBhzLoKnedmfZhEArU_TjMqGnJeQRFEVzpWJPhlAYQ5BBELMjGC0FoZSSqtVyiXOMdVcCxPhZuim42Sdvt5u3r68vlltLJHm5C1te7vy7svLXaftYJ0AMudYa6o5xsIsJdc55GkKfdu23rrWCugl1e3QGOdSzFw45VxJaqmxlsfT8v2H_SHEIHSaw8fHfSpwOsVh1T2d5qfzodS8LPn9fs8ih3G6v38-h8iI0xIBoRZZYhKo58PYDf7wfBzPY5FSYj5_2OeQi9RaWRQhikI6HUYGuth27W797d9_M7TNt9_ebzYbIGKGlEuKAZFjXNatWqaZFIVYODAyfJplzykCQhlnAVVZDTfbHHKKFTTlhN1qWJ7HArUuIedF5lTCrJSA0ugaRe7wcd_v2mmcai7eNViV6puwH8sUTeupU9PTUZjdqgVmyNk3rpTirE2pMNLwYvP08en8fCilamfiHNu23fSbf_W77799fvr4fMpK5hg4FQWIWiGashSNoFGlXCsBOV1ZBIAZqqBZNVkqgaQlMqLyWmsAJGp0THFocJlCTZEUcY4QqxSpIQFJiYtVhmvtex-mBCmhoQIApACTlAzjAorqOStvWFhKhlQgZwAEICgJKkPNIBWEwRCQQEyQkxQg0pATpESNlciQM3KVUsEgVsFauTAQQmI0SkqVXJTWNRatSBuTp8WgGG1zSigMpbLg7vp2Op5zjgSFEFA75TynlOZZIddY2qvV-DQaQhAy3ny64VeEUBlJSS5UKqKKIRrnOEVQGEM0Tc-lCEjJASuLCBLWlImoCksF432OCQlBqrZNjQtXuX7zuWt6VHR6fDCWcs7a9tq4tEzO2jQvw65_-va9X6-5ZCQltZTCzKI1fYoksr7RzteQmq7LMYpA03dhWZTWzGibVYqzs5oRl1IRVTe0IYb1dtV48_rNXYznm_Xq-28-vH5xMXQtEV_ttpvWD21rnX737v7l9UUKsdZ6fbn55rv3L663u3U_tF44G6WqVGN1iqmysAATfgodOUzL0DtCrJmfD2el0RhzvWmlyqrxS6m1SEwpAwvQVJLV1ii1xBBLLVIV6pSLMYpRziGellhFkMx-nhJKZp5C3q1aAFmvuqvdxrBs1_3v3z9drPyma2zjraJXN8PluldIUhiJSi1hqaTN8TQmYQTyzsecpBTtLNfSDh4Bry82VTie58bZ3Wa16Xyj9S9-8KZzrrWOAarA42l___h0GCfvjCj_P_3VX3z55s3gm1XfamX--m9_49v-t7959_r13e9_-91mGBpCAJpjRMr_zj_66RfXtymVaYmp5Kf9cX86f_j4YKxr26bpe6giCE5b6-3V7U0OYd0P15frP_zhF-N4fv74-OLuardd73abvCw5lj_5459irfP5PC6RpY6naX2x69s1iHTed00jpcRp3m7Xu82GQPqur1IAKrOsukH9-D_5X52XHGLVxkgR09HTfp7mQATaaBAZGr9ru9O0eIWnJWSRD_vxXOoUaimMmtrOkSgUmVP58DjlwiC43rpxXkLI2pu-d0JorBq6xgitWhcZjofJGVNrLrkAKr9uj_tz3_oxRGKIBcqc-tZrsmNMqYACFXNxg306nJVUDpAkoyal1fE01VRyikprRXqJOS2pELDiilwrxJytcxpJIWmtSi6rvj2eJ2bOoR5Op3kJRFS5aEXaat_7MOZh1V9dDSHEOC8pF-W00hRjQKOFUAlwiEiUYlREmhQQVGCoKKWwOhGRAORaRUGOEaqgUWGcOSUWyKUAAnnt2qaUxFVII0hBwmWeSyraKNW0aVmoljjPJQbVWAGwStclXry5m_cjihbOQJhLgZW7vt1eXl4-jaerbXd5u3Ztc3N3gcZkhlzhfJpjKv1qePrwpDVo60vJiJjD2XiTQqwl5zmUEH0zVMSMtWsHhIpGKcDV0M3j4htbczFW55zbtlWKgKvROsXgvYaKwnXoO0Kel-X25ookv7nZSkxOUdu3pZbri-04hU3rrTFa4-Vmsxo6TtwN7au7y6t1s9u0zppScZrGnMrN9dXxePzyi8-sVh8-PHz52ZvON1-8vCHAoXWWMKXkrLZWca3MAoCrVauNsdo4hUso223nrO29_fDxcbdeVUJr9Waz8sbcrLsXu_Xtbkjzslv1KQYEpbW2CjSAJl1ytJqwijJ4PE8ppcKcc2GppFQIERFTyoDorBuXYJRCUlJZEW3Xw9u3119_8eqHn71qnLYgbePm8_z9w7Nyfj8uw_X6l797-ulnt_3KPnzz8euffrm6W3e7zb_-i395udlYwjEG13W__-3vvVE3dzdLDJw5xti1TaNtKiXsD_NxIpAYMxhjjGmHrhZuVm3NjEDztABqQahFdOdQUc4ZtLLGphCxsgKUlEAYiESBMrakIsxAUEIGBSKMSitASFmSUK1En7IopKSksMTj0bgOrDXG2n7QSoVpbLuh1Do9n9ZXV1xERGpJIFRSIqKa-BPgpp3v-ub4fAjTfHo-x1hN44GUdu7Fixc3V9t_-cu_G9p2mZb5PLdD8_79xy-__hwVbq53xhlSaI2ezqNt_Pp6HeelbfywbtKS5lPsVwMSaGv7oZ_nSUltG-8bfXmx1kqVUlKuYQ7TcZyPUymwulihMFpk5hiSCC5LgsrLEhvrS01xWazWc4g1StfblW-1QqdIgTJATd_YzvXbftW45TD1m2G9bfvBrPputR7G03S1HQhgs-qtUaVwLlkrba0dj4ttyKD2gJ7BgEplriGuhqbBcjs0n1_fWKtQmFkAoAqUUguX1lkiE3MGhUvKc0zGusJ8XlKI9bwsJddcauLSWLMURhEBjCnWwqGWUErnnXM6ljKeF2OVtaZr7dXNVilaDz2hXF1dbLcrZ7UI5JKfT0-llsM08acZh09tXA258uE0hVLHKRQWck5ptE5lkcNpEQEEpTUpgMyVBYHUeV5Cqc_H8_E0FVbDaiBH_br5_XdP-8P8cBrZmCJ8_3TOhPvDeX3Zx6X85vt70irGkEtBpGmeYypaa-1sLSGMQaAucwjzFOaUQgxTFGFtFOfCIEoRVrRGSyk15w_vHkOKWhMSDbt-nOf98bTerZTSZHFYudP-CAWWJaNBN3gp1TuEWsMY0QALcKqSa4ITsiL7SWEBOZfN3ebp3ft23U1PZ6mFl8ycnXXLhG__5IsPf_33vnNobTxPjdYAHGPyKz8fzuDJ3PXz46iAUWHVkKapLks6z3bdFKlKa9QqzDGExADGaUBdhb7-4Zv7p_tpnp_GceYqhsK8pFBAEXkjwDUWASCnkFQuKWUBY7S3xruCiF6LyHg4Zc4CssypSE0pT-NSlpRLFS08Z6lCqIxHgcznkULkJdWcXeuX01kJlTlIzlarMi3knECFOQNXRQoRuBQQ-lTfAwkIQy6QCxoNRSAWUiSxAAsIQs1SKtQKOQMACEMqigW0ksKSCyEioCCQcQjC80xEpBVwsdaUypwzgSopIQshklJKN0qpcD4qAqVRmdavL0qu4bSHUgiEUJnG1iUgkTY61yIsyEyIAFBThspak1RWWpPCEiIgKWWM8zVF4aqMJqW0Ik4FUTGCaRwImqaJywgAzKCNQShAWrW9tnZ8eJAUSCMAumFlXPP88YNvvHWWmXbXlzXHEqJWxMyktdbKt14ZzQBhCQDCUr33OSVElVP0TZtCGnab8-mwutwii2lb5TQaKiVf3d7Wyv_5f_kv7tYrTPzTn3751asXRLVvvDMapDbGpZJTCFcXu9P-aJVRSpHwbtPfXg4kYglyrUgYUp6XIIjjNIdSc6laq5TSbrfKqRDjkjIikrJtbwxpp1WofJ4X1OCs9s7tx3m96olARMY5zinhp6h0kcqQSpljMkqTUvM8WWWfxrjtvdVaESpSTesuhm7Tt6XUxMUoAlbMebsZnFYkmGJqvS-lakVN27DIOIVhGLQxy5wQzRxTnOdVN-hC8zK3zqUQRQRFXt9dvb2-RJDdxdo17jDPHx7uf_vt9wrNP_7jP_JeKaN--_vv_pN_909BSKoQ4eH5WBj_-m9_c3VzfZhmo02o8vR4KqWelikW-K__0z9PU_j4dPh__tu_eHlxuSw5ptB1PWhQRj_c39-9eD0fxyqVUC1hvLm5WbXNy91m5Zs3r25f3F121mnCWvnVq5cvX1wqpZzzH75_-uzLL8hSMwwEMB9PRtnL3coZV-KyHfp-NZwPx6vrS6PVhw8flFbOma6x6o__1_9n7ZQ3tJxmSCzenvbjGHLb-ufzzCBxiY2l7dA6hnEpMZW-b2otTrE2VlAfl2oIO2dDDr_b70HU_hTefTiySDaMmuY5nc8LI102XguVzJJr26s_fXX164_L0Ls5V6sUWypYtcLC1TtDRM4aIGQETQDCbec4sTNUGMiRMDnlK3I3tMs0l8w1VW2N6-zpNKYqIZRxGkPKXGvNWViYhUlKqgg0zotWynqlLBrrzocDIFXhvm_CFO5eXaOk3_zuXgHmnMjqmjPnyjnXkEiECAAwxWycJUO1SIqZiJquTSWmULgACLNgKeyMAa5xiSgsUsM8Np2fT5NpOk5JuJZUmUVZm1IkAZBifbOMM3CVlBWRMF18djMe59VmKCGc7598Z5grfMoaGPSLm8ttvwKtsaFlqZeXQxbYbFYpi-4cApqmef_hqAg5JURSjUVBZhmfJ9O6UqqgiEiVShpTLRfX1-Px2HTdeJq6pr3Ydvvng7Boa2MsiSWnZJVSiuZ5yYW10VrDqm2F0zB0hcuwbrHWzpt157arXoRJoEolwqeH52Hla5Fc0uXVxhkchmGajiqndb8yhpRS3373cHd3YZWuIq3X600_rFqrFRJYghyTIkJAZZQiiDE87I8hBuuMJkQAruy8__i4b60Fok_q9cbZ8zh6a3abdtDqq7dXLRlrzfZihaQUkUjVih2hc55rtUoro5zVJdUcs9IEAoQkIp9ay0brT0ftUjiFbL22hi62a9_4kMLlZtUaS4qO9x-0gsaYWPL3T1MGGe4uHt4__Z_-iz9fO_v_-r_9v3_8Bz_59a9_9_lnny8haKKha7VtxmmJ05JzXK96ZpBcfvz113E8rS_X3_zN76xTm4uLUsI4zqppSiy-c7mwCGpncipziH7oOSdjvdIqxUVpw8hxiWQ9GgMAKEiKgLmmAp8ErVZzzoAKFJNWUgFFEBVpjVSVhhwmAXJdV1MRZsS6HB_neWlXazJmCWfXdOfz2K-32uvlNO3uXihSmUEZPax3oEkbY1uLgEtIwnjz-ec5Ltb7Ms0f3z8UqacxtKuu5vzm6loqv7y93m2GkrIzHQJ445-fjuuhn87jPIe-b33b5Mxt4wlIEa5X65sXO9uaxpkvf_CDN69e3N3dXO62F5v1xe5CShFAIdLG-KYxjWaGtm2sNTHVccxSeBmDJoypOGeUNiVz0_XTErSx1tmXb-9qzs65WmplAFFcEjE02tmCzrpV3603_bbvZU7d0B4f9lfbIcWw7rrn0_Tq-no5nZxWjbff_P27F9er66tNa9ApIChN61d9-_L1rYX62aurn3_5RdPovMwalbFaITIzgmilkGg8BQEoIDGVXCTlIoC51inGOcRcJYS05BoKiwhXnqZFaQ0AoNBbhwDLnAnAaNBG7U9TSOWwH2OsKNw2dugbTaI1neZ4OB-_PexrQeecUuowBq6YhSvz6bTEVLXRqPVhzs_70zyHzsBS8Lg_o1IiIAqXUu7348NpnpaUBQTp4_1zRZWKvH_Yx8y__-75eVy-v3-Kgg_76Tgu5OzK6O8-HlDoNC3e6XEcbeNLKSHGFHPTNrp3XMpymp_PD8Y0zJVrJUTnFRGSopoyiDBzHBfr3NUXt-P-JAicC8dMAOPhbIyex9PpeDocD6RN03WS2TmPClZde9xPUHOcC5CgRimsP3ndnbWbQbIlwJiK6RwinR-fdxfXj-8e2t3AgOBAG7W-uRDQ25989vDLbyTm3Y9enu-PuhYMoSCCKFxy2Z-Nbtq-jQ8Hh1oRlLAIJ8xFcdVcS2K0SAxpCaQ157K-WHMtNcvrV7tvv30IpR7GGVZ-OU41lxwqOsMK4xS1UgiwhJw-6ZUR21WntaoiJXMquUqtJddSlCKAGE4LSkUCzgUZUSqXDHMUUvU88TlCLIBirK7nVGJpNi2w1FwghioC1klMIJ-q_CSxkDOcK8QEUCEXCAmrQC5QALBCLhirUiQKoFRggVqgIiJA_oQbCdRKgIhaQiRCrAyVCYk-SXaZqVYBAS4IRluNpUJl_odeMuUQhrvb5ThhrcYp4_rxuKzvLseng5HqNAGS9U2NQarUwop0AUEEZAYRVMhL1ERSRUS0c_E0CrNtG0TNtUCOmkiTIaPKtGCVT_JyJEIkZpYclTKkSLgQqdXlS-NX-4fHq6vNfD5lJN8NaF3NCaV433x6mBBOj09W67bpS0mAAoiAhKphkLYfcpwQMKfc9R1zQcSLq4t5WozVtTACrHfXOUXXtt1qzSVJTevNzhr8wz_4etO6i03XGHXen_u28Y3uG2eNEob9NG67BhDXq15r9N6UkIbeC0PNRUBSLjXVpvUiSEozgPPGeTueFkPKaSsEqdSh6eew9N5rJETYnyYEKMC7VRdDAZaQojPqMMaC4q3KuXJhY9UwuONpIcRPbi8AAIS-bU7nkUvdrjstgFV2694qfTqP3ilrrTPaEPbOWNKtcd5rpdQSQsq1Mn28fzbWiQCL7J8PWcp5GYe2BYF3Hz5AldvddrsbLtb9Dz9_uWlbYA4pHaf5_cen_WnCCrkWAnp4eFjmUFN-8_JFTvnx-TD0m7_6219FFlT65uYyM1vrSw3H4xLnsL1eg4U__eHbrfUgeP-4f3t70XVrYVlS0s4-Pz6s-8F7Ny5TqfXbb781SgPnq92mt5RC-tEXn5WcjKEQ0zB066GXWqTUCvT49Hz76vrx430pUEppu95bY0m_eHX3_Pj48cPHt69fVhYi7NrmfJzH4-n67rJpDc9Z_eK_-j9O82y1KSVDlef78TznYWeNo48PIyAT0Yf90Rt3uW4uu_6UStdYEKqgmFlpsgj4aWo25_fT0lolyF3nT3MU0tMpMGkQPoW4nwN_QnRBH84paem6VimFStXKUAQIayqn47L2bSkyTfNznLwyCmEJ4fLiUmlzfF5WWzdNGXLOObnG1VLinJTR0xJqzV77ULIinJZk27bWgiAs1XoTc5ZSAJhrts6nFJ13aSmcK3DNoawvhsPDYTqdT-N5mTMjaK2Yw3SeyJCIoECNCQUBdQwpx0yIYQkxZU2OiAVAWbNMkZQqOaGywDVOo1JonCspCeemb2JM3apLyywpIaK2nSgkghxLThkAnHc5LlJKmRbb9tbb49OJyNacSillicQ1pdBdXZHGknJV8OM_-um339_vXmznc95ddKjVum9bZ1zrlilsbzaR-fn7x5W3yzxXcJdfXoogV7TOKKvjefatjaUMq835PHZt2_WdsbrRylpTY5xjnsISpZjGckpaKYZsva2VrTMlpJzz9WalyKYQrFGusaqWwfvt0PSWvDNGkSUlwtuh3axWJIzA3mljySl1MXQX684qowiUUt6gCBDCZtUDiDAYrTRi66whTFIRAbX2zjDXmlkjtV2rlSIkY3VliUuy1lpjvHafZvkViUJ13B-Hxr26u-ysQZGYqm8sEoZUask1Z6WpZtBGk1ElJCRclphzJqVYIOd_MDYACwuAgFKq5GSNbRpHhNY6Ee6sWTVN13YGaWi7rmkVIgMOq_bhcH7_7f2r7arV1qL262499AD1w_v3Rpnf_-b7P_xHP9muu_v3H_ph--tf_3a12T4-PK6G9m9--TfLtJwOBw34h__8n_6r_-5_8F2nvQ_jmFOM86KsqykrAb9qsdUlV6rCtZRSm-02LqG9uEKUIlVIEyhBLDGTsdY5zjmnaJypwtQYULqkDIzAFQGYBZUSAOUHrYzkSABcRSorjcT5-HDfrS779aVrXEVOS9TaoNJlKaLRWOu6jkDNYQE0oPXtL_6ga1vv_TxPIeTx-aSNcQ3tupV2FM9zLsLCqZTnx4O3zjaGFK4au7ta31xsht5vVv3N5cX1ZrjZDD98efvVm5dXVxdv37y8vdl0TWNIXV5sLjcDlzxYK1JjjlJK07auaQCAhbvecuY0R6v0_jwpg97rTd-23iICKiUVNWnvVRynxruYMwiEkPrGnJ_G3Wa12rrtbvji7ct-aEiBMgaZG-8lVEO023QXu76z-uZydXeze3lz-eb2Ki3jzdVm3bdUy-vPbnZDs1v3b--uhrbZroeLzXB83t_t7B9-9fmP375uDCkW37pPPtGYc6m1lqKIALAy58rjFOZQS5VSuVTujPt4PufMiIoBPxVPUmUJCTXmXIloaF1ndcjMwoIQQzTGACrhCgRdY51zXuEyBQYaz_MUYgp5CbmxTWWpDKWUUpMSSIUTQ6nZWvV0HJ_Oy7LEQ0j3J344nJjo_vH48Xn85uP-3eNBdW0qssQQKs8hkzbH82KsQ8K_-OvfHeeguu7985RKZJBYa8z5PC6K8Hgefe-M1TGxIKUlKAW2abhwjiWHFFOxpF3jY0w1Cwgoo5SxSIBIymilrXW-ba0s9fg0AoBrtUIpNe1uLp_e328uLy6vr7yzp6encA6kwXkTp3T39Wfea0j54mUXlhweR2u1ViQVSyHXNavNEE_npu2GVZ_GxWhzsRmEqe1bljodFwVsrX38ft-BQlVrRaV8ms7AQmS1ceu3L_Lx3Brr12suVYWkS61xKSFabTAmb41wRaXtxbXEJc1BOysiwgyMd7e7X_31r4F0e7fZnxZlVViSAKC1LFxr1coobXLKwrWUbKxRynitoXJmTlJKiVyFscg41iV17a7GwDFxZSkAIpiFkwBWeDpAzUSiKktOhRlAQVhyFRGU8v8P6OQKlcEo4AQiEBNzBqmQKliEnCEUpVup8R-eLBUKc8lktKQCAFAzsFinJSRQCCxQ2Toj9VMeqCAigtLeIzFV4CmQUSUG3XSkNYckMSMpUgo4IwD43jdtGueSklECSIRmtdvOT8-wnK12orQ1KhwmIK2tKSFqb2sMNWbUSmJRCJCLKKWMkSpSkvNtKdU1fQ0TCAChtU1dguSKiKgVETKDNhpFsLIxFpFJZHV73Q0r53vkWvPCIna1QtJt08X5bLXWWoVl0Yri-VxSBgVkjAijgNbKGJNzEKnONgyVa7XeMUBJ9fLuMqaclzxsVjkmRYq5CErTb6bzYbe72O7WVxeXw9B98fJFY2jVtcT17mY39O08zZcXW2f1r7777mefv3LOdN7Ny0IAQ98wS2ctEiqlmOGTvgAI5ilpQ51vACHnyhVIoaAojacxLik1TmuFSFS5Ph1nTRRSVkSPp1kjISGhWmJlkFgqAQIgAaHAeQqkFKEIc8rZGd1ZYz-NERMZkhfXl0PrPz48-cYSKa619R6krrtepHrziavmKiJK7_cH0ppBauXzdLbWO-t73zeNeX7ebzb9q9vrVOrd1UXbWCAUgv_5b3_X9U0VOh7PIcQXdzexVCS82G0ab8cliajfffvhx1999t_99_96WLWff_b58XxOLNNxDku6f3jIU24bBZod6n_6j35iBc7ns2v8flycs09PT7e3d_NyXnUDgjjnx-NIWgnn5-fTi8uLFxfrlxcXf_TTrwwJcLnYrHfr_nLdXw7N4_3BGP3DL69rFcnw9HhoGqvJ1BykyuXFpuacQvnpz75sGycgUuH6anM-n3JK2pNG8-XLW_X5f_C_MNY8HaZu6ELKxhvD6t3jaQrpYjuIQMzZGcMIxxyXuTjnvrs_OedylVpBKjtD5-NciqB1hyVLrUuVwFIVn49zSlwLawUoFGIQhrazp-m8dW5c8uthNXIxygyuabwWJK5ca207rwkKyLrzUnnb94bUMi1D14UcD4e5xMggqXApgoLTfuxWjXb2dBpLqSEW4xRASTE2jZPKIHQcZwasC0POvvXjNDnvTtOkSAFWb5zSymilnQXk-_unHCPUAljznASklMIVcq3IgEbFFJkLGcpLFKmNbT4J-kqsytrKtZaMpEqMigBRgBQDc60IkudgfCOIyzQpRQiUAXIcAUhpnaZFW1PmpaTMzJ8-f8kCwKvdJsyLaX2JsSyT7dtlydvrN6k8g5gXr149n-YXry-F6_XV0A0-jBGlKARgtI367W8fT-8fh17Hpdx-cf3VV5_FWGxvpsPpeDi__frNeVp2d7fnaWy6hogAqPVOWxNSbLtWREjR_mnKOVmHcU6r9bbE4oyfx8m2DgUF5OKytWRiLo0xXecv1q2EvGkNSNVKnc4Lgmy23WbtCTiFCMhfff75dBz7znnvUkz90D4_H6yxMSUgNFq13lptpDIRKI0xlRCjCALCvMRxDOc5WGO01vO0CIIwK1SAGGPsutZrUzhqUud5ajo_DE3XmHXb9M475xtvao6Nd6Wk59M5plyBjLMEgkBKERKfxuBbB0qVXEqqqIBIIaIAe29FhIgQJaUilUvJ3pt112okkIzC3vxDJr2xikWGoRWRVzdbqHBxsYs1E_HVzeX9_dOPfvRZZXn56ubju3e__c3Hj_cff_jzn84xLvvzn_67f_Lh4WPXdlDh6vqykkzPp5Ti7u2beJ7SEhCxzJNzVhmVU0E0RSoixGXWbSc5VhYu0fmeyIoyeUlCoJQqtRIRKlXCTEAVCBRp70hbQIJPf0vEAlwKat-qyr5rcyqmsVWElAURRIjTU0Um7bt2WG2ux_PzeD5pq0OcrXVLCM3QutYpC6v12pWqtEalvXVXL267VXdzfZVynMfxaX_66hc_Dcu8Xq0R6m67BiUhJKOo6xvO-XJout7vVqvNqt-1tvd2OzRD43aNab16msbvTudcM-cCrLTTpvGoaYwhp-ytba2-3q1eXqyfj6eHcR5DvroYjFEpJmUMoSpV-tXATMoY3zUKFRrVdC1gtUav2hZRWeea1u2G1XyaP_UstVYiTMLOkDOoiJzWq77ZrDpL9d_7059-vupCmjwZRfLqsythyDH86T_5sSlAKYLgn__Z1zer7qdvb75-_WrXdY4UifwDTFhq4ZJTzYURkZnO41IRinCq8Cla_DwtpPRxSYd58d6FxCAiwrmyMkorpY321lqtapbTHJYlOmeUISK1hGS9L8zeWqWwMjfOnqZ4nOZYGBQWFkBCwK7px2VMqU7jOaR6PC_tYC52zd_86uN-Xs5TqKSY3Mf9oSjzdArdekgxTzns53g6L1OMTddXQdB6nFPJtbCMqYIzRSTWik4dD_OyRLDuOE2lyDTORWQZk0ZVCQBZkympglUpVUKpXFBEGcc5-75xptGaxymWUEWRIq0QSVNK1XWDMabvu_E0Adacck287J-Gi9V5nJZpVojDbquMyks8fP-hH1bHh_Nq2NjN5nh_dtZrUpro9HTiWhvXauskFcmsisRzHJr21etX28u-hhRzuX1x_Ys_-cMlxLyE6xe359N0_eaz82lshzacZyQk5c26r6dDzgmUUjt_Pp9yzGU8G6dSrchCIGGqyhgQ4TgJI4uYzsznpSQZhn78-DyHvLm9OY9TKAUaXs4LCACjIhCqylKNBb3KS8YYwZL2CoSE6hhiKgUIc0zWmZoqLCmGkXOQTxxGZSnMIhCyITJKQUxaoO9sFa6xAiAQwDjC0EJIEBMIAgkwQk6Q66fiHqYKBMAMuapSCbDGBQGhChCACBUQZCAEEFJK5kCgiYBTkZyA5RN7KKUAgNQKRikkQURADoFQhCsgEWlUWEMkImZQWiOiCPXXV3GcOCcAMY1HNP1uu5yPkJPRJkXpL9d5niVlt7aMUnNVIFIKAmtjuDApRK6glHG-pmKNzjkp66QkyZmUBiAFJLUoTSVXZTWQ0taTJilVG52WxXhXIuzefBHOE1otNedp2V1fg3Gn5_Pu-nI8PJdUvG9d052eHhSybxsAVVNp1uucUqns2rbWIoykABGJyDe-xKhRp8JNt66ShBkAmrZJeemGHRJ3XRen6Q9-9rMQTz_--su1VQiyaozTqvEGBdbrIcV0PI1v7q60to1zh_3JWwOIRlHbOGu0MANirQyIy5IEMeciiOMcj2PwjddGnfZjCnKeF1DYD83xNNVSjbJPh5PzLoQoSKnWzLLqmukcUCllVUyFS219V7iuGj_PqVRuvCWFvlFzKlqhFHGthVK905e7jdNEhN7YxunGOAFAlK5pW2-Yi9MaETN_SqJKpJQzuvPtEtLFbptKnZbldDzmmNfbvjdOWwVaPR1PT4fpu_dP7z8cuZbTGA_7aQnhYjfENJ_G6cX1zhmvrFmv1t--e3_78vZvf_3N-mJljT2ORxZ8-Phhu-o22_6Xf_ddq_nP_zf_wfu__P2f_eiL3lhr1GnKp3C6u9795tv3IgWh3l5dOkuncXx4etztdtP59It_8gtX-esfvP7y1fWr68vOEkpVwM5oa0wOcZym5-f96zd358fp9797f5iOl1eXlTmmxFw-f_1GRJDk-nKjkBRR1zf9av1w_1i5NsOwf5xubi87Z9WX_-l_HWI01laqT88zF0g5vrzqlyjD0D-eFkQ5HMfDOA7Wjan89sNz33X78xy5Iknr3RLi8zmRMaXwZm0bhwUhK065nA4LITNhqFyNOGcQZUl8HENheTpOtneZWUByjMJVadU1frMddAFLtuRKLJuunacglfu-H4Z2vx_RqhCib1zT9wjgvdmsdlMYnfPLEpkTgJpPZ1KqVohjts7EGCNXQwpyIcbj4USWcigCMI9TWNIyT1jh6fEZEUIMSkRqgVxqSKZtOJc0JpEqNXIpJZXC2bWOCyMAkSupllJQoSI1zTNXBpEa0qcNi4Xt0IZlJmCoueSsW1vLks4jIRaRXLMyKi-hafqaEyIrrXPMJAgpS8mCwoVVM4hSjFJLJQHtfckZKeZa1zfXw64bY1htVr5pVt4555vWaKOERZD9YC8udt_-9l2cl4L05X_yj8IDb1_cNq8vhovh4-NZO8sFkXhJaXu1K0uKOW8uLpa4xBhP0wQIJWWBysJAxEVKSnOKoNA3rpQshVPhzWojNVtjlMIyh9evdld9Q8KNNyzQtLZrXZgXYbBaD21bmMfT8epi3baOBJx3KWZrDSnarLvWWik1xNR4V2otpdZcrHVECkDiEgEx1ApEihBFAGVZlsY3pZSwpM12ZUix1HE8e2eFqPFNrRmRL1aDd04pEq611pLj-byEUorA0_7c9a0zWmkSLjFxEVEanbbjEpjFGKONahtfCiNKKbXvO0AAYaeVgGxWg0aVY8phNERaaxDIpRzHaZpys3KXm8FZw5Vvrq6mKQDK-TRf315vLy8Jdcn5-Rhe3my__PHnT0-HPC-v39yuLtp_-z_9mnP40R__wePH-4f7p5dfvD0-PZeUCHQJySiSlHOc8xKb1boWTrHYzmln0-FYoTbdigsrUjEHIDS-IWdQUKQKc84JjNGkEEVVLEvSRunO1iTkHBASaYtgqaKjFIrtmhwLac2lMCDXLEVqgeHqVYozIA_DxjedJsp5EjTz6RjmszbNKZy3_eY8L32_Ypama-ZpZObjOJ2nxTi3Wa0Pj08c09_-1V92w5o0nY7TYX-YUopzetiP_e7yPE33-_PH_WkR0K3_MI_3SwooiLxy_d2L20G3D4_PtcTfffNhCePDw_HDw_Nus02cQ0y_-v1HJth0_Y9-8OrC-lIrIB5D9NYoQkRc5mW96t68uvHa3l2tfdt0rTONvb26SDGjxqFrasocSl4WEogxEylv7T_--o3TZrtqbrb97fXq7mJlNfzg7d3d0Ajytmu326b1vjGKPP7TX_zowjcXg39xufrh66vOqpUzQ-usIkVChFUEFRcuSyzjNBtnamVBSSkLCGkqALkyINVUU64pFSBUSs0xK61SzsKca22cH6yNsfjWWGsql3EMqWRFn9CJWrkKSrdqrGJiUALHaRnnlKWmWuc5TiEtMTZNM81LrTWkXAFQK21tCOl8LuewZKlTkV-9e5jGOMZUhFPhULKAaNJzzP125Vzz2-8_Ph0nUeY8LyGx0joR7Ho3ZX4-hQ_3-xDSaZ7vPz4xyOnplCRrb0FhQYpzDHPUjgjo-DQCsiYlTMZ6TQKZrbOoxRivvXaN1bVaFJISl6W_XHfb3TIv-4cH6wgJOUsNM7HkZdbOEgHXch6XtARS1nlTSvHen0-nHKJpmykVYrTebq-uru-uV6u-aRwivX718g_-4Gevv3j54tULbWg8z3cvb1989vl135-Pp67dXF5dba8uD-8ezufnHBLWSEha2VrietOfP95rNMsUXdsuYZaUnLdSU2ZA1EqTtsY0poSqXAMAJRRjbK5itNp0zfPz8fLmgowVhHE_llQRmFPVSMqovCxY0DQm11rHRagKGqN9mmNIoULlAsQVCtTCmCvkCmnGUqFUsAgAiAghKiglRiWoReI0p1pAa64ACgAR0AMw5Aq5oCY0CCGBEgAApzAkFECtIS5QE5SMuUAqAIzIwAKZiYUA-BP_IwK5EKKUClxBEeRKhEpryBkBuDARiSAaQ4plCYAISivdSMk1BQSqtTCAcRYISHvbtsv5DCLKWyDFrLphPT49lCWwVGu99SZMM8faX23CczKN5pRziApRGUciyIUrAyhjdCmJayWNAlBZuBayRmktwjUlIeQiQKJt-2mk6lMZQKTIatd4BJkP48WLt3GZpGbXDox6td1wSZyzlNT0fU4JoBpjaq6IQgoFABUprV3bKMJh2JwPB62IRdquBamkyA-r03i6u3mhlKqMRLhebZfzyTiPJd9cblZre7x_-smXLz-7uVp3zRLGzlprtDEm5xRT7voOBdZDm-aoCbXRbetQwBiFBCGVWqo2GgRylcLsrI25IqhP02PLslhjpnHOwK7z5_NiSSHhOC9ZAAi11ud5EQYkJAWEhJqOp6VyAcCQEyCtGzvXao2uiFJr3zQGtZT0if7vvTVEq85brSvIPC815ZizNdp723qbQrbOaqMr1wISc1HGfdpOjyFo58ZpPhzPtVTmmjK_e3xsm75U-fa7j9bqpm0BMYbonF1t-q4zRqv7-6e__Hb_xz96tbvcDtbOpf79b39_fXn5fBrJ6HFcQs7t0HltDufJN_3-PK6HTlfOp9Cv7Z_-7EcO0DfGdx4KI5HSpm3a7TCM49kBjVOIMRuu7eBVkNW6_2c__-Jy6BpSCtFZ03hPgFxL2zgFtN2uVytPAFNIt1db4-yyxFDjD7_4PMZJIT2fTlahJhtC0t7mELQ22rmc89X1rmvMq6tL9fo__C-OH4_LmJYlIYPU4ptmLDXnEsPSrewyxjnE05ISg2us0gSonNM5y-E4gpYl8BJy02hn1HlKpyRjLJQkzFmhFpbT_omFcqkp1rRwiYWkagU3N8N3395720whFI0CtQgyiyNKLBXYGG0UAFCqrKxKSzTODkN7GKfW-2VZEBQIeOdDmBBVmCMqyEsUUDHMDFhydb0pyOfjQp_6GQo-2aprriw5x9g4R55yLkYpQFhCQiTXDVAyMmtDKeSKUGrWRFQZSlEa8xh1Y7Xv4rQoZG2tUkSEBaRWYWGpRSroxsbxRFZlKWFcjFLAJc4TIMXTWSlAFnK65EpEiAjMXFk15vTxUXvjWgdMVQCloiImIadKKilGDQyKOGXyjmzz5qc__OW_-atXb-4Uudbp3aqzlhBhmYJWSgARYEr83XcfS1zIN__x__KPBmr0zuaSbz-_-vJnX57G8h_81__EWPfwfJjORxSIIWuFxun5dGpdc96fjFU1MxJpMt3gLZl5is6aCpxSAaV8453RLy5W87IEKK9eX3_8cPj65dZqozQAg9FKAXatc84gSaml5LJdD4RotPLexRCctYSAIo11pdRpmpy1IkBEwgICq83wKWucWRCo5NI3tmtcrYIkLACIm80akVCYuS4hXF3uAAG1AgGt1MV248kACwDGnHPJJecpVHL-PCdSalqW3vlaakqlSHXWEOBhfyZFzptSs9a61myMRYSSC7L4xuZUrNWKUJNm5iWGUO6tXRmkkFIRIK2F0AiEpZKA85YYci7ffPPtZrtth-Gv__Jvt9tNnNL_8N_-39-8-WwZx4_vPv7g9Zvz_riM0_vfftzcrH7-9Ve_-uXv2s4_fLi3Xc_Mw-aixISkAE2pmRSkaS45edfM57np19a2JYUwz2i9MUYUIZNzDZJCBbkULqCsImW48iceTxAli6TKCkkpjlJqQkQSlUoN6ViLIiKtMaesG18ZlNKQYjx8X3MSoa7zlasgry7uSqm3L9_qT56mp0kbPE_LsszDur-8fZFS8m2TRe5e3O5urrTR19e7ZVy6rlcEJdWbVzcpBInFORqGbv_wQEjP-6f9x-dlmn7_uw8p5v3p-M2v3p2XjM2qxmVr1IuLixe312-ub8bTtIRUE-ecEImQN303jXOIIgAKZPD2h3fbzbDq2-bNi5uv3tzeXV12zl22ZjM0KMK5OK1e315dbNZt37z98i6el912pTRArcPQ9L23GvrWDE6tGv32evWTz-6-eLm7XfmrTX8xtI0zmtSqd33jrrfDxbr97PKiM9praqzpWt06qwAUEiGmUhCkwCcsKxfGFLNvPIAoUiEmQSxcT-OylBoKT3OoDJmr0iqXIkC1ACDmWmJKmUVAmIWM9saWzCEmp7XShIqYmUFCWJrG11y5yHSaBDHGbFtLpJY55SyZecnRKptyRKVCTJWrdW7du1whF-58k4XPMZ3mOI3zuw_HXApLnc8hC22ceb8___b7hykl5Vyp8rg_u6Y5Lenbjw-Ph_PHwyhKjUvRTj88PKdamAQ4S6055SKy5JyqlHnJS5rP2bbKWTdNM1aumYGr1hqRas2VOYbcuEZV1Nqw8DRG1Jo0ffXm1d32InM8Pp-td2CBl0zCIVSAAqAQoEom0vNxP6xXbd9xLe2mbTtvtGzaprGKlKFSHWEJmVO8e_VKOxeknsZFFCwxDbuVsW6ZJiAZ5_lf_9u_Pu1PN5fbH_zoi8v19quf_uHQ9LeXt_2w2T89W4XLGFCzACNAc7FK56nGbIeOWQhRCVjvc4iVsKRCikgpMsp07eXNnVP04uUtEi4pW0un_cjAShlgBsAqLMtktHOkQsgQkgaqAqaxyBwPZ6kMsbBGyULCkiKAwBIgFgCBLEAacsZSNHCNUXJGkJoWiZU_ZSIxozJQs2qszBG4QmJlRUIBQSgMlnFMmBIpkpyhAgFjBSkJEgMSCEBmQhEpIoxICCQpEQEBQGWpTMyEJDmjACAQAoCgVgKQT6MxTiqD0v_gL06zVk5QlNYcY468urtOc1YKNQogaWPbYVXyLDmJcNM0AKA6l6Zg-1YR8hJAuIakQaz3CIpTIAAypllvclxqWD6tMFpXalZAyprKhXNFEO2MiJimkVy1MXmaUBAJoIixTRrnkkvT9fMy9sOq1Cyk2q7V1rz_3a992w5Df34-dtthet6rKrZtUpjjnExjb-7eHp8etLNDvz6f9iKsjEZBYTbOcuYKMnTD8flxs1mnNFln52nqVmvj1Gro37y5vX9-_rM_-Nnb2-3dbnOeFpa8ar0CQUTtjSHwzjhFRhMCWqtFhACFRZFS2hyOT864UiXmXAW00TEna9xpmgERCEREE8WSmqbdH8fOuVh4CdE6x8LD0AhLDMV53bQ2h1oB93OYQiyFULAwK2eSlJKr1ppQjFbjuOxWLYg0znadH1rfOKUQETCEmHIEQKNM2zRWK2M0IDirgOg8ztMUmrZdphkQSdn98RhrHacl5aKM6dretKZrm4v1cBpnZ_R6NcwhGaWds2leOm9jzpWz1ebrL27vri9iTAXM__g__WXbt8fD9P7poWnaymV7eVlS-fb9-2G1XqZZiZnn8e7uum3U16_fXAydFtAa53mZzvOSitbKKJJaapWn_T7VajSt12uv9A8-f_mTz14M1mAV48z99LBpN1rrJYa2cTGlGAsLkFK58GpomqYx1lxtNtb6FOPxOCKYb5-f39xelVq0VaSUMco2NsWw3m2cV5zK9Xalbv_8XyAZrVXF4qxnknFeyIK1SlUlYERku-7XXV-k_O7DoXHd82lkZqm1bf33H6e-M2BJRJ5Oc2RIWA0SCJM3Y4wG0WiTC8c5aGOBcuuGIjyXnCP7Rp3OU4w1hCiKSq7ffniiCrGkblgTsvWuAqIyvrGucd76mBKIlFoUU85ls13nlE-H0ycPXwjBWCulgEISkZTDnI3zS1g00TwlIcllKdOUQzjtT65xkTMXnKepcEUmYa41h2nhWvOnVdaKjNZaa8I4LyUWAOyGXitKISqFSCpn7tabnBYQSSFImJX6tDdGzgWQK4jWWhudw2yd0xrS6WSdrwAC7JtGa22s55Iqlziduu1OakIA0Eq4EqJvbZ6C7ddFinWWoQiR8brd9eC7Yd1p5xprms5Y5QZvAFELO03AGHKOqSyp-t32m998t77cvPjs1olSjobWNUbvz6ndNRU0iKxf7p6-eZ_GxRtrjNHWxphAMsfSWDfHcNwffOt6b0_PU9-2OS2fiNvCUGt1mtrWK4Jff3i8XPVLjLvWe6uRBRGUopxLTMk7oxQhQusdkqq1dG3DtYAIaU2kBCoLlJSVIaN1jimVbLSx3gIzCzwc9p1vtcJNPyDKvMTxPE4x3FxcCKIiEmFvnbe2cdZYHVPiWlGBIdVYY5U22hBBrdl5e5wWNwyPp_NxDCHlJaSLi5VDejwevbIpZQGoKABSmRXpUkrTtkZrpbAWVoQKsG1bAsgpt87FnOYQrrcvGt8gkrFaAIAglyosKSeryCrqvUNC65wAM0OaZqX1N99-_2f_9J8g8DjNP__Tn47H_cXl-jiOm83g2u5f_8u_NN4424zjIYYkpPaHk2m9KBJCEE7jTFBRpJxP1tm8LKTJDwMB-c7O-4P1voYQjhMZrY2z6zUSARBn0Y23rgEAow2gkIDUioqo88pYLepT6jyZHoSJFJeqG59zKUWYqyIlhQlgmY7Pjw_dapc4kSArmcbT7uoGCT77_KtlGt_-8LOSyjgeP7z7vvHNw9N-mhZCds6dpvn4vLdOde06l_h4OIZ5Rq0b35ynYEnFHE9TGKdwffdCiTQOf__-4-FpatoOrX14Or573P_Vr383p_y7Dx_7ob282BgyL1_e9Z07n6bnKXJlZ81XP3y9suZv_v7bQnBawrrtSq0hy5Lq9Xa9HlYLwBJS4OqsIUXONCHWcT_mJVpNJPz6xdWma29uNne7obPqq9vtly92r9f9y6vVxcp1RnmlGgsa5Xw4Nt4TklbEICSIAEaRV1i55pi4VE2GFADKEmKIMcacc60COQkqYJFUc63_UDPNKU_zEgvnIoU5lZJqFeAiknMGgVJZa0ARozUr1EZLZQOYSn04p64h5ywgGlIlJ60VMWw631k3DC2AAGghYoYlZhBx3jlrACUsAbUSgVQKIj4f57BE0iqXMi7JbhpRVkSthkYAndPO6uvN-rAkQShVppDOSzxNEY1KmR_2x9Z7JP0Xf_MrY5vn44gajbdoVDP0p4dTzlmApykolDwGhlpiSilN57nmZJ2xvbNIXBgNkrMojJ_gvFoJARBEoFl1yAyV7p-P7cp0_WoqsaY0PzxpY7Q1um2hoDU6nsc8Ra4CtXINzw_7fnORU5oP4_h4OD2eTsd5_-Hxw_fvp-PIrBvfGsDf_e773_7yr8fj9P7dd4_3x1__-htrzJyTICG6N69fNyDffvP93__dN9c31-_ef8MA_z-a_uvXsm2508QiYrjpltk2d2aePPYeXsPLS7KIMqzqbhUaMk-C9OfqRYIAAYJQDVUVu8giee0xedJts8x0w0VEP2z261qvE3OOEfH7fd_3f_zdduj_4i__-uH-sb3YPB2m6_1OSpVlLXO0hFAKZB6GlowBK1IBVRUBFHOS7cX28vZ2fHq0AJ--_3B5c1lj5JpijpVZmNUgGOacoWTngndmTSssUbjabZdLUQBZFpAKKT_rdcmiHk-gFaRCUQAFBECFmKAWKFVTelYWKyGwgggiAAuwAiKSamXICZjBAeRnj69CzMACqYhhJMHEgCKFSRQBCIFEEZAIUFQyIyAYglINGWssoKCCQdRS0diai_FWSgUypm2QAYAQAZVBBAlKXH07oDXGGM3FOGe7odluUA1JBZGcJbSt9fb89FRiQgNkaF0SICDadmhLTJwKItecDBkTPOcimVXBNk3TdvPDIwA550LXL-Pkm6AiRAQqoAoIImKQ0AdEBFVFEFVUCm3rLCogWNts96rSdG1aVmEKbVCuWkvbtJv9brvdj4-P3js00O73Ktz0vbM2xVlE27ZF1Wkcr2-uuVYbmhhT17XorAshxrjZXYOBrmlDE_ZX185b793__f_0P2333bDZfv7FzaUN-12b19WB3N5ceO8JMZWEiCWl4GwuVaoYRyDqjEUD1poUC1knCrnUqhBTFRRlUAOqmFMuLCVXFhUBVT3nIiyx8rgsRKSg3thlTXNMwZghNIJ0PE2xVgHMpRhDxhlvaBzXymINQskG0DmL3l5eDcLcN41zFJfUWMfCJVcVNcb1XWsNlZRBIHirAKdxmdbcdN20REA7rfHdx3vnmmmJqeRhP1xe7L21p3O8u9pYMgg4DC0SeO_VwK7rlTTncjjP57m-vL24GDbHKT4-narIaZzO8zqu8y9__i2i2Wx279_-NI7reZ69Dcs8sdaXN1fbTRtq_fnXnw3ejudzzvUZFWWsO52OiOgsgfB5HF-_uHn92d2r64sX-90Xd1e7xnlE76iktB92xhASkrWn83QYl3_-6eOmbaPUw2lxxsbCgHial_N5OZ-XbhiO5_FiNwBr8H4YhtPTwRmLxjQh5Bi7vr_eDg7BvPmf_m-5pJjZBmIWrqxEzMhVXW-0qiejVf_69eb9qVpnz-NM1sZSlIgFLq56qMoKRRgMruvaOEqLGMXTtKZUjdM11bHo0HmWVBRSTDb4dU7N0NrGxSz761CzrqeVRAZnci7W-fm8IOk4RSLyjQnGxiXvrjZpjFnqNM4CVAXatnk8HLlw37eKpsSiUi9vL1OuT8dJgAxZMsiVMZCytMHP4yRcmQsFo8rIajwZhfPxjErL-QHUWIPGOjQIRNZZKLXGoqyK4vtgjOVc0rRqBUTMa1KEHGcw5nw4Aeoz1bisRUlKybYNKqCiyMxx1VprXJDRb3ZlXQyh8U1VsCZ436k1znmpSRKrITLod9s8LVXwWSgjLLYxNjTLPHXbQQv_u__jXz98OL96c2u8_6ff_fEvf_21UTKBgFRZhRCsaRvXhtC_DMcfH23Xfv3t56C8cgKD15fBsG1725CVymHT_fjb74wYInt5fXOe534zSC1xrX7nx9PCzMY6BfLOrXEa-qGibnfdaVraxhnrvXUGMa1r37htsNebdr9pay7OGmeNs67tvDKXUg2SsVZF2xByzilGFhWRlIt1Lq0ZAHLOXds2wSGR986SCW34dP_-ar_3LqAxOa3C7L1vu3Cx27GwMTaXSoAE6K31wdXK05KmcVzWvOuH4IMlY4gAnvnochyXCpgKiyA5m5hvr_aq2DjPXJ1zlTkXRoKSqzFgrLHGGERLxnmTYm6aYJHIEhIGb1POnQ9t0yKQijhrSskMkHJBQ4lLIHh2fb378DD0XVG1xu52m1evrrd90_fd7__4489_8fnx4fjjDw-_-PNffHj_Ma7Rdx3nGNr-_U9vX3zzbc15qckEJwJQS7fdcqksYEJ4dtFbowYABFzwKebh1d4BxmW2iM5bVFADXIVLtcGrKKASEpKiNTlVJFIA4xzZzobGhYCsAlBLqXgSCrWwsda1jQ2emW3oBKiyuKbhVOo6L-c5zev2ciCgkmO_HVi522zH0ySAh08P6xRTjK--eLndbG5evCAjcVxV-fDp4XQafdM23nCVd49H1_hlKTY0r968OY_jnPjT777vd41InUsxhD_72WcfD2OurKh926wxno7T-4-P7-4Pm5vhuEy8ln__t7-8u71srf38ixc_fP-x34XC8p__-JMhdzycXlzvSirHKQrUmPLh6Qys82kc2jAeT2mehuBuroerm931Nvyb_-nXpx-fhmCvLjZXffjiZvvVi4vLodttWgcCoM_LN1U1CGQbZw1XziLkiAGnKanIEvM6ZURsQlCCaV4za6q8rNVYNNbFUopIZX46jU0TgnfG0rik-9PivK8CS8rOOgK42veOTLBBQRGoVHbWklIVrKAE6IicdSp8vfGiogprzIawCb5rGu_NrhsAyaI5z-sxnpg1xmy8Nc7lXEsubRO2u12pDKLDpgttWwuLNeOazks8TnGaWCr7YK63gyIt56VWQcT5NJ_G-PF0WlI5L4sgxiWmUi2RMEwp-9ZP51kEpuO57Yec6_R0ImtzKq5rmSuKGm9rkZSzdcZaAoOVZZnqzashp8os1qJBLZVrLWlNJdcUc2iaUmK33bjWP3w4VpY1S8lJmX3b-KZhdLbxu5ur8eFJkgIpEMQ5KaF3Li_r6f279XSqpbbbrr_aOFAX_DAM1y9uX76-ndOc1wnLcv50f7EPejpdX3bvf_-H4_uPH95-UiFZZ2_Nr3_25R9-_6Gm-fr26v7dp9PxYBB-_OHdOC_ffPHVb_76L9-8evH400cDppa63e2U1FuqsRCY5ZQk8_Vf_PL004Oi_fxXfz44sx6P18PlOp1bH66uLj__9vP3Hz-uuWQuagiI5BwBBHIMbZvWzOeZmClYTgKAsmRYZxAEBUgJFPWZwR8rIIIKkEJiIAu5YC6qGVShKhpUESAyBiUzGAvKUFgJIeZncQEAQiqgCvU5-k-QElQFT_9SCWBVFkRURCRAASBEZgRQAgAEUELSZ3gfV1RVVRYga6QWCt76Bhtf5wW5cIxKBIY4J9d4UCQTnG85FzDk-q0CnR_uNcd2u0Hn4jJyqQSEIF3vVXU55RdfvZKY0rqUGIEQVfI0u9CQteU5FQw07LfpPGopqmKbUNbVek_PqSBnuWRE0lqRDKsY6wBRABANIlnvDbmak-uapu-P9-_bzaVKdaEBrZc3L8bDgcj0XcsC58PZQBVUrmBMK5pa3zhrRDS0jYjEdQyhWaZlf3NTa-m73nWh22yKiFbZ7oa-CTmu3prN9iLV9fb6ounar-7ufv7V61f7YWhareWn0-Hu9ipYh0g55VJK2_i2ab2zbdMAKDF2XauFFcAYyixcFckAIAAa756Op2BdroXIjPPiQxBRBCWwc6zHedltunFNbdcuKV5cbCrrvKzeWSQSpNO0CgB5ex5XQSEyKVVD2DRuO7Q11y74Nvhd3xkEUgrPTirjgndAAApCiIjehya4eVq7JlhjrDfTvCqScXZeVkAba8ks1gVWISBnzc3FxrAYhP3QNtbmmC-23WbonAvH09kipVzikq01L19dDW2Hxljrfv_Dx34YjueRjOvb8M1XX7Tevrv_dH__WBVzSVcX-_N4Gnzz5vXdxW4zPU6_-eXXV9sehEOw223XNuE0rTGuF1d755p1nYa--_DTw6u766vdfts1L692XfC9sUAEIJ131lpLBgGK8E8Ph_vz2jj_3__pw6enudu3U5G3D6ff_v7dP_3xoxgYhu37D4-bzRAaf3t7mVM8PB5uXlxaZ8ZxvtxvQOTNm-vN4A2T2fzq_-A7f3k79Hv39JB2F56s11qc8xsDnMo6RWfwARAAvLefDlMuHEsurKFpFHFas1T2TZNTlcgo2Fo7Tetg2wxiexsBbhv_ZuuWRdYYj4djLtFYc5imeVrHZUE1NbO1mJfCVUHBeIQq6NR2NmV21izTaq0Zz7Nzdtj2ubJ3znnz8cNDP_TGABcWZgCwvsmQgbCWWrVuLy5TWlAAENI852nKcS01V2EppebCpRgki95ZBGZjAzBLKcY1z2HxnHNNRVUVhaxBwJKKb22pFYhE2TgvOZNB5mKd4VqhVN9YslhzBgXfOlAGgppX4IKg1pAoMagqo_FaGQFyyvCsolJ1BpAMKaxrare7FKO1hIjG0DP8AD12bTs-nmzT3P7s5osvXp3n5fZme__p_NXrK29NZCaEUoGZU60eiYu4zlrv_v4f3n755aveO_J4GOMX235hWdbMAMaHh6cpVTp9OhAqgjZDd3w8cixlmg3p4eEJVExw4zx1oUspOu9z1aZvRcQ7F0veb1qDxCo3lzuPVGO53PXCxSAZ6wAEQbnwuibrHAAIS9sGFc25iqpzLrhgEJm51tI2wRobY2yagIDu2eSw2REZESlrartgLK0ppiJK4J2LpdRcWWHbd4CQSpXK__juw6bti0rbNprFhWCQFYRVc61zquO0CsB5nJq-r8Ln07wfBjJoLBFBKtVY4xtXModgWx8a72qtUkpomiYEb501BkVrraXUUsV7C4iECIiFuZSSUrbWMYtztjHWGioshKZtfb_pAeHu9nKNcT4uf_ju7cvbi6Z1WOSXP__V46efvvr510gkFud5WZe1KvjG2mDmKRqAuua6lLbfrPOIHomIDGmuyGIU0jKncTaEeYztxS5Ns5ZqDCFqWWbvG3DG9kN3ccU5G2OkFkT0fQOK5L11FkvhmLlkdMZ3DVSwtiNEsp4NgAAZZ5wtnMlbRc5jDG2npVhLpLIeplJrXNdlLUDGtU0VCE24-ezNxX7_6s2rbd-t0yJcf_zvv-OS5-MJSjrfP0KtMSa_6dBIXVJVubu5-P67H7abcNV1mxCAcFzjjw_rdb_5-9-96y2AwuFpajo_jykzx5hUpFTJ07pE_e-__0CWttv2h3cfwdiHx-Vq3--DW9e023Xdprm5u7zebdOyemP2fRPn-PmXL7bbrvP2z755nca534VgaFmSX9ZX--Gzm93Li-Fm2-yHJljrnC9VpphEdEl1nOec1bjGEKnCeY4fD2clP07x06cnsq7rm9CGrm8K82man-WnqdYiKkjjEgE05ZJKDY03aFjg6TgvKYOhLLDMq2uaWouz1hExYqklxVKFE_OYEpFVQgIA0OF_l3C1rffWGWuttc5bldoPnbPu2TZ4nuc1puBDE7z3jRLknFUFgABBVLZdR4YIbUwcmVnh09NxXvJaCjnz9DDGoiOzgJCj1gdn3fEcX7y6IGfDdoiJT6fzeJ6rwvbi4jweFfXT07lpu1KTD-39pw-KCgAuNC40U1pvX70M1sSYlZAzM9fCasACs_P2cH_WqqdxQhFnw8XF7vR4UFVr0XmXUwS0ftPvhrakGDzN49GRjcuqTDFl13hQOX287zZ981lPQA_vDv3ltrvabS42OWVVaLY9OpuWZTlNSLS53L_85o2q_PDH77__p-_m87nMa9u187jM50kZ4jmChbZpxuPjdD79-PY9N_DzX379zTev1pTH43z16g6Z-z6MT8fT-SBRyEDXh7_5q1-_-_Cgwi9ev1xPY9v0iNI2DQBIKqbB_dXN_fc_XF3u717cLXH6q1_9eSBIy_iH3_6-5DpzlVpNsKCiBFiE2KAgK0taXUPGGo7ZGCApOkWoBcCAQWAGUkgF1gxIIApVgBPkaFtHOWNVjREANGdghjWhA60VcgECKBUMQMpQGQDBApQChiAxWIJUDYCWCrU8Az0RASojsHJVBSIAFq0FWAgAyUKtwGwMibAUJoOABlXJklQBZ60NtjPlPCMoGSKyZIykjGiRbLvZSFpVRK1rdlsDUqbRt54rq2plDcF7H9bpLIpV6LNffsPztD6dbbBSC1l8Tv_btlGAGiNZ49uh3fbT0wkQiICM5VKbrhMBAtKSQAEAjbMA4JuOc7FDW3JGY51zhAgoxlnb9qHbdfvLzWZvUK3zBrAZmqf7x_3V1jm3LEuKc-h6JPFtgwaCc3FdjLHMtdayv9zlFI31YIhVa-auHzw5LsUFTwBvvvo8p_XqxV3XtmRk6Dd3t5ev7m6u--aLu4vWucPDT_v95e3FhSUIxjtrci5tG5yjrmnleYFkDYgIMCgi4brmqqBA8xqtM0sqldlYI1WJDAsczrMNrutsKhy8PU5L5uq8nedovUMEb03OtVRGQ9ZaNUYQhBkQKkAIjTO071oCijH3vc-Fm9aJqkU0AKBgvdkNXcrFWZNSrbWKgPfeBCIFH4xzrhael4TGYDDv3j82XZtYEMmgkcpIZC05Sx5JKvR9l1OepzWmkhXmwt_9-JBLyZXP45xj2W4HFhrn9f39aU7xNI4fP90XlcPx-OrNC6lpzeXp8eiNF4Dt0HVtMx_Hv_j1n52ejvtu82__5md3F71RfXx4urwajsdlXlKq7NvQ-PD46ZMzNsb67befv3l127UhEOz7tmudqDw8jPvdYKybp1hVl1R-uj_8tz98mNd8mJNa_PDpcVn5H_7h-7Brxykyp4vrq3mJLhhjzX4zEDDnur_YGgu77Wbomr4NfXCdt733jshc_PV_FNF4Kjmr88ZZd15iHxoFPh1TjBm9eTqlF5vWW_dwWqoRQZjW1PQtKijzMwWlZG6CZdYqtentaY1Db7BqjNUIDl0zTvXlduiHNrOWUrtd3wZLxhhRLnw6zz5YG4x1ZIOJSypVljUzoUFKMasCV65rLlmewYY5Z4e2aZpasrO27RyXQgDWmRJZAHKOKAAKqjLPEUHIyLrOwuKt67e7GOeyrMLy7Coyvlmn0TfOBpOZSymGQERKqYhQawFA3zRlnhHVoAVENLZyLTka62stBkkZrPfembJERLSNLzERQckVvZVSSdmQKlCt7Nomp-y6QUFrStYY0zfruEDJWgoB5SQsigZM6xWUWbvt7Rones6_VTY-xAxN23_z7ed9H2pOc54R7NC3jXcpc8m1C7QfWo80lVqlnJg_3p--_OJl46yqRJE8xloKeUJPGeEPP366--bupz_81Ac_H1PTt_PjwSNDznmN_X5rvOWaVdR6a62b49o03TzOl5udINVcGu-5slVou7brAhQeWtu31gUXl9U8H4rRMPA4Td66pgksHNfogw-Nf6YaA0LbhuCsM0aErXON994ZMsSVDRoFDNYRIRE0wQOaaV0NmuO0jEs2xhzOY9t4QCylPI0zMTf9UHO53G6AoKRFQWrleVkro-nceYyAxoVwOi8pFePsdmigsg-ekBjUqCKAc64JgYukXIgwhCDCRMaQsc4BYkzZWPLeL9MagrOt5SrjuLCA9VZVG2cNWS6yzLEJ3jhrDS3zerHbno_n83l6cXl1Oh5-869-ub--ON_fx_PTxe7i4eG0aQMGOh9Wxhr6jnOpS_p3__Pf_v4f_pRKtsaEpiWDJUatSob8zR3mVGI0ZFxjUapBqEvEkjWnvCxYmblyir4NoMo1h74zztnugoUKkrG-pIrWqyqBeGeazUbUbK5uyVgR7C8vmFkyGt9qKWgskiHAsGs1VSRTq9QKzhCLSspEMD8cDvePhIrGoKoyl1pjKusqFy_2RfLj_SkqkLHbi6tSsmv78xhLUkuUx7XmuaTy4X40Dvqhb3yIMX356nq7a_cXDRIta3zz1W1NWVUP47Tpu3Ms_W5jGweofe9KkZTLtKabbf_13fBwjP_n_-Gbfhjavv3uxwcnwLUE48fzvO3cdtN0rV_WBZlvL9qr7dBY--XN5Rd3-6uhux66rnEINWV-d_9wrLyW-v5-_OH-NMb6h-8_zOvadl0bXNuFSvJ3__DdOK3NMMQ1skBcoiHabbqY8jjl43kma56JYVnqh0-P47qsMc9LIWcsGQDMuVSFWLmILEsia58X91zFWjcucV5i4513ngwywPMb0BJUZtHqDBkiJKiEJZWu847QoTPOEqEoxJwLq3POWENqpmlZ1mid3fQdAubKZG2trIg5c-QaU1lSVjCFhQliLeDduCYkYxvLVciYh4dD2_lu4zpyj6dxe7358P5ECtbTfJxS4tCG09O82TfrGqdl8X3PtZKhytw0jaBwKQ5JyShI3zdt06jB16-v41rzmppdT2j6xsc1Sq7ztKAKa5GMCkWqeEtxjutxAoaasrXBGEOIqZTN5YCVOVdgBqQ8Zui77a5Xhm475GWO4-KcITI1Z1AR0e3VFReZx2l6nOI09fvu4vrS9i1XXU-nPJ7QUH_dr-e5rEWUOcac4nicWfnTNP_2H787HQ6HxwOzvvj2zcu767hMJY9vf_owrcI5BeutpaHtLi8u2n6Ih3NmyArb3SBJdvvu66--aELo2-Zi128pDMNmt7_Qmt9_ejTEInYbrtIykbLkgiqgXEuGNYHztVRgUVatjKyoxooQomQGZCgZYgYQyEyu0XmGXNQYEoYqmvPzTRJSBmc0RigVQNBZEKXe6xQNoGmcnCeDoERgEEBAVEsBETDGGAOlWEWqjICiDAzGWCiVhLVkdE7pmW2DUgqqooKKKrNxFkS51uH6CqvkccIqAGC8h2csKxJaF3aDAVvWxXrfXeyBYXx4HHaXcZ6db0rJxhpjjSyLELnQ3n7x-fr4cP7pIxjyfeCcNWct1TijCDVGQTKh73bb5XjiWAyqCz6X7IKvAsbaZmjjebKEQAjWWxcMqHE-52KdJQEwgEhxHH3XobEKput7Ii65tG3IsRwen7a7wfvm-PDY7fdSc0mRrCE0wnWz2yDZw9PjxcVOWOZx_uLrr5Z1AcS0LP122PUtqjRNI6rb7cY7sx02hHpz-6LEOGw6Y9X6cDwfbvf94PzFZu-97TqXYiUCZzGzOoveWAOorNZaQlDQlKqCzPNKwZG1KeUquua8pFyylJI3mw0ziygSrnOe56RVYylZZGiaJdWrYXte4t3FngBFgKwF1FqE0CwxLmvKRZoQUs7GAKA8d_EBzH7XsYCzjtRUrm3wUtkYYww-PE3GknVORQHRea-VLRlWXHOpoPMaT8fReL8ucVnWNebCtdSyrskgffb6OriABqZpdmRc41aux2k5zSnn2PV9aFwp2TrXdU2tOi0LEjzcP6ZcljRv2vbq8qJrXUm1JP79H78_nsZXdzfem1pS78O__bd_obl-88XdxlvO1Rg0BCq8rPnxNA595517_-EeWLbbzfXl5mK_xQqc18aHuMyxirP26nqLAsfj2TW-KP9wOP_-3WFZWMg-Hua1yOPTMZW6vdoeDuvj_fGZtwYg-_3grRmatsbctY33pvF-npa7u0tDZAQsEae4aVtz9x_-L2IMorhgSubzsuYsIlwruIZAteSC_AwK1g-HqYoAGmEZz1Nhdt7NU-QChrBU8Y0hIKPmfM5SRYqYxmy3g1MQhHfTKSuWnBW5lKIiOVZryFtjAYrCH54eHZBWUEUAapqAJQszbExNBUBD48gZzgWNzZFjLmQMCrddx8rGuLJmZw2ROZ9OoWmX4wmkklXrTIyzAKcpokitiUtEBKMYvAMEVgEyqqoC1HoQlSpQivMuxwyVjfXGgHBRLqAYp1mN1FpdF2oW3w3KWTIrKiqX-QzMhSs6o8wiAgoqBUsCrTkWt9kJqIIxIZCzXBkVuIprB6mFgNAgqxpH28ub-TR2d5daGa1P09l6X2NsN53bb77611_lc6pgu4vd9YuuHbwiIdlht2EALhycCc6KaqoqiNYYT_qf_vHhq1cXFxu_xHzOZbdp-ybMc5RawdCaDIA-vnuq51PwjfMoa4bKcV2ZudvvmCUuc98Ow7YnYyvX_cVVLGtVyFxvrrac2QdrCEvOw6YzBLu-4cpDEwBwHqe2b5FMCKYNwTp7fDqWktdUraHN0DGzd7ZrWvyXXnTdDN2zr4oAAZ7Jb2q9S6WQgXXN4AyrxlJTrjFl13aVOaayGzafjudlWf_ud98Pm833H-6_fHOHBKpcUkay8xrJ-XefHlOuT6d1WdNpTmCo7_of3n7oG7fteiBBxJLLuiYFccYG73IqPrjGeyIiopKLb7wCsAgRuWdaAWCtmtYkIrlWMq6KqighIAAhhaZB1BLzOI6bYTAEwXspNcVorOVa7989GYbbq931zdU6x3GOd3cvzvMiqC-_-Lzx3Ve_-tV_-v_-_yxS6IKUylxzqsYSsggrprVUtq233tVSy5xc20haRdX61oagNVuimgVUoRReFylivEWHru_JNX4Y3KYj40UB0SAYJCMq8zyDtc-kWuesb9th09smlMzdMEgRFCQk4xxZIyDWGqni24YQbdsYkaYLoQ337x7Ih_2L66uX1-t4ePfd2_PxHLZds98aY0PjlCwqdL035C8_u7i5up7n9Obbz1Dqxw_HFy-u0Jq2bzJzqhxsO40lZqLKoTViDKsqim88KRJACO4Xv_r86e3p8HR-db0_jvE__PI35xyfxnKxHw4pN8FcD96TfXGzeXG1vbncX11t7_bbztq7i12Na2PhV9983lhE5s43RFpKHZf8MK6PYxzP6ePDuQDNqTw-ndAaALm9u-6JliX_dH86r1EIwZiHh2MztMYQkVGCJabH4xQa_9xr_PR0XlI9LBOBPc6RjO270DdhjblUGXONzCKYpc7Tkqu0PnDhaU3COsYEBi1SVYipqIA8n_dyaa2tqInrKWZDVlSwwpoKExSWcYnjEteUWVAUBXCJmVXbtomZpzlVFWPseV4P0_xwXB7PUywlJTbOpVrmVD9-OifmtSIr5JrqWhHwNKWSal1KJVqX9P7T8Xxc1yUiyEXbTkvKuZxO83ia47LYph3HeToe0jIfjmc3NCmvjQlSanANempsm5fyxd1VrqqK_dALaJxXsKZU3l3smz740FjjNxcX_-F__I9zYu-HoXPehONx7Jx7ZjK2faiplFQtkSikeXFklqcnJq3nlZFVaplWTpEr1yXmGEM3AEI3bNdlGp9Oy3m6uLowXVMzz9MxlsSpGNRusylRhqs9Sq0pkWJaE5cCpQCoOrscjliKLAdO5x_-8N39p-PFfv_i7tVnr1-9_e3vQkDrwv7u5WlJ4zxebDborN8P17fXQPrZZ5_thu7b1585YzKn__Zf_tef7j8c5_G__dMff_63v6xJDo8nKUnyLFwBRJfFcpWiqgBa0RuNCbgYsuRYl2yELWnloikZS65UqQylolGVAlghFWCVyioMtZICIqoqij7fFw2RFCBnqVbKRQGgVswJWBUQUKAyxALAkBc0HlSNqsREqoAKSKBqDCoLKCCSIqGh53Y-54qKCP-SpScCVbHdoBUAKM8TIRGh1oyiAEDWAaJ3_XI6VGEw3njbNh2XCKrN0C7TiIYQtBk2KZWvfvErg3ix697-83eKevv1y5JY1lVTASBQMNbUtYDz7WZLRPF8NmTkmVxExjpfc3KhkZxVUTIb7_3QCwMhCosJQWKSkruLfcmlGbZNvyOy7TAgCDI7550PLNwYf_niSpgRqOZUckLl3dXlPI777c5aSjkF71nFWvPms89TyfOyhC6QMSFYAjgfT599cdf1XY359cvbi-12OpyGob17efM3v_629y2ChJbeXO4b7xRUAIahtYiNd9ZZUDVIBlGKOO8QMZV8Oh37oSNL3rmYay6lirLoGBMAkjGi0jX-eY3_dBqtgVKZRcG7NeZP59G5cF5Gb41IZVHnbQgmrcn6JuVcQYkMKJTCOaeuC6K4xhJCg0jTvG63WxFZltV7Zwmcsao6rxEsAVJKhQyKijGmVO5a__g4x1JjLsen0bVNrTLNqzdBQRWRVVxwu21nREDRWjOezs67yhpT8n0_L7Ftm5_efyqVp2ne77Zc63Eaf3z7yVqz2Wyb4De7jQ9-OU1t64Yu_Jf_-ttXt9cvXuy41scPD29eXv_8zasf__TD3dXFza61RHGNu413jQfVUrHvmmleHg6HfrMVFjS63ey2jX94PL68uWHQnNPdiwtEqrVO07qs6e390-8_3P_dP_wEgx9zfHoaU5Gca2Xu-s3pMIECeWQWEhi2fVpSmtacVjImOMNcLeGmaTvnjTHbvh36BoC992bzm3_PVUSg1HI6ToiIwAbRBCK00xSHTehaF1MFIgCIMce1OMChH9aYc5FcqyF4eJpb30jVofXG2jXqdtNW5aYNXAsZaNQuS25b5xvLpKVW1X_B2yjS85T3puuHNuQ5g_KcMigv40hA26Z7OoxESOimKbnghKuAgsVlXgnNsqzO-XVZ1lwiyzLHvKR-1zaNf__2fS5FLCrqOq9SKqqIKiri8xG5bUqphQUBEBFR03khg4aenQAgVcg76w0hgICxFoBQucQkFUuOLriyLmRtFSZvpFYpBZTFkhZGJLRWSsSSIWZjTOZqnBck7zrT-FrZOQ8iRAZYXTPktJrQ1jW6NjCpqHCB9nInVYrIl7_62ZoSOyTfhiY03qlzrz6_88ZoVdsFchbIMcucC5GMS0ZjEJQN5ZTI2s-_2Mxz_vzVdWG9nxZr0SIO3hgGsOSC__Tw9OVXr9__03dv3rw63j-WZSVLcV6tt_P51F_sl9P56urq-HToL3Y5x4yVRVOK1thd28eUUlmvr6_WlLZdCyx3N7vGOgVIKfn2uf9L-gxy8NZYS4a6LgiLMBMZYwyoAmrjvXUeVQEQFBRgmlMRLVVYVVhVhYxRAAKqqgxGjD3NCyh0XUMEx-Pcbvul5K5pDdLt5W5cUsk1KwMSAxHQec6FoSIcp_X9w-E4x6Zp5zV2fdc4m2M2lnLKCigKhLTEHEIwZJxxKup8ANCYsjWmViaCnApXrSxIyIUTVzIGAUXqulZUMI5UEVDJUAGuqtYaY21a167tBVQKt10Dtbx8dbUbws__7PW41qxyPJ82u912v0lrrSVP53OZa5wW3zfMVQFLKUAqhQ0CVw2bDpCAjPEOAEFRcmYA5YLIqup8E7ZdzVlS1ZKCw7rM6TyB1FhT24Zm14ILu9u7pm03l5em8c3lTQbjuy50rXGmFlFUBqo52-D5mQfVddY5Yz0Qphh923YXW0VUwOPDqdsOXPLpeHLOllQwi0E5PR5FNLEgQ9u38TDnItQ024tNP3TLsqDS5vaq23Xj0xi6zhs5Pp29dWjo7m4Htd7d7S76zfVl99XdxbZtyDWm6NWr3dC1bWP64Opapnkh1cp6eb25uNz96e27UuPlfuiq_82LqyXnj0_zX_3qTVozxXXl8vJya8ncXg77vrm53N3d3sQ5xlisd-zh-w8Pf__dh4fjcn-aEuscV9e3iO7x6SAAT4_Hfmhu9tu-Dedc3n48rkWOp3VeY2hc430IPlee1hxziVwzAyF9OozTnABVFFwTyNrd0LXOLUtyIXw6njNzTHWa1yri2xBCG2POlZcY0VjrTUqlCY0QGEJA9cEbA9ZQaEKuSsYRAgsTmTnGXHRNhYwpXHPlw2ke13nJJReOXI11DHCeY2YmMmrIBXc8rUtJIlpyVbIAeDjNFExVrqrH01xSSWsW5lRkPK3em37oP96f-s12LvHtTx9rTcen85h4mhbhosi7vo8pHT4-NW0T58lZI1xP7x_LzLUUo5BS8U1TckKEvu8Q0ZF1FrdDb5rQdn7XteN5Mqo-WOOb2_12N_iv764uL3Zv7u72l1ftsA2bzfXd7bDfueBFybVhs98-fXrUWhFRACwZaiyS5VLIUqlKhow1vvFSpd3sk0QylmN0FuM8reMZALSu8TzVXJo2-LYHU-PTqR02XAURXGMRjTFmHWcm60Ti6Wy41HVFwP1lbyz98Ifv3373Y5xmg-ZXf_OL_8__4_-1HD7xcn7__tE1xt7sdV7m6bRM47Kmd-_uf_jux48_vqvK8xyZ5f6n97_7h9-3-810GiUXAhBhXrL1RoqYoZFaoYgCQWUg1MyEoksWEC6gVQBYU5GYQQBKBVbIFXIGNUACKlAUhaHwcxwDuP5LmMcaRUSPPEWtoqrKRVMmY5FIuSIA5EoiqoQW9RmSXTM88_9VlRlAEUAVlAsQSRVyBApSonEOQEX1GWUFaFzTkrWc12er97M1DA0SWrfdGuvW8SQ5b168KIVf_OJnp48PzEDemdDGZUIDoe1r1S9_8Rd1PI5Px8ePHwgJyL_52ZeHtx9BqoqK0P6L12lepcr2xQskTMeTCAsXAAEg0zRxntpusE3HORKBErnQcMyVBY0BgDIvhtAYVxW63SUZcj4435DRkkuO0YWwu95ba5rgOefQNFxrzmvoGhEG0bZvpRYEYgUW3u22292u1FJLbru2xvSzb3-2xKXtu2Cplnp7e_3ZZy9_-v6HX__659YZ1PJnP__m6fGMyJ-_efXxp0-fv7i8vBg67wHUoiECY6yIIAGqEhkiY52tzKA6xRIav4wrGKqipYoNtoga1xRhAKi11lItERItMbWb_jitzrePxzMrj-tqHX06nBtvvTW-81JqWhI5M88RnYml9qGdlli4dk1oXFOYu7ZRZu-M835NeVmW_aY3QM4bMlYFqlYyNk4JyMZU-FmCrjhPyXgzrSnl0m7amCsaO8eMSJG5FEbCoW0b758HcDmVT_dPS8yHeY5VisK0LNO0CqgCv9hf1FqcC875i-t9zLEbhsPxwLXs9_0Xn919_ebN4-F4dbnPtWz6wRH96pvPvv3y5devrj89Hr_-7NaAaRvbD55rHcc5puK9T8ynae27vlQW5Yv9RSn18fHYNc04L21wVxc7ZlmmRQinOX9Y0j_-8f3HQ3w8z_N5mc95iZlZwFLJvMZkm1CV26Z_9_jpxeVlG3xa8zA0bd86a4T5-mLHKruhG_pWgbvgVJVFAxnj3vwqpTXNC3qfSun7drjYjMe57UKwQIBMWokSC1liUTRujOV6u1GCJVe0WHJE0a4NTetb7378OPYehyEYRB9CXnNlhiJAZrfvkMyaMiCQNWlNZY2k2vom5SrMRqWKZeGmC36wKZbGBWV5Oq7WmIvrIeaprlWkIiEjuNZgBRWJSwKVrvdKOE-L875rfIprZjLG1LwCS2i7FKOKsLDznlWEGY1hVZGCCAjInH1o0Dqo7JybxjGtCQDJEuec5uV5DmEdAYBtPDyfO5eFyKwxWu9FZR0n76yUqsaAqoAoAdRqFJ0Pqko-aAUTGq6l313UJYJFmaNtApFVZbLGGDLePJtYXduY51PATXfzxRfvP328--bNeo6x5uDczcsX-892X319E1Qs4OEUx5S6vvPeaHl2Ohm0Bghb63LKouKtR8Wmbx6WmFlOc3LWWcXzYVmUUwRT9fTxeD4cd5tLLDVNk_MWDbACKKE1zvu4jNb6-0_3zbYvFblWEJAs6lCqlCpt3267llT70ARnL4cGuBbW07huN621zhqyRKTqrAneadUQAiI944HMM3XMm1q5VMZnfCMgWC8iZF2pZV7zaXoORJmYS2EZ1_z-8Wmz3b__dL8ZBu89GrsCHp4W2_gX1xfjnL77_qfHZe2aLokczyOjP8_rvCYluxZBQnJhPC3kKK-pb1ofHCEgoHGm9b4yT0tsG9-0jTUGCFLKgCCqyxpP01xKsd5Zb0PwiDAtyTZ-WnPM2RIIUawV_kVhA2tMiAgAwbk0R2tM5Vpyvr29ynX94vPPQOtm6B8O5-1-H5mv7m7_9P1PL1--fHo69Zt2Op1jjKbxm5sbDVRTKfNqQKUWtIYLUghkbFUw1mgVBdWK5MwzYxsVkVy42EEB21rrXJmyMcY6A4CQJY9zmVbRKlKr1eHmur24qpmvX75WxNtXn1_d3b5489VSKglhY3f7m5grEmHwotT2nTC4tvFdE2M13lqkZtP1m56axjbt5nJ3-fLKN-58XF5_-bq72VuDtYpxdn-xv7zebTb-dDyO49wGH5xdH-fz-Xw6TfNprqW0Xdvvh3GcPtwfzmNap_Lzb7-qKc1LepqXhqgLbp1i1zsU8-XN5cXlVU76-ouLr3_2gos6oZZks2laH95-fP-4xNu-3V1tfnj7eBrX64utNaYfemuolgoAQ9cUknmKbx-Pa1zPh3lO-TDGbgj9tv0XDI61aUk1l9PpvNu233z--vZyN8_x0-PpYZ7XXNGa43E2zlxf7ueYcq3f_fh-mnMRMd6e5iXFnFl901TW47S-erH3aEpm4-xpXY_jHEtVMqwgogrIrGvOT9PkrBfFtCbrLKuuawbh4MO6JlUEgIenc2Vg5ee1AJEppbBoqXWdc04MgEgmV2na1ljjrfEW56XEUllgjeU0LUSgxoCgKIKzlcvpvD48ToxKxpWiaBynbL0BJRbutq0wgzGbfffh_fvD4SzMw-UuNGY8nmpJMVcBNdandVnXVNalHbpSmBOjMqmQqjOm1hqLBGd94-4_PZ3Oow9hXVKtVQGPh6nkHNrg-_by6ur27jrY9n6cp2rQ25ODTw-HJefMLM_AFnJNN5yn8enj0RDdffP69PHIhZGUS1XmPE8SU47Jt4FLss6ThZoiqJRS13EJXRuatpY8f3ogwJqKIbsuU0nRGa-CBL6UVGvxbRtjVmXjbXd3O_74PeTqg0fvUKmkpGiabrO5vISypHX9x__yu_1Vr6k65xtDy-E4vv-4THNN8O2_-VtrzXz_sE5P58cDQ41rlpQNShPMcp5yXFVZRFTFisg8YX5e8Ck8Yzu1Qq1g0Drm40TeKheQCtZgzooFmIEraAUF4AKVjbOaGFggroColZUr1ArPqBdVqIzOaoogDMqgCmCQBYTVGCgFKpACEmoVBARlqGysA1RQBRVUVDIgggBoDDlHisqirAgGkJBApZCzaB0oSc2ciopaZ0WqVDbWNVfXHGNJpeTSXVxmKda2kjPHnOLq25DmsyJtLvYXL1_bxn_803fzw73ywixFzd3nb9797o-bzWYeRzTUDJua03Scrz-7q6ko6HI4WWuV2YUABkEgdFvftQC6nGYy1vWNbZu0riY4Bqi5EKptG63aXV1ury7OT8ea6-3r11rz_YcHF8LF7fU4jsuyxmnZ7jdpWbt-EK6IWir70O_3-6ZpChdHFhABcLfbrPM6x3ixu3SG5nl8_fUv4nTebndXw_Dnf_3r6fD453_2Ta2FlH_57TctqTH24eHpYttd7Yfbq4shBMLnYBf74BAwpjKOcxNc27WsAApVahXw3nlrnbWKeBiXxCIIZEhEaoVlXbx343nx3lcRMLSkGisfx4nAnMc1hDCPqyNjren6Ji7Ze8fMCgAKzNq3zf3DyTvTtO1u6Kd5IUWuEQUUkYxJKVcQYUCyQ-crM4M8nmdAREtrLqlURSxcRaCqplpTZjUoorFyraqIKRfnnAAYoovdAICo2jZhnFawhMZlrjkLIKXEXddcXu1I6KvP7n786X6a59O0snATuqfDQxdap3B9efHrr1_dP50-fny0zqiqC_78MP7im5df3l5X5THGl1cbS2Qt1VJF9TzOAHCc1iUmQTxPi3fe22es4mMIzZrrfjdsh84QLTG6Jjyd429_-PDjw3hK9bQkRqgC47QgGQadl0RoWMQYQ2gQYTvshm1rCA2h826aFu9s37Xn8_nF7bV3Nq7Ltuua1retbxtPIqb_9jdI1jpbNEul3cWm5rwuZWPdj2_PTWPWxFwBBMdzIkOMUKGM43I6ziyc1kWBfONvdsO4RE9wuW1TFi5sLWZVAvx0nHabLlWx23adUqlFAHzrS2YVGeeZK7ebttu267yKo6bvx2kJriHCZV4IDFkwAuNhqrmgpTRnrVrWkpeyrNEaM3RdXHJrTUol-MBSrSEgs6wrAXVdI1zSujxf-5w1XP_l3VEL11qYRVWtdarqvBNhQidSrSVOtR1a5VrnosiiLLVCKSCsoqAIqloEECSzccYGI6LOE7OAhRqjaRupGbgiF-EiQFJle3dXS37-wrngCV1NBcnwUsAbIsuV0YcUk_GGyHS7rWlsv-lt669fvSxSLl_evv3-8PLLOyFDzl9fb7xFJllZ_3A_XW2HxlAwXhVqZTWowsjc-WDJWKfo3MenKQK9O89gLSpdbd1U5GmOn05L64POoyJ9evth0_laBVGMM9YFEWxfX3EpaRlRxVpDjQ1NX7kG1-Sc-l3PCmpk124tmi9ublJOXeNbZ61Rb8hZg8YIMzNzEkVNSxaAUtha14RgrfHO1loN0fOPMedpjeOS76c1MmQiBlmWKIDe-3lZiHBeVnb-t9-9uz-PUypd19XCwTXnlIvoP__p7W7XBd-8fX_IpWw3jag8PJ186E7TcjwtSypLqcuaVjb_-Ps_heCrCFo6j_PVdkAFYXHGIKL3HgEVMXgrLPMcrTdorBp6eDqDC7nyknJcUq51zQyEwjovCciwqqgY6wGEWYRFEYJzxpq2CTGm0DoykGrddM2Hp-PPfvb5PMfN0FWWaVo2u820LpZMStE7F1MqlftN3277D3_8QMZ6b41Bi1ZVQBAbD4TMomCb7YZzRiDyRgkQEcj4dlMyCwt5AKKaxDQWnSkZaiyh2xAKQq3LWufz-vA0PT3G06FKYcmXF3sR4cKW8Pr22jd9t921TfPm668xOCEjABZpd3nBSIm17dph2BBKqmK8V8KbFy8sas2a1zjsu5LLMqVXL6-Gy-H2xd3Vi5uuaRHN5eWu74bHc_aOyFLX-avbq82mK4WHflO5DrsBoULipUiBWnKKkhGNJfjF16_HVLXiV2_uNpthnUYtK0e9u7jaefubb18Foo_Hkw-25IoipzVB5f31dtNY723XNAbzssb7j5_mJc3T-nB_PB3PwWHTNN7bw3F5-fo6Vz4_nRVQa2283feddbjdD3cvb0g0-PBwXA6n6WGKa6rCCgTD0BoyayzjGs9zQkS15nCc5piLaMx1TjE4n4reDG1cGAjWWk9TEgUFzMwqCgAiEEuplXPOTfBkqIiUmhvvQZEQrDEgcrXfgoAh8t4WrrVK2HaPT6dSZc55WhMzizW1PvPcDBdZY8mplgprLZ9Oi6iwalbhAud5AWdqhfO0PDxOtSqSnE_n85RSlSIFwZ4eTgJEzk5LIhMe7g-naVmnEmNc17JMcbPrtII8X_URl2neX-3TsiLJMo7xdABrsYr1wZiwnCdQrTEv09g4f321udz0__yHP3nXGkuFY9O2SSoAGLLKcjouX3724qdPD-PDGZnnx8lasaClcL_Z7K8v2n57PI-XL64vbq6No-P9cfvyEoFK5nVenPNN35ZxbVpbz7M1Nq2LVqxc0JpSirVkjHPOW-u8t4ZMLgKGfN9qYWfbKpUMChdjTU0JVKWosZSfTsiVCAGQXHBDLylyqbWU5XzOKYXQ_vxv_4fj259KzvPjx5rSfDxUQ8a6qzcvnr7_3dt_-v5Xf_PXF_srAbJNU0quJUlhZonLCiKgoiwWgddo4oLGg3eKCM-TOBEQhgqqFZlQ9TnUCtbAshCrRraEmiuKgggW9d7XHBEA6orkEBGUqTKKoqqyEJD3vk6zQSTXPCt0jIqKqgqBQVaDqipEaIyHUogRReiZIqoKikTGkCo_Y6ARiFABQFDVBCMpAQMZb6yVUpSrghoiAFWu5L0JjaTKuVjvu_3FeDgY09y--mwZDyqQ54m8BZGXX_ys2-6Z7MMf_yTzOUBR1GXRr_71X54_fczzmuPY7zfOB9v65Tx_9vWfqYhv-1JzibnrW9d4Fg4hoHFgrO-a-ekAwr5rbduu44qEpgl1Xq0zUFUNUGic6dZlCm3njAEtJWUy5osvPiuFyxr3F5ua8nSaLl9cxfNpXRap5dXrLxEkBFMLH-_vr15cYZVn7oiyxiXutoMx2IYQcxyGrrPkjMnr-h_-_b-xKteXu03bcqmvb6_ePT4a1KvL7mK33fVNsNQ4B6IibIxRhXlNQx9UiKyJa06prKmIqrXWkAHRVCWxIJllTmtMRXFZ1zHlnJOxtlZFUEUa51UIBNGQMa1vvKkq1lkS3XYOkbyzWsU6g4hoaElVCY21xppc65rKrmtyqd66KmytTZVTLobMbtflWFKqrHCcVlRMSqWKs0YAUmJGIKuHcRXFcVq4CiO-GNoMWFgUSEGNtRbp6TQNTRjnRRRjkQywFg6hKcyGcDv01lAgG4Jd5sqi3aY7Ho7Tsuw2Q8mxcY5TyqW-_enj9bavqM7ZV6-u_-pnn__Z569r4YdPp89fX1pnUdg6J1xjTM96osyABGvmtu1jzuO0jNM8bLbDMMzz-NndNSL-6cef5ljOc_rp0-HTuH54OM1V5jWvS0lrYgFBSLlWFmstiALC9e0u5zKERhlQZLtpp3HyxqHWy23XNj4QKUvXhE3f1lRDIGtQajbNl78Rxb7ZoJdgHAov52jI6DNIXNW2thax1hAhCKZU1iUelwURurZbY7ZIqDDNhVmMsd7YzFVFUmZvbS6lDeGq72MW4jqv0RDlzKkWMMhZbGNFa55PKSa2LsdcS2q6Ni_LMi5t19YsmlPfBuZigxcVFZUqBqmUXFKxzuackcy4rM75yrJOqwvN6TQqaynpPB6JSFVBCA0ZIhY1loJziiKV85KMtSUl79vlfJCcWTSmSMZZ7wDZeFcJrbfI0viOU5KYSpWyJq1sgzUhiPC_eDqBQAlQlNmHRslILQCkFQGrVGERQfRNn-eVRcgYIoqJgchtW7ImnUYFMr2xzhkVJZQK0-F08eLShbbd9JvNcJqXL3_zxdBt4mE2tr642jZkcszi3btjHHrfOmcsoqEqbABLZRGx6ExjEFTQfJoWswtT0Y-HxVoafHg6rtnU-8N0s3F93232w_f__L3WJIporCDFVJvbHSNVrbLMvK4x1cvPX5yf5v2Lq9PTE4pBo-3Qng9r39qhb9FzZ1RqllKf-1vOuzXlJoS28SxiyRCZ0DRd1yoCcDUGU2UAsM4L4rTGaUrVhqkKOHeMObO-fX9_fzjNpVhHtTKAhraZWd4_TuOyTFmDs7fXV2tOy3n9f__n__7Vm7sm-Iur_T_87u3-YpNrBbSRpWQZUyJjq2IWcEN7fzjtry5ENNfqmsY79_Jqr7VW0cxynFbfBCA6HKZh0xZW691pWk7TfDjHOZYCmFkq1zXloWvGXKoABKNk1lyextU4p8olCxkQ0ad1GYIDxVxraAMacM4NfbtM8-u7KwAcQlBEFGibJk-z9fT44dEIOGuBNed6_-ERjLHBW0fnpzNaW9ZkXIMG2-sNqlEg14b56WDahoxjxfZmz1XReAG1TYsIZN14nikYJAPWOd_6vlUtKoiA7fWVAlrf5CVBZZ6X-en48NOH8-OTITwcHlOpamCcxs6HdVk0mKHfXO4vd7ut8c51vTM2n-eh66w3P_vmZ00XWmosyvXF3lp3ebF98eLy5nIzdB2vmVO9GPr7d_cf330CQDVmv9u8uL7kUq5vL5yl0-EkqZ6np6_evJqnZZ3W_dXlxcXw8u5qfJxub3YWww9v3724uv7Pf_-7__hv_tXLy83h4enweGxb33njDP7hu4e_-ObF5y-6jvyw30kpWmpK65jW7ba7eXHlEDZDR9bOSyKkaV26LuQad_tNv22-_PZ1jTHFIqpkqOuazb61YLyzzpA6SKl676_2m1plzul4XsZYYimp1JyLqjrr53mtVbjoOaXdtrfOxZiCMQA4jfNpiptts-lDjmVa4of785JyVii1xsSKpmksKixLJmOKchUV1OfqZBuCIwresoAavNgOx3ExxqHBwlqLNq3LKcWUlasi1MqZCxChN8dxadoGDdSYFaEUYUYfTGUepzjHRN4_3J9z4XldBCCVqgQMdJjWvu-58rLmP3z447a7UJCcmQXGw7GUfDl04zKTIVFYpjlO0Qbv238B8iLJvEQi22w2av3m-kWtRQSnp4lz7DZdyandbXwbLNkxZnVut90f7x-dM-i6VGXb715cXk-Hpw9vHwHpNMUYF-MQDQHA4XAap_jizau26XLMT_dHH0Kt6ft__tEay6DzYXI-2KElkf7SszJnNTYQEZJoTCK5aSynQtav05TyUlJs2kDGNdd71zfVgAXFqmmZQIQTp7goK7OGpkGp1pqaChqTUyaDRFimyTx3vuc1rwuRVY_Hh3vjatt1QN55v7l70V1cieCnH975YFHrDz_84ccffqhS_LY5vf1RhUPTGAPCTAYkRussIUrKCOjaVpRAKj7P10FgPQMSGIXIPvQ8HkERUjXIIIqZgSsSGmskLVQyKCgXVIBqCMgaAmZkts5prWSt804KU6kAbEpCVSiMiIgEoMCFyHCpRGi8I1GsFQVIAUFVGFSRDAKpVhBAQimMziGA5AJVyRlQQEVDhFxV5TlbZbxFVWENw8aYUHIkMr71cZp91_fDJqXIKa_T1GyHyqXfXQ7bS2Ph-O7D8vFTQ2xDiFm3r-5kWZfTMecSnF3jysLXb74aNtsKzDkLiKTY7Yc0LqBMxmVm69vQNxwzF1bFi7sXolyyOGfQGllWg8AsIrq_fVFyXOf16vbGGtTCx8ejta5tnTEmx_z1N199enf_2S_eLKfx4f298eSsrTWHpn11--JwfIoxe09Nu1EV13hnvTVauH7x-VdrWnYXF0PXcoq3N1dd2_706cPLq6vttr252F7t-sHb68t9sPx4Gr_-7HVc4tD44MgQlVSQSESqSNeHnFhEkLSwlspIaIlUdEm5qMYqRZiFrXNjLFNKhBRjFn22yBhrzZIKED0-jQqQitxuwsfjYgFd51_t-1gk51JyBqA1ZTTmMM2IimhU8TjOImyDd40_nI5d0-xDOK-plpIK3-yHNeVa-PE4FQY25qf70TUm5yyKLpjzlMY1s8CcknV-WmZieFzyOM8KaAgRjYqkVEBxjjlXAbTndT2Mi990x8P5eJqFKwI9Po3e0uNxWmoGUlVoQye1ksjT_eGv_vKXr26uri624zQ1XVfW1Tftrm_-_PM7ArAGt7sOETlW661yzSnnwqlwZTiNCxOxQmVJa0bAJjREAMivbm_6xk1r_vvf_vjqzc3__-_-aHbt7_74fi46LYVcz5Ub4wVhHtdcsgs2WIuqoXFDE5bIweE4rZuuScw-eOutQQKFxrkQbE61bbz3jllSqct5_ng4Gfv6VwDEtQigiq5LQm-d9wrVg5mWmblY75m15JwykwUX7HmcXry4un84NJZsMMGbJWZrqRTJkWNlY0xRFQEk0-2253EumZd1zpysN2pEAY11UrMfGrS0nOcSGaD2fV8rL-exbXtV3XS98Q4sTYexaZp1Xpx1qmrApJLGw9x2HTkAwrgkZ4OACLMo5pwVwTV2Pp_bvl1PC1kDFtVIWlYkAhZmKaXWkpu-0Vq5Pi8dBRHJqG9aBOEcaypgCIwAK4LWFIEFnXXBoDOmsWnNiIYM1ZTJWgBTKzvvlAUUw2VX1vRs8AYyYC05B2B814mI1IpEIOI2GxVkxBzX0A-krIK2bcQ8Y8Sh7cKaqx-2Sfjln10TOGz95e2O4_p3Pz39xVcvUy19E-zOT7F6a1p0g3da5cfpyAJiQJS9cyvX0zmec7KNPcx5LvWUGIxxnRuX3O_cb98fvri9btCcx3UYmvHhqe2a8Zz3r_ZofHtxsebcX21xLaC62WxKKbVou9sQGWX1jSdvAFWR9peb02kihOBd773j2rW-aUMuLAYJlIxJqTjnAcSQQUIW_fA0EpECqTWp1CxwTuW4xqXiaUmfng4_3T-umdXaeZmZaxOcczYWeZzyh8eDGvp4mH798y_GczSK58Tvnu5vLi_WtXx8PItIrPn24jpVZtXzGhl0TOm4JLb2cF6Md6Xw0zx3_TB0PRLl_Pws64eHAyv44IV12PZCeP94TDmroSVWMmaOlVWPp9WHhoy5Py0Px_Fi6Jaipcq0xE3fzfNKZESh8_7xOF1tOyKjorkwiBhjALEmDt573yAgV5mXGQ0yy1py2zU_vX1nm7Ad-j999y7m0m76_WdXhw_HeV2brq8qSibFBMYqYzNsbAhcqwi2QweEXJWjmMaFpiuVTfApZd8GVXHO1rVQY1FYcmmHJgyhiOSYWIHII1kf2tA03jWGCFhqXKen43J6Oj8cLWEITap5fFra3jtjEdE3PqfcWrvbbalxFHoX_O12d31zObTDYVmEYLPpg3Nt465228vr_cXVZS3ShObzL1_2F20fWosQSG9eXmcuZa7nMX792R1X3xgKm_by5X6ZlvMxbVr3Vz9_9ek8v3v3yUl5eDpc7_vNzt_07Zrj9W7zxee3b-8f__IvvvrmIvzqiwuJcrXbPs0TejuOS991vglxSb2xwDKe5nWNDFLWHLrQt50CiohDQpW-bfqmub3abpyzBspaRcQH33ZhiaXrg3ekRdeYfnp_rwpzyvv9XlQQYb_bgEJOiVVrLUvMNvhSswP03qho37VkbFznxjdZ4OPj0Vhq-66xblxSKkyGUGVNVRmMNX3jWteQorEO8flPBdDKtWsaRHDWlcI5JiQjoCWWrm2GEEITyLg1F1RUxJwiIokqARWFzCxVY0yXbXuOJbThPK0p5ZhSKXm7vxQAZ0xVXXKUAt6Ytm1K5X2351qk6poSgnS75nQ6P94f53kVoOPTue0CaC1FSi0htMu8MgsLN00jUomM5MJSQ3DdttnsWubs22aZl-m89JcbFZSioWubEGKtHx-Pyuw9OmNME4bLjfOGhafzFGPKqeY1zvMsYqDyuz-9PZ_Ou4v9zc0uWNs05t_97S-Ph4VZcinnp_PF9WXJrALGGFUUgTjW0G5yXmqqayzNpnNd77umCUPJa025jKvzAa1b50SIUDh0rfGWjGUVBQGBmCJ5hwJoWBSsNcQFqqgCGme7xiKl-VFLBQUid_z0FIau218D-dPjo65rtxtOD8eSpGvbskZUHt9_QjKoYIxxYDhlNCTr5Lte0fC6mCrkLAtrTEiorFAK1AJiQBiqcF0hF9BnTRNrZgQAFBEBEU0JAVFRhbWydaSliEQVQXhm5auokgtQCpSCzPqsa1c1zgII5wIAgEqEKoBEyoyAqCpanhmgxllAEgU0AKwUrBSmQLJmVLHOAxmt1VqHz7Vg40CEALQKGevaAYBqjsZ60ZqWWcRcvnnDSzTe5XFGA2EYpMjrr74-nU-nn36s00hcHIkfLobrm93N1f0P70rOtnHkfEnp1ZffNJv2fHhKaYrTCMik2A7t-OnYX-zWJVrvQAkY07yQte1uI0XKmo1BrBVSUREANV27vb5p-4GQ-u3GGrPbXXKtFxfb3fXF6eEwz-vucn84HUEAwUzj2Tu_v9rfvnxVS7bGTeukwF3XMatF2Oy3vgnHx0cXfO_D4fT48tUrYynF-Pr2xd2L3cu7Wwtye30RPFzttk9PT1LixW7fN-1nn90RQh_Cpg8WDRmjhMbYJWVCCsE_HefG-5ir9RYAiYgQp2VRRDL2vKQlJSIzrzlWbpyJJRFhrjXF1PVNyfV0GvtNAGPunw6b_cCK7z88dUMnbELwayn3D8eu9Sw4zUkNfffpsPUBDU3TgkSEIKJD2xqg1ltj6N3TLMLMkIrmWlmp79sp5iVV1xKASpVcNTNMa66sZGypHOPqnUelT8fTru_bro1LMsZZpO3QiOI4zsZ7QRREt_U55tM5LsvahFYBD_OyxjSnFLzdXe0t2WmZyrJYo7_--TcXm651_k8_vq0icVx-_PFdzOnbL1-9urywYJVEuBAAAIrWWniNGY3NVcZ1IXLjNPumOU3zcZrePzz6YFDq5eUFAS1L-sN390SYAFxnf_unj8dxibmCsZwTZ2HWKWVF7DbNpnXrnDabjQLGZb0cmibYvrG5cGgCqHZtiGvcbXtQ-O6nh5v9QMaUUq015yVX1mlezP7P_7X1jkjyuuSY1BODllTIOCTYbXsTXKmc12wNqnKsEqzbbYfz00RIIjVVGXa7wzgxiyH7et9PuX46nMZpaTqnBlDpPE7ek2-8b5ySEhq0xjhDRHFdAQkARAoKKwKElgyVVFjMdts0XVsSWwN5XYE1TYsqllK4ctt2xsDp4ZhS9I0_nMe-bduNs-TOT2O_77TWdY7WWS6MhmoRCgYFOUcWFa7GOyKDqMoiudSSVRUBgYBzRWOstyVnVENKxOysyWsy3tpdV2JRoVrZemPRWCIRYQUTPIBKLU3fAwAXViBhAFQ1TskYtAhaKxvfEInEVCpj603wtmkIpS6zc5ZLZgQwWFNW4c3NZYEarje58Hku24vheFycobZt_q__489Pc7bFkLPLUt4_xbuXfWctPJvdLLxLS-N85do7nwWqMpMRogx4rvK0Jt-4WMA5ApC45KZz27aZUs5rBi4k5u4XL0vWWKrfbmIs7dCeP9zrmm9eXClgzoKOur6fxzmncvXmKo6ZBIw3ztE0LftN31i7aQPXEoJNRe6P08d5HdqmsCChd7awANJSxTojgGhdEp7m5fv70yFGsW7K9f58qoBo3XlZYs0qfH-cfvb5K6iChH_3ux9_-_373X6bGP7si89yKbXK__M__cOr19d3377-w48PTw_n-9MogMbbotw1_u_--a0xVqzhYKeYPz6eFDUrDH3nvWcuKHo6TXMuxjofGjCmbcKSMxJVzlzkf_nnt9u29X07Lun794_bm8uneVlZHg_rcY3jnM9rRKLddjsuZVrXrm-73p-OqwiJgrVkLeQqzGotVeY4Z-usqhISq75__-nxvKw5n5eyrOn-8Xxxfd30jfEuseyvLgCJFeJSmk2fY7RtlyuTJUS0hGmJtbANtul7AURC17bGUc2qpJvLq_k8-s7PhzMYa23jt4PrOhBFoBxrEaHQPPN81mkFAGNdTolZjbM-NMIaht4YM1xutMp0OpW1oPB6nh_fP8U0n4-H5TgZR2taYy3TvM5TrMHcn5_e_vB-juOH9z89fTwkqL_74cEPTlqbQb77xz_NNY5rfLw__fDjhw_v7396ez8uy-OnKS_r3c3l5qLbbkLXN4bo4cPTpuuc98a4Hz8-5ak4R5-9efH0dHrz2auPP7z_8ssXIbh967jmf_WbX3788f03b65f7Degsh86JKqi26EPwV1dbq92XRc8CChov2m0qjEm53R9tXHGOIDeU5wzc22HBhVyyjFmAG2bllkIKa7VGAQEZ23N1VjbtKEyi0rfNM46zdkZs-l7rcUTouB_-Ne_7JAu-uFmv7m7vjqMY6m5bZrQhHcPR0CD1i5L7K1L_7vAYVnSmrJ1dpxXRAIVFUGknHPNWQWWlHZDZ4yvtczzMs4LgFmWFQ2iQi5VjVUQY2hoWu-w8-2SiyKqQGh9601KtRRGkIiYVbhW11KOeZmXynJel5gqGtkMtkTSWFh4WWNhFakK0m26krNx5Bo7neZai1SN02wDCdf91T7FUmJc58l5W6Uuh7nfdH1oal4Z2Hm3zosW7jdhPE_zsjJov9-tpzNaX2suooLQ9t3V9VXjjVR-PI7H81xrKTHPcY3zuqTS9F3oXH-5Q63kiGtpu25Z4jgtwbq2bcszP6ZrW_LAWHM0ZLbXe63qWgsCbeeM5357gQZJZHqaw9AK13E8hbZzbbDOCAsYbJqeghku99NhQpDnZIuwKKkLTegbYeaCvmmMgXo-mxqZhZzlWtJ5NiZwLZKL8VaFWXU5P-ZpImRAjetiLYHmpmmlSl4jWTBkSlzQAiiqFKgFFV3oVKqsK6liMCwVRJEAuEDJwIDWgAEoFYlgmYBESyWDmlkrg7IhRKlaKwIqKiA8p5agJDBEQFKZEPUZfY8AuRCicFVAJaOAAKq1AhoFJSJEUBEAUmYwhms2CMoKiIpAzwbsWkAQg9VUKTheC1myzitXEJVSSBUQyRgAAUBjyQ0bG0KNCUTJoorYtum3eyIcHw5cy3BzLaUq6N3n39gAj-_ep2nm5WQBhaxtt9aZMp2ZZRnPod8Qma9-9mebbffp_cPjj2-J6_HtewMkueZYrMXCIgrd5YWUzDmCtd3V1hCl8-iC4zWVNRkV1_haeLi9absNIh0fn6xDBBzHszHkm3ZZVxEZNgMBcqmff_NmmabT6fT61W3b9U_3DyH4YdPfP9zf3tyWlF59dkeK1tpSaj9svLXA8ubVq23XlBz_8i9-db1t799_urm72vft5ba_3G44x48fD3Plbef7vt00Xrh6a3vvUiqAaMimWkVlGJq0sqIiIjOTMcbSGpOIApG39jzH47Ig0bzE0DYgKMyV4Yvr_XHJzjqyxpFdYj5OqzH2D-8eWuOSyDQtvg3Dpo0padUmeGEwzrrGz2ntjFMkJXM6ry6Y1jsWURVDYBTGpTBqKqVWKbUAGlap5M_jUlVyrDlVBihZYs5rLORtLDXn6l2wRCmX1ntWXdbU-JBTnXJ6PE4plbcPTwh2zrlt_PFx_PHtkwKbzhbWpZTpPH_88LDmQkjTkmLJn929uLu8ZOYvPr_bDp2ofvx4__Lzl1Nc26YJzv3Pf_s3HiHHJCD3T2eDJpaoiuO0NH1fReac2q7nKgwAaJm5seHV7dX1xc6B6ZqgpI-PZ_Bmf3vxp-8-LgDv3h_PU2y79uHT0bqg-i_mKutdyik4v-navvXMxVgBhcN5FqBU6sPDMQSfYm6cQ8R1jZuL9uPT3HfOeo8Eh_NsHJYqpv_mL0zwdY6ub1VZU7WExmJOmQtY60T4eBwJNM6rcyGuadu1CNj0IRZeloTGg1YFVYWuC1OBKS4EcLMbzudlHaOCeGsdgSNTlmiQrAV0Jj1vCQmst-N5cm1DSHFOxiKobjbttu8kFedM0xhj3Dgv5IxrmjUlBAREKZmsM4Gss877TdvkNUuSVNIwDE8Px6ubfckFjQBhZVYh5wzXKqVY70uqFiwhVJaaCjkHlW0b8pJURRWRSEr1rlOo9fygVXg9u74DQ_GckNR4q4bQGgQpRcDYZ5O1lILWWgfKioQggAZqyiyVjLHGpGkyNpBvgLCmaJCArN_uRBVY8jQZ52phMMY2QSpbQ2mNatzp45Pr2zjFeVpDQ33X77bDMst__cPvv_3qBZO5eTW8v1-YpHcWWAiNIFahwgyijfU514S0VFYkdpBYhRQJVWnfkGPuQsOxnueCFrrG_PCHh3DR2H77NOY3X9x9Op2IaP9qP_30XpclpcjKpm3JBxs81AKMvgtt61CQFKyj5bTst52w9sETIKCKSkrypw8PV7ttYkixWAvrkk7T0vWNIWsMceX_9U8_PS3xPC8r6267-d0P7wuLGodkdkMrRNdXuz9-9_TLL-_yWqec_uvv_qTg-svrwxRtcE8P4-N5WebZ9e3Hd6fvvvvYdMG1vgoapPN5Tau-uz9stu137w9E9nFcKnPJ3IT2YZodml3bPZ3nq91-iXFc4mborHNMBICncbHeVoBdF5aVPz1OwYY_vn1UlQLwtMTDvHx8PId--3g4vL65fDjF-8fHEHzfND98eLLOLUs2SDGVNeXCGHOWKrmwdXY8z13X1Mq51KfDeTM0vmkIIcZCBJcXF1Xh_fv7tgkAmHI5PE22tfNpQbQ5Z2NsLukZU8eqoQvONyIahk4QUs7ddq8gZNuUysXNdbffxIU__8UXXBXIOu-5CCFia0sl1wZWSLmEoWnaptZsrHFdAANxGnPJpCS1Nr6bTtP2Yvfiiy9qXlWKprlMc14mLUVyWmI-PxwJC6_z-jiOn55kHWOcgMV4q6JPHx6f3j0up_nv_5ffaS3z43h-OEItm74Zz-eaa9f1__rff9MP7flxevvjh8ubi5d3F8uUri8uXetFqhggztPptG3aL3_24uc__9LXZBwcD8eby-Hrz998_PjUNv6Lu91t31zsNqBQSj3N87yWNa7Cuhn6mvOuacGYcZqddcaZmlPXhb5plPl6t90O3aZv99seKzzrSddY2i4E6yrLfrexlpRZBVW4adtpWbz3z97KrmuUiyXq--7Ny-u-axHhNz__3FbunRnaAAgg8PE4Pj8JkSVztYbGeQYyEQSkFuZSuFawhkoujEAEMZXEutaacxGWZ2e2b5wBnuccczGGBKEoPncGnDWsiqCA6AhKqmQIkFjAIIHqspRaeFyjdV4q5FQI8Xhcci7Wmv-Np__qtnVJ0vOwiEj3uWmX2-Z4U1VdbUBCaFASRZCgQFLSwJ0u9B91L11IVxocEkQMCWjCdHe1qao-5-yzzXJzzs-liwhdrIJ-wXTjy5mZ8b7PI8zgrEFIK49TBcOlFgSsAttty8LLWpAM51KykNrCrAgxJxEGlhhTnFcfPAGokiGrXLe7bYnLPI9rKqHvDRq02Az9ZZoPt7c2WBBMafHDJi5LLKWsq7VeEVNOCNg0Q15qTdVZUjQ1RiQEVRXJuY6fnsbzVGrtNn0pGVCl8jwvX39zWxb2ZDZdG7zbDJ3zPgQvICz69HAJbbCIzGKahtAcr19jUK5KIE3X5Zy0KqIBVCkwnU5EloDbYVM5I2KcM3pDZMNhz-tac0UV4FLnkVjAeQydFHYgqKAim5sb5lJj6ne91IoowFVBUPT45d369MyJ65ra_bAuUWqxoa01OaSXQH6J0fpArYvzBJWNcSrEzIAAlaFWSAVEAA0SwJT-IPcFBWCtQoqgCsKN7aSsUAFElRUECIisefFzERoVRUQRQbJkjcZE-IIZIxS1jYdaCRRFydBL_gcJ8eVkgILCBo2KAIACqsLLoACETG95qWQNslDwkFm4vHQb0CAZI_wCY0N0LVnHL5-IVEtVNKHZOO9r5rwuYBUN5Xk-3r0x1j7--I5zSudps23Iu3C8Xqfz7vr16fHTOi9333z5_O7hz_7JP651mcbx4cePjYP0dB6O2xJXAEPOVBEG2n_-aj2NnCsg2bblGLFUEFbmkqI1qMCKaprWmib0w3y5dLuBEGvVfrOpKQJoTCsZN18m3wRCLaVOl-l4dXx-OnUhCFdnqWkDizgi48wfffPVssa4rJvdhvOSUr66vXYoSDg4-93Xr4fGf_Xm1TC0wRipKThTc74-7OKcbm6PfePO48yCNSeyiKqboUEkRLKIoWnH8-Qan1JWxLXWZUnjkp23ZMAY-unnJx8cg6ZSYq5g4P2n82HbXXKJMQGgb_zHD4_bvssKACAAxpiPz2cfnG-a5TJbIiCozKgghi7n-Txn3_pUZC0lV04xzYUF1Dva9ltDppTqG58Kk3Ol1mXNtmnvH05amUV2w6Bgx5iHrsmllsKCCIg-OPJ2XmIu6q15OM3bXU8Gn8flMi1oSY0tXEvWy9OYY3malss0u6Y5n5aisl7yeD41XWvJbA_Dusb_6r_4ozitcV6-_OI1Vz5fxr_97Y--a5xrnp5PoXW__ObLV_ut5BRjflEXLXOslXMuL_zaWAoZf5mWp8ukSkhUStkNQyl52PTKzApzLOJcLeX-4fx4Wf7qNz9c5pxF5jGLoW3oxmWJMQOhVb27Omw33gKAwvk8vqQSACBnLlwPh21MsSRZ13XoOuvM0DRcpe87Vvj54XmJWUSXJZrw5he8Vo45r4kIu82OpRpnSRS4OILzeWyGphb57rvreU7W2rhmcIYMiWDXDzWlNCdRdN5qkXmaT8vaBOe8E1DfBGtMqWVa4ktjY13TLvjeuXGtrCIsRADO1SSoAFwoZ2vtbjNUgT__5vvTkkhxHhdAqinWUlOuw3YQLpxS3_WqEJfEmY0j7xskB2SkFBtcWqOxTli5cvAhL9FYAAYVLSkZ68mSb4gzl1wQQUoxhowyqIpU6xHBlrQYVdNsFJ3dbJDQWocGayxQhRB5zTmKa4LbtZwLBS8KNeWaIueyjLNvgyqQtQDI82ybjisLGjSEaIgUBGrKYh0jkDFSqrNWcjHbBi0a58A2IEDOWuf2v7grsYS2ZQN917fBplQ_u73y1qfCj5d0GWci2xiwZNZcBRmJjHVP6-qc8Y1_GnNCeY6V0ETQUmRZk1W0hFLZ-zClTJaEYdP6w2e79rj_6d2n7dV-Xefz49QdNqilnqayRI5JFDD4dnvMRYy1eUrXr_pPPz6_evuGpWiVq6utD348Tdtt27a2lGqcj4DnOVcUsja8QIgNzWtp2yACYN3DEn97f1pFb2-Pf_k3Pz6NcxJeSl5rXQuPUsLgkfWbN4e-axH1__YXf1UQYL_vN21JKc1ZEX789Hy8PhaoD8_zp6fzZ1_cKehSpA2-75rf_fRx2G0-nM4uuKWU8xjJUmP9kvLv3z0473dDK6inaTJkc60CNC3Fte79p8fHOV0yz7HeT5MLnsDEqn__08N2vz8t8S_-6u9L1X6_-_nx8Xh1TJV--vkTs7z-5vr3Pz7mmMlYF4wqF1XwtopC5XUtzjsFDW3DIiLym3_44ep4NE14_-6hsIgKVwGUmusaa8zl-WmsAq5vlznlmLVKZUESYw2RictqnSVrci45c2ibtu9ZkDkjEdGLiABKlevXd4DYNj2wqDXtpuneXisTGtBcEdzweo-Z13FW0GF_WMcFgFIqqNhvBhGYp8l514TmdP_p6d37vGRSe3z7qun688Ml9MEYqkukStZbUuAqPoTQ9af3pd90Usvju1PX-d6blFNe4uuvbl99ddM2PqcUoxiyx1f9p3Oe72eDEoI5n-fxsnrfDp0_bkIcl_HxySGlUmJMP_18-u_-y-821v35r775zV_-cNh0h6G7uhreHjdv73YBsTXGWLNrnSH8-5-fDPJmt7FcHWHMcTd0ofEg3Fg7NGHXt51zTTC3h32tuXOWhddlMZbQoPcOBLyloe-5iMgfyu4pRWtpaD2zBAIDUNe4G_q3dzctoTPwxd3huGkbZ7rgOZWY8zjPaS2u9YbQGhtTXdeYS0mFlej--Txe1q4PqjCnsm39wrymBEC-8VxqVRn6xlljnfHOxzWBwXFOoliFk0hhrqrLslrjCGhdYyxw_3AWNWOMxhkV0D_YOZUMueDWeQUAAa7MS1rjnHfbRpFirC9BIxWexnWt9ek051znnJm5VknLSoSsIspkCJH67c5aV2tN5wtXTesKqhahFCainNPx6jouU5b884ePpf5B4ICKKRdj0IWuFJYcQ-MA0YUmpXS4vk5xmS_TOJ2HtiWjmlcpGQleKpgGIZ_OmuZ4mUpmQOo2Td85rRKCb2xjkKDCh4-fHp-fybm26a03d1dHv-kwmGC8pGR8yPNFDDzeP25vDwTYdL1BxCQGxBhBRFSUwpBqWVZD1jjXH67RuaYJkArPK-TEOUNO1pJRVWPJt4QAyogGazXB1cwmWEsglUspOWZZcy2iiDVXZFYBFxwEw6mgMCICVwQUQUFWYeu9ijIXFCRrRFm5IqkBhSpGEUBBGECwFgOoa0YSsh4VUAVyIQBlRq4oCMovbVzyBmpFUVRUBTJOhI011LoyrQaNqqiyqpJ92T-8lN0AiV6ig8KsRQgJEbVUFBZ8mSCAsVZfDgFC6K3kis6gICKgVACVUl_0lyJinENE27dkrArXkrmya9rQ9ca60Pc1xrwmVXbeqdLNV19ff3794Xfv4niRlKw35H1WQB98Y9O6lFL7Yds2m-9-9e2rN_u_-tf_4ae__f2mt3k8c-Vm6DE44xsAFUIAQ2hKzITYbId4Htsu1JzLmoxBEK2lAKJtOmuadtioCquAkrG2xBW45FxK5a9-9Qsp9Xi1a0Mw1jBz14WrmwMAxHW9urrp-86Qbvd7Y-j6sJuXRXJyhoTL7e3128_etBZ-8fUXn7-9OxX5-tX10PXWaNcEUt324Wo3bDfdeZqvDxtC8_7DkxIObQeoqNw5pwpSqwIoQEwFiJzzIiqITddexphS9N5uNn0uvBZWQ0vMqlCZS5brqyFmnuaVAGOpBBrnzIhTjJc5gqHLuF7GpbJIJSJoglFmFWAFFRDFouIGG1fJlcc5MoqxSADGmHGcq4ptbIylCmxvtuuUisqaiiKmmHKVKOayzKmW8yUWFkXKhckQl3x-vgijirjGW4O18v3z-O7h3jvLQPO8VlbmfHXYrqU-nS7DcT8tI1ofxzleltB44Wqa5v7-6dfff_mbv_nBgCmIfet_-8O7-4fnCkRIz5dpHdei5Z_8-hed90MXjEFhjqmsS1aRNeXDYff0NCHZ-6fnaU3O-SzClZc1zuu0aRpmBSBQvX8-jc-XAvzhNN1flufLMo4rWVsrCGJKaVxWcBAsBovOOmDtevd4OqcSDdlxXoJvrLfe2zQnBTQeuSqQEdBxzQrQePvXf_ORDPld_1d_88NlXM3mj_7M9ZtaGVtnGpPWFcjEmJBMSSnGRa3Ja7HBjJcS5xWdUUOV67KkdVnzulrnu773TTNPI6ha76AUg1BSrZWNwW7TIQCTcq0xVTABuvC4THFKsS5kzHReu6E3FjgxpwTWgDO5llg1dE2uZb8dSk5t602wKcu3r69Oj5OyjNNUKlvjNsNWlBEplyQojXe1lLbr1nl21hoCEMEKirDddyVWUHHeGjJrTCJSUjaEqkxkoLL1AVW5iIqSQSSstWitOVcEdMHXXAEtGMOF0SPZ4Lc9EtZYmIUFyHoDalFBxBpUqWBdYW7aNi8LIBrvKxjXdWmcu82OY8LGofPNYY-oZY1W2Da-rBHAQNtQ3wqqNQgM6Pz21VUuJefUbBwFA2C22-56E07jQsaYxj6el-NhIMGqmKtUNSYYUHrKBclEQUGaq6oB1HpOZc0JlLAxY8yVNKNc1nToW0OwGTqxmFkLFwWuUm0XSiyX959CcFKr9baydFc3ooJEYbCqgizMsj3uSs5S5bAf0rqsqZCh1pt5KX_989M4rU_P883ba2Apa_35eZpr9l3z_Lx8vCy_ff9psxkOh804LkBmyqt6Q97MqbBqTnmeI6JpyRkwAho2_nGKDO5v_vr3aFBURZSB_vb3P19q-vR0fp6Wq9v97_7hfTf0QBhTiZm7NjyO6-NlOqXYbrp1jdf7q7_76X0f_DzFKrXb9DVJVng6TQzUD0Ms8sOHBxuaaSlA_i_-w--bLqxS58zV0uM6__7dB-dt5mpccxpjPwyXdX0a1_E0zmv-29_-9OVndx9OF-MMGjPHwko5Fk4VEC8xO2dVARTWlIeuTyxobMm5MHvnuErOJRX-8HACTwI0L6txruQMoDUX17UKdnO8Yuarz26BjKiG4JsmMKuS2hBegM13b-6a0JChZujivKCxfR_aIShR2w-m4Ga32726Ce2267rd1bGKNt02Jznc3nXbjbH27qsvjq_ehs3g2v7qzd1wvELS8-nc7XbH13c3X7ySWtZl8Z1fL9H6phv67fdfu8Gvz8uw64ia3WdXwfrj611lKUmtc-BbYbWND90wx_XyeEHBJpiub-JFNs5aB49P4-F6pyB3b45fvL2FVHNc37y9_e3fP-6v933XqHAI-vGHh3_0y28twvfffH6KsevbvjWvtm2HpvHmJZWwxnqa1t2uP1ztS8rfffEqzqtIJYNt470zwKVpnUNpgt10jTdojLHBVJZlyS8b7qH3IYSuac5PYymZS_ns7ZWU0jbh6fHSN-H2uA_WWIKvXl_fHjfHPuyHfjs0FqAyO29ZZIzltz_95Jv2eZzHZT5N6dNpfvfxcbftxphzKS6EtvNDcM6ZtXDKmUX9EGoRFnUEzC97K2ytAedKKlVkiYUsssoSCyv0vgFAUQXVFEvRCsgGwTRUqpTCgFBFbeuZhZkRcVoTeZtVTk8Xay2S_PzTuTAX0lyYWVIqknI7eGMBCZZ5McaCyjTOlaVqFUVD9oWViUgp5cPtrbFkiERqXFfhYpwTqfNl3L96xQyHq-s0X0j0_PiMwC5QWQvXtNtuybkckw-haVtj8Onx4eb2tUHnvVMuiORMs9keqB2WeVovSz0vpODIbG5vW--W55PMOcaqSNM0f_n13enhHNdle9xScLVW46lvGkUdQr8uZRi2ucS0rqlWawhUS6xIlHIxDfnOGgN1KWUpRICIofUoCsylSpyW3eGIiPN5tM6oMaqVVa0FJFKybjgKF0WsIoiOQanzNWbnHBostaBBssZ2TdcGTeXFhkLWuqYtp9FaNNYAomhVRUTRkpp-EGbliqJAICqgCoSaCxYhFURVAWCGUgyRcDVo0BqJCYURiAgAFECVWWsmsoAKleHlYGANAFhjlEUVbWgkZSTUWomM1ozkyBpQlRSN9WiMqpI1UiuKkveqFVBBBMmoqPFeWMh7IiQFVVFA1zY1xpcRAZEBBLIkuZL1ymJDI-hqzkSQ19gMg3ENl2qMrbn4tjMebRPW02l7dbc93Fzeva_rqrUCVw2WgWLk3fHorXl6eH796vM0zr_8k1-tcfnxt7-_PDw7lKu3h3nJrgkp1cpqfRCV0G_CMFTOwuy8L0s0hkB0fnwOfShzaQ7bmhK60G0PzWYLFuZx6fv25su35w8fnTHG0u3rz5dpNgiGqA3teRwPV0dCJSJjXd-1_aZLadFSrq4PfRNOp9P333xxu99_-vjh2--_1spXV4ft4EHgq7srb-mPPr8jY8ZpnOfFe399tdlvN6SacgnBN61___HJODNsBuddmuc-hM22kyLW2lIrGhtzqSqXaSVjGfHTw1lRfXAWDdf608fHzbYDMi9pMIO0rhHUtBs_xcKs8xpjKsbYMabWhed5BWML8xoTOTNsmnldiIGrNoMrrORsKmWKFR2NY0ypVlACzKkys3M2qHrrT9OCSOgAYl4i__z4rMbkXIug9e6nDw9g0DojpKWyIWQp02k2RAjgnCWDtVTnvVgqLEPfcc4IVslUZhtC2zUfPpyarjs_PafMp6fLMs5t30_TKIascwB6Ps--b5dUcsq__-mj96EZuvM0nc7nNedu6O9e31wP_c1uKCURYco5lrrmgkRrTITompByfbqMbWhYQbh6F8Z52g39Zrsvwpd5-Z_-6t_dHG-z6OOy_vDp8tPDaZqTa0OqrMKhDZd5KoU3u34YOpBqjEHA-bJY-0Ll0qvjARHmZY1LIWtZFdGIQK48x8wMlzGe1-Rbow5iKfO0xiqm-dU_tZuDbfrK_HL7m3P6T_ffviKIYIzc-pbzapwrqIiqSMs4SS1krW_b0AZk8MG_vju2TTOOMbRhs99KFRFIXF1ruUiJuWJFwlJysNY31ngvyK7xtbKx1g5-uN4p0ThNoWuvb3a7trWICMYoFmElms7zOF206mYzcOVSOUutqQoqIZRUybmXKi9zbtqu5hh8ANGci4ooYM55vazdpkspIaBrHZdCRFoUa1FhlWp9D1K4MKjUWv6TAUqM9yVn37W5FBds2PboO1Wy1mkpACKFlQgNgLAKEzOKkPXrEpEQhK3zoCpo0HsgU1IioyqKzkAzUOMVNJ0nZ_7wkvoyWA3EiOhDtz-WXNdcw3GzLPmL2-ssKqykWgREda2sKD9_PL-53nq0BrCIjjl7axTNVLkSsEIFnlKyRMFgrPBhmecaDeG4ZO9xKfzT49k72AWDRBnw8XFE-weQc8rsnW-tRa7xMpNFG5oqStYjAQLlksaPz2FoIJDkoiyx5s6a-ZIY4NWmEYD_-P7REc3rWku9O26swuM5gkHftXNKl5jffXh8nuZpSl3vj9e787KKwMfHsarGVEqWYegPuy3PsxX46ePDX_7-w88Pl4fzuDsef_jh4-awa_quCE9TnGv-_W_fCeLv_u6ncUxffPXZ6Ty3PsSYsta-C__hb3-KtZ6XZNpwv17ImXWOlZVCmJd1XtYlJSFca2268HBZfvxwP9xs3z2dPj2O1uPf_fanmd0Ya6rl4-nCgOOyni4rdc1m18dcx3mVImuqvvOfv7r6-DTfnyYGWjIT0fk8O2sMGSCy1jKLKpTKhKYC7I_9-w8PlfHpdCm1AtHtsD0tUUBT0afHk3FeiqRcfedEsW9DLjKfpqbv53EuS14u00s_FY21PvSbPrQNMH94d78uKxG8-_l-rXz7dl9FUyzemZxSrTxOa-ZsW9N27TStzntqbb_fibBzpj3skaQwL_Mcds18Gp_uP6Y1-qZtuj0Yujzcnz48mdavc-oOg3GGjM1Ppzie4xSH40YJSsoCYEnWZeUiX_3pnesNoIauU6_n-4c80_5qOHz5pt8et1urKGHTbg_DfJ6xUED0BO8_PNRaMvK3v3izlPUltr49dKj4J7_8yrN8-PA43Lb_6NefyWW93rTA-uL8E5A5pr7vyHspdU3ZGbjZbRrrSyzeoDP29nr3-rhtQ3AGQSQ4l3JVkWlaLsuSqnRNY4zpglPWAth413gXl_T52ytH1jp6fXXogtv3zd3NvmucAfHOBkfKjPQHWW-K5Twvoti0je_bCvA8zrUwIqAJ4zimWtGYt4ddWpJ3_uPDxVozp8isgNA4672Nay6lFuEXrMY0r4BQSn259V8zk6FUShXkWmtmMuZ5XIwxTR9ylJhryjnGCBbP52VN9eF0WksBxJrLS-RDAQVM09h5XkXANF4kjafRkEEgIgeiADCPFydwenwWBOONSq2lAgEZAGH0LsWMALXUFCMSSpXx9IDgauG4rEUqChCY_XZwhsta1mlZzuc8jWsctdbQDjUuHz9-BEVr7DSe0jyNz4_LvFhrBcrp6VONYxPs_vpAjg6315fzWTiiVGNNM3g7mDgvBuH0dH56fF6nVQirwBJTrtUbCm1TRRrfret89-bNzVevcpHz0yn4UNZCUlF0eZzqInXNGtkacIgxVtE6HA6-7WzTGHJABAi7q6ucud3s8pJd46UUACLXVE45Ri252-8oOL8dtBQsDCJprSWzJRdCcERxXiSzWlNiFgAbqMwLoTWhFa6cmQwaUInaHQ9pHFFVq7ykWJEMlAJakQVURAQUQf5w_04ACkKGQCsAamUFEFAQIQWyjktF4xQRAJCQuSASAr54r5BQSlZhIgOq5AKzEBkQAQRRQULrG63MJSupMLz84i8aYNQX7jyRsyCqVcgYJKO1gigqGGtVMiBCERsaE4IiKZK1WEsSIWy8D1651pzbbsc1AyFZMz1f7r75_vWbN48PH-LzWUqKl1mRwn4njF_-0Tc8r1y1dd3NF59_8_0320P4m7_6u4eP7zlHKxSn7PomrcmHVkRLjN3-2N0eBbSkgiwqRXN21sXLjKpQ2XZeuICaw9u3w_W1sbZpOwK1RA8__AxS0SACGmOYOaXSDwM6s91s13ny1iurD-Hq6vjm1auu8a13h83Gkxm6sBs2Mc6__tNfpxy1anDYNWE_dEPfO0M-hI8Pj1fbfRt8PzSdD94igjk9Tz7YVLXvBwTIOTfWOGe2fWuIQEFAYyopl8JsrJ2WNC3rmmqspQtetDpjtl2bWfTlzOfMdFkeL1NOBVCI8Tznh6fn-UUUaOw4LWvhwsKED89TYRbEvmnWJXceRQ0DFIZaSq6chTPrvOYp1SJQS13TIkqu9Y3zkvkcU2ae55yrTEucUnbOpZjmZV1L6bqw37eXOa1LzTEy83a_U4EvPj8o4OP9eX_oGSB4N68lgVlTmpa8pKyIl2kShvNpdM4uMa2xuOCUgQDOl7HUF9GbN9b44O4fT8JSpI5xNd4uKd--fW2sIbJ3N4d_8z_-q--__uyz24Nwdc5MSzpdIhBZQ4RIZEVgTqWKnqfJOWeNKzWTtSGElHNMOZb69tWr02X-_c8PD1N-vCyZGVRTqoSOpQbfqopvvSPKa2mbVkqZ5nMpwgqGTCxSKo9rqjmtsYpCXHMWRsVljttNeHo6PU-ZpbjgT8-rGgAEzmo2__ifxXEV72zrd29vxnEJXeBaiRAFdm-v12ntu-CskcqI1ljDuaaYWuebvhflvK6iakStoWlcLuPqglvXaIwBiwBijNGizlllJREiVFDO6rxPS0ZU4xwYmpfFB19yFoXQu7isnsLdzdXpeeaadpteRMLWPj1eoMqaat8Fsi6zCAsawzHtro4ppTzH0LTrvG6HQYSXy6IA67paY4yzpRSp3G06VUXErutqLmSM5NKGBkFANZfKmlDROFMLO4c5r9Z617iacuhcWmPoAr4kJ1UNEUjhyus0--3OOqOiQKpakZmI1BAQAVep2fkBiUTRtq0SljiHrpVa0BgmEkUEJBWjyjmhc6wgzrptX1Xd9bD95vj07ml3sxdrDsc9sJUIy7QMwSmDAApo17pPj-eUeehbNUQGM1crSATPqRSGVNPKNbOurChaDdUUZa3BO8iVCEBqT5xiPRw27z5d5iUXYDTmMo4s0AwDC3Ms7WbYvDnOpzF4k5YoQM1hmJ5HZkHrXjjOVtF3VkT7oev7UHL-dEno7RzTD5-e284D2k3bAIBpzGnJv__5aeaatna-LGvORGbf71RqaNqi9byuYI0ztmtCRQbmT4_zmy9vssDzNDfX-_vzHIbgWncaJyVgxfunsQKH0Oy-2RNRvsx-0-alFmZE-v3PDxFgTOvlsqrBPKc4ZgC9TKtt_Yf3n87nabwsBfQypZ9-_mh798OPj3_7mx8KmvePJzEkpn768GSb5uHxCTtfg65zntalP2wv5-X2zd2P7-77bvPx6dkYh0gq9Pt395v98DwlQRnHkgUqqxqblRNXa2lckrMOGFIuIrqkmpiNdYnSggEAAQAASURBVKfz5TzlBHiZk3E-MaeUUs7Wu7hWVq2VD3fX5-cxBAvMyzQjQrsbFEERiZBV1yntr44htNNlNIZUddh1eZpOPz-ncUnLen58yly7zonUxw_Py7ieH05c6niaSy2haVjYusZ07RrLOsf18jQ-nFAhtN321TUYOD89CxfJ2W3avNTD6wMjVBEwGDoPpBSc71r1nuusgDlVsubzbz9rOjc9zW3T1iLLuLSbfjN0tzf7eolvDv0a43lZXx-vP717_ubr21_86jOH4eOnZxPC6TSenpY__fZLKPzq-mZ33H369PCnf_btt6-v9n1zez20JmDMu-2m9YEAXLBkEBC4iiFqrHHGDp2XnNYY2yYMfTuWuNv0bQhSxRBZQ0PbWmNYhFnmOTrn9_1GWLy1xiAAxlyCtyQavBfGaZqss23feJDGW2eMBUOIBC-gAZzmdV2jIzyvdZoTA358eK6F_TZ8-PkZrEFjQ-sq1efHy3G__e5uDy6cp7my-MaP8-KssUBYVYpWVt_YUlgFcmLjrGIlY2KsmZmsZdb8gj7jSkSKigTeWl5L0_qxFC4yj5MPIdeqwEPfOEuGqAkulbpM0XpDTpclOe9c8JuuS1PyrWN-wTmyoMSY08o-OG_tNC9calrXknl6vgAQIZYUnQ9NGxSpcg1DT9YiGmURqQZhOp_iNNWSc4rXu9frNNVSrDGgRePKMeZ1lJLJBBUBrv3hOD9-dAbH58t6eRofH2uKUplTWafVqS6n5_F0tgZqLf64BaLlccwx52VZ1wVRm75b14kL5yWePz0bS-Nlmi5zsAZUS83A5Hy4fv2GnM8xsarzXpm7TWu996Ela9VaNC60wbmmpIIKIuKdJTSn50dyprHeNm5ze-fcZtgdtle3SuRDCy7M4wVyzdNirFdhETGd8X3jHHXBrs8Ts7CCC76WYoMDVV6L6QI41SXVXCxZRARAE2yeFlIgQ-oIpAZrpBatxShqYSAEBGAmVQIDtaoqsaACiiKAlIJIIGpJVeXlDKNlRTSkpCLG2pdEuwstp2QUAUGNeQkWkkFiUUWpBYhUwPlOlWtM5AwxmD5AKsZYfGkQIxrnAUBKRUDylshoTi_VdkTlKj50frcX4BSzaUIzDNP9vW07dN41oWaRkrvtVU2LQFVRzbW_vtodb7q9-_Gv_t5aev70qdsOvu8PV69ROD5Oaa6H6-N_9k__HK38_W_-5q__7b_Pcc3T4g0QYHfVl5KIyLaGS3Wb7XB1k-fVOlvnucalXmbfNi_mAYmMwdSqBBj6oR12Lyp3zkmk2BfqYCmbw04VnTXO-7brFHG7263jxTv73fdfHI4HqKVr7On5ofGtSG1bv90OllC1vrq-ifP09ZevXt9db_p2XdevP3u1xhWt9ZZ2Q19qbBsXLA1taJwV5cbbtm1yVVTw3rZNUJG2cQbQIqlKaHwqHEtdS6mVBQwairWoiLFmmpZXNwdVenoeXetfVIBLKkvJx-1-TiLefHw458LO2MyacomFz2nptu3TecyFCxdrXWvdPM4WCb3NiXPlqng-rWYTLpHnVLJoqRUBSo7o7WYY5ilebXendUJnc-XLGCvXdttf5oVVlMg6Y4DGKcWUGLQK996NS_7mu7fTZX16GL98e4MK2-2Ahj6exnEax2mtlS_nqbCezhcRjWtuuvYyTS40z88nRazM42Xqd4Mhso7uXt2UXJZ59a0lY7z3S5yXNV7Oc2UJhi7j5dXN7n_1n_-ZVSaDz4-naU4FpFQR1lTUeQ8K45yIkFna0G533W9_eHd3daUKHz89p1IP-w2rjrH-_OlxTfz4NKlILbXySyYPgNAH1zZhvszDtudaSko5F2Ots6QAuVYBuZxXASIiFhVR78N4Wbq2W9bEIM7gMhWuNRdpbDg_R-Vsrv_5_8HuX-1evxrHRyGEENI0L-PcDh0qkUUA5VSs0W7b5zVb79fzRQobA8s8oWjKyrk4Zzeb3ljcX-2st9a6FGPbtHFZ6aVbrqjCQDanen21SZVP54s1RlEUQYAEARFZJNfaDUPbtp6a46Y9bDdSOC_5_ukEQkuMtaQ4JZbS7nqDhqw1St1-WJaoAs4aIu364fnxse3brh8eHx6Ot1fekag-PDx5HzjXuCYyppQSgl_HFQUQGABFAQnLEtEgoUEiROPDBhGMtZwKFIEi67iqwjpO-DJwMhZDa4fNGhNZQm-AgNdELFIzg5LzCIisIIKGuAp6a6wrcfGEIEJIbI0JXehCnhdZF2MNeKueqGmoacSYMPQsVdEY56zovg9vP7ue51WRm9ZZ71hkXeOY8k-PZ0Dd7HpRHWstVdtgRGVkGONsvYsiRVgMVKAWCUglFVWOsfaboArTXHKuaGBaUxEoXJ03aS0p16YJ3TDUUsj6nEpZk8TVGgJjh9t9PC8mkPOBi_RDm-a13bSuDc654C2ppLVm1f3NvjIgGRbebIdpmoZN-8PH87jG52lx1n16uMRShkMP1iwxNo2zxuyPwzC0UuWLz2_2bdj1bi7l8TK2u261-O75dHx1c7qMtZTL80TGVBZBaIeuu-6UzNP7Z0NmyvFwdWBla61t3N__9G5aUxjaZZxMfVF16dffv_344ankwrmkmtBQXFcA8G3z9HTuB__TD-9daM6X5fF56rtumkYMflrjMLTvfvuT33Rlrl7tNJ23vb_Zb9bKz5dpv98-XBbycJ5KLPLq9fbD_UgGauVS5Hbnn87JAFRQFFhiDpYiSy6FRWvWFGvX-odPT6Hv5pQFQFidMcaANzSNpT9ul3GpIsuyKJEJLRgrAMKolW3w3dDmNUuVeboc375lTlXx8ecHZ2DY9l0wVXNZcx7j9DitU2zbYFWE-e23bx8fLjUmIIPG2gFOP384PdyPl0vb983Q-s2epcyn1Q-d1lRTLgC-3ZNRIFzHBa0NTYAK0DioQIGgupLreMm-a4fjZnqIcS0l6eZ2BwLDYevQtr759PTAzIXr11--fXi6bIMbtp3zfrfdtr29XOZN61-93nPmhOXqbhcfz_fT6dVui6S9bdZ5bhsXCHKGq02HAN78YT3KuTALqICqSgGV3ofGhya40Pjj0DtreudJ1VqyRNaYKlqZGQCUgAwgsTCKviwD_aaTnK-OW2PsWkp9CUmQqakahwiqokgkoly5cJ1j8t5dUlmXBBa5sigy8zolF7y1jlkBpfOWqn7--qZUzGt8d_9ojEOEXKTm0ncdWSLEP7w3Fe8cII5zVGtYGJFSEWbNOUqVKuJ8IGMQbcnZeRdcmGKK60vMzOTMIkhknLEps7CsqZC1ZKwUQaAQgiqgaFpT0zoBiGvtuy7OS5yiqMRlvpxH4zwBK4vWjFJVVEGFANWeLs8IRMZY7y_nyzpNIXS1lpu712md9sdX1tK2aU6PT5fTvTEInJlLCA0zcynKogBNPzjnY7xITGBsnJcQvAHot60zhMaOl5N3BgwySD8EKUVynR4ep_uTcPFdX6QSWWsdS226_vzw3PXddt99ePfJevfx3SffmHbTxxSHzRZAa5Z2aA-fvaoVOZXdfh-n5H3nXGAFaoIlcqKSWLKa4H3wUBnJstS0lLTO-_1hmufN7bVzFgDA2_NpbLp-uLr2Qxtam-ZJCzvnbAh5TFJSiYkLA4mIElEtNbQNx8QVndvKPEItKkLeIrPzIccVEbiw9V5L1sJIKpmxCgkag8YYZTCIJGKpAU70UhEGhcqoQMaQCLACoVRRATIW0RlCIDBAXAt5Z11jiKQUrtl4-2IflyqowiJKCgpEZJ0XlZcxOzlHYF3roHJZExKRdTWzdVaFOa4mBCDDOROBcZZrRjTGB7AWRV6u7VzTrk_P7WaPwfm-Xac1DIPzXmtdxufQ9a7pjl9-eX37ptby8PsfOeXx6fTFn30_ntZmaAi0RO03m7dv3vz6n_ypQP7__L_-dVkWY23TueXpnmv1bZvnNU0x5tRtd2HYb69vpNYQ7HI6xdPUNE3Xb3Jca63t0E2PU3e9QbK7m6vDq1tLIS3L0HdgUITn55MCiIAavPvszXQ6qyCC3r19vU5nUnTOXt_t-q6fz2Pfum-_-nxdxtu7q69evXZEXd8j8XF3SGtsva-Z52Xqm9BZN8X07Zd3fducns5t16DW_W7TNy6ui7MBAAvXuCRWIQtN42JcjvuhccHSS02jzqkwYirFOqeA5GzftcLFOPvq6uAtPT6c94eerJ2mZYxlmpfddpMqn5f8_v6533SZJeVaVZLUy2V1TZjnfH9_SszDYQghEKolYgQWRDIZoYoUhNO4Jq65ypKSCy7FOMelb5quacBQrDyuKad8meJm6OYUU8GpZOcbUnDGGmOnaUKkrJxKRdbtduDC948n75yA7LpwOS_vH86pcFFZ1qKgm21PjsbT1PbN4bCpWtdaPn74ZLsGCYyhw81Vybnfb18Qveu0TnFRkbbrP358CKFx3jvr5vkc0zx0-zevD__oF19BKmTgNC7TNLd9k6soQdu047yUymvMhUUV-r5_9-79zdXBeZtzOS9r37dkaJzT0zhdlvx0nsh54631HpSkatt4S-idl5j2my1LXs9z5RpcAMXdbpszI9EyJSGqKjnnZc2IhKpt36VYwNtxjsZbUWYlce7hebo8Xh6fZ7P7b_73YRPWvC7n2fhm8-p6ejrtr_p4iUQhkJ8vZy5inMtrtH1_eXhSqa4NyziRdcbarm0RMATvGjdeZhEVFilqDdWc27YVgNAFUBDReV52-y1XfjifUdXahlWMszkX34bKtRYWFu-CIfpnf_4n9-8e85Jub48plZyrAKOl5TTtrvZxjiDku5ZzLaxNCKzCtSBI3_eVOQSXchrPp-3-8HD_dLXfl8LemmZomEutpW1DWbMqC0iOqaYilQXVEPrgVdFZL4BkLSECIP9hWVPfdWjBOHDOlJLinNCbFyCatVRqQUStVXLCUtAaDB7Jcs0IAIyh3-S42KYDopdRsm9azhmartlt0jg6H2ScfdfUwmCNaRtGY5sACFpNf-in08g53b6-qgn6XX_Js7Bola4NpSRrERv74f756mpnnKkp931YllIBlZQNxTVXllrLuGbj3ZlZtIxrAsKcKzRWqiAR55zXlxSUAMB8nvtNO14mNKZtAwpaY8ljjRFKqbUqOSDQzK4JHAVAj692OSZB2_hw1fUplmCNFGlCcwghp0KOrIVd36KYzvnHZUWniZSBrDHN1s1rycymMSyQWdquRVTX9GLsOMfLmrebZq1clMSS67vTZdzf7dO8fP7569_9_qNxWgFb763KsubLw2h7L8L73b6UwmqEtCikWkrmpmsMYGh6R_Th_b1v2_PlDACIdL6Mvu1S5vv7ZwRUoHmJprEpq2F-fjxff76fY05rSeeixv_pH3_7y8_f_ON_9PXf_fX7VDkWRkOlyuNp7Lfh8WkuuXR9Zxt7eprbxhk0JPwS0gDCNSZS6AcHgO_u7xvnDVKtfPji8OHDSUnJuZSLUQDC7c3wdL8AGRe8N55rqYW3h63xAR2xomhpgrckOdXnh7NIsQAqMJ8vRLj7_Lr1JiW2qGD7POfNq6t28KEPm7fHfJnmKYamm9diHbVdQ86kOc6fnjkmWFcRJoI8xZJjmZNzllPmypuhN9bPlzNBffrwzoVuf-g3V9s4pW_--I-G3aaUPC-rd74Yc_tqf_16f_k0HW-GdSm77SaVvNm0CmwNWG_OU-najlWtxb7xoHA4bPOclsv85ZfXu2NrlIJ3v_34lCO_ur1-9-F0e-g__vz4x1-_IUbK1PeuH0LXeKkqwACqLC_qA1FY5iWua993zhgWCd4DKFfugyOWXCswIxEBnqfl4-PzGGtkFtBSqrG0H7paK5eMAAax33YC-nCaPnx6Hg67H949Gef-8oenxhNaCwCVJTTBepdyfT7Pz_Osiiw6LisLVwEX_LqkLrjP7u4MgmE4HDbCcB7zx08PQKCiaH1KsR-6IqVkNtbyy82xd6KScrWGWNkCCkOVP0S6xRAQSa0GUVgKs7FuzWVdaykSlwXIFIYqSiox59NlboIvDCUXATbOVK7LvKA1IoKEBjTlSoaYlZAUxIRQU2bmEhciXOc1dDvm4gzldVlPi7fEyqiKxgvXpu1C6-Zp9K2bTicBnC6nl4jI0G9yKeuSuCZQEBZQRSTrLAiXtKCIlBK6HkGXdQHlm9tX0-kizFJLCK6sixZF4ThegEWJDq-vjbdkcDyfm27YHnf7w2Zdo3Bt-m5dsyRF1FLycn7iXOdxyakoV1SRynmNiLgZ2uP1wVjr-7bbNoiA1qCxX33zVS7ivL_68hVakzPHNYVhKKn6xrW-SfO4LKnMZdu1H394d3l43B12yzSlNeV5zHGVlI2z3dCllEqMxlplbQ4DgrIIGSq5em_SEts-lOliNIkCWjTGGDGu7dbpjEQIoCJSirWEqFiFlAlQkUHlBRpKgKIFpCIZkSoIBAhEwqwKgCKggGgMKTMhEhCBEWVEBLXDzfVyPtcYbfA1R12T7TtDxCySi7EO9IX4QqKKzGQIlKxzJUatQtaQNbUUYwwSlVIJjWs8GFSpysK1-G7ju43xFhS5ZKnVOJ8vZ9d0Csa0DcdKZMGSN0E5hWGYnqerV2-O17fC6fGnj4b4eNwjIaC13m63Nz__9tN3f_TFt7_4xr_a_M__4__7t7_5W08ica2lzPcPaMgiAqhUrpVff__tPKZ2f-0MruO4TpPkRKjOYM7ZeCcsLByGzrngm2F7vFGlmHMzdOfzhdN6-vRgvUdrjHeh6bjwbr_d7neb3SavC4LeXh-bNnz7-evf__YffvHV26vrzeP7j7_4xS9aZ0A4BH8en4fGB2uuNp0KGosI0hjbD82-74Kznz49XS7L4TBYg1eHbY3ZkCEElrqmFJwb54nI3N4c6lI2XSNVjTUKKlWramRmRWNtZRbVNaZa6uurY-sdAlhnNr37h3dPj-OsQiUWULi_P53m9Ol5QqQ5xpjqeZxEQVSYJZbsrAODm23IS0X6w_GfHM2xiME18RxL2IbHKS4xiSMWnsYlDE3X9oQISDnX8zSa4BMzGZpTiUW4iiUIzhOaKa_CGtdyN-wXkZyytU4AdvtNcC5XPR4PHx-fUuXEhYwRVFa11p0v481h3_fh6rC9jEtRQNJaCwJ2TcslgVLTWkcGkJ7Pz23biGqp1ZBp-8E3_v7jPSJu2sY7en2z-_bN674JU1w-3D-tucaXzrTi6XypzFWVAXzwzrllWfq-N2Rq4fcPj0Pbdm2TUjmf181-M1fOmckYUnJgjk2buUphjdUZctaXFBEgeLffboe2CSFwrWgoixQV40yt6oNrnLdkainLHK9uuufTMp6XcSkpF0Ycl_UyzbZzJNk0_-JfQANVoFYZl0IhXN-1bb8dH07GUC0ZEQ3heroAsBQObWtdMy3x1TdvQXGe1nYbNptNzcvz82mZ12maqfGKsp5XMmScL5UR9OHTaTsMvnHdYH2wTw_j0DRxld1dq6BYqZTivK2lbLqhrsmC3fZbh_b0eEFLS0xAAETztFRm5wNw0SKZxXdNP3RcS2ElgGlZ9ofjw8N9ux0QtelaAt0M_el8ASJAWqe13QzT8xo8xTmmNQ6HQ3wBelQB5lpFCiOIiJDxtVTrjOrLkw7GEDl6mfEIi4qaYFSkTDN5b5xVhG7YQikkRVcWAyzgNxtNBbj-gYOmQD5goDovwJUINOdSqpIl5xgEakFrVRXJMqg7dsZYThkIaWs2-_7dv_l9CTjcHpbELELMrXO5Zk-2CKRC7x-fhl0fyJDiuuZLXHKtlSBVjQJaTUq5KAOiAzlflrQkRVZV8ibOGQGIIMaCqGnNbevWyLZz3WE73k_eviQo6MX1lqZJU22vdyI8XeJmNxCgQai5fPf9V-N5RIHLZbq7udqEQICWBLFu2vY851Lr9d22NXZeuWoFZ9fClYkVhUzk8rJvrmjGnMa1FIGuC-tpPE_r47r-fJnIm6KagFkAnavCxtl5Tcebg6hxQ9O0ITJUS4Zwfh4Bc43l62-_OY_L3XF7fz6z1MtlCa6jBuMaUxIKVGsBtDnHMLRoqbLkknNKpUhWJUe5onolAplq131VeNr13jXNm-_e_uru-tC2b283j5dxIv5w_6RVFRmsTYm1CgKIAFcJjeMC07wMzlprGm9FhADdS9Yu577pFMBZN_RBVv70aXIIbdcLy4f7-e2bq7vDFsm5xiECocxTRCIwdp0XtPblz5tz3Rx2RFRqkVxzik3baa1SeXr_XIqggAFQzkhYYypVl8uynqac0ma3YzVV1DdhfJqHTYslc0pNG1zXKkDbNahSc94ejuQcqvZdv06LQdptet8Nruu7xsU1AxlRiGvsO386zYfr7eH1EWd49fVVmtlbt_vyAMqahNTtDr0DIsTjYf_Z66uOpCNjkG5vdtuhb5FUy-ur_eP7e-_Jget34W7fv9p29-8_3B2G77669SDbwb867He7tvdAhkB4XiOgGucUoW2cCDDrZV43m6GyNk3nvauFpfIL5ERVLRoWNI5EcSmM1gPah9Nz2_bee65lv-9_-vHTdtMbQC56uSyXZf3duydqfEa4nOeVBbg8TfHTnMY5-da2DmOsSyx___iw71qymGs9PY8GcbPpN0NrEQnxfDlvhpasRTI55udljimHpltrBoRN36eUlnEJwc9xNWRSLSUXY0yphYQrS--7WErK5ZLWUpmMRWNQpJSKBD64BkxMJaWkxGhczDnG6BvftDZFRlVBcIbyC-UwV6lyGddauKSyLus0LqxSKyuha0zKkVVY2CFxLd4F2zbz02kds6rktVhLnCNwVYVci3UOuBjTOOucs6BaUlouZ-fcOE2Vq4IaULKOay4xG0MqYEiDs7XkNM9kaF3mdtMF4y9Pp_H0UGMq61hTLiV2w0AolZOktaRyePsFa1GBnIvmaknrstz_-EHWaTxdPv3we7S21GS9cWSNsc5aZ5GQ12XtN5urq4MLQXJFtI1r2nZou246n9YpgaJhWNPcbLrrV1frGmMsqlJZXNvkmjjL9etXSmZzvHFEy5pcaLbHPQEwZxVt26bpQ82FiABQVJq2EWHOBRgoWK6KqgQKpAjObza6jI4MK4A1nKtrHNeUczLkEBGBSQWJVBGkoLKAAIAWRuekVhVGAC6VyCgA_cGBKQogMhG1oECA8FL_ECQfuGYksr7xfR_jKikZbwHY-tY0reSMrKJCIGQsajXGoaLkhNYgkaoY76QURVQFVGy6AEjCSpYICdFwTGitioZuMN6jdbWWWgoihRBECro27Hf9zQGKcJXt7V3JEbWScWSaL_7xn-669vTwaXp6LnFsOl8Zl1X_-b_8r21o777_7PO3x-9__e3HT-__-t_8x-X5wVCeT5caU-O81oKovu3ykkzbX331zelpbPpN6JymPD-dQLnMkeMZ1aD3wtU2oaz6R__9f5Evaf_mdWVOOadlmh9PwxDyunhHisIZhsGnZfbB3719k9b4R3_yfTxPm6H77uvPN20zBI-F95s2x-XNq7scp03XNr7JeUWg0IShaQ5Xx1zz7398vx9C1w2n5-fd0K-pKtdf_vqL-w8Pb26vNl2opYbGgSgrPJ7HNgTrHCDUJfVDcMYAiLVGmcc1xlxD07DQ49OzdS7mKIUN0e1hE4gAYVrTp6dLu-kfnhfjvahO6_o8pYd5LqjncSnChQuiAZW2aVPKjLDOqWkayWycZ9WUMhknYJaconBkEdRTjGtmBlKCnFLowv6w2w8bqOzQnKZ5ZUkq5H1MVYwRxWWdQTDHggjrWs7jzAYuOTGLseSI3r3_OE3Lh08PYO1PP38wzhyv9qfzMk1rTvXquH14-LROSUSMceM0__zu0Xgb42zIENK6xqePz93Q1Fy8d-dxvP_01HQ-5wzorm-vcskPjw9SqnB9Cb3_n_6P_-2V93ldL5cpljLOcY3VB3eepk3Xee-MJaIwL0sItmsbY6wSzHN6__HBBnf_dDlNy8fH04eH88f3T-QtCzBXJTjHuMScuJJBEMwlrzkxMyK1webKCkjWlFpPp4uSYQVBUkWnmHOtzNa4eaprSmx5nJaXsfCP7z85a-c5rUsx3b_434na82UtAuRg2HZp5Q8_vB-ud-s8CRdei_c2bPao2VibY2qHdrsdlKsLTbcZai7jeY6pxlRC6GzQ54_nXEq_6xg05Si1rDG_enVlAG82Xcm8zNkFWxRCIFK25GIqtQgRlFya0Cjotum2fTNdRgAppTZNV6U-fHpywanCfDqrMqJR5X7YLsu6Pe6fn54VuOnap_vH7XF_Pp2M9W3Xv-SkgdkHh6iVRau6FslASYUrKwNZAlROxYYABIBYpNbCtmmBAJRqrbUKgVhruXCVogZqZdf1L75lMqaWAoKqIoUtodZqnVFQUHo5e0gphqyqkLEMhlzgtJKqs06EwTn0XskIKOWMCqqMhFIRg8-xgEFhYmMrUnMcHj-Mx6sjGsgVU4xNG9QSWC8Wkje_e_-zt65vu0DEVSsJVymIPz9PCUxoiVQLV0GSwoS6TKsFAEYMBhAow3pZUKEWIERCNYiX84wGm96jKBpdp-w7x1qn-xOKasy2a1DBNyEuEQAVaY7p81evL6fnvHDTuVjS-59PobWG3FziJa6bXZdi6skXFm_cmNfqVCoqqQm0lOydj1wL1DA0haSQ_Pw4Nbu2gIBFH8g3DQY7r6vpHBCeLxM5__e_e2oG57peEYFqVDyfyqbzrneP95MC5VTmJZ4ua1zWVAoATJfTOC5gAMkM23aeIxhEwnlZ3RBYIU4VrEnKtu0KVvU29LYmKaDd20PVxXrrrof_9n_zrZ74q5vtbz_cf_PmdSH96edPtTB7P45xWaLRakyTctoMrQFTc77ddb1zU0xS2RprHSphrZURL9NqAI_7brpk72l_6E5L9gb2-83G43bo4lgEalI5P4w5ZdcGHzwaAgUuxQRvALjA7nh1GWdUHI47IKMIhcsyTcZbF0K_tQhUivjGQWMITCqZCEK_s0O3Oe4_--WXWOvh5rA7bueHcffqBoxjtImLc0HEtF0X-o0YPH96dt5-_uX3z6fTdr99eLh89u1nX__qm2kq-_3u-19_z7Wiul_-4iuy9PTTE6Jshj6vdbmct_uu6Vrnw6eP4_W-f_v29ni1H9pQYznsdl9_cUMMVzcbKLXvO2-p7zvrKS58e9hagO-_fYWFb46bX_7Jr_6ff_E3__TPfpli-eJ2l3IyQMsUTbCIsOaUUzFEhASIogCILHLc7ZaUrXGVM8tLDRKWmKtILCwi5zHGKtb7WHJel37TOkPP5zEx7TedMabr_JT57z89Po5lSjWJ_enHx36_XUtVY5TckvOS0_3DpfWeLBXhnowAnk8XMuCc22xbILvO0TmTl9QMDTj7_Hh6eJrWlFmKIQsWU4qAaoieL-MwNM76y7QAQiksIs7ZWgUAgShXiakCAhH6xgXnzpeplLqWwqpceFyTN46MWWJS0jlFFS2ZFUkRmVlYubCoGLDrOFvC4O2yRLIgqsuyGkJAYObldCGweV37pp2mmbmM51mZnTPDtiul9tuhaM7LCkApJqkVlddpXWLcH66ePj5sj_uYY-iGKtE7j0CcVyJSFf8Sf_cWDaowl6yMoOycS2sq67rd75zzUrMziERkkEvUwkTEMXJem-2GOdW4du2mO-6J-PLpcvvl67a14-kcrOl2G87xxQzjG6-qiJBiJO-IbF6W83kCEGtoOY3O0Lqm0-Pz9c31sO2HYVCRaVxdt6mZ3__4sNltwIIqAqHzrm0b9JbA5HV1VkPrcuJh2A7XRxu8Wlu5AtPbzz9v2lZK9cFNl5mrioixVgr0N7uSMle2aGzTEqqkqAKKiAbykrrtMD2drbXGuZKjloIv3hWuUKsqcGVyHoXJGVR4EWwRvjwHBKSEAMxGgVwLla01SApopGY0Dv7_xFKy5FyNqzVkjAIDGae1aM0KgEiqwJytcbbpFEFZkKDEaFxQRWDGF2yqASkVkMi8mMcEQBXAhYDOW9f44Gvm-gKoLQVUK0B_fScqeYwiSt6WFEFlOB660H323XdpXr1zP_3wozPknI9R99fX__x_-G-8Df_www-brn_z9vr_8n_-v44fPy2P91xKWVcsrCQGqXBhVWOCbdrbr745X07dtg8El8f7-fHctQGqEKpBywrGBbIo4I43N01oU6mlFPH28YefTc3WIEgSRVLTtMM3__TX0_1z2_S_-NWvx-eH0Lh_92_--uq42Wx74Sqp7Hf9YT8Y4Nd3N60PUsvxeETFf_sPf_XrL79nrn3Xruv68OlxN3T73XDcdl3TdG2jom3XpJQOm947hyxAYA2y6Pk0DkMHCAhqkYIzm74DBWdNynnKVRAqY8xchGMspRQAHNowz-nN9aZkvsxTrHpayu569_gwtZswr_nT6fzu-RxTVutLrgzAogRSqpSU900jYIWFEJumTSiARKJgCBw9zVGDnVJZY76sMdUqwjZYKflqf_RksAJwBYTzvBYR4928pH67O02XyzgbR9a7kqoaylqzlFpFGZY11lKmJYbgt5sWCIXr67ur-4_PseTTeYqV3769erx__vjxyRl7vD3M08KqClJKWS8LqFrnx8tZhQEQrXl-Oq3L2jR-vixN3--utus8T5fJEyloiXGc1u2u_8---0Zj_Iu_-re__Por6_0P7z8a65x3p9N0fbWvopXh4fEppdK1DRmjCuMcf_MPP-x2-6fLBGiiwJqKAD4-jEAEQIBauMQ5LzF550BVAEBYiWqta8njtKoxzphP98-XMaqBUlhY0QUuZVlLrBksxZRVkSvfn2YSCYNP69p6yzWul8RaTfMv_ruSYL7Mw6FVFjKKxjsKd7-8AaV4_2QVhVnK4nxQBN9u2rZxvrk8T2ippJhzKSmKlByXmiJZZ9tgrS3znKb8_of7Ydv1Qz-Na06l23alinHGehdzllyJDCNYcpaQDDjjRWWzGQbvj037eH8al7WUssQY2lBqNWBOD0-GqKwrEIW205wZ1ZI2bZtq8mSYVUoxxuyO28vTI1flWkHx8vzcdhs1VFL23ufMKkiGUEFBrXNpzc67WotUBlUkqlxUBK1RroRgiGpJtnEvWmJSqfOyXM7K1fmAgIhEBgGNcaay1pqNMcpqnNcXb3UpZI0SYONrZVJGYQQGBSELNqgPgIDrAlWNBfSWEXDvwVCuLKi289igsy6XiKT26kANKqu19PQ4qbMvkeZxHOc1vnp93Rmfqy4xzlrGVItoYnndYsl8ejhJ1SK5okCuhqAWSakEJBSRygoAgKEJcY4vsEJQIqCuaYSZYzYWWQoC5vNFU07TZJs-loqAYdMt49i2zZiLARsaw7Wy6tX17qf3nwzZu912KfVyGgVgu2msMTXzOM6msYV5Hld1RNaez5fr3e7HhyfTUn_oWfCyrGpg2DYMsNZakKeU1BgVNmAMoTFwuNqkqttdeOVpmvM55jYYgrq72335zZvf_Mcfalq6Td80fs5lXqP1DgB8MMSgCqxSY3HeIgIhOkBeGRBDCKxMAM43rnHIEFgNQjw_Hvt2LHJs2isi8xyfC336dMkcf7i_NMae5mxcP56eLVTnXGiaoe8NgiOynrZDMy-JWRrnUslpXedYnLXM0lgHAJm5cLXWL6lsd513RkRiTC74KaaSOcdirGUFBBNzKSzGEgASIygE75hraNtuu2Xhtu8FWP8A6Ya0rNb79tj98s__aH5Om_3QXx-v7l4f376-ur4mhO--eVPW-On94931Ma1rt9lqlaKsCiG4rm9vbvfHu32c8qb1hiAlppAF6Xiz_fyLz3eHfnxejsdN24TTeXbeD0M3PjzklLtN8_bu9dPHh7dfv8lzXp7WN5-9TvPy6qrrN11ZFy11XuPbV8fbm4Pnumm7f_UXv_n2s5vP3uw7Z4dgbg6bz2_2x8H__P4pjsvr4-560_98__i__JNvj7vmzfXWquyHThEqACG-f3xog--aDgAAdF6zIglA3zTGWADIuZyncbPpG-9L5DEuAnp16Kujx6fJOheahlC_eHPVWb-u6ePD5bDtDFHTNJnrzw-nqPRpnIUwlVpEXgxHD4-X0Ia18DplF_A0Re8DGdM0DgDa1j-d1v0mGCRLpu-boekrc9uEtKYSi6pYh846dDaE5vbq6IxZ1rnxIaUk8ofQQuO9oAbvhLFy8d4xai7ZoCGDwdJ5XF0IhqDxwXtD1pZSfXBFKqJxzrbONiFwZQWNS1xjAsRSxXq7zrMxVoWRBBXjNMe1gKrkikgl1tA2BqmseV2i9VZFvXfK1bhGAAghl-xDl1KxzgKrMLdtYwg513U8DZvtfDn1u906TiRAyBYR0KAlIiRRaxFBpRQCeOHbGOssYdd1VOs0j9YFQszT4kIoa_begSghEKAggvBy_yTMl6dPeV7adt_th1JqSTXGCFmDte3-VZ3e1yWmVHzT1Mq7w2FztSdQ78JhP7TBl5i3uw2RQYe7zS6tcwiuMCxrvrq9QpRSsjU2tL7b9r5viQxHDs7GeV3nZIwz1va7LRo4P57mdQ1NiPMaGrecTpeHex_atu8FyQ59d703zuY5G2NrzlqEmNvtVi3wmqBwzoUsgogxru0aXhJ5q8Iq_GLvNYSgLFVIlSwhECgQmZeAD7AgIIrqS-inMBkDCi_fGwCovHiAHRFxLdYE07aAVOIqDFoqKdgQQJhTAiTjgqqAiu1613RSqpTKwiBijAl9J6WqiHNGRKSA9Q38gUuKQGicC90AqoDOhxC8zcsizIhguwatM12PxgqXdVz6_bGUlaxBMlc3r7769ruhcaFtf_dX_3F7GBBRxP0v_qv_9VfffQmaf__Xf_f-9----OL2r_71vxnff0h5PT8-h9a7ronzHEKrZNCFdnfMCW--_CzVOU1r4_3jh3fE4J09fv56fnpCJCSyTVAgVPOLP_9Hje9cG54_PCHo-vCEabaoCmRDl5J8_yf_JK1PD__wrm195SKatOqf_fqPv_3iNUvZbTZvXl9__-Xb65uhb7ta86ZrLk-fXr96jVJ_-unnz-7ujsfd1X7DlbvG911g1OurnXe-7zpQuKzLpusM4aZvuyYYQ9O4EEEpXERVVZFAuGsbb42WYo0V1lgKEcUqp3HJtdaqgGSsWaaxbfyrm03fhGVZnpe4FD7PcZziNCUu9cd39z8_nH76eNocN6mUWgQISetymd6fxgU0A5jGl5jJ2n4Ia66ExFVUVRAm4TEVQRBVCDalXKUqYBsa-zJvBRWWx8sIrY-lxlh918Sc5ikqkYq-pOfneRWkUkpKGQyu80Qo6EiBAACNc8acn04h-IfTxRiy1jyfpnmejbPMNceYU12WdRnXZV58GwhxmZb5dHHBN5smzkspyRJa7170cyqc5_Th56emNQrsfeiGdmjaBuGz65sv795OyyKIsdScC5Dfb3skTJmneSFL--3AzLVIrCUzMxolnOdynlZGUJL3n06pVil1TYXQxLVMc7LB1lS6JqAxOde4xBgToJ7HxMyXZUFLuYjv_LIUH5rzeUxLmcYFLYLqjx9OPlBVIVUirTEvc-RSu80d8LQ-Phn4L_6ZWLs5DIy533pnfNv2ztj4NC2Xqa7Rd60xyiylJkVa10zG1CL-peCiUmOsqahI17YxLimJQRwfnpQLILZ9MM5M59lYBFFhMc7P42pErTMxxSJ1jlFyCd6RRRXVKhbMvu_qunZdNy9zG_oYc051mVfrAzPHeQQl14Td7i6XhVOZ5nl3PAJA6BprLCh4Hzjltu1LTt3QuSYsa1yXuD1sS1U0JIIi1RoT1-RaX2utysYaBQE0_W6roKpqnVNhrUwEZLFm5hytDyCiMTpU50kAVbHbb8s0EdpamcgYb9K8ArBUoKaxbRBlUrQ-CBI2XhFBMzKTAhqoioxEfetaX6cRFdjQSxWcYw2vBjWUzguTK6t2h94PDViblrTbbmosZMl44MKq6BB2u-2HD_c3my1m8J6yyjTHOaXIGiPPYqJkBFWoHAUqaC5IUjNLZSkQtsiVy1yCd2gRBUsulcUYA5kbT7638_MUnBVWsraMK8RojRWk7evrZcnWmVIyCgFRt2lR6rwuu92WDHShuZyWw3FjuWSSn87ngK5zwRAVrHPMKcdEVYTAIBdGlOvX-7-8P-1a55x11o7jakmNRWvJEU0xocEl5ZQltM46a719XtYK8HbfTmAil90mKBCIRXW7605IXDvcP0_b7bCu5dXnx5vvjkUAWYujN1-_Pn96jqXevrlJcylr8W24erM_PY_driGy_-y___W0qm3CV58f_K75n-a4vd51Q9d4O9ZinBvXcX-7fffxtPvy-NM_fPx0ekInm74psb794vW790-bzoqCsuz7ZlxWUHFtmGK0zhKhsUZYq2ho7WlcWIBFY6qmMY_PF0VIuTBgrHy-xDVl37hcOXEBomnOZS1xzWiMIbLWopKSOmutd5zFGtxcHdquvX5zu7062LaNK3-ckc6rb-27ae6Nb_p2uxmud-12s43r8vh4imO83m9_-9uPzOXu8zswGKd1fF5ujsccU1rq89O63_e_-id_fHWzb0P31bdfLcvSbtqnx6er4_HNF68u48LMXR_iZcolakFL5uq4TZV3g0tLevPm-nror_ft3c3Vzc3-auhRy7dfvb7adENwm7YPBr59uxu2naSKqEMXnLU51XVej5suE-769jfvH_7x16-v29AYVAZrTOi6dUkGQQEa60HRGFuZrTXW2BSzIgTvc6mAep7XWnU3dKLYBn9ZVkQtBc_npYisafHGrfN83G28cX_z2_fD0G6Gfp7mXPnTaX73MF7mtMZSKyw5G2cERAqnVBLzdFq6Xa8CQnCe4qtta401QKC6GzoWFNXgg3HWO2MMgGhhFpC74wAM5ExMiWvOMY7nqfWh9Q4NCapzRkEIwVkf1-y8L7UimZiSIRTVly4vCuDLqqJqjEkph8anVLy1gjCO4zKlaUkqejrPtQpZCwKFSwh2XjMAllqB3LysxpgKQug4s3FOajHOrjGWWskQ56iiVRitXabVOoPeEKPrvDFGRQ63t8syzdPIpXLJWoELM_N8mZsmXF1fnR5PgEIGU8wKoqWqAOd6HK5YxRCZ1mmptVQDhpq2pgUJfePQ2ZJT03hjUBi6w9BuBuYKoL7xyuy9ReWyjFJrezhW5uUyGwO1pHx-JiQyIKVoVUJKOaV53u22n332aj7Np4fT_ma_jpMPAf7T3jqtiQiF02bb3rw-lsS3d7fTvFhRb9yma4_Xu2mK_aZpOnd1vc8Fdq-Ou5s9WtuENo-ztzYti1EZ9rvL6XQ5jcYRViUlQ-iM3b-69sERGlJx_TDfPxnvuBYisdZIle2ru_OnR2Osa7qaIoIIKyGQpVoLAVpjhFX1DzJerVX1xcIrxiASAKJwRiQAAEOIIAqKSMYAKAIgGt9vrDM1JQUWqYgEhgQoL7OKGusEFZjRENkGiThFYLaGXtxYXCsSoqICkHPUtKCVc1ERAPLbLTkrwsDogvMhjM9nY154NZ2qAtl2u-NakTxZExy1myF0w2Z7-OzNm81u-Nt__-9_9_e_6bumDe3rz774-k9-senMx_tP_-r__v84Pd57ot_8f__d_c8fuURAdNa0hx1ZBTBNNxw-_9yHtun74Wa7XE4u9CKp1qqir777Oo1zijkvxW97IlMFXTt89otfYtZi8f7Th5JjnmaoSWLtrg5gHSjtrw8G8zxN26FHov_8z__8Mk13r-5--vD-s89eQcl_8sdfa6mcyi----L-4wOhvro97DbbrvEKiE1jCbnI1XFw6E7TRQCRqDEWlHfbXUkFUIOzzlvvrDVUc-mH1jnjrCPrnDWqOgydEVLRpvVocFmX4D2QAYAsEkJgljWlu9ujaN107dAGEVVji-BlzaVIjDLOMxv62x8-TUkrYSnl7fXx_mk2gU6XZV6zbf2aM5CpAmpQDUZmQKoqiaVpQlScc1lVKouCyQIVFcmlGO-urr2hrmsyl3Ga0Fog3G3bKCCil8sCqiJ6dbedzjMqGue4FFJFonWOjXO1svPeGvLOnsdpN2y1iCrcvL4-XZYUMyESALNeHk_WGz908_MJkZZxNs4zc44zqNaUrfUlRsAXUiouU_TBIALX6lqqhXMWRbj94s3zp_dvX7_69VevVXLb-Xc_f7x5c_PXv3t3c9w7H9CYp9OKCIUFDLHo6TyKgA_N4_NFBGJhY-nHdx8f7i-XNRtHqsiqVXSNWREJjLJ6Z0vmMRXQKkUKAzkSlGVOxhhRTaUK4TyvDIiI3rnNxl0uUxOopAwspVZGeX58erx_IIV1fspLSms2u3_5L21FXEvONs613ZhN1zHXqvDw0--643VJucQIqgBgnEWHZEgBl3laxnE5n9OSbKCw6dZxarve966mtaZE1qbE3WFfOVvvmr4pMbdtqCC1ck051-qDvz5uGx_WabbB5VJV1CLuhj6NS9d287oSmMt4aZpeRYzFlzu1tObQhJLz0_17Fb7evT6PU02RiNaYa8l3r18_PTxULqfHU6kcOl8KN01zeb6AqA3eNsEaO40TiBqLzjrmKlWkirUW0KABTllBicA5z8IvZ2kbPBlQ5poSAggoczXGmkB5Hq11isCoZA0hKFFN2TWdGsKXi5qYjTd5TWoN2sDrSspoDJJx_UYV_WaIlzlYByLoDQK1fZDKFa1_fSDnQtfnFLVF5z2CliWSYHB2OS_DodHMUqtYfHj_8PHdJ9uF3bBlgKpSAKtKrZorxDVudv58XlQkpwiZDYFttUYgMCTVsMaZNUYEIWdVoK4px-yDSWM0RKC6nFYFWR8nrcIxUok-hMrghw0IYjCmcBsCGf94_3R1dzedHqvCZugswvy8nE7L17-8m2NusTnN66vrvUFEUPb4u0t8e-j60D-fV9uaMVYi_C-_u4OIa2JQPWw6JfM4VdP4OVUVOMdY0STQnCUEaz0NffPw8fQpx9AGi1iLdMF3g3uexwKWUVMRtGY_hOu77dD5Dz-cPj3lq9fbmKQu06u31ynC8Xqz3XV3r1773v5v_4fvBc2a9e1dT2gLwGzd7bFtjPnqVTNH7nf96eGSxTxifYrzyHEx_m__7v3-eqfGpXkdz4t1dtH6-vaYp7lpfInFGlu4uqZ5fhxd8FwroBFRVVGVeUkCXKsw65JzzIyIz-fZANWqmau1GBOLiG18KuycR4DgbWgcWZrPU7tpm50X1mHfVeauCdYZKRWyqKhpPKK5-ez27T60Wx-6_nY_BB-IzLKuP7x77PtW0LouvHpzMxz64-0OfYDKX3_1ORn37S--DK0JQ9Mfdm-_uN5ebysTECKZXHm46vvN7uHjM4D85f_8NxbJkP7086ftZri5ffPVn_zKEXpH3_3ys0D0y28-J5Lx-fmzt3eQ0zxeOh_6tiGoQTQusW9s2wQi6r0DROdcH9wQ3L71h03fDL7dNGjMV7d7Teklyryk7J3RlMmiD84C0UvFDKmWAgDD0KGCJ5tLIdSUmYHkpWRLRkH7ru1DyLEo4DiPm6Htm6a3Jnh_iUVIuia0rV8Tj8v6NK9r1afL7IKPuSjalPNm27ZNQLDOEYB-_tnhdF6XxPn_x9J_9lq7ZWd62BhjpietsMMbzntCnapTiWSxyGIHkq2GWrJky7BsyYagCAsG7H9nw4A_2LA_2TAsd4vqbrnVoqiuJlmsqhPfsPde4QkzjOAPm39hrfXMuZ4x7vu6WjlOnXNkBjHFrosxhJg6JOtSAG6AwABbLo4InWssBrTb9dB4m-dpGvsUyPn9cbTGfRe56bZtakboiJAIYnQK5p1TU_RUWyMXmlUEqqWZ6LxlVW1Nn2-RWuszOQQd5VqfzVY1l1Z42bYYA9cKRk9PZ1ForfguPXepWympi3lbEXzOue-T93GrmULkWkNwVtlqc8FdPjw67zCEUvOw2ytI7HoRBlADBZGu64RlPj3d399cHs4GGmMw1ue5sooUzuTp2XRmXM2klFy2xZOHml3sDUxr43UOKeS1EiKatW2LKQgLEZV1QbayrWrq4zTd7BFhnc8BSbXlsoFyKy34SI5YZD3PrTUFe_jwELr0zdffOZcAEBH2x2nY9_cvDtGn3W5E0Mv7y5JLrZt3brvM8yk774m8Ab39m--0tRDTeJislnVuCDZMQ0Q37sbCNt3cIKW6ym4_BYOybNv1UpbrMufYpZh6NCvLio7qsvgQ1JS37LxHjGamXF2MBiptQ0Mz8eRarkjOxNABPBfQTAkJVQARCUEEAQ3QxByF50gcmTP7W4kvEJmZIcZxEhFrosoAIFWcD4BgKNrUdTGO03MeiFx05KVmYzVl58j7KAa1cgwJHMVxMPSGRgbgHDkXDwMB1Ny4PL-qpXy5xD6WbevGKW85DoPre0fIRbhJCgG9b6J__O_86Y---MGr28N__xf_XcllW5gsffHF977_s9_5p__vf_yv_-W_ePdXv1bW919--8nPflq3eT1fKSUEYsBtbsI03d_dvv4Ux7ReL7lkZu7H6ctf_Wo33Wzr3A-daFjO5xgiOaTQp_3xe7__u_v7G3BUXH73m2-WD2cPEohU1PUduW7bys3Ll4ebm_l6urk5gsPW2v3L-xBTIP3045feoHL9e3_wM2317uZmvp5jCl0Xoo9NWml1K_mw39VSdsMYQhBuXTdd5_M49Pc3B8583A3zVt5dP7y-ve9jGPvUcgWwrg_G0FiZJfWplTaNkw_OAXjvc2mlad_HVhoAtaaFmyHWxutWbnfj2MfReXTuKnKp7XxZjNxvfvNdRvvq6fx4XdfamuiauSGAg1z44bLksu2nUaot60reA4CPMbe2sVjyTa0CrNzAeQV8vM5FRQKSc3lZQvR9iiJcazsvy7zODPa45PPWnicX1-smKmJ2eppbaYb4XGyTpqDQCoPo7jA8vj_VXNd1jakDhW2thvrwdHn79rEb4vUyS7VtnVUZ0K7nU7muBs-26XZ590HMhFlYvQsG0k-dcwhEDihGn2I8PZ2BiLW1ysfDtMxXUv27v_jR6zE5xMPtNJ-XyzWL1d2037ZSWU7XrbGEIX14mq_X5f37E4X43YdHQweAtVZtHPr41bePse-XNRtAiv06X82AkMjAeWfCpXKplRxV0dq4qU7DWHI21sbcRMBRY1E1NOsGul7WZ0ujD6GU6gMUaXXdxl3Ky5VzWZbsU3Lh3_t3-GFWpjf_xp1D2r5cUVoRWS7ri48_CoQpDeNhyNdVawG2OL1qeU6pU8km1u-G0IVWCim0XB264N3puw_eeR-c5AYiIQZmBue9j3nLhlS31RGxyDKv_a7LS0n99PD4FLzPZUsxeYO1VDUadwM5WudipiH6yjJfln7o21aOd0dHcZ1Ppcr1ev7oex-Daqs1r0t08fT2_c39jQp3-30Mbj7NtfKw71M3lFyGacBcayshBuEGSIcuiSKRo86RQduySfMxtFJKaarqgwMzRQRu6GPJ2Udn2szAeceNZd1QsbG6PmGMLbduGBFApQXvDV0pLaRY59UHL61SSvasKBahEFXYTx2LMeJ4OIR9Ym3kkDyZqXO-FQPvKAV1hA5aqalPwy6Vxg9z-fzzl3WZudGWV4oBgPouXnN99-700asXpXFprTUGhCq6ZuZSDntsmcFMapFVCbm0ygoiBopd7xxhOy_Y0HWRoiPSfNnQhzpvzsXgQKsKGqiBGZrJtpgpoHNd97xSbPMqUvevbstl3i6Prz598_7d6cWLe2n60au7t6f3fT_d9t2lyNClLjlmrSWPfUiBvn0337841KYE-ObuwGwPT9kZEUhr-ng6kUMNeFnyNHRmet4qkA4hDH368LS6AMLcpfSrv_mwm_ppSoFw6NK2tmzQnFXhlvn7P75tJaeur2v9_vdfvzikVx8d_vRPP_r669N__xcP_8v_9R_d3HVvXt13_TSG8PB-7ruwvaBPv_9p24SmKAHW83Y_hIcVLlu7uZkKiXV6XmYkWuva1F6_Ob5_OB3uDuOLPZq8_eZkSClFMFQAYSWCWiWvuR87lefPUwkciG1NnnJ1RETECqUweFe5kidAJI_LWpEgxih_O1bB2hohmpmJKELXdaTAWVIfuep2ycLt-rSkvt-WzQyWh9wfEwIi-XVukhuzrmsbhgEUUnStsAkc99PN8dByRfAqDYjKWrmUoYs-dUgeAgUKl3dP42Foa3ZdFOGP7j7-zV_9-tPX9ymlIabDYXj10e3t7U1w4fXLY2zrPtJuv6_Cu9ubt19-05vd7fe9I1D77NMXXYpjcqR2GIfbm32KbhhTJCKzKUUE23K5zOu7D4_eYQiuLNvtfr_lfLw5NpH3p8vdYSQiURn6yI3Llr0PIUZD897Nl62LnpCco9pqjDE3nktVo_NlZmldjH2KgO4y55u74bTm77950YUEAKz6NC_zUk7zmmLaSrusBZxvahDcct0MKQYPQPj89wrMOfLOXU7bsmwriwJ8_d1pN_apC8F5RBRRBAOEXBqicWPnXAzekRNVAxATMjRhQ-q7qAjSNNeKSFJZTGPfiakZiIr3TsUISUTJYS5VRJd1i6GbL8t0GJtwLo1ZvaNWZd1yqwWJ0OHD4zkE8iFuy9YNHTOXUnbTVGvlWk0VWBDcumThZ_iQqYhLqZVtGsc8LwCWuqHVMo6DiNSc7TluicaVtzVPu52JmGFd8zhOeVtqzipKHpUrKplJ6Lqn908qLCwxBVBVBBUxVUKUVgBIhH3qSJUQWpZc8nTYdSmUWqy01EUA41bTmPK6cmvWFB22dU1937hxKzd3LxB9rWtIQUXA0DuXul5rMzPVptLQwJFvrb777a9ffe-jcUwIYqzX0xxC5LUigEod97vYdXcvb5_enxnRJxp2gw9hWTfvfJ_88Xi4zvXmMMbobg_7bc2IcHM8Ps4Li1yv634Yjnf7fpzAxe7m5nD_stvtEHB-uiCBbpuq1XWh4Ako9T15bEWG_W1ZrsaCYForOeJcQ9-pCQUEFjICMwVFBXTehJ8PbfIOCQCBnDNTM6Pg1RS9YxFEAjCk505FIkRpbNbIkZaGMQo3FJFcfOh99LIWKQ29jym2dUEVRwiIDl1ToBDG_bG1FscphI4CSWlaKyKREbJa0zB22locU543A5sOB-eCglFM5AKBL9xUIHgKfRr205_8gz99dTi8efHy3btvvv7uaavyo9_9_p_88d9lhX_5Z_8ETWsupdWybHefvDx_-15VffTdOJwuF0T__b_zM2s87A_pMLz_zXdtWdGDR7w-nu5fv_7wzdf741GbBB9efPJiXXJp8pPf_7lPoTVFsN_81d_kh2s5PwRtXQBR51xAAhedT8E7Um23dzenp5OZ_PQnP77Ml__kH_7JOB2_ffv17c3x5jBBa4dp_Orbrw7j1CefyAXvjodd55MPgdCO017UWqvkXC7r0CfOEmMcxiSG6-V8nA5D6tDYTMmhIwre1dKERRGVOYYwTr0DNDMXydT6lFS0VNFn66SjT1_drZnv9v1hGDwii6Y-_vLLh1zk3fmyKXz7eH68LL_98jTnrWoTQzZRFe_TXNbrdQayD-8fXUrHm-OyLLvDAQMtpaFzpbGKAdl5XQvrxlyAi7YqMk3TtazkwMduGrsl521ZD8c9GwhYEd5ag-g-PJyHPjbhmkvsfCnNOffMKs5lyXMuW861xJTGw-id46ZD3-fr2o3hfLoi6vW6eE8557pujjAvqzT2SMKNyNdl7vrog4tdit4hiLK0ytIUEYBEhetWYoiKUnML3neg5_McQlhK-eOf_mjsUlnL7rBblhK6uLs_Pr6fL8vKaBbc2w_n02ll0W7or8sSu-58nU_zejkv5HwTviwbOCy5SWEVCCHN8xKcN9H5uq65iKkDnC_ZnDNt63VVU1MoW_beLfNWRSq3ENxyWUF0Pq-AxGJiWraNTZ6eTmQYXNQCAC703Tavrvzwj2rB_m66XjKcuVyvVdkGsgxQeD2v3X4HbWlztWXx3nO-gErLG5iAOlUl0H7s82kZxy4NND_OUmW4uTNsiOYDcuUQByVqtUhmH3z0CZ17_ebV8TB9982767I2LimmspUYk-QthGgG33z1tokiWGMjIIXnDrhbzufj7d3p6USeyAcwJLL1cn0WnnfdeH06xa47PXzoxl2tWUSdi1LbPC9IbpyG2hoopj7F6Id-eHp8ui5zjFGZAajmzROVNZN3FLyp1pp9CKCKCIAGzpRVmrrQhWH00VurxuKjNx9YFJF8CKhsAMzFDCgl5oYq0oSeYzMuaHRtyw4UAAGFpbrxkG5vvXeNOXzyUT49tVxzEQuhf3kjAH4acy4h9rrlvNTD6z0KgNpvf_vdz376BXDJC_uO1KzUCkiFW5qSAyTnam2lliyNK3cKUABFQbQuGdWid-pQthaQjFvw3ljksllT6hMTWBNTVs5dQGkNoqK6-XolNDQzNV4WYI3DELrBheCcSc0pJDPziOcPl-nueJ3n6Nwwjtft-vLFsWz145f3H64bOdgfx6EPyTn1ZGqpj0_X1odYWRBhl2IP7rTmjw67NefDrv_N-TylcTPeGneRKuCylOfRp-tCq01A1el-t1vXcnMYgZsPNA3x8bL0XQQEqfL4dB368XhzTD5--urw4tXt-bx89X5JLt7ed__0z39dNn23Lj_64vVHr-8-2vfpmP6r_-Y3Hx3HX3942t10NW_3Q_zmcR78dHfcZWXa--FmzOuKoJUFyfk0rVwEQICLIjo9HHfoCBDMMHa-lSaVBbFVIe_JO0JHBCpaTEFxbgXQKQAQbGs1QzV63uE7T1uuPjiEKCoI9gx_cMm75AzdtBtj1xHa0AcCkKLd6A6vjlYlDN3L17fOOU-0rXW9rMx6OW_5OrdWHk_z2Pcm4h3VUgMBl0IEjnCMMSWvAkPfpRg-nJabw-7meAxor169_O437yxQ3dpx109DcEb7m939_W2374_7469-89uxn25upzpvQAixP122FNPl4Wno4u3N4Q__8Auv7fR0ig5AlblNw9AFt-U2b-V0Xa7zxkChC877yiLKpTKLsOjt_lDXdeyDCn_97vEHn7zsokMgNqm1ldy6vjOy58sbEaahc4CEBGAG6Bxt3BRdqVpaNbToUEQb827fh0BjjAFJBEvTdd1-9c23ZnS-5HGImfX9aWYDFihNQL2otta4SYphXkqpbbcbm4oAvT-du7FbroW5NYfJp3VrOTdWNbN1LapWVZnVEQEgeec8Be-S94BgSMebSU33495Mu5jMlEVi7IAwxkgABO45KO_IEIkIShan6KMT4S5GFd1yLZVNqdRCntB5IrosV0KXa0s-Xk-X2EUVyDl7F4RZmihLa2IqLOJSADRyPqbovBduplTKdtwdrrnkbfU-1FLRIRIGcPl6RcRxtyOQ87sHF0hUAEzBYj_4LtZ1lpqNua15yxkQDzd7U2mtoggSOe-1VuYmjQHBDztWhcoIaGpxSCasJRuSSzFfZvJORI1ZDcq8-uDJewLxMbWab-5ftG2Jw-h9YGneBUIY-gFVlYtVzmv2MRDh_ubl9XppYsM4gtjuuJuv2zgMpVUKeH9_t5b1o9evc67b1sbRo_eRCA3LMudlq61el3m_3003h7xWMJuz7sfRo_75r34LlZFIuQUfYwhlK6f5HFJY8zYvizKkLr548zLFnaJOhxeAPow7U0Xntms-vHrle399OHtPIQRTQQQfgzQRBRQgT9YEHSB5P_bgTCs77_4Wq2qI4MwUEcl7YcHgzQgQ0QcEcH3vY3KeTEVKRiQTpZSevbYhdWEc0WFISUVNlNBZa8KMz1-8CyJAwYehL7WG2AGhiVguKvo87A_RgwiSU2FVdb5jlePLl9u81Npc3_vgfAimsFzX4_1tbTWm-KMff3Gcjp999OJ0efrlX_9m2eof_p3f-ft_9w9gnf_5f_sXv_yrb__L_8N_XgvXRpKzMYPI_sWL_rDbf_p9ljbeHcEZEGxbefvVtyZbCJ5zJcDlusq23L76-MOHd7cvP2LgbW1f_Oz3PvnRD_NydSG8f_fd07ffeVOtmZ45Hz6GYXf7-vN-n0T4zWcfn98_9WO_3-8Q4Hh73B92ZSuuS6K15Lxu85_87k_HFEstbz-8f3m7v787Ju-8d8GHkvN1XqZxIIBlWfOaRWVe1uNxH4Fi9PuuX8tCng77HbfSh4T0vN4E5r8t6znCoe8cYSAHqk2sthpiMBNWFTVBAAWKoVZOyUXv-hgATAzfPZ6erutprudl-_VXD4_b-vS0zjmD82GYkFCrmodlWZtBf5hSlwBdN41g4mNScuadEG61qXt2WCAjzrlqcNeSFYGcK2qVWxfdfM2OkpmYWc6lCjSAIsoGpXIa0rYuy2VxRqbKhT1RXjOQ5XXj2kwyOVdKM3J1nc8P5-ACEA9D-ubtg4Fty5JrrVsmdC2v0rKxcq3TflfzkufFI8WhWy7ntuZu6Le8osO-689Pl5i896HVVmtxnV-XbehSKXm3v2nc-in9w1_8TnLUdd458p2_znW-ro-XGYDWXN89PKWYmlpTPc3n2I2N-elyUSMgQ--_ff90WtZ1q10KVhsaLuvGouuW0SGAvn33FCOqWTOptaBD552qtMpI6H1ER6FPnIuWhqCttZhSEymllry2UtbL1SfH67I-PTKv4Ax9jyYO_sG_AaGXTeOO9MpsII23awmeQue1SDudt8eZawt9ct2gJloaErXCQCaiPgZULfOCJpfHGVh8dGU-a95cCHVrw27nujg_npltf0h3N7vr0_n8dOl6T4QO6PG8xd6Xpexu9qq6Xde7F_ellHEc12WtORPSbjfN85q3nGKQWkFl2O2e3n24f3FL0eVlIYyOoG5NKqNDEzYAkebINdFtW8bDjnNJXV_ypiI-pQ8fnmJMpoqgeSsEgGYCjZtwzSESlxZCb1q9o5ozoQcw54I2AdWYgnfe8iZ5swYUPJuKAQXf3ey26xxC9F0qy-KIzPsm7AKQI1RTQ1HAIcmanUdUU1NDizc3YT8yMwCIVHCgYH4a3NRL9OrR91FMyAE01sppNwHA8Xb3_rfffXh7-uKLN19_9z5vDRBbY2GZr_Nymo_HfSsNEKvpfNnyVhM6I3IJtyWbslYmU8kZRQGMxDyRKENhEfFdZ4ZWmpUiWyPBfNlIPTd2SFL42Rle3n-IqVOkuNupmSnUre1u9rU2ZiFH58v1d3_xe6f3jyl2r-7v1nn98rv35639-PNPGvPpunTRe4e1KKE30v4Ytrk002qwmW7AnQfm-macHmv1XczaRh-uRXd996G2gkLOC8C6Vhf9vLUUQ0BXWt2WPPZ9CmHJlRWZFcyGof_u3amxHO_GaddP0f_gfkz7HvtBGP7Oz773859-_NVXbz_--KVFe_t0_fHLw433kOxuF_7yq7e81ZuXh7fnzUXUCNtyKSq7sVs_LD96efuXXz4k8kAuxLKxSaHH66asx7t9qbXWsmX-6Hb68GF25Lz3jUUBTU31eV7bGAwMxdTAQFEBahVDJIBWmRm8gwCoAKWImJVcRETVQvCAPud2u5uAVZiRKHaRK09jUoV-TIaYiDqSV3dHdfjx53ev76b7u_6zT25efXz70ZvbN6-O4xBev7qddv0nr-9ubna745S6sN_H68prkdd3-8NxP0z9m5c349BLbSl0TfTu9d1-mALBy5d7B_T6o1vvQwiOPM3Ltt9NXTeAgutDA1Siy_nyTA7vQ_jhm-MNYedwfxxY2oc1B0B0eHO_d86p2ryUVqsPLpBTgLaVXHlMcRzTfuy6QGOXPv_0Bhhe3uwQIRBV1qfrSZq5ELacGz_3I4FZbm4mpwRkAOi8Z7Ovvnt0ISylRR-cp7FLhLYfe1PzzoGAeHy6rPNWzktWc8M0Ru8p-jG4c5HamBWIEFw8X-c1VzPrU5rXOo5JFCrLddm0MbNNu741c44a6zT1T6eVRR8et61xZXv_YfUByeG8lmWrCuYdggE3CSGYwDBMtRUAWNa51bZtteaVXHjeY6_LSg4QSUWZG7O02oYu1sK5NucJDUpjNUCyGOhy2VQETMFwq7Xkenk6xdSpiUljMS6M7vl9VcIYWmnO0zqvwjaMnZnmJatpSh49bTU3bi64uqwxJRGpucaQXHCI1FptpfrgWq3Bk6iYmvcRWvMh1VK7aSRnwQdh84igEPsOUZlr2VaXokNABDIS2dA5F0itudQROG3VxbRdl-64MxBRcYQOoazXrovaWLiZgZm5mJiriJyfrv3xMJ9OeblyKfl8hm1D9N6HOA3KbGBbWWLXI0E3jLXW3GR_2CMCqoYQc2nH465sq6nupgHNond5K_vdMF8LoKauPz_NaLgty_F275zVLKmnl_vdYTeJaRUJKex3Uwhe2GppQEZkdVsPh_113QADElzPp-vDO3DY7_rxOHX9FHwcxun03YdhHJ-7v62KCwHIkdLh05eWmyohOSCEps45Kc0ZAaGaOhdcDBT9s_DLDHzX-ZQMMPYjACoLCBARbxnIEYEJPGsftEnoEqDXJqrQyjOn38fOt9rAUYid63tF9KmPXZdzRXQ-xJC8tWbCROgi5XW1yqFL5mNrxfuE3vmuU7O8lfG4dzFdPjykvjNMNy9fSqsq8Hs_-92fffGDH__g0zE4dW5p8vLlzR_-_k_-23_y3_1X__yX_5v_6H_yn_8X__6v_9Wvbg872k9vf_NbIrp99ZGfppef__jxy1-VvFGI64ezN7-cTkMfLo_nvh_uvv95m8v3fvLjdD8sl-14fwfen96fP__pj8lwOV0shK9__ddty8C8P_bM1YcYDvvuZj8dxnI9AVrqY-XiiVSVpdzf3Qxjr1w_-uTT9fL4dHr8-z__eUC53--dhV99-ZtX9zcvbvcegJmnrlNjYT7sxm3N87rlxi_vb6N3XYi15fvb_Tj0yzw77w-HcT5fX9wezHBZLgCoqg4IHJEDh84ToUGXgiJcl6VPSZhrY1UUg3lbhqEfYhLhjlwXEyDOy3rZ2rcfnq61ffP-8ZL18Wn-4fdvvnmcRfR0WSyQAWIgJHeZMxJO3vvQh74D0eu69btJzBpYbq2CZlZHLjMvtQoQo3nvAxGgE5XGTQxbLTVvxhJDbGK1NUCohR0QIszXxVQRTIURqY-et_K8uzqdTshipnktMSZ01Eru-h4BEWzdyro1MFnXzbj54Mv1XNdN0QCs6zsE2eaFPJiaiJq22KV1Xbpxaq2ytJiij-G6zGgN0aWpr6XuDlPO1Uxv7o4pek_2xesX85ITQa3qkv_weP3t198N-_3bx8tTyafLvJVaVVoTAzSwD0_XYTdcl8VEmvHT07WpnR4ec6kCCAg-BDMwUFCLnd9qNU8GCqCgHFxAR61m72LJa0odi5Qta61gmEuJjlSEawW0WgtFktJazi5Y2cScI4IueQc__2PcdX5CP8Hl3dkHB8BSSuicS6Fel84F4iaqhuAJfUqqQM5JNZe8NebS8ro6dDFFcJqmUWojMx9SW0sIXmrLy7I77nfTVFo5n67ehf3hAGqF5eWrF-S9NIldnM9PLRcWE1UfU122gDhft_1xQNTlupqDb9-_vzneOkdc283Lu3VeyUcR45K360WLVOX98Xg4HrZtG8ZxuV49BUMLISC6ktdp3KnJbjcxN21S1rUbO67VO8c5KwKmUNdCqGDatpUcuZjAzMcAann-kMZbZogxgLKhqQqLGBp4ZwrkAzdmFiAVMELUks0h4fNhqkgECC54iF7y6oYOFQ2UzPw4lZxra2k3lpwFwLzH4MPttJbmUihNRC3e9O28ytPFHafCImrRdFtrdnoch3Vbtnfn59v64ZtT_XDavbl1EsmhmC1byZeliwiNrdUKxk2xFe-SsjgiBCNWBAA1XrJzRDGAIxDmJqCVhKE0cOijQ7HovdbGuXojZ2hEvhsAnvOl5IP3MVwezn2fuEFp5fbmkLru6ekhOAdA53lOfS-VnWpK3qo4BC5trfXD6TpNg6H_9vwYOtfUNmUIznnngDi3JrZLUautDG92ScgtrcYYRCREz-CWNRth6ryCHaZeRZ33udbQORciRPfR918moul28IR5bj3CFNxt39u6yQhPD-v97c3D4_VmN6jKbT-UaqVIv0viQujDw9OytTbdHde2uZg-PJ7WYtPYPc0VHF5LZqfVqKmdrvOYopq-fLV3MTw-LG3brmsBNQCLiZoqIj6nnEXalis3CClV4aQYnc-VM7dtqxgAjZoKEKiCqjkPKhwcxhB88I4cm4UYa95S8izskHIu4zSICJo5pMPdzqRp00tu5B1Xhqaabdtkm-W7d6e__O1357UuWS55-fOvvkK2948XkHae25DCbuxD8I5cCAEQsxh6tADXNbseubaQnKK-v25vH84M7ptv30PFJi2NfWttW-rT0xOpXU9L5wAIDe33_uDN3gWpbb8fOudub8dXx-mL1wdu-u3bx3ldyUyFd7teKqcYQODmOH3--QuovC3bceqG6FOgdS4xeFEDA26qYqbW-4gAwQXvXQrOE3oK3pOZEjpy2JospZ1yHof9nLOpqUjXdVxacq42lsYs-nTdTvNK0a2ZzXkXQi48z9uXb0-NpZT28HQFxFza-bI8nC4pevWYUhhSYm3ny3ZZ19h1TaTfTWAWjMhhH8NlXkstSpBbnVtTlDVLMzR0iphLvZzny3ldag3BG9L5dNlKm69LKX_74gdEqsbCKaWUQt93Dt3lsh2OgwgA4WXbYkzLutathS7mxq1KSE7NTKQKM6hH2rZMQCG5uhVTWNeNnK-5oGHZGnrX8jaft9BFUZWmXJswX85X5wNza62t55VNCKBWDt6JKhBxa-jQuyCtTMe95IyEXCqiaWttm30I3nsXQ6sVzaw10GbMagxoypymAwCDmJmSGj4jlysP-x2K1nV1ZAAABqpsIjH26AhFrGSHAORN_lZ3pWrOe1UhCsMwpV2HIsLc8hZiMEAlUiA0UFQfUlny7nhT19UUdsd9Xef9Ye-IYgzRu3HolMs0TKXWbV0f3z8M07gbezC9Oe5vXuwPt3tgQpQUw3y9xOj6_bRt7bLkdWuH4253O_JWrZZ-N_bT1A-D996MeONlvgR0sXd13pwjRANVNKjFxICImhRH1k270A0-hf7mVg18cL7vQgxc2KdIgXyMzgcQ0cIUnHMOyYEhqEppQA5jpBAwOHzm8bNoE59i6Dspm4khQhgHruKQfAwUA5JzngCNHJkKIpEPnAVjil0vZkhA5NC7uhUfEwD6GNKU1qcLIICYIToK3TAI13VZXAihH2Popld3VjnEZGK8rjH1Am463vqAYRg---H3_uSP__AHH9-t2_I__tXf_OW__htl-fTz1__Dv_ylC_6__I___b_6V7_5x__4z_7sz_67f_1Xf_lXv_yrOIR0sy89lMty_vab5emx6w7Syt3Nzfuvv-z64fJ0fvHp9w6v75eHR0KVkh_fPl2vFzDc7Y6ffvGFSCPvzg8fTg_vUa1tqzerTfa3L5ZzAXS745iXTOj2x0MXo6Gb9ruPP3rzox__5ItPP_dOvvfZ96TM0eHr41GkTV384pPXS8lPy_XlYZjGfuyGUvI0duuSl60E73MuHt1uHIY-EhJwO_Tj2AcQZbAYvDLf3xwQoDGLaheCI69o3PTm5iY4CM5F70Qll-qTd96BwTB0phKCjxS8oz7Fbdt2Y0_kyBOonrbyzcNpKfL1h_OcRTycr3w954fTYxUO0bGij2G5XNVg20rsYlV1gSTLupUwRjVkNAs0byVLRfJKSJ5UtDVZlpU8HUK8blmY4zi0vC3XZRoHQTKgsmQTVWFn7vyw3Lw5lKUsT2vqAwFxFQRzzpmz8-MTSFO11EVDLOuC5KXJ43zdjdPT0wlM1URVYnTLwxMIC7fUdct18x4J3fx0cQ5bLY4or5sLgbznVkEBAWMfwSw_XUzVx9gNPRo0KcnHzodpSst1vjxu_9bf-ymC9THM23a-bv_kf_ib-_vbmetlzW_fP815m_MWUlcLRx-3dWPVJracrq206XZ6fFqW60VyVqAmHLsozDk3NVvXlYjQwbJuMaWyriBIjoRZ1fKyqhoiiclyuqgwgORtJUI1cV0nnPP5DCoqRarEoe9ub3wXQgiaFwc__1NgA3B8bWRWz7NUtfO7sD-GPgXy6-lp3E2hT7Ku3jtzoSqE3RRv9q1VitEHx60hOecRAbixHyMzq7l-mkRbeO6oh5Bit7s_dONweroAwvFmul7mx6dZre4Ou---_ZYbm-DL1x9t22qVnSdVc4QYwnZZ-i4ByIsXL88fHo0t9f31dN4dbpDMOVIWotBPg6m1Wi-X63g4PLx9t7851pJR3TJffSBhRhI0dzqdvUrfpRh9KdXUBFjNkJyKcGlExDkDmnMeECgEzgVERMFUfSQDYxZuzcVoqLw2RQB0ab8HMhAhJG2mJsYsiIbQHQ5W6zNcDZxD76AxEhmoqHlU8MFSghQxOmmt1IIIBhD3OxUxBCRUsFbZagPgUht6cpGIgCK-e3dtxi-PE3i_rYtoffn65dPj0_y07u9umFuupbJYa06Y1MSUvZFYimHNufO9lDxMI5dKwZFDzWKAFKNLgRC4FJ2LY3YESEQpcG5d79taUCVhMBbfd2YU-6Hrukikyt2Q0IBL_fgHn0ir25ofPjzdv37hg-9iWOviDBzBOKVSaxHZ9yl2HgM8bq3UFgNOcWSuVy0PyzYNu8eH-cU0fLYf_vLh_BXWw9BtWVOPc5HSpBVNnpbchj4aiiN3qa2xArienLQ2HTtjIXIA4BF3Y6ibfPzZi486v3c4diEo9AN9cz1_87j86NWh77vmICu64M-n-fH9-eG6hqGjkHb7HZdWS4lj9_B0CSkB0dbUvHvM6-52d9mKIG65kiNujEjffPcgqgrQar0-PHVdUtHcjFVNDQBLzdtaXfJatTael23qdx8uS1Vm4Bgic1PAyuJ9MFVPmDyhQ1VkEVMAMgou10I-lCZd7HKpKflu6LatgHNrqbZqLc3HhAHBAJzlzKUU9aiow7E_3gz7wzjthnEYbsdRlbm2XGsuXGu7zMs1F4rw7YfHx6fz09Pl8f2Zc314vzpnNZend_OH8zo_zvshBWFuzUcAwPVpC503NO_jcOw__8FnKaDzFPrwZhg-vh2PxwlbdYRDSp1PqO5m16_ZQujGLhjgfF2GoculHPdjLdUjENhPv__xcRySo20u09CF6JOPpTYfPSGYqgu-MbfWWJkQVfWT-0OpbKzoUExUrJiSi0_Xa86ZQqiliMjtYa9NnkHpbz-cVxE2uMx5ydV8WNb8dLqWJu9PsyA1gbmxAF3nXCs_6zZLkXEc1mW9rOW85FIqOKqlnU9zroWiHxEfPlznvBXmubEAzLm2pki4bU0U5m1d1qJqGBDMlK2prqU843HUwIfApo5IwLou-RDNoGzFQIcxAkApTQGA6BkorWYixpUVlACu56XUlkvd1tbUSi6eYFtzNw6qDGAGJiL9OLVaWq6mHPpQG9daidywG7a8DrtpOZ2J0KdgCuTITPuxm-cFAIXZOxdT3zj74GvZxumgpnXN3IrzoawbmKpaN0ygqiyp78qW1dS7xHUTMRUeuj1aA4OWCwKhI0_Q8vri5WcgXHJ5FjaS85yzAQxDDyLSMpkDsNB3AAQsLjit7Fy6--J323xeTw-oNO0OIpVzS0MSMAJqtZmjkAKR45qji7VyN6Xd4TCv9fawSyn2KX373dv9MJ4vS122sU_H28Pp6fy3cqIQTqdFsvZDzEuOY0RyPvhlzbXUum13t8eH07lumYj6rhPRsszTNFZuKXaH-1tHrtTqfAS0ELvGHLqu1ZaG3gzR-cdvvr7_-LNWG4Bsy6oG4_EgTVLq56cLL5v3ngxMpK2NPJH3zOKIFIz6zgWP3lMKIXZgZqz0nDpzDlAR8Dlg142TqrUscezRBVENIXa7fd4WM1RTANeNUxpH59Ph1X3NDdTQ7PlxCyH4w1ivJSXPuUitz7piIkREUVEDCtGFCOhCTCa8XtcUoguECBBjmoZ-3OV1u727_fkvfvL5xy9rq3_2F3_5-Di_fX_6-3_391hbVfjk45f_p__j_2Nrs6fw9PiwrUv0KJW5lHLafOcvb9_f3L68nh87786PTyHGNEy747Hruvdfv-XSQtc1bSmEFx99_PH3f-QIlnkmo1__8l9d3j2JNAJ89dkn6_nq03jz8W0auul2R6qq6rye3r4jBK51mvrbu8N_84__GaK8enH30Yv7slxf3d793k9_-OblbSQPpg_n04ubfdfF6MLhsAuezGBdt5SCdx7AwIGiAaKKCMJuSqiIALup8w771AFQrfV0WabdYGq1tb5Pu_1EBGQQQkA0VSulsTCiI3QASuRaZTOIKZhqdN4QEMB5fPtw-u3D4-Nle_e0XLaylmwhPTydcmun5Toed8QmbJHcsiy11t3Nfi4M3mUp1-sWp27Yj6zKZOfLzACKxiKGcK35uq1IvkjjxptqrVxEmBkQH58ego9rFeYWk8tVTg9nReo6lzw9fX3q-9jf7XhrMZKJuYCn95dAaK11046ZTTT1A5oQQN_3_dC1XGrJ62Xxzofg1_PsET15QCAC5zDPayBywQmLtJaGwXuH5NAgdCHESITLeY4pDtPYmrRaDa3ru5SCI_Axemc_-91PUvS7ru-7cF3WwjDsx3cPp2Gcfvvtw3m9qiEqpuSD91NKv_3uHRiKGSHV0ii5dx-etmWNKTnn6tpUGIBaq8xNhbWWUhuroaqW4kNQ0Lo9k0yz82E4jNu6ta0CAiFBCGXbTK1A4_lCpqKqgOPNwXWhLLkfx1qy5M3hH_2Jn6JTRJA2b2AMpm6aCDxncQ6NRQt3IankujIH19_ex32voDWv6_t33oeWN2R23tXGWtn1Xs2kNSQcjjfD7pBCmOeFpQGiMoy3R6i1LvPuZt-nYS3b2PfHm7vj8e76dMrzgk1aEa7N1LToepmd8-cPp_3dsdZtP-5LKQjaD4NI25bt5sXL8-Pp7uXtcp3v7-9EgQgAQKXVXEOMZdvIqB-61y8-u1weQCUva60NCZ0PbFJLqbmAAaBaY-9QanaegIW51vlsahACmPX9wJVj35mxqbbcANj1IwGEsZPSAJGcq6UQAbD4LpmqS13bKqC6LrQlO0foAsUIrRGiNDFuYMJNbezbtlQt4MlU4NkZ61G4AnmKpCzek6oE701FDca-n68rNzve9fPD07v3jyGk6OK6zg0txW59ut68OSTn5mUjb3UrAGKs67L6KUAVUpO1mFSHyJwdhbo1CqSlKrM6B4imLLmhiCMgQwdkTcrT1QEiGhQhAGNRFZ8ipQiqIs9PPsXQaeP56akLcZu31pqLXa4NHL68P5Z5-95nr6DwX_zl25DAd27XeWYMzgPiVq20-urlkYveTTuPOKZxq-WRy-vXd9-eyr7zkeS7U6aES9Nla0bQWAAhAZTS-l3366-eauE39wcznddiAJUbAhCgVrtmttJ2Y-JcWeyQXB_Cizhct7pUefny8Mmb2-XdxTGPA6G3x8viUlxqW0vZ3R0R3Mf7eLpWrvmp5lnKNPXcmqipsrcADlLnDS2Nbrfbv393Ob4anx4vUBjRx5QUlJwz4C03YQMPwqaAhKYKuWQBbU1T9DW3ymgAY3DPh1EM0RBYtbYGTj2FPiY1o-eoLgIgJ3LgSCsPXVCwofPjbgjRowdHtOti3eq7-fx2u3QqiNgPXddPU9_vhxGNwSAkF3eRVLWxI3g4nbi1-bSSoW4tpTjsuvGYvMff_uZdRGwgXaDk0QAPt8dS8nzJ43FqdSFCBYid88Hnp3PNW8llCHAXQq9wPAwEVGtL3hNh14-1ldf30xDd3X5oTV_c7g9T6vvoEZOn-8O0H_q-D2Dak5vGjo25MpANXQcKtUpKIXjvCacp3e73QwrRuVwVEdZaz5c5dVGdWwvXWudl2w0jEiSiSO71i1tpombV7OG8nLfNp1SqmnOGblvz4-Pcjemc69JqVRAgVr1uWxrSeEioOAxdzqUJP13X82kxer5_qbEsW7m5OUgR8kDBf_N-bohv310Nac3PVPW4lRIm35q23PLWcmsxeAIohadd77wHotIYCb3DEMJ-mkxVuamKI6ds85p3-31p1RHmUvKaj1OPCqWycBWVJnxds4_eEXIuddtYGjp6ePvkghcRAAgxIVprFclVkZA68OiIonPW2rqxtBqj42bGCg6scavsnUOHpZQhdarMrSHAOi-l5MqN0KGnGDvl4sxJbSrCrQFQKS1NY-p8zc2UEaBLe5OmdVMRQAohiTCoOSITW9erDyFOvTZGs-n-VtYsiI7oWc_SaiZySgSAqe9M2Xk_vXw1f_dbzpkQhGV8dczzAhCOx3tDAaAQve-6dNi9-N7HbZmZGzlPzr14eVvL1oE9Pp7F7NWruy6EYd_3MVSpzSh1sTV5cdgpWGtNpAnLzat7A-tiePjmw7gfonPbtoboh9SX0rbMwziiC6hY8pb6Xclr5dqn4e71HYtKYzBDJELfCh9f3AE5KWV_e9_KRs7Pj5fhcExdp2wAVpYteufH3lh4q8oWx0TRKznfJfJOwUFwUhtUgWb6zP43ADHvQ30mITo0wDQOYRh8iuP9oZ9GJPPOm4i0pujAqEtDN00UQq2c-lTzRgYxxdAlEwO2NI51zegcAYlw6KISIplJRXJhGrv93qeuOxx2t3tUaNuW-gRq1pTNhX68f_2i92E83Pzs5z_6o9_5Yc78y7_--rdffdhP3Rc_-97XX335z__r__Hbd08Y7V_82S__0f_q7_8__2__n7zMxq3z3mrVJv0Ut6drcl2rmw-hVBGG19__VHJWpJI3kba_2wsIYvejX_xDMxunJNtyefjAdSY0EPn0i8-vTx-WeenGdHz96um3b0nNp7BeFma-vXtx--JFiO7Nm08P-_Gju5v7u0PnlHP--suvPnpx_8MvPkWUz17sHeKybTHGF3eHV7fH_WGHBsry1Zff3d4eU0rDkK7XdexCitGTW9ftk1e3U5dSdGWT4DF1PjpfSuHaYopG5BCGqXeEJi2FkGJUVWXNrRGhmgVHnsCHkLeM5AjJu2AAMbin8wIAG-v7x8u1lsel_ParDxA7Nns6L3OpW2vj3b4WEbHYxW3L1qyK0BjOH05ryWhwmbfxdgIgNiu1ba1VY_NeRKehm0veWjUAs1alCRgLg1rOmyHGEAiAS3Pk9vvu9OGEoLzJ8X44fzdLri45AmrzFtCWywYInAuZAEtrHLz3iFzqep27Ydgdji0vh3G8Pp29g25MT2-_7VMSFjVFNOc8oXEusUsqjbwPoSOwbuhLyY4o9QlAyzWjw26c0AEBtFIRjAC65G7v7l69uotmP_zk3nL56RefS60Yw4e1rE0y2HXL7x5OXz2cxi7t-qGVlZSq1q-__eAD7Q6Tms3rwqzLvAJYaTJ0gxiT96rsDOq6KTORuS7lvAbCsmUCRHTbclUTREx9RwTbvHGpXReEmcumwq2WVjIIS-FnUnO1TAbe-7rMy-MFuLj0x_-AfFefspoCahqDzkUbd33nCVplri3FuK4Lby0d9hBSlwZCksYOQ9j1z51d8i56n8Zhndc47G5vbw8vbvNaKFLN65rr8OIgrdSaa2GupeUaUqRAl9Op1VoK9zGmGIhgK7kWpkBScyvNyHVjBDCf3LYWMEq9TzFUFueiVAYFLaUxP7x_S4qiMu32hi6kQMGJqCjHmJynkvPl_BC74LwnApXGLK1xN_b8jDpV2R5nJAwpKos0Nm5ISOScd855cyTMzhOokXMm6hyWnK0V79Lz64OPwadEhNoa2XPLxqFDpOc1hedWvUOuAhRAmYBYGyIAmDAOn7xsawFAR05JgZwRPJ_NZgABjVnZhl1qSzau3X4CEa5c19pNY3TKuV2ermVbb158fFnK60_uH759d34833_2Ypk3UVMxValzRnKWNSIZqFZGIWhsosYC5AXVeS-5uRgAEMy01OScbAXUnhdPRICVXQhaRZWtsjCEcWQVQCzrErreOUrJYy3beZmv63SzA9TL-fTq45eEQTLfDF1PwXv38f245vrV2yWl4HzIrKh23I2EYZ3X_jitkjNL34WtlBjSd6dL37u__HBhUSZSxhh8Acu5NiUiCmA--cZ22I25VhUM0RfHmTWDsuGlyHSYdrddq62INmgGbd-FHkDBXt8MoRuWWkMp56X9zeV0Oi-H_WDRE1FlPt5MA2re6pbb_cupNun7UHLb1nWK_bwyObeWFqNHBwZ4etqEWUkfvruul5WC37a1qgz9wCZSxQQMrLLELlbmlMJ1zehIDZwRczVDI2TTXGrqUmNxBAbgCYMjTx4RhSU5L8yVJfq4zoU8GVtlRfSMJEAoWHLTZjH45bxG56d-ugs9IJZsdZW8cs7y8N1jywWYt7XlJ0lddN5z1sYwpR7FsbS7-xs0K5m_-2aJvRu6UAo75xvZ3asbrm1ZuJs6ivjh_ePt3c35dGlLCc61tQ5TjDH2XefQ_973Pxp3aWnsTM9l_Yvf_MaTR1MuPPaJENYlP17Xvne309AHPyX_-v7Ye9cFFxyZSCIgR9F5IvLO1drenuY-ee-o5Zxr2w0dGSASqqHDvo9ffzjd399yVVYLXZiX3A99Yy65dMEdph4BDEzAHi7zec3XtaxFGsBW2mleL9dNEKrqdc3o4zxvLqZcZatNWPd9v2wNVJfC52X1wcfgjTDXti7rlsvt3RQIgnNqSJZyk61W9GHJqwlWMXBUm7aiXLkLHj2JAQIaQEhBxJLzsQveh87H3qdnlxmLNG6INHSptabkWs3euSZ8PV9Kq1tulXkrpbEaQgwJCKW0ujauNfWp5uq976fOTKZhyjl7csaqZtuyAAIBcFNtrMq1tt3NsJVacgVy5FFadT4849EQwQVf84aEREFbG2_2athKcTGqsIqAQT8euDR0ZNIE1KNreUMfpFU1BvJaN_cMYFZV0-iT997U_pZFgVC3zI19CIDItcRxIEfb9eJC1NIoBFMTlpAiKtSqw_EFotXLBRW8d9yaCISUmnJrVdSxSOpDZTW2Oufbm7vPvvjh08PD8e52vcy___OfHQ8HcXZ3sw8-pBSXOYvx0-m6VhY1ZxoMci3yrIl0rpYy9oOLfjcN62WdT_P5tApoY0ZDBZ7PKxqi6Xy-fvfuAyI8Xdbb20PJeX9z28XY98P9ixepn8gFBAeEcejKmsfbPYXY3x8BIPjIjeu2-OgaVx9DExnujvHFoCptZd8FkwaG4djpWonIJ69mQNaaha5L057QyFE37Lp-GMY9OCqsZePQjZxLWYqLMaZOHHkX4jiaIpdKPjhErW05L2St1VZzjX2f9iOLcGs-diFF5Yre1bkC-RA7pefQhVAMPiUubT1fybvjcV-KsNiP__B3f-cXP-F5eXhaf_jjz__0j3_xr__8l-fT2u_HMq-v3rx499uv_8U__Qskvbk_dOOI23Y6PW4PZ0eCLACWulhqLbmRITi_v7lx4x7N_-Qf_fzbf_03ea3p5sZMu77frvmjN5---eRT0QKtfvXXf_3uV18BcCvNVEPwl_MZyWFIh4_eYC0hkik1sc9__CM1LTUfDod5vsQAYJqX5T_7T_8Dp_YHf_i7uy59_tmblze784enw5BakaVsn33yMpIj0cNuAobS6jj1zrkxded52e2G0zzvx37o4qu7Q-c9ma05D2P0RKiQa1uWLZcWvTscRg8YvXdEkSIiAljOtdSKzrEoGnjvc-NWOcRoCs55UU0-1NaUzMXwm6_effnVB78f3z1dNoDrdSlNl5LVYS7tOZQOnhiwqS7X87bU4Tgu12sMThBU4OajXaucS1tyFhCITlidgQO3lk3FeM3Bh7xlABIRAHEEDpSMtNRAMabw9OFclzwMQ2t5mMbH9-cYqOu6VjYCqMvmk2slL48XT2AqT2_fD1PiJiVXDORIy7qQc0teaikAup0vRF5qCSkgArDubm9NlZznWlKKaPLcid_OFwrBwNXr-jzQVBNllsZc6t2rW0-YAn7v0xf_2__wf_69V8c__tFnHx1393e3FJCFzXfLlp-uWRy9ezgLwOOH02E3rWt7PM1EjpL79W--2R1GVrzmfDld2XQcu-vDpbHWVo2wtSpEeV0kM6Bwk5wrikjJDkkRzg_v0DkT8D4oN2lS8hJCpOCvT6eQOgMmRyCCzKgaEinnOhdMThHy-eoJxy45-r0_qnkDAN-jRxJRPS_AgoRpHJxzVtvydIpDr4DpsPND4lJ8l66XeXc4iFldL8AyjF2rFYhin6Kjy_mccx7vdnVdaqnzfJmfznXOeV3m01nNWGD_6vbp4fH0_hp66vv04eFBGr94_WrJueZMVpfrFlK3LHkYp1pzCvGyLD7EvGyOqFb-5suv71_cBU-qlvpkSCXn9bL4vu_HHkwBbX93XObVuYBo5IjzWnKbr7NzgUvdTZOCtly1yTCNeV19it55rbWVYiZg6p33ISkCEYGBmAKrKTpHoEqEISYV1tZ8H9tWMEZTBVMQMTGVaoDg_LN9xQhJLHSR2Rw5A6n5bdjfQhN0SopNDABURUp1fVCFkKLkAqDknK4FSgUz15EWdoDSOE5d3rLlXJWBQIsmH_LjU2kS39wt5_nNi7vHtw-85nE_knd1q96TtOcYuQNHrWYREW4QggV8HjMZGG8VawPCsBu0NGtVt2K1gEpZzxYSEUlRGgLXFjovpYY-oQ8-BqsFzErJu8NxvlwIEMHIYZPiKWxrpS7dHfetFGQbui4OqZq9uDkA6Fo0Dt3jeXl_usSYkg-o1oQJnKqgB08OQIu2qjB1cW7SACvopgKsIcazllPNd2MvBVAx9l7QlcYu-OSdKbKy93YcBlElQK5aa0NyolK2Gocx-aBAHuzxYQ7R3dzsVJUNC_Nu36saYcy1Zm7owuPj0tAFR2XlfZ_mpfkuCYIptCrrsl1P2QWnpg9vT7WJMaddykuWLQMKArZaJAubicjClRy1KqKgqMImAAIWUyq1GfiNm3l0wSFq8t4AhDVGP3adiqYYSmMxC96BCqqa2VI20wYBoveSqx88JQDVbc3FdG1Q8iakLsVhN6SboKz9LpZtjb2flxIPXYjQajk9LKa4n0YAutkdjrdJoK1zDVNyA6DDlJyB-CkhARfRrOOuR6Pr03KYJqktRD_1ab_rg1mX3K4fdmP_D372yYDmEQPaP_lXvz6k_vXhuBv6fd-Z8HXOY0xd51-Ofd7KNW_bxndTvwvPxbhWS5m3davVOc9qIuIdlSZ3-yk45x1NY__6fn85zw7R0FrTvovr2s5bKyxgMM-rmcUQtzXf3UxvXt_t-h5YgvPLltfCa-PzVoqCEj2dLuTDurUt12ZaGs-55q1RCKJWpBE5Q0hdmucNyLJw3jQN09CnwmxAiPSsrfEuillrMudSuIqpoQngWnJK6fR4NQVR6ZI3gtRFUGuVySE5QoQqAoRkZmqKhkgCwmqbtOh9KTXXxo1brQrovU9DalWYpanktSBpYV7nTZm5NkKLMXFtAiIsz2id1sowTdt19iGYKTh05MAU1OqWVaw2brWt1zX2iWvTWksprVbhhkamKswgGmPgmgXUBWdqhGimIU3KmZtwrcN-RwBAIGYeCclxq_1-j5GgKahKK4hkamSEHkzNDADUDFSNnE-7vdbMz8CDXPrdzrjWJftukNbMzMfwrBPw09TfpuXhSba2--j--v6JPPlhKCXv7-9LzWC4v9t59GpGYA4QtC3z9ePvfRxDmKa068OH9-8Owzjthqf3Hz58uMQxhtj1Uy8CXJuJmPH5sizXrYJsy3Z-OjdphF7Jhn68e303DLGVVnMxBUAZukGkdX083hxubqeYoqoNgb75-qHVspVyuL0lIjZ98equ7_y8rXnJw24idN99_V6bIOH1dELyrVUXkgCYGaHjprwyZ3ExACsCOh-tGBqgohkBRWUjnwxJgdEFwLC7v0_j4GMwcMGnoeu5rm1dWdFAFB35dPvJKyLXHUbnqKwLquXl2nXJUcDgh3GstdStNpHdi_sw9lKzd54bxaGfXh3DFDAkFXGEXeq3eS7Xs_fBDBpzZv39P_mjmyH-5l__eq36J__W3_1Hf_rz_-v_5f_lvP_FH_74fJrHfTpdnv7F__fPS17T2Psunh_OeV6f3j0GIGWW2gxABVO_M3Ix9bevPloblzXfvX7x3S__EkNqrZVS5mt-_frjn_zi56nvMdG3X369XE_KrKr72916ucbUA_puGIfDToqatNN3j8NufPPjH97e3LBsfRqmsd-ul32XfvHzn19PH6YUvv3u7effezMm9-bVXeet5dJ5d397jMn74Dwhr2W_P3BtWy61tZhSDC76WLmxtjcv7zsfALELISVfS-uHzgdqVRSsNdlYxrHb7zo0UAWtnEIkRBFTtiK81qKq3nlCqlxba4AgouCcKBNh47puW0hdYX66zBLD19899be3MQEIrstWm16WJZfm0Z1O15RSKdy2rMw1V3LODAypVfFdrE0V4XJeAU1EWmVW28e4rnOu1YRJkYA9ubplU5PGIQRrzLUGCtZaK9UjyFa5tT5Erpy3bdiNrRVkUQBnuF2ubavRu7ptCDbsdmVduZaSMzlEF1yI_W73za-_9J60lJYzArAqkW81x9QTogqLyfNQ38WOa50OBwzoUzIz8iRNXIi-67dtTYQOoBtc3eZPXt_97_6j_-Am4Mv9uAv4zdOHqR-C99O0u8zzuubTZcm5_fq378G5Unm_m5YlN80IZM64tOPdzflyDT5cT5e8bFwrBt9YqjQEx2Vz6MqWwdiRVmGXApLWLZNHNW1c-75DHxyi99Rqk9L2d_dNijKrNWXL57MzKdtCiRDAmAlFcs3n2SeHSNuanf3OH4TdYGKhQy0SIvFp9sH3x_H6uDnnoDarnMYOjQgcEazXbVtXUHMOuRS-riZGBgqGzrG0Mq91zfPpss1XZel2L-pyIlSfCMFRdCG69TLPD081V2m8rXVd1laylXL68P7NZ2-GcXx4ujzX9TqPdS3DflyWbdgNXKoUOeynZVnS0EFjANeNu3VZnif3oU8xds45NDseDzH4-TqLqaqBKqAzNXrOwYm2bRNWU5Zta3UBgrZuaeprzp4c14qIBtYat9wQqDvsZdukLLIuZuCdb03ILI1jvqzdbmxbRgQCktJIlUJwCAZoouQcm9Hzz1CFcwEi54k381OnS-ZSUM1CVEcYIzRGAFM33B3anKEIekIHRgCEgGhicl5MXFNxY9RS7bIqIItEbyLK1yVN0ETIhzevX5zfnZ2PVTSvmzUmEDMDDNADs5AZAisroQNWcCYBobDjpgbmvKk4BF6KJ0MicoGQfHCaKyWCBiACrCH0gGQoZcnexeBc6EJwbltnMiQgH3sB7I9JxbbM_-AXP_ju8XJ_M0nTFP1yLURYof3VV--noTMWNXi971nBmTnndi44xB_1HWCoSAbQTJqalDb0HYM3UQUZ0Y2IWwMIjnPRWh-tfai1C4EQeu_6lIQtGCrXsY8GWERWtKtBPHTnVh14YXt96H1y5zUfumhK--h3--HLr96z8M397tv3l4enzRyGLiznckj-OPhcrJjspjEGOp-X4-EoHl9_dPP47rSd1yZiCuucwUxUrRQwrc320_B0XVBVQM3MqvjgWtNScimauQlhUWA1wOepNIYQwACRvHd93z1rEc3MAFTARXrGcWAfffKtSPTucp1rruhou2aouuW8ZQYxh8Qtr7Ohx-3CxrSubbtkDPDN3_zm5Ud3Zd4c0Xxdo3evPjtcPpyFK_c0GL797tLHINqi6z1gyRq8vz5cMUswIoQ-xVJzn4Jw7rsQYjhOw26Kt2M3RP_7P_n0x7dT5wBV__y7p08O_Wd3x5DSyxf7IcUhhVrr29Plft_7FGJyU98r4t0-geDQJSAVFh-RzEIMgSj6mIIPjvquQwAWGfpAhLk0NeQmgOi9M6LLlhvA1tgRqdlhmta87cYxxWiNrbEA5FqXLRexatCQtty2XMPYb1u-XBZRW5aSGbnpUlteyzIvYkA-AABXTildtpWAvDOu-enp2lTBLPqACLtpakvdcs21bTmLaS21VMu1mdLDh3M_-trqmlsIYV5ZRUIgACIkUAVTM6qlPN_BW26ssuW6zDkF74hEjc2aVDUzpFprzo2bBOcv50teCjkgIjUFNWbRyqYausD8TGN0ouJDul4u6BwgcGMCRO_KVlstMXV1zS66PkXnnHAD1RACEZkJKhB649ZaI7BtnlMK0rRxPez3qiasoPrMYAVEIiBEVpPCJmqqMYa2rc6H50Nb1cAhEPkUmZuKmQm6Z0etM0LNWUWcd86MnBOWrhuQzNAA8LnIoY3VXDrulndPhN4akidTRkcKEH2XL_Pdq9dlW8q6-diVdZl2OyIBxVev7sfd_u6w_8Fnb6YQvv7t13_0B7-zrFtt4pJDwnXLqUtknqWO3iP6zz_7hNWW89JPIyhLbdfrHPqYuvTweL3MS3AYY-r7rkl7fHjPTcGw5Xa9ZFPou0AGpjruJ_K0rOvlPKfdALV9_c274_E2BB9TaK0a0E9_5_PWmlb1fXCkFAJFTzGRD_3tjlwFVm4tdrG2SkBECK2Ac2FIGENI8XC3R8I0Tv206w-7dZ61lJy36L1W1rZCLQLhk5990cWBYprGND9d2rJc3r-zUqU1EAMAtudzioi8qIW-DzE6clrEFEPXpZd7dFjWrT5lYR5ijwDb9RQIuVmI8Ue___Pjfvz8hz_aTo-_-e3bmxeHf_d_8e989ubmn_3jf9Hvux_99LP_35__9fK0LaH90__7P-fc9vvJhxhTWtctXy6yFilVaw0paTPvQ11yQ9jdHJu1vOb727ta1py3w-Hmkx__dN8PP_-7f9CnRCDvnj78zZ__yri1ZTWuaZzqVlWERfrp0LbcRAHdbuo--_zz1KWhj32M1_dPn37xWcnl7vbw-7_34-9---sffO_7_96_8fenPn7_41fHcSetgJFKu7-7AbAQIqju-yGluK1bP3QA6B2So3UriDZ24TANBIiGMXggl7fMBnmtzJpSULPamogS-HWpObfgfOpi8L41RkIjqLUBwtAlQlCF0_WauuRjNDRuWliv89JYnPcMoApzlZX1upXlOp-f5qfT5f37c-YmqOgcc3MOuRVWLtzalgOhOTQ1gICiMQXo3LytZsq1KSIEVyt3ES7XLedCnbOmjqC2ymYOyWoNIUSkei1B4Vno264rgsY-SFYRPd5NZd0ISdYSu6R501KklhiJiByhiTyPRLpurNs67gZpVYSjA621LZt3ruaaho7ASuFpGloubb60rbjkCJFr3t_fLtc59P2WKxqULRtRrhWDM2m3dzepd4ed_50ffv5f_Kf_4d00PV3mNHX_53_2z__0d3742Scfv304P12urcmXX7-9XLd5XbYiJVcWM9b5cja2MXUf3dyXUhzStpVWa1lyIMi5tFIZRc2EGzC3snqHnkhREEm0SMnKDGqtZELyPsSQ6raqavBODcxqK9nwb1GTbpe41LZtnlBbRQKp7Lx3iCiY-pdaL677-38suVpT3sQ7ZyhyuWhhSORC8MnJWuqW-_1OWyXAdDe26xqjQwQFOdzf1MvWSnMgPC_kEDygI_LoCCQXc9bqErtBSzFFedbNleqdlflc2eIwstRuiKTqHZ3ev99y66fh1euPLg-ztE0YDLz3tG1ZqgDCuN-BSs5Zq5S89kPPpQISl1rW7XjcgSoatlKHvvv2m7e7ad-Y33zyOpft9OHS9UlFWbWPgfNWyqpmLJrGVHMBAFEOfUSHphb6rq0bALgQVNV5ct6jgIsdmikooLUmpkyA3nkpLaT4_P_MlIGbjx2gIVDqeyVEQweq3HwgUHPBcWHz5AwQSctGMVkXoTUgQwMDbyBgYMzPlFwAABEFMDGo2QFi1_E8IxAIW-OYQj4vZAiVyzfvbV6vp8vKNaXIuVAIWkQLSxVo5gev2pwR5-KMVSREJ7k5R4ZorM-Mre52amsBaZoZ9VkQAwQuRIeNURSraVUHRmYKFqbeA_ZD39Y8L-f9q7s6b9tpUWUk64aOCMtWzk-Xp0Vior_68v1xHGqzpWy11vVSxym9_TAfdsNWoN_3pdbJ-et1c0jfvj1JjDPLp1N_XRsYfPnNo0PMai7ErahXOK8bi1UR9CgAFl1llKwYXDSfklcgQvSAQ0xzrnH06LEBPp3WrbJ3qbKecvvlu3NwUBp8_XTapXieSxf9Tz5-eX8Yz9vWJ7dspTAbun4avvlwcd4fdl2toK0sS_1wvn5zPdeGtdSPD_ta5XJaBFWFlZS8r2uJkfKatVnXd-SIWcFQ1ICwCQsLtwpoCGKOGJSVk6cUI5INXYwhBArQ2HvKayHEXNl7dM6hQogBDHz0wXtyzg9DGpOlwGwVtao658YplNaIIMQELIEMhI05Tci8JhryaSlzW67z7ev7fL460JLb1MVPXu0WlXQ7KpgheCRtTWoN5APRzWEwcrvdkBx5wmDS9ekXf_gjEni5H-dV_9EvPv38xWHvnQNopbSy_eTF8W_enT_59GX0bgz-7tB75xDx_jhdl20-r8M49F242-8O4zD0XSAQVhZ2RM65LfMwDGYgZmutoqYIQ5ec890Yt6Lek_fOO0-eRPH96VJEL8vqCKehz9umbOOQuAoAiEqp9bpU3yVx7pt3T-rSspW1tSW3b7790LhmFnLdsuXCrA26GBGhVdi4BBeJqGnLuc3XXEutYoLusN-ty0YAzlPN7Vmz-usPb0NIz_j_eS2GRirgoIkgYAhOzDyF4FwWISAkcI5EVBqn1LXKLKyq5KBlbqw-uEhOCK6XpeQ67sbko4g9vLuE5O7uxsu1IJKqGos0NdWWeRgHAe2GEHzYtkzeE1Et5XlqjoSxT4hQa26tgFme127oRZjQmjZtYiYsomqmBipmoiohxFZz7AYgBNW21crFTInQ-wCA3nmPbn58FFMLjhRMxUCD94DGhUU0Dh0gmZo0ed4DmJpwQyIxBEcxRQ-satKEojeAkCJX5srOURxGq9U5J4z3P_x4ef8kuaXeo7G0otz8OBgLqiGZORqPu5u713VbjLnm2qXuP_nf_2ff_PWvXr7cB64fHt__7Mc_-OIHn9ScBWnO5enDU_Jx3rZtzstSukhaytO8tryJMXp3ejylcTQBl2LL7TpfhmkClfO2fvTxJ1utw90NMQTfIYKablKKamW9e3nruk7QnIvAnLr-6d2Hx3cP-_2OtWqu3ruu619_-vH79w9D7Ma7F2nsAxEodjcHqJzna71u9VoM3bPEHcxtlWPqXeqn25cCxNkAXK4CQjSO9TqXdeF1retc85bnpZUVyYmAYQDW0Pun9w_r--9aXeU6A6EB7I83qgboROD44j6O_Zpz6rsUu34aDYG1xRR8n6w0aFVbk21zBgaW8-ZSBy795Od_-MXv_CTni_d-f-xP5_kf_pt_uh-mOs9f__Z96MNPf_SjP_uv_-Xl6fpwfvzyL7-8nq5f_IPP8jZXrq2U67tTma_M4gCMtWxbPw2Azo3p7s1LVXvx-o4QL5fH8bDf7W-mm7t-7O_u9oeXx7_5H_9y3S6PX31rWoPTtmUC6PaD805Rhv1kKGFMoe9fvHm120-1ZRSVWq3ybho__eTju_tjvpzevLi_Ox7_rb_3s5jwm2_eff-zFyCgyneHiVBMxBGiypBCCAFNibwP_v3TeRq7FEJMYewTyDNWnPrkl62oKHnX9-k5rHi5ru-eVvLOCNlEVKS027uDd06aIIFP_nS-Ok-xS6L6LNlNfWfoTpeFnF9zKbnm2krhXEs39BT8eVkoxOt1vl7X67rVZouztTbX-ba2QKnOKypcr9eY4vlxHYdeqoQU5svsE2FwWy4C2LgZIJuUraBpk8aNc92ciWYmR61WY8OSHbiUSDNjqaDaj8lU8-lyvDt203i42WupWmqb15JLl3ouS503AJWtdGPXmmipRGjaTEWtha4Tlf3tfYxBajm9e5yOU60NiYgA1Mb9ze5mNz-dQ0rKloax1S10vSGqgAskpRkgOuf7Lk19Fx2p9YNzIP_Tf_ff_I__Z__2rgvXx4fl9GBr_uMffv_ufrfO6-myOY_bUs9zXjK_vzxdc3k8nQm9RXj_9r0H8MGTo3m5ns7zOAwP7x8QQJQBcSm1G6ZtnZVb27JKUTEpFaxJrSAstSqLd855BLbYDdv15Mm3UlwK_ZCIwIzzPD9Preu8AZoHsLwi1yZE3iOZVPaRWDOqOfqdP-RzdYnC3oGhzMUuC5D3Q1eX5gx5KVaY0IQV0DdmNDBm10-Xx2tMPYKFPnDOadhLXnjdGuuWGwUfxg65ESu3Iqx1Kz5FFzw57PbjfM5pmjhXByBc7-6Oj-8eYuxE-Xrabu-Oh5vxaV4JXb_vmVWFXQicGyH55IYUfXAs0ir3h31et93NrrZG4Mz72_v7OKSH0-nFiztQRcK6lbKVcRwQFJ0zNe-ozCv6WEsZj7vl8Wl_e7ddLlrRETkX6lpDiugcGrluMG1alTyZmu86MaMYDbBuhRDMxFT92HEpakbkDdgUTdUAMERVBoTWKpm56OpWEIkQuLYw9LKuqOKcY240jeYcLIuBgHNudHxeoXOgDdQACYRhcrBlSMG2Bl0CAlCGwqCmjpAxdME7J1UsF68ARC6AifJWYoou-TJvITjXhXotiEBqWqtVUxUkA0Ql9DHI5ezUDJwhoCNk0VZQ1MVgCuhACjOrEVAHUpoyY4zdNLateI9dPz5-97S7PXJ7roBLQFe38uqnH7_77jzdHN-_fff9H35iqh_meei71CclIIrRuT64-1dDBfv6u-u0H30K6mgtxU3xX_76t9Nu-tVlaeTeXefpOFR0D-uyVKlS-11aSzFAcyBK5Nylys2hF5b5ku_vR0fEjYkQBJWQRTogrzo6F0f_9mHd7QcWNoYhUOpcM_VI_-ztu4_3u9ilx61c521jcwm7IT1ct6rKJl035ixm9nJ_YONTzQbSe6etIfpcWbTZ5JqqiUoxF4MfQyvVoUFjIu9cEFMENRZwxEWeMYgiFqNflvyMB35z2F1LFcFPb2_XrUaCENw0dEiECNOQyKCLARAcqKeQl3LYDZFo36U3N_vbXRq6ENF-9IMBmzqC3LQLbi3l1at9iAnBXv_o1XXj7czH2x3XzFXWBWIC70LNxZH_Z-9-eUgvoGj7_7P0Z722bVtiJtRa69WoZrmqXVenvPfGvXGjcEaE7bCddmRkpgNbYGwkBIKHBJSvwEP-IR54RGCJlHiABBvLSgfOqG95in3O3nutvdaa1ah62RoPK_7CmNKYffT2te9LMXnvx7ioXZgnZwmB1wu32Szbtnr54uJ829zfnF4_3ba2-u0vnj47W766XH56tWyVMlptV23KfH62ubzaWGe_fP5IEi9qB6UQYA6Zc7G1a5ytaxd9EkCjtIgQQMz8s4-_xKSyMAE0daudyZmnmPo5zD5WrkKtT4f-59_faQTjjCGNRMwyzMmzxJj2x9N2vaictUTaaiJCRbtp_uq797vBB1DKQEjMqK7v9yGVYY4s0q264zANY2DgCPk4DAU5BD9MXhQCQo7ZNG4c49D3pASAksD6rPGHIcecCRarZhxTVemUM2SpG5elxJRBkVE4zt4oO08xM-RcGLGqXBZmYUBsG32aEoEwIAsjqdNhXLR2jplFbGX9FH2cBKFkZhBBur7ZzX5arxZhDtNcmroSC1Xrwpy6TZ1i5iJ15U6jzzEhgK0rEQERThlJWWvH0-CsiTGlmDWiVqQrzVyijzlljtFWzs-eRQSYUyFUMSWjFFRESPPkAbGk2HTtPMx17YAImKuqjiESgl0suQhpUhoAFQBEHzgXV-mSMzA9rFcJs2QmTSICSqCwrY0UVgAlJQFCRVIkpaKtlpyUMyhojZWSGXHx6nH_7i5PsW4NaZ1SBEQkTdYIIjPr2uVSmuUqTZOE4Gq32Ky67fLm2-9_-Buf_os__s9LnP_pP_p9KKl4D0gfb3Yf7_bampx49LMztqobQb7-eBsLL-p6uVmJQt02gIUQ72_utFbJx8rYEGO7qEvIigVzWjXtfnc39uOw712jN9v1eBrmYb5crb7-9nv283ga-_1xc7ZCKgqlaeuLZ0-Dn6_fXfenvTHGpzAMAzF3bdOulttt298fFUKOQRkLBMZY65pHr15NfWhXC-tsLuXs8tzVlXG6XbRk9Xa1EUxYsrCQtrZqgo_tamFsc_Xy1eMvPz1eXx9u7khEG2u0ZXlQBqlp8GRUt950q6V1LudSdctuubSrZjyegp9yiMrp-XAK_cwhClNhOL-6bBeLqyfPHz179uLVC5H0_XffhxDb5QpI_fgnP_rm7Xfz0CtURPLmsxd_9cuv7j7uxZJrF4fDvSQOvR-ux93NCbTEKcYxNquGGU3bLM4uq6pmhNXFuTU2p3D74da11cXFxW_95k8uzrdPnz8tfro7Dh--eXd3-5FLynO01mhCBikxppy1VqJUfxiX56umW9TLdjqdnDE-pJevXj3__E2a-nZRW4WxH_7oH_ydLz55-sWbp7Whiunx022rtCKsKhMmf_txt1m3KAgA1mp4cHwYPY3T-WaJSJXRBFJYci6pSExcBDOLNQRKTVMArfqTH2NGrYzCkGB_PGlrurquKkOKSsqoIfk4x1RVhgHnOU4-hJy0simVXMSHAIiIOuUUYrDO-XEuLMC474fDMGahPqd3dwdyqvdhHkYFOscIBCnMUkRVcjqE1Vk3DjNZiHNwXZVzJoU5JaUwhACAUpIyQgySpcSIzNpoEpYQJSVESUkwA3KBWLTROQuHZAGkyGa9iXM-3NwNwyCMrnVkVBr6MAZXGSmgFpZQ-eNJQfHTzPpvX4YCuL648sPgT6e6tiWVIlK1CwIgstvLs-DD3E8ErJWe-pOyzg_54uWzMs_H24O2Wgq72hKZPM_GKY2sC_yrf_Unv_vDz9adM2D-8q9-_t_-h3_zR3__HynFgfndh927293N_SHG9O7uoB2-v9lVy3rfz4Awx6iIjOSuqRPA_X4XM_d97-o6xGCsDTkN3jOkHBLHYKwqOebEddtkP7AwlyzwYIQpOWTj6lx8KcU4V7IwSPSx7toUQ4kJOeZhBGTMxWjRdcW2cssOjcqxMHPOTEY3q1bpT74swwnAiQFCQhSePGlCoyGLIlVSMBqlsGuque9BYSoppURKaSXaGQBVda3PIfugFXEqaFApLCXnEBVqyZGRqXKmrlGRNUZrzSykELhISSUkbWyaZ0ZgFLDVxaPL6XhctMtusw7TNJ_6qq4hS5rC-mJTZi8Ci6v1PEcOpbJVmKduu3wY2WhjD_eD6ywQA4IwCqftcnV3ew9Iq80qxDIf-7oy8ziYRaU1Acu836_O1ykEAhFgyIyGbFOnmEhpYI5-RoVV0-QUJHNMQVnDD9kmgxACCkjKBamUpOsajUEkBEJhVCgigMAKlMHYj6pxkBkB8KHBTgJFUCvkrCpbjAVgKIkIJUYyjksCBtACAkAAmYEQfAZgiFF3LU-zqpTMGRAhRSUITOCEQJU5C0fwMR77OIZwnNuLNaCSVJSAsciplJSJi1GYfYACZlOXyMBItZLTbBFFGQAoKZbRE7BkBhBkIk1xGElh9ElrjUk4JkTKMXJh1EpQtFHOmmkem-XCTxMqHWMCY9xyubu-r5qKRRaLxe5277F83PeudqvNMo3ZONtqBYz9dHp_s7_309n5GpXanfqXjy76YdxuzwY_162b5nicZkSKsYCIAFXWTT6WnI-QGuvaxs1z3Fw0cyhWmQrVnJMxpIxwKRxTH6MkWTi6VDwWvu8nUynQ1NY6cXm6sFFoQdWQ8qauT_2pqqpI-O5uFKsFIBZJyKKAyGgN-_1Ok1mtFxIyETXr7rAfEGBMrJcueA9cFKIGJBHOUCaPzCiQcmaUEouxCphTSHGemsUiFHm4V7XaWq3nnC25McYssdFaBNu2QgQugohGERkS4EVdaUClpHUOGSpnFUApEVk2y65WZtrxUjnXWEX64qJZb1un0RBAKafdqW5rwlQr2D4_ry_WWpeGbN3Wq6vWkO2G9uys21wtL54t_WF--uLMKdcY-7u__YXJvKjJl3zV2r_3W282qL98dfXDzx-9frzdLhbC-XzdosihPy2axhpDkqzVKsn9wRsDtdXOKQPEUkgw5thUrgD6eV4uu0XbJB8IKackAufNmbK6qara1kojC5yG8TDO96dhjOnx-YoBhilYTeMUAASVrjRl5iGki_PucPJI-PzROQrGGI1RSSCE_O7uNASeRT7c7ae5zDEj4BSjMmrVNW1lv_3-kLLMKWbGLHQap7Hv98MQSlJOGa2JkECmcZpn7ycPytS1U8L310cALCjDaRKROSbSKqfCRUhRZtFKjf2UMhcoAEobnEIQQhF52FUAhpTFhygAqDCGnHJWmjILIwIpZMwlplgYQIC01XXdWq2ST8knslBZKwnmEOq6Bo3Zl5RK29aFpaoMMmZghRR8QKK6abXVWj3AN6iU9pM31oUQUSkWyjnJ34Z7gqlciVEKkNJKKUKRAiIsACzAUrTVMXgyOnkvDCggUogwCzOnunJhHGPI9XYNIoSMyJIFCJXSuaRSCiHaxmqtUspaKQJCLgikK-fWjQggISEaa0qMD09EECUlIDJdAxn8qTeOtDWxH5gZgNBopbQIC5C2ZrlYLVcrpdFZ8_LN8z_8-39PeH7y6GxVa2fBKVU1rqTctK625t2H--vdsW66fuytcTFOXdP4GMcpbhZLo9U4Tt9__a4_DrWrUghXV5ekxGmdYqjq5uP94dXzZxBTSen2fs-IiyfLylhh-e7ddbdsL55s-sE_enShnNZKa624RM48D4MP8bDvM0u3ac-vrkhZJK2Vbp0jluFwGE_zYnt28fz52aNn3WrVNc3jl48uXn_y1Te__PLHP7x6-WS5WXfr8xyL1nbzaNM0zek01229XGy1rVdnF7padKtVtz23i66q6-in26_elhxc04Y5mKYqhVxXd-eX1bpbXZ6Zqj57fJ4LH3f3Ruk0T_NhN-0PxWcAspXLPpU5NU1drdb1erF-tK3ahlCb2hzvdiEGo_VquTzbnB1O94rwm6_ffvnZmz_4rR_tPp7W64Uv_ptfv_v47r5dNXcfbvbv7zEnlszjVCwuNou5n6uuqteLEKOrnCJMpVRtu1h2wafDfv_kzauual-_fKWBrLVo1P3tLvphuN9PhxOnKIJG2WmcuuUSyNXdioxSrj5_-gyZu2VXYgrj_OTxlUZRDncfb33J__D3f_wP_5Pf_js_fH257c6WdauVFJn8NBxPzjpCzN7_8u2H188vtpuVVrquq65uEISBp2EOnKraOWMzl1xKyiVlqRYOkE7jnEvp59j7NE3p0E-Lpbsf0-Sjj-xDAKCusW1lnTbWWCEkQqXIWFNYAOFwmgozagOKU-bdofcxElHgFHPRWgEiaJNTPhz6D3d90zR3fX9z2-9G324XIRQGMNYIih-9n3xK0bSG08MYMyuCVEp3tmAGAOBYMBdgkZzTlFxdpRgJYb7vq8ZprSGVPHguxbiaCNgHh7qEUHy2i5bHIU-pbdp23X68-QiEylBdVSA8frxDVJCTcSrFVK-Wp5s7hSDIuqpiLMpYZY3RlXV6OvZKeH9zXF5cCOdSYo64WK-qxt19_0EBk8HCWbtaGbvarHOJ_jC4rikMrqmNFimZU2o6t9D4X_3X__NPr7Yvr84a4_5v__f_x2LT_ae_9_tGiU8pZv54ONW16xbVYlX_8tfX2_Pl7n48Bl9vNoebXYghzN5Wtq7cOIaP-ztOGQhDDKj1HGOMgUhBjhwjCAMiieQccgwC-WHPSddVTkk9tBpSKDmi1do2iJlL4pLDNOQQiVhiKDkrIm0kjgHr2lRWCqTZq86iIl3XIKBJlP7Bj4toEJLCWunYz5ADCIAxSCpzIUREKbkIaVPXBUFpQ4AlZltVnMvqYuP70Vo7n3pjXY5JSCmtSCNHNk6LFBZGAkWYvYfCcYrMWLVtysWu28wJteFYQEERAITxdHJaz-OIBD_-wetDP682Kx9Ct1iYShMRcyE0lbVVVa3PusKAAKv1woekNKIl4BJDRIS6dtqSH6bMXLnah2ArIzn6FLUz1ugQsnE2zokIQSSnXFf1A1H6oKGMMdbdkkswxnEui-1FSUFbIyDaVqZ1knOaZkUipaAm5qJNhdaKwhIiKZDEShMXzgIAjKJIqeKjtSb7CKhEkXIKWEoMhEi2FiTgBJmBEXMSFigCXCAL1BUwQKshCnQVzIGsYRbMIg8tz9GjNYhFBMkRo0gSEMbMgKwQ4qG37SIXTKMXFhGRkjShIJfAkJAMlFhAgH2hnJUAGEOVJgYIgUQgSy6sySAJ-EJOShDnVBpGyUl3TYxFBJKwtW7a91XXCWG_O7nG5pQUYU6sFZGCME1G28evrhRqp3RVm7cf7nwp1lk_x0qp_TAZrZpls9ud-n50WiOolPJmu_zqw7V1dn88XJ5vM8j3H-_tqilBks_PO0soThtg7TQxcO3sNBXPwiCVM8mzUhRDLJwTQ9ZwCIEjigAi3QPmrHwILOW-D3dzRqNUpcM4H-dx1dTHOWhFyuq-n03lii10sTjcjkAwTb6u2qbSx_3RoKBFIR19HIZZGS38YJuKhGgI_ZC6tnY1zsdZGR1Kqes6payNCjFpTSACKICAAJyytcZqW3IihU2lT8dBO11ZE3JRioiIQKRwETZagwgCWGNR2FUaEBRQ42xlm5JgUblnT9uYc5KyWbSNc41yllxVNUR6eb44Hee2qm5vd8vFWnF5frmuOpdDrkz72afPFgvpT6PSuPt-9_LZlSU6WzbLpvnj3__sy9dXX7x89Mnj7eWmrojOV-123VVKtZUhwDiNSGqe_H531BrH3ueY1quFUpT9WFmNqFOMOedvv79dLRsR8JNv61or0kS5FCTsh2GxaJXWAJBzaepKKSxFhin97Ov3pHG72WLKi0UzTf5-mlaLpjAcRq9I7eb5ZneqlB58Oo1z19Trtkkx9aMXVHNKf_3tzV0_HaawP01ROEoJsZAiH9OyqnXhjycfUgYNQmqcPFjdn07MmYwobaBAKaxJD2NfWJpF7UNaLDpdm-NuzKW0azeeJjIYY0YARZR9QoslsTX6dBpO_RjmkEI5X3XH09ifZkVmDhEA6srGXKYpIAAXPvWTVspUJkkuAJkLIMUYEFBbZ5zNuXBho5UoLinFEJ2t9rt-cbbMgYHZWdt2rdEaEVlhjBG1Oe5OxihttdaamcdhZhbjDIhMw4wK52kuIqRVzhEKIwKX4qdYStHOoSYEARDJWUCQsORUYhLAumtLygiCQDklQpyGoZQS5plI-WnU2g79rLGICCIhIinN5QGbVA9VH8mCiLpxnIsgcuYiAiIlstIKFEnkh-KBrps4TUYrES5Mi4vL4fbeGK0MJh-N0fV2maSkknISZesnv_EjhWmeR0j5x7_926ZMU_aPLtefvH76Oz_6gsP8w08-rZ3SANYCId6fpj_9m69NZcZ51lo7Sx9udk1brVaLytmmNuvt6nQaXe2chd1ur3VlEXIqZ5vt5mz79pv3XdPM_SkEHwAZpXAJw0xaF4XWGh9SAczCuYjktFivDCIWbqv6cJyrugKNqCDOTEQxJAEM4-BPh-G4c5VlYBFydaWIvnr37upimyPPU1gutjkyMJXCIcYYExY53u_8HBXz3f0hEYcstmmbi20Jqeqqcbd31vh5FizTPAXOGnFxvjbOtOdrZRSgUWiNVafDMafUnZ2XFFATS5HEyhoQQILVdrV9fqHaSjtz2vUhBI4Rtbq_u1-fn9VdS6RP43G_v73_ePqtn_7gYtG9evboeDqdX62rpfk3_58_i6NfrDbPfvez7_-HX-boSYnRLmX8rT_-7dtvriVLU9sEqJ1eXVyEHEpO7WK13qybRXt5sfnkzet4OqzXXWZkB__u__0f5uPpePMxzemz3_vy9OFjDKXpmrH3ypB2ja4VIzSLxdAPn37-ZeG4Wi1Xy5aTf_Xy6cLq_9l_-Yf_6CdfvHy07SoFzOM0f_P97aI2la26ReWsA0RldF1XdWMzswJZLRYPoQWFaIy2xoiAUYoBP94fQsmnyQuq0xh8SPt-7jZuGPPh6EWhWbjDGMdpLgKDH6u68tO0WDWNNl3bZpRx-LU1WyJiBh-ikIoizBhCRsH7w5iZi4j3Pgs_2m5Osz_0IygVYz5Ovqrdh4-728NQFPlUSsw5FiiMWUBoPp2wZFJuvdyEYSKNknIBQWWotpw5JU6zt7UJIaSYm7W1BH4_Yi7i02KzKsGn3oOAJaUs5sErZoUikZXVafLF5-7FZnl1-e3PvnKVm0bvjIKc8zSzFEMauMzTZFxz_vpquLkDKUqpVHh59ai_u3NVe_7seYzzfDiWHFVtXVv1t7fa1mfPnri1vf71O6PQrqqSRClFRgMRIIz3h5xjd76u1gtBnvupWy6qRX1xtvqX_-qfvjjbxHHabpe_-tXb3_jpJ48vL63Rxthff_XdatW8vb6PPitnz9vmw35aLStBRc6-_fX3Wco0DFVVjXNYrhfDEKOfwlRUredhdnWdMxcunMt0853RmpQBkDgNSgFLjP2orQFAYUEiLglYpAhqJYI5TZxjYYh-kBIwZ3koOgoUSSBAtdNVy7FIDqUwg1BTcRZJ2SCo8vQzMKiAJBdqFU9ea0AGqbSpDDMIkkBRdaWs5ZyLQBwnBaruagJVm2rq-26zLCxCGgiVrqon5yWVsB-briohEhHnlIcJJFmtU8moVbPsUvQA0J-mMu7iULTVpZScPGU2ltAoZbQfI2hlrAs-tl0T5qCRSAGncn5xcdwfxmGY5tlW1TxOTKSV8j60TaNJPfQljVKcyqJbxjCXGF1tAUqJSUo57U7MiUiRIY4JUYrk4lPKsaqbqe-BUCEhojX2QQnKJcZ5YhFbNSVlQUIEEIEYFTAwkXGkDCtt2kopVQAlMyJq44oUbTRLIUIiFIEcg60chwyKAEFywZxZGOtGuJAVZCERyUlqBykBIgCDFCCEDKAUhBk0sk-6qsrk0SjwQWtX5sxc7KoO97OqLSJWTYMYXWUolFqpyGn7yQsOAX0AAIYkALFPD7dupIhBQBsoQiEQlsykaispYeIH5I60ksLWYjh4UzcQMnKRzKRVzlyKaK2JQAMoBGsUFAYRNIpQvXj5xbDfhal8-dPPj9d7YcnGLKs2hKltmkW3yCl2bQ3MY_AEdHs6NbVru4az2KZxzqSYkw_aucgMoOaSbeVIQdtW9x-HSqseiQiLqGnyZ9sGUrZWTykFLMYpZ6xFjmNarpwvTAYRkUsB5JhxEuisVlYb5NFn1zZBZDcGNESGKmcKl9PJgyOVoCD5lO_uT7ubOc5xtx8SQWHZH8cnV5fCeXdzSt43503yEQWYC4FAYWApIUJhkZTmgDkJlxQKETMzouQCOSUucZ5zs-j8MCsFCMpUmpCOp9k1lozJubSNO_R9H-Ki6yqjrNGLtg4-guS2qmJI1tCqcYJgNDhLi6ZOKdUVDscYQnbGaCiNodWitco2nXr9Yr2qjNXULcxy3YzHU9yPhuS0P6269sWj7df_wy8aa374-WeKU5rj-3fH3_utNz96tf3hq8fO6RxyW9vWUoWoELTA2bIDKI2t5nmunDvudufr9fmmO1svmroC4dM07XYHpajrGkU4nIZpiJdn6zlEpTUpY4yCXIbZL9rmMPRd24RSJh-E2WoDUoiUoCQoqLCpG220H-PPv3o7Tun-_qha-1ffXp9tFtfXd8bQxbIGwinEaU5144BBikTmafZfvbu7PfS0aK9v7xLLsZ-N02-eXOwHP_o4-fzhbr-fppRLYlZGlVKm2ZccWQAytXWFABxj8JFRNsvlcRjXm6UmJABhjt6jQt3YFIq1WgENxyllzoWncZpmnwuTVUiCRKKw7yeUnEsmQFRQMk9TsEbHEFAZEdaauMDt3cFZG3wMMcYYQCEQakUAyCy5pPE0VU2jtVldrDnk6AMRGKsrVZVc5imUHJu6QaRpHs4uNqUUIkTB2fu2aYKftaIYonG2qp0Ia6uHw9FWFWBBQmtVUzciQiSxnx4O90hYSqqqOqbstMm5lOCj92Q0KKUAlEZljNZKEWpCUzdkaLNezuOoFJEyUhgBCZW2Slicq0oppBUIoyAX0bVdPDqjApxYGxIUAIICRAqQQIp2loQZ6PyT19P9LbIIgNGqctq11TSPtu5IKVt1GXA87rqmNYiLZTfubv74H_7jNy-f_fl_929-77d__PzR9sXlJQqEMM2n8Xy7IgX_p__2365WNTjXj31lLSn87IefaqWT94jq8eXlt99-65wrGLiIIK7WmzBOORTrdEijdWQeVmc4lpSH49F0NTBzAWNE5xKPo7ESh3F3c4tINzcfm8X6hHHVdM9fXq3P2rPV5ubd_bLS82GvmTlPeR5yTDFKtWjffPHFPHtEJpE3Lx8b59pFq6sqx4AKSEFJGRG5xLZx2ug5pKsf_6DukJQCSNH3H7_-Npcw9YPkwizzNIOgaDLa2qolpRlhf_1h7Kd5GCwJMlfL9TT00_GYQ4xDaNrF2cvnum0ItdLGVSYGPu4OBcQ11asvXq2uzuvWrbrV2fnF_u4uhDiO8csvPvtX_9M_Pl9166652d37Ev_mZ7_-t__2P_a9J42F8tf__c9CnHVlRBOSQ-s2XXe6OVVt1643F88fldnHOWtr_uDv_70U0us3rw7H49Mnz777-tsffPEGFO32-z_7d39qIQ37g6uNbaqbb29sawE5ldycL1JInNP26sIoKoUXbVcb2qwbLPzq1ZPf_90f__5vf_n5y6tN4yrFl6sGBUUBCry-Olt23bIylhCECaCqnLVKO7Nu61XVOGdzLjFEYxQXyAw5Z23t_tCziCBWtQshHk-eQWJhZphjKsxTjvv7KafiUwYUrVRV6c6ZJ5dni7ZSyBxz5dbIkHOZfRSNx9OMpHLhVDhl2Y2j1Sblh841fPfd9f44aqNJa0a8352U1h8O_X4Yg8jpNBHSPMyQi3V62B_Cfp7zbNo6lpjDzJlzYl071zg_zikmwaIRwzgUgDj6pjZ-N2tASRmFSAmiIAMWsAbj6MWz1cihAGpkjuPEKE29uP32ulstg5-bRUMppNOQU9HGconIgqivXj7dv7uTlIAZiXIpCllZp0kpo8I0lZg4Q7teTMfDYrNdnZ2FafbHIc4ekTmmHJlAbNegxpxSyaVuF2lO8zAp0qSVtqZ17j__H_3DL84XOqSnj7bnq_bRo_Vms5zGMI9hnH3TOmX0X_z1N4Jw6MN3NydQrK07u1zdHvuU5frdx3rhHj26evfVzQ9-8sn1zT4mP4Xi6iqkXLdNKXnqpzh7rZwIxOQ5ZyqcYy4ltWcbFlCgmQsIlJIRGEmTcXGaCJhLQVWwMCdGAtIKtQINnMW2rVY2TlOahhhF2bo6X0uYMEuJuWpqRa-_dKszLgkbVUImIiiFQxRmSUxG5xQ4FdBaWeuathgFhM5a5lwepMuKpuNkKkeawjBY1wGLEOralVJKSjll6wwIK639NCtb6cr4YUAyfhyryqK2rq7qrgFFXNg21WKzyilePn26aNz776-fPn02jIMx5vGji8xFijAIaZyGURC6ZRdKrNpmGkZjlKscEaYYq6aCXJyrD_c7ACGjxn5q2sWw70HKZrsmksyMgGGatHGuc2H2SmkiCt5vri5yirauKtcN_bGqGj-OACCC8zTmFKu289NIoEvK2poSk6kqBmAE7WpBFWNkpbgkIGBmQERluTCnAiz4wLAWeYg2o0ZSxNMkwgBAVnFMUjKhklBAZXAafAAGYIDMoBQIgyM4esggzgAzQII5ozFklExBrAZN7IvmUmZvSCefrTaQU5xHBlo8uoohG6dBS5yT5ILClAoXAGcABQpLiBqkpPJAH5dcICUUUlZJFkLIsdjOKBAOCTITkapr0kpidJWL89w0NftcVZ02NoVZaXW6-bBpV2Dww7v3deX6YTzd7J49fdJ27fdvb7XRuRTvg9bk50RKO6X8HLTWU0rD6Cvr1l1TshzGeR98XTkqFGKuTcUFMxZUdAzsutU0jkb49jhulvVwnM637YfbAZNqnKoUkpQQswWVSlaISPDtfNgslhGoICXBxunbMYwl-8xTjjFB5arjNGcE21T3fRhCXra4L3E3-N5HU7tMMKeCBpSU--P47PHGOTWMcZgiaVKEJRVkLCwcUpkDFgFmPwRrKuFsCOPgS0q6NlM_KatDDHGOrnHRe63Qh0CVLQLCWQD7KdaLRoRL5sooYHGkkHBRuXmOztJq1aRUoJRu1ZCiqjb9aQw55Ji6Sq02lHJpHXWL5mpTj2PoKlqcNSoUneLz8yWGcr7dNI3lWr1_fyikPrlc__Znz1JSm9X6D_7BFz9-efXjL5_-w995ta5MrWmzaGJMi8a2lemMMsYoJKP08XC6u9uzCElZr1fr1SLn6H0oIKi10WqzXK0XjTUGCadxXi3abtWSUc6ZXX9y1gIhp_L-end2ts5ZSNEwjLkwI1prIvPxNO77KYsKOStFLPz9-7ui1Q-_fGpd9fW3N-9u7q3T5-vlom1DzN7n6_ueCYyxTpk5pf40ZIAx5GGejbNg1BTiMIaYGUwTc5n8fHM83d8flaLTNMdQko9Oa6VIgFJI55s1M5fCPmbUlEIoKfkhSE7Rh5K57ye3qE7HMScGAiTyo2eSHJKyavYRSE3TRFrlUuKcQsoADCTMIIBzPyMq0qK0AaJcckkFAWIuyujDbjZGCWDJzAh-TECQc-Ik85yapkJQxpoS-dhP3s9NUxVh7-P93X5zvvLzPE5jTFkbY41DTc6ZHLPWioiEJedknEsxc2GGB_mSnfoeSYcQcpYYEyGUnLXW-gGvZ865hBC0ogcaQStqmuU4TFqRtpoL28U6jpPRah4nESwpaaWFIfisiFHplIvSRFoLSwxBaZ1CcM5prUhh0y1IiIuqu46ZY2IUBI2KBFEDFFSqxNI-uuw_HiBn25gcPBL6Ya7qClCHGFdnF8oo55wCNFAqY_7l_-J_sjD617_-G3-6_9_9r_-XbeugpLayp8O-H47nm-V33380i9XzV0-_-_Z2e_HIT8OpP26Xm3XbPH9yOUzzsmuLlLvrWy7l9v5oSKNCTnG9WYIUMnroR4m5cEFbhTnbqzXF0N8NSlGcxuO7O0A5__z1fHvr94flquU415U77XaqSMISBcscuanWTds09eXV0-BD23Zhzu1i2XULvWl-_Wd_vb-9X6yr3ceT94NP8zd__dX99d3uw41Cuf7m_XB_9_HtdRy9tppLev_dh_7b99NpyuM07IZwGDBHDh4IqrrStvqN3_iJT9Pl08thmB-_-SSnOWRYrjbrZ4_bpkFSd7e70-kkmZ-8eH7x2evtkwut8e7mY4reWlysl4uzDdm6W9TdYrFYrqHw21-8pwyr9bKx9OzJ89cvnv7-7_7k-ePLEsvXX33369Nw38-_-PWHX__6vTB3m5UA3N9P0zC-_vzNNE_znIyrPvvJm3F3RKAsUJJYIlH46NHjddctKlqsFszx7Gzth2mzrI9j_Is_-3l_nDTR5dmmuToPo68XXYY49Ue96MTo7dWjdrV49OLF7uZ-f5qev3hzvl390T_43a9_8et__k_-4OXj7edPH5VxenpxhkV2x2FI6T--vyWAhdHLuq60PvXThw-3971fr1rNYowGLq2tCDTiwxWQFJCYmUFCzMOcQFMROfTTNIaYi7a26mxIJecSsihrTqep6-oMACDLRysI8RTi548vG2uwCIo8kHjKGAYYQkzMscj9sZ9C2R2HBDyHUAqnnI_HsR9HbdR61c6xHPpxDhEUzilf35-GyWfEEGLw0YcoSLOPYZxYitJUCvphqpqmlFgEUGtAYBYfgqDEEAWRU1aqIEqe88PqOYoAcw5Jgco-KYVh9saRMir44roqDR5ybts6-9g2DRklKcvs42FkAdMYU1dpHBQp1y1Jm-lwQs51tRynARUJs7H12YuX027XVE4Zw5KVgB_5_Nnjypnp2Kcwaa04MxEQARAZ42zlcmHX1qWIabp208actHY__Hu_-Vs_evVyvfqP__6_-_zTT14_f2ydvr25O56mnHLd1raqfEj3h-l6d7LOzSV_9c33ORWnLGYcY97dHpCgqmslvFrU7bLe3Z6w0XPvlSVC1NqM4yBSJGdrjG5s9BOWogiVVTmLIm2MEylFGAwRISgk0NpWWiMIlOClZATSlQUkgMKZtbVkrK0XSEWD6LbSbb04W83v75VAirleLZplp8zzz_J4kgzsEAnlMGLJVishpetakNBoRAQWAmTm4BP7xIUffXYlnoVTCgGVFkSlnbK11goECjOCmLWLp1FKQYCSChAorckSsPj5wbhPnLPRDhFJxBrNpazX6-PHfdN1zaKbp5k0aYL-OBPiu5v7xappNo1WShOdjuNytVDGWFOlGLqmG6cp-FkQ4xxzTjlnPwxVXY1-fvT8rD8OpZTg5xD8MB4ZqOTYtYupH3PMy7NNiclPs1baOoMIOUmzaqMPisiPvWtrpUkbm7xXisIw6soCQtW2mYukwnNQzgICKEDrUIFdtgCQY1SEkjOUDFYTMLCgIhAGKcJCzuaSpbCUTISitRiNCFAyYAHJoAk4gbagELQCAkAFpQAxZAZhwAKEIAb6ESgIKVBasoBCVIC5KC5pDqUUwQxFypzRy9knj9NpPt3tJRcuAihYMoFwyqAIpIAwlCwhAhJq_SDchpxAGAunyRcBTgksUeGSSvFBafUg6MbCRUQZXVfNvLvvh77brqjg7vv3xup5ngBQIDNgDFGIjWsrZXSlsxSOaZ6DIFmtS2HUuq0cWq0r-_03H_aH6eLRxiq1XTS3H0_jMJ5tV1Y4Frnf9boycygFGGNUughSGKbzTU0knHm1tN_d7K7OFjFkZFWQlrU5RQYNDOAyKSWZ4ZuPt39xGmaf0Gifsi8ZEKXgqfdtZxqNfSqkMKgyxXTXz0H4NOQJou2qkIpAhlIs8c3dfgpFV26Y5uEwVSs1jymUAg3mGLQGBcwpaWeC91CyVkopKixCiEqnEJSgDyMpBSKIEnIJAtZahYpQhZRSefj92TrHmbVRi9ZUpDWph6znorM5wXgcKmtq5bTCfgirZbs7DMdTHmNeL9rv-6nWdjcWhTL0fhrSzcddHwMVaGu9Xi62y-UXX7z4ez96_oPXT4zTn74-e_lsSWFWWlWVVtoQiCR2zjz0IP0wEFHVOKfN-48HY6iyzjhzcX7OJe-O4-3HW1Tmw_1u2TaVNUZTXbthmt7d7f7s7Yfe50Lq5uOhbdwQygP7LCzby3UIyRj13dv3oNV2u7q-3f_83Ydu0SCpnNg0VfRpnOccOZby-sWVn0pKfJhnAWnbToB8ziHnmHMCKEC20iHGGPwcU-1qcto6tz-czs_Xi1V9dz8CQiqJmcc5nk7zq2eXZHHwaZj8PAUCe-iHUz-nFEYfSuG7-yMCMRftHAHcH6a6qRbni5QZCDLI_ccdAsRp4lKOu15pIofjON7f7VBT5pxDYi4oIplJUeEcfAAEIPXQ6EgMqv5bpqKIZOYQExGmkhQQKWuNYeHos4_JVMY4Z5QhQiKaZu-sXawWISVl3PHUX11tFYKIqtsFQEGGcRiCTwpRRNIccy7ez5WrCueSOSZvnS0CpKjkhITCpTzwhwjH48nVLoagtWZBrTUSigiicCpam5KSrSxH5hAUkR8GIFRWG-ugZKVUDMl1lTGaC-eSm7oJswcEIkClBFhppaxRZIQLMOUUAUQbcrUTAddUpFWJhSHbpiYiVKqq6xRmyankhMpILBcvvojzMRZ-YDttU19dXEGOy67-T__RH_74zZNnV-swjP_yT_5JW6vz821_6Ouq6g8jg3TLlW7a6_2QgN6_-3A4nd589uYv_sMvXjw7a40e-uHQT7v7nTJ6Gse2bUopzhKG2HSVJswxffr6WeI0HI5zjPfXd4Rw-OZ9u605lTiPwLmyyk9-uL1P85DmkmcvmZnB1dXxeFgv2-J9Zqk0Ller-_vT9ft3ZHCOU1HKIBLhsD8ClHk_2Yb6u8O7X3417O5LiDmEPI15moWhXbSXn1whU5j7--u7xXpJmiutipTFctEuu6prSkk5JWYBouubjzGk4-m0XK3a1VKjWl2caXKn2130IwuYul0u16aqYphvvrmejgdiePr82fnF47Orx826Pe1P42F8_PxCMmtUJcXVpjl_tOnH2HbVmzevV6uFtgYMXA_7v_zZ12-_v05RSJgI-2MARUiUQt5s2kcvzqFpN48ePf_kyfmT1S_-9N2Tz58sL5aXjy5KTq8__7QypBSJyMX51Xp7fnt7d393-OyHX_g4-3na3R3W55tT76PP3dXGn_aVq2xVKTJnFxdSilJmu90g6H_wj37vbNNUWn746vxP_vD3atLffrh5vF10i27209t3d9a6J5vt67PVi7NF1zSF0Sgaxulsu7w8X1ptnLPDMG271ihVWJCoAIeYTlO8O4zHfixABUQA7w9D5TRpW0RsXcVYphhjKkrroZ-sIa0QgRIXW4oz-JvPnywbZ1Ahka2tD56U0lrPIZ2mMMc4s4RcfEqTD5p0SnLo-4vtSgBI6dViYSr77YePPqZSxLb19f1p5DKmPE6-ZBj6SVhSiopkOA0xJu3M1PvFup36XlDQaNvUDOzHSRslMYiwQkzDYKq6pGKsjsNIKEgl-6iNLSkQo0ix2uQ5AaIwK1IlFVvZZrPhUnIuHJJzWKaZM5NR2lbTqcdCYOzVyxfZD_7Yg7D3UwExda2EquVCg_ipV8jKGUFqu_X6YuMqd__2-3kcjXWMhCDJs6qrZrURLiVlEVxcXA67k9FQL1Yc588-_-JKy6vWffrs8W_-6Dc-f_VYKQqjR2PWqwUgDqNfrbpT9P0Uh5D2s2dFv3r7_flyETMfTv3hOM7eN6vaAC06U-saM9_d7UviVAQJlDYpxug9lAKFS86mUqVwmiNZU1Ksmkag5JyUMgxYMksREDSVReKUEzmjKoecEZBz5JKxspwZkaRICj4OA2ptF9sy-ziNOSYA0M6So-H-qPDlp5JJk2YA8QVS0QTsoyCSQ2FVSkZE7kctYEylLAKwVpojlphMU0_9ZCpXL7sUckoxhkjOKXL9_ak5rzlxjoVYSECEOLMyVHySzNoqEck-WcWLrjGuahd1KbA79i9ePHHd8u797fb8HEiuv7_ulnWIUTgN_XTYj1VT3d_ekVLzNIYYt2frcfKc8ul4Wm1WhBBzPu5O2-3a-zDsxljy6f40TdNwOLWLhh-CEUgPmZvKNlmyH-ciXEpRpIKP3WpxOp42223wMYY5-lA4z1MgrapFBwDNask5IZII6spBjsICANqYHLJQ0UQ5F61sSokEjNGcihRAhSCoWotIIKidKzkDagQmEvbx4YMKuKAiSQVzgexBGRB8WFEGUpAKWAtzgClAYYgMgEAIqZAokQLWgpS_vT0MQSnDkjmlcjggKCRTgj9-8_7qk8dh8CkVYdYk7BNKUUYXJCANCBCDAhBhsoYTk0LKGUrBIsooFOZcXO0klzB6DYIaQVQuUSlX8mR0hZLbupmPowgsH58D52G_d-3idDguzh_vbnfLq-397qBErbcryHjsh4Kwm30QOF82pbAA5FRY6HiaNhfr_XT69S8_WGUulour7VqyFOHtaulT0pYy5tOpN8LMQMyciq5xfz-fr1Yhxsrp3d2pMDy5qEpBIKkIjUJO9ImjgCYVnlHIUGcxI0zek3VRoPczagWqDD5_dxhuJ38_h6PPe59Oc0BHgnnoZz-FduVSCpOPhylhzo839SHMjTFZ8uEwyxzLWABQkeAsMIryIDkrKQZtTomQuBTX1SWxUVpCdNakwJALa2LBEEuUgoI-lpijIC4WlWTpQzTOJhANWFlbW1U7c7VtjUYibBtnrVm13X7wnzzeVLVeONIGAsOzqzYyr2vz9Hz56nL98unm0arrWvfoan15tkQu21X3ZOVebrtVZQikMVQbrZRaVA2XUhtTQlk2VdfVyee2rZYWh1PKOUefSubz81Vb187ZpqlLzF9_810qyTlXIH76_Pm6WaKUknIRVqTbuqlR3e369abZDWFi6EP47sN-vVneHU9ktAJKnKumUUAh4_E0rJaLu_0xIBujv7u5j1l2p_Fn13eCsO9DpczlZqGVykAAtNsdQ-ZUSj8F0vbm9giAx3E6jpOu7KmfYxJCpUjd3ve_-Pk7URAD93PIgne7owCHIh_v-8ycStHOes774zGXYrVOpQz9pDQqTTnmatke9ydSuF4vAEhXVgRv3t9ohenUh9m7xgmCXVbHu2Pog7aIIkTgp6AAwhS2Z-v-1DOzAkgp101lNJYsAKCVTnNCrTNwDNkHn3LZjT2QyiVN05wLa02TT0CoEFLK2ug5xEM_GqNKLkqbGJPW5KpqGueqqfw0tt0CELtlF3NaLLvjcVitWtLa1XYOEQRzKX5OuZSScooJM2tXJe9BoF60fpzqpg3zbKwpMVV1RYh-nqSwctZZm6MHkJSyUloTGW2MtQAy9aO2TphjTADQdR0AK2uNqWIKVV0LQd0uAIQzG21SyECKCPw0lqlvqnrux5wDIAYfTWVJIQiWFMmYqm7DOHGMyKysVkRo7Dz1KYTFel3X7cXV-Wa1Pjtbx2H3Gz_68vzyMs7HH37y4jd_-NmycYfDrBm2Z6sU-V__zf_5h49_K4Qy-SCgciqn4_Hy8ny633356dMfffbqxcuXf_VXv7BWtV0bc4wxzTHVnd3f7rvl8urJRVNXVuk0jyUnP045ZSBEYbuw_hiMa3Ke4hiAWVFB5OTj5tkaCfFBwR4SlDIeJ2IJwe9uP-6u7_zpsFlVh497H-LVi6fJR1UTaBr7afXq6u7rm9hPWiE9nOIBRAoorF9e-P1wur6f-1OKc3e1nodxv9_XqwWXkkiDgPcBSFd1U69X8xwev3jy9Pmjx89fLM_OffSHm7t-tx_ub_Npx4WF0VhTVXVJse26i4vN-dX5crsR4cIlTKMz9tWrZ4tlFaZwvD9uH22WrXv--g3Hcr7Zvnz5rB-mkNLffPvuL_7s59--ve73oxbRoDnk5aJ-8mT7e3_wG0-ePnp00b18egWFn19cjoehtvUv_vQXz19fIejP3jw59WO3aIzRy65VoG9ubpWiUuI0RT8OTuP7X39QRlWu0poU6a6zP_zJm_44LxftnJhQffHpm-dPnnz5-SfnXfUbX75--eKpVvDT3_zRv_6__j_t5erb3fHVxepiu9iul4vKrNvqbNkYXdrKGlAxlVKkMhRyslZbY7QySqCpHCnixEIQSjmN8-HkC4CtzBRiCHm5bK8_7kWKMlYRCUFtaRi892G5aocQFAISCdLd5D99cfZqvXi0WLSVlSxEqDX6ELQyiJhi8ZljLkkkZGGGafJIqm40l-JDDDk_fvqosQ4RdoeRC4zeM6kxRNXW76_vQyjjMMeYUgiElEuZp4Gl5JxI68xFk55G79qqWqxzSX6cc06KhEouc6CUlaAA2Nam0ywxIUD2yTiLlsQXjrFtHRR8QCCauik5IUCzWfWnASCTc-k4QIhS5HQa27OOZy9FTNueP72aTv18Gjnz1Pdao3Zm7mfT1FW33F9_0FCsrXLO9XKhnV2fr2--eZeC3z667A_jtB-MVtuXTxhpfXE53t3FmMRoZt5sV9unF9vL7ZvXz2jaP7u6-KM__O1XTx-RAkLIKTtrqrqe_SRg3t3e3uyH_WkMgd_d7MaYQyjjKa6XLQPOcxjCvL-567ru6cuLb_7613_8j3_fi3_78-8Ll2nwzWKRYyEoRIgsZJQ25EdPikSBoCAjkPLes1BV10hGG1stGlvXLKXEWESi9-ohVsUAIAUAGZRSWhtSmOYTcmnWy8ppQZ6PR9e57nyb-vj8d940Siv18tMSAVCxFd1YHhMRIQAXkVxUXdHKiQ8YE5FJUwrjyCIlMRntrL273ldNRUbN4-y6ulo0cz9XXZumSbwPfRTOwAIxkwJCgsKKEBGsMhITkqkqk6aUiriuffXpJ_v90bZNt968f_tusVkOx-N0HBmKbZt-35vKaCThaJQ69T2iQkRFRKSU0cwZWCpjbm93fprXl6tpGHPKQKK1SvNgjM05CkuOkVlQGU5penAGa-Oays_eVlZrHeaoSCPpwjKPk7YWEAqztraUoEwliHEera3S6KuuY-YUE2pCqzlGRQg5p3lyi4oBldI5eGQgeQhoitIKiQRVmj0hKKPz5OlhvpMzKMDKgghIAWsACbWBLGSUcIaYQBAEgBiUAgAQAWGwGliAlYQJBN2iE4gQRCtgH0QYleJUbF2RVrqutCaK-nB7YoACxKkoB5yFWDhlMJYIJAYoRWJGArIKUkYWKQyllDlqW0tJHJJoksRSBDmV6HW3SDkpYcWFQ3FdG44Dam2U2V3fVItWmSr4qJwqpXSbjR_HbrUSnXXjlou25Ghrt2zaNE6D919-8bTvYxFxzjw6a-8Hr63pNtU8-f0USCtj9cf70-1h6LoGUlGAK2uxlNH75dVi9BMHjJIiqdbZlMtpiiFz66rCNJf4VYgICrU6ZXBAHvn2NNSNy8KGbGQWLgkYAU8-dpfVzcfT_WmaOE85JC19SEUwJEZNTV3nUJSgCCPB7H2JMcSs2-r-NOsHmIHQtrb4oAmSj5AZJCGh-Vs7FrP3KuUcorIGSi4pG6NFirBkzspp0hjmbJoq5iAsORXrHCjlcxnHyRrcnK385M9XXVMbS6gV9jEvFm7RLLyfPn16RUrWbbOsqzcXy1XbVIYebbonm65CczrsOWMBaZzlnKgACgDC0hop7Mf49ubmOAXNNMwJiYfB-zk4o43WKOJ9QuTRx4_7Y11XtqqyUpyzCFe1c7W-vz_042hq3VYOSr4834YYuOTMMs2hj8Wtl9-8uyGlv_9-N5X84XicplSUmuf4_f74-tF6iOX77-7arn5ASrpu_f27a1fX_Rze3Z_e3u5BYSiFI__eT56mgIy4Pxx3ff547ENMMcXTMP3y7QdSFgH3-9MQc2EOMX_7frcL0Va6IDiF85y-ud6lHOcUx5AmH1PKIZW33330MTLpmOLxcDodewCsXN12NZcSUkIkRSQApnJksXVGMs9D7-fw8fsP2kLqp-w9g6SYgWgeppxinIK1Ns0RCUhUjqH4hER-nkGgcGmadcqxMTZz9qMHBABMnMMYcimk9EOfvMTS96OzKhRZtl0Bnsegnc7MDBBTYeCPt_tTPxZQRaSq6nn2mWl_fa9tNfppuViUwotl44zb3eyqylV1ozSlnLkkY4yuLDNrY6AwIcaYOJaUkqls9CmntDhfFZ-BhAjmea66pbau8MPYpQAQZ-aU2naR4siFtXXGquRDtWht1RDCcDpUVRW8LykTIaJY7ebxpLXhwqTQOCtQkFBydk0rIoSkXIWkhKikZOuq5GJd1SwXLBlKYQQGqbs2FxBEawxIcW2LiG2t_8k__sN_92_-v08uzv7H__QfaK2k-M-ePjJA1lRtq9dNFWM6nYYni89AyFZuvzt26-Xf_OXP66b54gef3d3e_86PP1mvm__Lv_5_JZ-efn714e1NnOe2q_3kSeD5q6fb7RIzIxfMcDoNKbJW6tkXLzLk035SiafDGOcgKVetrZbN6smj7Aujrppt8t41dQoFBJquco2raxtTJA1xHnOMbtkNY372_Nn1d--YqeScZpnHIYfYLBsi6ZYLZRwpo43JiYmUTDFGrxRYrbVzz15_dur7F5-9_PDtR2vV5dUlWiMx18vFi0_etF232HaLRScEH97e3Hz7bTr1YRijn6qmKmwWF09evHxVNcZVDqV0q0pE-sNBKRTGcThcXp4L5P3-VJtarDx59rxw-fa7m_2h326X26ZbXyyNa3_5669ySfd3JwI6367-3h_-3sV6_eazl9ZoQOnH4bgf97vjN2_fh0y_-vZd01S7-129aEAQBe7vjq6qXGOnaYgxno6H15---vTN0_F0YuB-f3j25Orz3_hMWe1DePb8sbVGkvjJd9vt4-ePP33z5u_83k8vLi73-9vzzQYVXK7aP__Vzz7c3Oa5_5P_4h_85pPLHz69uFg1SimO0ViVcg7jYIyqjJsjXx_6s1WXSjkOfWWUQlJKI4lCYpB-CuPsE0NiOE6haqrMOM8xlzxO8dub3dVFV9du9qn4mAs8cHf9MCwWXWZ2CltnvrxYPll3rTXWaGEGFBbxc0RFACIic0jHcfRJ-tnHLKehDzGBIIM8fnRx_eFm0TSVNQrgOM1MigmJ1PE4KqdPx-nDu_sHFb6wgKIwzSnm_jgoo2JMSmtXN9HPpIyy1o8TC5fgMWQIKY0ToeKckUx7tuRpjv1kiHIqpmpJYe5HBCERZGIho7VVqoSUZl5sFmGeXF2lEMPp1DjlLIY5bl5cEqv-_lhtFlrb5ZPVcL0_3e4YirAAZyJtlm1dNxJnSOH5qzd314c3n3_Rna3rpoKU7t_dLteLoR9yDMttWy27XIAU5n7OAO1i0XXtalETx4U1w3e3j1r75OzqX_zzv_v8ciGc-mk8Wy7IGIUyTKM27s9_9dVu8teH4d3H3SlEdPZ0Gg79dHbRrS4WYz99_LhnTstFVVIwTOv1smnbb775MIwlpUJKK6MvXl2UkI63u2HX287mmKyzIUcSJK1tZZU2OaeqaQExxchYSKmcS-yD-dupj0gMSKpkLkkeSAFSWkDiMGhryZhms91_uCbtUk5KWYFyfnUZbn0cJ0XPP0GjlNVlTlhpMIbHSXctF0ZSpHWZImSGBNoZ0oY1KyX1onPrRZgmW5mKoOnsdJqss-gMKh18jnOwTVstDCkss1eKciykkQihCDBo3ZCG6BMrRFBIul1vj6fj6uzC1Xb2vm0cAMaQwjxbZ-c5Vm0FpaQYcyo5BkTtg3_05NH97T57r5Varlc5ZoVQGKBwpQ0AaK2Ou51t6uPuZCsTQwEopSTSqnAJ_aS0EmTtbJyntuukRCCMKVhrQ4ht24nkkhISIiAipWkUgWa5zskTEZdcSgZUpE32QZFiZmXMw6ZsHAMAGlflaUYipAcKVrNgSIWIqrr2-z0RogIpRYSFGQEFAEBAEZQMhQEIcgYpkBhKQafA4t_6YThBzgAFQgZXARYAAa3KOJu6KSVJKhIZkDhGKIyESBUALDbLMge7bOaQNRbSJKB4jsAJcxFWoAB8QWHwngjFR0QSrdh7BAZgNIqlSMm6thwy5Ii5ECnTLThn8JMxWjKbrs0xZS6c06NPP_n49p011lpMPiOquu6UVbOfmqYZTmPXtFqp02HqFvWzs-3d7dBUxsc0zHHoZ85wfXua_dx0HQiPp-np1YUPwdUmEwc_U5HGVNM8H4YYhQCoc-rj8aSts4vGh9S0LsQCilxlo0-itIaiNc9ZfCljlCKsDQ0-zWNkg9tVexgCGZpjLoyn3kcuYjBJyiH6kFNh1JBTBoWD9xIzlFTZKseMxAbJz0mbmgViCSIlDalpqzjNeU7WKcwZWSSIMYqlsDAxWGNSTNoZziWHRFYjIHAWxBTLotmUEgQxxiSFlQhoTQqbpg1zlCLGGWuNUdA5pxms1Stnu9pqEI2oLFqjUoxNrXoRiKW2VaV134cYs0K3rGzX1UbjZtF1tavrSldq1bVoqEJat93FZrlaLCtnlCKrVWH0PsYkTIIETNwPvgh3bTuGdHN7__h8vdksCSCnUhv75OllZ01X1dvlKodQUOZQfnlz-_EwIeC3b281WVfrwnx-tvzTX7077k_PXj367uPOh_ndfvzm-oYRv3l3a2yVEBpnVstOK8Wk_38_f1ti_O76LsSsrXm399f74z7mbz7cR4Dvr4-nKWKlhUFpOozz8myx2w8hl0cvL7_59qZS-uN-mGI-juHd_f79_ek4j3PKxjrRlHOegwdCU1llrI-ziAzjqVu0CrXTyrD4WERhSgkAwxQ0Un8clSa0y8Pu7ni_A4A0zfNpEkBQyCJaqxxCShERjBFgYWZlbfAjAhXOJacCoo0RyJzLNEchbLq2lMJcHtRSylDOORXQSLXT664WhnFOo_eFsBSZ5zhPYX-YtFaSc1VVxtmUc0msDKWU9_vj-myhFHhfvJ-Fs1YGhOu2VqSB6HB376dJCghA8LEwKwKt1TTPwsySjTVzP3brVY4JGEBRmGdlDTA0dZc5z6feOqOUyimRQqURJIqICDOy1kZrBUWU1SLoqmYYp9VqJZC5cFXXioCZpZS67VJkXVmtta6sNkZy0cZ0T9d5yvPsjbOSmWMCEGEpMUFJiIqMVlqVzEiE2vpx6hZrZBFJf_Jf_vFPfuOLX_7NV3_yx3_YGPUX__3Pfvzlq4tl1zaNQpzGMeUSczqOPpWslEGElOXXb99-8fmny2VT_Pj5y2ezT__Dn_1inrxzat12w2lGoadXZ2-_vX385GpRVaumk1KUgczyqw8_e7S9dMb1p7FEJqvrdcMhEeHZ2daHSRjmPiDidrNyFkMKpfBq0z19-nT2vqRS1XV7fjacTpWhHElScSvDKUvhzfkqpCnH1LaNn_z60bkhyoC2a4noeJxJq4snV8xQ1bWyzersvF2sjsejs3axWLz-5NWjpy_rrj0_vzh7dNZ2bWEZ_bS7233_9qvrb94d73YPWiUQssYuNpdvfvjZZrtqF2acZwRebzbbi6uYc1PVCpU1drtZzT7c3R8352tbV_2h74dZK_Xbv__TL148vlxv1WLxl3_2N7_66uuP7-9aU-nWfP768evnj2MOwmWcx--__ai1ub7ec8EPH25R6WGcnHPDNBltSNvt1TLnYiytztaH-93F-uzR2XnTVouu-Xh___a76-Px-OOffL5dLw_7vq6q9aY7P1t3Vf2Tn3zx6esXz588aZuWSzlbrn7x8591y5Vxznbt7jQY0_5X__wPf_P1s7Wxba0lFS6cQ1i2jSYIc6xbl3NxxpXCj883lbNW02rRGq0JVeGCgERUAO6OA4P4VPbjZK0NPg3TVFlNim7udm-enqOo2-t93biqcnXrSi77Y99UbuF0Y-jp2fLxpuuc1oIohIq8z7YxOYqPiQGm0c-xDGMMXEKBueR-9IjK5xhDauuqHyZN9ORyWyL7mNqq8imBQE4yTiHF_M3bDz5l3VofQ0ox-Hn2IXNCQFAApJplV7KEKWqnQREKu8b5_QFTREQQCT6a2lVNMx-mMMxaExLYujEOw2EqPlSNQ8bow8Xrq3KK82nihNuX5wJCgNEnjlEprMj6MbaPzvOMh-vd1bNzFlDWTfcj-8hxbtsaFTKAdq5eLBQIlmR1k0L87Kc_AJDjzS1HPt4dHj-7ZMXVpmm3y2M_lwIXT6667Tr79MVPv7h8folxthrSLvyzf_a7Z67-P_7v_9UPP32-bW0K6fb-uFlWxjhCAMF5jH_5i2_fH4Z6u73e7auq_ng8Dj7lTn_cHd-9vf3w4eP1_a12NoWRCOcpvfrk-ZNHj1LM4zh_-qMXAbLSVQhzmeNpdyDCqqlIIecM-NChUYQEBXNORGRsrZwJYS4pK5GcousqkFzmhKILpOwDC2BtCifjXEoJEUhYEJSpwjBpZUzlpJToR8myeP5svt3193cKnr4GJE0KDD6ohdCoPHmqnbFWFAIg5CIA2FbKKbQq7UcukEOZT4MSSMPEIPEUcygsxdUVx5JjstZAkRKL0oRchIEIiRE4C4tgFG1EUckZFWhNuYCrG63VNHk_zE3XjsehcAl-Rq21NYf7PSiFUFpT5xQFFAjrykz9KfqwXC0xMwjuTse7D-81lBQ8Zwgx1G01nY6S2TaWQPw8-dnXbZ1j0EoVZmEcDgdUgAICstycE4pIAUBSICyo0DgjwDl6bbQIWOeAOMe4PrtKwc_9YOsKSUkpIiiZSQFZoysjJQEoW9XMXGI0WmmtlK04ZaU1gihtcmTj3IMyg6eZtAKjQCvgAlxABDU-uDzAGMgJNEBm8AUKADMIo7IgCisDLcGcAAi4MDMphSDiA2hUAAhY5ok5CxQ_p5jy1e__wN8cNIuuXEZATBAT56KaWqRAOIKymEURYSmgtGglD6urpaAizgkziAJgQRHFAgyqqxApHntNBMJoqQiR0phz8qFeLP3Qa61yKMa4zGGxqEuBeZwRYXN2hiJ11QxzNBo_eXoZQtlcbvengQmFSBtCRT6VOSQ_zrd3pxePr6ZpyjGS0vdHX6-67dYWa95_c9da7VZNTmUY-qp2dV1FYSTa7YfLlxufZColCvdzGGMEhIvWTkUEcdkZMOpwN3zcT5ulO_bzPPmcSkypICZO8xSyQMr8EEInpfw0K4bp9hTn8LCQRApzykDk_Vy3FgTCyWNO2c-EJFnAIgdWiFy4rjRzYcR5nI11D0Mbgxh9UACabCqFcyo5pTIbZ5ixxAQo1pnhONVtBahSLjmlglhyOd8s2sbmkNuuut2dvr_fo6g5MyChUdMcv77eH-6CQWq67rCPo89n285Wdi58mubDaUwZxpSb2uY5-inu92MRUhqdsVlYW917P8yRCa73J1c1UwzHwfcpHse0n-YgwgzPn2z3h-EXX10TwHfX94g4HPrVqtNGpZinmOYsv_pw8xe_fmeWy_thzsC7Y__66SNnlBHo58y53B5OmctpP-z2p3e3u8XZ2cfDYR_TEPz1_X3TtkWZ4-Qvt6t22f3ym3f9KT1--ejrdx_f7e-_-3h_GIJe1Y-fNr_8_vZmP-5yHqfpm3e3TV0nLsnn93fHmw_3YNWbZ2eTz199_e7t-4-L5fL-cCoM9_vTNAaGv23mllz6U79cr2xlK1NNx3mxXgzHYZ5nBtZ1TSRcUtNUOUcpbKw-HG_j5AU5Jh_mWaAoo2xTC7NRughzFk4JgUssurJx7DklANLGgCASaGO4cAaxzgkpZQ0Ap5Rc7VgkMxOpGJMmhQgKlABwkiTsQ845KwW55IeYgDU6l2KUfYjKcS7HfgBEVxnnrNIWtV4sl13TKKNzgqq2N--urXWurkOIORdkSXNIcxhPvbI2TLNStDm_lJxzSkZprfXpuO9WSwTQ1h0Pd3XbuKplQSLVrDsQmHqvjSJSfg5EehxGY7RShMzamJSDsTbnaMiWzI9fvhpOR2tMSiWX3Cy6uquVsuNprJpGhA1pAEJEbZQz2lhn64qZl-uVdYoYoo9VVTnXmKoWwXrTXZxtnFJPHl19-cnLv_uf_FQXrh3-we98_uTR1WrtXj-77Jw1lhQIA47z7OesK1sSCHLXdU1baaVKCshytugAsLDc3e98CfMY_-if_f2b727fvH66fXbmJ391tbZOvXv_XdO0m9UKFV2cX7TKHXcnV7kieb8_zcO8PFvO4wlFXOf86di0dnO-jn7OnJCLIR72p2qhNRrUbAFSjpJzjPT46vLZT57nUwzz6Kz-_tv3y02nNG0vF9nntnXddglQXGVIY72smlWHWGrrNs-2q7OzqqlFizK0Wi2qbrk8X98dT3cfb24-fv_Lv_jr63cf7m9ugvccErJytmmbpltsuvpMd91P_s7vaI1KQfTzx483337zNqbU1c3UD6fTcbNZbpeLq9XKhzTOnkrc7fbXd_tS-OnTJxcXF9NhuP94vzsc_92__4umc5988flPf_wjpWQ6jtM41ev2m6-_e3dzc3_XIxQmMFV9e384v1gpo4mQRDznF58_O-3GtrNaO0UIzOvlsjZqnkajVIzx6cXF8xePNou2MtZ7_-Tx1eyn2pr9OP_kizfLZUNI9_tTBn50ti05OouKeLNplxZ_49Nnf_dHzxvFFrGuDBYcJl9Zq60epvn2ftwu20XrnK0IUGujQImA9wkIEElpYoZUcsocC_vMdWt_9f7OKHt76AvzHJNWilB9_ukjZrzf9YtlW7mqcXbs_XAa6tpt23pV282iWXeVpNxWVqFiwuhT09WpwMPpf5xDTGWYQ0a0lf36u-tx8kA6BD-H2DS1c2Z_f9p09WLRkVJjytd3dx93--vb4_XtbrNdtIsmo8wxMcF339wM0wyIJTJjKRmGk7fO1V2TcgQCMLqkDMKh73mahBmQSkq6ssa6fr-vW6edCj6h6HpjeZrLnJUmBIwxLDZLBOx3Q7NdrT6_GG5PaQxh8kqLtabMoZRsq6paViJls6pzSnMpypCG4vd929joZwHQpspcVpuL8Xg4O9uSqJefvKwq3R9Oq82yPx5MpT9-vGtqZ5Xt7w6ryyeLpibmpmpI2O9O8eP-Yln98z_6nf_N_-qff_ro7Hd_53OKubbaGhp91Aq6ulKkjXXHvr_dD_uUu_Ptu7uPv_rFuxL57GKdSvn-q-u3b28XhsLQN01rrP7-w72rqt_7g99-fnW2rKs__Q9_0W1XN3e70yn4MLvKhdEbTUQaFeWUtNYlBUJQhCXHEmckbBZtillQFJDWyk8eEivn0jwrRAbWaE1ltDNYkJihCDDbqipBqkW3eLzJY-IUkCSHbOt6sT7TIMB96EeFz14DgTyg6dYKkGkdIpm6ynMEjZwyMIBCzpzmWAggZGVMQZHJc0mFRQrauiZSEpkFU_Daaud09klrStFzKiJCWkHOiIgiGVBEAMg4Ox2OxlU-Rm2sH3tENARj3yMpEJn6ybW1AJBCBhGB4_FESsfo0-R9jP3hoLSehmm9Ws9zfzwcEbFuquEwCuqCMg_TarPe3eyZszxo2HOp26akKIKIsNieGau10yCSIucwdYtNSqnp2sJsXZVi4JyYJceoEEnr8XBcbs6H3f3pcNBK2borJT6M4JmLrgwQZR8BSXIRQG2UsRXnpBWl2ROiNg4KIxI-WGznkZxGICKAlEApedj7VATMKIJIUjIQQM4ABE5BFuACYQZlIBUklMi0qMRnMAi5QARqnULiEJRSxMCFUBgQOJd23UIp_n5oHz857HYsGjMb4OKDRPnbJeAIhAg5EhcoJcciCkFAAQgXYDRdzVNApQAFclFKc85EVhBBhKRwTHmOtqml8IPrtOnanGLKSWktKMrayOLaNs6eU9aKlNKSS-WUruoSU8z5cBxiDjEXFiQtxihl1OnUZyFVqW---e7TV28AyzDMQ_SSoj-VZ4_PlKX7vo8pnb9eD4dQhBbrlnO-2C7ubg-SpaqdL-zHIASpSC4wloREs49ZaJjjcfJjzqfZT1Nk4VISAJaSMpecS8lCSsUQUxIAyCkzIxnk4Dkz4cMfgSCChBQTuIZ85Lox_nYga3hOqAwpAWb2hZBIKVSKY7ZaI5cSiqnRKpoPIxjlmgYRwzxyTCyUmPPDgFab6D0JmrqNOVlrChcCroxSUVJM_Th5nx4_Pkehu_3Bz_F-P59drhat7ge_XlRAYFtqOmu1qmo7TbMyar1ZamdzyjGXtm1zKbPPt7uDRmi7DgD6OQLqfvQxw2n0b9_fR8Rv7o__7k9_ud50337_UUizguvJn60WzikfctPURGiNAlRdW_lY-pT-7V_8Yj9M28vtcYyn_cE5A1mEiiP7737x9Xpht5t18fJ3_84Xd_dzs2wY4P3dYYz8fnf8uD_9-sPNt9cf__Rn31ZVDVMk6379zbU7r3_1i--v74bD5FMpIeT31_uf_eL6cDyOYwihAEs_TO-_v9VOb15sf_6zrycfjqnox-cf399t66Zbdikl0uRLnAYfYiwlMAuQYJFSSvSx1vZi29m63h8OMUku88MmPyogMmTtPM4ll7kfpn7gGDnEHLwyDwy6S95zkaqq59ErwBzTwwtOgMMDGahUt1wxMxKlkowzMRdFShslKcdUSi6ApTAAoAhYrcmoYQrzFHbHQTsrwGRNKTDPXhvrYwakEMLuMPqQ84NaIufZe41UsoxjAmBjDAAoIs4lhDCc-sWyy_KAhduUU1XVLMVVpmrrB0RMawMgJQVCqutKGe1H33QdEczj2HRLBkEBpU3Tuuk0C_PiYpt90k4zIpZStXWYfC4ZSaUYn796FWPabjcpxc3Z5nB3JwxVW9eLWhsXR2-dKznllKIPVV2jMmeXW1LEzKQ1aRfHcPnp88P1vTaOFJE2SlPVtNEHV9Vf_PQHL54_-vDLb_8P_83_duG0jqGr3NXZcn129rOf_2K5qLaL1pEbxyEzT_M8DrOgqpqaS8lSzrfr797drJbdctnM_WlzsQXhf_8XfzVP09l2--LLN__x3__5dtu-ePToL__8l48fbZ020-QPw8lV9iHL0BoXZt-u29H7-ODbLnGx7hBxCtnPcX22HeeQCkuB8TQf99PiYlVV6te_vN5ebHOJ6_PLaRwiw8vnl5OPw-1p-2xx9ehx3VTb8_Xq7Ky_P-Z5xpTuPhzGPtiFuXr69NmzVxdPr9bLzfnFxdnFliz1-2EaxlM_MEFKefbh_dvr2w_X1lD0AUEZ40jZi8ePNpeXpnbPfvDy8vHFxcur9flic7W2Klujv_767TgFV5mzzerHX3765pOXVtnN2aZt69ViEYEO-13bNnXXrZYrY-yPPntzvuym42mzXsbCscDl-co56-fp7dt3-93hOIz1ovvqV98f74cYQaQopfenYRg8lywM0ziZyo5jirMYBEUIkUVg0dRN7ST62lgQOVt0XdfcfLxddt0c46Pz5dl6e3W2efF4e7lePb3cAqePN7uCvNh2vfcfb2_95C2qL948_4Offvlq3W07Y3KGAlOItbExp6o2ABxSbo1tG0cgwafaVfQA_6HKuQzDpC1VzoWUmTllDjEvV3YMZXeY-zmsmtYnNpqaxllSVeWwkEZVmEsuXdOm4FPKIeWffvZk2TYGsa0tF7AI4xy9T0VAkFLJMZdhjvf9CYlKAW11Kvl-198djkrpwXtNOsT04y9e39_tXj-9rJtKAzHln7_9kFPJLPencbFdurpeO7M7DHbdfrzeI4GfvQJ0XdVtVtNhPH-8ddY658bThISobMmppJjHgX0gpUoWkKIVzcNgtLVVLTkjkXWYjyH3I5EAEioa-9iebfcfjo-fX5XC4RTd0uQY8-ib1WK6PWhbkTZN27TrRTwMnMswZYWmW1b-eCwpkNXzMLqujd5fvXxyut0tmkXb1p_84M32ycU3P_uVa6pT3-_uD4D09MdvFlfru7cftLNd5TTh2XKxrOjRwv43__Wf_Iv_4vf-s7__k6ePz4STQbO7vV0vlpWzpCgxFC4frwdd28PJTynvhY9h-vr99X538rN_-uTi9U8u3_71d8qa-dRj8aZyL758evnq6s3V1W9--vrVo4ttU__5X_7c1paJBh_7vp9zclU9znN31g79lHJEo2IpYcwgOZx6H7J1FaeSUmQQo62pzHw6aSJTV2EaSpgkFXKaLGBkTpFTImWsJVCaQOpl66p6uD1xiiGmulnpCuumKoi1a3755399seqUPHmN9sEZUPI4o20zFy6ozuvcT-wDgiACVQoBgYAMUS4QE8QkYRbr3NM1hZRCEiSzbBlQmwZylBxBAIFMXcdpJiRXKfYZQVAhACIi56StY1Kmtu1ilUsy1mmFzXo193NVuTDP1lqFKAQpBgIcjkcCKjkOh2Fzvp6GUXKuKpPH2c-Tqytr7X6_AwYWiNNkCFOK-7s7a7UfJ1NVSEicTnf3iohLsc7m5F3TDsd-fX6Zg39gT1GRAMzTRApziqQoxyAxMTMIK6XmobfOESAQG-NQKyRslisQyZmBCBGQWUJELso6ACKlwjDZrss-ojZAZEwtnEkrQKWUgvy3GyGgDFonIPBg_ygJQJQ1lAF8QhKQhzSUBleBoO4qHicQFDIQEgAAIcQgCKIVxIAxS8kiQIjSnwBV8kll5inVT69U28a-r4xC70FYCpMCTsnUhkMiYUTIiZUxRBoBS4yaBQCwZGAGQOAHxYdGZAECZThFRMCSCUGYtXFIEnwkgs9_-uP9zV1OCUvh6P34_2fpP5ptS7f0PGyMz0275nLb7-PznDyZefNmXlPX1S2gUAUQVQJAkAJEKMiGIiipIamnhn6DfoOkjjpSyLAhUoQaBCAxCFcof33mTXf8tstO99kx1NjVXbFWZ0asOccc3_s-zygyI4hS9Mz47PmT_WabXLxerRfz5b7tR9snApTSaDGO1ltfFrnRpu267XrT9_uXb6_ef_Jcl0ZQHPq-nDVX67bvnWDpE2175_aOxiS0MYVp-3G0jg1SAESVGCBXDOi8N7keXQABIaXdYFVlBhulAS05uIDAiSgFopSAEQgYSRAABaAIxHcDIkRil5iAme-a4WmwyTk7BCAiIpKMAkVkZBaAlJICCL2TlSFmuKtcA-ocwt4qEMwJpQqJGBkSQYgAAQWmQEKpGJyRiCAdsTE6BlZGt53L6rI5nIxtn2d5EPL1as8IKstBwLrt2iHY0b96t1rvttvBtjF4otdv16-vdy9W68-_vsyUGAb_7vpWSe1TIk7NbHJ6Oi_KYt3Z0dMQ48--ePmrL1_e9kNZFqaQ-3aIw8Ac7OhUpojY-_Drn31zveuu1-1y2eyH0TtXTeoU0ujdaj_8q3_7ZzubXrxdt4NngVluplUlGA6X9at3N_t9d7kZZk21XDS71mVG6Sbbj26zH795e9X1ox3t7fV-vWm70bVD_-X17dWmPT0_Xe26m10LjLtdN7q4ud54G7c3bSTwPqKQ7X5sbzdNpTfXu998cdXuun4YB-vXr2_2Q7fvHTOMiXZda0weY9pcbwTDZDK5d3r_8vJd9DEvy9ls6rwbR2uj14UCSkQMUnIiLTEGG6y1_YCC4tBRIJMbcdcNyJRE5BiBaBz2QoIAEIKVwmG_D8GyEIIxL6txGE2RCym8T4koK3IpFUghhWQAgZxCSoSJMEUWEq31LoR-tMqoYbDOx8RgxyHFSJCQhXNWaa2NGp0lZmeDyJREpMCsZQwBKGmtC5O9entj8kIq1Uzn3XYnpAEBQigp5dgOidJ0Mu37EZgBRJ5rBB6GIdMmppSYps3U5CaGJIXQRo5tb52v6pJTyquy6_rEIStykSktZfRRaSUQlFHyzngfKS9zJZXRKvhQTaq8KFNIi-PjLCuUkhy8UjImms5mJjeT2fTmzVVRZFVVu8EZJYs6N5mKzimjNKBgImI_jEh8dLDgrjtdLH_3p9_56Mm5Rn7y3vnBYrFbrS6ubhPDR-8_mFcVU7I2ZEYhSpEpROms6-woGdp-rCcVMPnRA4tJk--342-_vrhZbcqqGNvhvffunR4ejoMbuz7FtNntgKDMCwkiRB9t8H2XfNClevDsEFGuL9djNwbvDs6Xm5tNUeTtbl8UuVFSIOdlVuSZ1lhUxWTSXF9tqspcv7s8PDhESF1rY7A09uNmuN2uf_XFuyw3mUrzSYVSf_j7nzbLJi9009TDrn_z-s3N2-vdaq00Xrx8ff3udn99Q8FSBAlCCmG7USmoi0IASpnNF8cffvrhydmJkmrf2aPjaV3VfrTrm7feh199-QsmPfR22tRGmbPlfD6f2XHc7VupTNt3v_jFZ7_47LPXb15drNrz06P7j57cOz25f9gsFtNlbdbdWFf1tu_Ojk-UNtvt5tWrKyEpecoahUIOY5sVOvqglYqRGUAqszyZlUXRzKYcYlllVZ0JhsPjxXQ-OThc5gKPDmZVWSrBh7OZ0eJnv_zyg2cPpISj-eT-yXFTagGREo3WxpDWm11R6F999vLFm1dj75u8-N5Hzz569ODRg-NcJC3Rja7MtM6MzhRSQpRucDf7XmlRFVlKwMDD6PLMsBAJcfShtbasS5Ri347btg-RxtFpY0YX3lxvQantaAEYlWBgZnA-hNGtN7v1apvnpixzTMH7cHzYvHe2FEIKAkDQElOk3b41WheTArXsh7Buhz6kbT_8xddvm7wYXIwpDL3_5t31pMg9QIjc2x6BNaKWZlJXKXFk_vyLV9erWx_ZJy7qqpyUgunF61W766xL7b4r8sIo7d2olfb7EbUq80xI2G220UXBhOCTs-x8GqzSBoEBEQVIIaUpq2Xt28HuR21Ukevxdk3dYKrMVJN26xb3D0HC9DCPYxr3Qz7Jhs0YR2eKHIKVSnXb8d7HT5C4zMzm4tZ5Kif5vW-dXn95wRSIY7dty6ZAaUxZNZP6_P696WTyvR88J-svXlwWk6Lv2hTjfDFhTG6969a3SuHp8fLpveN__Hvf-8m3Hv74k4f_oz_47vGiTj7G6Nvd9ujwyEhpskxLFWLabrqYEjOrXOoSfvbN5VfX619-_iIqsdnv7RjawX_87YcXL25evdt0wxg51ZNqPp99-J1P5rIqTP7s_YdHk3x9sx1i2Oz2kUXbdtVs2rd9v2mrstBZNrRDcN55b7tR50JqIAJpJIeRY5RSZJkOdhh3bTGrKSUhJTMxKp0btASBEsc7PmhzcOaGfQyQZbqsKts5DiNIBKUEhaOT4_Z6--RbT904KEQZrITzxwwInjkRCkANKjfkEifiQBAiBkaBjMyROBF3ViQUjBIhsdI6w96lwWVlAULHlBAg08Jb69pB6iz5KAwgQXQhdANSouQZBQALgSyE0EopXU4aDkkqhYzeJ2aWUrbbrZCSiZTM3NDOlodD2-ZlFp2nEIxSlNLkcOGHQaLQWVbUNQJ2fccpIQopoFkeCOQQYp5n2khTaGdHP47R-7vmcFZkKUY3OiHFZLFYXV5m1ZRTIOZgLSJ6F5gSIAfrTV5QSkKIseuIsagnY7s3ZU7EKcWqmQJzigkAAFgbjczIaEzGyaW7J5xUDJBCMkVOlJCRI6EUjIJiEihSTGS9FMjAnBIaxULCOKJUHAmFIAooEEBAYsjzu4AQMFMmhIucCLQGKQAYAMAHITL2AdKdeYoQWCKKquAAWishUFIcblf54XzYdHF0UggmohAlM9uBUKKQICXHIBKDEIxIzAJAIEXrBSAwUCIGQELBkGKilFRWUoxIpCRAIgBEwKwqs6zYXK3t0DbL5e3FhRCYYiym835vT84f-35jWysyE1JSRQ4C3WhPDpcM2LvQOx9copQiSQYEoiIz5aR2llP0F6vVvZNjI6Ub7H7ohRZSq3bXolTOx5MHR_vrlc4zASAkRMTrlxeTyYRQJIp2CBFZgPKOiBOiiAGNUZFS8N53jkMSmJiIYoLIAAyRQAjgxIODxOSilAoiAwXyTiAQM4Pg9Df_LEnIbZeXVQxRG51CxNErJQgRBOEQBGMKkjlJoVKISEytAxcEIqOIzDrPU4pxsBIJfEQWKjPGZK4bISWWAjRkec3AeZHF0Y-DA4neUzt6Yh57myJNp0VWZiWKSW5MpgcXZKbXq-H0oKmFGUcPIZwsJo_Oplqpi5vNfN68evMGgOazZr3Zb9tuOp2wyr56-e7l1a0kIZV89PisNNmf_vlvvRsJ4Xa7e9u1R9Ppk0fnm3377P5hP9jDRXOz2QVCa8Pry9vFfPryZnu93WJm8maGKCez2vvw028_7a1NIWJKf_V6Fdx4sKyFyNq-vd5sKWHXurrIYozlpDi5t2SCwUYHePbgZLVr312tEOTP__Kzt1dXnlLvrY-eAyLQYl5Pz2Zn9-alUVKJYb-vizwrTGaKv_UffTh0LjHvdm3vXQyslQxE69UW0ay322pe1pMKGMCl1XpLRGVVSKH9aAFBqmy32gYXESBGitYTpWCdHywRC8Gud1JKqTE4L3OTOAHiOFgpUKByLiAgADBicBalpOC1NiglMsRESmmtDQhgBp3nfhwFoA-OEiklpFKjdQLh7p6JCCmR7XohQWUmUYoxoZQAuN-MQktESZSEUiGk0VqhJUZKIfZjiJCEkAJEouicU1qGGLTGdrdJRNtta_LM-yCkUErlmTF55ry7C_zMTw9XF1dC4ti1k-k8hjhdzG9v10IZBGGM0Zke2-7u9iiV0gqV1hRpNp-zEErpft0rraNnQFnPGinUfLnc7_b77W62nDJFbQwz-34ATlKIEF1WVggIwAdHh5vr2wePTpUQbds-ff_9zdXthx9_C9hNq5o5KsSyMA8e3Ds-mS-XU5Pg3umD_-X_7J80pSHbz6aTSpvNdp9n-WffvPjdH34nR9DKpBjz0lCMg3fTWbNatwkpUybLisicKRFjnM6bcXB1NdkMdjGfPH_-NDPF119-c7RcAuEwDlKiUOApSikOF7PZvLm8vF6324Tw8u3qxdV-3Mf9emv7Ued6kpk0picffNC227pqpJLzplldb6p5ZQxSDBDg6PxQpiQFopbRucVySRSLQulcRMkS8fSwZhq7fhBaWpeGtnt4dBhQHRwujg6m906PlrOymearm003WCAClOfnxx9__1vk6cHDs4PD5aff-_bJycHZw5OTo8XRwWxS6llVZHk2m1XGGGB0nRMiL4ry3vkjieLsyUmm1RhcAtq17c1un4SJxKYo7p2dFUZ_9OH7H7_3wI3Dm5evb7abBNx5vlq1V1fry-u1MkgCdtvdbDpbniy1hKqur96uQvDr3TBrmmpelVVeTTJmdfLgUFCKoyWIHFNe5NWkPLh_nFJ0PiKlPNOZUoVWdVkJThHiTz55JkAumpoT9N1uUZedtS8vLt5c33rrA3GMdHRyVGT1f_wHn3z08PzRyXRWaA62kAgEVa6V1iGm3a5f7dp-17-73f-3v_7NgS4yo0FKIeB2P8osb63vHN3s2m60KSYWCEoUWUaISkll5MsXl5jp1lrrPKEAQs8UEyEKATybNvOmZqBFU-VGL2YTBJZCCSETM4U0jkFIlFKqXDlHg_W99b0Nl-vdyzfXk6oabdi07WLavLq6GftBZzrPDAPu-vZgPiu0yZWSJn_99urXX7-RRl7ebFyIV7fbYfTtrt3vh-T85cUmcBydT8i5RqmlG7x1QRXaJhpH2-8HVEIIdO1Q5bnd70VKQqIQGJNXJgNQ2aQaVnsabTUvVYb99VpRkiZHnTsfFk_PgSECD5dd4qQKSUxj15dVZred1BIAH3z0dNzsUsKLl6_qWV1Nm_msHi9vrUu26yfHS0ocIxCqs0fn8_k0y8zBdFpNplcXVwDBGCyrqii0kDpT9MGj4wcHh_-b__yP_-M__OEPP3x477CYlebdiy8f3H-wX7dv3lwv5_PDg0MhFDMLLQcXEqY3l9dQ6d-8vPq3v3y53o6vrjfXm23emGEY312tUfF0Oj2Zz3_9m2-WB_NhP8wWs8W0mc1mOsLmag0M7OnlN2_e3l4tF1MhkFF65w9mi6t3t2hDM51STC7GSEkqEJIFp-S8kJLGXiAHR3nRDLt9hoBI7WqbN43tbWJOMZZFQ2wlMiQGEEoqpWJdVpPFdDqbby6vVxdvi6pElXvncp1pwLqq_95_8Qdf_dVrTCnLlITzxyiVYBaUhEAiRqWJiVNCZikFAgkUHCKHJBiF8woREJCFNn_TPtO5cS7qPEsxSamqeZECAxOEFGwAgRxJaSUoUkgowBgTQ4jOCdQSFbM0JhsHl1dlVhTeWhAQfJIKszyHlKJ3RVXttqvoKRLf4WaHfkAUtu-VVomiAHl7eV01kzvygAJlY6wKtd93_b41mbZ2GPtOALq-lYh5Xauy4Lv9NLPWymQFISGx71o7Oql00UykYPIhLzI3WIIIBNE5U9UxRamUyYswDFJJjjT2XTGZDvseAYBI5xmFCHfw00AogWNKKeqiQhDMBICotcoyqVRillpyClJKIIbgKREISUJAJEBEJikkIUEioCSFBEqACQABAAjAhb_ZxDOCEiAlhAQpCp1DjKATEnOIyMAIMtMCkZFSjJlSaF1-ONMq88EhxWRHISQgMbDQGohRCxotMkujWAghBFkLQMhJCMGCmCLcDfnAUqnonJAgjMJImCJT5EBSQkop-FRVZdsNKs_Kuhqtz4pGGwMohmGltZEyjd2o8vLy6irT-Xq9icBFWYZEMaXt9cYFHxK1-7GeVBQIBFRV2XVDDA6VXkxms9nU6Pz25joR-hi6_S4vq27fG6VG602lBTKS9G2X1WVMkBB7O0ZkjokBgnNCyxCTEsCJOETXjRyZY2AfUCJwAkRIAJEFAFsLPkIIJECBkJDirmViiFEYKRjYepQCAzGzFBIQ4xjySqW9hcisIRFRN6pcgTIIJClCTMgoIAADEYCSiVmXORFxTEgBmFhK0LlAgTEAU2Im4DwvIHIKIYzOxbjet0CSU8ozgygudvuNtehw3dmmzNrW69oYwKYujmazGJmTeP93nrh9_-vfvq2nJga-vb1eNs0Xby4Xk7Ipy81-_6_-8q9Xby_eXm_Ozo-PDpev3l4f1eVfffn2wfn84SfvH5R5v7c_-fDJ0fFMAez39uhoQQJ22_5i1ReVIQIhYD0OJs8vrjbG1Nfb_bypyPqffnDfO7_adkVhuiFogZ31ddMEb99dbaqi2Nlhv-v2bWe0FgJ37Xi76SJRUeerVae1kgIN4sGiPjycnj2YZZOy243t3moUTVUf1TP2Cbzf236778fRQVU_f3rcrdp3bzbbfUsAjNInPw5xMW8sBTva9narjeEgtFbbti9qnSKxhH43SM1dPyQRkckNVuZKl5lAABTR3ZEyk1QqRo936GWpQQAFimNAECjkOA5GK0BI8a6HFylEbTQwZkUltFKZAWDnI2iRZRklkhK99UJIZo4ujcPAzCmmFKNSwvoYnc9yY7QaBhd9YuBI6Y4gvF1vGGG_6VFAohR8BMSu62MIgx1Qa-scM-uy7AZHIJgjMZjMqMwUZeWcrcraGB1iVNK0_ZCpDAUqKfu2nx0tU4xFWYUUEXAce6lVv2uJadjtUohFUXGiEL0ENfS2rptJPdvd3jbTWd8Oi-Pl7GjGjFmemzyr6xoRxnEkjsklSrw8OZ3MZyiw3e7yIjdlTpyklEypKksBvDyYIZCIMJvl3__-h-3NNY3jt58_h5D-3h_-fQXdbj-qTP4v_tf_7MP37v-DP_j-vBESWCi8f3KUmUxLrCflg_PDRVPkJkshKKWcT1mmLm72mVag5ayuTFb0g-37PhF37dA0dV6Yr75-3Q8un9bI6nZ3-_H7jyf1pJnWP__F58fLpiiLIi9vrm7W-93lxe0wDCdnp3lW5HW2mFdx7ELiAMl5Z623DOvbvTI6hnByutxv94XJpFLCKGZkghTT7OR4Mq0enp4LSUVTMgAoMS0n9-4fj2M8OJpJoT_46beuL_dX71a3b_sQfLvZ3V5eX9xsX3xz5YAVZkcnJ6f3zw7PDt7_6MnJ0YmIoirU_YdnFOJXn30uQPTtsG-HL19cDts-Au42LXNsihqYnjx-oBFRG2fjbjdISTfX66--_nq7b79685Y5aimZE7LESPP5Yui69XoXfTi-fy_4dL3a5Hne9265mP7o979zc7Xe7fYEvN_suv0-2nh1eXt4uJw0k1xpqdSkqKXAs5P5xbvdrC796J48PnOjTwm27ZiXefBhOZsYhrrINNBmszk5moFEreWTB2fP7h31gxMCjABtBCBmeT7J63lVZUbmKtta_PDhwfc_vt9oM69zZaQL3g4DaiFA2NH31vfdACiyvLBCr6z7_unBRx89JtDXt7tEKBQmwLbvgydhRPJ-3_fLZsJE3oVEYLRkxgB8u95vupFAde3AQlRl4WNY1JPlpI4hMqVbuz2opjFEBGRAIdGOAQUMzsHfUETEvu0f3EBFAAEAAElEQVSF0WNIV6v9ehjHxKvRDiFa57TWLPjycj1Z1Je32-TT52-u7x1MtTLKmEmdB043q9b6cTKtrzddCNQ09eHh9MvfXp4cLzpvhQRV5rvOjta9e3nZ2rDt-vlygVL44Le3GwBgjikmStG6IQwjAxGzzDJvozAGUVD05G2KKfmU2l5LjF7oeTM9PZaZpuDY8bDeCikkmur8sH1zKxVrgRLIWbj_6SeuH0yZ2bZn8nlRzg6XN28uJIKSKICijSmK5vjow--__-TRaS1IRPru7z67fn2xa3uOfmN3h5X-3gcP_7O_98Pf_eRbP_jO8-99-LTIVbvavr18--Wby0ePHp-e3y-NAYBHj-4zMBD4lCLFtre_fXvz179-HZS6avsvXlwg--Igv163OjdXV7vddjuZTJbz-cFsolhYCqSlUHmW6UleffnlW-ejFKouTIHwzetXP_rxd6fLvN36m-vN-0_ON7vu-5-8_-zbj598cHi1Wq1Xm5QSKA6ttcMw7joKMYUQI6isyCaZIB-tJ4Z8OvXOSaU5hkxrSJYIhjE9-OBZVhcEBCkE54qqKWeTrC4my6P9Zv-9_-QncvAAQip57_ETiuKj7z-fH0xvL64knD8CAo5JagUpUUwgEIwRUqBE4ZMWIqUIJITRMnpEZE9CaSAGlBQDRUwskEBIzURGGSU1heQHW1YVuVEA3q24UozAxMQpJqUy1DorSmYEFNGHer6QJg_BOxekQKIUXGKOxlQowY0DRY4x-HFUIEym3b6VErOisP0gGIMPEqjvx36_y7N8HPtuu_LOa20AyI9Wa5nnhe33Uigfos7yMAx217l-1FnmrZdSl5N6u1oLkCaTShvfj1Lp4JxWWhrDlICi1kZkWmrtrTV5LlEEZ-PoUKrgbVlP8rwIPqYYlNbexazIUEkhpZAquCiVugvzAICWihMJgVIhhyCESTEppe4O4oUSxAgZAiYgQgaRZ5wIAYAYEoIAsAEyA8TADDFC8sAIyvyNMQAArWdkEBKcBwQhhAAAAcgshIpjwECQyN5s8tND140QgjHqDphNIQipKDFjgkACKIWAUgMKoISUJAEEz5TYewDUWpOPQgmQjAmMKcUdjymS1ooppsggIRGZvFQaIQQJHN0ICEXTBGfDaClxCLGcHSIkSnHSTNrtkCKlEEymUWLfu6LWwGhdmMwn_a5nJECUedG3Ozv05aS-88pJoyM5oNTv-qLJrI3MYHKBKFBAu90hSpRqCAGlSMxEBJ5DikOISsoYSEgMBM55SBEMQB-AAFKCxBAZpRLk2XlgBiWg9QAKBNPg4c6YhloIScQAiW0QAihEoSUjEBJvRgQkqSEFlQBBoESVYeyd0EZKkEIxyhRIZIbvJn5EIQQwSyGij0Igc2IG8lYqKVAWRcOUKKW6KGIKLgUboirLTeez3EyqIpOiKfXxtOj3flYU3X6clmYyK5UQAvj4vYP9u22u5P2jw_Vu-P53n8yb5Yt37_7uT74LoJu6mFb1o4ODg8XiybPHyOEvf_nbxaKBTD6e1ifzpkw8LbIHD46VxOBTovj4_Ljv_UFTV1n--MlJiOmr1zchpHaIF1dX-2H47TcvGVJAeHS8-OLV6sW73WRiUJnT5Xxtfa51N9jgwvJg1nmXEgktcpMBAROdLGet9SGSUHx8MrejG6ybKFNW5cls9vLVzeWbnQY5mal6UhWTQki4vd3cDENU0u5HZMhyfXu1e_HiGjlY610MLFGiSIGz0uzW-6G3WsthvT84ORi93-1akYkUybaWICHA-t2lxizG6LwXWtlh5OiTD-QTCkTEGKIQkijdje_BB5QCBGaNIUpMZLKcOMWYICbgpJTKiiLEqPNcKRVDRCkYyGhDxEretfEZlUjeAUUi8D4WZYFA3W6QUg6juyvgpMRaSylF3zrnHCApY5hSnptu3zuXUAAT-zEQkFJ6vx9Mbooi3w-DkBIw9d2YFzlTCj5QilKoYXCZ0pt9t5jWQkhgAMSiKN04hkAIopkuhmE0xhDjsO_yskAgJdTs-MiPY16VMXgmFgK6basMGGW6bnd8dtL3vVD68GCpi9wIFZnzLO-HoZnPc2OyqgSG_WqlpNCZAcHR04P3np2fne53u6urm-cfPN3e3Pytv_PTx4_P-t3uO-8_-73f_8GwG__pP_37n3783vlh9oc__cHf-b1v_94PPjkpywfHizo3fnCANJtWzoUUfIxxu9seLBqJ0o9eKZEXWUyp7x0BF0WRIjV1cbvuwhgIQQISgnduHL00GXM6nEw2bSuYJ2WNAl-_etNMq2lZrtrtvu03u_7xw3MBsNn3Q995T4MN29uhnhSRiAIsThb1ou7aIcskE9ezJpHo2nYyq43R33xxU07y6aTJq6IuJuO-ZcbEKXo_Kcqr11dGwsXlJaF4t25362Q6PjuffuvjRx99_728kLOj2eRo5u04n-rAIctk7IfLi1vfu3bX5YKHfXtydrBb9--uLk9OT7q-a2bzFOnh-eHDZ_ffvXkXiIo8l0K-vbl9-fLVbFZe3K6GdhiHrd3aMs-YcDmdnB4tz46O3n_w4N7xaZGbqJWH8OZ6lby73qx2-zYOY7vrus0gFVaHzRc__-3bN1dFoS_eXEYflJGCCSISQTOdVE3tnJdS_k9-_8fvrm-LqrLdvjK67e29k4P758cfPT599Ojew6P5g-X8YDophDxbTj9--uB4PjmcVIumiT70g3twsvzWe2fM6EPMyzymVOa61Go-q9-_f_zR05PjuoRAldbAuF63bTtM6iLXGhBv1vveWe_jfDbZ-7C38f7x_HAx67r05s0NISLg1XobE--GodJ6UpiDWTXJin4cL9fbXW_3Xd-Ovhv9YjlVKh9TyrMctHTeUuLcmCrLh77LpMwyfTyZFrlRUqIUgSBQen29TYkiU15kiUjl0gb48purr99c9Uzb3q3adrNrY0q7riPvV7tWM5ycHWgpylI9e3xshOpbq7QGAbfr7uXby7IsVKFjiLODuiiL12_WqHmzt1VRMPG7m931Zh8i6VwFPyII78OiyLfrLgyjRI42ACQgDn2HCBSCUFplhpgAUWe6u9ooBN8PWa6YAE3WPL2XmSLZkXxst3uJOO67upnoRriLKxE8MqAPIM3jH3wy3t5Wh_N3n30BwQohyrreXl0FEFlZcIjKmLwqnv70o-c_-PikmBjPb2_W__SPvvPIyHbd_xf_8Kc__uDeH_3wox9_8v7Ts6NCS2OUkEqSCEzlpMrnzcN79zOd1UZLKVAwEXfWcSFe3az-5Z_-8tcvL3ZjfH21Pr9__MWry5tNN8SQPBPR2NuqMR8_fy8GAiYBsu3DetclFEKJz794lyKt11uTaxZ3gQ96fXH16PyoVObRyeEn33p0VFUAsIP06xcv_uv_93__zS-_2t7eAFEcvBSAEkXyWamFVKaqVCb26230lIC9jykxAhTVlNwopDBGffvj75w_vJcVev3mqm6a3fU1KP2dv_OTQhXeuX43GMAK836zOTg6_O6PvrM8PL2-Xh8fH--vry9fXUjx4DEzABEioxCQGAlRATkHkagdiSKwQiOVBuqjRHWX3kHmvM4gRqm1MEIIJOsZRfQ0W8wA0NtRIgolgDDPM4FICarDI6HylJAFSqWIMIREESbzWVmX3jqphRIy-SCVEEIgpKHbb9cbgdjvW0TUSi7ms-3lJYWQYkgAKES_31Z1PQ59CH55cGidJ6Jy0gQXdFY4Z4uyEALHrhWgzGRicun63veDNLnUUmWZyowQolttpFZhtMZk3W5X1BNORMwq0-QDUAr9EFNELZTJg_WIIAUIaVSmi7IMoxdKSiURmBNLpVHIFJz5m60YKCmkQK0LBLjr35nMUIymypOPQglUMsYoAFAIooQgAAUkwhSRGZCZ7jR2xESgFWiFQt5p5MBHISREBgFQ5-ATaMExCqNYEhAAA_jAlKQ2d4V9ZSR4r5SEkDoPoEwKXjCzD4wAzMY0AB4IOQZkRmbMjPibXX8CGwTzXZxLokAgpTKlDHh_Vx1JMaiiFCDTaEHIMAQS4IPTxpAL3bY1zNGOQhUJQJicU4AQyPtqOpGkdrs-UayaoinqdtsSAGYSBe5W-2HTKyP22309bS6vN810ikC-H3f7_Ww5E6gIcejHrMhW19sE4Hyszg7tZsNJGCkhk97G3fVqdjaJSQLFYTswAotkBFrn7ThIKQcbrQsAxMGDd5AYKElnOd65F4BDhBjARaAIRAplHCxEBiJIAeLfvKtBjGAdMvAYARg0oUs8RrZBFZJiAhtVZjhErYQbEglAqVlLFnfWHgZgIkAtOVAKjmMUEoVQzCgEQmSJLIApUEIZKGWlAYChG2KiKFDVWdeHRNGorB1dXRTWEwg8PJqvty2SePH6quv7ft3lhZqUpWSsJ9nV5Srx8Pj0wFlm4subtScOkaQyl1c3u26oi-y0rBTKl2MXhpjXhUPxmxfvvnr59tcvrstJfX27fXV5-69_8evVtu9bJ5C2u-6bV5fj6E6Pj56992A-mSqpO9-tO98P_RhjYIwshBaj9dGnoqiEFp0dx9ELFqP1kyzzwaeYrItFkU2b2jp7l7S23TiOo3Wu7eLp4fJ0NmEtE8Fg3e3Vftt1iXi_a4fOQ4qzppREMdgUE2vT2ZEBbfBEIAX63gVnnb-z-3Fi8MFpLd1odZEzJK21G5wuihiTNNqU-djug7WUAjJIJVBLFEIqRSHezcpSG5Hn0phMm5SSHzyirGZNCkEpCQmU1CbPR-uKLEdBKaXZ4nC0vTFZDDFRAiEQSEoM1vphYErMoLWJZNmlEBMDxxSHbtSZDtZqIQfb3wmhbQiZNt6O7W5XlVVMQQkMKRitfYwohZACicl5Rnb9GFNSUoSQ9ps9AwYOUkBM1Hc9CFBCWefrphES-9HGkIREk-Ukociy45PDtu-VyYVSRmeIYr-6UVIYZdBkMUSlVV4oAi7KPCYM0U_mM6ONHQcCYE7eeZmZZt4YbbLMnD4-s-OohKindTWZ5MZM5vMU3G6zPT05-uDDZ_v15uhwWWTY5Hqis29__Pj61W_-03_0BzK4ppSTOjdGGFQSoC6yMjPkgkaBgilQmed1XfrgDuaNEqiFksiIkBKHkBiAWQ7DKFC8u9qs9_skMDAQsbV2OW8S0egcRRLGaCMmeeV93O3a2cESAK5ub6eT2aSpT86WwSej9PHjEyEVhXgwzZ99ePbu1a2UoppOtm9XppBllsUhmNy011tvw8HBYrfaH54eBWcnZS61BITV-qaqc6VBSQBGFOK9Z-eA0NT1fFq9dzBdTIwXPun8YuWNgFxpTTpPsFq1GarQu_3Ndto0KNT9xycHB9X3fvTt6WI2Pz8KnubzucA0jL5tu-hiXRSXry9Dost3V1KoFL3tx_mkWXf746Nj1HQ2O6ya-vD46Pjk4MGj82leTOZzkPjq7asuDr3dffPZN-uLK9f3_Wq737W-j_efPDp-NHv64XtuSJcv333re09DSKg0IjPBxd7de__4YL48XEzfe3hfK_n8vWOQgEBVUT6-f1RoeTSfPn10Np3UdZW5YJdN45NXRAeL6WxaAeDBYqK11logsUvsrL3etlrI5XxqlKzzvMwVJT-pinlTNkUmpYjxzl3oqyqvSgMMSspNNwglJ3Uxjn6774INj-8v53VuR2JIVZlNmkor4VJ6fP9w2TTTwpCPWW527bDr7V34rajMvNTzWaUF3-4HU-hAcLPeTerCSAPRF1KXxiznjVRolBJCEHMK3lHYrNvL1W4IabPd13V9u2nLvLjZ9z_76oUjWu0Gj3y9bpfLuZEmxKiV7PfuydOHyXuT59Jkr1_f3G475wNJnE4ms6bYbHf3jxYC5EeP7_3q82--enWzty4lsDFILY3Bi1XrrSOkTJtpVmitIKVhGKwbY_Am08lFqSXEMfb2zhculEIlOLKSwrc9cjJa66YJgYtJbebz1I77q2sAAYDVcpESmUwJ5u56H8axrEpKrIppPl3wkM7vH735_Ct2jgnq5VKZQk2L8ydPbl--EIml0M1B8YMPHx2QeX52-J3nJ__kDz8-mU5QwacfPfLecUoxJa0KXZTKZFpLEvl__y_-_bbv9o6--PrV82cP3X6ntFqvNuVidrkd_uxXn7-4WL26bl9c3jghNvsODY4xrHcdgLjdbAPFGOC9s4d1PdnuunYYUUhK-ObihgFdoNub3Th2xmRFaSKkxbQRGJ8-OP3Bt55--OBk1pQSsW37__P_4__2737x23_9b_7k9Tfv3HYXbSiqzFsHIUoUzqd-P0qlZV4W9UQbHYJHoSVzMWmUVkWRcQzGmIdPnp6f3SsmeXC-3a679TqOPQDkxYQpee-bat7t101jNusVi-K7P_7uvXsnlKhuKhft6y-_vH13JeWD9ygQREatGFhqk2ISUpAPkJJAAkQstMlVaD0DoxEEBAKkNsk6afLgosxESiJEEkJhYqOMG11MiUJSQqOUQkjmwIRSaZCiKCdFVQ3DqIssryqQqihKAFZaA8ToYwgeAKMf_egzk-lMj9utFiCNcW0XvQ-jlVpH71EaopAV-Ti2mcliClJi23VKqxii9U5pYXLdb_eM4LqBIUTrQGgKoZzP7Dia0kTnmcn1fVFWQGSKIp-VOsv6_VhOSts7bbR3IzmvMuNDZBLMXE4mkNLdKH-3_xZSUkxSqtnyxPYDJwQmaTI3Oqk1AmBipVSKMatyAiYfTVbckb-JiBlTIrh7eyBCrYgBtQBgjhETiTwjIuAECYSQDAwshBYsGEIEJQQDCMFagEZIBCjAepkbQgYmZEKbQInkE4ISUkBiwQCAqBSUhTKK3SAZETk5JxAYPAMyAQpETkjMEUBKYLiTnSlmSCyZlMJITADaSEoUrROCUAryMauaSDEhKqNQoFa6nM8ReFhtODlpdEykpvOx29XNjKJLIYzb4d6zp96PEcBb327b2WLuIdjeJWIb0uHxrGt7pTUjGZPZbjyYVlVRbba7zXpjyrLKi7YdXQw-JW-DJExdy9H7OMqZGXoqijL0HSaJgJEipiQF6EjRR2-jMTJGQkBMAVOifgQfEYVCYB84RiAGIvAJIkGK4AkCISKlAAlBAYwW7qhVRHfNXWYWLiIja0E2gAsYnQAgRcxC5ObO6KIzzcRaSvbExN66FKPMTIikjErWMyWMEaQklDorgYmC55QAWZaSjXZDkFJRipEoAlufqklllOp2o0aRGQwx1VpqI9Mw_uqby-W0SEI8OD8IKY69bXf75dF0UhTLugyWTpYzbXSR6yzXu743ebbr2-tda4MPIPfj8P_6xWfnpr5__7DKzNVmv1rt9psehRht9DE1dVVKfXWzaopydrRsDurjw0PkqFH33XA2a6qmHGwYvPeRE6duHHfb_tXNruv7XTfure8HFxIIQC3lvnXD6Osqb6oq-lgpk0YnOFuvdtqgQPQp1pN6viw3bWdHDxLLqS7LIs_zvhvGfR8SZrlQmRlalyCNO4taRAZilkYQCJtSoVUaPYUQgavlVJcZMyMgEjmXvPVSIlNkATrTiaho8n4zeB-VktFHKVRIZJpcSUMxSiERcTKZgMBEUQohlajmtW9HY0zwjolBGWW0FCLGaPLcFHXfbouyiimBQEpRoKKYmACYhBR-dBKVG5zSigFcP6YYlFYUIgMi8tiPk-mk3e_uKijOBkChtYreAtM4DvN63tlBykwoZGTvg8mKQufIychsu-vrWcXAm5tdVmY-uHFvh956501mQggoRFEX3nsXXF4WzXQCKLO8cHaczmb96Ow4NLMlRZJaCgnepTzLj88f9EMnJZZlSczJJmHkwdHhOPp6MmvbXVHU-9V-fjCt5pO-G8u8VAoWi-V2s6cYy0m1u1mlRCGG5XLe7du6quqmMMh_-w9_vxDxe588Fz78vT_8ndN5fX58YhSUee6cN0pVxmgpEAQn6Idh39qv3C-n8mhSlkbLoR-NlkWWKSElQmJCASFSiGn0cdeOhOhC3O3Hw6NlmWsE1FIyMBPv9kNCambNfrtPPuVlIbSwMa5vV90wOIBxsAfzWZGbs7OlTynT-YN7J8_OFn4kTsK6CCi1QJRMlhfHs-Zk6ocYU3j09NzuO52bvh-P3j8XSra7AaXYb3e2df2-b4dhuZx-9eL6_NFBVAJY3H9yZrUkwrPHyzHSzetX_Wa_urh2zl9dXz-4d3q12R4eLU_vnwWiBw-P7z04-ubLy8s3t02VddtVSHGzvj09P3_w-N75vUXy7ubyKsvN8mje9-PisCGiLFfb3TaEsN31BWb3n5_V07If7fXVtSV_c7u5Wd28evHu5voGGS--uW6mzXzWdJ17-vH7h_cfHB4eT6b11Zv1sGtvrq7dMDoXtSmDsx9_-n41qT-6f3LUNItZbtuWwzibVhz41599vqiLJw8Om6o0Wkynk7tD8rIo5tPGWX91u8mUzLJsN9p62lzerq7X7TevbwLHybQhBCDSRiIFhVxl2SQ387oulfY-hUD96DyRljIRDTb0owspMgjvYyI6WMz2g8VcPzw9FMxvXt0CcGa0UBIBkGnZlKVRCtEOVqFMIICgdc4Yc9u7i82wceHLd5tff_POKbka3Nvr22ldHh8fdm0_jOOkyqdVrQAgJSFEoHSxWr-92v76q4uecEzp4mY9aeoYU2_drK5---ZWoXi32i0PZ4mYE-27QQqsZ2WI6eSgnuTqbLpc7btXby-LohBazptZTKmzLsW0TeHJ0TLPi5OD6k9__nKz74syM0Vm8myza9--u931u-T8-mYljIKmuHh9RSHu207JPCRHzEKKMLpoRykEMSothsEqkWul62buhk4qY4eQz6dmUoLOutUaKNVNEygyiPK4GduOiLr1RkqaTCo0ELKifvxgUpSc4sWLFyl4pfPn3_2d6WJKCc6_8-ziZ7-BkJSSD56c_cHvff_soH52enh-UB82BXpPBEaKpLKuC4Tq9eWOZ_m-t__Vv_y3f_7rl1--uCxq_dG3v3X75t0nz99r6iyryn4cXl2tVVH9t__dnziUOx_e3OyGIdx7eg-AgMVm1TZ10fuhKDUJXK1akLDe7Da7obchEP3q81emUNW8bAe_2q7mB_Pdbn_-8FG3uVaQPrx__p2nj04OZkrrzrv_-v_37_-b_-7f_uKLd_vBJRIhxDA6pSRxFCAgWdtZXRils2JSQfBso-2GZjkLfX8nvS3yRpK3XT8_OPnWtz4-PTu6Wq2__NXn1xdXtreZkdXsYLtdp8Sz49N333wdvBvtkIi__Xu_s2watnHfBZlnf_rnf3l1u9qt95IO74NAFAKl5ESAKCSm6IVkAFAmR5mS9YBa5opBMJM2RkklkoghEgOT5EAkJChpTJ7nRkmZT0pEcP0olWYi5uC6IXovlRQKUYJUmIhBqhiTVMaFmJd5iH7oBhSMRExBSZVXBXsfBmeHUWqDQgiCbnWtCy2FIArMCNGnEOr5fH9727dDUU-qSZMXeYiuKPLofV6WrndMkUIgSnkzFYBj3xNxM5_afiAGigEFAAoU2o0OCfJ6SpEEcJ7fCcMFAypjtDJ53Xhny2rih1FpE9wopRrtIJROMWljQvA6zwQKnRmjNCoEFFoqSpxCEgpRCBTorRdKSq2YSWmdiExVQAKQGEYLyEwAEjl4rST7xEIAE0S68z5LIYAS3n3PBZBS3PnDiDFJQAQGkYgSATGEAMQCAJhRCWK6w7AyEROzxBQ5m0wkpTg6wQAU8Y5IIwEFAiPHIIWARKi0FJC8B-8RmUOCOyIOamCgFFBIRLgTBkuJKUUzmwEIKVlr5W0SWQ6AKBIFDwQoJTGbrHDO5XmRbFCQu0Dz42XftbvbjbN7bZQATQR92-a5ygvjfXBdzwgxMTMJUGWVv_f4_sWbd6--fFmVZW6yBACSAFMafPK-rJswWp2XEYhDcrstGi2zXCnphxCtYwMsIHFkzykyAQGCETKMFnyCBIQAIYIPgAgogBlGDwKAAELg4AAlUAJB4AiYIERgAE4QIkiBPpGPqBUAQYoKKXYJCg2WKEUJyW32mGkmRkAQwsWo6wqR7wZQWeSut1JLiAmFACXh7gQzJcFMiZCQlDFaIcF0VvSdtaOzNqBAIFIgg_cCZT_4aVOoXPz1F1ePT5uD47nM1Ku310rKqix8hFwbBpBKai0Fir1N_-6vfv1vfv7L3oVX1-uvL24J-fmT-x_cP_EJny5mUgsbUz4137xZ_fWX777z6aMf_e57V9erd5fbo8PJq1dv66w4Wy6-en3ddcP77z9c77rL68vRBlOWgOFoMr3arH_12RdXu63RkqWqCv7m9Y0N7uXrd611rXU20OnxHBK_udgU04wER0Y7eqFkXWYPz87Ksii0vrjaTBvd7vu-79e7vu_H6Jh8Aop1Wc4XUymAlVSGJeijeUNEpw8PN7stEjMCKHn88Ei6IAGFVpwwMQnk_e0WgBJiiiHYIFOCSDLLmJJ3NFvWQzcKYKFFpo00KrokkkzeTZpaCqWUGEcrhMyLHCKlyMygjcmqSijBkQEF-QiSTFVIrXz0ZVkMuy4r8xRj9F5pIUBQCMG66D0x-uBNlistvB3IR29dnuc-Op0Z75zSOpGnGIGo21uppcA7oXDywxhjGmyrtYpjVEpHCsjMMYboh7530TMmN_gQvED2ziUBIFAgSyE3m11WZD54b33yYRwGkBBDTJ5QCAFiNp-EEKQ2WVGCAKm1YHX-6PzgZLnf7IXEMs-dC7OD5Xvvf5spde3YNBVzrIsyOHd272QyaUIM88ViMpn40RZ57ka723XNJK-KoqzK48PDcewVyCJTx8vD2bR4_vQcxuHhyeJb79-f14UAVIhaK0ShjAKGMPoxJCHQO58pkyt13jyss0xKpBiqKs-Nit6nRIhsY3q33lnnIwiUMiFhZtarNivy9Xa378YEiAhlZooq23fOu1DU1Xbf1_WkHwfrQrvvhRJlXSiUpsyZ0vq2J4x1UarIu33f9mM7uvPzqdBZJuDgdF7XlWQRPIoEq5v90WGjgJfHC6NlVeXgqK5rrWG5qJqqUpB0JnKT7dtukuvNzfb2cg3E11fbYbXPjTam8NEpltHH5cFSsEggg3e51EIwxBicf-_-sevGg6Z67-n90-PDadUcHx3M68n11cVXX71-8fW7Ojenh_Pb2-3NzXY6nSljHjw-u3f_WAq5OF7kWjx5evjmq3ef__yb69dXKcbkohvGdtWWhdBShTFUk9r79PS7H2aVAkHNdI4KtJLNtGjKST6pJvNGaqzrSaXNbttJZQBJEm43u8PZdFLVVVXGkDLNy_ny6vKmbfuDw0Mh5G5082b2lz_7ar_ej9YbFCFQ39qU0uXb6816mEzyZlJOl43SsNtue-fqQhw2k0U9mU9Lre4SlRKV4ETEgFK8vVm_vN7PpkVdF7nMQggvVrdHzWTeTAFSo2Tfj8GFQst6kvsQ_GApUSZFnWXOeiBKgbMiSxj_w89fvbbDkPDdurva9Zeb9up220wm1sdxsCl6AfLFi4vO2289ul8IMalziYzIqEQ_uot9t_VxH-MuhNGnnXNSqFfXq-P5NNPqze2mHWxWF4Fxsxu7XT8M_c7Zuij22-7eyXxW1yyxa7vVdjerG-_pdnN7O4y5YEXpBx88q6oSEf_s119uB2tjCgCj9ednB_tt--rzdyiYQszKYhyG7dWKRUrWCglCQWL2Q8gnld_vonXyTjslZDWdGWN0Ju3YE4rqcFYeLKREoc24b7NMZkURXTBGqwy6d2vyLhGEYayb2nZpHKA5ODIMoV_Fdq9yCSDKelI3Jbvh-Pgwbm4FoTHyD_7B9__xH_7Q7_rf_ua3nzw5PT9a0OiC9TrLk1BjSD__6u2ffv75__Gf_-vby82f__Xnzvpx2znf_eTH31ldXb94ufs7v_-B0vpmtf-zX3z59VdvopR750egr1--68ZQzybt0IbI7XagJK5u9kpnneNN352dH-_6cbCOEm9ud9YOy_k0pcQM3X5EiWVR9P0uT4SAf_d7H_74o-fTyrS9_-bd1V99-cWf_NmvbrsxAm1Xe1MW7c0GgENv7-xMAkSIaMoCEBSKZMeh3SuhKLDddTrP7OAEp27s8rL643_yjwzI33z5-eWbt3bXZkYYI5kIUAqTH9473d_cbG6uhn7PQudV_ekPv7vZ9OW0YQVj2l98-fL2arO5Xks4ui8kAjFIEAI4EgvkGCEFDAk5EAgGRhKShEAJiRVLrbIUWWZZTERCZlUudC4FZmUpGExZBxtQKASKMYLEce-yppRKDPsOGex-b3d7oYXSWT6pxn6QSibvfO9SZCQCIG-9YEzOaSV9PwgECkln2uQ69QMD2XHQRentOJkvu_12eXQ09OPicOGt96NlBhSins76XTddNsn7EJwEiNELJCV12UzLyRQYimYKQjWHB34YgbFupgAkUHnn8roqiiKEIAQAIjNwImMyBk4hMnNR10SUKBGzNllKVDUzTgQC86xEAZEICBlBSZGAlVYxJalMilEIqbRiSkyUKGVFYZSyndVGA5PONVNM1heLOnZWAAkGlAIQmEEqDQygAIBBCKB0N-5zjEwMAoEBhLiLSkMikWmOAYkABEikkITJmJkpUUyQWOVGSq2qIliLBDrTHBwwIUD0UQgBQnIIkIIQghiIEiKQcxIQEWKIBABScoqUvDIZxyi0ZB9TjJyCNIU2ahysECqGERGS90KrFB0QC6l1lpuqzIoqQUiRTWWa5cy62MxnUkkkssPgrNO5HvoBUG3bfV1PY4xSC62N9z7LZBgDI2ljUCnvx9PjIzv6rh327ZBVZRhHQeyBXD_Ozo5Eit1mhQLZCwL0HGSuwuCSTwDIMaIEclFJkWIkYIgBQhIS2Sfw8a7jDizgrpoXPBIAACgJkUADOAeJ76p74BOEJCvNgxMCEJkDASe2HkM0ElJnwUiWSkoNMaCUgEhEjMxISmhKdwkQiYIZE8bEFAEECJGYKEROCVK6Y5Nqkwef8twIjXYcYwy-CyLLfYhaSpRAKYWUvEtny2oYXIqwWe9n82oyrxnADkNVZEooYxQBiSxrB3ux2R7O5yHQprfD6NsQZ1Xxm6-vfvPV67qq_-TnX7KPr95uvrq4_t77Z0cn889-9fbp04NnTx_85ldfP7p3WuX60eHh67cXYuT1tsumWWA2Rm827XzaZAKPDw6aeX2z2RLhej9c3nab7X4YfGISChVyCHRxtXMubsfdb15fJhd8DKuuu1htppOi0qIp5EGRffL-QxtIAA8uESejRVnqdhg98-nxTCmplfr0p99yOzc9mfibnZQQYzr-4F7XD9aGzcZmwBx5GK3MlRLw8PnjSVZ0nVVKoFKIWnGSlIBQSZ2IlVRSQL8bijoHKThEilSU-fH5ghIQQ5bnShmhjZCy3bdlWfa9m80bpUy7GSYHjR2cVhhDEihZSUp36TJCIQkxWiszDYycEoAETjozMUattVHSuxCDV1pCimGwKs-dtdpkKIVUKi9yLTCvsui91BoJlJZ3dSySACnlZQkMUsiuH5XgaEfvo7OjAInMQmAabYgcfPBDUEoTMwNnSg1DOD2bDr2VLKRWQsi8LLrd3hjZ7feTSUPI1o2Lw2VVFEqIsp5QICkUAzfzpm6mSsk4jt1-AKbc5D7Esq5RisJk-67PlJ41Tdt2i8U0-LhdbY6PZt7Gsqqe3HvWjxuKpI14_PRRcANbuyiL9-8fPjxbVtpwZEoJUXoXiQgoCYHO-9W-I2IiRolKCwBWQgCwkioxeR9dTCSxD-Fq099uBqFV79PF1V5pvbFD3_vNbieULPJitIPWBgAESB9jnuf7bigKQymNPlxfrYXCwYbV9U5mOjcqN1JKaNtxsL7vBmfH2_X-aDmrivJklmFVsqPlYro8XMzKbLms758vJ0213YWDWZVCCIEI0u3bdSYUoljUk8hsytyCLFVmlNmuxkWRSWYMUZC_fHt7_fZ2dd028-ze_eMnT-59-9OHH33y9IP37n3y029_71tPlgeLZlIIAGW0Kavlorna7I_qyclifnawWEybj589fXC0_L0ffvK73__gW996VkjxP_-f_kFnw2JS9p2LxGVZ397sbi_3FOHwdL44n7btsLnZUALyAaWcNE05rRLx-ZMHv_nzzw8Xs92m911QKs-VanvbzCen94-0Uu3OLheT-cFsOq3qOjs7OkyJ87x8_q3npcmqWUWUrBtn07oqyoPDeVnkX371et8Ou-3-7PxgPqvbrkPmEEJhdFUV0yrXGQ52vF6vb3Y3U6PePz1572B2_3BRZlorSBrXt9v1ftj2_s3N5tXV5hdfv1vf7prZpM5NbrJEwJF_-ebdd-6dgJC5kKVRAqDMzbQqTaaUUEyQZbqu8ixTRW6G3iMIlRdRpIv9cLnZzYtq6521wYCQOV5cXq-GkaLnRC9eX5408pP3H3xydjA1CgC8sxFISHl9u_2L37zoCXoQL95drXd9SMCIypgsyy-uN9vR9TEKIVDoq9s9MlVFttv1Wqq6Lo3ApsqJBbNgSYuDhVBCII_B_7O__f3Hp0cHTc2JXr272bYDaf3163dY6L73QJybLNlw72iitLaEWWkgJR-sQhnsyMyYAECmGHUt7L4rq9KNXhVZ1tQCAFFa61BgPp0Hpugd-zTuWvYBmNrVDlMiiq4dif2dtrI5P6BAqi4OHxwZhM2rC8Fkitw6-Oh3Pp02EzcO986ON7cbH_z9-6dHx82PPnz69HTJ7f6f_NGPNFGIftcFL_Q3b27_q3_xl__N_-dPk1ZJ6aNycnG1GWI8OD3dddvBeqMIYvpn_-R3kwvffP3urz978_L1ulnOPv7xe3_y7z_b7ndvXt8UdXE2P1qvu5ev3yaU3RCKQl2v9s28ioRuDHb02_X--mpVNlleF957n0gqEUOIKYkICPCf_fSjf_yj7zy7v7TOb138F__DX_78t191g7ApPfr0-avfvoqjd9aKlMglxCTCzloWWaGzgkiM-zb4Po42ppDlxmRqUjbPfvA7_XZFQFld3D89OzlYCqG_-frLruuFFPV0urm-ocgi06eP399dXbRt5_b9008_qMvqez_97mI6aTcdAs0Pyr_6d3-1evuO3FjnUsLhORMDASSWUnBMrBGQZUoiEaQIMTExEqCUICGrCmkMIZrJRJhcZ6UsamvHPKukknFvMyO1yTY3O5Qkc5Mim8yoXFJiDkGmJFKA5MgOsqyc84xSClRax-QkIcQEyLYdVa4NiuicG-wd75pi0rkO3VBWlTLGj6NUspwfONu70enCcIIsz6N308XBdrvKqgkw2H4EAARQWvrBKo0QU3ADSwgxTpYHDND2IxJxYkT0wWtpCECwQIEmz0LwdrRl3aQQjMpjCkJJFFIbc7ciJ-JoXVU3IAQDFGWZYgKpQQqjs5RC7F0-abz3yIwCjFEpxhh8UVUxBKmMyUx0PqUkpQJmEKizzI9jiiSNFhxFYkiETMyMdwlVJCZiAqCExgATICLB3eEAKAmIKBFckAKAE7NEBuSIKJlAIDEjJ5JGK6lSSr4dZw_u-7ZlSkiJYkwMCIxay7ufhoDMFBNKiZnhFCEkRKBEQgkQKKURStKYVJn5fpCZkQIFMMcADKosQWAYeggu9S0KZGAUWhIIpBiiqWsQ2rkxxEDRM1NZzxIThTCfLzgkO47O26aZR5GAOAWf5TkS285OqoJT0EK_fnszP2lOjo53V7eRYl0XjLRZ71gRSUqDm04mw3arpCESiZJt27wqfd8zMg0BBXIIAAyBIUYYHTJFF4EZiMEHTgyQgBH5b5R7mAgxgQ9sg1CSkSAmAAYX7-BcApiJwCfOCGyEEDkkMAiYYIzgg8w0gYQIIAQn4kTA6e58ASKBVIwMPrJPaBQkFkJyjAIEoiTmBHev5gKQhdISZZ5nkWKgSMDBB28HZkjEhMQg-v1gh-6bq5UUum2HXMuXb66nZbVu-wTcNIVP8dFyGUIK3nOiSCw4zZdT8PTBJw-WTf34YPb4ZPn69c3Xr9-d31u-fXsrgC3z-dlc-GCJQh--_PqqG_mzz79p-_6vf_XFdLkQRj98eOp8qIusNtl-b79-_Xaz2WzXO1MVBuGwbvoU_-qzr5GSG7xBzSkhSCZ2nhOLaZ11Qy-1nhf57apb3FuykNeXq_V6O1BMjG1Klc7PlrOqmlxt9uyDApFcXM6bQstxv7--2X7w5GT37mZ_u1u93f_tnzy99_B4fX3LNuVGGaPnpSIX-k13ev-krgshRL_rhLxr1DMAsnc5ALkwdl4WSkjRTOuh7SVI0-SuH5BFpuSdL1xrzSC7dq9zE31USlfVREkZGZtmIgWSZArEyFILTqiVUlKhAiC-Yy1LKShFYKIQUkxgklHSj5YSS0Q39kogEwXnhFIJWKNQUgDRHVzchdhudoiYl3kYHFFiYmI-Olx0m15ImRKVWW29pRiqspBKhegzo4UQSiD5wAjeO2OEMZqIiME7H4JLHIbOCiEpxb7fB2KTl8jRaDNdzO8IZwpNcrGsCmLSUjIlY3QznddlcXZ8FBPZ6B8-PD2-d3hnvF-eHEjmxazcbbfHx8vVanv-4GRS5nlZlE3FwZ3dP7V9F_ymkGochh_98NvvH1ZnR0cFp7_zo29P6qwyKtcKiLVRd5aATAuFwhJ88eptpo1Wxvq4aweBPAwWpYiAuRY-wba3N-veurTtw6a31qW2dz5AQtr2_ZefX06aQkohhVIIQqoyM8C874eYiIhRKQEwWjuMjhBMlrf7rphUdzjXEGNRFNYGjomi10JIqRfz5urtrQ-ca71cTDSiAjqYlo_P5_NJpkE-fXCymJWz5Ww5n_yDf_SDx4vm3vHRrKk1xLN7h--dL0-a6qc__eC7v_Pk-cf37z0_Xj5cQpM_--S904P5h999cHbYXH5xmx9kN2_Xq8vb1dV17F236q21fTdySFWVl9Xk4-ePnpwfLkv9-PxgfX29aLLDeVNm4smT-0WmvfeNUqeHU2D57PzwcDZ5enI6UfDwZHn__GBU5nRellUebMpLs5jP67peHMymi7kNvixzckEhz5eT9967_8mnzxbT4vRgfnAwmU-K9z-8X2VGI87qbDGpm0wtF6UU8OrV6snDg3vnx9vrS8WkNU-r6mBaZxKLLN9sVoVSJ8vJ-cmhH2NTZLbbN2V9fjh3Pv7gOx8Oo48QUcBRM312cvAHn3785GB5MG1mhRaAFClE9yefv_6Xf_GbL17f3Oz7xHx4WJ8dTTIhAOHxg3sZ4qTKMyHev3egpDBKFkq54L0PWaYpJfbkYiQQdSazTEkl9_tOZ1k7-t7T24vN61XbTGdvVpsia96-vrrZ3Lbt7sNHZ995fPrD9x-fHU5--PxBlRcHzQSUdCkZhdYHpdXtdrexjqVZx_D2eksCXYrWhyIrd6O9Wm1AyKzJL6-2F1frL755K7VQUl1c3mitlYBh3zK5w-ViNqtdO2737dHhrN3t5pPid54_sWPI8txZf7PafHNxrar8ze36zesVCR1T3N72PnojEYDLZUMsTs8ONqsNWctK2GE02lBM3rosN3EMzEyAd3tMpVUMrt31WV0IQtsHIJYUx22rBJbHDYOQyEVZRm-tsyYvSRqZN4mgOZlWdXN4PHPDTmtTLWbLo6OjR_e1FMB0enqy2-8V0pPz4yzD8WL3kx9_e5rnMQXJ2PdujPHrvv8__d__xevt9qLtmyb7zeevX7296uyQhNBGBiDb9X_8d3_46Ufvf_zk3Gj5-V9_87Mv3s4fzz_74i1L_OrLyz45G6IykgF-8duXNg6T5SRxShSYuCyzQGHYjURp0lRNXQJRUeYmE223z4RgolKKs9n0n_z-d__BTz45P5zmmd62_ddX2xcX13vv317fXNy2q117c7m-vd4e3jt1w6hzBchhcNXh2WRxqIzKKsPEvv1KUK60LCaTkCBG8Yf_5T97-ctflZMmBWtd-of_8I8ns-rrL79yduz2uxRTtIPr-gcfPo8u7K5uUCtIyUh5eHp6vd4-__CDX_78szyvVje3b796c_nVS9-3EghTkHj6ACKjQiCiREIpNhJ8wMh4F9ZREhiIA5NAEL5vfd-zkklA9FQ2FQhRTGaAECM1y0W1WAiBujDtdidZEAD5IAGitZiiAKAQkg9CC0QUSkbrjFIpOD9aFAJF8q3N5jVQ9HZkH2IiTjGvagaOLpTzme3X-5tro3Q-mxMla61WConOzt9b37wjYuscCkSUJs-6bo9ESpkYYoykJBotk3NMVJRV8E5rnQIrpfKqave2amoQqIwRWhhtWIAA9s6bLBMoGJgBrHVlPZFKjv2QFQUy3EGBdJYJoRNFVeYElFXFMI4A3BwuQ_B925VVLbVmYECgBCgZpfYuNIs5AhMyM-u8SD5SSkKhECI6x0QcAlBgYlYKJFCKnCISi1xDEtIoSkmbnAFBKQAAErIpKASBIBIRgRColY4u3HW-tZJCagpRSgGJTN2QsyBk9N6HAALIeSISQnLiu-gASGSKUgJEYikEIFBCBGZGKQElM6HWQKDLPFgvQWAiQBBKBBsIEKWikIzE5BzfnbVHksqYpoqjtaNXRYaosrwYNqvgXFFVVVGQIzcO5bTabfZlVez3e5VJbbJxtQVrq0nNRM6O23WfKFSF6VurlVgeH_7yz35xfO-eZx-BXCQQItngvcfkfSRRG53l42Y9qUs_EBoZnAMmJZEiQiRZIriEgJAIEYAS3Hm27z5JDIEgMTAzJXAJYmRKEAESABHECJEgeg70NzUAiTB4iASDAyPBJxgJIIGLbBAQAAmY70Klyae8zkJIKbHIVCYEEjOxBGBkAQCJ8qwIKQghkIljFKBSikobkZsQovU-LwzHFEaHKRVNaXvnApk7l5QCP0apRb2YRoK8zpXUwcYqN01ZSiVDDCRws93dbroYYb3aQKbRYeisKfOb1Z4iffTJ42EcdZkdni_a9X43Dn_-ixcXlxuPcj6fQHSIcjmvV-9uJ5OJ0gVplU2Kfddf3-4_PD_-nafnlKsyV3_5iy8ynXVD9-D05PG900kzPZgvRYq5BkAsqqoo9f3Hx8Nu6AYfBIYQ8tK8fHMFUuZGxpCijz75dy8uN7vu3vkSoz-ZTg6Xs0f3j3Jtvn5z3TunjP70wfFyMt13bjmfPHtywsTHs_l-02VGuoBhCKUpTmb1_XvnHENIyajs9P2zzdub3e0WJVrbJ-uBQGvFRg274e7a39XghnYwuZlUVa5VXU-QsazKu-a-t7asJsDghqGuqmpaF1nuQhqGQSiBAnWmmPhoPm-Hrt-1yADMPrLMNTCP-0EJEdwoEtyJQgWCVOhdCDGWVZVXRQwJEU2Wh9EDk8kzZgpuyDLl-8H7wMxSKaMUCjkOY17UlBKDQISUvEDp7eBiQgJtzNB3FEFIyQx45xkmDgm8s1qpoRsFSwTOy0wIwSCjpRCDEkIXpt-PUpuYfIrBSCmkQiGuLy7mB3Pyfr26nTS1jU4KBcxkPRNLAU-e3l_vdoum6Qf7w9_98c3N7dnxMQp6drx4e7kFbx88vlfVuUkMIf7w20___u_9YFqV_-I__Ppvf_fZR88ezJpcA2SZYeaUkpBCSQ3AnLgf3WB9aYrJdCK1stYKASlBJI4MkXg_-OvV3vroiS3x63erfnAuBhtjYgiJ2rZfzCfXt5tJnV9ebqpSSyXzTL1-t5FG99bHSIP392aLF-_WQjHqjASBVkzEMZalcYNPTEWu54syN6Yq87IoytJMqryq6xRJIfrgbjf25LBe3_SbrT0-nd927WJanB4uDpfNqxdXB3V9sMjnk_K9R2eAhIoD4UybFze9kRL79PzxwfF0fiS0Njq14fhoNptOfvLxo6PjWZkZ0vr0ZH60aE4WBz_56Nmn7z_48Mn9p2fLw2lZK1FoYRCX8yb49NWbN3meZyj22_0XLy-26-1vXl9_79k5kqhzUeRwtpzMmuKsqJ8dLR4eHbvRHR4tf_a1_d7Towf3jwXK2XRyfno8beqz06O6zA4PJ4FSsPFgPptWuVIyxlhKM8n1YlLtdvsU3PMHJxmI84P5fFI3RfbBk5N5VVdGsZKVFoN1zx-cNEXW98Pg3Ej87cf3ntw71wQUZJap2TSr8-LsaHoym3z87N7jk8NHZ8t7h8s80yozTPD5zfbl7f7f_fblX3551TogzJTELDMyM7vWfbbZPz-Z10VZZ2pS5HmmjERnLadIzClFqbQ02e1254D-4t1lJlVRaEvw5ZdvN92w7910NrvY7vfDsN6NRHKza9veFYUWKTw8X_Sj_Yc__XahzSzXRhoOXFelHeL1tocQX19vCdOLN9fvbvf7wf_27dV63UYpWcrB-c6FTdtLo4vcaCXevL1OMV6ud_NlfXp6jPJvBCAUY9ePj-6dSdSff_659zGm8N69g5PD5bKstNao9NuLm3_z69--uVpvRvcf_vSzb15egDbWxxiC7drNzS74GBl0VWklhl07X1bbdmhX-3o29d4BgzBaal1MKxQKBEopTZ6HwQOgmRQiUW6MkGwUJjciR28t-xDGoJRMMUillMkQxMHZWV7lbMfClPfOj1ZvrtttXzaTyXzetqPrOmbCGAY7VFV9e32z2VxnSn3nwyfvPz4Nw6gE-CAu7Pi__b_-PzfvfJD5w-en17e79a7PZ_XZs9Nh2x49Pg9ulJk4nBTfff74dDGvynwY_V9_ffXw08c7SrvtPobQDnbw0RFu2xELbbQAIh_SzaanFHRl2m589251dm-ZmSIEr4VQRglOSXIlRJ0X__kf_eRvffz02x_cX1ZFInKB_81fff2rl9f5YuFkolxfXm-_eXFRLRa6zhbz6e3FpRDG9kNeVuX0AESuNXKi7c2aCVBVIYViMpsfHxKQUmZZ5O89fm4MbLebf_BHf1xWxZ_-6V-st-vXL9-iiF3njZLP3n_29sXLD370vdXFdbvdTxczjP7dxdv3nj4jwOOTw9nhwfrq4vOffzbs91VVElPwEeHjH4NSyII5ITBIxQB3zxaFEgBZMDOAUqQVACAopVQCBFVigvqgAZWFJAzqvK4IubvpTKXvtp5CZN1qldel0kpAoED97a1C9n1PkIrJjAUBCyRCpcdhn5V18gFYCIPDthOQyskkucjIAiVqqU22v33HfS8yY6oaZCaMKSa1X28H2-fl1FRZ9K5sluury8PzByAxpdCvVpPZNPjYbdeCIjmrTebHkRGnR4eolDK1da5eLJK1Kca8qvq2nS3nw25sls3tu6uyzpXSQqC3IzOMfTtZLLTJ-7bVSgVnx2G4gzPqrAzR5k3TbrbLe2d920IkKcTQtQhCIqcYx3GopzVQ8t4LqZhYZRJRAMq-66TWgIAAY7tFxGBHFCm2LQqQUnsGkQtiUJMs3m5QZ6hzEMhMnCJoI4yg3gJqqDUMCRRCCCAUFplCTCmStUCAxKJuKJIAAkZdFN4FBNXcO9-8ea3LLPU9EAkAQgGZhoSgifZ7ISTqDKucvJcggSL5ICRyTDGBzjMUCqRM3kmUkDxLYCJgKYsShHbtYDIhKQJhEoKjByGk1omEKmoqC1UUVVbuLy6Tc83pg8nBsjClc73KMYzRjuPYD5Nptb3d56VRKCfLhVBi7PsYWSqBxPPT47Hv57Nyfb0SQkOhLcZtZyGD1I0p-GJadtt--vjBOPb96kKrLJvNe2ZJEUJIHFPSqKXSnh1Fl0AQ5ApIggvQOZAA0QEBEAMKSAlyBcMAPqEWzAiogBgYIHkAAilBCXAEuQbvMQH7CEZAlcHWyegZETINSpM20DuZKSSIY5AGWChKiFoKa8EnBhIqU4Wx261IyWQ5S-P6XhVSJpSAwTmRF3o2TwjBubqoorUUEhKZymT1YduGo5NFlYkw-vmkmlTq5LABhlzJs8WCgteSPn12z4UE0foAcbCEnBIHSs2s9qPf7OO-az97-eL0_unLd-uut72Pwxj7Yf3w9OR4Nn3_w5O_-Px1vA3I8eR88ebiGtEj5ZKFTb6ZT32MqPTNrp_X2enBtO1a5_ujetHZ4emjh5k2v_r61eXlppnVkGg7-ggwyQ0izivz9dVeStnv9sfnszwr37zb5gqFgDzPrBs5-EVdClT37p1QipvBTqtysO5gUZ3U2cuXFz_7-uL0-BhBHB9UGcOby9vl4Xw-nXTDMPq0s7Yqq1lT7QY_ENl2fPf2AiTevru9OyANKfR7m2fSuWiMycrsbsoHKa11ifH03jEjaVRSiKEfNuvbSAwIkAARTZYVeVHP56hYaxNd7If-9vbm3sP7t5e30Y0xkXfRZKLMzb7tmlm9v9lGF4UEoCQzY3trTJY4Ka0RkAlDDIikVRaCSzEJFNJIRIlKhkiUklSiKeaD2wpUo7XzxTL64L3zg83qnBiM0sQJUduhz8s8pditNyrPfO-kUSBEYbJMKxcdsXBjlIWUQkmp_Ng30zqEJBUqrRnAKCOUmM7n29s1o1BaHB4f9Hvrxt4ocXhyqFAH7-7gSCGEzaY9OZpxiMvj-eXlNYrs_HARot1143w5932PBNPZrB_6oR3u3T8Myf3uD74zgVTmZb9rf_321fOHp0_PzyZlxon6Ycy0FCikUigEEwcfbQpdZyOiMma_71OiN1fbBydTgTJxaibF0FuhVNfavDKg5Ho32ACbfetCfHm9-8FHjy_e3TR1bYMbhv78ZDGblalPzvnRx8CsKjV2YRydcwGZlRJZ2ex2WxKABsfeS2Ih5HRSaS04JYDk-tDG4WA6X637k3sNEhuV3bGaCxTMFF1sJtXODkVRZJksihwjjc7OJ1WKKaIA4MHb04OKhbL7dvQIElWWja3NlJwokddVcoNlIZUgCiFiblBq1AlAKAZxJ8rMtEoAhRCrbXt7u1KmmC7m0XuCpHQ-WAsJo8CJhtW26wYvkBEoy_XhbGqtdS5tBy-lMkoMwS1k8du377K6JDTt2KUYq0J_-PDhy679D3_1s3lhlvOFrGsSfLNpf_TBk9269S5th-GoKk1mrm5ufERd5tMy15wG7-fNZFLoh0fTm511PlSFjIElCu9ciinTWmV5nksjpVLym7cXZVlk2kzKkpGQIFM6cVLAjsV61_3s67fFouDAVjIH8Ve__ar36j_9wYecQqXEp-8dRBDRx7LIVWJPYIN7fbWJwT55fL_Jysjpzc06Ucp1kSswRe5ifHO9tT4VGhHxct9eXG2X8-mutSavRmu_enPx3vkZcNAaRXCLw8WymuSFkolevlstFo0RGjVmLHe2FxrfXmxMpt-u-99-8zopqSfTmFI3jOPgyyJvZhO2_u3r64cP5gez2c16l-Uyhtju-7ouNre75bwpquKj-6c3232mhKC0WEwfnB270S1nRXR8s--vV5shpDdXN50LX3_zNjDv266YNHb0yPTDbz3987_8LAKMzkYfUiSl1c31ShlhB6frzHWhnORSCpTS9310MV_WglO0IcUUnNdSCZTSGLfdC8ku-HI2dUNnynwYnC7MbHnISZ5_8GS4uU4Sgo9-CBIgxnT15nJxfFTXudbZ4miZG_XdP_zbX_7bf_flq5exjef3jv93_6v_REVmBGZ-_e4mz_l__3_45_WstFqOna-b0tvYjf4P__hHP__Tn2FwDARST-rqv_wf_92ny7mW0Pvwz__Vn3UpHpydvHl78_b1VVEW7TBMDxe3631r_WRSd5vdoq4iJW0UI2VKD9YahYcHB0zR9rYp69vN1b3l7LvP33t273hilGXhgo-RN_vORd7u45__8rOnHz14fbO9ut5st70NzkdvsuLNV1-ncfQ-AaKzTplMogqug2RNVjrnpNL7zXYync1Pj4WC9evLw4OjDz797ovPfiMlPvrg4adPP7y8vNhH9_M__evnf_T8f_i__H_HrT04OkpDPz8-aduNUiYksP22rKbTeXl2dv_y5ubv_f0_fP3u6ou__NnVN2_6Ycwy03dbBi1heYoSkYHvSqJCg1RAQUikRITEiKwkCwCF4JMEhESQZUJJEX0aRjf4GJJG6va9VhK89d3edVYabdfropoggR8HaYwfhxSDkCpS0lWR_IhSJueYI6UIgMhJ5yV5yyEYI_OykFkexiE6rzLDAOR6EUNmTHNy6Ad3eHpfS9ntt916K43JjEkhIsJ-tZodHNqxFVomirootdHe2UBBK8UAAjCvp8CJgh-H0flBaeltbJaL6EIIIS_LIsutdc2kYoCsLGKMUv__afqvX1nTLD8TW2u95rPhY_vj8-RJX1lZvrqrutmc6mazySHE1pAazHAgXVA3EnSjC_03AiQIEAYQZoTRNJucZhsWy7s0VelOnjx--x0-PvfapYtdE1dx-SEQgXjXen-_59He2iTLUCrvAiJdb8ikEsF7Igw-AIJO0rqq-sOxNc1wNO4aQwJ7_T7EwMxCYpplbVUzEhIlaap0apoW6FqPSdEzAQNHAhQIQlJ0TgALKYLzyaCMxgMRGcuRMCJGBimAI5L8vTM2RoiMiYZryQAgu0ARGFEIEX2gCIgQmQARmZFBJpIjBxeKfg6kTNsK8AKRo2cBoARDRBIMjJElCG_M9e4TBUbrSCgkohCAGTxQljjTRe8QMfiIQgghCAiQVJKwNVKK6IIc9dxyBdGrLGUGH0IEIUgH54a70-1inZY5CVH2ixjc6mqbZYlQol5vgDnGYOvWbVtbtWmSmc7GyHXTWhuyPAvGTScTkWSL1frenZvr5ZoRnHMcwTsL1ru6CZGzad9sa7fZJGkiQHjnQuuEVBSZIvvGRYgIRMGzBUSGyNAZiAE4gGMAhhABBWCEzskY2LTgIqAADnDd2A4W_LWoj6_tAcI5MpYDAyBFhBijaSFEdgG0hojEADFSYIqcZEWwEdiDdZJISnLWI0FCAqznACQwImAM0QehEvaWEUWa2LYRJMF6hejqloIPxjPFJMuada2LxMdobJBa-Qiv3tpbb1pjzWTUy9PUOWvbsF7Xzrk8y_u9HhNlaVpV223XksTGmuWmQ-IbNw7Xq2VvnPULKBLd1PHet-8-_-3x6flSKh_Zq37yu09eKpL_3X_9Pevg6MHhYr2-mC2Dc1fHc6XEctss23rVGnbRthZJZIm4u3cwq9YuhC6EAJyqVKR6_2C0mm1nlzOJMVrSOmuB_cbcujNCgamWzLxtbFf7vNRCyPlyuZgtT89n_VHpfLhcdavGvPnqrTs3d3cmhco1Ih7uT0ni3Vs7SaqFhr39Sa_fA8LOuqjw_OnperXxLmyrTmppm1an2nuHFFUuZSaRhPMuAEcGZ02aZ4mWRZqVvbxrNm3bcYh5keo8R2DbdgyQpUljGq0lglBCJCoPwXnnmZmjJ0EQvXOmqwwAtuvaW68SwhA8UwxRIJKE4KPWiVJ6MBk0dSuQUCByQBJCKSllkmprOw4RkJMsrdarctBzzvSHw9ViUw5L0zYQAwACovc-hOBtK4mElEmuAYgBklSHECgKQWA7aztjrZdaoiTSSpIwdUdEETD4IEhGD2mRBc-b2QpjSAi3mwodK6mIw2o2QxbWWtu19WZbVdujo53JdByD29-bfPH5k8Ppbt5ToTXD8XjYK4okqduGEoWRCd2bD-74rvna26_vlamPzji6ml2-eu_mwaifai0BObKUqKQUUkJkRmy6ru3MtukikNZ6u2li4MZ2h5NeWfa6rutl6SBLjfedDwRsnK-37enZMi-0kCrXapSrQSoBZWW6RIpenvRSRREr456dzmvrGWm5bDvnADnTetXWHMVys76xd3g2u4qBBaHpQlamkuhqts4SqQURkhB6Mk4n016oHSFqxH6ep0r0y7SrGyVp0M8yrcosyVMdjBEktNbO-6auSUB0XmnRyxIBAlFGxESrHFEjnJ1uPz9-8bcfvL9c2tOLhZBKSZ2maQrU1a2UCiMWaSKEYI6R2bvfp1lUkjKLTCeBwTtbtYaYmmDOz1Y2hN6gtzcaZKlwgl7Ml797evzF4-O8yPb3Rnmq80Ha7-XLur5540Ag3NzfvXEwubk_3puOGGKO_O5rt1453B33ioNReZBmR72Sje2lKXLcHfWzTF8uVqM8u3E4HSWJFDjMs9bYQZEJAefnq_Vmu9msBkWxN-ozY4zxrLk6HO0Oisy5IKWIISglh2WR51kMruk6BlpU9clqs950P3v6NEbItby1sw8BNrXNE8wL_rd_-Pq039vtJUd7A2Rut12_V7RN2zpfdWbTeZ2mbzy4xQ4zpVfb2ninhOr1Mq2TZVUvui7rpQfTSS9LJIvPT85vDYa7w_HGI0h_uVq3tkUpTs7mp5vtvfs3DWIV4-Pnp20w472xB1B5igQ__vzznWF_MCyR6eYbNxaryntovMnKMoaYkOprPSqzfi-fZjQo8xt7Oz2tRr3euNcjpmpbJYmajIdSij9--_WmMy8vz6ej_tuv3uuVBYRYaFH2ctN1v_zk0_F02nr35ZcvLmbLzllgXm_apqo4hM6Hy8qYpiOMgGzaWupks1ikiXDeArPUSSYEO5f28xhcaI1ORLtt28s1hygkgaRobNJLTddAdIzMCKQpBraO8yxL85IwHe1Nm6uZ7RyUvep8MdqdBI4kRJInD776VqZEOSh6Wtx_48by04-lxxuT3v_l3_yTd28dLmcL77zK0jqE_-Unv1p39unxxdliCSSLvVIOdZliMS7W57NmtZEg-oPev_jH3_3HX7l_c9xLAL332y4sqnZZNSdnq6brjI3bph3vTNs1OGgbY8aj_nqxDByIMcv0aDTIBEz7PWSwVT3uZ3_xh2-fPH56NCj_8k--uT8eMNCqhR99-Olf_eyD2bK-qM0_-S_e-MmnpzLBZWsePzutjFltNlHA1dn51fPT9WymEhVCoERFZBYimIa3lbdms16LohBCjvYPkzQbTCfNtjLLerA7evLZpxfnZ29-_StXTx_3R-Vnnz9GEsdnL1_85tFmvjZ1l-Rysru_vDiPIfYmu8533geVZDH6xXr1tXe_2etnDPbFF09Wi03tjGBMe7rZbgSMDyAywnVnlEESaYV8LRhikEBSIlzXgiMwA0SCGHwA4CQrojeRARG77TrLCiIy1Ta2HVvDwbKzUiuQUuoEOAYXenu7KIXtnAAG70NTM3tCImad5swcnUPvEYBICCm9s0JrneokSaUg15poHSnJ3vi6apbzvDeKMTpvpzdvrBYLUjJR0loLFHu9AQPcee21tq5Wi_loZz_6sJ3PiTECE3He64XoEAlCIKF600mzrqTW166sEFze6ztjpFBCKYAYvMt7pZRakJBaaZV0dSNV2jW1ylPvHAHZzspES6Vs1w3H4-ADB59lmTU20Rr4OloPJAXEoJLUdkboxFvHzICERLa1OtUCBUYIMZqqSbLUNgYhAoNQggGIgWPkEKVWzJGEAGYOTFrGzpIgDgEio5QYIxgnhGBAQcJbh0AUIyKSUCyIjCUpAaHc3bXzRTO_0uMJ6SR0nRQiGIeeSSACCKXYB24qmSiOzAQQQRIF07KPHBwJhRxjiLKX-qYlAESE64nddgiIQlx7rCA4QEBrMYZoA8fAKESivQt5njtjVKLZ-eiD0sq0LSMniWYIaZGV_Z7zsVtvRGQ2bVYm9WbTG45RCKkUxnj-8rg3Hhln0yx9_uRkvlgO9kambYPxtmpJsaubNMtc10YtyGM0tdZSgpBE4Toww5EpMgQC5M6Q92xckukQA4KAzkshonOADIgkiK0H79kGEggBAAmkAONB4HUVGJIcnAMEQCBg8IEhkJDROkokkQQXiUgwQAjResGIpuMQlJTAgY1HQjZGEBEQxoiI7BwzMkSOEQVGFwRyiJEDk6TonEJUEHxVcYgAHgUwaUCSiTStw1LFyGz8ctNsG5MnSVkmg15Rratru_TJcnX35t7Vqmpsy8gRfQT46Nl8f5Tq_Hqk06urTeXc4eFeCLC3u7d3a3Ly2-dnF3OWtF50bdNdXMwLRSpNP_ji5HJZ_-7DR4t1JYVYr9b9fh48rJs6SZK2Md747abqD3qtdUWWlnnmAiwuNq6LZT9PE7U5Xy23Ni10MlL7D_bfezAdZYmKsKrsZFQCsRSqrsz-Tj9BWqzqLC-KXpGnRdfZ3b3xT372ydViu2rM3s29Dz_58smz04-fX5zP1qfni6ppKc2MdZsq1MY-fPj0crb5_LdPjPVpL9luG9vZNJORwTurtU4S4ZoAAZxpgwvXFdKiyNOit6kqAvK2W8xWi_k6UYoEVlULGJMkReTIbna2vPnKrdMXx9E71IqU3Nnb88ZABKk0RyAWOhU6VT5GgcCOVaJ1qiEGAeyNE0JkZZ5IVVUtIEglCQGBAYXvuuC8NYaU7Oo2y3NihuCuLddaizxREIO1Psly21qVJdF7YlBJIomctUiSiby1wESBfecFMmJEIYUSQkBTtVpnQC5NtLUm7efI4JxNk6TdbNmHGNw110gpkeWplLJrmryXD8ZDjgERBqPhsDd8-vjF3t746nI9HoyzMl3N5wLFq_dvIvvVfCkFTcbDb7x1p-7M2fHFjaM9KdA2bjodSYHB-6cvTpB52u8lRGmiYvTMQdA15wwYobPOhtgY1xknJSGSkJAkSkoVYyjKnIDrzlZNV7cuUSoyushpogBZKckIHEALuWptVTUkpfV-u2z74_LF1TJLE0jkclP18mzbOqFlVbUc6eziKisSY12M3jkviPuDUiDF4ItUpGkCAEWeEtB2sYkmBI5XZ4s0ERRhuW0EwmxeD_qZsUEKCcRFmijC615HZ-y1D65IE3AhbmvTeQpAHnxjJUCSJKNR78Hdo2-8euv1-4evv3Y0TFWvSPqJUoJ6ZQ6IQHjdjkAkiNw4h0KipujhqmqUVlfV9lfPji8X1fvPT4_PFh8-OZ6tthtrX2xXs9bvjvr9XtkvezpLHp1cPj2dL-bVF49PnAchZWucTtK6axEphiC1QIm9VCMjA4yHQwDqrFlt664NrQ1AkCXS-1ht2yRR7AMJMJ2pqzZVWirZdVZKjCFMe2XddI0LiVb9Mr852HEhds4bH5JEopbW-lnbGGNfXCyjABv42fk6-uCZX793IxG0M55y5KrpXt2Z7E6LV6dDJJUqaY0j4K61SZow46ZziOgj9POk9SxYIGITvLX-7z74dHdY7o4Hz8_nCOGHHz5-ZVB8_nKWJfn5evXx45MkVSfr-mR2cbJYvzg-B8ThaOQYM6lPrtY__c0nH3z06UdPnp-tqocns6tNva3Nr3_3aHa6HBe9k8V2p1dcXG1OLpbVtlouq2jNbr886pWz9eb5bJ4DFoNSiPjkxYWxzkVwkUmI27eO8iw_Pjl_5fbRyxfnX754kQhx_87dplqzCyhxUiTz2fpXnz376te-Akinl3ODuGlqto4Zt-s2z5J6XXGIm9kyzZRIdFO1xvrF5SLRIgYfPJMEQZSQTBO9WVZd01lrAUBnWucpRB8BXbNNez1TW9vUOkmNc2lvGFxIs3x6c3dyY6fojaJEQU6G4IzxnW-2W2AvlHbAu5ORIlAg9kblO99752__-oOdYf__9m_-7PadG67tMFMJ4xb8bx598cNffnKynn3--Lxjn43K7bbppZk0HOp2wCIFujMe_qu_-JN__M0HR_2eBB4UCXB8-Pj4k2dnv_308fTOvif15MunlmM-KCMEG_1ssbx5cHj6_OWw39NCCIyDIkFvm9VqZ9i7cbB_NBrdPzq8tTtcN_5f_cV3JanWU9V2_6-_-U9nZ0stZVDppm4_u1z_4qefmWB_99mTi4uF8wACX3zxWEq5urwYjvqUSe8gG2behOijryoCQVmqdOJR9I_28n5mW7OeX3hjXFvbronB3jy8fX76NAf9zjfe6o2mf_tX__7m66989v7HeZlJle29-tr87Lg3HLdtvV2t6qYt-gNvGhfC9_7Rn8xOLglodzqViVZHpQvcrdqdG3faqhUwOSBBxIwQBSEHBiIUBBCYIxBBjFIkEAITgY8cWAjBzAwQbMsBvIsIzJ7zXtFuN7GzWZpB9MFb9F4kkgEikFBJlmUSQCEopYJ3jBBjICEY2EfmGEkpRI7OAlwDaqKQQkhpO4tCBGsjsmtNcCa0rVDC266xDTMFH3rTHR980zXemLIoSCcglLHOBTfZOwRSL798UvaH3thyMorOKq3Ye5VkWW8YvGs3NcQopDCtHUzGzsWi35dIaZ5bY6ptJbVkjkmSkhI-xHpTqVRH5uBtXpbeeZISGXrjYWSXJKnOVFu1WZp2rSmLsmsbDi6EQFLEGISUwXvX2SQvbNcJKaUSpm7TMieEGKGrK-J47YDybZsP-65pY_Chs1IrlCLw76VgHDnGiEhMyBzBRwIEjogStfg9qAcwChEUAUdEEhGQMLiodofYtMQcI0D0WZa5YAEJCWNkjkwckrSMpgseUAqSGEPgGAlFDF6QCM4KqTAGqVToHCoJjEgqOMPeEREjEAKFgJFJJUCIgNEHjggcYgjXf9kAKPtjISh4X_Z6iBQ860znvXFXt1mRe-OWV5UQqjcoNrNl9BC8QyAM3nXGtG0kJVNFSGlRGtPZEIejPgBY65SSzaZOioQocPB-2wotkaPSSirR1ZWvTSLTgOBDYGJkZuvBOaJICoO1yBiv6xPM4Gz0HgnAR2BmvJZ9RYBIHMBHjgxEQAQcoOsoMorI0QMzsOPoITB4w94hERNEZ4k5ekeAIURMJQHHtqHgfedQaSKIEGPbEnCMILPc2zZ6DwxEFHwkBHZWXFuBhGDXRhuB2bmWGdg7ISOTRK2BWQBQkkQUPgYC9K0jZJ1qqWQihWS4e2u3TJJCaw5xvWm71rkYOWAMvD_M2o5fvJj3h70szZQWgqBabjmCAF7PNmk_S1Jtgp9Mel0IxSiTJFvvIoftehOjSzMZQwSmSKI_KqwLq0X99jfvHw2Ld169_ejp6dXVsnHNwWTaz_TtvfFwMrLe9Yvctnb_YFKAMsa8drDnal5sm-jo0eU6T_W9owN0YX8yvHNzZ3QwVoG__86rZTlYLla60NvO9Up5uDe8PLvcrGrnwnh3XOTS1-18semV5Ye_fX56scqGxdnL8_Oz-eXZJQmIAEQACMGYNFEqVfOtseum6OU60f1-SoqEkDdvHUmt0yyzEaSgw4O9plo32zorUs_OWd8aS0xCQlIU3ri2aruqsm3rnN2st-PhyJgmK_Kq7aQU26pK81xKIbSwrUkTFUMwTecDZakiperGjHemQqk8z4UAJVXXNc55YiinU_ZWJtRWTioiIfM8995d68aji6bphpOJMTbNM0QQknSa2tYQsesaIAyOOcaiXwB7EOSDl4lAScxQZLmQwgePEAHYOy_THACL_rBZr2OMgGBtUIlmhrwoZJJ0xg4GgwAhTdNqXZVFOb6xX5YF2NDU2-nOpLV2d3_y7OnTGNwffOed0Nq7R-OmantlLgXujPsMGKwP6NKiAM-v3TvctN3xk9PVtm627WCQ3Lu5L4ACB9u5JNFCEDMIEstlZVxEIQlJKrlabxFAp0oLxQBCKADoXNg0tu5sZIhEUuCyMyoVJxfrEGLro07lxbbZ1i0BAuJ00D_fNC9OFlVjQgjVtgFBq-027-Wddd4GREyyhD0HDkiIRLNlV2RpnksEBiKOkQNKgrLQRZlHpEm_vHE0zbNUCpUnMs_Tu3enWsgYWQi13daN6dq6e_LyhdZpkeV5nmapSDWBFN5BEJRlPVSSgxdahBilECEEALVcm23lZpttvbHBR2b0HJzznQuNsZer5nxRdT589uXpxXwbIstERiQbwxcvrzACoOyN-kJKB5j38yfHc5mls2X9q8_Onl5uTy8227Z569XbwHx0uDsclgIVERnnsyztjNNaAMJiuVmst845a42WtPX2Yr7uTHu0M5n08n6Zp1pHhmpbJ4li8AgieqcznZdZf1Q0bceBvQvrqmGye9NxkiRSy6YzrTGNtZHDbLO5vFpVdWecXa0bCAGZ57MqWFNkya2DSdtYcLZeNkmKg0LtjVNNtiBQIIJlEkRESZKoLJGKlpu26uxi08xXzYvtBnwcDUtvwmq5fXJ-sZuIe6_eauu2tbG_P_jhh1_uDtM87xlBT87OKud-_fDLT569eP_R6d2jyXQ6jSS3XbcxpnVOJakjFlL0hr31tjLBrDb1y7MryyHppY3x7752d6_f-_zR8R--_boWePdgfONg-trBdLbe_u75sfLNZG88X7a6J5mpbrv1cpsX-f2bB-x5tV5rIXxrl6tVlug3799m57wJpOV4UGotBYqLq7Wpt4Dy_HJ1_937EMNsvi572XJe3X3taLw7lEmSJwqEWm_rAGGz3Eb0eaqsNd4bQvQ2IEYEBmBrvc5VOhk0iy1GD8AoyTQBiVGSFGq0v0tSpUUmEcrhmEHqvLDGhGCX51d11c2WK9c0y4t12_lEy8nu4M7hVEn8v_6f_uL1o_3S-3_x3Ve_887dujNN3YWyd7qq_uMHD7-4mP3mo8-fnJ9DUpxdXgiVRBEyyLDCt-8eff-dt77--r0_ePe1r71-N3q_rdrOm2XdxkT--v1HJ5er6dGo2B-9__4Xj5-ddt7kKqtX1WK1BikAwNR1kaaJ1sNeNuiX_USoyP00_9pX3rx7eJBKfXF-pkh-7asP2safXK7-H__-7_7-xx8uLhdvffvBct20nd1U7r3v3Th5uQjsv_zi2Xg6hrHezFdmZULb-bartnUx7AmRZjd3q4uZ32zRGZGqdFR0dVccTaMNsy9ebGdzdtYZW2Tl_ffefftr7zz9-DNr3J__V_8MkP_6r34Uuu3q8rJzvihKlRfbiwutRAh-NV-lZS_L8nIyAG9vv_LK3Ts3EwyjUa_bLLOyf3D75uXlrDWdaWvXtkLuHHJg8Hx9NARmFhoIo_MACNYBAHJgjhAiSAL8_REQCNnZiAwEKkkIUSdaxBibBrwRQl7HP0ipYnrTgxVEdrshBuaYFaXMc-tDDJRkhcp6MQQAH4xBwBhDjFEoGSLoNAWKhOg7i5FlknWbdVok0VjvHAnJgMVgTyrcblaj3cO2riEGrXSIQWWlt22SZmmWRwghAiGP9_a6rl1fLgBiV1cA4JxBIhAiICHJcjQilHXVCAH1uoocGZiRSFL0ARkZQRIJJYuyEEIio1Y6xmi6jhHbzdabYDvXGWtdSNLEWcuEBJDoTAiM8frEyFJKjqy0tHWHihAAQMQYhZYcojOdur6CF5IhCq2iswiMzMHaiCIikkACiMFfS8EEIiOjZ7zGUaY6ugAxorWARFkBMYKPKIi9F8gQWCCHxgJEjhyscc4SafY270-Ywbc1ewshAEKMUSZJDJGdY_YQg8qy0FqV9ZAjxOhNI7SO3sUYABGJKDiSSkRkiOwccEStEYkRBUL0nZKaASAGDAGJUFF01mzOWRWUa4zxuuGdFwVAQEG9YZ-tadumPx0JRT5ERDbbuhwNwHvjHSU6KXsheCTUJIxpVZY2Vc0Em-Um1wpjjDHKRHarLYcgSMpMBe9DtdVCA4CPITadyiV2juqOBYME6AK5EJ2hQl-3fsE6BAb3-8MQxAgxgA_MEQGAAQEgRkAAH9h5cB4iACMYCyECITGSRyIAAPaBvZFSxfC_fjmQ2FgKAWMUaR6RSYjovQgBQhRaxcjRO4GBmEAK5EAxIiMTSp2yaZEDWxOjBUEYI3gfGPVwB12nle5Mw4mOXUCIjMK7mJYyT2XXNfujPpFAxGXVLNdVb1BwiFrJAGi8DSy0otG459swPRx655HxzoMb22q7N95ZVU3eH45u7ORSbDbbGwc7q7ZVUi0v1521XdUkReE6X1Wt9T4Et7hak2OdCNNB63i-bcoiL9JMspjNF0CJ7PWGoyJX6ups5gQMx_lqU2_W_OYrh5tto1IajNR-KdfrBkOUAHdvHu70dQL45cvj__6nv1pczo1z3_uTd158eTa_XFZte-fe7flsXpT5-cWybowQUkqsu67quiY0s9lqs1q33jlvkyQHwOC9N7YohoTF2999-2A3HR_s2Noe7B9yZ72j6e7k9TfuXZ4vQrAxuLJM63qTZ8V6vkqTpLMuAETr2FjvTVs3rrOSSGbKNK2zFgVfnF6Ww76U1Ov3kzSZHu5tl2slqEyzzngpBJFQeZqUiqTo6q4Yls66wahf5DkTs_eCBCnhOofAaZYG9_v9QproLNUAjIhCoRAyL1KUZK0XEpMka9sGgDBGgCCkFFKkeW6sAQCBAgm9C2kunbWuNc7UHNnZkPd7LnglU4YQrA3Waq3Ge7vNZpVmaZZr_r3EAnb2JgqCIrVarkfTUdnLQ-eWs6vNct05H7w_vHUDkaXAmwdTy_a1o4PJqDdf16_d3nnn_u22tZttvb83zdLEmHZ_MuoXqWm6w4OdV14_6PfyQZaP-kVwUSultYoxWOMRsGpbRiFSJRV2nQsAkdlHdi7YENdVC0CrbbNY1w7QRPYRjk-uPInFuu5csMzbtV1Vbd3609k6T9PWhKLMVptq0zZtY5iD9yEgcOAYgV3ESK3xZZE2tUv19e0BKS3LIsEYBVOuVa9IyMc8S4u80Er1y7RIdYi-a62SgqQAJJ0k6-XW-SiUbNqmSLIi1VLqnb09QQRS1pXVWlvnt3XnGIWWHfFm26lECakDomXsfLQmAFKRJrnOiyLNtCLEGECQCAwMKAG0xLJXDkdZr5cu1_XVassKXXCfPj9HiXKYPXs5e3Y2HxZZ8GFWb7ebpu1sUSglWQnYds2ybso0v1gukiSLbB6eL25O-pNBmeeZsZ21nKTKWpdnSgghk8RYLlLNIF6eXcy9e7aYxa6LgWUiOITHp-eIvHJtP8t3-33CeHW5GfXyoij2Rr0YuWvaEGOE2CuL07OZj_7Z6dX-zlAQCoD1dj0qy7RIpsOy1yt2d4b7476xZtIry1TkpdIcA7LtAklxcbk9ntVKp5vWDAZj52MxKFxn_-dff_Hm7f3axSb4TCdJmp6dLTpnbOAbtw7KXmGMRxC-8b_-9afPXpwH0uPb01_-8rPT0_mTk7PxaKxRPrhxkKNwUqV9dbJYnc1mDul0udxs64VpWmPTPOPA203LBKpMvvutd26NBvv7o8vLmZK43GwCx8F4INPkZ589__lvP11Va8_i4mJ1NV98-cXx6dnl5eV8NlumafLxp49evryY7vRff-3e7nh4885NyXBxOdufDDvTQYiHe2OthA2x6BXluOhq57w7fvLytXu3DybD2we7f_gHX_npbz5ZrKrzs_mmqYmjUjorUvbOGWebRkgZWwcIRBStC5GbuiNFeZFzDBAcMgSOzri835eS-vs7WdnP-73hdB8hqEzme5Pjzz4zm3ozXyJD11qZKaXVYDj4s3_-R3_6z99LkyIXePfWboHFe_ePuvVKuNDLyy5wF8Cg-mx5-ekXL54cH18t5gysZVJvu0Gvd9gfzq7g3_7LP_gv__ir79y54by7c7SXpPmX5xcuehtJCqg7_-Xnx2997b7I8t99_vT4bLmpzHpTTQYTa-o8LzHRaa6ne-N-Wr7xxj1btffuHNiujjH-0z_-5tffeqCS9Be_-vDRF4--eHJ2_-5NqdLPHr38yYe_e_jpycViGWNwIF68WLCSiHi1Wj_-4vT933yORHqaLy6X3XwZ20agEMh16yY3d9GAmS3sam3WnUxUkuUxRrZRF1mz2ciA_Uk_GGvbRiiym_Wzz79Iyvxo_2Bvf5KOxW9_-sFgWLx8dnL44N5q3nhvb791z2w2F6dX5WggtQrOnj9_qbPs3a-_c7i_e3l8fnA4CR4eP3y5NNv1xby1nfcduFbw-IADQ2QUxAhAxCQYAaInjAjMwMAMSCAQOAAIiOE6_AChAZJSafZBatWt1szRWxMRZJaDQhuiyHPAuF0vuGnyXmmdSfOCCX0MINPJ7pHKc9fWQsmurSECMAvCyMAxkBTsA0YQSgUHMlUAGL1FDsjXgh4AKYC9kJoQA6EkhBiEkKYz29UqH44YsK7aW6_dlUIGH4VKJWFvNKjrbZKqazJG0RuAENtqWfQnQhAq1dVNv99jYG-tThJjOkHi9wWpwM64LM-vP5ssy5mDtU5I6Oo6KQsfnVCyN-1HG6rtWmnpOyOVaDZbAPbeK62zomfbFgEAotS63jZCSgbWOgGA6J0git6TpMDBG8eRlSJmQIlADESIQEi_9_uiJEmxdYI0QgQEZEBKGAJdM_wFQgjXrjcMjEAQYrBe6lQqabtGKM3OERAqQg7tZqWyUkrBzgACew8I0UUqdeysEMAuAAMSIyESgCBvPCJyYBQUWkM6gcgkxHXyB0NAZAZBOpFSAgfXGSGkSJIYHMYYfAQUQickUozgth1iGO5MjXEosG7avN8PbV0M-iFYU3ccfDHs2Wob2FfbWpIAAIjsjVFZAhAHw-HVxcV4ZxKiDxzb1TbPlPeubo0qMgERfWDjQUlGdpuKmzZNEkThWiMA2Uf2QSiMPiB7gcie2UYSkgOA95IwWgshgmPwAQDBBfCOXcQY2AUgCYRgPSFw9MAAgn7fB2CAEEWMzEyZZgZwDIgRGDgCIUYSAtka4uB9kGkORDEweMfGCSLQyrcdCmTPMtHMARGQgSMrlUX07JzSxD7KRMkkic6gEIJ9kvWdtxEQKJZlr1pthZZ5L6mWVd06hZDlKQcEombbNM42rQ3IPoaubodlrqV20UcfW9eevZwF48q8oKikksvNUhJ98fCFc06EcHq6ev74Raq0aS0JVYySGFnmCRQKlEgTHW1QkooiZUKthBCcZYWL3nIc9MqA0B_2nr28uJptZvWapHhwbz-XOOkld--Nl8tqtWmuFpvxKPcCvTEd22LUmy2WO5MxAqf98k5ZTgb9neG4btujw9HV1cZ58bVvvLKsOkW8WdfDUeEjHJ-vs_FgvtzWbQveI9K2aVEKG4OPgYC8Z6lEklDhoF6sm00wzt69uZdreefo0Jq47drJqNcZQ0hd2yHTYr7av7kvlZ5drnujvpAihBAje8fTnUkAYATn7LWLj1Rkb1aXi7pu-sNiMuhX20bhddkDnQ9pKqRSOskE4M6NfWLq98vBoIAAi9mCOMYYOcT-sC-A27oq-wUApkXKkZTW_eHYmjaEKKQEIiQYDgfM0Tsrk5QEhBBi4N5w4oM1TSvzNHgvpQDA_cNpva6K4SiyRSFJUJqXbdsqKfujgQ-dROG9UToJ3vcHo_0bd0zbpHneK7OsKJrtlgPKVJWDrJeVABEwNqsqK5Lg-fDWge3aNNXjftEs12-8eufBzT0iLrSc9LLltpqv1iCVt6bfK3aHw36ZV01X1WZvtwcdC4CbR2NT2zxPdSKRQSoJgpxzNkQTuW5MU_v5uhGCpFYowbi4WFURaF21rfe18TIRQNR0DgXVTUdSblrjGVZV631oO193noCNC0JQa029NYgQQ8iKrK27vJ8764OPQgoGQAKOUSjOi0wAD4cFEQpCH3zV2VVV7eyMEWJdVcH5prWgOHpet0YTkaTJtDSNc5EBxbpqTIxFL58tVkyCA3fGB4ByJ92szZPLuQP8_GpxUVW_fXrRiPBkNv-b33w-N-35uhZFutq0WaIUEkpBQiAKj_FstfngdNVHUZPcWr-u2k8fnQhJQeHJxfxvPng2yJKzxUYAQ698_uRk2W0LrUDKtu5m23WqFJA03tVVtd3UwVkXOUR_trKv7o1v7u2-sb9zNO6lxPVq-8Hj52Wqkqx49OXxk_Orzx4_e34-R2OfXc1r25JWootvHh28eu9odzxIFT24vXt3b-dwMLg12nn89EQyvzhf3pj0h6OBJEKA5bYdDUuSYpDmq9Vq2bq9fnb3xv6ozKMPvTJf1fWrt4-Ozy76SSKl3FY1CcyTnATUVffJ2YIiPDqZrzb1y8ttf9jf25sogcyEGLt164EvZuudTMssOb9YDlO9szcohLxqXJqmOpMQOEt1XpRZqpUQX7bNvLO9w8HvHl0uFlWSS5lmTQjb1pZ7w86H47OLp8_ON3Wr8sRxrLaV83bbNkJAY8O6rd5585XV1WqY90ckowk6UU1rjW3TPCtHxdy6v__5Rw-fn1zN185GmWkSsFlVdbV1ISLheH_cNs3LZyc7h-NRL0-ypEwT07bH5xcPn72c1-vZdlk18eb-ZD5bZbl2gf_d3_5CJrLrutVqXW3bDz58VHfh9HJbb1uSaL1fL-vOGSVUkffLsijybLtppBIkCQRlZQYkvCLA31u9vA2khHeRSCR5LkQilCyzoshzqZRr23rTJUTloBQkBIKPnlCMjnYPb98eTvqeQmXi7HS2nC-OBsXX37j3YHe420_bqsvSxKNa1vZ5s_zRJ0_-6m9-fvzshW3berVaXFbBwdfee-e__fPvv3Kw-2ffeqUvqelCVXcvz843tfn1h48-fnSilVjb8MGvH3UmjPqD-6_s_Ie___D45cXVbHVxNj-8MaqWG5QiCByMh0Weu6ql1vX7yY3R2LXLr73x6ruv3MoEaS3-3b__8cuTk_7OZDIaf_3bb37x-dPTdfvFi4vW-ntv3mtW9bo209t7UcTPP340O5lXtU8SzNNk9vzCLbfLp2ekhNSJUMJ1bnh76LZdM19B54iiTlWzbaQEEtQu113Vhc6ADaapAUBn1DY2In7vj7_35ntvew__4X_8u65qWxObqnvwjbevnp3uH-3Mnp2GwAKpa9pEZ84ZZPFf_9t_eePoXjNffes7X9FZ5jjoSfrbX_6u3lZM6NqOHQuYHAAiAgLhNaiCAwAwIgADhggR2FogBLxeakaACAzw-2QPEkkCIBLROObAMTpjY7ToAaTUWRGdK_My65XgWQD54IKLg4MdIjU7P7V1W4z65bTHLtqmTrPUtS0RKq2jd2mWqyRnDmlRACFA9M5w8BCCEIRCSamij94bRmkbM7n_oD45CRyKwZhQZ8NebzAaTHea7bbe1nk52KyunLNpWvSGA6FVs1iKJNlstsPpodR6vDONITLEsiibehtDFEorrXSSSC2RKAaPAjmwUDLNc-bovW87t9ksimLoQwjRxxijC0mWVtuql-c61dHHwWgcrVFJIlXirLWdsW2HEaSSkVlJ4shKSiKIPgCDIArOAwMyqCwVwMF6BEQA9pGUxGsUJ0e2QUgFhEJpAkBG9gGRmByQFEgQmUhwjCgxMgqS7BwSMgCEwOo6kgEkBAsZrU0kRQahJQH54DlERJBK-NqS5GidQBREGALE4LpOlT0mAgIilIjBeyUTlCJ0FQmJSBEAvJNSQkTKU3YhciREiBA4hBCCD1LK6D0KhQhCKgJApoBB5AOGwM77apPledfUSmmlVLOuM50mRZaUuS5SYiZmiKjSrDedDifDzXpVZL1qWwkpkSAEd41AZe-t7ZSi2DpE0GnqA0dro7FZWYLUHD0ER5Fj28UQwDIFBwzIBMaJFCMQdDZ2DhAIgH38vYvtGvrvPQkEQEACJDCGo6cIbB1EB0JCZIAAwQNwNJakIBDsPVhHQhIlJEVsjEx1DB6YgQSlmfNBpAl5RxwhRibBiNH5CCwImSh4T8Ehh-BrodNgnBSSBEFgCJ6QwAf2bI1lIbumDU20bZNkSTDOmS74AJFccGmRjXYmL16cbjd1lqVSK6WkdYFtQGIAqpoulQIiTPplYHhl985ie7lZVYkS_bLoT8vNpkaMvTI7Opy-9fr-G68etsEHKWITnHGtCdHYrnGeo0AJVnj2aZGtZ-urxaJtzXK-vJytGtcN-2lvnHVNE6NsO_P4-cnDL6_SnkrK_JWbu5fzlema1bq7WFYyUau1-6fff_1wMjx9fpUmSSmT4agvtLo6WWzma0L92u3dxdWmlGLYy3tFPh6Pjq8WEoMLpAhms41GIhSJlL5jFqCV3FZVoiL4wM7c2Js4Z9bb5Wg0drZL8_yNN-78-bffWLRt5exmvrKdS6Tqldlo0Osas3-4t9lsttVWaUzLoutsrqnerJTUIfiua6UUKIhIYBDNphJKhBBmlwvvucizyXQqlWo6myaJNb7fH66ulsE6gNgrhyGEwbA3ny0BIEty660UCpGv0z6d8UmeCUnOdGmWdk0DCMPJME01eG9rpxOlSKJAb43rLEmlU91WlUq10lIglUW5Wa2FICW1VMrYLslSIbQ3noikEEIIRCyLQYxBXDPLGKttF0I7HvXrqt3fn_aHQ_a-6BUkcDoY102V5YmzLgICqaIsfVU3m3Y86j1_9uLo5mSQprvjQS5l8GFYZufnqzcf3EylPjmfT6f9G9NBZ21wpp8nznY7o0FTd3matG037JcIcK3PiJE3tbEM1oUQuTHOOU9KB47rym2qjoQ0Psw3dZrpSNh1tm661jhEqjuTpImJZlnZ86t1lifbxgmJEREButauN00E2e9n5TD3LgikbdNkWWpD3B31jbPtti1LLVFC8BJxsdwWRVLmuRI4GOS7o6GzxntgxDRLvY8hQGs8kbhcb1sbF_Nt3ZgAyAKl0rNllSR6WzcnZysfwDBWrV8uzYuzuTGua33XerO1n332VHT28mKlXXz-6NmPfvy7Dz7-4nfPXv7m00cfPH_pU3mxWrtETnf6zvBQgphk21X38nLz6PgUBK-3dlL2gFSO9vxs-dHTl4JEX0jjvWZx-8Zekei6c6sQ98rkja--Wiq1WlVkY7D-vbfv7ajkn3_z9VvjYS5VorGq2x9-_vHHq9k3b9-dTHZ2Rj0k2O9nvTRJJX3r3ddjgOmw_87NmyDi-Xz7wSdPUnbHJwtnOSJW1gLAZFzenPRHg7LUyluzPx6ViTgYl6Mim4xKIYmYb0-HvWFOjMY5TXhyfH44HqGCMkuWWyvY99IckKP1UqJAOhxl02F-a28yGeZ7k6EgXG2308mgMTaVynMsi7wxcW1bj8QMkzKvGvt8Vl1Z88XFxcvjK6VEpjNSigj_4_sf_-jZ8XLZ1R2fL1ZNU19uGqfl1arqHJ9dzS8Ws9VmbYKzHEzbtcZ6x0rLRKuE0JgKndgsN5Odyf_2B98olUyzZLfUzy5WidR127lg_5__7__l6nK7qFvrPDNExqbuCGPWLymCSES_V8wXq9296WQ8zMty0MufPz1--OyZMV0ipRC0O5786fe-lRP6wI1x86vZ5XpzNV9G5xOtfefzXI_39uaXF1XVpb18ujvJx1lXddY05Drvo5A8HI8tQiQ0DetEcojeB1Ky2daEMckTIhrt72aTUiIj8I07e7brusqmSb5dXeapNq1dzTZN47z3f_JPv3_69HiyP-Rge0r0sow9TzL5p994_c__i_f2R_molMa1jsna8GQ1-5__w3_61e8-_82vfxda09V2Wua745v_-__mf_PV12-_e-fgfLY4GA7W2-rxyeloPF5um6vFGoWugvkn3_lKEH4125yenb44v1huqp9__Ohwb-fhl8-8901np9Nhf9IPFiAGKZDrViDe2J_85Xe-cnFxeXq--t47D7RWhPo__i8_-fizx9l0_H_8P_zjH_34oU5p24Yff_C7s_MrkYnNqp5drPZf28uK_Df_-dfHLzdKigdfv7M4vUJNVVURxt6olxUJ-hCMcbUBD-1iwW0XmkYKCs66pkNC1euxIJ3nShGwJalVqo8ePCCErCh3x9Obt6c_-YeftfV6U9XBhW_86R-8-PjJO3_w9bPHT9lz2zZIKs216zqp9PRodzwYlUIdHo16ebraVM9envzulx-dPn1OSjkbXNdhZAGjfRCEgCiYYwRiIAlKQvQgiKMnQFASEaQUzAA-gECIEQiAkb2PzjAzBF-MpkRCShEZY_BSqbTX00mOgiBymha9Yc8570yLiKbrrl6caa3yftGtVvVyE60Bjt6563mEQ_DehhAZgncRkKRKrDM6TZw1ggRzRKE8R0KOzM4zMzSLq6RfyrRHWf_uu--RkIPxuOzlKMTy8vLsxZPo_WT3oK1WiDQ7PT24c29xNSt6fee80knRHzES4bWdDJFQZ2nXdM7aXlkCMJHQiSIS9bbxIaZ5jgQQWadZ9C6yJwL2DhEAIFUpABLhej5HZC0TY41UKoQYQsiK1HvLzN66st8XgkCQEIKkAAIlFURO8hSYEWL0jjlCBJUkSGjWaySJRKE1SsnoXeDri3ckTcwBCaJnYCS6RsZ7DiF4JimEFBAjAQsSAIhaRecBgmAQqkj6_dA17F0wRqcZM7nOCABCRAHQWUJCFMgCvScpo23AB9QKPMemBu9IKQAQWgKK4A1EQq28NUgCIrAQCAjEv6-eA3Nw7IMQMloLgkAo5y1Jwd44z8b6tKeEEvOzOQJMD8fLi4VpWxLSNI4QsrKnlFxdXjGw1KosBvP5ledIKILt9g8PZ2cXSl0_TCAMtuoIBVuPMcbWxOCjUMFZKajdVEJJ5mhro3JNnoO15B1F5M5LEN6aGAgkgfPXW_zrFi5GBknAANGB98DAIaIQcF1xaTogEBHYIwgQQrD14ANzIMTQeRBCJCpah96TN4SS4fdxPIiBlASRRQaOAOwJAkRmFEJIFBirDQgltA6eFQeAEG0kZGR2xgECSRF8QCLEGKzFLGEEklKI4Os27ZWA5IMXSqMQIlGzZeVc8CHY6B5dzSRpJpRIiCC1ZKS2bYtEIwmhE-f98fzEebvcbkxj0yLZnYySLAEksOFgf3h3Mt1u7dV5_b037waPCCIdZGmuOAhwJCXIVIyG_UKTt8ECS01EcjgslKD1fLs4r_rDcr5YAscbB9Nmszatay1qIVhAf1hY407Patv5caE_eXi6ae18uXn_yxfAQWk1nPSLTL_27v0EOC_0mw-O9ocDu64U0e2daQ_0d9-9b7ouRHz9zXv1pr19a_LaO0dd56qO337v3mg0Ulo_eOeVzvnL8_m2szrJW98oIbNeOijz5XZzOB4R4Xq9TROpJRHyrZt73abZLKvX33xzujdsqsYbl2SKIyPozlpkwQLTPEVJTNgrc2s8xNCfDtvN2rW1CGDaTibU72WDYS6lrqu27JfFKC97RaoTrTHTSd3Wk-ng6mquEi0JpZAhxt2jw-Fo5JzN8yw4R4IGgzJPcwB21wXK8ZAwhuCBQKICousNuk5T4CiFTLSq21ZpSUi264qigBiFUKnOUAidKkAOHJVOTFtzDGW_1xsOlKI0pei9s7bMM9cZiGEwKIfDsigL2zVXZ5dSUpapyc6w1y9evXtDSpzuT4B9PV92UXzrq6_vDnuFltNRT2kqcrk7HdRNd_doL9HStvbRk-OySPM08c5JKbNE5lk27y6n5YAZrfNCouc4W1Wdi57R-rCsWqmpbV0I2BgHwI6jc3HTms64Mk-rpkPCqu2M8c5GjtA2gZhESvW284SdDV3n836iSNjgp6OeM2aY6c7HyNS0JkuTXpFaZxOkfq6H_fzm7igyEcREU5YoRFaC8jQDBKWFkEIoEYCdD511KFRrrCChNCKS9aEL3DkOwCGG-XKLJPNhMV82PnLrwuVypRJtXFxX1gZPQk4nfRAqL3qj6Wjvxu6dVw_uv36rqs1kPGhbc3p8OltuOcpffnSyaf3jq8vffnbyyYszdo6YcylfuX3wu8eno15P9nvjYX9aZLvjEUrsZ8nh3nQ3L88vqq-9Mv3avb0BJTt58frOpHHxL7_zlf3pUBPv5MOr1XYyKpG4tUaRvH908O7ukRJZta3aatPrJfs7w0Qr0ipE_OL47P2HTy4X63ljpVR5L6k8z9frx1fNaJCXWeJ9yHWKSgngJJFSSYAgJGkljXc-wnxWLdbbdVWzR0Dc3RlnabK3NwbAwNxLssmwn6gkTVQvTVWaEEYfY5YnRKKXJEok1oNUQgrhI-tEbbbdsm6vFlsQAqQUSW44nqyrx3X7vO4WnbXW1RDP6-2PPn_83__dL37--ZcPz-dXF9uudcZaS-18UVXGrtqGCOvOdHV9cXrZeI-C0nFuY4sIXWfLMrsGzS1O1t_6xuuv3zr42qt3l-v2s-OrtEifncz__mcfH-0NYpF__OTFpvZthN44FVoKxjJL6k0dvKurtj_Io3fVcq3S5J2vvOFas5ivn7842bbdzfv3gAHBPTy9-JNvv707GHJkrWWW6yQvikn_k8cvv_3ugxuH-5umK_r9bdudXc4bb0_OL6t1HapYJuny8gKsI8GdcQFCf9zPkmwwnrq2RkYhlBSiN-orKUQitFbRRohRKo1I22UdA9RVtby8aK2NPvb7ZX9UHBxO-tMB2-4v_81f3r919JWbe8HYH3z9wQ--9eo337h9YzzpFYkQ2BpexPDFYvF___tf_PxXn51dLaqqTdP8n_3ge2-_cvuPvv_Ntx_czCRoqYyzk_74Zx999unZaWvaD784ZdvtHR1-460HeaZ-8eHHP__o4bOTM1LJ3s3p-dUcQN949dazL1_0d4ZCCkzSyf5BWer5fB29392b3j7a_cffePvDTz8rUvWD772XCZ1l6c8__PRsPtdl-c53vvIPf_thlmXf_IMHP_zlZ7_98JF1dr2uTp-fROTNrFtdLpqq3Zn2vvODu89fzLfzarPYqFQixwRIQKznyxi90iqEYKtKkogh-hhRirQ3kFK3q0Vk7OpWCeq6kOb5wev3N_OL-fn89dfemPYLdM0vf_bBcDK0zpASQHE9X89PT1eXc8HxGtZPBNWmzfr9r3_nm5v57K37t8fD0nTdvKp_9sNfnx6fAKLI9fz5uRCoSAicHiAi-8iBiQEAGCRIBM_gPFzzHIQA9ny9-A__q9WIrneZDNEjcXAOEEWS-Aij-3fRB0TJQNG7aB0hiVR70y3nSylVtarSMil7GWnljSGOHH3oGpVnHGN09lp0RYgcg0hTIVW9mlOSK6mYmX1sNhUhBONJKgbSaa9_cLPdrFTaA5Xc-do3UUidpZGJJEmtjbWJStMsVUkiAOrNJi_6SaouLy8m-7frusqywnrb6w2csdV2m-W56VpvXYghLYqiKK5OryZ70-226rqWhAwhpGnaNE3gSETA6JzTOm2qjRASGXxnOQYUBMDOeJ2lKHBxfoVKMLC3TqWZc56IovfemzQvmqqCGBEJCOvNRicJxIgYvfPBhQiMUiBJ753UGSExuxgCCQKBIYCQghkZAZghREqzGAIhkhKBI4EgRCH0dVAEmAkhcgQhhJShakggIwqBpHQwTpJoqq1ISqVVdAYYo3MCIToD3gJ4YogxMjMGug7YUrTsYwiREk0kmQMCACJfl2djQIwoVAwxRB-sV0WGBBCB4PoOCoAEShkjgzeEgCHY1vb3-mB82isXJ5euDe985w9Wl2dSiaLITLWdnZ75EEYH-8HZalX5aCRDkqXG-Plspoq83-_X202wngT4tkMQgCSQoneC0FuveoUAYeYXMtXIJLR268rHQAqEpNgFDFEo4uCJMLoAvRx8AOvAW_ARlIQQAADo900AJIQQgAEThSECMHIkHyEEgQgSr39BpEgwQoAYAgMCMncGmYEBEFkQAHHTkEBAiSSRIkQKdYPspCBAYgZGKYV0xkiF4DwgRQaIvw-JXb9IkOtaYEZBIUQUwjlLDIJj07RSqm1lQAnSSiWao1kuts4HpVIlxLIOiaA00dZGIYXxHpjXdbczHHbBl6msOkOJsK1Xqfz0bNnUppcliZC7--N51dzY37szmAzH4_cfPcvzFBF6Wa4EHowGX__WjTzJikFRGdex-OY799-5efON6d57t278wSv7Ly-380UnCJqmWc23axOSRCQJ7u2MJYrLy9lsVt26vQMa81QVOaaKhoPezt3xZrahaPMy76SsG98EBmMoVU9fzHo7aWtcjO7W4WFkl0ghUvXe2_fffWV_f9Afp1m0Vsfk3Tduj7Lk5eOzXpr2x_35xbrM8qObe__VX34_7Wca1YNXb3_nm28KY7989HKyM-HglBCvvfNK2Usl4tPnp5IgBts0FWHQKm-bygXumhYZ0iLt9fK0yKtVDcZj5brWCMGAWNcWorONzbKsabeXp1dKpCR0ALIhcPQpSdMZjG48HgLzel33hj3bOW9s2etv1iudJADRGBNjrKrq4Ogg0an3LsnSaruSirz3ABgD94fDJNWbVS1IKq17vSLYgIDedYlQKNG0VqXSG6elTLR2xjJBOS6lFKZzWaGd9bZtiBlZqCQXIlNKyjRPtHbe5EkWgTOdZEmi06yttnt7-741ijJgfuv1u8v5Mkv0eJJj9ON-77WbO7cnI03Y7-fsXdMYSepisUrzvG5bJQkjVF03LIuDvZ1cislwkGppO3swmCqlBEJVW-u9dWwRI-JiVVeN9cBEIiIIRfNl1Xa287E3yYlhOMi71vjOLzaVDYGUlEq1bbdpwtV840O4BmFDIAIe9rKu9c64RJMI0fg4SHsbUxepDs4lWhWpno6HeZ70izSE0M-TpEicdwiQZ4mS2puus65rrQdsW7PdNPG6-xPZOW-jj0QgqGqs81xXrfFuUzWAwiN01jmMxrnHxy8dQ-tD03aROC-Ltm2Fkj54ZvLBRw8OyHc86o96SveyMgo5LsrRZGDqZtust3V7NV8GaxtnHp2dnQd7cLRTECrmssyC7W4e7EyGuSSJhKREPxF11zAFY7n1dqdMLzdtwsEwZkV6VdWbuh1O-kFxT2kHwBCkUIExVYxa9Mt8tl4KwuBDmWrTtXmm37x1c7baXMxWs9X27GqZIL3x2r1m3fzi4bOPXp78x0-fJQJnq2pn1GeGUS8XSgFhsE4LZIAiz8teqlDkqb5ab-erLTF01nadXayaNE-dC1LQom6ti5u68z5uN_XFomYWyy5u23ZRdU-3m4vL9WKxfnkxH_bK_qA3mU6MMyD1x0-fbb1_dH55vG1Plpt58FedOZktztbVi7PL5WKzqbt1F62QLHC5XM_nWyyEIUEAddU2dRdDlFmmdNIr8ma-tNvonENU3sbO0MHRwX_5L_9ABSGTJJB8dnz56oNbp6dXf_fj37731u3BqPz__ehXD784X24s5DS6mR9_fh5tzMq82jSEIs0zJfVqtW4qk-ZFvWnauuYQ-_0iS4rONFJTlqf_53_1532lNNDVauO9d4hbY3_7yeOvvXl33B-cXs5nxn3y8Muf_OY3w-Ho7Oxcq7SpW98527ZFntk2dG1HqNbLNuuPXNN6YwfDfv_oEIL3NiZCDMcjAEykNk3XWWeMSbM8-qhTnabF3sHOdO8GKv3ee2_vHuwgBiXxajn_9JNP0bZ3poM_-_7XhYQQKdU6MDaOnTX_w88--vFHj_79P3xwdb6yxi_mzWBU_tkffuPO3rQ3LAukTWNI0rap__1PP6q6ZnQwefjwKYH4wZ9_-6uv3geU56v2b__-p09Oz4rhuHN2vlkZgKv1tihy7ppmUbcx3n_r_tXpLLa-2zZH0-Gd_f27R4cHw-HDh1--__mzP_7mm4Oyl2kJHP7df_rF6cUyKfPlok7zUmr5i48effHF87ppq6oCYp3o6XTn6Kt3m8XWdC7fL0_O1_Nni3q9ERoYmXxkY6vzK5XoelXLVCNB9F4QUZ4FIKWVlNK1RqepSMvR_p6W0oWY5ZlvN4Pp5P69V9979431bLZou9V6c3VxYTsnEj2_mEXr6vU6TTUI1Rv29-_emJ2d5L3hH_3zPxkP-v083d-Zbhbretv-9refn5yeoBRN03WbCoCj881mK3C8zy4gkRAUvUMC0AkoADsD1MQAEpAAfAAmQIAIAABKgDEkJZFg55kjBB-cR6K0LL3rijTtOicJVZZYazhwkhf1ZuWapuhnKHA0HAVjbNuGznRNxd7ariMpAaLrjEBAgCTvs3eRGVHpfNhulkonwTmdJLZrhRRCoM5zH1j18nq96k92dw5vDw9vKkFa6d6w3x-UF-eXALJaL3t5L1rTVlvbNnlZzk5O9u680lWVLjNEkCIlLaTS1XpZlKWpq2u4DRD5ELumLvv9JFG2szGwtV1vMKy3VdkbJokypvbBCaSm3gopr7toEINvW-88CqESFT37tlWpjJ6DdQwoCVWamM4oLZ2xQlBe5ptllSZpVmR5UZquRRLeOiUoKdKuaq-tszEG9iFenzURo4-MEIMnKQIhAiJHto4AAUFoHZ0nISAyxhicR0QmBB-AwBsHEWWaqTRx1ihB0TrnI7Nwm7XKUiEgRu-ZwVshIEKIIQq8TrAAJgpJRudFotm0188QMcTIRAIBOQZEREKOAXwgwOgsCymkwBCvQZ_X4TLmeI2oI6WQOTQWGEiga5tmtpzevW0rc_OV-111tbw8T9N8cTXjQEWZS62qpjVdO9zdG-5PN2eXoNF7yMqeStT8-DzJlFSJC0aR1Hnquk5rYa0LzhNJAHY2JklKUtqmRUQWgDGytUpSDBEUYvTIDM5KlXlrwcXrbA9wAAaMEUKAGCEC-ABAYByEABDBBSSCcD0dBaGF6yz7gMjXHmV2TpDkyCwISIAzRACRY4ikExRIMSIAxyCzxHvHLuhEh7aLzgqS3gchkQh8Z4UgBCQhSFC4rnOESHQ9PHB0HqxF9kJKIbUPMToj84FvbDoqslI3xpEUSaKDCwEwyTLnQr_sJ0rUmy7RqkhTY433sWk7E8J40FME3gcl1OXFarrTH_d6N6fDXIt-WUoNo156a3-4MxlZ3-ZZykm-Xq6Hw2LR1ttN9fJ0sTgz3pnzy0VXdW3XvTyfn67WIZWztnl8tf3K_dtvP7glJB7sT26_detwp1jO18bEg4NhDLBeb_I0Xy6bu3cOtQt3bh4-eXY5vb372S8eO-vr1nz-6DhTutrWL5-crdfbgzu7n37w5dnpWmmq2vZktTi5nO_sTo8OdlGAsFFmuTf-8qp6cOOws3ZvUo4G-f7e3nh3OCqSO3vj9-7frZddT2bDXkGBue5M25apauouev_6K_eIgYCHw3GZZ_dfvT8aDR-88dZidr7aLiKA9TZL83tvvHZ6etxWnbGx189IxGjj9EYvBrTOQya89aBU25jgLUDrvQ3WDPZ6O3t7g-EwTaieLxKR7RyMUp0oLbyPbd3IRGolyjKH63k7xBi91ipNMwKIDOvlimMoe32pJceQ56ltO2NCmop-v2jrtqu7pMiIYgiAzP3R0AcPHPMsRwFJkghBeZpfns6zXKs0XV_Oi17PdhYFo0TXtTKNdVWHGLI0UVKmmW7r-uDwIFVivZxlebaYXxXDssiy3d1BZ4wUeLlcb7bdwXT6xht3FYmnlx--fvsNil6SSPIsupCkiSDUREqnV_PFwcGkKDOBYWfaD84SUZ6nUgmOgMSrqlVa1l2oG4tSGhsQMUQOIYYAV_MqyZVxoWqMD9DZ0Fq3ru26tpumNZadi3XrWxc66wIF56GxHnxQUtabloCBOEmVd14mioXChLrWcvT7e0OtpEAkgYJYExEhIkoprHOpSrRSnbXW-c56pZUPgaTy_hpVIKwPrfVI5FzYbDshlRBCp-r5yZWNcf9wulhsXMC2dc5YLZR3IQQ2xtngu85CjOt1rROpEmGDH_cLY_3uoEy1xgj7B5MY1WQ8IMRtY5JcT4fZaDrMtbYe96djY8Lz09nzxfa82T55fnq62i5N9cHjk7N5c7Qz7ueFIjDOFmXGXYxApDQKMdoZWxs__vLl8curRbV9dn51vNxst83Voppbbur6t4-PF01rgITgcX-QF_ndnbFzvpfnk14fpEh09srNI2PN-enl1itrujdv7n7t9sE7e-PX9_qjNLvc1NWm-8mzi3W9NUzzzfbzF5c_-fzFtvEvlxtE4iQBYJAqTZKLVRs4ziu7MV3n-PHlOptmUco0k16I-bpWvZQSdVxXLXsJwjsvkPIyPRoN9vYmwfPJavv49Grp7cOT81nnXiyXq7pbmK5LedU1s8XStma7btMiTzIdAnbsjXNdZ2zonG1th8jMlm3tAqMFH4msaRCYfcx7xfhgcn9vZzwqv_Xq3Z1CbbfNelWfLTa_-e3jZVufnc4fPnz-2hu33rp_63g9e_-Dl0WR3vlHN86_mK2fLxOJQilSQAL7g37s3GqxaK0re-nh0e5sdhVYvP3um4G97TY3D3f_yXe-8drOQAuVJOp8vv788vJougNEVdMd7I90khhPv_nyKQGuN-1X3n3rxcmp1FomwgZvmvoaR0Ja9MoiBs8BzHaTpII9awTwFjl61-W9vGvNdPeg6GVCyluv3LN1dc27W87XQcS83982ddnLt-u5bdpMJ7vD7Juv3_7Xf_L1r9y5OSmLpq0AZWuilVh38a8__OSHv_ns4y-ebivTbPzOePDf_PPv_eB77_zgm-_kSQ4Iy7ZZVetnF_MPPnv45NmJ0iTT9POHn-_vj28c3Th-fvzFk9PVavP45MV8s51tqmxQ5kXW2S4tMy0FA6aDwlv-J__tX7TzFfkYQ7x5tPPV1-4vri5az6jcwY0bf_7tNw8nI2JmkH_9418fL9ZBJJ3hwXTc2e7Z4xcm0OxyLqSaz1cqzYZFoYusna8vT2cAkbRAX1ezjXchzxMfDBnDjQk2AgeVpAz-ellPQgISYEiSxHrPEJVOnHPdtg7WleNB0U_LwVBI-eaD-9Px5Oc__52n-Poff-X4s2NrTFGU1XJJhNVyrRJNQipF1WyJid7Z3_vB97-bJ_LW4S5SlIJeXl789f_0D877q5M5sxdKRGBrje-sgNEeEF03NIjwmscIDBAEsWDvkQAjo5Qc-dpnidfQQ5JEyBAR6JoiiQzecbQeAm-WNaH3zhtjSJDOMmeNaeosLfJhLgUh0PL0TKdKgMMYOUSdKI6eTQcMxIFjJGISSKQAOAafpLn3bufwiENgIQgx2BA5Bh-RhM6KfDhNyqzo94KPaZ4pQYSSJDrnEqXX8yuSEoGq5TLVmdTy6ux09_ari8vZ5PBm06zW82WSZd4627Vlv-86Uw4H1XJjjUWCPC_atkGUKAhCtM4lWhlrgveD_kBIYTvngk8S0dY1R_au00miU81E0fmkyE1bX3d5ZZYws_MuRBZSbjerRCsSpJKMEEMAIkGCnHPE2FU1EgCikIKYicA7R5JCjBy8LlIIjMBKJcEHlDJ2gSQKRkRAZnZeZNq15hrkDyAoUQIpBA8xEKEkijGKNAtdG9ruOtylEq3KzDU121YPR9YFdp0g4sgxREEEESMAqiQCEzKRYkSpk-Cs0Akw6jSFEGOIhAQMDIGACYFjFDoBFMEaQhRSAjMT-daQgBgsAwmpou2uSbD9cZ8DzE4uJ6_ca1YXw-k-Isok75qmrSuthZSopOboT5--TMvkxttvzE_OgSVppAgUsRwXvX4vWss-tJtqcnNnfbmSQiBidCFEnxYlCIocOXolJYcQXMAYiBiV8CGACxwiMwbrSSkOTJmkyGwMMohUx2unEgA4Bz4iIVorhAAGIgEcr1E_CFEgINH1qCAQo3UYI5GIDAAIIWCIGCMohUJCCCQkBh9DjM7KTAfnSWsKUQBgiADIzBAjQmDrgAGRQUhEhBijZxRIJGzXSkFJXkRjAgdG1PnYO-9tnZbZdrbpHQwFgu88RI8ojPFCqsjXHEyZaqmEtM5WrfliOUuldhzOrhapTjwws7hzc3-1qLNcgRCCRNu2eaJHeWo29e7OJLb1wbA8P12sl02ayaPD6cuTFQSXZeAjilxNDsb9QY8ERxcvL2dXF6vFevOrh89lWRwc7IyGg-NnL6-uNvWmEoJdIIx08_7BzVuHTbXezLcQMEsIu1Av2yi8jxwRB720cbY3yGWCOk3qur3abCHYq_nycG9vMh0kSVJk-cuL2WcPzyBG7_ywn06LDNkYY8o8GQ77g14vUXqUJq51War3B31CHmUJWjfpF_s7U6nk7mhQb6uL2UU_z589O0YhACnGeH52dnl28uDe_Z3xZLPenl8tlYLFcu3bLngfrY0xAmJWZETpZl0neWadD8je1UmaELBpHAferuo8zymK9Xrx_kePj47GlCluDAi8mC2atrIuCCFIqV6_7Je92eVMICVZAQiT8bCpmzTVbdPmee6dTfN8NBhF21V1u3-4V23bNEsRucyLaDskgRxVlkSP3lmtZZIm3tqubgMACR5PBgG4bdp82Pc2Sk3FuEckSMrgfSIle2-aOjIL4SfTnei79XJZFOWD11-VSgiiJFWH-7uSUMb45lfuJxAHWcpsq7Z9cPD6ziBFAq1U03aBQ_BOKam1aurGM_eLLE812pBpZY1XSlzXq5AoxMgIRKLpQgBsfWhMaFsjpchSva3dtvMhcuTYemCMm6ZZrhoLvA3GuZgmWWOtjcAUlSIMYEzsVltARoFKUQQGRO9DXRupkhjipt5MJ2WWplpo79g4P5svl6sKpDAugiBCyJNUKpWkYjbb5lmS55kQ0joXArsYjXPGWkTs52XVtUoq433wbL1rjXMx-BDWy9p5b6w33gcfe-nQQzDEJlh2TCBR4qKynkNnAoBYdk2apC74YH2aqXVnTWfrens1W19sVy8u1-utvVo2jfOYpher-p03Bmy9kjAYlFLSQCWlTg7z3uHOsKm7x8-uPnlxGiSer1Z_84uPt7E7vlzNZvV4Z7xsmqOd6Y17h7cPJ5GC3fpA-o3vv_erjz75n376u9Or5fm2_cUHn__wyfM3Xnvw0_cfbUy0xv6PP_vwoDdgllriZrPeHfXfe-_B3fFAamWEjIBW6qwsJqPiYDrs5_TKwejmtKcysTMZvHt7587uMPFmt5-t6-Y3nz376MXJ-8cX5TRbRnN6tbrqalDyYlNZig9Pr37x2fMvX15EGz95ciYAiiKPTYCAf_v5wy9Wp13tx0Wmi_z0avl4vnl0flUxPFtt1K3h-w8fffb0dGVME1y1NquLq9C4aK6bkbLtrOEYAwYTo4lm0ZU6AwLovG-NSKRMddpL6vVGMBMzkt7pD77x5pvL48V0OHFdt66qbWMeff7lerleL5eDfu_45YvRaPSVB69eLRd__R9-XrUVS3j6m2exayD6dV1nOgEXu9Zu1gshpVTy5o0bd24fDAfjzWb11TfvbjdLU29s0_13f_ED8jY4v95WF-vqt188PhpNts7eGE8-fvzixfPLG9PxLz56dDmb9XsDBAGIr739et1228W63y-3y63v2sqytWRj0Fma93KQECIqupZJ-qQoYuAsyyDEq4vzZtt4H9r1SqNQSu8f7mdpMp4M0zRtu1ZTuL03vbE_-pNvvvvg9v7u7njYLySJ2ofamI-fvXy-3vz648f_37_5qW_MuosqK7_x1ht_9u1333vtfpKqFGgbuqtq_bc_-nC23ly29ePnx2medRS--0d_dHz2EnR-4-jo1t7h88uzX_zqfST9-dPnm7buwK9W83bTBRNms5WUOk3VzaPdfl4-_uzRQOvd6fje_uh7rz34-fu_XS7X_-Kffve777355MmzumlyFDH4j5-8_PFHn_f2djwhCJACz89mm-V6ua1djPPlsujnOsn6g2FbrdaXF864rmrRerOtu60XUcS6Qmu9YyJd3J64prG1V4m-lqCjSJyHNNXGtEAopTbOp0UhJSV5unvj6Oa9O4vLy299-63Dg_2Lk5NHn3-xms2ff_ZMaZVmZbVZgAclZZ5nZVEGZySq3niks-Kb3_nuoJ88e_jiK--87p3dVPWPf_Tz-XzmkZNU6X4ZBKJIwTstUMBoFxA4MgIhByRCIRmRgCECxYDBY4wcGQAIkTBCYEAUKDgEROIYiQgB2QaVpyE613QyEcAeYgwx-LYDonq5kQKddWmaYOTF1bnWEtATszMGBHF0HLztWkGEzNFZYAQG0BkJqfJSJwmKpG0aqRKdld52Msu61o1uHKX9gcxLnfVWV_NyNPbMXdv1-_3Ndp2mGbMHkuv5VX-6r7XwwTPHarU2LuSjQdYrA8Pm8mr_1k32gSMDB6ETkpIZbddA8FqJ9XIzmE6rZhuYVZokSYokmaEoy-VimReF8XY9P5MgdZaY1ghJJMkZ3xsPbNsyR-MMOxs4FsNJ9F5IpbMECQSQFOhNFFIkKgGE4KJSJJWuV6skSziCs1FrzcD1epumKSACoBAiWgMMzJFIIArUOjhPqYQQmCO7CEIEAsFISqKPjCQy7ToLHJEQAjBicA5EmuQ937Uq0RBjsEFKpdPcGeNMJ7WMnUEARJBEEAPGSEiRAxAhA0SmRAX2REIIASyEUhEYYyASIXi-loI5RwDx9yDLEPHac8Dw-zcBPIYISCBV6q2FyCjQtQ0ptJt5khfr1co7lEpmZX97fmI7F4yPDEXaE8pcHS_Xl-c7d--kSRo4eMDBsDc_vgzO37p7r9vWLsTLF6fFcNh1rVIqBpcVul6ti-HAui4Y67ZVb2e3XW0BAZyXKgkhRu_YWRQKQiQCAIQ0Qee4ayhycBYiAhJ0FiiCZwQmjOw8IHIEjowMHBxwJGYAASGS0szXLs4oBMUAKKVA5uCQo9A6ehBKBe-ZWUTHNlCSRmtllmqdOdfFEDBGmatogsrz6D0KAkDnAqUJh4BaRAAQJCR5G9FbAHDGAokYbdqbogCSxBTbtU3yoj8c1usqBE7yTKvMO06TvGq6REstKTJb68dSMTBHlFr2R72rZUWMjEEQPXy-UCJKUnVld4b9JFU7k7HOUu9CrtOqcWUuiUTb-DdvTl997dbx2WVv2GusJ-s4BNd2WkjTmixL01RMpuXN2zv1ujk9W7fWvPrGzaZp5lf1cNjbO5y-cvv2yfPjezf380zVTXv3xtGjZ5ff_tqrB0cTF63uF1VtiWCzbs7Ol21nLjdtpsRitmKE8_PZpjE60H_-9advHU4J8f2nx7f3pzJRN2_s6oxGWf__88Of3dudTHcHd3cmg165uzvNizwglHk6mZY3jyZqkKVFVhY6Sh4O-8OdMZK8_cqNt955XSv18NMvNptNb1geH78wbbs3Gv3Jd7_3_PjEOgcMSrFA1omu61aRTssiWHdydq6zgjlkWhFhsKE_Hkmtj-7dXl7OqqoN3rx69yj67hvvvaOlKsr8tbv358uFkHK5XCZCtXXdtZ0PViUqSfPlapnrZGf3oDFdqtXh_h4jem_ausrSJM1ShDg-2Guqbaqlta5X5EOtev2y7kxZ5sa0ZZF3nZVaFf3i8MZ-W7VaaWNsmmgleLw7dl3HjkUitRDNuubgEXA0Hu7s7CRK7u_tIfj9w53Dg8Ozk5eCMC8LIeD5s5er5fJwf_fqcnbv9lGWpft70_1Rf39SSgIJ4Jx3zp8tr6bDYZ5oISlLk-l4qAh7aZKnKXDIsxQBlLgOurEPMQJEwNq4zjnrQt0Z60LVmHltWEBnjAtuU3cRoG7ttuq6zpnAWmr20XrXeeshqkxJxOW63m5aEpElBxIQoW0dIiudCoVppmNwFDhPEmSoXdjUTddaG1kkIkQ2xq4WjRCkiAAx-JhnGQEZ7xeLTQixc16l6bbuUJBzvuoaQcIBt60hgSSE87zebPMsEUQuBsex6lqhcWu7RGHjY9dZRBoUeQQWqerqVmulJIaA3rvnl8sYpYlh23pr7dViZb1bLBdCJ71-prRywFVdt515flo_vdh2gOer-uHzk8bbD08ui1HpOVCEe_dvjHv9erHc2Zn28yS23DXN48vNtqlfXFWkxLOLpbOmcnFbNw786fNj24XhYCSl9ESTQd9tm5eXi75Oji8X6_nmld7gi2dXv3328nTbVHVYAj4-W_7ky2PXmA8evrxabT8_u_j1s3ng5Hy9_WK2_Wy5-R9-9fPzZfz107O_-d2Tv_r0yUNQj2fNrx6dOebdwx2HUHvxxZdXtXGbrWlrd7zdNFtvTXj58soZc3K1QCQUomqcD3w0HdzIi0OQNyZD7vxvn5198uykVQBJujLudLV5-NnTJnob3bZqvXWWbZnl6CjPJEhm8NumcQ44ktY4nKSjvSzpq5enK52JfqmLrGxrI00Aj7d3JoOi9967X0ko1suaSSVa2pxevDx78fx805g0S5tNZbp6Opn8q3_5_c7Vf_93H23bdl3VMXD0lgCSXBXjkYzgvdWJ7vX6SqvJeJjkaT9Lnz17CTacHJ_W2-aPvv_VP_3218dFRhGgSD9_-OQ__fwjlRSL5Xq-qViJDz9_fvvmDkX8jz_8Za5V3Zq00HmanB0_f_nytL5crxdttCz7ucwSIaE37JFUKCiG2J_080GBEC_Or2zbOGsW5-daU5LospclhUoyHWPcPdqv66Yc9hIlbh9Ob-4M_tl33_nWu6-_duewyNLK-JfnV9sY5pvur370_qcvz758eXF2sfCNx7L413_63b_83le-8eadcZZIGaNrPjk-fnRy_sOPH__0Pz9KFRJpCECaGEKa6C-ePmm7zmB858Frs3n9yedfVFv76tv392-MK2CVqKLIXAj9QW-437t9547rOlvVZy-vvvf999pVe2OyN54OX5ye_ujTp_-7f_mPdorsVz_56Ke_-vRf_6Ovr4wx1v3kiyfPzhaLZWViYJYvn780nQGlB6NysW7appZKkFDQNdvLebXcQoLgrTfG1EaVIoBF9MwcA6ph4jdNdECaZCK990plMstkhgTYbDa90aC1YbC3P5pMu7Z75ytvJ4o2Fxc-xvFo13h4_1e_VFpSKm1jIvt2U6_OT4TU3rs0z7q6laSEzv7gj_5wZ2f06o2jv_u7_3QwGe5MhlVn_uEffnJ6fFZVTWRI8r4Llq33dQsxhq4TMN4DQQjAwYOP_3-a_uRXsi3Lz8TW2t3prb2t3-u9--tfxIs-MiMyMpkkk8kqkiJZnUhWQYCqJEADAQJqoJH-CZU00UACNBEgCAUWwSKryWImmZmRkdHHi9e7P--v39ba0-5uLQ3u49BsYAM7do7tvdfv930AgEqjUuydlNcUUAYhrs84UaBEAUxMdP2KmTgSCMYYmeO_x8YzIqBUIFAwaCMBohJCJ8bW_e69-fr1FTMpyV1d903NACqRiZH9YiUAUEgERKWURNd1LDWgCD5YilJilqeMsN1si9ksmUzz3V0g0nlZN41Mk_Huzma7RVSIlJd58A6BpFBhGMrx6OzpF7s37g7DgAxC4J133mm2jcmz4BwilpPp0A8UQprl9dVqfry_Pl-EEIL10TkhZV5W26ulTkwMLjVpP_TDYIEozUsfHCJWoxlEImI_eG1Us1hIhK6uTZoxoh_6xCQ-ONv2SZIBABNqY7q2S1IDBFKboetBKm00R_bkGQVdnyVHDhQiRaUlEAmlCUgACKXIBylEDE5qxQzMDAjkPCLKNKFAyWRs112SJMwEjKhFjIQIUkoGBmCpJFBQWR6vrx2xZGIJMXoWMraDThNkAiEFE0YHJIDp2kDMTBxjjF6kKbKI3iEFBEQpYowxOJCIhCABQoQQhUQGSVohEEhBIQohRJ6QDcCRQlBpGjyjVBJZZ5q8lxIgxmBtvVrpJJ3f2O36Pk3yneM7vu3zUjfruttepVk-mu2224th24I01e6udd73w-1bNy5enU92Kp0k0bo0z6VgYhZKB2uHus5GZSROdiboY3COvdWZghgVYHQOlWIAAITgtZKIGAbHQrDziITWKyWJAiIAEMQIkVAjBxIcr_WrIpEQopRI1oPzQBEFEl_n_gUMjjgooa57EswMMbJ3RIRCCAnMSN1gCoUiudYmhBAh0RwCUuAQaHCEkQgoeCEVIaBAFBhjFEJJIZBAEBOwznNlEmZEYFbAKEOMo-m-7ze-981ylZdVNZ_WV5voiFHoRLVtl6ZGC4wEfWdVYiLIIcQ8y9abtkiTph0C0WhUHuxO3OClVNNRkaXm_GJ9-9a-AamFWm2aKtdpniSJVolMSV5cbd55eMfo7GhvN0u0d7y6aAgxzytEEFJoKTbLbei7dtt0rXc-ZFl6dHQwG-WV0ievThYn6yjjrVu7fdNrhNyI0Sgfofz5Jy-mszwtDHoahliORl97797f-YMPXp2t264bhkGnyXRcPn99_vDBnVCkF8t1UZqDg9GLy7USCrWJFP7wW--l2cikxWLTLdebLtLFZvvhk6f_45___E9_-uFvnr18sdj8u5999Pjxq7_45ed5kY3LctP0k1G1vtr8yZ_-1Xg2y0bV5XptsnQ6m1VFeXZ5evf45mKztl07NK02pussUkQEBFBa5jo73s8lQHvVJ1X-5tvvnbx8aYwCGbUy2-02TZN6sxmNx1eLZVmO2qF9efoaiD3TeDyydVPmBQoalWXTdcSUaHm4PxeJXC0XQNHHMJ-PyNF8Ojm-eWNxuUlylarEW6-lBIToY0-Bop9MJq4fZvNJDKEa5ZP5eHXVUAyI6AaX5yn5iIBSiizLAKEqCoFQTqvRbG6k1Kka2nY0mpydvpyNp7PxOHJcr9ajorx5504c7N58Piqy9eJybza7dXSQSllopY2IvdOIJjExxLZrbh7sChZa6-2mzvNUCKEAjFYA5LzTWgIzInjnlRI-xG3T20CRqW2tDTGCCIGW2z5NlCda1j152nZubydvbVQKI3EE9M73zXDetEWSArGw1HV2sW4tu3J3b7BegNJKFGlKERgxy7KubRIli7xwzkWGVd04F2WWdM65wVsXiClLdfBhcJ4im8QAQNsPHMlkCUiMwM4FltI73_d9bd12sCH4PM37bgAQLrhRVQLwfFZu2z5RMgYILloXmi4KRPBgdNIGIiGC9wCy76I2ut4OwDBK07brt3UvJFrrxke7aWaMzotRaVBHYNTYtIOQotm2WaFs8HXTE4erxYZjfPzy5MVi9arZ_PUnj2rXv262bRNToQ5n5Qd3j6Z7o5GUF8tVqDefPD_54tWV87SpW2n0J08vri7qLlgfw8uzxbPTxeVmU9fd5ba_Cu7R4uJXF6vxvFyquOz9qlDDts-Bvnl7_-7-KE2TtuvOztab8-bV4uqzF4uXlyur_enj7WK5Pjm9PDlbbq5qbvsXJ-dFaTZ1jza0nTVanHVUFglL_OL1-kZVvXNjf73w__jvfvPpxXZ3f8za3Nmd-RDKwiRGGkXj6SgqdTkM530v83y1HS6tXTX9qmtBi753kUUEUEr4IWy3rRCqH_qu9ex9opRtXTUpJDqjDXuxuWoGiNNxenW2HkJUJLTM9mfz23dujqbl8y9fGpkWO9X8sFqcXn3-yZfryzUKQRAFStd1wwB_9Hf-4PPPn_3rf_WXlhwLmRZJZCIf87Lsmz7JjLVWKXPj-NZoNo3BcohpkoKFzWZ9dHx459bxnRuH33j34UhrI2QAOnl99er04tb9u188epKl6aa3779_z1oriH7z8ZPNMFSTYmdnVo7Lq8vF_mz-1v1bd28d5tO8dzyejh48vNtvW-CQJUohTyZF72PXOqP0nbceJEpIIXb251WRC6GqUT6b7SRGmVTH6BnE19-6_bU3775z7-ju4e7tG4daiK63fQifPX1Vd8OP_-qTn_7sY9t2r15e9l3_u--9-Z__re9_cGdXR_js1flffvbJ_-tP_uovfvr5T3_z9MnT89WqZ0veDsd3bqyadrlcghB1G-ez6Y9-9_s3jve3l6txkb9evmItXz99PdsZvfGNr33-m0-k0pPJNFX67t2b2phHnz8_nM3v37n13fffuvdgfz8fhab1oT_YGf-tDx7sjKoiz_b3Zvdv7g0hvjq9Ekr8f__1X-m84sLMb-1ePH998voEUdue4kzWZ4uhtWlehGHYnL3slutqPGn7jkNwgzVaDM6rtEDg4DjLUhose7Z9r3KzuepuvHn34J1boJRtrQQ2ifGOPfPu_vzlk-f7-_OuXe-MxsKYt99583Av__lf_bKtu03XLs9WSmpk7ld1nhhv4_7RMXu_WjX7hwf_9f_l__T4sy_ee-ftTz7-9Ly5fOf-vZ29PUjUv_mTf7tdrovRyDa2q5s4DEih29QUWSBLmOwDMxABoJRfWYhAyX_vl41MTDGgQABgEigkxwjMX3FOEDlGIQRZd71D4BiUNsGFyECRIJIySd92wJAmabdaU_Bd2woh_NAzAJOH4Mk73_WMYPJMJCZGB0IBs9ApI0ihQPB1yohivK61Ca26uqPgnfNEsZhMtUlDiFk-Hrp2VFW27xGRA6-XG5MooxOTpG2zmUymxDH4ePuNt0JwMk0oxPnODgP2TcNMAkSz7opx1TedEOStpRhG89nV6evp3u76alFW4_Or5Y1bN6c7EyJeXq3KqpBCuH4AAERUWjKxFCIOziSKAZVUKkubxWrnxrHrGnYhApgs69p2NJ82y7UyqXdeZ_kw9KCkShIUEph1Yoa2N3lCzOS9RETE4CwgI7B3VmstJFKIFEknBoS4dusgAbIIgYRkJRQCAHOSFywlhIAI5CNCRBRkPUTKRqXJRm7oBED0npmJQShBiIBEgQSA0iqEyERSKuZIkSBe50yAQkzKEgC9tQgspUJlYt8LCUQAoBBZAuD1Bi8xHKNQSqBkYkGIClEgEHP0HImVjM6SdeR9CBGIdZkLgOisG4a9G7f73rqhRyBEoQ3265YoDrZJk0ordkOnTaqzfL1cC427-7tf_OpX5WRnvVmbREciREExJFnm-sG5XiV5iAGiV0L5wSqhyAfyjnwQKKXRSBGYKBJIKZBNmgXrlADFkay_hn4KqSASIrP3KCU7J4XkSBBYag3Agkmpa3vQdViHldJCAAoQMQqjYmQAloIhRkbmEEBpjHSt9gAFKDRQBCFRaqlNdINSUiKTd1pJYRIOxAQSJYJABHF9b4eASikpovcgBGoZiKRAbWSM7F1tqiIONlG6q-sYqJhMnR3arvXB5Ul6vti4EIVBFtgOzgdggSgkgzRZRhCFUE0z-BhynXQ-Fmm22NSs9fHxyDl3udyu6laA7MhuoueAF5srK6gfhtv7VV7lt45n7xzvvv_m0bffOvrue7ffuHd4fHCwXIejvVFWlmWe3X_jKA6da4ff-dab928fcAQAPLpzIKJ7-fL1733__Y9-_fjB3dtaijTV9w_2zi9Xb9y_OUnKxbq7ebTzg7du28aORvmDm_vvHh9-9937u-PRpu5jHB49eXm1bBar-s9_9un568vFanF-vvnNJ89lgsf3Zr_89Mm__J9_8vzF62cvTj_-7NGrl5cnJ-cxuHbr623frLu26RHh8mJ1sW7Jh3FVDHY4OTm9deeWMObZi5fLul2tFp7pzuG-8-0bN29Pd8freutdCBSKMmdmzFOTjpSG5bonwqM3b9nWr1eL-_cets2yWfUhhjzNtJKjyXS9Xt442BUCn372LMkMIHviGMLewcEw1H3T3zg89MTVpBqVhUSsm14LUFpuNtt-sPP55ODoKHr3wdfeXa_WRZGF4MuyYIgQWaCYTMbaGCGxKMpm0ySJiYGz3GQmoUhJkphEsmCBkKQpMGdZYowK1s0ms3q7ybK0LIvxqMoTtbszu3d8EyQ_evR8MiljdNvVUkpGprpe785n92_e6rv65Op8WlXMdPNwVwg0WoFAS7bKM47AkfM8Q8YQglYKAOp20AIFSiUFMKIAYKjbHqRsuiEQ2ECBSUv16nKVaB0ibNZ923tEdD5oVNu6D4GIgCX4QKxFlai8SLqtHc9TAOFicNb5vku0tr1VUrZtY1Ijr2HNUszKvO99BDw9uwKQNtC26SlypNgPXgrl3FAk6cnlZjYtGdCHEKLvBuc8DS64CEJIa33XDEIqoqgz7XrPTFKrwdokSxIpnQ2shG1dWWXMqBD7EJNEaQlpJpmiEkiBu8GlSsbotUYi2Gx7lKINLgK13dCHKAjjwIzC-VCW-eJisV23bW2lhKQsh87mZZ4p1KlBIR1FVSatc8tFSxzWdXu2XD6_vHryevHr09Nfvl48PVvrvYm-xhSkSb6b1avtxfnVrz754uT1whSqH3zdNv3gd3bLO9-8c3Gy2Fq7GSWrq20b3EbLzdVQX9VnZ4tPv3j-5ar59YuLX355tRJhM3hU4rs_PLwYekJ5umqi5Zenq_W6AeZI3A9DCM5Zbhu_XNePV9u2hZ1x9V984_BHD-Zv7uXv7ZR3D6dv7I8jh2bo9kZFhvy3373dNv0k1UmimqFLtKkjn26H5xebLoinr0__l2ePQ-2CICFEAO4Gq7Okty5HwcgDEAec5qMgYl7kLpAujDGckLDOOwjnp6ucsXMuybPdvd1K6Bt743mRxsGdvr46vDlXh_nF09e_-dknzz57vWm6NJUiNX3XKa3zvPov_9d_1_v-88-e911jA1xdbbSRxKQzk0klALqu0wJH01meSY2QZaNbd2737ebi7DTN5HvvvNVtVrOy8m27Nx2DgkD0-MXZ6eKqs-F8vdkM3Xrb940_Ob3M8zQw3751kE_K9bp58vjZthvOL5ej8fjWzgwAD2Zl9GT7vijzruut7Zjh6nx9_84dATGGGPohS_R4Ms7z7N4b90Fgkpib-9M3bx_-we9-89Ys_8MffuNoZ5wZKQUiR5uknzx99tPHT59-eX5xWd882P3gvTvf--5bf_S9t7_75vE3b9-IEb9Ynf7f_uW__clvnv3685PnL5fQRA0shZjPSqlU9P7oYP8f_Wffv9hs9-dzlvidb98ZHe88-s2j9cXy9s0bn__qiydPT5Iq2bxaadAucSjhzsO3E60ylS8uLxMh3751_Iff-frhJP_NTz7E6Ee52RmVN_an03G1uFxNR4U22cXp5Yefv7xxMN3f2TlHd7JYp7tzaz07f_HqXHm3fzSrxkk6xfMnFxKxX29o6KjryFuWOD842K5WSZnavkuzyrk-y5N-1YHGQKRSI1MTnDt8eMeobKTL7XKzvVxIEdOq0sa8_zvf2ywWb7_10LbN93_v989PX997543JKP_xv_3ZUHfOepVIoKCU6NfbYeiyJHGRJocz8vjgwb3_3f_hn738_MXPf_arvd29v_z1hwJUNZ9--tkXz56dsIfDg8OARhVj2204gfZiaRKjJEtkCbM9QAHMwIREzMAowRiwDrRAKYDjtesJUAIwMOG18SRGIRXECAKB6BrdeY1vB2MEIl83G1EQRAEghHBDZwo1dK1A5muirLcIAN4JRIEs02zYNoICE6ZZGolQaoHEFAGlVqqaTIzRdd14NwQbsmoEIQoUwftu25iqUCpBYKWV6-3kYB6D65peMJbjsZAiRLKDHc32hnaTFuO2Xess1yYTQl1eXBZlJRVUkzEKkWZZWqRxGJwdQm-LSWUSbbt-urdrksRTKIoqOhtD1EKmWaIYGBhRtU2jlIzee-elENE5pWVwHqVOTNY3jZZIEXwMQiflaNINg9RSJyYEh0oxhbwqhYC2rglAm6TvB5UYEgwhSik5RG0kEOF1ZY9RGi2NCcMgECBGZIRAeL0ORFCJDjakVRW6AYRkQGGS4INkRoRrt5QQIBDbzVam-bBexRCFwDg4AGYmk2Rh6L6atVNkAcRMFK47uyyFklKCQh-JIisJCOwDAKBSjIQxoBBCiRgjcgTA6INSkhiiJylBSAxDUEqTdYgITEKqa8-0MhJjFEwx-jg4BJzuH_XNBlGmWSWU9M5tV7VKR-S9iI6JOVJW7pBrhtZOj46NkKvLZQheq8QOw6gqN-tV12zHsx0kDq5Nk4QCd_Vm9_Zxv1yrRIvofN8JRBGjRI7WohDCKGapEu23NVuLSsu8DPX6Oo4PREwkUHL0YC0IBh8lsGBABiEEMQMgMJKzKAS5wExIIJQEImQgZ5mZWeL1VYmMEpVJKAKBEALJRR5CkggONvQ9IKg0RSVc0187GGLv06oi76WUHBiVQgSOjIAcAkfmyL4fhNJoNMdILjKRABE8UHBMgihKbYBRZ6UwIs3StunSqui7rm7bJFOpTgBFZ4eud44BpAohMEHr3NCHRGsHMM2KLlqd6L5z_cadL-rttivSpOuGtnHLi-XV1fKzp6_mSbK8WJxebdbd8NmTl5--OF10_ePlOsTUE9u2f2NnfO9oOqqqdCS1Eb_47Mmy96ELZ5crKUQ5G2vBo6J4_mw9SuQHX3-4WW4J2A9uudxM8uTidHEwKz54--bt-bRuexawk5TbbZMYnY-ruht-8sXj1aYuspKFoBD9th1N8t35_Pzy8rPHzxfr5t99-PLRrz_xfrDBrzd1H-Iw2DgABl7Una09uRA4TndHzrl-GN6_f9cO8a9-9pEn-tWvPl6sN0d3jquytH3oYjdW-stnJ7PRKAR_fOdGNZ-8umqyRHHgPFV92zSbbZrL9ao9unXYrjbBWyk4LyrASIzlKE_yRAuxvze7cbT7-vnJ4e6srTsbwmhUGYnDMAzWz-ZjTPTujd2h6777jbeMlifPT5NERu-SNOOA99-8E60HAinC_nSUZAlbj0DGmFGVVVXOAFKL8aiq1-uqKsjF8U4lhPQuVqMSIqVJqo1SiAIwctRCCaCd3b22a0ZVeufOTaHF0HZvvXF7bzo1qezr5v7942iHaTHxvn_r_j2AOCmq73_nPSnEYTXemU3LNC0yLYEVSBeCFKLKcwFgjFJKAUGIxCECADBmSZLlRgAKRhDorY-RCJCFsI76wZsscTZeLGoUkKb6crElEFFQjC5NzOCDEIAspRIEABLSRBVa9p3tBvA-hEgukvdBKhQhKiFi8Fk1UoncrrYSRZKaPM-8dZeLldSqafuIEClcM5eRY9v0QogOqcxU27m6c3XTRcDW2c3QW_dVPClGMiZRUuhEuz4ED1JClqQMHF3s-w6YqyRJs7TrhtG4TFJZGp0bHSI1nRuVhQ-xKFMAQI3Ht3aePb-KAMrovh7IkxSghYzOC8WuD5kxobdd2wem1jltpHPU2kEp3bZNDLG1vultWVbrdUORhSYEuVquWxeEEt5721saeinik0cvT1-vTvqaTLq9qO3gdiYFUrx5d991tu_6pml---xRDHD26NzB0KybcLltNhtnKa7bbCyynUSWAasYhn57tTQYry7Xp5er84vNJ68XzdZ1m7raF-u6mU6yJEu0kWaSDhFA528e7_zhH976-vHh24fjd2_OltvNX5xd_Obp4iefvibCk3X3yavLfFaurSMbHp2cPz5dPu_bn5-dXAxu4YMwZuni81WrdQJAlsSto6lS6uqsLVK9bnojlQteKx2YkzQ1Uo2MTNj5PnAc8lQ058PuqJoXad1uLxZWQ6wOitarw8nuSOc7sxxTpoHqoc52sqvTxaNfPtos1gFA5vHWe3tnz5ZproPjVFXfePdhmpnPPn_06MuXs8OdgDQqqkSmTd3qwM7bPElm81mSmZv740cvX5y8PFltli-fPWvXawCxN50dHuxtL1cfvHPzd771ftuuN832X_zPP-5t-Oizx0VVHBzs7-7uHB1O7989BsYvX54u6k4Y_fL5-enFJUrV9-10d7rdbH_yy0-3NngR_7M_-r4HJO9vHO-WRSGBEqPZDlWZv_fgwXRcHN_ce3j3eDTJ7h5Mv_31e7_z_hsH82lVZuNJYrQa50ma6bIyBmFR94OFl6erWVbdvnN4_9YtYvnly5cnl_X_57__8z_79eOfv3r1ky-e_vUvv4Ct3zTWBdJaoGIIsV03g_Xe-rQwu7PZ6enK19unry6a3umIzz97_eL1qcyT58_O21VtXbg82873pqOb1eJ5HQOuFpfNaqHbsFOMP3hw_De_8ebhrBIhzPJsNJk4544O9wbrBuvL0ShPzJdnF7P55J__-qNb090k0__X_-e_0mny-LePhQsigt30qVQuhuefvX7x8ZlbbTAOGil0ndQQI9TrgRRJoZxjU6RxcHYYEKUlyso0HY1Nllfz2dHN2zdu3zao2Tbnz16ywKwoDo7fZOnJu25b3zi4wYF-_YsP_-bf_tHhQfGzH__m5eOTfJS--PKLdrOuqlmz3gqIRolusIhm7-bxP_3P__EH7z589erkn_-3_-PNW3sg1OXlVVUVeVH-4q9-sVmsr05PFuv1q5dnqDl4t3p1nhUZO09EFKLE2QGEAIQggH0U17B_gSABfGCKguBakEkgAAgBJOJXQ4Nr4gxFCCRRciSpNCICAIqv0mPKJMwUnEMpMFBaFK7plFHIAExMkZ3TRl9nHrRS-1972y23RJG8lzoFYJkWUqp8vOOGjiiiEFqbfDRWRkOMwQ460Vk5Itui1AIZhUYhIqEAdINTWpkkCS4QMwkdIydF0tYtAxHKruvvv3lv6HsmvgZuIggEkAIuX5_pxIxnc-KYF6liSBITYpztHwgp87RMkqSqKrg2t6JougaB602tjfEuAlOapUIK77yQmigyCkYGiCpNbW-zspLKRIohRqFkGJxJjdQamdJRNXRuNJs425kst12ntSaIwTpEJCKptdAyWG-yPDhLAIIBruumCFJLjoQChVZESDGiknjNeCUQqeFIdC2kYWImJBLGSGZUMi0qN_TaaImMyFJIoRIhpPcDRRcJhJBAnggAkIlRKgACikAM7EVRhRgERAAFAAzAHKOLUhsAiNZd27EQEbQCQBTMgRgBJTMQRZKAUkohFUMk55RQTAAx6sSgEH5oBMpuuyl395iwms8ZY1c3OtWCWaJkJt9sKDATOD_orCpGRVfX7H1fD0fHN-fT-Xq7Huxw9OCmHRiIJ7Odvl-3y1U2Hm8vFzqtMDrXdEIJ9iyUJBspEioFIBOTQHDeOqW1AA6DRSDyAaQAQdcFAWYCHyUQh8AoGIEo8jUbPBIACnE9SEBgZgAi5uhYCmCWSnBkJhAUEK8RqYyJJOu0UtTV180w9k6rhEEKmYQYRCShRYxRSAlSCylBIApBRAJRaiUzzSFIISgGZVLQGpCD88AEMTBIBtCZid5ypMhOZXmkoBIDIKpR0XR93TvvaT6vkPWiH3SSuj7cmZWPT9YsJSeqHQIieETvIgDkqSGi5abNc1MWOUiRVcZ2lGX61tGei-Hmm7eQ4fjWnkYcFYkBzEAXhXSOXnfdUoTHr89X62612BgStw8OJ3kyn41Xda1QzebjYIfL88sffe_hzmRspLx1uJtkRTlOzs9Xfd8_ffbyrPYhxrrrzpfbdV2v-zZ4N5_O2xDW2_7733x_Xo4j0Qdv35-NyyRRPvLjFxeT3Wq6v3Py_AK9i-zRaEcEiUlGo1Qm3_i9d3YOJpL17373PhL5wOeXNQkFkhfLteuG3g29d8Jok5i9vf0fvf3e99575-cffXxxeXlxcX55cQkxzHdmI6Pev3_r1uHenb0bz19e5lmiUKHzRglyvUKJIvRd54YmTZKiyoRS41k129lVwMvFNliK5PNpuVoOSC5N1NC5alyUeeaGfnc0Iwrj0ezp01eHR7sU4rtvvXF4tKclXLy-KMrka289aOtmr8ySTOWZtINL87zK0zTRiVICIHiPgHlmtNFKCiIWQFWhhZDW2qLMZ9ORd64oC-SoUUiJZVWOkiw1Otfixt7OZFTkRfr4y1dllmght9s2y5PJqEJk27s37x8pIYP1IIVW4IauTHWVZlorFNcOSpbSEDFKGUKITChQSXmNq_jqESKu6cKIUrlAPjII4QODQhep7lwg3vY2Iq3rdlQaR4IZ624AqYbBcYhdM4CPQGQ7R6CqMrfBNpvBlOm6bpz1AEAoR9OZ9wMHSo3O86Qq0k3dLZYbEIKVZAQfIgohEc-XTWKUVioyrtcdCt10nfXxcrm1g5NagFCD91IrZh5coEghkhu8VGpapkJJawMgO-822x4FRgJlpEmMHYZcGyDsXbiO-M3LMiIIiaMsJR_qzptEKSmUEVLLLE9XG5tksg2ubnuQQibCU-xDYIGjUSkY0jJrrEuNAeB-CMvtGoHtMDBi523onQFNzC5i753MUgZ2IQ4WYgxZpaL1y4sVYexFWNYNWyjm450bR4JpejB_6_5thTEyMymSMfieumFz8fMo86tN9_Lxq8XZhhdcbwdttEJxtVqqQEkpXd2Bi-B1u_DeUkiwHJuL083BuIoRjuZZSOAXH54-vmjOu9D2HgPv6sxI2Vm7GNzGU9Ty0cVq1VmvRTYffbFcf3Z-BSyfnS231r1atY-evvrZk2cD-NfLTYd8frkNHb1zPF7026GvF-dL8K6re8G8ulpv1ptcwjxJZlIObUDPxBw52sF3K7hzNKEYEzS3j8d7ZTJY1yJ98uRES0GGV6vu5fNToULXOUSMhImRbkOjtBhn6Y9-8N692fjF5eKjz59stxsXiVy8uljkmb59-3BvNh1Pyrwqnp2d2RBWq-3R4R2AIAj2pvNEqg_eeeOtNx-09fLW8e47D--sFovPPvvya--_0_vonUt1enF5NRmN664zKumtb5t61Vrv3eX5kgCabWN7u7O74300Wt-_c1ikaapUUhazUX5jb-fq_OLe8UFh5N6ouPfwzju3Dt994-jNBzfv7E1nVTLLk53dcaYTRq63bTUeSSVTkz47ubq87J--OPv0y9eLy_rzz08uFysysnXD589f2H710998eXF1te58Y92mtxSFMWp2Y1cIcfutu307BBcEawCpMykTlc3L3vaL8_NnJ5eCxB_-4LvCyX7oD28cvDi5LDIdNehZUU2K1bYtyuTOt96CTYNbW8b4977_zu-8c-vocBaInjx99eNffPrB1x_uH-wmUm3qDQohtRZp_qvPnv_iky-iFH_x3__i2994-Bc__WJRb09fnhmJb755mI3g_NVSsG9DrOua4yBFRGRTpb5z2ahMqxFpjS6qLCOELM2Grk-LwgU6_tpdgRh98EO8fffe3fffXF5enj178vlvP1aJGE12TFk07XK6cyMM3a3j2599-mlWJd_91rtPv3jy2SfPpDHe9sG615dnktN8VPbbWgqpyxSl_s43v_EP_6P_UBN--vGT0XT0O__BD5u6_dVPf_nud7_1-a9-9ezRk-D8sB226zUApUW6qbdpYoRiGpxKE2ctAkgY73zlABaARMAklAapgBkApZAYCQEoEDChEOwDIqBQQPEaM8OAiAjAyBH4Og0hQSAAIgMK5BgpkEkTJhJAFLzUSCESR_ABr5dFTFpKciwVut5RoOtPihyvFUW22QLzMFgWGq6bUn2_OnmtgVw_-NYSIgwbne3kowoEaimVhK4dGDh4r7Wx3uVFVpXl4vKqKPNyVJXVmGLc2Zs7H7IsI4p5VoQQ-rrRJs2KbDzd2SyvTJpuLs5j79K8kEoB6GRUmDR_9uJkd3cXBSNyvanzIuu7fjSbBueNVgLBOQtao5DReaLrKihmxajZ1vObx2HwpqpMYvS1DEHIJE3yogzO9W0TInV1PZrPKBIG8tYakzhLJjGCIXhnOwdCCCU4slAyOMchIPI1oBOERGahhFCK4nXonJFBah1jZCYJiCiis0JIFkIo5OhjCIBGaeO7TjAJvDYKOJ1nSIzXlmIhlDIcWAhABIavjFdSiOA9KyF0SkMHAFIqVOK6GiikYI4gkEOAGIkJ_r2ijKJnBvb-q5lGsF91rIDjMEgtWQqpU9cPKCQ4r4ykyE3fVzu75LyRervcCo3RexRGAIpgQ3DSKNvbaveGiE6i6te1SdRicZ5Px-zCdr25OruMva83V9H3xWTH951SiW1rcq3SBpznSEICOacTdd214OAheCEU-RAjIQFzgMjIkjgKZhTMEYAIvEUAFoIYEIFDuLa8sRQYhOAACOwjE6GUAEJow3YA5iRNgRGYMHpCQK2ERGABTNR1JslBKghRRgpuUCZFYqmTMFhBjFLEwIQA1yy3EMkTRBJKUYgUGQCue8egFF9LyigKASotKRJCuKZIRiKT5VlebpYrzyCEYOIQue2cNDp6IlZfPD_L8yRKTIt023dNM3TBORcDkUl0kphE6VXdpGnadoODmJqsqYe9nXLvxrw0ed0xDWFnf3pxut6ZFGWRFpViKbjnddtnJPfHRULUrraX56s-8P23bnadHZphdbFWAp8-e_bmvQfdapVX5cnLy8t2QKVijE2IN-_eeP56MT0-mOyOf_rrFx3xnVsH23p4_XrpnL21t-sREKBtW4UMkv_5n_75X_7sw5PL9Wy3kqlYLBom1rkqy6wYjx6-_7tdt_Z1QGcFBNf6qUr3DibPn50IJbHUHkI21qdPXxnPKMV4Mn73rTden5_bbjh9ffHhl5__-tEXH9x949npRZ4kuzd2Lla9NLk0yXQyP1usqyL73W-_960P3r1qtr2L02osJT747jurk1WmYFJV27o-PNxnG_dnE-FjVaS50fO9SVN3RqlqnO_t7x4c7c7HxcM3bm8WTZpleZZlJpPAgUNqjJKiylJE_eYbt49392LnMgOvX5y9uFzevXnYNq7KUylk0_VucFVVHN_Y7QertbLtkBfZaFIhY2YMAOd5JqUGBqWklJKYU62LPB9V6Wy641yPTDf293fm1d7uLDj_xWdfIjEquHFj3yiYjCpy9sGtG7uT8bBpkjQpTPLi1fO93fmkLNIkYSJgVgKdD4CISnnvrHPWepQaGZlZaS0RB--YrhX26IkGH9vBRWYGaBofmACk96Fzbr3urjNjRoGlSIx10zFzP3gGLKpEGbFt4uBCY3uhhWfq2t5HCtZLrbd1t1qvlBTX04YsS02irpYbNzhUMgaCaxv4MPg4zMtcCCGVCj4Iid1gCZgAhtZmWdYNrm2sC2yd8xQH52KMJKRnlohSsXfXvvI4G-Uhsh2cMKiVHgZHjJerDSqRJEYpkWqZaJFmRoBaX22ZeNsMnjCEoIzpnFW5RozDQNroybio8mx5UZ9fXboQlutms677wcUYxlm-XK4zrVnAeFyJECd5VmXZsmtft06iGB9MkmkKIIMNEoEEOCZQyiN5gczUtANqxd7HSC5E37Y707lQKYOJgct8ZNmPiwpBdp4Pjt4HUgqSsLbKMwAoFGWSLi9rHU29dSjN0EYMLBwicSSnldleNUWRnb5aWxSI5uTVMgCmoJNMlpma70wOdqpt8Hulunc03Z2ZW7OkHOWQ6bNN_XS58ahsjL0MnXWvT1bzm9kK7enzi0ePTxbr-tXp-abtni-vnp1uT84aPc6UpyxRiGAQC6vTgE0z_Or5s3VLvR2er-u9sri_t79aD5N51ruhKos2koI0kNgKu1rUum4hctvScrGaTIu28QCUqWJzFXcm5d_4m99_43jv-OZBEPHCbT765PlkUrE0-wc77Phv_b0f3dybxwAKZNf2m2YzH001ohtssH3wUQq4ffPwv_yn_-idO7e3_eZ8uxkJuHt8kOtEyuh9_OCDr-3ujI9v3EkT9fEnj0ajsXX2V7953Fl3eHe_2VqpdCSuV21aZJtFVzf--N7-5mpjjGpcP0pE9KHtmw_evD-e5B-8__Dd9x7cuLG7tz8t8iTGcNqu8jQ73JsLlL2LLBRwfL5Yf_by8mpZZ-Mqm-qnr85_8vOPHn77nUXoyoPq9cX5l6_Onjx5-fTlad11nrEeWqmVtcF5F0hulxuZqu2q833TN9aFOB4V8yIdTNxcbK5OT5eXq3VH7755N3L0Pl6-rFd1i5JFlN7Bj373B-v6PAHj_CDXztn493_4_t_44Tf3dkZJlhLTth5q77_znW_sTMdt3y8W9appd6aTsjAfP37557_8MNXqt589-0_-3ve-fu_Wzz_6ZHK8GxN5tfWTt-Z__i9_jj54LVcXy2qSu94qjfWqlchSondEwDLRKChTBkLwzksl06pKs4RZBsYQ-Bvf-bZItO36008fd_U2BvrGd76vJ3mzbt77xrfPn3-Zp_lqvbpcbf6r__0_--Kzx3meV3uT05evt5fr5Wqb5VW77nbn06uzq2xUVdXsH_yn_-h3vvd1RP740y__9f_wp8_Ozl6fLB5_8qnt-s9_89HqfAnMN-8_2NZbJi6L0fybbw5Xa9u2rq6ZmaVEgBiihPEuKIHXyq3rdTwgqoSjB4rIDIEEM39lFJJIBCA4BBTi-h0gkNcFgRiBGQQSs9AaBVIgBGBgIRVCZB8oBvJRKEkxIjAQSa0oRoiQ5BV719Z1dD4pS2aOISptEDiEANErpUgpgWhMgii7xVU5HQ-9TUaVQzDVRFTzNC_6vg2ekDkMloiEVEPbkQ_bVcPsk6xAgNnOfpopY8zhnVvIvuv7NC-2m00xGrVNU4zH1e5OjLBarKQCBADiEEJbdzZEoZXOEmP0ZrM1KBdXa4jBeUqzNEnT7Xad5_kwdFJnBCyUkloH74REjpxPxuP5PKAiphhiMZqE4IkRmMvxvNms-qZWJpFKjObTdlVzjMBkTEoxaqOlAIAYfTBJkhSZwGstAEUfpBQA1yGdiFIgspAiuMgoUEohlQBgIqET8h6ElIl0fY8MQgoiJu-AABlQoslHQFZwUFp754IdKILUEhjYRaU1eY8KyXshJUhJLgICRwJg8j4bja7HDoIBiAiAo0MpKUSZptcO28gBHcs0ua4iAJPWGohUkrBz7IlBgFYC0VuPQqBEpQV5p6V2XYc6kdooFNPZDiLqRAXXSiGHtkvKDBB875AdkI1Dm5RFMp4BByGZIw2D3dm_0Q_brt6y7bJE2W4A5hijNFIQ2W2jJSAIgai0BiG9c0wAkZEoWstMJAQwJUUSnccYpQAhObqALCg6RJJCxRAEAAoQgEx03Q7XSgsApkAuSC3w3yOQkrwAQOIQrBdKCxTXVwOsR6WIGYkZIjsrpJbKCGBoz4TIUAnUEpX01qFACIQSQ9OC0kwkjOJIDAEFMsL1HUrEMsuurR3RtoiKg9faRM8Uok4k9EO3Ws8nk2o0Pr9cSKmUVkJilOADaJ06Nxzvz7-4OO0dDL1NjbEhek9CawKInrwPQpshBoGqyIyzAYSYjrSRxjeDFGJnlO9M8ls740QJhWrduc0y3N3def_-jk5UatKnLy6klGdXm8k4D4PnCLdu75IS2-XW2f7qqu_67Td_-DXnZE1x6O1f__hXXzx_9bOff_bbpy9Am6fPzp-fr777nfeePX3-xeOTi6tNjKFvu0-fPHv2_NXVcjOfjpFBstjfn7379r2-bZu1LxJTVEldN-PpFACFEOvzE9fWiRZhY93glBGO4K39B10c-oGmuztVpheL-v6to29__31m9Xvf-e5AfZDKlHmk8PTxifOxzLLxfNJ0tmn83_7Dr_3Fn_1idblcLNb33tgHpsePv1gOdjdJ_ot__LcO9vbstvknf_y7Pvht3aMQIQoW4KMP3t-5eSxifPjO_cX51fHe_sGtnXbbai2HIayv6sXpRXSBfTg6PvZDQ64fVWPbdkqJSVUC02LVzMfV_vHBdru9ub9fr64ulrUC2DT9nTsHs-nYR8gzk2ZmVuazcTXfm9rBJ1IET4JBSaWEiBSLPC2LLMuMlnJc5kg8HlVuaIvU7O_OJcLudNqu28dfPmtXzYM37r33_sO96SQBuHljvyrSnXE1DHY-HwkjvO0t4t2DfaMUcQze-eis8_Lfc5C7znoX0jwjYiaWApkhRu9CyFMT6ZqCyxHABrI-DD5EJuuiAGCh-s4rLaXAq1WzbkIzuMHGEAJLRCmsjTqXV4uh9Q6QB-tDhPWqExKi9xApEhltkkyzgDRJpJIUo3V-sE5KYdIkeJ8aY_uhLNJUp0YZPzhEOQzWWpumWfTxel5ue88ggoh9P7St73onAJz3znqjlR9C0zoQsrdDJLY-gsA8NUOIFMg6CwwUgvOBIoGAyThvemcDdd4KBKHlZGeMgjhS3_WZzup1q2WiUwlBG0CjVAwwn1WutzH4yaxAgduu7waXZIlJZCokEwQXVUTJmKns9izrLIWt72sL3sfWohHr3isycdP7tg_1QIB26IKN0dvgQjdY6-Ojp8-DcN2mTlIVM2ShBjsku5NJPtt02_G4KjIznhZ7R_P5jZ3prCIlSYjbbxzqAt5-81Y1wrvv707GqaWYlOnRnel8b7x3e6w7-N4Hd6tU39irbh7kh6UGoq7vAXjthlfLbZ3g0_PtTx6_-h8-ffb81fqj56enm6YN4cOPnnofr7b1ZtPp3b0Xn16uTzaBcVIUtl6320Y6F5p6s1iw68C3nbcvzjcEsun6YmdcjBIj5E416jtbjdKdUX56shxciH5wIS6XXZonJk05ur4LzXKQFMmFO0dHJ4uzLNHdpt27MXv4xq23j3beeuPwaD6KwatMv7paXIh4-fSib_p62Rutvv7BnbOTxaunr07PL_1gN01zcDCVxmzXq7Zt7t6-NynT-Wg8Gxe_9_3vv3r98k9-_nMg90e_892H9266vnt1tdqZz2yIV8tFxvHx6erZq1dpllfzyWbb9bY_OJyfPjtjIQCgd1YnRipZjYqH79w8efw62ODIZUa_987tvd2qqsa9bZrWMaoQIhE577umtdaHgJ5E09tmcGeb-t_8-W-ePD0Z76TLTfvy9dUnj8627E_ONs-fX55drJ99eXF5dvn69dXmqm1WTd-7rnMmz7ebNfjQbdtJkZajTBOPp_OjO3dcvZY6GhRlYrRQV6vOD_Zb77493Z1-cO_OjXszcrzetnv3p7MH87vvHNkQNIjl85PFyWKkjTLyH_7g67_z7oOd2WS9bj8_vfzxLz7-iw8_ff5itXswq4qkt67vBxZ87949CvTf_Hd_qpx7_72Hb946vn_n6K27t__6t5_--LMnTd-enlwpEZ789BG4PkTfNj0Qe-d8a9lbARi7FpWOIUQprg-4yVqTZyREMi6zMossi2l1dHg0zYvJ_vjy5NWXP_2lXW-m0zwrRibLrIsPv_71z37-s8vnJ3menp0u_4__5__tX_3Zj89fn8sk-fVf_uzFk2fIODnYh94e3rt1_uq5EOk7v_vdH33jvVu3Dp48ff3y_PL5yeu3v_f11eL85eOnV6cXIYSm3mZldufNt6yW3gadaoRoLxdpkW3PLhUAAEYiFAKBEW6_C8DXllAMkWNAKTCvGBiCR2C2UQgmZkQJApmv484AgMQgtYJr8gwxAyEzC0kgVJITAoG4NpsAYPABIgstKDIqgSggBqEUBAAFijlERmCUmlmiVsIkEENwQWnRt50QKhmNGKRURhjFMRKBMunkxg3bNmDKNM-EkCjF5uIchZhMZn3fJknWDUNWZKk2Aqkoimaw0_m8brrZfJRnBUDUqdlsagEAzOvFihnKshiGvt60Z0-f3ri539aNGwajDHCQQnqC2dFxVmTbbT3NStt3gBwZIrsYIoIE8l3f2s6S8ygw-EjsEJmcK3cPZGJ0WgxN062Ws_19N9hiVDXrFUrlbTdsW0RO8kJniW87aRLggAK9c9G5yBxtLzj6wUmNUql2uyVmQJKIIbg4DFqpGDwIMlnp4ToWYpztdJoLBEAR_SBQMxAjc2CGiMQQBokClRi6kO3tSxbDZqGkiM6yFEIqUCJ6H0OUWghEoaTte7AOy4pDEAhggzCSrCel9Hzu60ahEFp72wsBEhQoGUOQJo22FwI4osorjpYIOAbmiElCROg9xwgyASkAkb0TiMigi8q1jdJCqdRaGj-4211tsr2j3RvHknG7Wdim6etaIOkig0C-6bIqjdZhOdWj3cTo1eUpDX3wfrp_i5Svm_WwXmcmcW2nlLDkRSIzk4a2BaboHQopExU4hmGgYEFpFBqVAi04BLZOpSYSUNuJEKQWwQbUkpmQgYLHEJEiIFMEoQwgRUShEw5BCE3OoreoJAckZJWnKFUYOg5OpRmTYCAQgp1jJSFNkAV3jZZCJmkglIwcBQUCJUlLlZeurqUIGCMYExmESYgIQbD3iCCUIo7UOZkIDoRJQiiYQGqUhL732WQCDIN317Y3jOxivP3db5HM16tNniRZrmwAIJlotb83t4MXAP3QsQ-T-TjPjFFJ0zZJIkdpemtv3vSOiRKjZ7kUISZJEsknuaryRIcohJIKdydVM_QAPLQhyYkcnC23F-tOKKGAAzEoMFovzhdFmZVZ4QMbhSRCIky9bX__D77zs59_9vr16_l03NR9F7vnL87qwIv1elyNg5AUoJwVozxdLjbBud293SRRfhj6TQ0ERqfVuLhxvDuu0vV6UCBOl6vXpwunArMiFxKNO9Py_GSpMqG0yJPs2ZOLfGySNCGGZuu0Ni66Isl2Dqd7k7Kc5J9_-mzx-lwmKSFQpNa2wcV8nI6qad13e7M5MO-W2RDC-mKlWO7tzy9PTl-cXB4d7ZTzIs9GVVF88xsPhQMGjpYCMWBMpUyn6dCGl8_Pvv7BnV__9vHL50ul4Z1377Vtt9r2T798cXA4T43OklJAePb81XsfvN01PSIKCRKg3rajcRWYVsuNHYb5fDabjtbLDdvwYlXP5oU2ibMuMcbFOCnLYRikEkaZuq4RkFAQBYEYhYiBsjQZ-kEq3ay3Amhnb9a2_Xw6HlfFzds3Ll-drepWSxBSgwIgurEzz4zZGVfWDuOqSJUBCNuuBcCbh3sUSAJ4Ct4HpSUixMh92wGKCBBDBESljbc2TxOtVYyxHrb707m1RBBtpKGPbQiDp00_XCzqTeOVhqAxeByc3_bttnZN16MQLtK0yrbbXiHGwM5FBggxIHLfOZUqkxrb223d5kUqpOybVgtUJlFKJEKlqRx6a5IMIUqVoCRkAIqIqFD6GAjAWmc7T0gILJXQMmEgrXSIxEIy-WuGhtEqBpJCJwa11KjVdX5wu2mU0UwkhMxTzQCIIACVlACAUmgltWREdbGuq1EJ3olMd320Qx9JSgn9EIwyfegTrStlPGDnu6rMgGm9bbVSZ8tlkpm-dYwxBO6agaWwwZ13w1ioVGk1ngd0bl0rtJ0PMtXooes2LfSVmHETTI4kMPggJEihXTeMxol37H3kMHS9T_M0NakwoqwKFzjVSiVCq_Ls8mKUjyTj7t7UOj-0Q91v9vfG7WIQBjSkL9rzezv7xdFku6izQUDkpMq0UcvW7u-Wlyer0SgFrbqmQyM2F6uQq6zIOgq7O-OF2zKo5csL8hFYytIMvQ_e2dp1vU1lvjcts8Kcny09MEpR6rycTbR0XWuXZ8t-USvBWhFpte16CHo2KU2ZLBehmJjZZFJl7AYXfVRCFkW-6LpSFyF68jQuDTCve--HITP6wb13fvPJ5yMTUCWjwlTjpKvrt967f_byajSp-sAf_vSTbFRs6-745s4HD-9urL26PH_25Wk5zqMLfd10IUopZtPR-fmiEOZr33pvWJ9__xvf8lrkkv7NLx_91__J33VMTdecLze97R_cvvXFk2dM8unrVzFy8HKx2Ty8e-fVy_Nkkndtt1ksk9QIlSS5QpEtV4sbxzcvTy8nWX54MDImaerVZDKRSkxGqYs4uEFKxYFPL-v9WfXw7r6U8cXJat10Bzf3X7--mozzjz95Qr3f9h1WycXF0qhks26FVFfL1ba5mpbTvhtG47SpGwqojBmPq8XFQgskZAGy7-PxrX1kJoPbzXboauGkYF_o4uDgsLFDOUrH06lhxlThYM_rumttH_j-O7cV84tnz2MQTDhSybgo__j339m_sW-YZZbIgD___Iv_6Se_vn9z_-13Hnz04Wf_4B_-oWi9DfAXv_nwn_zxH0bnfvHRlwJxdzZe975xYbldfPzpZx__9sveB9TJaJp1q2Z9tUqzTGYqDt5ap5Sq9qr1q8sIKJWgIabj3K1bUybkARit9Uff-qa9etU473r_B3_7R81y63t3fnH-_JNPVegFi9__p_-g2-Bf_Zs_f_uDd-r14sUnT_aPD9I0_9Hf_n3m7smjl_O9-ecffnLx8oQARrOp0OLsy2dJVVycNT_40Q_-43_yd7jrFk3705_81lLc2sG2oV5fXL46MQjWDcSYpeP53WNjkna77VebLFFA8eLkTCKBhOgJpDRZybGTMNsDGwERBSMxCmQfIEmuF_rX6BgGBCKhzTUOEZkkCg4BBFJkFAjMFAMyCRRMUSh1DTpElNeUeryOizAhEVG4hhNyiAiIAgRf09wUCgFCmCqPIUqtOUQWiBSlkMpkwAGlCs7FEAFY60xnmVASAGazuRISAaQ2IQSlE--sNjoGL4SMgbyPEFlI9M4xQzkaZUUmUNjeXpxdjUYjjhGIdZpokw62y_KqXm6Cp3Iy1loRIcdQVBNAobNMCN33AzLmeeq8894xh-2mrYrK2SHPMkRRr9qjOzcDRUY0adquN0ILjDTeO2zarpqMbVdvl-tqMnX9kGQj29dpUQEyEbmuM3nZd61OdAgBgaeznWazVUoCE3kHRIQspUJkYsJrWqgyyKTThEOMIcZAqJWUClFCjMggq5x8UCblwQmJgjkycSAhGELE6JkIlKbIMsmjDxy8UIggIhEFL74SgTnga8kYgZTX4EshUEghpUBmZEKlhUAmAiKgKPh6h6k4EEjkGJgBEYQx0XshGAQCCGIAARwiEjMxCgkSgQJGQkahUAjkSMgslLZtZ_LEDl2alcxsI7WbWiIZragjnRZCBLfZCIl-aEyak0TvrUmMkQDBzXYOfPCR2XddliQQnRZCMsSh0yiU0YTsrWNAUAaAKQQlNMVAINh7KSQ4T9bLPItDL7VgHxgA41fdGIj8VdyGmAVKicQRghUgCQCIlTZMBABSC8FAEVSSXoNQaRiu50XXYlcEAB-QowIkZyGQ0AqlCG6QiZFFGjmyYCVQIglAioQgQCsGBoUMEYVgRIGMQoALzJEZQCggEsYAklTgu05nI2BiCsisjGLJm1Vd7B9KgRTs2eXa936yMwK-Pg5GBq6KPMQ4dD56Ho8qRmltZITB-TRLGcGFyBQTrVdNi5KVlHEIEUAKkaeJEJxqVEJqlIKkFpnSWaLU3k6Wp0mSqMXWjotkNh9_-eQM2N-5eRAHu9n2X_vWmwezibeeArw8O6mdBYBHT89-95tvzPfGj15cKK2JMZJzkder7eDstmkioqpKk2VZlmRFWo0zAups_-Xjk7RIohLAUJTF3_jm-5PSHB7vbdrWh6CMWKzqdvBZoa95mhcX64CUZkk2So4fHDnr3bo5O7149uKs3tY-RlBATF1nR5PSxbBZtz4QIA6tK2a5lAko_cHf-sH-xCwuVtum3rsxNVLP9yY_-P573oWLxVInyXw2ysvk6vxif28HY1itNl8-ez1OFBP8vR99S2j57pu37NALEtb2s2nVtvbdd-4_ON5drxutsx_-4GuJEJNJubxaNc3w7jv3kWG52RxMx5P5iJGTrMjyZP9gNtsdC-K8SPb358Ngb-xPAKmpm82mAWCCaKSk4CfTQgnpncvTxA8uUarKsrJKy1EhFRqtbGfv3z4MXe-crco8eFfkKbDf35ne2J1NyhIxCBSTceVs_2xzdTydj4oSmRSIyBSiRwClNLK8xhl7BhToAnd9L5RSSgJCahLnfJIkWkofY90Og6feeetj7-O6sS4GkHyxbKyDgenicrtatJFDJAaJbWvdEJSSQESRhUQUSIKVlkJIJdAO1sVYb9fUem00yusnGQupmeM0L1rnVSIpAgEDUhiiklII6Z0nBk_kQvQ-gBRDGJpmaJ3tY4gRInAIEZGc7YVE4WNWZDFwWqV955jA-9g1bZ5nQgoiEhJRcogRhZ5O8jxNIoF3LitS5DhYi8yb9SorssHG3jo32M4OOkkik7cuzY0AbLqBKLTWsqf1soueQJA2ZpSmQ-dWy3qI1ocgNWqAxIDOJCEFYV3dijRgWVFEHKhQKRg99KGSeVFmqJCklKm2g0tMigjOkY_MUhajMq1S5zxKiiEOfRTIXR2FMBdXl6Y0xFal3HdN470WYDJx-eK17dz-3qTMyuPRbllUsaeD3SqrSs8cKzO-UaVK9cFm82J6Y7Tt-jPfc4QeYpbp56dnbj28enTuhtBcdZdX5663jNDXw7Dt_RDZxyTTdnPlvN9uWocREnBEkcJyuRqc370x29-f7Ozn5aQazWbFZB6CePPdw8Ro9l7pZHdeRAzrlV2vB2NMMkqztFh1HmPY1q0SYjwuLy43b90_fLy4qtLcZPDg7s7dW3uTIt3dHWmAndlu0w6oq5dn548_f8EYfFtLo3ZujT_69PGnnz9v2q2pyvlstrpaK6VvzA_m4yLRZpolP_zu1x_s7-0d7FezuS5N7-0P331omZVW6-1mYd3HXzz78IunTRc-evR8iIg6WW2302ry4uTqW9-4V4yqx1-cTXdH1gWUSiaJH_xkOlYab-zu7OxNUymavhfKBB9YpY-fvvri5emnn7x49OS5t2EIofPw2dPTH__00V__-klgevr87ONPTlaXa8esy-yLL05lac5fX_oYwAgC3KyXg40uRKWS0A_BWZ0lRTm5PF9oVIk2v_M3v8fEO8c7w9BerZp2u5QxUmBjzOGNG3mW7h7uHOzM8zxpXUsRV30XU-UFV3vZ_o299eurzcVSDJyy-bt_8MGPvvfOD777dpLlvR1a7f_iLz78F__2Zx89erIzn6o0--STR2EIgdx2XV8tFt9-_21E-fzkMqnGFsKHnz66XNV__emjv_yrX9WdB6ldJKFlWw9D22oJUsmhab11GKNSemhdjOwZhMBiPOrXG0TuO-8jzHfm7__h71x-9FFTd8zijTffCD4gqmcffbxdLLvFZW6YlSGsFmcXF69fbbdXm9XS6Px_9Z_-_fnu1DP_2Z_--OD2zZ_85U-7duiHYffwoMzyF18-2d3fYy__xt__gz_-4x9evji9WHf_zf_9vy0r5ES_ePSk26ybzdYHF2Ic7ez-8Ec_XF71f_j3f7-3_uWjpxK4ms_6oYvBBh8EEgNIJRlASJRQTEEIEAI1YojMhMQsNXOESKAUEwEwUBAoUAhm5shCSIbr8D-iAIqEAkEgM6AQFFkoSSFcw-aBIgiI3n01XgBgT9cJcA5Rp8YNPUopQbCASMyAWhuMkWPkSEwkZBK9jc6jkAwkTaakikxpkW9XG2ujzpKyLBGlUggR_OBt10uliRmFDM4qrZTk3g4xgkkzAuqbbrPe-BCk1ggEIIxReVF6521v18v1zsE-IIxn4-X5YrKzKyRGNwTmLCuJYlaWQ92rRLmmWS1rnUqpzOXpxWgyzovUu4AIaZY2TYcMaZXHEIMdgo-jg1tt2zJ5rQwyCUTvnRBosqJrO0YM1pokcX2vjfaDraqy2Wz7oUOBwFElad-2SWbsMPjopTYUowBAvJ7QiBiCVAkIQTFKIWNkAtYmiSHmo7EdeqE1eQ-AHEkahT4gR4gslcDrA6s8t11TTubso3dOICKRVJrJS2UwkmAWQvB1viuSTtIwOGlkoIgAcL2VysoYAnBUWkEIAEzX4FkUIBCYOHwVcgkxohTEhIBCKuRr8TEIrZlJSsUUkJE5AkohMPoAzDLJus0yLcau64rZzKSyKKu-7gQFJQR7KxAJ0Q-dEMJ3fTrZJyG3q6skTaJ1wmhmigJd0yZJQs5GG5LUxLZHKUAjCB0RYwjMkQMIpRGF0lIZiRTYeyUkIzGzYJAogg9CSybi6y1xDBy-astwjCAQrz29zNelYCEAUFAgBAJiwUjRE0UpFRBhDFJoIhYCmVkgITEiYggQCI1mUIwAyLIoUSUMjMELBg5RAIIEIRULIY0kGxhYJiYMg9aKKQIFkAhSS6kYiGMk7xGBvGNg-Mp_HDBGtrZeLBBgnOSzcbVerrrNlqTSSd60nRY4G5fRRghRGL3cNibV2kiK3A9WaO04EkCRa-dj2wcKiFIhigicKsU-BubLVW0JslQj8EBRGU4UN4Pddt24LO7e2KVIudFHh_PZuOraXiKZLJ2abFKmtreBnErUrZt31l0zLvP5wZ4y5uEb92WRklHLpr9zMDVS9Ms1OKcQwcfz09PV5SYQz-azvd35uMyCi7f2Z-OqsEM_Ks3F5dWLJ-eZwTfuHFy9WvnBf-N331ifLFMhPeDdB0cUcT4fH94-rDe1Eapeb28c7dfbVicqBnbOHd-6IRCllNqoobfz-Wi2My8yPXRdaWS7rpvlcvPyfHW1vXfv5r1374Eb7j14EBwLKU2MFOLb92-s6_XjFyf1elv325cvL1d1_8HXHh7v79y_d9Q5WxXpuEwPZ-ODg-lHL169dXv_xsHerMyB6OhorxznMjIS3Lt5cGNnZ29S3T7Y0UrmSl1t1mWW7B0e9k1LPsYQjVFEoJTkSEAgibq6m88mfTsIIbNEl3kWnFNCZkmChJkW851xKlXXtolR1Tjfm09Cb-_f2k8l9G0nmYniKM_HZXF1uX7_zXtVnti-1UruzycSwChxNJ8pQCkFAobofQwhkk60RIhEfdcHJh-od3FwjpgRBRMrJZlZSREjC4E-xGXdscCIIii8WDYewSHUtQ0o7GC71nbOAqKU0hE76yngdJoKxrYdEBBZoJbzadp2PlgP0SICSaQhQoxSSmsdSUmRlFZKiCjAOxd98EAxhGEYlJJGSxdd8FQ3nY_R--C9o2ssHLCzfb3pq2K03q4oEgiOngfnn3SbHE2WJfW2RkQfQrPtxqNCKWmtrZteSQxERZrVXW8H1zmLSGliovNpmhIiM-RJMrjoCbTR5TS7ulhHHyKzkEiMm-0Qo62KDADarivLZFaW7bbxgc-vVjo3SWa8jSG4oR8iEBK1bTeq0vWq7jvbbFpsGyAvJYUYB7ZCC1Tcht5SsNYRExMDQYghUnS9lToZBs8OgveJSChCZhREkkAh9N26jZ7Xp8tEGOiDisINdn1Z7x3O79w9bHsOFDs_2DA0w_LkYrV1lkw8uzg_e7H0AM-eXzbBP3_6erlsYoRVU0cmJ4VztphMEHugWG8bv_U0OBEE-4AExmid6dSkPABZPzgfPfXtENZDlibC-e6qXrxYrC62623n-1iWKYd4cLDLCkiKHoW2kEg5L1QfQ67U0HupEpB8fDD72uH07Xv7t2_sf_jbz-Z7kw-fX70xn4_HmWs60AJYFKMqLfK-Hs7X28vL1bLeeEcBaf_OXmCR5mlisqefPtccYqS9nT2IttBJmRc_-M7b77_z5r3jvTs3j-fjIk3En_z6V3_921-XMr17fKyVOV1c_urTxy8vl3WMxACMaZ7u781RkB-cMeaf_kc_fOfmkQ90ebGeHYy8cwRMgGWS7czGs8k4SRLPIQ7u5OzyJx9_srcz7-xQd02zHZTSs2l55_aNxbbZ2ZsczNXz51d9XWuD67rJ8-TNd48mVXK-3F5cLYSOVxfntrUcuG27CCQFsuOyKiT7brESLAlkVk3TNLl192Dv1vjR45PzVxd9uxk6t12sAELT-2wyns2mB7cOpkezclSery5fn11dbfr3vn3v9pu3P_3lx8jQtH2zaMDRTln-3T_8vd__0dvz-ShKvlqs_n__7k8__PTJL3775dmmvf3w5tvvP-w3dVIao_XialOlxdfef3jzYPfsdFGVpSnM__hnP72sN588-vLR85PT03MUIiogEAQUmV03iOhj7_qVTarcjJLde3fdUAtlnHN5nisQtm6ZYlqN8_Hk8PbRznx-8sUXV3X75rvv3XlwO8-z6PtXXz6tL65Ct2E7-AAoq4c_eO_00dNtWyeJRla__x_-0Wa7lUY_e_7i3hsPv_z8y1FZtOtVksDd-_eePHoqdfZ7f_xH77577_333hzvpP_uLz_6-c9--3t__G3b1afPT4a69W1rrY0g8mry1u99a3G13t2bgxZ__T_9mR-sStXmctlu1xSDBBBSMAoWIoSYaCFhNAMBwIjMwMA-KClRG6IIAFIKIRFiFIjILAQSAPMS2SB-tdwHZgT4qg8c4_WugBgAGK5T4ExCSqDrBT0LbaQQTAEQkRElRmuFVgDIiNEzquvDUXSDVcYonbqhl1qbokDBiBisBQF923Zdn4-q0XzSrrYoBCIsL1dD2-dlppTxzjKDMDoECwAglDYJ8DXAVIbBmlQDQ9c0MQRt9ND1m8VqebVMsxSBY4ypUZPZuO9skiQghE71eHceKbIQeWqadjCZGbrOGFOOstWyPjw8aJq-zKtALKXcblZZkveD1ZlJ8rxrahAMUulEh-DZ-_F03ra1SZJklKMQgUKSpsw-ei-MohiNyYhicD7NUmSiGL1zSouhaUySeh-ZotKamREQAAQCAAQfRJIACIoehZBKItG1dFZIiUIwRSRCKYWSHAMyU_BCgFSaAiEyCBVskIkO3iIy81ffmEAGAvIOmVF-RfxkJbTRwfbITD4IIQEAmFEoosjBK0AgCiECMypJkVAAeYcgrn8b0TtAoAiMLAVwJCBWSQoMDFGwkErFGJlICMUhAErvhmRSDU2bT8e23ZTjiRAq9FbnRd-0yBFTw8zIQD6q1Liumd16IIiEin6w5GI13Y9-8NEPq22SpkiMQATRWSeEBKmuv02JwphECiMkAwJEEQYPxNERIWG8PqYXFL0QCDGyEOy9YEahABgoQiSlFIcAIUJgIQUzM7BItJQ6hnB9y0RnBUpkZmKhFYeg04yuDdwqQRDgwjXan0JEo1EIBkAUAIIpcowixtj31xsbioRaCymFEhQjRY-I5EhIuO4gfBW3AwRgFMjEwARKQgzRe1WUeD2uIU_OWe8GT1JgMSmC8wIFhxAjuN6leeID1Z3rrQuBtZDdYKXW_eD6IUSQbgjBB0KUQoOMUqCKMBqnfe9sjKtthwpWm3axaXUuykJLKU2ifaBcq0KJ1JhEJyGG2e70jeN9Zvnw_t3gHXk3HVWDj3mSuBBOLpbs3MVic7ms7x3Mv_7G0d_-xsMPHt68vze_u7e38cOidUViKEDf2HXdgZGAvFg3JjH74-lPP346zpMbt24o4sSo6Wz8_GRRSXz_nQerbW-yNNXptvdSpOsmvHnn0LGc7czCut9erSXH5cVl23WzSVHmhWAOdmDy16kScoQCqjwjIWSMq6uVH9xoVHKktx4-jBQ_f3r-5oPjWwc7b92_WZmkD4E1K5Wul93VYrU3HS-X9d__o---cetAMmSp7Jru4nKzPx0Bxe1qy5G_cffWznS6vzNVgufTMtVyNipGoyoREZGqshiVGRGXiZmNqhu78yxNb85n4yL98uS0aQfBPBmXQEzEsypv2zZGvli2t26Mjw_nWWKis0arPEvKPKvKfDYZTUeVgKi1mo5HzsfcyKODnXGenl4sDnbnx2_cH-rGeTcq02---3BcZuz8KE_HZYLMiISETEzA3nkiJiBr_XXPjCMEIqEESNF0lhh8iIiYpIaBm7pVSkkhUaBUwvkojNn21ro4hFh31ktcbrvauidn5xBlBDZSSimFEEmupcSdSQ4heh9RIiIwspRYN0PXuhADCREtRWI7-Ajshp5Btl2XKD0EF6zte680ehfrekChKHrnQgjUh1DXrSdyLjjrmGHonVTKaB0iSGQ3NMRExAyYKikVJn3USnd1T8TOeQbQSrDnRCudyFGVVlVeL_okM0Yr56wA6QNJlCGS0VoJ1nkSIikptEm7punbAErkRYYEQ90RR4TonEclBxuMMtttNy4yTyFyHChI1FNtTK4Lnbjgi1He9gM47jtLigN5baIQHAI6gIg49JZ9RC0jsBIqMClA21sptHOe2QujmAOT1xp3jkrbDwe3dxevlwqw3rZd56TSMVKeGKOSq5fbxGTdsL66OolKLi42y3XtwZ-_uDh7fb56vbbWXjxari5WXdu_-PxVax2zP338ant2ScDO227TC6m2i3XvQ1_X8-OHw8klCE6qIsuz8XycmQwMmEzVtZNSTYtUKEiLkTY82ZuYPE8ylRaZTFVWJBLRGAzMfdf1zuUmnLxc3Tvaf-NofrQ3Ig5_-fnFTMnppLp1tDOdFs1FfX20-epi89nz87ffuiM9He9PDnYniTZHR8eSeCD35PmLjz9-Xo0yqNR8b_T8xWuj4Ox0iYSusSFQvdh87YO3v_ONr4Vhm4n45vGN_-BH375_72Y9dM9OLl6cn_Yu_ss__dO1t_vj_cPx3g-__raN_icff_Zv_-LDR8_OAiRayq7pgHG93X72-bPM4I3dySjLd9Lki9fLL16e7ozHeaoba6u8vLk_L8os06Lt-6ODg01dWzsUmX5466ZAunfveGc8LjKzMxnd2J1eLrfPTy6abf_rj16cX6y3wd7aG3_w3oNm1fZNsM4_-vz1dtusl267WOdacw_RukjomnY8GUupIIJWshxPdo_mpgCk2Ao6e7nsuloKGDp2A03m5f6N-c7ezt7-7jAMy4vNxenV5eV60zSjqizSbPF68fKzL4kh9p6C_9E33_i977z3wdff1oa2Q__Zi2f_6k9_9tGnL9s2zg72tREPPnirHKWf_-qTF6dXHZDW6m_-_je_8dYbZZa9fPZ6Z2d-1TX_j__3v_ACL5dNb13vYt80SskwxGZbh87ark0YswRRKkylSROV6O5qCYH6GBExT1Niz86xMcR4fHyMwK-fPbm8XP3Oj36UKlEU6WKx_PSnH9qu7uoeySGaYjp76w--uXhVP_nyqdJw6823EMS4GEWSL548QSV-89e_4hDAu_PX5zT0aZbOD3f-4X_899tmeXRw-PHPPvztR89enlwkBQz98PlvvugHy9ETw-zokFk-vHfr4vnLtCjnh9Mf_-s_IxeSVKGQ0VlmEhLS0QiAUBvUUimhEBCOHwKzQEnI6EkKYAqYpCA1xYhCfEV_jwEiisRcl05FiEKJCCxQACITg7gGyxMyU0SRFTEEvCaYpEnwAaUAHwCVTjUQUCCVpb6zJk981xMKBJBZ5j2ZLBNSxMACQahkqFuTJwgYYhAIIskECmYGoXRVJUkZgw-RpvMdBogkm7aWItFaBSJljJTYtV2SJGmRUowhxKIoislk6FulNCB479MsE9FnedrUbWISQDZp7rqOGXfns6vlEoSUUtTLq-t_IKGEUSrNkhhj27auD2kq29bt7s2dDwqlDXazWhRFKZRZnJ3vHu27rm3qlevW2fhAZkWaZUYKIbFdraSQSVUoo3w7tF1H3rmmqebTZnHhh5DlCSgJkZI83yyXUmtvW8ExOk-RhBTBBxAAROQDxSCMRkSZ6GB9GHqZJBycEImQGJmT6dz1DTIOV1emyil6Zo5NIwGEQJSIUhJImZWA2jqXT6bR1t1yIa9DLZFACGASLAm8TPMwdBSDyhNgQV-VRpwQApLUTHZd34IPxITkhTARiABkWVAIEij2ThQVB08hSK2iJ2GkQIzWCYoshMjKYAdBZHQaKTKwZGaWIBCVss6borqeixy9-145m9brdn12EYcO_aDzwlRpt2l8U2sNbLLpg7cQiosvP0mKxG6abDo3O5XbtO16lcQh-BC9M8Y43wspA4KZTmzboI_kQ7U77TYrcgGNis4KBoqRpBAEqBXHAMwQHQpmH9kRIscYQCDGCDEiM17TT4lASkIRh4BFJpWJwSOx4AhSc2BEQiVjW18XLQgESMFMiBoh8mAFAgrkPGdlODAjJnuHcbDeDsL1CMQCCIAi6GoUI4NgYgDvEZk9CSKUQDECCFBSJjkAhK5Gk7CPMk8hMMWolBDShEBSG1QyAKTV3NtQjEdJNQqeqtHYdk4gTCYlEYVIzgViun2wc7HYzmYFIofIaWruzMeDjSqRGjBJZGbkw3du1M_OKZJMZHCWkDFGgSJ6n5l0Mi-LIpce1pstBXcdzLtz5zDP09AN3eBI4o3dMVC8Ot9um05q2UcXZGLb9vX5ou6Hs8sFy1KnelzkpxcXR0f7RMRCTNLk2p2UV0oE8ZsPH1fj_NatG91qu-3bRy9PQIq9ydiY_Oh4TxCsY196eHj_mBVGH-v1ukpSjwIcnSyb44PpctW9uLh8-ODeyenpbDpat3WZmL3ZpK_rcZX3tkePq96uLlajSf7BnQd_-ttPVaamuTw_3UqhZ3ujD965v21aFjCrshCg3dZN8LOizNIsYgwhjvO03TRFniap5MBZmTVtF3w0WhmlyjILkTabGpUWKALFKtHEsNk2O7Np7waldNP2xMIGX6aGCHyIfdulZZIoTcyddVoq70ORF8tVjUBDb0WuJlV2frae7pS5SeptIwQut31VJlpqitAPPUo5M8qQZQABAABJREFUm1Tee2v94cGea1slxbZusiKXUm7r7dH-XqKk0QoBpEJynplQKBDgXTDaENHgvFYqxkDMwUeTJs46QmAG56MNARCFkt4FBnBdP6qKIssER4gASkSggOLsalv3tu7sEOFstfZCb5veudBbh4whRgDByG03ACGTQym3TY8CJAqFUghpg6NIIUaZmVzgum7r7WCUiCFkWeXJlplZrOo00UmeyuujCoFMUSoMnrJMNdu-64c0SwQIH6MA0MoAR-8Dg4-BmrrbG-_2to4QVJJlme6bYVqONkM3K0eWPQIoqSRKJJ8X2Wg6Glfm0dlmKoVOs24YEq36wWWJvg5a3r25s-16AHm-XJ9dXlXV2HEQJGKMSWq89XXrd3YnAGJdryVK77oszbTWEULfWFQYbAw-guAQ0SRCs1nzttn6QFFK3G5rYApbi8hpZUiKTd0rJDeQNEIXBkGj80AkhIyAzEFlmbdDmeftus2rol0PWnNwwaTYNK6alu3WjncqGmyaKSS5vloh8uB9UhrfDAIERSdIKIk-RkpkWkwpknPO-QGEjjEmhZHGeBtICV0lqkB7OQhrXfQ5M6eJSSeUKPJ9v6iNSTETCECEPkZJQuc6yUZ22KZ5wlFuV7VUKBOR5AkMFBmjcwooNJFtP97ZWffDaD5OlFZajkal4pBlpUBu2j70w_HBwenlqulaEvLo_sHNyWi9XaVabtctourbTubJ6mKTT1Nl-YtnZ0S9yTNEEQfOMpMlyY278ye_fVaU2fe-8-Y4069fnT-4eWc0rV6sl59-8eWLJ59rzteb7aSc7t66-b_5B3-zkMnTi8tffPrpuhu63uZ51tf-YD7Z1q1QfDjb2zka7xcm2nBZd03TrRbbre2rPNNKszbRhRsHe3XT7u5OJepnr17ev3ez72ySGojshi5NMiHl6avz0aw439TPTpdlIb758P756TKfVhIArP3xzx8d355vuvrp09er1RpA9eue2SopqmIspYIktX2tTNo0bjIt92_uqDy62J0_WTC7GMx20yipSGnJpkjyaqyEgAGtbR2HePPWQZpl23arlanytGsHzUAA-7vVB-88MKCzRIDAx5enf_2TT4P1yphyNBIjtTOdfvrxo2DtbHe_7euHt2-dX5zN9va_9uDOflbmmTFS_nd_8ldH9w_-8i8_7AcXAIUWQz_U27arbVllSZlG69vGCwH7x9ly29hlKG-kvofNyYUgtBGyMpcS_DAACKn1zbfv9xerBOhyub68av_Zf_VPH__2s_nezuMvPjl5_ir0QzJPTj8_27u92y_j_O6N6e7s5bMzJUJZVeXufDzfgbb5-BcfHhzsR471arW3t9tsW2B-9zvvyADf_t53__Lf_fmbbz748NefMvmdw4Mvvnj56tXjUVGdPHpRTHLPYvfem8vNuewDO2v7Lq8q760fhugIBAghoutd28hUB0cqMwjSFKPQXLnVSkI5Rfz_E_VfzbKlSXom5u6fWDLk1kfmOSdFZenq6qrWaKCBGQzABiFoMzSa8ZLGofGef4lmvKJhCNoQxAxUK0yrqsqqyqpUR58tQ8dSn3LnRWQPb3eYxQ7bEWvH8s_f93kQKUOJyEwAHCIoIyygNQgfoswEAojAIATISSnilA5UQWQEBPjaOiQggoACopUirVLnlLaQRCsDKYIIx8gxpJSYk83z6DySAhJhQRFBIlBxcEQKCZnFZFoTsQ90gEiCAMgBaQ-IxWga-k4SB-fJ2DAMo8kUUbIiN1rpwrqu17l1Q2-zIsSIhNqaELzO8shBAGOIzAwJjaGyyIfBMcPybjMa1QAyDH1R15zEaCOQxieTyXxUlfXq9g5ANU03mo4TAlJCQSQanAckyshmpus6RFCZRdSIgFpBihJ5ev9BP3TKmt1uNxpNUZLVRiH1nZ8cHSlNzXrl-y6FGDuXjwrfO9c5JLRF2e13qCj0Pq9GiVli0FmmtWJJPAyklNIaSLMg0gHib6MLpAlJRe8ZRBk9dB0Ka22Fk3DCBIQiiUGQWQQRLbGIKQs_OJuZLM_6pgESBERFKEiaBAg4ICqlJPWOtAFBEFGAihDkwM43MSUAVkolH0ChIOHhnBsRQlBGiQIgFBZjTYoRAJQ2kqIwoEIixYdaMCoB4JS0IkEGTsW9i9j1wJLntt3vYtJaGwDm0KGmFLEe1yAUnTOZAsH19WJ6cV8ptVndjCfToevczufjCUeHhg6qCo6RtGESZbOU0uFyIJbouZpWcfAckrYaBIgMAoiPSqnoPSnkkCQkDhFBDmOS-CgiKIiIgEAsCIpTQqXJaB56FgEyEgMAoiB-bUNg0hSdQwGQhOrrHyprgAFFgIATqrxWRKEdWJgyAoboHQAAgyoqjENy0eYFs0hMgAjOATNphJgARETg8O9BaUCCEJFZEqImFEw-QkyARMZ-jZkiFOGU2GSGBThxDMG7weaF80NW5EjIAM6FOi-Xq43Wphk6RnRD1FolACEqSxs8p23bOe999CmFIW43HRlLqBggyyyZLLggJKNRpTPSxo5H9XbT3i23iNL17vXN6ma1fXm1eHl5-_b29tV6p4tRjGGz3kyz3DO2Pt2sdm3vFqvFZu92e79v_bikuipGhKPCZmQUw7c_eu8bzy62vdu3QyI8nh4_uTifVgUSfPHydrPZf_L5Z0dVnWn91ct3765W2SSf1wUakOgujsZt9OeT0cn51LW73Wo3r-m4rpGTBK9JzyblSVWeVFldZRdH9cXpfD7KPnxy8sH944fHo6ePzj7-4MH5ZLRa7bbb5mqxyEWHmMK2_cnt22fzE9KqtNYoqa0pbJ4VNssySGm32zftQFoBCydous5ztFEGgQTw9nrpnJMIfTcE5-u6MIUZXL9vh7btt00_Kct6aq7221wUM9RVzgkyo-syizEgivf-eFaPyqrreksQfQSBnHA0yud1WRk7n4xKYxJKbg1GBh_vnR2FviWBxWJT5HlMcTqqzmbTwhitSOFBhJeawYfEPiY3MBMywODZx-S8dz4JAirqe8-AQDT4IAQuSj_4yGCsjTFZYzRpEQERk2etc4jKx-iTMKnFZr9uOlHq6mY3-NT3Xd-FrmmZFCnxiXf7XthHLzGwDzErjOujMgSIrouogGOKLvSdB0UElFiUUj5GRBLEkBgEYmQ3hIiskZwPmqjtvWIeQuwHl0IU5sQskpiT9z7FJJz6ttsPvY8dJ0jMTrxWOiYZQnDBJ4ggSRgiR9JUlUXf935Iuc2PRjUAM6ujSa21Oh5XxmgiNR2VfpDFovEQQoq2LKMLRV00-z5x6gfPietJ3Wy3CsXmtijs7XJNgC7JMERi4cQZgktRUAQSAoDlMISzkzozmEEaTcoiK2Yns9G0RrJaZfWoMrkdjSolNCoypZU1Bkltel_kWVXm47oyiqaTcV1n1qpJXZ6djqeziUeajmsRGgKffvzBpCib7VYy7bug87IbhizPjc19n4pqXIxmKSQQihy764XvehcGnVmtUdgnCUNMlE-lb4jFtZECYbTok0qEQEF6vw2TUWE1-7bj3sXWaZMV2qJWcQiu22cKhq0v67we5Sf3pkqR33bHs_psVmUGR5OqHBeU2WqUDV3UwNNpdTQrjeK0H8IQQau8tEWm1pvNpM4eXpw9PjrSg1uth6vF4q9_9Tq3mQ-hbbuvfv0SCIZ2eHOz-Hu_99t1UYeYfue3fvDo6f2_972PRPD-KH_43sOj8Wjb9v-fP_vZLvQhL_7zn_3s009fbJZbhaUBo7D4v_33_-rbHz-dz8qf_vrF67u7FGXX-j6KUTSe1O-9f9w0nTV6flRTjD6km03rXNh3DjV94xvPvI_HJ8c-hPlsZLQ6ms_bbk9I46rMMnU8GzX7VoMgqqTS1fXd3vcpsHfx3kn1wXv3JEFpC0nyxYuvltvh3ncvfv7y6tPPr9pVW41KMqi0jC4mwYfJdEKiSSEkXRT69P64PMq3i-XbV3fbm44dS1Rlburp6N7j-dG9-XRUPH08gzwWk7zt43vPLrIiB-bovBKErhdOxPIb333_G8-ePLp3FhLu-s2__ou__dWnL798ftW24d6jx6wzFrx5d3v99p2kRFo9-vBJkevF5a0O6vd-6zcyAUhijX1xvXi1Wry6XHVDdF7uv3-8a_x21WTWFLPCGC0SVWYACXXqtr5dtRCj24bN3RKNslV-fu98-fYNIhRFRZm-_-z95cu3NssWt4vMZD_6vd-6fv36g28-_tXnX15-8bJvGqUoL7KhC9OjWUz2mz_4LiQp63I0naC287PZ7fX15z_99OLexf0H9yfjSTWZ9223Xe2__d0P66q6d-_eL3_5y6br5hf3Xr25fvDk6S9-_ov9btfeLderjQL13g8-HB8fb3eLYbltF8thcLOT0_1q4fadyQ37aOpCAYWmzTQl51VlgcGUyq237FOmSFE9kyQoSRAUyKHeiaQASSBJjKQ0KeIQEAm1EWBhQYSDGFYpLSygCABZGA8IEVTAQlqRViyCKADMMSEKcAIE0gR4yEcEW5Ru35BWACxR4GCJIkICnedKK04hhAjCIIKkvB8AQZhJEafour3OSiISBBAxNiOtjM394LLMDv0QYwLmLMt0ZohUislaC8BD2yltUFixVHXpnA8-HFBroJXWGD3Xde5C0FpzTIH9aDoJPtSjUfRxebsgBBBIidc3m27fZ5nZrla9i2WVATIANbt2fDxLgyetjNJDs_NdT4igiQT3zdZtO0gSvdve3WljsqrYbdccQrPdiESrKMtznSmJkQgBwKdorEFGVBC6jlMUFkWaJaEgsCALKJUSZ9VIhPlwF47IHJN32mb9rrHjWUoOJEmIiCiHE-XAZIgPFghg33WCNpscddvdsN6oTJMykkQ46UMpNkUEkZSQEwqAoCIFwEgKBICFRTgkrCpOgpCSj0qbdMBeahROCIgCidFYyylJTAiMRAyKNB06sIhEykBikEQaRRgQOXoUCB55VBtCjAmVRsKIcXx0VBS1oBqaJuy3fbMpxpNyXDW3a63FlPl-aLNqFAV8006OTpTR7BkgucFl03FqWokskTkA5Xme2dD0RJRC1DaLLiUfJCXFACACQhIVUQweiZAZQYRZKWJOoIRICctBkg0sIAKSCAggiTCIKGu_9m-AYh8ABRB1lqMlEcRD4SYmSQGIQBDpa3UbsCAwQOAUSenkEpY2xYQSMQSILu13iHT4TQKIAKQBBDGBVoYHxzFSpgFBvGcCQCA8sIAZD8MBIUvSeRa9J41CIkLleJ76NvU-eu_6nhBII5ESwH63Q6X6fnA-5Lmxmd1v94C42XfO9_PZKHnxMY2qQkGUFBEocCpKyyCmMEIqKrRW15NsWladj0iYUizy4sG9OUfe9jGmZMv8_HTStOHNm6sgmJfVaDZtuuFysX57tXx-vS_OT-eF2frwz__4B__jv_3L_a47fzQfj7Ory9Wm719c3v7s-buv7vbrwJe77qvru5_--qufvryMoIxVpPDdzWI3-Hpc_853v3F2NPr2s2chpZ0LRHrvhl-_uf3kZn23GK63-2pSgaLb9TbPzfHx9Ml7F03kV3c3eZnZzFZ5drftWBtBtR1844a7tkugbpab3b4LqHzEVzc3rU9Kq3FZzkfjGMPgnSO8MHld5aT1YrtpW5dl1thMJK32zWa7p9zWdRViVNba3EQFOxd_9WaJIShtJmWeF9moLouiEABTmLZ3v_rqclxVStkQ_M_eXqGLySVBXOzaXdsZbUhrn9K-c0PwL25uxnU1-LTr3fn5yeRomueFT3Hb9qvVOjAxki70ZDSyRqHWWWH7trd5dnEynZ_OrdbCYqzOtUaFiTmJJEw-pnYITe9ZEJVhED7o70QSyxBiTDElAKVY2IW4a3ohCikNIbkQ923HgkVuY0p5bhkgSez6Ydf73gfHcrvcuyRCer3vN9tms1y76AUhMTY7b4usbduh95CYwAAhahraYItMGRy6ARGj8zFJWdiUotaEynRNRwRZbnzwzseYRFslwoMbCMmHmKJsd3utkBMrS34YNJILkZlT8ojoBhcGx8BApBW6zieIiVM7dKQNg3gOCqndtMoanevF7VYbNYSotFotVmRM2zsy2oegjOLEozqLAoums4a8d_P5KPporAWmpmmDT0qprum0NcHHGGNubUh8ebuJwY1H9dD7usyatkspjiaV1kC5TT6GGKKP_b533u12LUf2KYYIV3fXkVMzNDFJndnjWZGiTMZjq1ExawYQIbYn8-J4VkyLfHPXzMr65GQsUbbrZr1rI8tqtevbIYbWGJ0XavnpV1lm2rZBnZlcC7LKtc2KwPHo9FhE-qZP0ZePTkxdSg5ZVcYmSko8BK0AEvpmsJAgROSDfCgpTQISJQkRRfFuF33UemSs6faDNjg4H1hYBA2xT1obZtZJ7Vat34VKm4yyZtPfvFnu1836bssaWheE8PzpSaF11zfiZL3q0erJqA4Qr29vX7xblOPq6cMHy_XaA8dIm74vlRmNimG37XYdWiJmH8PxfDY6mjVtp5U6OZ-ur26v39zt-u5yfXu93F2umo-enP3iq7fDrularxFWi2XfJaOLup794Hvf_8f_-HcdJBH-m1-_-du_-ZUqbGRdT0qRVGTF2eOTqpqE2L93__xsPjbMg6R94-azST2trLZD3x0fHTX79vRoNp9OM8LNcgGJNYobhlGRp5QyY2yeM6ftuqmrqq7ySVWtt828zBVg10S06BU3-1iM8v1qf_P67vRspJTROrdl3rned_Gm8aqPtpTMqLOHx48_PkGUr774zA8dACCA1SVqpVkM0mRUpNbxehhN9eK68TvnmmG7WO9Wjet27H1R5D_-8Q_ee_jo2x9_eDSdWEt_-6sv_t1_-F-eP7_Z3OxsXdQn44RaG9xt934IfdMGH7__m98rx-WXv3qZ2vCbv_Gdf_jbP7TIL98uAqT_6a9_8T_8mz89f3Z_u3PBp2bvOXLwPg5RobJ50TdNCALGpjhYbRbXt0We9UPLkVHJ9PgcAJq7u_FkTll-7_6Di4cXzXZ7-eYlsCRRH338DYVYzsdffP7Zp3_zaRpcVmqIAhGjqOnJ6eR0lmdZEr6-vktuOL6YXn71Zvlu_ePf_uFu1QQ_NLvd3c1yNp7-_j_43dm4yIvyr__yF5Hpn_3Lf_bVFy-KqlhcLb749Weu2S0vV1kxfvr9j8v7sy__8tPk-n695eCyyvbtXiSZzLiuB0TxPOzX6nCoCsnvXQoc-05nGSe2GhSMpocvfiLhKEAEAKiMAIMwHsDLzCgMLIB_d_aeEiCBABKlxIIsLIQEAMBCKMIOWTPLAfKokCQhcNSkADG6gIqAWQSABRUBCwEeToIRSQAFABlMnguw23dKEwgAIUI67H1MUfqu-7oWTIojW5sDweCHYehEOHrX7ZvZfKZyK8wcIzATUdu0wKnfN812CymWZR0ZF9eLalQiCCPut40foiJo9_3d5buiqlFRCpFEJpOJ6_t-301OTprdfjSehOiJ1Nl7Z-1mq5UuyxJS6vq-rGsCWt8tJ7NjYRYSEYjBiY_DapuPpxBSZq01hG6wZcYsSGo8m3DwpirX11coID4MvUMCERnavp5MQ--ICDi6pstya3PjuqGeTFzbmsyCQGJBpTlFnZcgwCmS0ewDIklwWTXyftDGsg_q7woASATMnFgOmxwRZNRV3fVNnmXj8Wi_XZPWWVEkjsH12uaIBy9YBELgw0QoByoUACttBIQAhEVpxSFqrZCBigxCFGHxCUmBsuI_E5xnecYpESo-JNElAgtEByGZopLEyTtkJlKABEjaauGEfW_nmd_F4MP43syvt8EFMhmzlKORb7emKJp1qI9mNreu60kRGQPajOpKkhv6pq4n06MZGS0G_L7N8pyj18YIoTKKe2-UTiJAJJwUAaSoFCbvBYQ0Qvr6kiCjSIP4ACEqPKSYWCR93coQ5BQJgRODgEgCICAUIWZQpIgAOHHwX6uTGQCRU4LDOBEjIIIwgkIAnWUcgzJaooggCUjq0hC0tZAit82hl48IwgmUQkQCIlQalUCQ6IATKZIYhRPaErxHpQ_fniICiQ-fB2AGwYMaXAIDolYA3ofOKY3GGEmikLqut6a0mWVJGokFnfO2sJFFQEqdsQ9GobHZYj8URilEQrDW5HkGwgmhLDIBAg8pcXS82e0gyXa3CyHGKDerfWQhS7N5fXWz2u6767uFzrIh-Ovl5uXrq8V6f_7gtMqz9b758su3v_j128vr9Vcvb4_Px_cfnm7vhm7wnXdGaQR1ejxzMSyvd0cjtVis2m17flQ_Oj8ustwQlsYKSVR8c7NBqy6vrwcXnzy4b-vapfjR_Yv3jydx367X-5_-4vkXz9-9u9smNKvF7tXNRll4_tX1q7e3l9erVT9czKqudcH7PLelyY4m08MFxgCrXVcXeVWPityensxtYQujx7PJyWy0GHYf3DvVmeUY6jLLM5MX2d1663p3t9lt990Q4mbXrHdd72IIyeYZRh5by4DvlisOqXchs6Yqc1IcfOLACs2-6-rJZN90k9wen8_CELIySyE2bV9PRs67n__6lUh6_vLdg5PjBJDnBpCvb5d5mSmtUvKz6bi0hQAgUVFkza7RhEorF2JZ5lfXq37wIXEKIc9sVRYC4JxziYPAets1XWwal5U5CANS1w3ORaXN4L2PiUWcT0kYNXZDHEIkrZtuQKW7wbfdkECI1CFBr7Ru-77pfe-CtmbwabNthFQ7OFHqbrPzITjv1zsXEvsUs8Lmo7xvekKo65wlCXBCyeos9t73QeTrpKgLsczt0EUCDCmWuRFQiZlIIQAiSJLkOSbOlPFyKPsGP4TgA6CK7EOIhNhuWgQlzEQIqBDAta6sRggpBUEEYjyAtUOIxGByrXPV7Nq8sDEFzPTQ9-PpSGsKIdwuVjbL7pbb2Wj8brXbNu54VmpllDa9c1Zn-67fNu3R0bwdep3roir2bTuZjACxDzEvivm4Xt3titx0vfPeEUCM7AfvguRlqQC6Nhgyx9NZTKw1rla7IsuHPmVktrsWmfNSNe1-udrFEPuuBeS9920zJO-L3Do_NFtWGY1ndanVm3fXq1UrBH3nmIJWQKDEo-MUBiBSfdP5QZrN1irb7hqtdBhChoo59l1LmVRH9bDbpyAxsc2L_GxKBFmRpaiMLRhECSDqSEqPj8F3SBEAur7ztAfIsqpi4OQ44aCt0rqo8omgB5TgQpYbH2MKiZGxpGpahJwya7uYJheTel5LIo363r3jfdu16yEG1mVuMmNtdnbvDDRlSvV9yAkxqZwgyzOvUVdmcbsEBfu79X6zzXO72uyO56Oj-ezk-Pjs5OQb33w4Oq6v3yxc9CdPj7_86s1ive73zmpztdxtV5uQwtnZ8elsVFj7L_75H_zBj779G994dDQfd0P_6RevvJOY8OFHD4KPjOi9U4TOB-hEcbRII6U3q_2m7V98cXV0XJd51jdtVWbnp8fMyWb25Hj26uWb05PZw_sXJFIWdjqf5FnWD90Q06t3l29vlmcncwXUtL0CmU9HtsjeXF798tUlAt0su64fgovL5QaBo4soPD6qoO-nVX40LX_8nUf3z6cn03p-Ug2Srl6udpseyFbjo-lsPi70w3uT01H-wXeePnj2AFhv9n3Xeyb74befuRgLTfPR6PGD-fe-940Hjx89Oj_P8mzTtL_84sv_8hc_-fSzF0MfsiI_fXh6djoLCV4_vzJW3by93W_3xagymZrNZym4djH88OP3__BHPziu6k03_OJXz_-Xz56_entze706uzgu83J5s1TKlFNz79H8i09e1FUVUwjDACh5VTWrrUVqlltNiNq2zlXT0poy-UZrJYAC9v1vfmRt_tVPf7G4u3vw8HHq-m__4HvVKB_Ni__8H_7L5mZJMTRXbZ7D5HiajSscFWdPHlfjMbIgSN_u_WZX1nPf948_eBya5u2727ou33__6cPH99__xmPXNqauf_35V4G5HlU_-_mn1-_uun3zZ__xTy8e3sdc8SB_-H_6B5__5advfvI5cEo-omdihhB874GQXUBF5agOQxNdrwxxTIJAhz5UppBZkwp9r3A8Pxz6iwARASrgCHmGQAcrqFb6wPuBBCovBQVi0lpLZFSAQKgQOJJSACAxEhGwoFIECFpxCoQMAAIMIodEHhAxR0QkpIMxCpFSTACotCVjogu2sJpUSjE4hwhKEXsvhzwSkS6K5HoB4BhEuCwntiz90Lm-9ylluU0hAKH3weZ5iomY_dABiOtaY40MXbe6A2FCyIpR8CF6H7p-CD6kqAiMQj8MhMBAltR-31ajShMM3knCrKq6faONJm2Xd4vx8bzZbrrtPs-tzS0zg1JVXQ9DyIu8no4X1zfD0Lb7hjiZzABLHJwpctfsm7t1UZZD1yqb75qmms6860NKaegIJPYDKVRGo9XRBZMpZU2KgSUaUodiLwAprWKMyCwAaBUCKKUBMQSPADovJAQJHgjRGmWsiAiLUUoSo6JDPkWASdGB64CEtqgExG2XeVlKSq5pEZPJSwGJbScAIEgAihQDo4BCFBFhRhRICUkDABHpsgKW6DxqhRwAEZhJG0DkGEGdYEigIAUPSEhIAOwTKSJBZEkpqjwDFkxJkcrKafAONRjU0Ue398XZEYTBrVtiYedHsyMkkw7Vc5tLcJFTCjFIOtTQR-M5gkEiDs55l5cjk-ej-RGIhuhdPxT1JAZmP0BipZStjTjJKhOanhRhYEmMhOIjKYWEiHhY0SQftdLJBwZGhUSkFAALSlJEEhJpC3xg4wopi0gIIXUDKCJrCZHd8HX5XhtSJsVASh0YTaRIacXMAImyPIYICByYmXVRoM0BWRFLFEkJBVAfavcRv8aIQ4weETh6QFIgqBXHpAhRWUkJgVHRYWZDEVJKkQYWpY2IAKF4JykqosgAIjHGvKq4H9hH1zeT8cx7F0IEYGOMc4PSJgVm7x6eHIcYBKnMVQoxOF9UpVaq65wlHSJHzyKQWX08H8fICECayqxwIXZ9H1xIUWKQtu9G1qy33XZI81n-8Okj73hUZWD08rZ5d7OQGDKlrOZm1-Z1JVBQma_WvSVj8ny9dRhlCNG3HUjYD76qyp6FSL28WTuU680-Chdlff3m9sXdpWvdq8Uiary6W__1T754d7tm7TmyD6mcj0_fmwSdtNEOYtN0nz9_-8mvX3fOhZQEYb1vPvny1cvLG1b44OJEUKssa_u2zPPgg3e86_veh3_34nkW-dev32lmItUPfQk0HhXXm-26H25u93mVr_ousWKNymRkM5-YEY9PZ6vV3lhTEry6Wkym013XN207HdWrXXM8roi07_16375d7XoOZE1elJv9PmE0ZIo6f_nyerXdaWOWyxUCEUJMaTwbHZ8cdb3_9KtXEhkEoouLTXN1t7pZ7bVWBBhY7pbrELmNcbneXy92KXLTuyTY9348qqoi733Yt_52uXZBFutGGeMi68zcLdeoFSqVAIw1-64fer_rBseCiJt2GFxseudCCoAssO-HBCgHlqVAiuJCCCk1vYsRPHMIjJr6mASodWGz37-8XKLCEON0MiGSLLNE5IeQIpgsS0ISERUPfXA-oULSqI0O3jMLAilApYSZGQCRJHIC2a53SiEpEEk-eK3AhwgJvPcQOfk-DgMKD61LIaYUtEKWpA4TC0D0vQL0vtMlaWWD93mWCSdRmOf50Dul9dC6MHQ--NFktL7ZTCbV7e1SW-NdODk-cn2XWXOzXOZ5vts3IaEx5b7rSFHrhySSZXlMYTqdlIVRiiBxDB5j7L2PEhFwNKoE-N7piUcBAFGIgADR7bvgXFVXEDmKKwtLeOB-wGRWmqwsi1qLUqDIWgjaoi6ManY-K2plzNHptChyVKrz7mQ2Wq6aejIPnHZ9rMeFycz4bOx96ls3Go2qrMwKGk1KTKk6LvPSssD9x-fr3f5kMovIRZnbwvoYh77P61pDMrbwux4Sus4PzGZkwKAyFftU2VxZ0WGbZ1nokyqVtTkOWmmUFBWBKGlu94QUQ9AatLZIRKjreT69mNg8952HNrmu6zbD5cvr2XENStb7ZKwZn5V3V3v06WQ-nlejoXPcsvduc7t4efl2aLtM4-ls9Oj0SGV60TRvLm_-9K__qgJdFUVins6Pbm62o3HxjW--__6HT8fjutlufvKrT__iP_7lbteAov16v9l1wSWtiYNoY549e_T4wb0_-v0fF7kZCRydHLXd4AE75z778sVm2_zwB996dXN79fbudnXHSZg5s_qDpw-ePDw_moy_-cHDBBJDSMwPzk-IJPQhK7KjyazvnTbm2aOHkuLxfDKd1cKxHYZqlM-qavBu6J1z_mQ2u39y4lyYj0a2sC-XK468brrVer_at7fbdlRnkFwM0ZJikTwrQ-BpVU5tIYGOjmao8hgwYrq9XQcnjAmUjskiw8m4PpvNTo-no0n26fM3Xz1_1betG8KzD957-vH9xdXi7mbTd-69R48JSZO9XK_-y5__7WdffLndNK4NqswePL7_7s1lPR_fXS_fvb4VSdvtDpExJaXo3tPTFFNsmpP50R__0W-fz0-9j83Q_D_-X__hcr0E0icPjtr90PWude24rm9vN6OiuLveTme1MhJ8VBZtZkPn-3aXW6UUlfOZyrRR5uj8nlLS7huOODs6-cN_8ocQ3c_-y9_smuG__uP_zWhUPnnyXoz95dXVJ3_1E4yu3bTsh7PHx7YqfJRmGabnp6OiWl_dZqiXy9vg-qdPn-43i1E9Lir7n_7TZw8fjL73ox-8ffXu5NHFarWqR5N_86___dXV8nf_4R_eXl0qk129fnt7tfrB7_3IxbhdbepZ8fyvPmsXa2ZHGtIwKCJtlMozhQSSEks-qtmF2PVIBDFRhrFzJjfGaokpuWCUMgQKqxmyCCApBAAkAmBhRE0CRCxaawAATkggkSk3wiwcEQBRHVAkgCjxAKOkFAIRCdH_yk6GdEATEnJEBFLqQDjX2oqIRAYEJAKCw3EjIBHpg3ZRIYXoJUVSJJwYmFOwxoAIpEioOQWJrK113R6ASKnYO4mRU-QYM5ORBpAonIRDs22yovDtvlndaZCh7UYnp8H5GKPVwClwlDiE4DwwpRSFmQCV1s45rTGE0A1BCL1zSpMy9vrt5fz0pG-2yQdIoeu7vKpD8M2ur-qaJSmi5F1Vj9bX15P5NPRdlhlAMLZAbU1mx8fTFD2jiKS8KtumJSJttVZqaDqJnpSKMQIRAgbnQZBREgf2AZhBRCkFqFLwxmQxJqW1znNJAiQKSRIAsLGW_UCKog-mqESQJR6yNJJYBAAYgEVAASFpRAHE-t5J3Gyj6xUrkIDCSZItpxwDAkoMpEkYbFELJySKPqAmiF5QESfKs-QCaHsIrpBG8VEEBQEUobBIIkCV2-h7gMMDyDGgJkgJWRCJRYQMJ68UgYAga5u7pmMGo7Qgg3PMQHhokciuva3Gx0U5EqWHflDGEoGQja7XxoRu79tudHGq8tFqcUcQovPeAWl9fH4BALas-n2HiDbLAAgJlLYSZXw2c9tWKSJFMSat1SFuSEbxEEBRclFlhITMrKwGQfFBgQgAx3SoPoBEAGCOiIAgEiKSRoOcgKMHnZMgCBBCShFByFDqHSmNIigozMIJgCQJaM2SEEVpJaQ4JUwh7BqltbKIgBITCGOKolC0YpavM0WBkRlSguARBEDIaAEERA5RGUOALAyQQL7m_H7tIiA8LAMFAiKikM6syUwKjqJH5KqqQwiHVUkxqmII0Q-YpHfMZKKk9mCpS0FrowiT8zYzZWZd5KrIQTC4kFKMkkAgUwaQfIiAgMooovWusybrfZxVGYnutt6gP5nP7u6202nJAs_fXU4noy6l0wdnidPT9y6mRXHx6OjR_bHr4h__3vsqUxGQhb0fUoybzrEklene--QjxkS6-K1vvw-2UC5cLzdXb9fg_PH53Gb2_N5kJ-nN2yVlqlnvXr7bX17uUJmbm81m23RuYOGmd_3gZ8dH41FlrDq7OLtZ7r64ut308e3N6nQ-mtXj529uPvrg4d98eXl_Vv_Os0cns_GT8_loNN41PZINQNvW7R3niro4bDv3yS9viJiM3XcDS8qtVkq_vr6pCtO1w5urVfSMopfb3Zvrq9lsLIj3T44BMM9zynWZ2UcPj9er_eubld97qy0IV1WxWO5AU57lb28WxtLp6fH1andxNE0x3SyXeaZn8zmiGo-rxEApnZ9PR0VlMwuKmm7Ytd3rt0sWAoDpdASEWtF0UlujYmJUqvVh1bSD5z5GUMTMLsSuG0bjSpBiSoMP7eD3bT9EbtrBJ7ba9D62g8-LbLfvAYkRRKh3DklleZYkGWtjFO8jGZU4HQzTQ-Sb5VYZrYxp2n3f-d6Fp0fHnWeFZLRNKWWZdoPLNEV2gKppvNZIhIPzRpHWWkTGVZ5EErDzQViCc9ZYPzhtVN8OzOx9BFAputxaFwICx-QTJ9LU941RRIjC8QDLQ6VEvj58IIAYffQiKEWVBRerolJ21LedJkmBN3frk5NZt-8VKGVFhMuyVEbNT6ZD7_eNy_LMQzLG7LbtpC733R5RmrbdLvdtM5R15ofIUfI8a_a9NuZqsR3PxnVdBe-tIgGUkDJlOueij5wkzzNmsbm2xvi27WO_9x5YIsd6koHC4F3s9lVBo4khk9W6-N6HF4pslZXFpDaZTU10XR863-_76TQrjeWY-tjrOocoJ6fz98ajV68Wzb4zJQGxKbBziSA3s3Gz2i3vFtvQbJa76FMUT9raLC-KcTk7Rk7ihnbXDW3n2j6FkBVZ4AgM0QtZMooie9-7Zj0oFlCCyuZHU8ozRQo4Ba8UksktCurKhMhkTcegFZVlHfqqVPmj9-5Xx0ftvs0KICYSaPfDk4cnYb2vp9Wz-8csMJrVpHTXDI8fnNjcfvyNJ4_und-_dzwej_vIUui2k8vF-mhSj1Xx5OH5048eLm-3Tz56cnJ6lFl1ebv7iz_75Pmrt9t10wUZTccaiUEptED2H_3Od__JH_3e07PTDx-dnx3PilynviutnZ-etUPvAG9vN7_68uXjs7NvfOOJCN_crs9Oj_rUH09nKrfH42Ja6AxJI13fLlICJoiJq1HRtP3pfBaCn4-rUVUcjUepb4HlQJAblWWZWUrStv3d7SYvs1GZp5g4eqtotW-ozM7nE0Icn4zn43KW628_u8fkmh7ff3J2_vH7WmRc2rq207o6mU_H45K1Xu2a5y_uBp8mk_F4Mrt3cfbso0cPTiff-uAepnC72f37v_305rpfdn1R1L4JeZ7dXS5ef3WlFX7wrccPH9yPMd5uu9Vus1ysKamiqmxe5eOs7b33iXJcrnf7dev8cHu9ePzBY1R4772L2WT84qfv_vm_-MPzqv7-tz5iII78f_-zP_3sq9ed951DpWB51wTH3_vtDwBwu9yklGazujA2BK9IGZWJyLDvbt9emqwqrc3Hk13jMMbjZw_efv5lCkmTpQTf_PjjX_3pX757fUlCv__3fzuDpJFfvrv8xS9-uds1MUjqvUianY18Sk0XyE5sbp6-_0Hs-xjiYr39zd_9jS61cRiuXm9--3d-fHY--9a3H37nw4_YDbOz07vN9tWXb375s19__ze_XZTZ5598sty2b169YdEf_d4317vli08-sxgPG1UiYmYUTiFBCqhtTOzdoK0CVqPjo9g3wTmUhFqC88oYUgqYgRQwCkdSqNT4CAQgCYgAESQGQBFAm4uwpPj_d4GJAAMozSEcjopFBACIUECABQmZE6rDMWKCmIA0ARMAkJIUISVIInQwHgJAkoORmIgQEJVw4sTGWgA5QOI5BRAGSRIjEiAwD0khROcUEREQKSICBCQdUrC2UMam5EGwGFVEvL27U5lhRRClmo5d00h0ymjf-aNHT3fLOySNwJmyABGIw-BsZoTDftPYQoMIEMQQFMLq9sY73_eDMWSyjLSq6joELyHFGJLzNrMiwdqsqKtu35DIuKp88KvbxcWjx32zn8zPNne3ZK2AKFsAcJ5XSAoSBB8U2fnsot2ubFlxiv16U5alxMikiZTv-rIshAgRYnChH0CYBG01SikiILOQUoAERAJAqIQTKQUMh3YaAktMogiVhiRx6LS1Ivy_2twkibCIJEXkO2_KCYeI7JMbdJYRKT-46HrShowmoyUexobEIqgVIskQyGhSihNzSiKAWQ4MwgwiKIIE4qOkAErhoc2NrJRmHxCElAEigoMqgBEEAZS1AJi6RmkrjLqsIDoQTpAI6IA_hRgANZCSmFLk-miORoUQ22ZdVOO-3assP8iJxXEUyOrx5Hg2tAFIPf742_vdotu3o-OJGVV5MdVZNrv_SOX5_Oyk2TRJDm5iG1zCwkpiiAFRARFEFI4KiWMkooPNmmMiBCRBJE4RECRFZbQIgSBqTcyHMgxzQmOMzVOICIkO9xAipBQaJYKgEJBIWFJCEBQBkBhZV5UoJQAcvSlLDk5EJHjgRCiAJAjsBiQlnCAmMgWkKCAkQgjIrLQiIolRCJUyJMAieHiTDmMhMseBU0KtADSnKJEpsySiCPHgMwBSClLwfgjZqEwxFnkRnUuDEzqAedG7HjWkFLU1Xd-ORqNspHe7lhPvncNDBSXJcrPPc8UCzdAPPnqOeWG00eW4HBW5D6nr-30YlFaoNBPumjYB7XYuy7K8zpd3u2bfBkmDjzfNxrWuGbrb2-3LV9e_-vLddj0smn5E9m4Ii6vbT15sLCPG1PROg06JrUoPHs3X1-vr62W37569d-xZHCRSeWL-nd_9zmrdfP7Jq7cvL69vNrfLtYZDryMlH4auJQGIqXdDnWWr7a7tu6aNl8uVY57ZclbYsVIx4bu72y_f3v6nn3z-3_zo43FdSoKhTwrgbtu2IS7ckJgV4S-_fPmvf_G8b_rvf-vh0bj--On9mHypbN9sd-v13WK3alqO3LnBszDCvdNjInXv-AQJqzKfT-o6yzyEv_rp88CMKTX7MLj0zQ8uvvmdx6vbfd_3ZZXnWZ583O6as6P5yckMQ5xNJkbZL15dnh7PWan9rtl3zWa9a1w8m4zrIhdUV1e3u65lxiEMIcbMmvv3Tq5X66F3BhFJlZXd7Zsv3i0E1c1qLaS3-32mLWllrV7te47ikmy75s3VUmlDiF5QiCLLpmn3nRdEba0LCUXtu6EbfDcERogMVWF37dD2rumHwIxomqZt-rDbt0abth3yvNptm3w0Wmw3MYYQE4jEmAY_cJLMUN8Nzd4d35-E_mDv9ojovE-RCTGBsMDgfG714Abf9ywpBqeIUvAiEny_2V-lZDhGEI5hEE7K4NC0qABSTDGYwgTnAIQAOMW-6QRZmLIiSzFFFxBAEffDlgjLqswLNZuNUvRGK1ByPJ8Pg_fOj-txu-5evLguCr3Z7xWZmKI1OiVZb7eWtELSiqrZCAkmo7qwttnuyrJAImNU8AlFvPNG2yovSJHz7nQ20ZnpumFUmqLQzW7YN71jns8mtsy6Pu53Q17m3gmzJFAIeojgOWY2X93tskLpsU1RDHA5ImPMvfMZVtX11S50vqyLYTe0TRf6fnF541FZa02mxQdC2C6bYb3ru02_3pkcJvN5auH8wfGoLkl09H2Mbrfe9O0emSTR9OIYFBmt4hBMqTSSQTZaxX2rLLrBG2tH4wxCkMS9j27d2JA08Nl8ckDK1nUZQ7TakAgycxg8eHbhdJaZ2qSmAwln946Mzh6dn44KlaHqts10Xt5erX_x_DNJ2DaOkB88OjcanUuBJTj36s3V5Zurl29u9qsmt0UAyQDf3DbzUe79MJ5NN5s1EIvju-XiZD7qu2HXtqgLTqxt9c__8d___e89_fHT-_M6i4OfFtnspEbwt6vNJM_LsnxwcvTmzeLmze3l2ytkevjoou87iSEKNtvN7XI4nY9tDOfzuta2KPJN1_sh-hC8T2fHk4fnJ6MyOz6qcq3vn58oxv1260IoMsptZq0RhtVmFYLLjC3Hlfeh92m53Tad33ctmfzt1d267a7vtm9f3V7dbT-9XUawm7189PSYMC6vVlqnsiyJkmhc7tvBOxExQsbAvQdHwfnl3arv9opjadXj89lf_uIr53xdmLN707qoLu7PLFGZqw--9eTZB0_8vlE274O7enfz1S-_XN1sXdsrrY4elEPT377d9LsuxDYOabUennx8f2iHb_3og37dtE2UaFyQ__7_-r_NGMuioqL4y5_98v_9__1PIaTWJ1sWIokYTk8n89lkcX1392pRjLLToyOtqBt6jhCG4Hvnmi7swuR4cvb0rCiq9WJ7ce-4yPLl29uhj9N6-v7Th7__-99f3S5Y0733Hn308eN6ZN--uF5vV3_7059nWRZDsFpJiimxprxp4Ad__0dWqYvHF7dv3za9m44mH3336e5uefN22Qf4l__yn7Rtk5hvb_d_8id_sW3214vV4t3V0DtISZPyLpiievP6LQKdPJhdffX27c8_txSExfe9UloZIk6cojAqk2VVpRHIYLcLs4sTjn17txFMzAwHsntWElFwPkXPIgjKO4947xkERkIhgK_FQ8CQVDHmxMJRA6IiSUmAIUk2qV3vJHiFSjgCkrAwCggQACpKMeKhFiwMSAeDKxAm55UmScyAqDUqLSLAiVQGgKJIEpPJUoyICoxhFlSIDAgJUmIkMkprjdrGZg8MQKCLigXE5OPZkQ_sBqdsjtooRUbbBBhcZ60ZYtQ6yzUppbv9TptsfH7KSfr9Tik7uIEQLVllickwRGWBd8ENSWcE2taTMqvKfrFSuXadI2uKIkdUxXgiw7DZ7UCS7_roHTKbLAOkhJgV2ageM6fRtN5uGhYZjUaL26t2vSUNRlnQmc2zPCsludFo_Or5i7wslVZZlpHVzW7ZLZY5cIjeRRZSICGzBWst3oXQg_OKAIFYW0mSQrRVobXy3gmzLSulqG9a1_flaBRcD9FxipCiZzBljcCSQhx6pRQHFmFEJkRJkjgYpTmxB9RlGZpNBoJKibExJCAWQUmgM40CcejYDyYvUWtSKoaYQiJMACgpAGohY-pxDA4kErMkAUViiXuPmQYmMsQhISkOAyHpvBAESYGHqAiAUETZydRv1ngYRK1StojOa40syAnUtJZuAFHIUE7GQFAdnZnpmSmK7c2da_dZmXdNk_aN1oDMqqiqew9nx6deoHOt22yfPfugbdx-t8-qXJMauhaU8l2rQRC43S6ZhQm7Zi_e5bmObcPx76j50UOUlCJoEAKJAVOScACbRjJagpMUUQDwQNU6rAESaQ2cEhIQqaziJMIeQUgRJ0StBVg4YQza5OI6FDksT0QETGHG4xR86Htd5KAM9w4loPdAgNoEEAieiBgVkSJbMAtoTcwEJNFBjGSVMAdGtBlpzZwkJJOVkSMnAWTUGjgBENkcAFJiIm2UZhCtimI22W66yfF02G4YVF6PTVkWRZlCMooiIDNn1vJhJYhS1bW1VOXZaFpCkqFtsyxDgaNJOasrAqhHGRK0w6ASBB_OTiaKyPsIAClEBL7bt4_Pj1vvAFFAxAej7fF08vztVZkVygogA9FXX10qS19eLqdZ9u5uOz8t83HdrN13nzzcixvuduvVBqsis3K9bzOtI0sIOK7zFFlFd3O37Rr-e7__jW8_eDwfmz__4qW74y8u311tbh-ezDOV3vTDs4dnH9w764f08OzI3S0GH1Bj6_23njy53GxyBe3e3b9_OsmKz19eFaXd7pvPLq9HhfnjH_9wMpsh4LZ3n7x6E8fUbuLrz189eHjSrpok9vGDk0cX5d_8za-Lunr4-H5ZFmkIn371jiQNCE_ms7UbMsFt0xCa-yfT49P6ZDq2VGx323_zP__nf_IPf-_ZvQs39NfrbWWyn332-Xe-9fHlokkcfvzxvdbhL37-IivoaD65XW9n4-rT51cfP7snAefzet8Nfoi36w0QrFZrIo0KPvzg4cRmx9ORF_j5L17cLTaj-SgkWTe7xxcXm31TKh0hPrx3Ph_VafCA-HaxihrRmDdfvWNSx0f1e8dHWZ5fXt2qMpsW1bpz17fL6azue8eRbWbI6O1qpzNTmCLGMJ-NQkxD9MvlLoZIim7Xuw-fPMgytV7upnXd9oO26mw-Wu1bIH11vYSEVV23fbfaNkz67dWVDzzEZMvckrq-2c5GBSlkFhGwmZEIHp0PqWmHssjTMOR5AYqcj4NzMaW-aTQyMObjIg1OfGyHPnS9LnMEOPAVJGIxHpmM7168MUYRYEhiR5VWWhk9m5S7RRs56Vyb3LrWKxQfeHI01qjWd7dVVeuiYvZZUXjf50VR2GoYwvF8fHQ8-fTnX4TA09Ox0jYSBBeNUuPx-G61KbQ-mk72Q388HUeAmCIKKAH2rhjXIGgyK5la3KxDil3T6izLjB6VBQj0zp3O5pv9et10xIkRvIu-d_VoOvhWAm6blrQymY3BV5NytVtyUOfzKWmPnBljqrru--FusX7v4clff_LVxVF1elJfvtmcnk5nD8_b9cb1vGl20cfeBR_CeDzbrNYZ8e3NSqEEnaATPbYJcaQLJj2bjYJIdJ1nCC6UdQUCIXg7KpUAhHT56tJWptu3SsEwOI1oJ6XS2bD3ujA6V-yi7watNAAiqfnxONPGR1aF2W7b06PJfts9fPDe8ubt1eaWk7J5UebYLFrJdD4Zn84n7z28n0J4e3WzWnSTStflaDIp63F5fbO-entprH14cT6ejT1ICklienn5SkKaTo-Y6b33To3J2v02poRZ9tkvfiVJE0jb-dE8n88nzvN_9_e-v9rs-xgzo7o-jfN8PBtTJvsQ_uQ_fkIpeaBRbheN3JtlP_zuN-qMLiaj08cnf_nnv_zJr1_87__bf_Dl87t3d3ff-PBh6rp5WTFS2_kvr5cXR3Vt7aiwpbWUuA--b4fjs3Gm8v2uCSnWZd2EYbndffjwvsmKfhju7m5tZlGZdnC7ru8GL1qtlushpNY7rUyd5VrRg_vz58_fxcitdwmo2fRRRCQBmyLXOkupS3fLTTmyiXXb7M5Oj2bHo5Ky9XLxzW8-y0hevb3L69HV7fLodDYqC-f8sNls17t9P0St752fvb285SHeLlat8xZVbvXs49PUdt26X1zuQkrz756Fy6012Wa1rUajTONu09XjKtfZKLf_zX_9m5AItAo-_OzNzc_-6lNlVN-GalImAiWsBE8ejd0udW1gCYbM0clECb57fTWejxJyHLzzbrPemzxznqsyN5nd3C61wiG4wlajsv6N738AMTZD_8tfvVjc3X78m98ehvbVL971vgWQ_X5v8kwjxRQzm9_drN_74MHT3_qee327a7okEvtufO988fr65HwuIt_96OP5fNwP_dWbK5rVf_lnn0zKrO0H1_fT04vbN6-11u2-Gc1nzXo9PjmlxCn1m9tVbLeCmEKAAwMOQCGiMcqYGBKGkCSpssqPTrT43dsbDSA6BR-RAMAoaxTSsN8rBSyEAMAR8d4zRDwYSVFrTEkAOQUsRqgUBw_Bm7yQA30lBrS5yjLfNAqUSBQ5qMUObQHFwpIYRBAYkYAZlJGvlWBERHJQnJNChSDCIQApRAKlkJQIJABApTLDQ6TMsAukEYnEOTEGEUCImBGwqKs-eFOUxfR4v2uy8XzY73VRigBzLKq62-6M1VqbyCIChVEhpsRYTGeiDYRBUoo-pOBtWVkyqDgyEUkcvCKtjWUI7XI9Ojm3VeGbxpY2RbFVrrTmyJOTGYnq9u1oXr357HnbNpkxHAIhmlGt87zb7e8_ephl1A3p9uZuNp8UeQngX372ObIAZaYaFXmRlzkhRAmudSCpGE3b3VpYtq9_pnUNgpgZnRsRGbZ9cTRr77ZZTcN6qw0AIxSFIosxotWHUcwWxdC21WTS7bdD22lNWV7s10utASWlBClKMRql6Nl7AhaGFAOgIKowdMJRa0osREaKgvdrjAmAQSmV5xwToxhtmQ_BFEzOH2LuAUCVGYhBjsEHhUymiDHqLFOZDW0DIApBREQhJwZhJFK6iDGSAnaOgMhYUMQAyIihY2EEpUaTNPSSAgIFZpXlRJpDJAWShDJL-Zj9oCWhUikJ6_z-t38UkwCaYb-Iw6CMcZsNux6tcGSTjx7-xo8Dw9WLL4yIyfPxdG7siKNXlS5H49X1MtO0W7wlnfWbtSDZMh-aPgx76XsR0XlenOfrz95qRTGEg-pYl2bYNwSHKi0DHwRbSTghAYpIEgBhjgc4FhFiZqOPZDNhBESOThkLMaYUdVmgYAoeUlJKSwoSk0AiREbCvDaT2nc9uwHzEkR0SDgMaIkFEggKCxGEiHkmDKacJkgpBmM0D8Ohw0OkU2KwlkWIlAgSKVBKQACEfSStUvCUWyQNQoCotY4-iDLj07MweM8MzFV1hBCCi3Y8NZm1yopCP3ilqCwr1EoToKYis9HF-8_ux3aPkX1M3sXz09n58TwjGIY-L6yPISNFIoXFPDO71vkQ8jIjgc455sCM3eCyIrvcLbSHUVVoZZd3q5Rn46Kc2JpMmE2Km1u32a87j7OJvX80enV5tVt1y9Zt2_bkZPr-R8dfvFw8f3m9jb4MJmfQymZWIQYFoCwcnZ_e-DQ3xUeTcvrkrI7QhaEdBh5cZs0uDI_PZ8tO9l13_-LISBhV41qD91LWhaRQZGVuaLNpRoWNJm_2jSUDAqbMR4X9f_7P_-HLVdPd7Koqd94hF_ms-qf_6r9a_Op5EHaaN7fb5HtFNgygR8oTPH16cbvb7a_7iVLf_dGjuzcb7vHs8ckPHk086-V6-MWvf3VxND4_PreKqiK7HVrMc7_a1uXoerWfVMpmlsQYRU3bqSTbvn_46KRxYX23PT4ZZza7vb6rJtMw-J33Q99Zpbqu_-43ntRl3nfDX3_y2cYNSoy1SCZPEjMio6lphtPZ_P7FiQ-xb5o2wZfvrk7Ojq9ub3JROi8_fvKgMnh9t_3zr9794P3zPCt8TFe3q6y0m-UOAHdtVxc2t4UAG21za6aTchjS5WJ5ejbbbBpjlHBiAQwiChQqEa6KnBQMw6B1frfZ7DZtnpcms-tmP3Q-pnRzvabKaq2L3GxXTaZUwGTKer_azWd1SrHrh945U1QxeIwhyyyS8iFIjCCyWCxIYL9vrMU0RABRee7blozVRmVV1ax2ViVt9LBrQWFWZv2uRYSsqH1I2aRgd2isgS2MInKDK8tqu2nf-_jRbr3dLTZlXh6fH91dLrJJNb84fffidZ2XzqdH750CQNs4Ig1aBhdBITLmeaas7oc4LspV0xZ1zt5Za4MPk2osrpvO65--uPrBB4-V1lGgHQadmetXN4xpVFbsQ1HXu6bLc_Pk_oko_PzLd3VhffQZGY_S7t1snO_8jih3bhAvQz8oK6aw23U7HY0DC0DYrPtc59oKCtRVrSutt2Hf-8lJvW67m-vr3pj7Dy6M0uCG4GJyvlTWAYVhCCkF8VeXi0JBP7TiA4ACZB8CAxfGClAMDlFboyfzeQQcncyA1dB388ns3dWlzex2udLGxCgsLkYGAgQ0NieFBrWgEFCMqbAmKRJURaZsXYfOW2ujjikF3_TR-RTjaDIPDM12Nx5PhsFNxvnseP7w7CgF2DaNEbRWSUrjSXGzagYf3m4uteTGmNxoa010wUv89LPPvvfBR6PcLu7a93_4frdv372-1TozRvdd-PaH9957dtoudqOqyCs9G2e_fr7EPPvsxeXly3XgOJ5moyyLAX7rx-8_OJl5xlcv3hVVfjafP3_1dnG3-O3f-PbiamtzM51Xk0yNx9Wj-ejf_pdfTyrz6OG5Ep0SaCWg9dC2LFxnRTe0x_N5dD4KaINXq8379y4ASUS2-zakCIjbbSsKdWbabsjKvO1dH7jZ7LdtVxV563h2VN1ebVzqM6261pMCCSJE9-6NXr64SZHLwsYIA6d-GCDhbFLXdfntjx5ZTqwhB3m3cp_85JcPnz3sB_-zX36mlI3Bn56d3F5de5eU1czRWAukGIA0tusNabVZ7HODs_emy1fr44vZrhk4gndxVlWKlNbmR7_z_ekoG5nMGJIY_od_91eOuHWRGep51a72o9ns5WdXF_cmk1kREqwX6_l0REoXStvKLu_WVhuPoV33-bjs22bf-RTdk6dP3r5-GYfEwLPReDI7-c5HT7MMu3Z39e72b37yKRXWGMMprRd3Bk0Ifnm7P753GlPI8yyrypTC5N54Xk32t10_DN_51re-evHCD83tZpXb6uLi4g_-0T_UbdMO7d_89SdKwfNXl_1-m9d1GuTDP_zt53_zV13j5mdHxhb9viHhyfxkt7xdXt0YSd1mkySmkGxR6Dwjo1Wuw9CH3rMwCWptzGSulNpevcWYSPEh2SuEqDJBIeLQOaWETBGcI2CEi2cHoj4AoCKIkRAZEXUOWnN0iEAJ0GgCSqETlmwyGXYtcFKIh-AAIQgIJkGr2XsAODyPiAgRKs0iShtOCb6OR2ZCgCkKSeqjqUeCAITJBTSWI-tRLT4CRwRiDhCjKmoBBk6H5qIAKqMCQJFNv_cP_uhv_uOf12cnrm-btq8nk-gCKQCBsqpCcMmLAKehN1mG2aiYj13TxRRJOPWtMgpBMStAsONpCj2K8BCyot7v7_JqrohGR5VrXHQe87ysMu-jouz88YO2bSTEdrPp9y1o6Tf7cpShQExJNCGozBYX7z1k4WbbMhKkWBS23e3Xl9emLGxZFOUESDvXVdM6dF2MqZzM98u7zGrf7dZXVwq5nE4ic3k021zeFrNJu9jaTNxmhxg4oq5HQIYQ-t5lRY6KFCKLIKAqdLfexMhEQkAc-uR6RIVKM7MyWqInlsQ--YCEnBIhgEYZAlqbnNOjCTsf-70iIgRlTDyo5gkFFCoNKCkEAkCOiRlJZ9MJJxalOXSECgDDEFRmo3PIbKxOMaJSZDJ2HSMAE1kLKMgSw6BQgTYioBAVSoqBGYBI2Sx0nVJKACOLynK0GkJCEAFUeWmy2g87Im1zw5ExH40fP2Mwqd9pMiH60A8KIHRbCFGIEuqHv_GjvMwvv3qRVUWR2eloKmC3XW8zrRHXl9cMnMTVRZUwDl0XhwgcjFLJR21pfXlpcg3JRRc4ORFImDhFAuQYJQQkBSDiHSCzj0CoEAGQOYIgEkFiyiuOAwuqouTI7D0Ia2sPGSptFIsAIHAgVJIiIkhMKjMhJior1DqBSAJSBC5Q9GS0MItWEhwkoSLnGCVGU46i0sl9PWBATCyJEFDZmFgVGQrGOAAasuaAD-IYlQApE0NUWZaERYSU1QrdMGSjmSrqFPrg2GoxYCkbe5BqXMUkxXichqEoa0SwxgIkm5ssy5iTVqowWiGGEBnFaH1-ejSuswzhYBSqCzsb5dHzdrMPxJNR7YLXpIbBpRhnR9Oua0MMfT-8vVyMJrnJsxR4vWkKY6en9b4L6Pn0_LhGPB2NXl-tGhjevVv6xv_w7_2gu7r94tVbj3ld2PmoXDa7xg8S06OHMxjoi9c3BJAojYoMtUWNRV25NgTXvby7PK7OCMCz85FTiHmZGSGbKQJlMts2bSZ8fn7Se8dK8-BOj0b72812Ozx8cPThs8ek9NB1P_nVZ6O8YKtfvLxSWlNe_ot_-sPVXf_ly3dHs6IT8_rXl1mFp6fH1-udUUqJ2MqI46q0s7Gt53W_8e2-GY2KUV4YUySQepS_-_LNfFJ-4-OnubKO0_Z2vdp19x6fXi42727uuoEfnc8_fvLg9nbZdmFcZqU1RDiuawFcNOvVct_03fXt6vz8OK_K-_fOl8ubnPJvPLkXXXI-XS1XYJUgZQo6z_vdvkCq6uL9B-fbNizWLSp8fb24XW2LXG-bfgj9fDb75vuPXR_c0H_66vrZ2Zh1fnO3rGfTxOHmdo2EBNI07Xg6CT6VRSaAR7OJpNC1IUSvtUJNgbFv26H3eW5TSlU17vvmdDa6vmsvTsdOwnY_PH_-7v69s-hT4zwzKE0pyma7V5lu2t73MbPIkHRZaq38rkXSAJFRoaJm37EPZVXv17t6nIfgfTfEoWuavfcxKzSh0lp3zZYjF-NR3wwp9tV4HPouhUCglDUAEAcfIo9GlSptEgACjcRDIGAPWFWjos7yulhdLnVm3dCPR-XkaOLa5DgBoHAklNPzE43q8u2VsXlZV_l4dPn2KnkvCBfnZ1c3C2tznVvn_Hg6KXKqiip4n5sMCJ5Mq5f7tt305XQkCktjQ_KKspvrG-AAoH0c7l3cq0bF8nZZlzkJdq3b7ddlWfqUssxoa0NKm_0eotRlllh2u04D7ZM7O5q-eXeriH2I2ujjs8lq0YjnYlZW946l7TxD3Pcq8NvbO2KTTSgri-hi229hQG0yWysoDPdJBXESCEyZWUXY7XtV6GazAwANarVYT-ej7d3G5JpM5iQVo1oRjca1AVsWpUK6enuNGDe7NaNICjFwOZuOptMw-Ga3DZJUTHlmTVUIizAgKCIsinLnuuCjxNi3TkSOT48ERROWVTWfVKfH08XNmkEd3Z-ut40CGobg2mCMbno3KfJtt7dEhNqW5ukHD5tNt9lur99djevC5vnyeqMri0oJwre-8-GDozoTk1za900-rl8-f_eT16-KhEkIUbm-m8xmu8ZldZZl5vf-0Tc-_V9excip37_34HRWTz7__PXj-7Pf__63qlGtCbyH6-s3ZVXkqIYk01GeG910PYvEyIwqxDApR873aegJ1b17p9PRqG26CGlSFYzouyAIUWQYvEseCRMzKbNc7wVxWtVN2xtSbdu1Mdxtdj4Frcxu6C0p5-J4Xliim7erKDLEACI-pcKaTddqUN__-NmoLEd1Hpwfl_nzy-sXry6vV9tRXYJQntuvXl11bji9f0JMCLS6Wz_54OKzX7yIweVH5e52LynZTPfN3mZKGAtjQwBBiYGVMd_84P6zD55leVaXefBuCLzZ7v_0kxezKlst94lAkRTTcnu7dD1ri48en7hdJJUPQxhNda70ZDLl5HsfxyNzvdjcLDZHD-Zvfn0JHCcnE3RxcP0whAz1h8-evPfwQpvcq7hY3_z0J79ud26_2U2Pjzar5WgybpbdH_yrP3r388-vr-7e__ibwHEIvFxcdrtmejrZ7oZRlc0e3F88fxej9yEsL9v_4__5vxuhuOCLSfUnf_LXzTBELwrl5uo1N-q7_-zHP_0f_zMACmFWFc22LcoqU0qAQ0jJdW69gRhAgedPrf0NFE6EkiJqxd6llFCy-dP3kIfd5S1K5BSTZ00cUxLSpDRL9H2rtSFSqBUCSooKJkeoEA4Z_xgQ1YFdwolFKRRATpiSslZYhJkjc2JFh8KTHG4IDkgfOODR4RAi5sNlAEBkFMghOAwcEwKQ1kiKUxQQpQ0gpOA5McABtwYSIypKwUOKiIRaI6FwTM4TIUBCrb33J_ceeD9cvX6ptBHiajxPrtcK49CyMMfoun0afPTOaBQ_AKJPQRhQpK7q3bvnaXBGqWp0KjCYPAM_-N5FH4iQNMZBxuNxdVYP265dN6TJb3fORzR08f79ZrEWwcuvvtJ5mVVFv90DATBwOJA61dMPv9mubrrWD86TVq4PErAY2dXlFQtn1thiZKsqeLffrGNMQ9crZZvdZjSqFFFi0SYHZogpJbHWhBBBE_ugleYYRASRssmR0sbkWXCBmcr5hEMEADIm_R0H8vD2Kq2jCywsKFprUBiHHlCQ6AAUIkWHfjZElhQQIKVg65GQkugQEFmMzYQjISVJQMQsyppDc41QUCR5B0QMnFxMbrBFSUhgFH3tiyMRSSmBJATgGOBAqhQQRUQkKaIi-FqeRSyAB-o-KhBgSUppNPrAt2dhDpGIAABQyOQcJA2OQ4xDDCIJchBfVmVuC1A09H0aHGnI6golcUIOYIp6dbVp7jbZRHXtvpqMDwYFk9vJyQkzuq4titw73y33trCZMTGEzc1dWddk7dDsiVSWW47JGJ06rw4NmcQHOxhqRIADbpUUKq1S5EOcRxAkeQEGFk4RjSWlIUUikRAUIbCIJBBhETjgPengT4gKCUViN4Ac7mQOfz3hMAgLxCCcAAkSIyBzTCGRyTklJEUaBYHwAI4SVAiIkBLg4XVqFpYUDy0F4EiKJAZUiqM_FBG0togSvVNWG4DYtTF0Ni-JMMaIWhGScBLXGrJhcD4EYwtATNFH79zQt7uti5G0dc4DkVKUaYWAfYy5UeyZFAXgzgVgadre-2C06YPfb1ulVNME13M1Mkp0DKnrIzBf32y6vUu9367aEHjVDy_vdjfLbUrpZDq5d3H84ouXAHI0nR8befduI5ko4JPRVNDuF7tXN4vL1SqFcLcdQKmyqH3v1stN3_f93o-hmJ8dP3ry4HSaX75cQ_JWSFiszav5KA2h3XZK68ToXFzd7o9PJrc3u6YJti4m02lm1Zev3yXmXeduF9t15-ans-N7x5Nx9vLNtu8cUty3PiWI0td1uWo7MTwfV103BM-Pz4-iF7JVf9ffLjbXN_tRnd8_Om6368Bye7t6__HZP_6j3ysz-vLF1ZOHZ7NJ9eTJvevF7tXVonVeYtzu29F8ejKbYkwmU7Ed1m1fVLlLabNpyNpRXdVF0TSNG4bVeqORHt47SyzGqDc3dy7G29W6rOrNZk8ZguMvXrw1hf3Vq5tFs9_tG1aw7Qc7Kppt4xJnVbnatOcX8_Vqt9rs61EByvTBJ4EQohuCd3HX930fZ7NZ23e7tmWR52_uCqsOGx5Uut13kaCcZHe3m-2-oTyPxMvlFlFA4GqxjZwYsBv8Zr07uTjqejf4uFrtQGsGYZHg_dD7FCNgTAKgKbqggFL0HGPb9wwMnDQIc-93W0hBV2p7s4zeFaOsrOu-3cW-JWSjlOvaPMs5DAfzejGZuKYT4nI00oaq6WhyMg8-xBB822e2IEJhRIK8rowxw344PZ_HCFmmppOxQnry0ftd8HWRNZvV6dlZCn46nZBSi8Xu-GSuM3r52StUBALb7Y6wDCkURb5tunFdDz4-fHS2W-73Tdt7f3E-vd55PziWFCX6FNum19qkyEfTo27otVHTerzd7-b1BMC8u70VpKKqirqa1kXn43K52fc9ErZDeHx2vts3IcYBGC3GIanEZVnkucmtqcrcpbTfNkaRd3Hz-i7E9PqLd44l-Dia1ENsu0Uqq9K5ftgGW5YKQnPbbq-ag5ctudB2bVXVoPOsPJUIRlVKG5XZk4sHqtDz81MwRlBXR5NyVBzNjiyZsSl3_RYMjSfFdDa79-BJZMbEmbLRB7drfddnhW22vdEEQn3bLXddXebj6TgF3_bdbHbMnOZnp6j1o48eOp9Y-OLxA0lJU9Z73jf768Xm-u3qbrG6vdl89eJ1F9xklD1-76FG6hs_HWWzskwudOvderGOjlFhmRU3N9sPvvtke7cDrT56-mhxvTudjaPI7bbtYr_ndH19OzudJPFn906Uyeq6bju_XrVVZZ6-Nw9vN-ttP9aICu-dTCaZ-cd_8MNHR0fGYKGVhDR0-3o8bpreefbJF8au950PyZgsL8rJrB5aZ5WySle5vXdxwi7cLe7qUaEVGa3atq_rKsbgg48-ApG1JsQkCEWe1XnRdb2PYdvtvUAEGNWjwJwbUxfl0HQSEiH0rSMLREhKGat8TA_uzR89OPv208eTOi-KcnDuf_qLv3l1c7fate89ea_M7UffenZ2OospjqeT-clEZ2Zw6fLd1dnF8fMvXz9-cN9kZlSO-sHPJiOFKgZW2hwfHeV5_js__L2HD05_87e_-9s_-tbJ-ZEpMpXpv_75r__sJ5-9en292nZFjs3QCcQYU0zRaEOoH79_Hx3WVVlWYwGZHVd1MaaMOMWr22WR2V3nZmX9wx_88Ktffm6A8krvN30IIc-KP_zDH__Bb3zr7OIEje7T8Cd__rfXV3fbVbvddqfnM9fHspyenh8HF3noj05n85OzfbO-vbvarVcCYrNss9wiYob29vWLu7vbohrPT47-D_-X_92U9E9--pWP7heffamsHQJfvX25uLoB1mfffe_zf_8nWlsBKatRCEFpmo4mu81aaaMKu7tdcExMoHSm8keGNGhCTkTQdX1ksMVofHHGybWLRQwuuWSyEiUCIQOpvAxDj4BaGa01ggBT38UH3_uugnp2aPce2niAAjEhGUkCWikQXRQxBCEEASQthyajJk5MCKgICAAppUSkRPjrp0IUH8loYUEBAARS-HXDgCElQeB4MAoLASAejB5a5EAcIkIkIiSUGBRpBKFDTZUFiZDh-PGDfr2PnROGFCMiDm0zOj7i0LvWmcxIcgcGu7UZe8fRg4iyWRqCpOC3Sxh6rdi5IbhOYuz3O9RaW2UU2UwjSF5VfuhT76JLfvBaURK2Zc5Joo9DO2ildVaFvo9-yHIz7FvhGILnlICka3fdrh2dTF3X9bsmL6rYtc1mk0JM3hXjmSB67_a7RqEUZam0OngTFGlUSFpVo0nXtKJ0lhfttpnev-DeodLiBgTh4HSW-Ziyahy8nx4fyaGvnGUmL7p2yKsSkJIkRSpE1kZxCogYXdBlEXwQBAHQiGiMb_cqsxAFCYUYBVBQkggHW9YiIByEgWMAkOQjKvV3Pjjk4CnLIEYEgZhSiiazWikGCbstGquIADGmqLQGYCIlgUkREHJMqEiEtTEiiZOQykAREnBipTWQ4pgOJFlCjCkBosoriYFQEAEQEBFBlDUcElnNwnmWJd9Xde72fYxuOp4iki3s0DaC5PcNJFAasklFJMfnx5Pj8fXbW7JZdF5pgyBFXqKkIit2691uvUFUk5OJ7zqts6IY2ZwAMMvzbrNnSJAYSSGCzTOJiX06WPBARBmCwJKABEWAo5BSIiKHsZuZAIjw61UGaVbAMVprOXhkQE3MEVIkYwBEOIHWSisOCUgBidGkFCKjMkZZLcIcg7YGRDAx_B3Kh5NDbeFrDJMgEhoCERTgGBCBkCRGUIxJtC2EBVJU2hz02ykJKiAywung67A6AxAC1IiKwA0DynBQ8okwghBQ8IMIBY5k9OCjNkpSCDEJgHdea8sMKADEClEia51tmw6JLqZjH5EMGlJDCBYIkGaTkQ9BawgRJlVuFGtUJ0flduc_-uY9qgwMuFqFosrKWR45IOB-vY7effHllVKQFUqi--Ll5cD8wbcf37s3vl62CouH908g0a5389P6opq8_-TiOx8_--C9-2VJ15fL9XozuFRrXU1GoU1h1y032_nReL_o61pFx23bGtLNauuG6AfnQnCNCyE8OJ9Ho_MiF4LVevX5y8ve-_P7F7Nx_cHHD_7BP_3hyy-u37xZhjZYS6Np9fbtIpFQaYGlHVzSuFl0tTV37f7sZJ7VhZlNamGy0HtXl3o6Gbd9531yYfj4g0c__M7Hb1-_-7d_-cnvfevp3XJbVsWnL17_5Fcvl6utC1yM8r53rvdt2y-b7tdfvXq72tiiUCYb35vvFjtjrC1KY_ME3Hft-dF8Uhb3TmbW2qLUuirW640X3Db9m9fX681Q1NWorje9_-LVu8vrG5vnlzcrx_zqzVXT-l3TeNcv7rah903vE8rl7cr3QRRlhXEhrLab0aS-vFtNpnVM8OkvvhrV-TAEoyW3dr3ZEeDQO-cjANzcbpvO7_e7u8Xah-RimozGm13b7rswDO1-2O8aYQlDSMLL9aosir5rMqViimSJY1Qg49GYgRBEa-LoV3e3Yeirohj2blSXQ9_HLuZZnlK33wzeD4DEzM1qoxE4pn7fEAijSIzBBwBBULP7MwzJ-wSYICGR7na7alxmRaaLotvukTkxZHU-Pj7aLdbT-fTR_YerxfL9Dx7EoT8-Onn-xYt7F_fKPOMUr95d3X_w4Prt1YMH53mRpxCOT0-KPG-7PgQngiH0Bqjv2pPTGeWaU2TvQxLU-PryUrwyihJBBIieR2VVlkWMfnm3Qi3a6rqogNkPYd81zrVa4c31XZabxBwRnjx5XGd2Ohk3Tde23WKz1KT2fS8iF_PJNx8_7UNwoiCQIsVeNsv9yfH8btPkRoMw-FBaM5tmKbELiZ1kpdm9XcWh0wTDusWEzgXNnLph6Nuw7iAG126azXqzerdvbrIJ-7BTVry49d3dfrurx6PedyNT7labNDiJbnF3xylWVTmpRyy82q1OptPp7Ojx-89m43GmTV1kVulH9y_yohhPR8CQa5iO6-BiUeRKK8VpNptK5wlplhd-GDJtgGPTOUImo7Wi2bj-9reefvzBw0cPjr755EEppBHRhdm0uHf_9OHD05PjKQlhQfmsOpmNt7v9xcWRMjol-N3f_s50Mi5QXxyPdWbI6MvVavF2SWCv3i2c4-WqCV1ESedH9dG0flyaB5Pyw8n8-U3TK_vxxfzD86PvPDz_-MmjQpEyRgNcLjZ__bPP88oKqBSlrvOTsyPmKCSrptk2_Wa32212AJwZbRSNq3Iyqau6mIwqZNCKCFVMsXV-1wzbfcfI-3Zg4SzLo4uHOXnbd2VZiZI-ek6AEvNcHc1GKXJVFbm1eWZyaznFB2fHHzy8_-HDk0f3js4mowKVyu3Pv3z5k89ertfbDz58Zk2x37eL_fZu3f7t3_7q85dXby9Xm20XY9qt94vrWwvYtc14XLlm2K93wxBGZf5Hv_ut-fT4o6ePP_7o2YOzo2fPHhnL43HVh9hy_5_-6qc__-SLty9u2m6oR0VWmdyYu5vl8mbXd93kZFRY0y72dZWhiHdBhIdumM5zTml1t9DWrJer1aYZ1waBMKXF3R0gTHLDkP7bP_7Db33w6NsfPKqzzIN89eL1J198_suffNWs276NFw_OtdVapNn7b3_v2b3zycV797765fNuGFDbtmudG5pmKIu87Z02Jsvszdu3ZVkXWf0b3_nwd3_re83d7pe__HKz358-vP_l58-3m836-iYM_tF3nikOrz_5hSKtUfXtMHS9gIzHx0O31coYrYUjpYiUABiJUt-bolSEMQYhNZlPdF5P758qie16k4b-AEyX6AASAAlqXefsoyJkVHFwaK0uyvnTi365QTh_8jWTBwWZhZkUgtKchLRlTpgXkALEhERAihAwpgQJkZBFJKKxkqIISEqIAgFQISYBECABEVSKo1CWCwIII0DyiawhbcPQkyb2QRUlAsYYgZQAKGNJqxg8kSJmCcHkefAOlEZC1Npv2-r0eNi2ytjAbKtK2YIhAf7_ePqzJ7uyLD8TW2tPZ76T-_XZAQcQAGLIyIzMyqzsqiKLVd0kS80204NobdYmU_-BepNEsy41yaaoJtksFmvMITIGIBAAHD7d-cxnD2vp4UYJT_4Cczf3c9z3Xuv3-z7D3gKgiiPvrHfOaKOUdE3HCEIrMz70XYfIru7CUEkjfd3JPNdJCtoIlVjnkyTRSdw3zfhwbtt66Cx50HECAMG5dDoK5KI0Gzo7Ozppq1Iw1du1ibNmvXB9H5i0kHEWDV3nSWYHU2p7MDqJ074dsnG0W251JIbWTk_Prbd28HmRekegFAUfRZHru3xc-MHutZKnV4-aqtze3F399LO3f_8b23dUbih4oiAT41Hl0yNiAAqjk5P13Y0UQseGCXUcB2_vvr_ORhoCDPsUvkT2LgSPxpDtXVWaOFFae2d56BmAEQQAEAU76CRyg5VpLk3q-gqtB_LgvYwT5x0AoDGAIjgrlAztAGHQ2vjBsiTUkY5yQvC7rcpylY2s7WkYlJZkvVSKKQADIXMgGUeAQmhDdmAiRMEEKBikokAIDEwqju2ukkoGDkIqkApRishw8L7tEYXUsUgSnY1817qmkkkSxePP_-Cf_vZv_3eh4pMnz_qms943q1VoNzRUIAzJ-PKLXzAa5EGY5Ou_-svx-fHxxYXvbbVtx7P8aH7ADmxw5WK1Wd425UaAyuM4yeNqt1MKOdD2bqEiEMBusBQgnkSEwZWVbz05n83SoW6RSXhPBK7vZKxBiP2PDJho8DJSwQWptMjGgQO5HganpYJAKAUBeO9RMGrDISACIqNQgiGEIARInXgfRBShVuQ9BSesQ2m470BLlpJD4H2tIk_BB9TR3ojExOCD2INflQEfwlChNjLOCGQIHgQIECJ4Rggu6GJCTEABhAAgIo7SkZAapWBrXdeZbJRNDq0dUOk4m_RtCwLiPPMukBRaiVGRcwgS0EjDFFSqh8ZGqTm7OI4VStTKaAp-HJmRUd-9v5ufzFjAODXOBYOoYtEPQ9cNCBRLtWuGvIhMmi7uq6Oj0aLaOOq7OtQ7N9guj411QOSlUM4Oh0cHqLGvWiKvpU5iPTmIbSPZcVrEWaykUsqRVKK3dLcribtaw6bkxLnIRLZxHMH5UfTXv7ruB3v10RkAnb443163u8Xm-GpilOkGt7hemsAnV7Pvv7l_f7uOc1lu6qvL4zhLEaDc7EycPn9x8rvfLWLjkqJQgobB1mUXGdN7r1SaRVEci7rus1jPZtmmrB6fHG02Tb3dAWKSZ0UeaamHfjg_PUqUcHb44z_4Cbjw__xf_-J__pf_aL2pA9G6t3_z2--z-fjN6-ve76cqeDAeFXmqQgiePYVplry6vhuG4UcvHl8vyqurk4Nx4QdbSO4dCQTn7LgYCeQ3i5X18LArd5tqNh6dnJ3_7uvX0_Go88NXX79JpDx_cvL61QcpVNW2wdNu152dTVMTzw6mwCEwgRBd3Umhl7uV0UqZyPsQJdl6tel7f_X4UIJYbjZ5ljNyjAJQolax0Ra47trdurG2b_pudjg1ygQbNIqqqoo884Gm4_GHD3fWOmW0Zwoh9BbG0zQQRnHy7s27g2kqUZCKgh-iRDe78uHdO-fpxY8-7fvQ99324UECGm1QEMVoq2672ubjLAwegcaj0Xq5tn2vI4MAznulIxXrruqyPLn6ycfXX7_VRu2WqzzLhBaepYx0sK7Ik7YOUW4mJwe2bk-O5kUaf3h3a7QU4JN01DYNSKWUyIpku94G66M4kpGRoHdVqaNou92tV-XQDfOLUx9sJGMfXJwX1ofNco0KIMDB2awt-__mZy--_f7BMQYJ4zz3YA2J08ODxXLtJQ6d9d6nWZpGUV01DGHP7GKENIlWuxICH85n4yy1wR6NZ7_55lZIl6ZmsysDcRpFxogXl4ckxd3Nhrx3zo8PxlLIk4vDsg3fvXpvufnumw8cZOWawXHs-eR0JlntdlU_DNlkVK22yKRiEJFWWgytVVoAYL1ubT8Qs21bnUQstUm17QchtYzMpBhHWlHAONFKxKC4Wq4DuYFodjj1RGfHJzb4o-mkrptpnjILEkGrqC3bXfD3N4tJJKbjSWO71bZE77dlU-RJlhUHsxEKMR6POg7O-txERTZXQnTdbte396vlKI_m42gyHoOOENX1h-tvXn1vtBGAf_KPf_7Nt7dvr2-yzCyvd_Pj8eOL08vL48VidXA4mUzHucDr9fa3X33f9N2L58-21RZAOhaX8-PpGOajEXpXDk2RxLGEX1-vfeCrJyNl4WbRTMbjTEffv789mhRDcJv1LjHp0WzEyHkaHYwzreXifsFBjCa5HRwg5LEBqR6dHbVldXQwJQIQbPvBDr3Wuh08ADetY0SpBAOwFIjonXfObbc1UHCMKESWZcwUPG_K2ll3enTwsNv4wTlyB-OZNEoEbPomj4z3LorNbbn55maFQWRR9PjR5W9--1WUpXU7rBeLfDrq-9ZbV9X94IYiy6q60SaaFGnTD6G3nvjwcOabdjafdF0_nRX5eLZe7qq2VFIsyqUWSbmtfOv73o9G8dXTq9vbu6DROrt8c5skRmiDKBar8uz8SAkAAbHSVqonl-dd2RKzTKRR0jkqqzpBUFGiFCOIh8Vmfnrw2dMrZh_Hpmv7EIKM1GCbP_83_wlJ6TgBwCzPv_nNKx1F0-nBJ58_HWi4e3f95pu35baZH08mhwevv3qVZkmR5wcHh6u7h9v7HSrz6GI6Hs_a1n3x84_PjkfTPP5X_8t_RYA__R__u3_9f__z1XbX1vV4PG6b-uHdW4Xct52OTDqeeOudD6PxuO4aBBnH6cHJ8c3rV1qh4Kh1W4EEASggMUkVqzgJrs-nIxTcbSvnhna5jNIUggiBQAYmwRpFkH5whCi0jBKho6xuB5MlT55_JKGY7YeXgAQCYB_sIQYUe9YnIgqlAYmckzoKzgupGJFsI4QERmAGbfbpZIliL03c_2NiJGQmFIKBGCD4gMDMJKT2PmglERj-AQYKuE8mADAzeWZi7yE4IYQfnNCSnd_Hh4J1iPsOMUghGdn7IAB0pG1V6ShGBABCYIFCMgfnhRTSxAE8dR0g-qZF8uStThR5DwzIFIgYfZTEZD0R91WldMRAXecAAhPrOPLOEoFQSkgZ7GAibbvWE1fbhTJ6bzGO0tQPA_VdMioQ1dCU3lnnrDRSx7JeliTIaDO0PSOzD0IpDqwiLZUKRCGAEMCIJk6z0ajve-tICEBptuuN7TtAYvIspZRSxWkgzkcHTV0xeqWjtm6Dh_HBXGnJIUyPjtptmeQZUEApiLyUil0g9lJpFEQDaSmFUAAYQkAOwAREQqkw9FJF5ANIwcL4wSm1p3TSfp0T3D-UB5Q2SgUfkEnpiL1XCN5ZoZSIUt_35AepDCAT_xAhA0QhJAqNSgUXtDHkHAoh9iVgASGQ-KE8C-RIIEpjyDuBgigAEaCgEFCgRBBCokAKnpiSopBaA6Lrh7p-uHz2o9Xizg09mpgYlVLeD96TUSwjsVs-RONJkJG37tEnH_XNsq36fH5gBPVNvV3XcZoaoZI0sdZ1ZaslIoa-qqTWQsg4SnUSUaC-HeIk1pExRrhyIBeklsk47epOEJgsGZoB1F4PJpgY8Id0k5RSMggliYn8gNowAQLvN2B7HJbSMgwDKtwP3ZmQmaSJBIK3FolRIpNnQgCUJnLDABwQEQAFgxAKUAghQiBih0IgqrDP_AAhAAcCFEIYFIGIkEHqiIiAiCGAEIIIlURGpTUxBRcU8t6zw1IyBZNOEKy3XiA5b0EKcoNRUUC0wQuBwXkTmySJbD8oiVopChAlxrmAgptqyIqRUFIg2t6aSLc-CIWVc1meNu2AIEd5wj44S4Hdbd9GDLExIYhJmma5iRmPiuwgKpqyf3wxlQ5BiWdPz9ZVn2fGeopMLI2uqyrP8qqs6iqQFcH50XEKLG42VZImO9d-dXf_m2_fDE11t3ayIcnh0XykjGbDTWtXLgCq0-PZrChs1zfb4fdOj08uDqc6zTFOdaIZHj099xZaG44vDseT8aOLEwrh8GB6fHFmTPTHf_Lzv_yrr4m9kEohBheiyARPtvcmMXEsIHAUq5bsixfnTdU-VB0qYfseBJ4eHRiD-dFcDL3WQgt5OE4_e_GRa9uvv3v3xedXnnEg-n__h7_9i7_7tia-fdg0vu-aNiCIyBxdHn37-t3tclm1jQ-EyA-r3S9_-jIrisPZ5Pb2YbVpVqttZ0MP1A7D63c3o1FWtc2_-U-_uVuu40ne9UPVdUrh6fz83c3t1dnxYruenpz89X_53ZPLy7Iro8j0Plw8P1GgPntxtWtr72C1qZI8XW1267La7ZrDg1ms4tWqEojjSV5kkUD95t21974Y5b3z09kBgXDWEQrrQlm1B9O8OBi9f_VhaHup5dANOta9c2Xdd11fVi2R03G0XK4FgWcnBBqjBjdIoVbf38qIFEoWMrD3re2rxg1dnMUIwnluu873uzzLiHnw3e6hzKaF4OAG27dDQG52TZwkSRYncTJYK5SyvRVSZnkCKG1vUantw_3s6Gj18JBnGQiwXa-lGhVZXdV5nhmp8iwxyJE2tusuHp9RIBSolMzzpEjT8WxUlRUgf_HFj9uqms6KdDTe7ra9c1GUFKOsbTqljPM2ErKsWuutaxsTSSH0xeXZerVbrqqu6wIHAGbn2rJPTbJZbUfj2WK5lEr6QOtF-ejiNImTJM2dJ6mlII6yLDZqOpn2ffuwLt9el8fzYj4pFFEI2Ds7G-dAFJy_W1d3d-vNrlqut6DVd-9v-56U0Iv7TSLF3fttQDKpOHh8IjubKrVcrNiFAaxAFgpmB-NdubFKPdytbI1t2Qqls3yukgiFnJ7MRsWoq1slhUCeHc8uPj6X0pycnEzG4xdPP-qcnxXFwdE8IB8czsaToiqrarfrunK3qx_WpVIqLbI4NWXbKcVZEo1j_cmjk4PD6XicjfPs-csnjy_PLs5Pzy_OpocTGSdJFG3L8puvX9d9EzwrJdt-N_SdiARhWC2Xv3l9u935d29v1ovNw2IXj5KPn14hyrff30dGHUxGvrF_9s9_EQEUSaQkRFGsItM1_f2y3G12o8SkWfTo9OjN9d0Xzy4H3z86KqQwbgjWc2vhbtd8f1d93WzCED5cr_-PX735_mEVXPjtzf227kKg1oXj0yOpZLnZHozGL6_Or84PbOe2ZVe13Tg301GxXG-uzo_n03EkOItjo4QSSIEoeOvD4EJZt45YCgVSEoL1gTyxp7YbBKO3MJrlRkfOMXDo2502ZprHk1FuJBZ5Xoyy0WikpUwiHccmjk3t7aLsHrbl4mE3ipPzk5Oq7Rf3901tHTiluB384mHXdRZBBEJrfVOW9bYTSi1Xu652ly-O0snoNMufPrv4_u1NYLHalNtds6jL1WK5q-rdpredMzo5f3IKYIWS3331mqRq1tsk077tpdQyTlzw0-MjgaGYjmJjRkVxODlwXdcNfTd0gIBGrZarwJBExkjx8vnV0LaPH12cHo6Gfuhb1w0e0uTD7cN__Mtf__ZXb3wfpkeHcSzub7YPdwsP9OzlVZYmWpuvf_tqt6yCd1JKIZWzLk6TJI6846bu6107nc3-r__jn_oBVKSvrk6Oj6bv3j_8q__lry6fnD__8bN_9__683K3q7ZbgNA1tes6YyR5p6VEofq2FfvqHQQVJ5GJx4dT73oaBhChbUrBTI7IeyEUSjWezZWROkm97Tc3S5QETCgVKuEYdJoGIQXqNB-1q02UZ9nJgY600Mb2bnx0OJ1MIXgJ2RQECCmBCRmBGBGRCZUiZmASyMwSERGR7aDTmCkIbciSlLCXC_2gDgjMwECAwCgVBS-kAAYQIIQkZiIWWgGgABIogQglcggcAgb6QSjmAiJrEzMQIrBzQiA4J6OEgwdgHWtvLVEAH8gHlLiXkSmBRC60LngnpCAiZg7WCSVd3zOzSSKyFjlAIAEU_MDsAIAZs_FB6Cshod-VQhlillqBtwolC47iJE4ipZUdhqhIw-BUHEexNtoMfcXeKSmIne97IpcdzpG57xpkpr4HrYUAkxjwHphAyrauECge5eQYhTTamCiKitQ6K5MIEKUWUoAfelRSJSZYX27WwVnCoLQeHUwxSkbTw2ZbKqlCcDJKiCBKYhMnLJTWwkSpiZJuaHUUgRAmTSWKcvWglQreuX7g4JWUUhtne3AkAJWQzjkhEZHJu-ADKsnEUgimAVEE51Wa6Sj25IGYg0cpyQciLyWSDzw4UMKYxPUOBCED0T4uDoioswyJRWQE4r5xgkKCdwIA5D78IoIjEALlfvYvhRQcAqKQOmJgKTB4J4RkQNjnzVAAE_7DM6akJOfZOQjB-aCynKxLkqwbbN3ssnyKgMTonJVKRmnBDjhw8G5yOIdAjAZUtPrwYf74qRta8iFYlxTZeDqp6m0UKSVxdDT3Q7D9MLSVMbouSyGUjiOUilnoNMmn42AtOXKD21_hUAgTRUMzEBFTCM6jACJm7wRQcB4RxA_fEgAACIEBhTRAYY9mAh8YCKUCAAoMxEIoYKYQhARihUAMzIGC9dKkzIQCBGKggAhSKHYW9z6L_cvS9ygFomChABiIpQIMgTyhYgQJwZMjwoBCS4kcglCaKaDtBHMARoFCCA6EgQQKgSy16MudSWMhZQiDRDGUDUqI81E_tIBojNTKuMF6O-TFuN1Vtu_TcT44b_sBAUKw1gX_Q8WIO-fvl5u-s6tttXFdrI0d_DhPkyjKIjPPi2rTjIv06vygs3612c0OptuyXCy3b67vZ5ORJ1VkUVGkySRnwRQoiqTWOo2MktIonEzzWMvxOMkyE3pXWb9b75ab8v5-vW0ddn4yGafT7Ox4Fif5clnVnaPBb-83n3x0vLndbB623766iUCFqv_k6Vkz8LfXt6um_933r5wPX_72dd02QqmqatfbrQjU2DBOk_v7Zb0rm1375Gq-ftiV5U5CuN10Ria__08-_5M_-xmQhsCD5bOj_LOnl29e348TdZAkrupHWT6Zxutl_fRy_oe_eP7dNzdtbf_0H__k5dNzDOH_-Psvj48P8jR1Iby_r9_dLprgO--VMavFamjqNMs-urz49a--WiyWbK1R-NHTx31vX1ycpVlyu1jvdtVA3Lpuu905pLfvPjzcr_u-V0pVvZ3P5-8Wq67p18vN3WK5q7pyt9OxvFtupJD1rjw5me6W265zxXSild6tmrKs1uttXdZKQwg0eG_JSSkVcIyCGRG53NaCIcuSh-XKd8NqtQNEAuidZQzbslyu1u9u7vM8bpv2-nrh3BB8kEI1Xa9jvVptduu1UczEHjkgEvuu7wKxirQ2su27pqySQvnBySjq-sEYlOTID9WudIPXyoBRdhj6sgKCsuqNlDKJ2A3NtgoMgYP3FBdJCMF7D8gqNZaC0krHsVKGQag4Iu_YB0A_G0-YQtO4yfjgxU8__vDm7enZyShPYiPO5_MI8fT06Pmzq76pR3lyfnJy9dHlrJheX99GcfzFz78wggFxs6vH43E-LjabigD3HvO2rplpu9kWk0maZ-vtRkVRFMVPn168-va7YVU-LO8jIdpmcCFkWTqej2NlXNcLJYSSfdUNQ_f40eVX37w-Oj1WSkqldtvdbFYsFkstZTO0SpnxeHxyPqua7uT0JM3M2dHBaDQyRp8fz7uuPz-cAXl2IYmi1WZ3eXpsm37om6psHhbbixenh0ejcldtbsu-GwRzOhkLoqHtNcq2sUxhOsrrVW2As0zKXhLTrq8lgFBkg_WI8-eP8qKI4qhryvv3y9WHu4eb23fv3i03N_cPC-eHt9fvW9vcrhbeuyLPmrYTqD779MmH62WzK-8_LN5-9_71d9flptk0zXJb_ermerGpOu-9xNu7Vdn3LGQzdE7zu7fXbP1yWR7Mp1mRFfOxyKFp6uVq5YgCe98MWZ4czdLdclvVu2efPC23tfduvdglRv3xH_388fnk0dVZnkanJzOVRsZEm7IkpiKNlBLFKJlMcm1ixwMbLRWM0ixKpO1tFKuHahej-O56883Xtw8323EeZWnWlO1sms9GxfG0mOWxDrTbVMrwerX96efPPzqbf_iwOpoW5_PDo1H-2fPLaV6kkfn4yYUWApkxkIwEsijr1jkXxTEge8911TKgD4EQ55O86jqFqI1GlI7ocDoZgi1mhQGIIpOPxllqUKoQWEhQRlZdt6ya1Xp3ty2_u75_WJVV2W2r-uBgfHu36yxVTWutvXp5UVdd39K2a4WJXOjTJF6st13bR0YLUPPjOQd3djWLtYjS6PrVcr1Zf_X6erPegkDyvFpsXdfHReoHN5oWtu0D-eXdqqu7JDbeuSRLd9uKAyR5kc3Go8PDwTF6VhKEdT7wo_PTqqyst8UoUcZQ4Pl41pM7O5rVXVlvWhnLsm5MbDbrLYFkKY_Pxv_mf_2Lcr3zvj86nzV1u77bIoNS-qMX5-Ozqe1ClEbL-_uhqcpdGQIRgQDUWkshJrPJwfy4GGXHF6ePX56-en19825RTLKj-bRc7_7mr78-uZwih9_87a-Hwa2XGxQiBAqOgakoRr53wVopILgglUEppZZSGxdodFCs7xbtpmQEDiSERCkZ0KQjZSJru8F5k5mhbtgPkTFKaQbwNgAKnaZaRsXFRfPwEOdpOp_0ZV9MC088ns0OT443N-vTk5mEpAAEZEAJKBAIBAKiYAZpDO_LmETKxLDXHHrHAWWSAARiEsREBMxCSfj_i8CYODAjIgDvO1BMLAWQRxJCSSGE0ioEICZkUkoyB2JgIKGUkOh7K03ECOCDEEDMTIERkACFACYIQUVKag0I7Cmajvu7e9QGhUABYRhkZJCZyAVrgYPrWwEQrPdESCy1BCDXtVpHgZzvKvbOdV2UplJpcoG8C3YAEF3dA5KJIkaAQN5aYZSKDDILrYemU0oxka1rAIi1DoON4xjID3WljAQO1joQ6AefH836sgzsfe-iJA5ACKSM9MQAYIdBGeOsExTYeYnQ7lqBApj9MFSrB5PlwTkZmzTLmPnw7NwkERM650yUBO9RgDFx37dCIHOI0hgD2sEGDlES921vu1agYA57UqqUUpnIByeVgt6BwECERgXvhZICGBkQkD2hEgBEzkVpTh6UlsE770gZKbUOgzNxCsGT9zI1UkBwTii1J0kiABIzEgUPAJGJgg_BDrgPyDOQD0Jq8l7lsR96wcBESZr64JWWzEAhIAIhAhEgIhMAMjHK_ThcQCCgwAxSm71OmCnI2ATriIJAGVCQCLvdWigRJVHA4KybnV6Sb4SKhr4PjhlComQYBt_VJomJyVs_9M62Xeg6NwyAKFAU41FcZLvFxsQyznM_ODc47wIDx0nmOxsVWd_02ogoi7pdpXQU5YltOhDCRCadTW3TCImIACEIYKkEE_-gQEYkZgmsjWFAZBYSBQIT_vBqCIEAFAiJlJLBEQgCKdkTCkQU5AcdGw6gjAaBfrBCIoWAiIECBwAhUUvwgYmllAIFShXqFrVWai8wAgCQEtgTIiIKIRU5p43GQBw8-SCFZgYh96uzfYMZ4iy1XUs-KCW1joBC3_Uc-vFoTsEOrUONUojgSAhhIl3VnZKaBHVd7wYXfHDBAbA2um2HpunTNBYKktggMwFEUiECeS8Bq7Z9fnHc95YJWuutH9qmzWK1WOwencyn4-LZs6OnZ7N2COW6BYGRUtuqiUBL4FFqplni-iFJ5eHBeLFuFpV1LuQaEeh2WX365NBE5mA-0hLX611gAi1Go3Gax3Kkvvzdbbd1gMFM5Bd_8kk6ire7hnyfTsx2vdKoq9VGSmEtOWdPHs-t8xTo7PIUCYK3sdKo1LOrl8_Pxz_77MXlyfRf_MmPjsZpGqBb1o9n6eeXRy8v5gfT2WbVfP3VjbMBkE2kB-9jlP_0f_rn7n73_eu78-Ppn_43PzrMs9XD9vpuvW7rH798VrVNN4Rf_fabxcNaRloZLRB8PzysqtP5eFbkEvGLjy6fX5w8OzvN4ziKk_Vq-__4d3_BRK2Am-Xu9fc3vQ112T-sVoxgXXjYNFLoqqu6ofM-NLW9uDyRSlZNvasbk8Rt09wttsVkNJ5N2rZLs_jy_OD8fNr0rWfqXdiVNUjRtu1yUyO46XyKAjGVTV1naTQ5nz_cP2zWlYq0D2HyeNo2_WCHofMUAqCYzhLy9uFhqwxMjw-2mxIFe2d3i3Vft-M86XvrAziU7TBAoIfbzfz8uNzUfVV7ZnYeAwTi4IdyV0olurI5mx_uqhqFiJO47ixZOz7IkPH46bGtOhGrdlXHRkkhKHCUGaVF7wcllJCCAF3vVBRJuReTiHK5oOAV4Pzw6OlPfrK6_pBNCyOpXG9ffP4xQDi7OF3frj_55KPHj88B6HCSayV_8fuftZtNu9ntfb2f_ui5XW_Sothtt5tdycS__fVXznJA6FuHTElmEGiwru1su6uNltW2jCOzXW6HtgkhTI5HZdVNTw9nk_H7Nx_mJ_P37z4oqUIAFDwZ5ZGK2mb39KOP7u5uh649nM0lhOfHJyKK-66ZHRzYwduhr9uuqurBdQpkOQwE4fnZScT0yZML8OFgNhNS5aO0dHw0zvvOa0NplhOFmzfLtrJJoq1rCfy2Lk2ejQ7Gl59cgY711ChlwOjkj_-Rf7jTozROzaPn5-lREcep80EZo03kW189bEgIan0ca676bJwYE6koOj8_nR7OTi8u-r6ejXIG_v777733hGqxri6encej6GA-G4bhycvLqirX2xIFLO-XMUDv3HKxqdrqu1fvrl_dLO42u4dqu2kcoU5QRuZ-Ve025Zsv39--XVRdE4_jN1-9s32YFJlzZIP_8t0t9n2ixRc_evb5J89mo-Lmw91i3aLg33x78_5m87tX799e3_3m9duv37zd7dqy7qqmOzk_zvLIROZifswsWOq_-_L17968__WX733fe6LxSB8fp7_4xy8mRRE8n0xHH390WeTZq1c3bT-sFmUg-r0_ev7Ljz_p1lty_WcfPZpmKQQSgiOjfAhiH5gIwWgdmLqm7wbnXJBKda3d1U0IQAJByeV6m8SmaQdiynTkmDSyB6x2u751bH2cm66zQsqqGRbbXTM4y_zq3d12VcrMDI2TUiVpeng4sgFu7zchQN3WpojqslyW3Tevrqtm6BubRDq0fRTFwQfrXZFGRqFWIk110wxD6Yae7z6sGYK3PhmpzKTdYFFq6-HR00ck9HpZtlWtUCJxWzc-OCVB6MQ6iwDZOPNeGGMgkJHieFZ8-vzs9HCexPG7-5sP9w8L3zVVPZ1OlpsaIRiln1zMBYqTw6PB2ovTUyIez2Zt1b3-7u2rLz90TQ-Mh8eTpg2ru-Zn_-jTpumqXT_0vLjdmjiul4v1zXLonEDx6Omjl58__-03f5fmkx9__BlqM56kNx8e2l3ZbMv7RTU7nFx99rypuijNy-3m8PR4_XDXNu3N2xsXgpCyq0sItl6s6_VOCwo2ELEPHKVptd5mk8n5sxfUdcFzvVyjlMG7eGz61vkezHgURWkURyqOjEIC7stSSdZx0lVDlOXJeDy6eubrxhhV3i5UrOJiFAJ_8pPPduttNplIpbfr-tmLy-RwJnE03Z-ZEIA9MbBAAcSAILVmJvYBEVFrItiHCgSK4D0CkgtMQUglGFGJPYSevZdSMjDKPZsFIATEPRAdpTZCytB1wKCKItie_Q8xD2L4AY1CHoVAKZmCEAJCQAApJcIPhgFyAw0ehRByf3UIvu6ZWSohpSJnpVYoBBIHb9kHwV5KAOYQPAuJQEIr17cS2bWtEsAUaLBSawpOoFRxwsFCIAE8Pjpk8t4FExs_DMF6k0btthVKkHci9M3qrl7cO-fCHnVqBxPrZrMOIfi-zw8OAw1EpKVyXeOHPkqTZJT4IeyZLX3XKqOIKHQ9MQvnpUY3DMBo4kgp4VwvQOTT2VDu4ihp2np798CShsGzwKOnVxRQCkWOEbkpt1Gc9U0fPJsoAwGIIjLR0A19NyB7JSQNg9Dadj17m2STEKy3lgGQiJwVWiFQcA48AQdEIVCStwIJHTnb63gUnFVJGgggABIw0N7TzAHIORYopCLnhZJ7eQCTgxAQOPRDAJbGgJTsg4yz4ByKvb1FAbHUWgBQCCiFSYztew5BRRqIef_IWS-kFEIhsQAWe5UwMArhBy-MQEQlFRCRc0JH1nqhtdRmfDhPi6xvqixL89Gh0LpvdsXhSTSd9WWlkH1bD31__uyq3tTW-Sw_8XUlBUPfEAgjjU6SoW0HN4ymsyRKq7JWWotAWZbERSIQiQIzeU9d50BIBmGSJJuNm9VWxdqYuK07gWxMJJApBCSQQvA_dIIBBXBAKdFZYpRa-6Ejgj0rCAHZB1CKQpBCQCAiJ5SmEBCl1FowA6DS0veD1IIIVRwDh321IBCDRKGjvTgZidAHZTQIFgAgRegGMEKBpP1SbLAqMnvTA6IgCgKY94s-FAIlMwOQAMTgaOgZ2Q-9Usb3Q-gHQExGU0F-aBoODoGViv6hywHOu0CstWAmH7yQchhc6B0wWe_jPFVadk2rjQq9CwI6x005fHQxtv1gLW3bXkqVpZkwQqIUIAXj4ycn1abOkmSPGhsVedv74MJRnjd1nUqVRNHhdHQ5mxSRjKS6L60k1EabWD15fDKJtVQ6z7LHhxMGlMhCcZakUohPf3a43HbNrpToZkn2-JOjsrPnTxLN_vrLa9qGV9_ffHPzsLje9E3LzgXi08vTPIul0UaISMjD6WiiRVvuco0__-zpp4-OI7v7-vX3Q9PdL0pJ4SjPbhbbQupqgF3rW-v-_qu3RO78fPrTn77YLHd_8k9_ngk1n47vX72OI_mHP__R2XSmJCDyetv0Xf3py6vgw3JR9sHfb7Yq0tuyHY3zWIqn58c__8nLJ2fHWaSPT6bTPH1Y7majLM-Srz_cl3V99fxsMhvf367evbtPohgCQAgIen40cyxevjh_dDLv2uGXX3z8u2_fN-R88DGa4L1WBoCtta4NZdlqQUIE6PnmYc0SnIPNumFngw3kQQDGiEkcxYjfv1uul7VRchjsZrlab-rtrpvOs2Y72MG5uu03Fdm-3NRd20Lny-0uWNbatE3ne4cCIyPb1p9fnnRNr-LYUhiaJnR9rFApLaXAoR36TmtcrUudpjKOqK4yI-q6lgrrtget0nG2vNtOiqzelMbormyjRNRN15SlEmybXidJfJAjs-s630DwTghhe39wMOu3lRByPMmlkoGCIJIadRTdX9_80f_pT0_nR23VPnlyBaFtBnx-efqHv_zpQZIkWkdKFHk-KtK-6eu2e3Z1niTx5dXJ6y9fnRzNH5bbN2_eKyXytJjOpq--e3f58mp7vwzeDc2AQhMHIxWSS5LYuX5oumwUD13vbdCxSdKkWq-3i834YFyuSqaBGEwcv79beIbp0dHDw8PNh-vAXDbd9e1dHCWMmESRVvJ3X337_e19X_dNWZ7NJn_711-dXp2ut7sPi4fvbjeffXS5LhuHIUui46PJ8WwyPciP5rNnLy5rF7IoGU_T3Cglg5ai6fpslLmeuqpqq3Z9t2p2ZRpHu_sNA2ZV05ctGPPTP_n51__hV3bbD13td72rWnTD4XQkQCiQ48N8Nj-bHs4uHp-fnlxsNpVztq2q6w_Xs5PjbTWcnl9-8aPPEKOh79zQbzbb7Wb7cHMPgJvVTgpUiOWmlERtZ5WDpu1c1XVlMx4nj54e6ZkRqC4_nrqWPry7VwrSWIL3s8PMNnZ1u55MDqSIUECaT0aj7P_2L__7x4_nnzy7Wi53trPamMiYw-MjZUyeps-enj06n84Pis-env7Bj188PTuKJXxY7L56f_ftdw_L-92339-B650P3obTw-lsnhdFcbcuT4_nZdd_99XD7e2ualrtcdc0bdUeTmbnxwdXV8d_-JOXdlmHrp3E8cunj8ZpLBGySKVZ4gNv605pEWkjEAIFZKx7m6YpS0QhmrbzDJ6ZEchRliX7EZKW2vkQAo0n-a7vsiSSKLRUTT3oOPJEi_uy6vtYGwHgbPCB76-3cay01st11XQtAm63rbU2yqK66cuqQ-_Wu0WRJB76LEuXy61JNUuZxjkykpfsYLEqBQkhsa2bKFFFHgdi13FXDTT4yKjYqGGom27QCoIPYLh4crS9va3rjdHR6CidHIy7ypfr8tmLJ0QhEqrt2jyLXOB3D0twdtsNF8cHuUmcF7M8-_yzF4cHI-_8dldnSQbI-ajYldW761tvfdcNeZ4rJS8_uuh7V_Vuu2nm55PtZrfdduOL8eR0gs5z0zW77urq7PzydHG_PTqdI4jLo_PHJ6cid7_-29-9f_W193a9Wj_cLydHs-Ory1__9a-266puqvnl6X_-__zH1fLBWrJ2MFr15Ta0vQg-jpNsVihl4iQOxCZNKPh8Op6fnT-8fx8nsR96FKiN7rsBQZg4i7MkHUV1XRuDCsXTF5_dfPfGDd6YaHR2VBzNybkkS-1ui1r0TR_lUTYq9vB9YEji7PHTKxDq08-effTZURFpCcloH8f-h3ktIzMLxEAEAMioFDhHjDKOKHhyFpD3uB6pEJn3LmBgUImBPQCUGFEQEUhEgftbACKikPuSMUrpu14l8b4SIFAAEwjJRKg1SkFDh0JxCMxAwUtEJtpbU9k78EEbjUKStbas2WgTSUYWyBC8UJICCWMgeIbAzgliohCIpZJSy2A9eqeMck2ttFLSKG2Q_b7WGHxQcRwgsLM6Sb31aTb2rrf9AFJqLSTKuMiFhq5qfLvtVmuEIAV6FtZZP9jg7NDVUgodx11dsidpjEAOTbWPXoDS_a4VkWHvJbD3Pi1y31spJTnXNx0zSKVNGjflrqt7IYR3VhIDUl_V1HRSyCRLmXF1vwIgOwxu6FEACtU0rU5iFUXModw0xWgcXCAK2kjXNK5rQXDwLk5TZm-7an87ZCABjCjIWikkA-xnvxzCfgqMSqMQITCyZRTOhqgoUAqiwMFKrdnv6xkiOC-0JvLIJJWBwIgCAKSJGAJ5jyilkCS0d50yGpAAQQhQkWEgoqC0tq0VWkllnHXkSCiz3ycpo4AIEYE8IvD-Y0QUUpmInBMA7MOeWEUQorywXY0Sk8jMj8_IU1luyTmjpE6Soe65t5PTk3KxjvKsrmoXXJpN_OBdWw2O_NBlB8dAdvFw37ZdXhQPy-3QOR2J-dl5XVZhaCNjvIfJwZGONAtlolhpKbTURlFg2wwmNeSCVPtYmWUmaXRwAf8BegtCMO2FBqwQAQUAMUrQioMTUpALgvkH0C7t_9M_vA7EAlEoTUQMAaVUSg_NDkAwCAYQ0hCRTiJvndCGiWScAnhmIueBUUcxCgwceGjAJBxISSmEIO-BPArcp5OYmSmg2G_gWESaGRA9MEityDmpFAcnhZRChBAASUiNezoQsEAEJcl7AFZCSoHAnCSJp8CelUSUiAi9D13ToxbO0eJhLZRpB0soKNDN7a4hv-sGH1gJKWAvIIE4UuMs75oeQSZJAmCPTw84wKYqBaEklyZx3_XLoZ1Pi9zoXIvDIj-dFb___IkyhlGU613fdtKo5bJ5-fn5y08umo3LTKSMGivdVfCLT582vt_elTqRk7wY7pp_9i_-m9VOSIh-8fOPupayNC1mibUDaiWNmV3OjBRMIUriy-ODf_bFJ8-OZ588vXz66PggTxih6YdinF9cnD57fNZ0dtn3jy_mwZj3t5tdVd4utonEKIvSJNssV8cnx7v1bhzHg7O___GzR8fHWggkN5C_f1ht691sMsrH2d__3Zvb9ba1w_nF0fHJ9Hg-G2XRo6PpOI-1EhzIE3fODs6_fbf47mHx9buHV-9vTZLW2_Z2sRynyWQy_p_-0U8P5weZiCaT7Oz04Ccvr1IhnIcA_OFmcXk8f3xxFkkFQJ7xo8eXGsWTxxd5Yv7oH_-krNqbD5t8bIyUicnGSXJxcegCXl4cBoTT45mR6uRyWte-2XVn5-M0iQGF0vroaH5yMlVE0_nMdv1u25lYRnGkUtm3LQu0XXj64mkUy2bXaSPPLy_bth0lybgodKIfHtb3N-s40cF5Zy1KCeRyY4ZAXdeYVA-b0lWlswM53-6aeJzW6zbSslxvmX2camMkgW-qoRgXm-UuimXwARGcDVKib108PoxTI4A4BJRCIkdRMjuaq0gLozH4JI0RIErio-PZ7bsPDGEym9ab9Y8_efFPf_mzy6Pp4WRUpNl_ePtvXsyf90N_fDSTUhhJSmprSRIcnBxsV5t398vddjdJx611o3yqU9Xstl3XR0ZrFf3iF5_cL3Z11Zg0XS-3WZ4RAKApxin13dAMTdkAcwCuttX0bL5d79qy0akJfig3dVvXcRwLoxaLhR2G8XjUtrWOUhYcRSYxKpuMqmoXPN7flv_yX_x3__bf_kejRBqbMHQPi-XbDw-3i_Vdvfuw2M7y4uz4oIgSCu50Ns2T6POPHqdRfHp2vKnaq6Ojs8l8NsqbbRtrA35IoziSuP-FYAcbHKvAq-9v8lzvhkHK6PSTj410i7v73UMZFZE7TNd362_f3-WzMRhldfzo8ROTmkSbvraKfGbi2w9337y7__iji-cvrn7-5Nm6cqMklRSM1MjISHmae-DRZIxaHV2dAQQVa5NqbdSu7ptd1zTtw5vFdluBJyU1SBU8zoqxNLEN5pc___jlJ48fX54dHozzPNm1dRKlg_V6PC57_9tX7_7uu-v71er768U3r27aqn1Y7giwJfrq-v5mW5VNOxB_-vHly0_OTg-z02ny4yfn0yx5v2vZ05ff3bq6LVsfC1Fu_J_9059plI8vjz_-9Lxt7dHRNE1iAeRDJGh4dn50eXaepZFGnuQpMkqBg7WOyPvAAstd_e7mfr2ttTZFUXDg3vn1ZucJnA-BQ9O0KACEGAaLSgzOSimEQMdoOx9CSPK06XspBSIMvY1SPSmS5XLbdp4FSqXzkWGi9apKYrNa1V3THT-Ztm3HgA_3FbKczacmHW93nVbm5u5-PBk1XYegyVly_fHlTGgxmmajaZbmSTrNtRKLxXo0ztKRScfmyZ9-TtaGIRTTAiX2bX96crZZ1YlKpNBf_PT33n73IbRJO_jJvJgfn7Lr0izXSRZFahj6umxtsKPDqQshEHz22UfPzk9jbfq2bbshjnVW5ImJTBQDog28WtcXZ_Px9ODt2w9pFr1_d0cB9EiPpilAtNttkziJZHb71fs3r99Np8X88qS31lt69NHjg4NR0PK__tff1H355sv3TB5RSBCO1ex47j0u7ld5EvuhLbLs5sMNelfMZ7vFUkcxsdMCTao8sfMMjLbvrbXCGCKOstykeT8Mh8dHPlgUMlAAIQSqfDpN0jTJi9WHOxNLJZQUvFqtTGTSYnz28bOhaqplqSI99F3f2iDE6ePzYpz3vhdCnpwea2l-_rPPZ4cHXVnnR-P_8u_-9tdffilFMSXai3oRmYWSHBik2GPLGQGFYvISpYhiZhYC2HsgksoACmaiEARKYNovTJEJkRkAxQ8RIKYfQO6MAMRMTAhCgPcklabggZgBiQi1AWnAW1CKPUtjUEoklpKRgSkABwGwFxkE53Rk9GiEGm3dCCkweD9YRCAKCOSsFYxAQSBzCDqSwTkgJxARKfQtB49CBtex7ZAoBCelIiZrrdTa9i7OCj-0fb3r2x4FEoAQwnvPwOT6bru0uxUiK2NkFNm-QyApQujr0PfKmMABkCUQ2d7WlZASEKI0D0RSK4EgpXRD760LfedcJwW4YQAU2bjIRsXQdc2uRADbtIA6kJTGnL78CIAYkFzww5Ak8dDUQ9-BgCRLdTY2aZ6NJ0II17da6aapi-mka9o0SZVWCMhuAAoMQUshQPg9J36wOopc76RC4MAcfgC2MiASKslEjKCUZE9APkpGfdWoNAYpKQT2XiAASqGENBogSK3JBrYOxH5Cz0SEUrP3EhFQokBUse9bYSLvPAjQUcTMrrNopJKKmJ11WkcoAENQ2gAR7iNnWlLwwABA5DwDSCNBgFTa-yAihYjgnCMSUiqlhqZr6y4eT6WA4HxT1rPDI94T8RG6clscnLblNonToR2Uoa5tCamYTIjCw-vXIExWZFJBCDw9OswyAwjkbJqNyqrsqmpomm7oAhExoFBZUfjghJJM7J1lH4Lzru-SYgIArhuEVLYfmEEpJCAg3jedhcDgAwOFQMysoyJ4h8RCSaEkMpD3UkoQCAJASiKKIkM-UHBSGyYK3ul4IiF4H3RsABUggkDqrU4TlCiUCUPLAZiBg4XADMxiTwqV7DwqgYFQSmACF0AwKkm0LyEgeIcCAVFqjUQhWApBKgnkgQhRUAigpNw36gEBWSCQc37omb3tOgCKsiz4ABIoECK6fgAGoaSK1L645qyTUUQKy7JBA13TUgASwbVO66jtbd_3WWI-Oht1Hru2k1omaZwksfN-8DaLk6YZblbfd4GZfRTFaZZcHk3GcWyU8t6Ox1k-ym3g3ts0M2kcHR_PEcMkLx4Wu3bXR5GIo_jsIAVLTVW72l0cHvyLf_xJJjPXD98v6m5ZSZaXR_nh4ezyMBVJig6n03w-nz6sBmFtauTTw8nvvby6mhW7utaRHsC_e3u9rfssjhjw9Gg-yrPVth4Gf32_qHb23e3y9mYNXtyvNydH85dPn1Te7qrt99c3v__5i6dnR88enQoAAvbWheAHa7shOAZEbnrfu_Di02fr3e7Xv_r23c2ys9T6sC27v_ztq-_ePdSDW3f2u-_vXr-_j_NkV3dMHGllIpPnuTHJ-fE8z_Xb9aa1AygyRs6ODyg4a4f_9OVv2rJN0rgbbG_DJy8fRWhGWbzdrPpd-_52WRR5Vw-ZUS-vTmOTjIvszZv3ymgOVGRJPs2Hzvd142zAIPveTg6yJNK-J2ftuMjXy5Ui0JGQQQ7dcHCUF-MxgkCSQDpYf3J-VO12o1Guhey29Wpxe_7oVDhoqzaKjEQ5PTzw3h5cnIShV0pAcA_3K-cdeAYX2DolpGABEkBgNpk0VcnAzKyERqFsZ4euU1o6R_nhqCtb60OQGKexQkYCZwcpRZymADCdz-umzkd5vSuzUWY7O9T94dHh1dXT2eGRQjXO8vPTi5Pz8VB1f_wHPzk5GEdSRVre3j_8-NEnGKAPQxrF602phTBRzIiLqm7LdrHeVV1LwIvF8mB-8vbdW4N4e33789__Zdu2k8l4XTdN0wkJQiCTJw7BuTDYvmzIE2ips-Ls-dPq9sMwBArBeTsMrhiPm6qOYgMsettlWZbPCrK-Wq85hLIq7x8WddslJvnu7XviUK3rpmu_-faryXG6XDUt2a6zRkdPn59_9-b-7GAyGqd396s3N5s8SaezKRAvyu2f_83f3O-qo1k-H0-6wcZ5Mo7zT59dPXp0_vHzTyazWe1hejy6X2yRQkBCskK4vh0EMKFv1ovdps7Gqe8dE_ersm-6iQZXNWLob3_z5ubN-_dfvvFhSGMJgUmIKDbBNVUZCEhq8dHpoYz0Lz_98baxp7OjVd3lcWKJpNbjIs3j2AdqGssA2yGkyah04bMfv6RUf_zx80inxyczCO6wGB0fHb54dvZ7P7uSgO3QnhxOAvHd3Z1g8eV33_3nv_jy11-9arqGg__xy8cXJ9N-V5_MssNJ0rddmvD3t9u7m80ki89OD-dFXg_9X__uu3__21f_-999--e__t33i93RbHRxOPsnP_nk2cVRHEVINM00Dr7clDbYoa7qrl8sd4d5MhkVn54dPr-YR1pESkzH2TiLtZQowBMhYtX3Wqlh6PMky4sMQUitd1XtmMkGF0hpmSYxMKVxuqtrIqeUUogHBxMm0lIFF7z3cRLns7hrfFt3u10Vp9FAVFVdYJwdTFiKqu16623wzlE6igEsgNhs6iQWGMeMgSTJyNS75mCiUZHScd32V8_Om7JKlEaJzsHgqK8tBGh2bVvW5H0IQaJums5acfOb62Ho-7pe3C9d1w2D48BZIYddMwyuLstslOfTbDabRLEBAWk2QhAudDQMaZoobd6_356cHJ-fHp0cTLSJq7IZjwoXQiQVIQohq7L51d9_Y23XtO0oTtwQ2rpthz7KDAutIpkk6fV316vFdnG7muSpMVFaRD_7-eedc8kkSdL4w8O9kOKv_uKv7t_dCBqGtveDlVGkdVKMxlmRXzw5LzdboxAZ4iRqun51vxofzsvNptmW7IMSClzIR8cEmIyyvuuUhCTLQEfZdJQUxWg6jpL4w7v3eT5Sxuw2JQIrE2VZpmN8uFvOjqZxkjR1gyiUiQhFFCXVatWtq2I21UJJqb1zSazd0PuAOk4jE_34Zz_6yScfjw9nzTAsb99ef_V1VzWxTCTkY9yjH4FQIBCjEOTDD0lrlOwDCsHkyVshNQqJISDuOUQqMAOwUhIByXmtNTB57wUKpWMmAoF7ZzAKZGBA3CPIiUEAR2nMBMwkBQDz3h-ABEAkpELyCCAEAgfwAaVAAPaBiRCQgbx1aZFnk0m7WEVJzNajQgoklAzOa70_iUCwVpkIKITBMjNZC4BseyWElBpCH4YGUQQGEvt2mhJJikTeORq6EIYQSOxPukQCQQrwXd0urpkDeev6ztseAMh7Gjroe6EEk7flDhiRfBg6DkEqKaKorVsZRcjIDLwff2rhu1IQD02fjApnKckLJF9td0SgIyOM1toIhHxWVHc3HILtfF-1Oo36svRDG0VGaT04Z6I4HY1tVwfi5fvXUkcmTuvNJiuK4AciaqqSvDVx7Ic-OMcECKgjEwDYD8YICoFCEEIweQby3kmxP_3vRRBSm8ha6_s6zjPbdCbNmUlqGYIP3kslAdD3DoQQUgkRQteilCF4BAFSo5ShbygQSqGVQJ14N0gtQ9OzFEJrgej7gYj218u9Gox8YCIpFQoEgb5vpImYGQJJJfbrpuCdUJoZyAUAIaRE4OApyQ5ZkHehrduT509977qhX7x5G6dp8FYrHRiVFt6zJ3708sVmu0KEfhgEyIPpLCnyNE-3d_cKhR1athx8yPIslhFJUMYAu-AtQgjOA2NaZN7agKpaVaP5iGyw3gspfOeGwYbg46Jg6yg4QYEZpVYi1gD_oOUiUFoD8z6pI2QcnBPE6AOi5MBEtIdoAQMTsydkYADmoHXkgckPUVwwse06FChQIDKHsGf-mChiQiFQakXOCy3AeUABCEIqYhBA0hhvrRQIAoEYiBgQYf-FAYXAPiilvdsPAiRZh6iCd_uRPIMgP0BgpbXUJthOShWC01rZvlNiXyQGb_s9DUkQKonOBrbWJKntLKC0RAJgfw1FxDD4UZJ54bvWqthUVe2luFk3rbdRFDkfAOHkYKyN9o6LLNEyOpwdTpPEOzZKqESMsjTRernZSYmTcaZUBEwuDOACe277wQjNGKZGp1k6LYoff3aajJLJaDQuYqFlOhq3ztRDr41Osuj0MP_F54-FSR4edrWHp0-PLq_mTkaPj-Z_9nsvfvny4rOnj6ZZaiJVVg0RJUkmSIEUxaT4sKwA9bLu_9W__i9_86uvy6Z59_6uG3zZdlmeXP7Rjw7HxfHZ8b__j_-57_n55fx_-OVPRlmsJfZ2QKOcd2_vl-8Xu_nhLEoy592b94vZbBRC-ObVdT-EdJSDBEfU2nB9d98PQzFJ0yS_vllywN4No1HR1M1iuQ7OdcMgNZzMJ0ejtGps1_ZS6yJJR5MiuMF2vh7CNI6nk0nvnBBSCNxWXXCuJ7ve1dY7GYlE613begI9SlIlt12vUVhr-8HV1kotTuZzZjg4nmWZ6oaenWdUZ2dzjsA7H6VJ3Td1b5MiPb44dt1gWzce5wdnc3L25YurrIiEF9b67CCN0_Tu_d3R4ZGJkjhJZKzubxezccZG2rY7fvyTfnM9uOCcQ0CUmOXpYElqk59MNvdbrZTS0vceBCVJnhZFMcuVxGyURkliO-ctjY9mTEFYSiJj214J4WyvUDIHIm6b9uLi8Xx-kuXJdr2REqYnxwohMnKxXLpqd3h6WFWrJ2fHf_aPfj5OEyng9m4pBI9GKQEAotGyagbBzMAM7CB8uH74cP2wrjqtdVN148Pp5v6hmORN1ZrMxJEZBvf06aPb69tYm0CumE5sW3trydP88Agg1HWLKJMiq9dr3_qjRwfbmwchJSJ0u8ZZm6Tad323a_qh08oYFQHKtm5n01m5Wbu6fri9b5pGRbpvOsPsrD1IZ3e7XVzEHuDhZuMH19TterOzNpC3Jyfpl69vP9w9xEY9OTr-0cmJ0fhv_-IvOYBS_Nt3r79a3U-mE5wk2cn06Gj86Pz8bD75_U8--sUvPv_ik49NFJ9dHBdZ9FDWWgVvLTmvhUBkhkDoib0yxlrw1kdjVSQySkXfNPW2Xj1sNruqrCuBIsnF4m69XFVtorRQy6rM8shJ-L1PnoGg_-HnX9yV7SjOyrYeT6cUYDzKp2kxn-eH0_EoT39y9fh0mp8cFrMinh9Mz84P4yxmgr72UuEoT97er9-8ed_2fZYkh5Ppp88uv_j06vRwPB8XuVbB0micxXnUWhcI0vOZYZxORw79m7frVzdlkUTPn57_4uL450-Pf35-8smjo5P5KJ0kX769BYE__tmT40enHjlobNpmvS6ryg6D_2f_5IujJP7R-VEea2ctMM_yLDJKEmuplUEBcHe_vFuXWun79TZJUu-DIwo-EFBsUq3R-uC9m4-KXdtFEg6n47PDg1GaaBOx83FsGIBCiOJIS2FbNyriJEmKPPXM221bJEnTd4qF752zTimFIIMH2zvv4fpu1dchjiMKTqaxEBpDcJ11le9QoJBJZCJmti5JI0-QJdHd-5v5vHBDV-526TiyfZ8U-dB0SZ6aDGenk_XtQ5RGzntjpIyN1qrrXQjOxFooTYhXn1_5rpaIVdkkRTaa5w9vPmhpnlw-Ci588fkT7ntXNXESLxfb6XgECAQghMyyvGtqI-OLR0dZlC7X9SiJn3983nZtY62IcHm7zuP0-9fX5-fnk2n2yccXSZKvF8urJ5e7cvf93bIt2zdfvrG7rlrdC0LX-7TIR6NCJdnZ04uTq0epSuLElOttV7Wjg6kLvlxvQiClRVdtyA4yEDAbKZyD4vzx0JQ0dIwgsyJKYpMlo8lkOpl3Q_dw-6CVAMQkNofHJ_uwWVPVQ9tro20_MPkoSfvBeuYkjhlI6ujRp0-rpun7flykJtKjPDM6-vGPX3785NFHH11mJk7H2f_2b_79d99-3fd2GOjq5Ucf__HvS8inUu0BJCz3w0LvhBQoFPmAWkkpmRmREYXQMRGDFGwHCaySGFF6T-z9DwZfZEBEgbRPkAtEFhz255MAe4-YlIiIUrK1FEBEMTMFG6TWwPu4MwRHQhCiJG9VkgiBIRACIhMQITICS6EF4lBXjMwuhP3jTCSVCs7qOAUXpJSha0PfAlkAACKhBAIAe3AOgIicFDIQwt6Iq2OBKE0sJNhyp6KY3CCZdawFEA1OSkQlpJI0DNYOwETOAjkg1uOU2g7ZsyOdmGCdyVJBnodGKumcFVrv5awMLLViBmlUlMS2rdF5qbXQsUniKEo4WNt2Ko6FjqIkVSay3QAISZZXq0UIlBSTKI-kQDsM5H02mtRllU1nwOCtjdN8uVycXn0U7CBV5AYntNSxHro2WEveBeclIjAF12kpBGqQ0g8WmICCkAIRgw-SQEkBTELKECwwopYEZJLM9YNSAES2qQBYKA2otdau7aQUAsB3FiRLqaVQtC-xIsgoYkZhYiQAN-goAgHMqLRGJb0LAYgZhdEcPAIhCBAspBDEQAQIgAIEaBVRcEIpKRR7JxD2RjkG3D-3DEDOaaUEBzu0QoEf-tD1ljxqrbTUStXL-9D163J3fH4KFGSStFXjXX94dby-3aVZViTx0HZxnkih5hcXnqhZt-PZCJH7oT8-O9qst8CiLysjdT4de89pMZKRHE8nUWy6uqXg41Fu3SCVEdpA8GzdvmIjlQZCqaQfvDKS_T6sr_YdXAQAHxiCTlMAhOBRIDknEMQe4qwkomIO-xsyBY9CEhGA2PeLAVEKJA5KIqJCpWjoyTnnBxklzMDAICT3A0hgH1AKECgRyAdGQCHIeSGl1Al7v78w7J9elILCwAxCCJQy9AMAsRRSSvQgtGT-4cLv2g45ELPrhygtKDhlYte1AgCCkwL9YMeTUdu0zg0miZ33zrkkjQCF1AoE6ihSSrZVB85X24pRBAYP7K2v2k4q-fZ6iYl6WO8sstJKMGitFUqpJLGDgLGJk0SPssigkCids7mJZgczZq7qpto1Te-2u6ptOkKWQHEUMVEaG_YiF6pIMi1wnqfH4_RwlJ6fTCZF8uT48OxoMs3isVFHo6yI0O52GcDzg4Pjg5HWEgNlSewp9DbUw9BbH5l4tWu0jlSkF-Xwn__m16uqHk_Hl49PyQeTpYfzg1GenL48a2-r69dvFnfXh6PR__zf_-FBlkZCkncA8J_--suvPzz85u3N9f3uw6qsrfduiOLocD77V__6P9w9rCnG6_vlr7767vzZxYe71XKxSKJEoCg3dVnX3nutVdMM8_n02bOry9P5o8uT46MDCNBud5X16AkAhVCrTe29y7PYdfb9XRlJEBJBiqHt5wfTV68-lJs1uTC0vRDy9Gi-qerNtp4cZIeR_tVXb42JxkcTIjh9fJiaGAbaVVVizHqxMUlsZOwDFXm6XSxD753z223J3pf1MMuT3335RhJqxWgDWHd4NK2btq6Hoe_jxIAXy9V66BtEWbf1xZPz3WJdbbfeO8VgjLHbBSAgaEQlJQhtdm0_ms-mj46H3Y6ZACEMfnp4YHSSHx4GZ99_-VsB0XZTgiSJOsn00HW-7ZFJIFrnpBImLaLI6Fh7x9ro0XQG3tmhP3v8SAiRpFEkIgyuq7qLR2dS-qePHn_29Go-yRWIru9jLaPY1FXTtINzgw-MSgaG129eax31bW-ihADLXWly03b2q29ef_aTz67f3aTjETElccoA6-WibXsNcrvbWevmZxcQeHY4227XOk6jNCom493yPrgw2H56elRvt0jMiKPJyPVtsymz0SSfjBjCdrmp675uqrzIVoslMAoWKkmlUHVVEQJZf3-z6YPXCqplM86KNBcuDEfHsw_Xt0T-dt1cPj67fVjnmakH9_ffvVORMSY5Ozph4svH558cHd6_67q26ev2zW-_-fKr77998_buYfX2w_tvr99zngxI48l8dnTw6Wcfv3jx8pMffXbx9Eqezufn5xbJU7A1oWAjpGQSTN3gm7aTSmbjfLAWmH1viZks4RBAULfcvnv9vtxtx1mGQvzn33xzdTHfdf5oPp6OxpMiPZpMz8_ml6fzi6ODIskSqeqyfP3uZrNouiEE5oOT8yyKPJLzYbVeWYK6DUKbR1en84OjoRnmhwe9pcFSZ309hNK66w-r6_vV7779sNw0m3V5e736_vX17fUSWOQH0cllUczS3359v6p6FekiidaV--712-_e3_je3t2vrm83D_frXdlKkO-33S9-7-VPP33-fD6bZ9HROI-1uLu7Pzuax2nMzMF6rYxREpk3dfOb7-9-8vHTwGLbDb_53bcHh9NAXiqZSA1CfPP2w9nJLDI6BD8ZJeNxZpQIRDaESEltDDAJFI5psM7bAEqGAMQYfIgAA4qmb7LUtNYKhVLrQYZklJMbVAaOoWrq0Tha3W3SIu53nXc2imOD8enJ6bPTA4m9BjaIvg-AIlZqvV4fzg5DCNP5kY7UwdmjvmctxenpEQs5Sid91cdxbBubxrFKs3EyEhw673UcPb28qHdNXsTdevNws3TtcDCeluvNh7c388NJFufPrp603ZDmSZzERhrnOUsTZicY-n5QUi6WS5Nk3tu67dFAEmutxOJ-V9X1_Gx-_f29ESqKovOLozffP1xezIHEu5vbk0cnfe9e_f1XmgMN_VBXKEhI4VFc_PITW7m6GrI8j5Nk_bBCGQDFdlMWs3z1sHr79qs8HQmCpiypH7RUZIFZeObRfOLaHYWg0gxNfP78WTEuprOjLM-u378nR9Px6Oj4-PzydOjaD2_eWO-975M8B0HkiChIjCjwaD6dHM7s0KdJJpXUiem6fpQXTdN-9OLpz3722Wcvn0-yXMTRm7d398sP__Uv_353vz44mfRO7Sz90f_5j4QQEtLxfnePAkAg750AzEABpARi0Bo8CSWAmEGAVsCAzAiePUkVSSnIEyIC7yfHQUjJwEAEhACAUiAQ7oNFgCARhUTmfRNURbGzbn_uZ-JgPZpISKbgpUQmQGYQKgxunwDhfXxBSABArbz1rrdCCw4B9mEmgexJGC2AGQINvWDaZ6wDBQCBKJECCgxuEExSSaEkkIjHhSBmFkqpMFgVxUKK4GywTioVemeKlAMxIlEg20oObB0CoXf7MEkYLFBAAOJgkggoMDkarJCCpSDnVJwASmBAJYP33noicl0HHEwUBcbs4MB2nfeOAKM0ZUG2aQjYpFmcRM1uG0KI8wylCr0zedJXte0b21uhNAD0XWeiZHF3lxVFv11PZtO63pkoQYEcfGDummqoSqkVW6_jmJ11g2WBcZoE773_IclNTFKCQCbvGYAIhFQgJQbmACrPJGJf1toYGjohiLzDSEsEqY3tOwheZxn1FmhPhmVlTGAOIUgTAaLSgjj4thdSyii1w8A-RGnKRLzvfAstEJSQjHuUjQLySAgohDLEgQDJOyklMu6jLygUE7AUUmoUJJAhQPBBCEAhhFLBdX1VMYENbHfN5PiIbDN0_Xa9yg8PiKEoRm3dDK2LEt1tN7btTBIpFQmppJBNVYvc9IMDofqm9d5nWa606dpBJLGzlB9OTKRt12dpcXx6XO9KZUyzaacnx13VgsB2c5sUE2ZiYoFAzEPdqyTi3gIzCkEhCCkYUApUCoGYCWQUO--BeJ8ZI_IAwM7_4M0ITkgJiOS9NEoIwUzeem20AEEhBGeZAYVQSjMReyLXq8iEIJi8ylMaBpPGZD34ACgQ5V4MDIDkCdlLrcg7YgIUqHRwFpUUIMiT0AJCEALYk9SxkAqBhBTBB4EgBHCgH-hEbghEcZwDe9dbpkAh9F0fmKRWASgEH0JQcQzWBmZEabRCRteHzloplVAAQDYEFFIbPR5nH27WUaJv7tbFdHRzu9E6KfLYOtII3nqNIkkjKcU4zxJtBOqud5HWWZ5F2nRt2zm7WG1779Minc0mSkCaJGkSU_BnxwdG6kgocsR939shy0dl3ZXr7ShJgJyUSgUuEhNrdTzOjo8mR-OxQRGbxDu72rbbqvr-5lYITT6MJuM4MU1nl7vy2-9uPtzePn_5YlSMq6ZZ71qditn0QGkWoNc35Wa700S_-PyjP_j8E6QgAb7frP_1f_m7390sWi-aAT_5-edvXr0lQQLCetu8fPr47fXNzYdl630cJdfv7tBIzRIAZ5OZkHEUa9sPm41NEpEleZRGZ4cHy9Wu7ZvNqtQ6IRQPq91Xr66Xy52nAEAPqxKFdtbfLJZHR1PfDe1gz09PUq0TjeOiUEKSUioxwFjWVd0MkVJ2sA_rOo3ielc3TbNrhq61dV0DUrWprbfjacYEo1E0HedprIBBgjyc57GKZwezq8sThnB2Ni-SSGqdz0cU6ObmIUui6fkBERFzVVWLm4fJ0XQ0GcdxXG0q5wYUmKZFnEZA3Fs7nhww-cPZtBgVkYkmB-Pz40Nftt66zWJ59vzJ_OAoiqN0XNR1uXnYzk5PVQQMgFJEab5ZPPR1PT2ednW3V5Fkkwl537ZdmhZJnuhYd0Pn7XB0erJaPjz_9PPFzTvBEHyYz8Y__8MfTdL8Fz96cXE00UoqJYXCxXoLzGkR9-0gGB3RdFysVtvZ7DD4MD-ab5rm9u7h9Op8vdk9e_oIiI8Px1GWd0PbVNVmuUrz8TfffHt8elRVdW_7rhvautZaTWbT-5v7y8ePN-t1uV6FwBQon4yuX32vTORcb2LTV_1kcio0N3Vb70qUysRJXZZxZJgoik1TNSgESqFlvNtVs8PR-Hh6cn7inCuyqQt2qLpy2wCLdJSlsSk39WKxWS7W-3T4ZDzaLe5Xy_b4ZGbS-Lu31_W2OntyJjwJY04vjpXW2TivtmW1LXWsF_fbZlfd3tzf3i9e399hIoNgBnl-PJtG6cnh6Nmji59-_qPf__0fffrxj54-fV6kozzNVFpsa0sEu9qqWMdRDEIBQRSlSZFvVluGYCKkwd7eL8qqluxNHE9Oprth8N4NQK23AYVDWFY1SjU7mczGhZJ4ejwThrrO7cryZrH4-qu3N7eLpuo-XN-9vVlqAV1dM_Fnz8-2jr_8zeu71XK7qa9vV4tV1fa-Knsl5HSWg-TgbTHJj84mo5OR8251U9W7pntYo3Oryn3z-u5-_SCSfDydlo0HwMOTGQT1T37v5ceX81--ePTkcDxGyoqUrN11bte5JxeXiFjXzfcP91kUH44nRsje26q3RweTzlLtuovz43K1_e3vvnt8eZQnuQ_h3_31r37_848meTbJI0Fsu15J5Xo7OF83AwjhidrOXd8ugSGKo7odiiRqBv-w2gTnq3bQEjyxJRg8I4h26H1vXWuNkatNjY4PDkdGymKa-8DO-zg11g7FOAGw683WNc4DXC-2eZKZJDqcjpeb9nhaeGLX9PODaSRhkprDg_HpyfSwMJcnEyX55PLk6tn5s6eXZ4fzs_l4Op0lyjy9PDs7Ojg5Oj6aj71D5-V4nG-23fnp4dnZ4dX5-eXZCQefZxFK6AcnlZZKAMPdcrtrujRNttudlMIHH0eREbIs67od3i9Wrh_A4_395sefPplNp6ens0BU5MIbfvfuJkhY3S8_vLpBCElqVouymI50FLnBpVnm6wGZ8kn26JOni7sHoYKW0cP9Enyw3kcmOrt6mo3zZleikmmeDu0gjEwn46byWZ4xh_FkNplPT88uwtBV693y9na9WKRxNJuP81GxuFuuN6tyt2vadjweEYPrhq7t80neNUMyLqZHB-Rd3_W7qpuNisvLy48_e8aOfvbF8x-9eHZxcZYkyWpRiqPiX__5_3Zz_UHp_Ivf-9nDQ62NfvbF55__9Oni9e3iZivVeLY_eSPADxIAACYSQgARAKJSzAS0zwkLISUKlFKCDxy8UIr3eE5gJi-E2KuaIBAwCykZAgAgCiYSEgQiOS-kZoBAAQAoBKEMMtGeia4VIjILIWUgj0YjIwuBFFAIBCIXBArYW5QCMQUByFKgQAYQUgip99whZA7Bh75RSgMH4B_aqEIK3zUoEImkVM4PzEJGhoPzg91_FoCAQjIIIA8EOo384KURAtDZ2pc1hJBN4maxBm85BN5rDICYg1ACmACIfPBDCz7IOAnBKZQqTcl5BBiqTsdRFBulJAXftb34h-WCD3Zoex3FaDQ4K6REE0OwiCy0NknaV006KvKj8fZ-OXSDkBKlGh_O-7oEYnKu7fs4josiC27IR2PnrFEoEVCgrSt2llyPSgF7JmAA1zaeSOpYGMO2pxDAOhQCpGQgFAKEIB9ASCkEIAQ3yCgSUgTbxUlMIQTnkUJgACWklBSIg1VxgsjBeymA98-D0IGCiqLggjARAjKj_-G4SeQGgfKHhgnvH0gSUgMECl5ps99TeedACikkE1JwUknB4oehODEio1LIyBQYWWoJFFhIqZOoyKSQTIGdpaGxbaui6OzxZV-vNw-LZDwDCqPJzEisVmudpM2urMtaRlogaKPjUSGMduyTPPFdV-QFAXj2h6enUZooYbrNVpkoOMhHBSipjNZRlBQFeVZGR0UeHx5G47yvWiOVSSMAlLEKgXmwrCR5UsZIY1zfM6CQKngvGFhJFIL8D5fkvZxr_3YIpYSQ3jllzD_k4piDF4gheGKSWgcX2DupBQdEKSGQYEalAZFZAjMLEfpeRyYMFpFBKKHkPmolBJEjlCBAAIgQrNQGGBGY3KCjBIjIBQDJzLhP8SF4b0UckR-AGRH3xDAAL7Ue2ibKcyGktx44BNu7rhWSEQhDQISurqIk9T54DyggUvt9iKrKdRanXdeXba-NJgckJOgARjLKvveEVDZ9OonW6yowjUZpnMXvHnZJamKt-8EGgigyaR7HWhNT2bR13Rd5nmRJlmZt0zvnRqNUIcym43Geeu9VFOlIKq0PDqdV1XoflmVTtZal4gCLVRdIZpkm8hBwWQ5tH6wEo1URR2XVbbvw_OJgWuR_97s3d6vNYrv7-rubT18-yfL8q999E5DHRfr47PCgGL1-86atKY4gT7L_9pcvf_7Z1TROO9sHEP_pV1_9f__mm9F4HBWZKfLVdhfc0Fv3_vpu6N1kXHxycfA3v_5udjCeHo6__s2rbJwlOi5GaXB-1_fBcBKbR-eTJ-eH46P8zf1Kx-Z-t72-efjq7TvnRTP4h-02y3IpVdW0XW9XZfPJy8efX128vVk01i2r-na7G7y_X-0Ga7-7vpEmMkl8cXJyNBkdT6dPzo4fX56dnh4YIQ_m48ujw4ODidbqaD55fDY_nUy0FKfHxweHs6btTGwaG5AhIDVtH4CsdVmaJnm6XVcgcFKMt3U7GefDEL57-0EQr5frarkD8hL55sOHtqp7O_RdQ0p8_PJxuWuPj2aPHl8ezieua7M0Xi7ukNHkSWAmhs1ye393j4Jns8Px0Uxr1TbNerFiCG5wJlLOWj_YKIlt17bbjZbCVQOj8AwCuZiNvfdC4mQyNUbFafL0oxcfPtwUxtTlWktT79ZnJ-cX56d_8Ge_mCX6-nr5z_7w904nmSAm4mKSlmVXpKlSyrvAiCzFYB2H0Aw-jvVyuU3yZOisSXQU6bps2q5PizTPcmZ5v1jlSTZ0Xd-1u7IRCAg4Ppo125IdjSYjJtjuNsdnF33ftGVl4lRHJk2LYpQEG04-vlx-uHVt6PoyzqIojuMiQuCmapK8YHAY_PZhl-bJ-HBi0sSLcHR0sFuVSZrm4xg8BeTIGNvWo3HMRNvtcHZ2_PnnT8kHDvKLn7x89eWbb1-_i6L4-Hz-l3_9u8ePz87mk9a6-8Xu-dXjAPX3b-_Pjk689RyQAgwuHJ8dre83ihRQiC03y2q3rG5ef_-733z77t2HDx8WTW_b2uZxMZpMiiI-PZk9--jq-eOzn_3oRz_7yWe_-Owz7-mzz174KNqWVlhHwUeRcr0lojRJHjY7ZCKm1Wrb9vbt9e39drcduoPJqHZOaqWkbKu2a7vdrmIQMpIg1PjgBxn4oyfHT5-fn5wcjsbZyeF4opQlun3Yvlsu3n3_cPv-Zv_XbPABjIrS6OjyxGgFgSIlrA3eue2y7hvflG3bDkNDXprHV2d1NzhpVZyfHB38-OmTX7w4-2d_-Mmzk-lHx1MDHKPMUn232qzXzV998y5OkvODyTjJnfdtW1tnnQvPH1-ksRTA_-7vXl2dTDtr62Z4_fqNMcjMj8-OZ9Mxef_h4fYPfvL8YDJhoq9ef8izpBiN6m6wBAEEomh7Wze97W2aZ4hYVb3SKoqioe_asgGA9a5CobxDI6Qd-s2qcoMb5UnfOxHQADLw2UHROh9leQgAscgORkhSQnC9q6suzROd6Ml4lMeRlDydxGdHs2dPTuIoSbNoVKRd0_W23_Tdq1dvdZz-9tV3Ki--_PY7BLPa7HSSZnEcYvO-XL766ps-qK7rUWCWZdPR6PHl8TjPlaTj-TwQeGcHa30gGWmpJQALAVrDKM1PT0ejWLogJbDQquvb1Xq7bYbPnl_lSj09P3l6dXp2MCaQVdveLO-vb-5v7ja37-61Mrv7pQDOJ7FO44fbzWhSCI2bjXvyyVPP4umLc6WUkub6u_dG6b5r6rIemn42n81Oj33wJjbr-43WMk6TQHRwfEiCg4fRYZpnmSM6ODt9uFlZ52zfMsF0Mpsfz3yA3Wa7XW27vlLAm7IczaZxFA02ZFk2mk4R-Nnzz-JIdeW2bZoszw4m4_l8UiRJXW4_efliMp0AgcmS5XL91d__-j_8-78wQntL__z_8me2bWZH06rrv399P4oio8UXP_kZ4tHVnsguJCIDCiQmJpaIxEDMIo6YEZmQAgdQB-dkG_YOhkEgM7BK8uA9gGcA31ulhJDK9z0AAYq9WlgoRc5iCCgECyQWKITUkgIho0wTW7cSAQUHH1ApITUI3FPJpdRCSiACAEGOaN_-ZIkieAIhhNQBkShIJZgCCkXOyThBofzQCiJwjgWEQFJHJAVbu3dNMaLQkgHIi-TgwG5XxIBxEgarkwTQYBQFO3BAncW27VEqnSRkG3BOCCTv_OCYHSIIrYPfB-oNW4tSqCxxbScQ0AeVJMSo4wKjhACUjEDIfR9Cat13TbBBSKmimGEPtpRxngKglErGplqutJag43w-1UKjiIauAmZydrtZKf3_4-k_mmzNlvRMzN2X-OTWO-TRefKkunlV3apCw6ogCk1Yt9G6jRPyD_CHkWOOyBHNaMZugOhGFQqlr8q8qY4-Ibf-1FLuHOwszGIQFjtiCwtfvt73eQyJFgRIKUVP2szOH6xXN0pgvDw97Ndam_F8JH3ougYTA_a72zvXdcYojl6hFgWKCHWWUoLQSfDEx9V9QoYUIyAKICoigXQ8nFWVP2yNIvYR6KhdC8yINsvKgkOK3nEYdD7CEIA9CUVg1CamhFVhVRaGARE5JDxeRyqKXUdFoVAQkL0_HkhtXUniEJzShmMEJFTqx1NcSBKTQlaEgBi917b0YVAm12WRvAt9Z4qKhwF1JkqbchRCKMoqSfJto02WBAnRWgqCejQZn5xvt-3jp0_b5rDfrIp63DdrSVopffbokVY2AinFKlO72xUJjRaLYd_Nz-eoJMUYWje44eLBKYfgehejt3nWHJrBuUyZq_cfCIVjcN0htjsS1EZrQ8N2E9omeUYtKjMpRuEAkSmxAKNAYqDMgnByXhMoRck7IIyRVZ6TNjHG43uZ-aj0xuQ60DmEqIscUKfgJUWw1hYlMHP0MSSd5WRsjKwMheZAiiAlRABUSmUxRSABSXws-QCiLYMfTFYobTglkQgRTFmGvgeISpvgnNYGSXlhMsTMHEGRUhqVMX3TmiLXpoyCeVEDYui6I1MFAQFJZ1aQvIi2RXUyC10aTcbCSRdFlZeHuzuVZWZimi41m-1icaZFyCBWCkFjwiSpLovMKsUpy_N_-6sXkyoPvffdUJd5XRSm0JkiIkrOu5CUoSyz3RCJ0OZqt97f3G-mRTadTx88OJeUQojRh-m09iBNM1xvm33Xu8bZKjdGTWw2tqbMLEjUmmKMGxeHNkSrxpkF4EKRSnF96LKieHN7hySnl4v99RaL_PHp-X_5zdejrDy4FpBf_vCmY_q__s__SgkF4P7Q_vXf_H4d3M8-f7Hqh-223e17QByNMiR9aNvHl5Ndz29e31irfvXTpz958vAPv3-Vl8Wjy-X20Ly5WZfj_D_-1W-HEIcUvEvOxyovZospkbx6f7-cjgVltz1AjIKEzAhginw-r1Wk8UX54YebLNcZmCH5fdtn1ojRKqJr-9LYepy5PlXjUiKPZuW7m7umP5yMpqPx-Omji-1hrxD6YTiZjouqXG277b4F4kdn86vbnRZAUvtDz707fbAcmu5-uxtPq6KqD9tmtphwAo6xzIvS6M32sO-67W67nIzapp0upuv1ZlJXD589vL9ZPX5ygYRDOzRN2Ox2xbz8cHW_ud9ef7hrts3yfJEArt5dpZQ-_9kX716_O7s8DT4G54UgBSgv5-tvfzhs-yI3Q-fqkdntGmNsUeZD10mCbFTGFPt9--jZJ9cf3o7GNYqQ0o8__vjd-zePHzy4evMqQ5UIFsvp808-9n13Npk8eXx-Ohk9eXBCLIemNwbFWDcMfnC9Y4CUBAHEpQQAV_dro7BrHQBMxvXf__77-XzW9F1eVMbo3331h_tVMx1Pmv3hwcOLzWa92Td93y9nczutf_03_3j5-CExrteb2cXy9vV7rVXXdodDoxGni-l4Or-7uZ2eTkjb73_zbT0ZpRDIWGWJtKZM56rcrDYXzx4eNpu-HcrcqHwMWoxCRr15tzt7MK4W0-t3N0VZjOt8fb-hLDu5WO6vbvqg_vTnL3731Tc__fKTr757Bxh8iErBJ0_Ofvj27t_8xR-XRfndyz9oW_z8k89--_JlGpIubN-5wQ2vfrgblVYX8Cf_7o__63_4dVVkt--2ShtEN5pXL99cj-r80BxEYBBvsahn0z_-5U-5S2cXcy1EhKBTCgGJSm3Bp3DoNk2z6tz799fbZltq-_3NB3ThuhsqIpuXo9KIYDz-ewaajEd1bpMkTpAEF-eT68Pu-emTpm_71tWTOs_V1dt7IJpMKtKqnqgPt_fsaTGdZSWZzOSZadvYbJt8YobWSZB-01mNu0OjUUUrMcjFw-XidIYevvzs4TQrh7ZFz3WtCEBQrVf7qh6V4-xwaFVWbnf9-cUiIuzXw_OLeW6xznOjQFy6vrrponvx7MGjhw_8anNyPmWXeuYU_MGLyuz_7f_x__6Xv3jxqz_6OSn-9uuXi8Vsvd3Mi1Fe5fv9sOs7W1hI6DkZUq_e3-SZqYrs3dV6VOWzRe36UFqTMlIC1zd7EsFM7_s-9LHI7aTKv3-7UUbudn0OAFoQUCOK1q7r9puunOeUm6Hx56czz6BivF_vCdhW-bQ0N3eHJNx1vbI2RkgQCXTTd4oUIRV10bVt03Qh-KzI-t7XZdG6FhmTViAUOn5yuaim5dAOg_O7piny_POn58GH7eCYaVSPBk7Xd6uwb549e7Lab4fWrXc7Qo6iP_vo4c3NKglrgLwc_ckXzzs3WOYAPHS-8_79ekWEzeDu7ps6y_t2qE7n719eTeb1_u6-2-3K2Xhz04wXk9OziUO3_7BVWTYa113n6lF92O3OLi7vr67abpjNJs3-UOQFKDxsDimm3X5vDaBAYOmGHhKQ0dPpaDKZDn0LWg-NOz2ZNENnUF_f3p8s5_2hM3m-Xa81yWw2ef32HaLJC2sUoVKjemSL7OzsYnV3f3N9f7KcPnv20dXVO2Pl5z_51FAp4Ov54s2r15QVv_3bv1-t2icPL37-Fz979c31u69f_vLf_Hx7t_1P__Fvl5cn__ov_lVIYX2_fvrxx0jnH0lMRIgox_ixMAsACQMhJwGlQRsRVhIBJDLo0YwSpjAYRaHrKSNUGbAIxBQCsChlBFlihMQqz5kFJAGzpAQAQCiiUCtEYBZICZRSNo9thyioSEKiIiOlkyQOQRMJEDAoq5MLpMm3reKoyzJ2A1otSCrLOPrkAxGhyI_DfVHEticSjAkUABEqA4ipH4iAUxJldJ6h0qEdTG6D94BAWXlELaLOQVuOibQBBEDQWrGw9I45pK4DBQAIJMAMRpMcq5siAEpAjOYQUWk6qnDLWtvCDQ6VUTo3ZRYDHNfyTJAGr4scgYRBkGyZ-dZlZZXNRuFwaDZNMa0j29nZ3GZ53zex9ykOQBSGQWcmJkmu06KGti3mU5HoOl-NxwLofS9JxsuZb_bRp-RaZSm5wTVtHA4mz5P3qDSK5OMpp9hv1gpBK5SQhABiYiJQCAlT7ElIEAXEjEexczz0mTExOEFCBOaoTZ4AURPZzHcHiEmTUUDAKSGIBgSInrL5ODrPKShSIIgmI0SWmNxAgIAEISEmAUgsKiuBELUVTeCDDA4NsYAustQPShEhcfIxJETQJgtD1EVGWqXgU4hECExoNGgDpBGgnCxC17V3u3JRkkJBjD6GKHpxMjo7reoZKLu7_pB8X45q33RANJrPJicXianbH6bLKQJ2e5cXyqDStSkyS0oXeXZ1vT5dlpcP5t22bw-9KUx_6MXqu3e3h8OuKLLN_bqY2Hffvkx9lxfGd20cvAKeXSz6bucPzpbZ9vrOKEr9gIjCSVIyo0qAeOiREzIIHt9nwogIgJk9IvaZmRApq4PrCASUkhCVzYAUIHGKAKJMnsIgKYIA2YyygpTiFJLzJMDBIwqSBq2QDGASEPYRAYmO_R5NxpLRIhKD00ofyzcQAxExJmHWWcnAnJKQkhCV1ohg8tI1DRmjy9oHJmVNVhBKikF8QESb2-NeIDHZRW3tyPeOiiLLco0wGdWH3rGwT4kTWFHjUT64IUQx4yyrSj9E7-LZ43lFxgX_-Ysn06ou8lBrrR1PJtWqHU7rEiXdrbYPTpfj0gbhwxDbQ0cKx2VhMw0hZqW11nKUxWLser9eH_bOfXNzv927Y_2pbbrJfHY6KXKtfno5A6SvVnd__e2HM10CJSC92zTjuv7vfvIopDCtq6Hvx1VxdXUviuuq6gZns4xA-mGY1eM-9Ov7lRlVs7Ke1XWXwj9-9d315vAvPn_65r4LANtD8_7dtXeQj_LFZAwgX372RPzw5nrbeldm6ptvPgyhX1T5k2dPjFIO0m--e9U37nDobW4hhSK3RiOTZsS2H4Q1HJ0RDJkyzoWHD8599GTMz798cH27e_Pt2-26rctMZ1bnmc7t-tAVLFWmf_nF4rd_2N_f7arKXp7Pr643rQveDyRQlgUoAuHWDbH1xma6sEWeKUGlqWv7FLmo7Gxcd66fj6u37-_n03HTtYPzSFCVdVHkSmcKYbvZd3339PGDwbmiKKzBoigUiKC0fT-ajZDRDwMTXn9Yff_9m9Gscl149-aatLp8_nB3tUnR7zY73_lqUp89OdtvtqvrW2stkG52m3IyCrsOjeLApjDCsdl3ymSjxUgraHdNfxhmJwvvQ5bZLM9Z4unjx6urm6dPnxDRt9_8IcsKSv7f_5_-4g9_87uLR5dZZpbT2YuPHj5YzhTwqMwMgfOhdzy4YKzarnc6s0MMfT-EEMd1fb9vqqrYbJvFYua6vu1dO3TtkILzo2r05vr29dt31Xjy7VffnVycny2Xi_Pp23fXV1c3yfXv3l1lVdEc2r7tX3z6-bdf_f7FJx9vN7sgTEp1m21VlT7A0HXPvvzsD7_56uHHT25fvuUUdG6C924Ik8UJR1-Ox6vN4fzROUe_udtoq0f1aL3r5qeLuqoVSF7miWhzv2oPDUQJIZ0sphIH52NZVKePL1WdXV1dm5jW623w8vmnjyaT6dhC6_tf_uKn_8__z189eHgx7Lvt_d24mnxY7R5enjE4VMbk2tbFatvnFh9ejL75-5fv3m1mDyajsshLe3ezscTjs-lhtRavYor7dUO5Wu8O1hi09otPPm5d_3D5YJLb6WjEiV1KAcCHQQJPayMGCSQlH1y4caG9Xe2cH2e6C1wQ3193i5PR6XLy26_fLE7G-841q0YX5ex0tlrdl5nuW1-UuYvxw7urECUMoarzk-lUWTW4fvDRtf784Um7a3IDYItHZ6cnD2aHXX9zu33xbE5KKbLZOO-GkCu12Q-b6_1nz88SqRTT5flJGHaLyfSvfv-trctPLs44yeOTk1dX958_ni-n2aiov_n-Qz0ZK-_H41wbczIbuX44nU2Ngr_8w5ufPz7lKAOz5_CP__SNI5mN5woBEatMzafLbujyolitd7PFsg_DbrPjEP_y6z_821_-PMszN_Sz6ejqekMK3ODrzLQuxZB2IZZ5phQPfdzu9rbQVzfDrNb1opA-6cxut_3tzl8uitbFxcz-1683T2ZG50bF9OH9zXRWd27YduGzZyc_vL7PSSVDRaYjQ9MP7aEVBElkcotK7Ta7qrbPXjzfdYebNzfe-Zvb9cOLxabpzs6XLkrow08-_cVvvvonQK5GVdc3JESRQ5S8spv94aMvPnn33WsSur65no3rwuZtN9S1EZJRNmqci4FPzuZFlj97crFd74LzhPju_hYZSClTV998_SrPzGF3qGbj4dCWo3p1ez84P5qUzc0-G2VE3A1eWd1tXD2ulg-Xuc76tqlmk9sPN9YaINJW7XctJqir8fr27tFHF03Tvf3-zfx0PnR-6BplVQysc220wSQMsFu1s5Ppi59--vXf_P1me6hHpRu8VlKM6tvrO0gpy4soaTaZPn72sBqNbt6-f_rR8w9XH4ahJ4Jd0y3r0eOnL_72b__rk2eXf_Ivf9Kt23cvrz757CNb1X_3n_-KdJ6V5fNPP_vu97_bDPHDh5s__rM_-ubXvwdBq9Wf_as_2u-62237-ubVP_yX3ymoZkodAeMozEePLwpCEgQRIhEQAgREFiRCVMe6oRARKtQQQwQRbS0wCgohCvOxBiAonBIBgtIpJiCEFIlIkFARIKAk0oQMx2g4cyQkNCBJEDUnQUWS-KiABZGEghFPvvgodkOMHgUZBFEJACjF0QGgAkGlUowASCgIAsIgAkBECo7KgyNNnRQqIykgCnunFCFpIZIQBFAXhYBIYm0MIqDSpHRyHQcPzICsCZAZJEFiFCYUiPyj-xYYBCQ6rQ0iiQiQDs6ZLDPWKKVSjKS1KByaIR-POSYAEE5Ka9LEIWijmdkfDuyjzkxirs9OfD-Evgcik2lCcL3T2vRNB4xFUXAKAMyRq8Wp0eBCiGHITNbc3ymFRJDnuRu6brcniabKJaWUos0tcMLEKUQEUCoLXa8MpRjl2CrVlkWOJREUUdoIc3DRVCWnKIlRjiZpUspwdMrqFGMMQY9GEhkBU4pkFBAlMaZ6qlUbvdPWpMQCIPwjRAiRTF4E1yMgKSRSIHLs_SIBCAIys4hipbW1NvS9MiqlRGhIEZEKISEgEXFiQhQkYFCAcGTREgIiJE5-0JmuRpXvWmIMg1ccdWltZrv9JgKaLK_Gs8NuxwFmp5cq-c2HayQVJWYmv7rePX3yYL6cEjIRvvuwZubtfrBGnZ5MCpulISyWYwXq9998_fDsQgD7wT1-cvb4o8fX71f1uKrmk77vqskoeu_6npQOjUteXO-0ybOycn13DNcprciY1A8mL4LzCAKIEhMCSuKjGFzw2BpG5ARMkoLNiyOEU_65MyMiZDQc1b5akSJhPl4imaLgKMzHng8DiogACGktfNR8JCGClExWoMQYgwAD6eDXQBkIowgLc2RJgEScmJlJazjeHYlwYkVgtI0hQmKdFSAonIDADU5p1LlxTWesJqAUgj94EUkSUoj90LMwogopAgIpUgikwPUeEBBBaR2C00a5ZphMxin6_jBsd80Q42EAQDUM4bS0EdTm0O4PA2j1brVnlqSNVoSMiGoxqqdVOR1V1tq-d5zCED0g3Hf9h1Wz64IXyutS5zqhNG1PZA6d06C6yM1uuH5zG5Jvg7S9DwIxhF0Xb7f9YlplqDb395rww9V9O_RFkfd9V1X58bEhRDI2CJLR31_d__abN-OymNXlJ88u__HrN8-fnR92bev8r758zhBP5pWL4Xa1Xu9DRGl6Z43NKz02pk9cTop_-O0PP3x_lQIzQ1nltrScOIQgyhy6KAljBGRwLm5XHRkzmZV1Xuy6Zjke3d-v79_v9tuD6_2DRxc2z8qiQFTddn8xH5eZKUB_uHd9P1Tjipn3rVdK7du2qoqml5NFbSw2vUtJRpMSgYuxHVx8-uzB0DeT0ylwyqqCBQ777vpuV-R5WRW991VVFUW23ey9D-_e3iPxdD7JC-OHGKPs224I_vZ---sfXq5XTXC8PTQfru5fvrn-cLX--qsf9rt-6IcUgFNkgt3NzvfuwRcPCODk8TnG8PJ3r6q68IMjhd1uj8Lu0KImidFaG7wXpLLO3TAoha51s0cXmhMqzKs8hNSHYT5b7FabUV0SpKHvgdIfffHF00cXN2-u_8f_y_8RXb8cT158dPnx5alVbJUCFoWEmoILLqSbu3tgBq0fLCeBj2s2_O7DalrYqq4AJSR5--5qfrJIwq7ry1HVDX3fu9dv3z7_4sXmbr04mb59f71bb02ZN_vG-_jg8bPpfD6ejNZ3d4mTze1mtbt8-sQa7LteWVPVtRs6TnLy8PzD6zd1PSnzkRs6I5RlemiaxBxjBFRd6y4uLwghOD8EV2QZoBRWJxQWjC7Wdb44Xe5We2OVEPZdP7lYdsPgh0E79a9-8eLtzVoLlDPTdmHbdNPnT27e3Fxd3fzJz39aC6_W99v9xhb67HLa7LfFOBv6rlk1qXU_-_JBvxsOuzZYGc2K29e3zXqzW-9SFyKnbROWi4c__6P_Wcf2V3_2WQAY16M0uHZ_uL-_3d6vfvf7b9_dXv3-2z_84x9-_-27V9f3q7_96nchxLfr27_67XevV_dfvbtmhkPnJieLjy7P54vZYrKcLpaz02UU-P7lTT2pPtxtb1aHqjIPfvbg_atrH0I-rZQp8nEZEvteLh8vT8-m6GJmqG8G1_qs1JNJdXZ68uDi8uHDByfLuc3yMMRRoRn4w_3-bt2gtm_e3fgkm1VDqE8eTvKqskV-en6xO-znpwsBeP7w7MXDk1mdn5_MFaeTSZkb_eHN3dX97mw5W0zqLLd5nvX7_XRSj4uaiPpumI1zo3Qf45vr2__7_-v_O6pHk-n4048-vvpwdWj6qq5tUf7Dtz-8enNlivr7d2_vbtcv37xfjuvzxaI5NFVR_ONXL0e51bmpMiNIf_v627NqbqwtMuuGIbd2UlutbAqprCgCNnuvisKHsNs3y9pO8iz5QSv1xaPRssom06LI9XIxy6xCaxen02bbsFZVZZVVIDqxpBDmy3mdFSnBcjZJDJpQa3t9de8OPVlNikZloQx1XdBlvd13RWZ2h_tpYQJg8snktmvaqi6y0t6vtpLk_sN97MX1zWhcVeNJObGICBGalnstZVGenE4LawlxvdoqYj2vr95c7TtPRuuiuLm6E07CPJrUg_Pg2Wa1jz0K3F6vp_MRCBhrRJlm46bL8fR0CpE02SSMSN4P3rm6zFfbxhh9frHc7feL2ag9DO2-tYXdr_b1pAKNu7vDfDGuq2oymeYmN5mdzadVmX14-Xa32ZtcPXz0wBgjHE9OT0f1-NHjR598_mI5nSvgvK5-97uvmFM39FVVhjiI0ItnH0_G2WJaf_zsAly4fnX36GJZzc_--u_-8b_81e-yunr-4pPVocsy_Yevvtu3G6tl6MOf_tkvvvzy84LMeD7frze__cP3r37_MhsahdVMYiQiJETCH72_ikBYBFARcwRRRJpFUKGkBIlVUcbgU4xkLPw4i5AICIAiAgA8soM4IQAQSWLQBICCiIIoDEDAwgAgIJxiYmWz40vCMSECHJmhkVkppZCFWcBm9phOiYlDH0gTKoWIShuJUaJTSiNzAkEiDXCEPUMSVAqYBYWDICJEJqMhJVQgrk8pIiLpTDgegaFKGVJGYhAmMopZECW0ew5eIZCxEHpMSSEgCxKIMCQGgqP6APhIRAQiEhE81iI1itJD7445K-8DgCARiMCPdUlK0YWmNUXp2wa1QUKlUBA8gzJGkGyRCce8KtvNNoaICNEFBI59d7hb21xz8P1-ndi16y1oduu1UdyvN0DoXJd8AN9H5wREkUiKHDwKikREYAGjLWqVvMuyMkYnEQQSEHJKkiIKgjADayI-Sh9iIq2BGY83IYAco7Z58uFIPkVSiCq4pLRmLexWuijjEI8OaY4BhiExZ0WZRNgPWT1K3qWUIDEIAgLCfzN_GWUMKorNTmVlXo981yqlgg9oNJCmIwSWBIg4BCCSEIVFaY2KKMso08CMgirTiUUAg_ecAhCJqLDbFUV-uF9lo1p8zIt6_eGda269G7SimEI1nax3q5PL5f1um5elzXVRFvNJ7dqBrLq4mCvUZVYIsuvcerN79uhp712ZF5GlKLKzk0kU1EqHwJGhqkbWmqF1KElZQ0oFHxmT1ZpQKWNQqTh49SPeR5TNfrzjIkQQMjmgCIvSKoUoCej40QNKKVKWKaNRKw4RSUgBIkpIiVkbC0iJUaEgYepbshmKAIA2Jg1BKQSQFB1oBUBAhMxEGN1AWgEiaiOCSEZiUlmOzIJiihJRjrruyImUBkRAFAFjresHECZAiSGxI6VRkQAok_m-D-5o3ujdEIhQK-AYhFPglCGFwYEhnWWcWCIDitUqBT_0PSG79tCtD8PQU0n71d77qBRKgnJRzesCgjR94Erv9s61vRnpQxPud7uVD6ttH5MYqwPLfFojsJBqu-71h5vf_XCz3rWrxkmmdl38sNqCwvWhv75aR8-Dc4MLznVaKwZVzsqTx4uEuO_DdjVoq7U11ipC8QTLOs-sHtf5g9MlWT2pyjDEfdf_-tXb__SHr-52QwpSlPm-Gd68vr04meZ17pwohNBzcziMqxoV2Cp7YMzdpnl_tQ9REvKH63WKwpGXJ_O7zWG3P5RlfmjaKrOA0jVDSCkJk6IiyzernUEkQK1zEBiNSkV4cT6HxNN6jCD90BdZPq7LIUQRAEUJwOR6Opv6GLKicIPrerfZ7bU2RLjZ7rVW0YhHrMpsPMuTT7YqTJ4VWYbCxmpUlCm7Xq814tWbu7wumn1z7Au5FEdV3vadC6w0KK19kI-eXSgF1uoQ42bbmiIbnFNWHfZ7N3gtog2GxF3T3d6sEVNILnQhSSjLQpHqB29zIxzKUbFd7Q6bZnOzCsGjlhS9D4PrB4U6q0s-Cjd6zxJBUUpi6zoFh0g6yzJrbabLvADAyyeP_b67fPTI9c1nX3ymQD7--Hlm4eHF6eXJ3BC5zfbjpw-s8E-eP2Xvtvf7-awmpWOMu32_Xu27vu-GUFb2fn_wUbTRg3NXt6tHZwsAcoO31jKnKi_3TZsAQfCHN-9PFnNTFlVZny4XlbX7_WHo3Ha7JWvquhrN5ofden19d3Z56ftheXHeHPbL5fT1t6_KyUQkajKH_aaoyxhiVo4T-8P9mrT4oU8-pSSnp89i9CpTkkLs3Ga1zariwbOPABgYmvudH_pZPfIRg3NFbpzrbFaVVdUe9oSEBO_fXksInORu3VRloRLstkEgzGfjb37_7R99-Vm_75puf32_-eVPPi6q_Lf_8NvRaP7h-m6_b--3OwW4u1vRgGkwv_3NN9vrfVZl-bRMvWOBnnnx8PH29sZ3h-9-89dtu_n-2_fJ0_PnDyeL8f_07_61ydX5k8eLaWV02TSDuLi7P6zu16Wxu82BhwAhdlfb1bv7w_awX22_-vX3__TV99-_-vDddy-___aHD28_dMOegNt2V1ZF3A8px7ffrPrdwXf9h-9eDwe3u9mQQqXIKJVbS8oMDi-eLJ88f_Do-aPlfKaSMrlpXLPdbFeb9dc_vNsdBiepKrPFdKKNHvp483b_4tOL5y-eHLZBGE6n4-sPH07qjCRcvb_PSU3qsm0H71JZ5pZUEhlCvDyZAwHHlGfZert5eLaclnVmlZfw9bfv121ntd61_Xrn_u6r343L-vX7q8xmRV60fbs4O9veH759__bxw0dvXr2qivKLZ4-ePDxDZd9drUIMfe8-fvagPxzm86kmlMiLapxIOU7MKcvybTM4F5OwsaZvfPBxMqo4peRTkRlNat8PWZV5lnd3O2ZsXXRDTAqIdKbzZZ6XRVEU-Xw5JVSj0r7Zvz2v58x4OpnMZ_PEQ1WW9WyktZqUZZbnxaiKklhge9dWozrLlGJAiZj4ZndgLyrXQ9sPLmS5SSzbQ1NWeV5mTz8-mZ6N1ncHRuyauLkfRrNifj6ttC2REqe-85v1gVNqulipzEPSleEo--3eaFVWWZ5nXTfs7ltbaq1xGMJ4OsnHZjmbFlWmtOXE8_NxXdVIZJQahtYQpcTFOF_O5oRk87zMstl06p2r8iKyvPj8xW67OzlbZNbYrFgs5wzJaNN23WHfJ-EHFye3d6uhc1ZZYk3E-10_mY5OTk98Hx48PL9cjjf7gyZyfZ-ZrBm6zvvo3Xw2-7f__b9Z363fv7-VLH375vb-dvfv_4d_cXox-c__9deOYXY2vThbFuOia9qrl-_6Xbs4mZ2cn11enKOoXRf--u__4fXLl__4698fmh3EkBEpM1kICyoCEMBjD-AoBj7u8gURUWtmPoq9CBCSJI7KaEhsqlKSAIpEUUSIlDhxYkAyVSkxgsixWgBCAIKIwIz_jDs8juigFAHqIktRgNlYJYwIQIoYBEFQEQuSUpQEGPv9AQGRADmRJolCxjIzHnWieHwY_HHER8WcUESEj3VQIpSYBEBCADzebChIApKItLKWfdBFLjEBCCEiEEjShmLXIAd2A_hW0hFZipIYUeD4QzgdVdsKEYkgidIZENDRdntkrWudjrgVo0hRCkEEJUayWew7hZB8g6iVtcoolCiCMXI-mZgiJ6PzvNjd3bT39ynFGBOSiX5AktjsTKm01kPTEqUYBkQxOuO-RY4IDMicIrtehg45qVy7_V6YOURg1lr7oSdtCEip4-jZGWVEKzimuUTIGlTAiZWxKUSTZ6QVAyCzsUYik9IokJIwJ1IaU4SYAEgVJWhgBEoCzMklZQykKILKWswzcUPsByJSWR6GAQhIWyKljBFhZD5OsSJCpGw9AZYUI4EIUQpBW5N8JKMFAEVIESIhKqVBHb21nJTSKUVhIaX80AOLKkswEIbBViWHaK21BiFBiNHtVraqbVHmpY6uF04EEH1oVltT6P1uUxXm_m5dmsIU2pCaTkfehW4YCmOvblbWaK3o7HQBAolFSOoyH9e50mo2KZu-n8-nbd_3_ZASxZR8iknA5pkgQvTCHNzAzCbPyOrj2B32TufF0c2GInJ8VytFygizICMAAEmIpBUicowioLRVRoFAigkSK5unMKSY0FBeVclHRYojC3sUkYSo0FgbQ0CFifkIBgAkMkoSo9acPJJOMWqlCCgmD2kgrYWPHSFBAVQWFEpi_c9uMiLSVqcYEQVBpRQl-eMtASHYrFZaiwQBJANEgMzJe2aOXS8iDMLEru3BJ3YBkmiLXdchoR-czuxRMmKtdq1HJNJ2Np9CSM6lXz2c_e7N6nc_vNvsuk7SauPQZkppEjiZjXa7hpQ-m9arzi2m-dW2iwJd4MViOoT4zfdXd_fb1Wp_t9poRbcf7ttD2w0-JowpIdHAUuYZDaK83K_awcfJRCeGGCIgdL3vhv62Ha43jbE2EWilGKQqihDTuKq-OD9tDu1kMqrr6tC6Rw9mi8X40awe5_mzB2eLefX0ZOkTl1lxc7-xefnNu3XTuPG03O2bFKNS6stPH15fb169uskz2q07ARGMRVUoQ1lukiSDahgcoirzghEny9FoXtZVVpa6yPOhHQ5tY622WW616fo2xXhyvjwcDmVRAKLzcVSPusN-6AYAyApTj8r7-7vT2fjs4sQAP3l8ysJu1xMmjCIsf_TZ0gtO6_K7r98aJdPpiAh3-6aocmYBlN3-YDTOxtVh3y7qOrHE4Iu8BCWTur692_g-eudjlPF0dHN10-6HYXDWZDdXK07Qt8Prrz5khX7w5IHVRIDPP3pyu7kPLnSHJvne9W10ru87MsLec0z9riNkMpqTZOXUuz6GoLIs9i4fF8lzNR0zJGttCnHYbzKVffL8sz_7H_7VzbsrRt7vtn_0L_6Ufa-RJ3UNEl88fWopLab1x88ePnv08OH5Isutb4fRpEZE72PXDXfrAxLMFqPIlGeZVSbEQALt4E-Xy8F7a21mC-c8KRRC5zzlZn9o1veby4vlaD7J8-L9u2ud5X0_TOcLH5Mw94cBfCdJqvG4KGzbtJu79eLkVJHORtnV-9XZxbkbfJbn1WxKCrq2JTIhNCkd7_NFEIf-YMvSOS9Ak_NZGnoiXF_d56MaWfKiGFq33e73681oXinNm7umLMzZg6W26v52W03nypJzPHt41hx2Qy9FbV58-ujdu60GDJy6_TCdTi4vLt9dXR16Z8mgUut1433K6gJJA6nyZPLD6-td36bQ1QsLoA53DVldjOpuNXTrtdVUWpMp4Cgc-vvN5t3766ub1d999fXteh-Lor44HY-qk3n14tOHFz_5uCRbFGVmzPZml1ysMmWUxhSLXJtcWWCSNJ1Wvh_atks-Be9W1_v16hCBHn70QOnkNv18UptJXmhCSt5FjSbGcH-_adpD51tbZK7v7-63d9frcj5---rd6n49OKcQTy6WNoOirIOLRTlybRSWi9PJdDz65jfvLMKzR4vcSK2zf_GT5RDh_tD96188dU5S72ezuspMhNR13cl0rAmrslgspkPXjuvqYjHhEGNK16t92_daQlbW-97dbNa_-tnPx5PJs0ePrIFHjx-JpEPXf_fm9WI2_dknH7ft9mcfP40I3aH9_Zv3_-W33y0uzr559-GH1x-iwmbbNDG2jjvnmhDQQNt7bUlpJYCk1a51RW0dRyISoGqUZ5nNrCKj7-_3VZlNSrve95nVu8MhuBhCGmJgAJ3plhMG-Wg-BZTHi4tJXdRVOasrymhcV4OiMMS7XdMNPSnNwN3BOx_H4_GTy1O0KjrZbZrex5cfbo3FAm3TDbnVDCq4eNh3q_v9fFytN22z8S6mxXQyLvInDxe2VAWY9WpbV9n11Y4hDRBIqWpS3a23h23X7lqrNEtUJFev709PxxFS3-y0NUrrzBrgEJrBD46EylERfThfnnofhr43CtswnC3mAnh5ejaux1WRPXtwnpJcv7vWWofoRlU1tM1yMikLWxYVaDxbTLQ2ZVXMZuPRdPLgwXkiUlrV4-L5iydPP73QmY6BP_nyRWZtYSzZ7OXLN5vNXeuDIMboH12e_Z__p__D-XL52UdPbPL_8S9_-_hy9vnPfvn4-UltsrNHp__hf_n73339fVGPXn39W5sVdze7l--unz---PzzF08fPvirv_yn0-dnN4f2f_tf_3L37u1hv-saN5svWAQ5KimmRATpmCpOx_QKIv2YvkAQEEmirOaY4J_bAgikyzz5CIiKNKdEKESUYiRFpJBDBEY4nitiIk2oFSIRkYBwcAAIqEQpRSQEHCJL1EWBojhGBOAUQQS1JW3wCCiio2qAtdK6ylIIkgSFGYQ5kcmAOcVEICCA9M-XGCiIyFFIEfBxeA3ATMDw4-lC4zEDxUDKoMI0BFQUvdfWQAIiJIXsncSAApiiCCtrQFMKEZMcWewoCQSI-fjkISIRIZLEwCyIaOuRhIQIHBMpVAmi9yCijAIAGTpATCFko5kuS6uM7zqJYqpCkFCZajohhH63GnZbCX58PnO9c94pDeGwJWDKlG8aAY5Dh0C2rHyzFdclH1CBQmXKsl-vARICx2FQ-p_pTIhHRCkCAoHOC1JamFMIEgMkRiRQxMFpk7EAp0TAKQTKMjiyNoS11jEFQoXakNbAokxGpEWEU8wmMwFJLihSAJgVeRx6kOOTjyyAmkBEa8PCIsLBKWVYmIzCJCDCKaIAGQuiAMQUhdFKUmIGDlEbLQwsAMxKKUkeUaGIInNE43ByZIgTSwrWGmAJQ0-KtDHBBSKI7Z6TmHpsMq0Qu8N-dH5OrLp-AEkIIikCSuw9CFJuXNPuttvtum2j27EjnR22DRDFOKxWu5tVc2h7XejJuGaR-bT84c1tlZmhc-PJuKjKxXx-_vBhPZ_NLs-L8aQ6nXXbbXAOQXwzIDOyBD8ggzZWG4tGqYwkMQCQUqT_-WMSHWqjlBEGYlGKABgIABFYRBKqozgUmJOkpIjyauL7joPXeRlDIKMlMUBSWRbbHo3W1h4zVMl7MkRKAZAQExJHluAVCSKitVpbFlBWSeKj31MEko-EkGIQAaX1f6OCap0JIAAAS0pBQg-cmFlpIwBKaVuV0YcYYpSo8xIQjDWoxYigC8XYGJ0n50MMIUY01reDNipF77sQYzCGptPTwR1SEEGOrbt6e_fucCBNPsVD1-26wTPf3e2LcbnrQ9cFrbUidb3aHTr_oW2b_fDrb95aaw7Bt72bj2dBUgJ68vGj29UGBYu8bF1AEuYEAtf3-27bHla7ISRtcpWp3rnDrtl3_f2heXg5G1r35vWHr169_7BpXq-254upcz7EWBVF70JZFZO6rkcFCL5_t-q74duXb75-dXUyH_Up3t9v73eHGGMKrnHut2_fG0PzSQ3Bk6iqLh6eTrMsu9s0mcZMm9ya5tDNZuOffvrpcjEeFQWgmRaFZvPT5484yNnldGxrnSJHDxEkuU8--wgSnMxnKbjYDcAyKrLtZj-ui_m4Wr9fnU9LCQ4iI8Pnn318fjb_7g_fPv3kyeLs4rA-ZEoZKrarfWH0dDoHq7TRt6tmtdo2fU8Ek8mo7brO-Y8-_cj1w-OHj2MIIHwyn--bbrfvF_PxbFRro5Dh3bsPh8bllbW5brseOSHB_c16cTrNSptNSm20c34Y-rJSIQ2b-_37tzd5Ye_uVu2uZQnZpNrervfr9WQ26_Y7pVTbDllml48ui3ocXAeIwIFETJETsa1Hm7tVPZu5Qwuk-7apyip5efr8Y2BJQ__y-3cvPn3-5KOPdnd3n37y6XJSzke1ofSnv_hFu909OJ8_e_wQOFitJDIZlYS3271WioEZIAqwjsGxc309qg6H1hqzOwQ3DEVuUKnNevP-eh18EmFmtqTf32wLa7rBD326ubutymp_2CPhYb-LiSfTefLDets-fPSR1moynW9XG6PJDf3tenNyeUFJur5DkHJUNW0LAiSyvllf_uR5kKSqzDW91TZGSc6JcEQcmhYZDZH3LvTu7vq2Phn7LkhiY7WEZI2pqsn27tb5-OjpQxflsG_yTOdGrW93RHTY3oJw0zWz8aT3zjlXWnN2vnz56uVnP__l7eqOCSBTtrCzxQQzjE40iZLkutZkSaEowt3dfZ6rmNLls6WIG42zh4_OX_3wThf14eBAkaC8u_p1mU246WXw-_dXt9-_unr9YbNrvv_h_eZ6VZ5VqPHRT548--Lx5SeX5mRUlBMqodkOzkvb9SeLWegHi7osC7cLs-Vk9LA8f3y-WQ86JIpw9vG8Pr8Muz4xBMwqZU8vJw-fnLz47z7VWa4AdIS-6QlVYml2h8iYoBgvTp88PB9auTxbarLnZ9PL8-Xl48XjBycnZxNL6vKsfvpoASyrze7ybO4c7g7h588vtckSx_PThVbour7dHWZ1LSFYo1IMBKnrusvZqCoLY8yuObz37elimqncJW7c8P2rdy8-e-77AZjPTk-iH757-eZ2dXdxMv_ko-dN07s-dC799d__9p9evr3a7caTyatXb6qq_vM_-em__PwZc1of3Jub9fev7kip-9Vu33T_-PWHtu2b3ukiW-2b9uCjYAjcx5STWI3bNrSHnjkxpASkM8OctFKLeW2yjBT1PijAofUm010M23bonG9ccjF4DQn13WafKXNo95kpBNP9emMp64bO5mY6Kt7fbDa3q6HvlKboQ2WUbwcXU5FjilyMyq7vTK5OTma73WCsnkzLus5GWZE8z_LJ9Xpzu9pWZbHb7S-eLMpl2XWDJj00LnHY3d6PpkU2MiCqa4anz56s1tvB-eXFiTXZ3fWqtJpDWCynWZHxkVyvqO-H_aF_8fkzAnz6-LEmFMG6zrxzdVWv1jvfu7OzZZUX88VcmNq-V0a9Wd1royajcW7tvumCwOD40DvXH958_77vB1PmkPDlH143-_1kXt9cr9-9fTue13e31_f3Gx_TJ08-_tkXP_3yi09HdeFcuLrdosY3H1abze7Zx4__4__-DyZwaLsPb28hU-PJ1O2bz188n89my_lyMspEdFbBX__dP755_Xq_2n745nXyHYpwCKhMcM57UUiKqjlqhKMLOCVU6gizFJFjYPo4diMqAAZBAuDjFv-4vY6cj8aSOHHkyDYzIgDHbiLCMclz3EciACodOaIgao3wI7qRU0IAnRkICRhRK2E45oZACAFAEQiSIkBIPgCIRGEgazQwcwz_bQGPKAAIwggCAskH0hoFjoZhFGQROUJGNUlMCCLMR8SNAAAREkXvCVFlln1QRMzEwqRU7HuChCkyJxFgEaUVKg0cFSlQihmQCGISYUQl8KO4TIQ5JURNVhMgKvpRjcyJtFGodJaDH4STxJhXRUqYlSWQ9IeDyjJSSpcTQUKjow_D-p6CJyIwilNCJSqFNHRGa6QkwaEwSpIQFbKE8GOt05gUAhYmuYE4ESBAEj7-qsdzFaCIIISQtMkScxy8MjlI0kUmnIhQBAWA8kxSIkWYji8KpxQQEP753CXqxwwYI8TQ6bzQCv0wAKDEiMpwYmUzEOaUdG6FxeRZ9F5QohsUEZFm1x_NbMetFTJom4mkGBgVAGnf98fXS2sNSPIjcgpQUXJO2Zw5IukYAinNnATw2LtIzCmxspYQEVTw3o5rCAGQEcl3nSkrlRU--X69taOR1sVhtTKZhhjZp-nphCFFJf3dXli0VbvbDYhpu6Ztd23TFXXlfBzNak7OeznsO6XpwcOZd547_9dfffX5R8-afTubT8dlNZ1NZtPpYjLVOrt9_ca5QeeZsiYrK5Nb37TaalOWvu_JGA48unjAbggxSUiotMRIRiMAGgNApABIcYgCgkTCjETCgkoDCABycIiK2WltJKajPgxETG5jSux6lVv2kQiBFAoobWOMCIxKcQIQ0cYSkkjkmATEGAtEvne2KI7xPSQkq44IgSNTmJmV0USUggfSSATM2uQijBA5MnCwWRmDxBBtlpHRTOS7VitIMSArnT0g2Q-7VuJACoGFygwREEkpnXwYLabBt_u7jXc-n9a2qLum98Ej8qF3RZ2TzhSbvu2MqOi5GbwSxFwz4a4LTUyGaBj8u-t1lqvZtFrvfdMNZWWdh3Jc3q82N7fNYXAJYD5fDn0sq3K-mBwOrVXImWYQNABIJs9NZhDAh3Bo_Mn44XbfnJwuG9ff3e8_bLZJ1MlshiJK5HbTZsYUWRYdLubjxWwUAj9-vNDa7vftzf366u7eec6L3GTGGCtJUPFiMSdkQ_DR44v_9J9_k2UUfCxtNh7XPrEGUCIZ0KKufv7s4tPL5RdPH7jopqPiwXz-q4vpuue2dfuhCYOsVzsF4Pu2LsrHl-cMuJjXyuRfPrkoMhrluTWalL44PXny7LTv2t__-utFOT4M_vRinhtNRu-bncSY5drqfAhDWWV-8AL44Wb14MGlc3HXtkoBJyxH1Wa7RlTamqeXZ0obY_RyOuqCP7S9c2E-mQNKCJKIo4cY03bT-CGMJuMUwvZmDUjODZv71XQxGfqeEeq6jCFE71MYqul4GFyWW13k3a7L8pyMAWHUFNvQH5rjxRkpKopJDIETaJuPl6d-GJTW2ihOSRv76U-_-PjT52fLmQL-419-ud8djFE_-9lnFjm6ZlqXIOrzjy5PZ6PFZKxBQu8Vkc2MtsiRuz6gcFTUuXi13n33-npcV9oaqyxp44IPwVurx-PRar3vh7Cc1YlZa60I15t9XqhxPXF9P5-UTvD9D2_uNvuTk_lkNhqNx4fd9upu_ZPPX8QYgfnVDz9MpvVkunTOgdH7_UEbQuGPPn2xWzc__fmL_fbQte2oGnWbw6ie5pmJPg6NN1keUkBC9qGsM4XkXQgx5VkGCCmk5cNlMSqGfaNz0zSdZ3d-eXF3tXXt8PTpQ2VFMXSHYbYY7zfb5eXybrPLVCEipjLleNw0h7OnSw7y4erq9GzZ7w91Vbt-yLOiOfjM0qMXF2-_v2VLPerQcDEuksjgPBXF7r5nD9qagwsRgHNLi7rZ7JJwlNEQRIxdPr7wPkWBPLdt04zmRRh69mGz2rz-9u3b769UrlLjn3z5eF4VVZYtPj59dH4ChFlVTx5f5EU2u5wl4P3aJScPP1kuxrZN_dV1GBtcfvbwcjR5fDJ9_uLUg7z6YevuurxWdVWJ4PLsfHY-OT1bTMajejz5o88fPzobj7Ps6fnk4dn0bDoprKmyrC7ztukBdNd1CejN_SYv8xj4dFxlNlvM6tJYCWxJaQCrqSSzXI5OZ6PkU9N1D89OM6vOZuNRWXCS12-vbw_NWT1GId-HbKTLuvr-6_fBd10bfvL5R4v5hJgvL04fzGbL6cJoMwzDq83-b37zzbobzHiqtf3DH14_uFxeXJz7Ydjuuw7gb__w1pCYzDRNv-96m2VVaasyiwzNoVNacxKRpIw6tH2Kade6MMTIcTapY2JG3O2buson59PQ8u7QS-Kru50iIa2MprbtIksIafDu0HQ-wJs31_0wvH93E0MCzSjY-SDM2_1BE93cbaO4GCMpBVmmC50E8zKTTIZIMcr8ZDKa11GgG_zywSwzOnZRk2na9tGTk7v2wAKTUV2WBUoKjH2bmqZfLEcoMrhQLct32-F0NkqJJ_VYo8myrKzKGKAs89E4y4rCBWfzPMQUg1Sjcjqdtm1_cXmWaz2d1BzDeDwuC1NYaxUpNMENk0kVQkzsAWmz2Z6eLAlxWtWHYWi73qdU5Bkacq7fXN8wolF0drY8bBo3REzx8tHl9fUu17RYLKaj8YPziy-_-PTnP_tiOi5J47v3V7u2BbT3q7vW8asf3lurA4fxuGLvv_rdS9H66ePLVy-v_82_-hfeq8zaje_-6j_89aFrfvMPv2261jnftX6_GR5-8hgTLy7OuiZoa_JRlY8KRZMTRBABOGo-EeEYrwEhQmE-jlWoFTAjItKPmH6IWCxn4H0KUdlMWDhEUnjkMxICy_EQoDglIjyyOwmJQSQxEjIzaUSlOfFxfJQk2mZAyAwco84yiQkRWJiAQICTKKMEEiEiobBwSigiAKg1CACzSEIgJBA-TpCKk6jMpOCRiAQQUWI8NgiJ1LGyzCGhIkmJtDq2IAGFOYExqFRwHQFLjJwiGausUUZpQ-HQASEchWdHnYJShAjKIgLIcT2OZIwgcEzGGGaJfQspcWRlNSlMfZO8RxJBMlVNCMLs-k7bDEhXizMAjsztthEOqd9DHGLwwuwGV1RZe3uDHGLfQvSSoiCACDAjsADLsZUQHB4roZyAA3CSFI9_JdlcJB0jS6AUkDoWQCkrCIgFIEZIjCDJRSANwoQo8Sh9Y8qsMjqFgJyAQUIQZiAim4kIaJu8R0RTjhgEFLLrTVWFtmVhYBbnBZmUBkAkxJiQEEAJ_XghAAIgCAQojEqhppQ4cUDgMAwSIylSBNF7TunoWUMkSYEDIxFo4pQUEZJOwGQMquOJImpU0TthTn1v6nEKINEjAUfvu9aMRnmeCUpus7Ia729ukFkRtPdbawjZpa6PIfq2MbUZ2r1zbv7goijs29dXRZkDcGYyliQJ8rIYHIPwvKp3-_58OS_qKkZe328OTbtdrftuGJwbTU6oLBJhVlTN_cZ1XlmbF6PgHQABJG1sdH0-nySfgEhpIyBGWwYOrtdFFYMnY0gBgAjzjx9lxOSiICpbKGuQhYMXjkpbjlEpzcyEonQOQJCSLjL2kTkhEhlDAJIAKCGSRCYSpZSwcGJC5pRIoc4K17aIoqwBAYlB2TzFBMAojAjIx8s4SiEQCRnLMZq85iGYzEiKqW8VKlL62CPmlIwysW8RIEFKfp2Ekch1Q3C-OlkMu63EqACb-xVqDK4bLy5I6a7pJHq_2_TdYXPzIWntneuaQUS6Zv_w7JxDX07KGMLLl5vHz0_evV-vd812e1C5OfT9etcOgx-ElKEYeFJkj-fTd1eroi6jpeub-33Td11rNA6SvCSJoemGq_tVXhWbfbtpHSqySkWW4J0SvFmtskpd324S43xR3V5thsTX-0MXwul8PJuNNKl31_eTOp9PygxkOh2z592mQ-bxpA7M3juTZYrMZDaejcrcmHqUZ9b--3_5-f_vL3_34HL26OFyPqszjYrw2YPF8wdnRWFYpKxqh7JnuO7a8WK6uJghQrLqkweLZw_OXlye_PKLJ599fPn5xw8_ffrw4ny5mFTPLi-KkZ0Zc31z17RDtCg2G83qxrmXb-42u_Z663WBf_5vfjWsO-ejBrm5uUvsRdLsYtEduhhCOR932wMHTjFV45wh-bZfnMwM0riuT0-W47oa3GCAjNZkdd8NjKnvht51ZW5DDKvVvuv7alQonWyZDb63eYYa22ZouM-y0g-uO3QYBZXab3bluFSk28NhdDLe3GyMtnCMugBmeaVAA_gisz4GUDqrC5YkIEU1ThIFmQzlZdV3h-l4_ODjZ4-enX3x9PHf_83f_smf_NRFX1hzcXFaotiYPn_-fDmpf_bFs9ooAK4y62PU1gwuuuBvbrbdEENKAtR07uA6a9XQ9oi4WEw1AhFtNo1WcHk5b_vQNn1RVcKgDXWDX2_2jrkLvNv3uQIPEry_v9_YzG43-w_v7513WVGdnS66wwFQyrzYrDdFUbSDM9bOZvMY0ma9uXhw0ex7Qm0qGyOfnF8KxMlkFpInhmo0JsLx6ZgZFZFSetg3JrOECICaQGuTKXPzdmsqdf7RY-8jkcoU7rf707OTtms2691idgLCVuu968ajol3ty8waraOk8aJmH8eFhcQXZ4sUXbPZ399sx5PxyWJ2e7cu8lyLXixHmTLPP35sGEdlfv7skgOPx6PpZMQpKEvBs4_p9OKMSTTJ7HyejcpkcHI5zyrj2iGzyg3PUEEAAQAASURBVO2CzW1R1vt1a8kc1vvUR-gHCpwav36_vfvu5oc_fNjs23bTHdb7EEPXtBLdbtdLCDpTyCAhDm1gh8bmjx6MxouKBqjqfLKo3626SKkNrSLt-rjrYmazUVWzS4Z0lumL2Xhk877tHl6O6klJIJ1zQxcms-p-fRi6fntovAuK8NHZYl6V54uRITRGW4VKQCTO6gpEjKJRUWoERhTm8bgMzhVWz0Y1S2oO7cY7AOiGocjz3aEtbC6Jx9Pi4YPLT549yjPt3CBCVx9uxnWR2-xus1_tD1-_fqVN6bz3CYPzP_3J80ePzu7vNpOyzDLz4W63GNf5uFZGh5hMbgVgUpUM3PdOgAVEa7VtW0WSZzrTeui9pDCqyu2hZeDJqJpUZV5n3XpoB58p5dxwshxnxjrvFFJiObTBDa7ddqNJ2TddZimEaHKlrDrse2VM9EkAjFIKMQRnM-N9TAIKJUeFwifLuiqr0Lnzi5PD_a7ZdAR0ejqVLmAU70JVZqP5aLtvi7ro29Ylj4qyshSELNPjqvRDrIpysZjWZB6eTUMf2m2oxlYhYKaSSD6qUnSL0XzTHkb1OC8LSaCIZpNJf-in9Xg5n5RZ1h4OTz96st_vOcSqKglxt15xZARaLGed84OPMaa-75hjQp5UhW_doR3e_PD6sG_2m2Zxtiiy-vTkZHm6IGUuTmefffpsVFXT2ej5iydVVSqt69EYCQ5N--7mHjT84fuXL1--2qw23fbw7s1733WTarzabeq8ePnte6PtFz__pKzLk8uT-8P222-_u7p69c1vvtIK3GHvB7_b7Ccnpyzy0z__ot202_vm4unp5PzUagMA49FYYbUQZsotpEREIKBNCcxIcJSPIgAnEQY8JlVSIq1BGJEIAZA4BJ3liJggQmIA1NYyJ2RARSCCSomwpOM-EjgJ2X9eScZISh2LAceQPEdPylibxaNMFAESEyFZA4h81AArJYFBIRJJiqToOPEoY0SO33-sCBypMem4mVbASisEdXQcIAoCCCELAAIohaRAIhxjCoqONWQwBkkIBIQlHRfhzDERM6QIKQEiiiAREB4Nr4CKOSIix6ToiFhSpC1iEhAE4RCUVqQU_6gKDgBM2gho1AYVRedSYGWMnU373QGVAkLiJKGH6Hx3QBRS2vW9QkltoyShRIgejJYf_bGEInLEvBgLkmJwkFI2qeMwHKE9qI7PeGIRpOOVCChtEFVwg7UFgxiTI6cY_TG4SSSUkgSm40UNYnLBFCUgckyoDQAff2wMwU4mmJIQA3B0g60mOrPRR5aotYaQlAJSKvkoiMKirRVOAoKKFFFK4RgHIkWEEFMSQkmQ11MUBk4EIt4JRwFWhMwkIjqzSiEkBk2J2RgLIAAkKKgV-1hOFxK8MKbIpCCzmplSjHqaRRfJmhSiUlkIAYCH3aE7NPPTU2N1f9iAJEQAH_2hpwjGoDbU3N0B89C26zcfogSN2O4PMcT9zpExXd875yTxqzfXLvqf_Pyz-9XOaD0IN5378PbdZrN5--ZD17bT5Wx5eppX5X53SIGr-fzsk-dxCLYqlaL20MbgBSn6aPIMSR0PtMdjlCQ-6ueOS0488mW1SSmSJNQEAiBJ5RmKkFIxRpEERBKc0jpFICJjMwCJw3AMtIEwCmnUTJi64UeEkmNE0FaToiQsIaFWaeh1lhMisOjcMkdOMSsrCQGRmOXo8oMYlTacOMUAWgOyLusjOBgQBKJ4d5xLEJFQobYJicSTJmCQlKzNjDFuu4p9F3wQCdOTE0hOgJFZoSalFCYWViB5PfKtG41GKQyuG1KS6w93q_vh-s0dCYSua7dN13Sb9SH2bj8MUcvt6qAI901fZ9n1evPbb693hxYIN7vellnb9M51oR-Cj4DQ7_s-xtV2N6tGKSadmbvdznWxa13XuRQSspxeTpv1zkfPCijAruViUSvgP3z96ofrncosaTCoElIIYei90Sowj-vqJ8-XjUuI2uQ2hNj70DVdbmjo_FffvX-8mL55t6kzhUB-CHlZjKrsyfnppKokyQ836zzLP2x213fb91f3yYWrq9V-1yjQv351VeRWkVcaI6OyhRuCpMQ-JJDDYffy9dXeRTL0H3_zcmELYOmG8P7tFSkc1-VkpE4fnW7vd0PXbDa79WFX1tlutyvy0kVfTytN6v7q3uRkjVJGnZydGJCPP3leaGuszq0lkNAPzaGd1LUovNtsrq83XdtvNmtS6up2ZYqiWk6GrqU82227rCh67zhSCLjf7N3dMJ5neaHreqQUAUNWoNJKQb673xlClev20BhrUkrjxbLvDxyTO7RsM5tnRlmd5yF6FOz6hgSRqCwL1_fa2pQg-vDzT17cfrh6cL7kGAHk5z_7Mg5tacyvfv6TIiNj1KTKYx82201m8947rdWPSU8WFq7q8tD2SKh0_n61uV43Mfkiy5quX632PsYsz0Ibv391bTKtLG22u7Z1o3GhbXZ9v7tc1kMIYmwf_P39bjYbHyWds3Gdj_Oiqt5-_2axXJZV4YYhKi7qMnDKFWFGh_1hfrpgoWdPLuuq6prO2Dy5oZrUAZMyalzP3dDaMvchlHVdTKcxeZNnZO3po7NslKPG7pBQQ1EYDeqwbWyRnT84FUiTsiCC5cmsLNRhux_V1eXDuTBePHjYtAcvghrdEFLjE_t8VN69XS0upv_dr34ehy4rM8ro4ZOHszo7Xc7qeVko-vQXT__hf_sqy7KyKPa7A4nWRo8X85AkstR1cXI6U0Notm13cO5uX2RGhnQxmsR-SJ1YrT7_1bOu96PRLKWYiFMUNS_Kk2XvmRQBYaJYji1ADMPR2yO71YDMhclSgLzMbVWt1u3pxQJFdYNLQnGQ3W7XbvuX373H5GeZ_cUXz-pxVY4yW6jZuDRZqqp8NKp8YpuVythiXG2a4f3t5pu3dz6lyWTS9l0f0-39ZjIup2X54qOzghQwjDKFLhbWjovcDU5rQBBC5sSZ1VVuXd9xgsiRQxiVpVWKQe53h9vVbr05jOoyN2YyGd-uNqv1-uzyZJQXBiG4WOU5skyKjIz59of3f_v1t9smrLb7EHi3OXz-0dMvn85v7purd_eCMDh_v232u3a333vnQvBd16_atsgUR7i_3z19ckaKfDekkA6tH5cZJGbBurQhiraqOQwuyaSsy8Jabfe7ZjGrC62BNAJqTRyxKMzZaYVC02lVjav9piNr2s73kYlU27XKmGJUaaWTD5eXp3VdGKPGdTWdz1USTmwy5b1SaAehWT1OKU5HY6Xp0eWcfWCAssjLOpcYh2bIy8L3Q2ay6H2ZV865qiyJqG3aSVkduu7h-SK2brPpnzycPnp05p0DgPXtWlszDF3b9M3h0B7aUVl6F8bjGiRlRl9enC5OZhpkVJf1dBpTmEzHmdHH9SsqtTw5AZBD26ms1JUdep9ibIb-zbtt23YA6dnF5eBlPssoH2HCz764NNp89_ZqMamny8mh8duuKafVd9-_btsucfju1auvvvrh5mZ12B9--P6Da1yuDTEMh_7y4fmf_Pkf395tVleb2XJUFPlnv_gYxva7l2__8MPV7__6t9vVtWu7oXcSJM9tVZd5UQKbR88uprPycOj7PpxdnK03-7OHs9E45z4qNV6qzEhMwnJkYwowIACDJEFSIgJaAQsZhSJCKJEJAEFSjHysChgrjKgUCiutkg947FymZLLs-D0cIhIe14ryY8QIiFASa20AUFhA4o-XDCZXxsaYkIhD4MQcgyoKrQwwEMrRTMyJOSZg0ToTjoBEWSY-kNIiAiJK6-MwofM8dT0AozJMJMHBMY0DgseIESKIEAgAAZKyBXOEJDrLEJiIJMXkAilESQSCwmHwpJVSVpgBSJKQVkgkElH42KY-JmOQSCQxM8qRa6PI2hSiHA0JyECECJSZFFLoW9JGAEgb8Z5IAxEd0e9xkOTdfm9yQwimylPfpKGLzmtFLAxaK23iMCAIAoqAAkZOhEoksvcsESNLYlTIKWmtUYAI2CV1lCfHhCDKZBwDmTwIlNOlEHEKwKyVlsCkgIAEAJTgsThOGFnEJ22tJBBEpQghYWaiD8CMCME5lVtbFIzMzmttkSX5qPKc_aCzPEWHhBBRYrB1RcfYvSSdWeHjUS4cWUy2LtkFrY0yGQJEn1CAtBaB4_RIWUZaK8LknEKTokBiDlFplVJS2iROkhIpBEYA4iialMqNAFJWsaDNy3oyUiDI0fthsjxLAuxDNZu22yYf1Sk4SS51gyAIRIMoKZTlSJQ2NkvBF2XuXAuifIzbdn-8rUbMbq6u31_dumFQBEaZyWTy-NlHH330MQBbk7X73gU4PTsfX57evvngfShnE1sV-WgEhFlZJBd0XpIiENbagEERQWOExeYFxwjHEVprDgmZRURitHnG3rP3QoDWACAnRhGlM4lOmyyGgIhoMjKWrEk-aJsBQXADEGqTHV9EpSgmRgJUGkRQYTxsVZZDiArVkRFF2kbvgAGVIlviEaHFrJQRSUQEKMApJicsJsuVNcIsISFErTF1HQgLiso1KZOGSApBgI48WAFCBFI2y5hJ5ePQN8zY7ffeO4UpqytSOvhEaPIq6w8NKS0EfdsSJaM8YGTCclJ0bdPu-6xUbdsOg9_e74Tjft8lkk3fdU2HnPpuaIbhMMS3b291AYQ6dMEQuO2WctP1LQkPTZtAeu-zPI--d13HAkgqJjcMHLw45-_uWuFY5urt93dDP1hNWkSPy6vd8K4Z3t9t79qmSxENOEmvN-v12hVZ3g_xZDGbVNV8XE7rclxkuaI__vzptCwmdfng4dmsyplT33Yno2Jw7te___Z_-f3rh-MaSOdlvVpt-12fES7mk598-izEcJLnm0P3l__ww4f7ph6Nt03z7evb33539eZq9fpq_f2rKxTd96Go89NJKSllpe2Gbr_tLh-ebDeH8XiklXr3_q7ZbJhkOPRd77LCKlTvftgUWiPIYjqbzSazB9MiK5r1_vMvX-QAwDKpSxRZ32-6wb3dfCiyKsvyIbLvumKSeR-VAqXN3f2WnRv6VOSqGBW763UaXJFTe9jNz6rJsjqsDqhxt9lrmyVApci1ThLntQkuKKNMbrXJtdJh6FNIJjOqzIBBACGBDz0IDW03Xs69GyAmiawzW1ZlGByB_uijF4tZdb5clplRAorDxcnidDaeVlme6yzTVWZc72aLqeu80ooBJLGLYd8MB9dJgkPXPbm82B12jx4uZYg__eSRhIgJy3E-ndQhxiSgiKbTcT_02pjpZIxJ9vvWWr3fd8VodHu_-v1vvis0vb-6Pbk82e3byWxSjSYSwuX5Sdd09bi6v9sYq-qq1oBa20KbYlTNltOhGYBwVJfNvp3OJpnVfdM9_-Spa7vQ9UbjxdlSkWFJEhit_eJPP0susecweEjw_GdPqtJcXp4fDp0xpi5zP7gsy5OPZZ0durYqcgRILhirJuPJ979_-dNfPnv28Lzb9y8-f1IaOxpP_vwvfqoC-kPouu5iWj999tgg_v7XP2x23Z__0Yvvf_fudFZ-dLZ4fdX-6R89_eN_-eliVC-m1XQ-aXabi9PZv_73P203rWWe5RlpfPHpRTmuFtPqbDpxIf3Jlx89en7GEZp9o7Vudoe8yhFAKRV8KhdVtbRKVFFniKqa1EiSWYNIVZkvL6b1vCyrWiCVo-L00WI0zjeb3mqYjGxVmDyn-fmUQ8iNLiv7_uXt3c5Zptm01Kink3rfxYcny_E4y1BPJ1lhyG1X54u6IFhMi8V0tDwZWWWqWTUZT09Go0wZP8QM1XJeV0U-roq6znOjU4oKeD4qZ6PKKEJA792oLsuyiMNwuphORyOFuO09kM7HpQKkJJnVHIMQLqaz3NiJNdv9wbsAiEaRUebD_f1__tvfTE_PVpvDdLkQoW3bmLL85vXdqw-3VZmNR5PdrlGacmNOZ_M8t7lWdW6_-PjBbDTikB6fn334cKeAb5q-zM2Ds6VRtLxcWKWzwlqrx5OirouL5QiF2Yd-cFlhmrZrw0BA03EFgtNZYTM7-Dh48CxKy_J0MQwhpLg8m2oNh30fUmi6vi6Lqi59DJAAGc6ni9xoCcPDs1k9yZbTsihoPiq_-OjR6elsMsrPTka995SEE5jcSIgGpMhzCFFnJjNYFhWK5IY4pqYZnj681JZm47Lv2v1hnxU0GU9ef7gri0JrSgJuGCBCZozRtJzNU5S6LqaTivt4cr6cTMar281yUtejvM5yY6z3Qxi63Oj9oX386Lw5NN6FclQfmja6fjQuOElVlVWpJ5Pi4PTjB4vxbFTlFSLWZdZu2rYdyBCA3K93682GmG8-3K_v274fQhsPuy63FkDcEC-fnn3y5ad5aQmpGBdPf_H8f_9f_4lS-_Tjy-vr7c_-7Ze__puvvv6n7958_X3cbVEcuAiUZaZ2Dj_94sV4uijH45PTs3dvrq7e3P3ZX_zRzYe1UZTV-dMXH7errU1JQbXklI5qVUA4BnJEjlxxAkkAgPDjLAtwxD4qOjZZiVRuUoyxd9loDILBD5JYaX2kW6Ki6IKyVkRIKY4swkqbIyVfYoQjlj8xECljAI5N4pSiJ2UBIQZvjEaFeIQTKURCYBESpQ0IAyYRQQQBSIlJaRE-2gNIEycG0KA1xIAgx5w9ZbmkBByRBREAFBDRsTT8YzAIObJEZ-oyDV6AOQRI6UgYkpSAE5DC46iLxALCrK0FpX5UGSAhImoDgHykGLEcAxXAAoQgYMsixSicEAQ0xSGB0kcTK3ASZYVBF5nObHROOCXnjTWh2aICQPGNM1XByaehVQoIBABIawBM3hNxGjygiARJTDYjbUQYOCmrJEWJAREhgTqi0EGBMAAC0LGBwcygibQOvsuK2rddkoigEQEVCYsIRJ_AGEkSg1faiCJBIVJ05G8CApKyViJra9PQS-ToI2nDg2dOBEDacHTH5xW1YRQkkRhSlKyaKILQO-EkgFrbI-FHguMUBUgASFtFVlnNCAiiswxAog9ytFhzOgqzVGY1icmy6L0mpa1VWofgBRInUQqyMuOQQmRjLQrqvFRaNdsdCSiN_rD3Lqqq6l2fopjSKGOGQysoypIIA4I2mkC6w54opUHcofEuCPNuu58txjdXq67pJ9MREYUY3727L4rscGjPT87ud5tXL99vNmud6fm4_s0_fjVst_vV_ubDhzzX3X7HzqEcT1nKO2erfNg3hIhKggs6y8io6BhIRZeOLnRO8KPSFwCJjix_Io2EHFNKCU2mSYMAgnDilMIxhaUMipAkNkXhvEvBq6JEYTgaAZSCY8OdSGliEY2KikpCRMTgvQAiKtI2xaCVZgTmqLIMAIEFCJiPJzlU1pAclX2YQjJZrrOCo09DAASEyM6zIKFktgw-EBwRRp4lERxzhpHdYPLM-35oGw4J2Slk5pSUBQmuc4oRUWXlyCfnhqgIhv2AAJL8brPrD001GUGU7nBQCF1zGAbfDY4VNbtD34fp6VzZbL_d6cyEoe-2Q9-2NtPR9dradteqpFJwKCgsPnLf9wjWu2Fw7nBobGaFBUFsZQK7D-_ea8FRqdvet73vfGrSabu_AYG8ztv7ze---3A3-G3jyYlV1uhMmN58eF8UheuH7WF_Mh1PRpNRrjJD57NJkYMlXWf64nT-8Oy8LoqPHz34iz_59JOHFz__7Mkvnp1PMvuTTx5fnCxVlrF3fXDNMNjCLOaFAb3a7F6_uVPMSdJsNt5v99qo3GBKQNre3m0ePD5rep-Refri0ma2HlXbbZNCPHQDg5yenhijTJ45hqIwz56dE3LvXDEqQ-_urrt_9xe_eLI8kcFneWlBvr--vr1eFXludWHYKKUP28ZHH1MMQ5qOx-vbA6Fq1j0iWKPdwSmDwcXkXQr9Zrf1PVfzGWn0Pk0fzXc3-2Jehpj6fvC-8y7ks8oNnpMM7VDURVGW2mYm0_m4TpHzZd1vDkcgACEpjcbmxbga2i4FMUYziaR4OHSffvT0fF7d3t89OFtenp8sJuW4yjNtXD9oImS2VockSLRp2q7rm30DpPOivLrf5CZrXYoquINrmuBD3O_bN1drtMpmWeh9VhQmJ1K4bw5VZhSZoRsOh1ZleZbp3a7vvISme_z4LK-Ku1U_HpvB8_lyFkVyS1YpAT6_nCLq2WQWU4wcDk17vdk8Oj9_dHkpArnW3nvQUJbF6uZ-XI136_XDBxecwqPHz9a7vbZZm8J8VBdVDh6zzJajPNcmDP3JyWlGOSlQSsXoSYnNsmpUP336-G6zPT07KQp7tlgQ6bZz9Tj74iePm7u9Shi0fnZ2apHvWr-7uv_s44dVpqymi-UCIJU2O1uMPnt8dn29ntc2q6rV7e1PP788X87268P26u7TBw-ssZWV3Wr3-7_7frM9nF7M9vtmu9-v1zsRiCgHNwjBukvbm21ZZ9NROcrLapSdTUcp0KPPPrm4vNi8vJ8Wpt-AjqpvYuojEbLgkLiocqWl6RxzKjNd5Nn-rpuMyp9-folW5ePCiUyLqVFUVqVC0kqNirqo8qdPH0jk5XI-H49Pq-LBrJ5W-XwyciG1zt013abv3h2CUeZkOkkhLRdTneQnn17kzF8-O1dIZ6fjOjfB-cwqrVCLlKUZ1UWu9WazqquysLauCq2UAj6mVqzVXTv8_Tcvg0_L5fLq-m46rUZVJSyojUI1qnIXYj-4PMuNMiISY-qTQD35h3_8TV1Pvv7um_li0Q993w57FxRKEhBSxprOD2fzyWq71Ybq0o7zwpDuOhdiisnn1hRlPp-UmrQm1LmpjRl6F5lTSs2utVqDqBDDcjFxPo7HVVUWzaE_mU-KMkeRFFNurGZYTEYUVWEt-IAIhTVucCnKbDquinxcV0q43zvSOM51WVjvfN-3-Sjvhj4MfBTRhxDvV_eb-93V7Sa6cOhcoXXvhsH5RxeLIYpVlDRFjm_X28vF1GZWAdRlxclNx2Xqw-npPAa5Wx8eXp7tD61SGKK0vRvXRV6WSJJndrPtqtL-8suPOYHEdHKyFInjojg_mcTgFJDzPSdfaDUtCwSZTid9006qcjYdG0sGKXXuYjETRIUwm07O5qPzyeT9u7uUWErFQCbT1bgcnc23m4M2pjm0h02f2azpe6Wy0aiqxyMGVjZ3jXv4aOaG8O1Xr-9Xaz80Nsu-_-3L9rCxefb6h-uY4IffvO73TXCdJHX5-LwoRlU5_tkvf_Lf_4-_0qSEQKx99eqlUvH8fFGPykdPTosiz0pzerp88_tvZfBFYZWenf9YojUKQkKilBJpgwo4JkBQSIB8xIOCUojEMSIqRAAkYVBZdtSIqKxABIAkSZTWgCjH8csYRGIRQmROKAyEgAqVFo4oggiktSRGZTklNApFAFFpK0Bx8JRbDkeGI2ltkTn0AwvYskbB6AcEIWMEQGmFREAELCml49dKG06Bo1daAwAqDQB01CchpcSAClAhckoRGEgREAEo0Agpkaa0P6DWSCgpybEL8WM74ig2IJAEx1qCSPJOKQ3MQnAcelAp1D9WHYSZFCmbSYh2XPMwgAgIK2VtWSKn5Jm0QpNnZaFMlqLHGEXA5hlZFfs-BS8cMEUOLnovfa_0j6xSyg1w1FkRmnudlUQkwUtKLEnnFpmJIPQDgCKtUABSJBT50ceAQnjshopwDAGVBZboXTYq87wMSYCDxITMKbDODGn1I8sVyJS1UsQppZBEorY29oEUsPcCICkok3GMEqPK7NEOKykRCgKSNYoQQNJhJ8ooImbh6ISjNjalhCx0bKEza5sDKiFKfQB1JCRZ4CQMMQRBPEbWTGYISJhjTEr9aLdSJBxi4mSrQimVEisUEI7Om6IAZL9vEydQevzguQxNdE5i7A8tAoxPTlBRu9-kvuNEWiOB9E3HwbOPYXBZYd3tRiSRUsk5v2s14n7bZ6VVCorcEuL11Z1zPoawX903h_7bN68AMMszRBiNJ23vHj97fvb0IZN-_tOPU_KuD5CibztIKXStUto3AwEqo4-VGATM8joJE6LKDSZOwdNRHXCMAxEhAHDkFI5fEyKnKP_sdFNZcVR0G2vD0EtMpqpZkilrFkjeIZBSpLIsuh4YhECRioPLyiJFBjiqjUBAFJCIMIMyBpU-uveEOaWkbE7aHIlbkhKKcEqktMRgsjIMvXAkk-H_n6n_-rFs2_L0sDHGNMuvbcNHmpPH3HPuuaZsF5tt2UI3RUIgIUCP-gMFPckQECAQTYkA2SS7qrrcrTrmHpsu_HbLTTeGHnYWoKd8yAQiMvbeseYc4_f7PqsZmEym4MitTahRac0JUxiBmROjVtE7VFZnNnGs2zNltULkEKJz7jD4YQ8itrCZzjilcb_d73cKEBjiOLixiyEk5yDFcX8glYZusFVOWRbdQJL6zXbquuhct930-z1z2j5tJQIosUXhpyHG1G93gOgOBwCEgupFtrvfI-D2aQsxuMmNvQ9-6vpDO6-N0nWZzxfluO-J1Oim3cMWWZZ6vt3e9ftOgyrzeaV01ydInFmLWvV-CjHWRf203SjQg5_ePWz-P19_dbvfdKNsu7GbotHUtrUSOPiRgPIq00hKMEX57s37p31_F_pvX7__9qe3b2_vhQ0naJr69ZuHp8cdmezl83W1zAX47t1TnmfayH7TvfjkYr_bF3nugx8O4XTVWmu2246MEea2rSGl5Wox9GNelllRJi_r5XxWVcOhX5-eZEan5H_98XWjc46cIg_JHbbdaj6v2iamOLrJjb6srbE2eJ8-lNGlXdRG64_-9FNLsDpZoQZFyja5n7z3osnkeQZJ_OijjzAFY40lUkoTKqN1VVcoSpHOyqIoyuWzxf37rTFK57m2OYRUFEWMMflUzWtIwhGUUoBks6wsLCms2_bZs-fn56v_9n__L0-r8vp0cXVxqpAlxtVixik4PxIio0w-uRCnEELkoi5Mlo0pGWNDisHF5bJmz8ZqEkRLmszToS9yq4hiSkap-_uuzLPDwRVF3vvp729ePw5eJxyGkUGeXa0n72xebHf9J7-4gsCTC6-uL9_fPmgiY0z0AUHZMhuGPsS4mC8UqeViBohBGET6afz--zcn52tMablalJk9WZ7sxmG1Xrro18tFXmbrRTNftGVdVk11erZ-_uzy4uxsdrK0hT4cDk-b7fnZghW4KT27OheWu5vb33z5y_ubm3FzSBxOT5cnJ8uqLmudO07nZ-uL5WLn9n_0qy-ezc3L69OyKX7x0eXpyRoI67Zet7UpirrObWZmy3bfdw9uWtSL0ce___r7k5PT1ze3PgGzXF-cXFycPH_17OcfXjsXdmO8Pp8fYprNq0j0_MW1hFhaevbp1fZ-zwnqRX3z-jYAb27vxq4vG3u6Xn_55fWnn11fPJudntTrk3nRZs8uzwtjiqK02mTWXl2fa1b9KBcni4tV632IAWprZmX1-LTRAK-eX1xfn129PPv8o_Vilq9ndVbZ5INFUgK99_s-KKVm8_lJU3z26vxyVi3mRVFkxLBa1ezDNIQ8M55Za5UbBQm0kpPF0rvx7GRdZtootFqfzGd5nlmjgnfj6IPznlNuMxD4h-9_zPMctdpstkVhTxZzFEAy2_0-LzUnSUkG5422iXl76PoY_u6H1zePWy8xz4vHmwcn0u8GUWqKYRr9NLkEEDlYpbtxUladr1fzuh4mv-37piqTCGmyeQ4Ad4_bpslOVs14cEM3ClJTVQaVd_583Y6dA-axH6u8aOvGTaEw2hoTXMysnq9KZZTViInbstDEMTBqHEcHKEMID4_7iNSPY9-PplJTDFOAbNYgcPD-5m57tlrMmnxWFeWqBVIuSVvX9az2IRLDej2rynI_ujzXbVmY3JZ59vGzi7apg49aw2ox2x12zy7Pp0NX1uV2t0PEk_WcQEIUpaiuyqbIdtseibXVsyav62JeN1E4hXR2tqzr3GiqijyxIFBESCEN3hdFTtpqnY3jUNR1YmbmYQxPT9tyVt3ebfrRZ7lNCX96twdCm6umLpz3u6ddplRgPmwnZdEWGUc8O1vYPKtOGgRtrO4PnS2zuirKIlss281mOL1e1FrvtpOP2O233qcsz4wpPvnDV59--mz0-Ivffnx6cfHpF5-CQkIa_DCF-OPrn5Smh9t7YNfUzc8_v33x8bOqXqzWl-9u3zHrqT903UETKrO4ZO-FEBFNVSc3HWPueJweauSYjs_4oxX2Q69Q-DjjJ9IpJWYmQLR5TBEJUxJEBCIE0Ea73mmtUWuOSRkNIiDywVkkgCTH2h9pLQASE3CCRADMkLTJyBhOkZRWWsUQE7MyxhRFCEFSUrk9VhLx2DGICREQlWAClg81Ba04RhGhYyInRlOUwXtEoGP8HYAUSGJJoKyRGIiQlCFtMLF4T4AKAJUWZoJ0VNMCqmPPmAFQgGIiZRILsijCxMwMoBCARIDyAlKSoxfZ6uCcsll0o7ioMqOU4SS2KIQTktJZJgx53bquTyF-KF2ChHFSRrEkTh4kKa1QE2ICjkfAqMRjsDvpah7GCBx1ZjlGAECfkDQoLZFBAHwkOtY4EwCQ0YKYmI_fgFJG6YxAbFa4YXL7p6yss7Idu72w10orayR4IiUKjqHtI-BRa22KPExOW0sahZlAAJFHBmBSCpiRkzJGkQZC9s4YLYkZBInIFsfeuVKIKRLqECNpozXFcTxmuqKPyhhQGolSHI_ZMxFGogSSpp02OR7frMYgqRgCQASG6KNGJczR--C8tiav6jC5o7EtTJO2hckK3_WMMm3uq5NTibFeroZDx9PkDjtl8tX5ZUppGgfvnC0rygxI0sYmH46tcQ4xMZq8RWQfHQltNwcizOoyRQ7O53VWFOXoRk2y222S491mf_HR9d3NvQvT2XJWVVWW2932ME5pHDpMUVKcuh2yKNKLF-fAIIgmNylEARKJiKTImHoepoEUMUeTZ5wSiCibIWkkTJGP6g1C5JRQiI7VGwJbVsLJj6NSChH8fmeKRiQpZRBIGe29hxTJZogsiRlYGRPHEQWYj_s3BD4KQxIBAwqnaGwBkjgEZSyApJSU0olBa6PomHsTAcDglMk-fHsCAhKGDlEzM6SolLZ5hkQohIgheEjpyAgDQGAe-329XCJq51xW5ZISSkIf4-jGaSSAvK5JE3NCTkVRKEUpcV4WKMwcko-JUxi6OI0xisQmL65V3Cc3-HGautEPjhQNXT8eBkhh3HdTPwhLmqbMZs65MPA0jJJSnHymCCEooxSSRIdM0zAUdVmVpbXVUz-RUhAVEmZFxjxhFic3uclnBSpDf_TlvAvBDcHkGSfxKWiFq0WznNWfvrp6cbn-g5eXvzhbr9t6XlU2sybPvfejmwhIEUyBE8DffvvmL__-u91-LJrCQLbrDrM2P1utLi-Xf_LLazKm245ffvHsT3_9_Pc_3tw-OlDKZqgNbQ4OFdVFsd107axYtdWnn101M9sdRu_C1E98_JyCZHnWztu6KjHGZZOvV7O7t7fzxZy9L6u8sOby7CQ36m6zc5P79vufs7yIzo9jYE4IXJUFi7x785hXul7UVV1-8_X709PF_HzZ3x2MtoMLypj-bpfrPHKcr5dXn336w-9-YI5tWwfvAFApmvqAIFYpa8zJs8th8qQ1iORZNQ3-o19_srt_nDoXR0cCfnJp8s1iNu3Hj377q7at3DCVTaUUVU1DSvXdYTavP_707MW8abJs1taG0Gpd1YV3Ewj6FDlx102Rky3yfpxciP0wJoHJeTd5F5Ob3DR4732ZV5F5cNPeTy8vz_I8SyG2TS3MgflkmQ-jTxF2B7du21WZ2Uyvz-cPj_3U97osDoeuqrN-N3X9kBW5NmZykyas80xb8_Cw8VMo8iIri5vbu-VyLsBZVpRFziEJ4WLZFHnRzqv393eROWJyzpV5JgTbzZZy5Z13KWlryOrD2D9ud8ropqpAqVlbXV9eWEWr-fzFs6uTs2VdlMji4_DqkxcvXn1UVXVV2MzQctGenc6uL09nrX5xUr18eakVP0zT1XrRNOXTOHIYf3h32w_dYz--ul5snN8NTikxRMuyXp_OCfT8agGAVV0UKp1fn89XzR__8kVV2U_P1v_kTz751fPzf_abF__2z3512c7_2S-e_Ztfftz7xMOonC8L8_b2cNj267OZMiQEqLWtalbm3U233x76MfTDGAIMTkqdFVpdn67-4JcvXpyfrOtqVuh_9cef5FZ--unO-7hqKyU8L4uTRXXaliermUIslbqcVbu9M6z7rl-1tSGwJv_9ze7qpM2t9Yd-mtK6yiHyqq6KTNe57fddW5SK2ZAyRBIDIFe5pRgB-XS9JAFJvqnK3GaZ1iFMhPjwsHcgQTjL81XbTsE_9ONy0W423WxezKtaKWUz8_7u0Rh9GONqWTKaw2EchoG0Kpqqd-PTMP7ww-uibqYpzJfz0-fn_XbaHKamrb0bt9s9p9SP42LWdL2zSv_6i48fHrc__PTOaIWE86qqyyy6oKwus6wwxf12OF_Nuhg0wmN_aMrSKMyKrK6L0U1G6Sw3RVFkWiuC9bxNCUSiAjqfrzRAqawkAQRVZm_e3Y0-3t5tBh9Naffb3cNuXxRZcNzWFacAY5yGgZl9iofd1AU3JRg3U0ZU5XldlARyMqsJgUMyhl69Wi_ykkVKY5qyWNh8u-_KzNZZJik1ZT7F4EIah3G368_Pz_a7_eXJqqnnFMNHF-vS6MWqOV027OR0OTPWnK2XZaZnbQ0CCiQlqesSQcigJoUAmdVVliWO4zQRkbU2-ChC-_3h9Py0H_pZMxuH_vT6dL_rmspaY0Dpu7unpqxVUkSSmXxzv2vbCkA48sVqHUX6Pq7nteWImJq8erp_RMHZvDl0_WF3SBw-_8WLLz598eLl1S__4IvVvPr4y1dns_ru7X05y3STvfnhXZ6r33_1fVnRfj_evnlMMb19fSOATdt2_fDxRy_Pzi-Grh8Oe0KzfXro-6muK1NkisuVJP7QY0oRgVAYEUmrDxpd-JAHSiyISB8qtyKcIDGgKGUYQFAIsVqejLutLTKlNId4BNLYzLAwkiYkIOQQPkBCQeiYFBIRFjlOoU0GLKSAYwARnedKqRQZtUnBHZP9LAzKIIBC0FnGAsgJERURSBJEldeABCkpIkiMWiFqjkFSAkQQERCb5ewjM8AxLA-AWouIpHDsKiQXRBKEiMJIyDGQUoAAkSUlRAQUUAqElCFiBmBBAlIox2IxHvsMHKLO8qMeWB0xO0qR0giC6TiWJkYCYeAUY1BkqvnSjyMqsnmuUTWLFYsHRZJSTCFxgph4mozVHBwhAojEqKyRFIUxxgiZ0doCC6YEAgSEWqUQjthHBAFhhQSIgoJAKJIkAQNllQBxSBAmEaFMF02rAMZhVMZmTQtIwY0cE0Y5Sp1JawnpgyUAUCShMWGYRBiB4hSI0BjDMWEKqJQmAlTHAjcwICECA0MKUWuDAtF74EiAIsAxEn0AC4GACB9r5SyijCFSkBhTjDEkQFU0ytYkiVjCOKLWylqdZQAQE2tEUorZI0JRlcF5RK2yjBNIisgppZSVjS1zPwxAMPVje3b59Lhbn5-GMDFHo6jfTxcvX1VNPbhJmIp27npnjW2__Iy326rJvZuYI8HQtLMwHoiS-E5C2tw_ZZXN8ur27kFrA1pbq88unzenzcuL9Xdf_bR7evz5u3d5Xd483L949nJ-Ok8h7h43GhNPIS-yernq9j0xcUQfks0rAALSkthaC8zsg9DxrouApBCZRRATMBKhNkDHoo6A8PEarwhTjMCBjGWAo1dYWRPHURKjUkhKCK3NU2IQUVkJH6C8goj8gTQKICCk2HuyVkJSmsQ7IEbSIpgCM0ST5yDHLy7aGLI2uaiOry4HRSQCoBUCqbwRFG2tIsWJ3aFHZLJH22SWIoMkhKRzTYgSY_S-rFpdZP1hAGZTZNF5SQGSVwqAI08TcNKAY7fPZ3NhBvZFVaq6ghSN0qEfYZwgRQn7NLzzw2AXC1Q5KBYJJEJIJtcpTtF74VTkBZDqdr0WEPAaUCQpRB4caavRsI-kjK0LazI_uejjfr8tmnL_1NVNuV7P-m7q9gdEHDrnxhETfvf-_m9-3sKkIqfbd5vt1O92-__hu2_v3m_3o6u1fvswRNYuCqLej56Bh2H66vtbIv32afz_fvX6lx9f-oB3j7tFU5tMfffzm3pWGlPcPe2_-OJj5BSdPOx7pVTyvO3H2914cTqDkIYxrFbzj68vPv_oMnj3_PpCOJ2fLQ5P09dfv8mtJkUI2BTlZne4fnapCSmm3d1jTnlR2Ezh2eX6sDsA8PQ0_OZXH1-t524a3989iXBZZlrrzrkQInM6XS1A0sX1EhXNmgojj_10dbmqyyq6NI6HIiuaonJ-QsKiLBJhXTfT43Z5kp-cLPv9oaqbpm5Pz9caoamrzBoRCF76bjr75HJ67LMsM9pq0JnJFGFTlUVZKG3LvJy1dV5k7tARoqSoCWeztiprS3iyaOdt_uxk8dtPPykzo4zSBMrqsR9JkY_psO-zMlM6M5nt3dT1k1ZWiJxzhNoH711oZ6XJdJbbGDwj7PvpfLk4yrnX89pqjQr2-w4RximNbtJFPvQTCLOIHx0A53WeG-ND-va729W8Wp-eKFKIcnV-JoBGkXfOT35KabfbaqPrutZKP9w_5Hl-6AciQEXjOKXJGVttnrZZlj3e3w774ebxsSzmd0-Pvnei0FptdOEiz9s5Grh7d1tkeUpxdH6axqLIszKLnMZuDMG38yrPDJIGZoPq5vZu3x-M0Y-H8f7uaUq-Ws4B5Ye3O-_jzTAgZ7__4e2hi4P3Ji_vt9uf7zfb3fjN16-3m-737--2Y5fnpa7Uw333t1__vpu8IvM___Xvvv7p_uvvb05WS9ZKIqxmsx_fPzRVvWiaPLM_vr8NE1-drazSmS5__Yev_tk__RWBOkRSNiuK4uKTKzm4GsKiseuT-XxZkdDL85MXL9Zn61We6cSw6_oksO_7bT8hkCnp-uQMCZbr5enZOoU4eD_4kFnLBmZVVVeZ0SIxEWEIqSnz69NlchMyZAoWdZEZnuWlj7FUViuVZVRYk7zPtPFuWs7asspnbV0YXWVZU-XRudwYjWC1Til2h8NmmOazpshMVZaWVODgQtjv-7LNT1bLbn9oy0oQpn4cY2jK-ub-6f3tU_Dp_f3ji6sLbfTow7e__zEROoTXr998-unHwGE4uG3fDdMYUlSk86JYn5x2h0NRVcG5Zdve3W_fv7t9-dG11saNU-_GdzePMbEQFcYQYX_YZUVWl7kyqq6qFHxhsxSDJMjK3GitATWR81NmTQp8lEk778I4HR3wD7v9wfm7p23TNIzczEtr7cP9VgNmJpvGiWN6fbfJyZjMPL86YwFCqvIsxEBJEgAbfZhCjCGOISHMqlJnGkMKk0Olm7zQ2pSkf7i9X7dNROkm9_7dNnifaXVxtmrLOiFn2jRNKQzJOVJqOsY0SBW5mXwEAWtsZq1SRmkFMXXdmBW5d0HrY6SbhnGos3zX9W1VF1VJpN-8f0-G9rttXhWjd5r0br-7ulh1uy70Y5YVT_vBKl00hQS-uroQ5MzqdpYV1pCmxbzRRgmG-8fu46vV6bo5u1yJ4KKtTtar_fbp9PxkVlfrk7Wx5mS92HTDn__5X33_07uU-D_--d-9e3fnfPz5m9eztv7x6x_9NA59P3RjntuhG6s6P7-62m73NqsXZ4uLs7VW9Hh73_W7ixeXIQgBlmWp8rPnwqA0cUyoEFAAgZCSjzrLOCU59lkVIekPvA4B-cfTLQBySirLRCCOo8kzVMbHIEmKes4xCKcPp30gQDwyN5N3KEfxlgb-ABP8AO48BkoUaYUcJQWHSpM2_KEMCizpiK43RjNDSqKLMg4DIkhkUiScQAC1FgCERIScWBU5x4AERy1xigmVPpadFRGAcJKjRQABhAGVEUyQEjIf7xxAxCGqLIuTU0YDCxyHkEhIxCEdywlo7BG9edTiAhx7z8fsKBwV38ViZo1xfaeOaebIAKBslqaRtFFZ7ibPgLYsx8OeSFIcOUrk4MdJKWPyQhOAuDgOiCiRlbVHMjQggiJEwASCSEQcPSoEAQ6OlFKoPwQ2jpt3BBEgRGRO0SMqIgVGK0KWQKSi8yar4tCbLAdOIGJs7cYJiRUJaJKUUhRTNxwG7yYklRjIWIKUYgSlTGYlJkIiZERCQYbEKYkAgkTnJKUjt5QUAidllNKUQgJFCKIzG11EhXRURhASEQqS1kKKg1fGYgqIJAgKNUpKMSprtVVxdKg0KUNKxxQ5RaKjmkI4BlSakyRmshnHqJRoY2OIZXVW1m3_tFEWFMR6vpi67vTly_39PRpg5m6_tUVdV7MQ_PlHLw-bh3Ixz7p-6npUZLQKftQIrhvnz_5weHqb1_P-sCurzHsfgp-vVt3-YI1y3s_ny-7g56vr01U5Ob-8mFVNMw7j4-Pjaj4Lw3h5enn77r2LEUg7N9myFMFnv_qVH6fD4VDN58Lw7NNfPbx9a_NMaSuom_W6aqppnBIDEnBIx7sqICBpDkxaocI4DqQMESFR8EE4qTxTpFKIwqCUAUkSQ_QuRdaZ1aRDipKCzUs8KpdFUgRT5ADCIMwRjSZClRkQVlYnH1lYm1xpBSJxHIAUEgBRCkJAtrDJj8f2PX_o2ABqJQLAgApTSCnFvCokxhSZI5NVilAbTDFEHySyQlII-90elGralSmy8XBIMWmjldGx71JwzDHGlNcVEodpyqsaRPr9QEKmqNwwKVU7F0xhg5vEbwFpOhwShOCnFJLSpIxNCdyYbJZZa_t-CCGJkjwzwbsPwSdlQKKfPCuDBGRIl-XUD21VzdvZ77_6fprGosws2lwX5ydnpqDtdmIj226YzUurjZkkyy1Zdb1uX16vcjDGY5UZQ_rmcV8X9dev3zmfVE6UUT_FwUVGeTr4aRx_ebFYnrY3t0__8PVPpqB-f7i7fzx4v543V6cnY9fVddX3489vb3YPu36YLtbLy4sVCy-y_HK9vFy258t5mxVeEFmE5eJicfewbRvbzBslMExTblRRZRKChNBkdj1vy8oe9lsAxJg-enb-6urs1188Wy-ax8fDD69vl8uKtKmbshun-bytcnt2tkKUn97vL9eL68uTpiw5sgZ4-fzZbvfECMH592_ej0O_mteE5D6MvUstPnT-V7_-QillUH3-61-0ddlve43JufDR9XNt9dWzZyenS2PosN2sTheb-8dpcidna-9GAQgx_OKLXxyeHgkhBJdn6vr8-pdffnF-eoIg9SKv68z79F__m__8op3lmQ5uslqLJCDc7Lvd7mBMlhVZbvThMG72fd3UMUQRREUsEkMI3ldlbrTOc0ukp9HPZ1VVWD8GgJRZEwIngd12WM9mkGufmBBHN6WY_vbrH-s8f_-409ZyEp_is8sFKW1t3g1Dlqvjw0QZCpGLPNeZaZsmywpgJlI2s2VT3767H3qXfIQE7clJcFORF5QkuNFFLsuqP_QsnFtz89ONMD_cPnT77v7N3eOb-7osuu0hI7x5ewsK398-bvY9KrVY1E2Rv394aJtms93vn_bWYFu3q5OlJXXYd09PO2uzNzebr759X1S6UTJvCiT37t1m8A61cTFtHjs_sICQIWa5eb_VxoQYv_3m5u3NzXI-e3x4Ol3P_-jLX1TI86ZMKVaKHoew240n7awqmywv3cR3B392fgJx-oc3b66fnZZ5Xmfq_mH364-u_-iLq3_7r3_zz1-enVbFel7kZf64G_NMl6UmRZttP07DMHkXw8n5ChCj98tV0x36p4ddUdlh6lMIpCDLdJmXdZlpIhR5fXP_u-_fbB52J6uWEJpVe7FsGdEaDcDXF8u2zrMiYxFh9j74EIrMKgV1VQ1jf7Zeai1hHOoiK3JLHKxSZW5TDEoREe67Q1kUTV1r0kbrqeu0IgSs6ryZN4dtX-d53bZ9Nyilun6w2u6GfvLh5vHp7HSxXq5CiD_-9GY_DJGwboo__fyzZ6dX739-_We__uUP72-nkB4e95vNvlwsNGI_dufnZzfvb5PAfFYpUnmWnSxbQFFK3z8-KFKLRXuybLv98O7m9vxkfXv3KEw-sBsmo4iAZ1VV5NbHkJHq-oNKMTN6tZ5p0kmEDHKSxbwyVo8u5IVt6zLPLRIgKltkRlMKqWmrk_VCZ9l6Pr8-WRe5yXObQro6nVVNwcEtl_XpvLi4Wp7NzOlJfbasydB63ha5fdrsEYSR88xaRWXT3G122uimqFgkN_p0Pa-KTCMEl3SuQ0zWKK210TSb1cZopWjXjWVVKpC8tJmxKaXRua7r3rx9aCprjCFSVivnXZNXfT8CsNE6iRR5bpQ-DENb1caoVTsnpWaLxigiQEB6eHy6vrrICvXJizMCXMyKTz-93O02lnC5qm2eRxc2fWjr4uSkqqtsXti793e7_bTfdtv9_vx8tVq0ZLSL0Wi83-82D09ff__Tzbu77X63Oj_d7_a77SEv9DCM1mofJcVorZ4mXzblF__0V0PXTWPIbNa27W9-84vn56u60H_3D7-HJLbO-8PEzJ_9-uO8MAqXzwTwiMDXRvnRHyfk_3gwBCCSBMCMqBCYlBIESVEAlNYSIxqtlNZ1HScX_DS7uo7DKMB09GyJEBFLQq1JKRHhIGQNSoIkR_QnouKYhJm0QUWoKLmARKgQEVNKRIq09YeDna85BQUEHwIAgoCoNaLi4EiR-AhH5bDJGCT5CUVSSsByRPUDAGoiRGbWNpcYQICZj-sIJAJJqA2ngEfeEQoe5W8kwoRagTCgEJLgUTILgojAAoIspI0QQkpAQkfSvhz_iWIEYMYkWVXEEMLoAFkik7GAIjEc_16IyJgPZYws82Nv6zxvynHfEWlUqLVBUclPnIJBZA4CgCgEyCEJJ2XsUdyWVWUcvaRERMQCwEQK4HhJQA5BWyOJQeD4s1baRjeRIgTFgCwRBY5fyPuJlFHaACRtsjB5kRjdse2QEI8wyqSVTolRBBUBIjtPIEqZ6AJpQlIISVIUEJ1liJqM4egJhEhxDCJMWh1nxkAoiQFEawMfWgSW5FijYG0y4SQMECcipZCO0jpjsiTRO6_znDkhgM0rlnD8AUTnVWZJBBKLsFJWBEgrW1b-iBJCdv4QwmDzHD33T0-kclWUQ3-4-OiT7tChcFkWVpMxxk2OeewPh_79XZDkxyl6H_rOIKZ-SBymp9eolEsBQPwwzZ9dxmkcD0OMyaosRj8NHQF-9btvzz85B8YYxCc3O1mZQuXWllVZ1OWrL79cfPzy9nHDQV0-ey6YK4DT58_v3j3EmF789g-2T3eKzDR6IB3JZHVz8uqz7d29stpkOSYu20ZSSizHhrcAoBBmVqHiFIWjMiY5zyyCYotcYpIYJQmRQgRji5SC0toUVRLhOAGLyXJAUFr5_YEQgAgYiDD5QKQEIIyTyizHmIJHq40uVGY4huRHYytUxDGJOFVUoAWB2Ec63g1DQG1EhEMqFyuJnoWJiDQpotBPqEBZi6CBmb3nFFgINWpNLnhFKqsa0sr1oy0sJE4pAUeIIfTdscQfh1EgKSWSnOsOISVjKasqhsnYoptEawskwEkByDSGfjzsD0mC1ggCWutm3mSFMUY7501mgEWAldHMCVUWpoHdKEmMAQLZ7w_O-2bWEBkE2O_23TR0aUqizKLSAJkxMUn0CSSF4If9MAZ52o21wrapi8z-_PjgYrjruiG51-_v_-73r7_68d2b20fn3cfPz09W87asSZunx8PToY8CdZEnxI9fXQ9PvamL5aLSJheWzWZ7e3s3a4sXz67uH3YZmrYq16sGkWKMEuIUU1GYLM-REyb0MaxmTUpSV3lhTFOWT5vu1fXp6elagyzbWWZ18NN6MTeKFm19fXmmhZ8et_thqGfVi-cn2_3EAm1bVZldzeoUQ6bU9fnCuylMoRunui7buhqmYdbOH-8e2sViPmvc6I4B0bIofvnlR74fPn5-8cUXH3311e_J0mefXl2fzL78-Oqzz54Dy2cfPbt-dvZf_OmXizr_67_5av_w-PLTZ5BCbotD10OISqm2aU8uzopc_-o3v9rfbf5P_-f_elnn3eO2BHd9svj155_1u8N_83_4l__2j377bDUHSdPgJu9jjH03aW2YQWuNgDe3236asjIfJ5dCAoLDMNRFVRXWTaFuy0PXd_1Q5EU_DEetTmLOTOYjG8LNptschlmbTy5ySKzVdtclYaPN6elaKUVEPoRiVoCIsTYG8cGdniyCj4hqPAxIuNn3PvmYvM0yVLjtDiHG-XrRd71AWs7qp4dHnauzk1OXwtBt3vz0vc3ry-fXu82WUIaxd8Ph4uKErB6HePny8tMvL2arNoRpcB5QIoMiIEJ03o_D6x9vNttD17siL4rMrmZtVuRFrsehu7nfXFye5GVx6Pvz03bzfstD-POv797-fJvn-WxePD72WZ3tR9cdBpYUoozjBJhsrpMk76OxOoQUknv58tVhGG4fnxJDvSgThH_47va0znQGZ784RYK73fQ333z37u7WOd-ncHF25vr4_s19leUZkCFhUX_1Nz96H-u2nLfN-mR-fTL_7JPTi_Pm7eO0GULT2mVTJifj4Pb326vz9bvXd1Pv1suWo1ydrc4vT6bDYRx8dxjvnvYn6_Zi3tS5eTabzRftNLmUOAm8PDv5_dvbytDpycKy7HZ9VeSPj9tM07xpMUHbFKeLeZVbrRSCaEVE3BY5xjirSmO0d_4wDLNZwzEhogCQ1j6mp_0-y4wmTIwP2_3QO9LGasuMLkYfpiSQOITIb97fGqVns9YaxcJEcLqeXZ-fpMjfvnn33bffn12ePWz2__6__1_f7faj9za3h-12u99ttjvvfGZN3TSf_-LTu7uHru_btmyaWgt_8dmr4TD--otnSnC_HZAgz3LvHClSjJySIjy7PFVA-8Pho1efFFqeX56UxpZN5Qd_GB0oLDNzcbrURh-6sajzEPl-s_fMj7tdN0wPd08-JEUqxlhm2b4brcLM6Lq0CEmx_vnmvh_7elFlRcGAv__54b6b-p2fhuCDGMJhHDOrZm253Xbv321YQZLAzMG70Q8EZPICY5piQOC3N9sU_X50zy7PkYERGODucUdaA8DD_YMyen8IRGg09YdpM_qPn52SprKwSqlu31dV4dknFlJ63491kS3r3KW02-yUUUVRTONkNHkXD-OYF9nTrnt-cdF108npAhj7bjSKopM8V3VVzapmtx2vrlfrZWEJd5suL8vJhcuz5fnF2lr18RcfC0EIMnEcU-xC-Puvvl7MF92hY-B62Tw-bvMiq9pitl5IIGECgNXJwmQ5SxSA_cO4exw__eLVy5cvzs_q77_-7u3rx_Oz5eDZWHXYdyYvTk9Xm7vHfjsqffoKgCmmRIIMusiOlA-QD-0-ACIEQgWchCBFQaWPbdej6wuYBUhiyGeNJA4-5HUTY-QQrLUsKTiHWkkCFCGlBRhEhEGAUQRJAQkisghIQlKCaLIsxXg8UqAgCyMkskWc-nK2AGYgzT4oazmlMHptbUoJYlRGgSAC6rwSFjn6nM0HVTsIJGZC4CSISAoFtRy9vEdtLx05PULWArMAwAc_AQKpo_0XmIFQIgsAKhRBYIaj6kyBxKjyimNEjkdfMrMgUYqsrVakUkzAjJqSj0oTKo1IoglBSClQiMomP6msiseUjohGE8fxuExAggRY1aU2mR964IREHIPS6sPuRisANFnlwwiRi_ok-J4AjtHnD9h_QIREpDhGpQhYIAkhylH3KmyKQj6oVikFl5VNDC6FkSMHH2yW2zz3biJkYzIAABRFikiJT8IsHAEwr9sPFVCOusxZIDmviwyP_NbjxBeNMpR81FqhIo4szEprItKaju8KkmRMzgxESikLH1ZSmrQhrdiNBEoSA2BKSWkyRQWAwTmlSFLiEFBpZTNEIE2hH3VmFGqOSSAxJEmSFYUtazeNpBUkOV5g_OgoL2IagxtVXmmE9fqcrNlsH_f7fhz7ssxcD7_40z95ePtTGHulmaIHROJEeR7dSASQKIVICKBgvN9YO9s93Td1c_vm-3ZxESXluWkX9vb1w_Pra1Gp2w8-xe7Q391uBFKM7J3fbrqXH3_yy9_8crk6OXvxLCsKLIuLly-effpZXpYXz68_-eKzq48_mZ-cXb_6xWy5GKfxabu3uUGBFKOwB_7Q08EPZFBWxkASpUxKLCygFB5jbTGSUkopYAbAGLxSwJw4JRCm4-ukKKZAqImUzrPjp_SIDRURZs6KnFlS9KQIUQELQlLqeH62YfKootaUIqeUJBFlhSJIISmtmAVFjDWY2TgcqsXKTT4xS2BhRIrsooiwsMkLQEwK2EdC4TAJJx9CCo5UZjMbwghIAMTMikgpRBaQKClJ4DgFANGEfujTNJLCMHltTFZm42E01nBkTklJVHmBVmmtrdGZKawpQgyGsK7n211ns2KaAholDBwDx6hAdJHrVekHNw6jKQptjDJGCEY_AvJxc9VUNQA479glZKjL4uT0vB-75Unrvd9stu-fDnePu4d-GPdu6kJMsNkOzsdD1-02-xin3caZPMtYbJbf_fQ2r_Jnl6tnZzOlLcd0vmraxbzNbFtUq3m92xysyT756OU4-T_77cdTjPPKJIni_fm6yYwJiRHMbr8nohhiWeW5sVrAZAZB2raVFGZN1RZ5aTUK-XF6d3f76uXlpx9dnS3n5ydrkpBi6ifXj27RtAoMSHp2vjppq8qa4IIlfbKcWaNJEJHauiKWzeZp3i5ubt6fnq-r0hCKVmRydbI-KXNcL2fdtn92dXoyK371ybP_9t_8yUenq2dnyzJXhtPnH11dXp6czOf95KOSVy-uJbg_--0vd-NY1EVemaYpjFbjNDZNuV7NtUx__Ie_jYf9f_tf_e9-9cuPS23_5T_77cuT-a--eHFel7WxRxmN44SUCCnLCudTCJKYs1zbzChFKcJ2d9BGD8M4uqmpyxRZOC1nVZnl87YGTnVRKKLDNHkP_TCUdTEc_H0_XJzNQgRBnrzfHfo-RKM1KH3a5LvOH8Zea7PbHIpME-myyNzoWQQUvnn7DlmenjYnp8u6KkFUWWaHwyCJmSVOk9Hm-x_erk8XMdHjbmuJ-mFInBJTv_cphjIzqFWKsaoq5yILX39-GVzsHqf902H3uMlN1s7baRqiMDqeNYXWlFxwwV2en7bLZth3ffLv3t1-_-b21UdX59cXN_fbbjui1WlImBlk0MHvebR58_U3764u5g-bPvhgc50V1oUw-nDYT_WsenrcNe1st-uyTC1Pl9tdx0KFsfvDuNnuE9Pr15v9MArjD9_efv379z-_v33a7hBxDLzZufVycXKxuL46cVNQhn71-cu6tNvH_npRKkOzok4pNrOqUqqC7GI--2TdzLLcKro-WVxdLBbV7OOX6wRUFuUvPj-3YJqqbMpKrL18frFoqvWiVUY3bXX32AEno2G-mJVlvWprI5gX6nw2K7QJzjdlEX182D1-dHleaH19vqxyu7nbTBys0UWexehXs7ayurAGAcbJPe2HoizdOMXIkw8xxGH0-64PIWrEMiuUws1uH1iEMC_y-4en29uHLLdaUVsUU0r7flitlnVR7LqhzEuXwhT5b_762__wV_9QVFXZLrI8_4v_-Pc-8sAha5ppHDJti7KyVq9Wq7Ju_uU_-YP_-L_91WazbZqiLMvvv_-pLYtZXRZaRe83j4e-7-rSLNqZ0YSkRaPRNJ_VGUIIk7VZnekUfG4sEzkBD_L659dXF8tnyzkAbwc3X1YH727vn3xKLFJkRV5mRun3txubqW0_ZnleN9ntdgsJf37_gMoMrmeUNq8gEbFOzBChzbL3h815MyMjTVnstkNTFLO2aOrq9GTeNPW8LrWyCBJiypq6d1O37_t-XF2eG6W0pvmsdZAGP_Wjf9xsizwffTh6uwkxJ9NP7uXLs91-OF3OWdK7dw8mN8KSZdnT41NRlJk2Rabnszq3ttv27592y6YqqxyJIcHDbjdvq7Yozpfz85PlvC5OF21VZCEkJDxZztq6uHvcEcSyrs5WdVvkitSiqTjJrMoXdV5WRXJeBOI0guDtzcNf_6evM2u__t33l6t1iqyNfbw57B8Pn3356bjfbe675GJR5qerRVOVf_yfffbV33-vUqqr-cuPL3_1h59oIN_3rndPm-H8xcXeOd8PP_387tWr6-VqER083j6enc8VzF8U85LO59KNwXFzfjFu96SAlAEBZTNJCZAIUJg_RAkIUGtIjEfupAiISEyChAwKtc6LFINCSsxHCg8AHE-9SKRIoyIAFGHhhEf2plYkIpKEGUGUyQERGISTcAIRSaKsOXqFQevjYF2EAZUmhZqUNkdiqbCIJNREeRGdkxAR4ENXERURAbMiPCIJVZZJEkgJiTgJHgGlRycyAH3gnyoEAcRj9ReY0ZojMpQ-gP6BjJaQEAUAIC8ZEiRGo4AFFIFCQqu0SiGCQkQJg1OZQQIBUJkFSKF3ZIy2BWlN1iARZZkfeqWNLTLf9SBsyhII3dNgZw0S-sOGtBWJkBIzioDWGpiBxRQGYgquR01IKvmgyCAC-4QaFB5PQ0oAJEVgAQBhBnX0F7PEaMqCYxI-nhEFgbIsM2XO0ygAWVkYW4RpitELKGJgZoWklDnWvxEJUjxyRVGbMIy6yJCUAB_FDCQpeadyS6CAmUFSZGO0HANUQowEhIQQvKfjPer4OvLRIgE6zyUxkkYkYACJROCnYKpcZwWRFgBtTAyOPQPCca-ChKIIABFIOBGA0cZ5Z_LSVOXYj0prNwyadL1eT5sn5JQgQHTT0FezOSJRXkxdJzG4vtdGP96-f_Vnv42ji-MUht5ae6xkoNKQJIaUlUfUkKBSfurKdtZtdpeffKFVkphev7tdzU-eHh-enjZgFAOkyLlV074v66Y-WcZpcFOIgKCssmZ0LsbYdVNCnbcVavz27795d3ejCpW37ePmvqiadjlbnlw93LzFxNFNEgIm1kVmbY6I2byUwMICICxAikgrTkIEhICJJSVhIZsBR61Vck4bLTHGadJGwVG5wOLDJPBhi8IswTllLKEGJCQkrZEQoghHnWdpdEkSotLWcoiGBBGUzoEgxcQx6jw3JkvBW2MAQJCKskGC4GJC0VkWUzz-HiJrkYVdRHUsIqBiTilISlodl4uJY2QBRi1I-WJGov3YG50JiARGBElRK0RJMQSjiAQgTErTcOjySpPCaZhIM0-DUTkea87BT_0QY0gJADEv82kcdGZAS1mXYWJjlNUkPgjCcBjRR4WSVVU3DpktlAKTqeRTnhVZnod-dNt9FIkhzObzMs_Gfgyxb5ti99Ttn3Yk7N2gtJrC1M5bpXWCFJ33IQCRzrMYJavyelE2p_PHx_4v_9NXqiked91u9P00Dm4afVRWPWw2P3z_5vuffui9__7d-6LMoyTmdHO_U5w67401235k0NPkNptNTJIZe3G2WM5rizCN03q-LK3xQ58bs2obLSn4wBInP724vlg0dVXkdWGNBsK03ewft9u6LJUiDrHIrVG03XbT4PIiZ2EJKfrYNEWutNFICGVuFrP67GxttNLChuX0dFkYvXncfHR9-vLy9LSt__TXn16drdqqLPPsaXfItfIuNk2NQLt--ObdzRTSoes1gjXym9988uuPnn_y6XOOkVAF73NlfvPLz55dnNiU1rP8j__ol2EYNMqz62VdGGsUMh-zk5rQJR9ienja1VUBSCFGlljm1lilSQ_jtNnu67o0mVZIZZnnueGQUkqkSCkdQ4whxiiB42reECIyEEFIXBkTRV7_fDP4-LjtSOl-CiL0dL-NLIysrNZkQWFu7Di5u8en0uQIGKegkBQZm2W2LCSBAEAI26cDC2uly6bshrHJ84eHJ9SiSXkXZrNyGlzV1lWTu3Fq53OTqaauD8NQz2tDulTFbj-4fhtHdzM9sOiL9cn1i5eZNp_89rP2_BqT1Mvqi199tFovn-4fz5ZzY0xdF7O2dqN_fNi-uD775S9efPnRxc3mMc_qz_9g2ZxUq-rk7vWPu247P59dXq---qvXs6qIiZWoXNtx74xCZU0cIwr_yZ99QZb6XbdYzpnivCkXs3p0YTkvLq-WVV3snvY2Oz5U9O837qOzxa8-ufro2cX928ezk3Zwri5UrWXztK9zWswq5wJptsYISPSxyoxLYjQYxYt5a0vab0dwjomfr6ovP72YzZqTtgyeNQdx4XxdXZ_NXqxmYWJIvtaaSZ5fnn18dT6ri1yBJjBIKYWhmx43XVaaJiuv1qdNlc3bejj0eWa0Nv2hm9WlNaotTFNXKOBHx4RDP4g2fprKokQCtMoout8c8rzYd_uqLIrCvr971Fk--eh97Pu-76dt15dVXuX5vhuGYfKML87md7ueBb_5_ntSWe_81z--efHsmZjyabPbbrbvbjfvb-7nV-vdZjv2U_KROa1WJ-9v7xdt-ebtTQjh1acvNcI3337_7OpcJtd3h-dXaxEZXbh72CgkHyat9csvni2sPVvM-2n8X_7ua4PT58-f94ehLXNGPQ7-v_9Pv9t3w9Xl6enF-XY_KFQCvL3d3jxuu8kVtnDMu0OvtXHOZVleFLYq892uGw9u1w8acDGvq9Iu1wv2AYHPVguloM31yaoJk7uaLY9jKq2oLvNucpbU4HzZlG1dPG57AnDeEREpeH__1Lvp0bvQjT4mkyki_PnNXVkWb97d9v1oM2t0jpKQ4GTdDuOU58ZoFRj73X5xOr8-Wb1_swVkhdK2bfQhep63tVaIhM6H09VcEWZKVXlJCs7WCxLOrC20QhEByTIbQ1AoLvi-6yqjT-ZtnuVFYcbR9f1w9B9LSk1ddYf-55_uOudC5DfvH4sqy21-erns3XR-svJTnK_qV5-9lAD5vCmQXr68uH55_ezZed0U-_unYZyG7cSMwPj5lx-v27ap6nfvH_bT_uHQSUJDWT2rrNZffv5ZlqnucfP29v70dD50O4XNZfQBB68UQWKAqBUmBiHgxDrLYgwCQqhEGISVMcLy_xeCFwJCRYgELMraxMn1XdYup26T5VVMEQkUaVLIiY8H6aMDjIgkJbIkkYkUaYMixzRO4oRKAwEAShJtFCLEGI_bCEEUQJNZSVEpJQDJs8nylMIxtoTWxNHbskbAFCOIkD7KDBRZfRRyAcCHHoLVH5iJCvBDaF8-rCYEAEiONWj5cIIUjlrbJEzAhASIQAQgdLwUHXXAWh1Zh4gAQserFKeICkVAGSvMqCSNHogkMSoNgNpmkVOMAbUOPqk8T86rLAvOpRhsXgQfKS-VUeycCAoatCZMDhCVJkUozKgIEDiEvF34bp-YbZYzqOgnnWVKHWUACYhEgCWRMewDaSKt2AeltQhzYhRiABFARG1tuWimbkjeZ1UWx8GHmBdVVs6moUctSiv2ERRKYiSVYlImA0iJmSNnZWmyPHiPxw8HC3AiZQAQYiJFIQRgUFZDZEAFgZFAAEkrQEySOEYiEvxHHJWm4w4HtQZAjomMOgJtILGbHCCRzoTIHbaUFSYrODoR-tBqT3LcXRGQUpYsphgSAxHqsgp-smUxHSYBqZbL5CYE0gjusJ_2e9s0oMnkefLB9wdKkUPa3m0VqvGwF4HjPVkpbYviCI3l6JNzNG_SOErwwEFQop-a0xMkqm3-7v2b85PTXbcdhzD5UJ6txcdhfxj7w7vfv1N12dSLu3c3YXLv3_z0zd_9w_dffZcvKgj-8f5p83B7uN88vr1_un_s9j1puH37dj6buaHvDsNhv1eSbJHFFFKMWh3vaDaGKIjMglqnEABAZ5qyLPmASjGLABLwh1UAojJGIQmn6MYUQgIpZy0yxCTBT8e0IAszB6WtIuDEHEVpQwjAxDGozIJASCnGUNVtGLvYBwGGBEopQWGXyJIinUJMwinKNAw2z5E0aeLIJs8FkjBH58gYrZA5Ka2tscZmDGLzPIxDCkFcEJEYg9YKlQrjlNnclq0kARFT1qgpxqgtuWEiReBDihDGIN77wMlFAM7rMkwTASqF7jAICBApJcSJxXm3ixHaRdN3g0KVa9PUJSrYb3pTlzEmtMRp4pCmaTTGpOiV0m1WVFXlh9iNh90wGmvZCjFqlKYplFLBs3OBY1qerPPKMKJPyR08AyudhinkBbV1obLMxzg7XWw3fbeb3v98__h0f3a1ev36LjdGtBKNIYgPEhNogsGHfnLPrs6--Oyjbt9dnq7PVou8yMbRex9m1RzIfPfmLkZ3uVyu5_OmyBA4TB45zdp23-2stlbTom1_ur1fVKXOrNFwulwWRX4xnw3d2JQGRBSpw-gTJ2tovZg1VX0MxQJIXRZGq9yYuqnCNF2drZqmcMN0erp8dnF6fXlW55pTIuFD1z097f7FP_8nJ235r__pr5-tFs8uz5Riq3VT5RIlt1rn1iO8vdv8T3_x91-_fltXZaazN-_f7x42ly-u7t8-nSzaVulnq_nHL1_8yW9_0-23d7cPi2XxL_7wt9fny0WZN7nNFGYIGgGYRTBF8d4jABIB89l6NU6h6wcinQD2h85NaXfoA0gIYb6YZYqIlNHGjV6E89wmlhjjfpzunzbHKW_fu-BDYI5JtLGT85oUAzHhbvKKSGmdki9KHQMz4OhijJxiVEbtDkOWWVJ6dM45B4SP-43NsmZWjaNLItt9P28qa7O8zCJQP4ZXr57nbfnDd_cnJ21e5MN-Ol-vq7oOScSoYT9opcsie7rzL15c1nUDxNuH7uRsWSzr0_b0pF1w8jFFm6vQjX7_VBjdzhcc4fb2UYRfvHi-Xtbv3t7PFvV6NXO9K-vsabv7-c2D0WZ2uf5Pf_HaTZS3unPx7NnV5v3wtJn-zX_1JaEZutQ25atPrrQCTeY__-e__tUfnnXbOA5xVVX_7l__i8uyCc4fdgcNWLeLq8VJ14Uiy6tZU5X1n_7q1aevzv_tb159-ux83dQ58rOTeQqhyExZ5S6k4EOm0McIWt11h37k3331hoW--v7NzeP2__If_3aICYSY5aOPz9Yni9vHp9f3_YvFzBillZk3ZVllJ4u2G6f3rx8enw6bh203Dr98djVFmdVlP4XcGgF86DoGmMaYF3kzK3s3NkXR1HlmLMSolVbGTNNwul6UWUYiZWY5cG6NscYHDgJ__d3ffPr8FSl8f3cvIkwKSffTaKzJlSFSLqYA6AInkCQ4Ohc4CIIm0lme1flfffXdNz_f7g_9KLQdupD4r_76H2yezWbNfujvfrqpZu2vPnt-8ONm33WbfrVcN039_Pr53f1tkZeRo_P-4fHp5PSkqsqqKJOM4zh9fH15erbMgVbz5nTWPL8-XS_nfTeqAH3vNtsDJf9Hn320bOY2t0VR9Cm8vXv6f_wP_7MfpoOLV5dnmS0yrX0KRdtOg_-Pf_ctMD52fdePD497JQhJcquN1SFhWxZENKvy5bypq1IJHvbdet1og7khU2WcErtIxihDgaHQ5ulwYOCrixOb530_OOe1MsbQw7a7f9r5GIeDiwkWbbOcVRZoVpfK5j__fLtaze_uNyfLRd3WL65PT9p634WysHWpWODpMO43h0PXt7O266asyGZtuZjVSukQpiIzdV0oQOccATZNsV5WT5vOHGMPkIrMVEWGAP0UHp62MQkBtbNWKVApHfppVpdFbjTgZrM_Xy1MlgEwCRqrDodu8nGKfHl1Mps1ZyfrXGXsOQVGSG_e3Fity6r59R-_9FP6w998spi3bdFqogz0_eMDs2z309Wz1ee_ePXq42dGZ49P3TdffSeYnJd3P7_-7OX11fkcY7x8dvXw9PB3f_ddIvroxYtvv_oRCJRZP0NOgMKTlxQQgKw1VRWHCQk4RaU1iKSYtKIjZB2FRQS1QZAYIipiBkRSmmLwEpmUYRYGIIKynvtpAhGltIgg8PFUh6g4RvgwnEZhlsSgFR11Y5yEBQRQG0RIzpM2pJA0QUrMcIynCDMgKKVREQPbvIgpSUx4fOoQoTKSGBQkF8goVMdRsXBkpTWiEAgqc-QcQYxAGiIjAQgC0QdWUeR_TAEhJBYW0QYRJUVJDMKCSEjCx1NlgsRUziQGFEEAZYyAACESMQgiKgVAQEcKqkJEEKXJKL_bkaKsaUFRCkciJ5ExcRoIKbrJVkXywVgLhNoa0taUlc6zME3ETAJH-VdykZQ-ricAGImMyZgwjqNCAKLkGODD3YkTa6Ojc8JAVgkzmg_XOUYgIkHh4JXNrM0AyA-TcNCkvHdkC1QmdAMgklEcIgAKJp1ZTgFYgCglYREh0HmRnINjeiMlSSwIEGNitlXDKWmQFBKAKGtIIQgLqJhQUtDGHp1l0Y2oMqU1AKI-UllBmG1VSIzsPBkyhT1WrxEVZXl0o3BUJlPaHO94kiIKIDMASogpBABRSg9dbzJb1M3QHbKydm5Ko0ethKPvJ2Moz7LHN-_c5LOqYlKImURvs9x3PWmbrZvjG8la7UbHiQGgmLdKqxC8HAbKc0nCIc6vLt3g6nblJq8NTn03umG5WPbj2G-249MmeD9Ovrt_sBZ3u80w7lNKh-3DfLl6_smL88uT6P32cXN2fT4eut3tQ1mQ8YMi3z8-bN686faHxerMVnaxvnp4f5eYkcXmmZ88CMQUFKnIgkpxTNpYIZAkEgKQOpbISaMk5hRjiKRJUgICIg0MymhJyXeDLhpNZLQVSSYvsrwMISKycCL6sOIjpUhXwCF5L4RASDaLIWRVpbMcQbTJJARtcm2UxECKTDWLyWdFrgvDfEyLJpMXbhhsWWhbgSAgG6OJyHc9x8CJEQUSA6OEgIqA5FjQkTgqpbx3RKIzq7M8SRQGEZVStJnVWS5EOtPFYo4ai9IqEUFJ42QyO3adANvMcmIGyqoZYASR6Dk6H0MSYWIJKQJKEikW1WF3qNsyTTFOwWbW9RMQ5HkRU1JkkDDPs_Vi3cxzEIAkib1C3O679dkKEKu6Ol3Mg4tZblOMpcbgw6wtVWlf_frq528frFYpycPukAkVRss0sptsbk2RGY15kc1nTWnt2I1Fblaz2tjMB1dVxcNmV2b6dDk7ny-3u-5_-dvfhej95AklL7KPLk-uLs4VwtNuqzWtF3VbFm1ZOTeVVZllZlaXQcKyqn98esqMsjZbLFujIUwDAAgmQgo-1k1xerLQSh_VkYTY932eZVbrFFxbVkpSWRSH7eOhHz5-fl0UGXJUAoXRudGLuvr1F598-elL4vDFx9eVtoW1hOwmr0GUzRCpH9zdw_6v__abH77_-TCO4CGmdP_-LgT4gz_84rNXH-WAMfl5la3bVlt1e_u-yNR_8-_--S9fPasyIk7H5PTQT_th_Ont-yTK6jxyGKegNDHD6GKRG2Y5DGOUhIlnTVU3hTZWEZGmt-_vvY-g8KStgmAS6Ycpy8vReQSVGGdt3XXjNITAaTnL-zHe3R98SFNMghQkJua-m0grN055llubbw_9bDF72uyKPBucQ0KO3I_D0-agjMqsMca2ZXl3_zT0gwAklu1mBwqcj8PYN3W123bB-Y8-PSvzPPjQNk3vpszoata087Ytco7iQnr2_Hwxr_MiU4SGTN9P87rtRi8CRVkEH63Ni7x4__5uVrbTNJyfnUjwh93w9v6-rYuL05NX11fXJ2fn54veTTd3T9__eBOZYz9Vud3uhmlgSckinZwuLSkOtrawXrclIQpnWv_Rl9cPN_tv_-bdP_-TT1qrYiK3f5pX6tXFqc5Mqsx_-QdffHS2-M2n51cn9dki__h6UVnJifLCGkW5xSzLYvLf_fR27IdZ1fS991P85ub-L948zE3ZtHVWZfPMjl2_mDd5Zn97cXraNGVVPD0NmcbXbx4WZX6-nn37-s75EBLZwgrDrh9O23k3RG3o00-fn5zPBVXdVsroRWF-ety_vd999f5Ol_W7-8f_7q__fp0XqGyTGe9drtSynWe5Qok6y3JjN4dDWZVlnm_3HSOM3u-6sRumZ2dXuc3ev7-r69JkeQLs3RRiTDGdrJYpcT-53qfRB9JquWj7wStjgWU5X_iQFMG3P75pinKzG97e3KKhWVGdnCzbuhhD-Pb7N1GgOl3-L3_-t7dP-yg0Tb7v-tl8_u3vvyGih4fbsm5H5xaLedd3ddts9k-zIv_tF5_Gafjm739azGtA2u_7qi6Lqhy6UZh_vLnRyL9_f1PXeZXlVVPtQ_q__t_-37978_Pbp-7ZJ5_85V_85eN2_PwXHz_ePxGabur__X_4q6exu9ntnjaH-clKYhr7MUTuR5e3VV5kItIdxjK3dVVmRrvJLdpmGsYYeduPd4_bbpy-vXvaDH4cYgAu87xqcgwcI0wheEku8mEYH3fD9nDI8_x-syGlB-eapu77Kcvtsm32_aHMcxBo20YjzaraGkqjL3ILElermS2y-ayJU2hmJSlq2yakkOc2cgQRbU1ZVcxpcj4lQMJxdIduLAp7XFUV1qAizyAMj7u9UcpaE1PcPu1dSLnNzk8XTVNMLk5TLKpSkAYXphB__On2zft7BBynsW2ayPK0H_b74fbdLafw5u2bbje--Pj5-elFTOGnHx4_en6RW1PYcjf2b39-c795yvO8rqtf_PKjedWYohAGm-l_-OY7o9Xvf7zpuunZ5elqOfv-x3evfvH8P_z57w773eXV5X7f390_XH18wSGqF__y343bg6QgwZMmCSHFJMz1ah2GAUG0NswJlUJmAFFaC0L0rDQxiNJKmBGBMpN8_ABMUqRJ5bP5sNtlVaHJeE6SIrMQUowJtdZEQFoZdRzHEsExzg6ERzcUEh6H9KS0KIUoEJkDAwIAA3M5a5Q209BndRNDOjZC86oGRBZRRofek6UjKVJplMTIYnLLIkAiiVEAWIQjkiECEUAR1ICCIEcb8j_2IAAEGI5e1RRBAK3B4I6-1eP5CRQCp-M2QIBJKz62C5gFKKWEmjgGQmEXgSElVsqIMMSU1zP2Pm9nKcYwOpvnH8hEkSFFIkiTY4CsLFBbQEGisq6ZIzOYrODgtTVpcmQzENFGh-AhBZ3lwXtJDAjK5Noa5yetlDr-H1NKiQGRrDp2u4-PnGMiCESQxdgKUmA3HvcMtmwAIIwTAqfgfYz1bGGzYhrHf1RDQPJBWHRm07EZmZlj2RQ4JUAOSWXmqJpAIhEWBFRYVXVMwCkQoqTACYQIEYWS0ppD1EXOPmprOUbUWlKKIUhkXebBeWaxVa2M4RgwMnuPiKiO8TCNhFlRC2NetdNupzPjdweTZyCi8iOHCkiJtmbqe21N1izHoasWJ6Ji9JMQkQghJheKylrD4zDW52dZ01Ke94f9_OLKHTbBpaKZj30XJicpEiDHKD6wACRG8gKCkiBy8A4VxjCdXJ4fxslaS6S6aQwhGk1NU4nw-vmp23cyTduff3Ixnc7Wwzg83e0eb7ar9XLR1LvHh_s3b7vDWFYlkVVA--0QxsFoshk-3b6v5wul6frVLwVTt9-XbQ3Cyho3OK1MuV4c38kQk84KU5TKqjBOhJAYAIjIIvJRfocfaNaICDEGQCBFyClMEzALqBBjUVdV04qIn0ISIE2oKfiA7JXKSVuldUpREWVl6ccRRDgFFBQAjumYnvPOx-DK-UlwThKEYQKk6CeJqWha71zilFcNpDBNEwihNoQfPqmiSBBtUYJwDCG6HYnh6Il9CuNRTC7MgIQi2loEKttZd9gn72OIafLT5BEw-hic16Q__EKLfEweMWJEw8FxFNA6X9fQD_1m79047jfMAMDsQ1YU4kOWZ8baFFNZ18MwRB_85AKHYX-IwBA5JBm9X6_azVNn82wcJz-5s-dnVlFErgtT5vpPf_XJ7bb_J3_0y29uH5dF5Q5pMc_7nTckbVYmwaqtV6vF4mRh8qw7OCGdCG833e--_bnbHz56dpqh_unt7cvz1ecvr15eXh0e96er9TT1f_sPPz5bVp9cXZ-s17lSgFLmNnjvo2Pm5awE4SIvfn7zjiWRIs8Qp6ksMk6pMrYuCufT5mEHqMSo3oWf3txopLwoo4sIxJG1sdPkBECRyjLTlJXWOozTejU_mTek6JPrKwAwKPOmVYRDv5-31el6KTEQYqZVYa3VFiS9u7lBEEHlpzg5h6T2wzCfNc8_efa0H_6P__W_miZ__eK6qauTi8UP333_tN-9eX3jnU8oudVnq8XLZ2eZ1koEhYEARHxK4-C_-v7N-XrFYLQxgKQU3j3snfPVrHQ-7nrvkvyn719frucu8nY7dLsxcQKgoiyIKCTuBnfoh8PgkMzDZrfdHrQ1bVPcPzwtFkUA1lo97cfRM2QUU3LOP233kDimWOTl2A2Hwe0Og4sRicZhqJt6dC6rCkQCAIOqqitrTG5Nbm1VlA_bbrGYeeeij2VT1m1JhrxPnJI2xD51W9fth8QppjQ5X-Tzcej7Q-eca-dt05Trk5Pcwv3N083Pd2WjstIySFXbLKP9ftft-7IwRst-exjceHpycvnyKo7ukxen_9mfflkp01Q5WP03v_vm-9f3WZ6vL87mZb7d7u8PY1EUSWI7K0NybVPcP20NQV7qxWxWGtXUxXpeL8vKBbeo86ZpPro8-eUXL15erZrSZlpbQ6fz6uP1PMaogJGQJDZlhUJxDGVW5Mrm2t7uhvd3-29-elw2ddO0s1UjMZVFMSvtn3x8lhcGAWZlaayZz4p2VuZWn8ybrCyqLDtZtU_3e0tKEuTWVLkqbB6Bp30_dj2A2g6Hi7NFUzf90HvvTZlrrf7uuzf7kJ764ac3dylJEpXp7DefPjNK7Yfh8WmnFV1dnIlECMEWRW5M3_dFVTZFdhjGqsgRyadUFNYYgwqc80dDaD-FYXSL9Tq4sa1ra01m7W5yt9vDvp-GKTzsOm2UNsYYHULMjBFEH2IU6AcXOL2_exRJH788W69Xf_6Xf2_L8v5pW5XF_eMuxNh3vu_c4mR-_-712LvJufPrq_uHx8zasqwP_f5pt1utl59cXtxsdv_kz76cNYYxFoXJCwvKiHBZ5u2s_vXnHy_a5sX1uVG6Pj39v_8__8d__-d_aeu6bZY7x9998xNaFVP4D__rX_z1t9-9uXn33_2__qfN7vDLP_zku-9vnI8_v_5587B1KZaVZcG7-0fn43xeaYJ5XUcQFp7Nmv4wTD4gwv4wagWlMW2ZF4YWy6qdVZklnzCvimZVDb17etoLESB00ziMI0kyZQYsZVlkVsc4zat5AHaTM5qsVVWed-NwMmuA1KLKpykURb7vnBvDMPkkUtfl5Ka-6xdtXeUFx5gbCwKcEgIokarMhDnPzXLWokCI0RiVAA-Du7_vHp_2wU8hxeWyrYq8bfJh9Mt5EZlTZFvYCEDW9IchCh_1sdefnEngf_jpBkMwZRZDipNDhP2-9z7a2jTlTBspyiI3ajlrrVKb7umrb96eLprZus3zCgSqqqya6t2bt3_-l3_79u3d5qmbL2e__aPPr56fZ2X-H_-3v7NV2XXDfnfIq4oTn3_8fNp052ez85cXah8rjp6Eo_fH-i8pksTM8fhYJUQATC4qbQCJOSEpUloiIyIqo4BRkENUVcUxQvQsjKBAkZIUvMvqVpIk79EopQ2neLTkKiIgQqIkwsGrPEs-IAsqRBHgY8dAcUqIdDwfAApLUkoh4NQPJs9tXvabp7xdSEpJEkgyWZUSA4gtC0CVFUUKQUSIkwinFEkbEPgA89HEIaGh4yhe_jHXBCiShIzGD4LfYxua5IgzZSGbcQwAAIJw9CSrowEgEaBwstWMYxCWoxCZtEZtUOs0dEdgPyJ8oAgd7xfIKSYymmNMzsUQlNEcksksoAiRNlopTJ7jFPOmRkaJUducQ4gROCZB4hCEEyICJIhsqgpThCNj0ZBWBkhHH0gESUtihYIo0Udtc5EjOx5RRCLj0RSVJm0MILNzKaUEgkbrLPPDQEZJ4MixXq6UzZzzeV3FEGyZkyZlVZ7neHTxutHkJSGgUSjIIWmbJ5-UVcpoiBGCB22VMVGEg9d5FlM8Ql2RQWstAGmaBBG1sVUTp4kFjLW2apmj1jqMIztPSgMCxEAEPE1AiEoDEooSiYwQkq9Pz8MwZrPK78YPolwk4ZRcTNE162X3uEGNoJQf-6Jd8nGSmRK6CCiuG4SUH8cYgi5LUYZR-u1N1a6M0aBodnKuyhy1TdGjICEGH4SjzgttC1RmfnU-be_JmuRCeXIRgrv78ccsy_3YC3PwYXb2nJ0PXY9KDS4uLi_BiwtgjDWZlHVxe_80pLQ6PW9Wzfsff0Tg3Zs3gUJZGJtr3w3M4L1vlws0WlRark-TLh7fPWVlbm2tsgxFLT56dnj3QKC0VoAUY0g-ZlVtbC4pEYCtiuAikRaGIzw1xWiLTOf50foWfARUgqw1amWjmxInJJ3P5_JBEMYICMLMTEhIaDIrKNH7cjZXxh6ptaQMp4QgyKmo2gTInIzNQ3CmyGO3z6uKQxq7Q16UopAUapujtRwTAiuTc3TC4qYREQBZJBkyKquBozUWgUxehWkUF1gix-AnR4RAMLqgSBXtWgCFY9GU0XuWpEhppQTEIBBCHIO2CpAJgqQQ3QQp8n7Kqpmgh5iMUtPQhdGRta7vJQAZkzjoohjGHkEfZwHR-7Oz867fueCNyQWiRG7WzdRNzayM-8GNk5scC7SrxX7X__D69vOX5xLh82cniUkDWGVP5_XIKiW6WNWfrNc-hNdv9pkB0jhuBxH8L__sy1WezxV6hufnl0ZBXdqIauyH9WohwBLSbD1XqJp5m2f6qx--X83qENHHtFzOZ3VpFRmlht61dRWJyGgAte369w_bf3i3yTVNQLMmbxf165unv_7mJ2RAZebtLKaUJO0OBwBMHA_dWFVlWWYpxIwUSTo_WZW5QRGttEAqtTFaKwThpJHaquQYjbKKABnyLFeKnrbdODqb56J1SpwEJ-fyuhBSd-8fPv_olUIklc0XLaHqN92sWbRteXV-2rZVUehZVUtIhFRXGSA-bg_DMBhlAqc394_XV2e2KJBUSH7f9w8P22OSZ98PP765axbN01P3_HwRfBLEIz9X2UxEhJSwDKObQjCmOIyTC74ui7wsAMCPwfkoqMfRb3b9NMXOedJq140JkJROCIBq87Qz2hJQkHScG-V56bwPUULwIfE4eiGVaQuSumF0LuyHsShtPSvLIsss-clpAQCxqOumjEMYBv_b3z57uO1Ozmf1cp5rM-52PjhN6urq3Ptp0bbvf3qvCIRZKVgsZybTVVWSi5a0-LSu67LIm7p6dnWeZ7qy-un21ghfni0ynTsfJfHb9w9D12c2Y-R-P9w_bs_PTpeLZrlshWA1m2mtCq2nQH_yB1eN6O5hd366ODx2q7b-_OPL6_XqbLmoMyozw5GViEaU4DURxyTHPhhh37neRx9BGEKCGFIMsh99mRVtU6zPyqYs-9FBglk9yzLbzvLM2n4K8yr_6fX92A9VVb17f_u337_57ubRED7u9r_75vV6UZ4sVk1VTpOfGJ-fLy-W80VbN21TVsXkfD-FYZp-ev1Q1HWf5C_-5tsgsu2j5yRKH_qJrHWRQ0x3dw-EcgwGLJuyLgttVIrxcX_QWkcXUko2z3JN-8HteqeN6fthOV_cbXbzReOCaKuronr__m1u87aussxu--mp63ufRh9FUEillEKIRqnFrAXmfhjGJMv1GrTedd1_8a_-9Hp9YpS6v-__x7_83fnFxbbv58tZiOHm7unpoc-snVzg4NvVAkT6rkuSMkMx8WK-IOJxnH66uxlH95d_8e2bt-9-vH16cXpq87wb_Lunw-B5CO5hN4wukVaztv7v_v1_-P3rW5VnYbZ8-_5uiAmIi0wN-3672dzf3u67MEna7caf73ZjP-yfnrb7_dnqhADa5ezu4bGu6mHsN5veh7RczX74-e28aqOwRdW0xem87Sb36YsrF2M_TYumud-NrveH0b9_eJzGcffYm0ylmLrDECQJi1ZmnLwfY1lkJ6uFn6bSFlarn1-_Wy0aUurF9blGzm3mhn4Y3evb-8xk_dARaGv1sX8YYtRaz9o6xbTfHVAoeGeUnmXVpu-_fewbDQBKaR0jb7f7LDMhsgD0vTeFqeusnTVPe_fi8nR3GLUil6JImmISwCjoY0JUv__9j1mR3W_27bw5HIZpmCTxsq23u8Pmsc-MUUJj8MHz5eX6o2fnVpsYAqdoFU0-PtzuHrc9oBz68PbuJquK1z-_f3tzu990ogxzevbR85Pz9cP90_u3N-M4VqWpbf7dz-8uzpar-dpz-v7r79cXSxD-_j99q_Lzj48EemUoCWhFpLQwW60lJuEkSVSZAyAfZ1xRkBA_zNEAQUApADmC2E2es7AilZgxpWq59uPo3dSu1tG7JCIMmckEIkdRpMlYJKWtYuE0BWUMAnBiRBAWOf6hjzpfjDECEqCQoqNAGIAJVZTEyRX1XGvjfUgptcuzOI6iwGZ5dF5npXejUgqBOTKhog-EGZDIyihJCZVCQEDklAgRj50BgWNUBBUAAYsc64CQEhIeMaCIQEQsQoQCgAyoSVJiAMpsipEEUClIgIoQRRDZx6PZ4HipQCL2ERhiYCDIyiq4ibTicdJFpo1BbREZEwBSvV5qrUipGFPRVtaa_WaXFSUgkbVp6MEgMCitUmLkpLKcY5SUILEgGJsrawNHYSYFRPp4YSAR_tCrPnKZju1d5KMuQFtmQYjsHOZWW0PGCkPZtsG7aejzspYkbhyICCJDCikmSdCsTjkmtOSe3rEqFZEyhoWSdza3yScyxijLYfJjz4JFWSdSIQZttdKYUiIgbTOyR6t0RlrF4GyRJ-aUOCuqFHxiUYjaKIEPrjACBUghOk5o6jknN_U7aywzJJ8IUFcVSIp-PKaQSGGWZ8ISuj0p4uir-Sz6gMhlPfMhZmVBiYFZ53mYEqCQpChi6zbPFCoVvOMoMUZBowTJ5tN2f0RN2VKzdygowMoqtz2sX_3K7R4pt_1mW1UzbXD704-kdFsXwm5_c7O-OHXDOE1DaQtOjuOEadSa_DR6P4mLnOJiPgvej4fOT31WGoievdekbVW0bUuZvfn59W6zbxZrItW2M52Z-er09NXLm9c3KMKBYwyEJCIfyjYckUUETa6RMIagjUk-oDpG4pCFJUmKMa-bFKLShChGmRhCTInQNM1s6Lvgo7G50cp5L-OkrJWUjDV4bAspbbMyBUfagFCMAYC0QoCoszwGh4gpxpScspmkaKyN3muTlU3t-n3oRiLQJg_e57ZABX5yDEiKTKYhRYlCRKIkxkhKaZsBQpxiVi6RHYHyYVIKhFlSqmatMHo_KNTHS7hWOh5F4IhKZZJAqyrP6xgdoXYhKGtJqTjs0dhpmJAoeXeUNDMgT46Yo7jD085mpVKojPXjGEMCxBRDt9sH76OLSTxFiTERwGw-z2x2cXp5__Qwev90-3BzczNM0_awvbnftaetMuWiLZfLWpPKMvvybLloy9PZrKwyT_j8ZHF5Pv_ys6uT-eLzV5dx8gyqbqvZrNntd3WuF7OmrcromYXd6Bhg1RQXFycaKXn3_OysqetZ2xilgKNGLAujNEaG_TDo3Oz3w9__-HbyUZMeJ-dTSIBFVT9shxQTx-TYW5VFH6oqO5m1IDA4Z7SatU2MPoZwtlpWua2rAkEypbTR4zgUNlOkjKHcKKVUVtihm3xIT49b0kZrM41TSqkqiqKplKinwzSN_uCn9-8eX5yvzheLT15cnc3nmhSD_Ic__913P7zZdlMypKzm4BTK6WKhgWaz2oUYU9qPUz9575hBxxgnF5vCWqLR8Vc_vzEKkOjifE2Kdrvhaeg4Ra2NC95o41MyhX3sxkM_KKOH3rnJC6DR9vZpG3zonVvO2philtuYUkg8DD5EiSLG2nGKItEzjz4KggtpmFxMPLogKKS00tT1QWsTUzqMkwLs-3EcYgw8ToN3Yd9PWZmNo9OkL-aNzTJLUBXZ07avMnOxnk-De_58bbRRkLI8q6tCIuTGZpm-OF3P29L1Q9PWbVv2-_7icvnq42cxJAXYNnNrVPIxJiGlri_XP9z2ZyfzxbI9O1menMyenvZ__JtPZ_P2r_7m28M03TzsYkxVW6MmpdQw9m1V-hTyPG-bIni-PP3_UfUfPdNmW3omttba7nFhX_-ZzC_dOXlOHUOxqlRUqdlkk90SwCZAQC1BmmiigX5dQyOhIXRLItlVZPlTJo9J__nXh3vs9kuDyGpA84hBBCIe7LXXfV_XQgP8b3728S8-unpxdXF2uqjr5nxd2xg-PF_WlVGCkBNyntUFxpxyaoRQWpVFSSQwodLKNFprPYUAmT2DkPKxHVpvh5wFYeLU7YaQU9-PRWGUgLvHzdgN_RiWdTOMPnoINg6T1UqdNrNlWb94ev7x08sfPT17cnm6WpR1XTw5aU7nNQL6kPoQGDATP-7HyPzsdFmfzH_9m9ePuyEgRhY2paH3VVOTlCmmZV3e3e2WTfHJZ8_qSp3Pm4-fX_XdWBW67cfeunpe55QBQSncdfZ2c5jNql07xpgyopayHa2WKoX4_u7OKKVISqL9Ydp23bYbq2Vz6KwNcbPbSSliiHWplZJKSJ9CCvnxceujjwJ-9ukHtTb9bnz99q6Y6cn5YRwe7zaP95uHzWY-m6cYFpf10Pf7h62RGnSe2ilBfvrsCSFZN6WQ-25I0QOHdrLdOH21735703784el8bv7mb776zXfvohezuvj3f_Hr333_rks5lcX9w66fbNvadr8Pg93d73zIp8-e1bPZ23d3zbpu95Mq5cXF5ZtXb4wyNsA__-c_-5u_-5YTjz483u9WsxoSfPnN6_Ozxc37u65tU4zvb-9OFgtmBEjXN9uz81WIiIKvTuq7TRtdms_KsjDj4ACy1NIUZXC-LNXZojldzCGkru2VFOfrNVK8PFnOZ-XJar552Ll-isCJU2FEsLku1NnFMkR-d30vBahSa6UkEuc8aypIjAS7dqiNcTkT8MWiKMsqpaiU8DGiFO-uN0VhQoiq0HWhM6NAvrpYQ4LMKaGY-mlkfPX9XXsYRxdiCLttKwVZH6qi1I0Y29FZ38yq9Xr2zevbzz95WlS6qs2-tT96cbbb9Ww9KSULhcApZBsiSCjnJji_2-33u93Qj_ttO9kJlHTO_-h__fOylL_-1W9YxJwzsmgH_-OPny7q-g_-8Bcx-MPjtjGq3Q6f_us_6q9vhDr7PIQ4PznPCrONyMCchVCMkGMkgTlkIAFEgMCIyAwpg0BGICkBMjOnlDHzPzZGVZiskEIIYa3FnDHTMPXri6d26BGyrmYcIkkiEsFNJGVKQEoBUg4Rjz1cQkCmo7U3HtPiiEaTOtIJgQQRAAEG74wpYkjejqaeIQEgedcrVUxdl1IwzZwzE5EbLQAoLXIMQJSPCwVGQgBGzpm0BsAjDgg4_3AvT4Q_yEozIpJQxy5AToxG5xDxOBXk9MN9M2DKiRByjKI5YWcBIHMGzIR0XB4AAJljAYGIBKdEyCAlc5baADAKBDhOQem4j4CUAHNKaezG1dnZbL0qimpxtnrz9cunn__IDn3gDEjFbI4IyXvIUSnNMWXvAYCEoCMt9Hh9JWXyEXM8nvyZ-WjI4hBREBJIFCkEBhBScIrALKUmJYETjzaEYKoZsXB2LBdLpTRjnq_Oo_Ucgyx0Dh5zZs5-6kVZIhPNTuI0CUJTL4CYCI9NZeAIR2MwZEJQuhJKZoYcXApZVQpSYg4cIgD5cSApGQmlJMw5p5y9qWoGyDkiEHNiqZO3DBIYhFbEOfoJSCpT-2nSyuhCC4QUfIwpM5AUOSaSkgSJsiJgSBGY_Tg169Nxu6WcpCyzt8Vyln1EFMVJQ0rpYpZZnT97LpSyw4hCnV--sHaThokMmXlTn55koZJ3HAMCCqPS5DFFkGS39yRksC6lWJ2sFemirsI49tudyNl325xyDD66sX9_d_XpR5vrt6oSypiUvTaKiYWg_fZufXbGKc1PzoK1Rsqh64O1Q2dlXRGiAM6EbT9IUzTzWV0UvXdjP83Xq3a7W52dlvOZ6yfvoxRSG5NDSjnJQqFA77w0imOGnDNnVWoSEpBSSogYJgsSkCSBefLJj81s5sYREaLtpSoIkSkxsDaVKKvknanr5HxOyQerTCmlzClNw0BaCcDgfDGfH60hKSaOAYmCj0hSl_rYSIeYhCQlhKx09t5NoylnKUetS2VMjFEg5pSAWRY6OQ8ZOEfBEMPITECC2Uo1Z0jSVNlHyjk4H6bhSIvSVUFCWusIkHOUQgTrgANEJzTlNEktU3SkRLATygJFnW0gGYmzQPKjl0qp0nCKKSYiqUuT3JRiMkWhVTGbzyFlIkTBxOSt45BQSVWVPobDdmuM6aZuOV_ManO6XJGgzW6_mDUhhe22u3t4_Obd7f2-W8-aKbHXWCjVDaMjRplICk5wu2nfPO7GaUClTk8Xsi4S892hy4Bfv3r_66_f2ui--Oa7uih1aVbzZhjtr796yQy6KgXS3_7mGzfZmOP13f70ZJEYbea7zWGzO7y92w2jM6V2CTfjwIRGyqEdbl7fdf34v_-3f5RcXNW1C35elymz0VproaXydipLfblaVkYLhBiiUTKktNt1q2UjleGcOUMGZmAf0_cvb3dtd3F-ooxGyEhQVrXLOUT47uX7th0P4_D_-h__8__p3_1rg8drIfn1N9_95W-_-e56k-qqOl1NPg7OxpghxkKpi_MTKVU7TJOPbT92g2WQojBFUWqFUqrffPX6i_cv11V9tl7O6wYExJBTYgD4q998C8BSyKIqfv3169Gl97cPowu7brSTPT1bGyVSjqVRm31_era8PFs567yPSsn314-6kIw4WDdO8dCOUlBp5P5gBUkg3t4fEIQPx7VkzimDFFKKyU3jNPb9JKUKISfIPvh-tIkBtU6clovFzGhGKrQ8XTSLefPi8mK-nDdloYT64Nn5oR8l4bOrk1nTKIHnJ3OjBar49mZ7era8OluvFvWnH3-43-2WTf3sfDWrSy3h46cXV2enHz0__8WPXzy9XJ2eLZ4_XRRSksIXVyfny9myqm-33eX5Uhtdz2pNwlpbVyVR3m8PQnJl1LOLk1LAP_nJ8x-drSslrnebSplD3xfaLGZ63ZTnJ7PooyCMBKU2JKkwOhFmzlmgULIdxqqsBFGlTSGhdenl_fa-a6_fb-_b1jFP7fD9q5ulFsjicOi0otPV8vR0YQRJhUVZIhEpWRZqVptmUawX1Wo-W9TVYl6SEF03SiUxxRHy_f3uq3e3wxS_vNncbYfRhVfXm7fXmylFIdWrmwefsodcNpXUuh_tMNgMSQpFAgVRXahSCoF5s93_8pMPn5yu0SUhaYrh-1c3N_tuMW-6fmwqBcz7bjIzM6V86KfNvtXGKG3uH7rXb98fukEIqbRMzl2cr99vdp7o1cN-CGFKvB_6afICBcd8Miv3-5YIpZQMWRA45z__6IUfLMSYAaVSQ3CT9WNv_4t_8fub-93kAgCYRtl23N4-NstmaA_FrHzYbBLkh4ddDvG__W__6y_-9nffv7tblmK_70_Wy4Tod_sUw9_8-uWf_sVvru9vkfDLr779T3_x95HiyLy3Acri9v1GVPrx8SGMY0rJDbZcN13fBoVhHEnrJEEr8_K77wUJ65P34avvXx7aw93dtrXTvK6X6-XYdULh5ZOzGNLyZFE3RV3Xyaery3Ol8Gy9ur17MIakVOMYTamuThZt11ufks-mMMQ4Wn9xvvzZsyc2ZqMMY57PZ_Oy9sE-btr1eq6ECCFfXz8GHznT5D1menp12lTGhTQO05MnJ2VtlNL7TZ8hXp6tDoeeAabJrVcL6_3oHAOWdZWYJxvKQpOkvh9NKZxPweV-HJ0LXTsUVSWFGEZXzovRTe0wdYdOSEDKwijng5AKENeLZY78_cvr05OV1ma5ngdvpcRGSRcSEi5W1eJsuWrmzXL-yUdXr97dvnlzX82rsjHbbhxGf3f7aAf30ccftm0fbNaFuXxy4a1tH3df_-ar1arSUp0sTz7__EeXp6vk3enpyX7Yv3l53XYtKS0U7V_dyqYScfY0QwTEnHh2NnfDkBmQ4Iccp6QjWlMZk4Gji0IJPjJCCDgf8yuIhEKIFAPHpBZlTpxTOr5Rl6U0ChL7HE8urg67LXISSsWQUnBSCkJCYERB4gdzGGDGxFIaRj7mL0AJOEaD8pE5ChCZM2cGJDRNIxABwdtJSHXs46YUyqYO3icfEIGk-eE8fSSZciYhEycmhIwkCYCOowUiAfCxi4wMjICAsiqPlmIEJGZAwgxkJCRGQgJGpBQjkcwMhEDAAJizF6pIMUqBBMQ5ZkIkYMwcWUiJJDgmeSxZ5iwk5RiFVCklziyUQk4cMiHlGBBJGKOEsM6nzBlS8n5xenL75nVdz50dOMcUQlnOU7Q5xRyZhAAAQiKB7BOiSNYKbUiSJEiQOGdVFZxSjokZiCAHDyiEKZAhhghIKWVCJiWzz0LPED1zDlNfzGYpJe-cKkyyMaZcz5ppHIOzSOKISY0-IAMiCWBCRCQ_TdV8mWOKKUkpgES0ViqZE2NO3g4MVFZGFiakiIjJJyIWJFmQlDLlACByilV9lqMFAMhMUh6FZULrlCIIwpxlWaaYSBpAQmNIInLIzjNmVRRCyXo2TymmmAUmAZxC5BzFcTAlBKJkh7pu-t2Wkw8uphjL01UKiSMnG3JmU2O_3V08e25MOU1DiNNytRLSHDaPwecYUtGsGCKnECMnH8ysEczJWgRMk0spAfuh78gsgx9d1xZFyTkxp5xZSNJSuYedLoAjdw9brar946bbbIOfALK3rt3tltVqGA9Gl23fLi8uorfKSEoZIUIm6y1y1FrboY8hF6ZolpVQ2rk4TeOHP_pJ9P6T_-IXt99dA_GR-p-YKaNp5mPbAgkSpIyODClGU1QIwIhC6ZSzKsuiLiM7Z8f1xZWU2va9d9NRDUIkBInkPaK046BMlaODBIIwhoCARBIQquUiB-uHqagbRBJKxsi6LI0pURGH6GNCpYiQOScfc_yhucLJCSFiSgRCF82RLRYzHqfc4-sJKWZGRVIRIGaOMSUCFoXRpMpqFr3P7GOMxyeVUuXRfHhEJAlFhJhTTAljIipKIQpTFMBUVqVSnEMMPglFQgnShZ9GBEghxpjZeYbsJxdTQkTmdLI62-22MXLZVDGlFHNmsP0QgvP9xCHp0uSUD8PkQ5IZa22k1M4FowQznC3mYz8O0zRa93B_2LQDQ7q53rTbrmrKcRwHFzCGx8cuIb672fztF29i9FVTIoBP7Lyrq_qTj64e933bWVNU37y_XjbVYrmQQgyTyylKJXNOT87XSql-cl_87s3pajH6-HAYZqv64a7ddb1NsR1dAkQkMys-efH0u2_e_-jTZ9al5FxdmVldlUamnFz0T8_WUlBTmBRiiDnHNHgXU14sKiSJDAw5xaQLFWIepsCEzz94okhtHjacgaSJnBHxze39fdfdPmz-9D__6v_83_2bCokzU6G-v7n7__7VF-87--1du2tHL_W2PUBO0zAtZvXnH70QlBPTzcPhdr__m3_41meMCO_e3zMgczRKzJrigyfnmuS2HaVUzseqNDnlFNPjpv_Rp0_LosqM3TgC0m-_frM7HPrRfvj8IiUQRNZPb683RuLV1bLvprtNG3x42PZSKJLSOh9jYkQgSiFttkOCvB-GvvdaKWYIORPJdui1kApwCumwG2PKhKrtJ-Yf2EQkiQUWShmtDm0vkPb7_dl6ZghRSkJUQls7na8WgvHDJ-vz00VjSinoYr2ojVwU5nS5_MmLy8v1YjWv60JimD64OC21WFZFoejsZF5KujptTpe1kKLW6nLVzI1Zl2ZeVZQzavXusH-2Ws-aqsg8DcOT8_mLy9Pf--jyx8_PfvnZ8x9_dPXTJxfzQp3Nq1WlB-c4wfMnZ_O6TMHWUkvMznqOqdCqLLQdfdtNJCD6dN-2u2G8u9sPU-hG5yG3ncfC3O_HN9cbI8XpYnF5sXx6Mn-yXl2dLl48PZ2VxZ9_9dUvXzxtZoscs3cp5AxSDi6Mk-0nf7ttlZEZ0GjV9naCLCpBiW8P4-v77dvN_u9f3tw-9HePOzYUIjeVKRu4fxzrUv308w8Ou-7ubi9IPn92UZd0d7B9N1ZG1HWZOdrRa0EffvpxRfRyf_dvfv_3ZlKXSgCx1Pjy1YOQdLFsGMnFsdA6JP6rL95VpdkPvh3G3WH88LMn1zcP7Ti54GwIKHC5rE5mM63V797e9tGJQu9Hv--tFHh6tty1XaHw4eFQ16WWKoWwnDWSxHy5OGwPHPKzZ-fv7h-8tcuTRWGK17f337181w0DEb36_t0v_uD33n75HUoMo4sMPoQck9AE3hel_OJXf_tf_vM_-r_9u_8q3bUPO_vq_e7tze53u91cF5hyYp6tF9As-sE__enV0E3vb7f9EO6vtygoA1o3corRh8Wi6jZdyskPHWY087q929t2IIDhMChj_GCHticgoWRZFEaX7f7gvPchORcBSAsYRptTst5LEmezxmh5NltqCZu7XW9d301npysphVEFIyfIgujkdNmU5abrhdD3m4dCm6apu76dz-vL06UUYuhdURWL5UyRUAZmlfn40yfBxeBDkuAyLGfm_q4NMVfGpBSrykCGYxl1sm7XtlrpWV0_PGxSzKbQOcP-0IfEzseqLn2ISgsEKKvK1Hoagw9p6Nztu43SulnU4xTu29H7GDIvZs39wzanOE221OridGkUnq9mSurSaAKsTMnIp6vVw2PrphBz-v7t_Te_e_Xp589MXew23W7fxeSNludnJ9LAYed_8k8--OTHz7_78vUw2D_6w5-ezeY__fzz9WJ-sVq2Xfv27fvFqpZV_f2Xr3xKzsdmtQx-0gJ1YlF8_PMYIdoeEKLjs599xINz1iFmrXU-Xr4D58RCKpKSj2kBZkGIQjAA-0BaJ59QCkRMPkhTpWOInDMD5BCFlBBj225PLp4eA7hIEnIGTskGRBRS5syyNEDEMcFRR5yPHVGAxIQglDyOGjkkkgIg5ZwwcfSTUEYg5pxS8AxEKAAIAYWUOSYSBFKS0JDh2EZlTigEIBEQM-IPeMhMWsMxm58Y6WjyPcZ2BCAm75EEADIeEZosizo7B0egujgOMgJThuOqJCc9n-eQIEbAfyw7qoIYKCdCwTlyBuB0ZAIBMwALUwBjnEY8rh2O3rEEGZhziiEfE95SSKVLH6Mdgp-61ercHnbRuxSd0kV1-ixBIimBMTNgAiRRKCOUCMMkCw1MKGUMib1DVfzwZUpNCDkmyImUAkE5g5CUE7NzKDB7mzMrIZDYjZ3SmlJwfcc5Aymp9er5C9e3kkBqFcZJakmQOUVEgSQzMEnj7aC04aMjWghRFNknIURmhhzBO9KalEIpo_cICRFiiEIrjpmk4hBJKu96lCSF5AwZAZgJOfmgTYkkARlSRMIcPKMAZj9NmJmIkp3GflRViZKKqhFaR-eEQI6JU2QGEjqnTEzAKQYvpYLMZVXkmKJ3KBUDRu85WoohW1-dnAghgvP7mwcbPGCWUoC1JISbBqFKc3Iuy0VOMXmPzKYqkosIol4t_DBqaarL86nrwtCXlZZCESQ7dpgTAnhnTVGqurTd1nWHptBgR87R9f1idUY5PNy9Pzm_YkGqmTnrswvZuzjZYENIuZ7NBdPq6ZVE7ttuc39_cn6FklDgYfPIoPVyFmKchpFjKssKJXJIgFkpqk_Pp74ViGa9VFLb3gmRZ_WKgZmgbGZSms9_75fb-3sAMfYHPw2IIKVWxiBk27XBWWkKIQSjYE7lfGaqOgWfQmZAKSUA9Pv29PzT6IYcPEPKgELr4L1SSkit6wVoyTkjYQ45RxCKTGkIMnuXoldCezugQFVomtWcj9G1I823iABSFZQpcSCAFDwCBuuIIOQkC6XLihiFInYuTBNJKopazZY5JgQkYJQSgDIzSBREwB5SopTYh2o58zYIRGQmoSBBSh5YCKWQMmqljVJCaKXtNChtrHNFVeqyHPtBSe2tr6oCONrBVrN6GEY7TLv9Jqc8Dt1uvxWVPluvV6erpq6MKR1737u794-So0JUgperpSRaLGfrRW0KrYV4-e6wqFRZliHls9PZONnDbmjHcZr85NPb20dAIQrx7OK0H6bbzW7ezA79MB76fTc1s_rd3d1PfvxhoXQ_utGG-Vy_uX3ctP2Ycg7p7W5HAMEGQpKERams83cPm-CHqfPI6cnZqtbKWffYHp6enZzOF4q4EPofdXIiA-eYtVEAyAyJj8F6mXJq-2n0XkgxW8x2u8NisYrASisb-Ytff31wfnm-vnu8W5-d_MHnH5RVVRn9Z7_6-z_59bf3U7i1_ubuMaS83xwSxdN5o4T86IOL5OOsKu62w3e395uD3fb96GNiaMqqc_bh_rCcz5qm0Cju2v7QjVWl31w_QuL73YFQfPj8avRBSfyH37w2ZWmjX58tHh7aFy8ul_NZJeXLN7ecU1MWpyfz3_3ujfXRhqClIiXafuy7KSJE4Bhz8H7sbGeniGBTXNer3o7WBymo70aji34YfQgxRtLAEQDEft_GlJ31MaXEeWgtpCQJURLltKiKrhsfrV8tZkYf-3iQc1xdzJDF0E-IIIXohsGQ6Ae7nNUCQUvZHtquHYi5roqhH0Py89ns0PcEGFJGQG_DMPjJukLKstASsxYSAVbGKCkLSfPaPD1fnc7rWa0gByKQiJU2AtKsKKbuMNiYE5ydrn10h0M_9FYXauwHAEycY2IbwjB6n9LM6CHmdhyfXJ733WSkHEc_TO58MROE3TjeuHBV1dtxTGP4j3_9uzD5GNHU1cVKPj27SEhdO97vxi4GQv72_e27zSEQjYJev7v7sy----ru_tffv_3mfvPYT6_u93_13e3d7bhpp27ybgibcVvOijfv97IgYP_m3S77vD6bI8Pt_cN20_7eT1-Ukv6nP_2Hk9N6Gn1wDoCMUav5gpBrwLLAX1ydnM3nlZYhxhjzNE43gy0MffDk7Pph_-HFGQLsR2dqs4--H6L16f1mn1N-8-5Ol8XyZKkEtvvderGoC_32ZtuH_Njb-93gEx9GlzJsNvv5rDBSuil89qPn97fbZlYh0qHvysY83j8Yove3j9fv7rXRVaFur-_ut93Dw31Z1IxYLuqhG1KOqi43m60phD_0gkS01k9-7HtV1a9f3Vx--tQB_fN_9cuf_f7zj39yeb4oOxtlZYqZ7qbxYdNGkYbJjile9_fz2Yqjj-O0fXg0hXJjKGYVMRHh7vp2moboUvLJ9b3E5MfJTqPQOHWtUpRzbGYnfds6Fzy72XL-cP-gtHx8eHz58n1yyfn8z378_ItvX8cQb7aH0-WsKsqL05O2PShFRaWO9O95XWXIpTHRhakbS6XdOJTCXJyevH3_9vn5ydX5Smu13e2fPX82tL1U2ihVlpojhDFwSt6Ht--231_vJxeWVYkgTEHnJ-vtrmOk93eP85nRSpZF0dRlTllK4UN00ZMiJtEPQ1XXh3Zcn84RBBDlzO1h3Pd9iMH5QALuH_YXF6eji9LoSsmT1eLu8XFWlEVhhBTG6OubR2MKKYUP-f3dLuc4DpNUZr89aF103WAKHVJs6qrrxt1ji0jO-_VquaxnXdujEIWWmPjj58_qWn_6o49n89KH9O7tu0Kp4NyXX31FgvrB_vaL35bz6u5x8-HHL1jCNPjVrPnssw_F5b_4twjSdQdAn3zoNm1ZFesnzw6PW5RIUnobZEHAYGbNER-OP5zOc7SBlJRK5xSEFJAhJSYpc46mqQkoQT4qkARJU1fJu8l28_UqOBZaxeCRhBTIOXPMoFXOOWcWUibnOfPxKC6UPEa7k4-oFKeMhDkzxySkRGLOmHMiKYl_cNlKbZAwRo9EujA55eSi0JQZGAAxk9LBWmUMMJMUzAAEAJxjQiaQlCITIoofvALMCVCCAOCjQyAjIQGhEhxjBiZxRBYJlMgAxEBSAED0wTRNDAERETORgBSBjqMHEQALOMJMgYEIMwo_7kRRkxDZeyLizChQz5rkHRAzkhCqqKqxG2NiMyullGPbO7uHmJL3kGwCiEwkyVSzEELKmaREIRAgxkiIJCn6SIKk0jnnGKwsDBxd36oAZk4JEgMJBjxi4FMIwCwEEsnjN4WocgRR_aIsLBL7aXApppiU1t66HKMqjCAZQxJS5RhAmwigm1kMjpFySihFDJmkJq1BEmQQJDjH7FwMySxmnDJnllpHn4XAH7CVWh3L4BwZCTIzpFTOVsk7qZVURhAxZyQ0RUXAQKyKqlguvA-oEJiVltF7RkIhgdF7n0L-_6u_Ky20AcLgvRAQfAAgc_FjCJMs9LE0khmF0dM07m-uA-fF-dPAYer7aF1itl0bfDCVnPo-ZRRGVotTIoreuxCZkyz0cGh1VREBZhJC5BSEEPlgFxdPYhxsNwpF2TobbHAWvKMY3NQDkeAUrZNkgEL0bmp3whQhsFJlM18M2wcyioRQhYnBZ87DvlNNJYWWmu7f7U-vrkAIIr08u5ifzPt-iH5CouEwLFan8-Z07HYIwNFXi9Ww2_nRm6rQWoYYEsScKTMsTy5DDIXWTLS5vRGIymhTz6ahz5C1kJiBg4fko_dFMWPMOSVnJyGU0IY5sWBKUUg9Do-6qolA6iKnWM2XMcaxG6iQkKMum6HtgEgXJSILJcIUTHNCKaaYOAUiiLblmIQsBAklq-CDLhXpIgOYcs7Jc4xHooFuKjpO2kjeR2DQZQ0MghTkyMl6a7NE05xJOQvTxAyoFSNyShwjcE45csqIHF0AyaauhRA5sbdeaKWMiiGSFCmmFDMQokTnRmBAIQhIKiGEqJuqms988NFzJjyK1WPwwWalMiqOOfnIUwq97aqyuLxcLXX90WdXn3x6FX0057P-4HftIYSQgn3z5vbr76-7blqvi6uTs83dfnRhtCFYyxwLLSPiOLq6rkMIPqOb4ruHh5P54mS9EhLeXT82s3J92gDjajG73bTzZvHu4V4L1U5RKf3LH10QUgFUVFoizhazelboosAMi0UFOTPzejZ7crXu234-ry5W88oYwVkKFVN63OwDMwpCQdooQkwpIaCPeXS-70cbAUl4l6QQ3ofMUFRlyLg_9H_5N1_2MfY-_fXfff3m_d3__f_4bySZzvrv7jb_w1_-9qs3D9spdbs-Ibih996mKUyTa2pzsl7njP0wfP369sefX3x3vemsb9uhs9MnH334l3_7xTi5y_WqKMz3r9_99__Tn4vC_O3vvju9uGDkfTfakFxIq8VsnILW8nazacrCx_zf_Vc_f_mu6_vxsR2q0iDi5KIk0cc82uBiHoOLLoWUE9Do7aH3_eBiTumHx0WIISnibnKcWaKYvFdCaqWzFK3zwUXr7GRtWRZFpUAQAyijAuFqUQfOOeB6PTsGGIxRfT-07ahrZYTY9NOiqg5dLxBc8Nu2PVssikou6-rV9X2IgYGUlOfrxWIxq4titVrc7w-a5OXp6mS19D4pXTR1KSBzzsiQYrbOh4zv7u45R-cmpTQhZcy1NsfVRttPhCKGaKdIQAlEs1wLRO-skaI2Riisy0JKffO4edjtz06WZVUWhcRC3e276_v7afLRBUTa7dv5cvkfX_4_njc_CiHVi9lcU2lEyiCYnlyeSaO7GN49tNvAv_ry7V998-7-ML4-HL6-vv6Hb9_-5ts3N5vtl9_dvrt_2E7dz3_y7E_-01dxCv3gbHD9aLNLH_3o7GpR3u73-2Hyo3147BPi7m6PSk2TK5T5p3_w9NuXj5roZgr_8pfPvn798LgfP3p62iwaIaULbupHpeTJrP7s6emTuprXplKSEEFQN7m_-urLk8V8u5ve3O0WTV0YMdj0zd2utW5_sAfn98PAhDcPG6GkS7nv-sD-oydPn56udGESwKOzm97ebg8ZYLLO-7Rve58gRi-NXM-b4NJiVk7WuRjf3zy4GF2Cbds9ubr8m1_99puX7_7877983O_Lury7v2cm4Hx3fS10OY29rLTvh_l8FeyYYwaSVOmuH0nGv_7zv__u7f31_vCrm-3f_enX33x3t9v3tw-PN293HlBoGV30wClniJgBE_JiuZx9tCKBYXDaiHa3m_pRVaVQhEIF6zNESB44N2eLcRghQzGvgvfjOJh5zSjG3g7TJLXe7Kbf_4Nfvnn1bgpO1-VvXt2lnLMAF-z19Y1U6mTVPJk1L67Ort8_lkp3wzRYy4yFVnVdGWm8tyer5dOz9c3t20-ff6Aktfsu5Hhxdvrt9y-ZMXqvCbRQEEOOse2cY3ps98HakdOuHdbreT-MdV0umurXX_z2sw-epZDX81oZI0h2wwAopJT3mwMAxpRBQEyJMzgf7OT2bS-kUkq-u3kAIKFEYm4W1Zv3d0Kbu83uZD7vR_fudvejT55uDmPwTgphiqof-2Uz_9Vvv9WS3l3fO59-9-0rU2prw2K5kkb03WSdtcEVukACrfR46Ieu70fb7_b73fDk7HR3sLYfnn347OvfvlpdXEUf3r1_d3376COXs0WK2I0WUMwX87bdhCEYUz3_5DJPQeTywjSlmc8js9aiMBKASBspdfQpx1RUBYGwoxOlItKcsxACAUggCkl4DHszCcnHwzoDJ0bIKAQqnaxDyAzsxsmUVRynoT8UzUIIRYKidxCzqUtgQMGCZM6JhBBSESIc770zIDNJQoSUwpHrQlIIqVJ0JKXUGjgl7zlnBEgx5ZyLqiGhIHEKloQw9SxGp4qSOQcXkFEIAmYEFkohUkr8jx-KkEkaHX3EH8TCCZGYgEhyikQ_HKY5ZkAEIZg5p0xCALAoDCY-MvSRmZBZaRAyxUA58zFfRMeIECARCZGZOYFQGgQhIsmChPjBhCUQc8oE2Yfq5GTad8zIOZLUKChFQJAhcPSWJyeV9N0e_AGlUbrKFJihnK90UVfr8-QjMKCgFL3URZic0jqGIHSZcso-oFAIlKM_ri-ICCATEANkzEKqnDMcM1GcU8wSM2Ji-x4gk6pTjskl0mSKqpgt_WTDYIU2kHKCjKQT5aKaWWcXZxfB-cwopJBaphyRKEfgFAkVAyBkBI7jhCgRCRGJRHKOhCSUKSYkQYgoRE5RKcUA2U2mrsfDLidWVaVNOe53MUycIDiHUilRMII_9CiE1qZZLP3Y66LKKeuqzIzBjcroFNKRhhRCAMTECCCKpsrZw7SLboouVuumurqw3ai0nq1X2fWxG3s7LJ8-pUjVrNCqQEE5xBwzKlFKFZOTxphmJppTIJOTl1KjVsTAMRaLlSrL7vEh-ylGC5yL5jSFHokBWGlK3uXgyqZBRD9a4GiKMrkhtm0YR10a78ZCm35_N7s8LeezRBCHkLwrq5JzntpOqOIw2NXJRdtuoh_3-4NQWhr97MOL2WJ1e7sRgMnHnHzKThUKfJDK-GlsVqvorB3t6fOroqj3u71AZqCyNqXWplrsHu-lhKJQ-4ddjolI5MlGb4HB6IJTJIExOiJR1kshxXBohZZl3UitQ_CcEZEROcWUgyMhvAuLiwuhyA2Tm6bMaXZ6zin6cUAiCCmFEIeOCiF_2OCxMVWMSUsdYpBa66oMAX5wfUhEQl3NgFBowz4wEoAgpYSQ2VlO0YeAJHS54JyYI1tnfS-MLhYzqlaQIHMkFMpIRLJTVJUkqYIPOeSYUuaktFFaIhGhKJsCCb2Npqxs23OOJEUKXqmjsw-QMIVoqiJnJolKgi5kWS-NxBBzGqOSAhHHwzgehm7XHdrx9eu3b68f3ry5vrnZAvDd7WNhhAcYYzw9XS_W8-dPTrTSYQwP3aFclgmlMaIfhm_ebEgQZ9DaPO52IWQ7uVlRvn2zff78_HF_WM_nq-X8y1dvAPFiOZumGKOXWlrrAvNi3pyvawgsRUWVjAIXs8XkbAG0afsCECkVUlOIp001K8ysNqermVGSYxAkfYzBB2kEAY2T84mrshgGZ4xixGlyzsfRetIKCIgACW0IKcGh61iKr75599jZBPjyzZvdYJ_NF__sD396v-m_ePnyv_-Tv7zb2QFEzMCMtp-IqT0cjFSHrr84PxVCfPndyz_71Vdjin__9fs31w-9syHnzvryZP7V777__Z9-9tPPPt7v2tfvH__-9ZvFcv3YdcMYqnkjkbSAX3_5pij0fpgygPNxcsH6_MX3dyeN_urbmwjp0E85MSoxRd4euoT0uNlPowspK6UH64jkODlAjCkxidH6yQVE2nZDI7VNgRFjzgjIDCGFKcWcYnCeA3aTM6VSyhwLCVoQxCSBFrN6mOyhs52bIHP0TilNQsSUq9o47-7vdyRZkdJS5wCj84x0fnqCgJkTItWFsS40pRZExohZVZRG9_0YY2JOfdvHGF1IRaGUMVVdTIM9PVmuF6VUxsf0btvtJ2ukGaaQYlovl4TQDeH9Zvf948O8qutGF4VJzECYGK33NqXRegJRlvVu372-e9xMU045E37w7IkxJInOzs8LLXa77rOznzdVVdb1mMLg49vru5OT-T-8evvtzXUszde3d-8P7T98-_YffvMaZvox2lGm-4fd_cPufrtnyJvDfhr9vo2vN8NiKWyI0sj9xrqcR-L319v7oRt6u9n3AHC7nz48nUHkAGxDWC0XNME4OFkVv__xE2RxsW6unizt4G5vdsumkczLusIYf__HH51WZlYIAUkSglQh5QCwrksXYdf7XX_49Nll9Knz09989Z4BDpPvRj-MY1EW210_n52YQhqAYfD_q5-9wJA3--56195shtZOmcTjZm-q2oZwdb5az_T1zfb99fb5p0-H7Zhzuns4_NWvv6zr-qEdDt24WMybeYVUzuelB0icWYhu1336T36yub-fRuvdhEoO-1ZJE0YX3XQ0YkZd5xy9DcEGOwyPNw9237txzCKFGKSQyiiSMgImSWpduxjtlIfRCl3Iud7fPE6HMUYbfPIxCCOZY3CRSu2s9dbbzvqUhDK6qaP1nBmFYGQ7TCQgM_sYx9GaefGbv_1CQLzdtbswlc1svz_0k22aIkROEL97ezMviwjw5PKkHeyimt3cbxTlRVUbJaZxWMwbymGw_UfPn3JOQCiFnFz45tW7EPNmf1jOls8-uFguq1ev31w-OfEsfvf6TdDy5rEThTZGbx4fzlYLDTDYeHW5IhJSyMHHolDW--DiZnforS2rQmsx9K4bbAppdTK7ef8IgNW83ndDzByRXYiz-eLm7lFqdX5xvt-2D7sDAg3T8PzDq64dur4ry-q4rQfM1w_b0U02-uV6pZQ4Oz-NIQ3W9n3nAw_OBZsnZ8u62Tw-9sNQz2bj6DkEoWG-qC6ert-_eVxerr_55u2T5xdf_N2vb9_e-phQyacfPH__7l2KSWgyRqTgPnzxkTHVR5-8-N_98WfjbiticTK0fTNbi1LbYXCjyxmZs9KSk_QpkRCIYvHksjt0nLMk5AQpppRRaYNS5JxRUg5ZCMGMKFCQyDnnEGRhCChj5pQZgAjqxdI7l5JtlvOckAkyZxCUY8qJOQMgZx-FkgAUfQCRBUlEyCEiEqecOR3xO1JrFDJaD5hzZCIBxNlHIkJNbpp0UZXVPANObhQEgGIaelU2JChGjwIEyZSOdH9BCCRFDj9cz3NKyujovRAEhMBEACgFAzBnRIFAKEXOLLVCYEQQ8MPxGKTmnJEZmYFzil6aigRySkSEnImOnzcjSUAAzghAQgLnYxXhHzFHjMyyrIg5J47OmdlMHJHkGUgpqZQuDFB0basVJDdCCilBDpHDmDlDyrooGRAASemcsi5L7yMgo5QQPBOkmKvFec6Ojs1chCMT6YhpTzEgERlDJGRZReuYmBCElJwzJkDk4EJMSSnTLNcQUrvdSl2YqkwcYnCqLISQPgQ4SsJQTKNbPfsAIKWUMEZJKmcuqjIzq0IlF45WCM4_gJpySLIoGBilQGBSinPOKaToEYRQmjP7yQoCU83coWWQpJUuCne4F7qURucUVWVMUdbnJ26cvPWcLCZw3qOknHLR1JlTStlUJQJk5mqxzJya5ZIJxkMvUQBDUZWK-PA4LS7m5elye7tDqRGkqSvXD1PbnXz84ua7l370qtLGmAwxtF22LrqQhgEQdNUUdVXUdWIO1s_OnwOlbj-QUlorO7RFYbJPxclp-3jPwLoshNSJmZOHGM3sjLTwkxVKZGu1KpKb_DABIoSQUzjcPs6WT6Q08_lcKe1jDjmTMkIQJ1_MjCkKBnr64ccff_bJYlFLUplZ10136IHD8YcJOTFnAtBVmb0__eijqTvs7w_z89MnH724f38ry4JIFmWz292PbU_AEoWull3Xrc5PipOVH9tjJTelBEf9H0FwExEVs9mRtZsSZ0HHoF1KSRbGlOV0OEiiaRyKujHVTGqTnRvbgykrbQrvnS4LAgZmSFkVJSJIoTPnxMw5YE4cs6lqoaTWYuoHBmAkZkQppBBSqxQyCsoJc2IqJCKQFIxIRIxCqjLlkGOC6AUCoTBaMQsGTikBHcmxyk1WFQVzRMJjoMWH4BPX84UUsu-HlJI20iyKoqggQ3IpOI-Yx76LMZrCADDkPJs1iXmytpDC-rC6XFSNTlF0-zhbLZrZ3I6uMJRcjCEwpMlN_TA-tKNA6B7212-vB2sP7XR79zh0fVNoa9PZrNl1Xbfv6qISIswWVT_4s-Xs7fXDvDaf_uhZO40n82a9qCHkH3_6_NC586p68cEFSaO0zgzbQ8sRmsI8OV31g3_57tHndLPZnK-W42FoR48xvXr3_icvPpDMp6fLzz969uGTM0G8mDcpREh5csFZW5SlVNK5MFpXFGa1muWYZ43JjO9urkMiVCozC4EpxZz45fvHetbsUzjsxqefXvzp33xfz-qXtw8hgarK_8O_-qOTuvizL75_e789TKmdghSkqiJ6H_qBU9aFMJUMOc8Xy123f7jdJeTR-ph4t93u9u04eefit9-92-7a9elqWVXD4FVdj87fbvaC5K4bIojrh8fvX94XRpWquN33MSMCG20E8O39_mazP79al2X5uNlFhn6c9rseiOxkCdGUJsZsg5_V9f3jFiNMo8shuuBLTSGz89mlOE2emQ_doJRm5sQxxNz1oSkkGq1QpJiEFikzEQrIErEpy_m8PD8_qYxK3jVFIYBASJSqmTeb_bBpB9uNRtDtdlRSzmbFoqn2-34crTLSlMU0WmOMFEjAVWFKZewYTpZzKQSBKAshARXJ5bKpq8poZUoZJvfYjVmKvo-3u9bFuKzqWVlyBu9D5oyEk_NPrk7OT-ZP5iupZErJhRBySoxHj7tLefSptzam1NpOk5m8lyFgzqWUHNO8KTOzUUKUupDyzf0hxXDXdm3Xhwy__ur1l682X7-7PVj38v37rp1GN9lxLFb1lMP77x7a3SGmNHXe-9CcLG3fCym1ZDeE3rrFqopTIkmjt0Uhc4a-na73u_m8nLqgSrmoG0hpPq9-8YsPhtav5svnL2a399OTZkZaKjSHtlufzIeuLY358QfPfvrpk1UhSyGm6HvvCyGHyfYuZa3adrretaqUkvPZetFup3ebLRi5O0yo9f12W1V1P_a6nKUc5otZBv8vf_pxqaQk-v7u4a4dt6OThSIh5qtZ1002eib6zZfXICjEMNqwnDckZaN1UxYPh26xnr1_2By64YOrZ2TE0_PFpx88_Yu__fJxs_cxUaWS9fVqaacBAHVTQc5x6Dkjuw7AkKbExAolESntQrQ-m0Vtaul9ziDkRW337bDrrY0wl513bgyyhPu319vrB-d8jBFRu3HUWobBCcYcUpxs8pGAyqpaXZ2O-3Z-MovdVC0qa20YHcccA-cM0-CYhB1Gih5RlE35-vstkTek9v3oIvgMb1_fSYV__fdfn52vLk7Plqvm8nT-04-uzpezk6pIKT09O3m2KLxPq-VSSwwILHU32FfvN6-u7wqtQ04fPX3SHvbzskIpXOK___rN_aELrA6Hbt_1tw-77968-ebVO1NWT56evbvfL5salMopvrvdvL178D4IYxJjN05Gm95amaEszawpQsSqqt68vhYobAwpszKmHwaBRKTu7nebQ6cVrlerw74vtbl7PJycLEfvpim0_ZBJ7nbdZO16tSyMLlRpJ2edk1J140SIgCAYmdA5F7LbH9pxmGIMrNBnfvlm43o3jqMbnfPh_vr9sOt98Cenq2ny_W63WMwYcHk6_-2vvjm9evLRi6d1U1Dwf_4f_uz9uwcB5QKSGw8tIp19_svEMQydzMnntL54loJ1LsQMpqyevPj88fVbU1cc4rF_G2PQRmWGnBIACCEQMcYkBAkpY_AQIgrBKHOOFGNmOCbIwbvu4VE1TTk_tdZBTjklKWWKIIUizCkkWRVUmHzc3Weg44yhCDETgBIypQgIgJijB8w5RVIGEZFznibOOTgnyoqUIpRu6ExdIRKnYKoGGXIChCSl5MTAwDnjkXSUEnOSZZETk1SJGTKTFEexK-kC85E2mYH5hxN8xn9MHnPKTFIf4UUk5bFJDEQIMjNwikSCAUgogET_S20AMXkviAAg5UgAQmtgyCFyjigIvAcgIMkMJA2RIGZmMHXtp1EItH2XvVdlQQKZsyBQBOy96w5lPfPRFuWSlJzsVNYzKQ0RpcQCEAhSHJGPEqVakMz8A04TgEhQjkEwRAYkFP9LRyIzJs4MyECEiJBDSDFoU8UYhCRmgVIhkW0PWUhtdH12gUoIIU1VxeAjcBim6BylgCiCt9IU4zCY-YyUyhlQiMxZICmj4mjJmOPiJeXEiYkkSVnUCwAWAo-sJKGUKHXynnNKKatyEX0k5ByD7QZdlchEuvB9h4QAOfucYqjmi-itrisG8pOFHLXRQ9eqssSy1kW5ODsb9wfOOYZEDDGkcTv6MehCuGESUlnrdd3U89Xd61fFrA59G9repby4eFIvV8kNhZJsxzD0wfYRc7W4MmWDVTVuN_OrpxwiEs4uL_uHR3H88ZcqZs5DpzjllERR8TiqlGIO0tS6rIAjAgXni6rknAUiJIeQBadue-2HYXBTc3I6v7ooV6vt3VZINKb0Q_7sn_4X33_1D-1h__hw18wWdVVKKRFYKXN43KOAoq73N7c5wzQNZVWbqu4Om9XVM2LY7_rZat4sznZ3u8unl_vHBzeOlHOO0Ufr-oEQu7YdN9tqsU4hMCdEzEBCyZQCBO-900YJKTNnUjrGlFJaPn0SjopiF0zZCEE5BDsNzo4CYHn6TIDUpZayPHaLgUkIIQj8NEHOqI33QdVzjolIcU5-8uVirrVWpiIp3OiAoChmibNSWhYNaiWkFKUEQO8CB8AQU_ZESFKSLkzZpGAhhcxs7ajLRkoxP7vY3B_KUhdFnVIkwRkkAQFQDBEIhZTAyY4OpNRCFVUpSUUfETi6gAL9NJEgAozOSym0Ka0bAcla11R15BgYvU9FbRbreb9rQ7QXlxcSqapKjsl2TgDKSi-LGnN49vGTjz94tm7KxcIYqYlIKt11w6Hr7663Ra0BgTFb54fRD5MDostnZ0ap719e_zf_4o9--_X32fv9MNRGay2qolJSZISb67u7zaa30_1mM4WcRS60iCll53Pk88uT9Ulzvp4pps8_ehYjf_bBk3ljjKRCqqLQOWGIQQqBRIA4jhOTUFLMZ02KLIhcCI-7bvQZkDLibFFjzv_5i2_mdVWWZRfCV68fHm73j3389vXD28fHKESIWevqycnJ-5v7_89f_t3dtptdfepdexjGabMfH9pjn9jHVFTNycny5cs3b17fmMKcXj59-e6NDUlqc9gfUkoZmbScNXXb2--v7xez-fuH3e2uVXW5249924cYt5tDtZodJnv546ejjffb9nE3xBC7bpoiv93shFLd6FCSIElKjJMFKQFlTOBjyow3d7vEuR2motAZQEgZUQQXk4-HfpRSAuUpeF0Yb52SwoWQSWoEYiaSPgQh2Y4OSACBlnI2m_3i9z477O2iqUhwJfX9fpc0rZfzF89Xfop932rmmGG1Xj7_4Ko0qtRysq40ijkLQQB5NWu0krv94WQ2q5rK2TCfVSGm5GMC8Na_e9xnQkGotXYhHB63399uBQnO-f3dw69vd5eL2WEYOzs1VYGAUoq-s3dtJ4VwPmVgFJii_-b2PifSUj08Ht7cPZysz3fDMAydALaZf_7i-dPT9el8Ma_r43XYONmhHd_vO60VkDCSbvbtX3_z5euHzev7zavtJtXi7Zs3797dI9BwmKyNnGi_77rbQx4nP3kAoVDNFwaQqnIhVM6QYog9xKnzVSMBcuhcOVftGEjD6awJUyqM-PDji2Ktfvvq_hefPVufnMXRnzxdvXu7HXbd86enhFAIfXfz-Dh0v_zxJx-crypFeezmTZ1yuj30q6qImff7Xhjz0B5u7h5MUQklX91tPvvo6mHTqVL85XfvZoums04pUZa6KVUOlqQ4XZg__PSjZVn07WHfTTfd4LPuQ7zbHqTRg7W7fjy9XAUbhsmFHLuu37WdKsvX17cBoLfucXt47O3qdPn-7a2fwpv3D98_PvyHv_ib3tkQgx3t3Zv34zgc2sPJ5dPd7V2OyW4OsqpSjCSLFL5V1bOUHGgMIYWcc-YcIsjcbyewEyqeDhMvBMxqN9qp9-5gp0MLmTHLelbkkJNLSJQnn3JuLk5IUTVbgUJg4piRRA6eBI67Hec0HIb50w-ErGVlSFGOuaxLYSg757reQRaFOjur212fUyAAqMhZj5Bur-99TKYq_uNXX7f7YXfYn61Wu8H2MWmjdvv9q37_4xdXzgefckzid6_f397vQcskuO-7Qqrf-9EzIhx7i1od3PAf_udfo6QpBJ_y5ANyfvrkVJE0VfG7766NUGDw3fXDvh9KVUilQsw-ZSHkfhhTiJPzp4tGaRNDLKtyGO1sNksZd4e2qOsY4PZ-t9t1RamLwnjrrIvRJ1LSVHqw083t9mHXjnZCoof7zWq9HkarpBqG6e3NvYuBhFjMZynA_tB9-_p1M6sY8nI9f7jbLFeLEB1IfPf2YRqmZWlMoZ5_9twG2223QJABBOHVs2dju88ZMkdBmHJeLZqPPv6gKujjdfXXf_MPSOLHn38oQDfSKEUQfdffvV2cXp6cPTlsH7x143D4-Ge_UMI4axcnZ8IoF6YcYllWIfmcAgmRfZBaCyEyHHF9fLSJcQhIkpBzTFQYJWXKTqDgdFReJdKUgiXEanEqtJycJQQ9K_MP0YuMRERS6gIgJ584ZVICGCAxHJHkmVNigKzLMoUAxJCZmbXRJLUQRApt1wqty3qeU3LTUDfzFH0MoZotpBDeThkZ-Ggd5pRYSEIkZuAYUerjQuIYiESByACIJGXOCRnwyOvMIKTMKXJmJALOnI5X-AwpS6E4Z8iJtEJEJOCUUSrOgVBkH4CZpAI4moiyQCAhUuacmJSUSgXrifDIJwVgkEfXr0Hk5EO5bFKIgDxttkpTttbMZil4yJhjgpiAU3C9dz4klzPoakaEi5Nz52yMwRQlEpAgbUwIPnOWQpI4pn2yMkVKSUrJmDhEICGURpSAnH1gZmEUAXBmTOlYjyZjpDTT4VEUDQmSRgEpkoIh-2niiKuLTyB7lKqoGz-OUkvKwCkGF4TSKCSggMykDeScYsCjT5dAKU1SgRD_iGQ9yieQU65m58whh4iISCS1Yc4oBfMPHFelZIwpWgtaIKGZ1cF6ACyqOqcQxomKihkgMyISEgMLrVLwRVW43kLOQOj6iQQyISCbWnIK0SV9cUHRCaHIqBjc7PzM9V0xX3JOzIiYoosZ8nEOJMyScrB2aA-6VNIUZbNs9_cCpVJy2h3MvAr9EAX50Tcnp2FsMUROlBPXizPX7gBlSqCXZ27YJQBUWioFhNIIZBw7i4gEQonkp37qR63UbH2ipJifnOhCj1O3vX9zenpph0MO7t3L--Z8VtVzO9j5cjU7OX-4vXPjWJSGmFES55i8S1lY55dXT40x1-8fEeSHP_kMcg7eEdDJxUXfDrqsilkZM-eQdFMCp3J9AgSJWZcGMkslESnHmGLMIWbOcKwHMSPBfHXKjNKYHGPwEaX0w14LiQR9uyEpUnR1PUOl_Gil1N4FRkjJA1JMTpRlymCaWjfzHD2KlLyfhuCDU9oAg2D2dkJBUiqSpMvqBzEw0xFYjKRcsMpooQRIqUgzKO9TCpYJObhpsES8PFvmRDmHoqqtS83qZLLTsUSkjFFKI6AsTUpRaUNE_W6bfEJCZYoU4pGRaqrKOZtiij6Ng0scjJY3dzflbEYMy_UixiiAqkKfXlzuN48owA5BadUsGs6h3Xf3D69LPbt_PDjn3m9aVJXQ-tn5mYAkJNWz6uxyiRyczY8P48XT0ydn6-iTD5EYDu2wqme7du_tuDpZbXb7k3k9b5pumF6-u9ntDpDyZz_6VGt597jXUqTM52enQgnnA-dcaNPv-xzTxx9efnB5umqq56eNEUILYbSSUuSYCqMB0PngfHrY7lfLmVaGMwQXQKANKXI2RdF1w-XF2TBMdw87I2m5XGYp_8Of_203uOvNcJjCYez7Pnz1_RtVyk8_--T2sfv7b7_vuvFmN_72q2-wVtffv4-9JWSBJKXxPgijAGV7aGMIqiigwKFzDNi2w9gNUoiY0KX02ScvttvDu7c3qiweDoftZhc55RR32_3N-4cIdH292e2716-uqTQPm23bDoL06IIuTeI4TFbrapwmEpgy25CU1p5TDPnQ9oeuM0YbIwbvbXBS6m6cAoOFPE2TFDh5b60zRdV3Y1MV0-SE0kJwnKKSnEIMgFenZy6k6KOUBDlfnS66_eHZk3XIaa71rDSr5bI25cfPz4a9ywkOgz1ZlU1dny4WZSHdYH0O4-Qzc1HpEAInZsR-HOuqysxKCmOMDy7mjIQgKKVYGcVMUqmQ4umybK1jEM6HutQ2xX_x-YuqKmdFSYlJEAkxRS8kHdo-pkxKMsi7Q3vfjglkQjWF9BdffJliijEM3fCTD55cna6uVisGdCEEgMGnjXVvNu23m4cR3H_64u_f3mzvhvGdiH_2xVfXd7thijcPW-vj5q5jgWCUkUVTa3lWJReiD1VTNKuqXM-bi_r8g7NSpIeb9vTZymM2Vfl22wKCkFmCqpbi7OLMtvF8UXT33eLD2axp0ENViFevHj6YNU_OTwuUHGGa7GT7QukXFyfv77dFQTHnD59eGhTeu9qoRTU3RmHKJ-taCTGOlpS-2ew3-97ZuD0cGPDZ2eJsWcYpiVpOYxyty5w00d1mX6rym_fTP_vxsz_88PKkKjkGl5IH7kK-3XVfXt8tZrW3KeakdTnF_PL9XWJuh-Fx3-mqeLjddJ293RzqdRMZ391shBDXd5v11dKR__rLt_0U72639bzykwvTCMjjMPaHfUoheydMAYQpRiGFjyuKnDlgZhICjSQlMrJ3kVKUzkUHPmNE8tG5iIly8B5TmA4jp6wkORekKWIMSirOEEbPjGM_OB9cNyitYwwxR2BkyK4bckoxjCRTlpRjLFfLME12nIILRFJqFadEqnry7Fm3eyyN3jzuQ4ST9bxuyrGbppi6N7vddncYws22v37o7u62UuS__Ivfns2Ws6ZGrbaT_R_-_Z9PPmz6rutHktIHe3l6drpeVGWlFN28u_3LL152Nnhm01Qu5soYzBJJtD4O3VjPivuH7d__7n3VmHGwu76zIQz9-Lht7WRjTsYooZQPsR29TeBDdM4fum7fdcVicWj7x82eGKbgf_75R2-vH758-ebq_HR9unYuxASvX91Ws6LSWgmphLi4uji0B2WU965t-1lTCZQkaH84iEJ4ZwmEFrjfD85OdV1tN-3p4nS3H1az-uJ8XVXVrK6H3fjwfutCWJ6uldCf_eEfjo93VVlO3s0Xs74fxmF88fzJ82eXyfmbx92U8o8-fe67TlBzknwmIgRGSHZ_yDmvnj4PbZec2-_v5stL23cphdXFk2kc_TjEECSplKJUAlJmZkQUUqcYAVloicyEeGTYI6JQOmcQqsg5AmdEQiliCJCyj06aGsiosoacIEZSOqdEUibn6dj79FnOauCcnBdSAAPneKyE4hHXI1BInWNgzkSUYhSmzCEgAAmK1mcAXdSQIMepXp5G50KcytkagENKkDOkLJSGDJkzEB7fmHwgpY6wIMhZSAGJUSADHD9yZoacSQrO8I_gS0RkAkAlIB0v0vE4XWRm0gWiYODj9wBIICmHKASCkMzMwIIEEyIDaX1cIAAeIw8JiThmVEXmkENMgpCZvWdC27W6NHHoc47BTkeZL_DxEK-jj0hYSKkLA5ynyQJmocoQg5sGSIlIFbMVh8AAOSehC6nLlNPxnjIzJO9REKaUYgQkRKK6RAJ2SUjBgjhGAE4-MjCSRmG8m6qmyYmr1UmOCRDZ-RQD45AZgZSzVheVnUahNadsmgqZhZDAzHyckViXJRpFxpiydnYK45Q5ww-9ZMEIOWdGjMmjEACAKYcQU0pFNQdCJkrRASPkKBSiJD8GWRSEgoSKLnCK0mihFXPWRZ1TVEpIU_aHPcfIjGPbrc-fxOBNVTJwtA4FHg3NaXKZM2-34dBlJDWbu7FTWpTNfNgfLp89M9qk4Gar1di3dnCck5SCpORojaBxsymbpm7mxXLu7bA6Xfd329XVc0UwDRYSI3BzdtXvtwgRY0qYRFmGqcOcdYW6MM5OKYSYc1FXwQaGhMCQj8_YiASr07PHm3f72wdOWUv56e_9LHPa73eSNDICA-apPewedruqrnyILPJsdjI6p8uZQFJKcogJWGhjmlUxa84__qgp665rT87XQ9ummMq6Ov4jYgpZqJTAFEppNW334zQIEsAQJlc0dXReaK20wZSP4-zUj81iTZjHbnLDJDXp0uTM_1gjqxgwWG-KQhUKMnWHR6NLZKwWtTLFESzDITEjApx_8qI_DCEkqaiZn6CQShopZb_flE1VlTWnSAVB5mEYiqoqmjoEP03TfLlCkglYawMopmEyUgcftDamakgLIRVClpJSjjlyiBEI_WiXF2fRDWU9J8J6vmbKafJI6MZBFcZNgw-TQszMwbs4-mMGCQnGoUeCHEJ0XhoSUrSb9qPPXhzu71KKt-9uYoSH2zuUyCl0-8P121spMQZvh8CEpqjqYuGdC5Nzo4WU28PB9sPt23e314_3u82r1zfnT0-zw8W8-fHPXrx9_eb7725dsk-fXw7deHa5fn5-9c133z67fKYMlUqeLeeSaN_2AkGQGJ3zISDIsjTffffm4-dX1nk3TJenZ1rJWWnYxScX66vVqhD5dF5pBE7ZaJFT4sQADBknG9pxlFqeny21Ut4HKSRJSpA3h9GF7BMjqfvH7WjDy3c3T59fhhzvt_3_89__bbmoX757HGwcnG3H_uZhX5VVdNObt9fff__GQ97tuin7w-19CI4AAGgKjkVGJagQXdfbccoAstTBhnF0PqSxtxx8cB6JVVk87na7zS6HdLfZWO93m91-39d1_cs__tlstbq7uX_95ppkHgebAbHRyQdr_eHQm8rUTeVcii5wysF7pZUdbQr58fGQc6qbQiq1WjRK6If7vdE6pATM7aEfJ2etB6DC6KI0PiQpZRitJJVzSinNFjUzhJgH65x3hFlLLAs9n1dnq8V6Nc8sxqFngARwsl5UhQSXR-svL5eny7oqq1IJ611TFIrE06vTuioloBEyp3y6XDDwoqmWpRE5I2Hg9P5uY71nEv0w_enL73VCUxQZaRyGQz8KEuuTs7NV09TlsjZVaaYxBExAABKtCw9du5-sgxQBBs8Pm8O-HV_fP2z3u_3Qt32bMv_isw9P6_mnV-dayZxpGN31ob9-2P7pV9_8p69f_-b7t98-Hv7uq-_ft13r8O3D5nbXfvu7N91kUZr99lFIFSMIKc6Wq59_9OLZxaKPo5_4sO9OV_NmtgwREtHM6O79duidmAlroyDKgQoj1k1dI7HIaWJIqT67SGP9f_nn_-pppSfvn3z0tNCSpP7Rx8-fPz9tCvXrr9-3_eij8yF_cHlKjFKJ9WzuUtptdmeL9WJRlVpN48hE3X583LYBcNP2b-43-37KIr94_gGl-OuXb2eqrKsyZbzd7DDzrNAyxo9Xq5-_uPx3v__x81WtJWlKu2k4dG43-Yvni1fv901Visyq1FOwOePtdjM5V9WlmhljTLNsyqLc3G2YubNeKPKDjePYhwwCv339JiK9ff2-XtRj1zGDNmVwVipFUhAQCIVCKF24flBSlM0C2QuAlCMjZKlJlwGyMI0-meX1nJaLHFLYOVZCGVXNqkQyg1z_9PTknz7ZvtyIpsgaUOhgAxSKhfTRghIp5fJkqZTAzITZeyeQRFmSgGQ9R46jJ8AUcopJCqXLUiuZvU3O-5R2283MqOAdM0_tIKRE4DDwv_y3_1QiV03108-v3ry5fbjblLXwMf_eTz_8yU-epwxvr2__5K9_PU1-34_b_c4U6rDdb--H__pf_KEhStZyYbaPh4e2Xz09Pztf3WzbnKO3U99142CHwwgKCCmM_vJsgYDb7eH1--3pet7Z9OLDi8nafrBPn109bLvJWp9TyLEbptv73TR5rs1-s0sAzDCMdrlcIOa7-22ttK6K1bq5v3tMMQKwkhKJorWqEHf3m5Q5cU6ZTVkSCT8571yKiSMXRgtJzPl0vXJuNFKiROetkDifNSGE5aLmELyfGHNRa11oQH5889JmqJrqj__wn63Xq91u-3s__wRDvLm--eDZhZDFf_nHf_CTnzz56ccfCGxOpDaZIaeASJC8H7sU8_mzT63tnE_jsFku1t2hC8FXdW2nURmlhGBmhESEyUVlDOcsjYohcD5ezVKOCZFAijj5Yt5wjBkykhCCAIQqqxwCSun9MJsvUvBSSRAiZ67Wa0xZFc243yAiSBEGq5QCqZJzKOiI5oTEDCyQUwJVGCEEECfrECnFILU-WmaklmGaUIiqKmII1o5lPR_73k-DqWoldUoJCHKMDFnI4y4gIwCSzDkTIhABQ05JGhNdYAASgo_GMkDIjFIcSYUAP0h1OQMKzDnl4wQgFfPRK4YMjJyOqjPIQFLkFCIAaQnxqFhAFvJ4ykUpATCnpEyRY0Clg7OkVALAY08YKDgvBPixgxSz65DEcc-QUpCmzImr9UlZ6e7hIfad79vsnRRS1cucUrNc5uBjjMn7-fnTaKcYHCAppYUqI-ScoypKEgIRc8oAiJBQEnsWVJLE5CLknIUkJRiBBIFCXTYxBqYstPbWCV2NbV80cyl46LsUY1HPg7cp2gSICBAjZM4ZUkjBOwCEmIXE4L1Q5thdBiAAlGWhtGQ-ilxZFjqlREpB5hx9yllKKZViYBJaaoME0docIqDkkHRZEuRMR89g4hBAkFKFG6fjyqZvByFgeXoVvC2aOjjnXJ9jykzN6SrlVK5XoCCOVhdl8pbBkwRZaoiBIQ2HfbU4EcRuHMzqBHNCQL1YpJgQOHqbQkwph3ESEtzYxuhVNX-828xm88OuZd8rkosnz6btxjTNOI7FyTIMnZLgXJKlKWZN9NO461VRN6vzEKdkQ06-Wp1OwyQLKQsNmVVVee-Hw0EIUsTZjeMwjH178ewjOwzbx8eTy4-Gw97bKYy9m0K5mC2vzpJzWtNqeYEy55jbzaFZzlAq0zTnV0-Cj8QglIAUqspsHh6NUAiYcoo5ppwBKTvnrc2JhSmFEQS4Or9MYWJOmRkQcgYGZGApBSL4aeTM66eXU7fnGMdpqtYzTtmFZOpKalMu12GaUohSCR-stRMzA6OqG2W0mc-Juaxnzk3u0D350U-qqhwnP42jVGq9vpJF1fW91OTHqVmuGHMGVS3Ww6ENky3qKiZmAOfDYrGw06TLwtqISggpC2NiCikfqzQQY-QUgSAGJwQiAhz_lZwYyU0DoQSJAFIrWVS1G23OCaViBFUZpRQp4aYJhWApdVEKo6QSmTmEMF-t_TiuVquiagTBOPYn5-vD_SbmfHKyunxyMRx2DLmstC6ld05KLOtifT6_eHqmtUIpqlL5Ycopa61n60pmKgrdnJ66zhpdVI1BkLt9t5jPvfd3DzeXJ-vbx8cnF2cC6PLsxGe_78b5omnHiZgBZdd3l6fLq8uT6_c3y8USUlyvZ1pAv-9-_rOPKonLuii08t5VhakKc3w-pBRJSp9yP05Sy6YwwBQDE1IEGF2YQuwnvz8M2pSD9SGG-21rdCE0PG76X_36-0Tp0IXICQmDC5cfXCXOtu2F0VNr_TSCkbt2dM5jcghIJHKmDMQEKDEyuMkLMtbl86cX24fNNPromUPUilKKAdGXszT7cKVhGNtpnBLlzf1GKJqdnB42Lid6_c2ruimKqpra8bBplZbbu93XX3395PmTaXQ25KrQyLnWarRusv5qdfKwbwmBhALERVViwu2mnc8b52NKbEfngidCYA42VGXhfYgpEqGSolEmA7gpc0iVkTbzOFqpldb6yJeezxY-JU9iVujS6Nt3j2ZRBZeUlIlhviwFECRQUsxm5WpWY85S683-ECY72fDB1enZellIXC3ruTFD7_7y7TuNwjnXlPV23zKylLoEkEJKU0DONvib-x2yXM3KwqAbrZTqfjekhG_vt_ftmJX0Lr26vidUbx43Sshx9I_7Q3to276tpPijn3z22cX5B2cnpZaYwm4cDuPwu7fX__OvX_7Dq-v7yXcxzs8XUfjNdtxtDo-PwzAlYHI-WBtyIECEnGtTnJ3UwWXS1B72d28e2s4jUCnli48vDkOHGmsB0HvnfIDkXUqQFcmyMOx9U2rWpmBzuqiNJD4cPv2geeweH7q2ni_iaIPjJxfLpx-c9Ad-c7vZ7A_PP7wQAp5fnJ6dzFeLOkZ4eHgYczydV5frpRLEOR8OXeRMQmYJj7v21fvHopmdnZ3UQtWV-vLL76_m84-enRLQ2PWkDEf3r__ol6dN9dnTi9KQJJ5GH4na5N7e94fBT8zfvNwmjSSlkPr2caul3uwPTVMvV2vI-XQ2x5Qxh_fvHwDy43bbOdv3bjlvfvnLz7756u13X70ZB948PM4ul7ffvM8pe44kgQUGF0Lg5mQuiqLrewQ2VeF8EIVEosiCUaBURb1kBCLAQmWlvHOuHbHQuNL184WqZ7vHQwCcVYVR2t-PLMiGrGcFlThNNhkxWa_nMz5GHXJkAdVpY6cJgKUxSFIvamb2KQnBDCBqc_H8ievtH__z33_39mZ1uvZu8nlCYAJhXRqHUWicDv1-O3ZuevNqQ1R0nfvq6-vbh93ZSTON01dfvf34g9N9G95db9vN7p_84U9eXT_8X__N_7ZPeg6QIP7-zz8mgmCnopr9v__kL6BqfvXF9-_vtm3vDtudG7qxtxxz3RQKOPosi_J8vU4Zd-3-5GR1cbF49mx9sphR4G-_fv3Z5y9evr3tu-7mYb_d7BjY27DdH8YQt9sOEKzzInNTVqvF8h9-_VXR1KMdP_nkw6-_eiVICi1SgrbrM0mUNPkUEzPiYdMXZWEKjYjGmGkapVKnV2e77d7asSgrYwwKNY4jKkWCTFmg1ErB_f1ja_0wTbIyAiQR7HcHU5fzxUIourl5u908fvzs8qc_-gyD-_jZxayUn334VOdYA-93e0HzC2bkkEBAcpMuagw-9t2he5xdPPXWgR1iSspUh83D1cc_FkLs9g8CUEnpxxEyEwKmhEpxziSI05F5j4SUOXOMUskco57Nw2SZWSAiEQIKITgFjH7qW63NfP00RGe9832nqoozV8uL7D0h6LqKzgKSkFIYzSEgAkNGYJKKMGcfjsXcDAAAmLMQkpmT98xeIGYfkBQgp5iFQFPPObMbe5KKgURhfsi1MwupUKocM0AWRCgEESJSSikfYURSpsjAQEoJOKZP8_GkzikyAuQMOYMxkBmBGZFRMCIwpxSkNjkyc4YjYrMsmRgR0zigMggCmZkzp4xK4Q97FUwxklAMiEoxIpEQAqIPuqly9Jx9GEYiUrrgmJBACIkEyY0MHN0EgFJJkpIAlBJ-GtzU6sqEEHUzp4zMMXhb1PPgHfgQ2ZuqNqay45Sck9IcbWKEDDEcg5speCApqwa0JlMCACFGH0gXRpnTFx9t3r3JnIlQCIlKTe0OVJEnC5ynbj9bLouy1lU9DUNRFscGsCkLqbVAwhgZxTH1xMx-HDhmkgJi5JSK2ZwZMmNz9RRi4MScOYUAiIgqM8eUhFScmYQSUunZQgrilDCn5IMbbVk3KM0PveTgVFUEHwlpfXZ1eLxHyrP1WfLj_ORk2O5yTlLq4TCikNna0Ft2IfkgiJWSJFQYxuiDkEKbwrVdGAbgaGSSAsdpYO-ZMyOaQod-yClwTgKZYxy6Xkp18fQpFVVljBunaRhBFGEakgtlM7fbHQlB2iBgciFZe9RQI_A0tFXdlLPGWUcSGBCFlqSlMSAJfCDMmDi5kDnWs1m7uXPezZan3WFru8Ps8irFUC_OTWHiNN1990aberfbNvPatuNHn_8sOLvdtLPFgkCrQo7dSAR1VevCzBZLqZTRWgAywNnTy26_Z06mKMvZgjlU85kAyDH6adDaIGO9uBz7_ZHAmVNOPhIBBCeEdF1Xl3Uxb8LU20Pv7UhCuGGI0etFLbUhVQol5k8-FpxjiIScgwOpxsMekFBgUWhAMFrPl09CyoIwOmeWVcI8X57sN_uiKtw4QMh2dDmOs1mFghgICIXWBBinSVWFlDQ7W0YXCSBYm6OFzJGTLnRZ1NGH485BGVNUVXTOOze2rdAl50ACY4zMII1BpLJqZKVBCDz-abxPIR5XojnEHLzve0JGhKmzWpEfp8lOfXswRldFZcdJkFBITbPc7dpmsUASHCOP2SfHQIdtnxL3-2F01g8uDq5cVJ_-8eftbR-sv7u9r8pKG3799t3t_f5Hn3_UzBsG9s6Ngz0_O3ncbD95_qEu6KMnZ8n56MPdbl8ZBcBaiNVybgScLpd1XT-9PJ_PinlZvvr-ze_95MWPXjzLLqyaer2cE6RZURSlzswxJDwCjjhb5wPk5aIEQDtFEhQY9ofexnC_Pex7r4qq7fr7zdZo_Sd_-dtnT1eIQhXmi29eJ6Gubx4nF3LiZz_-7OV3L93gAHi33_WHVmu1azvrvOtHCcyZvbfSUIyZBOpSu2kiqUcXzq7mdhynoZdGeTfpUhCizzHloDim3ftp6iJDUevHN7fZe6X1NNjHm8exGwACE1vvitNmvqyFC4_v7s7OLiYf6qLspolQjuNovdvc7VShtC47PwGzcz7EqKRsx8koHWLSimKMm92-qkzXToRIRMiQUhp6r6TyLpCABDlMwYWYCELmLMBa60ertUEg1499ZylnpYh9NKtGadUPtiilqdVX39xqKXLmpion631i59O2bed1hQznJ8uyUFWhhaCYYtv2u3E6b-pSq5PVMsScM4cESqv7_YFIdIduNi80ym7sTtfzUkgEEWJIIX3x-u6h25NRdVWNg3357lYRSKXKwkBMJ7Pq44urTz64_OyDZx9eXZLAwbrvbu--v7_9T7_77uvbx1fbw9uH_uD8xbPV67e3m5vt9fvNm-9uQ4izWZligAxIaAqtlQFIGmVdlqcnK6Xkw25rx3Ho-0LN69lZtTZXp6u-7cCH6MO0H7t-8MCrs5OT8wWGtGgKjdJIDUxPTte_fHFxdX5SFbKsMGX89ru33eQ3u7ZpmsV8Nh2GWVVud6OUMgRvJydkPq_nM6WDDfvB_o9ffPnv_ujns7KSgpxztw_7xbwho52P284-dr5PwYb08v317nBox6FU6vLy1AhRGnk4DG_e364WzenJfF6ZnCIAp5gjwhjzw6ZTdb3r-jHEfW9fv9uM1u37PiMIpWxIAISSvE9j72KKfTc8PvQ-umZZMdP_j6Y_W7bsytL0sDHG7Fa329O5H-_gDgSA6LOJzIzKIllFUiKNMopmutSFdKOnkl5BupOMZjRKYolVJRXJyszIjA4BIAA4vDvtblcz2zF0caJeYF_sZXvbXP_8_-979vzR06fnH25vuVJjiX70MaXjfZ8jKxTJMSR-_PwjP4TTJ-fVyaIQuqo67Hasya26ENMUQiEkbUxdMYkyBiBz4eA9i6hZbRcVIA7bMUWvl6ZeNhx9TilJYavZUI4sou3CFQbbVZxzitEoTYDTGFlRTtl75ocKNxc02hhNSpPWxrk4xLbpgkllKpvtbr7opjGULCmnbjHv971CjNFrq0IYhEvT2eub2-HYl5w-bHbCcn_frx_NlyeLf_U__V6UfPnNVQ9Unz9aaTXvzHre7n3sb_b_6u__ONeqPxz_-__u39Qns7Ztjofj3fWd0WYaJlAqiTCTdY5LHnbbt1dXAnx-frpaLDbb483N9u2bK6V1YZ6iPL5YP3p68fjJ2bd_fP32_aarjQBO3hMKKffpxx81lXt7fVU39ny9CqOfhmm1XtraIkPvRzRqt9uHKdzd7TknlGKN0tp5PxyOw-3N_cXpejZfbO_uK6evtsfHJ_O6MVpRibGtqtra9XIRx-HsZBbHuN_sT86WlbXOaOuMMK-XC-Q0DfGHLx__r_78zx5frFaNevnRo3VXL7pZiHE8jvNOXd8dlT15SsYKF0WIaLAAiBijpJTJj-vLF2k85pi7rrXN_ObD29Wjx1XVbq8_aGNLjKTxQVjIwgBERiFpZnjQ-iKhVkpYUi6lsGmq5CcgksJVO8spk9aSGbnkGIb9ve4aBNR1XWJwdQucqtks5czJsxCScGFAZSr30LkXIsgihMIZUHHO5IxkIWVKjMpYcgoEQRiJUphs0yhN03DUSllbK1PlHLRTSFRSVob0w7yPkLTmIsz80JVQdQUAwgyAnAspDUSAf-r4ICKCQq1YGOSBBwqcClr7p22xImWtMlYIgYvtmhQjKQSFUASV1nVXYkSFUjI5B1oLFwbIU690VfxERDkFIEVItpmRc-GwV0aDcDtfcC7MrKjIn-QGzCUrrUARMEhhAFHGjX2vSKGwUarEKYz7ME66ruu2FeYiQkohaVu7OI6gtalbUy8EgTkgADNrpbkwF5GUmAApAxQupTBb27puYRoXxjFMXtdVpTQSTPsDEGnrTNuEsbdNh6VIZj8dU4rMQqjq1XkM3mgDwkBYchJUIuDaTgCy985ZskbXjXI6Fcm56NkJUUnDaJouhYwKOBckMlUDpEgBkgIRlocvI5E8YIcKKXw4guq27VZnxjkRKCV3i7kI5zhaV01jX2JIRQhNU7fD7phyVE7VbePDVLgYa-u2RgAuol3dLC605FIgeA8KtaY8-uF-M2w2_vpD8EEp1IKYk9JGOBOBVmjrLnnPHA6b7fzstIRcz5f7fgRkspBijIeNtkRamdPltBmUIU45l2zqyjjHhcfRi9D85bOUkkYz9j2UgopKSLPTtQJhLsppKRD9BCx-6O2srnQ9jV6z064aDkNTd0bbJz_9wbi5--aLb1ztZieLq7c3y7P5Jz_9y_12LwT7fV_PuyLc1jPUACiK1HA4HA-HGPI4jaghhyCgVe2UMKdoqioMU8rCzAUwx6CtCT4pq0gbXTsookhrpUEKKOWP06y71I7T5BFLO2slh3F7KKV0F2fAkg6HbnWqFdXzxcMHNot1itO03TFijjyFYTzuZ2fLruvcrHv3-q01ZrU-6Var_nAQgKprtRLOJfTB2KoQ-8OolBqnsW3akLJ1rRN09bzfHclQSsU4F6J31jhnjTXWGlPVEpMwpJiYmRTmvtcGx92OpZQSfAzamBBHa-qcEqEOw2iryra1rZyta0KUEuq2ThNrp5TSnNgaDcKo1XgYYs4itFyvSOFht2lq4_uxbiuyqm6rafDWqdPLNQl3Jw2B4sJaYxG9v--ds1Vbd7N2OPrvXl_NZ13M0_dfv4053t8fTs5XP_rRq8Pm-F__7Z-rijDxqnaHvV8t27Z14-gXy1nXtr_99tvHp0sScNZ0TZ04zbrm9KTrt0eNqJW2hqAwiFijQUSRQoWp8GEYSwFAXVk19vFwGNHoSLTd97f3h5v7fRbYDb4fwjCMDDLF8OH65vmzJ7_59urf_t0_bn3c9j1qMMb6FOsK31_dAUrO-bDvU85SsrF1LkEpSCWLcTkDCOhZxQIxxhhKu1q0J1U7r-_e3zMJSylcwuQjZzTKVi6nmFKMUzneH6ddXyvUCpTRqNlZzVju3r4rkEuW_d1RW313feeMbmfz3fGYcmjns2Hob7eHpqkyy_pk_v7mJuc0TNPk_XGYQswpZR_iYb8fxqn30-QDl-JDDsELgDG0OxyNUzmnqqui5Jw4syinUs6hlJKLMsbVTSnQtl2IU05hCOE4TVPkow_jOB63_nCcUs6H--M-Tb0f39zuMpZhDG1lx773MSyWnTHKGm00xRgVUN0187YyxjRNs9uN1_cbW7vEpalcFjg_nS-WCwVcGb3bD8-fnpcisSR01scUGXxMJfHu2B_6wQdfBH_541frunt2vlq0bSwxxrAdpkOMf3x3--_-8Y_fXG3vD9Pb20OO0Pty7ANqteuP3kcoCTKT1kpTATWMCQjWy0XOCEXq2jGH-dlKId_fHYfbA5rsZrNnzx9pzperOvbT5NOU8n7X150RjVVtFCHHbERh4ovV4tNXz87WM6cEi0oF__6bt8Z1YKup4Ol81cxqi3S-WqDAclZFn4_9iIqauhmn8C9-_gmx8t6_v7v-qx88b2xljBrGGKNv2zojVY2638fffPWtVJWp68n7d7fX__Hf_Pz-bmuUMiQXqwUZ_fU3by6frT95-ohjQRSfcT-Ov39395s3V521WFmtzW-_fL3P5c31vRdmZRBFhDb7PSpCZwqXkHLbuO1uN0zx_MUq7IdS6OlHjw-bO7-dEPVsVn3z7ds4eVRm6oe2a4SzamwcStM1qMj3IyRoulrZFiH3O5_8VHUNGiqSGJkh5wK6VQliymC6SrsZkuSCUCs1p7gZwadp6DnnTOxTzJBKSKgUNhaKDiGbyhQopCiOgxCyAIuYuq4WHZcMqUhmjqCtFgYAnK-bzbv7UsrzV8_H_cRU7m62J48fu64qPheJIJxzzKUUhixYMk-K9tsDac65hJRXj87u7-6_-vrmzXa63-5iiR9uN99_8-b26v3zixNVtX_37fvPnz0_Pz_5xWfPwMqj5SzXzdaPPpe7-yMzEOF8vgSAsffKGuPs4AcGHHb75WLZ1fXUj6eXjw7HMQLbqj0e96er-cligSLTvn_79r52ugCsFosEPOb09Mn5YX8gbdZnq8ao-_vbRd2Zqj47W_zx23fbXe8q50OK3icfO0eQwtBHY22WooiI8fxkQSBxGs_O1-fz7rOPHrdNPa_qblatZu22709WCz95f5y-_v7Dp6-e2br-i08_vbvfFE4vLs8_fv70X_7Njz9_8eQvf_zq48ePkMvox-W80ZUex7Sb-hQTWsszl4tW3F6AgLEWUCQLcslctLFEAIXHcWxXZ6Hvk_cCZNy8932zOskhCqKwABftanl4nsJAhA-d9cIPMTWXAppQK2FQyrquLZPPKQEn0oq5CABKKSzK6WqxjDEBIvsEKVSzpfc9IIm22mgE_RDGh3Gy84UUebhzAJE_1Y2EoTAhEQIoAigIf8rTlSZSGKZJoWbGNI1V65AIlPbTZK117XwaJyjFzZYleOZiq0YZy6WgQE7xAfbHwqSIHqYIgiCirIFcRAAVIQCQlphBayJCUsIMAFBA1R0RokgaJhQx7SwOA-JDmUlKDHa-5BC01swJtRVGFCFrSWnbztIwmaYCZqUpjQPV7qGBlPZ95qiMksJ5GHWlk_eoFUoSQqVVniJqLSyilDYmjiMzNIvTup2VnEFJ7vswjqtHz5Dz_vaWdPUAQwr9EJJ_SLWFKI99iRFKUcYohcyMxPTQkELh6HPyKedmdrY4-TT6u367E4DQ991yOW7vtXNaKZYCIrp2ZZwUiDZg6xmj5JitM2EYSyzaGi6ccyJrRQoz8MOYV-lp6LlICZE0ESXrGqWQ0AIUYMGCKFRSNt0s9AMpFWMxVaONno6HMuxJOSAlSNknIq207ZaL7P2wO4YhSkmL9dlue5-i18q2s0UYh2n03Wper04EgSWXnKrFqbKYQshTtK5OY-LisUQizSXl0ZO1iKK0tXUtaVLOamEIU5mmnJJSJCClpJI556wMQC4p-BwCWdcsl6vLJ1J4d729_NGPsiBnrdvW1h1YE46eGJzTcZri4ElpzlGSpylIKXYxKz6WGNiPOZUU_Oz8MocgWhESlxzHUaE53O7R6jJOfhim3aauqmZZZZHjXb88P1-fr-9fv5-G8Se_-LOr93fKwfnlZTNfaq1qa-9328ePnqBSMYaua7Wx6_NTO69EYb8fgp8Q0B82SKoUWF8-LZxNU5mqLikhQY65Oz1TjeFUSiqCJEBESKjKNCkqYdxmP9VNyzGXlAmV0RpiivsdpxJ8H7abKJxTrNv52B8KwfzkUbs4qecd55BiTjli4YJKOXPx-KmkMkY_Xy27-Yycm_pRaSMxKqOnvk9jBERMpZ1VWUrVVFB48GNT1WScqUxTLx50Lcw8-UFZG8KkjM05EyBZa5x58F8GH9ysAuG6adMYrLGgQIFmolxktljl6LHwcDj40aNCjmw7RwolShiCbaswhQdVFgg5o0HyNAymscKMgIVjOEyEBQlni7km1FYnRlcgTZwjNG118WiNGqp61nWVCCTmz3_6aQ5lnKbLy8vDdr8-P5vN57_6-y9eXiyP2ZdJfvaTl6ezZlZb5wxpqmxVGc0x_OzjF-t2VilDwgrAe38yn-UYz5fz5ayFwvNFS4BaPeCCARCCTz4kUqSMIYSYcmFkQp_lOPoAMEzparNPAvsh9EePCkpKU5ZHjy_q5ez_-T_8_3zk129vdodhOAZdO01wdXObcwam4-6ggPeH3s7r42FQqHMMsbCeV8rZup1XXd3UVclw-ekTbTQVLNNRMtaVW5ycLB-drE5Owhi0RiCK49R2J8KhrutHjy-kBCl4f7c_u3gep_Du27fNYmarut8fmDkOYZqGaQqoYbman19cao1_-OKrj1-9LCVXytxuDh_eb7W2MeeQ8unFMgQ_Dj7GxAC2skUkchGW4EPOYXc7NF2dmZXSIWU_piLofchSSimI9CdJtpA_DkrKbrcTVKhQoxXkEPPNzV6KkFGf_OTx6-_vq9qkIsbonPKX316No399e6uATs_WIYYnl-vo8zT50cfDNN1tx5yTratxDNfb48lq3tSNtXocA7I8fXLWGvPNt-9F4EefPq-NhpwPx_7NZldYOWuMrdrKWaNfffT4fN68ujzVCJZoKnE3jt9c3dz1w_7ov7_ZkLVMcPJixVju78Of_ewjTuXps0XsvTJ8dX0IhU3XFmtyDmXKhFhZ09_uGzHjMa9r_eLjZ5vb7bvv7u9uDk7Xy9Xi1ctnHCaSohd2czXEKM2ilSLOKLJuv9tqgFlbf_byxQ9fvXjx_KJy6qu3V5HH91d3v_7Hr0wpMSZ7sVqQTpOf1fb87MQonKa4mi8zYBTRTs9nzQ8vz8-XLYn8-vvvP3_19PH5qjaGha-uN8oaJnh3tbnvw_2xr-bz3TA-PLJHp6ffv357v-2fPTt_8fiRUrTdHVBrUzWuqXb3e0bYDeF4HMOUfvzs8nY_fP_hDqzbxXh1uym1cc59--adMhhLZsTHl6ezio5j7ocgjMM0FuZVO9vebn0fd9tt6v0_-8XP_vibb__4hzf3m53VEKYJEHIstl0A6E_-xV_749ZP026zf_rychjjYTicP7skxNnJSgiA0M4bREQN09jng8-TFMVm1oYywsoJQx5D2vZl3yNHHoJsj7zt4RBgSMa4EpKqOecMIDlG3dSH63sR1LO6Wjba6RCTGHgAXHFJ2U85TA9IgPE4aE0Fyndffbe-fFw7KyTDmKIPiyeX-w-3SDIcj1mgQCk5F2a_70VhCAlIgaFpCDF521BOqR_6N-9uR58lx_1x__XNdYj8k1dPbvbHHHJdGSA6ebT-9ZcffveHNzHzcd8bq0NOpTACurYZhoEUkiKRQqR_8Vd_nmPJJf36H35jXZMlX11dTSPP5k1TtVASC3z8gxdXd3sl0NT27voemDXgNHmfUr-_16Bv73Z115pZ9et_-v04TtqqYYiHfuAsIcWYUiyqGBj8xCkXxpTjo8uLy4vVZ59_1M26FONi1rVNlZmtNfW8eXp-spg3s6q9OD87O12cLJefffZSgNuq_vzzV48fn3eL2XZ3XF2sjYJ_9-3XXmIBvQf81__u19-9u_tX__afDn24OfRffXN1d7tX0F6wMEpGEdN0yAUeDvCJARiI7Ww2Pzn3KYlW60cX0YcUxlyKdXW3OPFxyjkBs3Y150JE2SftKPn8QIcUAckFUBmlyZoc2dQdUOaUECGHiFqRNQiYplRiTFNARdbqNIVxHJrZnLkAIAAqXflDj4rAUhqDaxqwtgSPigQJhBEeTtQFUJXk5QHuTQ_mnQKAqBQSOlcprYfNfRF2Vd008_12p5xp29Xoh1J81SyUosIMjNpU2rqSHvbHLKWg0pyLrWoiLCxcMhKCABcGpQAVKXqAhCqltXWcIiBwCCCotAXEnDJpYxfLOAxE8CdNArMylksGUsBFuwoedsEixhpUKk0eilijgHQKEZVCIts0kDMWJgLRIikp0kDCuYA8kP1Ja8UAIELGUGWBWSSmoecixjaKGDgO21tmEBEECD5V83m7WMVxrLvW-wEIrGsJ_7Th1qZGslIKopSQBEAp81CMDsEHf1stz4x2UErhyGF0lY6HvSAiqjRNrptX7SwOxxRT8X1VzxVZgqK0icwg0i7WQEoApICtay5cGBAFWEqMxljFIDGXyacx5By10nXX2apGa3OOtm2AMxDOVmvrupKDcw1ZW6SwQLVctGdn1WyRQhoPR1PZUKKr9DRNyujHr16kmPvjIaU8Wy1AeHfbk8aqbmMOgDDt9-18rRWlGIVZkJXWcZoeuu9kFEmO-33JIfW9FEYRyUzGcp4AgHMCKMoYTvlP9aYMJFymftje2bpx3bLrFtpVEEPddU9__FdVMzvebF_-5M-KxmGzI02IirQgC-RiNZU45Zin3TR_-UiJGOus1dPxmIbetBW5ilmURqUtGq2cm3bj8sm5gai1xDBM-2lxfkpKDb03tl2eL_1-f_P2va6rWrthGEHw_OIJKdV187OL86qt_BjW65OUcwyZAY_3e1CoQSA_NGFKBimZU4KQuZvNOUdbuQJKmBVopY2ZdzlmV1lgyZlN5UAho6AySChaO6eTL0BaAbJIztEZlWOQkoP3OfnZeq6VjtG7qkIk18y61dlx27PEOPkY0mK9AoBhPxhXoSJn6yLQrZZhHEOM5GxdO0WIKUkq2cehH0lkHDwoMFZnTlrQVFYKBz9IzjmMyhiRUjetInJNAwghTIgqhQhCYfAlZkUIIT38t4sIp0Iltl0HBMZVwQdlqWnaoQ_dfPGgUiFC21WkVE6FhThlpRXnjFmAwB8HYMg5DIegrDqOByDc9mF9OoOqunj56OJ8YZQulnOS7__wDQrUtWbBnHh2urDGHnaH9XJurdrf3P3Vzz__4vdfff7JR2cX64vFLI2lclqKzJqaEBzB-Wq1bFtm_qd3r189OpnNZgLcaksKG2tQxDpTciJBpbAUFmGfUiksCIJUUmkbM07pdjfEXELiUHiI6e3VJgpMPjGoox_vjwdC98VXb5q2-cM3372_uvWljDHZrq4a5w_HsJvCNALpMAXOJSd28zpNIafEOUvKutJQoFosUVE1a8Pon716CiyQ8a9_-fGHb26nyRutXVMBE2l6-uT84vEZCsUSwzQWxq6axRCLH8IwkFHj0LdnZ1Iw9N4Zl1m4QElT01RkjbbVT3_6UwPq5nbz_OXz5OPl47PdYYw5V40OwWtSISRhscbEKWhNiigkHiePqKZhzDEQs67cn3TnMSOgdhoFUk7AGH3Micd-fOA120ojEBIWJIVqUduiqe99O3MKdSr5-u2ec9FaZvXs6sNt27rLs9Wj9bxx1dnFWmsipNWs3W0OSpFzdhjHWVcB4mEId4e-7mzJ5Tj0zLyctxePVink0cf5rDmbd5UxmfN_---_7SyQtptD31TmZFGv53rWVJiLICFi4PyH9zfDmO-HeBzz12_vjsO0H2KIsFwtlq75X_7dF3_x46dapanvv397O2U-DLEw2HXnkw9D8vuBshSfOEg1a56_OH963l6-evwP_-7LmOTJs9WnPzvvjPvs1aUxuLufQinvPhzcXH364ydffvk9hBRTWsya5cL97LOPL2bzk_XycDz-_pvXv_2HP45jXLanrrYewv56v1wv_-yHlz_9-VMcy7Kt_-aHl1-9vjZKW6vW89mjx-e1gX_2yQvMEaKkwlWtX5ysnNI-wJt335-cnx7G7FPOQsWo7TApY1OWMIZ-v1UoJ6vlyaJtnDubtdGnurZA1J50v_mn7waflNVjKKhxtV6MMf_d7768fHT2zfvbCNyen9zcbvvDYJ0CxKZtIsu-99eb8XgYkHh7f--MQg3jGFNMMeVSkkN69OIyT_7Nu7faivcxx4SASpvTy8vFet7v-24-f_vH79p5KwqV1f3gj4exXrSgcZpiKuVwd0CtsLZlguWZy5zSKMKRojBDvai1e3CVYxnFOIOMdTerakexiI-y3cLIwskYjBMD52rR-vvh5OLc92MBiFOQIqp1BQW0QqOAAAA5hcknQVREUvK0P8Qw-TBhSQw83N-1T-Z-3xtrgo9V5RAAESRnziXnknMx3SJPXiIXxqRpnNI0xkwphRJzkZyG7NfPzu_u9p2ms272j7__7v_zP__27fvbKKysNUalFHiKgsBF0CBpvZh1ZxdnxYdf_vKX07B3pvr1P_6mauv77RYFc4af_4sf3727GQ7Dh3dXz548Kqk8vryYBt-0TS4gXNqubduqPx41wHZ_vHj6KMa02Q9-CpOfYkr7Y68alSY_9YPSRE5JAqWIYyKi9XqOwPv9lGK5290fx_79zea779_Nu1mK6dvXbycff_Pbrytrjv3w29e_q00rIt1ikcp0d3XDCXY3t13T_OGLr7_94p1OVRjiGNJnz85rV4WshsPuj9-9_cEPngurf_r918qsPiItPEUiIQKl3UMqzQi6MvKgj7Ut2cr3fYzj6bOPChelyDmTUp6fPiq5AIBxLsekiQCZtLJ1nVPGh10UKSgJgBWAm839cARgpY3ErIyCh90rotEqT5M2WimtTStc4nH7sFAlJEEilHqxCiFoa0zl4jSCoDJGz9o8RoUPaSIC4gNHiEQERUpR2gCKcEFhKQWcQyTlXDjuU5gA0dR1yVDVtuqWfgo5eWVrVzVx8qiwpKBdjQhKOykCHAlBWEjrB2QkixCC1ibFrBSS0sAZhCVnMg4eQJlIQgqUEiIRLiESatIaH3ropKQwInIpUBgBGRG1RQTNORdulwvfB6UhpQTIqmpyjKRUjh5ZCJiUklI4M2oE5j-Jln0ABlQkUhAghmRm67jdaY2KiDmknFFR054IQgo-x1jCFlEBKU2qrpfADyNLH7y3zQwYUoicPTCj0Uobco5LFpEioLQxRKXItLnDagbAHGMePaFoJFRKW4daJT865YAIksdSUhiSH2zVtMtl3c13mytQlrRDRe1sjQjaVqh0s1rarkVtcspV4wCBcwIEFKnaLoVp2G05Z0Dyfe_aWfalWa0kJ-YcJ191i2q-zCJASs9XAsQ-GWu4QClAwqTtsPez9dyaGlBSzAhAWIlg8UOGIiK2rrWrYphcN9e1JWtKKcIZlCJjq7OVQlSu1lVVSlZaKf0fRuUpgrAxzhDlXIpPuqpyzIIinG1VExdFGPY7qmq0VdN0x_vNbDbPsV91i_5wVLXUy5N6cVpIpxCwACGSUpKZAUoIpDHte0TyfQ_M2j2M4BXklGK2dY220a6qu1qTAEDy3rgmjf10PPh-y5lZm_04tfN2sT7VzlW1ORz2jy4uC_P9zW51ulwt5gLw6asnlWvfvnnfVg0LT9Ow3Rycc8P9npmRNGrS2iJI1TgR9MNxuT4rDApJcnLORh-AkDO3yzUAG2ftqvWDV0r7KZM2IpL6wVrSzoJGZMDC8qDrRlGJkZlTLMFnH-6ub5RSQiCYm9VKm8pal8fpsNvE4FlKu1gQSdO2KYXj_rC-fEaNs8vluDlKCLZ2uWRS2C1mnMti1ZZxCoMHgCLJaBM4VU3XNjNURAhx8EpTyWU8HoiUqSvVVqqu2vWagRHAGidKAAEzO6sNFSySGTIDi7R1F2IY49h2bUq5QHBNHYK3hhCFNBmnGCGnUnc1cCEAWxshIjAFBJFiym5udOHjzX6_2x_v9jfvN65tAe1-d3zy6FxrOuyGnMqLF09K5sPm8PFHj3_0n_35u2_evXzy5P5-8_TyElX5-GxxNq_XXaVAhmmqNCHDct5Zo8MUC_Ors3M_hYcikNO6MrptKwBIITpn6MGkATB670NmwFQkFyalfCqHwU-phFRef7hNAreb6W7wxykOY7jf7kGrd9d3fSxF0uPHF28-3HpFxyn-4G__Ytjvp8OAPiglSmlBtG09TclWTrjEYy-l5JDJKvZB20aRNgqdxVnb7g_HVx8_OV3Nuqb-xX_yw5sPx2fPLmaztq7rfhycqdaXJ-PYH3fDQ5Fj2m1n884fDlqpblbbpjJdRYoTZ-OUIsvCbVMZbebzs48-_fzbL343TmPtKtc0XNL1zQa0Ao1xSsysSG02BwUyjr7EjIioaH845JR9P-acObHW-nSxPBwPXTcPwT8gp_3kiUhppbRiEW2IU1HW1E0nAMyCiiprwxR8KolFGHJMYQq6UpVz0xSqtlsu51VVg9FDDC8vL2MJeUpx9DFHq7WAdG2TGcYpMOAwjN9_2FhrjdaLbma0TiHW1hz2x_OzpQLgwlMItzfHy7MZWlcASOv7w367n97cHjej76fCDENI_-bXf3Si62X7_mrrS-7mDVrTNa4_Hu-3hw8fttYI5_KbL6-vt_uNj_tNMEQ6SX8_paOXgBrNrKkQ27_-s6c_-vTRYq62-_4fvvxmfTZfnc7bSq-si0SbY__96w-pMCkT01Tr6vU3H0hB5Vqt7cunF3_56eevv3v70UdPvvzm-zdvro5jtLV9_OjJZveu3_vKmeefXrZWW8ZW3LJpHp8uP7zffX99v25dTEkjTtt97CdLsmib9XpGCE9O1w9i0C-_-HZ1uvQZskAfsme4Oxxfv72-vrl5dLbuFAbA__1_-ot_8-uvt_cbMnC5WqIm0vDFV2-H_VEhRWbUajmfzZqm6dw_ffH6448ee9SuqwLj1d19FBhzTiAMuDkOQkSGhnE8HHellBizH4NtGiB88-271cWcsBz3049_8eObD1df_vF7PyZdVbZzJSUA6s5Xs9lCG3V9cy0lOuXCEJ9--iyPIQbPpey2R2NJadPO67ifprsRmVtbtd0yBm8IgFES5DFyEQBlmjlWRgwpW2fmHCKKwiREmlBK79Nx1AiiJAuAEDLHKWtDVGkomGNAYwGpcA4h-O3eNbWtrKpMlqKNEs4xRDQ6DGNOnHOIhyBAaPQDLEEbg4YgsyJ4UL6iRQDO0Y_H_RTYtlVVa6WxKCCrpuMAvmz2k_fhq6--M8YxUADVR09tPY5eEABIOWuNUWQmP8XJa2Lf99mH5Mfjrj9ud8d-6KdJO9cf-6kfPnz7Zjr0N_f3Rfj9h81itS4hPb5cnz9Z1VWVfDlZLr5__X45ny1P1gDw6Mnp_jD96p--OHu0Xpwu33z7drle2Mrs74_JT8nHlBIShGlytSsIwly56rgf9uPQNvPDcSQyLBB8amezk9Pz25tNZat-nOq2PVlfIEHTzW7e3xplF4vFH799wyxNV1WmqmdV17bX2zty7g9vr9592B2H47NXlz_62Y_-_je_N4oIQXH3ihFtpaWEkgugkLLKOEEFSscwlsxuMau7xcmTJyWWaraoumbsj_u726quBWi5PqPKjcejdpaUzT4ASAnZVA4RcynKWq0o5QxIpLXrOj8FFERipSh5TwB_ukhmFig5hMKMSLabS85K6-SnFL2rW2Oqqmkzo98fAEUZKkVKLN1iiaRKiKCgCKIAIQqAlAhAIEK2BcnKaM6RUyFrCEnbKvmJS0JJzaw77o_a2sXiFEmHMOYY0ZqSMxIgYQrlYaHPqQA84H1QWSfMDwRMQCKFKAIPIB6FUkT4Ib7RJQVAQSTUWlkrnDgFbQ0zAyouosgUToQAmqSUByuvrdYxHqSIslXVNn4cCBVIlhyZCLiYqkrT-LAvJqVFGEQkxiJZGEiRspqZc8wISEppo6vaxBA4FUQCFBIJ06B15ezcGJNTRATOqeQw9HsiIlRV3SFRjJG0AWREAc5IlFI2rtHWqqpCkZwSAKGpkBRZx8yEoAglJ-CUYmQsytXAJFKa2RJJ5-ilAKGkaThsN5yLCIVjD1RYoJTsmlqgGGvGvpesRYSAU0lhCkopJK21QUVpGFRVKU3K1Zx4fnEmOcdhgMwgoI0ajgfBPF-dICpXVVppYWSk5fl509XDtv_pP_956PvxeCRSi9ML3bjJx1yYS9FG-35Uxvh-qppOKZyGKWfOkU3VIAJWVfI-jUMOSRjcamnJWFuHyWdOkgqRQmJUquRMioBUEdGzhlCEAFLR5Dh629jt9Xtd1bZa2UV7e7-NxwEpnj65vN8cT84vWNPy5Gz9-Ox4tyHSMfhmvkipoLZVO49TUMSmrqZjT9ooRW7mfD-YSgkIR1ldvIz9NqUoKeVxyik19cpWpqRpGidX6cPNlZiGmvp0dSYlm8r-7tvva2dfvjg3dWWJnDWny_nbt7cM8OjxxWrV3u_6yXttlK6qAiXEtLg4bVbneYqnjz56_sknNzfXPuVSYH5yQcD73b1xbV3XxjlOmXNWSpXCi8eXMWVTVWEc6_kMAKum9r0nbRfnJ3XXxDBlFiRyXYPMwqKtA8515dI0cEo5i20cACNR1XU5lqquSvL3t3fdcpF8yjFaU3FOihzHXNc1CMecC8tDLSeFyClzyq6qOfvDfscIKeWmqjNnY2vn6uXZ0xR9CimVpJXa3O5CCJU14ziSgK0sivI-PTBqiw9cslIYQ2QUaw1zcW0Txuis0ZpKAhHuFouc4jD5ECIZDQLLs5MYM5BdPXqRhoFIrU5P-sNIBJIhHnzbtjFG4kIayOk-jK52wQeGVHx-_tnzZdN9eH-17NqPP3o-hvTuy7enq0UBnnedJf34bPkXnz1tjJ6mqXJmMwy11VrpqrIk0Nbdbr9TBtq6nrWNMWSIrFYEyMxaG0AgwpR5GIPPzCJMEHO-349INKa8934K8TBOd7ujaLMb_WY_sKK3b26qeb2fpt2xNwbOTpdfffX-fr-rFjOf8f7Nh2lzDNPYdo2ra3JWOVdyzqWoWk_HIfpJW8UslrBdzk3tiiQpAqh_-tc__PTTF_NKr0-WBsrupn_18eXlkzPn3Hdv3zx58bRu3O_-599urzam0Rz9uNkCYMzRHwckEBLjGjam5BxT8SGnFMgq50yMnFPe3N0WKTdoIaFcAAEAAElEQVTX11abnDwqDaraHw8IarO9jzEdDoemrTnFnDIzG2vv73bBR9OaGOPUD9qQQjxutmR0yrHpzofh8AB54yJIpMgAw5-Gwkg5BIWglf5T6EOUBbKPVetyLMbZfgjGKFQUQlydtj4EA3C6WAxTHI7-_Oy0qoxR-vxkvTv0xqgYyzDF_aHf99Ns3nz0-MT7PI4TlkJalcyayFqNhYVQWZuJJ4bbzX6K6fXbD652vQ8hRGEoAIj67dXWMFxcLKbgE8h2mm7udr__4rUPQWkNxo4SfAXfvj3sD_0wJGBq5hZSOdz2COiUenTa_uD5-tNni_NV28ybzV3_9fe7Irqp66atpvve1nB3GDab8fZu7xr35OR8N_YUU8olhfj5Z59Qyp89e_Ti5Ud_9w-_DjHe3x36Yz9frJCUaerdfnsyb-efn0MfjDLDED9-fnk6a2ekOZev39_94ocvCuBw6M9OFufreT8NP3r-pHNOaUUlW62YYTz6-aojpRRSyZKY__Dt9yzy5vpGI3z3zWtj5PNPXnzxx_ffX91VtWPGw_awWMxCLH_3T982CxcKF-b5Yl5YjvudCKy65vR0uR3DyPL9-7sxFdY6SXF1Q1Ypo5moH3xKJQQfOSll-yGKFqUUGTRWV12zvb377JOPvvnq9b7vxSrtbMLIEQrnsD9cPHuiZ-3XX745vzj1uwMJ7be70_PlMB6Tz87qcgypD7l42zrDOR88ZwghqNY8CHby6AtnahSQxpllnY2raF2VnNEqTlEKk1JaW0RiH2T0uY_FM1hxF61dqrgZUUQZBfQnLY9qa03WVLZMHhi10kCUpqCd4xCFJUPJJftDIINkNAAgCSgS5Dx4RYgASMQopRRmRGRT16FEFM7MpjLJZ6V0vZj5ko-Dv90cSLAgpizHmK839370KcUUEyGAoWmcQpig5P5-23btfnd49fGrSivnLIL0IUwlF0DIpfh4HIanT57sDn2CXNVmv93OZ8vNfR8myTlfPF7f3m60UuTsYjlHEMn8xe--Pj9bllycs8HHs9Pl3dWGM-QSSWGMsaSMQpdPLln47OJ0tuwUADMP-932cCSCytnZYqE1ffPm7e3N3cn5sq2rmPPV7b3SeHt923X106en95teFFhtfvvFH84uV7__8g0qfvHp8_fvrne3x5evLhlkfXGSMs-M_vP_-Oe2iLr8r_5Px9srLB6KaGdSfyBjH_S0zKKcLbEU3ZiqO338-LjZtItuHAbbNYXF-2m1XsdwdO1MoZ6myFKMsUqpkpIyWooAklKAyilrOGcuWSlN1oTdnpzi-MCMEskFAEAhIqLRkqOyJseiNOq6BRbr9Hh7L4SkUaGuZgtQGlEIFJRUcgQk1bUsAgDAAviA1CSliTlDySIoQKQNEpaUdKWhkKm74idh9sOuqhfej7aqSStjnalmQJR8EkTO2VZNnAIAP4h-EQUKAxEAoNKodQlRO4vyHwClACAFRYSFrEMEEAAUXVUlF2UrIpVTAijMopTW1QKxlFyAH7QcCIqQEI0tOUmMJbOpK8mJQxBErR0ZXXIhrSAnACJjmHOJkyKSmEURCKC2okQABFFKRmEBkgfgAiMKSxGFIpyj77VWTXchBE3bpGkAZOE8HvdaG1fXWhuWQkZLgcyMIqRVCZ4JS5T69NL8B-g1ALCQqrsUPaaklJKciP7DhMJYjmPOk7FNzlFSREKllG1bIDFVpatWG6W1GfqRFM4W67rukGiYDnXT2m4uiM3qPE4eBWLMJRdtDHP2o88pMyKREoSSAgefQoBcUJhD9oeeC8QU4-gfffap7Zrjbjvcb5xS128-1HVDSk0h6PoBawh-mEghkVHGcEnNbD70x9nq1FSOJQFw8V4ZY5YzZi45Q96RW_rNBq0WALeaIagcM4ogAMf0MAAAZg4FNSnUkjMLk1XAHCevAPxuN5Qgrp11i1bl_WF_d3dfL6pxuw_Rnz4-izGcvnhFVTMOIz-Ioslq53RdZ5CcitaWlCCgrqzWKk7BdhXnEH3fnZ9F71PwddeFYWDICNw0nZQch0lVDhQGHyfv16enkx9OLi78OGVNjVOVNS-eXlxtduenayTc7Pss2Hbz5enpNEymqnIB4xyJtlrZ2k1jMJae_uDTNPmUoqJMWpMypBCZTd0M46isQSIQGTfHnIttjG6sZFGofIhV0wjjsNvHMBFp4_QDBTT7bOsq-PAw0SEBY1WJIWx3afJ9P55_8jT0PnNenj2qjTpsb8MhZCjrs7MYfNN0g-_3--PJ-Ul3urZN45o6-oAEIBlAkh8UIilqm-pBFYfIZHVMwfdbXVWFs60rQHTO5BwBpFusyCAKlpzqk9XDb8BYKyXH4IkojiPFLLkoq11tiLDu2jgGpZRxqunmqAkArFY55PHYI7Ex6nB_3XV1ycW11rYOFFUOZrNZLKJqO5_NQSCPwWl72G5L5H7gTz59dv7obHN9c_H4_OXLy2G_KyymMlhQW_3f_O_-Jt0ff_bps1VXw5-kGjTr6kXbPlzO5JJ3-92sdYtZZ7SK3hujnbMAkkpmlsIFUE1TDDGDVoHlOIaQJTEbRT7nw9FfXW_HmLRzBeEYypdfvwnMWeJ2208-jDHe3u5Wy9nF-en9Zj95357N_Tg5Y5011ro4pbp2J6cnP_zxq5jkcHM_bHttNQKIoGmtmXe27ZybA_BsvVhfnGqNs7aqq0oTI4N12hq92R7u9_3i5GQcp7ffveNUwv2mbuzUT8bWP_kv_9kM6Xhzl_wgBMpUkbVooxunlTCUnNkH77p6vV5t9tvN9WZ9foYam8V6KinGgsxh7DVRikFIUCSmqLRRRokCoIcISIgoppRDTikg0jgG0tpPXmmdpimGpK0GwOgDEABwSqWE6JQumR96anFKuRQkAuSSSjWrRNggAucc0mJVb-_6YXuMOVlQInJxPl-uGqPUYl5zFiL0PiZmFhBFWpu6qljIKvJTXC26tnPHw9G5BpAzcy784X6PoI79aNtqvx8Xy-UwjJv7_XzWIQpk3h3G88ulxFxYiugPd7vgs6312bPFtBsmHwnLfvS3746IUWIWYaNs8tEgNm7xy18-f_n4_KRzVKmQ0pv3m5vt-P5qEz0q4JxTnooy6Iza7sZhGkxnAWFzdx9SWi7X3pf_6J_9Zb_bXD4-ffnq4ps37-9utiFOP_rhp7bRYwwp5rZzrcXaEk5FAT59-uiXv_zxo1UHPn30_MI2FqzUxjZNteqak8V8GvuPL0_P142wcE6Vc4jY9wMZM-a82Y6bEG52-3dXG1O5Zx9fvnlz8_GLy3_2y5_wLjx_fPpvfvPlqyfnTz5-0h-H1rrO6ZvNfh-npm1B03re7g79u-s7RjLKFKCv3t2_2-z--GFzs9tPkH3mLJBLrpt2s9nmWI7TlEsCZcBqg2rWVFDKOPh50xKy0sh7Lz7sB3_6_Ozttx80EKfEY9TMksv5R0-c05jjejW3lR6Ow9772w_D849_drh7m3YTcSaS5EOKiVGAFCoGEEmMGjOLWtQKoPS9lIQZQp_TZuKSaVVnwVJKHgMayGHiUiQVJeBqowiwwHjdk4X4_j73Y1aYiwijaGkWXZwykcEkJIwlaSSWXEpRzogCbCuqbe2M-AwKBaGwCKl06EkEOAMgFwAGUhr4Txi39Y8_jZt7JBUOoxBnQESrZzZxNo0epqCUsaftd6-_T7FMKZrKnJ6e7Db3Etm1leRiNc5PF8OhPzs76brOH_pu1tzc3ZDRqE0uctzvjTI-p4P37cn62O85y2KxgCLLk-5k3Smj39_vc8oZymwx39xvtaZ-GjhJzvlnf_HjaRhfffr8_esPISdhdpaM0aau6qpyxhyPh-39brvZvX9zHXKIcZIsqPRf_eUPmqqafOynSWs162a7_fZ2e3j95sOPf_iqm81iCB998vH7q-vN_e54HACwmdUp8X57IMJ_8z_95rD1__w_-vnPPrn8d__-d-8_bK-__-Z2O_2r__4fnz5eK3j06eLyx3nYpDIaXSnr0jhpZRhEAEzbZY66bhaL1f319TQOZQwvf_yj11984Wrnh8Ef93Hyum6bWVvNlt6PpRRjHAuLgLFaWEQABU3VKSRESQ-kGk0CogAJmQgBSLiIAADpyqXRK01EClBzSVXXhuNg2iqHAMLKahFQpFPJ2jjOmVlQCQJo40grEObMgMBEwoJKiRSllTCXzNpaJIljAEJdOxAmAVBGKZCSwzRWVaWtExBE3S4WXErKuUjS1kER5qyMpYdrrlQQFYogIikCzkz4IPd9cOIgAQjyn078yIWhpId0HBiUVXkatSFA4Ry1s6g1KgKAwoIaJSXlKhBEeOj2FFRIhIIAnIg0_EnBVh68AoQoDFZrQiWlICJn1lXLOROBsRaS6K4GkRyzqVtOkZmFWWmFyFxSCiMzNK8-UjGOfa-waKNKGEVY15UIIZKxjana4D1phYKEBAR5Cq5p3HydQywgLFKtl0phSdFq-yBa1s66bu66NscQxynH2KyWyY-CmEKEwhyia9ZpOghjCGk2W5USjtv7GD0waKUy55JSiAE0Vs3MtbWrO1tVhSj6XK9WqEA5x1wAUWlDSpHWVduiwuSTkJACiKFADMd9u1w3y9Vxf5QpPXr2eHd3nzjFKXLO9WyxXJ80XWNm81zK7OzMTwMI1a3bXd1JEUVkTY2khHPsR-NqZevCNYe3pl1BybquOLNW1rSNsTr7LAiEQNaigG0silR1pxRxedj_KWREEEkJSmjXs-L922--AyKt6eLxua1dGIfN9bVWrh-mkmF9_qhwBgX1fKmMO7l8Tro2WptZnaYAQGGYAKGwpMCL5Ys4HfvtcX5xPu6PKQXjbJomEC6ZBVBXGhT741448jTuru6q-RlHISlp6H_3_Vs_jvfHY1XXm_4YCwvIzWb3kHA_e_YxajVbn17f3M1nbY7iXPfysx8dd_tpiqePzk9PHw3HsevmT55_dDjsUKuQAgAYq5fdxeSPpFVVu-N-KFnWJ0tlDCKwCClCzEoZyGX94tLfHd2sc3MnpJp5p5yN46SNjlNAKFyiQlBKV20lmU9ePL__7jULz5aLs08_Dru7m2-_TgUO2203a7uuHsZRMjjtjK1SnDLLw-4_5QgiApBHL1yUcJ58iQFy4gIhRNs2oQ_GGW3U4uJ8uz3kGFIus8UJKGSAqp3bqlaKss-iFBIiKeM0l1RiGsegTA2K6vmMNPo-9Ie-XcwU0DQMTd1EH8jo6IN2tpk3AhJDzrmY1kjMqbAomJ2shdT5xdNXP_wbktFaN_rp1Q9e5KHf3d9dPrqUXD77yWers5Pj3R0Z9f791fnqpFLq0XLx6HQWxiQAiIIolbFGKY3UuJpQlrO6do4AEcAYrY3mUoJPBcD7TEb5EIUwMYwx7w5TinwYR1SKQfohfPH197NlGzLkImzpq2_fHo5-t-9n5_PNZj_lZG1VCf7os-d__6s_vP7u_dMXT7bH4aOf_PC4OVZNZTXNZu2Pfvhxbe1-cwSRcZpSiil41IqcJVupxqWUS47GUbtotTWLZTub16tFu-zqrqmFUEBu94fnH10ehuFuu538FGNiBYIlhmyq5j_9T_4yZwgh7vb7mLIm_Rd_-9P7D7uEHEMwxhlDU9_nggXt0A_WGT96pXSf_DCFOA3j3b0fR9Lm5PK8qerh2CNRf5wqW0mSwjkxCJKPAUSargaWOAVldJx61KbkZCurldGa_GFARfygYlSamQtzymmMKaasjM2xaDJxSgopThEJEXHqAxmznp9kyQpVSTx6Pw3Dk9OlVrpxJsUswH7ygoRGgaLIvOt7rWi77w-HY9XUiuifvnxzsp4bTSg0TuO7q3vUmJgTcyk8TL7kEmJ69vh8HKfNZp8Ld01jtS6ZZ7Pu2-_exFzOlq3WtNunaZyGHMqoIPPLz0-LiEKqtfz4B2eff3Ty6mKxWFeG9N4PH7b9_THd3o6HfcqlVG3z-GdrU-lwCFWnosdj7-tFm7hM9wdjlXX65GQ5W9WX5ytr9P2HjXXNh3c3m7stEVw-OnWzqj9Oy4ulM9ogsuAfttvL9eIXn31aG31WNxLzR4_WDvHB_J4Ls8jj1Woch4vT9VnbbA_7w3a_Ws3Z4LffvItII0Mx_ObqsAvTtzfbzXHIhN_98c2L549bgg5pOZv9j__-N4cSLtenpq4HPykFq-Xs6OOH7fZkOd8fxqqqfvX66vGqWc-7wvDl9x--ub27Pfq7YShK20b7VAoXIBGBkNNxfwSlUojtonGrrlM6ppSkHI-jqypj1M0fb_6L_-wvf_LZD_71_-sfyGldEce8PFvtr_ZVY0Dg9m6_mp9c_fHbu_tdYR6OAxTolvXm7bclRiJtXEWIKJzGTKCKBK0VAXGMpfel9zk95FbAHrAUsqQq4CR5SsIAzlFX665C58QCNiQgUAAScw4cs2uRfFbOQipUq8JYfCBRqFBbG8NYYkLEGCZBfCD2PZBlCFTdVUUgQ2bUel5LCcBSuAgQWs3IqAmVQk3MJR99c7FMfaq6hUBOIYHSunP-6FNGe1ZPu6EQvvvuQwwRkYLPqHFze8-l5JIhxbZy2qji4Z__Z_9ytWh2tzdv__j96nw1hYSkbq_v-8ORBFBEazMFb12dkp-frIviH_7s0_3uiCx3uw1qvr296_sx5nSyWKzms88_fnVzuzk7X69Xs9_-w-9P1gsid_XhXYxJpIzTREoXYEXKH4eY4sXF6fFwaKxerBenq0XOzEk2h-E4hDfv31tr7-7uCpdHZycvXz21xo5jsFp__dW3JSYhur27X5-sfIqa1OnpyflZN_jhfLn8X_9vf_n__X__-2cvnnWV-sHLV0-fnX72cqlVUbMXP538bnnxEis9bI6Si2u7OI7GNSUnQVLOLlan3ekqjmPbdmEab69vPv3lL25ef183lSVT_NHvd4dhOnlxWRmTUqnaOXPhzMKgSBvnODOAcGGWQoi2dsa4LCIxoFbwJ3q_KKMQSQErTRzywy0ECwoX2860UUgUxzH5KU2jsZpLeXhhULaCDJwzi5SQTFPr2pZUFKCgICEglZC002iNBI-ISFRS4RhJm3q5QoEwTrP1aZ6OU7-fhgGJXNseN7vV04-M1jEm9XCcl4ez_gOTVBQRlyLCpq4BH4K_AgykjTBwzkiknc0-EAEKExJLRkAgBUi6mXEsJCK55OAB0TQzQJRSSsrKVg8_EigFckrHCVGUMlgYuBTJShuFyrgqBW8aZ2rHIXMRAkQiREClSvYIivhhbSOubqAwc-GUjHNSMkghJEISQCgRcpzubpuLk1wwDl4jU5EcI2ZBwJQycyJrdVVppci5OMW6acm4cNhlyVUzq09OU8pIxnarPPpSCgoorcjoHAtqi5pQmxQ8KWrPHvt-QE6YYykp-6GbnZSSWGAaNovFhXEuxTFGD6DG4zg_OZOSeZoIFYJUbdX3vamdabuxH61pkMDZqkgpISrroBQ_jYqMUiQsxft6NstTkMzVrI3jML-8uH39zlQmDCOyMOd6sbi_31XdopSUEwjCFD0WFpFmvlZU4jRYhYWZSFXWxj4WKURSd2suRlsCgTSNwGXc7YDQtI2bzaiuU4wAKMCQIflYYkCjFRHnB2SnQaR6dcLJh31ftWezx8_2715P17c3t1e7682zVy8P1-_77U6Rstoi8OXzH5AiP4xlHMftvVZV9NOTTz52bb25ul2enjIXLImAc9rbajHGyMztbFGYtTGAQEr9aY2TJfTeEFSNS4djDodpd3fY76vGufVTh1LN3P2Huw8fbq6vN1PwWtMPnl720zSNk7Z2vlhaV3386Y-abqa0ZdZdV61m67_6xd_84csvUx7H47jf7UPy3WIFWIyp0jB189k07lPOUz9oa7VzCJhjikOYna6MVpJT180RpDDHfhKQFMr6ydOSYvJBUlZGCUoaAwghqtXFWfJ-3BwUGn88jruDNm7-8uX177--eHzOkbuuVqpEH4hzzKVx9XDclJBs69rlWSYwsw6pNlVFiNmPD3Jx0kZyRoVx9JJiCZMiLCH2xxERrFZN15YYtQI0SjKG6OEBYzSvbDfPmVEopaitJSLnCLlISjmmB5VK8aOUjALOuRjio0-eo0IQqiqbfTo9exxj7Lf3RpmYStPMtFHgMwjP5_b6w5csaf308dnl0gHs77azefvZZy-P2_16Vm3eX4WYxr5__vTixOpPnj5-_mi1aJumMY2jurbI8tDoB0IBISJrDBcJKZFCbVVJnLL4lHIRn_JxCMfeJwFfSjF0d98fjsOUuWub3eSHcfzu_d36ZHm7OWTAt-_uvvruw77vJ59ijMEHQaor11gzxTIW7s7nX_zui-XZ2e9_9WsBuX77AQHPHp3sDoNT5snFhSJ69urp-_e3ZKyyDgGM1VSYC-dUQNOjl49ra70Pi_ViVtvWkbM0a2qW4rRhKfOZef_2btjubWNWy-XJ40fVSff8xbOmqxCr5mL5H_9Xf_v6m7vDQX7402fhkOrK3Nxtc8rNosOY_dGLMAIY6y5enIWcTaWtobjvcyi2sgLkp1BSUkYJiNEKS0SEwkUEwziVnLXRfhzqRRdDsbVBpTUZYXGzzk-T5CIMQEJKaUXRBwU6l8KSRx9I6xwCIpEggmilYs6cAQkAAZjvtzs_etEEGp3W9axerVa3t7umds6p3W7Y7I5MFDPnIuPku6YlpbKPTdtySgjw5GI-a2tm2NzvGGDTT4AyTcnHZCuLyMz58eNThbDq2svHp-uu7SrXWK0Jcki1NSerjhNLLs-fd86rlvQPXj16tJ6ftO15Vb94fPbk0cqgDhn6IMXgoPjN200_-LpuCrJrzaNHy8VZdX877e-Od5ut7WwJ3DitCMNQ2nm7PlvXTTWrW6utxHLcHV5dXly9u3p_dZjNzOc_eqkI1m3TNLNpODy5WHufnl2e_Oc___zJfDFrm3WlZp1xyjhLtQAg9qNXQF1dQ07zuurqClA-3N8-O7-IwsMQ2WLM5er-QIq-fHvLhm72PSr97sM7RWq373_22Sch-PE4_OqbD4ckq0X3zdvr4_G4mM9rYw7Bx5RnrZMi74feWvIA-z4POd-G6avbLWuKSo3Jj8E_5HUhFVu742Go2paRq7qyxhbPyBlIj5mXq7awXD559F_-1__yF5-8EinSaLZ42Iw-FGtNHEIuWRmbkr9-f_O3__Kv799fDYehnXUJZff2g3O2TImEyhREihQkTVrYGmMMSQANJAXscjE_X6FCO3OqUaQyGMCCBjLHICCQi2jNCrJAAQCh7H2OGYUJoUxDnAoCqgKUPUsRowERMqPSurG2qce-16SwCKQkJKQNOkeIkmTcHaVBdIajlJLCEExVoza6qhgKJy5E1LT1yYlpFBsdej-Nw9T3uRQBTjFp6wBzSjnHgsKcS4pTnlIhJKtT8EorYAg-iLBTjrPMl12jy4f3tz_90U9--c__-u7m7rtvX9_dbzkLs4QhGGOEURmVc-aSZl019uGimwvg_n47HKebm01mrNru5vr26dMnHz58eHt1d3d1-_zF4z9-9d04hNl6vt1upMB4GNerM62l3x-Vpt3dbfIhlkQgLKKNPj05azu7Xs_7yX_z7Xc3V7exlMfnp4-ePgKAEtm5CkT6cbr5cB3i9PKj59d328ePL0DBmw83v_jLn1SGJMvFyepqs_u3_8O_ufqw-T__X_7vv_j5s7vD5n57EJT_x__tv1W8vCw5pOjr-co2s-AnYaC60toEn7r1oqrqcTeevHgxbLYZSt00h9v74idiGQ89xLQ8OwcoUz-mMLXLUz-NVdfWs6WpKhaJKSNhAQEQpVUOUTsNiCWWatbFwQuIsJBRXAAESCkOWUC4ZAEQLLappHBJiZSydVNiFhGRnCdfLVcABYUArbZNDpPkyMScQ0lFG2XaVlICJEWg67rEDFBE_jQURkJFWGLKKdaLBSHHcTx59EpBAaIw9JyCbZr7N9-167U2JvhIzojSSAAKORckLKUQKS6MwIJE2oBIKUKIqBC15gyIQFpx5gdEKgBwCqQUCAIgs4iAIgABBOGUyDkiDUZzYe2s5MSFAUlZhVxKLgACAoIEJWutgYzkIonLlECAuSCC5MJoUsq6rpAevjMBlJIyuVqIEQgFq9kCObMUjomF_2Sq4eIPU7U61UaxD5oUl8TMkYttqhT8w6iABYjM_Ox0d78RRCGiUnLOrulAoMRYJm-cZZCUAmkbfNKVBa2Z8wOelXOGXGanlxinwsVqXWIsadDG2LZztTnsd9aqpl6TIqUJIA13G0DkFOKwDYcj52IdxRhAsq0qbYm0Dd7PVidDf-QcURtXVbqy9WJRLxs_RWYgTVyyH6aYim7nYfTdenHc7rVTtmun4XD6_EmahlJK1TTH3b5dLdqm2e93yY-L0wv2fcrZ98c4jCxRGyJiUpigmLqGzLZqYvCSWSSXaQpT0F2HRmkyZQolF9LaVKaUTEBgNGmX_GiMFUBhfsBKjf2-WbTrJy8KRy45-2H39vvifZnG6e4atbFtPfXH5fLcdd3d-7cp53g4-HGIk9emUxaGXb9--kJywpJ8lCKlmy1D79GqdrEqmQuX7D3qh3uSSmkpw5BTYCnaOi5eQh_G8f76WjeNUu2srura3b19fX99_fbbt-8_XA_jgYS_--7d5KfRB0Uwn8_OnzxZnZ_v7m_6OPzui9_0u03JKU0xpiBQYvY5xLqZgUKOMeWiEHPO2lpnLQPPZvOqdq7uQphiTHmYGDEzCBTXzay1aRgf7MOzkxNkVqS1rkxXkzYlM6IiUikHU1U5lItPXsjuLsXEJSltpuO-hHTy5OX-6hpjzmEEQONs9L6qXX_YA6NxpukWmqhqZ6RsLqqez2NK3mfXOGVUGoMy6uG6JqdgrAvHoTs795stJyaUFCbhorVGRhJoupZAKV1xAdc04xjTFLU1KJBjTiHaqhIfFBmW3J2dHG83zjkkUQCg6Xh_zyUIcN02z37wTDJePnoyhSOnOBx7EZl3y_3tpnF1yvHi5Gzsp-Xcffby6ZOzlQ_Hv_mrP9_cboYY_vrnn5907mI5VwhGKWFmZiKKOU1jImsQCQgzwjiGVGQIcYz5MMXtYThOuSCGyMchDCHd3h7adfv9681u3yeWi0fL2_vd--udMeb97bZq6tvtsR_G2-3xOHpA7g9HY8h27e12W9VVVTchJjFy9eHG1M23X3yNiJvr69l8frjfp0KoYHGx0sYM4_Srf_9b01gw9CBZA4CUEmitK2ddHVJRmlKRrmvnjW0q1ZAyIClDXdnffvPN-Wz97Mn5fLl8-vTRYZI_-_OXf_2jT05Wq__xf_lf_vzzH14dj09X6__iP_-lWtl-O3y4uX_26vF-d_QlKFRcWCnlaocIDDz0Pg1xd7sN-z3nVLXN-ZOL7fU9spRcGBEE0histcMw5VSS9wqw6hrIIfgUvW9m3XE3aKUJURnDpQSfjVbKEAASEccEAoW5riwCsiCUAsycGKGQIh-jEAKU7HOIqTAYTVzg2I_b3dGn0DQ1AqzXnTVquztut8N8NfMpH_oBSaecQ0zv7rZtVYUYVosZADprc84p8jD6btZOkUtmVZnDcdBGP-RlYZhAsK7qfvLGWEAcS9odhjHlo58QytJgFt7f--XKXJx1o8_McnWzR23BqN7nm8O02cf9fkqBb9_3h11vUTVtwz6uzjti2rw_7G72yHk1mxPon_7NRwJwd3Vs5g2U0tTdfDZv69poddjurVYkRMr-H_8P_3J9Pvv-y-8L8KvnFwtrz0_ma-eenCyfnawdqbPlXEr-7u3N0A_zxp4s5gboOAzKGK0oTOPpfH6ynBMJFZgvOp85iXz3_u56399ux9vd8cPN_lDSMcX73bg9HsWq47F3lXn24kkW3O1jz9kgRGOOYyAEQgpFxpStM5vjyKLfTfHgIxCOme6Pk2dAS0MshaQUBkIW3k3jPoyzdiFKocj6bI3KoBKFZb85aGs_efX4L37ystEaER8tuktrjz7vcvziq7fPf_iRMioFRgXN6XwaPTFbhfvRc2Y9r6-v76rFHMh2q1kI2dQ2QwalUoLu5CRLyjGHKImlWXRFAYvEKQqgIIkIMBUxiMrO1rotafKgFKgMDFjAaoWFkSwzc8yEiM5KLCACuahSMJcUolYm-iCkOYuwSBFgkcy6qQoAE7EizixcpHCOiMYCgq2tq6qEDFqFHBOAO1mgs-jc5EPfT9Vsrs9mCCLWkSZFKheRXPzoBYgBHoCQ1mhT2fHglUVtkAuWnNDqFJNShoxKOd_cbJHkzfurd--vFqcnUz9s971pq9lqUS1qZXXMBZVOOaYURMrpyclsvVzWzffff7CN3R6n5el66Pv1fJVCAOD7u81xt9vtD_1wFKC3377LOU394LPf3N-Ofc8xpmnIPnCR6Cdnrdb6L37-Z9vN9us_vG5Wy3_61e98DC-fPXYanTNFeHe_FS5i4Fd__-vMhRx-_NHHm8PuV__4m49ePCnFv7w8PVnNqZQxpuur25zHJ08f_dmf_-jPf_Kim8-Oh3w3Tr_6u19fvHiquqefnD__oR8OgKnpZtjNMHEYJyTStSs-rh5fTtutq1zlmsNhP243q7P1_bu3SrnU7wkgxQzKtd2sPw4hjFY73x_q2Woch8XZhQCVglXXxJiVUvWsLSkCqtBPxtWkSEgEQUJCo4VFOKMhzllbK5wRURi0mwFCHj2zmKYiICINKOGwS-M9ubaUhISqbqlZaFcBIpXCXHjypmk4eS6itHHdPPuoCHJmMpqISBEhcs5hHKqm45T2dx8ERSnrZgsyjqXM1o8Oh_tuddbOF9M4aq394I2tHyxmQgBQtNY5JyIsMdJDA4cFCQnpQXeApACRI5NWhAAMIEXbipRWRmUfAQSAEYDooS6DypgcgrCoegYIgCIlK1tzzkpr7SyURAApF9RWVxYRtLWMpRQGRtQKgMlajsl2CxFgjpKzKCStgKjECFKIBJUSACIDknMpDIACGjEORwRFpFLwtmmBgFCgCGqt67kmJ5yFkEuZnT2NPgIIKq2rJodQhI2t8IE_5yoWhaRJ61JEIdSPT0sCLVg7Fw77cXfXnJzEfpTC1pmcppzjNB5m63NkrSsnkI-HXUppcfKEoFhjQaTErAQklzAMinQcRgVIRFJSLiX5cX56YZwhohxzYQaiHMV2dfIhxygirp17H7rFBRLrpjl_-Ykf-nQYS8GqWfp-KIirs7PhMFhtD30_X56GsecwzU4fh-C1NsaplIPSLnsvhfMUNRnUkCZfNQsAce1CWY2lcD_lEEsqzXpNtSM02U_GaihcspA2D_czAFK4RO-r5QmnVJgrV-lZg2LTMBlLRimlkBBiCrPZwnRVZK9IN-uTbnl6_vKZqc399Y1y9KDB6O83gKiMVcoKUCzsmq5dr0rKYfKcWGtERVM_TFO0urp49sNxd6cKpuQVkiI17Dd5OIbD7vrNmyjiTPXsBx913Uk49pL6kmLwvpQCUuZ1c31zNz9Zjz642s26Npf46OLxfDF_8_q9tg8vPNx0M2PNYbMlBOeqAqCMIaPbtuk32xiDcvXxMMzPz8I4autYxFhbChujEVXwgRQprVVFJcQ4TcqYalFzAeecNir4sW6bbn06vzhr2-rdV3_kmEi7w2GYfCQoJMofdnXjyOgyTUprTr5pmn67MU5bZXw_WE2xpH4Y6lnbredcuOo6clYbm8ZEWpecCTWRstpwSsgQ9zuQUmIspYCwUgpQa4ISozVGCNuzmauaGHwza-vTpW06V1c5lbpruvlcNJIyBAqpNF0Tx1DX9cXLF_vb-5KKMFvU2lplbfHl_KPT_W54_vFTre2431EBEf7p3_78Yr5azOuPLs_-5i9_-hc__sGjk0Ua4-3dnavtv_jrn744PzmbzwGK00ppzIU5y77322ECRcfBx8wpy-1uf5ym795e69r5VAKzEO4nn5Hef7gfQsgMRfOxn96-2UYposlnvt4cXlyevr7Z3tztjjEUkvtd34d0DJ5Bbj_cizbHYSiFBeD29s7Nmu_--H2IcTgec0zDbsci_XFnrJnGceonseVXf_9PtzebYZhyLinkze02xFitFsoZ0MZatVotq8o9enx--Xw97-q2qlptlTCzWG0R4fmTR6jJVNXqpPvo1enzR484yxBSv5-yhk8uzoZDf3l5UtXzIfHLjy_-4e9-9_bNu-efvLj-_na-mOWQh8NQ1dXdm3uGog2VNEjymqQUDiHcXd8xQN11xrg4jVgKgQCL7wcBtkYTsKQsjKgoDEG4LFZzbQwICqKQ4pQApcSSU1JKpRBTTIBcBIQe-MdCigQYkXLJjADMfoyiYBx7VKpkRiDbmnbWGqOdNSJiFDa1BRFduYflrrMujCnGoI26PDtpnLXGNHWlFA3DoEgdx0kUHnOMIadcgLCy5ngclNJh8vPFTIk6jn70k3V2Sml3HGPJUbLR6ur-eN17Ryoi3k9yt_fDFN_ttgiqW86urnbb3WEMkUvhnFGb5Vlb1a6rm-iDVfTJZ6fvvr1F4imwoqpuLIqabstq1ly8Ol10sxLjk4vV91-_hhxlTH_11z_-Zz_9YUlRk9SEhvnlk7PPnj0F4b_-0aeIVHIZY5g1dSyyHafoQ9M6Z6vVcumsISQWmnKMOV2erlxVhZCw5CBZiF5fHa62fe-nzHSzPwwp3h-md3f3xxSzVYnM3W5ftW03775_dzVuj__6t1-zsT_9Tz6fotruDtqqz5895pz7Me-Gvmkan9JvPtxN06SX3durnWr07fE4FA5FXNcuFi0LxMxAxoNUxk4xrU9XoKnkOE1hfxxt5-azFmb13XW_6adPP35Zczl82Chj9uO4fHpxe7sJUwZAJtFWqdpN_YAp8TiRqrJIvWjPf_iMh8giYFRJxc0aAXAnS1W78ycvQJFqZ2JVYrGrJWglSrHWiJRSJCQ-JIlBjnvZZwhMnGTnIRTpxzJ5YZaZwodRp0Zh0Z2BLJIzoIYsiCUeRmqxlKTXlkOM_Vi1deEMClkACcTnkmIqTNaRNWgNIA3bw_yjp2yU6SrTVmDNNPXJ-5yirhwRTMNx2h-macwpAyFqrTurDTNKDD0qKSWDVSUVAVCOGHIhCH0SEQQ21hJALqEUfvbyo5QjMPthDD6NwzRbzlD0_fUN-xR7L5K9DzklyNw29ScvPwth-u7bt1MuurKbu_vBj13bItEU4vXNbd8P7ax68_rD6cVpKUUZFYIfhzGXPBz3HEOOkRQKP_RfICdGrYYw3F69TylVVeXHY1vZm3c3pPSf_dmPnLEK6fmTp_12_-rVKwnp5YtniPzt69f_zf_mP49jAJYf_fCzw-7w29999X_97_6V0rI7-s8__jgBEul__7vX__Sr39gctXFf_OEbhfOzw_ZGCw67zdgP7cnp8uRcW52myVZVYThutoDQ7_eziwvbro-7nbHW1t2w2XeLWThuUCEZhdYpIutMZV2_3fSbO0VyPPTtYr46vQCQbnVy3ByWF6fHwyicdFWX4B_aOWgUF1ZWA8AD-h61EnlQXYkytkjClKvZEgkBFEtRlctjIChAqkyjra0wG1cLcki56pZhjCgMIA853EOmArmYuibSgECKpHApDILOzXLyMXhtjHDOOeYYueQ4xXa2klIYpb-_Tykuz59yys1yXlIUEeWsQso-MfBDdE6KJBVSxIDKGpCCSgkIiJBWRChSiEgrxSmVErkwmcq4ppSs6yqHSEQgXFKEkpVWzALM2j643AuXYpoKQR5uQliE8yCCKFJyJmWUMQIgUGzlhNkoQm0QQVe1sCAikeaUq_YUchBOkkspBbTSlSWlU8hKKyClFCFk4SIxCBeRAoWaxx-JlJjGuPsAynFmZbStun6_b5crUEYUpFJIaVPVKUVG3a1PEEmK1Otl--i0O1uNu0O42yFSiblkkVKMs-N215ydTtsNaaVdRaQy53G_B6VzjM1iaU01jD6lqe1mKQdV1fOzixQClELWAoh1No-eS5ZSEEpJ0rQza7S2tbImjr0wr87O4jQp45QxqHWafMo5hb6ezdI02bZtu-Xpo8f1fBVSOXn8eBiTc7ZbreqqrmZt6oflYpH9FKajqWe2rpi5FJZUSCmOGSErKKWkAqIUIGH2SRsrjIqg5FCiLyUJkVFKoIQplFxEEKAoZ0VQVxUJFy55GkphjsEH354-amZzwVRy9sdeUIrPqpR43I-7bX8Y25OFQnz77WvXNCcnZ8uLp9PQFymj9_PlQttqd7ddnp_Oz1amqgWkxDJbn1w-e9F07XG3yyW36wVmLrn4_n6-WsxOuzBMBJBC0NaWEi1h21Qx9of95ub6Xlf1-dlZN5uN_fa42477AzOM-11Xt8fjPo7TH7_4fjWfn6xO98eDq-pp9Cn5rnHTMAz9GI-DdXaxWhjUq8vHVdfcf7gThtlqHXNyTdN0te-PzrppmowxTdMKkjKaJSOqdj33Po7DOF-fZM45se_z4uKUFB22-3EMyjkR8cdDf3NLRIDiuqrfHdePlsLRWB3iFCbPJVXtrHhfADjHHJL3IU9TU9nh2DezWlVmd7-1zmijnbVGkdZk2trWdc5cL-clF-byQJQjpx7uJpVWkAsPARJjScWHFKPkYsiAEmuVIGpU8-VqPO6tRdfY4-7AQm3XLR6f7W43JGJdkwIvF8snL18Mh-OLTz_eXU-vPv_k8aOLaTj0u_704mR7v7XG_fDHf-b9VFmbA__yL35qNTw-W758eqGAG1cfhoMo-PEPXp3Ou3ldEeE49NqqHDMpZMFvP2yUMjFz1bS7fry92yZmZ1sxSKQ-3O6-fX3tY0lCt_e72_1BgXl3cw8gYyl3m6PP-e7mMIV0jDFg-od__DZL-XC1u7m-H0vaH4bNZtsfxv4w2NqmXMZ-ICA_TMd-Utbsb-5TiEYbQtHO5Bhd3aYYh2O_u7rNOQ-7vTYguoRx4hR0bSRlV7mH0uLe95v98Xo7dst5M6-nUorigTMIGkIhJMSQCyfJQgqdImMqGwtEKIv5zLTO1fbN7eHsbPWrb9_MrPmrv_j8D199qOoqUeFStNI5A0MxtVs9Oalm3XCz1SVzZj8O4mNJ0TZdKeKHnhAO93u3aPe3W2soj1MZPYIoQzGU2WJeStZkNemmabkwK5VDkMKVswhUYpaSS84PhaySmUDlnIUFALggi7CwtSbGSIpSiA_MVtIKCGzV1F3bONO1LReed52wMPOfirWk-nEUlhDyejm3RLXWtTPGqu1mf7cdtFKe82GYWEhpKgDDcUwx2coNfT9fzJVRMcdfvf1-7Zr7fX84jMYoUznFGHPumma5cGh0yjwde0Swnbn-MHbzarfrYwzH3Tj2fnk275q2CJcpH7e-ba0z9mf__EXy45svd4cQZ4v2-cfL08enGNOPfvnp_u0dMI2H4-OLCwnhr3_-eUf6b3_2g88uTxWX2-u3P_vso2XXLep2uVoYrYxzx3FKKSRA7VwkDDFtjgMjxlzQmfliVmtdEmcot7fXl6ePWEQR7Qe_C0Mocj_k1x9u2Zg3H24HkLf3mwnw23dXbCBrEzIHTt16FkLa7Iev31ztUv7os48-3B-uNsfNrh9TIk1Xm913V9uqMrPOXc7Ur9_tv7vfNGfdN3-80q3dT9N2DKz-_yz9ya-sa3afia31tl8bze732ae9_c2GzEySokiRKlFNqaSyVa4qo1ywRzY88NQw4P_F8MgQ4FHBRsGGyoZLstVQFCUymWK2N2977ul2F93Xvu1aHuyMWSAmO4CI_b6x1u_3PKKPPim8vr-_2e6_nbuqtMdHrdSyqgsWOAWXctSVbFbF-rgpjB0nZwtjJJ8cr_rD8N_88R__9Odf7rteSNl7t73ZpZT9OKcMsi0hJPIBKd2_uikquz56NNz2D_3CclUTpXl2uiofTEGmQDS6Xi3On1yxkaatPIA9XsrKxuSJKMUg1polY41olJKQ5oQElEgiIhP5wOPMKSMiElAmBsghCOQcmfWDGiZBYpgiucSTk4ApzMraFBMKfLh5qarQdcFW6aaSi8ouFuXpqu96F2JMkHxiAKm08D7PnnzgEBEgzxP5QG6mFDlS8jEnyiFRyBAyuQiRc0iUKeeYCcIQBHJ0EbUSUsY5Uoa2ae7e3i1OVpLBKLXb3I_jVFh18ujRPPQiZV2o_WF6_Ozsd7_73cvLi6ePL3OMm93hMLhHT85evXm3KNovf_3q2XvPh3nYvLsf933Ttn502qqiKBjEzfWblLItVY7RDz0CFFWVYsRESEjInKmoim7XbTfbo9Ojl199c_fu7urJo8jpycXZz3_51VG9aJdH28N9pPjNt68E07OrR8-fnu9vtim5oimbajXMYz-Hu-2-NPzk_Ozv_9HvtYtiGLr_77__5X_4y5_O--00dq_e3tDgJRQtcVYgyuNF8pFzHiZ_8eJjXaquOyCx0spYE13ymakqjBA5J993tjbZZwYtBFDKPnhiLKvWuckWZXJTil5K5eYBmX0KuiiFNqDUxdPnIWUldAoRmQgoz05oG9wMxCiQiYRUDKyrBlNiiuBDBkjEfnZC2eAdEKuqFACcssgEOeQ4h6HT2gqjc6bm-IwFJBdzjAJBKgWJGBjFA5JfUCYpFQoCBE7emBIRU066KClR8gkoSEljf2CFzfKRrWoUMHUbRpRK26bOKc_9qNtKaZtCkEoBMD74KohRCo6EKCgEIGZAABRaY045ZmHNw0sMBIjKVCRFHAZbFczMMSmjOBEyKSU5ZaE0IOqiBoY4TggCtaEYWSAKg4mElsroTCy1FlIIIaP3D1JklJhi1u2SmYVSSmCKOcdZICNKigEFkgukBaNURYEMTJRS5IwCABGkFJwSMId-q8oCQWU2yGl5_sgPXY4OEYioPjlDo42tcmY_h-NHTxjZz3OY5-XpRdhvp02_f3uXKUNIR6dnUgiUENzMObNR2bnmeDltD0DRFLY9fZSjQyAEnsYDaquVmceYRNS27bs-ZypX6-b4LIeUIj2sXB6czUJpFDJME-XY7e7nfjC28LNPgVPM0zAKKZUtCXlxckoxr8-vyPXOOVM3ZdsobcqmRoWL1fHdzW69XBstu9v77m5rCoEsxm7PKaBVLKAoqjDOCFCUBSeETAiAOUcXss-c_MN9vj5fJBeQEZRMLhJTeXQklDVloaTglJiYYkjB26Z8sFgUTamVyIjjYa-LQi-a6vgMrZq6gWPEnG1tOUeiiAjt0dF6vbp7-46lRMznF09R2aIs-90AzE29yDHEgN7TJ7_z-93mrizrQlfHp6fri6t-cCk4BClyyinGGMbDoG2BAhmEVGpxdu67KUcvJCQ_S0Xb29f7rsfKHF89OX76_uriJAzj_e2mG3Zz152vT68eX2xubwmVLkpjrJuH_eHg59lIaYpivVobK3eb_fZ2d3R6DCkLrY4vrlhy07QUs7FyuNuGlM6unrppAoX1simXTQpRGX1yeU5My9PVzdu7k4vHKaW6LZMLOUVV2aOryzCG88ePYpqB4ejyErWSApRSAlJ1cvLuzbtysVLGFk2b3EREWqmirFcXZ344MKOxMobEmYCxUII9U85C6pBCf5hjzoi5bBtKSRemqMvV1RkxJZ85s7QGAMu6JspS4cNXqFzUKKRAkVJ2c7Blhcz7u-3i7CT5JJRuVqvKmAfN-ZP3XlhrqqZumlaXZnt765wrWkvIgrK2lDNICYWVbdMAQfQjcwzev__eJXi3tOb3vvfeoigqqxBo0RaPLo7XVaWFaksdnDelFgxCqZDj59_cSKtByevN9uBmoYSxum6Xm66LjDf3u36aSMh919_tujnyTd8f9tPNppv8PMc8p9jU6uBCN829C-MY7voDE9xv98MwOue2dzthtPczAofobWlyzjH8pn982Gw5R6bsp8gowhxNUbZHq-72BhB8DJRzphxml3ziFI0xafJCYXApZLDLpl2vjx6flo1xIZplWxhxf7fd9MPpspJGz5kjoVZCapsyW2PGce5GNwWqStNWbT-O-_14umw-_-VXP3zyJDAPEU-fnb-6ufvdv_8Hr7-6Vab8R_-Hf_If_z8_u3xyPO4HjD4PQxqdnyfJSRtRrFa2XShttJLzMCzXSwby84yAApmZwhhjyk27YCbv4kMhPLj0G1hczkrJFAMQIQDlqKSMLgihAFgAppxyIkQgikopKVUOHqRkRIkCQSmphUSg7Gfv-wkhG6sz5UVd3N3uOXEiMkbudsPZ8ToRHy3qeXbTFEBIq_V2PwhlVifL_dCj0pHZZ5pn70OoitLaApWoi8q5kFPe9NPVYmmsGX2wZWkKM3Zumn1TNzF6SvnbN_d3h_00e6GVLvRyWRtrRK2kVP2QTk5WkMh7D1lIo84uFquzZfbT9bfbl5_ft6fN-eURpHy8Xt6_HS6PW7_dUyA3hD_40Xctx6vV4sOnp5--eLxuaj-OBuHp08tSWynFMIdpmojZFqYbJ2nUfvZDTF-_vf3y1XX2NIeoBJ6crzHTclG-e3XnKTx78kQoPfrYj-PNof_63b0oy_txuu-GfnasxbYbyYp98D4zFGYOnpSy1goglHKa5sDkEbxEL9hFN81pt-8JEgkcQvruk5Nuip-92rxx893s7jY9FHKzObhEvZ9YynrZ3nfdMM3amnVTM_DrfW-1yZgJ4fZuEzOxQGW19-lu16MSPubT4_XYz9YUu83ts8tjY_U3r19dv92g0oxq3O1tUezvd7q0RVkmxKPnV4uj1TQOlbUxRGmUZFm1ZVlVrvfT9gBAd7f7MWa26CUqo8vHR9c3G0ZQR20Grl9cgkgkFBnIU0jdnDGjQVYCVOZMRiMiPMQdOQEiyFJiSjRHKY0QnEXOzEJJhCQAJDBgxJTJ54TAmITRIKVuK6GUj0mWhc-RlWYm0IpjYsqQIhKhTDxOefJaCQ4uzSP5WQIIJbRASFHmhBRT9ExgpMaUJCNS4pyRKOUsiOMUBSAjCyk5pqIstNG7d3cSKU9u7EYlsK3qRdsKLVHi1dXVxeMnzz95_8nzJ8v1Onq_3xyuN9dffPESrQ6Tu7u5Xa6WX3357fn5qirL4CbOPI3jerXcbbdDP7l5Isqb65voozaKKffbnUas6xXFWQqptIp-zpTdNAglhn4M82Ss-e4Pv_fym9cCYH_oyqZets2vv_ji-nb74tHV7_zgB88vz-_vNpv7fWBerI7evrrpu3G3v_cRfvbTX2GGP_zDv-Hm_Nmvfvn667e3L6-vX70SSEqX1erk9__-P5FYLETylNCP0_r8mQQ_u6m73yQfji4fAedqvUbIMSVEUa2W0_awPDrKQkQ3N-uTME9uHpQpQaliUQkAU9XDvqvqtUAiys2iyilP_cCIiIDSlFXVHp3N_aFqm7EfldFoDQJhSsSMiEorpiy15pRMvQDKQipAjsHJqoTshSlzyFprU7VSSEoREikpBXLyLs4zJM451suzYrmWkGOMyQWhhACg9BvqMiIKKyFzzkloHZ0DQKkLPzptC6kE5fRgKeI4z_1eVJWWRVWvbKmn7tDd70xVIZAfB0BhqlogSGtzIhZAiaUxAAxEsjDADESAQirBnBGBcxZCKVNSCpRCTLM0JUoR_ayEBERgQAZmRiahZHJOWht8kEIoa0PwD0JZZFBKSVVwzpQTIzIjKkGJAIBiZiImTikDJMhEjCmEoioAiJEfCE3yoZ6cWaICJQGElBqlFFKjQGlUnAMKgQI4pRjJVK0tSj_32c12ufB9n1NQMofddh6HjMDA7dEJSq7b9fLoVBVlN0716kRV1fLihGNECVqJnFgAHL_34eHdO6lt8ikxNYs2R59DCP1UL0-0rWJwCdjv7tVijYKMLSgnaXRdF3H20fujJ08VKt1WAiUDNMfHKaTE2CwWMQQWQhfaaA1IILLRZeRoyyrlgKBssyDvx36bplAasb1-e7g7LM5XQmsEpJzPLs6UlsBYVQ1xdn03jT0ip-DdMNVtK7UGlNqalLIUulqsEYkyMIOQCEJx9EKK7JK9Os1z0GUlBSQfmVhISQlQyId5CefEDEyZQpYg0cjkHMdYNdbNszZFTEkom0IyVksJcY5V04Z52t9uEnBZ1d677d39YTecPb4UjIuT1fr8ERbl-bMPh3E8Oj9BJb_9-uuiLne392Vh2tVxVRQnV8_22ztiBkr1sqEYUgqRsyqtKYrZJUqpXSxNoedu8lNUSGXdhLHjee52e6SUZnfx-MmzF8-bZUuU3755ff3mlUTlohu6PQpcLNppni6ePOkPe4aUQqqqdrFeAIJzUyLOREogGDMeDkKaxfK0bBvnUwpj2S7dOAvWHzz70TjdD4PHDCiUNmXRVCnF86tHAqUxdVkVJ5cXYRhDymkOnBMgjmMnQEppPvjRd6f9mHPKBFXbRDfkGI0tTy4fa636rkfBDBCJo49lW8bJQWKpNWNmUNM0FqVWMpvGkKeqqqZp5pyruqEoNJrV8qhuqpRISpVyUsb6OaCQAOh9atdrN_SAQit5fH7s5xFQEmVbFlKo3c3tYrnot31ZqJxJCFVq9f6Hn97fvm6aer1u7-83P_qdH55fnIxD1yya7e39xdnJ8ngV57Hf7eui-l_-b_8LM_snZ-uPXlxeHC1zjEVpgEgJYZRGREppniYthLVGK0mAc6bP3m0086YbdocBFKxWKxQyAx32fZf8ZtclFi5w9ImN7L17-eraWi2NLKviZn8ILuzn-TD4zjuPeLu5n1zu-9GnOE3Dfn_QZRFzSC6kxClnYEgx1WfHDCm4OBz6oq5SZlkUTduqQqPk-dAba6rFUggUSiBwnLzSkgGUFqjV2PXVqlZWgRBotAA-uzqNCeI4b--7l9d3Oz8cYk5aqcqGmMpC17UWGj1nAIAUr9bli4v1i5Py6rilwJfPj768O8zCbO6GdWlOjoqvv7zLnn03Pjo__upf_7TfHQSHMEdhMU6zn32OZKxiNLJcKFVIbZAIUUDObbPMKUqr586BRF0V2hgCctOspEREZgQBOSbOmUISQj4M_lNwiIAMSmuCDEQ-eKEEsKCcjFacWTDlTN4HrQQBeedEobQ2trAppdJqJaVQ9tOPP7BKShSRSWtDicvCuuAkAAEySJ_I5_TuvptDjIkIIoC-380ssDtMkIkQ4cHGgqAESi2l0sG5o9WirovtMEvB3TAjUEiRcqirYrkqRaG6Ljw5XR6GqACXVZ1dfnRxvCzk-Wn7-LxhEKU1l49Xzz89SRNN_VwqXbfF6dnCKi2ApzkFz6fHi09eXPox__Fvf_TDj6-OanPc1o9OVwoRADMDSqGsjplIwOD9u7EPAr68vfni29uv3m023bTpRpLixdPH67atjJVSLI6X3371utKqLW1TV7YohC273XjTD3_-yy-_en2jF8tXr2-_ff3OEwwh_vTLb2POzbo5xMAot31vKkvIbnbzFJm5XTZFqT1lz9yNYzdMg5sTZ9R8GFxNWJdqGMJudPvsb24Osw8ghUsRJJtSpgQ-xJTTw4pSICDKZVvVi0ab4uZ2mxmRc_ZZKqG01qiEEHVZIuCrVzdHTXV1vFI6vHp7__PPXh09P9nfH7rdVmgltfbBl3WTcso-AGSUVhv77NnTfti3hYnBx8DCaCERBPgUqmUpkVKKh_uDLYu3X765em-NIPOcfDeDn5EhhsRTemAHMwIL5pxBSukDzwkyA4icSTAhiuwTBBZGZ0E5RkYEFqgLhASZOOPD8J6BOScsJSvBwMjMikVtUaAwkogosTKC-i51e5wGcHPuZp69lMgpoRCQEhL9RjeUCEIWjBwzBwYfKHQpzoQglGLJyEKel7FzRiMzCauji3XT1KvK1hUEaNZLo7VWmoVcH9Ux5ffff_7xR-9LgUhEMWOJv_rpZ9fvNjFMwYdD10OKpbW7zR0RPPngSb_Z3757F-cgJFPO4zjlTChZSTUNh3kYlEBGim6ah6lsqrnfM1DIrt_ulDVSqHEcTFlIAUIpjXr1-PTu9Zv9_V7X1cmH7x-2N9dv3lKO3__043c3Gz9Mi_XKNNXt3e4Xn33VrNsnl8_q4-bXv_jVm9f3__h_9g-Sc__0__J_d0qPkL_-5isjM2p9_vjqH_z9P_rd7z-WbNZK1ciMGKfdbU50fPEohaiUPNzfzqPLcT56cpW9H8dRCSOMPH5-VRZlJB66vqjK-mSVIYtM0afm6ohZ5RT91Ftd5ZAAATgJKaf9AQW0Rye73f1-c0sMwc_t0dHy4mzqhjSFZnWag5dGMRFkBiaizJCFVCFGaQtdaFMWwXkUrK3kGJlTillo9dBiBWAERCmM0ijB5xRdVtYoU3AmoWXOBMyUozCaAXLIsm6BMYegrBYCEFlZnWOUQpSL5bwflQYgBqbk5kSZFUo0Zbs0ZdPv79bnTwAfwKDWTVPRNKgVMwolk48IKKzJMRKBeEj-E4ES9PAGgVFIYbRUSgiJQiptQMg4z1IrSAmAHyoQlKKyRZxnWxYMBEIIoZJ3KB5gRFkIFFLElHMGrQVkZsSckjTalCVRtnXthtk0ixwTKgRKiEpUZeh7wQkfPGxEgiG6wFKa2kipkw-UMgBIa-IcUClmUlrPvSuPz9iPQJRDLtfrNHbZB-QEwNmNyOQOu-Tn5Gel0VQ1IzCyNHo4ODRlGHoU0mgzu1kANEcrillpzQycvZIaE-UUOIbI2bTVg3gt9L0szbzrdWmktpTo5PKJmw_TfieNEkLoZWGLYndzV6zWLES1WJq28W6KIQQXTp486bb3s58fMgYUPUfHlE_f-8Aftjn66Kc4T2HYd9c3t-_edv0hxlAtaiJB5Hfb3d2rl03TxnmizEdnp9HPEiBSKuoFAWZGZhICow-cWUhUZYFSx5gokwTMBycYMhNlsE0lEHL0AMQCpDXlepViVFpxJikkUU6zE4CQU3Lez7MuinbRKm1R6GkYYz8uT4_G_b00GhA0Cl0t6vViffGobtrPfv7zjz_57uwmVZdN2w5zd3H5uGnri6v3itIu1kdWaVJCaRXjPMz7q0fPGWF7v0s5CmWJQZXFcJhNIZBzDt7N0xxD9WhV6zoOU_JOobTtIoxdf9i5cbp-ey2s1LaanGMQVV2N076qq0PXX1ycphBTSq-_-SL6CClPw-ycV8a2qxXFHBIpaaSSgNzd79bt8WE4GClOLy4Ukw9heXQklRj6jVTy7PnTlIKxJiSKbm4WKy111x9yjkCpWbXb27tm2RRFYUw1z70ptB8OkEW_O7TLRqAQxIvFKrpJAecUD7s75yerDSolpFDGRAKtCiI0SmSQD-V8g0iUFJjpficQhq6T2jx976PhcBj7vRQ0dluQRJwe-rWqrBKgtkXR1lVdxxAIAVFdvff4_s3N-ZPLlHOK3A_zqmmL0mqpytqujtZE9PjxZVnZedyvjo_PLs5AwaKq10drCMmUmpBarS_OVhLh_PToOx8808quEY6a8r0n55enRwpIKSkEIojELKRmTvfbznlf15ZR5UzD4G8PQ98PLtK3d7ff_-i9o3YpEVKmnNPd3e6uG1VRvX57_fb-fg55N01ls_ji-raymoVE5J_-_OvBx6-_vZ6j3w-jrKqbd9eIdpjmse9zBgBMlPzgOVK7bI3R0Qfvop-9LerxsH2wfemiLgpDOYbBz8NclDbGyEjEmZhzCMgQUxbCSKvrdtleXVAikIgSISc0KjI8_9Fjq3QI6fRydX6yPDlaZsSX14dXu93boT_0bs6wO4xDyt_uN99O03ZKX3dpR7JV9HqeG21y8KPr_s3L27dvp7_3n3__5OiYoviDP_mt15-_-sO__bvvrvf3NzdKqjB4VShBSReFqpp2fUrJubGfhhlQMoWUoi0s5bw-P60XNWVul8tI5H1QUgpErVUMPsWslFZaUsqZUgqJcwAJiVgJnXKMMeZED3MzqwsUGQAzUybSSjCRUAolkielZAieUk7eA2JT1zmG7XZfVfbybKkVdsP85npXWK0LtZvc9bbzMWuDb263h3769uZQlsXmMFwdL795veFMWeplU4YcNcrhgU_KoLREFAKhH3yMcV03hTHee0La7HrQKiblUz5ZVBH4qKqNko8vTwWCZJwmDwSH2S3aQmaolXn37SHNvtBGACDLH_zwvbmbDapHJ9Xf-50Pv_fo7LTWP_zwqiqURowEhTZGYVkVPsac4e7Q71P-qy---fp--66fN4dxP8SYuWoqiTi6UNbVomlmH7pDNztfFTZGL5Cfnp3vt9tFWerC-hD_4q_--ucvXydl--APo-umoa6bzdjd73pr5cXHZ59_8c4zRAGoDCPERLN3yhpAkYhXJ8ebbp-FvL3fM7LUqjlutrtDIeSPfveju3eHpIrP727mkt5e7wXyME1lVZ4cr2NCYmxWth_H6EJRagQRCYkg5yTrvL0b9rvh9Hg1DEPA6D2dnpwgg3c-RX-2WBQpTNv-__bP_m2zXrLGb756FUJcnK2bdTv342_GnVOGh3PNx6ouu2mi4P3Q-XFyOQ_TLBsTZ__Q4GIkP83VQo3X92kew24etp1WiMG5Vy8Ta6BoSgVEHEkSwBRUJOGiCIQsmBg4Swn0kF0rNCpFSEIpBgbvERDcRCEyMmjAHDkxAAklmIjGgCHy5NOcSOTUTzx7mGeY-nhzR-MkE6kMgjMyI7EwRuiCmBCkQMmZIROnIJFBIDEIZaRG1AZZYqLcD0LrNHoBnPuAIkeXUKuirWhMi7rx3YgKrp4_KYx98vjRe588Ozk6XlbVYtn0_fwXf_aXh12HSF__8gt28fhqOc1Oap1m76bRTUPKTMSKxf3trR97ZpZKolAPmaO6agRyt92WddVvNijlcr2IIeXoBFP0LgZfH7eYeHZz2VRF2dy8uT-9OD95dP729dv-fiulmA7j_u27L7_4Okb5yaefPHt2-euf_CQp_c2767fXd_tu--Txk4vLs2---mKz2f_wP_md3_7kg5_-5Mf_8k__4r33Lrt5ePXFt_N-Wpyd_Df_q__2O9_54K6_-T_9n_87qZcXLMWDZESWKiY3bXfOhaJtCmuL0lCYDtebRx99CCCG_gA55ZCkVig1liXnBGhy5NMP_zB0r-dtrM5XMsHQT2VVQsoowU1OqtIWcuzHHFyKM0SXpgEoITAzKGliSpzygwwAEAUKlACZiUEWloljDFIVMcbm6CL5SQhAIYDAlCUgqLJKzrMSCCwYgFlpXdSlLUo_B0IGEClmzlHZAlFCzoIAlcoxPsTBc85CCMrEzAI4EyHR8snlvNkDipxJKeDgY_SmtGM_WGlNVXe7W2ULNzvIUVc2zQEREaU0RkqlyhqV5MyoBDM_9IMBWWhNiQDwQSAPCEyASsADgwM5TaPUGphRIhCBkJwCCIzeIYC0VjxIiBE4xYeScSaSWnHyQACIui2klJmTFFJK7boDM-bkbV1SDMwMCLZuZakgJmRQRmcmQBISU8i2sLoshVJMGQUiAjILicACmFCK5KZycRz8AIh-HMuTK8E5uKiVIgbKWUpAiimMY7fvrq9RKE5JgIoEq-WqOToOzgEQStX3g-sHZRvKQUiRAxX1goIXAjmlnHJiVrZsnryI41DW9dHliR_nOHmhxXTo534QjL4fU4yHm129bnPKlGhxfOynKcdULRprzbjrg59XZ1fj4aC1LdtKMDjvKHN0rjk7Obx9Q8TAQCkiJcwJIQQ_3nx7vVgdzdPUVCtbFtM4KMzVYjHtu2q5RiX6fUeAtml0WTDzPDtlSxCCmIkIUAgthNJSSlSoQGZmYOSckw9xnnOMwFkrIwGk1hSZUWZKUkpAEAgADExAFOf-cHsrdL1Y1M1qPQ5d9A5NkVMKXQcgh34UWsfgjTLaiDevvrV1s2iWUgAgHp9dTK5vmrpuFmXVLI6PNnc7hli2rev6zX7z7MNPjTEksazbaXJGm7LQQ-dTSkWziMEBQDw4cqNSiolFaeduOnr0QmFIPrixHw6991PdtmVdTNO0ud8nN8SYd_vt-enparVarJZ93zfLVims6hIAyrqOPtTLRfDD5s3bME1C8bi7Kar64upyt90fn52uL58g8jTPKOQ8Tker5YuP399sukdXF1IbZEIBYQ6oVNnUd2_fnT56jKhTjpkyEUTndVWtjo-MUcDy7OJ0Gqd-t6vb1rmYODPRPLjlyVmY5mk_CiOASRVKa2kqS1ooW68eXyBHyDnHZOu6aEuUmGOexz1IMfdTyCGGmDMysbaaABnBlgUTo8KpG1OmsqzaZfvo0aUbR8705P1niEpr2TRlCuHoZK21ZWapdVHa3XbLTEaAEIK9__73vmuz__znn2uBf_uPf_TB0ydnpyenq8Xp6eqjT16sG_P-0_NPPniRopcoCmPHaZ5nh1odxvluN_ziy7cZcdf7RDkxMhMoMRN3_TS46YOnV3VhC6NC4JvN_pdfvRwjVevlVy_fMKspxsMwbrvJpfiQKn9xdbTd9Gzk16_ejDlASqjw-uUbo-zhsI_OuUiJY3lSc2ZKURcqI88uCWsTkS1sDl5JRBT1alk11bzfvf3sjamLZr0aN5ucMjIjMFOmmBAVStmcLYRWgBqQfIg-JDRCKjvPuWoa50KKqVxYLeXd6A4uFtI8vWoullVrZdnYOYX11fr-vl-17ehnT2kIAVy44XDYujf7SVlxerL44GnrhH97PYkCVk_Wb7_ZfPX13d_5nY_GOe-Hzo0DSUw-lqvlPDrTtpzy0A9pDCjAGAnMwc3aFFVbe--UlMaYlFIIKWWqqspNjiGRTw8UCsqZmWNOHL0xJvrIGRgQGQBBKuSYUAgQzJljijlnKaUERQkApQTUVuWUUswoJAPYuqiNOmx3zvvlYnG7Hb_4-s75ZI1mwJvt8ItfvclEGeCblzfbwzyHIBT4Kc4-O5a7bhRCff9y_W4_jr0HAdbonIgBqkoX1gDzFLwCJoAc0hD9y8395bptbFlJ8fhk2S5qIq7rsmnLB4gyFgCMlKNAtWgWQgrKpI04XzdPj-s_-Ruf_vCjx0dGfnB1-unT40-uLoqy1ELoQiFBN0dV2j6zl_TV9e3L-_2v327f7g4vb7vr_SGhIqF1WQgULoS2bQMlQFisWu8CUeq7Yej6nJiY_OxjcGdt3dZluyj7fffrl2--utlWZ6u394fNdi8L3YV5sWi_vr7RWld1eTjMQ04T0RyIrQQhdsNAEqu6ycTAWBX25rAbZ2eakhEohkPv3eiVFFbYfvBv-u7N3fb69X3XdXOYMvkSFQupDISYtnd7kAKNZAm7g1-fH4HANMdxDM55pJRjtNZ2_bhoqmEag_c5sSn1q29fldZcLY7btt4N4-19X58uq6o-bHfBB9sWu-utVEIKWF2cvH31LmU6f_zIjZObprKoUWLKqXNDdElUWmmc-0lYFUN2o6eUZEGhH4Ey5RgOk2paqTL7QJ0TUiElIWTOmTLQHElLQgaBwkjOEVjI9pj9pFGiUA9mVIgMedC6AMgAgDkDAYIQEnnyQrAQAlNEzhgDh6iYBQNNDlLmyaMQQiohZU4REsWcMnNGZimFUSglGA1KMDEzphhJIUlIRDllamqpEbXVRtOcwCjJsli0ytjsXeynom2NsHcv33308ft-nlOKMfN3Pnjx7bevvv7mm7Oj5Y9_8tlqfXR-dfXVr3-9vb2XEkUUm_v9_mbjxp1CDn4kVj_8-3-0e_WuqHR_f7Cl8TG6EChnrZV3fXd3jwhAJLWU2jbrpj_00ujsPeUspESQlAkEamXnaTo6PTm9PJnGYdh14zB5584uTuLcO58_-q3vPH7_-X_3T_-fkfLq5OhnP_vs7PSkKIsnz6_-H__jP_Mu_9Z3P3z59bcawbv0D_7e73_88cdGwHc-eP-P_u4f_I2_-Z0wzf_2X_37v_wPv4qHTtaXj6VSzCyMoMELzsgJkk_zFIJXdauFiSET6KHrtdXELEAvz87qo1Xw3vm8qhufBrd9K4pCCiFItSdHybmQc71YxnmMLqToZWmlIAgOc4qjM1qvL55M-41Qql6uY4g5RZRKAAAguSC0lVoBUY5ZWS2VSc4LpVPyEsUDdAUYmEmagon00QKFzp5QcKbk-jG4qSqq5ugCAEHpYrliIVJO8JCe1FKiAGYppRQKCDllAH5Y5kqUbu7JB7tqODEihn4QSjKz2x_q1XKeJ1tVqlwyirJecIpKW6kkABABEEulESk5L7SWhUap6eHjKQUTCCUR8GHGTykiExIxsSxrlFJoDUQPVmCptQBGlMCg6yL7ADEJpQFAyiJRZiYpFTCkQOVqrbRKMdIUiqOzNA_B-UTZFGW5WAKDQJBCZReIKU3eVE2MEfk3_uKcGQGqqo6Tz7OL0aWYU866rqSUOQYmZoFSWylV8I5SAorM0W_u0EhRa4EoZJlDKqoGGNknihEpQJxjv4-uV4K7w7ZdLo9OTn2gR--9L7X2KUc367KUAMQ5dgdgyBGlkdViBRzDPPrNXdXW_f0mx7x49Hje9e3J0erRRVVVh82uahttCxAcprA8OT_c3PlDn4MTBOO-X52dKSVTypydECp6Vxi1PL0MfgzTFFwwppZGxmm21kgpBBIn1hLLZSOIpZW6LKMPILCo6_39TlCKk8sp5JRs3QoQ4zCtLx-VTU0sRFnWp1dCCBQyxQSEUilplJImREZiWxVMEZkA2ZZWKxWmOfrZ1g1IFMcWCShFZEE-CSlYghSIMQopgZKPuV4fr64u5slTJq1sUZaXzz5GzPViQQzE-fj03FiLgu9vbnVZLlfrX332i7Pj89kPujCcsxBwcXae3PTmzZsnz56__va6GzbHxyeH_VgW5WK16vdDu16WZZECSY1SGak1UvaZdKGQabrdSEzz_i65gJTLuuU4h2ke9jvURlXFYr123VAVQiC_ef12fXpWVQvSRQjJaF03yxTj2PeHfR_DDMxFVRtjTFGVi6Pg3WF7EFIVte03mxh81TZXTx7fX29Z4PHRIgderhaIjALbtj0-O7l8_vT06qy73yQ_2qrKMbRtfXy-RoIwu6IwOca5702hpBLD7rA-O_IuHJ8dN-0qzB4ElbawpQUgVVtBWFWVGx0mbhbFdL9xbkYpAAm1HPuhbFopWRDnTKuTE0iEWhltKGZkJBJxTIKpXpRFXdR1cfH0MicuKxuc00rf3Pabwa3W5YeffjDvNobti2cnf_tv_qBRxfJ8efv2-vx4eXly2pTm7_z-D5qqduPhw_efvnh2_uNfvH5-tTpd1E8fnZ4cLazAj9-7WtbVqiqRskA4PVoCckyZgO8P_WEOu9FthmFxtDzM41evbjKpojDO-Zfv7iUKa-3zq_MY8jiHwzixVJt5Nm3z2Rff3F_fzTmOztdVoepiiq7bje2iuNtN2ceiKWbDCWjupzQFSsGHUNTFNHmhpCpt8sn5WQgphBbWyKpShSqbQgkUQAIFE1Gi_d29NmV7vLILmyi5wygFx2FDAYQAYM2oiqNFZgRULNBnKttF0dTSKl2YTGL0rihFAiASQshCybayptR-ptlFUHbfeUbeTzMxbMfRtFZoySkfDkNhhGm1T-GXd5tf3m7eHcLYp3Utuy6XFVxv-pv7wfXjt6_u1mfrbuqTCzmlnJKyhZTyQX-ulGrqWkgUUo7dBBIpcb_vU8jMiUEIKZRQyc_8QIlmKOpFCFFXNufEKSghKFNp25i9JESEkDMnQKmYQVB-YLbmnI1WQiIgcsooUVeGmAAl5Xh0dsSUQcrS2stHj6bopjkVTYFSjYMbXfDeZ0iHfioX1aYbh2H2IW63nbYm53S_OXgXB-fe9RNmPjs5Zk5lYSEzAxbahBCVFIUpg3MpBwSqmrIR6qhtpZTvru9ditt9D8yrqiQCmchNftUUUohKK0zZzeOqKI7b8ocfPzkt8Nn5YmElAEgAI2SJaK1VUrpIU84_-_bum8PQKfrLn718eX0XGd_e7bmSAcgLEK2ZUlo1hgUM89w0JSG8e3VjS5N8bKrSKNWU5cXRibFYlFoK0Imfn51cXBxXWv-rn_z8v_8Xf3bweTOMADwG1x6vSMBuvztatuWy6caJLN8NsyjsYR5R8mbX6VI3bW0Ko1HVpZ1D8JSThMxZKs6RTCuUpWHry-Xirt_f3h-GGGY_m7Ls-uHs0VHZrKbRs9GTc94HrXS36zmTqdQ0u2HbTfO0uduffnwce6fJhBibyvjJUWIkEC5UQtoEf_t3f3h3d79cr68399M4T72X0oQUnYuMyNGn0QutWJJRYuqncRyAlSnKu-0GpZFKFkaP40APmWhkzjGnADnxOFDOEBLkwCECEHKm0UsmgZhTRhQMGY0GIWRtoTTIiJkgREiMKcC0k0whRAAAZlVKIZAmByAhR84ZEyMDSmBkgQxEmJhjJh8AkRMxiey8FJIJgIkikRAgWBYVmkIU-iEJQc5TcFgUmZMwWhglCoUgwEeZWeRE0yycyzkxAQMXRzXlaI3xuz0QCQCJ5vTJ4zgMy3UzdDuFJoH85P0PCOKvf_HVi8ePysVyd383zsPnv_5pnCdEdENnq3ba3yQ_4XwfMyDwYlF-96MPUYppmCjS-aPzbz7_xlRFUTd9t4kx1HVVnj8Zt9fZh6KtWcI8Tqa0YZqEkqooZFFYa_McbNtU9fLk9DxT_vaXXygBnKksi67bWlMdX108ff_5m199VhpVGE1AZxcXN3c3y7pWRnz46OmLi0dlqZ5eXP75X_zElMXZo5PofXLh_n5nyvVP_-pnf_Ev_903X75qj5dSJAnlOnkPKJCxPD5VoIiAU4-JUwxunqKfQ4rzbrO8OPfTXFS1VPjum28vn7_HiBnN7dtvjS0zUYq5XZ_4eYiTW1-c-RBcikobTlEpTLOXQgJFZDSlyTkOuztEjM4LZU6ffjRsb1CruZ-kVqgUQ-ZIwigEyAmAQdmSOOXIdn3CKaYUkFOOBImENpSJQZqqCsOEQpii4Bz81E27TV0fhZidn0y18H0HAihmRgDKWlsCEEJpUyujUg7JRQYA1BI4x8whgEBMVBQtpSiVinFKbmQB0zQgM6NKPhR1O48DCBDaUE7AxMBxnlHI6B0IRBSmrR-6AZR_03ZgAKEUE3BOSJxzyj4IKYAxEyOCVCrniCgQAI3ilKXSKCHPU04ZtRAoOVOKAVGqUiXvlNDF4op5Cn4CqYgyA3HKqigEEsVsbIECAEAAKWuSiyQQhTBVpbTMiVLwSmsUwEzlqqEQKGdgltrkmFDKlFmagikJgBi8ZFBGQM7JzYjIRaWNIQCtbLE4EijCNEFKzMzRI6cc5mGzm8a-qguhEVEWVQNSKVtM80zIqAVxVoURRvthopQEAAMIaUUpXBeBWAh6KAAAm-XJaUS5324TJV0Wcz-tL06FwBBi1dYuuHkYCWTTrpvTRwoAOMxd193fnj3_rh92lJIbB8oRpQCKSCyELpdHlFN3u6OUXD8pLc_e_yBPjgHW55fDYQ9AKCUxorbLq-dN016_esPM7eo0pogpWFPEhLYojh8_Gfcdc84ZEUGXOroZAYm4qJvggpRGWR1mD5QBhWShmyI6FoURCIDIxGp1ochHF7WRbh4CkQBpTEVKD5uNqpp52LXro-5wUNY2izYTrE5OElNRNxT97fW7xWLx9s2rfTf5aS6KylRWKlyu1rouBjc9--iDqZ-LUmuj3rx56-O8ODkNOTdtAwJzzsQwjEFKDYLmOZjCrs6f-H6PGgUKIog-NM0pQCyMpOghs7WFssXc93VTKS13d3eJoCzK9XpZ1IvdducD16vVar0slg1TDi4__egjVDhNU71ctSfLtq1vXr-r23ocx6fPn9dNc3x6evnkQoL4-NNPrq_f7O_vnzy-7PtDTmnz5ra731ZtnUL63u_91jj1hRCnJ8dVXVMiAjg6Ok45IIpp7E4vLqZh-s7f_MH-7U23OSxPF1M3pJxMWRDh4uh0HgZtTUrcLpp53xmlmOHy44-77S7HfHR6HOaQPZ189B45Nx2mxdlxGCdjkFKgkKtlLRWilKapjDa7u361WpR1cX5-KoTIKbeNvTxZxGF6enYskvtbv_vd_-zv_P6Hj86fHLWPLs9UWUAKb-83zx6dXT299H784PmTs6PFk_Pjv_XbL06a6mjRKKtOV4u2LiEGyWALowGrssiUXUqdj3_1yy9e3x1mYZOQU0oxQ8xpdOPji1MK9PpuY6wdJ1-VhbX23e3ui69fJeQ50xTj9e0GUUx-FiIJ4vbs-KtvrmPk2-stIo-bzo1jSOnk7HjqxnFw49w3q4WbXBKg6iJSlFIgAoEwi_bq4xfVerE4XSFCcO5wf4_A0zCmzOfnp7u7u-TjxcfPUkioREwJgLRpc8xKKUZtmgYEkhKqtEqbaXYALA2iFKClKFXgPPkMSletqZZyBro7TMERZS4K7THHzEHhfnBCiMT5q82t1lJKXbRFtLC7n0lxUSitkZmwUntPM8SvvrmZptnz-Py3Lj769PJ63z39my82b7chRCGEkqZZrQ73O2LQSmmjpr57sLo8ZKQLa2KcASDFXNarcX87HaYH4VqMWUhg5BBCTgmS5xS9jynNQioAjjEnJm1tSBEl5pQZAQWmFECITA8FI8iZU-SyqqW1hSlzjMvVWmk9TWHys3O5nx0KjjGHKVaVvt9PN283qGDswxxiDpEB5tF7kLo42XXbnJNUygVXlsVhOJydrve7rqorBsAMKNEodbfZF0Z2ozs7OymMWa8WKSMlXq4bBPB-LrVqqzKmdHHRDvOcXT7049m6PV01L67O3j9fXazbRguLQhjNUk0kDp7-7WdffP7m9n_48Wfv-ul2mr7dDps5RhCHwywNXj0_PvQ-A5GSMYG05smjemEFkpxcnHw0Bgc3FYUhzlYbZGTi1fFSQyYikeN5W__okxfrxfL1N2__6T_7N3eBNnOYY4xE52dnn335pbHCGP3e06ub2-0EeD-5uyFwU-3H0QozuSStblaLnMlYQyAYoItu9CMpMfV9mNLkwn4z5piLuthu9t2h792IWmTIiMiUKepV24yziz5FZvY5-KgKBVKCUL5zAsXpcbO_34TbIQ9hdjMamDqvrCqqVhFwmE3AVlXni1ZOXmlYXawnTwlSCD7G7IP30yxQFrUdu5ETrC8vIAVCZiJWQMwppRyTFOKheIYalEJ_mJQSAlAaBYKQhGCJISNnSAEtAyO5JCRTiDQGTiSlQpaYWVdGSKaM5KOUVjJxzBAjpSCYs48cSBQF5iSV5pSVRMiZEYgSAzIzpSQUSqWIHwiNCYBZCmw11kXRlg-XK0DMDKAwx6QXJVjFmYw1nIhCQgaOxETAJBAgsRSaOAIJJAbmNM8PJXeClEIqmlJJlVwoi_LF--8hcrs6SinE6L795tuPv_fh6fn5v_-zP718_vzXP_2ZIBp3h2cfP1eq7Pc383BAIXS5oJwEkOvn3_3tHzoPb67fZBY-pItnj1KMQ7cN00wpRz91Ny8hZyFl9KlZtYebuzAMkHIGIVBoa10_K6OlsL_9h793e_32cH-nBZiq4BgXRw2COLo4P7u4_MWPfwGomclU5W_98Af1wvzZn_748nT5_PlTJdSf_fivPv_s19-8vf7Fz77Yb-9-_R8__70_-YOf__JXfaT9_d0Xv_z29uZw_vRy2HcQohT1SgBDTEJxHg6ZEiOiLlBJUxYoAJiNVWl0YRyEElIZLcX67IQzMEtmWJ8e14vm8O7G1qWUIJU53N2dfPge51TUhZ99colDUgIhRaBMMUulAIGBpRRKG5B62G-IslCmXh2jViklwaxr4_tRCISUGIBCREYQkoGYsT45idOsjNaFMUZyCpG8KIytVsEFJgIUCKyUmIeNLkppDFEqFyeZEgAjsFSSgdPkgDJIZspKl4CQMwNHlGCqIrs5e085AmZTVEwkJD6IyUxRhalvy1aYQle2ao_HvgdEJpJS6LJAZgZEKYAfRNdCKiWFlFIBIiIzc-qDWNQCgYgAWRWWCVRVMz38eH5w-gJFAsrAnEMWUoEAFCKOTpdWmUI1qxgip2CMJk6cJ9u0gCBQAUhklErOXceUAWUO8Teho0QpOJASMklpAEE3FlHknCEFJI4xEbEpKoopeQ9M0pZCS2EtAlFKUmkgppgYQRBJCcl5cPMDnyL4mCia2thqnR_ECMAxBmRsT88wzd39_XDYHXa7erFQRZmA1pdPhqEvF6feTQiGMgklECC6yZjCTSOEBMwxuKKytqrD7IrmOAOTsaqubGNjH9rTk3HXozGZOMyhKEtKiQhicHEa4xw4Z6MEEe_37xYnF8i5bBemssjk-ol9JEoAWRZWakM-UZiCc6__-q_LkysQsjvsjh8_ycApAScol8upO5iqySkSSFsvUhrjHBKR1jYLVFo2J-f9YTCmZCIg8jGlyKooTV1BzDkloKzKWqDIIUCkOARdl0IKisREqIXvDyhQSBmc45zWR0faNCjU-uQyME239yl5BCyXJ29fvry4eLpYHb1-8-rq-Xtddz_up_XJOqcUXHjv_cfzOLz66o3UanG0PPRdXdZziOM8P3n6tD_Mn3z64Ue_9dFXX70Z99vubhs5Nc1i7CchlSqFUagEIsVpiMDeLpscCSTm2QPF5EaUyExhmnEeD_f3trZ1c9LdbaXR1ig_j4uqJaTm5HR1fDYH19q633eVLdHYwlrEXNqGcqqa2vXTPPVuConTxeXFMG5mP3X7w5tXr49OT_fD4e7dXQoRJL73wQfL1cnm-maxbL1z50_P79_edtt-uT5iIad5XK6XQzcoJbVFYwwFUkauT47zbpxiQIayrmxTWmUR0Wp19-7u6fvvrY9Xq-OVn0c_B10YIRXHqCttTQGIRWHXF2cUoyqLomoAsipKZjx-8VgJlApZcAyxLHRyvqkLbRAY_tE__Lv94fD48qQpFOd0fLQCTmfr5r_8R38gWdlCr4_bGMLdYSeN-oPf-c4Pv__pv_7T__Dps4vHV5erxu777nazWbTlyXpJIcboK6vnyZ2eHEvIhbUhxpQJED-73t2NYcx8Nww-0mEccqZhnr95t__k6elhnn71zfXx8VoYWZYFI33-zfXpydHRo1Nbq-3O7XZ7FHhydvTk6eXHH773kx__UirR952WoEsppcgAb6933eTnYZzG8fT87O7bu8XFcp6C81EKvTpZNevV5Xc-uHrvcRLMUl9__o3SmjPG4LrN1hbl2bPzYdN5n4jw-NGZmyYfEiUSKPJ8MKVhELJpdFsoo_wU7Lr1MTNSiCkzJ2IXsjgpnQ-lknVr-_txP43Xm2m7n4jy3TTvs_Mzl60FEGgNCxRKvbg6AURCJM7OJ2UlIUck2xZYm5B59jPp2I3Tzc1WaPrsly9ffr25v91--_lbyiCMTOMYZy-FUMaGcVJa9YexqmtbVpcfPCfvKEOY5hhDDkkiJj9KpZvlwtYFMCglATjHBx9isloxImSKKTMCCAVClnUx9bOtjESMMWmBD6ezYEiUOBMBIaAtK8qRM3vnwxTc7ObBueDnafY-3d1tUorGWilEyrkb5rKQ4xz39yMLzBly5u3trBV2-7t-mAiwn8a2rignqQQwVmXJArSQUmOhVTdMxsqY8rJpElEpJUolFR66MaRcWetSXFW181EJnGd_eXGWKH344jHljMDHJ0tE0Q0zCs2gHMmQ8Mvd3f_1__3vD316-vziiy_uPvj-E9DFbpqENaowqHF1tkhAYzdrrRCFRWnQjDs3ujyHgCCDDwDQH6ZPXjzWtiiFVEI-fXwWhvn6zbvWmL7zH1ydlta-vr75Vz_-1b33L-_GfvRVVV1cnb95-_rx1SWQ-Ls_-N6b61tc2o1zd_1Adbm522urpJKRoKir9aLyLigplBKzj3f9Ifi43-yVseM4opZSiXEepdIA4L2Xxo7bXSY2RQUo14_PMkVBOJMHyckH1JiJTGk4z9P9pIXI3puiNMaWZfX0_SfDZlcI1dRVdLPFIo_wv_lf_IMyp5_8xU_HkFzGfT8SiXkOOTMAbDabwlRd3zMCUlIS3TymGIHZT04UlnJy3SCUnKcx-jnGwDHkmIAIIpHMQgvOQDGyRMjAgIwAjhAYiB6uMmgkMCOAbgvyITufUwJihMTJCRAILImBiHMWzDQ7ZoIUhSAQwC48zEEgEggEIoiZU2bBHIlzQilBgFQSY8qz042IPiXnc440z5wSpJzHiecAiVCi4ASzJ-c5eo6RU-SYkAGEJEZgEAAQE-cM0T8oNUAgp5hjPn_-vh-6w2aLiJv7TbMsb643Ssm_9fs_ur29Hvf9V7_6chwn4oRCsa3H3a2f5hiiNiYDpBCMUkrLX_zqi-pkxZRffvOGgYLrjCnmoTNaMqf5cCibUqBgiXF2yaeisCiUnydttSpsGAfbVIDy0XvvuTC--vwrZEoxU85E2Uh72E5PP3hPcLh5-w4lR07_6L_6x__hT__89et33__Oxx-8eBGZ_vn_-G-EFix4f7MJ5MdDJwrz6tX1j__8l0-fPxUKXn_9JuUEBmKIIZNk00qpUarkPQqEB09tBo6Czq_UtAc21elpUdj50GMOKUQ3TUJrNx1Wq1VR1tPorLWPnr9XLauun_zk2tPT_bt3q7PTOAcQoIsiz4MQQJxQgBAStERkJSUB-tE3FxfKqGG7QcFKSm1bUxXT0DNxsaizS7oogDIDPMR7mNLy7GS4u6vXx9654FwOsaiXbhqJhK0aZQtpDDCnRMhEOWfXUaZMAJyL5shUdXBTzATMpiiFAD8OD9AbABBS2aJwwcUwqrJCIMqZUxaSUvBKadmUHALHkJ3L4RDjLHVpq7osG4GqqJrZOT_NuqyLRfMA_IGc0-yy8yAEoFBGiwdGoFW5m6QAYMyZgeYMQAxlVQtVMnAMEVAILR-YQg_OCEoJQIDkHDxlAims1gwYRicRYwxxnHJmEMKWdU4xQwZmYYyQoEwVYwRiU9qUIlN6-GOyn6ftAIgohJTioUlDKf_mJMiRGQjJ1gtiKBZrIdBNk61bggScORETSykAiVNKYbZNCQyZAB5kD9ZkIibOKcRpyj4jBY4hhWk6bFJMRd2iElW9jCSOzp-Vq7Oh2wuliZGIdFsRESICEyQCwDR1OUU37Mu2YSkE8unTp9PsENXi8kIimELHlNzklTWrs4vgnXejFDLG6OdeG0uJKceiWYzTxMS6qqWVcRqlBqV0iiHFAIy2LK0xxWqZw5wSUeYUQrU-0oVVZR2mwXs_jpOpLCAQc4qzYKxWVXKuqKphCIi0XB9nZtseKWvK9YpyZinSHEA8MJcwZY4-mrqlnACBPSUfhDFKyzh5XeicckzJKE0Zpu3WTX3wzpblarE8uXo6HjqfSVlVVKXzTksx--TDsFwfCQBblicXj-7v7neHgyRWIs_7_cvPviKm45Pl1fnZ25dvmkV5crb6-tffVKZ6-v7zqq1Jcnc45BiWx-u6rJIPRMDaKKubZe0jL5YLVZUI-ACyQGRk5VwEwLZeAsUUATmUT8-yT66fUnDBTQgw9RNwXi3bolKnF-eJ8_HZ6ePnz5no8uLK6vLZe-89fvFkmvP3fvCdpl0-__CDtl1UVfXs6VNpJFGum6pdtJzCxfmjtqq_-NWvjo9PmkXjxvHy_OL0aPn-d96_u9kGF51zJ2enp49OgcQ0TnXTHF-cA8DYz6tVq4Ss2jqmNBxGVBIE3N3cn1ycjfuhMNU0zGGYvvcH33v1zRsUMOyHdtWO_SClnIZZSbVoF1ZrPw2CUWuhjE5jqEtd6BKy-PiP_-Z8dy-RCiu7fjg9OSkxPLs4eXF1vliuu7H76Lvvp3k4PT26Wi2P1wshKTpfWrletu-dna_Xi26__-SjRxcnR5ATUbbKMqWL09O6qmKMi6ZSQtrCHHY7zsknYiEH7372zfXr_dRFuN8d6qb2Kc_dWCwqXcDN2_3yeP3ZV2-LVX13t10smwjwb3_ymVaYEUOId7f3797djsN02E6Z-PuXJ_00Xd_uDl1_GGapNDELbYmZMVbLcrvZspQSQLYyuMzCHD07-Yf_5R-en58enx8xsNTw5Tevx2mOIcfEyXlKuWja5rhFtnM_VIvW-ZiT5wxSi9CPWnFygVGJotbGAjFqJbQMY9BVQZlnH3VZhJiZOYyZBRTLstuPKGG7d9VpsVhVplAGcbVu21pxEn03Bp9SpEKr_ZznMXTTnEICIcrKEsNhimOcYEZbqK6fur3P1oSUxxhACj_PEhhTmrpBSSkyMeUcQopRACij6qqU0nCi7L0fJyJiAm2MADRGxpC0sZkhhyikpJSEEAhAOSNQdjHHBIAgkBUiI4JQRgNju1p4HwCBKFKGwtTKGKCHfpHUWqcQGSUDZM4CSWsxz94WdnW66PYdYp6GwFgw8m7XD70PMW42B2E0P3ARIYeYqsYOw6iNMkXBzE1VoUCFoiwra9Q0-7qpDsOUOQvEEMJiURmjgakobIjx5q4raiuFjDkZKaQ2MUc3eSGxkFjXpcx5Hl1d2cLYwGishtrs-uHfff7qn__ZT2_v-kao__xPvheTKiu7aO3hME8-ghAKWEsxdHO_G49rWxc2xPTg3im1jFpWVRkhWymsVR-9eDx0XaUKyHHoxmWhn52e7-67959ffue9p6PzXed__PXL7_zok59-fT0GFxhAkrT45devP378-Mnl6TLTz769ORDc7eMwBT85SDj0hxwTgSgqtb3rYoz97MbgN_t-HMfkQgKKRNra4EKcGSmRZ2WNGz1nBiEY0M2patu4nzDFCOicy3PEKeYYyXueyA9OSapb22_6drXUpahP1q9__XVZamNrrUQ45P_df_2f_sP3L7784vavf_0toGzPF5vNuNv3knEaJ1Ryt-1D8AaZUmRmAD0PQ5jmnJIxOkNmBGGNLbWb5oyUQpAKc470G_sE55QgZlEAhQxIACRLyTkBk0QBmdl7IEIGwUA-IRGgyJNHJsn0cPxTiuQzPTyNkYiAWSoWlClmyBmJGRiAUWkJgCGiEogAElECCuScIJNglCjy6PIcIdIDwguYFbJSgkNAYgTIkxMMnDISKymlkqABETlnBmZE0FI-KJikwpwEC8oZGbKPUpmmXYy7rVTIiebBnV6sD7s9xHizuX_-6LJumz__d_9hfbrotl0SAoTw4yEMg5LSO8dMOXoEiomOzs5PLy7bRdu0DVJul6vNq1dFaee5nw6DMjq4OfgstCjqkmN085BjRBRKqRxijlQ2y8XJ6emTs5e__NwKSSm6flwfLZkpED354IPs6de__qwsrS3t0fHRL3_6UyPEOIWPvvsRQ_zn_69_xRSN1W--up7muNnsFMkYQnb5f_2__29_8m9_8vqLV955wZwJjbUhs2wevc9C5kRCCCF19JEBmEmIhPsbQYlzcPv7nINuG2FM9jMRUXLJu3cvX108fro-Pulnx0x1U6-PT-cxIYEUMvv0wY--9-bzV6hlTgGAo59ojlmCrSsmQKM5ZSEQhWTEPHutdAyhaBaZqV6fxugfpizIiMQoURmNRDnHOIyrJ5-EGNI0laUG5OnQW1tw5GnsbVWhVKosqpPzYbMTEjgz5GhK7YYJBUhT1EeXFH1OGQAok1Qyx0gp6cIyZWW0tTVRBpCAUkoJwOyjFJC9y6MTUmUiUzYxzAAUgxv7fbs8ZsGZcrM8J6Dg3LzvpNSZstJmeXb5EJ3XAiGnGCMlkEpJrbJgqaVc1Hn2UgqMmZBt3Qht0ZQ5RmRGZYj5gSgqygI5K2sgE1BEJmVLUFo3ZcwBiEFLISD6KLWsqlpZm5mZcpwdCIFap5wfUEhSKqIInAULEPIBPiqUopwZMuYgpaQYhDUCgZlRIgHM02hMKbVy4yCE5MyIiFJA4ocCAxKRd5gCp-DGSWgVSah2Ies2zyNwBE6msEBcFHWcR47O96NQulytFIthnmxVKG1RtbK0umnnfjBFkUIERFNZBQQpUvBMOfvYrE5cjJyoXrTD7tB33eWTD4KLq6vL9eVFdzggEIKMc9JGQ8o5U0zBGMMCUQlpFQC7ca7PjwWI6GMMLowetbCLhlLkFBhAarV89DRGn3JsV8f7-zuWsDg-s2U1O-d9kMZKLZJ3w6uXw-0dU-x2N1VThn7MOZT1IgLP8zDuuna1LuvG-2zLCoREoRBRKsUIRdGUi0VzdeR7J4XgRCAExywAhDYEpLRBBKakmaZuWJ1fAKTV5UVVVG--efXi4w9PH5-aWodhiomAqFm2u27vXEAl3r16A5HmsSukUpB89O_e3TPK84vz_aGrymq9XvfDgTIZY84fX7XVctwNgGroeyU1JYohAnGOWRmdvUvDxMzV-TlmSp6FkkohSozeZRAGOEQyqIZDxwhSqnl2gLSo23nq-l232W7rukqUMuM8TWhU2ZTL9erQH4qqaha1krIqyu3dZr1aX5w_cs6v10dN0-7utu_eXJvCNE3RdweaJuKUU0whnZ0e55wlQ4q-0jK7eLc_IMHc9-cXZ-1yvd3tnzy_6vb7N99-Y8tit98dnZ0VpW2aWipzdLRu20VRFBF98kkZGWOyVq-W9cff_dj1gy3Lk5PT3_7Bjyinu7dvS1sVVfH0oycUxNwN7330IvqYXRiGuZLcLBaffP9TreRvffpJuzB5dt__8H0KPswemN599dXvfv87v_fbnxw1tZHoQ9rd3xfWCMDop77vK1Ms69o7t67qxaIB5m7sz47XRHm9aIjIxXh3t7OFXS7bKcR9P_zLv_zl7RC2ye-64eX1PXFat_UcIkhUAueIQz9NKT0-PSEhyqb49s3du-vbQHiY5ydPL3_x2VfTHKTWy6ZdHLcfrJffvrmdib5-t_EuWGOG-y7GKBQSsamW_W6npExBEolP_vanf_yffO-Dy0erxrBS__Hzb7cxvnpzd_roXJRFdG7q99nPOXEGYkDnnG1KPwdTmPXJybg_uH6yRucQMzEqa9dLbXVR1ogYYyrben-_tW2TMXHOqtAhxgwpBg5EaYpE2M1OoogMoGytK61w9rSLoarLCFCW1jYmA5vKlIVBwMApU1ZCtlVRaikRgfjQTwPHyYfm0o5-nDf7hFkbVhIoZApBZMg5QwhIXDQLUxQSEUEA52G_jTmzlTnnMM05RxTCaMWA4-EQYoohCCmDC03TTocOmB7cMqiFUjq6oIxCVIggtAwxPayCw-S0MSmFnL1AgcgpQ44RJBhbhBApsQDo93NVVyhE3w1TNxElYh66iRGdd4FSSgmlSJni5MFoYl6sl_MwaSWUsdKo07N1jFFIcXK8qgq73XVSqsMw5ERCinGc-3EuCjNOUwy0H3otdWLcbXcuumXdSKWQ8unZkVXm5nYzjW69bFfL2hrb-XA_TJ-_ud5N07_-85__9as3t_eHxWn76fdfKAFQV29vD8aKeU6zj5nIGo1SAyCjlAIo0r4ft-PhgBFlOl3WhxCNgs5NlVDzPIXJdV3POUsJ56v2hx--12rz7NEpEaRh_vEvPzt60v7__vxXf_Effz7NLofo_aR1uWrt5WLx4fPHFKfPbnbXbroLbt-PCCxSFj55l68-OOnufVGqdl0TZzQipTgPQRsRUiTU2pphd1AgSWIttVIYp4mZMnJwEcoKkI2A6W6XQ7RVPex6A5AimVXFBFrJHBJYVRhjrQ79ILLwhwMkDomWi6pU1f_xf_4_KTv3bjP8xc-_mIZ5fVIujM4Citq8ud6szuvk8v1uLxSHYZZKMbGbRmMl-dmNA0pEBD97ZbUUOA4j5ZD8BIxKIlGSArPP8qHeO2cGgUZLRh0ZQgaUHFkgokJpBcWsCgmBkCDlCCEiMKcEwGBKyAmQxcNc02hdWCkEEAMDhMw5CwkCAAAoBgRSIJGZYwJGziBNCczGGiGQKHNi9kkAsfOAIAAgRQ4JiYmIU5QAFAIwC0QgAiKQEggBJEjBxIgAKT68jEKyBlkX5KItCyWE84EpM8Ppo8t-e2AJb765PjleFMaer48_--rLzf191dbd_gBKlG0zbO4ZWCjJQuQYKM3EqMpSKbvf7l59-9aNw35zf_fqZdWU--1O2cKWZbe9L5tKaYUgOKQwT3EO1WKlrBHIpqguP3y_Xa-Hvnv7-ZcK8u7mLkVXNXWI6dANz7_3MXL6yV_8Rdu2c_DL9frrX3_16PGj7__wB89fPL6-uf4X_8O_nMeusHZ7cycKBs4hxPfee7x91_3D_-rvXt-8_eVffSELaYya5gkE2tWzab-TsH6MKHRVogLvIqAAKRCF1BooP-A4BQIApZikKovyRAiQUiDlALjbXqcU67a2pcqRFk3z3icfVFXpYyrq6t3Lt8vVIudMKNwwtafHmaIfZiAJWquyzCnIolCq0MYao8I0opAAcHJ6OfZD8Am1yiECZqk0JS6qumqOALJQmP2gbVMdL7vtzhhbLcqiqrUxmUgIUkrHmDVg1TbeBQQkIIrRFhZzcsPB-9Qsz0xh3dSjgBSy1EopEaeZUeSYi_YEMftIRdMwARFRIhJCFhoESilBCoqhPj4O84yIlNO4v9FWS10brW1Zs1DVauXH3pQmxeznsSibenlK0RExJRICH2wDgijnJDLr9piD09b4eU5-Rql0UVlbCVOEeSZmBpRGck4AqLWRquJMQNlNE0slpSIC8p4TSa0AAoeIUgqhlS05Z1Qyzk4XhpmlUNoUxDm6AOI3FmZEQgYkKE4W7AMjMjOAgAe_WaYYqVqvRc5z3-uyYQZUUhmTM2ljUIocs5BSKg05c84ITNlRmiEnlIqTLx8y2RQ5JmaKflayVEIwpHF709-9sk2bAgmWxyen_TSU9bKoTL0603UFwMFFlkgJiFhKIR7-jXini8LWbVHW7XKdKL759S-zLaZhPDs_Pb183PfT8vQYVSGVPr64yhSkVt7NUqjgZkBBKacc4hCb1Vl9fESUhJE5RwqpbtYCRUw-RoK6ZCLUer-5uXr6QXajstqWFeVcrFaCcfnocry9NkK3S0vzhDFxmASk7t2tNgUxlVXlvbOmXF9caKu1tihA60JrVa-OhFJumo0t-9tDzkhEpipVZVRhQ0wCAAGFMVJZYFJSRD92d7fS1nZRxdlfPr386mffFLbYbzc3L9-kady9fbvfb45PTsq6aevGFGI8dN3oYw6E8vHT91DT_e3ddnMgKe63W621lGIaZ2LKCRbNcrU4jinGlObJ6VIJJE6eQyyr2o-zsZqRXTfZsizqJvoojU3xIdZoI6E2Rc5huVotT05i9MqaotLdYfDjbK2WAHfXN5k4hNg0Vd93KcZ2VTPTMA1Ko9by_MlpuyjbsxUH_80XXw_j4frVm6mbNts9CFodtXfX9yklpbWb3LP3ntZNk5JHFsqI5XKxPjkhztao1bo9P7voh6Gqm7ZpgLMbBm00sxKcTs4fDd3QlNYaVdtCafXm6zdHZ0tbakG0bBtOabU4mue5XjRWQWPKNzfXVVEog-Ritz0crxcUwjyPKeb1uv3H__U_GHa7s9NTgPj02dPz0-av_uPP_qd_8kd1qX77e5-enR_vp_7v_a3fe_7obL0onQ9laVGwNGboh5vN_pv76dPnj07WCy2hUIYoz8NIOZ0fH1Vam9_s6Oi-H-eQMqP3cXncvL3r3mwGLlVz3M4-qhLLuuz3w_np0ep0WTft-09On704XrbtMM0OePLxru-bZTPPPgv85nqz68fOz-ePT3s_Lwt1v-_rslycLify7643RVkohX03aG1iym72Uumj0-MPP332W3_4keGiktXiZPX2fnh5cwCrF1VxfrXqxvmw7epLrSsz9VEV1eL8SEihrAEpmRiVCjEdbvfaquxcDjmDVE0tCgtSpkzJpcXRceakrBnGYXm2Dj6ZqhAMYQwCSGthWkXIMYS2UoeDq1f66km1vfNzTsLKmKJAbFuxvx-ERBAEkoUABvJExNkn9pH8nISQy6YkBBmzOwQOKQyBx5EDxT5qpfwcKSdT2ji6om2ij1qqnNPcjfkBKjXNgohisGVBKdqmsYWdx1FJVEahAEpZAHvnmLKQmImZEAG1VtJoNzptrVI2-oBSCSkkQApBygfRIXNmEIoQGNGYEoViTkajEKKoLCLHGFIOKYbgXGYydSkEIIrk6WjRYmnc7IuiTCFRzItlcdj2KIWbxjAHFLIobFMVF2en3aE7WS1A4n7fHy2bGOPZ2dHJqkkxx5Taqjz0c0pRKrFcNnVVCcTD_nB-dqxSBgCt8ORkpcjcbof97Dtr3BS63WGa56OT1mqzKMsnT8-mYY6R55TdPGWm_eRjjmenrZJqnJ3UYFBlXQ6YleDjpr71CTUSQWA6WR1NoysExhgNysSp1CbO09_-re-JBEaKnFlq8-uvX_7Opx8IoT95_vTLX7wtjeUwb-_G_-If_8Hf_fDxyfF6N7k__dlLXrZfXe9dpEM_OR-V0qhtAPIsPnn-eB6jNMbF6EPIgbVCQtr1XlpJzON-UEZzEggQJo8hghYRgREkCsngbjcUY2YhtBSSRanKZTMMToQc-wk1HD8-6d_cj7thHl3VNkaJkODZxek__L0f_ZPv_eBIql0_fHFzc78btrvDth_e3e66KTfr6id__ZUpim4a0-zcOBWLEhGUtSk6pPzwCD5QyowMnKdhBiNSCFqqZVP6cUYmZiJkIVAgoBSIUgJrIpFzEkBAgIQCQCCFBJEoZv6NuDVBSkKheIDlz4MAQIHEWQhkxpwz58xC5BQlAjIjMwhkZiYAIgFMRKAl5wHQImdgIE6cKacklBBKAIKU8iFHBIkQkOHhZsKcMyQWQnBOyJkpU85MgICMSTAIIEEMxBAzEHMWnDImUlqBlNIWAtV-tw9TLwCl1U2h9ttDt-vOnz_7xS9-NoxumgaOGZFj3ykljC1ZCCEEKmmbhlksj84fPf2w3x9inmOI3ebeFmboesGAEvI8VsvV1HXWlJnibzYqWkIOPsairE21RIX9Zttt99lN2bkUfLNsR-cIaLE-QlL77e784vz-7c33f_e3xr57_OhyfXxsyyqG8PlPf33YXK-Wi0M3JKJ58vvJxwkun19cvXiWFf6L__5fS-ShH9w4JSRbFs-eXT6-vJRqeSWMzCEK_bB9AfnApQoBhSTKnEkagUyYE8Up-wNwbk_PF2cnMqap73138ONw9_bd2cXVruulkkar1fFxCO5odXx3e3f1_rP2-GiaHapSoizWR5SC0AqZhZTAKqWkrOGYTdtSDHEc7m7fnZ0_rpuFqVvTLEIMnKJQSDHk6HRhUj_FnIVQErVt134a4jSB0CFOWinf9dPYAdHY98SIQpqmwZQp08NuVRAXtoo0SiGrZh1jVKiS96i0UAqBQWDOs1LmYZOrbKmbEkAAEPnMIFJmYkApEWV9-n6aB2MNxxz8kOaBKRhdpZwzQLs6AWCBKvk5uCFFT8DGWgQABEoZmB4gmykEEQIAMNNvjDHBUfTCaJRKtwu0FWVmyuKhQBAj5AwSpVIApIQAKcrFSpY1SUkx6rJQUsnKusOBAJQpQKlEzD4WdUExex9sXdq2ZODsvVRSCi2AGYl9MusVTV4oDcwskHNGAJSScy7qs5gG3--FNvRgqlcyuiCVltoAJcqEgAQAiYREhSg452HglE1pTVP7kChmLSGH-Bu0aAzFYiWUcZHLuuCcdu_eEST2fvvN54FyTOH8xcfJe1s3RVsTUfRRKo2UY_TD21cxRF2UpimXq5Pjp09ljqvl8e6wrerq_NHjw7CPMeeUp3lCqVVRMSfgLKQSWtWrY1MUDHnqOqF1sVymlOTDbs7PgJCDA8rEePzoinKQSr3--svj00eH_VaXjbI2RR9doBTyOOWhRwIODhXM21EVujxeTvvdNA5j35V1tbo6Hw-Hw-2dEOjGQ3IzCtGcrAWInGJwc3u0rhZrlhKEniYP2sZ-QlTK2oeQHiVKiSTi4nQd-2HYdj5k5ixllgLG_UakZIwSyUU3CeCqKoiSRnV8eTztxqmfqsJs7zdlXXb327IuJSBQ2m225XG7OF2N0_TQ4jg9O0aJp-9diCzrothte1vYtm2lEC4E0EpXNQsIg0sx1icNo2BiqZUqClPos2dP-24ntX6okhtrKLEtCkRy_SSUrOsaBdSLZnN9f3K2IIDDrpuGcZ79q5fvMtLmze7rz799-_Ltu9e3q-UizO7DTz-KKV08Pru4vLx8dH77evPJdz744Z_8KAy-MObFB0_evHzV7XpGODu_mNywXDbIoq0rEDgNPcdQtXW_O7z3nQ_btro4PTbGKA1Nu4xxbqvm4vL8-t27xy-ezf3h6tmVtWbaHhJjcNP500ciRyuErm27arpxenF1eXx8-vEPP0SCrts_fXa5XB-l4D757RcG1M3t_Xc--KDWXCnxn_3R711erCGnqtaA4eMXj9aLerVogIAF1lURcv721Q1qfbxefv_DS6vtoT_URTHNbrfZLJcLU2hEYAYA6Gf39nb7sy-_NVX17nobE52etF_f7IbMd4f-6PQk5hDnuDkMj07XxKIb3Wbb3dweqsq82x6GGFUhfvXVm812Lwuz64fzy2NU4qdffV0Y43zOOXzn6fO_-Jd_-eGnH3fz0HWh76cQA2TQVTXu91VdpQjV8fr5-08__vT5F1_dZSWbdd0fBrQSDZ4dlU0tu2Ge3awqmbv06rOtbUtTFmhUTllYy8zZJ6VlGEaRycjfNBTrs4WQIk4BkIb7fc4p5yC0ZokMQgICgLKolKSUhJS-86AUFqZd1PM-dpvRFvr-zU5XWtqCKEpmAVmJTFL0KYZEIEQmCvkhwxyIE2pgIVxMjjDEyCr5QFkIiMQhIWX0RCGJhHn07CJqnV3QSvqui8GhwJwiBU-ZlBYZgFJUSvnR-XnknFNK0TkEIQAoEwgWQgqpBSIIkFJ5F1AqqR4OYhU5ppB1UepCWWvnfmzXR36aUaoYotZGaaOsSSnGmLSyQgoUkImCjwAw7kfg7KdYLBttjHd-7KfDYT-PMwOGaRICM6MpVVmX0YfF2ZEQLFGEGJZVeXN70x06lqStWbRloTWBMFoqIZRSlPI0-raujLEIoqg0AjLy0aq5vdvWbc2IAhlAspCyqjvn7-42r1697vt5yvBHf_Kj2-vdNEeUaJTRpR3m0QNoqcbgwpRDyJ4I7P-fpv9qti7L0vOwMcY0y257_Pm8yazMrKyqrKr2bDSJBkGCJCQgAjeMEEOXitAfUOjv6EKhUFAMQYYghYAIkQ20q67q8ukzP3_ststON4YuTuF-X-yLtWLNOcb7Po-uKt2GYfSuiFJp867tC6UmoCxaB1ELTMtqUtWLqui9Oz88siAfP3xYaWWUSor-9qe_-W__v3_5_e89Z0YGrjL9_NnRn_7e06ePDt97dHR6sowhfvPu3V__6sX8ycnr3XoY3b7tyWibaRHux54U7dzYBs7LIgIPzt9stkwcYsKZ9Z0HR4CiAjnPh4-O9--uufdKWWWqydETGbex7dPg08iz04N8WvumZy_loW1u9-AYU8gyGxz0q14zMEiuVFnmzbZFr3_4Bz_6UT17_uDkxat373a7L15cJOBdt1tdr0WRS363HbwbSKuqzqsyI0UiwfsUk0cR3_beja7vlULmpDQwM7OgJgJh52OKZO6660xGM8c7SaWgsESIUSH5JBA9iKi7lhoKAAAIBA8axEdClBiRhb2_y_2LCPAd8PAOZQ26sCjIKUFKWhcpjiJACFYREiibcWJSOaaEQJIioIjzwElSAhAkYI5kNCYBRkgMipAElQYRpQiAkUgpRUiKAFEgRghJWBBAFQVIgCQIAgYhRUkpOifBg6Abm2lVQoxlVQjJ5mrFMRweL9-9ePn25RsBQYXEMjtY7G-vARgVpQQq08aYoelIm8OTe5dvviFDzW7frTcmozj02ugkkb0TxOQGQlAIceh9iMZY4YCAIUE9W2Sl3W9WY9OUhaYgvu_L-XS3aarF8uj8zDsfXfzoR99_9c1X88PF0fHZ9dvLP_wHf8ycxsH99pefri4vxq6tqmW5WFSTertbnxwt9_vu_kf3d-v2f_lXf5lZMcYQYZYbMUhAl19fL2al0oszZdRd8icrc53nvm3ZR1SKmbUipTBFBhYQQWDgyNE161XfdtPnn9y__2Bze5O8I62uLt_aLOv7_nCxbNqGtCrLOqbgRieCtsgRVZIAooS5nh8Ji1bm6MOnq7fXKYaUwOYZkXJDq0y229zawo4uZnmu87LreoRESBwiEZDWwYcUXeI0WUyreuKiF4aiqpGIyLh2b4osz4skwQ1diFLU1eze_fb6FlGSQPSDpDHFO8N8lWU1WQohgAJm0EaHGOLolMLo0x24TVelnc4FQRRqbexkyt4zQeg3uigAbDE5dt0Wgd0wDMPWaBOEDu8_jW7IJpNychSjiESOnCTpotY20yYHpVJMQHA3K0BhBFBacxT2AVF81wQ_irDJ6iwvVFakEFmYtEFkQIlDvLsQh8GJJFCk8sJqDWTG3kXvbFbEcQijU6SVRoUYQ5QUs7JMPiLpO6YqB0YyIQRtDYfIISARGcsi2mTMom1urU5AIbRZNlG5IUKtdUxJJJksU3d0IUallSpyiQmNAhZOAsw208mPoetTCCrTxti7wQIiAAoSiIv29AMVGgIzOz7VRgff6czMT47vIn77m9Xh08f9dmttVk6nfvSM4H20ea7LAkiG7R5VXk6mHEPTdLvNZndxK4aqsrx3_EhrIKNBq7Yf-qbT2nIMWT0RkRhi6N18fpJ8w5zGvvchAGmjSGuSEFP04p3r9t16__QPf7x7fXl0dJpiHxOsbzfejUVVKaVRiRLE6MLYcvQAYjIdnLiuVwCmKDCOcRjH9ZpTcO02uoGIDGG72-2328n8EIGUNZP5sh_2-XSqTWanVTGZnTx_RsAxgcoyleVRBAFQ267poggSYAjNZquU7jebrmkx-mHbckjJ-3G_27x916y29x897v14fnyyOF4El1w3juMASM16F8e4W6-rvGzW-9XFNUd2XXfz9qr37eHBtG36wmqrM0LNQLqoBWIxn7BSPgatcgYmY_vOIZGy2lZ1Xhd5bpnT7GDRdb02GhHny6NqORPiFGKxmJ88exiGUec2jAESPnr-9ObtOi_z_a6zRjerTVkVrtmJJFRw7_GD9XqlFHJMQ-dG586O57_51aenx4snD05ff_l6Pp2UVfbpL34zravHzx4YoM1myz4-ePBAWySir758NZ-Ujx_e--qzr5eL5X6zOTw6app2Pl8gSq6MtRpEbla39--fTsqinpYS4sn5ydXVJfhY15Pbi91HHz45f3xfONZF-ejBmSDP6vLi9bv7x4ezSZVZzDU8e3JvuN2fn5_NZ9nzJ6cP7x09e3h2sKhFeDqtbab7wVVGg6BVGgAApdl3wzCWRV5W1fHBnJS6uVpNJ1Uco49hMZ_M51MEKYucidoQVl37-Vdvvvd7H12vmk3XZ5n9_M3N63dXnXdCcLPaOZeMpo-ePzisptpoJmza9tXtzdWq22ybzoer1S6vq3pZ9c7bIt-13RgiS2q7zmTaB_7e-0_bpstyq0118e4qpqiM3txuz5_ce_3tq_Jgsnh09NEPPphm1miaHdbX69uqyg-q4u3bdwBh3-zfXa6u321953lkz3D47FhPCh94bHpTZqCBAHWmZqfT21e3eWFi5MQQxtFkme-GFDmNrphkxAwgMUa0GhTYvHBD261aFokQhuD1VMWkipkCRd3eHz87zLJMvDArkDgM49VmczWMbgSfGEh3gxvH2I3RQbps28JmMUny0bP4lJBk7zuOsNn0LJyXSpGQJuJIirLCVIeFANjSpt4jiHAERGOUqYrYdMZaQAVKuXZUWt21EgHEO1_PZxIDJ4kxamuFcTo_9GFMAsoYUQR3e9gkvyP_QPJDJy4ggYgIgdFGRMrZHJF0phFhHDwpBE4SkxuGyBIjpxR915FCPwRbFt2-a9tmGBpFGDm6wUsCAAJEk5k0jMaYdr9HRGZfZ-ZgObndrB-cn1xcr3Jrut4tj6ZD58rMSIrKqBBSZCYy31y8OjtaEpB3URmz6_vGpaOD6udf31RZxlr7Gj-7vPqLv_7V7s3Ni5fXz54f7_Zjt-3KLDOZXu8Hk2fNvmv3flpViqDdDB7ctMpJGV2Z_W1zs2msSPQuJE-EC4UPlkulzMX15v7B9NF0kjNNMvvDH31n9fLdm9dXv__d5ynpTbPuovurn38-Pz96cbP9zdev_tW__-kvX7yLVm-b7tdfvRodZPPJ_-nf_OJqL9d93IVxtdru9t0QQhjdsG7cdrfb7VVu10OXT4oYEkrqhthttswoXlwbIGLyaTotxv1w-Px4-82lNAMjAdn6aDHub7SyrHRZF7MHBxE5eU59n02zMATpggkDNaEfw3SZB-eEKISoBQhAk_3R-ZP_w3_9n6bblmN4ud399FdflfPJ9eri8vIGFLeb_eBcDCl4TwTNatN1Y3BjkMQCErxRwN67YTS5NgYhMhCyRG00cAptL5KARZAEAQFTCIICSuBuXu48IAFASgwEmNAUVnwQBkgMpIBAHKMmiAk4ASe8y9yHEZCAFGiClJTSEhkRlEIAkJjupKsS-a53kBiY012vgAABARIjiyJUmiQlAEQQiKKtYp-UVqgRmUFQhCWI3AmKQe6wkxAEBEhERMACxIQckEUSKgJhBkEQNNqUi0U5mWmUMAzEAkT71Y5IcUikqJ7URmMKrm8aYIYUILEPLsUkwJKC63tU-YMP3rv-9uXt9RWoJC5ODw5CvzNaMxInD8KIkEbHnCQl9kkRKhJjsxQ9KIvJ9-tVGMYU0vRg0Td7rcmLgDV5VW-vr009yaw5Pjk6enDebTa3t7cPHp4__eGzz3711c_-6jfHjw66XaM0DRyJUIjevr4-Olq-98l726v1V79-eXg0nR0cFNOynE_3zVjPFspk_9G_-KOzKlc0v5fGqBQJy7Dtg49ZXmTTmoOXwIgAd74RFmEhpUgpIqQUwfndxeebmzfVYpFPplmejc3e9XuJ_vLqWmmDaLpxqKtl4ljXs3a3V8qkyLnJdW7iOAY3IGoUWt476rYtMxuArC6iC34YjIIoIcutrSaoMzuZxJRQgIjEB0FETcTiR2_yrKwWgaVvW5EQfTRFUVS1a1pjre9GrUkYx-1KAA8eP0ohEgFHRyhGKUg-hHH0vS0LW09iZK1MjF4rC0TAaHOrtAnDICmM-z0anSIzM1HSeR66gSMTR0Fh31XTg-C8Vui7TqILrm3efVNVdTuMaExW1Vle2XpOugjeCUDwXme5LUoznRISuyAChJRiVKS0zfwwGKMUsPjAvo8pZAeHVM8SKkgJOCIZpRURJRdsrjm44EYUyYqyqKdKqZQCR2-LigSUJj-E-clJMZuFbiSUzGbdfidaa5vdgYcIhUgzCwJyYh-SsUWKDlEpUklYYiLElDyHEEJSShtbpRRUSjorAe-A1SKCqBVmOUQhjTEkEVGIRivxnseYUtKVIZPxEIUZQyKNqblSEsah3a1vUGlTTNvdppjNus0WOIhEv9_mednttyyQ1zXoPF8cBR-UrkISkxXJu-3mBpSpJ9NqOr33-Inv-tv1ZnQ9ClSTWZblZTkZQ-DEZZ4Vk5mxprm5RpTkOoWaQ6oOjjm50LaxG_JyojICALJaafSt215c5WV--fpbJJwdPtSWjMmShNnywdjsSKC9uTFKcUh-dEpl2iolCUyCcdRGI3sEJsTpwT2JY7fdMgetszyvQnC2rEG42Wy3q301m1fTfFzvQCJp0sYUs4Wg0taaqq5m02q2KKpi6J0yKkWu62J5_9kwbKt6Og7elnlkpwjHxldVIYAvvnxhbd3HkFfTYlId3DsVoqKqjAKllCFUJJk2Rql6VhWZqepqGPrbprVkffRVWdiyrGZTbVRi5sh5VULk3GpjMl1nwkGRGYfw9OOPDw4qQ3a73Z3cP61MGWIojE3B7_YDIT55_rTdbfrtPgmvb7e2yK3l9mYLhsMwThez4MaiUu9eXS4Ws3pS2yxXmtp9n4K_vt5--IPnk6oeh_7s9KSupjHG05NTYwwnrCfVdDIZhu7s7FQpzG02DG1hTHR-Oqlm0-qHHz_pxrQ8nlZlPrb797_zPLh-dXn19OkDDZhZevL42er6yhqel5PZbErMmdb_7H_9nymQRw-W9x6cvH31mkNYTKY3l5cPTw7FNTPSpGnom5OTo08-_uAPP_mg0nqWq8Ws3DfNB4_uzSeFMTqmUORGASzrMtNaMRa5SRxCiKP3zgWbmcW0tkbfXKyQsCwLIRCQ5XLSd84F1tZs2vbbd5evbze__OzV7X6_H2Q_dkVZfv360ubl9b4pazuv87NZXVeFIly1w8BxE9uuH52L7dgfHi1vt2tbmqbtACRgFJHQ-bYZWdjzmBl1OCsWWXGwmAtlL1-8QWs3bbu-uc1mWer7FNhU84--952zZZUZ_ezx6cV6KxjJqKYb-uAC4IvLm2Y_Zse1KnJlLSvSB2XfjvrOsAYpzws_hnbbtatmebKwVoOilNLy7DA4l83r0A3GKEmSYkrMY4ymyIIPoDCOY79a3dlU-utdllmIIAkTs871fFp3_agz7cRLjpILgcKQlEZG6GNQiEpRblSIQqh7N9xu9mOKFsD7EFQgixwSKhSXIEQl4ra9u1wra_v9OGy7fKLd1Ta0LgQXR6cQ3b4N3TB2I0BMMTAHY00KvW87ZTRpyoui32yINCgiY4Ehq-sQIxkNiMzCMQmAMGutkQRFOMXYOyKIzkcGW-bldBrTnVRapRjc6BEpDl4hEqLSijQE72LbESEDoLHJD3etR0Umhai00nkBwgpRIXa7Zr_b-xBC9MGHZtMulot3l29_-P1PPLv5rG737dnx4dXt9vxkSQCoqCgyo3WRZ9GHyuTTuo4MPoWQ_Levb25X20GbF99cvrm4zorst7988-2nb6ZKTGXNyeFXv32xb4aT4-m2dVprW-qhd92umS2niRMqQiOTugieUaQQWZS1Yj46mGVl_uz-vX4b5oU9n9UicnIw2d7sFenUh7evrv7dv_7Jh-8_n2s1ndRfvL76l__6bzsJRx89_Mmvv3m5um0SXO-2ZV2-XW_--ufffPpmHUv9Tdv-5rOLbRy3u-b68npo_NCxrVW_6wFRlXl-sIwKDo8WuTIxhKzOdkNntI3OEyiJQoqMJteMdT7p112dKzcwKXP_k_ebiytV2oQCkUij27YyxuRGBayU8qu9u26UylRdzJ6dYOeVLcaum85L14wY7X_93_zzf_HD9zH6i5v1iPyu2W9225ffvB4YV7uNNsaWJon0fYeC_W6_PJzvtut-GKKA7wMCu37wLtYHhRCwc5A4eA-RJUZhJgLhBCJIlFIEQlIIIuAjBLnrqGsE4CTACkhCgBiRABAAAFKExHpaQoyKCGJABEACQMxLQhIBIkBh9gESS0hAYIoMGKILyAiMIMTCwncLMUAGEIEUEQhQCEAiEJOwUEoIID5opSSwMZlwBGFJfAfS4BAJQIJHYUC6y2mjEPpIIYHc8V1IUhRAiVEZkphSiMkHY3UYek5RAPquny4qAk4cUwp5UXg31pNJu97ZjFKKwhx9gBQlRmWy6vAkiN-8vTw4P-k3W1Q8NvvUdYBCyHe0AIzJGKWUSiEqRElB6yx4P50fKpGxH4whU2TMqd81MQRTlX2Ijz_4YL-6tUX93gffReJqWn3z2Rchykff_bjOis9-9WU1nYxDd_TwaHu9EY6LxXwcghv9--89yzNjEK8udkjm4fOnt5eD0SoFef79J0f3T60xemSKrOp776eUfNcrq8lonSvhOLYDEZIiuTsRWg2AIIiIHFJiEhGlFEpSgnHous1maJvj0wccguvabr9LkoL3JrNFWXIaSamTe_cEOMvLm6srIAJS2hAAJpbp_CifTNv1LsSUxnj4naeoybUdxzA0-3IyZaB2v5sc3Bu6gTiaoozOG23ns8eU6X6_Gbt2cnyCnLwbgMh7X9ZzUjSOLivLYd8WsxkShuDHZk86y00-XTwY21t_p2rLNafAiUGgyCbF9AgQUmJTFCGkFIMIAwgBCmAcgzIGYozOp5RQKZAowsk7IkoctbJKqenJcXOzVsQkEPqd77eub0MI2uYCkuWFyjOVl0wcvSdEYUGTqbzMyokgxcgMQEqrLEOg6D2B0lqS60PfAcBkcW7ykoWSMAtwYpPZFAIRSYiKUr_e2slcW5NVk77pmDmmRAAM4saBWPKqGtvBj6MpSmAGQkGMPpi6IkUsCQF0lgOCpBRjIqtRYWQWQU7CcRRmFtZZJkDGWAGIIbpxpEzTnWcNhARJKyRCQNJaAKIPSJTnllMQITTa2AzvruUxgGAKkZC1Vc6FowcP3H7ru6E-P22u12kYQ7Mfu11KPoXk3FguJgKSFbXJp_V8fvbo2eRwEVzI8mw6OYoSBSKQub19V5STEMeX37wkq0bnyNjJ8pAId9vVbH4wWy77_RqQog_eBTcMxWxiyEbvkhskxuRcZgtbzZF4dD2lpAmbi6t2e2usNtaGYejHZnZ4lgJPTo6HdqcUkNGEZKwWjsnHxCE5H31A5hTGbnMLKWSZQYDFvfvj0A3NCKQQpZzOEFO_24ybzfJoGfuhWzfGapFARNrqejYnpbXVikw9ndQHc5sVSUAZzMsin1TVfFLOa5XVIdHJ4wdj26WQskmZ27TfD-PoZ5Np17ajH69Xt3U9FeTJdDJ6d_Ls9PLtZXSJSR9MpyH61HtJ47vrVR_DpLLfee-RAB4vj5umJQBSauwHk9n9tju69yByOLv_sF1tHp3cWx4e9r5rdt3Z8dHyYPaHf_D7X3z57j_50-_9-Z__0b_91_-2LDJlrTKUV_n6YjVdLmazsqzqfhiGdqhnk3wym58uktBsOrm52bVt_N4PPnr85OFskill2m2zPDxYr9Z9t9-1DSoiFOeHrm26ppstpplVkJIhPj0-TjG44LLS1FVxcdXM6vz9Dx4ObX9yfBohPj6_v5xVCuCjDz9otrtcw7Quvvnixb3TZVWa8-PD6aTYr2__0R_9uJpUF5eX985OOHjXd3_2D_44U_Kv_-ZXP_zuwwfnZx998PzkcD4tzLQsHz06_n__5U--c__s-aPzKs8MSAqJkCFhkRmDMrqw7_2uG_b7brPrXEhjYk0qjLHZ98qo2awOiZVgnmWJpRnHYl795us3L682L65v9kPMF7PIyZjsatduds1t07-9us6qMikag3z24u2v37799vXtbdO8u95erXcBwFhTlvbt24tt31xf3gZmBr58fbXdNNrqJNyPw_m9kwxSDurDh_cyMt-8vXx7dYVV-fr1a6XVMPRZnT16_-l3f-97x0cziEmsfrfe7sbeg3Sdf_P2Mip69W617wJmhe8jElFKRZEZhXlhWFhiSIlBuJ5XRiCOsa4rQIgxVvMphOSi9E1LKClEYQGFzOJdYCWojIDEfiAikxnUCoRVpdEaOpoM7aAMDuyVQl3YwCEIhD4pBYAQfNi0fXFUeoa-c4FTjCmlSEjBDy_2m50EjDS41A8uJOEoJtNjMyBTntt8VgoIUcLows5RQioUh1hkGWFiTio3NleoCFMUhOQdMGtFHKIbRmEWwZQkr2sA0plFQK0NCycWo8hkRikiUgIMzNEFhagVQRLUxDHpXHfbRlvj3BhDjM7HlDgGRQAMHGKeF_2-iWMgQGszUUpcqsrpOLTG6JA8i_gQdGZdO-iMQmTnxqKyo_MIHINXFrtmd7CcxtGfHB_VRZFZW-Z53_VZbgDYj867qJUqtNFKC2knfNW7n_79F59_9qrrEwNCYV99_S6O8ctXV73rne8SS58IgbphE9ph1-zvPXvkole5RcAuehTuxuCHTki00qvNmgXacTC5qqs8hTCuhqfzSZ2p5XT6drvf9UGB1ta-fvF6mmcnR8vvfue-Rjq7f_bFxdWLyxsX_dV189Off3Ox3zz4hx_95idfbrabl2-udi5cb5td499dNl9_cfno946Dj-XM7pvBRVr-YEoRV282eVkAGh-jyrS2mhCafmw6D4BKKQBILqFCVNjf7mLbV3WV36-by6Yo6-Pzo-H15TjEMEZG8uPIg5O2l3Hwu4EY_b7BwNm81IVR2oRVA8xgMhwG8DIr6v_9__afnlOxa8dff_F61faPPnq2bpqg4O2ry3YYGdh1bfQCqCZHCx4DEcXoExJzEh9IODkHwqH34FLsR3YhhqS1yssyRZ9iIiKOzCkBiwhKFK00EoAAIvHoDOroR2QAUBKj0RkHB0jMjCJIiAAcmRSIjyAAgAKASCgCIkprSZFZMImyFiSxYxEWEULU2ggIGgJAsgqVQua77e7drR6AIa8EEt1R05HIaCCM0RNCihHumJLakFJ33EKku6aiAKAIc0pICrTCPANAThFCRLjLNwEhS4rWmiTgxvGOMRhHB8Rj15Ex0QVhuL1ZBZckeaPV2HWcgAjhrnysdQwRMbntPjcZCZzdO99cX0uMSkEcvUJiSXeLBYkRgDhFZU2KibQyea4QUgw2N-Pgq9lR9ENeFilhPZ-dPn5y9frVZLJ8_P4HF29efPTJD4emfffu-g_-5PesUsdHB4cHsy7C9bvr5nY3dENyru_7j7_38bOP3qvq4vriykynzz56npnsX_xv_vibz1-fHNXnj07Pzk9XF-tqsnjz7euTx49U_fx72ua6nNhCp95FH0kpO63ugoyYmGwmPiBpUgoVodKoALTi4HVWSkwQIzBL4ma_tWVuq4pQDdtVCi75gDbTZNId9JPFlPbw-HwcXZblQzvWi6lV-XqzmR8tEMi7WFRVdNE1XkSAI6G029vF4iwrS-_Hspo2-2103uaWEMfQxhjKouy7XhhSCMIgkVEhMwMDKmWyTJdVv1nb3EAUNEKa-t0eaczyOvmQYuDAOi-MycLYBzf23X6yOKlmB4ICrIQTxESZic4DEhlttDF5gZBSEIxRG2OMvnsow-AYIiBG5nJxgEDG2mG7V0axG4ED-JHDCJJE4dgNaAttzdA0pBFAJUmUZ6YsdV4hqRRE5zkzkrEsKEl0OVUIPPRpHFjEzpe6nLAC9hFiECAUtkURhx4VpmH0bgCkop4yi7KVgCgCYNZZEfygrUVjmKMii0ikLRHFEBCASCmtQ4h3IC0kHYc4OTtiFt-2piyIxRiDIHEYrEICJaTIUFZVvh9AQGLiO6saAYJCY5AQyYBWDCiJESmNTnwUjpRnAoBE7B0zxBCVNsnFfr_L61liQU7TwxNb5YQY25BPaqUUMsSuJ0JOqSjzxOHll1_YurJZ5kPcNfuD43vKamVNNTs0CpfLk2KSlXVVTqrbmxttgN0Ymu363RtblpP5ye52U9alcOLIsR9UVilQkAKmKOMQvHdD0GVpbdatdxxdbi2HcVxtbK5sbseuL2c1R4dGxSBmWrptC8IpRFLKFFkaPQLgHYZYRCkEAQnRZHnwHRoNzFphEkjCmc5i8NGP67dXaeyG_W13s-p3ez_sSaFolJQ2t43N9MHpvS9-82sO0ZS5d2M1mevMmKJE1NOT49ur1ej88b2Hi8dnnIItSgcpt9a5rpxUZT2r5pPt7Y5TggTNEAzbMI79rn33-tvttiFjQhIDtFhOMyXd0PVNKOqszLKDxUE2LSeTWdO4zNBkUq7Wq-l0sm_Wp2en-aQ4Pz_6gz_8_dOTg8Oj5Ucfvicc7t0_XlbVvhuOTo-PTk6dcynG5Nx8MfHDuN93oBSkNIyjEl6v90ooDIMIKJIYQp7ZfhiPDo8HFydFvrq9_fCT72qig6OjFBKS-uC958aqk6NjDmFS1mWWra5XNjeM8vzx47Ojg81qe-_8fBw9xkBEITprTLtrtITlYn5x8e746HjomrOT5e__4fcu3t48fnh6tJj07ebDJ0-Y-8WkKovcKgbBKrdlpjOFP_7uow-ePVQowu69x-eTskjB_eabl3_6w48mRVnmmR-czQhQgg8MCIoiYhDcNMMQmQEDABgTRapFcX290dYm4ZAwMfQujD589erq5fXtSOrVavXmZnW172y1uLxdB9Aqy15dXrgEztLh6VExqXoIr9abi8060wqsIUOJSOcKlNqst513vYtDNxRlTiZzPhwsZ6f3lhapKqva6uC7gtR_88_-C4n4-VevF-fHbHTS5uvPv9Aa0djl6elHf_QDo7Bru9t2M4y-D85LvLluhhDJKMcpKapmk0zZ89PJ4UGBlY2GHHPvoso0KLBGh4CTs9ptBk7KZBmHNDldtNvdsN-P7cAhSPSEKIoYsJwtEZhIq1rH3sWuF4GklBucjCFFVNMsRs_eD41zPprM-CGkEMbBJeG-daRAC8TONzebdj_cbm4lYTN6k-txSFToeVVhx-tu33YDWQwAINBsurzKTCneJ4zEKiVMft3AmAQAbcajpwRhHMhkybO2hIkJGUQ4eADQxkhiVVgAVJm1ZZkSkFJaa61VdC6KEBIIJxf8MCJSGocweAUinIRBiIw1CBB6R0oNbQuoWdhYS3c4dpsJR-QUg4_RBR8QIQqncUghhDCSpeAiGryjlyJACiHEcWh713Uxuhij95E5kVWu69p90wzD-fkxoZrNJl988-posfDBHR4cxuiVUmVhBclosx_GUdLLi-u3b96Y3FxcX_uETdsBslIYw7C9bdPIwziM3bB5d2sSolYk-urlajGpFClD-snjs0dPTpfGLiYFJHzv-cnb1e75yemm6ZQbH94_48E_vXfi-mGWZdf7_pdffo0JX11epaErtFI-lHXx_MlDF9q9i_-3__Fvhsp8_vL1bdO_3a7z5eyXf_3r68t1uSh3-6aPjLVBa1hhMsRWo1YX7_YmMz0Hye3-Yj-Zz8DmgaOpClVkicjFEF0ab1fUudANpAiiUiBu26beTeal6we3i5oUoclmVbfapzHoDDm045uL8XoNHAlAI1bVbNjtRcCaMnpx651WREiQHMQ0m07ff__97773XpbZtR_eXd9ud_2nX757d7EeWne7XTvnwxj73ToO3o0BOIHg_nqd1UWz3cTBETAP0SjiyArRKkgphuC00UiUvCdSgMIkKlMgiVAJiCLBlCQyOy8sxhpO3tgcYiQUAFCKhBNLQgERgJRAgJJITJIYQVATJ0GtIEYQkZgAUCIDMt8lkzUCAAoDoqCQ1YgCCBIS-CjMggREyAQASAQxCguPAyIJkcmsLovoA2UkKAJAhOwdRE7eIRIprREA0eQGCUARJCEADr2EQFpjEKU1KSsgHFNRTvvdzpYTTgmFKUZFFBPHJMVyJm5UpJi9cEQEBDRZFscBQSQFYM7qiiWGfX_44FGzuo1pbLcbDiGFpAizInftYLMshijMiJhSEkFApbNMIQXv7sgyytj58VG3XyMIKYPGHByf9_s9kF4eHu52mwf37683NxdXN3_65__R-eGi79q__fc_bft2fjS7vL4WUn_2j_7oOx9_78HDB5yEgf_9__xXeW4eP3-urJ0ac3R8PDZDWWTnDx9__elnFy9ev_3qdd-G4AYlswfBjzF4Jbi4f4aKxr5HYWUzABAQArkDEXBMoBBQgFQMEUlzZMqssQYAILFWJMGn5DnE4JIi7PfN2A9d299erwD5ZLn0IWiboch0sTi9_2i32XZN07XuLkvw8Icfxd6NnqtJNTs93lxdmiLXWdZ1tyBisonWNDs4GtzA7GxWMQdmSSw-emuNENo6D13LwsB48Pg77JqYOM_Lg9Pzod37FJNn4JDnNOw7hERKaWO0tcGPwXkgTQSgKAavlEKlDg7vMWDfNqQVaqOsleDj6CFGyiYmyxWxpJSCJ1SKiICFBRHBqDiOOrOKVHJeSJHSIowpxrGPQxf6PoZgiXRuTV0rMkjAkd04CqAgZmWVF0ViQWtVXihjVVEwYvIRSCliiC4FBzHZYqKUYiKliSzFMZJShEggKQyQIsdIpJ2LRVnl0-XYN86NhACoonchekmgskwErLGT5UGIzo0-BS5nEwFAY_MiB1Ico85yH6LWKg5eEgOiQuKUkuv5P9yOtc39MOrC3v2NGAMYpbVNzGQtKSUx3om6kFBlSiJLSolZa4tEImBzm_7DmAEUEqi-G13X9l1blGW5nEDkop5AciDS3dwCsO975Ggztb68Udbk9USAu6FDIBJBwa4fTGad8-v17vTBPa3M0LfsBqt1GF3XBzK6mE6Grq1mi2xSJI7OjbawqFUYeltWnBIpjIHRaFvlkVMYR0rRGPDNNrStUnp3_e7s8ft-6NAW7X5XlRNJAQAEgaxGRZKSzgzeDTVjQGYRTtELi8rKoWuYRQNV80WKvTamuVllWkiJQtQZkrB4F8e2X2-jG43G_XqzvVmdPn0gKRmr15fXMUQ_hqqaVLNZHDqTmyScGZV6h0aPrTt7_qjM83o2NTZLIRR5WdXldDY3RjX9WC8nJrenjx9M5nMEEYxFXgzeNc243XdWa5TU7fvNeqNypZUp8uzJkwfa2MXxmTVGKzw8mC8P520_3H903xg6Olyeny2nsyovs_m0UlYfHRweHB0IYDGpDw8Wm3V7dDqrZpO-HxGhKDOlCRXWdcUJpou5zjQjLE-W3vf7zfb26nqz3SDJ69e3nMbBuc1-IyzRBxBQShbLafJBK4CUstx6iFabO9WqNkokFIbyzEwmtU4CHOeT6nBel3lR5TmwPz89JgUphnKaP7l3mht4dHZ8eDCry4xjmBf6wdnR-eHy6cOzw1k9LbPz00NNhBwfPjzPFF3d3BaZOT9ZKtDWmLqwZEiALy_XgNT0_X7v9q3bNn1W5KjozcWVNXq1by8vVptmKMtSTfSbtyvPQtq8eHe9bjtHtGr8r7989e523UVxAtfXN9raw9OTNxdvb2922aIOiX1IL9_dvLtaoQJLVOTZpCqBg_feoERJfvQ-eJdGADg4XrSxn5RF9GFoAqDKSzu4fmiH_90_-6cnZf3f_n9-Ws-ydeeSVa9fvcomeX04_70_-f3l_IBDavbNm9v1vh0jJka6udmD0kYTGlwc1ilwbszZojqos6ub3fXO-xCjgHMeQggu-M6TovG6CT4BorYqjVE8nz651623_b4zRgQxpgQKGBAkCosqMLSD7zoODJmFghQHnRfMoDLDfSIiUghj0pn2PqTAOjNECnwkIVVCdOAlJhemdTZG7xsHmCTKMCRAzABnRMl5CDjsXVYZNtGnFHdBIasM9-uRhSkhNEkXZYqerJEQWWJyAVKQ6JA5pcghEhHElE2q4AMQhSA2r5TWiIaIfBjZRVRq2O-yzChAgKSN7fetzXK40xchMiApJSwpRiIAwJSC0pRikhA1ApLyzrlhRAC-k7yi4pTY-5Q8iHjvJSYQEoG-2RIixwTAIgFiUigcfRJhTKRV3_VkjLLU7roI8t7981XTHcyn3dATKef8pLBFnvXDOIx-P8ZvXl58-dWrizfXPmLXdv3gBSgObt90KcSuGR48OqJJ1W7HapKbwqI2fZDFbH7y9P7VmytxYTYv16vhIMutNqXS69U-tMOw7j56drasq_ODg2-_flmZfBja-XQSiTfNMDH67HD-_MF9FcJ_8R__4ZOH57vd7m9__fns_vnPv3lx0w0vr25fvLngkoLw1bur7arRWqGWFKLOrKptPzpTVSDSrppm1bZtF0LQYLnpNQBaYyuVzyekKM-1KGy3bXOzLzMj4yhaj50HFggSB1cUWb8b0Kez9x40141Ramyagqjfb9n3ftXahEVmJKXovMRIWnSeNbte54Y1g4CyZty3GYAxtixn_6v__B9fvtvcrFdXm_52tZXo5pV-_eLVu1eXlzdr0Nr1AwSniIRTSqkoqqzKkQiE3DDkWcEpLc8X7XqXGxu9TwwhMOUZoojCMDhUBIkwJgACIhSmu2MHIEhCRfQ7T7AgoEgCIkJS2khCImERuFtVeQ936fsQBe6OA4giICx333dEMEpiBGUlRGCRxIjIPtzBJVNIWltQIAiIiEoJoai7OwAAoM4tKM2BOSa5SzpE5iQghCEhglIKhTFBfTQdt70Ip5AUEjBDEgTQ2iIiAZhMg0hEQBRjTfQ-q2ciYMoy9Q0BqSxDjRyYhy4lDs5bazUpIpVlGRL7dhBOhKQIg3NG6-jC0O-i91mesQ8irBRISiLOZjlz0saS1qJQkSJFCJIVk6HvUCCvquB5dnSCBG4YdV7FGM-efpzcOLqhyLP7D57EmGbT4tGjx_dOlx-_9x5H93__V3_1n_2jP3r_u-8PvX_46OHR0UFK8M1X337z7ddff_b5p7_54nA5Pzo7lSBf_-rTg9ni9mpty-Lq6vbVV6_aXZdP6mfPHjz-8D6TVvm9j6Io8CEE59oWlYrOK6M5CmYWBBCUEHII8LsCuGIBUopTAq0UIofILMrcaU0ChOidR4JyMkOtyODB0RJBtuvNzdWNzspds1kujrtmK5TqycH05OTsyZP9apNnJrTt5uZWBARoaHtbFSiYBsfeD_2-yozOctRqenDoQ7zzXWdZPTpvbMaRQ2AOYXZ67trGxxTdvqyPxnbvui5GP1mexxSUCCYn0TPH6BynSMaQtgAqOE_WigAn0ca6bu_GcRja-ckpGhuCAIAwkLKkFYDEOEIKqJQ1OSEDMicRBFMVcXBlWfhxDC6gVvZwCWRAGJiSZ0CUyKQwjb2wD33vmi4rSxBSJkdgCYGQjLEqs4JANr9TRIlgUZ_oPNf5NAmRyQ0hIPuus1UtCKYsx3ZAZQAAhAQShKCIQCKhQArGGEEyRWnywjUtap1XU4hRlzlhit4LgtE6r-aiMCZJ3tfTZeI725he3nvg2tZUFYfxTrRBWkli0goSIwAykLUCTNqkEFKK2mrSym83Yow1WWTmxLosUWlTTRIn9om0TjEiS_IRCPNqEvyYFTWmkUMYV9dUlNpk2lCxnKXIXTv4oY1t572PLkwWCxKI3vX96Jvh2Y_-sL14228342oVxqHvh_liqlFRrqdlQQhK4fWrN8ujpe_73dUtSHr68R80m01gEWHQOoSARCbL8rJIIjrLU0LxQZHWtgClI6qTT75LSN45SIlDRFLlrCJhRardrsv5MSgA0cNmb4ucvU_Mw2aHeZ6YAShxFAFJLAruvLGSYhgGrY3OsuD71LcmL6ePn4Ruj7_jHA2ckjYqq3MZPbvRt20a-2paRjfsV7cuxGIxRcT5ZBbS0O4a78Z6NiNdjIPbvL3udntO8fbbGzf0_W6zu7jerm6jSAoyn011RtOq1mXGHKaT2eWrm6KsR4iTojJGV3UdQqirPDemKIp21xAmTklpct4Nzntg7301rR49uPfJ93-wWExPD8-0UT6ExWwytL1G1TX969e3m90OFA1d61JyfX9yevjJDz46Pjh4_7uP2tGXRUGoEKkqq8E5jagElwfzsR21wdubba5tDDyZ10iyPJ4Lc5UXChFZHj-6P_ZNs91XuTk5PHhwfrSYT43BJ-cntSkgxNzak5Ojs6O5Eiy1att9RqrIzEfvPVzMJqSwNKZvu9OTxXtP7s0mk0cnx12zXy4Xxio39sv5tMhNYbKma4vSGqVAUpmpqs5La7PCjsPYdaOIENHd1yzGBCCD8-tNrzT9xae_PZofeobBB7CWNV3frPd92PTDGHlMafAyBv_3v_629SF5-Puvvlw1zexg9vOvXq7b4brfR6WG6G9vtofH55k1V7erX_zqywcfPtms98vFfOTYOofCyuZuGPf77uZq55MUJgfGZj-6PkznU2VVZlXyslp3WiAwZIX53neffv3ll2NM331w-sfvf6fdDPefH_ziy5dv3t28ffVWlGGDH_3eD5yLOituNhsvrvfh8uo2z7P1qgENoLUAe8-TWb3bdmWW-SjXq4a07iXpQhgjjwFC6rddWWorOO7GyGIrm9lsd7O79_Co2W3b1S4GTwqRlDJWGcsxpNFRShwEgQRBmSybVX6_JzGstT2oTIbjthNgM8mIUFjMNEvBxyEkpqzKUIkmGcY0tI4h-hgEWSOmMYKB0Y_DKJSbkKTU2qTALna3O9lH_-2KU3CrQRTNn1XsKVx2aparLOMuqkwXB1OTKRhGg4BJknPMIEkUEZBiBpXlSut6uZDoU4gCHLoegEFB9EmRgjsmotKJo9YaUuQkAsgJjM2Q7gTiXhsFDEprJERlyChNmmOKMQgnrbUCYRHvHGIiBAYQRFICzCBJKZWc01YRIftBoqOUku85REBE9jI2KUZAM3QdxOiG7he_-aKoKlQmJn-4nFV5zimu9y0hmbJ8-_byerPdd3E_jPX8cOi998EqNTQNat00fT2dy2KuPNbL0hirbVFW5dOH9548P6_zwrX9dFH_6AePbve9Vcpay4lz5KLIn94_F8a6mgydOzu-t9pudpvm5HSJLD__zbeEUNSFIXVyOtvtd7_5xVdYlp7s3_7qi7_--0_7Qn3-5YuItL646lb7_eWNUcq3QxxcIkVaqfmyu1oZw65ph13Tt3tFpDRqq0GCKuqoSGXWRwkhYgzdvnGdU8yYWFkTQxRJHJIujYQ0tGN1OFGAt1eboiqOT46vX7xZvX5nVBZ8GLvR5IUt5jHGaj7JlPWO-65DouijJFGk86yQGP12yKaz73z4MRkaXFh1ncyg33c3by_E2NWu2Wx3aNXoQrPelFWBSOyDsZoBdJa3u81m_U6T4eiUoO-DoMTRA2g0ujieYmZcNyAnRQQiEqMihQiSIvqkWBQSM4uAQsjKIgwOUIQFBe58tCwJUTgJ3gVVowe8QwMaJERmRIL_IOKFxKQAWe5avBA9AACjvkvsIKMySmvUmmMQAADFPgEpAOG7PjGLyrPETEVmrUIkSWzNXVqBwIe78mqKyWSFRI4ukkIBIERmEefpLtLkg4TEwUvilASRQCA4b8vC1qVwiOOAMRJhdJ5IEQAKIlJeTYehiSEWVZViHNs9EqZxNEojosmyJBzdaAjZh-hGJJQYjbEpemZGIlKECETEMabEEL22NviABpFo7PbV8VFWFLv1SttidP3s4LRZ37Rdlxgm0-VHHz1HSKen9169ePHh04cS49dfffvjH33o_IBK6Tr76osvfvmzX1Slvvj2xZsXb4wxf_aP_8E4hn_wj_58fXPRbJt26H_we598_ulnMcpsuYgcRBdtM_zw9z4WEVU8_GR2775wEHGhC_m0QsIUgjIGkFSWg7BEACAwihXR3d4FFSIprRTz74BQgmGM2liiu2UmRu8O7z_e31wnPy4XR0aRIkRJzbZt99uqqrVWx8fHTds67x89e76Y1dvV5vLippxkiDQ7XPb7bWaKBx_9QXfzQlD5btdvtnldKYVFuWDQIXpQenlykB8cMadytkjeO9fPT0_rqujaNrg2z4sUPSBwDMV0IewlxBBYW0IQ9oFTQkWqyE1ZMeP09Awljm2LSMaQG4ex7zjyfH6a15V4F5yL0QuzMqC0FqEsKxKHGJm0iiEJCGXWjT1pqwCszTjcBZqSNjkaY4qMGUPwRhskIpUk-NAPKYwMiEBlfcASSLhr27ugG2kNChnAGIWkqnJibFlUkxhit9nlVTb2rRtCPpnWszkL6zwHAU5R2Sz5CCwSIscY_WjyYhjc9PCIjBq8967XWZ6GsLz3FGPftg0SKGOqxUFZ1mBts9uziM2LrKhJ09A0HCMk1tYCYkgJNAEgKbLWxBDiMBJpJLR55t0oAKStzmtOiVNApQhRhEkrAlCKlLXMwJxMlilCDgmiI6IwOiRt57P8eOn2jZnkktk0eIT8DnaHBAIIRmulSVkhLOoqMm6ur7RGxVxkxDG0Nxdd18zuHQXntDZFVShtyrwUhKqc-KFhhmHon_z4Bxni6LzSEkPQRjebNquqxfETQTM9ORnGQRU5KVsdnSoD4sGUMyBd1NPgHGr0bQ8xImrRWrJsHFK1OBjaffTe1lVW18V0qsiU0ykQJoDIkbRGQFNkyUVOiTQi6my5qKvF0Gx2Fxfj0M1mM9B26EetICs1MAMr4IQImpAAxrbxbZdcn8ax3ewIQCBoNMbmgHx7tUnARHTy-AkYqg8PGEKMvQYwJMPQ766vDKV-3zgf50eLB4_uh9EXWZlnmCszq_LFYnF-erqYTI8XC20yRq1z9d57713uGq1V37fj6ElRdRedAnx3eXN5efvFV1_7MOx3W-c5DoFTqurq-mb9__irv_jg_r08L7WxZZ4dHB6UxmRG3T86WF_vjw-P1-vN2cnhw7OzR4_uX9_s_vjHP9KEWmM1rZpdm-f27OSo8UNps816p0HCMO73bZnZ5Wx6e31jlcYUI8C9o2WmdWlNmeUx-t3QKEOzunLDaFBlljbbrdX66HA-DG42za9u1pv1ipN_cH6qlRnbdlpX4v20rkxuqswqpUhLiJEJrLaZNVWRKbizZQMweB_yPLeZiUm6fiBreheHELrRuxCaMZA23W60mQGtGXAcx6btmSFodXuz2o3hth2y89nf_N0XgjKbzy83u207_tN__Ef_089-24--nlaXm30z-NvV6v1n79-u1kh6s9suDhbv3q5--OPvXFzfXr2-HgeX57rZNt774qAsaltOddeHhAIKKlFlWYXe9ftoM304qSKoZ48Oj-8dfvmrr04Ojp8ezv75D36v2Xky5q9-_dlPP_9itetIa0Zl86zrOjfGN2_feuG2H93gyzoLY9h3TmXaFJoT3ztfBp9AUGtVZ5nJrEByhM1mHLYc114hcwK39cKCgPmkUIR-2yYnVVXsrm-T83EYEcBYS5kJLqSQwK9Il2QwkUhMBJLanR9CdlCKtsaq2A9xDChRMtAKnU9ocGjGKJLPDMeQQgxDVIrGYaeiH_cdeQGW8mR2_W5z90oigaqIfSqPC-9Vn0Q_nCtFGtHqjLtEo44jo1acAodISApZ-lBWZX-7oTtQOgJpBQqVtQlAGaO0VcoIiMQUQkCBssq0NRIZFEpK4W4Gn5iMhuQxCgPYvLBWoyQQceNIRHcnDFKKQWJiUgpBQhhjCFppRAFhQUiJ73prLMIgqAhSBJDoA3NAEvZO_MDBcxgZWFIU8cQxjR2whODvip7BhZRiiLEfhuPjQ6Xo2aOz2816tWmnk2rbbX77xds3by9bH1OMwQVU1KxX0bvgZHa6AGBKAl2fG3E-Ianze8en80mdFZiosFhV1dHp_PNvLg2qCMmnMLbd2Hfn58fWmKF1r95cMPPf__y3i0X949__JBcQpKuL2-99_J6KrFGOFgvncN-Oneb_5e9--dW3bzrv1-t1u21E-zSGcdstT49SlHJeWqNJEIX9diORXRdJkip1Vmoik0C67aDyPFk0B3UYPJDKC8NRAE232RXW6IyiC26MVhkABEqh96jIdQ6AEJUEWV9dh3YsJwUGj6VRxvimIcOowGba5jYvCh_S8t5p6EI5qdk7RVqSLM5PfvAnf-j68We__rxpB0mJToqXv_zSx3j4YPHF52-v3r2tJ7P97Y2OLg3DfrvLqyyFQJgFiMNuB5ExhujZKPPex-93Q2t0FkPK6kpSjKNfnB-HbkARSUJagUgU4Rg5BFQUnL8zbaEQp2DKwt-uVZETKjJaKYh9DwBolFIKOKbekbHCzJwwJaUNpIDCyKwJJLLESIAkgszCCJEBUFkUHxlRoqCAMJNgSlGASSullbEZaRIATJJGR0jsIyeW4CXEFGKKUUJUSMKQmAERWLTRIIlIVYfLMPSEACygEQmQSGkSACFFgCbLBKJwsnkJSQAgeY8pKa1ERBKnmESBybOxa1CBa7tqUYZuQENp9MYaQLh7AYXZZlaT1taCxuhGpVWQxCnpIkPEGCISpOCDT6CQCDkCE5gsY8asWsyPDtYXN5y4nEwU2QTgXP_sOx8wwNP3Hp-eHl2-u0zOA4dH9-_tmvHT336-Wu--_PzFv_uLn1y8edf27sGD8zcv3n3zxdfPP3jatGEys3_-j_6T__6_-3_--pdfTI-PsjwLpH76P__te99_enr_wetvXzy8f_j48b03X317db1RRx__R83mtp4cJvZZVbu-FwQExW40OhMEba0ucio1g0hIAEikCLUkAWBCDUSgFIKQQQARTiyokTEmpRmYh-02Bu-DFwRlFREp1MENfTu-u3h7sDwUgtV2PQ7h_tOnp48eBR-yonRtJ0l8DNpETuz6oaiq6F3c76Pz5Xxmy9zUs3azKyZlVU02u8ZYrXUhSNEHECry7I4-yYTsOfkeRAS1Xcwl-tQ7nRlIgkScZBhGU0-jd77rJ4dPrUWNiiUCqbLKgxtd3_ZDO10emeUiek_CnDj6XuVZdL0ACBHpzJRTIlAAElkwkQK_27AwKAWISRJlihlNWYAgGh0Gx0kUkgJQmpAjAHAYtNEpxGI6CcENqzWD-GbDjISpnMy63cbWRYpJ10V1cDIMw-ToROI4NHsgm1gAYHJwxhw5MgCiUiiAhEobYV9V5W67m52fSkQPySDF5H2zt3VNzJF5aLrkfD6bJRZRhoD7tjNlNjad78foe3DejWN-cGTySucZp5gGJyLAojJDIOMwZlWRFaV3AVlIA6EQIBHGGDlwDBEAgBQnr6xRWeaG0U5KJJTEd0QMDi60rWta9oGDk-jG3cb3-6zKjcmySa2UDT4kHxNzcKLL4uDsbLqY7W9vvHcxhOR9pjUKX37xDScVJNaTqSCyBEnSts18sazq2ei63dWtB7KZnR4cC7PSupxMmH2_XXs_ZJNcTYvsbJm2u_12q7XJ6omLrml2StnibKHBCIkbRmQOY28WM8qM79rJcgHiJVK33RqtJMWmberDQ5xkMYoEtnmOQIDAIUHiFENo967f66Iko-PoonCMsT44FuDYeUggIdzZTrRWMYXErI2xZUGIloSiD02HiN12RYZ0mQ3bRmllrb1bUVltwuB818UYUoh-HBRA3-13u93lqzfvXl_0TTd03WJx4KPLtb1cXX325Vd5Xqzaxhj1D__wR1erze31ejLNJ2VljTHWPn_8-OZ2AyDT-ezJ4ydt20qAh08eHB0dTauy2bVlXfZD1_bDJ08ePTw7Xu27r1-8bdvOFvnq4vZ2vVsezuqy5BCL3D5_-nhSZevN5uOPnnvnTKbv3z8lY1hYUsqITo8XR7M5KfjeD97_5OP3Hj04fe_Jw4vr1UfPnz64d_Kd5w_fe3xelbkGtd6sm2bHIGfHx8cH89mkqIuiqvLTg3mRF5FjofXh0fRoMddEs-nk-PhYgCd1Vk3qm9U2hsRI2pokEhJ_-ptvL1fNi3fr85Plvg1jCG0zbvdDiILGCKEy1jGvN-N26PbDcHm7-_rl1RB8DCCI1-vt64vbuioS4dAPb6_WeVH4yL989fr1fvdmu-9G__rd7W63u75eR2W1xftnB3_9m8-_-PyFF2lSJFCrvn_2-BEwz2fLrz__9MW2DRI_-cHjpunfvFkfnC5BRTTIg5vNq-a2222acTuEIYxDKq3umpEjlbP8_oODk_n8waRgn5rb5vbdBhl2bfPB_Yc_fv64rouX3f5vf_nperfzoBlIMlUtDoZ-t9_uxjCOzqXEWZUV-WTfDKf3Dp4_WfphODk6Xq-3-9WerSqqDBHbkFrfNSo0zWiGoMYYRSiihMCckJQxmrsw7ofTo1lRm6uv30UfwjgCCGV5DA4A3DhQOU_MYFW73maTgp3HzLDV-qAGYTaQQoTAGsWvu9SMcYy-H_UsR6O1UjD0FAREtAEEjGOE0fOqdU3TN_38pApDUky-d651IaTtrh8IuR_SGA7Pi3E_pt5pBSEENmxmJjEDgC0thEQxpb5LIbEibUttc06stI1jQG04SlHVKYYo4kaniCSBH8YUgrFlDH3ynpAFGASidySkrLJ5FpxDohS8oMBdvgIBhYILQgoRYogQE6MoJFIYg0dEROAYUCtAFgDhFIKH5EgRQyAOYRglehQGASEGZkwBUgRgpY13kQAQwfVudnhgtEKQrvdPnzxZzKbIKdPZ-dH8f_jLv_v1L16GFBOo3XanbaFE-bbf3qwBqJjXjrlb77vReQUhwvR0aY3qd_31zfpmvR0lNb1_cXn15mK_We97l64ubq_e3Tw7W0zr2lbWB_8v_-InH7__YFnPv_-dx_ODg1_84tN9O4yRi7KcTKur1Q4hvV5t_uX_8JNNt52_d_hXf_3btu-GxNvt7XjbLutZHMa6rtv9kBeF37fGKHNUDrsmjiykGaDft77p3RhiZLLazougWM1M7BoeQ0iJMZCCvmlTSCJ48GABo5SLstsNsG_9doghgqLkgxLxzV4bjQkfffQo9mPXdLYs4-hJEgBwjL4PY-_Pfvy9tN_Fztlcu763ZWZt1if5-M8-7K42CdO8qvrNNSoYN-3rry9Ubi-uroddm-W2mGXRcbduiukkLzM_jACcItvC-HHgwNPD5eTwBFJy4zDuOiAFqEBiWVcoBCkNTZeCR04iQgggIiHdMV201ZgSgihNrh-BJZ9PNRKnxNGjAJG681az9yIiSLoq2QdNgCziPUQPLMiMDASgiJDlricAiEgaOJJSJHyX_0Fg1HgXJE0xZVWJd6xMFwCYADClu5EycJQQiFAbI5JIKWAQIlQkIMZYgcQhivCw3SIix4iEiETCrvdkjSkKZTQR-K5DQNKmnEyAqG12BESKIDEAxhSJEInc6ISgmk4wcFEV_WZvLHFKymQ-RJZIpKIbgRkEdF64rtXK6CIDAu-8Qog-2jwHTikkzA3HpLISSLQ2jKCLO3dt3u131makNSchgvuPn0YARfBP_smfdevdMIaDg-kPvv9ht9_9_S9_--WXX2vLikxmMS9ss-8uX71LCuu6Orp_PF0eHZ-dv_j6ze5m_53f_4RIT-bl-uqGlPrn__yfvHrztpzmkEzf9xcv3_3sF1-o7N53kRSA6MyEMcyPDvuhQ5HETHe3oRjTMIYhCJOtckXg2y2azBSWOTGDcPrdphEohAgskFhlJcehb_uDe492V2_9MOi8YITtehujcIrVZMp-aLu277tmu58u6uVysVlvmmZfl2UCRC0-hRCSKMwyi7ZAUMuHZ-O-SXH0fW_LUhlTLqc31zdaZSf37o3Ojd6RzrRGnZmm6YBBmwyJTGVd0yJKYI4BqsNjosABSGtUhkhFFgE6vPc4um5oN8qY6mCZIrthQEDvI2o0mUrRpX5AQVPUpCiEIClqawFEGIQJtRJOeVVN7523NysWAEUcQugHIVB0V3AXpQwgiDBpm2JSWZZSFE4ISSRASuxcjAmFFWSmKCxqW08NYbfZkAY3dF23K-va-xHYkzbtfnf84D2TG-Y4Pzlxbgw-xJSyaqGLjJQmY0mb4ENkvoueI6mD-4-jdzHx0cOnvtsFP4YkktL0YDo27X610lluc3tw_1G72dgiM1nO3mW5UcZQnqeYjM2K6VQR9v2gtEH1O_MfaXK9y8oqL2uJLnlBEmNzNw4CoDJjrUUQWxYxBmbWpFKSO7We0oZZJCVtFCkkhdYQIIhz1iAqjM1O68w5X88f5tMiMC-Ojg8ePrBlvbndnD94mNfVEMYYQjWd-LEPUYp5nXy_ufzWZIux619_863SxppMAPfbTTVbmjwTAGX0brOdHR4NXS8Cmc2MKeLYrS9W2hZks_LDD-bLene5u_e9D6BQGZm22Ss0tq4Csx96JCQNPHYCRLYITXtw9Hgyn3PoxmEElPrgZH-7KeqFQkTg5KOIAiQzqcFQiAmJQRnQFJkmiwOOcbo439y8QUCb2xRSVhcmy5nAhyAKzHTKwaeQePSKRWJUiK5tAVK_2TQ3N1rr0HW-bw5PjhXSfrdbnj_cXV8hCmriIMZaNLqcF96N7Ie-3bumu7m82ux7NCxCz95_jpLyMrNV3oz9ew8fnp4eliY3Vt0_O6urSmtZLmdHR4vTo6P16oYYymkZnO_7nlOKMb559VaQAJSy6uJ28-bVRVEXdVVe364ePzz-_LNXxup3tyuj5PGj07YL15ub04OD6WQyrcuH9498N7ZN-8Gz-8fL2aPz-1dXVz_4-ANbmHvHB9Nyqhi2680HT-9P63w-rRBEiVitMkuzab6YVUWWCUjw3guzT1pTCKyVlNYUuSVBhZQXeV7kElNV5EwSYrCKUBnE1A_eQ2qH-OVXr1--vfn6qzeJYj2tv3l9c37vWNcFM3_75tqz8lH-5iefdd6t20HrfIgxy_ToXNN0612b1_np0YGL8OZq1Y0JZhZr9W_-3S8ur9eK7Le_-jaFcHO92W22i9li37ZHVX67br9-fZVb8_DDp5ttJ0JlYZ1zjoff_PbLTTPkRp8uZ4rVz3_5ZX4yvb26vrpYGUvalhBZKKlJNp9MloeLf_7nz3_96UqB1jU9e3Roc7trhrYfPn97rbWGUttMl6X5P_5X_8R3YTsO_91f_Pvr6_XVzW4IrK3yw8g-eOdZIYAahp6FE7CgHJwcHJ8fvvj26tW71liprDG5RaWcpD64q4vb_e363VdXPKawHZRBmKiqNDIk0sQh1lXZN8Oizj_56Pm_-b_-_yaHE6U1ZJqU5siZzXzXkojOcuejscoYFb0XQWUNKwPKAIoLibvBEEv0IgxKqVwlF6jIi2mx_-YyBSaNrvVJpDqquiHUB7XEKIToAIME74E4xciDS84r1AZZ6xQvejXE6kynAKApYsJIElkZio1DZqMgNH3sGmOMmU3K6UKQTF3b5QQImCErixg8AwohCds8R04IUZCT98F5AMDsnFODAEpB8hEQRO5Gq5FBUozIeFd4Q0Ih0HkmHAEBEK3OynLKEgCAmQUFEMLoRTilRDYXiBw8cODE7IPWZXKtSAQOHIKkSCgS7xyUgFoVVenHHpGEUxjvwkiULSdFXkKKL66uv3l5eXZ0tlpvYoyTaXV1sSXEGHy7WoFC1zth8m3HEsduIE193-93vUswdl3bD_u-X--6m-utQCoPJm4cuqZpm5YlvH5785c_-Y2dlt9-_e6_-uGHCeyQ4GbbvF7dTIvs5dubwmb1pC4Optv1zk6msigacT_9u1__zb_7rNnvvBs2765gjDA4HNqxaYD4-PsPN2-vjcJh03VXe_aSiFmTLjMoDJWZXhZgsxhiGJ2MDO2YuhB7Hzsfx9Hv2hREW5v6uFxWruHd1RaQlISkJCVQMWXaCMfo_Z2cdlhtn3_48PrNKg6ONGBMWtsYWQE8_ODJ7sXV9t31bj2ePD2fHR8X04mZ1CD8-suLajJRi-nFl9-YzLZt89mvvsoyGt0Q-jHEMO52Y-er-4fIod_caqXHrsMYJofz6MR1TZ5neVWlmADS7mpFhKKpntXAqWv7vnMpMIVACJA4ywtIgYfREFmlUoyKEFmijxJZKa0Y0hh0ZqP3khgAERRISmHUCpFBBBCYFCEq5gicFCq8wwYhsQih4hRJUABEBJBA4HeAkCSkkL0jUZJYWNIYEFBilJA4MiCkwKQJhZmF7p58AOEEiBKTMZaRJUQilUISEQSlSKPw716eCPMHp5KiMOosU4hxDBwCKSKrBYBZYkyQUp5pQpSESpfGWlMYkxcAYq2ppwfR9a7vOcaxbUBhEtGZRZTECYSywgLR2HVaAZJSRhMTAaCANjrFiICQWGkjKSELIpqq7m4uy8XxfH4UOSAJotJ5-fGPf-THIZ8UL75--6d_9uPN28u__Zuf__l_-sd5Ya-vVz_7219_-dXbGJwyRT92XdsBy6PvPNtfr9776L3TR_deffXi9__0Tz__-adodFVnn_3687PD5X7c_eynn__ZP_hhP44QXFIKgLphIK1MpZQ6_kBb02w6VDovqxh9fTB3gzNaa60hhhRYK60KxSK-j5IAs4IQ2Pvk_N1xFu6yX3c7MK1EkiSfVQV4dq5XhJjSuN3ENBpbWFsG54IbFWGeF812ba158_XLZreZTubsB5_C7OBUZebs3mOjaehHQCJt0OTNzS4Og1bCKe6u1wf3zqrJtD48XV28LeuiKCejT8bqopx0TW-KKsWole27ASUeP3rQbRvQkFIKzpenj0gRhITGMEA-mQEqRQKC_dgkF5rdKqtqbYw2upzNfdvG0Wl1J6YQNzamLqy1wbWkLQmpoiCtQ9eKACeM42iNFUJMSRMhsNGIKSpAiT46B4ghsilKU-Uqz1mEUAsgJMbMcIxKo3B0Qw9hSOyT8wBRkwLmejJJbux2awBq9puiqhTKdnOTV7PI4pKcP_ooK0s3jkOKTDorp2KzoR1RKxFV1hUCDftmc3VRzQ78OIahWzx_v1vvrDUQvB8cKi0xxmEwRQFKimoqQu16lVujSANZhaRBSCtlNZAGUxCi0lmKURDysiqn893tGoFJaVQECNEHk5XADCL5JI_OD21b1BNmIYVam-g8IoWYUGltc04BWOB3bOAABOICpKhRRe_yshzcfux86Nqx67rVNXBUikMYBYC1DkPrd6uinAIpTrqaHTz86BNCyKvcar1br4iwtFXb7n3wfedAa2usCHjny2oiKSmlul2bAhw_feD6zjVt3DTcdcNut_r2hd_usyK3ZZ6Xlc4LvayjBwneZNZvB0TOa2Mz0-82IfiiXoTB-3GMfgguxMh5VkwXC06QlcXY9cklVehyNgmjj8OY59aW06HfV9OpH5uD40ecUjmts8U0DKN37H0yk9KPIY6BY9KkrNbskzZaE8WQEISdt7m11uR13e-2WmdFNRFOY7PKp1lIQlodfPfD_mpFDGPjNFqFdPro0fZqrVXyzTZ6Pzi_urodh3BytHhwdNq1nTV227Va4270B_N6Pp1WZXHv5GyzXl9eX7ftcHBweHr_OCHEEHs3Zlmms_zlmysOIXC8uFk9ePrIBTedlG_frUIM3eiJ-fMXr1HA-XR1u_v29cXjR49---nnl29vPv361f3Tk2YYllWZOGZWn50fVVk2Nl3f9EeLyWq3nRQ1A0_rqh-HdrfPjRFEBaCM8j4559vBrXbdcj6bzcrMqNtVk0RsYZUxxlJZVowAArt91wwjgPy__qe_a4Zhu-3-zd988ezRMeX41ZeX66H76JPHfYKbdfP6ehOZf_Xbb379-bdN79ajdyBv3q7frlfVZPZ6df3y7dWrdxfz5awPce_825stKbUf-t988_Llxe2Xr19fXGx--pNP9_ut03x5sTLaIMD0ME-cYvJK23_4n3_w13_924tdd3iyvLq5enW9NRqms2qzba5vV16QrPn4g2dPHp3-5O8-W57MNuud4qiUcsPQ3LT9LuVk6qIYgltq-vpiVRamOlTvf3S8Wbvf_OzXN_vhzdVmtW5sZVM_Tu9NI_Z_9uyD7c3-p998_T_-7JcXb29tlfsozKHZdzYzh8fTy6vb6N1kMa-Xi3EY6umUY2j6sRvHp89OmCWk0DRDO7pxGC-_vXDdKB5ZZPngYDo31YHNUHcXDSTerdeYUqXLg1n15GTx4su3eZVPDorNzVblmR9GjpEUQEJDGpTYTDMzcwQkQGJLuiqiT7qyEly82RDwOAxgjRBmdWEyHSUyy-RwPqknIYQyz5glJtYKQUl3M-R5URYZxIGACZQQaKMMEQpIAgSdVbnvRRxESklEnChmdoOtNEVhH_NS86bBwCy6fngSHAZJQztApig3pPQ4dsKASilCSCIpIAIh-W5gAsQImNivhUOKiZDCGLUxgEIaUggIoLTi5EWYNAmz1gbuxv8MWZ4rTX2zRUWIKBxZEqAobURYZ0riCIk5eECRGBQhpxFSgBAIBUEA7hYMAiApJW3t0DldFIcPngxN9-AHHy6WJbvA_fjZp9-Q0c-fPlj1428_-2K12rT9sNk0s4PDfru9fXfJyFmR2yK3hUouxJQIeOh7Y8tx6FOX2s1mt29B6RjD1avX-9sd6TwJt9tWW4OKri9um32_3rWDj2-2gzmc_-zTL79-fRGiTKYH758fapttuvbXv_ziqzeX5nT-f_6__PcXn71b7zfXb94WRravbsq8lL5n11urPWWLH3242azb9V60Sor08UTmBR1OnaiiLnWhlaLgkqAAMABIYpNblanQDdI13PXJRdbEEfPMhC4Ih77twAcefYoMPiiFxKyVsiZDgTKvlsdHN5cbY8h7r0HfP38IVu_fXVudq1xtN01wsHh6rJ88bl682t6sUwoppaqq282qu77srjcibnl6Cpya7S0KbtYrrUgRQIhEBjCmKCml5eliXO-i6yUhJJbgUdGwb5WhYbc3JtOi2v2NpFTPFtpi2O3DOOa2CN7x2ElKmEARgQCHFIYRktwBz5UyKMwxpeg5RSTNd2I6SBjFmCkpUCAQBRBVaSCwhKSzMrkRgTixUgqBQe7oPhrojuUjdydGIiDUSHD3SwlJG4XMHBwg4h0GlBSQpBBI3aFAAUkhACbWxqIwJAEEROQQBFBbrRQBAHPKy4qIxn0fei8swXlMIsJIJCAxpaKamCxPbjTGKhA_jqRViiMZiuMY_BhHbzMztttxGMu6VJqyqgre4d17zEkpo5SJyQMzigBI9LGcTVzbcWJCRBBhJhQEijHZzAIhEbJItjialFVMqdmts2oSYjg4Ooth0DZbLpcfPn_4yfc-evvtm3_8X_6Xt5dvy0X12a-_ul2vbamMNVdvX16_urVFjowcudttm3b36uWbw8OD6Ma6Lj_6-Lu_-Lu_--EffH_fdGdH9_7wDz44ODza3GwY44sXr7747WevX74eRwfi1PEnf-J9KCYVqtSuW1MUKYK2mTYkwsxiyrycTfwYJbItMp3lxbQK_UhKY6ZRWGnFLL-LWAkIsCJNWnFIiIjKKK04uEwr4RC7jTaU5XmKztoMtSKlvB_zTI9th1o4pW3bHhwexODX6xuj1Om9h9oWLsXZ_DArpNvtSat6uXSud93eFHVRF9Vk-dXnL1WmHrz3eHW9EqWni0NO4IWV0YgyjgGNXjw6D2Mq6hqIus1QHcy1Nr53w340ZQUA49B7H6zNjJE7UzRqkiSa7Mmz71st64ubmKIpNMcQHNu8yCeHlFBnum86QdR5Hn2YHiyGfQvIqFUcI4iQ0rGPKMIhcgoIAoKIQkZDYj_4vKiNsXm9AJQoOvR9Vpaj9yABJCJgCJ4QlCYCMrMTYhYGrUEI-ttLU80QwAdf1TPh2HV7k5n64Hgyn8-Wp2BUBF3OZ0fvPUwJYwhFPfG9y0qbxlYJW2tDs7dlXs4mADiOwWiTFQUQpBg4Ur0880MrKRlNXdemxMZoWxZd04BISlxPZ2RsvDuyA3gfvPOT-ZQ5CmL0jIja5ghSzqbAceharTQLB-8AlHfe2kwbg0qRRgYhhcLCSCkFQoIYAUlCusMUCHJwHhQpbSS4FH1KYex2rm2HpvH7YTqf8bhTQsnz8Xd-DLEHnSHDftMURRUie-fa7SvBzObZttkl4AcPnnSuH8fh6N558G4YeiRVzWud5_t9GwNPp_Xu7TvX94U1yBFicLu22-yRU3kyD32YPTwLPRdVVdR1Vpow4uL0uzbHMQrmRVbW5WSSUgQMYX0bUupWW7IKUiznM6QEDIrs8vxBPZ-2-4ZjPHn4dOha0CaGQdui7xwpUsqaqlIGY0qitK4yrZTNS0TKqgIVMgNqRERlNUcfXBjbJivq5J33vdE69J1oYt9DN6jtbraclMv50enh0dlRMZ-1m_3h2Ume54qoKCuDCSEicbNvfvX513lmEUAhPntwejCZRB-1UZLS2-t3wYc8yxeLyYPjo4ubGxIKwSskIb1v2-ubTQju3eX1u-uWwxADi8Dmevv848ealHPetcN61wlA2-wN0sXF9dHhwcP7J4qgKHNOoen6zGYIMKnLSZFbrR-cHTrnZ5N6Oam0oWldGKOyPKsntc4MCDSj_9kvv3l3syVjlbJ_-Ysvdvvu8xdvL673UXi392WdJ8H1pr3abhNjXuVEarMfH9w78gFYoY3py9eXf_OTTx8-uv_N65t_829_PgZJqG72-7er7bppTGZHVtWkfHe1urq6Leezb99cbm_3t9cbQK8m87_9-69HVAPGv_yrn_3kl9-8fP2uD8PQu812rZXqev7wR0-HxuVWZ7X2mH3zxTsmgFy9_Gr72y_e2sxUh4XrxklWKkQfUjOEy5tNUZU__t5768vVGABy_e7Nu_m0vrm5tUbPJ1mh7fc_OD8_OSgszi29u9lfX_Uh4ND566thv-7HkCaziSg5PVh8_PH7H_zJs6vPX3x_cvbR4_PrzfZf_e3Prq9Xm84tTw8Pzg6PlgcxMIu8vbg8eHCyPD0mQ7fb3fL4yGowWaYRstxs921em7ZzKdO98Oam6Vs_O5mNmg0z71zsgVvfv95xNyhtsro4mC20gsuL6z_509_v9rt2211eXIOIwoRJkvdpdAiSZ5nrR1MViVNyCYTJaDYqJlbWphQhem10IjFVVcwqo7Fb7SVxXU9QMPkAyKjQjWM-z2Pvh_WgRGdV1q_2GDi5JC4kH9TEpjEAgzBASm43oBJbUhqDym30noYUrlpUOjUuKxUZCqs2rAZT56bKmJUy2hpKkDABgUrBK211kanKht6xdwpZmEkTWuX3b0iVkAKHAIkRgUPIqgwAhAW14RSTT3eANQCIflRKIQARCUue5SgQndNGCzEKBxf8ON4RklmYmSFG5KAIonf_f5r-q9fWLDvTxMYY03xuuW3PPjYiTviMjExmJslkJatYLNMSqwQ1IMi0DFroiwYEAS1d64foWhAkCFBDUEOCJFRBVdVlyKJNkplMH-bEOXHMtst_bpoxhi5W6Ces9e39rTnHeN_nQWWUzClISsYTp0z2MJQ9OF2ArJMstiz9dDoOXTWbh93-5uVtXdf7XTuOw-XV8he_eP7Vly9C1xVlsVnuAB3nxHks6tJaN8QBgSTnMIbQj9ZUiqYfgkXqd0sVMIVNWTSnprEcc2jbuGsVZLseVjfrmLmPXQzjertHQ89fvXz17NX58dGDk5Mf_-Szo9Ozz69e_-zXX4yq17erz3791erZi83qejLz7XYj41hWxloT9ytOoz2b4snpsB2GzeBmk4GBFg3VdRTMnKumil1IQ0o5gYIkBetMWbnSpsApZw0BCA7jZBgTIIiIJrWVj-3AQ7CeEFVztiLWOwUlIUUZdi2Id09OTZeUKOW8W273V3foafL01E6Pti_vjLcWaffZV95TPfFD26vIMPTLl69j28uYfFkcnZ-9ev6189Iv78qy4BTGTZ9CZB7HbctjtN5J5nHfqioikSOWFIdgvVcjGDOAqpFu2ztXGNHTR8f7q5Wvy363t4UXDsBKRL5pBFUOlRJHQAatRWU0JsUIhAqAAEQApEZZQSQHEFYgIMwxISs6ByJoUEEUkdAgEccsRIgkJJIZCSWLfsMLYdF8aNuCKgIIC3A-UMetaxASHmzViKp6MN-ZslBlQ86QVQEEk3JUBAX1VaFZjLWuLDhlEQUFBAZRBLXOqormbAofx9EVZTGdhDCGfvQGQCWnjESGNIdRc0ZDRekBMMVAllS1nkxVAA3lEBA056Sss_M5KIR-sM6jAQAjmmM_Gu_IGOEMWUiByAoZVQZAsjYxz6anYLDwtaqcPrw_WxwN-3VK6fe-94NZU87P7v34L_5yO4yAsZzX_-Zf_sfVut9ttkVRvvzq9cOn79x_eOGMncwnr7985kuzOD5hzmcP39rtt-9-8O6f_rs_RoQPP_zIVsXLZ58bW_7Hf_-Xt7c3N7e3_a7LUd5777EtzHIdDZcnYIgcCfPsaEqogIdAexlT4iik1O92hkwWRtEcRmV0ZWGaUhg0KpAaZzSK5CQs6Cx5ByqaswLGdgQiBE3jSKDAwszlbCHCY9tzlpijJLHGkHGp65jTbrna3F4Tw_nFORAM48CqSDYM3fHJvcWThznC2IXp6Tm6anm1Onv7sUXz8K2nr796HUP_wXc_3bddUZXW-WZxVMwmiracTnabQUOyvpKUrPF1VaYh-MnUT46mjx4MfeecKQqvkjlGZCUgYeYYq-mUcxh3d4imXMyAnGRGNNa7cbsnIusUwdjpVJSNomQFCOVkNrS9ABgESQlEkQhUgZUsOW-MNbkfJY6oWTWhZFNQ6FsFQtB6vuj3-3pxmsbRN1NByCGRtxIjQu6WV2AAAH1VelOBK2LfI5qDpKtq6hyTgPeTmnMmo0UzrY5Pc4hD21vyu-VuenpvDH3qeo1ZQQhhbFvukykmVDiTJIUEaA9LZytm6HfFZFaUs3bX-boJuz1rHnZ9HsfUt4Q2SyZnXT25__SjYlYi-Rzy7PQkjlFYjCvD0HEIgOhL5-opJxaWoikAUFIsmurQDE5jyjH5wqGCWUxQjYg4ZwFQmeHwKhJx9RnKIDkxsy2b-YMLjyaHHjVZUJXcr1c5ZFBkTO3Vy8X9c5XczGskdEVVzSfzszMy09Vt__S3Pgl91-72_djOTs6a-RGAVrOFQWXWzKpqweH0qNlvtpP5whoK7ei9s6XDnMrCpH3bX26axVSjGjDjdjWslt46Y3V987yYzpJyjElUUogS8cG7H06mpyCqOeRxHMZWhfMYYhxzGIf1mkqf2k6Ex93WNXW73U9OzshSs5j37Z6Ai6YGJDupbVkVRdXvx7hcU1lw5hxTzokZGMEv5qYqi6rIYzr8Vm3vtqg8OX94-9mXad9xTiGMIaW-7zfrzcsvn21vV5u7FSJs2q2tq3o6n80X00fvUxyqsvQqY4p3y_XL11dfvHr1_PpSmL9685qQ6mp6fHKyuttcXt20w4CEP_7pT6tqst5tC1usN9uu62azmW_q0pt-tyU0z754laLo3G1uttfLpa_cV19fdn0_9PGDpw9-5zsfXt3uum5Y7cfdrt_1Y1VWq836xz_95epuWbr6br2tmzKodkP-5Rdfj0mzwavV9s3tUgyWRbkf8922DQDvffvJ1ar9yWdfWW-uN7s-pHIy2Q3jVy_fVGV5_3T69d12vW3vdvsQczekVdu3qsu2jVkCymfPr5br_ce__-EvfvHssy-_qGZHN-0erYWiOnlw0vbD3_z0s-ubyxjSWx_eJ8C_-fWzfQg7Tb95efn6zeVut7-5W96-vksEKHp1uVQFEU0Jzs_u7cO43-5VjKjYan775nrSFK7w_7P_4nd_89NljPLxH77fr3f9jsMQm_mUari73ezGcXY63Sy7737ywS9_8-tXV1cchzyGsqg5mcW8Xm_Sbz25-Pzq-vZm-evL1fn8uDqbhjjGOHZhmJwcDV12BA8fXJSFa9fL_vWmv9397_6L_wwy_tXf_ureD578_PNXgqSGqmo29CMDjymZ0lZVvdnsfFXMFlNLOKTYBzbWxhjHkFfb_XrVP__sWoUDJ0TDMca-l8RlU-Y-pNWyLj3WzaHCB8JD3_9v_1f_85_88V_-9G9-1SxmAElSBEGOWRF42PmiYM62csN28NNy7HslVGDyLrYDaorjaKwt5g2DGtKhbTmxLVzq-9yNriyhsGG34y6PbfeNVIiw37f-qCyNGfYdqBgkiUH3QVNWY8gARTEgwhlQOXEYc3FSIYmrfNp1TVVI5LQLYEnRinDcDK6ubY0cMyJyCJrZV54F0jikLsTum4gI58jMrAJQWksKoiwArArkSyKw3nHM-o0HIAMRGlAVZ0kTk7OZGUDRkaSoqBxjGvrYtgCCqClG4Ww8cYqxH40lUSYCTYlzMGQQUfWw9CJC9EUNhFR4Mk4RyDkwhEpDu--3-7J0kSWBHp0sQPJuu2l3O7RmSAqCsd9sVnes4JspWbTWxxTTGGIfyZPmkTkJmnG_Nt4Lq3Mlo4Y-VouytPX56UepXcY2cA7Kcb_eEeD-Zm-9W13f3lytHjx9NIzDPvST2r9Y3_z5H__Zqxcvb27v-j6tXj8fNts0xMmHT3Vo29tlUZfD2AkYu5jzyVG2RUjJVo6akhXJFmGIRMqZ0xAYlA6FaUBT19iUwAICqmwsiSqkBPsRUCEnSEIzC1k0Bs0Zc_qG18cZggIRAnNiSawCriYfc3u37tpgiNJ2lceAroy7OLY701hQkLQzHMO-i_uefDFut5B50pROjYL73X_8-1jp6y-_Gve73PZ5HIWjAhSVgxCAk4zBWJKYOAZDqjkOYVdM5iDijRlWy7CPYsDPKqOS2j73u83Nhowp6ooMZRHNUDTTzAfmvpGszpdgHadsiiKnUYF8VVvncsqmcIDKIaEAASlnIFARsYRkjCFl4ZAUAI1FNOQNGSJnkEhE0FhriBBU4BtwJ8KBc4XWobDmDEQEYqwTyapJEQxa7wpVAQbnjIqqsmYVzXqYgAKa0hMYYxynjCJ5jDFEIsPMIJmUAMmWlSpzGoEsZHZNmUJWVUSsplPhDAK29ipKiCmzLYoUIxKRcSyJM1vvhv0uDAM6NGQBETjrqMY74QwAKSYgA5qBJXO2RSE5gwohiioad1CAAQA5V7jaeT8_PttububHJ2MYGJO3_vu_9b3jk6PF4ujnv_zly1dvnr779Md_8dO3n77zs5_-ehy66bwahwGQm7KY1Y2Ivv7qq36zIWvX6-3Fk_f7NFxevjFg4pj_3h_-MIb07LPPmqq8_Ppl6vt2GNrd8OjxB5vdKkToe_ff_y__F0bKoxDz8ekD9EKAx8dnMcrs-GTsu7qanTx-POy7MAQqDIBhZt_UdVWlcUAg6yxZSmMEBrIGvcWDCk5BckYgY52xFlBVEjAb5yUFAOEUAGzX984a8h4VjbOusDlz1TTzo2mOfbtZ37287LYba8x6s6prD0oKZIwvpkdoKCfdrbZn7zzZvLpKQNPZ4p3333bWsMKn3_1-luSqGr31denrBgCffOt9DiNYVMW-7wixrCb7XVtNm2IyIdDTJ09UIsdsyDp7cMowFiZ2vUEjOeScTFHklJqTIxbb79uyKR1JGsYEiArGl87Zi7cfra5uc4zkLYgYIjebARJ5lyO7sgBlDlEUVUSZQRgANIQ89hJHBVXNKUVjHVmDCEnY2co6l2MSAEJjC88x-cJ2-50AGOt8WZC3QEKg3WqrOTmS7c1N3dTb7X4M2Vmom2kY83vf-lZS7SXXs7nzBRrMieMwIgKhxHFIYk4__k7h7W7Tlk09OT9XQzkMYxsmJydACqjkrFVc3D-1FlkUEXMMripQcLe8Q1fkEJ01-81KYjbOh35nfVnMa2QJQ9SUqmbW7fYAIAyEJJklZmD1ZYGQOaUQo6J6X4C1ygxA6BxYgzkAosZec1JQVclhVObm-AFAHrtgnTHWoDAAAwiKIOGwXg9tt729zQSbu_WkmaGxs_mR9dBuVr6ZNNMmMRe-aHcbUJvDOJnNFbht-9Oz47K07TBiWSlg2Uynp8eb280okrNwEkKwBcGYwnafJGFMKfRFM4vrrcRx2O3CqGRgvliUJdWNvX31tTMOGT_41veLuuh2W8YMQNaZqnQsHNvOOptTJMJ2dYME7d2yqBpOkcDtVxuVTLbcXC-b6dSAnR_dx8J671zpmdk1lSq4srYE_WavACxgvGNhlKyqw-qWUKwDMjq0vSJYiwhsDFmLVVPFMPi6ZEBDsN-tV29eLY7nKUe0foxhOp1tN0tDOG9m6_Vuebd89erq2ZdfP3_1yhU2DuFnf_eFATOOcb_fpzC-fnU19MNyuc3KzaS-fHPz8P69q6vVyf3Tu5vb9dX65Hiy7oa2D_tuWJzPFOGzL1797LNngZJ6d3mzPj1Z_PxXz6bTShS_9-2PbVFc3q2-87337zaxjcOr2-Xzq-vldv-nf_l3f_OTXyVjPv_q5ZdfXqGj3ZC_ul199Wb55YubV6vV3W7z2VevlWxkiaqr7a48Wvz5j3_-Zz_75Xx29MWL1z_79RfX--58frbcrL9-fv3qarkNcdOn5a69bvXlb7744tWb-uiojeNssRj6oet6EHjw4OTDb7__i599tdn3n62Wd9erIee7y7vNm_XQjqwCKgzADGZaHB9P6tqPbbx_cfb61auL4-Nt34lQHzKUPNysh31_9PGT8W548ZubD3_rycXE3N0GtN55__777_z8r3-x32wxslP64OH9XU6ff3m1Wm4ohmoyIVt9__feWca-wvLV7XK1H7rMdl4Jp9CFu3Yzn1QR0QqdzYv3v_d2e7d-_vx127e2cZuby__hj344hPw3X361x_zycl0fL5qjOWdB47JRU_jTs9NmUt67f89aTwbHFPfdWExL8rje7cjZ1ao1IBcX0xgD7_ninfnJPR-7QGgNovRjbAdxRhGsw5PTeePd77z_9n_63e_823__40lTonUDpHEYRECQZcyiQCohCqOCIlonyqlvDTlVBmVSkBCrpsiBZ6dNXO_zfhQFEHbWaMycU-rGvE-EagB4H8ysACUWSV2uzieScuzGLGyKmkCNiu4DgGbNzlsRlRJL8jAG2cXCIXIqC7e_XouKquaQpw_n6K2bTDhEYRh3nS8RkIpJmZklcj1f5LG3FovGqTIgirCxhCAKGVJSUGNdisEWhbCqCIcMpNwHdCTMCqqcAUmEhQVE0hjl8KclmTnmPhhSlMzKSOALZwylsScjyCrKKgwiZIxkIWcRVAwZ66goU4zGWDRGEYTVoK-Oz2TY58AaR5BsCouuBCDnfBhTCoGMGbsQ9juOCTj46SK2bRyD5hTDmEICYATgEKHwnBMSqWRgLOs67PeowCO3beh3b3JIMQ0qsd_H6XljwWjmojKAeej2u-X65vWyOl24-yd_8n_9NzmNRWPvXl2n_Vb7HkREdVzeQew1JWQVVDGkx1Mufb8aCJnKYmijLS3VFgjIEAuAKBgCa5UAi4oMggLmhCmyssQM3mPhyDlVgMSQRXejquQ-yBh1iJAyhaRJTV3lfSt9kBBijHmUcja7_OLr08XJyfffW794ZRisNfWsBmUUIiXebnTTQWCIKfZd7AdDCs6k3YDGfPjh49_69rf-3b_709R2qW9zP5IlAZAszDl3gwyjxAAgmtk1hcRkDMUuEKDDImyWVjWPqT4_Crcr6RMhIghKlJSU1JjC1w0ZU9a1rwpCP1nMXVEraNnUKiLKPARbVb4oYojWOkTKkkHYGgOsoKrKqigqBEayaE7oDICCMAEYYyVnIBJUpUO-7CABE0BgZjUWUA2iAh8S8wBqjAFRIGQQBLJInBkAVBWdAcVyOjOEnCIogrWiSoCu8AiAZIq65Cy-qqx1kJNxjowBZ5WTJlZNxGjKYhyCsbZsmjiO42ZFZFJM5IgTW-MRkXP0RZlC8EXh6joNwVc-j0lUNUsOB8-hM6XhMdqCOGRAJYTctUSmaBpN2ZRGkhz2JnDYh6SgicnXVJS-qrtuzyq-cHEYvv3Jdy_unddlkQD_3_-P_1ddNczRGffg_lkzP7q9fjOZNb5oHjy82L55c-_tR3lMt2_eDPvd4mh-9uQRGT8_nf_8j__1b_32jzzp-dnJ6m71t3_-tyEGyW4MKUZmtKap0MrpwwtJ-Uf_4FNZ3xrbzHloh-0m56xZQ0z73fr66lVdz6nwOY2zk7NiMjdlLYxFXcYhcsqgmvsBnHVFhYhFM8sp5JBtVQt_Q3g8RMcUyBhCFeUszGVTkzARkbXWUs7JImWV0A2u9JbIWJdCvv_4gxyjNxC6ftyt-_W63-8fvP00h4xk1je3ZVNN5meCYK09fvAg53R3fbVpW7LF8up2u1rWk8mTdx_vttuccrtrU-L5bBYTz45PbVlaY1NMMYZ7jx-GfuScgeDlF19NZqd914Ji2nXGGOak4wiSLSmhdN0YhwSICFjUjS1dHkNZNynxOCRVsUgpK5Ba51NUwWytSwkADYMokitL5SyArvBgLB4Ah4hkTU7JIBCgxmAINIacImiyzikp51QspoZMPZ0OXeerBsn2u13R1KkfAIQVRcUYtd53rQABAABJREFUO-xbgzCud6q5rMs4tsxpd3cbh5FVnnz4yZe__sXb739AFsEV-3asj491zAbBljUDKhhri7HvBWG6OKqnsxhzzKBgm-l8cf8hmdT2_bjtYx-dQVN4FgHBoqpdWRZ1Gbs2pzh2LXkvItV0MTu6b6xHsiroPRkyyoLG-sK56YTISRZQRmWykFNwvpwdPVGNOWZRBiAksk3NiYVBFcl6gMOOT3xVkbLE1PVbU1VkKxDJcZSUNIkxpp6fqozKSWJUSUbZAOecWW2M4_zkaDqbhhDWq7UhNIIPHjyClMqydIUtXFVOy81-N2_m5Nw4hH4MrnTkqsXbj_xsCoERVIAPEgPmlNpddTpLCXkYi7ow1pOidZDGsV2tm9nM-ftkTLt-1e5Wu-4uhH66OGHF0HfOudh2IooiMY7O2bJsimaiITnvSFIcg_NmuliM_egL20ya1dUSFVRC3dRgSHKu5_MYozFm2O2M9c39sxwz1ZaHgKDVpGpOFnFoyZKwoHXNfGpdkUPql3sEQoR6MheAvg_Hx8ftepXaDlRvLq8uX75Z363b7a7fbsnaKBw5bNbruqxEMmD2hb1brrbrJWjY7Nc5h2HsU-Jy0kwWTeLRFG632RWVW97eIeB2u-261nl3fX0Xk3TdyJFVIMZ8c7VSydttv1pv92272W6dN9vd_uX19ddXly_fXN117YvL1__tH__Z3_7sl188e7Fa7W7vlv04rG7Xu74bx3HfdvVsMZ2e_eTXv_nNF89Xu_2ry7vQ59u7tQS-We2GIa2Xu7Yb-iE4W10ulw5MUU3rqv7rz3-zbcMPf_DJ8QcXP_3xL27u1hdPH05nfrtbZ8HF0fHJfHo0KStfEEI5nSTJl3e363b9-Yuvr3_x9RBGBBXi-mjmjfWFP6zoi-N62AkHNgkt4Wq9IY_BijUFOxzaoVtuw5COzk7ms6Pl85enb51aZ__jf_h1dTrvuuHBO-d__q9_POyGqm7Euh_8zrfun1d_-9ef9Wk0ZZ4eT0I3fOvjt3e77vXPXq12-8SSshrrK8Bus98NI4rtBzydH_2jP_zgbOJ_8uNnwuPsbE5Zj2bFf_VH_3zmi189e_Hf_Pv_8OXX6_UYN9vtdDHPhrocjXd1VS-O54hmjMlMDBE8-_zNycnsbrW5fHPb7wcg3-7H-tBCkcQSZBeWz3aScln63WrY3w6zs0Uzr6xBT2QZYxf_x__oH_76Ny8_e_7y-Px8t-83N3eQWVNkzhxG58gQiQqRJlXyJo_RGm8MaWY_nwon7uMBdxm2bR4HyWQILRGPGYmqSRXb1niLBk3hWFCyGGcL74xC2La-qchZ4ywBxT6oWOeN5GyIwAMPSRlSzpgTZRXWnBjASFZbels6QFUx5BwYYwuTul66XlU5CUdRESQT-j0ZiwZzZmEWEWMtGFDOyllSPPDMAUSyqjKQURFyBKIATAiaAgiHrkdv6JCQBkYEsggIeRzJIAJrGpUw9YPxTgFiO1gAUkEEyUGZyThQAQJ0HozTDAIqKR1iJCpoytJ5F3YbEUFyxhmJwn2sZ7MUh-Xdijkbg7FrNUdRRqucQZlFEoeYYhRRFC1nk5wyGSQkFrFofVkfsG9I6K0f2w3yKBqzCBpCW7i6KKqTYbdB0hjGrMocIYwQx93L62d__hOywmO3v1xSGowkBGHNxpIhSKsdqMbA5GwWK0UZQyIAzVlSBjDkfGgjGpvbDrKAKnjnykoQCQ1Z5JggZx52pnCaMmRG0YPGEcYAKQInDUFzgpxBmHJEVvDIiZ1Raywg-EkFAmVhch-VyDvfrvZlWbrCV7NFzsIphM2uqoxFstZhZm_zgbRvDahq7Yr_6n_zP_o__Z__xfZu1fVrGHs6NFJicpWHPDgEYwgBAFlVOCWyVpkxi7OYhxZAiIis0ZhsysLMPOYxyRg5BVBnJ0dxvytssb5e2qLyrnRVubm661f7LJkTAwIZm_oAypKTspjCASuHAckgGTAWyRpfIIFyRqOahIhkHMF4ApSQQSilBEAKQKqiQADfjDVVkByCShYAICRlQTIGUUUUUUSN9YiKiAJKBEhAxilq7EfvSwUl75xzaRw55czZejc7PZecBZTHEUQ5pUOeQpIggjFWBFTVOWvKglMsq0kcRmupmEw4JQSN42iMQSLhVBQF55hTQgJhNo5UBFQQwU9rZVaB1A5kKMXsnFdJZLx1Dq0Nbe-bOmex1qK1BymZqxvfzH1ZNZMJjwP5IuVUV9WPfu8PZpNKE6-XV89-9RtVjnk8Pju5vLr-9Ps_-PFf_vni-F4_7F8-f176YrPaLBbT2fTiy9_80noDQO98-wdlWS-vXy8W9x88efz47SdW5Je_-pJTP47x1YsrU9qzt-6JNXGfT2ZTYf5H__j7TelXtytjy9k3GiLOzdFJCKM3_vT-w7FtN6-eqyuLugRCsp4Q6-lRikEtGeuMN3mMkgUUUIWMQSJV0cxIqGTIWgFAMpzVOCJVZSFCVVBW-KbQHePYWefKyURzKsqibCqQ3O93Z-f3jS9HhqHr7j16kPu4vruJ_X6_3qAxilY5nj28QLLtvhv74cHb7-3X68m8lpzbsQfF1y-v7z9-eHZxPPRD2w_zSWWdyyI548Wjd6uqMsZuNxs0hfNmfbf0vrz_-L0wbI2r_HTab1e2qQHUFZaziNJkNq1qyykSkimwnMyRyvVyUzdTX7lDp1xFcmBXlcYb4ZxiQouoAkSI5Lw31rmm1iSurhRM7AcRBgGqS2S1zslBrYeIpDlE5aSaQXLqRl8VjFpWkzgGa4icQ0XjDACkdkvGl83UlS4OYzmfKWga-26ziyHM54vQ7XlM_X5FSNev35w_uDdp5kPXls10ejQT0X3bkSua09Os4Oq5qJmfnFeTE8ixbGpQJaPb29t7T96p65oICu-7zUaUyNjp2XFOuV2uu9X6UHcLfcvdzjcNZ1GLvp6EYVjcP9vdLlklZnaGXFnsVltjCBQyizFGVA9kwDHsUaGczob1zjhTNk2OyTh3aLaxKFlH1iGopCQKrrDCTOgMgau8JMk5u8IbS6FvJUlRT6xzmhktxhC6_ebk_tn17bqq6z6O1XQ6PznZrbcPn753_fLZZNYYi5xSUVjrSC19_fxlDnE6nXtL86NjQqx8CTkXTVM1TYw5ZzDel5NpYui34fjdD3LfQtZ-CKJS1WXhTByHlLgfh-m0isPQDy0Ix3E4vnfBWYwjkRyGEUAMoTITQU7ZYFmWc-eLNOxjTOMwoiFjXbtZj32LaGM_SBq3t3dj16nRbrd3hSdjXGnHvg9d76pSMxPD8aNHu9ulMVRMZsMQ0RlX1PvlvppNcsp-MvWFR-eRCBD63TYNnQFjrG3qifFFVRfn9-85g3fXd8679z5-b71ckuDd9R0gAfN2vdmtV-1m1-33_a4l6xQ4a9rd3cS2i0Mv49judjnkyGwrN6ZBVIa2U1HWvFutjTO2KVPOCLlr-6wSJUECt6gVZLveDu3u9u7uzfXdvh1ev7zlmDmrZE5Jm8ns7U8_7PZ9XTWbIZqiXG26H__kZ-PYA2Fdl5Hj8fH80aP73_nOO8-_vm3mJaDtw_jbn_zwZnOLAJPJtLDuZrP7_OsXi6PjX7x58d_-iz9Z7_bz05O79f7ll18Bm7vb3Scfvf3e2-_MptO2H3vOt_vtr5999ezLN7vlvl_usKCqadAWKcnZ-YmG1MwrUztqSkSK3S6MbXXk1NC9d-7RvBj2AVjWdxtFnR_N6nk5hjgpXF373W4ch5QxeUFModtsCXHS1J_89jtvP7m_23efffHqbr0rJgVyQqeqbnndv3xxc3xxJGou3j75_nfe-_C9ewFoGToLOJnV__y_9-nv_8EHf_lvvnj5-u706Vk3pDSEk6b-1uLeDz_6YN_zf_O3f_Z8uedm4o-a07fuJ2bn7P37p97i0bzJMUFh2z50bXj1_Hp-Oh0l7bft-cVJ6sbpqYkxTSq8vLzbtn1hGxhC03gJwixHZ0ePHp4fVb4q63bXO1TuQlP4P_rR7_7q-VWM4e7m1fX1zhf-d_7JJ89-9oxEvPfMchgcKgDzYfwCoCA5qHCKQWJCi3nXU-WkGzgxFRYNcIySsihwzgoqIZEzOPFq0JQOMw_7AQGsN5zAOmudT330E29LE8fMKRr0EhhzUM7adiKgolAYHkQ5F1MT24hEoAhMxmLsxhSjxuAmNYgAGlt6cpiHQQ6IFc1mYghQOCMqWsPjKMwoAiKIAIgKikRIpDmRKBEZY4QjxxHiaCygJFVQUAA0xgCCxhFUJSfNGQ5EPucJNMcIyoQCwpoSMBtrgRkcKpArJ9XpnBSNIWHJmcmQAoJ1oAfCE6AnRUPegbGcU7_vbV0gkiijKiHmEDlnUsPMBuFQtzCEhNzuOwWaLOZuNiXrfFV67y0RNZ6Z213rm9KIhC4qEiLUTeksjuu7GMbIUSxGEWMt98E7k8Z9lqQxoyZS9g55HESEvAMFSRER1NgYk60LmVUMhlkIDQKCOcDKwU6K3HegCIUFa8tJRcDWe2tBmHkImgIMUXMCBcgMMUPIoAqFg5SJDKloZAAFzkgGCTgrAICypswCOXF1PMvdyElYtWiqSTOpp009q2_evNmvOyJxFoE59RFEjEqIoyg5Z5RTu-7__h_90998_uL5129S6hGZJbGohNE5A0MvIaooWTwcEnJMACiZjSVVySGrCiKKCIgIC8fgjDGF1zg6ZzlG8gSYkdPu-vr83XfjkOrF9Pb5l6haTQuQDAK-LvIQrIPUdoSoh4MzqBIKi3GGRYhQOEtmFUAgVCAkW5ZI6Cel8Y4skSNSMJ5yP5IxRCg5EzkiQocqKKhkLBKiM8ZZAEBCUFJlAUYlACRLIEpAj979IIYQxxFBRJFZVNgaqyrWGEOGU-bMZJ1IJoIMGYko8-EWgIaQyPoCDYZ-MN6noSMySJBjotLnEEGRrBHgzEJkiUzKCVir89Ow2TEnYUbrjLMHJbCfFBISIAHwISkE6FkyiBBZsqQsKCwsjOTKxhg3OTpuqjpyIksO8Ec__ANX2NB1f_Fnf7bbbm8ul8v1zlelc9V2s3_vvbdevLhsN7dxTN3urnD27ffeW15dfvXVZ0_ef7rfbGzdHB8d3d1dKfqPPv3k6UdvXb5e_vG__TNEjDmWVVnOKrSFKSYG7B_-4Xd-77c_Oj9epO348s3q8vXKqJuqqrekPMbdSlViTIBknXNVpZxvLpeuLK0xDFpPj8rZbOwDCMRxKOqmKApEjCGAsC0rIutn93jYG0PkHSdRlXI2VQQyhy86AuohAuun89TviqIREM0pdu0w9EPfppjHvm_b9Wa7ruf19OLh5VcvJouZpGR86etyfjqXGPbrDWtWUHLu6PR0t10-fvdDUHnn_fcvLu5xTJOmZI2vnt1--oMPhs3u6vr23oP71pCm3G52s4uj6em5LwtjQSUXdS2i3e62qOoQkrBOTxeZGUJWUWQo6iKNY06pmM68K1WgqCbNZE4Wh91ARnw56bYtS7IEosCJ3cmEIzvrrPUKKGMwRAKiqq6qQ98roK1KO61YFK0RUVX1k4ly1ijAYshAZhCRnFFEhiRhiH1nCVMI5XyKBmKKHGMxOwXModsrgPWVIvI42rIoywIVc86-KF1diMikmQ67zpUFhwTMKsrMSqaZLci4iw8-8lUpoPV0bqwLaWym83IynZxeLM4vSm-Wy9Xx6UW772xRiaGcGdQAmn7TWWPIoKoS8OL-w7YdxdjyeF7Pj43zZERCnJ3cH_q2tDaFEIZ2Ol9Izq6sVCCrOu8MEYeAIDGnNIZ6NjGI3W4rLAqKZA6qAVVQNQBIomhAAUhE4zj2AwBOHz4UFREFAYPCLHEcRMQUZRqDpmRQVq9fk4T13d3i7DimNA5D5f3Vsy-725u718-728v9dgcE5bTq98Ppwwc5hatnf_z4o9_ut-t2vx3HUQ0Wk4a8Md6eP36YxkFQkqCtG0OumjTv_r3fBedEYX2z9XXliwqNSGhTHhanF0VVKkdO6e75L301NeSMd5xFmcumRiJNrIk1RYk9p55ZTVkQwdh2ZHR-70HYtiRhfjwxFq1FX9v-7g5RJPSpH0WSIQTJse1lGIXjsF8SShiGJNHP6jiMBvH04X3rvBqczefNYlE0xYHo1cznKBy6XUxhCF3shhTTdrWsrDs7P0pjt3z5ctjv1TB5g2nsuxZEqqocdnvrqK7LHFLoOxgjsva77t7jB2SMqvZd763p1pv2Zs19wMy-8OSMsy6O0Tjb73ZFUSoZVA3bbKwpj-YvP3uWRVGxXsyb6bTfd0DGkRmGQETVZFo25Zuv3xSzhqhA7-umCmNIOfimqaY1Gnc0P_WItvR_98vnf_CH33v-4s1-szt9ePbi6vXxxZya4vOvX_3m9ZWUVE-mb15dtevh9HShqi9eXDrvJvNjV5b_9J__wdnRkTp49vXz__gnf7ba3t7dvOlu1mG1IUljF5p65haLFIa8HZP2bu5iBA4y7mMKUiKT6HYzHp8dLd-s4ya1t8vK-rIsi8IZ1LZLTx6dnB3PXr1evff9R2KoW-7Dfgds4qD_7H_5T5_91a_XNx1M7LNfvs4mhbFLbatjWl5vj-an3um7Hz8RhLoqj8_O727Wv_7F891m123Gv_8Pvvfo5Gj5ur385SvkGGO8vblLqr_94fs_fP_dH370fpT0k1cvXo7dXZLJyb0w8nRSI8uT-0fjOF6-WY45fnl9ve12Met6tbbWaJLLy93xfF4YQyB1aafzanu96Zf7clJ2bW_Loh_GZjF7-8lZVTUhKnG_vd1JjhPnPNl_-A9-v0jt_-1f_klZmY8-ed9PjuqmvHr58vb5jfOUQgKQnFNOyRbOFE5FyJrQjaYgiQmNcoi2cOqJMOuYJDOomkUJxh0_PFdVWxYKqCljSDqmPKRD55AM5TBKyKAaulFytsaQ02HbkzMAohnQqI4Jpg4cAQoZ4Zg1JUkRGyImVshJXVkYqxqjpCEnyBnr0-PybI4OOcTcDd45zYFDrppq2O6ISEWEo6SkICSCiAAoCITGFBWSIoiIEKlqTmPPKRwsYCoMgKpQVE0OIY8jcFYVMpjCiKhIRMYAcI4jKnIehRnhEEVAEMloTFU3Dy-GdYsKhCAHDWo83BwEOAsjKFf1PEtC4-rpdHI0z8ymsLEfVDLHjMaQtc47560hjSGgMd5bY6wqNCfzovBF5XxZhJyGcaxqr8qh24W2A0toJLS9K7zx1jkb-nYYOvSGLMU4aGJCw8NGwiApoLEo7vj9d0i71A4EKgxsUEQ5RVFB49RZdBZ8gU2dg9q6srU3ZQmOAJCdskFTlnZaGCBTulhg7rMS56GXfoR9BxooZB0S7DtICVjh4KuxBCFqiHAY_wOAISACBAWFlCAyKB8uqmmMYExRl9aYse-9r9fX12VT26JYfO-DvFwOq60t6jREgegK55smhGBQXOnf-eHvrG43X3722fLqOux2ghmSAKi3XlMCQEADkkPfIxoFIGtBxDjHMR1ujpyYyLrST04eqGQqi4O6Ke33gKCimjX3Q2gHP5n5ug5ju3l1VU1qYyEMQx4DWUQDmrMqE1kkUlWJiayzVXmY8DrrVVgPAmlLaIicBSTOCQnjvufMzIIGNGZlRUCDZLwDFkRVYclZEQ1ZztmWBRkTh4EMaWay1iAqCxhCg6pkrXNlcf3qlbVWhMkYFiFAVc6iADCZzUDAF8Xs-Hx9c2kIq2IeYzBAAMKJbVFyTkAkysaV1XROhHkcXWHRWM1cTJvUDaxsrFHJBo0tvIKiqrM2950CkHHGOjepc7t3xoJySkxEeIi0oGEBBS3rUrNYVwAoICGQr5sQeXp8SqjTejLksWgWj999-smn30YOX372i1_97O-Gvj-__4DI9GO3OD9fLlc__NHveGt__fNfpJie_fm_OnvvOxKzdz5FvVvdgEoxnbuyGGMsqvrjb38Sc8DML569TBIW86mvqnYX9u346Xc--vCT9z599_7HH741mRd_9def_fFffF5P63c-emrM5JRKr5IJUXLOachhNFVZNDOJqZnNpieLFEJR-qKqYx6LspzOZtPFHNCOY1KUzOCssVUZ2zaGiBqn8_PMUbPWJyepG5CIEGM3FpM5KosoqnBmVgbEaj7nxKACKiA5hZziOJ1PSEE5MyeJQzmdGaux73PsQz90q62wctjffvW1dUXMYxiGYjHbD-3R-YlmDSHv22FSl_tVG4YhjnKyODo6Oeq68Xa5rZupdWW3jV23d9ayKjqvAs1kSjYjGgbylUW0iMXkg48L4pwFUMn4FGOOKefIzGM_COrjd94rmyIyh248enQW-0FZjLWaWcfsKw-qMWVlQes4RlSVzDGM1nllRiQAAyLGfbOHASVQsk1NlVUVOMTkAa1BQs2hJ2TJWVnyOEpMwhmJJCYyxhAK59QP5WwKKqBYLWZhGBUxDmOOnMYwdC2JpKFvNzsGXt3cgDGz2ZGSWOvHoU9JFscn89Nj1ky-RGuwbK7u7rbbDZFbX7-pJ1MCK4Z2uzYlsVXhqxpFqsWkms6-6fQTNKfHKY4C5F3pKi85ZoYsXM0WxhhvfT9mXzn0pfdFWTaZ5TDeS1mss0DGGAJAFiyK0pQU-7EsS-NdGseiqoAQVbAqVRRYhAVUDanCwX-OVVW7ogz9IKquLskZYbZFYY01xiCw5mQk99uV9IMtS835_OF9b_Ow3eQ4-sosX3zdblvri7FdOzClucCc50fH169ep5w2L19u3lxtbtfN8cnx2ZnxVYj54q13Tx_czzkWk0m_2TaTaTmbcRqGGFmgbI4UlJDCfpwcH63fXBoLOUeJ_dD3ZXO0OHlUTqZdu2cWAXRlqaA5M1nDLHkImllSiMMY283hNhuHwdvZ0HWxb8vZRHOSnI0jdAZBQUQ5i9yqWiJ0rtAcxn0PkoEjR1ZOqjLstsMwrG-u-_1uv14DqSLE_Q5UnCVWcN5Y1GG5Imsn9-8Nd8scBo65XW-BY-g6MuTns7jfkSXnvXG267tmOkeiB0_eVmU01Le9gFpjCEWZOfL5Ow9RZNztJeUUxmo62d1cocLJtz9UGZumICeLo8nt1zdJAhLYslTQ0Ifz8-P33ntSlaWm5Cd1WdVqnGA2AjHLOHamKEUBCNquBcXZW2fbu2W7bm_e3KTd_vpyf3pxBBZevlknCOzor_7yZyGmwnnu0s31cuj76bzZ7tpnX7166-nDBw_vPX1wdv_hueZ4_fr1z3_2m89_8ptuvQ67NqyH_c3KghGGca_f-U--lcdhMpuo9mGQkNxkXnAK_WbXHNXAmGN-8OheGlJZOGO4aIqYcyR49OQhOfdH__gH05Pms1-_rObVvkuvvloh0MXjewju499571_93__Dbh3f_-9-smvbzevrvm0hiRqaHR9_9O2nR4t5Gsflsp0tmoB6c3mz2WwDy-mDez_6Jz94-as3OeaitIujo4uH5wb1tx7f_y__B__sYVXMm-Y3b67_5Jdfvg5hOcr8_AQIrAFvVFSvrlY3y23ZFCfH8_MHp5WnZto41LPTcrPprcKTt4_IArHstuHudYeE06NKS53MJyp88fbFZFYMwvv17vkXX735-lpSaBbTzWotWNq6-Nf_7q8BtTk-_vxXn3Pm1deX1188RwCwxDkBsLJoTNY5sIXgAYcjhgT1gK4UW3uLGjctshrvRFQST4_nFhGNb9fdQVvOMQkgemM8UVFYY4p5rZIoiwwjsTjvyKCyMmdfFKkfTx8dd1cbymQkYgIJoCGBAETmfRYAMhYtamIesor66aw6mtVHM1EN-zHHhKocU-p7iUmSkLHKiSP7ppGx5xDt4a2HICACisYAAOcsOQOCSJJxBM2HsiUcTJFhNFXNnFUyoB6Axd90NL0x1gJoRgXOBsUgck5oCBUVWZ11xzPxTTGZ5b6Pw-jtYYJi0Xtb2jz0QIRkDsx1JtPMThkxDb2E3DR-3A8oKiwIiABIFEPIQ0RvkFBBlExGcN42dQWAQz_kmMfNtltvYjfEMIJKNZ-N-y3nlIZBEQA5hxBi4hzTGDkGVIY0SAyaoggbRww8bJZIEgOjJUbEohqHwU5qKCotvBYFW2eO5lB5iVkxpb4TAfBOWYx1VDg-7FsIch-gjYCiXdSbFsYEqpCSxowCKAosgASgQAgAkDMAAiIZVFRQIFRURRVUxEN8V0QJQRUbb7wLu45Fu26oJ_Xu5rqwxo9pd32L5PxsIpxs6UIWcD51rYAaN62PTt588bXwwN2uKB0iOHKak3MEZBNna50iWu-FCATQEBHqgStlCAiBSAjBlkQaU0oxqAiPPUoGQsnZT2tgKZqmKAvOMp8tDKkoE1pARYIUk8SMRMosLIbIFJaM0SzWWuYDzCcjGSIDB-UWIiAiADMDCBhQEBQBYVCwzhpDmVljskVxEF-AKBmyZSEiqFBMmjwkQygiiIKEYI2xDoEAvgHNo4D1VpgBCVBVFRTQWYNGVF1ZE1klTV1vHHGMvqwUFRGNMcb6sq6RKI2BrOUUqSglRWMMGcuZOQfN2ZYeBavp1HgnmfXQt2EGRFeUzCyRi8qFbYsWRcB4T4QpZ-AE5HLM5CyKQpZvRGnWhiTkymY-L8oyh-gn1enx_e9859PJrIoC__Zf_MvV8pZT-O4PvvPixeVysz-9OP_y7379vb__-_P57G_-8ievXrwhovvvf3j_3iNXFC--_nI2nR-dnqxW69Xd-v7DJ2ionNTTaf38y1ePn5xL4rosT-6faKLJdPajv_ethxcnk5Js5qHr_-Kvvnr5cvXOp_dtYb_8yS-Mnd-zzgEDOkLNICA5QxzC3Q1Zu9tujULKyRcleR-Gfr_bubomwuN7947PHg7DSGiRCMgCmqoqM-c49ipgjD-IIowxqKAKRhMiASEAukmDzlgqx33LcYxj9oUv5lPMiszoTApjGsd2tek2GwId2uGtT74LgqCCKABJAQrvUhyaajrsVzDE2-XqZLEYwuCcZ-CgcHx-7Exxe7OyZOez6b3z08KYdtu7ojCEw2Zrq8I634-x27YAcP7WoxQFhYmhakpV3l2-Sihky7ZLgGKArLOcEllzfO9iDCMW1Exms-P7213rjKvmTQ7R-0JTNIWDpABCxlnn0IIFQms0JwQ11gCAxGSdEVZrna2KFPgwv5HD9JeVWYgMEYIAS0ZA6wqDoCyoQAAI5MgrJNSYx9FXFXOUfnRVBQppjH5SyZics5xGQgCRoqqa-VE5rQhJUlLJty-vmqOT2em97c2b_aZtN8uY8s3rlxJG48uUw3wyqaZFVVXzxSL14ek773ZjnJ6cHp2flJN69fIKUnaFHXZ7YUGg2HeucJySUSGie48ebG-Wviy6XTv2Q5I8OzueHi9iTKg87HaZgyM8efQwjtG4Io3ROCOZEdEaO_adMVhUZewGZrFkVNg1ZY5s6loZEAEOCNqiaKqp8Q5zDnEgZ4ujEyWSFPNun_skyghqSyuRjYEcghHuu30ah74f_KyJfUgpDq-vNSdfUNrv29VyOl1wSGXpvKPtzfWjj9-vprZeLI7unyBK2O37_a7b7cvCt_vd5u4WVR8_uC8pJQ7dvlu89RbmFIaOKJBA33U55XazuvfknRiDsZT6nhxy6PphW0yrenJqmiMGOWzbXVPGNpA3rvCurmbnF-VkImOqF1NUiP2Y0x6NkDGpHyQxGUIViaPGpMJEBrBBRQLJKViDtnA8xKJsymrRbW-7u5Wt_LDfVaUlZg0DprG7uwVCjens_sfjuPGF7ze7ZlIP3ba9uY5pZA6YGVKElLjrNYG23Tj0IhDDKKIPnjw5Ojl2Hm9evdQUh3aX-l5TjF0_7DuOoaiK7dW16jc8Ex7jsN0JBxDdv7kqqury6zuNtF1tQzdsN-3x-aIualDKMXHWm7tN3_XFfMKq7KDbtc-__FXMMrR7JCCiMYZ2vVeWYla__OVnl89e3NxcxzHOjo_vf3C2G_avn7_abjZW9fkvnzvheTPZLjdxDIhWJStmtnQ8WTy5f_xbn344mRaQxr_7q7_71U9_sVltt8uVJ2hmdU708N3HZ-88bs5O3_7Be29-_uV-27IV7ysJ-ehsMi5366vN9Gzx5N23rl_f1U1ljZ3UReA4ZD07OXr4zsUf_t63u03b79raudevN9a584sTZ-XBxcIrzOdFB2m7WVGhWfL69R4Bxv2wW43VtLDOn94_nRbyy797DQaqSRGSPv_ydWSZzuZHT04v3jq7-uxF7sdHj0_TOD579jrE8J_9p__48aypyNzt9mjp__Av_2Ty8HgttN223X5cXa6nR7OU82rVJZCqKCaTWQRZ3u1YeHO12S_7pi59YxfzgkWvX94oG1NXxcSlbogxzs_nPOZpaSuWN89uJMNqGdqYH73_CFNGUmuLT959ulwuN5ttyslbv7662t5e5xCHtjNNOY7DodsHKs4aImIVFTUIhMA5ggARIGeMETIjiCaRw-uAKO1jSnHMoxK4iqh25ItyMbXOxNVgQCElTxhXOx4DJHCVBzJpP8Zdr2Q1CxqDoOW85hgpKjlQVU0MkGHq0JFzjocgY1JnbUFkPRWFWoh9SClJjqQhtR3k4AwisGs8guQ0AishgSRUsLYUiaigqsY7JERV44ykqDkCMIoaBARVPqANkcqClFA5p4O1l6j2MgwCCiiSgkpGUMgZ4UBQNCgqnMAaLSt3cmLqqm874KwpQU7CaqxlZg2jJra-RCJXTwShrGcAAhx5DMw5xSTp0FUQg6Scc2BAMIVz1nDMimi9kZDCvhuHQUSzcOpaUpYYUNLhXMBjyLkH1vnxueR9DCPHQAY0hjz01qOFQkJPwBxH43yOGQza2g93e2wcC1FTY1mzN-Z0Ic5Fb8E5qipFlCyKRsGoWmNN7uLhUfI46JikH2U_gCHACGHEMIIkyAx5BMkgYoENK2QBBBAFzpAZOIN1oEjeQoyYFYmMsMkCIipyYMwDoisK3vdx31rrDNjm_Fj7HpOE0Lerna8qcMbVXiJD5vKogcwy5uro6PSdt_bbuxRa7vYWOI0BBGXsUkgpRUXinNHYgw8L9JAXkxxFs1jvVdk3TVjt7LRpjs8yp8mD-7HfYwgkLMIIxhQFAvrK564du76azlIIaE0Ooe_2zmPmQyVX8jgeArcIhzMbWGtziJwiKICICJOSdYVwRkDf1Kkf0BIiQAZIrACa2PlCmQEBUUAh54TGGkQ0dKivO2MQbQojIAAhsCAACCgjgRKZFAKI4OEQP6mrSR36gAcyKVoyRkTIFRxzPV3s1ndVWSqLAoBoiiMSEZKqchpV4ADiBKI8Djll4z0zIwKKGDIqclAdg2q_3xdVxWHIzNZVQkJAhJpDMK4ga52zKQQEsmVjnMshWEtFXSuLIKL603ee1JPFft8VZfnw7aftbgVkHzy6-OR73zk-PVrfXX32y1-067s0DFlt5Pr04v73__4PGPC7v_eDB_fOlzd3P__ZL568_ySN6eTsIgMoMoqEkHa7_ezoBBVV6b0PP3r64dOxbW3K77z7KARFi7_52Vff_cG3nj6911RNRvjlZy_a7fhb33n368tVPw7TefP1F1-P253xxw-Nrzin0I_GOFPVCIIpE6jEgbKkrtcUhjYU8yNS1mHYru52y71r6sRhMpuXk0lRzdFYMmboB0DDKmSxnDY5JiSThpHKKsVknEFrJSZbFCqIZKkoEQCtqaYNoDFEVTUBlf7w_wnYLBakWSU7Q-vryzyOZVnUi9n65iaPUUGFpdvtjIM8dpD72xfP9svlZrk9Oj3O42gJJ00Z4_DBk0evXt_Mp5PJbJZibo6adthPjxfjOEzmc7SI1ojA0OaLpw_8yaK_vb59c8Ui9fHR9PRkerxYXDy00yr047iPrqpsVXft8PZHn6yv3oR-3HetL6ypqn7bkyNfN2GIaElYAH1z_x6RpJAlZzRWmJFMjgkQREU42aI4aB9dWRKRsQU4RF8YQ3YyBRURRQBwXljAmJwyGGOMIWslR-HIQwBhBlBmMNaRiUMPooi23w5lVTTNKVpIoqnflovFfrlmVUO-qEpv_dG9izi2b756hgoc-_NHF7vrG0xD3t1sv_5q7PdpDLPzk3KxMMzVfHZze1kdHT__1U8qPxn7dlLXiTMnsc4JoAKxUgxcH8_7fa_iJKf11aVCMqiqOeecQyyraTNZOOe7zSr0feac-g4M1dOZLwu0locYsxKIr-qUMyigK8ig8X7Y98a5Q8iHnFG0znlCRMBh30qMmmPOKeeEBOhc0UxMUbhJDZANGQIs6gnHeDDp5HH0TnPX7m9Wflrlfjh68qDfbvPAiwcXceg4DDGEMKaiqlerq5tnX3Xrzhi3uVrW0_lkPm1Xm7OLh76q1revYt_vNtvr61tnzd3NVbfebl9ezi_ulQ52r78-feddErbOuNKtrq6cr6bHJ5JzGpPzNsUw9n2MwVQT65Em06Hr0djE2RhiyZKThJhjQmVgaKYnzdE8hQGtExAwxjo8wEkwZeOcgpBBIDUH6QozJ8kpGmsTx9D25KzBPLa9AdBxjP3ovUFQUTagLJLy2le-XW2ni6PQtsVkwqknRWU5uBcBxdXV9GSOlrwrnnz8weL4uKhrQr25vt7drVMcNMY0jgoCkgm0ntbW4rhvy0lNIGgxDUFyJCPkLTl7cMGcPzx__P5bpw_Pmol77-N3iEg4KaqogCUhDiHvd_sw9MMweKT58dnF2b3ze_fO7t_3hSkXRey6MIbVm8vUtjHk-2_fnz04GuL48tfPr7943e_bWVnFlETzarkzRKfHs6ff_rBb3jSzcnFx8k_-4Pu3V7ePHz7o1-3Pf_nlX__HH3_9xdeAYCwdlph9z49_93dU-HbdHs1mj95-sL69IjIpcmELZ6DfDf0wmNLNj0_ef_tibv0H33ry8cdvkbVFYd95cr_0DhL_8V9_vpj6s7cvfFm1XacFvbq-GkV-8dOvXrx-dfVm9frV9XbXtevOV6VK7ndbW7nTB0dnTx9yP5yeHC_Xva_M_Pzo4unFcr07e3RRl2WKeW5p-2bZ7VvnKwvpn_2j3_ngwfk__d63KWRf13ft-C_-4udXm_jJb3_47NllkiAkY4yTeRljHNr-cDAtrCWCadMASIjjMIz33z5aXm9ePrs2apdXO6cmx7B8fZ2GsSrJnR63-5R3-_3VZrPaN4tpTHL_u08WSO3Vdd7v-81uMjtF4f12_-b1ZVG5sQ1vnr-eLuqxbcumcrPJ0HYIQogHBDAiqS8QleOgoBJiDok4KzOQCKuoAKlRgtKY2kNO3PaQAuWU216iaBLhyLtBxxHHxEOWmAgN73tDGmJEwGZeW0tikfcd-CK3AzC7wmZSZkQEyBkUoMvAKMiaBURARIGICERSjBpS2u5kvdO-xzGRSI6BFYCMxHiI8XAKpEJIwhFVFYC8JSJDVoUlJcnZECAIHQaKmVXkUIc0rvRNiQAHrgo5A5IPBSfO2ZCiCoRkDUliRTDGgAEgQ1WN0wWAI19IThKHqqxSDACIZFQ1cS6aCTnrqppVfdVYazLnMI5xSApKoiLpcCBDRFEGVUA05BARjaHMaQggaokkcQoh7HYqMfadKgmCRCZf6bBHEBa1RcX9VnI6kCGRE2mWodPUI6mqovWmKVJkqgtfV_1mUFNAUZrZLIDYxRybKiqCd4pGnQVDAAAW0ZKpCKcVTgtjUOKo4whxNM6qZBhG2AdoR8oKqpPGpyFgZuRMgZUFAUFQD0oIZsgMysQswwgCoKKSMGZk1ZwBUdKoIQI6ib1BJGPsrLIPZtQOm5dvCNKwHUgIJGtKhcXF6blo7to4tvHpp580k2az2bXbdexaGQJKzilxtwZbHjoM3qKxljlx5kMvVgGV2TrSLGiNZkAiUzST09PNzZ2tJtLtIIQ0DEaFyCiIM5T6KCkqCxoN3b48Oh7a1haeQy8paRZJAVImQhU2BskayZljNt7zGIwh63zue2NJQEVZVYFIYlBRBUQE6wgJyRpClBhJkCVpyqYoCA5JBhURchZEy2YqInE_GGcAEJ0hMr6sysUkR2YQd6BnWptzlpTjMOQcEdG7wtYTAMlZmuncGDeOvfc2dEOKCQkyJ83ii9KWZY6haCZhGKiwLCzMzjkiyjETUT2djm1LxuTDhzEYh65sqrHvDDlfNUjCkdPQW-eUmdC4wmsWzqxIhgwYI2GcLk76_c45b13B5M4u7t3d3JK1i5OTYbdm1rJs_pM_-ifzk8lf_9XPPvv5b5Zv3liA0wf3Yize__RbZ_eOUPHLX35-7-Ks73bPX1w20-qtp-_c3N4dn548fPvt1y9ekLUnZ_fO7j989fr1x9_73tMP3p8fz2-vLr948fL8ZHZ-76yp6sdv3felO51PRMhW9l__5a8184OH99gXP_-bXz3-6NGvf_LF3ZsljL1pHr0HYIHFVh4QOGRjnTHG2UJSRkRrjWauJmW3vEHyrphMZrPZ8Xx7t2om02Z60rXb2clpCKOCOb54BwzwGIkcoiHnhTN4T4SuqkFYEoMogGrOmmXY3xhfGVcV5YWE1bDbjX2LzrqqABEAJVUiC4BEQKoSgyp06ztLtpjNc47WEpGkPqhqWU_jfjuZ1O12tXlzGWJsh2FxNnfGRM7f-fjD19dLTtkXbtj1AqApL9f7PI7T0-Ptuq3rWoHXb5Ykcvz4QTG72G-3_d0yrNvdzS0yc4hH549mJw9MVcQhG2t211cGcezCxaPHIYaUUjObD10PmY13OYKval9X3XI7tm3ZTOBwQCNDxoKicZaMj8OonDkwIHjvyRyChAyH_hehKnBmWzZkvRqL1rqmQUDhLInh0AZy36zSICfJSSR9s2sBNlYBOA1bMDaOI4iEuyVAjl2fY0_Odl0wDstyUjVeM4vw7mp1dPFgd3uFDJbIGgzb7fXXr4blcrvZnr79uE8JAe49emt5eXfx4PHkZNGnVJZ16gOisaWbz2Z910uUZjo9e3p_8-JrS9qt9oDqrPfeSA6cxv3yJnOanCzK6ZEq9N1OBfv9TgmIzPzxA2IKKRFpYQtBkJwASXP2s0IjgwokVgTrHKFBRwBkCwfWEmq9mPuySodkIWjO7Isix8BDQKI0DKqkworoSx_bFgG8t_vl2i8mHKWo6hRz7tvp0Wm36Y1zk2YyvXgS17ezk_OwW47bpUPeL29ivy8m9XZzu11eH53dryZzVxhrwRkqm6Zf3hni_u42bTZkze3nnx-99SR0XdlMjLUxtMO-n5yflvU8D4M1FlhA2XCMqReh-uQIydbzk2HblnUlKSIKgeY4ski7X5PR5mSuhsauQ0XrCxV13ikAAIKgZFZRMkTWARjjLSAACyS23sSuV_TN-Zxy4pysQwVmTuQ9EHpnZQyp7ZUzMg9jX0-PnCvR-WY6t0VZzmZ5jCmza6wgYVF02_VutdlvN912ndLIYQztFkQsOSKDgIiGIw_bsTk-DpttHkI-UDWs4QzT8wfNycni4mLc74-Oz_thvL26vXx2vbm63l4vy6om5e3tyoEJY7h-8yYOLSncO39wfHx2dHRczxsEvLx83W7Xz3_1bHt3B5JjCFU5aY6PrXHry9W4H3ncL6ZTANy1AxXFB-9-cO_BvZPT6eJk-tM__etxuxKFr764MpLff_yw67uf_MVPd6u71e0qcUJnVGzKqe_y4vy-I-7T8OTtJ3NHly9fTmYVeMwhLZr67Oj8h7_33U---_Z7Hz6ZTEqNSob6Prb74ep6ve_3__5v_-7e-b2b5fqDj99ykzrGvN7up6fH-_1-fbv7-sVlvSjUoS9tjD2wlk39yX_nH0jkJ-8_nswmN5cbNHp8fu_m5U0_DCfnR7ub5fZ2N27DEPJ-uZ7X0_eePohtnE6nn3zrw28_ffjuxb2ui74wxrrr3fjv_vxvcVbebfcvvvo6cYbCXb26Say79Xj1Zrntu-Pj03pSLRYTVR661HVdt-_ymHbrttuMQzeQgb4byVlErRaTsi4Wp6djO4zL1e5y40xx8vDe8ZMnw24L6_3mzbqL_eT0-OLBWydnx_3dcr3bbJer0_sPbl88byrrnb15fTM5mQzbHecIIpwGGQbiTAbzYdM39OQMc5IUjUHlLCmjIUCWPpBzaIT7HlQ0jJSyJiYyOo667ySMyuwnE3u2aB6edjcr5xCVQPPi3pxTr4mNc2KMnUwMCredLTD0HRSkOQoiRIac0BugDAyQBIgQBEnRZpAx7fa86zAET2pZIDHnxFHcojoc_kAZUDRlY6ykhIic8uEdBYqiApzRAOqBCJ1VMwgCABkk60DVli6HnFLKKRtrbOVz6DUzqnxD-A_JEKkcOgWHgxqI8cXp6fS9ezyor4s0DLOjRex7zVzMFyKSVYvjI1cX6C3njIghjHkcRVgYWMV5RBEii8YgGM4pjSMaQ9ZYRzmyZpachRVQJeXc9wDM_WisCughKwCaVEdJrIoxDMKtIaOKHNPhy5GQ0UJOjITWFiyshgDAzpvUBqor9-AIrBNnwZdqHSOota6pwBCnJN0OyJCzoMCsstlpZInJzCpRhczathAT5ICAmJREAEniaAh1DHiI2gOyMFlCAjKgelgFsDKDKhyuPXF0iCKgBkUTMOKkQVJgQbKgyH3Il3e5G4qiFLVPf_i9qml211eTptovlyGKr-q3fuvTzLmcFsuXr7Z3t2m_1xQKQ1kEAaisRNVVNWtSVuM9EhAaVCZBBBJOuQvkbVnXIUQi2xzPOHNVVTl0cXXLMRpAECVrJGYyhhzllDhl4ywoxpjR-tC3dT0HyakfCdiQkaTGOkTMY4-KIofBPCOSpmi8yym70ud9DxaVmQCNdZoZUpQY0RUckgofxv1UWAl49MFb42anSIDCLJZIFTIK5-hKZ4xJIfu6dr6MYwAAY22KmQgFCME08zmJhjBqBuerlJMtqxSjK8qirouyGcahquty2qA1Y9sRElkLxihqUVQpJ0lZETXD_OJi3G4RCdH4usxpyCFaZ1w1BVJLduwH5jxdnCJSCoEQWMUYUBYA4izW2JiiQSmKaeZMhlxVjH3nmxrA9Mn-_j_-h3Ho922YLKaT6YSM-9Ef_v63P_00gwZJf_rv_-ri3mIyq54_v377g0--9_t_v65Qc_r53_4MER699ejk9Pz0rYvQDsPQEXplPTpb3Ly58r66uble77fvvPfew8f3N7t1Gsd3Hj14-9HZ47PzPozf_cFHN7dbiNkVnkGfv3g5KU1J_ub69ec__-L1l2_mDxdf_vrFpICx2xuuj1Wyq0swAmhNWeaQqXDMIAAx98oiqpoGlJxiLpvZ0LeIpppUw27X7Xeu8rdvLuvZHB3t281kupifPvLTCeeogovjczCWFVmFnFcR3zRyMJaLcg6WSkkh7O9A1fsihIhIoMiZh_XeeBr7kEL0RW1Lb53hzCIswjz2zelRHvpiMg_rJTmN205VeMzWWcTMaRx27e3Xb4ZhMFWhnk7nc0UY-_Hs_AQE6qr-4P33umHMIVXzyTgGV5Snjy_Gdre63TeFOV4cV9OGSMehNUaNdWOmYjpXY--9-8nkZLY4OnFFud7t0CAZJzlzjt7brFJNJyePHiLZoWvRmNDuy6oh68kXzheunihqEhVBWxXWe2MIkHmMKUZhsdbGEDiLZABVW5WABo1xVVP4xpYNpyxCYNBPa0XyVU3Oq6gvq4O2BkRBmWMiANCkOeWcOMW6bprH92xmY4nzOPa7sihiGkKIVEycL6bHpzF0xpCiFmUBIjEm5yxqVkkqaX-1On5wyjHtV2s4NKiQpotjlRxjImuBtB8iKN3_9On61XLctQRYz6e-KEEViMauz12QMILk0Hf7XWe9KxdTSWCM05xAc04pjiMZQkVyfmxbyUkVjDFAyDGTQRUga0PbHvwQw74n5wApj4ETx76PfZCcNQ6h6zgEVC6aAhhExVjjCn8oXotBzaJZ8jiQMalrjXPocH60GNveFJVvmrKuGGH98qu-H4btbnp86guSnDlzisFZJzkZ0M3dJqV4fO9B7Nt2u90uVwjqvAEWZgFlRuEQFE3gZO2hb8WSc9VMXFHUx_eH7TbFCENI_Z77Pvat90XVNEVR1bMjEQlDNoVXwhSGoqzSOPabfdqPKApqrcN6OlFUEcwxozNAZCwSkLCoKiiqgCsr35SqCpzr47klyH1QZI1ZVIFQsoqgZiYVyUlBcwy-LLu7GyDNnEQSlNZY4y01J7P2bm_I9ptNHsbUbTUFHkYeI2X2ZWmQbONM7WM_eudSGK0zRlQMqooiiKqfTOrTU1vacRgkjucPHovmbrNHVJJUeGfI3N3e7lZrVXr01rtF7Y4Ws7fefuf0_P500Wx3m9ub67uby9fPv263GySDhMjsVJIwqjMevbfAabEovC8R6ePf_dZbbz-5__C0a7df_ObLFPIXv35RGs5Abdv_4T_9g6OTxb2z8wR09umDH__x3-52O1M6KmxiVaLmpDGOeIx1WT88mleFef_dt07m0_feffjt958-eXA-XVSIsN8HNbDvxy7lo_Oj48cnP_vZ51VVPHr88OP3n5Loyb2T3Xb35W--vn5923fpq9-89J6o9P16qG3Zr3Zo0GZ66-0HDx8-6F9e8jiAUlkYV5SFKUPf97u9iL569loBimbqmubxJ-8euaoit1vvc6L_9X_-Ryeq-1e3MfD52VE2tI_d__7_8v-5Xm3_-f_0H96-bL_1yeO70H328xcx50P0-eR80czrm8tlVdH11c2-Hdb77WrbHl1U-9vWRiaC83fON6uNoNanvj5qSuuOH5x_9pPftDdL711dVLPTOWXdX9_xmO7e3DZ1sR_Co0dv37t31N7evv7iRVK49_Y7b778Om9bj3G7XDHS5HjWbbc5j6BZY1JlcsRZtWmAk_UeD8mgHEkVQBFAhPGbqYrqPhCBZiFVRJDEKoqqzlvNQmTUeUCgmEAgdaOxRnKO6y0k4Bg1JSJnrJ5cnHarfY4ZGGWfjQXNDMIw8zAkBAPCRKScICoEgd0g21FjoBCIs8YEOUnK5L3xTkLAECQrKpA1JKyqZFFUQIAAkIiF8WAMTYJERhUAOCdDFkEBSUERSFhySORIRJBIYuSYEMEcQJ6iZC2BIpEIKyJYYxdNdX6ippCMpiyOTmf7_T6OvVFbzqa28LZwaJ0kDl3PieMwiighWvrmiiWckEUyG0QV5TiAqHGOAHNmZCmqKsWQYzIW0BAYUQt5GExtjUFVBQLIh0qDqEFEQWQUyWGUzMYZQ6CHsAqiiByeniIZb0Uwj5l85S6O_PlRimJOj-ystIt5jFEQlIizWueMd5AzcwYiQAVg4AAs0o7fRHrIgDWQFGIkQ0hCICiqmVlYYzbOCioYo5zxYLoJDMyHQikCADNmITxoMg3UXlWgqhAEcjZARGggSwiAqjmTcR_9vR9sb-_a5V3sdghSTOcscnTvHondXN6p09h2OfTOEjkCADSYUzCiJJyHEVQPWkoCJVVkBRXMCQ2Sd6gknMlYX9bGlUh-e_kqj4OGqCH62dw4JERE0MwcGYGNtSoChEXT-KLKnFPqIUTrPCgaWxhvDvu3PAZXlgiAoJoS8oFsS2QsERpjQMUQEaDkrKoHXid4i8y2sKgooqrgrB2vbhEQjAEQVECizBkUgVlFwBx2DgQqkjnFXEym9XSWmVV1fnYOqPtNW5Z1vThGoBSCAmjm-b0LX_oQQre-swa61SZ03eFZI1FmEc5Ftei7rZ9Mymbiy3LsdilEAEJE5jist0XhOQsi-qLkcZjM59VkZsgB5rEdiNQ4l0Ymb8laJGOMJYNApCJgyHgvxoWs548fP3zrrQ8--paAxCQhhSfvfvDm9Yt7985Pz8-b6ewv_vonr1_eXn99LZIt6qP3Prr_4eM0Do7cf_tv_8PxYv7Rh9-6__AeWvrVT372-OFbKUgcw3d_9_fAQLvevrm--eDdDx-_df9sPvNkjLOffvT-aru6u92OQ_vq5YrIXF3ejmMEND_-01-6piyK4tXzS-WUt9unnz5tc3LOpNCFzd6oPzFoc8oxckoCiK5pjCvRWQaQMVtHvqrjGEEPcIBofb3ZttPZtJxMp0czIPVFNfRba60hE1JMeYxDN5ktAKmop5PjRT2_H4borGEGBUO2YEDjy8n5W3kczAEQZZyquKJ0ZVHMJ2U1qWdzY03dTDkJWnRk4zjGkACttTZ147jZE7oUB8kwOZkXpYWQlCPmLElyzIYIOHSb1ermenW1MlW5321y1i6MRVkJQTcMp2envqpWN5uze0fdMMR9C0LHRye79dY3HhRs3Uzni-XLK-tt3Uza1Q16bO8u766uxxj2u_XRxYXmIMKxH1PkB2899WXZ77ZpGMduAFTv_fTsTNFMZkfG2WI6bWbH5GpXTZXUVxUoUlEAECj5quHMAui9c3UJxIDEITPnsmrIGI4RrfV1beeznCAnkCxp2_E4ABGAOltZAuu9pmANQkoiSVJEzt65OI5VUcaQfFVZV6FxcezKcqYonEPs-v1-bcrKNxMR3i9XRXM_hXGMqZlP877PQ5_DPnZDYcqQQm7b0-NjELi7WU0m88X56fzszDeL3XZzdHHSLXdkQDm7prl9c1tNG0TlMAKqppDHnoz1VZlC4BTSGASAClfOJgQWADhGZS3qylhL1tazhXIOw0gMvq4lRiUwlqrFInQjOjM5XgzDIELVbALKZMlY9L4Ag9ZQURZxGIB8fXJk6zqHIY5R_v-eESKo5lNrFEHrxbRbdaacmtLWZ8c5Y30036-3w35vCKbHMxbOMQCipOQQ0zimOBCAd6Vv6pTTvm2ni9Pzd96XzTKGcVhvUIBzImcMgqYc-s6XZTWdhrEDQSLb7jZVMw3jCKIHWhFaozF5b3Pf9-tlOW3Wy2V9ciYEgmDJ-qomBFFxzjfThbFqC5eGPo1RgIrZnAqDBxcjowgDIsihyYbkLA8phUTOydCbwsVuPByzjLMkSs5hjuYbQggBAMegqmSthgCcQj9w38X9nmMIux0Ix74lSaBZshrvy3rhS2cKoylLzjmmuGtRJaaIRFVTjzEWdVk1k-bo3JXFAV6RYrBAY4ghhLLws_k8Dm0cAzIP_aAspw_Oz-8_TKrXry53my0C3i2vb968ubt8owj75Y4AIfPQdhpZxghZFvcfUm092psXr1V0fdPPjubvfus9ELy7utst7958_ere6enzzz_PeUgCk6OjH_zoB-N-s7zZ_uoXv7rZXv6r__r_64tCFTSKL6uqbjRK14cf_YO_9-D-2fd_8OnJ8Tzm_Op61UwndVErFJvdfjKvo-Qvn7388vnNs-dX4xB-8eWXt6-XIcZHD-4Dmcz65tXrvh99WaDS_OzUeD0-nVpfvnp9PcbR-uL00dn5w7O3v_Wu83S76a7Xm3bTVtM6pki26IYtZwAAdcZYe_zgHJi___vvbz67hj60V6sPPn3nP_-f_IGO8fmXL_uYHz04tR6u2_7_-F__P9fdfj2M123sOL26XD377IukykKzJ4tJU67XuzxKLsLQ7nerrVpcvVmlbbf6_Krb9rOLedqPl1_dKYHNgiOnblxd3V0-u7TWNnUzdvm3_uBJ0fCrz--2d3fG2pMH56u75dP336t98fJnv7q7Xam1b3_4bg795uWVk1E1Y9Wcvf9o3OzGvkv94ItSJImIqGphgZOEEVJCb3LfY86qQgSHOwCiwZSBMzADGQmRbEG-EFDjUHPiyGZSl4t73G8xS-xHU3pBsrUhSzywBNGYeIgoQORiGJw9iEgzBgYGtAAxwbYDY6BPBgFigKC2MtC3lAXiaB0hIBDyMKiAaQpRYU7ELDGCiiUCyZD4AMgHa0gADIHkw4FeWUCE8JsqrzUemMGQAqBzaKzxThGB0CAQiuaoqoAASQjkYA0DQEAAIkXAqkCq0Fe2aiInV3oygkjGEBnMMYUhDH2vOQOqRQU9-A6YQCALoEMRxAw5aUwqmSWBUQSDhoDAWmMQVfMBeHioiqoiYWUK5aSIyjEhIuSAKf__aPqzWNuy7DwTG2PMZrW7OWef7t4b995oMyIyMzJTTHYiKYqtyhIEybJlSK5SFayXgmHYfrBh-8WwHwwDLvjJQMEov5ULhmFXI1cVYJMliipKJEUmk8lMZkZmREZ7I-K2p9vd6mYzxvDDDr6fBudgz7XmGP__fz8IAzKHYJxP3Q6NURYgAQVlQWM0MRQELGqIHJE3KojO0HI-JRkue7M6qs9Wu81kW59ZNCZApAYxM09sfIkFEJEMA4QMUdECaIIxHWxTYC20M8hCgsoJclZWTgmUkIxmVmsAGRUxjCCsoKAMrMY7UFFgOtRagaXCQkrKigQwBp0iggICcOSYldnXJRbFcrHqdl13ee2MxjAszl-SEE7Pz68__6y_vQLmzH2OnGMgazkHTpOGpCgGCRDIEnI2IpgTj0Eyf0mDZTWAAJiGwVRlypxjnHY7Z6ia1xCCcSRpVE4pJ8nypXcLVBFt06YxGOeK2SyNfRomIMwhoKWYQw4RAYgQzZfZbg6jMQ45IxEzt0cLQJi2_ZelvgcjnAIiGuOVM0RWEU2KhCqCAugti-acQQnRAIIBstaqiHEOANCYOAZhNUUhDKLKqjmkqplJGiVlNKioWUQlubKWzGU7m3Zj0czHvpPMhS-rpjXOimbrrSo6a3xZjf02TwGAvPMKkKbRVx5VLJG3tixLVCZjFBQJwzCy4ux4MQ5jGkYiMmWhgMYZWxR5GBENkRpn2eCUeXXn7muvv_3w1a89fOXl5cnq4u69uq2T8A9_-CPvnS_qTz_6_JXXX_sbv_Fr_9f_8D-5e-c0csrKs-Vivjq13u634-cffPjjd9978-2vHp2uprF77fVXv_tvvhuGJAgsAgYu7l783n_1z19-7ZWXX33NGHjx_Oq1r7y53e0qX-76HWROJO1s8cGHn3vnd93Yzpof_-Dd5Wl79eRqdzugTB-_-0FVV-cPXv343Y95nLqra2vAPPjrv5Vibk-OrVGOomSss0XdSBZjbLM6t9WiW29tUagzoRsVNIfeEQFK3w37Tbc4OZ_6XoWeP35c1TPglMZht93FnHzh21nbDQE1nZ1f-KJYnD4wvsRiQZBjiJIBrQUBIRTVKQRTFGkM0344yJfGOO-rqmkRjaKwGkRTH82HrsfCFG3pbBFDKJyzdaEhFrMWQXJgIaDKo7E5cJpCs6i6_f7mxYtut7l88dwQ3VxeSUpFXYkKIcxn7Xy-_Jmvvn69G4_aJkvOIrvt2pVFjHp0dnc2b26e79IUFcEj5dhP21sOo4L23eSror04Lqu6KFyYRgI6u_dW5oGcq-oq5RxCcr4o7ixLRAHNOVVN1c7m1heZQQTQUj1fgoIrC7SejCHnY5-MLw2hIoPyoTImcVbQsjoyWDvnlNQ6Z70XFeuMtSQgKkwHRoYIGpPHhMYIq2ZRlnGzIYMpBSxKULREKQZAmfY7Toya5svj0PekqXSutDhbHNWLitAu3v6ZeX2xuXwMOW2u1wDC-_Hm9nJ17-zJZ0-beYFkXVEg2pyEAQBRJRoB6wrfVGG79nUJ6MrZ7JBiYpU8Rlc6QlVFQuLMkhWJiFwzP2JlTjnlKaekkhXAOV_O5sCJvHPepphU0BhbzObTvvdlXbYNpygsiMghASpz1swADMIIkoaJw3RIfRyaqo0lYZGYq3YhMUvOpnJpGlkRfZ1zrto2jIOKtovFGMK021sLrvaxy8u7ryJ3htA7M_ZdSpNBKgsrrAdIHxLlqM0MSRUArC1nZ3fQIADvt-uU2RXl_uoyhxDH3nhbzecg6CovLByEyNTLmeSQp1FSHHd7461BWxT1_PjOZn2jhCklzSGllKfYLGcSY8qJQEANmcIVDSilKRkiPaTPrZGckAwZNM6HoQdQZpZ8mJocAQqoxhHRGufQW9WDzVQN4WFJY62RGAkUVXOIqoLCnBmIXV0z5DT1PAVJOadonCUisuSKkgXa42Nryfmyadp2dZymaew7Vd7dbJ3zBjmHNOy7_maH5B9_-rnkaL1Znp9X8xIE6raKfYzT3joax3Hc95JTihFSsg7JWOMNWsNDZxXBgKa8fb6RFO68dMd5b62r59XVi-tPfvzh7dX1fjf4qn7y6Avv4PTunXt37rz-5qvzplZjP3zy-dMvPp82_Xw2T0Nq5rOybZE8QfELP_vNb337ncLg0fFKQXdh-PzRs6KtU4nd9fov_-LdTz774tOPX3z08XPj69d-5mWvdNKWn3_04s037r399psnJydTGJ48fjKMoapnm9stFRZb9-mHn643437IZ197aV7NZk0dmTXq8xc3kB2THXe71cOLzz9-kodw_eJm3HT72_W-68umEIXZSZ3HvP_8Vvf4M2-_8nd_45vffPnO5aNnjx89_erbr7762kt-Vo5j-I__2e9-8dnjwMzWoeTa2udPbzZdFwd5_Y0H_Xb79NGzoQtKHIe0e7GtnL95up7VvlA0Ehfni-3lbrcZqov2aDlPYzJWtrd9jvD2z7_Bgc_uncxnePPZ9pMfvYisZMzpyez5kxdHizsP7pw---TR1I--KZp23tbzFx98aDgIxyRSnq6aRXP18aeS2BEROeaAh5nVYO4Ha4xyVlHrMI-TZkEEFWFAlUTMIgpkhPQQIEaPQqIhIyp4b8tCeCBGVpCQhdVYwyEdQAtZsjVEigRCOQOY2aJJmlOIRCh5gsC6H8EjkQMSyCwCtFro1RpCUEEk4DBxjCICZNA51xSYsyHIIRGABUVJkDIowqF8tHYHb5GwkrMCTMIEqDGhIVAkBCDKmQEJjTXWiwqLaspEBJwO8QBkQYcEAJIVANGYumRVEWOqmWlbKgq1hkOfur1MEUuKfZCQJKQ0ZR4H1AwsmlhCQlWDKmECYM6BTMuxZxmQDJEYRxLjodVVFQAINQMi52StRRBCVWXCrGQlB04ZDxSClI03KJlzAlByVjWrqiIQoqoiADoSUA6K1pG10y6YquScEiPWtTs98otmmtLi7opzUmUgkGECRCyAdyN5RAT0TqZJBWCKWHgdBwgZlEEyoAIo5AQlamE0oiZRe2hBFEIEVRWBkOHAv48JkEAAQA-dNaCgnBWQvCMVzIIiOowgTPQleU1zQhCEDCLGVcvVarFob549LapqfrRgRlfUl59_3F9fI0n3xYdYFHG7V4kcRmEGUeOMqnJKZCxPEyGQZA4TqFgrHBmtdU0NISIpkkFXVotFnAbNsa6L2HcSIxqTp4nQqAKSphCBAJHQGFuUkLWYL-MYvPfWW2YGVY7Rlq4oSzJGmYu25hhUQVMm-pLZz1NCQ6HrjXGqB1yVkDGoQtaACCGSJeWMSEiASCyiomBURY07BARMc3Y67naISIhlM2MRYyxaq6rGW8ksmWfHp93NFR4g_mUTxqksSkRUwpTZ17X1vmyq3ea2bhsiysxxGiWEpl2yyNT15J2mOD89P1TW5RQlJzzkqAGrZp5DkANat6ljtxeg1ekFoMRuVM3GoCJJ0KOTs3HXW2PRoDPOFM1Lr7z18LWvrs7v-Lp69uzp0-cvdn1X181-P777gx---c7XK1t-_vmzZtb8vX_vv_vP_4vfiWP_137lm3fu3mnaGZA-e_Z8dXp36re7brx46cIV1cP79xbzFhH33Xh8clz41hpvVD_75NOvfOXVOy-dloVNMbz-5qsKOuxvP_rs88vHT0Xwdts9e345pVS3zdXT55cvLg_Q7WefPUEZ19fXRVG-8_d-9i_-5E_T-rbfr0GUYzBDtimOeRjQ-no5b46W427NUdrTe5K7MEVqnfMFFT5P2Td1c7KaunFxfqYsrqzLttlcvzg5vwPAy9OzaRyWx4vVnXvGe-_ssN503aap2mkagaRoCgHupuDbqlmetss7iXF198J43yxXguRdtbx3h0MC1apqDtfA9c1aVe68-ZqIABhOzBGaZbs4Pdre7uLYL05WIly09W7Tm6KydXWgcinjOE45JMmapuiIYggagkPl0IW-u352Wc2Lbj8BGFuV09B3Q7IGS19Wdbk4WrBq3bYh5nHfq4Jvald6IpEQ4pjI-LJu1BfIU5r664-fikiOwTiXCda3T1VtYmGA9bMrSFK1ze6zF8PmdtzfjNvrlKIvS3DG-PLi_sshxWHfpRAMUVG1ZI2IoiXnHQi5ps1RiUhisoVLYUz9fhy3RFBUDThfNEcMWcWwZEMKoCkGYxwgAgA6Z5y1tkBrEMB5ay1KiBJG0EzWkDWunoWx42nnnB-366MHdytbOaKrF5tMMj89i2karp4DDouL0_X1_vS1l2PXx34nmbvbm6OT46HrLl6-v-t2ZVOf3j1v502zXGyubp3zvqg5JjJFjhMgDv1YHx0XbaNAwAIqooLeyTCSyJdUO0s5TUg-TAOzEpHk7MtKc45xzJw4sWsaSAwitnQcRiMQ4qQqBg06IuPAOcnJEDGzijpfSGRlVhFmUcBmdQyqaUrWO46scVIATjlPY71cAACqLo4W-82-beqybXzVAmFRlTwlyNmQ2Tx77OpChUM_SGaeYup3SDZ026JwRTMrLxbjrpccSCSPE3mfpr5azuI0AR1i4np099QRjV0fUlLFcQi2rrxvEA2CpHFEII7JGPLGcBidc6JpGPbt6sQvl-N-Yyx4XzJnspZT8t6TCCpglhgGa225mJEty_ZYCYiccNIU0RqOgaxVzghf9pkggBpDYA6QaTnAaAkNGIIvO-BBQZiNsYgAqmQIySqJIcv9HtBI5AOpTR0ZX1XzWTNvBdB4X89qBe5vN2QxDt36-Ys0DtYZyEKQpu1md3mtmiHHWeP7_R5J5kczMnBzdXPz9CoOQ4yprMtxu99eX4dh4GlSEO-scAy7TsYEonF_S6o5saqmFEVyM5uHnEKY1EoehvXNNeeoxrqqFOY4hXo260Y5vlh41KefP_v86aPNzX53vYOEr7_-2ssv36mb-ZvvPHjn577-7W-8ISWutyNbcwO77_zL77z3_odffP50d3Vz8-T69nrz-Iubf_zv_vc---ln293uq-88-MvvvPfZR5-XdfHON99-6eFFHPnP_-S7V5vN0E3L1dHRafH88fP3_uLTzXbNqq5yD966uH50O657O7ePP3och6nfDCmE_vqWMmyuLlGFrB_W-3ZRN_P27lcezheexNw-X580pa-W_-Qf_M2XH5wb4e1m-OnHL371t75VVs1PHz15frv9b_7oez9494N-mOrj2WTgK7_6zTdXJz9898PDnr0bu83NZuyGsvEcYeo7jXHsxmZR8jjlmE3lRCim2FRNaX1cb0mo36Tzi7Ov_uI3n3742ApS6IcXN8OQYx_rqiAZh-vu9N7Dew_vOJk-evfjalZNu-mtr73x3p_-Oaa47_bk_ezuHaN5_fg5xwAg5GwO46FvyDqT9htbtipCZESyhIkIgRDwr2xAnJVZFdB7UiZr_VGZQiJrNWW0DqaomjkkMhbsl40lpGoQNWXXOGONhKwAeZoQ8rQexr4TIk5J44TWQGI0WJ60aT_AJIaIHJp9x5zRGDAghOAt1QVYa7wlyBASDxMRacrOWR7GQ65aANUiAICiIUIFsnT4W2RMaBARgQwiKKqSIVJT1qqKpAAEGg2qOWzoWY0xiEreyZQU0BkLBCyqvizPTrIvbOWVMHZ7FE43G1AIfUhDsMocJg6jJeGYDjIDApA1BzgpAjIzagJNKgZNYaxqzobMl6EFYZZMqKKqICqCiCzJIMQQYhhT3CkY28x42KECKn9JiiaCHFWAwNBJBfuIFlFRFJCMqyslNKi2rXNg8r65c4K-zGial85W9y4uP7288_C86zsOGWujIYEoRIas0o2yG3QYIQsIgGZEBGFIGUICTqgCU4CRITLOPYACEYHTaTAG0Tlhhi_prITGAWcABWHNrABgAQhBkSSjMmcBYXQOjRFRaxwhoGQJCQgAyBb1g1dfvbl8MfYjp9wen2rm_fUziHl-NK-PZkIUh444kTHKQnWhwpqSMQZFDrcZyElTRiJQlSRgCIlgGFhyGqNp2qNXXkaEuO9kmtI45HEiA2SADEnM1llUIONA0ZA99Cf4ZgYKZMzQddWiypxziuZwvU5Zc5KcAABURNgAHh77KkqkPAVA0MyoyomNtUhKgJCSqogoT8lUhQoY79EQEgIAHSpiWZWZyI7d3jiHiHW7DNNoigLJAoAoFmXt21lZN5wmUXVFXVTNyYNXxv065kxkBMga58sKka6vLhfHqxRCWVbTMIBkIjLOAdlmuSTSMEzWuZwiZwVmY0zZNDyOChj7LjL7piqqqt9sitncFt75MqW0vb51hTGu4sRnr7w-3L5wdTVOfb04mR2fvPLON11RKqGifvbhB1O3U0nTbnfz4nKzXrfz-eOPP990w8X9i6996-3nnz1dHC1e--pXrl9cv3h--8Unj8Zu_PrPffPZRx_vtjsGnTj8-m_-epz62xc3J2cnx6vTYRyfX7148uQLMbA6OT65OJnCtO-ny-c3GeJf_vkPPnrvo7svn6cozx8_XW-29axF0RgnztmI_eovvfzxu48uP_nceRgiX3zl3s2nL56__1g52NKEYdKUTHl2z5JJfWfI5Mzj7W3RNqKMnDiGsZ84hMOJRE5kXJzG85dfff7po6KZjd0eUIui7rp1VdbOk2YWVM2AAgQKOYUsCqm07vb5zbjdrW92Zdvu1p0tjS1N2bZlW84Wq6KpkUxRNc4VMYoAhWlQAZZMBqumGta7drmolsdVWTezeVFUZIs7r729fn7tfZFEkcTUVexGVFQGQnJn53VV3Hn9QdEWR3funp6fnD94sLlaE2rfDaYsCPP66dN-fbu-vvWlq9rieD7rx2mz3Z0fr8j5kHQ_9PO6Hfe9APmmdFXp6ooVjl-7q1CFfpA-yHZnUHxrSTMo7G5uJcdp6DlMoFhZO1suuvW2aav6yI-3a82DkRz22_7mJo69dTaF8Wh1JpIXy7N93wFo2bS-KsmWIkrOhSnW86UrnHFF0TTVbAaEvnQxxiSZijLl6Ku6XdwVzaZsRFUQWICKCv3h5JIqgvECwpklibUuhxGF0zgmyaHb1kerwlVHd14Zbi-n7S6M3dhP6EE1Dje349gTilED5AxwsShITE5hvmg4T93VVkWunz7RmGNOznpNPJvNGXQMPFvMmVAErPM5ZWMhhcSR_awhYDImjuGQ9LfGgQUkhZSR0HqvLL4qjTFhHK2lqlmmFMqmyah5TNVsnkLkKCIZgOKYfOl9UeScFYB8wTmBgi0cIlrn0XgRts4DKCKOu72taldWwrmoZ5wyK1tj0PjY9SzAnIn17CuvdjfXohincHx-kkIMUwjDpEnK1lsQTpnIucKXs5aMBWQVnfa7GFPRtsuj1Th0rqolR8mRkGIIYGy7OqnaWb9ZW1OgStlUyozIZVUcHvSurtBJOatzTEAgiDkxSOIwaZxSDNYWzLnwRWJxvogxKH4JZU4hxnHUlBUzK4dhp0Rj6Mumdb50RU2-ZFbrbFGVjKCarS9EGBGQ0BjHOSsCWQ-gAgIsiJhZyRoyxMpKkBMrYEpBVYXFzStTzVxVWGcVyDhLiKgwDt242ypLHAYOY9h11tg4jsN6ZwhQMEbOcdKcZBpRFRBEIOY0dYnIhr4fu5Gs8d7OZu00jJurW9BcOl_VjTVaz1vIAlkJsWpKZ4tx3xlfOO-LqgJVAdCY9uutxLjb7NIYiQxZMzs9ThKUGQC_9fPf-OZXv9LOjyCbN3_2GzeX65fv3_0n__bff_vN188uFm-_9eD87nG7agtrNt3ud__wey9eXK6f3zz64YeSk0Rumubk7CwmIbJ_69_5je_86--O-33l_E9_9MnY7975xhuvf_PtNMafvPfoer29eOni5NX7YbcLMb3_w0fe14uT5fHFvD1qbFGun-7CbqrbFkxsXD11HSTePr9kzinsb59dLk6O1OHpgzu2qgHkdn27v7qOHfyTf_Rvnfnit_7aV9ra_8Wfvnu8qP_ld96fndUP79_57rsff_LF1rTuj__ih88f36AHySkNcHbnbHNze_tiY4uCOeecxv3kikK3o-myYdEQZi8d5dCnHHYhLI6PxmmwCjklk6Jklcjf_uWfmd1f_OW_-N7LP3N_--mT3eNNF6Ss5taa7fMnZTNP2fzyL_xs2F7--R9873g5d75czI9Wq_qLd3-KjkrnmtOzcbdFyXkKOUYOkSypJhVGtDwFW5UE4HyVphERDs0nwqLCgAAH7ztaQLDW5zEAOWO8dT72AaZM3hnnNEdkQAA4q2GIJquvfXkykynEoM29lQMM0yhJ1Be2KZmjc5hjBEuWAJndvAibgQDIeh56zSxIajw4qyODNcYaq2AM5l2vQ-IhOO9BgKxgTgDAnMlbEbDW5inbWYWWJGTnPI98uCopMxoURVU9vH6R3CFCq8wSI6kYEVAFkS99KSIWjaKgNQIgim5-ZJdLqAtAypl5nHSYDAAqgHEQxRrDwyAhgmby1iBKziQszKyqqqIirFmzataY4LDJTQEO92pVZgGDEiMQSc5kraaYmQWEQZSzolBiY1GnkfKBdyQsTGREFFXBGkWiquAxobNorBIcgpvCotZTVUNB6My4HdxRVR41_e3ApPXFbN2tIXAeRmJGAR0ipAwHDCUBivwVHzqTM4oEBoicBj7QxomjhgnGCQlBwTWe0OYohwU8cAJASBE5gwAcftqBaJ4EFFEYWZT5UMsMBgDAHHZaIaIIEhlryLjm-GS1Ojs_P6vbZhjG9fVzTmnY71i4aqpufRvHUdMkMRMhkkgcIYbDaoyIgDOy_BVU3aOqscZaKyEhqrEOi9KXBYjyOCJn7whVJUVHxCyoBkBFsgr4si6OVjzuhUXBCquxrr9Zq6Q0BSA69GseypU1BT1oWYcAAAMedjrMSIYQlcV5r5IQhRAhMSB8mRi2RERAYq0TzqogIiBgrFUUBUXQsmnjOJRVA2REsvWeE8cpWOuMscw5DiOSPXxXuzw6ufPSFx9_mEWqek7GnN6576qyrCuRTABF43hKIYbQ9YTIrNM4LU7P0zDFsa_nR_ubta9KIqyrWcxTGKdmvnTOiyRjTE5ZhQ1a39TVfLm-urHGGAdIKMxEZththKGo65O7D4qqrZfHKlhW5ac__fj2i8-n3WbqhxwiqjHOLk9WnHHK_Ku_-atlWVg0P_3Jx8N-Ow3T86dPttc3OeRv_eIv_PiP__jx8xfeu1_5jd84ns2fPHn07MnlV7_5jS6Mf_Zv_vS99z88P18tT5a-KNb79Qc_-mDb9UO3f_bZF5-993F_s0aDYQhPPnkWwnR6fnr54sXN0-eX11vv_eJ03nX7L378KWGw1g5dAOarz74wHAySIS-cSLMpTh6O3eTrmWrWmAEopaSJiSiOfeHIwEHxZ3KOjGEVzWPd1nHsQFAlq6QY8s3VjfPF2Z0Hzx8_yVk2ly_KplmdnpbOba9veZoWJ8s8DZ4kDbuqsZyCiKjGMPE0TpL59KVTg-7m9ubo9LhuF6yAxizms_OHD5989nmeJs6p325Dmo7Pj1R4fbutK-fLko2_d_-l7Xas6poIiYypytnxLOx2eZzSFK21Z3cvEvPUjTFFBOGkGvI0DGXhF8sF5LHb7VjtydmZM8475wvXNGVZV7eXW07haLGcL9q2bqPK5voWFPLEaRhJs61MsahVjYGCQ0xT8Na6yrbLufYdasycUoy-bQC1v-0NZxBOXTDOGMTQDwZg3O_6zTYzx9jNjk5V0rTbD_vd0A3OeSD05bzb7wiwbNq-32iWA_OHEHOYwmYDKjmlZl6SszFnN5sbPwdTGGMVXFHN6pNXWBMDCufZxXmcBiTjygIAfF0SiopatJw57Hdl22jaV-2RbSpDRM6K5LCfIKYwdnG779eb8nhZlO2wW0-bHrQ4uv8QeSIRY3DY7XZ9f_7wQYqxKGfjMMRh8IUHzpxYQ67nC5A8bG80c4iTLxpXFqBovYvjmIeoMStnzTlNk7EUxskWJVkjLJmnaj6fhsn6ConilH1d-rJwVWWcqWd1HKacQjVfpBhVxXjnqta2lUw5ThOzKBLa0vqqbI-JqDldpG4EIOcKMgbI2MKqiDHIzA6BQTHz9ubGuYKIlKA9XoGn-fl5UdUxTinlHKMIxCEgmbKoIMvi6IIgxxhjPypSsTpCY0UEjaZxkhRTDmG3kxC8L8bN2hVNiAMAlb6c371_-8Xn0-1WCcduKBcnYMi3S2YhVOGkKVsEyTF0XTNfxRAYqJ2fKkoOgXOQLL6ujDGsmRA0JQQjKZIyhzD128wpS7LOG-dcWfqyZk6SRAnwgMAzYJwXzggHtrpVFbLeWg9fkqjJGGecASTy3jkPDMYaYyiHKew7VeWcyZJxZBRzCJxZUwQRCZE5W-t86YkIVBDVoKZxBADrXdE2KU4GfbNcGGs1BHKWYwYWEY79VM2L1Pcphqqp49jnfgSAFAbrXQxpGnrypqqXYRymbtjvu9Xdi6IsV_eOAXTou_nxolq2t7d7BJwfH7_00v1v_dw3X75_t9D8e__tH3704aeffPTJz7z11ulq9eP3P_js-bP3P_j0d_7gT9_94It3__LRu9977_0ffRS23bQfU9-BMZtN-vav_dr1i8uQY8qpmbVPHz3brLuvfu0rz19cn94_efMbb73yzoPf-90_-vH3f6wmR4UpTx__-H1l3PeDIxqHMU0TgN5s-xxzmnoTeXxxO1xvWJRDbmaLYlapEigcHy8Ibepie1TF3TYLn989247uf_4Pf3PVtMee2nunf_4XHz74yvmj241h-a1_8PO__zt_-v_5f_7-P_qf_M3_3X_wH02bKTciUTwQEnmhqTDSBRX5-isPuzyM41iBcIycAgn70oauV0FfLJ2iDAGTKAMnpmy__s4bv_hrX__xX_z0i_c_Ozlp3_v9P5MpRoW2XW236_3V5Z27D-48fHj_wflnP_zBfj_t1t3P_cav9rvN6b3TP_3__n5KMuyn-dlsd_UihACo027vCoOqhwoLXzYGAUlZOA9BrVhjgBOoqgFCIGtVGKIQAKKSNZyTrQtldKXLYwAVtAjKooKKpICicNVpSgQiwyT7yVdtiiltp2kYJMTibAbe5RwLY2UcSUGHSWOUjBzFVz5PGQgwCxgP1kChMA5oAKbJ5CTTKGMgRslsywJRcj9Zb3hKKAoGEcg4ryKm8KgISYBFciKDgASIkoTIkTUHDruqUuGFsypDZsyZUEEAFJHowIFDRMkJrGG0xeK0OD8Xg66u1GLY7TVnStlIghw5cvnSgvc9T4MBRBA0lHZ7O5sX9Vwxo7OIogAIYEoiQkmZjFXOB4kC5FBbcBhQhAhNaUWSxigcBBMUJGngFEkUCSEG60AjAyKoEtAho6Bo0HpFEhFlNGWFxiZmZrRtBUVhV0v2Nu6jX7R-uRhuNnGzJ6OpS_GmL3Icnt7gfnQWgEVCQhCIEwiDChmlqoSkEFiRQRCAdJyMKqSIWVAFhCiJpgCCvB-EFEDBApCBg6SQ48HTcnCoIwJkPTyvQAQPKmdiS2AVMQTITMJIBhFMYTkmQ_785VeeP3p68-JFN2x3m9swdnVd-6b01g7bW44j50jAZEly1MyQk3UOBRBVUnbOo0FgAQXOEQkNkh40AQFVEYH6aMUZ8zjyMMxOjqftGsEqiyErOaGConXGIlAYhjTl8s55vTyxhUljr5CLqrDWuqrJXWcRrbdp6Mka60skocIBM7CICKha6w66lXWeOaECGYPCqgAgRAYAD58QEIAkhKCsCooAykkia5LZnbPhZk1VIyEgogiStZyY0BhrYpgArfV-vjhKOaE1J-cXQ79bLI9F4OTiLhGGKRRF0e933Xa_WB4RGut9TllTLqoKQBGs816Vc86-qmZHR4YgjiOnWM8XxjjftlO3N-Q4TfXxKgxDOWvnR8eiPA2TSkTWaZrKpvHOMevFKy9Xs2UI4lx95-69xXL26Y9-ZGXc395Aznff-GrgfHR2xzfN27_47fnxySuvvfzZo0-uLl988t4Hzz__NHQ7TVFzvH3-AkL49P33N9vbr37j6z_7i7_87l9-9-ZyXdX1O1_7Bmj4iz_7nrO2Lor5bNndrD9496ek8Pl7H0CaUhh2Vy9k7MiKsCDZuq2X58f72_Vu053cvbj38L415dBPn_zgXaMCVtI0NfOy36xlHMmRimQOwmosGX_xZrE8JmsFpJw1KUZDSM7kYSQiMpZjHLedgqYQwVtC3d90xy_dM4YkjcZYAiVLEqZptyNlXxahXy-OF93N0_12P1-2R6fnSNBt1yoy7kbOkw5d2HbD1SVP8ehkLuMQ-k6HabO5bY4XoRvRuuX5STtfZJXQB1eXidUUPqZJeFpfvVAJvrC3V7fHp2cOwVX-pVdfAzJHq3vb3TolHrshxQQp9tt1nMbtzdX28mpzeZVDcIVvjud-VjminFO364c-Wm9F5dEHnwYO3tkphLIp68q_fO-uL-rC2h--91HTltcv1k1TtLO5iPjKxxiFVRTB2PLiqGqXzrhq3t4-fcrjkGOOYcwhZeF6UQOQX9WQcnm8JNFpTGVdurLqN3sCLGtHhra3G0NqwBy_9jXpN2RRcxi6HiEaR84XU7-p6llKcez2nLIIl2XhvQME4Wnc762xMU5xmGxZW2e9L8qqUSJQmVK0zs3mC0TKObEKALGqMgMrsEiYSl-T9dMU1Le72ysEq85PUwx9LGcNWuDM9cnSOW-JytmqdD6FsWzrwlBzdLJ9cSki9WrBYX_7_Hq2OkWQwljrnDF-sVotTo4BKXO8vbwp2kZVjPW-aFzly-U8doN1ha2cNQZANHNV1xymnAVBDZIhBDRxGlw5k5St9-S9dUXiKAI5RiQkdFlQ0gTGCDMqIRrvHFmSqOisdR4MpZw4R7JWpnz3zbem3S6xoKWibmMX2jv30hTIeWtcjjmMo3c-TH3ZlN1msJVJE4tC1c5CGE1RxMjkkbw1HiVGtAiay8VZnsLy7Gi7vh7HZAuPlvrbrRD6qiaksqkkMympwtRN5XzhKzd1Q8rRuKI4KVSibxrkKJnzFJvZomwbVUkxWmfJEKjmsROOkLJqqpqmPjqzhsYQUNkXjoyx1nEWQlKOKErCoKocJUWO4-GKn6axaGYpJ9XDvKcH9C4Ze0D0ABFZZ4231qNFBHRlYZznnK2xYCxItKXTfIBRky0LRXCV06wI6Kwz3pNBY4ywOO9yZgRlzjkzqzrrTFEAIiK5dt7d3lbzZbVc-LoGyUO3Q8T50RxBDSI56m93KQwImKeJJVerWU4ZiVgxa0YLooYR0Lnjuy_NVvNhigYxsnb7vmxrV1Q58S__-q_NyvJosSza5r13f_rJk8fvP_q8suXRYvn2G6_M2na_0A8--vz99z-WmDiwpKSZSYATi-I3vv2toU_NcvbOX__a4w_fGzd70TyfLbJMTz979Or9i8Ax7MPrb725G_Y_-jc_BM5hO6zOV7lP-6ubqrSbF1uq7bTvu3GMIGGM6ydXFqG_3iMzFFlIOedqMQtDIMU8DrOmDIlyxradU5oQ9Gf_-tf_6W__yl9__UHji-__4Z9dfO2tJ7dbPGo_efzk8rPnTTP7kz_9ydOrzi3M-q75_F8_YqeudsjGQPHaa_efPLtaNfWTT59s19ubfhi63iFM3UQON_31IBMiWDCkJanilCjL2IWybE6X87_1W9-uSvv9P_ng-nbfNL6_vtGQ7HKZkj785ldvn3yxrGdvf-2N177y2o_-4sc3N_tpmh6--fonH_ykdvbTH33AeUphmt0_Hoc9Zkk5xt2-bIvcDwCYczK-ENDcd6hEZYne6BRRkVNC-NKggYfHFyGCIpicD_2IaKxJ46QpS2ZClJRBFA0doPumckpGBMrFQjilEDKrr0tfOlt7UDFZZAzadd67uN8RJ4lqZ4UjUAZgRgKyFksPlHQ9QDfCMFoVzFnHCJklRgRCUpkCpKwpkTWSFAGoMApWFJC8dT6NPeeEZBT0QO0kJNsUEjOIKoAhK5LlS6QpgAASwiEHbExOB1RituT80THOFlRXiqxo0xBiP4EypoAhAYsKUFFwTGk3utKDiPFeCW0zyylCGCSrioIAwOEfiWmMCGjQIYKCIB5Kb0VFFQkNoLE5RFRQEckRQDQGiNmogGZC1RRF4VBZBkSmadSjsIC31ldm3lhnbNsmyWqNaRszq9Wgb2a2qlTUz2ohk3K2dU3IeZp4mgB5WneUc9n4aTOKKhxV2O0ss6YEQ69T1mFEjUgGWMkhAh9uzMYgZlFENBYBNGVUIQKNEUKCeBitFJVBVTMTICIgqQoDKKgC85d1XIcxSRWFCZQOaTYkQsR8SJdBCrI6uVvO6123yyk4Y7qnj31Rzc_Od5fPlRMRaGbO2XtLhIQkIaIiqpKxqKyZAQANAQAhSGQABbJgQAGJSJDRurBZF4UL-yHnbA24qkghAaD1M0PG17Uou7Kw7dzWc57GGELcbZx3oR9ySpwSpCgxKItkttYhK3DmmOCAJSUkZxAppYho1KCKoCoebvyAIl_Sp4FAFRXUFl44Z46giIiqYK3xZRH6AY0T1aqdpRRt6UKYDBIaEBU0pl0clWUFCN1m5wq_X9_aogCFqp0x52mKIjmHKcV0du_e5bNnLJKFQTJZO-y2QARgYpxUuD1ahb6TOClrihM5CwD3Xn2dyA77vQNwRRFjEJGymSkYKty0783hgBM67_thuvPgNd8069v96d2L0zsX1y9efPqT91N_G4deRV9682vX188CQHu0eP2tN1FQwXz23o_W1-tpt9cUjlazsB9CnHY322axQEy3V5enZxcnR3f_4L_9w_li_ou_-qso9MmjT37vd_7gGz__s-vL65def_mDH37v8skzjMEanTa7h1999fnHjzBmZd7d3KCrimrmimIaxnGYQHS2OJ6vFsP-9sXnnyFHtDB2vYpwTgQIBgE1x0zGHDLNBlavRURrDSIww-zsIoUAQtYQs2ROrqz8cmYJfTPjmGxpHVEM-2m3l6Sr1SvjcJNSrucrQzIOXRgmyXHc3GrM_Xa9W6_73brf7axxxlpVbo6OIcn87ptVKTwN_YvbfnvjSthvrvebXew2tjSgsru9UcBuuz85v-i7_cm9h650hkpHNg45TbmZH93e7sZpLJv2ydPnMXHOcbfdNctFfdTkkKbNDlBzZlBBFuVEihYkDd3-ZsuASPb4wasGAVg4syFzdLoIfb9b709OjowrU1Zj3JiCJffamw_Ozk--ePbo4vTe8vhkHEZfVr5oWKA9nntvu5sNj_0wDnkaTl5-Pex7X7dkqZw36WadOZVNFa9HBoz96JqZLwtOImp85UGUpyQxV3WlOWRO--dPXOlSHwxRO69TtxcQQ6Zo2xB6Q6Y5OzuUcEiKKbItK81ctXNlMcBoTNh3qJpiJGsVKYbgippTFIV6cYy2QGOBQUCEhUVRBURiHBCyGrJVURwvvS3bo2NgUCXvqHBF4KxTCFPHcdpfXWlKKQWexu759fryi6JqRW3c75y3ZFBtwVna5VFVNteXN1k5ddNutw7DsLp7VtbVIZ9kRPvtzdiPOXJx1ErWOAYDSIXLIRIhHYyowq4orS9BJE6BiBTJOl-1bQwTqVhf5JzJUVFWkrKoGsK6macwxiEiufm9k6JuwzChJV_W5Eg4ky36rl-9el-BtutbAudqN3Q9FR4EhMX70hDGmKz34xTO337t9vMnTV2zRDVEzvl53a7OyDtlJ6KubFOIMcYYJuO8dV5US19wjtZV9fExkMkjGwDNOcWcw-iMA2c5RknZGMqirIpccwhp6GMYZyensesQIjhSQXR-6oMvvTGWVVG4cIanCRWtNWCwWay6241Bk1OSmARRYiZvyRpEAERUIEPG2jRGEo0xTl3nioJZXNUoChClOHI-1NWpMVZSEOYs2TUFkY0xcIwZJKcd2YLHyAASo3ImMMCKwpBZUs4xpRRBBBHyFJAop2yryjjHor6pqnbOKWbOwmqLMoaJvMtTCCmnmKZxNFXZHB_tnj81ZPMUOSuLVvN5Ctk6QjJhjEXTAiIayhmcL9o752Vbk3ESoygX1i4XSyxos94pu9l8_vrXvpLHviyrMU4x9LLvbtebyxe3r73y8isvv1yumh-_98F3_-D726eXaRe67SCsvvAnJytRtN4r2G13Ux9V1fHs0fd_mIYcw3R6fjb1_eVPPyJLoU_dPv3yP_y17Xj13p_-pLu6HXsRMUen82Rk3HUlNVOIhTfjGJ06V1kMMKuKFEdLBiHPFlWKvL3aOOSmdDKlEHkkM7-3-tt_95f_9t94x6j8D_8Hv_WN116hJGOCjz99Uh0t93H84-9_7_lnz374ow9nbcXM__h_-su_-__-k11In37nQ4BsfW1rc3R-xvsRvQs57FI4Pjs9fXD30_d-qorTEDHH_nrfFk2llodQN62KIiCLINL9-xf_y__VP0yXm598_-MQ-OQrZ35Oj370aej6ql5ud-m3_9Hf--Ef_rGn-uXX791__cF3_vBPuv2eDMyPl08-eTQ7XhHx5sUlWiyP5912F1OSnKXvvTMco7WOcybvBRVyREIgVMnKjCJggAARSEQIFEVVWBXJEqgCKVqScRIRNOYQpjyUiaGKShIAMMhgVMTNWgUxZWUXCyRFAWWWIaRu5G4n-55EeBwBQJWKszNIk0ThJJqFFBRRc4ZdR1OwqAYiAiMiIYkCOWvPKwrMUzJ08E8rIoIhAVTVanlsCotGOTJZq6LkiHNGtIYcJ7YGTOXRExEaZ1G_LGRFAFEla4FMHqOxBEgiQsuZaeZJZOz7NE4cE6VsIEFimZKxhrwj78BZGCYEQgBb-hSTKhIcyq0yqErKCoeyeRQWNIQCxgAaoyqgIomNcwAKgM4Y0AySlaMigjF5Gi2icR6YFSFP0RZeEruq0ZTVWgkRizKNsX7pQq3FeTlcb9xLJ6YsEwCUno2ic2BsznHqxxQDNoQG8zBIN0rXQ1JNGZBVKA8DGQMosN5QVAUw1iuLVRGJkBEIgBAm1iQACIoSoiAqkIqCETQEIqBALIdQE0wBAUAVEhOpioAKiAAf7JCCRIRokFCFUEGyHkQmABFBY0GZmdEYACzaBRV2ffuiqMthvc5DD-hM4XbPPhNmzVElITMd1l4xkYIq46HtFgRR-XDPNhY4H2ZdRWQQyEzeaYx5HFM_AIIlQwZTCHlI6Ivl2d2DiwjyNPRdSrK4eMCGfF3xsA37vRH2dQWgxiCkIMME1tiqQhCSfLBsSc7GOVBBIkVzeCmDHjiiBzc_KKiSQUQiIuuREAmQQFIiNIiGUE1ZgLAIkHXWOyLDzDmlsqp9VXNKcQy2sEiGBeum8t5P03S0Ol3MF32_n82WzvnZ4mTod877MHYppJM791KKrij6bhe7HgxNXWdc2cxm1WKhIjkkVHGuDFPHkgGkrNuYpF0cbdbraRwNKRoiovZ45ctmmqax21vr4jgZWyiZacovv_nOvuvKdvHs8dOT85Wrqu3N5frF1dmdi5yzb-Zd39_ebBdHq9e__rZGZcx_-i__NYTorPbrdRzHsvQcM4iknEIK68vtxWuv33nl9R_85Q_uv3Lv-PT8w5_8-Onl8_ff--mrb7_yF3_8Z97797_3vf31bZp6BMzKHHkMY9jsNWdfVYJFOVuMXVc2x313W9T10erMVWaM0_MPPp36HQjnKeUQWZgOkGBANIYVjHVl1WgWc_atXynadnly1m9upymypKKZrV69H6decl5enLOAKSsqK8lx2u5SPyEYiYGQcxq63XNHRsmEfi-M7dFKcxj2W1WuZ3NnTAoDcvbeCej2xQvTFmnsu7HP_e32ei2Jy8Yo6LDbgTIpk2rq-uH2WsO4fv7clbbfbufHR9vNTTNbeE9Hd84X8yPryno-81W5W2-H3a6alXXlCguivLtZA0C7PD199U1bljkmJKpmDZBlpRij855VwNDZxX2eurKuWCETlotmijkmyZw3283Tx08FJITx_OIM0KC4uq7INK-9dHdKuWpqETg-Pd6Mg2Qw1lnvrHdAmEQkxfZ4pRzJeQAkV6WEPKViVjdHDRmTIgNDfXKsoKbwHDMaU88XnGMOSXNyiEPX18tme7lOaUIyYQiiOQ2bwlcppZyC85UiCytzwiyiLClqjJwyJJY44CHgpRz6HpBUcj1b7J9dA6kS-qL1da2IAghk4NBEc8ilppGHXvouSx7Hvlodl86CLalqq_YoSyRjOaWyaYQxs9iyBEO-bcduVzSFMAO6YbcL08gphH7o-66syjSNItkjzo5WcRzjMB5fXOw220NPTd027bJpl8eokFJizr6qFAmckcxICCoHgQ-Ntc5V9dwVPoxjnCbrLKAZui4mNs4578umMcYDgnE-5-SrAhGnzSApIyEZQ9af3n0NhLOqc77fj66q0DhAnMZkCh9DKtvWNRUSTf0w9UNZVSg6Xl8blv3NLSqgAQFJkacpzI7OytkyCxPhGFiBqroIQ4rDCCJp18UwgaGh6-v5cdvOfVV3m70vXWJGTTkn663zJsWJXJFj8N6evPTAlT6Ajpt9XVdxGqZ-AoTyaG7IKIIIgiVm4TEpiOQpjr0rCkSy1hBZY12MUQ0KZ2NJFUQUnEXRFEVFjXMICCq28KAsnClHcIZTIoGDExgUyqoBEGtNipxTVs5EDlTIGElgvVUDSlj4QgEA-fDKlCzGGQI4RLGJ8EtEFRnrHIOScUVdkzGShXMy1qWsAlgtjsj7atlWdWMLyzn3l8_LwhlrU045S7NaGgJTeCUAZ6q2tc407ays63q-mC1XiWNb1xcXZ6f3L_rNzhgFMtNuPDk_efDwbln6MAVhqaompfT0i0eb2_XFyekv_PovEdH3_-y77_7w_dvH1yBKQqdnJ8cv33nwzsvdTdft49GqXr4xU839dach7F_cfJkvF2COUz-u7l289tXXhiEcr5afv__JZ9_7kMcA6F75pdfaVXn75BJGhqiakmGIU9ZJ3_7Hv54eXRZkby7Xs_PF6t5pWHfemdN7Z0Tm5Gx1M-U798__1t_6pV_92dd-7etvzUFItHLu84-_eOeN13aRxhL--R9994vPXvzz3_3jf_A__ns_-Tc_IdJPH1126-mlty_-k__DP8NKq1lZleW9b_9mO3G-vEyhny-a3Tii9eCgfVBfvf_UWerD3oLWTRmGsS5LEURbcOHefPmlN1599ezh0TuvPAxdenG5cfPZq2-_9sM_f-_Z-0-PVi1hXRf-3_vf_NMf_d6_buvqW3_z629_4-3_-j_9b-J-ODqZmdLfPrtSZl8VV48eEUuKedjtfUUyZen3Rek0ZqQDcYRFxBijIQqrqgIc7tzKIX-Z_D0sHkM-kHxBARXsgVhlSBXIEH6JJlRR1cwA5JuF8YVpKusdpwCSUpjiemsKhwqco_Sjxkgg1lnlbIhzyFRUFINMEYGwsDoGQiRnMGccRyvJqgBgjglURUmSOOtNBAIRFs1MhRcEtCiqklJ5dAqIyhL2PQmQI1BQYUJrSqcsnB-BtqioMXNMMgUFMQYFAa21dQmIIgCajTUs4ppZdbQMg6Q0FUWBIVhST0IAHJMllZzlUPlrUWMGQ8xfEvdNYTSlHDKyAimzGmtt4YUTpGS9Q2ckJbCUUzTOo7GqGUBJ0TjPHAHkYMpCEQMHSn0GVCAEUGMNKTAwijGzyhaVKYtivgDvVDT0kwoAWVOjCPI4oSFVRYc8TpgZQsQx5BAhZ0IlIiA1hjQrFUZT1nG0MeIUnLeYMuRsVEBEkdAYI7kg4iTACATgzMGNQgYBBf7Kx49EKAJxAAE0QICAopwOK3-yHlSNMYcENxESIKiQIREBEbTO6CGffUh5s-qBq0DV0ck05e76OnS73PUE4L0HUY4DCMs0EaFB4JgPvi5BPcA7AFVSPMwBICAioAgiCgqCoAKAqEqApIgqiJhDTDEAwOmDV5rjo5TytNnnfUfON6vjanWyvr3M_QScxpsNxmSN5mkERAnBCNiqJGdJxBclh6AomgWM1RwBVBQPR83WHhmLk5n0QUAgKQIokgoAoSEAUWEGQFRAQFVWPczAmQwJi2apT44lRFEzXyzTFGKI3jkk462fHZ-kGLbr9XxxZIzLMSrA-uambOovPv6IU95vNoUvi3omnIqqur2-gszNYkGgrqrQHD6DkMNknA3jCKDMwjkfn98nZ1VhCikO-6Isp27POSn5xdk5EE77fVEWhgwZU80W--324uVX-_3-7N6DMI3L1Yn3tt-laRqsp5tnV75qXFUVdXnn5ZdP790rnPvso48ff_xIOe4vr8OwG3e7sva5D9V8NXWbovDoi_ro9I2vf-0Hf_mje_fPzy_uf_zuuwDw9NMnx2crjrnwNO3W_fUVABtCJLO-3hRVoTECB-sc2JqKsj09Uclj6Kwrm3qhNscYNs8uJUwapsIXOSaQKPEpQSnMmfmwSgAwFsGQGlg88G0duu18tXRVGaY4dgmNGTZ9szoed7th36fdNu27Q-jKWrKEKQykULWzPAw5sfOlCjMzgPq6rtpZDn0aJl95a6wvalOX9XJVLVboq2ma2tXd2N86X7jKkbGcohHQzIoowofCC-bsnT8-XW0vr1IcQTmFMKWoYkQ55CCIi-PjpmnapimMuXz-bL_bzVcXpfPjFHbbXYxjjmF1_66vKlu4YUxlVZMrWBQJQGF3fVVWVQSwVRNAxyEiCIuEbiABTdxv9-t1z6xjnpbL2RSysRg0zZq6LIvV6app6wevPGzbJRa2tNUUYtnMOQGLknGWjIJRcUev3C-qGpHUoDEF2lKQyHlVGochTqqQfV2KEovMTs5z4no5z0pThqOHLw2ba82pqLyOHaFIGBAQBGKcyBe2rF3dap6U2aBqDogKIL5pOUcC5SkCiUWZ-i7L5BoLnDgEEWHNZD26wnhbNMuYsiF7qKUXYVVBFQlBxz6M27Hb59QLs3XWHy_dfMHZeFudv_omWmiOjkMXFEwYBtc2ZEgEDir1_VdfRe-uXzxLIXCCaRhCmqqqrtoqc2pmC0tESISGh3j1yedAOD8_k8j1ySqlkPoOiyalbMuSCMkSx6QpW0_K2RQuTZMrG1PW6HxR-Gm3rdp5CBFVckzCGVQ5CafMMSgAKp2dvxHCZgq7ejYPMSyPV3VdK4IvK18Uqwd3U0icsiEYd10KuT5del9Ya47v3hk3-6Ozc-U49V3V1HmayrKQlFKI1hlblda3s5fObFl2Lzb3fu6tcNsbR-WsyiGApKqdTet1YnZNOzu_q4S5j6LZIHEKsevb5dIYcNbmvkt5tM2cVUzOyNFXpS_c2I0pRLTW1YtiMc-qgFYNaE5kDAqGcYhj74tyGseU2c0qIHL1LMcAikB0qLg_9FwCCKCidZrzATmIIhxZUyYw1roDp1lTQCQgctYDsGpGMGCstY0pjHUOGVFRUhYVSSJwCM6JHvYOriBE1QO9zhVNKzlxTIAgwmkY0JqskkL2zayZL9FaydIs5qHrZIp5HIvCcJIxpKKere6ezy9Otte71Z2TxfGqaGfjNCgIWOeqyhW-G_txCkVRiOCzx8_SNE1TKqvq4ctvTGE4OT8pUZ48e1ow_-AH3__4xx-UTXX3wVfeePNrP_3hX_7k--_mNBoCJHAFMsKYgYxfP76srNFGx324-vT26vFlU9rQ7zglJG89WYdovCjNTk7HfthuNgQcun6_3tm6aE9Xuye32y9uhhebpq5QoNvurHcs2RUFX16VrXHoEMl68kkrAw8fPjyZn_z6L33rl9958_X7dy6Ol7fr2-ebVFNxtDq7fHx1ue5-8zd-8fLZ5dUQ_qv_8vcL68BS09rv_dH7trBq_MWDez_361__T__j_7qc1_ffuNtv9zFOV-__aNhc7nZ7IAp96rZdWxdqcP_BC85ceL9sW0pikwiaTR-Ktvobf_3bv_XO1wzT5X6z_fSLv_Pbv_T446d_8t2Pf-2_8-2njz558tGT2jdNO__tf_s3Xnrl4gf_6s80whDl1_-tv_Ef_Qf_97HbL47mSeXy0XPraH7U3Hz2hbPGkHNF6zwWpeddf8AWMzMCMYItvHMmdj0JkjfCiZAOaGECRAYEMYY0ClmLBkEUVY0lySICiEaFDSoSaGYk68uabOnaGUDSMKX9jvvBkKHMnBLkhMJYWFt4GWLhPYrEKSgLWO-Pj8Aokei-Q-8kBmQ2VYmFgXHS3Z704BG3wqxgVNC3zUFVzzEdRhFAUEBUsGVrqsbAwb83SgzWfJlWtYYIUWMGzkhHJErGICkgqZKxTgCAjLAclnk5JeNcCtHMWmCksowxKSqwECeZBkjCKasAkDFkDwvmsJ-Y2bSl9zXnSI6YBVIi1QOxEYuSZnMeBgMG0QgIOCLjyFtjPYCBL1mZjAckjQpzJlAU1hRQ1SCpChojnA1assQhgyP0pjo6m1LKgqapwGrse81s64Jj4iycEgrqlCAlAIYQIIgh0JwgZWVWVhC11mURAICUEBARrTMOHOeICoAKZJSwaGcwBZWcxpHwgI5kOFyjk-JhaGGBnIEQRAAFAFXUkEEWUAAFBDJIh2JmFFFCZVAQUIBDSFtVATHzweJiCDkxEFlviYgTtMcrRFVOeb_BnIhIJKduj6DKQo4OnFswAAqoSopkvUhGUGNLVCU0nBnRoAoAKAMRIFlEABBNGQgNmRyTKdxseTRGrtp5s1xefvEEMHPKvp0j0rjbNUXVNOV0e6shGgPAAoDGeuCEigJAqspZOCKhqlrnERGNNcbYopEwCgCAAQZUzSFZZxENEAEBAKgyfpkaViRCBESiL-00AHJIj1lmjiEdjEX1rO73nXUEIr4oU4zL4xNWHYaxrRfXl89TzgbdbHncbW-MpcMvK9pi7Pbee_IGBaq2KavKFQVaJyrW2qnbAwIaqpoWEGfLI0QIQyeKSIYIDYASckrlbDY_PUs53j59RobC0Bvr0NpxGld37jazxauvvbHbrX3Zbjbr49VxNV98_sFPY5ja5fLo7OJ2c1M2s1lztFgsL598cvnkqaQJQIiTZkm7TNYvjo7SOGVhU9RHd-7dvXd_fXM1a9p7dx989tGH-36vAIujo7Ksdrc3YbfZPn9WVKVBCNNkLFWzxXi7zTGQoaKZFYu5qctpv91e3s5PV6fn94zh9YsXN4-fGcgQI1lI06Q56yS2vbBFIaoqWNbzNHTAklIEBGOP7m4un1rAaRyYsT0-4zgtzk6WqxUAOW-EkwjUq6NmPjeFA-UDRAlAOXPVNtM0pb4_KIghBDUmdN3q_usqgTODSNm03X4z7UdAsMZWs1l3ezk7OePQK-fKF7O7DyFPcgh0FdaWJZIDX4Biv9660sV-kJzSNEy72-7mMvSDiIxDUCBXFMb5JDxrZt1u2ty8KMpq6vfkCIHTEKvSn9w51gD33_7KsO1E-ejiXuGddbYq28g5IWRy5WJ5fHbSrhbtcj6_OJ774u2vv3n_lYs4hd12_fGj5ymk-bJpykIUEaFuCkNYt5Ulcr5o2vbi_n0ge-fizj6EnAUI0bhmPm-WyzDm8wcPytl8HBM6Z31JxrqqGadgq7KYV76upv3oap85xTi153fTFOcXFzGOBNA-eBA3GwJ1RNbZnLJksc5lVU58oL0eIjZkjTGoIhwjICH58ujMQI7TCDkaA7kfILOEqJIkTjnFoinIHoC7Us2OjHFy6Jy0NmdFQwrAKSAiSCbhNI7Tfo-omvPseAWYVYJxdhyGFPLseGUKP1tdWCNTSGEafVkN-9HVlbcOVI5Pz_p-vzg5iXFCAznG0hYvvfoz_bTebMP85Khelv1uz_1IhHGYTFH4si3qtj0-TnEYuwkRiropnOu7TjJzSsysICLSzI5zHou6Zc7t4sgatzi7KzmCsVlYQYtZSypqKIQNa57GMHZjOT8eu7FanhprQFENjtnkiU_uveTLSnKu5-2465hVQGI_oTFTt3PVTFMa-2nc9jlFBETAqR9cOWtms7jv85Sq2dy5MoUQUwQxs5cexN06hVRUBeeIZECkmq9MVZBz0zCRNd670HccpzRM1pMhnMYwO105a0PfpSnnGPBg4PHOFQVzNq407VxU88gHd7AxJCnBAQ8OpCLAFkWAgLwDQHIOCQ9nGZDo0CeqQoBoLR6uIYhkDR-6lpAQDlwPdd4DM6eooEjAPIExZLybzYhsGJMrC1Egb9USGQSDwGKc5ZyMta6u_ooXqGAcM6OxQMY3y3Z50ixX3pfkbB7GonahH6b9TpWJc2Ipm2Z2cW6MzYGXxwsDOIwTgQHmoqrJWSKKOW3XXZiCtYaAri6vQHJZ1J7g_PxitjoZhu3jR59Pmfv15rPnz9556523_to7Z68_7La3f_yv_ij2_TSMpvZkaBoGnnjab8uj2hpGYmXgAIYw9t28LWNMMUk9a4tZ061vhjGDsa98_a2iKS8ffcqZbd1cPr2szxfN6bLf99NuC8pHd86uX1yCapbUTcEVzpclKv_iL__y8by8c7x48817v_z2G7_w83_teHlUGqKyseT7GP-zH32nEvqF1x_-wjuv1KWrm-Z0ufjw88d3X37p-ub2-eX1iy-u__3_7b_7u__ZHwCwGJmfrHoZ3v3zn14-X7_1zdevb14Iw3a_H6dRMiqIta5PUQot60JOF-P1lROCKVSmCF1c1NXf_ju_-XNfe-tbb31lP8Q_-u6fb4b48KWTf-cf_P2PPv2Mmf_7_-S3Pv7xx9___k93L26__as_-7N_89U__C--8_H7XyiY5mj58hsvvfv990K3d57Gvn_x-PLofKaY9leX027XzOdFW07d3lkb-72GYB31_UCFIeNU0ZZWUmZWJIQsKnrYtiooKUrOQKI5ARlUEE6AyJJQCQCsL5gTGVAWMt66spjPVCLHKGGCzJKSqkLOKqpZrHEoCmGSxLnrOUWdxsPD1Fa1q0tiUUEeM7oCRXiKWBUoFsYA02iQwKgoCAKTKkDR1ECEoBxZYzbec04gUJ-eOFeLojEeNIVuz-NkiEAxDuOhP0oVOQY0xCHaugLlmBIQ2bJEZ1xVmspZMmQMxGxLxzGT9aCE3mUVjokAkaPEYMgAUc4ZjKohdJaMySpUF1SW1bzMY1BFBZCUMTORsCIaT0rEyXjLYYKcgAiAirJIkVEBDQIKEQqLqAKoqhx2aiQCh_yAOXDz1RrDSciaAwSGyga8Q1-JkMQpdZ3GaIQVjChLjFh4DQkZII6YFVIGFREgbxTAOmMIeAxkCAAOtlV1hIhGVJOIMhCJKKlKEsQMknNiMJZErGqOGRKDsG0rjfzltR6EAAFBWZCTcRY4GYJDmRkAIOGX5igFNKTKAAQGJDOkTBZQvhwJFEmVyTgiylMCa-vjUwI7jWNY32KOpKIgRMYRoPOcE6JIZDQIApDZqJAqSEIEMgQi_FecTdFrwPJLrj4oIh3oTwhorBNQVDVVzRnB-PlyNXZbIlXRarGUnFEU0hRjyDHLNFlnckhw6K3TrJLJWtuUHILwQRgRtO5wTA5CRw7jAdaHCPRl_tsIAKoSqaiSNYRwCEiIioASECEgomYBAGNtTiwIRV37wiNZ58swjSCSY2KGzEzGhmlcnJ4ba0QyoSFyZVVVTbtZb0Th6Ox0v92FYSyqZrlajftdt9302207XzhXWO_6fRfGPnX7GNh4Z21RNYt-uwHCdnZknTu_f1847dbrOI62qV1Rc0qz9qjfrI_OTpmhritfz1NKx6cXYB2K7Ya-qpuqqhaLxeOPPzaIoPLG137u9vqxZD4-Pg_d_smnn1w-fqopeF9Ya0GRwJ-_-oDIpDimmNCXR_fu3n354TTFFMLJ8cm73_teiuPpxYWoFN6N3TZubnkcDXA5q8duhwjN7OT862_11y-ct4imXa4YMIfJ-Xpxen5y53wc-5vHT6dhgByRYw4hZ6HCEQE6A5BVAQ0aa4b1mkBcU4motcY0dx4I56r0ZIVZcgjGonUVOdqtb8IQVy89JO_7bhv2uxQmHidfVRyTshC52A_18qgonAC4uiybmsOYphj2t2gtGuKkYdz7oprGIY1jtai9L9BZiQENaQoxhbC54ZxsW8wv7oduEsAU2VjHIUnKBIKIhMLTCCEYQFea2bImEGUZxjGJGOuXR4uL84eSxSAsVsc5ZO_86dnp808f73fdsOt3N-uck_PuyYcfuKLZr2_JoUpUifsnT0hYcrYsEtPti-tH73_y4vHTTz76fL_bAaj3qFmHqd8N_efPnq_XW0Zqm_b59bqua0Zxvry52S5Wx4h2vlwsVxcKND9a5ZxvbjcPHr6aFepZUzaNtUXXDe2sNc5aVxBa53wM7Oc1Itu6STFZIrTQb24NwdB3ed8Z53RMzhvJcvD_Sc5oyZctx1GF69m8Ol2kMUxDIEJDjlMk0Bwm31RGDScm51CAkCUkcsZY0sxpGiEFQhCOOQxU-cTZlHW7Oqpnp0kyCR5eUcKChEbEeSJOaRhCPxyf3QHNUxhnJydFVQvmYbvd3d6s7tybrVbIhMarcr_fbW5vi6JsV8ux29_eXHLkm-fP6vnSOJMwWe995R985XWepq7rrcWi8mkMSOidTSGIajVfuKKUmIwxzAqgSkqGJOe6XUiKeRqR3PzO6dWjZ1XjTVG8-OxRMaub5QLRC0uckrHm6OgohGCsyfnQ6Kec07C5GbZbQwQK1kDT2vX1FaecUwZRW1g4eBK8Nc4lyZpZlKp52yznwJIjL1bLwpZ9N149vblz9-zkeBVzrMpKABQghomHgRAzS56id36xWIawV1VEI2DbxdLMC2BApAN9WTgX86M47Yerm2kMy4t7OoU0Tmi0qptpuyFm1VRUtaTgfNGsjhDQABWNj1NQAOEIOQhnIqPIrqpEFeEg1zGRZWFURmNRFVWZBf9KVgY4wDNRRZGAyICyQYAc4a9WmmiNgnBMpJCnEQHL-QyM8UWVYiyLSkQwZ0XMKZBxVFaiSL4EAEEq2-Xi_MI3tS_aejFjScNuJ5imodMcpzhq5pwjWlLBanE0W51JnozBnNP2drvdbHLO25urGKb97fX-dp3GIQ2DQy08jX0Xhs4anPvq1be_cu-Nl7Lk7_zhH4Zhu7vd5JB__td-bT5rP_v0o08__OCD77-7vbo0BES2WjacZNznajHzR8X84pSmMK3XaTslZNHA3WCIctKsujg-E87TMJXN_PjeS3VZ5Wnst7fDze3t80tfl4aoWTab5-uw6_b7sWjqsR-Lsi7acnZ2UtWzr_3cOxd3j9bPrjfXN0bpt__OL-kgs6MFovvLDz7SJJ88-eJ3_s33CqTf-Nq33rxz2h7N1_vp8aePf_j-p48--eLk4uy9n370r_7Fd1PEv_Fb3_6d__Jf9P3U49icLj764DOm3FQFT9P68vbxZ49ta7NQVvazCjMUTWOW_uKtl4dnN76bPNval_2Of_lXfv4Xfv6vvfLqvasvnn_--NkrD09_-NNPP_z0-f_-f_E_enj39MkXj7_z5z_8uV_5-f_8__W7f_KdH1XzxenDB_ux--f_7A-Lsow82aLebLeQ4aP3P0Qyt9u9KcxiVof1ZrzaCnNp67s_89azn35ijCIyD1OKEQsnqISWyOYUIDFPAZiR1ZZORb-cSg9WbAAkiwCkCtaSJRUhdARI1uQUVUQZq-NVNZuLxtDv8zCCCKogABgLRGoMEblZLWHSxFRUpiwJTbU6EpXUdabwgETWgAqkrIrCCRAQjF3W0geiDEHtrD2sd9EZINKsgEZVFFhDQgBjUFWMr4gcAAoLIOe-kxAN6iHKbywSiEjO00jWAqKtPDmjAGgtWgJCEI3jlKfIOR_ugMxqrMG6PLCAcswESgiU1ddLJYlDUCDjHCKZpuCQBIwtSwVFBY5CtcfG4ZgQQBixraiyh6AEqPAQ0SggobPCkmMWAePQlJZzzplV1bgKgFEFFZAVDxsyVCQCBmOMIQQVJEulU-NUjJJSCJgmyoFyIkCqrXJWQogTaCYRU5QaRgyMCEDAkQkRLAgAONKJDSiHiIy2dDIlZ-BgyklTsm0pANZRGgOWpRDDGPHgnUGElIlAUyBrJSXihECoKpnxEDfhDHKQa1BEiQykpCKAiETCDABU2C9d8KDICigIVhUR6SAaICEi2XpmTSEscb-hNBJKDtEWBXwZL07OoDEWORtDmlmFUURR0TlNSiKgwsKgYqxBaBFJhRWYAESEAIkOaRQEIJBi8cbLHGLZ1tPQpTBRUUy73oJOmxtOExlChBwm4UwAgkiGNIkKg3PGF0Vb5SkVi9kBxMkpGzqkIhhEwBiyRhU5TEoEAlAUB7ePAUJjVQ1JJrKARGRB0Rin-mWVBSigtQJUNjNVGfvgihJIJKsKVPOFdUVRlygSM9fzpaii83VRXjx4yYIOQw_CKloVRU5peXYWuu7JJ5957-p2Zsoi5ohEHJIpbB6msp2jc_Pj0257m8MEatBQUVZNOyPE9dW1NdY63xyvDJrCUbfZGGuLuizbeUyprBrjyrv3HwLIzfYGAc_Oz8qqvL68nPqhrup61sY0AiCR__i9nyyW82nsQBKznr18_-zhyzcvbr_-G7_w7MMPp27EglxZ-fmsXR1dvni-XW-2683V06er1fHFg_ufP3pkTTHtd-N6rXFEzd6XQ7dFJOeb81dfXT_-Io2Tsa6om-N7rz1_9BEYWzRLW9r18ye766s09NYpxJEli5CvSskx9UFE_aIGQuXMITuH1psMEIZUVJWh9gzBpH7gKaY-QWIOU7_r9utbi5IEWYXQON8UjiDnmLMo27pCNPXqyBoch06yFtVMQHfXN3XTKkfhJFmqxcxXbhwiGHPnpTeqkkSgKmpfzUVynCZRBNWitpIxhcxhAm9ZsDla-FlpDNYXq9T3QCpZEMA3rStc2I_Tbp-GMe37EAZO0ZG5uHu3G3elry5eut_13eL4ztWLy3qxcIUviqrf7XKcDhKfrSqZBmup26x5CrGbjHXGaL_Zbq5uut1ueXIyW7SQ4vx44aoKjA05qzBZ7Xc9oVZlsd9v1ze3NzebYQi7_dj3_WxWTd1QurKoCl9W7XLWzurF0ZlKvLy5KWxNaHxhfVU1TXu8OHJ1PZu1Z_cvAGzVzMrZrO8zWpdZOQTOgNYZQ66qOOV6dixpkswIhz5ZAkUA4jggGWRJ04SCzpcHlc0Yg0TOO2WZhtSsFgrAIqauQNWVdZyCsYYzowJnydMEnJXz1Hem9Jyz9y6G0RrTHK9cVSpgzjmNUY3lxKqHQDmM2y2ntL663F9fK2DbHhnr20W7vdncXu9f_8Y30hjJ27MHd66evkBD1pD3hWImyKbwiXl2dMwswzCoyLjZKRA6P41BVZ3FA_ObrLVFsVtvZ0erpp11u51z3pVlmqKIIpKkaK1F1jAFzPzwG2-_-PBzMrQ4Xe2ub6eJy7ZqT45jzq4q92M6v_O6q1oyLkS23pVNY50n1DSOxtqhG5v5qihbsuRqP3ZjVdfTGJnBFIV1xUHndU1FzuQYnJ95B_3t7ThOpbNn56e7zS7mlGK0xi3PLoSTiLq2ahbLGKJxtj2abZ49F4aw36kmBeAcimqeY66OjtIwgE6skMJogJq6StMQx9CsFnU7G8eQY0Tnc0pp2g9DdM5wzrvdfrVatifnu6vbsircrJQoxWKuOaNTFQaBol4hqbEeiEBAyR58aQIKZMgag6icgUWUbFkBKh-av5DwMHYakqwHXioAoi2AGUU0TSISw1Q2rSt9PT8mY33ZuGLmy7ktmtnRaVXPyvnC-cLZwpel8WZ7c8shknC_vp622zwNoJTjCMIaJxF1hbftDMn4olg_f56mPI1xNj9Nw3bYbIETpIQ5GVJrIIeAinEMouBd9frbb917cP_FF49vPn_8-IMPHn32xBqvosezdrfffvCD718-fjwME4hYsAhICDlyiNk54woqZ1Xeh_Fqq2Mqq4LZ8JQgs_cm55RVjRCCsLKSOX_rNQSedsPm8nJYb7v9ePfhAyBIQ1p_cYOq7dHczMpqXtm6OL530qyOnn_--bx2T9__4PLxU0169_z47__d326L4tHjF3a--uzxo6psnt9enrSz3_zVbx8vWuAYIu7W3bbvf_9ff_eL51ff_Pbb73z1zn_4f_v_xSH-r__P__Sf_T9-b7feROExiJ97X1egwNtuuulARkUexlAcVZSxcMXq7FhiJlFc7_qrNTGcr5avP3jpq994oyno4w8_-eCTz3KWl7_6FpIb9rf_s3__H__Rv_qjfrfdv9h99Vtf-z_9H_8vUM03ff_yN79--ezx9mZrrbl6djmbza8vb7phyGEK04Aq87MFT2PhzLQfrUFgnR-vKARq3bjfh21PqGgpxVzM5jmzIBsyykwq1jklEMmEFokUARIjApEREciMziCAsBAZAkgxIpGxhWvbcr4kA91mk_tJv8y-6KGOWr4ElahG0Rw1ZxU1RZNz0CmZg5UIQMEop9gHSaLMkBlBBC2Qt61Lm95aX87K2PdOVQ0REVnDGbwzqJS2vTV4oOUbV1TLE7Jm3O5QUhxGi9jM6pwOfXnAqsJsnUfvrfegLFngr9wl8OWiXpBAkzhvlDMAIVJWRVVV1EO1KR1khMNAD7YsXFUAiYgigxKUTQkH63sSX3ooTLrckSgWDp01zkASzUqeZIqoisZwFrKWBQyh9ZZD4JBEGQVARPMEeqAdCYqQs6KC1qBFzGIKD6JIqIcUzvEpH2a3FAlUxkwFAQAfzCCHdkUgEBZUjNFUnmNCVAKVmJSVkioApUTMJELGGAKNrMYpKBVeHX0ZCAmiBNyNpqo1J2VWY0jQEfEwEhGCOtekNOGhPAUO8jAaJBFBIhAga5AAWBBUmcHMQCMCOjIiqnz4MobDjsRZRVIW6z0aC8b6emGMC9OkaUIQEHalT-OAB_0kRTQH3qoqiDIbIIMmM4MKgUUCUTXkAABztkRozUHmBWa0Fg7aGBkF45pZfXzKysO2n6YRFF1V5qnHnGO_dYY4hZQSp-zL0pcus7j5HEg1JbLAiU1dSjekKYhoDkk4I4AtnCqSc7YomMUQHTq2yTlCJO9ADwDTjASAqqLCgmSUFBBFGA0CkQCkxOhsszzOMZG1hMQHFJOvERSAJCYEyDn5uo1TCsxEVM_mV5fP-27gxL72opxivP_Gm-vr66GbTu5cKADnmJiZ8-3z55wS5FwUBQEaY2-fPy98aQyllI7PL8iYze16GkdAtM4u797tbm44RFANIXhXKiL5goDmq9XR0ekw7j_64CNG-s3f-E1XeIlBcjw6Wxmirhs2NzfL8zufvfeTu_dfGrs9KCSB_v_P0381S9tm933YCle4Q8ednvy8cfIMZsABMCBIMQkkRcoS5aJVlCiVbNkH8hdwlT-Kw5HLQZYsigoUKYpRBAmCBAkMBxgMZubNT3723t27w52u61pr-aBf6rSrD7pq7-pe91r__-93e3j6ta-UQ_f855_tb6-JQ2x8vV7X82U1a29fvYkxvvriRVOH5apGxDevN_P5qm7q_evnUibN2dRKGmNdC4ar9z9s5vHm82fOBQNaP3h08-yj5cXZ6sFjA526Lt3dUpE8DpimNPSI3C7WotmShLaOy5j7kQzVzESlFDF2PiyfPCYR5vOniAEA2JGvg-SECE0V1w_W0nc6TaXvgXTsjmG-ghibxb1uGKoYVTWNo4hV7Zw9y9TLODTzxdD3i_MH6wcP7q7fULapwPmjh-Ox63cbyT2BHu42xLQ8vzc_v3TOT8PkYoXEgH4c0thPzXpW8nR8ux36vnt7y1WMdVPNlyZlGvLJCM0IPjomnC_nMvSSxt1ms99tLh7c2w37Zr7e310vFrP95g2WqTt2TLherwFwf9gRmQtVnK2bto5V5WMgAiaKTazOajS5fvEy9cP5xftdf7Bi1aItaVItaZjm60V_7LvDXovNl-0333v3zc2b1HevX7zNmnMWAHn55qZuKgdGBCD58urB5f0HWhJ7RkQMnplvbzdtVZEjF8JiNY-xClWzWK_b5ezB03e7_VHV6rZBAh-qftc1zYwCuxhdXeUMgFgvzhyDaSEDHxwKsKec1U4ho7oh58Z-AIJYVYebW0TK44CIpzulr2o0bNcrLZmMTkZXIrRxwlS0HzEnkJTHSbUAuSlLPW-r9UWYNbkvZciIkIcp1rFuZ1Wz9E2dc57SdHbxwEyX5_cOh-NwPMa6WV2u3j57sb44r5tG0lTSWLercRyaZq65eMfeB2TO_VC1zer-PSQnAMjMDjWpCuQslgsAqGYkl5KQdxSCAhI4HyIbUmAXXJ6Kmh1vNqsH90tO43bjmyoP49R1agpFqhhDTePUFaf1ctnMZi54rtqxGw7bLsQQQkCErjvMLy_77hCqtlk0Oel8va5nzWy17vdH5x2HOPUdc9zc3sQ63nvy_tR3qjpNAyByIDQbj0MIlajUzTK0TR7TYXeoqiZPY-mmOvo8TiCSx3L_0eO-O8b1Mo8joOH52dDlaOagEDuVomqByIBE2EcPDk0BVZU8AcfaQxYdh7E7DtsbdlhEpJvCelbGMfcDEVVVVdJU9ncEpFqYoxHG-VIRqrpGomlM7J2qsa_QubhYihZ2vlotLRdCJCYkBkT0TOSIsKSkUzIDBGAfXRVN4FTgmYa-5CGNk3mUU9-OLXVd6nf93V2ZxnHoZBwgJ8gZJYNBSdPJ3AMK7frCr941O2r5Ejsy7HeeMI-d5fH49g04sFIQjcxEFZTSpPP1eawbQwbG2FZvnj178cln43Qg55wLFMIJyDDsD1jUpIBAFkNARiAXJE2OWNFJNjYo3Ygpm4ztarHf7eOsjVXI_cCMBt7hLM7quGiAoD1fbl68vn3-AiSBogFePrzq-_F4dySKy3vr8_fuac51rK3rZqHeP3vRXd_mfjy-2aDgr_zKd_7D_-Avv_vOE1fHH_7ko4uL1V_7r_6b3_uXfyiTvt3t_-gvfe-zF2-AuStyd7j7-__TP_jksy_WZ6tJ4CsPlv-3__vfePDOw7_4l3_tb_43f_ezz5_fbHf1RTMd-93rTdpMAWy63Y3H3hm6uGpC0yhXTJyku-uGbffBVz7YXW8c1n_2z__aL377q209_2f_-J92OX_7618bh_LV978yjNMf_sEfvv_0cawWf_j7P0Kx__Hv_MZmu3_47a9-8fz1O9_5-u_99m-7EPrjYX-zYRm7u_006de__4PDzRuksN9ul_PLbr8hwvEwzhbzr_7yd1I_uYqoACtZKZgyOacCWAqYMbGkVI4jVVHETE4wHyUkSAW_TKMVRiTvDQhETlnsMia_XCI7A2MfSj-UKWsRJmRGEDNQdghmUoqVwuigFDCx_khV46IjQ2KUPIHS_OGDMoyhqtHUMROjpOLqiiqPHvLNzhEDlXw4QMqSVYuBITFDVmqDDRlEUBSJEF21vpRSVCQdhhAjoZnZNCUOnjyLATL5pgIAdJT7gYjxSyyPghkhIZirHKgS0QmyTjEUKcxsgEQMCCDqmgrYp3HkyjEzOISTyvdLhxMaQOonIEJC50iPg4zjqRappeiY-fT6MOiYKTorytHZKXGuAqbeM3ouKaOhI4dSyNC0gAIymwgiAbKKmSixV4NSFB1BbISDaGaznBIU9XXN6FQNRNGZSXFEOIzMaJI0CwGDkR52GKNzNVsBEFQFE8jqGEE09VNcrPzl3HPsr-_MgfUjIVnODkEBLCcEBQEEQMlaig9B0gQEKGqareTT_wcxkOGpbqtmiMjkrMiXQCQAdIJARASi9q9rK3ACAiHiKSxkZmo5WzU_c1VNhFVTSxrZh7EbTQ2RCRzHCk4APi1a5KRgRyJV-RJAhKCiQAyieKLqfMmyAhEDlVPIHkLgehaXbWjmpmXsjvn6bvngqp7Xx5trTcnyCCAAYOiay0vfxPFuL0Bc1eRQx0GTcKgAuYph3B9dFYDZQNGUiSQl9KylqAiKqp6GdiBEVfN1JSJgp_sNgZmeIKAABqZF0XGczZARnTOgEOrUDxRiyRkYfahmZxenHoUj9t4hYi55fn45W67H_tCuVnfXb5HYEbaLdUpHNqyq9vrVcxUI0YXousMhp2He1qToo1fJjrwhTMejZ3SeREo9a0NskXB_d7dcn6exP_X1x-PBh2o4HFzVVnUFjCFUVd0-eufDs7PVOPYf__RnDx48-vD9Dw77u7cvXjz77Hkzb37-k5-9fvUyVN479_lHn3jC2XKx3-9TTnXVtov52f3zm1dvFvcu-64jNCQfF_Pt9e2pwjEdx3Y592TXr9-6dlE1bQz8-qOfMDGQlVyq2WJKeXZ2dfbk6XG72b56DUVKKb6KQ98BhtnZOTAMt9vu-oYBtCQ0BbXFw0fjoRcr465Hz2PXgyKSS8PEPohAnLexneUMobkoQ89nX_0lbmol6u72QBirql40h-vb8XaT-i54JpmGzSt2OO67OKsVbb5cicDi3jve4zRO4zgAIDsfqjiOfTVr43yRUmqqWZzNxmM3dsPZ_Qep24Lh2HV104z9fnfz1ryP9Wx99d5h181WZ-TCMIpvok45TSlEP5_P0QGaIbGhEYdQtz4EM0MOBiBqUxpSKvW8XZ-tNrevti9fzOfL49hRkdVy9eznL772ta_Vi_b5s8-m_ri8d-7Zp3EAy8ftLSOJltwPaUw5ixRNdwcZk0pmyYfdTYiBQiPTWD1-XAGPIvu3t6kbKPK474jc9c2umATierkcjwcmZLbowxefvyCyu82m76cmekNr2rZqmhB4sVpudxsiKmXKKX_28vXnL6-ZXKxCVVWhisTu_PLq7OL-mBIzpTGBD8NmFxf1lCGLnoBlOg0gGZlPM7oaWCkcK5DCjksq5IKZTYdBTckRgrroIGdmpzkDqSEYQKhqFwOyn7rBCDhGFY0xqAiYOtQp9SDCnpzziChJmuWqWTTOe195EBn6fb_b-hA9h3HM49C1s8XhsFtdXG5ur3Ua0jiM_ZimQUpqZ6uu2x0PO-fDdOjuP36PiG5fv9q-uZ4v2v3-SC644GJbYaxyzvPzC0KKbdvOmvN3Pnj1hz-hpg4hOl91h6OPMS7rWFXErDmLGIdoJbu2SeNUN3UasxQBUTACE1BIQ1IpJU2UJfdZoLTzBSrM16vV5SW5UC3a2DZoLKUQ8jSMojhbLsHo3qOnolMRHMaxWszbszNfB_bk2ZWS5mfrWFUuhDKOw1TG7rg6X7KnPE3TNI7DgOwWq6WLzgDHYZytlu29i77rplzG7iiqbMAow36wpHG98CCeeBqSKGIIpe-zKAUvpRiFqprNH93LXS8KMoqKIKhMXYghZyEAIjCRcd-faiE6FWbHjFZKyUlSLuOOiQmxiDgXY71ERPKhiBKxlEwqw6HXnBCJnA9VBeRM0RRyFgMD74AJkH2sAFAVqqbWnEvOaKK5AACSqRSZxtL1OvY6DWQAYJ695GySUUsRldO1d9HmsZOkYHlMd-yIQgjEWiRWNYiGGHRIvqrU2MDq-YwoxPmiXi-rdsZMBkjMUvLU92PflzTglxgYVuI0JJBkpSAzAGFg5xnZNGUiBe_LIVODQKomzgMrIfFwPCo7UyETZEPk-fnF_Mmlod4-fxbb-bg_Dts7FK18AATy3E9DSqVaL8BRU7lQ1_sX12UYIFnuh2EcQ6yatv3P_o__yb_55_7kh1_58OZ293Kz_ee__ZMvPnn-Bz_-2Ibur_wf_p1hc_i1H3z35fVbYr7Zj7__45__q3_6L3abu_e-_m5WeP7ZG6gXv_yDb__yr3zv55-8-Lt_-x8v5jMBsjKQI5ng6nKd07h9exfXUR2HulovllPfmWq_S9_87tf_jT_5q69fvnj88PKdX_j62-vrf_HDn_7eH_xUnHv0lfeev3w7b6urdfyf__Y_-bVf--6_8eu_9F_-P_6Ln3784ouXb0PTdFn7vh8LvP7i2ayu99e3u89ehjZAKdN49yf-_T__B7_z-_u7W4K8Wi0lde985StlGJ6--87jr7z3xY8_WS0X3XY_HLrx0KGhUagW8-X5-XgcYqgW9y6HQ-_riM4rQGzrvNtjBmKniIBoYqJkihyjC0FKcSEQM4eIHiEJAU1dd3LKopmqkOlpa2mTIqEhATConMRbWLfIlLuRTij-otV8MXWDZiEABC3DBArVfKmgKkXGwoSxXWt_0CkBIhD4OhCAFHVE6Hzujt65kotrZ-CCcz6nInkMnkyzmaYhc1PH4NUMARjRRKQUTZmdIwRUVQMryp5lmJjAiqQhuSqYmavCNEzgvIsRkKUUkyKpVItZKQXRNfNGUmEkJNRSNAshoWNTQYcGqinplEALFoqzFUgCVVIhFUuJSwFVYgBHRQyi1xOkiAkRSz-dLsaASoAl98ikaugYCY3YvuxrkyEZmCIoet-0AgBWUEqoIiABqZRs5tCyJEURlC-9tSgK6MwKBsBQoRFYgaJWChlYEgPQrOgJEXI_tJerYdMROwgEYtolFBAVmzISWDaOnkwtZ3SIzIagKSEDGSDaCV582o_BCW-pQuwBDAhMCiEY0Il8Ckh4UgAwAhACk6cTpFXGDOx93camcd73d3sfI5KOfS85kyNVYR-qdl7yJKVUszkxlnFk5lP4x07wDctEXk1P6W0AFhFCInSSE4CSZx8jQmgfPECDPMl4t5tKkVTO3n80Hg7Ht9c4JTPRIi56BSDnNSuqIXkXmuZ8Pr69AQMAczGqSSnifB2v1ppGnTIBmKmisXMi5p0zBElKwSOhqSBT7rNrKs1KjM5VRdU7AkD0jh37EAlMpfgYc1ZmF5pGiuZpJOeQXdXOfWzg9GyDoFIMyMixC4qQc5mvz7fXt44MCfv-GJqwf33zq3_6z6wurl58_pl3zsfIkUHL3YtXphKraFmRaTzsERA9qRH7UM9mrqql6L0nTw67u6Eb5-vVNHWAJKXEehZibGftlNSH5sHjd9D52zcvLWtVtfNm3rT19vYwdN17P_juz3_nR1N_bGdNGsbr2-3l1VXbtst7F7vt3Ve-_4sP7j9qLue3r5-PSVWmsR9SP7B3mxc33jsQK2ZTznVb3b54Nl-tmvmynTV5OKb9vuSxXs5D0-y3d4vzK66aPAxaiowdsC85A1MBrlcr18TNq-sy9YRF8lSmMVQRnEcpXFXd5q6az9h7F0hz9tGZEfpo4MJ8weTq1dm4v_UMbBdfYY8IHKrAHBCJ6rmmAU0IMI8DEit65kCey3HSXKAUIpM8cvQU62pxXi3mZHh3tzcreRw1jVN3KEXJISuiaC7DfH3OROxif9w387WCzeYLQ1KTs3sXaZrC7Gx5b315_-mUBLhaXt4bh74o-7oioqKChC56DrFZLuvzcwHA2qvCcLsT0sN2Z1J8oLfPPh222-NuM-zv3v_GV282m9nZg9h4KzDuDnXbapGmXfimyXmcJpitFosn9w6vtyDFLEsuZejYxDvL3V3ev52GIwyHvjvW81nV1vV8iQyc7e76OnWHvu9E9HDYDd04jRnQL8-XPiAzVMv53e3dzWbbzOoMamjO0Zims8tLdjRv1yHG9x49jUyxCsOQ3rx5U7eNc843Vd-PFMPDp--i47hYx-h1GlfrM5kmF06_NJkcmQLHylSRgYgkFx8aRFSVkjM3ra9njgkQiIl91CmDiHO-HEY4Yb1LySlrMWAWVeaI5EDNkgCeVmXivbech0OXhy71PQBiW1vW_fWWETx5dJyGoeRsivffeS9PPRAc95vLBw8JebaYO0JNKY1Dd9i7UElODIAA-7trKRJi27RNGY5ANo3p7YtrX1fztj178LTb7p339x89eXv9eugPVduqqqqdfL1M3oX6sN2x82cPn-aSKcbQtMbOz86mflhePWCq_Kxp7j2RYSRmz4EdeR988GjUb--6_aCC83uX3lfkHJE3MPZVDDG0tag1y7l3IVbNNA13mx16tzhbNfMZk0tJpv2RkHdvN30RI_QuxPZCdYSSHdKQdXZ2qag-VFNKzsXgqtn5edsuyYc0WmiqU3MM0iBjAsMqVCpofSEG5yKCqVpcXLi2IVXHWC-W46HjyFwxhxYQCA0tQ5rQOU3Fc1PKpMWsKFXBuYiqAJlUEclUyfnY1C7WqjC7uoKc1JTQkBidI2MtpWprJA6LtZiSI-djKdlXja9Cc3Ye6hqI_Gyh2Vys8pi9Cy66kpWY69VSBVxbs2PNWXJhATbh4A0I2IVYo2ORoqLkPZD3iwU6VwoA-vnl-dgP7BnRyVRIBMFAoUyjZjF01eK8lBE9d13iGGLd5Jymvut22zSOBtosWlQxNGZ_8eTDpg5JUs4jBjthKU6ZaVOTYlhAlbIhoPeLGIAkJ8dB-ylL0lx87UNdl5wNlLgKq-X8Yr158QJM6nnb7_aSc9XWs-W6qOVirqmAKQ85ktUhHt6-2d_cmiqiA-JQuf_Nf_QffP173_j-r_0ie_Yu_t3f_K2fffzJ3_uffuPm9mYWKbThT_z6H99s-rptD9P48acvHj65-Hv_5f-4efZZGdP5enG863ZjfnR59f0_8UtI-NnzZ__yX_6uShKQqe91gpTo7PG93YtXOdvq_AJSPmx2F-fn27d3nuLj95_-kT_2vbOz-T_8e7_52Sefh-Xi2I3VYi4qm_3-6TtPf_zPfnf35vZ7X__q3WH45i98xwFu7_Z_66_9Q6754XtPd4fh9cvtB7_2a2-ffd7UbX_cd7eH0HoHxZTi_PHdm5vDfnfx4PLB44ccPKF-9KN_1e3uAvGP_-Vvl1I-__iz97_6tSdPn87OFldP7q_vnVMVd_t9s1pWdb27vjGRuFxM44QAJaXQNq6qOAQApCa44Lh25pk8oagZSipIzlQsi04ZSM2AY03Bl773TCrCPgC7099dixialYJibtae8jcmQoxmIgVmV-flcNCcyzTksYRY-cuZptFMsIiOPZqBFZSsogDgQgBTKafdLciUiDjnUs2Wvm2c92YFoYzHnh2HuspJ4rxG1TRMZRiRkAGQgMwIQKYR1BCI2BOS5sTOmUERJR9UihqoWlyfEYGZShEtQt5xjGLkghcpMqWSsprKlBDNENgxuy9XuTYOZGZqxI6XsXR7SAJiWApIOV1aCMlEzAC84yZKP5oCB4KcNSVERDld7JDYmxi5E1DYQM1UiNmAkJ2U7JqZW7TmHJRCCHl_jFcrUFOT1A1AoCYAZlCQwADsdLVBBAJLFupIUCxNJ74mGbB3RABAJ2E8A6TjoFNiNkuT9hM5NgfmDAOBIRRByWAnCrEomXPBtFhR55yJIjAggCGckLPMYIrAQKSaTf-18Oskl0QDNVBFOp0YjBGlKBqFi-UJVxubdhqG2DbOOQDRlEBKmaaqbcEISNM4gFlY15ITmqkURQBEcs4AmQIA0AkOZQAqQKfUkp7Iny5W7AKAydABEjgnObk6emBX18fnr5jAewcIAKRqKji__wg0pWEipvpsPty-lSkhI4eYxl6zkHd-VQ2v3qAZiLjo8zC6UJH3jigNAxIZABKrGhKR82CITMiEzFoyM-uXkV1XpoKABMA-lCz1YlVyGo6djw17F5p26I5htlxcXO03W0AkM2A04zibuVAboPc-Z0GbYjs7bLchxjSOl5f31g_uf_rxz7vDQUtSLVpkOhwIDMHyNIkoE0vOWqQ-uzIrZSr1fOVjVTX1OAzsfd02JU0q5jiii1U7227fhNny8dMPz6_Oqrb5-NOfHfrj27ebe_eunn7wwaHbv3z22kA2n3zcH_aSk6gx8YN335ktlofD3ThO737zq68__-gn_-yfb1-93r-9HY6H1PXeOV_7aUgXD-5556YxOeMnX33_7UcfTcP48MP3-7vD_OG9L374u6BCzoXZkkIM7GJV103T7Tb9cZ_TyIjVYjkOuZovAOC43bBNw-GopRCYAiGdkLZShgQ-ILnh0DkXvkSr-RDqmYtVnFep64vk8dhNxyO_96f_7OH1HTsOizk7NxxHH6qx79A7DJxzMeSqnamaplI182k8msiUhjJNpXzZuE_T5F2I7bydn439gIghkGnJaQLC-f1HMo3jMIkYAHII47FXhfFup1IspeNh75s5koWmEbNmNru8d6-qq3a1Wtx74GPNzO18Hut23O-Jrd_tNi9fTN0wHrsYfXM1dwCx8rkfUpfIUdVWZRqm8dgddru73erevc3NzWI-e--DDwrAYT-IADCHqpovz0uaSpLZ1YWrTp1IEgHNhlY8IXswyGXo89AdrjfACIBj3-chnV2u2lmLzm3v7tqmqio-XH-qEx67TlSmfpwOhxj9cX_3-otXfddv7nZq7IhvXt9EhsgMAGrKFM4v5lfnZ_Om-fyj52pw2B_Pz9axqna7u6ZZ3m228_k8g9y9ebM6vzQgFeDoyIUM4KtoRirmY1SzkvNpQ6EqJSsB1IsFOSqn6hKxnGj_tWc-ZZQKIqqJawIyq1q1nudJZxdNmSZQBWRJCQ3IIxOyA5As05inrjlbM2GR3N9tEFlTNtRSUtPOPvz2L23eXpc8iZbbt5tmsTBTzVkMiaGqZzklRLff3ACo6FTGgq4SkdlisVzHcb8HNc2puzt2_V6LEXliWK2u9rs9oqUsVd0IqIuhimHoBkNxdZtTXl88nNIAWqZUFMx5LoqekeY1omvPziQVKyhiZuRirOZ1bJoQKmbmKh63G2Su2rmRZStNM2NiHypVvdvdLdar88uLEKNmYfbz9SxP5dB17XqOiCcB5KE_5inXi4adP-z2aGW_OzZtw8yi2VWBkVMeCXAxa5T50I9N3SiwC04djfujqxvIHeSxPxwosq_qVLRtV-27X5_22ykNTRslTTnjannmqzqNkwUPLnJdlQyh8UYgAn5ZW9EyFWQEA2MydkAoIpYVETSLpFFLViup70op7Dl4Dm1jgFmUmb3z_WHPiKUUMy2l5CkDgA-1lhKqqEU5hPn5mUg2clxHQlaENIyaC_tgZmG5cFUchz40bS4FWbMIOF-v17OLB6GuLh49qutmvl5z06TuWM9mmguJYJ60H4iYTgQ8BD9rDTKi5WzzsysXPTJDGiUnLeK9AwMpZRpGZEx90tzv37yZhj5NWadCSKGqiZwP3pgVITpmR94ZmKGIZ6NcLBeTbKknIlXULKoIGBbv3HMed8_fOoQyljImjzSljMy73d2Y8mzdFoMqxgdP39u9ep67XT-lGOPZw_v_yf_-r7z75Mm3fuk7N2_e3N11r95c_-Snn_zhzz57_uo1MYPCn__Lvx7Jf_CVD968uZty3k7bv_XXf_O43__Bb_0eDv1yuRr7hKFdXV7-1f_0L63OV313GGX43X_6u8f9HeQ85SSDnX_1QiHdvrzlmpdPH-5fvpGpnF2dHe4OX_3aez_43reXi7NnH3_66UefAeF3v__dbLh7u0l5_PTnnz588vj67cu7t9tf-qXvvPfowd_5n__p4nxdrP-v_t9_c8rDh9_82osvXr15-eYr3_ygz5vdm-upH3Pfe9N0OMYYH1699_XvfHO7eUEO92-u7-62w2azefUW2TFEJbq6_2g-X58_ODvebTbbzWG___inH9-8uUWyaZj2m60q5mGwAmlKLjgQK8cDkEME09MWxdJxlKnYOGlWch4JTvJRJCpDctEToQj44JlRpslMtSgyn6IjZgZyotaocz5U0VJ2RFqKFkHg0Mwtaem74Kkk8bOGaj_d9ZayFdV-QseYM5sAgCggESDmvlfBGOqqruv5jJBC0yASGZQ0pWFUVSjqmNl5QPKVz2OScfJ1tJKsiKZUxkJE5IwMgT14LqUAkqgZOlfXFB0yn9DjVooUKVNGPA2mGmIdm5jGvgwJtLB3cBr9EC0bO6-5gBQwMJlIDU8fvihkBVAEAymgiohErKZAJMVc0-QpgahnIlMdJzBgIwCzk9oMkYi5ijJmX0UTcYRmWK3nKEA-uBgRSUTKMLDzmo0UFTRPiRitJFMxsVMyHtkjsJ74Nqe5UJS-rCUbGiKjGWoxPPkg0CSDqRBg2R8YBUsxyOTIkgIyiEJOWIqlTESAhgouetQT-ueUYQRm_te5GkRVMCTHgMDeoyGCkWNNhZwHVTLTUkAMVZ33JuLY-aYOripTci5ITqa4urq_32zYYH1-NfUdOtZpIs_9bocIjl2-6_MwIBE5pyr_S9-DEIkQ1IDIcmZiItTTEybg6TPIMKLkMk55SgCyfvC-Dyz9YB4gF5WUi6ioaxrng4sRoPR3O3ZOUhlvb00stpWpggn7CkBRRbuBTE2_xP8DsW8azdOJekonrCchn9QQYqFpkClPk5lpyYigAM4HEzARQDCEYgbExiRjqhZLZvKxkTz52XyxvERyIuNw-6Zdn8fZ3NX14uxMRaZplKxVW-WU93f7s_sPTBRExnF8--yFaamrGgkxqws-H_YhBjD714I8SuMY2kZSRsP55WXbzvbb_eLscugPKFamHOsGzOaLs2a1uHn56t1vfPfBg_uOYbY6--LjT2JdIfD9e1eXl-evX11_8vEnzoFOeXu327-8uXrn0Td-8CuuqiGnV598fjzsZ7P29acfaz8EgpxGKxLbyrtgSHF-ZqpIkKccmOeL6vVnX0yH8dG3Pxy3x_sfPPnkX_w2CYTKuVClJORo6kaTdLy7S9OEoGUaQmgNuV6tQxV319fOSu46j9ScrWQcwCGkUs2XqDIOE8a6rtrYsOQcFvP-bgizebOY9dvt_mbD3qlIjCE65ElnKU3DsU_jKGZqGququVhTiKFdVevz5eWjoZ-ATqBxqdZr1ALKzhEZyTDm3EXy09iFGI2sXa7iYjX0vQE6JANAmaQkIur2B2Qi9oYQQiRH6FwILrR1d-y6uwMhVE282-y8p_3hLg-H2-ef3T77rNttynAY724MFDTPVudWpuDJMR53x357WDy5P93cIhGykgv9ZsPeQZac-jJ2t88-RpFu6FcXV0PXP37nqfcQY7PvekZz7FIqh7e3FGoZS6iiD1XwzjlvWvJYSMlAIRWSJP3h-OqlDodhc42Sj8cjItV13e8P6CoMs6YO427vm3i2nO-325dfvGEwR0BkTOW4u-0Oh2E_vN0cimR2TATEPInebPcAsFgtzNS7gI6klPX5GaBdnJ8bw8OnT733aCAGRU-cLuG6Pr7d1qtFXMwkq3eBzAwARFxdO-9NVUXIe1NjF32IxAEMAVmyqOkJ6Oxj1AJ5KnrcZPOhYlSrzuZlFA5BJaOiY8Lgxq7Px94HAGArVhTifFUtL4ApzuZE1HX7oetu3j7ziPvt3Wwxb-dtd9iGUPXHzjv2zNM4IBiTM4WpG0rK1Wp2uLurQuyPezSen50BoPdhebYiX_fHA7Dfvr1Rg6t799Bh5SrTrFl9CFo0Ng2odttDaCozna_WFMLi6rJkrRdLULi52SxX9252r-fL8zibxyq6GFMprmmib9cPr6YpbTd3i_WFC2FxsYptbUU9u_FwN3aDpmQKx8PkiVNKauX65XWow3F3CCFWbYXkpuOIzKmfUAoy56n4tkazftctzta72-uS8mze9rujY5y6jr2nujGg9b17rq7OHr87dhOhI-egJOfZJAPBdBiFQggVBscy-dbtb3ZaIDbN1E3dsHcxpGkMsVVnGEKzmo1dL1kxOlDLqVD0rg5UeQRC5081a0Q1AyIiA5ETm6eWkqUfikpVNSmPOk1ZTA1my5VzjigQs_PeMRvolMZp6EtKaCqlpMPeMaepz_0gJSODqwISApKpacllmjj61PexaSQXETUwSVlkkpzGwz6Nw-76TXd9qznJ0MvQaZqYzPlA7ChUknKct-PxmLbH2WLlqxYsS79Ph30eRvKualtCMCkyTCrZRKBk1AJmp6O0j2A5AShKYUBTLSVBASjyZYiuYe0T2ulUq4g-xrmLTRrVmNbfutd9sT28vpVhANM86vHugAj1YimAqR8QCKdMRcauv3nxOXGQ2P6V__h_94Nf_u43vvrhp5_8TA7Hf_D3_-cwi8v12cvXb49d_uo3P_iT_-afAucfPXm033RN2_gV_c3_13_XH65vX97y2Fs_jptN5arjpF_79ve-9f1vfOMX3jWwf_4vfnw8bn7nt35_82aTcxqHgorvfvPD8fV-9_wmegcFasDtZhfILc_Ov_2db3744btxVf3uD3_3Zx9_EerqP_qP_uqrl88-_uzjxjsrBoTvf_Wrfaff_yPf_gt_5lf_-__hH_z0Dz5q7re__3t_uL3d_bG_-Cf-6W_8Fle1C6Sqbz5-cXbxsLvdkY42Je_Ic_21b31j2N--fP4CzCAX6bfTOCURDvHDr35rdXlWtfPbV6-77d3dm9fTNA6Hnh15ojLkfrt3IUzHXrNWs6ZuK1WZusGHAJp0HE_tpZIyARoYeQZD8pz7gR0Tk6WMhFCEnEdmZi7TZGaIxNEzIGg5DZGgRnRaNaNjB2J5yuy8qSG7UFVgZdwfkBFcYKZps3dmpMJqpuqDAzUAMyAkV81X7DjO5qGKSEykUz-UVIhw6kdNo4oSopkQKKCBFBMZD4cyTBzYsnjnTJUAnQ9mWrIYOxfjKZaPzrm6cW0EPoksIxKfQiklJysFDQDJVVFLnoakJUMpvo7sqYwJEADBV7XkkcBO7yfyGPxJsAyllNORoZiZgALgl2hpco6c4-gJgIkgJciZDIgIcgZCUGDnDBSdN1UG0KJaRAw41s47yUUFiNlAU5_YEwIgA6AhGopYTgzmCM0UFJyPaAoqJoJEkrKZoYkBudgCoZoCoQEioUiGUhAZyPDk5kUDAcuKQKSFiDRNUJRPGXp2IMKIAGBJ8CSw1RPsH1EFv3QECfpgWswUzZ0EYVoyKFDgkzDhtJJHUANUKchM5Ey15NS08zxNOZfFxaWrOB27cb8_Xr_J4yA5O3LT1IMKx5hzQRNm5hhMlIlBwUohQlQjRFMwMDidQr5UEjA6tpQA1E49BEYUoRCn7pjHYzqOrm3L4Shgrqqr5UoRUYQA-rs7duSjO233Q1OlYTAR51hTMlUCUBNAFFVyDlB91ZS-J4BSipoR4On6pEVdrBFJJEsRcs5ETMEACclXERnSmBTBVS0gV6u1qOQpt8t1mnoAyalcPHp3eXZeStEsVT3nGG9e3tTzZuqHY9etLi6YiRBUoIpVO5tP_SGPOcbASO35-vbFCyZq1u3x5rpMoxERcRonAK6XqzLmOG9Fyny5Xl09EJGzyysA2N_eIqEaljTFtp2mHpGevv_NqT80s9WybXOx_X53--bu6t7D9WpuNr14_mochquH9x89efLg6ZOL9x4sr87efP7p248_29-8LN2-DrC7fksqYFamhEjAoVmtXZxRdFN3nI5DO1tUddXvDlOa6ibc-_Bhvz8Mx_749i3mUrIUhXHMi3uXeTjmqbjoZ4v5lEZf1cv77_q6LtmYOO32DrWMA3k2tDwNeRwBAZFySinlZn1ZzVd56mXKxF7YNeu5Y7z55NlifdYsWjAmh_3dQXJimT-pV8vZajmNd5B0df9-TlnAQAUxVKFhV3H0OUnqh-bsIg1dqOr119_Nm255_hjUxuNB-0NOk8g4dENY1TmlOF_E0LbLhwjj_u2bknMax9BUjn2zWNbLGTqzYqFpuaqWF_dMkuZpGo6vP_35NKQyDeP-bjxuJfWBwAf2RGgSvB-6fjoeHbOUXEoJwSFY2W6tZPCnJUEhJMvWnj0mRmdQcsrTWMbu-sVnMu2ff_YRGJhpU9cnDPrlg8euCRzYBVfN61A1hiU0Lfm4fPL0uN2WTFzXJX_Zb0FQRiDQ1B9zGqZ-Ty4wY5lSWDWOuNvfvX3xfBwmV8d53fTdOA7jcOzy2Euecn_Qqd--etMfDq9evx3GgTxKkSp671mzTEn2u2PdVoBQDByhZotEhq5dro1CKeqrauhHZkZHIGIKCBjaGbFv5kskGrqRHJdcmOPi8p6WBOilWFUv6sUVOhVVKUZVVFF2zhApOvQVlMxW8pikn8izIQYXm_WF5EGyhNUC2abtUcYeGFRETEIdcxqH46FZnHmGcTgAgkxFNN9d39Z1AMJ-t5ufnef-kA_7NJV2sSgpL1ers3sPgd3dm-3F04eExoTD4VgkjcOkgN65aRxKycNxT4Rl6Ms05FRExRGrwnq96odxe7v1MTpPVVtx8ElUxIKvQHWahtlyuThfM9pqeSF9YgOuKlWp6vri_tVxf-z2h3zsQ9Pmsa_rRosFdrMmhqY9din4YMjL83XdxFCH2Da3L17fe-_pcDzUvkpTXzXzEGsX4-HuWC_m_dgzs6_i8ny5eOceMXIV1w8eNHWrDJL6lz__aLY6A8u5ZPQ-jakkYeB2OYtNbUZ5EvZuGBISzx7ea9frMg1Irm4a9FXVzKdhiu0cHZRJfPBop9O71KEqqSyurtgRAPtYAROgMlBOyrEK7SLUtWPMY7IipQgScWBjnMbkXaDTPWiagCGXDAZxMVOAIjS_uJQhuSqqyLDvDJGRqrbOfV83FaohExOpTJ75NIWz95YzqKTuhigwc4it8z42zdiNbACmuZ8C8XA45GGQKTu2qqlkmpAgTwmdJ-9LyWkcU8rkPQHPLi5n99cmudsdIY-WJkQGRklTGSYTcUSIKFmICYoCIhOJiA5K4KRkKFgkAwIERwzAZApIVPoBDIy9WU4Avp1T63NRA63ms-HzbTocCGx1cYYxMmA1b4c-EbOrquC4Ch5PHQOxr33rW7_-5_7cr_7RX2LLr242__g3fuv1i1fXd52L1aN33n384PJus3_y-N4vfPPdV8-eO7Xddr978WrIw2_81_8olynEav_qtj8OZCS9-9Vf_7U__e_-WbHS931YhR_9i59sDtsp5e1mByjLx6vjOFSV37_c3r3cnp0tax_SOBbIAf13_sh3zs-Wzz754hvf--bf_u__zseffI5Snn7lK7_9W__4089elKmPvkGl_-Av_Yd_8Ic_erhevvP4wX_9n__Nm0M3XzaG_MXPP3fOT5hLIbMyu7y8ffV6vpi__eyL9qxJhy5UDCAXj55-7esf_vY__ucMcNzv2yqg4-7QPX3_w_e_8o3AfjWvP_6Dn-x3m6HrfKxCrEuaypBMZOoPIVb1fJGm1C7a0Picczp0TGi5ICFIMQME05xB1TEDkImoCon5ZaNd5nCCz4OAETEiq2RABjAmgjSpWknlpAAqJTnvnQ8qxZIgIzEhoG-aMo45JTKmGClG6cbASmC5nxgVQXMpoODbRagq9tE0S5HxsNc06pSmvlc1M9NSHPM09Trldrksw6gm5TACmKpAERc8AlTzGlToS3UxILOhd95Z0aLGMZLz3gc0TWMmZFdVlqcyTbkbwBDQnEcVNVP2TlM-cYPQsaYiRdAhGLIDzdlUzJTI7KR_QjSRMiVCADRCCKtZGbOrPBp9SSDywdSInCYhyaAKInoiUZAzUx9CSSXECtRKSgRAjoHYVVFTFtETJb6YkCcGRLOSi_YjOpRpxPKlK1AVmBw7h1oAkRydwNPOOcnqvZcTLZJMpLAPQF9iPSl4RCRAtWIi5AM6kGKMaFZAFAnJs-RspmAGYCdCh_Ou5KQqiKBFkQnxZA84ybjM-ehCNCgyTOzYTC0XNEERIJQs5N1Jyuab2gDzbg_sBEwV52cXXIX9zZYdkxl7IocmBR3LOIX5jKtgkk5lX0vZ1CwVBAICKIJMKnpSrYMhOa-aQMEUQ9MCkoAgkkz_-g-BFIJP_eCdb1aL7m4DTBxq510gnLqujD2ByalAqILkyjRqESI0VQNABCJHnksuJyQtAKIan1zRRKbmggc0VfShJoIypdjMvmy-pcI-snPsg5Qy9WNoW_ZBEYhYJE_Xt7Orq_5uB0SAOltdsq-axXIcRgSYLRZpSrPF8uLepfchFykyVvVMSmYk75vD3R1oXt97YCrbzbaazfLQmxRk19_d1aslgKVc6vm8ni_IhTRMvmkky8XDp8zeu-hDvH35MgRu21XOUzNfHff7xfqiWa5LGn30i8W65PT2zUsm9_Tdd5bzZuiG6-ubzfb4S7_6vWigmj_6yc-3b29eff7FcbvVsZeUfYiSBVRBTVXQhcXjByAmUsbdLk-ZkNrVuVmpFtW435mJor7-_NVhe-ccgel0PAKyoPoYzHDa710Moa42r99ePPmgFK3mCzCo6kpyyt3eBTxs-tl6AQZpGE81lFMYzzezECsfo-aUp4F9CPVs9-J1TuniyWPniEIzbjY69lJK7ju-_ws_KGw46TSmWFVUUXd7qwBayuWjp9PxVkGPu35-77JtF93hlQM3dkP__NU4jt3-Btm8i6Ft6tnMSjK1aXOYho7ADPLh5mVsZ-xZAWZnK8dxHHsrw9Adm8Vy8fSd7YvnQ3-8fflSplI3TdW2oZmH4Eseurs9M6BhnoqkoiZFDMl5H0rJJmUcJlMBFS3FB0SAaZhQoKSE7HyIOR9BtLpYOynTrgvBecZ0PIBM035zuHl7vH112F3HNrjac2ymLBcPH0_D0FRVd3cwNa2bad-dvfvEkF3bkK-yGoAj4ljVORXvCIuRZ9As-x2Jbm427aOzQBFQdv1RDkcgCW1DiGA2bLfp2FkqBBi8oRSHZer3h-vt7tXb3f6gIkjOTGJVVcGFOkxd6oaxin7WRhG7vrlpZwt2rl0sFmcXLoQQm2lKHNgEJI0--CmNLgbfNAhazdqUMrKJEXsHRGRJdFLi0M5CuzA0AARHSE5Mkf3y_rs6DipG0eV-kpyRMI97AjDnhrtjWKypDbGdyTjVy5mraf_27uydp5bH_nhcXNyb-kMaJxENjknGfndb-vGE0WauqAnsfH_sH777Qc7j8bCt5zPHiDmN3SRm7bxVE2Dt913XHVYX57Gul1eXkkcmZKKS0pQnQWjm87FMMQRmR4jnD-4_-_jzqgpN0yBCfzg6x8uzczA7v3d22HVkWM2jmCYpUjRJqap6tjyr2lm7ms-Xq7qqkuSmbaZx5KpCpcuHD5i997FpG0Ta7XYypeXlxd3rtzF69s4AUhrHoT9sb68e3UcwFypiuH72ppj2N8dunPr92G-O47HfvnxdxzrO43C405KzlKppXVWZFZNc1bUhKDPHqp0vm9UZ-qDG0yQuxrNH7x62W6yCqYkjVQtMZ0-uuuuNpGyT5GHALEgcFhUQ9nc7V0VjKpNw9ERYpsIEKqIiy0cPwSDOWlfFAqA5ueCIMdQxxApM1OgU5z1t9MUk93tfhb4_UhV91cSqNiYzIyAQUVFRlVzAUEuh0_Cdi4mCWGgWhCgpI5GJljH7OnIMJ3i1lqIqhBQqf8KGI4IphCbSCRgikIvMr-67WFVV7ZvQb3f9zUbHjplNQaGQqowjqJmdxiEwAhBw0dEJ8hc9tZ4bRzGYN9d6cXDSHqABSQE1Fyozo3kkx65qJRcE7Te7uKjKMMg4KiH6aI77bgLC9qypZzOAkvp-6A5g2K4uPvjOd7_1R375yftPXz57--lHH9-8fv6zH_74sD3ebfNf-qt_4Y_9iV_Zbrvf-_2fnN87f_To8vr2eNz2n3_82W_87b93eW_18vNXpTsQu9efPFvN10Pv_tRf-NN_5q_-emzdT37vp8exe_Cts5vXtz__6cfc8vWLW-dw-eRi__mNjRNkGfv-wdN7zLzdbGaL-e62-z__n_63N9fH7371SbOY_xf_n__KeWPz3_mFb9Z1fP78OStMnbZV-8vf_16Yyfb67t__y__G3_jrf-f61Zs_-Zf_1L_8Rz_cbXcAuFytLj94Z_P5F1VTj_s7j7R7fR3mXkRUZTr2peg73_7O7avnN69eVLNa0jGLgviv_eIfnV-0u5ubl59-9Mkf_N40DWy4unhw-fjJYfNmOvSISkyl0Nn7T-_e3AAYOkjjeLzdoyl9uajXE0f-9L9EzKpAzhGd8I2saJYKAZjCl0Db6MykpGSGiMCmYCJfUjJRVZidi0GKmJbTmKUqAEgu5H6sFss85LgKkHI5dEAkqbjaWSlmRhxC25CjNIw2TViKpgxT0lS893AKSSgAIzM5YkIghjSOhOTrwMGpiBVDxHLspZQypCJiYIKoCnHesKfUJyBCJlAlNC3lJNeWYQTJqEhA5OAkuiLvkcyygikzaS7EZKpWiqsqIDMzF72VTEgyFTzJPnIBBXbeRIgA2JWiLjg101wMCZnQAYcgQ4-mJMWyIOKXDxgAxKRghESOtIipEaMhEWHph9MviwtecgJCNAERRQMTjmwl2ZSRAZ3_MokqGU2QyYqAgpqxCyrigucqKBgxUYyIYKnoSUhSlBwjsuaEpmpqhOyYDE0zmKjqKaQOol_GV3wkECQsU-K60Zy_RJzZCbCJxM4kuxDRObWiYzp9I4EBmGqxU9ODiBHQtDAFFS3jRFWLZgYUmlZVdy-uL995msauPx7bxULMUtcDYlysSp6sJMhFSkZA5whNVYSJRZSdQ2TVws6pKCJITojOL9axrgAhpxGKonPEDMihnTFTHgdDALZ-dwDC1YOHkkZJQzrsT-grYmImU3XOh6ZNhx07Ni2ApFrIe0MwR8TAzqsYMROdgj0OQIm9nF70FRADADd1TpMapL4j54iIPEopJ3yqj5E8g1jOkxZp1mei6mMVF_Ph2NXL8wdP3ykqKSVGOew6cK6eLYoVYiL2KhJ8aGfLfn_g6NM0iEi9WKQ0hcqrGUgGJJOkxVxVhRhLUUSHxJJSrGv2rGqz5Vms2pRHyaXkcbZcTn1XNUuRHNuZD1V_PMZYt-3ycNhsbm-_8vVvzddnZun69TV7Lll8QOby49_-7Zvrt2O386jHu42mXFKKIQKhqjriIgjK8_tX_d3d2Pfsg6-a1aP7LgSRktOwv77udvv5_UUZEjmq6jjsDzYlF4OrKhVbXZ31tzfA6KIXBXZ-eXU-9EcpEzPtXr9K_cHUSrGrrz3u73aAiAAnz6AUXTx8BAZTPyBBt91JShzCdDzUsybM5kPXl2Gctm8xDWaFiUPlmM4_aM9Xcd6S56nrq6o5HnekVkSmzevhuD_uj_c--CB3XX_sCoZQz9b37lfzRREpoIDGwY3HwYVAzjE7QKFSnBaZBud9zgkdM_ux2-c8tc05gIoMm1d34_Hu8vG7pMg-VMvZNE2plBgiktWzWWwrVVxcXlXrlWqZ-hRrDwq-as8uH6qW1I1x3oIAeAQ15mBQLCffRkIicpoGk5T6jmcXs8vH4_a1TokMT7Uq50lKdih5OB5u3xyO3Xp9v25aCnzY3YGy-aoOsTlf9Ns9eQ-Akkq7nIcQ73_tK9Mxt2dLSZKLlmHSVIiYvVOg4faocpQicdHUbSiTmALNamCpm1jN56kAORr6aRqnEKN3rr48M8sqkqecMgA7Ii1putt3s7r-_PPPnFGoQtss1bRortom51zHqqgpQC65nq0MrZSsUsi5EGsxAw4-xnaxHPt-tl6qUrs8c1UAcllKKRKqGZKfnd0DLXE-KyWlYy659z4KqKr64AmtDCN7l0u2lJiwjJkNgJSZ-23nnXMV7Z6_YPLEQXJqzs_LlEPt5LCXIVuenKPUdz46ZC9Zrh4-CZWfhoNTzaVonpAQ2Yno2XLVD8dQVUDgAhPicNgDIoh6X6XDIVT12B99cAbgY9Uu1-3q_Hx9vnn1xsjOLi6uP38FHGLTLNeXLgQpVlK-uHdesvkY9rt-GPPsfCmljH0xYB_9vG3HaeqOHTH33VFNq6aOIUTvjschDQnRovPjMIBYM2vTNNSLOYLEKhBziHFxvj67ui9FVudnVmy-PqsXMzGJs2Y-b11AJiOQalF3u_3yyeMAfrG-t7-76Q99fzioMqAeD7tSFCKlklUwNJFDndVc8H2XjDRWjSmw43Y-c8RSVLNmzewZEOr1PI2DpJy7KQ9TzqVMiWvPyHnI5Nk7B6aEOAxDvz8675t2PnY9KqgUQtBSpikPx0FFQM3HwEzs_f8ihkzj6GezNI1ApKAKguhmqxURZcnoKM4WSAxoofJS5OS8NAMQE5mYTylNkZKtaJ6yGYgYeSbnAMCIrIBIQSZDGvqxalbgXdXMm_W5qyIApmk6vL3VMlgpSIREJ00sO0QgdA6YgFkNXFWhQ1XVnNA5BNOsMklOhsqWjZClZEgKZkQVc0AfQBEKIaCrau2GMkyakAMPmyEsF6Gum7NFkjxfzpFw3HepPw79AQCaqnnnq1975_0PmvP5i5998vs_-v1ht1W1m-1hu-3u3bv49_69P_365ctPfvbxrHb3n9wjx3fH4-_-1r969fzZs2evVpeX3WFEtO3zm3bVjGN5_yvv_bv_6b8da2Sgv_E3_uHF-bJ-uHz24y_-8Hc_Tn1nUyYA0Hz37GY4HNnD8ZAuPnhctfVxSGeXV7_0x__49_9XP_hv_n9_69mL68V6-dV33v-Tf_qPN3V1vjx75_G73_jGV37w_V9Yr853b978r__yn-Nl_G__-t89Hva_9Rv_6tVnr2brxfb565fPXtdt8_hr7zZPlq9_9FNUYCCXjEqu6tBtdvVqYYPMHi7643R-7_6zjz4umvpjd3nv4fryYb1a5WH_43_1cxknhFIU2PTJN39xf_PmsHnd3W7ycX_-3gdjN9YPV9O0n3b9CdxScmI2wtOyMhORnLL2lccQ7QSbL6JFTlU8UzEtqACEgCRlwujLkBHRATjndEqllFP921eBEImC5GyqkicEJOYiUq_XXPmcs0mRPjv26Xj0waOamqEpNw2FKiyvtO_yOEE_gmfLBQBdDPVspkDOBz9vSsowTWVKjERM_Wbj65piLCmBKLLTUhCUHLsY0SHHAETsPBBqzprFOWRkU7FSJBdQtZQBjAjNgBybFDA1AqpqkIKIZZjIO0kjAHIdkRCjl2ly7ABAxgnV4HQt_JI1CeAIQcEzh8rXjYmoAgEqgjFKKhT9iVjvnJoaeALF03xmwMBEjAxkhpIy-2CnOZtPJ7hCzGAAklnVspwarVYKIMKYgmMwtWkkZgI7rSfA0ADNlBwDoxqQ9zmrq6s0jtKPjACnIj-hwQm-Y4Qnb1fhyn1ZnM1C5LQUNNCUyDH7YECMqNlAxQBMSjVrT5YhFUFGcK6MiVxA5xBRhxFVEM3UABRU2TEwIRF7V_KEFHw7c8GzCyLFNxUi14uVQ0ySEUrJxURFMyCUNIFhqIOmkQyYAZnJFB1JSggGaKd7jUkGNABk51yoyQcMrDnnrisnjzUAOxIxjpVakVxkHMFXHIOV1CzmU3_Mhw5MIMtJG3Ta66uYb-vhbk-EyARmeOJIqJiaqRGilEIICCClEDvNiZw3Uw5eBKvFgtCmqZDZbH3W3W7YMzuWXIwQzeK8AZE8JhMtp96FIfsKpMS6UUkuNhf33onL5Uc_-0Mtyfs4X69dVZUy5VSaWetDmKYBEYfjsWrbseuH7tjOl_3QhTqawbDfaxkJMI3TxcNHhgiGs9lifnZ5vNvGpjbV_Xa7vHq8WK44uuu3m7oOUkoe0oMnHw65R6J2vjh2_Wp91rSLzz__CBEu7t1DwOFwGIcp1GG_u9u8vslTd_3sdRoGx0iEaRxyN6lq0zRx0Tqi5YOnfddX8-X6w3em42739nZ278qFqlovy5RAynDYl3EAKYokU8opKQAHzzkzY7VcpaFvVmfDbmtFiinH5eL87Oq9dz_6nR86z5rScbtBU2ZVJcmKRLmfSk5ILpcCwPXZ-SlbiAZlzGaFCbz3XIUQKzxJfPpj7g7EDp0ThaLK0NyXnMfdTtSAsLvbnj14NLu49IzHm7dNXU_T1N-8mvrONLXzMzBRUQwcq6pq56YgpRDZuN_nccopIWPdzNPQg2nqx2F_IIdWppwTSpFxB6Dt7B5STkOSPECstrcbJgzzVd91aUyL9SVocaEJ1aLrOjSIzUw5zOfn7WrRd4fN7cZXTXtxj6u6pFQvFyiimmOoABDFrKiRkpmKTCmV452mrWYhx-wJwVyILhAhy5gdo02TTcNx-_LNF5-szx9ePXqvOT_jqip5GnadJww-SIbLq4exrrfbXRn6nJLm7Bdn3IYQG4fUrM_GktPmNRqxGpj1rzfaj-wLpjTcbsqUesnsggWoKj9bX9SLufP1frfprrfH_b6kFAMZlNQf-0Pv0A3TGGp_OZtrLkK2298tzs5MAJ3zHNRssVoFHylGEQtVPVuc5VTAYBoGZEfOmREQuxAFiJxPeQTAUrJzwQAAxMdKcm-G4Pj--9_OqUcAqjw4BuITEw0d5nFiFxCRkD2T5AKpIIELWPrk5wtfV8NhZyn7tjX2mpL0HZSkoj4QAhC5PI7D7cHV1XDcpzQO-_1wPJY0nHjG7aLevt6hpL47lJRSd0xTSsNwdv_xbnNbt2dEBZGZHJqSwfr8avPiNUg5XL9mh4vFfDgM1WzWni3V1Ad3_eZ1M2tTKovlvN_3Kac8jlUTnadue1fPF0hQsgChY8oGROg8zeczU2OkoR-GlOqmQVPneEy5XSxCUyNiFWsiG_vx-tXtaj1bnl0M_SFNeZKk5oDYwJ6--26aRkmYj-N0u5cMU39kDrvdNh8PeRyG_dt2voizeAKHzC_u1bEC5NvXmxjj6vxsON75ulWkUDUXjx7LNHBgyypiRQyJqrphF0LdAAEYTsNoRVaXZ9O-Y-_b8zMiwqTIgAxoCCplTKKKBlWspOSxOyKTqyvvYy7FgJDBRSIiE0UVLZmDq-oaCet5o6moZFRL49TMlgqSx4SM7fm5mhlgUVUEUBQ90SqQOLL36CIwIXHJYqaawc_nsVqwD64KzldGvn3_g7Eb6uVCARNStV7Pzu4pkyHHqi0mw_FoJZWx02kEKYR8-qEnBCIatwMFr4YiYiLkPAKYCLInZkATAyuCksgBlOwcWJpIDEEdMSMrFNVJrTiPp1onE_pY1w_mwQVAV80brvn4emfjJKlPfUdI6ALN1h9847sPn74_m7X9Yfv28093Ny_6Yz9frtbrR6Fu_-2_8mcW8_au7370o0-nMpCrDvvD7_3O7_3sh3_QH49GMLtc52F6-ORq82IzjeHs_oN_6z_7i1eX59_-weN_8j_8izfPntFEf_Qv_cpv_u1_tHn2RnGaz2fH4xEAu20nSFTF5uzs8ivvHjbbu7tDO5sHzy-fv_jJP_3Ru-----_9O__uz3728_X58tHl-rvf__4_--EP_7u__td-9vFPP_rks81m8-TJo8X58v_7X_xdD9lsfPXpqw8-_Or3_swf_dHv_mg2W3bDXnN-_a8-KUMXwEEu07Ev0yiiIVYevPUlzoIn2rzd3Ht0X4GKr7_5zV-YXcYXn7_Ybq4j5by_ndKQOnn_F375-rOf5b6fxl6Z68v7ORVVKV0ebg6WM1fOr9u825OBJjECNZNcXPCurfKU0UClgBkRGKGPgTxDScheRZFJVYiYordJAAHLCS9jRIRIJ8eTdzE0dRlHdg7VENkAvI8KkMfCHAn9-vGlC6g5I6KCopKro0ixojaNUpKpAXt2_oSUVUBwjomNdDx0moprWhQBKGZEMYBaSeOpZmols3dmEueNlFymbFKQWXKxXBDMStEsKidxgUopRMBVOKGQRM0kI5GoYPDOeytFpJB3qkKefR1LSjImM0M1SdkhaspQBMFOkpWcCnlWUcnCTR3mjaHlIRnA6UUCdHVFkU2kHHpiPvVSJWdANVNCAjuRKgER5BSoRfAuAFEp6gJbLojqCEEMESxlJEARcowmKEZmiCeNGZ98IyeoGZID5yQV11aaCzKUYQBRtKJJTA0cAQKoshqgiRRua-dcOQyQi6oCGJ2Yr3zq0DpgRvkyrWFAjp0qSD7hMYjYqwoAoXPsnJai03SaqMh5YiQDQlA1YkagMiYgF5crE8njJKlUs1ms5-S4XixTP8W6TmNHjkua8jSaWWhq5yjt9gxaUgI1YmZEScUxoyMTY2ZTNWTy0TczhZzHUdMEopazIVgRQELHp-KD5BS8y_u9O1uFukI0y1nHCSSDFk2JiU3U2IEKInOoOHgqhRybFiQHAM4zOY92UiKbmboYy5iccwhIzqvIqSpWr1Z5TNMwxbat2qbkdKIVSSnsgox96VKR4psa1dSUHHOIsWmRyDnfHY7o48P3vrK6ujge-1hVTduYAhAdDvt2uWKmEMI49IvFajZbVrO55AlRxdRVFZ1ATNOQDkcVna_OHrz_fi799u0mlxxi5Xx0Lrx9-cJzuHj61DvvyKtB0zQlTQY4W683m7em8OjJ-8Ts2JlZt79DoOV89fDBw93dJudiAJ_99KfH7V2RwTm33d6yD_P5WozZeWZfzxc5FwR2od7tNyXD8t7Z5s31frdvztehmTFDf7sZ97vjZoMqvg4E5iOjFhQlhP712yLJxzD1Qz2fpaFPY0Jy97_5rTImIPjid36vbYPznIeBiFwIhuhidfb0aXfztpTs23boh2reVm3liKZh6Lc3oQrDvg-BQ2D2oW7XU3cESak7YC6hbY3d1CXXxBAc4_Iip8kRhlD1m5t2tkhDbs6Xx-tNGYsCBB-nYYeSNadxf4usqe-bJrjAaZrMiB1VizPvnaujqYY2lpRLEinqYnSeZBpzSlVbe2IXWFS6bheX96LPYz9I382X85Ly2G3P5mfjtO0313d3h9nZInpvgDG4EKIWNZDd7TWzu3j0bhoPROirOg3DNE5l0lBHyRnRU4hQJkOYpBAxnFgNGX10QJhTVlNTOaFRECnUZwRqWpwp5r67-ezNJz8bpLTL-Wq2WF6su7v9oR-s7A2CmuYii-WqnVVpynkaKQQw81V1-l727VmcN9M0MqNrPGQxg-HuiJZIy7C70SmXPLFTmUYQRZmqEIMPD9_5EB1ur-_MxJjquiKmcRj7Yz-lggHr-VySGBgDXr-9FcnHbjSCxbxdrc99FWeL9fb2dn5-Qd6nbMAc23axuhjHsWpmTz74wDVeiQTQwGaLxdAP5CMQtquz5WJ5OHZSyvnDh3W9QPb17PJ43BH6YsZVpabknAKWXJAYRNCxCoSwck6G_dFOAPYqTEPPzrvgxr43JIRCYI5CmN8j5-dXl75idCgph6pK49FEu5sXitG0XDx-ZFqIOThAk6YJdTs7XL8mdN3mllxIKfXHY6iqEKrd7c1yPUt9j8T73b4UdSH2XdeenTmmw-HQtLPN5u7q4YNnz1_mUharxThM7ByFMF-f5ayXl5fseBLtxjEGX9XNOIxVjIqwWM6nXDa7vYqZwTSOgBg8TcNIot3xoCZ1VY9Tnqa829yamYEiswDmPM4WC0IqAGM3mgqg5aGj4Kbjvp7PKWdPPo1D6o_sCM2M8O7NbbuaE3HtefvixXTzQgTu3rxhRwZsMs0Xq832rl2t-nGIdXQVoXIuFquZj3F5__HYHclXi8sLNTGyMk51O6_P5pYTIxOzEpck5FiyihXy3nmP6ABMVZm4mrWmqIJSFJlc8OQolyKpGJiMmb0HMIdoaponDvXJaDkcx9nqvJnNp2IMWFUVoMvFqtmcfRAwDrWoWhU5tOxCXC6IAxGxc1k1LObVvNWuny8XVNeundXNggxBzQXvCPrDPg1jHvoyjpaSGbjoiwiQqZkhudBUZ2tlNQDyzDEiAiKAM3JI5PAEvSLCUJ0QdpBVkhkrAnDweRwJVXMpUgys5GREisTogWK_66q2zsehTCJlJDZTVare-_rXv_bt717dexQW7vlHn755-3ro-v3m7jiVh08fn13df_n5Z1_92rtffPLZOPSDysXF-rabnn328vWzNyIYnD978IgQi1L3dn_9Yls34ft_8o9899e-c7zrylj-3n_7T26uD9_4U9-vW_h7f-3v5ENPHhZnq88_eVlUYtvE2QI5fvBHv2XZXn72fLZcXL3zDg5D6g6lm371B9_74z_4lZevn__jv_8Pv7jZfPDhk99_9uoPfvijxgWH7fvvfPDBO-_-4q_-sf_r_-X_ebVevfr8s7vNdhrhL_7H_-bf-s__Tp4klynMV_3tTRt86iZLOk0ZSHwVxzHP7j2w6VDS0N8NVbOKTfv03Xcrco_eeefm7fOf_svfH4akOaFMpeBqcfXBD77_k9_6h6SS8ziNOcSaZ7Pj5qauIjkq3bFatcac3tzVy5nmgiLAqDn5ujYzKuK8LymjCDPLlCkErjyUYnoKfRmiAjF5zkUAFBGIEFClJARkInY-l3LaazCDlAJAsZ4h4diNyO7hk_emaXIhzpazNz_9zLeNiroYlERSzkMh58kzxcBNRGYmkJxVhNghga_CdOzJsYGBaMmTGHxJ1fHuVDSBJORZppGcUwAGJCYgMlNUQBUGK9OEiN55LUW0uIAqCMSEqKdGBJoWBSIkZ2JiAlBMzbctmYkalgyEJ6kVEVjOdMrnfJlcF3R8WhJRFX3baMrjcdApW8kQPDFyVSGqjcXGFJoIahw8gxmYGZAhMRGxFkEEEyUiZvIhGpiWzJ7REBAJUbKAqSES6YmzSZGhKBoaKBHZia-vQoHKlMEFHyoj5OANTccJFAAEckFRxC_fbqkgkpYM1pnSySEYqkZLIQJQ0CKMwOQAyBRC20ybnYqQd8CMjonZVyE2dSmap-Sr2hQ4eijFippm-tLRoIhkpagCEbsQAADZxdWSANJxQALfVOT9mKbF2RW5sLu9rufNYbMTE5Nc1Q2ZoGgZJ89UxokdgyqgmRTTgsXARfLOxRYdIYEUgTxqklP0CAy0ZHIMRKeglxlqyoBoAM36LFQ1mI7bLRJ_aWkwOL0NwFz0zGxGYbFQVcsTM5qaSkZEK6d-vAJgSR0iq5jzjn2AUzneE_vAvkbAk66OHYLBMAwgAohWFECcd65pkH3pBzU1PUGiR1E1CgYU57N6sYr13LuKnIc8ee8VhZjYhVgFVXOOmcP67PJw3I3TuHt73S6XMVTOx8sH98vU37553czqZr5mXx1uN3dvr1fnV1XVHPaHqp0P3UGRY7NqZ_PLx09UtF3Oj8djyYWC31zfzBfLWTsvaZKcTYwDx-CfPHnqK__y2TOq6mHIzz_5SDVrmkKszu893u8Pv_DLv3j7evv-N7_aLBbb2y15BqRqPp-O-6wyX62llPXDKx-4XS5SN6ZxJMmIYiK-YslFx2SqUMQFJzk7zyFUYuq8TzkXVfbV5fvv535g7_evX8RIQNTtjlW7MC3l9KDq42G7QdXmbC05h9lMUgI1S5NOKacJVU0LqA7jgD6AlumwL2NPgFlMSBUgtDPnqbs7cHV-n6xoydN-w0TNcnXY3Ryubxb37qlanqaLdx87qFOCWNWSlRhk6Lu73bTdl6lv6wrYxkNXmHKREJup7xB5dXEFZkQuD4KEeUykloYhD5MVIaZhc6OSHVoZurHbI1io293mdn1xb3F-trg4f_XZ58Ryfnm5mM2H4di2Sxewruuh6_fbm7Pzy3EYm-WyqqpqMbeS-8MxnHqxDqrlaho6Z6eHe_Z1OJn7EBGIAAhM2bs8JA7eZCBGQ1fEFAjFmCAd7-7evO77PrQNx6ZdX_X9qLvbbvuFj_NYxZJT2y4U0IrOmzgN41RSNV_s94fVoytu3dRN3telHyGXuAjsOE8Tu-hNqQzlbpt2t7nb72-vFYSbMAxHNV8tFgB6ePuFTpqGXmXKQ-fRuq67ud6SYysa65pQCbRdzEFhSMkHH-uIiMvVvWJatQtyYbZclqkM47BYXynAVPTeo6foiClqASJ_du-qXi1T34_dcewTk1cpw9iVnJHIOZqvLtT5OL8QBURSIHauqKIJEuEpZipJVX0IJ5mwERBjGdP6_uPmbD10PaIF74ZxkqH3kZEhdWNJ03jsRKxezB0HP1sOt6_Ix_12E2IIVdy-etvU7XF3cOQAwHvHyAbUrlbeB2WXxyySvYvjWNhRHSN4rpsZ-zDmPF-vp3E0H2M7DyHEWBcQROi6IQ0a6kpKmtXtoT8WgCr6t2-um1BNOc3aVdFsyMOYyXF_OMbo60VEgvHYkUE7W7jan60X7dlquz08fO_BetmaWH_su24qRebLJTlLY055iFUbQjWbz9rVWVIlZEYa9jcxNlrKSRra3x5KGks_kqRhuweOcVHPZ5fonWnx3qnI-eqsSC45tYtFkRRj64i8CwAw9QMijynt99vV2Tm68OrzVz5GKAWLTF1nBlZstb4_dAdXV-SiEpqC8x4JQUVKQnSIpiJTP4Bhc3YGBgDgm9qEzJgMzAA9S8maFQAdO-dcGgfJpaqqWEfJSXKKdTXsD2M_cB18XQNgzsVXTWgajg6ASk5hNismrgpp6Eou1WymWsZ9ryBpSul4TIeuv70r0yh9n4bjuN-bFh-jlOKC8zGQD0VFDau2ifPaxWgAIpnYsSdVSH2HJgCIwA49aMasUOSU6ffekSeOjmPwtZMsJkaMYmoIaoxIIsYhMHLTVmkYUupApUxJzXyo2ot7H_6RX3z8lXfJV8dp__r5p28--Xy4203dwByR8Hgc5quzV6-ef_MXvrPZ759_8frp1z7s-_z69e1ufxdj1e_vxn0_jXJx_uT29Zt07Gq3ev9bH3z3V3_h3Q_fub3Zbj76-e_85o82--6D7319-_r2h7_5Qyh5HIZRpHDs9_npN97VlAHjcjXbXN9uX75Zn61CjP3d7Ytnb7_xja__uT__69_6xtc__vzzf_QP_hH4MJbxn_yT3_74J59Oxz62bVE7P19_44N3_-D3f7zdHzevnh92I8dmcbb88T__yfqsGcfDOA77N285BuLoya_OHw_d1jEjGDmajnfDMQ-TfO8v_pnDTf_-h0-aefj055998dHPVFNwIU1dGfvU69m9R-3l8tPf_s0QYy4Z2c3Pz5cX928-_3i-PHeOjzfXcTEvKlqUPJmK5EyOQdUQQRBBNEsaRsQTV0owOHJchkmLWAFAQAQtgs4BoooikonAl4EXYGbyIU0JEGKoJE8yZUcc6ioNAxCHpl1fPdhcvyXn54tZd3dTtw17NMBpGNv5IixX1XoB3g9d70Ot05T77Nj7WS1qKsVSHjZ3iqpTMjWTAgDe-9BUKIIgZUpMhKRkgAAyJhMFUUJCJpiSpox8upcSEZmqgllO5qKvah8joOWcLGVgJu_YOWIUFRh6ijWeZjopmjOSMylw2voTWy5EAIZIhCe-Z1JqawXA4EyFvC_9RIwUGAHMAEoxAMuCpmZWxkzMKpqn7GMA0VPlmkhNjZwn5tM1wESBGYnJUZlyyYUI4UvYJiIzEkEWIpAiX6ZQiPHkMlXFqmJkkWRgMg42JTxxnxRQhJGIvpQmoNkp-2TqSOHkhEYCRLBpQuYTlQYIichE8jj6duab1oCIoaQkKYfFTMRCXbm2MRJAkpQsZZNCzFaMmEDNTgBZJvIuj1lFw3LGIU67o6RkiIaQxry4eHj26P729SvJBUyX5xeWJzgVLhE1TYQGIoioagjm57NpfwyzOdUVeTJTGXsdxyICUk5HDJMvBdjsnEhB9kSn5pIZKRICMTsvecrjcCoyg9jpcdfMVMEAkDCN2ZwndulwOMmCgIgdi4kjFhEiZ2LsAiKTYyNSAyJUMfQBfRXrBsCG45E9p2FUtWo2N8nwZf3aG6CKYcmgxiECAKFH55v1GftoRKbmm9lsuQp1PBx2bag312-b-dy5GKqYcvbeo6HjsDtu8jQB2mJ5Tp5TKrEK3eHOMy3W6_3ttl2s6qrudptcctXOgX2oIgAOOS0v7p9fXV09eTz2IxOJCrHrh6Gu6tXFGQB69ill5zjnbAaLxUo0_eGPf17P2rHvbl-_sjQCQCrFxbDd7M7vXSBSM6-Hfvjk939sKOR5GMfDfrNY3VtcrNC5ZtX2h8P21QZMhtsby72kyUxc8HmYCNFKgixIIFlMgL3PKTfLRZomRb54-DQlCVUoWbrtTSQexwLIsWpCW03DiM418xVCMSnNcj4MR5XChFTy1B01JQLzMVjOoarTOLqqIg6H7QYJqsUSHYB3FB1xMNMy9MzEFhaoYpIJVM3G4ehjSF1HiFqmqonHux2F0F6cB1eJlDRMPgadpKlYhn7Yn6oGLtZRc66aZjZf9N2xDHsXG2Bw3pHnOAsmxZAQsGorLQUsmcB4uEMF50glTX3HIYoYIIPZfLXstre7m9e3b2_qVb2_vQXkdn117-oJRdvfvN1d7453m_lipcV8DElKyZNjAEYp1pw99cFcjFXTHrfb0NRgSsQK4E5hNTNXR_KMhGIATEack7gYgbyWbDLk_ni8ud5st75p58t5szhfnj8NdTscbnf7rj8c1aCMx93NLXsfmzaEOF-uNAmjBw-apVkuYxumIoe7oWT48qCcCoGaCqoSKEDutpth6EKIOaUyCYCfrZaOqZ2vx2HoD0fHlMtUeZr67u2nz-u6sqLFRPIwHI8MlHKpYsiSm6rxMZxdXCxXi6qqZ8uVq3ys26ptwPTqbNW2s6qqyLnzywe55PXVwxMob311BYi3L39OYeG8K2Zm6qvgvAtVfXb5sFqeT-PkohdDMQXH5J2pcnCSsk3Z1FI3Ou-YrNv9_3n6j2Zr1yQ9D8vMx71uue0-f84pX12Frupqi260AIIgGwAVDJIiFQEpKIRGCv0BaaKfoakUoQiNRCokKDgQIYACEQ3TvhttqsucquM-t92yr3tMZmqwDjTco71XrLXX-zyZ931d-9XlzWq9GYYppWwIfOXSMBpEW_mSsg1GhBHUOmuQTGjG06lu6vNNaZ5mQ0iIU5ytDcdxDE1b8lzS3LSLFOfQBlHIhesmgDPzNFdtl0sWzUR4uruvl8vC-uzVy27TdW1XNc3d-_vN1caQpmGYx3mec1F98fJFyoXIXT-7GU59mouvq8P-6J0bjr0nM-2Ow8MAwCVnV5v94844a4m4yGF_vHv_AORzKtb53f1-tVn0-75brpqulsJauK3qnLKIxJJX66Wv63ESIsDgORVCNMYqmdBVrqqbRVNSnsaoBE1d1ZdXfd8T4difKl_FWK6eP_N1WF9epHlKpbx5_ebyydPl5jJzPkMcltdXdVPVF4s0Z7CGrAURdJRSiuNsiYCwZK196G5uZI4c2ZArMSmiMp9xEyWnarUkBN8uTPC2rquqdnWdMouibSq0KIUVQUp2oSpz5lwIdR4GZbHeg_FAztUBnUfUc-4CiZTZ-cAlCyAZ6-vah5pzRjB5GqfTkA5HQ2pJAaRqgypbSwggUnJmF7wKlynb2jkfQh0Aadgd4zCd23uaczoOBGS8O-eCtEQUhXmms61e2Tkj81zmmKekRcqcFJBzUVHOIkLkQxWqi2cflXkg4WkYRZicc7568urFt777i89efbB6ctGfhteffDr308Obe8qRCOYh_vZ_-HfYcJr4t_7ub4JK3S1GKWDJ1eHh_fvpdHjzyWd18OOxL3MEkPWTm9g_9MfZhOabv_iNr3_lyfNXrz758x_91Z_-xS5mt2y_-5_-2k_-1e89vLlNwzD2Ea2vrzb3r-9--e_9infm4f02lmIJLr72wsxpHkYuedWsfucf_L3f-PUfLNrqj__gT_7Z__tf7HaPIti0i_nYOzK7x937u-N_8b_5X11692d_9udv3j38L_-3_4v_8Z_-wa_8vV-vv3Gx--Qw9L3kfBxGrCoBEGEWaTarvt8WYQDJLJwzkv3WD371a9_5WtzvF2293d598sNPD_fbprX5eDweDsYYY8LXf-uX83h8-PytxGSsiTPXi42UvHv3ZnV1UeY5Dr3zprBwYSKQkiVF6wyoqIglY-sG0gwCZNBYwyzKhawvmY2zAICqzlhERSEXvPP-PFuFosYbIkLv8Uw2RzRkhLMlImNKYkQriKFbbZ489T6QMaykCbkAAOESSURBVKvVYtMtHu63LBBTrkJlm0aRnHUKlIa5qgNIEWHnnHNu7gcAUmFra8SMCAhULZdGmYw1iBwnNBh3e0KVcUBVFOaiaI0lQkXOs84Rz1xeUCSjLGiRlZEMhtrWrbMmxnh-coEqWYvGQGFRVhZ0zjhjreFUVBiJNGUDaBBN5WSeEQj03IVHFkVjXVUrAOcicQaFPEy-9SiKLJITWcMxGbJwDlaxWG9VRYucWwQEAIY0szGOWVFBjUE0KgUMAmhJEc99YQMAikSFCzqrKoR4zuEgIoICEQabp5G8Q-PPJ3xlljkaRARRZmMJibQIIUARkKI5n7sCIGqMPW_7VYWMsc7nUgjIWDrvKyRnMkaFRaFZLF1d5XFePX-SErvguXCckuSYp6QxqwoUJQeIRNYoIDIDnHNJ7gwmUgVlSf2sLGgNoPoQwAVy1f3bdwBy9eRVXVXzsC_TJDkbQOGEAuRsSaIGiISBJKtrGhCEkjlmYAZVPW85RM7eMWOtMCOCgiIaY0iFhUdAh0SiYukcA8tpipJmYxC_dBWfSbWKxoKqGhsWC54iz9F6VIUvKwdKooxEoopkQcT6KsVkXKg3K45Rirh2achJSWkaEdQYY13VXm5ifypTJEtkHTmnRb21QChk85x9qMg7RgvG-rohMrnw5smzbnWZuQzD6L31dRj6XLfVYrX2wQ_96dWHX2Epd7fvzwnzdrFJ87C5ejL2x7vPXrPktlmlVBCkPx6Ph91ifTnHXNW1D6FdXpBzaEzTdvvdDlTjNFYhxBTnOVVN6KrWOJfTrKD3d3fL5XL7uJ2ncRzGZlUf94fH23tP5mvf_N5hd5-ZX334UbNcVm0zpfn-9evd7XvgSA7jNFgyi8sr5Sgqh7ttnsZ87L2lud9ZkDJNIEIKeZqtc6EJeUqgapwVBLCGjDHOnobJmurp178RpxFBj9td7HuLoqhEprm4hJL63U7AuRBiiXHqbRWO9482WM152u0lJmRGRDJGUiFnmRMY111dAhIIV8u2zDEnBjW-q5WZ55mZtSQML7-jzCAqUowJYAxzts5j8CWxb1u0zZyysRAWS-crMn68e4Oq8bhHEFSwlR32J9fW3fpyTtxt1lIKqRnHXgoi5FJSvVjPu117c82n43H3GJpQN-00Ta7qht3OoQiKOgouqDWc0dSL9dWFtYu5TPPxcTieVLFetiVlFXPx7EllyPvu7v2nx8P--slL61wByGOfpl5iVINEIJkBwVi05DhO5EzJDNahMhkrLAZNmSJ6k8eeyQIaMoTKJSugurqWFG0wUqAIqFuYut1c31RV4GmomuX7159Jid7ZdnUFhk6noVlv6qYhpDlOJRfrwnw4WYtY2cwZLZze3HuL9SJM72-Zcx6nUNdoSFBERABd3ZY5V20DOWcB6pa-6Wy1KDki8zzOi82m6xapP2aW_b5fXq6crz766CuffPaZimLtnj59XlI8HsYnz25Knivv-mlGVSTs-3G92Zz6o0frnJnTOM5zmsuy7VB5GsehH-ZpxMLLdZ3meNgewYbnX3sZh7nMk7OmiObMbGk-7vV0II2SRKQ456SwpiQALOqairOunn3QXV2qcY-vPxt3jwaFRJ2zWrR79pLTlDMXLpLz5bPnp8OhWy9v375zzhlf8zTPh_3myU2cp1ySX67IYu3CXIpw2Vw-m6ahahfHx93q6WXO83wa42lYrpZh2cYhffiNHzyc3hC5mOHp86ebi_awPbx_c1c31XjqrbFkXZ4jWu-Cq7qu7_sQjCHKUxpOJ3J09g07S1wAmDnl-dQ3y-bDr397mI6hCsqaGciYz16_DtbUlV8vutPj9ng6jsMMRN57Y121qNu2JYsxleOx7xYNGd0_PEjMZddbNKELOSXbNVM_AHlr_Pr5jQtVnk-FsT-ebMlpmBi0u7gskuvVhlmef_Bk7GfOOeeZAGIuy-Xy_v1DvVxyiWjRCJ3u3qZhUM4--HmYnLGiqkZXX3_S_-RNmSZUJSIknOOcU0aDvq4L85xi27Zpmoz1CuKbRplt8AJa5jwdD95762qQ7NtmPOwJiVBVhbP4ppvH2VXOhmocegDSwm3XAMA0zWBMaCpEmPueuSCgNRS6BQD65aKUImnSaR4OJwOAxlgBdJjmEtrAAKmffOtKjOQMFEXrTKjQkORS5omZCYiLIpwNpNYg5jyTAiGqKHyJDmTV88kD0FggRRNAwIWgKH7RjMc-DYkIRLlpll23-fCbPxAbnQchTdOgufz8xx8bi3VTj4ceXcgFvvkLv9C1V7PEt59_-uTFlW3C659-6lZts6nuvniz--yRC7969SRnFuCYlAv_wm_-apbh53_41-uLi__wv_gdB2KG6Z_-3__55z_6_Nf_s9-MnAYe3_zwE299v9254C9fPInMp9N-uVnymOY5110XQkCAYZxP_XB1eflLv_qb3_vWR5vr9e5u-2_-9b9-fPfuzbv3ORfnfUYFtKHuSs7f_5u_WoP87K8-_5Xf-O5v_63_4P_0f_6_fPCNj3KTfu-f_enu9ecXN5eH2wfXtmwdx-idqcgaYwBgtz11m-bZB19xBNT4NKTH928RKY5D8GY-TqlMbVefjgNW3c3Lrwml6fjY377nzN77eZrqzYrIl2FsVqupP51rWsBqu9paU-ZYUiIpAAoiiEaUQRQQDYEzVeEZDKFzqqqFkZyWBMJQBECp7iwhSylZwKANFhHzFLmAdYYQOGdjCAnjmNvlcrm5GoZjyuWb3_uleZ5WF1e7x7tuuXi4u1Uh8pZFCFGAU87j8UiAwMA5TcejCwGAAMQ6q6hcksRMBoGZasdzxFQYEFWttSVF-DJLIsKszOBqCqHMkzWG_v3MXVjRkLIgkQCrGtcuwIKUAikXBBABQkQElrN4kM8iC2MQBQSAUEFhTuQcghKgEGrOCEjGirIouLZhb5FFCgMgcpFUEMQQAeCXai9jzo4szUmVyBobvKSomVEEieBLQj2df6si2FAxM2em4KAU2zTK-QwPECkgotYQGS0FzoguQlUFUHJWQM8iRRA52x4MEfz_VzoAYFCLgCUjeJ6dqWQghwCqSsYIGNWCioiqxqiCFDZEZwwoi5jgrfN5jr6tjQvDaWiWCxE-I8hyKtaicRZYOWdJyXgDgnrO3uRsDAkgkSFnOKkoozFIvuQJnVMAQFttrtrN5TwOyuwNcU7TfitaHBJRSOlg0Bprc06SMxKY0Om5456ixomIgEBFQPG80QIEVFFFyaLGAIKxBqyRXNAYECiFbbC-btM0MgsiAicoQs6hQQAEICkZiJQFfEOWeJiMdyoZOIMhNAispbB1FshwZOO9IEgpTbcQZRUhWykASokxkUp79YzzpEBVE453D8ZSYQldU-aoOaP16iyIkAtYZI6pWlwsLtb1otve3rdXV1eX1_Vitdve102XY8qcL5_eWMBQVeM47B72H3z06tNPPj3tTtaaum3224fFcjmejoSQpwmBC3OoWkN4eHhQ0ScffDCPc2F58vLDcRpSnNt2ITkfhvnFy6eOMOXSrJdxnlOaJRXJsD_s0jRWTX119eTd-zdPnj4dj6fV9ebjH3-spVxcX-2295zy5ZOnBilUzU9-9FdSsgeWMrdNGwvXXd09eTHev59OvQs-9idQIZUUC5KUmX3j63bJMpc5WudKziWJc64I5yT1uiWF07ZffvDcABprh-2uqqtpOHGKgMaG9vrFN3fbT-KYnCckSxbnw5EMcMrCxRhFtFIYmK3z8KWWD7QUF2pbL7CueBpLySXOUsQYUiDgwixqyYCiFqP1FRGpgrHW1YEICaHkggIKJY59yZMh9b6SnKu2jUNft0u0LqWiXHLKRFQ1FbBIntMwlsTGhVzmGPs4ju1q5Zs6uEDOzP1Bcq67xnpz2O_IGeds6BrXeI4CAMrCqdS14zTNw8gAgKZp1t36Ik7HPPWGvgSf3d4-tKvGGofkQWUcejQu56QEddNxKSmOqEBkiMiRJedLKTnzmRGHaK3zzrdgTC7J1ksMPtSNs9Y6cj4AUZojizrjyBLk5CA5mOOwz8NxTrHZrDbr1ePto7FwxpCjARsq513d1O1yxQKnh-N6tSJH45BQKI4RpFTLLu-G-uoCVGwIObHvujOYuEyzlsI5EYhCyXEoczQAw9me3bbK6tpmuLvNOac0g5K3tj8edg-33lobXJyHw3a3XHT9qU_jOA6TIBqFt5--2T08auRpGoXLT3_-w65dpBQvL29q79quq0IgY7_y9W_mFI0zKnj14oWvwzhN_cPBIuY4pnGYh6Fqa4lz03YhuG5zI2hdVSkSC8asZwaLsAhgnvrhdHJ12y2XDBTnLCAGbUpDGQ7zHK3zABhzjIcj-YCGuvVGkRQl1E3VVYfjoe6WQkSoruoWN6_qys8pnQ77M_z44uYK1T0-bisXVHV5vdk97AoAIPumquvGGGKRRd26EOYhWkebm6ucE2fOia-fXS2b9tifOCdjvLXQLdaHw-HFq1cs3C3Xp8PBWE8AnOfpNAhnQNnevT88bl3dqAhZZ1RQzXHfrzbLOaecStU2COq8IYLxOIqkmJIJzhKWIp6sZCVr5nESJfK2vbo8P25tHcbEVdu4uvWutbVrlp13fv3iCdoQVp0iNaHKqYwpNc3CWOq6xnp7_fzizRfv-yE3dVit1yomTdN6fTnsRkFYXK6RUADHY9-0bdoOHGfJ7EIAMikVF1oBRGMBdRpmKGINuuARwVnkHLUoAYLA-bumahfMzDmpMiK23QWCCEIp0i5XXIrkLDm64GywngBVLAYgLXEq0xiPRyxaVRQ6jwhl7ufjKQ1D7ofUj6kf6lVTpNTryl8vSh-7qyUX5pTJoKRoyOKXkSQLAMAFAJAQLaU5gSg5gyDkLAgjERCZUFEIZ1qprSqwBKo-VN76tlmgtajIUrjoPCZVvH7-tF1uXn316y8--srF82dgyjRPj_vH11-8e_3xx_Nx1JRF0fkmJvWVWV4sxzl7r8tVcAEX1zfW4cOb26qr0jS9_ncfb26u_v4_-i-f3Txtry7I1bWrvvqLv_Dui5__9f_33_3y3_31r3_9I5PLH_-rP_yrv_iR-uprf-sXbr5_-Zf_8i_Gh6NzLqXsGt9sVrtjP88l1J4VUyrL5WK5vpj6cb97RDQvn7_6T37nd7764QfO4es3b__b_8c_KTHutsdpnCQlVtXahfX66umz3_qNv_v2Zx_f3u7-0X_1H_3Df_Af_Tf_1__b7nA8HA6__z_8sbfoTTDemtC--OaHv_Rrf2t1sWpC2D6cPvzw2Te__a0PvvXVi-ubNA3Hw8kg7B7u5-HY932ektVy2m6rhd-_O21ePX_-1W9N0zBv76a-J0JCSrnYEFxd94_bxeaq3z9yjDbYEnPYrKwxJc46R0AkYVAGQ9YiGcMshgyqgoowqyDas4oLoPAZ_KqWFMhUDkRLKQoAqKQgcwLF80PqjL6RrDcvP_jtf_CfPnvxMrRN1Tbf-t4P-uNx-3j3-aef3b-_X22WT5-9uHp6mebMPD-8-fzw7rM8jZCyzHMexhKjIeubCkBAmBBkmmSaEAFVgIVL4XkGAZBiDHFOquCsLbmoIBiDoSZLqmwQRYsW5lzO7FslA6oUggu1qSsFzdMspQgIqIAIgKAoKKKKqgArWQMomiOAGkIQNZZAFEQI8cszpSFlUDLWV2cPsjCjCDBjzIYMlowCIgwo6DwZq4Z4nNA5v1hYgyVFSQwiSHiG6iAhFwaDpTBZD6JIhjlZZ63zzCyFhRlVyBpRMM6DMrCgIlnPnNWA6lnSDIYMEUHJUjKBCAshfBnxdxaIlBNaA6Cqej4bA-j59HJWRACgdQ4QuBQfPBiQs6ZXwfggLM4HIqOiaZr0SyBZ0ZK1RC1ZhgQqaIzCWTCMRATGAsCXewAwZ3MaohrnbFMLgBapFgspGX3Vba5UqN8dus3F8Hg3HfYGkRCqdiFa0uHUbC6REJEQTVheECkAcBxFRLhYb_XM_kcqOSOSsiAaZT3f-hD0jPIBwPPLB2NAFIqcZYuIgmhsXZOzZAwhMquKICjZUK02ZEG4KGdEYRFjDKEBEUQCQDSEzvimBUTvg7E-j5MPVWgXaZgUxHqbc1FJJXPomtPjjgi16OLFTdofNbMoALp6tdZcyHhVWj95Ti6QNdMw1e1qc3NzdfM8TbFpwnLZlSLO-dWyM8bmGJuua5owz3EehovLzXK9IqSSSpzHxXq9v7t13rkqkHHTMPi25sKry-v3b95vbm5WmwtymOf5-urm-dU1C1jv4zyXkodh6ofBOZNSJNW5Hx7fvyGVi-vnfX9qmybneDr1YAwoBO9Puy0RPfvgIwVSLffvb3kcm9o6S2RoHMb1k5uc4vHNa54jcOGSQFSFS05lHqwPZC1ZyqdjnhIRlVSEOXTN0J9UtFkuq8WCc6nXa1KY-3E6Ho2hkhOpFBbfLJdXV3naj33vgvehNs6U_iQpcpyJmFQkp1IKGcqZERSYBYFLQXSuW_uuzdMw9wOfkWJncVVJSIwArqpKTCRi_NVHaAwCujqkftAzvVuUUyJUTpmIjCWDyNOch8E1IZeIoIsX18IU2jadJhccgOQ5NRcrypEzFyXfdNWiQ5b9mzeACZRcCAJ4LsuGypdc4rkdwrD66AUmKXNR1TxnIoQS03DgeZjmE5F2i0vyrq7b4dTzNNRts7u7u3zyPObZVLZbXPpAFzfP-sOBmbvN0qEpLCUlMjbF5KrwJZ3MkCrynFR5jgORmMoqS54nUK03i-O-ByRT1aR4VoJzFgDUoqCKpZRxkhj7w3aK8ebFB1B43h_ycJj70zTMFEK3XnGKbVUt10vA7OvGLxpgvXn1Ap1VAWMp55wTU6hZiwIwq4r6ZolqRJUUeMpkLCGUYTBYUr-N2y1q0jyftidT-2bTeV9lyTpHcuiN7Y87Y83p4WRDFSoDLPNpvn39RX_Yd82iu2jm_kRGckqB7PH-AQ0dtnsVnaZ-7Pu3b29Pw15Yh2Hc9TOCWlvnkr31ceyN0fnYz4ddHE9aopZSchz6U3t1I8outK7rus21or94-tRXdX-YyIExWMap3VwsLi671dU0TaGuc8pSiiHLXGwVUNE456tQSnY-HHY7QGqaxjch1IGCw3N_q66PD-_r1aJpFkUAiRardX86tU2nKlXd1F0XqnDzwYdxmO_v901TcZLLD1_2-z0Xnqe56mrn3PFxP_RTzvHyap1Letwer54-KZyX3eK42ysQSHn_-l2Jadjv8zgP_WnuR28pT_n5V77y_tOfIkhBsaECQpEiLIt1e7Hudo_3rqoEtL24Fi7zPPKcbz56Wspp7OfQVEOMVduK5na9JHRhs2jbbtgd5_2BWW1wy6vN8mJVcgEsoalQqRT2TQPOXXxw3XTdPCRRWF9c1l1rvEvTnFMa-wnQXFxfXj-5HPpBhBftQkHAmCfPnlZdZ3wgV03DuLm-nE-n9dPNcdtXXRPaVgqjc0BQLxu_auIYfbA-BCnpnCLFc6R0mp3zXFhyef7qg5Im6x2XrMJSsmo2violk3FDP9arVagXXw4q5liGE4Bkjecarl_Uvqpd8Hmc8zCn40QIvqpIxHlCKc6HMs6alWOZb3slVOHYT9YHztn4KqWMxiiStYFj5Fy4QJyzr5qqber12rUNFyVDhATGKPOcxJBxzlPweZyts67yDJBKFCQl65wPlV9eX6-uby6eP7l-8Wp5ufJNbYNLkof-eNrtdvvtZrFChWnG5ebC2tXD-93Tl5c3X31eDL54-fL-9j5NM4Tww9__o_d__eOYisz6eL9T6777699_99nb3emhZInjyVL52Z_9uxjT93_wg-Ex_uA3f-lf_vN_CkqzgHtSHff7n_ybv8SUMke0FoxLpYxRkIyvfHDGkuUYNevD9oELXL54-Q___n_wN3_tl5_dXDiEf_P7f_zzTz69_fz17m7HJeowGSQBY8OqWXRfefr09s3nbdX-zn_y29_88IPf_Vf_9sc_-_xv_r2_vd1uL6421pFxtm7a7_3yL3304tmnP_n4_vUdiHz9G1-7enZBVXN3e_eTP_8LyXH79u3-9pbnEYtWiy4-PvI8Khj0yw_-5q9J5qLp8dPPZT4BmZK4FAXn28Umj32o_enuvXGGrJ_7ob5aQymp72WOrq4kJQQlQkTSM0DwHN5IhVOqVksyBkA0RxUAyUQEqHyWVQmLFCVSFucMKZ1dtioicVbGXMpifXnz0as_-4M_-OLzT1585aMnT55_8slP7rc756tvfvvbX_vmB0B4--7ND__kT_J82r19B7l418T9CXLGlBUQjLHexXHiufjVgsskcyISe_ZpFQ5NBYUNEhcWFVV1bUfeqSFTBQDE8zmWi56bfQiAqghEFg2QDwKKlrgwGEVUVYXMgEgGjUFkBuGzlBWJRAqwQEHbdVoyshKAFoZz6t6QFEZnhcU3FTkDypoiiUAqmDMhgDBZqypAJAJ-vUSUkpK13gQv80QiUjIRKgiKWOfPkX5FRCS0xqA1zglnFrXGIYGq5jmSQTiXkpFAhHNGJFAAAgUBBlsHSUzeCDOnSAhQVFWtMQgohEiI5xIAIjCjKhkLzGeeMAAhGT3LxAABCVAkMRG5uj2zNUUBlF2o8jTC2TGSCyoAc0kJhH2zMNba4FE1TRHQABCwllJEzzl8g0QAQNaJiIq4tiU1vq61FCnR-KrqLp48f5HiWNVO81SGETkjgBrKqXDmxeVNnqd5iO3mkrxjTtNux2k6J56sN1qy5gJw_iTQmXV6NpqgITi_QYiAyJwB8csfReEMqgIBRCliqwrP3fTMKoWsEQHbLVB5Ph7PHFZAQiRbV5KLKhrvjA95jL6q4xR93XDKnBMZCybM01jVTb1a51NvHSFZJCLn5v3J1QEBZYzKBV2gqiFHxlJmVetWz15475mzC348HkPXdt1mu3uoqnoeJwPIjE-fXBlrmrr2NuR5AjCnw94aarqOOYuqBdpcX7_-678OTTunwdjquD3ePH9unKvbhavbZy9fNG03DMfCGpo25XTqxyK8OxwlR2Up01i39u3Hn-xv70MdHl6_Fk510yGRiIzjuN9uL58_ZZGpH1RFAJqmBeAyzrnE_vHQrduS5pxLTjksmjKOyCIlkxZrjXLSkoyxqsWGpsRoDCgKcLHBndeXLFJYyVC9WaeU0jgjmaquyzxzmoFZFIisFLXdIjSNSty9fzDBNqtVmvoyTrk_KUcEMc4gIDpnfbA-wLnArULGMFC9vLBNNQ3H2I82GOusMoMUyQkzozVIpJxJVaSg__pvCwuk6INYwjyMaFHFgDGm6VL_QIpSRMmQC7kUW1VCqGrby8vY95eXT7dvPnWVTcNgrC39YMgLCluLiIymce7mxZN3X3xCwS8WF0iuKKcxgmYEOO331osUa4nQQL3YpHEC49L-MTRtTqMamudoq8a3S3K2Xi5R6fBwD5qE0Th3_eKDoT-6UMdpCt4vV0-G0_vD_oAA3oY4nwzyPM4u1GQJWEBUgL2v89zP48FXSyLnfKNOjo_HKvjm6mLcby05Y83ZkAeIJUYWnA9HV1ddW1XtepqOiSE4p4TCWHIEg8YHsgHBXj9_5arACinO53wiWJynMvSnpg5a8rTf5zQb0sLZGDLOlFQ4RlQAAMwlvHhR7t6yajxNSuqDs3WVpwzO1qEbUwYF4-t6tcJcbPDb7fb6xavhtCW0BqkUtd5JjLa2cZ4RnXF2sb6Y5mE8nKTkiycXeRoLSymkApdPLlMu4zgsVquqaY677Xg6tYuVM4aB4_E0HY7tqnp8_XkeJ1-HL5nCaOvFBWLeb3euaerlhUNsFwuHJlkX4xgPexeacTgsb14FUw3jmOajYS55zPMoIj74WEo6Dc1yjYZYStMs9_tjW7dqYXP95PbuXdM2q9XNPO7TOKOxddcAmjSOrNitVsaiDdXh8XD97JoLj8NgraGuHbc7Z-xpnK21zlZt03SLJuVJAU_9YJ2tQtN2XWbph2me5vVy0bT17e19ifM8DsZQTrnEsrpcdet2--ltaF08nMbx5OoqlrnarBbtRVU3JtSqcNEtEWhWfvP2TWhC04R0OB4e9yhApNvHh9XNlfU-5iKqXbuum0pUJGeyLo1jnKYnL55WlxtTVAH7w7FddAW13w7ocblY5Jz7YVxvVsZaSYW8Px32dQjW4MPDIwFdP11zxnma1dh-ODVd7cmVcTbobEXb7XZ39-BR0zx7b3KKnGMVQp5SUSZDZCgLe2fI4PD4SAUWT1-O29c5F5Cz8sM0y65tm-Nuy6jd8qLvD8EHTmMc5ma5QuvQuePjLjQBWKAkayhPiUhVypzU1qRAAsTjQM4b48h5j8V6Nw9DHBNZOmtEVVQRyJLxvsRSOFtjiYhVrQ85RWMdGWOdVRFmAYFz_Xfu-8IcfCBnRJQEfNuiYNV1zOlw_yAiQMZX4fCwrdar1XLlQgCjXbepAlXrVU7lsD-S0PZwNx7HcXfq1gtrIc1ZUZ11ru3WT54GdGipsRTjxMF99tnbYKCy9oMPvvPZz_-C04ho-z79jd_63uuffvbtX_rOPOWH_bbr2revv4j9wQi2bfeD3_yVn__5jzYvro_v7vox68JMUo6vb2EqUhKUMuWClRPG7vnFNJXlsmna5en9WwKMU6za-sWHH_zDv_2bq80aNImQhu6_-3_997vD3hDdv39PCh_84Gs__Vf_ztVhdXnzi7_8_Q8-ev7pD3-eY_yl7317e3_64x_-5epi9ezlM7Th9v1dqDwI9Id9tegswutP797dPnzve98Fi28_-bRaVg_vHh5fv_GO0jTZYE93j1VdpRx9WxNajnDzt77Tv9_znOfDKY1jIM7CyuC6JmdulhuWcbx7ADGWwNbVdDrZ0KAlEOYcVQXP1V1WFQFC5UJVjUg8DL7rTDCcmEQ4ZSkFUREAvVMWcE5TJrIpTcZX51mPpEzGIiGoGoTq6ZVMpfKLOQ4ZjatMnFLt2-__xg-Yy3a7Ox1P2_vb4-3OVtahgIgNPsc5T9k1NXBWETLOP3-SH3boLAHGnPPphHG2VcjjTN5ZX6V5REJjDCElTqgmVIFLVgAAQEWVLMwcI1mrhCCKzgmib2oumbPi2dMLxJzPXlgiQwSqoqmgMZIZEVSz-ApYKRhiZWbDisZJycAC3knJaEgEXFsjkIqez8QICgSYRQCAhQwpgKIBY8A6ssgxA6ENQUtBkDLNCIKK1jkF0cTn-wk6D6DkK1ASjqgK3iMTOUrDiKio-u9zxUFEON8avEIilaKoaKyeVwoKUDIAICkogiFgQGOZEwCQJQFAJFWwzvE8nc_655APWmJVVAVFcg5Fzs9tMGSdkzmCd1JEAUAULRk9p_oFFEUZLaFxxlpJUVgYILQtIgqXM6oBFbkwz8kEp4As2ZJf3FxPhxNZm-ch51Svry5ffmUcx9PjdrFs-odHgALCnGX15Gld19M4zmMvKYVuOQ8nayn2vaQZHWqRar2YH7bGoRZRPcejjMoZrQwggM5yycZ6NOdWsCgLkhU5X2wmdFaL2Lqq6naeeo1RVEHYGAvOmdBWq2a4fUAE402ekyCcGyiSC6ABMipimto4a5zttwcjaCuvaKz3xnkEIMT-4c4FF6cSrjfjw6M1ITRNmSeQbKxVH-IwN-tNP_YXzz_0TY3kvGoa-4ftfbu8ePG1b5Bxp363XC7ncVLAm2dPm8qXLIBABQQFkB7uHoI1w3CccwlV8-Sjpx__yZ9zys1ivT_tEHC5XDnvkVASF9VXL1_sD_vT6VQ1zWl_bJrG2TDsd9moJX345FMCmMeRc7x4cjUM2RtsL6-2bx9uPvpQgKcY66aLKSKaNA8GMc2TlOKMm8ZhfXFBolHisN1Wyy5NA3AWVcmZijhnS54RAFCB2Xgfxwmdk1Js5SCxbeo4TogoxtbtAoxN09Qs12k6lJlVxVl7Zln7tk2ZcyrWW-ddGgfhEhbLOE6konHUkpUyAYkoIBlXnV2EzlpVSKVUVS2uBsB0GmwASZm8ARFgEWYiICK1iFlE9Dy_M80H33fLDqXkGNM8KZKkrCCKwOOAgKBqLPE8G4O28ghwef10Ouw8WVSdp2l5dRGWi6kfYz9aS3kuoTLegXE2eF9ixqpGa4V19_b1eDqWOKYY5ynVq65u1yq2Wy85xRhzKYVFptPROlfiyMLAWteNcNIUOZfxdAjt0oXgnK3rKg_D6bDtllfKab282m0f0zy0zSZzmscY41hVtTOk5KBwu2zSnMocDZk8jVyUbCApoJLnvoyjI5QS03A6H1hsaJVLjLMWOWfp_GJZr9t4mnKawVlOSQDROWo9hQqLxP5oLZJqyXH38HDcPaQ5be_vjbWp5PXVCgsPu20wnoyGupUCVbsg8nmeT7e3aBwQSkpICP1JkUXQds45X2KWwrEfEdSh1dw7i-PhQCACggaW64vHu_cXN0-nfmi62hva3T1uLtcc0-HhmPoTktx-_IUN1pEpSQj1dJjqurl8_lRK3N9vrbHCvN8epjg37RIEueTKd7vtY9Us0_h4er81BFQKQJIUSYRT4jTlYbIGtORyOuShP-wfXfCn_ZHTzHOcjvccE89TgdQ268Izo-acmsVCgeMciczm6TNlttYuNpu2Wzx98RyMQYAUh4v1Rd8P03haXlzrl00yrZu6W66lJBvs_ee3zWZZSkaD5C0Cj3PiosN-UOCqqdAhp9R07ePtHZPxdQMgOembz98r5Co0ilo4gyiXvFyuXN2mnNaXTwzCarN4-OLt6fbRORP7sbtaG-CYoiHiiZcvP1LN929uN1eXSYRRyEDTdnM_nG53KabYT8vOlxTTMBqDItwED5Iqco_v7ldPLuMUQx3inLz379_dc-JT30vOXEpMqVusQ1N572rvSmEVLEnarnXBzkPPRdtFowLNYpnmaT6NU5yHYW5qv96s333xeuzHetkWAAVdbzY22PX1k5zK0699GKcU6tpXDZLzLiw26_HYC0jsp1IUykzGgGZVsoaQAJCMc6KExlhP82kkS9b74_ZUdQsfAiiCscwMqpV3NticswobZTLGtbVxpEXQYikFDXFJSkAqBEwkxluFTCRkrSLSZiGWhK0Hb403zjaXm8Tq27VfNc1yVXdNqJpcsqjY0NRt0yyXCoqAZLyr6vX6sm2XiGSMKSnNp2McJxBcXKwXy40626yX64tNMM4YrOoaiOZxINR3b98Px75-uiIBa6FZt3Vbdev1q29-98U3vucad_XkBRl___7tw89-EufetPVnP_ph0zWryxWqPtx-lktmALDh5be_DgylRLLm5z_6cd1W7z__bOwnjnp59ezZ9bPd9u7V175mLfT7Q78dTofj9rOfI4NwMca7tlkvL0OoJVMVqjwnUDg-7MYxWue_9Qvf-a__6__Zr37_O1fXi1Xd3j7um6793X_5h7_7L__t1dV6Hud5nF3TIjswuLm6-Y__p7-zWoTPf_bF0E8fff3l7_2b3_vrn352-eLpYnPRT_lxf2iaxqA97rY5z_E0_O7_-HvjMF9fXeZx-LPf-6O6q9785CfzYV8h7x_3JWVv6fLZs-3DoWo7oNqtLi6_-_Xh_nb32f20u4W5R5WcoWmXyxffS_2jpAwlxt2BiFywAJqmCYn8ojMg8dgbazlHjZMAkvPGORC1zlnryjyTsUWKQxsPvYqACLJY61QYBVQBRekc3DDuyyx7yoRn5ptyYeMCiqnbLksW1e_-yq-lWL7-N37x6QfP9vv9xz_66dvPPzk83sfjyXvAkiALz3OeE5Gp11fMYx5TUbDG8qFPw8yZjSGeE5Z83lGAJ1UwoQYQ8pYR_FUHWYgMAJR51sKIqCmBMPA5qG0QLFhLzgIRxwSs6IlUgYvmfE7ynD0qkDMUOVurkEgNKhEIACiIgoJhVgYumYwBoHOC3HhP1p3LslIySVZVKAKoiAYQEbSInpGgWDfwpSpMAVRLIWUuRWa2zhCac7OUjAUEICopmao6S3aFBQBs7a1xkhLEfIYSKQqRU2ASUQmEVjiRMcZ5RdUiooy5nI-YACgsaCtA_vKFIYIUZVEWNAgsqMAChGiNAVU4rzsAQUFVRJUMWeukiIiUVFzljbdhtZRchLMCIhkRAWMASFnRGgLIhclZWzWcskgBJVctlDOCoOCXKwZj0Rjf1sa5OI2lFEDwdWNcyKkomnE8WIRQVZxju17VFxdNu5imfnv7eHZ9xmEwBrlEydGFgIRcIkpRYc4JrSXjVAXp3OIFMhYtAiI5iwRw5jIJ2LrlnI05mx-scZ6ct8HG08GQAQBVNWSQrF-sACQNQ5nil1EpQCKo2iYOIxirgEgWHRE5Y1zJucRknEkTu7atmoUy5JLH_c5VFpBMCLauOUO16JjZ4JkX0ipSvbk0IVSLC0XTbi5Oj4_97e1cUtWsXn7jm2hoHKMLdR5GZyxZk1kkS3_oJZZxSm1bMxdR9S7sdtvLy6dS8t37dynJarMyli6un5Jz_X6PCv04BGOW3YK5GGOG0ylNs68CaN7f3U39wVl8_-OfqEi3XPTHozIjYtsuwSiXUtXOePNwe1-3bYlpHEZEhVLG_d6iefLBi3G3__CbXx370-PtnXBGgxxj07acpngaLYrznvNsDSpnNEjnkjaRDZ6sIQB0Zj4Ntm7Rehsag1iKgLDkiIKIKlnIeTRVs3w-zwcWVVW0ODzuXHA-1JKTUS1xwnNzRgSBiIxxHlTJGmVNc6bgfbsEQ8ZbyRlYjKUzotgQKRcu_KWAZEpn7hYIEKrpPvo-Z66qDh3GMfqKnHclRlQ5b9TOywVjrQgGH_I8TYcdGYsgLCWXzDnPSdrVyi8WwoxGASSOs8REhKpFE1BomrYDwyWnLKVbtIvLyzhORCSi_XHwoaIQVMV6ZyuHRkWEAAFRBVTU-RAs5hTT6ZjzDIjN8nKzeZHi6KzzXqdxqEN1GofD7qFtO2soeDv2x1x0cXXZLuqH2zsCIu-QEEntohHOchb7KQABc_ZVZRyFqiKDaIRjUgvkkYhc5REk9VPTNsabkgoR2K4taczHuXLBmMXcHwz59dW3DrefkiEfKmvAW9nevjlub-dUVNj7oATe-cS6vrhBQmtdSTEyOGeNs1rENQGBVYAsIZGkBKCgHCrPc9EchROn2QZX0kwgUz9yzHW3fHz79vLmqVt1ZZgunj7JaWrXa2sMGixjbxuHmowIEBprus2qxDj1c-zHUFVkYDjuvQuby6thv1dEiWkeh2GYdm8-XT57QlLqi4UPdjyegHPV1nEcLIGWIqVATirFeyMlpvEUyB7v7jhPRNiurizm47u3OfagFKfZVRU573zVLi8QkFnnaUJj-sPhsHs87bbjcKyqqhRpV9cqkyVrEAyRsSZHqRfrnKd5nLuuHU8njtPu_f049loK2nOv07etBeDjbkBLuZ-Mw-l0VM37-13btCKxDX6ehv12F5qQUzTGzONASHMcq3px--Ztt97knERUJSFJLnke-mrVIGC1vOA89tst2aDCh4e7w-MhppQyxzhrUR9cGiNrVBEFqro2nk6cJZ0mEPDB55T7Yw9gi8rV00tjLEJxwTVtM8dovLWVn-MAoFJkmEZUA4Blng-PuzgPgnK42xpjq7pWKKvNmoGGMV4sFsf-sHt8vLp58fDudp5GBDnteoNojGFmV7nL9dpVLmUGA1VVzXHMOYpCTsl4Z-25KbrIKYeu9c9uOGZmU29WKqIKSGCcUxYFJG9zKVXTiYpfLiSxr0PMaTqelJmklDiLcC4AQLRuNbNBQiJjgveuNgogeYqotrq-5DkaMGg0D5MyhMulb1246IyhcZwqH0SSYXAWQRVUOKWcoqqmYQalUFfjaVhsNvMwzsMw9Qcpgggogt6L4vNvfw1Y-9PJt3W3WFVt03ZNtWpOj7uH9_fxsH98--7w_n2K0-lu3yy6t59-alGEeY5xe_d-mnbWGlDeP9yhyOWzV8aaw2lcri6W683tm9dFNHFeXlx859d-a3N9iSi3X3yRWS82L4_72932eHV9mbn8nb_z29_59jeaZTWm6d_-4Q-b2r_5-btc0rA7TtNgrF188CrO87JZjlN01pN1knNdV1cX66--evGP__F__h__nd_4wQ--ExyS80DhT_7or373j_788y_uv_j8ix_82nf_7t_5n3zx5m3TdZvrm29_48MffP-73_7WVy3oOOSH_X796umf_fGfH8Zh8_QyF_3xX__o7vahXTYq_Jd_8kcf_-in71-_-fznnxnjnz2_evni1c8__omFPA_96eHRUZnGCcHefPiyTGkYp-Xl5ebDZ1gbcmb38Wdx16NkLWJDSGDaZ1eVt8d3HwsXBEUFyNk1TZ7G82zTt12ao-YMqsYYBBUQF4IwCwuJGmM1Fy0suYSqlZwMAZx5M6haMjnLubjaqUjO2VhnnEVEqhwUIWcQgQVC13nv-91jLnw8Hj_46rcQ9fL6sh_jT3_4l9v7u_l0KPNsETTmUjLlTLZCUVW1zubxlA4nMmRrZ7zhOYqyr4OCggiISMlypiAbw3ECQi7FWpNPUXNREc0ZRYlACyMhoigSOosuKKCtAgCRNQIApWgqxEqiKkIAWvSsQgcRAQQDSCSoWnrEQJY0MyqgwpnLeUbyI6KKGOuBrLII87k8cNalqXyJSbVtk6dou8Y4D9ZCYXSO06xFAYCEVQVYjDNE_55DgyjCzIqgNjSIYIzllECLJLbOAUBOMyEgAudinAfOxjjljKJghIiMdyKMiKCMogaQyBZVNKQAiALnkyogICEAGkeAWiKes_kIKqwsZD2SUWYyqHj-ukUp5cueAJEIo0pORQH8cknOknXnvqQi2q4GIhO8FLGhUgVjDaCWwoJqAGWOJSZVIe-MNSbUyhrqNvaTihgX0Nhcoqs6NPWwf2i6djpsSYuxNM-p7VZxjts3b4BIgaq6I2QoKY-DSgGCPAzGGJ7jGZAqiuRQUYHVVqEUBkQBFVZAUlZlBgREo2fu7dmDArbqVmWa8jT7uj6LzZXFOm-qluPMOX2ZfVIlIkAgY2M_akGqK1_XaMhWDYgAgJQCqibUvmkXV5vT_b5gUeEyzFXboLGMBsjZqgHVPCZ01hgrBKJgqsZVra1rY1wc-lKYrHFVs7p-5oNnZmPsatVUwRtL6B2XkqbY1cFYezwep2kW0TTnaewRUEpxlrbbbV3XTVNXoc5lJrRXlxtbVSrsqno89Tb4-7tbZynNadoNx92B56gyxcNhnuflZu3bpluvbPDj2HOeT4cj58KaD_t9aNr5NBjnQQoZGrY7Z0y1WkmZT_389MXTfhjiOFXeMmcgnY4nVSUDwbsyR7LEKZvgc0wYauFE1omoqnKMIuBXq5I1dIuqqoZjT6rWIhmahhHQkvXkgxrJ8SSivvJACCWHtsoxSkrGOs4zgEIp1iBZk7IAOQBiYeEigtS2rmoIMRUkJAUBFE5DGabzOr0UMc6RBQRFA6igLGQJVRBuvrd--TxNsbpsynEaHh-sBRWlHDkVQCTnpBQyznhHymBtScm4wAwMsHh6PQ1Td3E9D73xnkCnfg9jFCllGkgJSBfrmxj7gtbXlVmu0jCM9--9NymJrarN1RP0ftjvbGjSeGJhAuBS6quNnsY4RplnPA9KRE3TEOI8jTYEBYME1thhN169fHY4HLuLy1w4c7FaUuTNzbVV9_6Lt3WjdagLgLF2GgbO2RpbuKQ5umB8cJwiZ-FUXLCiggbP_wiOjCqUUlT0TMNlMs2y6y6fSC6nx7dlLmG5VE4gwKyua8djb5xxhL67HIfeuMr5GgwomjT1NhhCGg6nqu3U-rar62Yxn06ursHr8fU7a2087awPMg4CmvsRzlwEa61BViUFg4oEOWUlaFebkoqtmlSErAdCEACiZnWR4zDHqEqby3VObAklpe37BxMohMb5SriIFhZt1xeZc7e52L6_dQI5p4unz_rxZIkA1bmQOd1_-mm9XJbd3nvgNOVpQqL26lU8fIFgzhnENJV2fZH6A6BKATCkIlBVxGK9FREV9N0FAysaH1q2pfKNaCEwdbPs9w_G1fu7z3zV5TwbMoIUfBBOJTGqhrotObp6UbQQeiSwBtAQp0TWmcrHaSJjmbVk8jUaxeZ6Mx_70_tTddE4suKMDS72AyiuLi7G44EBXfBxztfPnleLZu4nY5BZfaj2D_cisn_cXmxW83jSkstwQqCiCiy2qoXINR2AduuFZfBVdRinZrUEAE7JkxnH_rjdEhjlYgjIGOOMqqYptxcbsqYIO18pEgJNw8E7R84362XJaf9w2lxtunXbLJr7tw_9blrfbNKUbp49Oe1ucy7T7mR8VRCff_hi6kc0GIdpnvqnT168277PQwzeljRp5max9OsKkjnsjtcvrwioCl6JOPHdF58tm3a_355OvQt--3D_wVc_mPp-2B2RoxFCZ2lhdT7bdfHZ11-iod3rdxLj2M9kjXG-zCMi1m0TU5mm4emHzw_vH43DHEfJwjmjnN0bKiIseN4AWCIDcqa6s4olhw4lCjkbS1JBzGLIMgJLLnMh731wKgrCuQgaMEgCELxLmV0IpRRbVWRsCH4Yei3R-YZLdi6QcdYHW4Xt_Z1x1DXdPCXJs0OTC8_j4ebFcyiccsypkAsTK6sUKZeXVy8--oqpmxKjcjwOp5zKYrW5uLqonfnrv_jLeciIwoDTHFdPLq82l5fXN28_-0zy2G8f9w8HrbpV214-ubx-_vxx__iNb3704vqiTKXvh_Xz7t_-i99_-7M3j3cPm4s1ixLB6ThUXUVoCDENKbSLtgsvP3ryy7_9my-eX7283mTgkpmxpFPaH9JnX3zx53_ww1ff-vA3fv1X_vRf_8FqdfGH_-4PlaiuFx9945sXy2DAvH39NgsnZVD9_d_9veHU27r56NnN9rDPKhcXl826_uSHP9usV8-__dGbv_pJmvLXf_EHee5_8tc_SX3_4isffPxvft8s_GJ5MQz51a9-F6bdz__0p_XVenX5fHf7Jo0ZJHebumRKzFdPnh4P_XTcLa-X091dqCpFGIfkrXOVnY8nBZTgkGyoXNyfoBRCABIEEkQVQRLrGiwRCcqYwRkgwynTuSaLYslJSWCMFLHelZQVSRSMd2eovCJ466wzcYy2a5pm8fD2_fr6Usg8e_4ha2q7BRn62cc_zWNfYuQpkUFrrXIm4vkwhkWnch6bq3CxzohAOUvEgFxdq4IQhdrzPHJmMF_y5iElUS0xG_ryQ3-exSohCuI5PanCDBQ8R8YqIKkNPk-DloIKyIJIqABEiqholJMxICznMzEaROOIEFAhsyBiyVpUzwlxBDFgVMnXAKAEUli0EAu5GhDKPFvvVBkUxHoRMT6oFkRDBkEKZwYypEVTMcGXMdvKAosUJmO_nL-D-rYrOZ9n0iICkm3dkPfMXKYZiliLYKzKWXKcjSEpAoSEBIoCwlAIjJRijVUVIVJVChZZRM-vFtEoKmoRAlVEZaG6kTgSWmEFg4SKxqiqikoRcIaATPCEaL0rU0JLKiBFFs-fDYdjPByb9UKRFBAR52G2FplZ0uybLk2j7WoCk8aBAFAQLZTCxnnObHxo6s63VY552G_r9WYeekG3vrlRtdOwd2WO04DKzKLklhc389RPp6FaL0tJMM0oGbioiAIronJyzopoSUzWKYnOyVS1My7OkzEE3gko5C85pKqKxoKoIKsgWWt9QKSSZmVQEiJSRQUgUVcFUJWSWFiKWO_1TBs05JtujmPVtYpUYipzrNoaijAzoDEhKKILjavDPEzKRdNEZDhnE9qiZv3i5eFh210s4sMOJKU5onGbFy8BEZ2dx8nVDRma-vni6tKGinMqLFXbWnLLrs7zbCv7-vW7tmtK0uuX1w9v7jTni5u1IVciv_v83epysdysVbkIv3t9e3WzGccpx9ytF8o8DWOMKcVkVa03d-_ed03bLrv5MAnmNEyL69XuYVu19Zn9hUB5mnzthvtHJTDGxLlQ221unglCHqOrqmG3Mxadde1qkeZpdXWZteQxlmkmwP39WyTrgkeUcX8wwChsnZVSEEERc87WGhHEEJyrgBCJjLccS5xn722JWXJGMgrkqloJ0dlp6IkMoVZNO8-zxGKdkTxpKqYyksQtu_lxTyQGUI1lUOe9csmZWaW9fBJjDE3I_YDG8jSTBYnFBDKICpinmc5qlJwQ5MyZFRYiBASsX_2iOJengnXVXV5C4vHwmOMYfKVx4pItkX75LwbnS7kgIlnvmjj11vsp9YquWV66pjIG5yFKzq5rTp__zNe1ClAptvJoLLNmBABSkap2hDpN0RIpWbTWhU6Bh-Px4urJPB5UhZwDNZBzibOWAhZLLgLGoDZdzbkIUt3UaU55TPV6EYtUyxUgao5TLGUYFlc3XdOpckmpADpDvq6R8bB7AFTNHJaL6fTIok3bqgCIlFLK2J_vcCaYMmVfe85JAYyhohHAnxE0DqmonLkU1vtcGFT8souHk3feL1Zzf7ChMdaLsVW7tIYEJfYj5wzAoe0YcLFYE2hi2N_feWcunz69_-wT5kKoqFriiEici1_VPEV2QLOqKnIRUGYxxiggkCPr1TmRTAxV15ZSrAvoaJ5m6xyi801lDJUpnba7pqtLzM5Z413JDJYYDDa1J3N5cZHGfr_fL1cbax2gxjkJQn_oJR4qH-LpocRZ55JSamorBhUwzwWNA2AXvDOYplGKKCCLuNoTgipyKQBGxCCoWrXq1CIbIl8bH1bra-FsgIryPE7G0DQcrHecStUtSGE6HaUIkKBzAmax2MQ0Tsfp6tUrJZweH8GAFg21d1W33985b5UliwZbuaoTziBFyQ77U9UFR0YUV0-u79-85cJ111gTSk6C5vrmsiguV8sYxVVme_84nQ7d9ep4u1WRfDpVy3Y-jeRs3a2LRDSm8vWLj35l--4vhpmNRURqV11w1Reff0HeoPLp9tCtKiU0ACkmH6oQGgWeY6qqhpxFVZEz28vFxL52rq6nw9GH1ld1zml9ecGc5lgevrgLdShxXlwuQ1vP47hYrOummlMkhJ9-8klt_M3TJ875_fbh8eHw6vmTcX8AC1VbpSxxHl987WtSuG0bBUDRnEZUUtbMujtuSdUgouX93dY5mMdZMlx989vHN5_MY1l0re3qMvUhVKfdQUHn08CluGDnYTy_0e1yKZytN9Mwcs6GNE8JtBChArl1k-eCzuA4CxdLWHKWIs4RESogEIhgjukMs2YGALR1jQhERKo5zudK4flrN07JhYDOgOji8nJ5_eTh_RtE6g_7qm4Naqg677yv6_1hzyUhqql8_3AMwaNqXfuYS_845jiHNmSgq2c3lx9-8MUnn7342gdUShZFRascWU73d-2ma9s1kbm4XJ7ut1_51e_923_-uzb4OMwvvvr1hugv_vJPK-dFyldefrC-6VbrzZ_83g9ffPjs5vp6l2eTqV6Gqg7__X_z34FkYQbmHNlYOHPZ0wyri-XT588--sazJ-v1sw-eS4lZuG4WPtRtVf_FX_zlfT_cv7nNOaL4tql-8Ze-GzjPMn78o0___Ic_-vCDD773q79S2_r-sJv74f7h_vbxfrO-GeP0-sc_BhIs-D__x__ZD__qZ9v7va_pD__F_2Dqi66rfaivrjfd5bM__Gf_7PLJZT8Vy4WMGmv3d9urr74YDsPq-nre3k-nvcHm4psvxodDnhNY-tLptrki0PHuVhRD7eZ-cN456yNnUgqLLu0fNeawvJgMKaq3Mj8cfWVlykpssGJFwoIEmjIhFs6GLAYPCBITestjREuGSAHBODQkKZ-n3egdIJVcXGhCG6b9UVgM2Wdf_WgeR7DG-srXnXB-ePt-db3e3z5wmWXOltBW3lia-37uex8cAJExoooWtDCzIBkERFLJCoTGhBJj_dXr-Yud4vlpiorKMZlzv5JIOEpiBSHrlYsQoYIJgWMi68HZQoRckEgTIwGIcMqg2ZJVAUBkRbBEhOdSPpAFg9YbPU_xM4PImR8KhQmBGYhIiYQn61uwRgsLKzCbyiozGAcABg1zZi7kK-sDWOAiMkxUe2XWkq1zIMA5Gme1gK2DFi4xAaIhYhVR9aFROPcXhOeIZNAQF_Z1I1JkjmQAySISi3BhUHHO5FRc3anmEhMAAyEUQG_gTD7F86wAkVTOugODHDOhAVIEImNzLkRgkFSp5EwWCVSBzlwcZgVDxhtSKimHuuZSGMVZR-gLF195E-rT7rTcXLSbzfH-Fr0r84RkpWQXHJeSCi8vr8b9dt7vrfMlZ_S2attcCqlz3qepJ-uFWQyRDZubJ1XXDocDTn3_-JinGVC4iGva0HVpGpSc876MxzJPhOcKRzbWMWdlUS02hDwlco4McWEDCGgQBAyx6vkCKcySivVegZCk5OyahQmhpFSmaIJjzlCScU21Wc7Hk_EOUxL-8simrIogRaiuTXCSWBRDWxtr5mGwltIcjaqt6jkmA8av1sb6YRrbZtG9eL798z813jLYsLlY37xkwuPj1hlIfZ_6Y2hb46pquSqcC6Kybm6exBi5SNNWKUZLJsVSLzrOZb1sj4_beZoZMVRBC6ec05x9MKgMAjb4brH03gGhD36e4hgjoox9H8fBeJtOc7tqxv2QYqpClaYpc26a2jX16f7gG8xZqtqnlLrl4vDw0HX1-QyZ5igxm9rngt3VDRCO_WQMoXEgucRsveFYTBWMIef86uY6Df3u_S1wdlWo2iUrO49QuN_tSorOe85pnqN37sz_GA67sFykYfbeoeo89JqZRY2lumuG3dHVgXzlfNWfjkCECLYKcehJ1VVdHo4ALJmNASIjrNXFZn54tBZKYhsqtTgfelcFE2om45xJU-RStEQV9t6TAWZ1bVOGSUrRUqgKKEwWeY6qCqxojSqDCppn37Chda6O86g2dNcXRuh03MkwkGYooKLGGQTlNJMhBhEBshZFnQv15ZM098bb6dhbX2tF9eoyncahH5rlIvcniLOWKGVGQ6ho68q4hlyYx5EsutCc7u-kZOMtIAGBNc57j0T9mICQrPXOOm_znEqJIEBtgDEaIlQV0TjP9WqFwmkaQMm0XWZ_9fIZkX98_xZR6rqahl4UUbFugvNOVeY5Vos69oMkVqM5cmgqY0wquak7AQULklIek2FAK2maS8maxdY15kkoICkZK6yqjGRccCWVUhgQnHWoCEZLSczQXTxNaWYbQhd8vTDqoeTxtDeO4jAjUSq5WbQgyKDO226xmk-HnAspK_Pp2NehKli4nzffebH74ae-qYHFhSBpLLkwAxGaps5JECX2Y7fZKKEq1IsuRlZCRDOPIxduF23V1P3tQ9U1eZwUsTDnNFVNMw9TvVmL0JMXH7n6cvv2r4eh921TrzZIQkWlzPs3b-tVe3r_YIN1wHGcyCEXEeuAFWIyxAgKoMZZLsqckIwC-q5Nw0xEgqgxkXfOOyklpYTWKCEqmKZloWa5UmPzHJvNWvrBEBweXhu_cZXVWHgaKQQKjjMDUhqPvmuhsKtXKcW6XRDpNEYMVZx6LKkIQ2JThbZbTafJWPVtkAJVqBhxHidyoaRCkK3zhGS8R6KYpQBdPn1aBSpM8zjaQAZpOJ00y7jfb559IMj9_nFxebl780XVtuubK065JA5Vfa6as-RmdXE87s8ATQMaqup42Clr2y3Wl1dxPg3HE4gAEaGJc1QA650NKBmGfvJtE6pWETTn06F_9fWXZOzh8XHY7jgXX1ecs6C5evqsXTSCHCOzwd3bdwBIxnjnlLX1Jh4PcZ6LaFi0glQvli6YF6-eb-8PCuRbQ-pOpx6JnCNvLQnsdztrfX_aT8PoDdlQo1HjzLjrb14-UTLHx_s0jHgmDxf1rZ_H0Xt_fNxah5vrqzhPcxyH_Sk4IuuF1VgniOvN-u72TrXwoa-XjZQIwogArEUYyBhfkQtowZGd-9RdtGPfT_seQIy1ynw-_ImiDYFZ0YB1VlXbRTvPUYGunz9xdZv7qWS2FquqVSMGLasUZ9M4f4lx7KrKhDeffB4zv_jq89j3aGy7aMJ6mZhznHIWR2qDUS79w3baD9NQhDgzf_i1byEnRDzuT3OaNk-e9NuDoKwXy5cvXxln5mm8e7z_xne-ctE0VahKyrcPjz99-3n__n53u4v91LY1GOdCnVL0vlmtl6uby2kqv_wrP7i6WVpjbl-_vr5e1m13d_fwwdc_4gI__qu_HMd82o-__rd_9e2b928___zt2zdQ-LOPP_HeXtxspiT32-F__3_4373-7IuPf_Ljy-vLaYjH_eHy5vrjv_zzu9s7v6j3D4f__H_9j978_OMvfvru4vn69Y9_crw7rjadD353e18tupLL5YdP-7cP-93Wkg1NN6f87IOvz2WYh73MPTHGzE-__92h346f3qKzhQunBIQEKIokyvNsW59j6S420-mIiovrp8P7L8AYpEqMUWQX_LzdkqqxlMfZtRWcZ-3WKmdOSoaUAMSYYJQll4yitmnLNBrrFNEQqUFATMceXBWaVkGatnv2ra_s3twe98OzD17Nff9w97DaLG3dECGQDvfbtq3HOG3f3RmD7fIiXC2On_w8sQZv_cUmHU-kylziaVIVExyiFQIrDAJQhIIticFbv2zmx0FErCMpWVhMMKSI55w1qHBRIPK25HwGSyJZNBa955SECEpGIkvIMZ7VrPDlwZdUFImwsjxFMMYYEgE0iiISWRFQhM7SACQAUGG0FkHPUGkkK6Kg-YyUV1V0HgCNs2mcyFlbBbROStKCmpMxhjmLFBA1trLGMU9SRA0YtERasiAoIiqRce7cYZCUmBkQkUhVCJCMydMIcLbTOi1SCqv58k8822FLmkWA7Hm7jWDQAApAKQWQQAX1DLo8w4QUgUAVrVUEEEFUKWKsFQTNxVgLAFzYeseCwmyCVS5krOSC1oKir5uUs-Rkq5pcAOtr7-I0xXG0TZ37kawzzhhL3rcx9SzFh2qesiNCg7lwydwuF9a6435rQAWMIl4-fxVzWl9ecY6Pb94ZSRInLgURQt0ZH07HPaJrN108nng6ScmgLMCIZG0lks6LnjTPfrGMpxFByZAAoAKBAYMlRgoe9KzkPdciGKxDsmQtOlemmTyVnDSyWy5d5UuKZZgB1ahKYTzD3RGRDIu4prHepn42Pvjgx34EAu99mkbrA6dIdRPqVdUtYopxnp0FmKYUU0oaLi5ffPPbw3FqLhYPn789vL9dXixC1ZpgLRI4fzzs6uWSXGi7Dg2djiejao3r2jZlmcajNYZT2lwtbt89SCmAmscEIK5p0jz7pvbWpJQXi5VvggoioHd-v9-lNB-3OwQGKXMfERWNtdZdPn9-fLgtMS8uL4Fgmk4lzeNhCm0dgk37U3AQ50kFNM5F1deVq9tmfcXCDJTibNCUeY5TDMGGVcvzTEg-NCnNIqqcRUEK-ypQcHXdKvH9z99cvLiYx5GLijCgNRaNM4pQhlRyQlFEVSlclAgMYL3shse9sdYvOgCcx1HIGEMmhHk4ESBK0cJpmIy3pnIkqKhIRhWViyMSLQKkosZ5Cl_G2OY-1l2taUJhLhmMSdNs6kZLlpSMNQSkoKBCoACgyMAKZziXKrqbrxWhpl2AhTiPAsaGtlpuxu2jd0QiACiS8jSiISJiLqAKnJGMdaEk6tbLkmckUkPH_cF1LdnKV7X1XoQ0jmXs43A0Tg2ZPM7oG1N5v15xYsTKu0rm_XA65Xjy3iIY5mxt8FVbrMY5L1brFGdUtJUtU3Rtk45TTqPMHBqj1uS5LG7WqR_KmKuuTlnJNdXFlfc2TfM0HBWgpHT55DoO0zxPoOxclePcrtYljYhw3B3I2LquFUQBfPCKKEXIGmDO04zGosWSijEehUO3imOPzoAAooLy1A8iYqybj0dXBTJGU7aN41zIWNstYlEXWhPq1eVKRNI4A3Oomv3DoxprnSGDp2O_WC3XF8-m00PVNf3-kPopdE0eppgZSnZB4xCVC4GSJfIErMYEKJIlMasyu6rKU3bB5pSxslQ1rGzIK0jTNWXK1hCn0m0ujvfvWcBZG-MEoCaEcfewuLgi58owIZrMxa8qUIfk6sXCW3faPQ67R-c9KasoMJN3ce5zyaJqBRyJIaNn1xKQcOJcSsZqvcDOItrUT2mcoTAIeW8QkNOI1oAKeV9YyXtFIutAxDetqoJKSmy99Up48SS_fVMgqQKSzePBWgQ8N5N8yYWsMc0izcnXNQKDqKvNtOuJfNMuUz7lmI07P4-VrAdAUzUAyPO4fvrRfHg_z7nZbBhUBZvVqlp102mMY3Rkl5vF2I-WrPNhGIY8T8unV69__FdVvUCietmB6DDMi9UqdDWAlsSu6cZ-uLm8ivMMWo770zzH9cW6xJjSmKbULDrnPALM8yRaQIVU5z5SZclUJgRhcRZD23IqVVMb647bXU4pzTOANMsFGcxzNq5xja2akGLa3j1wkYvrdep7zsUqV_Vmjr2rOuPMGCMCWofLbtnP43Z3fPr8SWgqZlgtu8WyLjFL1sKF1Mxp7pp2mkch8pV_uH0PWVQ1ztN82FVt260uwqJ7_OJzkXLcbrvNZeVBkUBhHIexP2kuRFS1i1RicBUYQ0QCBWIUgNgPrvLT4QQGFEphtr5SgVK0WS67q2X_5n4eBiTUUtCQohgl3zXGWKy8qloy47E3xuZYNi-vCSDF7EMTgkvTPMdJlPOUFxcrX9dn0S9KzkSeqK2qUFfCbJFSOU92vVocYzxsH9qq--znHzuUeDhhyW3n24trf30xbvvlxUaKbu-2kuenr56DBcjm-tWNN9XD-zeSJeVYtfW7L96tblaO7Gcf_9wZTJmR6JvfePmw3T9_8vzT1ztm-0u_-JXV1VWZ58WmpaoGUV_bNMZ-e_rGd3_h3ZsviGS7396-vp-n8t1f-s73_8Hf-Cf_x__2R3_6l_NpTwC-aXfv77vLRb-bfvnv_23fri_b6vXd3aLplusNom0a___5J__POWZU-tW_91sIZfewjaeyWtSlhk__6K9QYTzsCMA4z7kokRg0dZWPcXP95NnL5-N8eri7H7aPeZqqRRvaxjRNf3dvCpecxRpQQcIy9ugqcg0ZwcIp5rBs4zQ5Yy-vX-xuP1NRBjTLm7Tb1euQDkejaiqbTpNpvGRG0DMg-IxAnHPydQNI5_osWQOggEZYXV2hMBBqygXIVW1oOiAtRdu2VU2G3PLpE45RVJXgdBzScBy2x3bVYckuBBdcHFP35Mn7H_1FydytVmHRFtR4GjDlnCKzGGfBknUGkSQlYNF8DtErM5qq5hgRIHR1iVGViUi4oKohA8rnUVnJmZxnLmidC9WZ7VhYsBTxTsbRhKAxojAAKpJwMmGpkAGUCEVAcqQqEKuKqLCKmDMZVBRB0VgAOXuFQUQRQdFar0TKWUGBVQABwNUByaQcoQBVta-9NTD1k2S2njQXAZWcbKgBQVNBh6qGFMoY0YD1hoLTonAm5ZczsAaQGMCIKvC_N5HlSM4Kq3EOVVlYQQ05UbXeqzLnCADAAITMikQGRRFFFazXks15jCRC1omwsFgygKgGNRW0RrkYawVRmIG_tAEgEhAY7wSkTMkGz6m4EOrr6zIMcY5kDKgB75t22XX-sN-Pu95UTrMAoXVASNY1Kc1Tvw9th86TtTnlkuXpRx9O_WF_9-jrQIL1sgMX5uP0_KsfiMjdF685TQgMzARgnY1TkiKbDz7Yv3nXXXf9uzvOo3AxxuQ0mbPIQhUJyThEU0Q0M6KqkpIaRBGRMtuqIWM5Z-OcFEYCzuKapUEqIlwSGOVU0Frjq9A2GtN4OBGqdQQEHCMqgrVnTZsNlW-aYbszxgIhIJaSXN1pKQDJ2JDm6JeXLjRkSVKaTj0RQI5KjprFk298Z3v78PT5iymNu3d366slFBmOR9-068urz37yMQZ__fxJu7wQTinGOKfLmyuWVKY0HGfmbJDSeFzfrN5-dhdqJ0PPqdjK-c1lPDwiIlkrcpY6uvXFRkSmYaxCleLAKeWcqsrnAgi6WF8cHh-GaayCv7i6GcZjibMao3kugnk46jQ1XaUxp6k3ZMAYCpX4yhpfNd08zUhGQEuOyEqEvq1jP4Sq1pQzM6KO_WCdCXUAgcScI3er5Xh4tGSsp_4w2LoqhYN3AIoAORVfVwCc-_4Mz7DeExLHEYwhhcXF9Wm3K0UAyFSevM_DydZV7o-ICjGid1IAgslDRGdDu9AYffAl5VKSrwKDIjgXvIgM-4PxFlEgZ-M9z6OgVQCy3khWQFEhQEWRwiqCKkiISgBIZISjsc2F9zZzYYHF9TcdJXROchLO8dibytvg0BhO2Xibcwl1bdpKBUSlpGwdpGkAUVYB1Xq9AlUiMmhinKsQYp59W4dmEYeZjENrVQvkkvtjSbHEoZRJABigWV_E02isN6jkbU4zgjqDqe9JpcxzjlMcTmkcwGLVNb6rmCUPk_N27pO97GrXnA4n0oKKw2FPdbtYrtA6jkqgnDMoeB9yysJsrMkxgSL52hnfrVfOWRCQlEqcyxgVWCWXnAExToOiCqCtayLiktOpT9OMUoRLjrOzDlHJoAle5my9MQjCBVKWEstpAgDXtSXNaZpK0cJ8Tl7O01Q3DRk_x7K-ulHVUlJOScEC0M1XX4VFx7E0i8Y3VZri6tmTks6FHuUicUplHlmECIABwBhDZJwAGGdAynz7LjTLOM5SNE_9tD-UHF1TzcOJSMmgrX2oFrmkUDVINo4ziYgBydxuVhJngsxTFsR6VVvj_Go5nnprTL1cxpzJ2Gq1VmN8qMPVRT6NnAspcWEiVfTGYNU1VEoeokR2qwadt8aqE2Uw3pMxCJxnVhEiRC6EAiVBSWUa8zSUFFELlcwl8vEOJJGDnDKS-G6pBMbW1hhJk87ZGOU0oWSJo6KIMALOp6FMJykjWetC0DJLTlpSGXrjfByPFoF5Orz7QkG0lDj0vmpCY0-747kEv1h009CTq5qmqpr2zevXy83K-XB83K4uLparCy4zqRket4ZgcbEyBsi4brVCKSjAwqEKoBraBlhKzv1pl-a5Wy25pHkY5u1-3vfWEU8xzxMU8T7IFK0zcRxyzs36MufcLZqxP-UputqjJetcnEZLwQSoQ7V__7B5fiUs6xfX8-HE41CGUx7G8XhMuUeAksdxvyOL0_GeS1EEa6lufBkHFq3a-tOffW6N6adxfbE89gNZG6pme9y29ZKR335x-_bzN8ZqFWpQKqIhNPM07u_u0Jiu69DQNAzG2ZLLOMTu6sL4UG_WzXo5HodQN9Visbq4eff-7vL65uLmKRp37j_YUAliypL7bENom85ZNAQwzOicKFw-fbV59qyAFnQffuXrsZR5mMqYZM7TMOQYtfz_ePqPn9u6LT8PG2GGFXZ4w0lf_m7dUFWkKJq03RAMCDLcc8MW3DKgv85ttWTQLRu0CZo0YIGmRFIFVrGqbvrCCW_aYYU55whurHPVPqfxYmPvteYc4_d7nsaB6nWdTqflcl0v89OHj9P5Mr88a1l1Xc8fn9bTpcyXpx9-OH18kLJ41ek677rhb__uj8-PVx4Ch0ghLsv88tOH508fA8IQY0Sj1kJAc_v0w1MAz6lDQzGr61XKfH46S237N_cdd9fp_PGPv40gf_M__U2ZZgK6Pl8__vSzSZ1OixT44vuvXh6n27dffvGrL9-8e_ubv_ySd6Hb7Qrp4-m0Fvnwww9Pnx5fHpfvfvkVHeFf_rN__vvf_-GH3_7w1a_-7PaX7_7mf_r3__f_y__1w-9-R60mwhjC_nAYD7vj_d1wd2tW_4__9f_hjz-_v1zOv_rNX_74u9_-9Iff_d1f_Y85DbXK_-a_-t-mBP_Pf_b_2O9v7l7ffvmLr__D__v_Mz1f2jyRmSwFAGPOqhUoDLtjzP2rb7-4vHz8-W__fr2eiDyPA4bQ1lZeXsjUpKkZB96KZZRyiJGY0dQA0LG_2ddp5hzn6eSmYr5_-_V8fuBEaM1bQUJnBANyA_RWCueIhIrmBqHr3VxbAwIKhDmaYOyG7st7N5V5hRiIw3i8V9O072MKueulXMtafvWP_jFGBgQkPz88a11INKI66PU0jcebcX-odXn44Y8hxW5_dIJW63y-SC1aGxOGoTdVdJBloda8VFMxE-6iMyNCPAwEwDlsMVBEsNbQnZnBfDv9EwfKnQPGod9UyirWSiW3EKK35iJosAVp3LYMPxERgqAb6Ib3MVQAUSJE0y3Fi9t51w0D--ZfQgR1CiEMiXKUpUYmCgFDwMDIxAEBQN0hxhADoZfrhEzWKqgSUUhx49wjGOXgzdDMVZCJGAgDBmYgd9PWXJ0jA7ibozszQWuwQUVT3jCs6O6I1izk7GYcAoJLqyYQOKCbAxChOwD_yXLlSq6uTo5E7G5mRrwl_cHdEAAdTBrgZ2PXhiRhDlvD1VRS35s5pUDMqiCllGky5G5_HN9-wWBluj4_P-VuBxxu794eb982Le4CbrUsSBi6hMTj4TZ1HVPgGIms3x_n6_rFt1-9--Uv58tp2N3ElLqxN63z5Xl-fI5dclFwX6YpxHjz7itnQ9QyXer5BdQIwVSJCREQHRBNFZGYAoB7U-Lg7jFllYqI3HVA3MqKTuBoqmYQck-R67o4iZqA4vjmFVEMKXlrbboSAW1jXzVidkeOmUNwQgRSUQMCA1NztcgREOsym1Etcvjyu5g7B6vT2cqK3nKOSCHuDsPta3O_--JdHrvlfOmHtD8en95_ROJu3E3nc3c47G6Ph9f3Lx8_5X4w9X7oyzxZtbIsoELs58ePWuZaSrfL0-NHmydrJXb55acfyG06z-Z0-PrX7fKSU5Blevrxg2pFBGQUkd3trbTGMe9vxun0xCF2XTrc3a_rZX15pgAEIksld1ovUCuqOLirYghxf2gN91-_DSmt1ysxhRSJICB6LegG1to61WWSWjmAm6tKjBGRMAXVLfyzylo4oqwlpaBt7XadSQ2EUlruOEW21ggpDh1zkrWgVkBaT8twf7_OE4H3x313ty_zhFIYUdcJzV0aIpmBuYJpyDl1PUX21qQKMWLul-cr5951M3nNCI7ovharQszmAOoxkKvIWjf6p0rDGJAIVIkZcSNlobsRAYbXvwQkBPJAKWeK3IrkYaciRLCeT45x2I8B-Xp-BgcndABgtFZcPeXg1SgEROCuV7F0vEGTZVnL5fep_45CSIcdqZk1XVYrtcxLiMSR45CtVgHSZjR0HFJrrQuR1MrlxREBDD7f7MHBiR2RENCctRlG5i4FRWKYLpObhZyYo6kiMxBjSmK8P94fb97Ny6PVenj1xfT0HphlLQqmraoJgEEDZsKNrlsqB-AY55dHjpkCx64313m6MoaYOwCsyxpDCl0yKa4qbdUmeXcIKZgBckDQ9enZ0YnI2ooUnJMxISVHyl3fZG0Vbt9-lXJKfVdLTcPw_PHTqy--Wi4njmmerlrauN9dThd0AKbUxxRxadXmSoHn5-fcBzefnp-RYwicx1GLIJGpgFsTyd0u3R20rKFLy7SQKyJePz0f7o6723up68vjQ97tAgagcHp8Ot7epH54-ukP2DEJgbupuLS871uDtDseX92LgUi9Pjy6QDemmLvL88urr766vnxKOU6PD7KuCK5iKbKpQjNEBwVnpxAwZByGdrmAN3dta2VDIKBI4OQqpoqB3IwJAcABnQATE7C3zZLI5q4CnHgbWCJA4GzlmodRtAJT-xwLVkh9GnsCLOfZXIlTGhOatarMTGRlKjzkMtX927d1OoE6ATuTAXrITPT2199zyC8P59QPLw_Px5ujaOt2h3V6ZghEjIAh5Zenh-Pdsc0zhjS9vBCDOMZh1_WZkB1ZxPt-AFApVaXUpXBklcbgGLhOa2SKKT789Gl33A2HERDW00UVS2l3377Nt8fL42m_G8o0l3nu9jum8PGHn77_y794_vTJgzEE06YKN6_feOByOV9fnnMMWopqlWWlQGhOKYu51ILEHANyAKduGFKf1ioppcyhiCvA_n6PEPqUmstuf1ymmd1Diss8zdNMTLtuPD8_xG64nl6Iwv4wzNN8enk-3hyn65UR867T5vO07I_76_W6PxyKSJc6JtoPu7VNZPTpw89mmmPCvlvnKxkQ0fT8MF9nRI9Dx5DMcJ6Xb371tRMcD7dDl0Piqvb08_vnj-9rXVU8d924P4YUT9NlPV1iirJWa81MuyGrOeNmW4ZahFMGDt3Yr1MJAcfb22o-7ncAgUJcz6d2LRC9Sdvf3FyePpbnawjU9wn77u7urkz16XQ-X6-s7Rd_9p_t3t6G5Ivgp9_99jrN5eW533WYYmsOEH79Z7_a3e3E2-npcnt73O0yRXx8PL395ZsU9qSS-tyk_Zt_9f-1IjnkzQjrMvwv_ukv_9W_-NePPz_8g3_6F9_87_7z3_3L__HDj590XiK0LuY__u2PsY9d3-9vx3ldXj6d_qv_0__-l7_5zd_8zV-_TOs__Mu__Nf_4l_84W_-djwcAPm_-T__Nw_l8m_-X__8_U_vv_j-q6Y0n0-6FJ2u2hoFAAUR48gYyDF885f_ULCcPz4-_vATgoJ7ioQpt7kygZSK6ADg5hRYzZA49D2lUC5zCJtHUvb_q1-d_83fBmJOua4TosXbm_Iycxd0rbbOKQZT39LdbmYiFJKiggimKEVjzu5upXBOrVWk0N3csLNJnS9TSOHw6m6dWuCQ-nQ9XxC9luX2zdvD7at5ugKn-fnT-eElRg5MoBK7VEXNw5_903_w2__hr8o87273sct1bWU5AwCYAiE0ZQYzMtPc96DitTpAWybkaEjeKP359_7DjwCMIdR54QhI5GUFIgdUtdCPHAKiqxsaErPUKvOKOWwvaRVxbdj1IKq1IDESAxO4uQOqgMMme0UmNEcAMDN33KjjZoAIBOgIgWxDZLobMGMABFcLMYg5JnZ3JHJTLQKAqd9pW7RJ7KJIRfV82LmDiwOYqVgzIAgcdC1A7IqUcwjGzPPl-tmt5gpqJkaMFJOVBcwhsK6Sxt4BtQm6YmAzQyZoTjm1ZdluiNuL3TaMKYGrMiEQuSgiOBACEgcFBQR3QEIXcyREoNIgkINz7tzdVYjYRJEY0Ztq7HtKcb1cQu5z16_XCQi7mxuvpuDMYAax6_q-o9iBoagu0znGOJ-fzRwIwAERdze3iGGZrtpMycbdePP6i1qmx58-7V_dx77XptPzy-Gw6w675x9-3L969fLzH02lFh3fvuOUn3_4PYPbOm13JSCEbVOvAgYhZlVBc-Do1hwZmRHU3NFBV-mPR-xSvZ5NFNEpBOQcQiqlap05oSp1r96QWpkWl0qIJgLgHAiRkKk1oZzQwADMOaTu8Oa-LFNbC5SWUii1mbsD9Ls9pqEbRwR9-fCJdG3TlI8HjnFZbHz9OnTj6XK5--Jr0zakrkzTOl1iDIbIlELXjfubdV1DDiknZGZwqzKdz4C0XqeY8rJeppeXLmCpjRnXl6c-JzNXrYAozeM4UBpc1EFzl1Uk9b0jEREEPn18vn1942qnl-u7b79crud1nlPuwZAYl5enOp8RDIBRhVxjjK0WNwcGSqMB5_ub5XQ2QVfpj7vAIQQu1w3tb6CCzKXUGHPMWZFi111fnpiDo7eiMXCbLwG5O-6krS7qzmoqZQ25CykNt4fy6YGGvL7MaddJE10K5YAUu7udLLXOy-2bV6ePL62UfshmYiqmTavEFNARc27r4k7d_hDGoV2vZu6qnLksJYx7Uq1rZUSAprVSYACAjRgbEoZoZWprDSkzghG2uYz3RylFNhEYo4s6kpvHABjf_YWaozuxEzgBQYgYEnLeBBxSVge0tXGA2HfG4O7x9e359-_ZTdeSxqFNSwiEBK7gRIbcjQPmHAnXZda5Qoih6-sypdwBE6KUl4ubMJKaUGAgqssCaQgR--HgWlWMQ0BvGNJyPkGzOPZSRVVB5pB3AA7EDhgzh25sZTXDFKJq09rMHQOncZ-GPVBWaxzZm-ZxFLd5aTfDQIBrWaTp3bu3p08_TKfT7as3NA7z06fl-Rq7TGCtrm4OIbkqgAHg7ubW3S6nUw6hLUWlGXgaRtemrTlgTGzrAkiIoKXm8aCyuIETGCD3WQU4dbnbAbA1mVodDgdkdvGb-7tlnvv9ngjnaVqu18PNXWkVkcHtq1_8YlkuP_z97xkASjGrYLC1uS-XabfrANkdpa0hJmZfS4nEdVkAQZrRECPC_u5uenggjmZGIVyfT_l4iDmn2BUpDJy7tC6F97fy8EddVxVFgsPbd1VsqfrVL_5cWsGYL4-fZJ4IQMGXaemGPJ2nL_78e63L9flkTVDElhkAvJUQmHNnZnVZY04xhDj288vp8zBJzBXzsdNlNlMkAjcK3NbqHigFbw2JwIxjMnQkMlUXY1QgMnAGpMDaGqfYSsMQKbI1BU5S19ClmLtWmqkGAhN1DgDedckF3aoElmb9zY03taYmYugck4sjAQ8jd4fYj8y8zjOnKHXVButyffPl14mTopR5Rofx8Pry_AERkbg77DDyMAw__PbH46sjAplqW6uq9MOOMJY6dbv9en1eLnPiMBxul-tzKzUg1WW2JnnX577DOELc-M-4vDxpqQaEAZG4GwcwP7x9c_r4w3JZzKAbx93trbisp3Nby-HtrTb1ZvV6stqYA8ZkwMPdrbc6nc6Hm_11mlIX2yLD_VGKHe8OrraUSikyx_W6AOE0r19-_eX1cg6BKARwHndjvb4wAYUYYjaTDx8fDvuja9nvdyl10_n89HS6vT0gc2kldzuR2RTubu_I9XI6E-E8z60KhjBdT636dZ3uj_vASbW8un33_PS-tPruyy-n0zkPiRBfXi6H21tGXNbp8eVlvk6Hw2EY9rkfUtfVWq7nS9yNaAXMEGIifzlfiWA5T_M8HYZRpR3evINAH__wMyf6_s9_eXl6-PjwqQv9cByt-PnlhSmO3fjLf_K__Hf_-p9bazmn6_P53bff1eVyfjnVJsNuf7g95nF4-PDh3Rff9kMvuvzub__e6pKO--ePL9x1_e3td7_45vX9K7N2vszvnx_fvb457LoyTT-9_1Br63L3-PGlo5ByBIcyTTGGUvSrr7_66vtf_viH35nOf_83v_3u139x88Xx3_2rfyXFA2kOAZwwd2bxH_3jf6r1048ffk5d-vZXv1bVaamm9vz48PLx_fOnp93tocv7P__P_wkH_fTDH__w29-_fffKOT89PFyfP8VNJWrGMad-b1Y4shnmm7sY_PLh4Xo-oRSMCAb97tvp8tuAAaw5kq4LDyOIIXNrNY87UzF1AIwpSGnY94FZ60KU23IFdA-J951dVoyuS2FRilGbIAJ-hmkCcXQ0VcWYzBwJQBRTAjB3JKCY-7qWLR-_f327PTdiCGIyXS65T7ubuxA74qB1nk9P09OzMUEzZIwpv_ru2_d__DkNe_PSprK_H7TI9XQ2FXRlImSSUlyMCFUtdtGlgQEyo4MBqVfGgLGzDRCECC5YZYN6AxHlDkJSN3IDMxfRJiHFmEIr1ZpQTC5i2tAwjL0TmVQ3Q9siIUCmiOQuG-AxpOhmYIK2DY0N6U9zd2YEArSN8O2A4JAOe1kWpBC6LLVKE2Jy8g0QSJ-7tAgKTStjcEbO0VpzA6ka2EABkNyNEd0QkCgSAkGANs1h6B3MRcEM3P1zt9nA0c2BCZ0oRwAzMzTYttPcdbY2B3U1dADYdhaEMZjZVg9AAydAcyAGMHA0MwCg1Lu1P_0zkSmoIrOpYkwU2FTQwdWREGMUa8wx3xyX8wUdQgwqCo5x3NflKnON-wGJYhq_-Pb7YX9Uh7pMp_PzPF90nayZS62lDX2f-gEAamshxVIKxTwc7sF12I3T5fT06dPh9bsACKB1Wofb_aff_b1X4RzT8S713Xq9hOjr0yO2BiZuiAHRnADMbStrwOd4vpsDcBCpTJx2R2krxwiiVhtE1rJSTM6hy6ODT88vREZE1O9jytpaWwsntNI-3xgROQaphUKkvl-u63Bzm4a9uuLmaN-8HNc55RyPt1Ja3u26lGrT66cf2Y0Awc1CVvXDl9_EvuduaE0RIIRYrtfp9NL1SYod373d3785n54R0M33t0dXMZMyXa5P1-FmBJdIPL08z5fz5ePz_t0BjOfnT2wAYGpKgWPKwCF0g7ZmbozctDGn3Zu3y_XUqqTUmUrqkqq4mK3V0Jd5SV2-_fbt89_-Fs2ZWeqi68qEGAMhA5ipOcd8f_cZhD-tcRxSl62UtixWVzOQVlKfiJKK5MOBQyzLbEjrdeYYABzBU5fm55eu761WTGy1ABJRUKkqQhxCt5eyQJP9_e18vkBgdydOlAK4hyGupwsCqNToMe6DLM2sgZmKuhoTwZaEQ0CODoDGEBgi67wAUhxHcDVpKo0JtEre7VqpAOpqWuVzE54YCQhJa-WcENmtgVhtDc058gaKRHcE43B4Yw5EQAygauZuHlKsy-LEfBhdQ4pEBGU5yzpbk7osMq23r-7z_hg4uMHNmzetFGmWd6NqjcwiiiG20nZvv0kxiBgH5i4ihsAEHEwQtpaKGwGFnJEDI2oTd3Uzcwc34qhVQoxx7MHQREOXVdwB1Foa-8DYmloTpEBopUrgOB7fpnEPaPP5xIHbOtfp6lLdcJnnYd8H2HBjKTJ1fa7TuR93Kq6i8-lS1uoIVkvoYuw6gIApUQjSFGOczpd-3KU-L9PcjTuIPBwOrtaPe0JcTk8hZd9ozYCxz24NDGI3uhbR1qZZ1d0txA5BpZXxdmfNb7997WW9ns5936spp4Duw-F4Pb-M-8N-fwyBiHiZ1v3t27IsCLouzQDG21ex62KfpcjXf_YrkVpaWctLm1vKOUWOxCFQygEBy7RoLQQemaVVBEzjWOfZ1ddlGvrjcHOU-brMF3l5zl1v5gTGMdRlJTAkW68zpSiu47BPxwN1McZ0fH3HHEOXc8roHLu9uREnE4XIgBSHnZoaQauFmJpZK4LMMScpypGBHUQpUMi9iWAMYIoUTAkj8NgTAsUIxEBQ57Ld_dwAkbZ8G8C2LRdTBxNAQidCJDdGEtENz-oqQIDgLk1aQ1B33A7HUkWauFUiVjMphZAA3aSALOs013UZj7chBplLTrHO13J5phBMGoVQLtc2v7RlrbWEmAB4vZxePj2--_U39TJrbdPjlLroZuu0GjYTXa8XQK-laqnMQVrtj_syzw6ehgzkQATMHGK3u6vrVUuJDI4WIlLMw7jPfX55_FTO8-H-9tVvvmuX6zpNAREQUkrrabK1aCkhxNAN_e5O0XO_I7CXh8fWKpgslzOYAnngICIckyOXpYDY-dPz_f091Gk9nRHs_PDcmqQExDhfXoZx11yneZqmqZQ1xiBSu2EQF6ktD92w65uJuocYERGBb-6OU1ku58vN7THGPHRd7ntE2N_fpNzlrjve3cZIquYgHOLN_T3HyDGWWktrOXcf3v9U69LWElNGZOJuXdfL0_Pp-dN8OaexE_Xn56fLZWbH2-Nhv9_f3t3GFI-3tyF3u8OBYlDV4-v7Vqfr-UScKYTD_asUUoxZAcbdcLi9efr5D5wSEoc0NJXD_W1Tg4j3774c7-81xHVdjPj13ZuPHx8-ffqg2pqFt19-_fVf_Po3_9k_-PKbLw77PTMIOCI-Xl7O5-l3v_3tT7__ND-fyYHUtAk0Wdb1erq64zd_9ouvv_3FZO0__rt_-9MPf3x8ePzmF9_94h_96l_-d_-3Ydi__frdmy--tMAPn6Zvf_PLb37z7eOnP6xVMOZhd8v98PPPHy7T8tf_7n94-fipqd8cbv_xf_lf9kP3V__2v398__Hy-BRjaCIPn36G2mxtKhpyNoPQd2W-NjFO_Xj7ioJfX17K5eRm7gK1qYHJC5i7mau5KhKbKTEDuingRp134ByIwBzT7c5qJYNaBcycKAxdvVzRDAl9WRnJDc0FHL0pE7oCMkhT7vrPNdDtjW0GwAGRu07azIHAgYi1itQ2Hg7z9VqWCdExdiF2RHB-eTi9f9-mRU1BpDvsXJtjKFXGmyOEsF5O5taaLJdrCBQCkTm46ryiG4eIiPy5mAsARiFuZmITdUrImdjIKfRdu16BEAGBQuhHTNHcvBY0s1LQndAJoM4LupGjg6kIxZDGwd10WT7nfMzQAc02TDuoccjEkcIW-wFXBNwQHABAGBiRfLsJEDoBMYdxtGqqwinUeXWi1EUngNaQiCm4KCCLqKNzCq0WjhEdichqYUYA3_gWLoVCIOaNqarazAyRQwpg5qpu6s2IkBBNjZgAnAO7A4QA7u7u0ogDxeRm4OqqBOgKQACAAICguLE-3ZE-e7_gcxbIMRAyExOCIiKIogm2BtsMHxGZgUhrRdwEV2SOmxDYFZDQpLVSwSGkWJbV1Lr96CoAyDlOyzRdrwD2_Pz0-Mff9t1hnSctJY-74bAfxptaFlkXcJ-vE1IgjqKisp4ePqzn52F3QzHM55f1sjDK9Pjg5mkYd7_4ust5PZ2ZrTy_2FpBjdCREFRCCCbiDrgxT5kdwVwdCIjBJOTeTQEQzNu0cGQwlaaxPxxu78rl0pYpEKhSGA6Rk1SRMiNDa7rJqFQt9kOrRcUo9ZSHOIxpv3fEusxSVhSRskrTPAz5cMQUTCUNw7pO8-MnEiEGSin0w1J89_pdHEajuMyl63uwOr2cpqeHmFiqjXd3aX-YTi8OuNvvKVBMaZ7O0-nChMQ0na_L6aplvnz45G1lBnctp-cYQ5uvRISkWhqFRJxKWUCNKbZ1smU19DJdTCV20a1Za8v5wrkDALImtcjL32HYt6cXUFOpgSmlHRG2tXIM4KDEwDEM-9ZManNgKTUOUa_XdrlujkBX23jWG5wXkJt67Lrh5ojgsc8mLabgrUmpxCit8ebEMGMkd4dqISVtK4F0fT9drhRj6jLnThVigEC4PDxpEy017zpXUTMt1U0Qid05bJBbAAdANoPU9dzlUopKi7FP-x2qAPJ6PgHYFs8zVa8FVF0UUdGNCDhGa01LdXNC1rWguYgQbDdD2GI1TEzgSK_-Yrz5oq6fAC1QbGVxAzCgGPNuRzGcHp5D38cu0Nb2SLillJCCGdy-fUXmy_VCIVqz6XzhlDgFcyBEdw39jpmaeAqMMZVpccLUJQ7BydanCwZtl6uqBCBT48ghREDjkGpdiXhzkYEDp-gGqopDH0Isz2ck_6xgRESOn_V-27rQMO8PbVmkCSLEmMQsxE5MTZ1TVrHb1_eu9fJyuXt92-2OH9__vL85Sl3U0dR0nuo8ccyArqbgaIBdPzK7i3HAMq9NPXa5tTkgI2LsurZW1dqN4zydsYm7Qi0YolZBAkfiwKqNkFtrFDvCMLy6mc6rIw43t2Vew5Zg6fqbN6-llN3-sC5rU_vm2--WdWHOP__w-_t330hdCHCZrmbt_PS8vnwaD3cKfvfmvhZx8HJ5kVagtZTi0A3X6cnNl_MFEWIIUkp32BvHTXJW60xIYJjHvWmVZamt5pgd0daSuqym7mqqN2--ukzLePvac0RGhvjw88-JfZrO--NdiNiNA2JelwkgBmTzFojL9FKnlzTsRa2uc2Qyaes09V2X9vvl5QXBQMW1gQgGdlNHBAMkcjQwdzFHRArITruxXleOjI4GGhNqqQgQQtZS1RTUTI1DNEBiIuK6SkhMAR2cAmsV21bwHIgZEImDuRMApOjmlIblqYRsHJK01R1DDNyPdW3d4WCQciZ0uL5cujEDxflyQnMOnvd3MfT7-1e1Tst1Kkt9_f27WqtVA3MO0IqbWeqiGgJ5ilzXZmpSltR13TBez2czL9eJ2Ftt3dB1-_1yuhh4ZE59LvPcity8e1eWuU6ro9dl7e_2XsVNQQTdWxNKo0MzdwLa391yDG2eUs7X55OousPx7evYZwC4PJ_6nD78-DGhAqAS5T4TUGBO4wFc1LbPiRW9VkVmcilzYeZW67KW2EdQH3e7Vsvh9uhu3W5Q8WVeh_2uLksI6fjFq9ra-x_eDxFzzAz89PHTeNwNw6AEgPzy9ByYpRbm0OV0czhiwoeHp-enxz5FdJrn-fXru77vYhrATZrMrVwen9al7o6Hru-ho9vd4Xw6__zh55ub26Eb6lq4SyJqWgng5ePDzas7A-Rh-PCHP4Bof9hZq6eHJ9AVQg9aIXSUwlfffJdTp2DaTGSJMb358l0tUuZl2O2Q8cff_35a5iFlMSAMr96-3b89Sqnnl-n1F3enpxOKch9y6q4vF0WLjB9--EnX6k2R0cDnUv_X_8U_iXnnZl3OYMuHH356_8N7Avj-l798_fWb16_f_bP_9r9d5vrm23dlak8fT4x-89XtGMfL9dIP_d27V-RkXv_63__7-XKtajl2h-Pt6bz8-i__8vnp96ePL9Pzp5g7htAfhvPLueuHm69-uT7_bjld2tq63d08Xyji8e4t9Z3J8vzHH02rV-NMWzKdUgAVV3VHdgQGAFQVwgCImDKIALmqcwpggCENN_v5w4MBYiRZLe8H1ZkAtay0pVEBtSjkYE2IgZhMlIgANuFd4RSRyVSRKaVO26rI2hrHZE597te6xhgIUEqlHNZLe_Wr7w_3d3_3b_5_gTGia2mOxkTcpdr08OW7jf0wX66EzhTwENrTS7uuBGAihIhAQMQhiFZZChGCA6IDk1NQ8XxziwFkKTLNFBlUDdk5pLEHNCsNzKxUdHOEzY-LxGAKqgrgYjT2upbQdQjgIptUy9QQcWv0IrKrIAWirTcBaAbM7uCfcZf42ZRF4G6uBkhOIUbub27m69zWlZjTuHMV0yZrRTB0B8AQkyOKVAdwYKg1H49mtV3OaThordtSCMkBA6cUmE2buG8yY0QGrSBq234DkABVlSIjgIs5MxBvsQRz1aWmcXBTB2_TGjOho6n5ZhsG3xj_ZGD2WaTmWzR-8z0gGxgR4xYDNt2UzwAAHIDcDDB3XkpICZo0BYyEhCFnc5RaOEYwJaAw7FTKtj3B2K3TxKlLY9_lfexi3x-d9PGHHw5fvq0vz88fn1IkEck5alMxz13m1J8v5_3t_Xx5Bseh391--8XDTz9PP_3EkXfjXr0ZaHd8XZZ5eryMN72W2daZCbSqqjKBuhLStt0iILWGFKSsYRgxxc27Cq7e1MzNNBByl6WIU7z5_is7nc-fHjkgh45STxykVbHW1hZy1729LQ9PboaA7gqATjzevxZ1AAg51KW1y4kRvImjm0Hoeo55S4qHoW9FI4vNiyt0dzeiFIZ9t9uHlGoTRnKwVqq16tKIczoc-t2utKJNd_sjMHYhNVnKvJi6tKq1qa3QVitLnWfTxrGz5bIZ4hDJMUiru9ubUlYpMhx3ripVkAADUUittu1DkVJ5m7VxUHEKGCg4Ari12lIIw839-dOH3Me2rOYEmwdutwfVsO-teVuWlIgDg1V9npwJEczR3WPftdrcKe-PAq6iu-N-na7IKMvKBFortLbJNJm2V6K7KCI5MiEDu7bGXV6fr-Pb15hyPZ2749Dm2ZZJm3DuDUPcDbZeoDRD2wBN4BumBxCBIruBGoSuRwpVxNSGm5taKyNCW9ZlBncOCOrkACAOaLUREzjgdhshBCICdwcV5chSGjNDSlYVwIgJQzQVkIrdV_9ABRCsuZABMboZOiOQgXMOnOK6tP72FqQFouV84cS1VHADb0xhu73GnCmkVqpZTcNQrkt_c7BlAQPe7Wtp3W43L1MgEoO-GzBtiT9XsvPPHwE0hbAx5AKho0uphNSkhRAcwMEImdOoMq9Vuv0-Hm5hWjAlFFvnCUC1Kfe5y7varnUVTj0TDDc3FOH0w3sOOaS8Gc2Wae76cZ4uu8NBrF1P55g6SmF3PF6fXobDocxXIC7XCcEAnVOHCLkbHXV6OaXc5cCEJAC1rMQwXyYE7Mcu5A4NalnTuL88fkRwbxXJKQQmEBFQUlXkKLJ0eRB3VemGvaeATpyylorITSoQ9vujIahFB_7-17_QKkPfq4dpmZBQ1vby8mzaDofdy8PP5PzFd1-en59rtcAEog3w-e__ljPGwGYac2q1ynROITsqEqoA9oMjI4XheL-e3zOG2GVwUtB1mtIwtMsc-yRr9VYhBFDmxJyjYAq7cdwftJU2z91hf_l0Gl8dLqczKkKiEBJTDOQpdlUKAZq7i6XceZtNy_X0sl6uGx8moJODarEyE0c33ahn7rapbdBJrCGQg2EIrmpqph67vD0DVA1jCMTmRuCIaKpEbIBgyDExuWgFQEwJ3ADQS9HmzOBMm8QbTBQQUuCQcfPWCKopx6i1IjIQUwwGOd_cEjoDA7os6zKfEQSc0-54--q7aXo09djnwFzbcvr0EmMIiZk5jwM4ns9npHi4uQGytpauG9Ta488Pr77-khBE1WqtyxJzbGWp87rhvKypuIEjUSTC1PfrPAGSNYkppF3W0rRVxgiEhmQmIWUwNW0qgo7Dfm8OgYMpPD6e-l2nKqnPMTLHDsE33WSdZ1OJsX95fDy-ej2t7YsvX58_fCrzkscxjT0RtVJT3ymjLWtbS71eQk6AAVQwRnRCJopY58a5J4eQWE2R3HXTbbThcMAYpRSO3W4c1tYQTcXcYeh6qVWWZZW6XmdwA8LW5HB_QATiFDCsl5e61hDjl9__8tPTBxO5LGUY-m7IMeZlOvd9X-baHfbX07OblstibjknB1Tyfr_rYgpj_-m3vyOX3e0rAwqBKEVVHcbdbhydeBw7BP7p5x8TJ1XlGJfz5fTyos3_wT_-h8N-9KaX5Tqf57osYTd0u36algDB6vry8WNr4iKyFOryOl2_-80v7g67cOyWaWlL9Uh19fPlXJ-e1_OVAo99GO9v-_Hwx7_-berjbtf347GAuEDfxZTD6ek8rW3Y5XUtMK-XTx-MHAMSdV_8-i_W-aKlitTzp48BwQSWyzWm4IDqlrsuv75Z3n9EcDcPeZBWqmh3uDm8ebs8f1ien8kNrLoTRpK1GRNzIGliEjm4upkjbyNchL4js7IsMXYQCUyb2s13X1x_98FF86FrjpySbWIQk8BJ1wUDoKM7mCm6I6CBATNyYMLWJCKJCKfOVDbPkWmDwOreD4duP0gDbSsRSKl1qeP9PRi__fr148Pjcr4El7qubW1x6GLO5ha6TrezS11Ntn6Z1WmCVnOXTOu2zeeUAEGbmKqpEgcFc1FMqRuPxFzLbGsDAthonQo8jB4YAdr5wts8UBp-LpQBhwCOAAauANAU4rgzqQCItTp8pju6qzu4FQx504mBgdu2_hAyQgYFAKQ_Dc4dDJAAiJAYYyBOMeQ6TwboAPs3b9r1KrW4Njf31jaPD4WoYCqNc0KKnGK9XAkBANnA3cCcGMVb4h7Hrp3PyAyBTR1NQc1bcwdKBM23_jEgcGQTQyYIkZjUvJaVmYkZ1FyquxMiUTCtSLjRg1y3Xh-bGKEZkqkSb8UAQySgYCpMiMAmFZEQEcx00xjFqGYUMpBpldRnQNbaMCVQNREIvK0mEMkBupu9ia3XGscdAPa7gTjtdre1zu62Xi4qKmUdb_ZlKa61VaEU-2409GF3-PDh_bjf7-_uLg8Pt2_fSVmX63VZZr1cCRWJ6ssL7PdgOOwSqkhbEYmJpBRtGlKUsmy7MnAwE0A2lZA6jAndfONGiRBBQDAFbRUAgBk47F7dl9NibQUEVeiPt6baRJo0DMER9zf3bZ1bbWCNwE2Nc5dujyCoTZbLJQbEwCgaAwMymAtCiNHB2ryGlDnl8fsvnv_j75jDcHezzsvxq6-uz2dgmk9XM7g57tQtcGi1MOfDq9dOfr1M_TiUtbhj33eBCNzVlInKskot9XpuZdblrCJSG4ExGSG3Kt3hUEvBGE0aqMehl3m1VhHEgSBuszlGBpsWc99AlsRsABSIPTaplJPOa-wHV-EY3FQQrTXsxpAzoLuji2CMqNWmSWuNgVzBCCnE0HetVASmlGM_NlMkzkNnbdWyrvO0DdcZmAm2xwJHlrlS2IYDCODm6IDcdaHvpLTueFien6GtVgVzjCl6RJ0bMNpaNkyCgzW9Bt4hIzSHzxssAgTkuDGdzCHkzt1kmctc0IV4201G94LaXP4EF0Z0cCJWbRx4M-JRIPeNNEWmDkwOAK5IBEimnhgxvvvNhjF1NAJHwFaEiGJg_RNBtomnmKtZHro0DO6iDdp0DkxSVwYUUwDkrrOqKhIixdR1N1-9fPwJTQM7dv389BLGcbg9np8e7l-9nsuautSWypSpQ5XqZuU0QVs_z53cAzNsv_4U2zQhkiMwh9YEkcgRU4CA4IQxhZTAqLUi64oYkLmu19wNibhpY6AmhuQ87EVq7vcpdzGP55dPCCZNYqJ1LWa2O97XZe7GEYjVBcxAPAz75foi8xS6LNq8SUDq-96ZAE3VpdS2lhjRAPthgBDruub-ILoi4no6k5trMxV1ZyIMHEIKMbWyEoITqmznx47Qc3esywvF7BhC32sTg1DL8vab73NOh5v7c605BVJ0ph9_9_sQyOtSy9q5U4B1XvpxgH6_LousE9Vm9aKqDsSRvVQmMGluyMMgoIQchr5eJ0AgCBuIgwPXtZqKKxg4M6d-5ypSF0aOKTdzdzdCxHB880brenl6YrTUj9PlLLVx6kIOu_2xSrXQV9OOe_BWy3r7-g17I8SXlzOqxQjL-QSu1rTViqCgwogQYlsXdHVToIhEuIFXzQmcU9JSQ05IbuoqAuYOBkTmaEsJOZg7ooMZQiAmignIVbUtjbvIn7eyW-1MwWkDZm_XTeLAga0BRNRaiRJ3iblrZSFOG7lCwQMFFQkxgUraD7KuoMp5w9FGIkjDri4LIriIusncuuNBRUMMZlqrYKTxeCCitorUcry9FdVu6N399PE9Mda1goNJpZgocuDgSDq_yNLCMIQUYv9qPr131fFwI7VJa22tscsOYiLIIUZGRFWT2sq8pjHvjm_n6RKC564z5DJfRJwTA6A0BVUOoaw1BG2Xq6Wuy93-cBj3X55ffmpldWgO1Exi6hExDj1BcNcQk1vDkJl0ndbAYV0VQcv1wgEp9XHYIyIGSIEQ3NXLvE7zlIe0XpduN6Y0gHnI5Ib9bowp11Ln61mlEZOs6_TySOQcklYNKZep7m523KU8dK00JxyGARL72so05XG3LHMtCwJC877v3OV0nuf3P8DhOOx35l7O83jcj4dj7rvLeeZIblqK7F_fvHnzxh3E1KTVWod-5xhNWsgBhYFkOO4f3n8Y9z2oLNfVMeRufHp6JKhedLffpyFLa7dv7-u6lHUmwD_8p99fpnXXx9TF0_NlfzyINLLqtZ2n-vrNm93teL1Osi4AqAJLc8IwxNBlXqZlaevXv_qiXuv7H_5Irc3TBDG_-uqbm1ffqJYPv_9PaCpt3r4AMSUvWtqixbqbIzLNp1MO7kC7m-8uL781Tn03Ht7cnT58Ws5PoA3h8zweCB1xO22GjeayVM4ZA4OCghOFfByvHx_i0DsiEqm0mMduTMvTyZG64741sbpAE23Ckb00YEAK4ODmjk4IDmDuIabQde06cUr1OsecILA7KlgIkSnMTQ_HYz-Mu_1hacvzx09lWW7u7vph3x_2rbS6Tofb-9Pjx64fHj_83GqJ_dCW2cSZUaQAgK4lpYBE0iqUFXF7dYKIxpSdNsBDUAcTdWJMOe-PnEhq0csV0bVWdeKUUz8oEaEj4_J8jggABuoYEIC1FiSkEEBF3VwtHg_bnBtqa2sNhKbm7tvzn5ycGNAA2R2sVUcHdUrdZ_LFVjlQBzEODA7ABOaqnnYDqAGAqhtw7Dt0C4TrPIM2DNGabrB8R1fTOHSOzDEiYpvmEKLWSuAIrmrahLsOzAFd14IxcIrWKpiBGOAWWwDiTURs4PCnsH4kYsxhOV04hJCCm2sVMIEtU75NKDfcD6KbAbmZEzG4Obh_RgKBAxKzq25eQHcDJsSA7qaCm3EwBhGL444jtbXJ2vr73foy8UYaLZqGwUQ5B3dX89il_vauzPOy1OPd_c2bd2VZX54e6nW-ff2Gga7nkzswWDMtZWXOX_zql1LmVkTcmIhjCIHG8aBWWrPL00dk1MtUlwkg5j5jCOU6dX26PDyaVo7szTgmAAU3RDBia02bEjFECv1I4JCTTVdQUVEtl0ADgG80KHEBYgpp__rV9PAoKpw6Sj3HWK5nBYYQuuNRpUpppIqBORACbAs6CuSOVoupIoSQgpTVEa1Bd9g7qLbalgU5WKCcBt4dbLkyJySqtXLuUj-k_XB6__z2m69lvq7L4oaqrT_elXV2BMfQ930K-Xp57nKfcz6fT9YMwAMhglyfnsBWmyZVcW2fI3wxAoKKc5dil8s00ZYJlArzgsNAMVAEWYs5eBNQC4Gd0M1NFJCZAyI2BGIOhMgsawUmJG5l7u7fSBFgQDNm8rqYii4LhcDErVmMKd4ey_UEihi7OIzASaVyyuqqtci0BAbw5iKugoAOQAjEweriBkgbVgK1NU6ZOIXjuDydEADATBoHphCZutpO6Ohr29yuyBEouDmGAK0g04bpdQTkYGYhdxhjrZpT1x33db7UeTIDN4VWObDbZgBEJnJVQNwGEuCOjN4EeNNkGhJtfSF3ckYXwxSRCcTAnUARDl9zzpzG0I3WTloEtv64GLhQilItDr2tRQAR0RG7_T6nzoiff_f3lJgAGMFgc8BwGnttlUOU1uLxtUwXUTC3dDNkxPn5rC66lDCO4tb3w253W8pSaqulDocByirrHHK_6UIQsNay7WoYWVwBAJzdjZkQUMHQ0dABOe9uiFBrBeK2FgqccvRakchVq1hKYZnW7u6GPBgxEbeyHO7unn762VAjBWUaxz2gn59fXHD37pWudRjHus51WVHl-O7dNJ_aPEPTEFlb-dMzN2fmZbo0kRAZHDlncAwhI0dCanWq8wKgiIYObsohAWCIUdoK5hDSMv8Y0tvY97Iu4IYcOY4bxMo8pCGjOxC1te5evx1ujjH2CuAKTw8f56fnwMZayvk5ZSZETz2PowmWZcFWgUxqHXY9O7i7mZh6W1cTC-M-dKk_DvPlUqayO-wNvC6TGYJ4vj0wkLQWcwYFs-IGINBai4mlFMxJ1do05743MDTjGLfcjpRr142OWsVDNwJQ6Ls4joHj0A9NJYbcpok5lua1LG5qWrSsKaVai6nFACY2LyUGNG2BWL2BipmDOSG5NiIE5s_amA1iZ8QhgDXioN6sCHNwt209ikRABA7IwaQSIBBsNUQL2yoA3QzRHQiAOEUAUhEiQoyOZKpIqMvKY5d2I0IkxFaKiZKKk5iBI4ODAYQU1QE5EkK329lauptDuyyi6mb59n65PLiF4XBwt5enU9qkuACmrbUCAP1ucHVDsCbIkQNrWQgcpIqZqYdhNBFZSuqDizlHDkiAVlZzM6M87pEJQR2tXWZVCF1EYiQkchO1Ju6NYiJmjp0zrafrcH-op2tInWjbpi_aKjgiMrjz0Jk2N6lLtRCp63Iecj-W6apVURpy6nZdmRckQ6Q2X9PuAHm31tmq9kzk2u_v1_llbUXLmnb7uDvEfl-efpxPU-pTSoMhqggaGWpdFgSzKm4tRzaF8eZQ1zIvKyH0h7GsyzqfY-gwhMCh78flfAmRp_N8-9Wb22--mH56WstVm6lKHsd-v0cwiom7ri7Xy8enseuKmqnff__188ePEVNMHRByivNydfTr88S5e_f2VT-Oh8PNTz_8fq3SDV0OCRvNdX768Y_z6dTthtiNb756nYbh_HKuZZalWlvbUkJAyinlfl3m_jCu87Rcz3Wq737x3enx7K4RYJ5rv-9yygrc7fdyvVht5-dTbbUbMwI2bexwfPtqHHZhyHOr1_cfro9PidDcZa0UgpjGFEUkpKQKFAlF6lpDQHWnGHJO8XAz7vbX9z_X5SrrCmiutlHZzY2IAAK4sZtJg9C5CTK5OsXEObbLlZi564s3RjeF_f2r88dPRIFicAAE06VsrlxGAjBt5mqcIxJZE3UFIjBIfe9mYArg0izGIKrm_PbLb1LKHCP12dSReRy66TpRoHK97o-v8tCt61RKPZ9OX__iL_7-P_7b9XLJXW_WWikbelKlWSlSaooB0FylrYWZ0REJzYxi2qBnCOCIBtzd3aTUVxEtVZbZwVAbmBpxyB3EnlPStagImoAJgENr5oCBMCQ0d62mRojABA6UU8ihXBZXBzRU3z5tJgIkR3SkjQvp6kCb3Qs_l6SBkEF1O0YDgBOyAaIZwHYqaphz6AcnlmUNzCbV1RAw9qmpMAUKrK2qWBr3bsZ9Xp6fETGGaCrWFBEoZQcn3kYhik5IKMsETZ0BqmLgz-VnB2IGQld3MCIGBrft8bAtiNxNrRmaEbNKw7Dh_REQTQzRIJAb0hbyADdXdETe0vCG-BnG5IhmSsSO6J8nro6BzABzZo6cIgKs8-JVw9g5OgD3u0O5XpyAiVSFQhDF27dfj8fjep2_-O67n3_4w4cf__D9r_8hhYBg59PL88dP42FH6EQBIYq20KU-d3nYlbKUeel3Q23l4w-_RwAvhRzbuvb7cXd3J2ayLKZSr5c8DvPpiRwQkJi0FCBCDodXr5y8LaWWgoERvJaKTQABXMhNHdgdt6wqoKhhjBSjSGMiiB2nWGrzJuPdHRCDIfWpTlPoMpq06-yothbihBzaMjmYO8a-CzEB2vI457vjeH8jpYCpN7Gm3KfS1Jr3h9vrwyfO0ZpwPwCGr379F9P0Mj2fb1_flvO5lNKaAMbjq9sQo7SmRlIrOjBh7Ibnxw_DOOZxd31-ZAQTWU-P4M2XgqgmAm6xGwEQibS1uOvr2sAMgbSurkIxU59BitTGgFs7PjCVpWKIDhCYw9BhoLq2DYfrtRggh5D3PQABkFNwaeBmy9Vd0ZTAtBmGqEZp2POumz6-Z05xt4fYhdypVgSYnq_pMDAqmvq8IsM6TQTKqTOTEJO1pq0Ss6kRkTaJ-z1CwD6DSr1OuNnazCgGV2dXABM1MN-Ep4jmohwTACChqSAFrQ1z0qJp3HOXiYhCklrXlxeKBIxWK6jiNsIHQEQkQKfPskFGZEJAMN0K5u4OgMTk_hkcZqIcIzI7EYiCGbpiev29GJg6MXVjn7pxul7bfAkhb8tGdKfc21pp6FNgMQEnA-duIIPYJQ54_fiBU9RppaFryzzsb7Stm51EjG9-8fXzH37Uqt2-AzdUa02YUU0BMSFzn6SpIY6Ho6nUItPT79PuzVaGIgxNSgw5pq6tk9TGMbVl5fAZHEwhugog6paGBHAmctBlTuPeWhPVfuyAWcuahyOgi6hQWB8ecX87jin3gyPWZUHAUmqKkQgdUdSYc1tnRMi7nYtiAHOz1qw2dyNiAnPgti7EBKAqVVXdMY8juHFMIgYUAkcgR-Tr0_vduJeyyLxwTrC9ZYnVwAHDtlJoggjSjENwJooZ4nDz-n5-eMi7Y5undVk58Nz87S9_EeJYawnO16f39fQJWuHgKaa51N3rLzBkiP3y8jF1DNXmy0tgjCGqQWsWUscxgbcmUq0OXSfu6_Nzd3OrrbjUlLI59oeb5XxFdqJQytqWmnLahjGpH7QJRM4xApK3ZlrLtGwMO2ZCUaftjbeF9jD0naqpAqY83u5T6Im4ij4__YeOv445EYJq1aYqkvto6uAEWhG51drlUbys86qysDsSalmIGd0RafvhmQMz47ZUdTRXXWuIRES61ew-s-UCMnIAF7cqm2zImE033qhTYCR2AKTgrlZL6HpFUg4hZnTkyG1erDQKnPudlEVKISZ0a00phG1JyDGKNACkEJlC6rq6zOvpko47cMLI2pxjBPfQpdyNwFSuZ9eGCFIrIolB6jNjcLR2ndtau8MoZckpOHpt6hhS7lKfzdWbrS8nDOBiyMgpu7upcZ-1yni7R5H5vIoJI30udzoQKKAhsDkg89auMXOVGrse0bd2ERAhcNcNqmW6XCmkNA6U83w6bSrvfjem2IfduL5c6lrqXPvbvRUBd_B1ejpR4n6_R2lmBkhG5J8B5SiqaEYh3nz7NaxTuS5eq7kh8HCzOz-eOcXcZxOTtnbDIfWZwK4vz-t1UpFaS-wSIbiZNmUADImYMQYibJOAKSaapynl6AYYOMboirGPbVrqPFMkAKyGTEx95GYGmPZZkAz59du3d3evunFssr7_4eN-fzOOw9P7n18eH2pZ69K6ITOE49tXuy9un37_o9b68uE5DhSAQp8DgSxXdxDxuRWdFxz61A2vXr_bv3lzfvjx8nSJOQy7jvP--vSyTvX7_-I37__D388Pz6AQUsy7rpRiZnfvvoC6tkDXjx_n5xdGdDd0Q4CYstbmRCoNOGKM4-1R1uX6fIkEyIwxqDUFO968xsDXxydfFkIFcJNKRGaOHAhYtRHQ9jNCYjWlmE0aRSYMFKPWlZAhoFR14n4YzK2taxiTFjNpFKFdS0gBgVwbIm_FG0QHjtIkpGzaCMnUAMzdDfD29deAfnN3H0JclytSCIGrWZXy_Pj89u2XzPTxx4d337y5fXW3XK-__7vfmuj-1X1g0rKUZQYkc3Np6_Uq15kDwedbtUgTRgIEYtJWiePnCG5gmReMAVMfOObj6ODldGmlBELircWqYtTdHDGFOs0gjUM0EVTlGHRdzQBzRCYE0FrQQU0ICbcTLYCqOQAFJjUHd0f8PDN0CuxEoEYhAJGWhggAihzQzBFVFR04RPzsAIMtIMkhAcUQibq-zTMRqDTX7dWPqsKBKWVZCxLkbjCzPHTX8wQmIeU2T2jg6Gm3AxBz0FodAAS2jTFsLQXGbVIC9PkxS9ujtQilgIAQoosioYMjgqm62iZIAgdwV7et7OjqwIwI4IYczB3NIATXRkju4OZEcQPzgyMQAADQdo4R4uTmBh5S4K7XZmkcpVYHqHMZbo_uYEYh0Vai1dq20SH349DvRRqlXkG_-_N_iI4__fjHV2_fOdZylVbOKvbw4_u7N69y7qf5UpdyvL0NxJfLyzK12ze318spEkhdY5dNSgipGw9WKyI8_vBjPZ3SzciBdF0JQMVUjRjTbo8IhFSWtc4LpTjcvVoeP21aT4BN8wohpm1XoGLEETiFHGR7QiN3NwdtKuJpN5oKiKY-iUm7XLU1bwpmFIiJQs5EYZmuHAJgcDBVi_sj5xiYTMxqLfNF5trthzz2wL3UpcyLiOTdMQ77fn8kxrIstuEKwFCaKnCKx7dfuhZQS2k4nZ4RQZumvnegZbmOh726Xz89H7-4nT_9XJ6e0JWcXIUIpEh3e5ClqMrGrOnu7-rlRVsLDhAjcKzTBVujQACEzKYi4qHrDZ1TDHEo8wXNKUSKQVo1lTSM206JcvTSTKqtq5uCCyAQJVfzmJEDMjsYqKeu8xCIYxUztW43cOI2rf1tf_3hATZWaG0IxinW5UKxUxF0J2Zw55wRYOuoAJI0sVIpMxG7GISAaLBMsAXemFzd1GG7UjvEHNzVFVzMAyOiOjrHzQoa-l5F2jyTCTBodXQLibVWDGyqbk6EhOSu7ujuBODmTo6Ovu0U8U91IXdTwxAQt2a8uRozoyvi4SsKkRnNFIBCTBCyqiEjubYmAMYcYwyqpsVCCrVUA4DEfR66cceJHn7-kJk4hnq68JAIiZA4RJXlumqM-fjtny0PP5hI6HpZizVVLfintYWbMWPus1R1ZOKuIZtMMcaYQl1nRHIHjoGckLlO0_D6zfr4GBK1WqUKRSInMMUYADB0O4BaVwGHGNxUvTVjQiB0CLmf5xk5YoghRqnV3PKwM5OuH1W1G8fr07O0FlPgGKS0Kha7lLteaxtubp4-vo-EFDiGXrUymK6l1rK73T99_NSNnTlKa4QMABgZQ2AKyBEhmFWZF3JvdSYCcAiJTH372wDcVYh5G1FLK1sFQTGkoQ8UTQ2diN20OhESj7fvGgVm3h-P5_d_uH78GVobhly0icHrb3_V3796_vD-9PHj61dfXk_vy3XKQwdIFCNxkLU5YAgwvr59-uHDzVdvH39472AxYFsXQmiGgHTz9o0VSd1QyrQsJbAF5lYkpogcEHC-zilQTLHOUy0rcYpDtmXq8tjaImsTsxQjMBhSiBE5lGVBpBAjcCCMzFzmCaA6JjfjyF6WZtDtBo4sVSEQMoECIZpZ4NCWqwOs04XQiBhVKUWdV4oJ3LYBPCBSl10UHFQaJ_JmSOCgAMwxgjqaO6KpbIE5AEMkVwUiV0Vk2H5JBGbqHMQ8diMiE3MOsa7TupYNiEGpCyGAqoqaKncRAFUaUkAwNWXgrcOAW8I1kOhGysY0DA5OIQYa1vmllhUc3Bo0F9c8ZEdGxBAYIula8zAsp7MjghtFRmQ3YlD4bOaz2HWI3OYLx6hq3CUDQw9dfrUuH90tpM6kgogjEGBr1cVDl9DdmuJ20mCilF1tQ5q01gA4xqCteYAYO6PepTphQK51IQKMHThV0ZjiMAzUh-nTSWtDcE5MAaXMtG1I3BwSmDZpqoIppkBOAUpzE3QHc0MlpO2vdQQMXKYJE-3GvVZHd3GTWjmwo2tTrTUQgUtMSQzM3B05cJ87kWaAFGLIsS7LFvgCh2F_mE8nMzWDPIyvv_5qd3zzx9_-laqF2FEM4_3bupyXZWaO19PEMbx6-_r-qy_n8-Xnv_5PCMakbS0KABLy7fH68QOA5CG3UjGEOs0OGwx5AMaYclMbd0N37LRBKUXmspzOHOPl9NDt34CrMfR57G7i8-8_xcRd7EKfW1uv51MIwdbVRRTd1RgcEbVVJjJ3RlY1jCylxcO-Ow7L09VFQAUQOB2KTV5L2B-PX37RHh8uHx9TRGZta3N3ZN6WXWSAiMBkVZwDOBCBE6kqh5THHkQBcLle85Br0_jqJhBPPz_ELkMkLRVMdJ059rjxKwEhEYoBkKoQB3dwcKKYchatJHT77q0rpKF3kNPzSVX6fljrCohLbTHEYTiklK5Pj6-_-Xqdl9bK488PN3eHGNOylpB5uZ66nM_PL4wIpmjIKG62zHPuOm0Sh-xuDuitAZBKIwpIqE0oJc4dEoO6l7W5om8PCkBiCpEPoytolXZ6hsCEtLldObKIxBBtCxOKa22EtJFW3YC3d3wrgAxu-KcROmzcFlcipsDIKE2BEAyJydUUnbaM1MbuI9gUToAIjnl3hBDUFVQIzJq2Vt2UUkcxM4K5y1q6oeccr0_n1GdG4pim8zPHKOuCMcWUmAOwSymBubW23T1QhRDdARlcDZC3pIGKcIpoFmJwN21G2x4AHWibmCioAoE3R9rOIttUktCVAHw71PvnAiQ6bARDR0TkbafgG2eV8XO7AN2JQMEAmNAB1RVDinlodUVEDiH2Q10WpJjGfndzfzk9zg-n0OXd4WYtS2t6vHvd39xdnn5Wgy9-8WsjCEBOpFuqyeDjz38A0ZtXb6HKsk7nj4-p57bWJq0bxrs3X0zzyzpf1mmKMdS5phSRWVpLmetlCjFSQlQwUGpN1UzU3KiLBODNyEHJzYBT1CIxBdfmohzJHbcutan5lnqi4IhNLHY7SrE16fcHClzXBZCtVikTI3wmujBKbWaGgRB4Q-UCEefOVGxdG4S0v8ljbpcLmboqAmJELasZOTHFKLWFYW9O-bAHNRXVKodX92Zt41yn3GEIjtAup7XUGALFWNY67G9C7kSWftgBOICCwfXlcX546AICGhJrqy4VgHnoy8szhIgUOMTusD9__DlGJo5mQOTQmqo6GIZkTbnrDBGRDNlBAxFy0KbEGGJerpc0fK7Ue23AppeJGcEMArshpWSAGJJtvzlVoADg_fHoiHVekYgQzIC65IsQNy8KoNbEXNHNXFU15J5ysKUiY-DQ3G2pnKNKBTMAADFM7I7bIdxVmXzrbCAaIBCSgSMAI0mthAzb_3AEQggJMHDOtk6mDm6gzVQpBiYyM0SXjRZA6A5oioAGtOU0EQBNP2eYCd0APg_wgZh8K9WrmSk6UIzEBFKQj98CIjMa6HYRxZiJA6aE6KEf55cLE4AZ-Zbjg64fWjMKpNLU6XBzg93w9NMPgZHd67QQOSAiEQRyVU4ZCUKM6r68TDz2EaNKSX0PHAnBaivzhUA5BEAGThyjM0it4I4cY4itTOtaAYCJASCmZKqBCVK0tRqYlhUcYkwGYAB5d-CbV-3Tz3o9g7sjEJGZABKoYe4oJqLAkYnicj1zzIC4zEtMfeiS1Qqm4CIGu_6Lps9NihMFChhjiHG5XCiwlVWqhgDEwVXBLXYJATCkMi0hsayVc6ytAkDsBgpBxYFCt-_FZH16SRzaemFAFSUCN2FiTsnctMp2n4nDodaCeej3u-vLC5szcbnOnELqUlPJ_V5Sf_zmCxd7-O3fwfnEos4ed_ta4ebbPwOwT3_449DFkLNKBbFlnvvDTubF3UCEU0AmM-iOR1lnA2B0YCzTlLq0XFcO1PWjbMJ5gC3uwonJA-Ugy8oUTFsed82MiKbTC4qh1m2VzUwQc-q6cn5xtFIkhBj6TpeVGBzAKWyx2nI9m9Nw2JVllbK4KiFtJkgDb7VQDCEmEWUOwLThgZfphTG4NNqccWZuTkiIIGqARIGIU5VCBGiGTFoFEbXOTJ2YAgciIgBiNNHPWDoDIPv8riJyNc55W1VTTNaAImGMHKM1a9Mc-iTNzISQOAVikmnlPprQhi-w0pyUkQ0g9QMHmj498dCpKMXExK01cEBQ4kCIsRvUDNBizL4h2Fs1QG-iqpxSzFGk1WlBpBCQANwVCUHBzaTUkEJIycAhdlJXK2ruSIgMHBKYKXhMiYiYAiA0awFZCvCQIkcc-vXykkK3Xl5sXRGMYwY3aQ3BgcmaxN2gohgTI4d-N7-cY4dmKM1Dji62yQcBPORB6gpW27JSCv3-oO6xv3MWQkRErUqky_kC60KIm5hJ1FTmbn9HZhBDWQtqi-Po1qyaiITATZxT4pS1VhclMLCmBu6Yxl23H6TWOq8AYbi9na9TNyTgkFOfj6M1vT4953E3dN20zDFxwHC9np6enrwuu1fvUuoUtRvH8_NZRbsUiHmdphjzfL3q-fLVL745v1zqshzub89P57IuIUjM_bKU4fa234_92OcuE7GWqiB1kes06ToR4TKvxKQqBOFw-6ZJBTRTKVVNFVUowO5wrJeltCLT0u17q8Xd0BSItgkyI2zDV1MFRCauzeM4mIm1usFiECnvRk67sp4o5cipzJOti9fCTG4CSO6gLuEz8gWlCYaIzK7GgWSpocuO3H15Uz-cTS3mpKUAGoSeu1wuZ3CkRK7m2pjYRSEwJdBV0MwNOSUgNBUOscwLp3443qkVZk4hcuRyXbtdb6qt1mldAwemvLt_VdsyDIfnD-8Pt_vL46Oxj8fb9Xq9Pl0Od3uZl2mZA2FdV0QMHLU1UAFANHMEigkR8ji0da6lEDIgeGthGMAdiYnYVKnjep4Cc0qDQCvzbI798QaIxJ0ZZF2tCYETkwOatJA6WSYDpC1NqAJgDghmAE4YnIHcfTvEI204f3BHR4jBREGdQnQHB1UDigEBwNBNARw4EG7TQnKAmLs43tT5TCmSWROVeQYzjoGYxQ1C7Hc3octErmsBd3Cta9lCPnWaMabd3XE-nZEZmYDIWoNaHBBMaeNwgpsKAX6OEDhSzOaVgJDgT4wjNAUKEWyLdSXVZqIUCKQB-Fbb22ApEBjMt3z0xo9ydFf_LDPbPMZbvVr1M-yBwIm3c4cjOqL75zknbOvbrpPakCOohi5TCCoWQhru786fXl599_XLx0fTFji0dXXGrusupykN_duvvqoG3OfjzY1WaaII9vLwcP_qzen5EcGvLy_T43nYjcc3757f_7bb7aS262X96le_PJ8-ceymTw_7d69snrTN5bwAYyBfXq6xC26fsf7EaOrWGuXUpiWNHYKH3LtZmWYOiEClrCFFRKAuBgdTq3PhECglNTWD7vZezUw05cw5rucruLlJnaaQ0ud2NUcHl-ZxyA5ggCCNKDggBGqnK-2GuBs5RJmm-nxKfQh5kFoR0KQRc-p7QXRIod-VtQyHgQEv1ylGjv2uXM5bPdWaqGlOMRAXU1Xtht1498pdHn74iWNEpBiZI6YQp8ePWlaTGnO21rQ1bS32Y1tXc4_jSDGaVNi8xOjmgFJh-6YjqhqlGDlDl1QahlSmmQK5QUyRAsuy8ibPMLV1BdXAvOVfNi4WhcT9XuvSqsTEimhi3CUmRAitFTBw4hADI5pa7KJMRb2llNW1XiYkDF221njoQZuWRUvjlE1lC3cB_snvZoaOpkLMKhoSu5mKIrgjABG4M5G2Bg6M5IiApL79uomH0aSpmIswI5q6qZshsG8cRAR1I8Aw7G29-ObGI9xizK5bHNoA3d2Yw_a5bNJAZHJRislbBSJE0s-PJsf-yz-vTa1WTkhAaJ_3kgpOMQ9391bNQOv5igFcZZvEx5goxOU6h0hqMBzvpJWYu-nTIwZCa4wABNKEOIYUtlVvLRWZZC2cghl0u3G4vZGrAcPp4RNai5lMUUUDMwQ08xCjmsc8tLKKNm0rxcCccxcD0bpKSklbMXQvn9lknKJqsYbD69cMtL68mLu1hVLczpmgVkpLXWJMa1ljisRJTShEax4Po7ZiVeIw1NOpukemAGDu0jR2SQxSTP1ur-zryxM4aitE5O7MSMSqwlvmB8EAWlnj2JfzhIytSuyTuMduTF2PjrquMl9V1UzQLTCYOTMZgJsBE1ByJBHY39ymw75er7WUIN69fV2ePrUiLhoyVXPojndff0NaL-8_tJcXY0Km45ffQegup4-yLIyYul3u-lqWVhZAM1WtJTNzZAdfLkvsM4FzYAB3dwNDoNj35XwyBwXI_eiqPKZ2XQAodUmWhlv-lxkUQ98jUVkKBy2XKQUAA1lXIIicuuNdWy64y20qWlUNmClEkuvkKZhC3h8QocwTAVDKuBXR0E0tBG6fgRIMBM6InDgEFeXtkmC-zFeEDSJukUlFgAK4UuhbnYgDJTJVE6fYObqLkBvGAEjorrXB9sNjBjdidhVCcjMM6EDk7iGJFOJAm4uAYugSR5JV1_Oc--gmJs1VOQQ3wMSIUVTI7fP3JAQ1t9ZCSo7kahwiBjZ3ZrZqYo3A3URViXmjx7p66rOpIRD1oV5nQK5Nu11PKYNBe3mOgVRFVUNgAhKpxO6KFBiY1baIrmuriIQc3MGadrsduEptYi5aYs7oGIeuzmtMKe5GxRCamlhMUQm8iZYWIxvr9HQOgYgJMOhWXMkZ3VoRII6BTVqI0ZApBDdzcybEMdtavNR1viAx7TslcsEud1qVWtuaXQgC3UBFkLPqIiqUo9_d-YdPoupriV3iFENKBGxo9XpeL1dEzt1o0ngY2zKZAzEv1-X4-n4Yd9zH08NLvx_Sfk9Ey3R9-PB-vz-is2vBGLqULpeLGewP-zAOY8wQwjTNc1uDMiNwwMvDQ-hSJBavfc6f_vjx9Vdvc8yXp1OZl9AzhAgE3W7g0M_n52WZl5eXrs8gqmBOrNLALfWdK6hIrW0Y95SSVA25U1Sr1d3qPI2HGzXLKVmba2tWC4oyuhYBZiRqpQRGxM8xcY6pu73lkC4PD5-DnkgiAmBIgYcdBzBgqJXJy-VC6Ihu0swcOboDI0lryGRbhpnRzFAh5IyRHRnNmggBAqlV8MC7m5vldAIwc1fzFBkCtfMcAgOhqmwsdgdHRyQ2E1Uf9oeUB3Npoqnr2jzN1ymEEHMSM-SIgIeb-9vb-6Yyt3U5PZelJMa21ukypX1v0lAd0eo0pz5Ja0wUUsTIuhQ1RXBkcuI2FwoxMDp4SglD3F5nIhXUOSVykrW0WpGcAwEHB3exfHvctARgWqcZ0ZHB3dwAmiIDGNiWZHfnDVNjCts12wEA_XNmF02dkA3d3YgZNyqkGyA7oLs5ImLs374pD59abcGc-s6sqVjquuHVG2vW7w_N5eXnD2RqpltVIxBzQHNTxXS8a8tFSwH0lLq6TFuYHsC36lR_f1dOlzj2LqLmas3WmgK5mpuAyv_8B5N7cwRzDNFaDSlS6MwauIEZOKg7xoAOGNhF3IFcwcFFkcHVgehPjH50MwcPFCyw16bgtMHIP7tMDZjdzM2AN3qS-naOBndHkxV4S_RFimyiAAAGlLKrujkSIafdq9ebdau_valLNSt1KdNl2d3sdrevpMn-eHCAu1dv_vDjH8tczJzRdbk6wqvXb4fjm4_v_365XIfUL9N5uc6564_3991uuJ7PSJD2o4i0-Vqv83o-g9T-uKPItij-4i_bX_33IspMYg6RECj12VW1NVdx3VxnigCE2ETcnPtBlzUNHaM5sqluh3jiEI834U8wDJHqa9G6bu8jNeSuU_d-HIEZiTlSq1WLgLubxC4DoywVHcPN4BUQWa4TMak0DtnBAWyTatamw-GYx9tws2-XyzIv5XSOu33O2VVizuvpJXa5raUbBm11KaXbHwHDbr9Xb9Nl6bsccyd1cdA6TcvphcC8qkgNMYhKSAndAZ1jcAoIpCLeKgUkACnVWmNCawqR3bC_vzM1EwdQc9OlhOMNRgIPej0TiG-jd0QtKzG7O4XsYKYQx8HU_pSpRggsYq5GRM5I5rzbt2UBAEZyc9CW-xtZr_Pl0h-GpupqMURkRBIpgm7e5P_f1Jv0WJJkWXrnDiKi-gYz8yEiMjKrulHdjSYXJEBww_-_5obghlwQTTSrKiszw8MHs_eeqorcgQuxbDJWHoiAwc2eqcpwz_k-hJNo34-yLjNfE-HIoLL4sRH4_ZPVQjJP0TFNZEQE1uiDmTOcVSMiqYBZSpt1QSjH9iCGb5tyejBYaDmRPSJ9Bsk5wZSUCCDnlwISySR1PWdEZGREDiemGAZOgNJGRvKyIn3A4FAWYvgwwst_ksrkzuzeB1REdE42QRIRVJZ6XrlodNvu9yI8tq20CtZxHNoKibTl7OnWo53OKDS-v3rfhCIS7ial-DAmghYm9kyiqHVxGzF6UD3_9Lm9XG9_-dIW8a1v95uKUJJzrO16jCMJJEVPZezDx_C-c6bU4s61tbFv4WjXNQ-bDaOEJ2CWujRtC8DH9kYWTGnmmKpxISG2PpJCtEQmSQEoMu04ZG3EQlMBcNxLaxmI0VlJygrWWhWij7fH-WUdt73vD-b3UGlEFNF6OvnwyERSZhCzR5h5USEhLcWTwKpVMjOJb99_NBD8iDACJ4VblPVUTqfRB4v0bavnJ61tf31FUDs1yvBA7D2jJ-fp4yeXhdvp-vyU4f3Yj0e_fHxB0Ovvv5W6llVFl-12u1xPydr3-xj9-5e_nliRaccdrJUQ5tmNawHAVccwpgTIrIOERc1zuZ7W6_XHv_0mDDDZ6CxqfTt_-DS2wSrt-TnTw3z7_nu9nPvbHeNAhIjquiald0-wZcSI4lFPK1cC63jc5s8sRtYPZ15XbIY--nETraP3jBBmKhLulqFSQc5aAzwHwfMGbmwPNk-mMOOizEIRkaAEq-R7aC6nVVCLqmjM3qMQidgwHLuU5mPjyEAIE4jnZC0AZqEiwnX0Lkl7eD1VLcv2_VWbwJOJtIp377sR0_Qq1kUik8BBREozewDnvg1d1D29yvX5Y4xhdsTIvt8nwnXONCYCcN7mRtK0fkipaTP2ExkR4SIiS6VEdEt3Es6I9ERTcy-1Rd-RcCIh4akPJErG5LTacQgLMtNjLt5JBFUCoOyB9nRmrstpefx4DRuF-HG7i0ckcxFZqzMI9T3jQCK1JuV47GVduGj2A3u30RPBRDbe__L-Pu6USEC5rAuDVAuE9_sjKcp1sd14eGRwUbLwCAaziO8bM3lmW1duJSPHPkiSSG1Eu14SuXy49h_3x4_7-nLp2yhFZkp7HAMxjOXpp58un16-_fblvJ7L6dzve7u07L1v--Prj-3xiv0r5CpNPagul3_6X_7n__K__m-Fo7SKGNu3V1Il0DH6-vw8ibIYw8NtdEQX0XQkyJOS0Jbm7mMLbtou6_r0aX_7EhnS6v1ty32AeXlZx9tD10Ijw3wcD2WOmfYhYlaEkfsMUkJkENb1VC5n633__koMJmHhmSwgFmlrIvbX12WpYYMzx2FFxNMSLq3NqyxE5NzqEsK8rJdUKrWC0iP7251V-rYVaXpea6tIe7w-KCGrxj60Fd-OiCylmXcwwib-nZbnqx1d23p-Ovf7XloZ-z4stKqbZzpTPbp_-tMft8dWmp4u1yJC6d9ev37781-uz-foox_drcfIjKyXS3-8ikdmUhNKURFHkDLXtr-9cZKNobUuT09hHeZ9P2pb0s3HADPCRTQj535a27rfN-FcX56PYURpW2cVjjErd6LiI6aMy8xm25UAAogk03mivWcxQzg9MS2_Qsk6oZwkMwKP6KOcru5hkcvlTLUhcuyPdBemAMFHOV-m5zsi-n5kBDLCnHmasHaO9DEASG2s7KPPvpN7Ipy1TL5OOz8nHPB47OYew2lp5IYxmBLv7cFZ8gUxU1iKZgBI4tnmZSDTjFSJ4eYJKU2m-CvdYYaAaAnv77t_IMGghDuxYMI8J-tHQJbxdzcYkDNv6Zl4VwInEZPMmAQThdkUC8JAsXcwt_M5LUiZmZNU6mrZr8-fv__ty8sffh3HjZipnJbTCpX0TOs__frzX_7rv2xvr-kBuI-xXk8MhtYMaZf29uXr6IeSfvj3_6jhj8f9229_izFKLT6GPcb6-dl-fM9w0ZJmGUGqpRJzjiBRprJYHzmMJWIfbpbIwpIZMUyLBkv0EWVGR98RUgYWbcvLB2qS7gBs32zbs5tQeLcAiCVZZVnBKk3CB7MQIh4Pd8_MyVRiFjPnIiKVqnKyJfp9r-eltJWYgrK_3hFWT2c9X929ns_cltfffqtL01JAHPsee4_Ry9K27VHbSsIJ6oHnTx_r0vpxZHjfelEOt3G_JQIWPg5z927ry2nctnJqGTG2jYsKFynF--5jUDoi4AQKEfEEWKQ2R4owsRz3w8NLq1oqKCMN-44-Isf7kL_o_G5jpNTFY0CFRLIfXNfoXVXA6hEs0reDOUQbLQ3p4ZnHTo4AaavhA8RBYOFST2E39O69v8fUawlLyywqmPJyECIhyMgUYmYEADBThMODVDDH0ALCvF2fdRgC84Avl482LRbuPnaYEea7I0h0zPwtIgEbwYUxo_8i4eHmnJkEma0tYoi26wLl_dtdhbLPAOxOvAKEeRJPzyBhibmP4s__PanU9gT_7scekdmNaiFARM124gIt3FqM0NZyHDYsCaXWsW_pEBVmtjBpjZhrOWktfYzH719qo7kHY9HsRiwsxWwEQGZ1XX0cYIQIcROV86ePY7PXr7_RsNrqcEO4qJpFaSW42LDLy9kfm4-eRE4hWimcWPwIFYkIbc27TRKzESKpXi5MVIgh5FvnKjZG71ZbFeH9dlPG6J2kQEiJ-nG00xqBAC2nsx279dHWZX_cEAFikAo5ax3mpTWt1cex_Xg7Pz9FWsSwrYsqmEE5x3NpYREUqbrE2Ik40gAEUttKWoiQPmzrWkpZV7NB0kgoCcLi4bYfRFienrbbPcdQVmQuz0-PL7-LcHhQBp1Pw0lKe_rlZ9X649u39cP5-HE7vv04_fwLOMfb_fz8ZKMLF201gR-3t7jdL8_X17_9GzgkKc2ZSURFS--7m81XVBICzExa2uPtUVp5x3pk-LEzvWskRNXME7J8eJai-3Yf2-BCYhH9wLzzYnhwHwYVsa91-UiG0Q8VJuFkMIubgxgpl18_WvrxdotjCFdCeB9prkvpvRMw2-TcKrOEWV0vMQ5ite0OwMahKhEQBBEIwoVyhv7naVAUFoza7Udyq-uSnrJoDqKIiJE2kt6zd-7EnAzKeF_YhDkZgEtRRGRIIIR57IOFGMJNw4ePwcxz4fSJMKolPMmSizpCT1Wk7cdR6pKCMBYWMKMfma6U_egwe9_JKbHK7OmICBIZIBCY5hE3kcwsLBmwvosKmMMMABcxG0xlHK6F002UCOTuKjUiQB4e80WTPhDvynoQkjkBaSV7JgNBgZB3N5GoKJayfb9xq-V6vv3rX9aPHymyH95OxdOsH9oWIfG9K6UUHfuREU4ukSQSnmBQwDO0asQculCagZFEbiGc8xXJoATmHSsTvVsctSD-_pprxYOXjy_j3hFIuO87ydB19Q5WZeKcJ3-mEb3MYMyx9-2REsorkCWMCiMhzPu2FSmRKEsFsXl8-o9__Nf__f86rzXdgoKVbBtSzwDbcXAVeLp7DlfJyNRWpTYDWWRdmwD7fRct-7ZnOiHrqW6PnYsQSNoaZrGbwCfUhSmlcppnAiIgpTGIUoQSlM44LYyIMdwNnhAi1jSziGRanq5xWPTOfgCYr5dp4JpZO2Qwkf89OhoTdi_l6ddPdj_228P3Q9daW02kBU4vL-jjeLuDM5G2D2klxqhaxn5IrZEJQlDEHu20SF24KDMx6fG4n8_r29uru2stUtZAluX0y8-_UCUb6Y63bRv95ta3729hnUY8fzjv-96PLiJM8AG-rIoYb_foB_FkgeWwrsvKT40GUTiIfbiUYrvF2GurrDy2w7pp4Un0TwiQXCg9qK5JfP75evvz18wk70zIBHxEhtS1_vpp3DZ_u5El0jPn7hk0C7KiyPnvs7CUTJiQHyLOjMyISCJBEamnej37MZLov22_w92tq4rdN26LlhbDkjDud16qiCAjI0Ra-JbWQSR1ldIQCDuGOzG305UFDCRlP_o4TAQIThsRTpTJAmIOR-_pA5TMnHOPAhCSpuxLyntLiSh9kpoAoTBnrXxZJMPvh0cQESciZ_JhmtoBovDkWf8NZ5FpAcsIEKkW8-G0C5ZJeZ9qM2RGIqKzLCKUDioUESxKE11A7MPWjx-PfavtPI5Dl8UO06bamgddP37YHhtRlqKny4djjK3vr3_7WoqC5NMfPj--_B77mypvWz8e4_nnn7ftXpbl0x__9C__x__5y3_-d_u3rZ7X_fu3vncb--m69uPox2jnExGhd4ZIWWz74X7s950WZTDXavvOUupavI80E0Fa9n4QiFgJswkS5hBdbOykpa2LLo1USXjsRzL8sUcYurmPoqUwG6ieT0GQ62W83QPUX2-iRJTZu6oCCQQyYzhrIdLkzKDI8I72-YM9Dl3a8ny9f9upAAZZtVyukrC-S2mP1xsywdClpmeOkd2YMhBSynK63m73tq7nl-cg_fLnv5yu5-37DyYUxTg2ppitGREFYWreyOE-cjg4edZh-6B0Xppvu5SS5lyk74NVeT354azCCUs368v1glRRHK83oQA8hyUnLEtdPNwCZanayrFtWmq8H2OdtFCEaO2PTVs5tlFOCxcJTyFilfF4-Ogi5d1dbT4y6-kkzP3tle2YPEAICDNsSRCN0Zll8tDCnESQiTmxzkTi7-jNmMXBcGPw-74fQVp5qRnVPLgIbHgO7EYSPK0gESBkcDARp5CQKjz6GMRMFDmcpXgaZXJR70NYpoudMkHsGfN_BGF4MpKapufUPrjl-8JHKfX80cPH6zcoSV2oColEOJCRQaWMY5_jqrBOkVRr_enZ7h0xiIlpXnN0ZPpjFyUR9HGwlBSILlKbm-UIaVVYM4OQqsRMbkOKeDcRKm2xY-u3vZzP-rQeQRTBlJnJQnWtPobWkhH9MfRU2nqSWn14DJs3BywSZqyUY4TAjpFCotLOixD1-77vWwKkREJQBU3pwVZqcT-IVZTTh9uhorYfDGf3fuztuhZt4ziYOTzTTSQpM8NFaWzHe31CqbZ16pnb-SnGEK3p6R7WzftBImFjjmKJUltLxHutK4Z3T8rl-fnYu6hAa1Jm5v7YRu8Maq1J-OO-LdfrrKgevecsg7hxhg07Ho9lVUqI1r4fvo3H92_bX__KIB_b8dtv--u34_6G8OO4L3XpfQg3zzj2x_Xz53K-Ho-9Lg0pEWHDAfJwgpS2mnsmJYmQhFltSkxhPY_QVsupVZEwj_B2Ppn36INrreuVCNvjngE9ra01KcUzuRUpWmsBnWm-pZgyw4db70lkw-ppFWU_3B97P8xtJBBmtVWpLeFaV2rMUrwbS-awTK-yDjtGd10qr2dSBXFRjXRmAsG7Zca75oIEc44WwSycUJEYfR7PklHauZzOriuvT0ScjhgHoGAiJnJLAeCI9O3IDPf3Kdx80yUbM8AUZplEyjGSVBFJERTOnOEju6dHhqTdbduyD6LwvsGG1NKPTiyqBaWW5Sy1hjuMwgeG29HTPdJsGDGX9RTmjBz7MY1HTBQe7kZCmclM3M6IYA6YaZE5uxTlTJvwAGSyckZmgoShQrVkPSEBS791ZsAdyRRJhL51XRotF9_2ogzk9vvb6eVZT6e0nTlZSw4jZG49tt2T7RjZdyys51VOl_7YIyCCZOZ1IXAejvA4erplBjyESRlTNwUzAsUIJirzExguUiKciZmJVWN4BrSVHIMlsu-iRc8v27c7F81j5HAiPv380fbj-Hbzey9Fc3RKVylje1RmpcLIx_cfEYQop58-rj99_vHbj_3Ha2v17a83z27bUVj22-F7REo7XzjSvKcbEkJJXEAqpydmGqP33ZOyb7eY2_dTG8dGxITRHw8QnT9-mm8YHMOPf-VUSbASkMOddeGUhKYNUYEQWJd_9_H8H__gP-73b29F1W3AyTNEeDk9c1NVVqa-bx5voqt3o7amlvp88seOSC76rpliHg4gIaynlaXa1r0ffhzLqYHIDSK6nC7b65uyH4_d3IVVVAiJdAhDyEY-ff7Z0gPl6Zef9bpMb9X9-w8bx9yZtsvT29e3ti7nl0_bbk-fP40cx9GPbatP-uX_-Ve7_xi3N3_cRZIyxt5ZSj29HPfvNqLUJpSPb7-nO1sPizCTpsTojyP3YfuYI80YYxw9zTBVdEcQAZyRCAsprVxf-u1Niprh_MdPpcrrn7-we1kZZjFsHixLW7gtaRF7H6_fIMoUTDKD7LP0CpGcZMvI5PfhC4jCYWEZDinry4dyeUrhJOpv94iI0ZVZK9sxfCQy7BittvLx0l_fvPf0oadWqsAz-gGLMEs_cg4kVce292OzY88kuVxEuW_34-223252WI4d89YwwscAJatweo6RbiwMD4Ajgxgz9zqP_eFJyqIl08M3YiVZ4UOagjV2S0vrh6jMdzgQwKSk57zdZiIwckp-CcmEgZkvSwsAFMrEMwfEIIAnw5RZZ2sL6egGg5sRixtlZr1efNhyucKjXS-Z6Wa11rqenj_9bH3bbvfj9S2PYekvn__w9PzUWjk_PZ0W2t9e71-_-uj7Pup6-fDv_mFdTiJEhWtd98d99MGRb7__Xltm78q0LM9mo16u_nj48eivd7djf3zzzPbyVEohETsGCVSEkLYdcew8u2QJpkSCiwJJDGapT1d9udgY9XrWpZHI4-v3HMO3exy7H5t4_L0VzeZArawS4fHY-uurPe7CyZSSQe6IYCA9WQoLA-ndCYSAlKqXExIeSaxJ1M4XqcXH4Mw49v54a22Bp9YS4_Axrr982n__Fm4-dl3b5JKPfauntSzN3NJCNfdvX9pakozc_DiEOMbgqiSEhO_buN1jWIYREXlEHxRGU83gQVKQybWFBURJuG9dWylVZFEzg2dZWvqIx51zxDiIMinj6FQKUQHHRMkQOMPHw9KH94P8faRkvbOSeZTziWtBEDORD3tsSclSmEtkxGHcCte61hrbW_YdMCDTg0QAItVEzFl-zlG8pwjTLLKDKTPCBeQxLSfBEMyNzWywEFNtkOpQUp5uKNhBSRTOTBE0K3zWPRmiDDNk2tGHOaukOSKYeIJ3p7mDVZNp8s3nep2eESGlhAcxcSFkCFOGhFlmAGClMBdHY2EI0kdm2Ehiqi-fMDqKCjHX6mZwD7f04Z5hvj6f7LFDNPoAURpJKSzk255uNtzHnhGZWZ6fRAXuBHZzFiYVG4GEB0SUi7ilj54Ap9-_f3fHUqT98hP1YW5-DEJQUn_cmVgU4WHHoXXRVsKMEm4DlBjm5sHg0kQLQWyz7D3MkclCaSagGNZfX-F-_LcWFKgsS4zux5gdA-Y0M6a0SDuMljI37mU5zUvWNJ-WQaTP-UsmIowVGQjz09MHkara-rFrKUnMyGQRYTD3PiJTSpOyuNt4DFaxffjw9eMFzkVlv71iHIguAHyMPoYdaUGUsig8hWUcG4TDQlRECrgkkET7NiAV4y6SbV3bv_s13x7gYBJi-vDy89vrl-N-9wzEQPpyufTDnj9_BnEiT9cLtLbnM2nt3U4vH8bYM7A8XdvzxbvX67lvG2kBM6kykXev65kpPcK6S6kRY-x7EIWPp58-p5tZt9Gtj_r0gpR6-RQWCNSP10njBtf2YSViEFCLWbAUG4ePg5FS2G1nFi5l5l1A5JbETIy0YGIE_NjAYPhcD5ikrSfiCJsZIOJWMjMiWIVLS581HUg5eU5Ql8QYzJThYR1hDLd9b-cL1WXC8lkEAImkcHhqqSTkPcFsEaxEyMwkkPXhw6lqIqeyIEkSRkSTuUciXCuQ0Q8KCMT6d_QgH9EP7zu8Z3RWpHfAQllKBaGul9IaS7PQtp65VLf0YUFUaiPV6CZCKQkW9-S2UFAE0mzWdokmmkOGxSwdBBBBQfRenFcNAKKRYFaKQTKFhURMUjjTI5MvNbvDOzUOUIJQGERjP9IGAb5tWUARXDJKFSVZGJUz2Lq_n0MKhhmouQc4Uwii3Jp5sijVYscRSZ5MRfh0iipUpKwXqYVOp7aeqNS2Xup65vMTcS3rmbRG0fbpSbKcfvo511NYtLWVy4W41H_8qZ3OuadeT-vzmYVZECBE0unEJEWVhIJl_fBzu1yXP_xEo_ttnD5fS-Pttvexr89LXVsS6tNZltPyy2e73QE3d9Yqa8t6tb4f20Y40g6iZAXYKSIDev1w_8tvGVuGcan16czcMoe_3f3YYc56ZQrijPQkCarJgSY0afrnIqXmyIpy_69_s8fBlW3vurQIJ2UujWujjPQY-05hBHF3aksI1WVhiLYaHjHec-hgQVUuhaSQiLAmUotoKx6I7u16pqpvf_sdMzWDlFrq0mJGcj3dcbo-rU_PxFyWhWvt2318u3ErsQ93Z5JSNaSWunz-hz-dXl768WjLioQnvf7-Zb-_ff_nf8u-se88eoxghrQZvfV-PGx3fn4u1_X4-o2ZiJKZkQ4Vt2BSqYUoi6ooE1P0AbdESCapJruPoGUhVl7Wstbjx-306RlVKQuRPL58YyYu7D0yU0qJSL1c-kZludi-5955PdF0igcCHKxEUp6fpTbVRa8vslQkZ7IsLUX1stTTmde11BMJxzFiWIyR7mGmzG59bIcPo0JaVVpFkB0GM1kKAO9jUkcTmf4gKokfLM-y_MH6t_BkqbQusp7Yw273DE8YFwVChAhhw9OjvFwlSZvAPbqlAOGzBQ4EBYMJ4KQ581YC6F3KrhEgCqiQrByRFL4_uGqGh717RjmJREGgJGad3V2AiTg8EUnKSMrRqShlsioS72qxKQ5jIuGcruhwmmRuEVIBMbfCqkjS0kDc98P7YBZSqefr6XS2I7b7W4zj_OG6PF37NrS1Y9--ffkdw5brH17_7c_tVAO8PL-cX16iDzsOlPbtn__89ni9fnhuL0-cYzzuYzvGfgesb69JspxP5ePnvN-Ih5SSmeXpqdTleOvamnJOqqsQwczDlQkq7g4SVrVuJEJSdTkv1-vj6y0D7XSJPo4ft1bYx0HhNnaOJCazQXNmIiHynt32bWRmIuYcjN1naz_hVPTdJmFgJW4liYNZysIsWpRLPX140Vr7toc7xZ7H4X3v-9bv29gfmS5lCbPx2MCoy0IkSz0t559sPIanmZOlax2vr8zY7xuxlrXWl2caxsLjvs_kaNjQwhkdAVUhZoo-kbIoygwQ-XAuVbTI6dL3UU8La7Xd5HrObtJUFMfXH0LhMQiaIJRS2mIeow8Sfo_B-LREOAilKC2V5tqkzG3lsmitaR69-755N25l7JsuFxKGdybwaS1Licfd90eGMRPN8_wk-2cSSQ6b4zue_1SNDCH6-1mXImzSfZlosm5noBJcdLkyhMuSo7uNGAeIYnThnKTg5Mg0kCRzZkzg4fvxRhhuojrt356ZkbN_T8TpyaphlsIEkPydi141zCGc5gCF20RuZiLMARI6PYWNIoQEFymqoztLiujx9UbMVEWhycyiAHyzQtkfR72cmdXunchJiNynDBIRLITw9IjNvY_srq0ApB-u-RgR4f9fPsGTkliS0iOIubRamMdj-GPnVgXzlyQ5kCkgaCkx-szGjUcnkeV8mpjq9vxEAbe0cTARi6owaaZ7mAM5LxJiDCJCpCyqk6VqFscBf9cU5ujJBBIfBjdm-Lb3bTALySX8GH0vpTGFuyWSS8txxPAcbvsGIoqMo3scmS6lQKg-fQSkLicW4tNJiFk1033rUNZWgIhIlQpDmtv9YY9BAAfSLMN8DBaQW4zuFhGoT08qtH39q5YlbJAoE4WNGJ3CwroP07KAuX_53m9v5kAQwN4fRXiMPt5eCciU5fpZhLYfbwjabgcT16ezHW7DhNUj5t7XHHYMA5WlBZEUJZIY6SNYpB8b1WVuDccwMEBJIcOR6W25SlVJHMfwfoCk95tqcTO_7-3pzKzbPlhJllME4EjzRKS7EJOU6Yqk5LFtYebDA-lm6ZnxTvnQ2mKuZJYARCVthAWS2vUDA9adgHCU0sySEj7ZY3Px87l9TSIKDwpicAwPc_cYex9HJ2JC6loT3O9j6lLTI0lYlVmIC83brfOFkKoKmjAkYm0I98MzwSqkFJI5kJZxHMKY3Wtk5XmhmJnDMZyQOQxmcbg_9uhHhiM9MgPQpbEytZOoyqnB4_Ck61pV3EGsVFeKjMNI6J0oyPpu3KwNS9VGWpVbIxFSJSluCaIMyphIR2QfmRnuGTPgEJSzz8oUIA8AY-s-Ah44kiLJ-ry8p_kDPQJOeQRVogTOV0ZSt8AE0yOhlv_C40LTcGZp4VmEikIaCViEiH0gnexxiAh89GPYMSIskFxpbNu43cexjb6njzTr3-_Rj-3bt9g223YfvW87CuJtt7dH5Hb_2_c0f7zewo3CkyR62H70-yuzBkmq7q_fx4-vGdHNx34QqNQS0Iy59hSikhboxxiDWjn_p3_C9-8-jv7jeyqKUvYR7jGmW-qgoIyI-52U07W0cz2veRi2nscBtxkmyXSyCMu0RFLqvyBegkg-nHAcsPD7HuZ-7BGe4FnsiHCQANo-XDP98dtvNkxU15dfER0qotUfZo-7DzvetvXlRWrRX15QZQyUVuvzGQ6uFZnRh_VkLqW1DJppn9IqFclgEskAsyQAbno6P_36UzdfLhdd9euff5cSCQgKXHofn_70h4R8_PXf7_cHiWxvGwPbfhBYJO9fvozbD1inCNt2IgEzkTJJuCGJSyUirhUpx5evrEyACLsHUmOQCiccEZwcfWQf7mAQtwIR_ulP_vpKwbKe5Xr6-29sXn_6eGwHkdS2HK_fCSlVEQxPnmoqVpAw8dh3ss2IiFmYqVaoJrO0gnlB2Pvowx-bm4MkQJbZnp-plvG6UxIDfhxpQ4jGfkxxLygpPMwogiY9xMBE6Z08ACI3mr7fOXzjhZLAZzDb_oNYlg8f5LqOexdK-PCjIyPMGEKZcCCCWKm0CM_DY4y0CRuZoR8hEEgAAqb6jwGeyuG5P2ddEMnMROTDwgcyuaxMDGZuMkVlM4YxtV8RkQEQY04qZjBk9qOlTA_Cu-4sERYsMtVnmAqjCf8hAgtJSdZwAimLaF3MRt96Oa11XdefPsWBupzbud1_fB9j9Ht3yv3ra21lf_vx-Prd9_3Y7re__bmuzSzD6Pr5A2yEeSkNZI5o9XR6-UTA65__xkg_NiEOM15O1oPS999-J637t7uuy9Mf__HtL99iu9u-IQ73sMOFKUZkQESJZUonItn7kNNSTxcWJcLYNhEqrfixYxx5HL7vQMwoFItkBAUgHHaIaPYRR49-vN86iVLhHO8JE4CQDGkYTslcSjqn09ihbQmi43ULKuvlg9bCSm9__Z3SKCJtZvBUROv5VM9Py4freLzFbkTCwowMQr9_FVWw-N5Bkb5TJomy6PLpxe93v9386FSFGUDEGGH-_jkLA4g-MiBSE-QjrAeXVp-eEkSt-b7N7yjMS1O_33EYEfWvb2UpaUGiYA5HJufcyqiGJwzvRPzuzMrarEdGhhMtra7PFskg8uy3O3MiU2pFBElN89h7gMFFWYWGvd6i-2wUuiWLzP7MO_EnkCLEAmLVJXpPB6ZUNwAWdiJVAjIZQCQSKsvHYBaugKcdlJYRxAwznhhvEPh9dD3ZKzQ3DUzh78dxEg0LViFWgN8fEMxg4czmpUfmfJqIPZEzlUdTvJ0gZp4jOSYRRZC-_AkeXDTMkiYBjN2Ci6yffn789lcWBRMXQQLuRHMEH85KCFKFBTy4FXeXwhw5z5-RKaWmdW41PD24nS8xbOybVkXCu7FKhkktEe4WzBLmosIMFPWeySRMY7vX5ZTI4YERpb5vjUj02LtW1aJhCSkklMPBdLwZNyZOoVloygRs7yxFBGAKT-9WqiI9A8w0gWVwR5GIQGmUQWGEJOacgWMXVg2mOLrU2fciEGUfEGKIjS7KopqR_TBtAuJunaWVZa2ns2-7rOt4PPrRKXx-EQRNI3ypjazPcwi1YvsRfWQ4V4aDljpJrkw0PImZSoVn7ANFM720pkXChh0D4MyUtmawj52rWGD96eKvO4YRklrb7t8WPZOWDOi6DMvnP_1h__E9dpdWzy8vj9truIdbact-386__OHHv_yXGLF-_NDv2-m8JLk9-jh2VXHPROi6hg-Y57tLq_jh5iasVGs7n6132_fY935_1dO1Pa2-2zj86dcXe4z3KSUn1ev-9Tc3W5q4eeSUc5G2GmGUSOJjexARcwGzdSutMCjDWSUTYSPH0FaJ6DgO1VrXlZjDM2KExdg2qTofIhFlQXrEsPdRPlJqhY00m3OVSf4i5ejmkVoqiKMfGZn8_p_y8EgjzLGSxrCMzCRWdnMCphY0wkHIoPJ5iS1oENwQw4aTyiT5srBnMjMlhQ3RCcaMiABSiiInbo5AiEgpJVmmfWx7u9eycE0kSDk2I2IIja1zE2RycqSFJamqTE9L6LJkBjO7e47BTEh4xGR00nvgHqQS-zxjk0eSKlFmdx9D18Xd00mXmmF-OAha2efvgxYo5e7ALezMOtd9JgaDwBTJGSIYHhY-2xEQ0YgQRgJ2dG11RrmEaWxHmmmpyWBg9INYKIKUKJmYzUxqtWETkCy16lJCeftyb5ezCvXHhszwPF0vkNwfRy1lWCQxOeplSevMnDbMRvYbLRcEp8PMIyFLJQ4ElqVFRH8cYxvl5RSHF808DtJ3bGJaELg_7lIbCEUlSfq-S6t6WfxhdrgkzLpUTvdkFpWxdymFCuaWKHsGFWZgOEVX4QQyLDJnH3SYs2pZiwfJhyfxuP3tK8aoSwE8EuQ0M10gQWbankRUBYMA9s2W50XXst_m1V3uj4eIqAglk5CFp0_saKYNPV_G_d7Op-V81la48Pa22zEorK7L24-3WhfPoESrZf30cvz48vb7rWhZXz4GEk33W7_-8hzbtn-_b6-PIsmIcGOlcXRtdZYmWQg8rRQtOW0_wMqg8fZDz0sOExWqHIeTp0empyzCkwVB7_1WBAekPbWytEw2i-P7W3k6I1Ka5GF9G6yzcEJByaA4uioHSJaVyzK2t9w9wkiShNKMWAKzrM4Unt0QjnSogkBE7mAtASIRVbX9IEo3J4IopTmLQMiOg1mnuRMiNvPQUyLgQSzvG7wEi2SCiiADkdOODAUlR6Tvg1ihQum8ltgPbcX74AhpJZD9vulyQUaMzoRAkDspwz2TpgZuorpy6kqACIDf5yvEnJTvcZ305ERkWpAqeshTi_seEyIEIqUc816NQECAhJE5QxTTMTIPGamc5umYDrUMe3cDm8tyBsDryiJzlcwEM0tRN2Owri0j-47Th4uWpbv5dti210vZfrxZd1FdLqt1Zwq4b_e3dl4Jev7D5-3743F_SMTl43W_PYI4gj_9w8_3r1-PtwfMSsvcj-DsKaLL-ekab9_C4_Tzhzydvv8_X9pS7HFn9PC0EdwqMopq-Gx6ONO0iy7t85PfD4ts69rvm_WdCBCmQOydONJ9WiPdQ5umJwFug6gAyUXRt4l3nOYcXq52_07KIhJzpWiFCHbbiTlZEiLrqZxbRtrWR6D99Fm59u-_k1sce71Wf2wRdGy2XM9tvTjnOCwj4uh6anGMzNAiczbTj16WS7iNxzafdySSRJB-bAknQgSkCNzTjIXcgwI5YVgMZiFhBxiMj5fx1zduIpGRmTaI4YfLqcIDFpmzOx-ibMcg0vCkqiyRASBABHvfztFURIgmEYR1LWHJrfS3fT5WnEGMjGBCGEjYh1MmN3XL9nyNx2HbD0SCYlKtMPHuohRJKjE6mMEEB2huyun9uj8xbDAzTamAp7QCYtYSCUSGe1hwJgngTgzwnLgiuiUrKRMy3WfhPmNyBBhIZp6EHyRY9e8PFIGQHsSc_h7c9Zx4dKRHRorqNG3BIoXDd0KdX4GVES7cPpAKpZSnNjGi9VRLK3b09OS1EZJZKXOewK13EmIRLkTIevk5RUApzKIiRd0NADHSHemzqc3CzGxHT7AsCyXKugZCVSdZEQRuSgKEz5_u_HZKW8KztJWI9HQiZqkCc6JMdy6FWIQZHloUaRQRCGWh04LwtjZEAE4g1kpMzAyKZIBQ1hLjoHRVjTAuC0tJAgsTAKHZQmJCDAcRPEprbiCp3Aoiy-mcbkTxXpN1K0tlzoicJzpdNCK5MIYRsd_3TOr7DqLl-SXCeUZtK2eEj05AjI2FkpK0UF1cwLUSEwWQsH4QsyozgyikFNJCLKWeuJSyKDyoqpw0M7hQMmMpulS-XImptvfjOYQjUtZLeVkJyeyxP5hjbG8v__Gf-o_vddXXv_5Grbo5RVAGNYrtwUsN0dbq6dOp3-4cQYtS0XSva8tIECDz2OUiwiqnX5_Cgtzb0sa-UdVyOWlr7ekJnKxy-nTet0f2PPrGqiQJIusDIvV8hjC3BaJlXUHpxy6iAEUEs5b1xEV4KVwmJIuIAEZ4ECBFcnQIE0epFeEJGuOQ85lr5Vr0fOZ1qX_83F8fUispkRZiJgJXna19LkpCrJzwNCMIMoqyhycJlwWEsixgEBOUZWmiRDFLHD4fdOZZMUgqzKpQ5VYhmpuFGWkBE7HwoqzKbQETkkCQ2gJzqhYJkIq0OkdtwpwRYAoPbXXyTyMjwbVVQsg8BXmSliRCkCxNhLlqIGSpXJkAqYwMLppjIDEeB6sQg4m0FSKaWuU0ByPeJc-M-eJT5kJpziCpBRmsJWeWPJNFuMwXpXAhAFw0iaiuCrAkC9wHIlQF4ayUEhDmqslEIpmW_U1EM4yVy1K0KgnFsIikTK11PhvvdypuxOCET-ZTICOZQEylLdo40uW0UEb2no83Eq1N66kNG-10Lpc1JGlp8vzEP33ob7ciWZcafcvI5JbWQVHXUs_X068f15dLHLugw70fGymvPz3XyzW2H6UVijDfCck6Y2O1tMIsZV1CCzJlLUTICOu9Lko5kMZlPj4htLDyJDnP8TYRaUkRYnRtqpUCEzUDUmUtXJWLjswASIsNlxilChJuwXVlJS0SHmZbshALgtr1tHy4SpUII0IESWEQI7JUJWFt6plcK6nwaT3_4y_yfCqX0_rTRdsiyuXctu0Rw8bjVgjHviPp_OH5OI7Lx-v545UW3b__uP53fwrR5eWUnG-vt_PH5XH_4dvb_vXrxFDZ7Y2LKp9YazJ771KUWKg20ZI5S_nGRetpEVVaWhxHW2uGEQBiKgWkolRLyfT5LooixEX_6WfOiAgM3x83jC5LneaWcIvRKYcqZYK0LM_PWoXX6pFEBJUYe7hpkbJWEqpPK2pFEVoakEpziUzwf_usGAyI6KlOxxMr3AYpw2zq9pDIuREuokt7J3UyE5gJwCCAlFmYCPAkFRKBKAkhgmoFCy8LWFOFieRU0ofUEszCIlVYiFulUtwDqqKFEGk7wIDzrCom5iYGJEnEMov9kQkS4VqQoImaZZobDi7i5pTgWkiYkVSUDsN0LovS3OgneCpIRYhpjhUyABai-V0mMcEcIsQEocxIEaqVy6p__DVVcmbaI4h1zPRsXfr9ocsyAw9MVE-LlHJ7_WEZKnT6fIpu9Vy1qXcnAVdlkdPnZ1mX0tp6WdL92Pp6ruLDrXvY86fnUmq3YdvG4pSxXE7uwaWytPJ03V9fA54w71EuZzsOyTFuD6bUpUEFHqVV60dSQjRVl48fn_-Hf9y-vRXRfgwg4-huO0nAY3252P5AHqoyr3Lf93yYQmUhVVaWqmmGSFGRWkQ4ScKClZiEqswgeILCQs4XWk60ru3zNRCxmd0fpLVIqR_Pty_figS8R2SaJzMIy2UVwfF4kIgUViEuwipIEmKtTJIYnUXs6HVZy7mVtWStXLR-uvTXm7AjAiTwYEaG01woWgNIm854Otc6IvV8DgXgAJSZYs8MpihNM1PMGeHpiORCVEp4yloiQKoQzkxSAnLmzUi01EpaZF25LZbQ82kqpAEALuThjveAGbGonqqHkRCKEAuxMGM8bsSO2CECD2h9T7qyZhpFojAzU9Ep9AUl5XvMLZO5lLKcoRQotLTy4YPNsDsLEKIEOMdOAZoBEGRmpCiKEvMUYmQGUbIwiRBI5qX8fFJKmwfrGU7OSGYhTMQgSAUirDrPnPO-aBbJiJhoIgcLEQkzEBFIQKI9JTQBH5mWMHKDj8jkBNwzQaLknhnuZhnMIn1QJPmQkTRpRMTiKW6OnFMPzqTw5KlA8eyHRVJZlzEGnOYh3v9-hRkp4Qh_B5xGhnl4UCbZgIh6KEMjlSJjdyQyOADzoAizJLx3GwDaH-6WXJcYGeaU7MHhBLB7pFOEeHCkcGYOJChcIhAJIgrPTMqY2sMgwHsSiVmmhyfTFLOB02HDkeQOH-Qx_5DTO27d09It4OnD4ZM1zwBnynE_wjxsCjgZJEQlh_lgkFDqGNx3A4qNjJ4MBnEGU5J7-HuDkX2EWY7dynrOlP4Ycbj17Lvbw1DaOChoca52xPEap8vL2A1ZHNWXy_HWfXPy2N5MlgV0fvtyG_etv933zVnVho_dRJVZH7cjwQlGiBuxByD7kaSFUrbHCJ9UidxvB5ITEkP6nerS9vveh0NLmPgRfXfKjCNqaW8_Bg2ntIgYx8DwNMRIN-rdOTVRiRUpMUJQwnJYRnAks7Zjs7FHaSfvDs9M9vfgKCgDThB1hw8DiXukI5Mj0E1Iz8-__IfbP__OSWnkQQkJx7EncfUAkYQjIJnigwAhIrMEcSSDxEefU-_0RJIZcRJDvXtGJjiSpNaMHDZtnhLDvefYHCJFCqCRlEHDSUrxrJmcwQElrm6UEFCZTKQeElQQ8N19uI8kEiSnw3swwOAIuAUBPgzJmUREmWyDkpEGIvaRCAlDWoRZf3Qbf9ftqAhzOGCZQTmDwJ7jCGZh1fdyHnE4PJiCAfIRCBx7WrAN0ulutGAWdxyHC-msPaerkPjuMSwCgIhqxDQys3UmwAciOT0zOKzMglQEJSSNbA84p6WNsJE5grlkirZVSJAayYQyjGptNkBSeTmjLfuPrin790FGGggTKQ2kxxEZut36vtnYheuy3zO2rEJ2s36brPsnrStMAmUfrTz_fP_9Ya-dIvxhto_sIHBw7a977BH3boOW07kfjvmhDOrO7fRydIpg6wnSKceEw7r5CARNGjtSbHgkhU_CD2BAICHRqW9AyHChiZBHIa4pNUhHB0SIK3vY7fD7MTNvRFXXBZExIgxJhahYyPWPv46DbPM8kMOPw5nJLXIkE8bWWcvjzRxFLi_1w2ctT7ffHuJKRvvb2PbB6_n7P_8WffjhlFza0pZLLk_ffz_--D_-T8zLuFmMpFy-_z56UFP59tfH08vz1__7tyIaW7fdCYiR4cLl7MBxDBGedMh-OJeSLBno9yOCpS5hkeYsSkERSSwZcIcNZHA5tbF3d0pQpEhbZT3Fm1E7k7ltO3laT9Z6dPfDMBwBG2Hdk1vgpLx4tzQKh3sgKc0I6T3C0_ewTlybo1BybntauIf1JOKAshRStWBItWAfFOb2GBkUM06PtG6qYoNIJVHD0nowNEncERFhiUQY0gBSsyQWN8Z8PwQTF3cRreMIJHwPAscRkQl6X_LGPtXLTMnTS-UROQizrwtKwuR8RRJmM5qI3gdGDC35bi8VGyBmTBWi-7yh9OEE9hSSMvpGiQAnaEo_Jht1howiMxJJE5RCOZ2mkZnz95MjQCSJevrwc8ilPf-0__6KRHSHJTOng6iUsiSpaJWikVLrkqR6Ot9ft_02EMTnC1uDlddvvZ0-k14iFMGZ8uP3ri-f9u_3vvn26p_-4Z-Y2-3LdwKZ80gR0v37nSjgkS5pQ8tydDn99Ce_7dGpVqWy9Luj2_7j5seuwkl0HKjL6fzzH25_-y0H1fNl_elnSBtG27cNI2IfYKS79-F7tKenPmg8Dj_GnB6ACMw2glXCZ92Cw0EQtyTKcArPDB6DpK2RTsIRzKLuImWJKNJOvF63TaRdzSs6w9JTREv9D__57b_-JfdDCDGShbw7gUcnKcv-2pfzeT_Cuw8P3yOdpBR4RESO6FuqFMolksPz8UjVchxp94Osx94nAsoOJ0KOAKYYQ4B32idJJa4sLZzjgPXIfaQNH0GRFPCRmeRj-AiQkupsvYZRJkXwbPG909Ut3eCdta6BouUSXgK6LGczSrfRe44R5ulIC9biRiJi0_IK8QAgZpC2-tZtu0_uDAmHz7o6MhEekfMCFnM-5pCJdgQ4klgUqVQuIgvF0l5-SSzjMXwk4u8R4j4DfrNcJ33MuhQIZEGZlDPYnSDiDM4JVsuYRoiYIZb5WCUiiaZg2zMiZosxglgE-f_bweK9dx9zHcd7qDyT3XP1_H8BUdoeyWvrHiIAAAAASUVORK5CYII=", - "mimeType": "image/png"}}, {"text": "What color is this image?"}], "role": "user"}], - "generationConfig": {"maxOutputTokens": 200}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '2611647' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61SwW7bMAy9+ysIneNAjuc13a3Yii1Ai3ZrUBTYemBs1hIqS4YkNzOC/Ptku06d - DL3VgAyBfHxP5OMuAmA56kIW6MmxL/A7RAB2/b/LGe1J+5AYQyFYo/Vv2OHbTe4B4ulvV8TWgkBW - WBIIdICQG2UsuFxQReAFepAOClNJHfQL2LSwUQ0FpC6gtETazaCTk3mj0KoWttKLUEhgckINW3wh - N4cgYwmwO8oZ2ArpDyTYOqgtudAGSN3X5so0xZBXshReS13O/2g26WF/uD/O3jq3RlHXVmUKUiN8 - PwLYk9TSiV+EzugOdre+uWWHLL6UV6asrdl0w4v5POOflotlkqVpenaWJUkSjcq9JmtcGNw1eQzm - 4MECFhiq2q/NM+mvpunNSVKeDjoTN48Qafaa98ajOilOl7P/qN23ICzV1OfJCoQBoJK+7T2+fFiz - yZD8MfnplN5hWV1ffL98n2ZxzkeiaOLKabsf9Oo0OxaLXt8/GH9P1snB4ZLC6sp4Mefxk0InYs6T - npWFjauNdrQqOtzF5weJq1he3bRt5Z9v3fmPO/6Ts2gf/QNWbzk6hAMAAA== - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Sun, 05 Oct 2025 17:04:04 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=1593 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_mixed_content_async[async_stream].yaml b/py/src/braintrust/wrappers/cassettes/test_mixed_content_async[async_stream].yaml deleted file mode 100644 index 09c0d69b1..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_mixed_content_async[async_stream].yaml +++ /dev/null @@ -1,83 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "First, look at this image:"}, {"inlineData": - {"data": "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", - "mimeType": "image/png"}}, {"text": "What color is this image?"}], "role": "user"}], - "generationConfig": {"maxOutputTokens": 200}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '2611647' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:streamGenerateContent?alt=sse - response: - body: - string: "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"The\"}],\"role\": - \"model\"}}],\"usageMetadata\": {\"promptTokenCount\": 272,\"totalTokenCount\": - 272,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 14},{\"modality\": - \"IMAGE\",\"tokenCount\": 258}]},\"modelVersion\": \"gemini-2.0-flash-001\",\"responseId\": - \"BaXiaKfbG8CDnvgP1eSZoQM\"}\r\n\r\ndata: {\"candidates\": [{\"content\": - {\"parts\": [{\"text\": \" image is predominantly\"}],\"role\": \"model\"}}],\"usageMetadata\": - {\"promptTokenCount\": 272,\"totalTokenCount\": 272,\"promptTokensDetails\": - [{\"modality\": \"TEXT\",\"tokenCount\": 14},{\"modality\": \"IMAGE\",\"tokenCount\": - 258}]},\"modelVersion\": \"gemini-2.0-flash-001\",\"responseId\": \"BaXiaKfbG8CDnvgP1eSZoQM\"}\r\n\r\ndata: - {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" blue and white, - with some darker shades of gray and black. The waves are a vibrant\"}],\"role\": - \"model\"}}],\"usageMetadata\": {\"promptTokenCount\": 272,\"totalTokenCount\": - 272,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 14},{\"modality\": - \"IMAGE\",\"tokenCount\": 258}]},\"modelVersion\": \"gemini-2.0-flash-001\",\"responseId\": - \"BaXiaKfbG8CDnvgP1eSZoQM\"}\r\n\r\ndata: {\"candidates\": [{\"content\": - {\"parts\": [{\"text\": \" turquoise blue, contrasting with the white foam - and the dark grays of the ship and storm\"}],\"role\": \"model\"}}],\"usageMetadata\": - {\"promptTokenCount\": 272,\"totalTokenCount\": 272,\"promptTokensDetails\": - [{\"modality\": \"TEXT\",\"tokenCount\": 14},{\"modality\": \"IMAGE\",\"tokenCount\": - 258}]},\"modelVersion\": \"gemini-2.0-flash-001\",\"responseId\": \"BaXiaKfbG8CDnvgP1eSZoQM\"}\r\n\r\ndata: - {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" clouds. The lightning - strikes are a bright white.\\n\"}],\"role\": \"model\"},\"finishReason\": - \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": 1303,\"candidatesTokenCount\": - 51,\"totalTokenCount\": 1354,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": - 13},{\"modality\": \"IMAGE\",\"tokenCount\": 1290}],\"candidatesTokensDetails\": - [{\"modality\": \"TEXT\",\"tokenCount\": 51}]},\"modelVersion\": \"gemini-2.0-flash-001\",\"responseId\": - \"BaXiaKfbG8CDnvgP1eSZoQM\"}\r\n\r\n" - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Disposition: - - attachment - Content-Type: - - text/event-stream - Date: - - Sun, 05 Oct 2025 17:04:06 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=1770 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_model_class_span_names.yaml b/py/src/braintrust/wrappers/cassettes/test_model_class_span_names.yaml deleted file mode 100644 index d5aab4cf6..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_model_class_span_names.yaml +++ /dev/null @@ -1,107 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 2+2?"}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '119' - Content-Type: - - application/json - Cookie: - - __cf_bm=32b.VMplxNQj3L4u_1uDEw4mJbFkX7XgxbW0AIaO4WI-1767741983-1.0.1.1-ngrHAoGsRus82vIYthILxaNTwRrSgq6MT17VyVyBWlwIdCX8AvWXc.5O8aoDYcvvfwwO.wkKSuvDVkjIkcKdBrusGxL1HyXKUH5Xfk3NhOU; - _cfuvid=beFRqK6f.Kw4Ih5NqMjxVqYpI9KKqCHTmRCh_PSGRiw-1767741983214-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.36.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.13.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJBb9swDIXv/hUCr42L2PEaJ7e0wG4Fut62oTBUmXbYyZIm0dm6Iv99 - kJ3G7tYBu/jAj3x6j+ZLIgRQDVsBai9ZdU6nN4fd0/2Pu9u7Tx/peXX4df3F7+j2/vPNLpMlLOKE - fXxCxa9Tl8p2TiOTNSNWHiVjVM3WV+t1kW3KDwPobI06jrWO08KmHRlK82VepMt1mp3E1d6SwgBb - 8TURQoiX4Rt9mhp/wlYsF6+VDkOQLcL23CQEeKtjBWQIFFgahsUElTWMZrCeiwuRC/zeSx1EcTnv - 8tj0QUanptd6BqQxlmVMOvh7OJHj2ZG2rfP2MfwxCg0ZCvvKowzWxNcDWwcDPSZCPAzJ+zdhwHnb - Oa7YfsPhuawY5WDa9wTLE2PLUk/lPF+8I1bVyJJ0mC0OlFR7rKfJacuyr8nOQDKL/LeX97TH2GTa - /5GfgFLoGOvKeaxJvc07tXmMx/ivtvOKB8MQ0B9IYcWEPv6GGhvZ6/FEIDwHxq5qyLTonafxThpX - 5ZvVaik3V2UJyTH5DQAA//8DAFhHeVE1AwAA - headers: - CF-RAY: - - 9b9efaf33bf137c1-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Tue, 06 Jan 2026 23:26:26 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '307' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '324' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_e03ef3aa121d4a0a8c12116743ac7d40 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_multi_turn.yaml b/py/src/braintrust/wrappers/cassettes/test_multi_turn.yaml deleted file mode 100644 index 279b849d2..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_multi_turn.yaml +++ /dev/null @@ -1,64 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "Hi, my name is Alice."}], "role": "user"}, - {"parts": [{"text": "Hello Alice! Nice to meet you."}], "role": "model"}, {"parts": - [{"text": "What did I just tell you my name was?"}], "role": "user"}], "generationConfig": - {"maxOutputTokens": 200}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '278' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61RTU/DMAy991dEOdMpawlft4lxmLbBBNU0BAiF1esCaVKaFDGm/XeSdt1SzuQQ - WX7PfvbzNkAIL5lMecoMaHyFnmwGoW39O0xJA9JYoE3ZZMFKc+Q2b+vFlmLg2xXhR1Wh90obZJRI - UQ5oo6oSSWYjrtFA8CX0niX2ineH+OXkKFkqAa5frlIQLX3XEvCKS67X98C0ko72kNzN8AFlX9lE - ZUWp3tzUIekRGseXNDqj8Sm5IJRQGrTStSiuNMtgCoZZW9hheWxb5IVJ1AfIa1XVtkS0kfFc7OB9 - sseNMkx0oLgt9drqoRXlwnfXM95uzwQ3G7dicrNIsOeQ6U7VWhR4Tv6d8Z/E+qQrFuwv0xxrDqXm - zVUyyO2dwqhHwpVgeh0S0q+74hJ0oaSGUep4w/GCs8l4dDv9XP+cj2biNeKbgcLBLvgFeALyD7EC - AAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Sun, 05 Oct 2025 17:04:13 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=427 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_multiple_identical_sequential_streams.yaml b/py/src/braintrust/wrappers/cassettes/test_multiple_identical_sequential_streams.yaml deleted file mode 100644 index d3d14eae3..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_multiple_identical_sequential_streams.yaml +++ /dev/null @@ -1,401 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 3."}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '164' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYDBAOf0KRCXhzfUPTYZNJ4f6xG","object":"chat.completion.chunk","created":1766265193,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"gnat2cENQ"} - - - data: {"id":"chatcmpl-CoyYDBAOf0KRCXhzfUPTYZNJ4f6xG","object":"chat.completion.chunk","created":1766265193,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"jNso0lvDB8"} - - - data: {"id":"chatcmpl-CoyYDBAOf0KRCXhzfUPTYZNJ4f6xG","object":"chat.completion.chunk","created":1766265193,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"725RaPoKoL"} - - - data: {"id":"chatcmpl-CoyYDBAOf0KRCXhzfUPTYZNJ4f6xG","object":"chat.completion.chunk","created":1766265193,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"xwX6S3QVKQ"} - - - data: {"id":"chatcmpl-CoyYDBAOf0KRCXhzfUPTYZNJ4f6xG","object":"chat.completion.chunk","created":1766265193,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"PRUOjecqaT"} - - - data: {"id":"chatcmpl-CoyYDBAOf0KRCXhzfUPTYZNJ4f6xG","object":"chat.completion.chunk","created":1766265193,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"D7zv7nDU1k"} - - - data: {"id":"chatcmpl-CoyYDBAOf0KRCXhzfUPTYZNJ4f6xG","object":"chat.completion.chunk","created":1766265193,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"kaWRfolrEw"} - - - data: {"id":"chatcmpl-CoyYDBAOf0KRCXhzfUPTYZNJ4f6xG","object":"chat.completion.chunk","created":1766265193,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"nxDRXx48YM"} - - - data: {"id":"chatcmpl-CoyYDBAOf0KRCXhzfUPTYZNJ4f6xG","object":"chat.completion.chunk","created":1766265193,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ArC233Ax3q"} - - - data: {"id":"chatcmpl-CoyYDBAOf0KRCXhzfUPTYZNJ4f6xG","object":"chat.completion.chunk","created":1766265193,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"k9ml5"} - - - data: {"id":"chatcmpl-CoyYDBAOf0KRCXhzfUPTYZNJ4f6xG","object":"chat.completion.chunk","created":1766265193,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[],"usage":{"prompt_tokens":15,"completion_tokens":8,"total_tokens":23,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"njMUeLtfPSB"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b12246bb8312590-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:13 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '171' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '418' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_b3f7508e23014bb5b3a6590f7a1745c4 - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 3."}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '164' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYE8bhF6SRDlCaMKHmcnFYvC7yM","object":"chat.completion.chunk","created":1766265194,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"mrpG2gfnr"} - - - data: {"id":"chatcmpl-CoyYE8bhF6SRDlCaMKHmcnFYvC7yM","object":"chat.completion.chunk","created":1766265194,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"KqII3iAzwu"} - - - data: {"id":"chatcmpl-CoyYE8bhF6SRDlCaMKHmcnFYvC7yM","object":"chat.completion.chunk","created":1766265194,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"pY077J0ITv"} - - - data: {"id":"chatcmpl-CoyYE8bhF6SRDlCaMKHmcnFYvC7yM","object":"chat.completion.chunk","created":1766265194,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"hVFZKhHEll"} - - - data: {"id":"chatcmpl-CoyYE8bhF6SRDlCaMKHmcnFYvC7yM","object":"chat.completion.chunk","created":1766265194,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"5q0E4Aipgr"} - - - data: {"id":"chatcmpl-CoyYE8bhF6SRDlCaMKHmcnFYvC7yM","object":"chat.completion.chunk","created":1766265194,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"SVkT4p2PRw"} - - - data: {"id":"chatcmpl-CoyYE8bhF6SRDlCaMKHmcnFYvC7yM","object":"chat.completion.chunk","created":1766265194,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"z0JxYWz9CZ"} - - - data: {"id":"chatcmpl-CoyYE8bhF6SRDlCaMKHmcnFYvC7yM","object":"chat.completion.chunk","created":1766265194,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Yhx947CVn5"} - - - data: {"id":"chatcmpl-CoyYE8bhF6SRDlCaMKHmcnFYvC7yM","object":"chat.completion.chunk","created":1766265194,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"8SvU2h85am"} - - - data: {"id":"chatcmpl-CoyYE8bhF6SRDlCaMKHmcnFYvC7yM","object":"chat.completion.chunk","created":1766265194,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"HltY4"} - - - data: {"id":"chatcmpl-CoyYE8bhF6SRDlCaMKHmcnFYvC7yM","object":"chat.completion.chunk","created":1766265194,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[],"usage":{"prompt_tokens":15,"completion_tokens":8,"total_tokens":23,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"clzo45rSqE6"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b1224736f8f8e7d-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:14 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '240' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '489' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_13f73e276a5246f7b8770120e77c5bfd - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 3."}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '164' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYFeEsDiTkRc0wpc2a3ZNmMIJFy","object":"chat.completion.chunk","created":1766265195,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"e6vrbHoPF"} - - - data: {"id":"chatcmpl-CoyYFeEsDiTkRc0wpc2a3ZNmMIJFy","object":"chat.completion.chunk","created":1766265195,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"2FLB1kR9AF"} - - - data: {"id":"chatcmpl-CoyYFeEsDiTkRc0wpc2a3ZNmMIJFy","object":"chat.completion.chunk","created":1766265195,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"szhq4G7pLT"} - - - data: {"id":"chatcmpl-CoyYFeEsDiTkRc0wpc2a3ZNmMIJFy","object":"chat.completion.chunk","created":1766265195,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"0FrhMhyMc8"} - - - data: {"id":"chatcmpl-CoyYFeEsDiTkRc0wpc2a3ZNmMIJFy","object":"chat.completion.chunk","created":1766265195,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"7KNhjjfvdr"} - - - data: {"id":"chatcmpl-CoyYFeEsDiTkRc0wpc2a3ZNmMIJFy","object":"chat.completion.chunk","created":1766265195,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"XTPcPMIYpY"} - - - data: {"id":"chatcmpl-CoyYFeEsDiTkRc0wpc2a3ZNmMIJFy","object":"chat.completion.chunk","created":1766265195,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"KjFORo18p2"} - - - data: {"id":"chatcmpl-CoyYFeEsDiTkRc0wpc2a3ZNmMIJFy","object":"chat.completion.chunk","created":1766265195,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"5ZO6emLP2u"} - - - data: {"id":"chatcmpl-CoyYFeEsDiTkRc0wpc2a3ZNmMIJFy","object":"chat.completion.chunk","created":1766265195,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"KglKHdiIqs"} - - - data: {"id":"chatcmpl-CoyYFeEsDiTkRc0wpc2a3ZNmMIJFy","object":"chat.completion.chunk","created":1766265195,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"7A7zk"} - - - data: {"id":"chatcmpl-CoyYFeEsDiTkRc0wpc2a3ZNmMIJFy","object":"chat.completion.chunk","created":1766265195,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[],"usage":{"prompt_tokens":15,"completion_tokens":8,"total_tokens":23,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"obu0EI4F1U3"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b12247b9e892eb7-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:15 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '146' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '390' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_23df3ca5e9104a9492ba6ac711f23720 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_multiple_sequential_streams.yaml b/py/src/braintrust/wrappers/cassettes/test_multiple_sequential_streams.yaml deleted file mode 100644 index b4e3402f2..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_multiple_sequential_streams.yaml +++ /dev/null @@ -1,268 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 3."}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '164' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYGsjBG1Nfut20yTQKe0sOUSI7h","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"qhnOqpIMj"} - - - data: {"id":"chatcmpl-CoyYGsjBG1Nfut20yTQKe0sOUSI7h","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"cTil7PW69p"} - - - data: {"id":"chatcmpl-CoyYGsjBG1Nfut20yTQKe0sOUSI7h","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"0YnAj34Co9"} - - - data: {"id":"chatcmpl-CoyYGsjBG1Nfut20yTQKe0sOUSI7h","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"2OTWUEmJAI"} - - - data: {"id":"chatcmpl-CoyYGsjBG1Nfut20yTQKe0sOUSI7h","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"PzH358Bjix"} - - - data: {"id":"chatcmpl-CoyYGsjBG1Nfut20yTQKe0sOUSI7h","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"LCfdy0Z80P"} - - - data: {"id":"chatcmpl-CoyYGsjBG1Nfut20yTQKe0sOUSI7h","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Luoz7Ty7RE"} - - - data: {"id":"chatcmpl-CoyYGsjBG1Nfut20yTQKe0sOUSI7h","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"imLiI1n5XP"} - - - data: {"id":"chatcmpl-CoyYGsjBG1Nfut20yTQKe0sOUSI7h","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"Vwy1Rp8rUH"} - - - data: {"id":"chatcmpl-CoyYGsjBG1Nfut20yTQKe0sOUSI7h","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"kRAeG"} - - - data: {"id":"chatcmpl-CoyYGsjBG1Nfut20yTQKe0sOUSI7h","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[],"usage":{"prompt_tokens":15,"completion_tokens":8,"total_tokens":23,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"sCkh8ATPHhR"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b122483382af514-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:16 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '162' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '181' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999995' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_b8eb6c241625442282f4f0519dfae9e7 - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 3."}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '164' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYGeZzJazlbqwMyj97GdwzSH9qX","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"vd7IkwFPY"} - - - data: {"id":"chatcmpl-CoyYGeZzJazlbqwMyj97GdwzSH9qX","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"n4Wkt6VLAo"} - - - data: {"id":"chatcmpl-CoyYGeZzJazlbqwMyj97GdwzSH9qX","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"UTIlWWs928"} - - - data: {"id":"chatcmpl-CoyYGeZzJazlbqwMyj97GdwzSH9qX","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"qmxxmaZhzl"} - - - data: {"id":"chatcmpl-CoyYGeZzJazlbqwMyj97GdwzSH9qX","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"j9Lclwk8ng"} - - - data: {"id":"chatcmpl-CoyYGeZzJazlbqwMyj97GdwzSH9qX","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"V4LeJ42IiW"} - - - data: {"id":"chatcmpl-CoyYGeZzJazlbqwMyj97GdwzSH9qX","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"wVN2Xpch61"} - - - data: {"id":"chatcmpl-CoyYGeZzJazlbqwMyj97GdwzSH9qX","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"QDHoCqZz2Q"} - - - data: {"id":"chatcmpl-CoyYGeZzJazlbqwMyj97GdwzSH9qX","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"KC95XCI89W"} - - - data: {"id":"chatcmpl-CoyYGeZzJazlbqwMyj97GdwzSH9qX","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"KxMjU"} - - - data: {"id":"chatcmpl-CoyYGeZzJazlbqwMyj97GdwzSH9qX","object":"chat.completion.chunk","created":1766265196,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[],"usage":{"prompt_tokens":15,"completion_tokens":8,"total_tokens":23,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"hKfsFUmwYyh"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b12248649dd29a5-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:16 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '249' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '262' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_9e59e81aa2714f478345ef8cba60e44c - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_no_model_agent_run.yaml b/py/src/braintrust/wrappers/cassettes/test_no_model_agent_run.yaml deleted file mode 100644 index d8cbce6c6..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_no_model_agent_run.yaml +++ /dev/null @@ -1,111 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 2+2? Answer with just the - number."}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '148' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJNb9swDIbv/hUCz/EQe6nb5LgN27GXoEBRFIYq0Y42SRQkemha5L8P - cj7s7APYxQc+fKn3pfleCAFGw0aA2klWLtjyM+0fP9HX5v7+2/KL3zqXttsHj33zcU9vsMgKevmO - is+qD4pcsMiG/BGriJIxT61um6Zubqp1NQJHGm2W9YHLFZXOeFPWy3pVLm/L6u6k3pFRmGAjngoh - hHgfv9mn1/gKG7FcnCsOU5I9wubSJAREsrkCMiWTWHqGxQQVeUY/Wl/N6xG7IcnszQ/WzoD0nljm - bKOj5xM5XDxY6kOkl/SbFDrjTdq1EWUin99LTAFGeiiEeB6zDlf2IURygVumHzg+V5+iwrThCVYn - xsTSzjTn+tWwViNLY9NsVaCk2qGelNNe5aANzUAxi/ynl7/NPsY2vv+f8RNQCgOjbkNEbdR13qkt - Yj6/f7VdVjwahoTxp1HYssGYf4PGTg72eBSQ9onRtZ3xPcYQzfEyutAiNmtVY7e6g+JQ/AIAAP// - AwDuaeQPJwMAAA== - headers: - CF-RAY: - - 9b12245f08957e95-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:11 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - path=/; expires=Sat, 20-Dec-25 21:43:11 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '157' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '431' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999987' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_33be6e1c06474f88aa886351e283ddd7 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_no_model_agent_run_with_logfire.yaml b/py/src/braintrust/wrappers/cassettes/test_no_model_agent_run_with_logfire.yaml deleted file mode 100644 index d8cbce6c6..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_no_model_agent_run_with_logfire.yaml +++ /dev/null @@ -1,111 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 2+2? Answer with just the - number."}],"model":"gpt-4o-mini","max_completion_tokens":50,"stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '148' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJNb9swDIbv/hUCz/EQe6nb5LgN27GXoEBRFIYq0Y42SRQkemha5L8P - cj7s7APYxQc+fKn3pfleCAFGw0aA2klWLtjyM+0fP9HX5v7+2/KL3zqXttsHj33zcU9vsMgKevmO - is+qD4pcsMiG/BGriJIxT61um6Zubqp1NQJHGm2W9YHLFZXOeFPWy3pVLm/L6u6k3pFRmGAjngoh - hHgfv9mn1/gKG7FcnCsOU5I9wubSJAREsrkCMiWTWHqGxQQVeUY/Wl/N6xG7IcnszQ/WzoD0nljm - bKOj5xM5XDxY6kOkl/SbFDrjTdq1EWUin99LTAFGeiiEeB6zDlf2IURygVumHzg+V5+iwrThCVYn - xsTSzjTn+tWwViNLY9NsVaCk2qGelNNe5aANzUAxi/ynl7/NPsY2vv+f8RNQCgOjbkNEbdR13qkt - Yj6/f7VdVjwahoTxp1HYssGYf4PGTg72eBSQ9onRtZ3xPcYQzfEyutAiNmtVY7e6g+JQ/AIAAP// - AwDuaeQPJwMAAA== - headers: - CF-RAY: - - 9b12245f08957e95-LAX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Sat, 20 Dec 2025 21:13:11 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - path=/; expires=Sat, 20-Dec-25 21:43:11 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '157' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '431' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999987' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_33be6e1c06474f88aa886351e283ddd7 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_async_parallel_requests.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_async_parallel_requests.yaml deleted file mode 100644 index 26d43abdd..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_async_parallel_requests.yaml +++ /dev/null @@ -1,320 +0,0 @@ -interactions: - - request: - body: '{"messages":[{"role":"user","content":"What is 5 + 5?"}],"model":"gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "79" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJBb9swDIXv/hUCr4uLOLERN8deCgzYEAzYaSgMVaIdrrKkSnS3osh/ - H2Snsdt1wC4+8OOj3qP5kgkBpGEvQB0lq96b/EZ9/XVzwMNnOujqkb+HuvgW6PbL5rB+eoZVUrj7 - n6j4VXWlXO8NMjk7YRVQMqapxa6sy7oudtcj6J1Gk2Sd57x0eU+W8s16U+brXV7UZ/XRkcIIe/Ej - E0KIl/GbfFqNv2Ev1qvXSo8xyg5hf2kSAoIzqQIyRoosLcNqhspZRjtar8QnUQl8HKSJolhfLdsC - tkOUyaodjFkAaa1jmaKOBu/O5HSxZFzng7uP76TQkqV4bALK6Gx6PrLzMNJTJsTdGH14kwZ8cL3n - ht0Djs8V1TQO5oXPsD4zdizNXN5sVx8MazSyJBMXmwMl1RH1rJzXLAdNbgGyReS/vXw0e4pNtvuf - 8TNQCj2jbnxATept3rktYLrGf7VdVjwahojhiRQ2TBjSb9DYysFMNwLxOTL2TUu2w+ADTYfS+mZb - yqqUeL1VkJ2yPwAAAP//AwAbCHd7NgMAAA== - headers: - CF-RAY: - - 9472cb4d79f27277-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:39 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=l7mbGZ3Egstfh3PVdZpsOkqxw0vgJZvR00yYcXnuUj0-1748488179-1.0.1.1-zGkugr7nCARwHeGFg9XPlc7ChjTjH6Av35tx.ewtqIg7hpn2SeuueDeV0sMixwIHsE7zECshDr4vaV2fXQpOBETRL98mLwHcpljBSJOCszo; - path=/; expires=Thu, 29-May-25 03:39:39 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=wRUFkIxH7r5aq8YviVboE1R1m74GbxwHWRDWa9j1tGU-1748488179468-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "419" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "424" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_c9e62f050322730d68d7df78f9b4144e - status: - code: 200 - message: OK - - request: - body: '{"messages":[{"role":"user","content":"What is 4 + 4?"}],"model":"gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "79" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJBb5wwEIXv/Aprrl0iIFR49xj1VimRkp5aRcixB9apsb320LSK9r9X - hs1C0lTKhcN888bvDfOcMQZawY6B3AuSgzf5lbx+utpu+beb74fbr93BdKi4qitBX+6eYJMU7uER - Jb2oLqQbvEHSzs5YBhSEaWrZ1LzmvGy2ExicQpNkvae8dvmgrc6roqrzoslLflLvnZYYYcd+ZIwx - 9jx9k0+r8DfsWLF5qQwYo+gRducmxiA4kyogYtSRhCXYLFA6S2gn6zX7xGqGh1GYyPjFuitgN0aR - nNrRmBUQ1joSKenk7/5EjmdHxvU+uIf4Rgqdtjru24AiOptej+Q8TPSYMXY/JR9fhQEf3OCpJfcT - p+fKz/M4WPa9QH5i5EiYpVxdbt4Z1iokoU1cLQ6kkHtUi3LZshiVdiuQrSL/6+W92XNsbfuPjF+A - lOgJVesDKi1f513aAqZj/F/becWTYYgYfmmJLWkM6Tco7MRo5hOB+CcSDm2nbY/BBz3fSefbbYXF - ZdMUvITsmP0FAAD//wMAHCTDkDUDAAA= - headers: - CF-RAY: - - 9472cb4d795e5f74-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:39 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=D5wymTQyeow3dD83thuE0eWShdgxY38D0kJXHd.ZMUs-1748488179-1.0.1.1-3bJsQ2EFtzxrDG1vWH33upwDiXRf3MLCgHZtvF2S2Z8eeqnEXgubmRS67THCTKIsxmdeS7xfGAclinCKqjvVrqhIqzYV9maCn8wdpz.gn7s; - path=/; expires=Thu, 29-May-25 03:39:39 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=62gNDFO6c1qtFW93mdU_wkFNdaV989TC7j.Q3x9737c-1748488179939-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "940" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "944" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_18867c173fff6d22299475f3b28f4309 - status: - code: 200 - message: OK - - request: - body: '{"messages":[{"role":"user","content":"What is 3 + 3?"}],"model":"gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "79" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJNb9QwEIbv+RXWXNlUmw+66R4LSIVDhZAQB1RFU2eSGBzba0/4qva/ - IyfbTQpF4pLDPPOO33cyD4kQoBrYC5A9shycTq/l7fdrf3ODH37dvj8Ur/r808c3r4fDu7flYYRN - VNj7LyT5UXUh7eA0sbJmxtITMsWp2a6syqrKdlcTGGxDOso6x2lp00EZlebbvEy3uzSrTureKkkB - 9uJzIoQQD9M3+jQN/YC92G4eKwOFgB3B/twkBHirYwUwBBUYDcNmgdIaJjNZL8QLUQg6jKiDuLxY - d3lqx4DRqRm1XgE0xjLGpJO/uxM5nh1p2zlv78MfUmiVUaGvPWGwJr4e2DqY6DER4m5KPj4JA87b - wXHN9itNz2Uv53Gw7HuB1YmxZdRLOS82zwyrG2JUOqwWBxJlT82iXLaMY6PsCiSryH97eW72HFuZ - 7n/GL0BKckxN7Tw1Sj7Nu7R5isf4r7bziifDEMh/U5JqVuTjb2ioxVHPJwLhZ2Aa6laZjrzzar6T - 1tWXOeYFVhm1kByT3wAAAP//AwCBHV+XNQMAAA== - headers: - CF-RAY: - - 9472cb4d78470cba-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:40 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=EulnPVDmBHvrBtVkP1Jb.FV9nLpFLLHSlsHyw3.ExiY-1748488180-1.0.1.1-ATZmk8OiTX7FxVt2AmMY6VbrIgBwJDUz.dZ3VuyP9F6AjARSsy1P35lGfqBnpwotplfQSvSeQGravGggG2YZCr9jsTkOHPjEPqtFv2XzaEQ; - path=/; expires=Thu, 29-May-25 03:39:40 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=yZeym3GpRkVaB2a4ERNO5W9Sg71J9kZgzB6.k9C_7Hc-1748488180353-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "1267" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "1272" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_fa5dfb6ce3a2637a5f9803efbf54bef0 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_chat_async.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_chat_async.yaml deleted file mode 100644 index 09719491d..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_chat_async.yaml +++ /dev/null @@ -1,212 +0,0 @@ -interactions: - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "80" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJBb9QwEIXv+RXWXNlUm5B2o71BhVQBggNHVEWuPUkMjse1J9VW1f53 - 5GS7SUuRuOQw37zJe+N5yoQAo2EvQPWS1eBt/lF9ezjckP56bW4eP3+4/t7/6NvdYffp8kt9D5uk - oLtfqPhZdaFo8BbZkJuxCigZ09RiV9VVXRdXlxMYSKNNss5zXlE+GGfycltW+XaXF/VJ3ZNRGGEv - fmZCCPE0fZNPp/EAe7HdPFcGjFF2CPtzkxAQyKYKyBhNZOkYNgtU5BjdZL0oxTtRlALvR2mjKKuL - dWPAdowymXWjtSsgnSOWKexk8fZEjmdTljof6C6+kkJrnIl9E1BGcslAZPIw0WMmxO0UfnyRB3yg - wXPD9Bun3xXVPA6WlS+wPjEmlnYpl+XmjWGNRpbGxtXuQEnVo16Uy6LlqA2tQLaK/LeXt2bPsY3r - /mf8ApRCz6gbH1Ab9TLv0hYw3eO/2s4rngxDxPBgFDZsMKRn0NjK0c5XAvExMg5Na1yHwQczn0rr - m6tSlu9lXWAL2TH7AwAA//8DAJIFUrc4AwAA - headers: - CF-RAY: - - 9472caf81ef08186-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:25 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=1jp7iu46cC7LTzqfTym6.GB7A38C8xsrwWCjGlyW.Zs-1748488165-1.0.1.1-HUMCsywTN7YO6EKTIJZBdpCNIKJbjNNrSu76iNiGcTdFQkL91RARv0WBpbFFLhM0V.ZRhO6vrlHps9b3sW9wPC03ieo_Omlh6SDn4Sr1g0k; - path=/; expires=Thu, 29-May-25 03:39:25 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=7HAy0drHIm.KI.NGoj.O5wWMpmoB_UvJpQNPf0GUxSY-1748488165900-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "650" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "654" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_1372de4ff197f2ab5467d8fa1aa9ba33 - status: - code: 200 - message: OK - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "80" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJBb9swDIXv/hUCr42L2PNSN8cht2LBDgMGbCgMRaIdpbKkiXSxrsh/ - H+Sksdt1wC4+8OOj36P4nAkBRsNagNpLVn2w+Se1fXw6HL5vN/T7rg0b+3mz/fqNbr90hwcFi6Tw - uwMqflFdK98Hi2y8O2EVUTKmqcVNVVd1XaxWI+i9RptkXeC88nlvnMnLZVnly5u8qM/qvTcKCdbi - RyaEEM/jN/l0Gn/BWiwXL5UeiWSHsL40CQHR21QBSWSIpWNYTFB5x+hG60UprkRRCvw5SEuirK7n - jRHbgWQy6wZrZ0A651mmsKPF+zM5XkxZ34Xod/RGCq1xhvZNREneJQPEPsBIj5kQ92P44VUeCNH3 - gRv2Dzj+rqhO42Ba+QTrM2PP0k7lsly8M6zRyNJYmu0OlFR71JNyWrQctPEzkM0i/+3lvdmn2MZ1 - /zN+AkphYNRNiKiNep13aouY7vFfbZcVj4aBMD4ahQ0bjOkZNLZysKcrAXoixr5pjeswhmhOp9KG - 5mOFu2qnV7cfIDtmfwAAAP//AwAHOUbKOAMAAA== - headers: - CF-RAY: - - 9472cafdb8d5429a-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:26 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=2tnlCSvS2cImTavzOy04_sA9uLoEZqsYBxshBl0yKeI-1748488166-1.0.1.1-FhGNAXq.70IxLpdlPsUUkGWLHBbuBNGktxhq7YkqzDJ3lvBvOSdSCBeJ0Nrw7CicajhN6AQUCFcUJsxtUrNayxIJeVI9uewXP1kiftTII2g; - path=/; expires=Thu, 29-May-25 03:39:26 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=xICitKMNXIOl.kF9pYQEx_CxCHvrsE7JnXnPdFpUGUo-1748488166544-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "377" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "382" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_597e214218a53799245347330be413a9 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_chat_async_context_manager.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_chat_async_context_manager.yaml deleted file mode 100644 index f517919bc..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_chat_async_context_manager.yaml +++ /dev/null @@ -1,271 +0,0 @@ -interactions: - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini","stream":true,"stream_options":{"include_usage":true}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "134" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: - 'data: {"id":"chatcmpl-BcNw6be6DuhpHqDlc8nKm7x3iMAL6","object":"chat.completion.chunk","created":1748488174,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw6be6DuhpHqDlc8nKm7x3iMAL6","object":"chat.completion.chunk","created":1748488174,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw6be6DuhpHqDlc8nKm7x3iMAL6","object":"chat.completion.chunk","created":1748488174,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":" - +"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw6be6DuhpHqDlc8nKm7x3iMAL6","object":"chat.completion.chunk","created":1748488174,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw6be6DuhpHqDlc8nKm7x3iMAL6","object":"chat.completion.chunk","created":1748488174,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw6be6DuhpHqDlc8nKm7x3iMAL6","object":"chat.completion.chunk","created":1748488174,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":" - equals"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw6be6DuhpHqDlc8nKm7x3iMAL6","object":"chat.completion.chunk","created":1748488174,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw6be6DuhpHqDlc8nKm7x3iMAL6","object":"chat.completion.chunk","created":1748488174,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":"24"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw6be6DuhpHqDlc8nKm7x3iMAL6","object":"chat.completion.chunk","created":1748488174,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw6be6DuhpHqDlc8nKm7x3iMAL6","object":"chat.completion.chunk","created":1748488174,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null} - - - data: {"id":"chatcmpl-BcNw6be6DuhpHqDlc8nKm7x3iMAL6","object":"chat.completion.chunk","created":1748488174,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":8,"total_tokens":22,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}}} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9472cb30e8d5e56c-EWR - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:09:34 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=AIq4yjX3ru.J9gwNR6zSYLQNorConUZa5qtJ6wXxuvE-1748488174-1.0.1.1-KquMaoYitsL5z76ow2IPzasSn98mtC1_QEt9VOT1pvvQt_obPUDugNtsEGJCc_wP50_X4wP.kC7nYuf98KX8dCPpiq2ZqY5vwVCdgocqRxU; - path=/; expires=Thu, 29-May-25 03:39:34 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=o0LrLIiV.VvLFX1H1bbtbV01AjzSfXrfrVn0fU7pANY-1748488174648-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "313" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "317" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_7718454117290f001d635e2ea50bf0b5 - status: - code: 200 - message: OK - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini","stream":true,"stream_options":{"include_usage":true}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "134" - content-type: - - application/json - cookie: - - __cf_bm=AIq4yjX3ru.J9gwNR6zSYLQNorConUZa5qtJ6wXxuvE-1748488174-1.0.1.1-KquMaoYitsL5z76ow2IPzasSn98mtC1_QEt9VOT1pvvQt_obPUDugNtsEGJCc_wP50_X4wP.kC7nYuf98KX8dCPpiq2ZqY5vwVCdgocqRxU; - _cfuvid=o0LrLIiV.VvLFX1H1bbtbV01AjzSfXrfrVn0fU7pANY-1748488174648-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: - 'data: {"id":"chatcmpl-BcNw7TPkf33tHhtv5BBYd6zunIaPW","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw7TPkf33tHhtv5BBYd6zunIaPW","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw7TPkf33tHhtv5BBYd6zunIaPW","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":" - +"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw7TPkf33tHhtv5BBYd6zunIaPW","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw7TPkf33tHhtv5BBYd6zunIaPW","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw7TPkf33tHhtv5BBYd6zunIaPW","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":" - equals"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw7TPkf33tHhtv5BBYd6zunIaPW","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw7TPkf33tHhtv5BBYd6zunIaPW","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":"24"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw7TPkf33tHhtv5BBYd6zunIaPW","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw7TPkf33tHhtv5BBYd6zunIaPW","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null} - - - data: {"id":"chatcmpl-BcNw7TPkf33tHhtv5BBYd6zunIaPW","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":8,"total_tokens":22,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}}} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9472cb34d8b0e56c-EWR - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:09:35 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "324" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "328" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_8e14ac90b3fc7df08ab71458200c0b80 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_chat_async_with_system_prompt.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_chat_async_with_system_prompt.yaml deleted file mode 100644 index 5caa2785f..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_chat_async_with_system_prompt.yaml +++ /dev/null @@ -1,213 +0,0 @@ -interactions: - - request: - body: - '{"messages":[{"role":"system","content":"You are a helpful assistant that - only responds with numbers."},{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "171" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJPj9MwEMXv+RTWnDeoSbO02+MKDgiJG0gIrSLHnqQGx2PZEyha9bsj - O6VJ+SPtJYf5zXt+M5nnQggwGg4C1FGyGr0tH9WHHzXeV5vGfKaO33za8cfTsHn77n21PcFdUlD3 - FRX/Vr1SNHqLbMjNWAWUjMm12jX7Zr+vdpsMRtJok2zwXDZUjsaZst7UTbnZldX+oj6SURjhIL4U - QgjxnL8pp9N4goPIXrkyYoxyQDhcm4SAQDZVQMZoIkvHcLdARY7R5eh1swYB+ynKFM5N1q6AdI5Y - puFypKcLOV9DWBp8oC7+IYXeOBOPbUAZyaUHI5OHTM+FEE952OkmP/hAo+eW6Rvm5+qH2Q6WFS+w - ujAmlnYpby/7uTVrNbI0Nq52BUqqI+pFuSxWTtrQChSrkf/O8i/veWzjhpfYL0Ap9Iy69QG1Ubfz - Lm0B0/39r+264hwYIobvRmHLBkP6DRp7Odn5KiD+jIxj2xs3YPDBzKfR+/a+wa7p9OuHLRTn4hcA - AAD//wMAVr/YZSgDAAA= - headers: - CF-RAY: - - 9472cb184e500f9d-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:30 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=z2Ic8fUwpskhLoChFn0SfEzhOfgA51ECWEr8bGcDOAU-1748488170-1.0.1.1-3G3XcIq9Svq616YfoviWP1tBVFUnyK5oqEpmdqksGBJYjIpBO8NytkA_b8eFnYmWdJAuXvn06hw7i4HrfgFfaPFiUHbQbgYYAVNOsIV3dAI; - path=/; expires=Thu, 29-May-25 03:39:30 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=veSl_gK4UARU6LJElYKitkIBU5I0K75WBw7EYDdP338-1748488170636-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "220" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "224" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999978" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_d06b62c50c671827b21d6ed9f0358cbb - status: - code: 200 - message: OK - - request: - body: - '{"messages":[{"role":"system","content":"You are a helpful assistant that - only responds with numbers."},{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "171" - content-type: - - application/json - cookie: - - __cf_bm=z2Ic8fUwpskhLoChFn0SfEzhOfgA51ECWEr8bGcDOAU-1748488170-1.0.1.1-3G3XcIq9Svq616YfoviWP1tBVFUnyK5oqEpmdqksGBJYjIpBO8NytkA_b8eFnYmWdJAuXvn06hw7i4HrfgFfaPFiUHbQbgYYAVNOsIV3dAI; - _cfuvid=veSl_gK4UARU6LJElYKitkIBU5I0K75WBw7EYDdP338-1748488170636-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJPb9swDMXv/hQCz/XgOB6c5lgMvRTY0NuAoTAUiXa0yqIg0e2KIt99 - kJzFzv4Au/jAH9/TI833QggwGvYC1FGyGr0t79Tn17r9eseP1XP1EKq3x9cvptWH+08voYGbpKDD - d1T8S/VB0egtsiE3YxVQMibXTdvsmt1u01YZjKTRJtnguWyoHI0zZV3VTVm15WZ3Vh/JKIywF98K - IYR4z9+U02n8AXuRvXJlxBjlgLC/NAkBgWyqgIzRRJaO4WaBihyjy9HrZg0C9lOUKZybrF0B6Ryx - TMPlSE9ncrqEsDT4QIf4mxR640w8dgFlJJcejEweMj0VQjzlYaer/OADjZ47pmfMz9W3sx0sK17g - 5syYWNqlvD3v59qs08jS2LjaFSipjqgX5bJYOWlDK1CsRv4zy9+857GNG/7HfgFKoWfUnQ+ojbqe - d2kLmO7vX22XFefAEDG8GIUdGwzpN2js5WTnq4D4FhnHrjduwOCDmU+j9922kR8bibdbBcWp+AkA - AP//AwA8d/+VKAMAAA== - headers: - CF-RAY: - - 9472cb1ab8300f9d-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:30 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "178" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "180" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999978" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_80e6fc88a032fe8f219ac811f814ab16 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_chat_error_in_async_context.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_chat_error_in_async_context.yaml deleted file mode 100644 index 515fa958c..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_chat_error_in_async_context.yaml +++ /dev/null @@ -1,136 +0,0 @@ -interactions: - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini","stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "94" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: - 'data: {"id":"chatcmpl-BcNw8NWjpuphnc6XUr373KNPztVnm","object":"chat.completion.chunk","created":1748488176,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw8NWjpuphnc6XUr373KNPztVnm","object":"chat.completion.chunk","created":1748488176,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw8NWjpuphnc6XUr373KNPztVnm","object":"chat.completion.chunk","created":1748488176,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":" - +"},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw8NWjpuphnc6XUr373KNPztVnm","object":"chat.completion.chunk","created":1748488176,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw8NWjpuphnc6XUr373KNPztVnm","object":"chat.completion.chunk","created":1748488176,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw8NWjpuphnc6XUr373KNPztVnm","object":"chat.completion.chunk","created":1748488176,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":" - equals"},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw8NWjpuphnc6XUr373KNPztVnm","object":"chat.completion.chunk","created":1748488176,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw8NWjpuphnc6XUr373KNPztVnm","object":"chat.completion.chunk","created":1748488176,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":"24"},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw8NWjpuphnc6XUr373KNPztVnm","object":"chat.completion.chunk","created":1748488176,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw8NWjpuphnc6XUr373KNPztVnm","object":"chat.completion.chunk","created":1748488176,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}]} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9472cb3e4a3143a3-EWR - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:09:36 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=6F6f.fzRO5zVOYUAiT5bcPPwUQdXa4rd1.Y.JWbab3c-1748488176-1.0.1.1-3rRtjM2olNTj900mSmISyfar8.oJ7t1cim.lqyhd9WsTQRoOq15s9vIei1qlGpc0RNSE.k.NfV_pB6V7u14_8d65UPjg_T9XMxWxmzikiek; - path=/; expires=Thu, 29-May-25 03:39:36 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=sjaMQlGTaX81GpiBljyaHhtJFsUc2w0XMik._kxjX0I-1748488176747-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "258" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "264" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_65937b46a3e55615088e7d7ffa7eecee - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_chat_metrics.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_chat_metrics.yaml deleted file mode 100644 index 642af8dd9..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_chat_metrics.yaml +++ /dev/null @@ -1,209 +0,0 @@ -interactions: - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "80" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJBb9QwEIXv+RXWXNlUm5B20z2CFgkhcWHFAVRFXnuSGByPsScFVO1/ - R85uNym0Epcc5ps3eW88D5kQYDRsBaheshq8zd+oj/dk97u37/TPDe/Hz5/elx++yN1u36sRVklB - h2+o+FF1pWjwFtmQO2EVUDKmqcWmqqu6Lq5vJjCQRptknee8onwwzuTluqzy9SYv6rO6J6MwwlZ8 - zYQQ4mH6Jp9O4y/YivXqsTJgjLJD2F6ahIBANlVAxmgiS8ewmqEix+gm60UpXomiFPhjlDaKsrpa - NgZsxyiTWTdauwDSOWKZwk4W787keDFlqfOBDvEvKbTGmdg3AWUklwxEJg8TPWZC3E3hxyd5wAca - PDdM33H6XVGdxsG88hnWZ8bE0s7lslw9M6zRyNLYuNgdKKl61LNyXrQctaEFyBaR//Xy3OxTbOO6 - /xk/A6XQM+rGB9RGPc07twVM9/hS22XFk2GIGO6NwoYNhvQMGls52tOVQPwdGYemNa7D4IM5nUrr - m+sKD9VB39y+huyY/QEAAP//AwCneqYZOAMAAA== - headers: - CF-RAY: - - 9472cac2a9b5de94-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:17 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=sWxznHK8dnr1ZZ08z5I2ZQmEwYjE4jBJk7LVdWYJUuE-1748488157-1.0.1.1-OMtXQYC8D6Je324xeQLIUyQlY9MIs6utypvJSWqa3uNwhZaotZS8o0MSpWREfvi.DwtHSvqh.5PBYGEJIksaBKTyEJYL0Z9U4okloVN4Ly4; - path=/; expires=Thu, 29-May-25 03:39:17 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=BxEHCUb89UDvpZLsyNEYKOkIyI9A.ZgoPKiVXOWNsaY-1748488157116-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "431" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "436" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_0bcc2689dc900e9e3399c07d7a3c0f76 - status: - code: 200 - message: OK - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "80" - content-type: - - application/json - cookie: - - __cf_bm=sWxznHK8dnr1ZZ08z5I2ZQmEwYjE4jBJk7LVdWYJUuE-1748488157-1.0.1.1-OMtXQYC8D6Je324xeQLIUyQlY9MIs6utypvJSWqa3uNwhZaotZS8o0MSpWREfvi.DwtHSvqh.5PBYGEJIksaBKTyEJYL0Z9U4okloVN4Ly4; - _cfuvid=BxEHCUb89UDvpZLsyNEYKOkIyI9A.ZgoPKiVXOWNsaY-1748488157116-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJPT+MwEMXv+RTWXGlQE1IaegTxRystB067WqHItSeJwbGNPUEg1O++ - clKasAsSlxzmN2/y3njeEsZASdgwEC0n0TmdnovbZ3ftz3/J1xdxcdH+PL25dOr31d2q+SFhERV2 - +4CC3lXHwnZOIylrRiw8csI4NVsXZVGW2Wo9gM5K1FHWOEoLm3bKqDRf5kW6XKdZuVe3VgkMsGF/ - EsYYexu+0aeR+AIbtly8VzoMgTcIm0MTY+CtjhXgIahA3BAsJiisITSD9SxnRyzLGT71XAeWF8fz - Ro91H3g0a3qtZ4AbY4nHsIPF+z3ZHUxp2zhvt+EfKdTKqNBWHnmwJhoIZB0MdJcwdj+E7z/kAedt - 56gi+4jD77JiHAfTyidY7hlZ4noq5/nik2GVROJKh9nuQHDRopyU06J5L5WdgWQW+X8vn80eYyvT - fGf8BIRARygr51Eq8THv1OYx3uNXbYcVD4YhoH9WAitS6OMzSKx5r8crgfAaCLuqVqZB77waT6V2 - 1arAbbGVp2cnkOySvwAAAP//AwAdEpQmOAMAAA== - headers: - CF-RAY: - - 9472cac67e58de94-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:17 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "618" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "622" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_0a8ccc08cb9b28094ef71fec29946dbe - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_chat_streaming_async.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_chat_streaming_async.yaml deleted file mode 100644 index c51d1e702..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_chat_streaming_async.yaml +++ /dev/null @@ -1,271 +0,0 @@ -interactions: - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini","stream":true,"stream_options":{"include_usage":true}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "134" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: - 'data: {"id":"chatcmpl-BcNw1TcpT45K1JBmXqRdGP8bWXEsg","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1TcpT45K1JBmXqRdGP8bWXEsg","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1TcpT45K1JBmXqRdGP8bWXEsg","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":" - +"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1TcpT45K1JBmXqRdGP8bWXEsg","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1TcpT45K1JBmXqRdGP8bWXEsg","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1TcpT45K1JBmXqRdGP8bWXEsg","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":" - equals"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1TcpT45K1JBmXqRdGP8bWXEsg","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1TcpT45K1JBmXqRdGP8bWXEsg","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":"24"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1TcpT45K1JBmXqRdGP8bWXEsg","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1TcpT45K1JBmXqRdGP8bWXEsg","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1TcpT45K1JBmXqRdGP8bWXEsg","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_54eb4bd693","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":8,"total_tokens":22,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}}} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9472cb0fba02b295-EWR - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:09:29 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=UOMiv.S868Q9si.6iaHrxb9QmtUMkB6hpbJdsfYbS2I-1748488169-1.0.1.1-fRHbvwvzOTQqhRsu4RPT5ZyfaUX_DwxyHENDo7.X0zOBcWu_niWJBD5cmvDBWjXfEB3YZRU9cxHmPtmjyhG3rSIJPTUAkTnO_UdVjq_ocow; - path=/; expires=Thu, 29-May-25 03:39:29 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=VP44b.RP9HAvddSD71w9WOG9EnO.dwBkkNkzRK76STg-1748488169490-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "467" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "471" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_456232b7d84706bbb08d9f97e42c8aaf - status: - code: 200 - message: OK - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini","stream":true,"stream_options":{"include_usage":true}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "134" - content-type: - - application/json - cookie: - - __cf_bm=UOMiv.S868Q9si.6iaHrxb9QmtUMkB6hpbJdsfYbS2I-1748488169-1.0.1.1-fRHbvwvzOTQqhRsu4RPT5ZyfaUX_DwxyHENDo7.X0zOBcWu_niWJBD5cmvDBWjXfEB3YZRU9cxHmPtmjyhG3rSIJPTUAkTnO_UdVjq_ocow; - _cfuvid=VP44b.RP9HAvddSD71w9WOG9EnO.dwBkkNkzRK76STg-1748488169490-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: - 'data: {"id":"chatcmpl-BcNw1HPqJBzP7RFEwiJU8Vr0fOlA7","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1HPqJBzP7RFEwiJU8Vr0fOlA7","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1HPqJBzP7RFEwiJU8Vr0fOlA7","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - +"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1HPqJBzP7RFEwiJU8Vr0fOlA7","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1HPqJBzP7RFEwiJU8Vr0fOlA7","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1HPqJBzP7RFEwiJU8Vr0fOlA7","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - equals"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1HPqJBzP7RFEwiJU8Vr0fOlA7","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1HPqJBzP7RFEwiJU8Vr0fOlA7","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"24"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1HPqJBzP7RFEwiJU8Vr0fOlA7","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1HPqJBzP7RFEwiJU8Vr0fOlA7","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null} - - - data: {"id":"chatcmpl-BcNw1HPqJBzP7RFEwiJU8Vr0fOlA7","object":"chat.completion.chunk","created":1748488169,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":8,"total_tokens":22,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}}} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9472cb14bcb3b295-EWR - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:09:30 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "237" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "240" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_136a017bdaa43b7493f0c1484fc1e487 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_chat_streaming_sync.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_chat_streaming_sync.yaml deleted file mode 100644 index e666c5db6..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_chat_streaming_sync.yaml +++ /dev/null @@ -1,271 +0,0 @@ -interactions: - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini","stream":true,"stream_options":{"include_usage":true}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "134" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: - 'data: {"id":"chatcmpl-BcNvsUEkWF6Xk2kAAUSi21kgVYyER","object":"chat.completion.chunk","created":1748488160,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvsUEkWF6Xk2kAAUSi21kgVYyER","object":"chat.completion.chunk","created":1748488160,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvsUEkWF6Xk2kAAUSi21kgVYyER","object":"chat.completion.chunk","created":1748488160,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - +"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvsUEkWF6Xk2kAAUSi21kgVYyER","object":"chat.completion.chunk","created":1748488160,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvsUEkWF6Xk2kAAUSi21kgVYyER","object":"chat.completion.chunk","created":1748488160,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvsUEkWF6Xk2kAAUSi21kgVYyER","object":"chat.completion.chunk","created":1748488160,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - equals"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvsUEkWF6Xk2kAAUSi21kgVYyER","object":"chat.completion.chunk","created":1748488160,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvsUEkWF6Xk2kAAUSi21kgVYyER","object":"chat.completion.chunk","created":1748488160,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"24"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvsUEkWF6Xk2kAAUSi21kgVYyER","object":"chat.completion.chunk","created":1748488160,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvsUEkWF6Xk2kAAUSi21kgVYyER","object":"chat.completion.chunk","created":1748488160,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null} - - - data: {"id":"chatcmpl-BcNvsUEkWF6Xk2kAAUSi21kgVYyER","object":"chat.completion.chunk","created":1748488160,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":8,"total_tokens":22,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}}} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9472cadbaa3a6109-EWR - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:09:21 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=TaY3Tidv7pN1rwXifsEbRpgiJBSYyZmtrqFVhID5fxU-1748488161-1.0.1.1-yge4Qd_h2Czeue_4iHBseCabVMKErLW_dzyoNMs9A2ATm_3je1fFN03F_YfpeLqu1yq_W7BFbR0dqQpI_OxzTmh2tTKXdQDjQLoJP5ivPHI; - path=/; expires=Thu, 29-May-25 03:39:21 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=hV6VthxryE_9X2dzgxNwp6TyFZV.fQvAIpOzE5TrGpU-1748488161396-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "681" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "686" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_301ee2fbed0944b5203d0a79fc80645b - status: - code: 200 - message: OK - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini","stream":true,"stream_options":{"include_usage":true}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "134" - content-type: - - application/json - cookie: - - __cf_bm=TaY3Tidv7pN1rwXifsEbRpgiJBSYyZmtrqFVhID5fxU-1748488161-1.0.1.1-yge4Qd_h2Czeue_4iHBseCabVMKErLW_dzyoNMs9A2ATm_3je1fFN03F_YfpeLqu1yq_W7BFbR0dqQpI_OxzTmh2tTKXdQDjQLoJP5ivPHI; - _cfuvid=hV6VthxryE_9X2dzgxNwp6TyFZV.fQvAIpOzE5TrGpU-1748488161396-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: - 'data: {"id":"chatcmpl-BcNvt62bH7Bdi0CHQVKMIhuQTFiFp","object":"chat.completion.chunk","created":1748488161,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvt62bH7Bdi0CHQVKMIhuQTFiFp","object":"chat.completion.chunk","created":1748488161,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvt62bH7Bdi0CHQVKMIhuQTFiFp","object":"chat.completion.chunk","created":1748488161,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - +"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvt62bH7Bdi0CHQVKMIhuQTFiFp","object":"chat.completion.chunk","created":1748488161,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvt62bH7Bdi0CHQVKMIhuQTFiFp","object":"chat.completion.chunk","created":1748488161,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvt62bH7Bdi0CHQVKMIhuQTFiFp","object":"chat.completion.chunk","created":1748488161,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - equals"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvt62bH7Bdi0CHQVKMIhuQTFiFp","object":"chat.completion.chunk","created":1748488161,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvt62bH7Bdi0CHQVKMIhuQTFiFp","object":"chat.completion.chunk","created":1748488161,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"24"},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvt62bH7Bdi0CHQVKMIhuQTFiFp","object":"chat.completion.chunk","created":1748488161,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null} - - - data: {"id":"chatcmpl-BcNvt62bH7Bdi0CHQVKMIhuQTFiFp","object":"chat.completion.chunk","created":1748488161,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null} - - - data: {"id":"chatcmpl-BcNvt62bH7Bdi0CHQVKMIhuQTFiFp","object":"chat.completion.chunk","created":1748488161,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":8,"total_tokens":22,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}}} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9472cae2792a6109-EWR - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:09:21 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "192" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "195" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_2d19c07b9dca45eb4d8ba0070cf1d930 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_chat_with_system_prompt.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_chat_with_system_prompt.yaml deleted file mode 100644 index b06f3e580..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_chat_with_system_prompt.yaml +++ /dev/null @@ -1,213 +0,0 @@ -interactions: - - request: - body: - '{"messages":[{"role":"system","content":"You are a helpful assistant that - only responds with numbers."},{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "171" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJPb9swDMXv/hQCz3ERO0br5rjbFmCXod3QoTAUiXbUyaIg0UGHIt99 - kJ3Gzv4Au/jAHx/1+My3TAgwGrYC1EGy6r3NP6jPx2HzZefXxX738PXjp5fXQh0f73ffnmIJq6Sg - /QsqflfdKOq9RTbkJqwCSsY0tbir6qqui9tyBD1ptEnWec4rynvjTF6uyypf3+VFfVYfyCiMsBXf - MyGEeBu/yafT+ApbsV69V3qMUXYI20uTEBDIpgrIGE1k6RhWM1TkGN1ovayWIGA7RJnMucHaBZDO - Ecu03Gjp+UxOFxOWOh9oH3+TQmuciYcmoIzk0oORycNIT5kQz+Oyw5V/8IF6zw3TDxyfK++ncTBH - PMPizJhY2rm8OedzPazRyNLYuMgKlFQH1LNyDlYO2tACZIuV//Tyt9nT2sZ1/zN+BkqhZ9SND6iN - ut53bguY7u9fbZeIR8MQMRyNwoYNhvQbNLZysNNVQPwZGfumNa7D4IOZTqP1zW0py42sC2whO2W/ - AAAA//8DAPUSQJ0oAwAA - headers: - CF-RAY: - - 9472cae638e8729e-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:22 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=ZjFMv.ZBiAaxl1Viuy0f5jRd8ixQZ19ec_8wpRze.bM-1748488162-1.0.1.1-e3N5dLdVbtE2fHmcn5YnBArdFCyaNfIiqKi7O4Lm6KI_Bh8XD0YdOM7ae78nsBWU9JrmS.z5cjoWY0WEFiX1_cogG4FtdPT0icCthH6KmIM; - path=/; expires=Thu, 29-May-25 03:39:22 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=wb9yw2JAvgu0HpK0Nc1hbHujFW3ggVyfVof1qMIIYD8-1748488162935-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "522" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "528" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999978" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_0f090d58b49555167feb876d72030990 - status: - code: 200 - message: OK - - request: - body: - '{"messages":[{"role":"system","content":"You are a helpful assistant that - only responds with numbers."},{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "171" - content-type: - - application/json - cookie: - - __cf_bm=ZjFMv.ZBiAaxl1Viuy0f5jRd8ixQZ19ec_8wpRze.bM-1748488162-1.0.1.1-e3N5dLdVbtE2fHmcn5YnBArdFCyaNfIiqKi7O4Lm6KI_Bh8XD0YdOM7ae78nsBWU9JrmS.z5cjoWY0WEFiX1_cogG4FtdPT0icCthH6KmIM; - _cfuvid=wb9yw2JAvgu0HpK0Nc1hbHujFW3ggVyfVof1qMIIYD8-1748488162935-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJPb9swDMXv/hQCz/GQP+6a5DgUxXYZsAJbgRaFoUq0zVWWNInOFhT5 - 7oXsNHbaDdjFB/74qMdnPmdCAGnYClCNZNV6k39SX3e7u92Xq/2Pz/b2qtl/v+brm1/0+1v9tIFZ - UrjHn6j4VfVBudYbZHJ2wCqgZExTF5fFulivFx9XPWidRpNktee8cHlLlvLlfFnk88t8sT6qG0cK - I2zFfSaEEM/9N/m0Gv/AVsxnr5UWY5Q1wvbUJAQEZ1IFZIwUWVqG2QiVs4y2t74spiBg1UWZzNnO - mAmQ1jqWabne0sORHE4mjKt9cI/xjRQqshSbMqCMzqYHIzsPPT1kQjz0y3Zn/sEH13ou2T1h/9xy - M4yDMeIRLo6MHUszllfHfM6HlRpZkomTrEBJ1aAelWOwstPkJiCbrPzey99mD2uTrf9n/AiUQs+o - Sx9Qkzrfd2wLmO7vX22niHvDEDHsSGHJhCH9Bo2V7MxwFRD3kbEtK7I1Bh9oOI3Kl6tCXhQSNysF - 2SF7AQAA//8DAPAiMEYoAwAA - headers: - CF-RAY: - - 9472caea8b03729e-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:23 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "506" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "516" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999978" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_5e8e2c038b495d648c008856b7457541 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_client_async_comparison.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_client_async_comparison.yaml deleted file mode 100644 index 882dab033..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_client_async_comparison.yaml +++ /dev/null @@ -1,212 +0,0 @@ -interactions: - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini","seed":42,"temperature":0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "106" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJBb9QwEIXv+RXWXLupEhORsMce2iIBQogDCFWRa0+ybh3b2BNaqPa/ - IyfbTQqt1EsO882bvDeeh4wx0Aq2DOROkBy8yc/kp7sqfPzz/tv9Z3759a64/X75RVUX52f8w1vY - JIW7vkFJj6pT6QZvkLSzM5YBBWGaWtZVUzVNWfMJDE6hSbLeU165fNBW57zgVV7Uedkc1DunJUbY - sh8ZY4w9TN/k0yq8hy0rNo+VAWMUPcL22MQYBGdSBUSMOpKwBJsFSmcJ7WS95OyElZzhz1GYyHh1 - um4M2I1RJLN2NGYFhLWORAo7Wbw6kP3RlHG9D+46/iOFTlsdd21AEZ1NBiI5DxPdZ4xdTeHHJ3nA - Bzd4asnd4vS7sprHwbLyBTYHRo6EWcqcb54Z1iokoU1c7Q6kkDtUi3JZtBiVdiuQrSL/7+W52XNs - bfvXjF+AlOgJVesDKi2f5l3aAqZ7fKntuOLJMEQMv7TEljSG9AwKOzGa+Uog/o6EQ9tp22PwQc+n - 0vn2HcfiTV0XTQnZPvsLAAD//wMAdPse5DgDAAA= - headers: - CF-RAY: - - 9472cb1dff31728a-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:32 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=ACvanrvDDdClYpufGDkvW3WdIRGVOem0UIhBjCRp4HE-1748488172-1.0.1.1-EbrqjqvlfugpDE5yBVbLhKNcI5siYyYyO1_gfUyFH19kF.u4BAL5vgjZ1YR_NXBIlbzchla2gDsOD8lMbVoeZzL977owwr85YNr6LjdeJkg; - path=/; expires=Thu, 29-May-25 03:39:32 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=NfWilA6YB4UOd_P4xU1o9cre4ute9B0ASs9R0fnJpKQ-1748488172895-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "426" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "429" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_001a33a36414defefecd0088fcc9672e - status: - code: 200 - message: OK - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini","seed":42,"temperature":0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "106" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJBT9wwEIXv+RXWXNmgjUnZdI+IS4taFS49IBR57UnW4NjGntBWaP87 - crK7CRQkLjnMN2/y3nieM8ZAK1gzkFtBsvMmv5A//3y5+n3xXd/YR7U8v3n6el3+uPz26zpsrmCR - FG5zj5IOqlPpOm+QtLMjlgEFYZparMqqrKpidTaAzik0SdZ6ykuXd9rqnC95mS9XeVHt1VunJUZY - s9uMMcaeh2/yaRX+hTVbLg6VDmMULcL62MQYBGdSBUSMOpKwBIsJSmcJ7WC94OyEFZzhYy9MZLw8 - nTcGbPooklnbGzMDwlpHIoUdLN7tye5oyrjWB7eJb6TQaKvjtg4oorPJQCTnYaC7jLG7IXz/Kg/4 - 4DpPNbkHHH5XlOM4mFY+wWrPyJEwU5nzxTvDaoUktImz3YEUcotqUk6LFr3SbgayWeT/vbw3e4yt - bfuZ8ROQEj2hqn1ApeXrvFNbwHSPH7UdVzwYhojhSUusSWNIz6CwEb0ZrwTiv0jY1Y22LQYf9Hgq - ja/PueBnoiqwgWyXvQAAAP//AwAEquOGOAMAAA== - headers: - CF-RAY: - - 9472cb291a25d826-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:33 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=YVSQNhGU5D_XZKKHlGiF2ASuyzAJ6dCDpQHNZ0PK45Y-1748488173-1.0.1.1-6Fwa3GoGwXMRDtobRN38cHAxxT.1JgwMWTJ8NyXBuRGzdJEkZt7GiwmbWmxIXXzJe0nsxMGCcP7gxTKgOw_ZmAwoh_dRaKeQqI3tYMpKZgQ; - path=/; expires=Thu, 29-May-25 03:39:33 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=qt53dwZTdoU.J1LuD_WqqiwsjRgIE6Lh9ziMs5KTO0s-1748488173691-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "605" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "608" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_454870f19e34ada2f4d3403f7a46ba71 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_client_async_error.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_client_async_error.yaml deleted file mode 100644 index d7a5d7c18..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_client_async_error.yaml +++ /dev/null @@ -1,83 +0,0 @@ -interactions: - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"non-existent-model"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "87" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA0yOQQ6DMBAD77zCyrn0Abyj9xCRbYkUdmmyQUWIv1faHsrRY1v20QGAo1KkuAGH - SUML1Rpe5Aa4x0xYJFLGyMI9fVJVYu2NjYhCFSwKMyAFuzREMTaHjRCmiWqFCpLe3e0/ovtqC4m3 - kFP0hd6Nqvrfn0twDSUsbgC3nC94kmh9e+JZ1D+lcXSWOLuz+wIAAP//AwDwJ9T24AAAAA== - headers: - CF-RAY: - - 9472cb2e5cc31a2c-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 29 May 2025 03:09:34 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=GTQ9lK9aXIagrFFLKxGeQ4yhPX4.lqMiHUg2tpn490s-1748488174-1.0.1.1-UjbQXOzWFJv3y_C9.kzpGt0eEcKc0AhkeNO1KD1i3oD2g6PUQkx_FyTPdHmt9YmN2xQ0cch2zfV5plYuuMeCXgPtbRPZ4iACGpmMp.mwVwA; - path=/; expires=Thu, 29-May-25 03:39:34 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=2FR2R_eFbznKP3sn24Ec_2XMfvCR.7ohFqG6v9C1COM-1748488174092-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - vary: - - Origin - x-request-id: - - req_98c81147f2f025a021ed636bd814c3e3 - status: - code: 404 - message: Not Found -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_client_comparison.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_client_comparison.yaml deleted file mode 100644 index 3932b26f9..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_client_comparison.yaml +++ /dev/null @@ -1,209 +0,0 @@ -interactions: - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini","seed":42,"temperature":0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "106" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJBb9QwEIXv+RXWXNlUSRrYsMflAhwqBEgcUBW59iRrcGzjmayKqv3v - yMl2k5YicclhvnmT98bzkAkBRsNOgDpIVkOw+V7dHI/f9h/ku7p8/+Xz65t9Q1/H7t7Qp489bJLC - 3/1AxY+qK+WHYJGNdzNWESVjmlpu66ZumvLN9QQGr9EmWR84r30+GGfyqqjqvNjmZXNWH7xRSLAT - 3zMhhHiYvsmn03gPO1FsHisDEskeYXdpEgKit6kCksgQS8ewWaDyjtFN1stKvBJlJfDXKC2Jqr5a - N0bsRpLJrButXQHpnGeZwk4Wb8/kdDFlfR+iv6NnUuiMM3RoI0ryLhkg9gEmesqEuJ3Cj0/yQIh+ - CNyy/4nT78p6HgfLyhfYnBl7lnYpV9XmhWGtRpbG0mp3oKQ6oF6Uy6LlqI1fgWwV+W8vL82eYxvX - /8/4BSiFgVG3IaI26mnepS1iusd/tV1WPBkGwng0Cls2GNMzaOzkaOcrAfpNjEPbGddjDNHMp9KF - 9m2FxfV2WzQlZKfsDwAAAP//AwCwMJgnOAMAAA== - headers: - CF-RAY: - - 9472caeefc07c674-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:24 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=JTYI3VmC3Z.1ZeFlZm0UnBhg2e9UAoSRy3zE2PqNvx8-1748488164-1.0.1.1-2a78CsWXdJSzVCF.0zBiK_lG_F1SKSU1dLyaFM.ijiP5Y0sgwpUrntITdlPTueXdgaijiedgYyvNt358XySz3XlnJVzWagAeB8kWr.0GzPI; - path=/; expires=Thu, 29-May-25 03:39:24 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=Q79oKiMDrSwA4zGocgHI.nmRNlEbok1i5HNAivxJMOM-1748488164364-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "575" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "580" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_49fc0026e0914ff639e48ccfac1f6b2f - status: - code: 200 - message: OK - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini","seed":42,"temperature":0}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "106" - content-type: - - application/json - cookie: - - __cf_bm=JTYI3VmC3Z.1ZeFlZm0UnBhg2e9UAoSRy3zE2PqNvx8-1748488164-1.0.1.1-2a78CsWXdJSzVCF.0zBiK_lG_F1SKSU1dLyaFM.ijiP5Y0sgwpUrntITdlPTueXdgaijiedgYyvNt358XySz3XlnJVzWagAeB8kWr.0GzPI; - _cfuvid=Q79oKiMDrSwA4zGocgHI.nmRNlEbok1i5HNAivxJMOM-1748488164364-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJPb9QwEMXv+RTWXNlUG9fQsEekIiEkTggkUBW59iTrxf+wJ6Wo2u+O - nGw3aSkSlxzmN2/y3ngeKsbAaNgxUHtJykVbv1Of7n69H7aHr+ra8Y/fWqfuuRWHzx+u3RfYFEW4 - PaCiR9WFCi5aJBP8jFVCSVimNleiFW3bvBETcEGjLbIhUi1C7Yw3Nd9yUW+v6qY9qffBKMywY98r - xhh7mL7Fp9d4Dzu23TxWHOYsB4TduYkxSMGWCsicTSbpCTYLVMET+sl6w9kr1nCGP0dpM+PiYt2Y - sB+zLGb9aO0KSO8DyRJ2snhzIsezKRuGmMJtfiaF3niT911CmYMvBjKFCBM9VozdTOHHJ3kgpuAi - dRR+4PS7RszjYFn5AtsTo0DSLmXONy8M6zSSNDavdgdKqj3qRbksWo7ahBWoVpH/9vLS7Dm28cP/ - jF+AUhgJdRcTaqOe5l3aEpZ7/FfbecWTYciY7ozCjgym8gwaezna+Uog/86EruuNHzDFZOZT6WN3 - KeRrIfHtpYLqWP0BAAD//wMAEKy8gTgDAAA= - headers: - CF-RAY: - - 9472caf36d88c674-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:24 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "319" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "321" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_aed77d6d5688f5c0ab576274999fdb80 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_client_error.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_client_error.yaml deleted file mode 100644 index fd44671de..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_client_error.yaml +++ /dev/null @@ -1,83 +0,0 @@ -interactions: - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"non-existent-model"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "87" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA0yOQQ6DMBAD77zCyrn0Abyj9xCRbYkUdmmyQUWIv1faHsrRY1v20QGAo1KkuAGH - SUML1Rpe5Aa4x0xYJFLGyMI9fVJVYu2NjYhCFSwKMyAFuzREMTaHjRCmiWqFCpLe3e0/ovtqC4m3 - kFP0hd6Nqvrfn0twDSUsbgC3nC94kmh9e+JZ1D+lcXSWOLuz+wIAAP//AwDwJ9T24AAAAA== - headers: - CF-RAY: - - 9472caf6acdb42e9-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=utf-8 - Date: - - Thu, 29 May 2025 03:09:25 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=tw5RpvNcilfwjUjOiCvIStwbXJbeRE_xXCqPZ.4RX7I-1748488165-1.0.1.1-FMTa0ZJqNJbuNSSA6DphhFklanxkVYlP.JqvtvujJtr4sYPh9SpE3tA0RGm.xS6wbQPTr3XYwQizdw4hssI3nii8ASbX11MhrVl9x0YOMrE; - path=/; expires=Thu, 29-May-25 03:39:25 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=2B8C1K9X3JEAGR.xZd9FRJAYUg1T1ogs5tZIZzvxNiI-1748488165031-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - vary: - - Origin - x-request-id: - - req_51b61b333398d569debb6e253ba8335a - status: - code: 404 - message: Not Found -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_embeddings.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_embeddings.yaml deleted file mode 100644 index ea70423b2..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_embeddings.yaml +++ /dev/null @@ -1,426 +0,0 @@ -interactions: - - request: - body: '{"input":"This is a test","model":"text-embedding-ada-002","encoding_format":"base64"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "86" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/embeddings - response: - body: - string: !!binary | - H4sIAAAAAAAAA1SXy9KyOhaG530VX/1Tu0pEIMs9AznIyQTkoPZIUBHEE5AE0jff5beruqsnDMKa - rCTv86z8+x8/P39eRXMphz9//fxp637488/v2vk0nP789fOvf/z8/Pz8+/f7f5WXR3E5n+tn9Vv+ - +7N+ni/jn79+pP+u/K/or58/nn6w2JZ0RddHMTqpiSIrVK6uU8HD8yGC9HkTjOhZiwYpU9YaRnrI - it25aqY8e0mA+3vGrKY3xFAfI4CsXhwwofbY8MsJ3dWZfPeJlcIsGPxFZ6HVsJnwdB1JN0ZNf4d6 - nD+Zs8xYx6Pd444kkCJ24sen4IZb+/D6yIKEu3dTTPt8sLRl7WbskD1I04U7aQY0O3RM/+Cm4Lct - T0HSdYmFbWWbo0yUCpbT9YPlu92hyWiPMqrjh0FLJa8bOgp1B5/0VTHLfg/J+NycSqBCEWwdOUYg - maY1aVazqajwrFfCUikM0TELemIfPl4ivL2CUaK8bHZ0rkYj1Od9BsmnaTC/Gr3JdTe20KI4vYml - vRTBvOvFQt48GTEo+4cYL914B/lpNti8Ag7YXRYSHLwupfL22Recnj0LxTyNiVtJXTC0adYDbZst - CzbRu5jurf+CdlFecC64VtBNUqTa1jQH4s6zfTA1vXMCbSkohcF9mpN1lUrYl4sl2ThuVUxb7agD - uosZvqkvo1lsjNgBc98d2TaJOOrtVb5DO/2ZYXGd5V1veFkOT8PYsO2Q2B1d3A4vFC3Ilfi9wAmd - mWsHHvZQE/+44mg4zgx/dZrxljhxt0rORoFrrXqfKLNmWxpwErsYjs2BEw8/rsl4T9wDDMr7ymx2 - XzaTu/U56mYPyvwXNzrJlo0L1OPqSReeAoLvNeeA7MjmJGj3zJxWHkxA3mxDQs4sxLu3bq3a9rBl - sZtUHbdl74K6KjkRO15vCr69bigYxKpYOHhdMn3CTwWq9gHmoSVJ+EsuT6BzlWLRhZP5lNTTAQzQ - r7Qal+9GnHElre6FSHA3Gmp38xeNA/JjujLvbV0Ei+ZvC6naeKHyrH4g0XJIYe0fbJJc0VuMohQc - bvlhRukjWRS0C9EDHjariX7VN2ihWX0PqJYJs0o3Nod9MP+gowUqXT28IuDfvKLA5R67nJ518t3P - EGbeJyCbuScln9BoNfS9/8S2pQCN9fGja8hZT3QxO/TNNErFAdbqRsf9ptiIfmGbzrzRI8CXAVAz - LV5DiW4Sckh404Jm+W6vJXjrpMbL+PhqhmFxB0gC6cU2Hl8nYs2jHLa3Y8LC4THrhsw/7qBa9iYL - dtd3MN6TY4mO45STACtdQm/jqQfX9jmeW3ta9HEgNDg2+RXXK7kXfHsZ7siL7ksS5n1kUvPx9KHv - TgGxy11X3KEXAPO2eBLfH0LEpRDLaJILjc6pkwmuTm4Eh5dXMv3Ta2JYxlsJivORkC08T91Edbhr - +5PikkAJrEDUq/CAbvmZ4ClqpGKIz62DRv9zoWOzxeKDJfeC+u4QMKKLczJmMbUgjrUT5o2ZNiP+ - OBgCf1CIndlS0Cs6kdG3P7Yu6FqMWXxeg1hDQs7Q7sxeUbQZalZJgKfUG0S/s7gPiyI9MJNhrRFf - 3sBMaVS8qs1bNyzyDqOz/aiJr1hyd//2p5Z+hpmxGnLE23VSwrzFEtOLUkbi6qUVolnkYeUY3AU3 - vHMKItHvZCuhZzeexfWCTtU5Jmsjlbrhm0+kV7VLNj5WhSizxQuokGs6yVFS0OTNJG07p09id9Wj - oTHLI3jGwRsrO102RRAr/W/+2PbN0oaerccDivO1YuaXn49JWlSwV8sb2zWHoWDLITmADS+XWM3w - CKbQKCWwrFLGY2qAOUlPLQIO4RPPxy4wO+IksvY9D7b++kMcbqcKhTY/UhUVVcGwrfZwL5Z3CoNP - mjHz3RCRt6qRIL+NDY0WDwnkRfRk4ebUdONxBilEbjYy1xnzRAjVS1GYe3NmFG2PRv2oYvDm8Uj3 - X1526rPQYCMLH+dlaXcjLKMU/EL2GV44j2Aw09UM5UZC2Lpgz4Aj8fgAq5BJ2yoVgvaOrsFLW2X4 - PS/v3bR4zWo0z/yG+WaVNVyevU9wbtGSOQe5D0SZ3e9IfsicfXluTkSq70CFVNNppWTFZFV2jS6R - smHWk+/QpOUU0OXmaLi1ZSmh9Ue1ILxHt799I3759ahPZ4KTCwT0kM9cxOpuTrWLvmo+armsQfMs - QWyN+x2nZ8NBK5TKzL/o56Z35F2lbR6fF7FmvpEsWZiF8PZyRAz1deum3okBdphvWPo9z57e6QxV - 6nsi2ySKhKC7tId9ybJfPweLzD9GMG8TmxjquxUTR44DThFNxN84JBgPNrNQ0b0SZgsvFOKMRwX2 - 6ili5iQY4lN8D0HdIk7sMlqLxS5/p/D1K7MOTYHGqFm8IAkUFWfGZBbM6eahOnjSmmByCszJvBoR - wtjakjQ9r5PpujRcKJfxlmCgrrlsOeTItYlBTMobc4TZ4MKUgcks7Sl1w+0alauvf+hczz8mTeti - jeLa3mJu1a+Ga9Pxy8MiYcZ+xoJX/8kOQN5II8Em3jaToIkCNLsAnoP2QUJSmxIW3TCjq3Gfd4+I - 6gAHuRzZ2lreCqFVbwzaszz++tMc8QdjTV/rOskZjcW4jC8KbB6vF9k4wWCOb/fJQTfVC+afXkM8 - PN9SYLsTwqsxn5Ju04Y1XPsLYy5i52Zs08eE/G3rYJTbdTdMTXZCLw1Z+Hs/ulGcQwklwdwnxnRF - yZDsywp9fca8jN4K/pblCvbhJcZwVhpzelzb3d95niet103vJPTRL5/8N1aDzz5fA7ofZw7RR2UQ - 49PhOcqNYqRyjD/mGN2vXFuVfcj8DLnJ2KbnHk6UpsS9xZdCVOubDEkw7ZkTE5ow9yJg9WTPK1mv - lrEpjjf4oDANI2Y2t6aY0jpZrxRmJSzI7XXDF5amI6LoJdYUS26o5xwsqG+0oUzNsoZXaQwAM2xR - 5bzdFqO/OOmIQ+ZR9Shp4tVsFAk92WWF23U8N1m1PnBQS1+iXL9Zyat8yjKayQ+fPsqy7Sbzusth - LmqP6FbtNqw/zFIE5nZBeXH8mLzZKDIYgygwH5Wt+O0P3TarDVnT5xAMzcnyoZtdQuaUpd3wTHmt - UeSUCQtOjiPExY12yC8kn2Fy6r7zUEdRZ1SYOfbqhsZyVC0Qc1knev24FZPRxvLf87K77MJuuQ2T - fCXW2pp5t0Lp2P7ZOBDdNZ+5jpihUT/5O3jL/oEZssW77/x1gszazSlbxPduvPQFhfK59r7vgZvg - wldr1ZS309/z1Oe8qicwiE6IvdyeBbt6wwOCZfugNLmUgVilRx99+U22Q9I2fHZVeqiWPCWmfLC/ - Ppgi+KSLhG0vlSRofsYUfvniovgRjM0pC2F9KnO2YUoYjFu+7bXdRXvTedK+uwmRnQ9gRA7xe2nX - cOg/GsL9I6PyQUmbyT56E+zDzqKg7B3EwuTqgEHckTiadkf8bqgpusJNJ0TNVdHrrq6vvvliZP+5 - fN8X+qQ63d5kVpc2gk1zSYeNPPrk62cxXtvbGpEAz5nZ/AcAAP//TJpbz4K8uq7Px68Y+U7JiIBK - H+YZAiLbFkFRkpkZcI8i+0KbzP++gu/Kyjo1GhDae3M9LVrErff+gNAhO1NzqSV8Mg5vBZicKtR+ - p1ouG3cn+vWRQXEbzViO2/SC1H7L6O6YTx7b060PH7scB3XOM3+/r/wwo/dXpiPOtcT/7Xeqre9e - wdHzcAZrPdQD3A7M4zHnLsz+M0z3at0y+XVQgE81HpTxbBTSWLFRpbpvk3Rx673m5xexN56I+R3c - nFdv3YVTayGqy9hF4+IRyfBM7gRXneFyShZnDaI+eQzMXDucQ8ZGRNJKJl6FHt7UiesRnZ3+Q/X7 - 8TH7+eb20zu8qm7HlhHJ7CAtnhE1H84x59S/+hDsjzrRN1FndFt5cwF/O9gEv/DDGwt7owDbTSEJ - XhaOO+heCpSHnY1RUmQeE/S1Du3DXRHnevbQKHyDB9yh0AbIIqfgx8HswBDPH6LbqoKG9WXxQPYx - Ff/WS1fsRhnx59mlKS4XeR8lSgbtY5+R3RtvuLQluxc8XKUkpvI9tGxUVB2un/VykPfBlg9tYFbq - IlFHYoT0ZPArrkRojbs6lIo6tWx9RCPMeksxTAc0bLpFB4oNe3LTnMKbvviGUfixVPy6ixCPiweA - MudH+rvf76x/v/yNaXk/e1xUgnKdCDbQc7RR4iYc5nf1GELqjLjOmRXrEfqqckG1pk2KyZU0QW3v - gkm28vAyJm9YZdCheu4fOx/V0ilI4HyCemCq7PPp1umV+svHq3f6iAeMlmewJwhwR8zBG6F7rcDy - RUS9OkN83NGVAv62s+lW4ct8sDKsobN8m/CivLQ5/YxFBD6rdnRbLB/5FCXsDG6QxcTdbV0+Zcux - BEUSnsMkW6k34pOiKIGx6f/0aRC/LIIFH4AST/22rNecTAkWKBtkRXlzth/ARpvr60R1OSiLiV9N - EfrzwaWXbL+NeaQcmNIUdoWXx8xHw/qovUHKbwqWzt2EWBWFoHZ4elInCVSPX4kr/PWnSu8/8SSH - mxKd1i82CJJVGlXa1fP+X6hYuHWnYmqR9AJtnHzi6KuC10HtgFIetvbwUcamHWsaNmjWK7ykyy9q - Oks0QUhlYX6/GRplITyAHZdf8vNbmuWSC7/3b+npiBq6SQZ4lsVjCExdaru0Y3Oeihj1kkLx6Gqw - SjDN547sHlWVs34X2EvYtx3VzPfk9WbAsKpnrUO35172OrbvfBSv2HfuB4d2ml4NBuOzuuIlv21b - mYnqC3jsWXTHlUPLiIga5AZfCy9O/jdn5b0PYV5vmH8/YsyF43BDAW0S6o6ZbzB398kg0NceITkR - jfbnB9J6oVMM41jwLO9M9M6lN7EE4chZONgCwsi6UnKT+nZ4tbGPGn7KcZ9dK4MW8n5A/Jm51Jh5 - BZv7JXoHaT+Mk7QxZn/AMGUDxatlY+dTtWsfaAQ7oYdN+Wj7pbPWYaU+XLqroogz1SkGOJ/EHd3E - 6BVP0yu1UWkIJfVvidJ2opdXMOsj/r67NO6FiQko2EfTgOozj3s9rhpgiX6gW0FELZ+skinTem/T - QFSKfOTRPUOz3hI8rw/aXNclkPR1GBTDLNvJhcUKXY+9SbC0faJh1kPlGD0MunuHTcxe7AbQXb0d - 9dzl1+uRcDBh5itkY1JaNL++Nfsvec/8rRWO1wwdo/JASKO/+fjEm7N6D8Qtlq0NQ8Oc31Eb6glx - 9LVtLAO/O6OkFxz8EURUtPX18YLr22yov7t0Xr/T/QiouSuptfc3rQTL5xkhbujUW3lvY9R17QXD - p6bECqqwZeA4Jai4SLEw8wpeTskFtOh0pJr2NHP+GR37p39YhXc/95lSADMCgbjX5xONlaSEIIZe - MvCffj50pih7o02wdAl1xAIF2UhwKu/H29DsVy4cvgXHsvMp+F8eTYT9DaPPiRh9ttpUwGNyIlqe - Nt7YNYsHLD7HhAYi2hXslFw0dGodnzopYzH/jG0ExulrEwe/ZfTrj4qwOlnUyNebfOolWYO7Mpq4 - iWIrH8r7BYNiKxrZoUJBfYvUF1yPDZ/z/CZeelG7Atx1S5L/eIhguNbv+fzxVy4pdAA7vmxpuriY - 7fJUBT7SKyUY1OmIPV6/pQTYrrxS7+ae0LRydQuoHqV/PIunr6CDorfOM2+lxTi8S0HZx9Nq1rcO - jU69PsPHbjfEdRvNo773cCFeDQmGLNx49S//17J9xsKqL1DDh05A8/Onuo2ieN7fkaJ8S4THu/ad - ++1eUNiOh9RdLp5Gu22vFgIq3sgmL8z4Tx+2dwXwIi571K1WTIC8lSyqmZ9jPmB0DCHpwaFhWQ9G - 11A2Ko+l/CGGnAUtFY5mghbJYsShajn5+MTZDf34bTqSvuhToQ3hym7hkF8HGzHpGTaodvx0ELzp - jSZS6Bd1V3ZriqVdk0/SaTvnue/+T0+azGErdFqfQ6IrEeJTlDwTpTlwndrdRs8la2Nr4IR9OvzW - m3Tylg1axiMllyxyWm4ywuAeKMkw3je+t8Z1rkH2+PC//NBraeUi+fzthi8qFD4erG8JQ9FpeHk1 - T3EzKqqmjHByqCZdC49p7f6AYNwVWCx6y+h7SdBRnX4W1IWtwv/47Qj4S/xdvpv7XRiqt8VjpO5K - x8a03Acyqr9LY+CCtjOkTSbd0MX1O+o8FvXcx64+splJiYNWvOi6xjzANtyNWF29trE481LAtyun - wer1iZn4PduwHfAeo1205/P3E2j4Mae6/2z5dPIWFVjrrh5WOINiylfZAD/+vT1uD97MBwR4LAeD - mg5+FdNxf9SA7ZqBakN0iBldr8Zf/xmkc9sXny9OMGxhSIe1+9iiaZNbrz+eIlcOoGmTdWf0SA9X - vFq2XdGhTmMQ8nNE3Y8fzvOH5qFcxcAnFh+znFbFQ1eV9Lgk+CPr3hS+TyPM/oc392pdMPORvNE7 - n2KCPeYY3fP4DZEirUIa9AcH9bAME9Q+7NU8bzDi5ZX0FpiRINCZZ+Zc7h4YfPEjk00jhWjWlwYO - NnKwMD38gu9uGgPEd/HAz6e1x4y7M/PJWCBESxqvi3xTQGYkXwieXpIxoe1phQ4SW1K9VF9t++Nr - tYNTsg0uwdyXVwcwTnVKbL3f5kxJTBHm+cQgbaXQkPvFGEF1SdqfvxvsTOrDX36d+1UrJxepUW+L - 74aYNLvGcvGuHmj5Mk1yg0nkTH5dVtDu1yLdfkEqqJd+G9iV5Ym6zy/Kp1RwXDic0j0uD2JR/OW/ - +lSF1MXRy5uKlJtq1EeEBqJwiMe092y04FVL49aPvMnEh+Svr2TJaRmPJXp0sO5O39n/rHbs36YM - lbI2Z57/RjOPbGD/iDRCPDByCRYkQlcxvhLD2R09ljm1iGA0IuKm4LfMsUJLVVJyxHfzHLWjwvYH - eNSXBQmSFUN9ZQcNzPmABqYpeMNVtRtgJ+lJDL9z43E6UwHN/k+u8A74pK6M12//U33ml+NWTUIY - LEH809sxG0iGdP8oEheP63a8PEIBAl1WiBE4atHJwjkBEVZPYqd+bfQzn0E/P79k9MJ5dsEY7t2F - 0tjZdsV061RRmedD1A7QA3HqIQt974ec7htp5PQFqQ/utZ95j63lXU3PFfz2f3K5fIr6cyhHmPWD - 2G+Zt1xfChi+qlgQ55od4unoar6CmDAR/Np3fBC/oata6+Y88/IMSa/0DHD4NEfiVN+2nVzJBjT3 - qaF8v+5eJ5mKDq/ncjsIa3dpdCXoMoTJW8LyPI+ipy+4yPLHZtYzw+vF46ipUuB8hnXKk4KNSiGs - ZTupiG6utjOPzXw088HZHwL0vTveBfjUYrqznHfBvJ1w++kB1da3XVx3gEvYDv6eBtpmH7PjJX/B - 7UkuGAyxmftBLf7mVWTTrK5Fj4SLpWi6uf9bb/QtIxmu24tGr7fXNZ75swxcX+nEYKJosKv6GuGm - P55EN9f1H59SfcbqYXk1YmOMt22CzCfWB0kedI8FSmOiYI8f1OsWe2PZnS8+2u+FlphKGeb9IaxF - OE7WhdjVdR+XE58i2N7VgBBSbDzJxF6kDHxhDhO7nebr7zvwtyz96wv8/CzeYOxeS1wFQtDyQtYq - 9fhansnGPx85e7W6q6ZHpyMk/tQF/7Zb5ceH8GTHj4KK6+IG83wESxcqtGO8zUJk5XZIgrr3Dd7v - WQmezRxKXqts5m1+gy7ZfST41tA5zzXVjxfi5THfe616sC0I6HtL9fC9Krq2tq0/vh8HjtoOrsV8 - qE/Dk/z8oyP71wGs9mgQV7xdPdb4rwf85hee0Z3jCQmeDnV6vxLdRiynar7QlLhJRuJVYObzegGo - T90Tq5H45MwoqQs72yTkl89Zlcrin/7av+cTapcEuotwoMGU3r1u8XAYzPkbA9E/7RSf5ErtUEtw - Fh2adrw+TRts5mjEvNiTMX50/Qy/eapxRzWicldhMM22JoGpH4vxsNg0YF23C2rckYMkB44jrLRu - oO7HtWe/fgtAvNNzmIbcjf/mI7Vs7YgWT7bBFlBlyJwyaRjNouNj2ikWLF/ukVozDxhPbP2GH9/9 - 8ezRHiUXeKy/iSeWGM3/Z1TWubAZgGyjmP3mM+FbyOc+sSymBfP1nz5Ty9pEfKq1UYZViJ50Z30v - xo8Ho39+pwL+91///vd//04YlNX19pkPBvS3qf/P/zsq8J/smv1HFOX/UPnvJMLQZY/bP//1fw8h - /FO3VVn3/9NX79u3++e//r36O23wT1/12ef/+/hf87X+91//BwAA//8DAHFvCBnhIAAA - headers: - CF-RAY: - - 9472cad75e7d1dc7-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:20 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=mOY1pyZf5R_Fm39ytE7OEGT0QQqo6zcG8W19tabX30s-1748488160-1.0.1.1-mhciSfzy_b3DeaPf5BbNjbQXsXXkBtmfbXvDmkldQhBHTSfebdNABaEhP6tSrC2uGK40q3ben8eanuh.gGR6X1bzC7s3dZ_dyQMZvWltzs4; - path=/; expires=Thu, 29-May-25 03:39:20 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=TrlgR7KvGJcRBCctTJMQIWVZDzxtCcOkEArqx2kI7eo-1748488160236-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-allow-origin: - - "*" - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-model: - - text-embedding-ada-002-v2 - openai-organization: - - braintrust-data - openai-processing-ms: - - "56" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - envoy-router-6b84dbcf9f-jlp7n - x-envoy-upstream-service-time: - - "59" - x-ratelimit-limit-requests: - - "10000" - x-ratelimit-limit-tokens: - - "10000000" - x-ratelimit-remaining-requests: - - "9999" - x-ratelimit-remaining-tokens: - - "9999996" - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_309a25382e85b3986be08f54747ad1ff - status: - code: 200 - message: OK - - request: - body: '{"input":"This is a test","model":"text-embedding-ada-002","encoding_format":"base64"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "86" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/embeddings - response: - body: - string: !!binary | - H4sIAAAAAAAAA1R6ybKyTLfm/L+KN94p9YeISC6/GdJJm4nSqBUVFWCDoKg0mUCeOPd+gr0rTlVN - HGAamM16upX/8a8/f/5+8up26f/+8+fvq+z6v/9jfnbN+uzvP3/+57/+/Pnz5z9+Pv+/kbc6v12v - 5bv4Gf7zZfm+3sa///wR//vJ/x30z5+/jnoyWEDavO3CPcrWkSzJVCruUz7411MI8fvBGVGTF+rF - RNYUjFSf5YdrUU1p8hEBd8+EGVW35X15DgGScnnChJpjNdwy9FwL0tMlRgyC17vL1kCbfjfh6T6S - dgyr7gnluHgza5WwdggP9ROJIIYsG85vPmzt0oVPI3HiH75VPh3T3lBWpZ2wU1KTqvUPogA0ObVM - bXCVD49giEFUVZH5r8LUR4nIBayme4Olp9miafs6S6jc11t6kdOyoiNfH6CJPwUzzG8fje9ddgHK - Zc600Np6oq4bk2JUu4Jyx/hELBZ9H50TryPmqXEi7hxljCL5Y7Kzdd9WfP1+ChA1VYWH+7bTB9Xe - G2iZZ19iKB+ZM+d+M5CziEYM8rHm460dnyC99Qrrd8Aee0pchJPTxlQK3l0+0KtjoP0Q74ldiK3X - v+KkA/qqAubtwm8+PV/uB17Lyw2nfFByuovyWAl0vSf2Ijl6U9VZGSgrTin09lufjLt4geNluSI7 - yy7yKVDOKqAnF/Bj/dlWy912b4F+bM8siMIBdeYmPaCD+k4wvwtp222dJIX3drtjQR+ZLV0+Th8U - LsmduB3HERV0zYLa7EvinjcD6s/C1t1kwvAi1r7dRNdtjkul+GaUGUJAvYHsbQzn6jQQB9f3aHxG - 9gl6+XtnJnuuqskO3AG1Qk2Z+xm2rWhK2xuU4+ZNl44MfDgq1gmZoTkQ73Vk+rRxYALyZTviD8xA - Q/tVjc3rdQrY3o6KdjAl54baIsqIudd2+RDcdxS2xCiY3zttNDV+U8BaaYA5aEWi4SNdMlCHNcW8 - 9Sf9La6zE2xBvdNiXH0rfsWFuHnmPMLtuF23D3dZWSDV0505X+PGWbj4GmitjDcqCWWN+GuAGDT3 - ZJLojr585Bc+wCM9CZTW0TKnrY9qqE1WEvWu7tBSMboOUCkRZlzsvd4fvUWDzgas6aZ2cm+Y6xV5 - 9uCwW/Yuo3k9fRCcxiO7hSNGjb99KWg+/8Q0RQ+N5blRFWRpE10Kp66aRjE/gbbeqbjb5TveLU3d - WlRqCPjWA6qm5ae/oIeILOI/FK9afV/3CzhaVOLV/vyp+n75BIg88cN2zqBFXBvCFILHOWJ+Xwtt - n7jnAxSrTmfe4f71xmd0vqDzOKXEw3Ib0ceYdWCb7oAXxpHm3d7jCpyr9I7LjdTxIbj1T+SEzxXx - 0y7UqV6/XejazCPm5dDmT+g4wOKVv4nr9j4aRB9LaJJyhS6olfBhPdkhnD7OhalNp/B+tQ9EyK9n - QgJ4Z+1EVXgqx0y2iSd7hsfLjX9Cj/RK8BRWYt7vry8LjW5zo2MVYN5g0b6hrj15jKj8Go3Jnhqw - 3ysZHio9rkbcWBg8t5eJmZii18kqkdA8P6blVONjsr9qwDWIyBVeB72TZUVA1Sby8BQ7Pe8OxuDC - Mo9PTGdYqfiMNyDI1RpvSv3R9su0xehq1iVxZUNqn/P81hc3wWy76VM0vLToAosXFpmaXyTE705c - IJqEDpbP3pMPW+caA4/UJwlE9G7HK7/fUFZc90TbxmLbz/WJ1KK0yc7Fa84vyfIDlEslnaQwymn0 - ZaISLOibmG1RV3TP0hDee++L5YMq6dzby91P/bHgy+KKXo26hvx6L5g+42c9icsCjuvLgx2qU5+z - VR+dwISPTYyqr73J315EMIyLhMd4C/okvpUQBvDfeDG2nt4SK5KUeT+YNvMHPz2yAvnmcKZrlBc5 - w+a6g2e+elLoXVKNiWv7iHzXCvHSx1jRcFmLIC3DN/N3WdWOZwFiCO1kZLY1phHnaydGfuos2DZ/ - dWhUz2sMzmI/0uOMl+36nSuwk7iL08vFbEdYhTG4ueQyvLRqr9fjjYDSbUSYlrO3NyBeN8AKpNNX - EXNOO0tV4KNsEvxdXJ7ttPwIJVokbsVcvUiqQRK+GVxfaMWsk9R5/JI8n0iqpYHNeK5PRCyfQLlY - 0mkjJ/lkFGaJbqG8Y8Z7OKBJSSmg28NS8MuUxIiWzdoA/xk+fvmG/+BXXWZXgqMbePSUCjZiZbug - yk3dVM36sipBcQxOTGVw24FetxbaoFhi7k29Vp0lHQplVzcfYgjuNloxP/Hh66SIbNefRzt11h7g - gIcdi+f97OiTCqhYfycSRGHIOT3EHRwvLPnhZ2+ZuOcQFq/IJNv198WnAVkWWHk4EXdnEW88mcxA - efuJmMkdn/MrHmU4rrOQ6RNnaJj2Tx/WARqIeQk1vjyk3xhmfmXGqcrRGFbLD0SevMbJdtJzZrUL - f907okYwyTx90u/bEGFsBCSOr1o03VdbGy6rfUAwUFtfvQZIkW2SLdHpUOkjCL0NUwI6M5S32PaP - e3jZzPxDF2ra6DQucw3tSzPAg1F+qkGZzjMe5hHbHgXmfbomOQH5IoV4u31QTZxGMtDkBngBSoO4 - uK4usGx7gW7GY9rWIVUBTtJlZJqxeuRcKb4YlPfl/MOf+ogbjBVVU1WSMrrn42p/k2FXfz5kZ3m9 - Pn7t9wCqvr7hoekUNPjXRwzskCG8GdMpancvv4R7d2PMRuxaja+4npAbvCyMUrNs+6lKMvRRkIHn - 89GO/OqLKPIWLtlOdxT10fFSoJnPmJPQRz58JamAo3/bY7jKlT7V99fht54X0ctpp2/ku+gHn9wv - XnvNMdUAPc+CRdRR7vn4toYUpdt8pNIeN/oYPu+Dsrl0PnMTZEfjK752kFEaE/uxv+W80B4SRN50 - ZNae0IjZNw6bN3vfibZZ7XV+fkCD/NgPmV49qnyKy0jbyMyImJeaWjUsDUVFRFYvWJENqaKOdTKg - fNCKsnWSVEMR7wFAwAaVr0GQj+4yU9EAiUPXZ1Hhn2oni+jNbhv80vYLnRXaaYD1xRXpoD6M6HN5 - SxISpNql9eXyaif9fkhhwUuHqEZpV6w7CTECPVjSIT83+lDtZAm2Pc/xMMoB/5kfeuw2O6LRd+/1 - VWa40Ao3n1mXi1kNifzRUGhdIuZllsX5zQ4PyM1Fl2GStbMeailqtwVmlrl5oPEyrg3gC0klalk/ - 8mn72ku/etletX67Cvwo3XBN0ZjzyOWWHd+VBeFTcZltcQGNauYe4Cu5J7aVjKGd9VcGiXFYULbc - P9vx1uUULm/Nmf3Agw/cXZdrXQqmXz3VXDflBFuiEmKugitnd6evwVu9akqj28Xjm/jsohm/SdBH - r2oQ7nIHxWqIiS6dzJkPphCaeBmx4FaInKZXTOEHX2y0r72xyhIftOySsh2TfW8MhqBTDjflSxfR - 69tOiBxcgG1oEbcTD9UAXaMg3NUJlU5yXE3m2Zng6LcGBfloIeZHdwu2xB6JpShPNDy36xjd4aES - sk7XvFNtVd3M9cXIsbnN/kKd1lZ71JnRxhVn00JUYSeNLpn5mY/310NDxMMLpldVi7j13McIxdmJ - GSs15aMePxWYpLPC7OdZzSX97hx+/AhV3EbVV4N5vqBNb05sl+SjN+2Z6cPLrge6mfXM7+8/fpix - e5lpiHM19X/qnanru1dx9IhPYK3pl8Itnjwece7CzD90vH/W7SSVsQJ8/GKqDCe9Wg6fadgwzbfJ - eXHrveaHLyJvOBLjTd2cf56aC8fWQkyTsIuGRXGQ4JHeCf50ussZWZxUOPRpQSdj7XAO2TQgcv5I - xPugwhs7cT2gk9O/mHZPipnPt7cfvMPy55a0E1kaHZyrx4EZhZPknPlXH4J9ohFte+j0zpS2F/BN - ahNc4sIbKnurwLQbQxKUFo466EoF6nhnY5RWmTcJ2lqDtnBl4lxPHhqEd1DAHSqVQnZwKp5QowNd - PL2IZm8URNeXRYHs5Cz+npeu2g0S4o+Ty864XuT9IVUyaIt9RnZPvOVLk+xKKFylJobyjttpUDYa - XF/rFZX2gclpGxifzSLdDEQP2VHnV/wRodXvG1orm7Gd1gkaYMZbhmGMEd12iw4UG/bkpjqVN77x - DaPwZW1weRchGhYFgDLrR/bzf98z/v3ob8zq+8njohLU61SwgZ0OWyVqQjrvVUFD5gz4m09WpB3Q - eyNVTG3atBrdpSps2rtgEFOipT56VM6gQ9/Zf+x89F0egxROR/jSaSP5fLx12mfzo4/l57mIKEar - E9gjBLgjBvUG6EoZLF9EzPtmiA87Jivgm53NTIWvcmplWEUn6TbiRX1pc/YaqgP402fHzGpV5OMh - nU7gBllE3J3p8jFbDTUoS+FBR8k6ewM+KooS6Nv+F5+o+J4OsOAUGPE273bqVSdTggXKqKQoTz7t - Kdhoey2PTJOCuhr51RChP8Uuu2R7M+IHJZ6UprI/eJVkPqLrRH3CMr8peHnqRjR9DiFsOjw+mJMG - G49fiSv8+qeP1r+iUQq3NTquy4kKS6vWP+fuO9f/YoOFW3esxhYtS1CH0SeOJlf8G3wdUOrYtOlL - GZp2+LKwQTNe4RVbvVHTWaIBwlkS5v3N0CAJYQx2VL/JD9+yLF+68LP/lnYeUMO2KYVHXRU0MLRl - 2527adZTh4l5aaV4TKZWDYbx2JFd8fnkU78L7BXs246pxnP0eiOY8EbLWoeZp17yumnf+SiSp/fs - D+J2HMsGg/6Sr3jFb2YrTeKmBB55FttxJW4nIqIGucHbwouj/86n+t6HMJ83zN8vMeJCQm8oYE3K - 3CHz9cndvTIItLVHSE5Evf3hg+V6oTEMw1DxLO8M9MyXT2IJQsKnkNoCwsi6MnJb9i0t28hHDT/m - uM+uH51V0p4i/shcps95xTT7S/QMzj0dxuVWn/kBw5hRhuVVY+fjZ9cWaAA7ZfG2Ltp+5aw1kDeF - y3afw4FPG6eicDqKO7aNUBmNY3m2Ua0LNfNvqdJ2opd/YMZH/H5256gXxklAwf4wUvQ98ajXok8D - U6rFzBRE1PLRqidlXO9tFohKlQ/8cM/QjLcEz+eDNdd1DeRcxlTRjbodXVjI6Jr0BsFL84HojIdK - cih0tnuGTTSV0w2gu3o75rmrt9cjITZgzlfI1mCsan781sy/5Dnnb62QXDOUHOqYkEZ78uGBt6fN - PRBNLFnbCdFZv6M21FLiaGtbXwV+d0JpLzj4JYioar/XooTr02iYv7t0Xr/T/AMwY1cza+9v2yWs - HieEuK4xT/ae+qBpagn09WXECj5hO4Hj1LDB1RkLc17B6zG9gHo4JkxVH0bOX4Nj/+Af3sCzn/1M - LYBxAIG418cDDZ+lEoIYeinlP/hZaJOi7PU2xctLqKEpUJCNBOfj/eRtaOYrF+J3xbHkvCr+q0dT - YX/D6HUkep/J2w/wiByJmp8bb+iaRQGLV5KyQES7ajqmFxUdW8dnznmaIv4a2gPox7dNHPyU0I9/ - VAT5aDE9X2/zsV9KKtyVwcDNIbJyWt8vGBRbUckOVQrqW7Qp4Zo0fNbz22jlHVoZcNetSP6Thwi6 - a/2sz2/+ypcKo2BHF5OdFxejXR0/gY+0jxLQzZhgj3+fyxSmXX1l3s09olF2NQuYdjj/5ln8XAYd - VL11mvNWVg30WQvKPhrlGd86NDjf9QledrslrtuoHvO9woVIpimGLNx63x/9/5XsExbkvkINp52A - 5vVnmo0O0VzfB0V51wgPd/U9+9u9oEw7HjJ3tXjordleLQRMvJFtXhnRLz6YdwXwIqp71MnyJEDe - Li2mGq8kpxglIaQ9OCysv1TvGjYNSrGSXkSXsqBlQmKkaJEuBhxuLCcfHji7oZ/89jyQvurPQhvC - dbqFNL9SG03LR9igr+OfqeCNTzSSSrtsdnW3Zni5a/JxeTRnPffe/+JJkzmTjI7rU0g05YD4eEgf - qdLEXGN2t9XypbW1VXDC/kx/ztvy6K0atIoGRi7ZwWm5MZEJ7oGS0uG+9b01/uYqZMWL/+qHXj1/ - XCSd3h19o0rhQ2y9a6BVp+LV1ThGzaBsVGWAo8PU5bXyJrXdxwiGXYXFqrf0vl8KGvqeXwvmgqnw - 3/x2APwm/i7fzf4uDDe3RTEwV9awPq72gYS+75VOuaDu9OU2W97QxfU75hSL7+zHrj6yJ4MRB8m8 - 6rrGiMEMdwPeyKUZiXNeCvh25SyQy1c0ie+TDSbFe4x2hz2fx6fQ8CRnmv9o+Xj0Fh+w1t2XyjiD - aszljMJP/m0mZuzN+YAAxYrqzHBwWY3JPlFh2jWUqfQQRxNby8OP/6HLU9tXrzdOMZhAz3TtFiYa - t7lV/uYp0scBNG6z7oSKc3zF8qrtqg516gQhPx2Y+/LDuf/QFMpVDHxi8SHL2acqtI1yTlYEvyTN - G8PncYCZ//D2/llXk1GkT/TMx4hgb3L07pG8Q6Qs5ZAFfeygHlZhitrClud+gx6trqS3wDgIApvz - zJxLXYHBF18S2TbLEM340kBsIwcLY+FXfHdTJ0B8F1F+Oq69Sb87cz4ZCYSoaeN1B98QkHGQLgSP - 5VIfkXmUUbycVkyrN2Xb/uRrXwefiRlcgtkvyzHox++Z2Fpv5pOSGiLM/Qm6NJehLvWL4QCfS9r+ - 8Ls+ncg3/tWvs79qpfSybDa3xXtLDJZdI6l6fgq0Kg2D3GAU+SSVFxna/Vpk5huWFfPO7wZ2dX1k - 7uON8vEsOC7Ex/Me17FYVb/673v8hMzFh9IbqzM3Nof+QFggCnE0nHvPRgv+aVnU+gdvNHCc/vqV - LD2uoqFGRQfr7vie+c9qh/5pSPBR1sac5z/RnEc2sC8OKiEe6PkSFuSArmJ0JbqzS7wpc74igkE/ - EPcMfjs5VmhtlDNJ8N04HdpBmfYxFN/LggSpPKH+YwcNzPqABYYhePS6sRuYjssH0f3OjYbxxAQ0 - 8z+5wjPg40bWy5/6Z9qcXw7mJg2BWoL4i7dDRkmGND8RiYuHdTtcilCAQJMUogfOpuok4ZSCCPKD - 2Gf/q/dzPoN++PySsQvn2QVjuHcXxiLH7Krx1m1EZe4PMTtABeLMQxZ63+Oc7ZvlwFkJZx/caz/n - Pbaad192+sBP/aeXy6v6vuJ6gBk/iP2UeMu1lYDhvREr4lyzOBoTV/UVNAkjweW+41R8h+7GWjen - OS/P0LI8nwDiV5MQ5/Nu29Fd2oBmP0XrZ3n3uqWhaFA+ViYV1u5K72rQJAjT5xJLcz+KHd/gIssf - mhnPdK8Xk0HdLAPnRddnnlbToFTCWrLTD9EM2Zzz2MxHcz4480OA3nfHuwAfW8x2lvOsJm8n3H7w - gKnr2y76doBrMKm/Z4G63UdTcslLuD3IBYMuNrM/+Io//SqybeRr1SPhYimqZux/zxt7SkiCq3lR - 2fVWXqM5f5aAa7JG9EkU9em6KQe4acWDaMb6+5tPbfxp+tLVVY/0ITLbFBkPrNGlRDVvCpTGQMEe - F8zrFnt91Z0uPtrvhZYYSh3mfRx+RUhG60Lsz3Uf1SMfD2DeNwEhpNp6SwN7B4XyhUHH6Xac37/v - wDen869f4KdH9QR9V67wJxCClleS+tkk5epEtv4p4VPZau7mnDgdIdHrW/F3ayo/+RAe7aiomLiu - bjD3R/DywoR2iMwsRFZuhyT49r7O+/1Ug2dPDiOlnM15m9+gS3YfCL41bNZzzecnL8SrJN977Sa2 - LQjY02Ra+JSrrv3a1m++HwXOpqWuNfnwPdIH+eGPjuzLGKw20Ykr3q7e1PhlAT/9C0/vTtGIBE+D - 7/l+JZqNppxt8oWqRE06EO8DRj6fF4DvsXvgzUF88EmvmQs72yDkR59Pn7Mk/uKv/bM+oXpJobsI - MQvG893rFoUzway/MRDt1Y7RUfpsOtQSnB3iph2uD8MGe3JUYlzsUR9emnaCn36qfkdfxKTug8Ew - 2i8JDC2phnixbcC6mgum35GDlg4kA8hqR5n7cu2Zr58CEO/4oCPN3ei3P/KVrB1Ro9HWpwV8MmSM - 2ZIORtXx4dwpFqxKN2HWnAcMx2n9hJ989yfPHuxh6QKPtCfxxBqjeT6Dss6FLQViHqLppz8TPoV8 - 9hOralxMvvaDz8yytgc+ftVBAjlED7az3hf9Jw9Gf39uBfznv/78+V8/Nwzqz/X2mi8G9Lex//d/ - XxX4d3bN/i2K0r+Z9HsTgXZZcfv7z/+5hPD3237qb/+/+8/z9u7+/vNH/r1t8Lf/9Nnr/3n8r/ld - //mv/wIAAP//AwBxbwgZ4SAAAA== - headers: - CF-RAY: - - 9472cada7afe7d11-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:20 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=vD2YsEJBR2ebZoWd2D9ZJCHxbtSQae6h0ejt5wU.PO4-1748488160-1.0.1.1-gr1R2weSB3qADCmsvlAWq3J9Dwjp5fGtdJkNOLNThoKEWu7Z1KReV0ImxAfTlUXuijFyn8OXqdTkezkTL7xlKx_YC3JCApMDKGM98BVOr_I; - path=/; expires=Thu, 29-May-25 03:39:20 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=ZTMtHj1A.fKEhi2PqrMnVjfeurCsxqnAI7RZskT8dbQ-1748488160511-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-allow-origin: - - "*" - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-model: - - text-embedding-ada-002-v2 - openai-organization: - - braintrust-data - openai-processing-ms: - - "51" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - envoy-router-6b84dbcf9f-psv4p - x-envoy-upstream-service-time: - - "53" - x-ratelimit-limit-requests: - - "10000" - x-ratelimit-limit-tokens: - - "10000000" - x-ratelimit-remaining-requests: - - "9999" - x-ratelimit-remaining-tokens: - - "9999996" - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_eff3daa1a051dfb962face8677567afd - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_embeddings_async.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_embeddings_async.yaml deleted file mode 100644 index e3405d8c9..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_embeddings_async.yaml +++ /dev/null @@ -1,423 +0,0 @@ -interactions: - - request: - body: '{"input":"This is a test","model":"text-embedding-ada-002","encoding_format":"base64"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "86" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/embeddings - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//VHrJsrJMt+b8v4o33in1h4hILr8Z0kmbidKoFRUVYIOgqDSZQJ44936C - vStOVU0cYBqYzXq6lf/xrz9//n7y6nbp//7z5++r7Pq//2N+ds367O8/f/7nv/78+fPnP34+/7+R - tzq/Xa/lu/gZ/vNl+b7exr///BH/+8n/HfTPn7+OejJYQNq87cI9ytaRLMlUKu5TPvjXUwjx+8EZ - UZMX6sVE1hSMVJ/lh2tRTWnyEQF3z4QZVbflfXkOAZJyecKEmmM13DL0XAvS0yVGDILXu8vWQJt+ - N+HpPpJ2DKvuCeW4eDNrlbB2CA/1E4kghiwbzm8+bO3ShU8jceIfvlU+HdPeUFalnbBTUpOq9Q+i - ADQ5tUxtcJUPj2CIQVRVkfmvwtRHicgFrKZ7g6Wn2aJp+zpLqNzXW3qR07KiI18foIk/BTPMbx+N - 7112AcplzrTQ2nqirhuTYlS7gnLH+EQsFn0fnROvI+apcSLuHGWMIvljsrN131Z8/X4KEDVVhYf7 - ttMH1d4baJlnX2IoH5kz534zkLOIRgzysebjrR2fIL31Cut3wB57SlyEk9PGVAreXT7Qq2Og/RDv - iV2Irde/4qQD+qoC5u3Cbz49X+4HXsvLDad8UHK6i/JYCXS9J/YiOXpT1VkZKCtOKfT2W5+Mu3iB - 42W5IjvLLvIpUM4qoCcX8GP92VbL3XZvgX5szyyIwgF15iY9oIP6TjC/C2nbbZ0khfd2u2NBH5kt - XT5OHxQuyZ24HccRFXTNgtrsS+KeNwPqz8LW3WTC8CLWvt1E122OS6X4ZpQZQkC9gextDOfqNBAH - 1/dofEb2CXr5e2cme66qyQ7cAbVCTZn7GbataErbG5Tj5k2Xjgx8OCrWCZmhORDvdWT6tHFgAvJl - O+IPzEBD+1WNzet1Ctjejop2MCXnhtoiyoi513b5ENx3FLbEKJjfO200NX5TwFppgDloRaLhI10y - UIc1xbz1J/0trrMTbEG902JcfSt+xYW4eeY8wu24XbcPd1lZINXTnTlf48ZZuPgaaK2MNyoJZY34 - a4AYNPdkkuiOvnzkFz7AIz0JlNbRMqetj2qoTVYS9a7u0FIxug5QKRFmXOy93h+9RYPOBqzppnZy - b5jrFXn24LBb9i6jeT19EJzGI7uFI0aNv30paD7/xDRFD43luVEVZGkTXQqnrppGMT+Btt6puNvl - O94tTd1aVGoI+NYDqqblp7+gh4gs4j8Ur1p9X/cLOFpU4tX+/Kn6fvkEiDzxw3bOoEVcG8IUgsc5 - Yn5fC22fuOcDFKtOZ97h/vXGZ3S+oPM4pcTDchvRx5h1YJvugBfGkebd3uMKnKv0jsuN1PEhuPVP - 5ITPFfHTLtSpXr9d6NrMI+bl0OZP6DjA4pW/iev2PhpEH0toknKFLqiV8GE92SGcPs6FqU2n8H61 - D0TIr2dCAnhn7URVeCrHTLaJJ3uGx8uNf0KP9ErwFFZi3u+vLwuNbnOjYxVg3mDRvqGuPXmMqPwa - jcmeGrDfKxkeKj2uRtxYGDy3l4mZmKLXySqR0Dw/puVU42Oyv2rANYjIFV4HvZNlRUDVJvLwFDs9 - 7w7G4MIyj09MZ1ip+Iw3IMjVGm9K/dH2y7TF6GrWJXFlQ2qf8/zWFzfBbLvpUzS8tOgCixcWmZpf - JMTvTlwgmoQOls/ekw9b5xoDj9QnCUT0bscrv99QVlz3RNvGYtvP9YnUorTJzsVrzi/J8gOUSyWd - pDDKafRlohIs6JuYbVFXdM/SEN5774vlgyrp3NvL3U/9seDL4opejbqG/HovmD7jZz2JywKO68uD - HapTn7NVH53AhI9NjKqvvcnfXkQwjIuEx3gL+iS+lRAG8N94Mbae3hIrkpR5P5g28wc/PbIC+eZw - pmuUFznD5rqDZ756UuhdUo2Ja/uIfNcK8dLHWNFwWYsgLcM383dZ1Y5nAWII7WRktjWmEedrJ0Z+ - 6izYNn91aFTPawzOYj/S44yX7fqdK7CTuIvTy8VsR1iFMbi55DK8tGqv1+ONgNJtRJiWs7c3IF43 - wAqk01cRc047S1Xgo2wS/F1cnu20/AglWiRuxVy9SKpBEr4ZXF9oxayT1Hn8kjyfSKqlgc14rk9E - LJ9AuVjSaSMn+WQUZoluobxjxns4oElJKaDbw1Lwy5TEiJbN2gD/GT5++Yb/4FddZleCoxt49JQK - NmJlu6DKTd1UzfqyKkFxDE5MZXDbgV63FtqgWGLuTb1WnSUdCmVXNx9iCO42WjE/8eHrpIhs159H - O3XWHuCAhx2L5/3s6JMKqFh/JxJEYcg5PcQdHC8s+eFnb5m45xAWr8gk2/X3xacBWRZYeTgRd2cR - bzyZzEB5+4mYyR2f8yseZTius5DpE2domPZPH9YBGoh5CTW+PKTfGGZ+ZcapytEYVssPRJ68xsl2 - 0nNmtQt/3TuiRjDJPH3S79sQYWwEJI6vWjTdV1sbLqt9QDBQW1+9BkiRbZIt0elQ6SMIvQ1TAjoz - lLfY9o97eNnM/EMXatroNC5zDe1LM8CDUX6qQZnOMx7mEdseBeZ9uiY5AfkihXi7fVBNnEYy0OQG - eAFKg7i4ri6wbHuBbsZj2tYhVQFO0mVkmrF65FwpvhiU9+X8w5/6iBuMFVVTVZIyuufjan+TYVd/ - PmRneb0+fu33AKq+vuGh6RQ0+NdHDOyQIbwZ0ylqdy+/hHt3Y8xG7FqNr7iekBu8LIxSs2z7qUoy - 9FGQgefz0Y786oso8hYu2U53FPXR8VKgmc+Yk9BHPnwlqYCjf9tjuMqVPtX31+G3nhfRy2mnb+S7 - 6Aef3C9ee80x1QA9z4JF1FHu+fi2hhSl23yk0h43+hg+74OyuXQ+cxNkR+MrvnaQURoT+7G/5bzQ - HhJE3nRk1p7QiNk3Dps3e9+JtlntdX5+QIP82A+ZXj2qfIrLSNvIzIiYl5paNSwNRUVEVi9YkQ2p - oo51MqB80IqydZJUQxHvAUDABpWvQZCP7jJT0QCJQ9dnUeGfaieL6M1uG/zS9gudFdppgPXFFemg - Pozoc3lLEhKk2qX15fJqJ/1+SGHBS4eoRmlXrDsJMQI9WNIhPzf6UO1kCbY9z/EwygH/mR967DY7 - otF37/VVZrjQCjefWZeLWQ2J/NFQaF0i5mWWxfnNDg/IzUWXYZK1sx5qKWq3BWaWuXmg8TKuDeAL - SSVqWT/yafvaS7962V61frsK/CjdcE3RmPPI5ZYd35UF4VNxmW1xAY1q5h7gK7kntpWMoZ31VwaJ - cVhQttw/2/HW5RQub82Z/cCDD9xdl2tdCqZfPdVcN+UEW6ISYq6CK2d3p6/BW71qSqPbxeOb+Oyi - Gb9J0EevahDucgfFaoiJLp3MmQ+mEJp4GbHgVoicpldM4QdfbLSvvbHKEh+07JKyHZN9bwyGoFMO - N+VLF9Hr206IHFyAbWgRtxMP1QBdoyDc1QmVTnJcTebZmeDotwYF+Wgh5kd3C7bEHomlKE80PLfr - GN3hoRKyTte8U21V3cz1xcixuc3+Qp3WVnvUmdHGFWfTQlRhJ40umfmZj/fXQ0PEwwumV1WLuPXc - xwjF2YkZKzXlox4/FZiks8Ls51nNJf3uHH78CFXcRtVXg3m+oE1vTmyX5KM37Znpw8uuB7qZ9czv - 7z9+mLF7mWmIczX1f+qdqeu7V3H0iE9gremXwi2ePB5x7sLMP3S8f9btJJWxAnz8YqoMJ71aDp9p - 2DDNt8l5ceu95ocvIm84EuNN3Zx/npoLx9ZCTJOwi4ZFcZDgkd4J/nS6yxlZnFQ49GlBJ2PtcA7Z - NCBy/kjE+6DCGztxPaCT07+Ydk+Kmc+3tx+8w/LnlrQTWRodnKvHgRmFk+Sc+Vcfgn2iEW176PTO - lLYX8E1qE1ziwhsqe6vAtBtDEpQWjjroSgXqeGdjlFaZNwnaWoO2cGXiXE8eGoR3UMAdKpVCdnAq - nlCjA108vYhmbxRE15dFgezkLP6el67aDRLij5PLzrhe5P0hVTJoi31Gdk+85UuT7EooXKUmhvKO - 22lQNhpcX+sVlfaByWkbGJ/NIt0MRA/ZUedX/BGh1e8bWiubsZ3WCRpgxluGYYwR3XaLDhQb9uSm - OpU3vvENo/BlbXB5FyEaFgWAMutH9vN/3zP+/ehvzOr7yeOiEtTrVLCBnQ5bJWpCOu9VQUPmDPib - T1akHdB7I1VMbdq0Gt2lKmzau2AQU6KlPnpUzqBD39l/7Hz0XR6DFE5H+NJpI/l8vHXaZ/Ojj+Xn - uYgoRqsT2CMEuCMG9QboShksX0TM+2aIDzsmK+Cbnc1Mha9yamVYRSfpNuJFfWlz9hqqA/jTZ8fM - alXk4yGdTuAGWUTcnenyMVsNNShL4UFHyTp7Az4qihLo2/4Xn6j4ng6w4BQY8TbvdupVJ1OCBcqo - pChPPu0p2Gh7LY9Mk4K6GvnVEKE/xS67ZHsz4gclnpSmsj94lWQ+outEfcIyvyl4eepGNH0OIWw6 - PD6YkwYbj1+JK/z6p4/Wv6JRCrc1Oq7LiQpLq9Y/5+471/9ig4Vbd6zGFi1LUIfRJ44mV/wbfB1Q - 6ti06UsZmnb4srBBM17hFVu9UdNZogHCWRLm/c3QIAlhDHZUv8kP37IsX7rws/+Wdh5Qw7YphUdd - FTQwtGXbnbtp1lOHiXlppXhMplYNhvHYkV3x+eRTvwvsFezbjqnGc/R6I5jwRstah5mnXvK6ad/5 - KJKn9+wP4nYcywaD/pKveMVvZitN4qYEHnkW23Elbicioga5wdvCi6P/zqf63ocwnzfM3y8x4kJC - byhgTcrcIfP1yd29Mgi0tUdITkS9/eGD5XqhMQzDUPEs7wz0zJdPYglCwqeQ2gLCyLoyclv2LS3b - yEcNP+a4z64fnVXSniL+yFymz3nFNPtL9AzOPR3G5Vaf+QHDmFGG5VVj5+Nn1xZoADtl8bYu2n7l - rDWQN4XLdp/DgU8bp6JwOoo7to1QGY1jebZRrQs182+p0nail39gxkf8fnbnqBfGSUDB/jBS9D3x - qNeiTwNTqsXMFETU8tGqJ2Vc720WiEqVD/xwz9CMtwTP54M113UN5FzGVNGNuh1dWMjomvQGwUvz - geiMh0pyKHS2e4ZNNJXTDaC7ejvmuau31yMhNmDOV8jWYKxqfvzWzL/kOedvrZBcM5Qc6piQRnvy - 4YG3p809EE0sWdsJ0Vm/ozbUUuJoa1tfBX53QmkvOPgliKhqv9eihOvTaJi/u3Rev9P8AzBjVzNr - 72/bJaweJ4S4rjFP9p76oGlqCfT1ZcQKPmE7gePUsMHVGQtzXsHrMb2AejgmTFUfRs5fg2P/4B/e - wLOf/UwtgHEAgbjXxwMNn6USghh6KeU/+Flok6Ls9TbFy0uooSlQkI0E5+P95G1o5isX4nfFseS8 - Kv6rR1Nhf8PodSR6n8nbD/CIHImanxtv6JpFAYtXkrJARLtqOqYXFR1bx2fOeZoi/hraA+jHt00c - /JTQj39UBPloMT1fb/OxX0oq3JXBwM0hsnJa3y8YFFtRyQ5VCupbtCnhmjR81vPbaOUdWhlw161I - /pOHCLpr/azPb/7KlwqjYEcXk50XF6NdHT+Bj7SPEtDNmGCPf5/LFKZdfWXezT2iUXY1C5h2OP/m - WfxcBh1UvXWa81ZWDfRZC8o+GuUZ3zo0ON/1CV52uyWu26ge873ChUimKYYs3HrfH/3/lewTFuS+ - Qg2nnYDm9WeajQ7RXN8HRXnXCA939T37272gTDseMne1eOit2V4tBEy8kW1eGdEvPph3BfAiqnvU - yfIkQN4uLaYarySnGCUhpD04LKy/VO8aNg1KsZJeRJeyoGVCYqRokS4GHG4sJx8eOLuhn/z2PJC+ - 6s9CG8J1uoU0v1IbTctH2KCv45+p4I1PNJJKu2x2dbdmeLlr8nF5NGc9997/4kmTOZOMjutTSDTl - gPh4SB+p0sRcY3a31fKltbVVcML+TH/O2/LorRq0igZGLtnBabkxkQnugZLS4b71vTX+5ipkxYv/ - 6odePX9cJJ3eHX2jSuFDbL1roFWn4tXVOEbNoGxUZYCjw9TltfImtd3HCIZdhcWqt/S+Xwoa+p5f - C+aCqfDf/HYA/Cb+Lt/N/i4MN7dFMTBX1rA+rvaBhL7vlU65oO705TZb3tDF9TvmFIvv7MeuPrIn - gxEHybzqusaIwQx3A97IpRmJc14K+HblLJDLVzSJ75MNJsV7jHaHPZ/Hp9DwJGea/2j5ePQWH7DW - 3ZfKOINqzOWMwk/+bSZm7M35gADFiurMcHBZjck+UWHaNZSp9BBHE1vLw4//octT21evN04xmEDP - dO0WJhq3uVX+5inSxwE0brPuhIpzfMXyqu2qDnXqBCE/HZj78sO5/9AUylUMfGLxIcvZpyq0jXJO - VgS/JM0bw+dxgJn/8Pb+WVeTUaRP9MzHiGBvcvTukbxDpCzlkAV97KAeVmGK2sKW536DHq2upLfA - OAgCm/PMnEtdgcEXXxLZNssQzfjSQGwjBwtj4Vd8d1MnQHwXUX46rr1JvztzPhkJhKhp43UH3xCQ - cZAuBI/lUh+ReZRRvJxWTKs3Zdv+5GtfB5+JGVyC2S/LMejH75nYWm/mk5IaIsz9Cbo0l6Eu9Yvh - AJ9L2v7wuz6dyDf+1a+zv2ql9LJsNrfFe0sMll0jqXp+CrQqDYPcYBT5JJUXGdr9WmTmG5YV887v - BnZ1fWTu443y8Sw4LsTH8x7XsVhVv/rve/yEzMWH0hurMzc2h/5AWCAKcTSce89GC/5pWdT6B280 - cJz++pUsPa6ioUZFB+vu+J75z2qH/mlI8FHWxpznP9GcRzawLw4qIR7o+RIW5ICuYnQlurNLvClz - viKCQT8Q9wx+OzlWaG2UM0nw3Tgd2kGZ9jEU38uCBKk8of5jBw3M+oAFhiF49LqxG5iOywfR/c6N - hvHEBDTzP7nCM+DjRtbLn/pn2pxfDuYmDYFagviLt0NGSYY0PxGJi4d1O1yKUIBAkxSiB86m6iTh - lIII8oPYZ/+r93M+g374/JKxC+fZBWO4dxfGIsfsqvHWbURl7g8xO0AF4sxDFnrf45ztm+XAWQln - H9xrP+c9tpp3X3b6wE/9p5fLq/q+4nqAGT+I/ZR4y7WVgOG9ESviXLM4GhNX9RU0CSPB5b7jVHyH - 7sZaN6c5L8/QsjyfAOJXkxDn827b0V3agGY/Retnefe6paFoUD5WJhXW7krvatAkCNPnEktzP4od - 3+Aiyx+aGc90rxeTQd0sA+dF12eeVtOgVMJastMP0QzZnPPYzEdzPjjzQ4Ded8e7AB9bzHaW86wm - byfcfvCAqevbLvp2gGswqb9ngbrdR1NyyUu4PcgFgy42sz/4ij/9KrJt5GvVI+FiKapm7H/PG3tK - SIKreVHZ9VZeozl/loBrskb0SRT16bopB7hpxYNoxvr7m09t/Gn60tVVj/QhMtsUGQ+s0aVENW8K - lMZAwR4XzOsWe33VnS4+2u+FlhhKHeZ9HH5FSEbrQuzPdR/VIx8PYN43ASGk2npLA3sHhfKFQcfp - dpzfv+/AN6fzr1/gp0f1BH1XrvAnEIKWV5L62STl6kS2/inhU9lq7uacOB0h0etb8XdrKj/5EB7t - qKiYuK5uMPdH8PLChHaIzCxEVm6HJPj2vs77/VSDZ08OI6WczXmb36BLdh8IvjVs1nPN5ycvxKsk - 33vtJrYtCNjTZFr4lKuu/drWb74fBc6mpa41+fA90gf54Y+O7MsYrDbRiSvert7U+GUBP/0LT+9O - 0YgET4Pv+X4lmo2mnG3yhapETToQ7wNGPp8XgO+xe+DNQXzwSa+ZCzvbIORHn0+fsyT+4q/9sz6h - ekmhuwgxC8bz3esWhTPBrL8xEO3VjtFR+mw61BKcHeKmHa4PwwZ7clRiXOxRH16adoKffqp+R1/E - pO6DwTDaLwkMLamGeLFtwLqaC6bfkYOWDiQDyGpHmfty7ZmvnwIQ7/igI83d6Lc/8pWsHVGj0dan - BXwyZIzZkg5G1fHh3CkWrEo3YdacBwzHaf2En3z3J88e7GHpAo+0J/HEGqN5PoOyzoUtBWIeoumn - PxM+hXz2E6tqXEy+9oPPzLK2Bz5+1UECOUQPtrPeF/0nD0Z/f24F/Oe//vz5Xz83DOrP9faaLwb0 - t7H/939fFfh3ds3+LYrSv5n0exOBdllx+/vP/7mE8Pfbfupv/7/7z/P27v7+80f+vW3wt//02ev/ - efyv+V3/+a//AgAA//8DAHFvCBnhIAAA - headers: - CF-RAY: - - 9472cb0bbc8ff9a9-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:28 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=84OzWlNXgYMGAt5FSILjYkBxQnLfxRM9T6sTPr7E2N0-1748488168-1.0.1.1-TJpRZ290t0Z5Uq9dhD15juux6xjityCLsOqmqy5zY6YxJMmg5ab2pYLgStF8FDqF4rP7Mjaj19wS_rQnFmSjwZzzddTv0dUkyS8jlLNceCY; - path=/; expires=Thu, 29-May-25 03:39:28 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=o9N.JCQtfm8gFHjK9_H7B8hekt9k6wXQI4CCCLcBspw-1748488168605-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-allow-origin: - - "*" - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-model: - - text-embedding-ada-002-v2 - openai-organization: - - braintrust-data - openai-processing-ms: - - "54" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - envoy-router-568fcbbc46-l4b5w - x-envoy-upstream-service-time: - - "56" - x-ratelimit-limit-requests: - - "10000" - x-ratelimit-limit-tokens: - - "10000000" - x-ratelimit-remaining-requests: - - "9999" - x-ratelimit-remaining-tokens: - - "9999996" - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_35cb99ebdd92a80fa815ff1c733b51fb - status: - code: 200 - message: OK - - request: - body: '{"input":"This is a test","model":"text-embedding-ada-002","encoding_format":"base64"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "86" - content-type: - - application/json - cookie: - - __cf_bm=84OzWlNXgYMGAt5FSILjYkBxQnLfxRM9T6sTPr7E2N0-1748488168-1.0.1.1-TJpRZ290t0Z5Uq9dhD15juux6xjityCLsOqmqy5zY6YxJMmg5ab2pYLgStF8FDqF4rP7Mjaj19wS_rQnFmSjwZzzddTv0dUkyS8jlLNceCY; - _cfuvid=o9N.JCQtfm8gFHjK9_H7B8hekt9k6wXQI4CCCLcBspw-1748488168605-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/embeddings - response: - body: - string: !!binary | - H4sIAAAAAAAAA1R6ybKyTLfm/L+KN94p9YeISC6/GdJJm4nSqBUVFWCDoKg0mUCeOPd+gr0rTlVN - HGAamM16upX/8a8/f/5+8up26f/+8+fvq+z6v/9jfnbN+uzvP3/+57/+/Pnz5z9+Pv+/kbc6v12v - 5bv4Gf7zZfm+3sa///wR//vJ/x30z5+/jnoyWEDavO3CPcrWkSzJVCruUz7411MI8fvBGVGTF+rF - RNYUjFSf5YdrUU1p8hEBd8+EGVW35X15DgGScnnChJpjNdwy9FwL0tMlRgyC17vL1kCbfjfh6T6S - dgyr7gnluHgza5WwdggP9ROJIIYsG85vPmzt0oVPI3HiH75VPh3T3lBWpZ2wU1KTqvUPogA0ObVM - bXCVD49giEFUVZH5r8LUR4nIBayme4Olp9miafs6S6jc11t6kdOyoiNfH6CJPwUzzG8fje9ddgHK - Zc600Np6oq4bk2JUu4Jyx/hELBZ9H50TryPmqXEi7hxljCL5Y7Kzdd9WfP1+ChA1VYWH+7bTB9Xe - G2iZZ19iKB+ZM+d+M5CziEYM8rHm460dnyC99Qrrd8Aee0pchJPTxlQK3l0+0KtjoP0Q74ldiK3X - v+KkA/qqAubtwm8+PV/uB17Lyw2nfFByuovyWAl0vSf2Ijl6U9VZGSgrTin09lufjLt4geNluSI7 - yy7yKVDOKqAnF/Bj/dlWy912b4F+bM8siMIBdeYmPaCD+k4wvwtp222dJIX3drtjQR+ZLV0+Th8U - LsmduB3HERV0zYLa7EvinjcD6s/C1t1kwvAi1r7dRNdtjkul+GaUGUJAvYHsbQzn6jQQB9f3aHxG - 9gl6+XtnJnuuqskO3AG1Qk2Z+xm2rWhK2xuU4+ZNl44MfDgq1gmZoTkQ73Vk+rRxYALyZTviD8xA - Q/tVjc3rdQrY3o6KdjAl54baIsqIudd2+RDcdxS2xCiY3zttNDV+U8BaaYA5aEWi4SNdMlCHNcW8 - 9Sf9La6zE2xBvdNiXH0rfsWFuHnmPMLtuF23D3dZWSDV0505X+PGWbj4GmitjDcqCWWN+GuAGDT3 - ZJLojr585Bc+wCM9CZTW0TKnrY9qqE1WEvWu7tBSMboOUCkRZlzsvd4fvUWDzgas6aZ2cm+Y6xV5 - 9uCwW/Yuo3k9fRCcxiO7hSNGjb99KWg+/8Q0RQ+N5blRFWRpE10Kp66aRjE/gbbeqbjb5TveLU3d - WlRqCPjWA6qm5ae/oIeILOI/FK9afV/3CzhaVOLV/vyp+n75BIg88cN2zqBFXBvCFILHOWJ+Xwtt - n7jnAxSrTmfe4f71xmd0vqDzOKXEw3Ib0ceYdWCb7oAXxpHm3d7jCpyr9I7LjdTxIbj1T+SEzxXx - 0y7UqV6/XejazCPm5dDmT+g4wOKVv4nr9j4aRB9LaJJyhS6olfBhPdkhnD7OhalNp/B+tQ9EyK9n - QgJ4Z+1EVXgqx0y2iSd7hsfLjX9Cj/RK8BRWYt7vry8LjW5zo2MVYN5g0b6hrj15jKj8Go3Jnhqw - 3ysZHio9rkbcWBg8t5eJmZii18kqkdA8P6blVONjsr9qwDWIyBVeB72TZUVA1Sby8BQ7Pe8OxuDC - Mo9PTGdYqfiMNyDI1RpvSv3R9su0xehq1iVxZUNqn/P81hc3wWy76VM0vLToAosXFpmaXyTE705c - IJqEDpbP3pMPW+caA4/UJwlE9G7HK7/fUFZc90TbxmLbz/WJ1KK0yc7Fa84vyfIDlEslnaQwymn0 - ZaISLOibmG1RV3TP0hDee++L5YMq6dzby91P/bHgy+KKXo26hvx6L5g+42c9icsCjuvLgx2qU5+z - VR+dwISPTYyqr73J315EMIyLhMd4C/okvpUQBvDfeDG2nt4SK5KUeT+YNvMHPz2yAvnmcKZrlBc5 - w+a6g2e+elLoXVKNiWv7iHzXCvHSx1jRcFmLIC3DN/N3WdWOZwFiCO1kZLY1phHnaydGfuos2DZ/ - dWhUz2sMzmI/0uOMl+36nSuwk7iL08vFbEdYhTG4ueQyvLRqr9fjjYDSbUSYlrO3NyBeN8AKpNNX - EXNOO0tV4KNsEvxdXJ7ttPwIJVokbsVcvUiqQRK+GVxfaMWsk9R5/JI8n0iqpYHNeK5PRCyfQLlY - 0mkjJ/lkFGaJbqG8Y8Z7OKBJSSmg28NS8MuUxIiWzdoA/xk+fvmG/+BXXWZXgqMbePSUCjZiZbug - yk3dVM36sipBcQxOTGVw24FetxbaoFhi7k29Vp0lHQplVzcfYgjuNloxP/Hh66SIbNefRzt11h7g - gIcdi+f97OiTCqhYfycSRGHIOT3EHRwvLPnhZ2+ZuOcQFq/IJNv198WnAVkWWHk4EXdnEW88mcxA - efuJmMkdn/MrHmU4rrOQ6RNnaJj2Tx/WARqIeQk1vjyk3xhmfmXGqcrRGFbLD0SevMbJdtJzZrUL - f907okYwyTx90u/bEGFsBCSOr1o03VdbGy6rfUAwUFtfvQZIkW2SLdHpUOkjCL0NUwI6M5S32PaP - e3jZzPxDF2ra6DQucw3tSzPAg1F+qkGZzjMe5hHbHgXmfbomOQH5IoV4u31QTZxGMtDkBngBSoO4 - uK4usGx7gW7GY9rWIVUBTtJlZJqxeuRcKb4YlPfl/MOf+ogbjBVVU1WSMrrn42p/k2FXfz5kZ3m9 - Pn7t9wCqvr7hoekUNPjXRwzskCG8GdMpancvv4R7d2PMRuxaja+4npAbvCyMUrNs+6lKMvRRkIHn - 89GO/OqLKPIWLtlOdxT10fFSoJnPmJPQRz58JamAo3/bY7jKlT7V99fht54X0ctpp2/ku+gHn9wv - XnvNMdUAPc+CRdRR7vn4toYUpdt8pNIeN/oYPu+Dsrl0PnMTZEfjK752kFEaE/uxv+W80B4SRN50 - ZNae0IjZNw6bN3vfibZZ7XV+fkCD/NgPmV49qnyKy0jbyMyImJeaWjUsDUVFRFYvWJENqaKOdTKg - fNCKsnWSVEMR7wFAwAaVr0GQj+4yU9EAiUPXZ1Hhn2oni+jNbhv80vYLnRXaaYD1xRXpoD6M6HN5 - SxISpNql9eXyaif9fkhhwUuHqEZpV6w7CTECPVjSIT83+lDtZAm2Pc/xMMoB/5kfeuw2O6LRd+/1 - VWa40Ao3n1mXi1kNifzRUGhdIuZllsX5zQ4PyM1Fl2GStbMeailqtwVmlrl5oPEyrg3gC0klalk/ - 8mn72ku/etletX67Cvwo3XBN0ZjzyOWWHd+VBeFTcZltcQGNauYe4Cu5J7aVjKGd9VcGiXFYULbc - P9vx1uUULm/Nmf3Agw/cXZdrXQqmXz3VXDflBFuiEmKugitnd6evwVu9akqj28Xjm/jsohm/SdBH - r2oQ7nIHxWqIiS6dzJkPphCaeBmx4FaInKZXTOEHX2y0r72xyhIftOySsh2TfW8MhqBTDjflSxfR - 69tOiBxcgG1oEbcTD9UAXaMg3NUJlU5yXE3m2Zng6LcGBfloIeZHdwu2xB6JpShPNDy36xjd4aES - sk7XvFNtVd3M9cXIsbnN/kKd1lZ71JnRxhVn00JUYSeNLpn5mY/310NDxMMLpldVi7j13McIxdmJ - GSs15aMePxWYpLPC7OdZzSX97hx+/AhV3EbVV4N5vqBNb05sl+SjN+2Z6cPLrge6mfXM7+8/fpix - e5lpiHM19X/qnanru1dx9IhPYK3pl8Itnjwece7CzD90vH/W7SSVsQJ8/GKqDCe9Wg6fadgwzbfJ - eXHrveaHLyJvOBLjTd2cf56aC8fWQkyTsIuGRXGQ4JHeCf50ussZWZxUOPRpQSdj7XAO2TQgcv5I - xPugwhs7cT2gk9O/mHZPipnPt7cfvMPy55a0E1kaHZyrx4EZhZPknPlXH4J9ohFte+j0zpS2F/BN - ahNc4sIbKnurwLQbQxKUFo466EoF6nhnY5RWmTcJ2lqDtnBl4lxPHhqEd1DAHSqVQnZwKp5QowNd - PL2IZm8URNeXRYHs5Cz+npeu2g0S4o+Ty864XuT9IVUyaIt9RnZPvOVLk+xKKFylJobyjttpUDYa - XF/rFZX2gclpGxifzSLdDEQP2VHnV/wRodXvG1orm7Gd1gkaYMZbhmGMEd12iw4UG/bkpjqVN77x - DaPwZW1weRchGhYFgDLrR/bzf98z/v3ob8zq+8njohLU61SwgZ0OWyVqQjrvVUFD5gz4m09WpB3Q - eyNVTG3atBrdpSps2rtgEFOipT56VM6gQ9/Zf+x89F0egxROR/jSaSP5fLx12mfzo4/l57mIKEar - E9gjBLgjBvUG6EoZLF9EzPtmiA87Jivgm53NTIWvcmplWEUn6TbiRX1pc/YaqgP402fHzGpV5OMh - nU7gBllE3J3p8jFbDTUoS+FBR8k6ewM+KooS6Nv+F5+o+J4OsOAUGPE273bqVSdTggXKqKQoTz7t - Kdhoey2PTJOCuhr51RChP8Uuu2R7M+IHJZ6UprI/eJVkPqLrRH3CMr8peHnqRjR9DiFsOjw+mJMG - G49fiSv8+qeP1r+iUQq3NTquy4kKS6vWP+fuO9f/YoOFW3esxhYtS1CH0SeOJlf8G3wdUOrYtOlL - GZp2+LKwQTNe4RVbvVHTWaIBwlkS5v3N0CAJYQx2VL/JD9+yLF+68LP/lnYeUMO2KYVHXRU0MLRl - 2527adZTh4l5aaV4TKZWDYbx2JFd8fnkU78L7BXs246pxnP0eiOY8EbLWoeZp17yumnf+SiSp/fs - D+J2HMsGg/6Sr3jFb2YrTeKmBB55FttxJW4nIqIGucHbwouj/86n+t6HMJ83zN8vMeJCQm8oYE3K - 3CHz9cndvTIItLVHSE5Evf3hg+V6oTEMw1DxLO8M9MyXT2IJQsKnkNoCwsi6MnJb9i0t28hHDT/m - uM+uH51V0p4i/shcps95xTT7S/QMzj0dxuVWn/kBw5hRhuVVY+fjZ9cWaAA7ZfG2Ltp+5aw1kDeF - y3afw4FPG6eicDqKO7aNUBmNY3m2Ua0LNfNvqdJ2opd/YMZH/H5256gXxklAwf4wUvQ98ajXok8D - U6rFzBRE1PLRqidlXO9tFohKlQ/8cM/QjLcEz+eDNdd1DeRcxlTRjbodXVjI6Jr0BsFL84HojIdK - cih0tnuGTTSV0w2gu3o75rmrt9cjITZgzlfI1mCsan781sy/5Dnnb62QXDOUHOqYkEZ78uGBt6fN - PRBNLFnbCdFZv6M21FLiaGtbXwV+d0JpLzj4JYioar/XooTr02iYv7t0Xr/T/AMwY1cza+9v2yWs - HieEuK4xT/ae+qBpagn09WXECj5hO4Hj1LDB1RkLc17B6zG9gHo4JkxVH0bOX4Nj/+Af3sCzn/1M - LYBxAIG418cDDZ+lEoIYeinlP/hZaJOi7PU2xctLqKEpUJCNBOfj/eRtaOYrF+J3xbHkvCr+q0dT - YX/D6HUkep/J2w/wiByJmp8bb+iaRQGLV5KyQES7ajqmFxUdW8dnznmaIv4a2gPox7dNHPyU0I9/ - VAT5aDE9X2/zsV9KKtyVwcDNIbJyWt8vGBRbUckOVQrqW7Qp4Zo0fNbz22jlHVoZcNetSP6Thwi6 - a/2sz2/+ypcKo2BHF5OdFxejXR0/gY+0jxLQzZhgj3+fyxSmXX1l3s09olF2NQuYdjj/5ln8XAYd - VL11mvNWVg30WQvKPhrlGd86NDjf9QledrslrtuoHvO9woVIpimGLNx63x/9/5XsExbkvkINp52A - 5vVnmo0O0VzfB0V51wgPd/U9+9u9oEw7HjJ3tXjordleLQRMvJFtXhnRLz6YdwXwIqp71MnyJEDe - Li2mGq8kpxglIaQ9OCysv1TvGjYNSrGSXkSXsqBlQmKkaJEuBhxuLCcfHji7oZ/89jyQvurPQhvC - dbqFNL9SG03LR9igr+OfqeCNTzSSSrtsdnW3Zni5a/JxeTRnPffe/+JJkzmTjI7rU0g05YD4eEgf - qdLEXGN2t9XypbW1VXDC/kx/ztvy6K0atIoGRi7ZwWm5MZEJ7oGS0uG+9b01/uYqZMWL/+qHXj1/ - XCSd3h19o0rhQ2y9a6BVp+LV1ThGzaBsVGWAo8PU5bXyJrXdxwiGXYXFqrf0vl8KGvqeXwvmgqnw - 3/x2APwm/i7fzf4uDDe3RTEwV9awPq72gYS+75VOuaDu9OU2W97QxfU75hSL7+zHrj6yJ4MRB8m8 - 6rrGiMEMdwPeyKUZiXNeCvh25SyQy1c0ie+TDSbFe4x2hz2fx6fQ8CRnmv9o+Xj0Fh+w1t2XyjiD - aszljMJP/m0mZuzN+YAAxYrqzHBwWY3JPlFh2jWUqfQQRxNby8OP/6HLU9tXrzdOMZhAz3TtFiYa - t7lV/uYp0scBNG6z7oSKc3zF8qrtqg516gQhPx2Y+/LDuf/QFMpVDHxi8SHL2acqtI1yTlYEvyTN - G8PncYCZ//D2/llXk1GkT/TMx4hgb3L07pG8Q6Qs5ZAFfeygHlZhitrClud+gx6trqS3wDgIApvz - zJxLXYHBF18S2TbLEM340kBsIwcLY+FXfHdTJ0B8F1F+Oq69Sb87cz4ZCYSoaeN1B98QkHGQLgSP - 5VIfkXmUUbycVkyrN2Xb/uRrXwefiRlcgtkvyzHox++Z2Fpv5pOSGiLM/Qm6NJehLvWL4QCfS9r+ - 8Ls+ncg3/tWvs79qpfSybDa3xXtLDJZdI6l6fgq0Kg2D3GAU+SSVFxna/Vpk5huWFfPO7wZ2dX1k - 7uON8vEsOC7Ex/Me17FYVb/673v8hMzFh9IbqzM3Nof+QFggCnE0nHvPRgv+aVnU+gdvNHCc/vqV - LD2uoqFGRQfr7vie+c9qh/5pSPBR1sac5z/RnEc2sC8OKiEe6PkSFuSArmJ0JbqzS7wpc74igkE/ - EPcMfjs5VmhtlDNJ8N04HdpBmfYxFN/LggSpPKH+YwcNzPqABYYhePS6sRuYjssH0f3OjYbxxAQ0 - 8z+5wjPg40bWy5/6Z9qcXw7mJg2BWoL4i7dDRkmGND8RiYuHdTtcilCAQJMUogfOpuok4ZSCCPKD - 2Gf/q/dzPoN++PySsQvn2QVjuHcXxiLH7Krx1m1EZe4PMTtABeLMQxZ63+Oc7ZvlwFkJZx/caz/n - Pbaad192+sBP/aeXy6v6vuJ6gBk/iP2UeMu1lYDhvREr4lyzOBoTV/UVNAkjweW+41R8h+7GWjen - OS/P0LI8nwDiV5MQ5/Nu29Fd2oBmP0XrZ3n3uqWhaFA+ViYV1u5K72rQJAjT5xJLcz+KHd/gIssf - mhnPdK8Xk0HdLAPnRddnnlbToFTCWrLTD9EM2Zzz2MxHcz4480OA3nfHuwAfW8x2lvOsJm8n3H7w - gKnr2y76doBrMKm/Z4G63UdTcslLuD3IBYMuNrM/+Io//SqybeRr1SPhYimqZux/zxt7SkiCq3lR - 2fVWXqM5f5aAa7JG9EkU9em6KQe4acWDaMb6+5tPbfxp+tLVVY/0ITLbFBkPrNGlRDVvCpTGQMEe - F8zrFnt91Z0uPtrvhZYYSh3mfRx+RUhG60Lsz3Uf1SMfD2DeNwEhpNp6SwN7B4XyhUHH6Xac37/v - wDen869f4KdH9QR9V67wJxCClleS+tkk5epEtv4p4VPZau7mnDgdIdHrW/F3ayo/+RAe7aiomLiu - bjD3R/DywoR2iMwsRFZuhyT49r7O+/1Ug2dPDiOlnM15m9+gS3YfCL41bNZzzecnL8SrJN977Sa2 - LQjY02Ra+JSrrv3a1m++HwXOpqWuNfnwPdIH+eGPjuzLGKw20Ykr3q7e1PhlAT/9C0/vTtGIBE+D - 7/l+JZqNppxt8oWqRE06EO8DRj6fF4DvsXvgzUF88EmvmQs72yDkR59Pn7Mk/uKv/bM+oXpJobsI - MQvG893rFoUzway/MRDt1Y7RUfpsOtQSnB3iph2uD8MGe3JUYlzsUR9emnaCn36qfkdfxKTug8Ew - 2i8JDC2phnixbcC6mgum35GDlg4kA8hqR5n7cu2Zr58CEO/4oCPN3ei3P/KVrB1Ro9HWpwV8MmSM - 2ZIORtXx4dwpFqxKN2HWnAcMx2n9hJ989yfPHuxh6QKPtCfxxBqjeT6Dss6FLQViHqLppz8TPoV8 - 9hOralxMvvaDz8yytgc+ftVBAjlED7az3hf9Jw9Gf39uBfznv/78+V8/Nwzqz/X2mi8G9Lex//d/ - XxX4d3bN/i2K0r+Z9HsTgXZZcfv7z/+5hPD3237qb/+/+8/z9u7+/vNH/r1t8Lf/9Nnr/3n8r/ld - //mv/wIAAP//AwBxbwgZ4SAAAA== - headers: - CF-RAY: - - 9472cb0e498df9a9-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:28 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-allow-origin: - - "*" - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-model: - - text-embedding-ada-002-v2 - openai-organization: - - braintrust-data - openai-processing-ms: - - "53" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - via: - - envoy-router-dc9d5f6f7-bfg9n - x-envoy-upstream-service-time: - - "56" - x-ratelimit-limit-requests: - - "10000" - x-ratelimit-limit-tokens: - - "10000000" - x-ratelimit-remaining-requests: - - "9999" - x-ratelimit-remaining-tokens: - - "9999996" - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_9392a0a1e391f86ea94c557497f4903a - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_not_given_filtering.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_not_given_filtering.yaml deleted file mode 100644 index 002071033..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_not_given_filtering.yaml +++ /dev/null @@ -1,108 +0,0 @@ -interactions: - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini","temperature":0.5}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "98" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFJNj9MwEL3nV1hzpVk12aBNewQkbgiJG2gVTe1p6q1ju/aEZVn1vyM7 - pcnCInHJYd5H3hvPcyEEaAVbAfKALAdvynfy0+P73dPxw+MG3ekrn35WY/v5qB42Xz5GWCWF2z2Q - 5N+qG+kGb4i1sxMsAyFTcq3umrZp26pdZ2BwikyS9Z7LxpWDtrqs13VTru/Kqr2oD05LirAV3woh - hHjO35TTKvoBW5G98mSgGLEn2F5JQkBwJk0AY9SR0TKsZlA6y2Rz9KoWb0RVCzqNaKKom5slMdB+ - jJjC2tGYBYDWOsZUNke8vyDnayjjeh/cLv4hhb22Oh66QBidTQEiOw8ZPRdC3Ofy44s+4IMbPHfs - jpR/VzWTHcwrn8H2grFjNPO4rlevmHWKGLWJi92BRHkgNSvnReOotFsAxaLy31le855qa9v/j/0M - SEmeSXU+kNLyZd+ZFijd479o1xXnwBApfNeSOtYU0jMo2uNopiuB+BSZhm6vbU/BBz2dyt53tw2+ - bZA2txKKc/ELAAD//wMAaAEkkTgDAAA= - headers: - CF-RAY: - - 9472cb57fe48659d-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:41 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=Yi6aaLaw0NZkdHvrki4WOE5tE6U94TABT1plkmJKfqQ-1748488181-1.0.1.1-LdRP3crB0p5QFhTA5pwITOIrJYA7eAyD9jWRNne6ofo.KlYxvbAHDHsub1yEy5RdsLo_SoAYmKEddFZv2adJjFbeq3.3hc1sdtnjLcs_J.E; - path=/; expires=Thu, 29-May-25 03:39:41 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=MoVXRPgslfEHsJs5qWj1Rd2oCC7HIsq2nTprVQqpfSQ-1748488181133-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "543" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "549" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_5fe641e45a5e8b15e3ad21c8469ecaf5 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_parallel_tool_calls.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_parallel_tool_calls.yaml deleted file mode 100644 index 0a798f3ab..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_parallel_tool_calls.yaml +++ /dev/null @@ -1,533 +0,0 @@ -interactions: - - request: - body: - '{"messages":[{"role":"user","content":"What''s the weather in New York - and the time in Tokyo?"}],"model":"gpt-4o-mini","stream":false,"stream_options":null,"temperature":0,"tools":[{"type":"function","function":{"name":"get_weather","description":"Get - the weather for a location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The - location to get weather for"}},"required":["location"]}}},{"type":"function","function":{"name":"get_time","description":"Get - the current time for a timezone","parameters":{"type":"object","properties":{"timezone":{"type":"string","description":"The - timezone to get time for"}},"required":["timezone"]}}}]}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "676" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.92.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA7RU32/aMBB+z19h3TNsQIMoeVt/TFOrVa2GWrZRRa5zJCaOndmXUkD871OSlgTa - bX1ZHiLnPn9333c5e+MxBjKCgIFIOIksV92TLH2is2Q9EJ9P7k5/nT6K8/T69Hpy8W2tFtApGeZh - gYJeWB+EyXKFJI2uYWGRE5ZZ+6Nhbzwcj0ejCshMhKqkxTl1fdPNpJbdQW/gd3ujbv/4mZ0YKdBB - wH56jDG2qd6lTh3hEwSs13mJZOgcjxGC3SbGwBpVRoA7Jx1xTdBpQGE0oS6l60KpFkDGqFBwpZrC - 9bNprZtmcaXCxZBuM3989nVyNZ2u3HnqLqJkcela9erUq7wSNC+02DWphe/iwUExxkDzrOLGSOES - OSVoD+iMAbdxkaGmUjpsZqCM4GXCGQRsBle4ZN+NTWewhT3mtvW17bzLMuaJ+nF5Q+mXk3Xvzt3I - VCyn54b/L8skM/y333LX2mis/X5ykn+cmHRl/u54t75vjYHFeeG4ej0fXGtDVVerAbn3DvoGysS5 - NQ/ugApzqaVLQovcVX7bk+a9CKkkQLE3zJBbk+UUkkmxKjr266TQnLcG9I+fQTLEVRPv+4POG+nC - CInLath350twkWDUUJtzxotImhbgtay/VvNW7tq+1PF70jeAEJgTRmFuMZJi33GzzWJ5Hf1p267J - lWBwaB+lwJAk2vJ3RDjnhaovCXArR5iFc6ljtLmV1U0B8zw88vnQ5zg+EuBtvd8AAAD//wMA/xPD - hjcFAAA= - headers: - CF-RAY: - - 955e85f4bc84c598-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 26 Jun 2025 17:46:18 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=ImsddYvCWfxjvgCkc.PQteneAt1.05OrnpctX.H9.6Q-1750959978-1.0.1.1-nNSwp_XWJ00JfcdLpEJJIkWuFwKp_G8OsvkqQJ1Y.t3LIgdq_FjD6D6k6xGKWUB1YmzkYT5DEps7_NG5XU.HYhGXfOrQ_qYymycHaizxQ64; - path=/; expires=Thu, 26-Jun-25 18:16:18 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=QM6hDu5SUhMw7byvxEvE9lxA0zi2uq0mxJsxgQgHJZQ-1750959978886-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "905" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "911" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999984" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_ce9634fb6e411458288df8bbff2c6949 - status: - code: 200 - message: OK - - request: - body: - '{"messages":[{"role":"user","content":"What''s the weather in New York - and the time in Tokyo?"}],"model":"gpt-4o-mini","stream":false,"stream_options":null,"temperature":0,"tools":[{"type":"function","function":{"name":"get_weather","description":"Get - the weather for a location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The - location to get weather for"}},"required":["location"]}}},{"type":"function","function":{"name":"get_time","description":"Get - the current time for a timezone","parameters":{"type":"object","properties":{"timezone":{"type":"string","description":"The - timezone to get time for"}},"required":["timezone"]}}}]}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "676" - content-type: - - application/json - cookie: - - __cf_bm=ImsddYvCWfxjvgCkc.PQteneAt1.05OrnpctX.H9.6Q-1750959978-1.0.1.1-nNSwp_XWJ00JfcdLpEJJIkWuFwKp_G8OsvkqQJ1Y.t3LIgdq_FjD6D6k6xGKWUB1YmzkYT5DEps7_NG5XU.HYhGXfOrQ_qYymycHaizxQ64; - _cfuvid=QM6hDu5SUhMw7byvxEvE9lxA0zi2uq0mxJsxgQgHJZQ-1750959978886-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.92.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//tFRNc9owEL37V2j2jFswBDA3kqbJTNo0ZTKdZkrGI+S1UZAlR5L5CMN/ - 71h82JC0zaU+eOR9ervvrVdae4QAj2FAgE2pZVku/PNstpxfPgXf8Cb8+ixv21dKNJfncjT8Li00 - SoaaPCGze9YHprJcoOVKbmGmkVoss7Z6Z83wLAx7oQMyFaMoaWlu/Y7yMy65HzSDjt/s+a3+jj1V - nKGBAfnlEULI2r1LnTLGJQxIs7GPZGgMTREGh02EgFaijAA1hhtLd5p3IFPSoiyly0KIGmCVEhGj - QlSFt8+6tq6aRYWIllej1vV9oL8MFxemKy+fb35MUPdkrd429Sp3gpJCskOTavghPjgpRghImjlu - ijZaILVT1Cd0QoDqtMhQ2lI6rMcgFKNlwjEMyBhucUEelJ6NYQNHzE3ta9N4l+Xk88PPeXuldKv7 - wkfD6+Ti012he/x/WbY8w3/7LXe9KIlbv0PD6cd7NVupvzs+rB9rY6AxKQwVr+eDSqms66obkEfv - pG8gVJprNTEnVEi45GYaaaTG+a1PmrcX4iRAcTTMkGuV5TayaoauaNjZJoXqvFVgp78DrbJUVPFW - J2i8kS6K0VLuhv1wvhhlU4wranXOaBFzVQO8mvXXat7KvbXPZfqe9BXAGOYW4yjXGHN27LjaprG8 - jv607dBkJxgM6jlnGFmOuvwdMSa0ELuLzayMxSxKuExR55q7mwKSPOoGNGjTfgsT8DbebwAAAP// - AwA/i1dUNwUAAA== - headers: - CF-RAY: - - 955e85fc49a8c598-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 26 Jun 2025 17:46:20 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "1353" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "1375" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999984" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_d7ad22f31a644826179f4d68275a2f4e - status: - code: 200 - message: OK - - request: - body: - '{"messages":[{"role":"user","content":"What''s the weather in New York - and the time in Tokyo?"}],"model":"gpt-4o-mini","stream":true,"stream_options":{"include_usage":true},"temperature":0,"tools":[{"type":"function","function":{"name":"get_weather","description":"Get - the weather for a location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The - location to get weather for"}},"required":["location"]}}},{"type":"function","function":{"name":"get_time","description":"Get - the current time for a timezone","parameters":{"type":"object","properties":{"timezone":{"type":"string","description":"The - timezone to get time for"}},"required":["timezone"]}}}]}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "693" - content-type: - - application/json - cookie: - - __cf_bm=ImsddYvCWfxjvgCkc.PQteneAt1.05OrnpctX.H9.6Q-1750959978-1.0.1.1-nNSwp_XWJ00JfcdLpEJJIkWuFwKp_G8OsvkqQJ1Y.t3LIgdq_FjD6D6k6xGKWUB1YmzkYT5DEps7_NG5XU.HYhGXfOrQ_qYymycHaizxQ64; - _cfuvid=QM6hDu5SUhMw7byvxEvE9lxA0zi2uq0mxJsxgQgHJZQ-1750959978886-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.92.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: - 'data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"role":"assistant","content":null},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"id":"call_WY2R9D3MQrwbUTvQFtua91zx","type":"function","function":{"name":"get_weather","arguments":""}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"{\"lo"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"catio"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"n\": - \"N"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"ew - Y"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"ork\"}"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"id":"call_ZwNK54BJyVcJ7sbNZzNOaHWW","type":"function","function":{"name":"get_time","arguments":""}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"{\"ti"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"mezon"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"e\": - \"A"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"sia/"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"Tokyo"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"\"}"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"tool_calls"}],"usage":null} - - - data: {"id":"chatcmpl-BmkxxakFMg9fugkFzAcDoNWSCaHLW","object":"chat.completion.chunk","created":1750959981,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_62a23a81ef","choices":[],"usage":{"prompt_tokens":94,"completion_tokens":48,"total_tokens":142,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}}} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 955e860739ffc598-EWR - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 26 Jun 2025 17:46:22 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "1073" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "1081" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999984" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_9b29e4d9569098cfbdd2d6afe87df7ba - status: - code: 200 - message: OK - - request: - body: - '{"messages":[{"role":"user","content":"What''s the weather in New York - and the time in Tokyo?"}],"model":"gpt-4o-mini","stream":true,"stream_options":{"include_usage":true},"temperature":0,"tools":[{"type":"function","function":{"name":"get_weather","description":"Get - the weather for a location","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The - location to get weather for"}},"required":["location"]}}},{"type":"function","function":{"name":"get_time","description":"Get - the current time for a timezone","parameters":{"type":"object","properties":{"timezone":{"type":"string","description":"The - timezone to get time for"}},"required":["timezone"]}}}]}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "693" - content-type: - - application/json - cookie: - - __cf_bm=ImsddYvCWfxjvgCkc.PQteneAt1.05OrnpctX.H9.6Q-1750959978-1.0.1.1-nNSwp_XWJ00JfcdLpEJJIkWuFwKp_G8OsvkqQJ1Y.t3LIgdq_FjD6D6k6xGKWUB1YmzkYT5DEps7_NG5XU.HYhGXfOrQ_qYymycHaizxQ64; - _cfuvid=QM6hDu5SUhMw7byvxEvE9lxA0zi2uq0mxJsxgQgHJZQ-1750959978886-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.92.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.92.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: - 'data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"role":"assistant","content":null},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"id":"call_jTy9LzkVyn6cPzokhRZK3wac","type":"function","function":{"name":"get_weather","arguments":""}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"{\"lo"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"catio"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"n\": - \"N"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"ew - Y"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"ork\"}"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"id":"call_kHgzyiyayXAQ2OBYC1r5QSRg","type":"function","function":{"name":"get_time","arguments":""}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"{\"ti"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"mezon"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"e\": - \"A"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"sia/"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"Tokyo"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","usage":null,"choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"\"}"}}]},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"tool_calls"}],"usage":null} - - - data: {"id":"chatcmpl-BmkxyGlaywPrIMWVV0sU4x39kgJtA","object":"chat.completion.chunk","created":1750959982,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[],"usage":{"prompt_tokens":94,"completion_tokens":48,"total_tokens":142,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}}} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 955e86124a90c598-EWR - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 26 Jun 2025 17:46:23 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "970" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "981" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999984" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_62275476d620d1e6433d08dca31bbde0 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_response_streaming_async.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_response_streaming_async.yaml deleted file mode 100644 index a7ab3e55c..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_response_streaming_async.yaml +++ /dev/null @@ -1,333 +0,0 @@ -interactions: - - request: - body: '{"input":"What''s 12 + 12?","model":"gpt-4o-mini","stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "63" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: 'event: response.created - - data: {"type":"response.created","sequence_number":0,"response":{"id":"resp_6837cff103f88198b48d6039e3f856cd039a45d2abd10a91","object":"response","created_at":1748488177,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}} - - - event: response.in_progress - - data: {"type":"response.in_progress","sequence_number":1,"response":{"id":"resp_6837cff103f88198b48d6039e3f856cd039a45d2abd10a91","object":"response","created_at":1748488177,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}} - - - event: response.output_item.added - - data: {"type":"response.output_item.added","sequence_number":2,"output_index":0,"item":{"id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","type":"message","status":"in_progress","content":[],"role":"assistant"}} - - - event: response.content_part.added - - data: {"type":"response.content_part.added","sequence_number":3,"item_id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"text":""}} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":4,"item_id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","output_index":0,"content_index":0,"delta":"12"} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":5,"item_id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","output_index":0,"content_index":0,"delta":" - +"} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":6,"item_id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","output_index":0,"content_index":0,"delta":" - "} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":7,"item_id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","output_index":0,"content_index":0,"delta":"12"} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":8,"item_id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","output_index":0,"content_index":0,"delta":" - equals"} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":9,"item_id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","output_index":0,"content_index":0,"delta":" - "} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":10,"item_id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","output_index":0,"content_index":0,"delta":"24"} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":11,"item_id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","output_index":0,"content_index":0,"delta":"."} - - - event: response.output_text.done - - data: {"type":"response.output_text.done","sequence_number":12,"item_id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","output_index":0,"content_index":0,"text":"12 - + 12 equals 24."} - - - event: response.content_part.done - - data: {"type":"response.content_part.done","sequence_number":13,"item_id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"text":"12 - + 12 equals 24."}} - - - event: response.output_item.done - - data: {"type":"response.output_item.done","sequence_number":14,"output_index":0,"item":{"id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"text":"12 - + 12 equals 24."}],"role":"assistant"}} - - - event: response.completed - - data: {"type":"response.completed","sequence_number":15,"response":{"id":"resp_6837cff103f88198b48d6039e3f856cd039a45d2abd10a91","object":"response","created_at":1748488177,"status":"completed","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"model":"gpt-4o-mini-2024-07-18","output":[{"id":"msg_6837cff183448198a6b50603bc5bf592039a45d2abd10a91","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"text":"12 - + 12 equals 24."}],"role":"assistant"}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"default","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":14,"input_tokens_details":{"cached_tokens":0},"output_tokens":9,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":23},"user":null,"metadata":{}}} - - - ' - headers: - CF-RAY: - - 9472cb41d9474364-EWR - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:09:37 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=xcwO9CpEIfCnqq7YaUa1xTsHb7PHgHBbrqIHapZiPnI-1748488177-1.0.1.1-gVS2m.T1Q0blZ_BZZDE4D_1TrW8eSj1nXNItfEi1nIYd_oeRzmN9JiknKpOnqLM_yGwiCAJeq5MYWkeKI1ukRrb7RpGQBqKCxwPooZdq7hU; - path=/; expires=Thu, 29-May-25 03:39:37 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=MvpgtBwiS2QiCi_sFTGCV0l53fKk38I432sxv4RxEsk-1748488177157-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "117" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-request-id: - - req_5416e77381569aa7379ad3cd2facfbbd - status: - code: 200 - message: OK - - request: - body: '{"input":"What''s 12 + 12?","model":"gpt-4o-mini","stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "63" - content-type: - - application/json - cookie: - - __cf_bm=xcwO9CpEIfCnqq7YaUa1xTsHb7PHgHBbrqIHapZiPnI-1748488177-1.0.1.1-gVS2m.T1Q0blZ_BZZDE4D_1TrW8eSj1nXNItfEi1nIYd_oeRzmN9JiknKpOnqLM_yGwiCAJeq5MYWkeKI1ukRrb7RpGQBqKCxwPooZdq7hU; - _cfuvid=MvpgtBwiS2QiCi_sFTGCV0l53fKk38I432sxv4RxEsk-1748488177157-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: 'event: response.created - - data: {"type":"response.created","sequence_number":0,"response":{"id":"resp_6837cff1f4608198b0c7325cd6d7a93d04bf0c0fe023e578","object":"response","created_at":1748488178,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}} - - - event: response.in_progress - - data: {"type":"response.in_progress","sequence_number":1,"response":{"id":"resp_6837cff1f4608198b0c7325cd6d7a93d04bf0c0fe023e578","object":"response","created_at":1748488178,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}} - - - event: response.output_item.added - - data: {"type":"response.output_item.added","sequence_number":2,"output_index":0,"item":{"id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","type":"message","status":"in_progress","content":[],"role":"assistant"}} - - - event: response.content_part.added - - data: {"type":"response.content_part.added","sequence_number":3,"item_id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"text":""}} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":4,"item_id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","output_index":0,"content_index":0,"delta":"12"} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":5,"item_id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","output_index":0,"content_index":0,"delta":" - +"} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":6,"item_id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","output_index":0,"content_index":0,"delta":" - "} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":7,"item_id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","output_index":0,"content_index":0,"delta":"12"} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":8,"item_id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","output_index":0,"content_index":0,"delta":" - equals"} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":9,"item_id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","output_index":0,"content_index":0,"delta":" - "} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":10,"item_id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","output_index":0,"content_index":0,"delta":"24"} - - - event: response.output_text.delta - - data: {"type":"response.output_text.delta","sequence_number":11,"item_id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","output_index":0,"content_index":0,"delta":"."} - - - event: response.output_text.done - - data: {"type":"response.output_text.done","sequence_number":12,"item_id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","output_index":0,"content_index":0,"text":"12 - + 12 equals 24."} - - - event: response.content_part.done - - data: {"type":"response.content_part.done","sequence_number":13,"item_id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"text":"12 - + 12 equals 24."}} - - - event: response.output_item.done - - data: {"type":"response.output_item.done","sequence_number":14,"output_index":0,"item":{"id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"text":"12 - + 12 equals 24."}],"role":"assistant"}} - - - event: response.completed - - data: {"type":"response.completed","sequence_number":15,"response":{"id":"resp_6837cff1f4608198b0c7325cd6d7a93d04bf0c0fe023e578","object":"response","created_at":1748488178,"status":"completed","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"model":"gpt-4o-mini-2024-07-18","output":[{"id":"msg_6837cff281e08198b93a44b690d1448c04bf0c0fe023e578","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"text":"12 - + 12 equals 24."}],"role":"assistant"}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"summary":null},"service_tier":"default","store":true,"temperature":1.0,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":14,"input_tokens_details":{"cached_tokens":0},"output_tokens":9,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":23},"user":null,"metadata":{}}} - - - ' - headers: - CF-RAY: - - 9472cb47bdb94364-EWR - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:09:38 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "118" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-request-id: - - req_4a434e2fa2c1a0df8c7a4e1b99dbd245 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_responses_async.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_responses_async.yaml deleted file mode 100644 index 1acb5f7dd..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_responses_async.yaml +++ /dev/null @@ -1,432 +0,0 @@ -interactions: - - request: - body: - '{"input":"What''s 12 + 12?","model":"gpt-4o-mini","instructions":"Just - the number please"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "89" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3RTW27jMAz8zykEfTcLW3FjO0foFYqFQUt0oq0sGRJVtChy94XlR+zd9idwhuRw - OKS+DoxxrfiFcY9haM7VqZQdnts2l1VeV5XKTwrb/FmovD6VmMlzJ7DsSlAnUWTP/GkkcO0flLSQ - OBtwwqVHIFQNjLG8LKqiqvLzOcUCAcUw1kjXDwYJ1VTUgny7ehftqKoDEzDB6L3z/MJsNCYB2i6F - jUICbcI+GshHSdrZ1OQlBmJ0Q2Zj36Jng0FYZPbw0bhIQ6SG3BvaHVHvFJqR4TrQsXDHXlt9FJko - jll5zKvZgFTNL+z1wBhjX+l3dbYP18XY8iTLajS2lrUoatHWVSGKPMu/NTZx0OeAiQVDgCs+Aj85 - mILSWUL7kLSVtaNdBscPWqtTAljrCBYDX3/vgin9wrgo+Arf5681k3tnUg8IQQcCS1PymJiS+AAe - jEHTkHOmkWDSEsnHaeeDx3ftYmiWs2qSoetuPEJwVtsrv8zDcew652mTNBoV+x785wweGLtPF4j+ - XUtsSON4WFxhB9FMLvBAzuNWC2E/oAeKCc5/ZTOafJibd8738Pi/cTnlrcNP/aeZb07LyaRIjq+B - h+ec3NAM254+WpkWk1TrAK1ZHk9MJ7IK0nZ31EI8/Y9vXs8qW4K8oXoUZpP0ufrftyK+w7+jXff1 - EzM5ArMhLlazYsDd6++RQAHBSH8/3P8CAAD//wMAhQO6aMgEAAA= - headers: - CF-RAY: - - 9472cb019ad9433e-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:27 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=WtTUoE6YrHiOeJzkV_hl69OWeRqm715jPbx69WN57Yw-1748488167-1.0.1.1-utal_YD9oicwIv2autnKRz4TbDXJBFO1KrWjEkd9S0bIFx49vU.ac4e1ypUAklFwsW1Tb6scSBerX8YuWWHuxlTTgI9sMvm9mRLsdPqW9bA; - path=/; expires=Thu, 29-May-25 03:39:27 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=mD8lr_Yu2M5EC1wPyAFxVEz648jOHHyWmqRwLqw0XUU-1748488167379-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "627" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999959" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_98e3cefc129761545e956f10ca19b950 - status: - code: 200 - message: OK - - request: - body: - '{"input":"What''s 12 + 12?","model":"gpt-4o-mini","instructions":"Just - the number please"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "89" - content-type: - - application/json - cookie: - - __cf_bm=WtTUoE6YrHiOeJzkV_hl69OWeRqm715jPbx69WN57Yw-1748488167-1.0.1.1-utal_YD9oicwIv2autnKRz4TbDXJBFO1KrWjEkd9S0bIFx49vU.ac4e1ypUAklFwsW1Tb6scSBerX8YuWWHuxlTTgI9sMvm9mRLsdPqW9bA; - _cfuvid=mD8lr_Yu2M5EC1wPyAFxVEz648jOHHyWmqRwLqw0XUU-1748488167379-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3RTW27jMAz8zykEfTcL21FiO0foFYqFQUt0oq0sGRJVtChy94XlR5zd9CdwhuRw - OKS+d4xxrfiZcY9haE7VoZQdlvURsyqvK1DV4VQfCylkVpZFldXy0B2Lrj7WqurEgb+MBK79g5IW - EmcDTrj0CISqgTGWl6ISVZWfyhQLBBTDWCNdPxgkVFNRC/L94l20o6oOTMAEo/fO8zOz0ZgEaLsU - NgoJtAmP0UA+StLOpiavMRCjKzIb+xY9GwzCIrOHz8ZFGiI15N7RPhD1TqEZGS4D7YXb99rqfZEV - Yp+V+7yaDUjV/Mzedowx9p1+V2f7cFmMrfK8FaOxrWoPXXZSohS5FKf2qbGJg74GTCwYAlzwHvjJ - wRSUzhLau6StrAfaZXD8pLU6JYC1jmAx8O33QzClnxkvBF/h2/y1ZnLvTOoBIehAYGlKHhNTEh/A - gzFoGnLONBJMWiL5OO188PihXQzNclZNMnTdjUcIzmp74ed5OI5d5zxtkkajYt+D/5rBHWO36QLR - f2iJDWkcD4sr7CCayQUeyHncaiHsB/RAMcH5r2xGkw9z8875Hu7/Ny6nvHX4qf8089VpOZkUyfE1 - cPeckxuaYdvTRyvTYpJqHaA1y+OJ6URWQdo+HHVRvPyPb17PKluCvKK6F2aT9Ln637dSPMOf0a77 - +omZHIHZEIvVrBjw4fX3SKCAYKS/7W5/AQAA//8DADqyKq/IBAAA - headers: - CF-RAY: - - 9472cb06ef9b433e-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:28 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "581" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999959" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_0cb0309b702c5eb0a192dc59212bbae6 - status: - code: 200 - message: OK - - request: - body: '{"input":"What''s 12 + 12?","model":"gpt-4o-mini","text":{"format":{"type":"json_schema","strict":true,"name":"NumberAnswer","schema":{"properties":{"value":{"title":"Value","type":"integer"},"reasoning":{"title":"Reasoning","type":"string"}},"required":["value","reasoning"],"title":"NumberAnswer","type":"object","additionalProperties":false}}}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "346" - content-type: - - application/json - cookie: - - _cfuvid=mD8lr_Yu2M5EC1wPyAFxVEz648jOHHyWmqRwLqw0XUU-1748488167379-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.70.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.70.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3RUTW/bMAy951cIOieFnaSN41v/wDDssEszGLREu2plyZOorkWR/z5YThw5TS/5 - 4CMp8vGRnwvGuJK8ZNyh76uHoqhrIR8ehMyKfL+vdw1KuROwz3cbcd9k2KybzRayrcAm3zZ8OSSw - 9QsKOiexxuNoFw6BUFYwYPnufrMvik2eRcwTUPBDjLBdr5FQjkE1iNfW2WCGqhrQHqMZnbOOl8wE - raNBmXNgJZFAaT9HPbkgSFkzs3fwXtlAfaCK7Ct+BclaXQnQ83SdlaiHYtueVlu76pRRq3W23q6y - 3SovTjTEvLxkTwvGGPuMnxO/nW/P9O72dV4M9BZYy+z+YVvLHQq52d+kN+agjx5jFvQeWrwA3/EY - QWENobmUlJY1S3umBN9pio4OYIwlONP49GcGatv2ztY3kJioZPzzwN9ABzzwcr1dHrhD8NYo0x54 - eeCPUirTsnzNwMjhq1Vv6BkwsgSa2Yatt3cHfuRT6uPp1/Qad1bHDsB75QkMjc6DY3TiPTjQGvV8 - suTCqKve4ZuywVdn6VZxXNPke2e7nioB4hmrV/xIsakbXp5o5dg01lHiNIwodB24c+SCseO4AdAg - fVRKoiHVKJyp26N7UwIrGu1cYgNBj8PhnqzDtAnCrkcHFKI5v8tO1jiEU2WNdR1c/ifDf/HWVF48 - YwcX6Uj0wql+mPysG8a4gS7G/Qhdje7R+H/oEkGOicpEaAOJPTpS6Gd2xkZ1XBmH0hSNY/0d8eUV - eipcGcIWHU/Q40yGXwf09YVfk883r3hyA5o+srjxHHf4NyiHcrZtU4vf1DVZk/251HaT4XRtx8Ob - ICClGmYG+mfKebyji6uaY2fxbg9CmtZmVOe4Lc9WiXG9Alk+AZeN52T7KrkD2WTsUyW6YASctMSl - 8lDr870P8Z5NMlVmdpvv98uv9uTgT2KOCyovgdki6ZVfn/z15hZwK+80qu9Sx1t1AYv1RGHw853u - kEACxd04Lo7/AQAA//8DAHTNXX18BwAA - headers: - CF-RAY: - - 967f53dbecab159c-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 31 Jul 2025 18:58:32 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=lkeCiRquYCqgiu623Z6irUAILQyVnYiSNXREMlvbNvU-1753988312-1.0.1.1-3wYvElBmEIyNAIBM8tphRiDq0ikOlZgfVJo46fL3aSXDNGFmV6Nro7Uoeku7SlTiGgA1JIUNX6Bmz4R1Gc5YpzBQmHzmAiCUQTzWIpNROlw; - path=/; expires=Thu, 31-Jul-25 19:28:32 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=yWKihNSpBvc.c4a.wglI7VJ8BoWki0lAjHeToYfyouE-1753988312112-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "1680" - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-decorator-operation: - - tasksapi.openai.svc.cluster.local:8081/* - x-envoy-upstream-service-time: - - "1689" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999922" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_0dfad232b9e4fb11521291a94f39c6b6 - status: - code: 200 - message: OK - - request: - body: '{"input":"What''s 12 + 12?","model":"gpt-4o-mini","text":{"format":{"type":"json_schema","strict":true,"name":"NumberAnswer","schema":{"properties":{"value":{"title":"Value","type":"integer"},"reasoning":{"title":"Reasoning","type":"string"}},"required":["value","reasoning"],"title":"NumberAnswer","type":"object","additionalProperties":false}}}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "346" - content-type: - - application/json - cookie: - - _cfuvid=yWKihNSpBvc.c4a.wglI7VJ8BoWki0lAjHeToYfyouE-1753988312112-0.0.1.1-604800000; - __cf_bm=lkeCiRquYCqgiu623Z6irUAILQyVnYiSNXREMlvbNvU-1753988312-1.0.1.1-3wYvElBmEIyNAIBM8tphRiDq0ikOlZgfVJo46fL3aSXDNGFmV6Nro7Uoeku7SlTiGgA1JIUNX6Bmz4R1Gc5YpzBQmHzmAiCUQTzWIpNROlw - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.70.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.70.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3RVTW/bMAy951cIOidD7LqNk9v+wDDssEszGLREO2plyZWofqDIfx8sJ46cppfA - 4RMp8vGR+lwwxpXkO8Yd+r56KMu6boq75v5BlNl2C5t7IWBTQCHFptmu18VDmQGIjRQo5Fbw5RDA - 1k8o6BzEGo+jXTgEQlnBgGWb+7ttWW7vsoh5Agp+8BG26zUSytGpBvHcOhvMkFUD2mM0o3PW8R0z - QetoUObsWEkkUNrPUU8uCFLWzOwdvFc2UB+oIvuMX0GyVlcC9DxcZyXqIdm2p1VhV50yapWv82K1 - 3qyy8kRDjMt37HHBGGOf8Xfit/Ptmd6irLdFpLdp6rsyz7OsFlBmDzfpjTHoo8cYBb2HFi/AdzxG - UFhDaC4ppWnNwp4pwXeavOMBMMYSnGl8/DcDtW17Z+sbSAy0Y/xzz19BB9zzXV4s99wheGuUafd8 - t+dZznodPMtyhi8BtGd5sWRvByUOTHkmQIugBwWx+oOBlMq0jA7I6M0yE7oanWdkW6QDuh97fuRT - CsfT15QVd1bHSsF75QkMjYeHg/EQ78GB1qjnCiAXRv31Dl+VDb46S7yKbZ0U0jvb9VQJEAesnvEj - xaaq+e5EP8emsY6SQ0MrQ9eBO3suGDuOkwIN0kelJBpSjcLZFHh0r0pgRaOdS2wg6LGJ3JN1mBZB - 2PXogEI0Zz/WJ2ts1imzxroOLv8TkTx5ayovDtjBRWISvXCqHxQyq4YxbqCLfr9iq34a/4YuEe4Y - aJcIciCxR0cK/czO2KiiK+OQmqKxrX8jvrxCT4krQ9ii4wl6nMn1a4O+3vBnOvPNLZ7cgKaXLG5c - xx2+BOVQzqZyKvGbvCZrMmeX3G4ynI73uKATZJimoWegf6ecx327uMo5Vhb3+yCkaWxGdY7TcrBK - jOMVyPIJuGwGTravkn2xnox9qkQXjICTlrhUHmp9fhdC3HuTTJWZ7fD77fKrPXkYJjHHAZUXx/Ui - qZVfPw15eQu4FXdq1XehyRLoC1huJgqDn890hwQSKM7GcXH8DwAA//8DADFQqW6kBwAA - headers: - CF-RAY: - - 967f630858ef2522-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 31 Jul 2025 19:08:53 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "1248" - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-decorator-operation: - - tasksapi.openai.svc.cluster.local:8081/* - x-envoy-upstream-service-time: - - "1268" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999922" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_6806eb7c8c8dc661df5873167c5c980e - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_responses_metadata_preservation.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_responses_metadata_preservation.yaml deleted file mode 100644 index b38d779c3..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_responses_metadata_preservation.yaml +++ /dev/null @@ -1,217 +0,0 @@ -interactions: -- request: - body: '{"input":"What is 10 + 10?","instructions":"Respond with just the number","model":"gpt-4o-mini"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '96' - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.99.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.99.1 - x-stainless-raw-response: - - 'true' - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3RTy27jMAy85ysEnZuFH4md5DN6LRYGLdOJWlk0JKrboMi/LyzHjr2bXgJnhhyS - Q+p7I4TUjTwJ6dD3VXFQed6kxb7M1SE9JpAmRbHLoEmLvNxnmKTHPMnKgzqqIk32rXwZBKh+R8WT - CFmPI64cAmNTwcCl5b4ssn2RZZHzDBz8kKOo6w0yNmNSDerj7CjYoasWjMcIo3Pk5EnYYEwEtJ0S - qwYZtPFr1rMLijXZWOQ1NtaIP5ov4j14FnxBYUNXoxvrdvBVUeA+cMX0gXYlN5BMZCoFZl2oowbN - UOHc83ZH205bvc2SbLdNym16uBsUdeVJvG2EEOI7/s7Od/48GV8m+XE3GF+neVukRYlY1qrF3VPj - owZfe4wq6D2c8UH85HAkFVlG+2hp2dZKdrIEv3jOjgFgLTFMBr/9XpGGzr2j+gkThU5CZomc4dv9 - a46UjkysDt5rz2B5DB4CY5DswYExaNZbYRfGa+kdfmoKvpoOsopWz1vrHXU9VwrUBasPvC45h+DJ - anuWp7slEtuWHC+CBntD14GbMjdC3Ma7hhb5WukGLetW4+pmPbpPrbDiEZcNthDMaKz0TA6XQzB2 - PTrgEOH0V3JHo4H3zlpyHTz+LxYX40bX7h1/oqvJa76O59Lo0Mm579HHC2k1Gh+Y5Ew89iiZ+mqx - 3WQG+2WPLlgVbyNOqT3UZnrfIV7pPIC2qxeX7V7+xxcPfB4zrq55JCarUf99yNkz/JnsvPyflJkY - zEK4mB0Mfr3sDhkaYBjkb5vbXwAAAP//AwDbGb2LawUAAA== - headers: - CF-RAY: - - 97da35698c67169a-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 11 Sep 2025 21:20:23 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=COKui1p1PyfxAaTpUl7QpKysrbwhNGcDSQhVcne3kn0-1757625623-1.0.1.1-cotK5hjBTwbR36WqOUJtnNS32IaMxlR1lVgkHWREnQpM0BNnnY06onyOG6.5XAD9EJC_HNH95gTjB64Yo69SXnEAqWWTTm1NatHsysUshwg; - path=/; expires=Thu, 11-Sep-25 21:50:23 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=6CYlt5ha6B9yTDGHSh9xg5_n8WVEqvDkNGxq6bU10GM-1757625623177-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '817' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - '819' - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999957' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_11fd255251fb3f822752f773e86a04f3 - status: - code: 200 - message: OK -- request: - body: '{"input":"What is 15 + 15?","model":"gpt-4o-mini","text":{"format":{"type":"json_schema","strict":true,"name":"SimpleAnswer","schema":{"properties":{"value":{"title":"Value","type":"integer"}},"required":["value"],"title":"SimpleAnswer","type":"object","additionalProperties":false}}}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '285' - content-type: - - application/json - cookie: - - __cf_bm=COKui1p1PyfxAaTpUl7QpKysrbwhNGcDSQhVcne3kn0-1757625623-1.0.1.1-cotK5hjBTwbR36WqOUJtnNS32IaMxlR1lVgkHWREnQpM0BNnnY06onyOG6.5XAD9EJC_HNH95gTjB64Yo69SXnEAqWWTTm1NatHsysUshwg; - _cfuvid=6CYlt5ha6B9yTDGHSh9xg5_n8WVEqvDkNGxq6bU10GM-1757625623177-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.99.1 - x-stainless-arch: - - arm64 - x-stainless-async: - - 'false' - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.99.1 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//dFTBjtowEL3zFZbPSxUSIIFb/6BSpV52q2iwJ6x3HTu1x7Roxb9XcSBx - WPaC4L2ZYfzmzXwsGONK8j3jDn1XbytRFHJVilxm1Wonq2Ytm7xois02F+tMZFDkctMcqnW1yrAo - +FNfwB7eUNCtiDUeB1w4BEJZQ8+tyk25zTfbvIicJ6Dg+xxh204joRySDiDej84G03fVgPYYYXTO - Or5nJmgdAWVuibVEAqX9nPXkgiBlzQxv4V9tA3WBarLv+Jkka3UtQM/LtVai7ps9drRc22WrjFrm - Wb5eZuVyVV1liHX5nj0vGGPsI36O+rb+eJO32oGsenl3sNs15a5CKDdZucsfyhtr0LnDWAW9hyNO - xFc6RlJYQ2imltK2ZmVvkuA/GrNjABhjCW4yPv+ekdoeO2cPD5hYaM/4xws/gQ74wvdFduFjyOX6 - bczizurYCXivPIGhIbgPjEG8Awdao55PiFwY/NE5PCkbfH2zYB1lHyfYOdt2VAsQr1i/4znlHIK3 - Rpkj31/l4dg01lES1Esd2hbcLXPB2GVwMjRI51pJNKQahTOXenQnJbCmAecSGwh6EJl7sg7TRxC2 - HTqgEOHVt+yKRjGvnTXWtTD9Tob45q2pvXjFFiYLSPTCqa6f4Ow1jHEDbcz7qXrjfDf+L7rEWEOh - fWKYXsQOHSn0M5yxYcp3YN+aomGsvyL/dMdeG1eG8IiOJ+xlssqUxB3+CcqhnBl6/PcRSbw4dfDw - lekKDEcsYUBK1esG+kf67niTFnfNcU9OxRvYD3ORcPyE7mC9ovOwv1KFlo/mGcz8apUY3B/I8pGY - FouT7epk3bIR7FKjuGAEXEfNpfJw0LezGuLZGF2kzOwErsunz3hyV0evxf2RU2I2e+r9Zd0+wh+V - HTfwq8pkCfREbopRweDnG9cigQSKzr0sLv8BAAD//wMAZ4DdGeIGAAA= - headers: - CF-RAY: - - 97da3571edd9169a-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 11 Sep 2025 21:20:25 GMT - Server: - - cloudflare - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '1229' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - '1233' - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999932' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_83645f5a51f5a71a48ecd36981925921 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_responses_metrics.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_responses_metrics.yaml deleted file mode 100644 index e60721c4d..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_responses_metrics.yaml +++ /dev/null @@ -1,441 +0,0 @@ -interactions: - - request: - body: - '{"input":"What''s 12 + 12?","model":"gpt-4o-mini","instructions":"Just - the number please"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "89" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3RTQW7jMAy85xWCzs3CVpzayRP6hWJh0BKTaCtLhkQVLYr8fWHZVuzd9hI4Q3I4 - HFJfO8a4VvzMuMcwtM/NoZYXhSVg1ZSnpsHqUEp5PFbHg6wBCnnoFArRiFNz6MqCP40ErvuDkhYS - ZwNOuPQIhKqFMVbWVVM1TXlsUiwQUAxjjXT9YJBQTUUdyLerd9GOqi5gAiYYvXeen5mNxiRA26Ww - VUigTdhGA/koSTubmrzEQIxuyGzsO/RsMAiLzB4+WhdpiNSSe0O7IeqdQjMyXAfaV27fa6v3ohDV - vqj3ZTMbkKr5mb3uGGPsK/1mZ/twzcae6mc5Gtupqi6UKoUSRQOi/tbYxEGfAyYWDAGu+Aj85GAK - SmcJ7UPSWtaGdhkcPyhXpwSw1hEsBr7+3gRT+plxUfEM3+evnMm9M6kHhKADgaUpeUxMSXwAD8ag - ack500owaYnk47TzweO7djG0y1m1ydC8G48QnNX2ys/zcBwvF+dplTQaFfse/OcM7hi7TxeI/l1L - bEnjeFhc4QWimVzggZzHtRbCfkAPFBNc/ipmNPkwN78438Pj/8rllJeHn/pPM9+clpNJkRzPgYfn - nNzQDuuePlqZFpNU6wCdWR5PTCeSBWm7OWohnv7HV68ny5Ygb6gehcUkfa7+962I7/DvaPO+fmIm - R2BWxFU2KwbcvP4eCRQQjPT33f0vAAAA//8DAPvvH7/IBAAA - headers: - CF-RAY: - - 9472cacbad828c83-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:18 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=mI1hauJmw2.LoIBdsHg_QC7_NHqZdnOMzWVIW8FsTRQ-1748488158-1.0.1.1-PfdMmNepTIKHAoMhhN4llNkTT13MFq_85COUdhxqy3ZRC49jL54D1VIubFkA9P6h7l9xUlSX8At.zsM0DfeQZ2ty5TkOlp7EiC.O7LqtTUI; - path=/; expires=Thu, 29-May-25 03:39:18 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=tPn8I_CbxQE_7n7eR0tfI8z79gYpGXIT.dYXd5DQUl4-1748488158744-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "611" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999959" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_ed1e4b8509568a7c5b182e720020214a - status: - code: 200 - message: OK - - request: - body: - '{"input":"What''s 12 + 12?","model":"gpt-4o-mini","instructions":"Just - the number please"}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "89" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3RT0Y6jMAx871dEed6egNIS+gn7C6sTMsG0uQ0JSpzVrlb99xOhpHDXfano2B6P - x873jjGuOn5m3KEfm5M4VLLv+rxGIfJaiF6Iqjwcu1qcslPWZ3krRFYcM6zqAxwEf5kIbPsHJS0k - 1niccekQCLsGplhelaIUIj/WMeYJKPipRtph1EjYzUUtyPeLs8FMqnrQHiOMzlnHz8wErSOgzFLY - dEigtN9GPbkgSVkTm7wGT4yuyEwYWnRs1AiLzAE+GxtoDNSQfUezIRpsh3piuIy0L+1+UEbti6wo - 91m1zxcDYjU/s7cdY4x9x9/k7OAvydg6O0Vj264vi2MNFYhjW2L+1NjIQV8jRhb0Hi74CPzkYAxK - awjNQ9Ja1oZ2GRw/KVXHBDDGEiwGvv3eBGP6mfGi5Am+3b9SJndWxx7gvfIEhubkKTEm8REcaI26 - IWt1I0HHJZIL885Hhx/KBt8sZ9VEQ9NuHIK3RpkLP9+H49j31tEqaTIqDAO4rzu4Y+w2XyC6DyWx - IYXTYfEOewh6doF7sg7XWgiHER1QiHD+K7uj0Yd78966AR7/Vy7HvDT83H+e+WqVnE0KZHkKPDzn - ZMdmXPd0wci4mKhaeWj18nhCPJEkSJnNURfFy//46vUk2RLkFbtHYTZLv1f/+1aKZ/gz2rSvn5jJ - EugVcZnMCh43r39Agg4IJvrb7vYXAAD//wMA5gltyMgEAAA= - headers: - CF-RAY: - - 9472cad0c942159f-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:19 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=QIXfljmZxZub9UwwuM6OT1N99na9ASw8TDtcrRd6Z8Q-1748488159-1.0.1.1-zbWSSmIJdFD_aTFzj0JP0WZWpbLM0wEDzYNyALtNsO07NwGG62DBhYk_IRdRHZ9Wf2ooX6MZUcYruGgEgAnGeXE7ply4Hwvl3PEANnp5GJk; - path=/; expires=Thu, 29-May-25 03:39:19 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=F7Q0gtFcXfGctocXEvQSjRs1S7gyxSThlxKpcdlXKG8-1748488159693-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "558" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999959" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_9593682049a6bc80e64872aee04f3bdf - status: - code: 200 - message: OK - - request: - body: '{"input":"What''s 12 + 12?","model":"gpt-4o-mini","text":{"format":{"type":"json_schema","strict":true,"name":"NumberAnswer","schema":{"properties":{"value":{"title":"Value","type":"integer"},"reasoning":{"title":"Reasoning","type":"string"}},"required":["value","reasoning"],"title":"NumberAnswer","type":"object","additionalProperties":false}}}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "346" - content-type: - - application/json - cookie: - - _cfuvid=tPn8I_CbxQE_7n7eR0tfI8z79gYpGXIT.dYXd5DQUl4-1748488158744-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.70.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.70.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3RVTW/bMAy951cIOjeD89XYue0PDMMOuyyDQUu0o1aWPInqVhT574PlRJHb9BLH - fCJFPj7SbwvGuJL8wLhDP9SPZdk0Qu5W27YsV1VViVaIzap4XFdQ4aotNgJhv92VsIMNoOAPYwDb - PKGgaxBrPE524RAIZQ0jttrvNlVZbooqYp6Agh99hO0HjYRycmpAPHfOBjNm1YL2GM3onHX8wEzQ - OhqUuTrWEgmU9nPUkwuClDUzew//ahtoCFSTfcaPIFmrawF6Hq63EvWYbDfQcmuXvTJquS7W22Wx - X67KCw0xLj+wXwvGGHuLv4nf3neJ3rIsi0jvXm6q3bp63AoJj+V9emMMeh0wRkHvocMb8BmPERTW - EJpbSnlas7BXSvAfJe94AIyxBFcaf/2egdp2g7PNHSQGOjD+duQvoAMe+WG9fThyh+CtUaY78sOR - f5VSmY6t1gyMHB+dekHPXm1g6y1rUEDwGF+F7RtlkNEJGf21LAb1jGyHdEL35cjPPN1/vvxLKXFn - dSwTvFeewNB0eDwYD/EBHGiNet5+cmES3+DwRdng66u+69jTJI/B2X6gWoA4Yf2MrzmWSuaHC/cc - 29Y6yg6NfQx9D+7quWDsPI0JtEivtZJoSLUKZyPg0b0ogTVNdi6xhaCnDnJP1mFeBGE/oAMK0bz6 - UlyssVOXzFrreri9Zwp58tbUXpywh5u+JHrh1DDKY1YNY9xAH/2+hb5B99X4v+gy1U6BDpkaRxIH - dKTQz+yMTRJ6ZxxTUzS19WfEH96hl8SVIezQ8Qw9z7T6sUEfb/iRznxyiyc3ovklizvXcYd/gnIo - ZyOZSvwkr2TNhuyW212G89metnOGgJRq7Bno7znncdku3uUcK4vLfRRSGptJndO0nKwS03gFsjwB - t7XAyQ51tiyKZBxyJbpgBFy0xKXy0OjrRyHEpZdkqsxsge+qh4/27KuQxBwHVN4ci0VWK3//XViX - 94B7cVOrPgtNlkDfwHKfKAx+PtM9EkigOBvnxfk/AAAA//8DADJDGZWhBwAA - headers: - CF-RAY: - - 967f53d37fb9ebeb-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 31 Jul 2025 18:58:30 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=MfH4U1GWQf0HgvfGCN2oeZz30rG272lA840H0ocITl4-1753988310-1.0.1.1-_2MfZykpsYaiBMLuP6hYF4d3UgjFvRm39iz6QLyl7KiQpHUQQy5kISxKt1Cz8a2u5kNTnEry7BCShyyz2tC1GV4R_AKK6yKQRPkdnSHFZEs; - path=/; expires=Thu, 31-Jul-25 19:28:30 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=wq6YLS4G9pN7FGqxeyEbqKUCae8GWtIXy1WxAM3P2oQ-1753988310124-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "1051" - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-decorator-operation: - - tasksapi.openai.svc.cluster.local:8081/* - x-envoy-upstream-service-time: - - "1058" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999922" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_08be9de3dcbf180a2e859fb2097486c5 - status: - code: 200 - message: OK - - request: - body: '{"input":"What''s 12 + 12?","model":"gpt-4o-mini","text":{"format":{"type":"json_schema","strict":true,"name":"NumberAnswer","schema":{"properties":{"value":{"title":"Value","type":"integer"},"reasoning":{"title":"Reasoning","type":"string"}},"required":["value","reasoning"],"title":"NumberAnswer","type":"object","additionalProperties":false}}}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "346" - content-type: - - application/json - cookie: - - _cfuvid=F7Q0gtFcXfGctocXEvQSjRs1S7gyxSThlxKpcdlXKG8-1748488159693-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.70.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.70.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//dFVNj+IwDL3zK6KcYUVLgZbb/oHVag97GVaVm7olM2nSSZz50Ij/vmoK - JZ1hLqj42Y7z/Ox8LBjjsuYHxi26vtzleVU1G9xXRZ4nBVTNdpcVmyIrcIfFZrdOiiIRu7xep1vc - QMWXQwJTPaKgaxKjHY52YREI6xIGLNlvN0WeF+kuYI6AvBtihOl6hYT1GFSBeGqt8XqoqgHlMJjR - WmP5gWmvVDBIfQ0saySQys1RR9YLkkbP7B28lcZT76kk84RfQTJGlQLUPF1nalRDsW1Pq8ysOqnl - Kl2n2Wq9XyX5hYaQlx/Yw4Ixxj7C78Rv59oLvdk63dbZQG++38J+t2kSkdXbTZbcpTfkoPceQxZ0 - Dlq8Ad/xGEBhNKG+lRSXNUt7pQTfaIoODqC1IbjS+PBvBirT9tZUd5CQ6MD4x5G/gPJ45Ic0Wx65 - RXBGS90e+eHIk5T1yjuWpAyfPSjH0oxVKMA7ZK8n1OzdeCZMV0mNjE7I6NUw7bsKrVsGECwyqGup - 2wGXloXjHCPTIp3Q/jjyM58qO1++pmK5NSoQAM5JR6BpdB4cgxPvwYJSqObCIOtHWfYWX6Txrrwq - vwzdnoTTW9P1VAoQJyyf8D3GJjL44dIVjk1jLEVOQ4d914G9Ri4YO48DBA3Seylr1CQbibPhcGhf - pMCSRjuvsQGvxt5yR8ZifAnCrkcL5IM5+bG+WEMPL5U1xnZw+x9p59EZXTpxwg5uyqvRCSv7QTiz - 2zDGNXQh7lfo40/tXtFGeh4THSKdDiT2aEmim9kZG8X1yTiUJmls69+ALz+hl8KlJmzR8gg9z1T8 - tUFfT/gz+XxziiM7oPEhizvHcYvPXlqsZ8M6XfGbuiZrNH632u4yHE/9uLcjZBiloWegfsechzW8 - +FRzuFlY+4OQprEZ1TlOy8lIMY6XJ8Mn4LYwOJm+jNbIejL2sRKt1wIuWuK1dFCp63PhwzqcZCr1 - bLVvi+VXe/ReTGIOA1rfAteL6K7884uxSe8B9/JOrfouNRkCdQOLZKLQu/lMd0hQA4XZOC/O/wEA - AP//AwBWTkAJuwcAAA== - headers: - CF-RAY: - - 967f62e628f6df9a-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 31 Jul 2025 19:08:51 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=7K88wLiwUejSYSpUrbbQTTUHXJchrH_l2kI9fgnxcXs-1753988931-1.0.1.1-0GVYMjJh__VuGclT3740O0X6qzhwEkxZ73NnDU0yto26W19LY229WoGh8h.VuBySdJvEqCoVFc72gOID6NOkvrw6Lw.BT.hvHaBAQIcmhQI; - path=/; expires=Thu, 31-Jul-25 19:38:51 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=VbWwIvwEnDviFllW86zIw2EM2IHt6E3y9YGf8UmVJhc-1753988931644-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "5122" - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-decorator-operation: - - tasksapi.openai.svc.cluster.local:8081/* - x-envoy-upstream-service-time: - - "5181" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999922" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_e9aad4c6852e5f8a6c7a20d0333cb94f - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_responses_not_given_filtering.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_responses_not_given_filtering.yaml deleted file mode 100644 index 0db16cee8..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_responses_not_given_filtering.yaml +++ /dev/null @@ -1,222 +0,0 @@ -interactions: - - request: - body: - '{"input":"What''s 12 + 12?","model":"gpt-4o-mini","instructions":"Just - the number please","temperature":0.5}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "107" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3RTW27jMAz8zykEfTeFrdixkyPsFYqFwUh0oq0sGRJVtChy94XlR+zd9MewhuRo - NCS/d4xxrfiZcY+hb471oZJtWxanOqvzUw3tsbyU2aWSQrUqLzNxUPmpEjliJSpx4i8Dgbv8QUkz - ibMBR1x6BELVwBDLq6Iu6jqv8xQLBBTDUCNd1xskVGPRBeT71btoB1UtmIAJRu+d52dmozEJ0HYu - bBQSaBO20UA+StLOpkt+xUCMbshs7C7oWW8QZpkdfDYuUh+pIfeOdkPUOYVmYLj2tC/cvtNW70Um - in1W7fN6MiBV8zN72zHG2Hf6Ls524boYKxXUg7GnUogcqmNel1gccvXU2MRBXz0mFgwBrvgI/ORg - CkpnCe1D0lrWhnZ+OH7SUp0SwFpHMBv49nsTTOlnxkXBF/g+/S2Z3DuT7oAQdCCwNCYPiSmJ9+DB - GDQNOWcaCSY1kXwce957/NAuhmYeqyYZuvTGIwRntb3y8/Q4jm3rPK2SBqNi14H/msAdY/dxAtF/ - aIkNaRwGiytsIZrRBR7IeVxrIex69EAxwdlrOaHJh+ny1vkOHueVyylvefx4//jmm9NyNCmS40vg - 4Tkn1zf9sECv2Xj20crUmKRaB7iYeXliGpFFkLaboRbi5X98tT2LbAnyhupRmI3Sp+p/d0U8w5/R - Lv36iZkcgVkRF4tZMeBm+zskUEAw0N93978AAAD//wMAT6oOaMgEAAA= - headers: - CF-RAY: - - 9472cb5c9a194396-EWR - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 29 May 2025 03:09:41 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=hky4PzuwZI0YHDeLe3UyB0OkeHxklBi6UeyYqib7OLc-1748488181-1.0.1.1-.8FXGe8MaMHhsboFbj_N_g2.OEI.83OjQL9De3dC2FClH.g2WHfq1pgLdORTu5xsjVMjtC8bkH8EggkP45z2HxbiKAeTLML8I1CsyTnv30s; - path=/; expires=Thu, 29-May-25 03:39:41 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=gQ7ZU3ok.ksIvbOQBFTWcOCVWLNwRjYQ.X9DzjPR8XU-1748488181926-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "603" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999959" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_972488ab47f149e1d2791593ecf33dc9 - status: - code: 200 - message: OK - - request: - body: '{"input":"What''s 12 + 12?","model":"gpt-4o-mini","temperature":0.7,"text":{"format":{"type":"json_schema","strict":true,"name":"NumberAnswer","schema":{"properties":{"value":{"title":"Value","type":"integer"},"reasoning":{"title":"Reasoning","type":"string"}},"required":["value","reasoning"],"title":"NumberAnswer","type":"object","additionalProperties":false}}}}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "364" - content-type: - - application/json - cookie: - - _cfuvid=gQ7ZU3ok.ksIvbOQBFTWcOCVWLNwRjYQ.X9DzjPR8XU-1748488181926-0.0.1.1-604800000 - host: - - api.openai.com - user-agent: - - OpenAI/Python 1.70.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - "false" - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.70.0 - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.11.10 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: !!binary | - H4sIAAAAAAAAA3RUTW/bMAy951cIOjdF7KSJndv+wDDssEszGLREu1plyZOorkWR/z5Ydhy5TS/5 - 4CMp8vGR7yvGuJL8yLhD31f7oqjlpjyU2U4UWQmw39eZzEUti4ciO2SbTByKLR6Kcg9NsUV+NySw - 9R8UdElijZ/swiEQygoGLDs8bMtyu90fIuYJKPghRtiu10gox6AaxHPrbDBDVQ1oj9GMzlnHj8wE - raNBmUtgJZFAab9EPbkgSFmzsHfwWtlAfaCK7DN+BslaXQnQy3SdlaiHYtue1ju77pRR63yT79ab - wzorJhpiXn5kjyvGGHuPnzO/nW8v9JbbfLsb6C2xyMW+yPblBgU09U16Yw566zFmQe+hTYCveIyg - sIbQXEtKy1qkvVCCrzRHRwcwxhJcaHz8vQC1bXtn6xtITHRk/P3EX0AHPPFjvrs7cYfgrVGmPfHj - iX+TUpmWZTkDI4cvsi3SEzrWqhf07M0Glu/uT/zM5+Tn6df8HndWxx7Ae+UJDI3Og2N04j040Br1 - crbkwqis3uGLssFXF/FWcWDz7Htnu54qAeIJq2d8S7G5H36ciOXYNNZR4jQMKXQduEvkirHzuAPQ - IL1VSqIh1Shc6Nuje1ECKxrtXGIDQY/j4Z6sw7QJwq5HBxSieXN/mKxxDFNljXUdXP8n4//jram8 - eMIOruKR6IVT/TD7RTeMcQNdjPseuhrdN+P/oUskOSY6JlIbSOzRkUK/sDM26uODcShN0TjWXxG/ - +4BOhStD2KLjCXpeCPHzgD6/8HP2+eIVT25A00dWN57jDv8G5VAu9m1u8Yu6ZmuyQdfabjKcLu54 - ehMEpFTDzED/SDmPl3T1oebYWbzcg5DmtRnVOW7Lk1ViXK9Als/Adec52b5KLsFmNvbD1b+f/rtg - BExa4lJ5qPXl4od40WaZKrO4zg/l3Wd7cvJnMccFldfAzSrplX88+nl+C7iVdx7VV6nJEugrWGQz - hcEvd7pDAgkUd+O8Ov8HAAD//wMABM88Qn4HAAA= - headers: - CF-RAY: - - 967fcf5269152516-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 31 Jul 2025 20:22:49 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=uJ3w5YBR6dmponclee_NmLgLrQLitkcZawa86jfPVHQ-1753993369-1.0.1.1-qr08wm0SZCBKHwJXFxjlhfIfDunsUFj0asTnOdlR1LSzjNFMtpKcm.yfqL5oKaGcQrbYi78yn7bTkCuePlS6z1.Gxv6jhTr231yTHyfmdTo; - path=/; expires=Thu, 31-Jul-25 20:52:49 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=xVb3Tn9r8L1_4xseZvaOZTdOzG0asai4Yw5SeZpVZCE-1753993369650-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "2106" - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-decorator-operation: - - tasksapi.openai.svc.cluster.local:8081/* - x-envoy-upstream-service-time: - - "2191" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999920" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_dc8741d95c10adb5e2f58f8d0d586737 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openai_streaming_with_break.yaml b/py/src/braintrust/wrappers/cassettes/test_openai_streaming_with_break.yaml deleted file mode 100644 index 5ad3cecc8..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openai_streaming_with_break.yaml +++ /dev/null @@ -1,136 +0,0 @@ -interactions: - - request: - body: '{"messages":[{"role":"user","content":"What''s 12 + 12?"}],"model":"gpt-4o-mini","stream":true}' - headers: - accept: - - application/json - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - "94" - content-type: - - application/json - host: - - api.openai.com - user-agent: - - AsyncOpenAI/Python 1.82.0 - x-stainless-arch: - - arm64 - x-stainless-async: - - async:asyncio - x-stainless-lang: - - python - x-stainless-os: - - MacOS - x-stainless-package-version: - - 1.82.0 - x-stainless-raw-response: - - "true" - x-stainless-read-timeout: - - "600" - x-stainless-retry-count: - - "0" - x-stainless-runtime: - - CPython - x-stainless-runtime-version: - - 3.13.3 - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: - 'data: {"id":"chatcmpl-BcNw7ndvnSncW8DxhS1idxONpgqxU","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw7ndvnSncW8DxhS1idxONpgqxU","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw7ndvnSncW8DxhS1idxONpgqxU","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":" - +"},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw7ndvnSncW8DxhS1idxONpgqxU","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw7ndvnSncW8DxhS1idxONpgqxU","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":"12"},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw7ndvnSncW8DxhS1idxONpgqxU","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":" - equals"},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw7ndvnSncW8DxhS1idxONpgqxU","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw7ndvnSncW8DxhS1idxONpgqxU","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":"24"},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw7ndvnSncW8DxhS1idxONpgqxU","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}]} - - - data: {"id":"chatcmpl-BcNw7ndvnSncW8DxhS1idxONpgqxU","object":"chat.completion.chunk","created":1748488175,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}]} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9472cb393cde1492-EWR - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Thu, 29 May 2025 03:09:36 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=h1vL7TCxyZQWYLiVATU5khuFWAfl7e7DD1hCduxzE8U-1748488176-1.0.1.1-sJaNE8XFsJQdiSrAjR90nA7rr9yBOdYJcgr.dqonlOei8.cltJKLgEqEf98WWTEAjzZY_3NkDCTKZ6BAoprnwscA9Xg3RSagZKs2syOsiqc; - path=/; expires=Thu, 29-May-25 03:39:36 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=SNSxlGXUc7grIzRg7NgjFZuLpm8RWoGQ8CcpSyF99Wo-1748488176143-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - "462" - openai-version: - - "2020-10-01" - strict-transport-security: - - max-age=31536000; includeSubDomains; preload - x-envoy-upstream-service-time: - - "481" - x-ratelimit-limit-requests: - - "30000" - x-ratelimit-limit-tokens: - - "150000000" - x-ratelimit-remaining-requests: - - "29999" - x-ratelimit-remaining-tokens: - - "149999993" - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_574eb3b1e3585ef7a72808f9c33a6bcb - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openrouter_chat_completion_async.yaml b/py/src/braintrust/wrappers/cassettes/test_openrouter_chat_completion_async.yaml deleted file mode 100644 index d0514a091..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openrouter_chat_completion_async.yaml +++ /dev/null @@ -1,82 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 3+3? Reply with just the - number."}],"model":"openai/gpt-4o-mini","max_tokens":10}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '128' - Content-Type: - - application/json - Host: - - openrouter.ai - User-Agent: - - AsyncOpenAI/Python 2.9.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.9.0 - X-Stainless-Raw-Response: - - 'true' - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.11.13 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://openrouter.ai/api/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//dFHBbpwwFPyXOZsUwobd+tZDK0WqlF5yqKoKeeEBrzG262eiRiv+vaJk - N0Ta+jhvPDNv3gncQqMnlxX7anfY78tDmd097h4ew5fhW7wv3dfDnfz+/hkKIfpnbilC4yGQ+3QP - hdG3ZKHhAznDH/qQsp3PRnYMBX/8RU2CRjOYdNP4MVhK7B0UmkgmUQv9ZqvQDJ4bEugfJ1jfh+iP - Au0maxU6dixDHcmId9CQ5AMUnEn8TPV/puxa+gOdK4wkYnqCPiF6S9AwIizJuLSk8S6RW5JWUIjU - TWLs2XkVZdevwDz/VJAXSTQutj3FEPnf3y7URdGV+e3HrjpCYTo7hujHkOrkn8gJ9G2+OJ7LuMCF - QvLJ2DdesfAkQec3+fLKSoGlPr74J+jOWCH1XrtuKRm2spg2phmovYjlCmZq2W+B5ZobYF7ttiJT - kBTJjDW7jiK5huo10VrNlfFrnve51XWhcwXySq8o289XutkmulxjuwiPpqfNIvP8FwAA//8DADfo - HoPZAgAA - headers: - Access-Control-Allow-Origin: - - '*' - CF-RAY: - - 9a8dca6118a01c37-PDX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 04 Dec 2025 19:43:04 GMT - Permissions-Policy: - - payment=(self "https://checkout.stripe.com" "https://connect-js.stripe.com" - "https://js.stripe.com" "https://*.js.stripe.com" "https://hooks.stripe.com") - Referrer-Policy: - - no-referrer, strict-origin-when-cross-origin - Server: - - cloudflare - Transfer-Encoding: - - chunked - Vary: - - Accept-Encoding - X-Content-Type-Options: - - nosniff - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openrouter_chat_completion_sync.yaml b/py/src/braintrust/wrappers/cassettes/test_openrouter_chat_completion_sync.yaml deleted file mode 100644 index faae3a000..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openrouter_chat_completion_sync.yaml +++ /dev/null @@ -1,82 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 2+2? Reply with just the - number."}],"model":"openai/gpt-4o-mini","max_tokens":10}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '128' - Content-Type: - - application/json - Host: - - openrouter.ai - User-Agent: - - OpenAI/Python 2.9.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - 'false' - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.9.0 - X-Stainless-Raw-Response: - - 'true' - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.11.13 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://openrouter.ai/api/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA+JSgAEuAAAAAP//dFHRauMwEPyXeZZbOw5JqrdrnwqBwnFPdxxGsdeOrrJWaOXS - Evzvh+smdSHV4+xoZnb2BNtAoyOfFdvNerfdlrsy+x327ePP/f1q91Cu1mF/X7hfUAiRX2xDERpP - gfyPRyj03JCDBgfyxt52IWVrznrrLRT48I/qBI36aNJNzX1wlCx7KNSRTKIG+tNWoT6yrUmg/5zg - uAuRDwLtB+cUWuutHKtIRthDQxIHKHiT7AtV30ytb+gVOlfoScR0BH1CZEfQMCJWkvFpSsM+kZ+S - rqEQqR3EuLPzLGp9NwPj+FdB3iRRP9l2FEO073/bUBVFW+aru3ZzgMJwdgyR+5CqxM/kBXqVT47n - Mi5woZA4GffJKyaeJOj8Jp9euVGwUh3e+Bm6NU5IfdWuGkrGOplMa1MfqbmI5QpmaCwvgemaC2Cc - 7ZYiQ5AUyfSV9S1F8jVVc6K5mivjjzxfc6vrQucK5IO+oWw7XulmmehyjeUitjcdLRYZx/8AAAD/ - /wMAr5knr+QCAAA= - headers: - Access-Control-Allow-Origin: - - '*' - CF-RAY: - - 9a8dca5cbc33e8e9-PDX - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Thu, 04 Dec 2025 19:43:03 GMT - Permissions-Policy: - - payment=(self "https://checkout.stripe.com" "https://connect-js.stripe.com" - "https://js.stripe.com" "https://*.js.stripe.com" "https://hooks.stripe.com") - Referrer-Policy: - - no-referrer, strict-origin-when-cross-origin - Server: - - cloudflare - Transfer-Encoding: - - chunked - Vary: - - Accept-Encoding - X-Content-Type-Options: - - nosniff - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_openrouter_streaming_sync.yaml b/py/src/braintrust/wrappers/cassettes/test_openrouter_streaming_sync.yaml deleted file mode 100644 index a2dd4a2f4..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_openrouter_streaming_sync.yaml +++ /dev/null @@ -1,89 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 5+5? Reply with just the - number."}],"model":"openai/gpt-4o-mini","max_tokens":10,"stream":true}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '142' - Content-Type: - - application/json - Host: - - openrouter.ai - User-Agent: - - OpenAI/Python 2.9.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - 'false' - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.9.0 - X-Stainless-Raw-Response: - - 'true' - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.11.13 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://openrouter.ai/api/v1/chat/completions - response: - body: - string: 'data: {"id":"gen-1764877384-kItWc9W8XjV58kFEXXmd","provider":"OpenAI","model":"openai/gpt-4o-mini","object":"chat.completion.chunk","created":1764877384,"choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null,"native_finish_reason":null,"logprobs":null}],"system_fingerprint":"fp_11f3029f6b"} - - - data: {"id":"gen-1764877384-kItWc9W8XjV58kFEXXmd","provider":"OpenAI","model":"openai/gpt-4o-mini","object":"chat.completion.chunk","created":1764877384,"choices":[{"index":0,"delta":{"role":"assistant","content":"10"},"finish_reason":null,"native_finish_reason":null,"logprobs":null}],"system_fingerprint":"fp_11f3029f6b"} - - - data: {"id":"gen-1764877384-kItWc9W8XjV58kFEXXmd","provider":"OpenAI","model":"openai/gpt-4o-mini","object":"chat.completion.chunk","created":1764877384,"choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":"stop","native_finish_reason":"stop","logprobs":null}],"system_fingerprint":"fp_11f3029f6b"} - - - data: {"id":"gen-1764877384-kItWc9W8XjV58kFEXXmd","provider":"OpenAI","model":"openai/gpt-4o-mini","object":"chat.completion.chunk","created":1764877384,"choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null,"native_finish_reason":null,"logprobs":null}],"usage":{"prompt_tokens":20,"completion_tokens":1,"total_tokens":21,"cost":0.0000036,"is_byok":false,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0,"video_tokens":0},"cost_details":{"upstream_inference_cost":null,"upstream_inference_prompt_cost":0.000003,"upstream_inference_completions_cost":6e-7},"completion_tokens_details":{"reasoning_tokens":0,"image_tokens":0}}} - - - data: [DONE] - - - ' - headers: - Access-Control-Allow-Origin: - - '*' - CF-RAY: - - 9a8dca64e90e28b9-PDX - Cache-Control: - - no-cache - Connection: - - keep-alive - Content-Type: - - text/event-stream - Date: - - Thu, 04 Dec 2025 19:43:04 GMT - Permissions-Policy: - - payment=(self "https://checkout.stripe.com" "https://connect-js.stripe.com" - "https://js.stripe.com" "https://*.js.stripe.com" "https://hooks.stripe.com") - Referrer-Policy: - - no-referrer, strict-origin-when-cross-origin - Server: - - cloudflare - Transfer-Encoding: - - chunked - Vary: - - Accept-Encoding - X-Content-Type-Options: - - nosniff - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_patch_litellm_aresponses.yaml b/py/src/braintrust/wrappers/cassettes/test_patch_litellm_aresponses.yaml deleted file mode 100644 index e9d155453..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_patch_litellm_aresponses.yaml +++ /dev/null @@ -1,98 +0,0 @@ -interactions: -- request: - body: '{"model": "gpt-4o-mini", "input": "What''s 12 + 12?", "instructions": "Just - the number please"}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate, zstd - connection: - - keep-alive - content-length: - - '94' - content-type: - - application/json - host: - - api.openai.com - user-agent: - - litellm/1.80.11 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: "{\n \"id\": \"resp_026bca77278090c400695da9f2336c8197a28a89d2eeea3847\"\ - ,\n \"object\": \"response\",\n \"created_at\": 1767746034,\n \"status\"\ - : \"completed\",\n \"background\": false,\n \"billing\": {\n \"payer\"\ - : \"developer\"\n },\n \"completed_at\": 1767746036,\n \"error\": null,\n\ - \ \"incomplete_details\": null,\n \"instructions\": \"Just the number please\"\ - ,\n \"max_output_tokens\": null,\n \"max_tool_calls\": null,\n \"model\"\ - : \"gpt-4o-mini-2024-07-18\",\n \"output\": [\n {\n \"id\": \"msg_026bca77278090c400695da9f40c608197ab0013c567aa9cff\"\ - ,\n \"type\": \"message\",\n \"status\": \"completed\",\n \"\ - content\": [\n {\n \"type\": \"output_text\",\n \"\ - annotations\": [],\n \"logprobs\": [],\n \"text\": \"24\"\ - \n }\n ],\n \"role\": \"assistant\"\n }\n ],\n \"parallel_tool_calls\"\ - : true,\n \"previous_response_id\": null,\n \"prompt_cache_key\": null,\n\ - \ \"prompt_cache_retention\": null,\n \"reasoning\": {\n \"effort\":\ - \ null,\n \"summary\": null\n },\n \"safety_identifier\": null,\n \"\ - service_tier\": \"default\",\n \"store\": true,\n \"temperature\": 1.0,\n\ - \ \"text\": {\n \"format\": {\n \"type\": \"text\"\n },\n \"\ - verbosity\": \"medium\"\n },\n \"tool_choice\": \"auto\",\n \"tools\":\ - \ [],\n \"top_logprobs\": 0,\n \"top_p\": 1.0,\n \"truncation\": \"disabled\"\ - ,\n \"usage\": {\n \"input_tokens\": 22,\n \"input_tokens_details\"\ - : {\n \"cached_tokens\": 0\n },\n \"output_tokens\": 2,\n \"\ - output_tokens_details\": {\n \"reasoning_tokens\": 0\n },\n \"\ - total_tokens\": 24\n },\n \"user\": null,\n \"metadata\": {}\n}" - headers: - CF-RAY: - - 9b9f5dc6cc8f88dc-PDX - Connection: - - keep-alive - Content-Type: - - application/json - Date: - - Wed, 07 Jan 2026 00:33:56 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=_y7fCdc9uilcXWWehABBb.Mld5QbTO5KpPG2Z8vNrVk-1767746036-1.0.1.1-SVJnu7TvCHcIGFk47ciU4dkHSA5T2btNr1nGsKdQHCN4ddCrnwJk5s1oZgJKwllLU42AQ86e6IWnerYag8EoUlFmM8hBMTFImeYCLKwAHW4; - path=/; expires=Wed, 07-Jan-26 01:03:56 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=tf9PFl6ALaHHYzNa_b0aZF9a3TVLXWEeHcFjWXTQvvc-1767746036217-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - user-bkcsfvrp2vh67rqzpgtsbnle - openai-processing-ms: - - '1992' - openai-project: - - proj_IG1Ou5SIiy81s3W66WZ5dtN6 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '1995' - x-ratelimit-limit-requests: - - '5000' - x-ratelimit-limit-tokens: - - '4000000' - x-ratelimit-remaining-requests: - - '4999' - x-ratelimit-remaining-tokens: - - '3999959' - x-ratelimit-reset-requests: - - 12ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_4d0d66110b8b40c8bbffdaa0446e1ba2 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_patch_litellm_responses.yaml b/py/src/braintrust/wrappers/cassettes/test_patch_litellm_responses.yaml deleted file mode 100644 index 3d82f70e0..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_patch_litellm_responses.yaml +++ /dev/null @@ -1,98 +0,0 @@ -interactions: -- request: - body: '{"model": "gpt-4o-mini", "input": "What''s 12 + 12?", "instructions": "Just - the number please"}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate, zstd - Connection: - - keep-alive - Content-Length: - - '94' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - litellm/1.80.11 - method: POST - uri: https://api.openai.com/v1/responses - response: - body: - string: "{\n \"id\": \"resp_0c1d868d4b13f47b00695da9f0716c8195aa610e236b2467e4\"\ - ,\n \"object\": \"response\",\n \"created_at\": 1767746032,\n \"status\"\ - : \"completed\",\n \"background\": false,\n \"billing\": {\n \"payer\"\ - : \"developer\"\n },\n \"completed_at\": 1767746033,\n \"error\": null,\n\ - \ \"incomplete_details\": null,\n \"instructions\": \"Just the number please\"\ - ,\n \"max_output_tokens\": null,\n \"max_tool_calls\": null,\n \"model\"\ - : \"gpt-4o-mini-2024-07-18\",\n \"output\": [\n {\n \"id\": \"msg_0c1d868d4b13f47b00695da9f15e50819583c61441cd08b841\"\ - ,\n \"type\": \"message\",\n \"status\": \"completed\",\n \"\ - content\": [\n {\n \"type\": \"output_text\",\n \"\ - annotations\": [],\n \"logprobs\": [],\n \"text\": \"24\"\ - \n }\n ],\n \"role\": \"assistant\"\n }\n ],\n \"parallel_tool_calls\"\ - : true,\n \"previous_response_id\": null,\n \"prompt_cache_key\": null,\n\ - \ \"prompt_cache_retention\": null,\n \"reasoning\": {\n \"effort\":\ - \ null,\n \"summary\": null\n },\n \"safety_identifier\": null,\n \"\ - service_tier\": \"default\",\n \"store\": true,\n \"temperature\": 1.0,\n\ - \ \"text\": {\n \"format\": {\n \"type\": \"text\"\n },\n \"\ - verbosity\": \"medium\"\n },\n \"tool_choice\": \"auto\",\n \"tools\":\ - \ [],\n \"top_logprobs\": 0,\n \"top_p\": 1.0,\n \"truncation\": \"disabled\"\ - ,\n \"usage\": {\n \"input_tokens\": 22,\n \"input_tokens_details\"\ - : {\n \"cached_tokens\": 0\n },\n \"output_tokens\": 2,\n \"\ - output_tokens_details\": {\n \"reasoning_tokens\": 0\n },\n \"\ - total_tokens\": 24\n },\n \"user\": null,\n \"metadata\": {}\n}" - headers: - CF-RAY: - - 9b9f5dbabdb9121f-PDX - Connection: - - keep-alive - Content-Type: - - application/json - Date: - - Wed, 07 Jan 2026 00:33:53 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=gzLtdrnV2HbuCKHt_I10NyUVXM.pTd0qboetSCQmg8Q-1767746033-1.0.1.1-wJ7_10.60MJUt53.SqOAx9RxVaTenNI_42WRp5n2mCHtM5URbzqzuY2hNWmUfRmtXegKRWGZ0cd.KPa2MV6IOuapltXXsNLnaqUIpxl3zEU; - path=/; expires=Wed, 07-Jan-26 01:03:53 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=H.FSS.Wxa0H38XUwRHp4Gtf36NbqyBKQwH7NV1dCs8o-1767746033539-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - X-Content-Type-Options: - - nosniff - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - user-bkcsfvrp2vh67rqzpgtsbnle - openai-processing-ms: - - '1065' - openai-project: - - proj_IG1Ou5SIiy81s3W66WZ5dtN6 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '1068' - x-ratelimit-limit-requests: - - '5000' - x-ratelimit-limit-tokens: - - '4000000' - x-ratelimit-remaining-requests: - - '4999' - x-ratelimit-remaining-tokens: - - '3999959' - x-ratelimit-reset-requests: - - 12ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_4f3f01e7d8094ab08cb403645a06c542 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_pydantic_wrapped_completion.yaml b/py/src/braintrust/wrappers/cassettes/test_pydantic_wrapped_completion.yaml deleted file mode 100644 index 9bdfe3fde..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_pydantic_wrapped_completion.yaml +++ /dev/null @@ -1,216 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is the capital of Italy?"}],"model":"gpt-3.5-turbo","stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '111' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.42.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJJTwMxDIXv8ysin1tEp6y9IhUBJ5CQEAiN0sSdBjJxSDys6n9HSZcZ - NolLDvn8nPccfxRCgNEwEaAWklXj7fDkrXy37e3FzdNUj8PltL0u9fnL2bMLp1czGCQFzR5Q8Ua1 - o6jxFtmQW2EVUDKmrqPDg6O98rAsjzNoSKNNstrzcLyzP+Q2zGi4Oyr318oFGYURJuKuEEKIj3wm - j07jK0zE7mBz02CMskaYbIuEgEA23YCM0USWjmHQQUWO0WXbV9RgHwWct1Ema661tgekc8QyRcum - 7tdkubVhqfaBZvGbFObGmbioAspILj0ZmTxkuiyEuM9x2y8JwAdqPFdMj5ifG+2t2kE34A6Wa8bE - 0vY0B4NfmlUaWRobe9MCJdUCdafsRitbbagHil7kn15+672KbVz9n/YdUAo9o658QG3U17xdWcC0 - fX+VbUecDUPE8GwUVmwwpG/QOJetXe0FxLfI2FRz42oMPpi8HOkbi2XxCQAA//8DAJZH/UkbAwAA - headers: - CF-RAY: - - 9be05484c98f8b02-IAD - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 14 Jan 2026 21:47:09 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=dUHsjFYieT4XukWfUSKpLou_UPpWKtEWImWgeyrhn24-1768427229-1.0.1.1-xNDhdyBdNXPI.2LGVcZBY1eY9.qPXmhcMcu8L6VTmrAK.bG07FI5uriRCbDwayuSUGmS4617jk0obuznieQ.Gocdtq.QioV5.Eas_cCPMHA; - path=/; expires=Wed, 14-Jan-26 22:17:09 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=BFWwlog_u_0qiPjvwentFglhJg5OIkGZAcwlzZ_Zbik-1768427229839-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '625' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '855' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '10000' - x-ratelimit-limit-tokens: - - '50000000' - x-ratelimit-remaining-requests: - - '9999' - x-ratelimit-remaining-tokens: - - '49999990' - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_76f1b4cacd884291917dc8fe8ce3219d - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"role":"user","content":"What is the capital of Italy?"}],"model":"gpt-3.5-turbo","stream":false}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '111' - Content-Type: - - application/json - Cookie: - - __cf_bm=dUHsjFYieT4XukWfUSKpLou_UPpWKtEWImWgeyrhn24-1768427229-1.0.1.1-xNDhdyBdNXPI.2LGVcZBY1eY9.qPXmhcMcu8L6VTmrAK.bG07FI5uriRCbDwayuSUGmS4617jk0obuznieQ.Gocdtq.QioV5.Eas_cCPMHA; - _cfuvid=BFWwlog_u_0qiPjvwentFglhJg5OIkGZAcwlzZ_Zbik-1768427229839-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.42.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Raw-Response: - - 'true' - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jJJbSwMxEIXf91eEeW7Frpdq31REEB9EQQSRJU2m22g2E5NZr/S/S9La - 3XoBX/KQb87knMl8FEKA0TARoOaSVePt8OStfG9O67Px7eXT+c0x3Sp3pM5fDg6vb/ACBklB0wdU - /KXaUtR4i2zILbEKKBlT19F4/2C3HJc72xk0pNEmWe15uLO1N+Q2TGm4PSr3Vso5GYURJuKuEEKI - j3wmj07jK0xE7pNvGoxR1giTdZEQEMimG5AxmsjSMQw6qMgxumz7ihrso4CzNspkzbXW9oB0jlim - aNnU/Yos1jYs1T7QNH6Twsw4E+dVQBnJpScjk4dMF4UQ9zluu5EAfKDGc8X0iPm50e6yHXQD7mC5 - YkwsbU+zP/ilWaWRpbGxNy1QUs1Rd8putLLVhnqg6EX+6eW33svYxtX/ad8BpdAz6soH1EZt5u3K - Aqbt+6tsPeJsGCKGZ6OwYoMhfYPGmWztci8gvkXGppoZV2PwweTlSN9YLIpPAAAA//8DAAOnVNEb - AwAA - headers: - CF-RAY: - - 9be0548aef455824-IAD - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Wed, 14 Jan 2026 21:47:10 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '136' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '160' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '10000' - x-ratelimit-limit-tokens: - - '50000000' - x-ratelimit-remaining-requests: - - '9999' - x-ratelimit-remaining-tokens: - - '49999990' - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_0b987b62cd3b42a9bdcc25051cd93e82 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_pydantic_wrapped_stream.yaml b/py/src/braintrust/wrappers/cassettes/test_pydantic_wrapped_stream.yaml deleted file mode 100644 index 0528601bb..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_pydantic_wrapped_stream.yaml +++ /dev/null @@ -1,233 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is the capital of Italy?"}],"model":"gpt-3.5-turbo","stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '150' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.42.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-Cy2zjeGWSECDn9XoT5ksWPV6r4Zl6","object":"chat.completion.chunk","created":1768427227,"model":"gpt-3.5-turbo-0125","service_tier":"default","system_fingerprint":null,"choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"oVacjk6A"} - - - data: {"id":"chatcmpl-Cy2zjeGWSECDn9XoT5ksWPV6r4Zl6","object":"chat.completion.chunk","created":1768427227,"model":"gpt-3.5-turbo-0125","service_tier":"default","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":"R"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"dHz4wvw99"} - - - data: {"id":"chatcmpl-Cy2zjeGWSECDn9XoT5ksWPV6r4Zl6","object":"chat.completion.chunk","created":1768427227,"model":"gpt-3.5-turbo-0125","service_tier":"default","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":"ome"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"59atS4Q"} - - - data: {"id":"chatcmpl-Cy2zjeGWSECDn9XoT5ksWPV6r4Zl6","object":"chat.completion.chunk","created":1768427227,"model":"gpt-3.5-turbo-0125","service_tier":"default","system_fingerprint":null,"choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"1pt7"} - - - data: {"id":"chatcmpl-Cy2zjeGWSECDn9XoT5ksWPV6r4Zl6","object":"chat.completion.chunk","created":1768427227,"model":"gpt-3.5-turbo-0125","service_tier":"default","system_fingerprint":null,"choices":[],"usage":{"prompt_tokens":14,"completion_tokens":2,"total_tokens":16,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"4u8mxRbAGv"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9be0547d9fcb39c0-IAD - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Wed, 14 Jan 2026 21:47:08 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=SZdqcj8Y3wOlv1eecRE.kmBuTf7CKolY4g5_zu53oNM-1768427228-1.0.1.1-Ttzl0IaT30dDG_zf2YnPJ3F9fUUCbWcAEEijMA.JwosexY6Oc3GsWtuwe0Jr7VzF3FlDknDL7e_yRNpLP7UxCpND8Ec4TIK8aQvmrgcKPeA; - path=/; expires=Wed, 14-Jan-26 22:17:08 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=xP5R5bizk01zn0j0k_DXvbJEaHTeY5VSnZTfdUse7K4-1768427228114-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '140' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '287' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '10000' - x-ratelimit-limit-tokens: - - '50000000' - x-ratelimit-remaining-requests: - - '9999' - x-ratelimit-remaining-tokens: - - '49999990' - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_31e968a8f69d4c309002320be186d165 - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"role":"user","content":"What is the capital of Italy?"}],"model":"gpt-3.5-turbo","stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '150' - Content-Type: - - application/json - Cookie: - - __cf_bm=SZdqcj8Y3wOlv1eecRE.kmBuTf7CKolY4g5_zu53oNM-1768427228-1.0.1.1-Ttzl0IaT30dDG_zf2YnPJ3F9fUUCbWcAEEijMA.JwosexY6Oc3GsWtuwe0Jr7VzF3FlDknDL7e_yRNpLP7UxCpND8Ec4TIK8aQvmrgcKPeA; - _cfuvid=xP5R5bizk01zn0j0k_DXvbJEaHTeY5VSnZTfdUse7K4-1768427228114-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.42.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.15.0 - X-Stainless-Raw-Response: - - 'true' - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-Cy2zkBELI0CyU0dC0e6yFHPIgnzC5","object":"chat.completion.chunk","created":1768427228,"model":"gpt-3.5-turbo-0125","service_tier":"default","system_fingerprint":null,"choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"LX0pQn5d"} - - - data: {"id":"chatcmpl-Cy2zkBELI0CyU0dC0e6yFHPIgnzC5","object":"chat.completion.chunk","created":1768427228,"model":"gpt-3.5-turbo-0125","service_tier":"default","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":"R"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"5TU5flA6m"} - - - data: {"id":"chatcmpl-Cy2zkBELI0CyU0dC0e6yFHPIgnzC5","object":"chat.completion.chunk","created":1768427228,"model":"gpt-3.5-turbo-0125","service_tier":"default","system_fingerprint":null,"choices":[{"index":0,"delta":{"content":"ome"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ck27IwO"} - - - data: {"id":"chatcmpl-Cy2zkBELI0CyU0dC0e6yFHPIgnzC5","object":"chat.completion.chunk","created":1768427228,"model":"gpt-3.5-turbo-0125","service_tier":"default","system_fingerprint":null,"choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"RpPa"} - - - data: {"id":"chatcmpl-Cy2zkBELI0CyU0dC0e6yFHPIgnzC5","object":"chat.completion.chunk","created":1768427228,"model":"gpt-3.5-turbo-0125","service_tier":"default","system_fingerprint":null,"choices":[],"usage":{"prompt_tokens":14,"completion_tokens":2,"total_tokens":16,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"zjoDbbLPDX"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9be05480d8e97ad2-IAD - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Wed, 14 Jan 2026 21:47:08 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '148' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '399' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '10000' - x-ratelimit-limit-tokens: - - '50000000' - x-ratelimit-remaining-requests: - - '9999' - x-ratelimit-remaining-tokens: - - '49999990' - x-ratelimit-reset-requests: - - 6ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_571231e3c4a94961b49b3224ed4dff63 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_stop_sequences.yaml b/py/src/braintrust/wrappers/cassettes/test_stop_sequences.yaml deleted file mode 100644 index 1ebc9066a..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_stop_sequences.yaml +++ /dev/null @@ -1,66 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "Write a short story about a robot."}], - "role": "user"}], "generationConfig": {"maxOutputTokens": 500, "stopSequences": - ["END", "\n\n"]}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '171' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61STW/aQBC98ytGezbIkIBLrwlqIrVKWtwqUtPDggd7lfWO2VmHWoj/3rEJxLTX - +mBb8/HemzezHwCotXaZyXRAVh/hp0QA9t27zZEL6IIkTiEJVtqH99rjs+/9S0nA322T+u5MgOTq - OoIM2eROWDJ4Vjc1B8qMdtGzgqIuS4lua4PBNqAZpKcia7iQcCgQ1oWnEsFrY43LGWjThZcvzavB - HaTovV7jCO6D5Kpg1toCo2PyHEFuaSddoIFpE2Bla4yAZWgn6BvykIkYKEnmH0EqsNr4SPCNAzEG - OKA3Vlp2heEKfSfJU50XnQZunHyEEiqrXRCIu7rUjqHyuBFdXblhYFPWtptePKg9QqCu36O2Yk7T - KsQ1cSN8JcMKRfVI9Uw9nP9/Re+r8GSx9bmkDO2p/HAqUBvjxMVvqJlcW7ZMHx7VOatf88+UV55W - 7TaH41E8m8aTq0kyn8fjZBYngxNxR6lq1jl+waDlWPT5JJQAlFVI6QXdDdXdsXw4cvRO6yI9S97y - gYK2F6lkGv2DyrfCaWz/5HrXKKNra0LTzpcunlLVsydciDrZM+i5+LfE/8Q1Sy7JBm9bOS7qB3o2 - x43kWMqOhpNRPNxYzcUwjscdqvLIFTnG+6ytu90+Gf1wN13wEreBH6/nn1L6ulCDw+APwgER5cUD - AAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Sun, 05 Oct 2025 17:04:15 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=849 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_stream_buffer_pattern_early_return.yaml b/py/src/braintrust/wrappers/cassettes/test_stream_buffer_pattern_early_return.yaml deleted file mode 100644 index cfb4ee992..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_stream_buffer_pattern_early_return.yaml +++ /dev/null @@ -1,158 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 5"}],"model":"gpt-4o-mini","stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '136' - Content-Type: - - application/json - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.36.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.13.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"ZamzQnojU"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"WWiXPzjJq9"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"gJNmPgBuw9"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"yGsyFEVtPi"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"yH3IrPgjP0"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"AK15hNn7i8"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"utG5gHCktq"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"yWv3vIP7ZQ"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"1OeK68RpYQ"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"smaOaaYOkb"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":"4"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"e5P3fw7bpW"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"5EN0R7Zjip"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"VGFZvNLTGn"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"99xgz0I5Lo"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"AZq6oNiZ98"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"D2sJG"} - - - data: {"id":"chatcmpl-CvAjPMGZTwupp42JEMnl5lMVhGL8T","object":"chat.completion.chunk","created":1767741983,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_29330a9688","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":14,"total_tokens":28,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"ZY2sBQm81c"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b9efae1781ed56a-SJC - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Tue, 06 Jan 2026 23:26:23 GMT - Server: - - cloudflare - Set-Cookie: - - __cf_bm=32b.VMplxNQj3L4u_1uDEw4mJbFkX7XgxbW0AIaO4WI-1767741983-1.0.1.1-ngrHAoGsRus82vIYthILxaNTwRrSgq6MT17VyVyBWlwIdCX8AvWXc.5O8aoDYcvvfwwO.wkKSuvDVkjIkcKdBrusGxL1HyXKUH5Xfk3NhOU; - path=/; expires=Tue, 06-Jan-26 23:56:23 GMT; domain=.api.openai.com; HttpOnly; - Secure; SameSite=None - - _cfuvid=beFRqK6f.Kw4Ih5NqMjxVqYpI9KKqCHTmRCh_PSGRiw-1767741983214-0.0.1.1-604800000; - path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '182' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '197' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_34b4a10ec004419fb01e9f6cf1585a92 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_stream_early_break_async_generator.yaml b/py/src/braintrust/wrappers/cassettes/test_stream_early_break_async_generator.yaml deleted file mode 100644 index 9a39ee7f2..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_stream_early_break_async_generator.yaml +++ /dev/null @@ -1,155 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"Count from 1 to 5"}],"model":"gpt-4o-mini","stream":true,"stream_options":{"include_usage":true}}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '136' - Content-Type: - - application/json - Cookie: - - __cf_bm=SnTjRxRlQXUGj3jo4FeKDaKGiTqzcsdhS_LPeF2hwmg-1766265191-1.0.1.1-aN3W.WEa6IjC4znMp0fTYaZOZeW.3xU8ex4fRGFibZ0fuR86Piz9hDDAEvh8Z9ewQ9WHoKwdnsDvPE5KIpoZY4xurXV7VS4TcwfukWZofIk; - _cfuvid=tXOZ7vGE2DBF6L6fDg_veKtSaUVC4UPotJDezWYoYXI-1766265191281-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.37.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.14.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: 'data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"vyDV0ccbW"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"1"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"6xkhwo3yn1"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"gA1GZQMkfT"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"VpfnRnw5bd"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"2"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"dWcE3btfjq"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"82INPmkTxB"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"4ZDDkYRJkQ"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"3"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"zyWdKSMEqD"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"DMB7OcXLv9"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"jHhmRBbVHl"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"4"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"wp2FQtUCRZ"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":","},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"7UslGpLBM2"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":" - "},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"J4tvuc7QGC"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"5"},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"poMYLOfKZv"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{"content":"."},"logprobs":null,"finish_reason":null}],"usage":null,"obfuscation":"WgmUbuN0yJ"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null,"obfuscation":"nnr88"} - - - data: {"id":"chatcmpl-CoyYZyjeqgdwTmWM41nlgzInfRddg","object":"chat.completion.chunk","created":1766265215,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_ee69c2ef48","choices":[],"usage":{"prompt_tokens":14,"completion_tokens":14,"total_tokens":28,"prompt_tokens_details":{"cached_tokens":0,"audio_tokens":0},"completion_tokens_details":{"reasoning_tokens":0,"audio_tokens":0,"accepted_prediction_tokens":0,"rejected_prediction_tokens":0}},"obfuscation":"I3w5xeq44S"} - - - data: [DONE] - - - ' - headers: - CF-RAY: - - 9b1224fcfa1bb74c-LAX - Connection: - - keep-alive - Content-Type: - - text/event-stream; charset=utf-8 - Date: - - Sat, 20 Dec 2025 21:13:35 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '184' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '196' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999992' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_4cbf5ea967a9925098194667a66e62b4 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_system_prompt.yaml b/py/src/braintrust/wrappers/cassettes/test_system_prompt.yaml deleted file mode 100644 index 3659bad91..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_system_prompt.yaml +++ /dev/null @@ -1,65 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "Tell me about the weather."}], "role": - "user"}], "systemInstruction": {"parts": [{"text": "You are a pirate. Always - respond in pirate speak."}], "role": "user"}, "generationConfig": {"maxOutputTokens": - 150}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '242' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61SwW7bMAy9+ys4XXJxAttdHKy3oduwDNnarUZRYN2BrplYiCwJktzMDfLvk5w6 - dbbrfDAk8j0+kk/7CIA9oqx4hY4su4SfPgKw7/8hp6Qj6XxiCPmgRuNescdvPzp7iKPfgcTe16oD - V5OhGBov0b2B25o/kYGGwPGmJGNjWEJJIJTacjkBdIEAdsvJwloZ6GgGD/JBFiREoO1COR8NJElU - BVJg7AiDEhjSyrgY/FiwnHiO1VwGPEKHRgKWqnW+ihdSYgJf8HELn4yy/mp8IR+2KFwH30i7VvYy - paHdREKrQydsNOrhdP4Vvy7IKEFh+kZVJAb4YQCwNZfc1j8IrZIBdltc37BTFp82K7XRRpVhx9Nk - ll9kWZrM0zzNk/nF22weDcq9JmstbugrOfQe4skp5is02hVqS/JKtb2H6eKoMrL8LJ9nL3mnHIqz - 1OJd/E9Z+8GLcjF+CqNX4odHwV0XJiw+3hdstCB33tWwoWi0yL97/E9ieXYuFr0Yc/Tqzj9HfjRl - Q423aZrNkulaoK2nSZL2VZkhq5W0tKwC7iq/53j9GVfzQj8vljd8teC774pFh+gPyUgRkV4DAAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Sun, 05 Oct 2025 17:04:12 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=892 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_temperature_and_top_p.yaml b/py/src/braintrust/wrappers/cassettes/test_temperature_and_top_p.yaml deleted file mode 100644 index b63770144..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_temperature_and_top_p.yaml +++ /dev/null @@ -1,64 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "Say something creative."}], "role": - "user"}], "generationConfig": {"temperature": 0.7, "topP": 0.95, "maxOutputTokens": - 50}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '159' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61SXY/TMBB8z69Y+bmtcskdPXjlKr5FgQqdBAhtm01ineMN9qbHqep/x04uvRRe - yUPkeMYz450cEgC1Q1voAoW8egHfwg7AoX9HjK2QlQCMW2GzRSdP3OE5TNaBIvQ7HlKbmqBhtiBs - dVULaA8IDRmhArw2e3Lg20CYgRftnLZVwPcUAAHPXQtcBgSdX8AKdzXIvbZ3hgadkl3FEgLCvfb1 - DLbddmuihDBIcPadK3FHUSN+9gkW362aZD2e1j9mTzd0bCjGb7ggM9KPI0GV2ga/z4SebaR92Xxc - qxOK++o9V63jbRzSPF0sr5eXWZ5d5enV8/x6mV0ko3PvqTqPFX0gwVACnkatgkLTyobvyL7kri/h - cjCZVHYG59kjLixozqFns39U/U3w1GZa5aTlcHc0Wh76Gle3GzWZj5yFGueTTMb4d8T/5JVn52bJ - Yy1DU1/JeT1UUlETSppni3ReGvT1PE0velXlKPxw1tObIvJu8Fbj2/Xu9RrLX+LX3btXPx8+rVRy - TP4A68C0Px0DAAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Sun, 05 Oct 2025 17:04:14 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=627 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_tool_execution_creates_spans.yaml b/py/src/braintrust/wrappers/cassettes/test_tool_execution_creates_spans.yaml deleted file mode 100644 index 9a2fce271..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_tool_execution_creates_spans.yaml +++ /dev/null @@ -1,216 +0,0 @@ -interactions: -- request: - body: '{"messages":[{"role":"user","content":"What is 127 multiplied by 49?"}],"model":"gpt-4o-mini","max_completion_tokens":500,"stream":false,"tool_choice":"auto","tools":[{"type":"function","function":{"name":"calculate","description":"Perform - a mathematical calculation.","parameters":{"additionalProperties":false,"properties":{"operation":{"type":"string"},"a":{"type":"number"},"b":{"type":"number"}},"required":["operation","a","b"],"type":"object"},"strict":true}}]}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '468' - Content-Type: - - application/json - Cookie: - - __cf_bm=32b.VMplxNQj3L4u_1uDEw4mJbFkX7XgxbW0AIaO4WI-1767741983-1.0.1.1-ngrHAoGsRus82vIYthILxaNTwRrSgq6MT17VyVyBWlwIdCX8AvWXc.5O8aoDYcvvfwwO.wkKSuvDVkjIkcKdBrusGxL1HyXKUH5Xfk3NhOU; - _cfuvid=beFRqK6f.Kw4Ih5NqMjxVqYpI9KKqCHTmRCh_PSGRiw-1767741983214-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.36.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.13.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAAwAAAP//jFNda9swFH33rxD3OR6J69WJ37LBYB1kHXSwMRdzI98k2mRJk+Rubch/ - L5ZT20kzmB+MuEfn3HM/tI8YA1FBzoDv0PPayPj9w/L3/NvqM37I9N1H+TX9I7Lstl5Nv4j0BiYt - Q69/EvcvrDdc10aSF1p1MLeEnlrVWXadZWmSTqcBqHVFsqVtjY9THddCiTiZJmk8zeLZ/MjeacHJ - Qc5+RIwxtg//1qeq6C/kLGiFSE3O4ZYg7y8xBlbLNgLonHAelYfJAHKtPKnWumqkHAFea1lylHJI - 3H370XloFkpZvvt+s6S0soTJavmEePvEF8s7/2mUr5N+NMHQplG8b9II7+P5WTLGQGFNx4S8kejp - jMwYoN02NSnfGod9AdqQxVavgLyAupFeGPlYwKQALCCfJdmkgHUBebo4wInYIbp0vh91ydKmcShf - tw+V0j5kDf27PyKHflRSb43Va3dGhY1Qwu1KS+hCB8aDiF6MBAvQnMwajNW18aXXvygkfTvvRGFY - xwFMZkfQa49yiGeLyQW1siKPIqxCv30c+Y6qgTlsITaV0CMgGlX+2swl7a56obb/Iz8AnJPxVJXG - UiX4acHDNUvtY/3Xtb7HwTA4sg+CU+kF2XYaFW2wkd0TAvfoPNXlRqgtWWNFeEewMWWyuLqa4uJ6 - PofoED0DAAD//wMA8jx53VUEAAA= - headers: - CF-RAY: - - 9b9f050f588cfa4a-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Tue, 06 Jan 2026 23:33:20 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '570' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '585' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999990' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_bf3237ddd052415f9c4b09fee6dcbb30 - status: - code: 200 - message: OK -- request: - body: '{"messages":[{"role":"user","content":"What is 127 multiplied by 49?"},{"role":"assistant","content":null,"tool_calls":[{"id":"call_BYJAe4drea2NAzaaPzc9ATtK","type":"function","function":{"name":"calculate","arguments":"{\"operation\":\"multiply\",\"a\":127,\"b\":49}"}}]},{"role":"tool","tool_call_id":"call_BYJAe4drea2NAzaaPzc9ATtK","content":"6223.0"}],"model":"gpt-4o-mini","max_completion_tokens":500,"stream":false,"tool_choice":"auto","tools":[{"type":"function","function":{"name":"calculate","description":"Perform - a mathematical calculation.","parameters":{"additionalProperties":false,"properties":{"operation":{"type":"string"},"a":{"type":"number"},"b":{"type":"number"}},"required":["operation","a","b"],"type":"object"},"strict":true}}]}' - headers: - Accept: - - application/json - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '752' - Content-Type: - - application/json - Cookie: - - __cf_bm=32b.VMplxNQj3L4u_1uDEw4mJbFkX7XgxbW0AIaO4WI-1767741983-1.0.1.1-ngrHAoGsRus82vIYthILxaNTwRrSgq6MT17VyVyBWlwIdCX8AvWXc.5O8aoDYcvvfwwO.wkKSuvDVkjIkcKdBrusGxL1HyXKUH5Xfk3NhOU; - _cfuvid=beFRqK6f.Kw4Ih5NqMjxVqYpI9KKqCHTmRCh_PSGRiw-1767741983214-0.0.1.1-604800000 - Host: - - api.openai.com - User-Agent: - - pydantic-ai/1.36.0 - X-Stainless-Arch: - - arm64 - X-Stainless-Async: - - async:asyncio - X-Stainless-Lang: - - python - X-Stainless-OS: - - MacOS - X-Stainless-Package-Version: - - 2.13.0 - X-Stainless-Runtime: - - CPython - X-Stainless-Runtime-Version: - - 3.13.3 - x-stainless-read-timeout: - - '600' - x-stainless-retry-count: - - '0' - method: POST - uri: https://api.openai.com/v1/chat/completions - response: - body: - string: !!binary | - H4sIAAAAAAAAA4yST2/bMAzF7/4Ugs51YTtG7OS2dtjQATvtMGBDYSgSbXOVJVWii2RFvvsgJ42d - /QF28YE/Pvrxia8JYxwV3zIue0FycDq9f3n3XOPPw8O3w9PHT3dfHj7XX/t9/f7ZiP0HfhMVdvcD - JL2pbqUdnAZCa05YehAEcWperauqLMosm8BgFego6xylpU0HNJgWWVGmWZXm9VndW5QQ+JZ9Txhj - 7HX6Rp9GwZ5v2TRrqgwQguiAby9NjHFvdaxwEQIGEob4zQylNQRmsp4XFRtGTeg0gmK7Ays3DANb - F8Xqdqnx0I5BRN9m1HoBhDGWRNx7cvt4JseLP2075+0u/CblLRoMfeNBBGuil0DW8YkeE8YepxzG - q9W483Zw1JB9gul3m3MMfE5/hnl+hmRJ6EU9ewNX4xoFJFCHRZBcCtmDmqVz6mJUaBcgWSz9p5u/ - zT4tjqb7n/EzkBIcgWqcB4XyeuO5zUM8zn+1XUKeDPMA/gUlNITg40MoaMWoTyfDwyEQDE2LpgPv - PJ7upnVNsVmtMrFZ1zVPjskvAAAA//8DAJ++QQRFAwAA - headers: - CF-RAY: - - 9b9f05143d609465-SJC - Connection: - - keep-alive - Content-Encoding: - - gzip - Content-Type: - - application/json - Date: - - Tue, 06 Jan 2026 23:33:21 GMT - Server: - - cloudflare - Strict-Transport-Security: - - max-age=31536000; includeSubDomains; preload - Transfer-Encoding: - - chunked - X-Content-Type-Options: - - nosniff - access-control-expose-headers: - - X-Request-ID - alt-svc: - - h3=":443"; ma=86400 - cf-cache-status: - - DYNAMIC - openai-organization: - - braintrust-data - openai-processing-ms: - - '612' - openai-project: - - proj_vsCSXafhhByzWOThMrJcZiw9 - openai-version: - - '2020-10-01' - x-envoy-upstream-service-time: - - '637' - x-openai-proxy-wasm: - - v0.1 - x-ratelimit-limit-requests: - - '30000' - x-ratelimit-limit-tokens: - - '150000000' - x-ratelimit-remaining-requests: - - '29999' - x-ratelimit-remaining-tokens: - - '149999987' - x-ratelimit-reset-requests: - - 2ms - x-ratelimit-reset-tokens: - - 0s - x-request-id: - - req_2934d61385c34a9dad5e9f0b5a7b5721 - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_tool_use[stream].yaml b/py/src/braintrust/wrappers/cassettes/test_tool_use[stream].yaml deleted file mode 100644 index 7e629f021..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_tool_use[stream].yaml +++ /dev/null @@ -1,137 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "What is the weather like in Paris, France?"}], - "role": "user"}], "tools": [{"functionDeclarations": [{"description": "Get the - current weather for a location.\n\nArgs:\n location: The city and state, - e.g. San Francisco, CA\n unit: The unit of temperature (celsius or fahrenheit)", - "name": "get_weather", "parameters": {"properties": {"location": {"type": "STRING"}, - "unit": {"default": "celsius", "type": "STRING"}}, "required": ["location"], - "type": "OBJECT"}}]}], "generationConfig": {"maxOutputTokens": 500}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '551' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:streamGenerateContent?alt=sse - response: - body: - string: "data: {\"candidates\": [{\"content\": {\"parts\": [{\"functionCall\": - {\"name\": \"get_weather\",\"args\": {\"location\": \"Paris, France\"}}}],\"role\": - \"model\"},\"finishReason\": \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": - 64,\"candidatesTokenCount\": 7,\"totalTokenCount\": 71,\"promptTokensDetails\": - [{\"modality\": \"TEXT\",\"tokenCount\": 64}],\"candidatesTokensDetails\": - [{\"modality\": \"TEXT\",\"tokenCount\": 7}]},\"modelVersion\": \"gemini-2.0-flash-001\",\"responseId\": - \"CKXiaLvRF-eh3NoP5O6p-AU\"}\r\n\r\n" - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Disposition: - - attachment - Content-Type: - - text/event-stream - Date: - - Sun, 05 Oct 2025 17:04:08 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=519 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -- request: - body: '{"contents": [{"parts": [{"text": "What is the weather like in Paris, France?"}], - "role": "user"}, {"parts": [{"functionCall": {"args": {"location": "Paris, France"}, - "name": "get_weather"}}], "role": "model"}, {"parts": [{"functionResponse": - {"name": "get_weather", "response": {"result": "22 degrees celsius and sunny - in Paris, France"}}}], "role": "user"}], "tools": [{"functionDeclarations": - [{"description": "Get the current weather for a location.\n\nArgs:\n location: - The city and state, e.g. San Francisco, CA\n unit: The unit of temperature - (celsius or fahrenheit)", "name": "get_weather", "parameters": {"properties": - {"location": {"type": "STRING"}, "unit": {"default": "celsius", "type": "STRING"}}, - "required": ["location"], "type": "OBJECT"}}]}], "generationConfig": {"maxOutputTokens": - 500}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '812' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:streamGenerateContent?alt=sse - response: - body: - string: "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"It\"}],\"role\": - \"model\"}}],\"usageMetadata\": {\"promptTokenCount\": 145,\"totalTokenCount\": - 145,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 145}]},\"modelVersion\": - \"gemini-2.0-flash-001\",\"responseId\": \"CKXiaKqeOc3-698PnKuguA0\"}\r\n\r\ndata: - {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" is 22 degrees celsius - and sunny in Paris, France.\\n\"}],\"role\": \"model\"},\"finishReason\": - \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": 85,\"candidatesTokenCount\": - 15,\"totalTokenCount\": 100,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": - 85}],\"candidatesTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": - 15}]},\"modelVersion\": \"gemini-2.0-flash-001\",\"responseId\": \"CKXiaKqeOc3-698PnKuguA0\"}\r\n\r\n" - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Disposition: - - attachment - Content-Type: - - text/event-stream - Date: - - Sun, 05 Oct 2025 17:04:09 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=343 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_tool_use[sync].yaml b/py/src/braintrust/wrappers/cassettes/test_tool_use[sync].yaml deleted file mode 100644 index 5a9eb9761..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_tool_use[sync].yaml +++ /dev/null @@ -1,136 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "What is the weather like in Paris, France?"}], - "role": "user"}], "tools": [{"functionDeclarations": [{"description": "Get the - current weather for a location.\n\nArgs:\n location: The city and state, - e.g. San Francisco, CA\n unit: The unit of temperature (celsius or fahrenheit)", - "name": "get_weather", "parameters": {"properties": {"location": {"type": "STRING"}, - "unit": {"default": "celsius", "type": "STRING"}}, "required": ["location"], - "type": "OBJECT"}}]}], "generationConfig": {"maxOutputTokens": 500}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '551' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61Sy07DMBC85ysin5sqLU1ScSQ8hAC1QASVEEJLskmtOnawXR6q+u84rzYpcMOH - yNkZz+x6vLFsm8TAE5qARkWO7SdTse1N9S0xwTVybYC2ZIoFSL3n1mvT2RtKuuaxpoKHwFjvcINz - yNHUSYb65QNBL1GSwSEJZKZ+OWwQJmIo5UuJOUiqBva5BB4jOeBurb/+9vvnvTGRglV95SJB1opt - WwJJKadqeYegau/7aDbf9U3gPbsWWSHFa9m24w89P/AC92jqTn3fGwc+Oq5nteaVLVkryPAGNZgA - YDcsMSJ5oSOxQh6KdRWAP6mNOnn18KCBtdDA+sho8ENVnRpPyroxdhI24wOj+qucMTpbRJ1sjH6v - qfaOrM5VHrb4T2ZB38tqkqnDekCpmheRYW5ycsZD10kZqKXjuqNKlEhUheAKL5OSd+IvKMzSi/Aq - /HzTaj6NncfJ7YpYW+sbjOm65BkDAAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Sun, 05 Oct 2025 17:04:07 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=643 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -- request: - body: '{"contents": [{"parts": [{"text": "What is the weather like in Paris, France?"}], - "role": "user"}, {"parts": [{"functionCall": {"args": {"location": "Paris, France"}, - "name": "get_weather"}}], "role": "model"}, {"parts": [{"functionResponse": - {"name": "get_weather", "response": {"result": "22 degrees celsius and sunny - in Paris, France"}}}], "role": "user"}], "tools": [{"functionDeclarations": - [{"description": "Get the current weather for a location.\n\nArgs:\n location: - The city and state, e.g. San Francisco, CA\n unit: The unit of temperature - (celsius or fahrenheit)", "name": "get_weather", "parameters": {"properties": - {"location": {"type": "STRING"}, "unit": {"default": "celsius", "type": "STRING"}}, - "required": ["location"], "type": "OBJECT"}}]}], "generationConfig": {"maxOutputTokens": - 500}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '812' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61R0U7CMBR931c0fWZkHWOCj4oaIwTUxZCoD5VdtsbRzt5OJYR/t9sYbPpqH9rm - ntN7bs/ZOYTQFZexiLkBpOfk2VYI2VV7iSlpQBoLNCVbzLk2J269dq27pRj4Lh/RKAXyBdykoImQ - ZMG1wB651lyugAgkvk9iSDQAkhVkKAokdhqChZTb/oukra774/21d5pFqwxKoY2KIWvo+4ZA10IK - TB+Ao5Il7TGaL+gR5Z/JVCW5Vm/ld1yv77GQjc8CPxiM7MkGw7HTSFeitECewAwMt37xoyvUttjk - JlLvIC9VUfk1GtYyLXs7OAsPuFGGZ13IY70/fXFiVUXW9r0Vif0+z4TZVp5fLSPassh0x2o8clpW - /h7yn8RY2BVzDtHUaT2BRlHHksDGBuX6fc9dZxxT1/NY1ZVqwFxJhNu45F2ES8Hnk3g2nfsfBheB - e3On7gPq7J0fMXv9UcsCAAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Sun, 05 Oct 2025 17:04:08 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=492 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_tool_use_async[async].yaml b/py/src/braintrust/wrappers/cassettes/test_tool_use_async[async].yaml deleted file mode 100644 index bd781f26b..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_tool_use_async[async].yaml +++ /dev/null @@ -1,136 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "What is the weather like in Paris, France?"}], - "role": "user"}], "tools": [{"functionDeclarations": [{"description": "Get the - current weather for a location.\n\nArgs:\n location: The city and state, - e.g. San Francisco, CA\n unit: The unit of temperature (celsius or fahrenheit)", - "name": "get_weather", "parameters": {"properties": {"location": {"type": "STRING"}, - "unit": {"default": "celsius", "type": "STRING"}}, "required": ["location"], - "type": "OBJECT"}}]}], "generationConfig": {"maxOutputTokens": 500}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '551' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61SXU/CMBR9369Y+szIQLYR3wx+BCOR6EKIxpjLdjcau3ZpiwQJ/93uCzbUN/uw - dPecnnNvT/eWbZMIeExj0KjIpf1qKra9L78FJrhGrg3QlEwxB6lP3GrtW3tDSTY80lTwCTDWOVzj - HDI0dZKift8i6DVK0jsngUzVL4cNwkQEhXwhMQdJVc++lcAjJGfcg/XX32n/djImUrCyr0zEyBqx - Q0MgCeVUrZ8QVOX9HD7Oj30T+EwfRJpLsSradvy+5wde4F6M3bHve8PAR8f1rMa8tCUbBSnOUIMJ - AI7DEiOS5ToUH8gnYlMG4I8qo1ZeHTyoYS00sC4y6P1QVdfGk7J2jK2EzfjAqN4VM4Y3y7CVjdHv - NNXckdW6yvMW/8ks6HpZdTJVWAuUqn4RKWYmJ2fYd52EgVo7rjsoRYlElQuucBoXvAksKdyvtnez - XfIVTOf6JRipK0Gsg/UNde2WMxkDAAA= - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Sun, 05 Oct 2025 17:04:09 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=509 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -- request: - body: '{"contents": [{"parts": [{"text": "What is the weather like in Paris, France?"}], - "role": "user"}, {"parts": [{"functionCall": {"args": {"location": "Paris, France"}, - "name": "get_weather"}}], "role": "model"}, {"parts": [{"functionResponse": - {"name": "get_weather", "response": {"result": "22 degrees celsius and sunny - in Paris, France"}}}], "role": "user"}], "tools": [{"functionDeclarations": - [{"description": "Get the current weather for a location.\n\nArgs:\n location: - The city and state, e.g. San Francisco, CA\n unit: The unit of temperature - (celsius or fahrenheit)", "name": "get_weather", "parameters": {"properties": - {"location": {"type": "STRING"}, "unit": {"default": "celsius", "type": "STRING"}}, - "required": ["location"], "type": "OBJECT"}}]}], "generationConfig": {"maxOutputTokens": - 500}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '812' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:generateContent - response: - body: - string: !!binary | - H4sIAAAAAAAC/61R0U7CMBR931c0fWakY8DANwOazGicuhiI8aGyy2gc7eztiEr4d7uNwaav9qFp - 7jk9595z9w4hdMVlIhJuAOkFebEVQvbVXWJKGpDGAk3JFnOuzZlbn33rbSkGPstPNDREIBkMSAKp - BkCyggxFgcR6Eiyk/CJCkohrgT1yrblcQZ+2pA6n92vv3IBWGZTqW5VA1tAPDYGuhRS4eQSOSpa0 - p/g+oieU79JbleZavZUzuKzPvMBnQcDYZDTyp54/njiNdWVKC+Qp3IHhNiR+ioJaiW1uYvUOcqaK - KqTJqLZpZdrBveERN8rwrANNp70/sji3piJrZ91ag52eZ8J8lSPGV4uYthIy3a6aiJxWkr97/Ccz - b9g1c46bqZf1DBpFvZUUtnZP7qDP3HXGceMy5lWqVAPmSiKEScmbfSwEv5lHl8ux+Q7CyN+JkD0s - qXNwfgBgmpRFvwIAAA== - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Encoding: - - gzip - Content-Type: - - application/json; charset=UTF-8 - Date: - - Sun, 05 Oct 2025 17:04:10 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=611 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/cassettes/test_tool_use_async[async_stream].yaml b/py/src/braintrust/wrappers/cassettes/test_tool_use_async[async_stream].yaml deleted file mode 100644 index 9ea64d563..000000000 --- a/py/src/braintrust/wrappers/cassettes/test_tool_use_async[async_stream].yaml +++ /dev/null @@ -1,137 +0,0 @@ -interactions: -- request: - body: '{"contents": [{"parts": [{"text": "What is the weather like in Paris, France?"}], - "role": "user"}], "tools": [{"functionDeclarations": [{"description": "Get the - current weather for a location.\n\nArgs:\n location: The city and state, - e.g. San Francisco, CA\n unit: The unit of temperature (celsius or fahrenheit)", - "name": "get_weather", "parameters": {"properties": {"location": {"type": "STRING"}, - "unit": {"default": "celsius", "type": "STRING"}}, "required": ["location"], - "type": "OBJECT"}}]}], "generationConfig": {"maxOutputTokens": 500}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '551' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:streamGenerateContent?alt=sse - response: - body: - string: "data: {\"candidates\": [{\"content\": {\"parts\": [{\"functionCall\": - {\"name\": \"get_weather\",\"args\": {\"location\": \"Paris, France\"}}}],\"role\": - \"model\"},\"finishReason\": \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": - 64,\"candidatesTokenCount\": 7,\"totalTokenCount\": 71,\"promptTokensDetails\": - [{\"modality\": \"TEXT\",\"tokenCount\": 64}],\"candidatesTokensDetails\": - [{\"modality\": \"TEXT\",\"tokenCount\": 7}]},\"modelVersion\": \"gemini-2.0-flash-001\",\"responseId\": - \"CqXiaOzcMeeh3NoP5O6p-AU\"}\r\n\r\n" - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Disposition: - - attachment - Content-Type: - - text/event-stream - Date: - - Sun, 05 Oct 2025 17:04:11 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=412 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -- request: - body: '{"contents": [{"parts": [{"text": "What is the weather like in Paris, France?"}], - "role": "user"}, {"parts": [{"functionCall": {"args": {"location": "Paris, France"}, - "name": "get_weather"}}], "role": "model"}, {"parts": [{"functionResponse": - {"name": "get_weather", "response": {"result": "22 degrees celsius and sunny - in Paris, France"}}}], "role": "user"}], "tools": [{"functionDeclarations": - [{"description": "Get the current weather for a location.\n\nArgs:\n location: - The city and state, e.g. San Francisco, CA\n unit: The unit of temperature - (celsius or fahrenheit)", "name": "get_weather", "parameters": {"properties": - {"location": {"type": "STRING"}, "unit": {"default": "celsius", "type": "STRING"}}, - "required": ["location"], "type": "OBJECT"}}]}], "generationConfig": {"maxOutputTokens": - 500}}' - headers: - accept: - - '*/*' - accept-encoding: - - gzip, deflate - connection: - - keep-alive - content-length: - - '812' - content-type: - - application/json - host: - - generativelanguage.googleapis.com - user-agent: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - x-goog-api-client: - - google-genai-sdk/1.41.0 gl-python/3.13.3 - method: POST - uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-001:streamGenerateContent?alt=sse - response: - body: - string: "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"It\"}],\"role\": - \"model\"}}],\"usageMetadata\": {\"promptTokenCount\": 145,\"totalTokenCount\": - 145,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 145}]},\"modelVersion\": - \"gemini-2.0-flash-001\",\"responseId\": \"C6XiaKPNEMCDnvgP1eSZoQM\"}\r\n\r\ndata: - {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \" is 22 degrees celsius - and sunny in Paris, France.\"}],\"role\": \"model\"},\"finishReason\": \"STOP\"}],\"usageMetadata\": - {\"promptTokenCount\": 85,\"candidatesTokenCount\": 14,\"totalTokenCount\": - 99,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 85}],\"candidatesTokensDetails\": - [{\"modality\": \"TEXT\",\"tokenCount\": 14}]},\"modelVersion\": \"gemini-2.0-flash-001\",\"responseId\": - \"C6XiaKPNEMCDnvgP1eSZoQM\"}\r\n\r\n" - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Disposition: - - attachment - Content-Type: - - text/event-stream - Date: - - Sun, 05 Oct 2025 17:04:11 GMT - Server: - - scaffolding on HTTPServer2 - Server-Timing: - - gfet4t7; dur=368 - Transfer-Encoding: - - chunked - Vary: - - Origin - - X-Origin - - Referer - X-Content-Type-Options: - - nosniff - X-Frame-Options: - - SAMEORIGIN - X-XSS-Protection: - - '0' - status: - code: 200 - message: OK -version: 1 diff --git a/py/src/braintrust/wrappers/claude_agent_sdk/__init__.py b/py/src/braintrust/wrappers/claude_agent_sdk/__init__.py deleted file mode 100644 index 870ec0e16..000000000 --- a/py/src/braintrust/wrappers/claude_agent_sdk/__init__.py +++ /dev/null @@ -1,110 +0,0 @@ -""" -Braintrust integration for Claude Agent SDK with automatic tracing. - -Usage (imports can be before or after setup): - from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions - from braintrust.wrappers.claude_agent_sdk import setup_claude_agent_sdk - - setup_claude_agent_sdk(project="my-project") - - # Use normally - all calls are automatically traced - options = ClaudeAgentOptions(model="claude-sonnet-4-5-20250929") - async with ClaudeSDKClient(options=options) as client: - await client.query("Hello!") - async for message in client.receive_response(): - print(message) -""" - -import logging - -from braintrust.logger import NOOP_SPAN, current_span, init_logger - -from ._wrapper import _create_client_wrapper_class, _create_tool_wrapper_class, _wrap_tool_factory - -logger = logging.getLogger(__name__) - -__all__ = ["setup_claude_agent_sdk"] - - -def setup_claude_agent_sdk( - api_key: str | None = None, - project_id: str | None = None, - project: str | None = None, -) -> bool: - """ - Setup Braintrust integration with Claude Agent SDK. Will automatically patch the SDK for automatic tracing. - - Args: - api_key (Optional[str]): Braintrust API key. - project_id (Optional[str]): Braintrust project ID. - project (Optional[str]): Braintrust project name. - - Returns: - bool: True if setup was successful, False otherwise. - - Example: - ```python - import claude_agent_sdk - from braintrust.wrappers.claude_agent_sdk import setup_claude_agent_sdk - - setup_claude_agent_sdk(project="my-project") - - # Now use claude_agent_sdk normally - all calls automatically traced - options = claude_agent_sdk.ClaudeAgentOptions(model="claude-sonnet-4-5-20250929") - async with claude_agent_sdk.ClaudeSDKClient(options=options) as client: - await client.query("Hello!") - async for message in client.receive_response(): - print(message) - ``` - """ - span = current_span() - if span == NOOP_SPAN: - init_logger(project=project, api_key=api_key, project_id=project_id) - - try: - import sys - - import claude_agent_sdk - - # Store original classes before patching - original_client = claude_agent_sdk.ClaudeSDKClient if hasattr(claude_agent_sdk, "ClaudeSDKClient") else None - original_tool_class = claude_agent_sdk.SdkMcpTool if hasattr(claude_agent_sdk, "SdkMcpTool") else None - original_tool_fn = claude_agent_sdk.tool if hasattr(claude_agent_sdk, "tool") else None - - # Patch ClaudeSDKClient - if original_client: - wrapped_client = _create_client_wrapper_class(original_client) - claude_agent_sdk.ClaudeSDKClient = wrapped_client - - # Update all modules that already imported ClaudeSDKClient - for module in list(sys.modules.values()): - if module and hasattr(module, "ClaudeSDKClient"): - if getattr(module, "ClaudeSDKClient", None) is original_client: - setattr(module, "ClaudeSDKClient", wrapped_client) - - # Patch SdkMcpTool - if original_tool_class: - wrapped_tool_class = _create_tool_wrapper_class(original_tool_class) - claude_agent_sdk.SdkMcpTool = wrapped_tool_class - - # Update all modules that already imported SdkMcpTool - for module in list(sys.modules.values()): - if module and hasattr(module, "SdkMcpTool"): - if getattr(module, "SdkMcpTool", None) is original_tool_class: - setattr(module, "SdkMcpTool", wrapped_tool_class) - - # Patch tool() decorator - if original_tool_fn: - wrapped_tool_fn = _wrap_tool_factory(original_tool_fn) - claude_agent_sdk.tool = wrapped_tool_fn - - # Update all modules that already imported tool - for module in list(sys.modules.values()): - if module and hasattr(module, "tool"): - if getattr(module, "tool", None) is original_tool_fn: - setattr(module, "tool", wrapped_tool_fn) - - return True - except ImportError: - # Not installed - this is expected when using auto_instrument() - return False diff --git a/py/src/braintrust/wrappers/claude_agent_sdk/_wrapper.py b/py/src/braintrust/wrappers/claude_agent_sdk/_wrapper.py deleted file mode 100644 index ef6f18295..000000000 --- a/py/src/braintrust/wrappers/claude_agent_sdk/_wrapper.py +++ /dev/null @@ -1,434 +0,0 @@ -import dataclasses -import logging -import threading -import time -from collections.abc import AsyncGenerator, AsyncIterable, Callable -from typing import Any - -from braintrust.logger import start_span -from braintrust.span_types import SpanTypeAttribute -from braintrust.wrappers._anthropic_utils import Wrapper, extract_anthropic_usage, finalize_anthropic_tokens - -log = logging.getLogger(__name__) - -# Thread-local storage to propagate parent span export to tool handlers -# The Claude Agent SDK may execute tools in separate async contexts that don't -# preserve contextvars, so we use threading.local() -_thread_local = threading.local() - - -class ClaudeAgentSDKWrapper(Wrapper): - """Main wrapper for claude_agent_sdk module. Intercepts query and tool creation.""" - - def __init__(self, sdk: Any): - super().__init__(sdk) - self.__sdk = sdk - - @property - def query(self) -> Any: - """Pass through query without wrapping - use ClaudeSDKClient for tracing.""" - return self.__sdk.query - - @property - def SdkMcpTool(self) -> Any: - """Intercept SdkMcpTool to wrap handlers.""" - return _create_tool_wrapper_class(self.__sdk.SdkMcpTool) - - @property - def tool(self) -> Any: - """Intercept tool() function if it exists.""" - if hasattr(self.__sdk, "tool"): - return _wrap_tool_factory(self.__sdk.tool) - raise AttributeError("tool") - - @property - def ClaudeSDKClient(self) -> Any: - """Intercept ClaudeSDKClient class to wrap its methods.""" - if hasattr(self.__sdk, "ClaudeSDKClient"): - return _create_client_wrapper_class(self.__sdk.ClaudeSDKClient) - raise AttributeError("ClaudeSDKClient") - - -def _create_tool_wrapper_class(original_tool_class: Any) -> Any: - """Creates a wrapper class for SdkMcpTool that wraps handlers.""" - - class WrappedSdkMcpTool(original_tool_class): # type: ignore[valid-type,misc] - def __init__( - self, - name: Any, - description: Any, - input_schema: Any, - handler: Any, - **kwargs: Any, - ): - wrapped_handler = _wrap_tool_handler(handler, name) - super().__init__(name, description, input_schema, wrapped_handler, **kwargs) # type: ignore[call-arg] - - # Preserve generic typing support - __class_getitem__ = classmethod(lambda cls, params: cls) # type: ignore[assignment] - - return WrappedSdkMcpTool - - -def _wrap_tool_factory(tool_fn: Any) -> Callable[..., Any]: - """Wraps the tool() factory function to return wrapped tools.""" - - def wrapped_tool(*args: Any, **kwargs: Any) -> Any: - result = tool_fn(*args, **kwargs) - - # The tool() function returns a decorator, not a tool definition - # We need to wrap the decorator to intercept the final tool definition - if not callable(result): - return result - - def wrapped_decorator(handler_fn: Any) -> Any: - tool_def = result(handler_fn) - - # Now we have the actual tool definition, wrap its handler - if tool_def and hasattr(tool_def, "handler"): - tool_name = getattr(tool_def, "name", "unknown") - original_handler = tool_def.handler - tool_def.handler = _wrap_tool_handler(original_handler, tool_name) - - return tool_def - - return wrapped_decorator - - return wrapped_tool - - -def _wrap_tool_handler(handler: Any, tool_name: Any) -> Callable[..., Any]: - """Wraps a tool handler to add tracing. - - Uses start_span context manager which automatically: - - Handles exceptions and logs them to the span - - Sets the span as current for nested operations - - Nests under the parent span (TASK span) via the parent parameter - - The Claude Agent SDK may execute tool handlers in a separate async context, - so we try the context variable first, then fall back to current_span export. - """ - # Check if already wrapped to prevent double-wrapping - if hasattr(handler, "_braintrust_wrapped"): - return handler - - async def wrapped_handler(args: Any) -> Any: - # Get parent span export from thread-local storage - parent_export = getattr(_thread_local, "parent_span_export", None) - - with start_span( - name=str(tool_name), - span_attributes={"type": SpanTypeAttribute.TOOL}, - input=args, - parent=parent_export, - ) as span: - result = await handler(args) - span.log(output=result) - return result - - # Mark as wrapped to prevent double-wrapping - wrapped_handler._braintrust_wrapped = True # type: ignore[attr-defined] - return wrapped_handler - - -def _create_client_wrapper_class(original_client_class: Any) -> Any: - """Creates a wrapper class for ClaudeSDKClient that wraps query and receive_response.""" - - class LLMSpanTracker: - """Manages LLM span lifecycle for Claude Agent SDK message streams. - - Message flow per turn: - 1. UserMessage (tool results) โ†’ mark the time when next LLM will start - 2. AssistantMessage - LLM response arrives โ†’ create span with the marked start time, ending previous span - 3. ResultMessage - usage metrics โ†’ log to span - - We end the previous span when the next AssistantMessage arrives, using the marked - start time to ensure sequential timing (no overlapping LLM spans). - """ - - def __init__(self, query_start_time: float | None = None): - self.current_span: Any | None = None - self.next_start_time: float | None = query_start_time - - def start_llm_span( - self, message: Any, prompt: Any, conversation_history: list[dict[str, Any]] - ) -> dict[str, Any] | None: - """Start a new LLM span, ending the previous one if it exists.""" - # Use the marked start time, or current time as fallback - start_time = self.next_start_time if self.next_start_time is not None else time.time() - - # End the previous span at this start time to ensure sequential spans - if self.current_span: - self.current_span.end(end_time=start_time) - - final_content, span = _create_llm_span_for_messages( - [message], prompt, conversation_history, start_time=start_time - ) - self.current_span = span - self.next_start_time = None # Reset for next span - return final_content - - def mark_next_llm_start(self) -> None: - """Mark when the next LLM call will start (after tool results).""" - self.next_start_time = time.time() - - def log_usage(self, usage_metrics: dict[str, float]) -> None: - """Log usage metrics to the current LLM span.""" - if self.current_span and usage_metrics: - self.current_span.log(metrics=usage_metrics) - - def cleanup(self) -> None: - """End any unclosed spans.""" - if self.current_span: - self.current_span.end() - self.current_span = None - - class WrappedClaudeSDKClient(Wrapper): - def __init__(self, *args: Any, **kwargs: Any): - # Create the original client instance - client = original_client_class(*args, **kwargs) - super().__init__(client) - self.__client = client - self.__last_prompt: str | None = None - self.__query_start_time: float | None = None - self.__captured_messages: list[dict[str, Any]] | None = None - - async def query(self, *args: Any, **kwargs: Any) -> Any: - """Wrap query to capture the prompt and start time for tracing.""" - # Capture the time when query is called (when LLM call starts) - self.__query_start_time = time.time() - self.__captured_messages = None - - # Capture the prompt for use in receive_response - prompt = args[0] if args else kwargs.get("prompt") - - if prompt is not None: - if isinstance(prompt, str): - self.__last_prompt = prompt - elif isinstance(prompt, AsyncIterable): - # AsyncIterable[dict] - wrap it to capture messages as they're yielded - captured: list[dict[str, Any]] = [] - self.__captured_messages = captured - self.__last_prompt = None # Will be set after messages are captured - - async def capturing_wrapper() -> AsyncGenerator[dict[str, Any], None]: - async for msg in prompt: - captured.append(msg) - yield msg - - # Replace the prompt with our capturing wrapper - if args: - args = (capturing_wrapper(),) + args[1:] - else: - kwargs["prompt"] = capturing_wrapper() - else: - self.__last_prompt = str(prompt) - - return await self.__client.query(*args, **kwargs) - - async def receive_response(self) -> AsyncGenerator[Any, None]: - """Wrap receive_response to add tracing. - - Uses start_span context manager which automatically: - - Handles exceptions and logs them as errors - - Sets the span as current so tool calls automatically nest under it - - Manages span lifecycle (start/end) - """ - generator = self.__client.receive_response() - - # Determine the initial input - may be updated later if using async generator - initial_input = self.__last_prompt if self.__last_prompt else None - - with start_span( - name="Claude Agent", - span_attributes={"type": SpanTypeAttribute.TASK}, - input=initial_input, - ) as span: - # If we're capturing async messages, we'll update input after they're consumed - input_needs_update = self.__captured_messages is not None - # Store the parent span export in thread-local storage for tool handlers - _thread_local.parent_span_export = span.export() - - final_results: list[dict[str, Any]] = [] - llm_tracker = LLMSpanTracker(query_start_time=self.__query_start_time) - - try: - async for message in generator: - # Update input from captured async messages (once, after they're consumed) - if input_needs_update and self.__captured_messages: - captured_input = _format_captured_messages(self.__captured_messages) - if captured_input: - span.log(input=captured_input) - input_needs_update = False - - message_type = type(message).__name__ - - if message_type == "AssistantMessage": - final_content = llm_tracker.start_llm_span(message, self.__last_prompt, final_results) - if final_content: - final_results.append(final_content) - elif message_type == "UserMessage": - if hasattr(message, "content"): - content = _serialize_content_blocks(message.content) - final_results.append({"content": content, "role": "user"}) - - llm_tracker.mark_next_llm_start() - elif message_type == "ResultMessage": - if hasattr(message, "usage"): - usage_metrics = _extract_usage_from_result_message(message) - llm_tracker.log_usage(usage_metrics) - - result_metadata = { - k: v - for k, v in { - "num_turns": getattr(message, "num_turns", None), - "session_id": getattr(message, "session_id", None), - }.items() - if v is not None - } - if result_metadata: - span.log(metadata=result_metadata) - - yield message - span.log(output=final_results[-1] if final_results else None) - except Exception as e: - log.warning("Error in tracing code", exc_info=e) - finally: - llm_tracker.cleanup() - if hasattr(_thread_local, "parent_span_export"): - delattr(_thread_local, "parent_span_export") - - async def __aenter__(self) -> "WrappedClaudeSDKClient": - await self.__client.__aenter__() - return self - - async def __aexit__(self, *args: Any) -> None: - await self.__client.__aexit__(*args) - - return WrappedClaudeSDKClient - - -def _create_llm_span_for_messages( - messages: list[Any], # List of AssistantMessage objects - prompt: Any, - conversation_history: list[dict[str, Any]], - start_time: float | None = None, -) -> tuple[dict[str, Any] | None, Any | None]: - """Creates an LLM span for a group of AssistantMessage objects. - - Returns a tuple of (final_content, span): - - final_content: The final message content to add to conversation history - - span: The LLM span object (for logging metrics later) - - Automatically nests under the current span (TASK span from receive_response). - - Note: This is called from within a catch_exceptions block, so errors won't break user code. - """ - if not messages: - return None, None - - last_message = messages[-1] - if type(last_message).__name__ != "AssistantMessage": - return None, None - model = getattr(last_message, "model", None) - input_messages = _build_llm_input(prompt, conversation_history) - - outputs: list[dict[str, Any]] = [] - for msg in messages: - if hasattr(msg, "content"): - content = _serialize_content_blocks(msg.content) - outputs.append({"content": content, "role": "assistant"}) - - llm_span = start_span( - name="anthropic.messages.create", - span_attributes={"type": SpanTypeAttribute.LLM}, - input=input_messages, - output=outputs, - metadata={"model": model} if model else None, - start_time=start_time, - ) - - # Return final message content for conversation history and the span - if hasattr(last_message, "content"): - content = _serialize_content_blocks(last_message.content) - return {"content": content, "role": "assistant"}, llm_span - - return None, llm_span - - -def _serialize_content_blocks(content: Any) -> Any: - """Converts content blocks to a serializable format with proper type fields. - - Claude Agent SDK uses dataclasses for content blocks, so we use dataclasses.asdict() - for serialization and add the 'type' field based on the class name. - """ - if isinstance(content, list): - result = [] - for block in content: - if dataclasses.is_dataclass(block): - serialized = dataclasses.asdict(block) - - block_type = type(block).__name__ - if block_type == "TextBlock": - serialized["type"] = "text" - elif block_type == "ToolUseBlock": - serialized["type"] = "tool_use" - elif block_type == "ToolResultBlock": - serialized["type"] = "tool_result" - - content_value = serialized.get("content") - if isinstance(content_value, list) and len(content_value) == 1: - item = content_value[0] - if isinstance(item, dict) and item.get("type") == "text" and "text" in item: - serialized["content"] = item["text"] - - if "is_error" in serialized and serialized["is_error"] is None: - del serialized["is_error"] - else: - serialized = block - - result.append(serialized) - return result - return content - - -def _extract_usage_from_result_message(result_message: Any) -> dict[str, float]: - """Extracts and normalizes usage metrics from a ResultMessage. - - Uses shared Anthropic utilities for consistent metric extraction. - """ - if not hasattr(result_message, "usage"): - return {} - - usage = result_message.usage - if not usage: - return {} - - metrics = extract_anthropic_usage(usage) - if metrics: - metrics = finalize_anthropic_tokens(metrics) - - return metrics - - -def _build_llm_input(prompt: Any, conversation_history: list[dict[str, Any]]) -> list[dict[str, Any]] | None: - """Builds the input array for an LLM span from the initial prompt and conversation history. - - Formats input to match Anthropic messages API format for proper UI rendering. - """ - if isinstance(prompt, str): - if len(conversation_history) == 0: - return [{"content": prompt, "role": "user"}] - else: - return [{"content": prompt, "role": "user"}] + conversation_history - - return conversation_history if conversation_history else None - - -def _format_captured_messages(messages: list[dict[str, Any]]) -> list[dict[str, Any]]: - """Formats captured async generator messages into structured input. - - Returns the messages as-is to preserve structure for tracing. - Empty list returns empty list. - """ - return messages if messages else [] diff --git a/py/src/braintrust/wrappers/claude_agent_sdk/test_wrapper.py b/py/src/braintrust/wrappers/claude_agent_sdk/test_wrapper.py deleted file mode 100644 index db2fd7295..000000000 --- a/py/src/braintrust/wrappers/claude_agent_sdk/test_wrapper.py +++ /dev/null @@ -1,294 +0,0 @@ -""" -Integration tests for the Claude Agent SDK wrapper. - -These tests verify the wrapper creates the correct span hierarchy when used with -the actual Claude Agent SDK. -""" - -import pytest - -# Try to import the Claude Agent SDK - skip tests if not available -try: - import claude_agent_sdk - - CLAUDE_SDK_AVAILABLE = True -except ImportError: - CLAUDE_SDK_AVAILABLE = False - print("Claude Agent SDK not installed, skipping integration tests") - -from braintrust import logger -from braintrust.span_types import SpanTypeAttribute -from braintrust.test_helpers import init_test_logger -from braintrust.wrappers.claude_agent_sdk._wrapper import ( - _create_client_wrapper_class, - _create_tool_wrapper_class, -) -from braintrust.wrappers.test_utils import verify_autoinstrument_script - -PROJECT_NAME = "test-claude-agent-sdk" -TEST_MODEL = "claude-haiku-4-5-20251001" - - -@pytest.fixture -def memory_logger(): - """Memory-based logger for testing span creation.""" - init_test_logger(PROJECT_NAME) - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -@pytest.mark.skipif(not CLAUDE_SDK_AVAILABLE, reason="Claude Agent SDK not installed") -@pytest.mark.asyncio -async def test_calculator_with_multiple_operations(memory_logger): - """Test claude_agent.py example - calculator with multiple operations. - - This integration test verifies: - - Task span is created for the overall agent interaction - - LLM spans are created for each message group - - Tool spans are created for calculator calls - - Span hierarchy is correct (children reference parent) - - Metrics are properly extracted and logged - """ - assert not memory_logger.pop() - - # Patch claude_agent_sdk for tracing (logger already initialized by fixture) - original_client = claude_agent_sdk.ClaudeSDKClient - original_tool_class = claude_agent_sdk.SdkMcpTool - - claude_agent_sdk.ClaudeSDKClient = _create_client_wrapper_class(original_client) - claude_agent_sdk.SdkMcpTool = _create_tool_wrapper_class(original_tool_class) - - # Create calculator tool - async def calculator_handler(args): - operation = args["operation"] - a = args["a"] - b = args["b"] - - if operation == "multiply": - result = a * b - elif operation == "subtract": - result = a - b - elif operation == "add": - result = a + b - elif operation == "divide": - if b == 0: - return { - "content": [{"type": "text", "text": "Error: Division by zero"}], - "isError": True, - } - result = a / b - else: - return { - "content": [{"type": "text", "text": f"Unknown operation: {operation}"}], - "isError": True, - } - - return { - "content": [{"type": "text", "text": f"The result of {operation}({a}, {b}) is {result}"}], - } - - calculator_tool = claude_agent_sdk.SdkMcpTool( - name="calculator", - description="Performs basic arithmetic operations", - input_schema={ - "type": "object", - "properties": { - "operation": { - "type": "string", - "enum": ["add", "subtract", "multiply", "divide"], - "description": "The arithmetic operation to perform", - }, - "a": {"type": "number", "description": "First number"}, - "b": {"type": "number", "description": "Second number"}, - }, - "required": ["operation", "a", "b"], - }, - handler=calculator_handler, - ) - - # Run the query using ClaudeSDKClient (required for tracing) - options = claude_agent_sdk.ClaudeAgentOptions( - model=TEST_MODEL, - mcp_servers={ - "calculator": claude_agent_sdk.create_sdk_mcp_server( - name="calculator", - version="1.0.0", - tools=[calculator_tool], - ) - }, - ) - - result_message = None - async with claude_agent_sdk.ClaudeSDKClient(options=options) as client: - await client.query("What is 15 multiplied by 7? Then subtract 5 from the result.") - async for message in client.receive_response(): - # Check for ResultMessage by class name - if type(message).__name__ == "ResultMessage": - result_message = message - - # Get logged spans - spans = memory_logger.pop() - - # Verify root task span - task_spans = [s for s in spans if s["span_attributes"]["type"] == SpanTypeAttribute.TASK] - assert len(task_spans) == 1, f"Should have exactly one task span, got {len(task_spans)}" - - task_span = task_spans[0] - assert task_span["span_attributes"]["name"] == "Claude Agent" - assert "15 multiplied by 7" in task_span["input"] - assert task_span["output"] is not None - - # Verify we received result message with metadata - assert result_message is not None, "Should have received result message" - if hasattr(result_message, "num_turns"): - assert task_span.get("metadata", {}).get("num_turns") is not None - if hasattr(result_message, "session_id"): - assert task_span.get("metadata", {}).get("session_id") is not None - - # Verify LLM spans (multiple anthropic.messages.create calls) - llm_spans = [s for s in spans if s["span_attributes"]["type"] == SpanTypeAttribute.LLM] - assert len(llm_spans) >= 1, f"Should have at least one LLM span, got {len(llm_spans)}" - - # Check that at least one LLM span has token metrics - llm_spans_with_metrics = [s for s in llm_spans if "prompt_tokens" in s.get("metrics", {})] - assert len(llm_spans_with_metrics) >= 1, "At least one LLM span should have token metrics" - - for llm_span in llm_spans: - assert llm_span["span_attributes"]["name"] == "anthropic.messages.create" - # Output should be an array of messages - assert isinstance(llm_span["output"], list) - assert len(llm_span["output"]) > 0 - - # Verify the last LLM span has complete metrics - last_llm_span = llm_spans[-1] - assert last_llm_span["metrics"]["prompt_tokens"] > 0 - assert last_llm_span["metrics"]["completion_tokens"] > 0 - - # Verify tool spans (calculator may or may not be called depending on model behavior) - tool_spans = [s for s in spans if s["span_attributes"]["type"] == SpanTypeAttribute.TOOL] - - for tool_span in tool_spans: - assert tool_span["span_attributes"]["name"] == "calculator" - assert tool_span["input"] is not None - assert tool_span["output"] is not None - - # Verify span hierarchy (all children should reference the root task span) - root_span_id = task_span["span_id"] - for span in spans: - if span["span_id"] != root_span_id: - assert span["root_span_id"] == root_span_id - assert root_span_id in span["span_parents"] - - -def _make_message(content: str) -> dict: - """Create a streaming format message dict.""" - return {"type": "user", "message": {"role": "user", "content": content}} - - -def _assert_structured_input(task_span: dict, expected_contents: list[str]) -> None: - """Assert that task span input is a structured list with expected content.""" - inp = task_span.get("input") - assert isinstance(inp, list), f"Expected list input, got {type(inp).__name__}: {inp}" - assert [x["message"]["content"] for x in inp] == expected_contents - - -class CustomAsyncIterable: - """Custom AsyncIterable class (not a generator) for testing.""" - - def __init__(self, messages: list[dict]): - self._messages = messages - - def __aiter__(self): - return CustomAsyncIterator(self._messages) - - -class CustomAsyncIterator: - """Iterator for CustomAsyncIterable.""" - - def __init__(self, messages: list[dict]): - self._messages = messages - self._index = 0 - - async def __anext__(self): - if self._index >= len(self._messages): - raise StopAsyncIteration - msg = self._messages[self._index] - self._index += 1 - return msg - - -@pytest.mark.skipif(not CLAUDE_SDK_AVAILABLE, reason="Claude Agent SDK not installed") -@pytest.mark.asyncio -@pytest.mark.parametrize( - "input_factory,expected_contents", - [ - pytest.param( - lambda: (msg async for msg in _single_message_generator()), - ["What is 2 + 2?"], - id="asyncgen_single", - ), - pytest.param( - lambda: (msg async for msg in _multi_message_generator()), - ["Part 1", "Part 2"], - id="asyncgen_multi", - ), - pytest.param( - lambda: CustomAsyncIterable([_make_message("Custom 1"), _make_message("Custom 2")]), - ["Custom 1", "Custom 2"], - id="custom_async_iterable", - ), - ], -) -async def test_query_async_iterable(memory_logger, input_factory, expected_contents): - """Test that async iterable inputs are captured as structured lists. - - Verifies that passing AsyncIterable[dict] to query() results in the span - input showing the structured message list, not a flattened string or repr. - """ - assert not memory_logger.pop() - - original_client = claude_agent_sdk.ClaudeSDKClient - claude_agent_sdk.ClaudeSDKClient = _create_client_wrapper_class(original_client) - - try: - options = claude_agent_sdk.ClaudeAgentOptions(model=TEST_MODEL) - - async with claude_agent_sdk.ClaudeSDKClient(options=options) as client: - await client.query(input_factory()) - async for message in client.receive_response(): - if type(message).__name__ == "ResultMessage": - break - - spans = memory_logger.pop() - - task_spans = [s for s in spans if s["span_attributes"]["type"] == SpanTypeAttribute.TASK] - assert len(task_spans) >= 1, f"Should have at least one task span, got {len(task_spans)}" - - task_span = next( - (s for s in task_spans if s["span_attributes"]["name"] == "Claude Agent"), - task_spans[0], - ) - - _assert_structured_input(task_span, expected_contents) - - finally: - claude_agent_sdk.ClaudeSDKClient = original_client - - -async def _single_message_generator(): - """Generator yielding a single message.""" - yield _make_message("What is 2 + 2?") - - -async def _multi_message_generator(): - """Generator yielding multiple messages.""" - yield _make_message("Part 1") - yield _make_message("Part 2") - - -class TestAutoInstrumentClaudeAgentSDK: - """Tests for auto_instrument() with Claude Agent SDK.""" - - def test_auto_instrument_claude_agent_sdk(self): - """Test auto_instrument patches Claude Agent SDK and creates spans.""" - verify_autoinstrument_script("test_auto_claude_agent_sdk.py") diff --git a/py/src/braintrust/wrappers/dspy.py b/py/src/braintrust/wrappers/dspy.py deleted file mode 100644 index 8fad6691c..000000000 --- a/py/src/braintrust/wrappers/dspy.py +++ /dev/null @@ -1,466 +0,0 @@ -""" -Braintrust integration for DSPy. - -This module provides the BraintrustDSpyCallback class for logging DSPy execution traces to Braintrust. - -Basic Usage: - ```python - import dspy - from braintrust import init_logger - from braintrust.wrappers.dspy import BraintrustDSpyCallback - - # Initialize Braintrust logger - init_logger(project="my-dspy-project") - - # Configure DSPy with Braintrust callback - lm = dspy.LM("openai/gpt-4o-mini") - dspy.configure(lm=lm, callbacks=[BraintrustDSpyCallback()]) - - # Use DSPy as normal - all execution will be logged to Braintrust - cot = dspy.ChainOfThought("question -> answer") - result = cot(question="What is the capital of France?") - ``` - -Advanced Usage with LiteLLM Patching: - For more detailed token metrics and tracing, you can patch LiteLLM before importing DSPy. - Note: You must disable DSPy's disk cache to ensure all LLM calls are traced. - - ```python - # IMPORTANT: Patch LiteLLM BEFORE importing DSPy - from braintrust.wrappers.litellm import patch_litellm - patch_litellm() - - import dspy - from braintrust import init_logger - from braintrust.wrappers.dspy import BraintrustDSpyCallback - - logger = init_logger(project="my-project") - - # Disable disk cache to ensure LiteLLM wrapper is always called - dspy.configure_cache( - enable_disk_cache=False, - enable_memory_cache=True, # Keep memory cache for performance - ) - - lm = dspy.LM("openai/gpt-4o-mini") - dspy.configure(lm=lm, callbacks=[BraintrustDSpyCallback()]) - ``` -""" - -from typing import Any - -from braintrust.logger import current_span, start_span -from braintrust.span_types import SpanTypeAttribute -from wrapt import wrap_function_wrapper - -# Note: For detailed token and cost metrics, use patch_litellm() before importing DSPy. -# The DSPy callback focuses on execution flow and span hierarchy. - -try: - from dspy.utils.callback import BaseCallback -except ImportError: - raise ImportError("DSPy is not installed. Please install it with: pip install dspy") - -__all__ = ["BraintrustDSpyCallback", "patch_dspy"] - - -class BraintrustDSpyCallback(BaseCallback): - """Callback handler that logs DSPy execution traces to Braintrust. - - This callback integrates DSPy with Braintrust's observability platform, automatically - logging language model calls, module executions, tool invocations, and evaluations. - - Logged information includes: - - Input parameters and output results - - Execution latency - - Error information when exceptions occur - - Hierarchical span relationships for nested operations - - Basic Example: - ```python - import dspy - from braintrust import init_logger - from braintrust.wrappers.dspy import BraintrustDSpyCallback - - # Initialize Braintrust - init_logger(project="dspy-example") - - # Configure DSPy with callback - lm = dspy.LM("openai/gpt-4o-mini") - dspy.configure(lm=lm, callbacks=[BraintrustDSpyCallback()]) - - # Use DSPy - execution is automatically logged - predictor = dspy.Predict("question -> answer") - result = predictor(question="What is 2+2?") - ``` - - Advanced Example with LiteLLM Patching: - For additional detailed token metrics from LiteLLM's wrapper, patch before importing DSPy - and disable DSPy's disk cache: - - ```python - from braintrust.wrappers.litellm import patch_litellm - patch_litellm() - - import dspy - from braintrust import init_logger - from braintrust.wrappers.dspy import BraintrustDSpyCallback - - init_logger(project="dspy-example") - - # Disable disk cache to ensure LiteLLM calls are traced - dspy.configure_cache(enable_disk_cache=False, enable_memory_cache=True) - - lm = dspy.LM("openai/gpt-4o-mini") - dspy.configure(lm=lm, callbacks=[BraintrustDSpyCallback()]) - ``` - - The callback creates Braintrust spans for: - - DSPy module executions (Predict, ChainOfThought, ReAct, etc.) - - LLM calls with latency metrics - - Tool calls - - Evaluation runs - - For detailed token usage and cost metrics, use LiteLLM patching (see Advanced Example above). - The patched LiteLLM wrapper will create additional "Completion" spans with comprehensive metrics. - - Spans are automatically nested based on the execution hierarchy. - """ - - def __init__(self): - """Initialize the Braintrust DSPy callback handler.""" - super().__init__() - # Map call_id to span objects for proper nesting - self._spans: dict[str, Any] = {} - - def on_lm_start( - self, - call_id: str, - instance: Any, - inputs: dict[str, Any], - ): - """Log the start of a language model call. - - Args: - call_id: Unique identifier for this call - instance: The LM instance being called - inputs: Input parameters to the LM - """ - # Extract metadata from the LM instance and inputs - metadata = {} - if hasattr(instance, "model"): - metadata["model"] = instance.model - if hasattr(instance, "provider"): - metadata["provider"] = str(instance.provider) - - # Extract common LM parameters from inputs - for key in ["temperature", "max_tokens", "top_p", "top_k", "stop"]: - if key in inputs: - metadata[key] = inputs[key] - - # Get the current active span to establish parent-child relationship - parent = current_span() - parent_export = parent.export() if parent else None - - span = start_span( - name="dspy.lm", - input=inputs, - metadata=metadata, - parent=parent_export, - ) - # Manually set as current span so children can find it - span.set_current() - self._spans[call_id] = span - - def on_lm_end( - self, - call_id: str, - outputs: dict[str, Any] | None, - exception: Exception | None = None, - ): - """Log the end of a language model call. - - Args: - call_id: Unique identifier for this call - outputs: Output from the LM, or None if there was an exception - exception: Exception raised during execution, if any - """ - span = self._spans.pop(call_id, None) - if not span: - return - - try: - log_data = {} - if exception: - log_data["error"] = exception - if outputs: - log_data["output"] = outputs - - if log_data: - span.log(**log_data) - finally: - span.unset_current() - span.end() - - def on_module_start( - self, - call_id: str, - instance: Any, - inputs: dict[str, Any], - ): - """Log the start of a DSPy module execution. - - Args: - call_id: Unique identifier for this call - instance: The Module instance being called - inputs: Input parameters to the module's forward() method - """ - # Get module name - module_name = instance.__class__.__name__ - if hasattr(instance, "__class__") and hasattr(instance.__class__, "__module__"): - module_name = f"{instance.__class__.__module__}.{instance.__class__.__name__}" - - # Get the current active span to establish parent-child relationship - parent = current_span() - parent_export = parent.export() if parent else None - - span = start_span( - name=f"dspy.module.{instance.__class__.__name__}", - input=inputs, - metadata={"module_class": module_name}, - parent=parent_export, - ) - # Manually set as current span so children can find it - span.set_current() - self._spans[call_id] = span - - def on_module_end( - self, - call_id: str, - outputs: Any | None, - exception: Exception | None = None, - ): - """Log the end of a DSPy module execution. - - Args: - call_id: Unique identifier for this call - outputs: Output from the module, or None if there was an exception - exception: Exception raised during execution, if any - """ - span = self._spans.pop(call_id, None) - if not span: - return - - try: - log_data = {} - if exception: - log_data["error"] = exception - if outputs is not None: - # Convert DSPy Prediction objects to dict for logging - if hasattr(outputs, "toDict"): - output_dict = outputs.toDict() - elif hasattr(outputs, "__dict__"): - output_dict = outputs.__dict__ - else: - output_dict = outputs - log_data["output"] = output_dict - - if log_data: - span.log(**log_data) - finally: - span.unset_current() - span.end() - - def on_tool_start( - self, - call_id: str, - instance: Any, - inputs: dict[str, Any], - ): - """Log the start of a tool invocation. - - Args: - call_id: Unique identifier for this call - instance: The Tool instance being called - inputs: Input parameters to the tool - """ - # Get tool name - tool_name = "unknown" - if hasattr(instance, "name"): - tool_name = instance.name - elif hasattr(instance, "__name__"): - tool_name = instance.__name__ - elif hasattr(instance, "func") and hasattr(instance.func, "__name__"): - tool_name = instance.func.__name__ - - # Get the current active span to establish parent-child relationship - parent = current_span() - parent_export = parent.export() if parent else None - - span = start_span( - name=tool_name, - span_attributes={"type": SpanTypeAttribute.TOOL}, - input=inputs, - parent=parent_export, - ) - # Manually set as current span so children can find it - span.set_current() - self._spans[call_id] = span - - def on_tool_end( - self, - call_id: str, - outputs: dict[str, Any] | None, - exception: Exception | None = None, - ): - """Log the end of a tool invocation. - - Args: - call_id: Unique identifier for this call - outputs: Output from the tool, or None if there was an exception - exception: Exception raised during execution, if any - """ - span = self._spans.pop(call_id, None) - if not span: - return - - try: - log_data = {} - if exception: - log_data["error"] = exception - if outputs is not None: - log_data["output"] = outputs - - if log_data: - span.log(**log_data) - finally: - span.unset_current() - span.end() - - def on_evaluate_start( - self, - call_id: str, - instance: Any, - inputs: dict[str, Any], - ): - """Log the start of an evaluation run. - - Args: - call_id: Unique identifier for this call - instance: The Evaluate instance - inputs: Input parameters to the evaluation - """ - metadata = {} - # Extract evaluation metadata - if hasattr(instance, "metric") and instance.metric: - if hasattr(instance.metric, "__name__"): - metadata["metric"] = instance.metric.__name__ - if hasattr(instance, "num_threads"): - metadata["num_threads"] = instance.num_threads - - # Get the current active span to establish parent-child relationship - parent = current_span() - parent_export = parent.export() if parent else None - - span = start_span( - name="dspy.evaluate", - input=inputs, - metadata=metadata, - parent=parent_export, - ) - # Manually set as current span so children can find it - span.set_current() - self._spans[call_id] = span - - def on_evaluate_end( - self, - call_id: str, - outputs: Any | None, - exception: Exception | None = None, - ): - """Log the end of an evaluation run. - - Args: - call_id: Unique identifier for this call - outputs: Output from the evaluation, or None if there was an exception - exception: Exception raised during execution, if any - """ - span = self._spans.pop(call_id, None) - if not span: - return - - try: - log_data = {} - if exception: - log_data["error"] = exception - if outputs is not None: - log_data["output"] = outputs - # Extract metrics from evaluation results - if isinstance(outputs, dict): - metrics = {} - # Common evaluation metrics - for key in ["accuracy", "score", "total", "correct"]: - if key in outputs: - try: - metrics[key] = float(outputs[key]) - except (ValueError, TypeError): - pass - if metrics: - log_data["metrics"] = metrics - - if log_data: - span.log(**log_data) - finally: - span.unset_current() - span.end() - - -def _configure_wrapper(wrapped, instance, args, kwargs): - """Wrapper for dspy.configure that auto-adds BraintrustDSpyCallback.""" - callbacks = kwargs.get("callbacks") - if callbacks is None: - callbacks = [] - else: - callbacks = list(callbacks) - - # Check if already has Braintrust callback - has_bt_callback = any(isinstance(cb, BraintrustDSpyCallback) for cb in callbacks) - if not has_bt_callback: - callbacks.append(BraintrustDSpyCallback()) - - kwargs["callbacks"] = callbacks - return wrapped(*args, **kwargs) - - -def patch_dspy() -> bool: - """ - Patch DSPy to automatically add Braintrust tracing callback. - - After calling this, all calls to dspy.configure() will automatically - include the BraintrustDSpyCallback. - - Returns: - True if DSPy was patched (or already patched), False if DSPy is not installed. - - Example: - ```python - import braintrust - braintrust.patch_dspy() - - import dspy - lm = dspy.LM("openai/gpt-4o-mini") - dspy.configure(lm=lm) # BraintrustDSpyCallback auto-added! - ``` - """ - try: - import dspy - - if getattr(dspy, "__braintrust_wrapped__", False): - return True # Already patched - - wrap_function_wrapper("dspy", "configure", _configure_wrapper) - dspy.__braintrust_wrapped__ = True - return True - - except ImportError: - return False diff --git a/py/src/braintrust/wrappers/google_genai/__init__.py b/py/src/braintrust/wrappers/google_genai/__init__.py deleted file mode 100644 index f80db1503..000000000 --- a/py/src/braintrust/wrappers/google_genai/__init__.py +++ /dev/null @@ -1,430 +0,0 @@ -import logging -import time -from collections.abc import Iterable -from typing import Any - -from braintrust.bt_json import bt_safe_deep_copy -from braintrust.logger import NOOP_SPAN, Attachment, current_span, init_logger, start_span -from braintrust.span_types import SpanTypeAttribute -from wrapt import wrap_function_wrapper - -logger = logging.getLogger(__name__) - - -def setup_genai( - api_key: str | None = None, - project_id: str | None = None, - project_name: str | None = None, -) -> bool: - """ - Setup Braintrust integration with Google GenAI. - - Returns: - True if setup was successful, False if google-genai is not installed. - """ - span = current_span() - if span == NOOP_SPAN: - init_logger(project=project_name, api_key=api_key, project_id=project_id) - - try: - import google.genai as genai # pyright: ignore - from google.genai import models - - genai.Client = wrap_client(genai.Client) - models.Models = wrap_models(models.Models) - models.AsyncModels = wrap_async_models(models.AsyncModels) - return True - except ImportError: - return False - - -def wrap_client(Client: Any): - if is_patched(Client): - return Client - - # noop for now, but may be useful in the future - - mark_patched(Client) - return Client - - -def wrap_models(Models: Any): - if is_patched(Models): - return Models - - def wrap_generate_content(wrapped: Any, instance: Any, args: Any, kwargs: Any): - input, clean_kwargs = get_args_kwargs(args, kwargs, ["model", "contents", "config"]) - - input = _serialize_input(instance._api_client, input) - - clean_kwargs["model"] = input["model"] - - start = time.time() - with start_span( - name="generate_content", type=SpanTypeAttribute.LLM, input=input, metadata=clean_kwargs - ) as span: - result = wrapped(*args, **kwargs) - metrics = _extract_generate_content_metrics(result, start) - span.log(output=result, metrics=metrics) - return result - - wrap_function_wrapper(Models, "_generate_content", wrap_generate_content) - - def wrap_generate_content_stream(wrapped: Any, instance: Any, args: Any, kwargs: Any): - input, clean_kwargs = get_args_kwargs(args, kwargs, ["model", "contents", "config"]) - - input = _serialize_input(instance._api_client, input) - - clean_kwargs["model"] = input["model"] - - start = time.time() - first_token_time = None - with start_span( - name="generate_content_stream", type=SpanTypeAttribute.LLM, input=input, metadata=clean_kwargs - ) as span: - chunks = [] - for chunk in wrapped(*args, **kwargs): - if first_token_time is None: - first_token_time = time.time() - chunks.append(chunk) - yield chunk - - aggregated, metrics = _aggregate_generate_content_chunks(chunks, start, first_token_time) - span.log(output=aggregated, metrics=metrics) - return aggregated - - wrap_function_wrapper(Models, "generate_content_stream", wrap_generate_content_stream) - - mark_patched(Models) - return Models - - -def wrap_async_models(AsyncModels: Any): - if is_patched(AsyncModels): - return AsyncModels - - async def wrap_generate_content(wrapped: Any, instance: Any, args: Any, kwargs: Any): - input, clean_kwargs = get_args_kwargs(args, kwargs, ["model", "contents", "config"]) - - input = _serialize_input(instance._api_client, input) - - clean_kwargs["model"] = input["model"] - - start = time.time() - with start_span( - name="generate_content", type=SpanTypeAttribute.LLM, input=input, metadata=clean_kwargs - ) as span: - result = await wrapped(*args, **kwargs) - metrics = _extract_generate_content_metrics(result, start) - span.log(output=result, metrics=metrics) - return result - - wrap_function_wrapper(AsyncModels, "generate_content", wrap_generate_content) - - async def wrap_generate_content_stream(wrapped: Any, instance: Any, args: Any, kwargs: Any): - input, clean_kwargs = get_args_kwargs(args, kwargs, ["model", "contents", "config"]) - - input = _serialize_input(instance._api_client, input) - - clean_kwargs["model"] = input["model"] - - async def stream_generator(): - start = time.time() - first_token_time = None - with start_span( - name="generate_content_stream", type=SpanTypeAttribute.LLM, input=input, metadata=clean_kwargs - ) as span: - chunks = [] - async for chunk in await wrapped(*args, **kwargs): - if first_token_time is None: - first_token_time = time.time() - chunks.append(chunk) - yield chunk - - aggregated, metrics = _aggregate_generate_content_chunks(chunks, start, first_token_time) - span.log(output=aggregated, metrics=metrics) - - return stream_generator() - - wrap_function_wrapper(AsyncModels, "generate_content_stream", wrap_generate_content_stream) - - mark_patched(AsyncModels) - return AsyncModels - - -def _serialize_input(api_client: Any, input: dict[str, Any]): - config = bt_safe_deep_copy(input.get("config")) - - if config is not None: - tools = _serialize_tools(api_client, input) - - if tools is not None: - config["tools"] = tools - - input["config"] = config - - # Serialize contents to handle binary data (e.g., images) - if "contents" in input: - input["contents"] = _serialize_contents(input["contents"]) - - return input - - -def _serialize_contents(contents: Any) -> Any: - """Serialize contents, converting binary data to base64-encoded data URLs.""" - if contents is None: - return None - - # Handle list of contents - if isinstance(contents, list): - return [_serialize_content_item(item) for item in contents] - - # Handle single content item - return _serialize_content_item(contents) - - -def _serialize_content_item(item: Any) -> Any: - """Serialize a single content item, handling binary data.""" - # If it's already a dict, return as-is - if isinstance(item, dict): - return item - - # Handle Part objects from google.genai - if hasattr(item, "__class__") and item.__class__.__name__ == "Part": - # Try to extract the data from the Part - if hasattr(item, "text") and item.text is not None: - return {"text": item.text} - elif hasattr(item, "inline_data"): - # Handle binary data (e.g., images) - inline_data = item.inline_data - if hasattr(inline_data, "data") and hasattr(inline_data, "mime_type"): - # Convert bytes to Attachment - data = inline_data.data - mime_type = inline_data.mime_type - - # Ensure data is bytes - if isinstance(data, bytes): - # Determine file extension from mime type - extension = mime_type.split("/")[1] if "/" in mime_type else "bin" - filename = f"file.{extension}" - - # Create an Attachment object - attachment = Attachment(data=data, filename=filename, content_type=mime_type) - - # Return the attachment object in image_url format - # The SDK's _extract_attachments will replace it with its reference when logging - return {"image_url": {"url": attachment}} - - # Try to use built-in serialization if available - if hasattr(item, "model_dump"): - return item.model_dump() - elif hasattr(item, "dump"): - return item.dump() - elif hasattr(item, "to_dict"): - return item.to_dict() - - # Return the item as-is if we can't serialize it - return item - - -def _serialize_tools(api_client: Any, input: Any | None): - try: - from google.genai.models import ( - _GenerateContentParameters_to_mldev, # pyright: ignore [reportPrivateUsage] - _GenerateContentParameters_to_vertex, # pyright: ignore [reportPrivateUsage] - ) - - # cheat by reusing genai library's serializers (they deal with interpreting a function signature etc.) - if api_client.vertexai: - serialized = _GenerateContentParameters_to_vertex(api_client, input) - else: - serialized = _GenerateContentParameters_to_mldev(api_client, input) - - tools = serialized.get("tools") - return tools - except Exception: - return None - - -def omit(obj: dict[str, Any], keys: Iterable[str]): - return {k: v for k, v in obj.items() if k not in keys} - - -def is_patched(obj: Any): - return getattr(obj, "_braintrust_patched", False) - - -def mark_patched(obj: Any): - return setattr(obj, "_braintrust_patched", True) - - -def get_args_kwargs(args: list[str], kwargs: dict[str, Any], keys: Iterable[str]): - return {k: args[i] if args else kwargs.get(k) for i, k in enumerate(keys)}, omit(kwargs, keys) - - -def _extract_generate_content_metrics(response: Any, start: float) -> dict[str, Any]: - """Extract metrics from a non-streaming generate_content response.""" - end_time = time.time() - metrics = dict( - start=start, - end=end_time, - duration=end_time - start, - ) - - # Extract usage metadata if available - if hasattr(response, "usage_metadata") and response.usage_metadata: - usage_metadata = response.usage_metadata - - # Extract token metrics - if hasattr(usage_metadata, "prompt_token_count"): - metrics["prompt_tokens"] = usage_metadata.prompt_token_count - if hasattr(usage_metadata, "candidates_token_count"): - metrics["completion_tokens"] = usage_metadata.candidates_token_count - if hasattr(usage_metadata, "total_token_count"): - metrics["tokens"] = usage_metadata.total_token_count - if hasattr(usage_metadata, "cached_content_token_count"): - metrics["prompt_cached_tokens"] = usage_metadata.cached_content_token_count - - # Extract additional metrics for thinking/reasoning tokens - if hasattr(usage_metadata, "thoughts_token_count"): - metrics["completion_reasoning_tokens"] = usage_metadata.thoughts_token_count - - # Extract tool use prompt tokens if available - if hasattr(usage_metadata, "tool_use_prompt_token_count"): - # Add to prompt_tokens if not already counted - tool_tokens = usage_metadata.tool_use_prompt_token_count - if tool_tokens and "prompt_tokens" in metrics: - # Tool tokens are typically part of prompt tokens, but track separately if needed - pass - - return clean(dict(metrics)) - - -def _aggregate_generate_content_chunks( - chunks: list[Any], start: float, first_token_time: float | None = None -) -> tuple[dict[str, Any], dict[str, Any]]: - """Aggregate streaming chunks into a single response with metrics.""" - end_time = time.time() - metrics = dict( - start=start, - end=end_time, - duration=end_time - start, - ) - - # Add time_to_first_token if available - if first_token_time is not None: - metrics["time_to_first_token"] = first_token_time - start - - if not chunks: - return {}, metrics - - # Accumulate text and metadata - text = "" - thought_text = "" - other_parts = [] - usage_metadata = None - last_response = None - - for chunk in chunks: - last_response = chunk - - # Accumulate usage metadata - if hasattr(chunk, "usage_metadata") and chunk.usage_metadata: - usage_metadata = chunk.usage_metadata - - # Process candidates and their parts - if hasattr(chunk, "candidates") and chunk.candidates: - for candidate in chunk.candidates: - if hasattr(candidate, "content") and candidate.content: - if hasattr(candidate.content, "parts") and candidate.content.parts: - for part in candidate.content.parts: - # Handle text parts - if hasattr(part, "text") and part.text: - if hasattr(part, "thought") and part.thought: - thought_text += part.text - else: - text += part.text - # Collect non-text parts - elif hasattr(part, "function_call"): - other_parts.append({"function_call": part.function_call}) - elif hasattr(part, "code_execution_result"): - other_parts.append({"code_execution_result": part.code_execution_result}) - elif hasattr(part, "executable_code"): - other_parts.append({"executable_code": part.executable_code}) - - # Build aggregated response - aggregated = {} - - # Build parts list - parts = [] - if thought_text: - parts.append({"text": thought_text, "thought": True}) - if text: - parts.append({"text": text}) - parts.extend(other_parts) - - # Build candidates - if parts and last_response and hasattr(last_response, "candidates"): - candidates = [] - for candidate in last_response.candidates: - candidate_dict = {"content": {"parts": parts, "role": "model"}} - - # Add metadata from last candidate - if hasattr(candidate, "finish_reason"): - candidate_dict["finish_reason"] = candidate.finish_reason - if hasattr(candidate, "safety_ratings"): - candidate_dict["safety_ratings"] = candidate.safety_ratings - - candidates.append(candidate_dict) - - aggregated["candidates"] = candidates - - # Add usage metadata - if usage_metadata: - aggregated["usage_metadata"] = usage_metadata - - # Extract token metrics - if hasattr(usage_metadata, "prompt_token_count"): - metrics["prompt_tokens"] = usage_metadata.prompt_token_count - if hasattr(usage_metadata, "candidates_token_count"): - metrics["completion_tokens"] = usage_metadata.candidates_token_count - if hasattr(usage_metadata, "total_token_count"): - metrics["tokens"] = usage_metadata.total_token_count - if hasattr(usage_metadata, "cached_content_token_count"): - metrics["prompt_cached_tokens"] = usage_metadata.cached_content_token_count - - # Extract additional metrics for thinking/reasoning tokens - if hasattr(usage_metadata, "thoughts_token_count"): - metrics["completion_reasoning_tokens"] = usage_metadata.thoughts_token_count - - # Extract tool use prompt tokens if available - if hasattr(usage_metadata, "tool_use_prompt_token_count"): - # Add to prompt_tokens if not already counted - tool_tokens = usage_metadata.tool_use_prompt_token_count - if tool_tokens and "prompt_tokens" in metrics: - # Tool tokens are typically part of prompt tokens, but track separately if needed - pass - - # Add convenience text property - if text: - aggregated["text"] = text - - clean_metrics = clean(dict(metrics)) - - return aggregated, clean_metrics - - -def clean(obj: dict[str, Any]) -> dict[str, Any]: - return {k: v for k, v in obj.items() if v is not None} - - -def get_path(obj: dict[str, Any], path: str, default: Any = None) -> Any | None: - keys = path.split(".") - current = obj - - for key in keys: - if not (isinstance(current, dict) and key in current): - return default - current = current[key] - - return current diff --git a/py/src/braintrust/wrappers/langchain.py b/py/src/braintrust/wrappers/langchain.py deleted file mode 100644 index c723d0628..000000000 --- a/py/src/braintrust/wrappers/langchain.py +++ /dev/null @@ -1,149 +0,0 @@ -import contextvars -import logging -from typing import Any -from uuid import UUID - -import braintrust - -_logger = logging.getLogger("braintrust.wrappers.langchain") - -try: - from langchain.callbacks.base import BaseCallbackHandler - from langchain.schema import Document - from langchain.schema.agent import AgentAction - from langchain.schema.messages import BaseMessage - from langchain.schema.output import LLMResult -except ImportError: - _logger.warning("Failed to import langchain, using stubs") - BaseCallbackHandler = object - Document = object - AgentAction = object - BaseMessage = object - LLMResult = object - -langchain_parent = contextvars.ContextVar("langchain_current_span", default=None) - - -class BraintrustTracer(BaseCallbackHandler): - def __init__(self, logger=None): - _logger.warning("BraintrustTracer is deprecated, use `pip install braintrust-langchain` instead") - self.logger = logger - self.spans = {} - - def _start_span(self, parent_run_id, run_id, name: str | None, **kwargs: Any) -> Any: - assert run_id not in self.spans, f"Span already exists for run_id {run_id} (this is likely a bug)" - - current_parent = langchain_parent.get() - if parent_run_id in self.spans: - parent_span = self.spans[parent_run_id] - elif current_parent is not None: - parent_span = current_parent - elif self.logger is not None: - parent_span = self.logger - else: - parent_span = braintrust - - span = parent_span.start_span(name=name, **kwargs) - langchain_parent.set(span) - self.spans[run_id] = span - return span - - def _end_span(self, run_id, **kwargs: Any) -> Any: - assert run_id in self.spans, f"No span exists for run_id {run_id} (this is likely a bug)" - span = self.spans.pop(run_id) - span.log(**kwargs) - - if langchain_parent.get() == span: - langchain_parent.set(None) - - span.end() - - def on_chain_start( - self, - serialized: dict[str, Any], - inputs: dict[str, Any], - *, - run_id: UUID, - parent_run_id: UUID | None = None, - tags: list[str] | None = None, - **kwargs: Any, - ) -> Any: - self._start_span(parent_run_id, run_id, "Chain", input=inputs, metadata={"tags": tags}) - - def on_chain_end( - self, outputs: dict[str, Any], *, run_id: UUID, parent_run_id: UUID | None = None, **kwargs: Any - ) -> Any: - self._end_span(run_id, output=outputs) - - def on_llm_start( - self, - serialized: dict[str, Any], - prompts: list[str], - *, - run_id: UUID, - parent_run_id: UUID | None = None, - tags: list[str] | None = None, - **kwargs: Any, - ) -> Any: - self._start_span( - parent_run_id, - run_id, - "LLM", - input=prompts, - metadata={"tags": tags, **kwargs["invocation_params"]}, - ) - - def on_chat_model_start( - self, - serialized: dict[str, Any], - messages: list[list[BaseMessage]], - *, - run_id: UUID, - parent_run_id: UUID | None = None, - tags: list[str] | None = None, - **kwargs: Any, - ) -> Any: - self._start_span( - parent_run_id, - run_id, - "Chat Model", - input=[[m.dict() for m in batch] for batch in messages], - metadata={"tags": tags, **kwargs["invocation_params"]}, - ) - - def on_llm_end( - self, response: LLMResult, *, run_id: UUID, parent_run_id: UUID | None = None, **kwargs: Any - ) -> Any: - metrics = {} - token_usage = response.llm_output.get("token_usage", {}) - if "total_tokens" in token_usage: - metrics["tokens"] = token_usage["total_tokens"] - if "prompt_tokens" in token_usage: - metrics["prompt_tokens"] = token_usage["prompt_tokens"] - if "completion_tokens" in token_usage: - metrics["completion_tokens"] = token_usage["completion_tokens"] - - self._end_span(run_id, output=[[m.dict() for m in batch] for batch in response.generations], metrics=metrics) - - def on_tool_start( - self, - serialized: dict[str, Any], - input_str: str, - *, - run_id: UUID, - parent_run_id: UUID | None = None, - tags: list[str] | None = None, - **kwargs: Any, - ) -> Any: - _logger.warning("Starting tool, but it will not be traced in braintrust (unsupported)") - - def on_tool_end(self, output: str, *, run_id: UUID, parent_run_id: UUID | None = None, **kwargs: Any) -> Any: - pass - - def on_retriever_start(self, query: str, *, run_id: UUID, parent_run_id: UUID | None = None, **kwargs: Any) -> Any: - _logger.warning("Starting retriever, but it will not be traced in braintrust (unsupported)") - - def on_retriever_end( - self, response: list[Document], *, run_id: UUID, parent_run_id: UUID | None = None, **kwargs: Any - ) -> Any: - pass diff --git a/py/src/braintrust/wrappers/langsmith_wrapper.py b/py/src/braintrust/wrappers/langsmith_wrapper.py deleted file mode 100644 index a00a9b40b..000000000 --- a/py/src/braintrust/wrappers/langsmith_wrapper.py +++ /dev/null @@ -1,517 +0,0 @@ -""" -Braintrust integration for LangSmith - provides a migration path from LangSmith to Braintrust. - -This module patches LangSmith's tracing and evaluation APIs to use Braintrust under the hood, -allowing users to migrate with minimal code changes. - -Usage: - ```python - import os - - # Enable LangSmith tracing and set project name (used by both services) - os.environ.setdefault("LANGCHAIN_TRACING_V2", "true") - os.environ.setdefault("LANGCHAIN_PROJECT", "my-project") - - from braintrust.wrappers.langsmith_wrapper import setup_langsmith - - # Call setup BEFORE importing from langsmith - # project_name defaults to LANGCHAIN_PROJECT env var - setup_langsmith() - - # Continue using langsmith imports - they now use Braintrust - from langsmith import traceable, Client - - @traceable - def my_function(inputs: dict) -> dict: - return {"result": inputs["x"] * 2} - - client = Client() - results = client.evaluate( - my_function, - data=[{"inputs": {"x": 1}, "outputs": {"result": 2}}], - evaluators=[my_evaluator], - ) - ``` - - Set BRAINTRUST_STANDALONE=1 to completely replace LangSmith with Braintrust - (no LangSmith code runs). Otherwise, both services run in tandem. -""" - -import inspect -import logging -import os -from typing import Any, Callable, Dict, Iterable, Iterator, List, Optional, ParamSpec, TypeVar - -from braintrust.framework import EvalCase -from braintrust.logger import NOOP_SPAN, current_span, init_logger, traced -from wrapt import wrap_function_wrapper - -logger = logging.getLogger(__name__) - -# Global list to store Braintrust eval results when running in tandem mode -_braintrust_eval_results: List[Any] = [] - -# TODO: langsmith.test/unit/expect, langsmith.AsyncClient, trace -__all__ = [ - "setup_langsmith", - "wrap_traceable", - "wrap_client", - "wrap_evaluate", - "wrap_aevaluate", - "get_braintrust_results", - "clear_braintrust_results", -] - -F = TypeVar("F", bound=Callable[..., Any]) -P = ParamSpec("P") -R = TypeVar("R") - - -def get_braintrust_results() -> List[Any]: - """Get all Braintrust eval results collected during tandem mode.""" - return _braintrust_eval_results.copy() - - -def clear_braintrust_results() -> None: - """Clear all stored Braintrust eval results.""" - _braintrust_eval_results.clear() - - -def setup_langsmith( - api_key: Optional[str] = None, - project_id: Optional[str] = None, - project_name: Optional[str] = None, - standalone: bool = False, -) -> bool: - """ - Setup Braintrust integration with LangSmith. - - This patches LangSmith's @traceable, Client.evaluate(), and aevaluate() - to use Braintrust under the hood. - - Args: - api_key: Braintrust API key (optional, can use env var BRAINTRUST_API_KEY) - project_id: Braintrust project ID (optional) - project_name: Braintrust project name (optional, falls back to LANGCHAIN_PROJECT - env var, then BRAINTRUST_PROJECT env var) - standalone: If True, completely replace LangSmith with Braintrust (no LangSmith - code runs). If False (default), run both LangSmith and Braintrust - in tandem. - - Returns: - True if setup was successful, False otherwise - """ - # Use LANGCHAIN_PROJECT as fallback for project_name to keep both services in sync - if project_name is None: - project_name = os.environ.get("LANGCHAIN_PROJECT") - - span = current_span() - if span == NOOP_SPAN: - init_logger(project=project_name, api_key=api_key, project_id=project_id) - - try: - import langsmith - - langsmith.traceable = wrap_traceable(langsmith.traceable, standalone=standalone) - wrap_client(langsmith.Client, project_name=project_name, project_id=project_id, standalone=standalone) - langsmith.evaluate = wrap_evaluate( - langsmith.evaluate, project_name=project_name, project_id=project_id, standalone=standalone - ) - langsmith.aevaluate = wrap_aevaluate( - langsmith.aevaluate, project_name=project_name, project_id=project_id, standalone=standalone - ) - - logger.info("LangSmith integration with Braintrust enabled") - return True - - except ImportError as e: - logger.error(f"Failed to import langsmith: {e}") - logger.error("langsmith is not installed. Please install it with: pip install langsmith") - return False - - -def wrap_traceable(traceable: F, standalone: bool = False) -> F: - """ - Wrap langsmith.traceable to also use Braintrust's @traced decorator. - - Args: - traceable: The langsmith.traceable function - standalone: If True, replace LangSmith tracing entirely with Braintrust. - If False, add Braintrust tracing alongside LangSmith tracing. - - Returns: - The wrapped traceable function (or the original if already patched) - """ - if _is_patched(traceable): - return traceable - - def traceable_wrapper(*args: Any, **kwargs: Any) -> Any: - # Handle both @traceable and @traceable(...) patterns - func = args[0] if args and callable(args[0]) else None - - def decorator(fn: Callable[P, R]) -> Callable[P, R]: - span_name = kwargs.get("name") or fn.__name__ - - # Conditionally apply LangSmith decorator first - if not standalone: - fn = traceable(fn, **kwargs) - - # Always apply Braintrust tracing - return traced(name=span_name)(fn) # type: ignore[return-value] - - if func is not None: - return decorator(func) - return decorator - - traceable_wrapper._braintrust_patched = True # type: ignore[attr-defined] - return traceable_wrapper # type: ignore[return-value] - - -def wrap_client( - Client: Any, project_name: Optional[str] = None, project_id: Optional[str] = None, standalone: bool = False -) -> Any: - """ - Wrap langsmith.Client to redirect evaluate() and aevaluate() to Braintrust's Eval. - - Args: - Client: The langsmith.Client class - project_name: Braintrust project name to use for evaluations - project_id: Braintrust project ID to use for evaluations - standalone: If True, only run Braintrust. If False, run both LangSmith and Braintrust. - - Returns: - The Client class (modified in place) - """ - - if hasattr(Client, "evaluate") and not _is_patched(Client.evaluate): - wrap_function_wrapper( - Client, - "evaluate", - make_evaluate_wrapper(standalone=standalone, project_name=project_name, project_id=project_id), - ) - Client.evaluate._braintrust_patched = True # type: ignore[attr-defined] - - if hasattr(Client, "aevaluate") and not _is_patched(Client.aevaluate): - wrap_function_wrapper( - Client, - "aevaluate", - make_aevaluate_wrapper(standalone=standalone, project_name=project_name, project_id=project_id), - ) - Client.aevaluate._braintrust_patched = True # type: ignore[attr-defined] - - return Client - - -def make_evaluate_wrapper( - *, project_name: Optional[str] = None, project_id: Optional[str] = None, standalone: bool = False -): - def evaluate_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any) -> Any: - result = None - if not standalone: - result = wrapped(*args, **kwargs) - - try: - result = _run_braintrust_eval( - args, - kwargs, - project_name, - project_id, - ) - _braintrust_eval_results.append(result) - except Exception as e: - if standalone: - raise e - else: - logger.warning(f"Braintrust evaluate failed: {e}") - - return result - - return evaluate_wrapper - - -def make_aevaluate_wrapper( - *, project_name: Optional[str] = None, project_id: Optional[str] = None, standalone: bool = False -): - async def aevaluate_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any) -> Any: - result = None - if not standalone: - result = await wrapped(*args, **kwargs) - - try: - result = await _run_braintrust_eval_async( - args, - kwargs, - project_name, - project_id, - ) - _braintrust_eval_results.append(result) - except Exception as e: - if standalone: - raise e - else: - logger.warning(f"Braintrust aevaluate failed: {e}") - - return result - - return aevaluate_wrapper - - -def wrap_evaluate( - evaluate: F, project_name: Optional[str] = None, project_id: Optional[str] = None, standalone: bool = False -) -> F: - """ - Wrap module-level langsmith.evaluate to redirect to Braintrust's Eval. - - Args: - evaluate: The langsmith.evaluate function - project_name: Braintrust project name to use for evaluations - project_id: Braintrust project ID to use for evaluations - standalone: If True, only run Braintrust. If False, run both LangSmith and Braintrust. - - Returns: - The wrapped evaluate function (or the original if already patched) - """ - if _is_patched(evaluate): - return evaluate - - evaluate_wrapper = make_evaluate_wrapper(standalone=standalone, project_name=project_name, project_id=project_id) - evaluate_wrapper._braintrust_patched = True # type: ignore[attr-defined] - return evaluate_wrapper # type: ignore[return-value] - - -def wrap_aevaluate( - aevaluate: F, - project_name: Optional[str] = None, - project_id: Optional[str] = None, - standalone: bool = False, -) -> F: - """ - Wrap module-level langsmith.aevaluate to redirect to Braintrust's EvalAsync. - - Args: - aevaluate: The langsmith.aevaluate function - project_name: Braintrust project name to use for evaluations - project_id: Braintrust project ID to use for evaluations - standalone: If True, only run Braintrust. If False, run both LangSmith and Braintrust. - - Returns: - The wrapped aevaluate function (or the original if already patched) - """ - if _is_patched(aevaluate): - return aevaluate - - aevaluate_wrapper = make_aevaluate_wrapper(standalone=standalone, project_name=project_name, project_id=project_id) - aevaluate_wrapper._braintrust_patched = True # type: ignore[attr-defined] - return aevaluate_wrapper # type: ignore[return-value] - - -def _is_patched(obj: Any) -> bool: - return getattr(obj, "_braintrust_patched", False) - - -# ============================================================================= -# Braintrust evaluation logic -# ============================================================================= - - -def _run_braintrust_eval( - args: Any, - kwargs: Any, - project_name: Optional[str] = None, - project_id: Optional[str] = None, -) -> Any: - """Run Braintrust Eval with LangSmith-style arguments.""" - from braintrust.framework import Eval - - target = args[0] if args else kwargs.get("target") - data = args[1] if len(args) > 1 else kwargs.get("data") - evaluators = kwargs.get("evaluators") - experiment_prefix = kwargs.get("experiment_prefix") - description = kwargs.get("description") - metadata = kwargs.get("metadata") - max_concurrency = kwargs.get("max_concurrency") - num_repetitions = kwargs.get("num_repetitions", 1) - - # Convert evaluators to scorers - scorers = [] - if evaluators: - for e in evaluators: - scorers.append(_make_braintrust_scorer(e)) - - return Eval( - name=project_name or "langsmith-migration", - data=_convert_langsmith_data(data), - task=_make_braintrust_task(target), - scores=scorers, - experiment_name=experiment_prefix, - project_id=project_id, - description=description, - metadata=metadata, - max_concurrency=max_concurrency, - trial_count=num_repetitions, - ) - - -async def _run_braintrust_eval_async( - args: Any, - kwargs: Any, - project_name: Optional[str] = None, - project_id: Optional[str] = None, -) -> Any: - """Run Braintrust EvalAsync with LangSmith-style arguments.""" - from braintrust.framework import EvalAsync - - target = args[0] if args else kwargs.get("target") - data = args[1] if len(args) > 1 else kwargs.get("data") - evaluators = kwargs.get("evaluators") - experiment_prefix = kwargs.get("experiment_prefix") - description = kwargs.get("description") - metadata = kwargs.get("metadata") - max_concurrency = kwargs.get("max_concurrency") - num_repetitions = kwargs.get("num_repetitions", 1) - - # Convert evaluators to scorers - scorers = [] - if evaluators: - for e in evaluators: - scorers.append(_make_braintrust_scorer(e)) - - return await EvalAsync( - name=project_name or "langsmith-migration", - data=_convert_langsmith_data(data), - task=_make_braintrust_task(target), - scores=scorers, - experiment_name=experiment_prefix, - project_id=project_id, - description=description, - metadata=metadata, - max_concurrency=max_concurrency, - trial_count=num_repetitions, - ) - - -# ============================================================================= -# Data conversion helpers -# ============================================================================= - - -def _wrap_output(output: Any) -> Dict[str, Any]: - """Wrap non-dict outputs the same way LangSmith does.""" - if not isinstance(output, dict): - return {"output": output} - return output - - -def _make_braintrust_scorer( - evaluator: Callable[..., Any], -) -> Callable[..., Any]: - """ - Create a Braintrust scorer from a LangSmith evaluator. - - Always runs the evaluator through Braintrust for full tracing (span duration, child LLM calls, etc.). - """ - evaluator_name = getattr(evaluator, "__name__", "score") - - def braintrust_scorer(input: Any, output: Any, expected: Optional[Any] = None, **kwargs: Any) -> Any: - from braintrust.score import Score - - # Run the evaluator with LangSmith's signature - # LangSmith evaluators use: (inputs, outputs, reference_outputs) -> bool | dict - # LangSmith auto-wraps non-dict outputs as {"output": value} - outputs = _wrap_output(output) - - # expected is the real LangSmith Example object passed through from data loading - reference_outputs = expected.outputs if hasattr(expected, "outputs") else expected - - result = evaluator(input, outputs, reference_outputs) - - return Score( - name=result.get("key", evaluator_name), - score=result.get("score"), - metadata=result.get("metadata", {}), - ) - - braintrust_scorer.__name__ = evaluator_name - return braintrust_scorer - - -def _convert_langsmith_data(data: Any) -> Callable[[], Iterator[EvalCase[Any, Any]]]: - """Convert LangSmith data format to Braintrust data format.""" - - def load_data() -> Iterator[EvalCase[Any, Any]]: - # Determine the source iterable without loading everything into memory - source: Iterable[Any] - if callable(data): - source = data() # type: ignore - elif isinstance(data, str): - # Load examples from LangSmith dataset by name - try: - from langsmith import Client # pylint: disable=import-error - - client = Client() - source = client.list_examples(dataset_name=data) - except Exception as e: - logger.warning(f"Failed to load LangSmith dataset '{data}': {e}") - return - elif hasattr(data, "__iter__"): - source = data - else: - source = [data] - - # Process items as a generator - yield one at a time - for item in source: - # Pass through LangSmith Example objects directly - if hasattr(item, "inputs"): - yield EvalCase( - input=item.inputs, - expected=item, # Pass the whole Example object - metadata=getattr(item, "metadata", None), - ) - elif isinstance(item, dict): - if "inputs" in item: - # LangSmith dict format - yield EvalCase( - input=item["inputs"], - expected=item, # Pass the whole dict - metadata=item.get("metadata"), - ) - elif "input" in item: - # Braintrust format - yield EvalCase( - input=item["input"], - expected=item.get("expected"), - metadata=item.get("metadata"), - ) - else: - yield EvalCase(input=item) - else: - yield EvalCase(input=item) - - return load_data - - -def _make_braintrust_task(target: Callable[..., Any]) -> Callable[..., Any]: - """Convert a LangSmith target function to Braintrust task format.""" - - def task_fn(task_input: Any, hooks: Any) -> Any: - if isinstance(task_input, dict): - # Try to get the original function's signature (unwrap decorators) - unwrapped = inspect.unwrap(target) - - try: - sig = inspect.signature(unwrapped) - params = list(sig.parameters.keys()) - if len(params) == 1: - return target(task_input) - if all(p in task_input for p in params): - return target(**task_input) - return target(task_input) - except (ValueError, TypeError): - # Fallback: try kwargs first, then single arg - try: - return target(**task_input) - except TypeError: - return target(task_input) - return target(task_input) - - return task_fn diff --git a/py/src/braintrust/wrappers/litellm.py b/py/src/braintrust/wrappers/litellm.py deleted file mode 100644 index 526b222f1..000000000 --- a/py/src/braintrust/wrappers/litellm.py +++ /dev/null @@ -1,667 +0,0 @@ -from __future__ import annotations - -import time -from collections.abc import AsyncGenerator, Callable, Generator -from types import TracebackType -from typing import Any - -from braintrust.logger import Span, start_span -from braintrust.span_types import SpanTypeAttribute -from braintrust.util import is_numeric, merge_dicts - -X_LEGACY_CACHED_HEADER = "x-cached" -X_CACHED_HEADER = "x-bt-cached" - - -# LiteLLM's representation to Braintrust's representation -TOKEN_NAME_MAP: dict[str, str] = { - # chat API - "total_tokens": "tokens", - "prompt_tokens": "prompt_tokens", - "completion_tokens": "completion_tokens", - # responses API - "tokens": "tokens", - "input_tokens": "prompt_tokens", - "output_tokens": "completion_tokens", -} - -TOKEN_PREFIX_MAP: dict[str, str] = { - "input": "prompt", - "output": "completion", -} - - -class NamedWrapper: - """Wrapper that preserves access to the original wrapped object's attributes.""" - - def __init__(self, wrapped: Any) -> None: - self.__wrapped = wrapped - - def __getattr__(self, name: str) -> Any: - return getattr(self.__wrapped, name) - - -class AsyncResponseWrapper: - """Wrapper that properly preserves async context manager behavior for LiteLLM responses.""" - - def __init__(self, response: Any) -> None: - self._response = response - - async def __aenter__(self) -> Any: - if hasattr(self._response, "__aenter__"): - return await self._response.__aenter__() - return self._response - - async def __aexit__( - self, exc_type: type[BaseException] | None, exc_val: BaseException | None, exc_tb: TracebackType | None - ) -> bool | None: - if hasattr(self._response, "__aexit__"): - return await self._response.__aexit__(exc_type, exc_val, exc_tb) - return None - - def __aiter__(self) -> AsyncGenerator[Any, None]: - if hasattr(self._response, "__aiter__"): - return self._response.__aiter__() - raise TypeError("Response object is not an async iterator") - - async def __anext__(self) -> Any: - if hasattr(self._response, "__anext__"): - return await self._response.__anext__() - raise StopAsyncIteration - - def __getattr__(self, name: str) -> Any: - return getattr(self._response, name) - - -class CompletionWrapper: - """Wrapper for LiteLLM completion functions with tracing support.""" - - def __init__(self, completion_fn: Callable[..., Any] | None, acompletion_fn: Callable[..., Any] | None) -> None: - self.completion_fn = completion_fn - self.acompletion_fn = acompletion_fn - - def _handle_streaming_response( - self, raw_response: Any, span: Span, start_time: float, is_async: bool = False - ) -> AsyncResponseWrapper | Generator[Any, None, None]: - """Handle streaming response for both sync and async cases.""" - if is_async: - - async def async_gen() -> AsyncGenerator[Any, None]: - try: - first = True - all_results: list[dict[str, Any]] = [] - async for item in raw_response: - if first: - span.log(metrics={"time_to_first_token": time.time() - start_time}) - first = False - all_results.append(_try_to_dict(item)) - yield item - - span.log(**self._postprocess_streaming_results(all_results)) - finally: - span.end() - - streamer = async_gen() - return AsyncResponseWrapper(streamer) - else: - - def sync_gen() -> Generator[Any, None, None]: - try: - first = True - all_results: list[dict[str, Any]] = [] - for item in raw_response: - if first: - span.log(metrics={"time_to_first_token": time.time() - start_time}) - first = False - all_results.append(_try_to_dict(item)) - yield item - - span.log(**self._postprocess_streaming_results(all_results)) - finally: - span.end() - - return sync_gen() - - def _handle_non_streaming_response(self, raw_response: Any, span: Span, start_time: float) -> Any: - """Handle non-streaming response.""" - log_response = _try_to_dict(raw_response) - metrics = _parse_metrics_from_usage(log_response.get("usage", {})) - metrics["time_to_first_token"] = time.time() - start_time - span.log(metrics=metrics, output=log_response["choices"]) - return raw_response - - def completion(self, *args: Any, **kwargs: Any) -> Any: - """Sync completion with tracing.""" - updated_span_payload = _update_span_payload_from_params(kwargs, input_key="messages") - is_streaming = kwargs.get("stream", False) - - span = start_span( - **merge_dicts( - dict(name="Completion", span_attributes={"type": SpanTypeAttribute.LLM}), updated_span_payload - ) - ) - should_end = True - - try: - start = time.time() - completion_response = self.completion_fn(*args, **kwargs) - # if hasattr(completion_response, "parse"): - # raw_response = completion_response.parse() - # log_headers(completion_response, span) - # else: - # raw_response = completion_response - - if is_streaming: - should_end = False - return self._handle_streaming_response(completion_response, span, start, is_async=False) - else: - return self._handle_non_streaming_response(completion_response, span, start) - finally: - if should_end: - span.end() - - async def acompletion(self, *args: Any, **kwargs: Any) -> Any: - """Async completion with tracing.""" - updated_span_payload = _update_span_payload_from_params(kwargs, input_key="messages") - is_streaming = kwargs.get("stream", False) - - span = start_span( - **merge_dicts( - dict(name="Completion", span_attributes={"type": SpanTypeAttribute.LLM}), updated_span_payload - ) - ) - should_end = True - - try: - start = time.time() - completion_response = await self.acompletion_fn(*args, **kwargs) - - # if hasattr(completion_response, "parse"): - # raw_response = completion_response.parse() - # log_headers(completion_response, span) - # else: - # raw_response = completion_response - - if is_streaming: - should_end = False - return self._handle_streaming_response(completion_response, span, start, is_async=True) - else: - return self._handle_non_streaming_response(completion_response, span, start) - finally: - if should_end: - span.end() - - @classmethod - def _postprocess_streaming_results(cls, all_results: list[dict[str, Any]]) -> dict[str, Any]: - """Process streaming results to extract final response.""" - role = None - content = None - tool_calls: list[Any] | None = None - finish_reason = None - metrics: dict[str, float] = {} - - for result in all_results: - usage = result.get("usage") - if usage: - metrics.update(_parse_metrics_from_usage(usage)) - - choices = result["choices"] - if not choices: - continue - delta = choices[0]["delta"] - if not delta: - continue - - if role is None and delta.get("role") is not None: - role = delta.get("role") - - if delta.get("finish_reason") is not None: - finish_reason = delta.get("finish_reason") - - if delta.get("content") is not None: - content = (content or "") + delta.get("content") - - if delta.get("tool_calls") is not None: - delta_tool_calls = delta.get("tool_calls") - if not delta_tool_calls: - continue - tool_delta = delta_tool_calls[0] - - # pylint: disable=unsubscriptable-object - if not tool_calls or (tool_delta.get("id") and tool_calls[-1]["id"] != tool_delta.get("id")): - tool_calls = (tool_calls or []) + [ - { - "id": tool_delta.get("id"), - "type": tool_delta.get("type"), - "function": tool_delta.get("function"), - } - ] - else: - # pylint: disable=unsubscriptable-object - tool_calls[-1]["function"]["arguments"] += delta["tool_calls"][0]["function"]["arguments"] - - return { - "metrics": metrics, - "output": [ - { - "index": 0, - "message": {"role": role, "content": content, "tool_calls": tool_calls}, - "logprobs": None, - "finish_reason": finish_reason, - } - ], - } - - -class ResponsesWrapper: - """Wrapper for LiteLLM responses functions with tracing support.""" - - def __init__(self, responses_fn: Callable[..., Any] | None, aresponses_fn: Callable[..., Any] | None) -> None: - self.responses_fn = responses_fn - self.aresponses_fn = aresponses_fn - - def _handle_streaming_response( - self, raw_response: Any, span: Span, start_time: float, is_async: bool = False - ) -> AsyncResponseWrapper | Generator[Any, None, None]: - """Handle streaming response for both sync and async cases.""" - if is_async: - - async def async_gen() -> AsyncGenerator[Any, None]: - try: - first = True - all_results: list[dict[str, Any]] = [] - async for item in raw_response: - if first: - span.log(metrics={"time_to_first_token": time.time() - start_time}) - first = False - all_results.append(item) - yield item - - span.log(**self._postprocess_streaming_results(all_results)) - finally: - span.end() - - streamer = async_gen() - return AsyncResponseWrapper(streamer) - else: - - def sync_gen() -> Generator[Any, None, None]: - try: - first = True - all_results: list[dict[str, Any]] = [] - for item in raw_response: - if first: - span.log(metrics={"time_to_first_token": time.time() - start_time}) - first = False - all_results.append(item) - yield item - - span.log(**self._postprocess_streaming_results(all_results)) - finally: - span.end() - - return sync_gen() - - def _handle_non_streaming_response(self, raw_response: Any, span: Span, start_time: float) -> Any: - """Handle non-streaming response.""" - log_response = _try_to_dict(raw_response) - metrics = _parse_metrics_from_usage(log_response.get("usage", {})) - metrics["time_to_first_token"] = time.time() - start_time - span.log(metrics=metrics, output=log_response["output"]) - return raw_response - - def responses(self, *args: Any, **kwargs: Any) -> Any: - """Sync responses with tracing.""" - updated_span_payload = _update_span_payload_from_params(kwargs, input_key="input") - is_streaming = kwargs.get("stream", False) - - span = start_span( - **merge_dicts(dict(name="Response", span_attributes={"type": SpanTypeAttribute.LLM}), updated_span_payload) - ) - should_end = True - - try: - start = time.time() - response = self.responses_fn(*args, **kwargs) - - if is_streaming: - should_end = False - return self._handle_streaming_response(response, span, start, is_async=False) - else: - return self._handle_non_streaming_response(response, span, start) - finally: - if should_end: - span.end() - - async def aresponses(self, *args: Any, **kwargs: Any) -> Any: - """Async completion with tracing.""" - updated_span_payload = _update_span_payload_from_params(kwargs, input_key="input") - is_streaming = kwargs.get("stream", False) - - span = start_span( - **merge_dicts(dict(name="Response", span_attributes={"type": SpanTypeAttribute.LLM}), updated_span_payload) - ) - should_end = True - - try: - start = time.time() - response = await self.aresponses_fn(*args, **kwargs) - - if is_streaming: - should_end = False - return self._handle_streaming_response(response, span, start, is_async=True) - else: - return self._handle_non_streaming_response(response, span, start) - finally: - if should_end: - span.end() - - @classmethod - def _postprocess_streaming_results(cls, all_results: list[Any]) -> dict[str, Any]: - role = None - content = None - tool_calls = None - finish_reason = None - metrics = {} - output = [] - for result in all_results: - usage = None - if hasattr(result, "usage"): - usage = getattr(result, "usage") - elif result.type == "response.completed" and hasattr(result, "response"): - usage = getattr(result.response, "usage") - - if usage: - parsed_metrics = _parse_metrics_from_usage(usage) - metrics.update(parsed_metrics) - - if result.type == "response.output_item.added": - output.append({"id": result.item.get("id"), "type": result.item.get("type")}) - continue - - if not hasattr(result, "output_index"): - continue - - output_index = result.output_index - current_output = output[output_index] - if result.type == "response.output_item.done": - current_output["status"] = result.item.get("status") - continue - - if result.type == "response.output_item.delta": - current_output["delta"] = result.delta - continue - - if hasattr(result, "content_index"): - if "content" not in current_output: - current_output["content"] = [] - content_index = result.content_index - if content_index == len(current_output["content"]): - current_output["content"].append({}) - current_content = current_output["content"][content_index] - if hasattr(result, "delta") and result.delta: - current_content["text"] = (current_content.get("text") or "") + result.delta - - if result.type == "response.output_text.annotation.added": - annotation_index = result.annotation_index - if "annotations" not in current_content: - current_content["annotations"] = [] - if annotation_index == len(current_content["annotations"]): - current_content["annotations"].append({}) - current_content["annotations"][annotation_index] = _try_to_dict(result.annotation) - - return { - "metrics": metrics, - "output": output, - } - - -class EmbeddingWrapper: - """Wrapper for LiteLLM embedding functions.""" - - def __init__(self, embedding_fn: Callable[..., Any] | None) -> None: - self.embedding_fn = embedding_fn - - def embedding(self, *args: Any, **kwargs: Any) -> Any: - """Sync embedding with tracing.""" - updated_span_payload = _update_span_payload_from_params(kwargs, input_key="input") - - with start_span( - **merge_dicts( - dict(name="Embedding", span_attributes={"type": SpanTypeAttribute.LLM}), updated_span_payload - ) - ) as span: - embedding_response = self.embedding_fn(*args, **kwargs) - log_response = _try_to_dict(embedding_response) - self._process_output(log_response, span) - return embedding_response - - def _process_output(self, response: dict[str, Any], span: Span) -> None: - """Process embedding response and log metrics.""" - usage = response.get("usage") - metrics = _parse_metrics_from_usage(usage) - span.log( - metrics=metrics, - # TODO: Add a flag to control whether to log the full embedding vector, - # possibly w/ JSON compression. - output={"embedding_length": len(response["data"][0]["embedding"])}, - ) - - -class ModerationWrapper: - """Wrapper for LiteLLM moderation functions.""" - - def __init__(self, moderation_fn: Callable[..., Any] | None) -> None: - self.moderation_fn = moderation_fn - - def moderation(self, *args: Any, **kwargs: Any) -> Any: - """Sync moderation with tracing.""" - updated_span_payload = _update_span_payload_from_params(kwargs, input_key="input") - - with start_span( - **merge_dicts( - dict(name="Moderation", span_attributes={"type": SpanTypeAttribute.LLM}), updated_span_payload - ) - ) as span: - moderation_response = self.moderation_fn(*args, **kwargs) - log_response = _try_to_dict(moderation_response) - self._process_output(log_response, span) - return moderation_response - - def _process_output(self, response: dict[str, Any], span: Span) -> None: - """Process moderation response and log metrics.""" - usage = response.get("usage") - metrics = _parse_metrics_from_usage(usage) - span.log( - metrics=metrics, - # TODO: Add a flag to control whether to log the full embedding vector, - # possibly w/ JSON compression. - output=response["results"], - ) - - -class LiteLLMWrapper(NamedWrapper): - """Main wrapper for the LiteLLM module.""" - - def __init__(self, litellm_module: Any) -> None: - super().__init__(litellm_module) - self._completion_wrapper = CompletionWrapper(litellm_module.completion, None) - self._acompletion_wrapper = CompletionWrapper(None, litellm_module.acompletion) - self._responses_wrapper = ResponsesWrapper(litellm_module.responses, None) - self._aresponses_wrapper = ResponsesWrapper(None, litellm_module.aresponses) - self._embedding_wrapper = EmbeddingWrapper(litellm_module.embedding) - self._moderation_wrapper = ModerationWrapper(litellm_module.moderation) - - def completion(self, *args: Any, **kwargs: Any) -> Any: - """Sync completion with tracing.""" - return self._completion_wrapper.completion(*args, **kwargs) - - async def acompletion(self, *args: Any, **kwargs: Any) -> Any: - """Async completion with tracing.""" - return await self._acompletion_wrapper.acompletion(*args, **kwargs) - - def responses(self, *args: Any, **kwargs: Any) -> Any: - """Sync responses with tracing.""" - return self._responses_wrapper.responses(*args, **kwargs) - - async def aresponses(self, *args: Any, **kwargs: Any) -> Any: - """Async responses with tracing.""" - return await self._aresponses_wrapper.aresponses(*args, **kwargs) - - def embedding(self, *args: Any, **kwargs: Any) -> Any: - """Sync embedding with tracing.""" - return self._embedding_wrapper.embedding(*args, **kwargs) - - def moderation(self, *args: Any, **kwargs: Any) -> Any: - """Sync moderation with tracing.""" - return self._moderation_wrapper.moderation(*args, **kwargs) - - -def wrap_litellm(litellm_module: Any) -> LiteLLMWrapper: - """ - Wrap the litellm module to add tracing. - If Braintrust is not configured, nothing will be traced. - - :param litellm_module: The litellm module - :return: Wrapped litellm module with tracing - """ - return LiteLLMWrapper(litellm_module) - - -def _update_span_payload_from_params(params: dict[str, Any], input_key: str = "input") -> dict[str, Any]: - """Updates the span payload with the parameters into LiteLLM's completion/acompletion methods.""" - span_info_d = params.pop("span_info", {}) - - params = prettify_params(params) - input_data = params.pop(input_key, None) - model = params.pop("model", None) - - return merge_dicts( - span_info_d, - {"input": input_data, "metadata": {**params, "provider": "litellm", "model": model}}, - ) - - -def _parse_metrics_from_usage(usage: Any) -> dict[str, Any]: - """Parse usage metrics from API response.""" - # For simplicity, this function handles all the different APIs - metrics: dict[str, Any] = {} - - if not usage: - return metrics - - # This might be a dict or a Usage object that can be cast to a dict - usage = _try_to_dict(usage) - if not isinstance(usage, dict): - return metrics # unexpected - - for oai_name, value in usage.items(): - if oai_name.endswith("_tokens_details"): - # handle `_tokens_detail` dicts - if not isinstance(value, dict): - continue # unexpected - raw_prefix = oai_name[: -len("_tokens_details")] - prefix = TOKEN_PREFIX_MAP.get(raw_prefix, raw_prefix) - for k, v in value.items(): - if is_numeric(v): - metrics[f"{prefix}_{k}"] = v - elif is_numeric(value): - name = TOKEN_NAME_MAP.get(oai_name, oai_name) - metrics[name] = value - - return metrics - - - -def prettify_params(params: dict[str, Any]) -> dict[str, Any]: - """Clean up parameters by filtering out NOT_GIVEN values and serializing response_format.""" - # Filter out NOT_GIVEN parameters - # https://linear.app/braintrustdata/issue/BRA-2467 - # ret = {k: v for k, v in params.items() if not _is_not_given(v)} - ret = {k: v for k, v in params.items()} - - if "response_format" in ret: - ret["response_format"] = serialize_response_format(ret["response_format"]) - return ret - - -def _try_to_dict(obj: Any) -> dict[str, Any] | Any: - """Try to convert an object to a dictionary.""" - if isinstance(obj, dict): - return obj - # convert a pydantic object to a dict - if hasattr(obj, "model_dump") and callable(obj.model_dump): - try: - result = obj.model_dump() - if isinstance(result, dict): - return result - except Exception: - pass - # deprecated pydantic method, try model_dump first. - if hasattr(obj, "dict") and callable(obj.dict): - try: - result = obj.dict() - if isinstance(result, dict): - return result - except Exception: - pass - return obj - - -def serialize_response_format(response_format: Any) -> Any: - """Serialize response format for logging.""" - try: - from pydantic import BaseModel - except ImportError: - return response_format - - if isinstance(response_format, type) and issubclass(response_format, BaseModel): - return dict( - type="json_schema", - json_schema=dict( - name=response_format.__name__, - schema=response_format.model_json_schema(), - ), - ) - else: - return response_format - - -def patch_litellm() -> bool: - """ - Patch LiteLLM to add Braintrust tracing. - - This wraps litellm.completion and litellm.acompletion to automatically - create Braintrust spans with detailed token metrics, timing, and costs. - - Returns: - True if LiteLLM was patched (or already patched), False if LiteLLM is not installed. - - Example: - ```python - import braintrust - braintrust.patch_litellm() - - import litellm - from braintrust import init_logger - - logger = init_logger(project="my-project") - response = litellm.completion( - model="gpt-4o-mini", - messages=[{"role": "user", "content": "Hello"}] - ) - ``` - """ - try: - import litellm - - if not hasattr(litellm, "_braintrust_wrapped"): - wrapped = wrap_litellm(litellm) - litellm.completion = wrapped.completion - litellm.acompletion = wrapped.acompletion - litellm.responses = wrapped.responses - litellm.aresponses = wrapped.aresponses - litellm._braintrust_wrapped = True - return True - except ImportError: - return False diff --git a/py/src/braintrust/wrappers/openai.py b/py/src/braintrust/wrappers/openai.py deleted file mode 100644 index 82bb39031..000000000 --- a/py/src/braintrust/wrappers/openai.py +++ /dev/null @@ -1,317 +0,0 @@ -""" -Exports `BraintrustTracingProcessor`, a `tracing.TracingProcessor` that logs traces to Braintrust. -""" - -import datetime -from typing import Any - -import braintrust -from agents import tracing -from braintrust.logger import NOOP_SPAN - - -def _span_type(span: tracing.Span[Any]) -> braintrust.SpanTypeAttribute: - if span.span_data.type in ["agent", "handoff", "custom", "speech_group"]: - return braintrust.SpanTypeAttribute.TASK - elif span.span_data.type in ["function", "guardrail", "mcp_tools"]: - return braintrust.SpanTypeAttribute.TOOL - elif span.span_data.type in ["generation", "response", "transcription", "speech"]: - return braintrust.SpanTypeAttribute.LLM - else: - return braintrust.SpanTypeAttribute.TASK - - -def _span_name(span: tracing.Span[Any]) -> str: - # TODO(sachin): span name should also come from the span_data. - if ( - isinstance(span.span_data, tracing.AgentSpanData) - or isinstance(span.span_data, tracing.FunctionSpanData) - or isinstance(span.span_data, tracing.GuardrailSpanData) - or isinstance(span.span_data, tracing.CustomSpanData) - ): - return span.span_data.name - elif isinstance(span.span_data, tracing.GenerationSpanData): - return "Generation" - elif isinstance(span.span_data, tracing.ResponseSpanData): - return "Response" - elif isinstance(span.span_data, tracing.HandoffSpanData): - return "Handoff" - elif isinstance(span.span_data, tracing.MCPListToolsSpanData): - if span.span_data.server: - return f"List Tools ({span.span_data.server})" - return "MCP List Tools" - elif isinstance(span.span_data, tracing.TranscriptionSpanData): - return "Transcription" - elif isinstance(span.span_data, tracing.SpeechSpanData): - return "Speech" - elif isinstance(span.span_data, tracing.SpeechGroupSpanData): - return "Speech Group" - else: - return "Unknown" - - -def _timestamp_from_maybe_iso(timestamp: str | None) -> float | None: - if timestamp is None: - return None - return datetime.datetime.fromisoformat(timestamp).timestamp() - - -def _maybe_timestamp_elapsed(end: str | None, start: str | None) -> float | None: - if start is None or end is None: - return None - return (datetime.datetime.fromisoformat(end) - datetime.datetime.fromisoformat(start)).total_seconds() - - -class BraintrustTracingProcessor(tracing.TracingProcessor): - """ - `BraintrustTracingProcessor` is a `tracing.TracingProcessor` that logs traces to Braintrust. - - Args: - logger: A `braintrust.Span` or `braintrust.Experiment` or `braintrust.Logger` to use for logging. - If `None`, the current span, experiment, or logger will be selected exactly as in `braintrust.start_span`. - """ - - def __init__(self, logger: braintrust.Span | braintrust.Experiment | braintrust.Logger | None = None): - self._logger = logger - self._spans: dict[str, braintrust.Span] = {} - self._first_input: dict[str, Any] = {} - self._last_output: dict[str, Any] = {} - - def on_trace_start(self, trace: tracing.Trace) -> None: - trace_meta = trace.export() or {} - metadata = { - "group_id": trace_meta.get("group_id"), - **(trace_meta.get("metadata") or {}), - } - - current_context = braintrust.current_span() - if current_context != NOOP_SPAN: - span = current_context.start_span( - name=trace.name, - span_attributes={"type": "task", "name": trace.name}, - metadata=metadata, - ) - elif self._logger is not None: - span = self._logger.start_span( - span_attributes={"type": "task", "name": trace.name}, - span_id=trace.trace_id, - root_span_id=trace.trace_id, - metadata=metadata, - # TODO(sachin): Add start time when SDK provides it. - # start_time=_timestamp_from_maybe_iso(trace.started_at), - ) - else: - span = braintrust.start_span( - id=trace.trace_id, - span_attributes={"type": "task", "name": trace.name}, - metadata=metadata, - # TODO(sachin): Add start time when SDK provides it. - # start_time=_timestamp_from_maybe_iso(trace.started_at), - ) - if span != NOOP_SPAN: - span.set_current() - self._spans[trace.trace_id] = span - - def on_trace_end(self, trace: tracing.Trace) -> None: - span = self._spans.pop(trace.trace_id) - # Get the first input and last output for this specific trace - trace_first_input = self._first_input.pop(trace.trace_id, None) - trace_last_output = self._last_output.pop(trace.trace_id, None) - span.log(input=trace_first_input, output=trace_last_output) - span.end() - span.unset_current() - # TODO(sachin): Add end time when SDK provides it. - # span.end(_timestamp_from_maybe_iso(trace.ended_at)) - - def _agent_log_data(self, span: tracing.Span[tracing.AgentSpanData]) -> dict[str, Any]: - return { - "metadata": { - "tools": span.span_data.tools, - "handoffs": span.span_data.handoffs, - "output_type": span.span_data.output_type, - } - } - - def _response_log_data(self, span: tracing.Span[tracing.ResponseSpanData]) -> dict[str, Any]: - data = {} - if span.span_data.input is not None: - data["input"] = span.span_data.input - if span.span_data.response is not None: - data["output"] = span.span_data.response.output - if span.span_data.response is not None: - data["metadata"] = span.span_data.response.metadata or {} - data["metadata"].update( - span.span_data.response.model_dump(exclude={"input", "output", "metadata", "usage"}) - ) - - data["metrics"] = {} - ttft = _maybe_timestamp_elapsed(span.ended_at, span.started_at) - if ttft is not None: - data["metrics"]["time_to_first_token"] = ttft - if span.span_data.response is not None and span.span_data.response.usage is not None: - data["metrics"]["tokens"] = span.span_data.response.usage.total_tokens - data["metrics"]["prompt_tokens"] = span.span_data.response.usage.input_tokens - data["metrics"]["completion_tokens"] = span.span_data.response.usage.output_tokens - - return data - - def _function_log_data(self, span: tracing.Span[tracing.FunctionSpanData]) -> dict[str, Any]: - return { - "input": span.span_data.input, - "output": span.span_data.output, - } - - def _handoff_log_data(self, span: tracing.Span[tracing.HandoffSpanData]) -> dict[str, Any]: - return { - "metadata": { - "from_agent": span.span_data.from_agent, - "to_agent": span.span_data.to_agent, - } - } - - def _guardrail_log_data(self, span: tracing.Span[tracing.GuardrailSpanData]) -> dict[str, Any]: - return { - "metadata": { - "triggered": span.span_data.triggered, - } - } - - def _generation_log_data(self, span: tracing.Span[tracing.GenerationSpanData]) -> dict[str, Any]: - metrics = {} - ttft = _maybe_timestamp_elapsed(span.ended_at, span.started_at) - - if ttft is not None: - metrics["time_to_first_token"] = ttft - - usage = span.span_data.usage or {} - if "prompt_tokens" in usage: - metrics["prompt_tokens"] = usage["prompt_tokens"] - elif "input_tokens" in usage: - metrics["prompt_tokens"] = usage["input_tokens"] - - if "completion_tokens" in usage: - metrics["completion_tokens"] = usage["completion_tokens"] - elif "output_tokens" in usage: - metrics["completion_tokens"] = usage["output_tokens"] - - if "total_tokens" in usage: - metrics["tokens"] = usage["total_tokens"] - elif "input_tokens" in usage and "output_tokens" in usage: - metrics["tokens"] = usage["input_tokens"] + usage["output_tokens"] - - return { - "input": span.span_data.input, - "output": span.span_data.output, - "metadata": { - "model": span.span_data.model, - "model_config": span.span_data.model_config, - }, - "metrics": metrics, - } - - def _custom_log_data(self, span: tracing.Span[tracing.CustomSpanData]) -> dict[str, Any]: - return span.span_data.data - - def _mcp_list_tools_log_data(self, span: tracing.Span[tracing.MCPListToolsSpanData]) -> dict[str, Any]: - return { - "output": span.span_data.result, - "metadata": { - "server": span.span_data.server, - } - } - - def _transcription_log_data(self, span: tracing.Span[tracing.TranscriptionSpanData]) -> dict[str, Any]: - return { - "input": span.span_data.input, - "output": span.span_data.output, - "metadata": { - "model": span.span_data.model, - "model_config": span.span_data.model_config, - } - } - - def _speech_log_data(self, span: tracing.Span[tracing.SpeechSpanData]) -> dict[str, Any]: - return { - "input": span.span_data.input, - "output": span.span_data.output, - "metadata": { - "model": span.span_data.model, - "model_config": span.span_data.model_config, - } - } - - def _speech_group_log_data(self, span: tracing.Span[tracing.SpeechGroupSpanData]) -> dict[str, Any]: - return { - "input": span.span_data.input, - } - - def _log_data(self, span: tracing.Span[Any]) -> dict[str, Any]: - if isinstance(span.span_data, tracing.AgentSpanData): - return self._agent_log_data(span) - elif isinstance(span.span_data, tracing.ResponseSpanData): - return self._response_log_data(span) - elif isinstance(span.span_data, tracing.FunctionSpanData): - return self._function_log_data(span) - elif isinstance(span.span_data, tracing.HandoffSpanData): - return self._handoff_log_data(span) - elif isinstance(span.span_data, tracing.GuardrailSpanData): - return self._guardrail_log_data(span) - elif isinstance(span.span_data, tracing.GenerationSpanData): - return self._generation_log_data(span) - elif isinstance(span.span_data, tracing.CustomSpanData): - return self._custom_log_data(span) - elif isinstance(span.span_data, tracing.MCPListToolsSpanData): - return self._mcp_list_tools_log_data(span) - elif isinstance(span.span_data, tracing.TranscriptionSpanData): - return self._transcription_log_data(span) - elif isinstance(span.span_data, tracing.SpeechSpanData): - return self._speech_log_data(span) - elif isinstance(span.span_data, tracing.SpeechGroupSpanData): - return self._speech_group_log_data(span) - else: - return {} - - def on_span_start(self, span: tracing.Span[tracing.SpanData]) -> None: - if span.parent_id is not None: - parent = self._spans[span.parent_id] - else: - parent = self._spans[span.trace_id] - created_span = parent.start_span( - id=span.span_id, - name=_span_name(span), - type=_span_type(span), - start_time=_timestamp_from_maybe_iso(span.started_at), - ) - self._spans[span.span_id] = created_span - - # Set the span as current so current_span() calls will return it - created_span.set_current() - - def on_span_end(self, span: tracing.Span[tracing.SpanData]) -> None: - s = self._spans.pop(span.span_id) - event = dict(error=span.error, **self._log_data(span)) - s.log(**event) - s.unset_current() - s.end(_timestamp_from_maybe_iso(span.ended_at)) - - input_ = event.get("input") - output = event.get("output") - # Store first input and last output per trace_id - trace_id = span.trace_id - if trace_id not in self._first_input and input_ is not None: - self._first_input[trace_id] = input_ - - if output is not None: - self._last_output[trace_id] = output - - def shutdown(self) -> None: - if self._logger is not None: - self._logger.flush() - else: - braintrust.flush() - - def force_flush(self) -> None: - if self._logger is not None: - self._logger.flush() - else: - braintrust.flush() diff --git a/py/src/braintrust/wrappers/pydantic_ai.py b/py/src/braintrust/wrappers/pydantic_ai.py deleted file mode 100644 index c522ec5af..000000000 --- a/py/src/braintrust/wrappers/pydantic_ai.py +++ /dev/null @@ -1,1325 +0,0 @@ -import asyncio -import logging -import sys -import time -from contextlib import AbstractAsyncContextManager -from typing import Any - -from braintrust.bt_json import bt_safe_deep_copy -from braintrust.logger import NOOP_SPAN, Attachment, current_span, init_logger, start_span -from braintrust.span_types import SpanTypeAttribute -from wrapt import wrap_function_wrapper - -logger = logging.getLogger(__name__) - -__all__ = ["setup_pydantic_ai"] - - -def setup_pydantic_ai( - api_key: str | None = None, - project_id: str | None = None, - project_name: str | None = None, -) -> bool: - """ - Setup Braintrust integration with Pydantic AI. Will automatically patch Pydantic AI Agents and direct API functions for automatic tracing. - - Args: - api_key (Optional[str]): Braintrust API key. - project_id (Optional[str]): Braintrust project ID. - project_name (Optional[str]): Braintrust project name. - - Returns: - bool: True if setup was successful, False otherwise. - """ - span = current_span() - if span == NOOP_SPAN: - init_logger(project=project_name, api_key=api_key, project_id=project_id) - - try: - import pydantic_ai.direct as direct_module - from pydantic_ai import Agent - - Agent = wrap_agent(Agent) - - wrap_function_wrapper(direct_module, "model_request", _create_direct_model_request_wrapper()) - wrap_function_wrapper(direct_module, "model_request_sync", _create_direct_model_request_sync_wrapper()) - wrap_function_wrapper(direct_module, "model_request_stream", _create_direct_model_request_stream_wrapper()) - wrap_function_wrapper( - direct_module, "model_request_stream_sync", _create_direct_model_request_stream_sync_wrapper() - ) - - wrap_model_classes() - - return True - except ImportError: - # Not installed - this is expected when using auto_instrument() - return False - - -def wrap_agent(Agent: Any) -> Any: - if _is_patched(Agent): - return Agent - - def _ensure_model_wrapped(instance: Any): - """Ensure the agent's model class is wrapped (lazy wrapping).""" - if hasattr(instance, "_model") and instance._model is not None: - model_class = type(instance._model) - _wrap_concrete_model_class(model_class) - - async def agent_run_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - _ensure_model_wrapped(instance) - input_data, metadata = _build_agent_input_and_metadata(args, kwargs, instance) - - with start_span( - name=f"agent_run [{instance.name}]" if hasattr(instance, "name") and instance.name else "agent_run", - type=SpanTypeAttribute.LLM, - input=input_data if input_data else None, - metadata=metadata, - ) as agent_span: - start_time = time.time() - result = await wrapped(*args, **kwargs) - end_time = time.time() - - output = _serialize_result_output(result) - metrics = _extract_usage_metrics(result, start_time, end_time) - - agent_span.log(output=output, metrics=metrics) - return result - - wrap_function_wrapper(Agent, "run", agent_run_wrapper) - - def agent_run_sync_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - _ensure_model_wrapped(instance) - input_data, metadata = _build_agent_input_and_metadata(args, kwargs, instance) - - with start_span( - name=f"agent_run_sync [{instance.name}]" - if hasattr(instance, "name") and instance.name - else "agent_run_sync", - type=SpanTypeAttribute.LLM, - input=input_data if input_data else None, - metadata=metadata, - ) as agent_span: - start_time = time.time() - result = wrapped(*args, **kwargs) - end_time = time.time() - - output = _serialize_result_output(result) - metrics = _extract_usage_metrics(result, start_time, end_time) - - agent_span.log(output=output, metrics=metrics) - return result - - wrap_function_wrapper(Agent, "run_sync", agent_run_sync_wrapper) - - def agent_run_stream_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - _ensure_model_wrapped(instance) - input_data, metadata = _build_agent_input_and_metadata(args, kwargs, instance) - agent_name = instance.name if hasattr(instance, "name") else None - span_name = f"agent_run_stream [{agent_name}]" if agent_name else "agent_run_stream" - - return _AgentStreamWrapper( - wrapped(*args, **kwargs), - span_name, - input_data, - metadata, - ) - - wrap_function_wrapper(Agent, "run_stream", agent_run_stream_wrapper) - - def agent_run_stream_sync_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - _ensure_model_wrapped(instance) - input_data, metadata = _build_agent_input_and_metadata(args, kwargs, instance) - agent_name = instance.name if hasattr(instance, "name") else None - span_name = f"agent_run_stream_sync [{agent_name}]" if agent_name else "agent_run_stream_sync" - - # Create span context BEFORE calling wrapped function so internal spans nest under it - span_cm = start_span( - name=span_name, - type=SpanTypeAttribute.LLM, - input=input_data if input_data else None, - metadata=metadata, - ) - span = span_cm.__enter__() - start_time = time.time() - - try: - # Call the original function within the span context - stream_result = wrapped(*args, **kwargs) - return _AgentStreamResultSyncProxy( - stream_result, - span, - span_cm, - start_time, - ) - except Exception: - # Clean up span on error - span_cm.__exit__(*sys.exc_info()) - raise - - wrap_function_wrapper(Agent, "run_stream_sync", agent_run_stream_sync_wrapper) - - async def agent_run_stream_events_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - _ensure_model_wrapped(instance) - input_data, metadata = _build_agent_input_and_metadata(args, kwargs, instance) - - agent_name = instance.name if hasattr(instance, "name") else None - span_name = f"agent_run_stream_events [{agent_name}]" if agent_name else "agent_run_stream_events" - - with start_span( - name=span_name, - type=SpanTypeAttribute.LLM, - input=input_data if input_data else None, - metadata=metadata, - ) as agent_span: - start_time = time.time() - event_count = 0 - final_result = None - - async for event in wrapped(*args, **kwargs): - event_count += 1 - if hasattr(event, "output"): - final_result = event - yield event - - end_time = time.time() - - output = None - metrics = { - "start": start_time, - "end": end_time, - "duration": end_time - start_time, - "event_count": event_count, - } - - if final_result: - output = _serialize_result_output(final_result) - usage_metrics = _extract_usage_metrics(final_result, start_time, end_time) - metrics.update(usage_metrics) - - agent_span.log(output=output, metrics=metrics) - - wrap_function_wrapper(Agent, "run_stream_events", agent_run_stream_events_wrapper) - - Agent._braintrust_patched = True - - return Agent - - -def _create_direct_model_request_wrapper(): - """Create wrapper for direct.model_request().""" - - async def wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - input_data, metadata = _build_direct_model_input_and_metadata(args, kwargs) - - with start_span( - name="model_request", - type=SpanTypeAttribute.LLM, - input=input_data, - metadata=metadata, - ) as span: - start_time = time.time() - result = await wrapped(*args, **kwargs) - end_time = time.time() - - output = _serialize_model_response(result) - metrics = _extract_response_metrics(result, start_time, end_time) - - span.log(output=output, metrics=metrics) - return result - - return wrapper - - -def _create_direct_model_request_sync_wrapper(): - """Create wrapper for direct.model_request_sync().""" - - def wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - input_data, metadata = _build_direct_model_input_and_metadata(args, kwargs) - - with start_span( - name="model_request_sync", - type=SpanTypeAttribute.LLM, - input=input_data, - metadata=metadata, - ) as span: - start_time = time.time() - result = wrapped(*args, **kwargs) - end_time = time.time() - - output = _serialize_model_response(result) - metrics = _extract_response_metrics(result, start_time, end_time) - - span.log(output=output, metrics=metrics) - return result - - return wrapper - - -def _create_direct_model_request_stream_wrapper(): - """Create wrapper for direct.model_request_stream().""" - - def wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - input_data, metadata = _build_direct_model_input_and_metadata(args, kwargs) - - return _DirectStreamWrapper( - wrapped(*args, **kwargs), - "model_request_stream", - input_data, - metadata, - ) - - return wrapper - - -def _create_direct_model_request_stream_sync_wrapper(): - """Create wrapper for direct.model_request_stream_sync().""" - - def wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - input_data, metadata = _build_direct_model_input_and_metadata(args, kwargs) - - return _DirectStreamWrapperSync( - wrapped(*args, **kwargs), - "model_request_stream_sync", - input_data, - metadata, - ) - - return wrapper - - -def wrap_model_request(original_func: Any) -> Any: - async def wrapper(*args, **kwargs): - input_data, metadata = _build_direct_model_input_and_metadata(args, kwargs) - - with start_span( - name="model_request", - type=SpanTypeAttribute.LLM, - input=input_data, - metadata=metadata, - ) as span: - start_time = time.time() - result = await original_func(*args, **kwargs) - end_time = time.time() - - output = _serialize_model_response(result) - metrics = _extract_response_metrics(result, start_time, end_time) - - span.log(output=output, metrics=metrics) - return result - - return wrapper - - -def wrap_model_request_sync(original_func: Any) -> Any: - def wrapper(*args, **kwargs): - input_data, metadata = _build_direct_model_input_and_metadata(args, kwargs) - - with start_span( - name="model_request_sync", - type=SpanTypeAttribute.LLM, - input=input_data, - metadata=metadata, - ) as span: - start_time = time.time() - result = original_func(*args, **kwargs) - end_time = time.time() - - output = _serialize_model_response(result) - metrics = _extract_response_metrics(result, start_time, end_time) - - span.log(output=output, metrics=metrics) - return result - - return wrapper - - -def wrap_model_request_stream(original_func: Any) -> Any: - def wrapper(*args, **kwargs): - input_data, metadata = _build_direct_model_input_and_metadata(args, kwargs) - - return _DirectStreamWrapper( - original_func(*args, **kwargs), - "model_request_stream", - input_data, - metadata, - ) - - return wrapper - - -def wrap_model_request_stream_sync(original_func: Any) -> Any: - def wrapper(*args, **kwargs): - input_data, metadata = _build_direct_model_input_and_metadata(args, kwargs) - - return _DirectStreamWrapperSync( - original_func(*args, **kwargs), - "model_request_stream_sync", - input_data, - metadata, - ) - - return wrapper - - -def wrap_model_classes(): - """Wrap Model classes to capture internal model requests made by agents.""" - try: - from pydantic_ai.models import Model - - def wrap_all_subclasses(base_class): - """Recursively wrap all subclasses of a base class.""" - for subclass in base_class.__subclasses__(): - if not getattr(subclass, "__abstractmethods__", None): - try: - _wrap_concrete_model_class(subclass) - except Exception as e: - logger.debug(f"Could not wrap {subclass.__name__}: {e}") - - wrap_all_subclasses(subclass) - - wrap_all_subclasses(Model) - - except Exception as e: - logger.warning(f"Failed to wrap Model classes: {e}") - - -def _build_model_class_input_and_metadata(instance: Any, args: Any, kwargs: Any): - """Build input data and metadata for model class request wrappers. - - Returns: - Tuple of (model_name, display_name, input_data, metadata) - """ - model_name, provider = _extract_model_info_from_model_instance(instance) - display_name = model_name or type(instance).__name__ - - messages = args[0] if len(args) > 0 else kwargs.get("messages") - model_settings = args[1] if len(args) > 1 else kwargs.get("model_settings") - - serialized_messages = _serialize_messages(messages) - - input_data = {"messages": serialized_messages} - if model_settings is not None: - input_data["model_settings"] = bt_safe_deep_copy(model_settings) - - metadata = _build_model_metadata(model_name, provider, model_settings=None) - - return model_name, display_name, input_data, metadata - - -def _wrap_concrete_model_class(model_class: Any): - """Wrap a concrete model class to trace its request methods.""" - if _is_patched(model_class): - return - - async def model_request_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - model_name, display_name, input_data, metadata = _build_model_class_input_and_metadata(instance, args, kwargs) - - with start_span( - name=f"chat {display_name}", - type=SpanTypeAttribute.LLM, - input=input_data, - metadata=metadata, - ) as span: - start_time = time.time() - result = await wrapped(*args, **kwargs) - end_time = time.time() - - output = _serialize_model_response(result) - metrics = _extract_response_metrics(result, start_time, end_time) - - span.log(output=output, metrics=metrics) - return result - - def model_request_stream_wrapper(wrapped: Any, instance: Any, args: Any, kwargs: Any): - model_name, display_name, input_data, metadata = _build_model_class_input_and_metadata(instance, args, kwargs) - - return _DirectStreamWrapper( - wrapped(*args, **kwargs), - f"chat {display_name}", - input_data, - metadata, - ) - - wrap_function_wrapper(model_class, "request", model_request_wrapper) - wrap_function_wrapper(model_class, "request_stream", model_request_stream_wrapper) - model_class._braintrust_patched = True - - -class _AgentStreamWrapper(AbstractAsyncContextManager): - """Wrapper for agent.run_stream() that adds tracing while passing through the stream result.""" - - def __init__(self, stream_cm: Any, span_name: str, input_data: Any, metadata: Any): - self.stream_cm = stream_cm - self.span_name = span_name - self.input_data = input_data - self.metadata = metadata - self.span_cm = None - self.start_time = None - self.stream_result = None - self._enter_task = None - self._first_token_time = None - - async def __aenter__(self): - self._enter_task = asyncio.current_task() - - # Use context manager properly so span stays current - # DON'T pass start_time here - we'll set it via metrics in __aexit__ - self.span_cm = start_span( - name=self.span_name, - type=SpanTypeAttribute.LLM, - input=self.input_data if self.input_data else None, - metadata=self.metadata, - ) - self.span_cm.__enter__() - - # Capture start time right before entering the stream (API call initiation) - self.start_time = time.time() - self.stream_result = await self.stream_cm.__aenter__() - - # Wrap the stream result to capture first token time - return _StreamResultProxy(self.stream_result, self) - - async def __aexit__(self, exc_type, exc_val, exc_tb): - try: - await self.stream_cm.__aexit__(exc_type, exc_val, exc_tb) - finally: - if self.span_cm and self.start_time and self.stream_result: - end_time = time.time() - - output = _serialize_stream_output(self.stream_result) - metrics = _extract_stream_usage_metrics( - self.stream_result, self.start_time, end_time, self._first_token_time - ) - self.span_cm.log(output=output, metrics=metrics) - - # Clean up span context - if self.span_cm: - if asyncio.current_task() is self._enter_task: - self.span_cm.__exit__(None, None, None) - else: - self.span_cm.end() - - return False - - -class _StreamResultProxy: - """Proxy for stream result that captures first token time.""" - - def __init__(self, stream_result: Any, wrapper: _AgentStreamWrapper): - self._stream_result = stream_result - self._wrapper = wrapper - - def __getattr__(self, name: str): - """Delegate all attribute access to the wrapped stream result.""" - attr = getattr(self._stream_result, name) - - # Wrap streaming methods to capture first token time - if callable(attr) and name in ("stream_text", "stream_output"): - - async def wrapped_method(*args, **kwargs): - result = attr(*args, **kwargs) - async for item in result: - if self._wrapper._first_token_time is None: - self._wrapper._first_token_time = time.time() - yield item - - return wrapped_method - - return attr - - -class _DirectStreamWrapper(AbstractAsyncContextManager): - """Wrapper for model_request_stream() that adds tracing while passing through the stream.""" - - def __init__(self, stream_cm: Any, span_name: str, input_data: Any, metadata: Any): - self.stream_cm = stream_cm - self.span_name = span_name - self.input_data = input_data - self.metadata = metadata - self.span_cm = None - self.start_time = None - self.stream = None - self._enter_task = None - self._first_token_time = None - - async def __aenter__(self): - self._enter_task = asyncio.current_task() - - # Use context manager properly so span stays current - # DON'T pass start_time here - we'll set it via metrics in __aexit__ - self.span_cm = start_span( - name=self.span_name, - type=SpanTypeAttribute.LLM, - input=self.input_data if self.input_data else None, - metadata=self.metadata, - ) - self.span_cm.__enter__() - - # Capture start time right before entering the stream (API call initiation) - self.start_time = time.time() - self.stream = await self.stream_cm.__aenter__() - - # Wrap the stream to capture first token time - return _DirectStreamIteratorProxy(self.stream, self) - - async def __aexit__(self, exc_type, exc_val, exc_tb): - try: - await self.stream_cm.__aexit__(exc_type, exc_val, exc_tb) - finally: - if self.span_cm and self.start_time and self.stream: - end_time = time.time() - - try: - final_response = self.stream.get() - output = _serialize_model_response(final_response) - metrics = _extract_response_metrics( - final_response, self.start_time, end_time, self._first_token_time - ) - self.span_cm.log(output=output, metrics=metrics) - except Exception as e: - logger.debug(f"Failed to extract stream output/metrics: {e}") - - # Clean up span context - if self.span_cm: - if asyncio.current_task() is self._enter_task: - self.span_cm.__exit__(None, None, None) - else: - self.span_cm.end() - - return False - - -class _DirectStreamIteratorProxy: - """Proxy for direct stream that captures first token time.""" - - def __init__(self, stream: Any, wrapper: _DirectStreamWrapper): - self._stream = stream - self._wrapper = wrapper - self._iterator = None - - def __getattr__(self, name: str): - """Delegate all attribute access to the wrapped stream.""" - return getattr(self._stream, name) - - def __aiter__(self): - """Return async iterator that captures first token time.""" - # Get the actual async iterator from the stream - self._iterator = self._stream.__aiter__() if hasattr(self._stream, "__aiter__") else self._stream - return self - - async def __anext__(self): - """Capture first token time on first iteration.""" - if self._iterator is None: - # In case __aiter__ wasn't called, initialize it - self._iterator = self._stream.__aiter__() if hasattr(self._stream, "__aiter__") else self._stream - - item = await self._iterator.__anext__() - if self._wrapper._first_token_time is None: - self._wrapper._first_token_time = time.time() - return item - - -class _AgentStreamResultSyncProxy: - """Proxy for agent.run_stream_sync() result that adds tracing while delegating to actual stream result.""" - - def __init__(self, stream_result: Any, span: Any, span_cm: Any, start_time: float): - self._stream_result = stream_result - self._span = span - self._span_cm = span_cm - self._start_time = start_time - self._logged = False - self._finalize_on_del = True - self._first_token_time = None - - def __getattr__(self, name: str): - """Delegate all attribute access to the wrapped stream result.""" - attr = getattr(self._stream_result, name) - - # Wrap any method that returns an iterator to auto-finalize when exhausted - if callable(attr) and name in ("stream_text", "stream_output", "__iter__"): - - def wrapped_method(*args, **kwargs): - try: - iterator = attr(*args, **kwargs) - # If it's an iterator, wrap it - if hasattr(iterator, "__iter__") or hasattr(iterator, "__next__"): - try: - for item in iterator: - if self._first_token_time is None: - self._first_token_time = time.time() - yield item - finally: - self._finalize() - self._finalize_on_del = False # Don't finalize again in __del__ - else: - return iterator - except Exception: - self._finalize() - self._finalize_on_del = False - raise - - return wrapped_method - - return attr - - def _finalize(self): - """Log metrics and close span.""" - if self._span and not self._logged and self._stream_result: - try: - end_time = time.time() - output = _serialize_stream_output(self._stream_result) - metrics = _extract_stream_usage_metrics( - self._stream_result, self._start_time, end_time, self._first_token_time - ) - self._span.log(output=output, metrics=metrics) - self._logged = True - finally: - try: - self._span_cm.__exit__(None, None, None) - except Exception: - pass - - def __del__(self): - """Ensure span is closed when proxy is destroyed.""" - if self._finalize_on_del: - self._finalize() - - -class _DirectStreamWrapperSync: - """Wrapper for model_request_stream_sync() that adds tracing while passing through the stream.""" - - def __init__(self, stream_cm: Any, span_name: str, input_data: Any, metadata: Any): - self.stream_cm = stream_cm - self.span_name = span_name - self.input_data = input_data - self.metadata = metadata - self.span_cm = None - self.start_time = None - self.stream = None - self._first_token_time = None - - def __enter__(self): - # Use context manager properly so span stays current - # DON'T pass start_time here - we'll set it via metrics in __exit__ - self.span_cm = start_span( - name=self.span_name, - type=SpanTypeAttribute.LLM, - input=self.input_data if self.input_data else None, - metadata=self.metadata, - ) - span = self.span_cm.__enter__() - - # Capture start time right before entering the stream (API call initiation) - self.start_time = time.time() - self.stream = self.stream_cm.__enter__() - - # Wrap the stream to capture first token time - return _DirectStreamIteratorSyncProxy(self.stream, self) - - def __exit__(self, exc_type, exc_val, exc_tb): - try: - self.stream_cm.__exit__(exc_type, exc_val, exc_tb) - finally: - if self.span_cm and self.start_time and self.stream: - end_time = time.time() - - try: - final_response = self.stream.get() - output = _serialize_model_response(final_response) - metrics = _extract_response_metrics( - final_response, self.start_time, end_time, self._first_token_time - ) - self.span_cm.log(output=output, metrics=metrics) - except Exception as e: - logger.debug(f"Failed to extract stream output/metrics: {e}") - - # Always clean up span context - if self.span_cm: - self.span_cm.__exit__(None, None, None) - - return False - - -class _DirectStreamIteratorSyncProxy: - """Proxy for direct stream (sync) that captures first token time.""" - - def __init__(self, stream: Any, wrapper: _DirectStreamWrapperSync): - self._stream = stream - self._wrapper = wrapper - self._iterator = None - - def __getattr__(self, name: str): - """Delegate all attribute access to the wrapped stream.""" - return getattr(self._stream, name) - - def __iter__(self): - """Return iterator that captures first token time.""" - # Get the actual iterator from the stream - self._iterator = self._stream.__iter__() if hasattr(self._stream, "__iter__") else self._stream - return self - - def __next__(self): - """Capture first token time on first iteration.""" - if self._iterator is None: - # In case __iter__ wasn't called, initialize it - self._iterator = self._stream.__iter__() if hasattr(self._stream, "__iter__") else self._stream - - item = self._iterator.__next__() - if self._wrapper._first_token_time is None: - self._wrapper._first_token_time = time.time() - return item - - -def _serialize_user_prompt(user_prompt: Any) -> Any: - """Serialize user prompt, handling BinaryContent and other types.""" - if user_prompt is None: - return None - - if isinstance(user_prompt, str): - return user_prompt - - if isinstance(user_prompt, list): - return [_serialize_content_part(part) for part in user_prompt] - - return _serialize_content_part(user_prompt) - - -def _serialize_content_part(part: Any) -> Any: - """Serialize a content part, handling BinaryContent specially. - - This function handles: - - BinaryContent: converts to Braintrust Attachment - - Parts with nested content (UserPromptPart): recursively serializes content items - - Strings: passes through unchanged - - Other objects: converts to dict via model_dump - """ - if part is None: - return None - - if hasattr(part, "data") and hasattr(part, "media_type") and hasattr(part, "kind"): - if part.kind == "binary": - data = part.data - media_type = part.media_type - - extension = media_type.split("/")[1] if "/" in media_type else "bin" - filename = f"file.{extension}" - - attachment = Attachment(data=data, filename=filename, content_type=media_type) - return {"type": "binary", "attachment": attachment, "media_type": media_type} - - if hasattr(part, "content"): - content = part.content - if isinstance(content, list): - serialized_content = [_serialize_content_part(item) for item in content] - result = bt_safe_deep_copy(part) - if isinstance(result, dict): - result["content"] = serialized_content - return result - elif content is not None: - serialized_content = _serialize_content_part(content) - result = bt_safe_deep_copy(part) - if isinstance(result, dict): - result["content"] = serialized_content - return result - - if isinstance(part, str): - return part - - return bt_safe_deep_copy(part) - - -def _serialize_messages(messages: Any) -> Any: - """Serialize messages list.""" - if not messages: - return [] - - result = [] - for msg in messages: - if hasattr(msg, "parts") and msg.parts: - original_parts = msg.parts - serialized_parts = [_serialize_content_part(p) for p in original_parts] - - # Use model_dump with exclude to avoid serializing parts field prematurely - if hasattr(msg, "model_dump"): - try: - serialized_msg = msg.model_dump(exclude={"parts"}, exclude_none=True) - except (TypeError, ValueError): - # If exclude parameter not supported, fall back to bt_safe_deep_copy - serialized_msg = bt_safe_deep_copy(msg) - else: - serialized_msg = bt_safe_deep_copy(msg) - - if isinstance(serialized_msg, dict): - serialized_msg["parts"] = serialized_parts - else: - serialized_msg = bt_safe_deep_copy(msg) - - result.append(serialized_msg) - - return result - - -def _serialize_result_output(result: Any) -> Any: - """Serialize agent run result output.""" - if not result: - return None - - output_dict = {} - - if hasattr(result, "output"): - output_dict["output"] = bt_safe_deep_copy(result.output) - - if hasattr(result, "response"): - output_dict["response"] = _serialize_model_response(result.response) - - return output_dict if output_dict else bt_safe_deep_copy(result) - - -def _serialize_stream_output(stream_result: Any) -> Any: - """Serialize stream result output.""" - if not stream_result: - return None - - output_dict = {} - - if hasattr(stream_result, "response"): - output_dict["response"] = _serialize_model_response(stream_result.response) - - return output_dict if output_dict else None - - -def _serialize_model_response(response: Any) -> Any: - """Serialize a model response.""" - if not response: - return None - - response_dict = bt_safe_deep_copy(response) - - if hasattr(response, "parts") and isinstance(response_dict, dict): - response_dict["parts"] = [_serialize_content_part(p) for p in response.parts] - - return response_dict - - -def _extract_model_info_from_model_instance(model: Any) -> tuple[str | None, str | None]: - """Extract model name and provider from a model instance. - - Args: - model: A Pydantic AI model instance (OpenAIChatModel, AnthropicModel, etc.) - - Returns: - Tuple of (model_name, provider) - """ - if not model: - return None, None - - if isinstance(model, str): - return _parse_model_string(model) - - if hasattr(model, "model_name"): - model_name = model.model_name - class_name = type(model).__name__ - provider = None - if "OpenAI" in class_name: - provider = "openai" - elif "Anthropic" in class_name: - provider = "anthropic" - elif "Gemini" in class_name: - provider = "gemini" - elif "Groq" in class_name: - provider = "groq" - elif "Mistral" in class_name: - provider = "mistral" - elif "VertexAI" in class_name: - provider = "vertexai" - - return model_name, provider - - if hasattr(model, "name"): - return _parse_model_string(model.name) - - return None, None - - -def _extract_model_info(agent: Any) -> tuple[str | None, str | None]: - """Extract model name and provider from agent. - - Args: - agent: A Pydantic AI Agent instance - - Returns: - Tuple of (model_name, provider) - """ - if not hasattr(agent, "model"): - return None, None - - return _extract_model_info_from_model_instance(agent.model) - - -def _build_model_metadata(model_name: str | None, provider: str | None, model_settings: Any = None) -> dict[str, Any]: - """Build metadata dictionary with model info. - - Args: - model_name: The model name (e.g., "gpt-4o") - provider: The provider (e.g., "openai") - model_settings: Optional model settings to include - - Returns: - Dictionary of metadata - """ - metadata = {} - if model_name: - metadata["model"] = model_name - if provider: - metadata["provider"] = provider - if model_settings: - metadata["model_settings"] = bt_safe_deep_copy(model_settings) - return metadata - - -def _parse_model_string(model: Any) -> tuple[str | None, str | None]: - """Parse model string to extract provider and model name. - - Pydantic AI uses format: "provider:model-name" (e.g., "openai:gpt-4o") - """ - if not model: - return None, None - - model_str = str(model) - - if ":" in model_str: - parts = model_str.split(":", 1) - return parts[1], parts[0] # (model_name, provider) - - return model_str, None - - -def _extract_usage_metrics(result: Any, start_time: float, end_time: float) -> dict[str, float] | None: - """Extract usage metrics from agent run result.""" - metrics: dict[str, float] = {} - - metrics["start"] = start_time - metrics["end"] = end_time - metrics["duration"] = end_time - start_time - - usage = None - if hasattr(result, "response"): - try: - response = result.response - if hasattr(response, "usage"): - usage = response.usage - except (AttributeError, ValueError): - pass - - if usage is None and hasattr(result, "usage"): - usage = result.usage - - if usage is None: - return metrics - - if hasattr(usage, "input_tokens"): - input_tokens = usage.input_tokens - if input_tokens is not None: - metrics["prompt_tokens"] = float(input_tokens) - - if hasattr(usage, "output_tokens"): - output_tokens = usage.output_tokens - if output_tokens is not None: - metrics["completion_tokens"] = float(output_tokens) - - if hasattr(usage, "total_tokens"): - total_tokens = usage.total_tokens - if total_tokens is not None: - metrics["tokens"] = float(total_tokens) - - if hasattr(usage, "cache_read_tokens") and usage.cache_read_tokens is not None: - metrics["prompt_cached_tokens"] = float(usage.cache_read_tokens) - - if hasattr(usage, "cache_write_tokens") and usage.cache_write_tokens is not None: - metrics["prompt_cache_creation_tokens"] = float(usage.cache_write_tokens) - - if hasattr(usage, "input_audio_tokens") and usage.input_audio_tokens is not None: - metrics["prompt_audio_tokens"] = float(usage.input_audio_tokens) - - if hasattr(usage, "output_audio_tokens") and usage.output_audio_tokens is not None: - metrics["completion_audio_tokens"] = float(usage.output_audio_tokens) - - if hasattr(usage, "details") and isinstance(usage.details, dict): - details = usage.details - - if "reasoning_tokens" in details: - metrics["completion_reasoning_tokens"] = float(details["reasoning_tokens"]) - - if "cached_tokens" in details: - metrics["prompt_cached_tokens"] = float(details["cached_tokens"]) - - return metrics if metrics else None - - -def _extract_stream_usage_metrics( - stream_result: Any, start_time: float, end_time: float, first_token_time: float | None -) -> dict[str, float] | None: - """Extract usage metrics from stream result.""" - metrics: dict[str, float] = {} - - metrics["start"] = start_time - metrics["end"] = end_time - metrics["duration"] = end_time - start_time - - if first_token_time: - metrics["time_to_first_token"] = first_token_time - start_time - - if hasattr(stream_result, "usage"): - usage_func = stream_result.usage - if callable(usage_func): - usage = usage_func() - else: - usage = usage_func - - if usage: - if hasattr(usage, "input_tokens") and usage.input_tokens is not None: - metrics["prompt_tokens"] = float(usage.input_tokens) - - if hasattr(usage, "output_tokens") and usage.output_tokens is not None: - metrics["completion_tokens"] = float(usage.output_tokens) - - if hasattr(usage, "total_tokens") and usage.total_tokens is not None: - metrics["tokens"] = float(usage.total_tokens) - - if hasattr(usage, "cache_read_tokens") and usage.cache_read_tokens is not None: - metrics["prompt_cached_tokens"] = float(usage.cache_read_tokens) - - if hasattr(usage, "cache_write_tokens") and usage.cache_write_tokens is not None: - metrics["prompt_cache_creation_tokens"] = float(usage.cache_write_tokens) - - return metrics if metrics else None - - -def _extract_response_metrics( - response: Any, start_time: float, end_time: float, first_token_time: float | None = None -) -> dict[str, float] | None: - """Extract metrics from model response.""" - metrics: dict[str, float] = {} - - metrics["start"] = start_time - metrics["end"] = end_time - metrics["duration"] = end_time - start_time - - if first_token_time: - metrics["time_to_first_token"] = first_token_time - start_time - - if hasattr(response, "usage") and response.usage: - usage = response.usage - - if hasattr(usage, "input_tokens") and usage.input_tokens is not None: - metrics["prompt_tokens"] = float(usage.input_tokens) - - if hasattr(usage, "output_tokens") and usage.output_tokens is not None: - metrics["completion_tokens"] = float(usage.output_tokens) - - if hasattr(usage, "total_tokens") and usage.total_tokens is not None: - metrics["tokens"] = float(usage.total_tokens) - - if hasattr(usage, "cache_read_tokens") and usage.cache_read_tokens is not None: - metrics["prompt_cached_tokens"] = float(usage.cache_read_tokens) - - if hasattr(usage, "cache_write_tokens") and usage.cache_write_tokens is not None: - metrics["prompt_cache_creation_tokens"] = float(usage.cache_write_tokens) - - # Extract reasoning tokens for reasoning models (o1/o3) - if hasattr(usage, "details") and usage.details is not None: - if hasattr(usage.details, "reasoning_tokens") and usage.details.reasoning_tokens is not None: - metrics["completion_reasoning_tokens"] = float(usage.details.reasoning_tokens) - - return metrics if metrics else None - - -def _is_patched(obj: Any) -> bool: - """Check if object is already patched. - - For classes we check __dict__ directly because getattr walks the MRO. - Without this, wrapping WrapperModel first causes InstrumentedModel to - appear already-patched (it inherits the flag), so its request() method - is never wrapped and the inner "chat" span is lost. - """ - if isinstance(obj, type): - return obj.__dict__.get("_braintrust_patched", False) - return getattr(obj, "_braintrust_patched", False) - - -def _serialize_type(obj: Any) -> Any: - """Serialize a type/class for logging, handling Pydantic models and other types. - - This is useful for output_type, toolsets, and similar type parameters. - Returns full JSON schema for Pydantic models so engineers can see exactly - what structured output schema was used. - """ - import inspect - - # For sequences of types (like Union types or list of models) - if isinstance(obj, (list, tuple)): - return [_serialize_type(item) for item in obj] - - # Handle Pydantic AI's output wrappers (ToolOutput, NativeOutput, PromptedOutput, TextOutput) - if hasattr(obj, "output"): - # These are wrapper classes with an 'output' field containing the actual type - wrapper_info = {"wrapper": type(obj).__name__} - if hasattr(obj, "name") and obj.name: - wrapper_info["name"] = obj.name - if hasattr(obj, "description") and obj.description: - wrapper_info["description"] = obj.description - wrapper_info["output"] = _serialize_type(obj.output) - return wrapper_info - - # If it's a Pydantic model class, return its full JSON schema - if inspect.isclass(obj): - try: - from pydantic import BaseModel - - if issubclass(obj, BaseModel): - # Return the full JSON schema - includes all field info, descriptions, constraints, etc. - return obj.model_json_schema() - except (ImportError, AttributeError, TypeError): - pass - - # Not a Pydantic model, return class name - return obj.__name__ - - # If it has a __name__ attribute (like functions), use that - if hasattr(obj, "__name__"): - return obj.__name__ - - # Try standard serialization - return bt_safe_deep_copy(obj) - - -def _build_agent_input_and_metadata(args: Any, kwargs: Any, instance: Any) -> tuple[dict[str, Any], dict[str, Any]]: - """Build input data and metadata for agent wrappers. - - Returns: - Tuple of (input_data, metadata) - """ - input_data = {} - - user_prompt = args[0] if len(args) > 0 else kwargs.get("user_prompt") - if user_prompt is not None: - input_data["user_prompt"] = _serialize_user_prompt(user_prompt) - - for key, value in kwargs.items(): - if key == "deps": - continue - elif key == "message_history": - input_data[key] = _serialize_messages(value) if value is not None else None - elif key in ("output_type", "toolsets"): - # These often contain types/classes, use special serialization - input_data[key] = _serialize_type(value) if value is not None else None - elif key == "model_settings": - # model_settings passed to run() goes in INPUT (it's a run() parameter) - input_data[key] = bt_safe_deep_copy(value) if value is not None else None - else: - input_data[key] = bt_safe_deep_copy(value) if value is not None else None - - if "model" in kwargs: - model_name, provider = _parse_model_string(kwargs["model"]) - else: - model_name, provider = _extract_model_info(instance) - - # Extract agent-level configuration for metadata - # Only add to metadata if NOT explicitly passed in kwargs (those go in input) - agent_model_settings = None - if "model_settings" not in kwargs and hasattr(instance, "model_settings") and instance.model_settings is not None: - agent_model_settings = instance.model_settings - - metadata = _build_model_metadata(model_name, provider, agent_model_settings) - - # Extract additional agent configuration (only if not passed as kwargs) - if "name" not in kwargs and hasattr(instance, "name") and instance.name is not None: - metadata["agent_name"] = instance.name - - if "end_strategy" not in kwargs and hasattr(instance, "end_strategy") and instance.end_strategy is not None: - metadata["end_strategy"] = str(instance.end_strategy) - - # Extract output_type if set on agent and not passed as kwarg - # output_type can be a Pydantic model, str, or other types that get converted to JSON schema - if "output_type" not in kwargs and hasattr(instance, "output_type") and instance.output_type is not None: - try: - metadata["output_type"] = _serialize_type(instance.output_type) - except Exception as e: - logger.debug(f"Failed to extract output_type from agent: {e}") - - # Extract toolsets if set on agent and not passed as kwarg - # Toolsets go in INPUT (not metadata) because agent.run() accepts toolsets parameter - if "toolsets" not in kwargs and hasattr(instance, "toolsets"): - try: - toolsets = instance.toolsets - if toolsets: - # Convert toolsets to a list with FULL tool schemas for input - serialized_toolsets = [] - for ts in toolsets: - ts_info = { - "id": getattr(ts, "id", str(type(ts).__name__)), - "label": getattr(ts, "label", None), - } - # Add full tool schemas (not just names) since toolsets can be passed to agent.run() - if hasattr(ts, "tools") and ts.tools: - tools_list = [] - tools_dict = ts.tools - # tools is a dict mapping tool name -> Tool object - for tool_name, tool_obj in tools_dict.items(): - tool_dict = { - "name": tool_name, - } - # Extract description - if hasattr(tool_obj, "description") and tool_obj.description: - tool_dict["description"] = tool_obj.description - # Extract JSON schema for parameters - if hasattr(tool_obj, "function_schema") and hasattr( - tool_obj.function_schema, "json_schema" - ): - tool_dict["parameters"] = tool_obj.function_schema.json_schema - tools_list.append(tool_dict) - ts_info["tools"] = tools_list - serialized_toolsets.append(ts_info) - input_data["toolsets"] = serialized_toolsets - except Exception as e: - logger.debug(f"Failed to extract toolsets from agent: {e}") - - # Extract system_prompt from agent if not passed as kwarg - # Note: system_prompt goes in input (not metadata) because it's semantically part of the LLM input - # Pydantic AI doesn't expose a public API for this, so we access the private _system_prompts - # attribute. This is wrapped in try/except to gracefully handle if the internal structure changes. - if "system_prompt" not in kwargs: - try: - if hasattr(instance, "_system_prompts") and instance._system_prompts: - input_data["system_prompt"] = "\n\n".join(instance._system_prompts) - except Exception as e: - logger.debug(f"Failed to extract system_prompt from agent: {e}") - - return input_data, metadata - - -def _build_direct_model_input_and_metadata(args: Any, kwargs: Any) -> tuple[dict[str, Any], dict[str, Any]]: - """Build input data and metadata for direct model request wrappers. - - Returns: - Tuple of (input_data, metadata) - """ - input_data = {} - - model = args[0] if len(args) > 0 else kwargs.get("model") - if model is not None: - input_data["model"] = str(model) - - messages = args[1] if len(args) > 1 else kwargs.get("messages", []) - if messages: - input_data["messages"] = _serialize_messages(messages) - - for key, value in kwargs.items(): - if key not in ["model", "messages"]: - input_data[key] = bt_safe_deep_copy(value) if value is not None else None - - model_name, provider = _parse_model_string(model) - metadata = _build_model_metadata(model_name, provider) - - return input_data, metadata diff --git a/py/src/braintrust/wrappers/test_agno.py b/py/src/braintrust/wrappers/test_agno.py deleted file mode 100644 index 4fd3d8455..000000000 --- a/py/src/braintrust/wrappers/test_agno.py +++ /dev/null @@ -1,105 +0,0 @@ -# pyright: reportPrivateUsage=false -# pyright: reportMissingParameterType=false -# pyright: reportUnknownMemberType=false -# pyright: reportUnknownParameterType=false -# pyright: reportUnknownVariableType=false -# pyright: reportUnknownArgumentType=false -import pytest -from braintrust import logger -from braintrust.test_helpers import init_test_logger -from braintrust.wrappers.agno import setup_agno -from braintrust.wrappers.test_utils import verify_autoinstrument_script - -TEST_ORG_ID = "test-org-123" -PROJECT_NAME = "test-agno-app" - - -@pytest.fixture -def memory_logger(): - init_test_logger(PROJECT_NAME) - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -@pytest.mark.vcr -def test_agno_simple_agent_execution(memory_logger): - Agent = pytest.importorskip("agno.agent.Agent") - OpenAIChat = pytest.importorskip("agno.models.openai.OpenAIChat") - - setup_agno(project_name=PROJECT_NAME) - - assert not memory_logger.pop() - - # Create and configure the agent - agent = Agent( - name="Author Agent", - model=OpenAIChat(id="gpt-4o-mini"), - instructions="You are librarian. Answer the questions by only replying with the author that wrote the book.", - ) - - response = agent.run("Charlotte's Web") - - # Basic assertion that the agent produced a response - assert response - assert response.content - assert len(response.content) > 0 - - # Check the spans generated - spans = memory_logger.pop() - assert len(spans) > 0 - - # More detailed assertions based on expected span structure - assert len(spans) == 2, f"Expected 2 spans, got {len(spans)}" - - # Check the root span (Agent.run) - root_span = spans[0] - assert root_span["span_attributes"]["name"] == "Author Agent.run" - assert root_span["span_attributes"]["type"].value == "task" - assert root_span["input"]["run_response"]["input"]["input_content"] == "Charlotte's Web" - assert root_span["output"]["content"] == "E.B. White" - assert root_span["output"]["status"] == "COMPLETED" - assert root_span["output"]["model"] == "gpt-4o-mini" - assert root_span["output"]["model_provider"] == "OpenAI" - - # Check metrics in root span - assert "metrics" in root_span - assert root_span["metrics"]["prompt_tokens"] > 0 - assert root_span["metrics"]["completion_tokens"] > 0 - assert ( - root_span["metrics"]["total_tokens"] - == root_span["metrics"]["prompt_tokens"] + root_span["metrics"]["completion_tokens"] - ) - assert root_span["metrics"]["duration"] > 0 - - # Check the LLM span (OpenAI.response) - llm_span = spans[1] - assert llm_span["span_attributes"]["name"] == "OpenAI.response" - assert llm_span["span_attributes"]["type"].value == "llm" - assert llm_span["span_parents"] == [root_span["span_id"]] - assert llm_span["metadata"]["model"] == "gpt-4o-mini" - assert llm_span["metadata"]["provider"] == "OpenAI" - - # Check messages in LLM span input - assert "messages" in llm_span["input"] - messages = llm_span["input"]["messages"] - assert len(messages) == 2 - assert messages[0]["role"] == "system" - assert "librarian" in messages[0]["content"] - assert messages[1]["role"] == "user" - assert messages[1]["content"] == "Charlotte's Web" - - # Check LLM span output - assert llm_span["output"]["content"] == "E.B. White" - - # Check LLM span metrics - assert llm_span["metrics"]["prompt_tokens"] == 38 - assert llm_span["metrics"]["completion_tokens"] == 4 - assert llm_span["metrics"]["tokens"] == 42 - - -class TestAutoInstrumentAgno: - """Tests for auto_instrument() with Agno.""" - - def test_auto_instrument_agno(self): - """Test auto_instrument patches Agno and creates spans.""" - verify_autoinstrument_script("test_auto_agno.py") diff --git a/py/src/braintrust/wrappers/test_anthropic.py b/py/src/braintrust/wrappers/test_anthropic.py deleted file mode 100644 index 5d8da9f3f..000000000 --- a/py/src/braintrust/wrappers/test_anthropic.py +++ /dev/null @@ -1,639 +0,0 @@ -""" -Tests to ensure we reliably wrap the Anthropic API. -""" - -import time - -import anthropic -import pytest -from braintrust import logger -from braintrust.test_helpers import init_test_logger -from braintrust.wrappers.anthropic import wrap_anthropic -from braintrust.wrappers.test_utils import run_in_subprocess, verify_autoinstrument_script - -TEST_ORG_ID = "test-org-123" -PROJECT_NAME = "test-anthropic-app" -MODEL = "claude-3-haiku-20240307" # use the cheapest model since answers dont matter - - -def _get_client(): - return anthropic.Anthropic() - - -def _get_async_client(): - return anthropic.AsyncAnthropic() - - -@pytest.fixture -def memory_logger(): - init_test_logger(PROJECT_NAME) - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -@pytest.mark.vcr -def test_anthropic_messages_create_stream_true(memory_logger): - assert not memory_logger.pop() - - client = wrap_anthropic(_get_client()) - kws = { - "model": MODEL, - "max_tokens": 300, - "messages": [{"role": "user", "content": "What is 3*4?"}], - "stream": True, - } - - start = time.time() - with client.messages.create(**kws) as out: - msgs = [m for m in out] - end = time.time() - - assert msgs # a very coarse grained check that this works - - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["model"] == MODEL - assert span["metadata"]["provider"] == "anthropic" - assert span["metadata"]["max_tokens"] == 300 - assert span["metadata"]["stream"] == True - metrics = span["metrics"] - _assert_metrics_are_valid(metrics, start, end) - assert span["input"] == kws["messages"] - assert span["output"] - assert span["output"]["role"] == "assistant" - assert "12" in span["output"]["content"][0]["text"] - - -@pytest.mark.vcr -def test_anthropic_messages_model_params_inputs(memory_logger): - assert not memory_logger.pop() - client = wrap_anthropic(_get_client()) - - kw = { - "model": MODEL, - "max_tokens": 300, - "system": "just return the number", - "messages": [{"role": "user", "content": "what is 1+1?"}], - "temperature": 0.5, - "top_p": 0.5, - } - - def _with_messages_create(): - return client.messages.create(**kw) - - def _with_messages_stream(): - with client.messages.stream(**kw) as stream: - for msg in stream: - pass - return stream.get_final_message() - - for f in [_with_messages_create, _with_messages_stream]: - msg = f() - assert msg.content[0].text == "2" - - logs = memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - assert log["output"]["role"] == "assistant" - assert "2" in log["output"]["content"][0]["text"] - assert log["metadata"]["model"] == MODEL - assert log["metadata"]["max_tokens"] == 300 - assert log["metadata"]["temperature"] == 0.5 - assert log["metadata"]["top_p"] == 0.5 - - -@pytest.mark.vcr -def test_anthropic_messages_system_prompt_inputs(memory_logger): - assert not memory_logger.pop() - - client = wrap_anthropic(_get_client()) - system = "Today's date is 2024-03-26. Only return the date" - q = [{"role": "user", "content": "what is tomorrow's date? only return the date"}] - - args = { - "messages": q, - "temperature": 0, - "max_tokens": 300, - "system": system, - "model": MODEL, - } - - def _with_messages_create(): - return client.messages.create(**args) - - def _with_messages_stream(): - with client.messages.stream(**args) as stream: - for msg in stream: - pass - return stream.get_final_message() - - for f in [_with_messages_create, _with_messages_stream]: - msg = f() - assert "2024-03-27" in msg.content[0].text - - logs = memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - inputs = log["input"] - assert len(inputs) == 2 - inputs_by_role = {m["role"]: m["content"] for m in inputs} - assert inputs_by_role["system"] == system - assert inputs_by_role["user"] == q[0]["content"] - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_anthropic_messages_create_async(memory_logger): - assert not memory_logger.pop() - - params = { - "model": MODEL, - "max_tokens": 100, - "messages": [{"role": "user", "content": "what is 6+1?, just return the number"}], - } - - client = wrap_anthropic(anthropic.AsyncAnthropic()) - msg = await client.messages.create(**params) - assert "7" in msg.content[0].text - - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["model"] == MODEL - assert span["metadata"]["max_tokens"] == 100 - assert span["input"] == params["messages"] - assert span["output"]["role"] == "assistant" - assert "7" in span["output"]["content"][0]["text"] - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_anthropic_messages_create_async_stream_true(memory_logger): - assert not memory_logger.pop() - - params = { - "model": MODEL, - "max_tokens": 100, - "messages": [{"role": "user", "content": "what is 6+1?, just return the number"}], - "stream": True, - } - - client = wrap_anthropic(anthropic.AsyncAnthropic()) - stream = await client.messages.create(**params) - async for event in stream: - pass - - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["model"] == MODEL - assert span["metadata"]["max_tokens"] == 100 - assert span["input"] == params["messages"] - assert span["output"]["role"] == "assistant" - assert "7" in span["output"]["content"][0]["text"] - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_anthropic_messages_streaming_async(memory_logger): - assert not memory_logger.pop() - - client = wrap_anthropic(_get_async_client()) - msgs_in = [{"role": "user", "content": "what is 1+1?, just return the number"}] - - start = time.time() - msg_out = None - - async with client.messages.stream(max_tokens=1024, messages=msgs_in, model=MODEL) as stream: - async for event in stream: - pass - msg_out = await stream.get_final_message() - assert msg_out.content[0].text == "2" - usage = msg_out.usage - end = time.time() - - logs = memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - assert "user" in str(log["input"]) - assert "1+1" in str(log["input"]) - assert "2" in str(log["output"]) - assert log["project_id"] == PROJECT_NAME - assert log["span_attributes"]["type"] == "llm" - assert log["metadata"]["model"] == MODEL - assert log["metadata"]["max_tokens"] == 1024 - _assert_metrics_are_valid(log["metrics"], start, end) - metrics = log["metrics"] - assert metrics["prompt_tokens"] == usage.input_tokens - assert metrics["completion_tokens"] == usage.output_tokens - assert metrics["tokens"] == usage.input_tokens + usage.output_tokens - assert metrics["prompt_cached_tokens"] == usage.cache_read_input_tokens - assert metrics["prompt_cache_creation_tokens"] == usage.cache_creation_input_tokens - assert log["metadata"]["model"] == MODEL - assert log["metadata"]["max_tokens"] == 1024 - - -@pytest.mark.vcr -def test_anthropic_client_error(memory_logger): - assert not memory_logger.pop() - - client = wrap_anthropic(_get_client()) - - fake_model = "there-is-no-such-model" - msg_in = {"role": "user", "content": "who are you?"} - - try: - client.messages.create(model=fake_model, max_tokens=999, messages=[msg_in]) - except Exception: - pass - else: - raise Exception("should have raised an exception") - - logs = memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - assert log["project_id"] == PROJECT_NAME - assert "404" in log["error"] - - -@pytest.mark.vcr -def test_anthropic_messages_stream_errors(memory_logger): - assert not memory_logger.pop() - - client = wrap_anthropic(_get_client()) - msg_in = {"role": "user", "content": "what is 2+2? (just the number)"} - - try: - with client.messages.stream(model=MODEL, max_tokens=300, messages=[msg_in]) as stream: - raise Exception("fake-error") - except Exception: - pass - else: - raise Exception("should have raised an exception") - - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert "Exception: fake-error" in span["error"] - assert span["metrics"]["end"] > 0 - - -@pytest.mark.vcr -def test_anthropic_messages_streaming_sync(memory_logger): - assert not memory_logger.pop() - - client = wrap_anthropic(_get_client()) - msg_in = {"role": "user", "content": "what is 2+2? (just the number)"} - - start = time.time() - with client.messages.stream(model=MODEL, max_tokens=300, messages=[msg_in]) as stream: - msgs_out = [m for m in stream] - end = time.time() - msg_out = stream.get_final_message() - usage = msg_out.usage - # crudely check that the stream is valid - assert len(msgs_out) > 3 - assert 1 <= len([m for m in msgs_out if m.type == "text"]) - assert msgs_out[0].type == "message_start" - assert msgs_out[-1].type == "message_stop" - - logs = memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - assert "user" in str(log["input"]) - assert "2+2" in str(log["input"]) - assert "4" in str(log["output"]) - assert log["project_id"] == PROJECT_NAME - assert log["span_attributes"]["type"] == "llm" - _assert_metrics_are_valid(log["metrics"], start, end) - assert log["metrics"]["prompt_tokens"] == usage.input_tokens - assert log["metrics"]["completion_tokens"] == usage.output_tokens - assert log["metrics"]["tokens"] == usage.input_tokens + usage.output_tokens - assert log["metrics"]["prompt_cached_tokens"] == usage.cache_read_input_tokens - assert log["metrics"]["prompt_cache_creation_tokens"] == usage.cache_creation_input_tokens - - -@pytest.mark.vcr -def test_anthropic_messages_sync(memory_logger): - assert not memory_logger.pop() - - client = wrap_anthropic(_get_client()) - - msg_in = {"role": "user", "content": "what's 2+2?"} - - start = time.time() - msg = client.messages.create(model=MODEL, max_tokens=300, messages=[msg_in]) - end = time.time() - - text = msg.content[0].text - assert text - - # verify we generated the right spans. - logs = memory_logger.pop() - - assert len(logs) == 1 - log = logs[0] - assert "2+2" in str(log["input"]) - assert "4" in str(log["output"]) - assert log["project_id"] == PROJECT_NAME - assert log["span_id"] - assert log["root_span_id"] - attrs = log["span_attributes"] - assert attrs["type"] == "llm" - assert "anthropic" in attrs["name"] - metrics = log["metrics"] - _assert_metrics_are_valid(metrics, start, end) - assert log["metadata"]["model"] == MODEL - - -def _assert_metrics_are_valid(metrics, start, end): - assert metrics["tokens"] > 0 - assert metrics["prompt_tokens"] > 0 - assert metrics["completion_tokens"] > 0 - assert "time_to_first_token" in metrics - assert metrics["time_to_first_token"] >= 0 - if start and end: - assert start <= metrics["start"] <= metrics["end"] <= end - else: - assert metrics["start"] <= metrics["end"] - - -@pytest.mark.vcr -def test_anthropic_beta_messages_sync(memory_logger): - assert not memory_logger.pop() - - client = wrap_anthropic(_get_client()) - msg_in = {"role": "user", "content": "what's 3+3?"} - - start = time.time() - msg = client.beta.messages.create(model=MODEL, max_tokens=300, messages=[msg_in]) - end = time.time() - - text = msg.content[0].text - assert text - assert "6" in text - - logs = memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - assert "3+3" in str(log["input"]) - assert "6" in str(log["output"]) - assert log["project_id"] == PROJECT_NAME - assert log["span_id"] - assert log["root_span_id"] - attrs = log["span_attributes"] - assert attrs["type"] == "llm" - assert "anthropic" in attrs["name"] - metrics = log["metrics"] - _assert_metrics_are_valid(metrics, start, end) - assert log["metadata"]["model"] == MODEL - - -@pytest.mark.vcr -def test_anthropic_beta_messages_stream_sync(memory_logger): - assert not memory_logger.pop() - - client = wrap_anthropic(_get_client()) - msg_in = {"role": "user", "content": "what is 5+5? (just the number)"} - - start = time.time() - with client.beta.messages.stream(model=MODEL, max_tokens=300, messages=[msg_in]) as stream: - msgs_out = [m for m in stream] - end = time.time() - msg_out = stream.get_final_message() - usage = msg_out.usage - - assert len(msgs_out) > 3 - assert msgs_out[0].type == "message_start" - assert msgs_out[-1].type == "message_stop" - assert "10" in msg_out.content[0].text - - logs = memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - assert "user" in str(log["input"]) - assert "5+5" in str(log["input"]) - assert "10" in str(log["output"]) - assert log["project_id"] == PROJECT_NAME - assert log["span_attributes"]["type"] == "llm" - _assert_metrics_are_valid(log["metrics"], start, end) - assert log["metrics"]["prompt_tokens"] == usage.input_tokens - assert log["metrics"]["completion_tokens"] == usage.output_tokens - assert log["metrics"]["tokens"] == usage.input_tokens + usage.output_tokens - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_anthropic_beta_messages_create_async(memory_logger): - assert not memory_logger.pop() - - params = { - "model": MODEL, - "max_tokens": 100, - "messages": [{"role": "user", "content": "what is 8+2?, just return the number"}], - } - - client = wrap_anthropic(anthropic.AsyncAnthropic()) - msg = await client.beta.messages.create(**params) - assert "10" in msg.content[0].text - - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["model"] == MODEL - assert span["metadata"]["max_tokens"] == 100 - assert span["input"] == params["messages"] - assert span["output"]["role"] == "assistant" - assert "10" in span["output"]["content"][0]["text"] - - -@pytest.mark.vcr(match_on=["method", "scheme", "host", "port", "path", "body"]) # exclude query - varies by SDK version -@pytest.mark.asyncio -async def test_anthropic_beta_messages_streaming_async(memory_logger): - assert not memory_logger.pop() - - client = wrap_anthropic(_get_async_client()) - msgs_in = [{"role": "user", "content": "what is 9+1?, just return the number"}] - - start = time.time() - msg_out = None - - async with client.beta.messages.stream(max_tokens=1024, messages=msgs_in, model=MODEL) as stream: - async for event in stream: - pass - msg_out = await stream.get_final_message() - assert "10" in msg_out.content[0].text - usage = msg_out.usage - end = time.time() - - logs = memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - assert "user" in str(log["input"]) - assert "9+1" in str(log["input"]) - assert "10" in str(log["output"]) - assert log["project_id"] == PROJECT_NAME - assert log["span_attributes"]["type"] == "llm" - assert log["metadata"]["model"] == MODEL - assert log["metadata"]["max_tokens"] == 1024 - _assert_metrics_are_valid(log["metrics"], start, end) - metrics = log["metrics"] - assert metrics["prompt_tokens"] == usage.input_tokens - assert metrics["completion_tokens"] == usage.output_tokens - assert metrics["tokens"] == usage.input_tokens + usage.output_tokens - - -class TestPatchAnthropic: - """Tests for patch_anthropic() / unpatch_anthropic().""" - - def test_patch_anthropic_sets_wrapped_flag(self): - """patch_anthropic() should set __braintrust_wrapped__ on anthropic module.""" - result = run_in_subprocess(""" - from braintrust.wrappers.anthropic import patch_anthropic - import anthropic - - assert not hasattr(anthropic, "__braintrust_wrapped__") - patch_anthropic() - assert hasattr(anthropic, "__braintrust_wrapped__") - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_anthropic_wraps_new_clients(self): - """After patch_anthropic(), new Anthropic() clients should be wrapped.""" - result = run_in_subprocess(""" - from braintrust.wrappers.anthropic import patch_anthropic - patch_anthropic() - - import anthropic - client = anthropic.Anthropic(api_key="test-key") - - # Check that messages is wrapped - messages_type = type(client.messages).__name__ - print(f"messages_type={messages_type}") - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_anthropic_idempotent(self): - """Multiple patch_anthropic() calls should be safe.""" - result = run_in_subprocess(""" - from braintrust.wrappers.anthropic import patch_anthropic - import anthropic - - patch_anthropic() - first_class = anthropic.Anthropic - - patch_anthropic() # Second call - second_class = anthropic.Anthropic - - assert first_class is second_class - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_anthropic_creates_spans(self): - """patch_anthropic() should create spans when making API calls.""" - result = run_in_subprocess(""" - from braintrust.wrappers.anthropic import patch_anthropic - from braintrust.test_helpers import init_test_logger - from braintrust import logger - - # Set up memory logger - init_test_logger("test-auto") - with logger._internal_with_memory_background_logger() as memory_logger: - patch_anthropic() - - import anthropic - client = anthropic.Anthropic() - - # Make a call within a span context - import braintrust - with braintrust.start_span(name="test") as span: - try: - # This will fail without API key, but span should still be created - client.messages.create( - model="claude-3-5-haiku-latest", - max_tokens=100, - messages=[{"role": "user", "content": "hi"}], - ) - except Exception: - pass # Expected without API key - - # Check that spans were logged - spans = memory_logger.pop() - # Should have at least the parent span - assert len(spans) >= 1, f"Expected spans, got {spans}" - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - -class TestPatchAnthropicSpans: - """VCR-based tests verifying that patch_anthropic() produces spans.""" - - @pytest.mark.vcr - def test_patch_anthropic_creates_spans(self, memory_logger): - """patch_anthropic() should create spans when making API calls.""" - from braintrust.wrappers.anthropic import patch_anthropic - - assert not memory_logger.pop() - - patch_anthropic() - client = anthropic.Anthropic() - response = client.messages.create( - model="claude-3-5-haiku-latest", - max_tokens=100, - messages=[{"role": "user", "content": "Say hi"}], - ) - assert response.content[0].text - - # Verify span was created - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["provider"] == "anthropic" - assert "claude" in span["metadata"]["model"] - assert span["input"] - - -class TestPatchAnthropicAsyncSpans: - """VCR-based tests verifying that patch_anthropic() produces spans for async clients.""" - - @pytest.mark.vcr - @pytest.mark.asyncio - async def test_patch_anthropic_async_creates_spans(self, memory_logger): - """patch_anthropic() should create spans for async API calls.""" - from braintrust.wrappers.anthropic import patch_anthropic - - assert not memory_logger.pop() - - patch_anthropic() - client = anthropic.AsyncAnthropic() - response = await client.messages.create( - model="claude-3-5-haiku-latest", - max_tokens=100, - messages=[{"role": "user", "content": "Say hi async"}], - ) - assert response.content[0].text - - # Verify span was created - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["provider"] == "anthropic" - assert "claude" in span["metadata"]["model"] - assert span["input"] - - -class TestAutoInstrumentAnthropic: - """Tests for auto_instrument() with Anthropic.""" - - def test_auto_instrument_anthropic(self): - """Test auto_instrument patches Anthropic, creates spans, and uninstrument works.""" - verify_autoinstrument_script("test_auto_anthropic.py") diff --git a/py/src/braintrust/wrappers/test_dspy.py b/py/src/braintrust/wrappers/test_dspy.py deleted file mode 100644 index a9faa6afe..000000000 --- a/py/src/braintrust/wrappers/test_dspy.py +++ /dev/null @@ -1,177 +0,0 @@ -""" -Tests for DSPy integration with Braintrust. -""" - -import dspy -import pytest -from braintrust import logger -from braintrust.test_helpers import init_test_logger -from braintrust.wrappers.dspy import BraintrustDSpyCallback -from braintrust.wrappers.test_utils import run_in_subprocess, verify_autoinstrument_script - -PROJECT_NAME = "test-dspy-app" -MODEL = "openai/gpt-4o-mini" - - -@pytest.fixture -def memory_logger(): - init_test_logger(PROJECT_NAME) - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -@pytest.mark.vcr -def test_dspy_callback(memory_logger): - """Test DSPy callback logs spans correctly.""" - assert not memory_logger.pop() - - # Configure DSPy with Braintrust callback - lm = dspy.LM(MODEL) - dspy.configure(lm=lm, callbacks=[BraintrustDSpyCallback()]) - - # Use ChainOfThought for a more interesting test - cot = dspy.ChainOfThought("question -> answer") - result = cot(question="What is 2+2?") - - assert result.answer # Verify we got a response - - # Check logged spans - spans = memory_logger.pop() - assert len(spans) >= 2 # Should have module span and LM span - - # Find LM span by checking span_attributes - lm_spans = [s for s in spans if s.get("span_attributes", {}).get("name") == "dspy.lm"] - assert len(lm_spans) >= 1 - - lm_span = lm_spans[0] - # Verify metadata - assert "metadata" in lm_span - assert "model" in lm_span["metadata"] - assert MODEL in lm_span["metadata"]["model"] - - # Verify input/output - assert "input" in lm_span - assert "output" in lm_span - - # Find module span - module_spans = [s for s in spans if "module" in s.get("span_attributes", {}).get("name", "")] - assert len(module_spans) >= 1 - - # Verify span parenting (LM span should have parent) - assert lm_span.get("span_parents") # LM span should have parent - - -class TestPatchDSPy: - """Tests for patch_dspy() / unpatch_dspy().""" - - def test_patch_dspy_sets_wrapped_flag(self): - """patch_dspy() should set __braintrust_wrapped__ on dspy module.""" - result = run_in_subprocess(""" - dspy = __import__("dspy") - from braintrust.wrappers.dspy import patch_dspy - - assert not hasattr(dspy, "__braintrust_wrapped__") - patch_dspy() - assert hasattr(dspy, "__braintrust_wrapped__") - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_dspy_wraps_configure(self): - """After patch_dspy(), dspy.configure() should auto-add BraintrustDSpyCallback.""" - result = run_in_subprocess(""" - from braintrust.wrappers.dspy import patch_dspy, BraintrustDSpyCallback - patch_dspy() - - import dspy - - # Configure without explicitly adding callback - dspy.configure(lm=None) - - # Check that BraintrustDSpyCallback was auto-added - from dspy.dsp.utils.settings import settings - callbacks = settings.callbacks - has_bt_callback = any(isinstance(cb, BraintrustDSpyCallback) for cb in callbacks) - assert has_bt_callback, f"Expected BraintrustDSpyCallback in {callbacks}" - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_dspy_preserves_existing_callbacks(self): - """patch_dspy() should preserve user-provided callbacks.""" - result = run_in_subprocess(""" - from braintrust.wrappers.dspy import patch_dspy, BraintrustDSpyCallback - patch_dspy() - - import dspy - from dspy.utils.callback import BaseCallback - - class MyCallback(BaseCallback): - pass - - my_callback = MyCallback() - dspy.configure(lm=None, callbacks=[my_callback]) - - from dspy.dsp.utils.settings import settings - callbacks = settings.callbacks - - # Should have both callbacks - has_my_callback = any(cb is my_callback for cb in callbacks) - has_bt_callback = any(isinstance(cb, BraintrustDSpyCallback) for cb in callbacks) - - assert has_my_callback, "User callback should be preserved" - assert has_bt_callback, "BraintrustDSpyCallback should be added" - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_dspy_does_not_duplicate_callback(self): - """patch_dspy() should not add duplicate BraintrustDSpyCallback.""" - result = run_in_subprocess(""" - from braintrust.wrappers.dspy import patch_dspy, BraintrustDSpyCallback - patch_dspy() - - import dspy - - # User explicitly adds BraintrustDSpyCallback - bt_callback = BraintrustDSpyCallback() - dspy.configure(lm=None, callbacks=[bt_callback]) - - from dspy.dsp.utils.settings import settings - callbacks = settings.callbacks - - # Should only have one BraintrustDSpyCallback - bt_callbacks = [cb for cb in callbacks if isinstance(cb, BraintrustDSpyCallback)] - assert len(bt_callbacks) == 1, f"Expected 1 BraintrustDSpyCallback, got {len(bt_callbacks)}" - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_dspy_idempotent(self): - """Multiple patch_dspy() calls should be safe.""" - result = run_in_subprocess(""" - from braintrust.wrappers.dspy import patch_dspy - import dspy - - patch_dspy() - patch_dspy() # Second call - should be no-op, not double-wrap - - # Verify configure still works - lm = dspy.LM("openai/gpt-4o-mini") - dspy.configure(lm=lm) - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - -class TestAutoInstrumentDSPy: - """Tests for auto_instrument() with DSPy.""" - - def test_auto_instrument_dspy(self): - """Test auto_instrument patches DSPy, creates spans, and uninstrument works.""" - verify_autoinstrument_script("test_auto_dspy.py") diff --git a/py/src/braintrust/wrappers/test_google_genai.py b/py/src/braintrust/wrappers/test_google_genai.py deleted file mode 100644 index 02fc21f55..000000000 --- a/py/src/braintrust/wrappers/test_google_genai.py +++ /dev/null @@ -1,648 +0,0 @@ -import os -import time -from pathlib import Path - -import pytest -from braintrust import logger -from braintrust.test_helpers import init_test_logger -from braintrust.wrappers.google_genai import setup_genai -from braintrust.wrappers.test_utils import verify_autoinstrument_script -from google.genai import types -from google.genai.client import Client - -PROJECT_NAME = "test-genai-app" -MODEL = "gemini-2.0-flash-001" -FIXTURES_DIR = Path(__file__).parent.parent.parent.parent.parent / "internal/golden/fixtures" - - -@pytest.fixture(scope="module") -def vcr_config(): - """Google-specific VCR config - needs to uppercase HTTP methods.""" - record_mode = "none" if (os.environ.get("CI") or os.environ.get("GITHUB_ACTIONS")) else "once" - - def before_record_request(request): - # Normalize HTTP method to uppercase for consistency (Google API quirk) - request.method = request.method.upper() - return request - - return { - "record_mode": record_mode, - "filter_headers": [ - "authorization", - "x-api-key", - "x-goog-api-key", - ], - "before_record_request": before_record_request, - } - - -@pytest.fixture(scope="module", autouse=True) -def setup_wrapper(): - """Setup genai wrapper once for all tests.""" - setup_genai(project_name=PROJECT_NAME) - - -@pytest.fixture -def memory_logger(): - init_test_logger(PROJECT_NAME) - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -# Helper to assert metrics are valid -def _assert_metrics_are_valid(metrics, start=None, end=None): - assert metrics["tokens"] > 0 - assert metrics["prompt_tokens"] > 0 - assert metrics["completion_tokens"] > 0 - if start and end: - assert start <= metrics["start"] <= metrics["end"] <= end - else: - assert metrics["start"] <= metrics["end"] - - -# Test 1: Basic Completion (Sync) -@pytest.mark.vcr -@pytest.mark.parametrize( - "mode", - ["sync", "stream"], -) -def test_basic_completion(memory_logger, mode): - """Test basic text completion in sync modes.""" - assert not memory_logger.pop() - - client = Client() - start = time.time() - - if mode == "sync": - response = client.models.generate_content( - model=MODEL, - contents="What is the capital of France?", - config=types.GenerateContentConfig( - max_output_tokens=100, - ), - ) - text = response.text - elif mode == "stream": - stream = client.models.generate_content_stream( - model=MODEL, - contents="What is the capital of France?", - config=types.GenerateContentConfig( - max_output_tokens=100, - ), - ) - text = "" - for chunk in stream: - if chunk.text: - text += chunk.text - - end = time.time() - - # Verify response contains expected content - assert "Paris" in text - - # Verify logging - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["model"] == MODEL - assert "What is the capital of France?" in str(span["input"]) - assert span["output"] - assert "Paris" in str(span["output"]) - _assert_metrics_are_valid(span["metrics"], start, end) - - -# Test 1b: Basic Completion (Async) -@pytest.mark.vcr -@pytest.mark.asyncio -@pytest.mark.parametrize( - "mode", - ["async", "async_stream"], -) -async def test_basic_completion_async(memory_logger, mode): - """Test basic text completion in async modes.""" - assert not memory_logger.pop() - - client = Client() - start = time.time() - - if mode == "async": - response = await client.aio.models.generate_content( - model=MODEL, - contents="What is the capital of France?", - config=types.GenerateContentConfig( - max_output_tokens=100, - ), - ) - text = response.text - elif mode == "async_stream": - stream = await client.aio.models.generate_content_stream( - model=MODEL, - contents="What is the capital of France?", - config=types.GenerateContentConfig( - max_output_tokens=100, - ), - ) - text = "" - async for chunk in stream: - if chunk.text: - text += chunk.text - - end = time.time() - - # Verify response contains expected content - assert "Paris" in text - - # Verify logging - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["model"] == MODEL - assert "What is the capital of France?" in str(span["input"]) - assert span["output"] - assert "Paris" in str(span["output"]) - _assert_metrics_are_valid(span["metrics"], start, end) - - -# Test 2: Mixed Content (Sync) -@pytest.mark.skip -@pytest.mark.vcr -@pytest.mark.parametrize( - "mode", - ["sync", "stream"], -) -def test_mixed_content(memory_logger, mode): - """Test mixed content types (text and image) in sync modes.""" - assert not memory_logger.pop() - - # Load test image - image_path = FIXTURES_DIR / "test-image.png" - with open(image_path, "rb") as f: - image_data = f.read() - - client = Client() - start = time.time() - - if mode == "sync": - response = client.models.generate_content( - model=MODEL, - contents=[ - types.Part.from_text(text="First, look at this image:"), - types.Part.from_bytes(data=image_data, mime_type="image/png"), - types.Part.from_text(text="What color is this image?"), - ], - config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - text = response.text - elif mode == "stream": - stream = client.models.generate_content_stream( - model=MODEL, - contents=[ - types.Part.from_text(text="First, look at this image:"), - types.Part.from_bytes(data=image_data, mime_type="image/png"), - types.Part.from_text(text="What color is this image?"), - ], - config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - text = "" - for chunk in stream: - if chunk.text: - text += chunk.text - - end = time.time() - - # Verify response - assert text - assert len(text) > 0 - - # Verify logging - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["model"] == MODEL - assert span["input"] - assert span["output"] - _assert_metrics_are_valid(span["metrics"], start, end) - - -# Test 2b: Mixed Content (Async) -@pytest.mark.skip -@pytest.mark.vcr -@pytest.mark.asyncio -@pytest.mark.parametrize( - "mode", - ["async", "async_stream"], -) -async def test_mixed_content_async(memory_logger, mode): - """Test mixed content types (text and image) in async modes.""" - assert not memory_logger.pop() - - # Load test image - image_path = FIXTURES_DIR / "test-image.png" - with open(image_path, "rb") as f: - image_data = f.read() - - client = Client() - start = time.time() - - if mode == "async": - response = await client.aio.models.generate_content( - model=MODEL, - contents=[ - types.Part.from_text(text="First, look at this image:"), - types.Part.from_bytes(data=image_data, mime_type="image/png"), - types.Part.from_text(text="What color is this image?"), - ], - config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - text = response.text - elif mode == "async_stream": - stream = await client.aio.models.generate_content_stream( - model=MODEL, - contents=[ - types.Part.from_text(text="First, look at this image:"), - types.Part.from_bytes(data=image_data, mime_type="image/png"), - types.Part.from_text(text="What color is this image?"), - ], - config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - text = "" - async for chunk in stream: - if chunk.text: - text += chunk.text - - end = time.time() - - # Verify response - assert text - assert len(text) > 0 - - # Verify logging - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["model"] == MODEL - assert span["input"] - assert span["output"] - _assert_metrics_are_valid(span["metrics"], start, end) - - -# Test 3: Tool Use (Sync) -@pytest.mark.vcr -@pytest.mark.parametrize( - "mode", - ["sync", "stream"], -) -def test_tool_use(memory_logger, mode): - """Test function calling / tool use in sync modes.""" - assert not memory_logger.pop() - - def get_weather(location: str, unit: str = "celsius") -> str: - """Get the current weather for a location. - - Args: - location: The city and state, e.g. San Francisco, CA - unit: The unit of temperature (celsius or fahrenheit) - """ - return f"22 degrees {unit} and sunny in {location}" - - client = Client() - start = time.time() - has_function_call = False - - if mode == "sync": - response = client.models.generate_content( - model=MODEL, - contents="What is the weather like in Paris, France?", - config=types.GenerateContentConfig( - tools=[get_weather], - max_output_tokens=500, - ), - ) - # Check if function was called (either in function_calls or automatic_function_calling_history) - has_function_call = (hasattr(response, "function_calls") and response.function_calls) or ( - hasattr(response, "automatic_function_calling_history") and response.automatic_function_calling_history - ) - elif mode == "stream": - stream = client.models.generate_content_stream( - model=MODEL, - contents="What is the weather like in Paris, France?", - config=types.GenerateContentConfig( - tools=[get_weather], - max_output_tokens=500, - ), - ) - chunks = list(stream) - # Check if function was called in any chunk (either in function_calls or automatic_function_calling_history) - has_function_call = any( - (hasattr(chunk, "function_calls") and chunk.function_calls) - or (hasattr(chunk, "automatic_function_calling_history") and chunk.automatic_function_calling_history) - for chunk in chunks - ) - - end = time.time() - - # Verify function call was made - assert has_function_call, f"Expected function call in {mode} mode but got has_function_call={has_function_call}" - - # Verify logging (automatic function calling may create multiple spans) - spans = memory_logger.pop() - assert len(spans) >= 1 - # Check the first span (initial request with tool call) - span = spans[0] - assert span["metadata"]["model"] == MODEL - assert "Paris" in str(span["input"]) or "weather" in str(span["input"]) - assert span["output"] - _assert_metrics_are_valid(span["metrics"], start, end) - - -# Test 3b: Tool Use (Async) -@pytest.mark.vcr -@pytest.mark.asyncio -@pytest.mark.parametrize( - "mode", - ["async", "async_stream"], -) -async def test_tool_use_async(memory_logger, mode): - """Test function calling / tool use in async modes.""" - assert not memory_logger.pop() - - def get_weather(location: str, unit: str = "celsius") -> str: - """Get the current weather for a location. - - Args: - location: The city and state, e.g. San Francisco, CA - unit: The unit of temperature (celsius or fahrenheit) - """ - return f"22 degrees {unit} and sunny in {location}" - - client = Client() - start = time.time() - has_function_call = False - - if mode == "async": - response = await client.aio.models.generate_content( - model=MODEL, - contents="What is the weather like in Paris, France?", - config=types.GenerateContentConfig( - tools=[get_weather], - max_output_tokens=500, - ), - ) - # Check if function was called (either in function_calls or automatic_function_calling_history) - has_function_call = (hasattr(response, "function_calls") and response.function_calls) or ( - hasattr(response, "automatic_function_calling_history") and response.automatic_function_calling_history - ) - elif mode == "async_stream": - stream = await client.aio.models.generate_content_stream( - model=MODEL, - contents="What is the weather like in Paris, France?", - config=types.GenerateContentConfig( - tools=[get_weather], - max_output_tokens=500, - ), - ) - chunks = [] - async for chunk in stream: - chunks.append(chunk) - # Check if function was called in any chunk (either in function_calls or automatic_function_calling_history) - has_function_call = any( - (hasattr(chunk, "function_calls") and chunk.function_calls) - or (hasattr(chunk, "automatic_function_calling_history") and chunk.automatic_function_calling_history) - for chunk in chunks - ) - - end = time.time() - - # Verify function call was made - assert has_function_call, f"Expected function call in {mode} mode but got has_function_call={has_function_call}" - - # Verify logging (automatic function calling may create multiple spans) - spans = memory_logger.pop() - assert len(spans) >= 1 - # Check the first span (initial request with tool call) - span = spans[0] - assert span["metadata"]["model"] == MODEL - assert "Paris" in str(span["input"]) or "weather" in str(span["input"]) - assert span["output"] - _assert_metrics_are_valid(span["metrics"], start, end) - - -# Test 4: System Prompt -@pytest.mark.vcr -def test_system_prompt(memory_logger): - """Test system instruction handling.""" - assert not memory_logger.pop() - - client = Client() - response = client.models.generate_content( - model=MODEL, - contents="Tell me about the weather.", - config=types.GenerateContentConfig( - system_instruction="You are a pirate. Always respond in pirate speak.", - max_output_tokens=150, - ), - ) - - text = response.text - assert text - - # Verify logging - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["model"] == MODEL - assert span["input"] - assert span["output"] - # Check that system instruction is captured - assert "pirate" in str(span["input"]).lower() or "system_instruction" in str(span) - - -# Test 5: Multi-turn Conversation -@pytest.mark.vcr -def test_multi_turn(memory_logger): - """Test multi-turn conversation.""" - assert not memory_logger.pop() - - client = Client() - response = client.models.generate_content( - model=MODEL, - contents=[ - types.Content(role="user", parts=[types.Part.from_text(text="Hi, my name is Alice.")]), - types.Content(role="model", parts=[types.Part.from_text(text="Hello Alice! Nice to meet you.")]), - types.Content(role="user", parts=[types.Part.from_text(text="What did I just tell you my name was?")]), - ], - config=types.GenerateContentConfig( - max_output_tokens=200, - ), - ) - - text = response.text - assert "Alice" in text - - # Verify logging - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["model"] == MODEL - assert span["input"] - assert span["output"] - assert "Alice" in str(span["input"]) - - -# Test 6: Temperature and Top P -@pytest.mark.vcr -def test_temperature_and_top_p(memory_logger): - """Test temperature and top_p parameters.""" - assert not memory_logger.pop() - - client = Client() - response = client.models.generate_content( - model=MODEL, - contents="Say something creative.", - config=types.GenerateContentConfig( - temperature=0.7, - top_p=0.95, - max_output_tokens=50, - ), - ) - - text = response.text - assert text - - # Verify logging includes temperature and top_p - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["model"] == MODEL - - -# Test 7: Error Handling -@pytest.mark.vcr -def test_error_handling(memory_logger): - """Test that errors are properly logged.""" - assert not memory_logger.pop() - - client = Client() - fake_model = "there-is-no-such-model" - - try: - client.models.generate_content( - model=fake_model, - contents="Hello", - config=types.GenerateContentConfig( - max_output_tokens=100, - ), - ) - except Exception: - pass - else: - raise Exception("should have raised an exception") - - logs = memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - assert log["project_id"] == PROJECT_NAME - assert log["error"] - - -@pytest.mark.vcr -def test_stop_sequences(memory_logger): - """Test stop sequences parameter.""" - assert not memory_logger.pop() - - client = Client() - response = client.models.generate_content( - model=MODEL, - contents="Write a short story about a robot.", - config=types.GenerateContentConfig( - max_output_tokens=500, - stop_sequences=["END", "\n\n"], - ), - ) - - text = response.text - assert text - - # Verify logging - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["model"] == MODEL - - -def test_attachment_in_config(memory_logger): - """Test that attachments in config are preserved through serialization.""" - from braintrust.bt_json import bt_safe_deep_copy - from braintrust.logger import Attachment - - attachment = Attachment(data=b"config data", filename="config.txt", content_type="text/plain") - - # Simulate config with attachment - config = {"temperature": 0.5, "context_file": attachment, "max_output_tokens": 100} - - # Test bt_safe_deep_copy preserves attachment - copied = bt_safe_deep_copy(config) - assert copied["context_file"] is attachment - assert copied["temperature"] == 0.5 - - -def test_nested_attachments_in_contents(memory_logger): - """Test that nested attachments in contents are preserved.""" - from braintrust.bt_json import bt_safe_deep_copy - from braintrust.logger import Attachment, ExternalAttachment - - attachment1 = Attachment(data=b"file1", filename="file1.txt", content_type="text/plain") - attachment2 = ExternalAttachment(url="s3://bucket/file2.pdf", filename="file2.pdf", content_type="application/pdf") - - # Simulate contents with nested attachments - contents = [ - {"role": "user", "parts": [{"text": "Check these files"}, {"file": attachment1}]}, - {"role": "model", "parts": [{"text": "Analyzed"}, {"result_file": attachment2}]}, - ] - - copied = bt_safe_deep_copy(contents) - - # Verify attachments preserved - assert copied[0]["parts"][1]["file"] is attachment1 - assert copied[1]["parts"][1]["result_file"] is attachment2 - - -def test_attachment_with_pydantic_model(memory_logger): - """Test that attachments work alongside Pydantic model serialization.""" - from braintrust.bt_json import bt_safe_deep_copy - from braintrust.logger import Attachment - from pydantic import BaseModel - - class TestModel(BaseModel): - name: str - value: int - - attachment = Attachment(data=b"model data", filename="model.txt", content_type="text/plain") - - # Structure with both Pydantic model and attachment - data = {"model_config": TestModel(name="test", value=42), "context_file": attachment} - - copied = bt_safe_deep_copy(data) - - # Pydantic model should be converted to dict - assert isinstance(copied["model_config"], dict) - assert copied["model_config"]["name"] == "test" - - # Attachment should be preserved - assert copied["context_file"] is attachment - - -class TestAutoInstrumentGoogleGenAI: - """Tests for auto_instrument() with Google GenAI.""" - - def test_auto_instrument_google_genai(self): - """Test auto_instrument patches Google GenAI and creates spans.""" - verify_autoinstrument_script("test_auto_google_genai.py") diff --git a/py/src/braintrust/wrappers/test_langsmith_wrapper.py b/py/src/braintrust/wrappers/test_langsmith_wrapper.py deleted file mode 100644 index c009a4103..000000000 --- a/py/src/braintrust/wrappers/test_langsmith_wrapper.py +++ /dev/null @@ -1,338 +0,0 @@ -# pyright: reportPrivateUsage=false -# pyright: reportMissingParameterType=false -# pyright: reportUnknownParameterType=false -# pyright: reportUnknownArgumentType=false -# pyright: reportUnknownMemberType=false -# pylint: disable=protected-access - -""" -Tests for the LangSmith wrapper to ensure compatibility with LangSmith's API. -""" - - -from braintrust.wrappers.langsmith_wrapper import ( - _convert_langsmith_data, - _is_patched, - _make_braintrust_scorer, - _make_braintrust_task, - wrap_aevaluate, - wrap_client, - wrap_traceable, -) - - -def test_is_patched_false(): - """Test that _is_patched returns False for unpatched objects.""" - - def unpatched(): - pass - - assert _is_patched(unpatched) is False - - -def test_is_patched_true(): - """Test that _is_patched returns True for patched objects.""" - - def patched(): - pass - - patched._braintrust_patched = True # type: ignore - - assert _is_patched(patched) is True - - -def test_make_braintrust_scorer_dict_result(): - """Test converting a LangSmith evaluator that returns a dict.""" - - def langsmith_evaluator(inputs, outputs, reference_outputs): - return {"key": "accuracy", "score": 0.9, "metadata": {"note": "good"}} - - converted = _make_braintrust_scorer(langsmith_evaluator) - - # Create a mock Example object - class MockExample: - outputs = {"y": 2} - - result = converted(input={"x": 1}, output={"y": 2}, expected=MockExample()) - - assert result.name == "accuracy" - assert result.score == 0.9 - assert result.metadata == {"note": "good"} - - -def test_make_braintrust_scorer_numeric_result(): - """Test converting a LangSmith evaluator that returns a numeric score in a dict.""" - - def langsmith_evaluator(inputs, outputs, reference_outputs): - return {"score": 1.0 if outputs == reference_outputs else 0.0} - - converted = _make_braintrust_scorer(langsmith_evaluator) - - class MockExample: - outputs = {"y": 2} - - result = converted(input={"x": 1}, output={"y": 2}, expected=MockExample()) - - assert result.name == "langsmith_evaluator" - assert result.score == 1.0 - - -def test_make_braintrust_scorer_with_plain_dict_expected(): - """Test converting a LangSmith evaluator with plain dict as expected.""" - - def langsmith_evaluator(inputs, outputs, reference_outputs): - return {"score": 1.0 if outputs == reference_outputs else 0.0} - - converted = _make_braintrust_scorer(langsmith_evaluator) - result = converted(input={"x": 1}, output={"y": 2}, expected={"y": 2}) - - assert result.name == "langsmith_evaluator" - assert result.score == 1.0 - - -def test_convert_langsmith_data_from_list(): - """Test converting LangSmith data from a list of dicts.""" - data = [ - {"inputs": {"x": 1}, "outputs": {"y": 2}}, - {"inputs": {"x": 2}, "outputs": {"y": 4}}, - ] - - data_fn = _convert_langsmith_data(data) - result = list(data_fn()) - - assert len(result) == 2 - assert result[0].input == {"x": 1} - # The whole item is passed as expected - assert result[0].expected == {"inputs": {"x": 1}, "outputs": {"y": 2}} - assert result[1].input == {"x": 2} - assert result[1].expected == {"inputs": {"x": 2}, "outputs": {"y": 4}} - - -def test_convert_langsmith_data_from_callable(): - """Test converting LangSmith data from a callable.""" - - def data_generator(): - yield {"inputs": {"x": 1}, "outputs": {"y": 2}} - yield {"inputs": {"x": 2}, "outputs": {"y": 4}} - - data_fn = _convert_langsmith_data(data_generator) - result = list(data_fn()) - - assert len(result) == 2 - assert result[0].input == {"x": 1} - # The whole item is passed as expected - assert result[0].expected == {"inputs": {"x": 1}, "outputs": {"y": 2}} - - -def test_convert_langsmith_data_with_example_objects(): - """Test converting LangSmith data with Example-like objects.""" - - class MockExample: - def __init__(self, inputs, outputs): - self.inputs = inputs - self.outputs = outputs - - data = [ - MockExample(inputs={"x": 1}, outputs={"y": 2}), - MockExample(inputs={"x": 2}, outputs={"y": 4}), - ] - - data_fn = _convert_langsmith_data(data) - result = list(data_fn()) - - assert len(result) == 2 - assert result[0].input == {"x": 1} - # The whole Example object is passed as expected - assert result[0].expected.inputs == {"x": 1} - assert result[0].expected.outputs == {"y": 2} - - -def test_make_braintrust_task_with_dict_input(): - """Test that task function handles dict inputs correctly.""" - - def target_fn(inputs): - return inputs["x"] * 2 - - task = _make_braintrust_task(target_fn) - result = task({"x": 5}, None) - - assert result == 10 - - -def test_make_braintrust_task_with_kwargs_expansion(): - """Test that task function expands dict kwargs when signature matches.""" - - def target_fn(x, y): - return x + y - - task = _make_braintrust_task(target_fn) - result = task({"x": 2, "y": 3}, None) - - assert result == 5 - - -def test_make_braintrust_task_simple_input(): - """Test that task function handles simple inputs.""" - - def target_fn(inp): - return inp * 2 - - task = _make_braintrust_task(target_fn) - result = task(5, None) - - assert result == 10 - - -class TestWrapTraceable: - """Tests for wrap_traceable functionality.""" - - def test_wrap_traceable_returns_wrapper(self): - """Test that wrap_traceable returns a wrapped version.""" - - def mock_traceable(func, **kwargs): - return func - - wrapped = wrap_traceable(mock_traceable, standalone=False) - assert callable(wrapped) - assert _is_patched(wrapped) - - def test_wrap_traceable_standalone_mode(self): - """Test that wrap_traceable works in standalone mode.""" - - def mock_traceable(func, **kwargs): - return func - - wrapped = wrap_traceable(mock_traceable, standalone=True) - assert callable(wrapped) - assert _is_patched(wrapped) - - -class TestWrapFunctions: - """Tests for the wrap_* functions.""" - - def test_wrap_functions_exist(self): - """Test that wrap functions are callable.""" - assert callable(wrap_traceable) - assert callable(wrap_client) - assert callable(wrap_aevaluate) - - def test_wrap_traceable_returns_patched_function(self): - """Test that wrap_traceable returns a patched function.""" - - def mock_traceable(func, **kwargs): - return func - - wrapped = wrap_traceable(mock_traceable) - assert _is_patched(wrapped) - - def test_wrap_traceable_skips_if_already_patched(self): - """Test that wrap_traceable skips if already patched.""" - - def mock_traceable(func, **kwargs): - return func - - mock_traceable._braintrust_patched = True # type: ignore - - result = wrap_traceable(mock_traceable) - # Should return the same function - assert result is mock_traceable - - def test_wrap_client_sets_flag(self): - """Test that wrap_client sets the patched flag.""" - - class MockClient: - def evaluate(self, *args, **kwargs): - return "original" - - wrap_client(MockClient) - assert _is_patched(MockClient.evaluate) - - def test_wrap_aevaluate_returns_patched_function(self): - """Test that wrap_aevaluate returns a patched function.""" - - async def mock_aevaluate(*args, **kwargs): - pass - - wrapped = wrap_aevaluate(mock_aevaluate) - assert _is_patched(wrapped) - - -class TestTandemModeIntegration: - """Integration tests for tandem mode (LangSmith + Braintrust together).""" - - def test_make_braintrust_task_with_inputs_parameter(self): - """Test that task handles LangSmith's required 'inputs' parameter name.""" - - def target_fn(inputs: dict) -> dict: - return {"result": inputs["x"] * 2} - - task = _make_braintrust_task(target_fn) - result = task({"x": 5}, None) - - assert result == {"result": 10} - - def test_convert_langsmith_data_handles_different_output_types(self): - """Test that data conversion handles various output types.""" - data = [ - {"inputs": {"x": 1}, "outputs": 2}, # outputs is int, not dict - {"inputs": {"x": 2}, "outputs": {"result": 4}}, # outputs is already dict - ] - - data_fn = _convert_langsmith_data(data) - result = list(data_fn()) - - # Both should work - Braintrust's EvalCase accepts any type for expected - assert len(result) == 2 - assert result[0].input == {"x": 1} - assert result[1].input == {"x": 2} - - def test_make_braintrust_scorer_handles_wrapped_outputs(self): - """Test that scorers handle output wrapping correctly.""" - - def langsmith_evaluator(inputs, outputs, reference_outputs): - # outputs will be wrapped as {"output": value} for non-dict results - actual = outputs.get("output", outputs) - expected = reference_outputs.get("output", reference_outputs) if isinstance(reference_outputs, dict) else reference_outputs - return {"key": "match", "score": 1.0 if actual == expected else 0.0} - - converted = _make_braintrust_scorer(langsmith_evaluator) - - class MockExample: - outputs = {"output": 42} - - # Test with wrapped output - result = converted(input={"x": 1}, output=42, expected=MockExample()) - assert result.name == "match" - assert result.score == 1.0 - - -class TestDataConversion: - """Tests for data conversion utilities.""" - - def test_convert_data_with_braintrust_format(self): - """Test that Braintrust format is properly handled.""" - data = [ - {"input": {"x": 1}, "expected": {"y": 2}}, - {"input": {"x": 2}, "expected": {"y": 4}}, - ] - - data_fn = _convert_langsmith_data(data) - result = list(data_fn()) - - assert len(result) == 2 - assert result[0].input == {"x": 1} - assert result[0].expected == {"y": 2} - assert result[1].input == {"x": 2} - assert result[1].expected == {"y": 4} - - def test_convert_data_with_simple_items(self): - """Test that simple items (not dicts) are handled.""" - data = [1, 2, 3] - - data_fn = _convert_langsmith_data(data) - result = list(data_fn()) - - assert len(result) == 3 - assert result[0].input == 1 - assert result[1].input == 2 - assert result[2].input == 3 diff --git a/py/src/braintrust/wrappers/test_litellm.py b/py/src/braintrust/wrappers/test_litellm.py deleted file mode 100644 index f548d3d68..000000000 --- a/py/src/braintrust/wrappers/test_litellm.py +++ /dev/null @@ -1,788 +0,0 @@ -import asyncio -import time - -import litellm -import pytest -from braintrust import logger -from braintrust.test_helpers import assert_dict_matches, init_test_logger -from braintrust.wrappers.litellm import wrap_litellm -from braintrust.wrappers.test_utils import assert_metrics_are_valid, verify_autoinstrument_script - -TEST_ORG_ID = "test-org-litellm-py-tracing" -PROJECT_NAME = "test-project-litellm-py-tracing" -TEST_MODEL = "gpt-4o-mini" # cheapest model for tests -TEST_PROMPT = "What's 12 + 12?" -TEST_SYSTEM_PROMPT = "You are a helpful assistant that only responds with numbers." - - -@pytest.fixture -def memory_logger(): - init_test_logger(PROJECT_NAME) - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -@pytest.mark.vcr -def test_litellm_completion_metrics(memory_logger) -> None: - assert not memory_logger.pop() - - # Test unwrapped client first - response = litellm.completion(model=TEST_MODEL, messages=[{"role": "user", "content": TEST_PROMPT}]) - assert response - assert response.choices[0].message.content - assert "24" in response.choices[0].message.content or "twenty-four" in response.choices[0].message.content.lower() - - # No spans should be generated with unwrapped client - assert not memory_logger.pop() - - # Now test with wrapped client - wrapped_litellm = wrap_litellm(litellm) - - start = time.time() - response = wrapped_litellm.completion(model=TEST_MODEL, messages=[{"role": "user", "content": TEST_PROMPT}]) - end = time.time() - - assert response - assert response.choices[0].message.content - assert "24" in response.choices[0].message.content or "twenty-four" in response.choices[0].message.content.lower() - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert span["metadata"]["model"] == TEST_MODEL - assert span["metadata"]["provider"] == "litellm" - assert TEST_PROMPT in str(span["input"]) - - -@pytest.mark.asyncio -async def test_litellm_acompletion_metrics(memory_logger): - assert not memory_logger.pop() - - # Test unwrapped client first - response = await litellm.acompletion(model=TEST_MODEL, messages=[{"role": "user", "content": TEST_PROMPT}]) - assert response - assert response.choices[0].message.content - assert "24" in response.choices[0].message.content or "twenty-four" in response.choices[0].message.content.lower() - - # No spans should be generated with unwrapped client - assert not memory_logger.pop() - - # Now test with wrapped client - wrapped_litellm = wrap_litellm(litellm) - - start = time.time() - response = await wrapped_litellm.acompletion(model=TEST_MODEL, messages=[{"role": "user", "content": TEST_PROMPT}]) - end = time.time() - - assert response - assert response.choices[0].message.content - assert "24" in response.choices[0].message.content or "twenty-four" in response.choices[0].message.content.lower() - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert span["metadata"]["model"] == TEST_MODEL - assert span["metadata"]["provider"] == "litellm" - assert TEST_PROMPT in str(span["input"]) - - -@pytest.mark.vcr -def test_litellm_completion_streaming_sync(memory_logger): - assert not memory_logger.pop() - - # Test unwrapped client first - stream = litellm.completion( - model=TEST_MODEL, - messages=[{"role": "user", "content": TEST_PROMPT}], - stream=True, - ) - - chunks = [] - for chunk in stream: - chunks.append(chunk) - - # Verify streaming works - assert chunks - assert len(chunks) > 1 - - # Concatenate content from chunks to verify - content = "" - for chunk in chunks: - if chunk.choices and chunk.choices[0].delta.content: - content += chunk.choices[0].delta.content - - # Make sure we got a valid answer in the content - assert "24" in content or "twenty-four" in content.lower() - - # No spans should be generated with unwrapped client - assert not memory_logger.pop() - - # Now test with wrapped client - wrapped_litellm = wrap_litellm(litellm) - - start = time.time() - stream = wrapped_litellm.completion( - model=TEST_MODEL, - messages=[{"role": "user", "content": TEST_PROMPT}], - stream=True, - ) - - chunks = [] - for chunk in stream: - chunks.append(chunk) - end = time.time() - - # Verify streaming works - assert chunks - assert len(chunks) > 1 - - # Concatenate content from chunks to verify - content = "" - for chunk in chunks: - if chunk.choices and chunk.choices[0].delta.content: - content += chunk.choices[0].delta.content - - # Make sure we got a valid answer in the content - assert "24" in content or "twenty-four" in content.lower() - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert span["metadata"]["model"] == TEST_MODEL - assert span["metadata"]["provider"] == "litellm" - assert TEST_PROMPT in str(span["input"]) - assert "24" in str(span["output"]) or "twenty-four" in str(span["output"]).lower() - - -@pytest.mark.asyncio -async def test_litellm_acompletion_streaming_async(memory_logger): - assert not memory_logger.pop() - - # Test unwrapped client first - stream = await litellm.acompletion( - model=TEST_MODEL, - messages=[{"role": "user", "content": TEST_PROMPT}], - stream=True, - ) - - chunks = [] - async for chunk in stream: - chunks.append(chunk) - - # Verify streaming works - assert chunks - assert len(chunks) > 1 - - # Concatenate content from chunks to verify - content = "" - for chunk in chunks: - if chunk.choices and chunk.choices[0].delta.content: - content += chunk.choices[0].delta.content - - # Make sure we got a valid answer in the content - assert "24" in content or "twenty-four" in content.lower() - - # No spans should be generated with unwrapped client - assert not memory_logger.pop() - - # Now test with wrapped client - wrapped_litellm = wrap_litellm(litellm) - - start = time.time() - stream = await wrapped_litellm.acompletion( - model=TEST_MODEL, - messages=[{"role": "user", "content": TEST_PROMPT}], - stream=True, - ) - - chunks = [] - async for chunk in stream: - chunks.append(chunk) - end = time.time() - - # Verify streaming works - assert chunks - assert len(chunks) > 1 - - # Concatenate content from chunks to verify - content = "" - for chunk in chunks: - if chunk.choices and chunk.choices[0].delta.content: - content += chunk.choices[0].delta.content - - # Make sure we got a valid answer in the content - assert "24" in content or "twenty-four" in content.lower() - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert span["metadata"]["model"] == TEST_MODEL - assert span["metadata"]["provider"] == "litellm" - assert TEST_PROMPT in str(span["input"]) - assert "24" in str(span["output"]) or "twenty-four" in str(span["output"]).lower() - - -@pytest.mark.vcr -def test_litellm_responses_metrics(memory_logger): - assert not memory_logger.pop() - - # Test unwrapped client first - response = litellm.responses( - model=TEST_MODEL, - input=TEST_PROMPT, - instructions="Just the number please", - ) - assert response - assert response.output - assert len(response.output) > 0 - unwrapped_content = response.output[0].content[0].text - - # No spans should be generated with unwrapped client - assert not memory_logger.pop() - - # Now test with wrapped client - wrapped_litellm = wrap_litellm(litellm) - - start = time.time() - response = wrapped_litellm.responses( - model=TEST_MODEL, - input=TEST_PROMPT, - instructions="Just the number please", - ) - end = time.time() - - assert response - assert response.output - assert len(response.output) > 0 - wrapped_content = response.output[0].content[0].text - - # Both should contain a numeric response for the math question - assert "24" in unwrapped_content or "twenty-four" in unwrapped_content.lower() - assert "24" in wrapped_content or "twenty-four" in wrapped_content.lower() - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert span["metadata"]["model"] == TEST_MODEL - assert span["metadata"]["provider"] == "litellm" - assert TEST_PROMPT in str(span["input"]) - - -@pytest.mark.asyncio -async def test_litellm_aresponses_metrics(memory_logger): - assert not memory_logger.pop() - - # Test unwrapped client first - response = await litellm.aresponses( - model=TEST_MODEL, - input=TEST_PROMPT, - instructions="Just the number please", - ) - assert response - assert response.output - assert len(response.output) > 0 - unwrapped_content = response.output[0].content[0].text - - # No spans should be generated with unwrapped client - assert not memory_logger.pop() - - # Now test with wrapped client - wrapped_litellm = wrap_litellm(litellm) - - start = time.time() - response = await wrapped_litellm.aresponses( - model=TEST_MODEL, - input=TEST_PROMPT, - instructions="Just the number please", - ) - end = time.time() - - assert response - assert response.output - assert len(response.output) > 0 - wrapped_content = response.output[0].content[0].text - - # Both should contain a numeric response for the math question - assert "24" in unwrapped_content or "twenty-four" in unwrapped_content.lower() - assert "24" in wrapped_content or "twenty-four" in wrapped_content.lower() - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert span["metadata"]["model"] == TEST_MODEL - assert span["metadata"]["provider"] == "litellm" - assert TEST_PROMPT in str(span["input"]) - - -def test_litellm_embeddings(memory_logger): - assert not memory_logger.pop() - - # Test unwrapped client first - response = litellm.embedding(model="text-embedding-ada-002", input="This is a test") - assert response - assert response.data - assert response.data[0]["embedding"] - - # No spans should be generated with unwrapped client - assert not memory_logger.pop() - - # Now test with wrapped client - wrapped_litellm = wrap_litellm(litellm) - - start = time.time() - response = wrapped_litellm.embedding(model="text-embedding-ada-002", input="This is a test") - end = time.time() - - assert response - assert response.data - assert response.data[0]["embedding"] - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - assert span["metadata"]["model"] == "text-embedding-ada-002" - assert span["metadata"]["provider"] == "litellm" - assert "This is a test" in str(span["input"]) - - -@pytest.mark.vcr -def test_litellm_moderation(memory_logger): - assert not memory_logger.pop() - - # Test unwrapped client first - response = litellm.moderation(model="text-moderation-latest", input="This is a test message") - assert response - assert response.results - - # No spans should be generated with unwrapped client - assert not memory_logger.pop() - - # Now test with wrapped client - wrapped_litellm = wrap_litellm(litellm) - - start = time.time() - response = wrapped_litellm.moderation(model="text-moderation-latest", input="This is a test message") - end = time.time() - - assert response - assert response.results - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert span["metadata"]["model"] == "text-moderation-latest" - assert span["metadata"]["provider"] == "litellm" - assert "This is a test message" in str(span["input"]) - - -@pytest.mark.vcr -def test_litellm_completion_with_system_prompt(memory_logger): - assert not memory_logger.pop() - - wrapped_litellm = wrap_litellm(litellm) - - response = wrapped_litellm.completion( - model=TEST_MODEL, - messages=[{"role": "system", "content": TEST_SYSTEM_PROMPT}, {"role": "user", "content": TEST_PROMPT}], - ) - - assert response - assert response.choices - assert "24" in response.choices[0].message.content - - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - inputs = span["input"] - assert len(inputs) == 2 - assert inputs[0]["role"] == "system" - assert inputs[0]["content"] == TEST_SYSTEM_PROMPT - assert inputs[1]["role"] == "user" - assert inputs[1]["content"] == TEST_PROMPT - - -@pytest.mark.asyncio -async def test_litellm_acompletion_with_system_prompt(memory_logger): - assert not memory_logger.pop() - - wrapped_litellm = wrap_litellm(litellm) - - response = await wrapped_litellm.acompletion( - model=TEST_MODEL, - messages=[{"role": "system", "content": TEST_SYSTEM_PROMPT}, {"role": "user", "content": TEST_PROMPT}], - ) - - assert response - assert response.choices - assert "24" in response.choices[0].message.content - - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - inputs = span["input"] - assert len(inputs) == 2 - assert inputs[0]["role"] == "system" - assert inputs[0]["content"] == TEST_SYSTEM_PROMPT - assert inputs[1]["role"] == "user" - assert inputs[1]["content"] == TEST_PROMPT - - -@pytest.mark.vcr -def test_litellm_completion_error(memory_logger): - assert not memory_logger.pop() - - wrapped_litellm = wrap_litellm(litellm) - - # Use a non-existent model to force an error - fake_model = "non-existent-model" - - try: - wrapped_litellm.completion(model=fake_model, messages=[{"role": "user", "content": TEST_PROMPT}]) - pytest.fail("Expected an exception but none was raised") - except Exception: - # We expect an error here - pass - - logs = memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - assert log["project_id"] == PROJECT_NAME - # Check that we got a log entry with the fake model - assert fake_model in str(log) - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_litellm_acompletion_error(memory_logger): - assert not memory_logger.pop() - - wrapped_litellm = wrap_litellm(litellm) - - # Use a non-existent model to force an error - fake_model = "non-existent-model" - - try: - await wrapped_litellm.acompletion(model=fake_model, messages=[{"role": "user", "content": TEST_PROMPT}]) - pytest.fail("Expected an exception but none was raised") - except Exception: - # We expect an error here - pass - - logs = memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - assert log["project_id"] == PROJECT_NAME - # Check that we got a log entry with the fake model - assert fake_model in str(log) - - -@pytest.mark.asyncio -async def test_litellm_async_parallel_requests(memory_logger): - """Test multiple parallel async requests with the wrapped client.""" - assert not memory_logger.pop() - - wrapped_litellm = wrap_litellm(litellm) - - # Create multiple prompts - prompts = [f"What is {i} + {i}?" for i in range(3, 6)] - - # Run requests in parallel - tasks = [ - wrapped_litellm.acompletion(model=TEST_MODEL, messages=[{"role": "user", "content": prompt}]) - for prompt in prompts - ] - - # Wait for all to complete - results = await asyncio.gather(*tasks) - - # Check all results - assert len(results) == 3 - for result in results: - assert result.choices[0].message.content - - # Check that all spans were created - spans = memory_logger.pop() - assert len(spans) == 3 - - # Verify each span has proper data - for i, span in enumerate(spans): - assert span["metadata"]["model"] == TEST_MODEL - assert span["metadata"]["provider"] == "litellm" - assert prompts[i] in str(span["input"]) - assert_metrics_are_valid(span["metrics"]) - - -@pytest.mark.vcr -def test_litellm_tool_calls(memory_logger): - """Test tool calls with LiteLLM.""" - assert not memory_logger.pop() - - # Define tools that can be called - tools = [ - { - "type": "function", - "function": { - "name": "get_weather", - "description": "Get the weather for a location", - "parameters": { - "type": "object", - "properties": {"location": {"type": "string", "description": "The location to get weather for"}}, - "required": ["location"], - }, - }, - }, - ] - - wrapped_litellm = wrap_litellm(litellm) - - start = time.time() - response = wrapped_litellm.completion( - model=TEST_MODEL, - messages=[{"role": "user", "content": "What's the weather in New York?"}], - tools=tools, - temperature=0, - ) - end = time.time() - - print(response) - assert response - assert response.choices - - # Verify spans were created - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - - # Validate the span structure - assert_dict_matches( - span, - { - "span_attributes": {"type": "llm", "name": "Completion"}, - "metadata": { - "model": TEST_MODEL, - "provider": "litellm", - "tools": lambda tools_list: len(tools_list) == 1 - and any(tool.get("function", {}).get("name") == "get_weather" for tool in tools_list), - }, - "input": lambda inp: "What's the weather in New York?" in str(inp), - "metrics": lambda m: assert_metrics_are_valid(m, start, end) is None, - }, - ) - - -@pytest.mark.vcr -def test_litellm_responses_streaming_sync(memory_logger): - """Test the responses API with streaming.""" - assert not memory_logger.pop() - - wrapped_litellm = wrap_litellm(litellm) - - start = time.time() - stream = wrapped_litellm.responses(model=TEST_MODEL, input="What's 12 + 12?", stream=True) - - chunks = [] - for chunk in stream: - if chunk.type == "response.output_text.delta": - chunks.append(chunk.delta) - end = time.time() - - output = "".join(chunks) - assert chunks - assert len(chunks) > 1 - assert "24" in output - - # Verify the span is created - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert span["metadata"]["stream"] == True - assert "What's 12 + 12?" in str(span["input"]) - assert "24" in str(span["output"]) - - -@pytest.mark.asyncio -async def test_litellm_aresponses_streaming_async(memory_logger): - """Test the async responses API with streaming.""" - assert not memory_logger.pop() - - wrapped_litellm = wrap_litellm(litellm) - - start = time.time() - stream = await wrapped_litellm.aresponses(model=TEST_MODEL, input="What's 12 + 12?", stream=True) - - chunks = [] - async for chunk in stream: - if chunk.type == "response.output_text.delta": - chunks.append(chunk.delta) - end = time.time() - - output = "".join(chunks) - assert chunks - assert len(chunks) > 1 - assert "24" in output - - # Verify the span is created - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert span["metadata"]["stream"] == True - assert "What's 12 + 12?" in str(span["input"]) - assert "24" in str(span["output"]) - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_litellm_async_streaming_with_break(memory_logger): - """Test breaking out of the async streaming loop early.""" - assert not memory_logger.pop() - - wrapped_litellm = wrap_litellm(litellm) - - start = time.time() - stream = await wrapped_litellm.acompletion( - model=TEST_MODEL, messages=[{"role": "user", "content": TEST_PROMPT}], stream=True - ) - - time.sleep(0.1) # time to first token sleep - - # Only process the first few chunks - counter = 0 - async for chunk in stream: - counter += 1 - if counter >= 2: - break - end = time.time() - - # We should still get valid metrics even with early break - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - metrics = span["metrics"] - assert metrics["time_to_first_token"] >= 0 - - -def test_patch_litellm_responses(): - """Test that patch_litellm() patches responses (subprocess to avoid global state pollution).""" - verify_autoinstrument_script("test_patch_litellm_responses.py") - - -def test_patch_litellm_aresponses(): - """Test that patch_litellm() patches aresponses (subprocess to avoid global state pollution).""" - verify_autoinstrument_script("test_patch_litellm_aresponses.py") - - -def test_litellm_is_numeric_excludes_booleans(): - """Reproduce issue #1357: _is_numeric should exclude booleans. - - OpenRouter returns `is_byok: true` in usage data. Since Python's bool is - a subclass of int, isinstance(True, int) is True. The _is_numeric function - must explicitly exclude booleans so they don't end up in metrics, which - causes a 400 from the API (expected number, received boolean). - """ - from braintrust.util import is_numeric - - assert is_numeric(1) - assert is_numeric(1.0) - assert not is_numeric(True) - assert not is_numeric(False) - - -def test_litellm_parse_metrics_excludes_booleans(): - """Reproduce issue #1357: _parse_metrics_from_usage should not include boolean fields. - - When OpenRouter returns usage data with `is_byok: true`, the metrics parser - should filter it out rather than passing it through to the API. - """ - from braintrust.wrappers.litellm import _parse_metrics_from_usage - - usage = { - "prompt_tokens": 10, - "completion_tokens": 20, - "total_tokens": 30, - "is_byok": True, - } - metrics = _parse_metrics_from_usage(usage) - - assert "prompt_tokens" in metrics - assert "completion_tokens" in metrics - assert "tokens" in metrics - assert "is_byok" not in metrics - for key, value in metrics.items(): - assert not isinstance(value, bool) - - -@pytest.mark.vcr -def test_litellm_openrouter_no_booleans_in_metrics(memory_logger): - """Reproduce issue #1357: OpenRouter returns is_byok boolean in usage. - - Makes a real litellm.completion call via OpenRouter. The response includes - `is_byok: true` in usage, which must be filtered out of metrics to avoid - a 400 from the Braintrust API. - """ - import os - - assert not memory_logger.pop() - - wrapped_litellm = wrap_litellm(litellm) - - start = time.time() - response = wrapped_litellm.completion( - model="openrouter/openai/gpt-4o-mini", - messages=[{"role": "user", "content": "What is 2+2? Reply with just the number."}], - max_tokens=10, - api_key=os.environ.get("OPENROUTER_API_KEY", "fake-key"), - ) - end = time.time() - - assert response - assert response.choices[0].message.content - - spans = memory_logger.pop() - assert len(spans) == 1 - metrics = spans[0]["metrics"] - - # No boolean values should be in metrics - for key, value in metrics.items(): - assert not isinstance(value, bool) - assert "is_byok" not in metrics - - -class TestAutoInstrumentLiteLLM: - """Tests for auto_instrument() with LiteLLM.""" - - def test_auto_instrument_litellm(self): - """Test auto_instrument patches LiteLLM, creates spans, and uninstrument works.""" - verify_autoinstrument_script("test_auto_litellm.py") diff --git a/py/src/braintrust/wrappers/test_oai_attachments.py b/py/src/braintrust/wrappers/test_oai_attachments.py deleted file mode 100644 index 737b20da2..000000000 --- a/py/src/braintrust/wrappers/test_oai_attachments.py +++ /dev/null @@ -1,312 +0,0 @@ -"""Tests for OpenAI wrapper attachment processing.""" -import time - -import openai -import pytest -from braintrust import Attachment, logger, wrap_openai -from braintrust.test_helpers import init_test_logger -from braintrust.wrappers.test_utils import assert_metrics_are_valid - -PROJECT_NAME = "test-project-openai-attachment-processing" -TEST_MODEL = "gpt-4o-mini" - - -@pytest.fixture -def memory_logger(): - init_test_logger(PROJECT_NAME) - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -def _is_wrapped(client): - return hasattr(client, "_NamedWrapper__wrapped") - - -@pytest.mark.vcr -def test_openai_image_data_url_converts_to_attachment(memory_logger): - """Test that image data URLs in chat completions are converted to Attachment objects.""" - assert not memory_logger.pop() - - # Create a simple 1x1 red pixel PNG - base64_image = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8z8DwHwAFBQIAX8jx0gAAAABJRU5ErkJggg==" - data_url = f"data:image/png;base64,{base64_image}" - - client = wrap_openai(openai.OpenAI()) - - start = time.time() - response = client.chat.completions.create( - model=TEST_MODEL, - messages=[ - { - "role": "user", - "content": [ - {"type": "text", "text": "What color is this image?"}, - {"type": "image_url", "image_url": {"url": data_url}}, - ], - } - ], - ) - end = time.time() - - # Verify we got a successful response - assert response - assert response.choices - assert response.choices[0].message.content - # The model should be able to see the image - content = response.choices[0].message.content.lower() - assert "red" in content or "pink" in content or "color" in content - - # Verify spans were created - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - - # Verify metrics - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert TEST_MODEL in span["metadata"]["model"] - assert span["metadata"]["provider"] == "openai" - - # Verify input contains the attachment - assert span["input"] - assert len(span["input"]) == 1 - message_content = span["input"][0]["content"] - assert len(message_content) == 2 - - # First item should be text - assert message_content[0]["type"] == "text" - assert message_content[0]["text"] == "What color is this image?" - - # Second item should have the image URL converted to Attachment - assert message_content[1]["type"] == "image_url" - image_url_value = message_content[1]["image_url"]["url"] - assert isinstance(image_url_value, Attachment) - assert image_url_value.reference["type"] == "braintrust_attachment" - assert image_url_value.reference["content_type"] == "image/png" - assert image_url_value.reference["filename"] == "image.png" - assert image_url_value.reference["key"] - - -@pytest.mark.vcr -def test_openai_pdf_data_url_converts_to_attachment(memory_logger): - """Test that PDF data URLs in chat completions are converted to Attachment objects.""" - assert not memory_logger.pop() - - # Create a minimal PDF - base64_pdf = "JVBERi0xLjAKMSAwIG9iago8PC9UeXBlL0NhdGFsb2cvUGFnZXMgMiAwIFI+PmVuZG9iagoyIDAgb2JqCjw8L1R5cGUvUGFnZXMvS2lkc1szIDAgUl0vQ291bnQgMT4+ZW5kb2JqCjMgMCBvYmoKPDwvVHlwZS9QYWdlL01lZGlhQm94WzAgMCA2MTIgNzkyXT4+ZW5kb2JqCnhyZWYKMCA0CjAwMDAwMDAwMDAgNjU1MzUgZg0KMDAwMDAwMDAxMCAwMDAwMCBuDQowMDAwMDAwMDUzIDAwMDAwIG4NCjAwMDAwMDAxMDIgMDAwMDAgbg0KdHJhaWxlcgo8PC9TaXplIDQvUm9vdCAxIDAgUj4+CnN0YXJ0eHJlZgoxNDkKJUVPRg==" - data_url = f"data:application/pdf;base64,{base64_pdf}" - - client = wrap_openai(openai.OpenAI()) - - start = time.time() - response = client.chat.completions.create( - model=TEST_MODEL, - messages=[ - { - "role": "user", - "content": [ - {"type": "text", "text": "What type of document is this?"}, - { - "type": "file", - "file": { - "file_data": data_url, - "filename": "test.pdf", - }, - }, - ], - } - ], - ) - end = time.time() - - # Verify we got a successful response - assert response - assert response.choices - assert response.choices[0].message.content - - # Verify spans were created - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - - # Verify metrics - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert TEST_MODEL in span["metadata"]["model"] - assert span["metadata"]["provider"] == "openai" - - # Verify input contains the attachment - assert span["input"] - assert len(span["input"]) == 1 - message_content = span["input"][0]["content"] - assert len(message_content) == 2 - - # First item should be text - assert message_content[0]["type"] == "text" - assert message_content[0]["text"] == "What type of document is this?" - - # Second item should have the file_data converted to Attachment - assert message_content[1]["type"] == "file" - file_data_value = message_content[1]["file"]["file_data"] - assert isinstance(file_data_value, Attachment) - assert file_data_value.reference["type"] == "braintrust_attachment" - assert file_data_value.reference["content_type"] == "application/pdf" - # Should use the provided filename, not a generic one - assert file_data_value.reference["filename"] == "test.pdf" - assert file_data_value.reference["key"] - - -@pytest.mark.vcr -def test_openai_pdf_data_url_without_filename_uses_fallback(memory_logger): - """Test that PDF data URLs without a filename use the generated fallback.""" - assert not memory_logger.pop() - - # Create a minimal PDF - base64_pdf = "JVBERi0xLjAKMSAwIG9iago8PC9UeXBlL0NhdGFsb2cvUGFnZXMgMiAwIFI+PmVuZG9iagoyIDAgb2JqCjw8L1R5cGUvUGFnZXMvS2lkc1szIDAgUl0vQ291bnQgMT4+ZW5kb2JqCjMgMCBvYmoKPDwvVHlwZS9QYWdlL01lZGlhQm94WzAgMCA2MTIgNzkyXT4+ZW5kb2JqCnhyZWYKMCA0CjAwMDAwMDAwMDAgNjU1MzUgZg0KMDAwMDAwMDAxMCAwMDAwMCBuDQowMDAwMDAwMDUzIDAwMDAwIG4NCjAwMDAwMDAxMDIgMDAwMDAgbg0KdHJhaWxlcgo8PC9TaXplIDQvUm9vdCAxIDAgUj4+CnN0YXJ0eHJlZgoxNDkKJUVPRg==" - data_url = f"data:application/pdf;base64,{base64_pdf}" - - client = wrap_openai(openai.OpenAI()) - - start = time.time() - response = client.chat.completions.create( - model=TEST_MODEL, - messages=[ - { - "role": "user", - "content": [ - {"type": "text", "text": "What type of document is this?"}, - { - "type": "file", - "file": { - "file_data": data_url, - # No filename provided - should use fallback - }, - }, - ], - } - ], - ) - end = time.time() - - # Verify we got a successful response - assert response - assert response.choices - assert response.choices[0].message.content - - # Verify spans were created - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - - # Verify metrics - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert TEST_MODEL in span["metadata"]["model"] - assert span["metadata"]["provider"] == "openai" - - # Verify input contains the attachment - assert span["input"] - assert len(span["input"]) == 1 - message_content = span["input"][0]["content"] - assert len(message_content) == 2 - - # First item should be text - assert message_content[0]["type"] == "text" - assert message_content[0]["text"] == "What type of document is this?" - - # Second item should have the file_data converted to Attachment - assert message_content[1]["type"] == "file" - file_data_value = message_content[1]["file"]["file_data"] - assert isinstance(file_data_value, Attachment) - assert file_data_value.reference["type"] == "braintrust_attachment" - assert file_data_value.reference["content_type"] == "application/pdf" - # Should use the fallback filename since none was provided - assert file_data_value.reference["filename"] == "document.pdf" - assert file_data_value.reference["key"] - - -@pytest.mark.vcr -def test_openai_regular_url_preserved(memory_logger): - """Test that regular URLs (non-data URLs) are preserved unchanged.""" - assert not memory_logger.pop() - - # Use a regular URL (not a data URL) - regular_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" - - client = wrap_openai(openai.OpenAI()) - - start = time.time() - response = client.chat.completions.create( - model=TEST_MODEL, - messages=[ - { - "role": "user", - "content": [ - {"type": "text", "text": "What's in this image?"}, - {"type": "image_url", "image_url": {"url": regular_url}}, - ], - } - ], - ) - end = time.time() - - # Verify we got a successful response - assert response - assert response.choices - assert response.choices[0].message.content - - # Verify spans were created - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - - # Verify metrics - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - - # Verify input has the URL unchanged (not converted to Attachment) - assert span["input"] - message_content = span["input"][0]["content"] - assert message_content[1]["type"] == "image_url" - image_url_value = message_content[1]["image_url"]["url"] - # Regular URLs should NOT be converted to Attachment - assert isinstance(image_url_value, str) - assert image_url_value == regular_url - - -@pytest.mark.vcr -def test_openai_unwrapped_client_no_conversion(memory_logger): - """Test that unwrapped clients don't process attachments and don't generate spans.""" - assert not memory_logger.pop() - - # Create a simple image data URL - base64_image = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8z8DwHwAFBQIAX8jx0gAAAABJRU5ErkJggg==" - data_url = f"data:image/png;base64,{base64_image}" - - # Use unwrapped client - client = openai.OpenAI() - - response = client.chat.completions.create( - model=TEST_MODEL, - messages=[ - { - "role": "user", - "content": [ - {"type": "text", "text": "What color is this image?"}, - {"type": "image_url", "image_url": {"url": data_url}}, - ], - } - ], - ) - - # Verify we got a successful response - assert response - assert response.choices - assert response.choices[0].message.content - - # No spans should be generated with unwrapped client - assert not memory_logger.pop() diff --git a/py/src/braintrust/wrappers/test_openai.py b/py/src/braintrust/wrappers/test_openai.py deleted file mode 100644 index d763cf22e..000000000 --- a/py/src/braintrust/wrappers/test_openai.py +++ /dev/null @@ -1,2035 +0,0 @@ -import asyncio -import time - -import braintrust -import openai -import pytest -from braintrust import logger, wrap_openai -from braintrust.oai import ChatCompletionWrapper -from braintrust.test_helpers import assert_dict_matches, init_test_logger -from braintrust.wrappers.test_utils import assert_metrics_are_valid, run_in_subprocess, verify_autoinstrument_script -from openai import AsyncOpenAI -from openai._types import NOT_GIVEN -from pydantic import BaseModel - -TEST_ORG_ID = "test-org-openai-py-tracing" -PROJECT_NAME = "test-project-openai-py-tracing" -TEST_MODEL = "gpt-4o-mini" # cheapest model for tests -TEST_PROMPT = "What's 12 + 12?" -TEST_SYSTEM_PROMPT = "You are a helpful assistant that only responds with numbers." - - -@pytest.fixture -def memory_logger(): - init_test_logger(PROJECT_NAME) - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -def test_tracing_processor_sets_current_span(memory_logger): - """Ensure that on_trace_start sets the span as current so nested spans work.""" - pytest.importorskip("agents", reason="agents package not available") - from braintrust.wrappers.openai import BraintrustTracingProcessor - - assert not memory_logger.pop() - processor = BraintrustTracingProcessor() - - class DummyTrace: - def __init__(self): - self.trace_id = "test-trace-id" - self.name = "test-trace" - - def export(self): - return {"group_id": "group", "metadata": {"foo": "bar"}} - - trace = DummyTrace() - - with braintrust.start_span(name="parent-span") as parent_span: - assert braintrust.current_span() == parent_span - processor.on_trace_start(trace) - created_span = processor._spans[trace.trace_id] - assert braintrust.current_span() == created_span - - processor.on_trace_end(trace) - assert braintrust.current_span() == parent_span - - spans = memory_logger.pop() - assert spans - assert any(span.get("span_attributes", {}).get("name") == trace.name for span in spans) - - -@pytest.mark.vcr -def test_openai_chat_metrics(memory_logger): - assert not memory_logger.pop() - - client = openai.OpenAI() - clients = [client, wrap_openai(client)] - - for client in clients: - start = time.time() - response = client.chat.completions.create( - model=TEST_MODEL, messages=[{"role": "user", "content": TEST_PROMPT}] - ) - end = time.time() - - assert response - assert response.choices[0].message.content - assert ( - "24" in response.choices[0].message.content or "twenty-four" in response.choices[0].message.content.lower() - ) - - if not _is_wrapped(client): - assert not memory_logger.pop() - continue - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert TEST_MODEL in span["metadata"]["model"] - assert span["metadata"]["provider"] == "openai" - assert TEST_PROMPT in str(span["input"]) - - -@pytest.mark.vcr -def test_openai_responses_metrics(memory_logger): - assert not memory_logger.pop() - - # First test with an unwrapped client - unwrapped_client = openai.OpenAI() - unwrapped_response = unwrapped_client.responses.create( - model=TEST_MODEL, - input=TEST_PROMPT, - instructions="Just the number please", - ) - assert unwrapped_response - assert unwrapped_response.output - assert len(unwrapped_response.output) > 0 - unwrapped_content = unwrapped_response.output[0].content[0].text - - # No spans should be generated with unwrapped client - assert not memory_logger.pop() - - # Now test with wrapped client - client = wrap_openai(openai.OpenAI()) - start = time.time() - response = client.responses.create( - model=TEST_MODEL, - input=TEST_PROMPT, - instructions="Just the number please", - ) - end = time.time() - - assert response - # Extract content from output field - assert response.output - assert len(response.output) > 0 - wrapped_content = response.output[0].content[0].text - - # Both should contain a numeric response for the math question - assert "24" in unwrapped_content or "twenty-four" in unwrapped_content.lower() - assert "24" in wrapped_content or "twenty-four" in wrapped_content.lower() - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert 0 <= metrics.get("prompt_cached_tokens", 0) - assert 0 <= metrics.get("completion_reasoning_tokens", 0) - assert TEST_MODEL in span["metadata"]["model"] - assert span["metadata"]["provider"] == "openai" - assert TEST_PROMPT in str(span["input"]) - assert len(span["output"]) > 0 - span_output_text = span["output"][0]["content"][0]["text"] - assert "24" in span_output_text or "twenty-four" in span_output_text.lower() - - # Test responses.parse method - class NumberAnswer(BaseModel): - value: int - reasoning: str - - # First test with unwrapped client - should work but no spans - parse_response = unwrapped_client.responses.parse(model=TEST_MODEL, input=TEST_PROMPT, text_format=NumberAnswer) - assert parse_response - # Access the structured output via text_format - assert parse_response.output_parsed - assert parse_response.output_parsed.value == 24 - assert parse_response.output_parsed.reasoning - - # No spans should be generated with unwrapped client - assert not memory_logger.pop() - - # Now test with wrapped client - should generate spans - start = time.time() - parse_response = client.responses.parse(model=TEST_MODEL, input=TEST_PROMPT, text_format=NumberAnswer) - end = time.time() - - assert parse_response - # Access the structured output via text_format - assert parse_response.output_parsed - assert parse_response.output_parsed.value == 24 - assert parse_response.output_parsed.reasoning - - # Verify spans are generated - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert 0 <= metrics.get("prompt_cached_tokens", 0) - assert 0 <= metrics.get("completion_reasoning_tokens", 0) - assert TEST_MODEL in span["metadata"]["model"] - assert span["metadata"]["provider"] == "openai" - assert TEST_PROMPT in str(span["input"]) - assert len(span["output"]) > 0 - assert span["output"][0]["content"][0]["parsed"] - assert span["output"][0]["content"][0]["parsed"]["value"] == 24 - assert span["output"][0]["content"][0]["parsed"]["reasoning"] == parse_response.output_parsed.reasoning - - -@pytest.mark.vcr -def test_openai_responses_metadata_preservation(memory_logger): - """Test that additional metadata fields in responses are preserved.""" - assert not memory_logger.pop() - - client = wrap_openai(openai.OpenAI()) - - # Test with responses.create - the response object has various metadata fields - start = time.time() - response = client.responses.create( - model=TEST_MODEL, - input="What is 10 + 10?", - instructions="Respond with just the number", - ) - end = time.time() - - assert response - assert response.output - - # Check that the response has metadata fields like id, created_at, object, etc. - assert hasattr(response, "id") - assert hasattr(response, "created_at") - assert hasattr(response, "object") - assert hasattr(response, "model") - - # Verify spans capture metadata - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - - # Check that span metadata includes the parameters - assert TEST_MODEL in span["metadata"]["model"] # Model name may include version date - assert span["metadata"]["provider"] == "openai" - assert span["metadata"]["instructions"] == "Respond with just the number" - - # Check that response metadata is preserved (non-output, non-usage fields) - # The metadata should be in span["metadata"] after our changes - assert "metadata" in span - if "id" in span.get("metadata", {}): - # Response metadata like id, created, object should be preserved - assert span["metadata"]["id"] == response.id - - # Verify metrics are properly extracted - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert "time_to_first_token" in metrics - - # Test with responses.parse to ensure metadata is preserved there too - class SimpleAnswer(BaseModel): - value: int - - start = time.time() - parse_response = client.responses.parse( - model=TEST_MODEL, - input="What is 15 + 15?", - text_format=SimpleAnswer, - ) - end = time.time() - - assert parse_response - assert parse_response.output_parsed - assert parse_response.output_parsed.value == 30 - - # Verify metadata preservation in parse response - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - - # Check parameters are in metadata - assert TEST_MODEL in span["metadata"]["model"] # Model name may include version date - assert span["metadata"]["provider"] == "openai" - - # Verify the structured output is captured - assert span["output"][0]["content"][0]["parsed"]["value"] == 30 - - # Check metrics - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - - -@pytest.mark.vcr -def test_openai_responses_sparse_indices(memory_logger): - """Test that streaming responses with sparse/out-of-order indices are handled correctly.""" - assert not memory_logger.pop() - - from braintrust.oai import ResponseWrapper - - # Create a mock response with sparse content indices (e.g., indices 0, 2, 5) - # This simulates a streaming response where items arrive out of order or with gaps - class MockResult: - def __init__( - self, - type, - content_index=None, - delta=None, - annotation_index=None, - annotation=None, - output_index=None, - item=None, - ): - self.type = type - if content_index is not None: - self.content_index = content_index - if delta is not None: - self.delta = delta - if annotation_index is not None: - self.annotation_index = annotation_index - if annotation is not None: - self.annotation = annotation - if output_index is not None: - self.output_index = output_index - if item is not None: - self.item = item - - class MockItem: - def __init__(self, id="test_id", type="message"): - self.id = id - self.type = type - - # Test sparse content indices - all_results = [ - MockResult("response.output_item.added", item=MockItem()), - MockResult("response.output_text.delta", content_index=0, delta="First", output_index=0), - MockResult("response.output_text.delta", content_index=2, delta="Third", output_index=0), # Gap at index 1 - MockResult("response.output_text.delta", content_index=5, delta="Sixth", output_index=0), # Gap at indices 3,4 - ] - - # Process the results - wrapper = ResponseWrapper(None, None) - output = [{}] # Initialize with one output item - result = wrapper._postprocess_streaming_results(all_results) - - # Verify the output was built correctly with gaps filled - assert "output" in result - assert len(result["output"]) == 1 - content = result["output"][0].get("content", []) - - # Should have 6 items (indices 0-5) - assert len(content) >= 6 - assert content[0].get("text") == "First" - assert content[1].get("text", "") == "" # Gap should be empty - assert content[2].get("text") == "Third" - assert content[3].get("text", "") == "" # Gap should be empty - assert content[4].get("text", "") == "" # Gap should be empty - assert content[5].get("text") == "Sixth" - - # Test sparse annotation indices - all_results_with_annotations = [ - MockResult("response.output_item.added", item=MockItem()), - MockResult("response.output_text.delta", content_index=0, delta="Text", output_index=0), - MockResult( - "response.output_text.annotation.added", - content_index=0, - annotation_index=1, - annotation={"text": "Second annotation"}, - output_index=0, - ), - MockResult( - "response.output_text.annotation.added", - content_index=0, - annotation_index=3, - annotation={"text": "Fourth annotation"}, - output_index=0, - ), - ] - - result = wrapper._postprocess_streaming_results(all_results_with_annotations) - - # Verify annotations were built correctly with gaps filled - assert "output" in result - content = result["output"][0].get("content", []) - assert len(content) >= 1 - annotations = content[0].get("annotations", []) - - # Should have 4 items (indices 0-3) - assert len(annotations) >= 4 - assert annotations[0] == {} # Gap should be empty dict - assert annotations[1] == {"text": "Second annotation"} - assert annotations[2] == {} # Gap should be empty dict - assert annotations[3] == {"text": "Fourth annotation"} - - # No spans should be generated from this unit test - assert not memory_logger.pop() - -@pytest.mark.vcr -def test_openai_embeddings(memory_logger): - assert not memory_logger.pop() - - client = openai.OpenAI() - response = client.embeddings.create(model="text-embedding-ada-002", input="This is a test") - - assert response - assert response.data - assert response.data[0].embedding - - assert not memory_logger.pop() - - client2 = wrap_openai(openai.OpenAI()) - - start = time.time() - response2 = client2.embeddings.create(model="text-embedding-ada-002", input="This is a test") - end = time.time() - - assert response2 - assert response2.data - assert response2.data[0].embedding - - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - assert span["metadata"]["model"] == "text-embedding-ada-002" - assert span["metadata"]["provider"] == "openai" - assert "This is a test" in str(span["input"]) - - -@pytest.mark.vcr -def test_openai_chat_streaming_sync(memory_logger): - assert not memory_logger.pop() - - client = openai.OpenAI() - clients = [(client, False), (wrap_openai(client), True)] - - for client, is_wrapped in clients: - start = time.time() - - stream = client.chat.completions.create( - model=TEST_MODEL, - messages=[{"role": "user", "content": TEST_PROMPT}], - stream=True, - stream_options={"include_usage": True}, - ) - - chunks = [] - for chunk in stream: - chunks.append(chunk) - end = time.time() - - # Verify streaming works - assert chunks - assert len(chunks) > 1 - - # Concatenate content from chunks to verify - content = "" - for chunk in chunks: - if chunk.choices and chunk.choices[0].delta.content: - content += chunk.choices[0].delta.content - - # Make sure we got a valid answer in the content - assert "24" in content or "twenty-four" in content.lower() - - if not is_wrapped: - assert not memory_logger.pop() - continue - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert TEST_MODEL in span["metadata"]["model"] - # assert span["metadata"]["provider"] == "openai" - assert TEST_PROMPT in str(span["input"]) - assert "24" in str(span["output"]) or "twenty-four" in str(span["output"]).lower() - - -@pytest.mark.vcr -def test_openai_chat_with_system_prompt(memory_logger): - assert not memory_logger.pop() - - client = openai.OpenAI() - clients = [(client, False), (wrap_openai(client), True)] - - for client, is_wrapped in clients: - response = client.chat.completions.create( - model=TEST_MODEL, - messages=[{"role": "system", "content": TEST_SYSTEM_PROMPT}, {"role": "user", "content": TEST_PROMPT}], - ) - - assert response - assert response.choices - assert "24" in response.choices[0].message.content - - if not is_wrapped: - assert not memory_logger.pop() - continue - - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - inputs = span["input"] - assert len(inputs) == 2 - assert inputs[0]["role"] == "system" - assert inputs[0]["content"] == TEST_SYSTEM_PROMPT - assert inputs[1]["role"] == "user" - assert inputs[1]["content"] == TEST_PROMPT - - -@pytest.mark.vcr -def test_openai_client_comparison(memory_logger): - """Test that wrapped and unwrapped clients produce the same output.""" - assert not memory_logger.pop() - - # Get regular and wrapped clients - client = openai.OpenAI() - clients = [(client, False), (wrap_openai(client), True)] - - for client, is_wrapped in clients: - response = client.chat.completions.create( - model=TEST_MODEL, messages=[{"role": "user", "content": TEST_PROMPT}], temperature=0, seed=42 - ) - - # Both should have data - assert response.choices[0].message.content - - if not is_wrapped: - assert not memory_logger.pop() - continue - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - - -@pytest.mark.vcr -def test_openai_client_error(memory_logger): - assert not memory_logger.pop() - - # For the wrapped client only, since we need special error handling - client = wrap_openai(openai.OpenAI()) - - # Use a non-existent model to force an error - fake_model = "non-existent-model" - - try: - client.chat.completions.create(model=fake_model, messages=[{"role": "user", "content": TEST_PROMPT}]) - pytest.fail("Expected an exception but none was raised") - except Exception as e: - # We expect an error here - pass - - logs = memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - assert log["project_id"] == PROJECT_NAME - # It seems the error field may not be present in newer OpenAI versions - # Just check that we got a log entry with the fake model - assert fake_model in str(log) - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_openai_chat_async(memory_logger): - assert not memory_logger.pop() - - # First test with an unwrapped async client - client = AsyncOpenAI() - resp = await client.chat.completions.create(model=TEST_MODEL, messages=[{"role": "user", "content": TEST_PROMPT}]) - - assert resp - assert resp.choices - assert resp.choices[0].message.content - content = resp.choices[0].message.content - - # Verify it contains a correct response - assert "24" in content or "twenty-four" in content.lower() - - # No spans should be generated with unwrapped client - assert not memory_logger.pop() - - # Now test with wrapped client - client2 = wrap_openai(AsyncOpenAI()) - - start = time.time() - resp2 = await client2.chat.completions.create( - model=TEST_MODEL, messages=[{"role": "user", "content": TEST_PROMPT}] - ) - end = time.time() - - assert resp2 - assert resp2.choices - assert resp2.choices[0].message.content - content2 = resp2.choices[0].message.content - - # Verify the wrapped client also gives correct responses - assert "24" in content2 or "twenty-four" in content2.lower() - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert TEST_MODEL in span["metadata"]["model"] - # assert span["metadata"]["provider"] == "openai" - assert TEST_PROMPT in str(span["input"]) - - -@pytest.mark.asyncio -@pytest.mark.vcr -async def test_openai_responses_async(memory_logger): - assert not memory_logger.pop() - - client = AsyncOpenAI() - clients = [(client, False), (wrap_openai(client), True)] - - for client, is_wrapped in clients: - start = time.time() - - resp = await client.responses.create( - model=TEST_MODEL, - input=TEST_PROMPT, - instructions="Just the number please", - ) - end = time.time() - - assert resp - assert resp.output - assert len(resp.output) > 0 - - # Extract the text from the output - content = resp.output[0].content[0].text - - # Verify response contains correct answer - assert "24" in content or "twenty-four" in content.lower() - - if not is_wrapped: - assert not memory_logger.pop() - continue - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert 0 <= metrics.get("prompt_cached_tokens", 0) - assert 0 <= metrics.get("completion_reasoning_tokens", 0) - assert TEST_MODEL in span["metadata"]["model"] - # assert span["metadata"]["provider"] == "openai" - assert TEST_PROMPT in str(span["input"]) - - # Test responses.parse method - class NumberAnswer(BaseModel): - value: int - reasoning: str - - for client, is_wrapped in clients: - if not is_wrapped: - # Test unwrapped client first - parse_response = await client.responses.parse( - model=TEST_MODEL, input=TEST_PROMPT, text_format=NumberAnswer - ) - assert parse_response - # Access the structured output via text_format - assert parse_response.output_parsed - assert parse_response.output_parsed.value == 24 - assert parse_response.output_parsed.reasoning - - # No spans should be generated with unwrapped client - assert not memory_logger.pop() - else: - # Test wrapped client - start = time.time() - parse_response = await client.responses.parse( - model=TEST_MODEL, input=TEST_PROMPT, text_format=NumberAnswer - ) - end = time.time() - - assert parse_response - # Access the structured output via text_format - assert parse_response.output_parsed - assert parse_response.output_parsed.value == 24 - assert parse_response.output_parsed.reasoning - - # Verify spans were created - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert 0 <= metrics.get("prompt_cached_tokens", 0) - assert 0 <= metrics.get("completion_reasoning_tokens", 0) - assert TEST_MODEL in span["metadata"]["model"] - # assert span["metadata"]["provider"] == "openai" - assert TEST_PROMPT in str(span["input"]) - assert len(span["output"]) > 0 - assert span["output"][0]["content"][0]["parsed"] - assert span["output"][0]["content"][0]["parsed"]["value"] == 24 - assert span["output"][0]["content"][0]["parsed"]["reasoning"] == parse_response.output_parsed.reasoning - - -@pytest.mark.asyncio -@pytest.mark.vcr -async def test_openai_embeddings_async(memory_logger): - assert not memory_logger.pop() - - client = AsyncOpenAI() - clients = [(client, False), (wrap_openai(client), True)] - - for client, is_wrapped in clients: - start = time.time() - - resp = await client.embeddings.create(model="text-embedding-ada-002", input="This is a test") - end = time.time() - - assert resp - assert resp.data - assert resp.data[0].embedding - - if not is_wrapped: - assert not memory_logger.pop() - continue - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - assert span["metadata"]["model"] == "text-embedding-ada-002" - assert span["metadata"]["provider"] == "openai" - assert "This is a test" in str(span["input"]) - - -@pytest.mark.asyncio -@pytest.mark.vcr -async def test_openai_chat_streaming_async(memory_logger): - assert not memory_logger.pop() - - client = AsyncOpenAI() - clients = [(client, False), (wrap_openai(client), True)] - - for client, is_wrapped in clients: - start = time.time() - - stream = await client.chat.completions.create( - model=TEST_MODEL, - messages=[{"role": "user", "content": TEST_PROMPT}], - stream=True, - stream_options={"include_usage": True}, - ) - - chunks = [] - async for chunk in stream: - chunks.append(chunk) - end = time.time() - - assert chunks - assert len(chunks) > 1 - - # Concatenate content from chunks to verify - content = "" - for chunk in chunks: - if chunk.choices and chunk.choices[0].delta.content: - content += chunk.choices[0].delta.content - - # Make sure we got a valid answer in the content - assert "24" in content or "twenty-four" in content.lower() - - if not is_wrapped: - assert not memory_logger.pop() - continue - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert span["metadata"]["stream"] == True - assert TEST_MODEL in span["metadata"]["model"] - # assert span["metadata"]["provider"] == "openai" - assert TEST_PROMPT in str(span["input"]) - assert "24" in str(span["output"]) or "twenty-four" in str(span["output"]).lower() - - -@pytest.mark.asyncio -@pytest.mark.vcr -async def test_openai_chat_async_with_system_prompt(memory_logger): - assert not memory_logger.pop() - - client = AsyncOpenAI() - clients = [(client, False), (wrap_openai(client), True)] - - for client, is_wrapped in clients: - response = await client.chat.completions.create( - model=TEST_MODEL, - messages=[{"role": "system", "content": TEST_SYSTEM_PROMPT}, {"role": "user", "content": TEST_PROMPT}], - ) - - assert response - assert response.choices - assert "24" in response.choices[0].message.content - - if not is_wrapped: - assert not memory_logger.pop() - continue - - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - inputs = span["input"] - assert len(inputs) == 2 - assert inputs[0]["role"] == "system" - assert inputs[0]["content"] == TEST_SYSTEM_PROMPT - assert inputs[1]["role"] == "user" - assert inputs[1]["content"] == TEST_PROMPT - - -@pytest.mark.asyncio -@pytest.mark.vcr -async def test_openai_client_async_comparison(memory_logger): - """Test that wrapped and unwrapped async clients produce the same output.""" - assert not memory_logger.pop() - - # Get regular and wrapped clients - regular_client = AsyncOpenAI() - wrapped_client = wrap_openai(AsyncOpenAI()) - - # Test with regular client - normal_response = await regular_client.chat.completions.create( - model=TEST_MODEL, messages=[{"role": "user", "content": TEST_PROMPT}], temperature=0, seed=42 - ) - - # No spans should be created for unwrapped client - assert not memory_logger.pop() - - # Test with wrapped client - wrapped_response = await wrapped_client.chat.completions.create( - model=TEST_MODEL, messages=[{"role": "user", "content": TEST_PROMPT}], temperature=0, seed=42 - ) - - # Both should have data - assert normal_response.choices[0].message.content - assert wrapped_response.choices[0].message.content - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - - -@pytest.mark.asyncio -@pytest.mark.vcr -async def test_openai_client_async_error(memory_logger): - assert not memory_logger.pop() - - # For the wrapped client only, since we need special error handling - client = wrap_openai(AsyncOpenAI()) - - # Use a non-existent model to force an error - fake_model = "non-existent-model" - - try: - await client.chat.completions.create(model=fake_model, messages=[{"role": "user", "content": TEST_PROMPT}]) - pytest.fail("Expected an exception but none was raised") - except Exception as e: - # We expect an error here - pass - - logs = memory_logger.pop() - assert len(logs) == 1 - log = logs[0] - assert log["project_id"] == PROJECT_NAME - # It seems the error field may not be present in newer OpenAI versions - # Just check that we got a log entry with the fake model - assert fake_model in str(log) - - -@pytest.mark.asyncio -@pytest.mark.vcr -async def test_openai_chat_async_context_manager(memory_logger): - """Test async context manager behavior for chat completions streams.""" - assert not memory_logger.pop() - - client = AsyncOpenAI() - clients = [(client, False), (wrap_openai(client), True)] - - for client, is_wrapped in clients: - start = time.time() - stream = await client.chat.completions.create( - model=TEST_MODEL, - messages=[{"role": "user", "content": TEST_PROMPT}], - stream=True, - stream_options={"include_usage": True}, - ) - - # Test the context manager behavior - chunks = [] - async with stream as s: - async for chunk in s: - chunks.append(chunk) - end = time.time() - - # Verify we got chunks from the stream - assert chunks - assert len(chunks) > 1 - - # Concatenate content from chunks to verify - content = "" - for chunk in chunks: - if chunk.choices and chunk.choices[0].delta.content: - content += chunk.choices[0].delta.content - - # Make sure we got a valid answer in the content - assert "24" in content or "twenty-four" in content.lower() - - if not is_wrapped: - assert not memory_logger.pop() - continue - - # Check metrics - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert span["metadata"]["stream"] == True - assert "24" in str(span["output"]) or "twenty-four" in str(span["output"]).lower() - - -@pytest.mark.asyncio -@pytest.mark.vcr -async def test_openai_streaming_with_break(memory_logger): - """Test breaking out of the streaming loop early.""" - assert not memory_logger.pop() - - # Only test with wrapped client - client = wrap_openai(AsyncOpenAI()) - - start = time.time() - stream = await client.chat.completions.create( - model=TEST_MODEL, messages=[{"role": "user", "content": TEST_PROMPT}], stream=True - ) - - # Only process the first few chunks - counter = 0 - async for chunk in stream: - counter += 1 - if counter >= 2: - break - end = time.time() - - # We should still get valid metrics even with early break - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - metrics = span["metrics"] - assert metrics["time_to_first_token"] >= 0 - - -@pytest.mark.asyncio -@pytest.mark.vcr -async def test_openai_chat_error_in_async_context(memory_logger): - """Test error handling inside the async context manager.""" - assert not memory_logger.pop() - - # We only test the wrapped client for this test since we need to check span error handling - client = wrap_openai(AsyncOpenAI()) - - stream = await client.chat.completions.create( - model=TEST_MODEL, messages=[{"role": "user", "content": TEST_PROMPT}], stream=True - ) - - # Simulate an error during streaming - try: - async with stream as s: - counter = 0 - async for chunk in s: - counter += 1 - if counter >= 2: - raise ValueError("Intentional test error") - pytest.fail("Expected an exception but none was raised") - except ValueError as e: - assert "Intentional test error" in str(e) - - # We should still get valid metrics even with error - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - # The error field might not be present in newer versions - # Just check that we got a span with time metrics - assert span["metrics"]["time_to_first_token"] >= 0 - - -@pytest.mark.asyncio -@pytest.mark.vcr -async def test_openai_response_streaming_async(memory_logger): - """Test the newer responses API with streaming.""" - assert not memory_logger.pop() - - client = openai.AsyncOpenAI() - clients = [client, wrap_openai(client)] - - for client in clients: - start = time.time() - - stream = await client.responses.create(model=TEST_MODEL, input="What's 12 + 12?", stream=True) - - chunks = [] - async for chunk in stream: - if chunk.type == "response.output_text.delta": - chunks.append(chunk.delta) - end = time.time() - output = "".join(chunks) - - assert chunks - assert len(chunks) > 1 - - assert "24" in output - - if not _is_wrapped(client): - assert not memory_logger.pop() - continue - # verify the span is created - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - assert span["metadata"]["stream"] == True - assert "What's 12 + 12?" in str(span["input"]) - assert "24" in str(span["output"]) - - -@pytest.mark.asyncio -@pytest.mark.vcr -async def test_openai_async_parallel_requests(memory_logger): - """Test multiple parallel async requests with the wrapped client.""" - assert not memory_logger.pop() - - client = wrap_openai(AsyncOpenAI()) - - # Create multiple prompts - prompts = [f"What is {i} + {i}?" for i in range(3, 6)] - - # Run requests in parallel - tasks = [ - client.chat.completions.create(model=TEST_MODEL, messages=[{"role": "user", "content": prompt}]) - for prompt in prompts - ] - - # Wait for all to complete - results = await asyncio.gather(*tasks) - - # Check all results - assert len(results) == 3 - for i, result in enumerate(results): - assert result.choices[0].message.content - - # Check that all spans were created - spans = memory_logger.pop() - assert len(spans) == 3 - - # Verify each span has proper data - for i, span in enumerate(spans): - assert TEST_MODEL in span["metadata"]["model"] - # assert span["metadata"]["provider"] == "openai" - assert prompts[i] in str(span["input"]) - assert_metrics_are_valid(span["metrics"]) - - -@pytest.mark.vcr -def test_openai_not_given_filtering(memory_logger): - """Test that NOT_GIVEN values are filtered out of logged inputs but API call still works.""" - assert not memory_logger.pop() - - client = wrap_openai(openai.OpenAI()) - - # Make a call with NOT_GIVEN for optional parameters - response = client.chat.completions.create( - model=TEST_MODEL, - messages=[{"role": "user", "content": TEST_PROMPT}], - max_tokens=NOT_GIVEN, - top_p=NOT_GIVEN, - frequency_penalty=NOT_GIVEN, - temperature=0.5, # one real one - presence_penalty=NOT_GIVEN, - tools=NOT_GIVEN, - ) - - # Verify the API call worked normally - assert response - assert response.choices[0].message.content - assert "24" in response.choices[0].message.content or "twenty-four" in response.choices[0].message.content.lower() - - # Check the logged span - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - - assert_dict_matches( - span, - { - "input": [{"role": "user", "content": TEST_PROMPT}], - "metadata": { - "model": TEST_MODEL, - "provider": "openai", - "temperature": 0.5, - }, - }, - ) - # Verify NOT_GIVEN values are not in the logged metadata - meta = span["metadata"] - assert "NOT_GIVEN" not in str(meta) - for k in ["max_tokens", "top_p", "frequency_penalty", "presence_penalty", "tools"]: - assert k not in meta - - -@pytest.mark.vcr -def test_openai_responses_not_given_filtering(memory_logger): - """Test that NOT_GIVEN values are filtered out of logged inputs for responses API.""" - assert not memory_logger.pop() - - client = wrap_openai(openai.OpenAI()) - - # Make a call with NOT_GIVEN for optional parameters - response = client.responses.create( - model=TEST_MODEL, - input=TEST_PROMPT, - instructions="Just the number please", - max_output_tokens=NOT_GIVEN, - tools=NOT_GIVEN, - temperature=0.5, # one real parameter - top_p=NOT_GIVEN, - metadata=NOT_GIVEN, - store=NOT_GIVEN, - ) - - # Verify the API call worked normally - assert response - assert response.output - assert len(response.output) > 0 - content = response.output[0].content[0].text - assert "24" in content or "twenty-four" in content.lower() - - # Check the logged span - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - - assert_dict_matches( - span, - { - "input": TEST_PROMPT, - "metadata": { - "model": lambda x: TEST_MODEL in x, - "provider": "openai", - "temperature": 0.5, - "instructions": "Just the number please", - }, - }, - ) - # Verify NOT_GIVEN values are not in the logged metadata (only check original request params) - # Note: Response fields like max_output_tokens may appear in metadata from the actual response - meta = span["metadata"] - assert "NOT_GIVEN" not in str(meta) - - # Test responses.parse with NOT_GIVEN filtering - class NumberAnswer(BaseModel): - value: int - reasoning: str - - # Make a parse call with NOT_GIVEN for optional parameters - parse_response = client.responses.parse( - model=TEST_MODEL, - input=TEST_PROMPT, - text_format=NumberAnswer, - max_output_tokens=NOT_GIVEN, - tools=NOT_GIVEN, - temperature=0.7, # one real parameter - top_p=NOT_GIVEN, - metadata=NOT_GIVEN, - store=NOT_GIVEN, - ) - - # Verify the API call worked normally - assert parse_response - assert parse_response.output_parsed - assert parse_response.output_parsed.value == 24 - assert parse_response.output_parsed.reasoning - - # Check the logged span for parse - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - - assert_dict_matches( - span, - { - "input": TEST_PROMPT, - "metadata": { - "model": lambda x: TEST_MODEL in x, - "provider": "openai", - "temperature": 0.7, - "text_format": lambda tf: tf is not None and "NumberAnswer" in str(tf), - }, - }, - ) - # Verify NOT_GIVEN values are not in the logged metadata (only check original request params) - # Note: Response fields like max_output_tokens may appear in metadata from the actual response - meta = span["metadata"] - assert "NOT_GIVEN" not in str(meta) - # Verify the output is properly logged in the span - assert span["output"] - assert isinstance(span["output"], list) - assert len(span["output"]) > 0 - assert span["output"][0]["content"][0]["parsed"] - assert span["output"][0]["content"][0]["parsed"]["value"] == 24 - assert span["output"][0]["content"][0]["parsed"]["reasoning"] - - -@pytest.mark.vcr -def test_openai_parallel_tool_calls(memory_logger): - """Test parallel tool calls with both streaming and non-streaming modes.""" - assert not memory_logger.pop() - - # Define tools that can be called in parallel - tools = [ - { - "type": "function", - "function": { - "name": "get_weather", - "description": "Get the weather for a location", - "parameters": { - "type": "object", - "properties": {"location": {"type": "string", "description": "The location to get weather for"}}, - "required": ["location"], - }, - }, - }, - { - "type": "function", - "function": { - "name": "get_time", - "description": "Get the current time for a timezone", - "parameters": { - "type": "object", - "properties": {"timezone": {"type": "string", "description": "The timezone to get time for"}}, - "required": ["timezone"], - }, - }, - }, - ] - - client = openai.OpenAI() - clients = [client, wrap_openai(client)] - - for stream in [False, True]: - for client in clients: - start = time.time() - - resp = client.chat.completions.create( - model=TEST_MODEL, - messages=[{"role": "user", "content": "What's the weather in New York and the time in Tokyo?"}], - tools=tools, - temperature=0, - stream=stream, - stream_options={"include_usage": True} if stream else None, - ) - - if stream: - # Consume the stream - for chunk in resp: # type: ignore - # Exhaust the stream - pass - - end = time.time() - - if not _is_wrapped(client): - assert not memory_logger.pop() - continue - - # Verify spans were created with wrapped client - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - - # Validate the span structure - assert_dict_matches( - span, - { - "span_attributes": {"type": "llm", "name": "Chat Completion"}, - "metadata": { - "model": TEST_MODEL, - "provider": "openai", - "stream": stream, - "tools": lambda tools_list: len(tools_list) == 2 - and any(tool.get("function", {}).get("name") == "get_weather" for tool in tools_list) - and any(tool.get("function", {}).get("name") == "get_time" for tool in tools_list), - }, - "input": lambda inp: "What's the weather in New York and the time in Tokyo?" in str(inp), - "metrics": lambda m: assert_metrics_are_valid(m, start, end) is None, - }, - ) - - # Verify tool calls are in the output (if present) - if span.get("output") and isinstance(span["output"], list) and len(span["output"]) > 0: - message = span["output"][0].get("message", {}) - tool_calls = message.get("tool_calls") - if tool_calls and len(tool_calls) >= 2: - # Extract tool names, handling cases where function.name might be None - tool_names = [] - for call in tool_calls: - func = call.get("function", {}) - name = func.get("name") if isinstance(func, dict) else None - if name: - tool_names.append(name) - - # Check if we have the expected tools (only if names are available) - if tool_names: - assert "get_weather" in tool_names or "get_time" in tool_names, ( - f"Expected weather/time tools, got: {tool_names}" - ) - - -def _is_wrapped(client): - return hasattr(client, "_NamedWrapper__wrapped") - - -@pytest.mark.asyncio -@pytest.mark.vcr -async def test_braintrust_tracing_processor_current_span_detection(memory_logger): - """Test that BraintrustTracingProcessor currentSpan() detection works with OpenAI Agents SDK.""" - pytest.importorskip("agents", reason="agents package not available") - - import agents - import braintrust - from agents import Agent - from agents.run import AgentRunner - from braintrust.wrappers.openai import BraintrustTracingProcessor - - assert not memory_logger.pop() - - @braintrust.traced(name="parent_span_test") - async def test_function(instructions: str): - # Verify we're in a traced context - detected_parent = braintrust.current_span() - assert detected_parent is not None, "Parent span should exist in traced context" - assert detected_parent != braintrust.logger.NOOP_SPAN, "Should not be NOOP span" - - # Create processor WITHOUT parentSpan - should auto-detect via current_span() - processor = BraintrustTracingProcessor() - - # Set up tracing - agents.set_tracing_disabled(False) - agents.add_trace_processor(processor) - - try: - # Create a simple agent - agent = Agent( - name="test-agent", - model=TEST_MODEL, - instructions="You are a helpful assistant. Be very concise.", - ) - - # Run the agent - this should create spans as children of detected parent - runner = AgentRunner() - result = await runner.run(agent, instructions) - assert result is not None, "Agent should return a result" - assert hasattr(result, "final_output") or hasattr(result, "output"), "Result should have output" - - return result - finally: - processor.shutdown() - - # Execute the wrapped function - result = await test_function("What is 2+2? Just the number.") - assert result is not None, "Test function should return a result" - - # Verify span hierarchy in logged spans - spans = memory_logger.pop() - assert len(spans) >= 2, f"Should have at least parent and child spans, got {len(spans)}" - - # Find parent and child spans - parent_span = None - child_spans = [] - - for span in spans: - if span.get("span_attributes", {}).get("name") == "parent_span_test": - parent_span = span - elif span.get("span_attributes", {}).get("name") == "Agent workflow": - child_spans.append(span) - - assert parent_span is not None, "Should find parent span with name 'parent_span_test'" - assert len(child_spans) > 0, "Should find at least one child span with name 'Agent workflow'" - - # Verify the child span has the parent as its parent - if child_spans and parent_span: - child_span = child_spans[0] - # In Braintrust, parent-child relationships are represented by span_parents array - child_span_parents = child_span.get("span_parents", []) - parent_span_id = parent_span.get("span_id") - - assert parent_span_id is not None, "Parent span should have a span_id" - assert isinstance(child_span_parents, list) and len(child_span_parents) > 0, ( - "Child span should have span_parents array" - ) - assert parent_span_id in child_span_parents, ( - f"Child span should include parent span_id {parent_span_id} in its span_parents array {child_span_parents} (currentSpan detection)" - ) - - # Verify both spans have the same root_span_id - assert child_span.get("root_span_id") == parent_span.get("root_span_id"), ( - "Parent and child should share the same root_span_id" - ) - - # Verify input/output are properly logged on parent span - assert parent_span.get("input") is not None, "Parent span should have input logged" - assert parent_span.get("output") is not None, "Parent span should have output logged" - - # Verify that we have child spans beyond just "Agent workflow" - # The OpenAI SDK should generate multiple span types (generation, response, etc.) - parent_span_id = parent_span.get("span_id") - assert parent_span_id is not None, "Parent span should have a span_id" - - all_child_spans = [s for s in spans if parent_span_id in (s.get("span_parents") or [])] - - assert len(all_child_spans) >= 1, f"Should have at least 1 child span, but found {len(all_child_spans)}" - - # We should see spans like Generation, Response, etc. from the OpenAI SDK - span_types = [s.get("span_attributes", {}).get("type") for s in all_child_spans] - has_llm_spans = "llm" in span_types - has_task_spans = "task" in span_types - - assert has_llm_spans or has_task_spans, ( - f"Should have LLM or task type spans from OpenAI SDK, got types: {span_types}" - ) - - -@pytest.mark.asyncio -@pytest.mark.vcr -async def test_braintrust_tracing_processor_concurrency_bug(memory_logger): - """Test that reproduces the concurrency bug where overlapping traces mix up first_input/last_output.""" - pytest.importorskip("agents", reason="agents package not available") - - import asyncio - - import agents - from agents import Agent - from agents.run import AgentRunner - from braintrust.wrappers.openai import BraintrustTracingProcessor - - assert not memory_logger.pop() - - # Create a single shared processor instance - processor = BraintrustTracingProcessor() - - # Set up tracing - agents.set_tracing_disabled(False) - agents.add_trace_processor(processor) - - try: - # Create agents for testing - agent_a = Agent( - name="agent-a", model=TEST_MODEL, instructions="You are agent A. Just respond with 'A' and nothing else." - ) - - agent_b = Agent( - name="agent-b", model=TEST_MODEL, instructions="You are agent B. Just respond with 'B' and nothing else." - ) - - runner = AgentRunner() - - # Define async functions to run agents - async def run_agent_a(): - """Run agent A with a delay to ensure overlap""" - result = await runner.run(agent_a, "What's your name?") - # Add a small delay to ensure traces overlap - await asyncio.sleep(0.1) - return result - - async def run_agent_b(): - """Run agent B immediately""" - result = await runner.run(agent_b, "Who are you?") - return result - - # Run both agents concurrently to create overlapping traces - results = await asyncio.gather(run_agent_a(), run_agent_b()) - - result_a, result_b = results - assert result_a is not None, "Agent A should return a result" - assert result_b is not None, "Agent B should return a result" - - finally: - processor.shutdown() - - # Get all spans - spans = memory_logger.pop() - assert len(spans) >= 2, f"Should have at least 2 trace spans, got {len(spans)}" - - # Find the root trace spans (these are created by on_trace_start/on_trace_end) - # These are actually the "Agent workflow" spans, not the agent-a/agent-b spans - trace_spans = [] - for span in spans: - span_name = span.get("span_attributes", {}).get("name", "") - # The actual traces are "Agent workflow" spans with no parents - if span_name == "Agent workflow" and not span.get("span_parents"): - trace_spans.append(span) - - # We should have exactly 2 trace spans - assert len(trace_spans) == 2, f"Should have exactly 2 trace spans, got {len(trace_spans)}" - - # Identify which trace is for which agent by looking at the input - agent_a_trace = None - agent_b_trace = None - for trace in trace_spans: - input_str = str(trace.get("input", "")) - if "What's your name?" in input_str: - agent_a_trace = trace - elif "Who are you?" in input_str: - agent_b_trace = trace - - assert agent_a_trace is not None, "Could not find Agent A's trace" - assert agent_b_trace is not None, "Could not find Agent B's trace" - - # With the fix, both traces should have their correct input and output - # Verify Agent A trace has correct input/output - assert agent_a_trace.get("input") is not None, "Agent A trace should have input" - assert agent_a_trace.get("output") is not None, "Agent A trace should have output" - - # Verify Agent B trace has correct input/output - assert agent_b_trace.get("input") is not None, "Agent B trace should have input" - assert agent_b_trace.get("output") is not None, "Agent B trace should have output" - - # Verify the inputs are different (they should be from different prompts) - assert agent_a_trace.get("input") != agent_b_trace.get("input"), ( - "Agent A and B traces should have different inputs" - ) - - # Verify the outputs are different (agents respond differently) - if agent_a_trace.get("output") and agent_b_trace.get("output"): - assert agent_a_trace.get("output") != agent_b_trace.get("output"), ( - "Agent A and B traces should have different outputs" - ) - - -@pytest.mark.asyncio -@pytest.mark.vcr -@pytest.mark.skip(reason="OAI Implementation changed, skipping until update") -async def test_agents_tool_openai_nested_spans(memory_logger): - """Test that OpenAI calls inside agent tools are properly nested under the tool span.""" - pytest.importorskip("agents", reason="agents package not available") - - from agents import Agent, Runner, function_tool, set_trace_processors - from braintrust import current_span, wrap_openai - from braintrust.wrappers.openai import BraintrustTracingProcessor - - assert not memory_logger.pop() - - # Create a tool that uses OpenAI within a manual span - @function_tool(strict_mode=False) - def analyze_text(text: str): - """Analyze text and return a structured summary with key points, sentiment, and statistics.""" - client = wrap_openai(openai.OpenAI()) - with current_span().start_span(name="text_analysis_tool") as span: - span.log(input={"text": text}) - - # Use a simple prompt for testing - just like other tests in this file - simple_prompt = f"Analyze this text briefly: {text}" - - response = client.chat.completions.create( - model=TEST_MODEL, - messages=[{"role": "user", "content": simple_prompt}], - ) - result = response.choices[0].message.content - span.log(output={"analysis": result}) - return result - - # Set up tracing - set_trace_processors([BraintrustTracingProcessor()]) - - # Create agent with the tool - agent = Agent( - name="Text Analysis Agent", - instructions="You are a helpful assistant that analyzes text. When asked to analyze text, you MUST use the analyze_text tool. Always call the tool with the exact text provided by the user. After using the tool, provide a two sentence summary of what the tool returned.", - tools=[analyze_text], - ) - - # Run agent with a specific text to analyze - test_text = "Artificial intelligence is transforming industries worldwide. Companies are adopting AI technologies to improve efficiency and innovation. However, challenges like ethics and job displacement remain concerns." - result = await Runner.run( - agent, - f"Please analyze this text: '{test_text}'", - max_turns=3, - ) - - assert result is not None, "Agent should return a result" - - # Verify spans were created - spans = memory_logger.pop() - assert len(spans) >= 3, f"Should have at least 3 spans (agent workflow, tool, chat completion), got {len(spans)}" - - # Find different types of spans - agent_spans = [] - tool_spans = [] - chat_spans = [] - - for span in spans: - span_name = span.get("span_attributes", {}).get("name", "") - span_type = span.get("span_attributes", {}).get("type", "") - - if "Agent workflow" in span_name or span_type == "task": - agent_spans.append(span) - elif span_name == "text_analysis_tool": - tool_spans.append(span) - elif span_name == "Chat Completion" and span_type == "llm": - chat_spans.append(span) - - # Verify we have the expected spans - assert len(agent_spans) > 0, "Should have at least one agent workflow span" - assert len(tool_spans) == 1, f"Should have exactly one tool span, got {len(tool_spans)}" - assert len(chat_spans) == 1, f"Should have exactly one chat completion span, got {len(chat_spans)}" - - tool_span = tool_spans[0] - chat_span = chat_spans[0] - - # Verify the chat completion span is nested under the tool span - chat_span_parents = chat_span.get("span_parents", []) - tool_span_id = tool_span.get("span_id") - - assert tool_span_id is not None, "Tool span should have a span_id" - assert isinstance(chat_span_parents, list) and len(chat_span_parents) > 0, ( - "Chat completion span should have span_parents array" - ) - assert tool_span_id in chat_span_parents, ( - f"Chat completion span should include tool span_id {tool_span_id} in its span_parents array {chat_span_parents}" - ) - - # Verify the tool span has input/output logged - assert "input" in tool_span, "Tool span should have input logged" - assert test_text in str(tool_span["input"]), "Tool span input should contain the test text" - assert "output" in tool_span, "Tool span should have output logged" - - # Verify we have chat completion spans - assert len(chat_spans) >= 1, f"Should have at least one chat completion span, got {len(chat_spans)}" - chat_span = chat_spans[0] - chat_span_parents = chat_span.get("span_parents", []) - - # Verify the chat completion span is nested under the tool span - assert isinstance(chat_span_parents, list) and len(chat_span_parents) > 0, ( - "Chat completion span should have span_parents array" - ) - assert tool_span_id in chat_span_parents, ( - f"Chat completion span should include tool span_id {tool_span_id} in its span_parents array {chat_span_parents}" - ) - - # Verify the chat completion span has proper LLM data - assert "input" in chat_span, "Chat completion span should have input logged" - assert "output" in chat_span, "Chat completion span should have output logged" - assert chat_span["metadata"]["model"] == TEST_MODEL, "Chat completion should use test model" - assert len(str(chat_span["output"])) > 0, "Chat completion should have some output content" - - -def test_braintrust_tracing_processor_trace_metadata_logging(memory_logger): - """Test that trace metadata flows through to root span via on_trace_end.""" - pytest.importorskip("agents", reason="agents package not available") - - from braintrust.wrappers.openai import BraintrustTracingProcessor - - assert not memory_logger.pop() - - processor = BraintrustTracingProcessor() - - # Mock trace with metadata (simulates native trace() API) - class MockTrace: - def __init__(self, trace_id, name, metadata): - self.trace_id = trace_id - self.name = name - self.metadata = metadata - - def export(self): - return {"group_id": self.trace_id, "metadata": self.metadata} - - trace = MockTrace("test-trace", "Test Trace", {"conversation_id": "test-12345"}) - - # Execute trace lifecycle - processor.on_trace_start(trace) - processor.on_trace_end(trace) - - # Verify metadata was logged to root span - spans = memory_logger.pop() - root_span = spans[0] - assert root_span["metadata"]["conversation_id"] == "test-12345", "Should log trace metadata" - - -class TestPatchOpenAI: - """Tests for patch_openai().""" - - def test_patch_openai_sets_wrapped_flag(self): - """patch_openai() should set __braintrust_wrapped__ on openai module.""" - result = run_in_subprocess(""" - from braintrust.oai import patch_openai - import openai - - assert not hasattr(openai, "__braintrust_wrapped__") - patch_openai() - assert hasattr(openai, "__braintrust_wrapped__") - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_openai_wraps_new_clients(self): - """After patch_openai(), new OpenAI() clients should be wrapped.""" - result = run_in_subprocess(""" - from braintrust.oai import patch_openai - patch_openai() - - import openai - client = openai.OpenAI(api_key="test-key") - - # Check that chat completions is wrapped (our wrapper adds tracing) - # The wrapper replaces client.chat with a wrapped version - chat_type = type(client.chat).__name__ - print(f"chat_type={chat_type}") - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_openai_creates_spans(self): - """patch_openai() should create spans when making API calls.""" - result = run_in_subprocess(""" - from braintrust.oai import patch_openai - from braintrust.test_helpers import init_test_logger - from braintrust import logger - - # Set up memory logger - init_test_logger("test-auto") - with logger._internal_with_memory_background_logger() as memory_logger: - patch_openai() - - import openai - client = openai.OpenAI() - - # Make a call within a span context - import braintrust - with braintrust.start_span(name="test") as span: - try: - # This will fail without API key, but span should still be created - client.chat.completions.create( - model="gpt-4o-mini", - messages=[{"role": "user", "content": "hi"}], - ) - except Exception: - pass # Expected without API key - - # Check that spans were logged - spans = memory_logger.pop() - # Should have at least the parent span - assert len(spans) >= 1, f"Expected spans, got {spans}" - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_openai_before_import(self): - """patch_openai() should work when called before importing openai.""" - result = run_in_subprocess(""" - from braintrust.oai import patch_openai - - # Patch BEFORE importing openai - patch_openai() - - import openai - assert hasattr(openai, "__braintrust_wrapped__") - - client = openai.OpenAI(api_key="test-key") - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_openai_after_import(self): - """patch_openai() should work when called after importing openai.""" - result = run_in_subprocess(""" - import openai - from braintrust.oai import patch_openai - - # Patch AFTER importing openai - patch_openai() - - assert hasattr(openai, "__braintrust_wrapped__") - - client = openai.OpenAI(api_key="test-key") - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_openai_idempotent(self): - """Multiple patch_openai() calls should be safe.""" - result = run_in_subprocess(""" - from braintrust.oai import patch_openai - import openai - - patch_openai() - patch_openai() # Second call - should be no-op, not double-wrap - - # Verify we can still create clients - client = openai.OpenAI(api_key="test-key") - assert hasattr(client, "chat") - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_openai_chains_with_other_patches(self): - """patch_openai() should chain with other libraries that patch OpenAI.""" - result = run_in_subprocess(""" - import openai - - # Simulate another library (like Datadog) patching OpenAI first - other_library_init_called = [] - - class OtherLibraryOpenAI(openai.OpenAI): - def __init__(self, *args, **kwargs): - other_library_init_called.append(True) - super().__init__(*args, **kwargs) - - openai.OpenAI = OtherLibraryOpenAI - - # Now apply our patch - should subclass OtherLibraryOpenAI - from braintrust.oai import patch_openai - patch_openai() - - # Create a client - both patches should run - client = openai.OpenAI(api_key="test-key") - - # Verify other library's __init__ was called (chaining works) - assert len(other_library_init_called) == 1, "Other library's patch should have run" - - # Verify our patch was applied (client has wrapped chat) - assert hasattr(client, "chat"), "Client should have chat attribute" - - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - def test_patch_openai_chains_async_client(self): - """patch_openai() should chain with other libraries for AsyncOpenAI too.""" - result = run_in_subprocess(""" - import openai - - # Simulate another library patching AsyncOpenAI first - other_library_init_called = [] - - class OtherLibraryAsyncOpenAI(openai.AsyncOpenAI): - def __init__(self, *args, **kwargs): - other_library_init_called.append(True) - super().__init__(*args, **kwargs) - - openai.AsyncOpenAI = OtherLibraryAsyncOpenAI - - # Now apply our patch - from braintrust.oai import patch_openai - patch_openai() - - # Create an async client - both patches should run - client = openai.AsyncOpenAI(api_key="test-key") - - # Verify other library's __init__ was called - assert len(other_library_init_called) == 1, "Other library's patch should have run" - - # Verify our patch was applied - assert hasattr(client, "chat"), "Client should have chat attribute" - - print("SUCCESS") - """) - assert result.returncode == 0, f"Failed: {result.stderr}" - assert "SUCCESS" in result.stdout - - -class TestPatchOpenAISpans: - """VCR-based tests verifying that patch_openai() produces spans.""" - - @pytest.mark.vcr - def test_patch_openai_creates_spans(self, memory_logger): - """patch_openai() should create spans when making API calls.""" - from braintrust.oai import patch_openai - - assert not memory_logger.pop() - - patch_openai() - client = openai.OpenAI() - response = client.chat.completions.create( - model="gpt-4o-mini", - messages=[{"role": "user", "content": "Say hi"}], - ) - assert response.choices[0].message.content - - # Verify span was created - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["provider"] == "openai" - assert "gpt-4o-mini" in span["metadata"]["model"] - assert span["input"] - - -class TestPatchOpenAIAsyncSpans: - """VCR-based tests verifying that patch_openai() produces spans for async clients.""" - - @pytest.mark.vcr - @pytest.mark.asyncio - async def test_patch_openai_async_creates_spans(self, memory_logger): - """patch_openai() should create spans for async API calls.""" - from braintrust.oai import patch_openai - - assert not memory_logger.pop() - - patch_openai() - client = openai.AsyncOpenAI() - response = await client.chat.completions.create( - model="gpt-4o-mini", - messages=[{"role": "user", "content": "Say hi async"}], - ) - assert response.choices[0].message.content - - # Verify span was created - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - assert span["metadata"]["provider"] == "openai" - assert "gpt-4o-mini" in span["metadata"]["model"] - assert span["input"] - - -class TestAutoInstrumentOpenAI: - """Tests for auto_instrument() with OpenAI.""" - - def test_auto_instrument_openai(self): - """Test auto_instrument patches OpenAI, creates spans, and uninstrument works.""" - verify_autoinstrument_script("test_auto_openai.py") - -class TestZAICompatibleOpenAI: - """Tests for validating some ZAI compatibility with OpenAI wrapper.""" - - def test_chat_completion_streaming_none_arguments(self, memory_logger): - """Test that ChatCompletionWrapper handles None arguments in tool calls (e.g., GLM-4.6 behavior).""" - assert not memory_logger.pop() - - # Simulate streaming results with None arguments in tool calls - # This mimics the behavior of GLM-4.6 which returns {'arguments': None, 'name': 'weather'} - all_results = [ - # First chunk: initial tool call with None arguments - { - "choices": [ - { - "delta": { - "role": "assistant", - "tool_calls": [ - { - "id": "call_123", - "type": "function", - "function": { - "name": "get_weather", - "arguments": None, # GLM-4.6 returns None here - }, - } - ], - }, - "finish_reason": None, - } - ], - }, - # Second chunk: subsequent tool call arguments (also None) - { - "choices": [ - { - "delta": { - "tool_calls": [ - { - "function": { - "arguments": None, # Subsequent chunks can also have None - } - } - ], - }, - "finish_reason": None, - } - ], - }, - # Third chunk: actual arguments - { - "choices": [ - { - "delta": { - "tool_calls": [ - { - "function": { - "arguments": '{"city": "New York"}', - } - } - ], - }, - "finish_reason": None, - } - ], - }, - # Final chunk - { - "choices": [ - { - "delta": {}, - "finish_reason": "tool_calls", - } - ], - }, - ] - - # Process the results - wrapper = ChatCompletionWrapper(None, None) - result = wrapper._postprocess_streaming_results(all_results) - - # Verify the output was built correctly - assert "output" in result - assert len(result["output"]) == 1 - message = result["output"][0]["message"] - assert message["role"] == "assistant" - assert message["tool_calls"] is not None - assert len(message["tool_calls"]) == 1 - - # Verify the tool call was assembled correctly despite None arguments - tool_call = message["tool_calls"][0] - assert tool_call["id"] == "call_123" - assert tool_call["type"] == "function" - assert tool_call["function"]["name"] == "get_weather" - # The arguments should be the concatenation: "" + "" + '{"city": "New York"}' - assert tool_call["function"]["arguments"] == '{"city": "New York"}' - - # No spans should be generated from this unit test - assert not memory_logger.pop() diff --git a/py/src/braintrust/wrappers/test_openrouter.py b/py/src/braintrust/wrappers/test_openrouter.py deleted file mode 100644 index 1d750659d..000000000 --- a/py/src/braintrust/wrappers/test_openrouter.py +++ /dev/null @@ -1,135 +0,0 @@ -""" -Tests to ensure wrap_openai works correctly with OpenRouter. - -OpenRouter is a popular API gateway that provides access to multiple LLM providers -through an OpenAI-compatible interface. This test validates that our wrapper handles -OpenRouter-specific response fields correctly (e.g., boolean `is_byok` in usage). -""" - -import os -import time - -import pytest -from braintrust import logger, wrap_openai -from braintrust.test_helpers import init_test_logger -from braintrust.wrappers.test_utils import assert_metrics_are_valid -from openai import AsyncOpenAI, OpenAI - -PROJECT_NAME = "test-openrouter" -TEST_MODEL = "openai/gpt-4o-mini" - - -@pytest.fixture -def memory_logger(): - init_test_logger(PROJECT_NAME) - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -def _get_client(): - return OpenAI( - base_url="https://openrouter.ai/api/v1", - api_key=os.environ.get("OPENROUTER_API_KEY"), - ) - - -def _get_async_client(): - return AsyncOpenAI( - base_url="https://openrouter.ai/api/v1", - api_key=os.environ.get("OPENROUTER_API_KEY"), - ) - - -@pytest.mark.vcr -def test_openrouter_chat_completion_sync(memory_logger): - assert not memory_logger.pop() - - client = wrap_openai(_get_client()) - - start = time.time() - response = client.chat.completions.create( - model=TEST_MODEL, - messages=[{"role": "user", "content": "What is 2+2? Reply with just the number."}], - max_tokens=10, - ) - end = time.time() - - assert response - assert response.choices[0].message.content - assert "4" in response.choices[0].message.content - - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - - # Ensure no boolean values in metrics (the original bug with is_byok) - for key, value in metrics.items(): - assert not isinstance(value, bool), f"Metric {key} should not be a boolean" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_openrouter_chat_completion_async(memory_logger): - """Test that wrap_openai works with OpenRouter's async client.""" - assert not memory_logger.pop() - - client = wrap_openai(_get_async_client()) - - start = time.time() - response = await client.chat.completions.create( - model=TEST_MODEL, - messages=[{"role": "user", "content": "What is 3+3? Reply with just the number."}], - max_tokens=10, - ) - end = time.time() - - assert response - assert response.choices[0].message.content - assert "6" in response.choices[0].message.content - - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - - for key, value in metrics.items(): - assert not isinstance(value, bool), f"Metric {key} should not be a boolean" - - -@pytest.mark.vcr -def test_openrouter_streaming_sync(memory_logger): - """Test that wrap_openai works with OpenRouter's streaming responses.""" - assert not memory_logger.pop() - - client = wrap_openai(_get_client()) - - start = time.time() - chunks = [] - stream = client.chat.completions.create( - model=TEST_MODEL, - messages=[{"role": "user", "content": "What is 5+5? Reply with just the number."}], - max_tokens=10, - stream=True, - ) - for chunk in stream: - chunks.append(chunk) - end = time.time() - - assert chunks - content = "".join(c.choices[0].delta.content or "" for c in chunks if c.choices) - assert "10" in content - - spans = memory_logger.pop() - assert len(spans) == 1 - span = spans[0] - - metrics = span["metrics"] - assert_metrics_are_valid(metrics, start, end) - - for key, value in metrics.items(): - assert not isinstance(value, bool), f"Metric {key} should not be a boolean" diff --git a/py/src/braintrust/wrappers/test_pydantic_ai_integration.py b/py/src/braintrust/wrappers/test_pydantic_ai_integration.py deleted file mode 100644 index ab17771c6..000000000 --- a/py/src/braintrust/wrappers/test_pydantic_ai_integration.py +++ /dev/null @@ -1,2623 +0,0 @@ -# pyright: reportUntypedFunctionDecorator=false -# pyright: reportUnknownMemberType=false -# pyright: reportUnknownParameterType=false -# pyright: reportPrivateUsage=false -import asyncio -import time - -import pytest -from braintrust import logger, setup_pydantic_ai, traced -from braintrust.span_types import SpanTypeAttribute -from braintrust.test_helpers import init_test_logger -from braintrust.wrappers.test_utils import verify_autoinstrument_script -from pydantic import BaseModel -from pydantic_ai import Agent, ModelSettings -from pydantic_ai.messages import ModelRequest, UserPromptPart - -PROJECT_NAME = "test-pydantic-ai-integration" -MODEL = "openai:gpt-4o-mini" # Use cheaper model for tests -TEST_PROMPT = "What is 2+2? Answer with just the number." - - -@pytest.fixture(scope="module", autouse=True) -def setup_wrapper(): - """Setup pydantic_ai wrapper before any tests run.""" - setup_pydantic_ai(project_name=PROJECT_NAME) - yield - - -@pytest.fixture(scope="module") -def direct(): - """Provide pydantic_ai.direct module after setup_wrapper has run.""" - import pydantic_ai.direct as direct_module - return direct_module - - -@pytest.fixture -def memory_logger(): - init_test_logger(PROJECT_NAME) - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -def _assert_metrics_are_valid(metrics, start, end): - """Assert that metrics contain expected fields and values.""" - assert "start" in metrics - assert "end" in metrics - assert "duration" in metrics - assert start <= metrics["start"] <= metrics["end"] <= end - assert metrics["duration"] > 0 - - # Token metrics (if present) - if "tokens" in metrics: - assert metrics["tokens"] > 0 - if "prompt_tokens" in metrics: - assert metrics["prompt_tokens"] > 0 - if "completion_tokens" in metrics: - assert metrics["completion_tokens"] > 0 - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_run_async(memory_logger): - """Test Agent.run() async method.""" - assert not memory_logger.pop() - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=50)) - - start = time.time() - result = await agent.run(TEST_PROMPT) - end = time.time() - - # Verify the result - assert result.output - assert "4" in str(result.output) - - # Check spans - should now have parent agent_run + nested chat span - spans = memory_logger.pop() - assert len(spans) == 2, f"Expected 2 spans (agent_run + chat), got {len(spans)}" - - # Find agent_run and chat spans - agent_span = next((s for s in spans if "agent_run" in s["span_attributes"]["name"]), None) - chat_span = next((s for s in spans if "chat" in s["span_attributes"]["name"]), None) - - assert agent_span is not None, "agent_run span not found" - assert chat_span is not None, "chat span not found" - - # Check agent span - assert agent_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert agent_span["metadata"]["model"] == "gpt-4o-mini" - assert agent_span["metadata"]["provider"] == "openai" - assert TEST_PROMPT in str(agent_span["input"]) - assert "4" in str(agent_span["output"]) - _assert_metrics_are_valid(agent_span["metrics"], start, end) - - # Check chat span is nested under agent span (use span_id, not id which is the row ID) - assert chat_span["span_parents"] == [agent_span["span_id"]], "chat span should be nested under agent_run" - assert chat_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert "gpt-4o-mini" in chat_span["span_attributes"]["name"] - assert chat_span["metadata"]["model"] == "gpt-4o-mini" - assert chat_span["metadata"]["provider"] == "openai" - _assert_metrics_are_valid(chat_span["metrics"], start, end) - - # Agent spans should have token metrics - assert "prompt_tokens" in agent_span["metrics"] - assert "completion_tokens" in agent_span["metrics"] - assert agent_span["metrics"]["prompt_tokens"] > 0 - assert agent_span["metrics"]["completion_tokens"] > 0 - - -@pytest.mark.vcr -def test_agent_run_sync(memory_logger): - """Test Agent.run_sync() synchronous method.""" - assert not memory_logger.pop() - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=50)) - - start = time.time() - result = agent.run_sync(TEST_PROMPT) - end = time.time() - - # Verify the result - assert result.output - assert "4" in str(result.output) - - # Check spans - should have parent agent_run_sync + nested spans - spans = memory_logger.pop() - assert len(spans) >= 2, f"Expected at least 2 spans (agent_run_sync + chat), got {len(spans)}" - - # Find agent_run_sync and chat spans - agent_sync_span = next((s for s in spans if "agent_run_sync" in s["span_attributes"]["name"]), None) - chat_span = next((s for s in spans if "chat" in s["span_attributes"]["name"]), None) - - assert agent_sync_span is not None, "agent_run_sync span not found" - assert chat_span is not None, "chat span not found" - - # Check agent span - assert agent_sync_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert agent_sync_span["metadata"]["model"] == "gpt-4o-mini" - assert agent_sync_span["metadata"]["provider"] == "openai" - assert TEST_PROMPT in str(agent_sync_span["input"]) - assert "4" in str(agent_sync_span["output"]) - _assert_metrics_are_valid(agent_sync_span["metrics"], start, end) - - # Check chat span is a descendant of agent_run_sync span - # Build span tree to verify nesting - span_by_id = {s["span_id"]: s for s in spans} - - def is_descendant(child_span, ancestor_id): - """Check if child_span is a descendant of ancestor_id.""" - if not child_span.get("span_parents"): - return False - if ancestor_id in child_span["span_parents"]: - return True - # Check if any parent is a descendant - for parent_id in chat_span["span_parents"]: - if parent_id in span_by_id and is_descendant(span_by_id[parent_id], ancestor_id): - return True - return False - - - assert is_descendant(chat_span, agent_sync_span["span_id"]), "chat span should be nested under agent_run_sync" - assert chat_span["metadata"]["model"] == "gpt-4o-mini" - assert chat_span["metadata"]["provider"] == "openai" - _assert_metrics_are_valid(chat_span["metrics"], start, end) - - # Agent spans should have token metrics - assert "prompt_tokens" in agent_sync_span["metrics"] - assert "completion_tokens" in agent_sync_span["metrics"] - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_multiple_identical_sequential_streams(memory_logger): - """Test multiple identical sequential streaming calls to ensure offsets don't accumulate. - - This test makes 3 identical streaming calls in sequence. If timing is captured correctly, - each chat span's offset relative to its parent agent span should be roughly the same - (typically < 100ms). If offsets are accumulating incorrectly, we'd see the second and - third chat spans having much larger offsets than the first. - """ - assert not memory_logger.pop() - - @traced - async def run_multiple_identical_streams(): - # Make 3 identical streaming calls - for i in range(3): - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=50)) - async with agent.run_stream("Count from 1 to 3.") as result: - full_text = "" - async for text in result.stream_text(delta=True): - full_text += text - print(f"Completed stream {i+1}") - - await run_multiple_identical_streams() - - # Check spans - spans = memory_logger.pop() - - # Find agent and chat spans - agent_spans = [s for s in spans if "agent_run" in s["span_attributes"]["name"]] - chat_spans = [s for s in spans if "chat" in s["span_attributes"]["name"]] - - assert len(agent_spans) >= 3, f"Expected at least 3 agent spans, got {len(agent_spans)}" - assert len(chat_spans) >= 3, f"Expected at least 3 chat spans, got {len(chat_spans)}" - - # Sort by creation time - agent_spans.sort(key=lambda s: s["created"]) - chat_spans.sort(key=lambda s: s["created"]) - - # Calculate time-to-first-token for each pair - time_to_first_tokens = [] - for i in range(3): - agent_start = agent_spans[i]["metrics"]["start"] - chat_start = chat_spans[i]["metrics"]["start"] - ttft = chat_start - agent_start - time_to_first_tokens.append(ttft) - - print(f"\n=== STREAM {i+1} ===") - print(f"Agent span start: {agent_start}") - print(f"Chat span start: {chat_start}") - print(f"Time to first token: {ttft}s") - print(f"Agent span ID: {agent_spans[i]['span_id']}") - print(f"Chat span parents: {chat_spans[i]['span_parents']}") - - # CRITICAL: All three time-to-first-token values should be similar (within 0.5s of each other) - # If they're accumulating, the second and third would be much larger - min_ttft = min(time_to_first_tokens) - max_ttft = max(time_to_first_tokens) - ttft_spread = max_ttft - min_ttft - - print(f"\n=== TIME-TO-FIRST-TOKEN ANALYSIS ===") - print(f"TTFT 1: {time_to_first_tokens[0]:.4f}s") - print(f"TTFT 2: {time_to_first_tokens[1]:.4f}s") - print(f"TTFT 3: {time_to_first_tokens[2]:.4f}s") - print(f"Min: {min_ttft:.4f}s, Max: {max_ttft:.4f}s, Spread: {ttft_spread:.4f}s") - - # All should be small (< 3s) - for i, ttft in enumerate(time_to_first_tokens): - assert ttft < 3.0, f"Stream {i+1} time to first token too large: {ttft}s" - - # Spread should be small (< 0.5s) - this catches the accumulation bug - assert ttft_spread < 0.5, f"Time-to-first-token spread too large: {ttft_spread}s - suggests timing is accumulating from previous calls" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_multiple_sequential_streams(memory_logger): - """Test multiple sequential streaming calls to ensure offsets don't accumulate.""" - assert not memory_logger.pop() - - @traced - async def run_multiple_streams(): - agent1 = Agent(MODEL, model_settings=ModelSettings(max_tokens=50)) - agent2 = Agent(MODEL, model_settings=ModelSettings(max_tokens=50)) - - start = time.time() - - # First stream - async with agent1.run_stream("Count from 1 to 3.") as result1: - full_text1 = "" - async for text in result1.stream_text(delta=True): - full_text1 += text - - # Second stream - async with agent2.run_stream("Count from 1 to 3.") as result2: - full_text2 = "" - async for text in result2.stream_text(delta=True): - full_text2 += text - - return start - - start = await run_multiple_streams() - end = time.time() - - # Check spans - spans = memory_logger.pop() - - # Should have: 1 parent (run_multiple_streams) + 2 agent_run_stream spans + 2 chat spans = 5 total - assert len(spans) >= 5, f"Expected at least 5 spans (1 parent + 2 agent_run_stream + 2 chat), got {len(spans)}" - - # Find agent and chat spans - agent_spans = [s for s in spans if "agent_run" in s["span_attributes"]["name"]] - chat_spans = [s for s in spans if "chat" in s["span_attributes"]["name"]] - - assert len(agent_spans) >= 2, f"Expected at least 2 agent spans, got {len(agent_spans)}" - assert len(chat_spans) >= 2, f"Expected at least 2 chat spans, got {len(chat_spans)}" - - # Sort by creation time - agent_spans.sort(key=lambda s: s["created"]) - chat_spans.sort(key=lambda s: s["created"]) - - agent1_span = agent_spans[0] - agent2_span = agent_spans[1] - chat1_span = chat_spans[0] - chat2_span = chat_spans[1] - - # Check timing for first pair - agent1_start = agent1_span["metrics"]["start"] - chat1_start = chat1_span["metrics"]["start"] - time_to_first_token_1 = chat1_start - agent1_start - - # Check timing for second pair - agent2_start = agent2_span["metrics"]["start"] - chat2_start = chat2_span["metrics"]["start"] - time_to_first_token_2 = chat2_start - agent2_start - - print(f"\n=== FIRST STREAM ===") - print(f"Agent1 start: {agent1_start}") - print(f"Chat1 start: {chat1_start}") - print(f"Time to first token 1: {time_to_first_token_1}s") - - print(f"\n=== SECOND STREAM ===") - print(f"Agent2 start: {agent2_start}") - print(f"Chat2 start: {chat2_start}") - print(f"Time to first token 2: {time_to_first_token_2}s") - - print(f"\n=== RELATIVE TIMING ===") - print(f"Agent2 start - Agent1 start: {agent2_start - agent1_start}s") - print(f"Chat2 start - Chat1 start: {chat2_start - chat1_start}s") - - # CRITICAL: Both time-to-first-token values should be small and similar - assert time_to_first_token_1 < 3.0, f"First time to first token too large: {time_to_first_token_1}s" - assert time_to_first_token_2 < 3.0, f"Second time to first token too large: {time_to_first_token_2}s - suggests start_time is being reused from first call" - - # Agent2 should start AFTER agent1 finishes (or near the end) - agent1_end = agent1_span["metrics"]["end"] - assert agent2_start >= agent1_end - 0.1, f"Agent2 started too early: {agent2_start} vs Agent1 end: {agent1_end}" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_run_stream(memory_logger): - """Test Agent.run_stream() streaming method.""" - assert not memory_logger.pop() - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=100)) - - start = time.time() - full_text = "" - async with agent.run_stream("Count from 1 to 5") as result: - async for text in result.stream_text(delta=True): - full_text += text - end = time.time() - - # Verify we got streaming content - assert full_text - assert any(str(i) in full_text for i in range(1, 6)) - - # Check spans - should now have parent agent_run_stream + nested chat span - spans = memory_logger.pop() - assert len(spans) == 2, f"Expected 2 spans (agent_run_stream + chat), got {len(spans)}" - - # Find agent_run_stream and chat spans - agent_span = next((s for s in spans if "agent_run_stream" in s["span_attributes"]["name"]), None) - chat_span = next((s for s in spans if "chat" in s["span_attributes"]["name"]), None) - - assert agent_span is not None, "agent_run_stream span not found" - assert chat_span is not None, "chat span not found" - - # Check agent span - assert agent_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert agent_span["metadata"]["model"] == "gpt-4o-mini" - assert "Count from 1 to 5" in str(agent_span["input"]) - _assert_metrics_are_valid(agent_span["metrics"], start, end) - - # Check chat span is nested under agent span - assert chat_span["span_parents"] == [agent_span["span_id"]], "chat span should be nested under agent_run_stream" - assert chat_span["metadata"]["model"] == "gpt-4o-mini" - assert chat_span["metadata"]["provider"] == "openai" - _assert_metrics_are_valid(chat_span["metrics"], start, end) - - # CRITICAL: Check that time_to_first_token is captured - assert "time_to_first_token" in agent_span["metrics"], "agent_run_stream span should have time_to_first_token metric" - ttft = agent_span["metrics"]["time_to_first_token"] - duration = agent_span["metrics"]["duration"] - - # time_to_first_token should be reasonable: > 0 and < duration - assert ttft > 0, f"time_to_first_token should be > 0, got {ttft}" - assert ttft <= duration, f"time_to_first_token ({ttft}s) should be <= duration ({duration}s)" - assert ttft < 3.0, f"time_to_first_token should be < 3s for API call, got {ttft}s" - - # Debug: Print full span data - print(f"\n=== AGENT SPAN ===") - print(f"ID: {agent_span['id']}") - print(f"span_id: {agent_span['span_id']}") - print(f"metrics: {agent_span['metrics']}") - print(f"time_to_first_token: {ttft}s") - print(f"\n=== CHAT SPAN ===") - print(f"ID: {chat_span['id']}") - print(f"span_id: {chat_span['span_id']}") - print(f"span_parents: {chat_span['span_parents']}") - print(f"metrics: {chat_span['metrics']}") - - # Agent spans should have token metrics - assert "prompt_tokens" in agent_span["metrics"] - assert "completion_tokens" in agent_span["metrics"] - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_with_tools(memory_logger): - """Test Agent with tool calls.""" - assert not memory_logger.pop() - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=200)) - - @agent.tool_plain - def get_weather(city: str) -> str: - """Get weather for a city. - - Args: - city: The city name - """ - return f"It's sunny in {city}" - - start = time.time() - result = await agent.run("What's the weather in Paris?") - end = time.time() - - # Verify tool was used - assert result.output - assert "Paris" in str(result.output) or "sunny" in str(result.output) - - # Check spans - spans = memory_logger.pop() - assert len(spans) >= 1 # At least the agent span, possibly more - - # Find the agent span - agent_span = next(s for s in spans if "agent_run" in s["span_attributes"]["name"]) - assert agent_span - assert "weather" in str(agent_span["input"]).lower() or "paris" in str(agent_span["input"]).lower() - _assert_metrics_are_valid(agent_span["metrics"], start, end) - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_direct_model_request(memory_logger, direct): - """Test direct API model_request().""" - assert not memory_logger.pop() - - messages = [ModelRequest(parts=[UserPromptPart(content=TEST_PROMPT)])] - - start = time.time() - response = await direct.model_request(model=MODEL, messages=messages) - end = time.time() - - # Verify response - assert response.parts - assert "4" in str(response.parts[0].content) - - # Check spans - spans = memory_logger.pop() - # Direct API calls may create 1 or 2 spans depending on model wrapping - assert len(spans) >= 1 - - # Find the direct API span - direct_span = next((s for s in spans if s["span_attributes"]["name"] == "model_request"), None) - assert direct_span is not None - - assert direct_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert direct_span["metadata"]["model"] == "gpt-4o-mini" - assert direct_span["metadata"]["provider"] == "openai" - assert TEST_PROMPT in str(direct_span["input"]) - assert "4" in str(direct_span["output"]) - _assert_metrics_are_valid(direct_span["metrics"], start, end) - - -@pytest.mark.vcr -def test_direct_model_request_sync(memory_logger, direct): - """Test direct API model_request_sync().""" - assert not memory_logger.pop() - - messages = [ModelRequest(parts=[UserPromptPart(content=TEST_PROMPT)])] - - start = time.time() - response = direct.model_request_sync(model=MODEL, messages=messages) - end = time.time() - - # Verify response - assert response.parts - assert "4" in str(response.parts[0].content) - - # Check spans - direct API may create 2-3 spans depending on wrapping layers - spans = memory_logger.pop() - assert len(spans) >= 2 - - # Find the model_request_sync span - span = next((s for s in spans if s["span_attributes"]["name"] == "model_request_sync"), None) - assert span is not None, "model_request_sync span not found" - assert span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert span["metadata"]["model"] == "gpt-4o-mini" - assert TEST_PROMPT in str(span["input"]) - _assert_metrics_are_valid(span["metrics"], start, end) - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_direct_model_request_with_settings(memory_logger, direct): - """Test that model_settings appears in input for direct API calls.""" - assert not memory_logger.pop() - - messages = [ModelRequest(parts=[UserPromptPart(content="Say hello")])] - custom_settings = ModelSettings(max_tokens=50, temperature=0.7) - - start = time.time() - result = await direct.model_request(model=MODEL, messages=messages, model_settings=custom_settings) - end = time.time() - - # Verify result - assert result.parts - - # Check spans - spans = memory_logger.pop() - # Direct API calls may create 1 or 2 spans depending on model wrapping - assert len(spans) >= 1 - - # Find the direct API span - direct_span = next((s for s in spans if s["span_attributes"]["name"] == "model_request"), None) - assert direct_span is not None - - assert direct_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - - # Verify model_settings is in input (NOT metadata) - assert "model_settings" in direct_span["input"], "model_settings should be in input" - settings = direct_span["input"]["model_settings"] - assert settings["max_tokens"] == 50 - assert settings["temperature"] == 0.7 - - # Verify model_settings is NOT in metadata - assert "model_settings" not in direct_span["metadata"], "model_settings should NOT be in metadata" - - # Verify metadata still has model and provider - assert direct_span["metadata"]["model"] == "gpt-4o-mini" - assert direct_span["metadata"]["provider"] == "openai" - - _assert_metrics_are_valid(direct_span["metrics"], start, end) - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_direct_model_request_stream(memory_logger, direct): - """Test direct API model_request_stream() - verifies time_to_first_token is captured.""" - assert not memory_logger.pop() - - messages = [ModelRequest(parts=[UserPromptPart(content="Count from 1 to 3")])] - - start = time.time() - chunk_count = 0 - async with direct.model_request_stream(model=MODEL, messages=messages) as stream: - async for chunk in stream: - chunk_count += 1 - end = time.time() - - # Verify we got chunks - assert chunk_count > 0 - - # Check spans - spans = memory_logger.pop() - # Direct API calls may create 1 or 2 spans depending on model wrapping - assert len(spans) >= 1 - - # Find the direct API span - direct_span = next((s for s in spans if s["span_attributes"]["name"] == "model_request_stream"), None) - assert direct_span is not None - - assert direct_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert direct_span["metadata"]["model"] == "gpt-4o-mini" - _assert_metrics_are_valid(direct_span["metrics"], start, end) - - # CRITICAL: Verify time_to_first_token is captured in direct streaming - assert "time_to_first_token" in direct_span["metrics"], "model_request_stream span should have time_to_first_token metric" - ttft = direct_span["metrics"]["time_to_first_token"] - duration = direct_span["metrics"]["duration"] - - # time_to_first_token should be reasonable: > 0 and < duration - assert ttft > 0, f"time_to_first_token should be > 0, got {ttft}" - assert ttft <= duration, f"time_to_first_token ({ttft}s) should be <= duration ({duration}s)" - assert ttft < 3.0, f"time_to_first_token should be < 3s for API call, got {ttft}s" - - print(f"โœ“ Direct stream time_to_first_token: {ttft}s (duration: {duration}s)") - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_direct_model_request_stream_complete_output(memory_logger, direct): - """Test that direct API streaming captures all text including first chunk from PartStartEvent.""" - assert not memory_logger.pop() - - messages = [ModelRequest(parts=[UserPromptPart(content="Say exactly: 1, 2, 3")])] - - collected_text = "" - seen_delta = False - async with direct.model_request_stream(model=MODEL, messages=messages) as stream: - async for chunk in stream: - # Extract text, skipping final PartStartEvent after deltas - if hasattr(chunk, 'part') and hasattr(chunk.part, 'content') and not seen_delta: - # PartStartEvent has part.content with initial text - collected_text += str(chunk.part.content) - elif hasattr(chunk, 'delta') and chunk.delta: - seen_delta = True - # PartDeltaEvent has delta.content_delta - if hasattr(chunk.delta, 'content_delta') and chunk.delta.content_delta: - collected_text += chunk.delta.content_delta - - # Verify we got complete output including "1" - assert "1" in collected_text - assert "2" in collected_text - assert "3" in collected_text - - # Check spans were created - spans = memory_logger.pop() - assert len(spans) >= 1 - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_direct_api_streaming_call_3(memory_logger, direct): - """Test direct API streaming (call 3) - should output complete '1, 2, 3, 4, 5'.""" - assert not memory_logger.pop() - - IDENTICAL_PROMPT = "Count from 1 to 5." - messages = [ModelRequest(parts=[UserPromptPart(content=IDENTICAL_PROMPT)])] - - collected_text = "" - async with direct.model_request_stream(model="openai:gpt-4o", messages=messages, model_settings=ModelSettings(max_tokens=100)) as stream: - async for chunk in stream: - # FIX: Handle PartStartEvent which contains initial text - if hasattr(chunk, 'part') and hasattr(chunk.part, 'content'): - collected_text += str(chunk.part.content) - # Handle PartDeltaEvent with delta content - elif hasattr(chunk, 'delta') and chunk.delta: - if hasattr(chunk.delta, 'content_delta') and chunk.delta.content_delta: - collected_text += chunk.delta.content_delta - - # Now this should pass! - assert "1" in collected_text, f"Expected '1' in output but got: {collected_text}" - assert "2" in collected_text - assert "3" in collected_text - assert "4" in collected_text - assert "5" in collected_text - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_direct_api_streaming_call_4(memory_logger, direct): - """Test direct API streaming (call 4) - identical to call 3.""" - assert not memory_logger.pop() - - IDENTICAL_PROMPT = "Count from 1 to 5." - messages = [ModelRequest(parts=[UserPromptPart(content=IDENTICAL_PROMPT)])] - - collected_text = "" - async with direct.model_request_stream(model="openai:gpt-4o", messages=messages, model_settings=ModelSettings(max_tokens=100)) as stream: - async for chunk in stream: - # FIX: Handle PartStartEvent which contains initial text - if hasattr(chunk, 'part') and hasattr(chunk.part, 'content'): - collected_text += str(chunk.part.content) - # Handle PartDeltaEvent with delta content - elif hasattr(chunk, 'delta') and chunk.delta: - if hasattr(chunk.delta, 'content_delta') and chunk.delta.content_delta: - collected_text += chunk.delta.content_delta - - # Now this should pass! - assert "1" in collected_text, f"Expected '1' in output but got: {collected_text}" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_direct_api_streaming_early_break_call_5(memory_logger, direct): - """Test direct API streaming with early break (call 5) - should still get first few chars including '1'.""" - assert not memory_logger.pop() - - IDENTICAL_PROMPT = "Count from 1 to 5." - messages = [ModelRequest(parts=[UserPromptPart(content=IDENTICAL_PROMPT)])] - - collected_text = "" - i = 0 - async with direct.model_request_stream(model="openai:gpt-4o", messages=messages, model_settings=ModelSettings(max_tokens=100)) as stream: - async for chunk in stream: - # FIX: Handle PartStartEvent which contains initial text - if hasattr(chunk, 'part') and hasattr(chunk.part, 'content'): - collected_text += str(chunk.part.content) - # Handle PartDeltaEvent with delta content - elif hasattr(chunk, 'delta') and chunk.delta: - if hasattr(chunk.delta, 'content_delta') and chunk.delta.content_delta: - collected_text += chunk.delta.content_delta - - i += 1 - if i >= 3: - break - - # Even with early break after 3 chunks, we should capture text from PartStartEvent (chunk 1) - print(f"Collected text: '{collected_text}'") - assert len(collected_text) > 0, f"Expected some text even with early break but got empty string" - # Verify we're capturing PartStartEvent by checking we got text before breaking at chunk 3 - assert collected_text, f"Should have captured text from PartStartEvent or first delta" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_direct_api_streaming_no_duplication(memory_logger, direct): - """Test that direct API streaming doesn't duplicate output and captures all text in span.""" - assert not memory_logger.pop() - - collected_text = "" - chunk_count = 0 - - # Use direct API streaming - messages = [ModelRequest(parts=[UserPromptPart(content="Count from 1 to 5, separated by commas.")])] - async with direct.model_request_stream( - messages=messages, - model_settings=ModelSettings(max_tokens=100), - model="openai:gpt-4o", - ) as response: - async for chunk in response: - chunk_count += 1 - # Extract text from chunk - text = None - if hasattr(chunk, 'part') and hasattr(chunk.part, 'content'): - text = str(chunk.part.content) - elif hasattr(chunk, 'delta') and chunk.delta: - if hasattr(chunk.delta, 'content_delta') and chunk.delta.content_delta: - text = chunk.delta.content_delta - - if text: - collected_text += text - - print(f"Collected text from stream: '{collected_text}'") - print(f"Total chunks: {chunk_count}") - - # Verify we collected complete text - assert len(collected_text) > 0, "Should have collected text from stream" - assert "1" in collected_text, "Should have '1' in output" - - # Check span captured the full output - spans = memory_logger.pop() - assert len(spans) >= 1, f"Expected at least 1 span, got {len(spans)}" - - # Find the model_request_stream span - stream_span = next((s for s in spans if "model_request_stream" in s["span_attributes"]["name"]), None) - assert stream_span is not None, "model_request_stream span not found" - - # Check that span output contains the full text, not just "1," - span_output = stream_span.get("output", {}) - print(f"Span output: {span_output}") - - # The span should capture the full response - if "response" in span_output and "parts" in span_output["response"]: - parts = span_output["response"]["parts"] - span_text = "".join(str(p.get("content", "")) for p in parts if isinstance(p, dict)) - print(f"Span captured text: '{span_text}'") - # Should have more than just "1," - assert len(span_text) > 2, f"Span should capture more than just '1,', got: '{span_text}'" - assert "1" in span_text, "Span should contain '1'" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_direct_api_streaming_no_duplication_comprehensive(memory_logger, direct): - """Comprehensive test matching golden test setup to verify no duplication and full output capture.""" - assert not memory_logger.pop() - - # Match golden test exactly - IDENTICAL_PROMPT = "Count from 1 to 5." - IDENTICAL_SETTINGS = ModelSettings(max_tokens=100) - - messages = [ModelRequest(parts=[UserPromptPart(content=IDENTICAL_PROMPT)])] - - collected_text = "" - chunk_types = [] - seen_delta = False - - async with direct.model_request_stream(messages=messages, model_settings=IDENTICAL_SETTINGS, model="openai:gpt-4o") as stream: - async for chunk in stream: - # Track chunk types - if hasattr(chunk, 'part') and hasattr(chunk.part, 'content') and not seen_delta: - chunk_types.append(('PartStartEvent', str(chunk.part.content))) - text = str(chunk.part.content) - collected_text += text - elif hasattr(chunk, 'delta') and chunk.delta: - seen_delta = True - if hasattr(chunk.delta, 'content_delta') and chunk.delta.content_delta: - chunk_types.append(('PartDeltaEvent', chunk.delta.content_delta)) - text = chunk.delta.content_delta - collected_text += text - - print(f"\nCollected text: '{collected_text}'") - print(f"Total chunks received: {len(chunk_types)}") - print(f"All chunk types:") - for i, (chunk_type, content) in enumerate(chunk_types): - print(f" {i}: {chunk_type} = {content!r}") - - # Verify no duplication in collected text - # Expected: "Sure! Here you go:\n\n1, 2, 3, 4, 5." or similar (length ~30) - # Should NOT be duplicated - assert len(collected_text) < 60, f"Text seems duplicated (too long): '{collected_text}' (len={len(collected_text)})" - assert collected_text.count("1, 2, 3") == 1, f"Text should appear once, not duplicated: '{collected_text}'" - - # Check span - spans = memory_logger.pop() - print(f"Number of spans: {len(spans)}") - for i, s in enumerate(spans): - print(f"Span {i}: {s['span_attributes']['name']} (type: {s['span_attributes'].get('type', 'N/A')})") - if 'span_parents' in s and s['span_parents']: - print(f" Parents: {s['span_parents']}") - - # Should have 1 or 2 spans (direct API wrapper + potentially model wrapper) - assert len(spans) >= 1, f"Expected at least 1 span, got {len(spans)}" - - # Find the model_request_stream span - stream_span = next((s for s in spans if "model_request_stream" in s["span_attributes"]["name"]), None) - assert stream_span is not None, "model_request_stream span not found" - - # Check that span output is not empty and captures reasonable amount of text - span_output = stream_span.get("output", {}) - print(f"Span output keys: {span_output.keys() if span_output else 'None'}") - - if "parts" in span_output: - parts = span_output.get("parts", []) - print(f"Span parts: {parts}") - if parts and len(parts) > 0: - first_part = parts[0] - print(f"First part type: {type(first_part)}") - print(f"First part: {first_part}") - if isinstance(first_part, dict): - part_content = first_part.get("content", "") - print(f"Part content: '{part_content}'") - print(f"Part content length: {len(part_content)}") - # The span should capture the FULL text, not just "1," - assert len(part_content) > 5, f"Span should capture full text, got: '{part_content}'" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_async_generator_pattern_call_6(memory_logger): - """Test async generator pattern (call 6) - wrapping stream in async generator.""" - assert not memory_logger.pop() - - IDENTICAL_PROMPT = "Count from 1 to 5." - - async def stream_with_async_generator(prompt: str): - """Wrap the stream in an async generator (customer pattern).""" - agent = Agent("openai:gpt-4o", model_settings=ModelSettings(max_tokens=100)) - async for event in agent.run_stream_events(prompt): - yield event - - collected_text = "" - i = 0 - async for event in stream_with_async_generator(IDENTICAL_PROMPT): - # run_stream_events returns ResultEvent objects with different structure - # Try to extract text from whatever event type we get - if hasattr(event, 'content') and event.content: - collected_text += str(event.content) - elif hasattr(event, 'part') and hasattr(event.part, 'content'): - collected_text += str(event.part.content) - elif hasattr(event, 'delta') and event.delta: - if hasattr(event.delta, 'content_delta') and event.delta.content_delta: - collected_text += event.delta.content_delta - - i += 1 - if i >= 3: - break - - # This should capture something - print(f"Collected text from generator: '{collected_text}'") - assert len(collected_text) > 0, f"Expected some text from async generator but got empty string" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_structured_output(memory_logger): - """Test Agent with structured output (Pydantic model).""" - assert not memory_logger.pop() - - class MathAnswer(BaseModel): - answer: int - explanation: str - - agent = Agent( - MODEL, - output_type=MathAnswer, - model_settings=ModelSettings(max_tokens=200) - ) - - start = time.time() - result = await agent.run("What is 10 + 15?") - end = time.time() - - # Verify structured output - assert isinstance(result.output, MathAnswer) - assert result.output.answer == 25 - assert result.output.explanation - - # Check spans - should have parent agent_run + nested spans - spans = memory_logger.pop() - assert len(spans) >= 2, f"Expected at least 2 spans (agent_run + chat), got {len(spans)}" - - # Find agent_run and chat spans - agent_span = next((s for s in spans if "agent_run" in s["span_attributes"]["name"] and "chat" not in s["span_attributes"]["name"]), None) - chat_span = next((s for s in spans if "chat" in s["span_attributes"]["name"]), None) - - assert agent_span is not None, "agent_run span not found" - assert chat_span is not None, "chat span not found" - - # Check agent span - assert agent_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert agent_span["metadata"]["model"] == "gpt-4o-mini" - assert agent_span["metadata"]["provider"] == "openai" - assert "10 + 15" in str(agent_span["input"]) - assert "25" in str(agent_span["output"]) - _assert_metrics_are_valid(agent_span["metrics"], start, end) - - # Check chat span is a descendant of agent_run - span_by_id = {s["span_id"]: s for s in spans} - - def is_descendant(child_span, ancestor_id): - """Check if child_span is a descendant of ancestor_id.""" - if not child_span.get("span_parents"): - return False - if ancestor_id in child_span["span_parents"]: - return True - for parent_id in child_span["span_parents"]: - if parent_id in span_by_id and is_descendant(span_by_id[parent_id], ancestor_id): - return True - return False - - assert is_descendant(chat_span, agent_span["span_id"]), "chat span should be nested under agent_run" - assert chat_span["metadata"]["model"] == "gpt-4o-mini" - assert chat_span["metadata"]["provider"] == "openai" - _assert_metrics_are_valid(chat_span["metrics"], start, end) - - # Agent spans should have token metrics - assert "prompt_tokens" in agent_span["metrics"] - assert "completion_tokens" in agent_span["metrics"] - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_with_model_settings_in_metadata(memory_logger): - """Test that model_settings from agent config appears in metadata, not input.""" - assert not memory_logger.pop() - - custom_settings = ModelSettings(max_tokens=100, temperature=0.5) - agent = Agent(MODEL, model_settings=custom_settings) - - start = time.time() - result = await agent.run("Say hello") - end = time.time() - - assert result.output - - # Check spans - spans = memory_logger.pop() - assert len(spans) == 2, f"Expected 2 spans (agent_run + chat), got {len(spans)}" - - # Find agent_run and chat spans - agent_span = next((s for s in spans if "agent_run" in s["span_attributes"]["name"] and "chat" not in s["span_attributes"]["name"]), None) - chat_span = next((s for s in spans if "chat" in s["span_attributes"]["name"]), None) - - assert agent_span is not None, "agent_run span not found" - assert chat_span is not None, "chat span not found" - - # Verify model_settings is in agent METADATA (not input, since it's agent config) - assert "model_settings" in agent_span["metadata"], "model_settings should be in agent_run metadata" - agent_settings = agent_span["metadata"]["model_settings"] - assert agent_settings["max_tokens"] == 100 - assert agent_settings["temperature"] == 0.5 - - # Verify model_settings is NOT in agent input (it wasn't passed to run()) - assert "model_settings" not in agent_span["input"], "model_settings should NOT be in agent_run input when not passed to run()" - - # Verify model_settings is in chat input (passed to the model) - assert "model_settings" in chat_span["input"], "model_settings should be in chat span input" - chat_settings = chat_span["input"]["model_settings"] - assert chat_settings["max_tokens"] == 100 - assert chat_settings["temperature"] == 0.5 - - # Verify model_settings is NOT in chat metadata (it's in input) - assert "model_settings" not in chat_span["metadata"], "model_settings should NOT be in chat span metadata" - - # Verify other metadata is present - assert chat_span["metadata"]["model"] == "gpt-4o-mini" - assert chat_span["metadata"]["provider"] == "openai" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_with_model_settings_override_in_input(memory_logger): - """Test that model_settings passed to run() appears in input, not metadata.""" - assert not memory_logger.pop() - - # Agent has default settings - default_settings = ModelSettings(max_tokens=50) - agent = Agent(MODEL, model_settings=default_settings) - - # Override with different settings in run() call - override_settings = ModelSettings(max_tokens=200, temperature=0.9) - - start = time.time() - result = await agent.run("Tell me a story", model_settings=override_settings) - end = time.time() - - assert result.output - - # Check spans - spans = memory_logger.pop() - assert len(spans) == 2, f"Expected 2 spans (agent_run + chat), got {len(spans)}" - - # Find agent_run span - agent_span = next((s for s in spans if "agent_run" in s["span_attributes"]["name"] and "chat" not in s["span_attributes"]["name"]), None) - assert agent_span is not None, "agent_run span not found" - - # Verify override settings are in agent INPUT (because they were passed to run()) - assert "model_settings" in agent_span["input"], "model_settings should be in agent_run input when passed to run()" - input_settings = agent_span["input"]["model_settings"] - assert input_settings["max_tokens"] == 200, "Should use override settings from run() call" - assert input_settings["temperature"] == 0.9 - - # Verify agent default settings are NOT in metadata (when overridden in input, we don't duplicate in metadata) - assert "model_settings" not in agent_span["metadata"], "model_settings should NOT be in metadata when explicitly passed to run()" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_with_system_prompt_in_metadata(memory_logger): - """Test that system_prompt from agent config appears in input (it's semantically part of LLM input).""" - assert not memory_logger.pop() - - system_prompt = "You are a helpful AI assistant who speaks like a pirate." - agent = Agent(MODEL, system_prompt=system_prompt, model_settings=ModelSettings(max_tokens=100)) - - start = time.time() - result = await agent.run("What is the weather?") - end = time.time() - - assert result.output - - # Check spans - spans = memory_logger.pop() - assert len(spans) == 2, f"Expected 2 spans (agent_run + chat), got {len(spans)}" - - # Find agent_run span - agent_span = next((s for s in spans if "agent_run" in s["span_attributes"]["name"] and "chat" not in s["span_attributes"]["name"]), None) - assert agent_span is not None, "agent_run span not found" - - # Verify system_prompt is in input (because it's semantically part of the LLM input) - assert "system_prompt" in agent_span["input"], "system_prompt should be in agent_run input" - assert agent_span["input"]["system_prompt"] == system_prompt, "system_prompt should be the actual string, not a method reference" - - # Verify system_prompt is NOT in metadata - assert "system_prompt" not in agent_span["metadata"], "system_prompt should NOT be in agent_run metadata" - - # Verify other metadata is present - assert agent_span["metadata"]["model"] == "gpt-4o-mini" - assert agent_span["metadata"]["provider"] == "openai" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_with_message_history(memory_logger): - """Test Agent with conversation history.""" - assert not memory_logger.pop() - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=100)) - - # First message - result1 = await agent.run("My name is Alice") - assert result1.output - memory_logger.pop() # Clear first span - - # Second message with history - start = time.time() - result2 = await agent.run( - "What is my name?", - message_history=result1.all_messages() - ) - end = time.time() - - # Verify it remembers - assert "Alice" in str(result2.output) - - # Check spans - should now have parent agent_run + nested chat span - spans = memory_logger.pop() - assert len(spans) == 2, f"Expected 2 spans (agent_run + chat), got {len(spans)}" - - # Find agent_run and chat spans - agent_span = next((s for s in spans if "agent_run" in s["span_attributes"]["name"] and "chat" not in s["span_attributes"]["name"]), None) - - assert agent_span is not None, "agent_run span not found" - assert "message_history" in str(agent_span["input"]) - assert "Alice" in str(agent_span["output"]) - _assert_metrics_are_valid(agent_span["metrics"], start, end) - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_with_custom_settings(memory_logger): - """Test Agent with custom model settings.""" - assert not memory_logger.pop() - - agent = Agent(MODEL) - - start = time.time() - result = await agent.run( - "Say hello", - model_settings=ModelSettings( - max_tokens=20, - temperature=0.5, - top_p=0.9 - ) - ) - end = time.time() - - assert result.output - - # Check spans - should now have parent agent_run + nested chat span - spans = memory_logger.pop() - assert len(spans) >= 2, f"Expected at least 2 spans (agent_run + chat), got {len(spans)}" - - # Find agent_run span - agent_span = next((s for s in spans if "agent_run" in s["span_attributes"]["name"] and "chat" not in s["span_attributes"]["name"]), None) - assert agent_span is not None, "agent_run span not found" - - # Model settings passed to run() should be in input (not metadata) - assert "model_settings" in agent_span["input"] - settings = agent_span["input"]["model_settings"] - assert settings["max_tokens"] == 20 - assert settings["temperature"] == 0.5 - assert settings["top_p"] == 0.9 - _assert_metrics_are_valid(agent_span["metrics"], start, end) - - -@pytest.mark.vcr -def test_agent_run_stream_sync(memory_logger): - """Test Agent.run_stream_sync() synchronous streaming method - verifies time_to_first_token.""" - assert not memory_logger.pop() - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=100)) - - start = time.time() - full_text = "" - result = agent.run_stream_sync("Count from 1 to 3") - for text in result.stream_text(delta=True): - full_text += text - end = time.time() - - # Verify we got streaming content - assert full_text - assert any(str(i) in full_text for i in range(1, 4)) - - # Check spans - should have parent agent_run_stream_sync + nested spans - spans = memory_logger.pop() - assert len(spans) >= 2, f"Expected at least 2 spans (agent_run_stream_sync + chat), got {len(spans)}" - - # Find agent_run_stream_sync and chat spans - agent_span = next((s for s in spans if "agent_run_stream_sync" in s["span_attributes"]["name"]), None) - chat_span = next((s for s in spans if "chat" in s["span_attributes"]["name"]), None) - - assert agent_span is not None, "agent_run_stream_sync span not found" - assert chat_span is not None, "chat span not found" - - # Check agent span - assert agent_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert agent_span["metadata"]["model"] == "gpt-4o-mini" - assert "Count from 1 to 3" in str(agent_span["input"]) - _assert_metrics_are_valid(agent_span["metrics"], start, end) - - # CRITICAL: Verify time_to_first_token is captured in sync streaming - assert "time_to_first_token" in agent_span["metrics"], "agent_run_stream_sync span should have time_to_first_token metric" - ttft = agent_span["metrics"]["time_to_first_token"] - duration = agent_span["metrics"]["duration"] - - # time_to_first_token should be reasonable: > 0 and < duration - assert ttft > 0, f"time_to_first_token should be > 0, got {ttft}" - assert ttft <= duration, f"time_to_first_token ({ttft}s) should be <= duration ({duration}s)" - assert ttft < 3.0, f"time_to_first_token should be < 3s for API call, got {ttft}s" - - print(f"โœ“ Sync stream time_to_first_token: {ttft}s (duration: {duration}s)") - - # Check chat span is a descendant of agent_run_stream_sync - span_by_id = {s["span_id"]: s for s in spans} - - def is_descendant(child_span, ancestor_id): - """Check if child_span is a descendant of ancestor_id.""" - if not child_span.get("span_parents"): - return False - if ancestor_id in child_span["span_parents"]: - return True - for parent_id in child_span["span_parents"]: - if parent_id in span_by_id and is_descendant(span_by_id[parent_id], ancestor_id): - return True - return False - - assert is_descendant(chat_span, agent_span["span_id"]), "chat span should be nested under agent_run_stream_sync" - assert chat_span["metadata"]["model"] == "gpt-4o-mini" - assert chat_span["metadata"]["provider"] == "openai" - # Chat span may not have complete metrics since it's an intermediate span - assert "start" in chat_span["metrics"] - - # Agent spans should have token metrics - assert "prompt_tokens" in agent_span["metrics"] - assert "completion_tokens" in agent_span["metrics"] - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_run_stream_events(memory_logger): - """Test Agent.run_stream_events() event streaming method.""" - assert not memory_logger.pop() - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=100)) - - start = time.time() - event_count = 0 - events = [] - # Consume all events - async for event in agent.run_stream_events("What is 5+5?"): - event_count += 1 - events.append(event) - end = time.time() - - # Verify we got events - assert event_count > 0, "Should receive at least one event" - - # Check spans - should have agent_run_stream_events span - spans = memory_logger.pop() - assert len(spans) >= 1, f"Expected at least 1 span, got {len(spans)}" - - # Find agent_run_stream_events span - agent_span = next((s for s in spans if "agent_run_stream_events" in s["span_attributes"]["name"]), None) - assert agent_span is not None, "agent_run_stream_events span not found" - - # Check agent span has basic structure - assert agent_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert agent_span["metadata"]["model"] == "gpt-4o-mini" - assert "5+5" in str(agent_span["input"]) or "What" in str(agent_span["input"]) - assert agent_span["metrics"]["event_count"] == event_count - _assert_metrics_are_valid(agent_span["metrics"], start, end) - - -@pytest.mark.vcr -def test_direct_model_request_stream_sync(memory_logger, direct): - """Test direct API model_request_stream_sync() - verifies time_to_first_token.""" - assert not memory_logger.pop() - - messages = [ModelRequest(parts=[UserPromptPart(content="Count from 1 to 3")])] - - start = time.time() - chunk_count = 0 - with direct.model_request_stream_sync(model=MODEL, messages=messages) as stream: - for chunk in stream: - chunk_count += 1 - end = time.time() - - # Verify we got chunks - assert chunk_count > 0 - - # Check spans - spans = memory_logger.pop() - assert len(spans) == 1 - - span = spans[0] - assert span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert span["span_attributes"]["name"] == "model_request_stream_sync" - assert span["metadata"]["model"] == "gpt-4o-mini" - _assert_metrics_are_valid(span["metrics"], start, end) - - # CRITICAL: Verify time_to_first_token is captured in sync direct streaming - assert "time_to_first_token" in span["metrics"], "model_request_stream_sync span should have time_to_first_token metric" - ttft = span["metrics"]["time_to_first_token"] - duration = span["metrics"]["duration"] - - # time_to_first_token should be reasonable: > 0 and < duration - assert ttft > 0, f"time_to_first_token should be > 0, got {ttft}" - assert ttft <= duration, f"time_to_first_token ({ttft}s) should be <= duration ({duration}s)" - assert ttft < 3.0, f"time_to_first_token should be < 3s for API call, got {ttft}s" - - print(f"โœ“ Direct sync stream time_to_first_token: {ttft}s (duration: {duration}s)") - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_stream_early_break_async_generator(memory_logger, direct): - """Test breaking early from an async generator wrapper around a stream. - - This reproduces the 'Token was created in a different Context' error that occurs - when breaking early from async generators. The cleanup happens in a different - async context, causing ContextVar token errors. - - Our fix: Clear the context token before cleanup to make unset_current() use - the safe set(None) path instead of reset(token). - """ - assert not memory_logger.pop() - - messages = [ModelRequest(parts=[UserPromptPart(content="Count from 1 to 5")])] - - async def stream_wrapper(): - """Wrap the stream in an async generator (common customer pattern).""" - async with direct.model_request_stream(model=MODEL, messages=messages) as stream: - count = 0 - async for chunk in stream: - yield chunk - count += 1 - if count >= 3: - # Break early - this triggers cleanup in different context - break - - start = time.time() - chunk_count = 0 - - # This should NOT raise ValueError about "different Context" - async for chunk in stream_wrapper(): - chunk_count += 1 - - end = time.time() - - # Should not raise ValueError about context token - assert chunk_count == 3 - - # Check spans - should have created a span despite early break - spans = memory_logger.pop() - assert len(spans) >= 1, "Should have at least one span even with early break" - - span = spans[0] - assert span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert span["span_attributes"]["name"] == "model_request_stream" - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_stream_early_break(memory_logger): - """Test breaking early from agent.run_stream() context manager. - - Verifies that breaking early from the stream doesn't cause context token errors - and that spans are still properly logged. - """ - assert not memory_logger.pop() - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=100)) - - start = time.time() - text_count = 0 - - # Break early from stream - should not raise context token error - async with agent.run_stream("Count from 1 to 10") as result: - async for text in result.stream_text(delta=True): - text_count += 1 - if text_count >= 2: # Lower threshold - streaming may not produce many chunks - break # Early break - - end = time.time() - - assert text_count >= 1 # At least one chunk received - - # Check spans - may have incomplete spans due to early break - spans = memory_logger.pop() - assert len(spans) >= 1, f"Expected at least 1 span, got {len(spans)}" - - # Find agent_run_stream span (if created) - agent_span = next((s for s in spans if "agent_run_stream" in s["span_attributes"]["name"]), None) - - # Verify at least agent_run_stream span exists and has basic structure - if agent_span: - assert agent_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - # Metrics may be incomplete due to early break - assert "start" in agent_span["metrics"] - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_stream_buffer_pattern_early_return(memory_logger, direct): - """Test the _stream_single/_buffer_stream pattern with early return. - - This tests a common customer pattern where: - 1. An async generator wraps a stream and yields chunks + final response - 2. A consumer function returns early when it sees the final ModelResponse - 3. The generator cleanup happens in a different async context - - This pattern would trigger 'Token was created in a different Context' errors - before the task-tracking fix, because the consumer's early return causes - the generator to be cleaned up in a different task context. - """ - from collections.abc import AsyncIterator - - from pydantic_ai.messages import ModelResponse - - assert not memory_logger.pop() - - messages = [ModelRequest(parts=[UserPromptPart(content="Count from 1 to 5")])] - - class LLMStreamResponse: - """Wrapper for streaming responses.""" - - def __init__(self, llm_response, is_final=False): - self.llm_response = llm_response - self.is_final = is_final - - async def _stream_single() -> AsyncIterator[LLMStreamResponse]: - """Async generator that yields streaming chunks and final response.""" - async with direct.model_request_stream(model=MODEL, messages=messages) as stream: - async for chunk in stream: - yield LLMStreamResponse(llm_response=chunk, is_final=False) - - # Yield the final response after streaming completes - response = stream.get() - yield LLMStreamResponse(llm_response=response, is_final=True) - - async def _buffer_stream() -> LLMStreamResponse: - """Consumer that returns early when it gets a ModelResponse. - - This early return causes the generator to be cleaned up in a different - async context than where it was created, triggering the context issue. - """ - async for event in _stream_single(): - if isinstance(event.llm_response, ModelResponse): - # Early return - generator cleanup happens in different context - return event - raise RuntimeError("No ModelResponse received") - - start = time.time() - - # This should NOT raise ValueError about "different Context" - result = await _buffer_stream() - end = time.time() - - # Verify we got the final response - assert isinstance(result.llm_response, ModelResponse) - assert result.is_final - - # Check spans - should have created a span despite early generator cleanup - spans = memory_logger.pop() - assert len(spans) >= 1, "Should have at least one span even with early return" - - span = spans[0] - assert span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert span["span_attributes"]["name"] == "model_request_stream" - assert "start" in span["metrics"] - assert span["metrics"]["start"] >= start - # "end" may not be present if span was terminated early, but if present it should be valid - if "end" in span["metrics"]: - assert span["metrics"]["end"] <= end - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_stream_buffer_pattern_early_return(memory_logger): - """Test the _stream_single/_buffer_stream pattern with agent.run_stream(). - - This tests the same buffer/stream pattern but with the high-level Agent API - to ensure _AgentStreamWrapper also handles context cleanup correctly. - - Pattern: - 1. An async generator wraps agent.run_stream() and yields events + final result - 2. A consumer returns early when it sees the final result - 3. Generator cleanup happens in a different context - - This verifies both _AgentStreamWrapper and _DirectStreamWrapper handle - task context changes correctly. - """ - from collections.abc import AsyncIterator - - assert not memory_logger.pop() - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=100)) - - class StreamEvent: - """Wrapper for stream events.""" - - def __init__(self, data, is_final=False): - self.data = data - self.is_final = is_final - - async def _agent_stream_wrapper() -> AsyncIterator[StreamEvent]: - """Async generator that wraps agent streaming.""" - async with agent.run_stream("Count from 1 to 5") as result: - # Yield text chunks - async for text in result.stream_text(delta=True): - yield StreamEvent(data=text, is_final=False) - - # Yield final result after streaming - # Note: We can't call result.output here as it's consumed during streaming, - # so we yield a marker for the final event - yield StreamEvent(data="FINAL", is_final=True) - - async def _consume_until_final() -> StreamEvent: - """Consumer that returns early when it sees final event. - - This early return causes generator cleanup in different context. - """ - async for event in _agent_stream_wrapper(): - if event.is_final: - # Early return - generator cleanup in different context - return event - raise RuntimeError("No final event received") - - start = time.time() - - # This should NOT raise ValueError about "different Context" - result = await _consume_until_final() - end = time.time() - - # Verify we got the final event - assert result.is_final - assert result.data == "FINAL" - - # Check spans - should have created spans despite early generator cleanup - spans = memory_logger.pop() - assert len(spans) >= 1, "Should have at least one span" - - # Find agent_run_stream span - agent_span = next((s for s in spans if "agent_run_stream" in s["span_attributes"]["name"]), None) - assert agent_span is not None, "agent_run_stream span should exist" - assert agent_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert "start" in agent_span["metrics"] - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_with_binary_content(memory_logger): - """Test that agents with binary content (images) work correctly. - - Verifies that BinaryContent is properly converted to Braintrust attachments - in both the agent_run span (parent) and chat span (child). - """ - from braintrust.logger import Attachment - from pydantic_ai.models.function import BinaryContent - - assert not memory_logger.pop() - - # Use a small test image (1x1 PNG) - image_data = b'\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00\x00\x00\x01\x00\x00\x00\x01\x08\x06\x00\x00\x00\x1f\x15\xc4\x89\x00\x00\x00\nIDATx\x9cc\x00\x01\x00\x00\x05\x00\x01\r\n-\xb4\x00\x00\x00\x00IEND\xaeB`\x82' - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=50)) - - start = time.time() - result = await agent.run( - [ - BinaryContent(data=image_data, media_type="image/png"), - "What color is this image?", - ] - ) - end = time.time() - - assert result.output - assert isinstance(result.output, str) - - # Check spans - should have both agent_run and chat spans - spans = memory_logger.pop() - assert len(spans) >= 2, f"Expected at least 2 spans (agent_run + chat), got {len(spans)}" - - # Find agent_run span (parent) - agent_span = next((s for s in spans if "agent_run" in s["span_attributes"]["name"] and "chat" not in s["span_attributes"]["name"]), None) - assert agent_span is not None, "agent_run span not found" - - # Find chat span (child) - chat_span = next((s for s in spans if "chat" in s["span_attributes"]["name"]), None) - assert chat_span is not None, "chat span not found" - - # Verify basic span structure - assert agent_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert agent_span["metadata"]["model"] == "gpt-4o-mini" - _assert_metrics_are_valid(agent_span["metrics"], start, end) - - # CRITICAL: Verify that BOTH spans properly serialize BinaryContent to attachments - def has_attachment_in_input(span_input): - """Check if span input contains a Braintrust Attachment object.""" - if not span_input: - return False - - def check_item(item): - """Recursively check an item for attachments.""" - if isinstance(item, dict): - if item.get("type") == "binary" and isinstance(item.get("attachment"), Attachment): - return True - # Check nested content field (for UserPromptPart-like structures) - if "content" in item: - content = item["content"] - if isinstance(content, list): - for sub_item in content: - if check_item(sub_item): - return True - return False - - # Check user_prompt (agent_run span) - if "user_prompt" in span_input: - user_prompt = span_input["user_prompt"] - if isinstance(user_prompt, list): - for item in user_prompt: - if check_item(item): - return True - - # Check messages (chat span) - if "messages" in span_input: - messages = span_input["messages"] - if isinstance(messages, list): - for msg in messages: - if isinstance(msg, dict) and "parts" in msg: - parts = msg["parts"] - if isinstance(parts, list): - for part in parts: - if check_item(part): - return True - - return False - - # Verify agent_run span has attachment - agent_has_attachment = has_attachment_in_input(agent_span.get("input", {})) - assert agent_has_attachment, ( - "agent_run span should have BinaryContent converted to Braintrust Attachment. " - f"Input: {agent_span.get('input', {})}" - ) - - # Verify chat span has attachment (this is the key test for the bug) - chat_has_attachment = has_attachment_in_input(chat_span.get("input", {})) - assert chat_has_attachment, ( - "chat span should have BinaryContent converted to Braintrust Attachment. " - "The child span should process attachments the same way as the parent. " - f"Input: {chat_span.get('input', {})}" - ) - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_with_document_input(memory_logger): - """Test that agents with document input (PDF) properly serialize attachments. - - This specifically tests the scenario from test_document_input in the golden tests, - verifying that both agent_run and chat spans convert BinaryContent to Braintrust - attachments for document files like PDFs. - """ - from braintrust.logger import Attachment - from pydantic_ai.models.function import BinaryContent - - assert not memory_logger.pop() - - # Create a minimal PDF (this is a valid but minimal PDF structure) - pdf_data = b'%PDF-1.4\n1 0 obj<>endobj 2 0 obj<>endobj 3 0 obj<>endobj 4 0 obj<>stream\nBT /F1 12 Tf 100 700 Td (Test Document) Tj ET\nendstream\nendobj\nxref\n0 5\n0000000000 65535 f\n0000000009 00000 n\n0000000058 00000 n\n0000000115 00000 n\n0000000214 00000 n\ntrailer<>\nstartxref\n307\n%%EOF' - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=150)) - - start = time.time() - result = await agent.run( - [ - BinaryContent(data=pdf_data, media_type="application/pdf"), - "What is in this document?", - ] - ) - end = time.time() - - assert result.output - assert isinstance(result.output, str) - - # Check spans - spans = memory_logger.pop() - assert len(spans) >= 2, f"Expected at least 2 spans (agent_run + chat), got {len(spans)}" - - # Find spans - agent_span = next((s for s in spans if "agent_run" in s["span_attributes"]["name"] and "chat" not in s["span_attributes"]["name"]), None) - chat_span = next((s for s in spans if "chat" in s["span_attributes"]["name"]), None) - - assert agent_span is not None, "agent_run span not found" - assert chat_span is not None, "chat span not found" - - # Helper to check for PDF attachment - def has_pdf_attachment(span_input): - """Check if span input contains a PDF Braintrust Attachment.""" - if not span_input: - return False - - def check_item(item): - """Recursively check an item for PDF attachments.""" - if isinstance(item, dict): - if item.get("type") == "binary" and item.get("media_type") == "application/pdf": - attachment = item.get("attachment") - if isinstance(attachment, Attachment): - if attachment._reference.get("content_type") == "application/pdf": - return True - # Check nested content field (for UserPromptPart-like structures) - if "content" in item: - content = item["content"] - if isinstance(content, list): - for sub_item in content: - if check_item(sub_item): - return True - return False - - # Check user_prompt (agent_run span) - if "user_prompt" in span_input: - user_prompt = span_input["user_prompt"] - if isinstance(user_prompt, list): - for item in user_prompt: - if check_item(item): - return True - - # Check messages (chat span) - if "messages" in span_input: - messages = span_input["messages"] - if isinstance(messages, list): - for msg in messages: - if isinstance(msg, dict) and "parts" in msg: - parts = msg["parts"] - if isinstance(parts, list): - for part in parts: - if check_item(part): - return True - - return False - - # Verify agent_run span has PDF attachment - assert has_pdf_attachment(agent_span.get("input", {})), ( - "agent_run span should have PDF BinaryContent converted to Braintrust Attachment" - ) - - # Verify chat span has PDF attachment (critical for document input) - assert has_pdf_attachment(chat_span.get("input", {})), ( - "chat span should have PDF BinaryContent converted to Braintrust Attachment. " - "This ensures documents are properly traced in the low-level model call. " - f"Chat span input: {chat_span.get('input', {})}" - ) - - # Verify metrics - _assert_metrics_are_valid(agent_span["metrics"], start, end) - _assert_metrics_are_valid(chat_span["metrics"], start, end) - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_with_tool_execution(memory_logger): - """Test that tool execution creates proper span hierarchy. - - Verifies that: - 1. Agent creates proper spans for tool calls - 2. Tool execution is captured in spans (ideally with "running tools" parent) - 3. Individual tool calls create child spans - """ - assert not memory_logger.pop() - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=200)) - - @agent.tool_plain - def calculate(operation: str, a: float, b: float) -> str: - """Perform a mathematical calculation. - - Args: - operation: The mathematical operation (add, subtract, multiply, divide) - a: First number - b: Second number - """ - ops = { - "add": a + b, - "subtract": a - b, - "multiply": a * b, - "divide": a / b if b != 0 else "Error: Division by zero", - } - return str(ops.get(operation, "Invalid operation")) - - start = time.time() - result = await agent.run("What is 127 multiplied by 49?") - end = time.time() - - assert result.output - assert "6" in str(result.output) and "223" in str(result.output) # Result contains 6223 (possibly formatted) - - # Check spans - spans = memory_logger.pop() - - # We should have at least agent_run and chat spans - # TODO: Add "running tools" parent span and "running tool: calculate" child span - assert len(spans) >= 2, f"Expected at least 2 spans, got {len(spans)}" - - # Find agent_run span - agent_span = next((s for s in spans if "agent_run" in s["span_attributes"]["name"]), None) - assert agent_span is not None, "agent_run span not found" - - # Verify that toolsets are captured in input with correct tool names - assert "toolsets" in agent_span["input"], "toolsets should be in input (not metadata)" - toolsets = agent_span["input"]["toolsets"] - assert len(toolsets) > 0, "At least one toolset should be present" - - # Find the agent toolset - agent_toolset = None - for ts in toolsets: - if ts.get("id") == "": - agent_toolset = ts - break - - assert agent_toolset is not None, "Agent toolset not found" - assert "tools" in agent_toolset, "tools should be in agent toolset" - - # Verify calculate tool is present (tools are now dicts with full schemas in input) - tools = agent_toolset["tools"] - assert isinstance(tools, list), "tools should be a list" - tool_names = [t["name"] for t in tools if isinstance(t, dict)] - assert "calculate" in tool_names, f"calculate tool should be in tools list, got: {tool_names}" - - # Verify toolsets are NOT in metadata (following the principle: agent.run() accepts it) - assert "toolsets" not in agent_span["metadata"], "toolsets should NOT be in metadata" - - -@pytest.mark.vcr -def test_tool_execution_creates_spans(memory_logger): - """Test that executing tools with agents works and creates traced spans. - - Note: Tool-level span creation is not yet implemented in the wrapper. - This test verifies that agents with tools work correctly and produce agent/chat spans. - - Future enhancement: Add automatic span creation for tool executions as children of - the chat span that requested them. - """ - assert not memory_logger.pop() - - start = time.time() - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=500)) - - @agent.tool_plain - def calculate(operation: str, a: float, b: float) -> float: - """Perform a mathematical calculation.""" - if operation == "multiply": - return a * b - elif operation == "add": - return a + b - else: - return 0.0 - - # Run the agent with a query that will use the tool - result = agent.run_sync("What is 127 multiplied by 49?") - end = time.time() - - # Verify the tool was actually called and result is correct - assert result.output - assert "6223" in str(result.output) or "6,223" in str(result.output), f"Expected calculation result in output: {result.output}" - - # Get logged spans - spans = memory_logger.pop() - - # Find spans by type - agent_span = next((s for s in spans if "agent_run" in s["span_attributes"]["name"]), None) - chat_spans = [s for s in spans if "chat" in s["span_attributes"]["name"]] - - # Assertions - verify basic tracing works with tools - assert agent_span is not None, "agent_run span should exist" - assert len(chat_spans) >= 1, f"Expected at least 1 chat span, got {len(chat_spans)}" - - # Verify agent span has tool information in input - assert "toolsets" in agent_span["input"], "Tool information should be captured in agent input" - toolsets = agent_span["input"]["toolsets"] - agent_toolset = next((ts for ts in toolsets if ts.get("id") == ""), None) - assert agent_toolset is not None, "Agent toolset should be in input" - - # Verify calculate tool is in the toolset - tools = agent_toolset.get("tools", []) - tool_names = [t["name"] for t in tools if isinstance(t, dict)] - assert "calculate" in tool_names, f"calculate tool should be in toolset, got: {tool_names}" - - # TODO: Future enhancement - verify tool execution spans are created - # tool_spans = [s for s in spans if "calculate" in s["span_attributes"].get("name", "")] - # assert len(tool_spans) > 0, "Tool execution should create spans" - - -def test_agent_tool_metadata_extraction(memory_logger): - """Test that agent tools are properly extracted with full schemas in INPUT (not metadata). - - Principle: If agent.run() accepts it, it goes in input only. - """ - from braintrust.wrappers.pydantic_ai import _build_agent_input_and_metadata - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=100)) - - # Add multiple tools with different signatures - @agent.tool_plain - def calculate(operation: str, a: float, b: float) -> str: - """Perform a mathematical calculation.""" - return str(a + b) - - @agent.tool_plain - def get_weather(location: str) -> str: - """Get weather for a location.""" - return f"Weather in {location}" - - @agent.tool_plain - def search_database(query: str, limit: int = 10) -> str: - """Search the database.""" - return "Results" - - # Extract metadata using the actual function signature - args = ("Test prompt",) - kwargs = {} - input_data, metadata = _build_agent_input_and_metadata(args, kwargs, agent) - - # Verify toolsets are in INPUT (since agent.run() accepts toolsets parameter) - assert "toolsets" in input_data, "toolsets should be in input (can be passed to agent.run())" - toolsets = input_data["toolsets"] - assert len(toolsets) > 0, "At least one toolset should be present" - - # Verify toolsets are NOT in metadata (following the principle) - assert "toolsets" not in metadata, "toolsets should NOT be in metadata (it's a run() parameter)" - - # Find the agent toolset - agent_toolset = None - for ts in toolsets: - if ts.get("id") == "": - agent_toolset = ts - break - - assert agent_toolset is not None, "Agent toolset not found in input" - assert agent_toolset.get("label") == "the agent", "Agent toolset should have correct label" - assert "tools" in agent_toolset, "tools should be in agent toolset" - - # Verify all tools are present with FULL SCHEMAS - tools = agent_toolset["tools"] - assert isinstance(tools, list), "tools should be a list" - assert len(tools) == 3, f"Should have exactly 3 tools, got {len(tools)}" - - # Check each tool has full schema information - tool_names = [t["name"] for t in tools] - assert "calculate" in tool_names, f"calculate tool should be present, got: {tool_names}" - assert "get_weather" in tool_names, f"get_weather tool should be present, got: {tool_names}" - assert "search_database" in tool_names, f"search_database tool should be present, got: {tool_names}" - - # Verify calculate tool has full schema - calculate_tool = next(t for t in tools if t["name"] == "calculate") - assert "description" in calculate_tool, "Tool should have description" - assert "Perform a mathematical calculation" in calculate_tool["description"] - assert "parameters" in calculate_tool, "Tool should have parameters schema" - params = calculate_tool["parameters"] - assert "properties" in params, "Parameters should have properties" - assert "operation" in params["properties"], "Should have 'operation' parameter" - assert "a" in params["properties"], "Should have 'a' parameter" - assert "b" in params["properties"], "Should have 'b' parameter" - assert params["properties"]["operation"]["type"] == "string" - assert params["properties"]["a"]["type"] == "number" - assert params["properties"]["b"]["type"] == "number" - - # Verify search_database has optional parameter - search_tool = next(t for t in tools if t["name"] == "search_database") - assert "parameters" in search_tool - search_params = search_tool["parameters"] - assert "query" in search_params["properties"] - assert "limit" in search_params["properties"] - # 'query' should be required, 'limit' should be optional (has default) - assert "query" in search_params.get("required", []) - - -def test_agent_without_tools_metadata(): - """Test metadata extraction for agent without tools.""" - from braintrust.wrappers.pydantic_ai import _build_agent_input_and_metadata - - # Agent with no tools - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=50)) - - args = ("Test prompt",) - kwargs = {} - input_data, metadata = _build_agent_input_and_metadata(args, kwargs, agent) - - # Should have toolsets in input (even if empty) - # Note: Pydantic AI agents always have some toolsets (e.g., for output parsing) - # so we just verify the structure exists - assert isinstance(input_data.get("toolsets"), (list, type(None))), "toolsets should be list or None in input" - - -def test_agent_tool_with_custom_name(): - """Test that tools with custom names are properly extracted with schemas in input.""" - from braintrust.wrappers.pydantic_ai import _build_agent_input_and_metadata - - agent = Agent(MODEL) - - # Add tool with custom name - @agent.tool_plain(name="custom_calculator") - def calc(a: int, b: int) -> int: - """Add two numbers.""" - return a + b - - args = ("Test",) - kwargs = {} - input_data, metadata = _build_agent_input_and_metadata(args, kwargs, agent) - - # Verify custom name is used in input (not metadata) - assert "toolsets" in input_data - assert "toolsets" not in metadata, "toolsets should not be in metadata" - - agent_toolset = next((ts for ts in input_data["toolsets"] if ts.get("id") == ""), None) - assert agent_toolset is not None - tools = agent_toolset.get("tools", []) - - # The tool should be a dict with schema info - assert len(tools) == 1, f"Should have 1 tool, got {len(tools)}" - tool = tools[0] - assert isinstance(tool, dict), "Tool should be a dict with schema" - assert tool["name"] == "custom_calculator", f"Should use custom name, got: {tool.get('name')}" - assert "description" in tool, "Tool should have description" - assert "parameters" in tool, "Tool should have parameters schema" - assert "a" in tool["parameters"]["properties"] - assert "b" in tool["parameters"]["properties"] - - -def test_explicit_toolsets_kwarg_in_input(): - """Test that explicitly passed toolsets kwarg goes to input (not just metadata).""" - from braintrust.wrappers.pydantic_ai import _build_agent_input_and_metadata - - agent = Agent(MODEL) - - # Add a tool to the agent - @agent.tool_plain - def helper_tool() -> str: - """A helper tool.""" - return "help" - - # Simulate passing toolsets as explicit kwarg (would be a different toolset in practice) - # For testing, we'll just pass the string "custom" to see it in input - args = ("Test",) - kwargs = {"toolsets": "custom_toolset_marker"} # Simplified for testing - input_data, metadata = _build_agent_input_and_metadata(args, kwargs, agent) - - # Toolsets passed as kwargs should be in input - assert "toolsets" in input_data, "explicitly passed toolsets should be in input" - - -@pytest.mark.vcr -def test_reasoning_tokens_extraction(memory_logger): - """Test that reasoning tokens are extracted from model responses. - - For reasoning models like o1/o3, usage.details.reasoning_tokens should be - captured in the metrics field. - """ - assert not memory_logger.pop() - - # Mock a response that has reasoning tokens - from unittest.mock import MagicMock - - # Create a mock response with reasoning tokens - mock_response = MagicMock() - mock_response.parts = [ - MagicMock( - part_kind="thinking", - content="Let me think about this...", - ), - MagicMock( - part_kind="text", - content="The answer is 42", - ), - ] - mock_response.usage = MagicMock() - mock_response.usage.input_tokens = 10 - mock_response.usage.output_tokens = 20 - mock_response.usage.total_tokens = 30 - mock_response.usage.cache_read_tokens = 0 - mock_response.usage.cache_write_tokens = 0 - mock_response.usage.details = MagicMock() - mock_response.usage.details.reasoning_tokens = 128 - - # Test the metric extraction function directly - from braintrust.wrappers.pydantic_ai import _extract_response_metrics - - start_time = time.time() - end_time = start_time + 5.0 - - metrics = _extract_response_metrics(mock_response, start_time, end_time) - - # Verify all metrics are present - assert metrics is not None, "Should extract metrics" - # pylint: disable=unsupported-membership-test,unsubscriptable-object - assert "prompt_tokens" in metrics, "Should have prompt_tokens" - assert metrics["prompt_tokens"] == 10.0 - assert "completion_tokens" in metrics, "Should have completion_tokens" - assert metrics["completion_tokens"] == 20.0 - assert "tokens" in metrics, "Should have total tokens" - assert metrics["tokens"] == 30.0 - assert "completion_reasoning_tokens" in metrics, "Should have completion_reasoning_tokens" - assert metrics["completion_reasoning_tokens"] == 128.0, f"Expected 128.0, got {metrics['completion_reasoning_tokens']}" - assert "duration" in metrics - assert "start" in metrics - assert "end" in metrics - # pylint: enable=unsupported-membership-test,unsubscriptable-object - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_agent_run_stream_structured_output(memory_logger): - """Test Agent.run_stream() with structured output (Pydantic model). - - Verifies that streaming structured output creates proper spans and - that the result can be accessed via get_output() method. - """ - assert not memory_logger.pop() - - class Product(BaseModel): - name: str - price: float - - agent = Agent( - MODEL, - output_type=Product, - model_settings=ModelSettings(max_tokens=200) - ) - - start = time.time() - async with agent.run_stream("Create a product: wireless mouse for $29.99") as result: - # For structured output, use get_output() instead of streaming text - product = await result.get_output() - end = time.time() - - # Verify structured output - assert isinstance(product, Product) - assert product.name - assert product.price > 0 - - # Check spans - spans = memory_logger.pop() - assert len(spans) >= 2, f"Expected at least 2 spans (agent_run_stream + chat), got {len(spans)}" - - # Find agent_run_stream and chat spans - agent_span = next((s for s in spans if "agent_run_stream" in s["span_attributes"]["name"]), None) - chat_span = next((s for s in spans if "chat" in s["span_attributes"]["name"]), None) - - assert agent_span is not None, "agent_run_stream span not found" - assert chat_span is not None, "chat span not found" - - # Check agent span - assert agent_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert agent_span["metadata"]["model"] == "gpt-4o-mini" - _assert_metrics_are_valid(agent_span["metrics"], start, end) - - # Check chat span is nested - assert chat_span["span_parents"] == [agent_span["span_id"]], "chat span should be nested under agent_run_stream" - assert chat_span["metadata"]["model"] == "gpt-4o-mini" - _assert_metrics_are_valid(chat_span["metrics"], start, end) - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_model_class_span_names(memory_logger): - """Test that model class spans have proper names. - - Verifies that the nested chat span from the model class wrapper has a - meaningful name (either the model name or class name), not a misleading - string like 'log'. - - This test ensures that when model_name is None, we fall back to the - class name (e.g., 'OpenAIChatModel') rather than str(instance) which - could return unexpected values. - """ - assert not memory_logger.pop() - - agent = Agent(MODEL, model_settings=ModelSettings(max_tokens=50)) - - start = time.time() - result = await agent.run("What is 2+2?") - end = time.time() - - assert result.output - - # Check spans - spans = memory_logger.pop() - assert len(spans) == 2, f"Expected 2 spans (agent_run + chat), got {len(spans)}" - - # Find chat span (the nested model class span) - chat_span = next((s for s in spans if "chat" in s["span_attributes"]["name"]), None) - assert chat_span is not None, "chat span not found" - - span_name = chat_span["span_attributes"]["name"] - - # Verify the span name is meaningful - # It should be either "chat " or "chat " - # but NOT "chat log" or other misleading names - assert span_name.startswith("chat "), f"Chat span should start with 'chat ', got: {span_name}" - - # Extract the model/class identifier part after "chat " - identifier = span_name[5:] # Skip "chat " - - # Should not be empty or misleading values - assert identifier, "Chat span should have a model name or class name after 'chat '" - assert identifier != "log", "Chat span should not be named 'log' - should use model name or class name" - assert len(identifier) > 2, f"Chat span identifier seems too short: {identifier}" - - # Common valid patterns: - # - "chat gpt-4o-mini" (model name extracted) - # - "chat OpenAIChatModel" (class name fallback) - # - "chat gpt-4o" (model name) - valid_patterns = [ - "gpt-" in identifier, # OpenAI model names - "claude" in identifier.lower(), # Anthropic models - "Model" in identifier, # Class name fallback (e.g., OpenAIChatModel) - "-" in identifier, # Model names typically have hyphens - ] - - assert any(valid_patterns), ( - f"Chat span name '{span_name}' doesn't match expected patterns. " - f"Should contain model name (e.g., 'gpt-4o-mini') or class name (e.g., 'OpenAIChatModel')" - ) - - # Verify span has proper structure - assert chat_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert chat_span["metadata"]["model"] == "gpt-4o-mini" - _assert_metrics_are_valid(chat_span["metrics"], start, end) - - -def test_serialize_content_part_with_binary_content(): - """Unit test to verify _serialize_content_part handles BinaryContent correctly. - - This tests the direct serialization of BinaryContent objects and verifies - they are converted to Braintrust Attachment objects. - """ - from braintrust.logger import Attachment - from braintrust.wrappers.pydantic_ai import _serialize_content_part - from pydantic_ai.models.function import BinaryContent - - # Test 1: Direct BinaryContent serialization - binary = BinaryContent(data=b"test pdf data", media_type="application/pdf") - result = _serialize_content_part(binary) - - assert result is not None, "Should serialize BinaryContent" - assert result["type"] == "binary", "Should have type 'binary'" - assert result["media_type"] == "application/pdf", "Should preserve media_type" - assert isinstance(result["attachment"], Attachment), "Should convert to Braintrust Attachment" - - # Verify attachment has correct content_type - assert result["attachment"]._reference["content_type"] == "application/pdf" - - -def test_serialize_content_part_with_user_prompt_part(): - """Unit test to verify _serialize_content_part handles UserPromptPart with nested BinaryContent. - - This is the critical test for the bug: when a UserPromptPart has a content list - containing BinaryContent, we need to recursively serialize the content items - so that BinaryContent is converted to Braintrust Attachment. - """ - from braintrust.logger import Attachment - from braintrust.wrappers.pydantic_ai import _serialize_content_part - from pydantic_ai.messages import UserPromptPart - from pydantic_ai.models.function import BinaryContent - - # Create a UserPromptPart with mixed content (BinaryContent + string) - pdf_data = b"%PDF-1.4 test document content" - binary = BinaryContent(data=pdf_data, media_type="application/pdf") - user_prompt_part = UserPromptPart(content=[binary, "What is in this document?"]) - - # Serialize the UserPromptPart - result = _serialize_content_part(user_prompt_part) - - # Verify the result is a dict with serialized content - assert isinstance(result, dict), f"Should return dict, got {type(result)}" - assert "content" in result, f"Should have 'content' key. Keys: {result.keys()}" - - content = result["content"] - assert isinstance(content, list), f"Content should be a list, got {type(content)}" - assert len(content) == 2, f"Should have 2 content items, got {len(content)}" - - # CRITICAL: First item should be serialized BinaryContent with Attachment - binary_item = content[0] - assert isinstance(binary_item, dict), f"Binary item should be dict, got {type(binary_item)}" - assert binary_item.get("type") == "binary", ( - f"Binary item should have type='binary'. Got: {binary_item}" - ) - assert "attachment" in binary_item, ( - f"Binary item should have 'attachment' key. Keys: {binary_item.keys()}" - ) - assert isinstance(binary_item["attachment"], Attachment), ( - f"Should be Braintrust Attachment, got {type(binary_item.get('attachment'))}" - ) - assert binary_item["media_type"] == "application/pdf" - - # Second item should be the string - assert content[1] == "What is in this document?" - - -def test_serialize_messages_with_binary_content(): - """Unit test to verify _serialize_messages handles ModelRequest with BinaryContent in parts. - - This tests the full message serialization path that's used for the chat span, - ensuring that nested BinaryContent in UserPromptPart is properly converted. - """ - from braintrust.logger import Attachment - from braintrust.wrappers.pydantic_ai import _serialize_messages - from pydantic_ai.messages import ModelRequest, UserPromptPart - from pydantic_ai.models.function import BinaryContent - - # Create a ModelRequest with UserPromptPart containing BinaryContent - pdf_data = b"%PDF-1.4 test document content" - binary = BinaryContent(data=pdf_data, media_type="application/pdf") - user_prompt_part = UserPromptPart(content=[binary, "What is in this document?"]) - model_request = ModelRequest(parts=[user_prompt_part]) - - # Serialize the messages - messages = [model_request] - result = _serialize_messages(messages) - - # Verify structure - assert len(result) == 1, f"Should have 1 message, got {len(result)}" - msg = result[0] - assert "parts" in msg, f"Message should have 'parts'. Keys: {msg.keys()}" - - parts = msg["parts"] - assert len(parts) == 1, f"Should have 1 part, got {len(parts)}" - - part = parts[0] - assert isinstance(part, dict), f"Part should be dict, got {type(part)}" - assert "content" in part, f"Part should have 'content'. Keys: {part.keys()}" - - content = part["content"] - assert isinstance(content, list), f"Content should be list, got {type(content)}" - assert len(content) == 2, f"Should have 2 content items, got {len(content)}" - - # CRITICAL: First content item should be serialized BinaryContent with Attachment - binary_item = content[0] - assert isinstance(binary_item, dict), f"Binary item should be dict, got {type(binary_item)}" - assert binary_item.get("type") == "binary", ( - f"Binary item should have type='binary'. Got: {binary_item}" - ) - assert "attachment" in binary_item, ( - f"Binary item should have 'attachment'. Keys: {binary_item.keys()}" - ) - assert isinstance(binary_item["attachment"], Attachment), ( - f"Should be Braintrust Attachment, got {type(binary_item.get('attachment'))}" - ) - assert binary_item["media_type"] == "application/pdf" - - # Second content item should be the string - assert content[1] == "What is in this document?" - - -@pytest.mark.asyncio -async def test_streaming_wrappers_capture_time_to_first_token(): - """Unit test verifying all streaming wrappers capture time_to_first_token. - - This test uses mocks to verify the internal wrapper logic without requiring - API calls. It ensures that _first_token_time is tracked correctly in: - - _AgentStreamWrapper (async agent streaming) - - _DirectStreamWrapper (async direct API streaming) - - _AgentStreamResultSyncProxy (sync agent streaming) - - _DirectStreamWrapperSync (sync direct API streaming) - """ - from unittest.mock import AsyncMock, MagicMock, Mock - - from braintrust.wrappers.pydantic_ai import ( - _AgentStreamResultSyncProxy, - _AgentStreamWrapper, - _DirectStreamIteratorProxy, - _DirectStreamIteratorSyncProxy, - _DirectStreamWrapper, - _DirectStreamWrapperSync, - _StreamResultProxy, - ) - - # Test 1: _AgentStreamWrapper captures first token time - print("\n--- Testing _AgentStreamWrapper ---") - - class MockStreamResult: - async def stream_text(self, delta=True): - for i in range(3): - await asyncio.sleep(0.001) - yield f"token{i} " - - def usage(self): - usage_mock = Mock(input_tokens=50, output_tokens=20, total_tokens=70) - usage_mock.cache_read_tokens = None - usage_mock.cache_write_tokens = None - return usage_mock - - mock_stream_result = MockStreamResult() - wrapper = _AgentStreamWrapper( - stream_cm=AsyncMock(), - span_name="test_stream", - input_data={"prompt": "test"}, - metadata={"model": "gpt-4o"}, - ) - - wrapper.span_cm = MagicMock() - wrapper.span_cm.__enter__ = MagicMock() - wrapper.start_time = time.time() - wrapper.stream_result = mock_stream_result - - proxy = _StreamResultProxy(mock_stream_result, wrapper) - - assert wrapper._first_token_time is None - - chunk_count = 0 - async for text in proxy.stream_text(delta=True): - chunk_count += 1 - if chunk_count == 1: - assert wrapper._first_token_time is not None - assert wrapper._first_token_time > wrapper.start_time - - assert chunk_count == 3 - assert wrapper._first_token_time is not None - print("โœ“ _AgentStreamWrapper captures first token time") - - # Test 2: _DirectStreamWrapper captures first token time - print("\n--- Testing _DirectStreamWrapper ---") - - class MockStream: - def __init__(self): - self.chunks = [] - - async def __anext__(self): - if len(self.chunks) < 3: - await asyncio.sleep(0.001) - chunk = Mock(delta=Mock(content_delta=f"chunk{len(self.chunks)}")) - self.chunks.append(chunk) - return chunk - raise StopAsyncIteration - - def __aiter__(self): - return self - - def get(self): - usage_mock = Mock(input_tokens=50, output_tokens=20, total_tokens=70) - usage_mock.cache_read_tokens = None - usage_mock.cache_write_tokens = None - return Mock(usage=usage_mock) - - mock_stream = MockStream() - direct_wrapper = _DirectStreamWrapper( - stream_cm=AsyncMock(), - span_name="test_direct_stream", - input_data={"messages": []}, - metadata={"model": "gpt-4o"}, - ) - - direct_wrapper.span_cm = MagicMock() - direct_wrapper.start_time = time.time() - direct_wrapper.stream = mock_stream - - proxy = _DirectStreamIteratorProxy(mock_stream, direct_wrapper) - - assert direct_wrapper._first_token_time is None - - chunk_count = 0 - async for chunk in proxy: - chunk_count += 1 - if chunk_count == 1: - assert direct_wrapper._first_token_time is not None - assert direct_wrapper._first_token_time > direct_wrapper.start_time - - assert chunk_count == 3 - assert direct_wrapper._first_token_time is not None - print("โœ“ _DirectStreamWrapper captures first token time") - - # Test 3: _AgentStreamResultSyncProxy captures first token time - print("\n--- Testing _AgentStreamResultSyncProxy ---") - - class MockSyncStreamResult: - def stream_text(self, delta=True): - for i in range(3): - time.sleep(0.001) - yield f"token{i} " - - def usage(self): - usage_mock = Mock(input_tokens=50, output_tokens=20, total_tokens=70) - usage_mock.cache_read_tokens = None - usage_mock.cache_write_tokens = None - return usage_mock - - mock_sync_result = MockSyncStreamResult() - sync_proxy = _AgentStreamResultSyncProxy( - stream_result=mock_sync_result, - span=MagicMock(), - span_cm=MagicMock(), - start_time=time.time(), - ) - - assert sync_proxy._first_token_time is None - - chunk_count = 0 - for text in sync_proxy.stream_text(delta=True): - chunk_count += 1 - if chunk_count == 1: - assert sync_proxy._first_token_time is not None - - assert chunk_count == 3 - assert sync_proxy._first_token_time is not None - print("โœ“ _AgentStreamResultSyncProxy captures first token time") - - # Test 4: _DirectStreamWrapperSync captures first token time - print("\n--- Testing _DirectStreamWrapperSync ---") - - class MockSyncStream: - def __init__(self): - self.chunks = [] - - def __iter__(self): - return self - - def __next__(self): - if len(self.chunks) < 3: - time.sleep(0.001) - chunk = Mock(delta=Mock(content_delta=f"chunk{len(self.chunks)}")) - self.chunks.append(chunk) - return chunk - raise StopIteration - - def get(self): - usage_mock = Mock(input_tokens=50, output_tokens=20, total_tokens=70) - usage_mock.cache_read_tokens = None - usage_mock.cache_write_tokens = None - return Mock(usage=usage_mock) - - mock_sync_stream = MockSyncStream() - sync_wrapper = _DirectStreamWrapperSync( - stream_cm=MagicMock(), - span_name="test_sync_stream", - input_data={"messages": []}, - metadata={"model": "gpt-4o"}, - ) - - sync_wrapper.start_time = time.time() - sync_wrapper.stream = mock_sync_stream - - sync_proxy = _DirectStreamIteratorSyncProxy(mock_sync_stream, sync_wrapper) - - assert sync_wrapper._first_token_time is None - - chunk_count = 0 - for chunk in sync_proxy: - chunk_count += 1 - if chunk_count == 1: - assert sync_wrapper._first_token_time is not None - assert sync_wrapper._first_token_time > sync_wrapper.start_time - - assert chunk_count == 3 - assert sync_wrapper._first_token_time is not None - print("โœ“ _DirectStreamWrapperSync captures first token time") - - print("\nโœ… All streaming wrapper unit tests passed!") - - -@pytest.mark.asyncio -async def test_attachment_preserved_in_model_settings(memory_logger): - """Test that attachments in model_settings are preserved through serialization.""" - from braintrust.bt_json import bt_safe_deep_copy - from braintrust.logger import Attachment - - attachment = Attachment(data=b"config data", filename="config.txt", content_type="text/plain") - - # Simulate model_settings with attachment - settings = {"temperature": 0.7, "context_file": attachment} - - # Test bt_safe_deep_copy preserves attachment - copied = bt_safe_deep_copy(settings) - assert copied["context_file"] is attachment - assert copied["temperature"] == 0.7 - - -@pytest.mark.asyncio -async def test_attachment_in_message_part(memory_logger): - """Test that attachment in custom message part is preserved.""" - from braintrust.bt_json import bt_safe_deep_copy - from braintrust.logger import Attachment - - attachment = Attachment(data=b"message data", filename="msg.txt", content_type="text/plain") - - # Simulate message part with attachment - message_part = {"type": "file", "content": attachment, "metadata": {"source": "upload"}} - - copied = bt_safe_deep_copy(message_part) - assert copied["content"] is attachment - assert copied["type"] == "file" - - -@pytest.mark.asyncio -async def test_attachment_in_result_data(memory_logger): - """Test that attachment in custom result data is preserved.""" - from braintrust.bt_json import bt_safe_deep_copy - from braintrust.logger import ExternalAttachment - - ext_attachment = ExternalAttachment( - url="s3://bucket/result.pdf", filename="result.pdf", content_type="application/pdf" - ) - - # Simulate agent result with attachment - result_data = {"success": True, "output_file": ext_attachment, "metadata": {"processed": True}} - - copied = bt_safe_deep_copy(result_data) - assert copied["output_file"] is ext_attachment - assert copied["success"] is True - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_no_model_agent_run(memory_logger): - """Agent created without a model should work when model is passed at runtime. - - Reproduces https://github.com/braintrustdata/braintrust-sdk/issues/1324: - _ensure_model_wrapped() calls type(instance._model) without checking for None, - crashing with: AttributeError: type object 'NoneType' has no attribute 'request' - """ - assert not memory_logger.pop() - - agent = Agent(model_settings=ModelSettings(max_tokens=50)) - - start = time.time() - result = await agent.run(TEST_PROMPT, model=MODEL) - end = time.time() - - assert result.output - assert "4" in str(result.output) - - spans = memory_logger.pop() - assert len(spans) == 2, f"Expected 2 spans (agent_run + chat), got {len(spans)}" - - agent_span = next((s for s in spans if "agent_run" in s["span_attributes"]["name"]), None) - chat_span = next((s for s in spans if "chat" in s["span_attributes"]["name"]), None) - - assert agent_span is not None, "agent_run span not found" - assert chat_span is not None, "chat span not found" - - assert agent_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert agent_span["metadata"]["model"] == "gpt-4o-mini" - assert agent_span["metadata"]["provider"] == "openai" - assert TEST_PROMPT in str(agent_span["input"]) - assert "4" in str(agent_span["output"]) - - assert chat_span["span_parents"] == [agent_span["span_id"]] - assert chat_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert chat_span["metadata"]["model"] == "gpt-4o-mini" - - -class TestAutoInstrumentPydanticAI: - """Tests for auto_instrument() with Pydantic AI.""" - - def test_auto_instrument_pydantic_ai(self): - """Test auto_instrument patches Pydantic AI and creates spans.""" - verify_autoinstrument_script("test_auto_pydantic_ai.py") diff --git a/py/src/braintrust/wrappers/test_pydantic_ai_logfire.py b/py/src/braintrust/wrappers/test_pydantic_ai_logfire.py deleted file mode 100644 index 538c32861..000000000 --- a/py/src/braintrust/wrappers/test_pydantic_ai_logfire.py +++ /dev/null @@ -1,76 +0,0 @@ -"""Test that braintrust's pydantic_ai integration works alongside logfire. - -Reproduces https://github.com/braintrustdata/braintrust-sdk/issues/1324: -setup_pydantic_ai() conflicts with logfire's instrument_pydantic_ai() when -an agent is created without a model parameter. -""" - -import time - -import pytest -from braintrust import logger, setup_pydantic_ai -from braintrust.span_types import SpanTypeAttribute -from braintrust.test_helpers import init_test_logger -from pydantic_ai import Agent, ModelSettings - -PROJECT_NAME = "test-pydantic-ai-logfire" -MODEL = "openai:gpt-4o-mini" -TEST_PROMPT = "What is 2+2? Answer with just the number." - - -@pytest.fixture(scope="module", autouse=True) -def setup_wrapper(): - """Setup pydantic_ai wrapper and logfire before any tests run.""" - import logfire - - logfire.configure(send_to_logfire=False) - logfire.instrument_pydantic_ai() - setup_pydantic_ai(project_name=PROJECT_NAME) - yield - - -@pytest.fixture -def memory_logger(): - init_test_logger(PROJECT_NAME) - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_no_model_agent_run_with_logfire(memory_logger): - """Agent created without a model should produce spans when model is passed at runtime. - - This is the core scenario from issue #1324: logfire's instrument_pydantic_ai() - is active alongside setup_pydantic_ai(), and the agent has no model set at - construction time. - """ - assert not memory_logger.pop() - - agent = Agent(model_settings=ModelSettings(max_tokens=50)) - - start = time.time() - result = await agent.run(TEST_PROMPT, model=MODEL) - end = time.time() - - assert result.output - assert "4" in str(result.output) - - spans = memory_logger.pop() - assert len(spans) == 2, f"Expected 2 spans (agent_run + chat), got {len(spans)}" - - agent_span = next((s for s in spans if "agent_run" in s["span_attributes"]["name"]), None) - chat_span = next((s for s in spans if "chat" in s["span_attributes"]["name"]), None) - - assert agent_span is not None, "agent_run span not found" - assert chat_span is not None, "chat span not found" - - assert agent_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert agent_span["metadata"]["model"] == "gpt-4o-mini" - assert agent_span["metadata"]["provider"] == "openai" - assert TEST_PROMPT in str(agent_span["input"]) - assert "4" in str(agent_span["output"]) - - assert chat_span["span_parents"] == [agent_span["span_id"]] - assert chat_span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert chat_span["metadata"]["model"] == "gpt-4o-mini" diff --git a/py/src/braintrust/wrappers/test_pydantic_ai_wrap_openai.py b/py/src/braintrust/wrappers/test_pydantic_ai_wrap_openai.py deleted file mode 100644 index b7e2bd9cf..000000000 --- a/py/src/braintrust/wrappers/test_pydantic_ai_wrap_openai.py +++ /dev/null @@ -1,151 +0,0 @@ -import time -from typing import Any, Dict - -import pytest -from openai import AsyncOpenAI -from pydantic_ai import Agent # pylint: disable=import-error - -try: - # Try new API first (pydantic_ai >= 1.0) - from pydantic_ai.models.openai import OpenAIChatModel # pylint: disable=import-error - - OpenAIModelClass = OpenAIChatModel -except ImportError: - # Fall back to old API (pydantic_ai < 1.0) - from pydantic_ai.models.openai import OpenAIModel # pylint: disable=import-error - - OpenAIModelClass = OpenAIModel -from braintrust import logger, wrap_openai -from braintrust.span_types import SpanTypeAttribute -from braintrust.test_helpers import init_test_logger -from pydantic_ai.providers.openai import OpenAIProvider # pylint: disable=import-error - -PROJECT_NAME = "test-pydantic-ai" -MODEL = "gpt-3.5-turbo" # Use a cheaper model for testing -TEST_PROMPT = "What is the capital of Italy?" - - -def get_pydantic_agents_client(model_name: str, client: AsyncOpenAI): - _provider = OpenAIProvider(openai_client=client) - return OpenAIModelClass(model_name, provider=_provider) - - -async def _run_prompt_streaming(client: AsyncOpenAI, prompt: str): - model = get_pydantic_agents_client(MODEL, client=client) - agent = Agent(model=model) - result_text = "" - async with agent.run_stream(prompt) as result: - # Use stream_output if available (pydantic_ai >= 1.0), otherwise use stream - if hasattr(result, "stream_output"): - async for text in result.stream_output(debounce_by=0.01): - result_text = text - else: - async for text in result.stream(debounce_by=0.01): - result_text = text - return result_text - - -async def _run_prompt_completion(client: AsyncOpenAI, prompt: str): - model = get_pydantic_agents_client(MODEL, client=client) - agent = Agent(model=model) - result = await agent.run(prompt) - return result.output # Return the string output - - -@pytest.fixture -def memory_logger(): - init_test_logger(PROJECT_NAME) - with logger._internal_with_memory_background_logger() as bgl: - yield bgl - - -def _assert_metrics_are_valid(metrics: Dict[str, Any]): - assert metrics["tokens"] > 0 - assert metrics["prompt_tokens"] > 0 - assert metrics["completion_tokens"] > 0 - assert "time_to_first_token" in metrics - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_pydantic_wrapped_stream(memory_logger): - """Test that Pydantic AI streaming operations work with Braintrust wrapping.""" - assert not memory_logger.pop() - - # First, verify pure Pydantic AI client works as expected (without wrapping) - async_client = AsyncOpenAI() - pure_output = await _run_prompt_streaming(async_client, TEST_PROMPT) - assert "Rome" in pure_output - - # No spans should be created for unwrapped client - assert not memory_logger.pop(), "No spans created" - - # Now test the wrapped client - start = time.time() - wrapped_output = await _run_prompt_streaming(wrap_openai(async_client), TEST_PROMPT) - end = time.time() - - # Verify output is still correct with wrapping - assert "Rome" in wrapped_output - - spans = memory_logger.pop() - - assert len(spans) == 1 - - span = spans[0] - assert span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert "name" in span["span_attributes"] - assert MODEL in str(span["metadata"]) - assert TEST_PROMPT in str(span["input"]) - assert "Rome" in str(span["output"]) - - # Verify timing - metrics = span["metrics"] - _assert_metrics_are_valid(metrics) - assert start <= metrics["start"] <= metrics["end"] <= end - - # Verify span relationships - assert span["span_id"] - assert span["root_span_id"] - - -@pytest.mark.vcr -@pytest.mark.asyncio -async def test_pydantic_wrapped_completion(memory_logger): - """Test that Pydantic AI completion operations work with Braintrust wrapping.""" - # Clear any previous logs - assert not memory_logger.pop() - - # First, verify pure Pydantic AI client works as expected (without wrapping) - async_client = AsyncOpenAI() - pure_output = await _run_prompt_completion(async_client, TEST_PROMPT) - assert "Rome" in pure_output - - # No spans should be created for unwrapped client - assert not memory_logger.pop(), "No spans created" - - # Now test the wrapped client - start = time.time() - wrapped_output = await _run_prompt_completion(wrap_openai(async_client), TEST_PROMPT) - end = time.time() - - # Verify output is still correct with wrapping - assert "Rome" in wrapped_output - - # Check the spans were created with wrapped client - spans = memory_logger.pop() - - assert len(spans) == 1 - - span = spans[0] - assert span["span_attributes"]["type"] == SpanTypeAttribute.LLM - assert "name" in span["span_attributes"] - assert MODEL in str(span["metadata"]) - assert TEST_PROMPT in str(span["input"]) - assert "Rome" in str(span["output"]) - metrics = span["metrics"] - _assert_metrics_are_valid(metrics) - assert start <= metrics["start"] <= metrics["end"] <= end - - assert span["span_id"] - assert span["root_span_id"] diff --git a/py/src/braintrust/wrappers/test_utils.py b/py/src/braintrust/wrappers/test_utils.py deleted file mode 100644 index 09754e2fd..000000000 --- a/py/src/braintrust/wrappers/test_utils.py +++ /dev/null @@ -1,91 +0,0 @@ -import os -import subprocess -import sys -import textwrap -from contextlib import contextmanager -from pathlib import Path - -import vcr -from braintrust import logger -from braintrust.conftest import get_vcr_config -from braintrust.test_helpers import init_test_logger - -# Source directory paths (resolved to handle installed vs source locations) -_SOURCE_DIR = Path(__file__).resolve().parent -AUTO_TEST_SCRIPTS_DIR = _SOURCE_DIR / "auto_test_scripts" - -# Cassettes dir can be overridden via env var for subprocess tests -CASSETTES_DIR = Path(os.environ.get("BRAINTRUST_CASSETTES_DIR", _SOURCE_DIR / "cassettes")) - - -def run_in_subprocess( - code: str, timeout: int = 30, env: dict[str, str] | None = None -) -> subprocess.CompletedProcess: - """Run Python code in a fresh subprocess.""" - run_env = os.environ.copy() - if env: - run_env.update(env) - return subprocess.run( - [sys.executable, "-c", textwrap.dedent(code)], - capture_output=True, - text=True, - timeout=timeout, - env=run_env, - ) - - -def verify_autoinstrument_script(script_name: str, timeout: int = 30) -> subprocess.CompletedProcess: - """Run a test script from the auto_test_scripts directory. - - Raises AssertionError if the script exits with non-zero code. - """ - script_path = AUTO_TEST_SCRIPTS_DIR / script_name - # Pass cassettes dir to subprocess since it may use installed package - env = os.environ.copy() - env["BRAINTRUST_CASSETTES_DIR"] = str(_SOURCE_DIR / "cassettes") - result = subprocess.run( - [sys.executable, str(script_path)], - capture_output=True, - text=True, - timeout=timeout, - env=env, - ) - assert result.returncode == 0, f"Script {script_name} failed:\n{result.stderr}" - return result - - -def assert_metrics_are_valid(metrics, start=None, end=None): - assert metrics - # assert 0 < metrics["time_to_first_token"] - assert 0 < metrics["tokens"] - assert 0 < metrics["prompt_tokens"] - assert 0 < metrics["completion_tokens"] - # we use <= because windows timestamps are not very precise and - # we use VCR which skips HTTP requests. - if start and end: - assert start <= metrics["start"] <= metrics["end"] <= end - else: - assert metrics["start"] <= metrics["end"] - - -@contextmanager -def autoinstrument_test_context(cassette_name: str): - """Context manager for auto_instrument tests. - - Sets up VCR and memory_logger, yields memory_logger for direct use. - - Usage: - with autoinstrument_test_context("test_auto_openai") as memory_logger: - # make API call - spans = memory_logger.pop() - """ - cassette_path = CASSETTES_DIR / f"{cassette_name}.yaml" - - init_test_logger("test-auto-instrument") - - with logger._internal_with_memory_background_logger() as memory_logger: - memory_logger.pop() # Clear any prior spans - - my_vcr = vcr.VCR(**get_vcr_config()) - with my_vcr.use_cassette(str(cassette_path)): - yield memory_logger diff --git a/py/src/braintrust/wrappers/threads.py b/py/src/braintrust/wrappers/threads.py deleted file mode 100644 index 4572e6387..000000000 --- a/py/src/braintrust/wrappers/threads.py +++ /dev/null @@ -1,114 +0,0 @@ -import contextvars -import functools -import logging -import threading -from concurrent import futures -from typing import Any, TypeVar - -from wrapt import wrap_function_wrapper # pyright: ignore[reportUnknownVariableType, reportMissingTypeStubs] - -logger = logging.getLogger(__name__) - -__all__ = ["setup_threads", "patch_thread", "patch_thread_pool_executor"] - - -def setup_threads() -> bool: - """ - Setup automatic context propagation for threading. - - This patches stdlib threading primitives to automatically - propagate Braintrust context across thread boundaries. - - Enable via: - - BRAINTRUST_INSTRUMENT_THREADS=true env var (automatic) - - Call this function directly (manual) - - Returns: - bool: True if instrumentation was successful, False otherwise. - """ - try: - patch_thread(threading.Thread) - patch_thread_pool_executor(futures.ThreadPoolExecutor) - - logger.debug("Braintrust thread instrumentation enabled") - return True - - except Exception as e: - logger.warning(f"Failed to enable thread instrumentation: {e}") - return False - - -T = TypeVar("T", bound=type[threading.Thread]) - - -def patch_thread(thread_cls: T) -> T: - if __is_patched(thread_cls): - return thread_cls - - def _wrap_thread_start(wrapped: Any, instance: Any, args: Any, kwargs: Any) -> Any: - try: - instance._braintrust_context = contextvars.copy_context() - except Exception as e: - logger.debug(f"Failed to capture context in thread start: {e}") - return wrapped(*args, **kwargs) - - wrap_function_wrapper(thread_cls, "start", _wrap_thread_start) - - def _wrap_thread_run(wrapped: Any, instance: Any, args: Any, kwargs: Any) -> Any: - try: - if hasattr(instance, "_braintrust_context"): - return instance._braintrust_context.run(wrapped, *args, **kwargs) - except Exception as e: - logger.debug(f"Failed to restore context in thread run: {e}") - return wrapped(*args, **kwargs) - - wrap_function_wrapper(thread_cls, "run", _wrap_thread_run) - - __mark_patched(thread_cls) - return thread_cls - - -def __is_patched(obj: Any) -> bool: - """Check if an object has already been patched.""" - return getattr(obj, "_braintrust_patched", False) - - -def __mark_patched(obj: Any) -> None: - setattr(obj, "_braintrust_patched", True) - - -P = TypeVar("P", bound=type[futures.ThreadPoolExecutor]) - - -def patch_thread_pool_executor(executor_cls: P) -> P: - if __is_patched(executor_cls): - return executor_cls - - def _wrap_executor_submit(wrapped: Any, instance: Any, args: Any, kwargs: Any) -> Any: - try: - if not args: - return wrapped(*args, **kwargs) - - func = args[0] - ctx = contextvars.copy_context() - - @functools.wraps(func) - def context_wrapper(*func_args: Any, **func_kwargs: Any) -> Any: - try: - return ctx.run(func, *func_args, **func_kwargs) - except Exception as e: - # context.run() can fail if token is invalid - logger.debug(f"Failed to run in captured context: {e}") - return func(*func_args, **func_kwargs) - - new_args = (context_wrapper,) + args[1:] - return wrapped(*new_args, **kwargs) - except Exception as e: - # Wrapping can fail - fall back to original - logger.debug(f"Failed to wrap executor submit: {e}") - return wrapped(*args, **kwargs) - - wrap_function_wrapper(executor_cls, "submit", _wrap_executor_submit) - - __mark_patched(executor_cls) - return executor_cls diff --git a/py/src/braintrust/xact_ids.py b/py/src/braintrust/xact_ids.py deleted file mode 100644 index 0327066e1..000000000 --- a/py/src/braintrust/xact_ids.py +++ /dev/null @@ -1,26 +0,0 @@ -TOP_BITS = 0x0DE1 << 48 - -MOD = 2**64 -COPRIME = 205891132094649 -COPRIME_INVERSE = 1522336535492693385 - - -def modular_multiply(value: int, prime: int): - return (value * prime) % MOD - - -# value : int | str -# Cannot use a | because of python 3.8 -def prettify_xact(value) -> str: - encoded = modular_multiply(int(value), COPRIME) - return hex(encoded)[2:].rjust(16, "0") - - -def load_pretty_xact(encoded_hex: str) -> str: - if len(encoded_hex) != 16: - return encoded_hex - - value = int(encoded_hex, 16) - multiplied_inverse = modular_multiply(value, COPRIME_INVERSE) - with_top_bits = TOP_BITS | multiplied_inverse - return str(with_top_bits) diff --git a/pyproject.toml b/pyproject.toml deleted file mode 100644 index f0618c8f0..000000000 --- a/pyproject.toml +++ /dev/null @@ -1,18 +0,0 @@ -[tool.black] -line-length = 119 - -[tool.ruff] -line-length = 119 - -[tool.ruff.lint] -select = [ - "I", # isort - "F401", # unused imports -] -[tool.ruff.lint.isort] -known-third-party = ["braintrust", "braintrust_local", "autoevals"] - -[tool.pytest.ini_options] -asyncio_mode = "strict" -asyncio_default_fixture_loop_scope = "function" -addopts = "--durations=3 --durations-min=0.1" diff --git a/pyrightconfig.json b/pyrightconfig.json deleted file mode 100644 index 477855fe5..000000000 --- a/pyrightconfig.json +++ /dev/null @@ -1,11 +0,0 @@ -{ - "typeCheckingMode": "strict", - "reportMissingTypeStubs": false, - "extraPaths": ["./py/src"], - "reportPrivateUsage": "warning", - "reportUnknownArgumentType": "warning", - "reportUnknownLambdaType": "warning", - "reportUnknownMemberType": "warning", - "reportUnknownParameterType": "warning", - "reportUnknownVariableType": "warning" -} diff --git a/scripts/claude-docker.sh b/scripts/claude-docker.sh index fcffa31b7..f5d503939 100755 --- a/scripts/claude-docker.sh +++ b/scripts/claude-docker.sh @@ -124,33 +124,17 @@ EOFPROFILE echo "Tools installed" echo " node: $(node --version)" echo " pnpm: $(pnpm --version)" - echo " python: $(python --version)" - - # Python SDK setup - echo "" - echo "Setting up Python SDK..." - cd /workspace/repo/py - make install-dev # TypeScript SDK setup echo "" echo "Setting up TypeScript SDK..." - cd /workspace/repo/js pnpm install - # Return to repo root - cd /workspace/repo - echo "" echo "============================================" echo "Development environment ready!" echo "============================================" echo "" - echo "Python SDK: cd py" - echo " make test-core - Run core tests" - echo " make build - Build package" - echo " make install-optional - Install optional deps (anthropic, openai, etc.)" - echo "" echo "TypeScript SDK: cd js" echo " pnpm test - Run core tests" echo " pnpm build - Build package" diff --git a/turbo.json b/turbo.json index 9bec71c82..9a7cb3cb0 100644 --- a/turbo.json +++ b/turbo.json @@ -14,6 +14,9 @@ "lint": { "outputs": [] }, + "fix:eslint": { + "outputs": [] + }, "dev": { "cache": false },